qkL1JetTagModel_hls_config.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55179fac",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-02-20 19:06:54.793418: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "#import plotting\n",
    "import os\n",
    "import tensorflow as tf\n",
    " \n",
    "#  The path below is needed when running on Scully computer.\n",
    "os.environ['PATH'] = '/home/xilinx/Vivado/2019.1/bin:' + os.environ['PATH'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2321706b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#from tensorflow.keras.models import load_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2642e0b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "31624c79",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qkeras.utils import load_qmodel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "15d4d971",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-02-20 19:07:05.744045: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2023-02-20 19:07:05.747258: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1\n",
      "2023-02-20 19:07:05.778667: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
      "2023-02-20 19:07:05.778926: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:0a:00.0 name: NVIDIA GeForce GT 1030 computeCapability: 6.1\n",
      "coreClock: 1.5185GHz coreCount: 3 deviceMemorySize: 1.95GiB deviceMemoryBandwidth: 44.76GiB/s\n",
      "2023-02-20 19:07:05.778938: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
      "2023-02-20 19:07:05.782879: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11\n",
      "2023-02-20 19:07:05.782901: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11\n",
      "2023-02-20 19:07:05.798753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10\n",
      "2023-02-20 19:07:05.799812: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10\n",
      "2023-02-20 19:07:05.800789: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusolver.so.10'; dlerror: libcusolver.so.10: cannot open shared object file: No such file or directory\n",
      "2023-02-20 19:07:05.803404: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11\n",
      "2023-02-20 19:07:05.804420: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory\n",
      "2023-02-20 19:07:05.804426: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\n",
      "Skipping registering GPU devices...\n",
      "2023-02-20 19:07:05.805352: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2023-02-20 19:07:05.805367: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2023-02-20 19:07:05.805370: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      \n"
     ]
    }
   ],
   "source": [
    "model = load_qmodel('qkL1JetTagModel.h5')\n",
    "#qkL1JetTagModel.h5 has QActivation(\"sigmoid\")\n",
    "#qkL1JetTagModel.h5 has Activation(\"sigmoid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "599b708e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/users/russelld/L1JetTagDaniel\r\n"
     ]
    }
   ],
   "source": [
    "!pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d90e37b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tensorflow.keras.utils.plot_model(model, show_shapes=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a990d6e6",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Interpreting Model\n",
      "Topology:\n",
      "Layer name: input_1, layer type: InputLayer, input shapes: [[None, 10, 14]], output shape: [None, 10, 14]\n",
      "Layer name: q_conv1d, layer type: QConv1D, input shapes: [[None, 10, 14]], output shape: [None, 4, 50]\n",
      "Layer name: q_activation, layer type: Activation, input shapes: [[None, 4, 50]], output shape: [None, 4, 50]\n",
      "Layer name: q_conv1d_1, layer type: QConv1D, input shapes: [[None, 4, 50]], output shape: [None, 1, 50]\n",
      "Layer name: q_activation_1, layer type: Activation, input shapes: [[None, 1, 50]], output shape: [None, 1, 50]\n",
      "Layer name: flatten, layer type: Reshape, input shapes: [[None, 1, 50]], output shape: [None, 50]\n",
      "Layer name: q_dense, layer type: QDense, input shapes: [[None, 50]], output shape: [None, 50]\n",
      "Layer name: q_activation_2, layer type: Activation, input shapes: [[None, 50]], output shape: [None, 50]\n",
      "Layer name: q_dense_1, layer type: QDense, input shapes: [[None, 50]], output shape: [None, 10]\n",
      "Layer name: q_activation_3, layer type: Activation, input shapes: [[None, 10]], output shape: [None, 10]\n",
      "Layer name: q_dense_2, layer type: QDense, input shapes: [[None, 10]], output shape: [None, 1]\n",
      "Layer name: dense, layer type: Dense, input shapes: [[None, 1]], output shape: [None, 1]\n",
      "-----------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/russelld/miniconda3/envs/L1JetTag/lib/python3.8/site-packages/hls4ml/converters/__init__.py:24: UserWarning: WARNING: Pytorch converter is not enabled!\n",
      "  warnings.warn(\"WARNING: Pytorch converter is not enabled!\")\n"
     ]
    }
   ],
   "source": [
    "import hls4ml\n",
    "config = hls4ml.utils.config_from_keras_model(model, granularity='name')\n",
    "print(\"-----------------------------------\")\n",
    "#plotting.print_dict(config)\n",
    "#print(\"-----------------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ace8fe06",
   "metadata": {},
   "outputs": [],
   "source": [
    "config['LayerName']['q_conv1d']['ReuseFactor'] = 10\n",
    "#config['LayerName']['q_activation_quantized_relu']['ReuseFactor'] = 10\n",
    "config['LayerName']['q_conv1d_1']['ReuseFactor'] = 10\n",
    "config['LayerName']['q_activation_1']['ReuseFactor'] = 10\n",
    "config['LayerName']['q_dense_1']['ReuseFactor'] = 10\n",
    "config['LayerName']['q_dense_2']['ReuseFactor'] = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06257df8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ca8da4a8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Interpreting Model\n",
      "Topology:\n",
      "Layer name: input_1, layer type: InputLayer, input shapes: [[None, 10, 14]], output shape: [None, 10, 14]\n",
      "Layer name: q_conv1d, layer type: QConv1D, input shapes: [[None, 10, 14]], output shape: [None, 4, 50]\n",
      "Layer name: q_activation, layer type: Activation, input shapes: [[None, 4, 50]], output shape: [None, 4, 50]\n",
      "Layer name: q_conv1d_1, layer type: QConv1D, input shapes: [[None, 4, 50]], output shape: [None, 1, 50]\n",
      "Layer name: q_activation_1, layer type: Activation, input shapes: [[None, 1, 50]], output shape: [None, 1, 50]\n",
      "Layer name: flatten, layer type: Reshape, input shapes: [[None, 1, 50]], output shape: [None, 50]\n",
      "Layer name: q_dense, layer type: QDense, input shapes: [[None, 50]], output shape: [None, 50]\n",
      "Layer name: q_activation_2, layer type: Activation, input shapes: [[None, 50]], output shape: [None, 50]\n",
      "Layer name: q_dense_1, layer type: QDense, input shapes: [[None, 50]], output shape: [None, 10]\n",
      "Layer name: q_activation_3, layer type: Activation, input shapes: [[None, 10]], output shape: [None, 10]\n",
      "Layer name: q_dense_2, layer type: QDense, input shapes: [[None, 10]], output shape: [None, 1]\n",
      "Layer name: dense, layer type: Dense, input shapes: [[None, 1]], output shape: [None, 1]\n",
      "Creating HLS model\n",
      "WARNING: Cannot use \"Latency\" model strategy for q_conv1d layer. Switching to \"Resource\" strategy.\n"
     ]
    }
   ],
   "source": [
    "hls_model = hls4ml.converters.convert_from_keras_model(model,\n",
    "                                                       hls_config=config,\n",
    "                                                       output_dir='model_1/hls4ml_prj',\n",
    "                                                       part='xcu250-figd2104-2L-e')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56b9d0f5",
   "metadata": {},
   "source": [
    "$N_{multiplications}$ = $\\sum^N_{n=2}$ $L_{n-1} * L_{n}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a0dfb658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zjDdNTExsz549rq6uT58+DQgIIBAI4FuA2MrKSjU1NdrK0Feb8eMBAFBUVNy1a1dgYGB6enpsbGxgYODKlSt9fX0NDQ0HbBUM3CspKYmXODk5CQgIFBUVcVqTQqHcvXv37Nmz+fn5np6eT58+hZEQR5yRjM+DYRiBS667TImKilq9ejU7Cb6/fPly69at5ORkQ0PDqKgo9k+hrq7u6uo6hDYiuA+MSccmUJW8f/+etlBQUFBbW5vT82IMSQ5++OEHToXgwPT0HR0d7FSeMmWKlJRUcXExXgIjjdvY2Ay6AVFRUXfv3qX7iBoYGEyePBl68YNv0b+5mCyvsrIyMTGRRCKtW7fuyJEjsFMoLS0NAEhKSqLrY8HRzOfPn/uTRiAQbG1tbW1ta2trL1y4sHjxYhUVFV9fXxcXFxajLjU1NUFBQdo1Q0JCQtLS0owfURY1q6qqzp8/TyKRdHV1fX19ly1bBiMhjhJGzM4jJydXVVUVFBTEI/kdHR3s9/uCg4PPnj2bkZGBB6xH8AmmpqYaGhrXrl3D3WkqKytbW1vd3NwAh/kJuJvkQFVVVVhYmM1VSOPGjYPdSXwJ2MOHD0VFRYeS8BI3r0Nw+z6u9AEAcPZYT0+PTZm9vb09PT34Jl0OCejjFB0dvXbtWh8fn9DQUDhvYWJiIi0tHRwcfPTo0erq6paWlqysrJ07d5qbmxOJxCtXrtDF74L3lhYlJaWgoKDi4uK9e/empKQ8fPiQRSMlJSUdHBwyMzPxMV9NTU1jYyOjcYZFzYiIiI6OjkePHqWnp7u6uo4qpQ/A2PHn4RRO3atZ+y8zBc3rjk44fS7Xr18HACxevLiqqqq6utrR0RG6lGAYFhcXBwA4depUe3v7+fPn586dCwCQk5M7f/48zNmZmpoaFxdXWVnp6+tLIBA2bNjQ0NBQUlJiaWn5ww8/QLcN9oXQNWzhwoUTJkygK6RSqVVVVePGjXNycqL1Q//69auGhsaaNWtaW1tTU1OlpKSOHz8Odzk5OSkqKsIATUzpTyYtTOd1AwICiERiTU0NhmGvX7+WlZU9fPhwf2eprKyEy+ZhWggMw+7evQsAsLCw6OzsrKurmzdv3okTJ/DKgoKCsrKy6enpFAqFrg8nKCiYmZmJYRhcxuzu7v758+dPnz5BW7+MjAyba9b6u/CioiI5OTlra+vy8vKKioqFCxcuWLCA6c1kUZMr8EiXjoze7+zsvHTpko2NTVBQEIZhHz58CAgIUFRUrK6u3r17t7y8vIqKSlJSEoZhubm5W7Zs0dDQqKys/Omnn2Ac+cePH2MYhs+hQZmTJ0+Gm21tbXRhmaHvxIAw9WNjAdL7o5NBPJfk5GToG66pqRkSEoIvwOns7Fy+fLmIiMiUKVMyMjIOHTo0a9YsEonU3t7e0NBgYWGhoKBw5coVDMN8fX3FxcWjo6Pl5OSkpKQ8PDwaGho4FULH5cuXAcMqpB07dtC+269evcJ3lZSU2Nvbw0XpCQkJeLmVlZWmpiYLn04WMnGY6v3p06fjYvPz82VkZPrT+zClD46Ojs7t27fxTWNjY7w3Db8i8+fPx/dCz8jY2FgdHR1RUdGZM2empaVBsX19fSEhIQoKChISEh4eHuHh4SYmJtHR0dC1dEBYXHhhYeHChQslJCSUlJS2b9+Oe4Iy3sz+anKF70rv07nuWllZQSXu5+eXl5fX3NxsbW0tIyNDJpN55BnNFKT3vw9G5LlAvc9dmRQKxdDQMCAgYOii2tvbuX5P8vPziUTiixcvuCt29MOLm9kfPNL7I2Pf9/DwgCtNIE+ePIHJswICAkxNTaWlpZcuXdrc3FxbW1tdXe3g4EAkEvft26eurm5gYBAVFdXT0xMZGSkjI2Nra4sLkZOTo91EIIYTXiQ5IBKJiYmJ586dy8nJGaKo06dPw78Yt+jp6dmyZUtAQMDMmTO5KHZMwPWbOfyM2LwunfeVoqIioHFthp7IcNqH657RCNZ8T1F/hwfeJTkwNTVNTEx0cXH566+/Bi0kMjLSwsLC0tKSW62C4SgmTZp0+PBhbskcK3D9Zo4II6b36Vx3WWRN4bpn9FhheML80vE9Rf0dHnid5MDJyen+/fvQvD44/Pz8huLQyUh8fLyrq2tCQgIfJjvi+s0cEUZ1fl0cjKue0WMC6IcKUwsMm5CcnJz169c/ffoUX94SHBycm5v75s0bOl+9trY2KysrQ0PDsrKy4uJiBweH9vb2Xbt2sXOW/mTiNDU1eXp64s55mpqaaWlpZmZmhw8fDgkJYfNahg2Y5ICnpzAyMuJoUQKvCQ0NHekmIIbEiH2u6Vx34QIQ3EIK//O0e7noGT0m2Lx586CXvw9OSF9fn5eXl7+/P+2axgsXLrx69Ypx1eiBAwfKyspIJJKcnJy5ubm/v39oaCibeY76k4mzdetWOkOTpKRkQkJCaGgo7bQQAoEYHCOm92Hgquzs7K6urp6enqdPnwIAMjIyMAwjk8mPHz8G3/x8AQAYhm3fvr2xsbG0tHT9+vUzZ8708PAAAMBFzyQSqaOjg0QiQV+xGTNmkEgkWVlZAEBubu758+erqqpYNwbDsOrq6q6ururqavgF4i6jJMwv60i5YyvqLwKBGDxc9xDC2PA9onPdnT17Nr557Ngx6I4JOX36NC88o+lgx3+ZETb9BUdPmF/WkXLHVtRfFiD/WsR3w4C6dJBiuS4R43ZbeeEZzRXY0S+jNswvHd9T1F+k9xHfDTzS+2NgOp4XntHDxqgN80sHP0T9RSAQkNGu93nnGT08jNowv3TwQ9RfBAIBGdV6nyue0R8+fGCRo8PFxYXbrf4feBrmFyag4AqjIervyZMn8efi7e0NADAwMNDX18frcD3qLwLBn4xqvQ89o3F8fHwGIURfX5+FnYuj3EyDYNSG+aXju4z6i0AgmDKq9f53gLCw8O+//97c3Ozu7l5dXV1TU7Np0yY7Ozs4zuDIDxUbsjNrQUGBnJwcnOxlbOfs2bPpxiWgfw/XsLAwZWXlX375pa2tLS0t7dSpU4cOHYKDm8WLFyspKUHHXKb0J3NACgsLiUSilZUV+4cgEAhGkN7nOa6ursnJyeXl5dra2rNmzZo2bVpKSgrsibu7uy9fvjwoKMjc3FxHR2f+/PmzZs06duzYypUrXVxcLCwsVq1aJS4uDvUpjEGtq6trYmKira19//592NNnXwjsSvfXTg8Pj/Lycrq1VwEBAWpqar29vXfu3BEVFc3Pz4fl8vLymZmZX758UVZW3rZtW2Rk5K+//gp3NTU1iYiIMP26sJY5IOnp6fb29kOZRUAgEAB8v3lXhoHh9BccBmfW7ybqL/LjRHw38EiXov7+2GAYnFlR1F8Egk9Aen8MMGzOrCjqLwLBDyC9P9rhdZhfOlDUXwTiu2dsxGHmZ4YhzC8dKOovAvF9gzpQCAQCwV8gvY9AIBD8BdL7CAQCwV8gvY9AIBD8Ba/mdWG0gO+byspKAEBSUtJINwTxP6DngkAMANdXgg2z8wkCgUB8x/BivS4BqWkEf0IgEK5fv+7q6jrSDUEghhtk30cgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+QnCkG4BADBMnT56sra3FN0VERK5fv56Xl4eX/Prrr4qKiiPRNARiWCFgGDbSbUAghoPt27f/8ccfwsLCjLvIZLKiomJVVRWRiEbAiO8f9JYj+IWff/4ZANDDDEFBQQ8PD6T0EXwC6u8j+AgtLa3y8nKmu/Ly8kxNTYe5PQjEiIA6OAg+wsPDQ0hIiLFcW1sbKX0E/4D0PoKPcHd3J5PJdIXjxo3z8vIakfYgECMCsvMg+IspU6a8f/+e7rX/999/9fT0RqpJCMQwg/r7CP7C09NTQEAA3yQQCNOmTUNKH8FXIL2P4C9WrVpFoVDwTUFBQWTkQfAbyM6D4Dt+/PHHFy9eUKlUAACBQKioqFBTUxvpRiEQwwfq7yP4Dg8PDwKBAAAgEomWlpZI6SP4DaT3EXyHq6sr/EEgEDw9PUe2MQjE8IP0PoLvGD9+/Pz58wkEAoFAcHZ2HunmIBDDDdL7CH5k9erVGIbZ2dnJycmNdFsQiGEHYw8XF5eRbikCgUAgWMGmPucgDvOsWbN++eUX3rV4LJKdnX3q1Knr16+PdEP4kZMnTwIABv1OnjlzxtvbW0REhKuNQiBGBqiL2KzMgd5XV1fHJ8QQOKdOnUK3ZUS4ceMGoJmk5RRbW1tk5EF8T7Cv95F9H8GnIKWP4FuQ3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BAKB4C+Q3kcgEAj+Aul9BGJgGhsb1dXVw8PDWVcrKiratWuXkpLSly9fBn2uvLy8ZcuWDfrw0cPhw4cTExMHffjbt28XLVokKSmppKTk4+OjrKw84P1nk5KSkt27d6uqqpaVlXFF4JgD6X0Egi0wDINR+1ng6+t74sSJurq6/ipERUU1NzezkHDz5k1nZ+fNmzfTlWdmZgoICHz48IHN1n758iUmJmbevHlbt27trw6nMgEAe/fuJXxDSEgIv9K6ujo3NzcpKakJEyZER0fDwtWrV58+fXrLli3sy8epqqqytrb28/OrqKjw8vKKj4+vra0d8P6zybZt237//feamhr2D7ly5cr06dMlJCRUVFRWr15dUVHRX0127vzIw35cNhcXFzYr8w8wMs9It4JPGZ3v5M6dOwEANTU1jLva29u1tbWbmpr6OzY7O1tWVrawsJCuvLGxUVNTEwAAM8Kzw5o1a4yMjAAAvr6+TCsMQmZra6uMjAyuOhYtWoSX6+rqLlmypKGhIScnR1ZW9siRI7S7fvvtNzZPgRMeHi4pKcnpUeyzb98+AEBpaSnTvVQqNTU1dcWKFSkpKRiGXbt2TVZW9t69e52dnRUVFStWrJg8eTKVSmV6LNM77+fnFxgY+PHjRx5cyv8HR7oI9feHAzatBMPMaLMnDNEsMEpQUFDob9fmzZtLSkr629vX1+fl5eXv729oaEi3a+vWrZw+qQsXLrx69UpYWLi/CoOQGRMTc/78eVx33Lt3D5YfOHCgrKyMRCLJycmZm5v7+/uHhoZCE4qkpGRCQkJoaOjbt285OldZWdm4ceM4OoQjFBUVmZbX1dVFRETo6uru3bvX0dFx4cKFAICUlBRTU9NFixaJioqqq6v7+/sXFRW1trYylcD0zgcGBoqJic2bN8/W1vbGjRtkMpnrV8QRSO8PExgbVoKhMKABgQ46ewKLwSnTITw7cGpqGIpZgDVaWlrQNLF06dKPHz/ilgplZWUAAF4Cu+pJSUnGxsbCwsJ6eno3b94EAHR1dV2+fHn27NnBwcG4zNu3b5uZmUlKSs6cOfP58+d4OZFIBAD09fXt3r1bXl5eTU3t9u3bAIANGzZcunQJACArK0sgENrb2+kaeenSpaKiorVr19KVx8bGzpgxw8TEhNOrFhAQ6C/a6CBkdnV1nThxYseOHT4+Pq9evcLLqVTqpUuXzM3N5eXlYYm9vT2ZTIYXCwCwsLAwNjYOCwuDm4WFhePHj//tt9/6O1FaWhqBQDh37lxDQwN8LsXFxbT3f86cOfgTfPz4cVhYGPydkJAAJTA+QcizZ8+srKzExMRMTU3pPsAYhqWnp7u5uU2ZMqW8vPz27dvPnj3z9PSEN3D69OkZGRm//fYbhULBMOz8+fO7du2Slpbu7xIY7z9czikAACAASURBVLyamtq+fftKSkr8/f0vXryopaUVFBT06dOnge46z2BzXDA6x9Qjziix8wxoQKCD0Z7Qn1mAxRB+QAZhauDILMD+O/n161c7OztBQcG6ujoMw5qamqysrMaPH9/R0QErREZGHjlypLu7Oz4+3trauri4uL6+fsmSJUQiMTc399KlS9C+sWvXLlj/zp07BAKBRCK1t7fHxsbCvxKRSKysrDx27BgAwM/P79WrV/X19T/++OP48eOhTQAO+Pp7TDY2Nnp6enSF79+/X758OZVKvXDhAuDEJgORlpZmvPmDk/nHH3/gSoNAIISEhMBy2JH/+eef8Zpfv34FNFYgDMP8/f2FhISam5sxDHvz5o2srOzBgwdZn27dunXy8vLwN939b2hoCAwMBADY2dlRqdTW1lZFRcWkpKTe3l4Mw5g+QQzDcnJyREREjh492tTUlJSUJCoqCgAoLS2FHfxJkyaZmZnFxsa2t7czNqa3t9fNzQ0AMHXq1JUrVyYlJQ14u5jeeZzPnz/v3btXXV0ddv9hy4cIR7oI6f0hMUr0PkwSy6beJ5PJenp6YWFhdOV9fX3CwsJ0L+vOnTuFhIS+fv0KN8PCwoSEhPqzijLCVCbOqlWr/P396VTP33//TSQS37x5M6Bwjt7J7OxsAMDly5fhZkxMDADg5cuXcNPd3b27u5tMJisqKuKNKS8vBwCsXLkSw7DKykpave/i4qKkpIQLnzFjxk8//QR/Q71fUlICNyMiIgAAX758wVjq/e7ubiEhoWXLltEW9vT02NnZwWO5pfcHLbO3t7eqquqvv/7y8vISFBQEAERFRWEYlpaWBgDw9/fHa/b19QEAzMzM8JIzZ84AAG7dusV+y2n1PsZw/zEMc3d3JxAIGRkZO3bsuHPnDixk8QSNjY3t7e3xw319faHed3NzExYWJpFIrNtDpVKXLl1KJBLFxcVv3LgxYPtZ631IZ2fnqlWrAADsCBwQZN8fXdBZCf7999/AwEAlJaWampo9e/aMHz9eVVUVhpLPy8vbunWrpqZmVVWVo6OjuLi4iYlJZmYmAEBQUBAOZqFMfX19uNne3s5oQGA9lO7PnsA4OB1wCD8ggzA10JkFuMWsWbP09PRu3boFN3Nzc+Xk5JKSkgAAra2tCgoKwsLCBQUFdXV1BgYG8N5OmDABAFBYWAgYrPZiYmItLS29vb1wU1lZOTc3l7YC7E7CmgCA7u5u1s0rKysjk8njx4+nLQwODvb391dSUhrsRTNh0DKFhIRUVVUdHBwSEhIyMjKkpKSOHj0KAIA3AV4mhEKhAABorfOqqqoAABZzGwPCOGsSGxtrZGS0bNkyRUVFR0dHWNjfE3z9+vXr16+hsR6Cv3iRkZH79+8PDw+3tLS8ePFiV1cX0wYcOnRo1qxZmZmZ0tLSrq6uuE1pcJSWloaEhGhra9fW1iYlJS1ZsmQo0gYB0vs8Jzk52c/PLysrC8MwAICPjw909Tty5Iizs/OnT58mTZq0YcOGvr4+R0fH6Ojourq6c+fOnT179uXLl2Qy2c7O7sOHD1+/fjUwMMBlPnv2zNzcHP6OjY2l7UhKSEhgGAYNC0zbc/HiRT09PQ0NjQFb/v79+7q6OtqakyZNAgDQmrMHx4cPHx48eLB9+3ame21sbP7888+WlpYhnoUOT0/PBw8edHZ21tbWqqiorFq1Cn5u7969C7td9fX1AIDKykranlFBQQH4ZrXHCQ4OlpKS2rlzZ1tb24sXL7Kysuzt7Vmcur9ngQPN/bSTgQ8ePMAwzMHBYZBXywxuybSysgoLC/v8+TOZTIZzJA0NDfjepqYmAAAsh4iLi9PV4RS6+w8AEBMT27NnT3Nz89OnT/Hb298TfP/+Pehnyl1RUXHXrl1FRUX79++/d++elpaWv7//u3fvaOtcv3791q1bu3btsrKy+ueffwwMDLZu3VpbW8vpVVAolJSUFAcHBwsLCwqF8vTp07S0tBUrVggJCXEqaoggvc9zPDw8aJ0Znjx5AvVdQECAqamptLT00qVLm5uba2trq6urHRwciETivn371NXVDQwMoqKienp6IiMjZWRkbG1tcSFycnK0m3RMnTq1sbFxz549jLt6enqys7OnTJnCTsvh4iNazwdoZh3EG09Lb2/v9u3bY2Ji+pvo1tfXJ5PJjx49GspZGPHw8Ojq6nrw4EFiYqKvr6+3t3dpaek///zz77//zpw5EwAAZ+rgIIA1+vr6O3fuLCgoUFZWXrFihY+PD0cz3ozAJDAdHR14SVRU1MmTJ/EJTG9vbwCAgYGBvr7+oM/CRZlWVlaqqqpCQkJTpkyRkpIqLi7Gd338+BEAYGNjg5fA4Y6EhMSgW85IZWVlYmIiiUS6c+fOkSNHYGF/TxAOPj5//tyfNAKBYGtrm5SUVFBQoKKisnjxYmtr68TERNjy6OjoH374AdZUVVX9888/u7q6MjIy2G9tVVXV/v37J06cGBkZ6e3t/fnz54iICB0dHU6umJsgvT8c0HU0oCbFDSBwjAxdu9TV1YlEooCAANw1d+5cKSmply9fgv8dONMezhFM7Qn9wc4QfhAMaGoYulmAKZqamnPnzr1582Zra6u6uvr06dONjY0vXryI90xNTEykpaWDg4OPHj1aXV3d0tKSlZUFnXzg04GWawDA8+fP7927l56e3tHRUV5efvz4cfwuwZrwRgEAqFQqfiD8zjHt+6uqqgoLC9OuJMJt1hDcFs/RMis6uCgzOzv7119/BQCMGzfO09Pz6dOnuDvZw4cPRUVFV6xYgVeGM716enrsy+/t7e3p6cE36e4/NG9GR0evXbvWx8cnNDQUTjP09wTNzc2JROKVK1fg48CB4wNalJSUgoKCiouL9+7dm5KS8vDhQ3iNtB82LS0tYWFhOIhhk4iIiI6OjkePHqWnp7u6ug5/B58OpPeHA7pRKuOglcUudXV13I48dBjtCSxgZwjPKeyYGoZuFugPLy+va9euLV68GG56e3ufP38ed2MXEREJCwvr6enZtWuXmpqajIzM/PnzYWU4+MjOzob23ytXrmRmZuKTLtCUnJqa2tTU9OTJEwBARkYGlUolk8lZWVkAgMzMTAzDZGVlAQC5ubnnz5+vqqqibZiwsPDs2bOhOYIdFi9erKSk9PTp0/4qYBhWXV3d1dVVXV094OzCgDL7+vq2bt0aHx/f09PT1NQUFxeXn58P9T4AICwsTFlZ+Zdffmlra0tLSzt16tShQ4fU1NTwwwsLC4lEopWVFQCgoKBATk6O9VqWqqqqJ0+etLe3431q2vsPHXUWLFigrq4Oz04gEFxdXR89ejRu3DimT1BNTW3jxo2FhYWenp4VFRUlJSXQuXbhwoVw4p0OAoGwYMGCGzduwKe/fft26MfZ1NRUW1u7ZcsWbW1tOzs7pjeN6Z2PjIw8evQoNJOOCtic/0X+PExhcw4d9lZwbwTo8lFfXw83obcDdJLx9fUVExOjPVZZWXnx4sUYhu3YsYP2XAcPHgQAtLW1YQM5CNICO9He3t5M99I5IfT09EhJSc2dOxcvge/3yZMnBzxRfzLxKTg6Jk+ejNe5e/cuAGBAb85BvJPt7e244w2GYV+/fl2+fDldndjYWB0dHVFR0ZkzZ6alpWEYBnUExNjYGMOwnJwcRquFiorK7Nmz8c3w8HAzMzN888KFCw0NDRYWFgoKCleuXGFs2+XLl0H/K0jpfG+srKw0NTVpfSXpgG8LzqtXr4Yik0qlrl69WkJCQlJS0tLSkrH9JSUl9vb2YmJi+vr6CQkJdHunT5+Oi83Pz5eRkTl8+HB/LYeeVzg6Ojp09x+fBYWLoufPn4/vTU1NxZg9QQzD+vr6QkJCFBQUJCQkPDw8wsPDTUxMoqOjoXfpgFy/fn3atGnjxo1TV1ffsGED/udlvGns3HlegPw4hw8273VnZycAYMeOHXATqmzoS4dhGDQNFxcXYxjm6+tLJBI7Ozvhrnfv3kE/cQzDgoKCcEWPYVhISAj45i8I7ZuNjY0DtqS7u1tYWJjWoY0WRuezrVu3CgkJ4V+UvXv3ioqK0s2bsYa1QxtTV0LoLDGgc9sIvpPXr1+Pi4vDNzs6Ot68eWNmZgbX9QwOCoViaGgYEBDAZv329nauXz4vZObn5xOJxBcvXnBX7OiBFzdtECA/zlEH7Si1p6cH9pozMjIwDCOTyY8fP4Z1MAwDAGAYtn379sbGxtLS0vXr18+cOdPDwwMAAGeBSCRSR0cHiUSC3aIZM2aQSCQ6AwKLoXR/9gSsH7MAiyE8L0wNEFqzwCjk33//3bRpE60jrJiY2JQpU1asWMHCgjcgRCIxMTHx3LlzOTk57NQ/ffp0fw5Rg4brMnt6erZs2RIQEABnzr9LePEgeA6b3wfU32cKO99YulEqrSng2LFjuDsmAOD06dO+vr7i4uLR0dFycnJSUlIeHh4NDQ1QTmdn5/Lly0VERKZMmZKRkQEdiuGSUToDAuuhNFN7AovBaX9DeF6YGiC0ZgEWjNQ7+eeffwIAfH198/LyWlpa2tvb8/Pz9+zZU11dzRXhampq9+7dY13tjz/+gHMGXITrMisrK21tbb28vIYyDBrl8OJBDI5RYed58ODBzz//rK2tLSIioqKismzZsmvXrtXV1eHLu3lER0fH2bNnDQ0NcS1Dq2ch4uLiGhoaTk5OJBKpr69vKKfj+npdqPe5KJARTu0JLBhZs8AI9kXu3btnZ2enpKQ0btw4HR2dwMBAdoxsbFJQUPB99LEOHDgQGxs70q3gF0ZY73/9+nXp0qUAAGlp6cjIyMrKyvb29n/++QcujVmyZAmbZ+SUsrKygIAAaPGg7V1SqVS49AbS2NhYU1Nz5swZSUlJAMD06dOrqqoGfVKu630fHx8REREuCmRKXl6elJRUdnb2EOWEh4fDVTPcoru729LSknY5PgvQGBSBwBlJ+353d7eTk9N///tfMTGxp0+fbtu2TU1NTVxcfMaMGf/5z39gzGsecejQoefPnzOGOSQQCEZGRrhHvJCQkLKy8saNGy9evAgAyMvLW7x4MRcdJYdCS0tLbm5ud3f3kydPsIFWeA4FU1PTxMREFxeXv/76a9BCIiMjLSwsLC0tudUqGJ1i0qRJhw8f5pZMBALBCJf1/pEjR+B848aNG6dOnUq3d8+ePTBiBgDgzz//NDMzg/Gsf/31V6ivr127hjtEx8TE2NraSktLT548GU4eTp06Fd87a9Ys8M11l0AgJCcnx8XFZWZmbtq0ic2mLlu2TFdXFwCQm5sLP5UjS3Nzs4yMDIxwa2NjQyKReHo6Jyen+/fvQ/P64PDz86Ndkzl04uPjYeSTocyOIhCIgWFzXMDOmJpMJuMBvKCzSn/cvn2bQCBMnjy5trYWKrjp06f39vZSKBQYYRUA4ObmVlNTA51zYXzakpISqKnBtxAcfX19S5YsOXfuHG6m3717N6xAN4uI9/dxP0gMw/BQ7w4ODmzeBzpGSTxO/gTZeRAInBGz85SWluJrLPF+PSMUCgVGbXVyclJUVPT09BQSEsrLyyORSEQiceLEibBaUFCQsrKyqakpAKCoqKi7u3vixIlnz56Fe2EIDgqFIisru2HDBlytc4SKigr8ASOKIBAIBD/ATb1PG0CRLg4GLa9fv4YBkqDaFRQUhNGU7ty5w1gZV+hw6dO8efOmTZsGAIiPjwcA/N///Z+zs/OgG4wHyx0l9n0EAoEYBrip93V0dPAIizDjAVPw4FN4ZDF4VF1dHQvh+IfEz88PAPD27duXL1/+888/ixYtGnSD8ahMuPkIgUAgvnu4qfdlZWV/+ukn+BuGx2OESqXiwSnx6Hqwuw2jLA2Iu7s7DCd55swZGL1y0A3G48gPZdCAQCAQYwsuO05ERERISUkBAM6cOVNdXU23Ny0t7cyZM9OnT4cBHWF01t7eXpiZfsGCBeycQkREZMOGDQCAa9eu0cZ6heCJ6vFAuP3x+vVrmMrKwMAABiJHIBAIfoDLet/Q0PDu3bsaGhrNzc02NjbJycn19fXd3d2vX7/etm1beHj4qlWrBAUFjx8/DgBISUmpr6+PiYnBMGzKlCk+Pj5UKhU3EJWVlVEoFHyztLQUP8vmzZsFBQVXrlwJs1XgfP36Fca6AQDcvXsXt9oXFRXhn4GioqLGxsZbt245ODhQqVQjI6O//vqLzbjEiDHKixcv1q9fj7sM0NHY2Kiurs46MjCn5OXl4eGdh8jhw4cTExO5Imps8fbt20WLFklKSiopKfn4+CgrK3PrGZWUlOzevVtVVbWsrIwrAscebPr9cOQz19raevr06blz58KMPHJycvPmzUtISKAN05GUlGRiYiIsLDx+/Hhvb+/a2loMw65evUrbNhigGIdMJuOHr1y5Mi8vj/akuFMmLW1tbYxxGgQEBGBKnYsXL9LKHATIj3MEYfOdpFAoqqqqBAKBNk83LQ0NDaqqquHh4dxqWHJyspaW1sOHD/GS0NBQ/PUTFBSEbzuGYbW1ta6urpKSkpqamjBNOSPl5eU//PDD5s2budW8MUFlZaWMjMz9+/ebmpoCAgLgFCC3ntGiRYtg7qD+ol4zUlNTEx0dPXfu3C1btjCt0NLScuTIkRkzZoiLi+/evZuFKPZrcsSoiM/DJyC9P4Jw9E7+9NNP/el97pKdnS0rK1tYWIiXtLa2wvyUEDzkXGtrq66u7pIlSxoaGnJycmRlZY8cOcJUJqw5YEKC74nw8HBJSUneyYexA/rT+1QqNTU1dcWKFSkpKbBkzZo1RkZGAACmQcWfPXumoaGhp6d39uzZ4uJiFr1Jxpp+fn6BgYEfP34c4hWhOMwIBD20WYJ5R19fn5eXl7+/v6GhIV4YExNz/vx5/C937949WH7gwIGysjISiSQnJ2dubu7v7x8aGsrU8iApKZmQkBAaGkqbqPn7pqysbIjpPFnT3/tQV1cXERGhq6u7d+9eR0fHhQsXwvILFy68evWKqUE4Kytr/vz55ubmBQUFvr6+kyZNEhQUZCqcac3AwEAxMbF58+bZ2treuHEDn6HkLWx+H1B/nymovz+CcPROrlu3Tl5e/tWrVzY2NiIiIsbGxjAIUmdn56VLl2xsbIKCgmDN8vJyFxeX8ePHi4mJWVhY4ObEoqIia2traWnpwMDA+Ph4mOyJDrj4/PPnz3hJZ2enoqLihAkT1q1bR2uZpFAoioqKVlZWeAkMu79///7+LsHU1NTZ2Rn+fvv2rby8/KFDh9i8/DFEamoqnY4qKiqifUa0ltuMjAw86teFCxegBDw3lq6ubnJyMi7577//trS0FBUVNTExgUHC8f4+lUpNS0tzdXUdP378pk2bCgoKmLaNMYlQfX29vLz8ggULBrQYs67Z19f3559//vTTT6qqqrt27RpE958jXcT8u4TgCLh4GDHMVFZWsun7C+no6Hjw4MH169dra2vd3d3t7e3//fffR48e+fn5NTc3//jjj7Cas7OzjIzMmzdv2tra5s2bt3nzZhhyatWqVbt27XJ0dHz+/LmzszPTFMEXL17U09PT0NDAS+Li4uDCFBKJFB8fHxwc/NtvvwEA3r9/X1dXR5sjECZfxX2LGbGxsYmJiWlpaZGWlsYwjEqlYrwM3jdS2NraYhjm4+Pz3//+F7r8Xb58mfYZ3bp1KyIi4ujRo3Z2drNnzzYzMztz5kxUVBQMA3zhwoULFy7cvHlTRkbGx8fH1dX1n3/+mT59+vPnz+fPn3/gwIG7d++mpqZ6eXnB09XX11+4cCEuLg7q9Pj4eI4Sph88eLChoWHu3LmzZs16+/atrq7uyZMnbW1tOa0pICDg5OTk5ORUUVFx/vz5OXPm6Ovr+/r6LlmyhCdJ2Nn8PqD+PlNGQ0A3fobT/j6+mZ+fTyAQYLyQyspKQJP9ePr06dHR0fC3l5eXgoIC9i1T5j///APLIyMjGfv73d3dQkJCy5Ytoy3s7e2tqqr666+/vLy84PAfzt/CBS6wARC4nMXMzKy/S4BuDrdu3WLzksc0dM+L7hlhGObu7k4gEDIyMnbs2HHnzh1YSCaTFRUV8TQ+0Btw5cqVGIYZGxvTphf19fUFAJSWlrq5uQkLC8NUpgNC19+nUCgKCgqqqqrJycmtra15eXlaWloiIiKMvXX2a0I6Ozth4PoBs43iIPv+cMPmvUZwFxcXl0E/MmNjYw0NjdevXwMA8IWEkNzc3M2bNz9//nz16tXXr1+H9lZRUVEVFZW5c+cGBwdXVVVt27YNrkGhpaysjEwmw0WFOEJCQqqqqg4ODgkJCRkZGVJSUkePHgXf1iqKiYnhNaGrMQujtqqqKgCgpKRk0Fc9dqF7RgCA2NhYIyOjZcuWKSoqOjo6wsKCgoK6ujoDAwMYphdGCSssLHz9+vXr169xYz0AwMTEBP6IjIzcv39/eHi4paXlxYsXu7q62G9VTU1NfX39nDlznJ2dJSUlTU1Njx8/3t3d/ccffwy6ZmlpaUhIiLa2dm1tbVJSEp5Enrsgvc8E5N7LDygoKDQ3NwMA6JZ8V1VVOTg4+Pr6Ojg4uLm5Yd9sKUlJSTIyMkeOHJk4ceLu3bsZI1DBWOIs1oJYWVmFhYV9/vyZTCbDzwYexxAA0NTUBABg/JzgQPsD7SH8A+OyfDExsT179jQ3N8PMP7AQRl6BwXpxCgoKYEJpxo8HAEBRUXHXrl1FRUX79++/d++elpaWv7//u3fv2GlVW1sbAABmcII4OTkJCAgUFRVxWpNCoaSkpDg4OFhYWFAolKdPn6alpa1YsYInRh4+1PtfvnyJiYmZN2/e1q1b+6uzbdu233//HY8jhPguqa6uhiZ1Wtrb2+HkbW5urru7Ox5CCgBgZWVVXFx88uRJeXn5w4cPnzp1iu5YuIqwo6ODxUmtrKzgopYpU6ZISUkVFxfju2BQWBYpDWBuegkJCXav8LumsrIyMTGRRCLduXPnyJEjsBBGeGScb4OjKBgOkikEAsHW1jYpKamgoAAu7rG2tk5MTIT3vD/U1NQEBQVpl5QKCQlJS0szfrxZ1Kyqqtq/f//EiRMjIyO9vb0/f/4cERGho6PD1l0YLHyn94ODg8+ePZuRkYFHB2Lk3r17wcHBw9kqxDCTk5NTU1Pj4eEBvsX2gO/DkydPSktL165diweChX3J7u7uQ4cOiYiIbN++/d9//zUwMICTvbSoqqoKCwuz7i5kZ2f/+uuvAIBx48Z5eno+ffoUjjkAAA8fPhQVFWUMPYIDJzn19PQGe9Fjid7e3p6eHnyT9hkBANrb2zds2BAdHb127VofH5/Q0FA4X2JiYiItLR0cHHz06NHq6uqWlpasrKydO3eam5sTicQrV67QjdLwyIw4SkpKQUFBxcXFe/fuTUlJefjwIYtGSkpKOjg4ZGZm4jFpampqGhsbGY0zLGpGRER0dHQ8evQoPT3d1dWVRx18eti3pX4387p9fX3CwsJM11/gREdHAzaW8yE/zhGEo3cyNDSUQCCEhITU1NQUFBTo6+uvW7cO7rp79y4AwMLCorOzMz8/HwDg6enZ3NyclJQ0depUQUHBwsLC+/fvjxs37uzZs83NzZ8/f9bX18fnfmlZuHDhhAkT8E0ymbxlyxYSidTd3d3Y2BgbG+vt7Q39cDAM+/r1q4aGxpo1a1pbW1NTU6WkpI4fPw53wdQU0NMUJyAggEgkwvnk169fy8rKHj58mLNbNkaorKzU0tICADx69AiW0D6jurq6efPmnThxAq8sKCgoKyubnp5OoVBOnjxJq98EBQUzMzMxDNu8eTMAwN3d/fPnz58+fYK2fmi4Y6dJVCq1qqpq3LhxTk5OXV1deHlRUZGcnJy1tXV5eXlFRcXChQsXLFgAd9E9RBY1ucIIr9d9/fq1o6OjpKTkhAkTrly5smjRInYWQ//1118//PCDiIiIlpbWH3/8gZc/fvzYxsZGTExMSUlp48aNTU1NGIZ9+PAhICBAUVGxurp69+7d8vLyKioqSUlJGIZNnjwZf+RwWv/YsWNwk3ZmnNEPF2Pp3tsfSO+PIBzpfSqVGhcXZ2hoOG7cOH19/ZiYGKh/b9++jb8wxsbGGIYFBgZKSUlNnTr11q1bly9fFhcX/+WXXzo6OqKiog4cOKCoqKimpnbw4EFcfdNy+fJl8L9e4atXr5aQkJCUlLS0tLxy5Qpd/ZKSEnt7ezExMX19/YSEBLzcyspKU1MTX9kLmT59Ol6Sn58vIyPzXep9uoGUjo4O3TPCe9PwE0jrC5uamophWGxsrI6Ojqio6MyZM9PS0qDYvr6+kJAQBQUFCQkJDw+P8PBwExOT6Ojo5uZmdloFFQIObTq/wsLChQsXSkhIKCkpbd++vb29HZYzPsT+anKFkdT7z549k5aWPnXqVFNT06tXr7S1tdnRnlevXlVRUcnKyurs7IRhdq5evYph2MOHDyUlJe/cudPW1nb9+nWYn51MJltZWcFhuJ+fX15eXnNzs7W1tYyMDJlMrqurmzNnDgAAd+2iUqlbt26Ni4uj/aMy6v2cnBwREZGjR482NTUlJSXBlCxI749mRuEYlEKhGBoaBgQEDF1Ue3s77dXl5+cTicQXL14MXTJi2KB7iDxlxPQ+hULR19f38fHBS+B8C2vt2d3draCgcO7cObj55s0bOTm58+fPU6lUXV3drVu34jXhwjwYvxN+fisqKuAuGOATzuO/efMGABAXF4cfuGbNGrqTMur9/tx7WV8y0vsjyCjU+xiG5eXlSUlJZWdnD1FOeHg49FTBMKy7u9vS0pLWex0xJqB9iLxmxPz38/LyPnz4gPvSgm/T66x58eJFfX29mZkZ3Jw6dWpDQ8O6detyc3OLi4uNjY3xmjDsPgxvAsNr4O4W0A8aTv5MnTp1/vz5eCbevLy8WbNmsW4DC/deBIIjTE1NExMTXVxc/vrrr0ELiYyMtLCwsLS0BABU6mY1DAAAIABJREFUVVU5OjpOmjTp8OHD3GsmgufQPsTRBjf1PnREY+GAzBS4ip1xYh2utYPrJCGqqqpiYmJwQpx1mq3t27fn5uZCQ+HVq1dXr17Nug0s3HsRCE5xcnK6f//+hQsXBi3Bz88Pd+iMj493dXVNSEgYSmo5xPBD+xBHG9yMzwN797W1tRwdBb2eL1++bG9vT1uupqYGvmlkHEFBQThnwJqffvpJV1c3KirK0NBQVFR0wIAbA7r3IhAcYWRkdOPGDa6Ioo3dj0BwBW72IKZOnUokElNSUjg6aubMmeLi4levXt23b19tbW1bW9u9e/cOHDhgamqqoaFx7do1uAwSAFBZWdna2urm5ga+rWHBs2hBt1zcvZdAIPj5+SUnJx8/fnzNmjUDtoF9914EAoEY63BT72toaHh7e1+8ePHEiRONjY2vXr36888/BzxKQkIiNDQUw7ADBw4oKytLSUmtWrXKxcVFWFj4999/b25udnd3r66urqmp2bRpk52dnYuLS09Pz9OnTwEAGRkZGIaRyWSYXhF6+0Kxa9asERMTy8/PpxsfYBhWXV3d1dVVXV2NL8ZTU1PbuHFjYWGhp6dnRUVFSUkJdB1buHBhREQEF28RAoFAjDxszv+y6TvR2dm5du1acXFxdXX1Y8eOxcTEAPaSmZ06dUpDQ0NCQmLBggW0YcqTk5ONjY2FhYU1NTVDQkK6u7ux/w3AfezYMXNzc3zz9OnT+LE7dux48OAB3Yn688MdnHvv9+rPk5ubu3Tp0mE+6W+//Xb58mX2649Ofx4EYkQYRXkWYeRY9pNYjjl4rfdPnz4Nl6oNpxDG9LCQx48fE4lEPMgtO3CUV5bTRLJI7yMQOKMoDjN0rMSt8AiO6OjooFt0PgxCcnJy1q9ff+/evQULFtCWNzU1eXp6MgahZEFbW9vp06fxzYULF0Lv27a2Nisrq56enrKysqSkpNDQUGhM09TUTEtLS01NRQ6LCARP4aHeJ5PJ0AqflpbGkb5AQDZv3jz0YOscCWGaHhaydevWZcuWcXTqQeSV5cNEsgjE8MNDvW9tbQ0Dom7cuFFAQIDQD0PJnjGGyMzMnD17tri4uLKy8qZNm2AURkFBQXgTYB19fX24CcMNXrp0CQAgKytLIBCysrK2bt2qqakJV/GIi4ubmJhkZmZyJKS9vb2wsHD8+PEw1R8jly5dKioqWrt2LV15bGzsjBkzOFrL1tXVdeLEiR07dvj4+Lx69Qovp1Kply5dMjc3l5eXhyX29vZkMhm2EwBgYWFhbGwcFhbG/rkQCARnsGkPQrZUprBpU+sv0FBTU5OBgQEuoaGhAc5Rt7W1YRgWHh4OAICmeRUVFQCAsLBwaGhoRUXFu3fvDA0NhYWF379/z74QDMPevHkjKyt78OBBpu20sbHR09OjK3z//v3y5cupVCpciMSmfZ82kRAMhAnLYUf+559/xmvC8MK04av8/f2FhIQGDJj1nb2TY2IufTh58+aNg4ODhISEoqLiunXrlJSUuBWH7tOnTyEhISoqKt/T1OMosu8jAAAYhm3ZssXLy8vR0VFCQsLV1XXnzp0vX76Mi4uTkZGhTcEsJyfHNCMzAKC6utrBwYFIJO7bt09dXd3AwCAqKqqnpycyMpJ9IQCAqVOnNjY27tmzh3FXT09Pdnb2lClTaAt7e3u3b98eExODjyfYZNOmTXheWQEBgcOHD8PQ1l++fAHfwmxAZGRkwP8u99PX1yeTyY8ePeLojDwiKioKD5HPOyE3b950dnaGsYJpyczMFBAQ+PDhA/vn2rt3Lz6YFhISguvhAQB1dXVubm5SUlITJkyAzwIAsHr16tOnT8NgiKOKqqoqa2trPz+/iooKLy+v+Pj42tpaTl/C/hhEYqUB8zW1trZGRETMnDlTQkKC6f9rEDV5B9L7PId1oCG6fKq0CZ7oUFdXJxKJeD6QuXPnSklJvXz5kiMhLGCaHjY4ONjf319JSYlTaUPJKzt6EskOz9Q6mktn5PLlyxQKxd7eXkZG5ujRozCYblBQEFeED5hYCcOwtLQ0V1dXfAUS63xN2dnZU6dOjY+P9/Hxyc/PZ2GlZKzp7++/a9euT58+De2aOAPpfZ7DOtAQ+zCGZ1FXV4dqlCswpoeFqx8cHByGKJnTvLKjJ5HsMEyto7l0ppSVlbFIMT90aEectNTV1UVEROjq6u7du9fR0RGP1XjhwoVXr14xTZ6clZU1f/58c3PzgoICX1/fSZMmCQoyj3/DtGZgYKCYmNi8efNsbW1v3LgBfSB5DdL7PGcogYbowL6tRoY0NjZOmDBhiM3DYUwPGxUVdfLkSdxo4O3tDQAwMDDQ19fnVDhHeWV5lEh2lEyt07VqFM6ls5785zVpaWkEAuHcuXMNDQ3wNhYXF1++fHn27Nmwkz5nzhz8nXz8+HFYWBj8nZCQACUkJSXBxZ56eno3b97EJT979szKykpMTMzU1JTuS4xhWHp6upub25QpU8rLy2/fvv3s2TNPT0/aobOAgADjSPrr16/Lly+3srK6evUq06/CgDXV1NT27dtXUlLi7+9/8eJFLS2toKAgXnf/kd7nOawDDcF0mviurq4u8C0uENQjtLq+u7sbVgAAvH//vra2FuYe4khIfzCmh8Vz10DweV2OzM0QjvLK8iKRbGpqqpOTU0BAQG1tbWRk5OXLlxcsWNDX1/f161c4Kw559uwZvvw7NjaWdlZ85cqV0dHRdXV1586dO3v27MuXL8lksp2d3YcPH9gXwvgxu3jxop6enoaGBm3hhw8fHjx4sH37do6uMS4urq6urry8nEQimZmZ7d69G5a/f/++rq6O9hQwofzz58/xEhsbmz///LOlpQUAgGEYtKtwdHZuYWtri2HYunXr5OXl4YuXk5Pj5+eXlZUFm3Tr1q3AwEAAgJ2d3ezZs3fs2KGoqJiUlOTu7g4AuHDhQlRU1M2bN6uqqgwNDV1dXfPy8uDFzp8/f8mSJdXV1SEhITCUAACgvr7+6NGjenp6u3btsrW1LSsri4mJMTIyYrO1Bw8ebGhomDt37qxZs0RERIyMjGCmX05rCggIODk53b17NycnR1hYeM6cOQsWLEhOTuZV95/N+d/vzHeCW7A5hw6rLV68uKqqqrq62tHR0c7ODv614uLiAACnTp1qb28/f/783LlzAQAw88y5c+cAAKmpqXFxcZWVlb6+vgQCYcOGDQ0NDSUlJZaWlj/88ENvby9HQljnZaVLD0sHnT8P0xywkEHnlYXQJpJlAfvvJOscPtu2baN9iFBdMvWGcnBwEBUV7evrg5tw5nnTpk0cCaGlu7tbSEho2bJltIU9PT12dnZfvnzBGO45a3p7e/G5dGhqgGuhoX7x9/fHa0IjtZmZGV4Cl9bfunWLnRMNA7R6H8OwyspKAABt5hl3d3cCgZCRkbFjxw68g0ImkxUVFfHbBU2sK1euxPpPrOTm5iYsLEwikdhpFV2+JgqFoqCgoKqqmpyc3NrampeXp6WlJSIi8vHjR7oD2a8J6ezsXLVqFfjf7LCsQf48ow5XV9fk5OTy8nJtbe1Zs2ZNmzYtJSUF9sTd3d2XL18eFBRkbm6uo6Mzf/78WbNmHTt2bOXKlS4uLhYWFqtWrRIXF4fGIjExMWNjY11dXRMTE21t7fv378OePvtC4FPvr50eHh7l5eXQ7DsgTU1NIiIiUKnRISAg0NLS4u/vr6Cg4OTkJCEhER8fj5tB5OXlMzMzv3z5oqysvG3btsjISDgUwElPT7e3t+c0kQMLRu3UOppLZxPG3BixsbFGRkbLli1TVFTEcz0VFBTU1dUZGBhAyw+0ghYWFrJIrBQZGbl///7w8HBLS8uLFy/i42l2qKmpqa+vnzNnjrOzs6SkpKmp6fHjx7u7u2mdmDmtWVpaGhISoq2tXVtbm5SUhCcT5i7cjL+PYIGzs7OzszNjuaioKK0Jcs6cOfjwXFxc/O+//6arv3nzZkZvP/aFGBsbw3lUpqxatSo8PDwmJgbqCzrWrFlDG9T6yZMnHR0dTMNcEwgEmGG8PyZOnHj//n2mu16/fp2fn5+Tk8PicE4ZtVPrvJ5L//XXX8fcXDpTGO+8mJjYnj17XF1dnz59GhAQAHsV0LZZWVkJ+0k4165dA/0kVlJUVNy1a1dgYGB6enpsbGxgYODKlSt9fX0Zp9kZaWtrAwBISkriJU5OTgICAkVFRZzWpFAod+/ePXv2bH5+PjSE6ujoDNiAQYP6+2MGCoXC60hHRCIxMTHx3LlzbKrd06dPc2qDZk1PT8+WLVsCAgJmzpzJRbGjdmr9u59L5x2VlZWJiYkkEunOnTswjzf4lvoJhgmgZcDESgQCwdbWNikpqaCgQEVFZfHixdbW1omJiXiodqaoqakJCgqWlpbiJUJCQtLS0oxDVRY1q6qq9u/fP3HixMjISG9v78+fP0dERPBU6QOk98cKLS0tubm53d3d0J7OuxOxnx6W6+lDeZdIdtROrX/fc+lDobe3t6enB9+E05u47zx0lIqOjl67dq2Pj09oaCicwzAxMZGWlg4ODj569Gh1dXVLS0tWVtbOnTvZT6ykpKQUFBRUXFy8d+/elJSUhw8fsmikpKSkg4NDZmYmPnCsqalpbGxkNM6wqBkREdHR0fHo0aP09HRXV1f4IvEcNucB0LwuU4Yn/j6dZSYuLo7XZywoKBj+x33gwIHY2Fj263P0To6eqXW6ho3CuXTWk//DQGVlpZaWFviWSQnDsLt37wIALCwsOjs76+rq5s2bd+LECbyyoKCgrKxseno6hUKhWyInKCiYmZmJYRi0jrq7u3/+/PnTp0/Q1i8jI3PkyBF2mkSlUquqqsaNG+fk5NTV1YWXFxUVycnJWVtbl5eXV1RULFy4cMGCBXAX3cNiUZMrjKL4+98932velTEBp+8k0xw+GIZ1dnYuX75cRERkypQpGRkZhw4dmjVrFolEam9vb2hosLCwUFBQuHLlCoZhvr6+4uLi0dHRcnJyUlJSHh4eDQ0NnAqhA06E9Bcohk7vW1lZaWpq0sYywqFSqatXr5aQkJCUlLS0tGQ8V0lJib29vZiYmL6+fkJCAt3e6dOn42Lz8/NlZGRGSu9nZ2fTKm4dHR2Y/A5ibGyM96bhV2r+/Pn43tTUVAzDYmNjdXR0REVFZ86cmZaWBsUOLrESTn/5mjAMKywsXLhwoYSEhJKS0vbt29vb22E548PqryZXQHp/+EB6fwQZ/ncS6n3uyqRQKIaGhgEBAWzWb29v5/pV5+fnE4nEFy9ecFcsghcPqz+QHycCwRN4MbX+vc6lIwAPHha3QHofgWAL3k2tf5dz6QiuPywugvz3EYiBaW5ulpWVhb9tbGzi4uJ8fHy4KN/JyUlLS+vAgQOLFi1iUc3Pz4+LJwUAxMfHu7q6rl+/nrtiEYAHD4uLIL2PQAyMjIwMd/v4jBgZGd24cYOnp2CENvE9gn9Adh4EAoHgL5DeRyAQCP4C6X0EAoHgL5DeRyAQCP4C6X0EAoHgL5DeRyAQCP6CAz/OyspKxgCnfA6MJYJuy4gAczChm49AgG+6iF3YjOfg4uLCswYjEAgEgguwqc8JvF6NgkCMTggEwvXr/4+98w6I4ur+/t2FpffuCmisqBhArAiYKBbsKGADFEUQRTBRFAsGG0ViCQhRcBERCyU+QUUfBUUUBY0goEQDCUUpskqRJrCw8/5xf5l3nwXWXcqC7vn8tXPn7pk7M/DdO2fOPSfG1ta2vwcCAMIG/PsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACiBeg+AACAaAG6DwAAIFqA7gMAAIgWoPsAAACihXh/DwAAhERYWFhNTQ1nS0JCQlFREbnp6OiooaEh9HEBgLChEATR32MAAGHg4uISFhYmKSmJNwmCoFAo+HNbW5uiomJlZaW4OMyEgK8f8PMAosKqVasQQi3/0traSn6mUqmrV68G0QdEBJjvA6ICm82m0+mVlZWd7n306JGJiYmQhwQA/QLM9wFRgUql2tnZSUhIdNw1aNCgadOmCX9IANAvgO4DIsSqVataW1u5Gmk02tq1a0lfPwB89YCfBxAtRowY8c8//3A15uTkfPvtt/0yHgAQPjDfB0QLOzs7Go3G2TJixAgQfUCkAN0HRAs7OzsWi0Vu0mi0devW9d9wAKAfAD8PIHIYGBi8ePGC/MsvKCgYMWJE/w4JAIQJzPcBkcPBwUFMTAwhRKFQjI2NQfQBUQN0HxA5Vq1axWazEUJiYmIODg79PRwAEDag+4DIQafTTUxMKBQKm822sbHp7+EAgLAB3QdEEXt7e4IgZsyYMWjQoP4eCwAIHaIHxMTE9PfwAQAARA5ra+ueSHcvJKIC9e8VTpw4gRD64Ycf+nsgosKJEyecnZ1lZWURQitWrNi2bRukagC+CLBW9IRe0H1bW9ueGwHi4uIQXEwhMn369MGDB+PPK1asmDZtGlx84IsAa0VPAP8+IKKQog8AogboPgAAgGgBug8AACBagO4DAACIFqD7AAAAogXo/hdMdXW1tra2n59ffw/kf8jKyrKyshLyQX19faOjo4V8UAD4QgHd/7IhCKJPC0WdOnWqtraW//6//fbb8uXLN2/ezNWempoqJib2+vVr/k3t37+f8i80Go3JZOJ2JpO5YsUKBQWFIUOGhISE4EY7O7vg4OAtW7bwbx8ARJZeiN8H+gsVFZWysrK+s9/Y2HjixAk7Ozs++2dkZGzcuDEtLW3s2LGc7TU1NQ4ODjgVGp/U19cHBweTm3PmzNHQ0MDtpqamY8eOLS4uLigosLS0bGho2LVrl66ubnJysrGxsa+v7549e/g/EACIIDDfB7pk8+bNhYWFfHZua2tbu3ath4cHl+gjhNzc3AT1/ISGhp49e5ZcVp6YmIjbDx48WFxczGAwVFRUpkyZ4uHh4e3tXVxcjBCSl5ePjIz09vZ++fKlQMcCAFEDdP9L5dOnTxcuXJgxY8bu3bsRQn/99dfOnTs1NTUrKir27dunpqZGp9Pxur6srCw3NzddXd2ysrKFCxfKysoaGhqmpqYihMTFxbEjBdvU09PDmw0NDc7OzlFRUQghZWVl3JKXl6empnbkyJFOxxMVFZWfn79+/Xqu9rCwsIkTJxoaGgp0asePH9++fbuTk9Pz58/JdjabHRUVNWXKFFVVVdwyb948FouFx4kQMjExMTAw8PHx4f9YACCCgO5/qcTHx7u7uz948ADXjXJycjp+/DiTyfT391++fPk///wzYsQIZ2fntra2hQsXhoSEMJnMM2fOnD59+tmzZywWa+7cua9fv/7w4cOYMWNIm48fP54yZQr+HBYWht8Y19TUEAQhJydHEASbzSa6KNB2/vz5UaNG6ejocDa+fv369u3b27ZtE+jUwsPDmUxmSUkJg8EwNjbeu3cvbn/16hWTyeQ8BC6Z8uTJE7LF3Nz82rVrHz9+FOiIACBS9IPunz179sGDB4J+a9OmTR8+fMCfT58+LS8vP3ny5IaGhh4Opo/MCgF7e3tOh8bDhw+xvHp6ehoZGSkqKi5durS2traysrK8vNzS0pJKpf7000/a2tpjxow5depUS0tLUFCQkpKShYUFaURFRYVzkwt9ff3q6up9+/Z13NXS0pKenj5u3DjOxtbW1m3btoWGhgr65tnV1bWsrOzmzZtr164VExPz9fXF72/fvXuHEMKOfoySkhJCqLKykmzR09NjsVj37t0T6IgAIFIIW/fZbHZgYGBgYKBA30pISDhz5gynEYIg2tvbeziYPjIrNNTV1Tk3sSBKSUnhTRkZGYQQriGura1NpVJxcUGE0Pfff6+goPDs2TOEkISEBKcR8usCUVxczGKx1NTUOBt3797t4eGhqakpqDUajUan0y0tLSMjI1NSUhQUFI4ePYoQam1tJc8Lg28W5ynQ6XSEEP+vJQBABBG27v/+++/5+fmJiYmvXr3i8ysPHjywt7fnbNm8eXNDQ0NmZqacnFy3R9JHZoUJlUrlscl7l7a2NpbRXgE/IUlKSpItt2/fJgjC0tKyh5ZNTU19fHzevHnDYrG0tLQQQlVVVeTempoahBBux+C8ypx9AADgQti6j18nEgTR6ZQ/NTXV1NRURkZGU1PTycmpvr7+4sWLs2fPrq+vRwipq6tTKJTvvvuODOtubm7W19cnN6dOnYoQ8vHxwZvx8fEIoejoaFNTUzk5OSUlpeXLl2NfwWfN4vFcu3bN2NhYWlpaW1v7xx9/xOp25coVsmdoaKiFhYWiouLo0aPT0tKEdBG7BZdfvrq6esiQIb1lXEVFBSHU2NhItpw6derEiRPkhXJ0dEQIjRkzRk9PT1DjpqamdDqdRqONGzdOQUGhoKCA3PX3338jhMzNzckWfO++lF9uAOgXhKr7KSkpa9asmThxIkLo4sWL5eXlnHvT0tJmz54tLi5eUlKipKTEYDB27NixZs0aT09P3OH9+/cEQdy5c2f+/Pnkt65fvz5y5Ej8+bfffkMIeXt7L1my5MyZM1ZWVocOHbK3tw8ICCgsLNTV1b169Squp/pZswih33//fenSpY2NjSUlJQcPHjxx4sSMGTNYLJatre3OnTtxnwcPHkRHR0+aNCk/P3/Dhg19cdF4gH04bW1teBNLHumnwvHynHs/ffqEP7969aqysnLJkiUIIRqNhv6dsCOEcJ/3798jhLBfvqsXuZzQ6XRJScmKigqy5fr165z1fc6dO4ePK9DSLUx6evqPP/6IEJKQkHBwcEhLSyOXkt25c0daWpqzRi5+WzNq1ChBjwIAooNQdT8pKWny5MkbN25ECLW2tgYFBXHu3bFjB4vFcnJyUldXd3Nzk5aW5nx+J5GQkPjmm2/IzW+++eb06dP4c2xsLEKovb1dWVnZ2dlZTEzs1KlTCKG0tDQNDY3p06cjhNLT0zsdG5fZ9vZ2Dw8PgiAWLVqkoaHh4OBAo9GysrIYDAaVSiV7enl5aWlpGRkZIYTy8/PJBwXhgN9epqenf/r0qaWlBT9wpKSkEATBYrHu37+P+2DhJghi27Zt1dXVRUVFGzdunDRpEnZzDR8+HCHEYDAaGxsZDAa+PhMnTmQwGMrKygihzMzMs2fPlpWV5ebmqqiodJoWQlJScsaMGfz77hYvXqypqdnpE1JbW5ubm1tERERLS0tNTU14eHh2djbWfYSQj4+PlpbWDz/8UF9fn5ycfPLkycOHD3Nm0s/Ly6NSqaampnxfRQAQOYSn+9nZ2VhiVq9ejR/DT58+jT0tCKG3b9/iaDz8Xm7r1q1NTU0HDhzgx/LMmTO//fZbhFBERARC6L///e/y5cvxrmXLlsnKyg4ePJggCBzb197ezs+b25ycnDdv3iCEcN1tcXFxRUVFhND169c7dibflzY1NfEz4F7h999/X7hwIULo8ePH06ZNmzt37u3btxFCq1atOnbsmJmZGQ7ed3FxwcEwMjIyBgYGI0eONDQ0HDZs2K1bt/BMf82aNcuWLfPy8poyZcrw4cNnzZo1derUwMDAlStXWltbm5iYrF69mryGPOb+9vb2JSUleAnVZ6mpqZGSkur0J0RMTOzjx48eHh7q6uqLFi2Sk5OLiIggI4JUVVVTU1PfvXunpaW1devWoKAg8icBc/fu3Xnz5nU6YwAA4P/oSXFeXFmXz84uLi4NDQ34s5OTEz76zz//jFvw5BQhlJCQwPVFMnwbO2QIgiDTsHz69Am3nD17Frf88ccf+/bta29vJ7/e3t5+/vz5qVOnTpgwAfdhsVifNXvjxg38OSQkBO/FwTMTJ04kCOLXX3/Fe58/f04QxK5du7hMdQNra+se1krmgYuLi6ysbB8Zx7S3t48dO9bT05PP/g0NDb1+vtnZ2VQq9enTp4J+ESEUExPTu4MBgD6i51ohpPl+UVHR2bNn5eTk8Fs+UqZPnjyJndTki7jMzMxu2F+zZg0OIvz1119xzCJuLygomDhx4rZt2yIiIgSqmk2GSJL+cRz9oq2t3Y3h9Tt8PuX0BCqVGh0dfebMmYyMDH76BwcHC7qeizctLS1btmzx9PScNGlSL5oFgK8PIen+kSNH0tLSyF+b9vb28ePHI4RKS0svX76MEPr2229x+PmFCxdIqW1paUEcXhQeSElJOTs7I4SuXLlCvuUjCGLhwoXPnz/ftm0b56pUDG+zEyZMwL4C/J6wtbW1rq4OITR79myBTnwg8PHjx8zMzObm5ocPHxJ8vKTtNkZGRtHR0dbW1jdv3uTdMygoyMTEBL9x6RVwCooRI0b4+vr2lk0A+Frpc92vqKjYu3dvRkYG52JOKpXq7e2NP7u7u9+6dYtKpWJvb1FRkbOzc3V1dW5uLl6tM3ToUNzzzz///PnnnxsaGkgncn5+Pmlz8+bN4uLiK1euxDGFCKH379/jDm/fvi0uLr527Rpux45+3mbFxcWPHTuGEEpISHj//n1oaChBEOPGjXNycmKz2SUlJbhncXFxe3s7uVlUVNRLl63XqK2tVVJSwlluzM3NGQxGnx5u0aJFt27dwtE7PHB3d+cMvuw5ERERtra2kZGRPBYxiA5fUwmEly9fzp8/X15eHsd2a2lp9VbBicLCwr1799LpdD5fSn1V9MRJxI9/f/To0eSx4uLicGPHPOl79+4lCCIyMnL06NESEhJ44oYd8a2trY6OjjIyMnp6eg8ePOAKl+R0qa9cuTIrK4vz6Js2bZKVldXX1/eqjJ1ZAAAgAElEQVT394+NjVVXV1dXV/fw8GCxWPyYjY2NNTQ0lJSUVFNTc3R0rKysJAgCP6CQkL5+DB5zN+hT/z7AGyQU/35wcDBOdtSnRuLj44cOHXrnzh2u9vv371Op1FevXvF/LHJyhhASFxfHf/8EQVRWVtra2srLy+vq6p46dQo3lpSUTJ48efPmzYKczWcoLS1VUlK6detWTU2Np6cnfr3v5+fXK8bnz5+PV3oXFRXx+ZWLFy8aGRnJyspqaWmtWbPmzZs3XfXs9BL1Fj3XCuG91wV4A7rfjwhB9xsaGoYNG9ZD3f+skfT0dGVl5by8PK726upqXV1dhBD/ul9XV4fTH2Hmz59Pto8cOXLJkiVVVVUZGRnKysr+/v6cu44cOSL4mXWOn5+fvLx8b1nryE8//cRD99lsdlJSko2NDQ42uXLlirKycmJiYlNT09u3b21sbEaPHo2Tu3DR1SVyd3ffuXPn33//3cNhg+5/PYDu9yNC0H0HBwf0b3LTPjLCYrFGjRrl4+PTcdfq1as9PDwE0n1/f//4+PiO7Tt27KDRaB8+fMCbPj4+NBqNlM5Hjx5RqdQXL17weRTeuLi4qKqq9oqpTsEhzh11v7Ky0t/ff/jw4dOmTTt//jyOG1y1atXMmTPJPmlpaRQKpba2tqPZri5RaWmpj4+Prq7urFmzYmNjW1tbuzds0P2vB9D9fkRQ3b9//765uTlOKLJp0yYsxGSkAO5Dejjr6+vxWkWS1NTULVu26OjolJaWLliwAC+tuH//vkBG6uvruUaFX950dD6cOXPm+PHj5JJpfk6wqalJQ0NjyJAhGzZs4PSdtre3a2homJqaki04fOvAgQNki5GR0fLly/Hnly9fqqqqHj58uNOj8DjZpKSk//UEo/z8/KioKHNzcy8vL4IgZsyYQe5KSUnBM3eE0Llz57C1mJiYb7/9VkJCYuTIkZw/YI8ePZo+fbq0tLShoeH27ds5dZ/NZicnJ9va2qqpqbm6uubm5nKONjAwkEKhHD58uK2tjc1mr1u3Do+Ei89eora2tmvXri1YsIBOp+/atasb03/Q/a8H0P1+RCDdv3Pnjry8/PXr1+vr62NiYmRlZSdOnMhisWpqanDYGO5WVVWFixlggeYsZoAXA0pKSnp7e799+/bPP/8cO3aspKTkq1ev+DfSEXNz81GjRnE1vnr1atmyZWw2WyDd/+WXX0hVpVAoe/bswe049feqVavInjjgjfQCEQTh4eFBo9HwRPjFixfKysqHDh3q9Ci8T5YgiA0bNpDz/aioKOx32rVrF+6M06XMnTuXzWbX1dVpaGiQk+iIiAgzM7OCgoL3798vWbKESqVmZmYSBJGRkSElJXX06NGamprY2FhpaWms+0wmMyAgYMSIEcbGxmFhYeRKI05aW1tXrFiBENLX11+5cmVsbGynJ8XPJcK8efNm//792traFhYWcXFx/E//e64VUF93AFFaWopTTQADFoIgtmzZsnbtWrxY2tbW9s8//zxw4EB4eLirq6uFhQWZrAIXM+CsCUNSXl4+f/78+/fv//TTT3jOe+rUqZkzZwYFBeFMf/wY4QKXQMCjIsElEM6fP9+NEgjW1tY5OTkxMTEXL1709fWl0+lbtmwRqASClZUVrtnQ1VFw+Qc+T9be3n7mzJnkAhoVFZWAgICysrJLly6lpqbeuHGDwWDg029ra/Py8kpNTcVleYKCghISEgIDAy9fvuzi4vLdd9/h3Fw2NjZ3797Fmdi3bt36+++/h4aGdiwYR0Kj0S5fvtzS0nLt2rWioiIyKQAX/FwijI6OzoEDB7y8vJycnGxsbOLi4qytrbs6eu8Cuj+AyMjIwBMKYMCSmZlZUFBAJuZDCDk7Ox84cCAxMdHV1ZX/Yga9XhGhL0og4CoITk5OCxYsOHr06JYtW3q9BIJAJ8tVcAIhFBYW9uLFCysrq927d5O/ebm5uUwmk2vJTl5eXk5OTk5Oztq1a8lGsvxnUFCQkZGRn58fg8Fwdna2tbXFjwJcHD58eOrUqdu3b1+xYoWtrW1ERMS6deu4+vBziTBFRUXh4eHnzp0bN25cbGwszpMoHL7aYOfq6mptbe3eCvXtC4MdAT9Pf8H/PcJrNTgTMdHpdBkZGa7ksp+l1ysiiEIJhI4XTUZGZt++fbW1tXhZKG7E2WRLS0s5b3Fubi5+sOj444EQ0tDQ2LVrV35+Pv4JHzp0qIeHx59//snZJyYm5urVq7t27TI1Nf3jjz/GjBnj5ubWcRb/2UvU3t6ekJBgaWlpYmLS3t6elpaWnJxsY2OD82UJh69K90+dOkVm6EUIEQQh6ONtXxsEvnRw7k+uzKPi4uLDhg0T1BTRqxURRLMEQmlpaXR0NIPBuH79ur+/P27EKRQ7ukzxjBvnW+wUCoViYWERGxubm5s7aNCgxYsXm5mZRUdH4zMKCQmZPHky7kmn069du/bp06eUlBQuIzwuUVlZ2YEDB7755pugoCBHR8c3b94EBATgbJVC5uvR/cbGxhMnTpCbKioqZWVlXl5eA8cg8BVgZGSko6Nz5coVsmJBaWlpXV0ddtAJVMygdysifKElEHicLEKotbUVJ2vBcBWcaGhocHZ2DgkJWb9+vZOTk7e3d3JyMkLI0NBQUVFx9+7dR48eLS8v//jx44MHD3bs2DFlyhQqlXrp0iVcmoKEPByJpqaml5dXQUHB/v37ExIS7ty5g8+dU82HDh0qKSmJH2444XGJAgICGhsb7927d/fuXVtbW2FO8LnpydPxgIrn6ZX46D41yBuI5+lHkCDxPPjPfvHixWVlZeXl5QsXLsQhJQRBhIeHI4ROnjzZ0NBw9uzZ77//HiGkoqJy9uxZ/P4wKSkpPDy8tLTUxcWFQqE4OztXVVUVFhZOnz598uTJOKKDfyNcA5szZ86QIUO6GjZXPA8uLIFTNnHBYrG2bNnCYDCam5urq6vDwsIcHR3JBUofPnzQ0dFZt25dXV1dUlKSgoLCsWPHOL/u6elJpVIrKioIgsjJyVFWVvb19e1qVDxOtrS0FCdTwTUkCILAWXJNTEyampqYTObMmTOPHz+Od5WWloqLiysrK9+9e7e9vZ1zxoYQEhcXT01NJQhi8+bNCCG81Paff/6ZM2cOQkhJSYlcesYDnIP98OHD1dXV7969c3FxGTduXEtLS8eL+dlL1EO+mDjOnJychQsXysvLDxky5NKlS/Pnz//s2uiSkhJra2s1NTUZGRkTExPOIOKbN29OnjxZSkpq6NChv/zyC0EQXKHNTCaTM9SXM1cE/rsnqzzGxcV1eiDeBjGdBnG/fv3a09NTQ0OjvLx87969qqqqgwYN6irkixPQ/X5EIN0nCCI+Pt7AwEBSUlJXV3fPnj3Nzc24vampadmyZVJSUuPGjUtJScGvARkMRkNDQ1VVlYmJibq6+qVLl4h/M2OHhISoqKgoKCjY29tXVVUJaoSLCxcuoK5Xn3Lpvqmpqa6ubsfgQoIg2Gy2nZ2dnJycvLz89OnTOx6rsLBw3rx5OMdJZGQk194JEyaQZrOzs5WUlHjoflcni2fuJMOHD//Pf/5DbhoYGJBvQfEPzKxZs8i9SUlJBEGEhYUNHz5cWlp60qRJycnJ+HBtbW179uxRV1eXk5Ozt7f38/MzNDQMCQnpdPlVR8g1Adra2s7OzmSSmI4Xk/cl6iFfhu4/fvxYUVHx5MmTNTU1z58/x57Qz+r+xIkTLSwsKioq8vPztbW1p06ditsvX748aNCgBw8eNDU14Tw/ly9fJv43tJkr1JfJZH733XeI48mXzWa7ubmFh4ez2eyuDsTDINF1ELepqSkO0nB3d8/KyqqtrTUzM1NSUvps3h7Q/X5EUN3vOX1REeGLLoHwpdMXF7MrvoD8+2w2e/369TY2Nh4eHkpKSoaGhjhhMj9ftLKy0tLSGjly5KxZs/755x+EUEtLi7u7u4+Pj5mZmbS09KZNm1RUVDjfZWHs7e3x6gmMurp6cHAw+je0FiFEoVAaGhqcnJwoFEqnB+JtkOAI4paTk7O1td2xY8ezZ8/Cw8MfPnyI08p7enoaGRkpKiouXbq0tra243t/QJTpi4oIUAKhH+n1i9mn9LnuZ2VlvX79mnM5CX7b/lkyMzM3b9785MkTOzu7mJgY/Ern6dOn79+/NzY2xn309fWrqqo6LWjOFa2lr68/a9YsshJvVlbW1KlTeRyIt0EcxG1gYEC24B+zxMRE9O+SDTISGUfydmX2q+drygncW/RdRQQogdAv9PrF7Gv6XPdxDFM36p2WlZVZWlq6uLhYWlquWLEC/3swmUzU2fv3jnQM9d22bVtmZiauG3758mU7OzseB+JtkHcQ98BMAc8VkyocI7/99tvy5cvxyzROUlNTxcTEBAos2b9/PxmSSKPR8F8CQojJZK5YsUJBQWHIkCE4zRZCyM7OLjg4uGO674FAX1dEgBIIwqfXL2Zf0+d3CM/uBfVyNDQ0mJmZKSoqZmZmrlmzhpw74yBl/P5KUBYsWDBy5MhTp059/PhRWloaB2B1dSDe9GIQt3DgikkVjpGMjIyNGzcmJiZyFSmrqalxcHDgiqXjTX19PfbUYebMmYMfqurr601NTVtaWoqLi2NjY729vQMCAhBCurq6ycnJSUlJA3DuqaSkxOlpJWtN9yLjx4+Pi4vrdbO88fb25oqGAAYsfa77+vr6VCo1ISFBoG89fPiwqKho/fr1nBn7EEKTJk2SlZW9fPnyTz/9VFlZWV9fn5iYePDgQdQhtJkr1Bd3cHd3j4+PP3bsGLm6uqsD8TbIO4gbr/IgvbdY4DhHInw2b97M57r53jLS1ta2du1aDw+PsWPHcu1yc3MT1PMTGhp69uxZUiuxPw0hdPDgweLiYgaDoaKiMmXKFA8PD29vb1w+SV5ePjIy0tvbm/PFDAAASAi6r6Oj4+joeP78+ePHj1dXVz9//pysd8gDnOLj4sWLHz9+jIuLe/ToUVNT059//vns2TNvb2+CIA4ePKilpaWgoLB69WqczEhZWRkhlJmZefbs2bKysnv37iGE0tPTyaUxCKF169bJyMhkZ2eTE/OuDnT//n0eBiUlJX/++efa2to1a9aUl5dXVFS4urrOnTvX2tq6paUlLS0NIZSSkkIQBIvFun//Pvo3BrlXLmlqauqMGTNw0R9XV1fseBEXF8c+ENxHT08Pb+K1LVFRUfgSUSiUBw8euLm56erqYoesrKysoaFhamqqQEYaGhry8vLU1NSOHDnS6SCjoqLy8/M7ZrkKCwubOHEimReFHz59+nT8+PHt27c7OTlh9wiGzWZHRUVNmTJFVVUVt8ybN4/FYuFxIoRMTEwMDAx8fHz4PxYAiAQ9CQbiM46zqalp/fr1srKy2tragYGBoaGhiI84zp07dyooKOjr61+9evXChQuysrI//PBDe3s7QRAnT57U0dGRk5ObPXs2GdfPGdrMFerLaXb79u04b8lnD/RZg50GcXOmBQ8MDMR5ZTHBwcE8zpfP2KyBkwSYd4rdAZgTmAdI6HGcANBtvoz4fS5wQVr+a1qKCPzcSzabPXLkSDc3N7IFl5vAZd+3bt3KeTv27t3blWRbWlpKS0u3tbXhTfwo4+rqKpARHjQ3N9NoNCsrK87GlpaWuXPnvnv3juiwhog3ra2tZWVlN2/eXLt2rbi4OEIIFyzFS3s8PDzIntiZZmxsTLbgP7arV6/yPgToPvAF8QXE73cEO8p7PXhZFOAdP9qPSYC56IucwJaWlpGRkSkpKQoKCkePHkX8JbwVKCcwAIgIwtZ9FouF3d/JyckCRXQAaAAnAeZCFHICA8CXi7B138zMDOdH3bRpk5iYGKULhFZ35stiwCYB5kI0cwIDwJeCsHU/IyODH/dTfHy8kAf2RTBgkwBz8YXmBAYAEUHkVtZ90fCIH0UI4QIODAajsbGRwWDglckTJ05kMBhcMakIIYIgtm3bVl1dXVRUtHHjxkmTJtnb2wtkJDc3V0VFpdMCZJKSkjNmzOB6LuHB4sWLNTU1sQOQi7a2Njc3t4iIiJaWlpqamvDw8OzsbKz7CCEfHx8tLa0ffvihvr4+OTn55MmThw8fxk9FmLy8PCqVampqyvc1BoCvH9D9LwxbW9v4+PiSkpJhw4ZNnTr122+/TUhIwDPxNWvWLFu2zMvLa8qUKcOHD581a9bUqVMDAwNXrlxpbW1tYmKyevVqWVlZLIsyMjIGBgYjR440NDQcNmzYrVu38EyffyN45t7VOO3t7UtKSvASqs9SU1MjJSXV6U+ImJjYx48fPTw81NXVFy1aJCcnFxERQa4wUFVVTU1NfffunZaW1tatW4OCgsifBMzdu3fnzZvXjTQhAPA105NgoAFVd+VLR5h5mPsiCTAXX1ZOYARxnMCXwxcZxwn0O32RBJgLyAkMAAMW0H2Ro++SAHMBOYEBYGACui9a9HUSYC4gJzAADEDE+3sAgFDBSYCFecT+ygks5CMCwBcEzIYAAABEC9B9AAAA0QJ0HwAAQLQA3QcAABAteuG9Lmc6FKDb4Dh3uJj9xYkTJ4T//hkAukFGRsbUqVN7YoHSk+iO9PT048eP9+TwANBfvHjxQldXV1FRsb8HAgACM23aNK6UJALRI90HgC8XCoUSExNja2vb3wMBAGED/n0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRAnQfAABAtADdBwAAEC1A9wEAAEQL0H0AAADRgkIQRH+PAQCEwezZs588eUL+wbe0tNBoNCr1/6Y+NBotJydHR0en/wYIAEJCvL8HAABCwtLSMjk5mbOFxWLhDxQKZcKECSD6gIgAfh5AVFi5ciU5u+dCTExs7dq1Qh4PAPQX4OcBRAhzc/NHjx6x2WyudiqVWl5erqmp2S+jAgAhA/N9QISwt7fv2CgmJvbdd9+B6AOiA+g+IEJYW1uLiYl1bO/09wAAvlZA9wERQllZefbs2VzST6VSly5d2l9DAgDhA7oPiBZ2dnac/n1xcfH58+crKSn145AAQMiA7gOixZIlSyQlJclNNpttZ2fXj+MBAOEDug+IFjIyMlZWVjQaDW9KSkouWLCgf4cEAEIGdB8QOVavXo1XbNFoNBsbG2lp6f4eEQAIFdB9QOSYO3eugoICQojFYq1evbq/hwMAwgZ0HxA5aDTaqlWrEEJKSkqzZs3q7+EAgLD5n/w8paWljx8/7q+hAIDQ0NLSQghNnjz56tWr/T0WAOhzdHR0pk2b9v+3CQ5iYmL6b2AAAABAn2Btbc0p9Z3k44SMPb2CjY0NQiguLq6/ByKKUCiUmJgYW1tbHn2Cg4Pd3NwoFIrQRgUA/QLWIk7Avw+IKCD6gMgCug+IKCD6gMgCug8AACBagO4DAACIFqD7AAAAogXoPgAAgGgBug8AACBagO4DAACIFqD7AAAAogXoPgD0iOrqam1tbT8/P97d8vPzd+3apamp+e7du24fKysry8rKqttfHzj4+vpGR0d3++svX76cP3++vLy8pqamk5OTlpbWZ68/nxQWFu7du5dOpxcXF/eKwYEJ6D4A9BSCID67CszFxeX48eNMJrOrDqdOnaqtreVh4bffflu+fPnmzZu52lNTU8XExF6/fs3/gPfv30/5FxqNRo6KyWSuWLFCQUFhyJAhISEh/BsU1KadnV1wcPCWLVsEOgSmrKzMzMzM3d397du3a9eujYiIqKys7K1VeFu3bv35558rKir4/8qlS5cmTJggJyc3aNAgOzu7t2/fdtXz3bt3oaGhM2fOdHNz643B9oCOedkIoDewtrbmyoUECA2EUExMTH+PgpsdO3YghCoqKjruamhoGDZsWE1NTVffTU9PV1ZWzsvL42qvrq7W1dVFCL169YrPYdTV1XHWE54/fz7ZPnLkyCVLllRVVWVkZCgrK/v7+/edTbzryJEjfB6CxM/PT15eXtBv8c9PP/2EECoqKup0L5vNTkpKsrGxSUhIIAjiypUrysrKiYmJTU1Nb9++tbGxGT16NJvN7vS769atGz9+PELIxcWFbHR3d9+5c+fff//dB6fyf3TUItD9vqIbul9VVTV48GBfX98+GlL3yMzMXLp0qZAPeuTIkQsXLnT76wNT9wMCArrSfQcHB4RQV7rPYrFGjRrl4+PTcdfq1as9PDwE0n1/f//4+PiO7Tt27KDRaB8+fMCbPj4+NBqtK/nrFZuPHj2iUqkvXrzgc+QYFxcXVVVVgb4iEPihpOOJV1ZW+vv7Dx8+fNq0aefPn//06RNBEKtWrZo5cybZJy0tjUKh1NbWdmW8ra1NUlKSU/dLS0t9fHx0dXVnzZoVGxvb2tray+cDui9Muqf7dDrdz8+vj4ZEEERwcDCPSWVH4uPjhw4deufOHa72+/fvU6lU/rWGIAhvb29yPiguLl5ZWYnbKysrbW1t5eXldXV1T506hRtLSkomT568efNm/u1zwr/uDxkyBA9pyZIlBQUF5Ag1NTUJgiBbtm/fThBETEzMt99+KyEhMXLkSCxzTU1NUVFR5ubmXl5epM2rV6/iB/+JEydmZGSQ7YGBgQiht2/f7tmzR0VFhU6nX716lSCIjRs3cj6C19fXcw2SwWAghN68ecPVfubMmePHj587d45/3W9qatLQ0BgyZMiGDRuysrLI9vb2dg0NDVNTU7IlIyMDIXTgwIE+tWlkZLR8+XL8+eXLl6qqqocPH+7qQElJSVzuivz8fM7rP2PGDHJXSkoKnrkjhM6dO4ctdLyDmEePHk2fPl1aWtrQ0HD79u2cus9ms5OTk21tbdXU1FxdXXNzczmHFBgYSKFQDh8+3NbWxmaz161bx/mX0CmKioqcuo9pa2u7du3aggUL6HT6rl27enf6D7ovPAagn+ezzgQu+te30G0/ACGI7n/48GHu3Lni4uJMJpMgiJqaGlNTUzU1tcbGRtwhKCjI39+/ubk5IiLCzMysoKDg/fv3S5YsoVKpmZmZUVFR+Lx27dqF+1+/fp1CoTAYjIaGhrCwMHy+VCq1tLQU6767u/vz58/fv38/bdo0NTU17BPAryW7ujXm5uajRo3ianz16tWyZcvYbLZAuv/LL7+Qd4FCoezZswe3v3z5EiG0atUqzivDeaf6yKaHhweNRsMT5BcvXigrKx86dIj34TZs2EDO97muf1VV1c6dOxFCc+fOZbPZdXV1Ghoa5CS60ztIEERGRoaUlNTRo0drampiY2NxveWioiImkxkQEDBixAhjY+OwsLCGhoaOg2ltbV2xYgVCSF9ff+XKlbGxsZ+9XJ3qPsmbN2/279+vra1tYWERFxfXK9N/0H3hMQB1n7czgYuB4Fvonh+AENDPk56ejhAi3UqhoaEIoWfPnuHNNWvWNDc3s1gsDQ0N8nxLSkoQQitXriQIorS0lFP3ra2t8bMCZuLEiQsWLMCfse4XFhbiTez2effuHcFT95ubm2k0mpWVFWdjS0vL3Llz8XcF0v3W1taysrKbN2+uXbtWXFwcIYSfsZKTkxFCHh4eZM+2tjaEkLGxcZ/a/PXXXxFC+LmHTzh1n+hw/QmCWLNmDYVCSUlJ2b59+/Xr13EjjztoYGAwb9488usuLi5Y91esWCEpKclgMHiPh81mL126lEqlysrKxsXFfXb8vHUf09TUhCs/82Pws3TUIojnGSh8+vTpwoULM2bM2L17N0Lor7/+2rlzp6amZkVFxb59+9TU1Oh0Oq7ikpWV5ebmpqurW1ZWtnDhQllZWUNDw9TUVISQuLg4DqjANvX09PBmQ0ODs7NzVFQUQkhZWRm35OXlqampHTlypNPxREVF5efnr1+/nqs9LCxs4sSJhoaGAp3a8ePHt2/f7uTk9Pz5c7KdzWZHRUVNmTJFVVUVt8ybN4/FYuFxIoRMTEwMDAx8fHz4P1Y3mDp16qhRo8iCi5mZmSoqKrGxsQihuro6dXV1SUnJ3NxcJpM5ZswYfD2xdygvLw8hpK6uzmlNRkbm48ePra2teFNLSyszM5OzA55O4p4IoebmZt7DKy4uZrFYampqnI27d+/28PDQ1NQU9GRpNBqdTre0tIyMjExJSVFQUDh69ChCCA8YDwnT3t6OEJKQkOhTm3Q6HSFUWFgo6ImQcF1/hFBYWNj48eOtrKw0NDQWLlyIG7u6gzk5OTk5OXPmzCG/Tv5tBwUFHThwwM/Pb/r06dih3+kADh8+PHXq1NTUVEVFRVtb28jIyG6fC0KoqKhoz549w4YNq6ysjI2NXbJkSU+sdQXo/kAhPj7e3d39wYMHBEEghJycnHDYn7+///Lly//5558RI0Y4Ozu3tbUtXLgwJCSEyWSeOXPm9OnTz549Y7FYc+fOff369YcPH8aMGUPafPz48ZQpU/DnsLAwzkmlnJwcQRDYydDpeM6fPz9q1CgdHR3OxtevX9++fXvbtm0CnVp4eDiTySwpKWEwGMbGxnv37sXtr169YjKZnIcYMWIEQujJkydki7m5+bVr1z5+/CjQEQXFwcHh9u3bTU1NlZWVgwYNWr16Nf6JvXHjBp52vX//HiFUWlrKOWnKzc1FCFGp//NPtHv3bgUFhR07dtTX1z99+vTBgwfz5s3jceiurj9JQ0MDQkhSUpJsuX37NkEQlpaW3TzbfzE1NfXx8Xnz5g2LxcIFh6uqqsi9NTU16N9CxH1nU1ZWlquPoHBdf4SQjIzMvn37amtr09LSyMvb1R189eoV6uzHA/dg6F4AACAASURBVCGkoaGxa9eu/Pz8AwcOJCYmDh061MPD488//+TsExMTc/Xq1V27dpmamv7xxx9jxoxxc3OrrKwU9Cza29sTEhIsLS1NTEza29vT0tKSk5NtbGxoNJqgpvgBdH+gYG9vj/2hmIcPH2J59fT0NDIyUlRUXLp0aW1tbWVlZXl5uaWlJZVK/emnn7S1tceMGXPq1KmWlpagoCAlJSULCwvSiIqKCucmF/r6+tXV1fv27eu4q6WlJT09fdy4cZyNra2t27ZtCw0NFTRW2tXVlfQDiImJ+fr64pAJvIJJQ0OD7Il9tZz/Nnp6eiwW6969ewIdUVDs7e0/ffp0+/bt6OhoFxcXR0fHoqKiP/7446+//po0aRJCSFFRESGEHwJ4o6ent2PHjtzcXC0tLRsbGycnJ0ED4blQUVFBCDU2NpItp06dOnHiBBks7+joiBAaM2aMnp6eoMZNTU3pdDqNRhs3bpyCggLnm+2///4bIWRubt6nNvHjjpycnKBH4UFpaWl0dDSDwbh+/bq/vz9u7OoO4oePN2/edGWNQqFYWFjExsbm5uYOGjRo8eLFZmZm0dHReOQhISGTJ0/GPel0+rVr1z59+pSSksL/aMvKyg4cOPDNN98EBQU5Ojq+efMmICBg+PDhgpyxwIDuDyC4Jh1YEKWkpPAmfl5msVgIIW1tbSqVKiYmhnd9//33CgoKz549Qx0ezMmvC8TA8S303A/AD7q6ut9///1vv/1WV1enra09YcIEAwOD8+fPkzNTQ0NDRUXF3bt3Hz16tLy8/OPHjw8ePMDx+PiOYM81QujJkyeJiYl3795tbGwsKSk5duwYeYK4Jz5HhBCbzSa/iH9KO5370+l0SUlJzpVEpM8aQ/r3BVq6hUlPT//xxx8RQhISEg4ODmlpaeTasTt37khLS3cszdq7NvGb3lGjRvFvv7W1taWlhdzkuv7YpRkSErJ+/XonJydvb2/8mqGrOzhlyhQqlXrp0iV8O0jw8wEnmpqaXl5eBQUF+/fvT0hIuHPnDj5Hzh+2oUOHSkpK4ocYPgkICGhsbLx3797du3dtbW37aILPBej+AILribXjAyyPXdra2qRPuecMHN9Cz/0AfLJ27dorV64sXrwYbzo6Op49e5ZMiiAlJeXj49PS0rJr167BgwcrKSnNmjULd8bPIunp6dj/e+nSpdTUVPJFC3YlJyUl1dTUPHz4ECGUkpLCZrNZLNaDBw8QQqmpqQRBKCsrI4QyMzPPnj1bVlbGOTBJSckZM2ZgdwQ/LF68WFNTMy0treOutrY2Nze3iIiIlpaWmpqa8PDw7OxsrNEIIR8fHy0trR9++KG+vj45OfnkyZOHDx8ePHhwH9nE5OXlUalUU1NThFBubq6KigrvjAtlZWUPHz5saGgg59Sc1x8H6syePVtbWxsfnUKh2Nra3rt3T0JCotM7OHjw4E2bNuXl5Tk4OLx9+7awsPA///kPQmjOnDn4xTsXFApl9uzZcXFx+O5v27YtJSXlyJEjNTU1lZWVW7ZsGTZs2Ny5czu9aARBlJeXf/r0qby8nHyvExQUdPToUezhFB6cEweI5+lFuhHPg2cuZGQCDv94//493sSRDzjWxcXFRUZGhvO7WlpaixcvJggCRx+T7YcOHUL/hoTzDhbkBM+vHR0dyRby/RgXo0ePFugcCYJ4+vQpnU4nCKKlpUVBQeH7778nd+F/khMnTpAtN27cQAgJGs2JBF+31dDQQAbeEATx4cOHZcuWcfUJCwsbPny4tLT0pEmTkpOTCYLAGoExMDAgCCIjI6Oj12LQoEGcoeV+fn7Gxsbk5rlz56qqqkxMTNTV1S9dutRxbBcuXEBdryDliucxNTXV1dXtNP6SzWbb2dnJycnJy8tPnz6947EKCwvnzZsnIyOjp6cXGRlJtveFTcyECRNIs9nZ2UpKSjzWLeLIK5Lhw4dzXX/yLSheHDdr1ixyb1JSEtHZHSQIoq2tbc+ePerq6nJycvb29n5+foaGhiEhITyWX3FCrgnQ1tZ2dnYm/2E7XjT8v0ny/Plzfuz3HIjjFB7d0P2mpib07xIh4l/JxrF6xL/LCAsKCgiCcHFxoVKpTU1NeNeff/6JY8YJgvDy8kIca3/27NmD/o0dxL7O6urqz46kublZUlKSM7iNC4FiB7n45Zdffv75Z/zZzc2NRqORP0X79++XlpbmfPmGoyMEjWbrhu73FjExMeHh4eRmY2PjixcvjI2N29vbu22zvb197Nixnp6efPZvaGjo9RjivrCZnZ1NpVKfPn3au2YHDn1x0boBxHEOaDifWFtaWvDkNyUlhSAIFot1//593IcgCIQQQRDbtm2rrq4uKirauHHjpEmT7O3tEUL4jRCDwWhsbGQwGHiKNHHiRAaDweVM4PFYPRB8CxhOP8DA56+//nJ1deUMfpWRkRk3bpyNjQ0Pr91noVKp0dHRZ86cwetdP0twcLCgMVfCt9nS0rJlyxZPT0/85vyrpC9uRO/A+SMA8/1eRND5PtcTK6dbIDAwkAzHRAgFBwe7uLjIysqGhISoqKgoKCjY29tXVVVhO01NTcuWLZOSkho3blxKSgoOLsbLR7mcCbwfq/vdt4Dh9APwD+qn+f61a9cQQi4uLllZWR8/fmxoaMjOzt63b195eXmvGB88eHBiYiLvbr/88gt+Z9CL9LrN0tJSCwuLtWvX9uQxaIDTFzeie/Syn+f27durVq0aNmyYlJTUoEGDrKysrly5wmQyyYXafURjY+Pp06fHjh1LOsg4VRIjKyuro6OzaNEiBoPR1tbWp+PplD5dr4t1v4+MYwaCb6HbfoD+0n2CIBITE+fOnaupqSkhITF8+PCdO3fy41jjk9zc3IHgN+g5Bw8eDAsL6+9RiAq9pvsfPnxYunQpQkhRUTEoKKi0tLShoeGPP/7Ai1yWLFnSm6PmoLi42NPTE/srEMeLETabjRfRYKqrqysqKn799Vd5eXmE0IQJE8rKyvpoSF3Rp7rv5OQkJSXVR8ZJsrKyFBQU0tPT+ens5+eHl8n0Fs3NzdOnT+dcf88//aj7ADDQ6B3/fnNz86JFi37//XcZGZm0tLStW7cOHjxYVlZ24sSJFy9eJHPg9QWHDx9+8uQJjjLkhEKhjB8/noxnp9FoWlpamzZtOn/+PEIoKytr8eLFvRjm2L98/PgxMzOzubn54cOHxOdWe/YEIyOj6Ohoa2vrmzdv8u4ZFBRkYmIyffr03jo0TkExYsQIX1/f3rIJAACmO7rv7++P3xZu2rRJX1+fa+++ffvI3LbXrl0zNjaWlpbW1tb+8ccfsV5fuXKFDG0ODQ21sLBQVFQcPXo0fiuor69P7p06dSr6NwiXQqHEx8eHh4enpqa6urryOVQrK6uRI0cihDIzM/HTzJdObW2tkpISznJjbm6OM/T2HYsWLbp16xb25vPA3d29Gws7eRAREYFTnfTkdSgAAJ3DOfnnx8/DYrHILFo41KQr/vOf/1AolNGjR1dWVmJ5mjBhQmtra3t7O86VihBasWJFRUUFDrPFmWYLCwuxUqN/k2m0tbUtWbLkzJkzpJueTPDCFQBLzvc5M5iTtdwsLS0/9zzUmwzAfJyiAwI/DwD8Sy/4eYqKisjFk+S8viPt7e04/+qiRYs0NDQcHBxoNFpWVhaDwaBSqd988w3u5uXlpaWlZWRkhBDKz89vbm7+5ptvTp8+jffiZBrt7e3KysrOzs6krAvEoEGD8AecGwQAAEDEEVj3OTMjcmW04CQnJwenOsKyKy4ujvMiXb9+vWNnUtDxwqWZM2d+++23CKGIiAiE0H//+9/ly5cLOk4SMu3tV+PfBwAA6AkC6/7w4cPJdIy4dkGnkGmkyLxg+FtMJpOHcfKHxN3dHSH08uXLZ8+e/fHHH/Pnzxd0nCRkfiXSfQQAACDKCKz7ysrKCxYswJ9xoruOsNlsMrUkmScPT7dxvqTPsmbNGpwM8tdff8W5JwUdJwmZzL0nDw0AAABfDd3R04CAAAUFBYTQr7/+Wl5ezrU3OTn5119/nTBhAs6qiPOstra21tXVIYRmz57NzyGkpKScnZ0RQleuXOmYCRbnL0McKW27IicnBxeiGjNmDE5TDgCcPH36dOPGjeQLJy6qq6u1tbV5Z4gUlKysLDLNZw/x9fWNjo7uFVNfFi9fvpw/f768vLympqaTk5OWllZv3aPCwsK9e/fS6fTi4uJeMTgw6Y7ujx079saNGzo6OrW1tebm5vHx8e/fv29ubs7Jydm6daufn9/q1avFxcWPHTuGEEpISHj//n1oaChBEOPGjXNycmKz2aSDqLi4uL29ndwsKioij7J582ZxcfGVK1fiuhMkHz58wJlqEEI3btwgvfb5+fnkz0B+fn51dfXVq1ctLS3ZbPb48eNv3rzJmVUYABBCbDbbysqKwWDU19d31YcgCEHrzPDgt99+W758+ebNm8mW/fv3k4HLNBqNdIQymcwVK1YoKCgMGTKkq8otdnZ2wcHBZMSaiFBWVmZmZubu7v727du1a9dGRERUVlb21j3aunXrzz//zFnt4LO8e/cuNDR05syZbm5unXaoq6sLCAiYNGmSnJxcp2WOutGzp3AG9wiUp6Guri44OPj777/HtXVUVFRmzpwZGRnJmXAjNjbW0NBQUlJSTU3N0dGxsrKSIIjLly9zDgCnFyZhsVjk11euXJmVlcV50E7/xOvr6zvmaRATE8PFcc6fP89pU2hAHGc/ggSJ41ywYAFnne6+Iz09XVlZOS8vj2ypq6vDJcYwZCaiurq6kSNHLlmypKqqKiMjQ1lZ2d/fv1ObuKegeaq/aPz8/OTl5fvOPl552lVmKjabnZSUZGNjk5CQgFvWrVs3fvx4hFCn1dIfP36so6MzatSo06dPFxQU8NCijj3d3d137tz5999/9/CMIA+z8ADd70cE0n1HR0ch6D6LxRo1apSPjw9no7+/f3x8fMfOO3bsoNFoHz58wJs+Pj40Gq0rJXr06BGVSn3x4kVvD3mA4uLi0qf3Cz9ddbzalZWV/v7+w4cPnzZtGi6zTu5qa2uTlJTsqPupqanS0tLW1tbNzc28D9ppz9LSUh8fH11d3VmzZsXGxra2tnbvjED3hQfofj8ikO5v2LBBVVX1+fPn5ubmUlJSBgYGOAFGU1NTVFSUubm5l5cX7llSUmJtba2mpiYjI2NiYkI+jObn55uZmSkqKu7cuTMiIgIX/eACL1188+YN2dLU1KShoTFkyJANGzZwPte2t7draGiYmpqSLTj98oEDB7o6BSMjo+XLl+PPL1++VFVVPXz4MJ+n/wWRlJTE9Vifn5/PeY84n/tTUlLInDHnzp3DFsgaKSNHjuT8xX306NH06dOlpaUNDQ1xdRRS99lsdnJysq2trZqamqura25ubqdjU1RU5NL99+/fq6qqzp49+7P+Bt4929rarl27tmDBAjqdvmvXrm5M/0H3hQfofj8iqO5LSUn5+/tXVFRkZ2ePGzdOVla2tLQ0KioKO2HI3HATJ060sLCoqKjIz8/X1taeOnUq2R4XF/fp06f79++rqqp2qvvm5uZ4RTrJL7/8QooUhUIhs9i+fPkSIbRq1SqyJw6O4JGP2sPDg0aj4fpQL168UFZWPnToEJ+n/8WBf6fxZ657VFVVhXMBzJ07l81m19XVaWhokDPliIgIMzOzgoICXI6RSqVmZmYSBJGRkSElJXX06NGamprY2Fi84qeoqIjJZAYEBIwYMcLY2DgsLKyhoYHHqDrqPg5G9/X1NTY2lpSU1NfXxzW/OsJnzzdv3uzfv19bW9vCwiIuLo7/6X9HLRLv1OkP9AoZGRndKEsNCB9ZWdldu3YhhLS0tC5evGhkZBQYGHjy5MmZM2dyRh7j98BaWlpaWlqzZs3C6eo+ffr07NmzoUOHSklJzZgxo9O8hC0tLenp6Vy1Kl1dXa2trXNycmJiYi5evOjr60un07ds2fLu3TuEkIaGBtkTS1tlZWVX49fT02OxWPfu3bOystLX16+uru7pFflCsLe357xHKioqAQEBZWVluMrxjRs3GAwGvuxtbW1eXl6pqam4km1QUFBCQkJgYODly5ddXFy+++47T09PhJCNjc3du3fPnDmDENq6devvv/8eGhrKWUiHT9hs9uXLl+l0+qhRo1JSUv7+++9ly5YtWrTo5cuXuDJSN3rq6OgcOHDAy8vLycnJxsYmLi7O2tq6e9cNkl4BwP9gYGCgo6OTk5ODECKXoWAyMzM3b9785MkTOzu7mJgYHE8sLS09aNCg77//fvfu3WVlZVu3buWsC48pLi5msVh4SQoJjUaj0+mWlpaRkZEpKSkKCgpHjx5F/650kZGRIXviQDUJCYmuxkyn0xFCuCqyqMF1jxBCYWFh48ePt7Ky0tDQIH9rc3NzmUzmmDFjyGL3CKG8vLycnJycnJw5c+aQXzc0NMQfgoKCDhw44OfnN336dOzQ539UFRUV79+//+6775YvXy4vL29kZHTs2LHm5mbOhzxBexYVFe3Zs2fYsGGVlZWxsbFkMeFuILrz/cLCQgaDce7cucePHw8dOrQvDjF16tS4uLi+sAzwpodRferq6rW1tQghrgWDZWVlTk5OFRUVnp6e4uLiv//+O26PjY1dtWqVv7//sWPHPD09Dx06xPVFnImWRySxqampj4/Pjz/+yGKx8M8GmQULIVRTU4MQ6vhzQiIrK8v1FdGh46JOGRmZffv22drapqWleXp64j8GvG6/tLSUs4onQujKlSuosx8PhJCGhsauXbt27tx59+7dsLCwnTt3rly50sXFZezYsZ8dFY4MxvU/MIsWLRITE8vPzxe0Z3t7+40bN06fPp2dne3g4JCWlsb1HNANvs75/mcjapGAgbr8GAS+GsrLy7E3gJOGhgb88jYzM3PNmjVkAhKEkKmpaUFBwYkTJ1RVVX19fU+ePMn1XbwGpbGxkcdBTU1NcUj0uHHjFBQUCgoKyF04pSCPTNfNzc0IITk5OX7P8KumtLQ0OjqawWBcv37d398fN+L8YDjVIyf4KQonE+sUCoViYWERGxubm5uLQ8PNzMyio6PxNe+KwYMHi4uLcy5IotFoioqKHX+8efQsKys7cODAN998ExQU5Ojo+ObNm4CAgJ6LPvpadX/37t2nT59OSUkhs0R0JDExcffu3b1oEPg6yMjIqKiowEXqsScH3/SHDx8WFRWtX7+eTCNIEARCqLm5+fDhw1JSUtu2bfvrr7/GjBmDq1NwQqfTJSUleU8y0tPTcbl5CQkJPK3DzxwIoTt37khLS/N4V4Rf/I4aNaq7J/0l0dra2tLSQm5y3iOEUENDg7Ozc0hIyPr1652cnLy9vXE6GUNDQ0VFxd27dx89erS8vPzjx48PHjzYsWPHlClTqFTqpUuXuLJMknm9SDQ1Nb28vAoKCvbv35+QkHDnzh0eg5SXl7e0tExNTSUzGlRUVFRXV3d0zvDoGRAQ0NjYeO/evbt379ra2tJoNEGvVZdwvuT9muJ5uoqo5aSrQN1uG+QE4nn6ESRIPI+3tzcOp6moqMjNzdXT09uwYQPedePGDYSQiYlJU1NTdnY2QsjBwaG2tjY2NlZfX19cXDwvL+/WrVsSEhKnT5+ura198+aNnp5eSEhIx6PMmTNnyJAh5CaLxdqyZQuDwWhubq6urg4LC3N0dGSz2Xjvhw8fdHR01q1bV1dXl5SUpKCgcOzYMbwLJzbHkaYknp6eVCoVxxHl5OQoKyv7+voKdsm+EEpLS7FX9t69e7iF8x4xmcyZM2ceP36c7CwuLq6srHz37t329vYTJ05wSp+4uDiue46XT69Zs+bNmzf//PMP9vUrKSl1tVaOCzabXVZWJiEhsWjRIs6g/vz8fBUVFTMzs5KSkrdv386ZM2f27Nl4F9dN5NGzV+i1OM6cnJyFCxfKy8sPGTLk0qVL8+fP50c9b968OXnyZCkpqaFDh/7yyy9k+/37983NzWVkZDQ1NTdt2lRTU0MQxOvXrz09PTU0NMrLy/fu3auqqjpo0KDY2FiCIEaPHk3evFevXhEEERgYiDfj4uJIsx0jqwiegbqfpVODXQG6348IpPtsNjs8PHzs2LESEhJ6enqhoaFYf//zn/+Qf2YGBgYEQezcuVNBQUFfX//q1asXLlyQlZX94YcfGhsbT506dfDgQQ0NjcGDBx86dIiUb04uXLiA/jcq3M7OTk5OTl5efvr06ZcuXeLqX1hYOG/ePBkZGT09vcjISLLd1NRUV1eXK6ZzwoQJZEt2draSktJXqftcD1LDhw/nukfkbBr/BOKCThgcGRkWFjZ8+HBpaelJkyYlJydjs21tbXv27FFXV5eTk7O3t/fz8zM0NAwJCcFxsZ8FywgJZzGovLy8OXPmyMnJaWpqbtu2jYwE7XgTu+rZK/SO7j9+/FhRUfHkyZM1NTXPnz8fNmwYP+p5+fLlQYMGPXjwoKmpCadbuHz5MkEQd+7ckZeXv379en19fUxMDK7Ty2KxTE1N8QO1u7t7VlZWbW2tmZmZkpISi8ViMpnfffcdQuj69evYOJvNdnNzCw8P5/yX6yjTXQXqfvaUuzLIA9D9fkQg3RcO7e3tY8eO9fT07LmphoYGzj+t7OxsKpX69OnTnlsGhAbXTexTekH329vb9fT0nJycyBb85oS3ejY3N6urq585cwZvvnjxQkVF5ezZs2w2e+TIkW5ubmRPHP6M87jhH9K3b9/iXTjRGy6++OLFC4RQeHg4+cV169ZxHbSjTBsYGMybN4/cdHFxAd3/KhmAuk8QRFZWloKCQnp6eg/t+Pn5paWl4c/Nzc3Tp08nV5YBXwqcN7Gv6YU6i1lZWa9fv+ZcgYJflPPm6dOn79+/NzY2xpv6+vpVVVUbNmzIzMwsKCgwMDAge+L0y4mJiejfpStk4ASOaMavcfT19WfNmkVWZMzKysJF2HnAI1AXAISAkZFRdHS0tbU1XvDVPYKCgkxMTKZPn44QKisrW7hw4YgRI3x9fXtvmECfw3kT+wWBdR+HlPEIJe4UnF224ytynIEZl1fE0Ol0GRkZ/Gqbd7mVbdu2ZWZmYpff5cuX7ezseI/h1atXqItAXQAQDosWLbp169a5c+e6bcHd3Z0M6IyIiLC1tY2MjOxJYSJA+HDexH5B4HVbeHbPY8l4p+D45QsXLsybN4+zHa+hwIr8/8ckLo7fGfBmwYIFI0eOPHXq1NixY6WlpfHSFR58NlAXAITA+PHje2s1n7e3d6/YAUQNgacJ+vr6VCo1ISFBoG9NmjRJVlb28uXLP/30U2VlZX19fWJi4sGDB42MjHR0dK5cuYIXNCKESktL6+rqVqxYgf5djUJWU8EBtmSgLoVCcXd3j4+PP3bs2Lp16z47Bv4DdQEAAL5iBNZ9HR0dR0fH8+fPHz9+vLq6+vnz59euXfvst+Tk5Ly9vQmCOHjwoJaWloKCwurVq62trSUlJX/++efa2to1a9aUl5dXVFS4urrOnTvX2tq6paUlLS0NIZSSkkIQBIvFwmW2cNwuNrtu3ToZGZns7Gyu5wOCIMrLyz99+lReXk4uqxs8ePCmTZvy8vIcHBzevn1bWFiIg8DmzJkTEBDAe/ydGgQAAPgi4XzJy2ccZ1NT0/r162VlZbW1tQMDA0NDQxF/UTEnT57U0dGRk5ObPXs2Z8Lx+Ph4AwMDSUlJXV3dPXv24MoDnKm0AwMDp0yZQm4GBweT392+ffvt27e5DtRVRG23A3V5hOh2BcTz9CNoQMbzAEC/0FGLKMS/c2eEUGxs7IoVKzhb+OH06dOurq5FRUV9lN3sCwWvqv/68rJlZWUdOnSIc72MEPD19dXV1f3sq3sSCoUSExNja2vbp6MCgC+CjlrUC2EAOLCS9MIDwuHUqVNk/hahGeEqC96TdHUC1RMXzQLiANBH9FT3WSwW9sInJydzvS8F+o7GxkauZCNCMJKRkbFx48bExMTZs2fjlm6nq6uvrw8ODiY358yZg9dq1NfXm5qatrS0FBcXx8bGent741cvurq6ycnJSUlJEKgOAD2np7pvZmaGU5tu2rRJTEyM0gXdrgsjBF6/ft3VsAfsyDdv3tzzIhsCGWlra1u7dq2Hhwdn8vFz5849f/6cR1r5rggNDT179izpbcTL9BBCBw8eLC4uZjAYKioqU6ZM8fDw8Pb2Li4uRgjJy8tHRkZ6e3vjMoQAAHSbnup+RkYGPy8W4uPje2W4fYGenl7/jjw1NXXGjBmysrJaWlqurq7Y8SIuLo5/eMhB4k2cZjYqKgohpKysTKFQHjx44Obmpquri1dvysrKGhoapqamCmSkoaEhLy9PTU3tyJEjnQ4yKioqPz+/Y8E5MTExzkz0/PDp06fjx49v377dycnp+fPnZDubzY6KipoyZYqqqipumTdvHovFwuNECJmYmBgYGPj4+Ah0OAAAuIBlfv1MUlLSokWLPD09Kysrg4KCLly4MHv27La2tg8fPowZM4bs9vjxYzKiKSwszM/PDyGEE5euXLkyJCSEyWSeOXPm9OnTz549Y7FYc+fOff36Nf9G5OTkCILAWe06Hef58+dHjRqlo6PT81MODw9nMpklJSUMBsPY2Hjv3r24/dWrV0wmk/MQuPjJkydPyBZzc/Nr1659/Pix58P4gsjKyrKyshLyQX19faOjo4V8UD55+fLl/Pnz5eXlNTU1nZyctLS08B9zzyksLNy7dy+dTsdPmV8roPv9CUEQW7ZsWbt27cKFC+Xk5GxtbXfs2PHs2bPw8HAlJSULCwuyp4qKCucmJ+Xl5ZaWlv+PvTsPaOJoHwc+CUGOcN8iooJYDxSoB4iIVVDBelRBUAFPBA8UrIJ4oHjU+yqHVSBokaog2nr/XoUiSgttBZFqtVgFFFBQDiEgEJL9/TFv95s3QEggB7DP5y8ymczObsKT4pbwbwAAIABJREFUzezsPHQ6fefOnSYmJsOGDYuKimpqaoqIiBC9EYQQzse9ffv21k/htOAjRozowr7+n9WrV5eWlt66dWvJkiUKCgr79u3D129FySdOJhCXSE+6SDaX1uFauoDS0tKJEyeuX7/+zZs3S5YsiY+PLy8v72JmTZJYafiwDt+R2tragwcPjh07Vk1Nrc3/r07U7CKI+/IkfFk6gTzaQoZTTExM6HQ6mQdq8uTJGhoaDx8+FKsRIdpMC95pXckn3n0SiMvm0jpcS2/t3LlzXC7XxcVFS0vr0KFD+EdqaGioRBrvMA0fQRCpqakeHh7k/arC35GsrCxLS8v4+HhfX9+8vDwho5StawYGBm7evPnly5dd26c2QNyXJ+HL0omu9bJcJiYmOIxKRIdpwTsN5xN//fq1iPnEu08CcRlcWodr6W0qKioSOJuRLP5fnPwqKioOHjxoYWGxY8eOmTNnkiv7CnlH7t+/7+TkZGtrm5+f7+/vP3jwYAaj7SXR2qwZEhKiqqo6ZcoUZ2fnS5cu4RnzEgFxX566siydAIFx+aqqqgEDBnSxeyRR0oJ3mlj5xKWUQLybXFoX6FU3vJYu/OK/tKWmptJotNOnT1dWVuLD+OLFi3Pnzk2aNAmfpH/xxRfkQNa9e/fCw8Px32fPnsUtJCcn46UBhgwZcvnyZbLlX3/91cHBQVVV1cbGRuCbmCCItLQ0T0/PESNGFBcX//jjj7/++uvixYv534I235EPHz7MmzfPwcHhwoULwr+n26vZr1+/nTt3vnr1KjAw8Pvvvx84cGBoaKhETv8h7suT8GXpcBpl8qlPnz6hf1eRw3GEP9Y3NjbiCgihZ8+elZeX45xzYjXSHlHSgneaWPnEpZFAvPtcWhfoWDe8li784r+0OTs7EwSxYsUKXV1d/KslOzt7/fr19+/fx126cuVKSEgIQmj69OmTJk3auHGjgYFBcnKyl5cXQujMmTNRUVGXL18uLS0dPny4h4dHbm4u3lknJ6c5c+aUlZVt3boVLzyDEHr//v2hQ4eGDBmyefNmZ2fnoqKikydPjhw5UsTe7tmzp7KycvLkyXZ2dsrKyiNHjsQZ3sWtqaCgMGvWrBs3bmRnZyspKX3xxRdTp05NSUnp0uk//5zF3pRXXe5EXJ8HH/PZs2eXlpaWlZXNnDlz+vTp+F8rNjYWIXTixAk2mx0XFzd58mSEEM5Tdvr0aYTQ3bt3Y2NjS0pK/P39aTSan59fZWXlq1evJkyYMG7cuObmZrEaEZ6PWyAtONZeRuk2c39jnc4njvEnEBcCibw+j/CMb+vWreP/j8Dhsq6ujiAI/pBNEISrq6uKikpLSwt+iK88r169WqxG+DU2NioqKs6dO7fNbouV+o0giObmZvJaOh5qiIqKIggCx5fAwECyJh6kHj16NFny3XffIYSuXLki+uakij/uEwRRUlKCEOLPOObl5UWj0dLT0zdu3EimYuVwOAYGBjgdN0EQeIh1wYIFRPtp+Dw9PZWUlFgslii9EnhHuFyuvr6+sbFxSkpKbW1tbm7uwIEDlZWV//nnH4EXil4Ta2hoWLRoEfrfXOLCSSDfFpAsDw+PlJSU4uJiMzMzOzu7UaNGXb16FZ+Je3l5zZs3LzQ01NbW1tzc3MnJyc7O7vDhwwsWLHB3d7e3t1+0aBGTycSDRaqqqlZWVhYWFtbW1mZmZrdv38Zn+qI3gj8Q7fXTx8enuLhYYHJbcHBwv379mpubr1+/rqKikpeXh8urq6uVlZXbnFqnoKDw8ePHwMBAfX39WbNmqampxcfHk8Mgurq6GRkZ7969MzIyWrduXUREBP4pQEpLS3NxcRE37Y8Q3fbSOlxLF1HrTEoxMTEjR46cO3eugYEBmRkwPz+/oqJi2LBheOQHj4I+ffpUSBq+iIiIXbt27d+/f8KECd9//z35e1oUb9++ff/+/RdffOHm5qaurm5jY3P06NHGxsZvv/220zULCwu3bt1qZmZWXl6enJxMJpHvBLHzrgCJc3Nzc3Nza12uoqLCPwT5xRdfkD/PmUzmL7/8IlB/zZo15Gy/TjRiZWWFr6O2adGiRfv37z958iSOF9iRI0eOHDnSuvKDBw/q6+vbTIpAo9HOnTvX3lYQQoMGDbp9+3abTz1+/DgvLy87O1vIy8XVbS+tS/ta+tdff93jrqW3qfWRV1VV3b59u4eHR2ZmZnBwMD6rwGObJSUl+DyJdPHiRdROGj4DA4PNmzeHhISkpaXFxMSEhIQsWLDA39+f/zJ7e+rq6hBC6urqZMmsWbMUFBQKCgrErcnlcm/cuHHq1Km8vDw8EGpubt5hB4SD8/3egMvlSntdPDqdnpiYePr0aRHDbmRkZFBQkAQ70NTUtHbt2uDg4LFjx0qw2W57ab3XX0uXnpKSksTERBaLdf369QMHDuBCnCgQLyrDr8M0fDQazdnZOTk5OT8/v2/fvrNnz544cWJiYqLwPBz9+vVjMBiFhYVkiaKioqamZuufqkJqlpaW7tq1a9CgQREREcuWLXv9+vXBgwe7HvQRxP1e4OPHjzk5OY2NjXg8XXobEj0tuMTTRksvgXi3vbTeu6+ld0Vzc3NTUxP5EF/eJOfO44lS0dHRy5cv9/X1DQsLw9cwrK2tNTU1t2zZcujQobKyso8fP96/f3/Tpk2ip+EzNDQMDQ198eLFjh07rl69eufOHSGdVFdXd3V1zcjIIH84vn37tqqqqvXgjJCaBw8erK+v//nnn9PS0jw8PPAHSTL4B/vhuq4EySbvisDITGxsrLS3mJ+fL/t8Mrt3746JiRG9PhIn70r3ubQu0LFueC1d+MV/GSgpKcF5PnDePYIgbty4gRCyt7dvaGioqKiYMmXKsWPHyMoMBkNbWzstLY3L5QrcIsdgMDIyMgiCwKOjXl5er1+/fvnyJR7r19LSOnDggChdau8dKSgo0NHRmThxYnFx8Zs3b6ZNmzZ16lT8lMCbJaSmRLSORRD3pQXybcmRWHGfaCfjG0EQDQ0N8+bNU1ZWHjFiRHp6+t69e+3s7FgsFpvNrqystLe319fXP3/+PEEQ/v7+TCYzOjpaR0dHQ0PDx8ensrJS3EYE4AshApns2kv95uDgYGpqOmPGjNbt8Hg8b29vNTU1dXX1CRMmtN7Wq1evXFxcVFVVhw4devbsWYFnP//8c7LZvLw8LS0tecX9rKws/n03Nzfnz/9jZWVFnk3jbyknJyfy2bt37xIEERMTY25urqKiMnbs2NTUVNxsp9PwYUKS8T19+nTatGlqamqGhoZBQUFsNhuXt36z2qspERD3ZQfivhyJG/e7Dsd9ybbJ5XKHDx8eHBwsYn02my3xj1xeXh6dTv/9998l2yyQxpvVHpjHCYBUSOPSem+9lg6QFN4ssUDcB6CrpHdpvVdeSwcSf7PEBfP3AeiSmpoabW1t/Lejo2NsbKyvr68E2581a9bAgQN37949Y8YMIdXWr18vwY0ihOLj4z08PFauXCnZZgGSwpslLoj7AHSJlpaWZM/xWxs5cuSlS5ekuonWwsLCZLxFIDMwzgMAANQCcR8AAKgF4j4AAFALxH0AAKAWiPsAAEAtEPcBAIBa2pjHyb8UH+g0fI8lHEx5OX78uOznPgLQDWVnZ9vZ2fGX0PinHmdlZR07dkzmvQJADtLS0iwtLQ0NDeXdEQCkbvz48fyp62jSvuUEgO6JRqMlJSV5eHjIuyMAyBqM7wMAALVA3AcAAGqBuA8AANQCcR8AAKgF4j4AAFALxH0AAKAWiPsAAEAtEPcBAIBaIO4DAAC1QNwHAABqgbgPAADUAnEfAACoBeI+AABQC8R9AACgFoj7AABALRD3AQCAWiDuAwAAtUDcBwAAaoG4DwAA1AJxHwAAqAXiPgAAUAvEfQAAoBaI+wAAQC0Q9wEAgFog7gMAALVA3AcAAGqBuA8AANQCcR8AAKgF4j4AAFALxH0AAKAWiPsAAEAtEPcBAIBaIO4DAAC10AiCkHcfAJAFHx+fvLw88mFRUZG+vj6TycQPFRUVb9y4YWxsLKfeASA7DHl3AAAZGTp0aGJiIn8Jm80m/x42bBgEfUARMM4DqGLhwoU0Gq3NpxQVFZcuXSrb7gAgNzDOAyhk9OjRjx49av2Zp9For169GjhwoDw6BYCswfk+oJDFixcrKCgIFNJoNFtbWwj6gDog7gMKWbhwIY/HEyhUUFBYvHixXPoDgFxA3AcUYmBg4OjoKHDKTxCEm5ubvLoEgOxB3AfU4uPjw/9QQUHBycnJwMBAXv0BQPYg7gNqcXd3p9P/72NPEIS3t7cc+wOA7EHcB9SioaHh6urKYPz3zhUGgzFnzhz5dgkAGYO4DyjH29uby+UihBgMxuzZszU0NOTdIwBkCuI+oJxZs2apqqoihLhcrpeXl7y7A4CsQdwHlKOsrDxv3jyEEJPJdHFxkXd3AJC1jtfnycrKevPmjQy6AoDMmJiYIITGjBlz7do1efcFAAnz8PDooAbREXd3d5l0FQAAgAR0GNVFWo/T3d390qVL0u4raE9ycrKnpyespCRZe/bs2bp1a+tlGwTMnz8fIQSff9Aj4FjRYTUY3wcUtWXLlg6DPgC9EsR9QFHkFH4AqAbiPgAAUAvEfQAAoBaI+wAAQC0Q9wEAgFog7vdOVVVVJiYm+/fvl3dH/kdubu7cuXNlvNF9+/YJpFMHgOIg7vdaBEG0l0ZcIqKiompqakSvf/nyZTc3tzVr1uCH7969O3ny5JQpUwICAsTd9I4dO2j/UlRUrKiowOUVFRWenp4aGhoDBgyIjo7Ghd7e3pGRkWvXrhV3KwD0VjCVrXfS0dEpLS2VXvv19fXHjx8XfeX67OzslStXZmZmDh8+HJds2bIlJyfnzz//HDJkiFibrquri4yMJB9OmzYNZ02pq6tzcHAYPnx4UVHRixcvXF1d2Wz25s2bTU1NU1NTR48evW/fvq1bt4q1LQB6JTjfB52xZs2aV69eiVi5paVlyZIlgYGBZNBHCJ05c+bRo0dKSkribvrkyZNxcXHkHec3b97E5bt37y4qKmKxWDo6Ora2toGBgWFhYUVFRQghdXX1s2fPhoWFPXnyRNzNAdD7QNzvhT59+nTu3LlJkyZt2bIFIfT333+HhIQYGhq+fft2+/btenp6xsbGeOGB3NzcgIAAU1PT0tLSmTNnMplMa2vrjIwMhBCDwcADKbjNoUOH4odsNtvPzy8hIQEhpK2tjUuePn2qp6f3zTfftNmfhISEgoKC5cuXC5QrKCgoKyuLu2vHjh3buHGjr6/vo0ePyHIej5eQkGBra6urq4tLXFxcOBwO7idCyN7e3srKKjw8XKzNAdArQdzvhVJSUtavX3///n28pI+vr++xY8cqKioOHDjg5ub28uXLwYMH+/n5tbS0zJw5Mzo6uqKi4vTp06dOnXr48CGHw5k+ffrz588/fPgwbNgwss1ff/3V1tYW/x0TE4OvGFdXVxMEoaamRhAEj8drbwWh77//fsiQIf379+/6rsXGxlZUVBQXF7NYrNGjR2/btg2XP3v2rKKign8TgwcPRgj99ttvZImjo+O1a9c+fvzY9W4A0KNJK+7HxcXdv39f3FetWrXqw4cP+O9Tp06pq6uPGzeOzWZ3sTNSarbb8vHx4R/QePDgQVBQEEIoODjYxsZGU1Pzq6++qqmpKS8vLysrc3V1pdPpO3fuNDExGTZsWFRUVFNTU0REhJaWlrOzM9mIjo4O/0MBlpaWVVVV27dvb/1UU1NTVlbWiBEjJLJrq1evLi0tvXXr1pIlSxQUFPbt24ev37579w4hxJ8eXUtLCyFUXl5OlgwdOpTD4fz8888S6QkAPZdU4j6Pxzt8+PDhw4fFetXVq1dPnz7N3whBEDgfXldIqdluTl9fn/8hDojkoArONsXhcBBCJiYmdDqdXKFs8uTJGhoaDx8+RAj16dOHvxFxx2SwoqIiDoejp6fXide2pqioaGxs7Orqevbs2fT0dA0NjUOHDiGEmpub0b/7heG3mH8XjI2NEUKiX5YAoLeSStz/6aefCgoKbt68+ezZMxFfcv/+fR8fH/6SNWvWsNnsnJwcNTW1TvdESs12f3Q6XchD4U+ZmJjgMCoR+HdVJ67fdsjBwSE8PPz169ccDsfIyAghVFlZST5bXV2NEMLlGJPJFKgDADVJJe7jC4MEQbR5yp+RkeHg4KCqqmpoaOjr61tXV/fDDz9MnTq1rq4OIaSvr0+j0b744gtygnZjY6OlpSX50M7ODiEUHh6OH6akpCCEEhMTHRwc1NTUtLS03Nzc8K/+DpvF/bl27dro0aNVVFRMTEy+/vprHKcuXrxI1jx58qSzs7OmpuZnn32WmZkpjSMmXwLj8lVVVQMGDJBU4zo6Ogih+vp6STXIz8HBwdjYWFFRccSIERoaGi9evCCf+ueffxBCjo6OZAl+x3v39z0AopB83E9PT/fy8hozZgxC6IcffigrK+N/NjMzc+rUqQwGo7i4WEtLi8Vibdq0ycvLKzg4GFd4//49QRB37tyZMWMG+arr169bWFjgvy9fvowQCgsLmzNnzunTp+fOnbtnzx4fH5+DBw++evXK1NT0ypUrOFdGh80ihH766aevvvqqvr6+uLh49+7dx48fnzRpEofD8fDwCAkJwXXu37+fmJg4duzYgoKCFStWSPyISQMew2lpacEPccgjR7d4PJ7As58+fcJ/P3v2rLy8fM6cOQghRUVF9O8JO0II13n//j1CCM/zESUVjLGxsZKS0tu3byW0Z/8jKyvr66+/Rgj16dNn8eLFmZmZ5K1kd+7cUVFRwZ8EDF/jEfd2AQB6H8nH/bt3744bN27lypUIoebm5oiICP5nN23axOFwfH199fX1AwICVFRU+H+Jk/r06TNo0CDy4aBBg06dOoX/Tk5ORghxuVxtbW0/Pz8FBYWoqCiEUGZmpoGBwYQJExBCWVlZbfZNoFkulxsYGEgQxKxZswwMDBYvXqyoqJibm8tiseh0OlkzNDTUyMjIxsYGIVRQUED+UOjO8NXLrKysT58+NTU14Z8p6enpBEFwOJx79+7hOjhwEwQRFBRUVVVVWFi4cuXKsWPH4sExc3NzhBCLxaqvr2exWPiojhkzhsViaWtrI4RycnLi4uJKS0vz8/N1dHTaXBZCSUlp0qRJrUf8CIIoKyv79OlTWVkZ/yGdPXu2oaFhm7+rWlpaAgIC4uPjm5qaqqurY2Nj8/LycNxHCIWHhxsZGW3YsKGuri41NfXEiRN79+7t168f+fKnT5/S6XQHB4fOH1YAegUJx/28vDwcLBYtWoR/UJ86dQqPtCCE3rx5g+fV4Sts69ata2ho2LVrlygtT5kyZdSoUQih+Ph4hND/+3//z83NDT81b948JpPZr18/giDwLD0ulyvKldvHjx+/fv0aIdS3b1+EEIPB0NTURAhdv369dWXyymdDQ4MoHZajn376aebMmQihX3/9dfz48dOnT//Pf/6DEFq4cOHRo0cnTpyIJ+/7+/vjyTCqqqpWVlYWFhbW1tZmZma3b9/GZ/peXl7z5s0LDQ21tbU1Nzd3cnKys7M7fPjwggUL3N3d7e3tFy1aRB55Ief+Pj4+xcXF+BYqUnBwcL9+/Zqbm69fv66iopKXl4fLq6urlZWV2/wKUVBQ+PjxY2BgoL6+/qxZs9TU1OLj48k7DHR1dTMyMt69e2dkZLRu3bqIiAjyKwFLS0tzcXFp8zwDAGoRJa+6u7t7h9Uwf39/NpuN//b19cWbOHLkCC7Bp5kIoatXrwq8kJyIjQdkCIIgF1T59OkTLomLi8Mlf/zxx/bt27lcLvlyLpf7/fff29nZff7557gOh8PpsNkbN27gv6Ojo/GzeBrMmDFjCIL47rvv8LOPHj0iCGLz5s0CTclMUlKSKO9U5/j7+zOZTCk1jnG53OHDhwcHB4tYn81mi/6RE1FeXh6dTv/999/FfaFYn38A5EvEWCHJ8/3CwsK4uDg1NTV8OZQM0ydOnMDDzeQltZycnE607+XlhacDfvfdd3j2IS5/8eLFmDFjgoKC4uPjx48fL3qD5GRHcqQbz2MxMTHpRPd6KBF/G3UFnU5PTEw8ffp0dna2KPUjIyPxDQeS0tTUtHbt2uDg4LFjx0qwWQB6KEnG/W+++SYzM5P8SuFyuSNHjkQIlZSUXLhwASE0atQoPJH83LlzZKhtampCfKMoQigrK/v5+SGELl68SF6vIwhi5syZjx49CgoK4r+/FBPe7Oeff45/9eMrfs3NzbW1tQihqVOnirXjPdfHjx9zcnIaGxsfPHhAiHCRttNsbGwSExPd3d1v3bolvGZERIS9vT2+TiMReAmKwYMH79u3T1JtAtCjSSbuv337dtu2bdnZ2fy3ZdLp9LCwMPz3+vXrb9++TafT8bhtYWGhn59fVVVVfn4+vu9m4MCBuOZff/115MgRNptNDgcXFBSQba5Zs4bBYCxYsADPDkQIvX//Hld48+ZNUVHRtWvXcDke6BfeLIPBOHr0KELo6tWr79+/P3nyJEEQI0aM8PX15fF4xcXFuGZRURGXyyUfFhYWSuSgyV1NTY2WlhZe5cbR0ZHFYkl1c7Nmzbp9+/aZM2eEV1u/fj3/5Muui4+P9/DwOHv2rJCbGKijN6VAePLkyYwZM9TV1fGMcCMjI0klnHj16tW2bduMjY0FLkr1Hh2OBIkyvvnZZ5+RDV66dAkXtl7xfNu2bQRBnD179rPPPuvTpw8+BcMD8c3NzcuWLVNVVR06dOj9+/cFpkvyD6kvWLAgNzeXf+urVq1iMpmWlpYHDhxITk7W19fX19cPDAzkcDiiNJucnGxtba2kpKSnp7ds2bLy8nKCIPAPFBI51o/hPsuMVMf3gXCyGd+PjIzEix1JtZGUlJSBAwfeuXMHP3z79m10dPTkyZPXrl0r7rbIUzqEEIPBwP81BEGUl5d7eHioq6ubmppGRUXhwuLi4nHjxq1Zs0bcrQhRUlKipaV1+/bt6urq4OBgfHl///79Eml8xowZ+E7vwsJCEV/yww8/2NjYMJlMIyMjLy+v169ft1ezzUMkKSLGCglf1wXSAHFfjmTw+Wez2WZmZl2M+x02kpWVpa2t/fTpU7Jk6dKleCTW399frG3V1tbi5Y+wGTNmkOUWFhZz5syprKzMzs7W1tY+cOAA/1PffPON+HvWtv3796urq0uqtdZ27twpJO7zeLy7d+/Onz8fT1G5ePGitrb2zZs3Gxoa3rx5M3/+/M8++wwvCSOgvUO0fv36kJCQf/75p4vdhrjfe0DclyMZfP4XL16M/l3cVEqNcDicIUOGhIeHC5S3tLQoKSmJG/cPHDiQkpLSunzTpk2KioofPnzAD8PDwxUVFcnQ+csvv9Dp9D///FOsbbXH399fV1dXIk21CU9xbh33y8vLDxw4YG5uPn78+O+//x7PNly4cOGUKVPIOpmZmTQaraampnWz7R2ikpKS8PBwU1NTJyen5OTk5ubmznUb4n7vAXFfjsT9/N+7d8/R0REvQ7Jq1SociMn5BbgOOS5aV1eH73AkZWRkrF27tn///iUlJV9++SW+teLevXtiNVJXVyfQK3zxps3BB01NTbHifkNDg4GBwYABA1asWME/4srlcg0MDBwcHMgSPH1r165dZImNjY2bmxv++8mTJ7q6unv37m1zK0J29u7duwIDyAUFBQkJCY6OjqGhoQRBTJo0iXwqPT0dn7kjhM6cOYNbS0pKGjVqVJ8+fSwsLPi/wH755ZcJEyaoqKhYW1tv3LiRP+7zeLzU1FQPDw89Pb3Vq1fn5+fz9/bw4cM0Gm3v3r0tLS08Hm/p0qW4JwI6PEQtLS3Xrl378ssvjY2NN2/e3InTf4j7vQfEfTkS6/N/584ddXX169ev19XVJSUlMZnMMWPGcDic6upqPNkMV6usrMTJDHCA5k9mgG8hVFJSCgsLe/PmzV9//TV8+HAlJaVnz56J3khrjo6OQ4YMafMpceP+t99+S0ZVGo22detWXI6X/l64cCFZE0+TI0eBCIIIDAxUVFTEJ8J//vmntrb2nj172tyK8J0lCGLFihXk+X5CQgIed9q8eTOujBdZmT59Oo/Hq62tNTAwIE+i4+PjJ06c+OLFi/fv38+ZM4dOp+fk5BAEkZ2draysfOjQoerq6uTkZBUVFRz3KyoqDh48OHjw4NGjR8fExJD3J/Frbm729PRECFlaWi5YsCA5ObnNnRLlEGGvX7/esWOHiYmJs7PzpUuXRD/9FzFWQH7dHoN/qRkgM9nZ2XgpwA4RBLF27dolS5bgm6U9PDz++uuvXbt2xcbGrl692tnZmVysAicz4M8JQyorK5sxY8a9e/d27tyJz3mjoqKmTJkSERGB1wcUpREBOAUC7lXXrV692t3d/fHjx0lJST/88MO+ffuMjY3Xrl0rVgqEuXPn4pwN7W0Fp38QcWd9fHymTJlC3najo6Nz8ODB0tLS8+fPZ2Rk3Lhxg8Vi4d1vaWkJDQ3NyMjAaXkiIiKuXr16+PDhCxcu+Pv7f/HFF3hFr/nz56elpeH129etW/fTTz+dPHmydcI4kqKi4oULF5qamq5du1ZYWEguJSBAlEOE9e/ff9euXaGhob6+vvPnz7906ZK7u3t7W+8EmNkGgGTk5OS8ePHCysqKLMG3m+AMwKInM5B4RoQemgJBrJ0VSDiBEIqJiRk5cuTcuXMNDAzI77z8/PyKiophw4bhe0vxurNPnz59/Pjx48ePp02bRr7c2toa/xEREbFr1679+/dPmDABD+i32YG9e/fa2dllZGRoamriecOt64hyiLDCwsKtW7eamZmVl5cnJyfjdRIlqGef71dVVY0aNWrt2rU4kWw3bFCC8KI6QMZE/5mF7/DgX77J2NhYVVVVYEnaDkk8I4K0UyB8/fXXck+B0PqgqapXSI+FAAAgAElEQVSqbt++3cPDIzMzk5zoiVeTLSkp4V+wDyF08eJF1NaXB0LIwMBg8+bNISEhaWlpMTExISEhCxYs8Pf3Hz58OFknKSnpypUr+FaYP/74Y+rUqQEBAa6uroaGhvxNdXiIuFzujRs3Tp06lZeXh9eXxcudSVzPO9+Piooi19pFCBEEQa7M1U0aFO7du3cnT56cMmVKQECA9LYCZA+HEoGVRxkMhpmZmbhNERLNiEDNFAglJSWJiYksFuv69esHDhzAhXjhRbymLz98xo1XaWwTjUZzdnZOTk7Oz8/v27fv7NmzJ06cmJiYiPcoOjp63LhxuKaxsfG1a9c+ffqUnp4u0IiQQ1RaWrpr165BgwZFREQsW7bs9evXBw8elFLQRz0u7tfX1x8/fpx8qKOjU1paGhoa2n0a7NCWLVtOnTqVnp5OrlQBegcbG5v+/ftfvHiRzFhQUlJSW1uLr/iJlcxAshkRemgKBCE7ixBqbm7GS7xgAgkn2Gy2n59fdHT08uXLfX19w8LCUlNTEULW1taamppbtmw5dOhQWVnZx48f79+/v2nTJltbWzqdfv78eZyagkRujmRoaBgaGvrixYsdO3ZcvXr1zp07eN/5o/nAgQOVlJTwjxt+Qg7RwYMH6+vrf/7557S0NA8PD7zvUtThld9uNZ9HIjOdpdqgKMSdNA3zeeRIrM8/fqdmz55dWlpaVlY2c+ZMPKWEIIjY2FiE0IkTJ9hsdlxc3OTJkxFCOjo6cXFx+Prh3bt3Y2NjS0pK/P39aTSan59fZWXlq1evJkyYMG7cODyjQ/RGBDo2bdq0AQMGCBTyeLzS0tI+ffrMmjWLXPWW+DcdBV6ySQCHw1m7di2LxWpsbKyqqoqJiVm2bBl5g9KHDx/69++/dOnS2trau3fvamhoHD16lP/lwcHBdDr97du3BEE8fvxYW1t737597R1MITtbUlKCl2DBOSQIgsBr69rb2zc0NFRUVEyZMuXYsWP4qZKSEgaDoa2tnZaWxuVy+c/zEEIMBiMjI4MgiDVr1iCE8K22L1++xGP9Wlpa5K1nQuCV2/fu3VtVVfXu3Tt/f/8RI0Y0NTW1PpgdHqIuksM8zsePH8+cOVNdXX3AgAHnz5+fMWNGh3c5FxcXu7u76+npqaqq2tvb808HvnXr1rhx45SVlQcOHPjtt98SBCEwSbmiooJ/0i7/WhHPnj0j+LI8Xrp0qc0NCW8Qa3M69vPnz4ODgw0MDMrKyrZt26arq9u3b9/2Jm+1SazJcxD35Ujc856UlBQrKyslJSVTU9OtW7c2Njbi8oaGhnnz5ikrK48YMSI9PR1fBmSxWGw2u7Ky0t7eXl9f//z588S/K2NHR0fr6OhoaGj4+PhUVlaK24iAc+fOoVZ3IeEp6iS83jhBEA4ODqampq0nFxIEwePxvL291dTU1NXVJ0yY0Hpbr169cnFxwSujnD17VuDZzz//nGw2Ly9PS0tLSNxvb2fxmTvJ3Nz8xx9/JB9aWVmRV0HxF4yTkxP57N27dwmCiImJMTc3V1FRGTt2bGpqKt5cS0vL1q1b9fX11dTUfHx89u/fb21tHR0d3ebtV62R9wSYmJj4+fmRS8u0PpjCD1EXyTru//rrr5qamidOnKiurn706BEe0+ww7o8ZM8bZ2fnt27cFBQUmJiZ2dna4/MKFC3379r1//35DQwNe5+fChQvE/05SFpi0W1FR8cUXXyCErl+/jhvh8XgBAQGxsbE8Hq+9DQlpkGh/OraDgwOebrF+/frc3NyampqJEydqaWmJvm4PxP2eQva/d6WREaFHp0Do6aRxMNsj0/X3eTze8uXL58+fHxgYqKWlZW1tjWewifLCuXPnGhkZWVhYODk5vXz5EiHU1NS0fv368PDwiRMnqqiorFq1SkdHp/VVKR8fH3wfBKavrx8ZGYn+nSSLEKLRaGw229fXl0ajtbkh4Q0SfNOx1dTUPDw8Nm3a9PDhw9jY2AcPHuAF4oODg21sbDQ1Nb/66quamprW83CBEL1pbUgJkkZGBEiBIEcSP5hdJ5m4n5ub+/z5c/4bQ/B18w7l5OSsWbPmt99+8/b2TkpKwhdnfv/99/fv348ePRrXsbS0rKysbDOhucC8K0tLSycnJzITb25uLnnHTZsbEt6g8OnY+OYLck4xnpPbXrPdnMCMJtk0cvnyZTc3Nzyoiro2zWnHjh20fykqKlZUVODyiooKT09PDQ2NAQMG4OVWEELe3t6RkZGtF4vtJqSXEQFSIMiFxA+mREgm7uPZSJ3IXFpaWurq6urv7+/q6urp6Yk/6Pj/tvWV9NZaT9oNCgrKycnBGcAvXLjg7e0tZEPCGxQ+HbvXLOYuMKNJNo1kZ2evXLny5s2bZIqbTk9zqqurw7/zsGnTpuGv5Lq6OgcHh6ampqKiouTk5LCwsIMHDyKETE1NU1NT79692w1jkLQzIkAKBNmT+MGUCMnct4XP7sUd5WCz2RMnThw3btyNGzcUFBQePHiAy/F043Pnzrm4uIjbky+//NLCwiIqKmr48OEqKip4KlV7GxJOgtOxu7M1a9aIeP+kpBppaWlZsmRJYGAg/50vZ86c4XK5rae+dejkyZNxcXGt74zfvXt3UVFRVlaWjo6Ora1tYGBgWFiYp6fnwIED1dXVz549O3HixNmzZ1taWoq7RenR0tKS7Dl+ayNHjpT9DYD8i/WD7kAyX7+WlpZ0Ov3q1ativerBgweFhYXLly/nX3sPITR27Fgmk3nhwoWdO3eWl5fX1dXdvHlz9+7dqNUkZYFJu7jC+vXrU1JSjh49unTpUuEbEt6g8OnY+H4NchwWT/uV+5T8jIyMSZMm4eQPq1evxgMvDAYDj4HgOkOHDsUP8RznhIQEhJC2tjaNRrt//35AQICpqSn+Yc5kMq2trTMyMsRqhM1mP336VE9P75tvvmmzkwkJCQUFBa1XO1FQUBBx4QHSp0+fjh07tnHjRl9fX3yajPF4vISEBFtbW11dXVzi4uLC4XBwPxFC9vb2VlZW4eHhYm0OgF6iwyu/Is5nWLFihYKCwtGjRysrK3Nzc11dXVFH83ny8vIQQosXL66pqUlOTra0tGQwGE+fPk1PTyfvr8M0NDRwvgiBScr8k3bJZuvq6rS0tGbNmiXKhoQ32N507MbGxunTpyOELly4wOPxmpub8c0pp0+fbjPZAr/2Jk0LIeI1+u6zGKTwpRa74dqQQnSr+1cAEE7W8zgbGhqWL1/OZDJNTEwOHz588uTJDuM+QRAhISEaGhqWlpZXrlw5d+4ck8ncsGEDl8slCOLEiRP9+/dXU1ObOnUqOa+ff5KywKRd/mY3btz4n//8R5QNddhgm9Ox+Rf4Pnz4MI6AWGRkpPBdbm/StBCivJc8Hs/CwiIgIIAswcuO46TB69at429h27Zt7YVsV1dXFRWVlpYW/PDnn39GCK1evVqsRoRobGxUVFScO3dum8+KG/ebm5tLS0tv3bq1ZMkSBoOBEMKJ6/AU78DAQLIm/ik2evRosgTnzrxy5YrwTUDcBz2InNffx/9UomenBEKI8l7+8ccfCKHY2FiypLS0FCH05ZdfEv9+2ZBP7dmzp72QvXLlSoHJ4xoaGmPHjhWrESGeP3+OEFq5cmWbz4ob9/k9ePBAQ0PD1NSUIAg8ZWXLli3ks/ie/vHjx5MleFjyyJEjwpuFuA96EJnO328ND5RLfBoyaE+3XQxSgLTXhnz9+rXc14YEoJuTStzncDiZmZkIodTUVIF1joCUdNvFIAVQc21IALoVqcT9iRMn4pVOV61apaCgQGuHZDPIdAfPnz9vb2elvb/ddjFIAT10bUgAehOpxP3s7GxRhqJSUlKksXU5Gjp0qLz2V0lJ6ciRIzU1NV5eXmVlZW/fvl29evX06dPxlw1eyJvFYtXX17NYLHxf25gxY1gslra2NkIoJycnLi4OXxIgCCIoKKiqqqqwsHDlypVjx4718fERq5H8/HwdHR086N+6n5MmTRL4XYI3WlZW9unTp7KyMnwmjs2ePdvQ0BD/fBTQ0tISEBAQHx/f1NRUXV0dGxubl5eH4z5CKDw83MjIaMOGDXV1dampqSdOnNi7dy9/to2nT5/S6XQHB4fOH3QAeibK3T7Xi3l4eKSkpBQXF5uZmdnZ2Y0aNerq1av4TNzLy2vevHmhoaG2trbm5uZOTk52dnaHDx9esGCBu7u7vb39okWLmEwmDouqqqpWVlYWFhbW1tZmZma3b9/GZ/qiN4K/59rrp4+PT3FxcVFREX9hcHBwv379mpubr1+/rqKigqfeIoSqq6uVlZXb/ApRUFD4+PFjYGCgvr7+rFmz1NTU4uPjyTsMdHV1MzIy3r17Z2RktG7duoiICPIrAUtLS3NxcenETeYA9HgdnpXDfAa5k+V6nNJYDFJAz1obEj7/oAeR83we0ENJYzFIAbA2JADyBXEf/B/pLQYpANaGBECOIO6D/5L2YpACYG1IAORFMutxgl5ABotBCoC1IQGQCzjlAQAAaoG4DwAA1AJxHwAAqAXiPgAAUAvEfQAAoBaR5vOkpKSQt78DeYG3QI7g4IPehNbh1L2srKw3b97IpjcAyIynp2dQUND48ePl3REAJMzDw0N4hY7jPgC9Eo1GS0pK6vA/BIDeB8b3AQCAWiDuAwAAtUDcBwAAaoG4DwAA1AJxHwAAqAXiPgAAUAvEfQAAoBaI+wAAQC0Q9wEAgFog7gMAALVA3AcAAGqBuA8AANQCcR8AAKgF4j4AAFALxH0AAKAWiPsAAEAtEPcBAIBaIO4DAAC1QNwHAABqgbgPAADUAnEfAACoBeI+AABQC8R9AACgFoj7AABALRD3AQCAWiDuAwAAtUDcBwAAaoG4DwAA1AJxHwAAqAXiPgAAUAvEfQAAoBaI+wAAQC0MeXcAABkpLi7mcrn8JeXl5a9evSIfGhsbKysry7xfAMgajSAIefcBAFn48ssvb9261d6zioqK5eXl2trasuwSAHIB4zyAKhYsWNDeU3Q6fdq0aRD0AUVA3AdUMW/evPaGcQiC8PHxkXF/AJAXiPuAKphM5syZMxUVFVs/paSkNHPmTNl3CQC5gLgPKMTLy6ulpUWgUFFRcd68eUwmUy5dAkD2IO4DCpkxY4aamppAIYfD8fLykkt/AJALiPuAQvr06TN//vw+ffrwF2poaDg7O8urSwDIHsR9QC2LFi1qbm4mHyoqKi5cuFDgmwCA3g3m7wNq4fF4RkZG79+/J0syMjIcHR3l2CUAZAzO9wG10Ol0Ly8vclaPvr6+g4ODfLsEgIxB3AeUs3DhQg6HgxDq06fP0qVL6XT4LwDUAuM8gHIIghg4cODr168RQg8fPhw9erS8ewSATMGZDqAcGo22ePFihJCZmRkEfUBB8l+P89ixY1lZWfLuBaCW2tpahJCysvL8+fPl3RdAOZcuXZJvB+R/vp+VlZWdnS3vXshZSkpKSUmJvHvRm5WUlKSkpJAPNTQ0tLS0+vfvL8cuAQoS+BzKi/zH9/EJl9y/AOWLRqMlJSV5eHjIuyO9VnJysqenJ/+nPTU1FW7XAjLW+nMoF/I/3wdALiDoA8qCuA8AANQCcR8AAKgF4j4AAFALxH0AAKAWiPs9RlVVlYmJyf79++Xdkf+Rm5s7d+5cGW903759iYmJMt4oAL0GxP2ehCAIGo0mvfajoqJqampEr3/58mU3N7c1a9bgh+/evTt58uSUKVMCAgLE3fSOHTto/1JUVKyoqMDlFRUVnp6eGhoaAwYMiI6OxoXe3t6RkZFr164VdysAANQd7tcFItLR0SktLZVe+/X19cePH/f29haxfnZ29sqVKzMzM4cPH45LtmzZkpOT8+effw4ZMkSsTdfV1UVGRpIPp02bZmBggMsdHByGDx9eVFT04sULV1dXNpu9efNmU1PT1NTU0aNH79u3b+vWrWJtCwAA5/vgv9asWfPq1SsRK7e0tCxZsiQwMJAM+gihM2fOPHr0SElJSdxNnzx5Mi4ujvjXzZs3cfnu3buLiopYLJaOjo6trW1gYGBYWFhRURFCSF1d/ezZs2FhYU+ePBF3cwBQHMT9nuHTp0/nzp2bNGnSli1bEEJ///13SEiIoaHh27dvt2/frqenZ2xsjO95zs3NDQgIMDU1LS0tnTlzJpPJtLa2zsjIQAgxGAw8kILbHDp0KH7IZrP9/PwSEhIQQtra2rjk6dOnenp633zzTZv9SUhIKCgoWL58uUC5goKCsrKyuLt27NixjRs3+vr6Pnr0iCzn8XgJCQm2tra6urq4xMXFhcPh4H4ihOzt7a2srMLDw8XaHAAA4n7PkJKSsn79+vv37+M7vH19fY8dO1ZRUXHgwAE3N7eXL18OHjzYz8+vpaVl5syZ0dHRFRUVp0+fPnXq1MOHDzkczvTp058/f/7hw4dhw4aRbf7666+2trb475iYGHzFuLq6miAINTU1giB4PF57N5R///33Q4YMkcj6NrGxsRUVFcXFxSwWa/To0du2bcPlz549q6io4N/E4MGDEUK//fYbWeLo6Hjt2rWPHz92vRsAUAfE/Z7Bx8eHf0DjwYMHQUFBCKHg4GAbGxtNTc2vvvqqpqamvLy8rKzM1dWVTqfv3LnTxMRk2LBhUVFRTU1NERERWlpa/IsT6OjoCFmrwNLSsqqqavv27a2fampqysrKGjFihER2bfXq1aWlpbdu3VqyZImCgsK+ffvw9dt3794hhPBAP6alpYUQKi8vJ0uGDh3K4XB+/vlnifQEAIroGXHf29ub9r/odLqqquqAAQPc3d35TwBFd/HiRbK1vLw8ifdZ4vT19fkf4oBIDqqoqqoihHAaKRMTEzqdrqCggJ+aPHmyhobGw4cPEUICCcTFHZPBioqKOByOnp5eJ17bmqKiorGxsaur69mzZ9PT0zU0NA4dOoQQwtnP8X5hXC4X/e8uGBsbI4REvywBAEA9Je6fO3eusLCQDAF1dXU1NTVXr15VUFC4fPmyo6NjJ874PDw8QkJCJN1TKRJIBygkO2Drp0xMTHAYlQg2m40Q6sT12w45ODiEh4e/fv2aw+EYGRkhhCorK8lnq6urEUK4HGMymQJ1AAAd6hlxn0ajDRw4UF1dnSzR0NCYOnXqkSNHEELNzc07duwQt006nT5o0CBJ9rI7ERiXr6qqGjBggKQa19HRQQjV19dLqkF+Dg4OxsbGioqKI0aM0NDQePHiBfnUP//8gxBydHQkSxobGxFCampq0ugJAL1Vz4j77SEnERYXF5OF9+7ds7OzU1ZWtrCwSEpKwoXp6emjRo3S1NTcunVrXFwcfzRBCD1//vzLL79UVVUdOXIkHg/BEhMTHRwc1NTUtLS03Nzc8Igz/6DTt99+a2JiwmQyp06diqOSkD50ER7DaWlpwQ9xyMNDHwghHo8n8OynT5/w38+ePSsvL58zZw5CSFFREf17wo4QwnXev3+PEMLzfERZGdzY2FhJSent27cS2S8BWVlZX3/9NUKoT58+ixcvzszMJG8lu3PnjoqKCn+GrA8fPiCExL1dAACK69lxnwy1Y8aMwX/cuXNn6tSpgwcPfv/+/ZgxYxYuXPjrr7/W1tbOmzdPRUXl1atXEyZM2LRpExn4sPPnzyckJDg6Oj558mTJkiW4cM+ePT4+PgcPHnz16pWpqemVK1dwxGGxWNOnT8d1Xr58+ddffy1cuBAn8cBhtM0+dH1n8VhWVlbWp0+fmpqaMjMzEULp6ekEQXA4nHv37uE6OHATBBEUFFRVVVVYWLhy5cqxY8f6+PgghMzNzfEu1NfXs1gsnOFyzJgxLBZLW1sbIZSTkxMXF1daWpqfn6+jo9PmshBKSkqTJk169uyZQDlBEGVlZZ8+fSorK8NfS9js2bMNDQ1xhwW0tLQEBATEx8c3NTVVV1fHxsbm5eXhuI8QCg8PNzIy2rBhQ11dXWpq6okTJ/bu3duvXz/y5U+fPqXT6Q4ODp0/rABQECFv7u7u7u7uotQ0NDTEfa6rq2Oz2RkZGRYWFgihfv36FRYW4jq45MGDBwRB4HxmM2bM+OOPPxBCOjo6v//+O0EQFy9exBMiv/vuO9zgw4cPCYIIDQ3FDxsbGwmCwBdODxw4QBDEqlWrEEIKCgp4K/7+/vw1//zzT/wwJiamvT4I3zWEUFJSkpAKP/74I/mWWVlZTZo0iXx4+PBhcjomQigyMtLf35/JZEZHR+vo6GhoaPj4+FRWVuJ2Ghoa5s2bp6ysPGLEiPT09L1799rZ2bFYLDabXVlZaW9vr6+vf/78eYIg8vLytLS09u3b12Z/zp07hxAiDzu2ceNG/o/Wo0ePcLmDg4OpqWmbB4HH43l7e6upqamrq0+YMAFvmt+rV69cXFxUVVWHDh169uxZgWc///zzDo8thn91iVITAOnpJp9D+fegE3Gf38aNG2tra3GFv//+u3UFY2NjNpuNg7iiomJ4eDiHw8H1ybiPIxQ5c7yqqoogiFWrVjGZzHPnzvF4vIULF+KnWlpaCL64j9shR1S8vb3b64PwXesw7osFx31JtdYmLpc7fPjw4OBgEeuz2WwR32XR5eXl0el0/F3eoW7y/wYorpt8DnvkOM/Hjx9dXV3x39evXyfL8fg7Quinn34i97C0tJTJZF67ds3IyIjD4YSHh0+ePLmurk5I+3jQ/LvvvqutreXxePb29mQ0J9oa/lZWVsaD45WVle31oav7LA4ul0uO+0sJnU5PTEw8ffp0dna2KPUjIyPxDQeS0tTUtHbt2uDg4LFjx0qwWQCooEfGfTqdfuHCBXw1r6CgYNmyZbicnOHeeujZ1tb2yZMnbm5uCKHMzMx9+/Z1uJUXL16MGTMmKCgoPj5+/PjxQmriHxAIIT09PSF9kI2PHz/m5OQ0NjbigSbpbcjGxiYxMdHd3f3WrVvCa0ZERNjb20+YMEFSm8ZLUAwePFiU9xEAIKBHxn2EkKam5tWrVzU0NBBCly9fPnr0KELI3Nwcj+ecPXsWz2/BSktL9+/fr6urm5KSgs86CwoKhLdPEMTMmTMfPXoUFBTEv7ZB62oIIbxSGELIwcGhvT7IRk1NjZaWFl7lxtHRkcViSXVzs2bNun379pkzZ4RXW79+Pf/ky66Lj4/38PA4e/askJsYej0JZj6QUj6DJ0+ezJgxQ11d3dDQ0NfX18jISFLZI169erVt2zZjY2PyXw+IR8bjSq2JMr7P4/GKi4tVVFRwn7Ozs7lcLkEQ165dwwMsDAbju+++q66uxl8ACKHAwMDKysrc3NyzZ8/W1NQwGIxvv/22pqZm9+7dCKHY2Fgul7t582Zc+cqVK01NTQsWLCDbJxcD8PX1LSwsJFeJ+fDhA8E3vh8YGFhTU4Pnn/Tv37++vp4giDb7IHwHkUTH90FrMhtXjYyMxGscSbWRlJSUgQMH3rlzhywJCwsj/6kZDEZ5eTkuLy8v9/DwUFdXNzU1jYqKarO14uLicePGrVmzpovd5ldSUqKlpXX79u3q6urg4GD8f7p//36JND5jxgx827bAzAIhfvjhBxsbGyaTaWRk5OXl9fr16/ZqinLEOq2bjO/LvweixH0vLy+Br6vRo0fjp/bs2UMW9uvXjyCII0eODBo0qE+fPoMHDz58+DCXy21paQkLC2OxWCYmJgYGBmFhYTwe78KFC/wN8q//jhDicDj4uq6lpeWBAweSk5P19fX19fUDAwM5HA4Z91NSUgYPHqyiojJ16tQXL16QHW7dB+E7CHFf2mTz/8Zms83MzLoY9ztsJCsrS1tb++nTp2RJbW0tXrwII+c41dbWWlhYzJkzp7KyMjs7W1tbG89Paw3X/Oabb7rSc3779+9XV1eXVGut7dy5U0jc5/F4d+/enT9//tWrVwmCuHjxora29s2bNxsaGt68eTN//vzPPvsMLzsooL0jtn79+pCQkH/++aeL3Ya4/1+iz+fpPgTm83QdxH1pk83/2+LFi9G/a5pKqREOhzNkyJDw8HD+wgMHDqSkpLSuvGnTJkVFRfwjlSCI8PBwRUXF9mLlL7/8QqfT//zzz650nuTv76+rqyuRptqEF+9rvS/l5eUHDhwwNzcfP378999//+nTJ4IgFi5cOGXKFLJOZmYmjUarqalp3Wx7R6ykpCQ8PNzU1NTJySk5Obm5ublz3Ya4/18Q9wmI+9LXif+3e/fuOTo6qqqqGhoarlq1CgdicrU7XOezzz7DD+vq6lauXMn/kzEjI2Pt2rX9+/cvKSnBd4NbWVndu3dPrEbq6uoEeoWv2fAPUzQ0NBgYGAwYMGDFihW5ublkOZfLNTAwcHBwIEvw5Ktdu3a1t8s2NjZubm747ydPnujq6u7du7fNmkJ24e7duwK/zgsKCvB9kaGhoQRB8N99kp6ejs/cEUJnzpzBrSUlJY0aNapPnz4WFhb832e//PLLhAkTVFRUrK2t8c0iZNzn8XipqakeHh56enqrV6/Oz8/n7+3hw4dpNNrevXtbWlp4PN7SpUtxTwR0eMRaWlquXbv25ZdfGhsbb968uROn/xD3/6vHxf3Gxkbyft2CggKJtAlxX9rE/X+7c+eOurr69evX6+rqkpKSmEzmmDFjOBxOdXU1vs6Pq1VWVuKb5nCA5s9h0LdvX4SQkpJSWFjYmzdv/vrrr+HDhyspKT179kz0RlpzdHQcMmQIf8m3335LhlEajbZ161ZcjhfuXrhwIVkTL2sh5E63wMBARUVFfCL8559/amtr79mzp82awneBIIgVK1aQ5/sJCQl4GGrz5s24Ml4Scfr06Twer7a21sDAgDyJjo+Pnzhx4osXL96/fz9nzhw6nZ6Tk0MQRHZ2trKy8qFDh6qrq5OTk/HVvsLCwoqKioMHDw4ePHj06NExMTFsNrt1b5ubmz09PRFClpaWCxYsSE5ObnOnRD9ir1+/3rFjh4mJibOz86VLlywLIDYAACAASURBVEQ//Ye4/189Lu4LXGz48ccfu94mxH1pE+v/jcfjWVhYBAQEkCX4nPTkyZMEQaxbt46/KXy7X5sh29XVVUVFBd/rRxAEXmlj9erVYjXCr7GxUVFRce7cufyFzc3NZAIDBoOBEMJXI1NTUxFCgYGBZE28fBN5baw1fCfjlStXRDlKQnaB+N+4TxBESUkJGfcxLy8vGo2Wnp6+cePG69ev40IOh2NgYPDs2TP8EK+7tWDBAoIgrKysXFxcyJfj39yFhYWenp5KSkosFkt4b3k83ldffUWn05lM5qVLl9qsI+4Ra2hoWLRoEUKovQZb6yZxn7rT4DotMTGR/wh+9dVXEmnW09OTBqQGn+6JKCcn58WLF1ZWVmSJn58fQggn/hU9h4HEEyG0mfmgKwkMBIiVz0CsXRDIHoEQiomJGTly5Ny5cw0MDGbOnIkL8/PzKyoqhg0bht81vIjs06dPHz9+/Pjx42nTppEvt7a2xn9ERETs2rVr//79EyZMwAP6bXYAL0mSkZGhqamJJwG3riP6ESssLNy6dauZmVl5eXlycjJe9LAHYci7AxLz5MmTkJCQBw8e0Gg0VVXVQYMGOTs788/26eaCgoKE3x0GuiIrK+vEiRMiVsanmQ0NDWSJsbGxqqpqWVmZWBuVeCKEDjMf4AQGX3/9tYgJDARIL59B60Ohqqq6fft2Dw+PzMxMcqInXhq2pKSEf/U9hNDFixdRW18eCCEDA4PNmzeHhISkpaXFxMSEhIQsWLDA39+fXKwXIZSUlHTlyhV8X8sff/wxderUgIAAV1dXgaVfOjxiXC73xo0bp06dysvLw4vF4oUOe5xeEvdLS0snTpx44cKF8+fPjxw5sqSkpLy83MnJqcMXRkVFeXt7k3PgBB7K0vjx4z08PGS/XeoQPe7joCNwxzWDwTAzMxN3o0SrRAjjxo0TtxGSKJkPxEpgIECW+QxKSkoSExNZLNaKFSsOHDiwZcsWhJCmpiZCKDk5ecOGDfyV8Rn369ev22uNRqM5Ozs7OzuXl5efOXNm9uzZffv29ff3d3d3V1ZWjo6OJg+7sbHxtWvXhgwZkp6eTt6ygwk5YqWlpXFxcSwWy8LCwt/ff+7cuXhJ8x6ql4zznDt3jsvluri4aGlpvXnzRsjng199ff3x48fbewgoy8bGpn///hcvXiTX6y4pKamtrcWDRWLlMJBsIgRRMh+IlcBAgFj5DITsAkKoubm5qamJrCyQPYLNZvv5+UVHRy9fvtzX1zcsLAyPrVtbW2tqam7ZsuXQoUNlZWUfP368f//+pk2bbG1t6XT6+fPnBe6BJzdHMjQ0DA0NffHixY4dO65evXrnzh18KPij+cCBA5WUlPCPG35CjtjBgwfr6+t//vnntLQ0Dw+PHh30EeoGVxgkcl1XYLIw/oW+bds24a8SmCgtkcnXnYPguq6UiXs9DdefPXt2aWlpWVnZzJkz8eQTgiBiY2MRQidOnGCz2XFxcZMnT0YI6ejoxMXFnT59GiF09+7d2NjYkpISf39/Go3m5+dXWVmJcz+MGzcOz/0QvRGBjk2bNm3AgAHkQw6Hs3btWhaL1djYWFVVFRMTs2zZMvKOpA8fPvTv33/p0qW1tbV3797V0NA4evQofmrWrFkGBgZ4ESdScHAwnU5/+/YtQRCPHz/W1tZubyFu4btQUlIycOBA9G9CCIIgbty4gRCyt7dvaGioqKiYMmXKsWPH8FMlJSUMBkNbWzstLY3L5QqcezEYjIyMDIIg1qxZgxDCt9q+fPkSj/VraWm1dycaP7x64969e6uqqt69e+fv7z9ixIimpqbWx0HIEZOIbnJdV/496GLcbz1Z+M2bN/jUg4z7xcXF7u7uenp6qqqq9vb2eI6zwERpcqVlDE9LaD2P+Pnz58HBwQYGBmVlZdu2bdPV1e3bt29708JEB3Ff2jrx/5aSkmJlZaWkpGRqarp161aca4EQJ4eBRBIhCBDIfNDpBAZtJkXgz2cgPAGDkF3AZ+4kc3NzgewR5FVQ/AXDPx579+5dgiBiYmLMzc1VVFTGjh2bmpqKN9fS0rJ161Z9fX01NTUfH5/9+/dbW1tHR0e3eftVa+T/somJiZ+f3/v379s7DsJTPnQRxP3/ksj5vsCkMYG4P2bMGGdn57dv3xYUFJiYmNjZ2eFygQlzAg/bnEfs4OCAp2esX78+Nze3pqZm4sSJWlpa5Jr+nQNxX9rk8v8mjUQI4mY+EEIgKYJY+Qx6E2kkh2hPN4n7vWR8Xzgejzd37lwjIyMLCwsnJ6eXL192+JKWlpbQ0NCYmJjBgwfr6elFRETweLzDhw8/ePAAr+gZHBxsY2Ojqan51Vdf1dTUkOu4AUCSRiIEcTMfCMGfFIHK+Qwknhyi+6NE3M/JyVmzZs1vv/3m7e2dlJSELzEJ1948YoQQXmaZnK2MZ/uK0iZldf8Vg6VBeokQRM98IAR/UgQq5zOQeHKIHoEScb+0tNTV1dXf39/V1dXT01OUf0JyHjH/j6P8/HzU1kzkniIqKoqcqCCzRi5fvuzm5oYvymE7duwgb6dSVFSsqKjA5RUVFZ6enhoaGgMGDMCrbrXm7e0dGRm5du3aruyCDEg7EYKImQ+E4E+KQOV8BhJPDtEj9P63mc1mT5w4UVNTMycnx8vLS8QbI8l5xFLunexIZJaquI1kZ2evXLny5s2bU6dOxSV1dXX8S15PmzYN/36qq6tzcHBoamoqKipKTk4OCws7ePBg6wZNTU1TU1Pv3r3bzc9MtbS0+M8YfH19Jb6JkSNHXrp0SSJNhYWFCUxzAL1bL4n7QiYLP3jwoLCwcPny5fwrCOI/BCZK8z9sbx4x+vfeFnLcFk8oJicmd1tr1qwR8f57STXS0tKyZMmSwMBA/jsnT548GRcXRwZEvPIBQmj37t1FRUUsFktHR8fW1jYwMDAsLKzNbErq6upnz54NCwvDq2gBAMTVG+J+aWnpgwcP2Gx2eno6LsF/PHjwoL6+Hi858sMPP3z8+PHSpUu//PJLQ0PDX3/9de/ePW1tbYRQTk5OXFxcaWkp/8PKysrw8PCmpqbNmzf369dPS0vLyclp9uzZTU1NmZmZeBMEQXA4nHv37qF/5ynLbJczMjImTZqEkwetXr0aD7wwGAw8eILrDB06FD/E98gkJCQghLS1tWk02v379wMCAkxNTfHALpPJtLa2zsjIEKsRNpv99OlTPT29b775ps1OJiQkFBQULF++nCz59OnTsWPHNm7c6Ovri8dAMB6Pl5CQYGtrq6uri0tcXFw4HA7eXGv29vZWVlbh4eFdOogAUJaU5wt1rIvzOLOysvh3x9zc/Pbt2+RDnIErJCREQ0PD0tLyypUr586dYzKZGzZs4HK5AhOlW8+bbj2PmH/p8MOHD+O1Z7HIyMhO7wUSZx5n91kiWPhSvTJbMVgU3WT+HKC4bvI5lH8Petw6zNIgetzvtksEC+hWKwYT3eb/DVBcN/kc9oZxHkrptksEC+hWKwYDAPhB3O9huu0SwQJEXDH49evX3W3FYAB6PYj7PYxUlwjGt6dJRG9aMRiAXgbifg/TbZcIFtCtVgwGAPCDuN/DKCkpHTlypKamxsvLq6ys7O3bt6tXr54+fbq7uztCCGf/YbFY9fX1LBYLT3YaM2YMi8USmLSKECIIIigoqKqqqrCwcOXKlWPHjvXx8RGrkfz8fB0dHXyxt3U/J02axP+7pKWlJSAgID4+vqmpqbq6OjY2Ni8vD8d9hFB4eLiRkdGGDRvq6upSU1NPnDixd+9e/ONm9uzZhoaGePos6enTp3Q63cHBQQrHGIBeDuJ+z+Ph4ZGSklJcXGxmZmZnZzdq1KirV6/iM3EvL6958+aFhoba2tqam5s7OTnZ2dkdPnx4wYIF7u7u9vb2ixYtYjKZOJ6qqqpaWVlZWFhYW1ubmZndvn0bn+mL3gieG9BeP318fIqLi8l7rxQUFD5+/BgYGKivrz9r1iw1NbX4+HjyRgFdXd2MjIx3794ZGRmtW7cuIiKC/Eqorq5WVlYW+HZJS0tzcXERcgEAANAu+U0l+i+Yx0nIYx1maSwRLKBbrRjcTebPAYrrJp9DON+nKGksESwAVgwGoHuCuE9F0lsiWACsGAxANwRxn3KkvUSwAFgxGIDuhiHvDgBZw0sEy3KLkl0xWCLtAEBlcNIEAADUAnEfAACoBeI+AABQC8R9AACglm5xXbekpKQ3ZbLtHIEEMkCy8OGFjxmQr+7yby7vG8cIvLAMAABQhLyDLkEjZDulD4BugkajJSUleXh4yLsjAMgajO8DAAC1QNwHAABqgbgPAADUAnEfAACoBeI+AABQC8R9AACgFoj7AABALRD3AQCAWiDuAwAAtUDcBwAAaoG4DwAA1AJxHwAAqAXiPgAAUAvEfQAAoBaI+wAAQC0Q9wEAgFog7gMAALVA3AcAAGqBuA8AANQCcR8AAKgF4j4AAFALxH0AAKAWiPsAAEAtEPcBAIBaIO4DAAC1QNwHAABqgbgPAADUAnEfAACoBeI+AABQC8R9AACgFoj7AABALRD3AQCAWiDuAwAAtTDk3QEAZOT48ePl5eXkQ2Vl5aSkpNzcXLLk66+/NjAwkEfXAJApGkEQ8u4DALIQFBT07bffKikptX6Kw+EYGBiUlpbS6fALGPR+8CkHVLFw4UKEUFNbGAyGj48PBH1AEXC+Dyhk4MCBxcXFbT6Vm5trY2Mj4/4AIBdwggMoxMfHR1FRsXW5mZkZBH1AHRD3AYV4eXlxOByBwj59+ixZskQu/QFALmCcB1DLiBEjnj17JvCx//vvv4cMGSKvLgEgY3C+D6hl8eLFCgoK5EMajTZq1CgI+oBSIO4Dalm0aBGXyyUfMhgMGOQBVAPjPIByxo8f//vvv/N4PIQQjUZ78+ZNv3795N0pAGQHzvcB5fj4+NBoNIQQnU6fMGECBH1ANRD3AeV4eHjgP2g02uLFi+XbGQBkD+I+oBw9PT0nJycajUaj0dzc3OTdHQBkDeI+oCJvb2+CIKZPn66joyPvvgAgc4QMyXtfAQCgm0pKSpJZKJb1OsxBQUHjx4+X8Ubl6Pjx4wihDRs2yLsjvUdWVtaJEyeSkpK62M533323bNkyZWVlifQKgK7w9PSU5eZkHffHjx9PXlWjgkuXLiG+C4lAIk6cONH1Q+rs7AyDPKCbkHHch/F9QFEQ9AFlQdwHAABqgbgPAADUAnEfAACoBeI+AABQC8R9AACgFoj7AABALRD3AQCAWiDuAyBMVVWViYnJ/v37hVcrKCjYvHmzoaHhu3fvOr2t3NzcuXPndvrlErdv377ExMTOvfbJkyczZsxQV1f//+y9eSDU2//4f2bs+5bBJCkRUWjTtbVpUbQJFVpFIbpXlpSiTeq2CbdoFLktUveq1PdGSblRN0Lr5WZrkJF9N2Zevz/Op9dv3oNpMPbz+Gte53Vez9c5Z2aer/N6nud5PhUUFBwdHRUVFX84hlxSUFCwb98+MplcVFTEE4GjEKT3EYgfgGEYjNfPAWdn59OnT9NotO4qhIaG1tbWcpBw+/ZtKysrFxcXvOTAgQOE7wgICODCaTSara2tpKTk+PHjw8LCetKVnsm0t7c/f/68q6trj24BACgtLTUxMXF3d//y5cumTZuioqIqKip+OIZcsmvXrl9//bW8vJz7S65duzZ9+nRxcXElJSV7e/svX750V/Pr16/h4eELFixwc3PjRWOHKgMWCQjDMDCwsYeGAmvXrl27du1gt2JEASPzDHYrumDPnj0AgPLy8s6nGhsbJ06cWFNT09216enpMjIy79+/x0vq6+ulpaXx/+myZcvwcnV19ZUrV1ZVVWVkZMjIyBw/fpzLFvZCJjx19OhRLm8BCQoKkpCQ6NElPeLgwYMAgMLCwi7PMpnMpKQka2vrhIQEDMNu3LghIyOTmJjY3Nz85csXa2vryZMnM5nMLq/dvHnz1KlTAQDOzs54obu7u7e393///dcPXfk/Blg3Ir3fv/RC71dVVY0dO/bYsWP91KTekZmZuWrVKp6IOnr06NWrV3t9+ZDV+8HBwd3pfZjdpTu9T6fTNTQ0AgICWAuPHz8eHx/fufKePXsEBAS+ffsGDwMCAgQEBLrTgGz0Tubff/9NJBLfvn3LzS0gzs7OcnJy3NfvKfCNpHOvKyoqjh8/rqam9tNPP0VHR7e0tGAYtn79+gULFuB10tLSCARCbW1td8I7OjqEhIRY9T6VSg0ICFBRUVm4cGFcXFx7ezuP+4P0/gijd3qfTCYHBQX1U5MwDDt//jyHuWdn4uPjVVVVHz16hJf4+/vj00Z+fv6KigpYXlFRYWNjIyEhoaKiEhoa2qW04uLi2bNnu7i49K7xPdL748ePh41cuXJlfn4+3mYFBQUMw/AST09PKHnatGmCgoLq6upQPzY3N8fExJiamvr6+uIy79y5A40GM2fOzMjIwMtPnjwJAPjy5Yufn5+srCyZTL5z5w6GYdu3b2d9w25oaGBrJIVCAQCUlJTgJc3NzSQSafz48du2bcvKysLLGQwGiUQyNjbGSzIyMgAAgYGBPxyKvsjU19e3srKCn9+9eycnJ3fkyJEu75KUlMRmUcjLy2Mdw7lz5+KnUlJS4MwdAHD58mUoofO3APn777+NjIxERET09PQ8PT1Z9T6TyUxOTraxsRkzZszOnTtzc3NZm3Ty5EkCgXDkyJGOjg4mk7l582bWb7NLpKSkWPU+pKOj4+7du8uXLyeTyT4+Pryd/iO9P6IYgnaeH9oc2OgPE0TvrAeQHun9b9++LVmyhJ+fn0ajYRhWU1NjbGw8ZsyYpqYmWCEkJOT48eOtra1RUVEmJib5+fmVlZUrV64kEomZmZkxMTGwpz4+PrD+vXv3CAQChUJpbGyMiIiAI0AkEqlUKtT77u7ub968qays/Omnn8aMGQPtCXBJs7sxNzU11dDQYC05d+4cPrwEAsHPzw+Wv3v3DgCwfv161g6yfgUc6ItMDw8PAQEBOEd++/atjIzM4cOHOdxr27Zt+HyfbQyrqqq8vb0BAEuWLGEymfX19SQSCZ9Ed/ktYBiWkZEhLCx84sSJmpqauLg4ERERqPdpNFpwcPCkSZNmzJgRERHR2NjYuTHt7e0w2qWOjs66devi4uJ+OFZd6n2ckpKSAwcOKCsrm5mZ3bp1iyfTf6T3RxRDUO9ztjmw0X8miF5YDyA9tfOkp6cDAHDLUnh4OADg9evX8NDOzq61tZVOp5NIpI8fP8LC4uJiAMC6deswDKNSqax6f+3atfBdATJz5szly5fDz1DvFxQUwENo9vn69SvGUe+3trYKCAisXr2atbC9vb20tPTBgwebNm3i5+cHAMCXp+TkZACAh4cHXrOjowMAMGPGjB+OQ19k/vbbbwAA+PrCDax6H+s0hhiG2dnZEQiElJQUT0/Pe/fuwUIO34Kuru7SpUvxy52dnaHet7W1FRISolAonNvDZDJXrVpFJBLFxMRu3br1w/Zz1vuQ5ubmDRs2AAC4EfhDBlg3In+eoUVLS8vVq1fnzp27d+9eAMC///7r7e2toKBQXl6+f//+MWPGkMlkGNM/KyvLzc1NRUWltLTUwsJCTExMT08vNTUVAMDPzw8dNqBMTU1NeNjY2Ojk5BQTEwMAkJGRgSXv378fM2bM0aNHu2xPTExMXl7e1q1bWVt4+vRpT09PR0fHN2/e4OVMJjMmJsbAwEBOTg6WLF26lE6nw9t1xtDQUFdXNyAgoM9j9gPmzJmjoaFx584deJiZmSkrKxsXFwcAqK+vl5eXFxISys3NpdFoWlpacKCgdej9+/cAAHl5eVZpoqKidXV17e3t8FBRUTEzM5O1ApyKwpoAgNbWVs7NKyoqotPpY8aMYS0UEBAgk8nm5uZXrlxJSUmRlJQ8ceIEAADeF0qGMBgMAICgoOAPx6EvMslkMgCgoKDgh3fpErYxBABERERMnTp19erVJBLJwsICFnb3LeTk5OTk5CxevBi/XE9PD34ICQkJDAwMCgoyMjKCBv0uG3DkyJE5c+akpqZKSUnZ2NhcuXKldx2BFBYW+vn5TZw4saKiIi4ubuXKlX2RNiggvT+0iI+Pd3d3f/bsGZwCODo6Qu/A48ePW1lZff78edKkSU5OTh0dHRYWFmFhYTQa7eLFixcuXHj9+jWdTl+yZMmnT5++ffumpaWFy3zx4oWBgQH8HBERwTr3FBcXxzAM2iK6bE90dLSGhsa4cePwksjISBqNVlxcTKFQZsyYsW/fPlj+8eNHGo3GWnPSpEkAgJcvX3bXWVNT07t379bV1fV6uLhk48aNf/31V3Nzc0VFhZKS0oYNG+Cz8/79+3DKVllZCQCgUqmsc6Lc3FwAAJH4P/+RvXv3SkpK7tmzp6Gh4dWrV8+ePVu6dCmHW3c3sDiNjY0AACEhoe4qGBsbBwQElJSU0Ol0RUVFAEBVVRV+tqamBgAAy7mnpzLFxMTY6vQItjEEAIiKiu7fv7+2tjYtLQ0fou6+hY8fP4KuHh4AABKJ5OPjk5eXFxgYmJiYqKqq6uHh8eHDB9Y6N2/evHPnjo+Pj7Gx8T///KOlpeXm5lZRUdHTXjAYjISEBHNzc0NDQwaDkZaWlpycbG1tLSAg0FNRgw7S+0MLBwcHaG+FPH/+fPfu3QAALy8vfX19KSmpVatW1dbWVlRUlJWVmZubE4nEgwcPKisra2lphYaGtrW1hYSESEtLm5mZ4UJkZWVZD9nQ0dGprq7ev39/51NtbW3p6ena2tqshTt37sTNBXx8fMeOHYPOFXC/EolEwmtCqy6HP5impiadTn/y5AkXA9MnHBwcWlpa/vrrr9jYWGdn5y1bthQWFv7zzz///vvvrFmzAABSUlIAAPgSwBlNTc09e/bk5uYqKipaW1s7Ojr21IOeDZj+pampiUMdY2NjMpksICCgra0tKSnJukD933//AQBMTU17et8eyYRvLeLi4j29S3dQqdTY2FgKhXLv3r3jx4/Dwu6+BfjmUVJS0p00AoFgZmYWFxeXm5urpKS0YsUKExOT2NhY2OywsLDZs2fDmmQy+e7duy0tLSkpKdy3trS0NDAwcMKECSEhIVu2bCkpKQkODlZTU+tJj4cWSO8POdjmNVCT4mlg4fs4nU4HACgrKxOJRD4+Pnhq/vz5kpKSr1+/Bp1e/HuXRba/TRB9tB5wj4qKyvz582/fvl1fX6+srDx9+nRdXd3o6Gh8SqunpyclJbV3794TJ06UlZXV1dU9e/YM+uPDoYYmbwDAy5cvExMTHz9+3NTUVFxcfOrUKbzLsCbsNQCAyWTiF0KbW5dzfzKZLCQkxHkXUnp6+i+//AIAEBQU3LhxY1paGr4F7NGjRyIiItbW1j0dkx7JhCu9GhoaXApvb29va2vDD9nGENobw8LCtm7d6ujo6O/vD9cYuvsWDAwMiETitWvX4JDiwPcDVhQUFHx9ffPz8w8cOJCQkPDo0SPYQdanmqqqqpCQEHyD4ZLg4OCmpqYnT548fvzYxsZmOE7w2RmgdQQMw9C6LnfAPwm+CAZXCysrK+EhXGGDi6XOzs5iYmKs106ZMkVXVxfDMOjohpcfPnwYfPcg5Oxbwgp8hLi5uXGoc/r0aQBAe3t7VlYWAMDJyQk/Bd8A2FYsWYH/9r179/6wJaz0zn8/Ojqaj48PX849e/Ys1LZ4hTNnzrD+L/j5+VNTUzEMu3//PgDA0NCwubkZwzB3d3e2f5CKisqjR4+qq6vNzc0BAFevXmUwGO3t7VZWVgCAS5cuMZnMixcvAgCSkpIiIyPZ7BgYhi1evHj8+PH4IZ1Od3V1pVAora2t1dXVERERW7ZswfcZffv2bdy4cZs3b66vr09KSpKUlDx16hQ8ZWlpSSKRnj9/3rn7vZYJ8fLyIhKJcLhycnJkZGQ47C+hUqmqqqoAgCdPnsAS1jGk0WgLFiw4ffo0Xpmfn19GRubx48cMBqO7bwFuY7azsyspKfn8+TO09UtLS3OzZ+3evXsAgCNHjlRXV3/9+tXZ2VlbW7utra3LEWMymaWlpYKCgpaWltD9f2AYYN2I9H7/0t96X1RUlPVaRUXFFStWYDzS+3AmvmXLFg51Xr16RSaTMQxra2uTlJScP38+fiotLQ0AcObMme6uheqgp96cvdP7jY2NuOMNhmHfvn1bs2YNW52IiAg1NTUREZFZs2YlJydjGPbHH3/gOgg+UDMyMjqbO5SUlFjd0oOCgmbMmIEfXr58uaqqytDQUF5e/tq1a53bdvXqVfC/3uj29vbi4uISEhJGRkadLykoKFi6dKmoqKimpuaVK1fwcmNjYxUVlS59OnstEzJ9+nRcbHZ2trS0dHd6H3pP4aipqbGNIb4KCp8iCxcuxM8mJSV1+S1gGNbR0eHn5ycvLy8uLu7g4BAUFKSnpxcWFsZh+xUr+J4AZWVlJycn/N/UecTgHwfnzZs33MjvO0jvjyh6ofebm5vB951E2HeVDd0Bse87FfPz8zEMc3Z2JhKJcB6KYdiHDx+gazmGYb6+voBli5Cfnx/47mIIzanV1dU/bElra6uQkBCr/1xnzp079+uvv8LPbm5uAgIC+BPlwIEDIiIinae3ONCtoqducIO7X/fmzZuRkZH4YVNT09u3b2fMmMFgMHotk8FgTJkyxcvLq+/Na2xs5LnfcHZ2NpFIfPXqFW/FDhH6Y8R6wQDrRmTfH3LAdc709PSWlpa2tjY4a05JScEwjE6nP336FHx/gwYAYBi2e/fu6urqwsLC7du3z5o1y8HBAQAAF50oFEpTUxOFQoGzsJkzZ1IoFBkZGQBAZmbmpUuXSktLc3NzZWVlu4yVKCQkNHfuXOhNAeno6HBzc4uKimpra6upqYmMjMzOzoZmYgBAQECAoqLizz//3NDQkJycfPbs2SNHjowdOxYAsGLFjM/jlAAAIABJREFUCgUFBdgXnPfv3xOJRGNj434YxX7h33//3blzJ6tXq6ioqLa2trW1dWeXFe4hEomxsbEXL16EG2X7wvnz56EjAK9oa2tzdXX18vKCC+AjD56P2PBgwJ4wGJrvcwHbSzGr9eDkyZO4OyYA4Pz589C+HxYWJisrKykp6eDgUFVVBeU0NzevWbNGWFhYW1s7JSUF+i/DXaZsNgfOr+39aoJgtR5wzyDO9+/evQsAcHZ2zsrKqqura2xszM7O3r9/f1lZGU+Ejx07NjExsdcSzp07B63hvIJKpZqZmW3atKkvbzNDGZ6PWK8ZYN04tPQ+q5qDiImJjRs3ztLSkkKhdHR0DFhTeUW/7tftvK7Lc/rPBNFr68Hg2nkSExOXLFmioKAgKCiopqbm7e3NjcWMS3Jzc4eCzQHn0KFDERERg92KUcGo1vtMJhNuloFUV1eXl5f/9ttvEhISAIDp06eXlpYOWGt5Qr/qfUdHR2Fh4X4SjpOVlSUpKZment5HOUFBQXCTDoZhra2tRkZGrBv3uWfIxuNEIHrNAOv9oWXfJxAIU6dOxR3SBQQEFBUVd+zYER0dDQDIyspasWIFvkV+lFNXV5eZmdna2gq90PrvRvr6+rGxsWvXrn3w4EGvhYSEhBgaGhoZGQEAYGCJSZMmHTt2jHfNRCAQ3DK09H53rF69Wl1dHQCQmZkJp3sAgKdPn86ZM0dYWFhdXR0W3rhxA88lFB4ebmZmJiUlNXnyZHw5MSUlZdq0aVJSUn5+fpcuXcJ3c3QWNcSpra2VlpaG4XFMTU1hIN/+w9LS8uHDh5cvX+61BHd3d3z/Z1RUFIyR0pe1UAQC0WuGzR8Pj8p0/fp1AMCjR48WLVo0adKkysrKmTNnrl+//sWLFzY2NjDEKwDg2bNnsbGxs2bNysvL27ZtGwCgvr5+zZo1IiIiBQUFRkZGe/bsgaFRuhQ1SL3kFmlpada3NkdHx/6+49SpU2FMm77j7+/PFpIegUAMJMNG7yspKcEPMHiIm5tbR0fHjh07JCQkoAH96NGjRCJxwoQJsJqvr6+ioqK+vj4AIC8vr7W1NS8vr7a29r///isoKFi+fPnFixeh3u9S1CD1EoFAIPod/sFuALfg4W3b29vz8vKgicbExASvkJ2d3fkqfKmgublZS0uLRCLRaDQjI6N9+/bt27ePn5+fe1EIBAIxMhg28308BpO6ujoM/AIA+PPPP3FbR2lpKYfLmUymmJjY3bt3FRUV6XR6QEDA/PnzGxoaeiEKgUAghjXDRu/jYdytrKzwiJWsW0m5wcDA4N27dzBgVlpa2rFjx3otCoFAIIYpw0Pv5+TkwExSWlpaW7ZsUVNTg9GJr1y5whaalQOlpaVBQUFycnLx8fFwZ3ZeXl7vRCEQCMTwZcjp/by8PDyCeV5eXnV19Z07d8zNzZlM5tSpUx88eCAkJCQoKOjj4wMA+Pfff3/55Zfq6uo3b95ER0czmUyYkxMAUFRUxGAw8MPCwkJxcfEDBw6EhITU1dXBZBfm5ubdiRqEniP6gVevXm3fvh1f7WejurpaWVm5y9hEvSYrK2v16tU8EXXs2LHY2FieiBp43r17t2zZMgkJCQUFBUdHR0VFRV6Nc0FBwb59+8hkclFREU8EjkYGaH8YhmG9itPAx8cHE+hER0fT6XTWyr/++uuECRMEBQUnTZp08uRJBoMBXTxxYMhinNbWVn9/fwqFoqysTCKR/P398fjjnUXxqstDMK/6cIf7/boMBoNMJhMIBNYc36xUVVWRyeSgoCBetS0+Pl5VVfXRo0d4ib+/P/4L5Ofnr6iogOUVFRU2NjYSEhIqKiowv3lniouLZ8+e7eLiwqvmDRhUKlVaWvrhw4c1NTVeXl4w7QyvxnnZsmUwmQ8eNuqH/P777/r6+mJiYoqKijCIf3c1y8vLw8LC5s+f7+rqypPWcskPdSOPbzdgd8JQXDYEL+hpnIbly5d3p/d5S3p6uoyMzPv37/GS+vp6mGwSggehq6+vV1dXX7lyZVVVVUZGhoyMTHf5Q2DNnqYoGHSCgoIkJCT6T/7Bgwc56H0mk5mUlGRtbZ2QkIBh2I0bN2RkZBITE5ubm798+WJtbT158mR8zsfG5s2bp06dCgBwdnbGC93d3b29vf/7779+6Mr/McC6ccjZeRAI3sKa8rf/6Ojo2LRpk4eHx5QpU/DC8PDwS5cu4X+2xMREWH7o0KGioiIKhSIrK2tgYODh4eHv79+l1UJCQuLKlSv+/v6sWZeHPkVFRRzya/ad7r5TGo0WHBysrq5+4MABCwsLuNkzISFBX19/2bJlIiIiysrKHh4eeXl59fX1XUq4fPnymzdv2NLce3t7i4qKLliwwMzM7NatWzAz0rAG6X3ECAdGg8jOzp47d66IiIienh6M29HS0nL16tW5c+fu3bsX1iwpKbG2tpaXlxcTEzMyMoJhMAAA+fn5pqam0tLSPj4+ly9fxn1/WYmJicnLy2MNzd/S0nL69GlPT09HR0dcFACAyWTGxMQYGBjIycnBkqVLl9Lp9JiYmC7bb2hoqKurGxAQAA/fv38/ZsyYIbu1MDk5mUAgXLx4saqqCkZMyc/PZx3nefPm4cFUnj59GhAQAD/DJDwAgLi4OF1dXSEhIQ0Njdu3b+OSX7x4YWxsLCoqqq+vz5aTGcOwx48f29raamtrFxcX//HHHy9evNi4cSNMKz19+vSUlJSjR49C++2lS5d8fHxgDvcu4ePjY8tHPXbs2IMHDxYUFHh4eERHR6uqqvr6+n7+/Jl3wzbQDJt9W8MXKpUaFxc32K0YObBl8uOGpqamv/766+bNmxUVFXZ2dkuXLv3333+fPHni7u5eW1v7008/wWpWVlbS0tJv375taGhYsGCBi4sLvNeGDRt8fHwsLCxevnxpZWUF8+iyER0draGhMW7cOLwkMjKSRqMBACgUSlRU1N69e6Gy/vjxI41GY80vOGnSJMDiqdwZU1PT8PDwuro6KSkpDMOgjaKngzAwmJmZYRjm6Oj4559/wmzsV69eZR3nO3fuBAcHnzhxYsmSJXPnzp0xY8Zvv/0WGhq6atUqAMDly5cvX758+/ZtaWlpR0dHGxubf/75Z/r06S9fvly4cOGhQ4fu37+flJS0adMmeLvKysrLly9HRkZKSUk5OztHRUV1Tpju4eHx+vXr/fv337hxQ0dHZ82aNb1IQw8A4OPjs7S0tLS0/PLly6VLl+bNm6epqens7Lxy5crhl2l9wCxK2Gi17w/2Nzwy4f4r2LZtG6t9Pzs7m0AgeHh4YBhGpVIBSyrj6dOnh4WFwc+bNm2Sl5fHvqe9/Oeff2B5SEgIazZ2SGtrq4CAAFsG+fb29tLS0gcPHmzatImfnx8AANdvYTZ52ABIR0cHAGDGjBnddQF6KNy5c4f7Xg8ubGPONs4YhtnZ2REIhJSUFE9Pz3v37sFCOp1OIpE+fvwID6Ez3rp16zAM09XVZc336ezsDAAoLCy0tbUVEhKCuUU5wGQyV61aRSQSxcTEuMnrCZ8inOs0Nzdv2LAB9DxRaJcAZN8fYaB1Xd7Sx4Cpurq648aNy8nJAQDgu/YgmZmZLi4uL1++tLe3v3nzJjTjioiIKCkpzZ8/f+/evaWlpbt27VJUVGSTWVRURKfTx4wZw1ooICBAJpPNzc2vXLmSkpIiKSl54sQJAAAMJC4qKorXhI7LHAziZDIZAMBm3BhGsI0zACAiImLq1KmrV68mkUgWFhawMDc3l0ajaWlpQcvP+PHjAQDv37/PycnJycnBIzMCAPT09OCHkJCQwMDAoKAgIyOj6OjolpaWLhsA882lpqZKSUnBWLB96U5hYaGfn9/EiRMrKiri4uLwTPHDiBGo95F7L4Iz8vLytbW14LvpH6e0tNTc3NzZ2dnc3NzW1hb7bkuJi4uTlpY+fvz4hAkT9u3b13l/Hwzwx7YYyIqxsXFAQEBJSQmdToePjaqqKvxsTU0NAKDz4wQH2i5YLxledA64LSoqun///traWpiKBxbCWCxUKpX1MZ+bmwv30nd+eAAASCSSj49PXl5eYGBgYmKiqqqqh4fHhw8fWOvcvHnzzp07Pj4+xsbG//zzj5aWlpubW0VFRU97wWAwEhISzM3NDQ0NGQxGWlpacnKytbX18DPyjEi9v2vXrl9//bW8vHywG4IYopSVlUGTOiuNjY0mJiZSUlKZmZl2dnasK3vGxsb5+flnzpyRk5M7duzY2bNn2a6F2wCbmpo43NTY2JhMJgsICGhra0tKSuK5H8D3ELN4foLOtLa2AgDExcW57eGQh0qlxsbGUiiUe/fuHT9+HBbCtdbOi2HwTaikpKQ7aQQCwczMLC4uLjc3F273MTExiY2NheMWFhY2e/ZsWJNMJt+9e7elpSUlJYX71paWlgYGBk6YMCEkJGTLli0lJSXBwcFqamo96fHQYgTq/cTERNxDA4FgIyMjo7y83MHBAQAALTnQvP78+fPCwsKtW7fiMVzhPLS1tfXIkSPCwsK7d+/+999/tbS0Oi8sk8lkISEhzlON9PT0X375BQAgKCi4cePGtLQ0+M4BAHj06JGIiAiHxUa4QKqhodHbTg807e3tbW1t+CHrOAMAGhsbnZycwsLCtm7d6ujo6O/vD9c89PT0pKSk9u7de+LEibKysrq6umfPnu3Zs8fAwIBIJF67do3tTQuP1YijoKDg6+ubn59/4MCBhISER48eAQAEBQVZn7KqqqpCQkKdl385EBwc3NTU9OTJk8ePH9vY2AzHCT47A2mZBQO1dhEWFgZ6sp2v/0D7tnhOT/dt+fv7EwgEPz+/8vLy3NxcTU3Nbdu2wVP3798HABgaGjY3N8Pg2xs3bqytrY2Li9PR0eHn53///v3Dhw8FBQUvXLhQW1tbUlKiqamJr/2ysnjx4vHjx+OHdDrd1dWVQqG0trZWV1dHRERs2bIF3yv07du3cePGbd68ub6+PikpSVJS8tSpU/CUpaUliUSCuTNxvLy8iEQiXE/OycmRkZE5duxYD4ZsYKFSqaqqqgCAJ0+ewBLWcabRaAsWLDh9+jRemZ+fX0ZG5vHjxwwG48yZM6zaiZ+fPzU1FcMwFxcXAADcavv582do64fGtx+25969ewCAI0eOVFdXf/361dnZWVtbu62tDetqtJlMZmlpqaCgoKWlZUtLC+9HpxsGTDf+3+0G7E4Y133LycmxsLCQkJAYP378tWvXli1bxo0G//vvv42MjKCDtqenJ6vev3nz5rRp0wQFBdXV1ePj4zEM+/Tpk5eXF4lEKisr27dvn5ycnJKSUlxcHKyfl5cHX/m9vb2joqJw/43Ocn4I0vs8p6d6n8lkRkZGTpkyRVBQUFNTMzw8HOrfP/74A9cvurq6GIZ5e3tLSkrq6OjcuXPn6tWrYmJiP//8c1NTU2ho6KFDh0gk0tixYw8fPtzlVs+rV6+y/uSYTKa9vb24uLiEhISRkdG1a9fY6hcUFCxdulRUVFRTU/PKlSt4ubGxsYqKCr6zFzJ9+nS8JDs7W1paesjqfbaXITU1NbZxxldB4d+K1Z81KSkJw7CIiAg1NTUREZFZs2YlJydDsR0dHX5+fvLy8uLi4g4ODkFBQXp6emFhYbW1tdy0Cv/nKisrOzk5VVZWwvLOow1VB86bN294PEDdMNr1/osXL6SkpM6ePVtTU/PmzZuJEydyM3PPyMgQFhY+ceJETU1NXFwcTNICr4qKijIxMcnPz6+srFy5ciWRSMzMzDQ2Noav8+7u7llZWbW1tSYmJtLS0jAE0MyZM2/dutXS0vL06VM5OTn4A+1Szg+7jPQ+z+mp3h8YGAzGlClTvLy8+i6qsbGR9TeTnZ1NJBJfvXrVd8mIzrCN9mAxqvU+g8HQ1NR0dHTES+Cazw/1fnfuvRw8guGD/cuXL/DUqVOnAABUKrVLf20OcjiD9D7PGZp6H8OwrKwsSUnJ9PT0PsoJCgqCXi4YhrW2thoZGbF6viN4C+toDyIDrPeH1rpuVlbWp0+fcH9e8H2JnzMc3Hu78wgG30N84G4b0J+aTqd36a/NQQ4CAdHX14+NjV27du2DBw96LSQkJMTQ0NDIyAgAUFpaamFhMWnSpGPHjvGumYj/H9bRHlUMLb0PHdo4ODJ3CQf33u48gkFXPsU4nf21OchBIHAsLS0fPnx4+fLlXktwd3fHHTqjoqLgJiMOv1VEX2Ad7VHF0Po9wdl9T7dUcHDv7c4jmDOd/bV7JwcxCpk6deqtW7d4Isrf33/79u08EYVAsDK09L6Ojg6RSExISOjRVRzce7vzCAbf98Lgub3gtR0dHV36a3OQg0AgEMOLoaX3x40bt2XLlujo6NOnT8OUh3fv3v3hVWPHjt2xY8f79+83btz45cuXgoIC6Dq2ePHic+fOBQQEtLW1+fj4jB07VlpaeuHChStWrGhra4PBeFNSUjAMo9PpT58+Bd89jg8fPnzx4sW6urq6ujoMw+bPny8sLNylnH4eDwQCgegHBmwFGeNuzbq5uXnr1q1iYmLKysonT54MDw8HXPjzcHbv7ewRzJrQ8eTJkwYGBqyH3flrd+lZzJmR6s+TmZm5atUqnog6evTo1atXua8/ZP15EIhew41u5OXtBuxOWK/6BiPQDoWdt72jv/X++fPna2pqBljI4GaRRXofMfIYYL0/tOw8nYGRPXArPIKVpqYmtn3tAyAkIyNj+/btiYmJixYtgiUNDQ3nz5/HKyxevBj6yDY0NBgbG7e1tRUVFcXFxfn7+wcHB3cWqKKikpycnJSUhLwVEYiBYUjrfTqdDq3wycnJnYPfIlxcXPoek71HQlAWWQRiJDBgbxZYz99lWM3uHLCysuq/NvcR7u08T58+NTU1FRUVVVBQ2LFjBzS8sMaGxDBs8uTJ8LChoYHNwy81NdXV1XXcuHFUKnX58uWioqK6urpPnz7tkZCGhoZ3797JyckdOXKky0ZSKBQAQElJCV7S3NxMIpHGjx+/bdu2rKwsvJzBYJBIJGNjY7wkIyMDABAYGNjdCOjr63PzVSI7D2Lk0VPd2NfbDdidsNGaZ5Ebvf/o0SMJCYl79+41NDTcvHlTTExs5syZdDq9pqZGS0sLV3NVVVXwWdjQ0IBhWFBQEAAAPiGUlJQAAEJCQv7+/l++fPnw4cOUKVOEhIQ+fvzIvRAMw96+fSsjI3P48OEu22lqaqqhocFacu7cOfyxAcNewnI4c1+/fj1eEwYTZos4xoqHh4eAgMAPI22NPL0/iIvk/cfbt2/Nzc3FxcVJJNK2bdsUFBR4FUvu8+fPfn5+SkpKw3fZrzMDrBuHtJ1nlIBhmKur66ZNmywsLMTFxW1sbPbs2fP69evIyEhpaWkzMzO8pqysLOshK2VlZebm5kQi8eDBg8rKylpaWqGhoW1tbSEhIdwLAQDo6OhUV1fv37+/86m2trb09HRtbW3Wwp07d+JZZPn4+I4dOwaDYH/9+hV8D4YBkZaWBhw35WlqatLp9CdPnnRXYYAJDQ3FQ+T3n5Dbt29bWVnBOMOQAwcOEL4jICAAk7MDAGg0mq2traSk5Pjx4+Egd8be3v78+fOurq59bHYfKS0tNTExcXd3//Lly6ZNm6KioioqKggEAk+E9yKx0tevX8PDwxcsWODm5tZlhfr6+uDg4FmzZomLi3f54+9FzaEM0vuDT2ZmZn5+vq6uLl7i5OQEAICGcra0q6x5oNhQVlYmEom4VWf+/PmSkpKvX7/ukRAOjKossgOzZj5SF8mvXr3KYDCWLl0qLS194sQJ6Ant6+vLE+E/TKyEYVhycrKNjQ2++2fv3r0XLlxISUnBc7+wkp6erqOjExUV5ejomJ2dHRAQ0J3kzjU9PDx8fHw+f/7ctz4NNEjvDz4wuieMAwohk8mioqJlZWU9ktM5iouysjLUvzxhVGWRHYA18xG8SF5UVMThAd93WN8jWaHRaMHBwerq6gcOHLCwsMBjNV6+fPnNmzdd/nSfPXu2cOFCAwOD3NxcZ2fnSZMm8fPzdym8y5re3t6ioqILFiwwMzO7desW9D8c+iC9P/iMHTsWfI8uh8PPzw9zD/QI7HuKakh1dTUMHcoThm8W2dTU1Llz54qJiSkqKu7cuRMaXvj5+aEtBdbR1NSEhzALYExMDABARkaGQCA8e/bMzc1NRUUFBsgUExPT09NLTU3tkRD41GQlJiYmLy9v69ateElLS8vp06c9PT0dHR3fvHmDlzOZzJiYGAMDAzk5OViydOlSOp0O5XfG0NBQV1cXn7e+f/9+zJgxR48e7eMwckNycjKBQLh48WJVVRUcivz8/KtXr86dOxdO0ufNm4dbsZ4+fRoQEAA/X7lyBUqIi4vT1dUVEhLS0NC4ffs2LvnFixfGxsaioqL6+vpsT1MMwx4/fmxra6utrV1cXPzHH3+8ePFi48aNrO+1fHx8nV9zv337tmbNGmNj4+vXr3OY0HCoOXbs2IMHDxYUFHh4eERHR6uqqvr6+g796T/S+4OPvr7+uHHjbty4gasGKpVaX19va2sLAIDJPPFTLS0t4HucUahuWHV9a2srrAAA+PjxY0VFBUxv1CMh3TFMs8gmJSVZWlp6eXlVVFSEhIRcvXp10aJFHR0d3759g8vdkBcvXuD+YxEREazL3evWrQsLC6PRaBcvXrxw4cLr16/pdPqSJUs+ffrEvZDOz7Po6GgNDY1x48bhJZGRkTQarbi4mEKhzJgxY9++fbD848ePNBqNtSbMC//y5cvuem1qanr37t26ujoAAIZh0NLSi9HrKWZmZhiGbdu2TU5ODr6yZGRkuLu7P3v2DDbgzp073t7eAIAlS5bMnTvX09OTRCLFxcXZ2dkBAC5fvhwaGnr79u3S0tIpU6bY2NhkZWXBni5cuHDlypVlZWV+fn5wGz8AoLKy8sSJExoaGj4+PmZmZkVFReHh4VOnTuWytYcPH66qqpo/f/6cOXOEhYWnTp0KM/32tCYfH5+lpeX9+/czMjKEhITmzZu3aNGi+Pj4oTv9H7AVZAz583QP9FFZsWJFaWlpWVmZhYXFkiVL4H81MjISAHD27NnGxsZLly7Nnz8fACArK3vp0qWLFy8CAJKSkiIjI6lUqrOzM4FAcHJyqqqqKigoMDIymj17dnt7e4+EcE7fOmBZZH84Vj8cUgiTyVRXV3dzc8NLDh48CAAIDw/HMGzXrl2soqCe7dLNydzcXEREpKOjAx7CxeedO3f2SAgrra2tAgICq1evZi1sb2/HF8mhtQFucoYqxsPDA68J7dQzZszoruNwo/udO3e4HCjewqr3MQyjUqkAANbsMXZ2dgQCISUlxdPT8969e7CQQ3aj7hIr2draCgkJUSgUblolJSXl7OyMHzIYDHl5eTKZHB8fX19fn5WVpaqqKiws/N9//7FdyH1NSHNz84YNGwAAt27d4qZhGPLnGZ3Y2NjEx8cXFxdPnDhxzpw506ZNS0hIgDNxOzu7NWvW+Pr6GhgYqKmpLVy4cM6cOSdPnly3bt3atWsNDQ03bNggJiYGjUXQbV9dXV1PT2/ixIkPHz6EM33uheC/wi5xcHAoLi7Gzcp8fHx1dXUeHh7y8vKWlpbi4uJRUVG40UNOTi41NfXr16+Kioq7du0KCQmBrwIAgJqaGmFhYagWcR4/frx06dKeZl/gzJBdMx9Vi+Sdc2NERERMnTp19erVJBIJz7PUXXYjDomVQkJCAgMDg4KCjIyMoqOj8ZddbigvL6+srJw3b56VlZWEhIS+vv6pU6daW1tZXZN7WrOwsNDPz2/ixIkVFRVxcXF4MuGhRtcrGIiBx8rKysrKqnO5iIgIq5Vz3rx5+Ou/mJjY33//zVbfxcWF1Smwp0J0dXXhAmyXbNiwISgoKDw8HOojAoEA84l3x4QJEx4+fNi5/Pnz501NTZs3b8ZLcnJysrOz4d4uHjJk18y5XCT/5ZdfRsAieefRExUV3b9/v42NTVpampeXF5wr4NmN4CQG58aNG6CbxEokEsnHx8fb2/vx48cRERHe3t7r1q1zdnZmXSrvjoaGBgCAhIQEXmJpacnHx5eXl9fTmgwG4/79+xcuXMjOzobmTTU1tR82YBBB8/2RA4PB6O9ARkQiMTY29uLFi31X0OfPn9+9ezf83NbW5urq6uXlNWvWrD638X8Ysmvmw3eRnCdQqdTY2FgKhXLv3j2YQxt0nyWJQ2IlCIFAMDMzi4uLy83NVVJSWrFihYmJSWxsLByE7hg7diw/P39hYSFeIiAgICUl1flpyqFmaWlpYGDghAkTQkJCtmzZUlJSEhwcPMSVPkB6f8RQV1eXmZnZ2toKjeb9d6PhlUV2yK6ZD9NFci5pb29va2vDD+HyJu47D52dwsLCtm7d6ujo6O/vDxcwustuxCGxEtt9FRQUfH198/PzDxw4kJCQ8OjRIw6NlJCQMDc3T01NxV/+ysvLq6urOxtnONQMDg5uamp68uTJ48ePbWxs4I9hGDBgKwkYWtftN9gsM5GRkf19x9zcXF7169ChQxEREdzX72mchqGzZs7WsAFbJOe8Vs9zqFSqqqoq+J7FCMOw+/fvAwAMDQ2bm5tpNNqCBQtOnz6NV+bn55eRkXn8+DGDwWDb5sbPz5+amophGDRd2tnZlZSUfP78Gdr6YRJsbprEZDJLS0sFBQUtLS1bWlrw8ry8PFlZWRMTk+Li4i9fvixevHjRokXwFNuocqjJEwZYNyK937+M1Lwrg0gv4vPEx8dDl3AVFRU/P7/W1lZY3tzcvGbNGmFhYW1t7ZSUlCNHjsyZM4dCoTQ2NlZVVRkaGsrLy1+7dg3DMGdnZzExsbCwMFlZWUlJSQcHh6qqqp4KYQMujeBBZphMpr29vbi4uISEhJGRUedLCgoKli5dKioqqqmpeeXKFbzc2NhYRUWFLfDR9OnT8ZLs7GxpaemtW8m6AAAgAElEQVSB0fvp6emsiltNTQ0mv4Po6uris2n4TFq4cCF+NikpCesmuxHnxEo/xNPTk7VVb968wU+9f/9+8eLF4uLiCgoKu3fvbmxshOWdR7W7mjwB6f0RBdL7PGdQ4rJBvc9bmQwGY8qUKV5eXn0X1djYyPozy87OJhKJr1696rvk0QzbqPYrA6wbkX0fgfgx/bFmPuwWyUcbrKM6wkB6H4H4Af23Zj68FslHFayjOvJA/vsIBCdqa2tlZGTgZ1NT08jISEdHRx7Kt7S0VFVVPXTo0LJly3onwd3dHf8cFRVlY2PDlk4H0QtYR3XkgfQ+AsEJaWlp3s7xOzN16tRbt27xRBRrgnsEojuQnQeBQCBGF0jvIxAIxOgC6X0EAoEYXSC9j0AgEKMLpPcRCARidIH0PgKBQIwuBtqPky18x4gHZhrqHFoW0WvgTwgNKQLRewYsIkR/O0EjEAjE8GUg4/MQkDpGjE4IBMLNmzdtbGwGuyEIxECD7PsIBAIxukB6H4FAIEYXSO8jEAjE6ALpfQQCgRhdIL2PQCAQowuk9xEIBGJ0gfQ+AoFAjC6Q3kcgEIjRBdL7CAQCMbpAeh+BQCBGF0jvIxAIxOgC6X0EAoEYXSC9j0AgEKMLpPcRCARidIH0PgKBQIwukN5HIBCI0QXS+wgEAjG6QHofgUAgRhdI7yMQCMToAul9BAKBGF0gvY9AIBCjC6T3EQgEYnSB9D4CgUCMLpDeRyAQiNEF0vsIBAIxukB6H4FAIEYXSO8jEAjE6ALpfQQCgRhdIL2PQCAQowuk9xEIBGJ0gfQ+AoFAjC6Q3kcgEIjRBdL7CAQCMbrgH+wGIBADRERERE1NDWtJQkJCYWEhfrhlyxYSiTTg7UIgBhoChmGD3QYEYiBwdnaOiIgQEhKChxiGEQgE+Lmjo0NKSqqiooKfH82EECMfZOdBjBbWr18PAGj7Tnt7O/6ZSCRu2LABKX3EKAHN9xGjBSaTSSaTKyoqujz7999/GxoaDnCTEIhBAc33EaMFIpFob28vKCjY+ZSSktJPP/008E1CIAYFpPcRo4j169e3t7ezFQoICGzatAm39SMQIx5k50GMLiZNmvT582e2wpycnGnTpg1KexCIgQfN9xGjC3t7ewEBAdaSSZMmIaWPGFUgvY8YXdjb29PpdPxQQEBg8+bNg9ccBGIQQHYexKhDV1f37du3+C8/Pz9/0qRJg9skBGIgQfN9xKhj48aNfHx8AAACgTBjxgyk9BGjDaT3EaOO9evXM5lMAAAfH9/GjRsHuzkIxECD9D5i1EEmkw0NDQkEApPJtLa2HuzmIBADDdL7iNGIg4MDhmFz585VUlIa7LYgEAMOxiNu3rw52F1BIBCIEcvatWt5pa55HIgKaf/BxdbWdvfu3SjkADecOXPGyclJTEzsh9UAAD///POANAqB6Br4O+QVPNb7NjY2vBWI6BG2trY//fQT+ha4wcjIaOzYsT+sduvWLYB+2IjBBv4OeQWy7yNGKdwofQRiRIL0PgKBQIwukN5HIBCI0QXS+wgEAjG6QHofgUAgRhdI7492qqurlZWVg4KCBrsh/0NWVtbq1at5IurYsWOxsbE8EYVAjAyQ3kcADMP6NdtUaGhobW0t9/Vv375tZWXl4uKClxw4cIDwHQEBARqNBstpNJqtra2kpOT48ePDwsK6lGZvb3/+/HlXV9e+dAGBGEnw2H8fMeyQlZUtLS3tP/lNTU1nzpyxt7fnsn5GRsb27dvT0tKmTJkCSxoaGs6fP49XWLx4MYlEguXGxsZTpkwpKirKz883NzdvbGz08fFhE6iiopKcnDxjxoxjx475+fnxok8IxPAGzfcR/YuLi0tBQQGXlTs6OjZt2uTh4YErfQBAeHj4pUuX8C3miYmJsPzQoUNFRUUUCkVWVtbAwMDDw8Pf37+oqKizWAkJiStXrvj7+797967PHUIghj1I749qWlparl69Onfu3L179wIA/v33X29vbwUFhfLy8v37948ZM4ZMJsONgllZWW5ubioqKqWlpRYWFmJiYnp6eqmpqQAAfn5+aIGBMjU1NeFhY2Ojk5NTTEwMAEBGRgaWvH//fsyYMUePHu2yPTExMXl5eVu3bmVt4enTpz09PR0dHd+8eYOXM5nMmJgYAwMDOTk5WLJ06VI6nQ5v1xlDQ0NdXd2AgIA+jxkCMexBen9UEx8f7+7u/uzZMwzDAACOjo6nT5+m0WjHjx+3srL6/PnzpEmTnJycOjo6LCwswsLCaDTaxYsXL1y48Pr1azqdvmTJkk+fPn379k1LSwuX+eLFCwMDA/g5IiICrhjX1NRgGCYuLo5hGJPJxLrJ8hYdHa2hoTFu3Di8JDIykkajFRcXUyiUGTNm7Nu3D5Z//PiRRqOx1oTpU16+fNldZ01NTe/evVtXV9fr4UIgRgaDrPcvXbr07Nmznl61Y8eOb9++wc8XLlyQkJCYPXt2Y2NjHxvTT2KHMg4ODqymj+fPn+/evRsA4OXlpa+vLyUltWrVqtra2oqKirKyMnNzcyKRePDgQWVlZS0trdDQ0La2tpCQEGlpaTMzM1yIrKws6yEbOjo61dXV+/fv73yqra0tPT1dW1ubtXDnzp2lpaUPHjzYtGkTHx/fsWPH4Prt169fAQDQ0A+RlpYGAFRUVHR3a01NTTqd/uTJEy4GBoEYyQym3mcymSdPnjx58mSPrkpISLh48SKrEAzDGAxGHxvTT2KHPvLy8qyHUJMKCwvDQ1FRUQAATESurKxMJBJhhkIAwPz58yUlJV+/fg0AEBQUZBWCX94jioqK6HT6mDFjWAsFBATIZLK5ufmVK1dSUlIkJSVPnDgBAGhvb8ebB4FfFltLWCGTyQAA7hcbEIiRymDq/T///DMvLy8xMfHjx49cXvLs2TMHBwfWEhcXl8bGxszMTHFx8V63pJ/EDguIRCKHQ86nlJWVof7lCfDVSkhIqLsKxsbGAQEBJSUldDpdUVERAFBVVYWframpAQDA8i6BIZdZL0EgRieDqffhqiCGYV1O+VNTU42NjUVFRRUUFBwdHRsaGn7//fdFixY1NDQAAOTl5QkEwrx583C37tbWVh0dHfxwzpw5AICAgAB4GB8fDwCIjY01NjYWFxeXlpa2srKCtoIfioXtuXv37owZM0RERJSVlX/55ReopG7cuIHXDA8PNzMzk5KSmjx5clpa2gAN4sDCZpevrq4eP348r4TLysoCAJqamjjUMTY2JpPJAgIC2trakpKS+fn5+Kn//vsPAGBqatrdtfCrHPEPcgTihwya3k9JSbGzs5s5cyYA4Pfffy8rK2M9m5aWtmjRIn5+/uLiYmlpaQqFsmfPHjs7Oy8vL1ihsrISw7BHjx4tW7YMv+revXvq6urw8+3btwEA/v7+K1euvHjx4urVqw8fPuzg4BAcHFxQUKCionLnzh2YW/WHYgEAf/7556pVq5qamoqLiw8dOnTmzJm5c+fS6XQbGxtvb29Y59mzZ7GxsbNmzcrLy9u2bVt/DFp/AG04HR0d8BAqR9zABfOPs55taWmBnz9+/FhRUbFy5UoAgICAAPg+YQcAwDqVlZUAAOjn091CLitkMllISKi8vJxDnfT09F9++QUAICgouHHjxrS0NHxH2KNHj0RERDjky4WLNxoaGj9sCQIxshk0vZ+UlDR79uzt27cDANrb20NCQljP7tmzh06nOzo6ysvLu7m5iYiIdPn+LigoOGHCBPxwwoQJFy5cgJ/j4uIAAAwGQ0ZGxsnJiY+PLzQ0FACQlpZGIpGMjIwAAOnp6V22jU0sg8Hw8PDAMMzS0pJEIm3cuFFAQCArK4tCoRCJRLymr6+voqKivr4+ACAvLw9/URjiwHXO9PT0lpaWtrY2+KaSkpKCYRidTn/69CmsAxU3hmG7d++urq4uLCzcvn37rFmzoH1MTU0NAEChUJqamigUChzYmTNnUigUGRkZAEBmZualS5dKS0tzc3NlZWW7DAshJCQ0d+5cVqNfR0eHm5tbVFRUW1tbTU1NZGRkdnY21PsAgICAAEVFxZ9//rmhoSE5Ofns2bNHjhyBUfVXrFihoKDA9tb1/v17IpFobGzcD6OIQAwnBkfvZ2dnQ02xYcMG+N594cIFaGkBAHz58gV648GFuF27djU3NwcGBnIjecGCBdOmTQMAREVFAQD+3//7f1ZWVvDUmjVrxMTExo4di2EYdOZjMBjcrNzm5OSUlJQAAGAObn5+fikpKQDAvXv3OlfGlz2bm5u5afDg8ueff1pYWAAAXrx48dNPPy1ZsuSvv/4CAKxfv/7UqVMmJibQed/Z2Rl60YiKiurq6qqrq+vp6U2cOPHhw4dwpm9nZ7dmzRpfX18DAwM1NbWFCxfOmTPn5MmT69atW7t2raGh4YYNG/DB5zD3d3BwKC4uxvde8fHx1dXVeXh4yMvLW1paiouLR0VF4RsF5OTkUlNTv379qqiouGvXrpCQEPyRUFNTIywszPZ0efz48dKlSzksACAQowVeJeqFmXW5rOzs7NzY2Ag/Ozo6wpb8+uuvsATOMQEACQkJbBfi7tvQIINhGB53paWlBZZcunQJlvzzzz/79+9nMBj45QwGIzo6es6cOdOnT4d16HT6D8Xev38ffg4LC4NnoQ/MzJkzMQz77bff4Nk3b95gGIbHCcBFDSQAgJs3b/aTcGdnZzExsX4SDmEwGFOmTPHy8uq7qMbGRtY81NnZ2UQi8dWrVz2Vs3btWh7ms0Ygegdvf4eDMN8vLCy8dOmSuLg4XA7F1fTZs2ehrRlfecvMzOyFfDs7O+gL+Ntvv0HXQ1ien58/c+bM3bt3R0VF9SjzOO7piJu5oROLsrJyL5o3fOHy9agvEInE2NjYixcvZmRk9FHU+fPn4V4EAEBbW5urq6uXl9esWbP63EYEYtgzCHr/6NGjaWlp+JOHwWBMnToVAEClUq9fvw4AmDZtGvQiv3r1Kq5q29raAIsVhQPCwsJOTk4AgBs3buCrfBiGWVhYvHnzZvfu3aybSyGcxU6fPh0aB+DCYHt7e319PQBg0aJFPer4sKauri4zM7O1tfX58+cYF4u0vUZfXz82Nnbt2rUPHjzotZCQkBBDQ0O4igMDS0yaNOnYsWO8ayYCMYwZUL1fXl6+b9++jIwM1j2ZRCLR398ffnZ3d3/48CGRSISW2cLCQicnp+rq6tzcXLhbR1VVFdb88OHDr7/+2tjYiNuC8/LycJkuLi78/Pzr1q2DroEAgMrKSljhy5cvRUVFd+/eheXQ0M9ZLD8//6lTpwAACQkJlZWV4eHhGIZpa2s7Ojoymczi4mJYs6ioiMFg4IeFhYU8GrbBp7a2VlpaGobHMTU1pVAo/Xo7S0vLhw8fXr58udcS3N3dcYfOqKgoGxubK1eucNiaMHoYFokN3r17t2zZMgkJCejDraioyKv8EAUFBfv27SOTyV3G7xtF8MpgxI19f/Lkyfh9b926BQs7B0bft28fhmFXrlyZPHmyoKAgnKlBQ3x7e/uWLVtERUU1NTWfPXvG5i7JalJft25dVlYW69137NghJiamo6Nz/PjxuLg4eXl5eXl5Dw8POp3Ojdi4uDg9PT0hIaExY8Zs2bKloqICwzD4goKD2/ohsM0DCehP+/7oZGDs++fPn4chjPpVSHx8vKqq6qNHj/ASfMoFAODn54e/agzDKioqbGxsJCQkVFRUQkNDu5RWXFw8e/ZsFxeXPjabDSqVKi0t/fDhw5qaGi8vL7iMHxQUxBPhy5Ytgzu6CwsLubzk999/19fXFxMTU1RUtLOzKykp6a4mN4PWa3j7OxycdV1EP4H0Ps8ZAL3f2Ng4ceLEPur9HwpJT0+XkZF5//49XlJfXw+DGkGWLVuGl6urq69cubKqqiojI0NGRub48eNdyoQ1jx492peWsxEUFCQhIcFDgWwcPHiQg95nMplJSUnW1tbQqeTGjRsyMjKJiYnNzc1fvnyxtraePHkyDOLCRneD5u7u7u3t/d9///Wx2UjvI7oF6X2eMwB6f+PGjeB7yNJ+EkKn0zU0NAICAlgLjx8/Hh8f37nynj17BAQEvn37Bg8DAgIEBAS6U5R///03kUh8+/ZtXxrPirOzs5ycHK+kdQZ6JHfuTkVFxfHjx9XU1H766afo6GjoH7h+/foFCxbgddLS0ggEQm1tbWex3Q0alUoNCAhQUVFZuHBhXFxce3t775qN9D6iW5De5zk9/b89ffrU1NQUxhfZsWMHVMS44wCsgxs8Gxoa4NZFnNTUVFdX13HjxlGp1OXLl8MNE0+fPu2RkIaGBrZWwSUZVhtFc3MziUQaP378tm3bWC2iDAaDRCIZGxvjJdC3KjAwsLsu6+vrW1lZwc/v3r2Tk5M7cuRId5U59CIpKYnN5JuXlxcTE2Nqaurr64th2Ny5c/FTKSkpcOYOALh8+TKUdvPmzWnTpgkKCqqrq7M+0v7++28jIyMRERE9PT1PT09Wvc9kMpOTk21sbMaMGbNz587c3FzW1p48eZJAIBw5cqSjo4PJZG7evBm2hI0fDlpHR8fdu3eXL19OJpN9fHx6Mf1Heh/RLUjv85we/d8ePXokISFx7969hoaGmzdviomJzZw5k06n19TUQC8yWK2qqgqmKIAKmjVFAdwbKCQk5O/v/+XLlw8fPkyZMkVISOjjx4/cC+mMqamphoYGa8m5c+dwHUogEPz8/GA5jMu9fv16vCZ0Y8OtQJ3x8PAQEBCAs+C3b9/KyMgcPny4u8qce4Fh2LZt2/D5fkxMDLRE+fj4wMowLMqSJUuYTGZ9fT2JRMIn0VFRUSYmJvn5+ZWVlStXriQSiZmZmRiGZWRkCAsLnzhxoqamJi4uTkREBOp9Go0WHBw8adKkGTNmRERE4DuKWGlvb7e1tQUA6OjorFu3Li4urstOcT9oJSUlBw4cUFZWNjMzu3XrFvfTf97qfZRfd6TRXfAJRO+gUqlcbtTAMMzV1XXTpk1wC7SNjc2HDx8CAwMjIyN37txpZmaGh6CAKQq6TBFTVla2bNmyp0+fHjx4EE6NQ0NDFyxYEBISAgP/cSOEDZjYALYKZ+fOnWvXrs3Jybl58+bvv/9+7NgxMpns6ural8QGq1evhvkVODQGZmvgshcODg4LFizAx19WVjY4OLi0tPTatWupqan379+nUCiwXx0dHb6+vqmpqTD9TkhISEJCwsmTJ69fv+7s7Dxv3jwYg8va2vrx48cw4vquXbv+/PPP8PBw1vxubAgICFy/fr2tre3u3buFhYX45n82uB+0cePGBQYG+vr6Ojo6Wltb37p1a+3atRyGq59Aen+kcfbs2bNnzw52K0YUXP4zMzMz8/Pz8Th9AAAnJ6fAwMDExMSdO3dyn6KA53kOOCQ2gLkNHB0dly9ffuLECVdX1wFIbNCjXrDlhwAAREREvH37dvXq1Xv37sUfZrm5uTQajW1rzvv373NycnJycjZt2oQX6unpwQ8hISH6+vpBQUEUCsXJycnGxga+CrBx5MiROXPmeHp62tra2tjYREVFbd68ma0O94NWWFgYGRl5+fJlbW3tuLg4GNZw4BkVHs3V1dXKysq8cgHuD4E8BNl5eAv30zG4dYM1LhOZTBYVFWWLNftDeJ7nYFgnNug8GqKiovv376+trYXbP2EhDP5KpVJZv7vc3Fz4YtH54QEAIJFIPj4+eXl58Nmsqqrq4eHx4cMH1jo3b968c+eOj4+PsbHxP//8o6Wl5ebm1nkW/8NBYzAYCQkJ5ubmhoaGDAYjLS0tOTnZ2toahrcaeEas3g8NDcUj9AIAMAzD43kNEYEcaGtr8/f3nzBhgpiY2NSpU3/77TesP7fIIngCDAXKlkSIn59/4sSJPRWF8TTPwQhLbEClUmNjYykUyr17944fPw4LYahEGIWXFTjjhnEVu4RAIJiZmcXFxeXm5iopKa1YscLExCQ2NhZ2KiwsbPbs2bAmmUy+e/duS0tLSkoKmxAOg1ZaWhoYGDhhwoSQkJAtW7aUlJQEBwfDqJSDyMjU+01NTWfOnMEPZWVlS0tLfX19h45Aznh6ek6cODEnJ+fTp08zZ850cXHBw70hhiz6+vrjxo27ceMGnoeASqXW19fDhcEepSjgbZ6DoZbYgEMvAADt7e0wKAuELT9EY2Ojk5NTWFjY1q1bHR0d/f39k5OTAQB6enpSUlJ79+49ceJEWVlZXV3ds2fP9uzZY2BgQCQSr127BjNJ4OC3w1FQUPD19c3Pzz9w4EBCQsKjR4/gaLBqc1VVVSEhIfh+wwqHQQsODm5qanry5Mnjx49tbGwGa4LPDq9eh4eUPw9PHKL7VSAHaDRaTEwMfshgMLS0tJSUlLi5FiA7D6/pkR8F/BesWLGitLS0rKzMwsICep5gGBYZGQkAOHv2bGNj46VLl+bPnw8AkJWVvXTpElxmTEpKioyMpFKpzs7OBALBycmpqqqqoKDAyMho9uzZ0PGDeyFsDVu8ePH48ePxQzqd7urqSqFQWltbq6urIyIitmzZgm9H+vbt27hx4zZv3lxfX5+UlCQpKXnq1Cl4CqaggDGacLy8vIhEYnl5OYZhOTk5MjIyx44d4zBKHHpBpVJh0BSY8gHDMBgN19DQsLm5mUajLViw4PTp0/AUlUrl5+eXkZF5/Pgxg8FgnZkBAPj5+VNTUzEMc3FxAQDArbafP39evHgxAEBaWrq7zWiswFjrR44cqa6u/vr1q7Ozs7a2dltbW+eh4DBoPGHY+3Hm5ORYWFhISEiMHz/+2rVry5Yt++Ge6eLi4rVr144ZM0ZUVNTQ0JDV3fjBgwezZ88WFhZWVVU9d+4chmFsvsxQjeIuwKyxIj5+/IixZHm8detWlzfiLBDSpdf2p0+fvLy8SCRSWVnZvn375OTklJSUunMF48CaNWsMDAy4qYn0Ps/p6f8tPj5eV1dXSEhIRUXFz8+vtbUVljc3N69Zs0ZYWFhbWzslJQWuFlIolMbGxqqqKkNDQ3l5+WvXrmHf412HhYXJyspKSko6ODhUVVX1VAgbV69eBf/rtG5vby8uLi4hIWFkZNT5koKCgqVLl8LIJVeuXMHLjY2NVVRU2NwTp0+fjpdkZ2dLS0tz1vvd9QLO3HHU1NT++OMP/FBXVxdfBYXPmIULF+Jnk5KSMAyLiIhQU1MTERGZNWtWcnIyvF1HR4efn5+8vLy4uLiDg0NQUJCenl5YWFiX2686g+8JUFZWdnJywoPBdB6K7gaNJwxvvf/ixQspKamzZ8/W1NS8efMGmj5/qPdnzpxpZmZWXl6el5enrKw8Z84cWH79+nUlJaVnz541NzfDOD/Xr1/H/teXmc0FmEajzZs3DwBw7949KITJZLq5uUVGRjKZzO5uxEEg1r3XtrGxMfTKcHd3z8rKqq2tNTExkZaW7mncHi0trYiICG5qIr3PcwY+/n5/5DkYgokNRgBsQ9GvDOP4+0wmc+vWrdbW1h4eHtLS0np6ejBgMjcXrl69WlFRUV1dfeHChZ8/fwYAtLW1ubu7BwQEmJiYiIiI7NixQ1ZWtvPilYODA9xVAZGXlz9//jz47nILACAQCI2NjY6OjgQCocsbcRaIsXhti4uL29jY7Nmz5/Xr15GRkc+fP4ch4L28vPT19aWkpFatWlVbW8vBFbozaWlp/Pz8HFyMESOM/shzgBIb9AesQzG8GFC9n5WV9enTJ9b9I3AV/odkZma6uLi8fPnS3t7+5s2bcKnn1atXlZWVM2bMgHV0dHSqqqq6TGjO5sWlo6OzcOFCPBNvVlbWnDlzONyIs0Dota2rq4uXwIdZYmIi+L6VA/dQhh6+3YntDJ1O9/Pzu3btGjeJB0YqwyJ0MK/ovzwHKLEBb2EdimHHgOp96NvUiwSnpaWl5ubmzs7O5ubmtra28P9Ao9FAV+vynensArx79+7MzEy4tfX69ev29vYcbsRZIGev7T7GfN+zZ4+np6eOjk5fhPAKNk/WgRFy+/ZtKysruDQHOXDgAOE7AgIC8GcAAKDRaLa2tpKSkuPHj4extzpjb29//vz5zqG/hwj9necAJTbgIaxDMewY0C8Mzu57ZOUAADQ2NpqYmEhJSWVmZtrZ2eFzZ+iVDBesesry5cvV1dVDQ0Pr6upERESgY1Z3N+IMD7222Thz5sy8efPwtSzezv56Cpsn68AIycjI2L59e2JiIp7arKGhAZrpIIsXL4ZvVA0NDcbGxm1tbUVFRXFxcf7+/sHBwZ0FqqioJCcnJyUlDc0pqrS0NKsRFk89zUOmTp1669Ytnojy9/dnc3lADBcGVO/r6OgQicSEhIQeXfX8+fPCwsKtW7eyRvIDAMyaNUtMTOz69esHDx6sqKhoaGhITEw8dOgQ6OTLzOYCDCu4u7vHx8efOnUK33Xd3Y04C+TstQ13f+DmWuhEzNqS7rhx48bMmTOhfYNOp6emph45cqRH48ZbXFz+P/buO6CpK2wY+EnYe8mQJYpSFBRwQRlOFLEuFHAguFAcCLbKUERxMcRVFCoIuKhKRFtXfasgolRoK4go1YKyZAjKkA0hud8f5+398gaIAQIB8vz+Iic3J+eehCf3nrmV+4n4PMmkvb19zZo1np6e48aNIxMjIiKio6PJyIgb0xBCBw8eLCwsjImJUVRUNDU19fT09Pf373RPJRkZmQsXLvj7+7N20gAgWHjVQczleJ4NGzYICQkdP368qqoqMzPT1tYWfW08T1ZWFkLIxcWltraWRqMZGhoKCwvn5OQkJyeTs/UwWVlZvK0E21hm1iHAZLb19fXy8vILFy7k5o04Z9jVqO2WlhYbGxuE0NWrV5lMZltbG578EhkZ2enWDaRDhw51/KT+53/+56vVi7gbzzNA1grmvGZvvy0dzFn/j+cBoKPBPY6zqalp/fr1UlJSmpqaoaGhERERX437BEF4e3vLysoaGrcy54wAACAASURBVBrevHnz8uXLUlJS33//PYPBIAji1KlTWlpa0tLSc+bMIWMB61hmtiHArNnu3Lnz999/5+aNvpphp6O2WZcLDw0NxevNYqdPn+7qZI8dO9Yx6EtKSpIjwTngJu4PnLWCOa/Z229LB3MGcR8MBIM77rPBG9Jyv9cl4OyrcZ/JZI4ZM8bd3Z1MwZtX4M3it2/fzvoh+vn5dRWybW1tJSQk2tvb8cNHjx4hhLZs2dKtTDhoaWkRERGxs7NjTWxraystLf3tt9/WrFkjLCyMEMK7mOL5Pp6enuSRuCVt0qRJXeWPv3g3b978akkg7oOBYBCP3+8IN5TzfLQy6ArnUad8XCuYDYelg21tbS9cuJCcnCwrK3v06FHUnVVwSd1dOhiAoYSfcZ9Op6empiKEEhMT2VZNAn1kwK4VzGZQLx0MwADHz7hvZWWF103dvHmzkJAQpQt82Y+mT719+7ark+3r8x2wawWzGWJLBwMwoPAz7qenp3PTFJWQkMDHQvYFfX19fp3vgF0rmM1AWzoYgKFEECfaCTIxMbFjx47V1tY6OTmVlZWVl5dv2bLFxsYG32Tg7SBiYmIaGxtjYmLwfObJkyfHxMQoKCgghDIyMqKjo0tLSxFCBEHs2LGjurq6oKBg48aNU6ZMcXZ27lYm2dnZioqKnW5bJiYmNn36dNb7kvb2dnd399jY2NbW1pqamnPnzmVlZeG4jxAKCAhQU1P7/vvv6+vrExMTT506dfjwYXxzs2jRIlVVVdyiSMrJyaFSqZaWln1QxwAMdBD3BY6jo2NCQkJRUdGoUaPMzMwmTJhw69YtfCXu5OS0dOlSX19fU1NTXV3d2bNnm5mZhYaGrlixwt7e3tzcfNWqVVJSUjie4mH7Y8aMMTY2HjVq1P379/GVPveZ4Pubrsrp7OxcVFREzr0SEhL68uWLp6ensrLywoULpaWlY2NjyS3PlJSUUlJSPn78qKamtn379rCwMPInoaamRlxcnO3XJSkpad68eT1YMgSAoaCX44FIA2rfFYGF+msd5r5YK5jNAFk6GMZxgoFgSI3jBINUX6wVzAaWDgagj0DcB93Wd2sFs4GlgwHoCxD3Qff09VrBbGDpYAB4TpjfBQCDDF4ruD/fkbdLB/MkHwAGNbjqAQAAwQJxHwAABAvEfQAAECwQ9wEAQLDwuF+Xw4oooH+cPHmSV72gACGEZw/AFxvwV3p6upmZGa9yo/BqbEZaWtqJEyd4khUA/eDVq1fa2tpycnL8LggAXPn222/J1Ud6iWdxH4DBhUKhxMfHOzo68rsgAPQ3aN8HAADBAnEfAAAEC8R9AAAQLBD3AQBAsEDcBwAAwQJxHwAABAvEfQAAECwQ9wEAQLBA3AcAAMECcR8AAAQLxH0AABAsEPcBAECwQNwHAADBAnEfAAAEC8R9AAAQLBD3AQBAsEDcBwAAwQJxHwAABAvEfQAAECwQ9wEAQLBA3AcAAMECcR8AAAQLxH0AABAsEPcBAECwQNwHAADBAnEfAAAEC8R9AAAQLBD3AQBAsEDcBwAAwQJxHwAABAvEfQAAECwQ9wEAQLBA3AcAAMFCIQiC32UAoD/MmTPnzz//JL/wra2tIiIiVOr/XvqIiIi8fPlSS0uLfwUEoJ8I87sAAPQTW1vbxMRE1hQ6nY7/oFAoEydOhKAPBAS08wBBsWLFCvLqno2QkNCaNWv6uTwA8Au08wABMm3atD/++IPJZLKlU6nUsrIyVVVVvpQKgH4G1/tAgDg7O3dMFBISmjFjBgR9IDgg7gMBYm9vLyQk1DG9098DAIYqiPtAgCgoKMyZM4ct9FOp1CVLlvCrSAD0P4j7QLCsXr2atX1fWFh4/vz58vLyfCwSAP0M4j4QLIsXLxYTEyMfMpnM1atX87E8APQ/iPtAsEhKStrZ2YmIiOCHYmJi3333HX+LBEA/g7gPBM6qVavwjC0REREHBwcJCQl+lwiAfgVxHwgcGxsbWVlZhBCdTl+1ahW/iwNAf4O4DwSOiIjIypUrEULy8vKzZ8/md3EA6G+8X58nLS3tw4cPPM8WAB5SU1NDCE2dOvXmzZv8LgsAX+Ho6MjjHAles7e353ERAQBAgPE8SvfJepz29vbXr1/vi5yHEgqFEh8fz/tfcgHm4OCAEOLyu3f69Gl3d3cKhdLHhQKg52g02vLly3meLbTvAwEFQR8ILIj7QEBB0AcCC+I+AAAIFoj7AAAgWCDuAwCAYIG4DwAAggXiPgAACBaI+wAAIFgg7gMAgGCBuA9AD1VXV2tqagYFBXE+LDc318fHR1VV9ePHjz1+r8zMTDs7ux6/nOcCAwPj4uJ69trXr1/Pnz9fRkZGVVXV1dVVTU3tq3XIpfz8fD8/P3V19cLCQp5kOFRB3Aeg5wiC+Or8Lzc3txMnTlRWVnZ1wJkzZ2praznkcOPGjWXLlm3dupVM2bdvH+U/IiIiZOaVlZXLly+XlZUdMWJEeHg49yfy8ePHiIiIWbNmubu7sz3VaZ6rV68+ffr0tm3buH8LrLS01MrKysPD48OHD2vWrImNja2oqODVHLrt27cfO3asvLyc+5dcuXJl4sSJ0tLSw4cPX716NYc1JTlU0eDD8xV/7O3t7e3teZ7t0IMQio+P53cphpQB+93btWsXQqi8vLzjUw0NDaNGjaqpqenqtWlpaQoKCjk5OWRKXV0d64bA8+fPJ9PHjBmzePHiqqqq9PR0BQWF4OBgLku4du3a8ePHI4Tc3NxY0znkiZ86cuQIl2+BBQUFycjIdOsl3bJ//36EUEFBQafPMpnMhw8fOjg43Lp1iyCIa9euKSgo3Lt3r6mp6cOHDw4ODt988w2Tyez0tZ1WkYeHh7e397t37/rgVAiCIOLj4/siSkPc55sexP2qqioNDY3AwMA+KlLPZGRkLFmyhCdZHTly5PLlyz1++YD97oWEhHQV911cXBBCXcV9Op2up6cXEBDAmhgcHJyQkNDx4F27domIiHz+/Bk/DAgIEBER6SoCdtTe3i4mJsYW9znn+ccff1Cp1FevXnH5FgRBuLm5KSkpcX98d+E7ko5nXVFRERwcrKur++233168eLG5uZkgiJUrV86aNYs8JjU1lUKh1NbWdpV5xyoqKSkJCAjQ1taePXs2jUZra2vj7en0UdyHdp5BhuCiYaE3vtrmwIa3TRA9bj3oAR0dHVzIJUuWvHv3jiwzXpqfTMGX6jQazcjISExMTE9P78aNGwih5ubmy5cvT58+fffu3WSev/zyy6RJk2RkZKZMmfLnn3+S6VQqFSHU3t7u5+enpKSkoaHxyy+/IIQ2bdp06dIlhJCCggKFQmloaGAr5KVLl3Jzc9evX0+mNDc3nzhxYufOna6uri9evCDTmUzmpUuXTE1NlZSUcMq8efPodDrOnxtCQkLi4uKsKV/N09zc3MjIKCAgAD/MyckZNmzYkSNHOs0/MTGRQqFERkZWVVXhus3Ly2OtwxkzZpCfwuPHjwMCAvDfFy5cwDl0/BSwZ8+eWVpaSkpKmpiY5Ofns74pQRBJSUnLly83MDAoKir65Zdfnj175uLigs904sSJycnJR44cYTAYBEFER0f7+PjIyclxX0UaGhr79+/Pz8/39PS8ePGijo6Or6/v+/fvv1bZ/MbzX5IBe8010KCB187z1TYHNn3RBNGz1gOsW9+9z58/29jYCAsLV1ZWEgRRU1NjaWk5bNiwxsZGfEBYWFhwcHBLS0tsbKyVlVVeXt6nT58WL15MpVIzMjIuXbqEz9THxwcff+fOHQqFEhMT09DQEBUVhWuASqWWlJSEhoYihDw8PF68ePHp06dvv/122LBhuD0Bd2l2VefTpk3T09NjTfnxxx/J6qVQKHv27MHpr1+/RgitXLmS9QRZPwJuyMnJsV7McpOnp6eniIgIvkZ+9eqVgoLCoUOHOLzFhg0byOt9tjqsqqry9vZGCNnY2DCZzLq6OhUVFfIiutNPgSCI9PR0cXHxo0eP1tTU0Gg0vFtyQUFBZWVlSEjI6NGjJ02aFBUV1dDQ0LEwbW1teJVjQ0PDFStW0Gi07lYRm+Li4n379mlqalpbW1+/fr33l//QzjPUDMC4z7nNgU3fNUH0oPUA6+53Ly0tDSFEtixFREQghJ4/f44fOjk5tbS00Ol0FRWVN2/e4MSioiKE0IoVKwiCKCkpYY379vb2qqqqZOaTJ0/+7rvv8N847ufn5+OHuNnn48ePBMe439LSIiIiYmdnx5rY1tZWWlr622+/rVmzRlhYGCF05swZgiASExMRQp6enuSR7e3tCKFJkyZxXyFsQY2bPH/66SeE0M2bN7l8C9a4T3SoQ4IgnJycKBRKcnLyzp0779y5gxM5fApGRkbz5s0jX+7m5obj/vLly8XExGJiYjiXh8lkLlmyhEqlSklJXb9+/avl5xz3saamJrxvMzcZcgbtPIKOrWHh33//9fb2VlVVLS8v37t377Bhw9TV1fGWI5mZme7u7tra2qWlpQsWLJCSkjI2Nk5JSUEICQsL43tnnKe+vj5+2NDQ0LHNgfNte981QbC1HvQdMzMzPT09cqvFjIwMRUVFGo2GEKqrq1NWVhYTE8vOzq6srBw7diyuqBEjRiCEcnJyEELKysqsuUlKSn758qWtrQ0/VFNTy8jIYD0AX4riIxFCLS0tnItXWFhIp9OHDRvGmigiIqKurm5ra3vhwoXk5GRZWdmjR48ihPD74pwxBoOBEBIVFe1epbDgJk91dXWEEFvrCvfY6hAhFBUVNX78eDs7OxUVlQULFuDErj6Fly9fvnz5cu7cueTLjY2N8R9hYWEHDhwICgqysLDADfqdFuDw4cNmZmYpKSlycnKOjo5km1LPFBQU7NmzZ9SoURUVFTQabfHixb3Jre9A3B80EhISPDw8njx5QhAEQsjV1RWPDgwODl62bNn79+9Hjx69adOm9vb2BQsWhIeHV1ZWRkZGnj179vnz53Q63cbG5u3bt58/fx47diyZ57Nnz0xNTfHfUVFRrNee0tLSBEHgtohOy3Px4kU9PT0tLS0y5dy5c5WVlUVFRTExMZMmTfLz88Ppb968qaysZD1y9OjRCCHWFnA206ZNu3379pcvX3pcXVxycXH5/fffm5qaKioqhg8fvmrVKvzbeffuXXzJ9unTJ4RQSUkJ6+VSdnY2+q/VnrR7925ZWdldu3bV19f/9ddfT548mTdvHoe37qpiSbi5X0xMrKsDLC0tAwICiouL6XQ67paoqqoin62pqUH/7STcM9zkKSUlxXZMt7DVIUJIUlJy7969tbW1qampZBV19Sm8efMGdfbjgRBSUVHx8fHJzc09cODAvXv3dHR0PD09//nnH9Zj4uPjb9686ePjY2lp+ffff48dO9bd3b2ioqK7Z8FgMG7dumVra2tubs5gMFJTUxMTEx0cHERERLqbVf+AuD9oODs74/ZW7OnTpzt27EAIeXl5mZiYyMnJLVmypLa2tqKioqyszNbWlkql7t+/X1NTc+zYsWfOnGltbQ0LC5OXl7e2tiYzUVRUZH3IxtDQsLq6eu/evR2fam1tTUtLMzAwYE3csmUL2QQhJCQUGBiI+2/xfCUVFRXySNyqy+EfTF9fn06nP3r0iIuK6RVnZ+fm5ubff/89Li7Ozc1t3bp1BQUFf//997///jtlyhSEEO7lwzcBnOnr6+/atSs7O1tNTc3BwcHV1bVbI+g7UlRURAg1NjZyOMbS0lJdXV1ERMTAwEBWVjYvL4986t27dwihadOm9bgA3OSJ71qkpaV7/C5sSkpK4uLiYmJi7ty5ExwcjBO7+hTwnUdxcXFXuVEoFGtraxqNlp2dPXz48EWLFllZWcXFxeFih4eHT506FR+prq5++/bt5ubm5ORk7ktbWlp64MCBkSNHhoWFrVu3rri4OCQkRFdXtztnzAcQ9wcTtusaHEnJAQb4fpxOpyOENDU1qVSqkJAQfmrmzJmysrLPnz9HHW782cYncKmvmyB62XrAPW1t7ZkzZ964caOurk5TU3PixIlGRkYXL14kL2mNjY3l5OR279599OjRsrKyL1++PHnyBA/ywVWNm7wRQn/++ee9e/eSkpIaGxuLioqOHz9OnjI+Ep81QojJZJIvxG1unV77q6uri4mJcZ6FlJaW9sMPPyCEREVFXVxcUlNTyeFYDx48kJCQwHsO9ww3eeKeXj09PS7zbGtra21tJR+y1SFubwwPD1+/fr2rq6u/vz/uY+jqUzA1NaVSqVeuXMFVSsL3B6xUVVV9fX3z8vL27dt369atBw8e4BNk/VXT0dERExPDdzBcCgkJaWxsfPToUVJSkqOj44C9wGcDcX8wYbsp7niPzOEpTU1Nsum59/q6CaKXrQfdsmbNmmvXri1atAg/XLduXXR0NLkogri4eEBAQGtrq4+Pj4aGhry8/OzZs/HB+HYkLS0Ntx1fuXIlJSWF7EHBzdAPHz6sqal5+vQpQig5OZnJZNLp9CdPniCEUlJSCIJQUFBACGVkZERHR5eWlrIWTExMbPr06bgpA2tvb3d3d4+NjW1tba2pqTl37lxWVhaO+wihgIAANTW177//vr6+PjEx8dSpU4cPH9bQ0EAILVq0SFVVNTU1tatKIAiirKysubm5rKyMteOBQ55YTk4OlUq1tLRECGVnZysqKnJYdKG0tPTp06cNDQ3kNTVrHeKBOnPmzNHU1MRvTaFQHB0dHz16JCoq2umnoKGhsXnz5pycHBcXlw8fPuTn5+MBsnPnzsWd52woFMqcOXOuX7+OP8EdO3bgcZw1NTUVFRXbtm0bNWqUjY1NpzXWaRWFhYUdPXoUt1sOJjzvKYbxPFxC3R/Pgy+OyMEPeJTIp0+f8EM8sgIPknFzc5OUlGR9rZqa2qJFiwiC2LlzJ+vnfujQIYRQfX098bUxhazwlfi6des4HPPXX3+pq6sTBNHa2iorKztz5kzyKfzvdPLkya5ee/fuXYRQd0dz9uy719DQQA68IQji8+fPS5cuZTsmKipKV1dXQkJiypQpiYmJBEHg+IIZGRkRBJGent6xuWP48OHTp08nHwYFBU2aNIl8eP78+aqqKnNzc2Vl5StXrnQs2+XLlxHLLCQmk7l69WppaWkZGRkLC4uOL8nPz583b56kpKS+vv6FCxfIdEtLS21tbQ5jOvG3gvTixYuv5olNnDiRzDYrK0teXr6reYV49BRJV1eXrQ7JXlA8wW327Nnksw8fPuz0UyAIor29fc+ePcrKytLS0s7OzkFBQcbGxuHh4RymX7GKj4+fMGGCqKiopqbmpk2byP+mjjXGoYr6DozjHGp6EPebmpoQQjt37sQPccjGwwGJ/2Yq5uXlEQTh5uZGpVKbmprwU//88w8eWk4QhK+vLxnoCYLYs2cP+m+IIW5Ora6u/mpJWlpaxMTEWMfPdfTjjz8eO3YM/+3u7i4iIkL+ouzbt09CQoKtm44VHlbR3WFw/P3uxcfHnzt3jnzY2Nj46tWrSZMm4TlBPcNgMMaNG+fl5dX74jU0NPC8crKysqhU6l9//cXbbAeIvqix7oJxnOD/3BS3trbiq+bk5GSCIOh0+uPHj/ExBEEghAiC2LFjR3V1dUFBwcaNG6dMmeLs7IwQwp1OMTExjY2NMTEx+Cps8uTJMTExbG0OHG7b+7oJgrX1YFD4999/t2zZwjqqVVJS0sDAwMHBgUNz3FdRqdS4uLjIyMj09PRelvD06dN4IACvtLa2btu2zcvLC3eADz08r7EBhOe/JHC9zyXUzet9tpti1taD0NBQcjgmQuj06dNubm5SUlLh4eGKioqysrLOzs5VVVU4n6ampqVLl4qLixsYGCQnJ+Pxy3iWKVubA+fb9j5tgmBtPeAeH797t2/fRgi5ubllZmZ++fKloaEhKytr7969ZWVlPMlcQ0Pj3r17Pc7hxx9/xN0JvFJSUmJtbb1mzZre3M0MZDyvsZ4ZUu08rDELk5KS0tLSWrhwYUxMTHt7O89LNQB1N+53C477fZQ51ndNED1uPeDvNce9e/dsbGxUVVVFRUV1dXW9vb25aTHjUnZ29oC6nDp48GBUVBS/SzH0Dam4z2Qy8cwXrLq6ury8/KeffpKRkUEITZw4sbS0lOcFG2j6NO67urqKi4v3UeakzMxMWVnZtLS0XuYTFBSEJ+kQBNHS0mJhYcE6cZ97cK8Jhpgh1b5PoVDGjx9Pji4XERFRU1PbvHnzxYsXEUKZmZmLFi3i4aBDQfPly5eMjIyWlpanT58SX5sU2hsmJiZxcXH29va//fZbjzMJCwszNze3sLBACOGFJUaPHh0YGMi7YgIA/o+B1a9rZ2c3ZswYhFBGRgb+oUMIPX782MzMTFxcfMyYMTjx2rVr5BDpiIgIa2trOTm5b775huwbTE5OnjBhgpyc3J49e6Kjo8mpGR2zGnpqa2vl5eXx8jjTpk2LiYnp07dbuHDh/fv3z58/3+McPDw8yPmfsbGxeI2U3vSFAgA4G3D/XeQSS1evXkUIPXjwYM6cOaNHj/706dPkyZNXrlz57NkzR0dHvF4rQujJkydxcXFTpkzJzc3dsGEDQqiurm7p0qUSEhL5+fkWFha7du3Ck4w6zYpPZ9mH5OXlWW/oXF1d+/odx48fj9e06T1/f/+NGzfyJCsAQFcGXNwfPnw4/gOvBOLu7t7e3r5582YZGRncdHvkyBEqlTpy5Eh8mK+vr5qamomJCUIoNze3paUlNze3trb23bt3+fn53333XWRkJI77nWbFp7MEAAC+EeZ3AdiRa9W2tbXl5ubiJhorKyvygKysrI6vIrsKmpqaxo4dq6KiUllZaWFh4efn5+fnJywszH1WAAAwtA24631yQaUxY8bgdRwRQr/++ivZcMG2hgkbJpMpJSV1+/ZtNTU1Op0eEBAwc+bM+vr6HmQFAABD0oCL++Sa7MuWLSOXn2SdF8oNU1PT169fL1u2DCGUmpoaGBjY46wAAGCIGVhx/+XLl3hbqLFjx65bt05XVxcvNXzhwgW2dVY5KC0tDQoKUlJSSkhIwNOsc3Nze5YVGML++uuvjRs3kh1FbKqrqzU1NTksLdkDmZmZ5DKfvRQYGBgXF8eTrPrf69ev58+fLyMjo6qq6urqqqamxqt6zs/P9/PzU1dXLyws5EmGQxXf4n5ubi65HHlubm51dfXNmzdtbW2ZTOb48eN/++03MTExUVFRHx8fhNC///77ww8/VFdXv3jx4uLFi0wmE2+wiRAqLCxkMBjkw4KCAmlp6X379oWFhX358gXvXGFra9tVVnw4czAAMJlMOzu7mJiY+vr6ro4hCILckLL3bty4sWzZsq1bt+KHHz9+jIiImDVrlru7O9uRlZWVy5cvl5WVHTFiRFc7t6xevfr06dPbtm3jVfH6TWlpqZWVlYeHx4cPH9asWRMbG1tRUcGret6+ffuxY8c471jA5sqVKxMnTpSWlh4+fPjq1as/fPjQ1ZEcPrLBh+czwXq2ToOQkBDeDefixYt0Op314GPHjo0cOVJUVHT06NGhoaEMBgMP8STh9YdJLS0t/v7+MTExmpqaKioq/v7+eLPATrPi+elzDw28fdUHu+7O1/3uu+9Y9/juO2lpaQoKCjk5OWTK2rVrx48fjxBi26S7rq5uzJgxixcvrqqqSk9PV1BQCA4O7jRPfGR3l6rmu6CgIBkZmb7Lf//+/Yhl2Sg2TCbz4cOHDg4Ot27dIgji2rVrCgoK9+7da2pq+vDhg4ODwzfffEOGCzadfmQeHh7e3t7v3r3rg1MhiCG2TgMgIO73ge5+99atW9cPcZ9Op+vp6QUEBLClt7e3i4mJscX9Xbt2iYiIfP78GT8MCAgQERHpKor98ccfVCr11atXfVDqvuLm5tandY7vkDrWWEVFRXBwsK6u7rfffou3WScIYuXKlbNmzSKPSU1NpVAoHBbu7/iRlZSUBAQEaGtrz549m0ajtbW18fZ0htQ6DQAMBHhWcFZW1vTp0yUkJIyNjfGU7+bm5suXL0+fPn337t34yOLiYgcHB2VlZSkpKQsLCzwdGiGUl5c3bdo0eXl5Hx+f8+fPk8PGWF26dCk3N5d1iWZMSEiIbZNLJpN56dIlU1NTJSUlnDJv3jw6nX7p0qVOy29ubm5kZBQQEIAf5uTkDBs2bMDOSklMTKRQKJGRkVVVVXiyfV5eHms9z5gxg5yH//jxY7zfFoVCwZsxIIRoNJqRkZGYmJient6NGzfInJ89e2ZpaSkpKWliYsK2NydBEElJScuXLzcwMCgqKvrll1+ePXvm4uKCa37ixIl4vy186x8dHe3j44P38u1Ux49MQ0Nj//79+fn5np6eFy9e1NHR8fX1ff/+Pe+qrW/w/JcErve5hOB6n9e6+93bsGGDuLh4cHBweXl5VlaWgYGBlJRUSUnJpUuX8M7v5PJwkydPtra2Li8vz83N1dTUNDMzI9OvX7/e3Nz8+PFjJSUlvFEUm2nTpunp6XVaADk5OdaLx9evXyOEVq5cSabg3Ws5LEnt6ekpIiKCL1FfvXqloKBw6NAh7mug/23YsIG83mer56qqKjwP38bGhslk1tXVqaiokBfRsbGxVlZWeXl5eDtGKpWakZFBEER6erq4uPjRo0drampoNBqeAFRQUFBZWRkSEjJ69OhJkyZFRUU1NDR0LExbW9vy5csRQoaGhitWrKDRaF8tP9tHxqa4uHjfvn2amprW1tbXr1/v/eV/H13vD7h5WwLl5MmTvFrhACCE0tPTzczMuvUSKSkp3OGvpqb2888/m5iYhIaGnjp1atasWXiXVwz3A6upqampqc2ePRuvQ9fc3Pz8+XMdHR1xcfHp06fjlmU2ra2taWlpCxYs4KYw+HYBDzzDcFisqKjo6iX6+vp0Ov3Ro0d2dnaGhobV1dXcnvkA4OzszFrPioqKISEhpaWleKfiy03F3gAAIABJREFUu3fvxsTE4Kprb2/39fVNSUnBO9mGhYXdunUrNDT06tWrbm5uM2bM8PLyQgg5ODgkJSVFRkYihLZv3/7rr79GRER0vNMiiYiIXL16tbW19fbt2wUFBXjkd29oaWkdOHDA19fX1dXVwcHh+vXr9vb2vcyzL0A7DwD/y8jISEtL6+XLlwghcsIHlpGRsXXr1j///HP16tXx8fF4o2MJCYnhw4fPnDlz9+7dpaWl27dv77hTfGFhIZ1OHzZsGDcFwGvQSkpKkil4zJuoqGhXL1FXV0cIsTVuDCJs9YwQioqKGj9+vJ2dnYqKCvl7mZ2dXVlZOXbsWHLDeoRQTk7Oy5cvX758SS7qhRAyNjbGf4SFhR04cCAoKMjCwgI36HdaALzvUEpKipycHF4TsDenU1BQsGfPnlGjRlVUVNBoNHLH4IFmEF/v5+fnx8TEnD9//tmzZzo6OvwuTk98//33jo6O/C7F0OHg4NDLHJSVlWtra9F/Tf+k0tJSV1fX8vJyLy8vYWHhX3/9FafTaLSVK1cGBwcfP37cy8vr0KFDbC/Ea0OJiYlx8+74Z6OqqopMqampIdM7JSUlxfaSwaXjwquSkpJ79+51dHRMTU318vLCQzzxNP6SkhK8Nyfp2rVrqLMfD4SQioqKj4+Pt7d3UlJSVFSUt7f3ihUr3Nzcxo0bRx4THx9/8+ZN3Fvz999/z5kzx93d3dbWVlVVtVtnwWAw7t69e/bs2aysLBcXl9TUVLyb6YA1iK/3ezBWt+8MqbG9AqysrAy3JLBqaGiwsrKSk5PLyMhwcnJi7dmztLTMy8s7efKkkpJSYGDgqVOn2F6LZ5A0NjZy8+4GBgaysrLksuHov9UJyXWqO2ppaUEISUtLc5P/oFBSUhIXFxcTE3Pnzp3g4GCciPtaaTQa28H4Tqi4uLir3CgUirW1NY1Gy87OxiPFrays4uLicL2Fh4dPnToVH6murn779u3m5ubk5GTuS1taWnrgwIGRI0eGhYWtW7euuLg4JCRkgAd9NKjj/r1798jhFny3e/fus2fPJicnt7e387ssoIfS09PLy8vx7vO4JQd/mk+fPi0oKFi/fj25/B9BEAihlpaWw4cPi4uL79ix499//x07dizepJ6Vurq6mJgYl1cnoqKi+GoR33MghB48eCAhIcHhPgZ3/Orp6XX3ZPmlra2ttbWVfMhazwihhoaGTZs2hYeHr1+/3tXV1d/fPzExESFkbGwsJye3e/fuo0ePlpWVffny5cmTJ7t27TI1NaVSqVeuXGGbhE8u80VSVVX19fXNy8vbt2/frVu3Hjx4gBASFRVl/ZXV0dERExPDt1BcCgkJaWxsfPToUVJSkqOjo4iISPeqg1943lPcn+N5uhqryxedDsfmAMF4Hl7r7nfP39+fQqHs2bOnvLw8OztbX19/w4YN+Km7d+8ihMzNzZuamvC6rS4uLrW1tTQazdDQUFhYOCcn5/79+6KiomfPnq2trS0uLtbX1w8PD+/4LnPnzh0xYgRbIpPJLC0tFRUVXbhwIR5Ljn3+/FlLS2vt2rV1dXUPHz6UlZU9fvw4fmrhwoUqKip4DzWSl5cXlUrF44hevnypoKAQGBjIfQ30s5KSEtwk++jRI5zCWs+VlZWzZs06ceIEebCwsLCCgkJSUhKDwTh58iRr4BIWFsb7nuMp0E5OTsXFxe/fv8dt/fLy8l3Nd2N1584dhNDhw4erq6s/fvzo5uZmYGDQ2tpKdFbbXX1kfWoIztt6+fLlggULZGRkRowYceXKlfnz53MTwf/44w8LCws82nrnzp2scT8+Pn7ChAmioqJjxoxJSEggCOLt27deXl4qKiplZWV+fn5KSkrDhw8nR2vl5ubi+3dvb+/Y2FhyEF7HfLjEeYwXG4j7PNfduM9kMs+dOzdu3DhRUVF9ff2IiAg8V/OXX34h44uRkRFBEN7e3rKysoaGhjdv3rx8+bKUlNT333/f2Nh45syZgwcPqqioaGhoHDp0qNOpnpcvX+54dYK/uqQXL16QT+Xn58+bN09SUlJfX//ChQtkuqWlpba2NtuYzokTJ5IpWVlZ8vLyAzbus90M6erqstUz2QuK/xNnz55NPvvw4UOCIKKionR1dSUkJKZMmZKYmIizbW9v37Nnj7KysrS0tLOzc1BQkLGxcXh4OIfpV6zIf3ZNTc1NmzZ9+vQJp3esbQ4fWd8ZanH/2bNncnJyp06dqqmpefHixahRo7i5cu9qrC7RxfBeS0tLfG/u4eGRmZlZW1trZWUlLy+Pl4LodPB1V8OEuQFxn78G5twRBoMxbtw4Ly+v3mfV0NDAeoJZWVlUKvWvv/7qfc6gI7ba5oshFfcZDIa+vr6rqyuZgjtwvhr3jYyM5s2bRz50c3PDr6LT6SoqKm/evMHpeJm2FStWEP/9Sn/48AE/dfz4cYRQSUlJU1MTQujvv//G6WFhYeXl5Rzy4QbEff4amHGfIIjMzExZWdm0tLRe5hMUFJSamor/bmlpsbCwIGeWAZ5jrW1+GVLrNGRmZr59+5Z1MguHudEkDmN1uxrei/6bBUOOwcCDo+l0eqeDrznkA0CPmZiYxMXF2dvb4wlfPRMWFmZubm5hYYEQKi0tXbBgwejRowMDA3lXTPD/sdb20MOfuI9Hp3EYldwpvGVKp2N1yeG9rL9p2dnZqLMBwiQajYb7f0aOHOnn58dkMjnkA0BvLFy48P79++fPn+9xDh4eHuSAztjYWDzJiMPXG/QGa20PPfz50uCrew6zzzvFYaxuV8N7Oes4+Lpn+QDAjfHjx/NqWQ5/f/+NGzfyJCsggPgT9w0NDalU6q1bt7r1Kg5jdbsa3ov+m9hC7vGCX9ve3t7p4GsO+QAAwNDAn7ivpaW1bt26ixcvnjhxAm99dfv27a++SkNDY/PmzTk5OS4uLh8+fMjPz8fjwObOnfvjjz8GBAS0trb6+PhoaGjIy8vPnj170aJFra2teGXd5ORkgiDodPrjx4/Rf8OHDx06FBkZ+eXLly9fvhAEMXPmTHFx8U7z+WrZCIIoKytrbm4uKyvDvzQAADBA8bynmMsxFU1NTevXr5eSktLU1AwNDY2IiEBcjOfhPFa34/Be1o29QkNDTU1NWR92Nfi602HCnPVgbC+C8Ty8NmDH8wDQM300nodCEARvf0jwnPLutmOePXt2y5YtBQUFg3SFtR6gUCjx8fFDbF22zMzMQ4cOsc7H6bHAwEBtbe3Vq1dz/5KeffcAGLBoNNry5ct5HqUHymAAvEwH2QoPeunMmTPkGi/9lglsHQ7AoDAg4j6dTset8ImJiWx9tqAHGhsb2RYz6YdM0tPTN27ceO/evTlz5uCUrtaqq6+vt7S0bG1tLSwspNFo/v7+ISEhHTPU1tZOTEx8+PAhDFEHgLcGRNy3srLCQyc3b94sJCRE6QK/dq55+/ZtV0XiY6k42Lp1a+834uhWJu3t7WvWrPH09GRd3Pz8+fMvXrzouPT8wYMHCwsLY2JiFBUVTU1NPT09/f39CwsLO2YrIyNz4cIFf39/vAEhAIAnBkTcT09P56YvIiEhgS/F09fX52OpUlJSpk+fLiUlpaamtmXLFtzwIiwsjH91yBLih3gZW7wNt4KCAoVCefLkibu7u7a2Np7hKSUlZWxsnJKS0q1MGhoaOO/Z3W9bhwMAem9AxH3QlYcPHy5cuNDLy6uioiIsLOzy5ctz5sxpb2///Pnz2LFjycOePXtGDlWKiooKCgpCCNXU1BAEsWLFivDw8MrKysjIyLNnzz5//pxOp9vY2Lx9+5b7TKSlpQmCwOOdOi3nxYsX9fT0tLS0vnpGb968qaysZD0S73Py559/dvWSadOm3b59+8uXL1/NfOjJzMy0s7PjSVaBgYFxcXE8yaqXXr9+PX/+fBkZGVVVVVdXVzU1Nfxl6738/Hw/Pz91dfVObx8BCeL+wEUQxLZt29asWbNgwQJpaWlHR8ddu3Y9f/783Llz8vLy1tbW5JGKioqsD1mVlZXZ2tpSqdT9+/dramqOHTv2zJkzra2tYWFh3GeCEMJ7du/du7fjU3jrcAMDA25Oqjdbh3OTf//on27zIdlPXlpaamVl5eHh8eHDhzVr1sTGxlZUVJA3nb3Ugz34vrpTXl1dXUhIyJQpU6SlpTv9/vfgSL6DuD9wZWRk5OXlGRkZkSmbNm1CCN27dw912GubrTmFlaamJpVKJfeKmjlzpqys7PPnz7uVCQeCtnV4/3SbD9V+8suXLzMYjHnz5snLyx89ehTfRPr6+vIk86/uwUcQRGJioqOjIzlRlPNOeWlpaYaGhrGxsa6urllZWRzaGzse6enp6ePj8/79+96dU58YxPuqD3l4FWi8XjSmrq4uKSlZVlbWrXw6Lt2lqamJ4y9PCNrW4f3Qbd5VPzmDwei4CyDuJ09LS2PtJ1++fHnHqTC4n9zKymrRokWGhoa9PIWeKSws5PAb33ust5KsKisrz58/f+7cORUVlc2bN5PL+nZVqwihJ0+ezJs377vvvouLi+P89e70SG9v7+jo6FmzZo0ZM8bNzW3JkiUDZxdGuN4fuDQ0NNB/q5CShIWF8R413cLWLl9dXY2XmOaJQb11+ADpNmcrVb/1k3PuruetxMRECoUSGRlZVVWFqyIvL+/y5cvTp0/HF+kzZswgh8k9fvw4ICAA/33hwgWcA41GMzIyEhMT09PTu3HjBpnzs2fPLC0tJSUlTUxM2H5NCYJISkpavny5gYFBUVHRL7/88uzZMxcXF9Zq7FirCKHPnz8vXbrU0tLy6tWrnIN+V0dqaGjs378/Pz/f09Pz4sWLOjo6vr6+A+TyH+L+wGViYqKlpXXt2jUyLpSUlNTV1S1fvhwhhK8dyKeam5vRf+tR41jDGutbWlrwAQihN2/eVFRU4D3tupVJVwbv1uEDp9ucrWD91k/Oubuet6ytrQmC2LBhg5KSEh4Ll56e7uHh8eTJE1yAmzdvent7I4RsbGymT5++c+dOFRUVGo3m5OSEEDp//vyZM2du3LhRWlo6btw4R0fHzMxMfKazZ89evHhxWVnZnj178IovCKFPnz4dPXpUT0/Px8fH2tq6sLAwIiJi/PjxXJb20KFDVVVVM2fONDMzExcXHz9+PN7hvbtHCgkJLVy48O7du+np6WJiYjNmzJgzZ05CQgKeqco33V3Y4atgjRQuIS7W58GrcyxatKi0tLSsrGzBggU2Njb4H/XcuXMIoVOnTjU0NERHR8+cORMhpKioGB0dHRkZiRB6+PDhuXPnSkpK3NzcKBTKpk2bqqqq8vPzLSwspk6d2tbW1q1MOO/Z3W9bh3PWre8ek8kcM2aMu7s7mbJ//36EUEREBEEQ27dvZ/3v8PPzQwjV19cTBMEasgmCsLW1lZCQaG9vxw9x//OWLVu6lQmrlpYWEREROzu7TovNtqcbDjGenp5kCm6nnjRpUlcn/tNPPyGEbt682XXd9CHWuE8QRElJCUKIddcwJycnCoWSnJy8c+fOO3fu4EQOG+F1tQff8uXLxcTEYmJiuCkVW60yGAxlZWV1dfWEhIS6urrMzEwdHR1xcfF3796xvZD7I7GmpqZVq1YhhK5fv85NwYbUfluAS46OjgkJCUVFRaNGjTIzM5swYcKtW7fwlbiTk9PSpUt9fX1NTU11dXVnz55tZmYWGhq6YsUKe3t7c3PzVatWSUlJ4cYiSUlJIyOjMWPGGBsbjxo16v79+/hKn/tM8Nelq3I6OzsXFRWxDZ7z8vLS0NBoa2u7c+eOhIREVlYWTldSUkpJSfn48aOamtr27dvDwsJ++OEH/FRNTY24uDjbqL6kpKR58+Z1d5eerxqw3eYC1U/ecRulqKio8ePH29nZqaiokFvydbURHoc9+MLCwg4cOBAUFGRhYXHx4kXyfpcb5eXlnz59mjFjxrJly2RkZExMTI4fP97S0vLjjz/2+MiCgoI9e/aMGjWqoqKCRqORm8jzBfTrDnTLli1btmxZx3QJCQnWJs4ZM2bgy0mEkJSU1B9//MF2/NatW8kRgT3IxMjICHfAdmrVqlVBQUERERFHjx4lE48dO3bs2LFOjx85cuT9+/c7pj99+rSxsXHt2rVkysuXL7OystLT07t66x4bsN3mAtVP3rH2JCUl9+7d6+jomJqa6uXlha9yyI3w8HUM6dq1a6iLPfhUVFR8fHy8vb2TkpKioqK8vb1XrFjh5ubG2lXelfr6eoSQjIwMmbJw4UIhIaHc3NzuHslgMO7evXv27NmsrCzcwqmrq/vVAvQ1uN4f+hgMRl8veEelUuPi4iIjI3sfoE+fPr1jxw78d2tr67Zt27y8vKZMmdLrMrIbsN3mg7qfvPdKSkri4uJiYmLu3LkTHByME7vaCI/DHnwYhUKxtram0WjZ2dnDhw9ftGiRlZVVXFwc500yNDQ0hIWFCwoKyBQRERE5ObmOv6YcjiwtLT1w4MDIkSPDwsLWrVtXXFwcEhIyEII+grg/5H358iUjI6OlpQU3mvfdGw26rcMHbLf54O0n50ZbW1trayv5EHdvkmPn8WCn8PDw9evXu7q6+vv74w6MrjbC47AHH9v7qqqq+vr65uXl7du379atWw8ePOBQSBkZGVtb25SUFPLmr7y8vLq6umPjDIcjQ0JCGhsbHz16lJSU5OjoOHAGcSIE/br8g/p+3xW2lplz58716dsRBJGdnc2rT//gwYNRUVHdekl3v3sDp9ucrWD91k/Oubue50pKSvCsArzhHUEQd+/eRQiZm5s3NTVVVlbOmjXrxIkT5MHCwsIKCgpJSUkMBoNtmpuwsHBKSgpBELj10snJqbi4+P3797itX15ePjg4mJsidVWrubm5ioqKVlZWRUVFHz58mDt37pw5c/BTbLXK4cje66N+XYj7fNMPcV/Q9OC7l5CQgIeEa2tr79mzp6WlBac3NTUtXbpUXFzcwMAgOTn58OHDZmZmMTExDQ0NVVVV5ubmysrKV65cIQjCzc1NSkoqPDxcUVFRVlbW2dm5qqqqu5mwuXz5Muqw/RyHPd3y8/PnzZsnKSmpr69/4cIFMt3S0lJbW3v+/Pms+UycOJFMycrKkpeX75+4n5aWxlp+XV1d1v15jIyMyKtp/Js0e/Zs8tmHDx8SXWyEx3kPvq/iUKs5OTlz586VlpZWVVXdsWNHQ0MDTu9Yq10d2XsQ94caiPs8x5fvHo77vM2TwWCMGzfOy8ur91k1NDSw1klWVhaVSv3rr796n7MgY6vVvgPjOAEYiPqi23ww9pMLFNZaHYwg7gPQc33XbT7o+skFB2utDlIwfh+AHqqtrVVQUMB/T5s27dy5c66urjzMf+HChTo6OgcPHpw/f37PcvDw8CD/jo2NdXR03LhxI49KJ7hYa3WQgrgPQA/Jy8vz9hq/o/Hjx1+/fp0nWfn7+/MkHzAEQDsPAAAIFoj7AAAgWCDuAwCAYIG4DwAAggXiPgAACBaI+wAAIFj6ZBxneno6h+UAAenkyZO8GqUHEEJ4dit898CQgfcj4zkKzwcgnzhxgm0BJgAGoKSkJENDQ1VVVX4XBICv4PnVIe/jPgCDAoVCiY+Pd3R05HdBAOhv0L4PAACCBeI+AAAIFoj7AAAgWCDuAwCAYIG4DwAAggXiPgAACBaI+wAAIFgg7gMAgGCBuA8AAIIF4j4AAAgWiPsAACBYIO4DAIBggbgPAACCBeI+AAAIFoj7AAAgWCDuAwCAYIG4DwAAggXiPgAACBaI+wAAIFgg7gMAgGCBuA8AAIIF4j4AAAgWiPsAACBYIO4DAIBggbgPAACCBeI+AAAIFoj7AAAgWCDuAwCAYIG4DwAAggXiPgAACBaI+wAAIFgg7gMAgGCBuA8AAIKFQhAEv8sAQH9wdnbOysoiHxYWFiorK0tJSeGHIiIid+/eVVdX51PpAOg/wvwuAAD9RF9fPy4ujjWloaGB/Hvs2LEQ9IGAgHYeIChWrlxJoVA6fUpERGTt2rX9WxwA+AbaeYAAmTRp0osXLzp+5ykUSn5+vo6ODj8KBUB/g+t9IEBcXFyEhITYEikUiqmpKQR9IDgg7gMBsnLlSiaTyZYoJCTk4uLCl/IAwBcQ94EAUVFRmTZtGtslP0EQy5Yt41eRAOh/EPeBYHF2dmZ9KCQkNHv2bBUVFX6VB4D+B3EfCBZ7e3sq9f9/7QmCWL16NR/LA0D/g7gPBIusrKytra2w8P/OXBEWFl68eDF/iwRAP4O4DwTO6tWrGQwGQkhYWHjRokWysrL8LhEA/QriPhA4CxculJSURAgxGAwnJyd+FweA/gZxHwgccXHxpUuXIoSkpKTmzZvH7+IA0N94tj5PSUnJs2fPeJUbAH1KU1MTITR58uTbt2/zuywAcEVLS+vbb7/lTV4Ej8THx/OmQAAAADqwt7fnVbjm8XqcBKz2w1cUCiU+Pt7R0ZHfBRkEDh06tGfPno7LNrBxcHBACF2/fr1fCgVA5/D3kFegfR8IqN27d3816AMwJEHcBwKKHMIPgKCBuA8AAIIF4j4AAAgWiPsAACBYIO4DAIBggbgv6KqrqzU1NYOCgvhdkP8jMzPTzs6OJ1kFBgaybacOgICDuA8QQRBdbTjOE2fOnKmtreX++Bs3bixbtmzr1q344cePHyMiImbNmuXu7s52ZGVl5fLly2VlZUeMGBEeHt5pbqtXrz59+vS2bdt6VngAhh4YyiboFBUVS0tL+y7/xsbGkydPcr/GfXp6+saNG1NTU8eNG4dTdu/enZGR8erVKz09PdYj6+vrLS0tx40bV1hYmJeXZ2tr29DQ4OPjw5ahtrZ2YmLipEmTAgMD9+zZ0/szAmCwg+t90Le2bt2an5/P5cHt7e1r1qzx9PQkgz5C6Pz58y9evBATE2M7+ODBg4WFhTExMYqKiqampp6env7+/oWFhR2zlZGRuXDhgr+//+vXr3t6HgAMHRD3BVpzc/Ply5enT5++e/duhNC///7r7e2tqqpaXl6+d+/eYcOGqaur4yUKMjMz3d3dtbW1S0tLFyxYICUlZWxsnJKSghASFhamUChkS5G+vj5+2NDQsGnTpkuXLiGEFBQUcEpOTs6wYcOOHDnSaXkuXbqUm5u7fv16tnQhISFxcXHWFCaTeenSJVNTUyUlJZwyb948Op2O364jc3NzIyOjgICAnlYVAEMHxH2BlpCQ4OHh8eTJE7ywkqur64kTJyorK4ODg5ctW/b+/fvRo0dv2rSpvb19wYIF4eHhlZWVkZGRZ8+eff78OZ1Ot7Gxefv27efPn8eOHUvm+ezZM1NTU/x3VFQU7jGuqakhCEJaWpogCCaT2dU6ThcvXtTT09PS0vpqyd+8eVNZWcl65OjRoxFCf/75Z1cvmTZt2u3bt798+cJV1QAwdPE57kdHRz958qS7r9q8efPnz5/x32fPnpWRkZk6dWpDQ0MvC9NH2Q5kzs7OrE0fT58+3bFjB0LIy8vLxMRETk5uyZIltbW1FRUVZWVltra2VCp1//79mpqaY8eOPXPmTGtra1hYmLy8vLW1NZmJoqIi60M2hoaG1dXVe/fu7fhUa2trWlqagYEBNyX/+PEjQoh1P3R5eXmEUEVFRVcv0dfXp9Ppjx494iZ/AIYwfsZ9JpMZGhoaGhrarVfdunUrMjKSNROCIPC2eb3RR9kOfMrKyqwPcSQlG1XwvlR0Oh0hpKmpSaVSybXMZs6cKSsr+/z5c4SQqKgoayZsbTJcKiwspNPpw4YN4+bgtrY2sngY/rDYSsJKXV0dIcR9ZwMAQxU/4/6vv/6am5t77969N2/ecPmSJ0+eODs7s6Zs3bq1oaEhIyNDWlq6xyXpo2wHBSqVyuEh56c0NTVx/OUJfGvVsf+2U2pqagihqqoqMqWmpoZM75SUlBTbSwAQTPyM+7hXkCCITi/5U1JSLC0tJSUlVVVVXV1d6+vrf/755zlz5tTX1yOElJWVKRTKjBkzKP9paWkxNDQkH5qZmSGEAgIC8MOEhASEUFxcnKWlpbS0tLy8/LJly3BbwVezxeW5ffv2pEmTJCQkNDU1f/jhBxykrl27Rh4ZERFhbW0tJyf3zTffpKam9lMl9i+2dvnq6uoRI0bwKnNFRUWEUGNjIzcHGxgYyMrK5uXlkSnv3r1DCE2bNq2rl+CPcsj/kAPwVXyL+8nJyU5OTpMnT0YI/fzzz2VlZazPpqamzpkzR1hYuKioSF5ePiYmZteuXU5OTl5eXviAT58+EQTx4MGD+fPnk6+6c+fOmDFj8N83btxACPn7+y9evDgyMtLOzu7QoUPOzs4hISH5+fna2to3b97EWxl8NVuE0K+//rpkyZLGxsaioqKDBw+ePHly+vTpdDrd0dHR29sbH/PkyZO4uLgpU6bk5uZu2LChLyqtL+A2nPb2dvwQB0eygYvJZLI929zcjP9+8+ZNRUXF4sWLEUIiIiLovwt2hBA+5tOnTwghPM6Hmw151NXVxcTEysvLuSm2qKioi4tLamoqOSPswYMHEhISHLanwJ03bJMAABBAfIv7Dx8+nDp16saNGxFCbW1tYWFhrM/u2rWLTqe7uroqKyu7u7tLSEh0ev8uKio6cuRI8uHIkSPPnj2L/6bRaAghBoOhoKCwadMmISGhM2fOIIRSU1NVVFQsLCwQQmlpaZ2WjS1bBoPh6elJEMTChQtVVFRcXFxEREQyMzNjYmKoVCp5pK+vr5qamomJCUIoNzeXvFEY4HA/Z1paWnNzc2trK75TSU5OJgiCTqc/fvwYH4MDN0EQO3bsqK6uLigo2Lhx45QpU3D7mK6uLkIoJiamsbExJiYGV+zkyZNjYmIUFBQQQhkZGdHR0aWlpdnZ2YqKip0uCyEmJjZ9+vSOjX4EQZSVlTU3N5eVlbHWakBAgJqa2vfff19fX5+YmHjq1KnDhw9raGgghBYtWqSqqsp215Uymv0kAAAgAElEQVSTk0OlUi0tLXlXeQAMSvyJ+1lZWThSrFq1Ct93nz17Fre0IIQ+fPiAR+Phjrjt27c3NTUdOHCAm5xnzZo1YcIEhFBsbCxC6H/+53+WLVuGn1q6dKmUlJSGhgZBEHgwH4PB4Kbn9uXLl8XFxQih4cOHI4SEhYXl5OQQQnfu3Ol4MNnt2dTUxE2B+evXX39dsGABQujZs2fffvutjY3N77//jhBauXLl8ePHrays8OB9Nzc3vAqCpKSkkZHRmDFjjI2NR40adf/+fXyl7+TktHTpUl9fX1NTU11d3dmzZ5uZmYWGhq5YscLe3t7c3HzVqlVk5XO49nd2di4qKmKbe+Xl5aWhodHW1nbnzh0JCYmsrCycrqSklJKS8vHjRzU1te3bt4eFhf3www/4qZqaGnFxcbZfl6SkpHnz5nHoAABAUPBqo168rzqXB7u5uTU0NOC/XV1dcUmOHTuGU/A1JkLo1q1bbC/08/PDT+EGGYIgyHVXmpubcUp0dDRO+fvvv/fu3ctgMMiXMxiMixcvmpmZTZw4ER9Dp9O/mu3du3fx3+Hh4fhZPAZm8uTJBEH89NNP+NkXL14QBEGuE0Bm1Z8QQvHx8X2UuZubm5SUVB9ljjEYjHHjxnl5efU+q4aGBtZ9qLOysqhU6l9//dXdfOzt7Xm4nzUAPcPb7yEfrvcLCgqio6OlpaVxdygZpk+dOoXbmsmet4yMjB7k7+TkhMcC/vTTT3joIU7Py8ubPHnyjh07YmNjv/32W+4zJEc6ks3ceBCLpqZmD4o3eHF5e9QbVCo1Li4uMjIyPT29l1mdPn0az0VACLW2tm7bts3Ly2vKlCm9LiMAgx4f4v6RI0dSU1PJXx4GgzF+/HiEUElJydWrVxFCEyZMwKPIL1++TIba1tZWxNKKwoG4uPimTZsQQteuXSN7+QiCWLBgwYsXL3bs2ME6uRTjnO3EiRNx4wDuGGxra6urq0MIzZkzp1snPqh9+fIlIyOjpaXl6dOnBBedtD1mYmISFxdnb2//22+/9TiTsLAwc3Nz3IuDF5YYPXp0YGAg74oJwCDWr3G/vLzcz88vPT2ddU4mlUr19/fHf3t4eNy/f59KpeKW2YKCgk2bNlVXV2dnZx89ehQhpKOjg4/8559/jh071tDQQLYF5+bmknlu3bpVWFh4xYoVeGggQujTp0/4gA8fPhQWFt6+fRun44Z+ztkKCwsfP34cIXTr1q1Pnz5FREQQBGFgYODq6spkMouKivCRhYWFDAaDfFhQUMCjauO/2tpaeXn5Fy9eIISmTZsWExPTp2+3cOHC+/fvnz9/vsc5eHh4kAM6Y2NjHR0dL1y4wGFqguAYFBsbvH79ev78+TIyMngMt5qaGq/2h8jPz/fz81NXV+90/T4BwqsGI27a97/55hvyfa9fv44TOy6M7ufnRxDEhQsXvvnmG1FRUXylhhvi29ra1q1bJykpqa+v/+TJE7bhkqxN6itWrMjMzGR9982bN0tJSRkaGgYHB9NoNGVlZWVlZU9PTzqdzk22NBrN2NhYTExs2LBh69atq6ioIAgC36CQyLZ+DJe5P6G+bN8XTP3Tvn/69Gm8hFGfZpKQkKCjo/PgwQP8sLy8PDw8fObMmdu2bWM7sqKiwtHRUUZGRltb+8yZM53mVlRUNHXq1K1bt/ay2GxKSkrk5eXv379fU1Pj5eWFxwEHBQXxJPP58+fjGd0FBQVcvuTnn382MTGRkpJSU1NzcnIqLi7u6khuKq3HePs95E+/LugjEPd5rh/ifkNDw6hRo3oZ97+aSVpamoKCQk5ODpmydu1a3MTq5ubGemRdXd2YMWMWL15cVVWVnp6uoKAQHBzcaZ74yCNHjvSm5GyCgoJkZGR4mCGb/fv3c4j7TCbz4cOHDg4OeFDJtWvXFBQU7t2719TU9OHDBwcHh2+++QYv4sKmq0rz8PDw9vZ+9+5dL4sNcR90CeI+z/VD3HdxcUH/LVnaR5nQ6XQ9Pb2AgAC29Pb2djExMba4v2vXLhERkc+fP+OHAQEBIiIiXQXKP/74g0qlvnr1qjeFZ+Xm5qakpMSr3DrCI5I7nk5FRUVwcLCuru6333578eJFPD5w5cqVs2bNIo9JTU2lUCi1tbUds+2q0kpKSgICArS1tWfPnk2j0dra2npWbIj7oEsQ93muu/9vjx8/njZtGl5fZPPmzTgQkwMH8DFkg2d9fT2eukhKSUnZtm2blpZWSUnJd999hydMPH78uFuZ1NfXs5UKd8l02kYhJyfHGvcZDIaKioqlpSWZgsdWHThwoKtTNjExWbZsGf779evXSkpKhw8f7upgDmfx8OFDtibf3NzcS5cuTZs2zdfXlyCI6dOnk08lJyfjK3eE0Pnz53Fu8fHxEyZMEBUVHTNmTEJCAvmmf/zxh4WFhYSEhLGx8c6dO1njPpPJTExMdHR0HDZs2JYtW7Kzs1lLGxoaSqFQDh8+3N7ezmQy165di0vC5quV1t7efvv27e+++05dXd3Hx6cHl/8Q90GXIO7zXLf+3x48eCAjI3Pnzp36+vr4+HgpKanJkyfT6fSamho8igwfVlVVhbcowAGadYsCPDdQTEzM39//w4cP//zzz7hx48TExN68ecN9Jh1NmzZNT0+v06fY4j5el3vlypVkCh7GNn/+/K7O2tPTU0REBF8Fv3r1SkFB4dChQ10dzPksCILYsGEDeb1/6dIlvLy2j48PPhgvi2JjY8NkMuvq6lRUVMiL6NjYWCsrq7y8vE+fPi1evJhKpWZkZBAEkZ6eLi4ufvTo0ZqaGhqNJiEhgeN+ZWVlSEjI6NGjJ02aFBUVRc4oYtXW1rZ8+XKEkKGh4YoVK2g0WqcnxX2lFRcX79u3T1NT09ra+vr169xf/vM27sP+ukPNyZMn8SRbwBPp6el4jb+vIghi27Zta9aswVOgHR0d//nnnwMHDpw7d27Lli3W1tbkEhR4i4JOt4gpKyubP3/+48eP9+/fjy+Nz5w5M2vWrLCwMLzwHzeZsMEbG+BSfVVvNjaws7PD+ytwyB/v1sDlWTg7O8+aNYucKKOoqBgSElJaWnrlypWUlJS7d+/GxMTg82pvb/f19U1JScHb74SFhd26dSs0NPTq1atubm4zZszAa3A5ODgkJSXhFde3b9/+66+/RkREdNzfjSQiInL16tXW1tbbt28XFBSQk/97XGlaWloHDhzw9fV1dXV1cHC4fv26vb09h+rqIzCyDQDeyMjIyMvLMzIyIlPwPJJ79+6h7mxRwPN9DgbaxgbdOgu2/SEQQlFRUePHj7ezs1NRUSF/zLKzsysrK8eOHYtng+JlYnNycl6+fPny5cu5c+eSLzc2NsZ/hIWFHThwICgoyMLCAjfod1qAw4cPm5mZpaSkyMnJ4QHBHY/hvtIKCgr27NkzatSoiooKGo2GlzXsfwJxvV9dXT1hwoRt27bhXWQHYIY89P333zs6OvK7FEMHhwU+2eCpG6zrMqmrq0tKSrKtNftVPN/nYFBvbNCxNiQlJffu3evo6JiamkoO9MSLv5aUlOCF+UjXrl1Dnf14IIRUVFR8fHy8vb2TkpKioqK8vb1XrFjh5uY2btw48pj4+PibN2/imSt///33nDlz3N3dbW1tVVVVWbP6aqUxGIy7d++ePXs2KysLryOLFyjjlyF7vX/mzBlyhV6EEEEQ5MbfAyRDzn755RcDAwNpaWkzM7Nnz5713RsBXsERh209UWFh4VGjRnU3K4Kn+xwMsY0NSkpK4uLiYmJi7ty5ExwcjBPxUol4FV5W+Iobr6vYKQqFYm1tTaPRsrOzhw8fvmjRIisrq7i4OHxS4eHhU6dOxUeqq6vfvn27ubk5OTmZLRMOlVZaWnrgwIGRI0eGhYWtW7euuLg4JCSEv0EfDdW439jYePLkSfKhoqJiaWmpr6/vwMmQs8ePH+fm5qanp//5559MJtPGxqaysrKP3gvwiomJiZaW1rVr18h9CEpKSurq6nDHYLe2KODtPgcDbWMDDmeBEGpra8OLsmBs+0M0NDRs2rQpPDx8/fr1rq6u/v7+iYmJCCFjY2M5Obndu3cfPXq0rKzsy5cvT5482bVrl6mpKZVKvXLlCt5JgkS+HUlVVdXX1zcvL2/fvn23bt168OABrg3WaK6joyMmJobvb1hxqLSQkJDGxsZHjx4lJSU5Ojric+c/XnUQD6jxPDwZEN2nGXJ26tQp8m+8GigeyfdVCMbz8Fq3xlHg/4JFixaVlpaWlZUtWLAAjzwhCOLcuXMIoVOnTjU0NERHR8+cORMhpKioGB0djbsZHz58eO7cuZKSEjc3NwqFsmnTpqqqqvz8fAsLi6lTp+KBH9xnwlawuXPnjhgxgi2RyWSWlpaKioouXLiQXM6WIIjPnz9raWmtXbu2rq7u4cOHsrKyx48fx0/hLSjwGk0kLy8vKpVaXl5OEMTLly8VFBQCAwM51BKHsygpKcGLpuAtH4j/vv/m5uZNTU2VlZWzZs06ceIEfqqkpERYWFhBQSEpKYnBYLBemSGEhIWFU1JSCILYunUrQghPtX3//j1u65eXl+9qMhorvNb64cOHq6urP3786ObmZmBg0Nra2rEqOFQaTwz6cZwvX75csGCBjIzMiBEjrly5Mn/+/K/OmS4qKrK3tx82bJikpKS5uTnrAgy//fbb1KlTxcXFdXR0fvzxR4Ig2MYyV1ZWsg4BZl0r4s2bNwTLLo/Xr1/v9I04Z4h1Omr77du3Xl5eKioqZWVlfn5+SkpKw4cP72ooGKuWlhby78DAwBEjRrD+W3IAcZ/nuvv/lpCQYGRkJCYmpq2tvWfPHvKjbGr6f+zdZ1xTSdsw8EkoAUJHelBXhLXgAvalWFFExYaAiogFZVUEvZUiil0Ry94uiqsIYuGxILo3KrevgqKggq4goKwu7AJqAAEpYqQl5Lwf5tnzy5OQECAEMNf/U3IyZzJnCFcm51xnpmHBggVKSkrDhw9PTU3FVwtjYmJYLFZ1dbWNjY2uru6lS5eIf+a7joyM1NbWVldX9/T0rK6u7mglfC5evIgEblbCmewkPJE4VlRUNGPGDDxzyblz58jtdnZ2/fv350tPHDlyJLklJydHU1NTdNwXdhR45E4yNTX97bffyKeWlpbkVVD8HTN16lTy1eTkZIIgoqKiTE1NlZWVx4wZk5KSgt+Ow+GEhITo6uqqqqp6enqGhYVZWVlFRka2efuVIPKeAAaDsWbNGnIyGMGuENZpEtG34/7Tp081NDSOHTtWW1v78uVLfOqz3bg/evRoBweH8vLygoICBoMxfvx4vP3y5cuGhoZpaWkNDQ14np/Lly8T/zeXmS8FuLKyctKkSQihW7du4Uq4XK6vr++ZM2e4XK6wNxJRISE8a9vOzg5nZfj5+WVnZ9fV1dnb22tqaoo5b09RUVFISAiDweC7l0QEiPsSJ/3597tjnYNeuLDBN4CvK7pVH55/n8vlrly50tXV1d/fX1NT08rKCie6ibPj/PnzDQwMzMzMpk6d+vfffyOEmpub/fz8du3aZW9vr6ys/NNPP2lrawtevPL09MR3VWC6urrHjx9H/6TcIoQoFAqLxfL29qZQKG2+kegKCZ6sbVVVVTc3ty1btrx48eLMmTPp6el4CviAgABra2sNDY158+bV1dWJSIUmMZnMQYMGHThwoKqq6sKFC9098X1v1iemkJSg7ljnABY26A68XdG3SDXuZ2dnv337lvf+EXwVvl1ZWVnr1q179uzZ0qVLr169ii/1PH/+vKqqatSoUbiMhYVFdXV1mwua82VxWVhYTJ06lVyJNzs7m7wxp803El2h6KxtfCsHmaGMM3yFVcuLwWDgzAEbG5sjR47s2bOn3V26G19Gk3QquX79uouLCz5FixD6+PHjyZMnp0yZ4uvry1eysrLS3d1dXV19wIABeA4WQUuXLj1+/LjgFLC9R/etcwALG0gWb1f0OVKN+zi3qRMLnJaWljo5Ofn4+Dg5Obm7u+P/B5ziInhdXpBgCvDGjRuzsrLw8t+XL19eunSpiDcSXaHorO2uzPmupKQ0adKkO3fuDBs2DKch9yC+jCbpVJKZmbl69eqkpCRyiZutW7eeOnUqNTWVTPDAvnz5Ymdn19zcXFJSEh8fHxoaGh4eLlhh//79U1JSkpOTe2eo6u51DmBhAwni7Yo+R6p/MDy6F+csBy8Wi2Vvb6+hoZGVleXh4UGOnXFWMr5g1VGzZs0yMzM7ceLE58+flZWVcWKWsDcSTYJZ222i0WgLFy7kC3PSt27dOvFvyJRIJRwOx8vLy9/fn/c+mtjY2JcvXwregrRnz56SkpKYmBhtbe1x48b5+/uHhoa2ubaGmprauXPnQkNDeU/W9RKampq8J2HJpaclaMSIEZKaxiM0NJQv5QH0FVKN+xYWFlQqNTExsUN7paenFxcXr1y5kncmP4TQmDFj6HT65cuXd+7cWVFR8eXLl6SkJHw+hC+XmS8FGBfw8/NLSEg4evTo8uXLRb+R6ApFZ23juz/I07U4ibijQby4uHjmzJkd2kW0R48eTZw4ES8lsXbtWnziRV5eHt/jjssMGTIEP8UZ0xcuXEAIaWlpUSiUtLQ0X1/f/v3741/6dDrdysrq0aNHHaqExWLl5+f369dv//79bTbywoULBQUFgnOnyMnJ8X0lc7ncCxcujBs3TkdHB2+ZMWMGm83GbyfIxsbG0tJy165dnek7AL4BkrpALGY+z6pVq+Tk5I4ePVpdXZ2dne3k5ITay+fJyclBCC1btqyuri4+Pt7CwkJeXj4/Pz81NZW8Ww9TV1fHy0rw5TLzpgCT1X758kVTU9PZ2VmcNxJdobCs7aamJkdHR4TQ5cuXuVxuS0sLvvnl9OnTbS7dgH348EFPT8/Ly6ugoKCuru7YsWOWlpY1NTVi/BHEyufpPXNGip67UWpTSIom/XweAAT17TzOhoaGlStX0ul0BoNx+PDhkydPthv3CYIIDAxUV1e3sLC4cePGxYsX6XT6pk2bWltbCYI4duyYiYmJqqrqtGnTyLx+3lxmvhRg3mo3b9589+5dcd6o3QrbzNrmnS788OHDOAJix48fF3awLBZr+vTpKioqysrKI0aM2LVrl+B06sK0G/e5XK6ZmZmvry+5BU9ijhcN3rBhA+8fcdu2bcJCtpOTk7KyMofDwU8fPHiAEFq7dm2HKhGhqalJQUFh/vz5bb7KF/dx3re/vz+5Bf+iGjVqlLD68YqYN27caLclEPdBb9C352FWVlaOiYkhL1iRSTWihYeH816mIy/DIoT8/f39/f35ymtraz958oR8Sgi5PHvkyBEx36jdCl1cXATnaH348CHv0y1btrTZDD50Ov3u3bvilOwEnH2EJzHH1qxZs3v37qSkpLVr1/bgnJF8etsUkgB8S3r4Qjw+US7LyelS1mvnjOTTp6eQBKCX68m4z2azHz9+jBBKSUnhmzUJdJNeO2ckn29sCkkAepWejPv29vZ43tSffvpJTk6OIkSPrEfTrd6+fSvsYLv7eHvtnJF8etsUkgB8S3oy7mdmZopzCSIhIaEHG9kdhgwZ0lPHS6PRjhw5UldX5+HhUVZWVl5evnbtWkdHR/xlg6cFj4mJ+fr1a0xMDL6vbfTo0TExMVpaWgihrKys6Ojo0tJShBBBEBs3bqypqSkuLl69evWYMWM8PT07VEleXp62tja+2CvYzokTJ/L9LsFvWlZW1tjYWFZWhsfs2K5duwwMDDZt2vTly5eUlJRjx47t27cP/7iZM2eOvr4+/mVJys/Pp1KpdnZ2kutaAPoMWbzRTsa5ubklJCS8e/du0KBB48eP/+GHHxITE/FI3MPDY8GCBcHBwePGjTM1NZ06der48eMPHz68aNGihQsX2tjYLFmyhE6n43iqoqJiaWlpZmZmZWU1aNCgO3fu4JG++JXg7zlh7fT09Hz37h3fvVcBAQHGxsYtLS23bt1SVlbGqbcIIR0dnUePHn38+NHAwGDDhg0RERH/+te/8Eu1tbVKSkp83y7379+fMWNGJ24dB+Bb0JVkIF69av59mYWkNR9nd8wZyaeXTCEJeZygN+jD83GCb0Z3zBnJB6aQBKCbQNwHHdZ9c0bygSkkAegOEPdBx3T3nJF8YApJACRO2vfrgr4OzxkpzXeU7BSSEqkHgD4NRj0AACBbIO4DAIBsgbgPAACyBeI+AADIFoj7AAAgYyR1Axi+XxcAAEB3kOD9uhRCQjl5TCbz6dOnEqkKACnw8/NbsWKFtbV1TzcEALGYmJj8+OOPEqlKYnEfgL6FQqFcvXrVzc2tpxsCgLTB+X0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZAvEfQAAkC0Q9wEAQLZA3AcAANkCcR8AAGQLxH0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZAvEfQAAkC0Q9wEAQLZA3AcAANkCcR8AAGQLxH0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZIt8TzcAAClJT09vbm7m3fLq1SttbW3y6ejRozU1NaXeLgCkjUIQRE+3AQBpcHFxuXHjhrBXlZWVKyoq1NTUpNkkAHoEnOcBsmLx4sXCXpKTk5s1axYEfSAjIO4DWTF79mw6nd7mS1wud+nSpVJuDwA9BeI+kBVKSkoLFixQUFAQfIlOp8+YMUP6TQKgR0DcBzJkyZIlbDabb6OCgoK7uzuNRuuRJgEgfXBdF8gQDoejr69fU1PDt/3+/ftTpkzpkSYBIH0w3gcyRF5efvHixXynevr16zdx4sSeahIA0gdxH8iWxYsX857qUVRUXLp0qZycXA82CQApg/M8QLYQBGFiYlJaWkpuefbs2dixY3uwSQBIGYz3gWyhUCienp7kqR4TE5MxY8b0bJMAkDKI+0DmkKd6FBQUli9fTqFQerpFAEgVnOcBsuj7778vKChACOXn5w8bNqynmwOAVMF4H8iiZcuWIYSGDRsGQR/IIKnOx+nq6irNtwNAmK9fvyKE5OTk4DMJeol//etfP/74o3TeS6rj/YSEBCaTKc137IuYTGZCQkJPt6Lv6VC/0el0HR0dBoPRrU0CQEwJCQkfPnyQ2ttJ9fw+hUK5evWqm5ub1N6xL4qPj3d3d4frLh3V0X57/vw5pG+CXkLKsRHO7wMZBUEfyCyI+wAAIFsg7gMAgGyBuA8AALIF4j4AAMgWiPsAACBbIO4DAIBsgbgPAACyBeI+AADIFoj7AHRGTU0Ng8EICwsTXaygoCAoKEhfX//jx4+dfq/s7Oz58+d3evfOOXDgQFxcXKd3f/369cyZM9XU1PT19b29vQ0MDNrtKzEVFRVt27bNyMiopKREIhXKIIj7AHQSQRDtzt3v4+Pz888/V1ZWCitw4sSJuro6ETVcv37dxcVl3bp1+OnHjx9Pnjw5ZcoUX19fvpKVlZXu7u7q6uoDBgyIjIwU7yCE1rl06dLjx4+vX79e/HpIpaWl9vb2fn5+Hz588PLyOnv2bEVFhaTWOdiwYcORI0fKy8vF3+XSpUsjR45UVVU1NDRcunSpiJlwRHTvN4WQIoTQ1atXpfmOfdHVq1fF+btUV1cbGxsfOHBACk0SX1ZW1rx58yRS1f79+y9evCh+eTH7Tfq2bNmCECovLxd8icViDRo0qLa2Vti+GRkZWlpa+fn55Jbly5ePGDECIeTj48Nbsr6+3szMbO7cudXV1ZmZmVpaWgcPHhSzhaLr3L9/v5j1kMLCwtTU1Dq6l/h27tyJECouLm7zVS6Xm5yc7OrqmpiYSBDElStXtLS0kpKSGhoaPnz44Orq+v3333O53Db3bbMr/Pz8AgMD//rrr244lP8l5dgI4/0+jBBjvNkV7Q5F+Uh2ZNqV8WavoqurK+yldevWFRUVCXuVw+F4eXn5+/vzLhIQGxv78uVLGo3GV3jPnj0lJSUxMTHa2trjxo3z9/cPDQ0V80yIsDrV1NTOnTsXGhr6+vVrceohlZSUKCoqdmiXDtHT02tze2VlZXh4uJmZ2Y4dO2bPnj19+nSEUGJiorW19cyZM5WVlRkMhr+/f0FBQX19fZs1tNkVgYGBKioqU6ZMcXBwuHbtGl6srW+T2jcMAeN98fSScWu7Q1E+3TEy7dB4s0P9NmDAAPz5nzt3bmFhIfnvoK+vTxAEuWXz5s245h9++EFRUdHMzCwhIYEgiIaGhgsXLkyYMCE4OJis88aNG/hkwujRozMzM8nthw8fRgh9+PAhJCREW1vbyMjoxo0bBEGsXr2a9z/xy5cvfI2MiYlBCL1//16w/RoaGry92traqqenZ2dnR27JzMxECO3evVvMDhGsk2Rtbe3i4oIfv379WkdHZ9++fcIqSU5O5oswBQUFvH01ceJE8qXU1FQ8ckcIxcbG4hoEext78uSJra2tsrKylZXV5s2bEc94n8vlpqSkuLm59evXb+3atXl5ebxNOnz4MIVC2bdvH4fD4XK5y5cv5/2rid8VHA7n5s2bs2bNMjIyCgoKkuzwX8qxEeJ+r9NL4j5ekUrMuM9ms83NzXft2sW3ncPh0Gg0vn+hLVu2KCgofPr0CT/dtWuXgoKCsN/sT548oVKpr169arcNHeq3T58+OTo6ysvLV1ZWEgRRW1trZ2fXr1+/r1+/4gIREREHDx5samo6e/asvb19YWFhVVXV3LlzqVRqVlbWhQsXNDU1EUJBQUG4/K1btygUSkxMDIvFioqKwrGMSqUymUwc9/38/F6+fFlVVfXjjz/269cPn2fAlzqFdfKECRPMzc3bfIkvMOHx+OLFi3kPECE0c+ZMMTtEsE6Sv7+/goJCXV0dQRCvXr3S0tLau3ev6KpWrVqlo6ODH8VO6esAACAASURBVPP1VXV1dWBgIELI0dGRy+XW19fr6enFx8e3tLQQBNFmbxMEkZmZqaSkdOjQodra2vj4eGVlZRz38QB/8ODBo0aNioqKYrFYgo1paWlxd3dHCFlYWCxatCg+Pr7TXYG9f/9+x44dDAYDD/9xy7sI4r6sEyd+8Y033759GxAQoKenV1ZWtm3bNh0dHUNDQ/z5zsrKWr9+vYmJCZPJnDVrloqKiqWl5cOHDwmCkJOT4/3N9/3335MDT8GhqOiBXreOTHnHmyJ09PsyIyMDIUReQjh58iRC6MWLF/iph4dHU1MTm83W09N78+YN3vju3TuE0KJFiwiCwCsIkXF/4cKF+LcCNnr06FmzZuHHOO4XFRXhp+Hh4Qihjx8/EiLjflNTk4KCwvz589tsPF+vpqSkIIT8/f3JLRwOByE0atQo8TtEWLD79ddfEUL4N4qYeOM+IdBXBEF4eHhQKJTU1NTNmzffunULbxTR25aWljNmzCB39/HxwXHf3d2dRqPFxMSIbg+Xy503bx6VSqXT6deuXWu3/aLjPtbQ0LBkyRKEkDgVtkvKsRHO7/dJCQkJfn5+aWlp+BPj7e2Nk0YOHjzo4uLy999/Dx48eM2aNRwOZ/bs2ZGRkZWVladPnz516tSLFy/YbLajo+Pbt28/ffo0dOhQss6nT5+OGzcOP46KiuINSaqqqgRB4CFqm+05f/68ubm5iYlJuy1/8+ZNZWUlb8nBgwcjhJ49eyZslwkTJty8efPz589idY3Yxo8fb25ufuPGDfw0KytLW1s7Pj4eIVRfX6+rq0uj0fLy8iorK4cOHUqhUCgUCj47lJ+fjwTO2quoqHz+/LmlpQU/NTAwyMrK4i2Ah6i4JEKoqalJdPNKSkrYbHa/fv3EORb8vrhmrLW1FSEkkZPsRkZGCCER1yHaJXiFIyoqasSIEfPnz9fT05s9ezbeKKy3c3Nzc3Nz8cl6zMrKCj+IiIjYvXt3WFiYra3t+fPnGxsb22zAvn37xo8f/+jRIw0NDTc3t3PnznX6WBBCxcXFISEhgwYNqqioiI+Pnzt3bldq6xEQ9/skT09P3ktt6enpGzduRAgFBARYW1traGjMmzevrq6uoqKirKzMycmJSqXu3LmTwWAMHTr0xIkTzc3NERERmpqaDg4OZCXa2tq8T/lYWFjU1NRs375d8KXm5uaMjIzhw4eL03Kcxs57XQ6fBKioqBC2y5AhQ9hs9oMHD8Spv0OWLVt29+7dhoaGiooKQ0PDJUuWXLt2DSF0+/ZtPJSrqqpCCDGZTN6xUl5eHkKISv0//ztbt25VV1ffsmXLly9fnj9/npaWNmPGDBFvLewblMRisRBCgtda22RgYIAQqq6uJrfU1taS27uITqfzVd5RfH2FEFJRUdm+fXtdXd3jx4/JrhDW22/evEFCLo/r6ekFBQUVFBTs3r07KSlp4MCB/v7+f/zxB2+Zq1ev3rhxIygoyM7O7vfffx86dKivr6+Iz5swra2tiYmJTk5ONjY2ra2tjx8/TklJcXV1VVBQ6GhVPQ7ifl/F92+AI6mSkhJ+iod+OPGAwWBQqVTyrM7kyZPV1dVfvHiBBMaD5O4d0t0j066PN4Xx9PRsbGy8e/duXFycj4/PihUriouLf//99z///HPMmDEIIQ0NDYQQ/hEg2pAhQ7Zs2ZKXl2dgYODq6urt7d2hDHpB2tra6J/139s1fPhwdXV13gvUf/31F0JowoQJXWkDhn+aqKqqdr0qEpPJjIuLi4mJuXXr1sGDB/FGYb2NPxvv378XVhuFQnFwcIiPj8/LyzM0NJwzZ469vX1cXBxueWRkJLm2mpGR0c2bNxsbG1NTU8VvbWlp6e7du7/77ruIiIgVK1a8f/8+PDzc1NS0I0fcu8j3dANAJ/GNoQSHVCJeYjAY5BmJruvukWnXx5vC9O/ff/LkydevXzc1NWUwGAwGw9LS8vz58+RvFysrKw0Nja1bt7LZ7KVLl9Lp9Nzc3Js3bx45cgR/p+LT6AihZ8+eJSUl3b9/n/x+JeGS+OsNIcTlcskdcRpum2N/IyMjGo0m5t1JioqKy5YtO336dF1dHf79dO/ePWVlZVdX1w53igB8idjc3Fz8XVpaWpqbm8mnfH3FYrHWrFkTFRXFYDAyMjJCQ0PHjBnj4OAgrLc3bdpEpVIvXboUHBzM+2GuqqoaOHAg7/vq6+sHBwcHBQWlpKRERUWpq6vPmTNHUVGR9xtx4MCBNBoNf6jEFB4erqSk9ODBA3xO8hsA432ZwBdZampqyETGruvukWl3jDdJXl5eV65cmTNnDn66YsWK6OhoclIEJSWlXbt2NTc3BwUFGRsba2pqTp06FRfG550yMjLwOeVLly49evRIXl6e8o8BAwYkJyfX1tamp6cjhFJTU7lcLpvNTktLQwg9evSIIAgtLS2EUFZWVnR0dGlpKW/DaDTaxIkT8SkOXgRBlJWVNTY2lpWV8V4k2LVrl4GBwaZNm758+ZKSknLs2LF9+/YZGxsjhObMmaOvr//48WNhnSCsTiw/P59KpdrZ2SGE8vLytLW1Rc+4UFpamp6ezmKxyDE1b1/hRJ1p06YxGAzcbAqF4ubm9uDBA0VFxTZ729jY+KeffsrPz1+2bNmHDx+Kiop+++03hND06dPxRXI+FApl2rRp165dw3+pjRs3pqam7t+/v7a2tqKiYv369YMGDXJ0dGyzZ9rsioiIiEOHDn0zQR8hyN/vfcTMS2loaED/JJgTBLF37170T5YIQRD4JENhYSFBED4+PlQqtaGhAb/0xx9/4IxDgiCCg4MRT+Z4SEgI+ifzBP/6rqmpabclTU1NNBqNN92Cl2BqhK+vr4KCApnEsmPHDmVlZb6zurzwVbh2syY6l//KYrHIxBuCID59+rRgwQK+MlFRUaampsrKymPGjElJSSEIAscdzNLSkiCIzMxMwW8mQ0ND3nT1sLCwUaNGkU9jY2Orq6ttbGx0dXUvXbok2LaLFy8igbtSceo66eXLl+RLRUVFM2bMUFFRGTJkyLlz58jtdnZ2/fv3F5HTKaJOgiBGjhxJ7puTk6OpqSniLnGcJUUyNTXl6yvyKii+gXnq1Knkq8nJyW32NkEQHA4nJCREV1dXVVXV09MzLCzMysoqMjISZ5e2i7wngMFgrFmzpqqqSljPiO6K7iPl2Ahxv9cRM37dvn0bIWRjY9PQ0NDU1ITHL5cvX+ZyuS0tLfgH/unTp7lcro+PD4VCWbNmTXV1dVFRka2t7dixY3HS8ZkzZxBCx44dY7FY0dHRkydPRghpa2tHR0efPn0a/yueOXOGyWTm5uZqaWkJ+4efPn36gAED+DZyudzS0lJFRUVnZ+fGxkZy+6dPn0xMTJYvX15fX5+cnKyurn706FH8krOzs56eXnp6Om89AQEBVCq1zXkOOtFv3eTq1atnzpwhn379+vXVq1ejRo1qbW3tdJ2tra3Dhg0LCAjoevNYLNbChQs7sWNOTg6VSn3+/HnX29A7dbpnJAvivqwTJ37xjaF4B5WHDx8m0zERQsePH/fx8aHT6ZGRkdra2urq6p6entXV1biehoaGBQsWKCkpDR8+PDU1Fae74ZuP+Iaiogd63Toy5R1vdrHfusnbt2+1tbX5QjyXyxV/hhxhsrOz1dXVMzIyulhPWFgYzpzpkKamJltbW968+29P53pG4mQ67vPGL4xOp5uYmDg7O8fExHA4HKk1tQdJPH7huC/BCgV138hU/PFmD8b9mzdvIoR8fHyys7M/f/7MYrFycnK2b99eVlYmkcqNjY2TkpI6XcMvv/yCLyd0CJPJdHBw8PLy6spPll6ucz3THWQ67nO5XJwcjdXU1JSXl//6669qamoIoZEjR5aWlkqttT1F4vHL29tbSUlJghW2qTtGph0ab/bseZ6kpCRHR0d9fX1FRUVTU9PAwEBxLo2IKS8vT/rnIvbs2RMVFSXlN5VZMh33MTITjrzeSN5UOWrUqObm5m5uZg+TbPyqq6uztrZGCKWlpQmbe1ZSJDsy7eh4s5fMawRAJ0g57veNPM758+ebmZkhhLKysvC/N0Lo4cOH48ePV1JSMjMzwxuvXLlCZtGdPHnSwcFBQ0Pj+++/J/O0UlNTf/jhBw0NjZCQkOjoaDKbULCqbwPO5n758iVCaMKECXgWne7j7Ox8586d2NjYTtfg5+dHJnSePXsW31Iv4tYEAEBnSO0bhujCeJ8gCHIedicnJ4Ig7t69Ky8v7+HhUV9fv2jRIgqF8uTJk9bWVjzVH0LI3d29vLwcZ4nhSQ0/f/6sqak5duzYT58+3b59W0NDIzs7W1hV3dYH7YNxa+dAv4G+S8zYKCl9ZiRlaGiIH+DbfHx9fTkczk8//aSmpoZPfe7fv59KpX733Xe4WHBwsIGBAT7FUVBQ0NTUVFBQUFdX99dffxUVFc2aNev06dP4RtM2q+qhowQAgG7XZ+ZpIKczbGlpKSgowKdo7O3tyQI5OTmCe5E/HRoaGoYOHaqnp1dZWWlra7tt27Zt27bJy8uLXxUAAHwb+sx4H8/VhxAyMzPDczoihP7zn/+Qv1z4bnPnw+Vy6XT6zZs3DQwM2Gz2rl27Jk+e/OXLl05UBQAAfVqfifvk/OwuLi7kVJSCs5eINm7cuNevX7u4uCCEHj9+fODAgU5XBQAAfVTfiPu5ubmPHj1CCA0dOnTFihWmpqZ42uFz587h2Q3FUVpaGhYWpqOjk5CQgGerLygo6FxVAADQd/W6uF9QUEDOWFtQUFBTU3Pjxg0nJyculztixIj//ve/NBpNUVExKCgIIfTnn3/+61//qqmpefny5fnz57lcLl6bDSFUUlLS2tpKPi0uLlZVVd2xY0dERMTnz5/xFJJOTk7CquqBIwdS9Pz589WrV5NZAHxqamoYDIboWSc7Kjs7m5zmUxwHDhyIi4uTYAOk7PXr1zNnzlRTU9PX1/f29jYwMJBUfxYVFW3bts3IyKikpEQiFcoiqWUOEZ2ap0FOTg4vpHD+/Hk2m81b+MiRI999952iouLgwYMPHz7c2tp6+fJl3n3xuqCkpqam0NDQmJgYBoOhp6cXGhpK3sckWFU39kJ7IB+xc8Tvt9bWViMjIwqFwrsGLK/q6mojI6OwsDBJtS0hIWHgwIH37t3DT8vLyyMjIydPnrx+/Xphu7x7927s2LHr1q2TVBukiclkampq3rlzp7a2NiAgAC8zIKn+nDlzJl6JhW8+KBH+53/+x9ramk6nGxgYeHh4tLkQNCbOn6Y7tBsbJfx2UnsnAuZlEw/E/c7paL/NmjVLWNyXrIyMDC0trfz8fHLL8uXLR4wYgRASvXh3fX29mZnZ/v37u7+NEhYWFqamptZ99e/cuVNE3OdyucnJya6uromJiQRBXLlyRUtLKykpqaGh4cOHD66urt9//72we9fb/NP4+fkFBgb+9ddf3XAo/0vKsbHXnecBQDp41/jtPhwOx8vLy9/ff9iwYeTG2NjYly9ftrtCmZqa2rlz50JDQ3nXUu4TSkpKJLKkuzDC/naVlZXh4eFmZmY7duyYPXs2Xoo9MTHR2tp65syZysrKDAbD39+/oKCgvr6+zRra/NMEBgaqqKhMmTLFwcHh2rVrePmwPg3iPpBRePqHnJyciRMnKisrW1lZ4fk8GhsbL168OHHixK1bt+KS79+/d3V11dXVpdPptra2eN4LhFBhYeGECRM0NTWDgoJiY2PJnGBeFy5cKCgoWLlyJd92OTk5cVYztrGxsbS03LVrF36an5/fr1+/3nxfYUpKCoVCOX36dHV1NZ4xpbCwkLc/J02aRE6m8vDhQ7zeFoVCwavrIITi4+MtLS1pNJq5ufn169fJmp8+fWpnZ6eiomJtbc232DJBEPfv33d3dx8+fPi7d+9+++23p0+fLlu2DPfwyJEj8Xpb+PxtdHR0UFAQXsu3TYJ/GmNj4507dxYVFfn7+58/f37gwIHBwcF///235LpN6qT2y4KA8zzigfM8ndPRflu1apWSktLBgwfLy8tzcnKGDx9Op9OZTOaFCxfwErXkPKCjR492cHAoLy8vKChgMBjjx48nt1+7dq2xsfHhw4c6OjptrgwzYcIEPE2IIMGVyNrk7++voKCAF5Z69eqVlpbW3r17xT/MHrFq1SryHBpff1ZXV+PJVBwdHblcbn19vZ6eXnx8PF4I6OzZs/b29oWFhXg5RiqVmpWVRRBEZmamkpLSoUOHamtr4+Pj8V2cxcXFeIA/ePDgUaNGRUVFsVgswca0tLS4u7sjhCwsLBYtWhQfH99u+0X/ad6/f79jxw4Gg4GH/7jlXSTl2Ahxv9f5liaGkz7x+5k3NhEEkZOTQ6FQ/P39CYJgMpmIJ+6PHDkyMjISP/by8tLV1SX+Wefy999/x9sjIiIE435TU5OCgsL8+fPbbICYcR+nJ9y4cUP8Q+txfH3L158EQXh4eFAolNTU1M2bN9+6dQtvZLPZenp6b968wU9xMt6iRYsIgrC0tORdyNPHxwchVFxc7O7uTqPR8KKhInC53Hnz5lGpVDqd3u6CnYR4f5qGhoYlS5YgMVYAFQeSbmzsM/M0yBqI/h2VkZFx7NixTu9uaWlpYmKSm5uLECLv5sOysrIQQs+ePTt+/Pj169fxSQBlZWVDQ8PJkyf7+vr6+vpu2LBBsM6SkhI2m92vX79OtwohZGRkhBDiO7PRt/D1J0IoKirq1atX8+fP37p16+zZs/HGvLy8ysrKoUOH8pbMz8/Pzc3Nzc318vIiN1pZWeEHERER1tbWYWFhMTExa9ascXNzIyd04YUXktu8ebO7u7ubm9vZs2eXL1/e6cMpLi4+c+ZMbGzs8OHD4+PjyRWD+5BvMO4XFRXFxMTExsY+ffp04MCBPd2cTnJzc+vpJvQ9XYn7CCFdXd26ujr0z6l/Umlpqbe3d3l5eUBAgLy8/H/+8x+8PT4+fvHixQcPHjx69GhAQMDevXv5dsQT/7V7/VY0Op2OEKquru5KJT1LcCZtFRWV7du3u7m5PX78mEz0xHOxMJlMY2Nj3sJXrlxBbX15IIT09PSCgoICAwPv378fFRUVGBi4aNEiHx8f3qvoV69evXHjBr4q8/vvv0+bNs3X19fJyUlfX79DR9Ha2nr79u1Tp07l5OQsW7bs8ePHpqamHaqh9/gGr+tu2LDhyJEj5eXlPd0Q1NzcHBoa+t1339Hp9BEjRvz666/4Bx3oncrKygYPHsy3kcVi2dvba2hoZGVleXh48F7xs7OzKyws/Pe//62jo3PgwAHBbx18e+DXr1+70qqmpiaEkKqqalcq6W2YTGZcXFxMTMytW7cOHjyIN+JrrfHx8XyFcWrQ+/fvhdVGoVAcHBzi4+Pz8vLw7T729vZxcXG46yIjI8eOHYtLGhkZ3bx5s7GxMTU1VfzWlpaW7t69+7vvvouIiFixYsX79+/Dw8P7btBH32TcT0pKIjMxetbmzZsHDRqUm5v79u3b0aNHr1u3Dt8bDHqhzMzM8vJyT09PhBBO1ONwOAih9PT04uLilStXknO74i/vpqamffv2KSkpbdy48c8//xw6dGhGRgZfnUZGRjQarYtDkE+fPiGEzM3Nu1KJlLW0tDQ3N5NPefsTIcRisdasWRMZGbly5Upvb+/Q0NCUlBSEkJWVlYaGxtatWw8dOlRWVvb58+e0tLQtW7aMGzeOSqVeunSJbyYVcq5Gkr6+fnBwcGFh4Y4dOxITE+/du4cQUlRUJFdYQggNHDiQRqPhX1FiCg8P//r164MHD+7fv+/m5qagoNCx7uiFpHYlgZDitYvIyEjUkdv5ukNlZeWFCxfIp62trUOHDjU0NGx3R8jn6ZyO9ltoaCiFQgkJCSkvL8/LyxsyZMiqVavwS7dv30YI2djYNDQ04Em5ly1bVldXFx8fb2FhIS8vn5+ff+fOHUVFxVOnTtXV1b1//37IkCHktV9e06dPHzBgAN9GLpdbWlqqqKjo7Ozc2NhIbnd2dtbT00tPT+ctHBAQQKVS8UXj3NxcLS2tAwcOiH+Y0sdkMvH51QcPHuAtvP1ZWVk5ZcqUn3/+mSwsLy+vpaV1//791tbWf//737zRSV5eHq+7uW7dOoQQvtX277//xon5mpqaBw8ebLc9t27dQgjt27evpqbm48ePPj4+w4cPx8u1Cna4sD9Nd5NabPzft5PaOxFiH1tubu7s2bPV1NQGDBhw6dKlmTNnihPBnzx5YmtrixOxN2/ezBv3r169+sMPPygqKpqZmSUkJBAE8fbt24CAAD09vbKysm3btuno6BgaGpIJXgUFBfinfWBg4NmzZ8k8DcF6OmTBggXjxo1rtxjE/c7paL9xudwzZ84MGzZMUVFxyJAhJ0+exPdw/vbbb2TcsbS0JAgiMDBQXV3dwsLixo0bFy9epNPpmzZt+vr164kTJ/bs2aOnp2dsbLx37942bwG9ePGi4BAEfz5JL1++xNvt7Oz69+8/c+ZM3sIjR44kt+Tk5GhqavbmuM/3o8fU1JSvP8mroPjfCq+IhyUnJxMEERUVZWpqqqysPGbMmJSUFFwth8MJCQnR1dVVVVX19PQMCwuzsrKKjIzE6a3tIv9zGQzGmjVrqqqq8HbBDhf2p+lush73nz59qqGhcezYsdra2pcvXw4aNEickbuw9F5CSEawnZ0d/tnu5+eXnZ1dV1dnb2+vqamJpwBqMy9bWGax+IYOHRoVFdVuMYj7ndM7+621tXXYsGEBAQFilmexWHjRNywnJ4dKpT5//rx7Wgf4O7ynyHTcb21tHTJkiLe3N7kFX/NpN+4LS+8VkRGMv9g/fPiAXzp69ChCiMlktpmXLaIeMaWnp48YMYLD4bRbsnfGr96v1/Zbdna2urp6RkaGOIXDwsIeP36MHzc1Ndna2vKmvQOJ4+3wHiTluN+7rutmZ2e/ffuWzOdF/1ziFw2n9+JTfhiZ3ktmBON7wQcMGIAQys/PR/9M8UGmZ6ioqCCE2Gw2mZe9devW0tLSDRs2GBgYiKhHHGw2OyQk5NKlS+S1QSA7rK2t4+LiFi5c+N///ld0yYiICBsbG1tbW4RQaWnp7NmzBw8efODAAak0UxbxdrhM6V1xH6+ZbmBg0KG98FJZbab3khnBvN91eXl5qK2cYlJ8fDy+ZPTdd99t27aNy+WKqEccW7Zs2bx5s4WFRYeOC3wznJ2d79y5ExsbK7qYn5/fhAkT8OOzZ8+6ubmdO3dOxAcVdBFvh8uU3vWRwqP7ioqKDu0lIr1XWEawaIJ52Z2rB/v3v/89adIk8nIWASn8MmnEiBHXrl0Tv3xoaOjq1au7rz1AlvWuuG9hYUGlUhMTEzu0l4j0XmEZweif22HItb3wvhwOp828bBH1iHblypXRo0fjhZbYbPajR4/27dvXoaMDAAAJk9qVBEK8axerVq2Sk5M7evRodXV1dna2k5MTEuO6roj03jYzgpuamhwdHRFCly9f5nK5LS0trq6uCKHTp083NDS0mZctLLNYhL179wp2+P/7f/9P9F699vpkLwf9BvoucWKjJN9Oau9EiHdsDQ0NK1eupNPpDAbj8OHDJ0+eFCfui07vFcwI5l3Q8fDhw+PGjeN9Kiwvu83MYmGOHDkiGPRVVFSamppE7wjxq3Og30DfJetxnw+ehLZn77yVsm81fmVlZc2bN0/88vv377948aL45b/VfgOyQMpxv3ed3xeEZ/Ygz8KDrjtx4gSedVKalVy/ft3FxQWfjkMIffz48eTJk1OmTPH19RW2y9KlS48fP75+/fouNhUAwKdXx302m42XvktJSeG7Zgs65+vXr3wXKqRQSWZm5urVq5OSkqZNm4a3bN269dSpU6mpqeRcXYL69++fkpKSnJwMCewASFavjvv29vY4dfKnn36Sk5OjCLFw4cIead7bt2+FNakHWyXaunXrur6CR4cqkc2FxQHozXp13M/MzBTnXFVCQkKPNG/IkCE926pHjx5NnDiRTqcbGBisXbsWn3iRl5fHXzxkI/FTPPnthQsXEEJaWloUCiUtLc3X17d///741lA6nW5lZfXo0aMOVcJisUQv9i3ZhcVlSnZ2Ns4AFtOBAwfi4uK6rz0d8vr165kzZ6qpqenr63t7exsYGISFhUmk5qKiom3bthkZGZWUlEikQlkkoesEYkGwvq4YxLw+ee/ePTU1tVu3bn358uXq1at0On306NFsNru2thavVIeLVVdX42ylL1++EASB//dqa2sJgjA0NEQI0Wi00NDQDx8+/PHHH8OGDaPRaG/evBG/EqK9xb4lu7C4CFK7rnv8+HHy2LuvkoSEhIEDB967dw8/LS8vj4yMnDx58vr164Xt8u7du7Fjx65bt66Lbes6JpOpqal5586d2tpacjmtsLAwiVQ+c+ZMfKum+Oke7fbe58+fDx48OHr0aDqdvm3bNhFViV+yQ6QcGyHu9zrixC8ul2tmZubr60tu2blzJ0Lo5MmTBEHgtV7Jl7Zt2yYsZDs5OSkrK5OzxT148AAhtHbt2g5VIoI0FxaXTtxnsViDBg3qYtxvt5KMjAwtLa38/Hxyy/Lly0eMGIEQEt1j9fX1ZmZm+/fv70rzui4sLExNTa376sefdmFxn8vlJicnu7q6JiYm4i2ie+/p06cmJibm5uanTp0qLCzEk/K2SbCkn59fYGDgX3/91cUjknJs7NXneYAwWVlZhYWFlpaW5JY1a9YghJKSktA/E1eQRJxOYTAYVCqVnC1u8uTJ6urqL1686FAlInx7C4tL4QLJN3BFpKSkhO/zI1l4UkVBlZWV4eHhZmZmO3bsmD17NjlXo4jeS0tLmzp16rhx4/Ly8nx8fAYPHiwv3/aq422WDAwMVFFRmTJlioODw7Vr13D+Ye8Hcb9PwhNB4ymjMSMjIxUVlbKysg7VIzjnF4PBaGlp6XoLsV6+sHgvhqahsgAAIABJREFUuUDC1yrJXhERffVF4lJSUigUyunTp6urq/EhFxYWXrx4ceLEiXj100mTJpG5Dw8fPty1axd+fO7cOVxDfHy8paUljUYzNze/fv06WfPTp0/t7OxUVFSsra35vjUJgrh//767u/vw4cPfvXv322+/PX36dNmyZbzd1Wbvffr0acGCBXZ2dpcvXxb9KRVW0tjYeOfOnUVFRf7+/ufPnx84cGBwcPDff//dye6TFoj7fZKxsTH6ZyJSkry8PF6mpkOI/ztPXE1NDZ5lWiJ688LiycnJzs7OAQEBFRUVERERFy9enDZtGofD+fTpE762gT19+pS8nTsqKor3HNeiRYsiIyMrKytPnz596tSpFy9esNlsR0fHt2/fil+J4HGdP3/e3NzcxMSk04c2YcKEmzdvfv78GSFEEAS+4bzTtXWIg4MDQRCrVq3S0dHBpxQyMzP9/PzS0tJwG27cuBEYGIgQcnR0nDhx4ubNm/X09OLj4z08PBBCsbGxJ06cuH79emlp6bBhw9zc3LKzsxFCz549mzp16ty5c8vKykJCQvBt/AihqqqqQ4cOmZubBwUFOTg4lJSUnDx5Ep/SEcfevXurq6snT548fvx4JSWlESNG4JV+O1pSTk7O2dn59u3bmZmZNBpt0qRJ06ZNS0hI6LXDf4j7fZK1tbWJicmVK1fI0SKTyayvr3d3d0cI4XWfyZcaGxvRP1NS4xEobxRoamrCBRBCb968qaiowFOHdqgSYXrtwuIEQaxfv97Ly2v27Nmqqqpubm5btmx58eLFmTNnNDU1HRwcyJLa2tq8T3mVlZU5OTlRqdSdO3cyGIyhQ4eeOHGiubk5IiJC/Er4NDc3Z2RkDB8+vCtHN2TIEDabja/WWFhY1NTUbN++vSsVdoWnpyfvSSdtbe3w8HAPD4979+49evRo9+7dMTExrq6uCgoKHA4nODg4Kipq8ODB/fr1i4iI4HK5hw8fRgj5+PhMmjQpICBAU1PT1dV12bJluLYNGzbs2LFj69atL168WL16dYdWS+dyuZcvXzYyMjI3N09NTc3IyGCxWM7OzoKjdfFLmpiY7N69u6CgQE9PD19g6EyXdT+I+30SjUY7cuRIXV2dh4dHWVlZeXn52rVrHR0d8U0DpqamCKGYmJivX7/GxMTgJU9Hjx4dExOjpaWFEMrKyoqOji4tLUUIEQSxcePGmpqa4uLi1atXjxkzxtPTs0OV5OXlaWtrt5mlR6PRJk6cyPe7BL9pWVlZY2NjWVkZHs5jc+bM0dfXxzfrkfLz86lUqp2dnQQ7sNdeIPn2roigttbGiIqKGjFixPz58/X09Mh1loStbiRiYaWIiIjdu3eHhYXZ2tqeP3+eHMGIo7y8vKqqatKkSS4uLmpqatbW1kePHm1qavrll186XbK4uDgkJGTQoEEVFRXx8fHk7Ou9DcT9vsrNzS0hIeHdu3eDBg0aP378Dz/8kJiYiEfiHh4eCxYsCA4OHjdunKmp6dSpU8ePH3/48OFFixYtXLjQxsZmyZIldDodnyxSUVGxtLQ0MzOzsrIaNGjQnTt38Ehf/ErIhIQ2eXp6vnv3ji/VOiAgwNjYuKWl5datW8rKyjk5OXh7bW2tkpIS31fI/fv3Z8yY0dHVeETrtRdIevkVkc4R7CUVFZXt27fX1dXhNQ7xRmGrG4lYWElPTy8oKKigoGD37t1JSUkDBw709/f/448/xGnVly9fEEJqamrkFmdnZzk5uYKCgo6WbG1tTUxMdHJysrGxaW1tffz4cUpKCv4RI05LpK/tK9egT3BxcXFxcRHcrqyszHtBbNKkSTgLEyFEp9OfPHnCV37dunXkzDmdqMTS0rK2tlZYI5csWRIWFnby5MlDhw6RG48cOdLmfKXp6elfv35dvnw5uSU3NzcnJyczM1NY/Z3TrRdIxo4d2+mG9eYrIhLEZDLj4uJiYmJWrVp18OBBfMmXXN1o06ZNvIVFLKyEUSgUBwcHBweHioqK2NjYOXPmGBoa+vj4LFy4UMTPLGNjY3l5+eLiYnKLgoKChoaG4AhDRMnS0tLo6OiYmBgzMzMfH5/58+f32ljPC8b7Mq21tbW757yjUqlxcXGnT58WM3YfP35848aN+HFzc/P69esDAgLGjBkj2Vb12gskvfaKSIe0tLQ0NzeTT/HlTXIuJpzUFBkZuXLlSm9v79DQUHyNVNjqRiIWVuJ7X319/eDg4MLCwh07diQmJt67d09EI9XU1JycnB49ekT+yCsvL6+pqRE8OSOiZHh4+NevXx88eHD//n03N7c+EfQRgvt1ex+p3XdaV1dnbW2NEEpLSyPXGOgmN2/eNDY2TkpKEl3sl19+IVezYTKZDg4OXl5era2t4rxFR/sNl58zZ05paWlZWdns2bMdHR1xP5w5cwYhdOzYMRaLFR0dPXnyZISQtrZ2dHT06dOnEULJyclnzpxhMpk+Pj4UCmXNmjXV1dVFRUW2trZjx45taWnpUCV8DZs+ffqAAQP4NnK53NLSUkVFRWdn58bGRnK7s7Oznp5eeno6b+GAgAAqlVpeXk4QRG5urpaW1oEDB8TvmS5iMpkDBw5ECD148ABvuX37NkLIxsamoaGhsrJyypQpP//8M1lYXl5eS0vr/v37ra2twlY3ErGwkjhNEtZ7BQUF2tra9vb27969+/Dhw/Tp06dNm4Zf4utYESUlQsqxEeJ+ryOduM93ZubMmTPd/Y55eXkLFy4Uv/yePXuioqLEL9+JfktISMCp4v379w8JCSGXxGloaFiwYIGSktLw4cNTU1P37ds3fvz4mJgYFotVXV1tY2Ojq6t76dIlgiB8fHzodHpkZKS2tra6urqnp2d1dXVHK+Fz8eJFJHAz6ubNm3n/Xi9fvsTb7ezs+vfvP3PmTN7CI0eOJLfk5ORoampKLe7j6/8kU1PT3377jXxqaWlJjqbx19LUqVPJV5OTkwkhqxuJXlipXcJ6jyCI/Pz86dOnq6qq6uvrb9y4kcVi4e2CHSuspERA3Jd1sH5I5/RIv+G4L9k6W1tbhw0bFhAQIGZ5FovF+4Wak5NDpVKfP38u2VbJIL6O7VZSjo1wfh+AzuuOCyS984qIDOLt2G8MxH0AOunz589ZWVlNTU34LLAEa7a2to6Li1u4cOF///tf0SUjIiJsbGxsbW0RQni6iMGDB8NKNV3H27HfHsjjBKAz6urq8P1rCKEJEyacOXPG29tbgvU7OzsPHDhwz549M2fOFFHMz8+PfHz27Fk3N7fVq1dLsBkyi7djvz0Q9wHoDE1NTcmO8QWNGDHi2rVr4pcPDQ3tvsaAbwmc5wEAANkCcR8AAGQLxH0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQMVKbEaK7k50BAKDvkub8PFK9bwvPnAVAb+Du7r5x48Yff/yxpxsCAEII2djYSO29KDAMB7KJQqFcvXrVzc2tpxsCgLTB+X0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZAvEfQAAkC0Q9wEAQLZA3AcAANkCcR8AAGQLxH0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZAvEfQAAkC0Q9wEAQLZA3AcAANkCcR8AAGQLxH0AAJAtEPcBAEC2QNwHAADZAnEfAABkC8R9AACQLRD3AQBAtkDcBwAA2QJxHwAAZIt8TzcAACm5dOkSi8Xi3ZKSklJXV0c+nTdvnp6entTbBYC0UQiC6Ok2ACANXl5eFy5cUFBQwE/xJ59CoSCEWltb6XR6VVUVjUbrySYCIBVwngfIisWLFyOE2P/gcDgcDgc/lpOTc3V1haAPZASM94Gs4HA4+vr6NTU1bb6akpIydepUKTcJgB4B430gK+Tl5RcvXkye5+Glo6MzadIkqbcIgJ4BcR/IkMWLF7PZbL6NioqKnp6ecnJyPdIkAKQPzvMAGUIQBIPBKCsr49v+7NmzsWPH9kiTAJA+GO8DGUKhUDw9PflO9ZiYmIwZM6anmgSA9EHcB7KF71SPgoLC8uXLcTYnADICzvMAmTNkyJA///yTfPr69evhw4f3YHsAkDIY7wOZw3uqZ9iwYRD0gayBuA9kzuLFizkcDkJIQUHBy8urp5sDgLTBeR4gi0aPHp2dnY0QKi4uHjBgQE83BwCpgvE+kEWenp4EQYwdOxaCPpBBfWY+TldX155uAvh2NDU1USiUlpYW+FwBCfrXv/71448/9nQr2tdnxvsJCQlMJrOnWyEZ39KxSJME+01JSUlfX5/BYEikNgAQQgkJCR8+fOjpVoilz4z3EUKbNm1yc3Pr6VZIAIVC+WaORZok22+FhYVmZmYSqQoA9M+c3n1CnxnvAyBZEPSBzIK4DwAAsgXiPgAAyBaI+wAAIFsg7gMAgGyBuA8AALIF4j4AAMgWiPsAACBbIO4DAIBsgbgPQBtqamoYDEZYWJjoYgUFBUFBQfr6+h8/fuz0e2VnZ8+fP7/Tu4tw4MCBuLi4zu37+vXrmTNnqqmp6evre3t7GxgYtNsbYioqKtq2bZuRkVFJSYlEKgQdBXEfgLYRBNHunfc+Pj4///xzZWWlsAInTpyoq6sTUcP169ddXFzWrVuHn378+PHkyZNTpkzx9fXtUGvb3HHp0qXHjx9fv359h6pCCJWWltrb2/v5+X348MHLy+vs2bMVFRWSmodgw4YNR44cKS8vF3+Xdrulvr4+PDx8zJgxqqqq27dvF1GV+CW/ZUQfgRC6evVqT7dCMjpxLNXV1cbGxgcOHOimJnVOVlbWvHnzxC+/f//+ixcvdvrteudnYMuWLQih8vJywZdYLNagQYNqa2uF7ZuRkaGlpZWfn09uWb58+YgRIxBCPj4+HWqGsB3r6+vNzMz279/fodrCwsLU1NQ6tEuH7Ny5EyFUXFzc5qtcLjc5OdnV1TUxMRFvEd0tT58+NTExMTc3P3XqVGFhIZvNFva+giX9/PwCAwP/+uuvrh9U7/x8tgnG+30GIcbwsyvaHZny6cRAtdPDz95MV1dX2Evr1q0rKioS9iqHw/Hy8vL39x82bBi5MTY29uXLlzQaraPNELajmprauXPnQkNDX79+LX5tJSUlioqKHW2D+PT09NrcXllZGR4ebmZmtmPHjtmzZ0+fPh1vF9EtaWlpU6dOHTduXF5eno+Pz+DBg+Xl255uss2SgYGBKioqU6ZMcXBwuHbtGpvNltQx9mo9/cUjLtR3vkvb1QuPpd2RKZ9OD1Q7N/zExO83cjWVuXPnFhYWkp92fX19giDILZs3byYI4urVqz/88IOioqKZmVlCQgJBEA0NDRcuXJgwYUJwcDBZ540bN0aOHKmqqjp69OjMzExy++HDhxFCHz58CAkJ0dbWNjIyunHjBkEQq1ev5v1H+/LlC18jY2JiEELv378XbL+GhkZHx/uid7S2tnZxccGPX79+raOjs2/fvjZrSE5O5gsRBQUFvL0xceJE8qXU1FQ8ckcIxcbG4hoE+xN78uSJra2tsrKylZXV5s2bEc94n8vlpqSkuLm59evXb+3atXl5eWIeXVVVlY6OzrRp00SM8cUpyeFwbt68OWvWLCMjo6CgoM4N/3vh/7UwEPd7QC88lmXLliGExIz7bDbb3Nx8165dfNs5HA6NRms3YD158oRKpb569aqjjRS/3z59+uTo6CgvL19ZWUkQRG1trZ2dXb9+/b5+/YoLREREHDx4sKmp6ezZs/b29oWFhVVVVXPnzqVSqVlZWRcuXNDU1EQIBQUF4fK3bt2iUCgxMTEsFisqKgpHOiqVymQycdz38/N7+fJlVVXVjz/+2K9fPy6XSxAEvhAqrFcnTJhgbm7e5ksSj/v+/v4KCgp1dXUEQbx69UpLS2vv3r0i6lm1apWOjg5+zNcb1dXVgYGBCCFHR0cul1tfX6+npxcfH9/S0kIQRJv9SRBEZmamkpLSoUOHamtr4+PjlZWVcdzHA/zBgwePGjUqKiqKxWJ16Oj8/PwQQgcOHBg1ahSNRrOwsEhOTm5zXzFLvn//fseOHQwGAw//8UGJqRf+XwsDcb8HdPRY+Iafb9++DQgI0NPTKysr27Ztm46OjqGhYXx8PEEQWVlZ69evNzExYTKZs2bNUlFRsbS0fPjwIUEQcnJyvL/wvv/+e3IcKjgyFT0k7PpAlXf4Kb4O9VtGRgZCiLyccPLkSYTQixcv8FMPD4+mpiY2m62np/fmzRu88d27dwihRYsWEQSBF3gh4/7ChQvxbwVs9OjRs2bNwo9x3C8qKsJPw8PDEUIfP34kRMb9pqYmBQWF+fPnt9l4icf9X3/9FSGEf4iIgzfuEwK9QRCEh4cHhUJJTU3dvHnzrVu38EYR/WlpaTljxgxydx8fHxz33d3daTRaTExMJ46utbVVV1fXyMgoISGhvr4+Ozt74MCBSkpKgqN18UtiDQ0NS5YsQQhdu3ZNnIZhfShGwfn9PiAhIcHPzy8tLY0gCISQt7c3ziE5ePCgi4vL33//PXjw4DVr1nA4nNmzZ0dGRlZWVp4+ffrUqVMvXrxgs9mOjo5v37799OnT0KFDyTqfPn06btw4/DgqKoo3QqmqqhIEgUesbbbn/Pnz5ubmJiYmnT6iCRMm3Lx58/Pnz52uoV3jx483Nze/ceMGfpqVlaWtrR0fH48Qqq+v19XVpdFoeXl5lZWVQ4cOpVAoFAoFnx3Kz89HAmftVVRUPn/+3NLSgp8aGBhkZWXxFsADWFwSIdTU1CS6eSUlJWw2u1+/fl0/UnEYGRkhhERcbBBN8BpGVFTUiBEj5s+fr6enN3v2bLxRWH/m5ubm5uaSJ+sRQlZWVvhBRETE7t27w8LCbG1tz58/39jYKH6rysvLq6qqJk2a5OLioqamZm1tffTo0aampl9++aXTJYuLi0NCQgYNGlRRUREfHz937lzx29OHQNzvAzw9PXkvyqWnp2/cuBEhFBAQYG1traGhMW/evLq6uoqKirKyMicnJyqVunPnTgaDMXTo0BMnTjQ3N0dERGhqajo4OJCVaGtr8z7lY2FhUVNT02aWW3Nzc0ZGxvDhw7tyREOGDGGz2Q8ePOhKJe1atmzZ3bt3GxoaKioqDA0NlyxZcu3aNYTQ7du38WiuqqoKIcRkMnmHQnl5eQghKvX//Gts3bpVXV19y5YtX758ef78eVpa2owZM0S8tbCvTBKLxUIIdeL6befQ6XSEUHV1ded25+sNhJCKisr27dvr6uoeP35MHqyw/nzz5g0ScgFcT08vKCiooKBg9+7dSUlJAwcO9Pf3/+OPP8Rp1ZcvXxBCampq5BZnZ2c5ObmCgoKOlmxtbU1MTHRycrKxsWltbX38+HFKSoqrq6uCgoI4LelzIO73DXz/MzgdQklJCT/FY0ycisBgMKhUKnlWZ/Lkyerq6i9evEAI8WVokLt3iEQGql0cforJ09OzsbHx7t27cXFxPj4+K1asKC4u/v333//8888xY8YghDQ0NBBC+EeAaEOGDNmyZUteXp6BgYGrq6u3t3dkZGRX2qatrY0Q+vr1a1cqER/+/aGqqiqpCplMZlxcXExMzK1btw4ePIg3CutP/MF7//69sNooFIqDg0N8fHxeXp6hoeGcOXPs7e3j4uJE/2wyNjaWl5cvLi4mtygoKGhoaBgYGIhfsrS0dPfu3d99911ERMSKFSvev38fHh5uamoqVi/0WX1pfV1ZxjfgEhx/iXiJwWCQJyi6TiID1S4OP8XUv3//yZMnX79+3dTUlMFgMBgMS0vL8+fPkz9WrKysNDQ0tm7dymazly5dSqfTc3Nzb968eeTIEfwlyuFwcMlnz54lJSXdv3+f/EIl4ZKtra34KZfLJXfEebdtjv2NjIxoNFqH7l3qik+fPiGEzM3NxSzf0tLS3NxMPuXrDRaLtWbNmqioKAaDkZGRERoaOmbMGAcHB2H9uWnTJiqVeunSpeDgYN7PZ1VV1cCBA3nfV19fPzg4OCgoKCUlJSoqSl1dfc6cOcIaqaam5uTkdO/evbKyMjySKC8vr6mpETw5I6JkeHi4kpLSgwcPBg8eLGbnfANgvP8N4gs0NTU1ZF5j10lkoCrx4acwXl5eV65cIWPHihUroqOjyUkRlJSUdu3a1dzcHBQUZGxsrKmpOXXqVFwYn4PKyMjAZ5wvXbr06NEjeXl5yj8GDBiQnJxcW1ubnp6OEEpNTeVyuWw2Oy0tDSH06NEjgiC0tLQQQllZWdHR0aWlpbwNo9FoEydOxCdAeBEEUVZW1tjYWFZWxjvanTNnjr6+/uPHj4UdqbAdsfz8fCqVamdnhxDKy8vT1tYWMelCaWlpeno6i8VKTU3FW3h7AyfqTJs2jcFgIIR27dpFoVDc3NwePHigqKjYZn8aGxv/9NNP+fn5y5Yt+/DhQ1FR0W+//YYQmj59Or4MzodCoUybNu3atWvkH07Y0R09epROpy9atOj9+/dMJnP58uXTpk3Df1++HhNWMiIi4tChQzIV9BGC/P2e0IljaWhoQP/kmxMEsXfvXvRP0ghBEPicQ2FhIUEQPj4+VCq1oaEBv/THH3/gBESCIIKDgxFPInlISAj6JxEF/1SvqalptyVNTU00Go03N4OXmIko586dQx1MliA61W8sFotMvCEI4tOnTwsWLOArExUVZWpqqqysPGbMmJSUFIIgcFTCLC0tCYLIzMwU/JYyNDTkTWYPCwsbNWoU+TQ2Nra6utrGxkZXV/fSpUuCbbt48SISuGcVJ7aTXr58ibfb2dn1799/5syZwo5U2I7YyJEjyX1zcnI0NTWF3fuN86BIpqamfL1BjqbxLcpTp04lX8WZkYL9SRAEh8MJCQnR1dVVVVX19PQMCwuzsrKKjIzEqaXtEnF0+fn506dPV1VV1dfX37hxI5kJKthjwkpKSh+KURD3e0AnjuX27dsIIRsbm4aGhqamJkdHR4TQ5cuXuVxuS0uLq6srQuj06dNcLtfHx4dCoaxZs6a6urqoqMjW1nbs2LE4DfnMmTMIoWPHjrFYrOjo6MmTJyOEtLW1o6OjT58+jf9vz5w5w2Qyc3NztbS0hIWG6dOnDxgwgG8jl8stLS1VVFR0dnZubGwktzs7O+vp6aWnp/MWDggIoFKpbc5tIEIPfgauXr165swZ8unXr19fvXo1atSo1tbWTtfZ2to6bNiwgIAAMcuzWKyFCxd24o1ycnKoVOrz5887sW+f1uke65w+FKMg7veAjh4L34CLd4x5+PBhMh0TIXT8+HEfHx86nR4ZGamtra2uru7p6VldXY3raWhoWLBggZKS0vDhw1NTU/ft2zd+/Hh8LxLfyFT0kLDrA1Xe4af4euoz8PbtW21tbb4Qz+VyDx482MWas7Oz1dXVMzIyxCkcFhaGk2c6pKmpydbWljf1XnZ0rsc6rQ/FqG8n7vNGQ4xOp5uYmDg7O8fExHA4HKk1tV3d+vnAcb+bKse6OFDt9PCzp/6vbt68iRDy8fHJzs7+/Pkzi8XKycnZvn17WVmZRCo3NjZOSkoSXeyXX37B1ww6hMlkOjg4eHl5deV3SR/VuR7rCoj7ktdun3K5XJx5jdXU1JSXl//66684aXfkyJGlpaVSa61o3fr58Pb2VlJS6qbKSZ0eqHZl+NmD/1dJSUmOjo76+vqKioqmpqaBgYHiXAsRU15eXjedjtizZ09UVFR31AwEQdyXPDH7lEyzI69ekndsjho1qrm5uZubKZbu+3zU1dVZW1sjhNLS0vANt92nEwPVLg4/+9D/FZBBfejz+e3ncc6fP9/MzAwhlJWVdfXqVbzx4cOH48ePV1JSMjMzwxuvXLlCpuidPHnSwcFBQ0Pj+++/J/PAUlNTf/jhBw0NjZCQkOjoaHJOR8GqekpdXZ2mpubLly8RQhMmTMCz6HQfZ2fnO3fuxMbGii7m5+c3YcIE/Pjs2bNubm7nzp0Tcf8BAKDb9fQXj7hQZ8f7BEGQE747OTkRBHH37l15eXkPD4/6+vpFixZRKJQnT560trbiWQYRQu7u7uXl5ThBDc+Y+PnzZ01NzbFjx3769On27dsaGhrZ2dnCqpLUsQA+0G+gN+tDn0+ZGHYZGhriB3/99RdCyNfXl8Ph/PTTT2pqavi86v7/396ZhzV1dI9/EtkX2WSRTRShLiiguLEpiloRbBEEKkVbRVFUpK+CIOJaAddWFMsqLrxVEbW41OcroKIUsBUElFqhgmAAQdlB1uT+/pif98mbkJBACEvO56/cueeeO/cQTubOnDnn8GEqlTp+/HgsFhAQoKGhgSdMioqK2tvbi4qKGhoa/v3335KSkuXLl0dFReFtqz2qGqSnBAAA4AmRyNNA5krs7OwsKirCUzRWVlakQF5eHvtV5KvDp0+fJk+erKamVlNTY2FhERQUFBQUJCYmxrsqAACAoYNIjPdxmkCEkIGBwfv37/Hn3377jXzrYdlDzwKDwZCVlb1165aGhkZXV9f+/fttbGyam5v7oAoAAGDQEQm///TpU/zBycmJTGzJnhqFO3PmzHn58qWTkxNCKCMjIyQkpM+qAAAABpGR7/fz8/PT09MRQpMnT/7+++/19fVxEuPz58/j1Im8UFFRERoaqqKikpSUhHPfFxUV9U0VAADA4DKi/H5RURGZDreoqKiuru7GjRvLli1jMBjTpk37/fffJSUlJSQkdu3ahRB6/fr1f/7zn7q6uufPn1+4cIHBYOCycAiht2/f0ul08rC0tFROTm7v3r3h4eGNjY04IeWyZcs4qRqEJwf+lz///HPDhg3kQj0LdXV12traXBJS9oHc3FwyzScvhISEJCQkCLADAufly5d2dnby8vLq6uqenp4aGhqCslhJSUlQUJCmpubbt28FohDgG+GHEPUNxH+ehlGjRuEaDhcuXOjq6mIWPn78+Pii6zljAAAgAElEQVTx4yUkJCZOnHjs2DE6nX758mXma3E9UpL29vbg4OC4uDhtbW01NbXg4GByVxS7qv4/C9AjPNqNTqdrampSKBTmCrHM1NbWampqhoaGCqpjSUlJenp69+/fx4dVVVURERE2NjZbtmzhdElZWdns2bO9vb0F1QfBQqPRFBUV7927V19f7+fnhwsJCMpidnZ2uBILS4onLvRq0sbGxrCwMDMzM1lZ2aCgIC6qeJfkl2H0fz1y/P4wYiQ9izDhy27Lly/n5PcFS1ZWlpKSUmFhIdny3XffTZs2DSHEPSV1U1OTgYHB4cOHB76PfBMaGiovLz9w+vft28fF7zMYjJSUlFWrViUnJ+MW7ibNzMzU0dExNDSMjIwsLi5mGeRxl/Tx8fH39+dUYJ0vhtH/tUjEcQIiCF56GWi6u7vXrl27ffv2KVOmkI3x8fF0Oh3XFOOCvLz8+fPnraysVqxYYWRkNMA95Y+3b9+yVOUULJz+OjU1NfHx8TExMWpqaps2bSJLsXMxKa51vHz58oSEBO5l4HqU9Pf3j42NXbhwoYGBgZeX19dffz1Sa+oyM6Lm9wGABKeCyMvLmz9/vrS0tImJCU650dbWdunSpfnz5wcGBmLJ8vLyVatWqaqqysrKWlhY4EQXCKHi4mJra2tFRcVdu3bFx8eTYbvMXLx4saioaN26dSzto0aN4qV8sbm5ubGx8f79+/FhYWHhmDFjBnfrX2pqKoVCiYqKqq2txWlLiouLmS22YMECMqPJo0ePcL0tCoWCa+kghBITE42NjSUlJQ0NDa9fv05qzszMtLS0lJGRMTU1ZSmtTBBEWlqaq6vr1KlTy8rKbt68mZmZuWbNGmYb9mhSXEjH0tLy8uXL3J0+J0ktLa19+/aVlJRs3779woULenp6AQEBb9686aP5hguD/cLBK2j4vEP1ykh6FmHCl93Wr18vJSUVFhZWVVWVl5c3depUWVlZGo128eJFRUVFhBCZE9TMzMzW1raqqqqoqEhbW3vu3Llk+7Vr19ra2h49eqSiotJjlRhra2ucyYMdHkuPbd++XVxcHJedevHihZKS0qFDh3h8xoFj/fr15CwZi8Vqa2txRpOlS5cyGIympiY1NbXExERc2+fcuXNWVlbFxcW4HCOVSs3JySEIIjs7W0pK6ujRo/X19YmJiXgrZWlpaU1NzZEjRyZOnDhz5szo6GjuNbDYTerj44MQCgkJmTlzpqSkpJGREa75xQ6PkuXl5Xv37tXW1ra1tb127Rp+KB4ZRv/X4PcHgUH6iR8J8OX3mef38/LyKBTK9u3bCYKg0WiIye/PmDEjIiICf167dq2qqirxubDlX3/9hdvDw8PZ/X57e7u4uLijo2OPHeDR7+MIghs3bvD4XMKBxXosFiMIwt3dnUKhPHz4cMeOHbdv38aNXV1dampqr169woc4Is7NzY0gCGNjY+banF5eXgih0tJSV1dXSUlJXAe0V1hMSqfTVVVVNTU1k5KSmpqacnNz9fT0pKSk2CfreZfEfPr0afXq1YjPUqB8fT8HF5jfHxx8fX3nzZs32L0YZri6uvb5WmNjYx0dnfz8fIQQueEOk5OTgxB6+vTp6dOnr1+/jicTpKWlx44da2Njs3Xr1q1bt27bto1d59u3b7u6usaMGdPnXiGENDU1EUIs8x5DDRaLIYSio6NfvHjh6OgYGBhob2+PGwsKCmpqaiZPnswsWVhYmJ+fn5+fv3btWrLRxMQEfwgPDzc1NQ0NDY2Li9u4caOLiwuZVaVXqqqqPnz4sHr1aryb0tTU9MSJE05OTqdOnQoPD++bZGlpaUxMTHx8/NSpUxMTE8liwiOMke/3S0pK4uLi4uPjMzMz9fT0Brs7/5958+a5uLgMdi+GGf3x+wghVVXVhoYG9Hnqn6SiosLT07OqqsrPz09MTOy3337D7YmJid98801YWNiJEyf8/PwOHTrEciHOzcd9WrlX8FplbW1tf5QMNOx5s2VkZPbs2ePi4pKRkUEGeuKEKDQaTUtLi1n4ypUrqKcfD4SQmprarl27/P3909LSoqOj/f393dzcvLy8mNfJOdHc3IwQwoWVMA4ODqNGjSoqKuJXkk6n37lzJzIyMi8vb82aNRkZGfr6+r12YPgy8td1t23bdvz48aqqqsHuCDDIVFZWTpw4kaWxpaXFyspKQUEhJyfH3d2deeXQ0tKyuLj4p59+UlFRCQkJ+fnnn1muxTv4Wltb+9Or9vZ2hJCcnFx/lAgfGo2WkJAQFxd3+/btsLAw3KigoIAQSkxMZBHGoUHl5eWctFEoFFtb28TExIKCArznxsrKKiEhARuHE1paWmJiYqWlpWSLuLi4goKChoYG75IVFRUHDhwYP358eHj4999/X15efuTIkZHt9JEo+P27d++SkRuAyJKdnV1VVeXh4YEQ6urqQgh1d3cjhJ48eVJaWrpu3Toy/SpBEAih9vb2H3/8UUpKytfX9/Xr15MnT87KymLRqampKSkp2c8hxcePHxFChoaG/VEicDo7Ozs6OshDZoshhFpaWjZu3BgREbFu3TpPT8/g4ODU1FSEkImJiYKCQmBg4NGjRysrKxsbGx8/frxz5845c+ZQqdRff/2VJZ0JmTCRRF1dPSAgoLi4eO/evcnJyffv3+fSSXl5+WXLlqWnp1dWVuKWqqqquro69skZLpJHjhxpbW198OBBWlqai4uLKARxIiQa8TwRERGIn82BA01/nkWU4ctuwcHBFApl9+7dVVVVBQUFkyZNWr9+PT51584dhJC5ufmnT59w3uw1a9Y0NDQkJiYaGRmJiYkVFhbeu3dPQkIiMjKyoaGhvLx80qRJ5NovM0uWLBk3bhxLI4PBqKiokJCQcHBwaGtrI9sdHBzU1NSePHnCLOzn50elUvGicX5+vpKSUkhICM8mGRBoNBqeEX3w4AFuYbZYTU3NwoULT548SQqLiYkpKSmlpaXR6fSffvqJ2b2IiYnhKpve3t4IIXd39/Ly8jdv3uDAfEVFxbCwMF66xMmkRUVFysrKVlZWZWVl7969W7JkyeLFi/EpFmtzkRQUw+j/esT6/T/++MPCwgIHbu/YsYPZ71+9enX69OkSEhIGBgZJSUkEQfzzzz9+fn5qamqVlZVBQUEqKipjx45NTEzE8kVFRXgqwN/f/9y5c2RcB7ueAXoWAMOX3RgMRkxMzJQpUyQkJCZNmnT27FmcWuPmzZukVzI2NiYIwt/ff/To0UZGRjdu3Lh06ZKsrOwPP/zQ2tp65syZgwcPqqmpaWlpHTp0qMd6xZcuXWIfUuDvG8nz589xu6Wlpa6urp2dHbPwjBkzyJa8vDxFRcXB9fssrzX6+vosFiNH0/gfAZelw+DIyOjoaH19fWlp6VmzZqWmpmK13d3du3fvVlVVlZOT8/DwCA0NNTExiYiIwAGsvcLJpARBFBYWLlmyRE5OTl1d3dfXl4wEZbc2J0lBMYz+r0em3+cULExwiC+2tLTEr/k+Pj65ubkNDQ1WVlaKiop4w3ePcdyc4pQF/iwAyRC0G51OnzJlip+fH4/yLS0tuC4bJi8vj0ql/vnnnwPTO1GHxdoDzRD8fnJiZPp9TsHCXOKL8YDi3bt3+NSJEycQQjQarcc4bi56BP4sAMnQtFtubu7o0aOzsrJ4EQ4NDc3IyMCf29vbLSwsmIPiAcHCbG0hMDS/nz0yAtd1cbAwmdkDMQULk/HFeGf5uHHjEEKFhYXoc8IQMpxDRkYGIdTV1UXGcQcGBlZUVGzbtk1DQ4OLHkDUMDU1TUhIcHZ2/v3337lLhoeHm5ubW1hYIIQqKirs7e0nTpwYEhIilG6KHMzWBlgYgX4fV7/qMViYjC9m/ukrKChAPUUokyQmJuIFqPHjxwcFBTEYDC56ABHEwcHh3r178fHx3MV8fHysra3x53Pnzrm4uJw/f57LFw/oD8zWBlgYgd85LsHCnOKLucMex903PcAIZtq0adeuXeNdPjg4eMOGDQPXHwDgwgj0+1yChTnFF6PP22fIcl342u7u7h7juLnoAQAAGOKMQL+vpaW1adOmwsLCNWvWvHv3rqSkBAeiLVmy5NSpU/v37+/o6Ni1a5eWlpaiouKiRYtWrFjR0dGBk/Q+fPiQIIiurq5Hjx6hz/HLhw4dioqKamxsbGxsJAjCxsZGSkqqRz2D++AAAAC8MDLz84SHhysqKsbExCQnJzs6OtrY2NTU1GzYsMHd3V1BQUFWVvbIkSOVlZVGRkahoaHW1tYLFizAtde/+eYbGo2WlJT09OlThJCXl1dTU9PJkydramoMDQ3FxcU3bdq0efNmhJCvry+7nkF+bAAAAF4QXuhQ/0DDJ0aqV0bSs5Dk5OR8/fXXvMsfPnz40qVLfN1iRNoNGDEMo+/nCJznEXHOnDmDs04KU8n169ednJzwXnyE0Pv378+ePbtw4cKtW7dyuuTbb789ffr0li1b+tlVAAD4Bfz+iKK1tZUlQYoQlGRnZ2/YsOHu3buLFy/GLYGBgZGRkQ8fPiQzebGjq6ubmpqakpICAewAIGRG5vy+yOLt7d3/Ch58KRmphcUBYAQD4/2hS3p6+vz582VlZTU0NDZv3ownXsTExPAmYSwzadIkfIhT4168eBEhpKSkRKFQHj9+vHXrVl1dXbw1VFZW1sTEBC9f866kpaWFe7FvwRYWFylyc3MdHR15lw8JCUlISBi4/rDw8uVLOzs7eXl5dXV1T09PDQ2N0NBQgWguKSkJCgrS1NR8+/atQBQCfDPYCwy8gobPmkmv8PIs9+/fl5eXv337dnNz89WrV2VlZc3MzLq6uurr63EdOyxWW1s7Z84chFBzczNBEPg/s76+niCIsWPHIoQkJSWDg4PfvXv3999/T5kyRVJS8tWrV7wrIXor9i3YwuLcEc534PTp0+SzD5ySpKQkPT29+/fv48OqqqqIiAgbG5stW7ZwuqSsrGz27Nne3t797Bsv0Gg0RUXFe/fu1dfXk+W0QkNDBaLczs4Ob67kPTV6r/ZpbGwMCwszMzOTlZUNCgrioop3SX4ZRj4K/P4g0OuzMBgMAwODrVu3ki379u1DCJ09e5YgCFzrlTwVFBTEyWUvW7ZMWlq6u7sbHz548AAhtHnzZr6UcEHIhcWF8B1oaWmZMGFCP/1+r0qysrKUlJQKCwvJlu+++27atGkIIe4Wa2pqMjAwOHz4cH+6xwuhoaHy8vIDpx9/nzn5fQaDkZKSsmrVquTkZNzC3T6ZmZk6OjqGhoaRkZHFxcU4jW6PsEv6+Pj4+/tzKrDOF8PIR8E8z1AkJyenuLjY2NiYbNm4cSNC6O7du+hzIgoSLtMp2traVCqVrCRlY2MzevToZ8+e8aWECyOvsLgQFkg4rYg8f/6811K9eEUkODj45cuX/ewkd96+fcvyDREsOA0iOzU1NUeOHDEwMNi7d6+9vT2ZXZGLfR4/frxo0aI5c+YUFBR4eXlNnDhRTKznZcseJf39/WVkZBYuXGhra3vt2jVcWWzEA35/KIITO+MU0BhNTU0ZGRmyShyPsOf80tbW7uzs7H8PMUO8sPgQWSBh6ZVgV0S4r770gdTUVAqFEhUVVVtbix+quLj40qVL8+fPx/VKFyxYQPnMo0eP9u/fjz+fP38ea0hMTDQ2NpaUlDQ0NLx+/TqpOTMz09LSUkZGxtTUlOV3kSCItLQ0V1fXqVOnlpWV3bx5MzMzc82aNcwG6dE+Hz9+XLlypaWl5eXLl7l/DzlJamlp7du3r6SkZPv27RcuXNDT0wsICHjz5k0fzTdMAL8/FNHS0kKfE4uSiImJTZgwgV9VBEEwH9bV1eGs0QJhKBcWT0lJcXBw8PPzq66uDg8Pv3Tp0uLFi7u7uz9+/IjXNjCZmZl4bQMhFB0dzTzH5ebmFhERUVNTExUVFRkZ+ezZs66urqVLl/7zzz+8K2F/rgsXLhgaGuro6PT50aytrW/dutXY2IgQIggCFwLrszYWbG1tCYJYv369iooKnhPIzs728fF5/PgxvsuNGzf8/f0RQkuXLp0/f/6OHTvU1NQSExPd3d0RQvHx8WfOnLl+/XpFRcWUKVNcXFxyc3MRQk+fPl20aNFXX31VWVm5e/fus2fP4tt9+PDh6NGjhoaGu3btsrW1ffv27dmzZ/GUDi8cOnSotrbWxsZm7ty5UlJS06ZNw5V++ZUcNWqUg4PDnTt3srOzJSUlFyxYsHjx4qSkpJE6/Ae/PxQxNTXV0dG5cuUKOVqk0WhNTU2urq4IIVz6mTzV1taGPqeYxiNQZi/Q3t6OBRBCr169qq6uxnXy+FLCiSFbWJwgiC1btqxdu9be3l5OTs7FxWXnzp3Pnj2LiYlRVFS0tbUlJZWVlZkPmamsrFy2bBmVSt23b5+2tvbkyZPPnDnT0dGBs4DwqISFjo6OrKysqVOn9ufpJk2a1NXVhVdrjIyM6urq9uzZ0x+F3PHw8GCeVlJWVj5y5Ii7u/v9+/fT09MPHDgQFxe3atUqcXHx7u7ugICA6OjoiRMnjhkzJjw8nMFgHDt2DCHk5eW1YMECPz8/RUXFVatWrVmzBmvbtm3b3r17AwMDnz17tmHDhl5jf5lhMBiXL1/W1NQ0NDR8+PBhVlZWS0uLg4MD+2idd0kdHZ0DBw4UFRWpqanhBYa+mGzIA35/KCIpKXn8+PGGhgZ3d/fKysqqqqrNmzcvXbrU2dkZIaSvr48QiouLa21tjYuLwwVRzczM4uLilJSUEEI5OTmxsbEVFRUIIYIgfH196+rqSktLN2zYMGvWLA8PD76UFBQUKCsr9xjDJykpOX/+fJb3EnzTysrKtra2yspKPJzHrFixQl1dHafAIyksLKRSqZaWlgI04JBdIBmmKyLs1Syio6OnTZvm6OiopqZmb2+PGznVI+JSCik8PPzAgQOhoaEWFhYXLlwgxyi8UFVV9eHDhwULFjg5OcnLy5uamp44caK9vf3UqVN9liwtLd29e/eECROqq6sTExPJYsIjDPD7QxQXF5ekpKSysrIJEybMnTt3+vTpycnJeCTu7u6+cuXKgICAOXPm6OvrL1q0aO7cuceOHXNzc3N2djY3N1+9erWsrCyeLJKRkTE2NjYwMDAxMZkwYcK9e/fwSJ93Jfhln1M/PTw8ysrKWAKx/fz8tLS0Ojs7b9++LS0tnZeXh9vr6+ulpKRYfkLS0tK+/PJLDQ0NAVpvyC6QDPEVEU6w20FGRmbPnj0NDQ24kCFu5FSPiEspJDU1tV27dhUVFR04cODu3bt6enrbt2//+++/eelVc3MzQkheXp5scXBwGDVqVFFREb+SdDo9OTl52bJl5ubmdDo9IyMjNTUVv8Tw0pNhB+zXHbo4OTk5OTmxt0tLSzMvly1YsABHYSKEZGVl//jjDxZ5b29vMnNOH5QYGxvX19dz6uTq1atDQ0PPnj179OhRsvH48ePHjx9nF37y5Elra+t3331HtuTn5+fl5WVnZ3PS3zcGdIFk9uzZfe7YUF4R4QsajZaQkBAXF7d+/fqwsDC85EvWI/rhhx+YhbmUQsJQKBRbW1tbW9vq6ur4+PgVK1aMHTvWy8vL2dmZy4uUlpaWmJhYaWkp2SIuLq6goMA+huAiWVFRERsbGxcXZ2Bg4OXl5ejoOFJ9PTMw3h/J0Ol0spLMAEGlUhMSEqKionj03adPn/b19cWfOzo6tmzZ4ufnN2vWLMH2asgukAzZFREWOjs7Ozo6yEO8vElmW8JhSxEREevWrfP09AwODsZrpJzqEXEphcRyX3V19YCAgOLi4r179yYnJ9+/f59LJ+Xl5ZctW5aenk6+xlVVVdXV1bFPznCRPHLkSGtr64MHD9LS0lxcXETB6SME+3UHA+E8S0NDg6mpKULo8ePHOORj4Lh165aWltbdu3e5i506dSo9PR1/ptFotra2a9eupdPpPN6FL7tdvXoVIbRixYqKiorKykp7e/ulS5diO8TExCCEfv7555aWltjYWBsbG4SQsrJybGxsVFQUQiglJSUmJoZGo3l5eVEolI0bN9bW1paUlFhYWMyePbuzs5MvJSwdW7Jkybhx41gaGQxGRUWFhISEg4NDW1sb2e7g4KCmpvbkyRNmYT8/PyqVWlVVRRBEfn6+kpJSSEgIj2bhBRqNpqenhz7XHSII4s6dOwghc3PzT58+1dTULFy48OTJk6SwmJiYkpJSWloanU5nyegnJiaG/+L4jdPd3b28vPzNmzd4rh+XrealS5zsU1RUpKysbGVlVVZW9u7duyVLlixevBifYjEdF0lBMYx8FPj9QUAIz8IyMxMTEzOgtyMIoqCgwNnZmXf5gwcPRkdH83ULfu2WlJSEA8l1dXV3797d3t6O2z99+rRy5UopKampU6c+fPjwxx9/nDt3blxcXEtLS21trbm5uaqq6q+//koQhJeXl6ysbEREhLKy8ujRoz08PGpra/lVwsKlS5cQ21bVHTt2MP+9nj9/jtstLS11dXXt7OyYhWfMmEG25OXlKSoqCtDv4xV+En19fVyuDmNsbEyOpvEPz6JFi8izKSkpBEFER0fr6+tLS0vPmjUrNTUVq+3u7t69e7eqqqqcnJyHh0doaKiJiUlERAQv+Tm42IcgiMLCwiVLlsjJyamrq/v6+ra0tOB2dtNxkhQUw8hHgd8fBEbSswgT4dsN+33B6qTT6VOmTPHz8+NRvqWlhfkHNS8vj0ql/vnnn4Lt1YiExXQDzTD6v4b5fQDgyEAskAzNFZERCbPpAGbA7wNAzzQ2Nubk5LS3t+M5YgFqNjU1TUhIcHZ2/v3337lLhoeHm5ubW1hYIIRwuoiJEydCpRpeYDYdwALEcQJADzQ0NOD9awgha2vrmJgYT09PAep3cHDQ09M7ePCgnZ0dFzEfHx/y87lz51xcXDZs2CDAboxgmE0HsAB+HwB6QFFRUbBjfHamTZt27do13uWDg4MHrjOASAHzPAAAAKIF+H0AAADRAvw+AACAaAF+HwAAQLQAvw8AACBagN8HAAAQLcDvAwAAiBaUgQ5SFhRkDWsAAIChydWrV11cXAa7F70zbPZt4bS6ACAoXF1dfX19582bN9gdAUYO5ubmg90Fnhg2430AECwUCmW4jM4AQLDA/D4AAIBoAX4fAABAtAC/DwAAIFqA3wcAABAtwO8DAACIFuD3AQAARAvw+wAAAKIF+H0AAADRAvw+AACAaAF+HwAAQLQAvw8AACBagN8HAAAQLcDvAwAAiBbg9wEAAEQL8PsAAACiBfh9AAAA0QL8PgAAgGgBfh8AAEC0AL8PAAAgWoDfBwAAEC3A7wMAAIgW4PcBAABEC/D7AAAAogX4fQAAANEC/D4AAIBoAX4fAABAtAC/DwAAIFqA3wcAABAtwO8DAACIFuD3AQAARAvw+wAAAKIF+H0AAADRQmywOwAAQqKsrIxOpzO3VFdXl5SUkIeamppSUlJC7xcACBsKQRCD3QcAEAZ2dnb37t3jdFZcXPz9+/fKysrC7BIADAowzwOICm5ubpxOUanUxYsXg9MHRATw+4Co4OjoKCkpyemsh4eHMDsDAIMI+H1AVJCXl7e3txcXF2c/JSEh4eDgIPwuAcCgAH4fECHc3d27u7tZGsXExBwdHWVlZQelSwAgfMDvAyLE8uXL5eTkWBrpdLq7u/ug9AcABgXw+4AIISEh4ezsLCEhwdwoLy+/ePHiweoSAAgf8PuAaLF69erOzk7yUFxc3M3NjeWXAABGNhC/D4gWDAZDXV3948ePZMujR4/mz58/iF0CACED431AtKBSqe7u7uQAX1VV1crKanC7BABCBvw+IHJ88803eKpHQkJi7dq1VCr8FwCiBczzACIHQRB6enrl5eUIoWfPns2cOXOwewQAQgVGOoDIQaFQ1qxZgxAaN24cOH1ABBFGPs6TJ09mZWUJ4UYAwCNNTU0IIVlZ2VWrVg12XwDgf7h27dpA30IY4/2srKzs7Gwh3AjgTlJSEo1GG+xeDAlGjx6toKCgo6PDizDYDRAONBotKSlJCDcSxvw+HlIJ4UcM4A6FQrl69aqLi8tgd2RIkJKSwuN2LbAbIBwSExNdXV2F4JNhfh8QUWCPLiCygN8HAAAQLcDvAwAAiBbg9wEAAEQL8PsAAACiBfh9gBt1dXXa2tqhoaGD3ZH/ITc319HRkXf5kJCQhISEgesPAAwvwO8DvUAQBIVCGTj9Z86caWho4F3++vXrTk5O3t7e+PD9+/dnz55duHDh1q1bOV3y7bffnj59esuWLf3tKwCMCISxXxcYvigrK1dUVAyc/tbW1p9++unbb7/lUT47O3vDhg0ZGRlTpkzBLYGBgTk5OS9evDA0NOR0la6ubmpq6syZM0NCQnbv3i2AfgPAcAb8PjCYeHt7l5SU8Cjc3d29du3a7du3k04fIRQfH0+n03utjisvL3/+/HkrK6sVK1YYGRn1vccAMPyBeR6AI21tbZcuXZo/f35gYCBC6PXr1/7+/urq6lVVVXv27BkzZoympibehp2bm7t161ZdXd2Kigp7e3tZWVkTE5P09HSEkJiYGIVCIWeKJk2ahA9bWlo2btx48eJFhJCSkhJuKSwsHDNmzOHDh3vsz8WLF4uKitatW8fSPmrUKCkpqV4fx9zc3NjYeP/+/X23CACMCMDvAxxJSkry8fF5/Pgx3jju6el58uTJmpqasLAwJyenN2/eTJw4cePGjd3d3fb29hERETU1NVFRUZGRkc+ePevq6lq6dOk///zz8ePHyZMnkzozMzPnzJmDP0dHR+MV4/r6eoIg5OTkCIJgMBic9qlfuHDB0NCQx6Q6PWJtbX3r1q3GxsY+awCAEQD4fYAjHh4eL1++JA+fPHni6+uLEPLz8zM1NVVQUPj6668bGhqqq6srKyuXLVtGpVL37dunra09efLkM2fOdHR0hIeHKyoq2trakoJX7ngAABjfSURBVEqUlZWZD1kwMjKqq6vbs2cP+6mOjo6srKypU6f254kmTZrU1dX14MGD/igBgOHO0PX7sbGxjx8/5veqTZs2kaVTIyMj5eXlZ8+e3dLS0s/ODJDaoY+qqirzoZqaGkKInFSRkZFBCHV1dSGEtLW1qVTqqFGj8CkbG5vRo0c/e/YMIcRStZyXORl23r5929XVNWbMmD5cS6KpqYkQ4n1FAQBGJEPU7zMYjGPHjh07doyvq5KTk6OiopiVEARBp9P72ZkBUjssYKlByKUkIfspbW1tXM5QIOBfWUlJyf4owcu/tbW1gukTAAxPhqjf/+2334qKiu7evfvq1SseL3n8+LGHhwdzi7e3d0tLS05OjpycXJ97MkBqRyQs8/J1dXXjxo0TlHJlZWWEUGtra3+UtLe3I4TgDweIOEPU7+NQEIIgehzyp6enW1paysjIqKure3p6Njc3//e//128eHFzczNCSFVVlUKhLFiwgPKZ9vZ2IyMj8nDu3LkIof379+NDXOggISHB0tJSTk5OUVHRycnp/fv3CKFe1eL+3Lp1a+bMmdLS0tra2v/5z3/wyPTKlSuk5NmzZ21tbRUUFL744ouMjAwhGVEQ4Dmc7u5ufIgfmXzXYTAYLGfb2trw51evXlVXV3/11VcIIXFxcfR5wI4QwjIfPnxACOE4H14SjmtqakpKSlZVVfXncfBkHZdIfwAQCYiBx9nZ2dnZmXf5Bw8ePH361MzMDCEkISFRUVHBfPbJkyfi4uLz58+vqanB/8AbN24kCCIoKAg/0YcPHwiC6OjosLOzwy1tbW0lJSUGBgb4kEajEQTR3d391VdfRUVFdXd3Hzx4ECGUkZFRXV09bdo0hJClpSW+HXe1BEHcvHmTQqF88cUX1dXVcXFxCKEZM2Z0dnbS6XR/f38s6erqWlVVtWjRIoSQoaGhgOzKNwihq1ev8nXJnTt3EELm5uafPn1qb29funQpQujy5csMBqOzsxNX1ImKimIwGF5eXhQKZePGjbW1tSUlJRYWFrNnz+7s7CQIIiYmBiH0888/t7S0xMbG2tjYIISUlZVjY2PxBFpKSkpMTAyNRsvPz1dSUgoJCemxM0uWLBk3bhxLI4PBqKiokJCQcHBwwH8RjIODg5qa2pMnT5iF/fz8qFRqVVUVX0bog90AoA9cvXpVOD55KI73U1JSZs+evWHDBoRQZ2dneHg489mdO3d2dXV5enqqqqpu3bpVWlpaQ0ODXYmEhMT48ePJw/Hjx0dGRuLPiYmJCCE6na6kpLRx48ZRo0adOXMGIZSRkaGmpmZhYYEQ4lQQmEUtnU7fvn078dnLrFmzRlxcPDc3Ny4ujkqlkpIBAQEaGhqmpqYIoaKiIvJFYYjz22+/2dvbI4QyMzPnzZu3dOnS//u//0MIffPNNydOnLCyssLB+15eXhEREQghGRkZY2NjAwMDExOTCRMm3Lt3D4/03d3dV65cGRAQMGfOHH19/UWLFs2dO/fYsWNubm7Ozs7m5uarV6+WlZXV0tLCX0pO/fHw8CgrK3v79i1zo5+fn5aWVmdn5+3bt6WlpfPy8nB7fX29lJQUS2ahtLS0L7/8sscvDACIEEL4beFrvP/8+fPY2FiCIJqbm/E8rIKCQlNTEz5bXl6Ou52WlsZyIcvAnCAIMh8LOQycPn06QsjIyIggiOTk5Nu3b+P2TZs2ycrKXrp0icFgfPPNN/iq7u7uXtXm5OTgzydOnMBnccCJnZ0dQRC//PILPvv8+XOCIHbt2oUPa2tr+2DG/oMGctzq5eUlKys7QMoxdDp9ypQpfn5+PMq3tLQwf/Hy8vKoVOqff/7J730H1G4AQCK64/3IyEg3NzeEkJycHP7Q2NgYHR2Nz5IReH2LofTx8UEIvXz58tmzZ3/99Rc5Y/PLL780NTUxGAxzc/PXr1/jRoKHSWdyupmMTcQT1jU1NVyuwtPiIww6nT7QMU5UKjUhISEqKio7O5sX+dOnT+MNBwihjo6OLVu2+Pn5zZo1ayD7CADDgKHl90tLS2NjY+Xk5PByaGxsLG7/+eef8QIjGYlBDrT5wt3dHY/Hf/nlFxxvjtuLi4vNzMx8fX3PnTs3b9483hWS4e3k2iaOXNTW1u5D94YvjY2NOTk57e3teD594G5kamqakJDg7Oz8+++/c5cMDw83NzfHs3Y4e8TEiRNDQkIGrm8AMFwYWn7/8OHDGRkZ5MsInU7Hq6w0Gu3y5csIoenTp+OtQ5cuXSJdbUdHB0KI3DHEBSkpqY0bNyKErly5gtckEUIEQdjb2z9//tzX15c5owCGu9oZM2bgyWIcKNLZ2dnU1IRErGZ3Q0ODoqLi8+fPEULW1tZ4cXvgcHBwuHfvXnx8PHcxHx8fa2tr/PncuXMuLi7nz5/nsv9ApBBmAYOXL1/a2dnJy8vj6DsNDQ1BlXMoKSkJCgrS1NRkWfIBekcIc0m8zO9XVlbu3r176tSp5FQ+Bq/BIoQUFBR+//337u5u0q18//33tbW1+fn5Bw8eJAji3LlzuD09Pf3YsWPNzc3Lly/HLfn5+aRCGo0mJia2bt06sqW6uhqLeXp6lpaWkulfPn78yIva//73vwih6dOn19TU/PTTTwihqVOndnR00On0gIAALHnz5s3u7m48bYUQ6sMUs0BAME/dJ4Rmt9OnT+NURQOqJCkpSU9P7/79+/iwqqoqIiLCxsZmy5YtnC4pKyubPXu2t7c3v52h0WiKior37t2rr6/38/PDs6ChoaH86ukROzs7vBW8tLSUx0t6fdjGxsawsDAzMzNZWdmgoCAuqniX5B2hze8PFb//xRdfkD9F165dw43shTKwfc+fP//FF19ISEjgN/euri6CIDo7O7///nsZGZlJkyY9fvx4/fr1zBeSq7IEQbi5ueXm5jLfHa/rGhkZhYWFJSYmqqqqqqqqbt++vaurixe1iYmJJiYmkpKSY8aM+f7776urqwmCwC8oJOQaLwb3WciA3+8bwrFbS0vLhAkT+un3e1WSlZWlpKRUWFhItnz33Xf4rdrLy4uL5qamJgMDg8OHD/PVn9DQUHl5eb4u4Yt9+/Zx8fsMBiMlJWXVqlXJycm4hfvDZmZm6ujoGBoaRkZGFhcXc/knZZf08fHx9/f/999/+/M4Iuf3ASEAfr9vCMdua9asQZ9Tkw6Qkq6uLkNDw/3797O0d3d3S0pKcvf7BEH88ccfVCr1xYsXvPfHy8tLRUWFd3l+wQHE7H6/uro6LCxMX19/3rx5Fy5cYN7Ywelh09PTpaWlnZ2d29vbud+0R0kajbZ//35dXd1FixYlJibinSv8An4fEDzg9/tGH+z26NEja2trvKV806ZN2BGTa0VYhnzHbW5uxrtVSNLT07ds2aKjo0Oj0ZYvX443Rjx69IgvJc3NzSy9wnOk5eXl7B1WUFDo1e8TBGFqaurk5IQ/v3z5UkVF5ccff+xRMiUlheVlvaio6OLFi9bW1gEBAQRBzJ8/nzz18OFDPHJHCMXHx2MNV69enT59uoSEhIGBQVJSEqn5jz/+sLCwkJaWNjEx2bFjB7PfZzAYqampLi4uY8aM2bx5c0FBQY99Y3/YDx8+qKioLF68uNcXce6S3d3dt27dWr58uaam5q5du/gd/oPfBwQP+P2+wa/d7t+/Ly8vf/v27ebm5qtXr8rKypqZmXV1ddXX1+PAASxWW1uLSxFgB81cimDs2LEIIUlJyeDg4Hfv3v39999TpkyRlJR89eoV70rYsba25rRdnEe/v337dnFx8YaGBoIgXrx4oaSkdOjQIS7y69evJ8f7Fy9eVFRURAjt2rUL9xxvaF+6dCmDwWhqalJTUyNHyufOnbOysiouLv7w4cNXX31FpVJzcnIIgsjOzpaSkjp69Gh9fX1iYqK0tDT2+zU1NUeOHJk4ceLMmTOjo6NbWlq49Ir9YXGEd0hIyMyZMyUlJY2MjFJSUnq8lkfJ8vLyvXv3amtr29raXrt2jcfhP/h9QPCA3+8bfNmNwWAYGBhs3bqVbMEj2bNnzxIEsW3bNuZ/bLwrsEeXvWzZMmlpabx5kCAIXDNg8+bNfClhpr29XVxc3NHRscdu8+j38TLVjRs3epXEMPt9giBoNBrp9zHu7u4UCuXhw4c7duwg91F2dXWpqam9evUKH5aVlSGE3NzcCIIwNjb+8ssvycu9vLyw33d1dZWUlIyLi+OlVywPS6fTVVVVNTU1k5KSmpqacnNz9fT0pKSk2EfrvEtiPn36tHr1asS0Zskd0d23BQworq6uFIBP+LJwTk5OcXGxsbEx2YJDh+/evYv4KUUg8HoGQ6GAAUs5B4RQdHT0tGnTHB0d1dTUcFIQhFBBQUFNTc3kyZOx/XFW18LCwvz8/Pz8/CVLlpCXm5iY4A/h4eEHDhwIDQ21sLDAE/q896qqqurDhw8LFixwcnKSl5c3NTU9ceJEe3v7qVOn+ixZWlq6e/fuCRMmVFdXJyYm4gSFQ4chWle9pKQkLi4uPj4+MzNTT09vsLvDSl1d3fTp07ds2YILzw7uHfmyla+vL18b0wCEkKurK+/CeHD66dMnskVTU1NGRqayspKvmwq8nsFQKGDA/lAyMjJ79uxxcXHJyMggAz1xrlYajaalpcUsfOXKFdTTjwdCSE1NbdeuXf7+/mlpadHR0f7+/m5ubl5eXlOmTOm1Vzjhrry8PNni4OAwatSooqIifiXpdPqdO3ciIyPz8vLWrFmTkZGhr6/faweEzxD1+9u2bUtNTRVg1Q6BQxAEvyPBAbojX7aaN2+ei4uLoLs2wuHL72NXxVI3QkxMbMKECfzel2CrZzB79mx+lZAMzQIGNBotISEhLi5u/fr1YWFheFijoKCAEEpMTPzhhx+YhfGLDpmkix0KhWJra2tra1tdXR0fH79ixYqxY8d6eXk5OztzeSvS0tISExMrLS0lW8TFxRUUFNjz93GRrKioiI2NjYuLMzAw8PLycnR0xEkJhyZDdJ7n7t27QhtK9wFlZeWKigpyW9bg3nGI20rUMDU11dHRuXLlCplCikajNTU14R8PvkoRCLaewaAUMOjs7MTb6TEs5RxaWlo2btwYERGxbt06T0/P4ODg1NRUhJCJiYmCgkJgYODRo0crKysbGxsfP368c+fOOXPmUKnUX3/9lSXDFX52ZtTV1QMCAoqLi/fu3ZucnHz//n0unZSXl1+2bFl6ejr5TlZVVVVXV8c+OcNF8siRI62trQ8ePEhLS3NxcRnKTh+hIbNflx1OkbkAOzzaCsG6bp/g1254dW7FihUVFRWVlZX29vY4ZIXgpxSBQOoZsHRMsAUMuBdLIAiCRqPhiccHDx7gFuZyDjU1NQsXLjx58iQpLCYmpqSklJaWRqfT8dZ3EjExsfT0dIIgvL29EULu7u7l5eVv3rzBc/2KiophYWG8/Gk4PWxRUZGysrKVlVVZWdm7d++WLFmyePHiHu3ARbL/iGg8D5fIXPZg3n/++cfPz09NTa2ysjIoKEhFRWXs2LGJiYlYvqioyMrKSkFBwd/f/9y5c2SpDU5BwZxg1/Pp0yfmMGTMjRs3ZsyYIScnZ2Zmlp2djRv//fffwMDAsWPHlpSUnDx5UkdHR0VF5fTp0wRBnDp1SkdHR05ObufOncy36zHuu8c7crEVJ8Dv940+2C0pKcnY2FhSUlJXV3f37t3kBp9Pnz6tXLlSSkpq6tSpDx8+/PHHH+fOnRsXF9fS0lJbW2tubq6qqvrrr78Sn/NaR0REKCsrjx492sPDg0zfzbsSFi5dusT+PcFfHhKcM5wgCEtLS11dXZxRnGTGjBlkS15enqKiIie/z1LBQl9f/+bNm+ShsbExOZrG/5u4KhEGR0ZGR0fr6+tLS0vPmjUrNTUVq+3u7t69e7eqqqqcnJyHh0doaKiJiUlERAQOLe0VTg9LEERhYeGSJUvk5OTU1dV9fX3JSFB2O3CS7D+i6Pc5ReYSHIJ5LS0tcbSDj49Pbm5uQ0ODlZWVoqIi3k9hZmZ27dq1tra2R48eqaio4O8Wp6BgLrDrYQlDJgji9u3bFAoF/+ORKaOpVKqRkRF+3QsICMjOzq6vr7ezs6NSqYGBgffu3WttbcURfg8fPsR6OMV9s9+Ri624AH6/bwyK3QainsFgFTAY7rDYYeAQRb/PKTKXSzAv/vV+9+4dPnXixAmEEI1Gw9EUf/31F24PDw+vqqrioocTPeoh2MKQnZ2d1dXVyavMzMyWL1+OP2PP/vr1a3x4+/ZthNCdO3fwIc71HxkZSfQW981yR0624m5h8Pt9Y1Ds5unpKSUlJXC1ubm5o0ePzsrK4kU4NDSUzI/b3t5uYWHBHHovOjDbYUARufh9LpG5nIJ5EUI4JzO5Ui8jI4MQ6urqkpaWHjt2rI2NTWBgYEVFxbZt2zQ0NLjo4USPehBbJJmMjExjYyMZUaOhoUGWB8A9JAOucSAEGZSN2/FiF/e4b+Y7crGVCCLMlMJCY+DqGUABA35htsOIYaj4fRz31mNkLhnMy/x7VVBQgHoKByZJTEzEqz3jx48PCgpiMBhc9HCBXQ/7fQMDA0ePHr1z587m5uY///zz8ePHX375JT7Fe8J37nHfzHq42GoQOXPmTENDg5CVXL9+3cnJCa/1IYTev39/9uzZhQsXbt26ldMl33777enTp9lTvQ4dBrqeARQw4AtmO4wYhspfkUtkLhnMy5dCS0vL4uLin376SUVFJSQk5OeffxaUHnaZSZMm7dy5s6CgQENDY9WqVZ6enjjAhi94j/vuNYpZ+LS2trIEYAhBSXZ29oYNG+7evUtWuQkMDIyMjHz48CEZKciOrq5uampqSkrKkB26KioqMg9NPD09BX6LadOmXbt2jXf54OBglqRvwLBmqPh9LpG5nIJ50eddJGRZV3xtd3d3e3v7jz/+KCUl5evr+/r168mTJ2dlZXHRw4ke9SC2MOSnT5/evXs3LS2ttbW1rKzsxIkTeMaJlGTpIXuHUW9x38x35D2KWWh4e3v3ee9+35R0d3evXbt2+/btzBsy4+Pjnz9/3uuWVHl5+fPnzwcHB798+bLv3QWA4YsQ1hB4XNflEpnbYzBve3v70qVLEUKXL19mMBidnZ24dGJUVNSnT58kJCQiIyMbGhrKy8snTZoUERFBEASnoGBOtLW19aiHOQyZ+JyijxldXd379+93dHTgqeeYmBg6nd7V1YUTEPr5+XV1dTEYDBxt/dVXX+E4Py5x3yx37FsUM+JtfXKI5BDmnuZXsCmFucOj3QCgn4hiPA/3yFz2YF7m/N3Hjh3D2WjJwzNnzhw8eFBNTU1LS+vQoUPYe/aohwttbW3seljCkAmCyM7OZt+5PnbsWLIiI0Jo37597u7u5KGrqyuZcBwhRMb/9Bj3zX7HvkUx8+K/hk4OYe5pfgWbUpg74PcB4SCKfn/4cvXq1ZiYGPKwtbX1xYsXM2fOpNPpg9grdnr1X0M2hzALQk4pDH4fEA4iF8c5fHn9+vXmzZvXrVtHtsjIyEydOnXVqlXDLvhhyOYQZmEopBQGgOHLMHNMQ5CioqK6ujpvb+/nz583NTW1trbm5+fv3bsXVzodXgzZHMIsDIWUwgAwfBF1v//PP/9wKbjh7OzcqwYHB4e7d+++fft22bJlqqqqxsbGv/7663/+8x88zT28GNAcwnijnEAYmimFAWC4METz7wuNSZMmEf3eD2lnZ2dnZyeQ/gwuZCzpsWPHsEPsMYcwPkWm/5WTk+OUQxgnDuoxhzAvSjgxKCmFAWDEIOrjfYAZSUnJ48ePNzQ0uLu7V1ZWVlVVbd68eenSpfi9B1cOiouLa21tjYuLw1sZzMzM4uLilJSUEEI5OTmxsbEVFRUIIYIgfH196+rqSktLN2zYMGvWLA8PD76UFBQUKCsr48Ve9n7Onz+f5b0E37SysrKtra2yshIP5zErVqxQV1fPyMhgFi4sLKRSqZaWlgI0IAAMC8DvA/+Di4tLUlJSWVnZhAkT5s6dO3369OTkZDwSd3d3X7lyZUBAwJw5c/T19RctWjR37txjx465ubk5Ozubm5uvXr1aVlYWTxbhsH0DAwMTE5MJEybcu3cPj/R5V4IDDzj108PDo6ys7O3bt8yNfn5+WlpanZ2dt2/flpaWzsvLw+319fVSUlIsPyFpaWlffvkle00lABj5CCFmaMTHcQ4XkLDiEQcihzALwkwpLDS7ASIOxHECwxg6nU7mohggqFRqQkJCVFRUdnY2L/KnT5/29fXFnzs6OrZs2eLn5zdr1qyB7CMADFHA7wMCZuByCLMAKYUBoG+A3wcEyUDnEGYBUgoDQB8Q9ThOQLDgHMLCvGMfUgoPXGcAYFgAQx4AAADRAvw+AACAaAF+HwAAQLQAvw8AACBaCGldl0aj8VvYFhgIcF4EgF/AboAQEN7XTAh7w3jJagkAAAAgofhkCiHcqDsAAABgcIH5fQAAANEC/D4AAIBoAX4fAABAtAC/DwAAIFr8P/otkwwP0E1PAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hls4ml.utils.plot_model(hls_model, show_shapes=True, show_precision=True, to_file=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ec730381",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing HLS project\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "hls_model.compile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2eacc7cc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "993ede28",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "****** Vivado(TM) HLS - High-Level Synthesis from C, C++ and SystemC v2019.1 (64-bit)\n",
      "  **** SW Build 2552052 on Fri May 24 14:47:09 MDT 2019\n",
      "  **** IP Build 2548770 on Fri May 24 18:01:18 MDT 2019\n",
      "    ** Copyright 1986-2019 Xilinx, Inc. All Rights Reserved.\n",
      "\n",
      "source /home/xilinx/Vivado/2019.1/scripts/vivado_hls/hls.tcl -notrace\n",
      "INFO: Applying HLS Y2K22 patch v1.2 for IP revision\n",
      "INFO: [HLS 200-10] Running '/home/xilinx/Vivado/2019.1/bin/unwrapped/lnx64.o/vivado_hls'\n",
      "INFO: [HLS 200-10] For user 'russelld' on host 'scully.physics.ucsd.edu' (Linux_x86_64 version 4.18.0-348.12.2.el8_5.x86_64) on Mon Feb 20 19:07:39 PST 2023\n",
      "INFO: [HLS 200-10] In directory '/home/users/russelld/L1JetTagDaniel/model_1/hls4ml_prj'\n",
      "Sourcing Tcl script 'build_prj.tcl'\n",
      "INFO: [HLS 200-10] Opening project '/home/users/russelld/L1JetTagDaniel/model_1/hls4ml_prj/myproject_prj'.\n",
      "INFO: [HLS 200-10] Adding design file 'firmware/myproject.cpp' to the project\n",
      "INFO: [HLS 200-10] Adding test bench file 'myproject_test.cpp' to the project\n",
      "INFO: [HLS 200-10] Adding test bench file 'firmware/weights' to the project\n",
      "INFO: [HLS 200-10] Adding test bench file 'tb_data' to the project\n",
      "INFO: [HLS 200-10] Opening solution '/home/users/russelld/L1JetTagDaniel/model_1/hls4ml_prj/myproject_prj/solution1'.\n",
      "INFO: [SYN 201-201] Setting up clock 'default' with a period of 5ns.\n",
      "INFO: [HLS 200-10] Setting target device to 'xcu250-figd2104-2L-e'\n",
      "INFO: [XFORM 203-101] Allowed max sub elements number after partition is 4096.\n",
      "INFO: [XFORM 203-1161] The maximum of name length is set into 60.\n",
      "INFO: [XFORM 203-101] Allowed max sub elements number after partition is 8192.\n",
      "INFO: [XFORM 203-1161] The maximum of name length is set into 60.\n",
      "***** C/RTL SYNTHESIS *****\n",
      "INFO: [SCHED 204-61] Option 'relax_ii_for_timing' is enabled, will increase II to preserve clock frequency constraints.\n",
      "INFO: [HLS 200-10] Analyzing design file 'firmware/myproject.cpp' ... \n",
      "WARNING: [HLS 214-113] Either use an argument of the function or declare the variable inside the dataflow loop body: firmware/myproject.cpp:63:68\n",
      "WARNING: [HLS 200-471] Dataflow form checks found 1 issue(s) in file firmware/myproject.cpp\n",
      "INFO: [HLS 200-111] Finished Linking Time (s): cpu = 00:00:14 ; elapsed = 00:00:16 . Memory (MB): peak = 1054.578 ; gain = 134.191 ; free physical = 5047 ; free virtual = 43706\n",
      "INFO: [HLS 200-111] Finished Checking Pragmas Time (s): cpu = 00:00:14 ; elapsed = 00:00:16 . Memory (MB): peak = 1054.578 ; gain = 134.191 ; free physical = 5047 ; free virtual = 43706\n",
      "INFO: [HLS 200-10] Starting code transformations ...\n",
      "INFO: [HLS 200-489] Unrolling loop 'InitAccum' (firmware/nnet_utils/nnet_dense_resource.h:58) in function 'void nnet::dense_resource_rf_leq_nin<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'MultLoop' (firmware/nnet_utils/nnet_dense_resource.h:73) in function 'void nnet::dense_resource_rf_leq_nin<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Result' (firmware/nnet_utils/nnet_dense_resource.h:98) in function 'void nnet::dense_resource_rf_leq_nin<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'InitAccum' (firmware/nnet_utils/nnet_dense_resource.h:58) in function 'void nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'MultLoop' (firmware/nnet_utils/nnet_dense_resource.h:73) in function 'void nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Result' (firmware/nnet_utils/nnet_dense_resource.h:98) in function 'void nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'PixelInitAccumLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:40) in function 'void nnet::conv_1d_resource_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'PixelMultLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:64) in function 'void nnet::conv_1d_resource_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'PixelResultLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:89) in function 'void nnet::conv_1d_resource_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'PixelLoop' (firmware/nnet_utils/nnet_conv1d_latency.h:42) in function 'void nnet::conv_1d_latency_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>(FORWARD_REFERENCE*, FORWARD_REFERENCE*, FORWARD_REFERENCE::weight_t*, FORWARD_REFERENCE::bias_t*)' completely with a factor of 1.\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::limit' into 'nnet::conv_1d_latency_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:33).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::conv_1d_latency_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:51).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::conv_1d_latency_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' into 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d.h:64).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::conv_1d_resource_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' (firmware/nnet_utils/nnet_conv1d_resource.h:68).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' (firmware/nnet_utils/nnet_dense_resource.h:77).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' (firmware/nnet_utils/nnet_dense_resource.h:77).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<8, 1, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' (firmware/nnet_utils/nnet_dense_resource.h:77).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::conv_1d_resource_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' into 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' (firmware/nnet_utils/nnet_conv1d.h:66).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' (firmware/nnet_utils/nnet_dense_resource.h:276).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' into 'myproject' (firmware/myproject.cpp:79).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' (firmware/nnet_utils/nnet_dense_resource.h:276).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' into 'myproject' (firmware/myproject.cpp:87).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense_resource_rf_leq_nin<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' (firmware/nnet_utils/nnet_dense_resource.h:276).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' into 'myproject' (firmware/myproject.cpp:95).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_resource_rf_leq_nin<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' (firmware/nnet_utils/nnet_dense_resource.h:77).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense_resource_rf_leq_nin<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' into 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' (firmware/nnet_utils/nnet_dense_resource.h:276).\n",
      "INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' into 'myproject' (firmware/myproject.cpp:99).\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [HLS 200-111] Finished Standard Transforms Time (s): cpu = 00:00:18 ; elapsed = 00:00:20 . Memory (MB): peak = 1124.199 ; gain = 203.812 ; free physical = 4915 ; free virtual = 43574\n",
      "INFO: [HLS 200-10] Checking synthesizability ...\n",
      "INFO: [XFORM 203-602] Inlining function 'fp_struct<double>::mantissa' into 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:15) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'fp_struct<double>::expv' into 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:18) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'fp_struct<double>::__signbit' into 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:59) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' into 'generic_cast_IEEE754<int, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:117) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'generic_cast_IEEE754<int, double>' into '__hls_fptosi_double_i32' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/src/lib_floatconversion.cpp:55) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function '__hls_fptosi_double_i32' into 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:32->firmware/nnet_utils/nnet_conv1d.h:64) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' into 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:69->firmware/nnet_utils/nnet_conv1d.h:64) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5_mult>' into 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' (firmware/nnet_utils/nnet_conv1d_resource.h:95->firmware/nnet_utils/nnet_conv1d.h:66) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' into 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [HLS 200-111] Finished Checking Synthesizability Time (s): cpu = 00:00:20 ; elapsed = 00:00:22 . Memory (MB): peak = 1124.199 ; gain = 203.812 ; free physical = 4913 ; free virtual = 43571\n",
      "WARNING: [XFORM 203-505] Ignore pipeline pragma in Loop whose tripcount is only 1 (firmware/nnet_utils/nnet_dense_resource.h:65) in function 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>'.\n",
      "WARNING: [XFORM 203-505] Ignore pipeline pragma in Loop whose tripcount is only 1 (firmware/nnet_utils/nnet_dense_resource.h:65) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>'.\n",
      "INFO: [XFORM 203-502] Unrolling small iteration loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' automatically.\n",
      "INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config14>' (firmware/nnet_utils/nnet_activation.h:66:39).\n",
      "INFO: [XFORM 203-502] Unrolling all sub-loops inside loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' for pipelining.\n",
      "INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config11>' (firmware/nnet_utils/nnet_activation.h:66:39).\n",
      "INFO: [XFORM 203-502] Unrolling small iteration loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' automatically.\n",
      "INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config7>' (firmware/nnet_utils/nnet_activation.h:66:39).\n",
      "INFO: [XFORM 203-502] Unrolling small iteration loop 'PartitionLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:34) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' automatically.\n",
      "INFO: [XFORM 203-502] Unrolling all sub-loops inside loop 'ReuseLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:51) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' for pipelining.\n",
      "INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config4>' (firmware/nnet_utils/nnet_activation.h:66:39).\n",
      "INFO: [XFORM 203-502] Unrolling all sub-loops inside loop 'PartitionLoop' (firmware/nnet_utils/nnet_conv1d_latency.h:36) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' for pipelining.\n",
      "INFO: [HLS 200-489] Unrolling loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Loop-1' (firmware/nnet_utils/nnet_activation.h:69) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config14>' completely with a factor of 10.\n",
      "INFO: [HLS 200-489] Unrolling loop 'InitAccum' (firmware/nnet_utils/nnet_dense_resource.h:58) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' completely with a factor of 10.\n",
      "INFO: [HLS 200-489] Unrolling loop 'MultLoop' (firmware/nnet_utils/nnet_dense_resource.h:73) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' completely with a factor of 50.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [HLS 200-489] Unrolling loop 'Result' (firmware/nnet_utils/nnet_dense_resource.h:98) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' completely with a factor of 10.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Loop-1' (firmware/nnet_utils/nnet_activation.h:69) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config11>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'InitAccum' (firmware/nnet_utils/nnet_dense_resource.h:58) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'MultLoop' (firmware/nnet_utils/nnet_dense_resource.h:73) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' completely with a factor of 2500.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Result' (firmware/nnet_utils/nnet_dense_resource.h:98) in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Loop-1' (firmware/nnet_utils/nnet_activation.h:69) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config7>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'PartitionLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:34) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' completely with a factor of 1.\n",
      "INFO: [HLS 200-489] Unrolling loop 'InitAccumLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:44) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'MultLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:60) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' completely with a factor of 1000.\n",
      "INFO: [HLS 200-489] Unrolling loop 'ResultLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:93) in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Loop-1' (firmware/nnet_utils/nnet_activation.h:69) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config4>' completely with a factor of 200.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Product1' (firmware/nnet_utils/nnet_conv1d_latency.h:48) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 56.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Product2' (firmware/nnet_utils/nnet_conv1d_latency.h:50) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'ResetAccum' (firmware/nnet_utils/nnet_conv1d_latency.h:56) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Accum1' (firmware/nnet_utils/nnet_conv1d_latency.h:61) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 56.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Accum2' (firmware/nnet_utils/nnet_conv1d_latency.h:62) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 50.\n",
      "INFO: [HLS 200-489] Unrolling loop 'Result' (firmware/nnet_utils/nnet_conv1d_latency.h:68) in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 50.\n",
      "WARNING: [XFORM 203-135] Cannot reshape array 'w15.V' : incorrect reshape factor 1.\n",
      "WARNING: [XFORM 203-135] Cannot reshape array 'w15.V' : incorrect reshape factor 1.\n",
      "INFO: [XFORM 203-131] Reshaping array 'input_1.V' (firmware/myproject.cpp:25) in dimension 1 completely.\n",
      "INFO: [XFORM 203-131] Reshaping array 'w17.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-131] Reshaping array 'w12.V'  in dimension 1 with a block factor of 50.\n",
      "INFO: [XFORM 203-131] Reshaping array 'w9.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-131] Reshaping array 'w5.V'  in dimension 1 with a block factor of 1000.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer18_out.V' (firmware/myproject.cpp:26) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer2_out.V' (firmware/myproject.cpp:61) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer4_out.V' (firmware/myproject.cpp:65) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer5_out.V' (firmware/myproject.cpp:69) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer7_out.V' (firmware/myproject.cpp:73) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer9_out.V' (firmware/myproject.cpp:77) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer11_out.V' (firmware/myproject.cpp:81) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer12_out.V' (firmware/myproject.cpp:85) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer14_out.V' (firmware/myproject.cpp:89) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer15_out.V' (firmware/myproject.cpp:93) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'layer17_out.V' (firmware/myproject.cpp:97) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'data_buf.i'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'mult.V' (firmware/nnet_utils/nnet_conv1d_latency.h:23) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_conv1d_latency.h:26) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'w2.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b2.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b17.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_dense_resource.h:54) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b15.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_dense_resource.h:54) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b12.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_dense_resource.h:54) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b9.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_dense_resource.h:54) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'data_buf.i'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'b5.V'  in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_conv1d_resource.h:30) in dimension 1 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'data_buf.i'  in dimension 2 completely.\n",
      "WARNING: [XFORM 203-104] Completely partitioning array 'data_buf.i'  accessed through non-constant indices on dimension 1 (firmware/nnet_utils/nnet_conv1d_resource.h:68:29), which may result in long runtime and suboptimal QoR due to large multiplexers. Please consider wrapping the array access into a function or using a register file core instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [XFORM 203-101] Partitioning array 'data_buf.i'  in dimension 2 completely.\n",
      "INFO: [XFORM 203-101] Partitioning array 'acc.V' (firmware/nnet_utils/nnet_conv1d_resource.h:30) in dimension 2 completely.\n",
      "WARNING: [XFORM 203-104] Completely partitioning array 'layer2_out.V' (firmware/myproject.cpp:61) accessed through non-constant indices on dimension 1, which may result in long runtime and suboptimal QoR due to large multiplexers. Please consider wrapping the array access into a function or using a register file core instead.\n",
      "WARNING: [XFORM 203-104] Completely partitioning array 'layer11_out.V' (firmware/myproject.cpp:81) accessed through non-constant indices on dimension 1 (firmware/nnet_utils/nnet_dense_resource.h:77:15), which may result in long runtime and suboptimal QoR due to large multiplexers. Please consider wrapping the array access into a function or using a register file core instead.\n",
      "INFO: [XFORM 203-602] Inlining function 'fp_struct<double>::mantissa' into 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:15) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'generic_cast_IEEE754<int, (ap_q_mode)6, double>' into 'generic_cast_IEEE754<int, double>' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/include/FloatingPoint/hls_case_IEEE754.h:117) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'generic_cast_IEEE754<int, double>' into '__hls_fptosi_double_i32' (/wrk/2019.1/continuous/2019_05_24_2552052/src/products/hls/hls_lib/hlsmath/src/lib_floatconversion.cpp:55) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function '__hls_fptosi_double_i32' into 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:32->firmware/nnet_utils/nnet_conv1d.h:64) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' into 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:69->firmware/nnet_utils/nnet_conv1d.h:64) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5_mult>' into 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' (firmware/nnet_utils/nnet_conv1d_resource.h:95->firmware/nnet_utils/nnet_conv1d.h:66) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' into 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' into 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' (firmware/nnet_utils/nnet_dense_resource.h:100->firmware/nnet_utils/nnet_dense_resource.h:276) automatically.\n",
      "INFO: [XFORM 203-712] Applying dataflow to function 'myproject', detected/extracted 11 process function(s): \n",
      "\t 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>'\n",
      "\t 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config4>'\n",
      "\t 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>'\n",
      "\t 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config7>'\n",
      "\t 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>'\n",
      "\t 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config11>'\n",
      "\t 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>'\n",
      "\t 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config14>'\n",
      "\t 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>'\n",
      "\t 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>'\n",
      "\t 'nnet::sigmoid<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, sigmoid_config18>'.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock from (firmware/nnet_utils/nnet_activation.h:125:21) to (firmware/nnet_utils/nnet_activation.h:152:1) in function 'nnet::sigmoid<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, sigmoid_config18>'... converting 3 basic blocks.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock from (firmware/nnet_utils/nnet_activation.h:64:18) to (firmware/nnet_utils/nnet_activation.h:74:1) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config7>'... converting 55 basic blocks.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock from (firmware/nnet_utils/nnet_activation.h:64:18) to (firmware/nnet_utils/nnet_activation.h:74:1) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config4>'... converting 401 basic blocks.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock from (firmware/nnet_utils/nnet_activation.h:64:18) to (firmware/nnet_utils/nnet_activation.h:74:1) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config14>'... converting 21 basic blocks.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock from (firmware/nnet_utils/nnet_activation.h:64:18) to (firmware/nnet_utils/nnet_activation.h:74:1) in function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config11>'... converting 75 basic blocks.\n",
      "INFO: [XFORM 203-401] Performing if-conversion on hyperblock to (firmware/nnet_utils/nnet_code_gen.h:58:5) in function 'nnet::fill_buffer_2<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>::fill_buffer'... converting 9 basic blocks.\n",
      "INFO: [XFORM 203-11] Balancing expressions in function 'nnet::fill_buffer_2<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>::fill_buffer' (firmware/nnet_utils/nnet_code_gen.h:38)...3 expression(s) balanced.\n",
      "INFO: [XFORM 203-11] Balancing expressions in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' (firmware/nnet_utils/nnet_dense_resource.h:65:15)...89 expression(s) balanced.\n",
      "INFO: [XFORM 203-11] Balancing expressions in function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' (firmware/nnet_utils/nnet_dense_resource.h:64:37)...48 expression(s) balanced.\n",
      "INFO: [XFORM 203-11] Balancing expressions in function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' (firmware/nnet_utils/nnet_conv1d_resource.h:34:29)...1000 expression(s) balanced.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [XFORM 203-11] Balancing expressions in function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:36:59)...5482 expression(s) balanced.\n",
      "INFO: [HLS 200-111] Finished Pre-synthesis Time (s): cpu = 00:06:15 ; elapsed = 00:06:20 . Memory (MB): peak = 8670.602 ; gain = 7750.215 ; free physical = 3931 ; free virtual = 39838\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::sigmoid<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, sigmoid_config18>' to 'sigmoid<ap_fixed,ap_fixed,sigmoid_config18>' (firmware/nnet_utils/nnet_activation.h:140:1)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config7>' to 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config7>' (firmware/nnet_utils/nnet_activation.h:66:1)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config4>' to 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config4>' (firmware/nnet_utils/nnet_activation.h:66:26)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config14>' to 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config14>' (firmware/nnet_utils/nnet_activation.h:66:1)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::relu<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, relu_config11>' to 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config11>' (firmware/nnet_utils/nnet_activation.h:66:1)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::fill_buffer_5<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>::fill_buffer' to 'fill_buffer' (firmware/nnet_utils/nnet_code_gen.h:64)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::fill_buffer_2<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>::fill_buffer' to 'fill_buffer.1' (firmware/nnet_utils/nnet_code_gen.h:42:5)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config9>' to 'dense_resource<ap_ufixed,ap_fixed<16,6,5,3,0>,config9>' (firmware/nnet_utils/nnet_dense_resource.h:65:15)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config15>' to 'dense_resource<ap_ufixed,ap_fixed,config15>' (firmware/nnet_utils/nnet_dense_resource.h:64:37)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::dense_resource<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config12>' to 'dense_resource<ap_ufixed,ap_fixed,config12>' (firmware/nnet_utils/nnet_dense_resource.h:64:37)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::dense_resource<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config17>' to 'dense_resource<ap_fixed,ap_fixed<16,6,5,3,0>,config17>' (firmware/nnet_utils/nnet_dense_resource.h:65:1)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::conv_1d_cl<ap_ufixed<8, 0, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config5>' to 'conv_1d_cl<ap_ufixed,ap_fixed<16,6,5,3,0>,config5>' (firmware/nnet_utils/nnet_conv1d_resource.h:34:29)\n",
      "WARNING: [XFORM 203-631] Renaming function 'nnet::conv_1d_cl<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' to 'conv_1d_cl<ap_fixed,ap_fixed<16,6,5,3,0>,config2>' (firmware/nnet_utils/nnet_conv1d_latency.h:36:55)\n",
      "WARNING: [XFORM 203-532] Ignored the rewind option for Function 'dense_resource<ap_ufixed,ap_fixed<16,6,5,3,0>,config9>' (firmware/nnet_utils/nnet_dense_resource.h:65:15) as the option is not applicable to function pipelining.\n",
      "INFO: [XFORM 203-531] Rewinding loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'dense_resource<ap_ufixed,ap_fixed,config15>'.\n",
      "WARNING: [XFORM 203-532] Ignored the rewind option for Function 'dense_resource<ap_fixed,ap_fixed<16,6,5,3,0>,config17>' (firmware/nnet_utils/nnet_dense_resource.h:65:1) as the option is not applicable to function pipelining.\n",
      "INFO: [XFORM 203-531] Rewinding loop 'ReuseLoop' (firmware/nnet_utils/nnet_conv1d_resource.h:51) in function 'conv_1d_cl<ap_ufixed,ap_fixed<16,6,5,3,0>,config5>'.\n",
      "INFO: [XFORM 203-531] Rewinding loop 'ReuseLoop' (firmware/nnet_utils/nnet_dense_resource.h:64) in function 'dense_resource<ap_ufixed,ap_fixed,config12>'.\n",
      "WARNING: [XFORM 203-561] Ignored multiple trip count directives for loop 'ReuseLoop' in function 'dense_resource<ap_ufixed,ap_fixed,config15>'.\n",
      "WARNING: [XFORM 203-561] Ignored multiple trip count directives for loop 'ReuseLoop' in function 'conv_1d_cl<ap_ufixed,ap_fixed<16,6,5,3,0>,config5>'.\n",
      "WARNING: [XFORM 203-561] Ignored multiple trip count directives for loop 'ReuseLoop' in function 'dense_resource<ap_ufixed,ap_fixed,config12>'.\n",
      "INFO: [HLS 200-111] Finished Architecture Synthesis Time (s): cpu = 00:08:32 ; elapsed = 00:08:38 . Memory (MB): peak = 8670.602 ; gain = 7750.215 ; free physical = 3928 ; free virtual = 39838\n",
      "INFO: [HLS 200-10] Starting hardware synthesis ...\n",
      "INFO: [HLS 200-10] Synthesizing 'myproject' ...\n",
      "WARNING: [SYN 201-103] Legalizing function name 'myproject.entry4' to 'myproject_entry4'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'fill_buffer.1' to 'fill_buffer_1'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'conv_1d_cl<ap_fixed,ap_fixed<16,6,5,3,0>,config2>' to 'conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config4>' to 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'conv_1d_cl<ap_ufixed,ap_fixed<16,6,5,3,0>,config5>' to 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config7>' to 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'dense_resource<ap_ufixed,ap_fixed<16,6,5,3,0>,config9>' to 'dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config11>' to 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'dense_resource<ap_ufixed,ap_fixed,config12>' to 'dense_resource_ap_ufixed_ap_fixed_config12_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config14>' to 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'dense_resource<ap_ufixed,ap_fixed,config15>' to 'dense_resource_ap_ufixed_ap_fixed_config15_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'dense_resource<ap_fixed,ap_fixed<16,6,5,3,0>,config17>' to 'dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s'.\n",
      "WARNING: [SYN 201-103] Legalizing function name 'sigmoid<ap_fixed,ap_fixed,sigmoid_config18>' to 'sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s'.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'myproject_entry4' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 517.9 seconds; current allocated memory: 1.125 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.14 seconds; current allocated memory: 1.125 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'fill_buffer_1' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'fill_buffer.1'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 10, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.15 seconds; current allocated memory: 1.126 GB.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.92 seconds; current allocated memory: 1.128 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining loop 'PartitionLoop'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 10, Final II = 5, Depth = 5.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 25.11 seconds; current allocated memory: 1.171 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Starting global binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 38.97 seconds; current allocated memory: 1.315 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config4>'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 21.23 seconds; current allocated memory: 1.321 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 1.75 seconds; current allocated memory: 1.326 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'fill_buffer' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'fill_buffer'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 1.85 seconds; current allocated memory: 1.328 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.69 seconds; current allocated memory: 1.329 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining loop 'ReuseLoop'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 3.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 12.49 seconds; current allocated memory: 1.361 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 22.52 seconds; current allocated memory: 1.574 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config7>'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 12.22 seconds; current allocated memory: 1.576 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.31 seconds; current allocated memory: 1.577 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.53 seconds; current allocated memory: 1.579 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 1.61 seconds; current allocated memory: 1.581 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config11>'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 1.28 seconds; current allocated memory: 1.582 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.1 seconds; current allocated memory: 1.582 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'dense_resource_ap_ufixed_ap_fixed_config12_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining loop 'ReuseLoop'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 3.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.37 seconds; current allocated memory: 1.583 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.99 seconds; current allocated memory: 1.586 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'relu<ap_fixed,ap_ufixed<8,0,5,3,0>,relu_config14>'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 1.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [HLS 200-111]  Elapsed time: 1.03 seconds; current allocated memory: 1.586 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.15 seconds; current allocated memory: 1.586 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'dense_resource_ap_ufixed_ap_fixed_config15_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining loop 'ReuseLoop'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 2.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.2 seconds; current allocated memory: 1.586 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.16 seconds; current allocated memory: 1.587 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.17 seconds; current allocated memory: 1.587 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.15 seconds; current allocated memory: 1.587 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-61] Pipelining function 'sigmoid<ap_fixed,ap_fixed,sigmoid_config18>'.\n",
      "INFO: [SCHED 204-61] Pipelining result : Target II = 1, Final II = 1, Depth = 2.\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.08 seconds; current allocated memory: 1.587 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.11 seconds; current allocated memory: 1.587 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-42] -- Implementing module 'myproject' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [SCHED 204-11] Starting scheduling ...\n",
      "INFO: [SCHED 204-11] Finished scheduling.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.19 seconds; current allocated memory: 1.588 GB.\n",
      "INFO: [BIND 205-100] Starting micro-architecture generation ...\n",
      "INFO: [BIND 205-101] Performing variable lifetime analysis.\n",
      "INFO: [BIND 205-101] Exploring resource sharing.\n",
      "INFO: [BIND 205-101] Binding ...\n",
      "INFO: [BIND 205-100] Finished micro-architecture generation.\n",
      "INFO: [HLS 200-111]  Elapsed time: 14.55 seconds; current allocated memory: 1.603 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'myproject_entry4' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'myproject_entry4'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 6.08 seconds; current allocated memory: 1.609 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'fill_buffer_1' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'fill_buffer_1'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 0.26 seconds; current allocated memory: 1.619 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-104] Estimated max fanout for 'conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s' is 12882 from HDL expression: (1'b1 == ap_CS_fsm_state4)\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mux_2568_16_1_1': 200 instance(s).\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mux_2568_1_1_1': 200 instance(s).\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 8.16 seconds; current allocated memory: 2.144 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 38.89 seconds; current allocated memory: 2.539 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'fill_buffer' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'fill_buffer'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 4.56 seconds; current allocated memory: 2.641 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-104] Estimated max fanout for 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s' is 8640 from HDL expression: ((1'b0 == ap_block_pp0_stage0) & (1'b1 == ap_CS_fsm_pp0_stage0) & (ap_enable_reg_pp0_iter1 == 1'b1))\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mux_2568_8_1_1': 999 instance(s).\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 18.26 seconds; current allocated memory: 3.574 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 23.06 seconds; current allocated memory: 3.963 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 2.81 seconds; current allocated memory: 3.969 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 4 seconds; current allocated memory: 3.979 GB.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'dense_resource_ap_ufixed_ap_fixed_config12_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mux_164_8_1_1': 50 instance(s).\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'dense_resource_ap_ufixed_ap_fixed_config12_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 2.7 seconds; current allocated memory: 3.985 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 3.59 seconds; current allocated memory: 3.994 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'dense_resource_ap_ufixed_ap_fixed_config15_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mux_104_8_1_1': 1 instance(s).\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'dense_resource_ap_ufixed_ap_fixed_config15_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 2.71 seconds; current allocated memory: 3.996 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Generating core module 'myproject_mul_mul_15s_12s_26_1_1': 1 instance(s).\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 2.7 seconds; current allocated memory: 3.997 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 2.61 seconds; current allocated memory: 3.998 GB.\n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [HLS 200-10] -- Generating RTL for module 'myproject' \n",
      "INFO: [HLS 200-10] ----------------------------------------------------------------\n",
      "INFO: [RTGEN 206-500] Setting interface mode on port 'myproject/input_1_V' to 'ap_vld'.\n",
      "INFO: [RTGEN 206-500] Setting interface mode on port 'myproject/layer18_out_0_V' to 'ap_vld'.\n",
      "INFO: [RTGEN 206-500] Setting interface mode on function 'myproject' to 'ap_ctrl_hs'.\n",
      "INFO: [SYN 201-210] Renamed object name 'start_for_conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_U0' to 'start_for_conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2bkb' due to the length limit 60\n",
      "INFO: [RTGEN 206-100] Finished creating RTL model for 'myproject'.\n",
      "INFO: [HLS 200-111]  Elapsed time: 5.79 seconds; current allocated memory: 24.449 MB.\n",
      "INFO: [RTMG 210-279] Implementing memory 'conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s_w5_V_rom' using auto ROMs.\n",
      "INFO: [RTMG 210-279] Implementing memory 'dense_resource_ap_ufixed_ap_fixed_config12_s_w12_V_rom' using auto ROMs.\n",
      "INFO: [RTMG 210-279] Implementing memory 'dense_resource_ap_ufixed_ap_fixed_config15_s_w15_V_rom' using distributed ROMs.\n",
      "INFO: [RTMG 210-279] Implementing memory 'sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s_sigmoid_table1_rom' using auto ROMs.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'input_1_V_c_U(fifo_w2240_d2_A)' using Block RAMs.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_0_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_1_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_2_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_3_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_4_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_5_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_6_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_7_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_8_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_9_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_10_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_11_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_12_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_13_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_14_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_15_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_16_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_17_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_18_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_19_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_20_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_21_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_22_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_23_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_24_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_25_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_26_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_27_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_28_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_29_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_30_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_31_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_32_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_33_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_34_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_35_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_36_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_37_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_38_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_39_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_40_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_41_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_42_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_43_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_44_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_45_V_U(fifo_w16_d2_A)' using Shift Registers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_46_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_47_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_48_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_49_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_50_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_51_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_52_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_53_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_54_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_55_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_56_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_57_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_58_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_59_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_60_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_61_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_62_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_63_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_64_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_65_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_66_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_67_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_68_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_69_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_70_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_71_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_72_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_73_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_74_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_75_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_76_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_77_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_78_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_79_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_80_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_81_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_82_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_83_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_84_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_85_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_86_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_87_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_88_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_89_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_90_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_91_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_92_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_93_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_94_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_95_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_96_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_97_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_98_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_99_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_100_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_101_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_102_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_103_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_104_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_105_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_106_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_107_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_108_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_109_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_110_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_111_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_112_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_113_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_114_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_115_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_116_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_117_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_118_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_119_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_120_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_121_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_122_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_123_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_124_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_125_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_126_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_127_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_128_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_129_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_130_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_131_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_132_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_133_V_U(fifo_w16_d2_A)' using Shift Registers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_134_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_135_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_136_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_137_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_138_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_139_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_140_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_141_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_142_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_143_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_144_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_145_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_146_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_147_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_148_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_149_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_150_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_151_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_152_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_153_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_154_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_155_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_156_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_157_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_158_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_159_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_160_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_161_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_162_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_163_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_164_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_165_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_166_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_167_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_168_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_169_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_170_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_171_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_172_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_173_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_174_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_175_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_176_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_177_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_178_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_179_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_180_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_181_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_182_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_183_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_184_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_185_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_186_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_187_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_188_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_189_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_190_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_191_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_192_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_193_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_194_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_195_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_196_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_197_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_198_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer2_out_199_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_0_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_1_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_2_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_3_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_4_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_5_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_6_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_7_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_8_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_9_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_10_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_11_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_12_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_13_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_14_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_15_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_16_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_17_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_18_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_19_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_20_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_21_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_22_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_23_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_24_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_25_V_U(fifo_w8_d2_A)' using Shift Registers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_26_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_27_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_28_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_29_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_30_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_31_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_32_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_33_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_34_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_35_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_36_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_37_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_38_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_39_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_40_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_41_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_42_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_43_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_44_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_45_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_46_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_47_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_48_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_49_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_50_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_51_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_52_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_53_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_54_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_55_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_56_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_57_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_58_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_59_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_60_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_61_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_62_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_63_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_64_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_65_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_66_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_67_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_68_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_69_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_70_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_71_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_72_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_73_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_74_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_75_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_76_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_77_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_78_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_79_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_80_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_81_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_82_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_83_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_84_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_85_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_86_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_87_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_88_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_89_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_90_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_91_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_92_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_93_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_94_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_95_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_96_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_97_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_98_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_99_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_100_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_101_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_102_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_103_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_104_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_105_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_106_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_107_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_108_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_109_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_110_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_111_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_112_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_113_V_U(fifo_w8_d2_A)' using Shift Registers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_114_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_115_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_116_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_117_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_118_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_119_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_120_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_121_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_122_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_123_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_124_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_125_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_126_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_127_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_128_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_129_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_130_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_131_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_132_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_133_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_134_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_135_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_136_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_137_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_138_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_139_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_140_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_141_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_142_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_143_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_144_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_145_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_146_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_147_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_148_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_149_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_150_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_151_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_152_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_153_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_154_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_155_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_156_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_157_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_158_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_159_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_160_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_161_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_162_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_163_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_164_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_165_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_166_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_167_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_168_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_169_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_170_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_171_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_172_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_173_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_174_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_175_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_176_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_177_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_178_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_179_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_180_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_181_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_182_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_183_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_184_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_185_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_186_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_187_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_188_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_189_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_190_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_191_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_192_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_193_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_194_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_195_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_196_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_197_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_198_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer4_out_199_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_1_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_3_V_U(fifo_w16_d2_A)' using Shift Registers.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_4_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_9_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_10_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_12_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_13_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_18_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_20_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_21_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_22_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_24_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_25_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_29_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_30_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_31_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_34_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_36_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_37_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_38_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_39_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_40_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_41_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_42_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_46_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_47_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer5_out_49_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_1_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_3_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_4_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_9_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_10_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_12_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_13_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_18_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_20_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_21_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_22_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_24_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_25_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_29_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_30_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_31_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_34_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_36_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_37_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_38_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_39_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_40_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_41_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_42_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_46_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_47_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer7_out_49_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer9_out_0_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer9_out_2_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer9_out_19_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer9_out_25_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer11_out_0_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer11_out_2_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer11_out_19_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer11_out_25_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_0_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_1_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_2_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_3_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_4_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_5_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_6_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_7_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_8_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer12_out_9_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_0_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_1_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_2_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_3_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_4_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_5_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_6_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_7_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_8_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer14_out_9_V_U(fifo_w8_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer15_out_0_V_U(fifo_w15_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'layer17_out_0_V_U(fifo_w16_d2_A)' using Shift Registers.\n",
      "INFO: [RTMG 210-285] Implementing FIFO 'start_for_conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2bkb_U(start_for_conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2bkb)' using Shift Registers.\n",
      "INFO: [HLS 200-111] Finished generating all RTL models Time (s): cpu = 00:13:14 ; elapsed = 00:14:15 . Memory (MB): peak = 8670.602 ; gain = 7750.215 ; free physical = 2116 ; free virtual = 39033\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: [VHDL 208-304] Generating VHDL RTL for myproject.\n",
      "INFO: [VLOG 209-307] Generating Verilog RTL for myproject.\n",
      "***** C/RTL SYNTHESIS COMPLETED IN 0h14m15s *****\n",
      "INFO: [HLS 200-112] Total elapsed time: 857.78 seconds; peak allocated memory: 3.998 GB.\n",
      "INFO: [Common 17-206] Exiting vivado_hls at Mon Feb 20 19:21:57 2023...\n",
      "Vivado synthesis report not found.\n",
      "Cosim report not found.\n",
      "Timing report not found.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'CSynthesisReport': {'EstimatedClockPeriod': '4.357',\n",
       "  'BestLatency': '64',\n",
       "  'WorstLatency': '67',\n",
       "  'IntervalMin': '23',\n",
       "  'IntervalMax': '23',\n",
       "  'BRAM_18K': '360',\n",
       "  'DSP48E': '272',\n",
       "  'FF': '42249',\n",
       "  'LUT': '236107',\n",
       "  'URAM': '0',\n",
       "  'AvailableBRAM_18K': '5376',\n",
       "  'AvailableDSP48E': '12288',\n",
       "  'AvailableFF': '3456000',\n",
       "  'AvailableLUT': '1728000',\n",
       "  'AvailableURAM': '1280'}}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hls_model.build(csim=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7d57cff8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1 solution(s) in model_1/hls4ml_prj//myproject_prj.\n",
      "Reports for solution \"solution1\":\n",
      "\n",
      "C simulation report not found.\n",
      "SYNTHESIS REPORT:\n",
      "================================================================\n",
      "== Vivado HLS Report for 'myproject'\n",
      "================================================================\n",
      "* Date:           Mon Feb 20 19:21:06 2023\n",
      "\n",
      "* Version:        2019.1 (Build 2552052 on Fri May 24 15:28:33 MDT 2019)\n",
      "* Project:        myproject_prj\n",
      "* Solution:       solution1\n",
      "* Product family: virtexuplus\n",
      "* Target device:  xcu250-figd2104-2L-e\n",
      "\n",
      "\n",
      "================================================================\n",
      "== Performance Estimates\n",
      "================================================================\n",
      "+ Timing (ns): \n",
      "    * Summary: \n",
      "    +--------+-------+----------+------------+\n",
      "    |  Clock | Target| Estimated| Uncertainty|\n",
      "    +--------+-------+----------+------------+\n",
      "    |ap_clk  |   5.00|     4.357|        0.62|\n",
      "    +--------+-------+----------+------------+\n",
      "\n",
      "+ Latency (clock cycles): \n",
      "    * Summary: \n",
      "    +-----+-----+-----+-----+----------+\n",
      "    |  Latency  |  Interval | Pipeline |\n",
      "    | min | max | min | max |   Type   |\n",
      "    +-----+-----+-----+-----+----------+\n",
      "    |   64|   67|   23|   23| dataflow |\n",
      "    +-----+-----+-----+-----+----------+\n",
      "\n",
      "    + Detail: \n",
      "        * Instance: \n",
      "        +---------------------------------------------------------+--------------------------------------------------------+-----+-----+-----+-----+---------------------------------------------+\n",
      "        |                                                         |                                                        |  Latency  |  Interval |                   Pipeline                  |\n",
      "        |                         Instance                        |                         Module                         | min | max | min | max |                     Type                    |\n",
      "        +---------------------------------------------------------+--------------------------------------------------------+-----+-----+-----+-----+---------------------------------------------+\n",
      "        |conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_U0       |conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s       |   22|   22|   22|   22|                     none                    |\n",
      "        |conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_U0      |conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s      |   11|   12|   10|   10| loop rewind(delay=0 initiation interval(s)) |\n",
      "        |dense_resource_ap_ufixed_ap_fixed_config12_U0            |dense_resource_ap_ufixed_ap_fixed_config12_s            |   11|   12|   10|   10| loop rewind(delay=0 initiation interval(s)) |\n",
      "        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_U0        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s        |    0|    0|    1|    1|                   function                  |\n",
      "        |dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_U0  |dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s  |    1|    1|    1|    1|                     none                    |\n",
      "        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_U0        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s        |    0|    0|    1|    1|                   function                  |\n",
      "        |dense_resource_ap_ufixed_ap_fixed_config15_U0            |dense_resource_ap_ufixed_ap_fixed_config15_s            |   10|   11|   10|   10| loop rewind(delay=0 initiation interval(s)) |\n",
      "        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_U0       |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s       |    0|    0|    1|    1|                   function                  |\n",
      "        |sigmoid_ap_fixed_ap_fixed_sigmoid_config18_U0            |sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s            |    1|    1|    1|    1|                   function                  |\n",
      "        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_U0       |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s       |    0|    0|    1|    1|                   function                  |\n",
      "        |dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_U0  |dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s  |    0|    0|    0|    0|                     none                    |\n",
      "        |myproject_entry4_U0                                      |myproject_entry4                                        |    0|    0|    0|    0|                     none                    |\n",
      "        +---------------------------------------------------------+--------------------------------------------------------+-----+-----+-----+-----+---------------------------------------------+\n",
      "\n",
      "        * Loop: \n",
      "        N/A\n",
      "\n",
      "\n",
      "\n",
      "================================================================\n",
      "== Utilization Estimates\n",
      "================================================================\n",
      "* Summary: \n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|         Name        | BRAM_18K| DSP48E|    FF   |   LUT   | URAM |\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|DSP                  |        -|      -|        -|        -|     -|\n",
      "|Expression           |        -|      -|        0|     1962|     -|\n",
      "|FIFO                 |      125|      -|     4670|    13807|     -|\n",
      "|Instance             |      235|    272|    37097|   216000|     -|\n",
      "|Memory               |        -|      -|        -|        -|     -|\n",
      "|Multiplexer          |        -|      -|        -|     4338|     -|\n",
      "|Register             |        -|      -|      482|        -|     -|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|Total                |      360|    272|    42249|   236107|     0|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|Available SLR        |     1344|   3072|   864000|   432000|   320|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|Utilization SLR (%)  |       26|      8|        4|       54|     0|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|Available            |     5376|  12288|  3456000|  1728000|  1280|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "|Utilization (%)      |        6|      2|        1|       13|     0|\n",
      "+---------------------+---------+-------+---------+---------+------+\n",
      "\n",
      "+ Detail: \n",
      "    * Instance: \n",
      "    +---------------------------------------------------------+--------------------------------------------------------+---------+-------+-------+--------+-----+\n",
      "    |                         Instance                        |                         Module                         | BRAM_18K| DSP48E|   FF  |   LUT  | URAM|\n",
      "    +---------------------------------------------------------+--------------------------------------------------------+---------+-------+-------+--------+-----+\n",
      "    |conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_U0       |conv_1d_cl_ap_fixed_ap_fixed_16_6_5_3_0_config2_s       |        0|    271|  25834|  107197|    0|\n",
      "    |conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_U0      |conv_1d_cl_ap_ufixed_ap_fixed_16_6_5_3_0_config5_s      |      223|      0|   8380|   91573|    0|\n",
      "    |dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_U0  |dense_resource_ap_fixed_ap_fixed_16_6_5_3_0_config17_s  |        0|      1|     18|      36|    0|\n",
      "    |dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_U0  |dense_resource_ap_ufixed_ap_fixed_16_6_5_3_0_config9_s  |        0|      0|    140|    3591|    0|\n",
      "    |dense_resource_ap_ufixed_ap_fixed_config12_U0            |dense_resource_ap_ufixed_ap_fixed_config12_s            |       11|      0|    571|    5744|    0|\n",
      "    |dense_resource_ap_ufixed_ap_fixed_config15_U0            |dense_resource_ap_ufixed_ap_fixed_config15_s            |        0|      0|    212|     405|    0|\n",
      "    |myproject_entry4_U0                                      |myproject_entry4                                        |        0|      0|      3|      38|    0|\n",
      "    |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_U0       |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config11_s       |        0|      0|     34|     131|    0|\n",
      "    |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_U0       |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config14_s       |        0|      0|     82|     311|    0|\n",
      "    |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_U0        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config4_s        |        0|      0|   1602|    6011|    0|\n",
      "    |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_U0        |relu_ap_fixed_ap_ufixed_8_0_5_3_0_relu_config7_s        |        0|      0|    218|     821|    0|\n",
      "    |sigmoid_ap_fixed_ap_fixed_sigmoid_config18_U0            |sigmoid_ap_fixed_ap_fixed_sigmoid_config18_s            |        1|      0|      3|     142|    0|\n",
      "    +---------------------------------------------------------+--------------------------------------------------------+---------+-------+-------+--------+-----+\n",
      "    |Total                                                    |                                                        |      235|    272|  37097|  216000|    0|\n",
      "    +---------------------------------------------------------+--------------------------------------------------------+---------+-------+-------+--------+-----+\n",
      "\n",
      "Co-simulation report not found.\n"
     ]
    }
   ],
   "source": [
    "hls4ml.report.read_vivado_report('model_1/hls4ml_prj/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3a30119",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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