{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib\n", "import matplotlib.pyplot as plt\n", "import IPython.display as ipd\n", "\n", "import sys\n", "sys.path.append('waveglow/')\n", "\n", "from itertools import cycle\n", "import numpy as np\n", "import scipy as sp\n", "from scipy.io.wavfile import write\n", "import pandas as pd\n", "import librosa\n", "import torch\n", "\n", "from hparams import create_hparams\n", "from model import Tacotron2, load_model\n", "from waveglow.denoiser import Denoiser\n", "from layers import TacotronSTFT\n", "from data_utils import TextMelLoader, TextMelCollate\n", "from text import cmudict, text_to_sequence\n", "from mellotron_utils import get_data_from_musicxml" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "def panner(signal, angle):\n", " angle = np.radians(angle)\n", " left = np.sqrt(2)/2.0 * (np.cos(angle) - np.sin(angle)) * signal\n", " right = np.sqrt(2)/2.0 * (np.cos(angle) + np.sin(angle)) * signal\n", " return np.dstack((left, right))[0]" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "def plot_mel_f0_alignment(mel_source, mel_outputs_postnet, f0s, alignments, figsize=(16, 16)):\n", " fig, axes = plt.subplots(4, 1, figsize=figsize)\n", " axes = axes.flatten()\n", " axes[0].imshow(mel_source, aspect='auto', origin='bottom', interpolation='none')\n", " axes[1].imshow(mel_outputs_postnet, aspect='auto', origin='bottom', interpolation='none')\n", " axes[2].scatter(range(len(f0s)), f0s, alpha=0.5, color='red', marker='.', s=1)\n", " axes[2].set_xlim(0, len(f0s))\n", " axes[3].imshow(alignments, aspect='auto', origin='bottom', interpolation='none')\n", " axes[0].set_title(\"Source Mel\")\n", " axes[1].set_title(\"Predicted Mel\")\n", " axes[2].set_title(\"Source pitch contour\")\n", " axes[3].set_title(\"Source rhythm\")\n", " plt.tight_layout()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def load_mel(path):\n", " audio, sampling_rate = librosa.core.load(path, sr=hparams.sampling_rate)\n", " audio = torch.from_numpy(audio)\n", " if sampling_rate != hparams.sampling_rate:\n", " raise ValueError(\"{} SR doesn't match target {} SR\".format(\n", " sampling_rate, stft.sampling_rate))\n", " audio_norm = audio.unsqueeze(0)\n", " audio_norm = torch.autograd.Variable(audio_norm, requires_grad=False)\n", " melspec = stft.mel_spectrogram(audio_norm)\n", " melspec = melspec.to(device)\n", " return melspec" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING:tensorflow:\n", "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n", "For more information, please see:\n", " * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n", " * https://github.com/tensorflow/addons\n", " * https://github.com/tensorflow/io (for I/O related ops)\n", "If you depend on functionality not listed there, please file an issue.\n", "\n" ] } ], "source": [ "hparams = create_hparams()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "stft = TacotronSTFT(hparams.filter_length, hparams.hop_length, hparams.win_length,\n", " hparams.n_mel_channels, hparams.sampling_rate, hparams.mel_fmin,\n", " hparams.mel_fmax)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load Models" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "checkpoint_path = \"models/mellotron_libritts.pt\"\n", "# mellotron = load_model(hparams).cuda().eval()\n", "mellotron = load_model(hparams).to(device).eval()\n", "mellotron.load_state_dict(torch.load(checkpoint_path,map_location=torch.device('cpu'))['state_dict'])" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/tzld/opt/anaconda3/lib/python3.7/site-packages/torch/serialization.py:656: SourceChangeWarning: source code of class 'glow.WaveGlow' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n", " warnings.warn(msg, SourceChangeWarning)\n", "/Users/tzld/opt/anaconda3/lib/python3.7/site-packages/torch/serialization.py:656: SourceChangeWarning: source code of class 'torch.nn.modules.conv.ConvTranspose1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n", " warnings.warn(msg, SourceChangeWarning)\n", "/Users/tzld/opt/anaconda3/lib/python3.7/site-packages/torch/serialization.py:656: SourceChangeWarning: source code of class 'torch.nn.modules.container.ModuleList' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n", " warnings.warn(msg, SourceChangeWarning)\n", "/Users/tzld/opt/anaconda3/lib/python3.7/site-packages/torch/serialization.py:656: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n", " warnings.warn(msg, SourceChangeWarning)\n" ] } ], "source": [ "waveglow_path = 'models/waveglow_256channels_universal_v4.pt'\n", "waveglow = torch.load(waveglow_path,map_location=torch.device('cpu'))['model'].to(device).eval()\n", "denoiser = Denoiser(waveglow).to(device).eval()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup dataloaders" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true }, "outputs": [], "source": [ "arpabet_dict = cmudict.CMUDict('data/cmu_dictionary')\n", "audio_paths = 'data/examples_filelist.txt'\n", "dataloader = TextMelLoader(audio_paths, hparams)\n", "datacollate = TextMelCollate(1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load data" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "data/example1.wav exploring the expanses of space to keep our planet safe\n" ] } ], "source": [ "file_idx = 0\n", "audio_path, text, sid = dataloader.audiopaths_and_text[file_idx]\n", "\n", "# get audio path, encoded text, pitch contour and mel for gst\n", "text_encoded = torch.LongTensor(text_to_sequence(text, hparams.text_cleaners, arpabet_dict))[None, :].to(device) \n", "pitch_contour = dataloader[file_idx][3][None].to(device)\n", "mel = load_mel(audio_path)\n", "print(audio_path, text)\n", "\n", "# load source data to obtain rhythm using tacotron 2 as a forced aligner\n", "x, y = mellotron.parse_batch(datacollate([dataloader[file_idx]]))" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(tensor([[145, 153, 168, 166, 154, 115, 167, 145, 157, 8, 128, 110, 8, 145,\n", " 153, 168, 166, 107, 156, 168, 145, 183, 8, 111, 180, 8, 168, 166,\n", " 139, 168, 8, 170, 178, 8, 153, 150, 166, 8, 119, 134, 8, 166,\n", " 154, 107, 156, 110, 170, 8, 168, 139, 141]]),\n", " tensor([51]),\n", " tensor([[[ -6.1974, -5.6973, -5.8164, ..., -4.4820, -4.3939, -5.0746],\n", " [ -6.7440, -5.5365, -4.3589, ..., -4.6080, -4.6072, -5.3200],\n", " [ -6.2189, -5.3365, -4.2016, ..., -5.3071, -5.0197, -5.4305],\n", " ...,\n", " [-10.3804, -9.5551, -8.1752, ..., -10.4715, -10.2128, -10.3555],\n", " [-10.4665, -9.2635, -8.3367, ..., -10.4089, -10.4013, -10.3220],\n", " [-10.3404, -8.8286, -7.2513, ..., -10.4941, -10.6084, -10.5577]]]),\n", " 51,\n", " tensor([345]),\n", " tensor([0]),\n", " tensor([[[ 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 191.7391, 190.0862,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 214.0777, 214.0777, 214.0777, 212.0192, 212.0192, 212.0192, 214.0777,\n", " 218.3168, 222.7273, 225.0000, 229.6875, 232.1053, 237.0968, 242.3077,\n", " 247.7528, 253.4483, 259.4118, 262.5000, 265.6627, 272.2222, 275.6250,\n", " 279.1139, 282.6923, 282.6923, 282.6923, 282.6923, 279.1139, 275.6250,\n", " 272.2222, 265.6627, 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0.0000, 156.3830, 155.2817, 154.1958, 153.1250,\n", " 153.1250, 152.0690, 151.0274, 151.0274, 148.9865, 147.9866, 147.0000,\n", " 146.0265, 144.1176, 143.1818, 141.3462, 140.4459, 139.5570, 138.6792,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 152.0690, 148.9865,\n", " 146.0265, 144.1176, 138.6792, 135.2761, 132.8313, 131.2500, 130.4734,\n", " 130.4734, 130.4734, 129.7059, 128.1977, 126.7241, 126.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n", " 0.0000, 0.0000]]]))" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([[[ -6.1974, -5.6973, -5.8164, ..., -4.4820, -4.3939, -5.0746],\n", " [ -6.7440, -5.5365, -4.3589, ..., -4.6080, -4.6072, -5.3200],\n", " [ -6.2189, -5.3365, -4.2016, ..., -5.3071, -5.0197, -5.4305],\n", " ...,\n", " [-10.3804, -9.5551, -8.1752, ..., -10.4715, -10.2128, -10.3555],\n", " [-10.4665, -9.2635, -8.3367, ..., -10.4089, -10.4013, -10.3220],\n", " [-10.3404, -8.8286, -7.2513, ..., -10.4941, -10.6084, -10.5577]]])" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mel" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'data/example1.wav'" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "audio_path" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'data/example1.wav'" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "audio_path" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'exploring the expanses of space to keep our planet safe'" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "text" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "torch.Size([1, 51])" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "text_encoded.shape" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ipd.Audio(audio_path, rate=hparams.sampling_rate)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Define Speakers Set" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "speaker_ids = TextMelLoader(\"filelists/libritts_train_clean_100_audiopath_text_sid_shorterthan10s_atleast5min_train_filelist.txt\", hparams).speaker_ids\n", "speakers = pd.read_csv('filelists/libritts_speakerinfo.txt', engine='python',header=None, comment=';', sep=' *\\| *', \n", " names=['ID', 'SEX', 'SUBSET', 'MINUTES', 'NAME'])\n", "speakers['MELLOTRON_ID'] = speakers['ID'].apply(lambda x: speaker_ids[x] if x in speaker_ids else -1)\n", "female_speakers = cycle(\n", " speakers.query(\"SEX == 'F' and MINUTES > 20 and MELLOTRON_ID >= 0\")['MELLOTRON_ID'].sample(frac=1).tolist())\n", "male_speakers = cycle(\n", " speakers.query(\"SEX == 'M' and MINUTES > 20 and MELLOTRON_ID >= 0\")['MELLOTRON_ID'].sample(frac=1).tolist())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Style Transfer (Rhythm and Pitch Contour)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "with torch.no_grad():\n", " # get rhythm (alignment map) using tacotron 2\n", " mel_outputs, mel_outputs_postnet, gate_outputs, rhythm = mellotron.forward(x)\n", " rhythm = rhythm.permute(1, 0, 2)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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YXSVJC4hF9mxZJxPR/CRnq/PHmu+SRdPZjPGD1Vs4GEnbL+I1X/0OGCBJ3Zd38fzTDAtLbMZlLOddw33Wb+NnZY732YwsgOUmHmvaYhe1J9Az0o33PD/6DDYzqIPrt/HvV4n9V4WJBr7/ZiabQXMkNuMh7rTseM2FfACdWaZ+dDXpkcWdjsdYZ5cj69+8jfeydCwz/T5eXPcQ95l2OBQ+mzeJABLQhfQl60M2TuKrIblAuZRUwGTd/PYJ+zSnuNO8jUNoisskVg2K/6QknCH3c8fz0/7TM4MLaAbus/TktM6bQ5Km2GXwYGJ7SmseL3l+imcym73AedI5Nwe+gAVis2niPhUErZ7iPv092x86M7xjSQXCXCKL2chmzw1fQLuKBX14EU90fMVnufkyjvPbhySF7uLx2mO85tuf4/n334r7zFegzJJEZwP5V4FYXkri3MzPkp2D/DeFbEay/SwHOZcFrjkJc9E20JrbxJaS/cv2393Hi2uPEMtCXCpJDfnZRGebJAUOSc6ygTwn85noT2Ce7nB+/JPKGAyXhMYoZ5Vyo1QA4Z6/foNdum99Mx7q8iJe1ya2i5JUYX7MGSVVqIFQn9pnSRs57cTOwTkvu1jQS1Av/D4NxWBtEmgtsdCWGYQ5O39oLweOczVTcPgE3TjBPMlYZDPbbRxM7Ha8l3oZP3sYr7AP5VPdPv59c8ribMiZV0/wfzQH+HJJWraJcyAgztQQn0sWM6D9ozkkjddwZl08T3+XxJ9UG/kaLlNSSWogIaCvkjRdxUXYOamnj1AbmKAP+QspiT+SmG0Ge7ZObCaN18NZLg98/k0HG7pgO7+s43M+QZ3v+Bnv5fQq3kzNwvz7uJ1ilvGC529Bz2Y285g3TTvSJR6LYsM2cRkUz5CcN4lZymqwBNpAkP8szyfm7fn1nAXu7PSS56F6Vv+Q6V8s/7sv4t9TLUuSyhTL/7w5/1VxO8C7SdAXSZp28T6H5H0WvjeilDXZCo6VuIUWfCDVU+dExjHPTHRmObNum9WZx6vz3+dR3jrAWFmdh+6McgmJc0DyS9Mm8b/wPjXLc+l96vA6c7RxM9VGyC5L/A52SmwWkckZQbV+sn+S2DbHaab65ChPNxCbVjYaHdTt2mOcZ7RgFyVJn70Im+l7Ckkqp4/nKcsT3r98wH+RxxhjjDHGGGOMMcYYY4wxxhhjjDHGmGeAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmGeAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjHkG+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhjngH+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxphnQPepF/CsqFKZlo+bk8+dante++PDGja3Qwnbt1+OONS0iyeaNvFYknR4HW9oXse/X9K9JM+AZjXH85xgooEvoMRDSQvv/3gbb7S08Wa65P7bMe4TydE/erbdhu3DZ7uwfYp/Lklaen5GVNjnsonbM/kvcP/tkc+fB4ubM12isxmv+fyX/jyhrd35Qt7csWmtq/PH6+7iS6BzLmwyUGdql9xZB5ewP3IfYrcJm9uHAbvUPt7/sorby5Lo3xL36R6wi2awp+Ui/n1mMxuw85kt7Q5x++oObNY+2f9tslGgmeJ5Vu9pEpal00uwmXQuktpDfGekm6nNAt3I+jRjvLZlB50q74XmIRmXpHFL8g+/v2ZhOn0bDiD7rBv2L/Al9cgKUKZ4LPJLktCft6f4501i/8ifFJBxSRqv4aAB0pfHh3Fze0z6rODMwM1k8R/RUCwlaXUbr61JppkX0HMwTdT+4WnYmsU/zXTePO2JNzNexnuZLvjOyATMW4i/rmHBkq5exTZ7nllp92/ieLLsYwUoPL0K6F/DLht1kO5lvOKzpHC+6VhodrvYONy9ioVm2nDMNl7F+t9+zee/wHinm7jPw+9JYtZLOLQpMdpgZ+ku0zh3BWvLQlnwAfNFPFZ3n+yFbEYyfwGfRTLbJqFsNg+xfhN32ryLDe1IsYT4zrI4c47DbNS/bn9+zJJB+k/+l2LcbP4sNyT7S2PNa94/5UztcL5gZH5u91U80earWDjLGoo2ksoF2P8N96lTLByli21ZGROncYztb72+5Pk34NCPIExtFrTHz8aXoBiSxst4n/092JIjB02lQnEiy01P8XlWqBmWY5IzX8X3vyT3X+DO8J6nZP+7eP81CRrJZsxg/7L4ZzidXxxbKJ+EfHZJbAZRk4Li9CI+5/46vufxyDFLv40Ps03yrNMhPrMKcUYWM9QNyMaY6Cz0GcA31ibZ/y3IzAXnch3ZGaCuWMYK5T9PiCXIz00XLH/k//OJ4ubxgh3tFnRg9fV12N5kNpvsSWIzah+vjWKjLGagOk9JYpP1W1gb5SxJzkRro5hN4ry9tvECpkRnx6vYN1H9M4PyaVALSdIEuXEK2WaqTSVvPcn/UPwtnf/epIG8TGLZyGSmO8R3RvWs5pC9HIA4Z+SYhZ+Rzebpuz2sOZH/aQtrhj5ZzkSykb0bobrJBvK/42sei+pJ85r1ovk8zg3aLjYMhw2/UOzex4eT+Xl6B7XgWfJYVBvOoBow6exwk9wliHJ2/ssW9O+ChbZCDDRDbLgk7wb6O5oEu6jCO1CqTZY5iTOonrlJ8hwYr4UaUGYzD5+BnQH/J0kreG/YDrH8r5KYpXsT12YL5GyPi3uCn0vwX+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmGeAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjHkG+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhjngH+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxphngD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5hnQfeoFPC+qVOtHrf0D91jWcXszFuzTjHH76v3Hc0tS7XiseR0/mzb8jdbSx+3TjuaP2yVJsLS6b7FLhTWXI/RZkunneKzuwH2GVTxP7eKJSjI/Mk74qG5WYfvcx3fnsypMAAAgAElEQVQ2Xib3Hw+lFmRMkrqHeJ4pkH1Jml/xYMOruM/pc77/9i5+tn4b75Pk9fFZPH974DMrE81DY7EuVXhUEpXp3sWdMjmrcJwd2Kb1W17A5m08UX/LMltOIAPzHLe3fP/NQ6yctWd31KzjZ6s53ud0yUKz9PH91ybRM3hUYPs1kdkK2yx8/Ogzmgn2v02+0V3B4uguJQ2X8Xgkl83A07dHOP+Wz5/0DPUPdFxiPWuT8yfmhQSD9Y/s2bxmnVkgBpg38e+HV2xMCvjzSv5X7Gcr+Iza8P4LnBm1S0k8BdOQjj3OA+0Tn9n6yz0PGHD81o4fwjTTjvdPkP0heyFJDdjMrM8MMvsUn0UxazuwzNTzjwZtA9tSHovUeWGV0XwBh0PbTGKG/UOs6PMhWQBNs4mFph4SpQF7nl3LvIk3tMCxLFk2ShM9RTBaWFfiszHPSWKW+TIOzh9+FnxppkxT3Kc5Jn4+kafw533mM+JnlQIjsZxpjNc8r3nB7ek8+/8kElGi2CwTP4rNyJePFzzYAnlelhuTnSO7vEAskdEe+dl4FbdTbJjlTKQa05b7kD5Te7aX/uF8n0n+rB2T2IjyCcpNEvtT1yA0SR+9fR+P9RDHP2UDBTBJdYqVpiS1kXRt0Vh7vjTaf3PiPKdsQDkozlwltYEpHqv98h77RPVHSdJCC0hk6R6KYJesNGWCszmB0m7ZaNQtywYxUxfY5ulIhlGqX8aD9Q+Jz6J8FvS8v2NZmq7hbJI6Q3sVT3RzFd/lbcPn37bnFy67Vayb3S6+/2nk+HO8h7vJ6skQG+DPv8EG+BZqRu3AudnN3477UA2+f3fCsQ6fx/L38Dnv8fA5xAbXdJdJzAR1li6R/xbUnPRC4rh9vojvvwwss8su7rPAXUpSc4pldnUP8dcqqTMMUJtIRJbOrAH/n4X5M6ytJHb+9BLeAV1CPX91/vucJZGzBeL26RI6JNPTu6ZmYJ3BaIJqhlnKSM/I/ybjtWAaGjYZ6iE0yGojzQC5Gdis2ifv5rr40MiWSVxPJznvTryXCWpDS1Ibxnoe1bkSASDXQLUMKX/XG0FyIXE+k9VG15vYB677uH2A94+StMC7rgo1E4lr7XhmiTGlsnH6Ph1sNtb5kpyNcsPM/7V7MDR7PucC+yFbmu2faiOUS0pcg+vu473Qu1FJWsCf0B4lfqfawXvb4TqRGdDZJnkH1FFstIe9zOy0l4vYNmbvE0p0AeUJtcwP+C/yGGOMMcYYY4wxxhhjjDHGGGOMMcYY8wzwhzzGGGOMMcYYY4wxxhhjjDHGGGOMMcY8A/whjzHGGGOMMcYYY4wxxhhjjDHGGGOMMc8Af8hjjDHGGGOMMcYYY4wxxhhjjDHGGGPMM8Af8hhjjDHGGGOMMcYYY4wxxhhjjDHGGPMM6D71Ap4VVdJcP2puJu5S5nL2NGWGdpinPUAHSV0P8yfLGvfx91vbL+NOx1c81rKK+9AeJam2bdzn46OXJLX788+42yfzN/H+qX3zNc+/+XoM28tpwD7Lm3dhe//yImzffm+FYw3XcP4LHKYkLXGf9hi3T6ceh6pgQeY1z7+sl7D99DI+//6ez5/0r+HjV38PY01P0OV4K6qxiKdkdkbJdUbQuh7niQfr7k7cieR5uwmba8cHUIZYZ1T4/Nv7eG1Nf/5BD1exnLWwLEnSHT0A/UvuknQmu+NmjB+2p7h99Z4XUB8S4whs3sQGfdqQ/eG7HK/i9iWxGRU+OW7G88+f9IzsnyRVeNR+FdvmJpGli+/Eyrn5hyhkmrY3YfvpIZb/1Rv+Rns6gj2nTUrsnEFn6b4ktk3tKdH/Q/ysO8S/7+9Zli7/QSwAzchBy+kbO5g/Hqsmtoxis0xm2yHeD8aSiS1pj3F7f2CnURtYdE10Fu5sAP3PYkae5/xzJlqQJUnagmxmKrOswDfBVqYd+7LhRXw3pU0umnKTBvpkMQbpcxJndBS3wzxNEn5UMFnHe05h92Udtpc92Mw7PoD+fby4LM7voM/uu3HMtLSJzb6Mz3JJwh+MTeHI6onnryRLEMtLYjkD45TZLNKzVMVxQDhLTnNYZhM/P20hN8nifIDmyXwG6SzJTLZ/ymcWTk3xzKhPZn9/knkW+Zkm8T+UT/b7831mf5/ozLlAzUJKbNORDS3FLXUCARwSDexiQ1P7pOxIa4aaUb3Y4lDlGI/V7llpe7iz9giKFtQLfxTLZRxLSlKZYyEspyw5jcGYLZEZirMWyBnLyOsiyWh3bDQ2X8W9TjP4zCRnbMBndUk9iewJ5RP9Lfv/5m1caJo+v8Y+87s4ZnkDe1lt2AGs+/jZ/sjnP0+gZ0ssMyVx2u1FLBvzPTuaQjEIhRJJnWF1C2tOaqOrr2M5n67ie8EYX9ICtXnUS7Gfp9pElmdT3XT9lvdPfjaLc9bv407tLfiZ5PwL5OBtkpvT+4T+IZ6nUlwqridP7GY0xaZJLdxzmudDne8p9RSap0mi5nkXD4Y1S0kVctAynv93AtCcJCHT6j3oBqjmdJH4bEpZs61gbgCxRJLnUj233ye56T3UoEj+BhbA+RJy5qTOc24+M6+SPPMp702gNob2N5VlaH/Cn7yY4d1oWuend1CJnz08xP782ICff8/+l+qsmZ899x046YUkrW7Pf59HOksx2+qWz7I7xYbm4ZssmNOW3idjF5RBOsusNrrAWBD+Pc4PtoF0mXRJSt6bZqVZ2g/0mXbJuwGoZ+++ZKexfhdvlL61aG9hEknl7W3Ynr5ni3Lg8QmFoQ/4L/IYY4wxxhhjjDHGGGOMMcYYY4wxxhjzDPCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxjwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxz4BP/iFPKeUPlVL+cinlO6WU04d//6dSyh8LfvuLpZTfKKW8KaXsSyl/q5Typ0spT/gvKxpjjDHGGGOMMcYYY4wxxhhjjDHGGPN86D7l5KWUPyvpv5L0laT/QdJ3JH0m6V+U9Eck/cYP/PZPSPrLko6Sfl3SG0l/XNKfl/QHJf3K7+LSjTHGGGOMMcYYY4wxxhhjjDHGGGOM+YnyyT7kKaX8ih4/4vmfJf37tda7H3re/8D//1rSX5A0S/ojtda/8aH9z0n6TUm/XEr51Vrrr/0TLkrqPv4jRcMVdzm9WuKh4mZJUndf4gc1bj+96sP2bJ6lgzkkLX38bF7TJDiU6hP+ptO8hTObk4mAdh/3aUbus/k67jNexL/P9ri0sOaGO5VVfJ/t/Sls37zb8gIU/zGqeZV0AXkuFWY4JfcSL1lN0mdZxRMtYI2mHSxMUg+61D9gF6Q9xfPUwnupsOb2ntdMOjte8jzNBO0jz0NM21g2j9/cYZ/uJjYOS2AvJanMyZ292cd9jqy004tYB+ZtfAFLz/o3XMbP5g120bQFm3EJHRKbUeAuy8x9yAiXOZ5o9T7RvzfvwvbmEgyg2GeQbczOssLfz2vGn5z9T4E1k/2RpO4Qt9M5Z/7n4jux0WzuYBJJZbmO+0yxnpWJz4XkL/PzFJssa5g/kWW6Z5hCEvsAihmaNQ82XoDOrPgPO7bHeEPkG7o9H8DFF+etS5KGi/PknPyFJLVDfJYz6Lgk9YfYaaW+cYnnaY9n2lJJ49UTbMMxbiefme2l38d9qF3iGGzagC7d4lAqC/gs0D+JbXNZyGbx/ukslYQf5ANorC4OCyRJC+QmzZ51Flyj2kP8oAMZl6TagM2650CzXMQxC8WZ69gtf+gDOhO7hce1NfE8zQHu/8T2h+6y3CXnvwGbDTKT5QzUJ/Nz5IPJl2f+j+xpn8T567tYnkjOCgVGCVluSvZs4XICQv68HbgPnT/ZxSxmoHPuQJYlPpuG/B/YZYlztn7PNqOFe25PvNEyQ5+v78P2+sBGs0ANoo4cnJbruDhQNqAAUxJorOOLrj0H2mUPzuEUr7lecm2E5sn8vKieA/lsM/D+yz3cDdyxJKlCbLIDA5zVmcZ4bXVIkhNYW9nA/DXZC7FwnwbsCekfxZIS11mzOIPYvANfdkh06QDFsUz+1vFG+3V8l6cDG/NpjP3Jas1rvr6gQC/m/T0n+iSZc8s+sznGvciXZLXJ9Zu4/frvstOarpPCRcC8ZZ9Nfr7N6hwgG/3d+bLcHSD/Sn029EnqjKt38eU078Fnbbg4XcbYN5YjL3r89suw/fBZLEvjLns3Ere3oMoSx8aUz/bxsUiSKoQG8+r8OAffp3RJbTqJpxHIJ0k3a6L/At3o79nP0d1QbT6zvxSCPyXPxvgzCZnIzqV9hlhoFqhnLTvWv+YUTzT3bBepNrx+F69rA/G3JB2aeM0F4iJJWuDOyP6leR7IbJfVmel1LqyLclmJa7Nt8m50fBff59JDzSrJmSifark0jfun2Cyzfx3U07pjon8Qs1Of9TtWprufjR3AkNQfpye8N6Z4lu6/SXJjqpuj/VPyfpi2mcgs2qakD9VgyP6t3/BgOBa8G5H4zBqIPygve+z0hI8guuBysrzgR/BJ/tNapZRG0n8jaS/pP/zhj3gkqdb6g1f6y5K+IenXvv8Rz4ffHCX92Q//53/y01uxMcYYY4wxxhhjjDHGGGOMMcYYY4wxP10+1V/k+UVJPy/pL0l6W0r5dyX9fj3+Z7P+eq31r/3Q7//oh3//SjDWb+nxg6BfLKWsa63Jt9PGGGOMMcYYY4wxxhhjjDHGGGOMMcY8Tz7Vhzz/6od/v5D0f0j6Az/4sJTyW5J+udb65YemX/jw7//7wwPVWqdSyt+R9C9I+n2S/q9s4lLK/w6P/vkfb+nGGGOMMcYYY4wxxhhjjDHGGGOMMcb85Pkk/2ktSZ9/+Pc/lrSV9G9KutLjX+X5q5J+SdJf/IHf33z49z2M9/32Fz/ZZRpjjDHGGGOMMcYYY4wxxhhjjDHGGPO7w6f6izzth3+LHv/yzt/88H//n6WUP6nHv7zzh0sp/0bwn9mKKB/+rT/qh7XWfzkc4PEv9fxLP8ZcxhhjjDHGGGOMMcYYY4wxxhhjjDHG/MT5VB/yvP3w79/+gY94JEm11kMp5a9K+o8k/WuS/pr+8V/cuVHM9Yd/6S/2/HgUaVm1HzUvfdKngW+H5hK3f5gnHGqO25eOx2qHeP6aTF/h7zAtH2/9kWysLp5/WfE3VeUUD9iMMFH2eRZ0WdbcpRnj9vYUt/d3vID+dogf1GT/mw10ifuUicda38VCc/8zdJnSeBG3V5Ll5P6bie6S+5Ql7tNN9PtkftCZ7pAIDTwiPWvHZCyQmXnNh9bM8Xjtkeeh8ZYe1pyMRXdWG15z9z7eaBniS6srdi3j613YPq9ZZpsxFoKlj43ZcM1jkf07veD9z1uwszDNeM1CW9t4rObIfyBv9T5+RrpUOx6r/dlvxQ+OIMySpk083ullPP94lcky2LnUZ8L5X8LvE5tB9qx74PknsJm0l3SsTSw0qxUHGqTn4wXMkxwl/R1GkkuJ/XldxQddTskfe4S1zbvk0shmr+J5xqvE/o5xn+1XbDP6r/e8toC6zoLGVdh6+3OJzQQ5b49xe7dP4g+wGRnDZXxmS3t+nLvANjOfOcUhUxpnduDPV7fgS5Ns6LiN+5xueM1gsjieScS/QGykLM6F2IjmwfhP0ryK91loDrE9WWCsjCVWGW2/SOwMPGsP8c/X7+iQpe57kFr2rOfzLl40xRnjJZ8LyeaS2Gyy8zMI5rxL7v9lfDYlkRnKjRfy81miTTlzkmegn4H5O7Clj/NAzA75t8Q5OOlM/8DKVEvsm44Qfz1OBM2g/+RLJGkGO5PmebCd1R38Pslz+wdYV2L/yWY0pOZJzkRnOe7Y/nT7+ACyPKe7j/vUXXwBJakz1AI2e5/YzBHyuSMIR8t7KU08T5abaBNfWjnGdZZySgTwFPepN1vsMm0pOIGcbc85kxaImXcQzEgqBxgP7lJdlueSnU3knHIQuheQl8cFwP57XvMAf1N9uoSckWqGklq6Sr5+jLOmDcSMO/ZZzT4+s6zO0qxj/V+t4oUNxyRnBD93PIBhlHSENRM1KTTX6fw/+E8xcztQnYvHohyomTjQLvSM1O+ex5q2sc3u78+PGSbIP7LaKNWzqf4oSevbWP4o/pGkdn9mDTzxWcT8ggo9UhnjNVP8QTU7SapkM7hLks/G7VnMRD6bYplsHqKF63oE6vlZnndmnDuDLZVY/5vEzdJ+Kpxz9m6MzhLzb0kt2Fnqk90X2bOaxuaxQBfQc2rPWL/lA1jWYOcxzUveM5zitVH9ReJ4nuQvs5mUT9fkHSzVUyhky2omPZQZ8d2spP7deX4W37NKed2cupz7FUEyfQc5GPm/bDyyC8dXvOD0XT9Nj+/tkxos2Az0P09YV5eUrPm9PYx1l8R5IJtZbo41aOjSQc3ucSyKM7jP6n0sHO3b+NBqnwj5Zfw+UxecaJQhcE5JXvCj+FT/aa3/58O/7+D59z/0+f5JfP/3/9wP/7CU0kn6eUmTpL/9k1qgMcYYY4wxxhhjjDHGGGOMMcYYY4wxv5t8qg95fkuPH978s6WU6Buw3//h39/+8O9vfvj33wl++0uSdpL+t1pr8t2uMcYYY4wxxhhjjDHGGGOMMcYYY4wxz5dP8iFPrfUrSb+ux/9U1n/xg89KKf+WpH9bj/+ZrL/yofkvSfpK0q+WUv6VH/jtRtJ//eH//O9+yss2xhhjjDHGGGOMMcYYY4wxxhhjjDHmp8a5/3W7nyR/RtK/Luk/L6X8kqS/LunnJP1JPf4nSf9UrfWdJNVab0spf0qPH/T8L6WUX5P0RtK/J+kXPrT/+u/+FowxxhhjjDHGGGOMMcYYY4wxxhhjjPnJ8Kn+01qqtX5Pjx/y/HlJv0fSfybpj0r6HyX9oVrrX/yh3//3kv6wHv+zXP+BpP9U0qjHD4J+tdZaf/dWb4wxxhhjjDHGGGOMMcYYY4wxxhhjzE+WT/kXeVRrfaPHD3H+zI/5+/9V0h/7qS2oSGrKx+3J5051tcTtXTDO99m3cXs8lJZkrHaIv1+qyZqXHtpXcfu042+klqspbC9d0qeN91/u40V3e95Me4zbmxN2QQqcf0okL5JqB3csqcww0TSHzcuK73/axGdzesl9xut4/mUL6wIZfxwsnqf/mk1Le0x0I/p9cpfNGLfPyZk1Yyyb3TFunzbnrVeS+geW/2kL7btszXF7e4C9HHAoZFknMvNiEz+ALmXi/bcP8WaoXZKmq9g4VZh/YfXT4fO40wxblNhmjt+I19xsYl2WpPoQ60ZN1jzcxDpYllj/D695sG0PukntCU1s/vM+YDOWVfItLtxzXeI+ZU50ton7zKCXEutfgf23A49VW1gb+BKJfRPJZW35LOcdxSzJ+YMPaNcg55c81Hw6L/7JmGGfy5Hlf17HOjOvOM6on12E7QW+H8/GGm5iPWvB/zyOF8sG+ZJM/st8/jfvHcRZWZw5XUBsBEtL7e8a1pzIDM0zwTzZ/KR/NbEZBVQD48zEZJFvaAfutJA+050lYkHnf24sJ0kz2Hm0i5IW0POsD/GkOH+MDX0dOWahtU3buH284gugZ5R/SVLpYaNwZP2ax1q18Vh9x3HONMeCNg6x/Vu+lcRMYM+mke38dIrnbyGfnA5J/D1BzJjkGZu3lE/E8w9Xifyv43aycSlkSiGWkKQGrmaGmoHEOQj5uSxmGiGeyM6f5Jx8ZpZnks06vWAHOK/iw9m8YTlvITYqD/HhlGNyaAX87xGcuSTNsLZ1LIBllzlAcvSJo2ni81wuYJ6Oz78M8fkva85zKJ6hmGm5BMWUpOt4zUuy5vaQjBcxsTNrTrFvqkmeQX4Oeyw8f72OY+banv+/H6U8i3I5ieO5zM6RPaWctfbsf+ics5ilNPF5dtDedMn9l/hsGvDlkrSAzyY/W2AOSaL/aW2h+rekeQO5KZxZGVmWVvew/0MSM41QG92cXxtpj+ft5XEBcTPVE5Pj5zj3Kf+TZ6izSGKb/fo6bC8j+7/lIrZ/p1dsF6meS2TxP9YNE5tBtoninzXEhRkzxJ+SdHoNNYgN5ExJnafu4G4yOYNaS4HclPJiKann9sk7kCQECedI343RWXKfGQSK5klzdthndmbNED8kW9YMbP+WVWzn5g3bbHw/BTKTnf8IuXG/5z4LmGZ6n5m+T3pCPRvrKXBnQ2wWH7uAzj4FGovORRLe2ZTUc7EGDrWhLP4aoWY4XiYxE+WzVDN7wv1n+j9enllnE7/roDPL5BLrnLukzxNqgDgWnHMWm1AfyvOz4uglxHlkFyTp+Fl8obsD5ExJnF8gZ0qJ+vwT/C2aT/YXeYwxxhhjjDHGGGOMMcYYY4wxxhhjjDH/GH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzDPAH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhjzDPCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxjwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxz4DuUy/gWVGKlr79qHlpa9LnzHZJ8yYeb7qIO80rHqx/iNunLfeZLuL22sTrak881nINY83cp4zwrCaHRvODBLfJJ2pLD9NDH7oXSRperMP27df32Keu4wU8/MJnYftXf4DVdN7Gd9YM2AXvsxk+ln1JmuCOJUmrJe5zFbdLUn8Xz9NM0CERi/YU779/YJ1dunjAZXXeHJI0r+Oxjq950c0Yt2drJtWg+VV4LJqnzNhFZYrvc97FstmI739cxwe99Ky0zRiPV+Euh+vEZsUqq2mX2PlvH8Pmy90pbJ9n3svcxwfdgP2VpNM+thnjEG/mdMPz113cZ1mznXn4mXi84SZeM/k4Saqx+qv2yflfgnG4i9fc3yXnD/dPvkSSBEtrwJeRjkvS+m1snMkvSNLxRbyfeRP/nnycJFWIZ5pLXnQHMjuBz8hYXcT7L4nNWq/IOcTcvd/is+PrWAAOn7EAXP92rP/EtOFzITnL7ozkqYVlkY2TpBFsY3/H50/2NPMZ6LNAZin+kqRmoJiF+2BsvIMOSZxBa8vWTOD+kzyjkmiym8U+2ZkRDcSMaczQwoGSn0v20k4U53CfeQV2DvMPHksNCQB3mi5ihaY4syy8mY5kGQVDqut4bbWDWCqxsV0XX/Rufb4wHbv4XA4nNoCTYnu62cTxlyTNu/g8p208z3xgm90c4/uvDd/ZvImftbxkZIGlkS2RpAXkvzxBl1A3E52ZwAUPN3AuiYvtKZ1O1kw+syzxopc+qZmALGX7p9ysHTI7HxuHMscX0N3veQEniLP6JNBYgXHaJAHFmZQ5cxokm3F7Dep1/6jLGM9DOaPE+rys43kq+ThJZaakIbEZYJu69wfsQ1A+kZ2Z+tiflAMYrYl9RjnFCpiV+SgGojhruWRZWtZxp+6WgzaKZ6g21b5PjBbJcsIyxmsbZ0qaeY7xFPfJlkV123KE+SEul6SS5fM0/1V80DOsa0pihuESbEaX3X9sZ9sDyXKiy59DbeaK56cckN4BZL6khdCsGc+vjbaJ+SE7Ww6wgEwAl/j8k9KAmiGef4S6/XiZTE/vBpLcrAPZbCjOS/bSHeFhcmT9LfgsUNnlgm1mu4baZMt9RsUxQ+ZnEbBnWZ69gG5QnkdxsSSNLyA32iYxC9nMFdTMeCSNLyCfS/K84+dxoL16B/qX2D/SvyGzWXDPFGeneQY8m5I8B2MDiOdrYkwozseakdgFU8wwXiX2F2ST3s1mC6g92NLk3SzapiTOwOOEeynJWBPkzBkd1UDh/jfvuNB0/21aNM/f3533PlGSage5OSwtj5nj9i5JDQW5KcW/NUkZifb4BPv/BEbMzROZBTtXoc5XhiTPGSA2zD5C6IJLe0K+8H38F3mMMcYYY4wxxhhjjDHGGGOMMcYYY4x5BvhDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY54B/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYZ4A/5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYZ4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMeQZ0n3oBz4lapHn98bdNy5r7tBfT2fPMtY/H+k78XVV3qjzWpoTtS3KzSxePB8vSeD3jWKVfYJJ4XY/zxPPPPczT8Pdm2+/Gz8YL7KIKZ9Me4/aSXHEzxPsvE59Z7dqwfbiO9zJv+f7pnrt77KL2CDKzgt+f4vU+zh8/m65ALiQdfjY+m/VX8VjbL3j/DdzNvGL56w/xeGUftx9fnf+94/YrXrPg0eklr5n6bL+Oz7mDPUpSt4/Pf97wPt/+wjZsH69gzcn21+/jh6s7lpnjy1jQp208/5To/+mfPoXtVy/23AmgbbYt7+V0iA1tnfn8K0y0rOMH7YhDab6MHVrtWP6m+PqxvSYqs6zhbMAvSZJmWNsmHmt4zUPVFubJVPZ4nm2uDZ/l/lvx+V/+PfYZtLZC7jfx/2Ubz7PZDtiH5LkHn73q2Gm2DdjfwhewP8XOaX8Xn2V5C85MUnuK7+bwOd/ZvIoFffdlcmc4f7zPpWOlGV7Aukj/wcc/PoOxIJZ8XFvcTvIncQxGtoHiT0maV3BmSZ8FYoDxEsba8maaQ7zo/j7x2UCl+DuxmRWmyWY/1zZUDvMwZyD/k83fDPGq2yTOprWNSZy5bEA3hniwQk5WUt3E9iTrs/ryIWy/+Aex0N7+PhaA8bN4n+2rOJaRpMuLWNHJzn5+yUnDDMI5Lbzm+1Nsm8c5Pv8lyRnJzzQN338PuekA/mdaJXnOFnK2jh0txdNkf7dfJDkzLG0GGZfYNhawpVn8Qzlwt0/WjHYG8v91Ys0ozUi6UDmB7FKW52PImNlMeLYkcfZ4Qc82Yev2dI1jtd97i8+QhZwGtGd1jlNsm8om3osk1S3Ec1BnKPdJ/LUkAk3zw52VOR6ru+eYuUI8t6zZZjQTnPMIwtnzWLWHM6M5JDwzuhetOc7WHN9NElGZRNwAACAASURBVOZjbLBAzpLWXyH+nAqvucD8wzXkDL/3Csfq786vDVeITY6HeM3zXRIAEyPbnwby7BbsfBZ/93dQm9kl9bxvQOECDP2yYvkfr0j/2Gg3p/jOmi/ehO3zt7nQ0B0gZttxzET1zMw3n0tWGy0Q52X1jGaMbUN/iG1jGZLiVGHfQJxeg25AbSqT2azWjsRhvjqoJ7fsMtQOVBvg81/dxu3Uh94/SNIyQJ1rzX6228VCm9VziHkCnRVf2gI2s0KcT3Fp1qd07DPrCPMfwf9S/VNC5zhBzUJK4uYC998m+g9/2yGLzWcIDSg3GOidgaRpB2NBziRxDZr0nGIMSZrB/CyUACR9SPynyyRmhXejedAEzZAALSCvkjg2yGpTlBpAMJ3VuQocTdaHzn/97vx345RnjhdJbYjuLKlnoJ+nLlluTtMnoTkxwT7T2iSIU5PMj7XBiWLGbKy4D8mSJFX4pqD/ZjzR6h3X2XBdY7KAJG9+Cv6LPMYYY4wxxhhjjDHGGGOMMcYYY4wxxjwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxzwB/yGOMMcYYY4wxxhhjjDHGGGOMMcYYY8wzwB/yGGOMMcYYY4wxxhhjjDHGGGOMMcYY8wzwhzzGGGOMMcYYY4wxxhhjjDHGGGOMMcY8A7pPvYD/PzBvFny2Xk1h+2Y1Yp/bGrcP1/F1jLuCY63u4sFW9zCJpNMh/n5rKnGfFn4vSQutreH5ywh9aKgT739ex+3Tjufv9vF4/V38+/U7vv/Vm0PYXtvkG7lVHzZf/R0Yq9niUNMm3ksz8f6VPIrn52fH1/H82f5rGy+gxKqk2mTyP4ft7cibnFfnfb+4+5Lvf9zGa6N7kaQG9rl+m1wMDEe2Ye55/gWsfnbOyypuJ/2jOSTp+Bk8KHwv3QPJWfz74YbPsu7jTrfLBfYpHcjAbazLNbF/WsVjlRNsRlL3EJ9NicU/lb8F5L+7PWGfy7+/gScgf8n89RA/G1+wnmmIm7v7eC/tMfEZG7ibZPoWfBDZshb2KEndMZ6ochetHuJ5+vu40/Ay8X/r2ACtezBMklZdLGhdE+9lmFmWH46xMWnb5AKAOoMsJ/ff38ft63d8Zqv7eG39fXxmpGOSNO1i49jDHT9ynp6Rj5Gk9hDPM15mMgsPkivrH+J2iicmDnPYz8Tm98NE8T5rB+ecuV+wsw3Ypcd5YKwJzpnWJaH/L8n502jdAIMlY9H+50TOKM7GM0vCMpSZi8RowglQbLL0Scx6Af7vHSQNktTE49UWbPYNX0CFmCGzGMchVo5lief/nZGDNrL/Y2Lnj8d4/vkYz9P0IGSPvcLWZeH5lyU+/3GI5y9JzNb08fnPW17zDOdcoH28xKEw/s7ibLIZFJu0cfr5OBRsM7e/cfPqPZxLcv04zxNsBulfmbOcGWoG77lPD3528xXXhsgGrW7jPs2eY3aqM9SOdYYo9/t4rOtEaC93YfOySYQG7qC5i4OJugbFkFRhnrIkep7VTcJJkrEOcGfQLknlzfuwfXn9Iv79wj6juUsUmphACUdYc893Wbdx0FZmXnML4twcY71YRr5/5AWffwN5/lGx/7/7PWyAX/3fcXCU25mzmtMAoIG6bUPxp7gGR3FmD3UZSWohZ2io/ivpQHEWxD9N4v+6/flxPsbAbWwzs7uctvH5z6ukNkPqBF2ymgG50zbJWdoB7G9mF8nPrs9/vVQ7OLM1O/pzc7MlqY00YH8yOaf3Bh2Y39UD2z+Sp4nKb5JW9EIJhKaZ+CxPcDZLEptRCthCbFyTPHN5iBWgu+WYJat1hCS/79/F8yxQf5WkHmqQJH9ZbZrqlus32IXtCSy5veOYcdnF/vTqd9hoUMxKtqlmRpsMXUIXh6aYM2U1G3qfenyVrAvem5KfKZ+zMnUbiBmT3HSezoznk0SrQs2iWSV9IJ9doDa+JHVGem9cHniP9H768A2YP6vzwKOF3hlIWiA2yVggBqvwDoxy5nSOJDQmHaDaBL4zkTRD3ZLybIlroxyc8VgnqA2v4lTqcRayzVcUzPBh9gXqKQ9sZ+vq43eN9btP/7s6/os8xhhjjDHGGGOMMcYYY4wxxhhjjDHGPAP8IY8xxhhjjDHGGGOMMcYYY4wxxhhjjDHPAH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzDPAH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhjzDPCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxjwDuk+9gOdEbYuGm4+PpF7O2Ofm4hC2r1ruM9cStt99O76Oh1OPY5Xfib/FWpKbXb+tYft4Hf9+Wce/l6RuPcHCuM/8Mn623Mf7bMb4vCSpwj67B+6zuo3b6cyGax5r3sVr7vYn7FNLPF73bh+3Hzc4FrF0yZrX5/WpbTIRfAqYXL+myyVsP67iTv0dL+B0Ey+gHXj+1V08fzPF8x9eZwcQs3kfzyFJ4y5e8/6biZzDEvo7mP8d2x+654dv8ned0y5u72KR1WbPAgDmT8fXvP/hJh6P7rm/57GWHTw78D23YJvmLdzzju9fE+hZojTTDdjZOR5res8O4PQSbNYdK83tz8fznD6L5az2iQFo42flxPLX7uNnhdwPtEtSB7KR2bkKS2uP8Vgr0EtJWn8d+4ZlndzZFdwz6OWyYfkroICH0wr7SLFszM3534IPSTxDTHcgsyTnifoJRLMdWGbXb2KBIlu6tIn9Od+daIGraca4fXXLeyngGiiWkqQGzqY7ch/cJxzN0vOZtQd+di61BeG4hsOUNN/E7Yct60x/B2uGq8nkoj3FY9FdPj6Mm7sH+Hlissk2NuB/JI5NyJaSLXvsFDdvv5voWR8vugWZrQ2PVYZY/+vPvMY+p8/jDT18G2zGNzhnePkyvrTdimX2oo9t9kKCkXCaYuPw7sC5yXodr+24gCw/QcVpDknqmljPW9D/4cQGcAGfWXp2NPUCfAac5fASh8J4pkninGaANdOSs/OHZ6nNgPYGwkxcl3if/R0vYIEwY16B/mU5M4j5AHGZJPVQg+iObOjJBk1zLDPd2/Pjr/rdL/FZ8+pF2D5/K7ZzZU4cECh0mZLY9CGupy0vr+IOSzLWAQTtmm0Wnf94GZ9/mdn/NwdSWuwiwTkvW5h/YflvwP81b5LkZAR72sXz1yP7rFLjtdXPLnn6K+gDOWN2lnVN9p/P7MV1XNC472M5v9/zXnbfi2Vj8yWfmcA3Ik+w2VizkNBoV6jNZTl75puQDdgTOJdlxXs5vQKZTXIzZBU7k2XFtny8iM/mKXHueEkOmIdavQddSnSGfGMzss60D7HNKFQDbxP/19L7jKyeHT/bfzte85zU5lZfx2vL6kkUG3SxK8NcOmP1kNSTt5RQx+2U/0jS6h34P6izSxJFAPN4fmzSHOM+2fscqoFQbpy9G6MaSBabUj2b1oV1AfGaszibbMAEMUP9/AKHak7xAqL3ot+H5K8/gM/IanO0rvn8RIPeDUyb821Jk4S5dJ9UMxkSvZgKxPn0nlVSB7HJQnl2opbNKp4ny80hzBO5jGVICl1UMoP4Q5Kmi1jRmlV8LvsLjtlXT8inqJ6evc+pXfxsuiEDkLybonCSDJP4fVoH7zMaeGclSQvpRqKyC7wfotikJu9zyTdkcQ7pJr0bbgc2Wt0tONQkN40UKrXxPwL/RR5jjDHGGGOMMcYYY4wxxhhjjDHGGGOeAf6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmGeAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmGeAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjHkG+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhjngHdp17As6JK7VA/bh/4e6d5iZ8da8E+m34K2x+2cft4zde09HF7Mr3Gy/jh0gZ7l1RXC441z/H+SzL/cmzD9v5t3F6beF2S1B6SiYB5HbdXOOZ24LGaYYZOLDNlhj5zfM4Ffi5J8yref3b/m3fxefYPsfwtHQ92uo7vrDlxn6WN+xDTBT+7+IL2wjJ7eBXPT7rUHVj+xot4n+/+Gd7jAo/aE3ZRfwdjreL2u38qmR/6HL7B+1SJn02w/zG5/xKLmbo9T98d4/GGm/j3S897WX0Vn810yTIzfR4bgaaDPgvvv4LPaK7gYCRVsrNvY6FtEpvV7cHOTLx/uH41p3hddebzX9bxPLXjPvM27rOs43OeLhOfAbIk3r6WVTxeM8X77/Y8P53z+Bock6R5A/vcwjyJz/7sxX3cpWVH05AAACPIuCS9uI4V/TCAAZa0zPH+Z4jN+luen/x8D3ohSdMF+Yzz/S/q0sh9+vu4E/lm8mWStLmL97m+5T7k5zLWD/Gaxx3YjOR/VkAxUHfkPi08KzW+y2FIYhY4z5LYDMFwzRQ/WIGPl5KYNbmWCvH8tIs7pSoO+8xiYzozzFmy+4f5SZclXlt7gpjxfbKZr9+FzU3PitZeb2D+OACrB97MbbcL2++SSysN+FmKP9rEZ9zEPuObV3G7JL3Zb8P2cYz1b4Z2SVpKvOZp4j4z9KH5MwWo9Oie778ZYz1r99Ce2B+KmZ9ifwR7OdPFS5K6B35G+gzmN/VZlINNsYh9GA98I+Q/yxOqYT2Lf1xLEufMkvBuuofzagaSVDfxRpuba+7Tx4fQ7OPktNxz0lZ3sf2rO45z63Vs52ofn1k5JPtfx/tfVuef/+pd7BsKGgZJLej5l++5D9DAXuqGlaYkOdjZwD7LKlNaqOcltTGKZxqwjRRLSVJ5H88z/zwH2scxlv/hGLevk/rj6jY22rXj/TdHWHMLef4hCZro+rOYcQP6BPlXlrPMN2CzEp+1uYz1bIF6ylDAmEs6vYoP4Pb3cp+bBfL8Ib7L9o4TkB7inzmzP0AzQv6XqB/lTFmfCYSjQiwlSd11bM83X0FCeUqERpdha2ZnC8hG9wAym7zP6Q40CXbBc55BzI4v+f7Xd/FgWQ2+heOkOGeMj/hDHzjnRGcpzl3AmGdxZknsOUExKObsmfuH6bM8W1C3rA3k+UmdhWLm/o4P7eIfnheb1OTlXAH7h/GnpBZq/fMaataJLlPMLjhLiW0j+T+KyyVpgZhtzuwsxYxk/t5xojHDu9kR6v+SNMH70WaVvDikscA2VvD/Er8DKVB/yt6no51N6tl0AfTOhOpikjS8gL0k73PINpbEaXQP8drovVWXxJkz2OzsHRjaeSCz2XSeFLNLbDMonsR3Nkmf7B0Y+Wyyv+2B380tm1iflzXrefQOiPzFj4P/Io8xxhhjjDHGGGOMMcYYY4wxxhhjjDHPAH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzDPAH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhjzDPCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxjwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxz4DuUy/gWVGkeVU+bl8qdrk/rMP2plmwT9vCM5qGh1I7xJ2mTbCP7z/bwoMSj1XWM45VYJr52GIfQZ8FpLE/8F4qfIo2r/nOVhOPF0+SPJvhzO4PPNwwxH1Wq7i9ZguIaeMpJEkLXM1wFT843SSytIufzbFaSJKaEca6iPc5r3n+03X8bNyy/K3vztO/h2/yWNNF3N7fYxc1oLOHz5N9fgaLg61svuax2mPcvv2C+6zfxu0VdHaORVmSdHoVt+9fsJyDaVL/HuRvw/MP30qUg6jxPC9ePITt237Cod7c78L24xcgTJLKGM/f38YGcPsVn+XmO7Fwnr4Rr0uS+ru4vRlA/65wKI0dyFli5uoqflgLKEDLg9Uu1mc648dOcfMM68rs33zRh+3Tlr+rJj/Hk/Be3t3HAQD5cklagTw3oJhZ/HM4xcbh8JYCE6m5j++sO1EwgUOpv6OYiQ+ZxGyOrxLt1WOfeM0Tqx/O3x7h/Nn8aLyI95nJLJi/NM6YwG9XcKeZjC/gT0riZ+k8aX6KSzO6PXfafHWenaM9StLSQ5yZ6Dld2ryBsRKdITufySzFeRR/1MxnQ2yYyXl/H6+5ATvf3p2SBcBmIGZ/HBDkH+S8bHkzL2/iOON6A4cpadvFa0abnTjgVRuv7XbgS3uxjddWQS7JL0jSaR8b2iEpYZAPmifw/4kqLQP04dRYyzqef4HcOMsZSGYW8D+SOM8GW4JGXqyzSnSW7Em3P1+Xef+8Zjob2ktJVJniif6edWbags0E+ytJHZQNKtiSlCY+tLrhjZYRLuEQ28ZKdlGSLmPnUMZEaUAJyz1c2pwFerFtyOoplM+qgXUNPP94AwFVeYF9mttYAMoDCEZitCrsX9n9T3D/c3xnFe5YkuZXl2H7skryHIoNYStL4rMqHP9uy0HrDfisCXzGeMnzDzfxotdvEp0hcaJpkjyjewDZoHZJ403cXpa4z+o93+UMddslyTOGi/jMrq9AL5JEa3iI72xO8jyigP0jGZek4TKeZ7zk8x+gbkJ5FsXYEutM95DEeQ+xADZTImgUZ1zHtqG53eNQ8zq+MzpLSWpP8do2X8W/H68S+Yc8oyZxFtUgKWcarnmsZor3SbGEJLYB0CWLszAHTXNzODOIf7O3GWWE2sScLOAWfDOFuclQFJvNl+znawf1pF080ebLTJZpDuyi8fK8OKe/ZwFojvDsJokZIJyj+s94keQZoMtZPa3Akin+z+wvzdMmdpZqIFltBIH5C70zllSg1k3vmbPXiatdfJjDKUs0Y7ouFowZ9EWSyhFylswArc7fJ0E2m2ycJNUN3E3yPmECe1J78L+wLon1L7PzVDdsoZ6evU/HGkRy/rQ2em9IOi6xzczquT3EQFRPKCfOWZshWRz1CexsSb4z+ZHjPbmnMcYYY4wxxhhjjDHGGGOMMcYYY4wx5ieGP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmGeAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjHkG+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhjngH+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxphnQPepF/DcKDVoG/l7p3mKn3Wb+ey5l0N8Het94fl7GAvaM9pTPM8M65KkejmG7aVbuA+c2bKGPg8tjqXgviSpS85sgeGaCdrjLT6OtY3Ppm14/tLA/l9dhe01GWvzLj6zuec+lY6TzvKAQ6l/iOcfrnj+8RKmh/sfXsPCJK3ex5vZfY/l7/gyPv9xF685u//1u3ht+28m+7+O25dEZ/q7eM2RvZKkwzf4zOZdPE+Zec0H2E8DZq5NZKbbx+3rt9n88X5On8V76e7ZZpeHWGebbxyxT9PE87x9Gwvz2yXRPzrnNfuMBmzw9nvx77dfgzGTpDk+y9rymoebuH3axWNNV4n/60E2R54f6WCsge+/fxc/q8lnzRVcINnS8SLz2WB/tryAaRe3t0M8z5TIUgd25sWOlXbdxfI0zvEBHCeOGbouXlt/dcI+0zoeb9yDLh/4LPc/Ez+bkjtrD7GcUcxQEvGnPpmfJd/ULrAu0HFJWkjPuYvoZIabRM7XcTvZ//6e56ez6Y686GEVr62AP1+BXchoBn7WwtoonkvjzO5820hyNq/BZoAtfxwsbqazlKRKYgY2syQui/aSyewCJqiAbpTKg5WbODZX0mfaxBslP1OPnOe8eXsRtn91gmBS4guAoPHqswcc6meu7sL2i55t9ptjvGZiTuLPCvHPfEri3B7iacg/y5H1v4G1LReJoYfp5y3EsomKdw/xw/E6ybNB/mmsPr5iSRzPYy4pjlmmDfiyxJZSPYN0XMrsH3RIzr+F1KDw8asF2aScSWIbNEFsOL+EQ5bUvgF97pNDO8aXUG8gaU9Y1nBpiZstJzicPha05WrD86/iPvOahXZaQ2x+Fe+lPSUx+zaepyTFuQZyg66FmtFuhWNRnrfs2C6XG5CnAjHLWw7amhMo4BWveXULsQnkhss68b+QZ16s2dD0bSx/lP9vvn5CXDawAVg28TzNLj7LZUp85um8+EOSCoxHteEsZlsdoZ6ciOyR5PkqdkBXO44/vrqIDX1tzq8nz6+hNpvUTHCKpAv50yPUQOleJPbnWT1ZJRYO8mUS55NliW1JD7ZEkpoZ6nlJnke17gFCY4q/JH5vkMUmlOsvIMpjEhaTn89qAxS3UGyUjbXAWS5Us8tIaqBEbeN55hXPf/icBoP2xP4tME+lXEJSgXd9yyqe6Ji8du3v6PyT2hTkjR3obPfA/me+iIV2vGKbSfpHa85qJuSbxsvEz1FtFrpk8TfpTOYzaT/kGymXkKQFajP0zlSSVtvYB7ZtkpwA8wxxZhZnQJ8W6rwZler5if4JYnCMZR6Sd0PQPr/iQIfedVd4zytJ/XfiHGCB+D/Lc8Flq4X4S5JW7+N2ytkz+d+8gXr6lvvQQVM9kd5zSlwbyOIsqqeiL4f3/JLUvotzoCbJDdUG9jSpJf4o/Bd5jDHGGGOMMcYYY4wxxhhjjDHGGGOMeQb4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGOeAf6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmGfAJ/uQp5Ty26WUCv/vu9DnF0spv1FKeVNK2ZdS/lYp5U+XUpL/6K0xxhhjjDHGGGOMMcYYY4wxxhhjjDHPn+4Tz/9e0n8btN//cEMp5U9I+suSjpJ+XdIbSX9c0p+X9Acl/cpPb5nGGGOMMcYYY4wxxhhjjDHGGGOMMcb8dPnUH/K8q7X+lz/qR6WUa0l/QdIs6Y/UWv/Gh/Y/J+k3Jf1yKeVXa62/9k+ymLJI7XH5qL0Z+Jja7uPfP66t8jzUvpnD9qXvcazxMh5tWWEXlXjJErSX7YRjdX285rnhP/ZUm/hsljHuM1zTgqXVu7hPw13UwHYWOObhBd2YdPjWJn5QX2Gf7t0+bJ938aWdrvksF/hbVKsHlr9pHe9nXse/JxmTpHkLY614fjrnMsM8PL2GF/E8ww2fWf8Qt6/fxGONV7yA+98bty8rFsD2GI+3uuc1H78VC+3Vt+/C9tebE451GGN79nAAAZB0uo2fzVO85vE13z9RDrz/zZexoDen+CyHF3z+tY+fzQ9sZ+cxnqfsYvtX9/xH4jbfjc8f7fJTSI6/uY/tT7ffcp8Bprn6/9h7s5Bd1zS/6/9M7/iNa9pj166untKZNJ2gxoQkRJA4IIgRPHBAiRAxiBoViVFaEFFIDpIIRmJoQ+cgAQ/EiMlRkg7RINik1XSG7qquqt41rLXX8E3v/EwerLWbSq3rd1V9q3fV+hr+Pwg7fT/vPV33dV/T89S3YKIpb6acgJ+rkz8QSLahg3OBdkk63I/nrzY8fwHnP8Ix9+AWJGlo4nnILkrSACFIEW9FI/hSSer72/8hxn6ANY+xXKrEAdP8VZX4rFuak7FO/A8862asM2MJz2CaaodDabKi+bkP6VkLvvyQ+CxcW+Jn6RnZBUkYT4LKpDHbCHLevMOLHiAGKeEud4tEyeDRJLEz/SR+1h7Fv09SBvWz+CHGTJLao7gP6VLZ8vwUsxdFcmdIZyE3IVsmsf1r1jz//Gm85ukl5B+TJM+7jpVznHGi1azimK25AUOfmGXKM6dzPrTlLL6cy0ncPq04z9v3EDPSYUpa7+NnN6s4zui3HDM1L+Jn/Ty5NPCHegvYZr1hXSqG+Nk+8TN0Z/iiJ3eZcuDEZtP85Msol5SkDtLZMfHZdP+bG5g/iX/qLcyR7J9isJFiKVZ/rKd0HDKrghSsOrDMmg3Uk8A2DlM+tHISC7Q4sM0Yl7AhsPNjYv+RpE9/Gh9auY8PZ5gkSluBntXZPY/PpofYMIvzmnW85j45M4ozRqinYVwqaWzieerrZNFDrH8D1KbGJQet3Un8bIRzkdgGkJ2pVzxWt4j3cr3hNV8Osf7vn8Xt5xDLS9LkMj7/7MyqNfi5W/7+5URxc71N9B9sM9kyqhlKksCeUv1VEuYMV1eLsD3Lc+tnYP/6xP5exnej2Mc2szuL1yVJk1W8mdUHvObDKcTZtGQu86HPyvws2fMiqQFPruLFLR5DzJzUeZpncW2K9EKSdg/jjbYnFOcntQHy80luQvnk5AJ+n+k/iKZMCiC7+5BnQm2uS96njFC3zmqzY0NFEGhPclbB/OCWXz6jGIymyWpJ9CwJNGuoZ1Z1bDP2Fcv/UMWXs0pyI4qzMzuHY4Fv2iXvU3qoQVV7yn94/nZ5u5qJxLURqg1QLUli20h3KYPkMiQ+cwTbNDthQ380j5/1kLNWlJdK2sG7oQ7aJWkAgbY76AP2UkrepyR+vjjAM7A/WcZSQWzUX/L+qdZcJDaDclCKzQaysRLarKzP/n7c3kE9pToktYklPMi+gQDdxHfzyfcMIxz/4tnt7+we7NxY8aUtD8dhe9ElQUvw7I1y6U/X8MY9v7/8fkkPJf2FTz/ikaRxHHeS/uir//PfeRsLM8YYY4wxxhhjjDHGGGOMMcYYY4wx5rPgbf9FnmlRFP+qpM9JWkv6fyX9jXEcv/2zvN/76r9/JRjjb0jaSPoni6KYjuOYfKNujDHGGGOMMcYYY4wxxhhjjDHGGGPM3eRtf8jzrqSf/ra2LxdF8W+O4/gz39L2Y6/++wvfPsA4jl1RFF+W9BskfUHS38smLIriZ+HRr/vulmyMMcYYY4wxxhhjjDHGGGOMMcYYY8xnz9v8p7V+StI/pZcf8ywl/SZJ/4Okz0v6y0VR/CPf8tvTV/+9grE+bT/77JdpjDHGGGOMMcYYY4wxxhhjjDHGGGPM95639hd5xnH8L7+t6e9I+oNFUawk/WFJPynpX/wuhys+Hfa7mPe3hgO8/Es9P/FdzmeMMcYYY4wxxhhjjDHGGGOMMcYYY8xnytv8izzEn37139/1LW2f/sWdU8WcfNvvjDHGGGOMMcYYY4wxxhhjjDHGGGOM+TXFW/uLPAmfvPrv8lva/oGk3ybpRyX9deE3ewAAIABJREFU7Lf+uCiKWtIPSuok/dKvZuKxlLrF6982DYsB+3RtFbYfL3bYpyziPxx0vTsK2+HnL9c2idv7Kfdpj+MBxwrat6wm9dE+bC9LXvRuB4v7jn9PKZingwcFtEsa4yPTANss+PhV7ZOHQPsoPuf6Yhu2l90cxxqaZKPA4lkftjerWJjdDASm+L5IUjfnde1P4j6rz8FYJ/F6Jak9ipXm6Jd5/uYm7rO/F/c5nLJi1tu4T/OU5yc927zPulSdtmH7ft+E7Y/XMxxLj+P7V6/4u86zJ3F7swFZnvL+dw/jPh2cpSTtz2PZzJ/Ea5495b1s343bx5r1rGjj8Zqv8d0gukW8z8lVorOruH2Ijx/vpST194/D9rLl/ffzeM39adynaFiXh+4Nvh/uY9kUs3j+EX4vSdUqPjP0JZIKeFbCPNMXyVig5svHvIBuFh/09t3bO813Tm/C9mnF8x+GWGbzJrZLqwMEJpIKOJrFLI4lJOne8Tpsb/t4XZc3ic/cLsP28hq7aIQ1DxDKVAcei2Kzfpr4crgyZSx+lS3rxVDDXeq5D+ks3QtJKsE0UjxFcZkk7c9ANokpqTdxnwrUrLlh+VMINibzt3GYh/s/nLH8xzp+ViZ6RjEwxfkDXUyxLLOYfZhAPoFHyfOjbiTzH47j8Uhm5R4ukySVcGd2fADVVZwDZvE8QXlmu2I7e1jGgeaFFmH78ZJz1kdHcQCyaXkv601s6Po9+N8bzjPLFuSfpF/0rBhgrMz/Q2g0eZ7kRst4Af0RtI+szNMXkBstuU9FMROHeQjZ/3qV3Fl4RL4xWxfZWYp/0/FgL+QXpETPsvSb7FyiZ0MFZ0ayXLH9Ka8gaeiSBUxigY5NfDeL6vb5T3sW2x9J6ieQZw3gsya3n7+AsSSpAKWttrev89Beii7J83fx2RR9rMzlPqkzTOMz65dJbN7D2ihmqzkAap7HMXv/4UnYLkn9lM4Zfj9jWY4Qf+y3bDRG8A31Taxnk2vWpQb8P52LxDarAFue2axqB32SmJFqU2R/pxc8FtlZOktJmn8zlvMW5i+OOWbroW4/SXyW4G6Ob2DnVu9CzAb1d0kaSJ+hy1jw/RspZk38LOlGneh5vaODvn1tYpjFCjiCX5SkwxLsLIgys5lElpsOELe1lH8kacb0Ih6rWbMsqdZ+IDPbJfsH0zgesdKUE6gBUsqYuFKqDRYQ/0tSAfshmzk2yf2bvMH7nF2ss3jMW1amah/vP6szTK9ut+Z+yoNR3QjvuDiepfuXxexEs+FnJZ5//PtMljXMQzljBuU/WdLQPYiFVlV8xocu1qe6igWwazn+6GCsJDWVVvF4aGezmhG8Z9E0ewkLOntD74aSd5PnVOjk6Uu4s9mL+wHqeYLXds11suZ7sWyGWVIbgHd9VGfJjp/qfBkVlJrIz2Z3lup59fb2NquEGnjZJe8mH8Q1sPlXL7FPFBsV6SXLuYt/kee3v/rvt36U81df/ff3Bb//XZIWkv7PcRyTtMYYY4wxxhhjjDHGGGOMMcYYY4wxxpi7y1v5kKcoit9QFMW9oP0jSf/dq//zz3/Lo/9Z0jNJ/0pRFL/tW34/k/Rfvfo///vv0XKNMcYYY4wxxhhjjDHGGGOMMcYYY4z5nvO2/mmtf1nSf1oUxV+T9GVJN5J+SNI/p5d/XOp/l/THPv3xOI7XRVH823r5Qc9fL4riL0h6IelfkPRjr9r/4vd1B8YYY4wxxhhjjDHGGGOMMcYYY4wxxnyGvK0Pef6aXn6A81v08p/SWkq6lPQ3Jf20pJ8ex3/4Hwwbx/F/KYrid0v6zyT9S3r5wc8XJf2Hkv7kt//eGGOMMcYYY4wxxhhjjDHGGGOMMcaYX0u8lQ95xnH8GUk/8wb9/g9J/+xnvyJjjDHGGGOMMcYYY4wxxhhjjDHGGGPeLm/rL/LcWcru9T/sM9b8x34+fHgRti+bA/Z5sjoO25uTfdjeXlc4lsYybO7mvObuXhc/qIewuZr2ONZyFu9ztZ1iH8XTqL6J9zl9UeBQPUyT7b9Zx+NVsfhVb3AotYtY/uWer9ZYxfMXR/FmKlYlHWJV0uEokVkTy7mfxH36aTIW9sEu6mdxewlqKZ4eOZzys/15PGAJcp4/4QXQPKuP+M6Mc7gA0CxJ/VUTP4D5Z3NWms3DeD9Dy4c21nGf/WncXu/4/p1+MW5v1txn8yjW2W4R/36Y4FBSEc9TtPFdzvp0R/HPJxc81tHH8VhD4o3357AsUiU4L0kaJvFE23fhYiq5zz3cJfAlklTAPuuG78x+E+v/uAPfmNkMOMtUZ0CeYxAvSGzjJWmER/2Udaafx+3tcTx/PSdjKt3s441ej3z/j6axPTmd7ML2d+Y3ONbhOD6zb6zYaF+sYwFsV/Gay094L5Mr0FkWmeafxPo8NPFYbeJ/D8fg/xP7j74BTCaEhZKkbklj8ZrJN1YHttkUT5Vt3L76kOfvFvE82ZnRfvbn8Vj9jPdSgJ0bK+5THuI+zQ34zC3vvz0Cm9Vk8gc9B7mQjF9OBO3gfyU+Z1pXZrNJl/ppsuYC9g9uZgS/KEnFdSyAcc525vAovmgt3f8kzzo/X4XtJzMQjKQJbHTdxvb/Zsd7+dLjh2F7v06CFjoaujPJUZL9oTOW2DaQmctsJj2rYvcnSZpcxZ0OZ2RLeCwim5/2WXaQ/8J9laQBziaLWSlvpX0WrP7oG5v4Wrx6BosGuVAuI7GfGxP9I9vcQyonSQPUE2j+cpscWhWPNe5Y0MPTZ/FQDx/EYx0lDoCWteY1F22sHMMsbj+csQJW+9vFbBLXM8p5LMs6kSU9G2o2NN0iVo5uGbfXiSxHOP9yx32qi3U81iz2GSPUkiSp2Ma+aUhyI8ozB6qZZHke5KDDNjFaYBtnz+L2+XMOQPcP4pyF9FKSBKoxgi3plonTxEdJbgqiKUBlOshLpaSeus3WDDHzJdS5IZaRpAri6YKcmaQB7p/K28esFH9QLiFJ41HcidzMQHVBScUKZBlf8VdrgwdJbESQzX6TPvsz3ifFE9TeT26fM1WbJM6EuzF78Qb/SASYhi6pwRMUM9Xw/kOSykuosyXvwPpJ3Kc/TgI6oKDYdMsKSPvEckZW5h0gNi+Ts6T7DAugPUp8/8iWStLhKN7Q/EVsS2aP2QBs348L2lmdZwq5cTeL97k5SWIGCtmTMLfeQJwNd6Zsk5oN2Owe9iJJQxLPh79P7E8BMUtBgpH04Cg+zwby/+cbKgBKl9vYnw6bpDaS1S0D0jyX9pnU2UZ6BwJy3ryXzA/3fDhLchboM4ItkaSyiRfdgpxHemkiaaAaWFbOA9mU7e39TLeM95KNRbVWitnqxP+S/rVL7lNv4/bJMzDAic+oIM8bp0lstkkM+hvwBuGZMcYYY4wxxhhjjDHGGGOMMcYYY4wx5rPGH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzB/CHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxtwB/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxdwB/yGOMMcYYY4wxxhhjjDHGGGOMMcYYY8wdoH7bC7hLjIXUTYNvmyYt9umH+FuoWcV9jqb7sP35s+Owve4Knn8+3qpdkopmiB+UcZ/ZjPfyYLGO+9Qd9tnODmH7zck0bN8VRzhWcxPLZnLFMhsmcfv+LN7/UPNY04v4WT+rsE+3iHVmrGCsBodSCUczJp/olX28z8lVfGaHMzYT1SEeq7xg/aN9rg6xzA4PcCiND2Jd2i1Z/ouvxAKdwprXH/D87TncJd6+ypt4bc2H8V2SpH/0g6+H7T929IQnAn7++r2w/WcPn8c+G8UyK3roAGKRpLKNz79Z85lNX4BAi3is3cNE/6bx4oo9X5rjL8dr2z6K5zmQXkjqlvGaqx2vuTzEfUYQWbtI7N807tRPuU93Eh90fRLfv/tnKxxr3sRG69Dz+b/QMmzfbWPbVBz4LAewpyW7LKmIz6bo4VySyGpyCf7v83PsM/LRhHQ7XsCL3Un8IJHZxTQ+/68V98L2omb9Xyzj+KcukzvTxbpRT+NDGz/gsbbLOACovswyq+luQnvDplz7U/L/3Gd373b3f/qCFaaMxS8lOkZ3ZkhsRjHEstmfx33a0yRmBT9TDImdgzU3K7C/Wx6L7Dndf0mq9vGzbgn7zGIG8JnpmSX6dGtgHoq/Xy4gbh4pnn2D/ddb7kNx8+EY9O9shmNNL2N/VmzpMkntCcSzp/Hv64aCKWnexHauBL8kSQMc2tEkXnNT8fyLaeyznlexX5ak7hDb07EFP5PkLORPKxY/6xOobJKyo/+l/EvieKJex4Ptz/ks+2OwP4n9G6t4vHYSj9Xu+AAm15TnJmuG64S5+RvYMppDkoYmHpB8SRaz7SGezs5/ehG3l3zN0J9Tnq2Wg9bx6iZsL07jOpMkVbO4BjPewFgVO5miizc6NtxnXMRG+3AaH07m40rIDTM/Q/d8gJrF5p1YXpLUrCFn2rAC9JP4Dlb7+M5WV+wAu/NFPMcRFMAkDZNYzvXT67C9IBknUP1HkgbIzcdlrOcV2DJJ6veUHCdrhkdkZ7o528zZi9hnDjX3KeMuKrekF4n9h/inA7/wcqK4uaKLkfjfehvPg7mU2J/3c4ilF8lebnmXJak8xHezWO/i+R+wLZ1dxrq5fZQYLdDZEfJvzdmWUJ2pZ5Olagd5ZnLPJ9eQAz/fhO3Fnn1WfxrXQKp5UhuMTZNGUOZhwTajbON5kjAbofcGlBdL4jdyScxAdUPKc7M700/jZxXYJSmRJ71nSiCbNSZ2Du052LKszjLOYkGX0J5R1dDnKKmzvogdzXDFi6b3ORTn9EeJAXgDDkexoDuw2UMSZxekSivW2cMJ2Cw4/4ZL01hno1qSxHeG9pLVchuoZx7N2NHSO+jrXaxL6x3Hf911/KxMckPMpyj8rpM6H7zrrp+z0lAO2h/f/s4WW0o0kzon2DmqTUvSQO86IJ/vl4nPgtgwe58xTGKZUc0gm5/etWR6TvU8as/8D8XMZH8k/gagAVlOLpOzhJxt+x7XxqYXr+vz+LUyjacz/Bd5jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQP4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAP6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmDuAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD1G97AXeJYpSqdny9fcNi+vjr98P2r5X3eKLy9TkkaRyK+PcDDzVW0N5wp2ba8YDRWPFyJUn9EH8L1lQ99pnW8fy7NpZzB/KSpLGKZZaITP08Hm8AWbZHPH+3iOcfSxhMUtnH43XzWJb7U/7erjuK2+sNdtH+hJ40YWsZ3InvRDfjNbcgM5J/seexxjp+Vt2w/IdJ3H79Q9gFmbyI5++WLLPlD12F7f/05/4+9vlgehG2f7yL7czfu34Xx/qlp7HNmv0yCEbSyVfi/TTr+Kbt7vGZ7c/j9gPqpdTNYp2p9vHvZ0/Blko67GM7Q7ZUkg6ncfvkMp6neMHzd/O4vZ8ldq6In02uYH42vyq6+MzqHVvNah2fZ7+M2wtYryRNq9j+ky+RpLKM11Ydt/FYZRLa1PHa+o7PTLCdYQr2Z8vKtPoIFCCZvkzOM+Lk3hqfHc3iS3O9nWGfrov30zTxWR7DHJJ0PtuG7XXB+nfTTsP2j5+dhe39geVfwDlnPrOfxn1KCKWGN4is2yNWgOoQt5fQntmyegu2fJPZn3htu/uJnT2GZ9BMtlR6Q5tJY0HMNFY8Fp1nEuaqn8bjlS3FjEmcRaLJQjMwp91pvOjiwPKnmGl/nsgf9k80EEtJL3OziN0DHo/kWYzgy2Z8abpHcQBQHm5pmCUVYDP6nvf/+EUcHI19cmbbWGnrFxD/NMl5vbcLm6uKbTauDdqrHe+FXENmZ8s4NFAdbwXPRZJ6cI2ZnaW8uY9dWfo/q6J5hlmW6QIg/yzGOJyALUtkVoI9oXPJIPuT2T/SjZHOMgv/QP4Vh1mpbIg+TsE1HoHNug/OTFJ9Ey9uXMfxlyTpNB6vGOP24ewYh+rux0676PjQKDeZPY0DncMJCEzC+9RDzeDlAm7XntmfdhHPU+75zta7+BJS/LX5wTj+laQC6kzTZ8n5wzwq471Q/UWSNCdDl5DcwVtDfgZyWYltVnMT/75KzrLcx2dZbtkwFOAcyGZmERblDPWahby/T7XJuH327PY+e3LDMlu/GxvazDbfliIpaHfHsfwnF7ECZPp/AJud2YxiHuvGdBErANWyJKlv4/nr69vH2VlsQH36Y3C0ST19+07cp5uzAuzOoAZ7AvdsypsZGqhnJXF2DeaUYpZmhUPhha53LLOrL8Rrbk/iezYm+jccxzLLSmNlA3aO8unkMg8w0TDh/Tcb6gPTn3EAeu9+fM9nUOeSpIvVIu4zuX2gew010C0GwNL8KcQZcP/HiseiOtf2AduMHmrzSOa0YKh2eXsHAGk+5nKS1MVHmeaGFehzt4D3jB9AAirp0WlsHBqof0vSvo99Zg/vk/e7JGams8neQYOcqy28m4D2bB6qmUlSuY+f9dCe1vlANNU8eZ89g0ArYfucciPYJ7yzkLhu0yd2nmRQbeLDnD7lQgedf5f4eXo/RfXc7M42N7HMZs+T+UHPanifWUFeJiUx047tf3n1+ssGyn2/G/wXeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A9RvewF3iWKQqu3wWvuYSOnd9y7C9lndYZ+nN0dh+/rJMmyv9gWO1U/H+AF3UVm9vkdJqqB9MW1xrHcW12H7vOI+X13dC9vHMV50P4/XJUnQRWWXCAAoexqL+3SzeJ6xgHORRIczhW12sbq8mocecB/aZzuPBytgj5LUQZ+y5QU0m/jZ6VfjhbXHfAG3k/hbxOHRAfvsH8KDqyZsrlf8vWP7g7uw/Yfff4p9Pn/8PGwvE535f25+IGz/0tWDsP1rj89xrNkvzsL25Td4/uoQPxua+PxJLySpj8WsZoVdkP29eF3dKdsMYvFxhc/a43iew1ncXm15/9Pn8bPJDfdpwQaMsGQ6L0kam1ifqx33IXs6lnGfpmT5T6r4nh81N9ingT5PiuOwfb3lsywn8VhDx3amXMZOYKjjedpTthm7s1iW1R67aIA7M05i+e/20EFS28Vr3j5b8AKA/TyWy27H8x+OYjkfTVkA2zYeb+jjvYw7Pv96E59NDX5Jkob6do62SMwP2cYiiTPaWM0lOLJqy2ONZTz/AfRSkgT7yfZZwxp2sctSySGjCorN2M2rn0D7Ml50FrOVh1hnxiqxs6CC/Qz6JP+zimEGgk7mL2DNFBuSLXnZBZ4l84vk2cbr6ufJ/aO1YQAs1WuKTePfV3tQMkndcaxMxZDoDMXA0Pwj73+CY/3w8bOw/cWBbfYvXd0P21cPpmF727LNPFzFffpM/xq4Z3BnB55efaKbRNneLgek+ypx/FcMPMf8MfRZQJ5Lubyk8Sh2DkUi/+kyFnTfwf17PMexCor/EpmRb9jdv70saSzyC5LUxmkOkvkfJFHLeh8/XL/Dhv5wFrdTaLx7yJtcbOM6S/nsCvuMF/Ds9CRurxOn1VPOxLEh5ZM9tFdJnYHOpuySe1bE+9mfQM3mmgMgsv/Z/MUhHq9ex7FxP6PAkN3vMOU8p1rHNmOcQzCVMGa6QYAJKKC93ycGCHLTIYszIDZr1/E83Zz32DRxn6JjnSEfQDVQsssS5+yHc94/zVPu4n0eTnEozGe7GctsdgE24/j29VzSpTqpc/Tz+MyG8/ie0e8lqT2KF4CxrKTxEI83P1+H7T/4IK4lSlL7XjzWE3j/IEmrqzgGODzl+99DDXZyHdv55oYdbT+JZbY7Z50ZYGnlHmrDiVmieKY9yfxMvOZ6E/98f57oMk3zgrtQDFT0oH9NshfIzbI4Z6DUdB4vrIRaniSNcABDEud2EJuPNbxngLskSRX4jGdXfGc6yJtKGGvasP4fH8VFk8ubpJ4HdmasoGaRqN/0CvzP9A3sL9BxmqE6fp2Svk8aK4gZITReJ75kAJ2h+qvE9nwAX3p8DJuUdLmOhTOb3D45uVmBoLNUmmLmLJeGR/jePKlz0ixDkhvjWNCF3j9JUnE/Dlpmcy40HvbxRul9tiSNYBtFNbuE4pZ1jped4uYRfEMHd0xi/aeahSSN8N6EbHYJNXuJ69mZnndQg1m/F5/lCeRlL8cC+3/gPCuqppG9/m7wX+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g5Qv+0F3CXGUhqmxWvt9VWFfS5Xi7C9rnvss9tOwvZqFc9TtjiUysPr65WkYuQ1H5ZNPH89hO2PTlY41rxKFgc8mt+E7XUZz//3NrG8JGkc4mfDG3yiVnTQ3sYylqQCjnmYcJ+yHcP2EdZc7XAodXOYPz5iSVK9jdsXn8SbKfp4vZJUtvGZqeT9789is3P1UdzenvD8msbz1xM4TEntOtaZcojXPPl11zjW584veG3Az794L2xPdqmb3TRs327ido0s//Y4nmn9PveBa6YS7kYyvfpFPH9xxZ2Ofzk+57GKL013xPOPk3j+9ohPYPYsXlu7i9s72KMk7R7Ez0p2GapX8TxNbEpV73n+egU2O1HAoo/v5rCO25/PY78oSY8W8aLvT9fYZ9XGej7Cmpf3wMhJ2pI/acCWSRo28T6LSdynO0oOU7Fvpjv28mHcPBaxAA6rbDAgO3/ygX3saNodxx/XMNS9+Qb7/PjDJ/E89+N5nu9Z//7u43fD9sM3j7EPiFk1LTmRZT+D9uzIQGZkZ1veCsYs2Wf9FVyngq+MDifwIHN0AK25h/hHQpFp+jTWGYr/JGn7ATw8YQEUN2AzKGY8SRbQw24gZpekahnb+QHGGlZJ0AhnVsx4/hFsQLUGRUtiBlJ01GUJ9bkEMY9FErPv44nKjvd/OI3PfwQxHzV7HGsA4TzZ8kW/uIltIPnMquKLuXwQGzrKZSWpP8AB1JD/QLsk9TPKc7GLesrn3sD+kc1GYYrX/CYszmIDnKisjmaxPh26+F5ennM5aIC7XHS8gLGIBUpnVgzJYVL8k5wZlUAaiKX7Oc/P8yS1AeiUlGZUHuL2ehOvrVklPoOUY8p3tujJOcUHcLjPDnhobl+EGSrIJ6F9e8RzZLpBkG8gm3FY8iQV1Hn6RP71JpZztYS7mdifEWow1C5JRUuBFl3A5M42EP8k97y5hNyI8pnkjAfI87OYoV5Dng0l0MkNDzZM4sVVScxANmhcwjwQY0psZ7Lwu9rEa6Z7UXHIogGW1s1Z/ygHor0M8yRnB5998yHL7OHPQcw8i/tUWz5/ys3G5K0LxeyHLu70ZMWFru0+FuZ+m8T5lOYvszg31pn1O/Gaz67ByUlqwP4NV9hFh2Oyc9AhCxrL+FmX1AYpzjmcwRSJy6Y6X3uU2Gw6GuqSxPm0/2LGel438bN7p3E972zGtbkeDu3rs1Pss3uyDNvHabyudZKzNLCXEuQiScMhNk6bLjZAuwnfv6qCw0xqk/vzuJ3eDU6vE5vZQGxM+Y/4nmFtmst8aOczn0HvuvpZfGbkl6Q3uEuShkXcaQo16A7yL0maT2PbmIRsurqJY/AC7NywZwFUa4i/GtZ/klm9uaVdFr9Pykw2vWvppxBLzdmW0T2f1Gy0KQTOcnOymeSbi+fJO3A4mzGxWeQDsAad5VI0DdUsJZV7qEGSLJOxSDd2D7hPBSEIxWw9xPKSNLmMY7ZyzzpTrl4PnAvKsb4L/Bd5jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQP4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAP6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmDuAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD1G97AXeJshs1vWhffzBW2Gd3NY3HmvbYZ9jGYi8mY9g+VgWONX0ODwru0z+J1zw08fwvFgsc64vFw7B937FqlUU8z/rQxOvaJGpaxWOJt48UbfxdW9nefrBqB+uSJHhUHeIHBauSqn3cXnbcp1vE+7n+XCznIVaXl/PA/MXI++8n8fygFlp8g+XfXU7C9v39RP8exYv+4Mfjy3Q22+JYz7fx3fjmJ2fY5+gkHu/XP3yCfR7cX4ft6z7e/5euHuBYH+/iO7t4zDLru/gMykP8+/YEh1J3PMRzgF5Ikgq6m/HPZ0/ZZvfTWNGGWJSSpN2DuM/kIl7z8us81vZR3AeO8uWzWdw+ruL2EmyJxP6kPebzH0CcxTQ+y65j+V8d5mF7XcZjSVI/xuc/qWPjOIysSwPY+ekSlFlSD/vp1rHPKpL5yf6SLmdMn8Zn1v/IBvvMF7H9a1s+/wKMcwPynzbsgM7Bnp5O2c5OwKGV4ExJxySp3cf7rOGOSVJFdu4IzjLzv0sai/W/BPtb34Av5aEwNirAl2fjZfOQP6c4U2VyZynOSyA/M/xAfJgV6LIkVXD/hxdstMtDvJ8B4vwqyRlKsI3dge1sAX0K+N9vFAtW2hHmGcGWSlLzIu7TL8D/nvD8RQl94F5IUnER22YyzYcztn/TC8jNhsTPgj5T/HGx5zyL/Nnjq2Oe/5diQzO7tikaAAAgAElEQVSFmKUFuyRJm3ugm6eJ0+pAN8hmZOEf9Kl23Ili0xK2UrL7ke7FzWPN59/Nb2ebM5+xuYr92fKMF72FfJpipiz+2bXgHPvk0OjOQheyl5I0zG+fGxOHc3JM3KdZkdPkPn2SNyMwHsUZm0fsf05fxLrRnyYXPXsWUK/5/vczqCfUidBmsc1ob3mXpDeTfz+L56ESYLW/vf1veu5TwLNuGS8gy/NKGKvaJ5eG6jYDCHoS2xhJGuD8yy5ZM/jzEeI/siVpnxnPP8D5lxD/9NPkfwtL02ShLKy5bCDPbXh+elbtk5gJVGOA0CirWUwu4/ayvf2dody4SBSAzv+Q1KZKuBtDA/n/MqmZwNXIYpZ2F483PY7z+QcLzvOXpxdh+6Jmm71qY6N5deDk+KuL+2H78LV4rPaYbcbhKNZZiqUk6XACNmMZ77NIYrYRctNiw3kWlKYwAS6S+ze5idszO799N27vF2Czj/n8p/P4WVbPm83juLHtY8GsDuyYmyq+f3WSm4/z+Fk1iwPq2Yz3v16Bnj9L1ryNzxPr3Iku95BPV2u285SDdBAz1on9oXgqi6WonjO5un3MPMA2qZYkcd2e1kx5oSRNoJ62eY8DTaqbUJ2xfINa1pD4uaqO17Z7zjVQnAdqU5j/SJg3Ycyc6B/RJzEb5Y31Bu5lYn9byFm7Bd+/qooFkNXT25btaUSW55SbeG10lpI0LMBmHsW2cUzy/GEV+/MK1vVywLi52sZ96nX2PiUejM5f4niSYrbD6e3OS5KKJDacBHHu+HEpJTX4DP9FHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO4A/5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYO4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQP4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAPXbXsBdYiwL9dPqtfbZ0wL7rO7H7dN5i3320F5cxccxezriWBUMNkx5zfv78XjlIe5z/c1jHOu6Poof1AP20Qhr28fflRUd70UgmrFmmdWr189YkupNPM/0kqc//kYXtjc3Pfah7Zd9vObDEX9v183j9oKnx2cltLdK5A9LK1j9NbmO91nv4/b1e7z/7bvxomfvr7HPO6c38fxlrLNfuTjHsbou1qXf+SNfxD7/+OmXw/azaoN9vrx/GLb/b1/7jWH7k6/zmucfg515zndmsoplszuNz6Y9YZ0p2vhZveU+7Um8tvaUlJn3Mn3chO3zx9hF+/N4vB7uX3vEe5lcxWM1rLLqp3F7EZsfFSPvf/0BGQ2ev4DhiotYlodNfC8k6YvX74btX1my0ZgvYke33cSC6VbxuiSpaGOdPaw5HKpW4Jvmt/OlkjR/FvepwP5J0vYB3DNwzd2e5b8Cp1F9E5RMUgl6dpjFa14luvQCttkvk5ihgWcwTz2DBUsaLydxe/JZOz1rVuDLtjzW4ThedDPwAoaG7A/YkuQAyP8PfGXUxyLTyGqGsdnkKl7bmGUjk7jPIdGZcRpvtIe70W94AQWMldnMsYoFQLa0T+zPMIP5KZiU1B3i8UaYp9yx/pUUg9NmJNXruE+1j9v7TWKzSfw8vUqYp9rFv2+u2WaQLlcryuakvgE/C9zsE/sLG502vOb+h1Zh+7aNz38Av/hycaBLq+TSzuBu9vE8mc9sbuJnReIyiBKOrN6yMlFuNCQGoAY9I18yfcbyb9v4bmwvE5txFusG+cYxsSWYz5NdlDR0sdPAM0vUb/Y0fkhxucQ2o7lO9gk08VVK7f8c6jZZnLc7v52eVy2PNUxj3aifxfmvJA0nC3gQL2AoWP/6GQQHSW5C+6TaQLNJ/D/YjA3E0pLUwfapZjG5SfzfPl5bmZx/s4rv5tDEa+6nScxYxfsfau5TbWKjNTbxObfn7OOKId4nrUtKw5kQqn9KUgN1vh5yFonz6ckVtF8mhS6AzlKSyh3ERiD/+poDcMzZs3oqdKJYjnycxLlBVhvp5vGzFsrM1ZplSfE35bKSdDiLfdbk8gCTJPYXwtnDCdusAvzs1U1smC4uQDCSKhjr0b1r7DOrY+EcetazehI72v0p6MxD9hnNBuz8lmV2OIZ8BmLT4fT2d3ZM6ok9xFnlOpbZkITMFBsOdZbPx2sboWZSUy1F0kf3L8L2h3MKgKR7k7hwuYeNfn1zhmNd7GJ/QnU+SdIhFtoAfVZJnjPSM8plJJW7+JybC1oXz0/+h3LmNyHVP7jmJZi/l51gbXBlarjjEufmffI+k8IJyhmzmJ3q7PRuUJK6IvYZlM92R5wzFfcgzs5qgwc6NPB/SW2e4o86qSeSP83qqQTJPxsLXttxzSgz/108Eb3nk6QCYqau5T79NeTGEJsNk6zQBecMZylJBbxrH6AGRbU0Sarg/g/TxGbC3cDaQLJ96kM1c4n9KdmSLC8ZYawiyc0V5UbJz78T/os8xhhjjDHGGGOMMcYYY4wxxhhjjDHG3AH8IY8xxhhjjDHGGGOMMcYYY4wxxhhjjDF3AH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzB3AH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzB/CHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxtwB6re9gLtEMYyqtv1r7f0s6dQXYfP2Zsp9tlXYPNnFPx+reA5JGpox7sNd8NkwH+IHVTyHJKmDwYpkAW38/djscayO3Zznb27ieboj7lPtkrUFDA0/q3YwTyKyav+6jr18EK+rgJ9LUr2B6d/gE735s3ii402yAKBbxjouSetH8bPrj+JF7x6CXkoaZ/Gz7P595RIudBfPv3y0xrF+z0dfDNt/fPFN7NOO8f5/bv057PM3n3whbH/+dx6G7cdPWMfPf6EL22FZkqQBdPNwFrcPdXL/tnEfapckwaP2DH6fzN+TPbni+Zdfj9urQzzW5h0ei+x5ZmcWT2I972Zg/2aJASCTnVxzspnkfwqw8ZI0TmP9664n2OcGnhWHeF2TG56/AJ/V8DVXES9ZPci/hN9LUtHHZ1kkPmOASK07AtsIMYYkFYdYNgWbWdSN9M4CdP/Koxb7TEBnzo7AASZ8MsRr3u840GtWoGfX0CE5S9KNbsGdyDaQLAuISyVpehG3Z+dfwtHsyf5K+D8TKA9xe5vEbKTnI9gfSSrgDpRgM7IzG+a3D6jqDRnauLnv+c6OK3iWXD+y2di+57EonuyW3If0vIIrSzGGJLUnYDPoLCXV27h98TQ2Zs01KGbCOGWn3axjnZ1cxsZ813I6vmji8+8G1suhj5+NoOc12FhJGiaxzPpL9tkCPyNKMxNfQv7nTXzWZBULgHzsy4cwR2YWEnsSTpGIsgJbkk0x3sQbGq7j9rFMYvYW4px9VpuAseCa1Wseq1nBg6TQQfkM5cxZnaeHdHL2nGU2vYoVMIuzD8fgs8D/VtskN65i5exP2WgXLax5Hx9aVfIFaE9iBegTX0p3kPKsvuHzpxwok38DtoFsRj9NfNYiPkvaiyR1y3jNk8vYNmc5A8/Bhq68dxI/qEGWWZzb3j7PoWdk5zObQf6/S2IGzMEpZKyTsZJ4hmgobwU7R3ZBkibXcR+yZZKwbkuxIdY/JbXHVOfh6Zsb8M2TeKzdu8llJlG+SGoTdGbl7evcqOdvUJt9916caL67pARUqsv40pRJ1HB5mMdjJYHW8wpqsO/F7dOkzkbTHI5ZaBW8N6GaTfZqYgTZFAvWs5FybRAz1RIkvptjfCwvn1HaOImF2Uw4zj8M8WBfvHyAferyXjxPFcusTfLc1S4WwHzByWk/jY1g18XztFvO2ahmkNVTSqqNYWyc1Hng/Fs4S0kqoZ5Jdc6szk/+hHypJImekf1N7F97BGtO+pBv6hZxe3PDY9E89J5RkkrIjSif6iDEkqS+jQ9nhFw+g3Q5y/NI/4YkziWbTfX07N00upnEaNP5ky6P5MvF7xMOh9t/KjE+SRLKKdQzZ7Exqa54frrP6T2HfZL+Z/aPY2PWM/KZA8X/Ux5rcnH7eiatmWqWmSx7iE1nTyEwkTRG+VQWmHwH/Bd5jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQP4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAHfmQ56iKP61oijGV//vD8Bv/vmiKP56URRXRVGsiqL4v4qi+De+32s1xhhjjDHGGGOMMcYYY4wxxhhjjDHms+ZOfMhTFMUPSPpTkuhfQldRFH9I0l+S9Bsl/XlJf0bS+5L+p6Io/tj3Y53GGGOMMcYYY4wxxhhjjDHGGGOMMcZ8r3jrH/IURVFI+ilJzyX9afjN5yX9MUkvJP22cRz/3XEc/wNJv1nSlyT94aIofvv3ZcHGGGOMMcYYY4wxxhhjjDHGGGOMMcZ8D6jf9gIk/XuSfq+k3/PqvxH/lqSppP92HMevfNo4juNFURT/taQ/K+kPSvpbv+rVBJ82NTf88/YiFmF31vMUh/j7qWKEDgXPP1YwR8d96i0MCO3tUbIAYKxoM5LgUb2F9g3P38+gz5r7FHA09S5un1zxXqpdPFjZDthHQzzeWMVr7qc8VLeI+4zJkZHM1u/HulwMbCbqDTxIPhFsl3H70MTt0+c8WPPL8bMxmX/7biz/2Y9che0//vAJjrXvY9n8r49/M/b5+PlZPNZ6gn2q57FwJtfxQXcLHEqP/4nYaPQ8Pd7nYoj1vOxYASuwM5nNmj2DM3sa72V3n3V2BD3L7hnZpukV7L9lBaT7p8Rk9JNYZs0m7jS9ZGHWN4d4+gk4E0n1NlaobhmvqwAbJ0kjyKbcsMzKA+hMC7/vE/sPosnOvwB1qsBnzJ4nPgPWXPSJzOBohibxs8CwjH3WkNgMlfE85RT8X+L/Swh06oZjpvk01tnVLj60Sc36P5nGz/ZzvoB9F+smucbFDe9lLOPDrHZJnDOH9ibuU+1xKPSzhzM+s3oF9mfN8xB0z2bPeP/jRSyzDuQiSbt343Oefh7/8CeyXceLLp+w0aA7O7kEWwY2TmKbVbKaYWw2uY7PmfRCkvZnoGeUSyRQbIb5jzgH6BbcqYAcYHoVC22s2f/UV7GhHxYcNJVdvDa6y7s1BQbSBp4VH3OfBu7sDGKZJMzX7mFsG4tJYjPAnw913Id8qSQ1cGWHJGat15Bn3V5lNbmiOIf7VPvb5XlkLyTOWcs2sZk3t5uHYilJmlzH7bRHiXNTyk0ml8lYEGdmOUMBPhDtT3KW1GcA//uyz+3PuZ/FfSjOa48Sm7WLJyq7LNEA27iI/dzhHjvg3T2qJ/D05INI/6s2iTMhni7B/knS/gRqYHPS5ez8oZ1qJpKabbzmw2ksy8kVXwDaf7dgBeyPYoM6TKDOArZMkqoaZDbPcmPwmdPbxywq4vmzOJfuGeXzVz/I8R/VBppVUhsGG0z1hyLLc5PYkKC8geYfQcaS1KxiWU6TeurhmOLM+PcTyAskvn8US0hsz7s55Gx7FvL0eXxnV59nA0i56TefnobtV1uO/84XsdAeLfiFxnvz2NHvk+BwdRLbjG82saPPdJbiidNPODi5+NH4DpJtGLesM8X8DS7NHt7nQA2UbJzEddMszm3hXdNkEcvsB84vcawPl/Gzq5b17BefPwzbaZe7HRvtdhNvtFjxmZUg/x7qXJolAQg8GxOdHQ5gG+h9VpIzD6DmmZ+dXkAfcrNJnt1s4oeTm6Q2CfO8yXvDGubvp4mfg+MkX5bFjG/yPm36Im5vKWfZcvwzVBAz77gP2ZlhGgumvknuUlxmxXaJ6wbtUdxeJzVDijOy2gTFOdn7LIRy46Q4NYBykPwlqaLaCMSZ2ftsep80JLWZ5gp8Fi05e81AcdYNH9rhlN4bJvMAVE+oMp0lF0RxduIymjX4jCQ2Lg+B0o63f5fzK+O9cc/PgKIoflzSfyPpT4zj+DeSn376gc9fCZ795W/7jTHGGGOMMcYYY4wxxhhjjDHGGGOMMb/meGt/kacoilrST0v6ZUl/5Dv8/Mde/fcXvv3BOI7fLIpiLenDoigW45j9712koih+Fh79uu+wBmOMMcYYY4wxxhhjjDHGGGOMMcYYY75nvM1/Wuu/kPRbJP3OcRyTP3YrSfr070rG//bNy/blq9+lH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzF3krH/IURfGP6eVf4fnj4zj+rc9iyFf//Y7/yNg4jr8V1vSzkn7iM1iLMcYYY4wxxhhjjDHGGGOMMcYYY4wxt6b8fk/4Lf+k1i9I+s+/y26f/iWeU3h+8uq/17+KpRljjDHGGGOMMcYYY4wxxhhjjDHGGPPWeBt/kedI0o+++v/viqKIfvNniqL4M5L+xDiO/76kfyDpwat+/9Bf8CmK4j29/Ge1vjaO46/un9UaRlWb7rXmMZFSfzSE7dVxy33KeMDisgnbx1BEr5418cNuzn2Knp9FzJ7x9160tsMZjzdO4j+cdDiN2+s1C6CCf5Stn/H8Qyxm7Zbx/GPJ8x/O4rOcPdljn6KPdWYcYjlPr/kPTZWgZu0xr3mEPtWBOuBQTLxFSVJzE7dPr0D+if5f/3DcfnifNiM9fBR/7/dgsQ7bv7Gi7welx8/jZ/22wj7q4D5VLOjmo3ht+nzcZ7ee4Fjl0/hZtWdBl4d4zcXr5lKSNEx5L7t3oFPDfTYfxPM3V3H74jEOpWofz7N9wPvfvBe3b9+Jz3n2jOe///O7sL2bsc6s3o/tTD+FcxnYaTVXsW0qepY/+QxqrzqWZXMdry3TmaGOnw1x/KBx4LEqMChFYrP6WTxe2cZjZf7n6Jux/veTxM/ScVKXeeLk+3jN02+wzRhB/uU+7kO/l9j/7kHGkrSdw+EUt3dOxS6+Z9lQzU0ss9lFvK7ykNjybfysahM/DyaTSK6/duex0hxOwuaX403j9jJRs9kz0BnyGcmau3ks//15YrMW8eL2+1gBkzBD82VsMzdniZ+/ip+1JOdE/6ohXl0ZuxJJUg/XuT2Kx2qPeCyKweguS+wbusXtfi+xbSb7K/F+rj+KF336S4nP2IDN2HKeV3TxATTwPzfZgV2SpKKGnOGcDUN/BLHBAXQJ2iWpXsdjDYnN6o7BNkKc2UH+JUnDBNbM4le1i/vU+3hdPcwhSc2a/D/PT88GiHO7RZbox81zsLESx7OY5yUMYEvqpOIyex7LeQ95buZLKrJzichK0E2yZf3s9vLP2J9CzrJOAk2Yp4JywvwpK2DZxvMU+8xmwd04iQPafsYxK62tWfH823fiedoF6ExifyjOaZN7RnpOviSLGSk3zvp0oINDDTlLUpycPY0v+uyTJGigdS3jcxmT/ylo0YPPSOI8so1UM6wh/5f4LMcy8fPbWM4NlF8Wn7DRmr6IL+3Y8Jrb43ht7Vk8T7lLDgAOJ81zQWbky0jHJakCmWV1BtJzyk1S/YN9VkluRvakuY7vUneU5MwQzlUbXnTzbnzO753HQWMHvlSSnq/iQPvxC0702l18OScLttmHyzg5vPfz4P82LP8DxKzbB7eXM703GA4cZw9QG6GaiSQVYNApzspylh7y7Iz5N+B90qNYl672XJxat4/idSVF+KpMDEr0+6TOPc5igzI0bGf7bbz/6graX/D5T66hnsfqh7U5jv95LIpnszyD9H/6Ipbz7JLPi2Kj7B0o2WyKZWm9knD/zSqp88B2yM5sH7DNpNgsy03IB2HNLis0Ud08izNhbfU1CDrxmaSb8Mry5TyQA1LOQu9fJD7LSSY06EN1ti55z1BCzaC9YsM8ux+/hC7vcZzdNjAe+Jl+ypeGbAPVWSTWc6rBZO9gaayszwDxfAH6n72bpHcNaJckvE/tEuL/zP5AzjwkZzZWwTzJdwbfibfxIc9e0p+FZz8h6bdI+pt6+fHOpx/t/FVJv0PS79O3fcgj6Z/5lt8YY4wxxhhjjDHGGGOMMcYYY4wxxhjza5Lv+4c84zhuJf2B6FlRFD+plx/y/LlxHP/Hb3n0U5L+E0l/qCiKnxrH8Suvfn8u6Y+8+s2f/l6t2RhjjDHGGGOMMcYYY4wxxhhjjDHGmO81b+Mv8tyacRy/XBTFfyzpT0r6v4ui+IuSDpJ+v6QPJf3xcRy//S/1GGOMMcYYY4wxxhhjjDHGGGOMMcYY82uGXxMf8kjSOI5/qiiKr0j6jyT963r5L/39XUl/dBzHP/c212aMMcYYY4wxxhhjjDHGGGOMMcYYY8yvljv1Ic84jj8p6SeT539J0l/6fq3HGGOMMcYYY4wxxhhjjDHGGGOMMcaY7xd36kOet01x6FR9/Mlr7YeTY+xT3duH7c2kwz593Yftu3qMOwwTnv8AXRrsgs+6BcxfDDzYWMRd4i2+pI/79LDNsYB1iZdWwByS1M/i8apd3KdscSjcZ9GzzMpD3Gn73jxsv/iREsfqjmEvG+yi0y/Fa5tdZIcW00/jtdVb3v/2fhW2X38hHmv7IR9Acxrfv2nJOnOzmYXtl9eLsL07xOuVpOXJLmz/6IML7HPSxH3KRM+/fH0vbP/Gx/fjsda85tNfiPV8/oLPjPR8ew90k1VWYxmvrQVdlqRxFi/g8JAMALu22dN4/8tv8Pz7e3Gf9Qfx/Pt7if59PjZ0ZH8kaXIVP6vX8e/HKrF/y9gBdDPWGcF2mpt4nvaI969Ez4lhGvcZJ7FeFDveC7gsleyyJehzOIF1lSx/ejYm4q9ik6H6Or5oLdjljKG5vZ+lNRcD77/oQWYU/0ia3tuG7SfLWDBVybbs6UUcz5Vfjf2vJFWxm1E3hfjniA+zh/irXbLMCJJ/FrP0U+iTxEwl7J/GkqSrH+Zn4Rwtz0/636wSPfs4trMUTmdh7u5DMhrZnYn7HM5jm1Vt+M5msiHobMg3ZTkDyiZZVkG5AdjZbp74f3DnmLNIqrewOMwZeKx+CT77BhRT0uE0XnR7Ev9+eR7bOEl67/Q6bO8G1pldF8/f9YmjAXrQ5SuImSVpXMfzD0W85nKfKBMcDeVyktRDPLU7j9vJxmTzD0kFZXoN9wxy9sNpYn/BnlMsI0k17KeL05838hnrDzKbDc+guVvc/vyxXVIFcVYP+8/GIj87wllKkgqqjfCdJRvcQjxPNkaSll+KbUb5jHPTcRPboPILH0IHDgCGJt7nMGX7Q35mehX7zDaJs8jPTK/4oA/HoDOwzSxmqA4Q5yZqPrmOByzGeKxDsv/9/ViZFl9PEp0hnn/6PDYmdMYZZc86O0woN4jX1U94fkwzkwPojuN5NuCz6qTOMn0BDxKdwRyMTGmX5JmwNJKxJI0gzuoQzzNwyoQ1iKHO7B/Upp7Ga746570MEBvsNnxmE8inxyreaJbnH85uXxvfrGJDs57EzvloComZpPfPYvt/DPVHSZpU8eI2Hb+D+Pvjo7jPe7H9IRsrScdfu32iQe8NqDa1e8QXcKR8bprU88EGkJnJzp/6JK+A1P1IXOz/iXceh+0/evT6O65P2UNA+3MX4P8lrXaxzm43cXu/T/KPQ3z/qhvu00Dc2p2Az4D8W5IO9+P5i7Q2ATYDzFxms8n+jxSzKqvBwvusju0vxcZtEptTbt7cxHuhdUlJbSqJs6k2R2NNIC+TpA3U4LJ6NtY6KWc85virqG6faPb3ssL165SXPBbVmbI4l2xTB6WBbs7nf9ucVZJqKJug/U3yPNp/D/GnJPVQN21XmdGG9znXt6/NkJ3J3sG1EANi/J3FjKSzGeBnu0Vsm7vkfULzPNbn/f3kzuJ7e9L/RJhFHOc0a9aZydXrd/YNpPgr3D4LM8YYY4wxxhhjjDHGGGOMMcYYY4wxxnzm+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A9RvewF3iWHeaPfrP3ytvVlxn/2+Cttn8wP26dq4j4a4uV+MOFbZFnGfCfcZ4NTHWR+2F/O4XZKqOl40zy4NILPhJl5YMfL3ZkUL7dkCYpFpmMad2iV0kNTN47Xt3pljn2bVxfMs4rFoXS8fxs31jrts3onnWb8ftxcwhyQVoBrDBHRc0u5evJ/uUXxnqlksL0nqdk3YXj6dYB+i/HATtv/uH/tF7PPbT78Utp+UW+zzjfY8bP+5m9dtz6dcrmN9mn4j3v/8CQ6lYojlP9Ss59t3Y904HMe/75assyPYn9kzvudjAfPfi5Xz8DDRmWWsm2PJ8zereD/Lr8d9tu/w/rvjeM39MdtZWvPJL4LN4Oun3b34bpQtr3n3EGzjabzmcs+yLG9iPSv4yKQh7lPd0FnyUPU2HqubJ2dG+9zGE5U936XDcdynm/GiO3AnJckssdnH78QBTfNuon89+Owx3ues4cM8m8e2cVpxn6NmH7bPqzgA6GFdL+eJ9/nVS/YZ9So2WrsH8TzDFQ6lbh73OZxwnzE285pc0hw81h78b3vM+t+s4JyfspwruGcD7IX8giQNcDRDzWvu4T6P78S6RLGsJFUQUGZ9xufxRqtNfM+z/e/vxzrbnrD8yWYOC1hzGufFY42J/IfJ7ex8ZrMJylkkqYOYoZ+DLUvin2ESH87QLLAP2fn9eSxoHkm62U/D9mcXEIBJGl7El6boQC+O2f4+fC82aB88BAMk6XEdr63bx7JsK74AHcQT1Z7PbPcg1s2G4o8kzSopz0zuTN9AnrOAu5TEbH18/DiWxPepn/E8BNlsyv+yPiX0SccC1aB2SWpPIM8hX3rFsqRzzs6M5tnd/+zObHfOC5gvIDeeJrnxvdOwuVhDQaFY4lDtMt5Me8Tz0x08HN0+zp9dxIe2O0tyk46MAPk/nr+EEuDyE1Z0qg2Rb6ob1qV6A7nxKcu/auM+5TZeVwm/l6R+evszGyfxeNUR1JUllbIAACAASURBVMwgxpGk+dfiwzm8w7XZEuKJrohlNkx4M4fzuE+95vNH2ZQQy2bxF/iMGvyfJPUzqg1Bh8Rnks9qj5P5odb5JjnDuIjlvHvE8598FcYqb++zN+/Huty8v8Y+v+ndx2H7DHLjL1/fw7E+eRYnlPfv8QuN42mcGx1D/i1J907iuukn53FEm9WGVh9QnIdd8Aw2H8UyKxZJoWkTK1SZ1KAHyI2qXbywrM5EdSO6F5L04YM4Bl/WsZ1b0cWUVEES+BvOvol9Pn/0Imy/OMRFiCtol6RtG1/0FyvOjrafxM+aS/A/66zOC7XBpJ7dLeEdWAV5Rhozx/PU6+QdFIhm9jweq+yT2jy8T6Q5JI5Ne8j/M5tN9zxRWXyf18/iBy2nzOjnqP4hSROo9e3j1zxYl5E4/ijO2QB2K4jz11DnOErijxbeASZBG5ZaQc2ml7z/9ihuz+xfAQtAvUx0qd6A/kNcKkmTCcSMSZ/iOla0ahfPT/UHSTpAPak/S/wc6XMFNmOa6Ay8zy/hfb4kjTCPTuKNlkmc223j+anOI0ntEcTTDdly1v+hjp9NrrM49/U+Y5LLfSf8F3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO4A/5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYO4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQPUb3sBd4lilMp2eK29Wyad2vhbqK6rsEvfx31mvzwJ26eXyfRHcXsxch96WOziNZfXrCbdso8fJJ+IFYcibK83cadqG//+5fyw0YEFUG/i8YYm7tMteKy+idunL0Aukspd/IzOrLnh/fezuP1wzGseYc2CLv0sGQvOueywiwZQp+oiflBtaMFS04FsEv1vf2wbtv/uL3wxbP8dp7/I8xfxWf7tzUfY52e++cNh+5PHZ9infhbLYH4d/36yYgG0i7j9+iO+tPtzsBmvm8uX81+xztL5NyvsgvpUHeI1788Tm3ESn9nND8NmJDVXsW2cPo9/f+//Y/kPTbzm9fvsM9qjeLzDafz7+QscStUh3ufQsMzIZvazeC9le/vz705Z/jpu47EGmOeKbUY/j2U51onRgGfUp9zzUChnFpmGODRA+1vM2P/QNNs9TCKOWaoqPrNDwbp8s5+G7Z8cIJiR1EI8tb0EB1hlAVBMuWf7RzEYyT87yxFEk/nMEa5GGV8LjAskjifoXkq8z3qbxVlx++EEbEmsFi+fwX7aJM4ZHsTCOT7exe0zvrSHPj60Z8+OsY8WcGi0ZLJlkgp4VvTcZyzBZ+8p/s7izHisgfYoiZKAsYB5MvsLcV4NMaMkVQdY1YFseXL/n8c6kzE0oNCwz82KL8DmJn427tnONut4PzXc//prbP+f7e+F7Yv3OGibTGIf1K55HgRklqR5qkBnSnCNY2KzO4iZsz4awGfuYS98lOpOSGeT+Uk2FH4kmyFb3iV+Bu8f+KzdwyxmpnUlNpPOHwSTyb+GNVeJWcj8KULpLJim/Rnv/+YH48LV6QY2I6kYqQgRb6a55rHaZWyzDkdsZ5tNPD/dmYzpZby27YMk0KCxrm6vM7PL2DdizCipW8YD1pvYaJWJXErI87o5L7rexvOQbyyCeumvjHUZX47hg8RoAAPUWasV74XsPNU5Jfan82/E7bOLrGYQ6197yrkp5QaCWC7NWSHOI7ssSRXk7WTLyJa/fBg3ky+RpGoXz0/1p2GaxZ8x2ZqndGfhXMYyib+z2AAYwDi8N7sK248bdkC/NIkPuoO4RJIuNvOwfdOwzl6u4j6zZ/E8iydJbfLoDXJDCiensQFoppxoH6CeOLSJoYfCfQt1xgJsmSSVLek5y4zOswcF/OLNQxxrdYgFfZPUhq5v4uC4hNpQXXNtiupM7T4JpuCetffIASTvc+aQsyZ2tgYf1EANPLO/pP8Zk9g0oG9qVmwzqZ67eYf1P4uBQxKTTfHU5Ib7wCsY9FkHfs2iAkwDvRuU+MxoXeWc7U9ZxsJpt2x/66PYodGrsWLH9ofqSSQXSYIloy/PYuYe7BzVvyX2s3hnk5DpcBZvZrbgS0spky75zOi9WXt8u/gjBXzZywFv1z5WyVgUm54nMqO6FdQ5+yu2/zXoWQnfGUjSBOJcejeEMYb4nlP79wL/RR5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAP6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmDuAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD1217AnWIYVW0OrzUX7TzpU4TNbVthl2bShe37d/qwffl1/t6qn8Xzj4e4XZIaWvNyjH+/4rHqbbzPfoZdNMJwQwPzX/P8xUDt3KebxfP0i3iwasPy392Pny2eYBfVL9Zhe/lBLLR+wmP103gvZcf7nzyHdW3isbol738ANa/22EVFPI3KQ/xg/QHvZfdhG7a/88EF9vnCaSyAh5ObsP2Lu3dwrL9/Ez/721/5AewzXsQH2qwSOTdx++pzsc6uvgBCljRWdADcR9QHmrtTtn8F2Kax4v3Pn8YTzZ7C7z/BobT+IHZ7+/tgTCS157FtHup4n5ObxP6u4r2c/wOef/UB2NnENhD1Ot5Lt0x8Vnw18MyK+FpKkg5n8f7HebwuSdI+XltxiOcvk/m7OczfsPwFj8g3VK+HEb9CvQU79y7rzACR2gjtZbKX7S42Jv3jBfapQZ87UJk+MSUrkv8DFtq4iTdarUn/kpgBJ8Eu6pIQMCLzf9ML8LO3nEOShibeTRGHmJKkEWxGvcv0L17zJtHZ6Yu4vT2COaY4FN6/Molz9TzW893XzsL26wdsf+qTWDfHln0WrW38/9l7k1jN0jy963nP9M3fd8eIyLGysuYe6HZ3g0UZ2gghZBDGEtiSl0jgBbAxyBsmwQJLIBYWSMgSsAIhtRGoWbUsY9qoZeP20EMV1eWaK6fIiBtxx28+M4vILCcVz/NW3eiqjov0/Dap/J/7zv/p/Z8T92o3q8ffiHOOuMxmxNtkW/7zsXllW95XuotcIcXWyJgV8dkyn48cfyfGqRa8kbpLAUByIzYt1+tPlDsTZ5Zk2mcnImmuG61/9TF3AiqfT8pIznLN22x7YcwA0iPuBIPKJYWOA0Ai/LmKi4C+GzbibprtdF8q/4mNP7gRcU4cWWz8VJxNLM7sj7m8GQtdEvd/AOjD7XwJoPdfkQofAwBB+YzIGK1Yp4yNL/DP2lQsAyLnvI/0N+HyrlD3L71nbSHiz1ArbVgKJez5+MWH17KvenFK5UkkN2mED872Yvwb3Vl5wOO/yr8BoBmI/RRNph/qoNUOuQLUY61oxYordJfyeeXryPqP+Pq7LFIbWnJ5UvJx6oUu9CUDnlAou3j2UOis2P+Yj1HPho90olMv+EDKz6eiZgUAnVj/C6GOLJL/tKLOqeICAGQ7EWeEz1K1DABohS3F8kyVz46eCL+w0b6sOuIKEKuzpXtuz72wv5BH+ir5sz7isytRUP2mqDM2nR5/kvEEdCzkAPClA164rlWhF8DX8IDKL4c8OEaWj+HFLZMGAJtX+R5kT3nS0LyixyhmfG+qlS605ZdcB+sFV+Z+qC9t7VQVVPWmKQs8LdZUflTopO29zSGVX21vX5xoKlGzVEUjAK2q512JAjiA+fu8TTXjP1/P9fm3E/EsUhtS741koIvWhrlc3iUB5BsRs0RtSPkyQMe5WJ1BLTPnr7lkjhujWtx+fJXLxO4sKp42kTnXc7X/4v4R8X+pqAHU6qUZgPaKF87CTMUy3Vf+Ibez4UUkZgk7U7qk7tIAkIoaZGzO6j6rUDkOAFTifWpV6TyjEzWYdK9jczMTBiWmpurcgM6nYnumvlsIop4Zy1nUHTyW56t3gNkF3+dYX+o+2YuaNRB5n6KWGdlKtf+F8MsAkJN3cLetl3wS/0YeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A2cuewF2iTwOqw+Fz8nyt2+wGLZUnSSfbNLXYdtUk8rlVUouuUt2mHfZUHvhSUB7ptQTxqM/4GDHyJV9oPY30dfthkO0ClXcDLo+upedtkAg5AGT8cLIt38zBtT7MphRryfXwas/SUsn1+nuhm33Es5QHfM7bz/Jx8le1Ab4231D5KBeGAeDd1SGV/84Hb1B5vY8s5rqg4lScCwB0Qp+6t3ayzWhU8bnVXDfKm+f92A/mds3Xk2/0nNM9lyd8WmgHsitUC77+8lQ4IADVIZ/b4Jwr4OG3dF/Tf8DtbH+k7Wz1Jt+zesbXsn5ddoVsy+c8e1/72fET/kz5+aTRNls8WlJ5ejiWbZJPc4eSCJ8Rs/9U6Ux5+++K+4Svs53o9WdLvmlhp89f6bny/y13C8/G3/GzHF5q+1M+M4jx66WeQCu25vCbevzdqYgzYv+ziC9ROtuUev/TuTiAORfH0oL2kjunybuR8YWeq/wnE/4SABrtmiX5lsvLAy5X8wKAYsXlnRgDgMxnVPoDAEEcgvKZMZ+h/ExaRWKWiMHDc/7zoyd6Aus3uG6kQv8BIBV5ZlILW46cWZeLnCGW54m51TP+49lW72VohP2P9PrV3aRYCp8ZsQs1fmzPlM+evccbpcIvA0Bf8I3uc+0z8h3fm+KKt2lPZFc4mAvjFP4vRtPyONt2Ov7udjyehEcj2ab/UBzogO9LErFlhbIxAIB4NLjm8hfxZTE/P7rgOWi54Ptc8LQMgM6n98e3X7/yi504FwDIxNWki/hsdTdUezm80OO3w9vfc9V9ptEqK+mFmat7EQC5//kmlp2ImCFsY/GOvudmG65/XaF9VhhxO09u+D27n+jNLK7EnXWmDy1f8b2pFur+pdfSFkJnMm0z8pxrcc8YaZ+ZiDajp7Eza6i8mQhDi1yZ1D2jS/X6s2tu6O2MO6Bsq9dST/k5K/sHgCByox78YIobvRaVM+5P9ARUbUbds5SNPeuLt4nlGUkjcgOR/6QbrQC5yLNybsoAtD9Vfl75ZQAYn6k6i56zus804s4g7+XQd1CV/wNAl6ugxcWxO4u6hE7HOmh8dvaUyhvhmP7e4zdlXzcrXs9JU61/Wcb1+XCia5PrPfcNqgYSi9n78e32HwDyNd/o/akYf6MnUHfinrHXcUblOUiFAsRStjVXqH4QeQcj5A/33Jg+WAkjA7ApRT078j7rcMEdimrTtJH3GeJush7oy+Eq5c/ytcilhC8FgNH3+P6ruyyg9TnhoVy+ZwOARpRgVV+Avhs0I1Ezv47UhkX+Vay0zw5ibvX09vc5tZcqLwN0Dq72OaLK2J+K2lQkz1I5Q7oX948rXZvd51z/wjCiNGI9xfe5XTRTvQFKl8rDSJ1H3E3UPXt0rscfXPO+qlkkzxPvOsojkTNF7mzZjh/0JokUp8T5x+oJ6h2EsvNYbUTpeT2/fZtmLHRZ7EuUSG1UrUfVINtC96X8fMzPqndQ6v4Z82XFUuxZpfWc3gG6F/iY4SP8G3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO4A/5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYO4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQNkL3sCd4nQA2ndPSevDiNt0p7Ku05/I9VdF1Q+fJJSeb55fk4/mNss8DFy2QT1jM8ZYi19rsdP1nzOxQWXA0Bo1AMuridivgDyDW/UjHUbRV+INrWYGIDRBd+bLtdt9q9MbzWvpNZr6eZ8nN2rrWzT56K/RMj1UoAm9pCTLioqP5ht+c+reQE4X06ovLwcyTah5XPuhf7nB3vZ1+ztNZW/Nl/KNkXCDWBVDWWbhzcLKq/OxlQ+/462v2LJ11mstc40Q+7Phle8TTPSelEueF+rt7TPrOfczqojLr/+nF7/9H0+zvy9yDm/y/fs6gtczyphlwBQc5XF6g29/uKGy8fnfP1txP+Ur3NdCq22M/WsGwj/O9R9tVM+52RW6/GFD2hLcc6N3kthfmgjc1bxNIgpKx8DANWMz62PfFZdrLh8J1xGbPwg/O/yn+VyABgO+UKnhZAPStnXIOUHMM70+IrLPTemG7UxAK6FzqRKlwAML7nOKj9Xc7cMAOgKEX8iobTiJit1JkTSn3TH5fUs0kYcZ76K2PmQLyjbCrmYVww1LwDYnXL58rP8LGX+BwAiNI4eR/JckTYrebbRw9ciz4/lxt2UP0s3XGlkXg6gEOlMHVHaUsRmpZxJqftSrkHtJQB0Ay7fH/FxcrEvANAccH/SDmPnL/JJ4cvrTq//eskdSnOh/VwQ9xa1Z+1Eb2Y6FwdwTxtgf84PIKn4vJQcALqB0BmdMiDb3c7P5httS6nSv0jO1Aj/14icqVro9feiUhO75wbhs/K12P+lHr8RapboK4Pc506YTJ/d/i4Zy5kUi++Ju4TwsYA+y7SM5Yy3j/PDc+GzKzFOxP8pmqkuDrVDrmh5weXJDb+zA0A74m26XB9aL/Qs2/GFlovbx9/omSkdFE3KuR5f1W0G4i4HAPsJ95mtyBnVXQYAsq0wzojNNAf8PtuM9DoVfcYHUmsBoGtQQt5FKtituhvF8pwtn3NxzX++T/VahmfcNjZv3q7+BwAQ97l0H9lL8aia3354FWfVHgPA9oFQtBfwWeqeHfOlKs4NriMTEFOux7fX5XbEx9mVvP4PAJuG2//roysq/+MP3pN9fXvML0CPbrQClHseGx7t9JyVb1SmrO6/ANALN6PuvwDQB5HnNiKWrrQvk+nMQOtMJ/LWUL+A/mdi0waRer6QX4jayPVW18arkjvUeqXPP1SinqXWEqnnK58VdpF6ntj/6pjvWRjqvazv3S7+PxtIxAzxDmxwpfVf+dlYnFN5vopNsXdT1ZSvJdYmiPu8rHPoMjsScTduxV0+hhp/L+pCgK7zxvIsCP1TsUnaBSDjfL+P5LkzPrlSvOfLL3Vfoye3v4M1otap3nN0qbbl6oDL25Hes2wl6olCz2K2pO6mxXXk3dRMvIM5jrzP2PCBsnMuj9W5VN1UnQug9Xx0Juw/tmfqfbKIy7Hx1bcJzTT2Ppvv2fihHj92B2RMzvQBDK65/eXL273PUPXCHwf/Rh5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuAP6QxxhjjDHGGGOMMcYYY4wxxhhjjDHGmDuAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gDZy57AnaLrkW6b58TtoJdN+op/C9XW+hupcMtpbe/f/nur5Pll/IC+6Kg81HxmgzOtJtUx72s/r2WbdJnyeYll9rnef/UtWtLqFp1YTp+IcSLbvz/iaxmf6fVDDJOWfC93p1pjyhPeBpH9Pz1ZyWeMvtfjpwkfv+1ur7ObfUHl+8cT2SZbivMfa53pFnxvDo/XVP7lV96RfX1h/JjK657rBQD8wfpVKv/G0/uyze6dGZUPrvn60ypiM+I4d8f6zOo5b7R5jRtTvowM3/O5Da60nmVbvp+NOOdS+CUAqGd8nO2DkWwzesrHyfZcnkTMf3zG2zRDvf5mwp81Ay4v1nr92aqi8j7XOtsnfJyEd4XATfkZLe8rzbTTHgx4QCsTrn/1Vk+gnvL973O9Z4mI813G+0pLfZbFkq9z/Wou21RzLk/3okGjx+87/qxvIvaf8r3JU76WTaX3fwP+7BJj3UbEhu0Nt9kg/AUAJBVff3kkm8jkJF8LX7bR/nf9Bh9f6SUAqHCSrYUt7WRXMjeqFpHxhZ6PzrTOZFshF3MbXujxmyGXq7gEAPWC62x/yJ1WJnwMALQ1P4B6IyYGIN3fMtOPhOxGhKb6QPssOYzIp7MbfZZK/9oikmcNxNyELnVFZL/EBLLIHjdDPk495W2GT7TRBLHM0Or1l0fcnzdT/vMx/9uIZyr/BYB8xdepcplmrO95m9eEAryuAhCA05LLHw2oWN3/ACBbi/gb0T9lT7XY/5j+TT94ATtLeX/jc+6Ai43egPVr/FmITEvpbD0TOauIizFS4eMBYHzGJ9dlfJzVmxFfLuYcK6akO/5wf8j3sjzQfbXinqHiLwCkIjfOIiZTHvL+gsiZYzaTr3k8y5diYgA6cQdoB0L+ikhMofU/cjWWbYon3JdUc31nU7rRRuy8Eym4kkdKI6jH/GG214c2POdns33A819VywIABD5+W0TivLjnKZ1RPgYA0HH7Lw94LePZ+KoGJ+5sEV1Sc8sjNhvdTzqIfrR+iweatNSbFlpxNkqXI7Vp5TPTiJ/Pb35yOWsm7kCDZSRnvBB9iTpLLP7thJ9XfhkAsg2PzSpm1ZNI/iX2sjnVSvvVc14bfGfIL6ejTBeacnHRe/tYbDKALEQK54KzLbfnR9fcZ9UTvf7pQ37OQz1lrF8TZzO/fc6QbPl59idaadKpuE/mfC/rSjuZZsn3LBXvbADgcsXr44en51T++ZMnsq9OJBSPN9pnlzVfz1rcjWPvxnrh//LIPSfbitrkUz6v8lDrn6onI43URob8nKt7vE07iAQZEbQGl5FET8RsCJXZH+j1q/gXi4tB5BkqZ6oO9F4m4h1kiLzPVLX2SqusJNuo/DvSRuxzOxL3bNUAQBB23m/0AWSPuc9opryv+kgvpk+5bozOtNNU+690RsVyAKjVPUe20DmA1OXIuwmVz5f3Igqo6lxClwFdz1C10dgGKDuLxjl1ZqKvmP4XSz7Q7n4kOYtdnBhqjwHU4h34vtLvU8aPVGdcXImaIQB0KVc0lTMCwOBS1MZeEP9GHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO4A/5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYO4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQP4Qx5jjDHGGGOMMcYYY4wxxhhjjDHGGGPuANnLnsCdIgR0RfqceHgeZJPmtY53lfSyTSee7R+IBo+en9PH5Csu73UTQIzfF/zHWyF/1kjIW71nam59xjsLte4raW43BgBkG95f6HijXg+PtORzTiquFwDQjm43TiHOGACaGW9Ud3rSq+2QyvdrcdD7mDJxQhX5RjDwPUt3os1Y7yU+vaXiN45vZJPPLZ5S+S/O3qPy02wp+7psplT+d64/I9t85cPXqHx/MZJtklvqRpfp868nok3EzuupsE3p5vT4XR4xKEG+FvIV76sZR9Y/45PevK71bPM6lxc3fJzJQ9kVBkI1R5etbLMDt8F2IBqI/QJAYxwA1LNcN1KI8+8GOv71Od/nvtM+I0tEnB3WVF4rXwagn/M2qPX43YAHmrAVvlzEMgDoCj6OimUA0Imj6VPhS0/3sq8g9rJ9PNbjP+b7uem5M2lHsfMXzyaRDdiIVFWsPzTa/gdXfP9DZHiVT9Qi/sbOMttwecxnK9+s9EL7ZSCphc5olUErVKM8jOi58PNq/fujSM4oTDN2ZoOnvFG35E6zGWuf0S2Ebx7q9SfCzag8rzyUXclwKm0JAISfbUWa0ey0/9/fF3eGyD0nETlgF/i8EuWXAbRi09JYnqnmJXRmf0/nX+1A3Rn0OJ1wWY3SmZjRivOPNcl2XN4OxZ1B5IUAkC95m/21tpn0sKTy5pAfQHau9U/F09jdrBE56/CpyBn18WP9Btez4iYS54Rq5jkPJsqXx/rKtrE8m8tjPlOR8qNEttXrv/k0n3Sv1hmxpWwn4qyYFwBpM9tX+ZzbiC+XZynuH4C2/zpyN1ExI61EnhPZs909bpv5RjcaPOX36WbOY2aXa/9bT1WhRzaRz6ojvhZRsgGg/XzMZ7YFP5vtvdvneYNroWcilgBAecSNo095m2Kp74z5sqLyesrrPwBQHvPxR4/5OM1Ql5DbAdeNNnb/F/l8MhDjT7UuB2G0daSNjLMt76ucawVUNtsJHQO0Pat6Wsz/18r8YuUXVWcSJbBqprvaH6ucTbdR9lwu+PrVHgPa/+YbbTOhEXUG0STmfwuRM3WFdhr3p7yg92TD64zvPD6WfXVbvgGjI5EYAgjCOQ4LnZtXDR8nvxY6q4eX55/oI5NnoHLGpLr9PTOLnFkn6lb7Rzyh7kcx/RP3jEjQynM+t03NY+aVugACmBU8oXow0S8hOuE0yinXCzUvANiU/Nky13Ou9nwc5TNDqc9/KGoGyv4BoJ6Le670P7evTTdjff6DSy6fnIk6a+TKvD+63VoAoBc1aGXnqcjlAW3nacRnqNpcLM9TqP1PIu8g1d1IBdpQRpJWUbNJFzpo1oHbTHajNkYPr+r2+1PdJlurpImLy8PIBMSZxfIctf/KZtUdCwBqHmYRIu9TseLGMX6kDU3WAA/4Bqj7b6wveS4AclWDPRF3FmEXAJBtxD0/5jNSoefiHXCIvINW70Biea6qtWe9uGdH/H8j6mlJq+eckdysD7d/L/qDsV64pTHGGGOMMcYYY4wxxhhjjDHGGGOMMeYnhj/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A7y0D3lCCP9lCOH/DCG8H0LYhRAuQwi/F0L4T0MI9A+/hhC+HEL4jY9+dhtCUNCIIAAAIABJREFU+GoI4S+GECJ/dNAYY4wxxhhjjDHGGGOMMcYYY4wxxpi7z8v8jTz/HoAJgP8DwH8N4H8G0AD4zwB8NYTwxid/OITwZwD8FoBfBfDrAP5bAAWAvwLg1/7IZm2MMcYYY4wxxhhjjDHGGGOMMcYYY8xPgewljj3v+37/w8IQwl8G8B8C+A8A/DsfyeYA/nsALYB/ru/7f/iR/D8B8JsA/mwI4c/3ff+H+qCnT4CueP7bpnag2+SDhspPF2vZZlfzbb/8cCEmpn/hUOi4PKllE4Saf7/VJz2VN0d8jQCQ3vC19CnvCwC6ScvnNeLy/iaXfWWb23+L1osmSp5Uuq98w9fJ9OhjsjU/nGYszFFvJZoRf5hkQjEA7NeFeMD1bPhYu4l6xscJTZBtmjlvk73NbeZn7z2Rff3q8bep/GeGD2WbcVJS+dNmTuW/t/2U7OurN69R+dfefVW2SR8Lh7LQdtZn/Jz3R0L/tMmgnfD9Typ9Zr14FFrxYKaVtrjR4yiGF7w/Na9cu1+MnnL5zWf1vOoj7pvK1/heVgttM/mKjzM6022Gl8KexZSboV5L6CIORdBMuLwTqqzO5dn4tz//7Z77rBD4WgZzbuMxqr02GuVPuw33mdlar3F/yNskjT6XdsjljbDlQc71FdB71u8j9i9SkE7E+U7EcgCA8hlKDiCZ8yCciXMJh3ovy2O+mOLbI9lGeWaVM0jDBFALW2qHes4qnqo8L5IyoprzvoqlbpNc8DbVgW4j8ywxN6XjANAWfG9ivmRwzeW7GZenpe6r2/HFdEOdZzUtb6NiZixnbyZCN4QtA0AQttGLeSWRnA0iZuRrneequ0l5wuVppn1GM+Ob064ilzMxtSCGSWp9ltlO5Vl6/fWEK3o75uMcH+ukZT587qoMABi8oXPGLBG5Scvnta70Xl6suNMKD4UzA9CKe2Y+4b68EfcPAGgK4ef3ev+7muvz7j7/eZWXAUDKtx/FSttfNeP9Kf8fCRky/6qnWmcTsX41jrILIOabIz5zcLucPYRIziq2uTzW69edcXEnYgyg428rrtIA0Iq7eb6M7JnoT51lttdzzrf8WbbRPiPUXAnSHW9TT3TQ7jKxZ5G7aZ8o5eB2PriJxIyRir+R+4/QQaX/qcgxAKARbdo84mfEHTzb3e7+BwDNVGx07PonntVzrphdGluL8Nmx++dtr4axtYgta+cRR5fzRq24f8bubMVK2FIZGR9caZT/k3khAIh6brQ2J3xWMxZDqBgDHU+29yN3o6nK8/nPp5E7a6pKAJEta4c8B1E+I+ZL6imf2zjX/vezM16c+sWDD6j80bF4ZwDgu0ueaJ+vdc62Ffl0melAl6Sibi/cTx7JmfYnwv9G0nx1nn0u8o8DXdBXd6Om1LW5XuS5ImQBlc5Z+7HYy0hB7Wi8o/JFwZPWs+1U9vXuxRGVlxt9/r3Y/3zI9TyL1Kb2Wz5OH9kz5RyDqBmlkXcjzau3r422NfcZ3VboTOQPiCSiBqHrTEArar2rN/g4o3O9/nbA+1L3D0D7ZhVmVF4MAJ1qFEnz1bsOlUvH9lLlX53wJQCwvacKCkIvY7VRQVtqnRkec/uv50IvL7UzzZbizh65G1cLURsR97/iOmbLXNyKvp6Nw+WqBl/c6OH3p7e3f5XnBB3mUUfq04xmfPt5Da4i7yCORWwUatZHvhSpF+odsG7TTfmmtQte5wsXOv5kojY7FDVrACiW4r3Riq9lexKpc4qjSWp9Zrt7z6+nj9wLfxQv7TfysI94PuJ/+ei/n/uE7M8COAXwax9/xPOJPv7jj/733/6JT9IYY4wxxhhjjDHGGGOMMcYYY4wxxpg/Il7mn9ZS/OmP/vvVT8j++Y/++9fJz/8WgC2AL4cQYt9tG2OMMcYYY4wxxhhjjDHGGGOMMcYYc2d5mX9aCwAQQvhLAKYAFgB+BcA/g2cf8fwXn/ixL3z032/9cPu+75sQwvcB/CyAtwH8ox8x3u+IR1+83cyNMcYYY4wxxhhjjDHGGGOMMcYYY4z5yfHSP+QB8JcAfPKv1v91AP9G3/ef/GOxH/8hWPXX7T6WH/yE52aMMcYYY4wxxhhjjDHGGGOMMcYYY8wfCS/9Q56+7x8AQAjhPoAv49lv4vm9EMK/0vf97/6Y3YSPu/sxxvtl2sGz39TzSz/meMYYY4wxxhhjjDHGGGOMMcYYY4wxxvxESV72BD6m7/uzvu9/HcC/COAYwP/4iccf/8adxXMNnzH/oZ8zxhhjjDHGGGOMMcYYY4wxxhhjjDHm/1e89N/I88P0ff9uCOHrAH4xhHDS9/05gG8C+BUAnwfwO5/8+RBCBuDTABoA3/vDjB3aHtm6fk5ezQeyTZG1VD7IGtnmajOi8nTJjyMtZVfI1+KXEIXA5QDSDf9+q1nwtcTohh2V9wWXAwBaPrd+w9efr/X3ZvWMr78d6V/OlFR8/CCWH2K/50k8K863skl9yM+/POTrryJ/MC6IbS6GWv+KnD+rm5Q3ONXj97ucy7X64Zc/9T6Vf/mQm+/PDB/Kvo7SNZXXvVgLgG+Ur1L53775HJX/9vtvyb7Ks7F8pojtjSI72VP5+E3uHOpWr7/r+ASqkp8lAHQr8UzoXzfSi6xn4kFkY6oZfza85PKkkl3949/f9kOMH+sm1Zbb5u7N5+MFAKSn/LwAoBX2dHNS6PHf5+OPH3MHlJURpyViQ8zPNULN92/yjQ5pxP8vuS6lIpYCwHzC93O1HfLxI4tpGhFPIuvvKmFPQmdfJGaU8xdwDKJJLnw8AAzFs6enfC8BIGT8PBcHPM7lkbN8MF1ReZHoOc9y7ufuDXhfm0bnbL9/8RqVPzrXbUZnImca8sOshY8FgHrB23TaZSNpeZuw5uPUE91XL7L+mM9UeVanQwbyFZ9bJ8Zvxtpo0lLYGXe/AID9scgNxZn1yY/8hZ7Pz2urc9Ok4XPOxJmVJxGfKQjKlwFIxB2kFXvW5Xr9QeTssTxbhvNM2MxK25+8M0RsRt1NqgVvtDvR1+HZe9z/pHvt59av8v5Uzj4ptAF+YfGEyjN1aQHQ9Vw3SmGA3Vj7rNWUn8074yPZ5ukH/OLS5eLOONb+X57/WK8/veDOqZny8btcrz9f3f7fPCn9rw6EL4uYfyauk+1Az1mtM9nztXTi55895OJ8pQ1QxYy+4HJVlwCAbCPOP3Is6p6v0oyYL1GoWPKswxfoT/jTIGJJl+nzD52K2XrT+gG3mWTPN210tpN97e/xfHL7KZ00NCJvkXUu6ENL6tsfgKyniH8imO0j8U9scxIpsxU3ImYPeWd9pM7XiDt4Wuk5Zxs+uWbM9znb6sW0Az7nmJ9TNtOLfDoTeSGgbTMMbl/nTLeiZjLVtpQK/UsqvQFKZ/r09nVeFX9CLMxG8jmG8ssAMHrC+yqPdJtM7HO+4T+fRuxPxcZqpn3G7Pu8zlAec18WzRnEnPeV9n8fbHnO9OnJBZW/ObqUfd0fLKn84kBfDtW9eVnr2sCj1ZzKVxUfJ3LNRyrKZurOCOj7rIyZdSTQi8JNGrkbtSLOJnuR572iX+h0Is+NFZRORrwG/uqIB63jgVBMAI+G/Cwf5urf0Gu6Fyh0ZwVXjmbF35kAQCreD2UbXk/dv6oVMJ3zO1ivzgXAaMLbtOIdTDnQdd5WjJNeaQOoJ2JuIpaENpZni5zxvmyCTlzb8xsRs4WPB3T8K48i9ifivMz/IzUjqLrdC+QsED5jNNH2n4q6+fpav2faX4j3yTPxbuJIj19nQjeD9pnKNancIPY+W+UmSSTPUzVwRatdiayBhToS51U9L6KzyjYbkX+lIpYAQCfu07t7kbuJcCcqz42+G1E1mIj/T0WtR+X5sfWrElin3az0mUE4oFidQW1N7P5Zzp/vsE9e4P3Px2O9cMufLh+/af/4iH7zo//+KfKzvwpgDOD/7vs+4iKMMcYYY4wxxhhjjDHGGGOMMcYYY4y5u7yUD3lCCF8MITwg8iSE8JcB3MOzD3OuPnr0vwI4B/DnQwi/8omfHwL4zz/637/6U562McYYY4wxxhhjjDHGGGOMMcYYY4wxPzVe1p/W+lMA/qsQwm8B+C6ACwD3AfxJAG8DeAzgL3z8w33fL0MIfwHPPuj5v0IIvwbgEsC/CuALH8n/2h/pCowxxhhjjDHGGGOMMcYYY4wxxhhjjPkJ8rI+5PmbAP47AH8CwC8AOACwAfAtAP8TgP+m7/v/zx9/7fv+fw8h/EkA/xGAfx3AEMB3APz7H/38C/xFcmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4GL+VDnr7vvwbg332Bdn8HwL/8k5+RMcYYY4wxxhhjjDHGGGOMMcYYY4wxL5eX9Rt57iR9lqA8Gjwn7wr9y37Gg5rKy0Zv7X5bUHmxDlQ+uNbj98nt5ACQbfk4XcEb9WlkfLE3YdjqCaxzKk6XfPxm1um+Wr6WEGnS5XzOacf7Qi/kANKaDxR2lWwTDoZUXi7E+seRXzYlpnZ/sZJN3pxdUvkXJ2e8r/xGjy9IIwfwanZF5ZOkpPKLdir7+purn6Py725PZZuvX92n8icXcyrvqlT2hQFf5+hwJ5uczDZU/vr0WraZZFyfzvYzKv/6wweyL7WecMXtEgCGV1w3U35k6CNbVi24PjdHjWxTL/g+1wfczw7O9QTGj/n4ETPH+DGXh5bv2e5V7YD7obCNoO28OuDPchEzsr3ua3fv+RgHAOle22w94f0lOffzXR1RAOF/YxQpH2dY8Pi7Wo90XyJmA1r/2kdjKlextIjE7LTiz/ZHkaCN2+3ZbsvPGADefJX7mTc/z/0yABQJ3/9Xhjw2HOfcxwHASa5jk6IWDuWm4edyXuqYsdyLvYlssbK/Tqh5LGdsp9zO+kzbXyvynJqHLKQ7rUvpjvcVyxlVDpKW2mkGkQKKI5O5DAC0Yj+7md7nbsCfDe5vqXwx0TF7V3E/v3zE4y8AYM2VozoU5x/Js5O9yM0T3SaIeJIM+ME049tfB/tD5UsBiLklQt4LHQeAcMHvTElk+E6EgFboRVvo8asFP/9YnqPyiWQvbLnTBvjB9oDKv/P0RLZR90yIe04+0pt5/4D77MOhtpn9fa5Pq4sJbxCx/1Dyje7HkZg94XaWX/J9bvm1DACwu8d1pp5GnKZYj/KLMf/bCdNU+QcAhEbcJ0Uu14u7DAAkK77/nb4yIBGxoRnxcWIxM6xEnruJKQ0Xq/UruwR0ap5WkfFvn+bLPeuEKZcLPX6242c2iuT56WOeA3ZHPM7F7kxdLtaiU1NJIsy8jfTVDF+gNiTsLBf3KZXLP+tL1ZP0+PVU3M3FnPN1xP+pel6iDy0R9aziOlLPE6jzj6J8psiNlC0DQCJss99HgnbB199MxfijSM5Q8/1PInfjLhO+eSRytljOWN3O/wPan6l5qVoOoGNTxtPvKCrPiuV/+ZafZVpH6iyHwqGIY55+qCewvc+d9iDXNntV8svRByue/w0z3ZdiPtjLZ2NRZ1RyAMhEbaYVMWt/cvs7o6ozAkAv8ykR52/0PSfc13ujSIXPaGd8YrFb1nDM93m30YHuYs/z6XvDNZUfFbo2o+o5f/zoHdlmlvI9a4XRrCOJ9tOK5xnfPLkn23zvHf6sT/lOJ5HaSL8Vc4uEso3w5yEVQfsmkjSLHDxE7sZQ7wBFk1jOpOxPjfFsoNu1if3tFJXnqTo3AOTibiBLkNH8i8urhW6TiToPxJ2pmWhfqt4nD050zfTqhtt//4QfdCvuX4B+b1sfyiZI1/ygs1rd/3Rf6vxVXg4A7ZAfaCbqnGoMAMjFWmKo3Ch2n1V1U5nPvEAqreqfANCLOasihLqXAkCnSu3K/wHoRG7ct0IeeQeuzlNbGWQNrBX5fLaN1PNF3XB7qvN8em/8Q/xRqdtrrTHGGGOMMcYYY4wxxhhjjDHGGGOMMeYnjj/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO0D2sidwp+h7JHX/nDgtg2yyLXMq31VcDgBZ0VL5/vWaykOn+xqdPT9fAEj3XA4AWc7XU8/4z3fTTvYVxFqSTI/fTRoqb8aiQaW/N0v3KZ9Xo89M0Uz4OrOgx+8yPk43G8o26bKi8rYY8b4Kvf+KaVHKZz8/e0jlp9mKymfJXvZ1mi2pPIWe86rj6/x7289S+W9ff1r29fsfvEblzQUfAwDk1Bbc/t5646ns6leO3+NthueyzTDwcS7biWzzne09Kn+85kYb3tPrH665zgZuys+eCXNOhWr03CwBAEWvbFOHo+aQ+4zkgNvSfqwn0BXcnxY32mekOy6fvc+VqVhFNgD8WaNdBqoDfgDKZ4+1yiLf8INuRtrPKd1oV3wv053uq13wsxwUXA4AKpp0QpfGE+2zdtsBn1ej59wP+Tl3JT/Leqp1aXjNV6NsDNA5SJfxOYdE+99NXVD5k81UtslTrgDLmivt/SGPJQDwbnJE5SvRFwBcljw5uNxx+cWlXgue8vNPq5j982dqmZGUDe1O6MxMj19c8XOuDvk5q/kCQGjFs4gC9so0IqmJaqNiRrbVc66nfG6xOJMc8RxoMeHOfFLwWAIAhdD/zVzrbFfz9eRLvjFJ5J6h1tkX+szaijfqa3Ewo8hhpmKcSG6OnPfXK/1T84L2v4lYIwD0Ys7KNqWOA2hGwv4vdMzKprzDtOTy5U7rUt3yde633JcDQPKEPxtc8PHrhe7rYcH97PEXLmSb+7M1lVcVz/NqIQeAPhO6GdG/fszPpt2J/E/4WAAIYvhUX7OkO1W5VLXQfXU576yJXXOEb+gHfDFhH7tnc/3vI/f8dsSfZUthsy8QS/KN9pnlobB/4UtCq9cf882KbHs7OQAUN3zO7UCMH/FZWSl8Zqkvet1C5E09n1d5qn3WfiFqM5F7ZrHh48zf5XfmTtSyAGD1GvcnXaTqmYoUQM15f6gPoFjytYwu9QbsD0TMjl0nBfVY5Blt5KKR8M3JxJ0xNNpo8xU/s/1x5ABEdzJnUHkJgJan+UhE/g0AnfBn9YGoc35f9yX1PFbOk3m2qNnEciaV5sdcmdhO5X9j/xJY5VmyzgugGQv/J9xMzJckIv8eP9aznr/Lxy+uuWOoF/qil4u74Xig7xlfWpxR+ZOS++X3Vweyr03J87n3zw5lm0TYU4jcDbOcH0Ir6unp+7HanHwkkfo04vNKj3RtqFDvZvb6nFuRgyYi/4yRJHyfJzM956crrhujjPvfItFGU3X8bOaFHv9T40sqX6iiaYRMGPSi0H3NTzZUXotYmqbaAde1yFkiPlPdW1RtNIgzBoAgalCxPFs5+kSon5IDQJ+I8SNzluNw9YvWxhph/6pmBEDGrP2x+PHIWpT/idUG2kkkCBFGEf0rG65/ByO9AQcP+LumD4dzPsb3uBwAOlGbyMT9D9B7Uy34PrN37D/oS4WG21+/EFaqZn77vurIO3B1zxaveQDo3CSIPE++MoO+m4quPmrExd2Y63I3jHSmtiZyn4bQc1VnaCP73wsFrE4i99yCj19c8/Fjd/Zsd/va9PDq+bnF/PKPwr+RxxhjjDHGGGOMMcYYY4wxxhhjjDHGmDuAP+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7QPayJ3Cn6IHQ9c+J2+Hzsh9Qp1R8NN/KJveO11R+sRhT+YftieyruOZHmJaROSsCFydrvkYA6Ia8UT+tZZt8xJ/1YsrtFd8XAMg2/Fu00MomSBouLzOxARHqEW9THQ5lm2zDJ9ALa+wj00oq/vBqP5Jtfu/mTSq/rnibLOlkX/N8T+V5og/gbDej8scrLr86m8u+8nO+af2JOGQAxbyk8n/yjfeo/F84+rrs64vFIyqvoG3mK7tPUfnfvXxbtvn2xSmV777H9ybfaaUpllzeFrIJqgNunO2Aj5NUui+lGsOnes7tMqfy/QNu/+kxP2MA6D/DJ7epdDhMnvLNSWo+56j/FY/UuQBA0vJx1Jk1wi8DwO6Er1P5RQAYXPH+iiXvqx3ovtpDLn9tcSPbHBQ7Kn+aT6n80Y32Gc2K6xI6vWfJnuuZ0uVWu39JF8nGulTY34xP4CSSf9Qt901PPzyQbZIhV45HPW/zrYL7KwDoO76XbRP5rvyGn1mfCWOKmJ/YSuQ3kfMXttELN18s9QRqoWd9osdvpqI/pbOR9Svf3PDw+1EjLq6PdG7QzPjc8qVavx5e+ZNuovMM5TPPHgk9Fz8PAMNDnueEENnoOVeaKudKEyL+p8/5Picj7bTTjLepaxE0Er0WZf8hdmY7vs58wvP/OnIdTTbC/nWaJe8z6siyvV7/8IKvv8v1maUV7y8Trnm30wlYWfK9CZe6TRD6XC/4vF7knnF+rp3G5FXuaO4t+P33fDWRfWUZt/P1Ut9z+q3ITQ74WZap1r/JByL+62uu9GeNmHI0/quUZaD9rzp/dc/O1tqY01Lccxd6/H7Mz6wT+cfoTI+v9rKL2L+K2dmN8L+xlF2Mn3FVBgCMznmHlYiLANAWt4vnKQ9LAHQNJKkixZFM1FNq3ibd6/Mfn/MDyLf6nNX686W4s72u7V+d/+hSr7+cC91ob3f/BbQ952sds+uJyI1FMAuNVtp8y8+mmsb+/SZ/Nrjg92mlFwDQDV6gNqly41rMOY/0Ffj6Y3lmJvKppuEOuFpEcsYrPn5xo4sjfSoujiL/CxvtABPhs/vInnUFfza45JtW6Cs7yiPxIJJnVKdcn8JY5Z96LY2I/9lOBNMYQdVftDJ1IjXLI/XUt0dPqfyfmn2XyldH2v99c/uAyn//4nXZ5tHFgsqTVM+5bcUeqKt5xP4qPjy6mM6qvEnUE5qnes/SBzw5V/knAAwG4j4j3g1NRtr+O5GEpxGduTflSYiqmT3a6tpYJXKzszWvswHAHzzheqZQdxkASEVxptrrNp24GyqfcXiok7YH8xWVJ5GCSiMUenXAixa7SvsfdQfsn+iCoghz0s5i97xic/t6mrqbqHcG2TqSMwk7j9ZTlWmo+782JWTivUkTewc8FB02vK/5OJK0Cy7W+h3o4YTb+elsQ+VXn9MbsLrm4+TnuqCv/G8jLlTpXp9/vhL+L/I+qRIlCHX/ySLbvznhexOLP6puFyK1gXZ0u/fz2SZ2Z+TydBt7ny1qQ8JmY7/yJQzFRkeGV3Wr4krEbPGeDdA5a6gi9QQRZ3K1z7F6urjO5cqXAsiXzysH+/bkx8W/kccYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g7gD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4y5A/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY+4A/pDHGGOMMcYYY4wxxhhjjDHGGGOMMcaYO0D2sidwl0iaDsXZ6jl5NzyUbd46uabyt2cXsk3T8++nLnZj3qCTXSHb9fqhYHePt2kPGjF+kH2FouVN1rlsU6Vc7ULBF9rPxbwAlEO+l8lef6OWbfl6korLxXE9eyYsqB2msk245ZH1hW7QjPiePTo7kG3Us16cc3peyL7aBT+bUOlNSw4r/kBtTKv17+gXnlL5Zw/OZZt/+uC7VP7Lw3f4GOle9vW4nVD5P9y+Ldv8jSdfovJv/aPXZZv8ku/n5JLvTRfx7Ku3uM50E27LAICMn016xQeaPNTn34y4PGZn6giyFW/UNkPd2YMdFR8cbGSTclJS+dWU++zhQ+3/8jWXh5if3/L9D422DUUQx7w/0H01IjQ1Yz6vJKJKYc1947bWfmaa8/2vW97X5kJMGEDY8zb9VMcZ5RtrobNJrfeyHvFn6lwAoBuoiek2ikHG15mO9fq7C342Sv/qmY5/SIQvGUX2X8SMcM43phtqYwribFKuYgCAVuy/0v8QyZlGT3mb4kaPvxThRIXMtNTjJ2KbQ63HH95wRS+PI06r53NQ+Vd5qJW5E3lOeq0DXbblPrgd8nFi8acsuT9Jj7XS9Go56mgithxEPtul2s7SXDgUoTRhoM8yH3Cl6SJ63m25z1A+M6R6/G7M1xJUZ4DcT+Vni40eX/mzpNGHpmyzmYj9lz0BfcfXqfwiADSt2BuVT0dMWeXz+QcqMAHXBzzRuzflCVAi4gIAtGItI5GXAcDumtt/H0TOfKAd4LbjfeUi/wSAREwtFmcUnbgD9iIvB4B+KhS95HOO5Z9dzsdRfhkAIHID5f/reWQtMs/SwyvUOtW8okTcj7yCRIYRIVPm07m4FwDA/pD7rOFTPYHqmNts0og7Yxbpa8rHr2a6TTvkz66+wO/ZKi8DtJ/fnuqYqe7NY5GztfsXqL+d6Luhiln5TuQ/pba/5QMef5uJ3v9UrGdwyedcPNHxp5uL3DyPRjoqlbXBSG0oNNw4s2N+/3/WIe+vOBc1y8idrZqJmDXQ+tcLP5uPuKOrI+tPdyL/jdQTe3Fv2ot59ZH8M9tyeT3T46cr3l96IXzJUazQoB8phue80BRaYf8D7YCqOZeXomYBAGc1b3Q/55fDzxWPZV9vFbw2+ivT78s256/x8S8b7n8B4OvLB1T+++f80lrp0jS6VO1z5G6onom+kiPts45mvAaYRor2V1seM4dDbrM3V3ovRzOuf7OhThrfmPB3UP/E9AMqrxda/94rj6j8Gzf3ZZsPl1xn1jcil4jkrJ0w526jY2a6FknYitvmpYgLAHBd8LOJxZnDI36f6UUsSSK6lIo7cB25G6n7hMplBjeRvmrl5yM521jkJhtRm4/YsorFMxoiAAAgAElEQVSn6T5STxXxRN2ZslUsZ+Dydhqrcwm5uP+Mcn1pGWX82dVK17MfvntM5YND7ktGAz3+7IAH7dVnZBOkj0Xd/gXirzINdS8CgFy8tlF3gzIWf4TNJOLODOhacx9J85Vu6EH0I2X/sTzr1i+hY/4n55NrKx1n1Lt2NefYdFUNJl/qNvWUy9V7riymzGJymX5tjNWnni8OtH/wAgbzEf6NPMYYY4wxxhhjjDHGGGOMMcYYY4wxxtwB/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxdwB/yGOMMcYYY4wxxhhjjDHGGGOMMcYYY8wdwB/yGGOMMcYYY4wxxhhjjDHGGGOMMcYYcwfwhzzGGGOMMcYYY4wxxhhjjDHGGGOMMcbcAbKXPYG7RJ8lqO9Nn5PnV6ls03b8W6hdm8s27yyPqPzRd0+pfPqOHj/bd1S+P9LfaKVlT+Xdlo/Tp/znnz3j44RJo9vs+Dj5w4LPK6KlfcbnNrjQ6w98y1Ae8r6SWo+fllxeXFd6fLGd2UY8EPMFAOS8Tb+P6MyML6iteJv2WG9ASMT4Qg4ASdpS+enBmsp/7rOPZF9/bPoelX9u8Fi2OU62VF6J7xp/d/+67Os3Ln+eyv/u99+WbZobrufpLsg26Z4/2x/zfW4Hsiv5+WYi7B/QdhY6Pq/6eTf6j/tSpqmXj3bE5bN3ubwZa/vfr8dUfnWfnwsAFAtu6JNTrkvlTPv/8pIfTn6l5zw855szuObnklba/vINdyhdpsdv+JahG/G+0mvdVz/kbR5fz2Sb988O+fg119kw4D4GAHq1NWVkzgWfcxDGlHG1AAAMb3hf9VTbX1DLEX42S3TQ2NZaNxX9RExA+Iz8qQ7aKv5Vp9oB5DMeT4dv3fAxZE/AerfgbVrdav4u38/Vm/z8+8gEkkbZrG4zEL5B5UYqxwGAeiYOQLsMFCsxjnTmeg7TD4T/ySN9tcLOIjGzE7lRNxA5SyTPTbfinMuhbJM3fG5JKWLmQh9aJ3xmeq3trFb+bMRtud/ovqpr7jNU/AeAgYgB6YfcZ0i9BNCMhM2IvOjZ3Lh89ETE0nNtgEnF96w80eevfICS3z9ayr4+d/CUyo/yjWyjYkAj7qzLRiRZAL63Oqbyd8+4HACuL3gSmKVClyMxa/mY5wbpXJ9ZP+D95Zdcz2M+ux2rmK3nnAvfqO6TMsYDyFe8ryKSZ7XCz6XC/1QHkaAhTHP4SPuMbCe6UmlOJP6ovcnVnRnATuQT9Zyvs4/4kuEll6taSow6cjdTeePwStjyIHJnrMWdrdHnnFTCNve8ntOM9PmPzrmi1xN9z5LzEjlTJuovADB+zH3D1ef1AXQ5388+4fKY/sXqVoqkFevc3e5cACAVeX4QuRwADG+4odVzbrTNZC77yld8brG7abITeW7gmxkidzaVG/SHt//3q4nI5bKtXku258/qSeRuVPNxmkq0qfVasi3vqx1pn9GL8VWeF7T6yfwrVuca8jRH9pUvI/nvlO9/HtH//SnP55RfjNq4WOZyq3PGv/HeF6n8N9PPU/krM50z3h/yhb46vJZtEhGEu1hyJOhFDSY0us5x+H0+fjXT41dzbgPbN/jPt0LHAeAin1B5F7nnBPEoidTAb8vjS+1n35rz5GTfc+XMI4nmW8NzKj/JeW0eAM4XPM+/vM+LhutIArSquW28nx/INmUh+lP1nFie+Vj0FbHzyw2fW7K/fc6OQuTskZKdOs75Q3FnGWtdVs9idZZUxODimrcpxTsLIFKbjZxZtuHjdOJqqOIiAHRin9NNpDaschZRs1nutf6Ppjxn/sw9bpcA8G7Ga+O7D/iduYusv77Px09y7TPaV3gS3guf2VZ6L6sTkWdEarO5sKd8xdsML2RXyNe8r1aHbOwLkWdG3oErfVb1vFidq56LPGet2zQ8zCFd8vU3p/odcFOKdwCP9T1P5YCqBl4daAdQT9R7c73+6Qe3e29WLm5f5+5SPb66570o/o08xhhjjDHGGGOMMcYYY4wxxhhjjDHG3AH8IY8xxhhjjDHGGGOMMcYYY4wxxhhjjDF3AH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzB3AH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzB/CHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxtwBspc9gbtElwaUB/lz8ul7us3y5wZU/gEOZJvHl3MxAS5Oaj1+H4KQR9qIz7eSUjQSYwBAV4vOQi/bqN46oY3Dp3r8bC+eib0EgD7l8mbE+0r3uq/BsuF9TZ/Xox+ML6Y8WPE9y7b6e7u24Z2FB3rSo3FJ5a/cX1H58XAj+1rWQy4vuRwAfunkfSr/mfGHVH4vW8q+Nh23v/frY9nmd5u3qPw723tU/s3r+7KvR1fclsM7I9lmWPEz6zJtM+2IP6sPuaL3EftLDyoqz7JWtskyMY4YZr8rZF/dmttGfi0ME0BxLfYs5/LhRWT9Oy4fPdE2u3mDO6ftPb6XgwmXA0A44ROoIz6jHYr9FL4528qu0BZinyMxIxGq0de8USLkAJCs+fhlwm0ZAIKyjYr7xn6vfWa6u/33y8mNWI+YVsJdLACgGYiYHcnGgtj/dMX3Mk+1Lb8+5n7+j508lG0yMYFOJBO7VutyLdoMlJIBGKXanhjn5VQ++0rLx980Ii8D0I54m2rOFSDhaQEA4GYqdDaJ+CwRztWWtTr8yvxPxRgAKEWeNflQt6kWvE0p5Ivv6qRtf8AnXR7KJmhECO4PuS5N5jpnahpuZ/sLHecTEc/UWQZ1MADKE73Piun3uUPZ3ePz6opIzi6OprjRcw7CBoobPo7KvwFgcKVyJtlE+kyVf29e10YzecgderbVPqsrxJxFKJ8WOmhMhP+r1WUGQNvxs+nEBkwyPf6XFmdUPst1m+9cnFD5ruKxIUlilzYublc6ziDljdoBl6fq/guguOZ7OTzXbWoRglqR5rTDmP/n4+T6aoTuiLdpJnycLo/4GKFm3V63yS6E/1elkUhaNrgQTSJxVtVN8uXt8z/lMyIuG/Xk9vWEfM33U42Txfa/VH1FcvOSb2g7EHnmUudl7Yg752x3+zgzWPIHodV9NWM+5yyy/9I2hc/Ot3r84RWPDdlGK22X84NW61R7DMTPWZEKfUpqvv9Jo312uuXr3J1qn53txJx3/CyDqH8BOp9t9nrPkoKfWXvE5YNIzQJL4WdFXgDoGmy75nPOb/T4KjUYnUXqicNb+sYX+KfA1aG2mf09/qy4UkVrPY6qQTQT3WbzgG9aIWKG8vEAZD0lTbXNTAbcn54v+aTPn7wu+/qaGGc01TlbJ3LGYaFfQtStiA3n3M6LG9kVhpfczvKNPug+EeMLnakjd8ZyyQNAEP4HANJjvp99J+r5A+3/E1EDyHN9z3hvxRekavPvX+t3U6/MeUI5jeT5hShCNCJpySJ5/qLgtdHkWPuMmylfpxonNv7+Fe5na1EzAoDNjutMdTbm8iM9vvL/Kv8HgEzkIPtD8W4ods1Sr/MieXYqYnAnwny+irxPFGY2iPiMRlzbW1FnjdXGB9d8L9dvRu554j7Vi/un0hcAeCh86YMZr9kCwOsHfHMeC/+/fKpro8kN1//BpX6fo2qg3VDk7JF3A724g8baqNpA7J6lULaRRMrPqjaA68g7MFGDUDWrTLyzAnQ+o+ocgJ6zsvM+1zlzKnJ2JQe0PauaSWz/M/kOSrdR97ZsxxWgGd7+LjVY6ZjNiPnlH4V/I48xxhhjjDHGGGOMMcYYY4wxxhhjjDF3AH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzB3AH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzB/CHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxtwB/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wxd4DsZU/gThGAPg3PiauD52UfUwh52aayTXvDW+Vr/l1VPZNdId9wea+Hl8/yFR+/Ouh0Z4uay0Ovx99xtUuW/OebqR4+23F5l+s2QSwnMmWNaJPUes9Cxxt1A65nodaHmQTe5mC+lW1+6d77VP5zkw+p/H5+LfsqQkvlba+/ERwmlXzGeFwfyGe/vfwMlf8/F6/INtfrEZWXN0MqD2Xke0d1/hH9a+Z8zzBtZJvJgiv6zx4/pfLDQhgGgElWUnkuzhIAauE0yo7b8qYZyL6WNd/nR6u5bHNxyZ1A8oT70ul7+sxa4bQ75cwBDJ9wO2tv+DqrI60A3YArTT/U+98ecj+7Tvn+jz/U6x+fifEjMWNwyddfHvGfb0YR/3/E15IVkfU3Yj0D3ia90PufNHwtzSwS5zreprgWfU10V2kt9l+nGRBmhl7Id7Ve/73BisofFCIAAxin3GekwgG20IspRXDeRgzwpuE++7IayzaK4ymPjR8MdaKxuyfWI8RKXQEgtMI2IuffTHibUPNGaSTEtkORfyx0/NkN+YJ64X8AYHjJ5bMPuM1WM71p+ZbPuTzWm9a/sqfyT93nEzsdrWVf24br5reae7JNU/E4l5Tc0apcHgC6a743yi8A2p/3ufA/Y+1/e+Ezq0jOnG15m83r/Oebkfa/SSVy41jOLp41Yi1trnWpHQj9z7TOBmFOKjXeN9pnf+2K57MPz3Vu3ImY1bdcPppyHw8Anzq6ovK3pxeyzeGA+9mvPHmVyrd77f+nD7htrq95XACAsObGofxcV0XuLGe8LxGWAAAqnO5PuFzlhQBkbOg3WmfVPVfZxeBcJ4BybpEpt9z9yX1pI3up+ooFzUTYn6oZlEd6MeWRiLNlJP6IR/laj1PPhG8qRP55o/sqVlwBkq2o2QDyn/Y1U26bfabX35FaGhD32SrOD8/4oalaCgBs3uRJeB3JzVUKKtfS6phVzbk9dbE9E+csbfZan2UqgnM1ieTmC5Wb8DbDJzrRVPofO38VG1vhf9T9C9DxN7nWSVN3qDaan3Mz1D5zf8AXM39P59mJuDh0YjNjd8bhOZfXkXpql/L1q1wuUuaTdZYopzwHaR/w/W9bPYFuyfOp6ff1+YtrLhJ1Z4vEnz7hbY7Gujb35dPvUfngFa4zV42+/76zPqby95cL2WZf8T1bLnVw7rZ8P1U5J9trB3D+83x8Hf8hfWM7Fg/mEZ+ZiZg51X7u3gHPTdUqHz/V+79Z8YUOx3r8D84OqfxmzvtqO20z33jvAZX3G20zQTmhCdfZkEbuecL/DIb6zDaibj+Y8D07meuL9sFQ26bidML72y64XlSRd4M3G25nzfe0025GYv/FMacR+1NKq+qMAFCL2DwUNeN8FakNi63pIndzlU+nomaQ7fT469dF/i1qZoCOje2Uy2djfc9uRDz74Fr7jNMZ179X5vyitRjxuhgAPL7iL5vLXscZtf7imh+mirEA0IrXRpmesnzXq/SijLzPV++aVf4JAPlS6HmknrcVryeVK6308cs7aCJqwwAw5K8NZW0iidxzh+f8WewdvEKtX9W/AUC9thyd6TkvP8XtLN1z+fBSj6/WWU11nKX1+Ugu/6Pwb+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmDuAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjLkD+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhj7gD+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxpg7gD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5g6QvewJ3CVCB6S77jn55rOtbHM0qKh8PtjLNuVrfNuvR1Mqz749kH0p+sjJ9mlP5c2E/3zQy0e/4gNlJ3r99T6l8upBTeXJUi8mX/Fv0bpcNkG+4vLQiAZB99Vl/GFS6k3rCr7+LuV9dYUevx0/r68AkKWRQxN8d39K5Wf1XLa5ny/5vCKb9qTi/X1rfY/KH64Xsq+La24z7dlItukzrv9BTLkf672cH22o/N5sLdu8Obmi8s+Mn8o2i2xL5VuhHI9LvWc71Wavz/mm5Pu5qXlfo5zbMgDMcu4bPn1wIdvcn3Kj/f7kiMqXwpcCQKj4QQ+f6O9aA1cZDC/4g/ETrf9twccpD7lfAIDyhNu5MrOY/1PP6qme8/6Er7PLhS2J6QJASPnD2XQn26QJH+dqOebzGuqYkV7zdfbqkKFjZi3MLFvrvewTMb4+frQjPn5f8L0sa73+76y4n//t7VuyTdNync3EWcZQfbWdtr/NludA7YYr8/iI+0sA6MQ4yT5i/yIEZHt+lpl2/0h5yoiGq/KzNqV+xhhcaV2++SyfczXTOhtGfAP2b+rzL0+5Qq8+Lfa/jiRaYjn1oUragNmUx5nrLY9l+0bbzFjEszTT629boRvCzSU6ZCLd8b7aA33Orcgb8yXvq2m1A1J+PhGxFABacW1pF+LMGt1XIe4ABU+lAABpJWKWOObxU61L3YDrbH6jD03m+cOIngtq4bO6x0PZRuW5g0txzqXu6xtf4oeZvKn1T+W5D2Y8l/vG9QPZ12jA93k4Fc4UQHXNY0NfCT8/0La8f5WPH3baZsaP+DiDS/7zQcRFAICYWrXQ+6/86eBK+JJImUHlM4k2GRnPhhs154hdiEfloW6SiJitTrmexfI/3qq41mem/G9snSo2yJx9rvsqRT4zqfWhBfEsH/AJ1DNdnOjFPSep9T43wjdu3uDKlJa6r9Dd/m6icvBK7HM71PavxskGkTi35o3UnaGe6JylE1OLXHOQlaKetOPGFNqIz7zPz6zN9fq7QtxzxFpiOVMmcqbNG7e/s8j8M+J/01LU8yLrT8V9Qv2b28FFxP55aSR6l1C60YnY0EdctvRlIi8BgCDu+Yq80L6sEXfz/Ym22WzDF1SI+5yq2QJAeV/cGRKtfyc5H+gXRu9S+WnK648AsD/i67xsdW3sYc0D6nkzk22+snydyv/+O29Ref1Y12brqaizzCOxWeRt6ZznhklEabta5NmRf/NeiXuTOuc+Mv5gxHWmrrSf/9QrvG56f8zz7FGqneZFyV8CPVzq2vD1DW/Tq/tvoevpfSd89pl4OQUg2Yl6qjjLhxda/yDqfGGg53xwyG1Q1bPG4p0hAExH3DlfvqrPv73i6xlc8rVMnui17ITP6CN+ORU1gGwrbHmi9T9Xd4NIPbs84v2pml2itx+N8D8qLwF0PUG9Nzoa6dqk8hnffsTfjQHAu0/5s3zBdWkx03X2ewc8/qyG2mesV7xuUF+KpEHYGACkW2HLx7e/56pcqtVlDrRDFX+0zbQjPucm8g6gPhT5tLQlHX9UPjW4jNxNxR6od+BtJM/dvM6fZRs9fiNcsMrzO3EuAIBW1SZ1nqfu5tUBlyfR2iQfP3bPYXfTWC79o/Bv5DHGGGOMMcYYY4wxxhhjjDHGGGOMMeYO4A95jDHGGGOMMcYYY4wxxhhjjDHGGGOMuQO8lA95QgjHIYR/K4Tw6yGE74QQdiGEmxDC3w4h/JshBDqvEMKXQwi/EUK4DCFsQwhfDSH8xRBC5I9SGGOMMcYYY4wxxhhjjDHGGGOMMcYYc/fRf3jxp8ufA/BXATwC8LcAvAfgPoB/DcD/AOBfCiH8ub7vf/CHxEIIfwbA/wZgD+CvAbgE8KcB/BUAf+KjPo0xxhhjjDHGmP+XvTeLtTS9zvPef97D2Wefqebq6pHdTVIcLJIaEUmRjcARYMWAFEQIkPjKF0YAQ3EMBIgtQAgcwHdGnAsH8EWEIBcSYCPyhRQ5sChLsmhTFCWKTYpNsofqYtd8pj3v/Y+5qGpZYb3vR51WU3UIvA8gtLj+s75xfWutb/1/nWOMMcYYY4wxxhhjjDHfkzytD3m+AeCnAfxa13Xte8Ioiv4nAL8P4Gfw6KOef/lYvg3gnwNoAPxE13V/8Fj+CwA+C+Bnoyj6ua7rfvkvdRbGGGOMMcYYY4wxxhhjjDHGGGOMMcZ8QDyVD3m6rvuskN+Louh/B/C/APgJPP6QB8DPArgA4P987yOexz+/jqLoHwL4TQB/B8Bf+EOeqCOyvH1S+Jgk5s928pXUuXRxRuV/hGtUPhvnsq16GvEHZB5/+kjsepM3/EFg/oo40TrxsKbydsEHFldijgAasTTZXI+t6XF5J/5AWxf4A3Rxwxd6cV10AqAT02nys+9lsuCDe3C0LXX+jXjWbvgCRKney07sWdBmaj7meMnlvUO9AdGQL07U04vWbnM7v3r1mMp/6MJN2dYnhreo/EbG2wKALOL2v2gLqfP1zVUq/+LkWSr//OsvyLZQ8fVUtgQAyZrbZlPwdVZnCQDaMZ9/Piylzu5oSeUXRguuoOQApmu+zpMLA6kT3+HnOZ3zdSlOZVNI1nzN+g+1Tj7hexMJlx1a/80OH3MUOrIj0VEizpl22UiFTtNq+9vu8Xg6S/lebmJ9/lU8icuz/6XRTvSjYiyg/X/Iz7O8BAC6Ht+Xa+OJbGuQ8nP29nJf6qxPuP3HS25oXaon04n9jwbcLwBA14pFEza7enek2xKxKTBkNFtcp0u4zeQn+gAI9482cGZjYZrJWvx8rSfTvy/ib51JnTbj7dX9QJzt8zVrxEI3AZ8hz0amndbsaHimtiJhywDQjcSmiVwGAPKliJkiNSzHei3TRWhxONWYr02rfJPy5dDnOeZXmUf9iCHHc77O+VSv5d5XuZ9bHWidzS4fQCquZum8km0h4W1lJ/qe9/AH9vgDEWh7qe5/T/jskxs6Z+m+wvP8TOyZuksBQH6Tx9k/aXleCgCr69yfjMXdeDzmOR4ATE75PNNCx4x2yG2muMcPQPc+/kJ3XOtzKe95Is0f3NPnT9ny5uDsSUO8Eeci4GMyYebrQP+NuINFwmeqHAcAUmEaoZxVofxfW+jGIuHMpC+FzhnKwF+0b3rCz4h6hrIlAEhKvqDlVV0bKG4e8QetyH8CKbOaSzkM3OdVbG7FXLYDd9YN11H+HwAiUc8ppqL/oT4z6sw2RaieJfZ/xfvvHWr/Vw/42lSBMau9GdzmixYv9Z29S3j+FbIZWYMTOXvTD+TZIv+KAj47PuIxS57/UM4uwnlxquN8suYNJquz39klAR3VT3HK7W+9f/Z7TsjPt0fcofXe5etSjQLxZ4/H/zSQSmeLwODYuE4CMaMv8o9En9k/nN6g8sNqi8pf7D2QbV1Ip1Tei7T9PZNx/z+MN1LnQU/ftRmlDj/IZ3xzlBwA2pQ7lM1H+TyLnvZZsajnLGa6nn8y4X6uFRfa6FAn2s0VbjP9gV7/l7YPqfzl4T0qz1TREEC7xddyuRsYs3DorSgCqp8HgFXD/e/t9Y7Uub/k9ne84HeGUJ1xcdqn8i5wzz894fuf97n9zcRdBgBi8Q4uyfSerS6K3CxSY9ZBq834ntVD7edaVTgT+xxr9yf7D6TMSMTRULnx6nIgZon8T73/AIDywtkCnToXAPChLe5/X3pZvxy4t+YO9eaE1x8mc27jANDU3DYa8W4QACLxrje9yHPGutRt1Zl4FigOtsI1zwthf4G9TEXOWI8C/YvaYNkLGG0hzvmE+9mAy0Y+E+/zdMiQeXYj6rmpyAsBoNrh+78R7/kBIBL7Ga/4XNR7FgDSnTXazNF/wNtbXRR1FlHKA4Bym+uE6jk1uRt30dlrvO9x9jdX333ei35/1gp+8vF/f4P8/O8AWAL4kSiKAmUNY4wxxhhjjDHGGGOMMcYYY4wxxhhjzi9P609rUaIoSgH8t4//55/9aOeVx//9xrfrdF1XR1H0NoCPAngBwNe+Qx9fFI9ePdtojTHGGGOMMcYYY4wxxhhjjDHGGGOM+eA4b7+R5x8D+D4Av9513b/+M/Lx4/+qvxfxnlz//j1jjDHGGGOMMcYYY4wxxhhjjDHGGGPOMefmN/JEUfR3AfwPAF4H8N+cVf3xf7/jH7jtuu5Tov8vAvj+M/ZrjDHGGGOMMcYYY4wxxhhjjDHGGGPMB8K5+I08URT9dwD+VwB/AuA/7bru+Nt+5L3fuDMGZ/vbfs4YY4wxxhhjjDHGGGOMMcYYY4wxxpjvKZ76b+SJoujnAfwTAF8B8Fe7rntAfuzrAD4N4GUAX/w2/RTA8wBqAG/9RcfTkU+buqVeppfHbLjAs71v/xbpP/LOeo/K12VG5c2wlW3Vw4TKk7VUQdvj7WU7ASVBNSmovFzzuQBAdJxTufqqLC51/3Ej+tBLJp/VQ/4LnSLRBwCsd/j6x7X+5VBdFFF5tuI6XcJ/HtB7GbLZqOQrHZe8n3yiv/dr+mLM4OsCAJFYmnqLz2X5ojaAnYM5lV/Znkqdj47vUvmnhjep/EP5fdnWKK6ofNZq+3+zukDlX11dlzqfP3qOyr/x7iUqz+/o/tVBS9bazqKay+uB2P9U23+04LZRNtyXAMDRzSHv55kVlV/a0/t/Y3zKHyg5gMMD3v+9420q3xzpuSQrvgH9+3r98wlfz1jsS2ApEbW8n6andVDwsxklAUcriIXOqLeROrMNjxmbBZf37mn/p2wzZP+deKR0QvFn8z7+AGiXifO04WfpUm8m2+on3Gf1C+1nN+WAytstboDJqV7/lm8Zolj7jDgTOcsWH/PmAR/vIyXeVhqImfWuiLMV3/82C9iSCI1pIP1SOusDLq/7OmYXwpesRV4CABD2PLin+2kT/qwVvqlN9P7nEz62alvrqBCsYlYoz0secqNVcRHgd4lHcjHmwPKvLwj7E34ZAOK1GIDwf11g/aNa2blUgUiNkM1V/NP9z27wA7DZ1TpNX6zZMe+/2taT6d1fUnm01Ic2tDaMnYLnMgAwTLif293i4wKA+Se5QTetOJdN4CzX/Fk3Fc4cwDsP+D33pcsPqfzaWP87nOWa91NttM8uxH12E/FEJ7+v2+odijvbLPBLgMV53uzwB3VfO4Ba5GbtUDutqCf2f8oNM9no/S/Hwv+OAvdcEWdLkX+qGAPoeBryv63YTjnmgP9TOWMnYhwAdGL960CekxwKP7cvfn4Zshk+tiYPnPNRn8tzvpjpUqSD+yQAACAASURBVG/AZpfr1KHUjF/nZSwtt/T84x5/Nnioz0y5xTtKShFLRrrOkc3FPUNfc3RbC95/stbrn0/52NbjQD0nF3E+F3XGjQjyAKoB76ccBepZudgb5ct6gTqTWJpspuevcsN6xPtPxRoDOp8st3WcUb6p2hbOUflSANn07DlbsuI6s+f5z3exdtp9cTeIxJ0JAFJRgxTpD7qA/2tTvjfZIlDnavn6Ly+I/CfwT6GTlK/NVqYdwIeG/H3CnQ3/N8xfOP6MbKsVRYtxrvNMNbZEFW0BTEqenDRzbufqLgsAtbDNwR3d//xZ8UCMua71AIZ9Pv/Blt6z1ZLnpnmPO6Dqsp5LXfGxzdY6aG4ucZ3DakTlb85F0QDAOOM5806m7xmqntQTF8AikLQpna1Ur/+1Hq/bVrvi3UzAlutnRP6lkkkAk4rb/9unPGlbZzr/ULZZCbsAgK7g8yl3uLwtAjmT8LNtL5AbF3w+Zc3XrDjSTlOYEhqelgIAKl6al+9AZf0FOjaqOjsAJBM+z2bMlU5XejIPii0q//j2banzkcEdKp+Muc94bXZNtvXH969S+TrS9/xa1E0rUU9IjvVZUu8g09A9R+RsjbDZkC2rY9YFfIas24n4H0KNORH1T0C/g21FLg/o3FTF5lDMTqciNwroqG8aWlGz6x3onKUVOfB6TzgGAIX4PCNbcHno3Vj7PtaM+pm/wK/Veaq/kSeKov8Rjz7i+RIe/SYensUCn338379Onv0YgAGAz3Vd9z6uyMYYY4wxxhhjjDHGGGOMMcYYY4wxxjx9ntqHPFEU/QKAf4xHv2Hnr3Zddxj48X8B4BDAz0VR9Ok/00YPwD96/D//2XdrrMYYY4wxxhhjjDHGGGOMMcYYY4wxxny3eSp/WiuKor8F4H8G0AD4XQB/N3ry1/rf7LrulwCg67ppFEV/G48+6Pm3URT9MoBjAD8N4JXH8l/5yxm9McYYY4wxxhhjjDHGGGOMMcYYY4wxHzxP5UMeAO/9xd0EwM+Ln/ltAL/03v/ouu5Xoyj6cQD/AMDPAOgBeAPA3wPwT7uuC/wRO2OMMcYYY4wxxhhjjDHGGGOMMcYYY843T+VDnq7rfhHAL74Pvd8D8FMf9HiMMcYYY4wxxhhjjDHGGGOMMcYYY4x52jyt38hzLmkTYDNOnpBH/VLqXMjnVH6QzaTOUTWk8ktjrnNrlcm20PW5ONYq6eTJOQJA3efm0DW6sWjN2+q6J/5U2n/sf8WfNX3xS5V0U2gK/UyRTXk/csh8igCAzZgrJRuts3WvofLVHu+ozfUvm+oS8Sz0+6lGFVeZcTvb7PPxApBr0/W0zvb+gsovjvhZ+vjObdnWx4bvUvkL+QOpcy3h/QzE/h+32gA+t3qeyr+0uCF1vvCQP7t3OJY6bcnHEC25vHpG+yzE3DjKKuA0GrE4Qpye6NDSDFs+rHngoIl+sq8PqPzugXYMs2f4sxs7p1Lnue1jKn9hfEjl8+u6/7uLbSq/t7Mndba/xs9mVPOf7wKRXfk/PPnnLb8jvSG3s9VMz3/Q4zplo/f/+PYO7/8en2hbaAfY5Fze9rhdAtrPRh0fc7rQaxmJbloxLgDAFvfZgy0eaG70ub0CwEAEpy/l16TO4sKKytXvQaxUXAIQCf/TF7YEAHnKDf0jB/epPL6u9/L2gtvSvd2R1ImXfHPamu9zta33v3fIn4VytpqneWiEnQuzBACUu1zeiX0BgHTOx9wG/Ix6Vg15PzE38UfPhJ+LS73OCTdZ2U89eB+/1DPgMpM1f1iIo7l4JpDnBfIpRTsSi1ZyQ4s2AQMUthFI8wFxBKsRb0tcix41VfDG2r4+56r/LuXzXO0HjLnjeUa8Lw4m9HnuMj6wFwY8lwCATw1vUvl/dSCMHEAecZtZdzyXeFBr//f66iqVf+n0utS5P9+i8uMVX8uDAb8XAMDWYM3bOuG+HADQ4wc9GXJ5FHBm8xt8zyKVFwNIRDhL+FSwOdDnv9rhe5kMxRkH0IhzXhzx4KDGBej7bBSoDTT9s8W5phfwf8KXpkupgoqbn8y/olrPpSv4+ndpIM8Rzzq9ZTJuq1iSBvZMmXM+0XlWtc/PZjUUjQVrM/yhiuUAEImEMhLLnC1CtRHe/+KiTo5aUWqLA3auKCZ8bKoPAKhEEWK9w8e83hFGDiCpeP9JIM9qxNhWl/h9rs31nVXGvzRgNEInEvcJlf8CQDZVubnOGZpddaHm4lqXbLC8Iup5WaA2IvIcbIuaXcBn1Q3vJ58GdERurmo20ebs91xV/w31v95X+y+bkjljKmrWADC7wce29S7vf7MTiP8pjxnjTDvtTwxuUflLPT7RMpCzHG14Qv32yb7UWaz4PTfL9P2jqkRtUtwnQnFe5Tnry1JF5vnYiNrMUM9luebzL8X9HwAKUbdIxf6HUK45ClxNalGffrDh+fzhSseMd2c8nz6Z8bwAAGJxN3w/8+/nfAVilQAAaFpuZ/viPnGxr9/N7WT8PrWX67uJenax4O8Z2kDSdFzydf7m8YHUWYh13mQ9Kg/dc0L3GYm4Z8QiNmx29V6qOlcoZsQinS3HIv8JxCz12nZ9IVAbFnEmH/NLk7JLAJhX3M//yeyK1HlhyJO2S9mUyj+ydVe2VYuk7WitizM37/N4Ui/4uJotvZbRqXg3HarNiXQmn4j4o94zA6gHfGzJKnDPVTlbgOQ4cAkgVNuB+cvutU4s6taqNhp6Bx21oq3AO3C1aY1Y/56ICwAQidhwOtK1uXJbvWvnP987Cr1POnttPCOhQZTr/lyc/XZqjDHGGGOMMcYYY4wxxhhjjDHGGGOM+cDxhzzGGGOMMcYYY4wxxhhjjDHGGGOMMcacA/whjzHGGGOMMcYYY4wxxhhjjDHGGGOMMecAf8hjjDHGGGOMMcYYY4wxxhhjjDHGGGPMOcAf8hhjjDHGGGOMMcYYY4wxxhhjjDHGGHMOSJ/2AM4TUQckZfeEvDcspc6m5Ut4u9yVOl85vUrledxQeVvr7602u0+OFwDyaSR1olY86IROo9vq+nzM4MMCALQZfxjVovuebixd8LEVR1qnGnGduOY6cannD/EorrRKuuQb0FxORB96LpHas75YTAAH+zMqf+mlQyp/ZnAi2xolayrPImEXAK7nx1T+XPaQ9xHr87dsMypfd1wOAN+s9qn8qNmi8i8tbsi2fvfei1R+/119/hXRSuw/AIhzlu7z9U8zvf6rkz7vfx34rlM8ilfc/ro44ADE0LKZPmdxJZ6Jbobf0mtZHfG9+erlkdTpHyyp/Ll9bsuX+vyMAUCe8AWor+oxnwyHVN4sePxJj3Vo76V8LQNHFvGUt9cMuWFEScD/NnyeZa3nn+9yO18nhdTRAxD+f6PtP1mc7ZvnptDzr3u8fxXLASDOeMwoN9zPKb8MAB/p3abyV168K3VyYRxlx/esDXwjHoPPJZGJiabqRP5Vaf/7/2y+j8p3hiupc+chP3+R8Mubi7IpbK6ffZ6x8OeRWOYm0EVb8T1LD3XMLPd4g5Hyy4DMjbpU5H8b3dbqEtcpjrTO/EWeA21f4b752tZCttW0fKEP59wuAGAx6VF5PcypPJQzIhdnptBOu5nyfiDWP9bTByK+zslGq8Q118lFaFxd1EarcvB4E4gZ4g6k1rmY6rVMNmL9N1onbsR5Enu5FVjMnSS0OZxexCeaiYtWnOr1X/eELe3o/mMRz75w9CyVTzf8vABALXKGbBwwQEEz4XNJQumvsL96J3D+xHpGSz6XZHX2f1fVnop9gc6Z1XWyGgVytm3Vh1RBJM4/RG5YHOr5qzEHc1YxNnFlRCdyLACyBiLKP4/aa8X6B/JMlTcm4p6180bA/jIx5iJwzxS0oq10qftP12fzvwCQVGL+a743vSNd51hc4XeDaqhzhs2OWDMx/607ev7KZpsiYOeiuXzB57/aDbR19jQTxZQrZXOR5+7onFHlf6HaYCTOWSdqI8VE76UMp4GUFerM5iL/7un9r0TMyOb6/HViO7uVuOefnv0sh1A2k8z5wEJnuRHhPNXXLKwvi3Ue8HOein0BgDThk9ls65hZ3OQ+Y7Mr4j8vpQEAOlWbDTCK+eK8kPHa7M6BzgtnDR/c0QVe5wSAuyVP6OaNrrO8NT+g8ps9fgefHes7U7Tg9hzv6DwvTbkNNKKeFAdqk+slt41O5TIAyg0/m63wJeWpXsuo4ucsv8jrjwDw9nSPyp/f5rXJvZ62GVWbDPHgkCeHbSHif2D9j1d8/Zt1INESdeujhtvfNwLHUr3Pygba0W0Nea0tEfPc6WsHOMp4W9s9bf+zhXC0wv5CFOJVz2Yv8D5R+Dl1/w7lzCo3D+UMmToaomYRujOIciLSpZ5/JY5znvOY9ewWP5cAUIYWR/Bb9z5E5YlIQC8OAu8mxDvofqrtv+jxZ7GIv1ng3dRy8D7q+TNuNI3wP6r+CEC+52pGgURHvJ9PTvVetrkYgxhbF3ifonLAkM2Wu3xv1PkLnZl6yNvq3w3kueKVrrpnLdc6Z0uEnal3kwCQLvl6Nupbh8BdKluIeqq4ywJAtfVkPyr3//Pg38hjjDHGGGOMMcYYY4wxxhhjjDHGGGPMOcAf8hhjjDHGGGOMMcYYY4wxxhhjjDHGGHMO8Ic8xhhjjDHGGGOMMcYYY4wxxhhjjDHGnAP8IY8xxhhjjDHGGGOMMcYYY4wxxhhjjDHnAH/IY4wxxhhjjDHGGGOMMcYYY4wxxhhjzDkgfdoDOFd0QLLpnhCXm0yqfHN2kcov9OZSp0hrKl/Vop82km3VOw2Vp0u9tcmKt8dHBURZK9vqSvEtWKPH3Gzx9tJpwhV092j6T+4XAKwPdP/ZjMuTNdeJS91/6Jmi3Obz7BLefzbT39s1OZdnFyup89z4mMqv9U+p/MP9O7Kty+mEynuR7j+LlKVx3qoO5LPfm32Iyn/33otSp6z5+q82fDE3C7HIADDj5ywO2H87EvOPuC0DAMSjasF9RlUXsqlkwe0p3ugxd8IE1ZA7cZQBIBamoc7fo2dn61/1Aegzm0+0zyzvbFP56xeHVP7NvY1sqz/gz7ousP7KNIRvrrd5XACAWsSG4kSqoO3xfuKYDyzNdP8rcZ7iRNu/bE/0r84LACQrbpwh+1Nbo+w8DbTVqKMZOP9pyuefiXW5tdmTbR2kUyrfSZZSR6H8fBLpoN0IZ7LudJ512gyo/G61S+WH1ZZsa69YUPmi0n6+2FvJZ4wqDaTWymSD558/6yolD3yjL+ys3tVxOSq4nXWBPFP5JpUbNo0OGnHNdZbXtZ2lY+7ot3rc/14b8vwHAOqWj61u9TpnCV+z05rrZEeBtVRrNtdnBjlfm2jB5xIFchZ1nNvAkBMRArMZt7/NXsBn5lynONLrr+J8MRH239Nt5VN+Ntr87P2n4ixVgaTpD1fPUfkXJ8/q/oWjeXe+Q+V7Pe3/rw54nv/y4J7UGYgFuD3k/Z9suI8HgGXJ7TwvtM8qS7GeImeotrUv6d/lbWUi/weAzX7g4kpIF4H8d8P7r7Z1zqDy+brHdUI5uzrL1SjQv8jB8xMRswL9p6Kcks11/22u7vNinQN1FkWk01x0wp+mov4CBPJMYWarXe1/ErH+82v6bth/IPK5jbhnDAObJlhe0mNWNjC8wxemHOn+VWyqhoH1FzpxLXzGMLD+JddRbQFAF6szy+XFVPsYFbPXu6G7ichNluL+V+m5lBd5W7V284DI8yL1b04DObPyTa3IJQAgWonayJCfi1bkcgAQi9xc3v+gfVPbEwoBl1Uci/5VW9BjVn6u2gr434w/C9Z5lnw920rUuUL3rEIcAFWzBlCKHCAS+xyqM5VzUU8UdwkA+PziJSq/nh9R+b4KjNC12auZLvR8tLhN5ffqsdSZVH0qH1zg+d/XcEm2NZvxfkL3nEYVwcX9p+jpTUtSEecW2s6UB45VbirGBQCdqIGVaz3/Z6/x/fyBnbep/P3UeU53Ak5bXEEy4TRC95ylcI7vrHU9643pBSo/nPPa7O5A13LUff54HgpanI14z/DGLf7OEADyAbfNPNf3nPqInz/13kjV8gFg9qy4G4TKSSoHDtRgFaoGnS5DOROX9/hrLjSBkslmX8Q/kZcAQL3Nn1XV2XPjH9x+i8oHsX6fcJDzGHBccvu/u+LvMgDgS3e5bXaBu1EkHsWi/rWY6AQkFv43WBsVPjM64PGnU3UBQOafQcQ9rxD33EfwZ5s9Pn+Z/+mmgiTqXZ8ITepe9Kh/9Q5ex7lE5LldKmpzgT0rxXcTmbrnQ9cG0jXvvxH3LwCIF0JH9AHwukXUvg+H+d4Y3remMcYYY4wxxhhjjDHGGGOMMcYYY4wx5gPDH/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzDvCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxpwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wx5wB/yGOMMcYYY4wxxhhjjDHGGGOMMcYYY8w5IH3aAzhPxE2HfFI9IW/mepnKNqHy5/uHUuelwQMqf31xmcrv7m7LtpqGf4u1GWRSp9vwMaPibWWjjWwrHnS8/3khdVDyfpphS+VdwvsAgKaOqLzN9TdqUcd10gX/+U4s16O2+NiaHu8DAJYZH1ub859PF7qtNuP9R5Fes1vTXSp//fAild+9OJZt7eVi0QIcl0MqX9bcZmdVT7Z1bzqi8vn9LakTCZvpcm5/ED8PAHEj7G/Q6P4z3k+8r3UGwzWV7w1WVN5Ln/Rj79F03P6KpJY6ecyf1eJwzEp9/g/nfP+bZ/WZnS/54eiEb07n+tD2DvmebXb0mUmXXCc74WOOjvuyrU3EnwWOLIQKolwoBRpLuckA2syBgA9mtMLHhugCOusptyd1ljoRywAgqsReTnX/pbCNbMZ1In2UJeJYPmpPDG2z4fb/Bw9vyLYmFTemh2vtM6cb7oOTWPjM90HV6DM7XQfyCULIllYr7ktCFtuc8P47cc7yIz2XZMN7SspA/yI3UDYTa/ePaszHrHIJAGh4mAVirRMpnyHkjU5z0Yg4Gw10zEpSfghPF9z+X28uybZ6Ke/ncMpjGQC0IjeP1iLPDvifpsfPecjNKhtIF7z/RKf5qPt8z7qzHUsAgEglUByF/C+XRwH3o0JgUwhbErk8AKQzfjirsV6AbMXbq8X9a97otlrhneaV1nmw4P78ZMJt9nYjFhnAV+KrvP8XhGMC8MnRu1T+IXH/fRMXZFu3wMeWi3MJAKM+z5knKTeazbd0/FN3s1blXwDiku9ZM+L9l7vamJO1sFk9fX2fFj47mwZi1krMJXD+VT+JWJc2UI1qRTmjHAfuxqI95X+CCbiIWV0WcMAqzvV0P4m4Z6h9Xl3U/at8YnhH919vcRtQ/a93dNJabfGxlbqcgEadJ5HobL+jE+1yW9RZdGlM5lMqzoRy9vWOqDOp+xeAbMnnv9oTNYs4MADxqFS5HPTY4g1fgFD8BbgtheppMp8U4lrUHwGgE/lssq8TnXrJnYY6ZZ34+UcPuTiUm6v1TIVvVvfPEPUwsGbCZ6kaZBaqTaa8rWqsjSYWca5/yI15fUG31Qr7TwK1oYSnDDI3jgN3NqjaYMBpTBp+N3nz9FUqf7jROcsg5YO73JtKnSv5hMrHyVLqHORzKn9zfkDlVa3XX/qTQD1H1eDKS9z+loF3E5HyPz0dZ4ZjbjQqN1W1LADSZrq1XrOLxYzKE+GAvrbiuTwAjMQBOEh5HwDQEw6tF3F5FiiOJaIGfz0/kjqXC27Pyz2etCsbB4BCzKUKBK2Tmt+n3lzw+0x9QdvytOR1NlV/A4BFywN6rfL/LX1pkDWbE33PU3nGZl/kv2JcAFBPRc0kkGfEop67Ejq5NmXUos4eegepntXCz92c7cu2rhbcNl/p3ZU6/8no61S+7nii+/nZi7Ktb53ye7aqMwNAv8fPzGLJ/Vx2T9uSes+y2dMG0A25P4lULr8MxB/1rm+hdZT9hfJclYOptooj7TNUOlGNAvdMkbfIe752P4g3fABx6L2pyIHbRNzZAoVOFbNDtRlVN1C1+WwWaGtb7Nlp4J5Nvg/o1EuePwf+jTzGGGOMMcYYY4wxxhhjjDHGGGOMMcacA/whjzHGGGOMMcYYY4wxxhhjjDHGGGOMMecAf8hjjDHGGGOMMcYYY4wxxhhjjDHGGGPMOcAf8hhjjDHGGGOMMcYYY4wxxhhjjDHGGHMO8Ic8xhhjjDHGGGOMMcYYY4wxxhhjjDHGnAPSpz2A80QXR6iHZEkCnzs1LX+4l861jmjw3cUOlcdxK9tKxLNyHdjaouFtpbytJOlkU1v9DZXXdSJ1mk1O5VEVUXkX6F/pRHyKAIBWDK13qvtRFFOuU/e0zmbMx9wU4uf39P63uRhzqff//im3M8XnTl/UDycZFXdZwGaX4kB1fF2SUndfD/j848BWtn0xNmFnO5dmsq2DrQWVP7d1LHWu906o/PnigdS5mPIxlB035i+vbsi2BjFf0AZ8/QFgKYxz03I7W7b8jAPAasxt5u5qLHUUO/mSyg/XW1LncDmk8uWJ1qmW4jypJRN+CQCSFbf/NgsYrTgbcan60f2vD3g/IZ8ZLbmdVUMub2sdNPtDHjM2a20zUEsz5bYUafeDfCLWRi8ZmoIPQBw/FMe6seKEt7W4EYhzEX82Emv5/Qffkm3Foq2vHF6ROssNX+flpE/lvXf0XmYiNVpdOnv8VTar4gIAdL2AoStEQCkecgPoAjljyl2WtAsAKHdEbiT6iWrdf9SK/KMX8lln6x8I+xP686GYLdxvN9V55maHP4vE/q/uav+PUcX7D/i5eMYH3TvkOjHvAoDOc0N5TiceKnnNw+KjfmScCfgsYYPrfWV/uv+o5jr9Q91/tuDPsoUIDgH/v9nng8tmetOSktvf7j53gLvKMQSYl+LSAKBuuJ11IpdoV/rOEJW8rf9w83mp0z7LdX5w/DaVPz84lG0Nr/I4d7jRZ/bt6R5vq8fz3/qKXv/+i7z/NNGJxmzJbabd8HXuTnTMrA7eR8wSPiM75XZZnOoDsNkV5yzggNoef7a6wOX5VPevfEPCtwUA0H/I+9mIWIpg/s3FUaPH3ImAJo7foyHM+MN6KHzZXDfW8pQNTR7ITUU9oxqcPWap3EDlzADQ9EX/Iz7m1Z6Ov6XQiQO5Ub3F+19eFrWJgP3lk7PNJYQac1wFckZRZwrmxinXmV/nvmn8xkq3pa5ZgfXvcu5PVc7W5AFjEvWcj167J1VUPWFa8nvOV6HvTK3w/9U4kLMIH1iLc9EFyryNOv/iLgtAJuHVNv/xRG+/POfJZR1nI2Ezy5mIjYH7Rz7kcb5MdZxN7otFE+MK+bJ0K+AcBQcZr/Mdlzw5/1aglnt6R2xawP309vmGfub6O1InETbzjcOLVL464Wfp0QDOnpuruvlwn9tZluhcanI64MPa0kXo8YCv2cmct6XuhQDQDvnYolyPWdVz7pa8nvp791+QbS1Lbv9Vow19WPC1ycU6DzK9llcGUyofZ9rRfGPK7awVAaga67lcySdUrmrmAHAlO6Xyg7F+B6g4rPl95nOHes8OXuDvGh7eE/X0lZ6/rOeMAkF7wdurd4TNpjr+VH2hs9GOPlmc7fdR1FvamahtVnkpAMRr3n8j3oFcfYHbGKDfm/z68cekzqvD+7yfnL9nemWg85/+8zxm3V3rdzP9hOu8uxTvs6/rO3MpCn2bRvvMWFzO7s1GVD4PvBtIMpFnBt5n1ws+tkbcmQCd56YnvK1S3b8RqPMFcsN6m/dfHIr3OYFXM604z10g/VH3eVUzjsW3CY864uc5XepzLtIsSTUMtCXqjOrOCPC8OVRL/074N/IYY4wxxhhjjDHGGGOMMcYYY4wxxhhzDvCHPMYYY4wxxhhjjDHGGGOMMcYYY4wxxpwD/CGPMcYYY4wxxhhjjDHGGGOMMcYYY4wx5wB/yGOMMcYYY4wxxhhjjDHGGGOMMcYYY8w5wB/yGGOMMcYYY4wxxhhjjDHGGGOMMcYYcw5In/YAzhNdApQj9m1TK3U+vHOPyuOokzqvLy9R+dFiQOXrVS7bqpYZlfe+pXUghtZ+ZE7lUWAuk1mft3VcSJ1kHZ1JXr+P7816h7wtAIhLLl/vc5240f1E4lki+gCA3jFfz8mH+M+3B5VsK+vzZx++fF8PQPDWyR6VL2Y9qdMOa/6g0+vf5nz+Xc7PWbStF3PQ58/G/bXUeWF8SOUvDx9Q+Yd7d2Rbz2W8rR1lZAAysTSNPmaowJVuVjtUPmv0nr29PKDyt2b7Ukf5prblZ7MLzGXY42szyLSdP799ROWfGH2Lyi/szWRbVZdQ+azhvuzRM76e98ptKv/a5LLuv+H9qzUGgPmJWP8FbyudaZ9Zj/g567LApokYkCS8rbbk4wK0zbSN9hm98YbKy4KnMNEDHX9Wl/mY01UgZlT8WSvWrE10W4kw8ygw/7rma5b0ef/XilPZVhzx+W/3tM9UdNt8zOW2Ti3TFZ9LutDzL3fPaLNbgZhZ8JhVzbTNQNh5ucfHXDzU9q+oh3r+jUjnOnHM40D3y+s8aekGOtGJp3w/s6n2MyoEqtyoGmn/k81EbjgI6BzzMXcJl7epbqub8DwbIpcBgGzKxyzCD9rAbawdCJ+1p8+ssqZyyo0pmWmjieqz5exAYJ+3RB/6yKIT9t/kgf7P6M4alZgBKLf45sS13v/lwdl8wDhdymeJuIPu9RZSZyPyjCzn/q8VewwAsfCn1VzfM794+xkq38v5mH9y/DXZ1mi4ovI/Xj0rdaYVz9keLLgB7ox4HwCQxHz9Q/f8sRjzNOLjWisjB5Bt8cMUxbr/8oT3ky5FzB7rtpSf7QpdG0lPuf2J9EP6RUDfs3tHeszqPl+LND/OdPyLEt5P0+ozo3RULg0ArTABlRuG4l8i8lm1/gBkbSgp+QO1lo86CDVC3gAAIABJREFUCjwTZOLekk/4z4dspgmkcwrVnlqzkP1txiL+h6quwp6KqTo0gaZS3lYu8hIAqMUVtBK5abmjfZYy85D9RcKfFAMef9YrvZjFDk8ArvSFMQG4XEyp/N1ol8rTgM/Y7PExdw/0mpU7ws+I/C8WdykAaPuinlYGfJawv2Yo7l+R7r9/jz/rfVgnZh+/cJfK85jnLHWrHcDRZkjlX15fkzrlRdHPkPczekvPPy/4/vdVAQDAC/nDM8kvCXsFgNuXeG3w4Vok4AA2DT9PhwGdSuxBuRFnM5CzIBI1+ICdN7t8PS9t8xrgMNO12VGP15nWtfYzJ3PuNDdrfmfsdgMvB0Sdp2v0/I9L3n8i6umpyGUBIE+5P1uX4v4L4PCU20an6lmBvOAbLX83dv3SidRZiLGdHI2o/JvJRdlWJ95bxCqXAzDe5veZYc7tskjFOxMA14e8brcfuucJ28zFnaES9goA+YTPf3MpUBvpCTsT9ZeEHzEAgRpI4BWguhuomm3gdS7UFXyxrZU6UQPavsz9z6tD/s4YAAaiaPba6VWp82sT/j5HvU8ZZTr+Xu3zeKLu7AAwTvk995UBn2cWaftvxEZvWu1/1LuZkx1u5zfn+j3XrQmPmct1IM8V9eTQO7ByydtT70ZDPlPl0604lwAAERvqIV//OJAztoXIWbd0/yqep3PeT1VpB9CJnHUr8A1A70i8txI1QHWXAwI1yMD+F5MnH4a+M/hO+DfyGGOMMcYYY4wxxhhjjDHGGGOMMcYYcw7whzzGGGOMMcYYY4wxxhhjjDHGGGOMMcacA/whjzHGGGOMMcYYY4wxxhhjjDHGGGOMMecAf8hjjDHGGGOMMcYYY4wxxhhjjDHGGGPMOcAf8hhjjDHGGGOMMcYYY4wxxhhjjDHGGHMOSJ/2AM4TXQS0WfSEvBivpc614oTKh/FG6iRoqTxPGyofba1kWydlQuVxKVVQbne8nz4f83ZPz2VR5lQ+S/gcAaBcZVSe3CqovIv5eAEg3vBv0aqhVEF1ibfX9Lk8Lp+0iT8dW8SfFSd6zP1jvjZdzOeS9SvZVlHwZz+2/02pMxC2eX9nzPuPuF0CwLubXSr/8tFVqXNxMKPyq/0plb80uC/beiF/QOXX0lOpsyMOx0Bvs+Rhy13ovWYgdY6aLSp/q7wodW6LdT4uuaHfWvCfB4B3HvJnlTiXABAtzhgqtPljOeT2FKXaZ0xWPSqvWu7/Pja6Ldv6cI8/+0zvHakzjvUZoOO6oJ89bLmf+8PVc1Lnc5MXqfytyQGV333IzzIAdBu+ZkgCm9byw5GKmLV7cSmbmi75XvaHOs70cu7nOjHksuBxCQDiXX7+u0jPvz7l7aVzvpbNQLe13lWOJhDnRAyMxZgPUu5jASCLaiq/0J9rHWH/F4ZcZ7Kl9x8f5eJeyscFAMOM79n1AffzaSBmfX1yicrfxp7UqaYiN+nzfuq+/ka+4eaPZK0DkMrnNgfCZwaO8ugZHmdHgTzv4RaPWWWs41y64POpeVNAIP52wjdV13Si++y1Qyq/NpxQ+U6m8+xVw2Pja0dXpM7xfJ8/EGc2WQb2X9hG02g7S0QOHq/EnaHS/TcFH3MX+Kcgap9FyoREmx+KYz421RYAzJ7lOmuRy/SO9KFp+PFHNRKxFHptTo74wgxf1gvwkYLnLB+7/i2po6g6Pv9Fp2PmkdjMNzfclwLAaxN+B/jqKT8zF3Mds35g8CaVf3rwltS5eoXfzb+8fIbK//3h87Kt02WfyicT7f+6ihtAXPCY0fV0/tu2vK02cDeF6Gd9QRhmIP+LRD/xXDuASExHpVl1IGdSbW12AndzMbRYXKc7keM+GgAXp0faAdXiCpYE/Kyap67n6LbUcdq+petZ+a1jKl+8yu+mIf+bzUWdJddjrsVxUjlTVOu2hnd5/6uLZ8+z0oUYF6kX/mlbws7iQGqcizXLFly+vBg4fyIFrgO1MRXnm57IP4QcAFKRTqlYCgBRoG5If36g7wwH23zTiljr3FrxO8Cm4YY+COTM68nZ65nNQORs29yYmlTXbJCJOuMwcDkQtQHl/wNXZqyuiHp2YI9zsTelcDTq5wFgt+AHbTTWef70Ic9z2oKPebOrz9+ox51JyP7U3TwXh/nTw7dlWx8f8L1U+R+g3000gX/z/W7Jz8zns+eo/J2Jrk2engrntAo5DS4eZYELhWCnx22jbHSef/hwm8r7Ix5nNxt9ZpuV2BuRywG6BvjRa3ep/L9+5vdlW1XH59kGLnqxSFpUW0oOAJuWr82k5vn3o/6FE7rOxeouDwBvzHjh9nil8/yy5vM5mnMdlcsDwLG4Z4Tewcl+VG0g4LTV+6wQUS7uM4mwpUDONLjLnwVMBuVIP2OEYpbMMxs95myX+4wP7T+k8pcK/T5rP+H11PEVkYBC38G/Pufyr9zXNas3Yu5LQj7ryi6vJx6IerI8r4FndeDMtJ24m4q2lL8CgAtDvs7vVjpmrhY8NkWBPE+9t4DIv0VYftSWuLeG7kbqnOenfJ3rQM6YihpAmwXmL5az1SWoM1PysAwAiIQ9DR7whRavGQEATSHsL/DKMNmQtZFG8Z3xb+QxxhhjjDHGGGOMMcYYY4wxxhhjjDHmHOAPeYwxxhhjjDHGGGOMMcYYY4wxxhhjjDkH+EMeY4wxxhhjjDHGGGOMMcYYY4wxxhhjzgH+kMcYY4wxxhhjjDHGGGOMMcYYY4wxxphzgD/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5hyQPu0BnCeiFkhX3RPyOH5S9h69qKbyRVtInU2bUfmo2FD56aov28p6vP96qMfcjFoqH/fXfFw5HxcATNd8nttD3hYAHFfc7JqeUEhkU0hEN2KJAQAxXzK0Ysm6TK8looiL+RI/6iflOm3Ofz70tR1vCXipuCd1fqT3kMrHMd+AZVfKtt6o+OY83B1JnZ14SeUXkpUYl5olkEV8ddpO79lMPHrYcrt8qzqQbf3+/AUq/8Lxs1JnVXHjfHC6JXWamq9zkjZU3rXaapqaP4sWOhwkS65Tj8VhygMHoBNn5kgcAACTGV+z37vP7exLB9dkWz96/S0q/9ToHanzanGHy7MFlV9Ph7Kt54X8hfQbUudjvW9R+W8NP0Ll/3f1cdlWWZ897K9XfG92hvzMhhgLnaOQ/Tfc/so1t4su1ec/y4XNBlAays/XA93//DkVaAL9i/OfxnwAOwn3sQDwan6fyj957V2ps+54/+uOr/86FIAFSSBoJmJxMpF/qXEBwGv9Z6j8c8WLUucP37lB5QOR5ywKlcxoqrVOdJRv7rKAnxU8u3tC5S9sHUqde6NtKn8tvSJ11kvuM6KE72Uz1f5fnY3dvblU+RtXXqPyHxy8QeU7sc5z36z2qXxS/YjUaV7hcW6+5LZRTvSdIRLxNAncTVqRA7R9njMkSx0XsiWfS7mj7a8Z8X7iObfzuNI5C7uXAcDiqlRBtc116i0+l07k8oC+M6x39JltM95eUoh1gV7Lqwm3zVGs+6863t7ZPQaA4oiKZ/2bUuW1wWUq/1dHf4XKf/vhh2Rbsz1+Zn50S+dMr+b8DrSXcJ8RR/os/cEx9//vh+mU3+e3L2pfVov8Z7XQPgOtsHNx/tNTff5jcQUM5Tn1Nre0dMbnIq4Fj3RW4s4cSGXV2KJGdBQYQMeXTF/AAUD0E1daSRxzObTekV5/5TPXezrOZne4P6lGXN4EzE/5U1nnAdCJ3EDZctzo+Q/vcae9GevcMFN3UzWsQMqSbLhSF6hntMKdKzvP5nr+6sxu9gL957w9FcvCdS4uD51zlRtGAd+s2Onxe+YrA10bU7XZX739CSrPksACiLl0gYJeNOCOptfnm7nchO4M/FnX02OOhxWVtylvK9/WObPiYMBrJgBwUg6o/Mt3eKJ3eWcm2yoSfv6LLHD/Fz47Pxb3bz0VdMLQL+R6zN8S94w/nPJ6YhqrwARsiWCyleo9G4sa7LO5vhtez4+p/I3iIpX/yYrnhQDQCntOau00osC9mTFIdT37ndkulfdSbTO7+3w/FyseHDsRywAg6oncrND9bxf6XQtjHgjARczP/16qc9NexHVUbSZEqAakyMDXLI+4vBS1LACYbfPcfBEI9McNr1ve3nBb2gSS1lnN9+Zrx5ekTiJikHo30AQCsLozpyO+x6F+ygv855tSr/90yINjKt4/AJAXWpmzhd4NimmG3gGqdzOtWOdQbfJI2NLldCJ1rmW8nvdyj+c5Lw35+z8AeH3G7ewbR2IzAcw2/Gy8c5vHLFX/ACCTw/5Ax6xc+Gblf1UtHQD2xoGALkgzMZ9Aztod8zVTuVlUavvvCqETuGdGG95epb4bCOTs6myE7rmtKOgq998FaoNQ7zMDZqburemSD6A41o2tLvLznK71/vfvPRmzk/Lsd5z38G/kMcYYY4wxxhhjjDHGGGOMMcYYY4wx5hzgD3mMMcYYY4wxxhhjjDHGGGOMMcYYY4w5B/hDHmOMMcYYY4wxxhhjjDHGGGOMMcYYY84BT+VDniiKfjaKov8tiqLfjaJoGkVRF0XR//UddH4kiqJfj6LoOIqiZRRFX46i6OejKDrbH0g1xhhjjDHGGGOMMcYYY4wxxhhjjDHmHJI+pX7/IYBPAJgDeBfAq6EfjqLovwDwLwGsAfwKgGMAfwPAPwHwowD+y+/mYI0xxhhjjDHGGGOMMcYYY4wxxhhjjPlu87Q+5Pnv8egDnjcA/DiA31I/GEXRNoB/DqAB8BNd1/3BY/kvAPgsgJ+Noujnuq775b/ooOKqQ//++gn5eplLnWXLn31//22p86neTSq/OT6g8t+cfES29fXJRSp/kNdSp14UVD7On5w7AMRRK9tKE/5svuJ9hMiem1P5ZpVJnWaX999M9J7lR/yXOHVxx+U9Pf/lVa7TFPoXRVWTSDzhbaVpI9viGsCy1evfE7/EqgWf56zV/V9K+LNRfCx1li13O0dizDfrnmzrdrVL5W9v+LkAgDeX/Jy9OeHystZu8uhoiz/o1B4DUcrXuWu1Tix0koRbQFmdva12VEmdTpznaC3svNa/7K0ruM2kcz1mROoZ72c9Hcmm/t+Tj1L5v8n196Q3LnN7/sTebSr/2OBd2dYz2RGV7yfaz/Ui7s9v5IdU/sOX35FtHZZDKn/zhNs/AJQlPwP7/SWVLyrtfx/Oef/VRPusfJfHpp2dBVfYkU1hIWy5WutzHonz3CkzD5iyctqRcuaA9CezNZ/LvXosmxrFq0BHnETkAI1YgAo6/imddavtv+r43swaHhtGCbcXALianVD5Z3ZuSp1ewn3jtOxT+dc2l2RbndjnttH2FyvXXIpYHshZWmFL41TbxbUxX7NXtu5LHbWficgzVC4dYjfl/gcALmWTM7UVy2wKuJzytj6zo/3s80Pu5798co3K7xU6ZjUtPzOrwN2kXXJ7SkScD6QMaGfczpqBtjO1nO2Qx/91yGZzYeeB38fa5by9SoSZdBby/1xeDfWi5cL8VD4/aXhcBIA/Lnls/srqGamjfONG5N+h8/9Swc/5h3J9/j+W36PyvYu/S+U3xRwB4PdnL1L5r518Qur8la1bVP5Mzs/lp4f6zv588ZDKl5d0zqLW/90Nv7MclwPZ1tcP+X1muQodAGGbwpabwPmrd/izbHujdTbczrq5uEsEXEnT44MOpAySVvis6FQ31qUqadP9ROI+F5daR21ZIpa5C2x/3eeNJaWOc8sP7VN5XHGd4X3d1nrMY5ZalxCxKGeFbGZ58X2UN8XQshmfZ6RLIxDHH8lar5naz9U+X8su1mtZC3dSjfSidfnZztnikr7ntykfm1oXAMhF3XJ3i+d5p4FL017B74af6b8ldXpiQ4tneM7028cvy7bGBb+D3Nri/h8AIjGfXi5ytoG2cZXPJcdapxW1mf4On0uR6TqzGvMP7ek4q3JwdWeZldqYLvR5PXkk6twAcLTF63mlyiV3tAMuF3xsJ+pgQt9bZzWPmd88uiDbmov+Y1GzB3QN8j976XWpsy3yxq+f8pylC9RGY5WDi9o8AHTizKQxt+U44DNO5nxvksCaNQ33gRuR54QuWlFPnL++Tho+tnOHytX9+9fufZ9sS62NOn8hnUy8G8jEvgDATs5t6Vr/VOpUImiqOsN2qs//QCRaqv766Bn3c9cKXjNJAnWGtahz5SoBAvDOfI/KHy74fXIz0D4zWnFbzgLvExWdeAeQHQZi1j7vpxI1AwCIFsIHK9dca1sWV2N0RcBnPuDnPH2W65w22v/fLXnhet7oe6aqge2lPP+5UfD7LwBcyqZUHqpzSZ7j4kIWM4GN8Fmh2qDyczPx3jB0z3644vH/4V1dT4+Fz26ngcvpFteJxH2+y7T9qXdwobuRureoe26ozpcInxGqzSUbfgbrvrhnLXVjsYinATOTz6bPKd+kfZa6z6Whex67t539WvynPJU/rdV13W91XffNrlOvNP5//CyACwB++b2PeB63scaj3+wDAH/nuzBMY4wxxhhjjDHGGGOMMcYYY4wxxhhj/tJ4Wr+R5yz85OP//gZ59jsAlgB+JIqious6/c/DHhNF0RfFo+Cf9zLGGGOMMcYYY4wxxhhjjDHGGGOMMea7yVP5jTxn5JXH//3Gtz/ouq4G8DYefZD0wl/moIwxxhhjjDHGGGOMMcYYY4wxxhhjjPkg+V74jTzv/XG6iXj+npz/ccFvo+u6TzH549/U8/1nG5oxxhhjjDHGGGOMMcYYY4wxxhhjjDEfDN8Lv5HnOxE9/m/3VEdhjDHGGGOMMcYYY4wxxhhjjDHGGGPMX4DvhQ953vuNO2PxfPvbfs4YY4wxxhhjjDHGGGOMMcYYY4wxxpjvOb4X/rTW1wF8GsDLAL74Zx9EUZQCeB5ADeCtv2hHUVUju3v6hLzbXJQ6r82uUfkPDt6UOnvxmsovp0/2DQB72UK2td/jz+JI/4KiO21E5bOqoPKm1d97rStuQmWpTStOGipPkpbKd3b0/NXYFh2fIwCUMV+beFBzeeBztyZOqHyjVdCmvMEu4eNS6wIA2z3e01dW1wMj4Lwl7Pw3H7widUYZ77/u9KLdnvBv8hZLbn9xYP6bKddBrftPFvxZM+J2iVrbUjbh+9/m+vy16miI/QeARthsK8YWV3rM7X7FdTK9zs22OBtLPn8E+u9S/qy8INYfQLzieybnGTj/0ZxvQDrNpM7N2SUu712g8n/VfVK2lfT4PPd25lLnpZ1DKn9hyOVxpPfy3Rn/K5Qnk6HUGQ55zCob4f9q7f9X4pyHKCdcp9rwfnqDUrbVifjXlcKWAUCcjXqP72W00PMvTrgtJ3yJAQCLIbfNfMxj4+cnz8u2fmX6aSqfb3Kpc3qibYPRVdr/RgE/I9sT/ry3zePPQMRFANjp84W+sXUidbZSbk/3l9tUXs71WqrfHZmeapvJJ9xmq5HIGSZ6/V+/w33Zg8WW1Bn3+JplsfbZ2znXiT/AX555D3z9AeB3Hr5E5aerHpV//MJd2dant29S+ThZSp03ljyfujsbSR3F8g7fG5XLAEC7w2N2s+R2JmM5gGQt4mmrdVQ+2xVcHgVyhnTOn60uB3yJiLMQvqnT4R/Z+/hnIq0Ic7HI5Zat9hk3S55nfHFyQ+p85d4VPTjC6qQvnxVjfpY/fvWO1Plr+1+j8h/q86v6Z3q3ZFuJuM/+6+OPSp0vTHkM/I3N91H5fqHvmXs5fzatuS8B9Jg3DT9/J+uBbGux4rbR319JnUrcwZNv8n42F7m/AKDzn7U+NDLPSsX9W/kYACqdDZQ5EG94eyqWxoHpxyKdrPWRQSnuwNKXAshmXN4IMyu3Az5ThybJZsz9ebrhC92/r/OsasAH3cV6zLG4zxanZ88ZVAki4GZRjsU9W9xZc16ye/RsLuKfnj6qEX8Y1bytbBE6AO+jNnDG63TMSwmPnpViLXPdfxNaHEJd6/xjWfONHkV60FfFPs9671D5reG+bOs0584hCjit+yI3PDnRubkiUjWj/tnPUtPww7Rs9GHq5XydP9zTOcOr+X0q/2ujr1B5ErhLnLZ8/X/99BNSp3yGx8x3Rc1y/n5qGbIACFzPj6j8x/f4Wo4zXTRQNaDbS17/AYAtUc+d1nqelXC0i5LnBir/BXRu0GYBm035PCcl3/82sGad8D9KHnqWFPz+kW7pREPlbOuNzrMGIjkZiYLSxYFIMgDcXfD79PFM1382C+ED1D6rIBPQKfraZzeiNtSKd0NxrO+M7RnjT6g9ZedZpmsmL+7x86/OJQAMRG0qjviexbNAnVNQV1qn3+f9r8RSFieBNe64/QsxACBdipxJLHM5DrznGPJn0frsv/Pi4UrUbKD7v1Hw/f/s8atS57cefojK+yL+hvKP/T6/NGwHfGY/4f1cKqZUnsWBBFzQBN4nKoYJPzN5T/vf043I2fKAzxD1tNCvSYlW/Dx1Ym+iTaCefvZyurwbqfgbBfyiis1R4D6tYkDUqDu7nn9xzOUhn5FP+JjVfTrUVt0TaxPpMfcenj3OhPhe+I08n338379Onv0YgAGAz3VdF/p2whhjjDHGGGOMMcYYY4wxxhhjjDHGmHPN98KHPP8CwCGAn4ui6E//KXkURT0A/+jx//xnT2NgxhhjjDHGGGOMMcYYY4wxxhhjjDHGfFA8lT+tFUXR3wTwNx//z8uP//vDURT90uP//7Drur8PAF3XTaMo+tt49EHPv42i6JcBHAP4aQCvPJb/yl/W2I0xxhhjjDHGGGOMMcYYY4wxxhhjjPlu8FQ+5AHwSQB/69tkLzz+PwB4B8Dff+9B13W/GkXRjwP4BwB+BkAPwBsA/h6Af9p13dn/6K8xxhhjjDHGGGOMMcYYY4wxxhhjjDHniKfyIU/Xdb8I4BfPqPN7AH7quzEeY4wxxhhjjDHGGGOMMcYYY4wxxhhjnjZP6zfynEuaYYbTT19+Qh5ttE4WN1T+1c01qfPv6iGVD+KSym+vd2Rbb5/uU/l00ZM6XRtR+eGcj6uqE9lW08SiE94HAFSLnMrb29wcF4NWtgXxu5jSqR5zIh41iWisFnMEUDzgjUVijQEgFvbUFlxelvqYnrZ8bPNGNAbg301fpvI/OuI2+/B0S7ZVH/WpPCr1/JOVeCbEVaF/4VYu2gqYH5oeb69/K6Py9SV+xgGgulDxB6EBCDvrb6+lyqXxjMqHGfcZIXbyFZVvZ7p/RSwO4KrhawkAVcdtdh3QmWy4nT2Yc9tcrLiPAYB2w89TWQTCYcTnGa2EMwn8jrim4vM/PN6TOofjEZW/NrpC5WmsfeZszteyPdFrtslqKr8z3eZ9HPNYAgCo+dlIFtrPxhXXaXK+/s1K+79E+SbhFwCgGnMfEJe8/+Khnku25PKIL/Gjfla6PUYi7BUA9np8AN+6o+0vEj6rW/IzEy/1eLtUjC3gMiPxbF1xW97UA9nWccHPxtv5gdTZ2V1Q+WrDz0xyqn1JNuNrk/IuAACdcDMylgaoTvj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" ] }, "metadata": { "image/png": { "height": 1143, "width": 1145 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "speaker_id = next(female_speakers) if np.random.randint(2) else next(male_speakers)\n", "speaker_id = torch.LongTensor([speaker_id]).to(device)\n", "\n", "with torch.no_grad():\n", " mel_outputs, mel_outputs_postnet, gate_outputs, _ = mellotron.inference_noattention(\n", " (text_encoded, mel, speaker_id, pitch_contour, rhythm))\n", "\n", "plot_mel_f0_alignment(x[2].data.cpu().numpy()[0],\n", " mel_outputs_postnet.data.cpu().numpy()[0],\n", " pitch_contour.data.cpu().numpy()[0, 0],\n", " rhythm.data.cpu().numpy()[:, 0].T)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "with torch.no_grad():\n", " audio = denoiser(waveglow.infer(mel_outputs_postnet, sigma=0.8), 0.01)[:, 0]\n", "ipd.Audio(audio[0].data.cpu().numpy(), rate=hparams.sampling_rate)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Singing Voice from Music Score" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "scrolled": false }, "outputs": [], "source": [ "data = get_data_from_musicxml('data/Dream_a_little_dream_of_me.musicxml', 132, convert_stress=True)\n", "# data = get_data_from_musicxml('data/haendel_hallelujah_1.musicxml', 132, convert_stress=True)\n", "# data = get_data_from_musicxml('data/哈利油.musicxml', 132, convert_stress=True)\n", "panning = {'Soprano': [-60, -30], 'Alto': [-40, -10], 'Tenor': [30, 60], 'Bass': [10, 40]}" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "tensor([33])" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "torch.LongTensor([next(female_speakers)]).to(device)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Soprano MellotronID 37 pan -36\n" ] }, { "ename": "RuntimeError", "evalue": "Expected batch2_sizes[0] == bs && batch2_sizes[1] == contraction_size to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mno_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 19\u001b[0m mel_outputs, mel_outputs_postnet, gate_outputs, alignments_transfer = mellotron.inference_noattention(\n\u001b[0;32m---> 20\u001b[0;31m (text_encoded, mel, speaker_id, pitch_contour*frequency_scaling, rhythm))\n\u001b[0m\u001b[1;32m 21\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0maudio\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdenoiser\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwaveglow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmel_outputs_postnet\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.01\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m~/mellotron/model.py\u001b[0m in \u001b[0;36minference_noattention\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m 686\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 687\u001b[0m mel_outputs, gate_outputs, alignments = self.decoder.inference_noattention(\n\u001b[0;32m--> 688\u001b[0;31m encoder_outputs, f0s, attention_map)\n\u001b[0m\u001b[1;32m 689\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 690\u001b[0m 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(Could this error message be improved? If so, please report an enhancement request to PyTorch.)" ] } ], "source": [ "n_speakers_per_part = 4\n", "frequency_scaling = 0.4\n", "n_seconds = 90\n", "audio_stereo = np.zeros((hparams.sampling_rate*n_seconds, 2), dtype=np.float32)\n", "for i, (part, v) in enumerate(data.items()):\n", " rhythm = data[part]['rhythm'].to(device)\n", " pitch_contour = data[part]['pitch_contour'].to(device)\n", " text_encoded = data[part]['text_encoded'].to(device)\n", " \n", " for k in range(n_speakers_per_part):\n", " pan = np.random.randint(panning[part][0], panning[part][1])\n", " if any(x in part.lower() for x in ('soprano', 'alto', 'female')):\n", " speaker_id = torch.LongTensor([next(female_speakers)]).to(device)\n", " else:\n", " speaker_id = torch.LongTensor([next(male_speakers)]).to(device)\n", " print(\"{} MellotronID {} pan {}\".format(part, speaker_id.item(), pan))\n", "\n", " with torch.no_grad():\n", " mel_outputs, mel_outputs_postnet, gate_outputs, alignments_transfer = mellotron.inference_noattention(\n", " (text_encoded, mel, speaker_id, pitch_contour*frequency_scaling, rhythm))\n", "\n", " audio = denoiser(waveglow.infer(mel_outputs_postnet, sigma=0.8), 0.01)[0, 0]\n", " audio = audio.cpu().numpy()\n", " audio = panner(audio, pan)\n", " audio_stereo[:audio.shape[0]] += audio \n", " write(\"{} {}.wav\".format(part, speaker_id.item()), hparams.sampling_rate, audio)\n", " break\n", "# break" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "torch.Size([1183, 1, 75])" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rhythm.shape" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "torch.Size([1, 1, 1183])" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pitch_contour.shape" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "torch.Size([1, 63])" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "text_encoded.shape" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "audio_stereo_1 = audio_stereo / np.max(np.abs(audio_stereo))\n", "write(\"audio_stereo_1.wav\", hparams.sampling_rate, audio_stereo)\n", "ipd.Audio([audio_stereo_1[:,0], audio_stereo_1[:,1]], rate=hparams.sampling_rate)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "torch.Size([1, 80, 345])" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mel_outputs_postnet.shape" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 2 }