FftStyleTransfer.ipynb

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   "source": [
    "import utility_functions\n",
    "import plotly.express as px\n",
    "import numpy as np\n",
    "from scipy.fft import fft2, ifft2, fftshift, ifftshift\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "import os\n",
    "import cv2\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from tqdm.notebook import tqdm\n",
    "import numpy as np"
   ]
  },
  {
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   "source": [
    "def replace_low_frequencies(src, dst, n_freq=1, alpha=0.5):\n",
    "    chunk_slice_x = slice(int(src.shape[0] * 0.5 - n_freq), int(src.shape[0] * 0.5 + n_freq))\n",
    "    chunk_slice_y = slice(int(src.shape[1] * 0.5 - n_freq), int(src.shape[1] * 0.5 + n_freq))\n",
    "    \n",
    "    # Take the center chunk from a\n",
    "    src_chunk = src[chunk_slice_x, chunk_slice_y, :]\n",
    "    \n",
    "    # Put the center chunk into the center of b\n",
    "    dst_cp = np.copy(dst)\n",
    "    dst_cp[chunk_slice_x, chunk_slice_y, :] = src_chunk\n",
    "    dst_interpolated = (1-alpha) * dst + alpha * dst_cp\n",
    "    return dst_interpolated\n",
    "\n",
    "def plot_img_and_transform(image_data, fft_rgb):\n",
    "    # Compute the magnitude spectrum for each component\n",
    "    magnitude_spectrum_rgb = np.abs(fft_rgb)\n",
    "\n",
    "    # Log scale the magnitude spectrum for each component (add 1 to avoid log(0))\n",
    "    log_magnitude_spectrum_rgb = np.log(magnitude_spectrum_rgb + 1)\n",
    "    \n",
    "    # Display the original image\n",
    "    plt.figure(figsize=(16, 6))\n",
    "    \n",
    "    plt.subplot(1, 4, 1)\n",
    "    plt.title(\"Original Image\")\n",
    "    plt.imshow(image_data)\n",
    "    \n",
    "    # Display the magnitude spectrum for each component\n",
    "    plt.subplot(1, 4, 2)\n",
    "    plt.title(\"Red Channel Magnitude Spectrum\")\n",
    "    plt.imshow(log_magnitude_spectrum_rgb[:,:,0], cmap='gray')\n",
    "    \n",
    "    plt.subplot(1, 4, 3)\n",
    "    plt.title(\"Green Channel Magnitude Spectrum\")\n",
    "    plt.imshow(log_magnitude_spectrum_rgb[:,:,1], cmap='gray')\n",
    "    \n",
    "    plt.subplot(1, 4, 4)\n",
    "    plt.title(\"Green Channel Magnitude Spectrum\")\n",
    "    plt.imshow(log_magnitude_spectrum_rgb[:,:,2], cmap='gray')\n",
    "    \n",
    "    # Show the plots\n",
    "    plt.show()\n",
    "\n",
    "def transform(image_data, show=True, shift=True):\n",
    "    # Split the image into its RGB components\n",
    "    r, g, b = image_data[:, :, 0], image_data[:, :, 1], image_data[:, :, 2]\n",
    "    \n",
    "    # Apply 2D FFT to each component\n",
    "    fft_r, fft_g, fft_b = fft2(r), fft2(g), fft2(b)\n",
    "    \n",
    "    if shift:\n",
    "        # Shift the zero-frequency component to the center for each component\n",
    "        fft_r, fft_g, fft_b = fftshift(fft_r), fftshift(fft_g), fftshift(fft_b)\n",
    "        \n",
    "    fft_rgb = np.stack([fft_r, fft_g, fft_b], axis=-1)\n",
    "    \n",
    "    if show:\n",
    "        plot_img_and_transform(image_data, fft_rgb)\n",
    "    return fft_rgb\n",
    "\n",
    "def inverse_transform(fft_rgb):\n",
    "    fft_unshifted = ifftshift(fft_rgb, axes=(-3, -2))\n",
    "    \n",
    "    # Apply the inverse 2D FFT to each component\n",
    "    ifft_r = np.abs(ifft2(fft_unshifted[:, :, 0]))\n",
    "    ifft_g = np.abs(ifft2(fft_unshifted[:, :, 1]))\n",
    "    ifft_b = np.abs(ifft2(fft_unshifted[:, :, 2]))\n",
    "    \n",
    "    # Combine the components back into an RGB image\n",
    "    rgb_image = np.stack([ifft_r, ifft_g, ifft_b], axis=-1)\n",
    "    \n",
    "    # Clip the values to the range 0-255\n",
    "    clipped = np.clip(rgb_image, 0, 1)\n",
    "    return clipped\n",
    "\n",
    "def translate(fft_sim, fft_real, n_freq, show=False, alpha=1, noise_level=0.0):\n",
    "    fft_res = replace_low_frequencies(fft_real, fft_sim, n_freq, alpha=alpha)\n",
    "    fft_res = fft_res + np.random.normal(0, noise_level * np.real(fft_res).max(), fft_res.shape)\n",
    "    res = inverse_transform(fft_res)\n",
    "    np.clip(res, 0, 1)\n",
    "    if show:\n",
    "        plot_img_and_transform(res, fft_res)\n",
    "    return res\n",
    "\n",
    "def to_lowest_freq(fft):\n",
    "    chunk_slice_x = slice(int(fft.shape[0] * 0.5 - 1), int(fft.shape[0] * 0.5 + 1))\n",
    "    chunk_slice_y = slice(int(fft.shape[1] * 0.5 - 1), int(fft.shape[1] * 0.5 + 1))\n",
    "    \n",
    "    return np.expand_dims(fft[chunk_slice_x, chunk_slice_y, :].flatten().real, 0)\n",
    "\n",
    "def find_most_similar_image(fft_sim, candidates):\n",
    "    sims = cosine_similarity(fft_sim, candidates)\n",
    "    return np.argmax(sims)\n",
    "\n",
    "def translate_with_most_similar(sim, candidates, n_freq=1, show=False):\n",
    "    real = find_most_similar_image(sim, candidates)\n",
    "    return translate(sim, real, n_freq, show)"
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   "source": [
    "size = (320//2, 240//2)\n",
    "\n",
    "real_imgs_path = \"datasets/denoising/test\"\n",
    "sim_imgs_path = \"datasets/sim/test/data\"\n",
    "real_imgs = os.listdir(real_imgs_path)\n",
    "real_imgs = np.random.choice(real_imgs, 1000)\n",
    "sim_imgs = os.listdir(sim_imgs_path)\n",
    "\n",
    "real_imgs_data = [utility_functions.read(os.path.join(real_imgs_path, img_name), size) for img_name in tqdm(real_imgs)]\n",
    "sim_imgs_data = [utility_functions.read(os.path.join(sim_imgs_path, img_name), size) for img_name in tqdm(sim_imgs)]\n",
    "sim_imgs_fft = [transform(x, show=False) for x in tqdm(sim_imgs_data)]\n",
    "real_imgs_fft = [transform(x, show=False) for x in tqdm(real_imgs_data)]\n",
    "sim_imgs_fft_lowest_freq = [to_lowest_freq(x) for x in tqdm(sim_imgs_fft)]\n",
    "real_imgs_fft_lowest_freq = np.array([to_lowest_freq(x) for x in tqdm(real_imgs_fft)]).squeeze()"
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   "source": [
    "for n_freq in [1, 2, 3]:\n",
    "    save_path = f\"datasets/translatedcs{n_freq}/train/data\"\n",
    "    \n",
    "    if not os.path.exists(save_path):\n",
    "        os.makedirs(save_path, exist_ok=False)\n",
    "    for i, (img_sim, img_sim_fft, img_sim_fft_lowest_freq) in tqdm(enumerate(zip(sim_imgs_data, sim_imgs_fft, sim_imgs_fft_lowest_freq)), total=len(sim_imgs)):\n",
    "        most_similar_ind = find_most_similar_image(img_sim_fft_lowest_freq, real_imgs_fft_lowest_freq)\n",
    "        # most_similar_ind = np.random.choice(len(real_imgs_fft))\n",
    "        # img_real = real_imgs_data[most_similar_ind]\n",
    "        img_real_fft = real_imgs_fft[most_similar_ind]\n",
    "        img_res = translate(img_sim_fft, img_real_fft, n_freq=n_freq, alpha=1, noise_level=0.0)\n",
    "        im = Image.fromarray((img_res * 255).astype(np.uint8))\n",
    "        im.save(os.path.join(save_path, sim_imgs[i]))"
   ],
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voEblI9jYl09QJs32Juw4QNcO7Kn0I7UUrR1A2lBR7QS+pz2zY9g8WLOoTG9yuKEORbXV18E1kXUihknoT2IWBW2EBI54gXhPeFMFAQgvVOAkHC\\u002fxaccOJlpyiodBrS1YKMw5sUhZTGtWd5ISHobdlzgxQy0mAJcMPMzxHQxmTcchsohrBuNLCJ0O\\u002fPldJEZJfa8ssuMeQRaPfuRKex8U6RrClTFbtmqErOD4Fbu9IoeCbxp54TQooqwKni2Nof7FnxQM8+ELKLqMxgrrzXFwel1wXM\\u002f53E3au7TJr6pYHPTgJeCLc7xFa3aGTZtK1lbzqrIq3hoRQsy90d+kwmZpfdG710PYcllhXZb3jHhrl9lGJv40WRfgFAW6MiUlZ2Lv5dgFdkMpiM4Yw0f4YHkRWgd8R+9fzfrGvn2HdkMc3PHlmAxI778xcuqo\\u002fxoeqhwpuOveH25Q84vQzydQAFOtRO54AnPaOlq6GYwELlPMW33xM9m98fQMZ311xpIKiasrQG5\\u002fNJUdKDSOw5nXu3Kp9UXpzGfWDhq3n7RVQMT3SR5qmhiA\\u002fjRlAWPcTqdJH7o060YiMazp6pg8wRa3oB\\u002fRHCBy3ONN42jlDy4aPNqEiYR0fJP48bR+CqqHBhGHtwSCkyIEDkJhXzLdc+8ykhRQwXV0rTnE0EPwughQwciTS80wynBCwDZGNhySu54AMNv1\\u002fAf57qGzXngp56vKso9tV70\\u002f4MpskofFGeXa0zlgZdbMxnYM4ULALgYyJ\\u002f0hhFSQLcuoltfNvMfgp0V8i2wIbgJKVANcZMvXkQhyPfPq2zrdNqUrVxmNg4fBxBrerfh620\\u002fb8VfsbAH+eo\\u002fayMEeo2BAh\\u002fm4XbI5ezoIK+1\\u002fL\\u002fjAZ85E+3pFrCmokGjI74InbOVCEbTQ+RjwGIqk9OUU40SDPdszep8EX94bqWE3Fph42qCcOOzvq0oyfg77ps3aYGVYjjk9cvTwcZ3h5vd5\\u002f7DxtvZOxM8E18tl+mDUAAM4FY0ez5+rgbSM4FpoCgHlVbyM1RaYy5LruEaV0o0GzQIdg4qPEti3Sq8qYjHjNGqheEflqNBzRy0HiUSAIQy7DSIA8ccxx5HyCuMYmhoCa3JFZE2jLIfQfkhim5PlJ9xi0OHQedMtTbxU6x9AcutOtIwGLYsQGeuiIOyB0p\\u002foS9dRrkHzCzdOAadRuLsJ3mn5kikgeJ3bFYVWOatG1tI0k6gYmV12K9nYvft+qNJXL582jN35QSUTvCRux0EF9+gOk\\u002f9XzRcqL7v2U50Vfa5oKGtLJPQMBbyPf3dy5hR+fJt16QuxG0z7oX9hTzTLb3RpORjwpCf4PDTm0HciJGZl1j20HCEGleEbmhzFaR+M5G6aYFJ7BsUZAV612Zaqg5c6VnEvo5ahQVKe+irJEHRG9QSYeOzw\\u002fWF1E8itP2HryMAu+DJU3Hn88IlcgAHGi3G6u1Bn8lVVvP\\u002fMXvdgqVf2z\\u002fEVLQ4m6WBAhslv1311NzvYoFQ8CL2KpC+Cow1q5yYJ42n08MSclWR537zPEZTQxXD4PJvtdAKSQyQOTPgkMJkNXiNB72Yt2Plmo8b7wPqToue16Oe76yXM\\u002fEo+PbhZlvgIQSy9RCVPHYlrbOg8FoF7gET1Aronx0K5ulDVTvCQY3nclRjlyRwixJBvUL4iD1jMelkqOFLegFM0k6ZR3YvNv2Z9fVqdvu7tV9MR4s6coAEdyP1wPROZxngP60KDOP6j6kFz5ndhm7BVR8eFeTzAMbykF8Ndedj\\u002f5lgdPh0OuWisgm87cfCiio58NwS1rfkfJRwGvy5p0mq7ik2nXOHz8Y4BpZvlIAqBW7JeZrRo99OTQgV30IVqcKJ5tiyru0aP2MLJBXx1nAS1baA23h9mYFadJ2pQqyuNP4sBYdTLCyqlV89KS7aRf\\u002fox2Y5EG\\u002fR1TS6TpYA+v8XkB8T0V35leX7xPijPUg95vIA3usD73gemyIWyuRUnyL9seXkyiKjiu5TKwvQ52VTsskwLry0afr8meu5443fqQ0DZyTirn8YcOSGtdyQ4L+kRaUrGehQ8jO44B65Rayb8EfrpxjyL8tAzrSJxi9BiiBxcR6Wsik5ZctPHO6z0uQshpcxwYSZ0hufJrsTNEO2f0mBMyEq8EdSfGRx+eBUMv40F4ARfMB2dt26aBOXSjEVDr5BxeVpnzYBwNg+fbgbb30WdKqij5cij7j4Eugt63nGe8tyiEZ0GnCSuQ7NRk1qtqqIM9OeJ2eV1AEA1gsiSLfc+P83fzexi0nYkg3udt9NFJR96waKGGu4d8htZLIf9d6kPIFgM11\\u002fe3dgU7F03146xfPDzZ3Y0+OywnCSDtHNuY7DN03h+GPzhtfONDNDbHsPJ5SGlErykIrPBb3Xn9Y83eBuPs52lvRRAMj7Y73dqArsLg3vzsPZaez7rpZe+7A96a35\\u002fYvwhBfDiAC49ZuPOD+FiEE3bn6vno77teNzb7Fdj\\u002fjel1451YfGwibHXBN5d9ptMFjX+0BngOCt9v5eFmyzgXuf6eJ78KyvFBbNp4QP3JANZ09Jk\\u002fHs37BXQRfFHZeNd7NRdrNK6C03iogEiIF1vRcuFpMOooEKFlIrOk7cPosOnKiqS+QvGuD5yuDdIBTT+y7HJcf\\u002fw53U\\u002fCX1yulfGwRS3yCJ1Qt64K0uxSMfeb6a4l\\u002fdMqrLzxFkjcj5T61KgPDlpLR8+c5UzLZLd5eD6L+phERAYCdOhgvwLBt6n2K9kDGgLUtVsPdxC+COD8MAdOt2Q7Usznrt\\u002fnCAaAK2BN1zTs40v4m56+AkWk\\u002fIXLflr600FVTX8nU\\u002fiOHJbH55BaEt4de4N9xFvenP47obxzFU+DeL+PB\\u002faY+0QMGoK75PjqYQF6r7t0Z+81bgz9OQRfyl07SCrPjyM6X0h0PB\\u002f5fuYmnB4DTjzAcPWysZMxdmXtFtF8bJnDc2LzBF3LEWFYfyJokNyTaeHZZ2B047qV3omPC0WCNhjzYnJ0AgZqGEPCDEzQxNHDzw\\u002fGW9tvfm2XEoiYMd0qunjLVBjiOzAyx+KKIoGbBYJlpfh0f+LzC8uBSRu7K3lDKodYQqglILYdlESDJsABgLjY+LKJ8Ep1aeMrOk6Qv95Ni9T58atv7LPHqqzIpcvXMa6Iyq8\\u002fPyqsoZALjc8KYpu5m+9LuB8wsMVqRVmefi3X\\u002fUeshKkSApbIv21DBm+0PDmABwj+zwDgFCAbYKpaimMHCI3FsZCWBp4lCaGNHyPknsjNoSTuVFZJSNadlyShhy5Nf1cm76kBxn0TEdw7iyeblU48Fd6h7aHbY5+lVULgIPTEhEUM05DPjGwEQB4ricPQpRs2ZOa4aSd4ni5bkOtHy19J+vZTwRF2ORuNIBx7VvB5HtbDY4BODoCtSLLKs+8\\u002ff1R20nF8GR0nCI5NZxKAaJTYqyNqJDMO7HmNSZSqehvJ+WD7KgRQVpb5MwbX7\\u002ffxyUnBC+Uq22Sel1\\u002fwGNr+RqDUruvhNp68OItIweHtHcgnSRPsn0SZLhwzfZqfXa+1W8bh\\u002fY1MbdS62cWJKWuHDaSnno9KtMHIQuH5ZmqGjRFPolxgjP\\u002fu5pg6Y4NuGbwst73xemVZGNpmrD2AlTKQ6XSI+uBeKDAHZx\\u002fbrsda8OJX0VV1N1oG9+Oxz\\u002fSZpLmfDBrg0ZqgLK2Z6C9ZksL9FvJ9YYKbeEDAmwFkQPuLvlnQcoPHvTOFyAfCzNgjYB6yZhncIrDfnST2G1ghr95tjwM9bM07Ye4VTXw1t+yJ3Q5NOUQwZrazO1fhYeuOnSB+nyhsuOKGZisLJ3aL4HWaVCigpTQFQFsrSet3Ij+ny388TIgp9uQLoQYlzhKyAqTVYErDJyXncrq6HV0UzZ0eKJBrXL65\\u002fjNOmc4Pr1IzqtokNqQzW0S5v6jmdy04+INIu4CSaFPck2TlfHuIrasHfAwjk3rp8zQ7Z24I62wyXI2i+20yAyM7+O1Ztl\\u002fGX0XZaxStmH++HMhqWnNbzPZkJaIZNGJMpSHclOdu0J6Z0zyMp4eu3PqQwiUYwEF2cmS3dVdpdnrxzagmHfqpH7d58BSgz8p+Z3oFxVHYEtJjSKXvdudoR7vCZ8V+c6jJHg9P8mRRa2XpeAwfcvZsPe7vzuHO3zw5S+bNHtFw3zeUknN\\u002f1riFx86WrG7qnx6jzY+87ejE02sI\\u002fq85CI\\u002f08zxZFEc\\u002fBz2PwETSnWyayNM5DnYcsI74XDoBw0l7tKE9ovEw2nlKBDzPaDVVHHyNuncSMF\\u002fvjfydgB1W9SlGm+SR7Jae3xcMtahOi3kahjrXBrYnXdr2prRWBzQQeRn\\u002f3kYpEijQMSugZjL0MKd95Urd6AB+BbmJe4uB+ngC56h5jn6l6vGOH6P6xPf2YBKdjcmjKSXvNoOkFlEyj2xrkH2lz\\u002f+2u7m4PPP6TyXBRoNj3XRyO59cgVFuuOFQPA9Pb973pyfPSYi+YOy7zSfnGhWWMznfelVEzhj2JvKIUfRhWL+4eM0\\u002fy8dMQcT7sp3On5SHdSjG+dlJo4sOm53FpCyWmSeUl1KWw4yaeFvfVKbyPG8+id+9OxQHKXJEoXx69UI1W2BHgLxb0TFymOC\\u002fVPYuR9HDcTddvWgOj58gmjH6Gxar8cd7KgorrF0FatPiBEAV2PNpdTaGf1JTr2+7UsFTNwnwVyHqjmANwX8BgABBuBBtSWOJfKAQMOF\\u002fRNubSJtGecv5+93h3A8SEb4bojT\\u002fXHCVHXGn1w1KY5jFz2M8M\\u002fhI3WF8sYzvtuqjh18MRLbiQ2qm1MLIl\\u002fcUIDrx2tepe4jBrJXjTVCsOB8Pte9PNE64ob678yqDohdZ\\u002fUjt1YfkTRvKwXm4ixBogZZTTJgPzFDE518fhv0A\\u002fCvvMmJRv9\\u002fQoBOWQnuMjSdRTCO9q2gplRc1NRhycjUVaBBcKVWhERJTtu9C5Q2JF4Lg6erLVl8DMPalvMjOhBCfmkacbEVNfkm+6aXoOYxsosnwchL8fPiH6fMlrzHU+SRM6+LhMMIe16eM03DWFeOALDkqpMvuIqID84PMQXzYbXwv2bV\\u002fPgkvEhPew93hUPSeDG08mQZR1zE6h3M77Eslln4sB3mYsdeJq9\\u002fb4wfd\\u002f4ovFmC2Gx86+TI2970R9+JzxnTb8Zid+WEajd2EthsuB7Y4k6cbOu5U1eO6nl1D8F8C0jNNKATGJSPQrwMczdh8iDZHcWvkGKDRDr6Jm4xe7vc3KYDiIZxctv2TRfk40keRXsYZC\\u002frYoC5TDZrPJpVu\\u002fCHrWJvt7z7DdDYxanibn\\u002fzjqB86NoQ4AXbBSbc+3phwAWnm8zIFCtvzUg4RLBk507DE9vxt+d\\u002fsdRS6WPprocSZvdBw9mr2zHld1dcIAZ\\u002fTxoRE9cxlDjcSHhLjx5Ppbbl5xH3QlU\\u002fi59ScUkQ5RX23c2AsutvrAXsUGAESPHjhOWaNP5kkJpVa4WyCFLr5\\u002fHYeEpLObg8mx7uXV\\u002fOhQ34UVmNvnaRKh4iO1EzimdLbphxCE1Sk8uDE6ckQVvf3Q+LtNcxil+DQetrWqu49VjzQpxfnSpWiFV03LOf6WELstLVP55fO4M\\u002fx\\u002furR3mXx4u5QxracPV0d18fMO3t1+bvP2z8q4e26f9AHysLJEe5ZxzsqQ+95loRmfFQAb+U45dPYxfePH4SvpXW\\u002fEi8h+C+nIDyA7iISXpdtHPQSqrp1Mb0C\\u002fn7RWWFoKoItotEEXir7OHqbpnKMY7ojcjUqCILNS31ZO1LGrX9FWSSZ5CdSV03qiX3SjY9Hcf277MSxk861rbJttJnqk1W6Kutg20g8Q5kdJlFsmtH3LEX5Q\\u002ffjKA9O2VP89aMdoflZtxVzv0TBYgKgIM3SzzgFGmnAkZTVSZ63Rh9MCQWpBuIhdBYu7rZbmp6JsZilrjmCA3hDeBjjU1KNVWr7toi8Q3M42buHJ9OFTy4tHWfAj2JmqTmsjw7LPFve7raA4OUk8kiDzfPq8T5fMZrRXddOYDYILGBftr0q95dZ7rG857kbj9uH2veOGKRsYQbVXQzRQ6g\\u002f78uZPz0hywAehQk0jRQYb\\u002fYDQuQ3X89fnjx\\u002f+LT5sHv\\u002feXw4Tc6DAWkylCgKHZxP8\\u002ffrt0\\u002foJWrtgxjs\\u002fJHxi9OyfjBND3kyW2U6qPuxwaMc6URSDZR2h8f+gaXkkv41AbrkkIjoviV4YuNy2NZeBDx\\u002f\\u002f4CCRTDxDL2pO7narqFY\\u002fgnxJ9jlDIugbiTNlsf4hu0w1\\u002f1mThPb4dUGIulObVj3MJ1e0+vVqDqELLvGmxMZpcllGgXVeOKxDxXYVqZ4dv78uim8yQUHGIOW7rMGvfvCn2\\u002fVzbaCUdilqM+Sf1IXuwM7Oryks8WLMPMlH0EFInpoqh6zTb\\u002fgvqfF3\\u002fd98BTPWWJ+OP50efFclmtAh71U8+nS1pkHVtUjx\\u002fNeVJ+TNNnXL9No\\u002f0uZjcea\\u002fqJUVSCMilUgNBYEaDJPZbMgCfbiDE08YI\\u002fFB+iXozrtC6XUUJmjTyZwEHMMat\\u002ftLEUDmiQsD0Nr616FbfvmBJ82dr589ot288fMPurhvgmzbZfA+OCGbnjUcQBpJnP+z293\\u002fQ\\u002fbt0b0Xsuf8vD7\\u002foPZ4cNqTHSZpxfP2fMeN5\\u002f87+ZsSSXTst2IfDq5S6JX02F+HEcB5LZ8zydpCnBi3C2QmL7KxAlCDTl79evjzRG4h6giWmkSMwRbRLDQF\\u002f7jss0uysmausfwy67bkDgxjaEc9h3+xZOpYJVMFI67EJ3+WUtwpnQ+Bwc80ibHfiZWdSxxyb0rmz3UaJ3tQ9JZ7ed2eWxTW7ez4GTW0dlsFauJs3O9iG\\u002fIH6fEHb1UJSfM4X8\\u002fSBodyj44Wc3S8exAPt3Ix8B7Osg98QjpPaymHal78\\u002flsXHwRBLfrYZNYIOtUn304Do5VDPcx5wMwXCV5REZ8M4tmapzLcsKZuAN+Cdvn+bN\\u002f5P\\u002fqD\\u002f13lo\\u002fH1tDwDErj6T5iL9gvJqZbJ35mukofMmgSxWzTNClbhHPrdDQaVTTbLfL1WJ8AR45IrSSO\\u002fGLvAXoS2ssli6zBs8UvPxXbyzQI61D012vZ+mTx6ukvNKAbeavb4\\u002fr+uwkbh2qHJ9Pft8IOT+pcqOb9+TIrEUOuEu0RbPO7FcyyXbkbUthO8cuuj39Q3z4l57d9mievJ8OQEEY973cm\\u002f\\u002ffgw8GVj2AHwX8+i6k\\u002fUKLVDOI7RzqPpwrsp2LSWt82hTeNS3yTFs9wMCinCfHQdJDjCZ\\u002fSGPV35WHiLhU9+AWpkBckw7KLtC88P9Db4mx5xYi93\\u002fzcpOCh3Lygv\\u002fLjtg\\u002fCj9u3GblaRK+o2+bQ2JOJstlyskJdXxy+NXQQ5YnhVXEATdJ4gz7tl\\u002fzJyXr7brnkDYKjAkuX3R9vg69fpPXRITUOxgFajoeUTqbwRGBY7D\\u002fR5YnDpYHbdDgZjd\\u002fpiZd+N\\u002fRPJKJoLKwUlKvXk+n+kCxCvXVoxIZ1xjlaLtVFKp8OiTS0pgMHkbIIdZVx3mA6qccGV0gzZvJpdvpu9ycjo8vpyoe9EyK5eHE33I2fD9uOJ5cxcfUkz8bmsKILJfx31UMYREbv0whjm\\u002ffjd3F0OvF5\\u002f9C9w3YcF1moDspr4Eju3\\u002fMUw9nzZ\\u002fXlp+EPHXx3Bl8\\u002fu\\u002fpKqfbPH7\\u002fnyZDxf0r4ngsk29M6un0Kc6W4SxQLB3ygP28e\\u002fSibBT4E\\u002f0cAkBftp07dD1fAYkD6l\\u002foX73gLsMDjIWRpbSMoYXLWdUgnHTdKVHH85RC0Kxh7mI3HQGdeoNZQHCTeTNqTz5RUevxLkN6nfjAGfbPL4udi7MTsc6x\\u002frbHBdD+oB5+DafIrURxb2qY8mvUreSLHfvv4EMreeUnVIM8bfBO6j\\u002f3jNxEKG9zHMcSzMNe8JKq\\u002fpfOVFhE2SrDGBWekW+ves72BCze2XQ6VVvBamKfT3zp1Q\\u002f1yHnzddkWNK4XjpH7csTQY+6zDhddhntQWwQFJQpm9JyHJLn4J75VhW0xYqOimU6k\\u002fHZAu1aZC11OdhZTOSHKj+hjT0zBZJk\\u002fL7taLrw6Hjx8PROPmPJntdm\\u002fipT1+Xs7Oh6ERjK0GuT5CGgTbS\\u002fzVPxzfLkC4hzovQxSCvdGy6Z6dPamGWwnZpEnGycC8\\u002fV2NzyBbTL\\u002fxoN+Rpvz83Q5vK3RxQfpluLgXNI6KScNtjkWz4jZXDGxMZXvyAjYEoGdeV8Cr+7aiuFGZ\\u002f7q4eJN9YsW9orM0PiHVdc29334DaEsLz10YsYvCAsBAqUJ4B+bySYqvG1tF0XHchusvjsFWozLiaRFlnko+oR\\u002fD05NPn\\u002f+Hly\\u002fPEr2C4Y9NK3P2i4YCqNvxUC3RJcmqjI\\u002fRJNyhuHeu8jckWOwa8izBg1+Bsf06mG+3XeqAy8gqCkLoGjqOMRpQS0jne+h2RFeHD3rkR4iJEktthkpXk1R7dZaPR\\u002fNvqcxW4ReF+bMf\\u002fRa0HkUDS58BPYh0eZGx4s\\u002f3moSLiYgMO9SorD2pzBQTuGSUfIHgcKjBkqwnXnwUBgFihWWORjgYSaPKTXL+1f1m6Pq3yxOx236+E4feuefxXNXleZ5jd5kune\\u002fLTfvu9WnysBVjVS7nLwNC9Zuqz1yWrjAd\\u002f27872bjxSSKQbsW7RhMg8fo9qW5+Ha3mDCGdWoH03G3Xn9HEgB3v+bBgxKXt0ZPfZatM70I\\u002fT6PSLnlP5WDgcA\\u002focl1P0DwX7zMHvrqbGdTBfYYOO2rAA5YJUzjo2Puhf2L98kPycZ4qZQsmodPK3GLIfLiqe7f7yuYTa8erPXd4EHVgfKp+F3d\\u002fBhGEydNll8KeSMiL7K\\u002fvd29w+qn5clFlD4VJbJeyfweBIJi\\u002ftR8GXE6EOS6+f3x7hF\\u002fd2y1xVhrcBZMIkp7Adaly1P9jCjKmc5fT1nSd8Xb3cMERUtG3svtgSpoM1rCM+yk99iLALGncGJrf33exkhA5IMw0sjAmE2Cnutl0dwnPqYG3123jRrAcnE6T9K7aj2PWXmsol\\u002f9Y7zXVO+0orYoaZoP6nB72MZxehy2WLdn3m\\u002fK3A6fP8bphcaamvrLk99Bv9tvH10rBSeEwpjzon8k1t+WArjzCNc\\u002f33\\u002fg02WU6iSI3U1t43k489mj98e7f9ecnqzYbEXwh3b9wP50jqZL8y8UvA+6xfTUZuPq7fgPMAnpEfF4vi7XAr6voPlt8M9TsjiMf2u8IAVPdvhPwYN3xyk+12fjFcT\\u002fFw8dIMFidDlFIOWK7RhY7VoCNItk7zzSIY47aTT2V\\u002fEv5a6twZrER3icyBATZKKlaU0TmmUMEyBADVyHqSeOQ7lPgxXHEWacJYdY\\u002fRbjIzR+HmbeTL9rNqcqTFjomAcIJCNDaGxFyZnbae\\u002f4cDslxg\\u002frzoWNIBje+NPfkQckQp0Hz+LpzkKnzOy7H29g\\u002fJh6+Qz7kvRAxIWp0vm0rT6fhk\\u002f0YFUJ6nnjEbQMJ55JZfuIvGwEaOITf5pTobblbcDM\\u002fvH9MDzLFt6DarP4i+UU4PIxjmZFCRxJPGe\\u002fvHyxaz5++8d\\u002fX+kehuh08hy548FRu9Ymhg9uv\\u002fKnaVe9OJu2\\u002fLw4dnk634v7w3aTRrEVcZ6dfP\\u002fub1KPB3C92x02yyev\\u002fIvSk2eYJur0bndXJpHZv48pBmjd69bY19iUlFg\\u002fnZLgKieMbkKYjH+EP+NjNos4cfaIRaJgBpPekVaJCVaFR54GgKuwGJ9Z9H5A348+g8F\\u002fHhvkEb8Vw1xHJTAOVDafDIL5g8w8CEV9y6aLBRrbeTreH5ODHT2G4sqgC5XusVKnw4sP4uc8f920+zH2fVsTKYFTBl8E8y\\u002fD9g7KwoLlIoJ30eE5YSNtqD7J\\u002fWgkgRjQNIh9vfd53sneCxMA9uowaLTUefnuumtrV6vycvbljNDQ96ivYVUfXc8s2pS1jcHAB6JDwPpl02G3PFJTNeQp0cuLaTmmjMJP7fcpJ4nL\\u002f+LJv+zGx0dnnBbYtZz5xtUDAl3hE4k823oL83ZzFGo2ne8D56REEcn9OKKI5x5f72+Kpqvaw655\\u002f\\u002frpVNLFXp2prjf4QyOGSy\\u002f8Xfa\\u002fQHH7WH7fFQuEBpb51cN+lBxRhL3yD4\\u002f7V08WujoYGKdstZzOdwc10goCxlg7iDLv1NG6AF4+trsu\\u002ftPC\\u002fhNkMxsKOhdfDNGuWx96I\\u002fWT8ynicfjhcFdpPUPeiQu2rl9bPTUiQ9nFZLE20qqttAPx4bpdQ\\u002f6\\u002f5yIWDGdpWOweAZjQ5DSSXTCaAdAjGAHR04nLUj5+4Ao+ZHzVj2RPoH6qrwanmnZPQRM\\u002f88ddAgLd65GO0R5Ufk6GO7QAqYuY4HyKjA6qM\\u002fiNVw+9tSQY+2jMSDwPTjAVSmcQD2FspFRAG+Eap+blvimT\\u002feEInyXz\\u002fOg\\u002fLj5Tw1nwqwO6f9Fln9fvlE\\u002f8WazFMSyfUPhwm6xheypjPyxhMBkPpvjN5OluHLOu+mzw189+pzeH5GSp1TidpnftppfWA0arQaGtlF6YR2\\u002ffvwvAsnd3k9kyJdnUD8F+\\u002fxAKbbJFNO1bwZRLvNluXzw5mVw\\u002f3LhEF2XJtW4Aeeo\\u002fbVnuh6XWbZITStVocqfk\\u002ffX6JLs0eri+e\\u002ffq9FVXFjjFHfKmADlmQaVv+sfo5CS\\u002fbT5HMak6j4lGlpuh9uNvnk79CV59+PyH2cQot9orzOPHhJ6MbQPcxpdsDRrFMbZPrqIgh6efh6EXXYE\\u002fzzVgeUCaXW1iIhjyj9kA0a6fgoBGvtNtMz50IE\\u002fi\\u002fek0TUy4rOXdh0KdQl6k9yfBYr1JQn\\u002f9Dn0EyoT+Avur\\u002fcM75RJHAtYdFA4XOZ9YPHv6qu6O43jtJecMhb8y\\u002f1lN+iK5zWT0c\\u002fU5MSmPk6pLFOuT+RhyYEflanjAY2YufWJJ4lQtVokawPDZ31tRjyGjzU\\u002fzTD2irZqeWO1E+zjjMZyIRmupVpzVYS\\u002fH2Jhhn5j5z3Tt6YmVQzTJNtXHDCw24xsWLWkLJmGOOqHQHhwE42ejd2fup6znF9PTVs\\u002fTLCjrYlcUmcOHO4G8MUEbZzXmkQLb6SophweZKgZcPI+3H7\\u002f35i83AZSHH\\u002fHKXxTn4\\u002fZhufqmBndWrSpXMqZH109n\\u002fGRy4fxMRHfvb24HMJG4XZqvBn19iZN7clP3DUMF9rluV5eTkydnWfvgKvsHHyshllsPHk++H8sPs\\u002f61Hjkm9gk9rfRmNGoaDdx\\u002fZgVYzna7wm4HeGM+2fWETX99WpeQ\\u002f1dzSMyIIfABb1pQa+2+\\u002fALF75Kjdy4DWbS4RCXo45ee2PlA182ZQB1ewUlDDalf1X4N8CCoMmMhbocUMB\\u002fM9OqK8Ufbjzz35og94ovE+9CHtv9eefEqOr3Sk2PcjA4qmzrkLmx\\u002fTcCA\\u002fK+mGpe4Yu5BtR2qMiigu5jVmhpYpo9Q8Wo4q1DlDcer+ROPTwHsetDpZlACTT32UNYtLbQTYNBWe36eruIMjqr19dChV2iGWZdenPPI93GCXFGW+Vrux\\u002fHOT8oP349nZ2cONrPJ+e4WVPInBaqL7KTWHlApCrqy2z1NJ4ZPBOPv94+vcefji7OzJ\\u002f\\u002fm7\\u002f77ZMXjOpZj9WS+OFDVt2gaGgSeHeRmV92+uvza6y8s\\u002fqFSZZrMvlx9+e7Du71sBLR8Pms+3Zyff\\u002fXm3b8N0Nm1261S1m5Ncr4IwMn+uAP722er1YfmcbV8cZRqsDfkYEB0fhw7Z49PkjnxMp\\u002f5fhscza6kbbOvsMLCGxbRWWhqphVE\\u002f7vlJAmcDwr3CQiQ5lxEYnRfePbea5tkedHt71T6Vd9+8PxLsB9Cvt2MgndLNA1mQdyiokWG3iWq\\u002frh8eikR6VQ9ndJjD70kvDL+zIxmwhoU3m3\\u002f5PQLrh4n5nk359iAUAYwe9DBHLed8zehyi\\u002fJpUtMo3HC52NZfSi\\u002fv2OH05TT6uTKD7+tr4kjv1yeAwmtFyGPpNSIfrwvHwcm7rc\\u002ffv3kfwqOpBNbEx3vlbcMprpTfJo9gX6tHaOto8ksXoaeu+DTO1DfPu5dh+OE60l\\u002f8\\u002f7xfPpS9+NhX9MT8Pnnb1+++EoWJpjzRCzuj7dt2CR0RQjOeL8bP4A4m4g4lMsPh5+zebJ2zlr5NM8iaS04NNuVYsDHpm\\u002f0Vy+fyHb4dP0Op3yWLUKebNWNGSBXAQ\\u002fyn++\\u002fk46mjC391c+7GkXbDBFVLer4MEsmX7P5d9X\\u002fiOU8ZLNGDF2Nu+jzHCgWnqiHgiye4WDChgfDQt2ZXV9IqaDv21JmU4UDGUYXcPJ\\u002fIujRt3zhXaQ20FrhMR5TcARt6CTo8KdGQUYnkqsl9qpPu0hdwVlpnr4Ej8Nw\\u002fGThKLYm56n+5qLe3ETMs7nIhpEMXjCdeD05EjsR2eBXtb7Q9M1JnIZ8WpHot3hW9MeQLPp6fUvKiQERPQCePnLESBdD3jwWiK54HjHQ8iZYF9sExPnyFz8e\\u002fs3r5a9ZKAUVooX3oqQo9jqQTmDDap\\u002fnzU5gzdNZtC\\u002fKRZDkkwzRtj52UnXGoSS5CnA8Z\\u002fhoqw\\u002f7x2W+woZXtsVum+FUF0iOaHDdB1GQGY+sOQvO+QZ+9+bPL\\u002f+Tp\\u002f\\u002fp6q\\u002f\\u002f4cOP5UQFqq8qxT002E\\u002fGn4bL8OGnzyc807CVBMlDPJtGH3dHTKL2+PHFq\\u002fMgXm7fHbzMfzKZ1mIIkBvwIAz88HjU1SFOycX8G6O3H3uQAXkoh26yQG0Vqsan0VOWtrQ73kkYJjw6flT8Ksoqv5wPq518F\\u002fAciqEokfSKXYn1qFiIICQ+O4niHdQIZv+3f4Eefzyc7IH0uZoHeVyYH5KG1lwBkU20w6w5VAYcAcAA0WSevQ6e9vhOvPfXTyG8WTcrjuwc6xrR6DwSaSfq\\u002fVCJyCd0ONMuimdrqyw2HHlTXgyolvbLl\\u002f6yHm4nOB50R5NV7ajuI4J2XbCJIHsa\\u002fKXqsCMVNEdqUQm3nSm5m0\\u002fxa4Q7EgxO822g9SjyTVrPKgjDqFc0aEf32OsJd8k8SHtsTFMDJ2WIA4+iAQA4TRPddyrxgvPT3+bi+e\\u002fX\\u002f1bGhY9Audk5jIpqXXaRIbnc\\u002f\\u002fHF61dra3vAr4IJuTtQzuBKLuBsJ4oFj1sNHFbB1Lv9+CmOkyfLV\\u002fWg5nj6af09CMIpykPifa7unW33d99\\u002f+c3X+8YrnNmv7V89Wx31Wwqyrs+1bQr7KfbOPaDKGgK\\u002f74bxLF4QGQz0gxDhY2lrdsgd9wM2qXXhgw2Zv1DRn8frv+YXN+qzJCEYSpZGYRfe9MVN\\u002fcNJkHsmG4w4Bvd+8CsfehD83ycAlxG7+KvkC33Y3JX2sfjc8paYq4g2krQdU0DwSAxoBL0HovxZbpe9ft96sZVGNuUiz\\u002fbqxq9PSSAPaAvee8GXl4gUifVdvA\\u002fNTHSx9mUYcix017Hl2bQDLLb9jSCnB9+P2xGK2kKBvj8jX17m0U6oBIZt26bBQg1lOplaMtaMOUpE\\u002f2AglNrjxBDUUBRSQYXuxWh66xbTRQS5E+EoTAfkb188vbl7HNBx1z9eLp7N0Lmf++14iFiONWmOdUNKA4a6VVVd+0k4qMOu7K\\u002fSZW0IJhyaFqV+jr2x2c2XrwiUjIZtC7Gr3NiEXhykV8XYxRj9z3\\u002fxv\\u002fpX3\\u002f0r0d5VElNbG4uWpy8fDz\\u002fJqlbGPju7Ymp2vf1+SN0T\\u002f3RX7rLoi04+IhwIcCyKO08FYeRfg31\\u002fVP\\u002fxN\\u002f8TvKWirfDUGhj\\u002f4fZfj8hxiBUGXCY0t92AYK1eLF\\u002fFICrULXSRbd3Hjx\\u002f1ZGfBas5RI2RCFiA9pj0T9jOhffnP5n\\u002f1u+W\\u002feJGf38HPP6ubt8PbCX896mMR9GS0QHlg6MUEkBjMmBd44lP3wwJp1+9Y6PX++LAbPerhCS7Ghvpn7MtpJ3+aCkVRiJqrQ\\u002fqYe1K6Lwr9bwFYLDwajFbo+MZrl\\u002fewXby2atOWP9gITZKXIf2FHW3V3fchC6Nz6+\\u002fh1BcyYYoyx8pyz8mEsqAfNMWRka1vV514iGfBIgUIsR7iiRcZYbnqsPbWXXuUx+1tlybReOJv9WbyqGgStaKp5VCYg9Y65RxJ8Z\\u002f++n\\u002fz\\u002f\\u002fv5v3lo0Gl69dluuCeWIJgFGURTBU0N4tRjEx8eilKFtW7VJHruzZpud9MNxPr8\\u002f\\u002fPd\\u002f1eJLaYyUrZJnS10aNlvl7\\u002f90bwPPXvln360rgf4UNSQVR4ADu7pOGjv0\\u002fboIPICfrot\\u002fj4KfjcFMMJRM2nZFDYHL6PJC\\u002fcK2mS\\u002f2r873I\\u002fm8bftr64o+8l8fmjePg19EuNq31Ian\\u002f\\u002fm6rDFPRy3fae8VRfdcGNc8HyNpuQJ\\u002f6u\\u002fzv\\u002fFBBFMakTU492HWcw5YKVDsFlp2wNQAAoS+\\u002fQsnnF7v96AhC08q4\\u002fe504o2KKAnqolLuRtrBf0p9JcRUmyAPBgWnkIfrSaDv3IdJXTXz+iQ31qejki5wUf9LgwcPe3RUHSV5c4iSqLNH37YbNLWNabA8Nnjwc65ZDH1zhboKJxzX0+\\u002f1Vjii+nAQSuUk07dvM8ZwEy0lQahonqxp7qxdgEq7Pgfn07tCGP3JPnl+12yM6WQ92qUUHKD7udY6BfV5Ck\\u002f\\u002fKf\\u002fGfekICeTVEZKERNMMU85Vmngzy8HI9v48jIoVTjSuyOCQl7IireZOgyj1keVzF68ufqe0eaXX+cJjwyfrrKMeooS4+ke+gaFr3cgbVOTuPay6FfenhsnNW1K09WgZAC9mhPmHqBO\\u002fc1eWiuFy7e4GMaDEkc7MrFfvzZ30aX\\u002fvMRH39W+69wABjb1YKTkAPTYBxbi4\\u002f7G\\u002fcRdK9D20Xz94l8\\u002fQbQejyu\\u002fBP4v\\u002f5v\\u002f7f\\u002fNPCqSt+307r++f8tfgzH+77uiAPtABcNGi85SgCAc4fr6oiA7cApnxzD8uaBzudzNiei6eF9ndrMmz+fnX+QBte5Gn\\u002fqxeSk97vJtTehg8QSbJDMM996wD7u0Nfo2V18raLLSTqDfWX1tNMjpzIMYFDjB1oFbMy4mmTTxF2W6w8lk2l82rcgOEMRSXE1lmPZYpVkX0atpqMxAS2s8F3FYOB7CRpB2+4+H95F82eeTylOCBO5YlsoXBsklGqxkzQATv36+W9v3v+7ew\\u002fmJKo7m57nth3soHfHwzcnX103t2RCAVOR5qIvCD2h0p5OMsFILwSm8wjBt8c\\u002fYTs+qJ6Dch6\\u002fyoN4GvKhUjeH3iAzmc7N7lNDyOMozhE5Ok+U1cliSlFBnBgO43Q5eXtg7dByJRaz0E\\u002fyAJK26JZZGDD\\u002fw\\u002fvu+\\u002fZTGPnN2CzR6MervugPpoln0RNv4tnwbnOomElptdkbn+oOQcInyHTYwGFekGV9fLOd\\u002f6vy\\u002f1EWUQBPCB0BDYzvAXkA6enoKtBaRT20BE3dAqxI+\\u002fWikF1YLc+WHdtUogTR00l88Rxe1fXmsfkchtHHxx8AMzPHqribT5euQzVWttUo+7qtjzvw42l0uucttV8vPCQP1YONstUR9sVp8M2n47Wis7P5NIAbYzl16W7dOP81ix4LYTClGTgbql4pGZrFbJJrXfewQUkERBUo4rEIA5sA\\u002f6N5sxV3v3n9H+yLj6IyIKQEmKauXU+bQLFocSiYh+4Y9D\\u002fdHv\\u002fYbn4Z\\u002frOxeK+9DSpmXV\\u002f49OLZ1QIzMDFBKUfO6L5vSAVJ2OWr7FiXXgC1tHo8AKLaqlYMToOkq\\u002faW36Jw2tVeLycjtaoqz+LOeFk4yeT1416sR7BZZC\\u002fr\\u002fdGGOztNvjx9LrRv0Z8DGpI8QLU4+o8j9M5OyajJ0APoynQ6F9ImupdJ7lk9RtD1GChw8BtGe38aNcf+nXMyqr5oLjbZWrLbvFgM01aJlOxt+\\u002ff1v3Z9DEDTm89hl7Gs5eBVO+QYPfShmcT2hND7dQFpOjMMvZDbauuX0yGlJ5BZv+\\u002fTfWRWd9vfB\\u002fILgRZ1d51jxkOirUkic+j2ODqgaoZwAsc7QtCT5b8wHYpR1dHDdviMzeQsnw4HPOMvzb6eLuIIbboWRNl5wvIZpyB+7FgbKMbQMp3FRXunqoAz5Xs8iODjR5nRE0Z8iLski6zVymw2VXlsD6fLr\\u002fYNPdbWXznPwLoXXQAi2saWYVUZT+yO+F+++M2\\u002f\\u002fsN\\u002fez4NWv3u81ifiVfx\\u002fGfszgEsMFsMGCBfBEK19V4MbLa8lLYqqgckad0L2cdhGH\\u002fefgq9CyOqENrSmrJDUW6cGdxo3VD5gbNu1mkWj92oRb54dncLOHMcQyxm6vPHe4+Fy9D1XkxqMya19sPyrM33GKS9GJxqeWim3Rkgg4tV5wgGfBmPDqgWA\\u002fDg8gnsq\\u002fUkoe4Qxf55ktWzytvSpMCXg3jztV6jP\\u002f78\\u002fae\\u002fN8Ouo20MjFNPNnC+kAKC+p1RXZhHoffy+\\u002f2mLepzeoSLh8P9u1w\\u002feX7qPYWt0cgGkd0nj+azl\\u002fU2+4Ojm2WgjxO222Pqdd2wkh5\\u002fOCJv8HVUNebx5Cw17a0YvpdgD\\u002fs2lK89jxblg7F7xN+i8NOJe+ioPMfT2EWxXx0PNzigUClAZ9HkELFrNuwdKH28xC6pip30NkOwP7pti1qND1I1PIAABE\\u002fR01OSHqp\\u002fk6cqtPSBHXHYLq3oRNcTvyjrQBwXfrAetI5eu9Wl6dovLr8Ry46A\\u002f1mWTSGnmA+gh3GSHap9hG0s+w73mpAGsN5P8e4kly5V4xzExB9ogm6rvgVfEKaQtXLwJAwHcdsOVafTjj8eBUpjiLriKpr\\u002fL\\u002f\\u002f5\\u002f4GqBKWRxtMsMwTa80VEYmRBC3gxqLun8puHh7HvqHbJgBJA32n1LSQ6iJuI1nMWTnF6GuQg6lvTh5MzhE8wDdZt+TOkk+R5qJ2P\\u002f+hJYYaMvH0nqI\\u002floPCX0xAeJohvf7o29jr0wckvVmjw3x9+YGlMmUWbIZ4ulqtlafuNvWMwgiqGo1XLIiyXfHTVaIW3A8d0gaf9ydqiBKtiuNk8C3CHNtlW0Fe\\u002fEc2SiHAYg4bM\\u002fY4Z\\u002fq5X3qF5eLJ42SvfC9xO98me4CS2fNhXQ2+q0d3OZtBroqbpxegZPO2BTXw16mpbqPPoifMccIoiYFCkXd+X3uFwH18ubu92KHwyWdVjyU4eD+fZ\\u002fJ4GSgX+XJtGkG52kNu1++NiKvLkVcVmBGy+YZeD+8lZWNmtPD55EnTHprIxrlEcTqjeb5eLC+WDRhyKxCoXC5gcEKboUYo+iipfbKm5EjvrFCJL5NZX+VLI9u7p0\\u002fNd8yhU\\u002f9j0rcN\\u002f\\u002fvgt4fRzcxeGF0IfeRB2rt1wNxNwDGCyBzv0+ywgwIZag32nmPN888LirushILBuOk7CoTUzLxuqJqCah96UeXfWfexq3shkeewEhbpXuiWUMd4m9hwu2mLizMfCqCA+WQuRwW5bbtr1Av8zjW\\u002fDieSrrz7XD5ec6nq09h9F\\u002frmO\\u002fsf6k4YKU+YsGvI8fUTjIR14cchBBEg0Gb1j1HxcQPDYP8nOaDtc1++iaM09v4cTSA8TM9nd\\u002f\\u002f2Lr7\\u002fKVGcYbewIwU9B\\u002fk+lH3JsfWoYufRMDnvxqb5NoWdA24Ito6vYPhnBu5PcH13b9MJzcB5OfIeO2nZGz+exg2Pg6wU\\u002focWTe3EXBmcHAO7W7\\u002fxp7plVR\\u002fmePpiATQLHeQyUo8o3Ctt84aHpvl5PyPM48TqoS3XHGQ5gTiGlHuuHaGidI87rFGca2e2pacvqHJNSCV5AEUUOAD9x0X5\\u002f8HzoBxe1xlKEeDzR8j5B7Vi\\u002f+\\u002fnw3zs192Q8AwC9DoXXXJLfRtVPVfrg3fjSAdHTLHTOtu2APLLej9b4iRtKos7phFslfd7v6UgdcZT12OLxcE1wj1sf22MQNXq6hteYA7GcEnVVKr6bGxAyVhqD5yZ6AO3khF+IeqymLxZmc3eSBXuPbncfTs+DbvOdB12yQJuuGw+SnzkPh2ZQmwTNjWLlqUO7BE0J2vHh5\\u002fsInCfn1ce7RoAQTit+oH6cUg33Ocqvd6o\\u002fkIG+ehYxVtXU4F3bjWeL\\u002f9hRuWTOG8Ofu4NPOXZrY4eJ2nZ8emh2KTm7Wr6c8LwazywGbbHvvSYMMoZnhSwrUmugc+ybxsU4IakpzZ9pP8Gz6MP9m8xzwTDLaUCD277NoNsyR2fxoimOVkeSlqO1GOKT6blsS25GiwHYjwyNAOw5WVbGIPAeOJyyZ847CAR73I1R79rrFX3Gxkkq1txLN+1+nMQPkND6ocJo4s1NpetuY21nlMfJC4zQbixU2O6DamJOaIN6\\u002fVl0zoGJIMT1G1\\u002fsavpUWChQ7fWTLGyO3hZ1XhSXrhdhnBinAtP3Yzo3cxj72vmJ\\u002fqGQu3UyA0GDXbDsp9AAUSICUAxY08ApkbMS7MfNAeuJfhKDYgjpdHtdfrnU74jm5fqXzy5UmT6oGMX5cXPf9cVpyrbDgyufGnZ\\u002fbgEYX2OGgZm1+AEOTxHeIfLsdvtJROAsWJpM+m0UsF41iESdVIPmdSbPFiMyqrQBWARfPbdhJ5V1uLLVx+4DX2QEU91Nts2bkK+q8hEzTOaCJGDb\\u002fBmhs3bYW6KvQAIl27o2pZ7vGgMJcXSkDsNmOHI1fOXxxtY7g6ELrhAHBzVUDQGg5XWWzL1j5zpLKdEAhyMOjaDAbYEnKffcYLoxZDFrhnKULJhMusp6HEcx2bXOSR43PpFxhfbSHvk06q57JUYKYtYOcfVw9FdIhZ6uiV04xxH0pe0lAiNsCaa586luqsLmobvZbaOo3sl2nibKEElnCY+FMK35CAgFEKxcegQz2g5etCiGDlCfSs2w+hHcTesFwMfDoFy8+lp8xq1isyccpZXG3TBHwB1DGK0gecR\\u002fpse15\\u002fn+1dNn03lDWLPKVvGLn8LQr08c\\u002fU\\u002f2x+W7zZ9JhEx\\u002f54Duo+f9eFWXT4IM6yTofYhOQ4myJALUZi74BFBL9Js5iZZVin1Ou6xy00I+mDS6D+RW66nMaOksnajwPBFnqI135h6gNUWm6Wq3pKxJYO019Y9AOeWG2qM4XL2YvzxUY1mJcSiSQGOmYDTHLI0Yui3b3sC9NHvEG9ESPun6Op3K0wzuBq2IT4c6Jroxh0JQ5CfhqTnWQuMiSafCoL6DGDshd62ROzdqj\\u002fedUU5TlkKS+tECsbEZ2iBxA7yWIxpM1YOtSkfIhB+6emgQDE1Lu24npELmTLebJMdeGnTe2MPaKZlJcGoBH2Nkcd2Zg0WygZBOWHqOUICdGxXBPBrVdhA9VBSZlxUcQEM5WSbqtqHFYEpFQesCjHNPoas+2Om3pYJX+bMntYU42XJVAdyH8kB3Hf+BXEWvdQIPtQPFaRsoZNVgvm3WAfVDXn7I40U+Hsf0EHpPj3d2tvjKV7HmcOzKy\\u002fDTiKVT5sF3ofyClG5\\u002fK2j4sOc1At4UzbHFTDb3\\u002feOC\\u002fGOohg3502B1RGftOPAqwK6Nw9SumE6Adndh8OUW3CIEZiAZFGihH7ae9Y5js6FBUnVrJRAHYJ4sRZeV8NM8WjhhxBhFJDMDCzxSH9fYtlyDie\\u002f1Q6+oEEBAog5uYzXNCI8Yj1pc9gk+4lXtzGlFuTZKyh7b+IMy9CRb+cJXsFFjlaJJW+qdlHw2Cg2JpIarYd0mdHRkJjqBeWWlgSGPAm3FhMJTqrYjBxXZxIJWSmoRp7MQDvuG5GEiYhHxFX1vjpIOT804CcRHu3bjWZRABmJP3lg0Dbpm4CpWVuq5iPWkfcuwt3arDVqPfUsR9SzsRY7Bp7l7z8ZgjDyJ7vP6Vzp5PxhaB8uaDpL+qmu3DMbPSHonHsgevGNbr+kxoBpGxAPTtmzhlEZtHQaLIzxZ2\\u002f7S\\u002fWJXDn6GqfM+d98ixoCHLPWHklvSTXTnUTr2xKPWkRaXCXn27PZxDfxDDE9a+ECSd4CzTp6GvUpYsG7qmoxP\\u002fHkPvkgAnJRF61YOkQfzJp7H2+aJ7FF8ErFAgSoWzUERRW3wEblTP84DNpQ3sYFJAgZIFQyaww31sjjxRn0fkyVTPUG1QgLxdDy2s\\u002fTCItDUtTWm6TZ8loCeRInXoBvh\\u002fGR8unNbD3qoIJi3FEmje8AxVRhqIPsG9E0cXPbiXcRnAD1qTnC0TLC\\u002fHzqnJyEOKOx8tRrw\\u002fWDbMcGC9\\u002fCYHLBicEypAuS0DOUMDr\\u002fl\\u002f+iN\\u002fxna4nU4G0TLyEudFqpYz5WMdn2NPlWizWYdF34PxXGO3KMFNrz3GOsXE+gbXOeDL+B87w0QvrO6GEwiXEGGTEe\\u002f2A9VbK8srna88JsIhg02GjNd6JHGEelG2+qeMA7cE70\\u002ftCA9yYKjK4tEyWWNC\\u002ftLlqnj54hMNVBYHplWgPrYh3Vdjy1CwTj2l1tzc+pVjmaY\\u002flWS\\u002f425\\u002fbtYYw5fv0M\\u002fLiZhhDMkJdrfpKuFVm88YR36p\\u002f4EyvE7Z76uFGnzvlPrYbTn8ukWsWzahAHya\\u002f65vWG+8ZzPBj01anXhGTgWhb1Mc6KMkgXifSN2X5w+a8vW4aWWI0Jh1YMWe7FAyG9wNKCx7J0CACUoDGzU+Gos1QCy0I93UgRWJlYPSng4GvTAuQ84oo4YcE94SDjb2DtGZ747IUC6sY8CvxANKoyOSuckIxEmICQltuHpkH\\u002fU9ug6aAwL3T04JI5hmyqnHvC3BNFadyOIob8y9oeaTFwnTWy2qHA6cOjA20U33OSeDfrLa7YDzpBxZHDvoK1t5KFZRCPe3w+KI5wrvBYWQKNWDU3dgG0OgDc3sIaHD8O6siutOy9UzkjiFASV8xan7fGt7ye+3T2GddYR4aWmcjGY9qbQ+au+3\\u002fkT1W7e1wpE3MZImg4EATZZVg27+X6lQYgjXpK\\u002fzfroKI4ns9c34sdzMsVYyCGERJNcEjY7Vv08BCD7U92\\u002fiPzTh36dT2ZKHCszBqkPhnoBYhTTThE7+j6cNGOpkQ8kehb3YEgZDxehihLcaGs43XW7eDHt250YdQ+B1F7IoJH7RRQBzZQntt2YWUQcbSjl0Af+PGvq0bSEcTg20imBAMIJ61qLjIpcDw2GCMPAOF8751gD2gVKBuHeaZQf4WNAV6ixR7wKWdGjTgHC2Odta08o3llBmpKoeRQKIJveNJcgT0ZpQYXcL4+uGTWgZhvI1sAnoOva0E7d9Xx8BcSEBCMc7eCWVCKmQAJ+Zded0sPe3woSCDM2CqQ+jHUwtZ81vSjkVwNRY9Aeq4Mih9qOp81zhktMZ6dbv4luIn1hcd6rNUE74l2SYbcHCzBQZb2eWpzxHEZD6M6QABtvnedjUFBQi6SeXaZOIX3\\u002fI\\u002fCjZ2RSDlsx0xfUAxrfqUnWNrFzbZ4+6ToVkdNHVU7chJChhpEX\\u002feN7IKP0JdZ9T+5Tuod9AtDOM8o2LB\\u002fmfkwmk4ho3w69QOzP+BA0Rx4pJA4ch10cntGTvn1kGdsOpYZSKOQ4cswOY6Uqvoq8hsp+IGE0G1krHMMqoxCOyBpaU1nNwguqrLWwoZCAUQReerBTiywY7ry3CEWefzKI5XMv6bgxViBRwAHlaWO73oO+0SrBPIThwFzoHzCOjaCJ748d86zUIHYD32tJ5T1jUCE1GRaz0BbVe8oXvdSs6w9QQuNfnf2mrT4\\u002fwmMyelEcEgU1fABOKp+KRhmxrPlgwLEGyIQqhquRAcBdLIPQpkfr3QaRwtiDLi2JGYJ9ogbrM1k6+w+HMKsH7FZbu60ruk\\u002fF01y9QHbhA\\u002fGXaD6AgRKd+DHioGo9HXazDXxfj9sr+Qv\\u002ffp628\\u002fKeay8o6eKHTZc\\u002f\\u002fY30ClFDRX3oHYfUoeAElSTmdMA8wGFm1wPfza0v2GGJyq+q9ZKXQbeNnArJKRAnjVlt5HZls041yh7a4FsbvZH83dF\\u002fr9UcFVX+cE+w9fEZNDMvmlOLMNEEck78um\\u002fbUY3aOZghowUYau++9tjocO8OxPONXgBzAMN6hgmuXEawYo6GpldNNZqNjAezRCN6pPc\\u002fZPjacxa\\u002fjL2lLyIKdm3bDrZ3oJFad0ByL2TYatV4AYPIOiuhlFPix94IJcSYGlgTIj2w0+HdJFj36LhzrCuy1j9UDZPaM0C2w41EmvMBwULKvSbdAIxyDIPswFXjFlI8LbfJQEVJ3zz6NyGtCvlIoezMGMpyrqn1nOY+D+OlEK+Fx10n5XjMP5zB5qRbGpl9AEyPrvf0tMDQ+0KpMFF3HfAJ9ure\\u002fAkcpyCzcJZ2H4d0NQkqKZmS8nyOIdDlBzFq\\u002fej74C4HszWfhmc39zf+fLyKo48HWczSwG4AQ1KXEc5P1Tcbe0\\u002foXNZyHRVnY1DKbIz9eK\\u002fgSG12\\u002fya5js3ViFU7xsMkvK6a2JyFwVkev35sby+hwt7xYxFx\\u002fgvuvav0d9N5VoEwIc8P\\u002fV1CT4f2kKRRL9qQdCOkosSMeRE\\u002fLcot9WySWOIgVFMpNxjgg2sbvwFl4AVLp0IICcOdh7YeSAjQs+acO\\u002fbJoCm12sOBCzFKtuI4U5gQoho4McpvwlIHimCAIorFCHCPLOTctx4mRDsyaIRhiAGGgxok0cAhdxxpAUDcUgjFCegSTiNNSzVCLUjVCmsoFshT3FUBRr0Fbx3jcmSF3lsXRfVCp+UCTSbGGaHXoaWC+yIp4H1FU478OqysRi69udw\\u002fbWMuKJzrs7F8ADPydIR\\u002fwyDHITElrBZT\\u002fxMK6SloZ+B0c+J5i\\u002fLAk7u5GO8IPtIu9hVj3vX4ADQEYu5yF43LKP211cPqtGVxpCSBbDdTIzEHV5Az81JWcEM\\u002f9abnrL8EZX6U96m+J4+MHQU6RB4h+uRl\\u002fTvWFdG+n9pamBJ13EvALJ2L0kksD7jdyPva7bB3U9uJ0l9A9wrYnAPZjNUB7mpfj5BJTZ2lwPgKhkUNvaSDqDKmg8J3Qm23f0QY+C7Hjcc7KvHDOe3I+Bn2n5F95+nOd64f7+qou4uso4fGg3UlBiUpdmjcQlIZpqUbPVYdbbEBvYnoOBwsodpqDAxTFrQ4Ig5agQwyDra9wYU\\u002fujOir2jj6jFigAh7QP4exztFtwghJxM5xoPyHN4HWqfOUVMF2tNj1pi0pqEbg9wASFzQzWqF3uh+ndnwCDLdO6PFPgy7ndSFax+yIzkovAm6EVQj+LaHGxfex9VtNVb\\u002fRFxmVeu6\\u002fAM4HtU5wmbH0HtPkoEei1IbQ9+KjY60Z0TqVT36kEuQ1j1pU0S\\u002foPqi7q49mPHuZXx0JYFYndQGMsdSb\\u002fHZOB6m0TjMqTfqi00ctzM\\u002fuJ7M49WuZbDzFS2Wft\\u002fqxuiTR78AYTofMuLUEl\\u002f2ot8FPwplpHrV71ZzxSkMfKlSVKGOz+xqtMTRGKPJZHwRSBOGo+iVHHgMsdDHuq6lR4F1A4OVMg40vo4pogW+c0ELdV6D8CD9DuB9QwMU1V6\\u002fBX0WTC4GNYWhwVXCowANcGyE8nrpDa3ZYNnAFwTKXE1TDYDUMRZUN0Y62MeI9IZYiRDsS2BEMYwq2Gbu24L8Qx2WnpthNUnlc2WCTmvIPDu2qQszOhj2vu2mavSsqRoAtqbeCVjL4arCoU7vmWlp+ylAB\\u002fyY6TipC2T54NaGH0f6Y+cJrLzauMdgGwqj7AE5f9U+leSNtP6tMwU\\u002fKcnDNalg9r7FN5+n\\u002f09UVHOAJn4AyjVM9emie2FEBKr7CJpatptBXMf4GHX66iNEkstHYHwv6xu227tE3PQ9Xksip\\u002f43dWwzLEO\\u002f3nsxgF7YrZd9l5bdbN7aegTyg\\u002fSP1MMdJpJvnL8JLcTK+wdlZ9lsoB+B+LEd\\u002fFvU78l3QyhVegu9WvaD0uFgi9H9ROoyRTPqKs89HsCoQ9j7SCB+I+4yL+R1PhuJoomng71wiE59hyxyxGEMhBeSERvMPVFLRy+Yo6az0XAJlHlQrU+9q5pKDVvMeot8EkD5dBgXmFjlbbFmkNwLi1pgjUtGmNdQ6vQgMCIj8zTrfIh1iGFvjfDZMtFB22BKP8jTgpj7Ht2Fqo9cUI6HkTwi2oLW+DCmgLZaNODgVHsV76bGlO7WkjrpWdIP0xFGhB\\u002ftgQ5CdMy24dPqJES7WISODMSyroe70e8HE5tKYEybywOaazydC4Hgsy\\u002fWz3AVSh2y9a8RhevoyVk7vgbVaMJ6j68DCyAN7mYqbNOrmuJrEtbpWbuId62BgoRV00WHetl2eBvuQ3121SefXH0c\\u002fjjOuroIzlSv0Wab3O6Ro+gLRU637a0P5mGXziaTW3EjGRPhteCoJI+8f4vQKa2pU9\\u002fwevrVyLxBGbiWJqp7JKiPx8hDW2unFasdr7o2ajSiYjD7iIIgRHcASy\\u002fkLaoO2xOG272UUNEn0eTWuqNrmPWhCR3TSCsilaeBn98Dxs4ljU3T0IJITUdu4QT6Wg42tGgKB4WuNfmcQs6HS0FaYHJf49RA6UQr74BTcJiMsCqprTsLRFjZHR+dNd3B2+yRJ0nu9GuvFc1EQDsI6zrEkWOtiIRJMPEVAZjRgE6tdmCs9t1C1ErzVlt6C7yPVslRXKqalWJD8MHcbEzw\\u002fUQdxBeN5ZST2kGt7UTTgxs+ALqBh2sd8cZI\\u002fXAPf7DI3kW7DRi1iiqxJ4pYMPygPoL8\\u002fK+38jvAOsDycxrq8nxPCtrSyPSLCbp3PQnStldneC4bn8I\\u002fm33KTn054z1enB2K9waowBgfFRYoBIhZIJw2ZBw6E6DfAD1256ErgOMEOqbqpccHq2xMTwLwmKR51TER\\u002fs2AF0OZE++E08FVoxd1B0Ja6C3oZkWXoHWO2kL7VIcWlsojRtHgqOBsCiNu1eMcrcZgowG99gPlbqidU3S+E93ThFNLq7EXTHNFO00Kqhb2hMm6iIc9vMeuXdiXysRHhE0skY0BmrhOQNJx8VXH\\u002ftj5YUMr6vf9IAnFg\\u002fts+1wAwVSLwQH7WTGOPiKu3weHLE0H6H32DxcThGqBd0yejC0cTQM+EJpJuVRRDzHiIOGI3Mb9VFEEfUJf0urN3APSaQBdz1nH6qmbXjMb+eurdXgMipuhzahmbYeBGCjChDFbTJRS7I2EobQqIeepfMeTx28OF4eeDTEjuf\\u002fLYVeRmPTiz4x2ZAIi41v+2LZcyUqFRxAuJ8T1H371zQLc5QaZuzb\\u002fWQwKR13KKeygtQ83ITolXxLxQL0v1l1LWjj1CJYfICHm5ssOfDusggl7OahjPDDf7IzqB0FYzcFUYmegHDT4ROGr\\u002fZ4AVk66IuevHvQn65UU+adGQIHawFLDgBs6t\\u002fcY8W3Eq7pRdRwmQFW2KOHENvqJcbyFXVTyCX1uRx1OcANr5H0lhqMgLQ4CpwzHRBvbz1E\\u002fRtBSYnvSvkJ5rNhB9hFr8yhFzLmNrCcs0eSdk4x3w8QRp+dt1YSpF4LwaBusAgOJROtJr6R0B7CIAMpnf8B9JpAeIBhcmKkJIHJf7YXrMpe28o55uRhDZUSDtG2Jlx43+HOGXgVuG0LiGyEdLvy3DjxT3QrSKoGbhcm1m4SI0f4NU3lDFJRnNngftATkRxH\\u002fMhOXN+h2rLKJC3\\u002fyWGzbT+FNy5eGCdLzN+4+PDnFDx01LZnAp+rEbY8sbDuv8PR0+nzfvUHt6svhBiQly\\u002fuu9TR1BU2TKURDZFDjGsWLUSY8MH3zd2HYI+2rPtF2pephmKwRnjDyS4BvgDSlrXpSigHAUYVsEZhAUFXptYBtqFCiXB\\u002fyhiPn7tG0mEOqjvA4NTPyGpUDdDIKCebYGW89HHrUYwtnfmyLwg3HafRa8Zt93wtNNQSXGBIvVMKG\\u002fBTw7dgqaZAhg6dzAC0YyzRIkS+Lqgs4BbQRVRvyl3L4BH0LBVSIO0ocZdJiAUujRo2Fh2phgALhAHxqjbJCu8ECXjE4Dh2xHRt5039Vw6MB3QW7r8WzFhqPQYBqoGs0rigMPdaE2gzGICOAG2thUzT1RsIQ3hO3FZ7jM9zBnPWCfnzkk\\u002fDxSqTezntz0vqkPwXpY9w+aWlnec+P56zNKMUA\\u002fTTv+31IDmr91XGl2IbUZwBVdRui8YdTcUZvxxY+ZDM\\u002fGZLK3VbL41xhPCKr1eE4p7n\\u002fDW1Cb3sOrIuNVx5jFIyL6TU2zT5Y73xtnYzMC6cjCPJSLIHIFYy6ONmjTqFNEOaR3UT7L3UXxwxpmSfeLDdpxXAQcsQL2jxP5ZfXg0Zhf9p0y7RzVRvrq+1d7gXpfDxNeSNlCRiqWh7wX+oRO91F\\u002fsj1sUBmB9gYsyj2nHA9OnLsuE0P2B9zf4PXcEFcnWDTek7iTnfKVO4BpULBAfc2Qpi5BPudMx6EH3x2SFHGGGv7kRGOBsfs1nPS9SEYnmCdMOWo22D33iHh4B3G11ykQY9wJ8e6FuDo0br1t3SsPMc83vmAEzVRQo7G9fJTY+oDgh08VMFuR7Yd60vgl8Q7BG83cOVcWudvQ\\u002fdDoLXSO8G1c07kPwX4DRGmTPI93ujh6U3Q7tF5Oj5z\\u002flGoI0FUd88P+mxQFCr5wIp33N55VQstsZYE6dEqPVrspmM0Sal6RzG4QRlABHh0CiA+ooDs7wOug5\\u002foWClLmNUpm1dd1wdBMlRxw\\u002fJs+in6rt8+S6KfBFkJRT1uqqFiQObsRBDIJ+lN+20nRT6c181PNMqH1FkAzZBtJi4MjwNKooZzrxOxh8VgTHdn1iyINmLyMjpHintBqJkVBmHr2rHSEztZL346A+FReEnooUC2XQu8TT88Tx3HKtF9Oka+pEkVl2anR0+12PORcoVFiKKTXqC9Hk6y3FRVQNwIym6cdzhovO18ODmW42o6AZUYU9OBpsON9blA3Ka4MZTASSC5dVNLWGshJ01jecdGxP0Bls5M1nQyJSXBoxPaulPDAmlIHSXM9POq3QPUB1pDalRMyvvZ\\u002fFQNAHk\\u002ff7C7+PhkM1Kf7MMA6jF04tGplXQYmDoZN+\\u002f9m6XSk5oW+f5aDrTRDFQKbpBx1g2BVmwAHZATEyGWCHJrx5xYVI\\u002f7OQDKvdp8Hh3YEwYy0PvAjoA\\u002fCD+VOGlwwY3M1NeQXgtb8bjvJUEo9eTZvfl+FevP4DTZ7bLsz0cEMjGyZCA2zIsSoHPQJ3ngs\\u002fKIhs08+cWu\\u002f7xkl8pWJ3K+DE4f4GcmoWOJ134epcX5TEJ9OLAsj0lZxeAUMLX1SkQdE2Jhk9l4unPrwhHUopuw+uXhZR3oqlXkJLjtHse2+yJ6HQISAMcIhkCa0IDwAPbWSiDYFnpag4lxBkNpWeN3nrZq42CuF5gTWNmcDs6OddJACAWRm+Ut7hoEEs1EZKKw9RTufesRVQrqdbKvxH0IUokfLLn2yHMLBzv4BopcTgVlunFQyoQla0EbMJ0ajaS4YRGzih9mWv2gJlth2la8q\\u002fXTqO0nqv+ES0XzmTtSfTWxWpsRu\\u002fVHomhyGqirSN3f0lvlQqLzQNqBqFILBR+IOws1JNAv+c2gs6BZMbbbdac5M2T0ARh3ICahoLCWtbNy1YQfdm64kpPQ+gkprrpYxanD5IfhmlagPZ9kU\\u002f9399Xvsd7MFRsjA8i+85HtTiQpPQjgeHm42Uz4r3EkwfRQ4x\\u002fbkcsw9v2HslA0tX4fF5PVQR2UqaHrtaFgJCyNuioyvomsPwy3g9+goPP9s05FnjpxwUPb6nkC5e6ekdJRS0eCrQqGjkIC62HCzHZkzEtFOerFEYPp2AtLk7onmspe1txjofUrIJjyCUYjDsO5BGqImB7ZPqyCXns7TCCPL0cOA4UGd4L8rkCSQjqc4CA4oFLhPoBdoC5iZOtGYc\\u002fnsCx1UtpnEIeROcX0gyciSevKrjF6YbzQgHLiPzZdUHI9esWFUZJATEYCZdvvzSANhNp93sAdZVd8V9tQbn0Quwr0HkY2QcaVxka296uNI1rE3CBSmszkB\\u002f\\u002fNqPzDoDIvxmpbeOuJ+q2yP7XJwLuXlr7F9gsSHzMzkxM6e3AFegTh6WW3PXacBQtjtKGySfxHCkvVZIq9cvLPp3yWxF9s6OM+WIef5sm88QYk1MqAmYu+a4hfwae0eesBwyKitVZwAOIZUv1idSz3i4RqqIWXgAzYutVRlLVBUG\\u002fkCcl6+ClNs77ytC55zwPemD5JkZegasbrduTGJ3tSa1dOXCDawANAAimQ9mLb9ED1HnH7GdlvE5hJEICopC4M+uTIVEwHoC0BAkvUQYwYHmKGWxVwYC1T1vmutFjrTQjJZMyP\\u002fpFYXo09jIXJ1aFzgNxBeol7xNQYMR+jjz30O3mw3A58D20gBmxHGKYPju6JorVHAZycDxyBD5J5irNYwhYwSk4MZv3YAXy0Q+pk1LvjOM6RvrHhEvU1gzBChh6foIA7doNDoMXStAc4HLQZTyjcdlZ5pHENAXdRCzLL8BhN2Wbf+4heKvcRUIPgAdnnL\\u002frXI\\u002fh71EDRS\\u002fsgERi85HxAwZvY7Nj5qh9N4DgnYuCKiaXi1cF\\u002fU2cDOllqjt3xff6BBrHeqgtH50q+y9KHoH115uEp+KwO9SyeNU70UUAp0+bjiqvZ\\u002fpXXHWdoOu9bz7ysyVvBNt6QZ\\u002f3SgMIHHnPYw6MyVY1iHE0m9i9klSDaAIyawRPOOuYdpRTSHDxY2wp5uvdka0ahKYDWwg8MpvcWChjWYNUG2sED5rRd3LXmI+IdRqXV1wLspDfQtOb6UghVD1VIKeh0qtsY6YB6SvpWTiu\\u002freEWDYlu5119jCTwhtuO\\u002f0wMl52r+2UNMAUBl0s7LMuD5+n9jPch0gVOjMXA9rFzYQg7S4mezw5+N0Kv7C5MuXW\\u002fb4mqWbEb9yOtBwLq4FvNu0CaWC4MLxtU9fZmJ+72vSw6MMKDc9AQWPpCWneATT6ywFSFnJYmaHjV8\\u002ftBpJorVm6KkX15f4oOvfJ+eJt8f+AxAhKE4RAMn8DDlrO52AFKL9LxLQgLQ3tsJrwYGn5tAFrcp1HAT+a0qv+2BdXx\\u002f1\\u002fSn+3slqWHgtY7+tnPr\\u002f\\u002f+bvXRZGSkndvYZputKhVC3AUnIHEJhYSEuATuhBvgACFBFdSu7bKd6YyIjIi1YjV\\u002f9\\u002fWzn3P0ow54buRZs4voXxgGepEXm6PdX2Anh62uJFnHv\\u002fqjwSOGZ7CJD7fMbdvwgPlcI2ZDROQPXu45AV\\u002fs+3E\\u002fA7Iv\\u002f\\u002fvYlrVcHeSUrJ+RCU\\u002foks0mIVNEJI\\u002f2iTQ3+ho9J2M0\\u002fzLu0vhLMU1rUy5pno1ETAOYP6B0meoxI1E+wwUajDHMZGGMnySn9AXS673OcGAFxGDzj8VfvA1ILSqUUxUPzLmYaaaA6MRN8z666RSymfI69zAJ0qJSTVghLRFcQlOeMvBF5z93skgRQtE\\u002fTPZKPL9kTUIoLOw2wOKxNwy\\u002fCA72ONTivi0vAeSb080LI\\u002fNLMST7PY5i+eCfl4q92slPz9kXJf1wAEvnZzIhBPYCsUscMNQMkWkZ71LHLuLZSujji2TjxUJF1s\\u002f214ntsFWztvu3\\u002f\\u002fDpVECdcULj18zieF2MEsQ6gvX1ZE8aMEmWzWETSyL97OL1swOLF3gfbVbxN\\u002fIfebetwlcD+X1pUQHRuaRT\\u002fNM545n+quDFOByraRHZKIveRhyn8Vi4QaZMFkU\\u002f8oaOujV98sbRl\\u002f3hlUNvNXpzaRIf5r571aZrfQ4hYcJ1egwel6xId4ZS+MZWK01WiIkd\\u002fHnKq2uITuyuI8mH9rNi13uZK\\u002f8y0EcSpVJQwe5LbU+SzulGGM58uQpzEH3LzZDcfIoiGUo1BiRRCaKAJlL90BNPMeYIYwyByYlOLjqLOKfdiH9xwkaAbBi5W0iWXpCkYepmElI+w7dvdOxkvoHd3PMzPkVBC+CMPtNwJKGR9h4TFaw4Si8hufDXv5ak8ctIl6+mm43+MKIXKD5swnBt05ueLpxN3PWAL9cj2+qXBX\\u002f3DCqhVQTJTP9RKBEPuadMxbO7z9eJAD+B1jcd1wTWY8zHeDOd\\u002fmbdRoWkV0pMRlNtOkg21S8dfP\\u002fs\\u002fxRna133j9Gt7LpeFFQd6nSF+eBHMvuC1n9\\u002fs37o9tF4FMNpEpwX73gH2fSfrtPHMTsgS03fYHLlxMDJB2ZXRuMDUzlmn8znTSxKFe\\u002fT49ecGnWfRNEsab1eRryd4\\u002fKMUxH9NNJ6ka2f93K7fQx9D\\u002f0sm3qaD4\\u002fR6XU+P1w+q2lOjm0czWcX0SZRWpQZukjQXssc3dYN4YuN1GqaU2nsXRH36llxQjw2U594DdxOYIw5ORZSTGush5iJ6WxXsAzISBmQN1ieVASpjaS4J70zOfG6QpOwGuCvDP2uk31hJiYKCIqF9n55kg1x6Btg4+hIbgyh1owRjycOtJlOZUathpWmbBCKnpXjhFWdUIOrj9MyAjs6oZ0fqRhgZJdb4byIX7ZDT\\u002finwUCxiAcHwKXgH41rcVbCLqSoNvk009hKSn1f4Nx7Op+ic\\u002fo5w5zjbHmG92h85BY7NgR1YF8tUHfTv4714s7oo285SmbBDvH0YpN+XwkQi\\u002fYrFo6+aet9\\u002fzihBLbILv1nQg9m81mx6dEeKtAjMrKoiJwJjzuv6hkhh2wxJdse11A4LkpaDXj\\u002fiLhLX0tZjJPwCVexv2tW\\u002ffEG+a\\u002fyDrKZUVO2RSnpFZT8WeLeX3l++6Uyml9yYAabFCIuz0V8lr43aSMjfvS\\u002frpf38Vi\\u002fy1EsoxQRjmMDqXNXgQfnTMYAutOapxM7wnKH3JfRPvauG7255hkdEB4owzEWSIS\\u002fxuHHmcxRPLKpR3UrgeRDKtwflIkaPrXFKImN25XSZfL8N+FSoHBwF0f5v2lKhnA74qhVcYNXZ7SqxGwHAeEbN0ZzJ2\\u002f0pL1o8GccBJFIopq6dOmbrBsLXjTrul88xOmXVXbJKNwVSd7NrAacxYMvJ5qwJnk13CpytXdqMDTHXKCnQHuw3RgL6KJ1sxhwUPxzkpo3A2A4EWLBSBnQUzkP+vyZbf9pUAmCUp9mLJlNftjwrcz+vsHfHvrBtI7Ow0Jc9zEeokIFj+LDWRbz6Xf9B0n8325wg1kLMotmlRjPvMC2i5jJ5lNb6yfqfmdkeqvtMiGduVjbYrwgdpRXvzbJAeL+DCfhsgT1LXqookOEUly7G4ixvVT6lxjwCLeRI4M9alccZ2wKweLaixPQbzURGXIdzfZhn4jQ6mfkNSP3rQ0V953X0lpFe+Jup9PvrH5XnWcA4Ev7mzu+h+pUTNpg11nu48vQtTefLpMf8ViXXdYkbfZzTsxeP\\u002ftxNjVfYQcO904onIU2r1PbjO7jbFpPwFKaQ1vlYZ5Mx9yydIey4Wnw\\u002f2rKw8U+d\\u002fg09cPi8rocJkr8plt7mfyabj9kbgy9CgM1UdR8\\u002f9nB3q\\u002flnndYDHkKMAh2ig1u8uJnEDQ+8iMMxI0lLvmca07EiJkuVo4FNJ9XhyKmAWn\\u002fFeYyxPw7BmVpc91XsKGmPkO08OQM4ZRsbbU\\u002fcDy+MEPZD6xu6urTZoYG+5yim6Kzm\\u002fWLKRiXNtoatUHZ\\u002fF+1nfsONZQc3GY6rYHPH5lso0unjssAS37pUCTo6tJVyKxjhO6I0ricQvaqK9nEE5hTVXqZEJSQaHWWYUAyDnDYnaTccHzLog\\u002fPqqrThIrTm3YDfYHaEhmT5DUZcpq+QkO8cnmAepJ1kcydAmqfYumknCH6B1vPOO0knEcW56yeK7vq+LyPuQOh5r0gP\\u002fr7p3nPQsobn08d1iJvZoj5+y6p6HZQZmaml\\u002fhF2s2Lfpp1XOmfF9Z2aKFMVafYGUldI0lTR9E+f4rETuNhN2NMJGoqBjc3IRl5v5tdRiid6hOr8n4PTr7deX9wr06CS9mVP8zaJDbNvqyX8tMqDOqZBMiGAGtTEbujT5kvoZzyF30WBZOqJtZaT7hz4ewPcMlvju8wXfO4p3q91c1PsAQfwyRuKIr8YfLf3pPLOl8V7dBeLa9iw23YPoo\\u002f7VV39fotYmagMbZfofipuDzfjNBzf37+8DdfvUDtm3v8hRJQRmOdZhFC4b0vFqouSdapECNYJeNTub5p64vnq2d\\u002fNnROpp\\u002fnyuqw6hNtyArJGY8czr7Mui2xlsS6iMTHv3Y3ntKuRUkZ3ETDEHFq42Nfv59Sm0W3GfqOkfsZJGqwO98mduv9VCyarms5Ev\\u002f\\u002fnE8wXqoMzCpGipv6Pp1J7V6ShA8TE3fETJRn7mmVeCn97ZlFWn\\u002fJDVx859jhZqhKf74h6oiWS14X1HXFkyTOkCK2KrF8Qm8WU7wn6mNoBfp629g9L3TYYVuYSjiNnTtC9CpFF+naYcLE0xdjeyp0w\\u002fimU0f28i4d9uFiOF31yybbL3r+tSge4xEcJKkl4yV37tfcOia5BwrQkjGNage8gURYE6kWUKSzobdQZ59p9G4pv1AABMUVRDtpNyA7O1XkpkRffpfd\\u002fJtIXmjgQO+cf478YJ794sR3343QhHSdR+KvFqkTigmZP41t9u3mt3wQ6RieoklSBv0SZ9r5iZdxC5Hc9dEiQsNFxvPw\\u002fU\\u002fmorJzhNBNzPMq2vHv91nXjX8qxPeJwwj\\u002fdQZ3+vQumwtQ05TZI4Iq9L6MFzOduhc4fUbmXRbxYe8TuXRRNaPjfPpkMvrgjrM8geHsudUqaPn3AcZeOY20D7Rw1POoJo8iY+phuCNr3VtN1DPXqTupKfFDS2kvIRb6E5g8i65a9NFz6oxVXFuTVqFYkt4Rf\\u002fbZ2c\\u002fmdoWHPytBDDz1SRBkjIbYo7yzz2O+4JI1\\u002fSuSF9a\\u002fl96m8C5Ix0wWRAT0OVUPnzGMmQwWYhnw4nAcoJUgNdzMTdbBvdAtoWHcJrTvuh5lkQN2NVI1SQCgVd6tu5Pg257PMurtOBCg2qUS0JiYGXLo\\u002fTMFDPiQ5s2KrmLleEg4TE6dw\\u002fIDT+cx8isj8p5ktrzIj5\\u002fTPXl9s8U7nE1DCE9RdIgS0DzsMK9fF+QFu4xtN9W8NjOTL75uztQwOxssUfp5\\u002ffvCzQb5ruM7vzkl55+vVCR8xcekZuNIPjZ1MvMboEeLn4FyRYyZ\\u002fSqHUbmFEezzp8itgMcfi3Dnh7ow36X+5Gz1kVc+WiWwKOrfj27hLBYkad3k9XI\\u002f+TKdD\\u002fLxIOoxOk\\u002f42HN+Zk6JQPWcqKGLTHcecrFAzCd2OsIParXnrCPhZNWXTkhM7kf2L0i1HAqBUhf9voIKB3pBsUaZlpPi0TH50i7KXggb0AZxw4eOnd\\u002faIOqKYdOjIV4cL+gHTKb15Oasmhlso4Oln4KaYBQvBawuRfl8BU5S+4rqeC4gJ+CBkFWS8tmYjY5eGks7lZf9kNbBw9nMU46gWhtBgQs95T34dESrs4AJQW2\\u002f3cfQJ23MRZFmNGfzXE5jWLXRp2hnY5rpXKaXedgWld1t58XpGQpikD8Dh3U4\\u002fVYBX+USMwbNBpK6blbJeSNyczhDzvRp2Ia5WxvqtYhBpMiZQXL8Hy\\u002f0390s9U\\u002fv2B8fDtJtfm+Mz5UZ5lCr50yJPPmBhdBW3wOeKA4Y5xgXLTmuOU\\u002fHOzP9d4K5xF7zaOCRqOUZLUsjixtTH+iPM8wmUXoSgqKbELfKxNgEp1A5m740X1Gxb11MyyD3Ufx6or2gFHV3iTzaREr604B6n810cy14jxqW+GTSfYQWnTClPF4S71WHEXHZr8nlLZ2WzkQrTFw\\u002fH8gFmSsX7Ez3GJTHLYMgU\\u002f+5+wHPxTg+5MPKxY4DCt2xRXgGrc53AUOrIVCYGNPtWiVQhVPCv+mxCV06mRkTz700oUC4r+d1kl9m+urUvtCD+XsU\\u002f5q1WTx9bezlduBd8ptu7Zx+g8eiJn+5IVFv9UB\\u002fjXmydEkSEu0M7VRpbYFcL6zQcwNNjw2s37WAjj77tuubkf91QJGRN\\u002f8gwyf0FMdvC1ce8IdAivbZB5O3WekW5gvx4TwXNCieYqLqfmR6QZTYE5KI9Al\\u002fLqfiam1O0eEJPflIXGEbw7cXMs2Qx9GmlToi3038r96ZVVLYkegxo9wMRVbV+2rt9Hh6d\\u002fXq0HYkGMgTkHONf6RxLtxVgFVP25Vey6idhBvOarqyEeBQD0raXSIH\\u002f75n4hW\\u002fJqQl45YmMNhHxFPpx4mAU7pQKLgxC2mvPgr89uT7lKJEAqZJbJxBGnSZdH93ZJNoufbkkjHeKmsJQw0h98LMVDf6q\\u002fDEPNeT5V5Vx++W\\u002f+mv43tEoLMj8q8C\\u002f8GMwND1hO1VsPuOVNRqwXNoGLE2DAXrR1QRgb0Bk1FqUGReaGHPi\\u002fdJVUqj2+K3yCtj41P2m\\u002fZ1QEDtZskvJOQVO8wHACUKjcfcONQrg8WQ50mJ6eK9WnwY8VFB45+EzNHb7WtwVwre7F2l2Cgx9d2uoPKfZ1XfvHyxyveXbJG+mE37i\\u002f\\u002fir0xX4id7n7gpU10q3ozrTuN2yu77\\u002fNeh\\u002fMLlKubbo56aYtfH5aN\\u002fQogsleY2m1j0ooEUxyDbOC5DsiPSE2qdAJVd6ugncjV\\u002fN42Lp19X4+Fv0m9CS0ZWt+LFkt5ShQYlGwmYTleySWSCKJqHBRsGEW8WnzfL8e3YowgTcbrMwt1qYAj7ijwLcxZU9aYZMU3AXRuVed9YP9pXtdtexrnzGkNm\\u002fIvWsT3WlBajKRjpyjAletclf\\u002fb0cD0ux2zvOEG4DabvGH6OAmj19cnemlX8HBL37mRjomzSdvN2zvtdpEGmrGJIUjBOInnamnfbziGHhUls2xZeMoIKm61kIqxEOjD8V2OnAb+y2RTnYB3WWBFcz6auMPCihUXTIhRPxq5j42Zb5\\u002fH5Gp6VWY5rEr7FzTweAG8N0BFI7IACoXlu\\u002f6ujiI6JsGjD9Mx1Rdxqm8KBnNgF8vXrtjuy2\\u002ffzyujKlNErad3bqct66AY7JUkS51fVnZnoTH3\\u002fCiIyqfTr+3Py72FhybZoxpDrWaQsZkVKF44eWlJN2jBsKEpM6zib1iCwj3UttuBfuasv+4fnoquGPPGZsVXahTmcZuR8jH9M4tJkPhKrHY9SUzgrHSePLaLiIrOjEKiUacvw6ERL3Cg2CtVl2NRcT67jgGK5H\\u002fn5C0rDVGAdE1CN10AJ1YgijMmPjMjIUc0tmcoW\\u002fn4M1IbE6LmIftPpn3srlnaSGN3HLwzO8nGtGXpIyODqgaXILQdybEiHsKaCujKtNFfmakI4tkVQK0L4EB6rInJOKBtWWVBMjWVagz8SGCmL49pg8HK6OrcGa0bYy3AWGDTJwZEYkykr4tJXQ0Zi+8Ce++hxRgxNRpHA+8w6drFZ23hJH0+wSm6b8dElwDf79cJ4fcPwKAjd139V2qrxnVJrHj+vV8ziD\\u002ffy6a1\\u002foU51tcKx6bLkzYPdpQ1sfEtnkQwfDXd3CDX2h+cw\\u002fxa+exoP0+60zVk2PEv1hvoE6ygb4zYKEtEiEra2FL3kpNOO4nhWQsJPUwgXv\\u002f3mSb3\\u002fDRfMWpyJB8K5Tygs4jl\\u002f7LoAqxo5KrsYbxQ6PC5+W8LbvuuBwVN7oqvEoqYiyMjnS\\u002fkQxhLiLLiYCG10PioGoaSmVmTrVXfO0KB+StiyVGRix5PHCkqY3qxMBG4WommKPpDwNOH1qCeLLdBZVb1d2D89FwPqinfaMMRV\\u002fD74KaDCAEBQhP+Pso1JmD0TC6pxehJxIvF94kHYWGMfRZGnrmr2eZjZeVSlfhjKUXUQ30asj7r8PK8nHxbDxXKgFVxSQyVLfTEwKAY9GLqP7QRasGfcrTN+Y0m\\u002f86KRoKxPTXYqIR0JziiFLTv5fXIEIyH5+l0TBYz0GpfPZ7i4EHwM4hdIZtpvrS+1GuP05jeLFySU6YLrK9eAQLILAIRvo0g3k6Kwi1I+DdeePW6M3Y0zPqciJz7EeX8ZOJsHsUS0r1OZFMnqmVshLmEKnA04ytrIjn6a0du3yH3qbcEf3VN892p26TXCLHH4rhY\\u002fDxdEisJnpphr8rihT03FVnF6uOho08h2SvlV55zml2Y6r83CDE+lFzR8PdmKBEK8RGgWEJvBZ08tGYYnVNKY3uPdsrkyQLXw0kVF3jr4GEZJA5\\u002fptYvvJT6pAbFwxcSfPpQ73n+fTqRhBie\\u002fXunpafqdop+TMAkNa3WD091ewSZIpcQz2w7yM2claILCGtjZ+JQLE0WeOqUqTRnesiZINNET5qB5wVvCkbUMMv1mch\\u002fn8s5H+pySZXfVZw+nqAqpYgNQDa7888a8MpcXP7Fdqu18WJ+Zu63rasVtf6JgVnD\\u002fPF4xbMwZdwv\\u002fvXeX2rRkPBCrGc2D0QEavqZWjbHLXvjVn\\u002fu2T675DrPF6PB5t78A+\\u002f3ipZVTk0XoxKogE4zeVVGgje\\u002fstlwmI7cwQY\\u002fkVRYDXHX2gfclJclp1PQm0l07VYTO4kHdWCMZjJKbyvyHL\\u002f3\\u002fXVBazxhKsGhlDSJ\\u002fk+0u2JBSBOlLlgc6Of5r+jYN7GiPrWg5zThdLBG5yF5LKoNgRk70lSL4Dk\\u002fx5WgXg9B3NF486H+X3W1M7IQuLHxa1f+L2LCBPcaaUhfijPnReeEVNUVAF7a\\u002f7paDTT3VRuQnQ1L8HWIGuQlFR9Ouf2KzJFyY8qMvByPsrHHR2urzU7lKG8ecQzOwpikzAl2LTSImXTjK+u0oLjIa0Pr1buo0Ch4GJEHwjyVedf700M9kdGERoXbvwWqcXxY\\u002fZpXJjknbeUvliHzJ3im0QNkYu9t12B1ivgGFebM2pFkaDOoZCljN3epltE0QsZ9CvDv7+uAsuDweG5RjkwSjYsCep+NOXlbmcT59fMnWMnyqXAs5j99W1ndej06nzJm8TlLauBAfrHPY2sjRhtuwwCF6prFleGPujFjWkUNkph\\u002fHXu\\u002fdclQwy8hPhTLY5i+mm\\u002fr8rz4Nddq9fZWs5HmOXcRbb9KLrxKGQ06RttTrCSbf+yzBVss1T\\u002f3wlyKWfUeGLu5UjLxuQ4ciQNHxWO4\\u002fbfyYvLkg1rWTRK8pnIj\\u002fHMJk+eKSdHvqqJtLQblJnXzKiOdTLMZVpSbGrj+QUfpfkfmMuTSJ0Kz3wU6htUWXqE8xeuJwWE3K4Zbq6mWLvu9uANH4fESuAo2JiUoA3m8PiW2IBDJe+OXIv0zeTR5nj9ifr0MPuUecxcZBh1WfQjqvU6eJcqM1sQ1p3+Zq7VOsr3uGrnt34xh6UjtHPtLpad3\\u002fWSk1sjD65sT+5j6ktybGMADMvprcdw1fu+AD5INUyh5w1zMy9t3Shat0WpZgSFeEMYhLYNok5ewS3av2mrVyYWdLU5ftTGXpkxiNQ\\u002fQ2JXiTSn6Nu9tci14Z7pn4H0j8vHXnRTDayzl9XHYRdtNrDOz09UK\\u002fjdEjN3fGHmfxFKKS26e8iothhjwZ\\u002fGLvxUb81zBZGq0wxDkVBCqHP6azp5zsUuk\\u002fRx8dMDBzDFedrwbyQU7\\u002fJTI9UYmMbEAE93ypktUwFLZnfjdDDzoil3YbXFzAWow8G5xVXnWlCnkW1hTPOHnQJKlIJdDpuj8Suwa1VLVC7YkMPav7JZazU1ljHmzuDTUICosD4U3iPrFH7CQjAAow\\u002fTIbsVf8EB9sMweUPkZ2yK5tCRQkKHFcHW5sHduNrdb2eE3dFVXhas+SCSIyVbMMh\\u002fgRg0XwOX2YhpvQ\\u002fGMwn+L4ASdhPU252+xF9MQAnH+lUFop0Xxhdth1txRIFKfzBP+pH1FVv8kyHXwNvxV+3U4TgdtZmnXe5aCfRQ6P0y7J59rEPrGX4ZeopUW05ovR1KXkNe6OFL0NKJFx9kQ\\u002fs7JIpmGJ\\u002f+50qdLNr8CuwoQnOivEyil3tBpFn1bR7Lkv0yQLuAGyGBhOWHppSZ7ozy72Gt1slpEZrLnz9JPK\\u002fy30ZQaOCuVHiMPd1LveHebpGzuo1\\u002fZri71jPHYi0Q2R6U77IY071r8d4wS\\u002fHcenLLvbmYHBsiH9xbb51EWR9WaGPDq7g\\u002fCKFS+CPfTu3Vz9NGCF7O94OM\\u002fU28EsmmIvTkwzIkAuCTIYn4quG6IZNjxQ5tuWwL2HVb1A4XhiyazRhGZdg0ncxWnWW47c9kb91Cdlp3TWZmt8qUegRNy2Tlw2NXz2YhIOCnsIPUY3yT4YLW97TLE9K5AME+Tc1QTTCbnNXyW4BUrSNszV1kZfFiiKUDmqMKTowq\\u002fy5DmMSFzd480rMrH\\u002fohPtJWXicZBeNysoA3TACnw9+7kkjCJ5ircHwDMa96ex2Bb7y8V2rzv8+pSJA\\u002fljg00ixAZv09WjK8VC0Zs2u5ZRJsjg75N5PJOvnduSOJAZfzAfjvQvnHy6grd1XYj+6G64gitkX1L2K8en3xVfSfP\\u002fWO+TBFLsgjRFC0GUgE4u1kfwbT9kRKAOHnux964rfXuv\\u002fIEbw7Gmdycc74RylE068AZue9\\u002f3nUVnLw6ErZba97zytH09BWykhSbE1TDNxiT3aClDHUy65LtCbw2jD+7Xus9D3rHp8PrCUZDM3xP8pBTa49rpbujFEIrK3sn6q3m9vKkhpP1Ice7nkkEsY2YAjSuBYg6KcnWUr83QatzSxUmi5GBRzTibi0m1BSzqAc4eKg4PxF\\u002fCYEpI\\u002fYkKf8V6mYdZvayntYOFnX1OuulOQ9dHfRTusXDj24tDTZm7wgp2\\u002fzbfg76KYKsetij6vy2lLUj45CDkeqnGSnsPnsTOudtMz3PRHJMyLdxN1btJ2hd5UdkPLYsdmcBMEX95N63G\\u002fDGptuOi1Srk8bvDdL8mwFuTFmHH+uW0sBB0+O6qtJo9W6tNL1zcZYS3QaaBFOGuHtuoRPCs2xhtZoufL38dp7BeJSaKtI0KTXOcADYuaovplom1Gg5j7up0t1KzQn9n9f9znnxzdK6cZVNbcYt\\u002fnHoYyTKrR9JEsHbBUxLTOPMeNaohU0Ncqmgt5ADsbyF6vPcfsZ4tqBpwAmNY0CVbVB+q3UIWRxEtXJ9PlZMxw2uekrX6+JwXY3XLwuD4gKeLQIvJmSaeEDfqi+CbkNtrjQ\\u002fae0zUWKyifkhwEQPBBrdB2rpNMnzuJTKJ4IbE24k8N63jJk7TyWpg60xBMio\\u002fM3WlLZxvGdHX3rkEp67uIvyMAqjbrNQ5vszFWy9tH\\u002f3amIDjLBplzS0b36D1RyyFBSCunoODbvQBR+ABl266gnyO8mMOuLSAdgZJwqmPdoS2Zh7XDN5fbdwN4ujz9XuPX8ibp52o0FZP4ZOPTpU7N3n0MxmcBhot+pTcivuW7riswLLT\\u002fEL4lbYpC7kD9jTuo8g\\u002f4N2PNzqj+NLA3jCb5WOSRtBF45FyOcUfL2AHdxtcJPmPDe20g7j7DnAs8RNEb97zXYjK2HIUsjPP0bSjm0stxOSvFY4RvF7j1IxIGBfrhMF9sPsJ2XacXH8OuktOhfAxar8X9Z3xDkKlaurruzOI292cVsU4AR+vrXme8i8n9IexvfE66tYPEzlLWh7IuVul6nmuD6nQKmI6YidvJjEm8Qg3o8ZiwpZTJ5Bxwq3TvCiWW0igFbZGxnbVpiegkEaGTPOuS5DWqVuXw2lx+WatsgU8bofjfVz1s1FxN+Z6E3kuPvXkSRGhaXde3cfqzQy2Xsl9bIlOiatevQcKowf5PjUgK4Z9ME0B69F7AIH0PVuQfXP9FdO\\u002fiObXyWzmm+RBfeBUyNZl1+vDXC\\u002fUUhzxFMthylZQZO65s2fq45Rfh85erzkbjUZxbsuhWGn5pw+CgPIzsyjQ5RFQydeh0VFStVgnCra1p7PZc\\u002f3\\u002fEUHy8r9etIOj5UlUf4vvnr0MyYGPUVPU1o9t0s1wNtdD7DKQ2JTb9VToeM9DGTtV9xITt5GrE9IjkUXLYzOkL9ryVI6ZU9SOZDnAbO2a40wU9MdB3sZKJtH6lPVZ1QEFhBe+D8vk\\u002fglFJywRySecN\\u002fkOdYuXrdvFfxksSzxLpjfatidv8mamyfPwGtIDIwF0tZCJ9gZ6qIBC6VNbtyM7TNiZQAOctdX96Lu2zJACAmJhLkpDAOpTaRThiZ1yR581rD4sf9zeEz3dVrPzq27mGLFdhhDRuaZ9dTfGw8xok69sXKFPZnfrv65vnu2YzEjE\\u002f7LGGMYOako0cH1n8Bw2O0gAijLDogv6IXmDJ9e2r0\\u002fjH\\u002f16U1sMttLRzs6OnP\\u002flbaM57QDHcShiUmbsA9fLyUJGl51+gHBJ26symgn\\u002fzMtnhX+I4vnNZOd2kPpmUrPIpZ1rfkt3Ufoys0xN2iy0QV2kXufx3\\u002f5+2lgfoWH4W\\u002fbHs\\u002fNYwka9ksyn5jvcfD+fXrDuGjFeEz3NSezvPdDCzZ6V+I3AJzqw6KYjJx\\u002fqbfu1EXIUH\\u002f5krqd5QgdMp+dcz3A9BtRuvKdDRvHnLrajg2IcLb+84Bvr6IhEPy23et9tf+npXjh7J+fl1F9g0ZtNAGPYyPxpTKdCdKeXdURm+W7GFghiEGkvE2u18H41eqDFiUQgGIl9UnI0R0XOgLko5iCcKhWg53xOSSSB28aLjE4XZL9c0+5V0755WreLN\\u002fLV43W1rhb7MQJTeguTkS90KvZXU0aFg6NJLxm54Zn85vQPXkCBT2iYXT\\u002fWGBSAWrS+mMpnsB\\u002fBp7T7p438o3xMSRyVceVPp7QbiuU0sV0vfuZjmj\\u002fAltyV8koWuO0Z476BCzeVpmpnaki+RtEsZJ4k8514boLYJc8C8ayxFnYjv6UZ+ipWjE4ZP9EhXNP+0H5+MKVMtFWbB3Ok2fgiohf8maPG4GjwgtL3nK6QO9yqC5gzxUMR1UvXrmysVbFBkcYdTj+y4KUbkTOiaynB1hYwECKUQhuc\\u002fc3SD34EC1OjUWNdTCVRXKM0+I08f5MIL5I\\u002fOT92vUXuMrEjsA\\u002fX8jmzb4q9SO1EKNJ9k2RkIhUyZXL5Zqb+hju8bHs1QHmM0YCQqdEQH7JsTCnyMkaKHZqtXIFKgqRA0ejYME1+MMpDoJeJNRVsevzVlOgGLQgGPYKSB5p+G08vDvibn4r0uL3E8Xti4Gmxb+D2jHzPFTuLIfuYIhxf8g8+oDHhU47DBWdNxX95gW+F3OK1luYbCjHA5QBZBv0d+BGK4Oy5Mw+BLlFW9uhJ8NpKDljBmBMDlAxojr3px\\u002fU72V1m7H2vwhz+GxKCiujIn3XckdM3BN2mok\\u002fsTKb77fgHp8MllecpliktwcTdZcJFgFWSVlTfflJYxrvlyEk82K4JdCPGZUiSg\\u002filFGmkh58SVSRH4m7FiDn9\\u002f4L8SttFPL961p9mTgTGa11u9VXHngfXxc4n4ksTBKAryjDgk+PEiALrOkafJfbcRDXykMHoSA\\u002f0plTYfibuj8EwQNo7Z0S6qMZKJjscX40dsitM50HbPfplZmZ5J4D\\u002fOpJEUdYipuyLTFUg5zO25KpxJqnQM5vy6ML2ltAr1vIpJUolSJ3KOT0pQTFqIgoM5FKB94dcEpPN0T4EDhkCyrMu\\u002fOTxQthu4aulebu3ddoAti13DzMEvYcq4kCiEu0PFrJT2Zdd5sgj2izcNB6jfylJRr+Ei52JM4L\\u002fPcAMIgriAeg6mxY9Fcv2\\u002fgzf5rAOcBTxpUrojZ09Ni6Fto8oBJ3k8zJO8EgC9i7R4YIjnMyJ\\u002fiijeY6HvSmyVkfzb4ok2HoW0xGHXmYfzOk62ZY168eu\\u002f9psO2dFRIdKOa9wkkfhI\\u002fbuC3Or4fsN+etTdk3qwzLnu\\u002faD2f7HlYoigoRkAXGP8O+oPrBoLrw0tOWddxobJBwckBrxGU8b78AxzQNPQ5a4f\\u002fHR69Mg0nJ9Pn\\u002fgiDw3+9XixSgpUTKUvG8vOeosEMxqVW1mtwD1vQ5MgyacoCMPPBu44EPLF2fRQhpePKAq5Xgd2j2Bp+FFHGEaGteIFGkpkgzNM5l+Gf9z5kuT9Hh1FboWRZ2jydj5gkmoBIpIokZLE5VM4hykA9zM8BjIugEGh4xseeJtJ\\u002fXcUuzqMxUQJrglSwHDcxmnzE16OjqHo6ic5i\\u002fEtk\\u002fsiHZDVJFHk4sUvRzuTwsKFRQRtK4MG6+KLhevu65ld4Ajpd+zQIdpcTXBfu3juSuaegt3T4LwJLnW3Z8HYdH0e7n8kqplLMMptC8B7x7elrnn5RlooxqfpYZOE\\u002fh9iqM48tqZQekrLBz6VSe\\u002fN6qJ3DNEDda3QzIn8oG7uJv\\u002fsFD\\u002fFA1KjrmKpjjbzrsZsr\\u002fk69udrYeo\\u002fI9QPlHcqdh7nYugfbJoF\\u002fehC2Un+5MIQ4KsZuRkv+DwGqPZjv197CZH\\u002f2pdtvddTEegNbSFilQSTRT8ndGDSDDjxitMK6dxxTxT1\\u002fFJySupoEP2EFCOJtO5bVCSx\\u002fcFzMmE9klkpEzcY6pTwTrlYoJQMZli3tTKQQpWI22vOLFJJBlZ7Yy9rqUurhM0dBnWMamGIW15Q7SkgZDaciAYfL3drvdQd+m4zeh+KJaVA+mgdARw9pTwS+xlHchormwEhdJATpv3pYp6ckCnYsj+UdlfyWkIVUDwf1pDPwBKYH4CDGtNrH3JrlqhZvf4E5RLGDkGmHHSN5+jDKy6uivyk6eXvmMCkZwRM8pk5DKfI8qUoLTv\\u002fKsZs2N8dCJe9HnQsaIdT9p1dG3bclAyuAZlJdJP0vs6Oxb6ruiWvy1+9GO65W2pMaO3D9442iOSwZSs3IsxlUsTy+xRT1myRo3kZSaolkKJjljw0k\\u002fPNkn6Hk+jmcUEWEXtPp5utciw3iKU7sR\\u002fJtSnh5vRjF+iqcgw6Y4ZLbF\\u002fVQ\\u002f\\u002fQvwfO9xF7hy5wHnU04NqRgtiTpaM7ABLM6WSsWKZJfXhzPU5QBHdkoHisbW+ohHACIW+7mif5FoJ1VvId8jOUidRjGMzOyQKPIPT8c5FYxSjNrqUKrgTUA+hYwSbi4rAIxBT5mFgOKRsLTyxZs+hOOeN6woB1CwwY4YYJhEk+pT2xTAr5jio1M01H3bH5AqPOyB4065t4iiOjn4AiLfQzKDojguP0MdXblHraqVuIpi1+JHj29N04UvcWoiiXQppvf80Y3+rkwtRlUpZHFhmz+AKK+p2eJNuh5lyZASCtsCOLb2kYZnIbzV+uecfM2b2Y5PxC\\u002fZRbcsTDhhTQ46u4mtGJlxAeWfkYZTxHNbet4Qbo38hKT8N3GE7W7yIx48rn+MhGuM9AZTJIoweBTd2yeTTLJwh3NaSSzpseOzIxiR97MKL8I++\\u002fXUnlsTbJfKiPUVjwnPs2L8Asjr68Aqp4XJ0szmeSsR+B7iK4wjcJdGCdncm7Ce2RWqsRzos2TVAFPrI5tNlcSkGIzRiUPUXDpHufWLeynG02pPAKH10zsQNTOQfiL3P9YPEArkoZRtkbUidGoCnUg0oIlJmUASIBFdIZ9oxSmPmhPWOd+knYa7ykbeCYx+RPksDGVnPYuPJeVYl01aGjsHrc\\u002fpRwYbd1ezZUo7g\\u002fwLQExAOdF7y0WM3rm6dDJyQdH3r3D2Z3IR3soVoAmDpbPNP\\u002feWvFO+DKhZCTNFNET9b1rYyoej3E\\u002fx7uazjsOHDq7MO8eK26x8S2sehtPkLr+9BODTVCVtcJq\\u002flgrpjnO0rAKIya2ZoPik5rskNaxaK\\u002fbicob4jjLxmdljF7ui1I+jF1VYfPIteSfs5FZFWjbGHezXIeX7bcm2GoTCiipFZ69DxmSnH9ZnpuShbc6rL1u59gnTUukoMlgDGuOi\\u002fqc2vJhGcSto6LgLReFXY8YimvBvVTLsTRlpLQPZujePzGLHkMxXepzTE0eFkCqeugXftdlp8tAYSpWeZn0ZQTbzE2Q4fN+XvO2cM+wJBODX3bp9HGsWR6a7Yc2WvpoOTygJMOT7b0qHxbuSGc34jU3+lW123nL0e2rHiOyLiJKLzLN41E5iuSwDiF7Nqqhf1bbZc9e5X927F61FT5cgNOlHYEQgACMOyax0kK7Qi+lDnqLxmyFZtMV8K+aSuUzsNUL8YjtMXF1cg2eqm2WHM4Fn6u\\u002fRyNSvJQB4L8g7qQizCk3qYr1DpVBtbiYulMsz9OHWUD7MqPuHJJWS\\u002fwGZCtoP\\u002fEEITT4+cfYybb8YCg2Ie\\u002fVDiKzd1gkbKjLM0Ya2i2RwBmSrq8T41j8rqNh2liji8RvqpQNNIY99u5yxpsx\\u002fOE2YT\\u002fhu5uBg9C4UUrOCz\\u002fvkYkOMoaWIpyMa5A7G58BPS9Vf8q0v\\u002fUpg97++fRabMW2ov0WUd+9BHA46IkY6g3TS32EBmwJWptJooyY0Ee3Pc8Ib9FMt3eaLa7om5b2rfA++HfEiH1514SGzbUnBeqaqFnDv1cp33Ff1Nvc77NivhOhH7ynaQJ1d2nBTsgrbMX9WuyYwqit5dFrxTZZT6fAhnUU2pmjGKTdc4vqvJhoTcTupUtLfPw2c2kfg7en78tLAU9BJCB90EjIaYDGMyQJW+dWDDQR\\u002fJ1k\\u002fNCCR6rjJYntYPV8fYg4shzmv7xSZmmm5LPuuiR4u+YujPSyu2LLsfnxfifiW\\u002frkNUp6dUsDp6PTTudfzb0FNAc4vmzrgjNpZyjv9fuaKuKJ\\u002f1N9w\\u002fzJpvA\\u002f2FOjaLmh08c7aR+BLz2Ye4F+xmHQo0oSkpax3ZLOLDow9R5acmjwMdMv5wlSCm7nx3K5Aay+o3u6U6oPhh7t+SHrsyRM73PX4SQ0FcLhMN1W+LJ3mJCWu1ea8xIctXxnRkmmb8VJWXo\\u002f1K9KuybrGRE+MwTiMdZRSX4YapTpvR+xvnhlndoxoFNLRAOJ9RvxuhpeZqNZ2NSgYqLhK2U9rNhcJjaSYff\\u002fopxdgJf+k8DHgaApuaFAQbf6nYKqyigJvoKEnZiiEM0StfnrIRJuliS1KHD\\u002fxxduLuWxua7ORv0OMOAUtKSMtzZkkC\\u002fHxP6MzTnkJ+AASQAQAGFoBViKWGviAPpwXXdPR25FEvfZJC9BKbHMgn0CRhn0ZYz6Xk6aXpzmyZ4\\u002fHno8U4efVEI9V+isqNhnGA8wvFEm\\u002fc+PQCbU4om6L3C7gZomc7RrE4sn5+TDfQ88APK\\u002fZ4M35TLb9obz1WNrrWVe3IOYJU6jgxOJPj8Ztk8fCXN+rrn9UhxwtKS991VGarhQnmKnGSuQEnjROfQnf7XT2vsl\\u002f2b9wLeZvpp7345c1InsyMu+NKKxFlnhJ+WJXFlzVmmjxCSKbezCMWLp9W8zeNIU69jP17wcF184F2PYMSfcvJiQaaOVxHRgzLd138WP42oK8NJmS5owYJTdpgMwSh2HkMHv3IPGSBtmPLI5hHUKdLEcTtOe34RTPej5YW0zmU4r6ki0cMZsxV7GXOzDCMpCMpKg7jSBMLFwhx7qWrWDuXQPjP0wS9zkzSzfn3Ur0P9u908m9TD\\u002fx2NGf3n4Ytgv8dwPYF8AouffkNSanLycvLZHVomoSAamECgCLNkrXY4PrhQV9IALPJZoCQ4wItE6U0zHoSybhaZ9dRZVrWXJUJncYLNpTeRRzp6WkUyPbXgn3eoNcu0NGekB4k1R5xjT4a\\u002fY1EqzUpUnRo9VnQJOYgUN4M09U8HlE7GZoAsTfg93wOMy1PY1ZGktXkHk1FFmY5OpF4s3dfDERT5ybd5eR34OwrhnxaPtFfSE\\u002fAoynURp5L43flVxG20HWX3t\\u002fOR9vMO\\u002fYD9baM4GMC4P+G9B+u8LxSdT7eVmGD6Q8QLOeSgskokLDJdXRGpycyOsgikuDTyaQJzaa4cQTxeuQbPp1czPxQJizwbJDV3OIn5Ai8CjjfJAfh\\u002fG7qidM7E9+k4WkaQc6IDog1V+KGjcdqbWqNF0NhpobFazU2U6ESA1eqhAsfN+RJ7ziHGcpRvEU7S7+O3Ez3n39LRWZDtMgdjtYrEPfQDUmBmn452LIe6XmaGh7AtHCEm3oBOJRCuME9nq1LN1OWL7olj5yXSeujCV81\\u002fFn46jtU9zZUeIHYrYekpuZeGI33WYccyldmPrqa4u8OxamTQkbqSGMXkiOdUn47Fw\\u002fz5M8xU8YqAvM0eWVsUJY3jGs8O1VRBFeaJPzzEsibtu5zJ15LbPWxMN+OKGnTLyOqSfAZXc1sfGdtzOyUHPZ5sy++GPBD\\u002f\\u002fLC9dNsz7QniFfu7aV8gBAMrwVt1NQO+V4T3wdaq3+c6d\\u002fNzY+pNTXVueYqHOb+BwBsnAS2dRAbhJUfulJYH9623y07P+\\u002faNSwd6gdPLCmF1WHZK+No0o8BH3TcwYh52llnQoZ97+TDSO0Oc2nkyP08GpwLYCIhkCPNjc7A97XZKhm\\u002fmujF647Rmh6HkUMH8gzvZ81TesyifquWWJOD843\\u002f3L391JMLO\\u002f7mAXRIYxlL8FjGDUwAq6C+CsAPkX631zscVzM1wg6wensMl5dMh0oc9XEVj4TN5\\u002fKmx4QZKrJybuzCkMy8y2fRFF3P6UOM\\u002f3kWycaZGh\\u002femmwJs7\\u002fQ0eWyncyKLEUgUZtQ8j+p6eDNOKIyVeHUzKS5ejn9bWQ+25BFwSGd4TQavSzoDtkxQr7mVZ\\u002fwmiARsKTZhVw9TUixdeD9Ci7zcZv5P\\u002fYQHiHsw\\u002fAcgoevKC5e4LUzUe906j9AoEeMa7LaRUIV57m6w6N0siV+g82C8WRG3iC2DkIyG8AuD2E1ylDxruXTJaR6CpgR6ZSlpWUzCrhDv14AnlJyEvg8LNrAMElSG1e1MOjvg4bGrePjf+WBzOIecTkGGfhyLvs7RF6zDRpX5agNeUeqG4yuam3migSjYAClytGIig50RNjCWtOYGI9ziJF3hJIZff+CUPjsdRKXUi2iMEjPhr6sHyjj71wah6Iq08BUQ6EzEIAzrB8px8vT\\u002fCc4Ed5d1\\u002fgAm9zDsz\\u002f8b77k+7i55y55nEXE9hWgt\\u002fj1+UR5ljWLD6qbYulbEhfxM1LNzPy9ly5ro7R8JTJ6MfEq3FF7meiQMWmj+1RNneDR8JoEEVCT4vmvaYMXyXBc1h5qfL9Cau2Wv5p5IB0R8YgKyrGGduv1E8oc\\u002ftd2tmPkP4zNmdFNglHntM\\u002fZBdzYtBETg\\u002ftXT+dJGGL7FfKVCYshVMHezc39xrkv9pdAwu20HUk8hMaSLSZHLwaqltVUeRcI6gXTymmB137cMYcoqNxB3MkO3\\u002fV97bjUudEElfKV8+kp\\u002fqJVXwh16GfF5cby9\\u002fMcnm3FBBiOT+wLBfPIQmqizpY237sRiGfSnhC51DcLc\\u002f5Q8EjbdTy8rvEA7FLmsOePEBBiYRHnbZ\\u002fPU+GGNpki12R1jhAp+HXn6vXMGhM9FiOgOMvqTQRDzw5a\\u002fY2ePuSBPbEdIUCBbGF20cGISUcxbx40yOUUxcnS6VNtNdx8+6+NkcNKTB9rKME19SIfW0ds6CboZ4rvTujq7u3cONVvW1kj\\u002fq52v\\u002fjsIceLwmoif0FsdzT9bbyxl+26TzGHZ92P5tc3ycva9AO+u+uvYzTUqiJkH3sbkneVeS5lTIMieKvsvzn9x23oa2EQCnBZzpIxIxPGY6RQFUCIQhvLCIwxK0wI5i7ghSZiy\\u002fEIhwu3anoRh48MXT8bTrXiKLkUqdGV72pPpTV4XNz5AYMc8iwc6ce1zlMZBeq7ISW0mzxUvGiwStjHGXPIz2xdqsVTS0pwl0XdCod7jIswXa\\u002fkw5CqeriiueKDlmjpbeeXOStIuOQQjaPQsRrwI\\u002fdXjt4m5pk2peV4rixOaZDPVi6RSUrFEB+CHXpexqE+XUgUY4y8Yo8MMo8HNZX54klf3D7mvEzNQW1ie7jm4nj9FP6VoHlIqtsn+GG+psAkuDXIk2Crxh\\u002fAOCgPIWnGCyQWUAp7jTL2knwZ3JqKUUC6IUjW6CDEd1us7uWP7Pql8HOTNb47+Uz\\u002fQv\\u002ffK3XFLW0nodDVlcGYvCmMfPSneDueVIOpedW6Eb+u4Hj2i5Sa1dwHjVdR+psna5bn022DgeLhAvFrtoRmDMIyfqXU\\u002fXXePWsb+5eBvpDCOHREmo7EBMh060rPQCBFFlhFgpbNaJVekdIv1IfBC0svXFKLrrZIWXSO2\\u002fZhrdNmlUmuW6nBH5RJkrkwhx5mE+oy0i39AeUzDnBEPyeZg245mQtJVSgc1wuUJDoeVZgdW7iOvW+Th9okmC1RPKT2lRSN2nV51oF\\u002fERYjJR2vC19EX9h6FTTKLn0h2IlZlYS0okr0jVcsLc\\u002fBC+8RQtGJpSv34FIQofc+HzBXC2WQgqGA2UPSRy0VZTcMFi226BCqleHH\\u002fMzUt5B0px8N3cyXo6MRRDKy4FEbPUHHQWRiEVQ9gIVRQzJbsCSNHp7iEDt1ovAS6fta4xJruZEX80lwfkVWdOJYBo2nd1PWWzKFjOHupsBttxuxdsnnykwG31+T\\u002f61yrte\\u002fOJMj6Hq5ElxCTmrpKdW6\\u002f5xnv\\u002fO99mi3pNtO3UOSHmW7X9BFgBL5LLDaShjc9io28j33GWfzS\\u002fgQq9eEWVL+1kgIqsSTwFEX09eJGqS41BhjUmoj+ikF\\u002fLMNW9pvef7xyF6K4YOx4y4Pq9JGdYtjZWji9UuqautFVawlHHCNDQdfuP7CNsJecoEsE0PUpCkZeNQoEJoENlZXevNlrjFw9+wFN4svnROagGAjPezI59+ZTdJUFVS62D44peb3EUtG4klsfvPX21E\\u002fJ20GtG9jy2Pi98CyXF\\u002fHtM10v7ONnXU67twunfuBW2O92xc96H4CWE9gbBL4pdUgGKjNU2lfizd+x+8BgEqi4VMlCKg1QL2AdFIfAGYILVjotN1sRb\\u002fbkwm2ATzMHxG5ykf3ZblIGviJ+7EAhnWm0gsmBxDnv0LH0LI39wuHguiPwW74ko0xkffp+p+G8cT9J9avAnrZQe\\u002fif7uj\\u002f2vWmBaxSRwUn2Xs3or+yL4Z8DPj9q0p38v3b\\u002fwbBp8H9mYUqXTHfMkJvWr9nwJyjAQ7HlNhWfumTzAYN5mesNhZROIvFeZ6imaDqaPcwRPr6tLFElU8z4LiWfz0McRCsNi8FOH5Mn7ahIRN\\u002f17HPBsTnJ4iyVrPcNTF1ET1UhgaMup752Aro8bjk00MDnGl5MKnNvl13uQm4tROzNRROXnHLysrdJR34narfnP3jlIPrp8e13zFzyskHnDO0vgNGT9eYrG0YkpUgtHYsg28Pov9xE+At6MzOokHO6UjrMNQ9fOKdHd4Tkcb9jiPSVs2VFVojLiXUrzgFwfxb52Ts\\u002fHWXK4wiAow4K9ugK3A7SA0wBog67DTt\\u002fFX7pRV9Rvg5OWYzxpQc3IyHpCYOrse7li3DAk38X8u6c9newjT6sUQmcuzF22GUWn02mV5D2raLfFXr2GAwR7tlRRyJO+5+5Lqr6bidM7OUfazQ1rB5WwiwNcQVZQNvkm\\u002feBrruIovn8U3OFjahXkXyuCxeYxshGD2PAAGpAw9sYDxwrNRZwfE21xBZK67oco5zTufDLAZSenenazr46xLm9Gx0b7eDCTgxzV5rm0y6a+BrLwtgmJ1tCBG3FzQ9RSVNOEop7EyK\\u002fTJDsfBavQxWDvHJNdv93haAnKgmL2u1ZX3J60LzBdLkcuiLS8hNpiy\\u002fMmyyXFgcyU3hbiZglRgHCtHap6mSpsXKUqVDcJFpn8p\\u002faYiVp\\u002fBd2gwqs+s7iZOlszOO1ukPEA031lnhxsX4XbdKFkONEREdgUyUaPxMSQ4CY6Oj279P1H4Asn6fzme91A9QQZAGO1iCwe4g1pUN62w\\u002fie4+IdZPCcvaKrhfEzw25juzeFXWmwg3HG34aqa6aJEQ6elGG\\u002fzKKT0TVQ\\u002fXEmy23bGFcvZyZ69kdmMNNy2kKw+mPFVPNOSpNFgz6+XaLygKe2mnAiM5t145q6hjk\\u002f4SnbV95nXQSZhDfimYSnRnzL7zgbj\\u002fdnTfxqEe23t0cwx6rbO7Ye+npMXMbzqb10Pg6iI1jIiwf20If3kZ77HxBeP\\u002fn9Aczpv\\u002ft6LhxztO1Z3arEoZ0J9wUYnxJ3SNBJ3w\\u002fHnbUnRIfGJtlYaF\\u002fj4jrMdS2ZjqLb93dQdIYukUSYDChuW6OAuewD3AJ3iLFGIyqC+Xhio2\\u002fNqTo15DHQJ+ao2P3BfXqOpgjrt4FSmRvY03fvgNVOKoBRHytezZNHSi+374K4btEeScXckDFYFPcqLa9ks022diHK+rdc6\\u002fne7cyvyfY\\u002fsl6td1rxA8H8A9FURmhaOJdwCwMRIaqCA9DyLx3ri4BhEFHoHmeVhitrwdbEd3f6DiK78fCo2Kd2t+vQLHgDFSZ8WppcvrjITd7LzmRAdw0JCMaieROP6gj31TY9zgusZSXDG2kYU7ILMgNqXWsg4M4iMdlpfkVNnWsU3ZCqvkvV+qssCG7sYs18W\\u002fQ3h9UG3yuMR3G2SFLR86J9DNBzNgnWfInqzSu+0+TfXfT3BMNFPs\\u002fD7aRon9oMFITybvFfTSmyeskMBhE84OqgDD+fMZSmPLtLMLwAZGTky9gHPQR3mDgEAECoWjqp0\\u002f5oSCjdHHYIbPoTTAhf56TYTT7s0FgiWxp7aqh\\u002fJIvnDIf9nM9vOOsq6kOS2usRDGNMNeL0OIkn9PytNQMwSfe4FVBcgInYqzNySAvPpME\\u002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AEYQFkMsALQOKmCOXFFvCsl82pUXI40xlrVkADE4zLgBjxg0tzyh60CcbQXALAqI6ZYCQ4AMq9kmYqgbB2mnWU2+qb3QGhcStCMCDWYEbwgAqlcAkKUjS7DhdoQokWK3SkXwrczcQFskc+Uli5eotxkN\\u002fOmLn\\u002f4Xzv8FolUcDkapiRgdfeM3fcMHH3743nvv3d3dxkhpHMfdbrfdbGv14D8AuTx0gOqJGKb2AlAeml207glPc4isLhwSiHJbjMk6AxQH2UzuLTD+U5ylYwMRpgwSXBgADcI+yAwVWAYJxWAi6kICsGUiCELR5Q4yVxwgASCwaI7ChiTSWRteA0AChTBSksAyAfQwa0fuQHsv4bPKiXeRkNuCiF49AcCWZqAPUdQJ5l2DGUBiEmQnlORCd5Jd7jdj16WqarK0EtxqzLUcZ3mli6oGEsxH3Qf1\\u002ffeu3\\u002f1NJ9+FYCUSRDsXfv23fPPNzY0lg2EYh7EUd6+l7va7qIXUapUbNUFm+NQ5JVQeJu+Shqg5BKWHmYNowaNScXSWjpLRAOTT7Dc1dADAhi4BCKTuVDclP45OMAjU65oWczMJVPkgO2YUAAAgW2VGeUiss7Y1H3WRoH\\u002fUA6gXJR23\\u002fjPJNhFE5Ec5TlREAGTdOPYew61I3Z\\u002f15XpEpCMApkUqr8YGLCiABh61IjT7+cjuvCMJMC1NeyehEYSiZ4Cq4BQuqCJmkqBIsFulKmchQTM6LC3NSwVJI0XmRFfuWbxEzI9f\\u002f9+r1y\\u002fRl57n88v99Ye7D++G6+\\u002f6n3xPrYXGlOyrvvIr\\u002f6uf+qlxHIdxUDPZBuX1z33Zl33Lr\\u002f+WHGBYpVPmBrpHXz8DEBdJgwRBqBeDMdlx1B2Ayk3tjjOaHDOfZr8Kg3uTXQC6C9MeANSXJT3J9cUYkPlQCXCRMXoTn414xKCo7lTvCsHuaUeQoMx828YtAAja0wW2YZwDgO68OzTwBADrqIq6cZIE6o0DyKfZlolAd9aDKNeFhC2MQPekJzC+mjrWmRpgy2AAAEBReTl2T\\u002ft4iS1TeT6k4+heEQCit94BAASvksRMFATnMJMO1qikaNRY4NU6EkxLygWImlAnP3f5j+VOF13m+NTJZ95\\u002f\\u002f4MHD89LKb\\u002f07i+VWkoZo+kHAeGrvvqrvvnXfXPf9cvFMi\\u002ff60XffWLfbgrpjn6GKcgWqX40gMmYQOlOons2UIkYPhrNbPnWAlC5rEbKjZOcpKVxRSJGwwJZX1cka\\u002fN9gcqDPH4cJkAAxAbpcaovSiMHWF\\u002fW7kmnbYBE7aqtO4KtL73OIKJxZccG7PSf7x1EWpr2obMIABUTiwBEd9aV67HFEAD7J125CgQAwvcgkZbUXesc1Jdj96QnMX40EPC7CnCaw0DdC4Mk2DEJCESd2juAIEkmlsvKY9IZQUOxHppAhTkgOut1AYk2osA7n\\u002fmV+\\u002f3ugw8+sGSbzaaUkswkERDRpfyd3\\u002fGdDx8+fPjwYWfd537xc431+vf73Sf3ELg30NO16hnjGb\\u002fac51gwEYQQHEB0lENCOHW+HpIKRkJEBCcPnp\\u002fHmwMQPlRLhdVE12ZDO4E+mdLEP2zBYjy8UgwP8kEu6d9fVkC4O5pTwBHWdvWd9DW00kCp1ETiDXKR2P3uAMaeAB872wmSWIZUCms076piIENMV4NkRhAWiUC46XHq2kN5SiznVHXFQSA8nJMxzEhBgBkwAx0xuhSQn7nkuyE3oZ7cYBkuahGllt3F49IMq9y8VL3YMc2GCMB5LM8XFaQggh879d878vXL4149fLlZrfZ3N3tdrtWDPHZs2f\\u002f5Bf+ybOnzz7\\u002f3udzypu7TUaILYCRrKZmmVa69nIsXheZRRIeAVWgIr1lVyEo9AIkd9FkIuijkxyvSn\\u002feIZiiKJ1avYm+IMDW8yIxIcD+WS8\\u002fmBG6p32jCKfftWnn+fgwdAEAGoDy4UiyvKr94y6ix5etIUgnc7uLtCSnAgCom1o2NS0OMb5z30WRCAAiBCbkdcPSzpKuHYRFz\\u002fEsgfArj2raqQEA4FuIgNCdJUmBTaBAUdVbnUQS9Vbubo+MpIF1Dzisp7mFgKezrtby53\\u002f7j+1u9+9\\u002f8IWb65uc883NTanl8vKSJKPnA5Ec9sN7773X5+78\\u002fMF2s82iBOyfjgCUJGeU1Y8EQMeGuyiaLKfUGfZCjPEoVocDYVsPLjD5UCcqYrwa+\\u002fNumrphPjGS5cZt1apbNmN31BPQriIAh7gkATLmBmjrA6J+5+Wu9m91cUlSzvLxSIsnUF6VwCa6fiD81hvGUaYYMiWCKHeVoA+wBQGQsGypA8h7vMjF055kvW2ya2epXtYwlYkgGswhJhFsDQnWJSm6ICQIkWjo5hOD5FeVooEGlhdl9GKPQnytvj8UL\\u002fbMghd+8Nf\\u002fgVzTdrMZhjGnTJGA0cb9GILiwGKxMFBSGLNevXpFMO8fjzJNCEFJ6dLGd5pLGwAeGwezcHMC0jKZJe3ct0omQb6ptiYoJgDighgggEA+ShqdZKgsgEC8DYg6A2Uz+o3682kQBWIPl9sEqnYN5rlhLs9r\\u002f3ZHEDLe0\\u002fAA1Hi5oROQ5NMOQLlpdmcAXgPnSItoodNRAqJQyKcGMLRFiznJgXG5LCTLdQXZnbZHbNWMqeFwAig\\u002fyJJ0J6jVy4zl1hG9fpJiPk3ldeEUjCwvy+jVVdvlR6XWcv6ZB586+vTN9Q2EMo6Qyjga7MWrF0YKNBiks9MzkhQgNUQBE6ZJRUhEvjAA3YdN1QDQVa27CoRiloCyjcFHewiQbyssrgSBC9gCaW33XiQA9arWqwpAG829a79xEuUq5J4kVUEZFBAjYrVrnawI5XmtN5M+Jwnrny0w8QQZE3QE2L+zjCzyaZdPuyh4PJQWbV4EZHfWsTPrgvoAWK\\u002fK\\u002fv2mrwPjdJLH16MIAUGBcl2ZaauJXFQ6Smmd8nkbENoRedz4qEQjPQIjCZCsl5Ug3OGtSCT705xOUjpJZCveH\\u002fz6P7i5u9ttd\\u002fvdjkIZC0GjjcN4enKaaAYzcrVYxkkMpuPIzkl8O+UXyeGBZPchylqVEgmi7KpRadWXXXTbgCWxl6B0lowWmkXhsBIeNdXzcmYUenEeA3dNkAGkLo0XYyMeMV4Vkvkok1F\\u002f0A0JQV8CdmIEdQcAtk4k653n4wSSQLmsMfjxfWgIgFh+cgkg2EwACAFgvF8gbEkAaXIFBMCOKiGmALh\\u002ff0dw+cmlgP17WwJtCJAIoHuYAfjgBLFocycgNAA9iFZZHtEvCqeKE8DI\\u002fCAPr\\u002fckYpSM6nB1Z7l4NdLIfJz8uhptu9lW1aGMw7gfh7EMo9FevHp5dnz6Pd\\u002f7W9zdJcn\\u002f1t\\u002f6W4rKtheTgLVJ44WLGp6OTSQBFPJmLi8gGFB3BY1UAoQl01n0wxXZWDIPjAFBZe8CanEv3uh8FC9HfpAB9A+7\\u002flHrbNuC1hOlWawC12SWwuDcYmhLpqMcIJGod+63tUzTtwBtYSCWn1oGumg1JclyPUZMxAJUhSpKOB0gaE+MaEPbCZD9+7twDjxA5G4N0IjXbIKNBBqkoaUvlwUEF2DzNmRMkC8\\u002fvVp+akWQgWhKupau3WAGI5lO8v\\u002f0y7952O03t5u769vb67vd3Q5iYvqyL\\u002f3nnj196+\\u002f+7b97fXkd07gxZTAJdIiymS\\u002fcl+5UdASHZ1UQaqgg2I14UwlYVESw+E\\u002fwPXxAuanjdUCqOFJPCVJTz7awfJQV6AKAeMSmwabQP+qsD9ICoIo0OgjLDIpb+LMRiOled9xztEsLy8dhnWlhhnYONDJzwqcFxbQhCKDc1XJXAfpWkSod5TRNEPXPFgAW7ywX77ScLRuIaHHmXMtlKeF4NEVqwPB8vP9WLpCXBjA4kuTy06vVp1bJEkGCBtO1kzQai\\u002f6\\u002f7\\u002f7dYT\\u002fcXd9ubu+G3d7AROtzV8dax1KG8R\\u002f8\\u002fZ\\u002f5mf\\u002f2ZxLt23\\u002fjtwXSiZZoKWCuUFV4YcspLxgeaXjS0BKgVczJT0EwRbdzhlHjTfMxi0tbMBLkkxxxuTkty\\u002ffyvcbbMt4e+nF17+HaOFOqf7roHnQIjQoBMjNbNKlqkXJbWFqEXU35KKUjE9Q96UOH3D+CQ\\u002fuH89AclEWI+wBA1l0VQwUjlEQ6zvm0KYwo3uITy0A3QrluHYu6CRlHuSzjBPN4MQLwQb7XpIVAAneuuxg7kaAlLj6zCLEjSRqulS0FTru7nVdPTAbrUtel7nh9fHZy9vTRk2W\\u002fNNj2bvP6xas+9\\u002f\\u002fSt\\u002f1LiZaaNKdEM6c7VSFRXg4UGZ+YCG+TuGyeEgAWxgUhpWM2Mkrdw8TeGk9IkLiwfJobcQEB6ahDdPFaRhpvx7r3um+yyM7QmaA+DIFAOolhOtSZOgriUZaE4Dxn2dSyqROjNabcv9jfj9m\\u002f3iNFwSChe9h3D3uIc3o2mMGkVlpORUoxnwjftolngMzs31n0kyhHqFc1PITmUC5LeLBEIBDMbZYABtjayABLASkXn14sP700mIH9eW+w3Hd50d3ubijC0aXOaMtucbI+Pj85Ozs9e+vJs6ePnzw4fXB1cVWHcnJ08ht\\u002fw29sEkwzGtd\\u002ftgeQrkxQOQaCoAQcIrWJPn40EobC\\u002fkHXFD3NaGmRzRjnRtKMo\\u002fKyaxqGjSd9WyfepO\\u002fDFse0NJJGcvK1J2mJ3VnfLkGS48dDjpgpEqDuapAJAMF0ZADq3ay3GVwyvG7+lCAWTxrfDBctkuGcB4CQxKSQrlCdyQyM0\\u002fgl24hrigFIjh\\u002fsp6fYcssEYCcJQjDWeD1I0RWSy21Jl9dYhlTGKucpw7sjZnyH67GWycfDa\\u002fH6ve\\u002f81urV4UyWcjo7P+sXCxDVa3UHQcBS6rpuuVzmnH\\u002f2537u4+cfA8hO2BUqHQJvIULHhKMNM44Mm6AaNcrAclH6B72IYH8fKhdZkCiBlMqdp4VICCIgYXhZuiMTAAJAWpjvFd1XhEBTEMOCLWi8Hgh2Zz2A4fmeZLka8mnfYADpwpLaerSWJG1pAP32APDu4x1GId5CQNh9vFs8WczoghCqteEdSYRTkRKI8BSIJ+dfILHeRVe\\u002fAxqsToJI0\\u002fgbAIrSg26qF0Dk0268GoimIcrWA+YwO1OsV9Xd7dQcwl1NNCUlSkogRGRa1EJVloiK1WK5Xq9FjONYvQrwWgVQNNo3ft03bLfby8vL7CDoUQ4BAFUBi0EkCGAdxjkBITAol6V\\u002f0LVqUxqq07jgeDmGNA8Xw+LhApCI4WUxsmw8H7V1WlxaXhpJ3zuBeHU6MzX5owRQ49XQptkVqO8JpqPmaEOEB7V8i\\u002fwwuzsIe2Tjy9IoHT3YLbAkBBICSy12Zm0IJILgEqT5xg\\u002fVqzGNMYUGMScfRwKodyUfdwR2Hw4hzc62nBFAepwBUVATLQGgUzIyXG5FsG5drLEsKuxZJWA2E5QoUSkJlKRd2S3zio7iddyNR8\\u002fWCQmO09OTxXK53W5LLbXW6l7KePHy4tWrVx988EGtld2fWwHgVQGoVessExSDjsQeBElicMKM7J8sjGQlGcqZZsYBmlaW0szIZKYaapqhqvORpWWadTVJ3znJsD+0mFsnUcOJhySQ+tbntD4TMWWECWTaehopT9QnMX44DVCmdN0nmg9zS0qWy5JXE7sQvlG80FIryaGcgCSSKYdFukWyt\\u002fKqtPymt3eP5nFjCIxUMV6M0eQ3Lc3q7rBYO+our6aqWt3dVN2rV1dobC9eh9vx8erRt7z1raGQq6qkBw8fVPnR0VH1uj5aHx+fbHfbFy9eXF9f397dbTcbSQJyGOt11mvffNMb+QDt4owACXKRtfeYsQGAcLer0l5OGGmJ8qaoYRTADFVBJCSi7qr23p13UXUAXtU9yFKImATwyAKeYHMB2st6WpddFQjPE7AjhLROzTkmSoowNZOPU\\u002fm4LUOjiBXry33\\u002faMIYIMhEl5MMjWFrktTeFY9NEJEM92YAXp1g6izQJRDrY8urVobFWUYY\\u002fTJFUBKAqnySxpsKIbQ03cwgyECRFFllTvQJ7mKIvwSAqFvPTK+2rzITCRrprKoXry6q+6sXr1ar1eXrS0FjKddX1y6XlKx1LLn4C6e+G1vjANCaIrXjRLK+qgBIEkxrM9A6m3pONFq5rl0XQjmJMknZ1MMykqiw1LymI4RTRI01QlNMUH98f+qzRMcLAJBOkqmpSAQHAvkszecACKJGRDxFhIF6mkEiSbB7nEm2IQpJRo1IsFzXiMmrxEmC08IYrQk5mcdjqSpJcHpXeVX6ZvOJICUIwOAhu5LG6xoSLGu2J6GGL62780l29+FydPeQ3ep13BSPdS7uj5ePvuXtb\\u002fUmxO7uVTETARDjOA7jeK8r116bMTiZ2JgNcKXTkFESyI86EvVVTatmTlIBJxkO42Itzi4xVHvfUNWucTDJ\\u002fp3OyPF5syIRKFcjs5EM2QYwXAzdg27\\u002fhR3J1mhVwBgTQdVrjdWiMgBhFRmjIz3ZgWvrV4fdsdF9tNJm1COKrC9rXkS712y2GmVdqtclHiJQdzWvMgBbWOCYl9n3k98b4Vsn2fYdIAj0b\\u002fUEEG5ZkkAWqNTwIgyNlU+SpHJXXK14ktFpRHrWRzeiO+tcVRcC4TtPtFYo8tX21evtq0fLx7RKZ8wlutyruwQhW3I3gztkkCBRPPlLj8r1GOpIAAYAyK0hQZCsXJS0nEYyoIXwkU1MSdK6zmyZLS4bxjSyfxYCYjSWj8LjKZxPQdLb5B4xIuqhoc3KAegf93WctmQAgk7Wtd72HLiyGV0QQCwz5\\u002fh6QJSZtBwCyW6VySAb44STQvKN2IZ8JLl6ttLg7TFaiK\\u002fvJ7\\u002fgQB60VbI3bGTCThC8VAmAJMFi2O11bEIcy5BC4KpXd89v5eqTd637\\u002fsN9XN77rZX+ZPHkW579hjnep0fc\\u002fWa8\\u002fonnP+kZka1vqySe\\u002f+WnIczlVWnlAQDkhxnAeDE2ZgPzMgVV6l0IxayoSVruE8kQjtDMRubTQDfSkGSNWSMGcUBQNWy28R4A0FAB9I\\u002fbUh8AZWiGoXLT8O4fdsGQEGLZtY+aMyFYtwf9H5BYl7pV4Bwlb4WMSzMzmm88TlfPlsG+GDQlI0dwUkts\\u002fES\\u002f8cU7\\u002fQRwK5LfVklBzSCvJG\\u002fqU9FMuuS7CSe5u1ye38p+D937QOKU7l7l4\\u002fX4DY++8bNHn72XQD939XP\\u002f8PrnInOXvDRO4qN\\u002f\\u002fy2HfFMl+VZSYzsAsoOYkASQF2lyYJsoROY+zSQzMi3MzMI\\u002fK2JWn1mS5MHEAewV\\u002f5OoO8HjIogDQN1JAppOiRKVsdTrNtMVMTGTgzZPDRA+CkH3ykDXh8aLJFNnpPWr6EQY2RDtjjujJTOjmdFo3UlvtEk\\u002fmRk1iANaRmSDGag3oW1JoH+nD7rVmxIlBFphdQ\\u002fd+81kWqfdq723ew1mQYFolfwezDxlXEYDPN6MX3n2lV919s\\u002ffDDf\\u002f6Qc\\u002f7nKZXHL3MtZ4CwA++Q8+EbIcoW5dku9rkw9gbuTCLxCY6tnEIrcuFjnBTG1nrg8acfWZpe\\u002fnkRfJ1lzVGApH8GZV7p+kaDB837htuBjiLOoPQFJ+kAEhcUIYwJs9f5KgRrfoBgaEgbGZ0bSJZXPWB6JmiZZX03mXEi3+yovRyLzOc8UJppO8f3\\u002fPeOFUgHTCKGr86VBuSW3mPUQ4rZNCjuX7CWaXA\\u002fPasgZwlY+3o8vzW51PPSyXI3O8GuZuWjxevao9KMmz7UlOk4YQ1xwvRtLaqAXCVlyZShs+RN0aFXMmqEkao4aqsIVp0BxjyzR8XNKptRwkgeW2hj1hAkci+kdZQNhlJKGT7zRMg0hJM8b5PI11hBS+xy0TI5cA0NwfA4gOxko3U8io+cYzEoHEJAOE8XY0Wn\\u002fSc2mSYnSmIvQgOH68NxpA37qtc2SbjjPJ5SeXw\\u002fsDpqqmoyRXrEkSRRFAPu0EDZd7AI2FqbTIJCTEaHDxcBEwE8nlpBkQtwHUu5poBOpHJT0LWylTl1zO04XLh+uBRroTtGSSF1TK5cyWs0ol2n4AXFh6K++f7xRD02mmLIy6gSSI1OeGaxwwgazQZN5Ni0RSg9Iy+kTymAI7NRDjywICBeHlAwBAOk9lrEyBpOLXE2ot7XKKt\\u002fM0TpGAVMEMGGN5IAguqY1IwtRwpdHNaAkpC8WULEEVAgWKlqxuqnZYPDS1IklF5S68Vhk\\u002fvnPQ+ic9CYIAY2pyeH\\u002fftg9gqCKRLqg7X0ii0J8t9pe7VtNFJ8lLODmxGfjAvM4uhfeqx7ptWPcgxYYWUaL60ejy\\u002fpNLlxOkORz96WK8Hkga5ZKDXaJLBSUnmCeqlrbsXHL64tlqeL4T1D9dABDQP1yMFw3j3GcSFsYLNIHOC5KxSqdhDsDWbR1EKx7k115jPbwASNF5Skrnyd0FaZQgmiS5QxIfG6Tx+RCIuksviqB0bv+Lb\\u002fne\\u002f9Mf\\u002fU\\u002fqbZEgSqab\\u002f+yKsA\\u002fxoVC++\\u002f\\u002fyPV+4+ALJRDOLyfCEAlApOmaWCEHVaC6RIjRejvZwIQFEva1GS32KVctx5NNeA2xhoY+iqtabitiFfQcQJNPOeTbVFejPFlITZUSqAheYCCm2DCOQVlmbYoDLFg\\u002fp0vpTS5c2722bBgDqZXV5Ok8QQRLO0368KXInnICDkGfr+Om\\u002f\\u002fGUu+bbwyGIxqyThIENz+QCMF0Pq08TNjJxJ65YkabTAmHEVqzZIkwUpCMAcQG0GfwkAxAXsKPSaNNnzgCjBoUjj8yHuPXv21gd\\u002f\\u002fX3cRMGmtJAgp+pRvfzxC4Ix7\\u002fbkLz6x6ENZsq1lprzsUsrZUrKcLXFkTqlbLSImWcqWkqXc51hEGb9mhlHdWU+2IRMBWxqB8cU0gSGwm+xXu1bw\\u002flkXFYnLsi+SVOFTjKRyO6CzQyK5S7aES9GYRpO8+fzO5TwybzHurnSeXD7ejHOkvDXekjL3oGA0v5NLdmwOH97buRrJ+k+FtR77j\\u002fYA2RMI9USC1jPmNxk6i7Cj5INCikO4ZaITMZEugLIedYAg6xGI1psaGEuqtzVqyiM7ACxhSb\\u002fxv\\u002fNH\\u002f\\u002fav\\u002fU2\\u002fNm9y4zth4sIosP\\u002fSj39hwJ6wcHz58Pd99D6+8PV\\u002f8evstiZLMmknJceyB6ChZssult1oKzO4YIKa7yOaMgo1lWM1aVQXJKE99h\\u002fsYhEsAFAaBSjsp5HF8HyQ1D3rANT95OZgYm0tst+NBDRUuNo2XiCB3bujS8tPJwcoM\\u002fj6k0t37K8GwBGmPXq9rDAZbZZEp9PMHDJlg4HuMIMD5rc+vt4TNDbnsuHzu8Wnl7tAN3yJie64A2NVJ+AkgRREIHvrFmQ4Ek8Y24mRqLcHly52grOxkVxQDbeQkNsI11US1\\u002fTbKuHx44f\\u002fzQ\\u002f+tMN\\u002f\\u002fCd\\u002f\\u002fLd9y2+jAAUN1UQZ+rmf+rkBQ3BaAJxgb+Nt\\u002fjd2ZVenX30qCBQc2EGWsnWkm9zkdT\\u002fSZKsU67KCY9BCuE6SFrNKIcAYPtxz9v0TBBBIZxnS8Dp8T1vpho8GJPB4yg+AiVK9LhMnAAD2zt4EjB\\u002fHwg7t3i0uLT+dHaSbwRenvcv3VwNAyEIfTyUlYIGKm0lu+TwTB0dLjbLj8GtkC2C5a767wVkA6121QHSKpgDQ+hQwA8wnXSTPsbOQYMd5RsIrXGFm81BEVc41uIS7u9d21FA8+s5v+c6\\u002f933\\u002f9YBhwPDe9r2udl3tOu\\u002fqV9Txy2td1d3Z\\u002fqd\\u002f6qf3GCLNeDjGEeN7\\u002f9F7\\u002fMDuvrApXqqX6rWqulxwV23qTs51Qg5sZ2gBxD4hmFiYZiI1fLhvEWC99XCjbxwNdA9S9yAkmwAsE4JfH1zJAKTeukd996iHZoSgfU1txgwBCoHduyM1NY4gwf607097kilbixQoErSpeTIYf8V\\u002f\\u002fFUuL5dlHEroQ5cL8tvikj0KRxwIqjcxvUmzBmx31hnaSJfLZDHUjNEwgsvJNivfyiuo3ozuaJIKuVwmyW1Nl0I519sYmsOOKIk7\\u002fvwP\\u002fnyFO6rDHV5RAUXPf5Lg4KxW\\u002f0l803xk5Eff+aj79XmxXHQpZ+u61OWUu9Rly9ny8nSVW3zO0RinnCxxi2QpWeof3zOAdEZy90u7CVABkLT8xEIt+KyNylWZqxaBJ3ApNmOIMLzcSZJgR2mO3HxhiBOXLz\\u002fVu6Y2tjW3KpvRpVqbHMRbXO5AXDbwJ5cwBnIEeZzS49yIBhDMp4lo0IEkWK9j\\u002fyJyGYOjaKyD2ERtvl6RA0KI+5QfLQRI8kBX7sW5pstdNcQXK2EpriF3VP2jH\\u002fzvRpSCMcRxxFhQBowho\\u002fdOZvE9pJzTF5Sf\\u002fX\\u002f8bPmpOpYyllrVhDgYOj\\u002fIQTghfkPXTEvKAADlVWtBY0sCAKvPrpafDecsAli+s5KoppoZcum7ih6zhAbq9cqHD1p3OkL3aNE9WqTjsMw1iV5+olu+00FYfWoRcQdqgtqG+wCMNjE3AKISBbFi3caPS1P3zXaL+MvnXduPoiEOAOzjAkRDuV5XLOLBuNHuxNQtAbBVWIDFDo5Q97jrnnSSXErnOZ0nGdzCglMDZL91v65y\\u002faXf9x8UjBO65ZeDN+vh\\u002f9GjTOgWlGd4mpSG\\u002f\\u002ffgqqUeNLOdmcvZN+oftEstbVOHqABQX5WY1poOAFh9dklg8c5qSgop7FnwffRkxB7oZ87ReDcI2vzSne6FcjX4rvou9BuiIIDySXtR5P3GSeMEMPQo0IwBEUZMvjmRxgkwn+d83hbQxCZyALSPZbJEW43dMDczf1UbrI2DMD4f64uYHGx5S1Rj6DjkUvck5wcp9pBqkmQxePB665Lg+BWf\\u002fvKvx9ftJwjLF2Mc52+gXlC+CNfpGPcYfs13\\u002fRpT2v38zuWBcaArueTsxB6Bg0oFIOiAMdAoE9OCLRBA\\u002f6xHmYYJ7T94mVqQhhbQC73G2yEABLR992777h2kctW0saS6qy2BNF4VSePrYXg9RMka+C4u5p5zK09aWz4xhPUmAAIQfdEGRfP9PLCMrZL2wIweiY7sgmEMAMH6svqrQqJ+XOrzQoBkfdH2qgMAE4A6VGDmTO1f7obLvUv3Ma7bWu8q5HDR8Vf\\u002f5b+6xXaPfWD8RZgFuoH6L4OzVpTaTmpFLSgV5T\\u002f5\\u002ff\\u002fnv\\u002f6f\\u002fwQ\\u002fsoboKd1dcaHQ0WIP1eaNi8C4BxfKZ5MjsICdYtU5IN96iy2uuYbFIcEAIxDASVLdua0PrWyEzbt3SPGgohR1V+uujlel4QkBGi6G8WKQ4GEDkrAgF010pFaefGppWshqbC7sQHVUAagvCgGEvAN+Uy3BmkiHnJINRKDpdABtTvceb6CEHFu8WYDKEITD8LJ5L4+X0blwycvd4HKZZAo23GCzwz7kr8IHjHvsttjtsd9ie4ObW9xssQt5HTAOGO5w9wO\\u002f+gd+16\\u002f+3f\\u002fib\\u002fu1n8PnBgwB7YgyogwYfwV+xS\\u002f8jV94+uBpOg9zf2uG58MJrjPbggxBEDRe+\\u002f75EKSMugDSVhiEqF7DuKJ4QBwQSLEeRJLqrnGRrRJXNrN1fpQlB+MRBTWwgJ2anR46YnFruNjfR10SFsSCtopXtqKlUwIwSFwQ1Vv5NAEj+E3VTSUaZpYYZywN6ekOQKbzxDaLzCbsRH6YEAs1J5JAKEMdXu1a\\u002fSFBw+V+uNqPd6MryCkIMOFKA8aKssPu2\\u002f833\\u002fb9X\\u002f+vXeHqClcbbG5wc4WrO9zd4jbOr3F9h9sb3HzP\\u002f\\u002fJ7kqck+7LPfdkPf\\u002f2P\\u002fLZv\\u002fO3f8Ru+4\\u002fP4\\u002fA67ghJ9MYf\\u002f9u\\u002f4V+cCSIp2X5I4lUCwdQdAULlq\\u002ff798\\u002f3u+X56DOFSj4ygawuQ6jymb+oB1vbriEufYLaVdY+y5N6iFGOKOZm72wnthO6uVkQNF+N4MUSyKAt7V4YOI3hASic0QQTsaJ5WbSBrI84rgiIQ\\u002fYOOBxd\\u002fBJAEU+xeQwAMTwFMLgMAdM\\u002flXw447GiSD8glwdGbKKExeFD4j\\u002fzv\\u002ftge+7+\\u002f\\u002ffu\\u002f6xu+762\\u002f98TcfvrVT9\\u002fi7hIXl7gKaG9xd43rK1xf4vICl5e4+op\\u002f8hUmu3+stqv\\u002f1b\\u002f4ey7w+gqXd9jssd9h933vfJ\\u002fuQxKHFGU9EG6dbdlEWZAECLvne0hqihaSkID70yRvBJfcB0liBjLkrkl2eZycfLOVcJnKLsx5h5R2Sm+Ix6\\u002fG1+PwepAcXQNekhI0laLc1gwEa8qOUrkdA2ZbJ0ECkKyZ3YDw1cpPuvoifEUZnGFs6n6W6\\u002fww3eMLANIIQWoTS8FK4rrT7U4QenNVQSIgNQveqX\\u002f18qt\\u002fz5\\u002f4N\\u002fiTY1ImSPHP\\u002fcC\\u002f+7\\u002f\\u002fv\\u002f4ZAAVtIaTDo8yCDPyTv\\u002flPfIl\\u002fKY0GCuZwA1008AVenuGsx5CRFnhj4UlQphGiVMnUt1VVqA6z\\u002fmlXXlREEghA7EU0uUSo\\u002fSWoKERRAUKTsrhwyeWODB9ckh0lhVyHGo7RslTuqqR6Wey0MVHcYC9Jau4+LXJ4PdZd7T6VD5FJLo2XVVKWpppBdpR4ZOW2BO0i0JK8TJ54INA97eqLAiB8kgGowOZlXQQDjiIG7QFA9a4I4kkKMsZbeZQxqlUSEhwmOfwE5thgc\\u002f13Xp3hjAgbDT77uc\\u002f+oX\\u002f9B3\\u002fkx340dpJyOQifWPAXf\\u002fEXv+xzX+YMJ4KmXYgYwfF1eZWydeiXWFZ4TCjpUMIGXoOwVHXB5YoC9087o5WPq+D9J5YuEXCgjYckBaPEpMk4Y+AuL7cF4SrVZFdI8Dqbe2YApVrLXYNZUr2okuzUXPLwxVDbstt3zSmn7FzS7t1998mudb0kKVxNYoW\\u002fWh14ZILsOCZEDxXnyX2HUADIT7sJ3SapMfHHTE6zAMxEJiAhXB4hoU4rdAWxF3pwZQriRjEg3iC9b4B22B1fH0X6OXzl3\\u002f+KX\\u002fjcP72+ub6+ub67u7u5ubm9vb2+vv7c5z73s7\\u002f\\u002fZ8CpRNETuHf5R\\u002f\\u002fwv32HzQabPfbx++u+\\u002fNdFnnVXfTfPuQbCUq0Io8dEH0nd05zf6Q5iKbXlmZOMuuRypQZtoOvyMpSyLy2ypazj7eARpsTjtjgnM603i8BwMYJw1cPhFZ3cvWyLWqRv39vt3t1FPvWqSHLJ2KmdHU9gS3ZkUUmswTXRGPQQxouxDvdH1BBQN9EXnSMECJn1rk78IkHlehDEvsUA4ppcNxsIriQIUH4\\u002fDx7cIACggKa+\\u002f7vv\\u002f5ndbr\\u002fZbG5ub+42d9vdbhjHhw8frjdrUc2UNEsW2kj\\u002f7uXmdnc3YNhjP2DcY3+2PCdi\\u002fxcIqLtat+GrJElIlBCOTgrYpLp3v\\u002fN6FzjN\\u002fzTeDB6YTlBFd2m8LQ1Rd5eXfXF3Vy0l\\u002fJ99uN0Pt\\u002fvqNY6Gn1U3d3mY29K5uVcuWe8DL+cC6dSmzGu8evferu4mC77cXHK4HTEqEFQWZMfG1UzdIJUAjBdjrHkFY1zbgo8uqFzXcl0BBaJOiLDzZn47ZLUpghCxcxZH1FWdUkpEbOAmSLz\\u002f67vVji0Yp7EFwK\\u002f7v32j6KLar7koWECuB28\\u002fKOM4jMNW24o6YPiJv\\u002feT5XnBNMKPEvmuSkBiI4UkczeXVPaT8cu93tWgoMvr9d7dx5thvBnCB7ahuBvRxYRJ9Qm\\u002fcT9qKZc3tOTudbzdxzEh7dVrvSfKEc+lcWlV7qoz2HbKCebIzV2uvqkQq\\u002fsqqdwUSZPmkQQxvGcAaIZm\\u002fHia2Z5CHaoAH9+YJBkD45B8CJCdH+aRmCnIL0u9nNU1NDpG4XFqQFKCD8OoJFFOj0N0p3\\u002fHX\\u002fuuaVYjjhRzHl3u3v3se27u1tLPJ6L\\u002fjt\\u002f5faSVUmv1giIItwLoVz43NFFEHxW1DkpEqG2U0wTU3etdKXd1vBqqu6u6e\\u002fU6Xg\\u002futbqXbanuLkcndWqkb86RNVRjw0\\u002fVvfKUdjrFzLiyjttxxrJ6rapcEktK7l6bA57XdGrxivQkuTeM1WMaa8OnvpXEKrYeox12RlCzWsxjHkEAM9w9usf3otHsMgCgoJadJbXB9JwnPFbCj2oNJulPOGP8N\\u002f8\\u002f\\u002f\\u002fmv\\u002fZO\\u002fUfQ4ArB3v+RdSOFokSz28EjhkWO07\\u002fux3\\u002fnwR5+4TVrO3OlK\\u002ftV\\u002f8Gs+8YlPRBq5qurPf+4fR\\u002f8LpF\\u002f5NLAHU4JQN6obl+TTIUnZlRXkC2qOu6GUgHb6UR1uhrIdZ0gCP3XuXnGCFunVVbFuC3x5xojnKXnKSY5ruR3d6\\u002faDzeaDzfSK9jgWqGoxoQ\\u002fs1EITz8VzeXTPWytTbopQJTXJCwgNmkwfCHAmjGPT9JBAmYI\\u002fIOSHJoix\\u002fGlOMLitTX10qQ4g77+wQ0gQAUBEeeIOr+tyvbj5mq\\u002f5WqdXejV3q5V1\\u002fU0PA9TElA5ONjlZm+P7+q\\u002f7+ppqtVqtVtYXn3jxe\\u002f\\u002fav\\u002fnt3\\u002f7txpTY+ADCv\\u002fND\\u002f05T8yDIeuX1ypGmcSOk6FUEaYZJ+7krx\\u002f912I1xNpZaxiZe1V0plgo2JOaTsh+H57sviuQaSJoRjYOnqF7H23GOCZgj2\\u002fa4HAsEzDUwHqvL622J5iMOvvVnPhESBoTYQZStw+MTIMbXFYQGhWFyJkpaH+aajG00Akf\\u002fMHbvZjxeq9AmVULduUPe+pN1fz1UVVfNz7o6MTtU80dMSvVZ+lP\\u002f6p+uqj\\u002fyx374k\\u002f+\\u002fx0lmSL\\u002f1x3+HYp4RgoKBWitqJGkGu76+\\u002fis\\u002f8pe\\u002f\\u002f4d+11vP3louljHdG0dnOaf8A7\\u002f5B+xr7fhXn9R3x5ziVlo+XeWUE7rM4JiJjfrDjgYkDUZCIz26IAIgSULzFWwjotDK907K9ejukrt7epwjXpJ2LjlWrTMxh3rVPK1aACS51D+LzSPlU6SAuile27kACVgDQC63gx3lgDbiJdRNw3h81dYwszfMDa2Enl48xc4p8RihIoKCKKpZK2CGsg1bRHsvIPTEHuNNAVr2w0f7\\u002fKwLYcLHHiur0nMkMwg\\u002f+sf\\u002fhMs\\u002f\\u002f4X3\\u002fsp\\u002f+FdyytIEcOQGAAxJNJqRTx4+\\u002fiM\\u002f9sPJLKT8gJYls\\u002fRvfvcPwLD+2iOSyy9d13dHgvlxDxACTAhtFFTtXIoV8g4gqkaRS3LJcllmgAGpCr3gbwAciJbr0eUBsNzL85IeJ7l7881z3UgS1g3melUlcE0TxpuiyFXK56lsRy7sPrqSeGx+EX0HKEhzJwF8+COPJaTzNuoHMMtu3c3zywzxjc9XsbdZdsm2riv26A0h76evhgIxPlYdNUvwLH+7lzFoC31Sq9xOrF6PUDXJZElmnv7UH\\u002frzcdcVHjYtk6iFWnnbq5uQ0UIbhwg2L0nLmTlZ+r3f83sef9uT4RPDjD3vms9GJGiCi5T7ptLbERoMZNfoAqhclmAGQOybrySgwDWQjjmGshtnyOMPC1gORCNGkrBmvWoOLZrCeFsk5fM0KS5J4GIazWbGiYDxou2XI8BHz+4uwi895sLAoBnHFyMIO0kUQbVeUA5K3guCSvgCsRFb2L8aA+Pm9gywA4E6BiQgIWDxuN+92BGh3q07zS63k67eyOGAA5LhJ\\u002f7bn\\u002fzur\\u002f8uhgupJLkHmyoq0kgdbYSRFvtDmQXMDS1LmSlZ+tEf+VGttH9nHxxAsjyvyRINedpzEAIoh4ddSpDgLog0ET2jAaMAiKeEUC6KLYL7AkKFBpW87j1wRYe6baNVubCE5GUvy2yJ4+dSku6jK4FrMqO6z+gK0rYK4iKFq70ACXZmAMbLIsDl2RE8gOFqzGcZwhCOKQTAelPTyeRB6rFAFhNdBQFEPu3I2LdajUHA4VXpzkKOGw4CmCf7pVq6\\u002fsli\\u002f2JHsDvpXQ4CBpz29Waocsnr2v+rn\\u002fnPvvebfsssuK43Wt\\u002fGMKHcyVlLh8ylyd89hbcz0+f\\u002f0Xurf2Xtl9496ozW0CUJ+gap2c3kLqPKWI3KHYKvCdZd5ZY20ySKIXGNMtaYRpA8sHJ3DSGbTXDRQeHEs2jz0HKve0myDHd5DFffRDeumo7GHAMBUuxAv5hjgiJ2ZsOLQQBP\\u002fugZMHWpABWAEIJoAAkinWRKoZyCikFSkt1Z39KR9SYmkmFdCjmP3bdno1K5dkFcRfliztod4kLDVXGF0LjLXV5uR6wBiXKD\\u002fuIP\\u002fIeRXpj+gInZ+CbAnIfIiWZMU2NshvS\\u002f\\u002fT\\u002f8oc3ZNpkZ0\\u002fLxsj6vZimWPsQWYt1xmrikqWWjpZxIalcZjA8AsJOYJhSGoLtLquNsUfBy3WaE0DHqJXfJy65ggQMTTMEyfZyvJCkglNqMZLu891smK6GEPmAGAMbWuiJifwxJBNva+HJTQEISCYhgWtE3UquYAFJIZx0ZpGacpJNcb0brEqBIXTY1tdUrKjdt2se34goIbUCmBQXvz\\u002fJwVdr0DEmxVjdrfpYF+sXnv\\u002fgr3\\u002f5yBW9AAIZxeP36YtjvP\\u002f2ZzxD4\\u002fHuf\\u002f4s\\u002f9u9B\\u002fNN\\u002f9k9P8AROKfrACen7v\\u002f93rL553dB9tDRa93ZXnpewiAV4cjHYEwp6OVyjLCfIAUQySPWq2knScH96XzLVsUpeb8qEnmv3BsbuVXfuCi2tJvZS3UgSW6s85wiuGbNPUuDaqFDuakNUELB7vhVmmF0gBB7\\u002fkZNYlBPoAgBZbgtBEP2zPmrLtqofJAHm40yCedrDIIQHoMtjQIWZFAKaJ1gAI0hQuB9w2RSPIMnbLhbw8WL0oK\\u002fczmLwodPF6V\\u002f41\\u002f+PiCpBv\\u002fRLv\\u002fTnfvBPxnsiND2U8O\\u002f\\u002fp\\u002f8x58aYzQP+r\\u002f\\u002fDn\\u002fwbP\\u002fs3MMBoy0fLuZE22vi8RMq8brJL0sAGPGEpESTQPpAMRG3q1iHlB\\u002fPMsEtyuaTxYgh5bRi7u5w96zbckyPVjLHUlLP0JsZchxVe4b8nBcYSUG4cJglqVG6\\u002fMQ8UJnge\\u002feHj\\u002fp1luWx7KUx8zHJbF8+a5zoDWMI3DjAfpymGTDEGBkG6R1ofFIwQpI8dznxoZQh4BKQHnHgx6iJB43UdL2Kud6ojYKcGSEWAvvsbfvP3fNP3APihH\\u002fqh5\\u002f\\u002fonyHCXHgApB31f+rP\\u002fLuf\\u002ftSnA9rX25c\\u002f9Nd+yGCkmRk2Wjxb3RPxxgT1eiQt6hMYB6iWEyZuJaB9DI0AqGya+ObzmO4POZtsDjcl8J2VM5asd2VO1v6X0AVvaKq2JDGbIK7ZIgEJPoSREeNNwxvA5BRFAf3bfZSuXrkIPvgLjwSAbBg3YOhDzQ9iYBoAx51ANf6f7mUjCI8VLC0Db98Dxv1NxeIrTI04GQDspMUEF0oYrrxcDXHeIgFAdmTzowD+o\\u002f\\u002f1X\\u002f3tv\\u002fW3cqgI0kdx2ttJ2uN3nv6lf+8vG\\u002fgTP\\u002f8Tf\\u002f1nfnKSZvpGcbJ4tor2NUD1jRuo2rYhZ\\u002fuFLTrUgyFzKoO0q7FYHkF8SVI+N73ZDLur3gSijkWb0fG7e5Z\\u002fVyRjPxs6ZoyR2icfgkZBKPjexxufSAQAQjRuFNG\\u002fFU7YEz3O\\u002f\\u002fyjxppEaZvjUoODANmd56m+YNudAyn0c0QFPSdc4zcy9xFM7XwO4dox2zijfOkkCqrhstWlXo1z4QUs3ukBlKt7uz0Dj46e\\u002fN7\\u002f2Q88Sg9+37\\u002fxA8FxBAl+4jOf\\u002fON\\u002f6o\\u002f93X\\u002f2X\\u002f+Nf\\u002fiTsXMbSYOhQhtx6oURXD5bkmagb+7tN19EsNU4AAbQPgE90VOoV6PHmAX3hE5ux9OYRz5B6PWmYolJLbfI2DYj0J1FmX0YjyUhZmUgTFoaQoN5fFHaRjqtQAQgYvFObGwSRKcInv\\u002f5h2ioEOTwfD\\u002fDFnjlBx1I39QDkmQ+TnE5f6OEjM91Rk6s8cGi5ovZICah0ZliaqKhGyGdcrzy+zGAAtFAN0K5ip0KCSCdda0eVYHHr3z7y\\u002f\\u002fpR78QJpdYgX5PHA0FurfBSPxa9CferDMBLyJgi2k4BABQiS1gVK\\u002fGSaQ0d5EEpbBDsR6AnOEsc2McqUOUa1PhkiY+YU8EuhHZ3oNwx5BQXhQh2AxuBFrno3+SQnDZ2X0Jfoi4IOut1037QtdUWYCMBQ2HSwJgPk6+Q5zPv7YmwTr4HGu53QWg2M0dYHwffAqxV7Ha2OreDSAfHeKiyADqdQ0XIs7vDy1KokZVSLTv\\u002fra\\u002f6cNjvol11iRBMD6UxGRxef8tzecQQJMTQFKp9bI0qZ1k1yXILb5RMeNKb2Y3uQaEpDrrlMQloUhSvbdHygxziuWKcYkGJ9cMdJvgCmDDGGD3JKhKAewTADT\\u002fGgJAvakg01GOj0bN8baIb8YIkEC2O+KS2LlENjuXBNaNkDywlUTSi6wjIY2hSABA7tbkGCFwAODAgaYkYQbsmWLP6pYIBPN5fwCDIELjAoOHKz5JAhwIMi0MBYw16GA+zvWuLelpKAOoiG8woFES5dUIoH3CDgAamTV4Vb2PLiBJ7prde+5jLDn2mGKEKsXQT0Jp0sw+VotHrpKQTkxyARClA8DlumKB+ArmhDFZBSA\\u002fC49GCAARjSz7xPW\\u002fddS\\u002fs6y3NdgaBMk6bUzRxk5BHDka5dg9iuX7qBcC71F6AZAxv3sfAWw9Pk0yRwC0nKbPA7c4kjIStDTFgCBSrM1txYhSRoIWSSAtDITfTLaI6f2WLXgyXkrEf6x3Ndbnz4FAbP89vhqAIJYQMEtCfKA8CK5yOx4AaaYM8bBioaGYz2x8OR7UeMS7nI4ySet0p+xcUD6Z5zoAQBXtBPDaWrHYTCjOAWIBEPk8o9msOKPG9b91ZGtjzo1cDCKwbootc7ucKCYJRB\\u002f7kbIRsV420eTyQFkUTafErg2f0jKemZI5aW1ZXKSNEzt8d6VFE0xrAoSimef08pYmPi0Zl\\u002fW2uW5P6IJkUCviI5D01nVCo5WAmDyIs6ArJKl72ms7m0gb+ctdLBZSbNsQIsyEGcUcI3hpfDnOkfGIx9yeS4o3tIA+qDy\\u002fJ4oCNX0\\u002flxUCMMEclA\\u002f6pfMc5AGw\\u002f6jw+I+dNGhzjG4BMJ1ktG8ZBTHbw4zFCmx\\u002fE5FRLxVM1P5IAIiZhl30ACJv2iqwITzSkWQMPUkCMWHFdBSGhRZJkqAtrV1OuUW2tggFPRcH9aYCSHlW+MABMKClFABvy0wACFC9bEuSgshB+\\u002fjNp9PXBNRgllRvR3SczMRxyyUhAVIKgL3Fjy+bHdLr\\u002ffQzw8SVJLBvBW4lEzS6MwyHQExzRNgBSwCNxgBE5gcZ4P6jEYwveEbSWpEy0Pb\\u002fBJDPc72a5oMA9iBR7zwdm9pTilbZ5TZ9mCUoR4Ad\\u002fboG0YP+ILQDV5S3Tk0gB7ChPKg1p1sA7eNIkSydtnO0fQ8niIu4aQzRqgmm0zxehNH0XpjNKq3CkOLr4arFoRglBlGFRt+GKI+tlCLIGMLaoEgPTdB4dc8cF3hWdY9yWCpn9OxBKi9jzv8QKYm\\u002fDGDtwAWiIAI0uIDWGjfWbHXIb3cAy+txpjuFclHANuU1NUICRNU6fyM1Qorv3wjsFamA+DRC8BbG12V4XQH4ve9fR6jXs1VvjiVA37ZWdAavITOomRWnX2zDKGH5LM8mp7RIie2wysRkTNjAmBKaU069rEbzvcKSZTADCSMPS90xW1QFSzF1fz+EMnV3xxGjC+zupRzcYLFokXbMFuW13TINr4cY4EaM4iI23FG7kit0r7vkTfijGL6V7yQJCpAb9enTJdA96CBCyA+bE3JLA1BIK6ZVOFw1oxNimegXhXSWQmNEEISGMYbXbWfYyDwwbueBbmRMAA3EVsi9gAO6pKUu56NuirmPMfJZF8i1X8Y8fGJFQprmEhLCRIVUL9yQDMnQMGagC9atANadH8ghSKhV6TxLzV44j24E3Uc3gCqlyOuMbty0Y9gxXO5yJLlc8vFiGC6GyGpC1NmJ3UFk25lBJgloGIf4ynfSEBJ\\u002fD2OJU0xT1kJ+0OcHodkPgELThwiAhu4bjrEChHI16E2v2MjT+qaTWwj8dvLr6td1esXhP4L3QY29Did0m\\u002fpNR50121NYEM2Wya+iM3ZAnTQWxIe+ZhklTHeqFyXktYksrLYNxli3MRcECGXXLLpqU\\u002fmSZOf3OsHuLk9vd+nU7Kw5l0e0ey2l7F\\u002fsG7zu4dcouR0T9kX84MPr1vSW68NcoEXHvF0B8WuKrRUDYwhklJJxOR2EYLQ4YdwFIeQHC+BeSoAnP3yiYSZ+++2eLeK8XMcG+gRhfQqgQHYPOhIg988HTtgRSKexgfgYl4wAkoQO55xsTGmRYx9ihlkYNFrYmwzGlU0prTuf5bttU0hgKnR7e+A3fYhJAiA0HONkJmoMWqG0YK1NG7dfqbweBOV3YuFWiLPGy9ZnllzbKglSW9eryF5145DcfX5Ve5sECxQjZkJUqjvFjFAUWQIE1QZPSGi7O0EGgClNQxek5ljRBkh+V0H66BFpFntJvhnGj4dyNZSrN1S2j61N7R7EqlkAWLzVz\\u002fogncbEQjiwAQx2AAiuzI6snQcqJMEUH3kDQ4UGfukoM9AFQzQJ1sswF9uEbjwS6rcdBhLMi5QWCWi9DABNZSmgfoP4ZThYkZrIyXme0ts5zucwrx6od2WO3H+8C4GdHnafBlOaLuUq+1q2tTSLVQP6TaQPyhkCDBBapzn0sICY1j2cgyDEellnUWZUVrAuRR\\u002fTIKTTcJedDiCdJAtb15vBRw9074fFWz0QXyljAAqwexQYAyBXCSCmwU+LBPNpJsgUaBMgYQDrdVEVQTLsGw3OeunaaMY1Mmn8Ef22dgBAmss\\u002foQshUI0TSdEx9VI92sgILlWvN3Nnqqlrd7dTq3flHujV3fcf7\\u002fcf7929hGHZW3KENlC0vYG3yqYqbF4uOXzrcqAABRLaSlgBDlsa+wQxjglaUjTLcY6GPetlrVcOwW+cAYPQYA6KtBXcQZrjFFS4N8xQ+8+5+2gAGhlbLNC+PDjfAEB2jxZcJa5j86UGgE2X+TSM1CQIaxgT4fdjBP22tZ0BG8HcJROnMWDcijfy\\u002fhrzqDmilzBhKYXkNMF1AZPl2CUvpZ0HPHJJflM8JnQbvr7\\u002feO9JnuKqdZjdXe7lrh4ej5\\u002fpTWUf7mXtKJtatvM4uMEpCWFfcUC0rkFrfXNVP2CcprWfczymZrgtnAMUVCOAaa0nkE5Tva6HL94DAKxLoZmlidTA7qNh+fa8iT2HlyNJ33kY7sGWLq0sr1JbqTbFk+TaUjeJ4BQJgmK5Lm1CCpwxzieZ4OyDTYSRJF5CoO0g4HtZH+gr\\u002fryIid4mfkIXTnSdJuUOclur5EjzxPskeTcVawgaXuwltdtJ8TmVyC8dJZ9cPeM1QLASSuzPQkFT0SJ+I6IxohpUgKP1egMUEYB1WYD2rYcoxf8Awvs8zhFw2oogve0OA4SKbkd8PQrTZUsj65O8ifx87D9sne3h5WGO1rdTZzscgECQ\\u002fcNFgxYIOLWRX8WEREAUd6mCtO4wXc4A+o2nLgGEiGlcQDHYX0PQGQJqQCBIbQsjNdthBEhyabws46syvixNo6qpZ5dknOV1DvX20OhOUT7JsdvKpk50BE1Cr3HTvLljeiJ4JhyCmdm2fIiYIKwDBboTRBxoTopNXSdj6DARih62x3k6Jqceta0YHEOFBBMA7Mgg2AnrbcMWAgCvQp722r4X9h8N7JoItijCt57WOT56ElABXDxcjBdjS3aneMSv3M7yBCQ1hIqGrTu1zzW3W7a0um3fuVH0LAgBFLw44qIF+V7Ww9tWPhOwCRB8dEnlsggKQOor2QNK7ZK9ubsSYujpB0zkt7HIu0U3MUyQwvIgYeKyOIXCXauVLaAKRADLFqAyEaIOzg3QIAh+WSy2VGhVI4G0zALqOInygeyejlOIe9wAaCuA8C0MgB1ZoAtBgJ00P0gA3tbx4rC97hTe\\u002fN7yJHOEb8ONZjpIgP3DBUDcaZJkAvRrr1cOEm2o1TKc5BgQuLQgWpm+zttoKNhxzuedGr0jQFK4Gc8QTRdiwngZXSdpaljHsB260KVDfKI3KXS1P+fSuGQIqHssF3UMXm4jh2CSyKydB3tMB1SoSjnkU38qpDmFfibEaIPh9MvirXscoswQ5ZRb8zx3rSGWj+r4Ufs28L2eNmxFa7mrodtunBoUy2Rnoh4wZubkcwOAh7P4IceLEidTHAnm6GZPrNASg77zOJnyIIC0ygBtGYzZIsumSoAkwY7b2sV83k2SoxAul7zIy5vkdVe27q1uBjHSuzS8KugtAAks5e4JnuCuaQGu4p\\u002fdwxhDu1Fvi7zhHnmACkthYy+XXJDgMhCCBDkUhHUwGRO1D33bYIPDLytFiAbCCW8YB8yBpW6j\\u002fhw\\u002fauOldgB1J4OgrXAP3YBaLrQYIc50H9oZ1jhvB6djvChEaF0SqIMD7J71geskrOTCALprFt85q\\u002fgkMBBvjgKjbKsAO4kd55rs5vM8EXD+lUv1gLGrsyB+96xrSE6he5x8LAFVw0gtjJsxnp4ekFyBMZpTbBxebku9jS63EF5ZLklpRbjQigUaJWAUYj8jZ4PZIRcXKSKnX0KolzX3+YCcB64hysBt44YQ6PGjMj5vTp++BTR1snwX5GoErZcVAC2uJ+rOWLfwRbJ7LxAEmhyDdZgGZ2RujtaBbjtBtPTTuQDRJbTlrJjBhATEV8TU6OaAS\\u002fk85weHfYRmkOaFAi75hEj3VhfnkvKTHLE+Vh9jPNPCcLl319h6WHMWLpdl4zK+UnQvX1e9rQd0J1Wc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                       {\"responsive\": true}                    ).then(function(){\n                            \nvar gd = document.getElementById('633a0b26-95d9-4979-b4a2-63a9f022528a');\nvar x = new MutationObserver(function (mutations, observer) {{\n        var display = window.getComputedStyle(gd).display;\n        if (!display || display === 'none') {{\n            console.log([gd, 'removed!']);\n            Plotly.purge(gd);\n            observer.disconnect();\n        }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n    x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n    x.observe(outputEl, {childList: true});\n}}\n\n                        })                };                });            </script>        </div>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_sim_fft = sim_imgs_fft[20]\n",
    "most_similar_ind = find_most_similar_image(img_sim_fft, real_imgs_fft, display=False)\n",
    "img_real_fft = real_imgs_fft[most_similar_ind]\n",
    "img_res = translate(img_sim_fft, img_real_fft, n_freq=n_freq, alpha=1, noise_level=0.0)\n",
    "im = Image.fromarray((img_res * 255).astype(np.uint8))\n",
    "px.imshow(real_imgs_data[most_similar_ind]).show()\n",
    "px.imshow(im)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-13T21:17:56.114682100Z",
     "start_time": "2024-04-13T21:17:55.610704100Z"
    }
   },
   "id": "6e019030f29a63b5"
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 4000x7500 with 10 Axes>",
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_log_magnitude(fft_rgb):\n",
    "    magnitude_spectrum_rgb = np.abs(fft_rgb)\n",
    "    log_magnitude_spectrum_rgb = np.log(magnitude_spectrum_rgb + 1)\n",
    "    return log_magnitude_spectrum_rgb[:,:,0]\n",
    "\n",
    "# img_real = real_imgs_data[np.random.choice(range(len(real_imgs_data)))]\n",
    "i = np.random.choice(len(sim_imgs_data))\n",
    "img_sim, img_sim_fft, img_sim_fft_lowest_freq = sim_imgs_data[i], sim_imgs_fft[i], sim_imgs_fft_lowest_freq[i]\n",
    "most_similar_ind = find_most_similar_image(img_sim_fft_lowest_freq, real_imgs_fft_lowest_freq)\n",
    "# most_similar_ind = np.random.choice(len(real_imgs_fft))\n",
    "img_real = real_imgs_data[most_similar_ind]\n",
    "img_real_fft = real_imgs_fft[most_similar_ind]\n",
    "\n",
    "fig, ax = plt.subplots(nrows=5, ncols=2, figsize=(40, 75))\n",
    "fig.set_facecolor(\"white\")\n",
    "\n",
    "ax[0,0].imshow(img_sim)\n",
    "ax[0,1].imshow(get_log_magnitude(img_sim_fft), cmap=\"gray\")\n",
    "\n",
    "ax[1,0].imshow(img_real)\n",
    "ax[1,1].imshow(get_log_magnitude(img_real_fft), cmap=\"gray\")\n",
    "\n",
    "ax[2,0].imshow(translate(img_sim_fft, img_real_fft, 1, alpha=1))\n",
    "ax[3,0].imshow(translate(img_sim_fft, img_real_fft, 3, alpha=1))\n",
    "ax[4,0].imshow(translate(img_sim_fft, img_real_fft, 5, alpha=1))\n",
    "\n",
    "for i in range(5):\n",
    "    for j in range(2):\n",
    "        ax[i, j].axis('off')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-14T11:26:08.058350100Z",
     "start_time": "2024-04-14T11:26:05.612347100Z"
    }
   },
   "id": "d793ff0beab6794f"
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "outputs": [],
   "source": [
    "fig.savefig(r\"C:\\Users\\Alex\\Documents\\Master\\Bilder\\fft.png\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-14T11:27:06.385017Z",
     "start_time": "2024-04-14T11:27:04.817389900Z"
    }
   },
   "id": "52ee5717855a9220"
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "outputs": [],
   "source": [
    "img_size = img_sim.shape[:2]\n",
    "img_size = img_size[1] * 3, img_size[0] * 3\n",
    "img_size\n",
    "\n",
    "def save_img_resized(img, name):\n",
    "    img = Image.fromarray((img * 255).astype(np.uint8)).resize(img_size, Image.Resampling.NEAREST)\n",
    "    img.save(rf\"C:\\Users\\Alex\\Documents\\Master\\Bilder\\fft\\{name}.png\")\n",
    "   \n",
    "im = (get_log_magnitude(img_real_fft) / get_log_magnitude(img_real_fft).max())\n",
    "save_img_resized(im, \"real_fft\")\n",
    "\n",
    "im = (get_log_magnitude(img_sim_fft) / get_log_magnitude(img_sim_fft).max())\n",
    "save_img_resized(im, \"sim_fft\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-04-14T12:00:10.471131100Z",
     "start_time": "2024-04-14T12:00:10.411128900Z"
    }
   },
   "id": "57fa0ff00315508"
  },
  {
   "cell_type": "markdown",
   "source": [],
   "metadata": {
    "collapsed": false
   },
   "id": "93d688d1ec64008b"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
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 },
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