{
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"source": [
"# Convolutions"
]
},
{
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"id": "b70f14ae",
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"source": [
"[](https://github.com/borisbolliet/ResearchComputing/blob/main/docs/material/misc1/convolutions.ipynb) [](https://colab.research.google.com/github/borisbolliet/ResearchComputing/blob/main/docs/material/misc1/convolutions.ipynb)"
]
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"source": [
"## Introduction\n",
"\n",
"\n",
"- **What are Convolutions?**\n",
" - Convolutions are mathematical operations that combine two functions to produce a third function. In image processing, this typically involves applying a filter (kernel) to an image, resulting in feature extraction such as edges, textures, or other visual information.\n",
" - This concept, originally from signal processing, forms the foundation of many modern techniques in both image and sound analysis.\n",
"\n",
"
\n",
"\n",
"- **Why are Convolutions Important in Neural Networks?**\n",
" - In neural networks, especially Convolutional Neural Networks (CNNs), convolutions help in reducing the number of parameters by using local connections, which allows for efficient processing of large images.\n",
" - Convolutions preserve spatial relationships between pixels, enabling the network to detect features like edges and patterns in various layers, leading to hierarchical learning (from simple to complex features).\n",
"\n",
"\n",
"## Mathematical Operation\n",
"\n",
"- **Convolution Operation (1D Example)**:\n",
" - A convolution in one dimension can be expressed as:\n",
" $$(f * g)(t) = \\int_{-\\infty}^{\\infty} f(\\tau) g(t - \\tau) d\\tau$$\n",
" For discrete data, this becomes:\n",
" $$(f * g)[n] = \\sum_{m=-\\infty}^{\\infty} f[m] g[n - m]$$\n",
" Here, $f$ is the input signal, and $g$ is the kernel/filter.\n",
"\n",
"
\n",
"\n",
"- **2D Convolution (Image Example)**:\n",
" - In 2D, the convolution operation is applied between an image $I$ and a filter $K$:\n",
" $$(I * K)(x, y) = \\sum_{i=-k}^{k} \\sum_{j=-k}^{k} I(x+i, y+j) K(i, j)$$\n",
" where $I(x, y)$ is the pixel value of the image at position $I(x, y)$ and $K(i, j)$ represents the kernel/filter.\n",
" \n",
"
\n",
"\n",
"- **Key Parameters**:\n",
" - **Stride**: Number of pixels by which the filter moves across the input.\n",
" - **Padding**: Adds borders around the image to control the output size.\n"
]
},
{
"cell_type": "markdown",
"id": "4e23108e-bca9-49db-a294-34121fe31633",
"metadata": {},
"source": [
"## 1D convolution\n",
"\n",
"### Sawtooth Signal and Adjustable Gaussian Kernel"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "0ced7526-c851-4dcc-836a-69d15a9bcdeb",
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"interactive(children=(IntSlider(value=0, description='step', max=179), IntSlider(value=21, description='Kernel…"
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""
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],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from ipywidgets import interact, IntSlider, FloatSlider, Checkbox\n",
"\n",
"# Function to generate a sawtooth signal\n",
"def generate_sawtooth_pattern(length=200, period=50):\n",
" return np.tile(np.linspace(-1, 1, period), length // period)\n",
"\n",
"# Function to create a Gaussian kernel\n",
"def gaussian_kernel(size=21, sigma=3.0):\n",
" \"\"\"\n",
" Generate a Gaussian kernel.\n",
" - Adjust the `size` parameter to control the width of the kernel.\n",
" - Adjust the `sigma` parameter to control the amplitude (spread) of the kernel.\n",
" \"\"\"\n",
" kernel = np.linspace(-(size // 2), size // 2, size)\n",
" kernel = np.exp(-kernel**2 / (2 * sigma**2))\n",
" kernel = kernel / np.sum(kernel) # Normalize\n",
" return kernel\n",
"\n",
"# Function to perform 1D convolution (valid mode)\n",
"def convolve_1d(input_array, kernel):\n",
" return np.convolve(input_array, kernel, mode='valid')\n",
"\n",
"# Function to visualize the convolution process\n",
"def plot_convolution(step, input_array, kernel, result, save_as_svg):\n",
" kernel_size = len(kernel)\n",
" input_size = len(input_array)\n",
" \n",
" fig, axs = plt.subplots(3, 1, figsize=(9, 7))\n",
"\n",
" # Plot the input signal (Sawtooth)\n",
" axs[0].plot(range(input_size), input_array, 'C0-')\n",
" axs[0].set_title('Input Array (Sawtooth Signal)')\n",
" axs[0].set_xlim(0, input_size - 1)\n",
"\n",
" # Plot the kernel centered at the current step\n",
" axs[1].stem(range(step, step + kernel_size), kernel, basefmt=\" \", linefmt='C1-', markerfmt='C1o')\n",
" axs[1].set_title(f'Gaussian Kernel (Center at Step {step})')\n",
" axs[1].set_xlim(0, input_size - 1)\n",
"\n",
" # Plot the result up to the current step\n",
" axs[2].plot(range(len(result)), result, 'C2-')\n",
" axs[2].set_title('Result of Convolution (Partial)')\n",
" axs[2].set_xlim(0, input_size - kernel_size)\n",
" \n",
" \n",
" plt.tight_layout()\n",
"\n",
" \n",
" # Save the plot as an SVG if requested\n",
" if save_as_svg:\n",
" plt.savefig('1dconv_sawtooth_plot.svg', format='svg')\n",
" print(\"Plot saved as '1dconv_sawtooth_plot.svg'\")\n",
" \n",
" \n",
" plt.show()\n",
"\n",
"# Interactive function\n",
"def interactive_convolution(step, size, sigma, save_as_svg=False):\n",
" input_array = generate_sawtooth_pattern(length=200, period=50) # More points, sawtooth pattern\n",
" kernel = gaussian_kernel(size=size, sigma=sigma) # Adjust width and amplitude here\n",
" result = convolve_1d(input_array, kernel)\n",
" plot_convolution(step, input_array, kernel, result[:step+1],save_as_svg)\n",
"\n",
"# Create interactive sliders for convolution steps, kernel size (width), and kernel sigma (amplitude)\n",
"input_array = generate_sawtooth_pattern(length=200, period=50)\n",
"\n",
"interact(\n",
" interactive_convolution,\n",
" step=IntSlider(min=0, max=len(convolve_1d(input_array, gaussian_kernel(21, 3.0))) - 1, step=1, value=0),\n",
" size=IntSlider(min=3, max=51, step=2, value=21, description='Kernel Size'),\n",
" sigma=FloatSlider(min=0.1, max=10.0, step=0.1, value=3.0, description='Sigma'),\n",
" save_as_svg=Checkbox(value=False, description='Save as SVG')\n",
")\n"
]
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""
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xsXmOx8u9ZuDd780TTzyBVqtl4cKFBsvnzp2LRqPRfw6eeOIJIOfsmXf6+OOPAfRn9cx9rsJ+Bh7Etm3b8l2ee7xgnTp18r3d3NycTp06sW7dOmJjY/XLT548qT/m8GE8yGcrP0eOHCE9PZ0WLVo8dA1CCFESZCRPCCFKmZo1a9KqVStefPFFfeNQqVIlXn31Vf06Tz/9NB9//DFdunThmWee4cqVK3z66ac0aNCApKQk/Xq2trbUr1+fFStWULt2bVxcXPD398ff3z/P8+7Zs4eTJ08SFhaWb11VqlQhODiY8PBwJk+e/NCvr0ePHnz77bc4OTlRv359du/ezdatW/VTLO82YsQI5s+fz44dO/jwww8L/Ty9e/dm7dq1BsdYXbx4kaZNm9KhQwc6duyIp6cnV65cYfny5URHRzN+/Hj9KF2PHj2YMWMGTz31FC1atODgwYOEh4dTo0aNPM/VvHlzLCwsiImJMZjO2qZNG5YsWQKQp8lr3LgxAOPGjaNLly6Ym5szZMgQevbsSfv27Xn99dc5e/YsjRo14tdff2X9+vWMHz9ef/KRRo0aMXLkSD7//HMSEhJo27Yte/fu5X//+x99+vShffv2Bs+1ZMkS3n33XWrWrIm7u3uhj2u839+4evXq9OzZEz8/P1JTU9m6dSsbNmzgscceo2fPngXe9+233+bXX3+lZcuWvPjii/rG1t/fX38Jjgf1oJ+tu23ZsgU7Ozsef/zxh3p+IYQoMcY6racQQpRHBV1CoUKFCnnWnTZtmsGp4nMvoTB79mz10UcfKR8fH2Vtba1at26toqOj89z/u+++UzVq1FBWVlYqMDBQ/fLLL3kuoaCUUrt27VKNGzdWVlZW97ycwtixYxWgTp06VeDre/vttxWgrwdQoaGhhfo75Lp586Z66qmnlKurq7K3t1ddunRRx44dU76+vgVeGqFBgwbKzMzM4NIS9xMZGakA9ccff+iXJSUlqU8++UR16dJFeXt7K0tLS+Xg4KCaN2+uvvjiC4PLCKSnp6tJkyapypUrK1tbW9WyZUu1e/fuAi9f8dhjjylA7dmzR7/s4sWLClA+Pj551s/OzlZjx45Vbm5uSqPRGHwWkpOT1YQJE5SXl5eytLRUtWrVUrNnzzaoTymlsrKy1PTp01X16tWVpaWl8vHxUVOnTlXp6ekG68XFxanu3bsrBwcHBejrL+h9utclBu60fPlyNWTIEOXn56dsbW2VjY2Nql+/vnr99df1l5TIld9nb9u2bSooKEhZWVkpPz8/9eWXX6pJkyYpGxubPPfN73N292emsJ+tgl5fSEiIevLJJ+/5moUQwhRolHqAo6aFEEIYzdmzZ6levTqzZ8/m5ZdfNnY5JiUoKAgXF5cCpwcWpGPHjnh5eeW54LgwXX369OHw4cP5HptanKKioggODiYyMpLAwMASfW4hhHhQckyeEEKIUu3ff/8lKiqKESNGPPB933//fVasWPFAlxMQJefWrVsGv584cYKffvqJdu3alXgtH3zwAQMGDJAGTwhRKsgxeUIIIUqlQ4cOsW/fPj766CMqV67M4MGDH/gxQkJCyMzMLIbqRFGoUaMGo0aNokaNGpw7d44lS5ZgZWVlcPxpSfn+++9L/DmFEOJhSZMnhBCiVFq9ejUzZsygTp06LF++HBsbG2OXJIpY165dWb58OXFxcVhbW9O8eXPef/99uU6dEELchxyTJ4QQQgghhBBliByTJ4QQQgghhBBliDR5QgghhBBCCFGGlMtj8nQ6HbGxsTg4OOgvgCuEEEIIIYQQpkwpRXJyMl5eXpiZFTxeVy6bvNjYWHx8fIxdhhBCCCGEEEI8sAsXLuDt7V3g7eWyyXNwcABy/jiOjo5GrkYIIYQQQggh7i8pKQkfHx99P1OQctnk5U7RdHR0lCZPCCGEEEIIUarc75Azo5945ffff6dnz554eXmh0WhYt27dfe+zc+dOgoODsba2pmbNmixbtqzY6xRCCCGEEEKI0sDoTV5qaiqNGjVi0aJFhVr/zJkzdO/enfbt2xMVFcX48eN59tln+eWXX4q5UiGEEEIIIYQwfUafrtmtWze6detW6PU//fRTqlevzkcffQRAvXr1+PPPP5k7dy5dunQprjKFEEIIIYQQolQw+kjeg9q9ezedOnUyWNalSxd2795tpIqEKJvSs7TGLkGIUkWrU2RpdcYuQ4hSRbJGiAdzLTmjUOuVuiYvLi4ODw8Pg2UeHh4kJSVx69atfO+TkZFBUlKSwY8QIn9pmdm8vCqaBtN+YdOBy8YuR4hSYdfJa7T4YBs9F/yJTqeMXY4QJu9WppZXbmfNhuhYY5cjRKmw69Q1Bny6q1Drlrom72HMnDkTJycn/Y9cI0+I/J28kkzvhX+xet9FtDpF1IWbxi5JCJOm1SnmbzvBk1/tIT4pg2NxyaTJyIQQ93TySjK9F/3JKn3WJBi7JCFMmk6nWLDtBE9+uYdrKZmFuk+pa/I8PT2Jj483WBYfH4+joyO2trb53mfq1KkkJibqfy5cuFASpQpRqqzdf5GeC/7ixJUU/bLMbJl6JkRBrqVkMGrpXj7ecpw7B+9kuxGiYGv3X6TXwr84Hi9ZI0RhXE/JYOTSvXx0O2t6B3oV6n6lrslr3rw527ZtM1i2ZcsWmjdvXuB9rK2t9dfEk2vjCWEoPUvLlB8OMGFFNLeytLSsWYmRzX0ByJTji4TI157T1+k+/w/+OHENG0sz5gxshIVZzjWLZIdViLzSs7RMXZOTNWmZWprXqMSoFtUA2WaEKMg/Z2/Qff6f+qyZPaAh7/UNKNR9jd7kpaSkEBUVRVRUFJBziYSoqCjOnz8P5IzCjRgxQr/+Cy+8wOnTp3n11Vc5duwYixcvZuXKlUyYMMEY5QtRqp2+mkKfRX/x/T8X0GhgfKdafPN0CJWdc0bFMyR4hTCg0ykW7zzJsC9zpmfWdLfnx7BWDGjsjaV5TqTKDqsQhk5fTaHv4l0s35uTNeM61uK7Z0PwcrYB5AtFIe6m0ymW7DzFkM//Ji4pHT+3CqwPbcXAJoU/5Mzol1D4999/ad++vf73iRMnAjBy5EiWLVvG5cuX9Q0fQPXq1dm0aRMTJkzgk08+wdvbmy+//FIunyDEA9oQHcuUHw6QmqnF1d6KeYODaFXLFQAr2VkVIo+bqZlMXBnFjpirAPQLqsI7ffypYJ0TpVYWZtzK0pKplWPyhMi18UAsU344SEpGNpUqWDFvSCCta7kBkjVC5OdmaiaTVkWz/dgVAPoEevFe3wB91hSW0Zu8du3aoVTBZyJbtmxZvvfZv39/MVYlRNmVnqXl3U1H+O7vnC9PQqq7MH9oEB6ONvp1rCwkeIW4075zNwiL2M/lxHSsLcyY3qsBgx/zQaPR6NfJ3W5kBFwIyMjW8u7Go3z79zkAmlZzYcGwu7PG/Pa6ss0IARB5/iZh4ZHEJqZjZWHGjHyyprCM3uQJIUrOueuphEZEcuhSzmVEQtv7MaFTbSzMDWdu65s8mUIjyjmlFF/+cYYPNx8jW6eo7lqBxcODqVc577HdMiohRI7z19MYE7FPnzVj2vkx8XHJGiEKopTiqz/P8MHP/2XNomHB1Pd6+POISJMnRDmx+dBlXll1gOSMbCraWTJ3cCDt6rjnu6717eCVCzuL8iwxLYtJq6LZejTnjM49G3kxs18A9gVMmflvu5Hr5Inya/OhOF5ZHU1yejbOdpbMHRRI+7r5Z01uk5clX4yIciwxLYtXVkfz65GcrOnRsDIz+wXgYGP5SI8rTZ4QZVxmto6ZPx9l6V9nAWjsW5EFQ4Pwcs7/kiMgIxJCRF9IIDQikos3b2FlbsabPevzZEjVe06ZkWnOojy7O2uCqzqzcFhw4bJGvlAU5dSBiwmMCb8ja3rU48lmvg81PfNu0uQJUYZduJFG2PL9RN++0OzzbWrwcpc6+rMAFkR2VkV5pZRi2a6zvP/TUbK0iqoudiweHox/Faf73ve/qWdy4hVRvly8mUZoxH9ZM7p1dV7tWve+WWMtWSPKKaUU3+w+x3ubjpKp1VHVxY5Fw4IJ8L5/1hSWNHlClFFbjsQzaWUUSenZONla8tHARnSq71Go+8oJJER5lJSexeTVB/j5UBwAXRt4MmtgQxwLOWVGRsBFebT1SDyTVkWTeCsLRxsLPhoUyOMPmDWyzYjyJCk9i6k/HGTTwcsAdGngwawBjXCyfbTpmXeTJk+IMiZLq2P2LzF8/vtpABr5OLNoWBDeFe0K/RgyhUaUN4cuJRIaEcm562lYmmt47Yl6jGpR7YGmzMiXI6I8ydLqmPNLDJ/lZo23EwuHBePj8gBZIydeEeXM4dhEQsMjOXs7a6Z2q8dTLR8sawpLmjwhypDYhFuMXb6ffeduAvB0y+pM6VZXH6SFJd+uivJCKUX4nvPM2HCETK2OKs62LBoeTKCP8wM/lmw3ory4nHiLsIj/smZUi2q89kS9B88aGf0W5YRSioi955m+4QiZ2Y+WNYUlTZ4QZcSOmCtMXBHFzbQsHGwsmD2gIV39Kz/UY8nOqigPUjKymbrmIBuiYwHoVM+dOQMb4Wxn9VCPJyPgojzYGXOFCblZY23BrAEN6RbwaFkjo9+iLEvNyOa1tQdZH1U0WVNY0uQJUcpla3V8vOU4i3eeAsC/iiOLhzWmaqXCT5m5m7VMoRFl3NHLSYSGR3L6WirmZhqmdK3Ls62rP9KUGflyRJRl2Vodc7ceZ9GOnKxp4OXI4uHB+Faq8NCP+d82IycrEmXTsbgkxoRHcvpqTtZM7lqH0a1rFMv0zLtJkydEKRaflM7Y5fvZe+YGAP/XzJfXu9fDxtL8kR7Xyjzn/rKzKsoapRQr/73AW+sPk5Gto7KTDQuHBdHY1+WRH1uaPFFWxSelM275fvbczponm1Xlje71iyBr5AtFUTYppVj170XeXH+IjGwdno45WdOk2qNnTWFJkydEKfXniWu89P1+rqdmYm9twcx+AfRs5FUkj21pkfMNk+ysirIkLTObN9YeYs3+SwC0q+PGx4MCcalQNFNm5PgiURb9dTIna66lZFLBypyZ/RvSq4iyRr4YEWVRWmY2b6w7xJrInKxpW9uNuYOLLmsKS5o8IUoZrU4xf9sJ5m8/gVJQ19OBxcODqeFmX2TPkbuzmq1T6HQKM7Pin1YgRHE6EZ/MmPBITlxJwUwDkzrX4cW2fkX62ZYzBYqyJL+sWTQ8GL9iyBqdypkOanGf6+oJYepKImsKS5o8IUqRq8kZjF+xn79OXgdgaFMfpvVs8MhTZu525xnSMrU6bMyK9vGFKEk/7LvIG+sOcStLi7uDNQuGBhFSo1KRP4+M5Imy4u6sGfKYD2/3Kv6skSZPlGZrIi/y+tr/smb+0CCaFUPWFJY0eUKUErtPXWfc9/u5mpyBraU57/fzp2+Qd7E8V54mr4iDXYiSkJ6lZdr6w6z49wIArWq6Mm9IIK721sXyfDKSJ8qCv09fZ+zy/7Lmvb7+9Asu/qzJylZQsrPZhCgS+WXN3MGBuDkUT9YUljR5Qpg4nU6xeOdJPt5yHJ2C2h72LB4eTE13h2J7Tqs7vk2VUQlRGp26mkJoeCTH4pLRaGB8x9qEdaiJeTFOmZHji0RpptMplvx2io9+jUGnoJZ7TtbU8ii+rLEw06DRgFKQodUClsX2XEIUh9NXUxhzR9a81LEWYzvUKtasKSxp8oQwYddTMpiwMprfj18FYEBjb2b0boCdVfFuuhqNBitzMzK1OtlhFaXO+qhLTF1zkLRMLa72VnwyJIiWNV2L/XmlyROl1Y3UTCasiOK321nTL7gK7/bxL7GsyciWrBGlz4/RsUz94QCpJZw1hSVNnhAm6p+zNxgbsZ+4pHRsLM2Y0dufQU18Suz5rSykyROlS3qWlhkbjxCx5zwAzWq4MH9IEO6ONiXy/HI6eFEa/Xv2BmG3s8bawox3evszsIl3iVzHC3KyRpo8UZqkZ2l5d9MRvvs7J2tCqruwYGjJZU1hSZMnhInR6RSf/3Ga2b/EoNUparhVYMnwxtTxLL4pM/mxsjCDDNlhFaXD2WupjAmP5MjlJDQaCGtfk5c61irREzlYy0ieKEV0OsUXf5xmVm7WuFZg0fBg6lV2LNE6rC3MSEayRpQO567nZM3h2CQgJ2vGdyrZrCksafKEMCE3UzOZtCqa7ceuANA70Iv3+wZQwbrkN1U5U6AoLX46eJlXVx8gJSMblwpWzB0cSNvabiVeh0zXFKVFQlomk1ZGs+121vRq5MX7/QKwl6wRokA/386a5IxsKtpZMndwIO3quBu7rAJJkyeEiYg8f5OxEfu5lHALKwsz3u7ZgKFNfUpsyszdcndYMyR4hYnKyNby/qaj/G/3OQAeq1aR+UODqOxka5R65OyaojS4O2um9azPsKZVjZ410uQJU5WZreP9n46ybNdZAJr4VmTBMONlTWFJkyeEkSml+OrPM3zw8zGydYpqlexYNDyYBl5ORq1LgleYsgs30giNiOTAxUQAnm9bg5c718HSiFNmrMxzLjUiX4wIU3R31vhWsmPRsGD8q0jWCFGQCzfSCIuIJNqEsqawpMkTwogS07J4ZXU0vx6JB6B7QGU+6B+Ag43xTyMtJ5EQpurXw3G8vCqapPRsnGwt+XhQIzrW8zB2WbKzKkxW4q0sXl0dzS+Hc7LmiQBPPujfEEdTyJrcWSOSNcLEbDkSz6SVUSaXNYUlTZ4QRnLgYgJjwiO5ePMWVuZmvNGjHv/XzNdoU2buZik7rMLEZGl1fPjzMb788wwAQVWdWTgsmCrOpjFlxtI8Z9uVbUaYkgMXEwiNiOTCjVtYmmt4/Yl6jGxRzXSyRo7JEyYmS6tj1uZjfPFHTtYE+jizcFgQ3hXtjFzZg5EmT4gSppTim93neG/TUTK1OnxcbFk0LJiG3s7GLs2AtQSvMCGXEm4RFhHJ/vMJADzTqjqTu9bVjwKYAjkmT5gSpRTf/n2OdzfmZI13xZysaeTjbOzSDMiJV4Qpib2dNZG3s+bpltWZ0s20sqawpMkTogQlpWcx9YeDbDp4GYDO9T2YPbARTrbGnzJzt/92WLVGrkSUd9uPxTNxZTQJaVk42FgwZ2AjujTwNHZZecglFISpSE7PYsodWfN4fQ/mDGiEk50JZ41sN8LIdsRcYeKKKG7ezprZAxrR1d/0sqawpMkTooQcjk0kNDySs9fTsDDTMPWJejzd0nSmzNwtN3izspWRKxHlVbZWx5xfj/Ppb6cAaOjtxKJhwfi4mOaUmdwTr2TJSJ4woruzZkq3ujzTqrrJZk3ulyOy3Qhjydbq+GjLcZbszMmagCo5WVO1kmlmTWFJkydEMVNKEbH3PNM3HCEzW0cVZ1sWDAsiuGpFY5d2T7lTaORgeGEMcYnpjF0eyT9nbwIwqkU1pj5RF2sLcyNXVjAZkRDGpJRi+d4LvL3hMJnZOrycbFg4PNj0s0amOQsjik9KZ+zy/ew9cwOAEc19eb17PZPOmsIyiQmmixYtolq1atjY2BASEsLevXsLXHfZsmVoNBqDHxsbmxKsVojCS83IZvyKKF5fe4jMbB0d67qzaVwrkw9dkB1WYTy/H7/KE/P/4J+zN7G3tmDRsGDe7tXA5ENXthlhLLlZ89rag2Rm6+hQ151N41qXjqyRY/KEkfxx4ipPfPIHe8/cwN7agoXDgpjR29/ks6awjD6St2LFCiZOnMinn35KSEgI8+bNo0uXLsTExODunv9V5B0dHYmJidH/bqpTEET5diwuiTHhkZy+moq5mYZXu9RhdOsamJmVjs+r7LCKkqbVKeZtPc7CHSdRCupXdmTx8GCquVYwdmmFIqeCF8YQE5fMmPB9nLqdNa90qcNzpTBr5PqSoqRodYpPtp1gwfYTKAX1bmdN9VKSNYVl9Cbv448/ZvTo0Tz11FMAfPrpp2zatImvv/6aKVOm5HsfjUaDp2fpPRBSlH0r/73AW+sPkZ6lw9PRhoXDgmhSzcXYZT0QafJESbqSnM5Ly6PYffo6AMNCqvJWj/rYWJaeb1TvHJFQSskXkKLY3Zk1Ho7WLBwWzGOSNUIU6EpyOuO/j2LXqZysGdq0KtN6lq6sKSyjNnmZmZns27ePqVOn6peZmZnRqVMndu/eXeD9UlJS8PX1RafTERwczPvvv0+DBg1KomQh7iktM5s31x3mh8iLALSp7cbcQY2oZG9t5Moe3H8XQ5eza4ritevkNcZ9H8W1lAzsrMyZ2S+A3oFVjF3WA7vzFNtZWoWVhTR5onjcytTy5vpDrN6XkzWta7kyb3BgKc2anJ1rOSZPFLddp67x0vdRXE3OyZr3+wbQJ6j0ZU1hGbXJu3btGlqtFg8Pw6vHe3h4cOzYsXzvU6dOHb7++msaNmxIYmIic+bMoUWLFhw+fBhvb+9875ORkUFGRob+96SkpKJ7EULcdvJKMi9+F8mJKymYaWBS5zq82Nav1EyZuZucDl4UN61OsWjHSeZtPY5OQR0PBxYND6amu72xS3so1nc0eZlaXam8rpIwfSevJDMmPJLj8TlZM6FTbULb1yy1WSMjeaK46W5nzdzbWVPbw57FwxuX2qwpLKNP13xQzZs3p3nz5vrfW7RoQb169fjss89455138r3PzJkzmT59ekmVKMqhtfsv8tqaQ9zK0uLmYM38IUE096tk7LIeiQSvKE7XUjKYsCKKP05cA2BQE2+m9/LH1qr0TpnJHf2G29tN6RtUESZu7f6LvL72EGmZOVnzyZBAWvi5GrusRyJZI4rT9ZQMxt+RNQMbezOjd+nOmsIyapPn6uqKubk58fHxBsvj4+MLfcydpaUlQUFBnDx5ssB1pk6dysSJE/W/JyUl4ePj83BFC3GH9Cwtb/94mO//uQBAy5qVmDc4CDeH0r939990TQleUbT2nL7OuO/3E5+UgY2lGe/2CWBA4/xnYpQmZmYaLMw0ZOuU7LCKIpWepWX6hsMs35uTNc1rVOKToYG4O5T+s4vLrBFRXP45e4OxEfuJS0rHxtKMd3r7M7BJ+dn/N2qTZ2VlRePGjdm2bRt9+vQBQKfTsW3bNsLCwgr1GFqtloMHD/LEE08UuI61tTXW1qV/p1uYltNXUxgTHsmxuGQ0GnipYy3GdqiFeSmdMnM3SznjmShiOp3i099P8dGvx9HqFDXd7Vk8PJjaHg7GLq3IWJqbka3Tyg6rKDKnr6YQGrGfo5eT0GhgbIdavNSxDGWNec7rkC8URVHR6RSf/X6aOb/GoNUp/NwqsHh4Y+p4lp2sKQyjT9ecOHEiI0eOpEmTJjRt2pR58+aRmpqqP9vmiBEjqFKlCjNnzgRgxowZNGvWjJo1a5KQkMDs2bM5d+4czz77rDFfhihnNkTHMuWHA6RmanG1t2Le4CBa1SrdU2buJtcuEkXpZmomE1dGsSPmKgD9gqrwTh9/KlgbPYaKlJWFGbeytHLCIlEkNh6IZcoPB0nJyKZSBSvmDQmkdS03Y5dVpCRrRFG6mZrJpFXRbD92BYC+QVV4twxmTWEY/RUPHjyYq1ev8tZbbxEXF0dgYCCbN2/Wn4zl/PnzmJn9d5zDzZs3GT16NHFxcVSsWJHGjRuza9cu6tevb6yXIMqR9Cwt7246wnd/nwcgpLoL84cG4eFY+qfM3E2OkxBFZd+5G4RF7OdyYjrWFmZM79WAwY/5lMlLDMg1v0RRyMjW8u7Go3z79zkAmlZzYcGwspo1OcdGyTYjHlXk+ZuEhUcSm5iOlYUZM8pw1hSG0Zs8gLCwsAKnZ+7cudPg97lz5zJ37twSqEoIQ+eupxIaEcmhSzlnZw1t78eETrWxMC+bZ9DTN3kyhUY8JKUUX/5xhg83HyNbp6juWoHFw4OpV9nR2KUVGxmVEI/q/PU0xkTs02fNmHZ+THxcskaIgiil+OrPM3zw839Zs2hYMPW9ym7WFIZJNHlCmLrNhy7zyqoDJGdkU9HOkrmDA2lXx93YZRWr3IPhsyR4xUNITMti0qpoth7NObFWz0ZezOwXgH0ZnzLz33ajjFyJKI02H4rjldXRJKdn42xnydxBgbSvW7azJrfJy5IvRsRDSEzL4uXV0Ww5kpM1PRpWZma/ABxsLI1cmfGV7bQV4hFlZuuY+fNRlv51FoDGvhVZMDQIL2db4xZWAmREQjys6AsJhEZEcvHmLazMzXizZ32eDKlaLqbMyDRn8TDuzprgqs4sHBZcvrJGvlAUDyhP1vSox5PNfMtF1hSGNHlCFODCjTTClu8n+kICAM+3qcHLXepgWUanzNxNdlbFg1JKsWzXWd7/6ShZWkVVFzsWDw/Gv4qTsUsrMf9NPZMTr4jCuXgzjdCI/7JmdOvqvNq1brnJGrmEgnhQSin+t+ss792RNYuGBRPgXX6ypjCkyRMiH1uOxDNpZRRJ6dk42Vry0cBGdKrvYeyySpScQEI8iKT0LCavPsDPh+IA6NrAk1kDG+JYzqbMyAi4eBBbj8QzaVU0ibeycLSx4KNBgTxeTrNGthlRGEnpWUz54QA/HczJmi4NPJg1oBFOtuUrawpDmjwh7pCl1TH7lxg+//00AI18nFk0LAjvinZGrqzkyRQaUViHLiUSGhHJuetpWJpreO2JeoxqUa1cTpmRL0dEYWRpdcz5JYbPcrPG24mFw4LxcSmHWSMnXhGFdHfWTO1Wj6dals+sKQxp8oS4LTbhFmOX72ffuZsAPN2yOlO61dUHUHkj366K+1FK8d2e87yz4QiZWh1VnG1ZNDyYQB9nY5dmNLLdiPu5nHiLsIj/smZUi2q89kS98ps1Mvot7kMpRfie88zYeITMbMmawpImTwhgR8wVJq6I4mZaFg42Fswe0JCu/pWNXZZRyc6quJeUjGym/HCAjQcuA9CpnjtzBjbC2c7KyJUZl4yAi3vZGXOFCblZY23BrAEN6RYgWQMy+i3yl5KRzWtrDvJjdCwgWfMgpMkT5Vq2VsfHW46zeOcpAPyrOLJ4WGOqVip/U2buZi1TaEQBjl5OIjQ8ktPXUjE30zCla12ebV1dpswgX46I/GVrdczdepxFO3KypoGXI4uHB+NbqYKRKzO+/7YZOVmRMHQsLokx3/2XNZO71mF06xqSNYUkTZ4ot+KT0hm7fD97z9wA4P+a+fJ693rYWJobuTLTYClTaMRdlFKs+OcC0348TEa2jspONiwcFkRjXxdjl2YyZOqZuFt8Ujrjlu9nz+2sebJZVd7oXl+y5jYZ/RZ3U0qx6t+LvLn+EBnZOjwdc7KmSTXJmgchTZ4ol/48cY2Xvt/P9dRM7K0tmNkvgJ6NvIxdlkmREQlxp7TMbN5Ye4g1+y8B0K6OGx8PCsSlgkyZuZNsN+JOf53MyZprKZlUsDJnZv+G9JKsMSDbjLhTWmY2b6w7xJrInKxpW9uNuYMlax6GNHmiXNHqFPO3nWD+9hMoBXU9HVg8PJgabvbGLs3k5H67mq1T6HQKMzOZHlFeHY9PZkx4JCevpGCmgUmd6/BiWz/5TORDzhQoIP+sWTQ8GD/Jmjxys0ancqa1WpST6wOKvE7czpoTkjVFQpo8UW5cTc5g/Ir9/HXyOgBDm/owrWcDmTJTgDvP9Jap1WFjJn+n8mj1vou8ue4Qt7K0uDtYs2BoECE1Khm7LJMl0zXF3Vkz5DEf3u4lWVOQu7NGmrzyaU3kRV5f+1/WzB8aRDPJmkciTZ4oF3afus647/dzNTkDW0tz3u/nT98gb2OXZdLyNHmyg1Ku3MrUMu3HQ6z89yIArWq6Mm9IIK721kauzLTJSF759vfp64xd/l/WvNfXn37BkjX3cmfWZGUrkFl55Up6lpZp6w+z4t8LQE7WzB0ciJuDZM2jkiZPlGk6nWLxzpN8vOU4OgW1PexZPDyYmu4Oxi7N5Fnd8W2qjEqUL6eupjDmu0hi4pPRaGB8x9qEdaiJuUyZuS85vqh80ukUS347xUe/xqBTUMs9J2tqeUjW3I+FmQaNBpSCDK0WsDR2SaKEnL6awpjwSI7F5WTNSx1rMbZDLcmaIiJNniizrqdkMGFlNL8fvwrAgMbezOjdADsr+dgXhkajwcrcjEytTnZYy5H1UZeYuuYgaZlaXO2t+GRIEC1ruhq7rFJDmrzy50ZqJhNWRPHb7azpF1yFd/v4S9YUUm7WZGRL1pQnP0bHMvWHA6RK1hQb+RdIlEn/nL3B2Ij9xCWlY2Npxoze/gxq4mPsskodKwtp8sqL9CwtMzYeIWLPeQCa1XBh/pAg3B1tjFxZ6SKngy9f/j17g7DbWWNtYcY7vf0Z2MRbruP1gKwspMkrL9KztLy76Qjf/Z2TNSHVXVgwVLKmOEiTJ8oUnU7x+R+nmf1LDFqdooZbBZYMb0wdT5ky8zCsLMwgQ3ZYy7qz11IZEx7JkctJaDQwtn1NXupUW6bMPARrGckrF/LLmsXDg6nr6Wjs0kolawszkpGsKevOXc/JmsOxSQCEta/J+E615GQ7xUSaPFFm3EzNZNKqaLYfuwJA70Av3u8bQAVr+Zg/LDlTYNn308HLvLr6ACkZ2bhUsGLe4EDa1HYzdlmllkzXLPvyy5r3+gZgL1nz0CRryr6fb2dNckY2Fe0smTs4kHZ13I1dVpkm/yKJMiHy/E3CwiOJTUzHysKMt3s2YGhTH5ky84hyd1gzJHjLnIxsLe9vOsr/dp8D4LFqFVkwNBhPJ5ky8yjk7JplW+T5m4yN2M+lhFtYWZgxrWd9hjWtKlnziOTLkbIrM1vH+z8dZdmuswA08a3IgmFBVHayNW5h5YA0eaJUU0rx1Z9n+ODnY2TrFNUq2bFoeDANvJyMXVqZIMFbNl24kUZoRCQHLiYC8EJbP17uXFumzBQBK/OcS43IFyNlS35Zs3BYMP5VJGuKgmRN2XThRhphEZFE386a59vW4OXOdbCUrCkR0uSJUisxLYtXVkfz65F4ALoHVOaD/gE42Mjpl4uKpZxEosz59XAcL6+KJik9G2c7Sz4e1IgOdT2MXVaZYWmeM6IjO6tlR+KtLF5dHc0vh3Oy5okATz7o3xBHyZoik5s1GZI1ZcaWI/FMWhlFUno2TrY5WdOxnmRNSZImT5RKBy4mMCY8kos3b2FlbsabPerxZDNfmTJTxOTb1bIjS6vjw5+P8eWfZwAIqurMwmHBVHGWKTNFSbaZsuXAxQRCIyK5cOMWluYa3uhenxHNJWuKmmw3ZUeWVseszcf44o+crAn0cWbhsCC8K9oZubLyR5o8Uaoopfhm9zne23SUTK0OHxdbFg9rTIC3TJkpDtZyMHyZcCnhFmERkew/nwDAs62q82rXuvodK1F05Ji8skEpxbd/n+PdjTlZ413RlsXDg2no7Wzs0sokOfFK2RB7O2sib2fN0y2rM6WbZI2xSJMnSo2k9Cym/nCQTQcvA9ClgQezBjTCyVamzBSX/3ZYtUauRDys7cfimbgymoS0LBxsLJgzsBFdGngau6wySy6hUPolp2cx5Y6seby+B3MGNMLJTrKmuMhIXum3I+YKE1dEcfN21swe0Iiu/pI1xiRNnigVDscmEhoeydnraViYaZj6RD2ebllNpswUs9zgzcpWRq5EPKhsrY45vx7n099OAdDQ24lFw4LxcZEpM8Up98QrWTKSVyrdnTVTutXlmVbVJWuKWe6XI7LdlD7ZWh0fbTnOkp05WRNQJSdrqlaSrDE2afKESVNKEbH3PNM3HCEzW0cVZ1sWDgsiqGpFY5dWLljJwfClUlxiOmOXR/LP2ZsAjGpRjalP1MXawtzIlZV9MiJROimlWL73Am9vOExmtg4vJxsWDg8mWLKmRMg059IpPimdscv3s/fMDQBGNPfl9e71JGtMhDR5wmSlZmTz2tqDrI+KBaBjXXc+GtQIZzsrI1dWfsgOa+nz+/GrjF8RxY3UTOytLfiwf0O6N6xs7LLKDdlmSp+7s6ZDXXc+GtiIihUka0qKHJNX+vxx4irjv4/i+u2s+aB/AD0aehm7LHEHkzgSctGiRVSrVg0bGxtCQkLYu3fvPddftWoVdevWxcbGhoCAAH766acSqlSUlGNxSfRc+Cfro2IxN9MwtVtdvhjRRBq8EiY7rKWHVqf46NcYRi7dy43UTOpXdmTj2FbS4JWw3G1GRr9Lh5i4ZHrdkTVTutXlyxFNpMErYfrtRrLG5Gl1io+3HGfE13u5nppJvcqObBjbSho8E2T0kbwVK1YwceJEPv30U0JCQpg3bx5dunQhJiYGd3f3POvv2rWLoUOHMnPmTHr06EFERAR9+vQhMjISf39/I7wCUdRW/nuBt9YfIj1Lh6ejDQuHBdGkmouxyyqXpMkrHa4kp/PS8ih2n74OwLCQqrzVoz42ljJlpqTdOSKhlJJjuUzYnVnj4WjNwmHBPCZZYxSSNaXDleR0xn8fxa5TOVkztGlVpvWUrDFVRh/J+/jjjxk9ejRPPfUU9evX59NPP8XOzo6vv/463/U/+eQTunbtyiuvvEK9evV45513CA4OZuHChSVcuShqaZnZTFoZzaurD5CepaNNbTc2jWslDZ4R6XdY5eyaJmvXyWs88cmf7D59HTsrcz4ZEsj7fQMkdI3kzlOFZ2nlhEWm6FamlpdX/Zc1rWu58tO41tLgGVHuCYvkmDzTtevUNbrP/5Ndp3KyZt7gQGb2k6wxZUYdycvMzGTfvn1MnTpVv8zMzIxOnTqxe/fufO+ze/duJk6caLCsS5curFu3rjhLFcXs5JVkXvwukhNXUjDTwKTOdXixrR9mZvItuDHJ6eBNl1anWLTjJPO2HkenoI6HA4uGB1PT3d7YpZVr1nc0eZlanVwfysScvJLMmPBIjsfnZM2ETrUJbV9TssbIZCTPdOl0ioWSNaWSUZu8a9euodVq8fDwMFju4eHBsWPH8r1PXFxcvuvHxcUV+DwZGRlkZGTof09KSnqEqkVRW7v/Iq+tOcStLC1uDtbMHxJEc79Kxi5LIMFrqq6lZDBhRRR/nLgGwKAm3kzv5Y+tlXyjamy5o99we7uxNmIxwsDa/Rd5fe0h0jJzsuaTIYG08HM1dlkCyRpTdT0lg/F3ZM3Axt7M6C1ZU1oY/Zi8kjBz5kymT59u7DLEXdKztLz942G+/+cCAC1rVmLe4CDcHGSvyFT8N11TgtdU7Dl9nXHf7yc+KQMbSzPe7RPAgMbexi5L3GZmpsHCTEO2TskOq4lIz9IyfcNhlu/NyZrmNSrxydBA3B1sjFyZyCWzRkzP3jM3GLs8UrKmFDNqk+fq6oq5uTnx8fEGy+Pj4/H09Mz3Pp6eng+0PsDUqVMNpngmJSXh4+PzCJWLR3X6agpjwiM5FpeMRgMvdazF2A61MJcpMybFUs54ZjJ0OsWS307x8ZbjaHWKmu72LB4eTG0PB2OXJu5iaW5Gtk4rO6wm4PTVFEIj9nP0chIaDYztUIuXOkrWmBpL85z3Q75QND6dTvHZ76eZ82sMWp3Cz60Ci4c3po6nZE1pY9Qmz8rKisaNG7Nt2zb69OkDgE6nY9u2bYSFheV7n+bNm7Nt2zbGjx+vX7ZlyxaaN29e4PNYW1tjbS2jQ6ZiQ3QsU344QGqmFld7K+YNDqJVLZkyY4rk2kWm4UZqJhNXRrEz5ioA/YKq8E4ffypYl4vJGKWOlYUZt7K0csIiI9t4IJYpPxwkJSObShWsmDckkNa13IxdlsiHZI1puHk7a3bczpq+QVV4V7Km1DL6uzZx4kRGjhxJkyZNaNq0KfPmzSM1NZWnnnoKgBEjRlClShVmzpwJwEsvvUTbtm356KOP6N69O99//z3//vsvn3/+uTFfhiiE9Cwt7246wnd/nwcgpLoL84cG4eEoU2ZMlRwnYXz7zt0gLGI/lxPTsbYwY3qvBgx+zEdOzW/C5JpfxpWRreXdjUf59u9zADSt5sKCYZI1pszKIucYL9lmjGffuZuMjYgkNjEdKwszZkjWlHpGb/IGDx7M1atXeeutt4iLiyMwMJDNmzfrT65y/vx5zMz+O5C9RYsWRERE8MYbb/Daa69Rq1Yt1q1bJ9fIM3HnrqcSGhHJoUs5J70Jbe/HhE61sTCXM8+Zstyd1SyZQlPilFJ88cdpZm2OIVunqO5agcXDg6lX2dHYpYn7yB2VkEsolLzz19MYE7FPnzVj2vkx8XHJGlMnWWM8Sim++vMMH/x8TJ81i4YFU99Lsqa0M3qTBxAWFlbg9MydO3fmWTZw4EAGDhxYzFWJorL50GVeWXWA5IxsKtpZMndwIO3q5L3QvTA9+oPhJXhLVGJaFpNWRbP1aM7xxz0beTGzXwD2MmWmVJCTSBjH5kNxvLI6muT0bJztLJk7KJD2dSVrSgOZNWIciWlZvLw6mi1HcrKmR8PKzOwXgIONpZErE0VB9hhEscnM1jHz56Ms/essAI19K7JgaBBezrbGLUwUmhwnUfKiLiQQGh7JpYRbWJmb8WbP+jwZUlWmzJQissNasu7OmuCqziwcFixZU4rImZxLXvSFBEIjIrl483bW9KjHk818JWvKEGnyRLG4cCONsOX7ib6QAMDzbWrwcpc6WMqUmVJFdlZLjlKKZbvO8v5PR8nSKqq62LF4eDD+VZyMXZp4QPrtRk68Uuwu3kwjNOK/rBndujqvdq0rWVPKyOh3yVFK8b9dZ3nvjqxZNCyYAG/JmrJGmjxR5LYciWfSyiiS0rNxsrXko4GN6FTf4/53FCZHTiBRMpLSs5i8+gA/H4oDoGsDT2YNbIijTJkplWQEvGRsPRLPpFXRJN7KwtHGgo8GBfK4ZE2pJF8oloyk9Cym/HCAnw7mZE2XBh7MGtAIJ1vJmrJImjxRZLK0Omb/EsPnv58GoJGPM4uGBeFd0c7IlYmHJVNoit+hS4mMCY/k/I00LM01vPZEPUa1qCZTZkox+XKkeGVpdcz5JYbPcrPG24mFw4LxcZGsKa2s5PjvYnfoUiKhEZGcu56TNVO71eOplpI1ZZk0eaJIxCbcYuzy/ew7dxOAp1tWZ0q3uvp/uEXpJN+uFh+lFN/tOc87G46QqdVRxdmWRcODCfRxNnZp4hHJdlN8LifeIiziv6wZ1aIarz1RT7KmlJPR7+KjlCJ8z3lmbDxCZrZkTXkiTZ54ZDtirjBxRRQ307JwsLFg9oCGdPWvbOyyRBGQndXikZKRzZQfDrDxwGUAOtXzYM7AhjjbWRm5MlEUZAS8eOyMucKE3KyxtmDWgIZ0C5CsKQtk9Lt4pGRk89qag/wYHQtAp3ruzBnYSLKmnJAmTzy0bK2Oj7ccZ/HOUwD4V3Fk8bDGVK0kU2bKCrmEQtE7ejmJ0PBITl9LxcJMw+SudXm2dXWZMlOGyJcjRStbq2Pu1uMs2vFf1iwaFoxvpQpGrkwUlf+2GTlZUVE5FpfEmO9yssbcTMPkrnUY3bqGZE05Ik2eeCjxSemMXb6fvWduAPB/zXx5vXs9bCzNjVyZKEqWMoWmyCilWPHPBab9eJiMbB2VnWxYOCyYxr4VjV2aKGIy9azoxCelM275fvZI1pRpMvpddJRSrPr3Im+uP0RGtg5PRxsWDguiSTUXY5cmSpg0eeKB/XniGi99v5/rqZnYW1sws18APRt5GbssUQxkRKJopGVm88baQ6zZfwmAdnXc+HhQIC4VZMpMWSTbTdH462RO1lxLyaSClTkf9G8oWVNGyTZTNNIys3lj3SHWROZkTdvabswdLFlTXkmTJwpNq1PM33aC+dtPoBTU9XRg8fBgarjZG7s0UUxyv13N1il0OoWZmUzzeFDH45MZEx7JySspmJtpmNS5Ni+08ZO/ZRkmZwp8NJI15U9u1uhUzvRcC7nO4QM7cTtrTlxJwUwDkzrX4cW2kjXlmTR5olCuJmcwfsV+/jp5HYChTX2Y1rOBTJkp4+48Y12mVoeNmbzfD2L1vou8ue4Qt7K0uDtYs2BoECE1Khm7LFHMZOrZw7s7a4Y85sPbvSRryro7syZLq7CQt/uBrIm8yOtr/8ua+UODaCZZU+5Jkyfua/ep64z7fj9XkzOwtTTn/X7+9A3yNnZZogTkafJkR6tQbmVqmfbjIVb+exGA1rVcmTs4EFd7ayNXJkqCTD17OH+fvs7Y5ZI15ZFB1mTrsLWSrCmM9Cwt09YfZsW/FwBoVTMna9wcJGuENHniHnQ6xeKdJ/l4y3F0Cmp72LN4eDA13R2MXZooIVbmhsEr7u/U1RTGfBdJTHwyGg1M6FSb0PY1MZcpM+WGNHkPRqdTLPntFB/9GoNOQS33nKyp5SFZU15YmGnQaEApyNBqAUtjl2TyTl9NYUx4JMficrLmpY61GNuhlmSN0JMmT+TrekoGE1ZG8/vxqwAMbOzNjN7+8u1aOaPRaLAyNyNTq5Md1kJYH3WJqWsOkpapxdXemvlDAmlR09XYZYkSJk1e4d2dNf2DvXmnTwPsrGT3pDzJzZqMbMmawvgxOpapPxwgNVOLq70VnwwJoqVkjbiL/Csq8vjn7A3GRuwnLikdG0sz3untz8AmPsYuSxiJlYU0efeTnqVlxsYjROw5D0CzGi7MHxqEu4ONkSsTxiDH5BXOnVljbWHGO338GSRZU25ZWUiTdz/pWVre3XSE7/7OyZqQ6i4sGBqEu6NkjchLmjyhp9MpPv/jNLN/iUGrU/i5VWDx8MbU8ZQpM+WZlYUZZMgOa0HOXktlTHgkRy4nodHA2PY1ealTbZkyU45Zy0jePd2dNTXcKrB4eDB1PR2NXZowImsLM5KRrCnIues5WXM4NgmAsPY1Gd+plpyJVBRImjwBwM3UTCatimb7sSsA9An04r2+AVSwlo9IeScXdi7YTwcv8+rqA6RkZONSwYp5gwNpU9vN2GUJI5PpmgW7O2t6384ae8mack+ypmA/386a5IxsKtpZMndwIO3quBu7LGHi5F9VQeT5m4SFRxKbmI6VhRnTezVgyGM+aDQyEiH+22HNkODVy8jW8v6mo/xv9zkAHqtWkQVDg/F0kikzQq6TV5DI8zcZG7GfSwm3sLIwY1rP+gxrWlWyRgDy5Uh+MrN1vP/TUZbtOgtAE9+KLBgWRGUnW+MWJkoFafLKMaUUX/15hg9+Pka2TlGtkh2LhgfTwMvJ2KUJEyLBa+jCjTRCIyI5cDERgBfa+vFy59oyZUboWZnnnKBKvhjJkV/WLBwWjH8VyRrxH8kaQxdupBEWEUn07ax5vm0NXu5cB0vJGlFI0uSVU4lpWbyyOppfj8QD0L1hZT7oF4CDjZy2WBiylJNI6P16OI6XV0WTlJ6Ns50lHw9qRIe6HsYuS5gYS/OckSnZWYXEW1m8ujqaXw7nZM0TAZ580L8hjpI14i65WZMhWcOWI/FMWhlFUno2TrY5WdOxnmSNeDDS5JVDBy4mMCY8kos3b2FlbsabPerxZDNfmTIj8iXfrkKWVseHPx/jyz/PABBU1ZmFw4Kp4ixTZkRess3kOHAxgdCISC7cuIWluYY3utdnRHPJGpE/2W5ysmbW5mN88UdO1gT6OLNwWBDeFe2MXJkojaTJK0eUUnyz+xzvbTpKplaHj4sti4c1JsBbpsyIglmX84PhLyXcIiwikv3nEwB4tlV1Xu1aV79DIsTdyvsxeUopvv37HO9uzMka74q2LB4eTENvZ2OXJkxYeT/xSuztrIm8nTVPt6zOlG6SNeLhSZNXTiSlZzH1h4NsOngZgC4NPJg1oBFOtjJlRtxbbsBklcMd1u3H4pm4MpqEtCwcbCyYM7ARXRp4GrssYeKsy/E2k5yexZQ7subx+h7MGdAIJzvJGnFv5Tlrdhy7woSVUfqsmT2gEV39JWvEo5Emrxw4HJtIaHgkZ6+nYWGmYeoT9Xi6ZTWZMiMKpTxOocnS6vjo1+N8+tspABp6O7FoWDA+LjJlRtxf7olXytM2A3mzZkq3ujzTqrpkjSiU8nh9yWytjo+2HGfJzpysCaiSkzVVK0nWiEcnTV4ZppQiYu95pm84Qma2jirOtiwcFkRQ1YrGLk2UIlbl7GD4uMR0xi6P5J+zNwEY1aIaU5+oi7WFuZErE6VFeftiRCnF8r0XeHvDYTKzdXg52bBweDDBkjXiAZS3ac5xiemMW76fvWdvADCiuS+vd68nWSOKjDR5ZVRqRjavrT3I+qhYADrWdeejQY1wtrMycmWitClPO6y/Hb/KhBVR3EjNxN7agg/7N6R7w8rGLkuUMuVpm7k7azrUdeejgY2oWEGyRjyY8nRM3u+3s+b67az5oH8APRp6GbssUcZIk1cGHYtLYkx4JKevpmJupuHVLnUY3boGZmYyZUY8uPKww6rVKeZtPc7CHSdRCupXdmTx8GCquVYwdmmiFMrdZsr66HdMXDJjwvdx6nbWvNKlDs9J1oiHpN9uynjWfLL1OAvuyJpFw4OpLlkjioFRT9lz48YNhg8fjqOjI87OzjzzzDOkpKTc8z7t2rVDo9EY/LzwwgslVLHpW/nvBfos+ovTV1PxdLRhxXPNeL6tn4SueGhlvcm7kpTO8C//ZsH2nNAdFlKVNWNaSIMnHtqdIxJKKSNXUzxW/nuB3ov+5NTVVDwcrfn+uWa8IFkjHkGZz5rkdJ78cg/z78oaafBEcTHqSN7w4cO5fPkyW7ZsISsri6eeeornnnuOiIiIe95v9OjRzJgxQ/+7nZ0coJqWmc2b6w7zQ+RFANrUdmPuoEZUsrc2cmWitNPvsGq1Rq6k6O06eY1x30dxLSUDOytzZvYLoHdgFWOXJUq5O095nqVVWFmUncbnVqaWN9cfYvW+nKxpXcuVeYMDJWvEI9OfsKgMjoDvOnWNccsla0TJMlqTd/ToUTZv3sw///xDkyZNAFiwYAFPPPEEc+bMwcur4LnJdnZ2eHrKqWVznbySzIvfRXLiSgpmGpjUuQ4vyjeqooiUxTOeaXWKhdtPMm/bcZSCOh4OLBoeTE13e2OXJsoA6zuavEytrsxc5+rklWTGhEdyPD4nayZ0qk1o+5qSNaJIlMWRPJ1OsXDHSeZtPY5OskaUMKMlz+7du3F2dtY3eACdOnXCzMyMPXv23PO+4eHhuLq64u/vz9SpU0lLSyvuck3W2v0X6bngL05cScHNwZrwZ5tJ6IoiVdaC91pKBiO/3svcrTkN3qAm3qwLbSmhK4qMpfkdTV4Z2W7W7r9Ir4V/cTw+J2u+ezaEsR1rSdaIIlPWsuZ6SgYjl+7l4y05Dd7AxpI1omQZbSQvLi4Od3d3g2UWFha4uLgQFxdX4P2GDRuGr68vXl5eHDhwgMmTJxMTE8OaNWsKvE9GRgYZGRn635OSkh79BRhZepaWt388zPf/XACgZc1KzBschJuDTJkRRcvSvOyc1nrP6euMXb6fK8kZ2Fia8W6fAAY09jZ2WaKMMTfTYG6mQatTpX6HNT1Ly/QNh1m+NydrmteoxCdDA3F3sDFyZaKssTLP+cKgtG8zAHvP3GDs8kjikyRrhPEUeZM3ZcoUPvzww3uuc/To0Yd+/Oeee07//wEBAVSuXJmOHTty6tQp/Pz88r3PzJkzmT59+kM/p6k5fTWFMeGRHItLRqOBlzrWYmyHWpjLN6qiGJSFM57pdIolv53io19j0Cmo6W7P4uHB1PZwMHZpooyyMjfjlk5bqndYT19NITRiP0cvJ6HRwNgOtXipo2SNKB5l4Tp5Op3is99PM+fXGLQ6hZ9bBRYPb0wdT8kaUfKKvMmbNGkSo0aNuuc6NWrUwNPTkytXrhgsz87O5saNGw90vF1ISAgAJ0+eLLDJmzp1KhMnTtT/npSUhI+PT6Gfw5RsiI5lyg8HSM3U4mpvxbzBQbSq5WrsskQZVtqvXXQjNZOJK6PYGXMVgH5BVXinjz8VrOUKMqL4WFmYcStLW2pPWLTxQCxTfjhISkY2lSpYMW9IIK1ruRm7LFGGlfasuXk7a3bczpq+QVV4V7JGGFGRf/Lc3Nxwc7t/EDRv3pyEhAT27dtH48aNAdi+fTs6nU7fuBVGVFQUAJUrF3zBYmtra6ytS/c0xvQsLe9uOsJ3f58HIKS6C/OHBuHhKFNmRPEqzcdJ7Dt3g7CI/VxOTMfawowZvRswqIkPGo2MRIjiVVpHwDOytby78Sjf/n0OgKbVXVggWSNKgJVFztk1S9s2A7Dv3E3GRkQSm5iOlYUZM3o1YPBjkjXCuIz29UK9evXo2rUro0eP5tNPPyUrK4uwsDCGDBmiP7PmpUuX6NixI9988w1Nmzbl1KlTRERE8MQTT1CpUiUOHDjAhAkTaNOmDQ0bNjTWSyl2566nEhoRyaFLOccShrb3Y0Kn2liYl40ztgnTlruzmlWKptAopfjij9PM2hxDtk5Rw7UCi4YHU6+yo7FLE+VE7qhElrb0XCfv/PU0xkTs02fNmHZ+THxcskaUjNKaNV/9eYYPfj5Gtk5R3bUCi4YFU99LskYYn1HHkMPDwwkLC6Njx46YmZnRv39/5s+fr789KyuLmJgY/dkzrays2Lp1K/PmzSM1NRUfHx/69+/PG2+8YayXUOw2H7rMK6sOkJyRTUU7S+YODqRdHff731GIImJdyo6TSEzLYtKqaLYejQegZyMvZvYLwF6mzIgSVNouPbL5UByvrI4mOT0naz4eHEh7yRpRgkrbrJHEtCxeXh3NliM5WdOjYWVm9gvAwcbSyJUJkcOoez0uLi73vPB5tWrVUOq/b0F9fHz47bffSqI0o8vM1jHz56Ms/essAI19K7JgaBBezrbGLUyUO6XpOImoCwmEhkdyKeEWVuZmvNWzPsNDqsqUGVHiSssOq2SNMBVWpehMztEXEgiNiOTizZysebNHPZ5s5itZI0yKfLVtgi7cSCNs+X6iLyQA8HybGrzcpY7BtZeEKCmlYWdVKcWyXWd5/6ejZGkVVV3sWDw8GP8qTsYuTZRT/50p0HRPvHLxZhqhEf9lzXNtavCKZI0wktIw+q2U4n+7zvLeHVmzaFgwAd6SNcL0SJNnYrYciWfSyiiS0rNxsrXko4GN6FTfw9hliXLM1E8gkZSexeTVB/j5UM71Nbv5e/LhgIY4ypQZYUSmPgK+9Ug8k1ZFk3grS7JGmART/0IxKT2LKT8c4KeDOVnTpYEHswY0wslWskaYJmnyTESWVsfsX2L4/PfTADTycWbRsCC8K9oZuTJR3pnyFJpDlxIZEx7J+RtpWJpreP2JeoxsUU2mzAijM9UvR7K0Oub8EsNnd2TNwqFB+LhI1gjjMuXr5B26lEhoRCTnrudkzdRu9XiqpWSNMG3S5JmA2IRbjF2+n33nbgLwdMvqTOlWV/8PnhDGZIrfriql+G7Ped7ZcIRMrY4qzrYsGh5MoI+zsUsTAjDN7eZy4i3CIv7LmqdaVmNqt3qSNcIkmOLot1KK8D3nmbHxCJnZkjWidJEmz8h2xFxh4ooobqZl4WBjwewBDenqX/A1/4Qoaaa2s5qSkc2UHw6w8cBlADrV8+CjgY1wspMpM8J0mNoI+M6YK0zIzRprC2YNaEi3AMkaYTpMbfQ7JSOb19Yc5MfoWAA61XNnzsBGONtZGbkyIQpHmjwjydbq+HjLcRbvPAVAQBUnFg0LpmolmTIjTIsp7awevZxEaHgkp6+lYmGmYXLXujzburpMmREmx9JEvhzJ1uqYu/U4i3bkZI1/FUcWDQvGt1IFo9YlxN0s9SN5xj9Z0bG4JMZ8l5M15mYaJnetw+jWNSRrRKkiTZ4RxCelM3b5fvaeuQHAiOa+vN69HtYW5kauTIi8TGEkTynFin8uMO3Hw2Rk66jsZMPCYcE09q1otJqEuBdrE5h6Fp+Uzrjl+9lzO2v+r1lO1thYStYI02MK12RVSrHq34u8uf4QGdk6PB1tWDgsiCbVXIxWkxAPS5q8EvbniWu89P1+rqdmYm9twQf9A+jR0MvYZQlRIGM3eWmZ2byx9hBr9l8CoF0dNz4eFIhLBZkyI0yXsbebv07mZM21lEwqWJnzQf+G9GwkWSNMl7G3mbTMbN5Yd4g1kTlZ07a2G3MHS9aI0kuavBKi1SnmbzvB/O0nUArqVXZk8fBgqrvKlBlh2nKna2brFDqdwsys5KarHI9PZkx4JCevpGBupmFS59q80MavRGsQ4mEY60yBd2dNXU8HFg8PpoabfYnWIcSDys0ancqZZmxRgtdrPHE7a05cScFMA5M61+HFtpI1onSTJq8EXE3OYPyK/fx18joAQ5tWZVrP+jJlRpQKd555L1Orw8asZD63q/dd5M11h7iVpcXdwZoFQ4MIqVGpRJ5biEdljGNZ786aIY/58HavBpI1olS4M2uytIqSOoJlTeRFXl/7X9bMHxpEM8kaUQZIk1fMdp+6zrjv93M1OQM7K3Pe7xtAn6Aqxi5LiELL0+QV8w7jrUwt0348xMp/LwLQupYrcwcH4mpvXazPK0RRKumpZ3dmja2lOe/386dvkHeJPLcQRcEga7J12FoVb9akZ2mZtv4wK/69AECrmjlZ4+YgWSPKBmnyiolOp1i88yQfbzmOTkFtD3sWD29MTXeZMiNKFytzw+AtTqeupjDmu0hi4pPRaGBCp9qEtq+JuUyZEaVMSTV5d2dNLXd7Fg8PppaHQ7E+rxBFzcJMg0YDSkGGVgsU32VxTl9NYUx4JMficrLmpY61GNuhlmSNKFOkySsG11MymLAymt+PXwVgYGNvZvT2L/ZvpYQoDhqNBitzMzK1umLdYV0fdYmpaw6SlqnF1d6a+UMCaVHTtdieT4jiVBJN3t1Z0z/Ym3f6NMDOSqJdlD65WZORXbxZ82N0LFN/OEBqphZXeys+GRJES8kaUQZJEhSxf87eYGzEfuKS0rGxNOOd3v4MbOJj7LKEeCRWFsXX5KVnaZmx8QgRe84D0KyGC/OHBuHuYFPkzyVESSnuY/LuzBprCzPe6ePPIMkaUcpZWRRfk5eepeWdjUcIv501IdVdWDA0CHdHyRpRNkmTV0R0OsVnv59mzq8xaHUKP7cKLB7emDqeMmVGlH5WFmaQUfQ7rGevpTImPJIjl5PQaGBs+5q81Km2TJkRpZ51MY3k6XSKz/84zexfcrKmhlsFFg8Ppq6nY5E+jxDGYG1hRjLFkzWhEZEcjk0CIKx9TcZ3qlWiZ/AUoqRJk1cEbqZmMmlVNNuPXQGgT6AX7/UNoIK1/HlF2WBVDBd23nTgMpN/OEBKRjYuFayYNziQNrXdiuzxhTCm4piueXfW9L6dNfaSNaKMKI6s+fngZV5dfYDkjGwq2lkyd3Ag7eq4F9njC2GqJBkeUeT5m4SFRxKbmI6VhRnTezVgyGM+aDQyEiHKjtwd1owiCN6MbC3vbzrK/3afA+CxahVZMDQYTyeZMiPKjqK+Tl7k+ZuMjdjPpYRbWFmYMa1nfYY1rSpZI8qUovxyJCNby8yfjrFs11kAmvhWZMGwICo72T7yYwtRGkiT95CUUnz15xk++PkY2TpFtUp2LBoeTAMvJ2OXJkSRszTP2ZF81OC9cCON0IhIDlxMBOCFtn683Lm2TJkRZY6ledF8MZJf1iwcFox/FckaUfZYFtFI3oUbaYRFRBJ9O2ueb1uDlzvX0T++EOWBNHkPITEti1dWR/PrkXgAujeszAf9AnCwKb7T/QphTFa3r0r7KKMSvxyO4+VV0SSnZ+NsZ8nHgxrRoa5HUZUohEkpimlnibeyeHV1NL8czsmaJwI8+aB/Qxwla0QZpZ818ghZ8+vtrElKz8bJNidrOtaTrBHljzR5D+jAxQTGhEdy8eYtrMzNeLNHPZ5s5itTZkSZ9ihTaDKzdXy4+Rhf/XkGgKCqziwcFkwVZ5kyI8quR512duBiAqERkVy4cQtLcw1vdK/PiOaSNaJse5TtJkur48Ofj/Hl7awJ9HFm4bAgvCvaFWmNQpQW0uQVklKKb3af471NR8nU6vBxsWXxsMYEeMuUGVH2WT/kqMSlhFuEhkcSdSEBgGdbVefVrnX1QS5EWfWwx+Qppfj273O8uzEna7wr2rJ4eDANvZ2LoUohTMvDjoDHJtwiLCKSyPMJADzdsjpTuknWiPJNmrxCSErPYuoPB9l08DIAXRp4MGtAI5xsZcqMKB9ygzLrAXZYtx+LZ+LKaBLSsnCwsWDOwEZ0aeBZXCUKYVKsH2KbSU7PYsodWfN4fQ/mDGiEk51kjSgfHiZrdhy7woSVUfqsmT2gEV39JWuEkCbvPg7HJhIaHsnZ62lYmGmY+kQ9nm5ZTabMiHLlQabQZGl1zPk1hs9+Ow1AQ28nFg0LxsdFpsyI8sPK/PZxrIUckbg7a6Z0q8szrapL1ohy5UGuL5mt1fHRluMs2XkKgIAqOVlTtZJkjRAgTV6BlFJE7D3P9A1HyMzWUcXZloXDggiqWtHYpQlR4nKn0NzvYPi4xHTGLo/kn7M3ARjVohpTn6iL9e0TtwhRXhT2ixGlFMv3XuDtDYfJzNbh5WTDwuHBBEvWiHKosNOc4xLTGbd8P3vP3gBgZHNfXuteT7JGiDtIk5eP1IxsXlt7kPVRsQB0rOvOR4Ma4WxnZeTKhDCOwuyw/nb8KhNWRHEjNRMHaws+HNCQJwIql1SJQpiUwmwzd2dNh7rufDSwERUrSNaI8qkwx+T9fjtrrqdmYm9twYf9G9K9oWSNEHeTJu8ux+KSGBMeyemrqZibaXi1Sx1Gt66BmZlMmRHl1712WLU6xbytx1m44yRKQf3KjiweHkw11wolXaYQJuN+p4KPiUtmTPg+Tt3Omle61OE5yRpRzum3mwKy5pOtx1lwR9YsGh5MdckaIfIlTd4dVv57gbfWHyI9S4enow0LhwXRpJqLscsSwugKavKuJKUz7vv9/H06Z8rM8JCqvNmjPjaWMmVGlG93jkgopQyOrbs7axYMC+IxyRohCs6a5HReWh7F7tPXARgWUpW3JGuEuCdp8oC0zGzeXHeYHyIvAtCmthtzBzWikr21kSsTwjTod1i1Wv2yXSevMe77KK6lZFDBypz3+wXQO7CKsUoUwqTceer2LK3CykLDrUwtb64/xOp9kjVC5Ed/wqI7RsB3nbrGuOU5WWNnZc5MyRohCsWoFxB57733aNGiBXZ2djg7OxfqPkop3nrrLSpXroytrS2dOnXixIkTD13DySvJ9F74Fz9EXsRMA690qcOyUY9J6ApxhzvPeJYzZeYEw7/aw7WUDOp6OvDj2FYSukLcwfqOJi9Tq8vJmkV/snpfTta83Lm2ZI0Qd7lzJE+nU8zfdoInv8zJmjoeDvwYJlkjRGEZdSQvMzOTgQMH0rx5c7766qtC3WfWrFnMnz+f//3vf1SvXp0333yTLl26cOTIEWxsbB7o+TdEX+LdX89xK0uLm4M184cE0dyv0sO8FCHKtNzgvZyYzsiv9/LnyWsADG7iw9u9GmBrJVNmhLiTpfl/Td7Kfy4w59cY0jIla4S4l9ysiUtMZ+TSvfxxIidrBjb2ZkZvf8kaIR6AUZu86dOnA7Bs2bJCra+UYt68ebzxxhv07t0bgG+++QYPDw/WrVvHkCFDHuj5p645hJm1HS1rVmLe4CDcHOQbVSHyk7vDuvFAzkWabS3NebePP/0bexuzLCFMlrmZBnMzDVqdYsbGIwC08KvEJ0Mka4QoiJV5zrGrmw7mZI2NpRnv9glggGSNEA+sVB2Td+bMGeLi4ujUqZN+mZOTEyEhIezevbvAJi8jI4OMjAz970lJSQBoNDC+Uy3GdqiFuZzRTIgC3Xl8UU13e5YMD6aWh4MRKxLC9FmZm3FLp0WjgXEdajGuo2SNEPdyZ9b4uVVg8fDG1PGUrBHiYZSqJi8uLg4ADw8Pg+UeHh762/Izc+ZM/ajhnT7/vyZ0CapetEUKUQY18a2IvbUFXf09mdG7AXZWpeqfDiGMonUtVw5eSmTWgIa0ruVm7HKEMHmNfV1wsLagc4OcrKlgLVkjxMMq8q1nypQpfPjhh/dc5+jRo9StW7eon7pAU6dOZeLEifrfk5KS8PHxkWMihCikJtVcODCts1zDS4gH8Nn/NUYpZLsRopAa+1YkWrJGiCJR5E3epEmTGDVq1D3XqVGjxkM9tqenJwDx8fFUrlxZvzw+Pp7AwMAC72dtbY21tRwDIcSjkNAV4sFoNBo0stkI8UAka4QoGkXe5Lm5ueHmVjzTUqpXr46npyfbtm3TN3VJSUns2bOHF198sVieUwghhBBCCCFKE6NeJ+/8+fNERUVx/vx5tFotUVFRREVFkZKSol+nbt26rF27Fsj5VnT8+PG8++67/Pjjjxw8eJARI0bg5eVFnz59jPQqhBBCCCGEEMJ0GPWI1rfeeov//e9/+t+DgoIA2LFjB+3atQMgJiaGxMRE/TqvvvoqqampPPfccyQkJNCqVSs2b978wNfIE0IIIYQQQoiySKOUUsYuoqQlJSXh5OREYmIijo6Oxi5HCCGEEEIIIe6rsH1MuTw3bW5fm3u9PCGEEEIIIYQwdbn9y/3G6cplk3f9+nUAfHx8jFyJEEIIIYQQQjyY5ORknJycCry9XDZ5Li4uQM6JX+71xxElL/cahhcuXJCptCZG3hvTJO+L6ZL3xnTJe2O65L0xTfK+mA6lFMnJyXh5ed1zvXLZ5JmZ5ZxU1MnJST6oJsrR0VHeGxMl741pkvfFdMl7Y7rkvTFd8t6YJnlfTENhBqmMegkFIYQQQgghhBBFS5o8IYQQQgghhChDymWTZ21tzbRp07C2tjZ2KeIu8t6YLnlvTJO8L6ZL3hvTJe+N6ZL3xjTJ+1L6lMvr5AkhhBBCCCFEWVUuR/KEEEIIIYQQoqySJk8IIYQQQgghyhBp8oQQQgghhBCiDCmXTd6iRYuoVq0aNjY2hISEsHfvXmOXVK7MnDmTxx57DAcHB9zd3enTpw8xMTEG67Rr1w6NRmPw88ILLxip4vLj7bffzvN3r1u3rv729PR0QkNDqVSpEvb29vTv35/4+HgjVlx+VKtWLc97o9FoCA0NBWSbKSm///47PXv2xMvLC41Gw7p16wxuV0rx1ltvUblyZWxtbenUqRMnTpwwWOfGjRsMHz4cR0dHnJ2deeaZZ0hJSSnBV1E23eu9ycrKYvLkyQQEBFChQgW8vLwYMWIEsbGxBo+R33b2wQcflPArKXvut92MGjUqz9+9a9euBuvIdlM87vfe5Jc7Go2G2bNn69eR7cY0lbsmb8WKFUycOJFp06YRGRlJo0aN6NKlC1euXDF2aeXGb7/9RmhoKH///TdbtmwhKyuLzp07k5qaarDe6NGjuXz5sv5n1qxZRqq4fGnQoIHB3/3PP//U3zZhwgQ2bNjAqlWr+O2334iNjaVfv35GrLb8+Oeffwzely1btgAwcOBA/TqyzRS/1NRUGjVqxKJFi/K9fdasWcyfP59PP/2UPXv2UKFCBbp06UJ6erp+neHDh3P48GG2bNnCxo0b+f3333nuuedK6iWUWfd6b9LS0oiMjOTNN98kMjKSNWvWEBMTQ69evfKsO2PGDIPtaOzYsSVRfpl2v+0GoGvXrgZ/9+XLlxvcLttN8bjfe3Pne3L58mW+/vprNBoN/fv3N1hPthsTpMqZpk2bqtDQUP3vWq1WeXl5qZkzZxqxqvLtypUrClC//fabflnbtm3VSy+9ZLyiyqlp06apRo0a5XtbQkKCsrS0VKtWrdIvO3r0qALU7t27S6hCkeull15Sfn5+SqfTKaVkmzEGQK1du1b/u06nU56enmr27Nn6ZQkJCcra2lotX75cKaXUkSNHFKD++ecf/To///yz0mg06tKlSyVWe1l393uTn7179ypAnTt3Tr/M19dXzZ07t3iLK+fye29GjhypevfuXeB9ZLspGYXZbnr37q06dOhgsEy2G9NUrkbyMjMz2bdvH506ddIvMzMzo1OnTuzevduIlZVviYmJALi4uBgsDw8Px9XVFX9/f6ZOnUpaWpoxyit3Tpw4gZeXFzVq1GD48OGcP38egH379pGVlWWw/dStW5eqVavK9lPCMjMz+e6773j66afRaDT65bLNGNeZM2eIi4sz2EacnJwICQnRbyO7d+/G2dmZJk2a6Nfp1KkTZmZm7Nmzp8RrLs8SExPRaDQ4OzsbLP/ggw+oVKkSQUFBzJ49m+zsbOMUWM7s3LkTd3d36tSpw4svvsj169f1t8l2Yxri4+PZtGkTzzzzTJ7bZLsxPRbGLqAkXbt2Da1Wi4eHh8FyDw8Pjh07ZqSqyjedTsf48eNp2bIl/v7++uXDhg3D19cXLy8vDhw4wOTJk4mJiWHNmjVGrLbsCwkJYdmyZdSpU4fLly8zffp0WrduzaFDh4iLi8PKyirPDpGHhwdxcXHGKbicWrduHQkJCYwaNUq/TLYZ48vdDvLLmNzb4uLicHd3N7jdwsICFxcX2Y5KUHp6OpMnT2bo0KE4Ojrql48bN47g4GBcXFzYtWsXU6dO5fLly3z88cdGrLbs69q1K/369aN69eqcOnWK1157jW7durF7927Mzc1luzER//vf/3BwcMhzmIZsN6apXDV5wvSEhoZy6NAhg+O+AIN59gEBAVSuXJmOHTty6tQp/Pz8SrrMcqNbt276/2/YsCEhISH4+vqycuVKbG1tjViZuNNXX31Ft27d8PLy0i+TbUaIwsnKymLQoEEopViyZInBbRMnTtT/f8OGDbGysuL5559n5syZWFtbl3Sp5caQIUP0/x8QEEDDhg3x8/Nj586ddOzY0YiViTt9/fXXDB8+HBsbG4Plst2YpnI1XdPV1RVzc/M8ZwOMj4/H09PTSFWVX2FhYWzcuJEdO3bg7e19z3VDQkIAOHnyZEmUJm5zdnamdu3anDx5Ek9PTzIzM0lISDBYR7afknXu3Dm2bt3Ks88+e8/1ZJspebnbwb0yxtPTM8+JvrKzs7lx44ZsRyUgt8E7d+4cW7ZsMRjFy09ISAjZ2dmcPXu2ZAoUANSoUQNXV1f9v1+y3RjfH3/8QUxMzH2zB2S7MRXlqsmzsrKicePGbNu2Tb9Mp9Oxbds2mjdvbsTKyhelFGFhYaxdu5bt27dTvXr1+94nKioKgMqVKxdzdeJOKSkpnDp1isqVK9O4cWMsLS0Ntp+YmBjOnz8v208JWrp0Ke7u7nTv3v2e68k2U/KqV6+Op6enwTaSlJTEnj179NtI8+bNSUhIYN++ffp1tm/fjk6n0zfmonjkNngnTpxg69atVKpU6b73iYqKwszMLM9UQVG8Ll68yPXr1/X/fsl2Y3xfffUVjRs3plGjRvddV7Yb01DupmtOnDiRkSNH0qRJE5o2bcq8efNITU3lqaeeMnZp5UZoaCgRERGsX78eBwcH/Xx6JycnbG1tOXXqFBERETzxxBNUqlSJAwcOMGHCBNq0aUPDhg2NXH3Z9vLLL9OzZ098fX2JjY1l2rRpmJubM3ToUJycnHjmmWeYOHEiLi4uODo6MnbsWJo3b06zZs2MXXq5oNPpWLp0KSNHjsTC4r9/vmWbKTkpKSkGo6NnzpwhKioKFxcXqlatyvjx43n33XepVasW1atX580338TLy4s+ffoAUK9ePbp27cro0aP59NNPycrKIiwsjCFDhhhMvxUP7l7vTeXKlRkwYACRkZFs3LgRrVarzx4XFxesrKzYvXs3e/bsoX379jg4OLB7924mTJjAk08+ScWKFY31ssqEe703Li4uTJ8+nf79++Pp6cmpU6d49dVXqVmzJl26dAFkuylO9/s3DXK+rFq1ahUfffRRnvvLdmPCjH16T2NYsGCBqlq1qrKyslJNmzZVf//9t7FLKleAfH+WLl2qlFLq/Pnzqk2bNsrFxUVZW1urmjVrqldeeUUlJiYat/ByYPDgwapy5crKyspKValSRQ0ePFidPHlSf/utW7fUmDFjVMWKFZWdnZ3q27evunz5shErLl9++eUXBaiYmBiD5bLNlJwdO3bk++/XyJEjlVI5l1F48803lYeHh7K2tlYdO3bM835dv35dDR06VNnb2ytHR0f11FNPqeTkZCO8mrLlXu/NmTNnCsyeHTt2KKWU2rdvnwoJCVFOTk7KxsZG1atXT73//vsqPT3duC+sDLjXe5OWlqY6d+6s3NzclKWlpfL19VWjR49WcXFxBo8h203xuN+/aUop9dlnnylbW1uVkJCQ5/6y3ZgujVJKFXsnKYQQQgghhBCiRJSrY/KEEEIIIYQQoqyTJk8IIYQQQgghyhBp8oQQQgghhBCiDJEmTwghhBBCCCHKEGnyhBBCCCGEEKIMkSZPCCGEEEIIIcoQafKEEEIIIYQQogyRJk8IIYQQQgghyhBp8oQQQgghhBCiDJEmTwghhBBCCCHKEGnyhBBCCCGEEKIMkSZPCCGEEEIIIcoQafKEEEIIIYQQogyRJk8IIYQQQgghyhBp8oQQQgghhBCiDJEmTwghhBBCCCHKEGnyhBBCCCGEEKIMkSZPCCHKgWXLlqHRaDh79qyxSylVdu7ciUajYefOnYVaf9asWdStWxedTle8hYkyY8qUKYSEhBi7DCFEGSNNnhBC3MeZM2cICwujdu3a2NnZYWdnR/369QkNDeXAgQPGLs/kVatWjR49euRZ/u2332Jubk7Xrl1JT083QmVFKykpiQ8//JDJkydjZmYYr+np6cydO5eQkBCcnJywsbGhdu3ahIWFcfz48WKta/HixSxbtqxYn+NhPWhtKSkpTJs2DX9/fypUqEClSpUIDAzkpZdeIjY2Vr/eTz/9xNtvv130BT+gH3/8keDgYGxsbKhatSrTpk0jOzvbYJ3x48cTHR3Njz/+aKQqhRBlkUYppYxdhBBCmKqNGzcyePBgLCwsGD58OI0aNcLMzIxjx46xZs0azp07x5kzZ/D19TV2qfek1WrJysrC2toajUZTos9drVo1/P392bhxo35ZeHg4I0aMoFOnTqxfvx4bG5sSramwdu7cSfv27dmxYwft2rW757rz5s1j2rRpxMfHG7yea9eu0bVrV/bt20ePHj3o1KkT9vb2xMTE8P333xMXF0dmZmaxvQZ/f39cXV0LPRpZkh6ktqysLEJCQjh27BgjR44kMDCQlJQUDh8+zIYNG1i1apX+PQoLC2PRokUYcxfn559/pnv37rRr146hQ4dy8OBBFi1axHPPPceSJUsM1h08eDCXL1/m999/N1K1QoiyxsLYBQghhKk6deoUQ4YMwdfXl23btlG5cmWD2z/88EMWL16cZ9TGFJmbm2Nubm7sMgD4/vvvGTlyJB06dCiyBi8tLQ07O7siqO7hLV26lF69euV5PaNGjWL//v2sXr2a/v37G9z2zjvv8Prrr5dkmUUiOzsbnU6HlZVViT3nunXr2L9/P+Hh4QwbNszgtvT09GJtlB/Gyy+/TMOGDfn111+xsMjZ3XJ0dOT999/npZdeom7duvp1Bw0axMCBAzl9+jQ1atQwVslCiDLE9PdMhBDCSGbNmkVqaipLly7N0+ABWFhYMG7cOHx8fPTLDhw4wKhRo6hRowY2NjZ4enry9NNPc/36dYP7jho1imrVquV5zLfffjvPSNuWLVto1aoVzs7O2NvbU6dOHV577TWDdRYsWECDBg2ws7OjYsWKNGnShIiICP3t+R2Tt379erp3746XlxfW1tb4+fnxzjvvoNVqDR67Xbt2+Pv7c+TIEdq3b4+dnR1VqlRh1qxZ9/0b3m3lypU8+eSTtGvXjh9//DFPQ/Tdd9/RuHFjbG1tcXFxYciQIVy4cCHfevbt20ebNm2ws7Pjtdde4+zZs2g0GubMmcPnn3+On58f1tbWPPbYY/zzzz95ajl27BgDBgzAxcUFGxsbmjRp8tBT5s6cOcOBAwfo1KmTwfI9e/awadMmnnnmmTwNHoC1tTVz5sx54Lpy38+//vqLiRMn4ubmRoUKFejbty9Xr17Vr1etWjUOHz7Mb7/9hkajQaPRGIxIJiQkMH78eHx8fLC2tqZmzZp8+OGHBscU3vl3nTdvnv7veuTIkQL/HkuXLqVDhw64u7tjbW1N/fr184xe3a+2u506dQqAli1b5rnNxsYGR0dHIGfbWrRoEYD+ce/cpnQ6HfPmzaNBgwbY2Njg4eHB888/z82bN/PU16NHD3799VcCAwOxsbGhfv36rFmzpsAacx05coQjR47w3HPP6Rs8gDFjxqCUYvXq1Qbr535u1q9ff9/HFkKIwpCRPCGEKMDGjRupWbPmA50UYcuWLZw+fZqnnnoKT09PDh8+zOeff87hw4f5+++/H3iq5OHDh+nRowcNGzZkxowZWFtbc/LkSf766y/9Ol988QXjxo1jwIABvPTSS6Snp3PgwAH27NmTZ8TjTsuWLcPe3p6JEydib2/P9u3beeutt0hKSmL27NkG6968eZOuXbvSr18/Bg0axOrVq5k8eTIBAQF069atUK/lhx9+YPjw4bRp04YNGzZga2trcPt7773Hm2++yaBBg3j22We5evUqCxYsoE2bNuzfvx9nZ2f9utevX6dbt24MGTKEJ598Eg8PD/1tERERJCcn8/zzz6PRaJg1axb9+vXj9OnTWFpa6v+uLVu2pEqVKkyZMoUKFSqwcuVK+vTpww8//EDfvn0L9Zpy7dq1C4Dg4GCD5bnN2f/93/8V6nEetK6xY8dSsWJFpk2bxtmzZ5k3bx5hYWGsWLECyJlCOnbsWOzt7fUjhrl/q7S0NNq2bculS5d4/vnnqVq1Krt27WLq1KlcvnyZefPmGTzX0qVLSU9P57nnnsPa2hoXF5cCX8eSJUto0KABvXr1wsLCgg0bNjBmzBh0Oh2hoaH3rS0/uVOiv/nmG954440Ct6Xnn3+e2NhYtmzZwrfffpvv7cuWLeOpp55i3LhxnDlzhoULF7J//37++usv/WcE4MSJEwwePJgXXniBkSNHsnTpUgYOHMjmzZt5/PHHC6x1//79ADRp0sRguZeXF97e3vrbczk5OeHn58dff/3FhAkTCnxcIYQoNCWEECKPxMREBag+ffrkue3mzZvq6tWr+p+0tDT9bXf+f67ly5crQP3+++/6ZSNHjlS+vr551p02bZq685/muXPnKkBdvXq1wFp79+6tGjRocM/Xs3TpUgWoM2fO3LPW559/XtnZ2an09HT9srZt2ypAffPNN/plGRkZytPTU/Xv3/+ez6uUUr6+vsrLy0tZWFiodu3aqdTU1DzrnD17Vpmbm6v33nvPYPnBgweVhYWFwfLcej799FODdc+cOaMAValSJXXjxg398vXr1ytAbdiwQb+sY8eOKiAgwOB16nQ61aJFC1WrVi39sh07dihA7dix456v8Y033lCASk5ONljet29fBaibN2/e8/4PWlfu+9mpUyel0+n0yydMmKDMzc1VQkKCflmDBg1U27Zt8zzXO++8oypUqKCOHz9usHzKlCnK3NxcnT9/Xin139/V0dFRXblypVCvI7/PVpcuXVSNGjUMlhVUW0GPWadOHQUoX19fNWrUKPXVV1+p+Pj4POuGhoaq/HZx/vjjDwWo8PBwg+WbN2/Os9zX11cB6ocfftAvS0xMVJUrV1ZBQUH3rHX27NkK0P8N7/TYY4+pZs2a5VneuXNnVa9evXs+rhBCFJZM1xRCiHwkJSUBYG9vn+e2du3a4ebmpv/JnRoGGIxOpaenc+3aNZo1awZAZGTkA9eRO3q1fv36Ak/L7+zszMWLF/Odkngvd9aanJzMtWvXaN26NWlpaRw7dsxgXXt7e5588kn971ZWVjRt2pTTp08X6rlu3LhBdnY23t7eeUbwANasWYNOp2PQoEFcu3ZN/+Pp6UmtWrXYsWOHwfrW1tY89dRT+T7X4MGDqVixov731q1bA+hrvXHjBtu3b2fQoEH6133t2jWuX79Oly5dOHHiBJcuXSrU68p1/fp1LCws8nxecj9HDg4O932Mh6nrueeeMxjRat26NVqtlnPnzt33+VatWkXr1q2pWLGiwd+8U6dOaLXaPCcB6d+/P25ubvd9XDD8bCUmJnLt2jXatm3L6dOnSUxMLNRj5PeYe/bs4ZVXXgFyRqKfeeYZKleuzNixY8nIyLjvY6xatQonJycef/xxg9fcuHFj7O3t83zOvLy8DEZPHR0dGTFiBPv37ycuLq7A57l16xaQ8zm9m42Njf72O+W+D0IIURRkuqYQQuQjd6c8JSUlz22fffYZycnJxMfHGzQ+kLOjPn36dL7//nuuXLlicNvD7NwOHjyYL7/8kmeffZYpU6bQsWNH+vXrx4ABA/QnfJk8eTJbt26ladOm1KxZk86dOzNs2LB8j1260+HDh3njjTfYvn27vhkpqFZvb+880+MqVqxY6EtIdOzYkapVq7JkyRJcXFz45JNPDG4/ceIESilq1aqV7/3vnEIHUKVKlQJP+lG1atU8dQL6Y65OnjyJUoo333yTN998M9/HuHLlClWqVLn/C7uP3OPEkpOTDaab5udh6rrfa72XEydOcODAgQIbt7s/v9WrV7/vY+b666+/mDZtGrt37yYtLc3gtsTERJycnAr9WHdycnJi1qxZzJo1i3PnzrFt2zbmzJnDwoULcXJy4t13373n/U+cOEFiYiLu7u753n73a65Zs2aez33t2rWBnGMVPT09832c3CY3v8YzPT093y86lFIlfuZbIUTZJU2eEELkw8nJicqVK3Po0KE8t+Ueo5ffhcUHDRrErl27eOWVVwgMDMTe3h6dTkfXrl0NRuIK2pm7+6Qntra2/P777+zYsYNNmzaxefNmVqxYQYcOHfj1118xNzenXr16xMTEsHHjRjZv3swPP/zA4sWLeeutt5g+fXq+z5OQkEDbtm1xdHRkxowZ+Pn5YWNjQ2RkJJMnT84zaljQmTnVA5yifuHChdy8eZP58+dTsWJFg+uY6XQ6NBoNP//8c77PdfcIWX47yYWtNfe1vfzyy3Tp0iXfdWvWrHnP13K3SpUqkZ2dTXJyssGoXe4ZFA8ePKgfUSzIw9T1KO+LTqfj8ccf59VXX8339txmJte9/uZ3OnXqFB07dqRu3bp8/PHH+Pj4YGVlxU8//cTcuXOL7ELxvr6+PP300/Tt25caNWoQHh5+3yZPp9Ph7u5OeHh4vrcXdqTyfnJP1HT58mWDEzPlLmvatGme+9y8eRNXV9cieX4hhJAmTwghCtC9e3e+/PJL9u7dm+9O2d1u3rzJtm3bmD59Om+99ZZ++YkTJ/KsW7FiRRISEvIsz2+anZmZGR07dqRjx458/PHHvP/++7z++uvs2LFDf1a+ChUqMHjwYAYPHkxmZib9+vXjvffeY+rUqfleomDnzp1cv36dNWvW0KZNG/3yM2fO3Pd1PiwzMzO++eYbEhMTmT59Oi4uLowbNw4APz8/lFJUr149T3NR1HJPUW9paZnnbJgPK7eZO3PmDA0bNtQv79mzJzNnzuS77767b5NXHHVBwV8o+Pn5kZKSUqTPBbBhwwYyMjL48ccfDUYa754Kea/aHkTFihXx8/Mz+ELmXq9569attGzZslBNa+7o6p2Pl3vx+vzOjpsrMDAQgH///dfg347Y2FguXrzIc889l+c+Z86coVGjRvetSQghCkOOyRNCiAK8+uqr2NnZ8fTTTxMfH5/n9rtHS3JHVe5efvdZCiFnZzMxMdFguuPly5dZu3atwXo3btzIc9/cHcjcqWB3X57BysqK+vXro5QiKysr39eWX62ZmZksXrw43/WLiqWlJatXr6Zly5aMHz9ef/bDfv36YW5uzvTp0/P8/ZRSeV7jo3B3d6ddu3Z89tlnXL58Oc/td16CoLCaN28O5OzU3728a9eufPnll6xbty7P/TIzM3n55ZeLrS7I+QIgvy8UBg0axO7du/nll1/y3JaQkEB2dvZDPV9+n63ExESWLl1a6NryEx0dne8xa+fOnePIkSPUqVPH4HGBPI89aNAgtFot77zzTp7Hyc7OzrN+bGyswTaZlJTEN998Q2BgYIFTNQEaNGhA3bp1+fzzzw1G55csWYJGo2HAgAEG6ycmJnLq1ClatGhR4GMKIcSDkJE8IYQoQK1atYiIiGDo0KHUqVOH4cOH06hRI5RSnDlzhoiICMzMzPD29gZyjr9q06YNs2bNIisriypVqvDrr7/mOzo2ZMgQJk+eTN++fRk3bhxpaWksWbKE2rVrG5ygZcaMGfz+++90794dX19frly5wuLFi/H29qZVq1YAdO7cGU9PT1q2bImHhwdHjx5l4cKFdO/evcATfrRo0YKKFSsycuRIxo0bh0aj4dtvv32g6ZcPy87Ojk2bNtG2bVuefvppnJyc6NWrF++++y5Tp07l7Nmz9OnTBwcHB86cOcPatWt57rnn9M1QUVi0aBGtWrUiICCA0aNHU6NGDeLj49m9ezcXL14kOjr6gR6vRo0a+Pv7s3XrVp5++mmD27755hs6d+5Mv3796NmzJx07dqRChQqcOHGC77//nsuXL+uvlVfUdQE0btyYJUuW8O6771KzZk3c3d3p0KEDr7zyCj/++CM9evRg1KhRNG7cmNTUVA4ePMjq1as5e/bsQ00f7Ny5M1ZWVvTs2ZPnn3+elJQUvvjiC9zd3fM0rwXVlp8tW7Ywbdo0evXqRbNmzbC3t+f06dN8/fXXZGRkGEz/bdy4MQDjxo2jS5cumJubM2TIENq2bcvzzz/PzJkziYqKonPnzlhaWnLixAlWrVrFJ598YtCA1a5dm2eeeYZ//vkHDw8Pvv76a+Lj4/NtWO82e/ZsevXqRefOnRkyZAiHDh1i4cKFPPvss9SrV89g3a1bt6KUonfv3oX9MwshxL2V8Nk8hRCi1Dl58qR68cUXVc2aNZWNjY2ytbVVdevWVS+88IKKiooyWPfixYuqb9++ytnZWTk5OamBAweq2NhYBahp06YZrPvrr78qf39/ZWVlperUqaO+++67PJdQ2LZtm+rdu7fy8vJSVlZWysvLSw0dOtTgtPefffaZatOmjapUqZKytrZWfn5+6pVXXlGJiYn6dfK7hMJff/2lmjVrpmxtbZWXl5d69dVX1S+//JLnkgFt27bN9xINBV0G4m6+vr6qe/fueZbHxcXp/6a5z/fDDz+oVq1aqQoVKqgKFSqounXrqtDQUBUTE3PfenJP9T979uw8t+X39z916pQaMWKE8vT0VJaWlqpKlSqqR48eavXq1fp1CnsJBaWU+vjjj5W9vX2+lw9IS0tTc+bMUY899piyt7dXVlZWqlatWmrs2LHq5MmTD1xX7vv5zz//GNw3v3rj4uJU9+7dlYODgwIMLlmQnJyspk6dqmrWrKmsrKyUq6uratGihZozZ47KzMxUSt3771qQH3/8UTVs2FDZ2NioatWqqQ8//FB9/fXXeT6D96rtbqdPn1ZvvfWWatasmXJ3d1cWFhbKzc1Nde/eXW3fvt1g3ezsbDV27Fjl5uamNBpNnsspfP7556px48bK1tZWOTg4qICAAPXqq6+q2NhY/Tq5n9tffvlFNWzYUFlbW6u6deuqVatWFfrvsHbtWhUYGKisra2Vt7e3euONN/R/1zsNHjxYtWrVqtCPK4QQ96NRqgS+thVCCCHKuMTERGrUqMGsWbN45plnjF2OeETVqlXD39+fjRs3FuvzxMXFUb16db7//nsZyRNCFBk5Jk8IIYQoAk5OTrz66qvMnj27yM4gKcq+efPmERAQIA2eEKJIyUieEEIIIcRdSmokTwghioOM5AkhhBBCCCFEGSIjeUIIIYQQQghRhshInhBCCCGEEEKUIdLkCSGEEEIIIUQZIk2eEEIIIYQQQpQhFsYuwBh0Oh2xsbE4ODig0WiMXY4QQgghhBBC3JdSiuTkZLy8vDAzK3i8rlw2ebGxsfj4+Bi7DCGEEEIIIYR4YBcuXMDb27vA28tlk+fg4ADk/HEcHR2NXI0QQgghhBBC3F9SUhI+Pj76fqYg5bLJy52i6ejoaJpNnk4L53ZBSjzYe4BvCzAzN3ZVQgghhBBCCBNwv0POymWTZ9KO/AibJ0NS7H/LHL2g64dQv5fx6hJCCCGEEEKUCnJ2TVNy5EdYOcKwwQNIupyz/MiPxqlLCCGEEEIIUWpIk2cqdNqcETxUPjfeXrZ5Ss56QgghhBBCCFEAafJMxbldeUfwDChIupSznhBCCCGEEEIUQJo8U5ESX7TrCSGEEEIIIcolafJMhb1H0a4nhBBCCCGEKJekyTMVvi1yzqJJQadD1YBjlZz1hBBCCCGEEKIA0uSZgtzr4tXvQ85JVvJr9BTU752znpx8RQghhBBCCFEAuU6eseV3XTyNBtQdZ9nUmIHSwd+Lc37kunlCCCGEEEKIAjzySN6iRYuoVq0aNjY2hISEsHfv3gLXPXz4MP3796datWpoNBrmzZuXZ52ZM2fy2GOP4eDggLu7O3369CEmJsZgnXbt2qHRaAx+XnjhhUd9KSWvoOviKd29f5fr5gkhhBBCCCEK8EhN3ooVK5g4cSLTpk0jMjKSRo0a0aVLF65cuZLv+mlpadSoUYMPPvgAT0/PfNf57bffCA0N5e+//2bLli1kZWXRuXNnUlNTDdYbPXo0ly9f1v/MmjXrUV5KybvndfHuR66bJ4QQQgghhMjfI03X/Pjjjxk9ejRPPfUUAJ9++imbNm3i66+/ZsqUKXnWf+yxx3jssccA8r0dYPPmzQa/L1u2DHd3d/bt20ebNm30y+3s7ApsFEuF+14X737uuG5e9dZFVpYQQgghhBCidHvokbzMzEz27dtHp06d/nswMzM6derE7t27i6Q4gMTERABcXFwMloeHh+Pq6oq/vz9Tp04lLS2twMfIyMggKSnJ4Mfoiup6d3LdPCGEEEIIIcQdHnok79q1a2i1Wjw8DK/b5uHhwbFjxx65MACdTsf48eNp2bIl/v7++uXDhg3D19cXLy8vDhw4wOTJk4mJiWHNmjX5Ps7MmTOZPn16kdRUZIrqendy3TwhhBBCCCHEHUz67JqhoaEcOnSIP//802D5c889p///gIAAKleuTMeOHTl16hR+fn55Hmfq1KlMnDhR/3tSUhI+Pj7FV3hh5F4XL+ky9z4uT1PA7Zqc+8t184QQQgghhBB3eOjpmq6urpibmxMfbzhdMD4+vkiOlQsLC2Pjxo3s2LEDb2/ve64bEhICwMmTJ/O93draGkdHR4MfozMzz7kMApD3uniF/L3rBzmPI4QQQgghhBC3PXSTZ2VlRePGjdm2bZt+mU6nY9u2bTRv3vyhC1JKERYWxtq1a9m+fTvVq1e/732ioqIAqFy58kM/r1HU7wWDvgGHu5pixzteR78v8rndK+d+cp08IYQQQgghxF0eabrmxIkTGTlyJE2aNKFp06bMmzeP1NRU/dk2R4wYQZUqVZg5cyaQc7KWI0eO6P//0qVLREVFYW9vT82aNYGcKZoRERGsX78eBwcH4uLiAHBycsLW1pZTp04RERHBE088QaVKlThw4AATJkygTZs2NGzY8FFejnHU7wU12sEHt6ePDl8NPiH//V73CajdxfB2vw4ygieEEEIIIYTI1yM1eYMHD+bq1au89dZbxMXFERgYyObNm/UnYzl//jxmZv8NFsbGxhIUFKT/fc6cOcyZM4e2bduyc+dOAJYsWQLkXPD8TkuXLmXUqFFYWVmxdetWfUPp4+ND//79eeONNx7lpRjXnQ1bfsfY3X27NHhCCCGEEEKIAjzyiVfCwsIICwvL97bcxi1XtWrVUOreF/++3+0+Pj789ttvD1SjEEIIIYQQQpQXD31MnhBCCCGEEEII0yNNnhBCCCGEEEKUIdLkCSGEEEIIIUQZIk2eEEIIIYQQQpQh0uQJIYQQQgghRBkiTZ4QQgghhBBClCHS5AkhhBBCCCFEGSJNnhBCCCGEEEKUIdLkCSGEEEIIIUQZIk2eEEIIIYQQQpQhFsYuoFzSaeHcLkiJB3sPqNzo0e7v2wLMzIunViGEEEIIIUSpIk1eSTvyI//f3p3HZVXm/x9/34iAC4uobKbiNoK5axLqpCYF6mRO5jY0KkNYk1SK46hNbjkzWKaZ5i9zJltmNE3HzJyGBtcyERUzx43U3FIBlQB3kfv8/uDrXbfcArLdcPN6Ph73I7jOdc75nOvmCO/Ouc+lhElSztmf2tz9i7/+4c+lDdOs1/cIkCJeldoMLLs6AQAAAFRJ3K5ZkQ6ukz4eaR3QJOlSWvG3sSam4Po55/K3e3Bd6WsEAAAAUKUR8iqKOS//Cp4MGwsN636FKmT9hMnFWB8AAACAIyPkVZST2wtegbPldHIJd2BIOWfy9wMAAACg2iLkVZTL6WXbr7zWBwAAAFClEfIqSl3fsu1XXusDAAAAqNIIeRWlaff8p2DKVHi/xiFFbOhu65skj0b5+wEAAABQbZU65C1atEiBgYFyc3NTSEiIdu7cede+Bw4c0ODBgxUYGCiTyaT58+eXaJvXr1/X2LFjVb9+fdWtW1eDBw9Wenolv03RqUb+NAeSCgY1k3W/It1l/YjZzJcHAAAAVHOlCnkrV65UXFycpk+frj179qhDhw4KDw9XRkaGzf5Xr15V8+bNNXv2bPn5+ZV4m+PHj9dnn32mVatWaevWrTp79qyeeOKJ0hxKxWgzUBr6oeR+x7F73MM8eU/8zcb6AfnbZZ48AAAAoNozGYZh65n8xRISEqIHHnhAb731liTJbDarcePGev755zV58uRC1w0MDNS4ceM0bty4e9pmdna2GjZsqOXLl+vJJ5+UJB0+fFjBwcFKSkrSgw8+WGTdOTk58vT0VHZ2tjw8PEpw5KV0PUea3Tj/68jV+bdo3v7+pf97AudfA+7+vTnPev0WD3MFDwAAAHBwxc0xJb6Sd/PmTaWkpCgsLOynjTk5KSwsTElJSeW2zZSUFOXm5lr1CQoKUpMmTe663xs3bignJ8fqZVc/D2RNu997QCvt+gAAAAAcVolD3oULF5SXlydfX+unOfr6+iotLa3ctpmWliYXFxd5eXkVe7/x8fHy9PS0vBo3blyi+gAAAACgsqsWT9ecMmWKsrOzLa/Tp0/buyQAAAAAKBfOJV2xQYMGqlGjRoGnWqanp9/1oSplsU0/Pz/dvHlTWVlZVlfzCtuvq6urXF1dS1QTAAAAAFQlJb6S5+Lioi5dumjjxo2WNrPZrI0bNyo0NLTcttmlSxfVrFnTqk9qaqpOnTpV4v0CAAAAgKMo8ZU8SYqLi9OoUaPUtWtXdevWTfPnz9eVK1cUFRUlSRo5cqQaNWqk+Ph4SfkPVjl48KDl6zNnzmjv3r2qW7euWrZsWaxtenp6Kjo6WnFxcfL29paHh4eef/55hYaGFuvJmgAAAADgyEoV8oYNG6bz589r2rRpSktLU8eOHZWQkGB5cMqpU6fk5PTTxcKzZ8+qU6dOlu9ff/11vf766+rVq5e2bNlSrG1K0htvvCEnJycNHjxYN27cUHh4uP7f//t/pTkUAAAAAHAIpZonr6qy+zx5N68UPg/evX7vUqd86wUAAABgd+U+Tx4AAAAAoPIh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgANxtncB1YI5Tzq5XbqcLtX1lfw7lP8+mnaXnGqU/X4AAAAAVGqEvPJ2cJ2UMEnKOftTm7t/+e/DI0CKeFVqM7Bs9wUAAACgUuN2zfJ0cJ308Ujr8CVJl9LKbh+HP7e9j5xz+e0H15XdvgAAAABUeoS88mLOy7+6JsPGQsO6X2kkTi18HwmTS78PAAAAAFUGIa+8nNxe8OqaLaeTS7efS+cKWWhIOWfyawEAAABQLRDyysvl9LLtVxoVsQ8AAAAAlQIhr7zU9S3bfqVREfsAAAAAUCmUOuQtWrRIgYGBcnNzU0hIiHbu3Flo/1WrVikoKEhubm5q166dPv/8c6vlJpPJ5mvOnDmWPoGBgQWWz549u7SHUraads9/wqVMhfdrHFK6/bj7F7IPk+TRKL8WAAAAANVCqULeypUrFRcXp+nTp2vPnj3q0KGDwsPDlZGRYbP/9u3bNWLECEVHR+ubb77RoEGDNGjQIO3fv9/S59y5c1avpUuXymQyafDgwVbbeuWVV6z6Pf/886U5lLLnVCN/CgNJBUOYybpfaTwyq/B9RMxmvjwAAACgGilVyJs3b55iYmIUFRWlNm3aaPHixapdu7aWLl1qs/+bb76piIgITZw4UcHBwZo1a5Y6d+6st956y9LHz8/P6vXpp5+qT58+at68udW23N3drfrVqVOnNIdSPtoMlIZ+KLn7Wbd7lOE8eUH977KPgPx25skDAAAAqpUSh7ybN28qJSVFYWFhP23MyUlhYWFKSkqyuU5SUpJVf0kKDw+/a//09HT9+9//VnR0dIFls2fPVv369dWpUyfNmTNHt27dKumhlK82A6WxP7uFNXK19Fwpn6hZnH2M+x8BDwAAAKiGnEu64oULF5SXlydfX+uHevj6+urw4cM210lLS7PZPy3N9uTgH3zwgdzd3fXEE09Ytb/wwgvq3LmzvL29tX37dk2ZMkXnzp3TvHnzbG7nxo0bunHjhuX7nJycIo+vTP38dsny+nzcnfvgFk0AAACgWipxyKsIS5cuVWRkpNzc3Kza4+LiLF+3b99eLi4ueuaZZxQfHy9XV9cC24mPj9fMmTPLvV4AAAAAsLcS367ZoEED1ahRQ+np1nOwpaeny8/Pz+Y6fn5+xe7/1VdfKTU1VU8//XSRtYSEhOjWrVs6ceKEzeVTpkxRdna25XX69OkitwkAAAAAVVGJQ56Li4u6dOmijRs3WtrMZrM2btyo0NBQm+uEhoZa9ZekxMREm/3fffdddenSRR06dCiylr1798rJyUk+Pj42l7u6usrDw8PqBQAAAACOqFS3a8bFxWnUqFHq2rWrunXrpvnz5+vKlSuKioqSJI0cOVKNGjVSfHy8JOnFF19Ur169NHfuXA0YMEArVqzQ7t27tWTJEqvt5uTkaNWqVZo7d26BfSYlJSk5OVl9+vSRu7u7kpKSNH78eD311FOqV69eaQ4HAAAAAKq8UoW8YcOG6fz585o2bZrS0tLUsWNHJSQkWB6ucurUKTk5/XSxsHv37lq+fLlefvllvfTSS2rVqpXWrl2rtm3bWm13xYoVMgxDI0aMKLBPV1dXrVixQjNmzNCNGzfUrFkzjR8/3upzegAAAABQXZX6wSuxsbGKjY21uWzLli0F2oYMGaIhQ4YUus0xY8ZozJgxNpd17txZO3bsuOc6AQAAAKA6KNVk6AAAAACAyoWQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA7E2d4FOCRznnRyu3Q5XarrK/l3sH8NTbtLTjUqvg4AAAAAFYqQV9YOrpMSJkk5Z39qc/ev2BoOfy5tmGZdg0eAFPGq1GZgxdYCAAAAoEJxu2ZZOrhO+nikdbiSpEtpFVvHmpiCNeScy6/t4LqKrQUAAABAhSLklRVzXv4VPBk2FhrW/cpdITUkTK6gGgAAAADYAyGvrJzcXvDqmS2nk8u/lrsypJwz+bUCAAAAcEiEvLJyOb1s+5WnylADAAAAgHJR6pC3aNEiBQYGys3NTSEhIdq5c2eh/VetWqWgoCC5ubmpXbt2+vzzz62Wjx49WiaTyeoVERFh1SczM1ORkZHy8PCQl5eXoqOjdfny5dIeSunU9S3bfuWpMtQAAAAAoFyUKuStXLlScXFxmj59uvbs2aMOHTooPDxcGRkZNvtv375dI0aMUHR0tL755hsNGjRIgwYN0v79+636RURE6Ny5c5bXRx99ZLU8MjJSBw4cUGJiotavX68vv/xSY8aMKc2hlF7T7vlPsJSp8H6NQyqgmLvVYJI8GuXXCgAAAMAhlSrkzZs3TzExMYqKilKbNm20ePFi1a5dW0uXLrXZ/80331RERIQmTpyo4OBgzZo1S507d9Zbb71l1c/V1VV+fn6WV7169SzLDh06pISEBP39739XSEiIevbsqYULF2rFihU6e7YYn4krL0418qcokFQwZJms+1WIu9QQMZv58gAAAAAHVuKQd/PmTaWkpCgsLOynjTk5KSwsTElJSTbXSUpKsuovSeHh4QX6b9myRT4+PmrdurV+//vf6+LFi1bb8PLyUteuXS1tYWFhcnJyUnKy7Yea3LhxQzk5OVavctFmoDT0Q8ndz7rdo4LnyXvibzZqCMivjXnyAAAAAIdW4pB34cIF5eXlydfX+vNdvr6+SkuzPS9cWlpakf0jIiL04YcfauPGjXr11Ve1detW9evXT3l5eZZt+Pj4WG3D2dlZ3t7ed91vfHy8PD09La/GjRvf8/EWW5uB0tiffS4xcrX0XAU/UTOof8Eaxv2PgAcAAABUA872LuBOw4cPt3zdrl07tW/fXi1atNCWLVvUt2/fEm1zypQpiouLs3yfk5NTvkHv57dD2uvzb3fWwC2aAAAAQLVQ4it5DRo0UI0aNZSebv04/vT0dPn5+dlcx8/P7576S1Lz5s3VoEEDHT161LKNOx/scuvWLWVmZt51O66urvLw8LB6AQAAAIAjKnHIc3FxUZcuXbRx40ZLm9ls1saNGxUaGmpzndDQUKv+kpSYmHjX/pL0ww8/6OLFi/L397dsIysrSykpKZY+mzZtktlsVkhIRTy5EgAAAAAqr1I9XTMuLk5/+9vf9MEHH+jQoUP6/e9/rytXrigqKkqSNHLkSE2ZMsXS/8UXX1RCQoLmzp2rw4cPa8aMGdq9e7diY2MlSZcvX9bEiRO1Y8cOnThxQhs3btTjjz+uli1bKjw8XJIUHBysiIgIxcTEaOfOnfr6668VGxur4cOHKyAgoDSHAwAAAABVXqk+kzds2DCdP39e06ZNU1pamjp27KiEhATLw1VOnTolJ6efcmT37t21fPlyvfzyy3rppZfUqlUrrV27Vm3btpUk1ahRQ/v27dMHH3ygrKwsBQQE6NFHH9WsWbPk6upq2c6yZcsUGxurvn37ysnJSYMHD9aCBQtKcygAAAAA4BBK/eCV2NhYy5W4O23ZsqVA25AhQzRkyBCb/WvVqqUvvviiyH16e3tr+fLl91QnAAAAAFQHpbpdEwAAAABQuRDyAAAAAMCBEPIAAAAAwIEQ8gAAAADAgRDyAAAAAMCBEPIAAAAAwIEQ8gAAAADAgZR6njxIMudJJ7dLl9Olur6Sfwd7V1TQnTU27S451bB3VQAAAADKGCGvtA6ukxImSTlnf2pz97dfPbYc/lzaMM26Ro8AKeJVqc1A+9UFAAAAoMxxu2ZpHFwnfTzSOjxJ0qU0+9RzN2tiCtaYcy6/9oPr7FMTAAAAgHJByCspc17+FTwZNhYa1v3srpAaEyZXkhoBAAAAlAVCXkmd3F7w6pgtp5PLv5YSM6ScM/nHAgAAAMAhEPJK6nJ62fazp6pQIwAAAIBiIeSVVF3fsu1nT1WhRgAAAADFQsgrqabd859QKVPh/RqHVEg5hbtbjSbJo1H+sQAAAABwCIS8knKqkT8FgaSCIcpk3a9SuEuNEbMrUY0AAAAASouQVxptBkpDP5Tc/azbPSrZPHlP/M1GjQH5tTNPHgAAAOBQSh3yFi1apMDAQLm5uSkkJEQ7d+4stP+qVasUFBQkNzc3tWvXTp9//rllWW5uriZNmqR27dqpTp06CggI0MiRI3X2rPVTLAMDA2Uymaxes2fPLu2hlEybgdLYnx1z5GrpuUr2RM2g/gVrHPc/Ah4AAADggEoV8lauXKm4uDhNnz5de/bsUYcOHRQeHq6MjAyb/bdv364RI0YoOjpa33zzjQYNGqRBgwZp//79kqSrV69qz549mjp1qvbs2aM1a9YoNTVVAwcWDCOvvPKKzp07Z3k9//zzpTmU0vn57Y5Nu1fO2x+rQo0AAAAASq1UIW/evHmKiYlRVFSU2rRpo8WLF6t27dpaunSpzf5vvvmmIiIiNHHiRAUHB2vWrFnq3Lmz3nrrLUmSp6enEhMTNXToULVu3VoPPvig3nrrLaWkpOjUqVNW23J3d5efn5/lVadOndIcCgAAAAA4hBKHvJs3byolJUVhYWE/bczJSWFhYUpKSrK5TlJSklV/SQoPD79rf0nKzs6WyWSSl5eXVfvs2bNVv359derUSXPmzNGtW7dKeigAAAAA4DCcS7rihQsXlJeXJ19f6znWfH19dfjwYZvrpKWl2eyflpZms//169c1adIkjRgxQh4eHpb2F154QZ07d5a3t7e2b9+uKVOm6Ny5c5o3b57N7dy4cUM3btywfJ+Tk1OsYwQAAACAqqbEIa+85ebmaujQoTIMQ2+//bbVsri4OMvX7du3l4uLi5555hnFx8fL1dW1wLbi4+M1c+bMcq8ZAAAAAOytxLdrNmjQQDVq1FB6erpVe3p6uvz8/Gyu4+fnV6z+twPeyZMnlZiYaHUVz5aQkBDdunVLJ06csLl8ypQpys7OtrxOnz5dxNEBAAAAQNVU4pDn4uKiLl26aOPGjZY2s9msjRs3KjQ01OY6oaGhVv0lKTEx0ar/7YB35MgRbdiwQfXr1y+ylr1798rJyUk+Pj42l7u6usrDw8PqBQAAAACOqFS3a8bFxWnUqFHq2rWrunXrpvnz5+vKlSuKioqSJI0cOVKNGjVSfHy8JOnFF19Ur169NHfuXA0YMEArVqzQ7t27tWTJEkn5Ae/JJ5/Unj17tH79euXl5Vk+r+ft7S0XFxclJSUpOTlZffr0kbu7u5KSkjR+/Hg99dRTqlevXmkOp/jMedLJ7dLldKmur+TfoWL2W5buPAamVQAAAAAcQqlC3rBhw3T+/HlNmzZNaWlp6tixoxISEiwPVzl16pScnH66WNi9e3ctX75cL7/8sl566SW1atVKa9euVdu2bSVJZ86c0bp16yRJHTt2tNrX5s2b1bt3b7m6umrFihWaMWOGbty4oWbNmmn8+PFWn9MrVwfXSQmTpJyfTdDu7l8x+y4rhz+XNkyzPgaPACniVSZIBwAAAKq4Uj94JTY2VrGxsTaXbdmypUDbkCFDNGTIEJv9AwMDZRhGofvr3LmzduzYcc91lomD66SPR0q6o8ZLtp8OWmmtiVGBY8g5l39sQz8k6AEAAABVWKkmQ69WzHn5V/DuDEeSdZs5r6IqKoVCjiFhchU5BgAAAAC2EPKK6+R269sb7+Z0cvnXUm4MKedM/rECAAAAqJIIecV1Ob3oPvfSrzJzhGMAAAAAqilCXnHV9S3bfpWZIxwDAAAAUE0R8oqraff8J1DKVHi/xiEVUk7p3O0YTJJHo/xjBQAAAFAlEfKKy6lG/hQDkgqGJJN1vyrhLscQMbsKHQMAAACAOxHy7kWbgflTDLj7Wbd7VLF58p74m41jCGD6BAAAAMABEPKKYs6Tjn8l/W91/n+DBkhjd/60PHK19FwVe6JmUP+Cx/DCXqlWvZ+Ok2kUAAAAgCqp1JOhO7SD6/Lnxvv51AkeAVLYKz99X1U/v/bzWzKvZUkLOhQ8zohXubIHAAAAVDFcybubg+ukj0cWnBsv55y0JsY+NZWXNTG2j/PjkfnjAAAAAKDKIOTZYs7Lv4Inw8ZCW21VXSHHmTCZWzcBAACAKoSQZ8vJ7QWvbFlxxKBniyHlnMkfDwAAAABVAiHPlsvp9q6gcmE8AAAAgCqDkHcncx6h5k6X07llEwAAAKgiCHk/d3CdNL+t9MVLRXS8cyLxqq6I4/nipfxx4SEsAAAAQKVHyLvtbk/TLMDRAt5tRRwXT9sEAAAAqgRCnjlPOrZF+uwFFeuBKh4B0hN/K++qKtYTf5Pc/YroZOS/PntB+n4rt28CAAAAlVT1ngz9qzek1BXFuHr3f8JmSN1fkG5dL9eyKlxQf+kX4dLsxkX3vfaj9OFAyd1f6hIl1W8h1fXNnxT+5xOsAwAAALCLUl/JW7RokQIDA+Xm5qaQkBDt3Lmz0P6rVq1SUFCQ3Nzc1K5dO33++edWyw3D0LRp0+Tv769atWopLCxMR44cseqTmZmpyMhIeXh4yMvLS9HR0bp8+fK9F79tbvEDniTVaei4QeZej+vSOWnLX6V/RUsf/IrP7AEAAACVRKlC3sqVKxUXF6fp06drz5496tChg8LDw5WRkWGz//bt2zVixAhFR0frm2++0aBBgzRo0CDt37/f0ue1117TggULtHjxYiUnJ6tOnToKDw/X9es/XT2LjIzUgQMHlJiYqPXr1+vLL7/UmDFjSnMoxVPXt/z3UVXxmT0AAACgUihVyJs3b55iYmIUFRWlNm3aaPHixapdu7aWLl1qs/+bb76piIgITZw4UcHBwZo1a5Y6d+6st956S1L+Vbz58+fr5Zdf1uOPP6727dvrww8/1NmzZ7V27VpJ0qFDh5SQkKC///3vCgkJUc+ePbVw4UKtWLFCZ8/ew1W5kmgcUr7brzRK8nCZ//s8Y8JkPq8HAAAA2FGJQ97NmzeVkpKisLCwnzbm5KSwsDAlJSXZXCcpKcmqvySFh4db+h8/flxpaWlWfTw9PRUSEmLpk5SUJC8vL3Xt2tXSJywsTE5OTkpOTra53xs3bignJ8fqVXw/CzyOequmTSUMejlnpJPby7waAAAAAMVT4gevXLhwQXl5efL1tb6F0dfXV4cPH7a5Tlpams3+aWlpluW32wrr4+PjY30Qzs7y9va29LlTfHy8Zs6cWcwju4NHgBQxW2oz8Kc2lzrSjGzrfvb+vixrOrhOSph0b59X/DkmkwcAAADsplpMoTBlyhRlZ2dbXqdPny56pVr1pJHrpHH/sw541UGbgdK4/dJvP80fh3vFZxcBAAAAuylxyGvQoIFq1Kih9HTrqzbp6eny87M955qfn1+h/W//t6g+dz7Y5datW8rMzLzrfl1dXeXh4WH1ujtT/uuxBVLzXtXsFs2fcaohteidPw63x6RIJsmjUf50CgAAAADsosQhz8XFRV26dNHGjRstbWazWRs3blRoaKjNdUJDQ636S1JiYqKlf7NmzeTn52fVJycnR8nJyZY+oaGhysrKUkpKiqXPpk2bZDabFRJSBg9G8QiQhn5Y/a7e3U2bgfnj4eFfRMf/C4ERs6tvMAYAAAAqgVJNhh4XF6dRo0apa9eu6tatm+bPn68rV64oKipKkjRy5Eg1atRI8fHxkqQXX3xRvXr10ty5czVgwACtWLFCu3fv1pIlSyRJJpNJ48aN05///Ge1atVKzZo109SpUxUQEKBBgwZJkoKDgxUREaGYmBgtXrxYubm5io2N1fDhwxUQEHDvB+EeIHUZzaTehWkzUAoakP9Alcvp0sVj0p73rT+zZ+uziwAAAAAqXKlC3rBhw3T+/HlNmzZNaWlp6tixoxISEiwPTjl16pScnH66WNi9e3ctX75cL7/8sl566SW1atVKa9euVdu2bS19/vjHP+rKlSsaM2aMsrKy1LNnTyUkJMjNzc3SZ9myZYqNjVXfvn3l5OSkwYMHa8GCBfd+ACM+lto+QqgrDqcaUrNf/vT9Q3/4KfQRjgEAAIBKw2QYhmHvIipaTk6OPD09lZ2dXcTn8wAAAACgcihujinVlbyq6nauvbf58gAAAADAfm7nl6Ku01XLkHfx4kVJUuPGje1cCQAAAADcm0uXLsnT0/Ouy6tlyPP29paU/5nBwgYHFS8nJ0eNGzfW6dOnuZW2kuG9qZx4Xyov3pvKi/em8uK9qZx4XyoPwzB06dKlIh84WS1D3u2HwXh6evKDWkkVPZ8h7IX3pnLifam8eG8qL96byov3pnLifakcinORqsTz5AEAAAAAKh9CHgAAAAA4kGoZ8lxdXTV9+nS5urrauxTcgfem8uK9qZx4Xyov3pvKi/em8uK9qZx4X6qeajlPHgAAAAA4qmp5JQ8AAAAAHBUhDwAAAAAcCCEPAAAAABwIIQ8AAAAAHEi1DHmLFi1SYGCg3NzcFBISop07d9q7pGolPj5eDzzwgNzd3eXj46NBgwYpNTXVqk/v3r1lMpmsXs8++6ydKq4+ZsyYUWDcg4KCLMuvX7+usWPHqn79+qpbt64GDx6s9PR0O1ZcfQQGBhZ4b0wmk8aOHSuJc6aifPnll3rssccUEBAgk8mktWvXWi03DEPTpk2Tv7+/atWqpbCwMB05csSqT2ZmpiIjI+Xh4SEvLy9FR0fr8uXLFXgUjqmw9yY3N1eTJk1Su3btVKdOHQUEBGjkyJE6e/as1TZsnWezZ8+u4CNxPEWdN6NHjy4w7hEREVZ9OG/KR1Hvja3fOyaTSXPmzLH04bypnKpdyFu5cqXi4uI0ffp07dmzRx06dFB4eLgyMjLsXVq1sXXrVo0dO1Y7duxQYmKicnNz9eijj+rKlStW/WJiYnTu3DnL67XXXrNTxdXL/fffbzXu27ZtsywbP368PvvsM61atUpbt27V2bNn9cQTT9ix2upj165dVu9LYmKiJGnIkCGWPpwz5e/KlSvq0KGDFi1aZHP5a6+9pgULFmjx4sVKTk5WnTp1FB4eruvXr1v6REZG6sCBA0pMTNT69ev15ZdfasyYMRV1CA6rsPfm6tWr2rNnj6ZOnao9e/ZozZo1Sk1N1cCBAwv0feWVV6zOo+eff74iyndoRZ03khQREWE17h999JHVcs6b8lHUe/Pz9+TcuXNaunSpTCaTBg8ebNWP86YSMqqZbt26GWPHjrV8n5eXZwQEBBjx8fF2rKp6y8jIMCQZW7dutbT16tXLePHFF+1XVDU1ffp0o0OHDjaXZWVlGTVr1jRWrVplaTt06JAhyUhKSqqgCnHbiy++aLRo0cIwm82GYXDO2IMk45NPPrF8bzabDT8/P2POnDmWtqysLMPV1dX46KOPDMMwjIMHDxqSjF27dln6/Oc//zFMJpNx5syZCqvd0d353tiyc+dOQ5Jx8uRJS1vTpk2NN954o3yLq+ZsvTejRo0yHn/88buuw3lTMYpz3jz++OPGww8/bNXGeVM5VasreTdv3lRKSorCwsIsbU5OTgoLC1NSUpIdK6vesrOzJUne3t5W7cuWLVODBg3Utm1bTZkyRVevXrVHedXOkSNHFBAQoObNmysyMlKnTp2SJKWkpCg3N9fq/AkKClKTJk04fyrYzZs39c9//lO/+93vZDKZLO2cM/Z1/PhxpaWlWZ0jnp6eCgkJsZwjSUlJ8vLyUteuXS19wsLC5OTkpOTk5AqvuTrLzs6WyWSSl5eXVfvs2bNVv359derUSXPmzNGtW7fsU2A1s2XLFvn4+Kh169b6/e9/r4sXL1qWcd5UDunp6fr3v/+t6OjoAss4byofZ3sXUJEuXLigvLw8+fr6WrX7+vrq8OHDdqqqejObzRo3bpx69Oihtm3bWtp/85vfqGnTpgoICNC+ffs0adIkpaamas2aNXas1vGFhITo/fffV+vWrXXu3DnNnDlTv/zlL7V//36lpaXJxcWlwB9Evr6+SktLs0/B1dTatWuVlZWl0aNHW9o4Z+zv9nlg63fM7WVpaWny8fGxWu7s7Cxvb2/Oowp0/fp1TZo0SSNGjJCHh4el/YUXXlDnzp3l7e2t7du3a8qUKTp37pzmzZtnx2odX0REhJ544gk1a9ZMx44d00svvaR+/fopKSlJNWrU4LypJD744AO5u7sX+JgG503lVK1CHiqfsWPHav/+/Vaf+5JkdZ99u3bt5O/vr759++rYsWNq0aJFRZdZbfTr18/ydfv27RUSEqKmTZvq448/Vq1atexYGX7u3XffVb9+/RQQEGBp45wBiic3N1dDhw6VYRh6++23rZbFxcVZvm7fvr1cXFz0zDPPKD4+Xq6urhVdarUxfPhwy9ft2rVT+/bt1aJFC23ZskV9+/a1Y2X4uaVLlyoyMlJubm5W7Zw3lVO1ul2zQYMGqlGjRoGnAaanp8vPz89OVVVfsbGxWr9+vTZv3qz77ruv0L4hISGSpKNHj1ZEafg/Xl5e+sUvfqGjR4/Kz89PN2/eVFZWllUfzp+KdfLkSW3YsEFPP/10of04Zyre7fOgsN8xfn5+BR70devWLWVmZnIeVYDbAe/kyZNKTEy0uopnS0hIiG7duqUTJ05UTIGQJDVv3lwNGjSw/PvFeWN/X331lVJTU4v83SNx3lQW1Srkubi4qEuXLtq4caOlzWw2a+PGjQoNDbVjZdWLYRiKjY3VJ598ok2bNqlZs2ZFrrN3715Jkr+/fzlXh5+7fPmyjh07Jn9/f3Xp0kU1a9a0On9SU1N16tQpzp8K9N5778nHx0cDBgwotB/nTMVr1qyZ/Pz8rM6RnJwcJScnW86R0NBQZWVlKSUlxdJn06ZNMpvNlmCO8nE74B05ckQbNmxQ/fr1i1xn7969cnJyKnCrIMrXDz/8oIsXL1r+/eK8sb93331XXbp0UYcOHYrsy3lTOVS72zXj4uI0atQode3aVd26ddP8+fN15coVRUVF2bu0amPs2LFavny5Pv30U7m7u1vup/f09FStWrV07NgxLV++XP3791f9+vW1b98+jR8/Xg899JDat29v5+od2x/+8Ac99thjatq0qc6ePavp06erRo0aGjFihDw9PRUdHa24uDh5e3vLw8NDzz//vEJDQ/Xggw/au/RqwWw267333tOoUaPk7PzTP9+cMxXn8uXLVldHjx8/rr1798rb21tNmjTRuHHj9Oc//1mtWrVSs2bNNHXqVAUEBGjQoEGSpODgYEVERCgmJkaLFy9Wbm6uYmNjNXz4cKvbb3HvCntv/P399eSTT2rPnj1av3698vLyLL97vL295eLioqSkJCUnJ6tPnz5yd3dXUlKSxo8fr6eeekr16tWz12E5hMLeG29vb82cOVODBw+Wn5+fjh07pj/+8Y9q2bKlwsPDJXHelKei/k2T8v9n1apVqzR37twC63PeVGL2frynPSxcuNBo0qSJ4eLiYnTr1s3YsWOHvUuqViTZfL333nuGYRjGqVOnjIceesjw9vY2XF1djZYtWxoTJ040srOz7Vt4NTBs2DDD39/fcHFxMRo1amQMGzbMOHr0qGX5tWvXjOeee86oV6+eUbt2bePXv/61ce7cOTtWXL188cUXhiQjNTXVqp1zpuJs3rzZ5r9fo0aNMgwjfxqFqVOnGr6+voarq6vRt2/fAu/XxYsXjREjRhh169Y1PDw8jKioKOPSpUt2OBrHUth7c/z48bv+7tm8ebNhGIaRkpJihISEGJ6enoabm5sRHBxs/PWvfzWuX79u3wNzAIW9N1evXjUeffRRo2HDhkbNmjWNpk2bGjExMUZaWprVNjhvykdR/6YZhmG88847Rq1atYysrKwC63PeVF4mwzCMck+SAAAAAIAKUa0+kwcAAAAAjo6QBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHALAwmUyaMWNGhewrISFBHTt2lJubm0wmk7Kysipkv/a2ZcsWmUwmbdmypUy3O3r0aAUGBpbpNu/Fzp075eLiopMnT9qtBlsCAwM1evToe17vxIkTMplMev/99y1tkydPVkhISNkVBwDlhJAHABXk/fffl8lksrycnZ3VqFEjjR49WmfOnLF3eTZt375dM2bMKPMAdvHiRQ0dOlS1atXSokWL9I9//EN16tQpdJ1jx47pmWeeUfPmzeXm5iYPDw/16NFDb775pq5du1am9VVWZ8+e1YwZM7R37157l1LAn/70J40YMUJNmza1tPXu3dvqZ97b21sPPPCAli5dKrPZXGb7Lq+f0zuNGzdO3377rdatW1eu+wGA0nK2dwEAUN288soratasma5fv64dO3bo/fff17Zt27R//365ubnZuzwr27dv18yZMzV69Gh5eXmV2XZ37dqlS5cuadasWQoLCyuy/7///W8NGTJErq6uGjlypNq2baubN29q27Ztmjhxog4cOKAlS5aUWX2V1dmzZzVz5kwFBgaqY8eOVsv+9re/lWlwuhd79+7Vhg0btH379gLL7rvvPsXHx0uSzp8/rw8//FDR0dH67rvvNHv27DLZf2E/p6mpqXJyKpv/p+3n56fHH39cr7/+ugYOHFgm2wSA8kDIA4AK1q9fP3Xt2lWS9PTTT6tBgwZ69dVXtW7dOg0dOtTO1VWMjIwMSSpWcDx+/LiGDx+upk2batOmTfL397csGzt2rI4ePap///vf5VVqlVGzZk277fu9995TkyZN9OCDDxZY5unpqaeeesry/TPPPKPWrVvrrbfe0qxZs0pV95UrV4q8Auzq6lri7dsydOhQDRkyRN9//72aN29eptsGgLLC7ZoAYGe//OUvJeXfjvhzhw8f1pNPPilvb2+5ubmpa9euBW4Ty83N1cyZM9WqVSu5ubmpfv366tmzpxITEy19evfurd69exfYb1Gf4ZoxY4YmTpwoSWrWrJnllrsTJ04UejyrVq1Sly5dVKtWLTVo0EBPPfWU1e2ovXv31qhRoyRJDzzwgEwmU6GfmXrttdd0+fJlvfvuu1YB77aWLVvqxRdftHx/69YtzZo1Sy1atJCrq6sCAwP10ksv6caNG1brBQYG6le/+pW2bdumbt26yc3NTc2bN9eHH35o6bN7926ZTCZ98MEHBfb7xRdfyGQyaf369Za2b775Rv369ZOHh4fq1q2rvn37aseOHYWO1+1abI3Bz9+7LVu26IEHHpAkRUVFWd6P258Zs/V+XrlyRRMmTFDjxo3l6uqq1q1b6/XXX5dhGFb9TCaTYmNjtXbtWrVt21aurq66//77lZCQUGTtkrR27Vo9/PDDMplMRfatXbu2HnzwQV25ckXnz5/XyZMn9dxzz6l169aqVauW6tevryFDhhT4Obt9u/PWrVv13HPPycfHR/fdd1+RP6d3jm1mZqb+8Ic/qF27dqpbt648PDzUr18/ffvtt8U61ttXnj/99NNi9QcAe+BKHgDY2e0/RuvVq2dpO3DggHr06KFGjRpp8uTJqlOnjj7++GMNGjRI//rXv/TrX/9aUn4Qi4+P19NPP61u3bopJydHu3fv1p49e/TII4+Uqq4nnnhC3333nT766CO98cYbatCggSSpYcOGd13n/fffV1RUlB544AHFx8crPT1db775pr7++mt988038vLy0p/+9Ce1bt1aS5Yssdy62qJFi7tu87PPPlPz5s3VvXv3YtX99NNP64MPPtCTTz6pCRMmKDk5WfHx8Tp06JA++eQTq75Hjx7Vk08+qejoaI0aNUpLly7V6NGj1aVLF91///3q2rWrmjdvro8//tgSTG9buXKl6tWrp/DwcEn579kvf/lLeXh46I9//KNq1qypd955R71799bWrVtL/cCO4OBgvfLKK5o2bZrGjBlj+Z8DdxsXwzA0cOBAbd68WdHR0erYsaO++OILTZw4UWfOnNEbb7xh1X/btm1as2aNnnvuObm7u2vBggUaPHiwTp06pfr169+1rjNnzujUqVPq3LlzsY/l+++/V40aNeTl5aXPP/9c27dv1/Dhw3XffffpxIkTevvtt9W7d28dPHhQtWvXtlr3ueeeU8OGDTVt2jRduXJF/fr1u6ef0++//15r167VkCFD1KxZM6Wnp+udd95Rr169dPDgQQUEBBRau6enp1q0aKGvv/5a48ePL/YxA0CFMgAAFeK9994zJBkbNmwwzp8/b5w+fdpYvXq10bBhQ8PV1dU4ffq0pW/fvn2Ndu3aGdevX7e0mc1mo3v37karVq0sbR06dDAGDBhQ6H579epl9OrVq0D7qFGjjKZNm1q1STKmT59u+X7OnDmGJOP48eNFHt/NmzcNHx8fo23btsa1a9cs7evXrzckGdOmTbO03R6LXbt2FbrN7OxsQ5Lx+OOPF7l/wzCMvXv3GpKMp59+2qr9D3/4gyHJ2LRpk6WtadOmhiTjyy+/tLRlZGQYrq6uxoQJEyxtU6ZMMWrWrGlkZmZa2m7cuGF4eXkZv/vd7yxtgwYNMlxcXIxjx45Z2s6ePWu4u7sbDz30kKVt8+bNhiRj8+bNVrWMGjWqwPHc+d7t2rXLkGS89957Bfre+X6uXbvWkGT8+c9/tur35JNPGiaTyTh69KilTZLh4uJi1fbtt98akoyFCxcW2NfPbdiwwZBkfPbZZzbrDwoKMs6fP2+cP3/eOHTokPHCCy8YkozHHnvMMAzDuHr1aoH1kpKSDEnGhx9+aGm7/TPTs2dP49atW1b9C/s5vXNsr1+/buTl5Vn1OX78uOHq6mq88sorVm13G+tHH33UCA4OtjkeAFAZcLsmAFSwsLAwNWzYUI0bN9aTTz6pOnXqaN26dbrvvvsk5d9OtmnTJg0dOlSXLl3ShQsXdOHCBV28eFHh4eE6cuSI5fZHLy8vHThwQEeOHLHnIUnKv7UxIyNDzz33nNUDZAYMGKCgoKASfW4uJydHkuTu7l6s/p9//rkkKS4uzqp9woQJklSghjZt2liuiEn5V39at26t77//3tI2bNgw5ebmas2aNZa2//73v8rKytKwYcMkSXl5efrvf/+rQYMGWX1Oy9/fX7/5zW+0bds2y7FUlM8//1w1atTQCy+8YNU+YcIEGYah//znP1btYWFhVldU27dvLw8PD6uxsOXixYuSrK9E/9zhw4fVsGFDNWzYUMHBwVq4cKEGDBigpUuXSpJq1apl6Zubm6uLFy+qZcuW8vLy0p49ewpsLyYmRjVq1Ci0psK4urpaHsSSl5enixcvqm7dumrdurXN/dlSr149XbhwocQ1AEB5I+QBQAVbtGiREhMTtXr1avXv318XLlywejjE0aNHZRiGpk6davnj+PZr+vTpkn56cMkrr7yirKws/eIXv1C7du00ceJE7du3zy7HdXt+tNatWxdYFhQUVKL50zw8PCRJly5dKnYNTk5OatmypVW7n5+fvLy8CtTQpEmTAtuoV6+efvzxR8v3HTp0UFBQkFauXGlpW7lypRo0aKCHH35YUv5TI69evWrz2IODg2U2m3X69OliHUNZOXnypAICAgoE5ODgYMvynyvOWBTGuONzfrcFBgYqMTFRGzZs0LZt25SWlqb169dbbqu8du2apk2bZvncYIMGDdSwYUNlZWUpOzu7wPaaNWtWrHruxmw264033lCrVq2s9rdv3z6b+7PFMIxiff4QAOyFz+QBQAXr1q2b5emagwYNUs+ePfWb3/xGqampqlu3ruUx+H/4wx8sn/e60+0Q89BDD+nYsWP69NNP9d///ld///vf9cYbb2jx4sV6+umnJeU/VMPWH+B5eXnlcXhlysPDQwEBAdq/f/89rVfcP8DvdkXozvEaNmyY/vKXv+jChQtyd3fXunXrNGLECDk7l82v0bvVm5eXV6qrVveiuGNxp9uf17tbGKxTp06h02Q8//zzeu+99zRu3DiFhobK09NTJpNJw4cPtzklxM+v/JXEX//6V02dOlW/+93vNGvWLHl7e8vJyUnjxo0r9hQUP/74oyWkAkBlRMgDADuqUaOG4uPj1adPH7311luaPHmy5Xa/mjVrFmsOOW9vb0VFRSkqKkqXL1/WQw89pBkzZlhCXr169WzeclecK2v3crXi9iTYqamplitct6WmplpNkn0vfvWrX2nJkiVKSkpSaGhokTWYzWYdOXLEcsVKktLT05WVlVXiGoYNG6aZM2fqX//6l3x9fZWTk6Phw4dbljds2FC1a9dWampqgXUPHz4sJycnNW7c+K7br1evns2JvE+ePGl1++e9vh8bNmzQpUuXrK7mHT582LK8LAQFBUnKn+qiJFavXq1Ro0Zp7ty5lrbr16/f08Tm9zIuq1evVp8+ffTuu+9atWdlZRU7uB0/flwdOnQo9j4BoKJxuyYA2Fnv3r3VrVs3zZ8/X9evX5ePj4969+6td955R+fOnSvQ//z585avb38e6ra6deuqZcuWVtMFtGjRQocPH7Za79tvv9XXX39dZG235yArzh/cXbt2lY+PjxYvXmy1///85z86dOiQBgwYUOQ2bPnjH/+oOnXq6Omnn1Z6enqB5ceOHdObb74pSerfv78kaf78+VZ95s2bJ0klriE4OFjt2rXTypUrtXLlSvn7++uhhx6yLK9Ro4YeffRRffrpp1aP/k9PT9fy5cvVs2dPy62ntrRo0UI7duzQzZs3LW3r168vcIvnvbwf/fv3V15ent566y2r9jfeeEMmk0n9+vUrchvF0ahRIzVu3Fi7d+8u0fo1atQocLVw4cKF93Sl+V7Gxdb+Vq1aZTXNR2Gys7N17NixYj/tFQDsgSt5AFAJTJw4UUOGDNH777+vZ599VosWLVLPnj3Vrl07xcTEqHnz5kpPT1dSUpJ++OEHy5xebdq0Ue/evdWlSxd5e3tr9+7dWr16tWJjYy3b/t3vfqd58+YpPDxc0dHRysjI0OLFi3X//fcX+TCQLl26SJL+9Kc/afjw4apZs6Yee+wxmxNQ16xZU6+++qqioqLUq1cvjRgxwjKFQmBgYIkfN9+iRQstX75cw4YNU3BwsEaOHKm2bdvq5s2b2r59u1atWmWZB61Dhw4aNWqUlixZoqysLPXq1Us7d+7UBx98oEGDBqlPnz4lqkHKv5o3bdo0ubm5KTo62vLwjtv+/Oc/KzExUT179tRzzz0nZ2dnvfPOO7px44Zee+21Qrf99NNPa/Xq1YqIiNDQoUN17Ngx/fOf/ywwtUSLFi3k5eWlxYsXy93dXXXq1FFISIjNz6k99thj6tOnj/70pz/pxIkT6tChg/773//q008/1bhx4wqdtuJePf744/rkk09K9Fm1X/3qV/rHP/4hT09PtWnTRklJSdqwYUOh0zbc6V5+Tn/1q1/plVdeUVRUlLp3767//e9/WrZsWbEnNt+wYYMMw9Djjz9e7PoAoMLZ6ameAFDtFDZtQF5entGiRQujRYsWlsfDHzt2zBg5cqTh5+dn1KxZ02jUqJHxq1/9yli9erVlvT//+c9Gt27dDC8vL6NWrVpGUFCQ8Ze//MW4efOm1fb/+c9/Gs2bNzdcXFyMjh07Gl988UWxplAwDMOYNWuW0ahRI8PJyalY0ymsXLnS6NSpk+Hq6mp4e3sbkZGRxg8//FDssbib7777zoiJiTECAwMNFxcXw93d3ejRo4excOFCq6kmcnNzjZkzZxrNmjUzatasaTRu3NiYMmWKVR/DyH+0vq3pJ+425cSRI0cMSYYkY9u2bTZr3LNnjxEeHm7UrVvXqF27ttGnTx9j+/btVn1sTaFgGIYxd+5co1GjRoarq6vRo0cPY/fu3TZr+fTTT402bdoYzs7OVo/4t/V+Xrp0yRg/frwREBBg1KxZ02jVqpUxZ84cw2w2W/WTZIwdO7bA8dxtagdbxy3J+Oqrr6zae/XqZdx///2Frvvjjz8aUVFRRoMGDYy6desa4eHhxuHDhwvsu6ifmbv9nNqaQmHChAmGv7+/UatWLaNHjx5GUlJSgbG+2xQKw4YNM3r27FnkmACAPZkMo4hPVAMAABShb9++CggI0D/+8Q97l1Ju0tLS1KxZM61YsYIreQAqNUIeAAAoteTkZP3yl7/UkSNHyuyhLpXN5MmTtWnTJu3cudPepQBAoQh5AAAAAOBAeLomAAAAADgQQh4AAAAAOJByC3mZmZmKjIyUh4eHvLy8FB0drcuXLxe6Tu/evWUymaxezz77bIF+77//vtq3by83Nzf5+Pho7Nix5XUYAAAAAFCllNs8eZGRkTp37pwSExOVm5urqKgojRkzRsuXLy90vZiYGL3yyiuW72vXrm21fN68eZo7d67mzJmjkJAQXblyxWriWQAAAACozsrlwSuHDh1SmzZttGvXLnXt2lWSlJCQoP79++uHH35QQECAzfV69+6tjh07av78+TaX//jjj2rUqJE+++wz9e3bt8T1mc1mnT17Vu7u7vc8aSsAAAAA2INhGLp06ZICAgLk5HT3mzLL5UpeUlKSvLy8LAFPksLCwuTk5KTk5GT9+te/vuu6y5Yt0z//+U/5+fnpscce09SpUy1X8xITE2U2m3XmzBkFBwfr0qVL6t69u+bOnavGjRsXu76zZ8/eU38AAAAAqCxOnz6t++67767LyyXkpaWlycfHx3pHzs7y9vZWWlraXdf7zW9+o6ZNmyogIED79u3TpEmTlJqaqjVr1kiSvv/+e5nNZv31r3/Vm2++KU9PT7388st65JFHtG/fPrm4uNjc7o0bN3Tjxg3L97cvXp4+fVoeHh6lPVwAAAAAKHc5OTlq3Lix3N3dC+13TyFv8uTJevXVVwvtc+jQoXvZpJUxY8ZYvm7Xrp38/f3Vt29fHTt2TC1atJDZbFZubq4WLFigRx99VJL00Ucfyc/PT5s3b1Z4eLjN7cbHx2vmzJkF2j08PAh5AAAAAKqUoj5ydk8hb8KECRo9enShfZo3by4/Pz9lZGRYtd+6dUuZmZny8/Mr9v5CQkIkSUePHlWLFi3k7+8vSWrTpo2lT8OGDdWgQQOdOnXqrtuZMmWK4uLiLN/fTsAAAAAA4GjuKeQ1bNhQDRs2LLJfaGiosrKylJKSoi5dukiSNm3aJLPZbAluxbF3715JsoS7Hj16SJJSU1Mt96BmZmbqwoULatq06V234+rqKldX12LvFwAAAACqqnJ5uqYk9evXT+np6Vq8eLFlCoWuXbtaplA4c+aM+vbtqw8//FDdunXTsWPHtHz5cvXv31/169fXvn37NH78eN13333aunWrZbuDBg3S0aNHtWTJEnl4eGjKlCn6/vvvtXfvXtWsWbNYteXk5MjT01PZ2dncrgkAAACgSihujim3ydCXLVumoKAg9e3bV/3791fPnj21ZMkSy/Lc3Fylpqbq6tWrkiQXFxdt2LBBjz76qIKCgjRhwgQNHjxYn332mdV2P/zwQ4WEhGjAgAHq1auXatasqYSEhGIHPAAAAABwZOV2Ja8y40oeAAAAgKrG7lfyAAAAAAAVj5AHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6EkAcAAAAADoSQBwAAAAAOhJAHAAAAAA6k3EJeZmamIiMj5eHhIS8vL0VHR+vy5cuFrtO7d2+ZTCar17PPPmvVZ9euXerbt6+8vLxUr149hYeH69tvvy2vwwAAAACAKqXcQl5kZKQOHDigxMRErV+/Xl9++aXGjBlT5HoxMTE6d+6c5fXaa69Zll2+fFkRERFq0qSJkpOTtW3bNrm7uys8PFy5ubnldSgAAAAAUGU4l8dGDx06pISEBO3atUtdu3aVJC1cuFD9+/fX66+/roCAgLuuW7t2bfn5+dlcdvjwYWVmZuqVV15R48aNJUnTp09X+/btdfLkSbVs2bLsDwYAAAAAqpByuZKXlJQkLy8vS8CTpLCwMDk5OSk5ObnQdZctW6YGDRqobdu2mjJliq5evWpZ1rp1a9WvX1/vvvuubt68qWvXrundd99VcHCwAgMD77rNGzduKCcnx+oFAAAAAI6oXK7kpaWlycfHx3pHzs7y9vZWWlraXdf7zW9+o6ZNmyogIED79u3TpEmTlJqaqjVr1kiS3N3dtWXLFg0aNEizZs2SJLVq1UpffPGFnJ3vfijx8fGaOXNmGRwZAAAAAFRu93Qlb/LkyQUejHLn6/DhwyUuZsyYMQoPD1e7du0UGRmpDz/8UJ988omOHTsmSbp27Zqio6PVo0cP7dixQ19//bXatm2rAQMG6Nq1a3fd7pQpU5SdnW15nT59usQ1AgAAAEBldk9X8iZMmKDRo0cX2qd58+by8/NTRkaGVfutW7eUmZl518/b2RISEiJJOnr0qFq0aKHly5frxIkTSkpKkpNTfj5dvny56tWrp08//VTDhw+3uR1XV1e5uroWe78AAAAAUFXdU8hr2LChGjZsWGS/0NBQZWVlKSUlRV26dJEkbdq0SWaz2RLcimPv3r2SJH9/f0nS1atX5eTkJJPJZOlz+3uz2XwPRwIAAAAAjqlcHrwSHBysiIgIxcTEaOfOnfr6668VGxur4cOHW56seebMGQUFBWnnzp2SpGPHjmnWrFlKSUnRiRMntG7dOo0cOVIPPfSQ2rdvL0l65JFH9OOPP2rs2LE6dOiQDhw4oKioKDk7O6tPnz7lcSgAAAAAUKWU2zx5y5YtU1BQkPr27av+/furZ8+eWrJkiWV5bm6uUlNTLU/PdHFx0YYNG/Too48qKChIEyZM0ODBg/XZZ59Z1gkKCtJnn32mffv2KTQ0VL/85S919uxZJSQkWK72AQAAAEB1ZjIMw7B3ERUtJydHnp6eys7OloeHh73LAQAAAIAiFTfHlNuVPAAAAABAxSPkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAMh5AEAAACAAyHkAQAAAIADIeQBAAAAgAM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