{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" }, "colab": { "name": "Exercise_08_2.ipynb", "provenance": [], "include_colab_link": true }, "accelerator": "GPU" }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "id": "zhevd7m4MEoT" }, "source": [ "# Air-shower reconstruction using a convolutional neural network\n", "## Cosmic-ray observatory\n", "In this example, we will train a neural network to reconstruct air-shower properties measured by a hypothetic cosmic-ray observatory located at a height of 1400 m. The observatory features a cartesian array of 14 x 14 particle detectors with a distance of 750 m. \n", "Thus, the measured data contain the simulated detector responses from secondary particles of the cosmic-ray induced air shower that interact with the ground-based observatory. \n", "\n", "Each particle detector measures two quantities that are stored in the form of a cartesian image (2D array with 14 x 14 pixels)\n", "- arrival time `T`: arrival time of the first particles\n", "- signal `S`: integrated signal\n", "\n", "In this task, we are interested in reconstructing the cosmic-ray energy in EeV (exaelectronvolt = $10^{18}~\\mathrm{eV}$) using the measured particle footprint and a convolutional neural network.\n", "\n", "\n", "# Preparation:\n", "**Enable a GPU for this task.** \n", "Therefore, click:\n", "*Edit* -> *Notebook settings* -> *select GPU* as *Hardware accelerator*\n", "\n", "# References\n", "The tutorial is inspired by the simulation and the study performed in https://doi.org/10.1016/j.astropartphys.2017.10.006. \n" ] }, { "cell_type": "code", "metadata": { "id": "dc1W4fDQMEoZ", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "f3e0cc67-a420-4ed1-c5e3-89039857c30d" }, "source": [ "import tensorflow as tf\n", "from tensorflow import keras\n", "import numpy as np\n", "import seaborn as sns\n", "from matplotlib import pyplot as plt\n", "\n", "layers = keras.layers\n", "\n", "print(\"tf\", tf.__version__)\n" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "keras 2.6.0\n", "tf 2.6.0\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "qlKbYg4eMEod" }, "source": [ "---\n", "# Data\n", "### Download data\n", "As a first step, we have to download the simulated air shower data." ] }, { "cell_type": "code", "metadata": { "id": "afCf7h-HMEoe" }, "source": [ "import os\n", "import gdown\n", "url = \"https://drive.google.com/u/0/uc?export=download&confirm=HgGH&id=19gOSVQ0mhdjMkm5i2u5NsGrWNBdlhR4F\"\n", "output = 'airshowers_mnist.npz'\n", "\n", "if os.path.exists(output) == False:\n", " gdown.download(url, output, quiet=False)\n", "\n", "f = np.load(output)" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "lpTcoB3xMEof" }, "source": [ "### Input 1: Arrival times\n", "Our first input is the arrival times of the first shower particles, measured at the various stations. We normalize the arrival times with respect to the mean and the standard deviation of the arrival time distribution. \n", "Remember that each input has the shape of 14 x 14, as each station measures a specific arrival time.\n" ] }, { "cell_type": "code", "metadata": { "id": "Im1FDnqBMEog", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "f187a008-b149-40a7-cfa7-b654fee88b2e" }, "source": [ "# time map\n", "T = f['time']\n", "T -= np.nanmean(T)\n", "T /= np.nanstd(T)\n", "T[np.isnan(T)] = 0\n", "\n", "print(T.shape)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(100000, 14, 14)\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "3p35M05lMEoh" }, "source": [ "#### Plot four example maps\n", "To visualize a map of arrival times, we can plot a random example event. Here, the dark blue indicates an early trigger and a bright yellow a late trigger. \n", "With this information, one can directly get an impression of the shower axis (arrival direction) of the arriving particle shower." ] }, { "cell_type": "code", "metadata": { "id": "FRw8E9H7MEoi", "colab": { "base_uri": "https://localhost:8080/", "height": 513 }, "outputId": "15ee1d8d-ff1c-4d3c-e2cd-136218c12cc9" }, "source": [ "nsamples=len(T)\n", "random_samples = np.random.choice(nsamples, 4)\n", "\n", "def rectangular_array(n=14):\n", " \"\"\" Return x,y coordinates for rectangular array with n^2 stations. \"\"\"\n", " n0 = (n - 1) / 2\n", " return (np.mgrid[0:n, 0:n].astype(float) - n0)\n", "\n", "plt.figure(figsize=(9,7))\n", "\n", "for i,j in enumerate(random_samples):\n", " plt.subplot(2,2,i+1)\n", " footprint=T[j,...]\n", " xd, yd = rectangular_array()\n", " mask = footprint != 0\n", " mask[5, 5] = True\n", " marker_size = 50 * footprint[mask]\n", " plot = plt.scatter(xd, yd, c='grey', s=10, alpha=0.3, label=\"silent\")\n", " circles = plt.scatter(xd[mask], yd[mask], c=footprint[mask], \n", " cmap=\"viridis\", alpha=1, label=\"loud\",\n", " edgecolors=\"k\", linewidths=0.3)\n", " cbar = plt.colorbar(circles)\n", " cbar.set_label('normalized time [a.u.]')\n", " plt.xlabel(\"x / km\")\n", " plt.ylabel(\"y / km\")\n", " plt.grid(True)\n", "\n", "plt.tight_layout()\n", "plt.show()" ], "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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r4r64a41lM/jYS/l+bj8mFL+NEKRrz+M57Sz71cxxvgetzvvs+l6ravgZDIb4USDs4gmcRaR3Q+mqurylYzG4n/z8fK76/R9SHYYjGbDPIAbsMyjVYSQNN3tfIr5nGn4GQ5qjQDDs6tsdk4l8DSGyEsZOwAJgz1QGZTAYnI3Lva/JvmcafgaDwdW3O1R17+j3IrI/8H8pCsdgMLgIt3pfIr5nGn4GQ5pTO6VBa0FVvxGRg1Mdh8FgcDatyfvi8T3T8DMYDK4d5wIgIrdHvfUA+wO/pigcg8HgItzqfYn4nmn4GQxpjqqrx7kA5EW9DhIZ+/J2imIxGAwuweXe12TfMw0/g8Hg6tsdqmpvsVCDwWDYAbd6XyK+Zxp+BkOa05rGudQiIkNV9cVUx2FwH6rKx58XM3/ZAgbsvCdHHXx4vWXcGuOrb7/mq5/msHO3Ppw4eIht3U+LfmTGN9Pp3K4bpx5/Bj6fvX/NK1et4IPPJtA+qzuVlZVkZ2fb0hkitDbvs+t7puFnMBjQVmR+NbS6L2Rofqqrq7n5yTtZ3HczmT3bMmnZ14z7fBJP3PywZWNMVbnnub/yfcefyerTlmkbZzHusUkMu+lx2rRpY5nnsDf+xXxfMe2Lsigpr+aDp//HfRf9i25drFffGvPuCGaXv0HhvkLOL+dyz8vnc/XvHqKon5nFKB5amffZ+jKuvbndEH6/nzVr1sS9kLNbdLXaYDDo+FhToXNDuaQqTytUW99avar6QqpjaEncVE+dXL9fmTCanwdsJbNLWwAyC9uyaI9yXn93jKXuveJpzOu5jKzeNbpOOZQOCjPsv9an4Q8LfmB+VjHtd88CIKtdBnnHVPLyu09b6kpLS/l64xi67+dBRPB4hJ7HbGXcJ8NsfU9w12/fHL4H9r3PLdj1vVbT4+f3+ykpKUFEUFXb6xa6RRetDQQClJSUODbWVOmcXi6pytMOybrqFZEhwJOAFxiuqo/s8PnlwD+BVTVJw1R1eBLyPZnIxKW/3etS1QcTPa4bcFs9dXL9Xrh5Gd6uGXXSfG0y+XHVEkvdNyvmkblrTp00j8/D0i3Wiyh8+t102hdl1UkTEdZWL7PUfTDjXbrtH2LHvpuNoaWWulrc9ts3l++Bu3v8mup77mnKxsDv9yMi5OXlISK2rw7coovWer1eR8eaKp3TyyVVecYmMs7FzmZ5FBEv8AxwIrAHcIGI7NHArmNUdd+aLRmNvueB3wM3EbnVcS7QJ9HjugW31VMn1+82nqwG09t6rMfO5fpy0LDWS88MWvetdMwtILA1WC/dG2w4jlp6dd+JinWh+rpQTgN718dtv33z+B7Y9T4nkojvtZqGX25uLqpKRUUFqmr7qsAtumhtKBRydKyp0jm9XFKVpx1UxdYWg4OAxaq6VFUDwFvA6UkNtGEOVdVLgdKaJ90GAf1bIF9H4LZ66uT6fd7hp6MlFXUT55Vz/lFnWuouPuF8ZM7WOmmVC8o5Zb8TLHWnH382276s21grX1bFIX2OsdQdMvAwqub3JhzV2PRvqGa39kda6mpx22/fXL4H9rzPoTTZ91rNrd7c3FyKiorw+/3k5ubGdWK5QRetLSsri6vL2y3fMVGd08slVXnGQhVC4aSYWw9gRdT7lUBDM8mfLSJHAguB21R1RQP7xMO2mr9bRaQ7sBEoTPCYrsFt9dTJ9Xuv3fbgni1Dee3Tt1kf3EwXXwcuO/IG+u/cz1JX0KmAvw65g5HFb7Cqai1twzmcttf5/O6I4yx1mZmZ3H3uo4yc9hxrAr+QEcrmqD5n8PtTLrLUiQh3XvYkL0/4J2sCP9Glg5ee5Wdz+QU3xPyO4L7fvjl8D5Lqfamgyb7Xahp+QJNPDLfoarU+ny9uvVu+YyI6N5RLqvKMRRyz1xeIyOyo9y/GOW3KJOBNVa0SkWuBVwHr7o3YvCsi7YmMHfyGyMLlLyV4TFfhpnrq9Pp92P6DOGz/QXFpAPbabU8e3+2huHW9evTm3iv/Ebeuffv2/OHySH7FxcUMHjw4Lr2bfvvm8j1w78odJOB7KWv4iUgvYBTQlUjAL6rqk6mKx2BIV5S4BjhvUNWBjXy2CugV9b4n2x/iiOSlujHq7XDgMbsZN4aq/q3m5dsi8i6QrapliR63uTDeZzA4gzi9z1Ek4nupHOMXBP6gqnsAhwA3NDIQ3GAwNCvJebgD+BroJyI7iUgmcD4wsU5OItG3Ik4DSpoctcj+O6apalW0+TW0jwMw3mcwOAL3PdyRDN9LWY+fqq4GVte8rhCREiJjhH5MVUwGQ7oSTsI4F1UNisiNwDQi07mMUNUfRORBYLaqTgRuFpHTiDR+NgGXJ5DlKyIyGOtJS18G9ksgj6RjvM9gcA7J8L4WJmHfc8QYPxHpSyTIWQ18NhQYCtC1a1eKi4tbMjQg8kh5KvJtDCfFY2JpGCfFEgvV5N3uUNUpwJQd0u6Len0XcFdSMoN8YA7WBrg+SXk1C8b77OOkWMBZ8ZhYmkYyva8FSdj3Ut7wE5Fc4G3gVlUt3/HzmoHjLwIMHDhQ4x3AmgyaMnC2OXFSPCaWhnFSLHZw2u0MO6hq31THkAjG++LDSbGAs+IxsTQdt3lfMnwvpQ0/EckgYnyvq+r4VMZiMKQzWn/uWUMzYrzPYHAG6eh9KXu4Q0SEyH3oElX9d6riMBjSHUUIhz22NkPiGO9rOfx+P0uXLiUYrL86hhWVlZUsXbqUqqqquHTV1dUsXbqULVu2xKULh8P8/PPPlJfX6/i1RFVZvnw5oVD9VTwMsbHrfa2NVPb4HQZcAswTke9q0u6uGSNkMBhakDS86E0lxvuaGVXl3ueeYfLypWzM8NI3BNceegQXnXJaTO2/R7/KmJK5/JrpoUcgzIV77sfNF14SUzfq3fGMmFvMqrZKx63Kyd12594rbiDSzm+cKTM/4pnP32F5uwC5W+Gw7D48et0deL1eS93Xc2fz7MfDWddxM2e2OYHbn76Tv191H23atIkZq2E76eh9KWvKquqnqiqqOiBq3c6EjM/v97NmzZq41/Nzi65WGwwGHR9rKnRuKJdU5WmJJm3JtpQgES4Wkftq3vcWkYNSHVdjGO9r/vr93FtvMHprKaW9u+Mp7Mrynl156MuZLFi82FI38cMPGbZqEWv7FuLt3pU1fQt5avlPvD9zhqVu7o/zeXzxJ6wpKsDbuzNlu3fhdc8qRkwYa6nbuHEjD3/xX1bv3Y6MPgVUFRXwYeFm/jn6BUtddXU1//roGbYeDLn92uPJ8bJiv008/No/LXXRuOm3bxbfA9ve50QS8b2UP9yRLPx+PyUlJYgIqmp7aR+36KK1gUCAkpISx8aaKp3TyyVVedrC3Ze9zwJhIiuAPAhUEBk/d2Aqg2op3FZPW6J+z/h5CbSv2/O1pbALb370AQ/sumujuqnzvyXcMb9OWrBTeyZ/+zW/O6LxdXDHfT6dQO9OddKkXQ7Tl8zjKn7fqO71999hS1HHOo9nerIz+HLJokY1AFM+nkrV3pAZrfN6+GmrdcO2Frf99s3me+Bm72uy77Wam9d+vx8RIS8vDxGxfXXgFl201uv1OjrWVOmcXi6pytMO4bDY2hzKwap6A1AJoKql1P2f2KpxWz1tqfq9I7FuuVrR1LZBU8fehcJhy89VtcHvEw7by89tv31z+R7Y8z6H0mTfazUNv9zcXFSViooKVDWuRaDdoIvWhkIhR8eaKp3TyyVVecaidtkit97yAKpFxEvN/2cR6UzkSjgtcFs9bYn6feROu6DbttVJy1m1hvOPPc5Sd8Je++ItrfuAhXdjKSfv29gqhRHOOfQYMldsqpOm5Vs5qneRpe6i351O259K66SFK6s5sENfS93Jx5xI1ry6zdFwKEy/7J0tdbW47bdvDt8D+97nUJrse63mVm9ubi5FRUX4/f64FnV2iy5aW1ZWFleXt1u+Y6I6p5dLqvKMiQLONTc7PAX8D+giIg8B5wB/SW1ILYfb6mlL1O/rz7+QVc8O491lS9iUmUGf6jDXHXYUu+/az1J3+nHHs2j1Kt4qmcvaLC+FVSEu2mt/TjjyKEvdPnvsxe1LjmDkvBmsaBumfXmQIQX9uO4y64dCOnXqxF0Hn80zX0xkWV4Vbf3KoMwe3H3jTZa6jIwMbjvmBp77eDhrO5YSbhOkcGEe9w21Nze62377ZvE9cLv3Ndn3Wk3DD2jyieEWXa3W5/PFrXfLd0xE54ZySVWesXDzXFaq+rqIzAGOJTKb/Rmq2uQ1gN2Im+ppS9RvEeGhG27iLr+ftWvX0qdPH3w+e//u/njJ5dxYWcmqVavo0aMH2dnZtnSXn3o2Fw05jeXLl9OtWzfatm1rS3fykcdx4uHH8Msvv9CpUyfy8/Nji4CD9hnIgQMOYNmyZSxZsoSrz7nSlq4WN/32zeV7kDzvE5EhwJNElqscrqqP7PD55cA/gVU1ScNUdXhT80vE91pVw89gMDQFQZ07jsUua4GZRDwtR0T2V9VvUhyTIcU0tdGQnZ3NLrvsErcuIyOjSTqPx8POO9u7TRuNiNC3b19++eWXuLUGSJb31dxyfQY4HlgJfC0iE1V1x/W3x6jqjQlnuJ0m+Z5p+BkMBjc/2YaI/A24HFjC9m+iRJ52MxgMhsZJjvcdBCxW1aUAIvIWcDqwY8MvaSTie6bhZzCkO+5cqDya84BdVDWQ6kAMBoOLsO99BSIyO+r9izVradfSA1gR9X4lcHADxzlbRI4EFgK3qeqKBvaxS5N9zzT8DAaDq3v8gPlAe2BdqgMxGAwuw573bVBV60e7YzMJeFNVq0TkWuBVErsr0WTfs93wE5F20fur6iaL3Q0Gg5twd4/fP4BvRWQ+8Nviqqoae30uGxjvMxhaMcnxvlVAr6j3Pdn+EEckG9WNUW+HA48lmGeTfS9mw6+mZfpXIpMERt9Hjn8kqsFgcCbu7vF7FXgUmEcS5+8z3mcwpAHJ8b6vgX4ishORBt/5wIXRO4hIoaqurnl7GpDozANN9j07PX5/BPZS1Q1NCMxgMDgdd89lBbBVVZ9qhuMa7zMYWjNJ8j5VDYrIjcA0ItO5jFDVH0TkQWC2qk4EbhaR04AgsInIgxmJ0GTfs9PwWwJsbcrBDelHVVUVD774ArPXrMGHcOROO/GnK6/E43HeIjHjxr3L5Hdn4a+oonef9txy66X07t0zpu7D9z5m3CtTKF1bQeFOnbj69ovYa8AeLRBx8+HmefyAmSLyD2AidW95JDqdi/E+F/PuB9N588OZbNpaRd9Oedx84TkU9beewBlg5qyvGD5lGqu3bKN7bhuuPfUkBh2wf0zd9yUlPDVhAr/4yynIyuayowZz4lHWEz8DLF+1ikfGvsaCilLa+zI5Z9+DuOCkU2PqysrKePC1F/jBv45zd9qPknGvc93ZF8Zcmi4QCPDQq8/wbdkKvOJhUOdd+ePFQx3p0S1BsrxPVacAU3ZIuy/q9V2AvRm27dFk37PT8LsL+FxEZu1w8JubEGiz4vf7mzTDt1t0tdpgMPib3mmx3vDYY3yUnYUUFADw4/p1lA0bxsM32ztdEokznnJ5++3JPDPsUzySD7Rh0ya49eZ/8tbYf5KZ2fhyhzOLP+dft4yCijaAl/KFm7lr3qOMmPo4nTt3th1rS583MXH3PH771fw9JCotGdO5GO9zkC6e+v3BJzO5b/x0AnmdIAdWbIWfHn+edx6/n3bt2jWqm/djCbe/NZ7yjl0hP5dlwI+jxjC6fT79Lebn27BxI9e+PJy1PXtATmeWAvPen0p2ZiZHDxrUqK66uporn/kni/sXQoeOAHxf8gUgXHDSKY3qVJWrnvw7c3fPRbrls83r4alN31P55khuu/AKy7K5ZdhDfLpTNZ7CyATTi7f9zOaX/s3D1/7RUleLW84Z27jX+5rse3aa+C8A04EvgTlRm6Pw+/2UlJSwcuVKSkpK4loE2g26aG0gEHBkrCtXreLTinIkaoZ8yc7m/V9+pqqqykKZnDjjKZcpU2bVNPq2s3FjB8aOnWipm/jGtJpG33aqV7Vl1AtvxRVrS543dhC1tzkRVT26gS0Zc/gZ73OQLp76/d/pn0YafVGsa1fIy2PfttSNem9apNEXRVlBN0ZOmtKIIt+q40IAACAASURBVMJL/xvPmu6FddK2de7Max9Pt9S9MXkiC3t1rJNW3Smfsd98Yamb+dWXfN8FJLqXLr8N7y6da6lbvXo1s2Qtngzvb2menEyKNy2isrLSUgvuOWfiIR19z06PX4aq3p5gjM2O3+9HRMjLy6OiosL2laFbdNFar9eLiDgu1pW/rmJrdna9k6oc2LJlC1lZWc0aZzzl4q+oAnLqpPl8WaxfV9qwoFa3eVu9NBFpMN0q1pY8b2KiJO3hDhvLFmUBo4ADgI3A71X1lybmdbGqjhaRBv1JVf/dlONGYbzPQbp46nd5ZTVQd6k18Xgp9Vs3bsqrAkBGvfSyKuup0jZXVtVthNVQus3aF9ZsLsWTU98XSwPWcS5duRzt0JYd+6rKqq11v65dzbY8Hzve0/BnKhUVFTGXp3PLOWObJHpfS5EM37PT4/eeiAwVkUIR6Vi7xR1tM5Obm4tq5ORV1bgWgXaDLlobCoUcGev+++xL7waMbtfMLDp06NDsccZTLn136ojuMLgjFNrAMcce0oiiRrdHd8Ja9wGqarax36A944q1Jc+b2EhkgLOdzeoo25ctOhHYA7hARHYc/HgVUKqquwL/IfJUWlOpXQw1r4EtGQVkvM9Bunjqd78uHdAd6qn6yzh8H+uxuHv1KCRcXbeRF66qYp9ePSx1g/r3h4qKuvmFw+zRqcBSd+JBg8j4te6zQ6rK7nnWp9lpRx9Pu6Ub66X3b9Opgb23M2DPvenRwKNKfQNtKCiwjhXcc87YJ3HfSwEJ+56dHr8Lav5GD0p03JQGubm5FBUVxT0WwC26aG1ZWRlFRUWOizUzM5ObjzmWhz/8gLLu3SEcpvOvv/Kn358fc8BxMuKMp1xuu+1ybrrxH6xb2w6fL4dgcANDTtqJffbZ21J30x1D+fHbP7Lqq0oyyKba52f/U/pw6lknxRVrS543tkjOJCh2li06HXig5vU4YJiIiO7YCreBqr5Q8/JDVf0s+jMROSze4zWA8T4H6eKp33+65jJ+uOfv/EQ7PDltkfKNDOndnuMHH2mpu+7C8/n6vgeZVemFvHwoL+PwTOXK886x1J1+/PF89O03TN1USqhjB9TvZ+/NZdz91wctdQP22JNLPtuZ0b8uJdC9gPDWSvot28h9t91tqevYsSPX9D+UZxZ/TuXOnUGVbvPWcNeF1svAZmRkcMNBp/Do7Als3a0TqNLuh43cdtylLeLRjvM9SOIEUC1DMnzPTsNvF93h0klErPuDU0RTTwy36Gq1Pp8vbn1LxXreiScyeOBA3pg8mcyMDC657nry8vJaJM54yqVbt668+dbjjB8/mdW/buC4489gzz2LYuratGnDyAnPMPmdqSxd8AsHHb4/hxzW0Mo81rG29HkTE/vNLquli+wsW/TbPjVTIJQBnYBEpkx5GtjxscuG0uLFeJ+DdPHU73bt2jHuyUd45733WbJyFUcdeDQH7r9vTF1GRgavPvwgH3wyg+8XL2G/wQdyzOGHxWwUiQhP//lOPp89m8/mzqXfHntx2nHH2XpS9r5rrufsn0qYMutzevTsxHlDT8Hni/2v+bqzL2DIisN4+5MP6Jabw/t3/SvmrVqAM48ZwuEDDuDN9yeS6cvgopvPbDGPdpzvgetu9UbRZN+z0/AbDlxZ+0ZE2hJ5fPjYOAJskFjjgQzupEvnztx6+eWpDiMmPp+P8847PW6diHDKGSc2Q0QpIr65rJKxdFFSEJFBwKFA5x3Gu7Qj4imJYrzPxXg8Hs48eUjcOhHhd4OP4neDY0/FsiOHDhzIoQPjrx577l7EnrvHvvDckb69evOHi6+iuLjYVqOvls4Fnbn5wqvizq/V4cI5TJPhe3bG+K0SkWdrMuwAfACMjjPWetgcD2QwGFqAJD3VG3PZouh9RMQH5BN5yKMpZBIZ0+Kj7jiXcsD63pw9jPcZDK0cFz7Vm7DvxezxU9V7ReQxEXmeyJN4j6iq9TPx9rAzHshgMLQELbRsEZEes8uAL4iY1PSmjO8DUNVPgE9EZKSqLmt62I0e33ifwdDacV7DzpJk+F6jDT8ROSvq7SzgXuArQEXkLFUd35QMo7AzHggRGQoMBejatSvFxcUJZhs/fr8/Jfk2hpPiMbE0jJNisUMyrmptLlv0MvCaiCwmsmzR+UnIN6mNPuN923HSeeykWMBZ8ZhYmo4De/RskYjvWfX47bhmzLdEJjg6lUgbOVHzs0XNwPEXAQYOHKiDBw9uiWzrUFxcTCrybQwnxWNiaRgnxWKLJI1zsbFsUSVwblIyaz6M99XgpPPYSbGAs+IxsSSAy8b4JYNGG36qar3uS+LYGQ9kMBiaG8V1Uxo0J8b7DIY0IU29z85Tvc2FnfFABoOhBXDj7Q4ReRqLETpOXFO3BuN9BoNDcJv3JcP3Utbwa2w8UKriaa0Eg0HGTHmLxaWLyaEN5x97Pr179o6pU1XGTXuXL1aUkIOPC44cwl672Xvw8L1PPmbavO/wCJxzyBEceoC96Q0+/+pr/jfjc0Kq/O6AfRlyzGBbuvk/lvDWpA/ZvXdXxk6YxLmnn2JrMtLly1cwatQEKiqq2KOoFxdfcg5eb+yn4Tds2MCIZ9+gdL2f3rt05YrrLoprKgVH4jLzq6F2PsHDiDwdO6bm/bk4+EEJ430tw5q1a3n5tfGUVlSya+/OXHnJeWRm7rhYWX0qKip4/tUxrN5UQY+Cdlx76e9tzSNXWVnJS2+MZcnajRS0zebaC86lc+fYq2GEQiFeHfc2c5evol1mBleeeRo79bbp0ZMn8+niRRzUvQff//gjA/aw59HTZnzCe99/gxfhrEMO47CBB9rStUrc530J+57Vwx2DgC+b+sSdHRoaD2RIHqrKHcP+xIb91pHZPQNV5e7Jd/KnI/7MPnvsY6n987OP8V779XgKI+vZfjT1Wf664VxOOMx6bqtHX32Z59ctJdwpH4DJ74/jrpUruPz0My11o96ewOOffE11fsQop078mPlLfuaP11jfdZs2/RP+OnIqlTld6FEIL0z9jm9+WMQj91gvsfrtt/O4+64RVFV1RkT48osf+XLWAzz77IOWjcYVy1dy80UPsG15LiLCHF3N5x9/w8v//Y+tfyqOxX3mh6q+CiAi1wOHq2qw5v3zwMymHtd4n/tZtGQpN/zlGco8hYh4mLFgFTO/uo9Xn/m75eTIpaWbueQPf+NXTyHi8aLLSyme8wBvPHG/5STH1dXVXPyn+yjxFuDxZaAbtvLxPY/wyr230rtXz0Z1qso19z/IDM3Gm52Nbgvw/uNP88xVlzBwnwGW3/GO//yHcVv8SG4u/VAuGjWKR4cM4aQY4+seH/UKz61eQqhjxKMnTRvPnSuXc+UZZ1vqWi0u875k+J7VPH6XAnNE5C0RuVxEuiUacHPj9/tZs2YNfr+/VepqtcFg0JZ2+ufTWdt/NZltI4uOiwjZB2Ty1mdvWuoWLlnMh7oCT37Ob2nbdunAK7Os/09VVFTw1uL5vzX6ACq7dmTknM8JhxsfSBEKhXjtky9+a/QBaF57/vvtj1TssP7ljoycMJ3KnC6/vfdk5/Lhj+tZuGixte6ViQQCXX5r5Pl82fz4Y4iPPpphqRv+9OtUrsj7TecVH2u+Fd4Y+V9LXTSpOG+sEAUJi63NoXQgMnlpLbk1aU3FeJ8DdXZ9D+ClURMo9/ZAJPIvzuPLYOHmPMaOf9dS99yrb/GrtzviifT8i8fLKunG86PGWOpGjfsfP0pHPL5ar/Wwrl0PnnljnKXuo5mf8mlA8NbcMRARNnfuzvMTJ1vqFv/8M++uW4tE9URu6dqFl6Z/ZKnz+/28uXDeb40+gECXjoya8yWhUMhSG30MN5wzdrDrfQ6lyb5n9XDH9QAisjuRiUZHikg+8DEwFfhMVe2dKS2A3++npKQEEUFVba/p6BZdtDYQCFBSUhJTW7L8R3L61b8FuT643jKfGXO+JNinPTue7iu2bbbUzSspYV1+Tr2TaiXVlJaW0qlTwwuIb9q0idWB+qfSRl8O80tKGHTQQY3muWpjBeS2r5MWatuZGV98Rf9+uzaqW7OmHKir83nz+P77RRx3XOO9mutW1C8DnyeDXxb92qgmmlScN7Zw2VXvDjwCfCsiHwMCHMn29YDjxnifM3V2fQ/g1w0VROa03Y43I4eFP1s/Q7NqYwWRecW3Ix4vK9ZZe9/iVevwZmbVS1+2wVr3zYKFSF5+vfTlpeWWuuJZs6js3LmeRy8rt9b9uOAn1uZmN+DRQTZu3EiXLl0a1NXilnMmLtzrfU32vZgrd6jqT6r6H1UdAhwDfErkXvKsJofbDPj9fkSEvLxIb4zdqwO36KK1Xq/XlnbnbrtQubGqXnrb6jaWuoMH7Id3ZVm99E4xlindo39/OpZvq5deUK20b9++AUWEDh060NlX/6qqXWUFRf37W+bZtUPbemniX8chB+xnqSsoqG8e1dV++vfvY6nrWFj/dk9IgxT2jj2WB1Jz3tghSSt3pARVfYXIPHj/IzLVyqDa2yEJHtd4n4N0dn0PoEuH+h4Xqq6iT4/O1rr8Nux4h181TLcO1o2N3p07EK4O1EvvkGU9ZniPnfqgW+rf1eiYZT38/tD99iVzQ/0FbzrHGG6y2679KPBX1ksvCITp2LGjpRbcc87EQzr6np0l26Iz2qaqU1T1Jqes11lLbm4uqkpFRQWqavuqwC26aG0oFLKlPXHwieTP60CoenvnRPkcP2cdaD2WY+/d9+TwygLCW7c3GuXnjVywz9GWuvbt23Nmj12gYstvaZ4Npfx+j30tH5rw+Xyce8j+eP3br47DWyo4cbe+lg1GgAtPPBzf1g3bdYFKDu6Vw157Wq97edHFQ/B6t/d8hsNB+vSt5OSTj7PUXX79efi6lP/2z0E1TH6/Si692t48xKk4b2yhNjcHIpH77scB+6jqO0CmiDTeTdwEjPelXmfX9wCuvPAUcqq398JrOEzP7HVcdN4ZlrrrLj2XjpUrouq3UlC1kmsvOc9Sd8Xvz2bnwDq0ZkiLqpKz7meGnmu9FvjJxx7LAeFKwsHgb2lZa1dy5QnWPrTHbrtzXLt2aOX2RlzG2nVccuhhlrr8/HzO6LUrlG9vQMnGUs7dY1/LsY+1uOWciYs09D1pxvHLSWfgwIE6e/bsRj/3+/34/X5yc3PjOkFi6RqbkLK58oul/fLLLznkkENsaauqqhgxYQQ/ly/BG8jgzEPP5KD9Yp8b4XCYl95+g69XL8IXUs4+8BiOP3xwvf12LBtV5Y1J7/DBgvloKMSpAwZyzkkn2/puUz6azjufzaKqqpoj99qdK84/19bTuZ9++RVjJ3/M/rv1pmJrFTdcfSkeT+xrmnnzfuC1UZPYvHkr/foXcvPNV5KVVf92zY78vHQZLw97nfWrN9N71y7c+MdryM+ve7vGahLT5j5vRGROPI2T7B69tPf/WT8MU8uiv9we17FbAhF5jshsXMeoalHNurrvq2qreVQx3b0vXt8DWLR4KS+9Np4NpX527tmJ2264krZt698h2JHVa9by9IjX+XWDnx4FedxyzcV06Vy/p3DHsikvL2fYq2+yeM168jK9XH3O6ey9Z+ynbKuqqhg2+g3mrfyVbODSE4/nUIvhLbWEw2FeGjuWz5cs5pidd6FbYSEn2Jg4WVV5691JvF/yPeFgmFP22Z9zTz4lpq4Wp54z8foe2Pe+1uZ7rarh11w4bSZyJ8VjYmmYVMbSpIbf9TYbfvc60gC/UdX9ReRbVd2vJm2uqlo/uu4ijPc5KxZwVjwmlgQafja8r7X5XsxuERG5qaYlaTAYWiluHuMHVIuIl5qbMiLSmSTMx2+8z2Bo/aSj79kZ49cV+FpExorIELFz781gMBhajqeIDHDuIiIPEXkI4+EkHNd4n8FgcCpN9r2YozlV9S8ici/wO+AKYJiIjAVeVtUlTY/ZYDA4AgVx8XqVqvq6iMwBjiUyrcEZqlqShOMa7zMYWjMu9r5EfM/WU701M9ivqdmCRCYJHCcijzUtZIPB4Cjc/VTvy0C2qj6jqsNUtUREHkjGsY33GQytnDT0PTtj/G6paVU+BnwG7F0zwekBQJqu8WIwtDJc3PADTgBeFZFLo9JOS/SgxvsMhjQgDX0v9sQ90BE4S1WXRSeqalhE7D8DbjAYHIng6AHMdlgHHA2MFpGDgVug3qIGTcF4n8HQinG59zXZ9+ys3HH/jsYX9VnC42gMzc+vq1cxatzLFH/2Ub1Z6a0oLS3l5f++xjsfTLa9jiPA1q1bGfH2GN6cNIFAoP5s9o0RCAR4Y8IEXhk7lq1bt9rWhUIhJkyeyoaNmygtLbWtU1U++OgTXnx5NKtW2VtyrZYvP/+Kl54bycKF1msC78i8ufN54cmX+Hb2t3HpmpWacS52NociqlqmqqcC64FioP46WHFivM8ZqCrT3vuQDRs2sXbt2rh0M2d+wYsvvcbSpb/Elec3387lhZde4/t58+PSLVy0mBeGv8bnX34Vl+7X1at54ZXRvP9Rcdwe/dJrb7C5rDxujx45Zixv/C8+j2512PQ+h9Jk37PT42dwMS+Pe5bZ296jwwAf36wPMuGJ0fz1yifqTTi8I29OHc/wnyYT3COfcEWAUY+9y+MX38lOvayXNHtvZjH3fzCedTt1RkMhnvvbx/znvKs4YO8Blrqv587ljyNHsbygAPF6eeGev/DAGWcw5KgjLXU//7KMmx9+ml+0Pdcf0Y+Tb/k7N5x+JBedbT1j/ubNm7nu9of5eWMbvBm5vPbOvzlnyF7c8n+XW+oCgQA3X3Mvi2dvJUPzGPv8LI44ZVfu/fvtlpNNqyp/HnoPX4+Zj8+fxZg2kxhwVn/+9cqjlquatBjuveoFmFj7QlUfqLk9e1sK4zEkifXrN3DrNQ+yZoGX828cyCUn3c85Vx7K0BsutdRVVlbyfzc8wOKlHrzePN5862mOP3Yn7r77RktdOBzmtj8+xJz5frwZnRg9bj4H7ZPPPx+5M+ak8Pc//CQfzvqVcFZn9N2F7NlzEs/9+14yYyyj9tRLo3hz+jwCbboRrlrCS2On8OIjd9Ohg/WqRW/8byJPTp6BP78b/7dvD0698c88fceN7LJTX0vd+zNm8tcx/2N9x0IIhXhp+kweufISDt5vX0tdq8W93tdk34tryTan4/f7WbNmTdzr+blFV6sNBoO2tAsW/8Sc0GQ67pOBiNC2SwZtjt7Mi//7j6WuvLycl0smE9q7A+L14M3PZuNBbXn8neGWulAoxKMfvsP6/oVIhg9PdhYrduvG3ye+FTPWh8aOZWWPHniyshCfj/U9evLopEkxr2IfeWk0K7J64M1uCyJsze/JsxNnUB5jsfJHnxjB8vLO+DIja0CGswoZ+96P/LRgkaXu2SdH8PMsJUMja/b6qjswY/wyPpg23VL35sgxfD3iB3z+yMog3q1ZzH1tMSOfG2WpiyaR8yYmLh7jp6r37/B+kqoek6p4UoFbPCxe3b8ffpENC3PJ8LQBBE9lJ/47/HNWLF9hqXviiREs/SUPn68dIoJ4OjP1gxXMnPmFpW7kqLHMnq94MzoB4PF14su5Ad58a4Kl7oOPPmHaVxvR7C6ICJ6s9vywJpennhtpqVu4aDGjP5pPddvCyHrE2XksDXblkWEvW+oqKioYNvkTtnTogXi8iHhZntuDh4ePttSFQiH++fYkNnbphcfnw5OVxeqCnjz65jhLXTROP2fiJg19r9U0/Px+PyUlJaxcuZKSkpK4FoF2gy5aGwgEbGk/nj2NDkV1lyATj7CqynomigkfTqZ6z/o9gou2rrLUfTP3O5a0z6iX/kOw3PIW7KZNm1iwtf7C4UszM/l27lzLPEtW1l+o3N+2kPGTp1rqFv6yAZEdTv/srkyZNsNSt2DeKjyeuh3lGZLLF598Z6mbO3MePq175e+TDL79ZJ6lrpZEzhs7uHECZxH5tOZvhYiUR20VImLd8m9FuMXDmqJb8uPaej3pnqqOvDP+fUvdwkVr8Xjq9qT7fB345JM5lrrv5y/Dl5G9g64N38619syZX36PJ6uuZ3q8Pr5fYD2EZNL7nxBq27VOmojw47L1jSgi/G/KVDa361Yv/YdfNzSw93bmzpvHUup79E8VW9m4sb6X7ogbzpl4SUffa1UNPxEhLy/SgxPPieUGXbTW6/Xa0uZltyNYVb/HzBO0vsPfraArofL6DbFMtdZ17lRA9rbqeultgpCTk9OoLicnhzYNpGdVBehcUGCZZ5us+iYWrtpCj25dG9g7SpddXxcKVdM+33oNyZw29XWqSpu21mv8ZudmN5juy7Z3mzeR8yYmSmS+dztbAohIRxH5QEQW1fxtcFUMEQmJyHc128SG9gFQ1cNr/uaparuoLU9V2yUWrXtwi4c1RZfdtv5t0lA4QEFn6wVVsrPre5VqmDYNHC+anJz69RsgpwG/iKZNTkaDY/MyvNathg75uWiovmdmeq3H6Pcs7IZU1h8HneOz/pfeuaCA7Abyy1a19Oha3HDOxIVd77NBzSTvC0RksYjc2cDnWSIypubzWSLSt0khJ8H3Wk3DLzc3F1WloqICVbW9CLRbdNHaUChkS3vWCedT/mVdo6v4NcABPY+y1B1/xNH0WCR1jCxYUcVhXfa01PXt04eDtS0a3l5TwoFqDs/vTnZ2ww0fiDT8jijsRrh6uyFpOMwB2Zn06d3bMs+jB+xKOLC9kaqq7Owt57jB1mMDf3fUPoQDdS+O2ntWc+HvrccGnnTWkYR8FXXSpN0mLrziLEvduVefhadbsE5aqH0lZ11hb9aRRM4bO7RQj9+dwEeq2g/4qOZ9Q2xT1X1rtkYLqKYh2eiWcLQuwS0e1hTdUSfsS5C6DZy8nhWcfd6plrqTTjyYcHhznbRM32ouu9R6Fp6zzzgWCdftbfOE13Heucdb6i678AzahFfXSQtXbuC0EwZZ6i4853Q6h+s+sBLaVsbvBu1tqTv6iMPp791Sx6PDVds4eo+dLXW9evbkwPw2dT06GGRQ9860adPQ5Xdd3HDOxEsyfK9m6bRngBOBPYALRGSPHXa7CihV1V2B/wCPNineJPheq3m4Izc3l6KiIvx+P7m5uXGdWG7QRWvLysooKiqKqc3JyeHWk/7G6x+/wNrqX8gIZjOw+wlcdPblljoR4T9X/IXH3n6eBVt/JUM9HNp5T/58+U0xY3z+lju5Z/gzzN60GtEwgwp68fAtt8bU/fO2W2n73HN8umwF1aEg+3XpzKN33RVTd8cNV+N5fgTTv12AN1TAwbl+/nrrHZYPWgBccsFZBKqqmTz9G8oqqtipZz5/uOEGywYqwHG/G0zFvX7eHv0Rpev9FPbpyJU3XkWPHt0tdXsN2JM7RtzE60/8l7VL19G+ezvOvf5ijjzmiJjfERI7b2zRMrczTgcG17x+lchTaH9O4HhziETe0I+tgPV/wVaCWzysKbqrrr2IYDDE9MmzEV81uxwEt951BxkZ1j1wp5zyO/z+bUx453NKS7fSq1d7rrv2Kjp16mSpG3jAPtx5Wymj35jG2g1b6NYlj8suOp2997K+6C3s1o2//+kChr8+mWW/lpHf1scZZxzM6acMsdRlZ2fz5D3/x79HjGXRyo20zfIyZPBeXHv5hZY6EeG5v/yRB599mfm/bsAX7syFu3bgnpuus9QBPHP3n7j36eeYs2oVaJiDe/Xgodv/FFMH7jhn4iY53ncQsFhVlwKIyFtE/O7HqH1OBx6oeT2OyEpAovE8xh0hYd+T+PNMHQMHDtTZs2e3eL7FxcUMHjy4xfNtDCfFY2JpmFTGIiJzVHWg3f1zuvXSXS++3da+8/91+zIgeiDRi6r6os24Nqtq+5rXQuTqt96jiyISBL4jslLGI6pqPbI+DTDe56xYwFnxmFji9z2w732xfE9EzgGGqOrVNe8vAQ5W1Ruj9plfs8/KmvdLavaxHpjZDKSkx09E/gmcCgSAJcAVqrrZWmUwGJqF2nEu9thgZa4i8iFQf9Q53FMnS1UVafQmSh9VXSUiOwPTRWRerLVxa8YL9gN+67JVVesndVKA8T6DwUHY9z5L30sVTfW9VI3x+wDYS1UHAAuB2Pf0DAZDsyBxbLFQ1eNUda8GtneAtSJSCFDzd10jx1hV83cpkdvB+1nGL3I1MAOYBvy15u8DNsJNBcb7DAaHkCzfA1YBvaLe96xJa3AfEfERmWw59qPUjcWegO+lpOGnqu+rau1I9y+JFJLBYEgVLTOP30TgsprXlwHv7LiDiHQQkaya1wXAYdQdJ9MQtwAHAstU9WgiDUVH9qIZ7zMYHEZyfO9roJ+I7CQimcD5RE2wXEO0/50DTG/C+L5omux7Tni440pgTGMfishQYChA165dKS4ubqGwtuP3+1OSb2M4KR4TS8M4KRY7tNBcVY8AY0XkKmAZcB6AiAwErqsZH1MEvCAiYSIXpo+oaqyGX6WqVooIIpKlqj+JyG7N+D2ShfG+OHBSLOCseEwsTScZ3qeqQRG5kUivmxcYoao/iMiDwGxVnQi8DLwmIouBTUQah4nQZN9rtoaf1Vifmts+iMg9RAZwv97YcWoGUL4IkQHOqRg06qSBs+CseEwsDeOkWGzRAutRqupG4NgG0mcDV9e8/hywnsuiPitFpD0wAfhAREqJNCxTgvG+5sFJsYCz4jGxJECSvE9VpwBTdki7L+p1JXBucnIDEvC9Zmv4qepxVp+LyOXAKcCxCXZ3GgyGRHDg7PTxoKpn1rx8QEQ+JjJ2xnrpluaNx3ifweAGXOx9ifheSsb4icgQ4A7gNFWtP/24oUFUlU2bNjVJt3nzZgKBQNza8vJyKivrr+IRC7/fz9at8f+0W7dubdLs7JWVlYTD8V+6BQIBNm/e3OCs+1YEg0E2bdoUty4cDrNp06aYaxC3OC5eqxd+Gxs4AKgAVgJ7pTikBjHe17IEWp4qbQAAIABJREFUg0FKS0vjrqehUIhNmzbF7SmqSmlpKcFgMPbOO+gS8Whz/ZAAaeh7qRrjNwzIItI9CfClqsaeeTKN+WTGf1m49Dly2/1Cht7B+AnfcNYZsecf+mJ2MVO/fZ7qtivRrW3plX0411/0l5gTHM/7aT5PvD+clb71ZFT7GJC1Cw9ceSeZmdZLHi1btZK7Rz/P99WleBUG5nTh30Nvo10765VkysrKuP3pp5hduokgsG+7fP5x9TX07tHDUhcIBPjzY0/y5S9ruOTw/XjhD/dy95UXsM+eO06aXhdV5W+PPsPM2T/jr1R6dcni+stP5egjD7XUATzz1Cu8P+VbykqDdCnM4cJLj+OMs06MqXt9+FuMf3YSG38uo2Ofdpx6zQlcccNlMXUtgVuvegFE5G/A5cBStt+4UcDWguUtjPG+FuKJh55h+tjPqFhbSdd+Hbjk9nM4+czY9fTVl8cwccxMStcF6Ng1mzMuPJKLLzsnpm7i+Km88fJU1q3aRl7HDI47dT9uuu2qmLpPZnzB8y+9w8pV22jTxsPhh+zEPXffiMdj3S8z/4cSHn3ydZau9HPZ2QOZ/MGjPPzAbTE92lAXt3pfIr6Xqqd6d1XVXlHLMiXF+Px+P2vWrIm7x8jpukWLfmB92V848tif2P/ASvLaBehY+B8+/OhNS93mzZuZOPchuh+5mj4HeOl7RCWB3aYx+n/PWOqCwSB/m/QE6/YLkbl3R2T/dnzXbw3/GPWfmLHe/spTfLVzNpW7FbJl90KKewm3vxRbd9vTTzG9bQ4VvXuxrXcvvmjfjluftY4T4P4nnmVaKVR07AkZmfzg7cgdw0bE7FF7+vlXmTxrM1s83ZE2PVjpL+DvT46jrKzMUjdu7ETGv/ET2zYXkCnd2Lwmn2f/PZWfShZa6j6b8QUj/jSG8rlBMsrbUjEvxGt3TuCD9z6K+R1raer5ZgcJ29scynnALqp6lKoeXbM5sdFnvC8BXTAYtK0bPfxN3n1sJlVLMsj051H6bZCnbh/Jsl+sh0B99OEnjB72OVvWtCcz3AX/6naMenIGn878wlK34KeFDHtkEptX5pGpXaja2IF3Rv7Af9+q9+B6HcrLy3n4sTGsXt8Bb2Z3qoLdeL+4lGHPjLTUhUIh7nloOD9vbI/k9ETJ4PMS5cF/xPbMWtz02zeX70F6+l6rWavX7/dTUlLCypUrKSkpiWsRaKfrZn/zBnvvW3d92MLuIZatmGSpm/Th6/Q6pKpOWk47L0s2fmape/ej96jY01snzZvpZW75AktdycIFfN+27q0K8Xj4estatmzZ0qjO7/cze3MpssMV7nfhEAsWLbLMc9bSVXi8dTuuV2R0YNLU9y11X3yzBG9G3UXJt0o3Xh9jbdSfTP8OL23rJgY78fZ/p1nqprw5DU953Stx79ZMprxhHWctTT3fbGH3Nq9zr4znA/VWAEkX3OBhydAFAgHbus/e+xpvKKtOmq7LYsyI8Za6D979HG8or06aJ9iOqRM/tdS9PWYqnqq6y6T6aMtH731lqXv9zQlsC3Spk+b1ZfP5l9YXklOmfshaf37dOD0+vv5+uaWuFrf99s3ie5C2vteqGn4iQl5eHiIS14nldJ3S8HiRYMh67F0wXI3H21C69TiSquoqJLP+qVEdqrbUVVZWEvbV1wVFLXvgQqEQDX0a8nhiji8MhRuolV4f22LqGriMEw+BauuxOaFQwy4QClpfFoaDDX//qm1VDabvSFPPN9u42wD/AXwrItNEZGLtluqgWgo3eFgydF6v17YuWF2/volIg+nRhIKN1O8YunAjvhCosvbM6upgg8NuAgFrH9q2bRuROYDrH88Obvvtm833IC19r9U0/HJzc1FVKioqUNW4FoF2uq5ot9NYsrBub1HZZmifd4Sl7oQjzmXFnLotv+pAmC6Z1rNlnH7cKWTOq9tw0rDSL6tXI4oI++49gP4NTB+5lzffcoxffn4+A3Lz6qX3D1QzYC/rsaoDenZGtW6jq1PFGs482Xosz967FRIO1zVJX9WvnBdjrN5+A3chFK7bWAtqKSecfJil7ohTDiOUuYPOW8WhJx5kqaulqeebHYTIOBc7m0N5FXiUyDyB/4ra0gI3eFgydKFQyLZu3yP2ILTDBXMwdyunnj/EUjfoqL0Jat27E0H8HHaM5eIxnHDqEQQ9dc0vGK5kv4N3tdSde/ZJeHdYwCYcDrLXnt0tdaefeiL5GXWXeFVVinbtbKmrxW2/fXP4Htj3PofSZN9zwgTOSSE3N5eioiL8fj+5ublxnVhO1+2372Esm3QrX8wYyc79V7PF72HZV+dwzZW3Wuq6F/bg0K7X8dnMV2nXbxMVa3xkrd+bO4febanLzs7mpkGX8fznoyntFUQqQvTZ0IH7r/2zpU5EeOjMK7hn/AgWdvBAKMSeZR4eiREnwMNXXsVtzz/H96KEPB76b6vi0csvj/kQyt9uvpbSh/7Fd5sCaKgrXTev5M5LziY7O9tS9+dbh7L27keZs2A9Ac2hY7afqy87lu6FhZa6q4dexLJfHufLT34hUJlDm3bbOO/cgzn4YOtlHE86fQglf/6J90fMYNvKIJndhKMvPJiLrrzAUldLU883u0hDPafuYauqPpXqIFKFGzwsGbqysjKKiops6a7/wzWs+HkVX0/8keAmoW0fL+fdeAp772N9IXnWuaey8KdfmD5pPoGKbLLaVXLimftyymknWOoOPHB/zrvmB9558wu2bMzEl7ONgUf14oZbrrbUFRZ24/prjuGV16ZTWpaD17OVvYry+Mvdf7LUZWVlcceNZ/Of58ezpiwbDXdj504b+fu9d1rqanHbb99cvgeu9r4m+5646THwgQMH6uzZs1s8X6dMSBkZ7/AdZWWVHHec5VRhdaiqqmLuvDl0L+xFzx7WvXbRhEIhZn/3DQUdO7LLTrs0uE9DZaP6/+ydeXgUVdaH39Pd2RMSIOwgm6gRAUHABRdUVMQF93Ed923U0VHH0fFzGZdRRx33DXcdFRVBUEFFIe4gIIJAFNkXZYckHUKS7j7fH0kwIUl1ddJJV3Xf93n6IX27fn1P3a76cerWrXuVufPnkZySwj575dmuD2BBQQHlZWUMHDAgbNJXkyVLl/HLLz8z8phj8Hrrub/dAKvXrGH16t8YvN++ET0Nt3HjRhYvXsq++/YjIyOjzucNHTOFhYUsmL+QvL570aZNmzqfRwMRmRPJguIZud00b/TfbG0756UbIvrulkBE/guUUbkk0s5uVVX9IWZBRZlE9z5oXCzr1q1j6a/LGLjfvqSnp9vWbd26lUWLfmafffYmOzu73m3qi6ekpIQff5xPnz69ad++fb26+igvL2f2nLl069qFbt3sr+IXDAaZM+cHtm7dyjHHHG1b15zE6piJ1PfAvvfFm+/FTY9fIpCZmcmQIQdHvBxOSkoKQweHn6ZkV7xeL/vvNyRinYgwaMC+EesA9smLLFGsZvfevVizelVESR9At65d6dY18uVS27VrR7t29m6r1CQ7O5thh0T+WzQ3Dr6dYYfq+3AH1Chz6nQuhhakY8eOdOxY3yIq1rRu3Zphww6MWJeRkdEoXXJyMgcduH/EOq/Xy9ChQ1y1RJrTcLH3Ndr3TOJnMBicPIDZEhHxApNUNfycQQaDwbArLvS+pvpe3DzcYTAYGo9b5/FT1SBgb6CkwWAw7EIi+p7p8TMYEh1nP7lmh29E5EngbWDnI5nxNMbPYDA0A+72vkb7nkn8DAaDK2931KB6QOldNcrMGD+DwRAe93pfo33PJH4GQ4JTPZeVW1HVw2Mdg8FgcB9u9r6m+J5J/AwGg5vnskJEsoE7gEOrir4A7lJV64WXDQZDwuNW72uK75nEzyWsXr2Er798BI8sJyn1DObP+4b+A6xXiwDYvHkj705+mBJdilez2G+P0znkQOvVKQC2b9/OE+88yYodq0iRFA7pNYxTjzolrC4QCPDfN19k1qYVeMXDYV3zuOK0c8LOyaeqPPP2W0xbupigKgd07sYNf74Any/8Ifrm+5OYPGseh+/dm+mPPsnNl19MWlpaWN3HU6cz7tNvKdpeRu9Orbn+ivNol5sbVvftN9/z9hufsnVzCZ265nD5X/5Er949wuoWzi/glcffZP2qLbTr1obzrjqNfQcNCKtrdpy9LJEdXqJy3cozqt6fB7wMhD9gDYZdmPfDfF599A02rtxC+x65XHj9uewzoG9Y3fKly3n2vhf57dd1tO6Yw5lXncpBh4af2mXTps08/sALrFy8gazsNI47YzjHHm9/nlZDE3C39zXa9+Iq8fP7/Y2a4dvpuq1btzJ96p85bmTlAtw/LhzJmhWX4/W9RN++DS/5FQgEeOKNi+k3ahXtqxKvHxfPJ/RtiMMOOs6yzr8/+w+27V+Cx+fBzw7G/v4e2z/cznnHn2upu/6p+5naqRRP78oF0ucX/8TmV57h/y78i6XurjHP8nLJRsitbI85JRtY/chDPPl365non3/rHR77voBQRisOFB/vbNjBktvv4Y0H77XUffDx59zz+jSCqW2BNJYuC1Fw032MG/OAZbI5e9Zc7rr1LUJlbYB01q0q528LH+bVsXeTk9PwetmrV63m5vPuo2Jt5YoiG35Yz60zHuSR8Xewx559LGOtprHHmx2c+ORaBPRW1VNrvP+XiPwYs2higNM9LBq6QCCwU9tc9S1ZvIRbTr+bihWVE16s+7qIf3x3J89MfZjduu/WoK6oqIjrTr6Z7QsqT6R1FHLnl//h3vG3MuTAhuf9DQaDXHP+bWz9OR0RDxso45HZ4wgGghx/kvVqITX3sSXaxm06u7jY+xrte3EznUvlqhYFrFmzhoKCgogWgXa6btrnzzHyqJW1yvYfso05s8ZY6j7+7B16H7qiVm9blz2CfF/wpqVuxpwZrO+xGY/vj8MjtVMany/Lt9T9vu53vqr4HU9K0s4yyUpjym8LKC8vb1BXXl7O5BW/QsYfM+t7kpP5fNsG1q9fb1nn+9/PJZTxxzrA4vEyt8zDd9/PstS99+k3VUlflU6ElRVtGDfxI0vd229+UpX0/UHJtra88tK7lrrXnhlL+ZqUWmXB9em88oT1b1FNY48329hZqNy5V8alInJw9RsRGQaUxjCeFsUNHhYNXXl5ebPX9/pTY3cmfdWULRFefeINS93LT76G/6faawPreh//e3Kspe69dyaxqcBXy6O95VlMeGNq2FihZdvGTbqISEDfi6vET0TIyspCRCI6sJyu09BGvN76bpVuqqfsD7YUryEjq+5KFhW61VL3y4rFpHaqe6u0OFRsqVuxejUlOXWXPStMClFc3LC2qKiILfUsuFGcmcbyVSvrflCDLdvL6pRpVg6Lliy11G3119V5k9NYs866TYsLd9Qp84iXbVtK6tn6D4o2l9R7u3vrxiJLXTWNPd5soZXjXOy8moKInC4iC0UkJCINdoOIyEgR+UVEloiIncVHrwCeEpEVIrISeLKqLCFwg4dFQ+f1epu9vqJNdX1KRCjcZK3dum4bHqn73+m29dbDrX5btR6fJ6VOeeFmaz+ppiXbxk0629j0PofSaN+Lm8QvMzMTVaW4uBhVjWgRaKfrWuUMZOvW2gdfKKQge1rq+u5+COuW1y1Pk56WuqOHHUXZwu11yjt5rZc+GtivPx031u3Z6x5Is1yXtm3btvSSpDrlXYpKGdjfegxc79y662imbv6dUUcMt9T17FBXp9u3cOj+A+vZ+g+6dm+Dau17A4FgKfv072Ud5z67EdTaPQIhDdKrr721kxt7vNlF1N6riSygcvzJlw3GUTkj/VPAscDewFkisrfVl6rqPFUdAPQH+qnqQFWd1+RoXYIbPCwaumAw2Oz19ezbjZAGa5UFNcDu/btb6vY5II+A1PY+VWW3vtbLQQ47fCgV3roXf912t7ccZEu2jZt0kdACvtcsNMX34irxy8vLo2vXruTl5UV0YDldN2LE2Uz7agTrqu56BkPw9vi9GX3SPy11+w08kNCqo9lQOTSQsh0h5k7O5bSRf7fUderYieGZh1C6tPKqMxQIUfbddi46/HxLXWpqKhfvcwQpSzehqmhISV+0gasOOcHy4Q4R4ZojR5Kz6nc0FEJVSVv9O1fsfzApKXWvhmty7ekn0XbzGjRUadaeLRs4Z7++dAqzPue1F/+JdhVrCAUqKvdx+xaO6tuaoYMHWequue582nbZSiBQ2fNXEfCTN9DDKacdb6m74Ipz2W14BhVU6bSM9vt7ueYmex1TjT3ebNMCt3pVtUBVfwmz2VBgiaouU9VyYCww2kogIikicjZwNXCdiNwuIrc3LVr34AYPi4YuOTm52eu77PpL6HpMawJUJnEBKaf7qFwuuvoCS90pZ55M3zN6EvBV6bSCnIOSuf7Ov1rqhgwdxLCTelEhlT2NwVCA5M5bueYfF9rYw5ZtGzfpIsKlt3qb4ntx9XBHYwd/Ol3n8Xi49PJX+PqrD/h5yQ8kpXTh8isnk5RUt5dsV66+6AFmzhpFwZyvSE9pxz8v+bOtJ16vOvMvHLzwYKb9OI20pDTOvugsWrVqFVZ3/gmnctDyfXn3i09I8vg476Ir6dgh/CLpxw8/nP32yuO1yR9SEQpy5sWnsXtP655JgCH7DuDD+2/n5fcm0CbJw+tXnM3A/v3C6nr26M745+7ltbfHs2mbn4MHH8BhBx8UVpednc3rYx/knbETWbN6A/36H8Cxx40I+9RycnIyz7/7GBPf+5DFPy2j1167ccqfRuP11nOPuwGabXCzRnQ7I1dEZtd4P0ZVrQebRkYXYHWN92uAcKvXTwQKgTlA3Xv4CYDTPSwaOp/PF7E20vpSU1N56cNnGf/W+yxbtII+/Xtx0hmj8Xis+0g8Hg9PvPkIH3/wCfNnLKBzr06cef4Ztjz6Xw/8g6+P+5Zv8+fQJjebcy483ZZHV9NSbeM2nR0i9D6n0Wjfi2niJyI3AA8B7VTVenBVgiMiHHLoicCJ5Ofn2zKUavYfchj7Dzks4joH9O3PgL79I9b16dmbf/a0foq3Pjp17Mg/LrokYl12djbXXXQB+fn5tpK+atLS0rj8gnMiri8pKYlzzjstYp3H4+Hk00+E0yOWNjsR3M7YpKpW4/M+A+rL9G9V1YmNCM0OXVV1ZDN9d7NgvM+5eL1eTj/31PAb7oKIcOyJIzn2xMgPxYMPPYiDDw1/4WmIPk69lWuDRvtezBI/EekGHA2silUMBoOhiiiZn6o2dQKytUDNgY9dq8qs+FZE+qnqT02su0Uw3mcwOAj3Jn6N9r1YjvF7BLgJNze7wRAntNDDHXaYBfQRkZ4ikgycCUwKozkYmFP1JPB8EflJROY3e6SNx3ifweAQHOJ7jaHRvheTHj8RGQ2sVdV54cZGichlwGUAHTp0ID8/v/kD3AW/3x+TehvCSfGYWOrHSbGERYFg87ubiJwMPAG0Az4SkR9V9RgR6Qy8oKqjVDUgIlcDnwBe4CVVXRjmq8MvReMQjPc1HifFAs6Kx8TSSFrI+5qJRvtesyV+VmN9gH9SeasjLFUDx8cADB48WIcPHx6tEG2Tn59PLOptCCfFY2KpHyfFYoeWuKpV1QnAhHrKfwNG1Xg/GZgcwfdaT/bYwhjvax6cFAs4Kx4TS+NxcI+eJU3xvWZL/Boa6yMi/YCeQPUVb1fgBxEZqqrrmiseg8FggbrU/RyI8T6DwUUkoPe1+K3eqoGI7avfi8gKYLB5ss1giB1uvep1E8b7DAbnkYjeF1fz+MUzgUCAaZ+9QWnxIkjaj5KSEjIyMsLqVJXP8yewZsP3+KQ1o0ZcarmKRk3yv5vO7KXfkSwpnHL4n+ja2XoW+mq+nzuHD+d+iU88nH7wSPL6WK8wUk3B4l94Y/pnBFU5+YBhDN3XehWNalavXcsrEz+gV25bpn75FUcdeogt3ZYtW3jxzffYVlLG4L69Oem4kWHn4wMoKSnh5VfeZcPGIvbo04Uz/zQan8+9p5JULVtkMBgMiUSiel/M/7dS1R6xjsHpBAIBXhlzLqcdNYtWWV6+mN+N8W+cxLGnvEFubntL7ePPX0W3QZ+xW08hGFReev9DTh4+ht698ix1j7z+Hxa1/Y7MfVJQVe6Y8h2X7HsdB+53sKXumXGv8/LWGdCtckm0Tz55lBtWncApR46y1L3z8RTunDmNki6V+zPuo7e59udFXH2m9Tx7X8yYyY1vjWNbu05c26YNd304lTPn/cS/rrGeR7Dg58Vcdd9zbE3tjHg8fPTzbKZ99wNP3HurpW7Dho1c9pd72VLcHo/Hx7SvF/D59Fk8/+w9rk7+CIXfxBBdjPcZDA6gmb1PRNoAbwM9gBXAGaq6tZ7tgkD11CyrVPXE5oopbpZsg8qnidatWxfxQs5O130+9fWdSR+AeODsE1Yw/dNHLHUzv59O+72nkZNb2Yvl9QqDjtjA1K+fsNStXL2Cnzzfkdm5crk0EaHVfj7GzxlrqSspKeGdFd/sTPoAKnZvzatzPyYUavjsCoVCPPfNH0kfQHmHtryyYA7bt9ddM7gmT384hcL2nXf21Gl2ayYsXcmKVdZTpD31xgS2pXdFqmbk96Rm8s2acr745jtr3TNvstXfCY+nMsnzJaXx64o0xr5tf27ilj7e7CCqtl4GZ+J0D4uGLhAIOD7OWNTplrZxou+BPe9rIjcDn6tqH+Dzqvf1Uaqq+1a9mi3pAwf0+EULv99PQUEBIoKq2l7Xzw26Hf6CnUlfNSKCJ7TMUvfrypl0HlL3oN0RWmqp+/L7fFrtnVynfGPFb5a6+YsWsLWDj12Va33b2bp1K23btq1Xt3nzZlZJsE75763SmLdwAQcOGdpgnSu2FUFadq2y0twOTP3qay495+wGdas2FQG5tQvTc/h+3iIOG3Zgg7rf1hUhUnv9YF9SGot/DTfHcCUtfbzZwsHrURrC4wYPi4auvLycgoICx8YZizrd0jaO9D1oKe8bDQyv+vtVIB/4R7PXakHc9Pj5/X5EhKysLETE9tWBG3Ti7UhFRd2js2RHdj1b/0G71r0p3Fq3py1UnmOp67fHAPyr6i79lxq0PuF279GL9M0VdcpblXrIzm441pycHHLr5n1kF5bQp2cvyzrbZdRd09KzdRMD9+lrqcvNqqsL7SihV9dOlrrWOfXoQgHatcuy1FXT0sebPSrXq7TzMjgPN3hYNHRer9fRccaiTre0jTN9D+x6H1VrlNd4XRZBJR1U9feqv9cBHRrYLrXqu2eIyElN2atwxE3il5mZiapSXFyMqtq+KnCD7oijL+Pdj7ujNbqcJ09LZ98h1uvajjj8FAq+6kuwxgSVv8xNZtBe51nq9u03kLYrexAo+yMbK1q2g0N7HGWpa9euHYel9CLk/yNpDG7yM7Lzvpbj35KSkjhlz354Cv84qXV7KUe17khubm6DOoAzDxyKb9sfwyVCFRUMTfYweMAAS925xx9O8vaNf9QXCtHTt4WTj7de+vC8s0eR5Fn/h06VnPT1XHi+vQV4W/p4s42qvZfBcbjBw6KhCwaDjo4zFnW6pW0c63tg1/c2qergGq8xNb9CRD4TkQX1vEbXrkqt+hi7V62DfjbwqIj0jv7OVhI3t3ozMzPJy8vD7/eTmZkZ0YHldF1mZibHnPQ/xk99tPL2bmoWffo+R/8BDd8ChcrFxq+58HXGffgwxWUFBMvTGNrvHIYdaJ3AAdxz5YO8MO4ZlhUvhgo4aY+jOOGo0WF1/77iJrqPe53vfimAQIjhPQ/kwlPOCqv7+58vpNMHE5n801zKAwGG7daL686/MKzu3JNG07pVFu9++S3pwQAX5Gbyj8v/FlZ3xKHDeDglmdffn8o2/3b6dMnl5mvuxuOxvhbq129v/nv/xbz0yvts2lxC1y7ZXPvXWx153NhGQczDHa7FDR4WDV1hYWFEt/pica6ZtnGGzjZR8j6rNcpFZL2IdFLV30WkE7Chge9YW/XvMhHJBwYC1uOyGkncJH5Aow8MN+jatevI6WffD1TOjN5/wP62dFlZWVx41p2RhkhSUhJXnvXXiHUiwhWn/5krIlbCuSeM5twTwieXu3LcEUdw3BFHkJ+fz0UW4/p2Zdj+Qxi2/5CI6+vXb28eeXjviHXVtPTxZgvTm+dq3OBhTdX5fL6ItbE410zbOENnm+b3vknA+cD9Vf/WeRJQRFoD21W1TERygWHAf5oroLhK/AwGQ+Mw4/cMBkMi0gLedz/wjohcDKwEzgAQkcHAFap6CZAHPCciISqH4N2vqouaKyCT+BkMBtPjZzAYEpNm9j5V3QwcWU/5bOCSqr+/Bfo1ayA1MImfwZDoKGYCZ4PBkHgkqPeZxM9gSHAEMzmzwWBIPBLV+0ziZzAYwGJlFYPBYIhbEtD7TOJnMCQ6CXq7w2AwJDgJ6n1xM4GzoWGKioqY8slYFi6cG5GutLSUjz6dwMzZ39aaPDocFRUVfPT5x3z+9XTLNXp3JRQKMfXLL5j02ScEAgHbOlXl65kz2VZYSGlpqW0dwNx583lnwiSKiooi0sUbZq1eg8GQiCSi75kevzjng4+eYUPRc/QdtJEla5P4/MsDuOT8l0hPT7fUffLlJKb+Moa2A7ezo1AZ/0QXbjjrYdq3a2i1mUq++eE7Hpn+IsV7CRQrL/x3LHec9Df22n0vS93Cxb/wtzefZXHHNNTr4eGvp3D38Wdx6GDr+Qp/X7+eKx78Lwt9qVw3II8jbr6Nv486mlOOOdpSt337di7/v38zvxBCqVk8OulLLjxqKJeefYalLm6JQ3MzGAyGsCSg98VVj5/f72fdunURr+fnFl21NhAI2NKuXLWUbRWPMnjYZtLSPPTYPciwY77m3fF3WepKSkqYuvhZuhxcTmqGj5zOSXQYsZ4XJt5vqQuFQjye/zJlQ9NIbpVKcts0/Psn8/Dk58LGese4V1kmn+XjAAAgAElEQVSyZzs82Zl4M9NZvWd77vrw7bA9hnc8/yIL23RAsnNAPGzq2IX/TP6EkpISS929Tz7PvEBryGqLJymZkuwuPDd1NstXrgwbKzT9N2zp48YS1cpxLnZeBkfiFg9ris6u70WrPrec325pG8f5Htj3vjgjbnr8/H4/BQUFiAiqanv5GrfoamrLy8spKCgIq/1u5jj6DS0BZGeZzyeUVsyxrGfy5xPoMKScmtcFIsLGwC+Wuh9/+pHNXcpII6VW+QrvBgoLC8nOzq5Xt23bNhYGi4Da+/Jrtoe58+ex374DG6zzpw2bkE7dapVtyu3IuI8mc/4ZDa+fu2DNBsRTex3g8lYdGT/lM2644uIGdRCd37AljxtbxJ+3JQxu8bCm6uz6XqzijEWdbmkbx/oeJKT3xU2Pn9/vR0TIyspCRGxfHbhFV1Pr9XptaZOTMghU1C0PBpMsddmt2lBWUvdskKD1dUKrrFZIaV2dt1xITk5uOM7kZFK07qHoK6sgp1X9yWI1qT5vnTItKyO3dWtLXYq37r5oMEhGepqlDqLzG7bkcWOHlhjjJyKni8hCEQlVzVrf0HYrROQnEflRRGY3qdIEwC0e1lSdXd+LVZyxqNMtbeNU34PEHOMXN4lfZmYmqkpxcTGqGtEi0G7Q1dQGg0Fb2qNHXMCML7rUKtu0QWjX2nr824hDR1I4p3ZvWNn2ILul72ep273X7vTc0rbWgyChQIg8z26kpTWcUKWnp3NgZgc0GNxZpqoMLEuhd69elnUe2qsnofKyWmW9i7dw7JFHWOqOHLQXoR21TaSN/zfOOzX8WsHR+A1b8rixhaq9V9NYAJwCfGlj28NVdV9VbTBBNFTiFg9rqs6u78UqzljU6Za2cazvQUv4nuOIm1u9mZmZ5OXl4ff7I1rU2S26mtrCwkJbXd6ZmZkcdsDjfDvtQSpCPxMKtKJtq+M4+0/XWuo8Hg9/OfE+Xv/0ITYHlyDBJHZLO5Brzv+/sDHee/7/cd/YR/i5dCUSgr7pvfjXZbeE1f33yutJfv5xvt24ikAoxL6t2vPQNTeH1d1+5eWEnnqGaUuW4emSyxD/Vu667ho8HutrmsvOPRP/9leYMmsBhaXl9G6fw43XXkBGRkbYOqPxG7bkcRMWVQg2//0OVS2AymEDhujhFg9rqs6u78UqzljU6Za2caTvQYt5n9OIm8QPaPSB4RZdtdbn89nW9+u7P/36jiMUCoVNhmrSs3tvbr/0mZ29d3b/s27XNpf/XnVvxLq0tDQe++s/ItZ5vV7u/uvV3KXKF198wV/+fJ4tnYhww+UXcsPlRNw20PTfsKWPm7DYv6rN3eX26xhVHRPtaIBPRUSB55rh++MOt3hYU3SR+F406nPL+e2WtnGk70Fc9uiFI2aJn4hcA1wFBIGPVPWmWMWSCESa2FTT2N4Zt+ig8W0TV9g3v01Wt19F5DOgYz0f3aqqE23WcbCqrhWR9sBUEflZVe3cHnYFxvsMBgdhEr+WQUQOB0YDA1S1rMrgDQZDLFAgFB3zU9URUfiOtVX/bhCRCcBQ7I0LdDzG+wwGBxFF73MTserxuxK4X1XLoNLgYxSHwWBAIRQMv1kLICIZgEdVi6v+PhqwnnjSXRjvMxgcg3O8ryWJVeK3B3CIiNwL7ABuVNVZ9W0oIpcBlwF06NCB/Pz8FguyGr/fH5N6G8JJ8ZhY6sdJsYSlha56ReRk4AmgHfCRiPyoqseISGfgBVUdBXQAJlTduvcBb6rqx80eXMthvK+ROCkWcFY8JpZGYnr8oovVWJ+qetsABwBDgHdEpJfWsyBs1cDuMQCDBw/W4cOHN1fIDZKfn08s6m0IJ8VjYqkfJ8ViixYY56KqE4AJ9ZT/Boyq+nsZMKDZg2lGjPc1D06KBZwVj4mlCZgxftHDaqyPiFwJjK8yu+9FJATkAhubKx6DwWBBAppfc2G8z2BwEQnofbF6nPF94HAAEdkDSAY2xSgWQxxQT4eJwS6qEAzaexmaivE+g8Ep2PW+OCNWid9LQC8RWQCMBc6v71aHwRCOYDDIrU89wbCbb2DRmtWcc8+d/Lp8WazDch8ts3KHwXifweAsEtD3YpL4qWq5qp6rqvuo6iBVnRaN7/X7/axbty7i9fzcoqvWBgIBx8faUro7xzzD6xXF/NajM8GUZL5pm8lVzz1NKGRvNvZY/YYtXWdYTOLXIhjva7zODb4Xizrd0jaO9D1ISN+Lm5U7/H4/BQUFiAiqanv5GrfoamrLy8spKChwbKwtqfti9Uo83TrUKvulbRYfff4ZJxxlvSZxLH/DlqwzPJqQT7bFC244T6Ohc7rvxaJOt7SNM30PEtX74mbJAr/fj4iQlZWFiNi+OnCLrqbW6/U6OtaW1O0IBuoWpiSzrbjIUXHGss6wKGgwaOtlcB5uOE+joXO678WiTre0jSN9D2x7X7wRN4lfZmYmqkpxcTGqGtEi0G7Q1dQGg0FHx9qSugGtc+s82JG7ej2njhzlqDhjWactzK1e1+KG8zQaOqf7XizqdEvbONb3ICF9L25u9WZmZpKXl4ff749oUWe36GpqCwsLI+rydss+NkZ390WXsuGxh5mflgRtutB++RpuOeY40tPTHRVnLOsMiyrYHBNpcB5uOE+joXO678WiTre0jSN9DxLW++Im8QMafWC4RVet9fl8Eevdso+R6jq2b8/799zPd7Nns+H33/nyrvtJTU11XJyxrjMscXhVm0g4/TyNhs4NvheLOt3SNo70PUhI74ubW72GxEVEOGjIEHJatYoo6TNUo2aMn8FgSEDseV+8EVc9fgaDoREk6HqVBoMhwUlQ7zOJn8FgAE28cS4Gg8GQiN5nEj+DIcFRQBPwqtdgMCQ2iep9JvEzGBId1bgcx2IwGAyWJKj3iZuWiRSRjcDKGFSdi7MWUndSPCaW+ollLN1VtZ3djUXkYyrjtcMmVR3ZuLAMjcV4H+CsWMBZ8ZhYIvQ9iMj74sr3XJX4xQoRma2qg2MdRzVOisfEUj9OisVgaCxOOo6dFAs4Kx4TiyESzHQuBoPBYDAYDAmCSfwMBoPBYDAYEgST+NljTKwD2AUnxWNiqR8nxWIwNBYnHcdOigWcFY+JxWAbM8bPYDAYDAaDIUEwPX4Gg8FgMBgMCYJJ/AwGg8FgMBgSBJP41YOI3Ckia0Xkx6rXqAa2Gykiv4jIEhG5uRnjeVBEfhaR+SIyQURyGthuhYj8VBXz7CjHYLmvIpIiIm9XfT5TRHpEs/4a9XQTkekiskhEForItfVsM1xECmv8frc3RyxVdVm2uVTyeFW7zBeRQc0Vi8HQVJzkfcb36tRlvM8QHVTVvHZ5AXcCN4bZxgssBXoBycA8YO9miudowFf19wPAAw1stwLIbYb6w+4r8Bfg2aq/zwTebqa26AQMqvo7C1hcTyzDgQ9b6FixbHNgFDAFEOAAYGZLxGVe5tWYl5O8z/henXiM95lXVF6mx6/xDAWWqOoyVS0HxgKjm6MiVf1UVQNVb2cAXZujHgvs7Oto4NWqv8cBR4qIRDsQVf1dVX+o+rsYKAC6RLueKDIaeE0rmQHkiEinWAdlMDSBFvE+43u1Md5niBYm8WuYq6u6p18Skdb1fN4FWF3j/Rpa5iS8iMqrqPpQ4FMRmSMil0WxTjv7unObKrMuBNpGMYY6VN1WGQjMrOfjA0VknohMEZG+zRhGuDaP1XFiMDQWJ3qf8b0aGO8zNAVfrAOIFSLyGdCxno9uBZ4B7qbywL4beJhK44lJPKo6sWqbW4EA8EYDX3Owqq4VkfbAVBH5WVW/bJ6IY4uIZALvAdepatEuH/9A5bqN/qoxSu8DfZoplIRpc0N84CTvM74XOcb7DE0lYRM/VR1hZzsReR74sJ6P1gLdarzvWlXWLPGIyAXA8cCRqlrv5Iuqurbq3w0iMoHKWxXROBHt7Gv1NmtExAdkA5ujUHcdRCSJSuN7Q1XH7/p5TTNU1cki8rSI5Kpq1BcOt9HmUT1ODIam4iTvM74XGcb7DNHA3Oqth13GIZwMLKhns1lAHxHpKSLJVA7sndRM8YwEbgJOVNXtDWyTISJZ1X9TOTC6vrgbg519nQScX/X3acC0hoy6KVSNn3kRKFDV/zawTcfqcTYiMpTK4zzqZmyzzScBf656wu0AoFBVf492LAZDNHCS9xnfq43xPkO0SNgevzD8R0T2pfJ2xwrgcgAR6Qy8oKqjVDUgIlcDn1D59NdLqrqwmeJ5EkihsjsdYIaqXlEzHqADMKHqcx/wpqp+HI3KG9pXEbkLmK2qk6g0pNdFZAmwhUqTbA6GAecBP4nIj1Vl/wR2q4r1WSoN+EoRCQClwJnNZMb1trmIXFEjlslUPt22BNgOXNgMcRgM0cJJ3md8rzbG+wxRwSzZZjAYDAaDwZAgmFu9BoPBYDAYDAmCSfwMBoPBYDAYEgST+BkMBoPBYDAkCCbxMxgMBoPBYEgQTOJnMBgMBoPBkCCYxM9gGxF5VkSG7VL2ioicFquYDAaDobkx3meIJ0ziZ4iEA6hcLN1gMBgSCeN9hrjBJH4JjogMkcoF2VOrZmNfKCL71LNdHrBYVYMW33V31VWwV0RWiMh9IvKjiMwWkUEi8omILK2e5NNgMBhihfE+Q6JiVu5IcFR1lohMAu4B0oD/qWp9Sx4dCzQ4I76IPAhkAReqqlbN6L5KVfcVkUeAV6iceT6VyqV9no3qjhgMBkMEGO8zJCom8TMA3EXlupQ7gL82sM0xNLzkzm3ATFW9bJfy6nUtfwIyVbUYKBaRMhHJUdVtTYzbYDAYmoLxPkPCYW71GgDaAplUXrWm7vqhiKQDOar6WwP6WcB+ItJml/Kyqn9DNf6ufm8uOgwGQ6wx3mdIOEziZwB4jsor1zeAB+r5/HBguoX+Y+B+4CMRyYp+eAaDwdAsGO8zJBzmyiPBEZE/AxWq+qaIeIFvReQIVZ1WY7NjgXFW36Oq71YZ3yQRGdWMIRsMBkOTMd5nSFREVWMdg8HhiMgPwP6qWhHrWAwGg6GlMN5niEdM4mcwGAwGg8GQIJgxfgaDwWAwGAwJgkn8DAaDwWAwGBIEk/gZDAaDwWAwJAgm8TMYDAaDwWBIEEziZzAYDAaDwZAgmMTPYDAYDAaDIUEwiZ/BYDAYDAZDgmASP4PBYDAYDIYEwSR+BoPBYDAYDAmCSfwMBoPBYDAYEgST+BkMBoPBYDAkCCbxMxgMUUNERorILyKyRERuttjuVBFRERnckvEZDAZDouOLdQCRkJubqz169GjxektKSsjIyGjxehvCSfGYWOonlrHMmTNnk6q2s7v9MYdn6OYtQXvfPb/sE1UdWd9nIuIFngKOAtYAs0Rkkqou2mW7LOBaYKbdGBMd433OigWcFY+JJXLfA/veZ+V7bsRViV+PHj2YPXt2i9ebn5/P8OHDW7zehnBSPCaW+ollLCKyMpLtN20JMvOTrra2Teq0NNfi46HAElVdVhXHWGA0sGiX7e4GHgD+HkmciYzxPmfFAs6Kx8QSue+Bfe8L43uuw9zqNRgSHiWoIVuvMHQBVtd4v6aqbCciMgjopqofRXcfDAaDIVLseV+84aoeP4PBEH0UCGDvVi+QKyI1u57GqOoYO0IR8QD/BS6IKECDwWBoBiL0vrjBJH4GQ4KjKEFVu5tvUtWGHshYC3Sr8b5rVVk1WcA+QL6IAHQEJonIiara8vcxDQZDQhOh9zWIiLwEHA9sUNV96vl8ODARWF5VNF5V72pyxY3EJH4Gg4EQTTc/YBbQR0R6UpnwnQmcXf2hqhYCO8fKiEg+cKNJ+gwGQ6yIkve9AjwJvGaxzVeqenw0KmsqJvEzGBIcBYJRMD9VDYjI1cAngBd4SVUXishdwGxVndTkSgwGgyFKRNH7vhSRHk3+ohYirhI/v9+P3+8nMzOTzMzMuNNVawOBwE69U2ONhc4N7RKrOq1QoCJKA5hVdTIweZey2xvYdnhUKjW46jw153f0dW5oG6f5HkTkfY0e21yDA0VkHvAblXc6Fkaojxpxk/j5/X4KCgoQEVSVvLw8WweJW3Q1teXl5RQUFDg21ljpnN4usarTDvH33Fri4Lbz1Jzf0dc5vW2c6ntg2/usxjbb4Qegu6r6RWQU8D7Qpwnf1yTiZjoXv9+PiJCVlYWI4Pf740pXU+v1eh0da6x0Tm+XWNUZDkUJ2nwZnIfbzlNzfkdf5/S2caLvgX3va3I9qkWq6q/6ezKQJCIxmxswbnr8MjMzUVWKi4tRVdtXBW7R1dQGg0FHxxorndPbJVZ1hkUhaHI61+K289Sc39HXOb1tHOl70GLeJyIdgfWqqiIylMpOt83NX3P9xFXil5eXF/FYALfoamoLCwsj6vJ2yz42Vef0dolVneFQhAokat9naFncdp6a8zv6Oqe3jRN9D6LnfSLyFjCcyrGAa4A7gCQAVX0WOA24UkQCQClwpmoU5pFpJHGT+AGNPjDcoqvW+ny+iPVu2cem6NzQLrGq0woFQqbHz9W46Tw153f0dW5oG6f5HkTP+1T1rDCfP0nldC+OIKZj/EQkR0TGicjPIlIgIgfGMh6DIVEJIrZehuhgvM9gcAaJ6Hux7vF7DPhYVU8TkWQgPcbxGAwJR+VcVvFnbg7HeJ/BEGMS1ftilviJSDZwKFXrdqpqOVAeq3gMhkSlci6ruHnA3/EY7zMYnEGiel8se/x6AhuBl0VkADAHuFZVS2puJCKXAZcBdOjQgfz8/JaOE7/fH5N6G8JJ8ZhY6sdJsYRDEYLxM7OTGzDe1wicFAs4Kx4TS+NIVO+LZeLnAwYB16jqTBF5DLgZuK3mRlWzY48BGDx4sA4fPryl4yQ/P59Y1NsQTorHxFI/TorFDiFNvNsdMcR4XyNwUizgrHhMLI0nEb0vlqnuGmCNqs6sej+OSjM0GAwtSPU4l0Qc5BwjjPcZDA7ArvfFGzHr8VPVdSKyWkT2VNVfgCOBRbGKx2BIVBShQmP9nFfiYLzPYHAGiep9sd7ja4A3qp5qWwZcGON4DIaEJB6vah2O8b44Y9nKlTzy7jus9BeTm5LKRSOO4uAhQ8LqNm/ewn+ef5WlG7bRKjWZ0444iFEjDg+rKy0t5aHHXuTnpes5+pC9GfvuRM48fXQ0dqVeVJWXnnmNGVPnEQyE2OeA3fnrP67A54t1GtE0EtH7YvqLqeqPQFMWPq6F3+9v1AzfbtFVawOBwE69U2ONhc4N7RKrOq1QFYIJ+GRbLDHeF1/nd1FRERc8/hhrdusKrXMAmDPhPcb4fOw/cGCDumAwyEX/92+WpXZGJAd2wI/vfE4gGODEY46yrPOq6+/ll9+zEE82Oyo8PPfuHPwlpVxywZnNso8P3/0Enz79I15NAWDNzHn8vvpfPPjs3c1SX1N1dkhU73N3ql4Dv99PQUEBIoKq2l6+xi26mtry8nIKCgocG2usdE5vl1jVaYdQAl71xgtuO0/j8fx+bty7rO7SqdZZVNyhPc9PmWyZ+L076SOWetrgkT+Ugcy2vPXpV5aJ3/ezfuDnVSE8Kd6dZZ6kVnz46RxbiV+k+1hRUcGXE3/Aq2k7y7ziY+6nS/ntt9/o3LlzVOtrqi4SEtH74ibV9fv9iAhZWVmICH6/P650NbVer9fRscZK5/R2iVWd4VCEcvXZehmch9vO03g8vzdt3454vXXLd5Ra6lav24gnJa1O+eaSHZa6RQW/Isk5dcq3FlnXV02k++j3+ynZXHeqyWCRl2VLl0e9vqbq7GLX++KNuEn8MjMzUVWKi4tRVdtXBW7R1dQGg0FHxxorndPbJVZ1hkOBEB5bL4PzcNt5Go/n96DuPdCSWtMwoqrskdPaUjd8/0FI8eY65b3bZVvqjj3mcHyBDXXKu3e2rq+aSPcxJyeHDrvXjSmjqzB4yH5Rr6+pOrvY9b54I25S2czMTPLy8iIeC+AWXU1tYWFhRF3ebtnHpuqc3i6xqtMOwQScyypecNt5Go/n9+nHHccnc+aQHyqGrCxCO3awx7oN3HLHnZa6IYMGcmzvfD5augXJakMoUEEH/2/ceM11lroOHdpzysi+vD3lFzzJuYCSGlrDNZed3yz7KCJceP1p/Pfvr6AbMwAIZhZz9tUnkJqaGvX6mqqLhET0vrhJ/IBGHxhu0VVrfT5fxHq37GNTdG5ol1jVaUWizl4fT7jpPI3H89vj8fDiHXfw0eefM3vpErp32Y1zr/87SUlJYbX33/w3Rn07gy9nzyM3O5Pzz7iGtLS6t3935dqrLmT4IT8x+dNvaN0qiXGv3ElOTt3bvw0R6T4eNepI+g3ah7Evv0dFRQUnnXkcffbYvdnqa6rODonqfXGV+BkMhsipXK/SWIHB0BREhONHjOD4ESMi1h560AEcetABEesG9O/HgP79yM/PjyjpaywdO3bgulv+0uz1tBSJ6n2Jt8cGg6EWiiTk7Q6DwZDYJKr3mcTPYDDE5QBmg8FgCEciep9J/AyGBEeVhJzE1GAwJDaJ6n0m8TMYEpzK9SrrzkFmMBgM8Uyiep9J/AwGQ0I+2WYwGAyJ6H0m8TMYEhxFCCXgAGeDwZDYJKr3mcTPYDAk5FWvwVAfZWVlvPT+OFYUbqZXTjsuPOlUkpOTw+oCgQBvfTiJBb+vpWNGFpedejoZGRlhdarKxCmfMvOXX8lJS+WS00+mbdu2tmKd/sXXTJ/xI3v37MDqNWvp1rWLLd3s2XOZ8vE3iEc49eQR5OXtaUv3y8+LGf/WFIKBEEefeChD9w+/agfA2jVreePZsewoKeOgYw5gxMgjbOlagkT0PpP4GQwJTqKOczEYdqWkpIQzHriNhT1b4clMJuTfwkf33sLbN99jOalyMBjkvLtu55s2qXjS01C/nw/uvpU3r/8nHdu3t6zzr3ffz9StFXjSs9BQGR/93795+q+Xsk/eXpa6ex9+hgnf/4YnrTWdOoQ498ZH+ddVpzL8EOv5AF94cSyvv/kDHm9lcjlt+hiuuuJITj11lKVu0vjJPPWv9/Fsr5wv8IvxYzj9qoO47Grr1UK+yf+Wey54iIqVHkSEaU/PYOZ133PrAzdb6lqCRPW+uEp1/X4/69ati3ghZ7foqrWBQMDxscZC54Z2iVWdVigQUo+tl8GZuOk8dfL5/dg7/2NRn9Z4Uip7+DypyfzUO5un333TUvfGBxN3Jn0A4vOxtGdnHnnbWvfVdzOZtqkUT3pWpc7jYVObrjz17vuWutVr1vLhzGV40irX5hWgNLUTL7wzxVJXWlrKe+Nn7kz6AFTa8+bY6YRCoQZ1qsqbY6bsTPoAfIFsJr3+DSW7rFG8Ky8/+D8Cq7yIVN5STapIYdoL37Js6TJLXTXN5Xtg3/vijbjp8fP7/RQUFCAiqKrtNR3doqupLS8vp6CgwLGxxkrn9HaJVZ12CJJ441ziBbedp04+v5cXb0Fya/cAic/Hki2bLHULfl+zM+nbqRNhSeEWS9138xegWa3rlC/bXGip+yz/awJpHeqctSvXbbPULVy4iG1FKaTu0nm5bkMFmzZton0DvZPbtm1j46oSkqktLNngY+4P8zj4kIMarHPt4nXALm26JZnpH+fT66pelvE2t+9BdLxPRF4Cjgc2qOo+9XwuwGPAKGA7cIGq/tDkihtJ3KSyfr8fESErKwsRsX114BZdTa3X63V0rLHSOb1dYlVnOFTF9Pi5GLedp04+v3OT01DVWmWqSvsU62Sjc2Y2GgjUKc8W69uIu3ftTGh73R6znGRr3cD+eyOlW+vqMqzHIvbq1ZO01B11yjPTQ5ZLvmVlZdGqbd3v9mWUscee1uv1tulU93sDaWX0H9zfUgfN63tg3/ts8Aow0uLzY4E+Va/LgGeaHHwTiBsnz8zMRFUpLi5GVW1fFbhFV1MbDAYdHWusdE5vl1jVGY7K9Sq9tl4G5+G289TJ5/eVJ5xGh1/X1yrr+Mt6rjzxNEvdpaecRu9V62sljZnL13DpMdbj5k469hj2DhWhNW6z+jb/zjkjDrPU7du/H4N2SyYUrNhZFtq+mdFHWD9s0aZNGw4+aDeCwdKdZYGKYo44PM/yARafz8eIU4YQkD+S1ECojEFHdm+wl7Ca0ZeMIpRVI04N0mdkN4bsP9hSB83re2Df+8J+j+qXgFX37mjgNa1kBpAjIp2isxeREze3ejMzM8nLy8Pv95OZmRmRObhBV1NbWFgYUZe3W/axqTqnt0us6gyPJOTs9fGC285TJ5/fu3XpyuvnX8djE99mbWkR3dJacd0lN9CxQwdLXUZGBm9e/08eeectlmzbTLZ4ufTUczlw8BBLncfj4fV/38FDL75KwW8bSPMKZ/1pFEcfPjxsrE/c90+eGPMaP/6ymlRvR24++yBOO+m4sLp/3fk3XnjxTWbMXIxqkEMO3ocLLzgzrO6qv11M+45tmTZ5JuU7Khh40D785dqLw+rO+PNptGrdig9enUxJ0Xb22r8P1992bVgdNLfvQQTelysis2u8H6OqYyKoqAuwusb7NVVlv0fwHVEjbhI/oNEHhlt01Vqfzxex3i372BSdG9olVnVaUTnAOTpj/ERkJJVjWbzAC6p6/y6fXw9cAgSAjcBFqroyKpUnMG46T51+fvfp2Ysnr7slIg1Ax/bteeBqewlNTTIyMrjjr3+JWJeUlMT1V1UmXvn5+QwfPtyWTkS49JJzuPSSiKvk9LNO4vSzTopYN/KEoxl5wtGRV0jz+R5E5H2bVDV8F6VLiPllvoh4RWSuiHwY61gMhkQliMfWywoR8QJPUTmeZW/gLBHZe5fN5gKDVbU/MA74TzPsjisw3mcwxJ6m+p5N1gLdarzvWlUWE2Ke+AHXAgWxDsJgSFQUIaBeW68wDAWWqOoyVS0HxlI5tuWPulSnq+r2qrczqDTARMV4n8EQQ+x6XxSYBPxZKjkAKFTVmNzmhRgnfiLSFTgOeCGWcRgMibNXLhAAACAASURBVIwqBFVsvaga61LjdVmNr2poHEtDXAxYTzwWpxjvMxhij13vC4eIvAV8B+wpImtE5GIRuUJErqjaZDKwDFgCPA9Efm8/isR6jN+jwE1AVkMbVP3HchlAhw4dyM/Pb5nIauD3+2NSb0M4KR4TS/04KRY7RDDGLypjXUTkXGAwYP34YvxivC9CnBQLOCseE0vjicb4ZlU9K8znClzV5IqiRMwSPxGpnuxwjogMb2i7qidnxgAMHjxY7Q5gjSaRDJxtCZwUj4mlfpwUSzgqFypvuXEsIjICuBU4TFXLolGxmzDe1zicFAs4Kx4TS+OIove5ilj2+A0DThSRUUAq0EpE/qeq58YwJoMh4aicyyoq5jcL6CMiPalM+M4Ezq65gYgMBJ4DRqrqhmhU6kKM9xkMDiCK3ucqYpb4qeotwC0AVVe9Nxrjax6KioqYOvlzdt+zNwMGhp8tvZodO3bw8afT6NAulwMOGLJzrcVwBAIBPp4+ndSUZI44+BA8nsQ7sdxFdK56VTUgIlcDn1A5nctLqrpQRO4CZqvqJOBBIBN4t+p4WqWqJzYqapFTbGy2Q1UnN+b7mwvjfZHz409zKCzaunM+N7v8/GsBBUsKOHToYbRt2za8oIqVq1cxY94cDho4hG5d7D9/tGHjRqbN+JZ98/Zmr9372NYVFxczZXo+u3fvzqABkXn0lKnTSPYoqhqRR0/9LJ/kpCQOP9y+R4dCIfLzv2JHaRlHHX04SUlJtnSqyoxvZ7J+3UaOGTWCtLS08KIWwX09ftHwvViP8TM0My8/9SpvP/g+5SshlB5gj6N247G3Hgp74r3/4Sc8+eonFGpbJLiDXm3e49F/30DHDtaztH/5/ffc9s7brGidgycYYo8PP+TRSy8jr499EzS0PKEordVbZTaTdym7vcbfI6JSUSXPAxPBMvhDd43H4B6Kiop45LWryNjjZ3okXcRD405gUOeLOfFo6zy5oqKC28fcwrp2S0jvlsSkiW9wYNaRXHa69Zh6VeWWZ//D9MByAt2ySBr/CUel7M5dl94QNqm676XneXP5zxR2bEvK3G84IrkVT//9Frxe66dCX3hnHM99M4MtbXLxfTWT/ca+wwu3/ZP09HRL3aSPP+ORsR+zOaktVwzrzulX3cwTt19Pp47Wk01/890s7nt0LBtLWiESotNLH3DPrZfQd++9LHW//LyY229+mg2rfIh6ef6JD7jhn+dw8KEHWOo2bNjIjeffxprvt+Gp8PFij7FcetvZnHh6+MmmW4JoeV8L0mTfc0Sqq6r5qnp8U7/H7/ezbt26iNfzc4uuWhsIBGxply1dxv/ueI/gKh9e8ZFUmsrSiev4z63/tdSVlJTwxKufUOLrgi8pFW9qDitK2nHvf60fQAyFQtw17l1Wd+2CNyMDaZXFr507cfv/Xo9o/xrbpnbbJVr1NeU3bOk6rVCFipDX1sthTFHVi1T1woZeVD5p51iM91nz6oR/0+OoxXTo6cXjEXoPK2XuxmdZv36dpe75cU9TtN8qWvVJw5fqo9XAZGZ4pvLD/NmWujc+HMenbdYR2r0NnpQkgru3YXLWGsZ98oGl7ssZ3/HC+uUU79YRT3ISFZ3aMSVTePR/r1rqVqxaxWPffs+2jl3wJKcQatOW7zNbc9dzz1vqtm/fzsNvTWFbRhe8yamIx8cSOnDX4y9a6kKhEA89+Q7bAp1ISsnAl5zFxh0duf+xNyx1AP+592W2rW1NsjeLJF862zfn8ugDbxGqsdxcfTxw86Os/6aM5EA6PkmmYmUKz97xv4jWXG4O3wP73ucwmux7jkj8ooHf76egoIA1a9ZQUFAQ0UHlBl1NbXl5uS3txLc+RDbXXn/RIx4KvltsqRs/aQp+qX3VKCIsWmo9JGvuvHn8mpJSp3yB309hYaGlFprepnbbJVr1NeU3bMk6w1E5wNney0nYuT2aCLdQ3eJhjdEVhgrweGofdz0GVzD1q3GWuuXbf8WXUvs/7KxeqXzx03RL3fdrf8HbqvbdEE9OOt+tWmipmzJ3NsHc1rV1KcnMXGO9KM27n06ltH3HWmXi8TD3N+vE9v2PPmZbal2PXrDa2qN/+mkBazfXTWSWrPKzZUvDS80WFRWxYvG2OuUb13qYM/sHyzoXz1lZp7c0sCaZCW9PtNRB8/oe2Pc+JxEN34urxE9EyMrKQkQiMiM36GpqvV6vLW1GVjqK1in3JFn/7G2yW6HBug9b+sJc+LRq1YqkivI65UmhkOUC4NU0tU3ttku06mvKb9iSddohhNh6uQUR6Rh+q/jALR7WGJ1H615IVpSFSE9tcBYcAHxad+yZhpQksR6Tliz1j35KFmvzS/H6qJyxozbeespqkpWWBsFgnfJwY7DatM5BK+rxaI/1OZqdnY3XU099nhAp9Vy0V5OcnExScj3fLRVk52Rb1pmcWndvghIgu3WOpQ6a3/fAnve5Bbu+FzeJX2ZmJqpKcXExqhrRQt5u0NXUBoNBW9qzLz6TtL1qH7QVnnIOPnF/S92xI0fQOaOoVlkwUMb+/XtY6vr07s0gX1ItA9RgkP3btLE1mLepbWq3XaJVX1N+w5asMxzV61W67co3DNb3vOIIt3hYY3S75RxCybbaicqyr3I47qgzLXUH9DiU0t9rX4QWzangtCOtdaP3G45nVe27E97l2zht6FGWuguOPY6c1etrlXk2b+OE/vtZ6v588kl03Fh7AQctKWFE3h6WuqOPGE4PX22PDlWUc9Be3eoXVNGjR3f22i25tkeHgvTfow0ZGRkN6lJTU9lnUGdCoT9+C1Wlx54p7LGH9fjtoUf3J6AVtcpy+no5bvRISx00r++Bfe9zEbZ8L24e7sjMzCQvL2/nU1+RmJEbdDW1hYWF5OXlhdVmZmZy58s38+xdL7F83irSc9I45vTDuPKGyy11Ho+Hh+64igcef42fV2wm2QcH7NuDO26+JmyMT133N/455jnmbFiPKOzfoSMP3/j3iPavsW1qt12iVV9TfsOWrDMsKgScN46lSaiqM0aOtwBu8bDG6M45+WpeeaeUxdumsVdbWDWtD+cceaNl7xTA6BEnUzhpG19//Rl+LSLX25GLh55Hxw7WHSKHDD6AG7Zs5I25U1kfKKZjUiv+vN/xDB4w0FLXo9tu/OeYk3h62icsLd5KW28yp/UfxNknjrbUpaen8+jF5/PQuAn8vGkLmT4vI/P24LoLL7DUeTweHrnlKu595jUWrd6EJ5jLsd193HXTtZY6gIfuvYE773uaBYs3gIYYkNeR+/51U1jdPQ/cyL9ue5R5s1ZSURFgj707cOe/bwmru/HOawkEHmbGlHmUFu+g54Cu3HT/NWEfeoFm9j2IO++z63tSX/e0Uxk8eLDOnm09OLc5cNqElI2JJxQKNWpalerjo6En2hqKJZyuOXDS7xTLWERkTiSra7Teq70e8dJptrYdP+yZiL67JRCR3eorV9VVLR1Lc2G8r/GxNNb7wukaiqe56msIVeWLL76IuG0a69FO/T8hUt8D+94Xb74XNz1+BmsaO5deY0/Slkz4DE3HZbczduUjKu/aCJUTIvcEfgH6xjIogzNorPe5RdfSHh1v/ye42Psa7Xsm8TMYEpzqcS5uRVX71XwvIoOI8SLoBoPB+bjZ+5rieybxMxgSHEUIhOLmOS9U9QcRsX6CyWAwJDzx5H2R+J5J/AwGg6umLNgVEbm+xlsPMAj4LUbhGAwGF+FW72uK75nEz2BIdNS9tzuqqDmpW4DKsS/vxSgWg8HgFtztfY32PZP4GQwJjpvHuQCo6r9iHYPBYHAfbva+pvhefNzcNoQl3HqKVrrGTPmjqi2qMzSe6nEudl5uQUQui3UMBmfQFO+LZ11Le7SqNjrW5sKu97kFu75nevzinFmz5vLsM+NZsXwLma2SOeKIfvz1rxeGfbT+12XLueeF11m0YQvpPi+H7tGDO6/9S9hJNzdu2sTNY55h7ubN+DxwYIfO3H/VNWFX7igtLeXOVx5ifslyghoiL60rt539N3LbtI14nw2Roy696rUg7nbIEBn/m/QSM9Z+znaKaOvtxOiB53LwkEPD6sZNncS7C6ayIVhEB282fxpwDCcfEX5e3E+++ZJnv57CitJt5PrSOKPv/lx68p/C6mbNm8dD48fzy7Zt5CQnc2xeHjddGN6jly5fwT3Pv8aidVu46LDBfP7w49x53VVhPXrz5i3c8e+nWbh0I16PsO9enbjr/64hPT3dUrdjxw7uvO1RfpqzmmAgxJ77dOTWO/9C+/btLHXBYJD7b3uEWZ/+RGlJOb36d+H6u6+gzx67W+paijjzPls7455U1gZ+v59169ZFvJ6fW3TV2kAgYEvr9/u5446XWbE8HeiKv6g9E95bzosvjrXUhUIhrn34KWaRRUn77mxs05V3fyvhnqeeC1vnVY89wudZaWzt2Y2N3bsxMQmuf/zRsLpbX7yf7/tspny/HIKD2/DT3iXc9PK9YXXVRNIuu+pi8Ru2dJ3hiLe1elU1/MEaR7jFw5qii+T8nvTZeGamTCRzWBnth6XgPWALr89/hHXrf7fUfT17Bk+t/YgNA5JhUC7rByTx+PKJzJ7/g6VuxepV3PLlOBb0ysDftwsr9mzDw7/PYfxnUyx1JSUlXPfqq8zOzqa4e3dWd+rEmLVrefqttyx1oVCIax98ilmBLEpyuxP0JfPemlLuevwZSx3ADf/3MD+sSKHc141ST1e+/RluufORsLr/u+VhZk8vpcLfgdCOTiyaBTdf/1BY3YP/epz8MQWUrUzDsymbFdP83HrZfQTrWaO4PprT9yC+1uq163txk/j5/X4KCgpYs2YNBQUFES0c7gZdTW15ebkt7ZtvTKC0pPbVmNebzhf58y11H039jGXJtRfQ9iSn8MXPyyx1vy5dypxQRa0rVfF6+WbjBkpLSxvUbd++nfmBVXi8fxyOIsKvrbaydLl1nRB5u+yqi8Vv2JJ1hkPV/Wv1ishxInKTiNxe/Yp1TC2FWzysqbpIzu9Zq74go1NSrbKc/TyMn2590fvB3Gmw2y7LgvXMYsKsTy11r039kKLetb022K4VE+fNsNS9PnEiv3fcZRm5jAw+XrjQUvfptHyWeVrVKvMkJfNlwXJL3YoVKylYVVbboz1efijYSElJSYO6HTt28NOc3/B4/uhNFBGWLipl8eJfLeuc/dkCfFL7t9iyMMTkiR9b6qB5fQ/se59TaazvxVXiJyJkZWUhIhGZiht0NbVer9eWtmT7DkTqdvuXlpbXs/UfbC0sgqS6a2GWlgcsdUXFRVQkJ9UpLxOlvLzhOsvLy6nw1h37EUwTioqL6lHUJtJ22VUXi9+wJesMjxAMeWy9nIiIPAv8CbiGylsdpwPdYxpUC+IWD2uqLpLzO6AVdcrEIwRC1t5XofV7XLla907tCAbqvTVbYuF7AMWlpVDPrdntFXXjr8nmbdsguR6PrrD26MLCQkKhuiO8KgJQVlbWoK68vJyK8rrj+kIhH4XbCi3rLN9Rd1+8+v/tnXl4VNX5xz9vMgQICWsg7AICGlxZFCmg4Iq44C4udS/VanfbuvTXVq1Wa9XW2lap+65VUdzFJe4gILsRxAVlCTshE7LNzPv7YyYySSZ37my592bO53nuk5kz93vPO2fu+ebce8/iY8d2ax1k2vfArve5kVR8z53fKAkKCgpQVSorK1HVhBYO94IuWhsMBm1pp007CtjcKC0UCrLX3tYLlZ963LF037mxUZqqsk/v7pa6kfsfwLAYjcoRHTrRpUuXFnVdu3ZlSLCoWXrxOh8H7Lu/ZZ6QeLk01TnxG7ZmnnZQFVubS/mBqp4HbI+MdBsHDHc4plbDKx6Wqi6R+j0wfy8CtY0baxWra5mw7xGWujF9SwhW1DRKC2yvZuyAfS11Uw44iJyNOxqlhWrrGNMr5nKq33PG0UfTqby8UZqGQhzY07rf3MlTp9C9MoZH97H26P3225f+PZo3Yof07Uj37i1rO3fuzOBhXZulF/WpZ/SYUZZ5Dhu1R7PBIDnFuzj5zBMtdZB53wN73udSkva9NtXwKykpoX///pSUlCRkKl7QRWvz8vJsaYcMGcS5543F59tIMFhHff0WBg+p5Pe/v8JS16lTJ35z8jH02LaWYG0NoZ3bGO7fwJ9/eqmlLicnhz+ecjoDv11PsKoKrdjJnmvWcdN5F8T9br897kd0n19N/ZZd1FdUk/9JBVcefbGt9SsTLZemOid+w9bMMx4NUxp4+JFHQz+CXSLSF6gH+jgYT6viFQ9LVZdI/b7ktJ/Q4ZPB7FhVQ311gK0L6hgVmsKo/cdY6s467jQmbupPaOV2grX16Oc7OHzbYE492rqRcujB47igcBidVm8iVFePb81mJq9VfnOB9SDLPQYM4Gdjx9J13TpCtbXkbNnC6C1buOHyyy11+fn5/Ob0Y+m+PezRGgwwdNcG/vyz+B595eVn0C13PfW1VQRqKinKW8+1vz7fUgfwm2svoFvfbdQFKqkL7KJD1438+upz4nr07276GcVjc6jLqSIQqiOnr5/L/nS2rd8xk74H9r3PpSTte21qVG9BQUFSJ4ZXdA1an89nW3/RRdM57bSpzJlTytChgznggP3ii4CTjzmKYw+byKtvvk1xzyLGHXyQrUW2Dz34YN4aNYrXSt+hY157Jk+YYKvxVjJsb5668l+Ufvw+NbU1HP3rI/D57J+eiZZLtM6J37C187REw31dPMxLItIVuBX4lLCf/9fZkFoXr3hYKrpE6ne7du348+W38/kXZXy++jMmTptEjx7xZwgQEW788dWs+e5bPlm2kHHTDqJ/v/628rz6/B9z8ebNvDPvIw4YO4K9hw6zpfvRaacx/ZhjeLW0lGF77MHI/eM/5QCYdvSRHHPoBF59823yBJ6/66+2PHr8uIN4/qCRzHmzlPZ57Zg0aaItj9577+E88dztvPvuB1TvquGooyfTrl3zrj1N6dWrJw++9G/mzZ3PxvUbOXrqkXFneYgmY74HXve+pH3PsYafiAwAHgaKCQc8U1X/4VQ8bZnOnTtz6qnxb6s3pUOHDpx8/NSEdT6fj+OPPCphXU5ODoePPyxhnSE1FAiqd2/+q+oNkZfPishLQAdVjd+ByCGM97Ueew8rYe9hJQnr9hgwkD0GWD+mjUWvnj058/hpCesKCws544QTEtY1eHRpaamtRl8DPp+PY6ccmXB+OTk5TJ4cf0qcpogIh4w7OGFdpkmn94nIFOAfQC5wr6re3OTzCwg30tZFku5S1XuTzS8V33PS7QPAr1V1BHAIcLmIjHAwHoMhS7H3mNdtjzxEpFnnIlWtjTa/WPu4AON9BoMrSI/vSXgU5b+AY4ERwFkt1OmnVPXAyJZUoy8dvufYHT9V3QBsiLyuFJEyoB/wmVMxGQzZikcfdzwgIpOwnrT0PmBk64RjD+N9BoN7SJP3HQysVtWvAETkSWAamanTKfueK/r4icggwkHOi/HZDGAGQHFxMaWlpa0ZGhAeUu5Evi3hpnhMLLFxUyx2cPHINSu6AAuxNsDNFp85jvE++7gpFnBXPCaW5LHpfUUisiDq/UxVnRn1vh/wXdT7tcDYGMc5VUQOBVYBv1TV72LsE4+Ufc/xhp+IFADPAr9Q1WaTtkUKdybAmDFjdNKkSa0bIFBaWooT+baEm+IxscTGTbHEQxXXzlVlhaoOcjqGVDDelxhuigXcFY+JJTkS8L4tqmo9JDw+LwJPqGqtiPwYeAg4PNGDpMP3HHV7EWlH2PgeU9XnnIzFYMhmVO1thvRgvM9gcAdp8r11wICo9/3ZPYgjko9uVdWGWbLvBUanI/5kcKzhJ+EhSPcBZap6u1NxGAwGz0/g7CmM9xkM7iFNvjcfGCYig0UkD5gOzI7eQUSi59g7EShL25dIECcf9Y4HfggsE5HFkbRrVPUVB2NyLRvKN/Lv/z7J2k0VHDFuL5Yu/4z9940/ELCyspLbH3iEVRu30aVDHuccPZnxYw+Kq6uvr+f2Rx5i0cYN5Of6OOWgsRw/Of5daVXlnmceYeGmleRIDpMGjeKsqSfb+o4vzXmSlRveQQkxoMtBnHHijxKaosCQHIpp1LUyxvsSYOHCt1m58nE6dPgBTz31Liec8Bvy8/Pj6pZ99ilz5j9OXc4OCujP9KmXU9TDekUMgNXffMkjbz3B1uAOeuR248Kjz2HQgEFxdeWbNvKPWY/xbc0OerTL56JJx3PgCOsVPwCqqqr46yMP8fn2LXRt155zDp3EoQfH6h7WmPr6ev7+wMMs+W4DR40Yyotz3uKEo6xXJoGwR//3oSeYt+yr8BRaY/fhrNPsTUHz1NMv8O67ywiFQowaOYRLLjnb1hyAr7/6Fq8+9z61u+oZvl9/Lv/VxeTl5dnKM5Oky/tUNSAiVwCvE57O5X5VXSEi1wMLVHU28DMROZHwqP5twAUpZ5wkTo7q/QDrzokJ4/f78fv9CU/46Had3+/nR7+8ma3Bfoh0YmwN/PyP9/PPGy5m3xEtz1EVDAY5/9obKOtUjEgnqIa5D8/i1ro6jpg43jLPH918I+906YB0DU+0+cGHb7HD7+fcE6znA7z2nlt4u/dGcoeHK/XSrW+z6cmt/Hz6JZa6R577O9uLn6RoXNhEtu5cxl0PreGnF9xoqWvA7/cTCAS+L1e7tPZv71SelkQWKvcqkTto5wBDVPV6ERkI9FbVTxwOLSbG++zrPvroRXZV/ZpJh/lZ8dn+7DX8bh54YDE/+clzlheFS1cs5NllV9H3kDo6AaqruPWxpVw343E6dOjQou7bdd9x9ewbYEzY9zZSxW+fu447z7qZ3r2KW9RVVVVx3n9u4Lv9eyCSA9Twycv3cA+XcsCIfVrUhUIhzv7zdSzuV4R0CTdmP3h5FnfU1XH0hImWZXPZdTfxfqgjOb5OjNMcbn35XbZXVnLeKSdZ6n5/09957bNqcvLC+S2atZj1G7fy68svstT9864HeebZL8j1FQJQ9vlqvllzOzfdeKWl7n9PvMC9N84hp64TAF/NW83qz//Avx682VLXQMZ8D9LqfZELt1eapP0h6vXVwNVpyYzUfM97PbpbwO/3U1ZWxtq1aykrK0toAXC36+57+H9sCfRpZHS1vj7c+/DzlrrnXn6VFbmdI0YUpqZLTx545U1L3YIlS3hf65B2u68L6np049F5H1rqNm/ezPt1X5LbafeVXE6PfF75bj6BQMuLh9fX1/PF9lfp0mt3nJ0657A17122bNlimSfsLtO6ujrX/oZO5mkLtbm5k38TXqfyrMj7SsJzamUFXvCwZHVffvkgI0bs3s/nE34w7hM+/ND65ugb8x+l78jd64aLCP0P28Tzrz9iqXvkjSfQ0Y0bhqEx7Xn4tcctdfe+8DTfjejWyKN3DuvBPW9Yd9+c9cbrLO5egETdNasqLuK+t609etHSZXy8s54c3+6VM4Kdu/Hke3Mtddu2beOdpWvJydv9HSWvkJc/XE5dXfN11hsIBAK8PmfJ940+gFxfBz6eu5ZNmzZZ5jn7idLvG30AOTk+Pv+4gk/mLbTUQSv4HmSl77Wphp+IUFhYiIgkZEZu123aWklOTm6z9M3bd1nqvlpfTm7HTs3SN/mtdQs/W06gqFuz9PJqa93qb76iuqj5Ej472tdRUdHyhOIVFRX4Ojf/vHP/ar5es9oyT9hdprm5ua79DZ3M0w4e7+M3VlUvB2oAVHU74PxzpFbCCx6WrC4np3mjorhY2bjRenq0OtneLC2vQy47qjdY6naG/M3uJIoI2wPWCyKU76pA2jX36E111t9x9fp1SKfmj63Lq6ssdYtWfEawS3OP3lQV53/CV1/jDzVfLm1HDezYsaNFXWVlJTsrQs3S6+rzWbXqS8s8t29uXgbtQoUsWxx/irtM+x6krY+fEyTte22m4VdQUICqUllZiaomtAC423V77dmPQH1NozRVZWDvzpa6sfuVQGXzyjyom7XumPETyd/Q3HCHFFjrDthnP7qWB5ul967pSLduzU2qge7duxOq6N0sffvqruxTEn/dyoYyDQaDrv0NnczTDh4f1VsfmTlfAUSkJ9D8v1QbxQselqwuFBzcLG3VqnbstddkS10n6dssrWp7gIFFLT92BejToSehQONTJ1QfpH9+nxYUYUb0GkCoqrlHD+rYsu8B/GCf/cjZ1ryROqSwi6XuqIkT6LBtY7P0QV2tPXqffUZQlFfTLL1P51yKiopa1HXt2pXi4uZtik75VYwcae3RfQc1XyM52H4Hk4+cYKmDzPseZKfvtamGX0lJCf3796ekpCQhM3K77uwzplHSy0+grjqSonTP+Y5fXnGBpW7S+PFM6t4O3RW+StJQiO5bvuWX555hqRs0cCCn9x2EbAs3GlWVrmvW87Op1v378vPzOX2P8bBm95RkOat2cP7o4yw7AOfk5DBu6A/5bsnuK+YNK5X9ep5hqxN3Q5nm5eW59jd0Ms94qIKGcmxt8RCRKSKyUkRWi8hVMT5vLyJPRT6fF5nAOFXuBGYBvUTkRuAD4KY0HNcTeMHDktUdPPaXvPVWH0Kh8H/f8nLh62+mse++1lOqnX705Xw1pzPB+vD/waqKADvnj2DK4dYDzX500kV0+lgJ1NQDEKiup3CucNG08yx1Zx93EqO/Dn3f+NP6IH0Xb+LKMy+01E0cO5Zj23VCd1aGdaEQxV+v5dennm6pG9C/H6fsPRipbGg0KgWb13H5ycdb6jp27Mj0o8cg1bvn983dVc4FJ0229GgR4dyzj0TYfUMgGNjKqScfRKdOzZ8qRXP+T04mp+t2NNKCqqeSSaeMYMiezRv1Tcmk74F973MpSfueqIubs00ZM2aMLliwIP6OacYNE1IGAgGefOYFVn25gf2G92Hq1ClxKxyEG23Pv/I6n6xcTbf8Dlxyxil0797dVp5z3n+fv2x4ogAAIABJREFUt5YtJt/XjouOP5H+fZtfRccqm08WL+SVT98jV3I4bcIUSobtZSu/L1aX8c78Z1ECjN33OA7cL/7o43ixOIWTsYjIwkQmG20/pJ/2u/FyW/t+ffa1LR47cvW5CjiK8Mz184GzVPWzqH1+AuyvqpeKyHTgZFU9026sLSEiewNHEB408ZaqOjZVQibIZu/bsmUz77wzE59vED16FDJx4gm2RvtXVlby3OsPsCuwlX5dR3DcUaeRm9v8cWxTamtreeylJ9mwayP9Cvpw9nFnxhyB2rRsAoEAT776Ais2fUfvjp25ZNqZtj36hTfe4OMvV9GtfQdmnHyqbY9++/0PeHPBYvbrX8yEcT9gQP9+tnTzFy7m5bc+ICcnh9NPOJKSvYbb0q1c+QXPPvsGgUCIKVPGc/DBzZeEjXXOrFu3nscfeI7qqjrGHz6KI46a1EyXKon6Htj3Pivfc5Jkfc/xlTsM9vD5fJw7/VQgXLHsGAqEr9ROPm4KJx+XeJ5HTZzIUROtR5bF4uADR3PwgYnPTTlsaAnDhv4+YZ0hDbTeepXTgD9FXj8D3CUioqlfgW4E3ifsaR1FZJSqfpriMQ0uoKioJ6effi2lpaUceugk27rCwkLOP+1nCefXvn17Ljr1/IR1Pp+Pc084NWGdiHDSMcdwEsckrD184gQOnziB0tJS240+gINGH8hBow9MOL+99hrGNdcMS1jXr19ffvP7KxLWtQreufcVi6R8zzT8DIasJ6EOzFZrVtpZr/L7fSJzX1UAPYD4w7dbQERuIDwn1pfstnElieWQDAZDNuHqwRuWpOJ7puFnMGQ7ChqybX7pWLMy3ZwB7KmqLc9HYTAYDE1JzPvcRtK+59peiwaDoRVJzzx+cderjN5HRHxAF2BrSrHDcqBriscwGAzZiHfn8Uva92zf8RORztH7q+q2ZDI0GAxuJC1Xvd+vV0m4gTcdOLvJPrOB84GPgdOAt9PQv+8vwCIRWQ40LIKOqloPQ7eJ8T6DoS3j2Tt+Sfte3IafiPwYuI7wJIHRz5GHJBWqwWBwH2m4qrW5XuV9wCMisprwepXTU8+Zh4BbgGWkcf4+430GQxbg3jt68Uja9+zc8bsS2FdVk+58bTAYXIwCaernYmO9yhrAepKyxNmlqnem+ZhgvM9gaNuk0fscIGnfs9Pw+xKwXgfG4GpKP/6I0uVL6VVQyIUnnULHjs2X7InFp8uW8Mai9+nUrgPnTT2dLl2sZ5Nv4MuvV/PG3OfJlVxOnDyd3sXWs943sHHjBt5+70FCoQDjD5nOoD0SnzbAkBwems4zFu+LyF8IP0aOfuSR6nQuxvtcQFVVFe/MuZ+gFrF40YccOHK8LV1dXR2vvvEI/up1DOxzEBPGT7E1/18wGOSFOc/z7fY1DO4xmBOOnGY5uXEDqsorpW+y6LuVDOjSk7OnnkK7ds2XsIzFe/M+5u1lS+jVqZALpp1sa+J6gE+XLuWlDz9ir5492b59u+UKSdF8+dXXPP3SHHy5OZxzynH07WPPozdsKOfx/71EfX2AU048kuHDhtrSVVRU8OhDz+L313DUMeMZNfoAW7rWwMPel7Tv2Wn4XQ18JCLzmhw88QmSDK3OlXfcxrM129HuXdGt23nqT9fwwOW/YMjAPSx1dzx+D8/WLCRnjy5oMMRL/72Sm475CaP3G2mpe/b1x3h/2yMU7ZeLKtz06pucPPxnTP6B9RxVH378Ep+tuYZR48Iz0b+/+DHKVv6OY4+2nvnekCa8a34ADSflIVFp6ZjOxXifw3zzzUrmvj2Dk45cz9xVP6dD9XU8/dipnHHOjZa6rVs3898nzuPAw7+ga34OGzc8yj/umczPf3y3ZeOvpqaGX931M2pH76D9Xnks2zGXN+94ndt+emfMSZwbCIVCXHb771nQt4rcXp0I7vqa5295j/uv+DPdulo3xn5z5+08U7sFLeqKVm7jyT9fw/0zfsHQQYMsdbc98CD3rlhFoKgnP+8WYOp1f+bv5/+QsSOt5+d75H/P88/nP6K+ILxM5qyPb+Pa86Zy3NHW1eW1OaXcctds6nJ6A8LL79zDJdMP4fxzrecu/PTTpfzhdzOpqSwiR3J5ffaDHH9aCb+6coalrtXwrvcl7Xt2RvXeA7wNzAUWRm2uw+/3U15envBCzl7RNWgDgYAt7UcLFjBr11a0e3jgj7Rrx5oh/bjtmacsdevLN/D8tvnk7BG+wye5OVSP7Mp/Sp+21NXU1PDumv/Rc38fIkJOjlB8kPDKskew6r+vqiwuu5PRP9iBiCAi7DNyF9+U30NtbW2LumgSKZemOid+w9bOMy4q9jYXoqqTY2zpmMPPeJ/Duvkf3MYZUzeQlxc+94YPCTGszyxWrVpmqXvulb9xyHGr6Zgf/hfXsw/sMfod3nl3tqXuwefvIzixkvZdwo289l3zqB23g0dffNhS98zrL7JgQDW53cMT6+fmt2ft6M7c+cyDlrpPFi9i1q5NaFGDR/v4dlhfbptl7dEbN23ikSUrCBT1jKQIW3r35x/Pv2Cpq62t5cGXPiBQ2Od7r60p6MfMZ+fE9ej7HnmN+ty+iOQgImheMY/P+ojq6uoWdQAz//UMdf5iciS8aopPuvPK88tZt269pa6BjPoeZKXv2bnj105Vf5VijBnH7/dTVlYWPiFVba/r5xVdtLauro6ysrK42neXLCJY1Hzpn5U7rAclvvbBW4T26tpsrNPX1c0XBY9m6YrFtB9SCTR+lFzdqZxt27bRo0fzxboBtm7dSqduXzVLHzjsW5YvX8To0YfEUO0m0XJpqnPiN2zNPOOiIGkbEtF6iMi5qvqoiMT0J1W9PcUsjPc5rMvLae4LB4wI8OKHbzB8+H4t6gLyVbM7e917wpqv5hNePCY262vWktuu8bJuvg4+vvN/Yxnn0g1fktu3se+JCF9UlVvq3lm8kEBxDI+usJ7h6OW338Hfq3czj165ZXvM/RtYtmw55YGOtG+SvmZHHZs3b6ZXr14xdTt27GDdljpyOjRO37Yrn4ULFzNhwrgW8/z2m21AcaM0CRTx2qtvc/El51rGm1HfA096Xzp8z84dv1dFZIaI9BGR7g1bwtFmGL/fj4hQWFiIiNi+OvCKLlqbm5trS9u/qIhQjKuxQrH+2UsGDyO4sfmxC2j5UQfAwH57ULepeZ8WrWxPYWFhi7rOnTtTXdn8lNq4rpD+/eMv5J1ouTTVOfEbtmae8bF5t899V74N6xYWxtjS8d/BeJ/Duvpg88ekm7aE6NrdemC1hJrr6mpDdGgXu2HTQL40P21UlU4x0qPp0b4ADTZvQeQHre+tDCzqRWhXc4/uLNZrCu87fDi5O3c0S++SFye/gQPoRE2z9ILcoGUf7oKCAjrnN6//7aSKIUMGWebZpWvzPuWB0E722mtPSx1k2vfAtve5i5R9z07D7ywifV3Y/aij9VcLj0NBQQGqSmVlJapq+6rAK7pobTAYtKU967gTKNmwrdEt/HYbNnP2Idado8eNHste6zs1MrJguZ9jB1vfeevduw+9/AdQVx38Pm3XtnqGd/yBZf+YvLw8CvOmsiPqYrW6OkTV1kkUFxe3qGsg0XJpqnPiN2zNPG2RngmcWxVVvSfy8k1VvS56A95KQxbG+xzW9R54Bp+t2t2YCYWU2W/vzcTDWr5rB3Dw/uexaknjARIL3uzPccdcbKk7/bAzqVrQeCGEqk/qOfOIptNRNubiE6bTY2lFo7Scsi2c84NjLXVnHHsc+6yraOLRW5h+0A8sdQePGsmYHEWDu72Wih2cdOD+lrpevXoxcVhPgvW7u9CEaquYvP8g2rdveh9wN+3atWPSuGGEArvHOgUDdYwu6UrfvtYDQ6accBBB3bk7Pw0ycKgyYWLLdwkbyLjvQVb6nsSbO1VEclQ11CStQ2RahlZlzJgxumBBy77r9/vx+/0UFBQkdILE05WWljJp0qRWyy+edu7cuRxyyCG2tJu3bOGWxx/hs21bKBDhzLETOHXKlLi66upq/vbE3Xy281t8QeHoYWP54YlnNtuvadkEAgHu/98/+apyCaGAsnfRWC48/bK4o+lUlRde+g8btrxBMFhHYcdDOHf6teTmWl/5NpBouUTrWvOcyWSeDYjIwkSWVWu/xwDtc9XPbe275ie/SejYrYGIfKqqo+KlJXFc430u8L6PP5jNt18+SV7B4VRXljH1pP+ja9f4CxYs+LSUjxfdT4DN5MmenDTlN/Traz2oDWDZ50t5/J1H2B7aSvfcIn54xAWUDBvRbL+mZfP1d2u466XHWFO9hcJQHueOO5Yjxh8WN7+t27Zx82MPsWLHJjqRw5kHjee0KVPj6qqrq7n53vtZtH4D0/YdAT4fF595RlxdMBjk7/c8yLzPvkE1xIT9h/KzGRfY8uh7H3iC9+aWUVtbz4H7DuC3v/wxPl/ju4yxzpln/vcir700lyp/LcP2Luaqay+3PXI5U74H9r2vrfmenYbf/ap6UdT7TsBsVT0i2YCTJZ75ZQqrf+JO4KZ4TCyxcTKWhBt+Awdon9/9wta+a6640jUGKCLjgB8AvwDuiPqoM3CyqqY0Z4TxPlOnrHBTPCaWJBt+Nr2vrfmenUe960Tk35EMuwFzgEcTD7c5IjJFRFaKyGoRuSodxzQYDIkjam9zGXmE+7T4aNzPZSfh5eBSxXifwdDGyUbfizuqV1X/T0T+KiJ3A6OBm1X12aRDjiAiucC/gKOAtcB8EZmtqp+lemyDwZAg7jO3uKjqu8C7IvKgqq7JwPGN9xkMbR2PeV86fK/FO34ickrDBswjPEngIkAjaalyMLBaVb9S1TrgSazG2RsMhozh0Tt+AKS70We8z2DIHrLR96zu+J3Q5P0ioF0kXYHnks00Qj/gu6j3a4GxTXcSkRnADIDi4mJKS0tTzDZx/H6/I/m2hJviMbHExk2x2MJ9UxY4ifG+CG46j90UC7grHhNLCmSh97XY8FNVV6yVpaozgZkQ7uDsRKdRN3WcBXfFY2KJjZtiiYsLpyxwEuN9u3HTeeymWMBd8ZhYkiSN3iciU4B/ALnAvap6c5PP2wMPE+42shU4U1W/SU/uiWFn5Y5MsQ4YEPW+fyTNYDC0Nh5s+InIP7GI3MVr6hrvMxjcQhq8z2a/3YuB7ao6VESmA7cAzedIi59Xyr5nZ1RvppgPDBORwSKSB0wHrBdSNLQqwWCQeQvmsvqrLxLSqSpLly7g88+t19M0uAcJ2dtcxgLCkyp3AEYBX0S2AyHOMjPOYryvlSgv38C8T95j165d8XeOYtu2bXww93127Gi+OoYVVVVVfDD3QzZusl7esim1tbV8MG8u3373XfydowgGg3z8ySe21zRvQFX5dNFili5fbrlGbyyWL/+MhQs/TVjnVtLke3b67U4DHoq8fgY4QuJNnhiblH2vxTt+kbli5mqGfl1VDYjIFcDrhG+N3q+qKzKRlyFx3p33No/Nv4/AED/BL6HHS/35w3k3xp049fOyhXz60e85aJ9V1O3I4ZH39+XwqXfQr9+g1gnckBwe9HBVfQhARC4DJqhqIPL+buD9ZI9rvM/7BINB7n34V+R1fYPi/pU8PKsPfbtexInHXWapU1XueuxWVgQ+oP2AAI8+52P/jpP4yVnxl2y+59kHeHH9+1T1E/IWBzlIhnH9j64mJ8f6/srjr77IP+e9xdoeHcj31zIhpwv//sXVlitpAMz58ANunP08X+a353fDRnD//13Lf351Jd27NV+uLppFy1bwh7sf4svaPCBESSfl1l9eypBB1pNbr/n2O6667t98WQ6KMKD7k1z7y3MZPcp6tRDXk55abqff7vf7RDygAugBbEkko3T4ntUZeR6wUESeFJELRKR3IsHZQVVfUdXhqrqnqt6Y6vH8fj/l5eUJr+fnFV2DNhAIZDTPmpoaHlpwDx3Hhyjsk0/X4fkExm/l7//7q6VOVfn0o/9j+nFfsuegXEqGC+ecsIJ337g2I3E21WW6XNKhcypPK+yO6HXr6DagG+HJSxsoiKQli/E+F+oSqd/PvnAnex8yi31HV9Oz2MfoiZvx5/ydss+XWupenDOLr/q+T49RPgp6dqDHGB+rerzN66UvW+o+WbyQZ6o+IHhAIR2KCsgZ0YV5A9Zy77MPWeo2lJdz8/w3KR9WjK97F+oG9uKt3rn8+cGZlrra2lr++PxzrOnfB1/37qjPx7ye3bhm5t2WOlXlj3c/zDcd+pDbpQe5XXqyyteLP9x1v6UO4Pq/3se3O4tol19EXn4PNtYUc+Mdj9i+8+c234OEfK9IRBZEbTPSHkziJO17VoM7LgMQkb2BY4EHRaQL8A7wGvChqgZb0rc2fr+fsrIyRARVpaSkxNaSQF7RRWvr6uooKyvLWJ4vvTmbjqNCRF8XSI6wptb6ke+KFUsYXbKKptcTPTsvYefOnXTu3Dm2MMk4m+oyXS6p6pzK0xbeHtl2M7BIRN4BBDgU+FOyBzPe505dIvV7R9XHDO7U2IeG7VPLwrnPUrJ3y3eolq3/hPxR7Rqldeqdx+IlH3MMx7Woe2NJKb7BjWPyFeSx4KvPsGohPP7GK+wc3Ivo2ic+H/M2Wz/ynfXaq6wrLmrktCLCp3EeMa/4rIwvanLxdWicvnxzJTt27GjxiY7f72flNxXQsbBR+rfb2vHposWMHjXSMl/X+h7Y9b4tcVbusNNvt2GftSLiA7oQHuSRLEn7Xtw+fqr6uareoapTgMOBD4DTCc9v5Rr8fj8iQmFhISJi++rAK7pobW5ubkbzbN++PaH6GFdxcf7VtW/fnpra5qdUXX2urTV3Uy3TTJdLqjqn8rSDR/v4AaCqDxB+rDKL8FQr4xoeh6R4XON9LtIlVr+b39NQVUStxzPmSAs+pdb/KnNa+lcatK40eT4fhJp7bU6MtGjyO3aEQHNDljh339q3zyNXm8eUg1p6dE5ODrm5zRtIOQTp2KFDDEVj3Op7kDbfs9NvdzZwfuT1acDbqXQnScX3EhrcoarVkUcUP3XLunUNFBQUoKpUVlaiqravCryii9YGg8GM5nns5OMILGrcvyRQF2TPjs0XKo9m2LASlqzet1FaKKRs3jmSTp06pT3OprpMl0uqOqfytIXa3FxIpIP0kcABqvoCkCciB6czD+N9zusSqd99i45i68bGDZWln3Tm0PE/tNSN3+tIdn5T1yit4st6Dh1xjKXutInHEyrb2SitftMuJg46yFJ3/vEn0eurTY3SdFcNh/YdYqk77ogjGbqt8cATDQQY17uvpW7Y0KHs07nxv33VEAcUd6awsLAFFeTn57Pv0G5ok0bj4J7KiBEllnmCi30P0uJ7kX52Df12y4CnVXWFiFwvIidGdrsP6CEiq4FfASkt1ZiK7zk5nUtaKSgooKSkBL/fT0FBQUInlhd00dqKioqEbnknmqfP5+MXU67i3jf/xea89UhdDoNzSvjtxfH76h11/N954pVr6FGwhPpADlv9ozhl+j8yEmdTXabLJVWdU3nGxd399+zwbyBE+K7c9UAl8Cxg/V+3jeAVD2vN+n38sRfy5LObWLV8Fh0LtlJdMYiRJT9lQP9BlrpDD5nMhpfX8u57s6krqCTP34XJQ09j3JjxlrrhQ4Zx+V6n8cSnL7Mpr5KOVbkc1XsMPzxtuqWuc+fO3DL1bG6fM4tVwV0U1CtHFg/m6isutdTl5uZyx4WXcP2Tj7Giyk9ut14cWxPgr7/+jaUO4LbfXsE1f7+H5Rt3Iqoc0KcLd1wTf/DKX/74c665/k6WrtpCIKgM61/ADdfamzHJlb4HafU+VX0FeKVJ2h+iXtcQfmKQLpL2vTbT8AOSPjG8omvQ+ny+hPWJ5rnPXvtxx153s3PnTtq3bx93hFkDffoM5JyLHsXv95OTk0N+fn5G44zWtUa5pKpzKs+4eLvhN1ZVR4nIIgBV3R553JI1eMXDWrN+Tz/1dwQCv6ayspKuXbtid+aMM4/7IacFz2bnzp106dIl7qjcBk6cdBwnHDaVHTt2UFhYiM9n79/r5LGHMHnsIezYsYP8/Hzy8uyduvuXlPDMdX9m586dLFy4kJ+ca303s4H+ffvy8F+vS9ijO3fuzF1/+z27du0iFAp5wmtt4V3vS9r34p6ZIvJT4FFV3Z5ikAYPEm9ARktktKIa0o5b++/ZpD4ygaoCiEhPwlfCKWG8z/v4fD66xZneJBa5ublJ6UQkKR0Qd6qslujcubPtRm00yXp0ohfzbsfD3pe079m5lCkmPAv10yIyJckJBw0GgyFT3Em4g3MvEbmR8CCMm9JwXON9BoPBrSTte3ZG9f4eGEa4Y+IFwBcicpOI7Jl0uAaDwV14eHCHqj4G/Bb4C7ABOElV/5eG4xrvMxjaOlnoe7Y6L0SGHJdHtgDhSQKfERHrGX0NBoP78fgEziJyH9BBVf+lqnepapmI/CkdxzbeZzC0YbLU9+I2/ETk5yKyEPgr8CGwX2SC09HAqSnEbTAY3ELI5uZOjgEeEpHzotJObGlnuxjvMxiygCz0PTvDjroDp6jqmuhEVQ2JyPH2YzQYDG5EcO9VrU02AZOBR0VkLPBzIB398Yz3GQxtGI97X9K+Z6eP3x+bGl/UZ2WJRGkwGFyKh/v4AaKqFap6ArAZKCW8HFJKGO8zGLKALPS9NjWPn6E5y1d+zq0vPs1K/za6+tpzUslILj3VelJRQ5bh4n4sNvl+aSRV/VPk8ewvHYzH4AIefeEFnpr3CVtrahnSpQs/PfF4xo60XlMWoPTj13h3xRNUyybyKWbSvudw6Nij4urmLZ7Pwx89zYb6zXTN7czUvQ7ntKNOiqv77IuV/O3lJ/iiaitdfB04fuhILj317Li6DRs38qcH7mf5ti2cf8AoPrp3JldddEnceQerqqr4/Z3/ZtG6TeTm5HDIoH788YpLbc8f2Kbwtvcl7XsJLdnmdvx+P+Xl5Qmv5+cVXYM2EAjY0lZXV3PZo//hvT7t2DismJWDu3LrhqU8+MKzGY/VCZ3dcklXfqn8hq2dZ1w83MdPVf/Y5P2Lqnq4U/E4gZfqaWvU7xfmzOHP8xZQ1q0Hm/r0ZW5+J372yKNs3brVUrdk+QLe2XArPSd+y8AJNRRNWMOcb2/hs5XLLHXryzfwlw/uYv0Bu9Axndg+MshDW15gzodvW+pqamq44ol/8vEewpYRRXw5vIB/7FjEA7OtB2eqKjNu/xtvdGzHhv59qWvnY+aWTfzl3nstdQCX33Qrr1blsLF7X9Z37c0zW2r53W32VlcC75wztslC32szDT+/309ZWRlr166lrKwsoUWgvaCL1tbV1dnSPvziLL4d0qNRWqhbIc+vWJjRWJ3S2S0Xp+J0Kk87eHFUr4h8EPlbKSI7o7ZKEdkZT99W8Fo9bY36PeuT+QSaTKS8pbgP9z43y1L3zqJnKd6n8X/6PvsHeWv+05a6J+Y8DQc2Xo/cNzCfl5a8bql79JXnWTe8ycTN3Qt48fMFlrq33n+PFYX5jSZuzsnvyBurV1rqvvtuLQu270Ki7grm+Hy8/80Gdu3aZakF75wziZCNvtemGn4iQmFhISKS0InlBV20Njc315Z2+y4/OXntmqVX1tdmNFandHbLxak4ncrTFq3Qx09EuovIHBH5IvK32RIHInKgiHwsIitEZKmInNliyKoTIn8LVbVz1FaoqsktOeNBvFZPW6N+V9XXN0uTnBz8dXWWuiA1MdMDLaQ3UB2qi7l6RlWg2lK33b8TyWve4yqeR6/btAmNsYJGZZzvt3nLFmpym/9P2KXhJ0Tx8Mo5kxAe6+OXDt9rMw2/goICVJXKykpUNaFFoL2gi9YGg0Fb2mnjJ5H33eZGaRoKsW/noozG6pTObrk4FadTecbFbqMvdQO8CnhLVYcBb0XeN2UXcJ6q7gNMAf4uIjHXsoo0JFvcUo7WI3itnrZG/d6vuBcaDDZKk+3bOGqUdR+//l32o9rfWFe1I8Ae3Q+01I0bOoa68sZ3zEL1QYYVDLLUTRt/OHnfNH78rKqMKOhpqTvlmCl037CxWfqIbtan/QH778dgmjeKh3XKo0ePHjEUjfHKOWMbDw5qS4fvtZnBHQUFBZSUlOD3+xNa1NkrumhtRUUFJSUlcbUlw4Yzo/9+PPDNEvx79EK2+9lvYzXX/+ZPGY3VKZ3dcnEqTqfytEMrrVc5DZgUef0Q4VFov4veQVVXRb1eLyKbgJ7AjhjHW0jYlmNNYaDAkJQj9gBeq6etUb9/e+GFfH79DcyXHEJdutJh00ZOGzyIQ8eNs9SdfvwF3PLfpfj7f0rPoblsXBmkU/lYTv6R9WCLI8ZPZu598/mocjnthhZQt76K/t904Ze/uMJSN3zPoVzUZzQPr17AriE9YMcu9vq2lut+eb2lrrCwkF8eOonb3itlR9/eaCjEkDVrue6nP7fU5ebm8pvTTuD6p2axuWtvCIXoU7GRa2dcYKlrwCvnTCJ4cK3elH2vzTT8gKRPDK/oGrQ+n8+2/tfnXshZGzbwwjtvsucBAzlq4qEJLejtlbJJtFzSkV8qv2Fr5xmPBPqxFIlIdAekmao606a2WFU3RF6XE14Lt+WYRA4G8oAvY32uqoNt5tvm8VI9bY363aFDBx6/6Ube+/hjVqxezTFnnMqQQYPi6nJycrj6x39n6YpFLF0+n8P2Gcc+J+5nK89rL/4tq79eTen899l3zxEccsZYW7pfnHUBZ5Qfwwulc9hz2ECOuugwWx597gkncsKhh/HUKy/TK78Tr//1b+Tm5sbVHX3YRCYcNJqnX3yZ9nntOPW4XyU0otcr54xd3NaHLx7p8D1HGn4icitwAlBH2NQvVNVYV/SGNNC3Tx8uO/uHTodhcDP2zW+Lqo5p6UMReRPoHeOjaxtlp6oiLVuuiPQBHgHOV9W41+SR/oLDgA5RebwXT9faGO9rXQ4dNy7uXb7p96n3AAAXwElEQVRY7L/PSPbfJ/7UL00ZOngoQwcPTVjXt3cfLpt+Xvwdm9ClSxdmnHU2paWlthp9DeTn53PBmacnnF+bxGMNv2iS9T2n7vjNAa5W1YCI3AJcTZNHPgaDoZVIYz8WVT2ypc9EZKOI9FHVDZGG3aYW9usMvAxcq6pz4+UpIpcQnrW+P7AYOAT4GHDjlC7G+wwGt+DCPnx2ScX3HBncoapvqGog8nYu4cANBoMDNCxb1ArTGswGzo+8Ph94oVksInnALOBhVX3G5nF/DhwErFHVycBIYvcJdBzjfQaDe7DrfS4lad9zQx+/i4CnWvpQRGYAMwCKi4spLS1tpbB24/f7Hcm3JdwUj4klNm6KxQ6tZG43A0+LyMXAGuAMABEZA1yqqpdE0g4FeojIBRHdBaq62OK4NapaIyKISHtV/VxE9src10gbxvsSwE2xgLviMbEkj4sbdvFI2vcy1vCz6uujqi9E9rkWCACPtXScSMfxmQBjxozRSZMmpT/YOJSWluJEvi3hpnhMLLFxUyy2aAXzU9WtwBEx0hcAl0RePwo8muCh10amfHkemCMi2wk3LB3BeF9mcFMs4K54TCwp4N2GX9K+l7GGn1VfH4DI1fzxwBGq6t2iNxjaAh6ugap6cuTln0TkHcILlb/mYDzG+wwGr+DRGpiK7zk1qncK8FvgMFWNv06MwWDIHOrJuawaERndNgCojGz7Ap86GlQMjPcZDC7C496XrO851cfvLqA94duTAHNV9VKHYjEYsh4P93NBRG4ALgC+YveS6oo7R/Ua7zMYXIRXvS8V33Ok4aeqiU90ZAO/35/UDN9e0TVoA4HA93q3xuqEzgvl4lSecfGo+UU4A9hTVa0XKnUBxvtM/c6Ezgtl40rfAy97X9K+54ZRvWnB7/dTVlaGiKCqtpf28YouWltXV0dZWZlrY3VK5/ZycSpPO3j1qjfCcqArLcwL2NbxWj019Tv9OreXjVt9DzztfUn7niPz+GUCv9+PiFBYWIiI4Pf725QuWpubm+vqWJ3Sub1cnMozLkr4QYGdzZ38BVgkIq+LyOyGzemgWguv1VNTv9Ovc3vZuNL3wL73pYCIdBeROSLyReRvtxb2C4rI4shmx7+S9r02c8evoKAAVaWyshJVTWgRaC/oorXBYNDVsTqlc3u5OJVnPBomMfUwDwG3AMtwc/M0Q3itnpr6nX6d28vGjb4HreZ9VwFvqerNInJV5H2s1XqqVfXABI6btO+1qYZfSUlJwn0BvKKL1lZUVCR0y9sr3zFVndvLxak8beHtht8uVb3T6SCcwmv11NTv9OvcXjau9T1oDe+bBkyKvH4IKCU9yzQm7XttpuEHJH1ieEXXoPX5fAnrvfIdU9F5oVycyjMe4u3p5N4Xkb8QXhKutiFRVV03nUum8FI9NfU7/TovlI0bfQ9se1+RiCyIej8zMsG6HYpVdUPkdTlQ3MJ+HSJ5BICbVfX5OMdN2vfaVMPPYDAkgcfnsiK8RiWEFylvwK3TuRgMBrdg3/u2qOqYlj60Wq2nUXaqKtLiw+U9VHWdiAwB3haRZar6pUVMSfueafgZDAbPPuoVkVxgtqre4XQsBoPBg6TB+6xW6xGRjSLSR1U3iEgfWhiFq6rrIn+/EpFSwg27mA2/VH2vzYzqNRgMySNqb3MbqhoEznI6DoPB4E1awfdmA+dHXp8PvNAsBpFuItI+8roIGA981tIBU/U9c8fPYDB49o5fhA9F5C7gKaCqITGb+vgZDIYkybz33Qw8LSIXA2sIT7yMiIwBLlXVS4AS4B4RCRG+IXezqrbY8IuQtO+Zhp/BkO14v49fwxQI10elmT5+BoPBmlbwPlXdChwRI30BcEnk9UfAfgkeOmnfMw0/gyHL8fo8fqo62ekYDAaD9/Cy96Xie6aPn8FgAFV7mwsRkS4icruILIhst4lIF6fjMhgMHiALfc80/AwGg2cHd0S4H6gk3HfmDGAn8ICjERkMBk+Qjb5nHvUaDNmOggSdDiIl9lTVU6PeXyciix2LxmAweANve1/Svtem7vj5/X7Ky8sTXsjZK7oGbSAQcH2sTui8UC5O5RkXtbm5k2oRmdDwRkTGA9UOxtPqeKmemvqdfp0XysaVvgdZ6Xtt5o6f3++nrKwMEUFVba9b6BVdtLauro6ysjLXxuqUzu3l4lSednDx4ww7XAo8HOnfIsA24AJHI2pFvFZPTf1Ov87tZeNW3wNPe1/Svtdm7vj5/X5EhMLCQkTE9tWBV3TR2tzcXFfH6pTO7eXiVJ5xUTw9uENVl6jqAcD+wH6qOlJVlzgdV2vhtXpq6nf6dW4vG1f6Htj3PheSiu+1mTt+BQUFqCqVlZWoqu2rAq/oorXBYNDVsTqlc3u5OJWnHbw8j19kxvtTgUGAT0QAUNXrLWRtBq/VU1O/069ze9m41ffAu96Xiu+1qYZfSUkJfr+fgoKChE4sL+iitRUVFQnd8vbKd0xV5/ZycSrPeHh5LqsILwAVwEKg1uFYWh2v1VNTv9Ovc3vZuNH3wPPel7TvtZmGH5D0ieEVXYPW5/MlrPfKd0xF54VycSpPS1z8OMMm/VV1itNBOImX6qmp3+nXeaFsXOd74HXvS9r3HO3jJyK/FhGNLEpsMBgcQkL2NpfykYgkutyRoxjvMxjcQTb6nmN3/ERkAHA08K1TMRgMhjAeftwBMAG4QES+JvzIQwBV1f2dDSs2xvsMBvfgYe9L2vecfNR7B/Bbws+pDQaDUygQ8q77Acc6HUCCGO8zGNyAt70vad9zpOEnItOAdaq6pGEkisW+M4AZAMXFxZSWlmY+wCb4/X5H8m0JN8VjYomNm2KxhWe9D1R1jdMx2MV4X/K4KRZwVzwmlhTwqPel4nsZa/iJyJtA7xgfXQtcQ/hRR1xUdSYwE2DMmDE6adKkdIVom9LSUpzItyXcFI+JJTZuisUO4t2rXtdhvC8zuCkWcFc8JpbkyUbvy1jDT1WPjJUe6Yw4GGi44u0PfCoiB6tqeabiMRgMLePhfi6uw3ifweAdstH7Wv1Rr6ouA3o1vBeRb4AxqrqltWMxGAy4fT3KNoPxPoPBZWSp97WpefwMBkPihCcxzUL3MxgMWU22ep/ja/Wq6qB0XfH6/X7Ky8sTXs/PK7oGbSAQcH2sTui8UC5O5RkPCaqtLaU8RLqLyBwR+SLyt5vFvp1FZK2I3JVSpi7GeF9iOlO/W9Z5oWzc6Htgz/vaGm3mjp/f76esrAwRQVVtL1/jFV20tq6ujrKyMtfG6pTO7eXiVJ5xab3HHVcBb6nqzSJyVeT971rY9wbgvVaJyuN4rZ6a+p1+ndvLxpW+B1n7qNfxO37pwu/3IyIUFhYiIravDryii9bm5ua6OlandG4vF6fyjI/uXroo3pYa04CHIq8fAk6KtZOIjAaKgTdSzTAb8Fo9NfU7/Tq3l407fQ9se18bo800/AoKClBVKisrUdWEFoH2gi5aGwwGXR2rUzq3l4tTedpB1N4GFInIgqhtRgLZFKvqhsjrcsKNu8ZxiOQAtwFXpvqdsgWv1VNTv9Ovc3vZuNX3wLbvtSnazKPegoICSkpK8Pv9CS3q7BVdtLaioiKhW95e+Y6p6txeLk7lGRclkX4sW1R1TEsfxpnDbneWqioS01J/AryiqmvjTXBsCOO1emrqd/p1bi8bV/oeJOp9bYY20/ADkj4xvKJr0Pp8voT1XvmOqei8UC5O5RmXND3OaGkOOwAR2SgifVR1g4j0ATbF2G0cMFFEfgIUAHki4lfVq9ISYBvFS/XU1O/067xQNq70PWiTj3Lj0WYe9RoMhhRQm1tqzAbOj7w+nxhr1arqOao6UFUHEX7c+7Bp9BkMhoyRYd8TkdNFZIWIhETE6mnJFBFZKSKrI4PfMoZp+BkMBkTV1pYiNwNHicgXwJGR94jIGBG5N9WDGwwGQ6K0gu8tB07BYpYCEckF/gUcC4wAzhKREalm3BJt6lGvwWBIAgVaoZ+Lqm4FjoiRvgC4JEb6g8CDGQ/MYDBkJ63gfapaBhCnz/LBwGpV/Sqy75OEZ0H4LBMxmYafwZDlCGm5qjUYDAZPkYD3FYnIgqj3M1V1ZhpD6Qd8F/V+LTA2jcdvhGn4GQyGrOzgbDAYDDa9L+nZDFS1WV9mpzENP4PBYBp+BoMhO0mD91nNZmCTdcCAqPf9I2kZwTT8DIZsJ0vnsjIYDFmOe7xvPjBMRAYTbvBNB87OVGZmVK/BYGitJdsMBoPBXWTY90TkZBFZS3iO0pdF5PVIel8ReSUcggaAK4DXgTLgaVVdkVLGFrSpO35+vz+pGb69omvQBgKB7/VujdUJnRfKxak8rTGNOq/jpXpq6nf6dV4oG/f5HrSG96nqLGBWjPT1wNSo968Ar2Q0mAhtpuHn9/spKytDRFBV28vXeEUXra2rq6OsrMy1sTqlc3u5OJVnXBTT8PMwXqunpn6nX+f2snGl70HWel+bedTr9/sREQoLCxER/H5/m9JFa3Nzc10dq1M6t5eLU3naQYJqazO4D6/VU1O/069ze9m41ffAnve1NdrMHb+CggJUlcrKSlTV9lWBV3TR2mAw6OpYndK5vVycytMWWXjV21bwWj019Tv9OreXjWt9D7LS+9pUw6+kpCThvgBe0UVrKyoqErrl7ZXvmKrO7eXiVJ5xUSCUfebXVvBaPTX1O/06t5eNK30Pstb72kzDD0j6xPCKrkHr8/kS1nvlO6ai80K5OJWnNWZwh9fxUj019Tv9Oi+Ujft8D7LV+xzr4yciPxWRz0VkhYj81ak4DAYDEArZ2wwpY7zPYHARWeh7jtzxE5HJhBcgPkBVa0WklxNxGAwGsvZxhxMY7zMYXESWep9Tj3ovA25W1VoAVd3kUBwGgwEFbXtXtS7FeJ/B4Bqy0/ucavgNByaKyI1ADXClqs6PtaOIzABmABQXF1NaWtpqQTbg9/sdybcl3BSPiSU2borFFlnYz8UhjPcliZtiAXfFY2JJgSz0vow1/ETkTaB3jI+ujeTbHTgEOAh4WkSGqDb/BVR1JjATYMyYMTpp0qRMhdwipaWlOJFvS7gpHhNLbNwUS1wUCGbfVW+mMN6XGdwUC7grHhNLkmSp92Ws4aeqR7b0mYhcBjwXMbtPRCQEFAGbMxWPwWCwIAuvejOF8T6DwUNkofc5Nar3eWAygIgMB/KALQ7FYjBkOTYWKU/DYuUGwHifweAistP3nOrjdz9wv4gsB+qA82M96jAYDK2A0ianLHApxvsMBreQpd7nSMNPVeuAc53I22AwxCALzc8JjPcZDC4jC73PsQmcM4Hf76e8vDzhhZy9omvQBgIB18fqhM4L5eJUntZoeC4rO5vBlXipnpr6nX6dF8rGfb4Htr2vjdFmlmzz+/2UlZUhIqiq7XULvaKL1tbV1VFWVubaWJ3Sub1cnMozLgqahXNZtRW8Vk9N/U6/zu1l40rfg6z1vjZzx8/v9yMiFBYWIiK2rw68oovW5ubmujpWp3RuLxen8rSFuePnWbxWT039Tr/O7WXjWt+DrPS9NnPHr6CgAFWlsrISVbV9VeAVXbQ2GAy6OlandG4vF6fyjIsqBIPpO56hVfFaPTX1O/06t5eNK30Pstb72lTDr6SkBL/fT0FBQUInlhd00dqKioqEbnl75TumqnN7uTiVpy3MwFLP4rV6aup3+nVuLxvX+h5kpfe1mYYfkPSJ4RVdg9bn8yWs98p3TEXnhXJxKs94aBaObGtLeKmemvqdfp0XysaNvgfZ6X1tquFnMBiSoW1OUmowGAzWZKf3mYafwZDtKFnZz8VgMGQ5Wep9puFnMGQ5CmgbHLlmMBgMVmSr95mGn8GQ7ahCFs5lZTAYspws9T7T8DMYDFl51WswGAzZ6H3ipfXBRWQzsMaBrIuALQ7k2xJuisfEEhsnY9lDVXva3VlEXiMcrx22qOqU5MIyJIvxPsBdsYC74jGxJOh7kJD3tSnf81TDzylEZIGqjnE6jgbcFI+JJTZuisVgSBY3ncduigXcFY+JxZAIbWbJNoPBYDAYDAaDNabhZzAYDAaDwZAlmIafPWY6HUAT3BSPiSU2borFYEgWN53HbooF3BWPicVgG9PHz2AwGAwGgyFLMHf8DAaDwWAwGLIE0/AzGAwGg8FgyBJMwy8GIvInEVknIosj29QW9psiIitFZLWIXJXBeG4Vkc9FZKmIzBKRri3s942ILIvEvCDNMVh+VxFpLyJPRT6fJyKD0pl/VD4DROQdEflMRFaIyM9j7DNJRCqifr8/ZCKWSF6WZS5h7oyUy1IRGZWpWAyGVHGT9xnfa5aX8T5DelBVszXZgD8BV8bZJxf4EhgC5AFLgBEZiudowBd5fQtwSwv7fQMUZSD/uN8V+Alwd+T1dOCpDJVFH2BU5HUhsCpGLJOAl1rpXLEsc2Aq8CogwCHAvNaIy2xmS2Zzk/cZ32sWj/E+s6VlM3f8kudgYLWqfqWqdcCTwLRMZKSqb6hqIPJ2LtA/E/lYYOe7TgMeirx+BjhCRCTdgajqBlX9NPK6EigD+qU7nzQyDXhYw8wFuopIH6eDMhhSoFW8z/heY4z3GdKFafi1zBWR29P3i0i3GJ/3A76Ler+W1qmEFxG+ioqFAm+IyEIRmZHGPO181+/3iZh1BdAjjTE0I/JYZSQwL8bH40RkiYi8KiL7ZDCMeGXu1HliMCSLG73P+F4UxvsMqeBzOgCnEJE3gd4xProW+A9wA+ET+wbgNsLG40g8qvpCZJ9rgQDwWAuHmaCq60SkFzBHRD5X1fcyE7GziEgB8CzwC1Xd2eTjTwmv2+iP9FF6HhiWoVCypswNbQM3eZ/xvcQx3mdIlaxt+KnqkXb2E5H/Ai/F+GgdMCDqff9IWkbiEZELgOOBI1Q15uSLqrou8neTiMwi/KgiHRXRzndt2GetiPiALsDWNOTdDBFpR9j4HlPV55p+Hm2GqvqKiPxbRIpUNe0Lh9so87SeJwZDqrjJ+4zvJYbxPkM6MI96Y9CkH8LJwPIYu80HhonIYBHJI9yxd3aG4pkC/BY4UVV3tbBPJxEpbHhNuGN0rLiTwc53nQ2cH3l9GvB2S0adCpH+M/cBZap6ewv79G7oZyMiBxM+z9NuxjbLfDZwXmSE2yFAhapuSHcsBkM6cJP3Gd9rjPE+Q7rI2jt+cfiriBxI+HHHN8CPAUSkL3Cvqk5V1YCIXAG8Tnj01/2quiJD8dwFtCd8Ox1grqpeGh0PUAzMinzuAx5X1dfSkXlL31VErgcWqOpswob0iIisBrYRNslMMB74IbBMRBZH0q4BBkZivZuwAV8mIgGgGpieITOOWeYicmlULK8QHt22GtgFXJiBOAyGdOEm7zO+1xjjfYa0YJZsMxgMBoPBYMgSzKNeg8FgMBgMhizBNPwMBoPBYDAYsgTT8DMYDAaDwWDIEkzDz2AwGAwGgyFLMA0/g8FgMBgMhizBNPwMthGRu0VkfJO0B0XkNKdiMhgMhkxjvM/QljANP0MiHEJ4sXSDwWDIJoz3GdoMpuGX5YjIQRJekL1DZDb2FSKyb4z9SoBVqhq0ONYNkavgXBH5RkT+IiKLRWSBiIwSkddF5MuGST4NBoPBKYz3GbIVs3JHlqOq80VkNvBnoCPwqKrGWvLoWKDFGfFF5FagELhQVTUyo/u3qnqgiNwBPEh45vkOhJf2uTutX8RgMBgSwHifIVsxDT8DwPWE16WsAX7Wwj7H0PKSO/8HzFPVGU3SG9a1XAYUqGolUCkitSLSVVV3pBi3wWAwpILxPkPWYR71GgB6AAWEr1o7NP1QRPKBrqq6vgX9fGC0iHRvkl4b+RuKet3w3lx0GAwGpzHeZ8g6TMPPAHAP4SvXx4BbYnw+GXjHQv8acDPwsogUpj88g8FgyAjG+wxZh7nyyHJE5DygXlUfF5Fc4CMROVxV347a7VjgGavjqOr/IsY3W0SmZjBkg8FgSBnjfYZsRVTV6RgMLkdEPgXGqmq907EYDAZDa2G8z9AWMQ0/g8FgMBgMhizB9PEzGAwGg8FgyBJMw89gMBgMBoMhSzANP4PBYDAYDIYswTT8DAaDwWAwGLIE0/AzGAwGg8FgyBJMw89gMBgMBoMhS/h/QblV4CsKqYUAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "metadata": { "id": "kA707hclMEoj" }, "source": [ "### Input 2: Measured signals\n", "In the following, we inspect the measured signals of the detectors. Again, we have 14 x 14 measurements (a few are zero as no signal was measured) that form a single event. We process the signal using a logarithmic re-scaling.\n" ] }, { "cell_type": "code", "metadata": { "id": "41_XzMnyMEok", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "b13a04f4-b5f5-41ee-daba-a8756f6b2aff" }, "source": [ "# signal map\n", "S = f['signal']\n", "S = np.log10(1 + S)\n", "S -= np.nanmin(S)\n", "S /= np.nanmax(S)\n", "S[np.isnan(S)] = 0\n", "\n", "print(S.shape)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(100000, 14, 14)\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "8MH4JaVhM0AA" }, "source": [ "#### Plot four example events" ] }, { "cell_type": "code", "metadata": { "id": "AAS9bA1kMEom", "colab": { "base_uri": "https://localhost:8080/", "height": 513 }, "outputId": "f2c8ab20-7281-4082-fcd9-2c151628a64d" }, "source": [ "plt.figure(figsize=(9,7))\n", "\n", "for i,j in enumerate(random_samples):\n", " plt.subplot(2,2,i+1)\n", " footprint=S[j,...]\n", " xd, yd = rectangular_array()\n", " mask = footprint != 0\n", " mask[5, 5] = True\n", " marker_size = 130 * footprint[mask] + 20\n", " plot = plt.scatter(xd, yd, c='grey', s=10, alpha=0.4, label=\"silent\")\n", " circles = plt.scatter(xd[mask], yd[mask], c=footprint[mask], s=marker_size,\n", " cmap=\"autumn_r\", alpha=1, label=\"loud\",\n", " edgecolors=\"k\", linewidths=0.4)\n", " cbar = plt.colorbar(circles)\n", " cbar.set_label('normalized signals [a.u.]')\n", " plt.xlabel(\"x / km\")\n", " plt.ylabel(\"y / km\")\n", " plt.grid(True)\n", "\n", "plt.tight_layout()\n", "plt.show()" ], "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "metadata": { "id": "5xk9pp_2MEon" }, "source": [ "### Labels\n", "Now, we can prepare the targets of our neural network training." ] }, { "cell_type": "code", "metadata": { "id": "8BbUO5g0MEon" }, "source": [ "axis = f['showeraxis']" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "SELMHC0xMEoo" }, "source": [ "core = f['showercore'][:, 0:2]\n", "core /= 750" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "t3TMaOzfMEoo", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "d53d38e7-5847-4e8a-a1c9-21083e2aaf91" }, "source": [ "# energy - log10(E/eV) in range 3 - 100 EeV\n", "energy = f['energy']\n", "print(energy)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "[ 4.00461776 5.99159294 7.49367551 ... 10.81657107 5.07542798\n", " 43.32910954]\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "7AXjf80PRHnx" }, "source": [ "---\n", "#### Training and test data\n", "We further split the data into one large training set and a smaller test set. This test set is used for the final evaluation of the model and is only used once to ensure an unbiased performance measure.\n", "\n", "\n", "Before, we combine our input `X` by concatenating the maps of arrival times with the maps of signals." ] }, { "cell_type": "code", "metadata": { "id": "LRWu-MIBMEon" }, "source": [ "X = np.stack([T, S], axis=-1)" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "djv28NqyMEop" }, "source": [ "X_train, X_test = np.split(X, [-20000])\n", "energy_train, energy_test = np.split(energy, [-20000])" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "hPuYYDR1MEoq" }, "source": [ "---\n", "## Define Model\n", "Now, we will set up a neural network to reconstruct the energy of the particle shower. In this **define step** we will set the architecture of the model.\n", "\n", "\n", "> **Modification section** \n", "> Feel free to modify the model.\n", "> For example:\n", "> * Change the number of nodes (but remember that the number of weights scales with n x n. Also, the final layer has to have only one node as we are reconstructing the energy, which is a scalar.).\n", "> * Change the activation function, e.g., use `relu, tanh, sigmoid, softplus, elu, ` (take care to not use an activation function for the final layer!).\n", "> * Add new layers convolutional layers.\n", "> * Add new pooling layers, followed by other convolutional layers.\n", "> * Add fully-connected layers (remember to use `Flatten()` before).\n", "> * Increase the Dropout fraction or place Dropout between several layers if you observe overtraining (validation loss increases).\n", "\n", "\n" ] }, { "cell_type": "code", "metadata": { "id": "osFl4FlNMEor" }, "source": [ "model = keras.models.Sequential(name=\"energy_regression_CNN\")\n", "kwargs = dict(kernel_initializer=\"he_normal\", padding=\"same\",)\n", "\n", "model.add(layers.Conv2D(16, (3, 3), activation=\"relu\", input_shape=X_train.shape[1:], **kwargs))\n", "model.add(layers.AveragePooling2D((2, 2)))\n", "model.add(layers.Conv2D(32, (3, 3), activation=\"relu\", **kwargs))\n", "model.add(layers.Flatten())\n", "model.add(layers.Dropout(0.3))\n", "model.add(layers.Dense(1))" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "kYCXaKAlTnY4" }, "source": [ "We can have a deeper look at our designed model and inspect the number of adaptive parameters by printing the model `summary`." ] }, { "cell_type": "code", "metadata": { "id": "gI2q65DlTvow", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "870dd6a2-5d5a-4ec0-9ced-382af4acafa1" }, "source": [ "print(model.summary())" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Model: \"energy_regression_CNN\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", "conv2d (Conv2D) (None, 14, 14, 16) 304 \n", "_________________________________________________________________\n", "average_pooling2d (AveragePo (None, 7, 7, 16) 0 \n", "_________________________________________________________________\n", "conv2d_1 (Conv2D) (None, 7, 7, 32) 4640 \n", "_________________________________________________________________\n", "flatten (Flatten) (None, 1568) 0 \n", "_________________________________________________________________\n", "dropout (Dropout) (None, 1568) 0 \n", "_________________________________________________________________\n", "dense (Dense) (None, 1) 1569 \n", "=================================================================\n", "Total params: 6,513\n", "Trainable params: 6,513\n", "Non-trainable params: 0\n", "_________________________________________________________________\n", "None\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "LvP_7f3kT6qC" }, "source": [ "### Compile\n", "We now compile the model to prepare it for the training. During the **compile** step, we set a loss/objective function (`mean_squared_error`, as energy reconstruction is a regression task) and set an optimizer. In this case, we use the Adam optimizer with a learning rate of 0.001.\n", "To monitor the resolution and the bias of the model, we add them as a metric." ] }, { "cell_type": "code", "metadata": { "id": "neGTmqafXVV2" }, "source": [ "def resolution(y_true, y_pred):\n", " \"\"\" Metric to control for standart deviation \"\"\"\n", " mean, var = tf.nn.moments((y_true - y_pred), axes=[0])\n", " return tf.sqrt(var)\n", "\n", "\n", "def bias(y_true, y_pred):\n", " \"\"\" Metric to control for standart deviation \"\"\"\n", " mean, var = tf.nn.moments((y_true - y_pred), axes=[0])\n", " return mean" ], "execution_count": null, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "bgigKtfOMEor" }, "source": [ "model.compile(\n", " loss='mean_squared_error',\n", " metrics=[bias, resolution],\n", " optimizer=keras.optimizers.Adam(learning_rate=1e-3))" ], "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "1gO22y3jUfos" }, "source": [ "---\n", "### Training\n", "We can now run the training for 20 `epochs` (20-fold iteration over the dataset) using our training data `X_train` and our energy labels `energy_train`.\n", "For each iteration (calculating the gradients, updating the model parameters), we use 128 samples (`batch_size`).\n", "\n", "We furthermore can set the fraction of validation data (initially set to `0.1`) that is used to monitor overtraining.\n", "\n", "> **Modification section** \n", "> Feel free to modify the training procedure, for example:\n", ">* Change (increase) the number of `epochs`.\n", ">* Modify the batch size via `batch_size`.\n" ] }, { "cell_type": "code", "metadata": { "id": "uj1ecZz7MEos", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "b6447b4d-e5e5-40c1-dd70-73830301b86d" }, "source": [ "fit = model.fit(\n", " X_train,\n", " energy_train,\n", " batch_size=128,\n", " epochs=20,\n", " verbose=2,\n", " validation_split=0.1,\n", ")" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Epoch 1/20\n", "563/563 - 4s - loss: 325.0489 - bias: 0.1453 - resolution: 16.1507 - val_loss: 41.0953 - val_bias: -1.8066e+00 - val_resolution: 6.0990\n", "Epoch 2/20\n", "563/563 - 2s - loss: 26.2303 - bias: 0.2216 - resolution: 4.9965 - val_loss: 14.7234 - val_bias: 0.0060 - val_resolution: 3.7989\n", "Epoch 3/20\n", "563/563 - 2s - loss: 16.7429 - bias: 0.2401 - resolution: 4.0058 - val_loss: 10.8091 - val_bias: 0.5168 - val_resolution: 3.2092\n", "Epoch 4/20\n", "563/563 - 2s - loss: 14.0478 - bias: 0.1709 - resolution: 3.6538 - val_loss: 9.3699 - val_bias: 0.6542 - val_resolution: 2.9514\n", "Epoch 5/20\n", "563/563 - 2s - loss: 12.3605 - bias: 0.1044 - resolution: 3.4159 - val_loss: 8.2507 - val_bias: -3.3918e-01 - val_resolution: 2.8145\n", "Epoch 6/20\n", "563/563 - 2s - loss: 11.3349 - bias: 0.0742 - resolution: 3.2860 - val_loss: 7.8655 - val_bias: -5.4563e-01 - val_resolution: 2.7143\n", "Epoch 7/20\n", "563/563 - 2s - loss: 11.1673 - bias: 0.0648 - resolution: 3.2315 - val_loss: 7.1230 - val_bias: -2.4382e-01 - val_resolution: 2.6214\n", "Epoch 8/20\n", "563/563 - 2s - loss: 10.6519 - bias: 0.0579 - resolution: 3.1750 - val_loss: 6.8807 - val_bias: -2.6234e-01 - val_resolution: 2.5734\n", "Epoch 9/20\n", "563/563 - 2s - loss: 10.4120 - bias: 0.0506 - resolution: 3.1250 - val_loss: 7.0425 - val_bias: 0.1974 - val_resolution: 2.6064\n", "Epoch 10/20\n", "563/563 - 2s - loss: 10.0534 - bias: 0.0560 - resolution: 3.0791 - val_loss: 6.4224 - val_bias: -4.1669e-02 - val_resolution: 2.4973\n", "Epoch 11/20\n", "563/563 - 2s - loss: 9.6740 - bias: 0.0448 - resolution: 3.0231 - val_loss: 6.5501 - val_bias: -3.7965e-01 - val_resolution: 2.4976\n", "Epoch 12/20\n", "563/563 - 2s - loss: 9.5946 - bias: 0.0489 - resolution: 3.0021 - val_loss: 6.4533 - val_bias: 0.1407 - val_resolution: 2.5026\n", "Epoch 13/20\n", "563/563 - 2s - loss: 9.2457 - bias: 0.0452 - resolution: 2.9682 - val_loss: 6.3114 - val_bias: 0.0585 - val_resolution: 2.4759\n", "Epoch 14/20\n", "563/563 - 2s - loss: 9.2130 - bias: 0.0433 - resolution: 2.9524 - val_loss: 6.5115 - val_bias: 0.6209 - val_resolution: 2.4414\n", "Epoch 15/20\n", "563/563 - 2s - loss: 8.9590 - bias: 0.0444 - resolution: 2.9150 - val_loss: 6.8284 - val_bias: 0.1688 - val_resolution: 2.5692\n", "Epoch 16/20\n", "563/563 - 2s - loss: 9.0625 - bias: 0.0413 - resolution: 2.9099 - val_loss: 6.0376 - val_bias: -4.2200e-01 - val_resolution: 2.3852\n", "Epoch 17/20\n", "563/563 - 2s - loss: 8.6702 - bias: 0.0395 - resolution: 2.8638 - val_loss: 5.9992 - val_bias: 0.2017 - val_resolution: 2.4051\n", "Epoch 18/20\n", "563/563 - 2s - loss: 8.8129 - bias: 0.0379 - resolution: 2.8662 - val_loss: 7.5701 - val_bias: -1.1417e+00 - val_resolution: 2.4691\n", "Epoch 19/20\n", "563/563 - 2s - loss: 8.8486 - bias: 0.0373 - resolution: 2.8626 - val_loss: 5.8710 - val_bias: 0.3706 - val_resolution: 2.3622\n", "Epoch 20/20\n", "563/563 - 2s - loss: 8.5313 - bias: 0.0360 - resolution: 2.8242 - val_loss: 5.5853 - val_bias: -2.3838e-01 - val_resolution: 2.3197\n" ] } ] }, { "cell_type": "markdown", "metadata": { "id": "iknMUMavMEos" }, "source": [ "### Plot training curves" ] }, { "cell_type": "code", "metadata": { "id": "iqt6hivFMEot", "colab": { "base_uri": "https://localhost:8080/", "height": 334 }, "outputId": "a11e0d2a-e620-4038-8db2-ccf958ad5046" }, "source": [ "fig, ax = plt.subplots(1, figsize=(8,5))\n", "n = np.arange(len(fit.history['loss']))\n", "\n", "ax.plot(n, fit.history['loss'], ls='--', c='k', label='loss')\n", "ax.plot(n, fit.history['val_loss'], label='val_loss', c='k')\n", "\n", "ax.set_xlabel('Epoch')\n", "ax.set_ylabel('Loss')\n", "ax.legend()\n", "ax.semilogy()\n", "ax.grid()\n", "plt.show()" ], "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "metadata": { "id": "-3j0ScknMEou" }, "source": [ "---\n", "### Performance of the DNN\n", "After training the model, we can use the test set `X_test` to evaluate the performance of the DNN. \n", "\n", "Particularly interesting are the resolution and the bias of the method. A bias close to 0 is desirable. A resolution below 3 EeV can be regarded as good." ] }, { "cell_type": "code", "metadata": { "id": "aObX1rK3MEov", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "85744db1-68bb-4620-8486-0c296df8c8c8" }, "source": [ "energy_pred = model.predict(X_test, batch_size=128, verbose=1)[:,0]\n" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "157/157 [==============================] - 0s 2ms/step\n" ] } ] }, { "cell_type": "code", "metadata": { "id": "DZoXjUnDg6pB", "colab": { "base_uri": "https://localhost:8080/", "height": 297 }, "outputId": "5465144c-4255-4276-e689-b8c3c98fc912" }, "source": [ "diff = energy_pred - energy_test\n", "resolution = np.std(diff)\n", "plt.figure()\n", "plt.hist(diff, bins=100)\n", "plt.xlabel('$E_\\mathrm{rec} - E_\\mathrm{true}$')\n", "plt.ylabel('# Events')\n", "plt.text(0.95, 0.95, '$\\sigma = %.3f$ EeV' % resolution, ha='right', va='top', transform=plt.gca().transAxes)\n", "plt.text(0.95, 0.85, '$\\mu = %.1f$ EeV' % diff.mean(), ha='right', va='top', transform=plt.gca().transAxes)\n", "plt.grid()\n", "plt.xlim(-10, 10)\n", "plt.tight_layout()" ], "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" } } ] }, { "cell_type": "markdown", "metadata": { "id": "xxTIoNH4O9ng" }, "source": [ "After estimating the bias and the resolution, we can now inspect the reconstruction via a scatter plot. \n", "\n", "Furthermore, we can study the energy dependence of the resolution. With increasing energy, the performance increases due to the lower sampling fluctuation of the ground-based particle detectors and the larger footprints." ] }, { "cell_type": "code", "metadata": { "id": "RSVhxnNFZ2Ro", "colab": { "base_uri": "https://localhost:8080/", "height": 559 }, "outputId": "d603d5dd-1189-429d-dfd7-f4b4100e2571" }, "source": [ "x = [3, 10, 30, 100]\n", "labels = [\"3\", \"10\", \"30\", \"100\"]\n", "\n", "diff = energy_pred - energy_test\n", "\n", "# Embedding plot\n", "fig, axes = plt.subplots(1, 2, figsize=(20, 9))\n", "axes[0].scatter(energy_test, energy_pred, s=3, alpha=0.60)\n", "axes[0].set_xlabel(r\"$E_{true}\\;/\\;\\mathrm{EeV}$\")\n", "axes[0].set_ylabel(r\"$E_{DNN}\\;/\\;\\mathrm{EeV}$\")\n", "\n", "stat_box = r\"$\\mu = $ %.3f\" % np.mean(diff) + \" / EeV\" + \"\\n\" + \"$\\sigma = $ %.3f\" % np.std(diff) + \" / EeV\"\n", "axes[0].text(0.95, 0.2, stat_box, verticalalignment=\"top\", horizontalalignment=\"right\",\n", " transform=axes[0].transAxes, backgroundcolor=\"w\")\n", "axes[0].plot([np.min(energy_test), np.max(energy_test)],\n", " [np.min(energy_test), np.max(energy_test)], color=\"red\")\n", "\n", "sns.regplot(x=energy_test, y=diff / energy_test, x_estimator=np.std, x_bins=12,\n", " fit_reg=False, color=\"royalblue\", ax=axes[1])\n", "axes[1].tick_params(axis=\"both\", which=\"major\")\n", "axes[1].set(xscale=\"log\")\n", "plt.xticks(x, labels)\n", "\n", "axes[1].set_xlabel(r\"$E_{true}\\;/\\;\\mathrm{EeV}$\")\n", "axes[1].set_ylabel(r\"$\\sigma_{E}/E$\")\n", "axes[1].set_ylim(0, 0.2)\n", "plt.show()" ], "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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GZAP00zUyl3PDWhs1xnyc4SlzTuB71tqXjDFfAp631v7UGHMd8BOgAHiXMeaL1torAYwxlzFcOVU95tL/ZowpBgywH/iL8/JAIiIiMmOZ4RluM8O1115rn3/++ekehojIJSGx6tmS4pzkSmhyZlKDmnMZ4KULBseGQqcKDtN+tz/6EdEP3sqJ2fPYcvtX+es73s6h1n4e3dPEravL2LSm/JyN/1SMMS9Ya689LzeTSdPfwURERGa21/t3MFU+iYjIWTldRc6l4PVWf6Xr33QubKtu4GBzHx39weT1U++VCJcermlkW3UDxhg2r12c3L+8xMteX89wjyhr4YEH4J57CFy7mu0f/zpvu3wBVXUtLC/xcl35bFbMz0veWxVxIiIiIjKWej6JiMhZmWg1tkvJ6foxnW+JHlK9gQjGwHDLnvE2VJTizXTxcmsfv2s6ycHm3lHPUN/upyg3gyOtvfCJT8A998B730verl/zdx++4ZSr6F1o70REREREpp8qn0RERM7ShVT9Vevr5t6dB/G4HJTOyuKKud6040pUJsWtJT/bA4R5w/z85LHbd/t45vcnyIyG+czDD8ALz/Hb9R/i5++7i/UnBllVnsmGilK+9tQhegNhnA7DvldDvOm+Z1g0O5v115Ri4IJ4JyIiIiJyYVD4JCIicpbOxbS5czVNraquJblC3R0pU+jSHdfYOYg300XFwlksK/FSc6STyppGACprGrBd3Ty08z7e2FLPV97xF/z7Net5Q/fQqGblRzoGiFoY6gkQjMaJWzgZ6GN2jofvbvrDs34OEREREZl5FD6JiIhMwlT1MkqdpjbRdU9178S+5SXeZMXRqa7T3h/Em+ni+suLqG/3s+toF79rOkkgHONQaz9L/e184dFPM8/fxY8/8wC/KrqG9ywtIhyNJ6uZtlU3ELcWY2H+rExO9AUJhONkuR0TTvUTERERkUuXwicREZFJmExIdDYmmrqXGjhV1bWw/1gve309bN24ctT9E+MycNpVB6vqWhgMxVhSnJPs25Sb4STb48QfjDL30Is88MSXcFjLX276Kuv+93qeTbOKnTGGnAwXVy+YxR1rF/NkXQvLSrwcbvdrup1cFL70r10c74iwcI6bz320aLqHIyIiMuMpfBIREZmEqervNNHUvdSwa0NFKXt9PXhcjmQj70QwlRjXshIvH9m+N7lyXeoxq8oLR1U9LSvxsutoF7kZTm5YWgzGsPrgf/L3P/4qnbkF/J/3fZGmwgXU1zRSc6Rz1DW/9vQrNHUPUjY7Ozm971JuOi8Xp+MdERqaI9M9DBERkUuGwicREZFJSA1ZpmoKXqoNFaVUVjfQ7g9xqLWfssJsHMawfqQSKhFMJaqd7t15kO6BUDKgsjBq1bl7dx7E43RQsWgW9e1+WnuHCEfjYLr4o/96nE2PP0h96VK+8NGv4PQWkD8YJhSNUdvYQyxu6R0Mc6JviBN9IYyBcGxg1HjPxzsRERERkYuTwicREZEzVFnTyIHmXjr9oSkLWlaVFyZDph17mijKzWBJcU7yfqlVWFV1LXhcDrI9TublZ1Hf5iduLYW5GcmwKhqL0+EP8v7rFgLw8xdbyXYabvjJt9m0+8fsvWoND93xJS5fUMTWjVdz+yP7eOHVHiKxGG6nk5dP9OEwBsdIS6eCLA+V1Q1U1jTSMxCi3R8iP9ONGRm7iIiIiEiCwicREZERk63esdaCHfl9CiWm1N181dxR/ZQSVVi1vm627Dwwqtl4VV0Lzx5qBwsr5uWxqryQQ639/PxAKwXZHg63+7FAeZ6LO7/3Zf7k5Wr+7Q/eSdWmT7O0tCB5D2stbqeDstnZtPlDuHEQisa5ZuEs3vXG+ew60smhNj99gQhDkRjZbifZbifLSrxs2XlAFVAiIiIikqTwSUREZMRkm4rfuW7J6+7/NJmga6J+SolzO/whWnuHxjUi7/SHsNYmx7fraBcOA4Oh6HBVVE8PX/jeZ/kD3wH+4cYP8y+r/oySgQj3jIxl+24fLx7vJRCO0jcUpiDbw1A4xmXFuSyf62XTmvKRqXtBegfDZLkN+dlubl1dxo49TXicDlVAiYiIiEiSwicREZERk20qfi6abL+e1fMSq9/1DYUJR+MEIlHuenw/D77/mrRjs9bicTpxOw3hRh8PPPK3lPW08pUPfpafXbmO7KEogXCMrz11CIzhxeO9xIeLuwDoD0b4m3esGFV9taGiFAO8/7qFye3bqhvoHgiR7XFq1TsRERERSXJM9wBEREQuFKvKC9m68eopqdhJTJGr9XUDw+HNkuKcswppNlSUEo7Fyc/24HE5iMUhEIrycE3jqHsk3LluCTe9oYTPzAux47t3MXegm4/d+mV+duU6Fs7OwZvtxuNy0OYP8VJrHxZwGMhyO/A4DW+Yl8+K+XmkTjJcVV7I+opS6keCp1XlhRgz0hAKg4iIiIhIgiqfREREzoOxlU6vp3pqOCRbSWV1A7GYJRSJcVlRLt0DIV483ktHf3DUtVeVF7Lq8PPw4VsIefP58ie/AQsvZ/PlRRxu9yd7Si0r8fKzF1s50Rdk89rFrJifl6wES1epNXbb5rWLubdrEI/TcVYVXSIiIiIyMyl8EhEROUuTbVAO6af0jT1/ouul276qvJBt1Q009Qzichh6hyLMynJjDCkVSCO+/3244w648koe+Pg/8vxgBn0n+olby53rloy616Y15aNOTd1XWd1AfZufj2zfy53rlrChopTK6gba/SFqfd3JUOz19sMSERERkZlF0+5ERETOUmrlz+kkpvQByalxY89Pd71aXzf37jzI7qNd3Lvz4KgpdcYYstxOrAWP08GsbDdvW1HCHWsXDx9gLXzhC/CRj8Bb3gK7dvGWt/0B4VicQCjK75pOjrtm4p63P7KPj2zfO2rfq90BGjoHkucBzMnLZCAYpbK6gS07DwBM2dRFEREREbk4qfJJRETkLC0v8bLX18PNV82d9DmJgKmyugELeDNdrK8opdbXTXt/cNTnqroW2vuDeJwOOvuDlM7OHhVU3XB5ESXeDJaVeJNNv5OhTyQCd94J3/8+z7/53cQf2sYf5uWxKg9uW13GA8/U4w/F8LjGT5GrqmvhQHMvWJL7qupa8DgdOI1hKBIjEo3z5Eg11pN1LbT7QzR2DvJwTeOkq8FEpkMgGKd/MA5A/2CcQDBOdqb+PVZERGQqKXwSERE5S/XtfopyMzjc7p/0OYmwZt+rPRzrCXDlvDxWlReyZecBBkMxlhTnJD83dg7izXQxf1YmWR4nA6Eoz9V3UN/mx+V0YID1FaVU1jRi7XA78FpfN0/99jB3VX6WWTX/zSM3fZjvvuU2ojtfosR7FIcxvNo9iD8UwxgIRmLjpgLWt/kJRWK4HYZlJd7kuDv9IfqGwrhcDk4OhVlW4k0GTH+78wCtvUHmz8rEH4yq55NckA4eDbLlW50MhYf/99LVG+N9W1r4yl8Vs/LyzGkenYiIyMylf+YRERE5S6dasW7s6nYJiel3g+EYkZjllTY/tb7ucdfaUFFKJBrj5RP99AyGcTsdnOgbwh+K8Wr3IF0DIZaVeJNVSgeb+3iyroVf/aqOTVs+jPc31Tzxl5/nsT/5CL1DEQKhKIdO9PNSaz/dg5Hhless3H3TcmDsVMABBkIx+kMxfnO0KznuYm8G+Vke/EMRHMCuI53AcKXU8ZNDhOOWoUj8rFfxE5lKgWCcLd/qJBCyjGS1WAuBkB0OpILx6R2giIjIDKbKJxERkbOUbsW61Olyg6FY2gqgWl838/IyOTkQotibwZN1LeP6JK0qL6QvGMUfjGKAdcuKWTHPy2+OdOHNdOFxOTnc7md5iZfqw53kuB0Efvcid337U3iH/Bz57r+zYN1bmT+yIt7xnkGiMcusbBfB6PB/ZGe6HWxaU87Gb+/mpdY+Drf5+fTNV1Bd30H/UJRIzFJ37CTbd/uoH7mXAbI9Tho6/RxKCc7qT/TT7g9xxw2LxzUtF7kQ/PqFAHGbfl/cDu9/55rc8zsoERGRS4TCJxEREc5s5bpTnZPo6eTNdI2rAKr1dbOtuoFX2vzkZ7lZs7SYOd6M5DGJ/X2B4cokgyUv0zUu0Kn1dSdXlKuqa2FhQTal+2v54vbPEnJl8PB93+OvN72PWl83h9r8dPlDRGIWC3QNRvBmOAmEY5QWZFHr66atb4hYHE70BVlVXsjmtUvY+tTLhGMQisTZsacJj8tBdX0n8/IziVtLdoab/Cx3Mjj7m3euoKquhRXz887ZdyJyLrV0RAiG06dPwbClpTNynkckIiJy6VD4JCIiM87ZBEmpK829nnMSPZ3Wp7l3VV0LB5v7iMRiZLud3LF28bhG3y+82jPcjwlwOw3XLy1mxfw8tuw8wPISL/XtfjZUlCZXzgPwffNfee93P0d7cSn/dNeDvOc91yev1xsIEY6N/g/uoUiMxcU5dPpDfGzH8xTmZgCGzWsXU+vrprKmgVgcnAbys93ctrqMHXuaGAxFeKk1TKbbQbbHSbbbySttfj6yfS/AhJVeIheC0jluMj0mbQCV6TGUFrunYVQiIiKXBoVPIiIy45xNkJQaGqWTGmgl7pGYhpZ6TrqpeKn36OgPYowZFzwl9lfXdxCOWoLROJGopWcglHye6sOdRGJxOv0hACqrG/jjp3Zwy48fgrVrmV9VxdcLCpLXW17iBWtwYMGAARxmuM9NQ8cgxoDDYXA6I1y9YBa7jnZRWdNA31AUh4E5eZk88P5rWFVeyIr5eVRWN9AbiHCibwiX08Hhdj9Oh8HtdLBodja9Q5EzWvlP5Hx685uy+c5/nEy7z2GG94uIiMjUUPgkIiIzQmo4dCZBUiIAOlVoBKMDLQs0dg5iYFQF0qmuf7p7JM7ZvHYJO/Y00dY3RDAS55U2P1cvnMWS4hzC0RiNnQO83NpH5a8P847Kr/De2p9xYM0fc/UzT0JGxqhr1rf7KSvMoal7kGjcDlcreZy09YfAQIbLwYKCLAZCMXoGwxw/GSASjZOf5WJevpf8bDdPHzzBvTsPcsPSIubkZbJ53RIA7t15kIIcD7G45Yq5XjAmGUiJXIiyMx185a+Kk6vdWQvGQJbH8JW/KiYrU+vwiIiITBWFTyIiclEaG/CkhkNjm3ePdTaVUctLvOz19XDzVXNZMT9vXLiVOp5010/sT506t6q8MLm9wx9iYKS5+NaNK3m4ppHdRzqxxvCbI108+8kbqfV1c+/Og3jjYT7+0GeoqKvh6ZtvZfY3HxgVPA1PnWvk5GCY+bMyef91C/nN0S6stdywtJifvdhKU/cgBTkeBkJR8rM8FGS7mZ0zC2stm9ctST7DEy80gzE88btmFszKZq+vh60bV7J148pR0wsTfag8Lgdvvf85bltdpsbjcsFZeXkmP/5KKZvuO0HnyRhFs5xs/7t5Cp5ERESmmMInERG5KI0NeE5X7ZTqTI5NqG/3U5SbweF2P5vWlKft55QYz4aKUh6uaaStP0itrzsZju0/1svPX2xlQUE2BkaFZrkZTpYU57CsxEtVXQvXX15E90CIDn+IW1eXJe+zIOLnnm99mitb6tlz1xeouf5P2eAY/R/OlTWN7D7SRabbwTtXzmPTmvJRQdCmNeV8ZPtedh/twuUwZHtcbF63ZNQzHWrtZ6+vhzWXF3G0Y4Drlxax60gXHpdjwtX5VpUX8tb7n6PDH+LRPU0Kn+SClJXpIC/HQefJGHk5DgVPIiIi54H+v62IiFyUNlSUjlpNblV54WkrnhLO5NiJ7neq/avKC7HAwZY+Hq5pTO4Px+LMzvEQicWT10mct3ndErZuvJr6dj+NnYMjK8w5WbesOBni7PrP3/Llf/gLlrY1cvf7Pssd3lXsP9bLk3Uto8ZirU02BV9fUUqtr5stOw9Q6+tOHmOMIcvtJD/Lw62ry6isaeQj2/dS6+um1tc9fH+ng9k5Hp795I184d1XsXXjSioWzmJZiXfc9RJuW11GiTdjVGAmIiIiIpc2VT6JiMhF6XQ9mhLOZuW7ydxv7HVXlRdyqLWfe3ce5LbVZVhrCUdivNzal6x+Sqwad+vqslHXaveH2FbdALxWlXXzVXM53O5/Lezas4dPfP7/EAzH+ML/+wZ7Zy9httlLANYAACAASURBVNMxKshKuHPdklGVXffuPIjH6UhWW23f7eNQax9LinP59M1XjKqUSvS08rgcRKLxtM3Ub39kHweae+n0h8a907FVViIiIiIiCp9ERGRGS0xre7imkW3VDRhj2JxmpbmzvW5qX6cde5qSU85uXV3GPl8PbqcjeUx9ux+Py8GOPU2smJ+XnHb3/KvdBCNxegfDLJ+XN64vFFVVxG/5AP0FxTz37Ucw7kI2l3iT4VS6Z0kEWsYYPC4HfYEI7f5QsqrpZCBCbyDCtpEV7FIrpYDkKn5je1ZtqCjFWgt2uMJKREREROR0NO1ORERmtMS0tri1HGzu42Dz+Glqp5JuylrqdVMrg1KnnNW3+1lQkI3b6Rg1xS4cjeMZCaQS29wOB9ZCU08gOeUuEWzx0EOwcSO+0iXcsul+7m+M0dg5yOF2P8tKvNy78yDbd/tGja2qroUDzb0cbO7j5ECIvqEIoUiU1t4hnqxr4bbVZbgdBofDcLC5j4JsN9deNpsr5uUB6aclpoZtd65bwk1vKEmufDfROxIRERERAVU+iYjIDDHR9LrEVLFaXzeVI5VA6fo2TXT+RCvjpZv2lzrlrNbXjYFkA/GEy4pywNpRvaoWFebwcmsfhTkelhTncPNVczlyoo8P/MdD8MOHeWXVm/nzG/+agDODnGgcb6aL9RWl3Lvz4Kjm3qkr6nX6Q1hr6Q1E6BkI43QY+gIR2vqDrK8o5e63L6dyVyNzvRmjVrebaAXA1NX+xj772aweKCIiIiKXDoVPIiIyI0wmAJmTlzlh76eJzj+blfHgtXBqy84DNHYOUlndwKE2P4OhCNddNjq8mZXtJtPtZCAUHZ7qNi8HNm2Bxx/nsevexd+t+ygOl4tY3DLHm8kcbwYADgOxWJzrlxYln2H/sV72+nrYunElq8oL+cj2vbgchpiNMzc/k8FQjCfrWmjrDxKJxinI8STHMtFzpjYgP9zuH7f/bN+RiIiIiFwaNO1OREQuWGcynSt1Gly68xLBzL07D6a93kSr2a0qL2R9RSlVdS1nNa0scd3jPQFO9AYZCMboGQixZecBtu/2cfsj+6hv68cfjBIIR/nKo7vpX/cWePxxHrr5Dj73tjvB6SQet7xtRQkVi2Ylp9u19gaJxi3PvNROra+bDRWl9A2F6R4IUTnSwPzOdUsoyc/kssJcDNA1EMLjcvBKm59AOML+473c/sg+gAlXAKyqaxluQJ6muXniHZ3p6oEiIiIiculQ5ZOIiFywzmQ6V+pUsES1Uep5GypK2evrweNypL3eqVazS21anm5qXq2vO20z81pfN1996hDt/hADQxEcBjJcDgpyM9h/vJequmaicUskNtzg29t+gm/s/CLZ3a388K6v8p+L/heZvQEGgjGKvR5m53jYuvFqtuw8gMflIG7jWCyDoQhP1rWwrMRLbyCCw2EwxiSf4YalRew60kWmdeBxOnjihWZm53hwGgexuOVgcy+V1Q0Trgq4oaJ0XAPy0z27iIiIiEiCwicREblgne10rnTnDVfnrJz09VIDp57BME3dg4QjMZxOBx39wXE9jw4292EMo4KtqroWXj7RT8xCfqaLuVlusj1OekaagDuMA0McJ5YVbUfZ/sQXyYhF+OWDP2Dxn9xERV0LfUNhgpE4PYNhlpV4k8/X6Q+R6XLgMIZZ2e5kDygLxOOWuLVU1jQyEIzSNRCiKDeDk4MhGrsGyc1w4nY6uPvty9l1pBNjDBbYf3z0lL3Ud5du1bvEan3pnl1EREREJEHhk4iIXLDSNfV+Peed6npjQ5VEgNXWH+T4yQADoShxCyYW41Cbn+27fdS3+9lQUcqGilIOt/k50RdMBkS1vm46/CEWFWRxMhBhUWEOs7LdHGzpozcQ4eoF+QD0BiLM/5/n+NrjX6Y/J4+tdz9E5vw3sHVkrNt3+3jgmXoKcjzJfkuJ0McfjLKkOIetG68Ghlfbe3hXI8FwlBN9QebnZyYbmB9u9/OLDj/WQjhqkyvybV63JNmQ/d6dB5Mr8U30niprGjnQ3EunP5R8Tx39QXpHmpnX+roVQMkFb+Ec96jfRUREZGopfBIRkRlpotXrJpI6xS/xecNIhdTDNY30DIQwxnCiL0h+ppsde5ooys1IVlL1DkXIz3InA6KquhYGglGuKy+krT/I7iOdhGLgBBYXZydDnyc+9gU2/PuX8c0t54Vv7yAzlj2qMmvTmnJWzM8bVbGVCLZyM5ysryhl+24fO/Y0cdvqMtYuK2b/sV4i0fioYGnX0S7CkRgOh2HFvDzq2/3JRuiJZ51MZZi1FuzI74xvrK7qJ7kYfO6jRdM9BBERkUuKwicREZlREqFTe38wubLbZMKQ1Kl6qUHU2Ebatb7uZH+lw+3+5PEel4NI9LWG3KnXq6xpJBQbPj8G9AQiVP2umdIHv8J7vnM/h6/5I/p+8G+8f+VlvD/Ns2yoKE02Gb9tpGJpYKTqCeBrTx8iHLN887+PcM2iArLcDuYXZHGotZ9t1Q3DzcVDUZxOB8VZLvKz3Swv8dLRH2T/8V5C0TjV9Z08eMs1ySqqiaxdWkxTd4AblhaPe38P1zSq+klERERExlH4JCIiM0oiOPJmukatXlfr66ayphFrLXeOVASlGjslb6IKoNR+ThsqSjnU2k91fQe5GS6Mgbse38/mGxazYn4eduSczWsXU/1KB9GRDTYcYs3ff4oFdb9k31s2YL/zHazbzZadB1he4mXX0S6stZwcDNN8coiO/iCvdgfo8Id4eFcjy+d6icbitPUHh5/JGGLWEghHOXC8F7fT4HY52bGnie6BEP6hKC6n4cr5eRTkZjAQjHK43c+cvEyCkRiD4TjW2kkFdfXtfopyM5IVXqnv5UwaxIuIiIjIpUPhk4iIXPRSK4RSK47GNgU/0NwL9vSNsU/VYDvRGykSi7PX10PvYIi+YIzeQISYtcQsPLqnievKZ4+qnvrs/34DlTUN0N/H13Z8mRua9vPtdbfy/Rtv4+rfHgNjONDcS/XhTgZDEYKROLkZLpwjK9fdtrqMR/c04c10MRiK0TsUweV0DDcPN4YgEIpYMlxxFs3OTfZ6qqxpYDAcI8vj5Ip5ecOVWNUNtPtD3HB5EflZbiBKfpaLZSVetuw8MOFUxVpfN+39QbyZrrTB3Nk2iBcRERGRmU3hk4iInDdn2odpsk41TS4hsUKctTZtODLR2BLXrqxuSE5hcxlDbyBM6exsMAaXAxYUZJGb4eJYT4C8rNemtbX7Q2zf7WPX0S5WZwa548F7uLz7OJ+6+RP8tOLtuKNxDp3wU5KXARbmejNoAwxRLivMYflcbzJIWzE/j8qaRrCWm68qS077O9TmZyAcwxgoys3g0zdfkQzKVszPZ+5AiNm5GcnrJJ7pcLufB2+pSAZG26obONjcN241v9R3MRiKsaQ454wbuouIiIjIpUvhk4iInDfppmWlqyw604BqeYmXvb4ebr5q7oTHpE6XS5W4X4c/xEAwOq4qKlHN0+4PUdvQTSAcw+M0fGDVIsLR+KjeT4nG2/uP9bJjTxNlhdmcODnE/c/Us6i1kfse/zz5oUE++t7Ps3fpmyjJzeTkUJj8LDcOY8jLcvPua4aDsR17mnjXG+ezYn5ecsyJJuZLinPYtKY8Ofa3v6GEX77cTok3g79554pRzzoQjCYrnhLXGVuhlJgeaIwhMrKaX7q+TZN5zyIiIiIiYyl8EhGR0zpXFUvppmWNXWUudUrb1o0rJ3W/sX2ITlfFlBowJbblZjjH9Yh6bRW4q6n1dfPbI51YIByzHGzuIz/bTbs/xOa1i1lVXsj23T6eeamNgWCUufmZOIwhHIvzlraXuG/H5xlyZ/DeP/8an//cn/MxSDYu/9mLrRw60U+xN4NdRzp5tTtAJBpnx54m8jJd+LoGqa7vYPPaJRhgfUVpcvqfx+mgYtEsdn/mrdT6utlW3UBlTSOb1y5Ovu9Es/JI9LX3mmgsnrpK3ea1i7m3axCPy5F2auJE/Z5ERERERE5F4ZOIiJzWuWoknW5a1thV5jwuBx3+IAtmZU/6fmMrciYab+q9EuHS8hJvMtBJF1R9ducB2vpDrLm8iBXz83mppQ+3y8GJviDHegIYA19/+hV6hyL0BsL0DUUxWNxOB3esXUxh1Y+57Huf4VjhAm7d+Dm6Ckq4d+dBtm5cmXzmE31DWOBkIAzGJN9BQbaH+jY/0fhwbdJvjnZR7M1Ijs/jctA/FEmuMLetuoHnXukkDhzvHuSZu28EXgv0ElMFE+9lbA+nVeWFbN24MhlYfWT7XowxyXAtw+Xg5RN9rJjnPes/AyIiIiJy6VH4JCIipzUVjaTHVhYlGOD91y5MTmWbjLEVORONNzX8SlT8GBh1/4TENQ429xKKxnn2UDtvKpvN9UuLKMnLZFmJl11HOjHG8HJrH/5QDGMtTgMZLie3rlrEqscq4d572b/kGh655wFCHRFMKEokGufJuhYssP9YL+FonIJsN5vXLmHF/Dwermkky+2krW+IIm8Gsbjlirle4tay/3gve3093La6jE5/iI6+IV54tYdKoC8QIT4y/uaTQwBsq26geyBEtsfJ3W9fPuq9puvhlHhHW3Ye4GBzH8a81qD9mZfaGArH+dn+VkLR+Dnv3SUiIiIiM5PCJxEROa2paCSdrjop3X0m6gm1vMRLfbt/3Ap3kx3vZAI1C6xdVkzN4U4Kctx4M13cMVIFVOvrTt7/UGs/lTWNhCJRjHGQ7YAV930GnvkxP7/yRu55xydwtATxuBxYIBCO0tYfZO3SYvb6eijOy6Ri4axkf6dj3YM09QQom53NtZfNZtnIsy4v8bJjTxMep4PD7X6KvRkEwnGGonGOnxxiQUEWmS5DKGopLcii1teNGamkmpeflRxv4t2c6h1sqCiloz+IMSa5f15+Fj2DETCkrSybqobyIiIiInJxU/gkIiLTYrLNq8eGVInPe309FOVmnHKFu1MZG1CNDU6q6lqGq5JicVYvKWQwFGOON2Ncr6jE/evb/ew+2sVgdx/ffOofufb3v+X7N7yfL/2vD2KNgyKPg5OBKA6gPxjhd00nMcBtq8vYsaeJZSXe5DWbugOEY5aewTBbN17N7Y/s40BzL53+0KhpcTVHOolbiwMYCEa4c91VzM3L5JU2P8d7AlRWN7B53RKerGuhrT+YNjCyjJeYwmeMSYZtAJ+++YrkvdNVpp2r6ZkiIiIiMrMofBIRmaEu9CqUyTavHludk/h881VzOdzuZ1mJly07D5zVc9b6uvn6069wom+IuflZuJ0OKqsbkpVVe309eFwOHMaMa0ae2isJhsO0/9n9Eo/+6Issbz3Cjg99mvvmr8VayHY78LhdeNyWSDSGx+kkGIljjBn1HjZUlPJwTSMepyEOFGS72bLzAD0DIbBgrR01LW4wFOPK+Xn0B6Pcuros+fzPPb6fSGz4+jBSwbW0eFRglGxY7nJgRt5H4s9LVV3LuCl3cPqKsg0VpVRWNwyvDJhmtTwRERERuTQpfBIRmaEu9CqUyUx7SxegjQ1AUldrO9PnrKxpZP/x3pFPhhXzvBxq89PaFxzpBbVy1BirRlbkS+2VlBhD69797Pjepyke7OXIvzzCr93LyGrsIRKLccW8PK5ekM9vjnRx/dIijvcEklVFMNyw/Be/P8Hzr56keyBIHJjjzWBRUS6NnYMU5mawYl7eqHeV+v7GNkrPz3ST7XZyx9rFyT8HY3tbVdW14HE6iETjycbnifc4dsrdZIPM1Mq0C/XPnYiIiIicfwqfRERmqHPZJHwqqqgm05dpbJCRbhyp0/dONc50+6y1ZLqdxG2czWsXU9/up7U3mAxkUseYOvXtjrWLR63Q59qzh3966FPEjeGDf76VE11zuXqBg7n5meRnuXE7HYSjcW4dmWJ32+oyNq0pT46tdyhCXzBG79AADgNOh+GKuV42r13MwzWNxK0dFzJN9P42VJSOWr3v6YMn0q5QN/Y4YFSYdbYB31Q0pxcRERGRi5vCJxGRGepcNgmfrmqWsUFG6jgSnzv8oeS0tfp2/7hxJkKnDn+IgWB0VJBljGH14tlsXrcEgJojnZQWZHH95UXJKqfEdXoGQviHIvQMhEa924L/+jnl//x/6S+ay63v+RyvZJdAX4gTfe3kZ7lwGohZuPmquVTWNNDhD1NZ05AMn2p93eRnuclyOYhZi43HyclwccPS4lG9p+7deZCtG1cmn3uyAduuI12A4TdHukYdm3iG7bt93LvzILetLku76l+67+FUpqI5vYiIiIhc3BQ+iYjIaZ1J+HAuq6TGBhmp40gEUbkZzmQ/pkOt/eOqoOrb/Bw/GWBRQTazst3JfkRVdS209g4RjsYB+OpTh3j5RD+LCrLwdQ2O64U0GIoRt3CkY4DbH9nH5rWL4Z/+meu++WW6rqxgzq9/wRf8ho9u34c/FAMgEI4xEI6xsCCbw+1+cjPctPeHyM10A7B9t4/7n6nHaSAQiWEMGGNwOEyyF9aGilKqD3cSCEV5uKaRYm/GuAAu8a63VTfwu6aTVNd38OAtFawqL+S21WU8uqeJW1eXpf1uduxposMf4tE9TaOqsU71PYiIiIiInAmFTyIiclpnEj6caZXUmYRVY8cxtioqtQpq19EuDjT3Eo9bHMZgreVQm384xAHuWLt4uKG408GTdS0c6wkQjlqOdAZwGsj2OJk/K4tt1Q0MhmJ0DwSJxi3RUIzfHu7g/T98kLf/4oc8e8Uf8cAHP8fn/YaqkZXgXmzuIxq3ZLodlHgz8Ga6WFbi5bn6DnIznCwsyAKGg5+ohYGRsAoLs7OdXL1g1qheSyXeDOoHQ/z2aBfvu25hMmwb+66NMQyEovQNRfnaU4fY+VfXs2lNeTJUSjd97oalRTzxu2auX1o0qe/3XH2XIiIiInLpcEz3AEREZGbZUFHKkuKc5Cp0tb7uUx4/dirdmbAp19h/rJdDrX1EY3Ha/aHkCnGXFeZw0xtKKMjNYDAUIRiJ0TMQoqquhdtWl1GxaDjoKSvMYWRxOGIWwtE4A8FocqW72bkZOB2GjFiYf676Gm//xQ/5+Y1/xpZbPktWXi7bqhto7BxkVrabOXkZzMpy4nY6aOwcYP+xk1TWNBCLW6yFG5YWA3Db6jJK8zP54ytLmJefydI5OVxTNps71i5mVXkhlTWNPH3wBMd6AoAhHIvzg982Ud/2WlVU6ip8m9cuxuN0YAy0+0MTfjepFWyhaJw3zMtPVoC9Hq/nu5SzY4x5hzGm3hhz1BjzmTT71xpjfmeMiRpj/mzMvpgxZv/Ir5+mbC83xtSOXPNxY4znfDyLiIiIzFyqfBIRmaHOtPn2uZKoTppsk+qzbVA9dnW2vb4eXE4Hh070Y4wh0+2gYlFBMsip9XVjGG4y3huI8Oyh9mTz8MqaRvqHwuRmuIYDJweUFWaPCmqeeamNvICfh3fexx8ce4nHbvkED1z5TroGIjhOBijImZUM3TAGrOVYT4CGzkGwseF7Ax6Xg8pdjQDUt/v5+40rxzU1//rTr7BsrpeegRDBSAyHgSy3k1A0jgX2H+/l4ZpG/vXD1yWf7SPb92KM4X3XLeQ3R7q4dXUZMP67HvtdnMsG4Wo2fn4ZY5zAt4CbgGZgnzHmp9bal1MOOwZsAu5Jc4kha+01abZ/DXjQWvuYMeZfgNuB75zTwYuIiMglRZVPIiIz1KmqUM5HhUq6Kpt0VpUXsnXj1WccgqVef/gaK3GPVP0EwjH6hyJYa5PXXVVeyB1rFzMnL5O4tWCHg6jKmkZ2H+miqWe4/5M300l+ppuBUHQ4SALueqyOnNbj/OgH93BVSz33vGcLr3zgo3QNRLBAuz/MgoIstm68mvp2PwPBKCV5mZiRrlHGgMM5/Hs4FicQirBjT9O478COjOtE3xCNnYMU5mZw/dJiZmV7mJOfxTULZ5HpNmS6ncPHjqiqa+Fgcx8Hm3sJR+M8+8kbWTE/jy07D1BZ03jK7zrx/oFkpVqtr3tSVWvAqGPP9ruUs/aHwFFrbaO1Ngw8BqxPPcBa+6q19gAwqdI2Y4wB3gL8x8imR4AN527IIiIicilS5ZOIyAx1qiqUqapQOV2Vzbm8Prw27Q5IBlCffHw/g+Fgsnl36rl3PVZH31CUTLeDaxbOYvO6JWyrbiDT7SAWixOz0BeMATGcBu7/ZT2XF+dScvj3VP74i3jiUW7/4FaeL1tJ6ZEu5s/KpLk3CMATv2vm5pXzWF7iTTY9f66+Ayy4nIYr5+cxEIrSPRDisqJc3vXG+Rxu94/q7bR2aTEOY3i1a4DjJwNsvmExm9aUU+vrHvV9jf3uNlSUcrjNz4m+YDIwG9uQPTENcqJqt9RA0sKk+3ZN10qIAkApcDzlczOw6gzOzzTGPA9Ega9aa6uAQqDXWhtNuWba/0NhjNkMbAZYtGjRGQ5dRERELiUKn0REZqhThT9TtXrZREHEZKf5TXRcYnuHP8RAMJo2INm+28eOPU10+kOJWW/csXZxcntepotAOEYwEsPtNBhjkoGPAfa9epJAMJq8Z8xCQbaHxftquO/fv8TJ7Hx+860fscQ7jxf2HWcoEqV/KIqD4ZKSeNxSWd3AnLzMZNPzzWuX8MAz9RTkeLhiXl5yzEuKc5JNwBMr3hVke+joD/Jqd4Auf4gMtzO54t3Y7ysx1S41TFo214vL6Uie81oIVsamNeWnnQY5NpCcbDipqXYXtTJrbYsxZjHw38aYg0DfZE+21lYClQDXXnutPc3hIiIicgnTtDsRETlnJppqlxpKnWpK10TTARPbTw6E6BoIsazEy/ISL10DITwux8j0sgY6/CEyXA68GU4+uLpspGl3A03dAY71BHhTWQFL5uTiNIa6YyfZfaSLHXuawBiCkVjyfhlOwzuuLOH/+ar5h0c/R/OcRXzq7n9hX1YJx08OEbfQ1hdiIBQb7uPkhEA4zj5fDxkuR3KMm9aU8/Cm61hzeRHrK0rZUFGKN9NFW38w+fyJFe96h8JgDB6Xg5wMd3LFOyDtOxv7rsa++/p2fzIES92frhF8Itxbn1KxNtnpc5pqN61agIUpnxeMbJsUa23LyO+NwHNABdANzDLGJP6B8oyuKSIiIpKOwicRETlnJgoiUoORU/WbShde1fq66fCHiERjtPmHw6bD7X7q2/14nA6eeKGZ/cd6mZefRYk3g7vfvpyHP3wdoWicWl83uRlurLVkuZ3MyctkQUEWDochFI3T2jdENBYHa7msMJtst4NNf1RG/Zdv5u9qf8jGf/kS/de/mb7/+iWXXbWE9RWlWGvJdDtwOsBhhn9FR3KroWiMXUe68DgdfPO/j/BHX3mWQ639yXeyqryQYm8Gg6FY8vkTK97dfdNyNq9dTMXCWTx4yzXJZuKQPpRLhG+JaXZj3/3Yd5nYX9/uH3ctrVJ30doHLB1Znc4D3AL89DTnAGCMKTDGZIz8XASsAV62w83Efg0kVsb7MPDkOR+5iIiIXFI07U5ERKZc6rSxQ639yZ5IpzouoaquhYFglL5glPxMN5FoPBmo7PX1MDvHQyQW59M3X5k8N3WK2YLZWZwMhIlbS2PnIN5MF1cvyGdvYw/WwkAwwuZ1S6iqa8Hp7OV/Dp2gc/t9lP7kRzy9+k944J138eWcXLZuLEuOv6k7wIalpRzvCXCozU80FmcgGGXFvDxWLsjniReaGYoM93d+dE9Tsm9TZU0jJwfDYC2vtPm5/ZF9bF67mGc/eeOodzBWuqltYyubJvMuJ7qWps5dnKy1UWPMx4FfAE7ge9bal4wxXwKet9b+1BhzHfAToAB4lzHmi9baK4EVwDZjTJzhf4z8asoqeX8DPGaM+TJQB3z3PD+aiIiIzDAKn0RE5HWZbD+nhERo8pujXdS3+097XobLwcutfay5vIjZOR6WlXiprGnEWsttq8uSTbtTr5EIU5aVeGnrD/LGhbNYUJDFriNdrJjnJRSNE7OWmIXuQJSvPf0K737jfF56+Rhf/MEXKD7yAjv/9E7+8bo/I9/jTvZJqvV1s2NPEx6Xg3A0nmxY7jCGO9YuZlV5IVt2HmBBQTYd/iAZLge3rh4OrarqWjjQ3Is/ECEUs2Q4DXnZ7kk16k4XJI0NjCb7PaS71lT1AJOpZ619CnhqzLbPpfy8j+Gpc2PP+y2wcoJrNjK8kp6cZ1/61y6Od0RYOMfN5z5aNN3DEREROWcUPv1/9u49PK6rvPv+d82eszQ6WJIlS7YVWT7EIXZQEsd+cGJzKJBQSow5NNC4MYE4BQptoAVsypk4QCn0edpAo4Q21KENJVEdQslLoAXJpLUcUjkWsS3bkiLrODqOZjTn2Xu9f4xmZyTLtpyYOHbuz3Vx2ZrZs2fNmoDJz/d9LyGEEC/JuZ52lgtNhsKJs76utXuMR5/pI2NpTgxP8YtPvp7bHzzAUydG8TodVBV52b117Yzr97b1s6oygAb2nRglmjSpryggmbEoL/Sw7/go5YWebLvdtPb+ENe5Yjz80Kdxd3Xw5Xd/iv+5/vepcjqYTGRYWRmgtXuMXU3tRBJpphIZ0hmTn/12EFNDRaGbXU3tbNtQy5aGGhTYgVhr9xi3P3iAY0NhwtPBkwISpsaRyOB2Ok75zC8mRJJT54S4+PUOp+nsS1/oZQghhBDnnYRPQgghZjjXSqYztWzNda9caNLaPXbWVq+9bf0sKHAzEUtx64ZaWrvHODoUwWVkh3LPfm1jSxeH+kI0HxthSamfQo8xY+7RY2393HRlFfuOj7CwyEtfKIEC1oydZMd3v4gzGWPXB79G89KriE3EWLkwYLe2dQQjpDMW49EUCjgxEsMBuJ0OTo7HMXX2/XdsWkZr9zgrKwOsrytjb1s/7X2TjEylAFCAz+VAa03K1Dx+cIDeiThaa+7cXG9/hpFIct4hUmv3GMFwgoDXKa1zQgghhBDiFUfCJyGEGS7OSAAAIABJREFUEDOcawXNmVq2Zg+yzg+i5nrd7LBqS0MNI5Ekltasri5ib1s/xV4XfpfBrRtq2dvWz5GBMB3BCB6ng33HhjEtWFaeDZ56x2McGQzbJ8/l1oBSTCUzGAo29x7i7x69m6THx0f/5Nv0LVlJLBSj1OdmcDLOFdXFM2ZMVZf46J+IowANvKa6iHAiTe94jEXFXvbs72FgMsHf/LwDgOFIkiWlPiaiKTI6+5r/U1/GRCzN4YFJ4mmTXx0dxucyqCryonX2ouzc5/l/Z9GkSaHHyH4+5p4ddbp9bu0e477mTpRS7JhuHxRCCCGEEOJ8kdPuhBBC2HInyxV6jHOqoGntHmNn0yFau8dmPD7fU+5yZl8z+3S4VZUBJhNpAl4n+06M0jUSZc/+HrpGojz6TB+mlQ13inxunh+L0T0WZTiS4qH9PTPuj9b4PU7e+dv/4r5//RwTZVXc/40fsHHrm2hYWsIn37yKjGURjmc4PDBpr2XbhloypsWiYg9uQ+F3Oyjxu/ij9bXUlPr5g6uq2bahFqcDfE6Dv3myg4GJOJcvKuKv3n4FHkNhKDjYG+IdV1Wz9erF+NwGloZ42mRlZYA7N9fz5isquWFFxYw9Pd0e5+8zSs3r1Lq9bf0c7A2xq6ndDqLa+yZp7wvJiXdCCCGEEOK8k/BJCCGELXeyXGWRF+C0Ycdcr5sr9FhfV8burWvtKqb8Fri55K5ZWRmw3zv/dR3BCGnTom8iDlpTX1HAtg21FHoMFhX7KPG5aFhSQrHfhdvpoMjrYmHAYw/9zt3rhuXl/MXTj/DNn3yLEytfy9B/PMnr33wNHdPDy7dvrGN1dTGJjMXgZJKv//SIPWw8nMgQDCcBcBmKUCxtDyE/FoywfWMdD9y2joDPhd/jpC8UsyuvNq4ox2UoMqbFsWCE3VvX8rE3riDgMVhc6uNYMML6ujJubqhhz/4e/vvE6IyA6HTBUu41wLyCwy0NNaQyFm7DwWPTFVBrFxezdnGJtO0JIYQQQojzTtruhBBC2PLnN51L+92qygAHusdZvSgbGuXPeMpv8cofDj6X3Gt2NbXjdjpQYIdXDz7VTXPHMKU+F0sW+Nmxud6+viMYYSppcu1lpezeupbW7jG+8cRRAKqKXwjStjTUsPsdV3Dgplu47heP8pM1b2D8/32XVUXF3PVwG7GUybGhCCurAiwp9dmtb8FIksaWLkanEqQz2UHlLqcDv9vF4GQcp8NhDxnPfY7dW9ewq6mdBX63fbLfphUVOJRCa21fmw26imbMv9rb1o/bcDAcSbC4xG8HRGeakZULDusrCuZ1et7urWvs+8lpd0IIIYQQ4ndJwichhBC22SFEfthxpkHkHcHIjJPk8gOr+YRY+ffOBS8j4QS/6hjmwae62b6xjj37e4gkTfxuJ9/bPvMU+NnBzPq6MkLxNKFYmolYiKFwgiWlfp747+Os/5evcN0vfsr9G/+Qb73+NmqeGWTdeJJoMkMyY/H8WJSTEzFcDgc1JT5C8RR33LCMluMjuA2D+upCAIYiSaqKvMTTJumMxd1bs6fWf/D7T9vDw3MBT+5kPwU8cNu6s+577sS8P1y3hGPT1VhnC4jmCqfO9J1J4CSEEEIIIV4uEj4JIYSY0+xw4kwhUi74uOnKKjssmf3c6Sp2WrvH2NXUTtq0ONA9zrYNtSjgVx3DTMTSfOvJDlZXF7FiYSE9Y1GWLzw1MJm91tbuMRwKrOmZ3QUuB1c54+z4yp9hHT9Mz1e/iev1W6nZ38P1K8rpnYhTX1HIgkIPY1NJ+ibiLCr2sqoqYAc/ueqklZUB9uzvweVQDE0PJL9jekj3zqZDHOoLgca+trV7nBtWlJPKWPNuaTtbMHS2UwRzVV6576yxufOcTjAUQgghhBDifJLwSQghxLycKUTKD0tywUjuFLr8dru5QpO9bf24ndkWs1Kfmz37e9i9dQ0rKwN868kOSgvcNDZ3cqB7HJfh4MTw1BnXmQuzhiYTKAVaAx0dfPixr+IPjfHJ93+RcM0N7Kguora8gMcP9mNqqK8opCLg4frl5RwLRlhZGaAjGLHv+0T7II8/O0BlkQe3YTAYiuMysi10uc+SO50v11a3q6md4UiSJ58bYvOqhefja7D37HRBYP5zue8sGEme0wmGQgghhBBCnE+viPBJKXUX8CGyhxS1Ax8AFgEPA2XAM8A2rXXqgi1SCCFe5Y4MhGntHmdlZeCMAcbetn4Ongzxk2cHWLzAj4I5W/ByP6+qDGRbzK5dYg/uvr+li4qAh0+8ZRXHghE6hiJowLI0xT6XPQR9rmqeXJhlaQufy2B11yEeePQrZBxObr31axxZvIoNSrG3rZ9DfSFC8QwAz49FcRovzG7Knzt1ZCDMg/+dPTEvNR7nXdcsxu826J2IoZSy33t2xdINK8ppeqaPQo+Tg70hmjuGWV1dzI7pSqkX60xBYP5z+dVQZ6o+E0IIIYQQ4nfpgodPSqka4OPAFVrruFLq34BbgLcB39ZaP6yU+gfgg8B3L+BShRDiVW3P/h6GI0nu39dlVzTNFaBsaajhQPc4pQVu0rNazWYPND94MsSB7nF2T89Lqi3z41AKS2u6RqIMhxNossEQGkxL094/ySd/eJDJeJoFBW5y0U8uyAqGE9SU+PjDa5fg/vdHedfDf0Vf8UK2v+dL9JZU4clYXL+8nJbjI5T63UzGUrgMg9oFfvukvV1N7aQzFom0yZHBMHvb+lFk/4aktsxvDzXPtdblD1nPr+5KZixWVxcT8Do5PDDJyFSK2PPjPBbwvKjw6cGnutmzv4dtG2pPO7x9rpY9me8kxCtfLGERjmYPNAhHLWIJC79XDqYWQghxabjg4dM0J+BTSqUBPzAIvBF4//Tz3we+iIRPQghxwWzbUMtD+3sIeJ1nbOGa6yS1/Ofyfz7QPW5XOh0emCSazHDtZQu4c3O93S7W3hsikTZJZiwyGjA1faEEbgMmYik7LHI7HTR3DBNLmfjdBp87/jOWfuvzHK27ko++5/MMKB9KQ8Dr5PFnBzjUF0Jr8LgMvC4HJQVuOxTLVTwFvE4OD4ZBa3wuB5dXBfj021bP+Cwf/P7THOoLMRJJsr6ujMaWLvvnOzYts/ehsaWL2PNjFHicL7oCKRcAPrS/h+0b617UPYQQrzztJxLsvHeEeCo7qG40ZPLenf3c89EK1iz3XuDVCSGEEC/dBQ+ftNb9SqlvAieBOPAk2Ta7kNY6M31ZHyC9AkIIcQFt31jH9o1182rhmk+lTX5INRROEEtlA6ZQLG1XDgE0NndyZDCC01AEJxOkLY3WkDbhjZeX0xGM4DYcpDMWhR4XI6EYn/zpP1J74DHaN/weX3//Z1EpqMlYhOIp/vSNK2hs6SSTLTDAtDQep0E0adLY3AlKUV3sZcfmehpbuvC5HDgdDpYs8FNa6OGJ9kF2NbWzbUMt2zfWobUGTfZXmPHzKacHBjynBHJnk19JlQsAb91QO+/XCyFe2WIJi533jhBLavsxrSGW1Oy8d4Qf3VODTyqghBBCXOQuePiklCoFbgbqgBDwI+DGc3j9DmAHwNKlS38XSxRCCJHnpbZwzR46nmtVu7+lC60149EUT7QP8uRvB7lqaSl3bq4HXjg97tcnRtl3bITMdAveHTcso7ljGIdSTI5Pcu+P/4a3dPw3g7f/Cc9s/wsGD/TOOG0ut/bGlk4KPU6WlhWwuNTHvuOjZEwXTsNBfUWBfd1jAQ/BSJJDvSG6R6M0d2RwKGWfwper0sqFcbN/fqn7lj8na/fWtVLxJMQl5pfPxOyTOWezdPb5t20sfHkXJYQQQpxnFzx8An4P6NZajwAopZqAjUCJUso5Xf20GOif68Va60agEeDaa689zR/dQgghzqe5Tq2bz7XAjEHe+a+tCHhYVRmgcV8XsZSZPYGib9IOXXLXbt9Yx5u/9Ss6R6IoNHv29xBNZjDGx/mnpq9ydf9R/vV9d5G8/WPs2d9D2rR48nCQy6sC9no6ghG+fUuDfc+dTYcoL/RQ6DFQSjEUTtDaPTYjHPv6T4/w3EA4O3tKa0oL3PbaIBsSwYsPmU63p2caLi6EuPj1D6dJpOb+v7CJlKZ/JP0yr0gIIYQ4/14J4dNJYINSyk+27e5NwG+AXwLvJnvi3W3AYxdshUIIcRE7l6BovvKrcc52z/xrNdgtcjc31NhrG44kmUpkONA9TrHXBRoWFXsp8bvs0KW1e4xvPHGUwck4freB16kYnExS5LMoH+7n/oc/T014hD/d8hm6r7uRyZbO6VY+E6XgqRNJFLCwyDtj7a3dYwTDCQJeJ3dsWjbnZzsyEOb48BQOpVAGvKa6mFVVAXvYeDCcIJo057Uf57qnMixciEtbzUIXXreaM4DyuhU1Fa4LsCohhBDi/Lrg4ZPWulUp9Qjwv0AGaCNbyfQfwMNKqa9OP/a9C7dKIYS4MM4WHM0nWJpvUHQuIdV8qnFy9/M4HYxOJbnpyipWVxehwG5/29l0iKeOjzI6lWT1oiK2bajlWDAy51ykvW39PDcQJmNpKos8GA4HhsPisq7nuP+RL2OYJu+/5W7+d/EV1JvZ+U/j0TTlhR7GoylcDkUolmY8mqJ3PEYqY9qnx7kNBw1LS15otZv12fbs7yFjaZSC19WXs2Nzvb3+rpEoAa+T+oqCF12d1No9xnAkSaHHkAonIV5l3nCNn+8+MjHncw6VfV4IIYS42F3w8AlAa/0F4AuzHu4CrrsAyxFCiFeMswVH8wmW5tu2dS7VTPOpxsndr3c8StrU7Ds+wvaNdfbrcoHL6FQSrRST8bQ90Dy/hS1nVWWAQo9BMmOxMOAh4DGofuqX/P2Pv85YQQnb3/8lOhcspszv5NYNtTS2dGI4YCyaJOB1EU9nW/n6JuKE4mnG+yY5ORZlYbHPrsQ63WfLH/SdP3Mpf29fSnXS3rZ+phKZGbOmhBCvDn6vg3s+WmGfdqc1KAU+t+Kej1bIsHEhhBCXBPnTTAghXsG2NNScsaLmbM9D7lS5tfOqZqqvKLBbyVq7x87L2hcV+0ibFkeGIrR2j9HaPcbOpkPc19zJVCLD5VUBaoq99gluudDq/pauGetoOT6CUoqA14nbabDuZz/i/qavcrxsKX/8wW8Tr1vOmy6v4DvbrqUjGMFlOEhmLIqmg6fFJX7QGpehYLq7JW1BKmPZ753/frl1tnaPsX1jHb/45OtZXV0045r1dWXc3FDD3rb+l7Rf8/kehRCXrjXLvfzonhrKSwwAyksMfnRPDWuWey/wyoQQQojz4xVR+SSEEGJuZ6swOp/zgHL3yrWSvZT5Rfn3a+0eyw4ZNxz23KeDvSEmY2muqC7i+uVVdAQjrK4uArIVTge6x0mbFpFEhsemq6Ce7Q0RSWSoW+Djj3/8D/z+z/6ZX9av45NbP8NltQv59NtWA9nwKneP6mIfbqeDD79+OceCEYKRJC6nwaJiH4OTcZIZC7fh4FgwQkcwQtdIlMbmTva29c85x2mu6rBzqRg7215dKL+LuWBCiHPj8zooKnAwMmFSVOCQiichhBCXFAmfhBDiVeZsQUMuuLnpyqrz9l43rChn3/FR3E4HvRNxJmMpnA4HhwcmOXhygoylGYkkWV9XRkcwYp88BxCMJLmvuZOMaeE0U3zioW/x1oP/yY+ueRtffuuHWVxRxIJCz4zB5QrYvXUNj7X1s7IyQEcwYp+2l2uT29vWz8HeEOmMxcrKAPtOjJIxLY4MRjk+PEUsmcHtdHDTlVX251hVGbBnVuVcCqfRnY8ATQghhBBCiNOR8EkIIV5lcqHLge5xdm9dc0rYkAt/jgUjZ73X7CAr/+d/+nU3P3suSLHPwO9xEUtm+NfWk/jcBvUVhYTiacJTaaLJDABtPePc/uABNq2oQAErKwM0tnQyGc/gdTmoc6b5zMNfYEPPIb79htv4zob34HEapE2Lsakkz/aGWFLq4/JFRfYMpvyh5j95doBPvmUVu7euBbIn2B3oHueGFeXZgeKmxXgsRanfzWgkScbS+N3GjKqobKi1dsYeXOiqpfPhUgjQhBBCCCHEK5eET0IIcRE4n21RWxpqONA9brfBzb5fLohYWRngg99/Gq01d06f7jZbfpC1bUNt9uQ4pwMF/PxwEA2E4iaxpImpwdKQimd4fizKussWMDARo7LISyJtEopn2Hd8FIdS3LFpGXc93MZwJIlpwYKJIb71oy+xZLSPu97+SX557e9R4XZyRXUxd2xaRmNLF/2hOAsKPaeEQ1saavjJswNkNDS2dNqzo7TWlBd6ePK5IWIpk2TGJOBxMRFLUV3iZXQqhd/9wulzl3I4cykEaEIIIYQQ4pVLwichhLgInM+2qOwA8jU0NncSjCRp7R6bcc/8iqFDfSHQ2HOXZgdgqyoD/OTQAKU+N3v29zAWSRBKmDw/OoWhwJwe7K0cCiujMRygNZiW5qnOUVCKcDxN/cJCJvomyVjZCqiv/TTJcCSJ1rBmtJv7/+2LFKTi7LjlyzxVexVeDd++pWHGuhubO9Fgf57W7jEaW7rQWvOuaxbz88NBIvE0+46PUuA2uPayBdRXFJAxLXonYnY1VpnTQ02Jj+vqPDNOsTvdvsu8JCGEEEIIIc5MwichhLjA5hNezG6LeqmBx/q6shmnys11ry0NNYxEkmitWVkZsIeGD4cT9vX7ToxiKEU0maHM5SaUMAGIp7OpkwJ8LgeGoXA6ALLHiC8MeJhKpgmGU3i8ToLhJKV+FxOxNOGkSefwFAp468Ahvv3IbkIuH3/5Z39PuHYlS+Npbt1Qe8rnPjIYZiKa5ldHhnEaiqVlfkLxNGioKvKyaWUFj7X1kTY1hiNbXZULqfL3Nvf7s+1r7juYazD574oEXUIIIYQQ4mIk4ZMQQlxg86lqmt0WdT4qoXKB1lA4MeOUt9xg7r1t/XZAs7PpEG6ng3TGAqXs9x6fShJPmxS6DSZiaXxOB4mMhSYbPGmgpsTLV7eu5es/PcLRoQgVAQ9TSZNgOIWlYSqRIW1aeJ0OCjwGibRFMmPxjmf/k6/9f/+P1MrL6f/ev1I6pNl+mtBlb1s/0WSGeMYCwDQ1/RNxXre8HK01NzfUcGQgDCi8TvC4jFP29lyDndx3EPA6qa8oeFla8mQwuBBCCCGEuBhJ+CSEEBfYixn2fD4GROeHLo+19ROMJO1KqO7RqD27aX1dmX0C3g0ryumdiFPoMVhZGeBXx0ZQGqaSJrVlHq5aUoKlNYOTCXpGoygF0XQ2EFq1qIiu0Sg943EMwJxeh+FQmBYkMpq0aaI1fHjfv3LXr3/Ar2uv4h8++DUeet0aGmatP/8EumA4wfKFASLJDL2jUSzgveuWcNOaRext6+fIQJg9+3soD3gIRVMU+1ynVHzd19xJe98kw+HEKcHOXMFU/ncwnyDofFQtyWBwIYQQQghxMZLwSQghLrAXM+z5bK85l6Bjdgg1FE6QzliMhBP84bVLgBdOwNt3fJTyQg/1FQV0BCMUe10MhxMYDsVgOMH719fScnyEmhIff3jtEnsA+WPTIdHDB3qBbPDkAJSCN1y+kIylOTwwSXQqzWefuJf3HvwZj175Rj5z48coijtmBE0dwQhbGmrsKqAD3eOUF3pYVRVg99a19qynZ3tDPHk4SLHXZQ9YV8An3rKKY8GIXfGVqyJSSqEUKKVO2aO5Ko5yv+6dnoeV+33+Gs93tZoMBhdCCCGEEBcjCZ+EEOISNFfQcbZAKj+E2tXUTs0CP8eCEeCFipubrqziWDBiV94MhxOYlkXfRNweOp4Lp7ZvrGN1dZF9cl5jSydOA9Im+JyKAo+TioCXBQVudm9dy9O/7cH7/vexpv1/+NGNt/HZ176btFb4XMYpQdP9LV1YWhPwOk9Z0962fg71hQjH0/hcBn6XwbYNtew7PgJKsbq6iO0b606Z9XTD8nKeH41y/fJye0/yQy8Fp1Qc5e+zBrpGojR3DJM29SkVVFK1JIQQQgghXq0kfBJCiEtQLuhYWRlgZ9OhGZVCsytvZodSudPw8oOS/Cqf/PCqsaWL4UgSp6HIaM0bV5TTOx6bcYpebmZULGViKAdFBQYOpVhS6uPyRUXc3FDD/x44TPX73k11zzGa/uTzPPLaG3H2hbBMjaVPDb+GwgkGQwlSpsUdm5axfWOd/VmODUWwLM3SUh+15YX23KqW4yO094ZobO6015W/D7nqrmPBCK3dY9zX3MnRoRequxYWeU+7z/nDynOn582uoJKqJSGEEEII8Wol4ZMQQlyC8kOfXOB0usqb/FAq9/OWhhp2b1172utyIcqRgRCheAYAh1LsOz5KbZmfwYk4u5ra2bYh24bXNx7DUNkT6MamkqRNiwWFHnZvXcuzP/8fKt67heJomA9t/StOrng9tV4nm1ZW8FTnKG95TeWM4CbXVjcZT1Hsd89Yz962fk5OxHAoxbq6shmf4UxtdTAzSNrb1k973yRp08LvMuwh67PnRM0OlOY6PU8IIeZryULXjF+FEEKIS4WET0IIcZE7Uzvd7KHYsyueGlu6GJ9K4lCKoXCC+5o7iSZNO9DJv/dc1VRjU2kge7Kd06EYnUpQ4nORMi0iiTRf/Y/DGEqRMjVOQ+FxOVgY8JKerlg6/MPHqfvAH5F0GPzh+7/Gb6uW4x2PsXSBn+PDUUr9bvYdH7WrqAB7MPjSBX5WVQVmhDxbGmo4NhTh+dEpOoYi9utau8eYiKZwOhxzttVtmWN/hsMJlFLcsWkZwIyTAc/lZEIhhJivz3+o/OwXCSGEEBchCZ+EEILzcxLZyy235uFIkqlExq5camzpQmvNnZvrTxuE5OY6jU4lcBsGRT4XTsNBwOukvqKAmxtqaO0e466H24ilTIbDCb63/bpTqqmWLPDRNRpjUZEbjSKT0mituay8gH3HhrE0mJZGARlTMxFNkcpYLC0rYMFP/p26T3yEwQWL2Lb18zxfXIUDeE11MSiF2+lgIBTD4zTsVjl4oYKpdHpWVL71dWWsrApwcjxG70TM3pOPPPQM49E0frfDbqvb29ZPMJywwzbIBltKKXZsWsb3tl93yr1zVU35AdzF8s+LEEIIIYQQF4rjQi9ACCFeCWa3nl0McmtGazswyg3bbu+bPONn2dvWj9vpoNDjYkmpjxKfi0KPwR2blrF761rW15Wxt62fWMokkbYIxdLsbDpEa/cYWxpq7Pe7e+tablm3hMpiP7GUid9toJTiUF8Ir8vAbSiWV/gp9Wf/riOe0YTjaTb/+Pus+PgdxF57DX/9uQcYX1iDywGLit08PxZlX8cwJ4IR0JA2LY4MZgMjgB2blvF7qyvtiqTW7jF7bZCtflq7uJi1i0tYWRlgV1M7oVi2Qktr7H3qGoniUGrG3rX3TdLeFzrt3q2fbuXrCEYuun9ehBBCCCGEuFCk8kkIIbg4TyKb3VLX2j1GMJxgaamfEr/Lrl6aq6JrS0ONfXpbLoipLPKeck2u9czS2g5bbm6oQU9fk6usetd3niKRtqivKKTY74JxWF5RaA8U/8YTRxk/GcJhmXzhPx/gj37zOE+vexP6n79PweExHGODoGAonMLUL3xGS2uUpXE61IyZVKsqA+zNq/Q61BdiJJK0n98xXfW1s+kQbsOB321gWpr3rltif8b8vcvJfd7T/XNwttPvhBBCCCGEEKeS8EkIIbgwc3peaqvf7DXvbesnmjRZVRWw29FyLXKzB2UDdoB0uuAt//4PPtXNnv093HRllR1Wfe7f2+mbiFNd4p2+n7bb/WaHYoOTcTzpBP/38W/y1uP7+dlb38/nXvfHrNmfDYpGIknaesaJpizIWGjA63JgOBQayFh6RlB2oHsct+HgQPc4xT4XaNBanzIUPReyVZf6mEpkSGWsOfdursfm+n5y91dwSsufEEJcir78wCi9w2mWLHTJTCohhBAvmoRPQghxgcx1etxc5htSzRUi5R4bCic42BviQPc4u7eusd/7/pYuKgKeGZVEc71HRzBCeaGHY8GIfc+9fSFiaYvOkRgOBZaG48EpALvdbcXCQn55dJiiqRAPP/oV1g508J0tH+N7V7+dRNrkyGAEgAduW8c77/01RwbDlBS4WL4wQH1FAUPhBO19k6xeFJhRsXTTlVXs2d+D2+mg1O/i8qpKVlYGaDk+QsDrtPcgFyidywl0c82Dyr33xVghJ4QQL0XvcJrOvvSFXoYQQoiLnIRPQgjxMprr9LizBRnzDanOVLkD2MPDv/HEUYr9LjKmxeGBSYr97hmVRLu3rrHvM1ebWe59xqMpfn44iKEglS0oImFaNDZ38uvjo6RMTfdIlCUTAzz4oy+wKDLGrj/6Aj9Ztp5kIoPLoXA6FHc93Mbq6mKUUnhdDhRQ6DHsfWls7gSlePCpbjqmw6/c+vbs7+GGFRVs31jHzqZDRJMm9RUFZ61qms9+5w9ffzH3EUIIIYQQQmRJ+CSEEC+j/CApN9j7bM4WUs0OmXK/n/1eq6uLae8LMTiZwGk4GJyME0uZQIodm+rtSqL8kCt/ntIDt62jtXuMrd95iqHJOH63QcDrZDKesdfiRHOwN0RyenDTNUMdNP7blwC49X1389ulV5BImngNxepFRQxOxhmZShF7foxrLytjMu4lY1ocGYpwX3Mnd26uZ2GRl66RKHv291Be6KGxuZPGli6ODExS7HNzLBix96mxuZNgJElr99hZW+hOt4+zgzYhhBBCCCHESyPhkxBCnGdnCjrOtW1rPqHJfc2dtPdNMhxO2EHNY9OvyX+vHZuW8VhbPysrAxwLRsiYFr0TMa6oLmb7xjogW0m0sjJg31trDRomoil2Nh1iOJLkuYFJTAvchsLSL8yOAkhaYGQsPIbiDcf+h7997K8Jl5TzpT/5BrqqFsdgGENpTK35g6uqefzZAUanUjgdDvv0uo889Axj0TShaJKqIq/9OVYvCrDv+Chp00XryX5rAAAgAElEQVTvRIx0xsLvtlhZGWBn0yG2NNTM+Pyz52GdrXpM5jkJIYQQQgjxu+G40AsQQohLTX7QMdv6urJ5Vzyd7V45SimUyv66paHGbhXLvRdkB48D0xVQRQQjSSytWVLqR/PCQPG0afH3/3Wc193zCx58qps7N9fz5isqsbTmF4eDTEwlubK6mGKfk5pSH6+pLiLgdth/mGgNXqeDb40+xb2P7uZk9TI+/rF7aVELODIY5sqaIgrcBtUlPo4FI2jAoaC2rADIVlpFEmkcKjtkPDh9gt3urWtJZizKCz0sKHBz1eISrqkt5e6ta+gIRmYEbrNb5YDTPn6u1wghhBBCCCHOnVQ+CSHEeXY+h1LPda/Z1VA3LC/n+dEo1y8vnzFgO1cNNLvqp7Gli6eOj2I4FA4Fixf47Za7wVCceNpCAQ/t7+EXn3w96+vK+OD3n6Z7NMrx4BQBv4uyAjcT8TRFXhfX1ZdzZGCSyXiadMbkz3/xPX6/5d/4zdrr+fItu3gubGFqE4CjQxE+8ZZVNLZ0cXQogtaagNdFid/F3rZ+DvWFcBkGXhesWBhgIBRnV1M7u7eumbEXs8O7/MfnCvbmenz2PuZf81JPIjzT+wghhBBCCPFqI+GTEEKcZ+dzKHXuPvkn0c0Ok/JPosvJn9V0x3S7XS7AGp9KksxYaMDnVBwPRvi91ZUsKHDjcxkcC0awLM2tG2rt++3YtIxdo1GeH40yFTJxG4oin4vnR6dIDFlkTM3yYicfe+gb3Nj+Kx5/3c18/W0fZmTKtNvyDAVbr15MRzBC2rTom4ixdnEJZYUeLK1ZVRlgJJKkZ3SK8ViaSCLDVDJNsc99xhlZ57rfuTBoOJJkKpGZsxVvvkPe5+N83ksIIYQQQoiLkbTdCSHEK9zs1rvZ7WFztYudHIsyNpXi6OAke/Oqglq7xwhGkmhAAYmMxmU4ODE8xe6ta1m7uBil4L3rlthzoHJhzbYNtZT4nDgNxdIFPt58RSWXlRcST1v4YhG++J2/4Mb2X/HNN2xn1xt3EIxlSJkaS0OR1+Bzb7+CL77jSrY01LB2cTFLSv1YWmNpTTRpciwY4YHb1mGhmIxnODkeY1Gxj5RpzZhDdb72E61n7FuuWqy1e+y8tuBJO58QQgghhHi1k8onIYR4hZvdeje70meuyp9oMoNDKcaj6VNa7mLJDEVeg4DXxZqaYg71hSj2uWjtHmPf8VFA8fPDQZIZi1WVAbslTwHf2XYtjc2doJS9nn966Ff8xQOfonZigL/c8pf8/LVvwsxYpKdPvHM5wOsy+PWJUTqCEbY01PC97dexs+kQB0+GmEykqQp47FPqtm2opbGlk0XFPor9LpyGY0ZV10ttY1tVGeBA9zg3XVlrB2zw4k4inI/zWQknhBAvp1jCIhy1AAhHLWIJC79X/u5aCCHEuZPwSQghXmHONItormvva+5EKcWOTcvs63Zsqueh/T1cv6Kc3vGYHeyMTyVJpE2uWFRE00evB7LDyLtGojQ2d2IoSKVNwpbFwd4QB7rHcRsO0pls9dHetn5Qym5X2xDu5avfvBN/JsmOP7qb51Y2UGA4iKUSKLLVVXXlBSwtK2A8muLZ6VbA9XVlbGmo4UD3OC6H4uhQBLczyv3AA7ets0Oh3CD0m66ssvclGE4QTZpnbGObK6DKb7eb3aYIZ5/VJbObhBCvJu0nEuy8d4R4KvsXCaMhk/fu7Oeej1awZrn3Aq9OCCHExUb+6kIIIV5hchU4jc2ddhsYzGwLy7+2vW+S9r6Q3ZbX2j1GRzDC3VvXcNOaRRwZDLOvY5j33befo0MRvC4HSqlTWsxCsTSdI1GSpiaatpiMpdi2oZaGpSXcvXUN+06M8osjQULRFBnTIv74f/CmO99DCge3bPtrhq7eQJHXxaqqAFXFPgwHLC71ce1lC3jgtnWU+F2gQevsv8hkT+Nbg9NwkLEswokM41NJ+zPc/uABGvd14XZmK59y++JQioDXyVA4MWMv5trD/FMCT9dul3O2kwhPd/LgXN+LEEJczGIJi533jhBLaqb/JxutIZbU2UAqYV3YBQohhLjoSOWTEOKSdDFXqeQqcIKR5IyWubkGV29pqGE4nEDltcF9/YmjPDcwybGhCCurAkSTGVLT/56QSFvUlBRgac0vDgfta7Y01HBfcyfTnXJYGgo9TvadGLXDIq01sWSG3/ZP8s5nn+SrP/07jlfUcuctX8KzdDHrlpTYa7i/pYuyAjdlhR77sTs3189ZWXRZeQHD4QRW2uLE8BQf/P7TjE8lOTwYxukAv8uwX5N7/dmGeM9VxXSm0/LO5XuZvX4ZKC6EuNT88pkYlp77OUtnn3/bxsKXd1FCCCEuahI+CSEuSecrELhQIZYGblhezrFgZMZg8dnhx1wteUOTcUwLBicTfOqmyxkOJ+gYCjMSSVFb5ucr71xDY0sX/aE4z49GOTkeYzic4M7N9TzbG2IsmgZgPJpiIp4mlTa5azBMVbEPy7T4SPMP+LOn/pWn6hr46w99hRXVFezYXG8PNP/aT49weCCM4YD/U18+Y325f5eZfeJcwOsibSaJpkyeOj5KocfA5zIo8Di5e+uaGffY29bPqsoACmYMCz9bq+JLnb10utefrV1PCCEuNv3DaRKpudOnRErTP5J+mVckhBDiYifhkxDiknS+AoHzWdXS2j1GY0sXWmvunA5rzvSeCti9de2M507zF9Ez5OY93bqh9oyBy2Nt/fzm+QmeH4tysDcEwHduvYaPPPQM49E0oViaqmIP0YRmMp7GSqX59i/u5cYDT7D3tW/mB7d/Fo/bjVIqOwtqeu2HB8OkTI024X86x/jij39LMmPNmNWkga6RKIUeg/qKAm66sorHnx2gvT+E06FYusDP5YuKZpzSlx9Wzd6b+5o7ae+bZDiceNmrj2SguBDiUlOz0IXXreYMoLxuRU2F6wKsSgghxMVMwichxCXpfAUC57OqZW9bP4f6QqA5Y5i1qjJAc8cwGdOitXvMvm4+QVj+vCfIDhPfMr322RVcGrC0RcrUjEfT3PVwGzs21eNxGWjSZDQMTiYpD3gwQ5P83Y+/zrqOp/nbje/jHzbfyvVFfhYGPAyFE/a6VlUGcBsOMqaJqcHUmqZn+lhdXUzGtAjF09x0ZRWrq4tOaYHrCEaIpUzSpsWn37b6lGqn/LBq9vehlEKp7K9CCCFemjdc4+e7j0zM+ZxDZZ8XQgghzoWET0IIcQbns6plS0MNI5EkWmtWVgbsYGj2/TuCEdKmpnciNiNoWlUZ4ED3+IyT31ZVBugIRuyAaVdTO27DgQKCkSSH+kIcG4owGE4QS2bsGU9HB8P0TcSxtMZlKNKmZmQqRWNLJ8V+N8PhBBkLTA3e4SHu/9GXWDbYxadv/Dg/vOotGJbm+uXl7DsxykQ0Zc92uq+5k5RpoRQUuBSGw8HWqxeTylgMhROMRJL8zZMdfPItq+zKpfzPkmulm70nZ5vXtGPTMml9E0KI88TvdXDPRyvs0+60BqXA51bc89EKfF45s0gIIcS5kfBJCCFeJvlB1s6mQxw8GeJA9zi7Z800yg0RD8XS9olu6+vK2HdilHAiza9PjNIRjHCwN3vCndvpYCSSpCLgwe10kM5Y3NxQw9efOEoknqbHihJPm8RSFs/2hjg6FCFjWricDjxOB2trijkyGCaetnAoRcOSEnwug0N9IeqHe/j+o18iEIvwiW1f4Ze1V+PXmveuW0JHMMKhvhDpTPakOshWHvlcBpbWFHpdvOWKSpIZi1WVAY4ORegPxXEaiof297B9Yx1w5jbDufYuX/6sp9O9VohLmVLqRuD/AgbwgNb6a7Oe3wT8LbAWuEVr/cj0468FvgsUASZwt9b6h9PPPQhsBianb7Nda33wd/9pxCvJmuVefnRPDdu/MsjIhEl5icGDn1skwZMQQogXRf70EEKIl1Fr9xg7mw6xqjJAyrRwOx08Nj0vKff83rZ+dmyunz6pzrSf11qTzli09YxzbCjCZCyFUpBIm0xEUzzdPUbX8BSOWZ1nCwrcFPvdOB3ZSqZoysS0NIm0iWlaHBkMk0xbOBRYWrN761o+fdPlvHXkKI889CmcmTS3f+Cv+c3l63ngA+s4/JWb+OI7rmRVZQDL0sSnW+Uea+vnhuXlOB2KRNrE6VDsOz5K10iUPft76B2P4XUpPE4Ht26otT9vMJwg4HXa1WCt3WPz3stdTe0cPJkN4XJ7O9/XC3GxU0oZwL3ATcAVwPuUUlfMuuwksB34l1mPx4A/1lq/BrgR+FulVEne83+ptX7t9H8keHqV8nkdFBVk/3WhqMAhwZMQQogXTSqfhBDiZTSzymfNKa1i+XOdZs+bunNzPbua2hmbStI7EWPt4hK01iilsLTmtwOTpExN92iUXU3tFHmdeF0GU8kMOzbVs+/4CM/2hkikLSytqQh46JuIY07Pk/U5FTs21QOwvvXnXP3gTnqKq/jz2+6mr2gh/ulx5w8+1c2e/T0UeZ04lMLnNnAbDm5uqKGxpYuJWBqtYTSS5PJFRQS8Tm66sop9x0cIxdIU+7ODanc2HWI4kiSaNKmvKLCrueaqBjvdXuZXep3P4fBCXCSuA05orbsAlFIPAzcDh3MXaK2fn37Oyn+h1vpY3u8HlFLDQAUQ+t0vWwghhBCvNvLXF0II8TLa0lBjD8xeX1fG7q1rT2m5K/QYdAxFuK+585TT3rZtqGVZeQFOw8HiUh8Li7xcv7wcpRRLS314XQrTgqlkhmjKZDKeYXAyyePPDvC97ddx763X8I7XVvOpGy9n4/Jy6sr9KMDpgI3LK1i9KMA/v/Mj8L730bZoFe/Z9tcc8y4glbEIxVI0NneyZ38PA5MJDg+EsbSmvqKQ5QsL+dCDT3N0cBKvy8DjUly+qIh4yqR7NMrq6iK+t/06u5prz/4eukaioLW9H1saakhlLNzGzGqwM+1lw5IS7p4OqvL3VohXiRqgN+/nvunHzolS6jrADXTmPXy3UuqQUurbSinPaV63Qyn1G6XUb0ZGRs71bYUQQgjxKiKVT0IIMYf8WUK5cGiux+bzunxnGmCeey1K0TkyRSJt4pg+vW1XUztuZ3aQ+KpFRcTTIR59po/FpX6aO4aJpUz8boPSAg8T0RTxVIZYMkPukOzBycQpQ8pXVQZ48rkhNNnTi26oKyV6x4f54/96hMcvv4HP/MEnsDxuListoD8UI57WhGJptm2o5W9+3oGFwnAoSgvc/PxwEFNDKmPxrmsW2wFQbt25aqTc0PQbVpSTylisrAyw78Qo9zV3cufm+jmrwU5n9l6ez+HwQrxaKKUWAXuA27TWueqoncAQ2UCqEfg08OXZr9VaN04/z7XXXqtnPy+EEEIIkSPhkxBCzGGuFq75tHWd7ZozhVP3NXfS3jfJklIffrcTrTVa62x7mZFtL8uFNZPxFAsK3KRNi0XFPp4bCAOwrLwAv8vg1g21/N1/HYekCcDaxcX22g50j+M2HPzk2QEi0887EgmWf2Q7G597in/8P+9m96Y/pmZBASsqA4xHU2RMjd9tANnT+D755lXsOz5it/y5DIWZ0dSW+WcM/t69dQ33t3TZg9M7ghHKCz2kMha7t65lZ9MhfvP8GIm0hQK+t/06CZCEmL9+YEnez4unH5sXpVQR8B/AZ7XW+3OPa60Hp3+bVEr9E/AX52GtQgghhHgVk/BJCCHmMHve0ukeg5mB0uxr8p+D6UogI3s63X3NnSil2LFpGevrylBKoRQsKPTw6bettu9zZCDMge5xtm2o5fFnB3huIMzSMj/X1pba73N/Sxdaa25YUUHL8RH2nRjlD66q5qH9PTiU4sTwFNevKKe9L8SCAhfxVHYQeSwZpzg2yfce+TJXDR7ja7//UU685zb+ank5x4IRhsIJOobCJE1NyjR55mSI/z0Z4uqlJTz6kY1AdgbU0aEIhW6DQq+L2x88wJ2b6+0QqXs0alc/5e9Pa/cYw5EkLocD5VIoNWtSuhDibJ4GViil6siGTrcA75/PC5VSbuDfgX/OnYCX99wirfWgyv6Xcgvw2/O7bCGEEEK82kj4JIQQnFqRNFcL1+nauvKrnWbPcMp/LhhJMjaVxO92sqjES3vfJEphV0nt2LTMDmby32tvWz/lhR6OBSMMTsbJWJqpRJrdW9fa675jOsC6/cED7Ds+itawsMjD762upLljmETa5N+e7iWesegLJSnyGlxXV8a7iuK866/+kvLJUT727s/y69dsZB3QMl3VtGlFBfs7x1Bgt/Bp4JmTId78rV/x1XeuoSMYYUmpn9HpQei949DY3Mnetn6C4YRdtTX7c+1sOsRUIsNVS0qoLPLap92dqa1RCPECrXVGKfWnwM8AA/hHrfVzSqkvA7/RWv9YKbWObMhUCvyBUupL0yfcvRfYBJQppbZP33L79Ml2P1BKVQAKOAj8ycv7yYQQQghxqZHwSQghmF9L3emcriJq9nP3NXfiMhysXhRgx+Z6Gqcrn3Kvyw+bjgyE6QhG2NJQY89JuunKKlZWBnhofw+3bqidse77W7rY29bPZCwNWpOxYCCUIBJPYwHDkWQ2QJpOkOIpk2sGO9h2z8cxTYs//dA3GV9zNdf6XYxNJTk8GAatOdA1xqaVFTz9/DiRRBrTwj4drzPvVL77W7pImxYlPhclfhcoRddIlIDXScPSkhmD0xunq7Q2rahAgf3czqZD8/4O5jN/S4hXA631T4Gfznrs83m/f5psO97s1z0EPHSae77xPC9TCCGEEK9yEj4JIV61ztQudy7ONOh69nNzVTbly5/LVF7osSumwok0vz4xyh2blrGubgGrq4sA7ODnQNcYsbSJy1D4XAbp6VlO8ZRJgcfAaThAa1TKxNKaD448y53f+gqpqkV84N1f5Dl/OSXhBJ+66XK+/sRRMqbOhkzK4lBfiBK/mwK3k4xloRQMh5N4XQYrKwOsrytjb1s/kUSGQo8BSjE+lcQxPQ/q5ryAaG9bP4f6QqChqsg7Yz7UuXwHLyUsFEIIMX9LFrpm/CqEEEK8GBI+CSFetc7ULnc+5YdcNzfUZE+0y1tDfvVOLoC56coqjgUjdsVUNJHmv0+MMhFN4TReOD3ODn6SJhrIWBrttHAAFlBV7GXTygpubqihsaWL9r4Qf37kZ7z/X77F1FVX89nbd9M1oUknTcKxNLua2inxuXAZDlxo3E4HhR4Xw5EE8ZSJqUGhqQh4WLKggH3HR+gIRvA4HfSOR0llLDJWtjTKtDSLS/0zAqItDTWMRJLo6VAqX35Alf/zXF5KWCiEEGL+Pv+h8gu9BCGEEJcACZ+EEK9aZwow5tPWNXuY+Omu39vWz8GTIQ50j1Nb5ieaNHmsrR8Np1TvzK6Iau0eA8C0IG1ZtPeHWFNTYp8eB3BsKGLPY3IABR4nDmWSMjXhRJqhcIIjA2EmwnH+/Gf38/59P+K5dW/g7z/0JX4zksDUmopCNyiF23BQ4ndx/YpytNYsWeDnX1p7yFjZezM9E3xRsY/6igKCkSRdI1FGp5KkTU3GsijwuNBa4zIcpE1rxv6eqUost1fzqWg6232EEEIIIYQQrxwSPgkhXrXOFGDMJwTJv2auIClnS0MNB7rHcTsdOJSi0GMQjCS5YXm5PfMoX36o9bWfHuHwYBgHGq3BNGFwMk4sZbKrqZ3aMj8nJ2IUuA0sbeEyHEwl0qTMbE4UTpjsOzbCka5hPvfIN3jbkX3889Vv55tv/RNWZBwsLfUzOBlnx6Z6VlcXzWgLBHjdPb8gle3gQwNlfhdXLSlhx/Rpdq3dY3al1r7pIeV3bFoGzGwxzJ/1lH8S3uzPPRxJks6YBCNJWrvHJGASQgghhBDiEiDhkxBCzGE+bV2zrznd9evryti9dY39/N62fg72htizv4fdW9ectlLq588NMRZNoxQs8LtwZSzCSZOJWBoAl+Hg2d4QaVPjQONzO0lkLKbHPQHgdCiKE2Hubbqbq3t+y92vv537r3snKp0NsVZXFxNLm/Za8mcwQbbCaXAyiQYcCjt4ym+Ny61/+8a6Uz53/mfKzXo6XaC3t62fqUSGyUQGl9OQeU5CCCGEEEJcIiR8EkKIPPlVR7ODmNnmqpw63byi2dc2d4wwNpXgA/94gE/deDmrq4vY29bPqsoAwXCCyUSacCIDgKHg7VdV84P9PQAk0hbJtMnYVCobPDkUpqWJpKwZ7+l1KjZ7YnzmgU+xeGKIz93yWR6p34hHawJeJ8V+N2jNZCxNNJmmsbnzlHV/6qbLuevhg0zGUxT7XHbwdLA320Y4V3g2154GwwmWlvop8btOG+jNNe9KCCGEEEIIcfGT8EkIIfK8lFPUcq9tbO4847yo9XVlrK4u4r+OJMC0aGzpYvOqCg6eDPGTZwfwuQ0i8TQOsq1uWsOhvkl7rpMGJmIZuxopN+A7R01fs7zvOF999Mt4zBQf/8DXaF1yJR5Lc01tKTesqKCxpRO/y6Cq2EvfhIVSas61fvuW13J/SxeWzr7PloYannxuiHAizTeeOMqjH9l41n2JJk1WVQXOGOjJHCchhBBCCCEuTY4LvQAhhHgl2dJQQ31FwYuqusm9FqU42Bvirh8e5PYHD9iDwSFbBbSz6RA3LC9nQYELpwGLir1saaghZVosKHAzHk1hAQkzG/ZkNBwdDGMohUE2XLIApcA4zf+Kv77zNzz8L58h6TC49QPf5L9rXoNpWZQXerhhRQV79vcwNpWirTfEybEo8ZTJ4lLfjHvk1gpQEfDYg9LX15XhcTrQWjE4mfid7qkQQgghhBDi4ieVT0KIS8p8Tqk7k5dSfZN7bWv3GLua2okm07T3Tc6oosrNc2ruGOaysgJK/C57eHduLpTb6eDR/+0Dbdrzm2JpCwfgMhQ+t4GhFCgITc9/yjEUvPvgz7j7Z/dydGEdn719N/HyhRhTScoKvSwpK+DxZwcYmkyQnA63RqNpfC6DJ58LksxYrKoM0HJ8hKODYYp9bhSnzrfasameh/b3cOuG2nPe09nfUWv3GPc1d6KUYsemZVL9JIQQQgghxCVGwichxCXlpbTNzfbgU93s2d/Dtg21pwzTPpNckHT/9Olu+RU/WxpqaO4YZjiSZHQqxaaVFQDsbDrEqsoAGrisrICVCwMcGwpjOCBjWZgmmGRb7Ao9BuF4htj0MXROB1QWeXnz6oXUfPtr3NH8L7Qsu4Yv3Pp5RnFjheIk0xYTsQyJjEXGtDAty27PcylwGVBV7KVrJMqB7nHGppLT91f2iXX5+7l9Y9057Um+2d/R3rZ+2vsmUer0w8iFEEIIIYQQFy8Jn4QQl5TTnVL3Yiqi9uzvYTiS5KH9PXbQMp/75K65Y44qnvV1ZVy+qIiRyAimpWnrGeeuH4Yp9rl48rkhppIZAh4nyqGIpi30/8/evcdHWZ75H//czxwzyeQcAoSDGA5CBUVR6SLQ1p50f1aKW3tYbWlVuttu97fWri20tWortmztbndrW8G2uNittZaC9eeptjVQXALaKFEgHBJDEnJOZjKZ4zPPc//+mMw4CQkkiJy83q8XJZPnmWfuefJ6peOX67puDU6HwukAy9JYGpoD8Uxw5FBw0aRCvnrV+RTf9iWmV/2WJxdczROf/wZGMEFR0qa9L0ZyYCxUIJLgyx+YxbYDnTT1RukOxTivNI87rr4AgO89tZdgJEE8kUSjGJ/vGdX9Gsv9HfozmlXup6qugwkFOdKaJ4QQQgghxDlIwichxDklu/Vt1abdmTDkRCqiblo49ajWstEMFT/eay2ZUcarTQFCMZNYUmNpE5/LAVpj2RBOJDEtja3B41DkeZygNPFwave77DFPXpeD8SrOrJs/ScH2Kv79yr9n3dJP8tXZE7AOdhEIJwjHTZRpY9s2M8b5mT0xnxWLprFq027qO8NUluVm1hmMJYlbGhuFQ0F/PMnND+9Ca82SGWXUtYdYNhAQZb//9Htev7X+uCHU0CqquvYQk4tzB61DCCGEEEIIce6Q8EkIcU4aGgCNVBF1LMO1lqWv0x6KD7p+duVP9msNVxFU1x7CUAqf24nP7WDOxAKunF7Kllda6AjFiSWS9JhJFOB2GUwv91PbHMChwGkoSvLcuBwGbcEYxYEOvvzQPeS2v8Ed1/wLj819PyThB3+oo6LIRyJpk+txYVoJyotyqWsPcdNDO5hbUci1F01EwaB7kg7clIJg1KQ/brG7OQAaGrsjmEmbJ189wvRxebidjqPub1tfbMwh34n8bIQQQgghhBBnD6W1Pv5ZZ4kFCxbol1566XQvQwhxBqhu6M4EGmOpphlt+9jQ62dXEa1ZPi9z3tDvVzd0s25rPb39cYrzPJnWvOzz3E6D/6luxGkYFOW60BrmTSrkYEc/Ny6cyhvdYR7Z0ciMjjf4+WN3kZ+IsOoT3+CJ8fMGrXFigZfxBV7aglFcDoPOUJyIaWeOX3VBGT9bcfkx39/Mcj9/OdhFT38clOK1lgCmlZoRtXhGWWZY+lu970KMllLqZa31gtO9DjGYfAYTQgghzm1v9TPYCJt0CyHE2S019HvemAOQ7IqpsVx/2fwKKstyj6remVXup6s/zsxyPwDrttazuzlAcZ6Hhz5zGZAKqDxOI3NePGkzf0oxOW4HrcE4fbEknaE46X8q2Hagi0VNr/HrR75KjgP++NPH+MOki1ADx10GzByXy4QCL029EQylaAlEcTsNPA6FIjWkXCnFSNLvD6ChKwxK4XIY+L0uDAVuh4PyfO+wM61O5L4LIYQQQgghzl3SdieEEFlOtAVs6KypWeV+6tpD1LWF6Iua/P7VI6nHrUG6+xMc7g4Db4ZdXf1xSvM87B+YqbSlpoWDHSHQYNua1mCUUNzikR2NfKFlBx/5n2/SVDaJH//rD/nY0oXMiezj9SN9TCnO4dLzilk2v4IHqw5BD3SEYtg2JJI2q66ZzWOYN40AACAASURBVF8OdqG15tYl5x/3fW3c0ciRQIzWQJR3V5bwpffNyDxf2uSEEEKcLvc81EVTh8nkcS7uvKX0dC9HCCHEcUj4JIQQWYYOwz6e6oZuHqw6hFKKlUvOz1Q2VdV1UpDj4mBHiKQN8aSF02HQEYqjNbQGYpmKp6aeMHkeF3keBzPL/Zm2v55wguf3trNkZhkLzy9h/dZDfKbqV1z/+3W8NO0i/nH5asIBJ0/9fCeFPid5Hgfd4QSvNAXoDMVRSjFvUgGHeyK80RXG53Zkho0P9z7SrwtvDhO/aeFU7v9DHUU+D+X53mHnYAkhhBCnWlOHyaFm83QvQwghxChJ+CSEEG/B5poWapuDKAVbalrQWoOGCQVeAlEz0yrnMgwqy3LpDSc43BPB4zIyFU/heJKecAK/18nGHY2YSZuqug7a++JYGl481MVPP3kxU7/5Fd775038cf5V3PPR2ynKzSHcGyWetGnrS+B2GDgMaO6NkONy4HKkXnPl0kpWb6rF7TSGHZCevVvduqpDvNEdwe0wUMCa5fOYPTFfBoILIYQQQgghTpiET0IIMWBoIDOa4eOzyv1U1XUwoSAnE85kBzXf3PwaTd1hrr14Ind95EI2bG9g445GZozL40BHPzPG5dHcE8HScKAjtQte3LRI2hprILnSoTC75i/lva+9yPq/+RgPfvBzKOVgerGPT10xlR/96QDhmInLqXAZinEFORT5XJTnezODv9csnztoXekKrc5QfNBude2hOG6ngZm0M+eOphpstIPahRBCCCGEEO88Ej4JIc5oJxpqnMjzsqt/Nte00BGK0x9LZqqF0tddt7UerTWfX1pJXXuIghw3gajJ3iN91A3MbEqfP7nYR0tvhMd2NXFeSS517SFK8zzsbgkSjCR4oyuM01AoBZG4hTIU00p8HOhIzYQqDffy803f5l2tB/nGB7/Ary65hvP9XoJRE6UUKxZNo649xPN720HDlGIfgajJ4hllg9rjhgZIWmvMpE1NYw83P7yLxdNL0cDi6aXsbw+Nebe67EHtEj4JIYQQQgghskn4JIQ4o51oqDGW56WDqlnlfhTQHopT3xkmz+MYtINddUM3qzfV0t0fx+VItbAtm1/BzoYekpbN/X+oI8fp4MlXj3D9pZNo6o3ySmMPkYSNoeCRHY3cO1CBlEhatAVjAGg0Boq4BixNQ1cElwEVXS08/NidlIUDfPH6r/Ns5RX4XAb5Xhe2hklFOdz88C56+uNMKfJR6HPRGzHpi5psO9B5zNlMS2aUseuNHkwLapsDvNEVpjTPk2m1G4vqhm7a+2L4vc5jtuZJdZQQQgghhBDvTMbpXoAQQhzLsvkVgwKgk/28dKD0SlOA/e0h1iyfx8ol52dmJaWDmFWbdvNg1aGBuUoKl0Mxs9wPwNQSH6alKfK56YkkSGp4bFcT2w90EUtq8jwOFNDRF+Pp2lbaQ3EAppflMqHAy7smFpDjdqBUak2mrbmoaS+/++W/UmDF+cHqn7LwXz7LJVMKKchxA1Ca5+HJV4/wwr4O9rf3M2u8n5+tuJyiXDemZfPK4QA3P7yL6obuYd93XXuISYU+CnKczJtUyE0Lp5LncdAeio/4nJFsrmkhHLcY5/ccM1TKDgSFEEIIIYQQ7xxS+SSEOKONdfe5sT5vc00LbsexZxylQ5OkZZOwbIpz3QQiJr9/9QgbdzTidhrMmZjPOL8Ht9PgLwe6UAo6Q3EsS5NI2iQ19MUt/vvFRpQCpWDpzDJ+tuLyVCtf1SHq2kI0B2J8uO5F/uPJ7xMeN4Gff/0BKi6aw9YDnbT2xXAaitZglDkTC9BaY2sIJyxeeqOH6oZuVi45n9VdYdqCMbYf6EINvJ+hPE6D5t4I1186ibs+ciGQCqROpMosPS/qeEHfaM8TQgghhBBCnFskfBJCnFXeautWeuD3TQunsmLRNJbNr0ABM8v9bB6oyBl63WXzK1hXdYi9bREKclwD85agNRijIMdFX9RkQoF30Jyk6oZuttS08OzrbYQSVuZaNoBO/XnxUDef27CTJTPKGJfvZW9rHytrnuBrz61n33lz+Ppn7yWW8NP8XB221piWRgE5bge94QQ5bic6kkQBDV1hVm+qZc3yuaxZPpfbHq0hkrDQWg97z7Yd6AKl+MuBrqPaDscSDo3l53GiQaIQQgiRLRKz6QvbAPSFbSIxG59XGjqEEOJMJr+lhRBnleFat6obulm1afeo2sU27mikIxTnkR2NAAM7wc0bVPUz1BXTShiX76XA68JM2nxwTjl+r4t5kwpIWDY+t4PaliDrt9YDqYBr9aZaZpb7mVqSm7mOAXidKvM4atr8tbGXtc/s4+lXm7n9mQdZ/dw6Xpj9N3ziY9+m051LMJqgONeN1uBzO3A7DWKmRWN3mI6B9j2AghwXbqeRWf8FE/JZcF4xK5dWZu7Z2qf3cdX9L7BhewM3LZxKud/DjQunZo6n2w5PdLaWEEII8XarPRjjhlUtdAVS/7DTFbC4YVULtQdjp3llQgghjkXCJyHEWWW4WU5jCUCyQ5fjXXfo8YqiHKaU+GjqjeJ2Gmzd30lXf4yW3ijd/Qn2HgmwatNu1m09RFNPhG8/uYfD3f2ZaxgK8jyDC04dCry2yb2P3cf1Wx/nd4uXc+v/uYM+w017KM7sCfksml7KHR++gGvmTmD6uDz8XhdTin34vU5cBsyfXMADN17K/MmFXDe/YtAMJiAzDLw1GM0EbysWTePGhVPZuKMRj9M4oblao7lvQgghxMkSidmseqCTSFyjdep7WkMkrln1QCfRmH16FyiEEGJE0nYnhDirDNe6NZZZQisWTTtqF7jqhm7Wba1Hpz/JjqChK4zbaTCxwEsiaaMURBI2SUujgba+BK8cDpDncdIaTFUldYWTmefbmkGvoYALc2y++t/fZM6h3dx31S1sXPhRlJ06Od/rYuXSykHvt7qhm+89tZe2UJxrL5pIYmBW1dD7sqWmhZnlflZvqsXtNJg/uZArl1TyyI7GTPCWrgL7y4Eunr/9Pce9d8ORVjohhBCnyp9fjmCP8H/Vtk4dv2ZR3qldlBBCiFGR8EkIcdYYab7QWAKQ7GtAqmqqIxRnd3MANCMO284eTD652Mfe1j4cSmFaNh5H6kNvntdFcyBCud+D2wGmlWqziyZTn5RtIGmn5jZpYGqwjXs33MO4rlZWf/zrPHnBldxwySSae6NorVm5tJK9R/pYvamWxTNKiSdtls2vIBhLEoolee71Ni6YkM/3nt5HUa6bxdNLqWsPMavcT3sozgt1HTgdRmaO0xXTSgYFbzctnDoojBJCCCHOZC0dJrHE8OlTLKFp6TRP8YqEEEKMloRPQoizxrqt9exuDtAZip9wtU12i54G6jvD5HkcXDSpEK31UdVTQ4dxzyz3c/9zdSQ1xBIWSkHShosmF9LWF6PA6yUYM7F0KmyKJwd/SA7GUjMq5rYe4Oe/vRu3lWTFJ7/DK+fN5Y4PzMqEQ+lqrBcPdIIy+O1fm5kzoYAtNS2Z0Kggx0Vtc5BQzCQ/x8UbXWFK8zzsbOihL2aSMC3K/F7uXT532Ps1XBXYcO/9RIe7CyGEECdTxTgXXrcaNoDyuhUVZa7TsCohhBCjIeGTEOKsobWGIa1rY7VsfgXrt9bT1hdjyYyyQVVB2dLBS3tfjNZAjKq6DmZPLKCtL0aRz00gmmDueYW81tKH1pr6zn7G+T0krNRA8l/vOkzS1gw3feK9h3bxwJbv0pNTwCc/cR8HSyfjSNr8T3UjG3c0MmNcHtsPdmFaNqal8Tg1118ymaaeCO2hONfNr+D529+TCqiqDhGImBTlurlyein720NcfeF4/nKwK1M9dTKCOgmfhBBCnG7vvdTHTx7vHfaYoVLHhRBCnJkkfBJCnDU+v7Ry1LOdRnLFtJKjdneDVNj0YNUhlFKsXHJ+5hy/10lHX5SeSJJgtIsLxueTtG2mj/Nz+4cuYHNNC0/XthIzbfrjFpOLfSSSNh+/bAobX2zE5TJwG4pwwkIBH3/lGe559sfsGTeNz/3dXXTnFQFgadjfEcbjUBzqDGda83LdBgvPL+Guj1zIzQ/vYndzgLVP72PmeD/L5lfwsxWXD/s+h6toGmsl01hmaQkhhBBvN5/X4L4vlqWGiydSQ8eVghy34r4vlpHjlb2UhBDiTCW/oYUQZ40rppWwZvm8UQUnG7Y3cNX9L7BhewOQCl5WbdpNdUP3iDvm1TYHqW0OsGUgoPF7ndhakxgYKG5aNoW5biIJi9rmALc9WsOscj+XTi1iSomPUMzkYEeImeV+4kkbr9sgZtpMLPRyXomPf922kXuf+RFV0y7hls+upTuvCKcDnCq1BgVYWuMyUsGTx6Eo9LnRA+vvDScIRU3e6ApT3xlm/db6zHtKy36fQ412V8D0NYBR328hhBDiVJg73ctv7qugtNABQGmhg9/cV8Hc6d7TvDIhhBDHctzwSSn1gFJq0du5CKVUoVLqcaXUPqXUXqXUu5VSxUqpPyilDgz8XfR2rkEIcfbLDl7SO7k9sqMROLqFbGiosmx+BfMmFTBvUmGmDa/M7yEct/A4DbxOg/NK8+gNJ+iPJzFt6Isl2d8eYuXSSloDUSIJi3A89b1l8ysIJ1JNdw1HAqx7/j/5/PZf8z8XfYh/+LtvEjC82EDCApehqCj0Mn9yAd/42zksmVnGzHG5lOS5GTewhnVVh2gLRvE4DUry3DT1Rqhp7OGVpsCgMOlYAdNwodtwRhtSCSGEEKdDjtcgPzf1nzH5uYZUPAkhxFlgNG13+4HvK6UmAI8Bv9Ja15zkdfwQeEZr/XdKKTfgA1YDf9Raf1cp9TXga8BXT/LrCiHOAel2so5QnP5Yki01LSyeUcqml5u5ckYpcPwWsuwd89IhVnrI+NUXjuf3rx6htjmQGiQ+MHIqblrsbOjm2ddaMS0bhwFTin289EYvL9R14AB88TAP/m4NlY2v8v3FN/Gjd9+Ax2lgGEBq9jgWmiUzyzLtcCsWTWPVpt28eLCLPUf6yPM4KMnzEowm0Vrj97rojaaGmptJe9B7Otb7HO2ugNJuJ4QQQgghhDiZjhs+aa1/CPxQKTUV+ATwc6VUDvArUkHU/reyAKVUAbAEWDHwegkgoZS6DnjPwGkPAy8g4ZMQ56zRziMael51Qze3PVpDOJ6ksiyPCybkc938CjbXtDB7YgFNPRFWbdrNsvkVmflOkGrL27ijkZsWTj1qPtLmmhZeaQqws6GHmxZOpa49RGN3mMSQ6eG2Dc29USydapnL97rojyfp6k9ga5gc7eGnv7qT6d1NfP2jX+HRWe/B5zSYVJRDfVc4cx2FGlRplN5db0tNC3FLY8eTeFwmlm3jMBStwShFPjf9MZMbF04ddL9GCpjGMu9ptCGVEEIIIYQQQozGqGtUtdaNWuvvaa3nA58ElgF7T8IapgGdwC+UUjVKqYeUUrlAuda6deCcNqD8JLyWEOIMtbmmhVcOB1i9qXbYeUXZ5w0NaiIJi3jSpjjPk2mnS7eYoRSvNB193XRb3rqt9dz88C4+t2En1Q3dbNjewHOvt3GoI4SZtNm4o5H6zjBx883kaWBEExqYXJRDjlORsDQ9YZNwPEm+18m7+5v59S9uY1KwnS/d+B3ar7uB98wq44bLUrvW2QOXcyh47wXj8HudtPXFeLDqUGYY+qSiHBSQ43SwckklcybkozU4DQPL1kwuzmV/e2jU91da6YQQQgghhBCnw6jDJ6WUUyl1rVLql8DTQB2w/CSswQlcAvxkINgKk2qxy9CpfdWH3VtdKbVSKfWSUuqlzs7Ok7AcIcTpsGx+BQnLxu00jhmQDJ1btGx+BQvOK2bR9FJuXXJ+5rz0XKfF00tp7ArTFoyy9ul9mZlQNy2cSrnfw/gCL7ubA9Q2B1lXdYj7n6sjEDGxbAhEEswYl0dXf5zxhV4Kc5yU5Loyr2EDU0vz6I/bmcfhhMXcfS/x0/VfRinFDTeupXb2ZZT5PaxcWsm2A10kdercHJeB3+vEtOzMfClDqcz7m1TsozTPzWXTipk9MZ9gLEmZ34PbaXDTwqmjmt800n0TQgghhBBCiFPluG13SqkPkKp0ugbYCTwKrNRah4/5xNFrBpq11tUDjx8nFT61K6UmaK1bB+ZNdQz3ZK31OmAdwIIFC4YNqIQQZ6ahrWBrls89atbQ0HOGzmbaXNPCrUvOH7FNrK49hMupiJs2rcEoEdOian8nF4z3c+/yuQCs31qP1preiImtNUqBoaAo183uliCmZTOlyMdl5xUzs9zPd57cQ3Lgt01PfxynIzU4HODa3X9i7dM/pL54Erd84m7a8kvxRkyerm3lyVeOgALT0iggkbRJ2ppXDge49uKJdPXHufrC8axYNI3qhm6UUsybVMDKpZU8WHWIrlCMXI+LtR+bm2k53DwQ1EkrnRBCCCGEEOJMNZqB46uA/wFu11r3nuwFaK3blFJNSqlZWus64Cpgz8CfzwDfHfh7y8l+bSHE6TV0B7rhApKh5wx3bP3W+hHnGS2bX0FnKE5jVz89EZOW3gjhmEVnKI4Cfrbicq6YVsKG7Q2sfWYfhqEY5/dSkOPCtGyKc500dIXZ39ZHY3eYZ19vw8qKuTtCcRyGgqTNP/3vY3xl20a2T53HP3z068R9eSQtTUxbKEthWhqHQ+FxKJRSGAriSZtY0mbbgS5K8zyZNrrNNS0cCURJJFNVVUopPC4HcybmZ97jse7NsYxl/pMQQgghhBBCvFXHbbvTWr9Pa/0QEFBK3aiUuhNAKTVFKXX5SVrHl4BfKqV2AxcDa0iFTh9QSh0A3j/wWAhxDhnaCpbeZS57NtOx2sXSx2ytB80zyr7OFdNKeOgzl2GTmsuUtDSGQ6FIBTp3PfEac775NHf/fg9R0yaasIgnLXxuB/cun8vXrpmNw1CEEjZdYZPusInL8eYamgMxEvEka579EV/ZtpHfveu9rPjY3YQ8uSQsjQYcSlHm9zC9zEe538NFkwtI5VU2SoHXabB4RilNPWHq2kJUN3Sn2hCTNm5Hqg1x5ZLzmVtRgB54f8e7N8ci85+EEEKc7SaPc1E5ycXkca7jnyyEEOK0G03lU9qPSY0peR9wDxACfgtc9lYXobV+BVgwzKGr3uq1hRBnluHa6NKGq+TJrvLJfpz+Ot1+lt2ulx5evrOhhzXLUy1qNy2cyvpt9YAmlrA4rzSPW5eczy0bdhHJGiZuawhGTWoOB/jCxpf40lUzMZODt7mzLMhxGiQsG088yo+2fI/31b/Ej959A/cvvgmvyzHoOXFL84E55dz1kQupbuge9JoOBR6XweGeCKalaeqNsH5rPbbWFOa4KPS5uG7gXo2mUmw0ls2vOKq9UQghhDib3HlL6eleghBCiDEY9cBx4Aqt9ReBGMBAC577bVmVEOKcdayqm5EqeY63E156uHg6iFk2v4JgNEF3f5x1VYeobuimrj3EBRPySSQ1ltYEoiZ7j/RRnu/B41DkOBUuh8KR6qDDBrojSe76/R5Me/A4OQvQaN6Tb/H4r1eztOGvrPrQP/H9JZ9GK0XStvF73vz1qoE/7GkHYO3T+4hmBU9OQ1Hgc2MMzHeaN6kQW2tqm4M09UYoz/cOel/p+zNcldhoDb1fQgghhBBCCPF2Gkvlk6mUcjCw65xSqozUf58JIcQxZVc7HavqJruSadWm3cwq91PXHmJWuZ+dDT0kLZvVm2oz1UyjoZTiwapD1DYHKcxx4nIotDZIWjZrn9mHZdtYNmgD0OByKJLJwWGT01D4XAYR00YBXqdiTt8R1vz0TvL7erj1+m/yp8o3i0BNG6yEjcGbvyTL/R4AWoNRtE4NHPd7nVSW5TFrvD9T3QRw1xOv8b8HuyjJ89DWF8u0D2ZXOq3atPuE5j0JIYQQQgghxKk2lsqn/wR+B4xTSt0L/AW4721ZlRDinDK0Xex4VTfp8zfuaKS+M8z+9hBrls/F6TAyM5CyZVcBVTd0s3pTLU6HQWmeh1uXnI9SCqUgbNpMLs5lakkuPZEEpmUTtyCpU7vVmTaYdioYyhaKW8RMG7cD8jwOLmnaw8/W34YjFuXWz32fbTMuozTXRWnum3m+0qkd8/LcDvxug7ZQnA3bG/jgu8ajFBR4HZTmebjj6guOuh/bDnThdDoIxkzCceu4VWJvpQpKCCGEEEIIId5uo6580lr/Uin1Mqk5TApYprXe+7atTAhxzhjrjKH0+VdfOJ797SFmlvvZXNPC4hmlbDvQhdtpsGrT7szcqOxwSwOmZdMbSXD7B2ZlQp0tNS24nQbbDnQRTZjEEhZag9uR2oUuXetk2al2uCHFT9ikAqqr91Wxdsv9NBeM47Mfu5twxWTygVyPk8M9USD1/OJcN4U5TmwUgUiCUCzJIzsauWxaMTPK/ZhJm3tHqOC6aeFUHtnRyJUzSkkk7WNWiYFUQQkhhBBCCCHObMcNn5RSd2it1w48nKu1fiDr2Bqt9eq3bXVCiHPCWAdjDz0/Ha509ccpzfOw7UAXpXmeTEXQvtY+2kNxrr5wPLMn5lNV14FDKbYd6GTFomkAtIfivNLYQ9LWxEwbW6fa6UryPDgNRVNvFE2qr3ho8JT2z6/+nn95dh1/rZjNLcu/QSAnH2fURGtAa9wORdLWVI7LY0qxjz1HghT43JxXkkswanLjwqnMnpiPgkyglB2iZbcnPn/7e0Z9v2SAuBBCCCGEEOJMNpq2u09kfb1qyLEPn8S1CCHEsNItZotnlNLVH2fxjNJMy9nmmhaae6MkLZv97SGumFbC7IkFuJ0GSqUa6DbXtLC7OUBf3CKSsDCM1PedDujuj9MWjDJC3gSAw7b4wYu/4MvPPMif5yzijpX/RsiXCpHSm9oFokkSlqY414XWmj/v66A1GKelN0KBz8W9y+dmgrD0aw0dvp4erH7bozXc/PCuYdvohmuxu2JaSeZeSOudEGc+pdS7TvcahBBCCCFOpdGET2qEr4d7LIQQJ116TlQ8aVOa5yGRtDNzkpbNr8jsEpeu/Fm55HzmTSqkuz/O8h9vZ9v+TnpCCZKWxtaQSNpoDeGExrQ11jGSp9xknAe2fI/l237Lo4uu55a/vYPWeGpYeKZVT6f+aKCr3+RwTyTzuC9mcaijf1DAlA6chu7ut2x+BQnLJpKwqG0ODDvraaTdAo+1i6AQ4oyzMf2FUuqW7ANKKd+pX44QQgghxNtrNDOf9AhfD/dYCCHeFtUN3bT3xfB7nYPay4Zr6UvPgXq1KUAoZmJaGmvgWHbQpACHSrXKDacoEmT9pu9wScs+HvvUbayafBUaiCY1k4rcRBMWiax5UZAaMj612EdrIEY4YaGBlkA0M6fK4zTo6k+1CKbXvTkrMDqvNJcCr5PiPM+wbXQjtdhJ650QZ5Xsf7z7AvBQ1uNtwKWndjlCCCGEEG+v0YRPFyml+kh9UMoZ+JqBx963bWVCiLNW9uyi4WY9He/4cOdtrmkhHLeoLMsd8TkbtjewcUcji2eUsr8thG3bTCn2EUlYtAZjeJypYs+ImeqVS41q0hiQCafSJgfaePixO6no6+QLy77GH6YsSs12IvXLT6NYdc1s1m+rx+dKtfg190YpzfOw4Lxirptfwfee3sfrLUGcDsVze9qZXOTLzK3a3x4C3qxYWr+1noauMG6nwfzJhaxZPm/Y9zjS/KyxztUSQpxW2Zn10CrysexELIQ4A93zUBdNHSaTx7m485bS070cIYQ4Ixw3fNJaO07FQoQQ547sFrDhApHswOXBqkMopVi55Pyjzh3aorb26X28UNfBhu0NmflJ2dZtq6cjFKepuhGlFF6nwYLzitFAfWeYyrJc9rb2UdMUzDxnuOHi81r387PH78FpW3zqE/fy8qQ5mf9UVEBxrgulYMsrLVwwIT+z9uqG7kz10eaaFlwOg5I8D6ZlM97vwe91Ylo2eR7HoFa7LTUttPXFcDsMzBF2txNCnFPGK6VWAK9ydPgkVeVCnOWaOkwONZunexlCCHFGkX9dE0KcdENnGY103Naa2ubgiPONhl5nf3uI3miSR3Y0Zs7JHsBd7vfgVOAw1MBudgYzy/1s29/JroYeDnaEaA/FR1y3Aj7eWsOjv1pF1OXh+hv/jZpJc/A43vxvw5JcFx9813gCUZM9rX1HrV0De4/0ZVoEP/iucvJzXHzk4go00NQbIRAxM8PB0/OsPr+0kvlTCrl3+VyumFbChu0NXHX/C2zY3jC2my+EOBvcRaq17j+ASUqpPUqp3yql7gWkTEIIIYQQ55zRtN0JIcSYHK8FLH28uqGbdVWHCERM2kPxTBgz3HVWbdpNjstBbyTBlTNK+YeNL/H83nbG53vx57h47vU2FDBnQj79cYvDPRFK/B7WbT3EkWAqcNr5RoBxfjeOgYAqkTUASgGfrX2Grz/9Y+omTufTH/0mXblFAJiWTvUduwz+6X0zAKja30lprgutUgEXvLlb3ZOvHmFSkY8cl8GLB7uwdaoqq9zvAQ2twShOhzGoMiz7nqzatJuqug5CcYtHdjQOW+UlhDir1QLrtU418yqlJgFzgXnA1rFcSCn1YeCHgAN4SGv93SHHl5AKueYBn9BaP5517DPANwYefkdr/fDA9y8FNgA5wFPA/02vVQghhBDiRBw3fFJKvRvYIR86hDg3jXb+0ttxzXTgsmrTbuo7w6x9eh+twSjjC3L46tUXZJ5b3dBNRyiO06GYXu4nkbR5fm87SRtaAjFywgkipo1DgdsZBzSWbbO/vf+o1wxEEnhdBlqDQhO3wNA2X93233z+fx/nT5WXsf4L93K+z0f3G4GB+U6psCrH7WDbwS6AYec3LZtfwc6GHopz3ZiWTTBmEkva2BoicZOSCfnMnpDPzHI/+9tDw1aGpVsNJxTk4Iua3Lhw6lv+eQghzjifBh5QSu0HngGe0Vo/DTw9/ToyawAAIABJREFUlosopRzAA8AHgGZgl1LqCa31nqzTDgMrgK8MeW4x8C1gAalfcy8PPLcX+AlwK1BNKnz68FjXJoQQQgiRbTSVT8N9QGp7e5clhDhVjjef6WRec6RQKj336IW6DjpCCXrCiUHP3VzTQn8syewJ+ZTne7lufgU94QR/3NtOmd9NJGETNVMhT1swlhoknrWefK+DcNzC1pCwwOWASUU5NPdGcSXirH3qh3x0zwv88uIPc+cH/pHyuEGONvG6HSitmT0hnze6wwSjJi+/0U1lmZ9A1GTxjFISSZuZ5X5WbdrNsvkV3LRwKht3NGZCo//60wHMpE1lmZ9bh5lrNVT2rnUyQFyIc5PW+h8BlFIXAFcDG5RSBcCfSX3W2q61HroPwnAuBw5qresHrvcocB2QCZ+01m8MHLOHPPdDwB+01j0Dx/8AfFgp9QKQr7XeMfD9/waWIeGTEEIIId6C0QwcP1kfkIQQZ6DssONkSFcpZQ/VTodO7X0xwnHrqFAqXQG1YXsD67bWk+dx0NYXy7TheZwGe44Euf7SSdz1kQszzyvKdeNxGjz3ehsOQxGKJQe10qX1xSxcBlg61V7nMBSTS3Jxhfr45m++xcLG3axd8ml+vPBjoBQTCrxce9FE1m+rZ5zfwx1XX8C6rfVU13eTSGpsrSnN85BI2qxZPo/PbdhJbXOQjr4YvRGTwz0R/uuPB/jxTZfywXeNzww7H02YJLvWCfHOobXeB+wD/l0plQO8F/gY8ANSFUnHUwE0ZT1uBq4Y5csP99yKgT/Nw3z/KEqplcBKgClTpozyZYUQQgjxTjTqmU8n4QOSEOIMdLLDjnSVUnbYsm5rPbubA0wp8jFrvH/EoGvFommsWDQtE+Z876m9zJqQT9X+TlCKvxzoorqhmwerDrGvLURBjotE0qYgx01LIIpta3KcqVlOQzMo04Z8rxOXAddeXEHoQANf//H/ZXJ3M1+59nYen/NeIHVOmd/Df/3pAKGYicNQfGPT7lSVlNPA53VS1xZi9oT8zPsIRkxCsSSBiElbMErS0vTFzMwufVtqWgZVR0m4JITIppS6VGv9MqkWt6dO93pGS2u9DlgHsGDBAhnPIIQQQogRndBud1rrqNb6Ka31l7TWEjwJIYBUhVN6l7fsgElrDRoKfS6um1/Bg1WHuPnhXVQ3dA97nXSYc7AzzPN728lzOyj3e7hyRim3/foVth3oojsUo7ErjEKnZiuZFihFRZGPiycXHnVNlwGzJ+TzoQsn0LfjJf71rs9SFuzgyyvWUP03H86c1x9PUrW/g+6wScKCwz1RDnZGiCY1cdMmmrDQKIJRMzMgvDUYxeNUFPpcrFxSycRCL3MrCjKtc2uWz6OuPZRpRRRCiCFuBlBK3Tnw93WjfF4LMDnr8aSB772V57YMfH0i1xTiHS8Ss+kLp7pc+8I2kdjQjlchhHhnOqHwSQghhrO5poVw3GKc3zOouufzSyv5wJxyVi6tZHNNC7XNQV5+o5vVm2qHDaD0wP9qrUmYFv3xJPcun8vu5iCtgRhJSwOKpK1pC8ZBawpynGhbU5zrygwAz5bjclDbHKD5109w9/1fwFaK6/9+LX+aeCHNgXjmPFszcP3B6zEUTCnO4fYPzqKi0JuZ6bS5poUCn5syv5eVSytZsWga2792FZu+eOVRc60qy3JPWnujEOKcNH7g7w+N8vxdwAyl1DSllBv4BPDEKJ/7LPBBpVSRUqoI+CDwrNa6FehTSi1USilSsz+3jP4tCPHOVXswxg2rWugKpCaSdAUsbljVQu3B2GlemRBCnH6jbrsTQojjGWl+1NDWvo6+GK82Bejuj7N+a/1RbWiFPhd+r4vJRTm0heJE4knWPr2P11uCaMCpIM/jIJbUWDrVdre/PYQF7HwjMOzaQnGL62uf575n/ouDJZNZ8bG7aPeXohI2HocilhU4WUP+kbI018XUklxag1He6A5z2bRiZk/Mz7xnBccdEC6znIQQx3C5UurHwGyl1EWM8vOZ1jqplPonUkGSA/i51vp1pdQ9wEta6yeUUpcBvwOKgGuVUndrrd+lte5RSn2bVIAFcE96+DjwBWADkENq0LgMGxfiOCIxm1UPdBKJv/l5QmuIxDWrHujkN/dVkOOVf/cXQrxzSfgkxFlqpJ3jTqfRBizj8r1MLvbR3BtNteRlqW7oRinFvEkFrFxayYNVh6htDtIajOJ0KOKWxmEocr0uihwGV84o5bnX2wbNeDKA7PxIac2Xd/yaL219hG1TL+YfP7qafo8PRaqiyTAUhW4H/fEkSTv1XLcDFAqXw+DiKUU0dIUJxS1+vfMweV4XHX2xzPsd6/0/E392QohTTyl1l9b6Lq31AqXUJOBS4HpGGPA9HK31UXOitNZ3Zn29i8FtdNnn/Rz4+TDffwm48OhnCCFG8ueXI9gjTD6zder4NYvyTu2ihBDiDDLm8Ekp9RipDaPeAP4K/FVrXXeS1yWEOI7NNS2ZGUKnO8Cobuhm3dZ6tNZ8fmnlMdeTXndJnicztDs7jBluYPn3ntrL4Z4IXqciZoLP48SyNf5cJ8+93kY4nsTjgIQ1ECaR+qCnALed5D+q1nH1zqfYNPcqVn3on4g7XHidCkMpXA5FZVkexXkedjZ00xdLlcq7HA4Wnl9Meb6X6+ZXsPdIH4/saMRQikA0Qaob5cScST87IcRpdefAJi7FpD5TPaq1lhY3Ic5CLR0mscTw6VMsoWnpNE/xioQQ4swy5vBJa30DgFKqEvgy8CCQf5LXJYQ4jpFa3E6HzTUt7G4OgOa4gUr2utPnrdq0OxPGZO8Od/PDu9Ba0xaKE7c04YFgKG5aGEpT05SaoaAG/rgGAihr4LVy4xF++uRarjz4Ej9Z/En+/cpPYdoq85xJRTm09cVo7A4zb3Ihe444CcdTzy7IcbJ4Rhl1A/Oj0jvxVTd0v6X7PtJQdiHEO5IGYqTa5i4BXlRKfUJr/erpXZYQYqwqxrnwutWwAZTXragoc52GVQkhxJnjRCqf3g/8LeADtgGrT/aihBDHdypnCFU3dPNg1SGUUqxccv5Rr7tsfgWdoTha61EFKumPZemKp1nlfhQws9zPg1WHCERMXqjrIBg1sWzN5KIcfC4PMa+TjlAcp0PRHU4Oup4mFTyllfX38IvH7+aCjga++uEv8dhFH8LnNDATdiqsUoreiEk4bqGU4rd/bWZSoQ+AORMLuHXJ+SNWKGlg75G+UVd7ZUsPZc+u7BJCvGPt01p/a+Drx5VSG4CfAu87fUsSQpyI917q4yeP9w57zFCp40II8U52IjOffg48A7xAaphl8KSuSAhxxknvUKfU8JVNYwnCsgMdDdR3hlHAmuXzuPnhXWw/2EVyYK6TApwO6I2YuJ2KzpCJaWsSlnXM16jsauK/H/8WhZE+brn+Tl6oXACA12lga7BtzYUV+Rzq6MfjNMhxGVSOy2Nva4hF00spynUDg6u00gHcvrYQBV4XOxt66IuZo6r2ynYmVawJIU67LqXUpVrrlwG01vuVUmWne1FCiLHzeQ3u+2IZqx7oJJrQaA1KQY5bcd8Xy86YYeP3PNRFU4fJ5HEu7ryl9HQvRwjxDnIibXdTBoZiXgLcqJSaobX+5MlfmhDiTDGr3E9VXQcTCnKOCk3GOjx7VrmfnQ09FPlc7G4OZK5Z3dDN3iNBLEtjabAszaRCDzaK9mBs0EDxNMWbVVRplze9xvpN38F0uPj4p77La+OnA5DjUlw8tZjdzQEicYu/Hg7gdTpwOxUet5NXmgJYNvx5Xwf5PhedoThXTi+luqGHmeV+6tpD1DYHMS0bn8vBTQun8peDXaOu9kqTXe+EEFn+GXhUKfUyUAvMAxpO75KEECdq7nQvv7mvghXfbqWz16K00MGGb044Y4IngKYOk0PNMn9KCHHqnYyB4788yWsSQpxh6tpDTC7OPapVrLqhm9WbanE7DRSMKlSpaw/hdhg8v7cdl8MBxNhc00JHKE6Bz017XzxzbmcowZyJ+XSG4lhD0ieHSpWxm1nb2v2fvVv5wf/7AYcLxrPihrtpLijPHHM5DJq6w9i2xrQskjb0Jyx8LgNIYtmpIeVJWxOKmLx4sIvq+m4iCYs1T+1hbkUhk4tyKM7zcOtA6+GKRdMGrUl2sRNCjIXW+lWl1MXA+0ntLvdn4Fend1VCiLcix2uQn2vQ2WuRn2ucUcGTEEKcTmP+bai1vkFr/TFSMwmuBHad9FUJIU6J6oZuVm3aTXVD9zHPWza/Ar/XSVtfbNC5m2tacDsMzKR9zOqf7NeZVe6nuTeCQ0HMtFBKU98ZBq2ZWOAl1+3IPM/pgHA8iVNBgddB9v5yts4KnrTm1upN/OiJtdRMmMX1N/7boOAJIGbaHO6JYNmafG9q6Geqckqz4LxiLppUwIRCLxWFOSS1RqNIJFMvkLTh9SN9FOd5eOgzl40YLGW3FAohxGhoreNa6/+ntf6e1vohrXX4dK9JCCGEEOJkk4HjQryDjTRQe6grppUcdW5617aKohyunF7K5oHAJX0sPUi8rj1Ee1+McNzKzHmaVOzjYHsIr9tBKJaktjnAxEIvU0vzqCjy4Y+ZlPs9FOd52HMkCMogGBs858kgtaudYVt864/r+cxfn+TJCxZz+9/eRtzpHnRujkvhczspyXXTH09S4HPjdTlo74uxdOY4fnpTaiZUdUM366oO4XEZRBIWcysK2PVGD4GIidNQaH107192tVO6pfDqC8e/pZ+LEEIIIYQQQpxLZOC4EO9gYxl+PfTczTUttAZiBKMJ9rT2UeB1ZVrv1m2tZ3dzgKq6TiYX++gNx2kNxpg9wc95JblU1XVQnu/F1hCKmURNm8aeKFNLcpk/pZDrBtrWNmxvYNv+DuJD5os7DXA7DFzxCGs3f58PHdjBuss+yn3v/SxaGYNmQSng3ZWlhOMWfq+T7v447aE45X4PFUU+OkNxrrr/BW5aOJUVi6axuaaF/rjFZeflogFDKfxeB6V5XlYurTzqvgwdoF6a52F/e+gt/FSEEEIIIYQQ4txyogPHJ5MaOP73SqmZMnBciLPTWIZfDz13VrmfJ189gj1QDdQfNfn4ZZMBUhVCGiYUeKksy+XZ9j4iCYtf7zrMuytLMa3U3KWSPA+5HgeHOsKYlqapJ8LiGWVsrmlh75E+vvf03kHBk8+liJoahaI8HuT+X97FxUf28633f56HL702c56hUm15GvA6FYGICVqz50iYSMLC7TQoyfMwzu/hhboOQnGLR3Y0MntiPh2hOHkeRyZk6+iLoZTKzHkaamgoJzvZCSGEEEIIIcRgJ9J2twL4NBAGGoFbTvKahBBnkKEtdOm/O0JxJhX7CEZMUOAyFBsHApzPL60cFMI8+3obmtQw7x2HuinyOQnHbUJRE8u2UQqUhv0dYe76/R4AXEYqQEpTQMRMfWNidws//823mBDq5h8/uopnZ/7NoDVbGtwOyPe6iCVtaluCGIDLaaA0OD0GV04vZcWiaWzY3sAjOxq5ceHUVNVTLEllWS6QqmpaubTyuC2J2cdl0LgQQgghzkSRmE1fODXPsi9sE4nZ+GQguhDiFDmRtrv3aK3fB6CUmgd8C7jjpK5KCHFKHWuXtgerDlHbHKSqroPJxbnsbOihNM9DnsfB/MmFmYBp9aZa3A6D9VvrKfN7Mte6+eFdxEwLl6HQaOJJmyPBBAU5Djr6EyOuKXsXO4BLphRS2xJgTlMdP3v8bhTwqU/cy18rZg/7/IQFbqeBBuKmRVKDsmyKc90UeF2s21bPE68eodDn4t7lczOzqtKh2WjnYQkhhBBCZJs8zjXo7zNB7cEYqx7oJJpI/UNeV8DihlUt3PfFMuZO957m1Qkh3glOJHzqS3+htd6tlDqRawghziDHClqUUigFEwpyqCzL5eoLx7O/PTRo9tOy+RWsWT6XLTUttPXFqO8Ms67qEJtrWqhrDRJO2HgccOHEglQVkqHoi1rDLWVEe1qDfPBANf/2u7V05hXxmY/dTUPxsdvbIgkLh1IU5LgoznXj97qwtaY9FCcST7LnSBC/15V530OrmI7VQneswE4IIYQQ71x33lJ6upcwSCRms+qBTiLxN0vKtYZIXLPqgU5+c18FOVIBJYR4m51IcLRQKfWfwMsDf9zHOV8IcQbKDk+ONXh85ZLzM8eGhiyrNu3OhFZrls8bVD3UHopT3xmmJ2ziUOAwDL56zWz2HunjkR2NGEqxv6N/1Ov9u+rfc9fz63htwnRWf/Ze2nQOWKl2PK9TYVoaW0N2wVQgmiTX7SDX42DBecVo4JXDAdCayrI8AAp9rmHf9/HmYUlllBBCCCHOBn9+OTJolEE2W6eOX7Mo79QuSgjxjnPc8Ekp9S6t9evpx1rry5VSk4BLgRuA896+5Qkh3i7Z4Uk6OBrOcCFM9hwoRaq97W/ue57xBTl85KKJaGDx9FL+crCLiYVeoqbNrYtTA7v3HukjYlr4XAaTCr00B2LHXKfSNl+teph/qP4tf5h+Of9y7R1MKS3DF4qh40mmFPvoT1h0h+I4gKklPloDUfoTNh6HoiDHyZyJBZmAaWdDDwU+N7PG+7lufgUPVh1i3db6zHvNfn/Hqmoay06BQgghhBCnS0uHSSwxfPoUS2haOs1TvCIhxDvRaCqfNpLa2Q6l1C1a64e01s1As1LqD1rryNu6QiHESZMdqswq97OzoYerLxw/7PHRVP0oYM3yeVx1/wt0hBL0hBO09cUwLZvOUBxba4LRJIU5TtZtq2fLK6mKqI5QHKeCd00sGBQ+OVRqWHiaJ2nyb0/9Ox/Zu5WN86/hng98Hls5eKMzhI0iYWnqu8J4nAamrfG5HFgabv/QBWw70DnsLnXp9sD0XKfa5iBKMaiCaTRVTWPZKVAIIYQQ4nSpGOfC61bDBlBet6Ki7MyZTSWEOHeNJnxSWV9/AXgo6/E2UhVQQoizQHaoooHSPA/720PDHs8OVjZsb2DdtnrK/R6+ds3so6p+blo4lXVb65lQ4MXWmubeKD39cQ73RAhGTQKRBEkbOkNxxuW5sC2Ncij2tPYNWl928JQf62fdpu+wsOk1vrt0BT+94npQqV9HqXFRqZMtG7wuB16nAUrhdhjsbw/xsxWXD3sPsgOmWeV+OvpiKKUGVTBJVZMQQgghzhXvvdTHTx7vHfaYoVLHhRDi7Taa8Ck7IldDjslkOiHOIkNDlaEBy0ihy8YdjXSE4nSG4tz2aA2zJxawMquiaMWiaaxYNA1IBVUbdzTSH7cIRJOpcMipQEHS0rQEUzvcxSyNMcIAgopgB7/4zV2c13uEf772Kzwx5z2DjrsdkLRS851cDjivJJeIadHZFyMYTeB2Gnxuw06UUiyeXkpde2hQNVd25dZwIdVoqppk4LgQQgghzgY+r8F9XyzL7Handerf83Lcivu+WCbDxoUQp4TSeoTpc+kTlDoCrAZeBX6htb4469hftdaXvL1LHL0FCxbol1566XQvQ4hzzobtDazfVk8skcxUJ5XkeVizfG5myHi6kmjjjkb6YyZd/QlsnUqofW4Dv8/NkawWOwUU+xx0RwbvejenvZ5fPH4XOWacr3/6bvbOuoSDnYO7ey+dUkihz8XethAFXhc+t4M9rUESSU2ex0Gp30tf1EQp8HtdlOZ58HudlPk9LMsK3maW+48KpkYrPWy9siyXNcvnjfmeCiFOjFLqZa31gtO9DjGYfAYT4swXjdms+HYrnb0WZUUONnxzggRPQohRe6ufwUZT+XQXqda6zwKTlFJ7gL3APuDM2kdUCHFSZVf3bP/aVVQ3dLOu6hB720K4HQZbaloAWL2pFrfToGp/J+G4SV/UQilwOxQleW6C0SRdofigmU4aCEYHB09L6l/mx1u+S9CTx/V/v5YDxVOZ7XAwqdBDcyAOgMtI7VD3sxWXZ6qscnDgcTowLQvT0iyeUUpTTwSlFFdOL2V/e4i9rX282hSgoy/Gz1ZczhXTSgbt1jeWYeMgrXlCCCGEOLvkeA3ycw06ey3ycw0JnoQQp9Rxwyet9brsxwM73c0F5gFb36Z1CSFOg+qGbh6sOoRSipVLzs+0p62rOpSpbBqX72XxjDL2t4eYWe7ntl+/QjDy/9m79/go6zP//6/Pfc8pk0wOJCFAiAjh5AGUVYtbK9SedW2lWA9tdeXXKvZX2931223duKv1CNUe7G5r+xXtateeUQqtq61rtWDdGhVDSRUIh4BJyDmZzGSO99z35/vHZIZJMgFUIAGu5+MRIXPf98znnoeE8M51XZ8kpX4PVQEvrSmHIi9YtsMZ00r4+FnTuPupN7F1utrJayoSQwlUKqfw8oqt/8Pq332PpsoZrPjUHXQF0sFPVyjOYCKFAkwDKgNeLpxTSX1zL4+/vA8r5dAxEGNWRSEdoQQlBW6SKWdYO119cy9/bOrGsh2UUtmAyesy6BlMZIeu1zf3poM000DBQcMnGTguhBBCCCGEEIfncCqfhsnsdAc8c+SXI4QYT5nd3yzb4daeCNeePwMF7OgIs7VtgI1N3dSU+bO73NWt20okYWE7mqqAl7Iib3ownFJMKvRww5JZ3P/M9mHVToZKVy9ZztCLas0/vfQz/umln7Pp1EV8cVkdEe+BwZcDMQs9dG3KAdfQQPEdnWHCcYvucJLKgIf5U4u55ZJq1mzczY6OMJ977BVuXFrL4pnlrG9oS7fnuU1uyAnVegYTw4aur29ow+MysFKOVDQJIYQQQgghxBHytsMnIcSJa9miarpCcbZ1hLFsh8df3seq5Qt4aONu6IMpAS+1lYXZYGbZomq6wwm01vRHLba2BHG0xnY0+3oU9z2znb+2BYe9RsrRGEoBGpedYtXvv8+Vjc+x9swPUfexL5EyXcOqo0bOJG/rj7G9I4wCBuMpPC7FYDxFRyg9T2pysY+tbQPQR7YtsCucYFqpj5VDYRSkj1185hSaOsPD7kcBl8kQcSGEEEIIIYQ4YiR8EuIE8E52Xst3TebXNZv2sG3/AIUeFxsa2rhxaS1rNu4mGLXY1h5iR0eYEr+bG5fWMr2sgCc3t1JS4EYpiCVsokNlTb1vBXEZCpWzaWb6kKYwEeUHG77B0ubX+d77Ps13L/gM9tCGmkn7wPllhW7K/O7s0HFbw+tvBSn0GMyfEiAUTxHwuYgkbDYM3U8mELtsUTXrG9oYjKeorSwcdp/53idppRNCCCGEEEKII0/CJyFOAJk2stzB2e/0mvUNbezsDBOMWkwp9mWrgvb2Rmnti5CwwWUovC6Dl3f3ErcctIJEyqZmUiGxRGrY62it+egZVWxq6iZlOyQdmBzu5dEn7mRe917uXf4VrOtWMPXNTlqDcTxDQ8ltwKVgRnkhCphTCW3BOLGUg9aQsjW3XHJadre9zO516xvauGHJrGH39HYGg7+TIE8IIYQQ4nhQM9k97FchhDhWJHwS4gTwTnZey3dNfXMvnaE4PeEEGkUong6Sbl3XiGU7JIc2p0s5GsO2sZ30LCaXglPLi0ikbOIpZ9jrmAqe396JxzRBwZzufTz6xB2UxgdZedXXqbpiGU2tA/QMJlGApaHIY1BVUgBotrYG0Rqqir187WPz+d7zOwnFLM6YVpwNnjJhUW6gBmQfX7V8Yd73IF/Q9E6CPCGEEEKI48Ht18tm5UKI8SH7awpxAlg8s5xVyxfmDUvqm3upW7eV+ubeYZ8Do65Z39BGJGEzvawAhUapdAuex2XgMQ2KvCaQDpRmTPLjdRnMmVzIT244n7s/eSZd4fiBQeJDkg4kbYhaNh/t3s6TP/0absfmqs98g+dnnMPz2zppH4hh5nw18rhNrjl/Rrp9T6cDrmjSpqkzzA+uOYcrzq3hlktOA9Lre7pxPzf/cgvzqgLZmVQjg6h88p2zbFH1sLlWQgghhBBCCCHeHal8EuIEN7KS52CVPcsWpXeLa+lL4TYVAzELtGZRTSmXLarmmcZ2fl7/Fh5ToZRCKdjXG+W2XzeigZil8y8C+MSbG7n/v7/LvtIprLjiTtpKJgPQF0nywdOqeG5bJ36PQSLlUOhx8fjL+yjxuUFrppYUoLWmM5wAGFbJ1DeYIBy3Sdmaps7wsGOHqgbLV/0lc5+EEEIIIYQQ4siSyichJpCRVUpHwshKnoNV9iyeWQ5KEU3auEyDmjI/KJXd/a2lP4YG4imH9oE4kaRDwtY0dUXY2RXJvwCt+cLLT/Dd33yThup5XH7NN7PBkwJmVhTx6t4+tIa45VBdWoDHZXDt+TNYdEopHzljCsGYhVLpXe1yq5Qee6mZHR1hPKZBqd8zKkQaqxrs7ZwjhBBCCCGEEOLdkconISaQozFvKFPJU9/cy+ceewWlFCtzBnLXN/eyZtMe+iNJSv1uWvqixC2bM6aVMHdKgD3dER7etIf1DW30R5LZfetStjP2iw4xHJs7n3uIaxue5qnTl/Bvl32FiDZBp5PvIq9JfyxJNJFCA9NKvMypCrC3Z5A1L+7hI6dX8eTmVlKOJpZM8f55k4cFTI+/vA8NeFyK71x19qj3TIaHCyGEEEIIIcT4k8onISaQkVVJuZVQ77Yqan1DG42tAzS2BodVD61vaGPz3j62tAR5fV8/kYRNwOem1O/OrqcvkuTpxv281RthZrmfyoAXW4/dYgfgs+I89OtVXNvwNP938eX882VfxXZ7yFzmkJ7lZKUcHA3FPhdVxQU090TY2xulK5xg3eZWJhV6cJuKlUtqmVsV4NZ1jTz2UjMA154/gzK/h9mTA2zbHxo12+rWdY1seSt40LlPQgghhBBCCCGOLql8EmICGTlvKLcSSkPeqqjDre5ZtqiarlAcNdRGB3DHb/7K+tdbUUpR4Dbwe0xWLplFU2eYuVUB1mzagx5Ki+KWg3IreiNJBmIWqYMUPpVHgvznk3dxZscubvvwF3j8by4FB5JJm9zLUrZDyoYCj5m4m/AmAAAgAElEQVQNs1K2g6kURT4XHz9rGsmUw9yqAJt2dvPy7l408JOX97HigpmsuGAmOzrD7OmO8PjL+6go8g6bbeVxGVgpR4aHCyGEEEIIIcQ4kvBJiAls5EDsfAO0D7dVL3PsG09v4+ZfbmHlhbN4cnMrSVvjdSkuO7s6+9wv7urhjzu6iCRToMFlGhR5TMoDPvb2DB40eDq1r43/Wvt1Kgf7+cInb+V/5pyfPebkFEsZClIaCoeCp+mlfkr9boIxi1mVRSw6pZSLF0xlfUMbm3Z209g6gGEoDAXXnD9j1Ht08ZlTaOoMD5ttpSA7r0oIIYQQQgghxPiQ8EmICWxkJVS+ECXfjm31zb08tHF3dr4TpEOqrnCCN9tDWLbmO8/u4LSpAV5/K8iSuZXZXeI+/+NXebGpG0dr/B6ThOWQStgADCYiGMoA8qdPf9O2jUeevBsNfPrTq9gybd6Y92Yo8LkMZlUU8omzq4cFR5n7yQRr/ZEEA7EkPrfJ//nwPE6bVkzduq3Zaq9874vsWieEEEIIIYQQE4OET0IcZ0a22eULWTLznZQi27K3pSXIQDRJZZGH9oEEBV4XvRGLc2ZMwrIdPv/jV+mPJNnXM4jtaAwFbsMgYtvYQ89r2xrIP+vpo03/y7//9lu0B8pZccWd7CubNuoclwK3S+E2TZTSeEyT+VOLWXHBzGHn5d7PhoY2/tgfxdGKZErT1BnOttodycHsQgghhBBCCCGODgmfhDjOHE6bXWa+UzBq0RGKs2ROJa809+EyDfqjSarLCvCYBtecP4OmzjCd4QSv7e0lFLOz0ZKjIWbZoBgrb8pasfm33P7cGrZMm8v1l99On79k2HGXSj/Fh06vwnI0fYMJDKUA6AjFqW/uze7Ily9Ye+ylZtZs2s3UkoKDtiAKIYQQQgghhJh4JHwS4jgzVpvdyKHjk4t9oBT7gzHWvLiHqoCXznCCsgIPHtPg3uULsoHP/c9sJ5qwh2VMGkg5mkKvSShuk4/SDnUvPMrKV3/Ns3PO5x8+/s/E3b5h5xR7TTTg97p4aXcP5lDoVF7k5dSKQvb3x7h1XSPXnj+Dx1/eh8dloBhe/ZQZLp5LKp6EEEIIIYQQ4vgg4ZMQx4ncgCkznyljZDVU5vMir0ky5RBJWLSmHBZOL6Gq2MfcqgDrG9rYtj/E4y/vo2MghuWAQTp0MhR4DDi9uoS9vREU9qjiJ28qybf/+wEu3f4ij/3Npdz1wRtwDHPUukMJG1NBImUzpbgAW2u01nhMA7QmaTt4XEY6eDIPf3e6w93lTwghhBBCCCHE+JLwSYjjxFjtdvXNvezoCNMxEOfiM6dQ39xLVzhBkddk5dJatu0P8b3nd+JozYVzKgH49rM7KHCbrNvcOhQGHeiuMxQEfC4uWTCVuVUB7n7qzVHBU0kszJp197C49Q3uff/nePg9n4ShiqZ8bA0m4HYZfG5op7rHX97HhXMqqZkU4cnNrVwwu4JJhZ5hwdiOzvCY4VLm/Xh40x4JoYQQQgghjnN3PdJDS5dFzWQ3t19fMd7LEUIcYcZ4L0AIcXiWLaqmtrJwVFXQ+oY2WvqjWLZDU2eYNZv2sLU1iFKKxTPL2dEZxlAK01C8uLObbz+7g0TKoXswScLWpBxAg8elMFR61pPLUMytCnDXb9/EHpE8TR/o5MmffJWz23fwpU98jYcXLx8VPJkjcihF+nl7BuN8//mdrNm0G4/LoKkzzLNvdBCzHLa2Blm1fCEv7urhuW2drHlxTzZsO9j74Wh90POEEEIIIcTE19JlsbvVoqXLGu+lCCGOAql8EmKCOFQbWb5d7SAdwnSHE2ituWxRNfc9s51wzGLLW/2cftszTCp0U1NWwKQiLxqYVOihP5rE50q3xAFMKnJTU+Zna9sAaIgkUtz/u+04I17rjI5dPPrEnXhTSa696h5eqTlz2HEF+FwKR4NjazRQ4FJYjqa0wE04kSKmHfweE78n3V63oyNMX8RiakkB9c29bNs/gJVyqCktyBu2jXw/6pt7Zfi4EEIIIYQQQkxgEj4JMUEcrK0uXyiV+/gj152XfbzU7ybgc9MzmEQD0WCC3sEkp08r4eNnTSMYSWLZDgunl/I/b3ZiawjFUuxMhtNVUEAspcnd4k4BFzW/xvd+/Q36CwJ85up7idXOhoHksHvQgFKKqoAXW2vmTwmwrT1EOGHjcRmcMamYt/qilPndnFJRCMDXLp6fDY/WN7RRUuDB73G45ZLTDquNbqxQTgghhBBCCCHExCBtd0JMEAdrqxvZVlbf3Mut6xrZ0hLMPv7YS8188Nt/5JRJfj58ehXTSr1kut9iKU1j2wBNnWHaB2J0hZNsbQ1y26WnU+w1cZkG4eTIOqf0FwiPCZ/b/hwPP3E3eydV88lrv82uilPoj6b42BlVeEf02HndJh6XwXeuOpsfrXgPK5fUEvCaFHnd7OuNkHI0kaTN/mB6lzsgGzzNqwqw6JTS7E58QgghhBBCCCGOf1L5JMQEkQlb1g+FSZmWss5QnIDPNSyUWt/QhpVy6ArHuercGgDWbNpNVzhJLNnBA1cvojOcYP4UTUtfjOaeQXxuk45QnCKvO9vmtuKCmelrX9xDJGlnn1+RDp5srbnpjz/lH//3F7xYew7/9Ml/odcsACBqOfzujU7mTi6kLRgjknRwGWA7TjY8qm/uZUdnmCklBbyxf4BUSuN2GdRWFhGMWXhMgw0NbWhgT3cEBaN28hNCCCGEEEIIcXyT8EmId+lQs5rejpGtd+sb2ogkbAI+17BQatmial5p7mN6mZ+mzjAAU0sKsqHS+oY2BuMpaisLuXBOJY+/vI9in4v2YJzewTiTCj18/Kxp1Df38r0/NBFK2JhAJn7SgGFb3Pe77/Opv/6BXyz8CP/2kS+SMkd/ydjdFcEw0tVPplL8nw/PywZPN/+igWA0ie2kd7or8hosOqWMG5bMAhg2q0nmNgkhhBBCnJyicYdQJF2FH4o4ROMOfp806QhxIpHwSYh3aaxZTe/EskXVw0KYzOcdofiw1rv1DW1ce/4MmjrD2XNzZydBOsyZWxXg8Zf34TENDKVo7Y8STdrY0RSrnn4Tl2EQtxyGT3iCokSUH/56FRfu28J33vdZ/uO9V4/a0S7DBmwnfbVpKE6bVpxd40DMImppfC7FlGLfqHa6sX4vhBBCCCFODo274tQ92E0smf5+sidoc2VdG6tvqmTBbN84r04IcaQorfWhzzpOnHvuufq1114b72WIk0zubmtHK0DJfY1M2FVbWTiqRS23Cgvg1nWNpGwHy9agIGU7dIWT+V4iqyrcw2Nr72B2bwt1H/syv174Iew8XyY8JqRscJkKl6GIWw4uU1ER8PLAVWcDcPMvtzAQTVLq9/CdoceOVJWYEOLkpJTarLU+d7zXIYaT78GEEO9ENO5wZV0b0cTobzb9XsXa1dUUSAWUEBPCu/0eTCqfhHiXxtpt7Z224+W7Lnce1LyqAArytqh94+ltvNkeYvPePgaTNl0DcVLp3AkNuNSB3+czt3svj629g0Aiwuc+9XVenPk3eU9Oz3YCh3TV06nlfjrDccJxm2jCYkNDG6uWL+SBq87OVmCt2bSHbfsHKPF7soPQ12zag9aaG5fWShglhBBCCHGSeWFzFGeMb0wdnT5+yQVFx3ZRQoijQsInIY6Ske14hxtGjdXGt2bTHjbv7WNjUzcrL5yVnQGVuWZeVYA394dI2pp9vVF8HoPU0F/mmb/TM5/nznfK+Nt9W3no1/cSc3u56jP38WbVrLzrcxtwZnUJW1sHgPQ3BoOJFOedWs5bvREGEzZzqwLAgWCubt1WtrYGsVIOfo+TreDa2hoEzRFpWRRCCCGEEMeXti6LeDJ/+hRPatq6rWO8IiHE0SLhkxBHycj5TYc7G2peVYBXmvu4+Mwpwx7XWhO3bCzb4dv/s4PpZX66QnG2tAQJxVP4XAapoR8dzSj3c0p5IS/t7CaWGv0Xug2Yimw73WVvvMA3n/53midN4/+74g72F08ec32OA5edXU1nKE5f1MJxHKaWFDC9rID/3dVDynFY8+IeTptWnL3PZYuq6Q4n0FqzMqfKKfOYDBoXQgghhDj5VE924/OovAGUz6OornSPw6qEEEeDhE9CHCUj2/FGhlFj2dEZpqLIm93FLuPGpbUEI0m2d4QpcJlYKQeUIhS3sGywbBuPAV6XwazKInZ2DTJ9kp89XZFRYRMM/V5rvvjyWr626b/48ykLuPGT/0rIN7q0udhrMpiwcQBlKJo6wzxw9SLuf2Y7f2kJ0vBW+sMZOn8gmhxV8XXDklmjBoznHs88JoQQQgghTg4XnePnh0/05z1mqPRxIcSJQaa3CXEU1Tf3UrduK/XNvSyeWc6q5QsPGbDMqwrQ0hdhR0eY+ube7OOLZ5ZTWujB4zJwmYp7ly+grS+CldM/ZzngNhUvbO9ib0+E5u4IhpGe8zRyaLjp2Nzz7A/42qb/Yv3pS7nuirvyBk8AkYTNolNKKS90U1LgwuMyeGjjbra1h0jp9OwnrdIBl89UlPo9eSu+8jnUcSGEEEIIcWLy+wxW31SJ36uyGysrlR42vvqmShk2LsQJRP40C3EUvZNg5cVdPfRGkuzuHhx1nVIKj8vg9GklAGzvjGSPuQyFBsJxm4StsXV6xlPKGT0zvCAZ56F193DNlmd48PwruPnSr5B0jV3WbAOheLrnPmU7PPtGB5v39pG0new5Aa/JbZeezvJzpvOdq84e1nJXW1k4ZsXXoY4LIYQYm1LqY0qpHUqpXUqpf8lz3KuU+uXQ8Xql1KlDj39WKbUl58NRSp09dOyPQ8+ZOTZ2L7YQQrxLC2b7WLu6mopSE4CKUpO1q6tZMNs3zisTQhxJ0nYnxFE01vymg9Fa43MZ+D2uYYHMYy81s23/ADVlft43u4Iv/mTzsOvsoXlPDsONDJ4qIv088uRdLOjYzb9+5Iv8dNElh1yTqaClL70biaFg9uQC2gdiKKVwGQrDUCycXsqKC2aOunas3QAP97gQQoj8lFIm8CDwYaAVeFUp9Rut9Zs5p30e6Ndaz1ZKXQ3cB1yltf4p8NOh51kArNdab8m57rNa69eOyY0IIU56BT6D4kKD7n6b4kJjQlU83fVIDy1dFjWT3dx+fcV4L0eI45aET0IcRWPNbzqYJXMq2d4eYkrJgZ/21Df3cv/vtpNIOQzGU9z/u+1EreEx0xi71A5T29/Go7+8nYpokJXL/5U/zF48ahZUrkKPiYFGGQZWysbnMqgq9lJa6OHjZ02jqTPM3KoATZ1hqVwSQohj7z3ALq31HgCl1C+Ay4Dc8Oky4I6h3z8BfF8ppbTWuV/5Pw384ugvVwghjj8tXRa7W2XXPSHerQkTPg399O41oE1rfalSaibpb4TKgc3AtVrr5HiuUYi363ArnzJDt5ctqmZHZxjL0ezpHuTWdY2sWr6AhzbuJmY5aCCatHFy/smgOLzg6W9at/GjdXeDYXD1p1ezdepcIH/w5FLgcRm4TXAZ6WHjKUejceiPWgRbgyjgkevOG7Z+kKHhQghxDFUDLTmftwKLxzpHa51SSg2Q/t6qJ+ecq0iHVLkeVUrZwJPAPSPCKiGEEEKIt2Xi1DPCPwLbcj6/D3hAaz0b6CddNi7EcSVf5VPuEPKM3NlQyxZVc9b0UkwFHQNxbv5FA8GohaHSQdOUEi9et0IBBS6F32Mc8g/yx3a8xM9++a8EC4pYccMDNA4FT/mU+11MKfERTzk4Gmom+TENRcqBeEoTilmgoW8wkb2PkbOt8t2jEEKIiUcptRiIaq3/mvPwZ7XWC4ALhz6uHePalUqp15RSr3V3dx+D1QohhBDieDUhwiel1HTg74BHhj5XwAdIl4cD/BhYNj6rE+KdyzdMO98Q8tzzFs8s54Yls/B6XMQtm+7BJAqoKvFRUuBi/tQSFOnh4rGUJpJ0Dlr59LlXN/CD9d/gjcmzWP7Zb7LVW3nQ8wcTKVqDcRwNkbjNZWdXM6XEx9AGJCil+PDpVZQVeYcFZrn3KTvYCSHEMdEG1OR8Pn3osbznKKVcQAmQ+5OBq4Gf516gtW4b+jUM/Ix0e98oWus1WutztdbnVlZWvovbEEKIiSkadwhF0qMuQhGHaHzkdFUhxOGaKG133wW+BgSGPi8Hglrr1NDnraTLxoU4ruQbpj1WK14mEKpv7uXWdY24jfQw75St2dcb4UsfmJOdrbStfYBoMHHQ11ba4d+e/xGff20Dz8x9L/906VdIuL15zzVUutUOpUjYGmNoPRUBD7/9y35ilk15oYto0uHK82q44xNnUt/cy4aGtmxglnufyxZVZ48JIYQ4al4F5gyNKmgjHSR9ZsQ5vwGuA/4MfAp4PtNCp5QygCtJVzcx9JgLKNVa9yil3MClwHNH+0aEEKJmsnvYr+OtcVecuge7iSXT36X3BG2urGtj9U2VshOfEO/AuIdPSqlLgS6t9Wal1PvfwfUrgZUAp5xyyhFenRCHL3du08HmHmVa8f60q4cdnWGWLapmzaY9bG0N0tQRJhizCMcsBmJWegc7BXHLYc2Le5g/JcC2/SF0tg4pbWQlkzeV5DtPfZu/2/ES/3nOJ7jnA5/HMcy8w8UV4GiwNBhKYyooLXDx5Q/O5Wf1+9j8VhCA6lIfr932wex1B9ulTnawE0KIo29ohtOXgN8DJvCfWus3lFJ3Aa9prX8D/Ah4XCm1C+gjHVBlLAFaMgPLh3iB3w8FTybp4OnhY3A7QoiT3ETaSS4ad6h7sJto4sA3zlpDNKGpe7CbtaurJ9SOfEIcD8Y9fAIuAD6hlLoE8AHFwL8DpUop11D1U74yciBd8g2sATj33HNlGKYYN7mtZmMFL/XNvXSG4gR8Lhyt2dMdYc3G3WxrD2GlHNoHYrhMg/5oMjtU3DTA0ZruUJz2YJxNO9JzNRTgM6HQ56YncmAHjtJYiIefvIfz2t7k7g9cz4/OO9Cx6mgIeA3CCQcFlBe66Y1YGECBx6DAbWIYipoyPzs6w7T2x7LXVgUOVE0dbtAmhBDi6NJaPw08PeKx23N+HweuGOPaPwLnj3gsApxzxBcqhBDHkRc2R4dt8JPL0enjl1xQdGwXJcRxbtzjWq11ndZ6utb6VNI/jXtea/1Z4AXS5eGQLhffME5LFOKwZOYeza0KZIdtjxy8vb6hjUjCZnLAy5I5lfQMJtjREaZnMInjaKaWFJCyHaaVFlDoNTEN8LlNKoq82b8AUzr9oYGkk/7VHFrD9GAHT/7kayzs2MkXL/uXYcETpM+NJR3cJgS8Jv1RCxS4TCgp8OBzm7gMlQ3Gqkt9+N0GcycXcsslp2WfR2Y6CSGEEEKIE1Vbl0U8mT99iic1bd1W3mNCiLFNhMqnsdwC/EIpdQ/QQLpsXIgJK9Nq9rnHXqGxdYCuUJzJxb5hIU1XOEGR1+SyRdWsb2ijosjL1pZ+bEcTSdpELZupJQUEYxa1lUW09sewbAePy+Dav53Br15tIWodGHRoa+gdqnpa0L6T/3ziTtxOis9efQ+vTT8j7zptDTiQcjQuQ5G0NaZh0D0YR2uFy4CpJQXUVhZy8ZlTsq2BMtNJCCGEEEKcDKonu/F5VN4AyudRVFdOjLlUQhxPJlT4NFT+/ceh3+9hjN1VhJjIlFIolf41N6RZ39DGYDxFbWVhNsjZ0NBGmd/NH7Z14nEZ7OuJUOAxmVzsI5JIMRBLAtAfTc94SqTSwZMCfK70jnfxlOai3a/y4IZv0Osv5eorVrO7vCbf0oCh+VAaUo5Dqd+DyzSIJlKkEg6mAp/boKzQw6rlC6lbt3VYeJbbaiftdkIIIYQQ4kR00Tl+fvhEf95jhkofnyjueqSHli6LmsnuCTU3S4iRJlT4JMTxaOT8o5VLZo3aBa6+uZemjjB7eyJYtkN9c2/22OU/eAml0rva+dwGcSvFvp4ItqOxnQPVTT+vfys7WVwDsZSmwIRPb/kd9zz7A96omsXnL/863UVlY67VVGTb9z4wv4pJhR7mVgX4064etNZcOKcyu6MeHKhwmlsV4NZ1jXhcBgokeBJCCCGEECcsv89g9U2V2d3utAaloMCjWH1T5YQaNt7SZbG7VdoAxcQn4ZMQ79LIQeP5qoLWbNrDG/tDWLZDqC3I9Y++QsDv4SOnV/HXtgGStibgNamtLGJ7RxjDUCQsBzvnORIjt6nTmi+98Dg3/flXPD/rXL502S1EPQUAeXe1MxSUFriJJFN4XQaW7WR3yXO0Rql0dVXuZZl7qVu3FY9pYKUcabUTQgghhBAnvAWzfaxdXc2Ku9vp7repKDV57LapEyp4EuJ4IuGTEO/S4cw/6htMkLKd7LylsO0wmIzz05ffIjVUihS3HPb1RvC4FOG4PSx4GsltW9z3zH+w/I0X+NlZH+W2j3wR2zCzx22dbs3LfDikt4c9b+YkUo5GD/34ZstbQZ76y36MoTbBV5p7mV7qH1XdtGxRNQqy1VxCCCGEEEKc6Ap8BsWFBt39NsWFhgRPQrwLEj4J8S4dbP5RpiWvO5wgpcFtwORiH6FokqjlYOXs4ZpyNL3RFJAOjMYSSET44a9X8b59f+GbF17Lg397ZboOeAQ99FFgKuK2RgNbWwf437oPZtd28y8a0IDbTP9FGk/Y7OuNcNV5w2dGyYwnIYQQQgghhBDvlIRPQrwN9c29rNm0B601Ny6tzQYyI+c+ZT7f3h6itT9GKJbuw7YcWFBdguVotu0fIBxPEU6ka5xy290yv/eaipSjsy10U0I9PPrEHczubeHmv/s//PrMD2SvMTgQOOUq9LlwpRwGEzZFXnPYWudPLaaxdYCasgI6QnHsmMbnNWjqDB/x904IIYQQQgghxMlJwich3ob1DW1sbQ2CZtgOcF3hBIPxVHbu0/qGNra8FaSpM4yjIeA1Sdg2CtjU1M2MikISlk1kKHgyFVQVe9g/kBz2erlznuZ3NfPo2jsoSkZZccWdvHTq2cPOLfO7KPK52dcXyz6mgEvPmkZLf4zG1iABn5ubf9FAKJ7i2Tc6OGWSn7NqSocGmDuA4vRpxe9qrtPIIE4IIYQQQghx5EXjDqFIejfsUMQhGnfwS2ugmKDk/0wh3oZ5VQHcpkFNWQGXLarODhtHa2orC4ftEpe0nex1MetAdZN2HPb1RIinHAwjHRAVekzCcRtTpYOokd67dwu/+uktAFzx2ftHBU8A5QEf7QOxYY9VBjy09sfQWlNT5qd9IEbvYJLBhE0watHaH2NywMvKJbNYVFPKA1efzSPXnfeuQqPcAexCCCGEEEIcz2omu6md7qZmsnu8lzJM4644V9a10RNM/zujJ2hzZV0bjbvi47wyIfKTyichRjhY5c6Lu3qwbIdJRd7sscyw8dxzF88s59rzZ/C9PzRhORBJpFCkd5zzelykHI2VcjCVIoUmnLCz7XLlhW4qizxs74wA8Mm/Ps/9z/w7uydNZ8UVd9JRXAGkk+NMvKWAaMLCyplSbipYOL0UR2siCZtgzKLE76FnMIGpwO82WTi9JLv2I1WldDgD2IUQQgghhDge3H59xXgvYZRo3KHuwW6iiQNdElpDNKGpe7CbtaurZTi6mHAkfBJihNzKnZGBjNYa9NCvjD2Iu765l+/9oYlgLIXLUJQXeoinbN5bW8FLu3qIJmxMIz0DCobPaeqNWPRGLNCam/78K7764uO8NGMhX/jkvxL2FmbP87kNDKWIJNPBVWswgcdUKOCMacXccslp2flTGxrauPjMKTR1hvG7TVr6oyycXsoj1513hN89GU4uhBBCCCHE0fTC5ijOyEGvQxydPn7JBUXHdlFCHIKET0KMcLDKnRuX1h5WVc/6hjZC8RS2Bm1rBmIWHpfBq3v7iFnpsMhyxr7edGzufvYHfOYvv2fdGRdxy8X/gGUeKPU1gAK3QWJoF7uMpK0JeE0W1pSyPqftTQOnTStmxQUzs2GUVCYJIYQQQghx/Gnrsogn86dP8aSmrds6xisS4tAkfBJihINV7hxuVc+yRdXsaA+xq2uQmGWTtHV64PhQxZPbBEMp4qnRf2n4kzG+v+E+PrDnNb7/t1fyrQuvBXVgEJQiPVx8cnEB+3ojKIZXTg0mbH5Wvw+lFJv39mFrsFIOrzT3sWr5gmH3IMPBhRBCCCGEOL5UT3bj86i8AZTPo6iunFjzqYQAGTguxDD1zb3UrdtKfXPvu3qO9Q1t3HLJacyuCmA5B8IhDaQcsJ10+DRS5WA/v/h5HUubX6fuo1/iW0v+fljwlHmO8iIvi04pZXpZAS5TYZD+w2wqmFToxucysR1o7Y/hcRkEo0k8LoMNDW3D7lGGgwshhBBCCHF8uegcP0aeTYogPWP2onP8x3ZBQhwGqXwSJ73c6p98857qm3tZs2kPWmtuXFp7yAqh9Q1tbGkJ8kpzH8FoMu85toboiL672t4WHlt7B+XRINdffhsv1Oafx2Qq6I0k6QwnAIWpFAU+A6/LpKasgHlTi/G6DP60s4f3zakgmXK46twamjrDw3bo2zB0z9KCJ4QQQgghxPHD7zNYfVMldQ92E0tqtE7/vLrAo1h9U6UMGxcTkoRP4qR3sDCmvrmXW9c10juYwG0aPLxpz6g2tUx4Na8qwKad3bT2xdjbO4jbNJlW4qUvYjHGPMCs97S+wZon78YyXFz16W/QOHXOmOfaOj2U/IVtXbhM8HtczKooZP7UYjrDCfZ0R6itLOS5r7x/zOfI3aFP2u2EEEIIIYQ4viyY7WPt6mpW3N1Od79NRanJY7dNnTDB012P9NDSZVEz2T0hdwwUx56ET+Kkt2xRNWs27h6qJIJVyxdmj61vaMNjGvg9Lk6bGsDRmi1vBdm4o4v5U4u5cWltttLpqa37MZUibjlYNiRtm45QgoDXJJSwx3z9S7b/iQee+jatJVVcd8UdtJZOGXbcpdKB08gAywHcpkFFkbkxw7kAACAASURBVDe7s91jLzXz+Mv7uPjMKYxFAichhBBCCCGOfwU+g+JCg+5+m+JCY8IETwAtXRa7W2XwuThg4vzfKcQxMnKu0+KZ5Uwu9jEYT42afbRsUTXVZQXMnxpg5dJablxaS9J2iCZtNu/t49Z1jcyrCjAQs0hYNqFYCts50E4XTtgHDZ4+/+p6vr/hPrZOmcPl19w/KngCMA1Fsc9EQfbDVFBd4uFvayu4d/kCAOrWbWXTzm48psHjL+97V3OrhBBCCCGEEEKII0XCJ3HSyTdke9miamorC7lsUfWwcGrxzHIqA14iCZsNDW0809hOezCGywDL1li2w2//sp9gJIltp6uTcgeMj8VwbG5/bg23Pf8Iz8x7L9dcfQ/BguK856ZsTTLlYCjwuRQXza/k3FMnsXReFY9cl54Ldeu6Rra8FcRQiqTtZIeLCyGEEEIIIYQQ403CJ3HSmVcVoGcwwdyqAHBgZlNmBtLIcCoTTM2tCvD4n/cRtRz6oylmVBRiO5pt7SFsrdO7zuXsOjHGBhR4rQQPbriPz23+DY+cexlfuuwWEi7P2AtWgE4PEiz2ezCUIuBz0RGKZ9fucRlYtsMNS2axavkCFtWUDhsifiR28RNCCCGEEEKIQ4nGHUKRdDdIKOIQjTuHuEKcDCR8EiedHZ1hKoq8NHWGqW/u5eZfbuGZxnYe3rQHGF4FBem2vFXLF/Lirh7soZImBfjdJvFkus3OVIoZ5X7MofTJVPmrn8qiA/z0l//GR5v+zJ0fvIF7PngDWo39x9AgPe8pZqdfM+B1ccOSWTha09g6wJqNu9OtgaUFnFLuH7be3LlO+aq9hBBCCCGEEOJIatwV58q6NnqC6dEjPUGbK+vaaNwVH+eVifEm4ZM46eSGS+sb2ogkLOKWjdbpuChfeAOgtc5WM9lAeyhOwtYkbLAdTW8kQXIonbLzJE81wQ6e/MlXObNzN19c9i88eu5lB12nOeLzskI39y5fwOKZ5SilUAqUUqNaAw91z0IIIYQQQogTQ81kN7XT3dRMdo/3UojGHeoe7CaaSHdtAGgN0YSm7sFuYlIBdVKT3e7ESSHTnrZsqLUuN1jqDifQWnPhnErq1m3NnpN7DcBA1KLIYxKzbLxukykBL2gYTNjpECqSGvP1F7Y38aMn7sLl2Hzmqnt5ffpph1yzYYChFClH4zIUX/rAnOy6Vy6ZxYahVkFIh0u5n4+Ue88j3wshhBBCCCHE8en26yvGewlZL2yO4owx/NbR6eOXXFB0bBeV465HemjpsqiZ7J5Q79vJQsIncVLIbTsbGcLcsGQWi2eWU7du67Bzcq/RwFv9UUxTUeJy4fW4cJmK3sFE9jUUYKjRVU8f3FXP935zPz3+UlZccSd7yqcfdK0fO6OKra1BppYUsGB6CU++3kqZ30NTZ3jYunPDo5GB2tt9L4QQQgghhBDi3Wjrsogn86dP8aSmrds6xisarqXLYnfr+K7hZCZtd+KEV9/cS2coTsDnGlYZNNZg8cyOd13hBFbK5rW9/Tz7RgdeUzEYT9EbTRGKWmzeFySRkzRpyJaXZlzT8DRr1t3LzvJTWH7tt8YMnrw5PXav7u3jgasX8bWL5/Pizh7KCjykbIfOcCIbPL2b+U3SgieEEEIIIYQ40qonu/F58m+75PMoqivHvzVQjB+pfBInhJEtcrmVQem5Tja1lYUA2da6fK1qmezooY27eX1fP7GknQ2Ycr+MJlJ23onimS5mpR2+uum/+OLLT/Bc7Xl8+RO3EPP4xlz/RfOreGF7FwlbE4xa3P/Mdpo6w5hGupJq7uQAg/EU9z+znfaBGFNLCkbtZre+oY15VQF2dIYP2lL3dqqkhBBCCCGEEOJwXHSOnx8+0Z/3mKHSx8XJS8IncUIY2SKX21aWGzLlnjdyqPiaTXvY2hqkqSNM+0CMaNLGGlHZlGEdZFaeJ2Vx/zPfZdmbG/nJ2Rfz9Q9/AdsYOT58uK2tQQwDsNNh0+a3gkB617y5VQFK/W6qin38cUcX4YSNP2YNW/tDG3fT2DrAxh1d1EwqlJY6IYQQQgghxDHl9xmsvqkyPVw8mR46rhQUeBSrb6qkwDd+jVfRuEMokv5HXCjiEI07+MdxPScjebfFCWHZomqKvCad4QTzqgIEfC46QnHqm3uH7V43rypAz2CCuVWBUc/RN5ggFLPY2zOIyzBwGYqA18RlpGueTAVeM38ZaUZxfJAfr72dZW9u5L6l1/FvH/li3uDJk/OQS0GR10XMGl1KVeZ3kbQdLpxTyarlC1m5pJaqgJf3zamgbt1W6pt7AbK7300tKZCWOiGEEEIIIcS4WDDbx9rV1VSUpv/BU1FqsnZ1NQtmj90FcrQ17opzZV0bPUEbgJ6gzZV1bTTuio/bmk5GEj6JE8LimeVMLvYxGE/xp109NPdEaA/Gs3OR6pt7qVu3lRd39VBR5M0O786llEIB5UVeUo6Dx2UwpcSH1gfa7hIjp4nnmBbqYu1Pv8Y5rdv4x0u/wg/PvyId9efxmcUzKC90o4BSv5ua8kIyuZap0n8wfabC43INW++KC2by3FfeTyLlDJv7tHLJLD50WhVfu3j+qIouIYQQQgghhDhWCnwGxYXpqKG40Bj3iqe6B7uJJnR2Pq/WEE3odIVW/CAtLeKIkrY7ccLItNd1hOJ4XAZWyslWAGXa0mrKCpg/tTg7VPwbT2+jM5xg5YWzGIyniKc0u7sjeEyF5WhMQ+Fzm0SSNqmxcydO79zDfz5xB/5knOuuvJM/zzjroGt96i/7icbTOy2U+d2sXDKLbe0hogmLc08t54Yls3h40x76IkmKvOaoSqaR86pkjpMQQgghhBBCDPfC5ijOGP+Oc3T6+CUXFB3bRZ2kJHwSE1ruIPFDhSuZAKa+uZc1G3cPqzrKtKVNKvKyavlCID14/M32ELaGn7y8j2gyBaRnLsVSGrepOLW8kHAiRVPn4Jiv+77mBn64fhVhbyGfuuZ+mipPPeR9heIpbCe9xOICD4tnlvPAVWfz8KY99A4muO+Z7XSE4pT43MyfEhh17xI2CSGEEEIIIcTBtXVZxJP506d4UtPWbR3jFZ28pO1OTGi5A8JzZdroMjOPcuW24K3ZuJvP//hV9vUM4jINQrEkC77+O77w+Gt0hRNUFLrxGIr3zalgelnBsOepLPLw8bOmsadr7ODpU43P8egTd9BaUsUnr/1W3uApX+NdSYGL0gIXHlOxrT3EYy81s3hmOZUBL639Md7cP0A0kcKyHZnfJIQQQgghhBDvQPVkNz5P/lEoPo+iutJ9jFd08pLwSUxoyxZV5x2gnS+Uyg2kMtcFoxYv7exhX1+MlO3w+ltBBhM2v3ujkxebuomnNAuml9LYOsAre4PZ53Ib0B9Jcsdv38zfbqc1//DSz/nW09/l5ZoFXPHZ++kMVOS9h3xf6iIJm7NOKcNQCtvRrH56G+9d/Rxel8HC6SWcMa2Ec0+dxL3LF0iFkxBCCCGEEOK4UjPZTe10NzWTxzfcuegcP8YYe0YZKn18IrjrkR5uWNXOXY/0jPdSjhppuxMTzshWu3zhy8iZRzA8kMoM3f7cY6/gcxuYChZOL8VlKP6wrRPLgaStCUYtirwmW94KDXt+ywFrjOZgl53inmd/wNVbn+XJMz/Av3zsy1jm2F9UXSYU+1z0RFLZxwrcikjCZv6UADu7BxmM27QPJPjtX/bzkTOmsHJprYROQgghhBBCiOPS7dfn/8H8seb3Gay+qTI9XDyZHjquFBR4FKtvqhzXYei5Wrosdree2C2AEj6JCSc3RBorgMkXSmUCqblVAerWbWVeVQClFOfMKBsW5tQ39/L3j9STsDVKKaqKfcyoKKL3rWC+lxqmMBHlwQ338f7mzfz7e6/mgfd9dswd7TL8HheJlMZU6XlSLkPh87iprSxkblWATTu7eW1vH3ErvdPCoe5dCCGEEEIIIcThWTDbx9rV1ay4u53ufpuKUpPHbps6YYKnaNwhFEn/WzAUcYjGHfwTZG1HkoRPYsLJV9V0KLnVUpmd7Z59owPDUJxS5md9Qxvb9ofY0RlmXlWAM6tLaOoM43EZzK0KcNmiar74+Gv0RlNjvkblYB+PPnEn87uaueVjX+aXZ330kOsqdKe/aCRTDgVuE6Ug4HOzoLqE+uY+trWH8LhMzjt1ElXFPuZWBWjqDMucJyGEEEIIIYQ4Qgp8BsWFBt39NsWFxoQJnhp3xbNVWQA9QZsr69pYfVMlC2b7xnl1R5aET2LCeSc7uWWqpdZs3M32jjCW7WAaCjS0D8SIWjYbGtowDMUGRxMocBNN2li25nvP78TnNhhM2HhMSNqjn7+2p4Ufr/06ZbEQ119+O3+sPXfMtbiM9BwngHjKocTvBjSDCZsPnVZFWaGHjTu6CCds4pbN0rmVXHaQ3fzezo5/QgghhBBCCCEmvmjcoe7BbqKJA+NetIZoQlP3YDdrV1dPmJDsSDhx7kScVEbudpcZMI5SlPjcVBR5+fIH5vDh06v4yBlT2NszSNxyGEzYJFIOXaEEtk6HQ70Ri7ZggoSt8wZP72n5K+t+8s947SRXfeYbBw2eFFDgMTjv1FJcBlQEvJw+rQTbAbdp8r+7etjTHWFqSQFVAS83XDgrO59qLGPt+CeEEEIIIYQQ4vj0wuYoY4wZxtHp4ycSqXwSx6XcSqc1m/agtebGpbUAw1r2flq/jz3dEQA06XDINBS2rVFDjx3Mpds28e3//g4tJVNYceWdtJZUHfR8DfjdJrMnBzh9Wgm/erWFvT2DXH7OdJ59o4Mir5sir8nKpXMPu4rpnbQhCiGEEEIIIYSYuNq6LOLJ/P8ijSc1bd0n1gByqXwSx6XcSqetrUEaWweyQ7pXLV8IwK3rGtnZFcHW6UHfmT/WmZa4gwZPWnND/Tq+/5v72TJ1Hpdf881DBk8ZPYNJ5lYFePbNTqKWw+7uKC19UZbOm0xZoYeq4nTvbm7l1sFk7kla7oQQQgghhBDinamZ7KZ2upuayWPvVH4sVU924/Pk37zK51FUV06MdR4pUvkkJpTDnW+UmQtV39zLw5v20DeYYHtHmM//+FUunF3B95/fSX/UwmsqEnZOD232P2MzHJvb//AwK15/iqfmX8hX/u5mEi7PIdd+YDc7eHFnNwkr3cNnGqCUGlbBNLKVTmY6CSGEEEIIIcTRc/v1FeO9hGEuOsfPD5/oz3vMUOnjJxKpfBITyqHmG42c9bR4ZjmPXHce86YWs7srzEs7u1mzaTf9UQtb5/8fPM9YpyyfFeeH61ez4vWnWHPeJ/nyJ756WMETQJnfTaHHwDQM+qMWk4t9TCvx8v55k3nf7ArWbNpDRygOHKjcyhdECSGEEEIIIYQ4sfl9BqtvqsTvVaihAiilwO9VrL6p8oQaNg5S+SQmmLHmG2UqonZ0hGnpj7J5bx+9gwksR1NbWcRlZ1ez0etCKZupJQV0hhIAxOxDTXU6YFJ0gEeevIuz9zfx9Q/dyI/P+fjbWnt/1KKqxIfbUHQMxDl9WjF3fOIMFs8sp27dVra2BkGnZ1KNbKOTmU5CCCGEEEIIcXJZMNvH2tXVrLi7ne5+m4pSk8dum3rCBU8g4ZOYYHLb6erWbWVeVYAdnWE6Q3HaB+Ls64mgFPSGkzhD12xrD3Ha1GIeuHoR9z+znb29kTF3DRjLjP79PLb260wN9/L/f7KO389979teu6Oh0G3goNDa4c39A6zZtIdt+0N0huKcUuan1O8eFTJl7lkIIYQQQgghxMmlwGdQXGjQ3W9TXGickMETSPgkJqhMK9orzX1UFHkJ+FwkUw4VRV56BhPpssSh+Uo1ZQW8tref3/+1ncGEjWXrQ+5il+vs/Tv40RN3ooDPXH0vr1eflj12ODvilfvdWI5DOG7TH7V48JpzuHVdI70DCV7a2c22/QPUTCpk3pRAdhi6EEIIIYQQQggBZIegT5Rh6EeDhE9iQsq031185hSaOsPMrQrQH0nSPhCjuqyA7nACUynOnlFGMJKkoSWIo9NDv31uA5epiCRsDtV19+GdL/Mfv/kmnUWTWHHFHeydNLwqqcBtELWcMa5OD4I7taIQDby5f4AZ5YVDu9Mt4OZfNBBNptsAM/OdhBBCCCGEEEKIXBNtGPrRIOGTGHf5drjLbb/b0RnmxV097OoOE7ccirwuyou8xK0Uf9rZjQHooZCp0GtS5DXpCiUPGTxd+/pT3PHcGhqnzObzl99Ob2HpqHMOFjxBOuwq9btZubR22NymxTPLeeDqRdnHpK1OCCGEEEIIIcTJSsInMe5yd3sbGdI8tHE3ja0D1JQV4DYMYtqhIxTH6zIJxSxsIOVoXKai2GtySnkhDS0DB309pR1u2fhjvlD/JP8zezFf/sRXibt9b3vd5YVuzq4pZeXS2rxzm2SWkxBCCCGEEEIIIeGTmADy7XCXqYYaiFooBUopNKC1Bp3egnJGuR9HQ9yy6QglGEzYRBL2QV/Lk7L41tMP8Iltm/ivRX/HHR9aiWOYh1xjeaGbQo+LYDRJIuVwyqQC7hnasS4zHH2ZVDgJIYQQQgghhBCjSPgkxl2+CqFMNVQolmQwnmJbe4ik7aA1uE3FwumlvG92Bb/5y37e6ouQciAF9EYSFLgUsdTonrvi+CBr1t3D+S1/ZfX7V/DQey5Pp1iHUO43+fIH5tDUGaYjFCeSsKmtLMyu+WCVW0IIIYQQQgghxMlOwicx7jJVTvOqAuzoDLNsUXW2GqqlP0rccnBID/d2GWBr6BtMsObFPewPxrPPo4BJfjf9EWvUa1QPdPHo2juYEdzPP3z8q/zm9KWHvb5I0qGpM8yq5Qupb+4dVaU1ryrAK819XHzmlLz3JRVRQgghhBBCCCFOZsZ4L0CcmDKtaPXNvYc8N1M59PjL+9jSEuTWdY0ArFq+kJUXzsqe53UpTi0vYjCRoqFlgPac4Cljd3eUkSPCT+/cw7qf/DNVg738/ZV3HzJ4cqn0R0ZNWcGwQeKrhtrtMnZ0hqko8tLUGc57Xxsa2g75HgghhBDvhFLqY0qpHUqpXUqpf8lz3KuU+uXQ8Xql1KlDj5+qlIoppbYMffzfnGvOUUo1Dl3zH0odRpmwEEIIIcRBSPgkjoq3E7wsW1RNbWUh154/g2TKwWMa2etWXDCTv3/vDArcipqyQop8Lpz02CdGNtZpGBU8LdmzmV/97BZSyuRTn72f+lMWHHQtCnC7FB86vYqAz6Qq4KEvYnHzL/9fe3ceHnV19n/8fc9kgyQQ2SEsIgICigQQaC20VFG0VhBwQfBBi6XW9qm1tnVp64pKrT7qo7Q/qWvVihsVHgVxF0slyhJBQdaoEJElELIns5zfHzOJSQjJRDOZJHxe15WLme+cc+bM5JvJlzv3uU8Wj6/MrmxXNbhWMf+q2VAQyojaX1jGgK6p9b4HIiIiDWVmXmA+cBYwGJhuZoNrNJsNHHTOHQ/cC/y5ymPbnXPDwl9XVDn+N+CnQP/w18RovQYRERE5Oij4JFFxpIBMbUb37ciArqk8+NZW9uaX4g8E2FNQxuMrs5n9xIf8X1YO/oBjb0EphaU+PBY6cdsleanrT7Hnr3+NR1+4hc/TunPeJXeztXOfeufiNfAHYV9BGQ/POoWUpHjyS33sOVTKPa9vrszkqlnnqWY2FBw5I0pERKSRjAK2Oed2OOfKgYXApBptJgFPhG+/AJxWVyaTmXUH2jnnVjnnHPAPYHLjT11ERESOJqr5JFFRWxHxujy56nNyi3w4oPxACfsKy3lvy14CwVCNJ4BDJX7ySvxAOEPJc4RrZ+f49cp/8uuVz7Di2Ax+Pvl6ihLb1jsHr4HXY5QHHB/nHOKhd7dzyZg+LMnK4dOvCjimTUJlsKm2HfpqiqSNiIjIt5AO7Kxyfxcw+khtnHN+MzsEVPyC7mtm64B84I/OuffC7XfVGFO/yERERORbUfBJmkTV4tvAYYW4LxnThzuXbqI84CgLOMpK/IdlNbkat3OL/Yc9T1zAzx3LH+SCDW/w3Emnc8OZv8Tvjew0794+ibwSH/5ggDivsWHXIQwY2L0d5w5LZ8ueAiZlpEdcSLyhATgREZEmtBvo7ZzLNbMRwEtmNqQhA5jZHGAOQO/evaMwRREREWktFHySJlF1mZqDakvWIFTbaVCPdlz55OrKoJLXICHOQ7EvSJwHju+czKd7io74HCllxfz1pTsZ99k67j31Yu4/dTpEWCM1Kc4o8QVoE+9lYNdUjklOwDkHZuzYV4QRKoAOcP2i9YfNX0REJAZygF5V7vcMH6utzS4ziwPaA7nhJXVlAM65NWa2HRgQbt+znjEJ91sALAAYOXJkzVKMIiIiIpUUfJImUXMJWtXbj6/M5slVnzO2fydKfF+XDHcOisP3A0HwBx1t4z2Vx6rqUpDL4y/czIB9n/O7s37F80PPaND8UpPiOaZtPIVlARzw03HHMbpvRzKzcyvnWpHxNLBrKgZaTiciIrH2IdDfzPoSChBdBFxco80SYBbwPjANeMs558ysM3DAORcws+MIFRbf4Zw7YGb5ZjYGyAT+C3igiV6PiIiItFIKPkmTqLkErSKwc/2i9by7ZR8FpX5eXLuLTqmJ7C8oo8QXJFClvwO27Suudez++z7n8edvpn1ZIT+ZdhMrjhvRoLnFe2DC4K5s2p3P5weKKS738/cVOyqX1tXMeKqaBSUiIhIr4RpOvwSWA17gUefcJ2Z2K7DaObcEeAR40sy2AQcIBagAxgG3mpmP0GaxVzjnDoQfuxJ4HGgDLAt/iYiIiHxjCj5JzDz07nY27DpEWps4jDgKSsrZdaCERG/1+k51GfPFehYsup2S+EQuvHgen3TtF1G/1EQv6WlJbNtXxGmDunLHlKHMfuJD2sR7SE6MI+jcYUvrVEBcRESaG+fcUmBpjWM3VrldCpxfS78XgRePMOZq4MTGnamIiIgczRR8kkZRWxHuIxUZr7idV+zDDPp0SqFzaiLPfriTIFASONKzVHfuxnf5y9J7+SKtO5eefws57btE1C85wUuXdknklwVokxDHtr2FAMwZdxyLUxNrXRoIKiAuIiIiIiIi8k0o+CSNompB8YoATc0i41lf5PFB9gGO7ZRMYamfDskJdEhOIOgciXEeUhK95JdGEHlyjisyX+S6dx9nVa8TmTPlj+QnpUQ816AL4vMH6ZaaSNt4LzPH9AFqXxooIiIiIiIiIt+Ogk/SKCqWpA3omsr1i9YzOSO98lhCnIfXPvmKcn+QtolxZH1+ADPjmOQEDhSWUVQe4B2/o2eHNvh8pZQEjrzozhMMcMsbD3HJuqUsGTSO3559NeVx8RHN0YAOyfF0aZeEzx/k2rMHKcAkIiIiIiIiEmUKPkmjqMgaqijKvXhdDndMGcrovh057Z53KCgLkOCB/QVllPqDOAf7i3zVxvjiQEmdz5HkK+WBJX9hwrZM/t/oqfz5+7Nw5ol4jh2S4/nxyT0o9wcZ0DWVl9blVM5dRERERERERKJDwSdpVFWLcj++MpsFK7bjCwTx+wO0T0kkr7iU4DcYt2NRHo+8eCsnfbWNP024gieHn9Og/l6DQNDx3tb9XDKmD0+u+pwErwdDwScRERERERGRaFLwSRpVRQZUZnYu97y2meLyAA5I8BolvgAer0HQgQOPJ3SzjlV2ABx7IIcnnr+JLoUHueK8G3i9/5gjtjUgKc7wBcFjDjCCztE2IY4yfwBfIBgKPMV58IUzoCqWCSoIJSIiIiIiItL4FHySb+VIO9o99O52yv3BysBSIOjw+YMkeY3ioCMAxHs8+P1150ENz9nEwy/ehgOmT7+DrB4D62xfEcdq3yaOcl+AIEb7NnGc0L0du/NK8QWCzBzThy17ChjQNVUZUCIiIiIiIiJRpuCTfCs1d7SruG1mlcvrDPAFwfmCBIOu8nhpPYGnM7f8h/v/7252p3bk0vNv4fNjekQ0pxK/I84b5JiURBK8Hm6fchJA5XLAiiDT9YvWV2ZATQoHz0RERERERESkcSn4JA1WNdupao0noHJ3u6wvDuILpz1VZCP5g/Wsr6ti1pr/46Y3FpDVYwCXT72RA23bN2iOJb4A/oJSrp349Y52NTObJmekY1AtICUiIiIiIiIijUvBJ6lX1WDT6L4deejd7WzYdYi9+aU8cumoaoGbit3tcmvsZBcpc0Guf/sx5nz4L17rP4Zf/fi3lMYnNXgcfxDiPPDkqs8Z1KNdrcGlivpUIiIiIiIiIhI9ke9TL0elzOxcbli0gf9s288NizaQmZ2LmWEGZlZrn0vG9PlGz5XoL+eBJX9hzof/4vHh53DF5OsbFHhqE2e0jQ+d0gaU+x3+QJDF63LIzM7l+kXryczO/UZzExEREREREZFvRplPUqeX1uWQ4PWwO6+EeK+x4N3tzPl+v2pL7SpUZEglxnlI8EJ5IPLnaV9SwIJFcxm96xPmjv8JD59yHhwhuFWV1yA5wYvHY7RNiCPOY+wvLKNNvJfkxDjivR4mZaRXq02lbCcRERERERGRpqPgk9RpckY6e/NL2VtQSiAYrMx2qq16U0WAZ+OXh/A1IPDU89AeHn/uJnod+opfnvt7Xh40LrJ+aUkM6JZKXrGPnQeK6d4+ibwSH306JZOe1oYuqYmVAbI9+aWkJsWpsLiIiIiIiIhIE1PwSeo0um9HXlqXQ5d2Sfj8QX467rjDsoiqZjztPFhMuzZx+INBSnz1Fxgf8tU2HnvhFhL95Vxy4Vw+6HVixHPblVeKx2P075LCCd26Vit6XnNXu6KyAP06JyvrSURERERERKSJKfgk9RrYNZUPsg9U1nLak1+KPxDkq/xSHl+ZzYIV28krLqfM7whvcBdRMbEfbF/N/MXzONimHdMvuoPtnXrV2d6ATinx7Cv8uph5XnE5c77f77Ci51XV3JFPRERERERERJqOgk9yRBUZTXsLyuiUWW/VsQAAIABJREFUksh7W/fx5KrPSfB62FdQSuGXAVZnH6DYF8AfrN43WPuQlS78aDm3L5/Ppi59+cm0m9iX0qHe+Thgf5XAkwFThvesN5tJu9qJiIiIiIiIxI6CT3JEFcvrUhK99OuczOavCsg5WIIvECTBa5T7HWX+iOqCf805rv7301z1n4W803cEV06+juKENg2alwHxXqNtgpfymlEvEREREREREWlWIlkdFVVm1svM3jazjWb2iZldFT7ewcxeN7Ot4X+PifVcjzYDu6ayv7CMsf07c8eUobRvG095IIgDkhPjSIr3kBhnBOsv7QRAfMDH3Uvv46r/LGTh0DO4fOqfGhx46pAcz6zv9mHcgM6M6HMMkzLSyczO5fpF68nMzm34ixQRERERERGRqGoOmU9+4Brn3FozSwXWmNnrwKXAm865eWZ2HXAdcG0M59mqVSyxm1ylUPfmPQUkeD08uepzAMyMfp3acrDYR++OyeSXlLNjf3FE46eUFfO3f93B2M+zuOd7M3jguxc1MGUKErxGRu9jKAsXPq9aULxqAXQRERERERERaT5invnknNvtnFsbvl0AbALSgUnAE+FmTwCTYzPDo0PFErsF726vzCKanJHOoZJycgvLWLBiB4Wlfnp3TMY5x4acQ+TklUSU9dS1YD/PP/17xuzcwDVnX80Dp05vUOAp0QtegziPkVtYVhloqjA5I51+nZNVUFxERERERESkGWoOmU+VzOxYIAPIBLo653aHH/oK6HqEPnOAOQC9e/eO/iRbqYod4fYUfB3cuWPKUE7o3o4Nuw6Rkuhlf2EZ2/aWkVvsB8AXqH/cAfs+4/Hnbya1rIjLpt3Mv/tmNGheiXGG14yOqQm0T4qnY0oiXVITqwWaVFBcREREREREpPlqNsEnM0sBXgR+7ZzLtyqZMc45Z2a15tg45xYACwBGjhwZYfUhqakiePPQu9vxB4Js/qqA8+b/m6KyAEHnyC0sIzkpntwif8Rjfufz9Tz0r9spjk/kghl/ZlOX4yLq1zMtkZLyIG0SvASdY864fgzq0Y7F63KYVGVZoIiIiIiIiIg0fzFfdgdgZvGEAk9PO+cWhQ/vMbPu4ce7A3tjNb/Wqmah7pfW5VBUFiCvxMcXB4v5+Mt8tu0rJLfIR26xny8OlEQ89qRP3uaJ525kd2pHzrvknogDTwDjBnThjBO7kX5MW34wsAuXntqX0X07cseUoQo8iUiL9OqrrzJw4ECOP/545s2bd9jjO3fuZPz48QwePJghQ4Zw//33V3s8Ly+PadOmccIJJzBo0CDef//9yscCgQAZGRmcc845dc7hiiuuYOXKldWOeb1ehg0bVvlV29yqGj9+PMuXL6927L777uPnP/95nf1ERERE5OgW8+CThVKcHgE2Oef+p8pDS4BZ4duzgMVNPbfWrqLOU0X9pK93t+tE72PaYjhoaC6Zc1z5/nPc//I9rO45mPNn3MXudp3r7OLh6xPRgAFdUyvrOA3omqqd7ESkRQsEAvziF79g2bJlbNy4kWeeeYaNGzdWaxMXF8c999zDxo0bWbVqFfPnz6/W5qqrrmLixIl8+umnfPTRRwwaNKjysfvvv7/a/SNZtWoVY8aMqXasTZs2ZGVlVX5dd911dY4xffp0Fi5cWO3YwoULmT59er3PLyIiIiJHr5gHn4BTgUuAH5pZVvjrbGAeMMHMtgKnh+9LI6jIeBrYNbVaoe73tu0nv9THhl2H+Gx/If5gKBjUNj6y4uDeYIDbX5vP71f8g38N/gGXnn8L+Ukp9fbr3C6Rbu0TSYoz2rfxsmVPQWWm0+Y9BYcVGBcRiaYf/OAHfPrppwDk5uZy4oknfqvxPvjgA44//niOO+44EhISuOiii1i8uPrfU7p3787w4cMBSE1NZdCgQeTkhD73Dh06xIoVK5g9ezYACQkJpKWlAbBr1y5eeeUVLr/88jrnsGnTJgYMGIDX64143k899RSjRo1i2LBh/OxnPyMQCDBt2jReeeUVysvLAfjss8/48ssvGTt2bMTjioiIiMjRJ+bBJ+fcv51z5pwb6pwbFv5a6pzLdc6d5pzr75w73Tl3INZzbS0qMp627ClgUkY6L63L4fGV2XywI5f9BeVk7cwjt9hP0EEAKPbVn/7UpryUhxbNZUbWq8wfcz6/Oec3lMfF19nHY6Fd7A4WleExIznBS7/OqdWKiWsnOxFpatu2bWPAgAEArF+/npNOOqna42PHjq22VK3i64033qh1vJycHHr16lV5v2fPnpWBpdp89tlnrFu3jtGjRwOQnZ1N586dueyyy8jIyODyyy+nqKgIgF//+tfcddddeDx1/zpftmwZEydOPOx4SUlJtdfw7LPPAqFg1bPPPsvKlSvJysrC6/Xy9NNP06FDB0aNGsWyZcuAUNbTBRdcgDVgB1MREREROfo0m4LjEn2Z2bksWLGDA4VldExJrAw87dhXxAfZByj1h7avCzRwqV2nooM88sKtnLhnO38440qezji73j5t4oz4OA8l5QGcg/2F5aQmxTGwW2q1uk4VO9lVZGtNVsFxEYmizz//nPT09Mpgzvr16xk6dGi1Nu+9917Unr+wsJCpU6dy33330a5dOwD8fj9r167lgQceYPTo0Vx11VXMmzeP0aNH06VLF0aMGME777xT57jLly/nscceO+x4xbK7mt58803WrFnDKaecAoSCVF26dAG+Xno3adIkFi5cyCOPPPItX7WIiIiItHYKPh1FXlqXw5rPDlBU5qdzaiIQqvP0QfYBxvbvxMsflbG/AbvZARyXu4vHn7+JTsV5zJnyB948fnS9fQw4JjmRQT3akVdUjnMOMyOtbfwRM5yq1qdS8ElEouWjjz6qFmxas2YNF154YbU2Y8eOpaCg4LC+d999N6effvphx9PT09m5c2fl/V27dpGefvhnnc/nY+rUqcyYMYMpU6ZUHu/Zsyc9e/aszISaNm0a8+bNw+/3s2TJEpYuXUppaSn5+fnMnDmTp556qtq4xcXF5OXl0aNHjwjfBXDOMWvWLO68887DHps0aRJXX301a9eupbi4mBEjRkQ8roiIiIgcnRR8OopMzkjn3S37KCj1s6+wnLuWfUpeiQ9fIMh7W/dTUBpo0Hgjdm3k4RdvI+DxcNH0O1nffUDEfZMTvRSW+hnYLZU7pgytt/3kjHQWr8vR8jsRiaqsrCxKS0sB2Lp1K4sXL2bu3LnV2jQ08+mUU05h69atZGdnk56ezsKFC/nnP/9ZrY1zjtmzZzNo0CB+85vfVHusW7du9OrVi82bNzNw4EDefPNNBg8ezJ133lkZHHrnnXe4++67Dws8Abz99tuMHz++QXM+7bTTKoNMXbp04cCBAxQUFNCnTx9SUlIYP348P/nJT1RoXEREREQiEvOaT9J0RvftyJyxxxHnMZyDrXsLyC0sY8+hUvYXlFJPyZBqJm5eyT8X/oGDbVKZMvPuiAJPRqjOU3KClz4dkytrOVUsqatrR7uKAuTKehKRaProo48IBoOcfPLJ3HrrrQwePJgnnnjiW40ZFxfHgw8+yJlnnsmgQYO44IILGDJkSOXjZ599Nu+99x5PPvkkb731VmX9paVLl1a2eeCBB5gxYwZDhw4lKyuLG264IeLnP1K9Jzi85lPFbneDBw9m7ty5nHHGGQwdOpQJEyawe/fuyn7Tp0/no48+UvBJRERERCJizjWwwE8zNnLkSLd69epYT6NZu37RepZk5VDiCxIH+IFEr5EY7yEYhPyy+rOffvLhYv741sOs6zGQy6f+iYNt29fbx4D0tEQOFvsJuiDXThzEoB7teGldDnvySykqC9Cvc3JEWVAiItHSv39/1q5dS2pqaqyn0miGDx9OZmYm8fF1bwLRUpjZGufcyFjPQ6rTNZiIiEjr9m2vwbTs7iiSmZ3L3oIykuI8lPuClIfjjiV+R4m//qCTuSB/fOsRZq9ezLIB3+XX51xDWXxiRM+dnOAliNG+TRzt2yawZU8Bm/cUsGNfEalJcdrRTkRirqCgADNrVYEngLVr18Z6CiIiIiJylFPwqZXKzM7lpXU5lbvDZWbncuWTq8kvC9A1NYHc4oYVFk/0l/M/L9/Djzav5NER5zL3h7MJerwR9w+4IHEeo3NKEnklPgZ0TWVQj3aVdZy0nE5EYi01NZUtW7bEehoiIiIiIq2Ogk+tVM3d4V5al0N+WQBfwLErr6xBY6WV5PP3F+dySs5Gbvvh5TxyyuQG9W+X5CU9rS2+QJD2beOJ83rYsqeAS0/tWzlXQAEoERERERERkVZIBcdbmEiKc2dm57Inv5TUpLjKgt6f7s7HaHh9r555X/HiU79n6FdbuXLSdREHnhI80DbeQ1obL93aJVEeCDJzTB9+9v1+1ZbYVQ2SiYiIiIiIiEjro8ynFqZmRtOR2lQU8Aa4YdEGvjpUSnn9ZZ2qOWn3Vh594Rbig35mXDSX1T2H1N8JSPBCp9Qk4jxGgtdDr47JFJb6+fe2/WzeU1C5FBBgckZ65dI7EREREREREWl9lPnUwkzOSK+3OPfkjHRSk+L4Kr+UBSt2kBDnodTXsMjT+O0f8uwz11Ean8jUmX+JOPBkQLukeM4Y3JV4r4eZY/owZ9xx9OucTNC5w7KcRvftyB1ThmrJnYiIiIiIiEgrpeBTC1NXsKZiSR5A59REisoCHCwsY19+KYEGrLibnvUqD794G9s69mLKzLvZ3rFXne2N0ImUkuAlJclL59Qk3tu6n4Q4D0+u+hyAO6YMPWzJnYiIiIiIiIi0fgo+tRKZ2blc/WwWSzd8yV3LPmXzVwXsPFAEZuSV+CIbxDl+u+If3Ln8Qd7tO5yLpt/JvpRj6u8GBIEex7ThmgkDyeidxiVj+lDuD5Lg9VRmOinLSUSONjt37mT8+PEMHjyYIUOGcP/999farrS0lFGjRnHyySczZMgQbrrppsrHjj32WE466SSGDRvGyJEjq/XLy8tj2rRpnHDCCQwaNIj333+/1vGvuOIKVq5cedhxr9fLsGHDKr/mzZt3xNcyfvx4li9fXu3Yfffdx89//vMj9hERERERAdV8ajVeWpdDcZmf4rIAm3bnE3SOMr9jz6EyIllwFx/w8edl/8uUT97mnydP5E9n/JyAxxvx8xsQDLrKHewABvVop3pOInJUi4uL45577mH48OEUFBQwYsQIJkyYwODBg6u1S0xM5K233iIlJQWfz8f3vvc9zjrrLMaMGQPA22+/TadOnQ4b/6qrrmLixIm88MILlJeXU1xcXOs8Vq1axfz58w873qZNG7KysiJ6LdOnT2fhwoWceeaZlccWLlzIXXfdFVF/ERERETl6KfOphaq5693kjHS6tEsiEITEeC/lfoeDiAJPqWVFPPb8zUz55G3uGvdf3HDmLxoUeErwQsfkeGaO6VPtuDKdRKSl+eijjxg3bhyDBw/G4/FgZtx4443feLzu3bszfPhwAFJTUxk0aBA5OYfv7mlmpKSkAODz+fD5fJhZnWMfOnSIFStWMHv2bAASEhJIS0s7rN2mTZsYMGAAXm/kn+tPPfUUo0aNYtiwYfzsZz8jEAgwbdo0XnnlFcrLywH47LPP+PLLLxk7dmzE44qIiIjI0UnBp2auZpCpQsWud39fsaOyzlNhmZ8gkFfso+7/snytW/5+nnv6Wkbv/Jirf/Qb/vqdC6Ce//BUlZrg5cnLx7D6T2dUy3oSEWlpSktLufDCC7n77rvZuHEjf/jDH/jtb3/LLbfcUtlm7Nix1ZapVXy98cYb9Y7/2WefsW7dOkaPHl3r44FAgGHDhtGlSxcmTJhQ2c7MOOOMMxgxYgQLFiyobJ+dnU3nzp257LLLyMjI4PLLL6eoqOiwcZctW8bEiRNrfc6SkpJqr+PZZ59l06ZNPPvss6xcuZKsrCy8Xi9PP/00HTp0YNSoUSxbtgwIZT1dcMEF9QbJRERERES07K6ZW7BiB+t35bGvoKxaBtHkjHQWr8th0+583t++n8XrcmiTEIolRprxdMLebB57/maSy0uYdf4t/OfYYRHPy2vg8UBq2/gGviIRkebpjTfeYPjw4YwaNQqAoUOH8uqrr1YLrrz33nvfaOzCwkKmTp3KfffdR7t27Wpt4/V6ycrKIi8vj/POO4+PP/6YE088kX//+9+kp6ezd+9eJkyYwAknnMC4cePw+/2sXbuWBx54gNGjR3PVVVcxb948brvttmrjLl++nMcee6zW56xt2d2DDz7ImjVrOOWUU4BQgKpLly7A10vvJk2axMKFC3nkkUe+0fshIiIiIkcXZT41c845cOF/q6hY0tYhJZGi8iDFviC5Rf6Ix/3uZ1k89/S1AJw/864GBZ4A0trG0zklkfZt4isLiouItGQff/wxJ510UuX9tWvXVi6Zq/BNMp98Ph9Tp05lxowZTJkypd55pKWlMX78eF599VUA0tNDdfO6dOnCeeedxwcffABAz5496dmzZ2WG1LRp01i7dm21sYqLi8nLy6NHjx4RvAMhzjlmzZpFVlYWWVlZbN68mZtvvhmASZMm8eabb7J27VqKi4sZMWJExOOKiIiIyNFLmU/N3M++3++wot2Z2bm8tC6HyRnpzBl3HB99cZDcIh+ujnGqOu/jt7hr2f1s69iLy6bdzFftDi9iW8EI1XM6UOQjGD7WsW08f50Z+g+HCoqLSGvRsWNH3nrrLQC2bNnCokWL+M9//lOtTUMzn5xzzJ49m0GDBvGb3/zmiO327dtHfHw8aWlplJSU8Prrr3PttddSVFREMBgkNTWVoqIiXnvttcoaVN26daNXr15s3ryZgQMH8uabbx5WyPztt99m/PjxDZrzaaedxqRJk7j66qvp0qULBw4coKCggD59+pCSksL48eP5yU9+wvTp0xs0roiIiIgcvRR8auYqltq9FM4u2vRlPne9+ing2JtfSq8ObSkq85PgNcoC9YSfnOMX7z/H7957kn/3OZmfn3cDBYnJdXcBnAuS0TuNoHN0TEnkp+OOq5yXiomLSGsxffp0lixZwoknnkinTp145pln6Njx233GrVy5kieffJKTTjqJYcNCGaZ33HEHZ599NgBnn302Dz/8MPv372fWrFkEAgGCwSAXXHAB55xzDjt27OC8884DwO/3c/HFF1er3/TAAw8wY8YMysvLOe644w5bXrds2TKmTZt2xPlV1HyqMHHiRObNm8fcuXM544wzCAaDxMfHM3/+fPr06VP5Pp133nksXLjwW703IiIiInL0sJrLuVqykSNHutWrV8d6Go0qMzuXGxZtICHOQ0avNN7ZvJcvD5UB0CMtidyCsvqDToA3GOC21/7KxR8t58Uh47nurF/h80ZeryneA2ltE5gwuCt3TBn6jV+PiIg0neHDh5OZmUl8fOupz2dma5xzI2M9D6muNV6DiYiIyNe+7TWYMp+auZfW5ZDg9XCo2MdX+aWkJMbhtTICDvYVlOKLoLJ42/ISHlz8Z364YzUPfOdC7hk7s94d7doleigoC1Yu5YvzGEN7ttcSOxGRFqRmDSgRERERkVhQwfFmbmDXVA6V+igs87H284OkJsXTNtELEFHgqXPhQRY+cz3jstdy/Zm/5J5xl9QbeAIoKg9ihGo+eSy01fec7/djdN+OZGbncv2i9WRm5367FyciIiIiIiIirZ6CT83c5j0FFJX5yC8NkFfiZ8OuPApKI4g6Af1yd7Loqd9yfO5OLp/6J54ZNrH+TmEBBxikpyWSnOilU0pi5a52L63LYce+Iu1yJyIiIiIiIiL10rK7ZigzO5cFK3bgnGNc/8689okHCAWcyoN1960wctcnPPzibfg8cVw4fR4buvevs327RA/F5UH8LpTtFOcxvAZBjGsmDGTLnoLKJXeTM9K1y52IiIiIiIiIRETBp2ZowYodrNy6n6R4D93aJXFsx2Ryi/Ii7n/2p//m3pfvYVf7rsw6/2Z2pXWrs32cQUKcl27t25BX4iPO66F9m3h2HSymfVI8W/YUVCsyPrpvR+1yJyIiIiIiIiIR0bK7Zsg5R1K8h7YJXiZlpHOopDzSjsz+4F88uPjPrO/Wn6kz76o38ATgd7C/yEdhWYDTB3VlztjjyOiVxjUTBpLRO00ZTiIiIs2UmU00s81mts3Mrqvl8UQzezb8eKaZHRs+PsHM1pjZhvC/P6zS553wmFnhry5N94pERESkNVLmUzORmZ3LS+tymJyRzrj+nfl0dz4pifHMW7qJ7P3F9fb3BAP86a2HuWzN//HKwFP5zTnXUBaXEPHzx3tgzrjjuPTUvt/mZYiIiEgTMTMvMB+YAOwCPjSzJc65jVWazQYOOueON7OLgD8DFwL7gR875740sxOB5UDVvzbNcM6tbpIXIiIiIq2egk/NRNUi3pu/KuDLQ2VAWUR9E31l3P/y3Uzc8j4Pj5zE7T+cjbP6k9riLJT1lBRnDOnRns17CsjMztWSOhERkZZhFLDNObcDwMwWApOAqsGnScDN4dsvAA+amTnn1lVp8wnQxswSnXORXXyIiIiINICW3TUDmdm5bPmqgJ0HihjQNZWtewoi7ntM8SH+ufAPnLFlFbec9lPmnvbTiAJPAGlt47n5x4OZMrwn7dvGawc7ERGRliUd2Fnl/i6qZy9Va+Oc8wOHgJp/ZZoKrK0ReHosvOTuT2ZmjTttEREROdoo8ynGMrNzuWHRBnILy4j3evj3tv2U+gIR9e19cDePP38TPQr2c+Xk63h14KkRP2+8B3p3aFu5zC4zO1c72ImIiBxlzGwIoaV4Z1Q5PMM5l2NmqcCLwCXAP2rpOweYA9C7d+8mmK2IiIi0VAo+xUhFjac9+aX4/EEKS/2h4zty8ZgBrs7+J3+5mUdevBVvMMjFF97O2p6DIn5uA45JTqBDSmLlMe1gJyIi0uLkAL2q3O8ZPlZbm11mFge0B3IBzKwn8C/gv5xz2ys6OOdywv8WmNk/CS3vOyz45JxbACwAGDlyZN0XLiIiInJUU/ApRh56dztrPjtAvNdDQpwH8xi+gKOgrP6sp9O2ZfLg4rvYl5zGpeffwo6OPSN6zk7JcZQHHN/t14kOyQnKchIREWnZPgT6m1lfQkGmi4CLa7RZAswC3gemAW8555yZpQGvANc551ZWNA4HqNKcc/vNLB44B3gj+i9FREREWjMFn5pQRbbTwK6pfPpVAcXlARLjQzlOSXEefIH6A08z1y3lltf/Hx937cfsaTeyP/mYiJ67XZKX+TNHKrtJRESklXDO+c3sl4R2qvMCjzrnPjGzW4HVzrklwCPAk2a2DThAKEAF8EvgeOBGM7sxfOwMoAhYHg48eQkFnv7eZC9KREREWiUFn6KoItg0OSOd0X07Vu5o90H2Adq3CUWd8orLyS3y4a2nlKe5IL9b8Q+uXPUCb/Q7hf8+91pKEpIimkecB045toMCTyIiIq2Mc24psLTGsRur3C4Fzq+l31xg7hGGHdGYcxQRERHRbndRVBFsqthBbnJGOqlJcRiOffmlmDmKfUEAAnVUSkjw+7j35Xu4ctULPDXsLH425Y8RB54GdEnmBwO7MOf7/SqPZWbncv2i9WRm537zFyciIiIiIiIiEgFlPkXR5Iz0w3aQy95fRM6BEkrrijZV0a60kIf+dTvf+WIDf/7+LP42ehpEsOOx12BYrzRevPLrHfCqFjkvKguweF2OsqFEREREREREJKoUfIqSqkvuAGY/8SFZXxykqCwQceCpR/5eHnv+Zvoe+JKrzrmGxUPGR9TPgO7tE0lLTiAzO7cywFSRiZWaFEe/zskqOC4iIiIiIiIiUafgU5RUXXK3+rODbNlb2KD+g/fs4NEXbqZteSmzLriF9/ucHHHfpHgv+SV+Ckv91bKbqmZiKeNJRERERERERJqCgk9RUjXQ86+1uxrU93vZ6/jbS3dQkJjMtJl3saXzsRH1MyAl0UvXdkl8r38nyv3BatlNo/t2VNBJRERERERERJqUgk9RUHPJXfoxbdi2rziivtM2vMGdrz7Ato69uPT8m9mT2imifv07t+VgsY/eHZO59qwTFGQSERERERERkWZBu91FQcWSu7uWfcolf1/Fjv0RBJ6c41crn+Hupffxfu+hnD/jrogDTwO6JPP6NeOZMKQb8V5P5e56IiIiIiIiIiKxpsynKBjYNZV3N+9jb34p/ghqi8cF/Mx97a9ctP41XjjxNK6b+N/4vXV/azwGw3q254Tu7SqX1tW2u56IiIiIiIiISCwp+NTIHl+ZzV2vfkqxLxhR++SyYuYv/jM/yF7D/d+dzr3fuxjM6u1ngJlxx5ShlcdU00lEREREREREmhsFnxqoaj2nqoGezOxcFqzYwbuf7o0o2wmgc+EBHnvhFk7Ym83vJ/6K504+I6J+7ZLiSIr3cExywhHnIyIiIiIiIiLSHCj41EAV9ZwWr8upDPZkZudyw6IN7Mwtijjw1G//Tp54/iaOKcnn8qk38k6/kfX2MSCjV3vOHZbOlj0FTMpIr3U+IiIiIiIiIiLNhYJPDVRbXaWX1uXgDwQpj2ylHaN2fszfX7yNsrgELrh4Hp90O77O9gYkxnmI8xiHSv0M6tGOS0/tW/m46jyJiIiIiIiISHOl4FMD1ayrlJmdy4fZuew8UBJR/3M2reCeV/6HL9K6c9n5N7Orfdd6+5w5pCv+oGPjl4dICO9mVzEH1XkSERERERERkeZMwacGqKivNLBrKu9t249zjrxiH9v2Fdff2Tl++sG/+MM7j5LZ60R+OuWP5Cel1NmlU3I882eOqLa8T1lOIiIiIiIiItKSKPjUABX1lT7IPkB+qY9yXwBfoP4iT55ggBvf/DuXrn2Zl08YyzU/upqyuIQ6+3RJSeD0wV2rZTUpy0lEREREREREWhpPrCfQkkzOSKdf52TG9u9EvNdDuS9Aia/uQk9JvlL+9tKdXLr2ZR4aNYX/Pvd39QYvucCYAAAP0ElEQVSeUhK9tGsTrwwnEREREREREWnxlPnUABWZR2f8zzt8mVdab/sOxYd4+MVbGfblFm48/Wf8Y8SP6+2TmuglNSmemWP6KMtJRERERERERFo8BZ8aoKLm09a9RfW27XPwSx5//ia6F+Ty8/OuZ/mA79bZPtFrfK9/JxxQVBZgy56CRpq1iIiIiIiIiEjsKPgUoczsXG5YtIGv8oqpr8rTsC8388gLt2DAxRfdztr0QXW279+5LXOnDGV0344qKi4iIiIiIiIirYqCTxFasGIHuYVlFPnqDj1N2LqK/13yF/akdODS82/msw51B5GG92rPol98r/K+ioqLiIiIiIiISGui4FMEMrNz+c+WvZQE6m53ydqXufmNBWzodjyzp95IbnLaEdt6DTwG5w5ThpOIiIiIiIiItF4KPkXgpXU5dQaezAW59p3HueKDRbx+/Gj++9zfURqfdMT2XsAMOqQkqraTiIiIiIiIiLRqCj5FYPveIweIEvw+7l56L+duWsE/Mn7EzafPIejxHrG91+DkXmmUlAfwBYKq7SQiIiIiIiIirZqCTxH44LO8Wo+3Ky3k74vmMnrnx9z5g0t5aNTUUErTEfRon0j7tgl0SE6gS7dEJmWkq76TiIiIiIiIiLRqCj59Q+mH9vL48zfRO283v/rx71gy+Pt1tu/YNo72bRLw+YP8dNxxCjqJiIiIiIiIyFFBwadvYMie7Tz2/M0k+sv5rwtuI7P3SXW2H9AlmYtH92HLngJlO4mIiIiIiIjIUUXBpwYat2MNf108j0OJKcyYMZetnfscsW1SnIchPdrx4pWnNuEMRURERERERESaDwWfGuD89a9x56sPsrnzsVw27Sb2ptaewWTArO/2odyvguIiIiIiIiIicnRT8CkSzvHrlf/k1yufYcWxGfx88vUUJbattemoY9N47gplOomIiIiIiIiIgIJP9fP7uWvZ/Vyw4Q2eO+l0bjjzl/i9tb9tXkOBJxERERERERGRKhR8qo/Xi9cFuffUi7n/1OlgVmuzTsnx/PKH/Zt4ciIiIiIiIiIizZuCT/Ux45qzrz5i0OnmHw/m0lP7NvGkRERERERERERaBk+sJ9Ai1JHtpMCTiIiIiIiIiMiRKfPpGzrthM7M+X6/WE9DRERERERERKRZU/ApAp2S49lf5AOgY9t4/nrJCEb37RjjWYmIiIiIiIiINH8KPkVg/swRLHh3O2bGT8cdp8CTiIiIiIiIiEiEFHyKwOi+HRVwEhERERERERH5BlRwXEREREREREREokbBJxERERERERERiRoFn0REREREREREJGqadfDJzCaa2WYz22Zm18V6PiIiIiIiIiIi0jDNNvhkZl5gPnAWMBiYbmaDYzsrERERERERERFpiGYbfAJGAducczucc+XAQmBSjOckIiIiIiIiIiIN0JyDT+nAzir3d4WPVWNmc8xstZmt3rdvX5NNTkRERERERERE6tecg08Rcc4tcM6NdM6N7Ny5c6ynIyIiIiIiIiIiVTTn4FMO0KvK/Z7hYyIiIiIiIiIi0kI05+DTh0B/M+trZgnARcCSGM9JREREREREREQaIC7WEzgS55zfzH4JLAe8wKPOuU9iPC0REREREREREWmAZht8AnDOLQWWxnoeIiIiIiIiIiLyzTTnZXciIiIiIiIiItLCKfgkIiIiIiIiIiJRo+CTiIiIiIiIiIhEjYJPIiIiIi2UmU00s81mts3Mrqvl8UQzezb8eKaZHVvlsevDxzeb2ZmRjikiIiLSUAo+iYiIiLRAZuYF5gNnAYOB6WY2uEaz2cBB59zxwL3An8N9BwMXAUOAicBfzcwb4ZgiIiIiDaLgk4iIiEjLNArY5pzb4ZwrBxYCk2q0mQQ8Eb79AnCamVn4+ELnXJlzLhvYFh4vkjFFREREGkTBJxEREZGWKR3YWeX+rvCxWts45/zAIaBjHX0jGVNERESkQeJiPYHGtGbNmv1m9nkdTToB+5tqPlKN3vvY0XsfW3r/Y0fvfexE873vE6VxpYHMbA4wJ3y3zMw+juV8ItCeUPDtaJhDtJ6nMcdtrLG+zTj6PdG8NIef0abSEs695vD90Gdm44/3bcYY+G2euFUFn5xznet63MxWO+dGNtV85Gt672NH731s6f2PHb33saP3vsnkAL2q3O8ZPlZbm11mFkfoojO3nr71jQmAc24BsABaxvfczBY45+bU37LlzyFaz9OY4zbWWN9mnJZw3h5NmsPPaFNpCedec/h+6DOz8cf7tp+Z3+a5texOREREpGX6EOhvZn3NLIFQAfElNdosAWaFb08D3nLOufDxi8K74fUF+gMfRDhmS/V/sZ4ATTeHaD1PY47bWGM1h++rNA59L5uX5vD90Gdm448Xs+9rq8p8EhERETlaOOf8ZvZLYDngBR51zn1iZrcCq51zS4BHgCfNbBtwgFAwiXC754CNgB/4hXMuAFDbmE392qLBORfz/0g11Ryi9TyNOW5jjdUcvq/SOPS9bF6aw/dDn5mNP14sv69HW/BpQawncBTTex87eu9jS+9/7Oi9jx29903EObcUWFrj2I1VbpcC5x+h7+3A7ZGMGQF9z6Ul0nkrsaJzT1qib3XeWijzWkREREREREREpPGp5pOIiIiIiIiIiETNURF8MrOJZrbZzLaZ2XWxnk9rZ2a9zOxtM9toZp+Y2VXh4x3M7HUz2xr+95hYz7W1MjOvma0zs5fD9/uaWWb4Z+DZcBFZaWRmlmZmL5jZp2a2ycy+o/O+aZjZ1eHPm4/N7BkzS9J5Hz1m9qiZ7TWzj6scq/Vct5D/DX8f1pvZ8NjNXBpT+OfsAzP7KPzzd0us5yRyJA353BJpLEf6nNQ1ijRH0b6+a/XBJzPzAvOBs4DBwHQzGxzbWbV6fuAa59xgYAzwi/B7fh3wpnOuP/Bm+L5Ex1XApir3/wzc65w7HjgIzI7JrFq/+4FXnXMnACcT+h7ovI8yM0sHfgWMdM6dSKhI8kXovI+mx4GJNY4d6Vw/i9BOav2BOcDfmmiOEn1lwA+dcycDw4CJZjYmxnMSOZLHifxzS6SxHOlzUtco0hw9ThSv71p98AkYBWxzzu1wzpUDC4FJMZ5Tq+ac2+2cWxu+XUDoP+DphN73J8LNngAmx2aGrZuZ9QR+BDwcvm/AD4EXwk303keBmbUHxhHaWQrnXLlzLg+d900lDmhjZnFAW2A3Ou+jxjm3gtDOaVUd6VyfBPzDhawC0syse9PMVKIp/D0tDN+ND3+pmKg0Sw383BJpFHV8TuoaRZqdaF/fHQ3Bp3RgZ5X7u8LHpAmY2bFABpAJdHXO7Q4/9BXQNUbTau3uA34PBMP3OwJ5zjl/+L5+BqKjL7APeCy85PFhM0tG533UOedygLuBLwgFnQ4Ba9B539SOdK7r93ArFl7mnQXsBV53zmXGek4iDaDf0RJ1NT8nge3oGkVajka7vjsagk8SI2aWArwI/No5l1/1MRfaZlF/HW1kZnYOsNc5tybWczkKxQHDgb855zKAImqk7+u8j47w2vNJhAKAPYBkDk8Zliakc/3o4ZwLOOeGAT2BUWZ2YqznJPJN6HNLoqXm5yRwQoynJPKNfNvPyaMh+JQD9Kpyv2f4mESRmcUTCjw97ZxbFD68pyIVL/zv3ljNrxU7FTjXzD4jtMT0h4TqEKWFlyOBfgaiZRewq8pf/V8gFIzSeR99pwPZzrl9zjkfsIjQz4LO+6Z1pHNdv4ePAuFlxm+jwK+0LPodLU2myufkd9A1irQcjXZ9dzQEnz4E+od3FEggVIR2SYzn1KqFaww9Amxyzv1PlYeWALPCt2cBi5t6bq2dc+5651xP59yxhM71t5xzMwj9opsWbqb3Pgqcc18BO81sYPjQacBGdN43hS+AMWbWNvz5U/He67xvWkc615cA/xXeFWUMcKhK+ra0YGbW2czSwrfbABOAT2M7K5EG0e9oiaojfE5uQtco0nI02vWdhTKnWjczO5tQHRwv8Khz7vYYT6lVM7PvAe8BG/i67tANhOo+PQf0Bj4HLnDO1SxoJo3EzH4A/NY5d46ZHUcoE6oDsA6Y6Zwri+X8WiMzG0ao0HsCsAO4jFCQX+d9lIW3Lr6Q0G6b64DLCa0713kfBWb2DPADoBOwB7gJeIlazvVwQPBBQhkxxcBlzrnVsZi3NC4zG0qo+KiX8Gedc+7W2M5KpHYN+dyK1Ryl9TnS56SuzaU5ivb13VERfBIRERERERERkdg4GpbdiYiIiIiIiIhIjCj4JCIiIiIiIiIiUaPgk4iIiIiIiIiIRI2CTyIiIiIiIiIiEjUKPomIiIiIiIiISNQo+CQiIiIiIiIiIlGj4JOIiIiIiIiIiESNgk8iElVm9jMz221mWVW+TmrE8f+fmZ1a41igxvNdV88Yb5vZmTWO/drM/tZY8xQRERFpSroGE5HmxJxzsZ6DiLRiZvYgsM4590iUxs8CRjjnAlWOFTrnUhowxhzgO865y6ocWwX83jm3olEnLCIiItIEdA0mIs2JMp9EJNqGAlnRGNjMBgFbql70RNBnppl9EP5r3ENm5gVeAH5kZgnhNscCPYD3ojBtERERkaagazARaTYUfBKRaBsCPFYl/XoOgJkd0whjnwW8WsvxNjVSvi8MP+cg4ELgVOfcMCAAzHDOHQA+CI8HcBHwnFNqqIiIiLRcugYTkWYjLtYTEJHWy8x6Afucc0Nrefhe4NIa7a2BFxtnApfVcrwkfGFT02nACOBDMwNoA+wNP/YMoQuexeF/ZzdgHiIiIiLNhq7BRKS5UfBJRKLpJGBTzYNmNhE4wcx+BzwJ/IvQX8+CwG1mNh/4HeADbgHaAh7n3K+qjNEWSHPOfdmA+RjwhHPu+loeWwzca2bDgbbOuTUNGFdERESkOdE1mIg0K1p2JyLRNBT4tJbj+4GnnHN/AYYR+otXNrAq/HiKc64YmEPoL2N5QPsaY4wH3m7gfN4EpplZFwAz62BmfQCcc4Xh8R4Nz0dERESkpdI1mIg0K8p8EpFoOgn4vplVrON3wFhCF0QfhY8NI/QXr58Ay82sXbgdQAbwC+dcWS1jn0WoSGVt2oR3YKnwqnPuOufcRjP7I/CamXkI/VXvF8Dn4XbPEPoL4EUNfJ0iIiIizYmuwUSkWTHVchORpmZm5wJTgXnAb4GfEqobcALgBw455+aZ2Y+Bi4GdwFvOuVerjLEWGO2c8zX1/EVERERaIl2DiUisKPgkIiIiIiIiIiJRo5pPIiIiIiIiIiISNQo+iYiIiIiIiIhI1Cj4JCIiIiIiIiIiUaPgk4iIiIiIiIiIRI2CTyIiIiIiIiIiEjUKPomIiIiIiIiISNQo+CQiIiIiIiIiIlGj4JOIiIiIiIiIiESNgk8iIiIiIiIiIhI1/x+TvI8IOIuNSQAAAABJRU5ErkJggg==\n", 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