{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Customizing Ticks" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Matplotlib's default tick locators and formatters are designed to be generally sufficient in many common situations, but are in no way optimal for every plot. This chapter will give several examples of adjusting the tick locations and formatting for the particular plot type you're interested in.\n", "\n", "Before we go into examples, however, let's talk a bit more about the object hierarchy of Matplotlib plots.\n", "Matplotlib aims to have a Python object representing everything that appears on the plot: for example, recall that the `Figure` is the bounding box within which plot elements appear.\n", "Each Matplotlib object can also act as a container of subobjects: for example, each `Figure` can contain one or more `Axes` objects, each of which in turn contains other objects representing plot contents.\n", "\n", "The tickmarks are no exception. Each axes has attributes `xaxis` and `yaxis`, which in turn have attributes that contain all the properties of the lines, ticks, and labels that make up the axes." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Major and Minor Ticks\n", "\n", "Within each axes, there is the concept of a *major* tickmark, and a *minor* tickmark. As the names imply, major ticks are usually bigger or more pronounced, while minor ticks are usually smaller. By default, Matplotlib rarely makes use of minor ticks, but one place you can see them is within logarithmic plots (see the following figure):" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "plt.style.use('classic')\n", "import numpy as np\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = plt.axes(xscale='log', yscale='log')\n", "ax.set(xlim=(1, 1E3), ylim=(1, 1E3))\n", "ax.grid(True);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this chart each major tick shows a large tickmark, label, and gridline, while each minor tick shows a smaller tickmark with no label or gridline.\n", "\n", "These tick properties—locations and labels, that is—can be customized by setting the `formatter` and `locator` objects of each axis. Let's examine these for the x-axis of the just-shown plot:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n" ] } ], "source": [ "print(ax.xaxis.get_major_locator())\n", "print(ax.xaxis.get_minor_locator())" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n" ] } ], "source": [ "print(ax.xaxis.get_major_formatter())\n", "print(ax.xaxis.get_minor_formatter())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that both major and minor tick labels have their locations specified by a `LogLocator` (which makes sense for a logarithmic plot). Minor ticks, though, have their labels formatted by a `NullFormatter`: this says that no labels will be shown.\n", "\n", "We'll now look at a few examples of setting these locators and formatters for various plots." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Hiding Ticks or Labels\n", "\n", "Perhaps the most common tick/label formatting operation is the act of hiding ticks or labels.\n", "This can be done using `plt.NullLocator` and `plt.NullFormatter`, as shown here (see the following figure):" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = plt.axes()\n", "rng = np.random.default_rng(1701)\n", "ax.plot(rng.random(50))\n", "ax.grid()\n", "\n", "ax.yaxis.set_major_locator(plt.NullLocator())\n", "ax.xaxis.set_major_formatter(plt.NullFormatter())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We've removed the labels (but kept the ticks/gridlines) from the x-axis, and removed the ticks (and thus the labels and gridlines as well) from the y-axis.\n", "Having no ticks at all can be useful in many situations—for example, when you want to show a grid of images.\n", "For instance, consider the following figure, which includes images of different faces, an example often used in supervised machine learning problems (see, for example, [In-Depth: Support Vector Machines](05.07-Support-Vector-Machines.ipynb)):" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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WqAw0gYFmHpENPC0GBKcxOzurUqmkQqEg6YaDcueGrJRKpSiIRS5Go1Hc9+LiQqenp4HwGQdhq2d5QYugAKgBN0bIKbKOk0PunBzHMPBM5AKEypXklTCM6I6T5p6UQVcxTEkkypwl7+O8GI4K+gC6YG5uLu7N3CKfyH+r1VIqldLh4eEUr8Y7faPN+cbf/lvhwysRN8/NzalSqSiXy4UBOj8/1/z8vM7OzkLQe72e0ul0GAtPF7oXQrF8EfDkhGTwDRgZkND8/HxM1MzMjJaWloIATqfTEfeCFpaWlkJgeSdQCCHXzMyM8vl8cAcQp7VaTcfHx5GJI7RC+SaTiXZ2drS0tKRer6dSqaSNjQ2Vy+XgBDyMGAwGOj09Da8FCpufnw+l8bkoFArK5XJTxjKTyUQ4lEylS9LOzk4YcAQ6n8/HlpPz83Nls9nwpnBV9Xo9QlVqThgPSAWezMlhDCOhC+EtxsIzYv1+f8ppQWQjG+l0OhIMHnYVi0VtbW1JujaeLp9O/ksKBEQZQa/X0+np6RTKGA6H8bOlpSWtrKxMcZQoEchoMBio2WwGL9dutzUYDILrceIbGSgUCsFhgdqYG5Q2Gdowr6AP52lBMoRZbDkaj8c6PT2NkBUDl81mQ3ZwyMw1DoGx8O6gu3q9HtFIu93W4eGhTk5OpjK6KysrqlarqlarKhaL4aiHw2FQJejg72yUgKkMlJhxZWVFmUxG9Xo9/hweHurFixdaWlrS8fGxhsOhisWiisWitre3tb6+rlKpFPdIZiAYMALuGZlGo6GTkxO1223NzMyo3+9rf38/FiGfz2tzc1Pvv/++tra2tLy8rMXFRfV6val0c6FQiOptJgolQGkojW80Gjo+Ptbbt291eHiojz/+WPv7+3rvvfdUq9U0Pz+vjY0Nvffee3r58qWazaZGo1GQnPV6XblcTu+//75yuZw6nY7Ozs7CgMJ7kNKXpHa7raOjI33yySc6OzsLFHV1daWPPvpIS0tLWl9f1507dzQ3N6fT01M1m031er2vFKBKCvISw4vRg0uq1WrhSHZ3d3V8fKzZ2VkdHBxoPB5rZWVF6XRarVZL9+7d0/LycmTA2I9FqAvSZW+jO57RaBR7u0qlkq6urnRycqLNzU39n//n/6mFhQWVy2U9fPhQc3Nz2traivs78phMJlpaWtKjR48kKYooQQQ4iH6/H46k2+0qk8lof38/jCqGn9B3bm5OzWZT9Xpdd+/enUIgHhZfXFxocXFR4/FYjUZD+/v76nQ6YdCq1apyuZx+9atfqdvtanZ2Vv/T//Q/6dGjR/rggw/0k5/8RNvb21paWgpEBnpEwT3pgwGSbgpe0ZNGo6F6va7d3V0dHR3pl7/8pf7xP/7H+p//5/9Z9Xpdjx490v3793V0dKTT09Nw7hgnny9CLeeeCNe73a5qtZrq9brOz8/15Zdf6tWrV2GkyuWyCoWCdnZ29Itf/EL379/X+++/r0wmo2azqdPT0691mr+VUSqXy2FJgaEQV2/evIlNoGdnZ3ry5IlarZZ+8IMfRCz5wQcfqNFo6M2bNzo/P9eHH34YPMNt2zqkG6IZLqDdbmtvb0+DwUCrq6u6d++eGo2GBoOBKpWK/vf//X/X/Py8Dg8Plc/n9fTpU33wwQe6e/du1J14yrtUKoV3Qujn5uaC2J1MJvr000/1+eef6/Hjx5qdndWPfvQjNRoNTSYT/eIXv4itKQ8ePND777+vpaUlffLJJ1Op+kKhoFqtpkajEc9GMDzcJIw4Pj4OhcMTpVIp/V//1/+lR48eaX19XRsbG/on/+SfKJ/P6+/8nb+j0Wikk5OTEOKkt724uFChUJjaapJOp1Wr1fT8+XN1u109ePBAuVxOb9680enpqQ4PD7W6uqqlpSV99NFHurq60u7urvb29pTJZFQul4OvkRRoC9QG78Ac93o9vX79WnNzc7p7964ePnyoRqOhvb09NRoNPX/+XH/9r/91FYtFbW5u6rPPPtPJyYk++OCDqY2o8GZzc3NaXl4O5fR3Pjs7i7nc29vTaDTSj3/8Y21ubmoymejjjz/W3/pbf0vtdlunp6e6d+9e8JYLCwvBhbgSgcYItzqdToSk/X5fm5ubGo1GevjwoYrFovL5vPb394PUPz4+1s7Ojl6+fKler6d79+7pgw8+0MbGRiCS8/PzCOt4HxAlOuJZ08PDQx0fH+vs7CwM109+8hP9j//j/6h8Pq+1tTV9+OGH+r3f+z1VKhW9ePEi0GGhUND29naEyGQXqdnq9/uRQV5YWND6+rqePn2qmZkZ/fSnP9VwOFS73db3vvc9/Xf/3X+n/+K/+C+0urqqP/qjP9Ivf/lL/bN/9s/U7/e1vb2to6OjqSgBKuN3Mkr5fD6U1gm4V69e6fHjx0qn0/rpT3+qarWqfD6vn//85/rss8+0srKicrmsjY0N5XI5vXr1SsPhUM1mU4VCQWdnZ1pcXAziFDQG6Ug4AXxEocrlchDMCwsLOjg4UKVS0d/8m39To9FIGxsb+tWvfqUnT55EzQdCjeErlUpaXV0NowRMJiR6+vSpnj59qslkog8//FD9fl8rKyv6T//T/1T/+B//Y/3hH/6hLi8vtbOzo7t370ZKe319PUolqtWqVlZW1Gq1tL+/L+mGhwHi5/P5QHgnJyd68eKFfvrTn2p9fV3lcllv3rxRs9nU5uam/spf+St6+PChVlZW9B/+h/+hfv3rX+vly5daW1sLMhwBlm5CAecTMLrn5+fa399Xv99XoVAIdDkcDvVv/s2/CUi/sbER77e6uqrj42NdXFwEF4Ux8kQBCAVkMRqN1Ov1tLm5qdXV1fDUc3Nz+vDDD3V0dKQPP/xQf+Nv/I0w5J1ORwcHB6rVarp3757y+XygMN7FeRjn6Eg87O/v6/z8XD/4wQ/0wQcfKJ/P6+DgQB988IE+++wzLS0taXt7Ww8fPtTl5WUoHWuErIAuu91uPAtjREjtSZxU6nqv10cffRQc4R/8wR/oj/7oj7SwsKCjoyO9evUqlPr999+PENar/yVNhaEYyU6no1arpX6/r2KxGB0gTk5O9PLlyzBg29vbeu+99yLpVK1Wp4h9gAVhOAiMRAEoaTgchpH77LPP9ODBA925c0fPnz/Xmzdv9L3vfU9/7a/9NVUqFc3Pz6tarWpzc1PPnz9XuVz+CkfMn9/JKJHpwTDNzs4G5C+VSsEd7Ozs6G//7b8dUJEwA5SytrYWLRqazeYURwAsBTmkUil1u92pjBshT7/fD8j40Ucf6eXLl5KuCV1+X6lUlM1mVavVVKlUomiNoi5alDBZZBnOz8+jRUYulwuEgeft9Xr62c9+FuElcXO/34+apZmZmZiXXq8X9+52u/F7iEiK93K5nFZXV7WwsKBnz54pk8no7t27kW5dX1/Xf/Kf/CfKZrM6ODhQNpvV/fv3p6quPVkwtcC2FQVhlBRdESRFSPKTn/xEFxcXOjg40OzsrFZXV5XNZtXpdNTtdoPkBemiTF7iAc/haAOHU6vVNDc3p/Pzc1UqFf3+7/++Xr9+rZWVFW1sbGh2dlb1el3FYjHIZGpokoWtni3DOGEkstmsut2uvve972l1dTUQ571792KelpeXlcvlgo8BCS0vL0eoi6GFa8TQ4njgWFHkWq0WfNHW1pay2aw+/vjjQJ0zMzNaW1uL0P3169fK5XKqVqthbDGsGAb4ObKtg8FAS0tLYdhzuZyWlpb0ve99L+6D4xiNRlGvBG+bz+eVTqeDSoCkx/jCbaLDjOPOnTs6ODiI97lz54729vb0H//H/7HW19e1srKivb09dTodra2tTdUJIpP/zsI3BB2mnixPNpvV+vq6Li4utLe3F8Kyvr6u1dXVMARYylKpFFmeTqejQqEwRYp6HQ3tRKgD4vsQ6Z7pWllZ0fz8vE5OTlQoFELJQQRXV1cqFotBWrLLGk4CdAFh2Ov1VCgUAolRrAfhWigUtLS0pKurq+Byzs/PpzZUgh7gj7xAzssHqKfJZrMqFAq6c+eOTk5OdHR0pNnZWa2vr4dhPDg4iHII0rfr6+tTtS5ft/+NjJzXY1F0CNcCWU51PtkU+KZisahCoaB2u61arRZhKsoKsuA53O/i4kJLS0sql8uBtFqtltLp60r8YrGoubk5tVqtkK1UKqVcLjdVyIfseU2SpClPjJLmcjltbGyEp2+322E4Hz58GJliHIRnLUFKoHZ+jiGhLAHUwdzjIEhekKV+9OjRVH0UfBzRwMnJiRYXF7W0tBRzx3t7lwBkaG1tbWqevdB3c3Mz5pDiRsbs9XIzMzNRZAkiSm7EpgynUCiEDm1sbOjLL7/U8fGxFhYW9P7778cav3nzJpz+3NycyuWySqWScrncX3r/2zuVBPDiKO5gMFA+n49UNd7m8vIywiIMgF9MivMryZQ88TupSchcYl94KD5HJm1ubk7FYjEW28sTMHiUD4zHY62vr0vSVKyOgFMv4xWq1BHBOWEYyEpQl8W7kb4m05iscSLdCuGaTqdVrVZ1eHgYpDcecWVlRQsLC+r1epFaXlhYCMWCI8MTeczOWDG8IFCyQEtLS1peXo7yAjKmGH68dD6fVy6Xi8LTxcXF4PxYx8XFxanwg0LayWSitbU1lUol1Wq1KAD0eqd0Oq1yuRylDmSNvE2Hlzt4oal0sy1lYWFBuVxOm5ubsQaURPC+oC4vMERO+Cx8DoabxAzGZnV1NbJ5oA3fRgLqqVQqIbfMp5dNIBu8n19kJT0UhxxPhkJOgGcymdAFyHnkA+7UM53IDWNHF9jrCSoul8tRMZ/JXO9YWF5eVj6fD4dLgSi2wbfMAAy+1eZ86weyN/1ZLi4uop4D604tyNnZWVQgg1Cw+g73KX7DwyNQKLUrAoZFuqmaRfAZmwsipDbGh4VO1ndQyStNQ0o8JGiCEgQXABYAxIWnQGDxXvATvq0Awg/UBPeCAcDA4tXJlOXz+ejUwGZNvN9kMtEPfvAD/eIXv5jKMiYvfoY3A9mRicnlcmq1WvFOrCP8TSZzXU3shtXrZ7zOyXeOp9Np9Xo9NZvNyEqCorj34uJiEMRU7LMGoCPWEgPIujl6ImuKfPJeOAbkgF0FXhSJsntJgmeHCVMx7pTFLC0taTQaxRYV3wyMk6IkhfkiLAMJsdbJdcMIe4EknCuOz+vqkGHqvIbDYRDXvCcJKwwQJDfP4F4YM99mRtRAiMlaY+wwvmR80+l0oHnm+F2ud9pmAjz38nrnD3gJJskREUYluZmSvxGw8fh6tzP3BanAE8zPz0/tvwORSDdpWxCG11g4d+UeDIMo3VhxFhgDydgwyiwmRoP4nfFgmPDQFALyWVeCZDqW+6+urqpWqwVSlPSVIkkXHFCfv6fDZK+6dqHH8GOcWB/m0St7qWdKKqcbCUcWPt84It6BMbHNAq4LRMS6M+9OIGMgeLZ0XTWNASP0RN4wTDyPOfBtN55lw0hSYe6o2MNVxgRHgyMi9PPQl2d6BbzLB3PHu/Ge0k0vM+aFBANyxRw6/+U1YhcXF5qbm1M+n4/3J2xGvjEWnhVDlnDKFM2SiUOnQepkDtFvnDbJnIWFhQAqSTR42/XOW3cxAr5Q4/F4iuS9zWg5Ucei4xkQCiYLL0yVM8WTcDZ4GhbWK1SBlM4DMMG+2B6z8178zrkt7u8KgDBD4ko3oR7j8LQ784XCIqDSdBtXwsDxeByVzowLTwz6QKCB/8PhMIhWHIRfX0eAU/HLdzE+GFmEDOHl/T3TxlzjnCg7gJTlby+FkG7CEg/d8OzwD8l18jCUtZKkjY2NkAdqqkA8vovADQvvwhp41szJZeTRiyjhAX2NkRmMNuvNuiYdIfLJd7w6OrlGPgY+73VbXkkNh8vnkU1kkLWELiBM417OKfE9nCe8WaFQUKVSCTqFZAnfI0yF20LnyV6+y/VO/ZS8mMsRii8Q//csAjUlTlK6MfH7Og8DwsLI+JYON2I+AT4GxukCxSIj2C4AblDdOCJI3MsvJw/hJID8LnT+fzd+Ht7wLpJitzoGGA7Dx+9cXDab1dHRUczxu6ylv4unoZPz5mvtISwCirIn54334TMYCXdUXKy7Oxzu6aEbP2f98dbVajUM6tLSUsgU42Yc/MydEGvMOmNQvLsDjky66f/tnRf8PTCuzCEox/eZOUpmLR2luL6B4rgv64NR8vl0OcWJe5TDmjIO5BB99f+7k726ugoECHKj8JOowA2a81/MuxP373K9k1HyB2EIfBIdrjORDg09fnUFTxJ8rmg8gxjf24owFr7rHpw/SaVikjFAPgY3DvzbUQ+fAxY7VJZueDdfGDwEP/NNocT8zskQQoAMfXc5CIo5cjRBGp1xJdfEFYu5Zf5AODzbw0sMhaNO5jy5+ZnLSWf31mSAEF4nw/k3z3anw3tg8Bijo45utxtyRrM4HJsrGM91YhgEirLBk1IGw0XY5QaVGqJkbRFjZHe+18fxfv7/JGHt94G35PMkVCRN6ZU7WDhVn1sMUzJCkBQUArLiuuB6DGcEJ+YRgGd9k8bJHVwSCX7d9U5GiQuLzGAZUBJS81kPgzyuBwG490tafiYIBOLhoxtJj4N5phsknwiH5VxJ651Mq/u7cX/CGw9NPbvgYSSxPfu3eCcyUz4veHwn7B3ZMVbmnzF92x4q5imZVkfxnaAmnPNEgaedCR94V0dujIs5kKYb57uRcDnwTbeEUh4+uyNz4llSVJlfXV1FzY4rBMroSsRauZEtlUpaWVmJEgz4Ql9n+ETIX/rW8x7+XObD14DPcblBShoX6ebQB8JdxkuE4s/2+fU597A5ieB7vV4UULqewvnyM6dtcMDMEZ/38h7XLwcF73p9q1FygXIuyEMRXj7pUd0wkdFgIlAKsnRkqvxlULzR6LpPePJ5ICiewfOTcb7D46RgOOFOFgIimxDBDTPGJmns+BxCxtYFdvwjtMwDRgbSEiH2nycVAsjMezDXnU5nCkXedmFMeBZrA5fjISyf97V2pOOIx9eeMYMeHEkm1yWpuDgT79/DhbFinPAi0nXBIp9hu0fSaYEyeI4bJRSvWCyqUqmEsWO9uAcOgPF54WEyLPTw3I2tO3PW0An4JOfCd0DT7lwmk0mgaMbnPJojI5dP/u71erHR1ntlQbfwBzLdkTdcIe/oiQOQJwbT5/DrnGbyeqcjlniww0dewuNF93TuMfH+kqKoi5+7kDJ5yRDQM1rUSXksjeXmuc6DMA6/JzwQn/FUuocyCIzzYAhHMuRknAjLZHKd6icL4WlTV3IyGLwj8+nZRg9DEUDe6+zsTM1m8ytCjXEpFosROrrh5l3cQHso7GuCwXBjwfNcIZOFoqTemV9fFzeKvJ+HXR5yYJCYRw8FvN2vp/kx6L52Lqtzc3NRjApB78jaDTR/U/rB2rDvjHUlPGM8KC33SHJILttJeWWOXeaQKxyZ0xA+rx4eoieO1Ngf6G2I3IAx54yBBAR6x5FJnrVzOXCjS0TgzuLbrncySvztWRRCLve8DkeZbBfmbrcbFcIu7NlsNvY3MRFMhqRoI8Lk+aQlhckXHc/qk4ugg4IQGMbPmF3Ak/yHE5C8PzwQiwesdaWijoYFI0aHUMRAMhaqYekN7kIID0AzOIfpfu3u7qpSqcR7c2/G6UbYjYWTnoTQ1BF5uxDnbNxw8v7MP5t3MdI+nyAQX388rKMPz+6yBQKjRE2OE8Ieyvv+SozA5eWlms2mZmdnY2/Y/Px8bD9hTQjD+SNdOw36Mvl2H9AiKCyJBt3QMT/MA06DtUWpMepeSCndOEvmz8tYHOkyd5Sf9Hq94OJANF4Owji4P1uyeHd+D8pCLh2keAdMCmi9+v6brnfOvrml8zDBEQOeAkPjMTy8ymQyiY24/hkUP5mVwPgxKY5qgNiuDFwsPt7ax8cY/R1AgwgJENU5Fxbax+gCREgB4eqZH0nRDoKFOT09DSRDSQMKxYZljJrzMRi92dlZvX79OjZZ+mIzF//0n/5T/Wf/2X+mQqGgfr+vpaWlKeeS9MY+B45gKNSkzYp7a+d4MAQeIvX7fW1sbITxRw7g0LiPyxNzxNxi2NPptN68eaMvvvhCkqK5Gt0JvAeV84E4KtCgI9pms6nd3d0gcHd3d2NcXDhFkhQYEirTHeU5MZ5E7txLmjYyTnn4GvIMxuxlF+5gvEwBp+HV2hDv7NvD0WGIJUWyoNvthgECyQMM4Np4Bj/nd8wPoKTRaAQH5/r2Tdc7h28QoUyE78mRbk4CcQPhoQbGwBurexzqrVYdccFR4EG8JsPj5iQB7ugHQbhNUG6L5TFSCLYjJTfQbkgpLkTw+T6bjD3rkkqlomGbh3i5XC729kHcsoESL+MhVSqV0hdffDFFLCYXvdVqqdFoqFqtTr1v0ii74iNgSXKY8+4x1N6BEGH0jBLfZcsCHpc5wwgmkUKSZ3LHl06n9atf/UrPnj2LdeWznU4nFIa9ZKwXDoK5w4ngzT/55BNJN9taqPGhKVy73VY+n9f6+nqgNOTWL3eo6A8IHNl0/s/JfL6fDNUdTbm+kYFjPTwcdlQGAgJ1DofD2E5EN83Z2dmoOaR54WQyCSS4vr6uYrGodDqter0e3UjZLO9rT+ZZuuH8GCdz8E3XOxklD2UQFKw2QuFw3rND/I4BF4vF2KmOYEs3cT4npDgUBz5zb4QX6O5endDLDYmPL+mRbuOhmETeme84SY6wDwbXXTbxDBDkdAWgJ/jR0ZEajcbU7u6dnZ2pUHI8Hmtvb2+KkyKspUbGw7DT01M9ffo0xpZcN0lxAEEyde1hkxt3L3Z0g857ogAuZPztaX0MN6l2eAWQFx43yTMlM6bu2FKpVHQ+5HLjivHgMAF3iMmi1slkEpXG3W5Xb9++jdNdPvjgAy0vL2s4vG61AyLe39+PVjLZ7HW3TpxOUp5cjtyBelTgTszfkYv19vAVx5zkND1s4x7OcbregH44My+bzarZbOrly5ch677FiHY0o9FIBwcHOjg40OrqqiaTyVTTQpdP6RqdHR0dha141+udtpkglEy6pCkI6cjE/3aDxeSUSiVls9noMVStVlUul3V+fh6p7YuLi9iBv7GxoYWFBbVaLU0mk6/dTe1CwGL5GDwMG4/HYRiB2oybyfWUsb8PRod34v70m6K9x97envb29tTr9UIAuMdodN0Xh24Go9F1S+DPP/9cR0dHsQGX93GkhGDPzMzoyZMnajabgZoc8fHvy8vLOBvNM3a+ZcKRlVdYO8pgjlAyFJH5xtDgYbk3SQ7n2hivVwN7tTNOzI0oCkfzNHd4fG84HOr4+DhalPAH+XBCezKZaHV1VZubmxoMBtrZ2VGr1dIvf/lLXVxc6MMPP1SpVNLm5uZUl8bDw0M1Gg2Nx+NoCe0brr/pb59Hxu5hZdIwJeXX54J5T/JVHrZKN+Q/Gd3Z2dnob/7ixQsNh0PVajWdnp5qYWFBpVJJ6fR1/yhOIc5krvc97u3t6fDwcCpUJ6R1588cn5+f6+DgQH/Z61uN0uvXr3Xv3r1bEQmTxcBdyH1PEcLb6XTU6/W0tLSker2upaWlODyPDFS/31er1VKz2YxK5XK5rG63q2KxOJUp8IX1DAbjQpD9/450fPy+6E56IzBOJsJTSTcVw94aIp1OK5fLxako2Ww2jCCfpddzr9dTo9HQixcvpjo+Li8vhwHnWe790+m0/vzP/1xXV1dRm3MbgTgYDLS/vx+/h4D1sMjnwrew+HzhnECoLoi8L8jDw0uMPXxGkhh3x8LP3Xj6eg2Hw+hA6mjAnSEtiUEHoGDWhT+sW6VSCSQEaiLcWVlZiXQ4BiKfzweCL5fLUxwdsp/MUHtI50Yoid49XHM5hAO9DUV62MZnkvwc7+qIbm1tLTbrDgbXTfwwWul0OpoPotc03kun09HAkH11PNMpm5mZmaAO/rLXtxqlf/7P/7n+/t//+1PCkiQjWQyPWd2LMpmlUimEisPvLi8v1Wg0ov1Gr9eLGhD6XAMlPXuFELqXYQHcart3AW28fv06iFIfq4cCfD+TudlPlHzf0WgUdSuEQSgeu9/xUhgBn7urqyu1Wi0dHByoXq8rm82qXC5reXlZy8vLcVhgv98PEpJ7nJ2dBa8iTXMRfo3HYx0dHandbsfGSl+v25yNZ+RQEuaOTqQYGgwYHtbvBSrk5+yudwXF+HumzutceLfR6PoUkpOTkymk4KiA9YQTgcfz8Ee6Saawh5GNpOydg9hl3J7AAOERlhK6MCZ0wPegMd9uPD00dkOTdOa+Do5qk2E0Rte5UOYWGXVHnc1e9/BCbhkrqDKTycQ+QMI33hmH6Rt9vXgUPTw8PJwqGnYk/03XtxqlL7/8Up1OR8Vi8dab3hYrJtETA55Mro8HYu8MMJCXoV0GyImL/WAohAuiL7LzEsnfM6bBYKDHjx/r17/+9dTv+VvSVwSIndBeYpAkTnlvF8a5ublo/zCZXGcdk5kSwr6NjQ2lUimtrq7Ge7qRcZ5uZmYmDirwDJiHyx7OXl1d6fj4OE4Auc0gOfHq5QGuCBcXF9H2FEOZzWbDWGA4PVzH0HFkk79TUjEdCbj3xahwQEVSxrjI5hF2eI0Yf3zjrx8smslkIqyB94MMd2PLnIB4fb4dWfsYHZF6Zs4/44jc19ydLPfA8fv9+be3NUmWQPB9HAy9vDBM8Lou37xXLpcLGeYUI+YNmSaSYF0ODg5ufYdvu77VKF1dXenjjz/WnTt3phaAheHCQvu+LPe4/B9i1y2z91tmVzwpS5Tb99tg6REuJodJ98lyPmg0GqnVaunt27fh/Xz80s1OeIwRi++GzzmE8Xgcp444EcnC0i7VF8b3Jg0GNwcHAp25B0JBoZ8L1pMnT3R6ehrz4h72tjVsNptTZDf8Q5KfA9lI0xuwQWeNRiM6b5bLZT148ECpVCoUnO+22231er1Yv1qtprW1tanwGiPiz0cJWFdHHkdHR9EOxJ0OY/Uw0RMRyB7/dtJYUhjXVOq6NgyZIToALfMu4/E4UARKyPoyfuSBZyUJfebKSfAkovMzAT3t7qiMe3qhbTKZA4LHUTD/HDI6Ho/DON0WTqNvdPWUNHXsFTKKbDHfdKT1sbzL9U5N3l6/fj110KCTiy5g0vRJoFj0JOnN/xE2j7WZOD4PqZr07Em46WEC/8dQAuWZKIoNpZtD/JwLcLIQXgXBdIEDBfLuHl4xbhacuSDr5DvgZ2ZmogGaZ66Y3yQavbi4iFKA2zaEMs9cGCXG4fPna+gcRxKlpdNprays6OjoKM7zIuQsFotRE9Pv99XpdNRut4MQpvjS0XYqlYp0soeNjlhnZmaihXKv19PBwcHUPi//m/UaDq/b33qPcFdIL0idTL66j4/yDTcacIDeL4jvcB8vmOX3yMxtiMkdAz+jmBV5cp6I0Je/3bn4nHmFO4bY55UssaN5Qlj0wWkIdJNSHhovJika58qYl729vXjXr3OYt13vVDzZaDTUbDZjQbGcbqmT4UOyNB0hc4PmXgRFdEsPoepeD7bfMxp4LCcGmQwWdzS67rm0t7cXXTARBu6DsvozHV6zAIRMPIf38n8nOTY3zoRzCPzMzMxUK1XKIUBMeEyMYK1W09u3byVNOwE3LFwIe7vd/totOiiV80Eu9PweXhBUACc2Go0i7d9qtaKfOaHDzMx1w3y6hnqYkjSA/kzei8rr4+PjKaeDrPE95AoDjPLg5GZmZqbCSwwc5Q7O/zE2EIobJi+H4B6O7BgHiJnPYkDcsSadiRPdjuiIMKgHQwaT8+e/S2bMvdU0KAe5R69ZaxApnBSdE9whU23Oe3iYyDFUSTLf+b+vu96pTuns7ExHR0fa2tqKieAFEDBXXvdmt33ODRYCcdvLsXEVhIFyepzKM9zb8XyEF4/J4YEYIoTHjat7YIQ6+Q5uPDFE0s1WCn7u8bajJTowQkA6h+ZGDaVEWbjvq1evYv8g120Czs+Hw6EODg50enqq9fX1KWObXOt0+qZ2yRGwe3DGTt9waqHOz8+j1of2sBim5O591jeZxWO9HKkOBgMdHByo3W7fKqP+Lul0Wo1GIw6AQL6YV5DCYDCIIlWypDMzM6rX65qdnY0ThHEOhPu8j3NfbshdN7xkxiMELhyxGyK/GCtz4JXRjnacj8P5IXvOF/Jd5/r4P3vhGAeO0x0LKJAQ1lGaZ4il6+4NyYMVkmv1ddc7dQk4OzvTwcGBfvjDH04hkNseQIzMYAj5nJxDcKnPgS8BHoMgvBYGUpz7cHms6mEjwo1hSdaYOKJwD+aFadzfQ1OvXMZAOZyljoktDwi8e1QE3Gt3rq6uQpH9vSeTyVRb1YuLC3355ZchWI5ofE38/SAdd3d39fDhwymBwsCybsn19T88w6E6lc8INVlSSOAkqe6K6r9LIh7ppliVg0+TB1F801Wv11WpVKY4FEIUDro4OTlRq9WK/ZiEM9lsNg4b9S1RR0dHqlQqkX3i3ZMon7miiT7OEaPvn/GIgbngIrwlmvDMLsgVWfEwyakFBwJOkruzoZLbi5Wl6VCQMeJIGLsbY4wgnOfFxUUQ5O+CkLjeCSldXFxod3dXvV4vTib1hXAFwNO6sGPBHU5jPX0joZOqCC9W2sljhMx5CSY/idgweB66gTyS74nR4d6+NcB3+EOkMje1Wk3tdjvCW05fhfxlQegnDYnPHwQhl8vFGVr83EOMVCqlVqulZ8+eTYUjt5Uz+HpI1wL+/Plz/cEf/EEcr3Qbqe3hswsc9/fwBidDAWGhUAgPy30Zv5cXMN++Xv5/D3MHg0EcCe9rlQyf/JqdnVWr1Zo6Dtu/A0e1t7cXx0XBe2Gc9/f3dXJyEutAx8VcLqdisai1tTVtbGxoeXk59gVivJycxlA4YmI8Hgohs46mHPV7Rb8bHA/tPSQGVU0mk0jp+7FXyCfUBqjIeeOZmRmVy+WpbB41dBQxOyeJYT8/P9eTJ0+m1uS2dfq66516dA+HQ719+zYyKBcXFyqVSlN1Ek62YWiAvvyfvUkcjexcBcrOAlIUiOFyo+TeBCPnZ9azMO4xms3m1BYOLjJjXu2L1WfSycK5oQVO7+7u6ssvvwzhxqOxrQLEyK5yNjwyBno45fN5zc3NaXd3V3fv3tX6+rqWl5enKp0phKzValO1KEnH4JcbmIODA7VaLVUqlVAWz2gmQ1SQK8rkxhiugz8+h44kWSM3sB6qe2jjfAuO6vLyUi9evFC73Z5CFtzbCXIPqer1emzTcd4EUnd2djaMM0kGKuxBrsgPCI/q+OPjY718+VLlcllra2tRc1epVII7A/En63d8XZxngftDJ/j5+fl5HHoKr4NzZ//ocDjd/wvEColdr9cjwcMRVt1uN+YKuQcFASD4Oaf/8J6lUkmPHj1SpVKZcojobr1e1+vXr+NeXv7z74RTkm7i9FevXum9995TqVSa2hmNMCMYl5eX6nQ6Ub5OFqXVasVJtPT+JWb2mgqENJ1OxySUSqWogmYiPJxyj+PpX68Sh5PgmZJiIy3ICAOI8WMS+b8vPAu3s7OjarU6tcWCsYDIFhcXo3ULpKrvkQMVHB4eRnUxZ7vxTv1+X19++aXa7XYYDt/QKn01pEahmAv26Tly8NCPe2IgmGcEfTKZTDWuu7y8jDX20g3e29fXU+AYKX7uVdqOqo6OjvT06dOp8g6/HO25vHa7XR0eHsYJJ4RBw+Ew2t5STMq/k8aE73kDQtCvN98n28d6M6bbuCauZLiFk0OWJcUOfmSbsInowB2Oz4MjTpIEAAJJcfoz6I+C3fF4rFarpU6nE04VWeTQVaq0z8/Pp5wnYxiNRnr+/Lk6nc5UpOHO9duud+KUMpnrLSKffvqp/upf/atTGx49DT83d33yZ6fT0f7+vo6OjqYakNFbBQSF8OPBgMGeVUAwqtVqnJKbz+dVLpdj24mTi3zfU5vdbneqHYM0TfqRRcAzeJN7lIi58FokKrDL5XIYUt6NqmIujF0+n5+ah3w+H4KH0rEHCe+MkB4fH+uzzz6bOqfLDcltl6MgKsy9psnX0LNKzJ10bVBBjBhe5sQNDff2+/n2BkIALtbKeSWQLwb0iy++UL1e/wpCShqn5O9nZmb09u3bqZNyPTSiHQt7Ej2TSzU+BL07Bt6FkM6LaKlLI/R0NOvz6llifobD85CTe2CccCyeJfZMsIeGnrW7c+eOVlZWwhl6yQOOn4LIubm5OGka+aXeTLrp6U1Yvb6+PoX62MMJIkW3b+M6v+565yOWMpmMPvnkE33xxRfa3t6eOqwP4+FE3/z8vLa3t1WtVnV2djZ1yKBvAcASe1bEiTgmZTS63mawtLQUZ6bjxTx+ZxJ4FifCErYluQzOxiJT4JWqXoPhgi8pBNbLE4i5QRP9fn+qDcRkMpnKSI1G18dWJ2uWCOWcM7q4uNDjx4/1+vXrKc/rRKl7Yh8zn+eZnU4n2oi4kuDtzs7O1Ol01Gq11O12o9UMxtazOm5kmHcU1t/VN8KG8GVvehMxFs/MHhwc6PHjx1Moyt8ZufT58PWlkp0qZNabNc7n89GojXYnKC6GCOcJivbdCM4LMneEUc4PJbOOLp9uiFF4srN0DMXAOx3i0QD3ThZykiDCkZMd9cSJO3EyqtRqcX8q3d0hcKglXBfvs7e3p+fPn8fnnFd+1+ud+ylRGvDHf/zH+ulPfxp1NbelHVlQ51+oW4BrYmFYEJ9sjJSn6Gn3gYBhFAkNWGwWbjy+aYzOBLkx8glmgdniMh6PIwb2OfB0qy8+z8O7I6iME2SEcRoOhzFH3B/PxWkahAaM++3bt/o3/+bfBBfgnuebeCXWTlLU2tA7nGpeDBbGnU3CtVpN3W43yNR+vx/hpq+HE/ZuIGdnZ5XL5SL0Zrx+QrKnxR3FnZ+f6/Hjxzo8PPzKuzmpmwyN3AhcXV3p4OBA5XI5DkVkzTGYy8vL8U7ILvSC85fshcNZ8H2QonNxPIf5dCrAwzXG66HbxcVFyCzcK7Lm2cokesex8SznDJF3z2SDhJgr/79zjTgZvosuwvc6GhwMBoFsvQSAOXjX651al7Bgc3Nz+vTTT7W/v6/l5eXwIO618fQoo3QTw8KpwPMQmjinAmIi3ckf9r85ZHaSFqOAgQMRcD8EAA/CxTYHPwAzmVl0rsM9VJJ/4V14vmeauC9cBe8g3XhvNjyymBjny8tL/ct/+S8jo+Hek3lPcklcrqwgnnT6uiEaWyVYZwRSulaCtbU1VatVtdtttdvtgOSUcQyHwwh/QFwcEU0YNz8/r1KppHK5rHT6evd5pVLRyspKODbppsiTNrTtdltPnjy5NVT19/U5lm7qy3CYzWZTh4eHKhaLwRdhcODAnJfMZK6PhXLkxXOSxsBJeuTEQzMPcZEp58sc2YPW0A/pOkKgJYwrv8syYx6Nbg4A4N0x8CAVEjbIPAaM4l1azDBWZBtD5nQKYaxXjEMvgMSYJ09yvMv1TkYJgYBNr9frajQaymazwTfwcH9REICk4Gkg6DwUwJB46OawmBL35FFLTu5i2G4riEvyFu5pC4XC1MZM4CiCzudBYJKi4byjBO7pSsGisXDuhdyzUpOFgYcPgJj88z//c/2rf/WvdHl5Gd6Zd7kNITkidCEGoaRSqciCMg4cAXCdsc7OzqpcLuvo6Ejdbjc4MdYYdMracW+fOzJHeFeEFK6BZzGv5+fnajabX9l8e1v4fduFwcYYHB4eBh9JCAbhT6kHyI1Mk68VY/ZMl/MoGCacDDKMHOBgQPeeZRsOrxv5I7uQ2NK1USJxwPPRNfRoNBqFsfViX9bCS0ZAeR6qO+BIVqsnDRH/dkqATGu/39eTJ0/06tWrKW5Pms40uk35uuudjRIviTW+vLyMLJATnQgMCu6KgdK5AcMguadxbkG62W7ifE+SVCU8QpnJtPli8gzPVFA7hLcEMqNsZBhBBiw6ZQue6ZBu2rx6eOhVucwN3gskxz2YDzxWo9HQP/2n/zQavTPHvI90g+BuWzeeQUN4hG52dla9Xm/K+PN3Op1WpVJRv99XOn3TK4lsKgrN+7nhLRaLwYsgxPPz81pZWVGpVIqQz0Nvwpazs7PgD8/OztRut6coAieM3SghMy57Ps/dblevX7/WwsKCVlZWQskYP+GPI14MEfPrykqRIXPufCjz54roDsmV2Tmk09PTqZOWJU3NsxPxyXfl9/xh9wCGxJ0yOuQEPX+QVRA0Rswz3byvO87xeKzDw0P94he/ULfbnerkkeQRmfNvut7ZKHlPblrW9vv9QAuQm3g8r/txy+g1TCycZ0Tc8HgYJ92U9OMJnIPA2xCTX1xcTJ2Q4kbCJ4p2IhhXL1mgPYVzB4RTmUwmGrjhKbmYJycLpelWs4S+HvMjuCx4r9fT//F//B969uzZVAiAYHj4lvQ+Hs6cnp5GXO982NXVVRwT5CERaXPI7UwmEw3i/ew+QjUU2TkVvg/RWiwWIz2PnLhSQ8KSeGg2m8Ezsm7MNU6GefO5d8cGCpCue0Ujq76evhbJkN0zsiAk1teLMj354XrjYSzoEOdE1T8lIvS8hvfjOcPhMDgm7pnL5aaMtOsDxx9BRTjKgv90mbstNPT7OhhwRI6Mont//ud/rs8//zxoEDdyzAHr+G3XOx+xxEAwQFjgbrc7FeKhPM71MBDnnRwJ8QyyLAgLz+IzHkd7qDcajSKVSsm8Z4xQOEc0LtQoiXtZvBRwGi6GqleQC7yYf5e5Ah4nSXKfL1cQ0BjKub+/r1//+tdTaMuJ3eQz/eJnZACp9/JUtodxkqbCFgwuwgW6GA6H0d7DCVM/ExCHBF+TDN1Qatax2+2GI+Fda7VaKLzzRxgaRzHID/OBIvA95u7g4GAqTPEMnsu0z5/Ppxt6ZBRjjFz6kUtuMFkv5JYEAluRQGcUcUqKHfkoPvfw+aOcBP3BWKbT6amSlKQxZ+6gPbwdj3RT4Mq8+5yQFMLIvXjxQv/6X/9rnZ6eRjTEGJIo1/ncr7u+1Sh5WOAL6S0eyF4wSU5e8jLuUZOhhkNyUEhyAj197EKKIYIkhYcBgnprEw/3uPiMCzzfZVH5nae3qckiU4QCu0f17FlSOPGMxPMgLy+fyOfzwc8klc/nJmmY/N/n5+cajUbRzZL39apqEA+Qn/DR+QfWAARL4avzMoQ1PrckKVx2SGoQrp6ensZccv/9/f0pZMx7oTjO5zh/5pkeR0qszZs3b4JXIwPKc1h3R/DIBmvv8u1EM+E88u0lEY4q4I5YY+QhnU5HI0PGRSaQsbBOg8FgqoWIn/KMo/M0vKNMIh4MsM8t+gWdgM5AR3iWGxk5Pj7W//P//D96/fr1VEjuNI3L/7tc71zRzcsBBb1C09GCdBPq8R0uwhkQkr80FjWJxjzDkYSqcEgIOSEclbl+D56DsXME5oaLtKhXz9LTh8UuFApTguBG1vkrV8RkqtZj7nQ6HeeWwTGQ/XIYncz4JAn22y5IadqX8lkn6AkhnHx3I+hbgTCgfvGuZGWYb57jio4hYu39rDZHyZ1OJ+7tV5JLSWZ1PLRyB4bxajabOjk5USqV0vr6ejyTeaT40X/uCMkdmCd4+Js/rDO8CyiGfzuvSUhbKBS0tLQUfJdzb9zPeVOa7S0uLkZoypy4kWLTt1erQ2Kz1uiXjx35R375PAap3W7rT/7kT/TLX/4yIhKXG7cfyfDvm653avLGAqPYwFMKF0ErHiZ5AZbXwLiX9KwNfxwSO8Hm4WCSJCQmB4Y6dyBpKivBJLlRcsVxwYZwdJIbgwBXQgElSM0JUEdl7p1QYDxvr9eLMMh70PDunIiSRAUojGdR/HcIKAIOQuDeTsr2er0YP+vq9/JnuMLeFuaAxjzE8jBWunZWZNoIeXBmtM4FBSSRkhsKZJQxsj6sAbLEO0IdnJycxDz4vXFSfCfJ8blzSsoOio6jpnMCoRf645+FJPetH4wJGQP940h8V7+X0vBu3skVXs4zncy/d6QA5fJsJ+eRg2SpwWeffaZ/+S//Zeh+ktfkOe9qjGI9/zIfPjs7m0orJyt1gZoXFxex0929CkIAX+OhzW18CfCfrpfucSFpaTtB5mNpaSnIaTgQL9bkHh4KOVHP5LJI/JwFlq5bvVIOAZkr3dQbeQk/YQPvnk7fbA/gOVQVdzqdIDulm3aol5eXUwWpvvie4eH3fnl876UIGMlM5rrVCGEohxRiBBFGjK3zFMxf8o+TzdwD58Qa4+0hZX0fZafTibnOZDKRnXXClot3QR7dgHlSg1ogeLXBYBAbm50TlBQ74D3z5yQ3TpfPeEtf5pGSlF6vN8VdUY/mNUCcCkJoyDt4gTBjRNacMMc5U+4wPz8fCIpxY2x8bTAwLhPJd5QUjp55HA6HevHihf74j/9Y9Xp9ylG6/DkH9Ze53qnzpBOixWJxqkiLMAYDxD6Z8Xiscrk8ReRinVOpVLSkhYT0xXCv50Yv6bUo6JNuWsouLi5OZczc8LlxdCXm+YwHIhvhwQvRkB4B7/V6UydaIKAoIYqIp2LOyPAhWKS/qZLmPTkt1xEe78NYfR/e160faXcE0I0NXAr35URYlJfvYKR875ujXITcW5t4fQ8KLt2gJGSFrTmseavVis+Csv39v8kj43g8jHCnxzYReJGjo6MI0T20LBQKU/sJ+T6Gj7lzBM99ut1urC90BJ9FVxjj/Px8lFzwPDdifoABBpKfE8qBLCeTSegcv8NIYUQ5lcSNXTZ7s2XKHRdZPrKBdC/tdDr6V//qX+np06chm6BhHIxXxPt6JZH1bVfqmz6USqXe/QiC767vru+u766/xDWZTG6N674VKf2v/+v/GmgBK+j7bPCKmUwmPG46nZ46HQFS1gu5QBLet9lrj0gjc4IG93TS1Ulj6SbbhRdwHkm62eEM4fdf/Vf/lf7ZP/tnU+Q6qI4xORx1Dga04nvk+B7N5BkP1bd4Ky+HAGGSGuZ7jAP+jXfh/7yfw3rIYdbo7//9v6//5X/5X6YybjwTGO91KF5TxXt7TyXG0e/3oyzAQ20n9dnvyD15NyfSnffx8D25SRcUwljhaf6H/+F/0L/4F/8i5t7RMfPqvCRjdXn0DBGFq4zJ63mYK/Y5gnSgLJKEe3J/J+/hqfx+v6+9vT1tbGzE80B6/+1/+9/qn/yTfxLPdTrAqQcuaAqQlMs/90ilUkHke6YRFDwYXPdyR1ZoYQKnCvcHGvbwmOexZs6/ZrPZoCfQoX/wD/7B19qcdyK6gV8uNMTEGAggJgsqKbJyQDvugZD4Z6i38J31HExJ+hSjhKC5IeD+yTSkZwzZdc97+Xj4t5PUnjn0rA735fkOXZ1Dcn4KYYMjYlsNhpsGcBgc+Dp/lr+Tj5U5pzA1uZkYIfZ0rRPyzgchpFyeWECgeD8ybAghSuGFtq6QvEcym5rkgXw9+Txr6qEQ33El5XueNPEQw/9mHKy1N7FzGfA6NsI7HDP/Z658XH65A+W5GAnWDTlN1hcl54LnEoIS2nkDQ4wEc+UnkdzW5oZ74hzH43GcbothYsO6d9jENjh94O/niYl0+nrDedKAJ693qlNyq8jEehrdvSgp+lTqpgUuk4XFdkIOQ4bSQw6S3ofIprKV7AeojTFBPDspiadwDsDrOlyQXDncqOHtktlCF3YyII488DakyZ1UdC4ArgWUwxw6unGP7Rko52F4bwxDkmPic8kso5P/PB/DyDikm+N+OLYaBwHnMRpdF9KORqNoqUr9Ee+eRNfMvysdP3Ml5WfOT93mVHwuuHxd3UGiUE6oMxc+Rpf78XgcNXGgWDbQ8ntHnj7HbpjRm1QqFRwi8+j8C+vsBtyLKSHR3bk4ge3boGZnZ1UsFqc4V5w7eoruMU/NZjPWgs3h6D3viRPzUgbXP/TO9dKd5m3XX6p4MklEA+uwohgN4De/owCQWgkaZ0ESk23iHo6MyMRQBeshgNdKLS4uRqP2ZFsMT+/SN6lYLIYwIgC8G0LmDbfwIhgg3ybD+EASVIAvLCxEVbPX77AZGehP+piFxKgTkszPz2s4HIZAUXnN+iTDTbw474UiuAFw48paOllNT2fuiSCzyVlSbF5l3HQnJMxBwJEPBJIxMiZIXg89HPVMJpN4Lo7HjQbz4MSzOxJfS8YDUuS4LRSFGjRCYOZqMplMbZrF6GIAuL/3kHKZ9/DR18ZDe6IGlJv380jDM7ts3wHJ8XPmSZIODg705s0bXVxcqNFoqNVqxVp6JheZpGZsNBqFPgM0INgZN39LN10yaSToYT1/k3kvl8vfaHPeySi5d0bAabMwmVyncMk4tFotHR4e6ujoSKlUSsViUVtbW+FhsfbNZlPz8/Pa2tqKU3GJadkUi9D4hk2v/JUUPZiZhH6/r0wmE20xnP/iPvASfvn/vTsmBq3ZbMbzveE6QsukY0QYJxkQr2WiLxGHGJyfn0+1xXUjAgIcj8cqFoth1LyIkc8jPA6rUWqMrRs9jIVvZqZuBgHlvTCy7E1zjhDOiIb0cGT0z+KdPbtDaJrNZqPXEWvmcobxIFNHH21HWyg4soWCcR8oAU+h+2dRrnT6uvUKmTfKX0ATOE0MEFtFkCvkTFIYG7JrOGAMJkiDLBXz4hdbuAi5qCtyisERH1THxcVFjPnw8FBv375Vv99XqVQKMECJzWQyiRIG9jPyrnTCAGHxbuhqKpWKAk4yxZ1OJ3SGd6eRIfVMZO9/a6PkxVJA3clkEl6Rl0qn09rc3NT3v/993b17N3pWo8w0DctkMtrc3NTm5qZmZ2fjlJH9/X2dn5+r0+kEiiB8A366h8SDp9NplUqlCAOdNPZtIRz1AlGL5/a6F7xtr9fT9va2tra2dH5+rsPDwzh0ke4ISdThSEO6KVGgvagfr43xwCvhjZwnAgnhXRBKEBohMAYilUpN8XHsn0ryRSC+VCoVa+LoT7qpAofzyGazgYolhbDSMx1DTUjhTgSDx7hZO2pfvO8WhX7JfVfO97DRmt+jWHAo3IOWru12W61WKyrmCXkIU33T7+zsrBqNRqAPED3Gl9ojV2Lnc5hvkFc2m1W1Wg0Dzzt7vVW3242NyoQ6yECz2QzkDxeD83FnQHkMTgYDyT3v3Lmjvb09jUajOODAmwmyY6HdbseugtPTUxUKBS0sLIR8QyXwfO9qiXxhxJFveoPT1x8n+zsZJbynGyHqcXw7CQTYzMyMjo+Ptbu7G4o1GAx0enqqdruto6MjvXz5UtVqNTwI4ReDvrq6UqPRiJdZXl4OSAlZxjEvXhnNZHCSBQrGQYlk+hBOhJ7FdHIUI0SB3/LyshYWFtRsNoMXco6JDOV4PFa9Xlen09HGxkbU4LjyXl5ehqLAxeTz+TCiCLTvswOSYyBQAjbTwlsRYnIwJkaP8ANDOJlMAvmtr6+HcGOY4L+oYSFb0+/3o+6FOQDpNZvNeD+ei+JjlLy2DfI1l8tFcejZ2Vls7CQUZp28bW0y0eFV+3fu3FEqldLR0dFXan0I6Zx3Ye3hiOjrTfjtoTsdMhyxO3IELTOuTCYzxUN5XRsJjmw2G/sSPSu5tLSk09PTCFlB56PR9V5GrzGTFFECyAm0OTMzo+3t7eCC8/l89LfHiCK/nPDCeOBhOesOOXPnCbcEUiMkn5ubiwME6vW6RqPr+i+nhH4ro0QzN8gsql2B9hTZ0UdlPL4+gQLo7p4aaImxKRQKKhaLYX05ZQJh893W6XQ62rdWq1U9ePBgqnoazwORXavVgoiVFGEmyuEtR1utVoQRjAWDsbi4GAZwOBzq6OgoTnPgXRwJELJ2Oh0tLy/rww8/VLlcDq4B4/769Wt1Oh2NRtdNyFZXV6dSz5DkbhByuVwUzZ2cnASyIxuEF+/1etGDmyOs4SYwSIRLxWJRf/tv/22Nx9cnWTSbzSlFItSr1Wo6OTlRu90OD4lhAA1xEoYjOydUQR+8H3yUh1YkNnB6VDtTvNrr9aZa24LKMKKTyUS1Wk3j8fXxRIVCQaVSSWdnZ6rX6yqXy7FmfA8vz6GrkvTo0aPo/4RBOz09jUMx4T1xjCAE3gveD46q3+8Hwnai250BoRnOnBOInVSfTCa6e/euyuVyOFr0DgS6sLAwlcon3M/n88EVsr3JD4OdTK6LSyHWMT65XE7lcjmQE8bTM6Xj8VilUkmtVkutVivIbdDwYDBQq9VSJpOZ6kz5Wxmly8vLOM+KSYWXqFar2tnZCZL3/v37qlQq+s1vfqPd3d3wPvwZjUbxeWA0tRCEX2Rs1tbWQjlGo5FKpZJWVlZ0dXWlH/zgB3rvvfe0t7en169fh0Bg8QuFQjTOAr2w4/7s7CzuK0lHR0dTyoNHGg6HKpfLKpVKmpmZ0draWoQMhH4IgXMVklQqlbSxsRGbJnO5XKAFxghqw6twWsX8/Lyq1WoYU+88SEjIsxuNRqDHlZUVzc/P6+DgIAQvFtn2DoJ0NjY2wknUajXNzc3p7du3qtfrYbSB9ZeXlzo8PFSn09HDhw+1uroalf3M5XB4fTYg6IGwD6FcWFjQ3bt3w2BLCkKZ97u4uNDx8XFk8fyoHzLAbkgkxTYHDwUPDw/j6CB4Dbi9ZrMZIa4Tu6CDzc1NNZtNVatVbWxsSLqpVqanFEjV184PgGCtQJlQD3t7e2o2m5IUlAKcV7fbVaVSiWps6Wbvm2dsV1ZWtLm5qfF4HLsOlpeX4/BNUAilBjgV36c5HA61srKi/f39kJdsNhstikGoOPzl5eWIinzLFQ7UM3xwpHB6lCOg2zid38kocXxxoVBQo9EIi72wsDBV0i5JxWJRKysrGo1GOj4+noqt+bO0tKRisai3b9+q2+1qfX1dmUxGr169UqfTUbFYDDhPipsQhk6EwEjIdlAbhKUXeMHjAE09Zpauw9ONjY0wfkwqHpZFoGHceDyOQ/2c4IYolRTjPz4+lnRdnr+7uzuVMOh0OhHXe9r0/fff1507d/TmzRsdHh7q8vIyUAdoB69HszXI7WKxGA3quD744AM9f/485iGbve4+sLOzo729vTjOqVgs6vnz59EiV5rmtdbW1iIM2train7pEJrj8VgnJydaXl7W3NxchCvValUzMzNaWVnRT3/6U83MzOhXv/pV1MCgfIQVXrwIgoWvm5ub+0p4SiEnY0V5d3Z2InReX19Xt9vVmzdvYs4wHjT5Y1458RZk1G63Y535HAYFZFQsFrWxsREtfDGioCWSFMViUf1+PzZdYzg9pPR5p3gYEEAHz2w2G6h0Y2ND1Wo1TvR1lEWkgRPMZDJxvt2DBw90dHSk4+NjtdttPXr0SBsbG3GGH+MGlbbbbd27d0+bm5s6Pj5Wq9W6NiD/Vq/RO4h0nBnvlM/ntbKyooODgymH+VsZJQ7s63a7Oj4+1urqqi4vL7W9va2ZmZmAyktLSzo5OVGv19OLFy9CuMggAPtg/h8+fKirqysVCgW9efNGn3zyiUajkf7aX/trIRReOYrnXl5e1tHRUaQ6G43GVJ0EvBD81GAw0MLCgs7Pz1WpVJTP5+NkFV88Fh1lIqzEsgPX/YQPjJh7g7m5uTizbW1tTdvb2zo+Ptb/+//+v2E08/m87t27p0qlEtAePuyHP/yhVlZW1G639erVqzDKV1dX8RmMAGG1p3dBXPAMS0tLajQaKpfLMd+FQiFITTKfHDWOIZVukCCKt76+Hs4Dct5LJs7OzlQul0OIQSlwVxDyjBWOxkMevC/KORgMVK1WVa/XNTs7G+MkrZzL5SJ8AXEXi0WVSiU1m01dXl7qRz/6UXBqp6enOjo6ivfjxJnZ2dk4T/Dq6kqrq6uSpE8++UTdbjc4ptXVVVUqlak1uH//vj788MMw6mRSCTdBcKAJL4Mhw8d7w0/yO8Y9Go3i8AN65HvmtlaraW9vLzK1cK++KVe6Kd14/vy5Tk5OguiHNPdkB2iwXq+rXq/rZz/7mba3t9VsNoNzxWGyZ9RroLgngKBYLKrZbIbu/dZGiXDt7du3Ojs7089+9jP96Z/+qSSp1WoFaspkMvriiy90enoa5z4xQSCdSqWixcVFtdttNRqN4EaazWZkqOj7DfRH+E5PTwMZ/cVf/IWOjo7Ubrd1cHCg+fl5PXr0KI7SIS4HQv/oRz/S48ePNRxed03sdDra29sLI4KCgoYo/js5OdHl5XV/psePH8dprYeHh0GuEz7B05DdaDQaoVTHx8fKZrNxXBAHaXLyL2ExZRXUkzSbzeAzCoVCKDyeBpSyubmpTCajVqsVvBRxe7PZ1MHBgYrFYhTrdbtdnZ6eRl3Jmzdv9OrVK7VaLT19+jTCZYwRXBb8Wj6f19bWlnZ3d/XkyROdnZ2FAhCuUJ9FV8nZ2dk4sw5OY29vT0+ePNHKyoqWl5cj6yVdI6W7d+/q2bNnunPnTswTZSPb29shY6enp5FuRxnb7bb29/e1urqqVqulJ0+e6OOPP1av19Pnn38eEQCZzMXFRa2trU1trH7+/HnMSzqd1sbGhra3t8OIgNpAPIQxCwsLajQa+uSTTzSZTLSxsRE9yjOZTBz3TQgJZ0QtFlwdxDGGN5vNqtFoqNPpREj29OlTvXz5Un/6p3+q169fa2VlJRBsv9+P02+RFzhiaJnvf//7ymazOjs70/Pnz7W5uRlZRi+oBLF3u109ffpUBwcHcSLO+vq68vl8GDxKI+DOACjICG1jfmujdHh4qK2tLR0cHGhra0tbW1v6gz/4A/3iF79Qv9/X7OxsIJejo6NQ9mq1GlkAsgcQyY1GQ41GQzs7O9rY2NDDhw9jAV69eqVmsxneqFAoaDAY6OTkZKpIrdvtqtVq6fj4OJQG4g8OA8j4wx/+UL1eT0+ePNHDhw/161//Wq9fv5akyNJgPGdmZgI5EP/Pz8+r0Wjo4OAgeJf19fUg3iVFbA+3MB5fN1OnIfx/9B/9R9rd3Q1C/OzsTCcnJ1HkCYT/sz/7M+Xzee3t7enNmzfKZDJ6/vy5qtWq7t27F6Q7ilsul/XgwQPNzs7qk08+kaQo7JOkt2/f6vLyUu+9956Ojo50dXWlk5OTqXJ/xnp1daV6vR7cVz6fj6xLoVDQ1dVVFJ2enJzo6dOnevz4sS4vL1UsFvX+++9LUvAQvCfc4tu3b1UoFLS8vByk/OPHj/Xee+/p5OREW1tbWl9fD97sxz/+cZyiAncH4Q0vNZlM1Gq1VKlUwhgOh8NwQjMzM/qzP/uz2LaEUhQKBZ2dnUXI5kcMXV5e6tNPP9Xc3Jz+8A//UIeHhzHfoKxCoRD3/PzzzzWZTFSv1/Xo0SOtrq7q9evX+sUvfhF8TavV0oMHD1QsFrW5uam/8lf+io6Pj/WLX/wiuDIcHe+/v7+vVOr6hNvT09MIJ0HNZD4PDw/14sWLSPzMzs5GC5psNhvc1XA4DL4M1EVYt7+/H0Z/MplEouTy8jI4x6dPnyqVSunzzz+Pk3DT6bR+7/d+L6gb1h8gcu/evahrAqQgp7+1Ufryyy8jNXnv3r3wLFSIZjKZKJ6UrmPHtbW1sO7UZ1Bvs7i4GHwCZ4LByywuLur4+DigKYpKtSj1KalUKgzA6uqqxuPx1AmoGEuyH7lcTvl8XrVaLZRrfX1de3t7IUzlcln3799XOp3Wb37zG3U6HdVqteASICOHw6Gq1arK5XJkwiBe4Vxo1E/a/7333tPq6qrK5XIQuE+ePFGv11Oz2QwhHA6H2tvbi2zR0tJSELlsQgUSe7sU967cBzR1cHCglZUVff/739f5+fmU8EmK0DeXy+n169daX18PgYLHgXjf39/Xmzdv1Gq14siijz76SKPR9akr7XY7wqFSqRT8GYV1ZIbS6XR43wcPHkxluEDehJn/+X/+n+sf/aN/pO9973vBxZVKJdVqNUmKgzOr1Wocl1Wv11Wr1UJBK5WKMpmMKpWKjo+P9f7776tarYZRBmF1u10tLCwEaby6uqr33ntPDx8+DIUmGsAADgbXJ/myJozx1atXkV0mbX5xcRHvD+8mKbJwcJUPHz4Mh/LTn/5UH330kb744gs9e/Ys9IzEEciTpIwnbUAmhFKdTkdnZ2eB9kiADIfDqOs6PT2NyMe3vmQyGb158yZCQ7jLXC4XqKrX6wVnlU5fn/H38OFD1Wq14IMp2fmdjFKr1dL+/n7ErS9fvlSj0QgiiwwEiAYy1XcV+16zbPa6k2KlUpnq8wxZXiqV9Pbt23hpoCgTQ6aPzE2pVIpwDYX1XsZXV1d6+fKl9vb2ouL80aNHWlxc1K9+9aupymWgb6lUmjqphLqo8/NzbW5uhhEi0+HbSDCiZP9ABvArvgEZMpV3IfQE5VDkBllMnRJcAoV0e3t7UaCK8QQyn5yc6N69e9FNkt47nU4nvD1ZP1ARY8RxUHuCcalWq9rc3NTCwkL0m37+/LkODg7U7XZVLpcDunvqG4WC6yuVSvr+978f2TfP1BKmEuLfv39fBwcH+s1vfqPf//3fDzKeEoSlpSU9fPhQBwcHOj09DT6MyvVMJhNZJAr5kE/CbN6To6fy+XxkSQeDgcrlcjjXXq8XPFO/39fR0dFUaD2ZTPTee+9JujmMEv3odrv6+OOP9ezZM0mKcBr9IhPdbrenCjgxoiQ1yK5hYKSbukKv3UN3Dg4OwgnB1Sars2lgyO+la1SIIQJBe48mOKnLy8sAFBjFnZ0djUYj7e/vR3IAFPZbGyVI3cXFRV1cXOjt27caDoehRMTUnBzip1KQUfHSdup/8IS+d2wymURBJWFPsViM7BeksHTDdTGBEG7Etnj5VCql3d1d9fv9SHmur6/HxBCbI3yzs7NaX1+PhZI0VSbfarXi7DNPfy8tLQWBi1caj8eRqvc9WhD/ZA65j29FgddYXFxUpVKJanavWIdcxiBAPMMX+dVsNqN4zgtVqWO5urqK43kwJhCt1NCQXl5aWlI+nw9DTBnGwcHB1FYWqqy5UDbWLLlpmDQ/Yfjz588j4wtKpYDV91yRVaKMhJORyfp5goD35Z0I9wl16AK6sbExdYKvJ0BarVZwkNLNrgfWGM6JSmdS6MzrycmJnj9/rmfPnmlnZyfCNBIVXnqSdNjcu1QqRTNC0vc4ImSazNns7GyQ0x9++GFwpz4m5ByuF/To+9twMCBeCktxKN1uNwwsn7u8vIzEEoZse3tbv/nNb77W5rxT8eRwOIx9MzysUqlEKMSE4kmBj8THII5isahf//rXwRX5DnMWPpvNanNzU59//rm63a5WV1dDGeGO+A4CT+EchgnDwMRyXwrDMF7SdfaN+/Z6vXgX0syU00s3p15AoiPILLzvyarX61peXo7CSd9Gks1mVSgUwlAgSF73gZK6cCAYFK2x4MPhTc9p+LD19XVJ1yUd7IEicUDYSdU0ISiOgQwKjoRQDmOBcvC8yWQSFcK+hw7SF8Pm6AlOxI0RyuQ77UejUZQjrK+va2trK0I9SeEsQZAgHC5CKuYXOWHPJA4VPrHVakWdnG+fIKtLEsMr+b3shVCbsfv2Hu7T7XbVbrejeLHb7UaC4N69e7pz5861cmazwRldXV2pWq0GJ0n0QViPXIC62auIEaNEp1qtTrXZRSbT6XQcXODFnMgIV3KrkO+B9JAPQ/z06VN98cUXqtVqoSMQ77+1USIrVK1WY+FBB4QbCDQGwuNQ39OTy+X0+PFj3bt3L6y1GyUqT1FmyHA/YcIFlgX3fT48CyF3GIqxmpoA29ZBrRLZDScI8UJ4T4wMHp/3JZPR6/X0/vvvT+2586I/Nn0SArtR5d0QGPeAVARjKBEKNjyz0Zc5KJVKU/vdPAXNnINuJQWfwLzA9dVqNZ2dnWlrayv4O9AB9SzFYlH1ej1QEutVLBanUs18j/UhxOe5jJOtKPAw+Xw++La3b99Kukmp+2ZuSVPyxbt7axu2vLhBmZub0+HhoZaXl6OJnW+Qpro5l8vF/jLWgsJJ5h2lZ90I9bxan4NAvbsFToN3kK6TTWSOfSsKKJX9aRgq3oe1a7fbqtfrqlarwfe4TjDm+fl5lctlHRwcTB00S+kD8odh5B44glwuF3I+HA6nng3nBi/6Tdc7dQk4Pj7Whx9+GPE53g/jw2B9iwQKC4pZWlrSq1evou6F7SoYFd9gm81mg4iGPMXLseBMqNdE+MtyP+6J8MAfYUSTO96BnwisLyDCkhwLBon3/Pzzz+MML2JxFNHDoXK5rKOjI52fn091csTIMW5XZDeiEKYIaaPRiPADo0UJgIe9s7OzU9XE8Ap8h8uNBHUpcIGsP3uj0um0tra2VK/X1W63pw6OcBQBcnFDD/cB78ia4VCQIwwbyEO6aYXCu7ChG+PKd0C0rBcOjeeAOvb39/XjH/84DB3viKNgnxpFgGQx3bEgj14f5IYeo1Sr1XR+fq52uz3VzsMdIDypyyocGEaQTd/MFXMIfXF0dBRrxxq77PB+1ELV63X1er3gWFlf7k3YjYHi54SeOFLsAIkcKItk2J683skoscUAspS0Oagouf+IK7nov/rVr/To0aOw7h7+sJAIeaFQ0Pr6uhqNRvBMyfsmwwF+BmJCiLgvXpMqXklTxhNy3eG3w1yejYfCE/Ie2Ww2PAOchKM5hJP7lcvlyPSgvB5q4MHw8AibI0aUiWrn4+Pj8MrSNdHNPimUF6MAqYxTcGEBHczNzUWtEWlk1sjXn/B8c3MzMl+EfVyOUhgjIVCyihzDwdr6/j3QAIqQSqXi8AV2y7vh8fdlvZNILZ/P6//+v/9vra6uBiHLWrCzgLGUSqXY20nI6Hwiz8Aogd4xBKTu5+fn9eLFCw0Gg+C7vFsDc8VYPRrBEIK+cQCehV1YWAiUAq+Lo8VA5nK52NrFmpXL5eA7KQHxNeQZFIG6bEo37ZaRdQw3Id3a2to32pxvNUr37t3TkydP9Nlnn02V1rPYbF4F0jmKYLIymYxev34d36MWhc+hdK9evZoi1tLpdJCCjx49irABhXV0lBQIhBYlAlkg1Cw8nMxoNJrilKTpE34RQN/C4cgGIX7y5ElwN75goCgyPAhNpVKJwlBCDldGvu+CjaK4V06n0zo9PVW3251a9D/7sz/TX//rfz24MRSS+iGEkTFxPxdwTo1ZWVmJ+cRgM3d8r1qtBmdCXRrr4gbKQ14EmnVi3fgOXRzYwQ7/Id0ca0U5AevrtALK7tkrl8+5ubnIhJEtZZ4IG9nxjkKTyaX/EgrolxssT8Y4J3l4eBgZsVqtFhGEpMiEeu8jAADO2B2mO0qyu6TfqTnL5XIx98gbBp8sG8R6o9GIZAAy6SEqmXDGxhq6YfT/E1l9W+uSr55Vk7h+9rOfaW5uTq9evdLp6Wk83FOQCDCKQmyLV2i326rVakEok5LNZDIRtoBQeBGI1tXV1TBY7JhGGVk8nxhHJaAJNkyyrQPjKF0T0vQehrRPwkvPEIJoML5A8UwmE1k+9pN5jE9yAMWGMF5ZWdHS0lIgpiSxyOJ7mt7RpxtEQqyNjY3Ym3RwcKDDw8Pw0nhKSjbI4jn6xPhRwcsmXjI+yfnFYBKybG9vRwmJhwYYCubTOzww78wNgks2EgXHwIFCWq3WVIobBeBzKBNzh8MCoS8sLOj09FR7e3tT7wgKoNxlY2Mjkjflcjm4H7LTrIcjeBAaz0deWDcM5cbGRuwOcPnzjhk+x97CxLkxiGaIezJpo9FIq6urU7VjJICoF6N6G36wXC7r8vJSx8fHMfcYWObXnZInZRgvOoIOovNJ+U5e34qUzs/P9Yd/+If69NNPA7JSUeqT4srBi1MhXK/XA95vbW1JujlDisk4Pz+P+JrFIVZ+//33tbu7q8ePH6tarWplZWVKOVz4+BuPlEpdNz+jP4y3XpCuvcHa2tpXduODiJh4uCUML88FYtdqNdXr9SB2McBOgiJk9JjhT6FQiGJUCE/mgOd49i0WzzJ1jHVjY0MbGxv69NNPJSnqgxAIBItw25EOykBpBHUnGFqKUEGZbCup1WoRIgwGg9hY+/r1a2WzWVUqlSlUi0JRkuBIgnVw78o8SoqCXK6Li4vgPjDoKC3f90QI74jy93o9HR4eRpnKxsbGlNOjLAKFpa4NPmkwGMSWIs/6uYHBAWKQHXFvbGzor/7Vvxqn9yIr0rVBRmac2/SIwDOKhMWSdHx8HKeHVKtVbW1tRbkENUS9Xi+cztXVVfCOGGKatNVqtciAMn4AhOsCjo3xon+gM4pHk4gyeb1T9u39999XqVQKhUco3UJjISkso7KWcKVcLuvevXuan59Xs9mMrQOU+9N/m77VTE65XI5q3c8//1yff/65isVibA0g/Ykg4W0nk0lklYD+w+EwPICHK3Nzc7GjHOEFcRHTgzSYcAzwYHB90urh4aEGg4FWVla0vb09daQ5Y2ODpme8KKGoVqtqNBo6PDzUxsbGV5IJeFeEAm4MAR8Oh1pdXdWHH34YmSveD4Of5Hf4vYcYXMk2Iuz+dwdEFgoEvbq6GtW9hKXPnj0LktV5IgQWdIoxwtCC3qgtQ/HhVlAguhqwNouLi1P9etxRurwOh0PV6/VIpszPz+v+/fuBJkgAkGEmVKMJ3Xh8ve9wdXVVnU5HBwcHWl5eDoLfUYOvGXNNiPTBBx/owYMHU/QI67C/v69KpfKVbHOSNgCNMJ/0M2NeHj58qFwup16vF50XGA/oGjSOvC8tLWl9fV3z8/M6Pj7WYDDQ5uZmtD+Bn8QYusHF0UB8UwLw7Nmz2GryOxmllZUVpVIpra6uBpKhZmhxcVG5XC6ql1mwer0eC0cB1+rqajSt2t/f14sXL5TL5fTgwYMoPWcSDw8P1Ww2lcvldPfuXd2/f1/ValXf//73o4iOFqDSzdlkCAE1H0DeJLHp6dqPPvoo9oTBAWEAQIR4KQQGlNhsNrW7uxuob25uTvfv34+tL/TtYZsMp88i3KTuKa9gc+yzZ8+ikRdGybOThD+kuilPuHPnjj766CN99tlnURz6d/7O39GXX36pTqejtbW1KbgPqco8IVyQ9aCDSqUSCIIumYuLiyHkGNjJZBIk89zcnB49eqRnz57ps88+0+rqaoQpGHyeKd1wTLwPPXkePHgQm5NBJvBHkvTDH/5QR0dHYaAJFdyxebZWut6a8vbtWx0cHMRG03v37mljYyPohkajEQZ0PL7eG0hhKfMyHl83HLx7966ePHmi169fq91uq1AoRNGwGxDCOWQDbqzRaATKgQ6QrvlcjJHzoo70eScMTK1WC6SVSqW0vb2t1dVV9Xo9nZyc6OXLl0qn03rw4IEkxe6M+fn52FuXz+e1ubmp1dXVKMJ9+vSpzs7OtLOzE10wbjMuycwpxpfo5dvKAd7JKFEHQjjlAoFQsx0AjgJSt1AoRGeAYrGoq6sr1Wo1ffzxx/rVr34VYRjNyWZmrpupsdnz4uJC9+/fV7fb1XvvvafZ2Vmtra0FHwDkpFWEpHguBY2ezsX7IWySAtYeHx9rMplEJSyQk2pvOJDLy+u+44eHhzo+Po7UZ6FQ0NbWVvQer9frOj4+jnYey8vL6nQ6UcdDGIz3o4vCaDTSp59+qo8//jgaejkBDpogHQsiJINDVTXe9sc//rG2traUTqenDlUATaFgIFsqfyVFWcN7770Xu/RbrVZAfub+7Ows2oRks9kouoTs//nPf669vT3V6/XoU4Wx8DDNd6VT2oBswUMmt/isr69rdnY2QjBaoED68jcbvtnY2u/3NTc3p5WVFVUqFa2urkbHiOfPn+sv/uIvlEql9JOf/ETFYjE2aM/OXvfxrtfrsaeOjeUg4U6nE7JEzR2Gkr7lbGWhPo45cL6FGjf6a99WpElf+1arFc4WrhKZor3048eP9Sd/8ieRMFpbW4umd5ubm/r44491eHioQqGgH/zgB8pkMlpfX9edO3eiT/3p6WnoB/tKvbSHaAfbwKZnOGaPUn5royQpYn2vcSDWHQwG2t/fD8/i5e0M1hfkzZs3+uKLLzQzM6P19fWplKt0HXcvLy9re3tbL168iA6Wk8kkDBvcBmRoMtYm3CF8YluB1wq596QnM0b16OhoisehVgRlBBUgdIVCYao1RavV0uvXr/Xpp5/GznE2xFINPB6PYwf8yspKzBO8BgL+61//Ova/0brE++z4CRSZTCb6E+E4vvzyy3AU9J4i7IXoRLBBobxPPp8PI4InPjw8VLlcjnnFGBEuJLsyrq6u6nvf+55evnwZ6IqWs95HiW6hhE6UCjjJC2rxnt7ZbFblcjn4IQ4wcEXx88xYb7JK/E1F/6tXr/TLX/5SX375pdbX16MrQLvdVrfbVbFY1Js3b/Tll18GkgV5IvfwNY1GQy9evFAqdb0xfHNzcyoMZowoMIaW/XOsMzsC4P9A2hhtmtDl8/noCgrakq6TAc+fP9dvfvMbHR0d6b333otwjQJOWqTMz8/r+fPngcKl644flUpFxWJR6XRa7XZbr1+//kovLAwVIXYqlYqyA+r1vs0gvZNRQtF9K4ek8EpkMO7duxeCRgqXF6axGnUkGxsb+uijj7Szs6NM5qY/Nzul5+bm9P3vf187Oztq/9vDBo6Pj4MoW11dDaUk20Cmz8sS6DCJF76NMOb9QESj0Sj2/uCRIVZnZ2e1uroawufeAW/A6Syff/65Hj9+HMQv2yNAdbTyODg4iKOL4N4kaXV1VY8ePYre0mQwJQW8JhXNXjRIXkIf6ToEYF48bGJ+eDcMbC6Xi0MSyDTCmz1//lx/+qd/qvv37+snP/mJJpOJDg4ONJlMYk/a8+fPlUqltLOzo4uLC21ubkZ4ff/+faVSqQi9MYKE1oR98GkQ8skWuAsLC1H2wDuRavZzx1j3+fn52DbCMVVwKd7Botvt6sWLF+r1erp7964ePHigjY2NMJQYSVrmYnTIVtHZgTAQ2aEYl24L6AbhDQaCTKhzl6lUKvhc3n84HMa+M+kaNJBckW6KL0EtJycnev36tUajkT766CM9evQotiEBCOiKsLi4GN0xeTcyoIS5oDvvyS4pkjueiSf8w9DiWH4nowTLDjR06Eh2ghMKUAiKELPZbEB1hGpnZ0cPHjzQ3bt3tbS0pH6/r/39/YDYZNzW1tZ09+5d9fv96KU0Pz8fiIExsCnXY2yUyUvwQTdMjGcAvECNDB1hH7wH/ZNp0ws575m+4fD6pFuIRlDUzs5OZPRANAjS0dGRzs7OtLu7G5kJ+ojTDGxnZ2eKZ2HTMLUzhIMgMJyCC6hzbp4x4ZkkDEAmoEvGc3x8rCdPnkS7l5WVFa2tranX68UaHBwc6NmzZzo/P4+iPQh5lBoF3tjYiPohng9pSqiMTHkRKzLnR2TxLqy/Jzw8G4QcNpvNGDM1OPBok8lEP/7xj6Od7tzcXPCdzPHa2ppmZ2f15s2bUE74EojemZnrlrkrKyu6c+dOFJj6Hkh3ahwsQJYTOXUy2+u64Ku8VQnIF3Q1Gl1vmeIEnt///d/X9vZ2bBLnveB9QFq5XC52BzQajQj9qd9ivyB1Y0QhXvBLlMLvvb7v2653OjgABYZRRzm9pgZ4DcqQbnpVw2Nsb2+HMsHMo+CQ0zRPKxQKymavN0yurKwEn4LXBSmhhI54vHI5SRInC87gahBcSWHQ2BIg3RhnvCpGzndLn52dRavYu3fvamVlJUJN9rlJCqO5s7Oj+fn5yOwQSqGACDhlA3Nzc1N7C/1z7oFGo9GUZ6IeyAsVIVURbk8AIEBsC+h2u7Ef8Ec/+lHwjJKmWrZUKhU9ePAgeK3Dw8OA9qTieR8yntRM8WzkDUH31P54PI7nuVGCAoBzQVHdWfB9QnBkGKeFV79//75WVlZiI7Wk6LNEAmRhYUHFYjH2Z0IlcOKH10Z5gsT1SNJUPyUijGazGUkKHBjvR0Tg5TjIkxdVehkKsnb//v3o543BovvHeDwOlLm8vKzl5WV1u93YcwcSYkM74SLGEL1A39BJopRkGcHvXBKAx4SjSadvjvohdevCT/jknpcFYgI87SldE6o7OztBzPmk+/4zrxxlPLysh2OMmwUjvsUo+XYY56CSRZ8YND6DZ8fbzc/Ph9GlZmlpaUmbm5sRDiHM4/E4TgVGkaiypRcSxhhezksCfNxuROGG3OsuLCxM8W2ULmCcMe5AbIw0SIAwKpPJhMFfWFjQD3/4Q5XL5UhBcwgpCDmTyejDDz/U/fv3A8UyR/B2lAOwxswt3h1l9JDNecBsNhuENZ/FyPreMhQfhXH55HNsxZEUSRb+TYkCGdhyuRwIhufBfVI0iQHGWCAnzs84ome9CNHS6bQ6nU4c/8WcUFDqmblktTqZQXf4o9Eo5BGEg4NgA2/p356riK4SbsG1ebsZzpqDR8Oh48QpEUC+cTCsH9e/kzolL65DmREur1FgMdxzYZExRqTauScvValU4ohfUqb0ymGBqJyNwdt4MFwoLlbZ93e54jo3BlHp3ojJd+H2miUWEeEiLKJRGgvLfUejUXAh7p2BuXfu3AnSEIHwvWUIOfPr2zR8ThBMFI7nDIfDQHUYSt4Nw4KCeKcCUNrdu3dj/dgNXq/X9fLly1jHXC435YlRXlARP2dcGF1CH88wsq7OhXG5HDiawMDdVnTqhhzFJeTB8DNnXoVOyQRZNMJwFBC5Gg6HU0aD+/ouBQw/xtZl0sNl5sg5W0JRN2Sue7y3l8JwD9aTzB3zCgEPYnTkzV455gbe1GU+aQOQSYw0fzuP6Ummr7u+1SglvavDUDcY/n88uNcDeZiXDKlmZmYCIaAsyUVjOwCCkjQaXsjl+5zgcZKG042rw2vexb0z74Ei8a7+PDyCV+RyX++9s7q6quXl5UACyTodLsIrqm0hpnmu18r45mLemVDRBULSFDrygkkcCWsj3RgOUBXzhjcdj8daXV2dyjwxJ5JCQXyOPSvmobQ7DMaGc/FQZTK5afjH+iFLrBNjRfHcW2PIk/dm3ag89nng/XkuB5G6UYcH8x5DzqN4SMqeQ9YP9M2mXN7NgYDPm5e5uIKzto4wPTR3fXSHg+5RlMr7M24n2d1Z8AxHTjyHoli+44YMef2661uNkhsIT83yMx7IpHHhFVxp+D4QEvTE5+EqEBD3Kp75Y0J83417d18UJs3/vg1K8gw3evzcSdZkKOgKhqfinRkLggea8IxE0rixiKPRKGA40JwUsZc24GWdg6Ieicu9VjIL5wQlv2eNuS+CDfEq3WyZYD8fPZ45hpr1TRpMUJFn05Az5tNJexd+l0dHJN4qh7F52O3rleTi3NihVKAS5s3Xl9o1fuZznKQK3MmQZfPUPvOAA6HJPjvzIaF9DH5f1t910REZ8+UGA1TL53Ec8EM+L64PjEe6caC8L993OgW5xKE6BeGyedv1Tq1LmLzkDRkYHpyL/5Op4wW9hxJV0EnrTxsFCtAQAgSaCeJvJo19VHAgbkwddSGELsBJ73N1dTWVofL3ZaH5LgrgsNY9ty80sbfvE3RhR1mcoKWfDYJO6QDozBGHcwycLOEIhVDRx8r7MF4UITlXtxliEAbFkmQj/bMYeDKkPha/H2PnO4QzvnaM1T033/F9exgqXz9HUrchM3gmECN8kI8VucNguhzxHX7HnLoBwzC54qNTxWIx5NyRtiMr3sMjBP72CupkVIAewQWCJhkD78c6gbYwyv6+yJ7LBM9KggLGkjRW6NbXXd9qlJKoBauI1fZ9OQyIixfzz9RqNR0dHWl/fz9INGJ2r5alpzKHIAKd3dLzXbfmCBvowzMeCAQCyhgh/fy+KBD39L/9PR2W4q352z0K0JrFh3NjDlAA/u3Fnr6JNJVKTUH/pMeXFEQ5lysiyuEK4ILp3RDcEPgfZAJPi5FFsR0Zcx/uRYjD81A8f18n7j2kZg18IzLvk+SgkhtFeX7S6zMGxj4YDOKwR/fyGDmKVXGyxWIxii/dgSfH4cmYJGr3bVLUBDF2V2jG7AbB6QuQvBtfOE2My/n5+RTKQ8YpK+Fvp1bIHDMG52GdK2Idk3QH42dMyPPXXd9qlJLElr8wltW5jPF4PFVzguD0+319+eWXccLqyclJFLZJCp6EGicmPJ/P6/j4WOVyOfgYJxidD0rCwqSiu3BjDJgwD29QPjdKjlY8rOEe/j3uxXd9LlkQjLWPLxlG8X1HUl4T4u/JfFB742N348U64cE9nHXil5/5OiffjW0DPl/OSznf42NkO0oS8TGXTg8kUdH5+flU1gxZ8XoeSH1HzCgJMuO0A07g4OBAtVotjqV23o3aKA6NgEerVqva2NiI/k6O/EHdhODMZ9JJeHjlqMwJd3cGTjl4FON8JuuJMT09PY1jsHiOb6GioFO6ybxxOIQnKJB15BNjmnQsSUPEuqZSqan1u+16p4put8YO35z5ZyAsIoo8Gl230+W00aOjI3U6nTiramdnJ7YIHB8fx6bR4fBm0229Xo/Cye3tbW1ubsZkekZBuvF8CLGjGxaKLROuBA7nHYomFcPjbQTauS6QA4VshFuMI51Ox74xPJJnfVxgGQcXobIbY98/56FTkmTkfo5GGDceDbLTQx7m0vswoZiUDwyHQzUajak2wl634oLphhCU4+/IXDunxzudn5+r1+tFuYTPi3Mg8GFeyc7PkQ8M02AwiH5Kb9++jc4IbLtgnPB/FxcXkf1jM+3R0ZGq1aqq1Wpsf3F04jLoTj3JafFOlDu4bnmWkRDMZdLnzTmtfr8fpySzUZ7Pkkxhy4rTLKVSSZVKJQ4MAQk68sUJepjJz31rF1EKcutbYG673qlOyW+KIPIC7lGlmyKqVquly8tLXV5eRsuRTqej3d1dnZ+fR1j2ox/9SDMzMzo+Po5zotiQ+fz5czWbzWgtQc+hWq2mjY2NUBY6FrjH9DqOpFEYDAZ68+ZNjNcNEIJ7Gynn1j75B7R2eXmpw8PD2MBJJ4BUKhU9nVqtVhzImc/nY18Rxox59bCPwjg3GK7IjM8r7nk/v0jdEvJgCPHYhJ7cF4PPNgx2onP0dj6fV6vVimPUqUJnn5QrIc/OZDJT3IeP05XUieTxeBxtedk8nJwHlIYMGnVF3M8RJwimXq/riy++0MuXL1Wv13V4eBgbgKnvSafT+uyzz/TgwYPY0U9XjFwuF46T48TJQkIJeFkAY2HN3GiCrF6+fBnv48kIL1b0sEi6QSygpeHwunJ9b29Pe3t7qtVqajab6vV6sS81nb4+gNO/Nx6Pgx/k4M+tra0ohwDZIits9XIdSzpAD1c9gvq661uNEqlPJsPjYgbpNT948rdv3wZkZOvB7OxsnIcmSa9fv1a1WtXy8rIGg+sdxbVaLZBWpVKJhmHU7TC5b9++jUMRvdLZSwo8jveQ8/z8XMfHxyEoPomSgozG8LpA8TfcBEaAvVC1Wi02J7OXCS/PIQFeVUwRHg352Wbg6Ib55l1QbCc8HTkkOYOkh3auxzkLkgSO/EASx8fHsSXGvWo6nY5KdtanVqtFvVYul5vaZsQ4XbglTSEqrmQIzMEA7XZbT58+nXpXFBcUltwH6etHlwBk8IsvvtDh4aEODg7iaO+VlRX97Gc/i2xqv9/XD3/4Q7148UJnZ2exa/7o6Ei5XG6Kj6FBP7sSXG5QVB+vH95wcHCgL774ImTWkyYkdDzEBYmA/lKpVByO+ezZM71580Z7e3txVJp03a6H6uxOpxMb49mnV6vVNBgMosFbu93W1taWtre3Yywe0rEO7lDcELvsInvfdH2rUXrz5o3u3r0b3tu5i2RsjKWnfQObLkulkj788EOtrKzo93//97W3txdbKz755JPwXP1+X5VKRR999JHu3r07pVx4dzZxZrPZ2GCJlff0J2X3DuGZKLZM+MInJ9g9N3AYxRoMBnEkdzab1enpqV69ehUbZgmHaCM7M3N9jA4dGhkfBCJCRC3M+vp6cGd4LowQfF0qlZrKbjBWtr8kQzA3cBh5FNhrzxBO3nd/fz8Qa3JT5Wg0ClTL3NKHnB5HKysr2traitM2yF55Vg7B9bohRxL8nue32+0wKsgf84nMkEFyL06Kend3V0dHR9FjiH5XOIPh8HqLzF/8xV8EqmBDMjVKkmITLONuNBrhdKrVqjKZTByr5NlI5hqdqtfrGgwGOj4+1u7ubsiRK7pHK66LSU43k8mo3W7r8ePHevLkSXBkV1dX2tjY0M7Ojv7G3/gbwQem02l9+OGH0d+LTcZQJxzLTTa8UqmEceGdPKvoTtAda/Kdfyej9Pbt2xi8W2OEaDi82RuDt4BIpdMknjWVSkUPG9K+fJ4Y3WE/+8BAJZwWy2eo32HRnK9wYpHxYsFpR8vlYZtbdvfiTC7dIo+OjiJDc3Z2psFgEOeou6FmcTzzgWJTXzMYDKIdBY3TOBueDCTCzXu4crsCE974kUouQE6i83u8HuNm/x675tmECzImLMcBgQYxdPBltVpN+/v72t/f1+bmZtRokUVNZjyd1/PUuRtvnumZKOcwfV0hfzEGdEVFNvL5fGR1WaNmsxkGGKqBOTw+Ptb6+rru3r07JW+0jWUuPAkiacrwOt3BO7548UKtVisctRPZyJ2H4Tga597oF5VKpfT69Wu9evUqelLRajeXy2l1dVUfffRRcLKnp6fa2tqK9c5mszo5OYlN1exTPDk5CedFVwsOp8Uw8s44StcBpzocANx2vdMJuUdHR7p7924oqtdsEOpgMem2uLS0pK2tLc3Pz6tWq0V/b9+ZneRCeDmycGRpED6yBZy6AEHuHsWNJQLr5fsovwuM1wy5V0vG/RhgBKdUKkU738vLy4D6voUD4SI5gBBDluIB/Z0Za6/X03g8jn1PzFHSALPwV1dXkTmCs2LOXRng3Hw7CONA6emSORrdnBeGEcHoEK4Ph8NYG4wSZPhkMomjxSuVSpCndGJwr38bGc67MjcglWS46llMZJGwEYdwdnYWBPiHH36ocrkcjfhQlFKppLt370Y46zV3vh3Gw6e5ubmpFsYcvAihi1I6x+kG7c2bN9EXyS+Xaf52isKRZ6PRCGP64sUL9ft9VatV5XK56JX1/Pnz6GDBceZffvlldMkcja5PVz4+Po6sWz6f1/z8vBqNht68eaPJZKK1tbXoHeaV/tJNiU1SJz20+53Dt1arpb29vSCWIcV4GMrlzPxkMglPD6k5mVy3h2DivZ4JNOFtT2j45ZssqQdBIJMGhPDRC818TJPJJIoz/dkYEN4Dr+kkOAoIb0BvpUqlErAX4+IeEQOQ5KQIE3g3kCKpX+mmQwNpdjdIZDZ83i8uLnRwcKCDg4MwvC4Q/D/Jt7lHxivPzs5qc3NTlUoljliSbnr3JIXLM0m0J2GNlpaWwhCTovb1QR54ho8HA+DHXJNx9PfxENZDOEJlkBKtVLa3t6c2CGNocWRs2AV9cR+e7+tAHRMJF7hEH6Okr2Ti0ul0ZKP9cmqBz7uOOZoEqfMHFLm1tRXHfC8sLOjNmzc6PDzUycmJ/sW/+BcR+dC/iaOllpaW4u9Hjx5N9bSnfxJbUwApzms6wnUKIQlkvul6J6L77du3evToUXRI9LgWz+MTOTc3p1wuFwtHZgwY3e12w8PSH2g0uu55DddAHYW3ogA1+fYVvIdnepKlAAg7XBDC6QLDvz0F6xuCMQKkOlk8toLw7p1OJ0JToDxzlMlk4rRcBC2Z6UIZaGUBKkiGoOyd47skCur1ehzCwDuBGnk/SfEulAGADCDhCZUJM9vtdry7X6BMsoO8E0hhbm4uMotkZJEX1iqVSsVcMWY3kHQDpZTCjTzvxs+QJYwQCAVFyWaz0fo2nU6Hgc1kMsGN8QcZdzTr6MnLJfzwCvgsZDnJaXINh0O9ffv2K0Y1WVvn9UcYEe6HnE0mk+haWq1Wp3ZZLC4uan19PQw75wPCHdKyZH19PbpeYJhHo1E0/sNog4qT3CXjR0YAJFygaw9tb7veqUvAmzdvdHBwEN0NGZgrsBPBDNI74GUyN+fdo1zAfBSXojQ26HoLCowa93VyGsThwszYPRSgFsoLxZxIHI9vqoUJh0Aont6cnZ1VqVQKOM/CI3Sj0XVjNJqyOU+AEfZwgDklPIPb8vSuCzbK7CHZYDCY6ubIvB0cHOjOnTtTu8Mx3nArvB+hKS0tUDKOMKJFL5wShpTwB2H2Y7i9+rtYLOr09HQK4oMAUKzbBL1Wq2l3dzeMvfN9KKmHy8iLPweUgcFnLlOpVDjQTCYTNANhIpFBs9nUxcVFzIk7TIpViRwchbozTiJmMrYuf44ekzwNMsLaE87CVa6urmp1dVX1el21Wi0QDj3Z19fXYxwYV2SOdi1uwNEbMonUbcExu34h9054u66DRt3oft31Tl0CWq2WvvjiizizDcLaCUYGyULdtgcNAaHpP4NDyDlixpEHL+hcA0gKJcOQ+M5kj/2do6GADCKYUCxJuHoGj5ADhfbtFB52eNnB3NxcKBrpVeesUEhp+pgj3tERSTKExOP4+11dXQXS9EX/+OOPtba2FoiG5/Ld8/Nzzc3NBYFNGOJhdyZzc2go68XJFxhvDDUZQ9bEEWaytQdzzO+9+NErrZ89e6Z2uz2VZWWtMBQ+FygzRoL5ZM5APXyOe2KcxuNxHAMOchyPx1MdF1Fk+jjxThhNnonseDiHfL59+3aKtPf3Qt6cnqCa3Z2S82ccO1apVCKh4x0PMNTcW1KMD17UnQO/p6UOnSYdfSbDSWTGKQyeRT/335lTYrI+//xz3b9/Xx999FF4Gq+cxnA4gmJCPPzgNBQ8biaTiaOafAc5SoL3xTp7Bbf/nskkfuW5jjJIcxICIEhkaLDufJ/fM7m8p/TV7o5Mvo8d5OEHDTAuYC3C7Wl7N9jOl4FwbuNUut2u6vX6lIOQrks6Xr16pUePHsV6YgQZL4KEoA+Hw68cxe4ebzS67jUO6qSzJgacsNC3EHnXTb8fvJnLkDugs7OzCHE8k8PFMyk8TW7dcUS5uLgYG2f5vReQ4mCcs/Ruj2zNIRT3EBIDK03vh8Q4OapNpVLqdDra398PuU4aLOaK+yEXLnNODUAl8J4cjQaPi/Hnu+PxTSEjCaButxvr5WE4zeGY12w2O7VHkvvgMD3BxDoOh8Mw8h7S3Xa9U+uSVOq64PDnP/+51tfXo2bIu+CBAjxmTCoUC+WpbN81jyXn33h3DAWCwCK68CUzZsmyBRTg7OxsKranIwDfd2VKp9MhwO5ZHCEi0B4yws3QSpaFQ2GZB0lTRo55QlE8hYoX5V3cEw2Hwzgeye8hXW9Z+Oyzz6JJmRssBJv5QqHx+MwdY4AP5JilyWQydXADPB2lA873pNPpkBmMLkbP+UiXl/F4PMV9uEzy7vQzX1xcnJI/l0HmGWrAn+V8pIdtyIVzmY7UGYcrOGOCN4MP864TPPvg4CBOzUmGrB4FJNE1R8w78e17TeGSOOUWhwX3hPww3larFT/HoPDeGCTCY+dyXW6Yy2Sk4jrCySsQ8990vRNSQviOjo70+PFjLS8vh8V2JOTVq07KStO7pGl3geC4gnExOW5cklXlHhpyn2RqmH+jBO7NJEWBpT+L+3h9kn/HjTHjcUPhCs3zPQRj8Rmz8w8+5843OVxOGmPQBHyVj3k0GsWRQL/3e78XBzo6ypVuMpl4QYh0xkb4y0GN1MSQEaWSHwOEEUI+QCiOaMlkumfmvRg/4+B3LvQ+LklfoQUIM7h3MrT7ujAD2fN9bJ48wVA5wnH5Zc0wzDwHp9rr9eKIIq8/SnJpbnzhvAAI8/PzU6EuBhWnjWHh5GeMLjVsGBOO8ZZuulRCTziyR/aQX59L6SYRxDjd2I7H19tyHC1/0/XOTd74t0NOwgBfEOdHpJvOAe7BOYM+GZM6OkDgiJk9XGRMPgEYAW8VweTxXEIFHzMTRfaE5znJTlrYSwSYWA95PF53zoHPSTfQGOTkxilZs+MC71XQyVqx4+NjHRwcTDkIvkupxdOnT+PQBg81mE8MGQgWbsSzmb69hOwLRon7kL3hGS7UzmlgGJzYdQXl/2T1knLmiguCk24chicRvOjUkTbv6uOket7XOcn1eDGkhyIux472PCUuSfV6XQcHB/HzZEjK5Y7dQ25Jgfj5OeNwvtBRHAWP0CYkYiaTSRRBIp+8H+/IfTwacIOO83Jkz+ekaxtAGPltHQKkd0RKXA7jWRwyLfwcpXPD5MqazMo4miGzwHe8BooJS6WuSwUQKDZfJvkB5wicCL9t4ZNFigggJKDXCHmfHifAnQuRFAQoKIJFYx5dCEFWrgw8V7rJarjAe+j26tWrOJ7KORvppr6FDcJsf0iGujzPMyZcvFs2mw0yuFwux1pg6HxtRqORTk9Pw4h61jCdTk9VkTsPxNxieJG1JJL2z9KXijlweeXdQEtulJA/lA9HSylDElm5wrlRcyVNIlnWlbVjwy0n5N6GtFwukD3Gjxzwh53+hEjJpIzXZznZT/0YOjwajaZkm7WSbvZ3JuXP1yeJfly+vCsHLYq+6Xpno4RH4k82m422qxgDXtrT2l6RzcKRTnWo77U0PjGS4oQIFyyH8V4e4JYd8hpP4jGvTx6QWlIUZzLhLITPg/Nb0nSnTcoTWGA/wcUF11Ov3NcRkHto/xyf5XfNZjNOYeVyxfD5BLVinN3jc6GwhIHMGVkYsmxey+JeFfRAaMYaeMLBhZxne8jvn0Hok2Eb19XVlcrlssbjcbQ2wej64QmENMmaOu6N3LpRc36PcRF+unHlvcjIulN0ozWZXNdzHR8fx7w4X5h8R+TKnaOk0DvmHXn0jqHcF+QPSmJtPWGE/jl3hry4g/TsKM/3DG3yHRgLBDdrCvf4ddc791PiDwx7Lpebyga4QvFSKCovRYaGwbqRcWHj3xgp+Ag8htd7OELxuN/DBL6TrBORrjsJViqV2FrBHiF4BMhT52H8nZLGVdKUp+W7CDcGiQUCXXhmI5PJxLwinEkCl+++fPkyaot4L4/1+ZwrFELB3DBOCH/vncRckn1idznfvy27yrwsLS2FYtLVEYfmJK07leS8JjM1SWN7dnY2VV+Dc+GIdzeA6XQ6MmgYWuTa+zq57LrR9gwhY3EnRkdKEiQeuvEd+DrXKTfILpv054avIQqBOPfQH31JGkGfNyIN1gKdTTpwN8IeejM2X3f/w++8VMYPk2UTsMv2bVfq62Dxvx3AN2/n/e767vru+u76La/JZPJVIk3vgJT+t//tf4szoOj34/CPP1hth8meTbGBTJHQTqR61stDpGRWxu/B31ROexU1XqnZbEZ6/vXr13r79q263a6ePn2qP/mTP4mUNn/jhUA38GBJ3sMRHgiIy0lBQhl/Nw/B8LT8AVFASOJdqCWhoO/y8lK9Xk+ffPKJPvnkE/V6vfCyS0tLev78uf71v/7XWlpamqo14d08tAbqu9dLJh74TDIEhWvD47vH5vKfsWa8I3/TqZPiTI7ErtVqevbsmZ49exY1ZjMzMzo4OFCxWAyaYGVlRX/37/5d/c2/+Td19+7dSCYks22OeJPkOvLo5DTf4z78nvUDFSSznsyZV6+DSnxtqds7PT2NDNp//9//91peXo65o9vGH/3RH+m//C//S21tbUUGmzVL1tx5aY2P18taPDzm3Vx2eQ9H+x7KMT7nbcmYsnOi2+2q3W7H4aWTyUT/9X/9X3+tzXmnim4XMGJchDqpZMkUp8fkSXLRF5t7+zO5h8eqbgicl3Bj5QLoNUR8xzNlPtFuiJKCCLfikNbH4Bef8S0ObtDc+LogM4fUtsCDsUPeC9Z83n0chGHMpRvY5BiZG+7ppQ3+OebJx+t8m2/QRundgKEkfM+dEkkKDJMbxuT7OU/jykJ43m63p3hMSV9xfBgUQiv/rBsPT/l7Zol3ICHAPQnJPAxNEsTJzpHOIyZlGnng8mcwZp9fHxdhupdZ8BxCTpyE88DwctyPEg7f4O76j1zQMwyDmOQKk47Onfdt1zsdHOBK6y+X9PY82NPwScFyItCzAbwwk+nGJLlgCJlP2mg0+kodDM/1MUg3Z3BJmkrN30amJpXVlYGfJ2s2fIzwTb4dwfm0pGBNJpOopkbAPMGAMvBexPDu4dl24MLo8+cVyChWMkHgPF0SyTlPhqL5fjIvwgQV8DxvzYJndWV3Bfaqd38ucoJiIujU/SQLFVEwlE66KVVxZ4RMoHQotGc+eR8cBCSydy9AX5An1hquEb4SOfStKS5j7hwwShxThqFIp9ORWQOJcE+Ag0c2fB6ZYE79kE3eDaRDt1Hei8Z3rD0nL7MVyfUL2UQnPHv/ddc7Ed14Dl4KZcL7uWK6wiQXCAOGt3TC0L2Fox43ECgews59EGiyD0lv52EYguZFlMmsl8NXR13+PIfsDnmBxwjXcDiMNLk/g/HwOTeu3h7Vn++K60S5zxmK5k3ueK4jIsJKR4IIJM9xx4CH9qOZqMViDr1UBMVxBSbM5v9JFI6x9qrr5PowFkcTvIM7zaTB7Xa7EQJPJpP4m0SDb5B2o4Yx5H0Jt0izo7hsVvYSBu7JMeEUJ7qBxciSRPI5TxpXTiGmhIWaqmazGd0v3HHxXFoS+3FYni1FJ+k+SRhN7zEa2CE/1N+x0Zc9gSAwHI+jaEdHv7NRkm4qXL2oypWLSXAvzu9deFwJGRgTxUKNx+MpeOotLfAAfNdrKfgdBskFNZnl8EliPNRNwXG4J2T8lMjDeySFCAVaWlqaEqikAnpc7ogPhORIyY0kBsZrvVAq5hEFYo7ccLonRIAZJ7UkFNdhRDBy3j8cT+lGSlK0B2Y9QRE0V2MfIH8zD769ASQxNzcXBYLMdbJrg3RjAMmaXl5eRrOzyeS6GJKe7LTugKODq6GYF8Vy5+vhG+tFC+B2ux1FiCguRhe5c6XFMLGmyCNriSxigGmvglzSpePw8DD25WUyGTUaDR0fH8fcsu48m46uHJtEuOWIl3nGCHU6nZB15gxDjo7xTryf10gxf8gDdiDJ4d12vXNFtyuSeyBHDUBKFMoLvRAgIDBIC/LVLbfHnigI90dhMYxJqEuM6xDf+SiU1BGT1zJBIiNcjIf0JsLI7/kMZfnU8VBWQDkDkN3DRp6P8rLPC+PBzyk44/4Uec7OzsYu//n5+eg9DlqTbhrFwbnQLsbDVYQZEp2tB87BINC0/OUPBtcNOKl2BBkl9s3YEPU8B4UtFAqhjDQ/gwD20BLFLZfLEVItLCzo9PRUL168CHnL5XLRsubk5CTarFBfs7CwEO9WLBZDgTnGiRDT97LRYJ/eVY5ySblTKkBh6Xg8DkfA/2lxPJlMYlwgHEmxzQW5mZ+f19XVlQ4ODqbq4Vg35ggUjH61Wi0VCgWVy+Upx4YMoX84ZNaJfZusqeuwn56Cw3b+lHdAhtEjpzF+a6OUJBgp6XciDKFkYvxoaYSaCfRG6uyzwmCArFAW7uXZGYSZMIbvErPDEVFJTSGfIyPqSVhwapRY3F6vp7Ozs5hICFngLYrmYQcCSON8UEUul1OhUIhtNcn9PxifdrsdPZrxUHRDROFALIVCIapwmXfphjubTK47f7IliMyHvx8KhDEGQTnCYp4ROgR2YWFBxWIx+CMvSERm4G/YL+c7xMnOsBbwGciTh3D8jK6TrEcyocI4xuOxjo6Owon5YYte5Mq9PbvJIReSAnnRqgRDn0qlAkWQgEDB6UmEMaDdB4bJyWVQqJ8K4vLEGnDxDDhHquU5OGN1dTUMPO+LDA8G173HR6NRyCQtanzDsXR9KAM6g/NmXj1LvbKyEu/qWUmcqvOP3mNqMpnEwZ1fd72TUXJW3mNPFgSojvAB8xgMMJ8WJYQ3xKSesvUwC/TgPZ9dafGaENWULiAgCBwKy4LBpbDYeD/gOM/j/R2KM24a1jkRzTM85Eun07EfzKEsxiPJSQCVXfHYVOlCiaePhbRq3HQ6Hcrl64c350gqScE5oKTj8TjCLQ9RUXyMFeeHgXJ4T8KRweBm86cfyonjwGuiwE5cEzqi2K7EzktK1ygKlArH5RnKVCqlUqmktbW1+AwIDieAArJHK5fLRR9xHABzn81m1Ww2Y4zIKhnATCYz1cmR5mjwsITnhEi8h+9JdATrWUic/3h8ffwYzfhWVlbiNFvW+vj4WLVaLRyby3i1Wo3NuugiY/M+YV4yIimigPX1dW1ubkY4Kd30kup2u3G+HPPBmqATTvH8VkbJYSv1PggbA4eUZrGBkb61I5W63qx5enoaKKJYLKpcLkcTeQ+zEBKabXGMMsjCX9JfHIVFwF0xR6NRjI3vuzLwh5oXhNiFEm/Q7XanyM1kPQeK4/F3MhNGPQ4ZDjgejCwCTh8gSTGnIDeIRenGw7qhAa3yTPgTuiUC4VOpVBgQGs1jnPz7IGbCBOfQvDKd1rx4TuYRQYcTgYvwOia+gzHsdrtT2UnnKJLr4lnicrmsYrE4pbTz8/Pq9/uxKbZer4csI7+EjRxSwR4x5MYTGc6rjkYjLS0tqVwua2trSzs7O7HZFXl2Z856up75RZQh3YT76AnhJi1pkBGcAnoKR5vJZCJERw74g7FLhlaEr84rYgRXVlYCCXl5jXOddOCAUknq3NfanG/8raa3IjhZ6QVk7BlCGZwIduFKKglxN1kKR0wIACEHYSKeloUiJGRCPabGQDBuDEeS8CakwIggiLlcbqpTIoLoKWxQDXA1ua0Bw+LnsvNcDuZEKdhc6UVvCJvzDHg1vs98Ms+gEElTYedoNAq+BETpJRzMJYrg5KavtScwFhcXVSwWAwk7b8e9Qa5O/vN/EKQrNkrf7/enjJmXbLB+5XI5iG06aGYymXCGt2WdpOnz/Lgn/a5wXAsLC2HAkSNPWDAPKCaGtlQqaXl5WYVCQTMzMxHGgohB+6wJcpncm5ekB0AfjIWxErYlj+HCyCGfICIQDOvC+npSBZ3neThWDkdg8zfID84QeUPvSSK5Q/ZQ/7brnZASgo9ByWazcRZZMpXpYQdwHWvtWTQMgMfubnl5lnsWMj2+iAicvzje+7YGW1huz2g5ge69ckBpGIdyuRyCPZlMwjM73GXivUaEs9mpHUIBMYQokPMokoI3Yg3gPphPlNCfyzx5IgCOgLn3UI49ahDYpM2lG4PmHQmTmRRCHHgKDCa9wr3+hj13rBfGFoQ1Go2mQhp3Zi7QqVQqCOy7d+9+pXEfxuXs7EzNZlNXV1cxRk4ocZ6DNZiZmYlWt+5scSQu43j/8XgcIbeH5Tg6nDlJFLg1+DXmwUse0B9XXmgC5mw4HEbfcLgpjCBy7aUsRCo4IpdPDDm6Nzc3p3K5rMFgEIc9eI1Wt9uNeQFJ9/v9qfbBhILouCe7vi0D905GiVAEVEC7CiApL1KpVDQzM6PDw8NAU3gD5xKSClQsFqMojEX0Sl/QFJbXQz3naAiBWCRCAqAn4YaTi4R+LnjAe4hSDgkgVubocBABBgoh9poer+XI5/OhPL5oXqd0W6bQ09Kgx/F4HKEBxnhm5vr4I06lkG7IUjiPXq+nRqMR81AulyPhQIjOsT+eih8OhxGCekEe6IrOj3hhn3vej/nnmGu8q5+OISnCNZ7BOvPvxcVFbWxs6OjoSJVKRdVqNeaG7CRIq9fraW1tbQrxNxoN7e/vBwIn5F9cXNTm5qaq1erU2YJeGMoF0gSFuxzs7+9rd3c3tmbhXPxZ7NhnvvxyA+U1fhhRQiEMBsaxXq+HfIKgoCwkxUknFDkiN14/R0aSRo5euwYP9umnnwb9AtmNffCwH1Ld2xS5/v/WRgkF8TqSyWQSR95AmA2Hw0iR1mq1OOYXErPf78cJJcSoGAsU1jNSoANeAiMFTMVwMPmlUilOlPXMS6FQiLEj6Ah7o9GIEA8lrtVqOjo6Cqiey+WCO2o2mzo4OIhCtfX1dW1vb8eYk6EkZ995Nz+8XDqdjjBqbm4uMmTMcbfbjXHMzl4fCrixsaHFxUWNRtc9stPpdMzp7OxsHJHN5zB+GANqeBgryKjdbqvT6US9y9u3bzUej2P8XCAJ1rxUKk2dduseHkMMjwhq8N4/u7u7Oj4+1szM9ek11Wo1iG2UzQs0QVTLy8u6c+eOPv74Y83MzOjevXtaXFzUq1ev4swyzxQjj8PhMN6RY6SWl5c1Go3iGKKHDx/GMfVuEKQbTm08Hk8hw3w+r7Ozsxjn1dWVDg8P9fjxY11cXCifz0e7l+T8eNMzQkjQTrVaDcNEDVGy7qfdbk+FTQcHB/HMnZ0dLS8va3V1VYVCQTs7O9ra2prKcGOMfDsJPJwkVSqVSAyBPE9OTvT5559rOBxqdXU1jC9rCyjw5JIXpf7OnBLQL52+OZa5Vqvp8PAwMi/A13a7rdevX0ff35WVFT148GAq4wFcz+fzkZWAgMQbSAp4WC6X47iYs7MzlUollcvlELDDw8MQqrt372ptbS1QlWeh4FmoRF1aWtLr16+nQigv6svlclP1MBcX10cz12o1tVqt4JuWlpZ0dXUV6DGfz2t9fV2zs7MqFosqFovhUTGoCOfCwkKQlCwURCm8w8nJia6urqLUoFKpBHdDvI5xwtMTgkgK9IaX5XN4dzx3u93W0dGR9vf31el0VCqVIqxDMarVqu7cuROGiW6dhNoYR+aDCmSycsPhMBwQmdFXr15Fpu3+/ftaXV2dmiOUkLnFeOXzeUkK5YZzKRaLKpVKofiVSkXNZlP1el2Hh4c6PT1Vq9UKOVhYWNB7770Xz4bDIyx2xSWjOBqNYu1IsIAICYG2tra0urqq3d3dMCbICBloEgQYUNYTg7G8vBxGMZVK6dWrV1pdXY2Wxvl8PhwNnBUk+NramtbW1rSzs6Pt7W2VSiXl8/lANb5fcTQaRYY0nU5HAmp2dlaVSiX0kqz3vXv39Pz5c71+/VpXV1dTBa/z8/NTCQznpZy/+52MEpbfG0jNzl6fnpoUeorplpaWdHl5qfX1da2urkpSeO5KpRKZLTwtiGhhYSFic+ohIHYRQBdyH8Ps7GwsGEbUBdsJ4Gq1qmq1qp///OfBW6DYa2trgZookEylUtG1sVqtqtvtBsGLBwTNlEolVSqVqWwbC0+ogtGEjykWi3rw4IEuLi7iXnfu3NHc3FwYZEIzwgHppkE/BDaGzt8dwZ1MJmHQRqNRtCeFE4RvKBQKcUJJqVSK0JojypeXl8PQI2yEeRTUecX53Nyc1tbW4qRV3i+VSmltbU3f+9731Gw2lcvlVC6XA/K7MSAkK5fL2tzcVC6Xm6okz2QyKhaL+uCDD1QoFLSysqJisRjIrN1ua29vTwsLC6rX69rY2FAmk1GlUtHq6moYkGKxGES2owkQUqfTiWOlSOrk8/lYW6++zmQyunfvngqFQpx1h2HyCmhPfPC+RAwcrU1ofn5+rmKxqNXV1ZDlyeS6+f/x8bE6nU4U2XJKcaVSiSpuQnh4XwwpRDyJBa/3g0fybTiLi4u6d++e8vl8ZPNAy175jzw4CvMC4t/aKDkPRCixtbUVhCFwdjgcamNjQ2tra1MxpfMQDLhSqQRhDA9BNo/Jcg9ZqVRULBaDgCVU+b3f+z09fPgwBJNJYLy+7YX4GkHC066vr0tSCDDe6+zsTPl8PrgWPHWlUgmymWciBJVKJcKHZHaCBQFFoLyUGzA3kiKc5ERiiGnnAVAc+DbCQLJuvDen3BJKY5SKxWJkcyjOzOVyWl1djQ2a/AxDS3gMgoBvgLiHW3SngPLAq+AlCbuq1aparVaEZyg7IRzGtVQqaTgcRsLAkymTySTWlMJOtqlQ1U0RZKPRiBIFnND6+rpyuVw4Cw954caurq4iDEWekFcydCAl1pRQjIw0a4Vj8S0tOF4vwQClgFTK5bLK5bKWl5fDQEg3yRsOTshkrg9+XV5eDt3BwEJXQCmQgEBnIeoxXN5RAOOIXMO7wRXxrqAyeFwSVwCbb2vy9k5GyeuIyKjB84CieOnV1dXIZOEZSCOSasfLkVHgJZNEmBsUMiJ4MGBmsVgM7+IcgGeCCHWGw2EYJYSa8MoF3JXHa2BImyfnhqpt57XIyuFF+D9ex8fpoRbv5nVAXgXvGUYnXwl3PbMoKUIt5gfjjMDh6TwJICnQCSETfzzNjBITfoCW3Cixlnh1J/b5OWgYRaZrJ6E1CukFlx5aDQaDqX1dSeKd+cOZ4WSQH7w684mDdP7Gs5ZednJ5eRkOi3khTCYM99o6zxy74WZdkHHmhmsymQQC5NBPMqpkRaESoA48K4rssW4kgkDxOF8vTiUZg46ho5DcVLb7nlMSV6wT8kjI+G2bcaV3MEp4cRYIYWFxyCiQBmTSgdjwEr7xEQPgtR4OKxFc7gXUZe8Pn8XQcA94BA/bmBQWHi/GguMhpRskQ8iAhwSxocju/UFXcGSe3pYUhod3wgiTGoXDIHz1RWQ8biT5HoQ+HAHGBI/GBfEO0sVIoxRe3IlHdkNIFb6HjcwRiBaBJwvkiRGcFeiGOUBgQWmgCOYZw8q7EP5zT+7rqBEuzeveIGlxIJ5CB634uJAvv4eXAqCs2Ww2djdgxIrFYoydMRWLxdALCGmMCe/jmV+vVveLe7E9BGNGKAkVgEMA8YOGnIIhecD33QhJilITNjWTZXNHQHjo7VeSDhInjkzyLL/Pbdc7bchlQbkxTDyoCWVBSCARiU1Ji3sdDkqGgLHwCKv/DJJ9eXk56k/I0HHsMRbeCxi5F7AUss0zRe51gdvssYJL8UXzZ8CbeEbPx+3GhNjcDSfZvVwup0ajEcQ8Y0aIQRW8pxe+sbkWwhVl5f0cQTFHzCkhmv8Mb813qNSmDowsmhcwkgrHKHloms1mA657LyD+3FadL91wSSASQtvkvEqaQqCsAUbX0bYXUXp2DYNBSQny7IWM7gRxiii5GzHeGefKc8mszc3NxRw6YuHeyB7P9AvH4fwOa45MOwJjbryYmfDRiW537FzMCXqRnDfnkpPRBPPHenJfnvNt17caJR8sgomx8ZDJ64eIWYnJeSFgIjFmEikhmFyk8anWJV6dTK73f/GHyXB0wgTyHBSb3+N58RwYMpTVrXmyCM0NXvIzjvJYBJ9DEBAKD7mMYktSoVAIVJrcf+aC6ptZvZKX53AhRKAK0AwZTzfovtbJEAzD7GvHMzEeg8EgHBhIhLYe+Xw+KuXxxMgC8+UI2UNVnABz5HLidTKOUjBqOEEvbkQZQcO+CRXj4SluLwT1EN/3v5FQ8LS+81OsuZcGoLxuoG8jghk7CMmRIGMgRHZngXMD3RIuYyzcKPE95t/flblCPxg/74CxQlYczbLG/O53JrodRjs0ds/lHJBPnF8OX3lBJsLDmiRJKimKzfBEIC/gY9II8LzBYBBhpf/Ox+zGBMFnUn1hkggOI8uz+JnzV57BobzAU7wsMO06KEugMA8+jjGiFJCFEMzJMNUvL5708XlCge+gXDgR/o9BpkqZ8MM5IowisuJITFLsu/JwcHFxccrQebcCUJujQ0c3yYJDN5LIBO+N8jryZn0wLMgHDtXDag9PPLwmW+ohHkbP91+6w5RuDL4rLfsp2aAtKQwwl28Lou4HOQcxuYN3PRiNRmGQoBgIV91R8nnq/9x4Mee+adgdJZ9nnfgeBhHD7wDhtuudwrekV3Lv6VkgvKynwbl4eRTYoSIK4ELnaAXBwMggOCgu3/PFQHFdkNLpdJTis+AYECcc3SD54rpA4DldSTxG9znDyCbjaeYWspVKXNqD4IWcm0F5QKocKcRz/N68A+vgvKAbVedn+I57W+Yeg8Rc+AUK8DV1o0SdC6gXQ+rlGtyHrQ8IsaMb/u2IkPVHuUDQzrM5XeDySqjHvEIYE2q6M3BjIGlqG4m3OPEkheuKI0vP9HmLF4hjXw/mxsNCnJEbaMYLz5ccP0YJeeJ9bqNSvGWQb+fiPXztkiGZUxYgQMprAAnfdL2TUXJE44VQLixugJLxKRPmYQKD516ueEw0BC3W2DfN8lzfq0aczeeZLIfennGQbrZ7YNCc0HNvwO9d8R2yMkdJYto/6yEuCkGYk8/np3bVOyfn4SVQn3t4pftt1+XlZbyfh3HO3XjI40rF5b/j3Vgj52x8viSFgs/OzsYeRgwc32EtGJOn4N07e5jhBtUVHqM3HA6jONRDQBAvCu2yi5OCMIbox0A4l5NEFc1mMzhIODjmwdFFEs2DkOjuSKaO+WGN+Tc65HvVkgYlCQxAnqBu+KRkaI7z8wTF+fm5arVaGFHnrjyCYP5ZN5ebbrcbYMK3LX3T9U7hmzPzIB0WyT/nYRGTyOQDgVEoR0d4K/di/Gx2dnaKgKR4Em/lnIMTkZ5tYIKSvALC4qnSyWQSxoDPO9R3JeC+9HkiNEXxfY74riuuG1YKSU9PTyM5QAW9IwnGA5fAmvg6zMzMfKVYzUMBL0FI8jhJcpUxYxSc7E8iLATUFYMwjc6KvhHYjRGy4OUSGJYk/+gG38N1P2YLfoWQJ6m0OCkSJ+fn5yqXy1PtYv39fP1xFMjd5eWlTk5OYssPSvx1qJt38l0EZLB983TS6Pjaw30l5cLfi71/hKPwvIwBueLfznOiC4PBQLVaLTgs5jTJIXE5dcFY/Y/X7X3d9a1Gyds1QP4hmJ6Rc74GmM3k0HuI7QRJ2ClN7x5mgvgsC+PnkWPZk0QyyuPEJT+HIMxkMhH20GKBTBoK6ql9J/64Px6P1qhsraEVrr+jh8DutTFK2Ww2eii3Wi212+3YAuEI4jblciSZNF4+H/45D5+4GAufc9TKHrLT09PI4PjOb97HjTkGh/oh9gv2+/2onUKo3fPi8JLdCp1kdu4M+ZM0ZZSoU+OdWAuUBY6DvuQU+0ma4lRwbl5giOMBOc3Ozur09FS1Wi1KNTACzCcOhPE7wY/Tx2nzWTdkrAPjIGvKPDBWZPTs7EzHx8eSrivDGQMb5FOpVCA07+jqe/GoyG+1Wjo8PAx0RnEweut8lr+jh4AYX88mf931rUbJW2qCQHzXNMYEQUFhqeFoNpsxOaCBJCQlfeykmqSoBSL9eHFxoXq9PkXs5nK5EFbPIjh5nozlJYW19mZ1Lsi3hXrAfCz+5eVl7KnqdDpaW1tToVCYSqt7yArcxQt7mpZaLnptn5ychJF09OkZTCdXUV4nXSVNhTK+zwoYnwzT+D7/Hwyu+zbV6/UoFHTD5SlfFNRJYz8I0zuWYvRZExQRxWJPXhK5SV9Nrkg3hpF9mBzM6aiFecFZdbvd6AaRzWaj26hXpl9dXanT6ej4+FhHR0dRu9Pv96eM2MXFhWq12lQ/KuYQg+J8JIbPuzBwH+cAudAtDC+GGqedzWbju8Ph9b5QjCTG6OLiYspY9vv92GDbaDQk3Wy6piaQfZHoCHOOTaAswNfGDSz34N3+nRglFooJ9YdCguHF6fczGo2i8+Dh4aGazWa0BkWAXJG8UA2hBcrzeXaS7+7uTiExkAY1Mngdb26G8rtAogTeIgXBoSDUiUW+gxHD4PKOl5eXKpVKUS2MQXFj6UpIRgh+wFufZjIZnZycTPEgfD8JiZ2A5TMQ2bwfKXHWDc4j6Ymd0HWnQksM0ATr5ZyiG06vWSEkgL8AWWYymdin6HVlbvg9TY4D87nkcrQE8uG+zIUXsKLc9Xpdx8fHGo/HarfbevPmTbQtodjz8vJStVpN+/v7gfaYT3YqMGe0gmWdMSyOUp1bSm4GRx48JHUDR2YOlAQfClHvcn9ychKHc0KZrK2txTaddDodHRRqtdrU2DBMGFgOkmi1WlN0xMLCQiQavFqdNYTaAGnyvrc5mr+UUaI40VPTXheC52SSgc+NRkP1ej08LBsX4RRiAP82lexHUfPHm7MjfMPhMJAX46E5fDKOpc0skJgxo4CSYmd1JpOJWBiF9hKB0WgURpdmXcfHx2o0Gup0Opqfn1ej0VA+n1cqlYq+MtSuYGThWNjWgLHDs8G9NJtNSTeFaygin2dXOPOJ8GJYEB7S1pKmUCqfJbRhbp1j63a72t/f1/HxcYTTPB9SMxnCgaxZs1arFRtFWf92uz2VAZJujrByrs4ztTg7TzdLN21icVRksbya2SkAFKbT6ejw8FD1ej32jHESCnzewsKCRqORTk5O4j1ozSxd9yfa3Nyc6kSBfPAOhEC8iztN5gNOySv0WS/uM5lMoiMAxoLoxZ3c1dWVTk5OQpYWFhYC6e7v70/1scdBsDmberJsNqvV1VVtb29PtWKeTCZqt9th7Nn7BshwHtMRL8aU7We/s1FCuQlHUAB4DmJvjFKn04n4ml4v9FRqNpuhrMPhMLZo5HK5sMJ4nV6vF5PLRKFUoDDCDwTIF8+9D+jm9PQ0hBRPS4mBVwDjZXknvBJeqN1uB+QF+ns/poODA52enurg4EDtdluzs7NaXl6Ocn2QFIZqOLxu2LW7uxuowHejS4rnsOgQoyw0hs85NIwSjsOVHZ4JBEFKHXRCs7Cjo6OoL+IUDZAFXTnhGh1hYCTphY3Xxmh6hT/oDkEGyThy9c/hGHkffofBdNmAAsB441xqtZrq9boGg4F2dna0uLio58+f6/nz54GSKaL0I7cgeuFKQatkGR31TiaTCOd93pFN1tGRZZKfde5sNLruzMlmeGSJqGE0ui40bjabajabIXfLy8vq9Xo6OjrSYDCYMjSgf4wq88apN3S/ABUyBgwLm26RSwyv0ziUufg8/E5GiZsC6+hXnEyHgyJohkasThe7paUldbtdHR4eam9vT6enpyoWi6pWq9FTCOOVyWQCgtKQa35+XisrK5EdOD09DUXybgQItceyGBTP/HGx4x+BwvDiaUEEwFDORWs0GtHYi0bxvOPr16+1u7urk5OTWHCMEgIBQiFxUK/XIyQATdH3hznGczoadM/jXB3X2dnZVJYFbuni4iKUy7kmPCawnh383Ov09FSnp6d69eqV9vb2tLS0pPX19Vg/7wqRTqfVbrd1cHAQ64SRcbRI2IYQs3ZwEq6sHnJKN433pRuyt9PpxLt5zRGhH+fAXVxcRDsa2pYcHR3FIRXSza4C5g8jRwkAfacIoxw1kBhw/s7rr9z4+jqClJxTkhRjx5iykdiNfbfbVavV0nA4jDYz8/PXZ79RB0eLEi/B4J3YrM4OCrpXgPIh0SnwxLkxbtYXw8Q6evY3uYbJ61uNklfYsi/MU4vARvajkaU5OzsL78nkgFqAwJ1OJxqmuedEaeiICErCCBKuQcCdnZ3F5lhpep+SlwkQMrhRYsIIk7gH2TNCB97v9PRUnU4ndlQvLi5qdXVV5XI5hB9BhsAntmbuQCdOpl9eXvefQgjy+Xy0rsUoJQ0vxhdh8PonLsImECKK41kTL6e4uLg+Kffo6EjNZlPZbDZS5ZJ0fHysvb09vXr1KpIOnU5natOml0IQEtAhAplqt9tTRgkBv21fHOtImJnMtiYzjp5ZLRaLwX0yz8jf/Px8NJUbj8cqFAq6d++e0ul0oHrmDpkvlUrBYWKIkDcUfX5+PniUfr8f/BnzDGfp1eyelAEZJpUXJ0zH1eXl5ZAJDDo6s7BwczZbOp2O3lGZTEbtdnsqgYLB8Up23iMpUxDnfnQ56+7JMMpjnLIhc+zE+G9llPBcnuLFSCAcWF8/4yudTke7Czolzs5ed7LjID1SksBlr1viedQlkWqlOI3uicBMqoedY3DilglxdCcpGtzjNYContrG6JI6BV15Ww/6Bc3Pz2trayvqOwhXQVxOuks3u/gxymQ0CGtBnnhGL1XA8+NhvaocgUP44R4w7l50iiIQTtCDfDK5bpexubkZLY9xBKlUKhrLTSaTcETIBReGGMOGE2HtkAvpppeQ15i5wjq5zTOcePWkgCc4yDYmM27b29thbJmj7e1tLSws6OTkRHt7e0E1IBvs0MfZEDJ5+QHbsGZmZtRut+MEE0e9SaV1o4TSJsMcZBd9Gw6HsUWJcUBas2bMzdzcnO7duxeoDm6IezJmDIwngzyBgiOG1+z3+1On/pDk8nXzglFfu6+7vtUo4akIQwaDQRgGt4oIGg+kvxChGYOpVqvheVqt1lSzf77rhofMG1wR3gghg5DlcERKCzzb5aUHyboqCDi8w9XV1VTGDa9NaMp3M5lM9JUB3qJItDHN5XKq1+tqNpvhOT27QpWtKxbPdMG/vLwM/orNlMnLU/PSTQjHaaXJ7QJO4qMUOAl6l9MAbXl5OZDG+vp6hA/wLMxHsjiWpnNe8Ep4zHzi6JA1whtkC8Vl3ZLFesxb8mKdcIAYLXoA0RXVyxFGo+ueTnRLHY1GqtVqUWOXLIPAeNDqw50qBiyXy2lvb09HR0exLYrx4ewxiIyRCw6GCzmZnZ2NTJ8XtkLEb21tqVqtBgebSl23xVlbWwudolrdw2NoBZ/X2+qqHDHiwLxGjXvybzeut61V8nrn1iXUQUDieQkAx/AMh8Pw5iw6/ZOxvnNzc9rY2AgCjRQuBo0FRfm8OMzRFLE01v74+DjgNuN1XoDvJcMbL1jD4/AsMn9eG8Lk03bV+0N5JfXKykoQ+YVCITgyJxUxvIzJQ8vRaBTzQOKg0+mEVyMc8++4EHF5vQ6ZILyae3tCjdPTU52fn8dJqBx8wH3z+bzu3bun+fn5qSODuD9okRDHa1uclwQxoeygHJycKy3f529fQw/luByFOrGKAZidnY1DCiSFQQANkG2mOycO9+LiIlr1IicYJ9bBt6UQhm9ubkbiBu6NMXoBJXKerMGSbohueE4iBfg56ebAjdXV1TixhPdHbuhxPhpdn+oCOnZU41EFY8L4UcJCD7HFxUU9e/ZMvV4v6AsvQ8DguYz/zuGbhxRMFEgEQSOFjDKzwdSzaQgeBCEGBajMpPp9WFwn5EBLhHberrPVagXKcs5BukEhTAwX9waaojgYK3gyECICC8FJ8djFxUUgj+FwGAQrygbsZlHwyiy8cyV8B0TokJ33Qhl4fwSANXPS1Gt7vOcPyuhQ/OLiQsvLy9ra2tLy8nKkqF0p8LiQqpxiw3NAt4QrELvMA6E9IR8G2ud9PL7phOBGyENvriSnxLqnUjeHRXi4iqHl2cnQHqdHg39QAugClOnteyjPcDQEes5ms9rc3JxSfvghxp2UV0kRWjpacUdLrRhjoQEcHSdYN+YN9F0qlUK20V+QPO9G1T/yAd1CMgjdKZfL2t7e1suXL8Mw8Ty+5/wpkdc3Xe8UvjlB7NWu1EpgRBDCfr8fR71wrhgxNgvABGJoMAYsIi8G/yHdkNJMMIvBAsJPMCF4RSf1kkKAR+c9WGSe74KQRFj9fj+eR1Gi8wLMGYQoxphMhGfhnIhl3jEctBglRY0R9a0nSdiPcLvXBV05oUpGB8NbLBa1s7Oj1dXVgP8e0oIE/Oww3oNz3Eaj0VRbXIwB2RgSCqVSSUdHRzo9PZ1SPP7wDh6uupNJrgnrzO9If0NSs8eQ3fz066ZYkM6NoL58Ph+og8MwUDTviIBDc6oDPss3wBaLxVBIDBKXGw/kzSuf3anjPLk3ckGZTSqVUqPRiDY4OEhkjrMMx+NxcMQ8kzX1cXk4NhgMgrRH/0FftVptKnHC+iSzprfRD369U52SK5YbIS+Ac09ELQOFU4VCQYPBzb433z4wNzcXJ4IQHiaNgKcX8TaMCRRHah7F9qyOe0Np2hthAJlkDB1cA9kyJhMldo4B4UD4QCpA2JmZ65NIQAJe3cpY+Lz3KoKropOn817JvWusQ/JiTCgD/8ebQ9wPh9f7tdbW1qL0AqXgXX0LCXNEpsk7KPrlYSaKBXFMeEOhH04PLinJITHfHqK6QfbwHIVJrvWdO3cC2bBnMZW6rnaGOmANSYlfXFzEUU1kXr2uivUjK3V+fq75+fnIOJIIyWQy0R6Xeq9k6OmhXBIROoqGEiG05nQdQvFer6dWq6Vut6tKpRLUCXK8srKixcVFtdvtKLDk3hgSbxsD59jpdIJDY35JAqysrIRBorYQeXbn8W3XO+198y6STBbKRuYIToiJxoC8efNGmUwmCrAIuVAqIKV0s9G21+tNZaoymYyOj4/DUwGt4VY8m0RmjAkGUfjEJJGSTxieJp1OT/FF7n2BxryjH5njJLIrJL+nmJF7eVEmxoF5RUkQOsJEEEGSS+LyEId1w4HgXMgWUoG9tLSkarUamRV4HebmNg6HcAxZIIMDcuB7nvJnzp2b8K1MhEpcvja3hTi8u/NpfAcF5V2z2WxUXyNHyEy9XletVot7s6ZwmxQlgkC8TszRKHJBnRRbppABL2Llbw9nPLxJhqOsrX/Xs60kWEiKYJwODg6CM/P3AuWzPskCR+YSxO5It9FoxPFNuVwusrHoL7wSz3VO8HcO3yjZlzQVOgAV6ZxIRgVhAzH1ej3t7e0FoU1q2z02HhgveXZ2FpXhoIODgwMtLCyoWq1GQRh8AUrHSyOgPhZX3CSndJvCkRXyvjqevqXkf3d3N2pCpOm+NKCdyWQyde7W+fl51Gml02n1ej3t7u5qNLo+bXVlZSWMN0aEMNR5Gy6MFAKfNLKegQRVYiDhc4rFYqTsyThJijlgLEn+yrfOEPLgGPi9dEMmO3pBYZkjFA0Dwjo4OrgtUeGXKy1UAjIGsiEBAS8Icm2329rd3dXR0VHMHUpMWQgcKeE5xYMeFrEm3jaF94LYdvKd9+beTpa7nLrRxZh5sel4PI6MHzLX7/fVarX06tUr7e/vS9LUGX+cC+ilI15zmOSAkSNvnUPU4qGqG9ukQUqGrsnrnTbk+gkhXp6OctCkjPDOszzZbFYfffSRDg4OtLe3F7uRfX/MeDwOko0Lz5RKpVQqlbS6uhp/IOCwwl4jwT3hfDgtlYX3MIJxJL0xP+M0loWFhakTWwjPlpeXdXJyEjCXHeTLy8tBHOJZ2EHOApG5whBAMFM7g9F1Tg1BuC2tehvUl26QoP8BNWWz2Qgx+Fmv1wsCejKZRKVzkuTlGaBgr2QmIwfyY075g+cEFWLEQWfcG4ThnETy3W8jvpEFxswGYEho+LB8Pj/VnfL8/FzVajVOtWWOmHtKI6AvMplMlC8QyoL6Waerq6twnITR6A7vKN10R2AHhXQ7ge//9xCr0+lE9AC3SbKp1+upWq3qs88+097e3lcKU5ljTy7BgYIUSV5h3KFsfEwgZM+asvbOz/7ORon4mwcAQVOpVEyIZ1UIDbCacAfLy8u6d++e3rx5E4Vf1M6woF7zghdjDH5Mky+WZ/YodBsOh+r1enr79q3u3Lmj1dXVr9S3JI2SK4pPMILmvIhzPalUKrJQ7CR3zobiSq9qpcZnMBjE5s3NzU1tbGyE4DOvjA2EBvrz90ga1eT/WS8QJQJIGJxKpaZ6EZ2enoZRpd8O5Kakqep66rW4N16XGjRKSCSFkcKJQSxTcImndnjva3ObMZZu0C5JBAyN8yFXV1fq9XqRbEHxkD3WdX5+Xjs7O1HewmnHcKSTyeQrfYK81i7JrXlhJOtI+MfYGKtXe/Ndf2fmwpE9iR+cHO+DQZ2ZmYmTkZeWlnT37t2pEgFoFN8Gwrh8CwkGCcTunCm6gZH0XQY4FHTrm9aR61uNEtXF3gvaW2IyySAmkAULzkVK9f33359SkMlkEgvrNRMsOhkdUu4YPqAsxJpX1p6fn8eG2VQqFVXljq6YGIh8JpZ74bl5Lze+GCoKBNfW1pROp3VycqI3b94EUeueljDBq2I3NjamtvAAq/HCjHU4HMbprF5U6ZkaF1wngjH8oDvfUkL4jRJTdcwpwBQ47u/vh9Fy5IZi++m89BWi6R3oipYZjI1Qxeuy4CJRPg+tvSrfEUaSV2NOvKYG45/JZILvIPHgzgYlxFCSqSTMhNT3cBjODtQHiid0gz/j3ZIRgodjKHpyq5MbC+aN90dnKCLGobmueESzs7Oj2dnrAyYxVoRsIHbfteCkNcQ6+gJnB2jBQWPgPIzGGAFGvun6VqM0Go1UqVRisJKmjgFGEJw85XdkWbgPsTLKQLGVGxqvDyKEcAOEMCRJT6/5oLEc2yLYMX0bLwHnwKT64mMYETKvNEfB8H4zMzPa2NjQxsZGeASMK7ukQUvD4VArKyvhvbvdbhD6LLgToqPRKGqUMJzesYF5QGmd7EXRCLVcSCQFSsEoYmilm2wjXRH29/fV6/WmCFbCVoSakAm0LF0rV6VSUaFQCOGE18II4Fld4VmTZKrf18r/n1QCEAvoBp6MbJFnEx05ozjNZlOvXr0Ko4RSOfp0NADH5MYEg+UGJSmvvt1kNBpF3zEPgXhHrxHEaGPs2u32FE/rn/XxEe5BRbgzpm6J9cVpMq8YvJmZmZAtOCb2dyILHnKjD3zmm653aoebz+dVqVR0cnISO+NR0mRtCYrISzAoFm84HAbUdLQF6Ypg+KZMh7i3XRgP6TpE2N3dDSg7HF534aPWxONmPi9Np64Z5//X3n/0Rppm6f3wFYae4cggGfSZWWnKdlV3dTe6egatwQzkIAkazFJb7fQFBK2ktb6CVtJC2kiAIAESRpDay3S1repyXZWGmbTBsAx6Msx/wfkdXvEUqyqnq/G+s6gHSJBJBiNuc+5zrnMdc5Ny4Ico2evY83fIW6IFLK9B8dBpkDwqcmRGRkaitYdHOTms1EkhEBw2UJQfwiQSxBAkkSCvw6XCqlNzB1obGRnR0tKSXnjhhXDrUqnr68Yp4MUd5eCBDEC+oEDniBgvsuHj4udJ4vomojsZwMBV4u95b1wdd3GSKQvsI+gD99URuXMprBuyjnH1z0amGcdNqRvIBi1CmId/jitl50WlKwW2v7+v0dHRKGL3M8jecNYGg0FEtN0lRFZcCcPbOrJlH5BJ3E5QYJLIZz5QK5/3PFdKAJmbnvvAhYlMHj+UPBo2y5l3Jukd6DzE7pbILYiTtL4hTB5FyMbQ7oSM2E6no6dPn6pYLMYVS04e+8NhcT/Y3QgsQ1IoGD8FtL42Xq5C8ikuHuQuQs86uaUCDrvCcsHn/8l5SAp0C1JCuJ0TJKxNJI00D0lDr0ch0gSNViR7e3vRhtYVUqfTUbPZHCKNndj17+EinEvzFBOXARd6lwseDo/zjRguyGnq7iRFkbO7lV5C5cEQ9h55A5l4YnASwSZl1RFhkkdjjfks31tfE8bLV4xPo9GIPcSY4sIyBm9xzZl1WcJYMB5kmc/2HD2XNc6ro13mjsL3yofPep6rS0C/34/0dLoAwNE4VAWCInz4105yOQMPEeoWkc3hdb1eLzgsNuimEKOTqVg5HpAGDflJaOP1SY6Cg+HC4KSpoy0E0AlyukcyPsLJTuS78mVOfIa7El5648rRXVp3k/kd7wE64ACwVnAJkobSBMjw5fEQOPwK3BKfSTM/53QwNJ6zJV0fNGSD/fN5IldJZZTce97PEQXj5SB4IiIoiMgmSNANK/uD4cBAocA5bBw+3tuDEsl9Qi7Yc2TH3ZlU6vo6d1//pLHh8zwFhO8Z59HR0VDfM99DPht3i7X2dURueW9HicnomSv85Gcgm0njClj4rOe5OCXpSmMSSaKwlMiNT5wJQ4q5dmdT0Loe8mVCwGM2nskhpDxJth9y0m8Aka4JdlyddrsdjbKkayToZSbStXLyEhfp6gCfn58P5Wz5WmEJPSWA75PhXzbZIyXMS1JYayx1kvRNHgpXbrwWd9vhPIcfEtatfJI3Qeiw6KAa9uv8/FwHBwdD9Y8+Brf6zhMhsO66nZ6eKpfLhULxw59Ep26d+RljR0nzc0cB7De8C/NK8niUQaXT6XA3WAs3YN5Xia+sNa4la8NnobTdTfR7/pLuYfJx95TzNzJy3esMw+xKlzUlGs66gtiZjxt/5DFpFPyrKyWP1nnAgbQM5uk3ptz0PFdBLgJAiPTs7EzNZjMOrmc+o2hYfA/XMgH+D6FKSJKFciFiUd0S8WBlcYkoWxgbG9Ph4WEcDl+ofr8/FDYmhwWhSlo7DlBSyXlSpisYt5qunBDmpMvlKMgFkfWjXQo8gwspeWH+fqAn9gzujv3BVfFmfcwFZQvxnUSnWLuDg4OhZFKSYiH9naPhwCTLYhxBwzPQOnhqaupTfAo8XPKQkjTI2rMuRCqd5GVM5PTQN77X64UL5sgAmaIVMIpTuk4YJHrJ9zxJV82/eqsf+Bo4OvcKPDXC3Sn20t185Jv1pLsk3JkT8yhcDJOjXD6LPeNcIPMoXlf4yIVHL7PZ7FDLX6/E+NJKqVwuh0YcHb3q+YuWh0x2AXYNykT9kOK6YEU9bwQ+CvTBQfQwJMKJ9QESenMq9+uTh4EH4SZPiHlwaClh4TCCihxB8ZokAYlwuXXy0gQOKl8RZvJ/ODzwUwcHB5FUybjdjSDcz88dKZ2fX91tNhgM4u+T+UooBxJYHc67K4kADgaDiCh6szKvj2QOWH4Oj1tQjApjbDab0dBvdHQ0yjWSXKO7OB4A8EAJ6BfZcpJ2fHw8rh9ir0GM+Xx+CI3x2ch8v98fKs8AAbqB6vf7kbvk1yhhoLgkgz13JIhB8r30J6mAkvIHdTA9PR37gjw6qmefuTQBJYoCZy9J+XDD7WfQg1ueFMr5pCUw1AAy/3nPFyql9fX1OJCp1FXjsrm5OZ2dnWl3dzcytEulUmyUC50fYibGYibJPzbS21y4wkPQOdwQyORb+MH0HkA8Du8R6mS0gtdBYDqh53wH6+E5U47MfBOByUmi1q2j8wSsCVfg0I+crFpyaJyD4X3dheMhR8ddDHcFnbxEaWLZnaQE5WGB2V+Ev9PphCFhH5wb8oPrLiE93c/OzqLpfy6XG0KWfvB8fhxiRxXSNcJ39O6fv7+/r7OzM7300kuRV4cyJCPaUztATul0OlrQohxdcaOI+B5lROdSkC9uFFFelC1yxvt96sD+FQrFGLt8Y/xoh8v78zsCGA4c3PC6MkRW+DsMDOMixQXj5LSFdJ0oi0H3q7m+6PlCpUQukS8Kbly329Xe3p729vZikDMzMyG4CPrY2FiUoSTdHQ4CcNs5J394vd/+cHZ2NpQYyfsmCWo/7Cw87w/hS7Kfu50oF3dHcEGZi7uWjl4QWjYVLsrrlPz3/hAEoKtfr9dTtVodIur5itvh1sezvslGbrfbsX+enMnaMn4Ok1tpJ2s5PCA8d1tZf/bfXUP2g/fjwHLVEYoX0rxUKoUSBlWyZz52T4mQPn2FeJIET6VSUV9JhTwoG9SAy+N/ByntxtJRKUbh8vL6+ivPiqcrAa64y4d7GzdxSDwoVZAKRtbTPbrdq9pF+C6UE64Ta4dBYf9YR97LPRPWlzl6ojNJtc6fujtH4IR/KP/Pe75QKXnOAv+AuQgwigmF4dEaeBp8ShIsPYyPgPrhYHFwkZiof6U9BA+a2VGHL2wyciVdKV24G5rse0jXi35RlhxOP7wINlZPGq56d9IamMs/XB7P92o2m9rd3Y0sa5AkbjN8x/j4eFxaAFHqTy6XG0JdWEmQrbsNSSWEUvaxOj/hriDCyPs7F4ECTyKw4+NjbW5uamdnRxcXF0MdCjqdTrRTpsjUI71J5JT83pUlP8dVa7fb4YI+fPgwXBIUA+N3Dgge6KYoKM/p6Wkk64KK4MqIWHkvIkdGbtwYsxtDn59HFD2VYDAYxNl4+PBh1PkhJ5KGul6y/+6dePSZPcQD8UCHB3JQ8v4zuDKUkfNmX6hzvugFznG4pWTCs7OzYclpmXB+fh4/90XwxUVomCCH1okyNDmanbwRJ389v4dwNX60t2N1C+SkMkqy3+8PNWRno2j56UltTsxzUFFeN8FihAhFDdGHgkP4QCpeqgGJj7VyqE0oud1ua3x8XDMzMzFe1np6ejrGwHXgCJkneLI/rpBcsXsgIOl2455QmuDRLA8IsAZE7XZ3d7W9va3Dw8OhvKhMJhPBlIODA+VyORUKhUDFcEGfJas8oAfG6wYRjvTo6Egffvjh0DhpL+OBEQ5fNnvdHgdCHYMB8js8PIx/5G9lMpkofEYGUfg+lySP54+705xJ5jsyMjIUzWu1Wtra2orrr7LZbHx1QtsNJugPIwji5uyD9rgMg9bJuIwQ2vBQXp6Fwnfk/FnPFyolj3p5dAkYRrEpCKnZbEZJCpXVziOwQRxA54ZOTk4CqrurhN/Khl9eXobbwiEh4sBBdr/fFaofNklDPi7K8/z8PBICS6VSXMddKBSiPSpuKWvCouOKef0biAnf210oLBwczeXlpVqtlnZ2duIyBOdQPGInXdeMkTU+MnLVnAwEOT09HYcKt5CLASqVSpQMeXSK8fIzIkseoQHZ8tmgRA82+EFCgbHn7XZbGxsbcemmK0fp2orDM3KhQbFYjHsEOYwefUNuMHBwL1hucuOcD9vf39dvf/tbnZ+fa3V1Vfl8PnoDecTNlZS7T4S8WV96ndO73It0UdS8H1+RE0dGIM9PHVoj+ZG9wWAQaAV6AJk7ODiQdF1S5F1BQYKcPac/3LXr9/thJJwfI8UGgh1Cm7OJEroJzX7W81xKyZl+97nhY6anp4cIvtPTU+3t7cXB7Ha7cf3O8fFxCDBKipCkH2AnWNlgID+5Ds4TOWHKBjgZygFh4bFCMzMz0Y7VN6Tf70dNGlbh7OxMxWIxSPVutxuui6RAVmxo0u8m0udCgWuLUj04OND29rb29vZiHVgX5uBCw8FIp9NRGM01zdKVu4AFQ8hOTk5UrVbDrTs/Px/Kdmffcb8ZczLK53uFoGFUJA3tj0dkzs7OtL+/r/39fZ2eng71UyKtgP3AvUD2cF/pX+WdIXw8yCmUAfNgrd316ff7evLkiQ4ODlStVrW+vh6N8ZmDu1uOFmnef3l5GVeMoRxYD0drGEoQcpJvY48Zlz9JRMU84G8x3p4vxDVdY2NjcT2Wr4cHCQjGOCiQNBRpBRF1Op2IDsO15XK5cBWdvPeAw/M8KXepPvXLVOqL70P56vnq+er56vk9nsFgcCOr/4VI6eWXX9bIyIi+/vWv63vf+55u374dmdzeVMq5B+B40roATbEAjgC8tuavBjwU4uZnTgSied2ieAgWn5c8kXq9rvfff18bGxvK5/P6t//23+qXv/zlUBQMNOU3YGD9cQWTETZcGXepPFyPxU9GdHw+joT891gtD90fHx/HLSK4vr/+9a/14x//OK70+fjjj/Wb3/wmeKZer6epqSn943/8j/Wnf/qn0eCsVCoNkZAemsZNcIKZdfd9YJ5JC+/ck4fjk1Erjygxx9PT02iDkfzZRx99pA8++ED/4T/8B/3H//gfg/RHFmlORlQyid5w3fg5cuouJ6/3fU3KH9+7+8i8HRm4LONSgf65GPP4+FjPnj3Tj3/8Yx0cHOjtt9/Wz3/+8+DxcIucPPYgjo/No6sexGCMPjenNJhHkirw4ITPnZ/hZtIxdm9vL6iW//pf/6uePn2qtbU1jY2NaXd3V++///5Q/6bk84V4ijKFYrEYDf4ZuEe33HdkAZKhZI/iMGn/58ol+fOb3sMPNsKQJDpd4EZHr+6ao7IdIfXonL+fC6n7+i5gKCTgNAfLD6WP1efG36CQ+D/8j0e0klCeuaE4Z2dnNRgMVK/XI5uX+eHW5HI5LS4uDhmREITEGjAOd43cBUy6bkkeAjcpOc/PWhOXF1dwrriIcnIzr6Shvuh+UPzwJHlE9pcxJd0Vj0S6y+GK1OWDvfOHNfSD7+/j3+My06LXDXUyHcWVnxt9j4j66/xvOaf+s5uMTfJvkmeAeflYXAc45zw3Nxe8ITzll+aUpKsozcLCQoQzb8qS9lwgJ8WTKAfL4yjIEZP/nO/5He/DV7Q+C+tande4MKJcR0dHow+zz8ejIUlF4AKYVJQ+Pn9ciJOK2N+fcfv3ZCSTduD1VHAAnkAJInr8+HHwSbyG9Zmbm1OlUglS3glIP/jOVfHPBdZ5h6Qh8n3kvT0bm7+HKPa6RF6HspOGAy2EzovFYnBKnt3tsjgYDPcDvwlV8FmOhFyeXAH53iWNixsrVwTOCdK7yftqpdNXCboY/omJCZVKpU8pLY9YOTrxNfVAge+pK2p/D19bV0Cu1JKPAwPkMkni41mw3qurq8pkMmo0GlpYWBga32c9z0V0z87OqlKpDLVBdUjom+Qb6ISyL5CH6R0C+8b6wU8qJ49UOGHIhkOWslmENr3jHk3U2XDGBqri57hLbrE8i5lxoSBcqHHvWA8OH4KE5QBhsV64O6QSeM2X15z5GoKCPvnkk2hqJ12nPHS7Xa2vr0d+khPtKDpX4MzN980TSV2gXdiZE2Nl/Aiyoyd+n8y+TuYB+TiYU7lcjvnz+Un3mSgZtWm4Nf3+dcTqJiI7Gap3uUAmnTrwQlvcTfbRs8Ehwx1xuoeQyQy3gU6iFT4Xwj+Vuu6Q6WkSUCEoCRSv73lSCfH+TiUkjQpf/bXkH3rE3embQqGgUqmkw8NDzc3N3ZilnnyeK3lyZWUlrqF2mMaECDlj0Tl8PnjpGuJ5GQlKCYFDgbAwRDaSKe0sBtbIrb6nFbjVw4Wbn58fap/gytQzXhEyMnFdcRJdQbC4zplwKGPCaiQ5JlfGrJ9n/tJSxdGgIz5HBwh9pVKJHB/Wb3p6Wq1WS2NjY1peXtbExMSQu+v1a45o6LhJpBTehmgSnBsHNukqkATZ6/XUbrfjMgESF+FKMBbOm5Dx7Kkd7jKDeNk7R2qp1FVXRRQ3ig/ZQkFyWEdGRiLVgyvnPV3Eb5HBgDjPxzyp32u322q1WnEeWI9k+ggy2ul0how7vcuRWfc8Li4uosKfDqCO1DziRzIqfc/g3PzceW4W83EUiYIi9w/+Mhnl5DIBz9nivUZHr65If/LkSeR3cW4/U+d8jj6KQ7awsBAp6q6MsOTkktyUut7r9WITEGwOKIKNNXM4TTjdG9Hv7+/HFdEcVg/7wjmUSqXI+0HYEeB0+up+LJQIn+cJjCjAVCo1lA6AUiTE3+/3I6TOBY63bt36VOtcJ46pyoYrQumdnJyo0WhEqPzg4CAUzNTUlMrlciSDkkeTTqejaFVSXM2ElUbJ9vt9LSwsxL1gCBjC6POr1Wrh/pHrwy0rCwsLsYd+gDnEKLjBYBCJg5eXl9rd3VW73Y76NlfYBEsGg6tcrUqlolKpFMrv5OQkLlnEAne73Ti4GCNPSSHJFSWEcmo2m0O3+HJ4SqWSKpWKlpeXVS6Xo0vm9PT0EGJCkXP46ZBwdHSkg4MDbWxsaHd3V7u7u5GPlkpdpc6Uy+U4O8ViMebNeuFSoxyRV2SODg6cO9ojO3HebrdjnTCkMzMzmpmZ0fr6unK5XAQA/DoklDnvzc8411zaWavVIkHajQZrnclklM/nlU5ftXshibZcLmtrayvSY4rFYvT1/r2UUqlU0szMTGyIs/RsOoljfkOHp55TYDk7OxvlAuSBeOZ2JpOJOhoWhVqoer2uvb29uAxQukII3JQyOTkZqMqtw9TUlGZmZgLSsnArKyuShuE/AsxlmN1uV/V6PfJpOFCsRb/fD8VJQqd0fZFhNpsNBcgmIjDNZnMokZCMaFAkgolS7ff70fSeww1ayufzqlQqmp2dValU0v7+fsyJNVhYWND4+Lja7baq1Wr0q56eng7Ivbq6qjt37gSqqtfr+uijj7S1tRX9uQuFQigPDi3WjxpHlDbj5P9kFaOgSYDt9/uq1+s6OjrSkydPVCwWVSgUNDY2FpUBnnDb7/djrUE77InzOyQyHh8fRy0hKMZvup2entbm5qa2t7e1vr6uhYUF5XI5VSqVoTa+fL5fy12v19VsNtVut/Xo0SNtb2+r0WjEWMbHx7W2tvap+i/OUTabjYRHjAh8GefM0T7opNvtBrImaRgkivyiGMvlsqrVqlZWVjQ/P6/JyUnNzc0NtYd2ZYfCbbfb6nQ6ajQa2tra0ubmpmq1WpzZ8/NzlUolLS4uBrnNfgwGg8iALxaLymazgZLv3bsX9MnvpZS4S51NOTs709bWlur1+pAbAHJYWFhQNpsNLYtQdjod1Wq1sICpVEorKysql8vBVeHC0M96c3Mz4C3al0PKBk1MTIQSch4F5VKr1bSzs6NyuRxZutzYgWJDQE5OTrSzs6Nnz56FEqUAmY1g85kfm9loNNTr9fTkyZOwYEdHR5qentb9+/e1vr4etV0gAA7G06dPdXp6Gp+HK4VQAo1BJ7jIKKqtrS09fPhQKysrmp6e1s7OTuxNuVxWq9XSxMSEGo2GdnZ2tLGxoe985zuB5M7OztRoNPTBBx9oZ2cnylbg09Lp9NCd9CQYvvbaa1FzhwI6OzvTxsaGHj9+HIZHUqyZJBWLRdVqNXW7Xa2urgYSKxaLoZhJznv69Kk2Nja0vLwc1QGgLEmfIo4zmUwgIBRfJpOJzHyQEl0CnCehOBi5wBV3pM0/0hMajUbUKR4fH6tYLKpcLsdnU7xeKpWGjBmHFuOBUur3+/FaL6JOp9PRfwlZZO1R4ijeg4OD4JwAEgcHB6EMSQDmfb1UCzAAINjb21OtVlO1Wo3kX2gaAmBE5fm50zj9fj8MWaPR0NLSkl566SX98Ic//P2VEin9g8HVLSFYzGw2O3SrajqdVr1e1+PHjwM9gZi63W7wUdlsNlrq1ut1feMb39DS0lJwB2w+bgRZxsBBOAcuqmQBZmZm4j2c6JOkarWqTz75ROPj47p37164Qwg1iOXx48fa3t7WxMREbBzV/YPBQLOzs7HBCJWkcNFwJ/2KqVarpcnJSb3++usqFouRkbyzsxOK98mTJ1pdXdXLL7+sdrutx48fazAYhKv70ksvBRrzO+dGRq6a+rdaLT1+/Fjz8/NaWVnRkydPYmxf//rXtbOzEwoGRbi0tBRzh+fgnvvR0VG99dZbajQa+sUvfqF+vx/Z+6+++qqKxaLef/99VSoVvfDCC5qfn9dgMIgC23fffVczMzMqFAoB2Rl/qVTSX/zFX+iTTz7R9va2KpVKIK3Z2VltbW2F21EsFjUYDLS5uamf/exn+ta3vhXdJijnwbVxOoDDjWvvh1e6usihUqlELg2KTbq+BHVsbEydTieq7F0xIS/sZaPRCNTA5Z5UHSALziFSw3l2dn1ZBi4TClS6TscB4RPwoOqf+YLCT05OIgTPGfOADOiRiJ9fngnfiZwAImq1WrTXBW1zeQY1bmSU40JzXqQr78MV4Pz8/FAR/e+llPL5fHRyfPfddzU5Oamvfe1rQ2QoxOfU1JSazaZeffVVdTodvf3225KurM75+bmWl5fDfcrn89ra2tLBwYHefPPNEJhms6lnz56p3W6H60WeA4fp5Zdf1jvvvKNMJhONo4rFoubm5rSxsRFWAheuWCzq3r17+u1vf6uNjQ298sorYcEpwdjZ2dHm5qaKxaJWVlY0MjKiTqejbrcb1fWvvfaa0ul0oACs8EsvvaSLiwu99957Q6kCRFKIiC0vLwcSSqfTUaXORZteoiJdlXY0m03du3dPkvSTn/wkFDubTXo/KOTrX/+6Go1GrH2lUtHa2lrwCM+ePdOtW7d0dnYWZQdY7rGxsUim5DpnSVFPiDDNz8/rgw8+0NbW1qdcWlrj0nMLgpv36na7evbsWXBcHP7Jycm4LaXRaMRV8GNjY7p//76azabeffddfec73wlejsOEleZgIJMoKPg93CcUix8kOBGIcGQrl8t9CgmAlOiO4dFZ5np6eqqpqamgL1AKGDOQNqiH6By8qHR95TruNUoDBUqQAK7Jy2dQUnCjRMjoMEH3CI80Q6McHh5qZ2dH1WpVFxcXgdCReZQhZDmkNWPw7pyDwVU/eOSKppFfSilJV1p8Y2ND+/v7euuttyQpOspBaON21et19fv96LWMW1coFLS6uqqRkRH94he/UC6XC1/+9PQ0Ov4h2K1WKxYOa3t8fKzHjx8PJWZls1ktLCyo2+3q0aNHqtfrSqevb/8kmsDtoJ988olWV1eHfOnDw0M9ffo0WrJ40iAkabVa1fvvv6+JiQmtrq6q0+lEoSPuEoIA2Xx4eKhKpaLR0VFVq1V94xvfCGL98vJSzWZTtVpNr776qhqNhn7wgx8onb667ZSN/5M/+RM9evQoXEhuooCwHhm5uq/t1q1b4Rr/2Z/9mT766CM1m01dXFxoampKy8vLIQy3b9+OWjwy4DEqoEjcoTt37gSkX11d1fvvvx9uycOHD/XjH/9Yi4uLoWS3t7eDKwGBUeXP5RMgvpmZmXDBU6mUnj17pk6nE4rbI0APHjzQz372M1Wr1XBRUdzMmwAFh77f7w/VsKVSqSDXz87Ohrido6OjUHBEeKenpzU/Px/rzedAJXDlGDwhV2xRqI5icwXofBYusadYeErJxMTEUAcNAhTwUtwWDZ1Bd4ixsbF4PZFI0OLZ2VkEg5gXipEzA5K/uLiICxQIhOCWem4f++QXWMIxMbeVlRVdXl6qWCx+Ksfxr62USBnf398PmN1ut8OFOT09jcrhXC6nF154ISzVnTt3QuOOjIzod7/7XURKKBJ8/PixfvCDH2hmZia6QG5vb6vT6cSBJrcGLX96eqpyuaxUKqVGozEU1cLNhGuigJfw5NTUlDY2NiIXpNvtBgdx7969KMmAP2Icd+7ciVYVHr0YDAba2dnR3t5ecBCtVmuoD/JgMNAPf/jDUBKnp6fa3d3V48ePQxBo5YF7hsvQ7/dVq9V0fHysubk5dTod7ezsKJPJBHeGJTo/P1e9XteDBw/0ve99TxsbGyqXy7p796663a4+/vhjNRqNoba7zB1Cl8gpKGphYWEoLwsXulAoaGtrS51ORysrK+G+b25u6uLiQgsLC+Fqw0XQG+ny8lK1Wm0oJQAFixtIATfR2Vwup29+85vRyva3v/2tpOv+QFhrXEW/IcQ5kk6no7m5uZBB3DIUoXQd0OE+O8/RIpJM8S2KgosgSZIE3V9eXvUbI2qKoqF42imHXu/6klHpGgmRc4cL7PlKksKIplLX168zNl4HepmYmIh2vCh+lAvlRhgsyGwQHWsDfUDQAsPdarV0enoaKRaeyrKysqJ6vR5A4UsppVQqFREw6bqKGxQExJufn1cqldLW1pY++eSTgL4LCwtaWFjQ8fGxqtWqdnZ2wlqmUint7Ozo5OREL774oiYmJnR6eqqnT58GgiADm0UjGoO7lc1m9eTJE3U6HS0vL0crDiwM33e7V5dS3rt3L7gh6co1KRQKun37ttbX10OgueMOy3B4eKhnz54NtTUpl8vhonG1OZvgmyZdoakHDx7EWrRarSBVc7mcdnZ2wqplMhl1Oh1tbGxofHw80N3a2lq0wyW6QtCA0DtRrr/9t/+2/t2/+3cql8taXV3VX/7lXwZqkq6jbgQiuFUYZUmy5Z07d6ItMFHB6enpuHigVCrp1q1bmpqaimzxn//85zo+Pg4EBUrodrvRSZOmabid8/PzKhQK4To5GiQAgkvX6/X0+uuv67/8l/+i6enpcHGk66p83p9uCJeXl3rvvff05MmT4H329/f1+uuvx1XWk5OTmpmZUbPZjOjn4eHhkIuLQQKZccg8PwsDsL29rfv37+tHP/qRRkdH9fLLLwehDy8ESvHETZQS7h9eCD2bOp3OUO+uy8tLPX36VB988IEuLi5Uq9VUqVS0vr6u2dlZFYtF3b59W9VqNbgoT/RESaBsSETGILAfuJFE+46Pj9VsNiNvDNTp+XTkMeXz+QhafWml9Oabb+qb3/xmMPCe18PEstlsNOuCi7m8vIx2o8vLy5KkW7duaWZmRplMRouLi2q321pcXNSf/Mmf6E//9E81OTmparWq//t//6/+83/+z9HPiDAoKAIuB/RElGtiYkI7OzuBHDhMHAb+lj7QkvT48WO99dZbQ1ENwv9Y2U8++UTZbDaigpCryaJCBJQ72/P5vA4PD9XpdDQyMqL19XWtr6/r4uJCxWJRH330kXZ2djQxMRGKkob57XZ7yJ/HStdqtUiwgwSlpcrIyEh0OSSlv9VqaXNzU4uLi5EXc3p6qpWVleikiGW/uLjQ7OxsELc0tyuXy2GYVlZWtLy8HG7a3bt3df/+/agrfPTokS4uLrS5uamxsTGtrq4ql8tpb29Ph4eHmpiY0P379yOKi0yh6ECANKBLpVLa39/X+Ph4FHu+8cYbETb31rUEQ3DRPIEXhQbCPzo60oMHD/T6669rfHxc1WpV6XRaS0tLmp2djZa8hMkvLi6GIsccLNYZNDM+Pq75+flY9//23/5bcH+FQiFSJZaWlsIl5B8yzaEmIo0ByOfzwQPRG4nAxMLCgt577z1JUqFQGAo0kAZw69at4DrHx8fjKibaAGF4yJinHxQKnODP1taWPvzwQ3388cfx+/X1dc3MzGhtbS30A1FSz4z/IoX0XEqp1+vp4cOHEbrnoIBACoVC3Et+584d5fN5bW9vh085NTWlubk5bW9va3R0VC+++GLktzx8+FD1en0oDySfz2tmZka93tVtt+VyOW5iRbiWlpZUKBQ0MjKira0tXV5eanV1VUtLS0NWHbKRnKD19XWNjY3p6dOnev3110Oof/azn2l+fl7z8/OByHifi4uLyFmZm5vT1taWstmrAtjZ2VnNz89rd3c3aukePHiglZUVVSoV7e7u6tGjR3ry5IkePHig+/fvq1wu6/LyqjvfwsKCNjc3wxrn8/mwbPV6Xc+ePdPx8bHu3bunW7duKZ/PB1eH705uCpFQEuUgn7PZbFzAmEqlVKlUVK1WValUNDExoaWlJS0sLAxdyZ3P50NY+/2+Go2Gjo+PI3ny4cOHev/997W4uKi7d+/GWhUKBb3yyiv6yU9+omazqcePH2tmZia4JNAPbvb4+LiWl5fDzSP8XiqV1O1eNV8D3a2urmpzc1OVSkUrKysxP89LIienUqno8vIybnFBDh88eKBisRj9wEulku7duxefMTc3F43eIL9BJjMzM5GHQ1Ig5C/IK51Ox5oShcVlnZub0xtvvBEdKUGsBwcHkZCaLJeBb1teXg6yutvtRlCI84nrhms7GAyUz+fDI1ldXVW329WtW7eGSoboi0RCJSQ/6TBjY2M6OTnR3/27f1f//b//95B5SXr27FlEFxcXF7W2thYcbL1ej7I0DDVo0JHZ762UlpeX9ejRI01NTWl+fj6a1wPHFhYWYqDOh3DwQDD8XaFQ0MTEhB4+fKjHjx9rZWVFr7zySlS5ZzIZ3b9/X8vLy9rb21OpVIp2KWSknp+fBxohq5j73ubn58M3hlDMZrOqVCrR0A0CTrqKvu3s7ETY20lQlICkCPMiKN1uN9p/FIvFuPXl9u3bunPnjlqtlh49ehSJdF/72te0srIS/NH6+rpef/11/b//9/9CaZBvsrKyotXVVZXLZe3t7WlpaUnz8/ORe4NLRBY4YVo4ksnJybhlBgJ2fHw8mtCdnJyoVqvpxRdfDMXmdX4Q0xcXFxEyp3To4uJCH3/8sQ4PD/WP/tE/UqVSCYve6/VULBb14osv6oMPPtD09LQajYZu376thYUF1et1NRoNNRqNcIO8Q2ipVAq3hpA+Yy6VSnr69GnsLxwJiH1qakqFQiHC9WRO407Ae/zxH/9xKByQCgYURHF5eampqanIuyKK5bV18EPdbleLi4tBZqdSqcg5++53v6u7d+8OGWg4SzhD57Gk62JiSYGSPUMbZefyCy/4rW99KxCtJzrn83nNzc1F2ZAjsMPDwyDlURgYvnQ6rampKb3zzjtaWloKT2J9fV1//Md/HIErGgTSWE9S7EMSATr/93srJbgRFpLkwhdffDEEEmtCujuDol0m1hH/8vDwUE+ePFG329XLL7+shYUFjY6OxuIWCgV9/etf1/e///0IY5ZKJWUymaEkrnT66tohFpSNRHl4T+d8Pj8UscJvT6VSarVamp+fj74v5DxxAwSlBAgz5CgC0e/3gyfI5XI6OjrSzs6O6vW62u22VldX9dJLLw3dEzcyMhKpEEQ5iIBBYBKx4pBKijR+1jiVSkXSJZHG0dFRPXv2LISdsoBsNhsN+cm7oq80f0domvk5Wekh/2984xv62te+FgLsRam3bt1Ss9kMlESBMEoAZeJhemSNQ01UlX1AMZLDwxgZNweYTGQOCOMngiQpeBoyunGNeV+CD3CnXpfJPmAgycGD0D87O4voKUaGVAHy2Pg89tbrO8kUR5ZBq5LiPXCJPEGTCCp8pHeR5DO8fzsEPhFB3ELODWvADS/OKY2NjenWrVuqVCqBegn8wP9S/kJ+FoQ6a/mllFK/3w9GfmxsTIVCIfzvtbW1yGp1MpqESRLEvC1u+69ubM1kMuHS0ELT67Hu3bund955J4TWCyvJPgURuQ/L4Tk7u7oF9/bt29ESliJGJxNffvllPX36NNyHs7OzSFeQri+55FZYksay2WwoKdbIm3f1ej2trKyo3W7rO9/5jhYWFoLEhitZXl7Wd77zHb333nv65je/qbGxsUhJIJOa+fE3WFdcjqWlJeVyOW1vb4fhGBkZUbValXSF8LDUhUJBzWYzSklQPJDLHHLp+lJN/p7o0cbGhiYmJvRHf/RHWlhY0MjISAgrVnBubk4rKys6OzvTwsLCUC0Y48OCEmHiexAZiBRuiURC5At5wA3kH8qZ3KFkuY0raTcSfgdfPp+PVBbGBHohogWq5jBTy0b0z9cQPonx8zNQD8jl4OAgqAbpulcUuT6eaMn7e9M3EjA5A+wba+7Jv562gTHhvE9OTqpYLGp/fz9ACRFDFJ3Xs5KO4GcRVxfXHyPyPM8XKiWuS4Hgm5ubi3AjWhQriWAgpJIi0Q8CcmZmJuD7yy+/HFE76TpywgF4/fXX9b//9//WSy+9FJyS93MmpIpQ+UaSZ4JvjKY/OzsL1CRJi4uLWl9fV6/X0/r6ulqtVhDHpBlwSLB+rAkPguBKg7yiO3fu6NVXXx2q8kZoxsfH9Wd/9md6++23dXZ2ptnZ2eAmSLD0UgDPDJauQux3796NqCdWjmijpCFofefOHf3qV78KpAb6c74C14fCTHJp+P3Dhw/1xhtv6Pbt21FTSMcGDgpu7G9+8xudnJzo9u3bQweIQl0EnLlxuLzNCOt7cHAQRgfrjgxgKPg9iMGViXSNLFlbUjYcwRGZoriVg0tuFeOBjCczmgRe5AOFRAY2SMH7D3GYURwgURQECJLxucFAhki/YQ3ZM18XXx8CHZwV1oXCbvavVCpF1QT0jCeZsm88GARPAAUdez6jR+c+6/lCpQSxRmmJ97Ih7I6FYcMQBPJO4A0oAPztb3+r0dFRraysBEnIZqF9R0dHde/ePdVqNb399tv68z//8yj49bwLBI0N53syccml8sjW/Px8HNpcLqcXX3xRv/nNbyLq0mw2wx0D9rvvz8ZxKIDhKC3yio6Pj/XWW28pn8/H3+Fi8V6rq6v63ve+p//xP/6H/uk//aeBPFz4eH8PucJP4IJxmBcXFyNMK10prvn5eT18+FAPHjzQSy+9FCFycpZQOLi3CKwLWbfb1fe//30tLy/rm9/8Zih7AhQIIhzP2NiYXnvtNf3whz/UX/zFXyifzwfaxCUG+nuOUr/fD1eMtcW6E3b2xvysB/84fG6ZMWigB2QRYjoZ7aLo240Cco3B4CCenZ1FpjLvTbcCR/AoJi+DYp1YM+bMHvB4xjVrxF7xPjyk4vjaYcgwyhD1zBmDiUwTtCCgBaLL5XKBUFGCXADC+qOAOPP5fD4qIvj3pYnuk5OTYNJPT0+1uroaqfQuHAyOfywmAsYEfvGLX6her+vv/b2/F3d5kbjmqfzA1e9+97v60Y9+pP/0n/6T/tk/+2fB49Cjx8O+LA4Z3IyJUpN33303EIzzUg8ePNCHH34YWcu1Wi1gOOFgNgsIy5U0ExMTAeU9Ae/Jkye6d++e7ty5E5voAsaaZTIZ/dEf/ZF+97vf6Uc/+pH+yT/5J9F2hfYfICwsGyiLHJ1utxvRo0qlosePH4eRWFxc1OHhoWZnZ/X9739f//Af/sM45CAqDjORGZAT/2+1Wnr33Xe1tLSkb33rW1EeImkI+uPe7+7uRl7R9773Pf37f//v9ed//ue6c+dOdJGg6JYseBQ1XATEdblc1scffxwoPdmtgYPm/BTKBHmQNPR9KpWKDhW4MYyDr15nRtcHUDCKEAWIC0yoXVIYTleOKHqnGXhQMChGxszje+RlJqB09g3DjpIZGRkZukIbHg2kBpqjdxRGIpfLKZfLBcEOoPAbU1gjDCLrhfJhrRkn/1ijz3q+UCkRgVhcXNT29rbW1tZUqVSGoL9ndqJZgY8Iba/Xi+S17373u0MhQ/eDsSZwPAcHB/r2t7+td955R9///vf1rW99KyqT4W+8XgmB5HPxiTkI5XJ5yMelxOW1117Tzs6O3nzzzSDmIdBRdORkUEGOJcK163a76nQ6evbsmZaXlwOVcGCxkm7t6J/zd/7O39Ff/uVf6qc//an+1t/6W0EWs85YataVKn7KI1ZXV1UsFrW7uxscFwcBF+GFF17Q//yf/1P379+PRncIDKQnnAvKY39/X3t7e+HmgiAd7cGr4LZwsIh0/v2///f18ccfq16vfyqQQPG2R4bgGC8vL/Xw4UM1Go2IcIHOsbbHx8eRJZ0MP/uhQBY5RITAHSH2er0IakAcw8cgq+56TE1NRU5ep9OJKBZ/R14SmdEYIcYO6kIRcJD5ClHsCNndQn7uZTDIFrLJOSDahhL3CKBHIFGQRIOpaqDtEBFH9sDHw5zIX+RBxohqf+noGwV2i4uLWlpa0q9//Ws9ePBgqHk71oOF4vBlMhkdHR2p0+loa2tLjUZDf/zHfxxV5UA8Jof2deUCHHzxxRd1dnam3/3ud1pcXNTc3Fzk9FxeXkZSHIvrZBtlK7Tp8CgKod5XXnkl2m7cunVLkoaiDbgEWFcKgTnQ5FVRrPvqq68GN+MdO4HOzJkIX7FY1Jtvvqlaraaf/vSneuutt6KSn8v/4M4QJIhzyGgusQQlSIr8MATj/v37evz4sX7+859rfn4+khtzuVwIMmVEKIvl5eWI8BEMQDg5cAQ2jo+P44CAIqampvTGG29ob29Pv/nNbyRdZXAvLCwEKoNwJfrEe0INeMdRd1koI8KI4e6iHJGjpHxyWDKZ606dtJklcxry1iObzn/CtZHvc3p6qlwuF3IICe/KEoPJ/mP4mBO/kxQKDSOD/MBtuQL2yBbj9Pcj+MP19JxPaA2UC+c5m73qAjI5OalarRbpEl6QSx6fpKF5SQqqhHlyjt2b+FJKqdfrRQLZ6OioHj16pMFgEFmjaFx8UDJmO52O9vf3Q7hfeuml4KM4VOfn50NtVlk8j3bhyiwtLUWN2NbWVqCASqUSm+RhegQUCwM0d3iJGzY2NqY33nhDGxsbevTokTKZjO7evRvXXhMWdWTh7TP29vaiy8ALL7wQ0bhkjoZ0HT0BQhOKL/5VQ/ydnR2988470XCsWCwGActY4ULS6XQ04iL9AkUhXfXkccuayVwVR9JXiZo9OCpQbiaTUblcDgU4GAwiPYNGYAggbiY3qYAWOPDHx8ean5/Xyy+/rKWlJe3t7Wl7e1sbGxuh2ID02exVn575+fkgZjF6RHGd+6LOi3328L4TwygEz8bGqHjhNa06nHgHIXl+FIiL96RAmyCKtwTBm3A+BWWD8aBmjXwvSUMXt/qDMfIwOzKFjLJeuLonJydRhuQ8oCto5oLrB4/UbDajHIvx8PnIpbvGrmDJGudse4rFZz3P5b6h6eg8eHl5qffff1+PHz+Owtfp6elQULg/RKmA68W/aoMJvK9Wq0ORAFIIarVa3LxJES0V7TT7qtVq2tzc1NOnT/X06dOh7FFJ4RaNjY3FRlMrlpwf5SSTk5NaXV3V2dmZ3nvvPX388ccql8vRUwpFAPFLl0wEmZaqvrGeI0PUi4OCAkZRQobev38/lBxKg/a3EKmEdREIhBvhYF2pyXPkkE6ntbCwoMPDw7jVlBwp9pM2FfAI+/v7UafIXlEC1Ol0os8WyHBubi5KOzqdTjRAW1tb08rKiu7fv69GoxHFoZ5U51aWaKAfYFcsGDZPGTg9Pb0xAsfeefgbdxCURCNCz+jHwnMg+UynDcjLg9LAZWSvGYNnoKMscBuTSgmXxw+8E+EoW+cCkSvABIqw3W6rVquFC4ZSoQsHSp1x45LzuewhCizpHjs/1u9fd/2En/N5f9Hz3EqJRbq8vAx/c29vL3gNFtB9cOqmIK1xh2j7QJnK8fGxRkdHo8HW1tZWCGOhUND8/LwmJiZUrVaD01pcXNQLL7wwVMjqAugJcB6pg9hFW/d6vSAC4aBQoPV6PTpNghhAEm7BJiYmwp0kF4sNZn2IkFFOgm/fbrejk+f4+HjwVXfu3Im+1tvb23r06FGsK/+mp6fDdWNuHFy+kuRHdjtW+9atW+GikFTn/ZsR8MFgEO173333XX3yySdaXl7WyclJZCd3Oh3V6/WojyTydvfu3Qhz7+3tBdIeGRnR3NycisXiULHr8fFxFJ7irjnXBbL0/eNQejqDh8w5PMkcHncXUYZHR0cR2QTlsZcobFAjV1ZTH4bxgzfxrpLuVqE0QJ605QHhg8h5QHFOrrtCSB5ykIgXa3e7Xe3u7kbmP24aKBRDSe91jGWr1YpeWgR9MBigR9w+xoGSI5HUbziB5mD8v7dSQtjRrLwpbUFg3PE1aXCPP8qESbI8OTmJBmGkv9N+lbKJ7e1tNZtNSdLq6mogDCJufN78/HwoApQnm0v3PDbFISXC7F+l4XSGbrcbESiPbvR6vSCaiR66EAO5mTNEKMq81WpF+cPh4WE0Cuv3+5EBfXFxoZWVFS0uLsaBPjo6Ur/fjygmAsr+eETF57S7uxsXCgCjcRVR3MwBdxRhZ91OTk6iQ+Yvf/lLvf/++zo4ONDy8nKEgff29vSrX/1Ke3t7UZSN4gQJuPvleTusF5zF9PR0WFrWz6OrSaFmb0EVvV4vasvgKB0pouycC0X2iB7VarUI95+eng5dAHF4eKjt7W1tb2+HQc3lcqFgmLMn/IIuQGeOrFDABBgwKCAiAkisnXSdLoKipTjbI8UoDFraUr/a6XRUrVaDEB8fH1en0wkUfnp6qmq1qo2NDVWrVaVSV7dhdzqdoeZwvqbMiyRlAmSeWEsUOemtJJ/navLGRNH8Y2NjUUsG4QfcJ//Dw4BkatMj+mc/+5l+/vOfq1gs6lvf+paWlpZiw9rttn79619rY2ND/X5fb7zxhiYmJqKvT6vVCq6D9ydah3BgcUFKQGKIuGQExMPRJAISSodkhL8CRfmVPMBjDhGf8/DhQ3388cfKZDLRY6bdbke2OMQ0xbzr6+taWloKt6FYLGpxcVGlUilSE1BChJs5dAgxSpQ9++Uvfxl90z0nJZvNBrJwfx9l5GQ8UcVUKqXV1dW4uQNh5cC8+OKL0Ve6Wq3q6dOnWlpaGurBBUmKq8qhQuk4+eqohix5lBDGxRP/kAdKmcjYhsjlAHnEC7mDl5udndXe3p7efvttHR0daXFxMVAltYv7+/t69OiRnj17ptPTU62trUVOG/ebgfB4cAHhrjwaxv857MyT/fE8MkqSUHSOeuCJQC3IBTQJ8/zlL3+pn/zkJzo/P9err76q1dXV6F5RKpV0dnbVN/5Xv/qVqtWqvv3tb0sabuOCW0sQAkDgF2nwlXkhJ550+XspJc9zQJDRzF6AC3+DxmZhHV7TYB037/j4OKr8USoQcxyqzc3NILUzmUzc/OGkpecnOVogP4paJxYSCM3D4WOcKCXa9yZ7IjMWDogvPnWA1WpV/+t//S/9n//zf+LAvvnmm5EfhYB88sknevLkSSgTSiFwjzignt9EUzGq3VG6juZQDvv7+8ElkDMFP8OBRFF51MaT7UhmpeVwpVKJdrAnJyeanJzU3bt3h1wbcsG8ncjR0VEQ2CgVcl3YEyeeUUigFdxh9km6dolwKbwUAoWXNDyuoHB1uJFkZGRE29vbeu+99/Tee+/p1q1b+u53vxtubL/f1/7+vn7zm9/ol7/8pc7OzvQP/sE/0NLSUhg1lyfk0RU+8/NUDIxOMjXA5QtFzbnidaw7n+XuondtPT4+jmu8jo6OwtVutVrq9/txE0673dbbb7+tzc1Ndbtdfe1rX4tz71UJcGt8lht+ZIqxQ5tg5L6UUqLuhcXASnt5AW6Eb/7p6elQhI3B0smxUCiEC0GHv3Q6HcW48CDkgtBlgKp36o5QKp5EiXAD+4nI4L74oiRzRJwvgtykG4D78wgNnwMMPz4+1u7ubkS2pOvuiB9++GG04h0ZGVGz2dSHH36og4OD6KTAfW9EcjxhEgHkIge4FuaJNcVtdOGFlMcl9SQ731/2dTAYRDLhxMSE1tfX9fjxY52enmpubi7C8FznRMLra6+9FlwYfBNcHPwCkSseV0BemAoBzmHj8f1yjoZD3u12A42yZyg3PoeDjMKg2yLu45tvvhnrQW8oyi0oNCf6TEoKa4+CxHA6opcUSjVJK4CikGuUGOtL7hSvZ14ekXTD4gaaSw5GRkaixRDtaJ4+fRoXWWD4Dw4Oon0z64NSYhwEtDx3C2XE/mDYcONcR3zW84VKybWe1yNB5EHeOlfgi85hlTR01fKtW7d07949pdNpPXnyRHt7exFK5jqcVqsVrT86nU5A9KOjoyghccSEm+jWxRUiTzKS4+QgVu7s7OpKIw8b+2K6MJGj0utd9bLe39+PmyWmp6e1uLiohYUF7ezsRKOzkZGRuGob7o3WIShfHwOujI8DxUKRKkK4v78fiEy6drsRek9nIMDAYWWNOdCjo1ftWOlcyOGbnJyMNriE0MnjomFbNpuNSnl38xypcXicN0LJIGsgdQ+43MS3oHRxf0nM5bXu8nHAUO60KsGFe+mll7S8vKyRkZG4tujo6EgTExNDXTIpmaF9bLlc1vn5eSBe9opDisIAWaP4WRMPVhCBJG3Es9TJyeIzPHDjZyGbveoxBQKEX6T1czab1fz8vDY3N4NjWltb09LSkpaWliI6SqQWuWdc7i6y1kQ04To9v8wR/2c9X6iUms2mCoXCkPZnk4HLziF5t8ckT7CysqLbt2/rvffeiwM9MzMT0B92n0ODcOPW0MPGiwodJqOhHR67ECDs7rc7wkNQmSOKl/C+cwRYdFqugn5ojEX2ON0mpeu2t6xTqVSK66KYO0KGdTk+Pg6ezoWO+WGBEMqLi4sI3fth4Hfu/iDUrqBx0zE4QO7p6Wl97WtfC1QImmR/USDe+IyiVfg4Mv9dkDFeSbcd+fD95MAydukql8eVlaTIFHe33l0f9s8V3cLCQlxPRR+gpaUllctlra2tRRcGWuY6wibhFI6RqJYT0Bg95usBCg/hQ9hL13fBIePSNfKFi/J8NQyyIxKU0htvvKEPP/wwmszNzs5GH3XSac7Pz2OPkL3Ly8tImyFh9vLyMhBoUsliXJhXsvTsi1CS9JxdAjgkWObBYBCtRnCjqIPDXWLDaXEApH7rrbciY/ri4iI0PhrcCVdyaIDUEM3OKQBjPQvYM7bdoiYFgZ/74qIwfM7ejwiFhWJMhpHpwtdsNsPak++zsrKiTCYTbYNTqVSUrdD/h6glSZG4RV7KwSF295UNx2W66SFfCvcPJcBYPCBAMID9kRQuNfzaYDCINrzewgTkSgCEMDSI0POOPELlwuu8EvviisppAj+UPElC24MAzseAPlC6o6Oj0Y/p+PhYy8vL0cOKjgCjo6OBjujYKSlQL8aCejAMCYoEhCYp1g25JB9QunbfcDdRMs6jki9HlBtDw//7/X6UGBUKhUDg9EoHBPiVVryGTgkgem4ccs+J88YtMiB5gg2kF/BzgMHnPc91cQCbipCAkID2boGAuPjQaFT+ZmpqKhp1cegvLy8jV6bf7w8VMoJAqBCHYPeIk8N/FgZY73lWCKm7BqTc43vzWtCdh49RrhxgrCEFqmQBQwr7gaNcgt7a0rUlHBsbC6vMjcQQ2LiuuJEedWOOzI2/YV0RUg4ka4Ph8IQ+J14h952YdWHr9/uhKNk3hJtkwHQ6HcYEHowH69vv9yOtBOWAQmRcrLOTxfxOui4TwtpjxTnMrD2Hl1wwbwXCPEulkl599dWgHPb394f2rdvthsEiyZDLMXBVk4oIZOoV+nB4mUwmqg+gGojKMUdPjmT+fM/esv/kq3nUkvmNjFz1UyLPDkXrmefOm5KzhgEi1xCUxvs6agPhubEh9aHb7YbsOHq/6XlupcRAyPx0wso1uhPBzoWAThBA/P/x8fFo/O/CTp4KBwSUhJJyLY2Qo1R8YyQNuXIe0WEBUbTSdVid90DhIgh+QHB1yB6Gg6FJf6/Xi6RFymUQ3sFgEMQqDcBo6cvnggxQ5swXVMhcPTnNLTfzcfgPFIeoRKnzeRgTR6PscbJAtd+/yq3y9yFCheL1yCEXFbBPXt+GQnKuzhNBEXzkioem+hDyflh4b+bEz/xxmYQTkxTcJg3/iBCDEJFF5gi6RRE5AkfpJ9EpLjqGz1Eh86aEC2PKmHk9yZooYoy8o38MEe/J+4JiOYt8FkqbcYJ0mYenVvhdbx5ogCpIIu8/CKckXfv9KB20rR9WXueMPFrYBc5rZwh3wyFBpGORIBP5G6JYLA4Lz+RdAfq43V/ngLLBWK3R0dFAB34wsQTeAIuDwXp4ZMeFnk3FClGj5VnhKBCfo5PvjJ/3AxWC+kCvCC0RK+egOJiMF9TEw+ewl5DWbj1dWbJeXj3P4aKHOoqEcUMD8DkcXFxh50JADhhDxgpvmYzE8XmsIw/vyXqR78OBYp9dafhhJmOeuRcKhYiGZrPZ4LNAXd41AhSLkvCbY9xowlkm14XxM8YkH4Ycp9PpcJ34PwqF9XYEjNH3lBnAAEYRWYEodxCCIkROQHqMF53APJLtW5C3z3ueqx2uCwKC5K4O2hOhcaLNXQX3o70xGpEZ0g8of8CScig99O9WAaTgTAtp7gAAVbdJREFUCoiF4Wc38S9ssG+6Kz4sBp8HAcrjOSNYDP4Oi8PngKYQdAjhg4ODcEE8vyR5OIkIeh4YytV5FqKANxWlevCBXB2+8jnMIZVKBWEMTyIpGv97cmev11OtVtPl5WU07kMZ93q9CIawRqBTJ3ZJUKVkAQuL3Li1Two4yhTXjZ+xbswfAwdviJwiHygROLd0Oh2IiE6kRJx8XfkK2mS8HGpoBa8pY34un268kSv2yzkiJ/odAfb714mijriQDYIXeBvMk2JsaBd4L864ewZu2FwOGSfriTGnHXYyGPF5z3MhJQSWDWdB3adlIc7Pz4f4GBYBdACCImxJmj49cbhtF9cOKwaZ5gLqpJtbFRdsj7q5Rk9qdRQcaM3zsrAyHlUA3fmm8VkoZOAw1gs/njITuAPW1VGPK1/WCuFKChxr0e/34ypxfu/GA2FBQXsLW4SORDvWEpTQbrfVaDSiq+ZgMIiWJ/Qm7/f7mp2dDZ5lbm4uBF9SFAbTKoR1JWDi7hH76iQ3a+2C7VYct8HRCsgWThBinDVC6SUPLcgHAjifzw+tF693Qh6Z9/d28tfD/87F8I+9gZtBNpMI15MQHfk7uc/P3CtJp9OB6FlHwAA9xi8vL6Mt0dHR0RDCc5nzSK7LlM+HCB7jdwX+ec9zcUp8KDyEdI0wnEfyDeBQsckIILfDkrCFxSUjtlar6eLiInoM0ccJpIJy8kJKT9aifsoPL79zYWbjvZiQjfZsbbS8dx10IcHCeZTKBYKDRtQyk8lEH2eCBe12eygr25U+42RdGacrEkcTKG6fg6MhhJp9TSqt8/OrdrB7e3sxJm7oYN1BNHQARQinp6e1vb0dypZLEb38CNlhneGB4JpwvzjsfD5uknOTLuCOrpwPdN6NUpBMJhOcHDLA+JBXPp97CUG3oBr6e9OjyIMijN8NKuOAv8JgonQ49Owf6+Sy66jQFXdSGbmbLWmoRzgEPjdbj46Oqlwu6+LiIsqk+v1+oF26m1J47NwsZxAEij7woBOdBZJj+7znuZInOZzOcyRdMxYWTY9VlK4scq1Wi6uv9/b2oscSfZi2trYizA30h9FfW1vTrVu3wr/lc0APuI5ObjsR7pocSF2v1yVdW9ok0e1QXLruR86BZ2z8LRGNVCoVm0lYnz42XLRJG4mTk5MgHFEOwF3GS36YK17v5eyK1iNVfmgR5sHguhyj2+3GHW/Ow5D5zfsR9u73rxLrZmZm4gZiBI8GelNTU8FpnZ9f3fLLrSrwFihzkDB36xFdxdhxsN3FciPjPCayB4+CiyspDAcKltYiHIx0Oj00LroUNBqNuM5renpa9+7d08TEhLa3t9VutzU7O6ulpSUtLy9HtwRHR8gSvApKGPTP2H1OyLRTJckqAo+s8ffIJm2BkAnWWFKkMAAEkI1MJqOZmRkVi8UomO/1etH5Ym1tLZC9ex4oemruiK5y5rrdbhD5PO5Wf97zXEoJYUFYGbRH39xan5ycqFqtRtOvfr8/lPvBoOhjRL1S0p1hY/b39/XRRx9pZGQk7nljbJKi2JWD4dbEhdaVFveiJTkC56+IaDAOh+ashTe4B/YfHR3p/fff18bGhh4+fKhqtarz83NVKhWtrq7q/Pxc9XpdZ2dnKhQKWl5e1tLSkkql0qe4MDKzEfZUKhW9oB09SYpiYA6idO2+YUyIVuFGQ0BLCqW/sLCgV199VZIip+Xs7CxQxOTkZLSkGQwGcSEmLZOxjhxsxkUkx4XTLWsyUOHui+8juV7sC0qQPXO5dRcNhQvvBtUAuUtnCbKbQb8TExNqtVpDpUqPHz8Opf7tb39bS0tLMQ72z8leeCyMoqNs3DpylDzdBePjBD1nzgMBtJdpNpvRAoV1xrgwfoITIKLBYBBuOZ9dq9X03nvvxcUa9KD34AFcLpFhR2+c68vL63sSiYZ+aaKbgSQjBPzOu9DBDxwdHUUvFtLz8T+psC8Wi1peXlahUNDZ2Zl2d3fVaDTCYgHZPdrEe3sEEAUGanEo69+7D35+fq6dnZ0Qakdg7tZgUX1ug8EgWsW6RRobG9PGxoZqtZoajYY2NzcjiTGVSsUlle+//35YzpGRETUaDT18+DA6L/hNpJeXl9EGgmiXl3M479Lv96PNh1sjvnqaAcof1xSlTJ8jspa5LZgiaITt8vKqgJXSn0wmE+1NWKNU6ur6b6rOOZTO10GCM99kKoNH7JADFA5GAWQJV8JBZ30grx21VKtVNZtN1Wq1oWTU8/PzSFEhSkouFpc34h1gqB8/fqxHjx5FKRHN+NyrwDikUteZ5c4roVj8kgrWwEl85uPGZDAYRLGtpCGEjjEhKgiq6fevatkODg7UarWiPQmoijPS612VdH3yyScqlUohG+yhF6hLGlLGABGMDefgD0J0Y5mwJB4mZsEhAPm+3+9reXlZd+/ejZAnrhkV59nsVQ/gXC4XiWnk4xDNoSeL9yViEYCLhEOJEjnndZN/j5V1X5eFQpO7pXJinQWn5zguGK9BsJxPQ7AZP+FUSREpuby8jCZpv/vd74Y6eGIhadZG/RGKljn4Z3gpEJ/lgu4hXaKEGBj2h4PvOTTn5+dR58c6Q+JDIJPx7GkIvIYIG5FIGoYRNoZAZ0+cg3JkRU6RpKgl5D1dmVGUy9+AkmjYxrXiuPKlUmkoN4fwOXwiWffIm0eVPvnkE33wwQdB/sNtQiKTgOjRKZQhCpNmicgf6SquYN31khRoju6o7Ofx8XE0oWNdaOdDOQwpAVtbW5Eu0Gq14m+JmvJ5HsUDiDjXzBm5uLiIchZADTymeyWf9TxXSgAElvMoHFSHlL1eL6B9Pp/X/Px8CB7anE2gop4CVg7x/v7+0EEaGRlRqVQKxQUZirViowjXY1EcKbgb1+v1tL29HRtPAawjBlwCBJ116PWukgNbrVa0QoHXAnGR5ElV+czMTEB0kAGHmb87ODiIJLZut6t6vR5WiMPr5QDOG3BQaV7PfiFMkMNYVdZIUowJdxyFwI3C/M7TA3CDaE8MAgY50Ofb867gjojkwWE5H+d5S+w/wu8cJvVZHMp2uz2US+QKBJcTcplxofSJGmJcIK5pD0v6xtTUlJrNps7Pz+MORCLHlGQUi8XwBCqVinK53FC430l8ZMmVG16AH1iQTTJyxbljjUul0lASLu85MzOjg4ODMMpEwtgvUI9n5aMU2ZORkRHdunUr7hik/o36zmR6AECCMhYCPPzjzH4ppeTuCxrY81s8V4HFY5JOJnJA6NvrroYnEHLIEWbp+iZPLDF5Fmw0OU1Eh9DgvgAcsNPTU7Varfg5wuhRQuAy8+SfowquvkYBOBEOkqS3NqgD5MFBoZwBS43CJ2o3OjoarVIRxKSSxOKSSsFac7BRQMmIm/cn8ja8HGr21oVpfHw8LqGk9zeuh/8N/1AGHGw+j3Hzd7gKzg25ovP0k8FgEOkj0hWP5kqJQ8Ce9Hq9IWRO9BOZoesmV3WhdFEAzImyCxAF64mMkpHPPzwJUCDuuvOFfrkqSt6jU8kUBxQGqBPECKHNmrkXQ1ADdIxSGwwGUVvJOmJgMIKcEYpx/VIJuDgUHkqK/k3tdjvOrcvjH8R9Y3EcWXikihR0snv9tVgqtDwLymGhLQJujR8EFgLXZXR0NLoEoPzcaiTJUYe+vK7b7UYzL88D8hoyh6buAqEoEeJyuaxSqRRjBvl5/Q8uCTkqCAkkZzqdDigNEsDV4HW5XC7SBzwSiJFgvu12OxQ6yJY9YozsG0J1eHioqamp+GwUIpYdhcv+TkxMaGJiQisrK+EO8xVeByXKGIkuuhw4ec1euXvmhDaHn0OFy+G5PKAlyo+w0N1ud6j6QNJQ8inyyOegKFhDeCwUODwMHA3yyfvjpiEz5ABhzDHAnscDooOjxAOQrusyXbliHFA+nhIA8eycFsgG982jhCAxZMpz6wAizM/PkRs46TpjH16Ovt6ulDhbX5QOID1nnhIQjUEeHBwMFWACI5kID4fdc2XGxsaUy+UkKRqbuYD5a9Ha0nV4k+Q653E4GAgR1ogD4OH2arUav5OuITKH1jfVNwA3ggJTCHsEzVEhN1M4wY8VBomwaZS2sG6uBDhcHhnEhWGDcd1ardZQtIbxfFbSGn2Zve8SSgKBZ93h8Pg8v7CAcUqKsgOQm6MP3tsNhrtZ7CHKLClD7CORMrgV0iUajUYoJU+dINrl8gTv59ndyByKx2WMPcQA4CZ5kIeIlr/O5Qa5Yv4Q9PB0GHCfO4XY9GZizOwV8wfRI+/Mi7mjmEDnHmjBkCF7yBdz8Vt8QKyShpQboIKIm7cuRu48Uv+l3TcGy8GZnJyMPBvyF4Dh3W43bgllwSQNKbRs9qqAdX5+PrQvG0lz/H6/HwebjUAhsXAIpkdmPFKHEPjiHB4ehsCxMORTJbkUyhCYv6NAhBgiEIHgQPC7TqcT8+DzfUzwLA6PEfhkcqC7Egg87gCEJsIiXfdndgXl8B2UBkdWLpdDOWAtcevYR3gvxgPMxwXxQMTk5KTy+XyQ/1wLxdojNxDk3vYExORBBkcm2Ww2unpiMIkEgiLYV6gFSGA3Ol4J4IEF3EzWAwQAUnFUB9Jyg+kupxs3J7dBTsfHx0N3HPq54SYVFAucF32xKRXBGCEroCfGhoxxyUaj0QjjwTicP3X5SXbkYE88RQFKhtuIcCkBKR7NBnh83vNcSsldJSAp5Qy0a0Dzuh8MQQq/gh88GAyiABDXBYIZSw8HQ50V78tC0u1QGu69w6JJ13VfCBRuEKSupEhDoK8NX7EybBD+OzCaDGEW2QlEkIW7I7g3l5eXQ5/vyieJytxSs5E+P6wfOSYcOn4naehnLnAISqFQUKPRUKvVipYykgIRIYyQpP1+P/Yby3h2dnWVDqkRHHxcTg486+plFfB8KCXWn7QFlHilUolD5gW4/X4/XCTypait9PIP7yzhLTSQRzgnEkS73W70QR8bG4tmexhG1gF0A5fF2rssOr9HigeKi1bQrhAwLM1mcygwgELnrPkhRzYZD245r8P19R7wfrUTiJegFIbPzxdgwCkP5kT6AGQ9yttTMvj+i57nSp50gpTJjY6Oql6vR8Yrguq5Jmw4VpVD4GQ0rh+pAyx0JnOVIQ0hyeQh5FBmn9Vvx6NwcF8IuWvrXC43dBUTrTkIezukBgWgJBirH3ZePzExoUqlooODgzi4cE6gRsbg1tYFDUPAhiJ8WKrp6Wnt7+8HUc78PHmS9fffsTd89tzcnJrNpvb29lQsFiPtgCgUtYjdbneoZAa+BTTDgWL/PPLkfYNcccKreEQKBIV83Lp1K1IrPBjC/EDwzWZT1Wo1lKAn7YHmfK9wgUm+RQHSxgPi3cn46enpIKXJ3WJ93WuQhntx4+YTYe33+9HLHKXIWWOP9vf3h5BJqVSKSxTcYOF90HiR8+kpHs4TkqoAcgOt4l6fnZ1FoTguJt+j0Dmr5FYdHR0FEua83MTNPs/z3EiJD2KhsSb1el3dbjeSxhBMEIFHXAh/S9e5TR4KZoJEr1AguFTkjSBcTpTyfyaOpQW6swmuDCRpbW1NH330kdrtdpQLONRnQUFx6XR66OIENpqbR1zoC4XCUCsI+ArGipWi2byHVzm8KCfG4m7D6empnj59Grk0TnB6+Jl1QOhxJxAYFOiTJ0+0u7ur09PTqIoHPSH88A0oUofyCDTuhOfeOMoh6ohry1wxPrh809PTcfuJ5+cQFOH/yFM2m437ApeXlzU3NxdjhxogpQACFwQFmifj3e8sdOTKWFCcBGtwyxino3QUCPINGknmleH+e6CIS1tBJ9QSgoJQ6ufn53HFPPIDOe8AgHPF+Dw67YiS3zE2UlNcNjG23OnoxtMDG9LwFelf9DyXUuJNEWoWenFxMULaWBGvAyJk6oolGRXDyuKucaiw9Hze8fFx5JYkXRSUHkoKBSddXVaQy+WGeADmI11FTEqlknZ3dyPPhk1z8totFmgAZY0SI1EO6EsRJweUcLGTfpDCjUYjlJR3HuRz2VRHCI8ePRpqfetEpL/OSXFXSP5309PTqlQqevz4sTY3NwPC4x5xQElCdLfQI1DsA/uGS1woFCL0DRnKZxDdcuQxMTERBxBj4iQyhx+lLSku3Nza2orDMTs7OyS7rAnV/xD7IGPkjp+768Rc4Gn4noget8Kybz5GULITwUkFxmtdYZBLdn5+HlX7JB07JcL6gWI9KRN0TW2m7ztjIlLJGngOmo8RA4kxJXMcpYesoWSTnpbL5mc9z62UfDIclKmpKc3OzkbhZafTifIEhAko7GFiICobAJ/k8BrlIim0Mf4xVgdOA9fAYb+kSOLEX0bg3c3LZrOanZ2NVAHGdHFxEfU+bik9H8uJR+k6kdHDycwPheZ36LGJKDKSLknP9xAvgoWwt1ot7e7uforE9rn5k1TG7o4zr3w+r3w+r4ODg6j2Pzo6imxhj1SBuHDNScTziCtuRjqdDqNDzZ+XRlBXhsHCUHgms8sMnyldo2PctbGxsbhlmaxibpWBiCf0zf5h3Igkw7sg614GgvvD/iJ/XtXAwQZVwGWSv9Pr9YaMN8oNQ4jc4zKD9HAZSSbO5/MRCc1ms2q1WsF7wes6OmJtWVPG5sYMZcTYQPEoOpJ0UUa1Wk2SwmXmH7LoHBK/+6K0gC9USq7xeGNYd5BQoVAIUhACuFAoqFAoxAGHU+JAd7vdIMWcuEVo8G8lhUIDiVCPheXwpEnagaCQOHjuirHhzIfIBIoJV7HX6w1FE6XrHCHnnxBQDgwC4Hd0cSi93MZzP0ALKEFvnwuS5CuXerr1QhD883lc+fN60A1jxjXlaqt6vR4XE7bb7aEe6U5kDgaDiAI5mkuiGQ6/8xZ+lxh8VS6XG7qSCcF23ubw8DA4Qt4Pl4wgA7KBAiSvLJ/PB0lN1jVj4ACDAj0SB+8CUvOIL7IM14URvby8jNpP0i96vV5cDoHcJ1EEeweaw6ChNM7Pr/qOTU9Px9XxuVwu0DhJoriDyCwgwaOIuMwgYNDtyclJFPeyHkQKa7VaBBaorXP5Q74cjXO+OXOf9zx3lwAEG42OtqV5GW0r9vb2lM/nIxxOrRG1QGwyKMHJ0FQqFa4WbhK+KwcXhUSyIGn0FOpOTU2FZfcNduSFBWKhcLWKxaJ2dnYiVMvneYY6c0BpjI2NfQrRDAaDyEh31w+B8hwd1rXbvbo/zusE4SD8INdqNe3t7cV8CL2y2a54petWLM4JeniWcDwRylwup1KpFPks5Fo1Go3owogCcx6LqBv7i7JFaROiZx4oHOk65YLDBWIk7J2MPm1tbUUKxLNnz5TJZOJWlYmJiWg8xyEiyjU3NxfGijFiHDAAHnzhuiRcURCHZ2kfHR0F+sONY89qtVrIKnSCZ3wzf0dl/nDRJSiN/YQw73Q6qtfrgSxnZmZi3vS1JyJO3tH+/n4gPc6Yu6AopNPT07hlGaKcYvOzs7Poqc85du7SkTpgALfS3dPPelLJhRj6ZSr1+S3ivnq+er56vnp+z2cwGNyonb4QKf3zf/7PdevWLc3Pz8fNtWQyY3WBiiRgoQ3RkkBkyEosjpOjRGY8/8LD2XApHjqWNFSn5EQosPTg4CD+eT6MJP3Lf/kv9YMf/CAazXmFu7+ndF2awRz4LNCcRxXc1eD1WGN4GObh8/QUAM/Ncq4sGQHiSnMnWbHW/+bf/Bv94Ac/iH2iMh7uhTHigsFt+FwlDY3b98PDvTwe1k+Gxh3ReTEqURx3+UCKWGzcoV6vp3a7ra2tLf30pz/Vv/gX/0Lr6+taWloK7ogn2ZHAyx48aCBdp0sgp07YuvV3F5j/e54Qa+/unSNY1gdXibkhn+zxv/pX/0r/+l//a2Wz17cMI5tweCS5MkcnlflcXG6v03T3HgTl5/CmJ8kVeZqJu2y+DqBi5uu5Tm+99daNnyM9Z0EucNGTvhB0lIsrp2RUhol6NOumsKSHK4GETuB6ygEukJOhnsfj6fzwGZCiLoyeRsDjeSOMj7n4vBkTnIwrI94nye/4IUYgUOL8PcIBpwHH5uRyUtD5OZ/v7iljdfeENfP1Z57M0aMnvu6euY7RcffeuUPmRRmSfw6f5WHmZI2Vk/euyOGUIGApCCVpkM9m3wgs8CRdCN8Hj7rxuPvrcsI4k6kmrsRcbhk/BscVcnIfDw8PoxTJkz6dA3Rjwucmz1xy3n4OXU59bknly/dumPiZK0KPGHMOMUhJhfZZz3O1LkGDe0U4vqoTn2jTZI6Ma9+kxeH3vtCOTnzy/L0rKg6mHxAsLtE5IgyOUjytgHFjifzguTJyAXeuCEFg3CgExubzcCSZjET4hjvn4O+BgnKr7MoWAXHF6ISt1+lhBBhzcm4+viSqcAvpe+n5P/73rtjcyPBzt9y+Ps4tMhdH2Y4m2eeb+Au37L7mN82P1yfnxVcncj1Q45+T/N4JawIfcK7erdIRHM3mQBleEeEGwJU8c0nON7kPnDnm4nP0oAjzcIScXKebziTJpj5v5pZE18nnuYhuPsA3n0ODEDAABCZ52NwaJ10WHgQNBeMCBaxl8slDw6SdFAYi8/Ok1fUFd63OAXa46huaPLg+B49MJQ+yo72koLg75Irws1wksoyxsklF64+H/QmLJ6G8IxHvAuFjdKFPziP5mRinpHAnDZCjpaQbyxxRwqwpe80YvbiVKBqfx1j8MLhs8n9Xmv7V55MMJHye9U8ebF9f9sxdVmTP34vW0W54kFXek/1KGjjfG8bjj59J9jNpKJIuGu/j59bPk++bK6Qk0v2i5wuVkmdeo/F8wZPuhE8oaemZ+E2TgnNxC5x0s9xiJhfJNzPJgfB/fw9HL563gUtIdIkxOiLzaEby0DFXXDDfED+4jjb4fJ8Hhzo5V99wjAS+OnNxhODIKcntJN0pVwisB0Lq+5E0Do5K/OAmD4I/rniT8uGI19EFe+GK2iNevu+OWkFfzMvXgPVyV8bn6WuYPPQuG7yP75/vv8saRsRdOT+8rpSYm6/nTYopOQenTnxOjqaTyMr32eXH98mRHCk7PkfWwuXOx8jef97zXEjJF93dMz9UHETIQRdM1+hJgpHfkRbAYoGObkJCHMLBYBA8iQskYyPr1seAQkoKnFui5Ka4IHijrqSbehN09/f0g3HT75JkYtJC+tw+y2r7ezN+hMoPdxId+Dqz9qwVCpxSG9bMk119LEk068o7eUBJR+DzeFxJ+lr6nknXBiCpYL3FB3uFrCbdOsbp++GK2xFe8ue+Vk7w+3zdbUHZplKp6Afuis3dKU8DgBNDeXvpFueK9bjJUDjCcQXFefW//awnqVyk61bFyT3iXLoBuUkGbnqeK3mSD+fDnBcBYiPs8BRMmNf2etftQFh4lAEHAYvmE/XXeCMpRysoRf4e5JVOpyN/yoUwCSHJOboJWiZJakd7bhFYdJSXW+okyvJ1ZR39NUTbuBaH2j4+E6GGBCVK5RYLIUFo+QzW2l1s3pd1daXIa11xk7PlLhwKLMmL+Po5YqR0iBYvSV4GeYAg99/jYvO9fz4yANfkWebenqPXG27Vmow6JRUVSpJyKeaHUnXl6q/nTPgeeJSTXDjKp1wheqse5zNxAbPZbCT5otB4LevFeXXUymtcASJ3rsCS64D8sK+u0G9C3eQDIhM3ccU3Pc/dedJr0chwJdTH4NHoCDUlJmTKko5/k1JySE06O6iI6JkndiG06XR6qK7MNTWLwMFlDtK1tu52u0O3sg4Gg08l7CUhtCtolKikaCGKomGOjAO+y61RUqBIWqRG6vDwcMitRZgdtVJIilAluQQEmsibc1UcXtYWZcEh4xAijHQAzefz0ZoYRMoBcpfEUQKH1jsm0KDO3WZ6EyFPExMTQ32vQKocDnhDDiPv60mObiQHg0H04EY+SRlIupWurJFB2o9AUrNvrN9gMFwGk8/nIyNeuu6bTvb4+Ph4XPboe0fIn6gbJUrwgrSz9dfxfsivB29YL5dNPtPTaBzR9fv9IdDh9W28P/3JHXGh3Ah6wJ8lOdibni9USkTZOMRU+lOQx+ag/fzgcQ/b9PR05I/Mzs4OaUzgLovgtUL0Z2EzCP1ScsF7ZLNXNzTMzMwEakIoki5R0iVho1hsEASHyZVhkkR313NkZCTqkBAOb3tCHhYbjRLm4PthxXpSmuAogfayKGXpOoUB5ejoBGuLAqOcgPVjTfkssuRdkbgspNNX1/dQd0VzOs8B8nwjV3qgXPYWREhPIcZYLBbjqiAUxejo6FCnAEdiHK6Li4u4DorMY4pUQXGUXJCbRskHGdD8LpVKhcJhnS4vL2N/Dg8Ph5QT9Wn8DQZkdHRUhUIhqvUHg0HcCsx6esjc3WpaTbNnyAVuW79/3WQOd3B8fFylUinaA9NPnXV0Y+1o2OWcdjucTQwehtCLkbkohHo7xoBnxLwwvj6/z3qeK0/J4XCj0VC3243B086WdiMohVQqFWn+lHCg4FigdDodm8333oCcTfZyC7/CCFRDGjzWxkliFA2LKg1HkhzSp1LX981JiiJK6qgouQA+O7ojoS2Xy0WvZhqOMR4EC6vCPJkfFfS8js9l7NlsNu7JQyCTZKW7DQi+/54DhTLlYLFXIDTnjlhjFDx9rCk3IIGPntGsTSqVilwcDq63LQGNcQsLCANaABlB+bKGGBZ+Bhqq1+vq9/uhZFutVrSZAQ1zHVA6nY49pW8Xc+Hges9z9olODuwT7VlAMhxylAnIjjo/Dxb5fiHTLpsoyW73qlukG0TOHDWC7u52Op24sYXOGpRH+XVIbjQAHt1uN2TBEx8xKu5+AgSgSZy3RD4YGwjSc6p+b6XkWpT+N0B6Dk6n0wmXB6TBpmSz2Th0FNNSuS9dI6terxfvzcHwuiOUl3cboLYMZIP7AvnpkUJcCU/4ROniDqEAJQ0pRridVqs1RHqmUqlIXmNzOeDU+nkmLVYW4UQhuCJ2AWD+jhZcyXjEhr1CoBE69sJdNJAGyo8DBlodDAbxf9aMroVEu5ycpSEaf++JthSnooQcDTN+lB5r6TV17jbfFCHjgKGsvFYQZYCxSaevW5Sk0+mgFE5Orq5Up04TdOkuDI3dqOn0PBz/h1x4Eimf73wsyor5eEufZACF1ADGgzKVFD3jPc1jZGRErVYrWpzQNZOaQjdkXmsJFUF2OR6Ko1zn+/hbjBzIDrmjUwGygRH50koJWI429QnhsnAgUSTuV+O6ISBUMNMADV4GRYTig+Blco4c2HjaaeAuseiTk5NDFpFDyvcIBt9nMpnYaJRTsuueIyMnhJM+PcLJwQM6o+goLgYtoPCwUI4Qu91u9O8mNcN5CfYh6cs7j+UHl/nwN8yLuSe7LjgPNz4+HsW6DtFBH7gJrDPWljIYOCQUlRPz9J2Cg3SXhHE7Yur1etH2BKQBqc06DAaDkE32kHkiMxQBF4tFnZycqFQqKZPJDLnIx8fHUfxNOQiI2ZUz++n8IvIN+sJF9BbQ7oayZ84HSsN92nHJoDOOjo6GeFnQ0OTkpEqlkkqlkgqFgmZmZqJhH61OUPgADhQeiMiTkLncwOcGxXF0dBQUCpfLwtUhmyijPwhSwoKAjjzqBHpot9tDXBD5FaCnfD6vubk5FQoFdbtdzc3NRZ1St3tVwY1lY+NRbBDLWHBvGue9qYHeVEZzHRLtU9xqeYgalOWIjc1wzsNbT/A9i0xleqlU0sTExFASJsoTsg8o3mg0ov0KVs/vUeO1IJl+vx9uIQqQej13ZTwSxQFNEu/ActYaF5UaQb+FhJtica/d1YLHmJiY0OrqqgqFgnq9XlzuuLe3F5XlKGtHgShVrC/r3el0wpiBhFFKIAzWzN09J9XpJgH/2ev1ApmSKZ1Op9VoNFQul4OPLJVKKpfLmp+fV79/ffU06wJdAXEuaQhRwh1yjdf5+dUFlhDrIF/OhBPP8DVJw8M6QUOgQFBIbjRdAeRyOZXLZZXL5ehMSRcNpzxwo2m6h9xwTjj3cGFnZ2fa29tTr9fTCy+8IElhTA4PD/Xs2TOVy2XNzc3F9Whwv066/95KiRsk4DQQIO5jR2Gl0+mIorDx+Xxes7OzwTVw20GhUNDCwkK0t0Wj0icIDoWNSqVScTAg1uhNDSdxcXERbqHzQGhwkFOSZIMHw2qBDg4ODuKWECws/WXoDIkilBRWBgTF2GdnZ7W2tqbx8XG1220NBoNAlNz17gQ8Ss6hOjwXSIFLJzudjiqVSkR2PM+LceFauvuHy4hCQlG0223t7e2FcBcKhWjYD2ojsoPQjo6OamZmRgsLC9EypN/vq16vB9/jqRbZ7PVV5hg69iqfz0ekCTK9XC5H9Bbj4i4r78drsOzs1eHhYbhfBwcHymazQ7faoihAUrTgnZmZGQogHB8fa3d3d2geuLJ4BZlMRrOzs7q8vNTTp0/DYNP7aGFhQaOjo9HgLp1Oq1QqDXGsSTeVOYOWMJAgNW6OJiJ9dnYWhqvX66nVaun8/Fzj4+N69dVXQwHjoaCcURbT09NDqTicoXT6Ku+vVCqFYq7X68pkMmo0GkOdW0dGRuLCj8XFxUDXyeDP762Uzs/P9eTJk4BkuDcoDhpora2t6YMPPlC1Wo1JcUMsGwac5RYTrALV6yAbUFc2e9UFEPg8GAy0tLSklZUVjY6OqtVqSbq+E25xcVHj4+Pa2dkJN+Lw8DAOE5+HVZaucyb4PUoHwXVuRlK4pyCxlZWVUEQ0ZEfAJicnNTc3F4oZ8r/Vag25l0SWaGS3tramUqmkZ8+ehVKanJwMBbG5uanT01NNT09HP22sGImlzAvhYj1AFrwOCzkxMaG5ubmwnun01f30q6urGh8f197enprNpiYnJ1UsFsNlK5fLcZ0z7z09PR1XlvuNLyiIubk5jY2NqV6vh9Li2q10Oq2tra1wX7HszuP1+/2YL0gX3ssPFK7y7du3dXR0pEePHgU5j7HC6OJ+kuqAUseVKxQKKpVKwQWCapwfK5VKWltbC5fm6OgoxkmvKA9cNBqNoVB+kkuiXzhdHT014/j4WIuLi3rw4IGq1aqePXsWcuWusCfBclOx19A5F+gXDGSzVxc0bG9v6+TkRFNTU1pdXdX6+rqq1WrwkA8fPlSxWNTS0pIqlYo6nY5OTk6iYJrzggFHCX4ppZTJXDUfx00g5wdlQf/lcrms9fV19XpXHekIS+I+pVJXLUiXlpaUy+WG8m1cIOipDOcAsw+iQQgLhYIWFxfDOo6OjqpSqQRExIIxbhAIGdk8Hor1zUI4zs7ONDU1pfn5+fCTj4+PNT4+rkqlokqlotPT04hKglqITABfiQDhHsBlQIBCsE9PTwdhiGt7fn4e7mE6ndbi4uKQ+4KCkK7znpz8RsjIVaLDI0gHS9br9TQ/Px+cEkoWpAqnMTk5qdnZWZVKpVBIICcQRLFYDIXMmhI2hlcB7jNnlEWhUIjLNTkkKACUkysluEeu0OYrOVx0nDw/Pw8CmMgUF0rkcjmtrKzEteR8DmtLZDWdTkc+HHwX606Eb3R0VMvLy5qYmAgOFPnG1eJsuauGoUI+IedRNMyt1+tpdnZWCwsLofhTqZSKxaIkxUWhuJ3ZbDbOo6MVzhd0B5E+eDAidxiC6elpZTIZlUolra+vR6M3jNPMzEwEDhjrzMxMIFK4wy96vlApQZJxsEulUhx4JgY6WFpaikSwZD7E+Pj4EMphYTzEiAIii/fy8jLu3ULwIKXT6bSWl5fD95c0tDlYFtqjOlkMB8HYOHSem4ISpXk9Ar68vBy9vBHSkZGRcDPGxsY0Ozur2dlZlcvl4NVAT3QJLJVKkauDMsJ3R4jX19e1sLAQSYQceoQBASQCA4fBYUUp8bkc+EqlMpQvBNLDpQINwGVdXl5Gzlkul9Pa2poqlUo0rkfZMQeEmlQQwsKe/oHShr8DeaRSKd26dUuVSiWSYv2iR/bFeTQUpreCZQ1A4uQMMUcCKNJV6B3Z9IMLwvD3GR8f19zcXLidR0dHQ61tMWgoZH7mOUm4n8gdChJFiNLCwDgvCQ0yMjIS55I17vf74aJfXl51C0Um5+fnI8UgyauiFJOZ34T9Ce5cXl5dfJrJZDQ3Nxf9+FFAnCFHrxgcXNQ/SPJkuVzW0tKSTk+v7pOan58PEqvZbH4qIQqXAujM4pfLZa2urkZaPL4yfBXKAIuBApmamgpXik3l81gQlBUb4744C+KFm64wfdylUilcGHgJbzp2fn513zrRJDbKUeTa2poWFxcjAshn8M9TJbi+XFIoKObhh8APmDTcEgZli+X2iA6fTZg9l8sFVwJ/1mg0IrCAQuIQURYETzAxMaHZ2dkQcH+8bQiHGtSUz+eVzWbjJlh/+AwUN/ua5MH4jFQqNXSd1cjI1b11kOMLCwtaXFzU3Nxc5AyR1sINvyhbgjEQ2+wHipzXkGaAYgEx5/P5aHVLACiZBIlsghY9GgX5zYFFQXu6A3s1MTER115h9LlNmXXyv8NlcrfNFZKvC+iI9YTicDQFuQ4VAGLGILLXnhbEWSbayHr+QTK6sZBAMPifsbGxiMbA4KM4gGr45PRelq5bb3jUBSvq+R3pdHoo6ZIwJmQ6vIgnDvJ3JPMRkYO38eghhx0+gk3EMsBbYd3hYCAGU6lUZATDn+HOeB5Wt9sN/sL5HfJLGIPnshCyB6kkhdxdQoQIpYeFRUA9PM1hTpYTEDVFaThvRCSMz3UUhuCCQDySlDyU3EvGHnnUCOPF3sM9oJRcmWHY2L9CoRCRwnK5HPJQr9eHSjMcXbJnyCaH0pP/PFJJQIbXYRD4XNbBk2IxtHw+a0LOF+jCc+fYS/aO98QlxrXExfNcPPbF95ngD94Ba8D7Io/8vUc5oREKhUIEtJgXyNDBhKdaoJBA0q5kv+h5roJccg+YoBODoCKUDDwSgowiYjFYRA5rt9uNaJRHaRxlYVU8WdILOhFYLO7Y2JhmZmaGioOxivAUCBcugmdHs3AsZjKrvFAoBMeEFUKZuHXhSSZ1ukXjcygOJZ8Fl9Vzizxh0/OfPDqHcNNY3w+Yo0x4GRAC+0FOEC4Fnycpcoyk60x/1ovMbS9r4UFpuTWmZgoiNFnO4oSoZ0mD8KampuKzUXigAemqQb8nihJMgUdijfl98qsra1C/o2vkGC4LjowDDSLjb1kz0gFIXQGJuVFNpnMQ9GHsqVRKjUZjSK5BJBgNxsC58tA+f+eKms/DaLO/brA9O91LcFCmoCWMGcow+XxppHR5eRk8EMKGRpybmwtITJ4PKAEextPTmbQnnnmpg3TdOsNza5iYk7oQwfjYftBdgYE4vGjTFwq05clnEJwLCwtR1sH8IPbcwjEPcntYeISX214lxXjYUIf8cDEcmlKpFIgGhYiS5rMddSahOeuJ4PsaotC4xoc1Zw6gItbFraN0bWSc9wDReSIryhVlnEwiJMrjWcWsQzqdDqIV+SHi64mUHlVijvPz80FuezGo3/ABqvGD6YYQBO81d3zvRseJYebNmL1IF96MA8v58mJqRzMoLfaHaLTzgr6uKEaPPIKo3H1C6eJ1+HlD8TuiQvHB33HjkFMGrImni+A1IY9+Nj7v+UKltLe3p9u3b8cbEb1xX5VJskhwHH6QESCHmNx9zqKRE+LIAjcJK8DCAws5DBxe+BAWCS7KYTe+tDTcpwmkwWcC7d16wknxPiAZ5uBoK4lQcNewKLglXiSKYGP1uU/NuQ0sutdRJT8ba4vQ+5jdtfMIkLtnN7nEWD721qG/57Dx2unpaRWLxcjAdniPC+VkKqgJOSFMzaHzORF9JDrqBcFeb4jL7MiGvCRHMMgDSnV8fDw4LE+8RWk4MkbRsHdemY9iRDZ9n0DUHpHyyLDvgbt0UAUoBc4Qn0nycnKf/Twhl4wB+XLD5i4dMpCUGVc2jIHnJiP5ByG6q9WqKpVKbDqWmUG5H+pJXrgBzvKzAL4x0hVH4KFVoDMKgFwSLA2WCUHhMHkeBweGMfp7++twHbx41olXHpQJ7iiCzvszDt9s3xS3RAhVKpVSs9mMv/GERMbjAuBZ0cBoXFIQH//4G3gqFB9zRHHxNem+ulXFqKAonJBlTuwpBwRESXIfPGDS5WAf4TBQ0siDGyjWBpTM70kYZF+9Xs6VJJ8D6gA9MT7PoGYd2XMOrXe1wLXxIAafg/z0er1QOr5mLiM8jj54+D3Kx9eac+dZ/Shffz9JQ2PzwIu/zpGqu5IegfTHvY6konFFyu9vmt9NzxcqJcKexWJxiHeQhq8dYgERGFc+Nx1gFvni4iIiO9L11cnuT3tIFQRBmwQ+gwXwhcOKu2XAz/bCW/7xGb5hHlFwSOsbzqJ7axI20XkfNoRwOWuA8FLwSdTNhcI5KeYKqe3chFd8S4qfsc4O551fSq4Tyofvz8/Po4uBKyI/+CBHFOZgMIjEQM+j4oZb3BgUY5LT6/f7Q1EllG02mw13n+x7wvIQ6Z5q4u+J7DFu1ibJF5EcKF1fXsrBJmUFeeLAuVvmwQf2FyXk83Oj5R6Hj5l5EXxBHrzYm3m67PGZ7AFrnXTPWUe8DtaQ90/yQsyLx5WTn42bQInrgs96nus2k8PDQ+Xz+eBvkpwGi+ALDneEQEvDFcLwTGyqJ0cizLz++PhY29vbcb88kQssEhvn1sf9ab73uitHZqenp5H9yibgW7uCZcGd5+EfaQuMya3gYDCIgADhaIQEi81V09Ra9XpXCaK0hOB9XGHA86CI+DnzkBTK1pGEu1qOhFhH0BiFsxRknp6eBqfAwcfq+do4GcoaM1b23OWLvXTUwtrzGhQ6a4eSI1AyMzMTisnRIuvg7wO6IvsYhc9DFBK3iwPsKJpkztPTU9Xr9WiTUi6Xh5rH+To5inG6AbfVZUTS0N+yH1NTU+GFeOkUiiJJ1IP2PALndIZzmnwm7+H1dMw9aTj4nUcOk6VFvv5/EKU0NjamdrutSqUSocikIPpAk4vItclYcwSF93Fho2bO+9iwaFyNLCkuxZQ0pDxcS6PxsYbeogPUwoJ62YwrNedWGIsTv6AHclVQIrzGURvjobaOMdL6gcPikSj+hgxixoyFJp/Kkx6Zh5ed8D6sJV9xQfgsRw50avCrmjlo7jrhrpE6gHL3Nq+dTkfNZjOUJUaCMXjY2vkq79DgZPXMzMzQgfA+Ri4DLvzIJWtGXRrpIrxXKpUKJeGcjStmkjCRcxAk452dnY0uGMw3abAxxry/t5FhTaVrlxniOomebkKrrD/rDWLEkHm0DLSUyVxnc7txwNj6Za0YEDdm0qd7d7F+/OP/bpRuep6rzIQJAqXT6XSUdjjf4ORru91Wo9HQ4eFhuH5sPPyPK41ms6m9vb2oW4NHQpDa7XaQeLhK1Hz5IrhVxZ1CqNl4Dqik4FucjMTaOynI3BCio6Mj1Wo17e/v6/j4OG4xxeV0V4p8Fg47KQb1el37+/tDvWvgR05PT7W3txf5Q7lcLjYWJcPrvVEc65zkR5KpAe46OBl5eXlV+9bpdFStVrW3txeKsdvtDuVtnZ5e3V6LWzE7OxvZxaRs1Go1PXnyRLVaLTgY0C4Jo8fHx0OZ2O468j7Ml79nnqBQlIhnbLNezpccHBxob29P1WpVkrS4uDgUjOHQIQsXFxdRcMrfeK7W5eWlarVaKFcUVLvdDvnEk0B+3F3HELl8YpQYh3eN6Ha7Qxdxopg8itloNIZaDHsgAjfevQw+P4nuCVBAnJ+dnQXfCe/EXIj6ubyhQF0xgeC+lFLCgh8cHKhSqYQQOPJBsPnQo6Mj7e7uql6va2RkJATr4OAgojH0q8EKbG5u6smTJ9HyAQKPpEf/maRooUodE5uOBR4MBtE7B8vHVyfBZ2ZmtLOzE4LJe3iY08lG0N/u7q729/d1cnISB5Gqe3iTbrcbqROgHTi6er2ura0tbW9vD1V2Q4Tjiuzs7GhycjLaz+L3MxdXUI46/cGqMjaMCeuE4kX4Dw4OQmGmUinNzc1pfn4+iPmHDx9GFwW4o/Hx8Sit4QCgWJ89e6ZGoxH5YyigsbGxcFdwoYncOqp0JOtRVPbHDVy/348uj55kCCKtVqva2trS2dmZSqXSUEeJmZkZXVxcRJoE+7i9va3NzU3t7+/H+pLWgJwVi8XI5zs6OtLe3p4ODg7CrRwfHx+iDDCajI25spcoBs4ge017X84FCgaDRKcHWuuQ45TP50M5o2Q4k/v7+xEQwSUEzVFGw7602+2ITJOfh9w5/+QpMo68/Oz93kqJQ9npdLSyshJIA+TkhxYB2t/fV61WG8oG3d3d1dOnTzU6Oqp6vR4tG3q9q/YKW1tb2t/fV6PRiNo2ilaTsBFLQcMtCkqdqANhsflYJbeekrSwsBDtUkjilK5Dm07SgVqwnN1uV+VyWYuLi1FG8fTpUx0cHKjVagX/QXsRCFoQxNbWlmq1mi4uLjQ1NRXFq165Pzo6Gi1O6CDIQeCgJvm08/NzNZvNIaV0eXlVRwg/4gLvluzk5ES1Wi1KQubn56P3FYanXq+r2WxGNj/zqtVqkbTprpIHM0BwWN2xsbGYH+4vh4lWMOwhgp90zeA96Sbh3CXo4OzsTK1WK9An7UmOjo60s7OjnZ0djY6OanV1VaVSaegQ7u3taWNjI4yOpMgj8+xwxkSZDO1TSCaG14NPZQ88gdRRm0epQVGTk5OhdJ3zBMHv7u4GL4nMttvtkGlSTCgtqlarYVyPj48jDYWEYqKPniDcaDR0dHQUTd1ATigoTzthD5AHL6P5vZUSD+4BHAb+KAvX7/fDrdnf31e/349qeHJC6MNycnKi2dnZEDB4B8oUZmZm1O/3I/zvt1uAKiD6jo6OVK1Wo4zFBThJ2jqKcB4slUoFWc18iFS4S0hjOVqiLiwsqFKpRM1UKpXS5uamarWams1m5KCcnZ0FwgMFUEuEQHvjeg4SaGJycjIQHujUBRuozObTzpTPk64tF4rLw+POldFp8ezsLPokoVAHg0E0Q+v3r3oeuZvjiIYDShcCkC6WmH0nx4fDgyJ37i9JemPF2T8+/+DgIPK/cH1A0PTsPjg4iCJz8qOgKEDpFLLiPtIIzTsFpFKpKLfiHLDGKGDOw+npqQqFwhBacVfHD6sfWOYqKQwNZwb6hNpBjGqz2QzKgHPVbrfVbDbVarWiCwJnularqV6vh8zgxaysrGh1dVVzc3PBk9IRpNvthgvsXCogg3ngRTlAQNa+lFKCcD45OdHW1lb4kSy8cxL4s0dHR5qfn1ehUFA6fdVXaH5+XktLS3EtDD6yR3Bo70BoHiH2ZDTQGEopk8lE21XIPl7jkQBfJBSIJH344YcRUkawiP4xf7f6WHWageXz+aE8m/X1dUkaKu70A8b4stnsUAW9Jycyblw57/4J0cph8ygI4+RWEpSR146xLuwrCgIXiEM0NTWlUqkUHSBYs7GxMc3NzSmTyahWqwVyPjo6Gspt8cADCo95OuGJfMBReWcCNwjSdTkNB1C6zpOjQyi8FWvP53FdlaSIkGUymZBNGvnBl7qbn81mVS6Xh2SO/SKKylo6SiDxFmKd8Xgkjvl48Ij58hVFdHh4GCgXhYR7ShSQ/vB4FrlcTrVaTZubmzo7u2ps55FtFNHKykqMN51OR+G1918HlU1PT6tcLmtvb0/1en1oLslAip8hZPRLu28I42Aw0M7OTrRQQCuyyCASuAH6CsHP0G2SeioOq4dJe73eUG6EhzKZHNbLyyXS6XQQjGyaL45bHyffpCulBPTEbfBEQ/9Mau24xsZJdukKHi8sLCiVSml/fz8sJ26hp1F4XhCChxLh8bwb1oI5OXnKpqPMKM3g/TwnCSK41+sNJd059wZnwOedn5/HvlBChNKisyJGyveS9ebzmLcrHBAUBihJhHoUp91uR6te3Cg3RJ7l7fldoNxutzsUHGHdi8WiKpXKkOuJouDv2S8nuRk3+WKsP2NiPTKZTFywQVSUz2FuHHgPz3sgQroyKLhmKCT+zpWqj5GGe5RyNZvNUGp0KKCQnOJyz1D3XCM37pzvnZ2d6FrAmji3CZ/EWv7BkBIDg8TmIgAW34lSIH42e924LJu9atNRqVQ0MTERUBWhh2eAhGVTWGCgtEf+2Gx+n8vlhlIJcDeS3EMSIqPIIO/xzSFvPRWAz6V+igNLHhDKGqUMghsZGQnkMhhct7V1C+KHxF0qXBpcO8+89nFx6OFhQHqEhZ08ZS35PLfwuE+eHsD+oBjhGXK5nIrFoprNpsbGxsLNQZF6QiIuCmNgHyC6SfDzZmPMEQTYarXUaDSG5NODLMjfyclJ8FfMhTUkislnjo2NRXY943elJCkUJzLL5/L+yL+XV3mSMG0+ILEJNLir40rakYQjWVAbN6v4fmFMxsfHh/hFzgZyheKjKyoKCB7JW/1whjjbzAVFTGM8vCPa1CSDEL5X/vWznudCSq4k2HhQgF+YhyUhpI1GxrouLy+rWCxGmJEFxMrwHgia51MwDiIqwHXC1c7HgCI4eGxeMm9Fui56hN+QhpUFG8v/UZCM3+vYQG5YmVwup2azqdHR0aGbUvz9WVusHm4Or4X8lBSEKfvAgeH33W43wuFOkII2ERZvmsf8MplMuEeQ4qw3rjNuGv9HwZGASETID7VzTo6QOGw0mYM0huchdcKDFaAdnx/vBVoi7wYD4v2okA8UEm4XLXaQTZCtu56OjrD6vCfrgeJCmdMojyJrKAKUFWeEvU/m/vjhRZ49mujuIAqDQAfuJTwQypRqAQp7WUtv5QJfTD4WsoZMogOQ4dnZ2Yjm0Y4FxOd7nSTAP+t5rnvfHFKm0+loUcEhdwWSTqfDf/ZWCmwg/ZH4P4LnyXRMxjOjWeRs9voOs3a7HU3UU6lURAw49J7hysKyuU50O/mIG+KFvBxA2rly2SECe3FxEQrND8v5+XmEm9lMolEcVDbLI4SgBwjnpaWlSBbFsnHxJgIJukgS+tT1ofCdr3MXmHGQWwZBenh4qP39/SFX1l1gj/xls9lwE1h/D9WjkFk7XEaIUkeng8Eg9pZDSCZzcv+Slhc0zqH1uk2UHdEwPgvD5wgHBcr3oMab3I9k3g/7R77S0tJSRIlBiB5hBF0hO8nH84f4PYrec5BoI4QHQccMghWgIm/rQyAJWfCaSwITjItIJnl6nGlQoisi1p+/5Zx+aaSUzERFE9P6FGhLKJHoGm1sEQQiB2wa1gi+BiHiwXIg2LghvvhEDO7evRskuRfmulvC2J0D4nMY08XFdQEwc8eSssmEy7l5hZIX0CACDbKgzQYK2PNBWINisRiW/fz8XO+++264RDTO915A0vUh9bwscl08lAzK8CipV6VzwEF6KINOp6Otra1Iz5ifn9fCwkIouMHgqv0sUUTIY9aWJv71ej32MZ2+6oO1sbGh7e1tSVd5YuVyeegQsYaQzSQGumHxPfTvLy4uAk3yWkLaFxcXqlararVaYSw4cB6xI9LsSp/PIUiDK4WCwU3EEOG6n52d6YUXXojrlAjJSwoFgtJjXX1eHpRAprylDGMCKXJ3Ipdqst8oG+bL2nhQgTOQVEQYGD+77XZbjx8/Vq/X061bt7SysjLElzlqTFImX/Q8l1JigfgeN4Gm61gjNhZNSpY2GzA7OxvuAhuP8JIUBhdQr9d1cXGhubm5SOibnp5WvV7X7u5uZBZPT0/rwYMHQ2QpiwEPxqIk66Ck4foiNsQ5AAQS2IvLMTY2po2NjSgxGRsb0yuvvKLl5WX1er3I7j49PdX6+rrK5XJcMUWi3ebmpur1uhYXF+NKGlDE3Nyc7ty5o9u3b8cFBHADJGA6GQv5C3TnAIOg/P8IMoeB/5NXNjs7G0q/1WqpXq/r8PBQU1NTqlQqKpfLGgwGKhaL0Rr4/v37KpfLqtVqgQ663a6ePHkS4yTdgEDF4uJiCDSuqaQo63C3FPfX9xC5dIFHmRWLxSF+i+TV4+Nj1et11Wo1PXz4MML25XI5OE8OKKQ4indubk4jIyNRolIsFkN2JycndXR0pK2trcgVgl+lAZ1fAIBXcBPJ7dSBAwL2CjnlPZB7uMu9vb1IsfGLPklzATHDh/E4jyRdl7ggU91uN+4GJKI8Pj4eaRbJ67c4Z84HcyY/7/lruW98ECkCJNRB4DkBTN3Us2fP1Ol09PDhQ73xxhu6d+/ekMuwtLSkQqGgarWqVCql1dXVcPcajYbm5+cjwpPP51WtVuPqmtXVVa2srOj27dtaXFxULpeLnBfIUQ4kAo3m92JR/HJ4JXxx56RwN2l2z5U7R0dH2t7e1sbGhqrVqtbX1+MGB6zQCy+8oNXVVZ2dncV1VVNTU+EaweGQ5Pbaa69pdnY2khadH+j1ehG2R/FKCkMAdPY0C9xdBA3Lyv56VGViYiKSQZeWlqKMYmNjI3gSMp4hhlOplPL5fOQwkUUMV0fJA3foVSoVvfDCC9HvnRwXOCncRg4c1t+jUh5u9ieVSkVeEO72+fl5RJbm5+djLdrttmq1mh4/fqzbt2/r9u3bUbVwdHSkW7duqVwuR9nG/fv3lclktLe3pydPnoRypusBe9Dr9eLC1Tt37uju3buqVCoqFAphkDEgjtxdUfF/V0jMj5wp0HG32w2lQEBgb28v0CjoEerk8vKqrzznBfefjHY8kHw+H1ni/B1pFwsLC1paWgpli0voQRzOHufQy7b+IErJ/48rcnFxEYgC5IT/iiUtlUqRuby5uamXX345EgLPzs60vLysxcVFTU9Pq9VqRWP7qakpVavVods1Op2OCoWCXnnllbhvDAvnFxmCGiji5DA62QZycMHG3QLxoQR4T5Dc0tKSTk5OtLS0FBdqPnnyRJubm3GAGo3GUA4VN4qS2zExMaH9/f3g31Ag3rvZW8K6smGjebBmfi0Vf5fL5SJHB8PiUTT4DBI1sXZ85uTkpN54440orcFt5HJHwv2/+tWvND09HblcWGFCxiC0iYkJvfjii4E8vXe4pyyQT0UqAMmSn0WUYlhAiZ1OR+VyWZICdU1OToZ8cXsshebItlfec59hsVjU48eP44orLj+t1+uSpP39/UDP8/PzWltbC4VbqVTiRhx4R+YIWS0NXxLgkVJkFuPj6IX2N1Q1TE9Pa25uTqenp8pkMrFHtVot5Gx2djai3AsLCyqVShHNW1painEAMnjgH9fX11UqlTQ/P69SqTRkvH0fIMi904AbwM97njv6xqFwAuv4+DjIQsg9Ig2EBxcXF3Xnzh3Nzc3pk08+iZovBFC6huuPHz+OnAfaQRAZuXXrVpCTaHl6BzvJjKuG0oRjcfSQjMTxAFMp+iXBDhKScL+HrblCplKp6N69e+EOYPHy+bxSqdQQaYs7k8lktL6+Hi4nhwpojWvJGLCKfJWuUGu73f5U+j7fYz07nc4QWuJzpOvcqEwmE7dTkPbh4f+lpaWIGrkrxTip6QORDgYDLS8vD2WjI0coRcbCQfDiaElDmd4oWn98zzm44+PjUZJDzRmpLBw0ahJXV1e1sLCgZ8+e6fT0VI8ePQoLj7vd7/f13nvvaXd3V9PT02o2m9rc3NTo6FWfcS6wLJVKYahyuVxEE1F0yWRVz+WRrtvveLRLGs5X4uyB6rPZbOTPofwGg0G4cqA4qhXYLzhQKAG6cLD3JEjitnmUkgqEm5APwRbKYhwUsMdfWimRSJhk/8kGPTk5US6Xi03M5/OR9clGcBkgbXWJuHW73SA2JyYmgo+hMfzLL78ct6hAQpObhJuF1XcYDLHNRrJwEIMeZufhb0dGRsIqw5NJ1y1YmRukvofVK5VKWAmvnQPdgCwRPrciXnjKPJkDSgxugyJYSeHmIMQ3RaIkBZfiCqjf7wfP4CQy7iV8lSeXskYoK35GaxMiXw7dQVcgK4TcI2meTU72OyiJdWd8rqA+S8B7vatyGwxIq9UaChagyKhdW1tbG+q1xT7gAeB+UxO4srISh5f1cXlkbTi4nkflpL3npYEukuieh/3FSHU6nbgm/ODgINBLpVKJPaEA2nP7JIWiJH+OixjS6bQqlYrm5+ejho+1ImLr7j9zg5dkbJw5dIXP8YvSAr5QKXm5hbtyfIXfSafT8b2HGD01PZvNhhvEwIjaZTKZiKohnGhXVw6OIqRrpen3s3sUCsvC9yhSNt6h8dnZWVwdzZXg3FmGEuXQ+YFknRhHMosaywT3wkH1lAg2LxkxTCYwgiRQaN57x7PjY4P/KqJVLpfjUJH57IKI4qNmi4ADmdH8Qw68Xw+Pu45wSo6wCaej7BgroX4MG8jq8PBQ9Xp9CE0klZC7P/wON4y0EYrCG42GJiYmorMEKJTDhmyiECVFZBWXHVeH+aBc2XP22hMPcZFZu6Ojo+Di2GfPxcIo3mRkkBMIcs5cs9lUs9kMD2JhYSGU7NjYWHwFSaE8UU4gpmw2O1Rk7NE51km6zv3jwUAPBoOhkio/e4PBIIzv5z3PdcWSb74vDqRbq9UKYpcojfe8hq9AMyOQSd6G9/Q0eSbu9VtMHuHBX2YhvGcS8JOIHJv+WbkmZ2dnunv3bkSfUqnrrgSeCQwS8ugd8wQpEK53ch2LmQznOqfAV/K3PBzsCYXeMN7dNxfmVCoV7uHMzExEPUl4lBRcHNFCLxdJjg2Fg4C51U8iJHcxuW6awyQN31zDwYYHPDk5iep1pw08tQO59P/zXqxBp9MJfqvdbod7mmw3jAHg0LPHyDAKG+OJrPqYPGqVdNFAOM6zeFY2coHB4fHPwMB6MufJyUkYs93d3eDKPBfQkTooDtfPo2XIIufAz6J7HMkcLum6nMl1BnvPPrO/BwcHn6tznlspYRGdl2EQlGhMTU0N5Sh5RTjWC7eHCXkuBgNn8REW3CHfbD8EEHf8zq0tVgh3CaXk5Ka7eeSBrK6u6uHDh2o0GoGQQIOEl90SeG4UisnXC0XihxABRuGArpKJpFgwCnK964GX6HzWg1UnAlOr1Yb2gMgJa0rI3tcIl+um93Yl4Pua/B3z9RwW+A//bAwdXJJn9POZPDcFYvxnuIDculOv1wMV8A8XFteNfcxms2HVHe0wLy9l4vBzNpBbUCHrgGF0xEjk11Gwz8UVMAbZz4KjpZ2dnciH8ioLvwqNfWDsyTIvHlBekgtzhcucnRvkvZAD6ArP4fq857n6KblA8LglZeOla+KVym+SyoDG5Pq4O+hRMXe3XKD9/65kJEUrE5AbRCz/sLx+caXXMPkm8C+Xy2lhYUGbm5s6ODjQYDAIxMTlBn5xgTRcTOsRMOm6l427jXx1jsWtG0LlmcLOe3jCnx8I3x8eoDpoiQPvewyaoQAXRe9Cy9o7fGfcHDJJQ0iUvwF5JAWaZEC3pLQR8bVKzonfOUq56fWE3sfHxyPLmiijo1xcOmTSDSBz5oCyXy6zvBeGhT3ioCObuL68lj3ln69bUkZRYih20BdpEvv7+0GHIK/p9PA1Tt7/yLliDwg5sgd1OUJi/OwpY/PcK5dJmuw1m03t7+9/ah/9ee6M7qRLkISuvV5PtVot+icTIgX+YiX6/f7QLQoQY6AH52L4PBATjwuL+/VOIqJ82Ojj4+NAB0kU4IINSslkMpG4SQ8lSXErsGfIctCwsigK3pscI3c7nUAEaYKIcH0QDkdJlKmg8G+KurnFcmSGW0J+lYekUSzULSJszotJ14rXuS/QBuvKzxFOXBb+DheElASMDftER0sexuik6U1KSBq+WzCJPOHE6vV65Ayh8Dl8vMapBf8MTy50VJZ03TzNAuWHceRAcyaogiCqijJJGhhkStKnFDZN8+DhaBDosuAlRh79dGPM3uEx+HnnNSAfR5ueCuB1nHgupCbUarU/HKfkC3CTH83CHRwcRO4D3BJoCT/VlRoLhNDwoHh8gmy6KyQOE8JPUhp/c3x8PNSnh1qgmx53P3q9XoT6+/1+ZCr7+J0oRPDcjXQ+DY6C3+OqeDmM1zF5eHwwuC5fOD4+jnVgzI7QmEOS88pmsyHsl5eXKhaLqtfrgSJ4v5GRkaGCzmTtIvOF2OS9iYh6HRb/OOhwKJDJlCxgYTEcIEFHA+y5uws8ybA08sNXcpQKhULkjTUajU/lZHlpk89/MBhE7zDWmDFjdBgv7wVacSVNcqW7USgjlBXKJCmXTvR7VI71wEsYGxtTq9WKq8GT99LxWgwQcszPUFqsMd/7OqfT6Sgu9q4V7DdyS0SV7g70Mid/7LOev1ZGt2td33wOAlCSEC7p94SlIRzhEqTra5cQau+p40mBaGasnkNJFuTo6CganPX7/YiWJDsWSNfum5OGHtXwg1YulyNZjvKBbveq6JFCUtw5zx1xgfHkRI9AuJJDiNl8hB6ejqxmBNRTNUAIjmzZH8oBsP40juv3+1He4mUcvkZE4eAoWBfaZSTlAwMDGmAOjBsL7W45USTcGleSjoodObtSRg78b9zI8XN6XXFIyIJ2ReQyjtvjsoDMePieekZHdD7eVCoVrguJl7hGNA28vLwM+cdoumvla5icL6+7uLjQzMxMtGymSyYck9fLYWSgVAhM+RqA5lkfzivyzvtI1ykztAym2LhWq2l3d1fNZlPZbFalUkmFQuFzdc5z3Wbi0A7lkFROTASrxCGmZShal/CkIwknjT1/xYUURAXvAacEkiLjGyXU7XbjwKH0eF8OP49bHUdLQNjR0dFoCE84l86SHGAni0lCdILPPwOL4kKC4DtyAvqenJyo1WoFROcg4yI4DHelxb6kUqng9EjBIMmTsK/3XgfhorB5P49Csp7utnKAcEmYN2PEHfK8Kng+srY9j+Umktv3i7EklVHyAPuztrYWh5bER++9RMGt80TItteKEQUF/SEnfCZoQbpSYgcHB9EWhfXh+jHIZr/ym71zw+toibPoigvXL5PJxB2C9KiC3MdjQIagXlhrD2hRWuKRuaTRwz3mEoJWq6Xz8/O4VuvZs2chZ1R4lEqlm1RNPM+VPMmCOH+UFA4eFmZ8fDz6/05MTESeUiqVivvdEVwPOXpEgsUjvwWlhdKA+IWHoGYKV8fzSVCK7v65ULvSoFYKhAH6IfHR3QxHJJ7TxAaz8ShCh/AuZHyFe2Fj6StN+YsXHDN256qSxgIlD1pMIlMgP/4/BbaTk5OR1d3r9VQqlT7Fq/i6sbcIKOsPmkMZsWfMFb7B+xf5/nAoQVfIoqOnz6IYUNpOUKfTaS0tLWlzczMUkys++oN5Ma8jM2m4PY0b1KQryHzb7bb29/dVr9fDyGA83dg6gpQ0VArl83NSms+DY3S5a7fbEQQCiU1PT4fCdB7XESnnzHlj1sCRGgaJdr/0AT8+Pla1WlW1Wo2OIvTLIjH3856/FlJKaknnlfiKUOXz+agKZ6OdRPTN88bkHNbk4oOY0N64NOQTAY1BMmSLO3nuXSyTG+1fncRjDUh6lK4UFxvBZ4E0KHrEX/eiy16vF21BeC/mDNnJYWBezG0wuO41xDpw8JLCknympqaGSkx4DWgOzor38kgQ8yKpdXZ2NvJ1cGdwx0FJ1P+5laUMieuUUE7NZjOy0lGuSRljzshMMgrnr2VtHLl5hAx5KxaL6nQ62t/f19jYWOyvKxZHaqBJPxPSdY6YG29QKBxgs9lUo9GIxFWMMYEBr9i/KZJ6E3/mawXHA5KGOyW1ApeQz0OhJNHP+fl58EseXfayKNY0malfr9dVrVZjntzmw8UDNJCbmpoaanFy0/Nc7XCTPrI/ST+a7+kBzKWGbs09s9d9UvxskAVuDiQ5n+FNtLA6KCWUAHDa0QGciCOS5LzcNfXWvNR/ucsFStva2gohXFxcDBjOPHEn+/1+1CmBQCB96b3DYUWwuYTTDyJKFo4NK+0Kl3H3er3gKAgcZLPZ8Os9euMwHuXC1TuHh4eanZ3V2dlZNNNDSbJ3zBU0ADpiHQg6uNKj5zRyg1wkyV3/f5Izu4nn9IPM/0GEuLC4cShX3FYvQ+J9mFev14s8NPYQ5AEaRSbhOEERTnJ7SQrI1RWof3aSYHdUnEqlwgWnENp5UmpJXUY8Cu0GH7LelTpKDAOL3FPwjozu7Oxof39fzWYzKh5QQBSYc+NQkshPPn8tpcRCJYUgiTRQBGjog4MDbW5uajAYRPGipCHk4f65w0XqvIDCWCWIUTbe0YcXQHIIk9mryTlisZybIaLmbieHj7VAkVApzm25FCWz2Yyd1zNnxkLDN3g0rJCksF6+xq6YEGZPEXCXhrVwZMVcgOD0Vobj4b0YM5wdZRscYKw7h5TDyV5yQHq93hBKYr9xsaXr5Enng3h/5C7JE/n3Nykt9sm7oFKDWCgU4l63weCqq4VfkooC8LwiEAOKm3liDJk/7hlol5q5weA6RQTFwPtxFpLEfnK+rIkb3ocPH4ZLzmsymasypmq1Gu/l99PhdlKqxd9RZO9BD9bUDQ/XUu3v78cFmKlUKi5OZXwEhGhzkjx/yee5731LLo4rpmS0wiEkt38cHh7q2bNnUeiHVYdzIdrGgUKzgypQSggAOTudTifC5J57weMKysl0t8KpVCq6KL7zzjuam5sLAZGuERPvMTU1NXQ4GB+HFkKPQ+AognnyN7wHygDEgrtGwiU1Sx6BchSSLOL0CJ2jTxcIBBvSnr2kJxVCjftG1Xw+nx+6sTdpNDwy5UES5uhuSZKYB4Wyvr6f7tIn0YPLKPOVrm8coeMD7kgqlYrqAm50Pj8/D6PpaSju4jJ2V9rIpCtlXFUQMPyWR77cdUMpoQT88X2XrpXv3NycarWa3n//fZ2dnem1114LVO2pJdzy2+v1Ij9LujYCbrRA7x5lYw1A0u6pkHtEgIRbgh0JEr29aW43Pc+tlBwu45szGX6ez+cDsSBQlGfge56cnERHPywSFtWhJJ9H/pHXi7EofBaRKywOKKLf74dSQtPzexdk3Jmf/OQn2t7ejsOSjAySrk+nSVoCI2ipVCou+KP4E/QFegABoZhAEbSNYB0g1+GOnJREUF35wqXRqsPhN+tIyB7hkq6Jfk/Y87Xm7znMuHP1en2osReIwtFV0vVHgXiUh0AEBsBTCBgffy9dKzLPuUkid5DEzMyMzs/Ptb29HUm9rAFzxV2jyT8oFxlnPVxWeUCIyXwyUixogcNB94AOCskPanJPk8oI6gNFViwW9dvf/lbValUrKyuBeBx54a0ACmh25+kAnj+XlGf2hKfb7UZ760ajEdUNs7Oz0SEVFOgpJSjez+I9h/bvJp7INvfzO3x/9Xz1fPV89fyez2AwuNGP+1yl9NXz1fPV89Xz/+vn0638vnq+er56vnr+//h8pZS+er56vnr+Rj1fKaWvnq+er56/Uc9XSumr56vnq+dv1POVUvrq+er56vkb9fx/3ob2rebVFZgAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(5, 5, figsize=(5, 5))\n", "fig.subplots_adjust(hspace=0, wspace=0)\n", "\n", "# Get some face data from Scikit-Learn\n", "from sklearn.datasets import fetch_olivetti_faces\n", "faces = fetch_olivetti_faces().images\n", "\n", "for i in range(5):\n", " for j in range(5):\n", " ax[i, j].xaxis.set_major_locator(plt.NullLocator())\n", " ax[i, j].yaxis.set_major_locator(plt.NullLocator())\n", " ax[i, j].imshow(faces[10 * i + j], cmap='binary_r')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each image is shown in its own axes, and we've set the tick locators to null because the tick values (pixel numbers in this case) do not convey relevant information for this particular visualization." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Reducing or Increasing the Number of Ticks\n", "\n", "One common problem with the default settings is that smaller subplots can end up with crowded labels.\n", "We can see this in the plot grid shown here (see the following figure):" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(4, 4, sharex=True, sharey=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Particularly for the x-axis ticks, the numbers nearly overlap, making them quite difficult to decipher.\n", "One way to adjust this is with `plt.MaxNLocator`, which allows us to specify the maximum number of ticks that will be displayed.\n", "Given this maximum number, Matplotlib will use internal logic to choose the particular tick locations (see the following figure):" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": "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", 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" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# For every axis, set the x and y major locator\n", "for axi in ax.flat:\n", " axi.xaxis.set_major_locator(plt.MaxNLocator(3))\n", " axi.yaxis.set_major_locator(plt.MaxNLocator(3))\n", "fig" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This makes things much cleaner. If you want even more control over the locations of regularly spaced ticks, you might also use `plt.MultipleLocator`, which we'll discuss in the following section." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fancy Tick Formats\n", "\n", "Matplotlib's default tick formatting can leave a lot to be desired: it works well as a broad default, but sometimes you'd like to do something different.\n", "Consider this plot of a sine and a cosine curve (see the following figure):" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot a sine and cosine curve\n", "fig, ax = plt.subplots()\n", "x = np.linspace(0, 3 * np.pi, 1000)\n", "ax.plot(x, np.sin(x), lw=3, label='Sine')\n", "ax.plot(x, np.cos(x), lw=3, label='Cosine')\n", "\n", "# Set up grid, legend, and limits\n", "ax.grid(True)\n", "ax.legend(frameon=False)\n", "ax.axis('equal')\n", "ax.set_xlim(0, 3 * np.pi);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are a couple of changes we might like to make here. First, it's more natural for this data to space the ticks and gridlines in multiples of $\\pi$. We can do this by setting a `MultipleLocator`, which locates ticks at a multiple of the number we provide. For good measure, we'll add both major and minor ticks in multiples of $\\pi/2$ and $\\pi/4$ (see the following figure):" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))\n", "ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))\n", "fig" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But now these tick labels look a little bit silly: we can see that they are multiples of $\\pi$, but the decimal representation does not immediately convey this.\n", "To fix this, we can change the tick formatter. There's no built-in formatter for what we want to do, so we'll instead use `plt.FuncFormatter`, which accepts a user-defined function giving fine-grained control over the tick outputs (see the following figure):" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [ { "data": { "image/png": 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" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def format_func(value, tick_number):\n", " # find number of multiples of pi/2\n", " N = int(np.round(2 * value / np.pi))\n", " if N == 0:\n", " return \"0\"\n", " elif N == 1:\n", " return r\"$\\pi/2$\"\n", " elif N == 2:\n", " return r\"$\\pi$\"\n", " elif N % 2 > 0:\n", " return rf\"${N}\\pi/2$\"\n", " else:\n", " return rf\"${N // 2}\\pi$\"\n", "\n", "ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))\n", "fig" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is much better! Notice that we've made use of Matplotlib's LaTeX support, specified by enclosing the string within dollar signs. This is very convenient for display of mathematical symbols and formulae: in this case, `\"$\\pi$\"` is rendered as the Greek character $\\pi$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary of Formatters and Locators\n", "\n", "We've seen a couple of the available formatters and locators; I'll conclude this chapter by briefly listing all of the built-in locator and formatter options. For more information on any of these, refer to the docstrings or to the Matplotlib online documentation.\n", "Each of the following is available in the `plt` namespace:\n", "\n", "Locator class | Description\n", "-------------------|-------------\n", "`NullLocator` | No ticks\n", "`FixedLocator` | Tick locations are fixed\n", "`IndexLocator` | Locator for index plots (e.g., where `x = range(len(y)))`\n", "`LinearLocator` | Evenly spaced ticks from min to max\n", "`LogLocator` | Logarithmically spaced ticks from min to max\n", "`MultipleLocator` | Ticks and range are a multiple of base\n", "`MaxNLocator` | Finds up to a max number of ticks at nice locations\n", "`AutoLocator` | (Default) `MaxNLocator` with simple defaults\n", "`AutoMinorLocator` | Locator for minor ticks\n", "\n", "Formatter class | Description\n", "--------------------|---------------\n", "`NullFormatter` | No labels on the ticks\n", "`IndexFormatter` | Set the strings from a list of labels\n", "`FixedFormatter` | Set the strings manually for the labels\n", "`FuncFormatter` | User-defined function sets the labels\n", "`FormatStrFormatter`| Use a format string for each value\n", "`ScalarFormatter` | Default formatter for scalar values\n", "`LogFormatter` | Default formatter for log axes\n", "\n", "We'll see further examples of these throughout the remainder of the book." ] } ], "metadata": { "anaconda-cloud": {}, "jupytext": { "encoding": "# -*- coding: utf-8 -*-", "formats": "ipynb,md" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.2" } }, "nbformat": 4, "nbformat_minor": 4 }