{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "fea4a059", "metadata": {}, "source": [ "# Adding Noise" ] }, { "attachments": {}, "cell_type": "markdown", "id": "117c8621", "metadata": {}, "source": [ "In order to generate realistic data, we need to add noise to the CSDs after they\n", "have been generated.\n", "\n", "First, we'll generate a sample CSD to add noise to." ] }, { "cell_type": "code", "execution_count": 1, "id": "2ebffef5", "metadata": {}, "outputs": [], "source": [ "from qdflow import generate\n", "import tutorial_helper\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from qdflow.physics import noise" ] }, { "cell_type": "code", "execution_count": 2, "id": "0b3ddae6", "metadata": {}, "outputs": [], "source": [ "# Generate a sample CSD to add noise to, this may take ~ 20 seconds\n", "phys = generate.default_physics(n_dots=2)\n", "V_x = np.linspace(3., 12., 80)\n", "V_y = np.linspace(3., 12., 80)\n", "csd = generate.calc_2d_csd(phys, V_x, V_y)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "d6af6c58", "metadata": {}, "source": [ "Now we want to randomize the strengths of different types of noise to add.\n", "This is done using the `NoiseRandomization` class." ] }, { "cell_type": "code", "execution_count": 3, "id": "5af6c4ce", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "White Noise Magnitude: distribution.Uniform(0.08, 0.12)\n", "Amount of Latching: (distribution.Normal(1, 0.3)).abs()\n" ] } ], "source": [ "# Create a randomization object with default distributions for each parameter\n", "noise_rand = noise.NoiseRandomization.default()\n", "\n", "# Print out some of the default distributions\n", "print(\"White Noise Magnitude: %s\" % str(noise_rand.white_noise_magnitude))\n", "print(\"Amount of Latching: %s\" % str(noise_rand.latching_pixels))" ] }, { "attachments": {}, "cell_type": "markdown", "id": "6e817f17", "metadata": {}, "source": [ "We can then sample each of the distributions and obtain a `NoiseParameters` instance, which defines the magnitude and other parameters for each type of noise.\n", "In general, you will want a seperate `NoiseParameters` instance for each CSD." ] }, { "cell_type": "code", "execution_count": 4, "id": "1bf29b7d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "White Noise Magnitude: 0.11480996815880339\n", "Amount of Latching: 1.1291457236662927\n" ] } ], "source": [ "noise.set_rng_seed(9)\n", "\n", "# Obtain a set of noise parameters by drawing from the noise_rand distributions.\n", "noise_params = noise.random_noise_params(noise_rand)\n", "\n", "# Print out some of the noise parameter values\n", "print(\"White Noise Magnitude: %s\" % str(noise_params.white_noise_magnitude))\n", "print(\"Amount of Latching: %s\" % str(noise_params.latching_pixels))" ] }, { "attachments": {}, "cell_type": "markdown", "id": "746228b6", "metadata": {}, "source": [ "Then noise can be added to a CSD using `NoiseGenerator.calc_noisy_map()`." ] }, { "cell_type": "code", "execution_count": 5, "id": "87f0f86b", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "clean_data = csd.sensor[:,:,0]\n", "\n", "noise.set_rng_seed(10)\n", "\n", "# Add noise to the CSD\n", "noisy_data = noise.NoiseGenerator(noise_params).calc_noisy_map(clean_data)\n", "\n", "# Plot the results\n", "fig, ax = plt.subplots(1, 2, figsize=(5,2.7))\n", "tutorial_helper.plot_csd_data(fig, ax[0], clean_data, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[0].set_title(\"Clean CSD\")\n", "tutorial_helper.plot_csd_data(fig, ax[1], noisy_data, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[1].set_title(\"Noisy CSD\")\n", "fig.tight_layout()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "64ccde7d", "metadata": {}, "source": [ "You can turn specific noise types on or off when adding noise." ] }, { "cell_type": "code", "execution_count": 6, "id": "eba6bc3e", "metadata": {}, "outputs": [ { "data": { "image/png": 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TNIOFljMGNJGIyBsjm+yFzJhwZcjtZdz8kc4444zStnwk8cfroZY8NfpcHi3sLLnrrruqnqM2TiP5LCSg2aFHsGevNwe1M8vMPQm9uskmm5Ta5m9/+9ulCYjH//zP/4xJ30YCM08xm3R7/tt5aKx5NyEZ8h6BCYGZjJizk7FlZg9lDySLqX3HHXeU9lD2slkLtgGNGTOm3coZI2Cb3h5eFmPcXrotxbw95O2Bv+mmm5Y22mb/ZYeU2do99NBDLRuPmZpceuml5TdqM4+xg8livtrnFrvUxmq2YfbCboeCHZ5m1279MlW7HVb2JcFMbLbZZptSdaYwB1T79m4Mo5W1GMbG/tuXDVOtmTNOItENsC+etieNJbK4xsCcJy2JlT2YbA+bSZY9uEwjZHveMto2A0uKZV9GTTtlcXftRdYSFBmz5TVMdj6Y38i3vvWtUvatjNmI2jli54XFDN51113LcuYcZWfLWWed1dZkW/YCYLGF7dwwRy+zIT399NPLc1Ff0hMJg+19i2dvzwx7Abe9q7BnjLG+hla/kNeTp0aey6OFmcSZRtpiru+9994lW2zniCUctOei+apEeOKJJ0ozN3s+24uxmZ/Yl3EjBXmZtZdxG5u97NqXGvvc7MefffbZ0vHc5NPkstV9Gwns/cace+19ydprNIdJ29DpMC+J5mDhkSyMkIXqsRBMFrtz3XXXLcMu/f3vf68Z9pBQQgcddFAZ39futdi+FmP0+OOPr4rve95551U+8IEPlKGTLHaqhUCKQqjZ33vttdewPkZt14KFVbJQahbCzOKJWmxmC7Fo/XzxxReHQlR9//vfL2MvW93WLytroRMtHJOGQCJsE/8stNx73vOeylprrVXW+cwzzzQx24nE2IQ99CDeuI9Dbnv/yCOPLEOAWRzdxRdfvNzHKuu1EMnslVdeWcY9NjmzM8TiBZ9//vnDwrRZyLItttiiPF/smoZss1i+X/nKV8rcCHaOWOhB6z+xmAlPdskll1S1HcU4rhX2MAqzZp/bmBQXX3xxeUbZmWDnho3vU5/6VPlZIuFhsmP7yJ57HhbK067Znv/Xv/4V7r9GnndR2MN68tToczmCtW31elj9PsyihVq1fAYWotDk32J3+9wiXkZNpm3MJk8WntHCGNqz1OJ3e5jcWwhVK2P1W74Py3lwzz331B1Do327cRTnisJyrFj5H/3oR5Vuw2z2X6e/FCQSiUQi0QqYfasxdBaOLZFIJBTm2GkZz81E0LKCdhPShjyRSCQSPQezV/U2tuaUZzbumpo8kUgkDGYPb6as5gvTbS/jhrQhTyQSiUTPwRzzzAfFnGLNydOiMpgdu4Ve23PPPTvdvUQi0SV4+eWXi+uuu660y//d735X7LPPPkU3Il/IE4lEItFzMKdvc4I799xzy0gOFsnCnLYs0ZI5biUSiYTBIqtYqENz4jz11FNLs7ZuRNqQJxKJRCKRSCQSg2pDfsstt5QhuEzdaOHoNNa12QcecMABZaxqYz6sjIX6++///u9OdjmRSNRBynQi0V9ImU4kBuCF3OJtWtxai3PtYbGnLZa0pWm1nxaz2uL0Wlr3RCLRnUiZTiT6CynTicSAmawYQ24B5y3hRS1Ycpc111yzzLioqZ/rwRLDGKtumaVqpa9NJHoRJrqW0dS0R61MntAqpEwnEs0hZTqf04nBlemecuq0NM/2kJ9vvvlqlrF0rqR0xRO/lalXE4luw3PPPVcstthiRS8iZTqRGI6U6URi8GR6zl6KH2k25dttt12ZqrUWjjnmmOLII48c9rmlnLfUuaOBhdMaCeox8/WuLbTQQkUnscgii9S8NlbahpHO8ViMsdvH9qc//alYfPHFS+1PL2K0Mv3kk08Ojd1SOoM33nijao/qXuUaP60PwFgMw7ve9a6afZljjjmGNG++bkvHbSA2toXaMigrYn02WJp3g6bFpk7qmWeeeYbdTxnG+/rrrw9d47O55pqrqqwSFLfffvvQ3iFSCUBZSp+YG+rRufn9739f1UeDhR00/O1vf6vqm6XfBq+88kpV3ZYmG5ivEOaK+lPHyNxwlmvfqMvSjvt5M58knRv+1n1HO7ShdbPujJt11/7THv2mHp1b6mTemA/K2D8rM6gybc9pv491btk3GkPar5vKFPOOTLKOGr+eumlXjQb8fVzTtWWtuKZ9437WXfeU76OXWz2naIP69Nxacsklw75qOcaG3FCv7mVkQuHlhb5pFCPGG42Rdn2+AJ1j5v9fb5XRM5Xfo2cnfYrk1SMaN+3RF/phScX8+Lmm/WbfedZb+29l7LmyzDLLNCTTPfFCbhO/7bbblpNx5pln1i170EEHFfvtt9+wlxZbkNG+kHMYj/TFLtpoLHD0gvvqq6+Oqr3Rol7g/LF6IedFwWAqnrEGL2HtaMtsMcdi/XrRFKsVMm0vh7xQ6sPEH7CR3AF9kfcHNC+y+jDhZZODWg9ofueg5qGle3rFFVesejDonpg2bVr5c+LEiTX3Ju3PPffcVT/RNmg/6Lc+CJgvXiT//Oc/D12jLzNmzKjqv4UU9POnL6KAvvBCyovB6quvPlTmrrvuKn8+9dRTVePRui2DXq2HMHVyNukZyQvgsssuW/58/vnnh66xJryg8CzQ9eMLAeuuLzaUpw3mymIaA/YEc6MvCLTDPmXe55133qEyVt7K2ZgGVabtiwr7KJItvhCq3DLvrLE+p/mMMhb2zqDvAsgideq6e1kCWga548VQZdrGFL0s6gs1ffHvBNou1yjLXlVZYN/qCyL3+RdjLUNdXjZ0vzJe/tYXW75cUkb3rp8/f8YaWO83HJGi68Y1lZdaX6T0WcB9zFF0TdfSrxV9i74sMW/UGb1fWnnubUSm5+wVITe78RtuuKHut26EQr+9JhKJ7kLKdCLRX0iZTiRGjzl7QchNzXvjjTd2dbKHF198cZZlWsnC1mpvtMyrfovzbbTTvMNAiMt2sNcaTrMd7TG37Z7TfpJpY0RgOZRxgemBwYhMHmBqImYdpoOfkXoapgQW2wAT4hkbZaFhdSirrMq6665bxTjRb23Dq86VfUd2YehgapVFHj9+fNX4za4RwFZ7DYOyedTNNTXvYS8zJurTPtIn1k37RnnmGJMfNd2D/WQelDGz5B9aXs1xqIt1o//K9MHsM15l6GHYWEu9D7CXWDfVMDI2CKWIhbc+1VO7D4JM2/gj0xHmJTJr4LNI64HsUifanojhpU7db5519my6ts/6q9YKEzXfN7Ul9polHRt7yDP9em49/fTTVX3U+UeWkFvqU80UY4xM3BgnffKaAoORpYZx48ZV9VXPYC8vOn+0+06nodLfGZtqpBinZ+EjcxjmVteGa35v6Rg5C1gvnXfPntNXz4RHc9aVL+R2uE2fPn3o75kzZxYPPPBAeWjb4f7pT3+6DHn485//vFxQVJl2fbTmJ4lEovVImU4k+gsp04nEAIQ9vOmmm4r1119/2Oc77bRTccQRRww5K3jYt/CPfvSjDbVh7IyxKDvuuGPHXuL5xtQJJ8lZtTva9tvBJjcyf2OBdowNjGRs7G2zYZyVKVc/yrR9gccBR48xz2JFDp+UV4aSfebZHP0bNgTmJPLzgDWGMVEWWhkaLat1whR5plztVWH6dNywYNzv2VhlmGGWlSmjbsv3oPVpGYDjHOyYMsqMg/nEXjxiOB999NGhazDpMG1okXT8zL93tlL2OrLhZtwwbN5uVMuzJlo3faD/rA1zVs/OXc8S+kH/tR/WhvXB2PxBlWmrE1Y3YmpZB5Uj73CozqDU4Z/9kdxHDoue2WZP6J707LXC+7FQj55J9B9mPvJ58TbgOh7VYHnQnvfHUK2ft4FWFtg7fEaOq7DPjF/Zf89eI1vaBtf+8dZaRc6P0RxzH/Ie9d+vu7LVzAHnO+uv5713uFXfGb/ekb+BncXNPKc7ypCbsNb7PtAlIdITiUSDSJlOJPoLKdOJRHvQfdlEEolEIpFIJBKJAUJXO3V2G0ZrVhLd3w4tQD2H09GaZeAM2Q6znGgcY2nGoo6eY23ComMbNEfPkcLU1qie1XEStSCq3Ch8WqSeRC3s48qq6YMPP6YqUfqAqQd907i2qHdpS00evANWFOucMvRRVfeMBUcyzGk0DBuOjr/97W+HhU+jTrIgMzZLrubNSlA9q9qWunEywzyDmOu6t2lXZQqnTI1b7tfPr5G2jxkO67DqqqsOq5u9wX3PPvvsUBnvuKZry2dqquD7hgoc1TtrreuMqQ9ronvD5qsXnTpbCTM3iMKVAtZEzVnqOVz6vAE+5rXeR9kobCDrHpVh3SNHYe1LLUdvZIE9onvAm7NEcdRpn7LaN+YJEzfuwyxMy3vzGIWXOzUL8aYbel4wFvrP+aH3+JwCrzsZU0RxxDlnuG/RRRetaUYSmTMB5lbLUCdzow7qJKik/z7mPG34duohGfJEIpFIJBKJRKKDSIa8CSgb0ouJG9qBdrPY7US7QiMOakjEkcgjDofK6vjsdFGCFlgNdYjyYcui0HZ8FoUoAz5coLJZhDCk3+rU6ZN20B91oPLOVXomwex4Z1DNXAhbDVOsDpuMDeaHsksttVTo6Oedw2CoSb4Cm6SyAgtFhkp1AGOc3E+CIg1tSL9hEzUMms9meM899wxdwxmLMbE3ll566aEyOLP6bK5ap9doKovuM0bq/cqIKjOuZ4rJe7TnBgm2h5kr3VueoY40y1HYPO8EDJThrSdTyDDrEmWF5AygXW3L99dn49W6o0Q1PjRfNG6/3yKtDeC80X1Hf3FmjRh+336UvCcK++edp33GUMUcQWIhn2E3egfzjuLK0Httn7LvtOc1AvU0M/q8QMvIczpaW+tbMzKdDHkikUgkEolEItFBJEM+QtRLed8Mw9pppr1VyXdGMh+tQKeSF7UjaVEy5fVBqvFadpMwJ8owe0Tss2fDtG7KwEJHNomwtzC7yvDSHky52pB79os2okQX1KN9oxwMM0w/bLQyZJRVNoc+wd5im6mhvmCfYKPVBp2cErQH86Ttw9bzUxlu+rLaaqtVsVJqt4nNN2sUrU1ky4s9vU86o2ErCd8HU66aDebS25JHGoooeQ1z65M2qYbE+j/oDLmtD/sgYmEjhpx9ArOurCzzWS+9Oe1Rpz6nsUeux1Sz3pFmjfX28qZ9pE7uV20K5dDs8LzR9jl3qDvS+nmGV31P0JJF9vE+pGTkZ8M6Rbb/1IkNO/Wonbe3768EPiPMsc5brZT3+jnnBe1F4U79uRtpCJgj1Yww35yJtKGMu42pmXDbyZAnEolEIpFIJBIdRL6QJxKJRCKRSCQSHUSarIwSnTLV6Be0ev7aHT4wTVc6B1Mf+gx4akaBmlMduLyJi6ogUWd6xy3dm97x0vdHnSJ9iEM1XfCmH9o31MqYRej9qJoZk5rDeMdDr65VR0lvgqHzRthCxqFzhBkNZVW9z2dkBWT8995777AxRqEFvVPe+PHjh5kFEb4Q8xg1+cD8h/K6bt5UwJsy6GfecVTLeXMU3XeUoQ3mSteSsT322GPDwh6aac6ghz3U/a/mVN6swWc4rRUSEfh1173hszGqTHhzjCi0nXei1j3tw6vyU01GkBN+Ro7C9C3KWEkfMWvRefOZRf35of3XcXvQBvOoc8yYIsdL2vH3q6maz6w7W7A2kTMt/fXX1OSE8fJeoBlLGTf7LTJnof+cwdGepB7GpJlebU6iZ0UtJEOeSCQSiUQikUh0EMmQjxIjZXbbwax20rlT54Zvp+0ea785RWbyoOF7DfYhCnuIQ5VeixL6AM8QRUlEPDOqTBWOijBdMCiw4soCL7vssuXP559/fli/Yc25T5kbX7c6JVI3fZo4cWJVeK6IFVIHMp+YCFZN9x3sMSwQzlrqvAkrRV817CJrATOs42du6SNl1akTh1X6qA6j9J+5UabKO7XBfuvcom1gvHpNGUW9FiWdipzjuMZZBJuG4ywhIAedIbd5Zv4i50xkMdI+MHfqqO0TA0UJYkDksOmfi+xRfe7j8FcvtJ5n6DVZl69T95pnf6NnKfsMjVbk8MmcRCw0/advqrXxoSB9+EmVU2RL599rwL2GTOd4kbdkI3IqpY/KUHuHyyiMYT1nXu8oGoW95L5Io+rb9SFdmct6mgePZMgTiUQikUgkEokOIhnyxJjBfztuV2KdTjDl7R6bjUmZ10HdX7AyynjB9Kh9tkdk3+1D6dVLEx0x5D5BCGyKhiGjXe7T9pUJVqZZGTfPwimb4xlC+q+p6z0DS0prZdv5LEpl7e1sCVGo9ulPPvlk1fwr4+ZDISpDT3+5H3tPtZNnjtdee+3y51VXXTV0jbq4T+ed/vrU3bq2rM3yyy9fFf7QgKxRTxSGzdulq52wD2nHuukeNdv9KPHLIMH2R7Q2PvmNso7eLyRK7ONtmCPNRsSee78MfzaofET26cgQdVJG5d4nFFL239vOU3d07kQaQb+fIoafM4WyqvVC9urZaXttQxQKlPv4qWvLmrz41nNafV7q+fz4sdXTaLJGL7/88tC1xRdfvKrOKLETLLjXMOic+KRPOrfmK9TMczoZ8kQikUgkEolEooPIF/JEIpFIJBKJRKKDSJOVEaJfwxy2y/TCO3K0A+1yiuw2h91+hakhvbOeInLyQlXKZ6re9OYoXt2sQC2s5hyoTH15HCFVZRo5rnn1OH1Vx83555+/6lqUKdSfUUsvvfTQZzgR4uipDkjU6TMlqpqW8fJTHTYnTJhQZXLCWHWOaOO5554blgUUcxLax/RE70duUSWvueaaQ9duu+22KtU9ZXSevOOWOtfxGWYlak5CeEXmj/vqZdZUBzTG5rMy6tra/rE+DHK2Ths7Mq3PWPa2D+OnnyHTes2XicwavKmLmqMgn/55r397c5Lomnf4jUL7UVZN1xiT37eENFUZYt6iLJyMl3MycnSnrJqIYe6G3EVZaH1oQzVHoTztMX49t7j2z7fu07FhVhLBh4BEttSB02fv1XHPnDmzykQGeY3MGJl3vebNYfy5TZlm3hWTIU8kEolEIpFIJDqIZMg7zIoPAptaL/lPP4dEHIS17SRsP8HqKHPhk87grBclttD7PIsKOxKx2JHDI+15pi4Kg0b7GpqPvqgTptZneOmll6pYsShpEX2D6VLHSVhrmFnVLJCIx2sRIkcmEvOokxQs8oc+9KHy5/3331/+VKcmmCplrwH9hLF65plnhrFp9BcWkVCP6mCKc6kyVYQ5RFsBw13POa6ew6a/J2Ixdd4px/yxVtp/a3fQnTptf3hHxugZoo6PIEqa4xnqyKnQs+e6BuwBNEpohFSLQV8izQbtePY2ehZGDpu+H5HjJr8jr5rQCrac84b2VabpN/frmeADMkTPSx/uMHIY9QmWFIzpbW+V1WRfvl3tt3eM9w7XOn6fbE3XmSRtFnbUn02e0Y+SzEUO/sDaa0bjlQx5IpFIJBKJRCLRQSRDPsD24u1GlDSo02xyMuW9C2M9YDyVOYFp8cyPfuaTieie9Ax7xHDD9Ki9og+RRVtqE0p/uaZsDPbJXIvs4mHjYJ2j/vsQXyprMOPIooYY4z5YXNpXhgemDYZe54a6qRP29/rrrx8qg7YCpslC/QFsxmH4YCM1eQ7twf4rU4h9PeuHjai2x31RghlAGU3v7fcE7ar2xbOAun4kNOI+xqiMoTGDti6DHM7U5CtKHuOZVd13/M5aqkz5hDRR8hfPDEdhA732Se20fdIclTfqov/Ij/oXgMgG2tsw+0Q1kUZG6/bnFddUe0Mb/tzU/lMPIRGRtWgsej9z4e3EVfvkQ1G+EWgfkBf16/BajygkZXSG+rF5LYC+g3i7eGXIvR8S13T/WP+bSQzU1Av5o48+Wlx88cXFrbfeWqoT7TCyGLOrrLJKsckmmxSf+tSnwo2WSCS6EynTiUR/IWU6kehNzFZpwGjtvvvuK/bff//Si33dddctPdvtW4S9/Rt7MW3atPIl3ZggK7fvvvt2zYu59ckYj4022ii08WkE7WBt/Tf5drVbD2PZfjNah3bPQzsjv4xmbMakLbPMMiV7oJE8GkE/yLSxNdG4G0lh7tloZVpgdj1zVCt1tK8bpsTXoxoZ7MRJd824lNWBHVJZwd4SFlUjIsBQw9zAJimbiH01TJeyN6wvcwrTo5GX6C9904gItLPiiitWsXAayYUzmEgsTzzxxNA1bMZh32E61c7a2+lrZJkll1yyakyM1fDII49U9d/Pta4fdUZsHJ/5VOzK4kVRPphb7GNZPx9lxtqxcQ+qTG+66aZVGi3gbb9VpvmdszRKGuRtp/U5S53sad1TPrqGZ3zVDyRKOuQT6USJddjfPsGQbydK0BPZV0ftcx9j0znyrHukyfbvJ9pH5m/cuHFVZaO55W+93yfYqQRJm6KIWZx93i9Hz2bmL9K61Iqco59TF3KqffP26VFUKrvfZH3SpEkNyXRDDLkx31//+teLn/70p1UPEI8777yzOOWUU4oTTjih+MY3vtFI1YlEogNImU4k+gsp04lEb6OhF3JjMRphlz/4wQ+W/7wneiKR6C6kTCcS/YWU6URiAF7I7WX89NNPL3bYYYe6DLmW7zXUM6HQhDKtMnOo1Z5+PhbtNoNWOVqO1im23Q6f3tGzXv9HG6asU86s/SDTpn6MVKioXiPHSVSnUdhAr/LF5CIya8GZT527vOMS9ytBYT436hSl6lXMIR577LEqswoNg4ijI2pewrHpuAGqVN2j3I96XB0IKc+Y6D8OiWqWQZ80cQdzSz2Me6GFFhqmZkZNbmYUvv+0EYUT437q1rUlFGM0NpIjYWKDeY+ql334OF1b6kItjslT5DAcwTuFsg80RJ1dw2RlUGXaxs9cqWywTpFZBnOKg7A66vpQiOxXNStinSPnO0yMWFufYMebdNV6XnC++7MpMuvQPUl73hld145xL7HEEsPmxs8DcxqFPYzCTfqkR1EoWMoQPlDPBH8mefMUNcN7x1uypPdwLXKURhY5n3xCM20n2lPepDEikvmMc1bft5gLL0feLGZMEgMdfPDB5ab6/Oc/X9xwww0NN5BIJLoTKdOJRH8hZTqR6HOnToN9a7/kkkuKKVOmFLfcckv5bWzXXXctdt5557rpTXvFqXMsQxs2wrSOZbsjRSP9baaNVo6/nYxyvfUbi0QejY5tNE6d/SDT5pgIq6xrA3PhHaIihk3ZGB/2K3K0hqGBYVU2BOcsmJeIzfJMlV7zaan5W1lUmBrvSKQsrg/3GLFZMOUa2g/W/uabb645fs8K6RzXSlqkbJwPTaehCc0pUcM1Ulb7CAsIc6ay4pl9XRsYabQPOJVGSWBolzb0fjQDjClKzBSFy/Qh7SKHWzQ+1u6gyvTmm28eyi3wadIjhjO6xrxTRtedMqyxOroiZ+wNnyY+Ytj1ft8nnyAq0lqpvPpkZT5Ne9S+7nvu5xkWhXb0Dq96JnptDfXp59zvk15F8krdOsbonADqUO8dbqmL+2hLy/hkS9q3WgmRdG39O6OGOZ04cWLojOq1D3Yur7TSSg3JdMMMuR1SX/jCF4obb7yxPMx23HHH4rzzzis9280z2g6BtB1PJHoHKdOJRH8hZTqRGACGPILdet111xUXXHBBcfnll5cMkaZS7gWGvJ2sdafDGDbCZo92PhplzFs1751gymuxh63GrMY2Woa812XaGFlsPJX58OyjMj6ePY9syL1todp7ept1ZVGBD3+mbJJPDBIx7PQNO2VlZTjD6Dd209oefWI8msSDfsP0fuADH6jJsEc28NiJUreyUdyPnNB/DR/oE2woU0YoRhIJ4cuhttyEmGP+tG9es6G2xNhUw7Zji/74448PlWFOIjtbWH/uj2xa6RNrhBZFP/PrP378+KEytl+tTQv/OKgyvfHGG4fPaeQcmVaGlzWI2HN/PvtEPVGdMNaR7bSXP22PMlo3ewk5j84U2qUefc6wv2k3aiMKF+j7Tz9gnNXHwIeG1DOJ++ppCDyzHYVNJOlXFFqR8f8rsPP2jL5e8wQwc6Q+K14jGmlGorMEeI1ExJ5H4TZ1bHYuLrfccq1lyCNY56xB+2kdbpYhN5XalltuWQ7I6rDDQmF1HnbYYeUGtcN1ww03HFI1JhKJ1iNlOpHoL6RMJxK9gRG9kD/33HPFUUcdVUyYMKFkns3L+Pvf/35DUUEUxuRMnjy5OOOMM8Lrxx13XHHqqacWZ511VvGb3/ym/GZvGUHrpUNNJBLNI2U6kegvpEwnEn0Y9hDq/tJLLy3OP//8MsqKsdY77bRT6TBiL+YjwWabbVb+i2Ds+Mknn1wccsghxdZbb11+dtFFF5XqCGPSP/e5z42ozUFGvS9MrTL9iNqIzFgiFVC3hw3UsbUzm+dYoddl2jRyPpNe5IilYL+hiowyFXqzlMjkhbpV9ewdhyKzJtTCXItCjGHWwN9ahlCIqGXVUY92aQ9tojqFYoaCOYVm+vTq7cgciCycU6dOHeZwiXqYzJw4S+kc+fBxmoUTkxVCFDJWVYmzbqyxOkXilOcd4XQs3gRB1dtoeJkb1fhijuPNmbRvfr21bm8iwrg1bKWpsyPHtkGSaZtf5lZNV9i3yLmuO+UjEzXtp5qPabhKbz6l7fqzwJug6O/cp/vGm0wg/5HpBWOzL1KAz2g/eu54U7t6DpP81P3IecMzVE3EvKMiZmDR+P3ZqmvBPsf0S+eY9ud0Y9XPorPcO0/TDw1DyfnoTYb0Pm/ZETnsRkEAvIlKdF7bWOqFQx3xC7nZAJkt48c//vHiZz/7WclURxu/VTDve7MRNTMVYA+PtdZaq8wIWkvQbXHVrpFDPZFIVCNlOpHoL6RMJxK9i4ZfyO0bsEVWgYUYaxBCS1kG/uZahGOOOaY48sgj69bd7vCDQL+5ddrBs52ox5r3IlMeJQ8aC4z1mPpBpqPEQLVCXmm5yHHPO0Xxd+QbAxmhDosww7BIns3VvvCZMvTeKTFimKmTz7Ru2G764evVOmFoo/BlnvnRMTInOIPq3iSkoGeXNLGRD3uobJpleTbcc8895c/VVlut/PnII48MlYHth2nTvjIXOJNqyDTPuuJMqX3D+RWGXM8kzz5GIc58Qih1xvVMPYy7OtdZ30bLkPe6TKvGROfPO/4pi8teYm0jh0fWMnLqZE+yfiSP0vPda110b3gWWvvmZRqH66hMxNB7J3T6rfs+YpaB71OkIaAu1dYAku5E7QKvpdS59Vo3ZEv3J+P961vrrX2j/5EzL+vlmXI9U81BWp1K9Yz3TsB+j2l5HxpSzxu0hJxJ6uhvfWkm8EPDFPd+++03TMjt4DEGWv91GgcddFB5aPNP1T+JROL/I2U6kegvpEwnEgPAkKspyVe+8pXipptuqmJn7FuAfRtqxl6mHvhGY9/alIW0v1deeeWa99k3ksgudFZhedqNVjHDrUKnGGbQqnbbrYXoB6a8V2XaGI7IzhvAZigL7G0pI4baMz16XngGU+fGM2VR+D3qrGeLCQsMg6MsMv2FBVY2DdYVtpKyjz766FAZmB5YHGW/YbF8GDa/J5TNUmaU+wjtBWOuduaLLbZYFVOsLDYhCGH4YZwsZBi49957q/qv7cNM00fVFPhkS9jQ6tjoE2HvlDH0KcyZd11bb/uvawPr50kr2mSeWhVGtVdlWv1CdP78+rHXdQ08G63wsq3zzPng/QMU1BnVTZ38VGafdfcsbJTYBznXPUXfaBetg5Kj3r5ZWWT2pJrxehbXh1TU+5EBPoMxr6fJ0Wt+bNHznzNhrrf6oevOXPrkRxGYaz3vWVM0YYRN1fH6fuv4/d5Q+NC1kL/jxo2raqMZ0+6mX8h32GGHcgOY04gdhmP1QmkJh0zYLSYtgm2HmUVb+bd/+7cxaTORGESkTCcS/YWU6USi99D0C/mDDz5YshSWkGS0MEZDE1vYt/oHHnigZEYsDeq+++5bfOtb3yrtFe0F/dBDDy1Zwm222aZoFTwj0W7GutuY8k5hLFjgfovAMlbsf6/KtLEWPmFFxHQoQ+GTjihDC5MIc0KdUaKPyOuez2BjouQ/MD0wVsq8eDYmYmxgxikTJaqAhaVdjaQCM8b9ytj6BBmwU5pYiP77JEbK9sKIw+KpLTHzDXutLCm/T5o0qfzJPlLGbY011qiyDZ02bdrQNRh1+qZrw1joYxSJh3HSD03iYftY14hx+9Tier8+W2if+1h/tVduVSKgXpZpm0/2axStw2uYIm2XagT8+RD5jiA3rE29BDFRYh8QnRfIoO+jZ6y1fTQ9uidoP4ry4pllHb9PgBZFqfFzpXV7G3A0S2hGdLz1Il75SDh67iIDiy666LD+e9t1tb33bDkypnUD1agA2H7vh6Rnqtfi6L6hPD/pG8nT0LbVY/VH/UJuB6JR860QdHPeWX/99avs3wwWpsmyiu2///7lA2T33XcvnQHWW2+94uqrr65alEQiMTqkTCcS/YWU6USi99D0C/m5555b7LnnnuW3AItJ6xmnlVZaqeG6PvrRj9a1mbNvKpaAyP4lEomxQcp0ItFfSJlOJAbghdySN8yYMaPYZZddql6cW+0s0u/AxGGQwh92Cv0aElFVm6NBr8q0qQIJG6dqZlSmkAVqVuCT7yghQB0+XGJUhnrU5AEHSe84qipQTE4i1TWqVk9y6NhQ+TJuTfqDwxL7gna1DKYiOFLRHzU1MTME7Zv20SfPQe2rfWMeIjXxU089VdV/VZ1T1/PPPx+GFdN5xzxFVcrMN/cvv/zyQ9dQI0dOcYD5isImYs7ik5AoMKOI1p095NddVeAagnFQZdrmh7lV2cLUCnMk3ZPsN/ammrP40KXMt8oU6xSZnGCigTlFFH6P+zGZUBMxf84wNr2fPlFW9x33cY39o6EBQdQ330dvjqfXvFmMzkWUWMf3Eahs+P3O2uj6Uea/33pOczZFY4pCiXK+R6Zi9MXLpp4F/iyJHG59iEXti08Ip/Nn520zz+mmX8gt49cqq6xS/PjHPx5Tp85EItEepEwnEv2FlOlEovfQ9Au5OdNceeWVxVJLLVX0E/KLRf8nL+rHkIitQK/KtMlsxGrhqAjjoclGYD8886S/w7h5Vks/i5y7vIM2/VAWWNk7/7dvzzui6V6ir9o+zLBnuEkfHSXP0bCBME2wghHjQxg0n+5bP4Mxgk3S0H4wVD5EocoLSXs8c6hyC0M/efLkoWtTp06tYtqNJfbz7LUg2r4mIPJOlsxXFBLRM2bsjSg0HFqDKM06SUQih7tBkWmbQ1hJlQ1+93Os+zYKU+q1ZTDLkeOiDzGo8E6lqnWjTs4bDSno++RDo2pf6KO2z973ScI0vwoMr9fiaF20EWl2vOOnnimshb+m/ffO4Ap/JnCfypZ3xnxJnMDRZPn11zn1Z6qOkfmP1oa+oDVEC6L7hzM8CnvptQd+jMxtpLGohcYDJL6Fj33sY6UHdyKR6A+kTCcS/YWU6URiABjyLbfcsvjqV79ashEWnsrbO2611VZFN8K+2XQjC95u++ZuR7tY7E6EROxWprxXZdoYCthbZcFhKKIwXiBKShKx5rXCYEXh03zYNVgtZfN8qCy1N/XMaMS0wrASKkwjTtE+rE7EWGFPDhulSYNWWGGFKhYqsiFnD3OfMlb0xTNmytDDQjPXyr7zO2OLwgBybeLEicPW1sLuGZ5++ulh68bcMpfMv/aftcBmXe3rOSdYE/pGOESt26f71rF5ptH3sVWJgXpVpm1eYZ8jDUMU9tDbPkfPecbvkzfpHor8OtjDPjSfJtTy9+sass70MQoNiNzQJw3750MZ+nVkzlTutYxPdsSZpHbN1M0ZGmn9vEZMw3UiG4xD7/dp7aMxUuaNwK+B5zRaMz0vfOIy5l/3DXXTfz0TGS99QzOoGj2fpCpKEueTPfn5G9OwhxZhxRBFPulmZ5FEIhEjZTqR6C+kTCcSvYemX8jrpUxNJBK9h5TpRKK/kDKdSAzAC3ki0U/ot2yegwRTP6KCVM1cPRUiJgqonKPQdP7+KAwZdap6GEdDbzoSOZkBVR3TDmpZVLFRVj9Cg6nql7nwYbZUBYuTFGYZOn4+YxyMTdX73hk0ymLKOLRvAJU5zlU6N9xPFk6Sz1lCOHDzzTdXhQhU0wXCPtL+fffdN2zd6TemO9o+c8GYdB5Ra+PUiemQmuNgvhI5jPKC7J2KvZOYfT7IL9O2h6Nskt7EKZKJyAmZz7wzdrTvorCB3nHP16tnQdRvZJJ9702ndCy0pWcK13w20XqhWKN+ejMePdN8CE4t60P7+Yy32ifaV7MQf15GGY69+d/fxGHWm8gg4zoGvyfUHNGHedTzwpuN0a6asfFeQD903bzDqncYHwkacuq8+OKLG67QvH9vv/32EXcokUiMPVKmE4n+Qsp0IjEADPmZZ55ZHHnkkWWSAXMWWW655aquG9tgL+E//OEPi2uvvbY477zzxqq/iQFyOG1n+4MWErEfZNpYi4jBihJcgHpMmXdKisLuwcpE7SrrFCUKmhV7DOtL3fRHk4AwJthbZXOo0zuDLrzwwsP2NvdpP7gP9pr2YYV1vDDthAzTsGuw6FESFzI5w3Qrm+ZZZJj6aPywUmgh1CmT9lZbbbVhzqTsDVgsZfq8M6yGhCTMIWsEC6dJl2DflOGrte/8WFuBfpBp218+xF/koK0scj2/Nc+sR4mBqMs7fioziixwvzK83vFRzwHa9YmhorCHPkSh74vWo0BOSLalDL8vH51byEAUkpFrXvug9fqEPnruelmInJkZ4z/fmj91VPdJizRJmA+JyPpF+0HrrDUX3gFW55a26rH/QMdv/Y80F6N6IbfD02KannbaacVBBx1UHrR2WNkg7YCyuJF2aO+8887FtGnTqg6yRCLRfUiZTiT6CynTiURvY7ZKk1/RjRG57bbbSjs/+/ZjL+KWudP+NfNNoF0w1sOYk4033jgMGdRt6Mbwh53uU6fab2e7I2HKjSX96Ec/WjJfUYi4fpdpsyuMQgvyez07U449ZU5ghjwLp0ckjBHMsrJhsDh8Rj2E09I+wVArmwXDxTXYIO0jrHNkG2qp0pWZZ26iNNnXX3/9MHtL2vE2kTpGbzep+455p336E4WYIzThY489NnSNhD70A6Ze2yDcog8/qJ/BdK+66qpD1x5++OHy50MPPVS1fjq3MOzYguvzgr3BnGqYTcC4YdVU6+YR2aTaPmOvDapMb7rppsO0UJHWK0rvDiIbfK/1ipK10EYUihSmlz2h57Vn1rV9+omc1Qp3qX3S+xmb9yvR/lMeTZbaSdeyc45YdB8uVst7bZeeKbSH/Gr/fZjPaIw+FOw7RCOGJjBaL2SXxEiRDbwPqRiFTfTQ54a33Vcbdp8sijb0vLQ2mnlON+3UaYu+zTbbNHtbIpHoUqRMJxL9hZTpRKL3MDBRVswGMLIpbQTttPNVVoVvep2OyNFpW/JOYVDH3SswtiFiHDybqTZ+yBS2v5EtKQxHxJB7pkwjcXC+EIGDtmC+tW/Uo8lnuM+zYmqH6RPbRGOD4YmUn9RJSnVNL0/7sHmejVcWGJtq7jFMmDChqg1sSrX/2GDD9Kl9Ooy4j/Ki44ChoqyyWcwba3vjjTcO6zdRUbAp12cCc8H4lWnDPh72nXmnr1G0CWX1PDPaTLKQQYKtgZe/WdkZsz94TtZLyMSZoL4XXtuiMu1Tr9OWpncHJA3S9n3kEcamKdw9+6v7jvuQlyiCD/D+DdoeqGeDz1zpmUJdzEkUQcSfRVEEG580S+XO22L/S2QjOoM8kFvsvLV9xu/PTZ136uZnZG9Onepz4hOoRYmhmk1I2X26q0QikUgkEolEYoCQL+SJRCKRSCQSiUQHMTAmK61K6FILY2lWUq/9TpuzDILpSDvaj9Z4ENZ2NDBVYBTiyqup1XmH3zFBUHANlTMqTDVrob3IqZP7UQfTvqosKYPqU1W33EcSDFToavKBOhTTjciBCXU6qtfIAY77VXXPuOkbph9qVuI/0/nnmnfOUrMO+r/mmmtWhT9UsxJU0Ji8YB6jY8JURvuP6ph503H78HXm3KjOnorIOUvNEHSsao6E8y5qdt1j9E3DNEbOyDY/9cL49TvMQRBzDpVbZKOeUycJpdQEBBlm/jHV8qYcapah5hw+JJ4PjapnAY7K6lTJWDBn4T41K/Fl1WTCjzsyWfGmF3omeFOpyKzCz2mU0Io2kGndx8wtz0mcO/U+X1b3vT+nKtK+N6fRs5jx0gbt63nlnWD1LPVhDqPnhQ+bydms7fNeQFkfCrcZJ+qmGHKbjIkTJw55uicSid5GynQi0V9ImU4kBoAht29rUUKLxNiw2PUiUvJtrp3sfb0wXoPg+Nju5EHtQC/LtMkHbESULjlypqkVhkuZEdgzmJsoRJlPTx8xNrBBysbRT5hdDfEF+wOL59kZ7SNsrDI+tAP7DVOuY4S1ZfzLLrvs0DX6i6MpTLWyUjiOIQuaOp5yJAsy8sag+4uQchFrBMPIuCF+qEfHCwunjBX3wZ5rPgzvcMaZqGzYfffdV/WZMqWwl7D4rL+OjflnjfWaZ9h9n2m3FYmCelmmrd/MY5SEJUrP7kOfKkPJWsBaIzfR2aDMKvAJxFhH3TecE8y5rjXtwyizfyPHSVh07b8/35BR7b93nFSNkmeYo33vmV09S5lnH3Yx0iLUc4pEk8T9OkavEZpNxlYv2Q/7hDmlj5qsi7OPOrXf7Bv6FDmc+nZ133nWnjb0vLW6o/C7LbMh32uvvYpjjz02vcQTiT5BynQi0V9ImU4kBiAx0Cc+8YkyqYTZGU6aNGlYgoRLL7206MaEA5MnTx5x2MNWoZU2wd6WrJnQOq3uy6wwlmxyp5nqdrRfa61alRioV2Xa2C6YF93/XhYaSRQSJZGA+VA2B6YNFkzZD8r7EFuRnXhkr1grpFmU0MwnMTI88cQTVddgfjS0IQw1fVIbaFg8z0rpfFIG9l3rBjBk48aNG5YYCWaZEGV6DWabOp977rlh7cOMkzRJtVaMm0Qhzz///DA2DBYUpj+y933yySer6tNyjJ8xRmwsn+ncMm72i7fJpX1be9tbgyrTa6yxRsiQe/ZbWWjKM6fKavpQfj6kaJQYR5O/UI66aUt9F1h37vdh7/SnTwLk+6JjNCy88MJV5Wk3YrE9G6zjpV3+jvwjaKue7X4U2tCPIwo76bO3R2EXX3c+LNG1aNz89Cy89pMzQdl7L4tee6ryGZ333ubd25KrXG+wwQZjkxjIBv2pT32q2dsSiUSXImU6kegvpEwnEr2Hpl/Ip0yZMjY9SSQSHUHKdCLRX0iZTiQGJOyhqVRuuummYsaMGcXnP//50tHFVIdGx6u6IVENdcD06o1mTU7ASO+r5Qw6FqYsY+kM2mlH07EMicjeaEfYxV6UaVO/ol5VJ0HvABZlvkNlqupNb6LiQ41pee7HyU9NHryTk6qAMV1A9aoqWB9uMQrx5vuhqucll1yyqk84Z6pZBJ/h3IkDptaFCpfxaPuohTF9iZxCH3roofLnHXfcUWW6on156qmnqtrS+cecBfWuqplx/OQzVX0zJ9OnT68Z2g1ZYo50beg/5il6P45imH5gOqDr7527NDQc42ZOvSqeucVkZZBlOnomRqEoAWsYZfGMzNW0rLZDG5gz6fPQl1GZYL34qdfYS+yt6EzBKZF+61mGaZY3dcEEQ8+QqG8+Myd/qzM4UGdQDz8PKrfs6SjDLeVeeOGFqvnQ+ed8eP2tMarJCPPG3EQhYBkb1/RMp0+Yxukz1O8z5l3NUpD7yCmUz5hv3ql0bax8M1bhTb+QW6zPTTfdtPRut45vtNFGpaCbo6f9fdZZZzVbZSKR6CBSphOJ/kLKdCLRe2j6hXyfffYpVl999eLBBx+scn4wJ5IvfelLre5fos/hGe5WssBjWXc/hV3sVZk25iEKn+eZ8SiMlmes9D5fp7JB3vFSGRsYEp/8R0Mkwqhyf+Qc5h1OtT/euSlyMoKZxUkSVlwZKphxbZ+xEH4NVlfZVOqOmD7Y43XXXbeqvpkzZw6VwWGTsjBnyoLBjDNGxmFYe+21q+pWZ8WpU6dWOZApew3TBZvHOFRDQHvUieOqgvtZE2VgI60F0DXQ+VPYmFoR9rDXZRr2VOcCuWXeVbOEfEYhCT0ihtfLvbK3yJcPZan73mtUIidsvyfUcdOHz4sYbu/oGjH0yKvOm3dY9WywXvOhHVUm6z1LOR8ijRpy6udP5wNt2Wxv9U0TC3Ef9URzCxiTaki89kHPa+bLO9j7ZF1R8iX9jDFRVjVjplloRuPV9Av5rbfeWqoi/QYbP3581eGaSCR6AynTiUR/IWU6keg9NP1Cbt8ioiDtFmJKGYlEffCNM9Ojx/MyFox2u2zZ22W7ruzmaNCrMm3sVZTgB8bDhwNTeLtDZWN8Yp/o/simlVTvMLqRDTssEixsxHSBKNEJn0Vptn1iI9rQ8HuwvtSp7DP9pw3CBup+9kyThvHyyWiwM+enweyZtQ21b2f8rBsaB01B78OPffjDHx66ZiHzDA8//HCVDbuuLWwedU+YMGEYi46GQM/me+65p+p+xqoaCm9T2khCEGUzbWytYsh7VaZtX0ThP/k9GpMPxRcl8vKhCaOkQ5HWB9tjH35Q++HZW+239yvwfgqRr4kytNTtw7vqucNe9AlutJ+eWY7ONM8G6/30kX6r9gifD86biBGuF3Las/cvSyhUrvnkSXqNOYq0pZwvrIOy157ZZ9xR2Ep/bmudrAVrq+d1s8/pphMDbbzxxsXJJ59c1WFTyR5++OHF5ptv3mx1iUSiw0iZTiT6CynTicQAMOQnnHBCsckmmxTLL798+Y3MvLctkYIlXPjxj3/c0s7Zt7Mjjjii+OEPf1h+IzOmZueddy4OOeSQEUcX6VZEzEgnxqjRVwaJvVeG23uUj7SuRuavG/Zxr8q0sS6eeVJEbBZyBquhbIaPgEKdEfPiE2VE7cKMKHOMPS9srDLcsFiwMbA72sda6bq1XZ/8Q23AuY/oDcpQezYIZlvtrGHqfEpwbZ959BFFtE6S/ij7Tb8tYIBh5ZVXrmLVdS6IZKDrzu/cv8QSSwxdY76JoMH6mfOjb5950LWBmcMs00ek0XH6nxGiNbU6bX/Ws4Hud5m2NWROI1bVs9m0r7KgLKa3XfaJbvR36okiH/loKbru1OkTa0WJiNhT9bQnet7QF2X0VX70ORPtN9rz52S0Lj55kI6F8pxpUbQR9rS+y3jNRLTvfTSpv4nWkr5QJ1GWVKPnz8koOg/16Bwxhz4hkmov/PNCx4amiTOF++vZubf8hdwmwRxFLr744jK8lR2+X/ziF4vtt9++aiCtgEVuOfPMM4sLL7ywWGGFFUq14S677FIe6nvvvXdL20okBhUp04lEfyFlOpEYkDjk9u1whx12KMYaZgO49dZbF1tsscWQ46h9u7/rrrvGvO1EYpCQMp1I9BdSphOJPn8hv/LKK8PPTU1g6pGlllpqKEHFaLHOOusU55xzTvHEE08USy+9dMnM33bbbcWJJ55Y8x5Tyag6SFWqvYZ6Dj7dYOow1mhHQpx6GG3SJsx/uj3cYq/KtKkfIzUl6+Z/RgmB9JoPf1YvRBjtar9QD3snnshJzEwH1KxD1aL08dVXXx2mHketiypYVcDemZWfahaC+Qntq1MnoflQ6/oQiWoO4M1rtG/MKe0ThlDLY0ISOaChgqcNNT3hs0cffXSYUynzbvtK5y8KSQk0xBrzhApanWExkWFshG/U9fdh4yKzishhEVjfWuXU2asybesbmTV42VTTAx8KUdeYtVDzI18GRE59UXvRWFQ2tKw3f4uS91AmCjvImeDD9+kc+TCpajLBZz7BjvbRm7VEzzvqiRw3ka3FF1982Ng4A7zDaBTK9R9BKFr6Rvvabx9uMDoT/ZmkY+M+3jO86YqCceg177AbzY2Vb8YErekX8m222absgD84+Mx+rrfeesXll19e9SAYCQ488MBSUC0bnE2sLcbRRx9dmsfUwjHHHFMceeSRo2o3kRgkpEwnEv2FlOlEovcwW6XJr+TXX399cfDBB5cvxmuuuWb5mZmQHHrooaUTh9l377HHHsVaa61VnHfeeaPqnNmp/8d//Efx3e9+t7Qhf+CBB4p99923/Oa90047NfzN2765TZ48uW7onU6jmx0AO+3c2SmG2Y87mv9mnHGbHcesRNMYwc997nMl26hMYbPoVZk2Zz++9CsDxrxFqZA9Q6SMC8xKFBIMUCfsjDqAse5cg/WLWFSgLK4nMDwDY+AMwzlUnTprJaDQ+2kPp06Yah0/jE40Dzgy4dyoIfRg23Hc9M6t6oB17733DnPYhJGmHzBWmoqa8dK+XoPZZh4J26jM/C233FI1Hl2/KEwlgKGEBaQ+Y4X9/DWCyCmYtPH2b1BlerXVVhuWICtKuhPJBHtDn/M+FCHrGCUEi+TNazR4JijD60My6j6InAH93xHr7ct5mVSZYow4Hkfy5scROSNHya7oP3PLGaNyzzVkI0qe489WXXuf9OlNad87dUaaETRoOJNHiX1oX9edsXkGW8/hepoVr/2IggDY2Gw9tttuu4ZkekSZOk09ZWoqsMEGG5Qd33333csYsBYWcddddy1GCxNyY8ntpcMwadKk0iveWPBagm6TpIdsIpGoj5TpRKK/kDKdSPQemn4hN0Yjesu3z0iB+oEPfKDK7nCksG8WPuSYfcNpRViobkVkCzsI9uK9gChhQL1yvkwUWrEb0KsybSSAt1eO7D4jpjfSlsGieLvHiDGKbIFhjzybo2G8vJ2kMk0wRT6Zh/af+2G4Iy2KT4YR2Yv+9re/Hcaw+3CJsOmahIQwgRMnTqyaB22PeeSnEiQw8oxD2ShYb5hybNqVxWfc2D8T4lDr4j71H2Lver8CWDVl2wmHpinnsadn/GgB1L4dWQFqy+tDwkUhOVv5XOtVmY4Y2yiFvcq7T6gTJdvyKefrhSuNWFgf/k4ZXm8frfvda52AypRPbBMx7D7sorbBmNhvUdg9nzwpCuXqzz2dP8bmQxzqNc/mR59FCdW8hmJOOe+8P4bPEK91+nnQdiPtlz+vqFvPBL+n9H7vF8D9uv+sjA9Z2dLEQKZSMuYapxaD/b7//vsPZUqzeKeoL0aDLbfcslS5/eIXvyjjT1522WWlGuwTn/jEqOtOJBL/i5TpRKK/kDKdSAwAQ272ZhaK0OKc8tJtjIKlIL7iiiuGvmGYndpocdppp5U2b1/+8pfL6ARmg2t2b4cddtio604kEv+LlOlEor+QMp1IDIBTJ2qAX/3qV0MOLcsss0yx0UYbhWqQTsPUlqZe7Hanzm4Ojdct5hXd4tw5UjRqetRoe61y6uxVmTa1PCYYkbMOn0VhxKKMf6g3fdhABapjb5ahamScqjCZULMQ70yqWTRrqbVVPY46lzrVrIL7cW6kP6repm/Tp08flvnOh0206Fbe8dQyMWqdGvYQUxlCCWJqomYp1IUDqJrz0Cfmhvowr8HMwsB+1/XDJEznG2CGgokL41DzBL8meg3TIsbCNR2/z/Qamfr4MJ21Hr+DKtPmJ8b86XnpHfAikxMf4i4yV+N+LUNd7HuVSW+2tuCCC1b9re0CPTcYg/dr0/bZQ/Q1Mrnw5hyR4ylO0Lr/Oa/4jPu1j/68rBfikf5o+75OnEvrmQ/60IDa1zcCR/to3vz4Ca+qc+3HovvBmzFFJlbemVbXmtCx3ixH59bK25m74447jo1TJ5O86aablv8SiUTvI2U6kegvpEwnEr2FOUcaUsn+mRmJ/1Zx/vnnt6pvA4VOJ8GpBwL/dwtT3u9OoZ1AL8q0zSFsiDIfzC0sLMxLxILpOsDaUCfsrd7vmWZlY6gbZhemSx3nfDIL7TdMGfdHTpXcRxn15fEOYD7kmYG1XX311YcxPjfddFMVC2gJXrxTJex3lOADR0cYfdggZbl8aDrzD/KME1oP5hMHUr2PudEQb4wfFlvb5ffll1++6n6dG8qQ4EOTJuFoyp7wTpp6dpP8CU1FxNS1KgFQv8m0raFPAqR7wYc/rJeQSn/3563KnU96EyXbogyaDk0oxVnCvo/YY+qMwqX6hEZR+97BO2L4cYqGKde6PMOrc1uPhfaJ1KL7vSZRNXqU99rKKDTlX9+SZdZBy9HHKEmbd+qMQmJSRvtGvzmnuBax6NF57fvhHUhpvxnLjKZfyC3pzlFHHVUe6PaC1m0vFolEojmkTCcS/YWU6USi99D0C/lZZ51VXHDBBaVNTKL1aCbRTKJ3NQRRptuxbK8fZdpYExiXSEZgiCM7ce5TdsgzLj5Ent4Hq6LMI0yytzPX8HuUwSZZWVSfdIi6NTQiIeuwl1R7V5gmbJkjm1p+nzlzZlWIQGWmvd2shvZjTmGTtH2YYRg/GGNllbhGXzWfBaw1c0RfNVyon9so6RHspa7NSiutVDVuSx2v86l1MW9q78k60Qa2+6q9gFGvp9moZ5/bSvSqTEcMqK6N33+RnEb23V5DUK+MrhHt+pCgUa4Tyup+9+d8veRT0RzA0NIeZ4MmrKG/EUPrz7vIr8Qz87pvo1CEWp/OH2WU4faMOG2ohoM5eocL16rzFNl3M07Ggn+IPjepM0pIxDiR7UhD4hNLqX2+10j4EJn0rZmEYU17d9gE6yGaSCR6GynTiUR/IWU6kRgAhny33XYrfvSjH5XhCBOJdkKZsm60tR8N2mFT2m8ybawL86aMjWdhlXHx7LcyRbAx9Rgn2GfsHZXp8bavUUQCHzlF74f9hSGGodVIJNhT0w+NgEI7sNYwP8p4YafOnGj7MPEw3VFiIvpCWzrvJOuBhUZeIzt7+jFu3Liha4zFR6tREMGB8WPbrbb6zLsy3NRNGdhsjZIS2ccC5oK55D7VfnAN7YXa3teSbz83Vq4VZ0GvyrTNAXIQaXZ88q0oZXnErMMo+4gmtDmrKCfeZ0JZdJ/6Xe9X+dA95iNx1PJL8O0xHt239M2neY/GxHiiyE0RG+0TAXktmoKx6nOaZFs+yoqO0bPfs0vdXmuoZ5nXCHJN58HbgOtZHEXz8RpVHxUr8ifyc6T9b1aWm34ht4k555xziuuuu65UA/qsUJa4J5FI9A5SphOJ/kLKdCLRe2j6hfyhhx4qVl555fL3adOmVV1LW+dEoveQMp1I9BdSphOJAXghv/HGG4tehCWCaDYhQifC/OHQF0HNNFCFtPNLkPZtEEMgtnv87QqF2asybWH2NOkM8OpRVYmiqkUFqk46mGMQvg8VrJbxYRZV9Yss+tB448ePr6mCJkGNqlcZU+Qk9bvf/a7KWYmEN6qq5Sd9VfU6Y+N+Be2hDo9COxJmkdCIOjdcY9yoklVt68O+6f0+RBkmJ2q6QpIgTE/UKRWVNWYkqt6mDzhz4pClpgs4hT3//PM1Vef8xCxIzYn4nXlQ9TbmQOxFxuRNGlplutarMm3rGckteyMKTceeZk0iB0CfbEod7bwZhZqBsU+55pMIRY6fyIaWw5LAl9U6I6dQb0blTWi0DG3pcwoTL9rwJlfaLnOiJhve0Tkyy/ChFXX+aY/y3oREy7/trbIqE/Tbh0JVGfKJifRMxXzMO56qSRn7hnYjh9ModCF94zmNeY4PIhDtx1rovpRdiUQikUgkEonEAKFphnz99devy8recMMNRb+gHlvdCaZYnSU82u3kmMmC2odarFmr2LR+kGllTqLwUwD2AsZSx+0T28BUa4IYrsHOREk0vANglCaafmiaae9wBYOjbBaMHeOFAVK2mfK0r3ND3xibMryE7yKFPfOhjCEsEHOibJJnfX2iH60LplJZZMbtnWG1DTQEPuFIpBl55JFHho3bJ1TS+2H0o5CKsGjUw/gjx1PKRinAmZuI8fMJVgZRpk12o3lg3zN/OrfsCbQmUWIeWGvP5kbaIq3bh1Ssl14eeVOG1jsj8pyOknWxl6Iwrf5v/dwz7Mo+46CN3EYaBp9sTLUHrAX7NXI89SERI2dcL9O6xtz/Zyd/2iegWi/v4OuTMEXj1bnxmpEoCIDXjEXOqHyG3Ov91kevBWvpCzn248Aaf+CBB0p78p122qnZ6hKJRIeRMp1I9BdSphOJ3kPTL+QnnXRS+PkRRxwx9A1nkNAIi94ONr0eez6WLHq98bdzvP0WBrGd2ohelmkf8iwK36VslmdFIjtVWFtvdxmxMspee/aK+6LEED4ltZaHFfLMlfaR9tWGmr7B3nrmSNkbUoCT4EbLb7TRRlWMnbLo2FnDmN11111D12AhmTf6pv33rLcy5BMmTKiyHYfh1jnyrFSUQj0KrQZ7RV2EW5wxY8ZQGW8fq3uKOfV7RBMjYbvuEzv5cSqUPbOxWJ+bSSTSjzLNfokSckWhCT3rrfLOGrIXo8Q6XKMeTT3vmXDaVd8R2PtIs+L9ODjLo7CHUdIh2kMGKVMvbKO277VWkdZkscUWq5qbyPfC28KrTHqNkM6N9yvhOa1r65MFvU3a92ur/Wfe/JhUblln+hYldPLsfZSYifsjjRz3c6ZqIjWb/2Y0Xy2zId9hhx2K888/v1XVJRKJDiNlOpHoL6RMJxLdi5a9kN95551hYPpEItGbSJlOJPoLKdOJRB+ZrHzyk5+s+ttUD6aGueeee3ouK1i70emwge12Cm2nOUs0trE0Y2lXSMJ2oJdlOsoY2UiIMe+IFDlwRWpSbzKhmSLVfMSAqlLVpKhzMXVR1TvXUAFHYcR8+DWctfQaDptPP/10zTG+733vG+awiaMrfYtMdtjv9Fszbd58881VfYrCD/prqvr2WRWXXXbZqnk03HfffVXtq8kIan3qxilVnduYG5xpdd9gloJJRxSSkRCUUYZY74AWjQ0VfOQU2EqTlV6VaZvPKGOkD8lXL7Sh7hf2kg9pFznnUYbQmmrSxRkSOUV6h1295rNBsiei+/mMDLvROcFzU8fvzXiiPelN7XSP8SyjjJplcE54E73IrIT7tW6fIROTN51/xjRXHafKKCQjoG7q1POedxDOnchE0Ttd6tqwXsi9Pgu45h3M1WTHTNWaCb7Q9Au5HnIMfplllimOOuqoYuONN262ukQi0WGkTCcS/YWU6USi9zBbpVWx07oUxpbY4WThwZpNDDSW6IXEOu1kf9s9HyMZ20hFpVXz6Ns3RnC//fYrw+PhCDcIQKYtvJh/8YjYS2WoffgqnVPvFBixcJ5N0TKEKYQ5gemJHIFgWpThpW8+tJ6O0WsEtH3uV/bKl8HxiLKwycoCwSo+9dRTVePw/dV6lBmi3zhlavswbDBWqiGAzYOxw9lMQWg7+qRjffjhh6sYbmW6GBvtEipPtRpoFLhPtQf0jfmHeVOHV699iVhQ9hv98WEXYcgHVaZNcxE53vm5jZwio6Qz7A/ujxLbeAdv1XQQVhTnSPZr5DgaadQox0/aUvNe6mTf6p6OxuTb59nptQF6P2NS9ta378+mqP84LOq5Sd8ix1F/3lJPNP/R3749Zd+9MyjrF+2fKFylZ/R5Tuva+HCXuu/8MyQKc2v32Rmx7777NiTT3fOGmkgkEolEIpFIDCAaMlkxu7tGU7R7O8pEjEysE89Hu9jzZuzpR6tEGq19+1gosfpBpm1ePDuibFYUdhCmI0oLz3z4EFfKqsCQ+LIG2A9YqMhelfsIgxclFqJO7FeV1fI27PWYqoix8WWxG9d2vb0tocu0L8ybMrz8Dou93nrrDUusRP+pU9lIH4qRerSPMGawiTr/H/zgB6vs2tUWGPYcLQbrqIw/YRdpF/tZtesltCPXKGt48sknq9ZEbcg9osRKNjejkfV+kOlaLGotW3wFDLUyzGgw/H6tl9hHzxKeS96WOkovH7HvXiZ9iEQ9i6hHk0358y1i6L3tfBR2Ec0U9Wgf6QtaGwXlmVuSHkVnqp8jvb+Wf45izrc+0/OO+Y/OO/9eEGk2/Vms8gYTThm0ZgpCYEa268wh1/xeA43KZDmGRgqdfPLJDVeYSCS6HynTiUR/IWU6kehtNPRCnhk4BxP9FElkNIx2Oxj6aI7H0r2jH2TamJAolbZnM6IkIhFj4j36I8YLthb7Yr0fFsrbZ/voG5GHfpQ0B6ZM2aiIBQQwNLQPi6x9JJ09zK7akHvWH8ZfmV5vU6r2lrS34oor1rTzhgWHvVb2CHtd2HPYa+0j44eFUjmC4YMN1wg4q666avnzhRdeqLqP/mgEiIhF5DOYcph2fip7z7w99NBDRS2w7t6W1v5FvguDItO2ruwJZVFhMdl3kdxG7LePpBHd34h9uWef9WyOmPVa5w11R5GTKKPj9slnfBIblReeIVE/kNMoSY2Xe2WoPZNNH/VM4yyMkq15FjqKhML58q8gsZLXPuhZQuQkgK+NJuFi/em3nlcw4p6ZV4ab84LPOD91vrx9vMLqjOz2R21DbpN87LHHFuuuu26xxhprFAceeGCVQ0sikegtpEwnEv2FlOlEonfR8Av50UcfXXzjG98oWQvzhD7llFOKvfbaa2x7l0gkxgwp04lEfyFlOpHoXTQch/yiiy4qvve97xV77LFH+fd1111XbLHFFsW5557bVeEEE4leROT4OdahIHtdplW1GTlHRs51qB4jpyLKedMRVUX6a9oH1KmocH1SDr0vUnP7/qJu1bF5cxpV4dIOKlvaikLzYQaidaPO9qHltA0fGk4dJwGfsYdUzUvYQa7p2kyfPr38+YEPfCAMNafgGk6W2k/m4bnnnhu6hhkJ93FN6yZpUKR6xnxGTVT8+jMntIEJi64Be4O59eZIozVT63WZ1rlRVX89uYsSsgBfHpMFXUdMnbypmN7nnTnV1AyZiBJp+URCkXOgD5eo+y8y8dA2o1CkkTmOnz/thzfH0bPRj595U7MQ+sZnet74pEeR6Ywf2xzSN+7nvihsIfNNmWhtOGd0bekv9URt+P6qmQzlSDKGOaOeaZihNYqGJdTs6zbffPOhvzfccMNysepFq0gkEt2LlOlEor+QMp1IDABDbt9U1CCeb1uRk0CicWT4w5yjTqHXZdoYisgRyKeJjhI9UEbZGc8iAS3jnfE8G6LOiTgARumWfTgx7ZNPt63rwXhhdzSkIEwRLFDkwIbjE0yXMkYwPNQJ46t99AyzMrwwdbCCOJnpHNE+2p9bb7116BrzRmg1nGSVYYdhph6dW+aJuSX8oY6BPsLiq1Mn88faakhDn2yIvxXcx35TxzdYWBzwWJMo0cmgyzTzpn1mTdlbygrDyCIT0Tx6pjRikaPEMqwp8oKGR9vwofwih0/G4s8mLUNbOm7PukcOm95hsp5Gjb0R1cM86th8eFbmPQp7iCxpQq9aidSUxfb9nj0IGxk5jPowrdGYvIN2lKyLuWVvqNzWc+at5UzstaaRxm3UL+TWkZ133rlqs9oA9txzz6r4lZdeemnDjScSic4hZTqR6C+kTCcSvYs5RxNSaYcddmh1fxJdiEENf9jvWoxel2ljOHwSHwUMhtqW+vBjkR26Dy2mzIsPoxUxZT4ZRcQmRamYayU20v7D3kR1008IEuzEtf8+eYXe79lDmCclXHxiELUlpU7Ya1jkqA3GqIwV7B3MNGyczhHsfcT+01/aJamHziV24rB4yuA9/vjjVfOlCZF8CErmRMfG3NBGFD4v0nq0Er0u07YfvPzovmUd1QbcM+PKYvpzoV5owoiFjtLBe3htl+4JHx60Xgg89oT2mTngPtpSO3X6xnNaGWofNrBeiD7kV2Xah22M/HLQGrAmkc8NPxmbavbw73jzrbGpTHLeoS3T84Jr3MdzWjVqzDv9Vc2K91WIWHDai7QX/O41cyr3NhdjwpBPmTKl4UoTiUT3I2U6kegvpEwnEr2Lrne7tsDs9g3f0inbN7dJkyYV99xzT6e7lUgkRoiU6USiv5AynUiMHg0z5J2AOUVZIqL111+/uOqqq8oQV08++eSQSjAxWEAl1Y/mI4NiKtNKmTbVIqpUVSWiZkSFqGG4+MyH+FM1sA9xpipU77il9/usfr///e9r3u8dMA1GOmgZ6sHZMspqF5mzAPqvKmjMOfisnlMj/Z4xY8awMTI2XTefIZRMmapeR71NBrwJEyYMXZs2bVpVGLGpU6eWP9VviTGiilbzANaZeYxMlTAroY8athETH9TaqpanXdpDDa3qce8AFpml0DeyBCps/kaTqbMfZNrmPJINH9pO5ygyJ/DXkCnMKtQMy58Xut9qybuaJbDv2BPRmcBe8o6A2m7kzOodNv18qJxGTqX8jlmId07W36NMnd60jr5ilqblkTE19eLZxfi9c6jW+YbLfBllP9azzGdLZk6iuiOTIcZWz9HVn4XaN+ScM5RzS6H97fkXcssMuvjii1ep4ZZccsm69/hUpZp2OZFIdBYp04lEfyFlOpFoDbr6hfzKK68sNtlkk+Izn/lMcfPNN5ffQL785S8XX/rSl2rec8wxxxRHHnlkW/uZGAwMGkPf7TJtzAiMpbIbsDF8MVc2DKYH5qKew40y67WgTBPlvXMk4Q8jxzF1FoM88KyM9gPW2Y9HAatUbxwwhTC2yh77kI7K0MMQ0VdNlAGjiTOlD/GocwE7pSwo7DnOaT7BkfbF99Ww1FJLVY1R+4bs0jfWbaWVVhrWf/aEzg2MNs5oJCSC6dd+st80NCLlvRZG0YzzV7/KtMlDJBte26XXWEufKKZekqsotB9yo5oRzhAfijRKWlSPqfeaPJUJ+kT72n/khPZpN9L6eaZf++ZDqkb990x75ATK/bpXvcOkzp9vI3KU92Fm5woSgUXsPf30668yaYRuFP5Rf4chj4IA+PC4kcOtd+ZUDYvd70M/ttSG/JZbbgnjfNpndq2VeOqpp4ozzzyzzNx2zTXXFP/2b/9W7L333sWFF15Y856DDjqofNjwT7O1JRKJ4UiZTiT6CynTiUTvYbZKk7l67RuCsQ3ve9/7qj43BsE+a+W3fPumuPrqqxd33HHH0Gf2Qn733XcXd955Z0N1GJNj9k6WdKIXUgd3M/PaTWEPOz1PnWjft2ksyX777Vd+8cRGcCToVZk222bPGCuQ9yjRhE8GouwHDFUUUtGHxooSRcCiwtwoY0N5z84o4wLD4hl3tTP1qawVzEkUss2H6nr00UeHrmEXSnvMQ2S3CYut2gfGzT71tvgKZQHBzJkzq2wymU/s1bUu2tV9DyMNe69twKx7xk8Z+rvuuqsqbJzazmNrzhhZq8gHgfmLQkLSf9aN+WS8pNoeVJm2ZwxrGzGLUfIY1oJ5V5mKNGizCjcYybtnQUli5feAb8vbZ8OCR3bqvj/aHmV8EiRtj76iaYo0ctQXJdihT5E/DmvB3Oj9/izU8aAZ8vbtkQ39v1yIxUhDofvWt0cf1ZfG+5zo/X5uaUv3Vq3xa/s+oRxjpi5bs3//939vSKabfkO1TkQxOU3Q9XBuBexgX3755as+W2655cr0wIlEojVImU4k+gsp04lEH9uQf/KTnyx/2su4z9hp3zoeeuihYp111mlp58xzm2QN4IknnqhKiZxIJEaGlOlEor+QMp1IDMALOepM++Zt6j9VmZhaZO21167rxDESfPWrXy1f8r/97W8X2267balSPOecc8p/ifYDNXW7zVe8aijRGvS6TEeORaqmjUJVQSRQRtWzPqsdqtRIPRtl+vThz7hPnYR8iC1Vy/t9Tn2qgvdh1CLVNe1huqFqUp9pVJ0acXzELCPKRsl9K6ywQvnzwQcfHGYWggOkzxyq8OpiA/4+9Jux6fz70JBqssNaMm96RmGaQ5hCzFt0/hmbz9ip+8Wr9fV+1oQ2dN58+Do1lQGtCHfY6zJt6xplg/T7Vs2RfNg9ndsoFKCW1WtRWWTRh82LTC4icxr2Ip8hC5GpHHXrucY19lJkuuEdpDX4AKH4fChOnT/6HTmVUp52ORuUkOV+nzHVz6Veqxe28R9yXtKOD1erdVAnY1SndhxNvVOp/u4dhSNnYj7TefemPtSj47d904ypdNOZOsePH198/etfb7l5SoQ11lijuOyyy0pHzaOOOqoMeXjyyScX22+//Zi3nUj0O1KmE4n+Qsp0IjFATp29hl5z6uwmx8VG+tZp1rrTc9TO9sfKqbNXZdqYTFhZlW2YIu8spfsVVkPZZ5iZeg5InjGKHCY9G6UsKs6BPtSatgsrw9jU8c87Z0Uh3qib9pU8gRmGfdSxPfLII1VlYJe0/7T3/PPPV/VRnS9hH0kMo7kg+J1r2jfmn0zMzKPubRwtYcp1/agrCvMIa0XYRcamjz/PkDNGvQ+GMNobfBY5rDIG6onCuCkGVaaNdPOMt+575jtypgbKrHs59Wy2lql3bniNmLaJ4yx1a789IxyFRPSJcSIW1ztGR1oroBoCzHs9w6v3+LCHKlPURf8jDQHnjXdY13nC0ZR2tYxnxucK+hbNuz9vuV+dOvlsiSWWqPpbx1DPqddrSXXf0G+vvdDntF1r5jnd9BuqPVB23HHHUh1oHbLO679EItFbSJlOJPoLKdOJxAAkBjKHTotycuihh5bfBDrNkCY6g9GuezN24ZESZxD33VglJupVmdZ+KisEa+vD9ylD5JP3RGG3YIqUcY3CZwHu8yEJlWH2yX8ihpW6o/B9lIfF1qRDPtkR7UbJMHwZX06ZI02BTjp7MiYrm+YZfsajrCB99AmCDLBH2GA//PDDw/pIXyINBew15V955ZWha4yX/jJ/astL0iB8ZZT99+sGdP/4vaFsHH1hTmDxtP9RQpVBk2lbD59ER9e7Xtg+n0QnYlYpo/LLOrE3dU/6cHessWq26oUUZL19Qh9N7844VZZ83T6hkO47zxQrw0+ffGhC3Q8+3J+edz50bOQ7w/1R0h8f0jBimv0avSn3+2RLke2/r0flztuZ61nKZ972Pep/lFCKvniNKOFbYeabkb2mX8hvu+224tZbby1WXnnlZm9NJBJdiJTpRKK/kDKdSPQemn4ht1SkfW52nmgAsEjNRFvJfdOd6FWZNlbcJ35Q9ipKhVyP/VZGVK9pGVjMKFqCZ5Fg6pT5JGkPdSr7S52MiXFoGTQB9FXZPM96R7bM3hZX7yfiioWwNbAnNNsxNqkRY2WZlZVpJiES9ptqD89Y9f6XXnqp6idt/M///M+w8VtwAR2PzjP9VqaUuURrgQ26srAvv/xyVZ+U6WK+YdO8LbnWxTpEkTBgy7h/rNCrMq0Mue5NWF/mOPIHY99rZBnWAGYz2hvUGUV38axrvfa9bOn9nhnX9WdvRfcjw8xJpNnyyXqUkcVnRRMZ6Ti07ijKj4/cFDHN3p9C6/GajQiRfbiHT+imv/skXTp+b9euMsHvrA31aD88+13PZ8hHm6GPzSThatqG3KKcHHjggcXTTz/d7K2JRKILkTKdSPQXUqYTiT5lyM1uT78ZGNswceLEksnxHr6a5jiRSHQnUqYTif5CynQiMQAv5PZtO5GIUMuxol6ZsXB07HT4w15Dv8h0pEr0zl31nIJV9UpCG58ERoE6EhWulsHxD9Up6mkcCFU9ihkG5h0GVJve4VBNZtjnmH6oOQ7t0X9U4YQKVKdI7lMzHdS6zB/tahlU5ThgavuYvEyfPr2q7IILLjhUhvnyzqk6/sUWW6xq3VC7K+FDu6oex3zOJ1pRMyCfGEVV95jDRM5drBMJhiKHVe/wpo577AnG60NTcp/V24yKu99k2sYemVN5cyA1K/AhQPUa6+TNQbSMD38XmWP4/RKZjHj50d9Zf+5TmfLR6bRu9gl7E1O7yCmSPuq+9Y7dPvmZ1uXHoe35kIx63npnUJ/FXZ/TyKjOvw/7OI+YfPjESjpuyvl2o2RvjCNKLOQdXnX+azms62feKVYdfs1BveWJgXbaaaeGK0wkEt2PlOlEor+QMp1IDJhTpyZ5UNg3EfuGEjkSdQOUZamHbmJaNcxdL/S3FrzTw0jDH0b39aJza6v2Rq2kIoMi07b3YZoixgY2Q0MDeqYqCmMFiwmromZ51M01DbcIQ8N84RymrApOkaS0VmdUmB6YehwQdf4Jnxc5gMFa+3HDOGudERvGWEi/HrHolLGQeoYJEybUTCXN2aQJdqgLpzZNDORDzDFW7aPfi9HcUF7DvzEmzzRq+/hF4fDJXBkeeOCBKlaO+pQN8/1XNs47cUZh1Fp5rvWqTJsGhH2kffQJWsxpFbBPffKaiP3lb5VbtCc+NKG2x3oDPRPY3z4Mnt6PZipiej0jq4wqffFJaKJwrZH2wLPmjDVy4KRPKjdeW8Q1ZcGZS+8AqXXSrg8xqGVmf6vfkVNtPc27dyaNkn3xnNYQrt4JP0qa5DVhet76tYiSOFm7zTynm34htygB9V6e7PC3GKiHH354z2XGTCQGESnTiUR/IWU6keg9NP1CfsEFFxQHH3xw+dK95pprlp/dddddxYUXXlgccsghpW3k8ccfX36D+sY3vlH0GhphpbuJmfb9bXe/6s0XrHE72OxOMdW9knCjH2W61r7yzAeprRWRLSWsomdltB3PaHqn9oipUXaNz6K09LC27GFCJBIGUEPzwebAtBtgYrCzjmypfagv2GDtJ6wa/dCwgwDGS23AqRv2EplUNo4QioxN66YcLNryyy9fFYZR14TERIRaVPYOFixiAbEFh9mOUnj7UHnaLnMKK6jr521RleljnlmbqG82J/a5anQGUabZf1H4OuZfnzs+FKHe52Xf+0eo3HkW3eDt+VlvlXtfZ5SYB58P6tZ+edv16LxhTD75mLYXnVf0jTOEv3VvIktRYh9vcx+x4Mgrc6Pz78/ZZ555Zti5g2bvb8H8eQ16Pdt3b9OtZXzZaL4iDUO9cJu17vM2+JGst+yF3AT6hBNOKLbddtuhz7bccsti0qRJxdlnn11cf/31ZdzZo48+uqsEPZFIxEiZTiT6CynTiUTvoWmbkjvuuKNYZZVVhn1un915553l7+utt96QjWEikehupEwnEv2FlOlEYkAydZ533nnFd77znarP7TNUleaUpMbz/YhGTVvabUbSTSY3qKwbab9VZi312ozMWUbqVOrvj9odyyymrTSV6VWZNjVi5IjjHZAUXvWpZTCjQPWIChbzDL0fswJ1bvKOll7drHVGJhOYjPgsmOqUyXpEIdYIN1hvb5I1ExW6quS9o2uUBZU9wFzp/GGOgnMl5hlq1lEvCymqa65RdvLkyUNlMPVh3tW8g3nDgV8dTun3Y489VvW3OmWixmdOl1122aFrmOZQdxQaDURhC5kLn5VQ5R5n3kGWaZsP76Ro8Nk7I1MhTD7UHAUTLxBlbMThlvCcKq/e+bZeNscomyTygYkTexoZMXiTBjUHISOt328qd5SPMlVGzt8+JCfvDFFZTLy4Fp07mIhEYQsB801ZdTr25jTvl+emd9DXsXkTFx/+Mupb9Jxmjr3jbL350/a86Ys+i2zddD1b/kJudmef+cxniquuuqpYY401ys/uueee8qD76U9/Wv599913F5/97GebrTqRSHQAKdOJRH8hZTqR6D3MVhkBNTlz5szinHPOKR5//PHy72WWWabYY489hr5pdBPsm5gPWdRN6Bbn0G7pTz0Wu13jbYZ9HmnfGmHP67H3ds2+/R933HFleDbYxZGiF2Xa2A4YJ2UlYDq8Q4/+HrEh/r4oGUS9MFyeafVOosrswpBpv2FzvAOXhmjzLKCGJKQ87cNsv/DCC8Pa4KcyZfQXhouQgFEIPeZE76c95hTmTZ0yqZv7NRwt7TCmJ598cli7rDdlVHvA/STv0bqRD+YC+dPQhrW0CAaYZJhu6oNx1/5GISXZSz5Em7KpJAaya4Mq06qNUbnzoRCjBC9RSEBfV+SUyJp4+VEWlOdE5NQZORx6eecaP3WcjC1igf1eYt+r1s4zszpvnuGNnil+TvUanyG3XIs0K7QVJQaiHsatfWRsr781t8r+055n6rVPnI9ewxY5WkbOsH7+dW1xPo2eBV4z4zWr3Gf76ZhjjmlIpptmyPHKtQYSiUR/IGU6kegvpEwnEr2Fhl7IjeFYccUVy28AynZEIH1yojcR2aC3kzWPbLzGsv1GwjZGGC1r78c5lm31q0wbexKxYT6ZQ5Q0KGKzatkL1ku3rAynDykYJYiBmY4YF5/Eo14iLWy4I3tRb2/7nve8Z1g9jzzyyDA20NI8a3+xaY7u98lY/DiVRVt33XWHPqNO5E7ZMNgjmG5YwIUWWmioDPNNGWXB0YR+4AMfKH9q8AFYNJg2WHTtP3NJohdsivUzb6+qcou2ANZ9xowZNROsRNqbyOdh0GTa5icKX+hlQ2WUzyijGiUYWa/ZijRq9VhUn4Jdzw/669nwKBQg7WpoPh/KUPeBHy9jUzt5PiN8YaSZ8ey/zh+f+QQ92m/fH31uch+apSh1vWfvtYy3y/+nXKP/2JlHawOLHZ33nBf1fA+4Fmk/CctKHyPNgNcCeA1Fy23IV1555XJCLHam/Y5qzcM+jxxaEolEdyFlOpHoL6RMJxK9jTkbtUWDLbDfE4MFvg13yr68U+17Fnss268XHYYvv9r+aKOs9INMGxPEPCgRUC8Rg2ffIjbIs1pahna8vbn+7pmXiJXBFlQZXm+TSPvKmMHU8JnW7aPC0FdlDGHWx40bN4ypI5IITF/EWMECRyw+Np0wbvytttiwd+xltcFm3NwP461sJn2MorxwH/1WO1vva0DdyvQRJYY6n3jiiaFrPpICc6LjZ5ysqb0g+7FxH4yfMp06T4Mq07Z2PiJHxF6qDTZ7KtLaeFt9n+hFy2gfaiGK6uT3QqTp8LIYaWa8/GhfGBvjjqITEVFGNVrePtp/rv2NfB/8mRix6IBQ1/qc8tqLSAvBZ7O/VafOH/LB3ETRZfDHof/qM+iZebVvB4wtKuN9PjSqkyel6T9nE/1thqRu6IWcw9v/7qGHSyKR6F6kTCcS/YWU6URiwBIDRbBvb5a9ExumRCLR20iZTiT6CynTiUR3Y85mhPmII44orr322lL9sP/++xfbbLNNMWXKlOLggw8uqf2vfvWrY9vbPkSnzUF6Cape7sR8tbv9es6cdm20zp69LtNROEJFPbOSKDFLvaQtvkwUPoz2UJnieKjqbR/KUMMWomFEhYvqVPvBfahrI4chyqOKVUck30eclrRu+o26Vk0HUJnzGSYk2g5mLSRcwelKx0YfN9xww6FrN9xwQ5XKl/WlHr0fEy+S3Gj/J06cWOW4qnXSF/oYOZDdf//9w9TyrAXjxyyF0JCG5ZZbrmoeNFs1amvu96ExW4Vel2lbX/adqv7Zb35vR462Ch/m0JuT6WesjYbNYw9iAoRTsJpOUJdPYqPtIveYXqhZCGW8WY1+xj7zZ4OOMbrG/T4RWmTip2Y0wCckoi01q/H3aYIrHMW1vJ8j5v/NoB/MW2R6482H+JvQpAZMuJgTHTd7ypu1RCY7vo+R0753+GdPNGNe2vAL+WGHHVacffbZ5QFqaXktOdAuu+xS/PrXvy5OPPHE8u8om1EikehOpEwnEv2FlOlEonfR8Av5JZdcUlx00UXFVlttVUybNq0Mm2TfJB588MGWpvFOJBLtQa/LtBEAMLTqwOcZbmU8YEiiNMswHVyDKdNU0D4FtjKsnqHzabOja8oww77oZ54hhimDuVK/HfoCMeKTgahTEoxRxD4D5kbHT3n6oYl1mFvKMH8Rm4kDmrJp1EWyH+ZD2TXPnur60R6svzp3UQestUUM0/5oX1hHZfapk3XHXlvHz9ziZKdsGkwdrBwsumdjba1GE6ms12Xa9qV30oycmOuNRe9jvbyjs6476x35wHnWlnqi0IJR2DvvhBkl//EOj5HDpXd81DbY28ikyjvl/H3RuYfc6lnKXPr5U6daELHY9Nuzx7pGXHvjrfv1vGCeIkd9HwozmhvvYBslhPLst57jvk4lnekvffTnLmNpJuxhwzbkFod1tdVWK3+3WKcmOKb66gUhTyQSw5EynUj0F1KmE4kBYMjt24B+q7JvHpo2OZFI9BZ6XaZhFGsxVlHYQtgKX4b6fP2ezfHsexQ2EcYK9lNtOr29qM6/Z6hgZbUM46QNtQ+HWfLhCpXFhVnmM11v2sFXgvErww/7y/06Nuy6SRDCOJRh9+mxI6YS+2z8NJRxoi7YzCikIuNQG+6ll166ak5J9KNzi2bC243qPDFuEgKpfwC2q5ENtLcVr8UGjtYvpB9kOkoB722Zo8RArJumJ2dNfZ2qdfEsqvoFsKe8LbieG5ThWpQYp17yGfoU+bwAziBkRPcdnyELut4+bF+UrKxe6nfmwidU0/5T3odd1fb8OR3Zub8ZhB3kDPUMvdblTaW1/94PJtIMMJZG2tB945NE0a72x9apGZlu+IXcKt15552HJss6tueee1ZtXsOll17acOOJRKJzSJlOJPoLKdOJRO+i4RfynXbaqervHXbYYSz6k0gk2oSU6USiv5AynUgMwAu5hU3qNL7zne8UBx10ULHPPvsUJ598cqe7kxjgcJGjbT8Km9dom6Npt59k2tSoaOjUrMKHAVM1pVe9qqmLV9miwlQ1pQ+jpvejqkT1jHmFqodRc2JyoepR32/qU5MPH2KNLHW6p7yaWR03fRg1TDd0DlGHY2ah7dOGD2Om46ZP0fxzH22pU+Paa69d/nzggQeq6lGVL1kIMR1ROSD75QsvvFDlSGmYMWNG1f1oegmRqPOPqYua+tAX9gTX1BHQr19kzoQ5AeNWx1F1cB1Uma7lDM1n3skwkpfIZIF9z15Skw8fEtCbxyiiTJs+e6uCunxoPN0b3nk8cirkPm+ComPzZ4P2zd+nzx2/byMTM2/y4kP71QrT6p+TPnOq3vfPt+ZI191fU3iHyyhDKmZ0Cy20UFX/ddzejKleOF0dmzcj4hoZf2lXTR7bkhioHbj77rvLsIvmNZ5IJHofKdOJRH8hZTqRaAND3kmYY8b2229ffP/73y++9a1v1S1r30b0G0mrEy8MMjqdmKdXMasEP4ZBi1bUCpk2ZgnGUdkRH75K2Zgo7FatEGX+8yh5jzI3PuwYjIuyyd7xS50ywTPPPFPFDukZ5kN9KbzDJXOibCKJiGBjYY6UmWa89E3n4+GHHy5/Tpo0qSrUn97H3MJGKQtOn+irMpXMG+EKIxadurlGf/Q+HzZR+8JPnP1uvfXWoTKUf+qpp6rmSMfmQ8wpU8re4BqhHdXhjv5HTGGvoxUybfPCHEfOzJyTGhqUct5JL3Km9Elk9PcosRDr5J1CtQ3v4B0lC6uXdMyHNowSA/m6ozONazhFa3hPz6Lr/cgXe1yvsZeRc9pQx8uoTuDHHTnTIzdvurnWOqP7aiU70r5Rd7Q3fJjJKMGUfy7r2vgzISpjY4rO6p5myPfaa69iiy22qMrqVgvHHHNMeTDzTzO5JRKJ7kDKdCLRX0iZTiT6nCG/+OKLi/vuu69UhTUCs13bb7/9qr5598JLeadtohOtRzPhjqIU7v2KVsm0MWM+jGDEGOl8Yh/pWTX9nfv5qbbEsC8wtDDO2gfKwAKrnbEP+6Xsr080QV8jxod6lP3mDIFhIuyeMj6w3aQAV/YGthyGjfnQVNSwQrDHGnaQufBzq23AYtNvtYFnLhgjDKoyzTB1hB3UtYGpov9qL0rfuLbssstWzYf2m/Z1bn0IStYqSj7EuNUWl7p8YildW7P1H23Yw354TjMHKtOe6dbobj6UaZSW3dtQ6zx7WVR58XuC+5QFZZ2jEKzsL8p4DYmCzyJ7ae/Povd7X5XIr6VeGz6tvM4N7dFGlLyI+yOG38sy44js/Od5q416/inab8pTV+S7wVkY2d4rE697K/J5icCYvBZA248SKPXsC7kZx5tjyLXXXtvwwGxz6CGXSCS6BynTiUR/IWU6kWgNuvqF/N577y3ZkVVXXXXoM/tmdssttxSnn356+Q3FfwNMJDqN0bJcjdxvbGi9aACDINM2fs9SRHaiyljA2FBe5xAW1duJeibFJx+pFR0CpkUZI59WXtkY2iOxDpFBNNEHdcEM67gXWGCBKjaXfaQ26FHyEgBb7e3yo1Te1KnzB0PF/EU2+fSJz2C6DY8//njV/fRDWS1+v//++4etrddMKHvP2Bg/0Re0b6wb+099ZpgvxgTT9/TTTw+VIYILGgUdWy2GVtl/G699rvbRgybTtSJcRKx5I8m+/H1RYhpYUORfo3wArxmJ7Nt90iv93WtP6jHske+Dn5Oo/SjaCNf8MyWSKeZENXr87qOd6Jnko9xE56Ufh2qfqPOfb/1UmfaJ0HRsfOY1yvU0zJG20Nvnq4bBa1h8Iq8ocpa/v5nndFe/kG+wwQbF1KlTqz7bZZddSnXjAQcckC/jiUSPIWU6kegvpEwnEq1BV7+Q2zfWFVdcseozsx2z2K3+80Qi0f1ImU4k+gsp04nEALyQJxLd7gyL6judcTuLSJWI6YA6XqIeRk2r17xa16tSVVXsk0qoqhKVLapv7Ruq2si5yofdoi11DmRMtKHqYcxYUKHytzrA+X2r40ctjeMkph96P3OEOYiq/rkP0w3UvKpeB4yRJD6qBsdREtlW9TimPlHSIUx16Ic6jI4fP75q3TAdUtU5fVljjTXKn7fffvuwuWHdMDXRvrHOjFtDQjJe5pKyun72Wa86dbYSkXNcvQQt7IEopKk3B/EOeHo/e0r91XwIRjVH8P2N9jnr7M8Nbd+bsUR7wJtX6LnDZ5FTpA/pRz06Rn/O6Z70a8E4oqRN3gE2khdCkkZmQSAKYRutDXUwX945Va9xlmiYVx/mMjI58qZOkS8j80b7owl72HMv5DfddFOnu5BIJFqIlOlEor+QMp1INI+eeyFPdAc6zUwnEsbEwIBETkYkxVAWGoc5H8ZLy8HCwhQpiwzbETmT0hfqjpJ4wCzTX23fOy7Rf1K56zXYnYgNxOGSsIfK0DBG0sprSEPYI1hj5kHHSFpoxrTooosOXYM9glmHcVaG3zu56dyqE6Y6taqGgfWDhVc2imvMyTLLLDOMPec+5kTnhrB7tAerrsmamD/KRAleosQ2sIbe8dezoYPOkNtei+bAp26PNGIRi+lDWFImknuf/Efr8s6gKneeadX++1Tz/K0ssofe75OccU1ZbB+aT/cdYT55TkfzV29uIk2g/9ufidp/P6fMdZTC/l8NhC2M7qP/keOvT1amdft142+dG19G59prD3yIS9Y5cqDv6cRAiUQikUgkEolEvyIZ8i5DpqdvDzwL0+/JePp1DT27w+e6ppGddhQODPbFhz9TxsSHRFQ2BBbG2yKq3SLsVRSiDIbYh2aMUnpji4wttI6TOSEFvLLY1EliH7Wh5vfp06dXsVPKCsG6Y4Ou7QPGBFOuLDzsfZQrAptv2Owo0QlrQz0w/TpP9JEx6me04bUJ2qfnn3++qmw9pjBi49B+aN30kzWGqfdhF20/RnbKgwLbc8ypzrW3T45seaOkPexhPuN+ZZG9fOl54UPaAfZolKRKk0X5cwZZimzYo+Q37A8+Y/9H4T59m3o/8xCFVvQ27Nq+D1eI1izyK/H28toXb4utffQ+Lv+U9j1rriFBfehav9Z6jXrq+exQn97v29LznrPPJ0SK9m2jSIY8kUgkEolEIpHoIPKFPJFIJBKJRCKR6CDSZCUxMGhHBs1E+6AOgWpyhHo5yvyGmpGslvUy3mFyoWYJXgWtjoiU9059qsJErR1ldUP1jFrWh8pTlTFmIKpKxwmUvuGUqGYR3pxGVbjcx09MN3SeuR8nMXWm9VlAGYeq1DHjQOU///zzD11jnKwlcxWZrDDHKpO0iznNUkstNXSN8pjlsFaMUc0FMTnAgVX74p3rdN/5dVdzIG+qwDxEe2uQYfsrUvOzl3z4PgXXkBH9zGc/VZn0jppRpkv6RLu67qwh+0br9qYi/IwcFyOnSPrisw9rGery5iFqcuPPwihsImXULIN2vFNrNEfcF4Ud5JxgHvXcYdxvvHVflHU5mjfv6Bs5T3JfFELWm7p4B+BoTiMnej8OXRu7L8ouWwvJkCcSiUQikUgkEh1EMuSJhPtWyzf0ZMS7G7ZOMN7KIsN0RGELYWo8Y6blYWFw6lQ2yCfIUKaJ8lyLHB49Y6PssWeWYbciFhg2Jkoa5MMvWmZjADPrk9jofbDXjFVDrDFeWB91XPTlYZX1fvpNu9p/2Kg111yz/HnNNdfUZONYU2VDYb0ZmyYd8n2Mwq+hNcGZU9kw9hf7h3ByyqZRF+NVFpe6aIO1UjbQ+mRr4MPYDRp8aEiVBa7p2niH/EjrVStEXRSSsBFnf2VqffKdSFvHPuFaVIZ61GG11jNIzx3P2ut5588J2qoX/k/rZk5qMfV6jfuiPlM+csqlzr+8Jct6zbPL2jf/nI6c0H1Cpkgj5edPmXbP2uu6cb/fN1HYyEaRDHkikUgkEolEItFBJEOeSDgkM94bMEYEVlQZb59MQsPXUR6mRRlemBJC1MEcKQPibYGVjYEp8mnZtW+0AXOlbJCGB1RmW1khz6Zp+7Bg9J/U7coG0l6UaMOHLYvSZNMXGOMoUYe399XxL7HEElUslPaf32lj4YUXDudF2TRdP+zRCSmozDx7gPLY22tIyscff7xq3Dq2SCPgQ9wRZtFrAZQ1435vU8ycDPrZY3Mf2TL78H+RZilimLnGnmJtI61TlLSHfc79UbhOzpSI4fXJqnRP1gqpp33zfgmMMeoH9ahM0W+fql5ZXF+37lufQItryjT7+5QV5jPu94mWtPwcQd1+vfQspA6vkdK58b4eUZhb1p+2orCR9DtKBOd9fnT97fdI81ILyZAnEolEIpFIJBIdRDLkiUSiJ2GMVJQ8x0fCUBtk7KNhryPPfNgsIqiofTrsCbbEkQ05DA1sqLIqPtnQyy+/PHRtscUWq2KIYF6UVRs3blz5c9q0aVVj1N+nTp1aVZ8myPGJPZQNZJ7oN2WVBfb1kHBH543+vvTSS8MiqTCn2Hcre4TtK/XQR412wjXWDTZcGUbq1nWHCWeOfLQbXRPKKKvobWh9giUdC31TzQRaC9h+xhr5GQwybO6Z6yhah4/2oeCaamSQcx8BI0r+Q3tqg14rkoeyoF5rFfk1eI2Q7k3PLEdaJ6/RiiKRRDbN/M48sCf1vPSJcKKoIMwf8673+8Q4PsqI/oxsqpnLv74lb1HkIp+8Rz/z0Ym0fa/1i6Kk0G7kM+Oj0mhbnjWPIv/YXog+r4VkyBOJRCKRSCQSiQ6i7xnyXrbJ82mauxHNxNgcS0RMZzv3QjPfglvdZi/v8ZFAbfci20JlqPzegA2hfLRvYFNg2nR+fRxybRdZ8HbiyurQN9pVFpZrXqaUseF3z+poX2DsqE9ZIc9CRQw55f04FLSl9qo+njB/R1EPIjtrH3PYx4XX3320Fy0fsXH+mv8Z1RlpH2r9nNU1H4Eiikhhv0f3DgJ03M3Obb05G8m6NXu/35MKfy0q61njRuqOooLVe1/wKet9ZBW9pvXQDjLhz7/oWmRfzk/OPT13/WezBTHeI4Y8mgv/t69Tn9OcPT4eeeRXE62DZ+hrxahv5jk9W6XPJd8SPyy++OKd7kYiMWYwlT7mCYOAlOlEvyNlOpEYPJnu+xdy+0ZjmdvMZq/ZmJDtgtls2pcGWzBsznoR/TKOXhmLia7ZoL7//e8PGY9+Rcp0+9ALctBPY0mZzuf0WKMX5GBQZbrvTVZsAnqFPbQN1a2bahDH0QtjiRzu+h0p0+1Ht8tBP40lZbq70e37Z9DG0U8yPTi0WiKRSCQSiUQi0YXIF/JEIpFIJBKJRKKDyBfyLoDF9jz88MPD2Kq9hH4ZR7+NJdF+9Mv+6Zdx9NtYEu1Hv+yffhlHv41lIJw6E4lEIpFIJBKJbkYy5IlEIpFIJBKJRAeRL+SJRCKRSCQSiUQHkS/kiUQikUgkEolEB5Ev5IlEIpFIJBKJRAeRL+RjjCOOOKLMEKr/ll122br3XHLJJWWZueeeu5g0aVLxy1/+sugGjB8/fthY7N9ee+0Vlr/ggguGlbUxtRu33HJLseWWW5aZsqwPl19+edV182s+7LDDikUWWaSYZ555ig033LB48sknZ1nvGWecUc6JjWmttdYq7rrrrjEcRaJbkDKdMp3oL6RMp0x3A/KFvA1YYYUVihdffHHo32233Vaz7B133FFst912xRe/+MXi/vvvL7bZZpvy37Rp04pO4+67764ax7XXXlt+/pnPfKbmPZY9S+955plninbjL3/5SzF58uTyBTrCcccdV5x66qnFWWedVfzmN78p3vnOdxabbLJJ8fe//71mnf/3//7fYr/99itDLt13331l/XbPyy+/PIYjSXQLUqZTphP9hZTplOmOw8IeJsYOhx9+eGXy5MkNl992220rW2yxRdVna621VmWPPfaodBv22WefysSJEytvvvlmeH3KlCmVeeedt9JNsC1/2WWXDf1tfV944YUr3/3ud4c+e/XVVytvf/vbKz/+8Y9r1rPmmmtW9tprr6G/33jjjcr73//+yjHHHDOGvU90A1KmU6YT/YWU6ZTpbkAy5G2AmT+YucSECROK7bffvnj22Wdrlr3zzjtLkwmFMa/2eTfh9ddfL374wx8Wu+66a2kGUgt//vOfi3HjxhWLL754sfXWWxcPP/xw0U2YOXNm8dJLL1XN+bzzzluaoNSacxv7vffeW3XP7LPPXv7dbeuUGBukTKdMJ/oLKdMp051GvpCPMezFzmypr7766uLMM88sXwA/9KEPFa+99lpY3l4OF1pooarP7G/7vJtgdtivvvpqsfPOO9css8wyyxTnn39+ccUVV5Qv72+++WaxzjrrFM8//3zRLWBem5nzV155pXjjjTd6Yp0SrUfKdMp0or+QMp0y3Q2Ys9Md6HdsttlmQ7+vtNJKpeAbY/yTn/yktBPvVZx33nnl2Iz5r4UPfvCD5T9gL+PLLbdccfbZZxff/OY329TTRKK1SJlOmU70F1KmU6a7AcmQtxnzzTdfsfTSSxfTp08Pry+88MLFb3/726rP7G/7vFtgjpnXXXddsdtuuzV131xzzVWsssoqNcfeCTCvzcz5AgssUMwxxxxdv06J9iBlOmU60V9ImU6Z7gTyhbzNMJvqGTNmlCH2IhijfP3111d9ZtFMlGnuNKZMmVK8733vK7bYYoum7jMzj6lTp9Yceyew5JJLli/ROud/+tOfymgrteb8bW97W7HaaqtV3WPmOPZ3N61Toj1ImU6ZTvQXUqZTpjuCTnuV9ju+9rWvVW666abKzJkzK7fffntlww03rCywwAKVl19+uby+4447Vg488MCh8lZmzjnnrBx//PGVRx99tPT+nmuuuSpTp06tdAMsmsgSSyxROeCAA4Zd82M58sgjK9dcc01lxowZlXvvvbfyuc99rjL33HNXHn744bb2+bXXXqvcf//95T/b8ieeeGL5+zPPPFNe/853vlOZb775KldccUXloYceqmy99daVJZdcsvK3v/1tqI6PfexjldNOO23o74svvriMxHLBBRdUHnnkkcruu+9e1vHSSy+1dWyJ9iNlOmU60V9ImU6Z7gbkC/kY47Of/WxlkUUWqbztbW+rLLroouXf06dPH7r+kY98pLLTTjtV3fOTn/yksvTSS5f3rLDCCpVf/OIXlW6BvWDbS+3jjz8+7Jofy7777lu+vNs4Flpoocrmm29eue+++9rc40rlxhtvLPvs/9FXC3146KGHln20l+wNNthg2PjGjRtXfjlS2As647MwiL/+9a/bOq5EZ5AynTKd6C+kTKdMdwNms/86w80nEolEIpFIJBKJtCFPJBKJRCKRSCQ6iHwhTyQSiUQikUgkOoh8IU8kEolEIpFIJDqIfCFPJBKJRCKRSCQ6iHwhTyQSiUQikUgkOoh8IU8kEolEIpFIJDqIfCFPJBKJRCKRSCQ6iHwhTyQSiUQikUgkOoh8Ie8BWO6m3XffvXjPe95TzDbbbMUDDzzQsro/+tGPFvvuu2/R63j88ceLhRdeuHjttdfGvK2rr766WHnllYs333xzzNtK9CdSpmeNlOlELyFletZIma6PfCFvA3beeedim222GdUL4AUXXFD8/Oc/L1588cVixRVXLF/ML7/88lnea+X4N++88xbrrrtuccMNNxT9hoMOOqj493//9+Ld7373iOuYNGlSseeee4bXfvCDHxRvf/vbi1deeaXYdNNNi7nmmqv4z//8z1H0ONHLSJkee6RMJ9qJlOmxR8p0feQLeQ9gxowZxSKLLFKss846JQs855xzNnX/lClTyhf522+/vVhggQWKj3/848VTTz1V9Br++c9/hp8/++yz5ZcVO1BHgy9+8YvFxRdfXPztb38L53CrrbYq589gbZ166qmjai8xuEiZ/l+kTCf6BSnT/4uU6ZEjX8i7ANOmTSs222yz4l3velex0EILFTvuuGPJxPLiZ8yvvXQayz1+/Pjyn+ETn/jE0Gf1MN9885Uv8sasn3nmmeUL57XXXhuWjZh3u98YesPTTz9dlrn00kuL9ddfv3jHO95RTJ48ubjzzjur7vn+979fLL744uV16+eJJ55Y1qO44oorilVXXbWYe+65iwkTJhRHHnlk8a9//auqL9ZfexF+5zvfWRx99NFhn3/yk5+UfVh00UWHPrP+Wnv2or7MMsuU/fj0pz9d/PWvfy0uvPDCcs7mn3/+Yu+99y7eeOON8p4ddtihnJv/+q//qqp/5syZxU033VS+sIMtt9yyuOeee8pDOJHwSJlOmU70F1KmU6bHGvlC3mG8+uqrxcc+9rFilVVWKV/wzDzlt7/9bbHtttuW10855ZTiqKOOKhZbbLGS5b777rvLf8p883cjmGeeecqfr7/++qj6ffDBBxdf//rXS3v2pZdeuthuu+2GXqaNiTfTj3322ae8vtFGGw17mb711luLL3zhC2WZRx55pDj77LPLl2hf7ogjjihf6KdOnVrsuuuuYV+srtVXX33Y5/bybSy2sd42r/ZSbXX98pe/LP+ZGYq1+9Of/rQsb+z31ltvXZx//vlV9Vi/bP433njjoc+WWGKJ8suTtZ1IKFKmU6YT/YWU6ZTptqCSGHPstNNOla233jq89s1vfrOy8cYbV3323HPPVWxpHn/88fLvk046qTJu3LiqMnb9sssum2XbWu4vf/lL5ctf/nJljjnmqDz44IPlZx/5yEcq++yzT91655133sqUKVPK32fOnFmWOffcc4euP/zww+Vnjz76aPn3Zz/72coWW2xRVcf2229f1gM22GCDyre//e2qMj/4wQ8qiyyySFVf9t1331mOcfLkyZWjjjqq6jPrr90/ffr0oc/22GOPyjve8Y7Ka6+9NvTZJptsUn4Orr766spss81Weeqpp8q/33zzzXLuDznkkGHtrrLKKpUjjjhilv1L9B9SplOmE/2FlOmU6U4jGfIO48EHHyxuvPHG0lyFf8suu2x5rVXmEMZeW73m8GjmGOedd16x0korjapOvd/s2w0vv/zykCf1mmuuWVXe/23jNuZfx/2lL32pZPyN2QYR8+1hZiZm9uJhZioTJ04c+tsYbTNVsbb0M/ptMDbf2HDTPhiuv/760lxol112CbUN2tdEgr2dMp0ynegfpEznc7odaM47MNFy/PnPfy7tkY899thh13jRHS1OOumkYsMNNyyjrCy44IJ1y5rd9v+S0/WdNCzKiN5jaCYMoI3bbMY/+clPDrumL9dmOz4rmKnJH/7wh7p9pJ/RZ9rv2WefvbTbNztzM5exF3OzlTcbd4/f//73s5zPxOAhZTplOtFfSJlOmW4H8oW8wzCnRmOtjbltJnqKvVjijDgrmEPnUkst1VBZe8E0lho8+eSTTbPA5kTp7dr93zZuY9Ib7Vc9mP292aG3CsaGf+tb3yodVy+77LLi3HPPHVbm73//e6nBsLYTCUXKdMp0or+QMp0y3Q7kC3mb8Mc//nFYQp/3vve9xV577VVGJDGzkv33379M/jN9+vTSEdFeBOeYY46wPnuBN3MKiytu8bEtYkgrYA6mp59+evHBD36wfOE/4IADhrHKs4JFhfnwhz9cRlYx9t/inl911VVDTLrhsMMOK8MvmnOkRT8xZtrUgubJbi/DzWCTTTYpdtttt7K/tearGSy55JLlPFgyJpvbiMX/9a9/XV6zeUoMJlKmU6YT/YWU6ZTpTiJtyNsEi/BhbKr+M5ON97///WVUEnuZtCgelpzGMmdayD57Sa2FE044oQxdaKEFW8nSWr1W54c+9KHi85//fBlJxWyxm4F9STjrrLPKF3ILR2gRTr761a9WmaLYS7SFJPzVr35VrLHGGsXaa69dmtaMGzeu6T5byEjTLlx33XVFq2AhDs0MxuYgsk//8Y9/XGy//fZNz02if5AynTKd6C+kTKdMdxKzmWdnR3uQGAiYw+Zjjz02ZmECzzjjjOLKK68srrnmmmKsYTHizSzHwlQam55IDCJSphOJ/kLKdGeRJiuJMcHxxx9fRiwxp0wzVzEnye9973tjNtt77LFHGSv2tddeK6PJjCUsOZKNJV/GE4OElOlEor+QMt1dSIY8MSawxEam/rMXZItQYnblliwokUj0JlKmE4n+Qsp0dyFfyBOJRCKRSCQSiQ4inToTiUQikUgkEokOIl/IE4lEIpFIJBKJDiJfyBOJRCKRSCQSiQ4iX8gTiUQikUgkEokOIl/IE4lEIpFIJBKJDiJfyBOJRCKRSCQSiQ4iX8gTiUQikUgkEokOIl/IE4lEIpFIJBKJonP4f/jdirBoWskqAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "noise.set_rng_seed(11)\n", "\n", "# Turn off latching\n", "no_latching = noise.NoiseGenerator(noise_params).calc_noisy_map(\n", " clean_data, latching=False)\n", "\n", "# Use white noise only\n", "white_noise_only = noise.NoiseGenerator(noise_params).calc_noisy_map(\n", " clean_data, noise_default=False, white_noise=True)\n", "\n", "# Plot the results\n", "fig, ax = plt.subplots(1, 3, figsize=(7.5,2.7))\n", "tutorial_helper.plot_csd_data(fig, ax[0], clean_data, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[0].set_title(\"Clean CSD\")\n", "tutorial_helper.plot_csd_data(fig, ax[1], no_latching, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[1].set_title(\"No latching\")\n", "tutorial_helper.plot_csd_data(fig, ax[2], white_noise_only, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[2].set_title(\"White noise only\")\n", "fig.tight_layout()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7b5c4922", "metadata": {}, "source": [ "Latching is implemented in two different ways:\n", "\n", "* The simple latching method is performed by shifting each row\n", "by a random number of pixels.\n", "\n", "* The excited-state latching method involves replacing pixels with excited state\n", "data for several pixels after each transition.\n", "\n", "The excited-state latching method is more realistic, but requires additional data\n", "about the excited states and transitions." ] }, { "cell_type": "code", "execution_count": 7, "id": "b9799430", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "noise.set_rng_seed(12)\n", "\n", "# Increase the latching amount for demonstration purposes\n", "noise_params_2 = noise_params.copy()\n", "noise_params_2.latching_pixels = 1.7\n", "\n", "# Simple latching is used if no additional data is provided\n", "simple_latching = noise.NoiseGenerator(noise_params_2).calc_noisy_map(\n", " clean_data, noise_default=False, latching=True)\n", "\n", "# Excited-state latching requires excited state data, charge states,\n", "# and whether dots are combined\n", "excited_data = csd.excited_sensor[:,:,0]\n", "dot_charges = csd.dot_charges\n", "are_dots_combined = csd.are_dots_combined\n", "\n", "excited_latching = noise.NoiseGenerator(noise_params_2).calc_noisy_map(\n", " clean_data, latching_data=(excited_data, dot_charges, are_dots_combined),\n", " noise_default=False, latching=True)\n", "\n", "# Plot the results\n", "fig, ax = plt.subplots(1, 3, figsize=(7.5,2.7))\n", "tutorial_helper.plot_csd_data(fig, ax[0], clean_data, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[0].set_title(\"Clean CSD\")\n", "tutorial_helper.plot_csd_data(fig, ax[1], simple_latching, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[1].set_title(\"Simple latching\")\n", "tutorial_helper.plot_csd_data(fig, ax[2], excited_latching, x_y_vals=(csd.V_x, csd.V_y))\n", "ax[2].set_title(\"Excited-state latching\")\n", "fig.tight_layout()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "456b461d", "metadata": {}, "source": [ "Note for simple latching, the latching pattern repeats for each transition,\n", "whereas for excited-state latching, the latching pattern is unique for each transition." ] } ], "metadata": { "kernelspec": { "display_name": "qdflow_venv", "language": "python", "name": "qdflow_venv" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 5 }