{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# The Advanced Harmonic Oscillator\n", "\n", "## Description\n", "\n", "This exercise is about more advanced fitting of data. The idea is to begin with the simplest possible function that even remotely does the job, which is then expanded to accommodate all the features present in the data fitted. The data is from three versions of a damped harmonic oscillator, consisting of a weight hanging from a spring, but with different damping:\n", "- No additional damping.\n", "- More damping from a round piece of cardboard, which increases the drag.\n", "- Damping from friction of the weight against metal.\n", "\n", "\n", "## Your task\n", "\n", "Take a look at the various dataset, and try to fit them with an appropriate function, by taking into account the deviations you can see from a perfect oscillator. Play around with the error estimates and the initial parameters of each fit. Answer / Discuss the questions written at the bottom of this notebook.\n", "\n", "_Note that the initial inputs of this notebook may not be the proper ones to begin with!!!_\n", "\n", "\n", "## Authors: \n", "- Troels Petersen ([email](mailto:petersen@nbi.dk))\n", "- Étienne Bourbeau (notebook conversion) ([email](mailto:etienne.bourbeau@icecube.wisc.edu))\n", "\n", "## Date\n", "10th January 2019" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n", "from scipy import stats\n", "from iminuit import Minuit\n", "import sys\n", "sys.path.append('../../External_Functions/')\n", "from ExternalFunctions import Chi2Regression,nice_string_output\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# function to draw parameters from a fit on the figure in one line\n", "def draw_fit_parameters(minuit_obj, axis, x, y, title=None, color='k', chi2=None, ndof=None, prob=None) :\n", " names = []\n", " values = []\n", " if title is not None :\n", " names += [title]\n", " values += ['']\n", " if chi2 is not None and ndof is not None and prob is not None :\n", " names += ['Chi2 / ndof','Prob']\n", " values += [\"{:.3f} / {:d}\".format(chi2, ndof), \"{:.3f}\".format(prob)]\n", " names += minuit_obj.values.keys()\n", " values += [\"{:.3f} +/- {:.3f}\".format(minuit_obj.values[val], minuit_obj.errors[val]) for val in minuit_obj.values.keys()]\n", " d ={}\n", " for n,v in zip(names,values):\n", " d[n] = v\n", " axis.text(x, y, nice_string_output(d), family='monospace', transform=axis.transAxes, fontsize=10, verticalalignment='top', color=color)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "SavePlots = False\n", "verbose = True\n", "Nverbose = 10" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "## 1st Dataset - no additional damping" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Time = 0.000 Dist = -0.683 \n", " Time = 0.010 Dist = -0.694 \n", " Time = 0.020 Dist = -0.702 \n", " Time = 0.030 Dist = -0.699 \n", " Time = 0.040 Dist = -0.702 \n", " Time = 0.050 Dist = -0.691 \n", " Time = 0.060 Dist = -0.684 \n", " Time = 0.070 Dist = -0.669 \n", " Time = 0.080 Dist = -0.644 \n", " Time = 0.090 Dist = -0.609 \n", " Number of entries read: 3806 Time of last read: 38.050\n" ] }, { "data": { "text/html": [ "
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FCN = 37330118.41895736TOTAL NCALL = 54NCALLS = 54
EDM = 1.5963922126280567e-17GOAL EDM = 1e-05\n", " UP = 1.0
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FCN = 37330118.41895736TOTAL NCALL = 80NCALLS = 80
EDM = 1.5963922181047106e-17GOAL EDM = 1e-05\n", " UP = 1.0
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-0.579\n", " Large residual in fit1: t = 0.070 d = -0.669 dd1 = -0.564\n", " Large residual in fit2: t = 0.070 d = -0.669 dd2 = -0.564\n", " Large residual in fit1: t = 0.080 d = -0.644 dd1 = -0.539\n", " Large residual in fit2: t = 0.080 d = -0.644 dd2 = -0.539\n", " Large residual in fit1: t = 0.090 d = -0.609 dd1 = -0.504\n", " Large residual in fit2: t = 0.090 d = -0.609 dd2 = -0.504\n", " Large residual in fit1: t = 0.100 d = -0.578 dd1 = -0.473\n", " Large residual in fit2: t = 0.100 d = -0.578 dd2 = -0.473\n", " Large residual in fit1: t = 0.110 d = -0.541 dd1 = -0.436\n", " Large residual in fit2: t = 0.110 d = -0.541 dd2 = -0.436\n", " Large residual in fit1: t = 0.120 d = -0.502 dd1 = -0.397\n", " Large residual in fit2: t = 0.120 d = -0.502 dd2 = -0.397\n", " Large residual in fit1: t = 0.130 d = -0.457 dd1 = -0.352\n", " Large residual in fit2: t = 0.130 d = -0.457 dd2 = -0.352\n", " Large residual in fit1: t = 0.140 d = -0.396 dd1 = -0.291\n", " Large residual in fit2: t = 0.140 d = -0.396 dd2 = -0.291\n", " Large residual in fit1: t = 0.150 d = -0.357 dd1 = -0.252\n", " Large residual in fit2: t = 0.150 d = -0.357 dd2 = -0.252\n", " Large residual in fit1: t = 0.160 d = -0.302 dd1 = -0.197\n", " Large residual in fit2: t = 0.160 d = -0.302 dd2 = -0.197\n", " Large residual in fit1: t = 0.170 d = -0.246 dd1 = -0.141\n", " Large residual in fit2: t = 0.170 d = -0.246 dd2 = -0.141\n", " Large residual in fit1: t = 0.180 d = -0.195 dd1 = -0.090\n", " Large residual in fit2: t = 0.180 d = -0.195 dd2 = -0.090\n", " Large residual in fit1: t = 0.190 d = -0.136 dd1 = -0.031\n", " Large residual in fit2: t = 0.190 d = -0.136 dd2 = -0.031\n" ] }, { "data": { "image/png": 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LcPzx2nr/5jd62ruQ667Ty1p//auWs2fPwtN73X9T3NZzrvJ07aqn7Hv2BL7yFb0csGqVt/yJAmCTSeQPm1j7m1hA7x4AgCFD9LEaNy9kJHsw+E6CQYP0npZXX9W/N27U1yZ6JQJccomeJhs50t08M2YAF17Ysofg1YknAq+9pr2YN98E1q3T8YMH6zJ9+qk+tLZwod6LQ5Rpw4b09r5pk25DRx2V/v9DD7W8Hy7f9PnGDx2q93xu2QK8/76eUvazHXbrptvw3r16GnrJEr2UlTJpkg4pv/oV8O67GphOmAD8/Oe6rxWSKv+8eXoZoNh9bl72X6/1nK88Q4boPXLbtulDsm+8odEQUUzYZBK5xyY2LQlN7LZt6SvdDQ2abrGTBGSXA00XgFz63//Vt7Fs26Z7+VNPtXyDTKaGBuA730nvoa++Cvz613oV6tFH9cGRu+/WaZ9+Wk+b5SKiD549/3ywsldUAJdeqj2H/v3TR8vKSn1DxUkn6d91dcARRwTLi0rPe+8Bl1+uv+/bB9x8c/q0eX293oN53HHFp/+//8ufztSp+vAUANx2G9Cm+bzk+PHAY48BH36oD5ndeac+WJlv/Nln6z1jbdoA48bp6e0ULw+55Uv/kku0N9G2LfDgg4UvkXndf73WM5C7PB076r1wZ56p99SNGaOXHohixCaTyB02sclqYlet0vHt2+snx+69FzjkEPfLTuY5UujhqBJTW1srixYtMl2M5HjmGd3bH3rIdEmIyCvuv0Sx4i5HVD64v1Mmx3EWi0itq2kZfBMRERERERF55yX45jPfRERERERERBFj8J0UBxygb5EZMEDfyOD3uwIdOoRbLiJKnlmzgL599Tssc+b4n97reKKYsMkkIlPYxFIhvO08KTp00Ne3igA/+IG+ceXaa/2nQ0TlqbFR3+qyYIG+NvaMM4B33km/Acft9E1N3sbnS58oAmwyicgENrHlibedlzLHAUaM0NcfAsBLLwFnnaUfGayqAn7yEx1/++36d1WVfgshRURfAVtVBVxzTezFJyLD6uv1cmDXrvp9kh49gOXLvU/vdTyRAWwyiShObGKpGH5qLGk+/1y/dfLNb6bHzZ8P/OMf2jv4+GP9bsrttwPLlun01dU6/RFHALt3a6/jD38ATjsNeOUV4NRTjS0OEcVs0yb9vslddwGdOunHUzdu1Ht0vUy/a5e38fnSJ4oQm0wiihObWCqGV76T4rPPdM8aMgTo3Vs/AppSU6O9CAA49FBg6VLtHXToABx2GDB0aPq02AEH6Gn/Nm30Z1JvwyeiYK64Ajj//ODTex1PFAM2mURkEptYyodXvpPi4IP1tHwuHTv6T9dx/M9LRMnTvbueJk9JnXb3Ov2uXd7GE8WITSYRmcAmlorhle9SNHgw8OqrwKef6j11CxcCAwfq//btA154Adi/H3j+eb0sQETlY+hQYOVKYMsW4P33gfXr08cHAJg0SYdi03sdT2QpNplEFBY2sVQMr3yXospK4Kqr9PWuAFBXpw+vAcCXvgT86U/62tevfhU45RRjxSQiA9q1A6ZOTe/7t93W8jWpmafUC03vdTyRpdhkElFY2MRSMfzUGBEREREREZEP/NQYERERERERkUUYfBMRERERERFFjME3ERERERERUcQYfCfdrFlA377AsccCc+aYLg1RMnndj/JNf8AB+nHhQYOAq6/WcRs2AMOHAwMGACeeCDz3XPDy7t+v6W3d6m/+sJY33/if/hTo2jX9MWUiS7DJJIofm1h/07OJLU184VqSNTYCxx0HLFgA7N0LnHEG8M47fO0hkRde96NC03fooB/hzLR5s36Is7oaWLcOGDZMewtBPPUU8OijwMyZ3ucNa3mbmvKn89pr+krWiy8GVqwIsqREoWGTSRQ/NrFsYssBX7hWahoagD59gPPPB/r3B26+WcfX1+upua5dgZ49gR49gOXLjRaVKHG87kdep+/aVXsFAFBRoS3t3r3FyzVzJjB5cu7/TZ+u30byI6zlLZTOsGFA587+ykcUEJtMInuwiWUTSy3xO99JsWaN3nNSWQkMHAhccIGe6uveHbjrLqBTJ6BbN/2A4KBBpktLlBxe96NC0+/Zo/e9HXwwcNNNwGmntZx37lz9f/v2/su7apWe+q+p8Td/WMu7axePP2QtNplEdmATyyaWWmLwnRQVFUC/fvr78OHAkiXp/11xhf587LH4y0VUKrzuR7mmX79eW8iFC4HvflfvETv4YP3fpk3A9dcDs2cHK+cddwATJgRLAwhnef2kQxQDNplEdmET6296Hq9KD287T7Lu3fU0WErq9BkR5VZfn35by2uv6Tiv+1Gh6bt1059DhgBHHqn3vwJ6un70aODWW4HevQuX8bbbtHw33KCnvAcNAn72M/3fjh3As89qWsWWy0/5vUzP4w8lDDdZomixiWUTS8XxyndSrFsHrF6tp/Pnzwfq6vTIs3IlsGWLPuCyfr3eX0dEuZ10ErBsWctxQ4cW3o8mTdKfN91UePpt2/QU/MEHa49gwwZ9UEsEuOQSYMwYYOTI4mW89lodZs7UdDIfSpsxA7jwQqBt2+LLlU9Yy9vUxOMPWYtNJlH82MSyiaXiGHwnRa9ewMSJ2psYN04fZAOAqVOBU07R32+7ja9tJfKqXbvC+1HmqedC069apT2A9u31eyj33gsccgjw6qv62tS33gLuvlvnefppjQS8EAHuuQd4/nl/y1ms/Clul7dQOuPH6z1yH34IHH00cOedwLnnBis3kQdsMonswCaWTSy1xE+NJUFDAzBqFL8nQFTOnnkGePBB4KGHTJeEyGpsMonIKzaxFISXT43xyjcRURKcc44OREREFCo2sRQX3nCVBJWVPIVPRETkAptMIiKyFYNvIiIiIiIioogx+E66n/4U6NoVqKoyXRKi5Jo1C+jbFzj2WGDOHP/TH3BA+nskV1+t4zZs0A8NDxgAnHgi8Nxzwcu7f7+mt3Wrv/nDWt5843lcIktx0ySKH5tYf9OziS1NfOFa0r32mr4S8eKLeZ8dkR+NjcBxxwELFuj3PM44A3jnnfyvQS40fYcOwK5dLaffvFk/0Fldrd8/GjZMewtBPPWUvt515kzv84a1vE1N+dPhcYksxU2TKF5sYtnElgMvL1zjle8kaGgA+vQBzj8f6N8fuPnm9P+GDQM6dzZWNKLEq6/XU9xdu+pHQ3v0AJYvD2/6rl21VwDoR4cbG7UlLWbmzJYfIM00fTpw1VXF08glrOUtlA6PS2QQm0wie7CJZRNLLfFt50mxZo3ec1JZCQwcCFxwgR5liCiYTZuA7t2Bu+4COnUCunXTD3EOGuR9+j179L63gw8GbroJOO20lvPOnav/b9/ef3lXrdJT/zU1/uYPa3l37fKWDlGM2GQS2YFNLJtYaonBd1JUVAD9+unvw4cDS5awJ0EUpiuu0J+PPeZ/+vXrtYVcuBD47nf1HrGDD9b/bdoEXH89MHt2sHLecQcwYUKwNIBwltdPOkQxYJNJZBc2sf6mZxNbeozedu44zn2O42xxHCfnEwuOut1xnHcdx1nuOM6JGf8b6zjOO83D2PhKTUSJVV+fflvLa6/puO7d9XRySuo0dD6Fpu/WTX8OGQIceaTe/wro6frRo4FbbwV69y5cxttu0/LdcIOe8h40CPjZz/R/O3YAzz6raRVbLj/l9zK913SIiKiksYllE0vFmb7yPRPAHQAeyPP/cwD0bR5OAvB7ACc5jtMJQB2AWgACYLHjOE+KyPbIS2zKunXA6tV66n7+fKCuznSJiJLnpJOAZctajhs6FFi5EtiyRR8UW79e71NNmTRJf950U+Hpt23TU/AHH6w9gg0b9EEtEeCSS4AxY4CRI4uX8dprdZg5U9PJfChtxgzgwguBtm2LL1c+YS1vU1PhdIgMYpNJFD82sWxiqTijwbeIvOw4TmWBSb4N4AHRV7IvcBznUMdxugM4HcBzIrINABzHeQ7ASAB/irbEBvXqBUycqL2JceP0QTYAGD9e70X58EPg6KOBO+8Ezj3XaFGJEqVdO2DqVOCUU/Tv225r+VrSzFPPhaZftUp7AO3b6/dQ7r0XOOQQ4NVX9bWpb70F3H23zvP003ra3gsR4J57gOef97ecxcqf4nZ5C6XD4xIZxiaTyA5sYtnEUkvGPzXWHHw/JSKtvlbnOM5TAKaKyKvNf78A4BfQ4PsgEflV8/j/BPCZiNyaI43LAVwOAD179qxZt25dNAsSpYYGYNQofk+AqJw98wzw4IPAQw+ZLgmR1dhkEpFXbGIpCH5qLIOI3C0itSJS26VLF9PFISLy55xz2CsgIiKKAJtYiovtwfcGAD0y/j66eVy+8aWpspKn8ImIiFxgk0lERLayPfh+EsBFzW89PxnAJyKyEcBcAF93HOcwx3EOA/D15nHlZcMG/YbKgAH6YcPnnjNdIqJkmjUL6NsXOPZY/Tiw3+m9jvdr/37d77du9Te/1/LccgtQVQX07w9MmZIeX1+vb4Dp1w84//yW8+zcqQ/d3drqaSAiI9hkEpnBJtbf9HEtL8VMRIwN0BekbQTwOYD1AC4FcAWAK5r/7wD4HYB/AngDQG3GvP8O4N3m4RI3+dXU1EhJ2bRJZNky/b2hQeTII82WhyiJ9u4VqazU/WndOpFjjhHZt8/79F7HBzFnjsjYsf7m9Vqe998X6d1bpLFR5+3VS2TNGp2nb1+RV17R6bZsaTnfL34hMmqUyC23+CsnUcjYZBLFj02s/ctLwQFYJC7jX9NvO/9Bkf8LgPF5/ncfgPuiKJd1GhqAr31NT9WvWAGMHQv84hdA1646APo9lcZG/R5B+/ZGi0uUKPX1eoo7tS/16AEsX64f9PQy/c6d3sbnSz8l13dQUqZPB379a48LWqT8hcrT1KTHFhF9BWvHjsDixUCXLnopEdDfU1av1u+j1NT4KyNRAGwyiezBJtaO5SV7mP7ON7m1Zo3eW1JZqbd5XnCB9h5S5s7VngZ7EUTebNoEdO8O3HUX0KkT0K2bfgskX0uWb/pdu7yN99tSrlqlafoNbL0u79FHA9dcox9U3bdPbyPv1Al48UUNwkeOBDZvBi67DPjxj3WeiROBadP0o6lEBrDJJLIDm1i7l5fix+A7KSoq9LlKQK80LVmS7kls2gRcfz0we7a58hEl3RVX6M/HHgs2vdfxXt1xBzBhQrA0vJRn+3b9BsvatcDnn+tHR0eNAvbsAebPB954Azj0UKC2VgPxlSv1QbTMSIcoZmwyiezCJtbf9FEvL8WPwXfS7dkDjB6tV6N69zZdGqLk6d5dTxunpE5De51+1y5v4/O57Tbg/vuBbdv0vtgnngDOOktferZjB/DsszpNpvp64Ec/0t/vvBMYNiy85X3hBb3q3bGj/j14MLB0qd7z1r+//g/QywSrVmlZ/vIXjWw+/BBo00bTv/DC/HkQxYRNJlG82MSaXV6yD4PvpFi3Tp+jrKjQq011dfr85SWXAGPG6BUnIvJu6FC9Wrtliz4Aun693qeaMmmS/rzppsLTNzV5G5/PtdfqkOuBtBkzNIht27blPCedBCxbFs3ydusGLFyo0+7fr5cQ6+r0Tebvvac9mA4d9Ar4MccA3/gG8Ktf6byTJ+v/GHhTzNhkEtmBTazZ5SX7MPhOil699DnK1auBceP0QbZXXwUefRR46y3g7rt1uqef1k4xEbnTrh0wdareTg3oKe82GV9hzDzFXGh6r+O9EgHuuQd4/nnv87opf0r28g4fDpx9NlBdrdONG5e+n3faNODMM/V29DFjgOOPD1Y2opCwySSyA5tYO5eXzHH0heLloba2VhYtWmS6GN41NOgzlitWmC4JEZnyzDPAgw8CDz1kuiREVmOTSUResYmlIBzHWSwitW6m5ZVvIqIkOOccHYiIiChUbGIpLrxRIQkqK3kKn4iIyAU2mUREZCsG30REREREREQRY/CdZB99pN/Wra4GBg3S7yUQkXezZgF9++r3qefM8T+91/F+7d8PDBgAbN3qfV6/x42dO/XNVLfemh53yy1AVZV+cmzKlOLjiQxik0lkRjk1sX7Kk6/JrK/XN5n36wecf37LeXI1yZQMfOFakn3+uX5noEMH/Z4V2fb4AAAgAElEQVTuCScAGzbwtYdEXjQ2AscdByxYoPvTGWcA77yTfz/KN31Tk7fxQfbTp57S1zbPnOl9Xr/HjYkT9fsmI0YAP/2pft/k9NP11dEi+qbzF17Qb7TkGt+rl48FJQoPm0yi+JVbE+t1efM1pRUV+vt99+lHR7ZuBbp0Sc+X3SSTWV5euMYmJwkaGoA+ffS0V//+wM036/i2bbUXAQCffKJ7eVOTsWISJVJ9vZ7i7toV6NkT6NEDWL7c+/Rexxczc2bLD5Bmmj4duOoqP0vr77ixerV+VLSmpuX4piadf+9e/f5Jx46FxxPFgE0mkT3KrYn1U55cTebixRpsDx+u02QG3vmaZEoGvu08Kdas0XtXKiv1HpQLLtDTYjt3AsOG6f//5390ryUi9zZtArp3B+66C+jUCejWTT/EOWiQt+l37fI2Pl/6xaxapWkGaXW9HjcmTtRves+YkR539NHANddo72LfPr33rVMnHXKNJ4oRm0wiO5RbE+t1efM1pS++qEH4yJHA5s3AZZcBP/6xzpOrSabkYPCdFBUV+tAHoKfBlizRcV/+MvDGG3q/yuWXA9/7np7eJyJvrrhCfz72WLDpvY736o47gAkTgqXh5bgxZ44+uFZR0XL89u36YdS1a/V+3lNO0Y8rH3RQ7vHduwcrM5EHbDKJ7FJOTayX8uRrSvfsAebP1+PVoYfq+ypGjtRbzXM1yZQcDL5LRb9+2oN4/XXdQ4nIne7d9bR0Suq0tdfpd+3yNj6f224D7r8f2LZNHx574gngrLP0jSw7dgDPPqvTZKqvB370I/39zjv10p4bbo4b9fXAX/4CzJ6tD8q2aaPlb99eT9WnbikfPBhYuhTYvTv3eAbfZBE2mUTxKLcm1uvyvvBC7iaza1d9bKZnTx1fU6NX5fM1yRdemD8PsoyIlM1QU1MjibR2rYjjiKxaJfLZZyJ9++q49etFPvxQp9m4UaRrV5EPPjBZUqLk2btXpLJSZPNmkffeE+ndW2TfvvT/J07Uodj0XscXM2OGSF1dy3HTpolMnhxseYsdN7KXN1Ndncgtt+jvr7wiMnCgyJ49Irt363HpzTfzjyeKCZtMInuUWxPrdXnzNZkffyxy5JEiH32kaQ4YIPLWWy3zymySySwAi8RlPMor30nRq5c+5LF6NTBunD7I9n//p/fNAfqgyM038+oSkVft2gFTp+q9XoCe8s58LWnmKexC03sd75UIcM89wPPPe58303vvFT5uZC9vPsOHA2efrd9tatNGj0up+3zzjSeKCZtMIjuUWxPrdXkLNaXTpgFnnqm3o48Zo28/p+Tjp8aSoKFBHwBZscJ0SYjIlGeeAR58EHjoIdMlIbIam0wi8opNLAXh5VNjvPJNRJQE55yjAxEREYWKTSzFhd/5ToLKSp7CJyIicoFNJhER2YrBNxEREZWNnTuBI4/U7+kSUfRmzQL69tVPZM2Z4396r+P92r8fGDAA2LrV+7wffaRfUKiu1m97P/GEu/lyHZduuQWoqtK3nk+ZUnw8JQOf+SYiIqKyMXGifit3xAjgpz81XRqi0tbYCBx3HLBgAbB3L3DGGcA77+R/KVq+6ZuavI3389K1lKeeAh59FJg50/u8n3+u5ejQQT8FdsIJwIYNxcuTfVxavx44/XTgrbf0ZXDHH6+fJWvbNvf4Xr18LCiFxssz37zyTURERCWjoQHo0wc4/3y9MnTzzen/rV4NbNmi38wloujV1+tV5K5d9ZvVPXoAy5d7n97r+GJmzgQmT879v+nTgauu8rO0Ghx36KC/f/KJBuJNTYXnyXdcamrS+ffu1beop74Fnm88JQNfuEZEREQlZc0avf20shIYOBC44AKgokKvLk2bBsyYYbqEROVh0yb9pN9ddwGdOgHduunntgYN8jb9rl3exudLv5hVqzTNICfodu4Ehg3T49D//I8GyIXkOi4dfTRwzTV6QmHfPr0dvVMnHXKNp+Rg8E1EREQlpaIi/a3c4cOBJUv0atixx+r/iCheV1yhPx97LNj0Xsd7dccdwIQJwdL48peBN97QW8Mvvxz43vf0inguc+bkPi5t366fP1u7Vm9lP+UU/YTiQQflHt+9e7AyU3wYfBMREVHJq68H/vIXYPZsfRazTRvtsF54oemSEZWu7t31SnRK6sq21+l37fI2Pp/bbgPuvx/Ytk2fL3/iCeCss/QlZjt2AM8+q9Nkqq8HfvQj/f3OO/Wqthv9+mnQ/frr+hK2XPIdl9q316vbqVvKBw8Gli4Fdu/OPZ7Bd3LwhWtERERUMhoagGOO0atOFRV62/mzz+ot6CmTJ+tzmXzhGlG0Ui9Qq69PvxDt7bfTLyCbNEl/3nRT4elTL1ZzO77YC85mztRjReZz37/9LfDxx0Bdnf/l3bBBr04ffrieCBg0qGVwnL28mTKPS6++CowfD/zjH/r29epqDdA/+ij3+NSdPmSGlxeu8co3ERERlZRevfQ5ytWrgXHjWgbeRBSfdu2AqVP19mhArypnBsaZV60LTe91vFciwD33AM8/733eTO+9p7eaA/pM9s03t7wqnb28+QwfDpx9tgbXbdrocSwVYOcbT8nAK99ERERUMhoa9BnIFStMl4SIkuKZZ4AHHwQeesh0SSiJeOWbiIiIiIjIhXPO0YEoavzONxEREZWMykpe9SYiIjsx+CYiIiIiIiKKGINvIiIiIiIioogx+CYiIiIiIiKKGINvIiIiIiIioogx+CYiIiIiIiKKGINvIiIiIiIioogx+CYiIiIiIiKKGINvIiIiIiIioogx+CYiIiIiIiKKGINvIiIiIiIioogZDb4dxxnpOM5qx3HedRxnYo7/3+Y4zrLm4W3HcT7O+N++jP89GW/JiYiIiIiIiNw70FTGjuMcAOB3AM4CsB7AQsdxnhSRN1PTiMi1GdNfBWBwRhKficiguMpLRERERERE5JfJK99DAbwrImtEpBHAwwC+XWD6HwD4UywlIyIiIiIiIgqRyeD7KADvZ/y9vnlcK47jVADoBeDvGaMPchxnkeM4CxzH+U6+TBzHubx5ukVbt24No9xEREREREREniTlhWsXAHhURPZljKsQkVoAYwBMcxynd64ZReRuEakVkdouXbrEUVYiIiIiIiKiFkwG3xsA9Mj4++jmcblcgKxbzkVkQ/PPNQBeQsvnwYmIiIiIiIisYTL4Xgigr+M4vRzHaQcNsFu9tdxxnOMBHAbg/zLGHeY4Tvvm3zsDOAXAm9nzEhEREREREdnA2NvORaTJcZwJAOYCOADAfSKy0nGcGwEsEpFUIH4BgIdFRDJm7wfgD47j7IeeQJia+ZZ0IiIiIiIiIps4LWPa0lZbWyuLFi0yXQwiIiIiIiIqAY7jLG5+F1lRSXnhGhEREREREVFiMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIMfgmIiIiIiIiihiDbyIiIiIiIqKIGQ2+HccZ6TjOasdx3nUcZ2KO/1/sOM5Wx3GWNQ/jMv431nGcd5qHsfGWnIiIiIiIiMi9A01l7DjOAQB+B+AsAOsBLHQc50kReTNr0kdEZELWvJ0A1AGoBSAAFjfPuz2GohMRERERERF5YvLK91AA74rIGhFpBPAwgG+7nPdsAM+JyLbmgPs5ACMjKicRERERERFRICaD76MAvJ/x9/rmcdm+5zjOcsdxHnUcp4fHeeE4zuWO4yxyHGfR1q1bwyg3ERERERERkSe2v3BtDoBKERkIvbp9v9cERORuEakVkdouXbqEXkAiIiIiIiKiYkwG3xsA9Mj4++jmcV8QkY9EZG/zn/cCqHE7r1uTJ0+G4zithsmTJ/tJjoiIiIiIiKgVR0TMZOw4BwJ4G8BXoYHzQgBjRGRlxjTdRWRj8+/fBfALETm5+YVriwGc2DzpEgA1IrKtUJ61tbWyaNGiVuNPP/10zJs3r9X4ESNG4KWXXiq4HJMnT8aUKVNy/q+urs51EJ9Kx8s8RERERESZOnfujMrKStPFICpJDQ0N+PDDD1uMcxxnsYjUupnf2NvORaTJcZwJAOYCOADAfSKy0nGcGwEsEpEnAVztOM65AJoAbANwcfO82xzH+SU0YAeAG4sF3vlMnjw5Z+DtNghOTZMvAC8mO/CfMmUKpkyZ4irwDxODfyIiIqLkq6ysRK6LTUQUXG2tqxg7L6PPfIvI0yJyrIj0FpH/ah53Q3PgDRGZJCIDRKRaRM4QkVUZ894nIn2ahxl+yzB58mTU1dW1Gj9lyhTXwXeuwNttEHv66afnHD9v3jzX8+e6bT5futlSt92nlmHKlCmJu+0+tQxJKjMREREREZUX21+4FovsALyurg4iEkswly/4dytfkO02+J45c6an8bny8Rv8B33evhROHBARERERUXko++A7O4AD3F/1Ts0vIq2Cdy8BYJDgP+iV+4aGBogIKioqAAAVFRUQETQ0NLgtvm9By55P0Pnjxiv3RERERESlj8F3CAFg9q3nXq7ABg3+U2lkLsOIESM8X7m/+OKLW/x066WXXsqZt9vn1cMoe1Cmgl9euSciIiIiKiMiUjZDTU2NFFJXVycApK6uruB0heYNOr/XeTPzzR7cpJVv/qjnDaPsudLxO5/fvEVEKioqBIBUVFT4mi978JpOkO02jPmJiIjIHsX6u0TkX679C/qycFfxqPGAOM6h0MEo7OA3ziAw7OBzxIgRrtPITstE/fnNf8SIEYGCf9PBc1QnP+Ko+7DwxAEREVFLDL6JosPgO2DwHUYAGlYQlAoG4w6e8gWhtl85jyKNuAPgIHWfb163264Nwbvfug+67ERERKWKwTdRdBh8Bwy+U/wEElEFL34DCK9XAW0IvvyUO8z8TZ08CLruo1p3Qcsf1/wpmUG4n6vffh8ZSAl65Z1X7omIKGwMvomiw+A7pOA7xU9nOKwOuKkgOKzye71ynz1/3EFImMG733Kn6iwVBCbhxEGh+ZOSf9BHBkzvs9npMHgnIqIUBt9E0WHwHXLwTd75DSTCuPoZVhAU1i3/Qa9cB627uE98+J3fhnUv4v/KedC8TT8ykJ1GnO95ICKiaLG/G602bdpIdXW1DBgwQEaNGiXbt2/3lc6ll14qK1eubDV+xowZMn78eN/lO+SQQ3zPS8Ux+A4h+A6rE2mqM2q6/KaXO8wrr0m7gun35EFYZQ8SvCc5/6i2PdPzuwnCTW/zKaltns/5ExG1xOA7WpnB7UUXXSS/+tWvQk2fwbfdGHwHCL7DuPpWKB2vAZyJ4EXE/0u/wso/O704g3jTJy6Csm3biysIC2u5TZ50CbLNhH3iIowXTMYVvIf1sr2gz/sHxZMHRBQVBt/Rygxuf//738uVV175xd+/+c1vpLa2Vk444QS54YYbRERk165d8o1vfEMGDhwoAwYMkIcfflhEtB1YuHChiIjcd9990rdvXxkyZIiMGzfui+B77Nix8uc//7lV3jt37pQzzzxTBg8eLFVVVfLEE0+0muaDDz6QU0899Yur9C+//HIU1VF2GHwHCL4zhXEly9Tbyv2mY0vwHOSN32ExdQIkrPnjvm0+qDC2vbBPGgWd32vd+V13ucoRxomLIOnEmX/QbSesTwT6DZ5L4U39pk42EpE7DL6jlQpum5qaZPTo0fLMM8+IiMjcuXPlsssuk/3798u+ffvkm9/8psybN08effRRGTdu3Bfzf/zxxyKSDr4/+OAD6dGjh2zZskX27t0rw4YNKxp8f/755/LJJ5+IiMjWrVuld+/esn///hbT3HrrrV9clW9qapIdO3ZEViflhMF3SMF3ipdOhS3Ba9D5w8rXRPCfWXY/yxF2ABdXABY0gEwJeuIjSABp+qSRbdt9GPP7rf+wrnzHcdw0nX+Q4DmMdRf2cdOLsNs8IooGg+9opZ757ty5s5x66qnS1NQkIiLXX3+9VFRUSHV1tVRXV0vv3r3l3nvvldWrV0tFRYX8/Oc/b3H1ORV8P/744/LDH/7wi/G//e1viwbfjY2NMn78eDnhhBOkurpaDjroINm4cWOLaebNmye9e/eWuro6Wbp0abSVUkYYfIccfJtgOggJS5zBf7EAplh6YQfPpjqxYQfvcQf/mWnFHTwHFVYQF/cVzyiCdxPbf5D8g5x0CqPsmfmXwomPpO27RKXO1v5uqUgFt59++qkMHz5cfvvb34qIyHXXXSd33XVXznk++ugjefDBB+W0006TKVOmiIi74PvSSy+VRx55RERE9u3bJ23bthURfS78/PPPl8bGRhHRu7rWrl3bonwiIhs2bJC7775bqqur5f777w+rCsoag+8Qgm/THYGg+YdVfq/p2Bb8+2Gq7ig4U4FE0BM3YZ248HviJVcacQbPUcxrw7oLWn7T88fxvL7p+bPTMHGrvy3tPZU2Bt/RygxulyxZIj179pTPP/9c5s6dK0OHDpWdO3eKiMj69etl8+bNsmHDBvnss89ERGTOnDny7W9/W0Ra3nbes2dP+fDDD6WxsVGGDx/+RfD9y1/+Un7+85+LiMjjjz8uAEREZNq0aTJhwgQREfn73/8uAFoF3w0NDV9clZ8+fbpcc801UVZL2WDwHSD4Nh082pq/3w5R0M5EkoL4sOourHIk6eRBWOs7aPAZ1vxBt3tTjxyYCLzDSiPougv6uEVYj2v43X78zh9V8Os2jaDPu0d1y7+b5/2D1p0NnxfMTMfvccv0iwrJHQbf0cp+m/ioUaPkgQceEBENiquqqqSqqkpOPvlkeffdd+Vvf/vbF7eH19bWfvGStXwvXLvsssu+CL43bdokJ510kgwcOFB+/vOff5H31q1b5eSTT5aqqiq5+OKL5fjjj28VfM+cOVMGDBgggwYNkuHDh8uaNWsir5tyEFvwDWAYgDEALkoNbue1ZXBz5dtPwxS0Q2I6gArakQ1LnAFgWMKqO6/Lnm+b83vbvInt1u9+F1UAkaTtTiT84D2uRy7CTMPUMc+W+eMO3lP8PjIRxvEm6H6bGQR37NjR97xxB9Cmj3thvaiQ4sHgmyg6sQTfAB4E8BqAOwFMbx5ud5uJLUPYbzsPGnQXSjOM4D/uYCLOACosfgPAsJi+ApcSxroLGkSY2g5MBXBB8w/K5FcGgtZd2C9KjCuAKbTvBCl/XMtga/3FcdyKct172f4zt/24+glhHvODvusiyPyZy5Gkrwv4weCbKDpxBd9vAXDcJmrrEPbbzoPMky+NIA1b0HIEDUKCNOphdPjDCiDjCELy5R9nh8D0dpuZv4kA1G/ZgwZQQfPPnt9E8O933QWtuzCOk5npJO2RgzD5DWJMnTAMa92HHbwGSSfO/INetQ9S9qD5F1r2OObPTifuPpaf+Rl8E0UnruD7zwC6u03U1iEJB6MkBSEmhRU8mw4ATTC9vqPIP0gAafrKtdf5gwawQYS132WnZyr4jTuADIuJAC7fvG5vO44ieA6j/H63vbDqPoz9Pu7tNsxjVtA0vLTzYdeb2zRMPK7gqb87e7bITTe5nz7bqlUi1dUihxwi0vz8Mpk3YIBI8yPgFLK4gu8XAWwHMBfAk6nBbSa2DLa+7TyosMrvJR3TAVx2OWwInuPOP8ygz0TdRRVAFUvT9LYbdhDg5+RBmOvez/wmjlm55jP1vHzYAWSQQNBr3Zl+VCbIdh+WoNtdWOsu7pe1BVl3QcoQdr0F2e5MlN9P8G7kYtOIEQy+LcLgOzpxBd8jcg1uM7FliONt53EGMWE2SHF2vONIK2qFOsFBgym/HXA/9WY6EPUj7ODVdAAYZ11Hsd2GkX9cQYzpbSdf/nG87C7sfT3utiPpAWTm/EHrLO4AMuh2G8V+H+e2H2ZfK67trlVwMG2ayPHHi5xwgkjzZ6tEROSHPxTp0UOk+c3azRmKnHaaSO/eIj/+sUjfviJbtmgk17u3yHnnifTrJzJ1ass8cgXfTz4pMmSIyMCBItdeW3RZyZ1Ro7RKa2pEpk9Pj7/5Zl3No0frqlq7VuSPf2y5eq+5RsTN574nTtSBWovzbeddAYxqHo5wO59NQ1RvO89Mw8vBMYqOoNvyh90RC8KWsgTp0Ma97YSVd660/JY3zmX3WuYo0jJx63Ghuo9zvwlzewtj2zPxpvYg6YS57XqVytvUlWNTyx5024kiePJ6rA+63Wen53e7NfGW/zD6CZlp+Nn+wm7jg6z7YvO36u927CiyY4f+vnlzy//NmNE6+L71VpGrr9afV12lt6avXSviOCJvvimye7dInz4iDQ3p+bKD782bNfD+9FP9e/RokRdeKLi85M777+vPxkY9N7Jxo66ePn101axYoatq7VqRTz4ROeYYkf37dZ6+fUW2by+ex9ixOlBrcV35Ph/AOgD3A3gAwFoAo91mYssQ9tvOC6Xjp0EI0hnxW35TAUyYAVwQtpQjsyxxd0j8CrPubOuQFyqHDR3hzHnirLso1nmQYCboMvtNx9Szs9nzmDhm+A2gbNhvgswX1vxB0jBd9qDbjm1fKQiy7wQ93vmdP/XJt2L7Tav+7te+psHvjBkiH3/c8n+5gu/77hO54Yb0zwce0EiusjI93cUXizz2WPrv7OB79myRww/X58Grq/VS7D33uF5myq+uTmTQoPSj9osXi/zlL7pKUior07edf/ObIvX1IkuWiHz96yZKXFriCr5fR8bVbgBdALzuNhNbBpvfdp5kNnSivaYVZhDht5xh5hvGspvoTIbFRKc0SJ4mt7/M/MPuhCcloPC7D4QRQPqtu0LzBQkkwghg4gjAwpo/e3n8zpekZ87D2G795Fss/7jrPrMcYRwvghwzvJbDax226u82NYm89JLIFVeInHhiy//lCr5nzGj9s1jwffrprYPvMWNcLR+59+KLIv/yL+kbCmpqtNofeyx/8D1jht5CfsMNIn/4Q8wFLkFxBd9vZP3dJntcEoawX0BRikFMECbKHjQIMFnfpte1qfzD3G+CpJXE7TWq/OM+ZoVR92Gs+zgDqLDWfWbdmdyG4/5KQNgBpKkgyo+w8g77ynNSPlOXb3mStN94nb9Ff3f/fpE1a/T3jz7Sq9GZvATfjqNvN//sM71/OfONXt/7nsjjj6f/3rxZnydP3SPd0KD3R1Mgs2eLfOtb+vuKFSIHHqjBd0ODyLHH6qpZuTJ927mIrvaqKr1anv3UQb5nu/nMd35xBd+3QN90fnHz8AyAm91mYssQ1dsfTXYkw25E3KYXRSfeTzlNlqEUmFyPQbddv/Ob3nYzy2BqWzW1/5gO/sPO3896NL3uTTO9/GHlH8Z2F/e2E1YA6HcZ/OYf1n4bJJ2gdedXvjJ7uu183z6RU07Rl63176+BtIhGZtXVGiB37qy///WvhYPvY44R+c539IVrN9/cMtP58zX6q64W2bBBxz31lEZ8VVUiJ50k8u67geuk3O3dq7eR9+sn8t3vigwdmr7hIPXCtX/9V11VmedGzjpLnwzIlu/Zbj7znV+cL1z7HoD/bh6+63Y+m4ZS+s53VJ1Ik8G/6U6ZFyaDf9MBTBRMBFDluu1mM1H2sIII0/Mn6cSf6QDQbxARVjlsWGem2o2o+gum6j7O9qLQOovjxIPf5Yikv7t2rX6/iqjMxRZ8l8IQR/Add0c2yZ3+FBs6RX7ZEISbeOt2Zv5hBP2m173fzmTcdV+sIxhX3WXWV9jBWKF0wtxevKZlcl/Px0/d+12OsIN3v2mY/k54WNugibbb1AvPstMJGnT7KUdYeYe1vURdhwy+iaITafAN4NXmnzsB7MgYdgLY4TYTWwY3nxrzK6yOXNCG2G8QEVYHIEh6JjojYTLVuIc1v9d8wuqEBwnggjK93/pNL2jdRdWRjKtDHub2YvqY6VVY+5/p/P3We1jbW9AALs7tIOz9Luj+H/fz/tnzmGgrwzrmxvWVgCTc6UmUVN27d281LrTgu9SG7INRFJ0YUx25UggiTDDVmcrM29SV66D87j9hb3tByp7KM+79Nmj+foUdwJjYbwqVJWm8lD2s9irM+jJR92G3mUHqPu79xvR+F7Qe/Mwfdt2HlX/cbZfXfgKDb6LoxPXCtQfdjLN9iOI737Z1/EyXx23+UQRgYXVko25Q8+Vt6kUupjrhJvKPYrvzU07TJ1qScpxwk4bpuvTKbxAQVb7ltO0Fzdvv/KYDuLDXvcnAP66gO+r8o677Fv3dsWNFevbU35ua9OVqmW83J5FHHhHp00ff4P7kk/6nzzf++utFjjgilNv2uTrTTK22WK58A1iS9feBAN50m4ktQ5jf+Y7qgGq6YxS3sDpDfuvOdBBiQilta36XJez17jU9m7a7OMsSxbZn8sSLl7orpf3OD5MBoC11n1lmkwGsiWNmmMvrJy3Tx9y4132r4Lt/f5Fly0TmzdNIolyjtVz27tWPYm/aJLJunb4mfN8+79MXSmf+fH0leUjBN1en2dUW9TPfk6DPdzeh5fPeHwG4yW0mtgxR3IZTap140w2UW+Fsh/UAACAASURBVEGD7jDLYHtd5ZMqfxJve8+ue1PrwpZOvR8myx5kfdkQBNiy3v0uiy3rPkgQldS6t4Xb8get77DWlw1tfnZZbN7vWgXfEyeK3HijXsqbNCkdrT35pMiQISIDB4pce216nlGjdFxNjcj06enxhxwiMmGCXiIcNy70chvx8sv67a6UESNEli71Pn2xdEJ6YR1XpzK52uK67TxxgXauoZSegQn7IO43PdMdEBP5F+oExNEhiKoBj6szFiQtWzreppk+cWIigLXxmGfb8cdvMOBmPpP7vZ/yhp13oXmj3gbctDlJCUC9zms66I6i7uPY71oF33/+s34U+lvf0m92jx8vsnmzRmqffqrTjR4t8sIL+vv77+vPxkaNzDZu1L8BvRzY2KjfB099zzvJZs3SyPP3v9f7j7//fZGnn/Y+fbF0Qgy+uTrNrraor3wf3/zzxFyD20xsGUop+I6KiQAsivTikF1XcXfETXT8C+UfV2csCl7zD7u8Qfe7uN4XEMV+mpR1b/oYZToIyS5HXQgnH0zWfRwBUNjCrPugZQjz5IXpfchL2U3Vvdf8cwbfV14p8rOfpaO12bNFDj9cpLpah969Re65J5WhyKBBOv6QQ0QWL9bx7dql0z3ttPT4JEtFXyluo7js6YulE3LwXe6r0+Rqizr4vrv554s5hr+7zcSWgcF3a3F1nkyll4S8w+qQmAogTXeogvBa9rCX1W96tgSsSV3vQYR5zPSTlul1n1mGuNe96fbKhrq3RZC6iLMeS+lY5WW/yxl8b98u8sknLaO1MWNaZ/TiiyL/8i/pS6g1Nfrgq4hGbikjRqTHJ8WCBenodP58HffKK97uX843fbF0Qg6+y2l12rba+Kkxn8G36U606YDFdP7Z5TAZbNvyzLPfurBl20tyx9TUiYuo0oszvySv9zgVCgKSGgwkhen2zoYA0PR+avqYY2r5o9jv3SxLzuA7JfM+5R490vckNzTo/cizZ+v9zCIiK1aIHHhg8qI1L1Jv3Nq8WeS99/SSceabuyZO1KHY9MXSCTn4TinX1WlytcX1zPd5AL7c/Pv/A/AYgMFuM7FlyFVZuQ5icZ7RDatB8Nu5MBVEmOwMme6IZZejFDpDXvM0HfiXY91n5ps9xP2ZOxNs3O/j3A5K6ZhrS3vnlYkg3E3wZyL/IP0r0/uwH3Hv966CbxGRp57S+5GrqkROOknk3Xc1GvnmN0X69dMHi4cOLY1orZCHH9ZvTfXp0/qbVWPH6uBm+nzjf/xjkW7dNPI96iiNiH3i6kwztdriCr6XN/8cDuAlAN8EUO82E1uGYredJ/nAnmJbp97W4D+KvN0qhe0sqLDq3mtdmq570/mbLE/Ygb/pY45t69ItEwFgdt5Bg+7U/CaD6bCXJWpB6870uos7eLUh/yDHGD5mSRSduL7zvbT5500AxmSOS9KQhIORyc5EGOIof6HOY9I6wmSGyZM+UeQfVJzlSeXl93EP0wGY6fzDFHS7TUIQUkplSVoAGEZ6UdS3l7pz09+Iax142e+S0N8lSqq4rnw/BeAPANYAOBRAewCvu83ElsHm73zb0rlIUkfStrKaDgLiTC+KZXWTpm37SdLfF2BDXm7TK8UgIIzyxlEWN3n7CeKDnngJe3niyt8rGwLAsJlqL/3WnQ39DS/bLYNvoujEFXx/CcC/Aujb/Hd3AF93m0mBdEcCWA3gXQATc/z/OgBvAlgO4AUAFRn/2wdgWfPwpJv8wjwYme6IZZcj7s6ILctvQtgd0bDyjyMIiWK9+0nTtgDQ9Ke+4tj2Cq2ncgj+o8rfq8z8bSqLifmD5hd0v/e6zQTdT4Ose1N9BdMKHTNNHa/DWgeF0mnR333xRZGvfEVfFX388fpBYxF9ILZnT/29qUmkc+f0w8O//rVI//46jB4dqLyJ8Mgj+sBv376tHx7O9uGH+srwgQO1Th9/PP2/BQtETjhB6/m883Tc3/6WflV3dbVI27aFX8tdBFdnmqnVFkvwrWmiGsCE5qHa7XwF0jsAwD8BHAOgHYDXAfTPmuYMAF9q/v1KAI9k/G+X1zxL6UygLQ2g6c6fSX47cnGVJ2l5mag/v/uRbeva1Lq35TiUZEnfb5PAlu3UxIkTkwFgkOnDZjL/VN5x3inVKvhOfUtpyxb9GPSGDRqt9e8vsmyZyLx5+krn8eNF/vEP/TbV3r06z5IloZfPKqnXXW/aJLJuncgxx7R83XW2xkaRnTv1961b9Y1c+/bp0LevfrtKROs62wcfaLQYAFenMrna4rryfQ2AFQBubB7eAHCV20zypPkvAOZm/D0JwKQC0w8GMD/j77IOvlNMN2hhK7XliYPpjqXp/MmbUjlx4jdvU2XNt5/Esd+Y3kcZALYuQ9zrIuiy+53f9LZnozi2w7zBt4i+Bvsf/9BobeJEkRtvFLn+epFJkzRa+/OfRc49N7KyWefll719MDrTu++KHHaYRoL/+IfIsGGFp//v/275/SsfuDqVydUW29vOARyS8fchaH4Dut8BwGgA92b8/UMAdxSY/g4A/y/j7yYAiwAsAPCdAvNd3jzdop6p+zEsYkNnwAamG2gT+Wev+6RvC17Kb3pZbck/zishpbaPeU3P9PJnl8OG/TzusoSVny3rMgibtoNCbKtrk+VJ0omTvMH3e+9ptLZnT/qbVd/9rn4IOvXNqu3b9TJfba3IL3+pl/1K2axZIuPG6f3bjzwi8v3vizz9dOF5duzQ73l96Usif/qTjnv0UZFzzhE5+2z93tfvftd6vpoavTQdAFenMrnacu2PUQTfbwA4KOPvgwC84TaTPGm6Dr4B/FtzkN0+Y9xRzT+PAdAAoHexPN1+5zsoN2lGdRB3uzwm87elMc9V1jg6RPmW32TgH5co1r2XNE1ve/nyj/M726a2exN52Zi/DUzvB0mVve2Y3JaC5u11ftMnTkzWvam8g7QXOZ/57t9fP+z87LM6PhWtXXmlyM9+1vKD0Z99pg/F/vCHIt27awRXqlJRXIqbKC7lzTdFhg/Xe5r/93+1ntetE/nkE72X+Z//TE+7apV+bDsgrk5lcrXFdeX7Ougz2ZObh2UAfuI2kzxpurrtHMDXALwF4IgCac0EMLpYnpmVZToIyJ7HlgYtzvxLKQAMs1wmAn9T6yDMfL2kaToAM51/djmStD2w7nKXw3R9+GEqAPSaXr51Hce6DzvvpG23YZfXS3q21JWf8uS98v3EEyI9emjUkYrWtm/XqCMzWss0apTIM89EsESWeOUV//cvi4iccYbIwoUizz0ncvLJ6fEXXCDy17+m/77hBpHJkwMXl6tTmVxtcb5w7UQAVzcPg93OVyC9A6GfLuuF9AvXBmRNMxj6Ura+WeMPQ/NVcACdAbyDrJe15RrcXvk23ZkxnX+5YD23xPrwj3XnT5I7wtnliqMcmXnZWh9ueC27yQAs13yp6UytexvYVp5CbOznBeGm7AWf+f7GN0RmzkxHaympaG3NGpG339Zxu3frfbrLl4e4BJZJvblr82a9j7t375Zv7po4seUDv+vX66uzRUQ2bhTp2lXv5f74Y5EjjxT56CNNc8AAkbfeSs/Xp49eRg2Iq1OZXG2RBt/Q28t/An3e+kcADnSbsKvMgW8AeLs5wP6P5nE3Aji3+ffnAWxG1ifFAAyD3gr/evPPS93kV+yFa6Y7gknuTJlQag2qKX62uyjq2UuatqxnE/usqWUvtKxBy2Ry3btNz+Tx2XTbkC//uMtjat1HxXT+foR14iIOpveb7HLEedKmYPA9f75GYBddlDtaW7lSZMgQva+5Xz+Rm26KrJzWePhhjbL69Gn9zaqxY3VIee01rb+qKq2fmTPT/5s1S79L1b+/yK9+lR6/YIE+UBwCrs40U6st6uD7EQD/2xx4PwFgmtuEbRyieNt5EhvPpHPbEbShkU0SN2U3fdLJ1s5UnHnatOy2lMmPJAURtjARRITJZHlN7zemlj2qZfWyPLYtexzrvRS/7kNki6iD7zcyfj8QwBK3Cds4lNLBqJwbNFuY6kzZEPDkWvdxbg+2dab8lsNPeqbr3m2ZqDUb112cSmW/DSvvOOojX/5xvuQxsxxh9VFMn/Czvb0rpf4ukW1y7Y9hBt9LCv2dtKEUD0YmGrQoG78kdERtbfzLsWMbBhvK73fd2VB205J8zLDhhJ3JADCsdsttOknYVqKSWna/nze0re7Kob0Lklcp9neJbBH1le99AHY0Dzuh39ZO/b7DbSa2DDwY2cuWIMK2DoYbfuouiuVMYt1lirr8prfxUsvfb3pJ306DyFx209tDEKbLbjr/ONlw4sTGQNtEmbysC/Z3iaIT29vOS2HgwaglGzuhcZbJpo5oXPmbXk4yv9/lyt/UfhdnejYEEUkX1rKWynHI9H5jOv8g6bhZ91FuJ0kI/vNxUx72d4miw+A7YPAdxUHV9EG9WJq2dHxMNWiFlt90Z8a2Rj4qpbjfJZEtx4IkKqe6i+qY6XXesPfbJBwz8tW96W0vScfQzLKa2G9N1BWDb6LoMPj2GXxH0ZnwclCPogHwmqapAMiWTqttnakkdGKCMr3dl3PdF2K6I52EIMh03vnyL4fjWNh58ZjhX5Lqw3RZo+hnusXgmyg6DL59Bt+5mD5QJ5mfujMV/FNucdad6XVvOv+wJXXd2RAEuVke021DvvxtaK/K5ZgbdDlNnzgJOy/Tx1svTOefqyxR77cMvomik2ufZfDtM/hOselATe6Y7hzHzVQAFKWkdOay8467/jLzjzPvQnlFEZiEMa2bdJJ0wjDOek6CJCyP6RMnJo/vUeRtS3sVVNTbLoNvoujwyncEwbdpbg/KSeh4RCnX8sdZJyaCoCjzMbU9eVkmk8tfLO+o6y/K4DeKMlFrJo4ZmfmaXk8mT5yYZlN7ZSL/sJVT3fnJKyn9XaIkYvBtKPg2eUbXlo5HuXb4bQyCsstmIgAMK203aYW5nKa3p+xysCNcesp9G4tq+U0dM6JMMw5e1keprjs38i276ZNmbvJn8E0UHQbfhoLvFJMNelQNUrF0SzEA88N0/rnKElfn3qZlTzquO//c1l25B7+FyhJnnZhY/iiWsxy3p7DysiHwz0zbb1/DdN0Xy5/BN1F0GHwbDr5LideGLszGx5bOTNLZ1LnPxYb1bLqO8uUfdblsqPvMcoSZr9s0TeYdlaD5my6/W6bXnakALN9+a8O+HETQug+ab5Lrzg32d4miw+A7wcG3rZ0ek+Wy/WxyqbCxIxs1050u0/lnl8NUvqaXPywmlidz3ZnOP640o1hOL2nast3a2F6Zzj8I032NqNnW3yUqJQy+Awbf5RgEZJcjiQ1nEDZcSchX91GvE9MdWbJTUgJyG49ZcZSpUD2Zzj+uNE0E/mHmb3rbDTN/G9ZdFOWMM/+o64TBN1F0cu27DL5dBN9RHpTdHlSjOvgWS9d0g+S2nCbyNxX8jhgxworgP4lMb8+m8w/ClrKbOmYlJYiwOX/TZbKd6X3MZF/H9LK7LWec+cdVJwy+iaLDK98+g++UMA/KphuapORvupw2yLfdme4kJJnpuosrf9Pbjul6jkJSggibsE68MRGA5cu/0Li48rYxTRv5XU4G30TRYfAdMPguRaYbJbf5s0G2j8n6M7ndJEG+Dntcd00UChjKdZ2EIel1l5Ty21hOU2XyGvzbVHflctIn6HKWS3+XyAQG3yEG37Yc1G1q6Gxm+kpCKTHZGXObty3r2PT+mS9/E1exbFknSWG67nJtI1FvN1Etpw3HDdPHgqCKlT/qbdRt/ZmuZ5P7bfayu82fwTdRdBh8hxh8p5hqkNiRdadQPZkIQNyMjyv/qNnQkY1q2bnf+2e6c2w708esfPmbDCJsT9dNnqb32aS2N27rz3R7Y3q/LaRY/gy+iaLD4DuC4NutUupM+GG6nDZ1umy49TdOptd9mLzWadL3+1JadymmTpyEXU4T+ZsuU5KZqjtbtue4hFnPfuouSP6mthEG30TRYfBtMPg2zVQQEFXDXwodCtMd2XLPP4hSD35t2L/CXvZyO3FiUqm1N2GXM+p8bbz6mmRR153p7bbU+rtENunevXurcQy+Szz4LvXglx0K70wHIbZsO27Y2Ik2UY7sfKOsl6iXvZzXaVKDCNPHLLfp2rCO3ZTTRFlM14lbJuvOxPFWhME3UZRyHfMYfJd48E2lK2iDbLoj6bb8UXQ8TC97UiWpXkwHILYF+XGuN1PBb1TiDv5zzW96ew7K5PHeTbo2HtviKhP7u0TR4ZVvBt++Jb3hD8LU2eh8DW9cz4xnl8P2Dm8UaZbzdl+IiXpxu+6i6rCazt9veW3adm0skxemjvk83tuXbpyiXifs7xJFh898M/j2zHTDZTJ/24PfpHdk3SrF5TS9THHkH1UebtMt1fyTyHQ7kjS5th1TgX+pnDQqh/3R7zKyv0sUHQbfAYLvsA/cXhu6UsvfK9P552Jjmagl0+soO/+4O7gm8relE1+qTG/TQZg6ceF2m+S2G/3jTFEznX+uskS9PQXNJ6zgu+KA9wXQn2ELI+2KA96PpGzlzLY6ta08Igy+fQXfUR88izUUpvOPii2dHJsa6qRIwrozXcZi+Ue93ZnOP1ceptdJ0pXDiRNb2ju2C63Z3lcxue3acLwtlE+x/MMKvoGWP8MURtpANGUrZ7bVqW3lEWHw7Sv4LsR0R6UUmAgCMseVw7qLqo5NdWS9rDvTy06tse4Ks6Ejz3UUjI3157dMXttKk8f7KLlZrqDLbqruGHyTX7bVqW3lEWHwHXrwnWJjQ0v2NNr5RL3dmF7+qPM3sd+ZrlOKj+njuun8c7GxTJlM75/58o/jPSEm8y5lcWxTprdbBt/kl211alt5RPi288iC70JKMQBJGtN1lJ1/3A2tbctfCkpxmVJMdwSzyxF2vsXStWX5bWJLnbjdJkxdQSyWfxzHDZN5J5Wb9VvK647BN/llW53aVh4RyXk8YfAdcfCdYmtnIKxyxN0ZSoJi68h0nZR7/klgYyc+alEFeqaPmUkLYIPMy7qjFFvWnRu2rd+46o7BN/llW53aVh4RXvk2GnybYrojm6SGNyrl2qDbmr8bpsuYL/9yuoXU9AnDqJg6cRLHNm16v6HgTO93pvO3UdRlZ/BNftlWp7aVR4TPfJdl8J1iukEznX9UTOcfRLGyR92RdlN3UdSvl+UyvX7z5W+qXEkKrkyvOxPcrB9TwT+5U64nTqLK3/RyJQGDb/LLtjq1rTwiDL7LOvguNaYb1Djzz+6Mxb3sJjrScXY2TXTCkh6c2LxN2HDSyMt0UbBt+zJ9vE4C20+c2LZNJY3NJ70YfJNfttWpbeURYfBtbfDNRs2/KOvOdGeoWP7cbpKnnIKQqLZPU9u9LcF/ktl+4oLrrrWk1YltJwbjqL+gfQUG3+SXbXVqW3lEGHxbF3x7OSib6shG3XC4WS7TQabp/G3FevHP9FWQUj5pVQpMrTvTbGhvvEwXVf42MtVXSNJJL9vWr9s6YfBNftlWp7aVR4TBd6DgO47OaqGOlqkGzU0Zo8rfhsa0FJhYd3HgiZvCeZq6CuO3bGTPujMd/JfaMct0/nEyfeLCdP5JxOCb/LKtTm0rjwjfdu4r+Lal0SzVA7/pjpzpeo3jpI6JbTfKvJNw4sZ0/pllsPGYYbJspjvxbpg6ZtkS/EfF5n0iLDa3d0lky0mvKDH4Jr9sq1PbyiMiOY8ZDL6LBN8pbLSSx+aOpOn848L9JhqmT1pFKap9w2265bJvFpL0/dbWEydx5Gtje5cUNp70igODb/LLtjq1rTwivO08UPBdiOmOiun8bWf6SoDp/G2V1GU32VGKI2/THcHscpTacdX0cpWyqLddN8dy0/uNbZJQL7aU0dSxgcE3+WVbndpWHhEG36EH314O2FEcVG1pMCg3rp/cklQvJk+cmD5pYzr/UmN6u48z/1I7cVEKdWdaseUyeeLEZnFsewy+yS/b6tS28ogkPPgGMBLAagDvAvj/7L17tCdXVe/7LTpCBhE7AYK3CaYfeegNmIR0i+Ll3r2ViBxkEC/GHDlXL6iHcI4gPoZIkOPdHWAQJQ6PR+OR8JAElYdRHvEZXtk5Ig+zCQlJwEASWpsEMW8ew2AC6/6xf79Ode2q+q3HXOs7V/3mZ4wavXvvqjnnes/vqvrV77yevz8CwDtnf/84gF2tv71i9vubAPywjz+pyajknaoxm4yFh51sakHros+OS7N/Zt/VPG40x6aJGvp2TuE41j9i/C9Dv8tVd7FxaOy7KfbYfSe1XDnzPBPfRiza6lRbPM5VLL4BbANwC4A9AB4O4DoAp3TO+TkAr5/9/BMA3jn7+ZTZ+Y8AsHtmZ9sinyW/5zsnuRaeELslkr0pJWFdmMnIFOt32csvAbteciaiEnGxEn22/1pj00Rfvy1Rd1rEfy5YsWtpuzFMfBuxaKtTbfE4V7f4fiqAK1r/fwWAV3TOuQLAU2c/HwHgTgBN99z2eWPHVMT3nFwLz5QXtJA4cm4sMMrIrt+SCYtmAWkcTohAyNV3tAp/Tf6NacFeD2phbNyVGJOx/k18G7Foq1Nt8ThXt/g+G8CbWv//KQAXdc65AcATWv+/BcBjAVwE4Cdbv38zgLMH/JwLYAPAxvHHH59U2UYZWAtayWSEuaCzk3i2/xxoSGTZiWAJ29L+NbTb1MlVxyF2pzjnlIRZfyzfmucGn9hMfBuxaKtTbfE4Z+J7ofhuH1O78z3GogWLnYxoXlA1x2ZwYY+bPkr0m6n3zSmPeS1tl6uOfTYy2WWvldz1x247jfN5CGPxm/g2YtFWp9ricc71zke1iO9JP3auNZljL2hakqHaF91cWL30U0O/Zbcd2/8iNMdXIjbN5deOxnGnZU6KoWTsfe3D9p+btbU1E99GNNrqVFs8zjm3Y8eOLb+rRXwfAeBWbL4wbf7CtSd2znkxDn/h2p/Ofn4iDn/h2q1Q8sI1n0ldw6KZY0HQUC4jDi1tV8PGDQPNZdccm3P8+Nj+jXFi5xwtAs42VfoJycVythnLv4lvIxZtdaotHucqfux8M048C8Bnsfk4+Stnv3sVgOfMfj4SwGXY/EqxfwCwp3XtK2fX3QTgP/j4m1dWiUXTZ1Kd6qLJLhfbf26mWL6QMVkiYZpS3ZaCXXeL/GuPjwkrNt9xnyM+qTyALeBYaI5NE339o0Tdmfg2YtFWp77x7Nx20O3cdvDQz4A79H9pqhbfpY9uZWlOhoxwtCQDufoVu3xs/znRULYS85F2kaXNdmgMtQl77ZteJdqW3XY+aI5R+6aXZnLWjYlvIxZtdeobT/u8nP3WORPfSeJbM7ZgjTNWPywRo0EEDMVWk/0pw+o3y9A3Gf2yZL3m7Ds+8ym77xjxTHVsTH0tSimfiW8jFm11auK78iNkMmJN6rUkOstaPz7+l7Vu2jFo669ttCairE0jI50SmwrWd+rFZ3OD1Xdyk6N8GsrVjkPar0T5THwbsWirUxPflR8+k1Etkzpr0tdSP2w0J6JaxSWbGmJkon3TSHt8peLQ2F81x+aczr5j/Sod1qZTqbZLyQNNfBuxaKtTE9+VH1J3vpmLZg2Tfm7fuWH7z8UyJHs+ttn+taG9XyzDnFcri9qG3bfY/n3QuDGgyb/m+tEcm4lvIxZtdWriu/JD+jPfzGRsiolgLclAqThy+dWcMGi0XYN/CdgbF4vI5XsKbacd9nrF9q8Z9qYTc9NN+5yXgolvIxZtdapRfPfNSSa+C4lvo17GFtQpJxsp8dUAO3aG/5JJKrtv5oTdd3IzxfIx++XUx92Ux/yUy+bcZvlMfBuxaKtTreK7O1+Y+DbxTd/N1koNyQyrbaaekEiguW1KxNbnw/pNOjnbTkvfyQkz/qmPu9r7xhi5y8bMw0x8G7Foq1ON4tseO1cqvlmT7qIFWcuCzV7Qp56spaC9bhjxaRGYmvuO5tic07lxwu5XbP++sPsW2/8YmmPTgMb1osS4M/FtxKKtTk18V36UEN8aJt22n2UV/0Y+cvQdn36hoe/kTuQskQ6nljlnrG3Z7a7VP7vt2P5rwNpucQyl8zDnTHwb8WirUxPflR/LcOdbC8zysQXSVNu2RDLDrjuWfy2bcjmZ+rhk992c5Cqbb79nt12q/ymOu2Vpu1ox8W3Eoq1OTXxXfnQra1kn5amSW8Assr8MAsrHPzu+GEq1nW8crEQ5B1rqNhdTHvdTLlvbL2vNaJ9T65ifatuFxMDaWBjDxLcRi7Y6NfFd+TGvLA2TtpHG2KLEFn+1J1OxaI/PB83JVC7/WpJ0dt2kwhz37H5be9vlxsZdPhjjTsOmTfu8Pr8mvo1YtNWpRvHdN+5MfC8Q3z7UviBNlSkIvNywky3NY4cVWw39VnvdsPuVRv/sfsX27wu77TSipe2G2kZ7fIv+ViKmsbox8W3Eoq1OtYrv7rgz8Z0gvtmJINu/r312MsP2r5FFfUdLMsNAS9mt3w7DTsLZ/muGvV5Y28XDqjstuU7NjLWdiW8jFm11qlV8d8ddiPhuNs9fDh51xClu77e+zevc+++/H/d//X4c+YgjceSRRx76/YH7X49/+vrFW87f+YgXYdeR/0UsVpb/RfbZ/kswVPe1sCh+dvly+tde9hrRMCZzoqV8U+ybWtaLKdZtKXLXHbttcvjXMKd89cT/jI2NjWQ7TbMpaeb/SiJhu2k2/10iKZMdbXXqG0/7vJz9FgAedcQpaOvJ03ffh/9x7eonnHP7fK438W30whYxjAVZw4IJ8JORXOSsX2u7/P7ZZcsNq3w2LvTbZ/pn3wiYKiXqj5lHmfg2YtFWp1MU3/RHwUseJb9qzNAL+zG2ZX9EMmf9L+vjrWz/xjAaHq9lz3m1wvwoj4Z+UzOa66/EfG2PnRuxaKtTjY+d29vOTXwbnrAFiuZkQJN/jbDbju0/JEat/YYdH9t/H+w5sRvHkF92ES31mwAAIABJREFU3THjY5d9CC19ZxFa6y83Jr6NWLTVqYnvyo+S4ps94Q/5Zy+YbP/GMFrapq/vloqtdhHAQPvGgJZ+rRmtbaNl3BvDsOdMa7t+THwbsWirUxPflR8lxDc7EWX7D43TFsxwpprM+PRd9rjJzRTHhRYBNcW6nQqsttMy7nOieT7XbJ+JRNlMfBuxaKtTE9+VHxrufGtJRKeKhgV56onilPvWVBPVto+pbbixxwW77XL6Z9dtKXKODR/bOfxb26Xb9Kk7Rt/xiS8l39257aADHvrXuX4R0z4vhpziOzW2WHZuO5jNZ07bbVLFt3Td5xTfsXXaNy5NfI+Iby0LEjsRzsUy1O+ybqxoaduaWdR2rERyCm3LnlOXUQSU8F0rWsZd7W3DjH/Mt4Y5cyy+FPHdFi5jIiZVPOcU3xK2JePRblvSj3Td5xTfsWXtG/MmvkfE9xyfCb32RYsJMxHMhe9iy+43y+6/D3aixPbvi9ZEVwPa42OgvV9riE97rqG1X2tou5ox8Z1uWzIe7bYl/SyL+O7ORSa+PcT3GDbpL4axYGtpF0tWdPr3gd12bP8aYW9qLfJfQ79edhb1DRt3W2H3e/a4nzomvtNtS8aj3bakn2UQ3/aZ7wzie87YpJ97QdC64GhIRLXWjbEJc9ywmXL5WHNeqTmHLeCs78TbtQ3HeJa93+fwz+4Xa2trJr5NfNP8mPg28Z0kvvtg7wazJ/XcTL18TJh1W9I3I5mbcr+dctk0UKJ+fcZEzSJkigLOx7aNzXHYdcfslya+021LxqPdtqQfE98mvsXF95wpL/Yl7C+jfy2JErNuSySpU3sqQ0O5fGGPW61oFr819K9l7Fch7bKM9TNGDX3aubztZuI73bZkPNptS/ox8W3iO5v4niq1LFopaN8NZydSbP+plBD4WjcuWPEtw7wRg5Z60dx3xnxrqD/2fMj2P4SGtlnEMtedie9025LxaLct6cfEt4lvE9+RaF20UtCeLLDjY/vXjPa60RKfz8bW1DYGtNR9jfjWXe6+02ff2tUP9mZyzblKzroz8Z1uWzIe7bYl/Zj4NvGtVnxPNRHt+tGUhBt+aG4fzbEZ/WgRvyYC9DLF9TDEds7yT7FuS9gPjUPSr0TZTHyn25aMR7ttST/LIL77xqWJb7L4Hps4NYhfn7+n+mWW3chHiUSuz8eyJHI5YYtDE7/x+GxmsgVkzbDEr5a2q1n8T7HtfPwv+ruJ73TbkvFoty3pZ1nEd3fcmfgmi+85PhN3SfFbkiknwj7UnMyM+SyRaDD7Lrvf5vCvJQmvGVa9aGk76xd5mbKATGHZx11KfCa+021LxqPdtqSfZRDf9th5pPi2ZKI+fBYc9m50Tv/aE6U5qWNrimNzUdux25btXytWL/5oHbda41p2xsZWyXHns57X2HdMfKfbloxHu21JPya+TXxvEd+WTNWPz4KYY9HU0ncWla2GuwXLSs3JXE5CNtZy1d1Uk/DcMNtOi4CbMlMdd1PuH2traya+TXzT/Jj4NvG9RXzPSZ3ULRlbXrS2fQ3JBDuZ0tp2NVCi7vp85O7XNYybWNhlK+WfvXHCnldy+Gf3nVKUWJMYdWbiO922ZDzabUv6MfFt4ntQfMdSckFiL+hdlmUxrh12IjoWE2vcaBABtbIs457ddlMVAVMm59gI2UzMOTZr7jua17vcbWfiO922ZDzabUv6MfFt4jtJfNcwceeKTaOAK8nUyqhFQE2tXuewk2C2f2McdtulxrjM+NQLe+NEc67CQGtcfeRqOxPf6bYl49FuW9KPiW8T31HiW/PEnTs2LWWfcjLBTKYswU5jUf3lqN+QPsluX7Z/bWiZT8fQEuNQ3ykhbPvKrqVeaqDbRlZ3MqT0fRPf6bYl49FuW9KPiW8T31HiuwammuROWfz6lM2SlnGmvCnjG4PGvqChftpxlBRwKXFpQtvYWllZKdanamifWJhlK+G7xObM2EZnjv4pYdvEd7ptyXi025b0swziu29smvheAvGdQg2JBkv8loAl/n1h948+/yXbzifh0jx2tFIiSV5mAccSIUY/7PWG7T83WsQve2wM+TfxnW5bMh7ttiX9LIP43rFjx5ZxZ+LbxHcv7MWY7b8bx1SSECl82ochoDT5z80UBZSWjZNclCifz4YQW4QY/fj0Sfa417omsuNi+x9j0dg08Z1uWzIe7bYl/SyD+K7ysXMAjwbwfgCfm/17TM85pwP4KIAbAXwKwH9s/e0SAJ8HcO3sON3Hb2nx7ZMwLaOI0LygaadE3fX5mLqAYvtfBgFVswhgEdJ2JuD60RqXc/yxuch/qbrr+mHXS00MtZGJ73TbkvFoty3px8S3XvH9OgDnzX4+D8Bv9pxzMoCTZj8/HsAXARztHhLfZ4f6LSW+xxaOqYsYLYsmO+GS9m/1uhywBRQLLf17CHbdsf2PoaXtmAIutX3Y7cuqOw3in1330szLY+I73bZkPNptS/ox8a1XfN8EYMfs5x0AbvK45rqWGI8W31oW5KlN+FpgJ4Js/904lnHjRVtsmuulC3teYvkfaqOSnxmvnaG2y92mTAGnZWznKmOp8Ti19crHdu6+Eyq+d2476ICH/nVOp/hux9mNUTK2ua+5H18Y4rtdJ936aZeh+7dQP2MM9Z++83LFkyq+feNxrl7xfW/r56b9/4HznwLgMwAe5h4S3zdh83H0/w7gESPXngtgA8DG8ccff6iS2EmmEY9P2+VoXy2J1hgaYtS86cT0zy77GBr6jYa4NLdRCow5c5naroTAH5tPtY1bLbDHMytXcS5cfA8Jbm3iu09c5RLfMSKUIb7H2itVkIbENuRvyLZ0PKm2Q/qMWvEN4AMAbug5zuqKbQD3jNjZMRPa39f5XQPgEQAuBfD/+cQUOhmxJ26tsOpFS6JRQ7/QFmPJtpta/9RSd1MVNyVgJeE+fUfLvGocTki7sMcH238X69Mmvk18j/8uxs+ia4b8DdmuWXxX+bZzeD52DuDbAFyDkUfMAawC+Esfv76TkZaJ2xY0Qxp2nypxh4jdP3OVUbOAy+lfAs0bMiX6LavvTAGrl2EW9d1SdTfFNkotk4nvtNjGbEtfk2rbxLeM7ZA+0zfn1SC+L8ThL1x7Xc85DwfwQQC/2PO3uXBvAPwOgN/w8St555shIkp//nCojCUWOvZiyhRQOfxrEaY1w+6TY7AFnNb+pSWumsUvS0Cx247tX4Kpt52GNtK6Vpv4TottzLb0Nam2TXzL2A7pM7Xe+X7MTFh/DpuPpz969vt9AN40+/knATyAh75O7NBXigH4EIDrsfkY+x8D+FYfvxJvO5/iZD9kn1HGqYoIX7sa+lc7Di2JMJOays4WcGz/Q7BESM1oEVDstkv173O9VgEnFUet44GRK/j49jnPxHdabGO2pa9JtW3iW8Z2SJ9R+5lvjYfkV43Vvqj4wCxjDt8hi2WusqcuqLnRkggvim8qfXJZyF13bLHB9t+OgTVn1eJnyC9jw1W7gCtFro2P1HjYmxdjLIrRxHdabGO2pa9JtW3iW8a2ie9MR6nv+TYMI5yxZKJkMsRORHPBKFfpJJYtQBn+tQgF9rhJ9c/uOwzYfWfIf8mP2PmMLY1tN6cb4/z/Jr7TYhuzLX1Nqm0T3zK2TXxnOpZdfLMTYfZCb9QBKxli34XK5T/E7jIKkDHYcxbbvw/sGBf5r7XvlYS9VjPaiD3fh54XionvtNjGbEtfk2rbxLeMbRPfmY5S4pudDCy7/5ywY2f7N8IJTfKmmIiGxsHya3NWvbAF5BRZhr4jXUbffpe7f5r4TottzLb0Nam2TXzL2DbxnekofeebnQywF06mf9aCqsU/G3bf00gNdaJN/Gr5hocaYc8ZbP/dOHL3mRzl9I2d3W/Z/oeoIQfJFaOJ77TYxmxLX5Nq28S3jG0T35mOdmXVMCkb4eRO+Ba1Hds/Gy0J91hsGmKpjVJ1N+RnWdouRznZIqD2tmPUn+88yp5vF/lnzRvsepEgte5MfKfFNmZb+ppU2ya+ZWyH9Jkqv2qMdezdu3cSk/Ky47Mo1Z7wxaI1GVr0e0mfy373lCECjH5qEFFa27h0XFMUcKVg1Z2W9U6S0LobKqOJ77TYxmxLX5Nq28S3jO2QPtM3Pk18DxzL/sI1KVgLmiVD/mhLJEv6Zwj/tv1cZVwUf07/vnWnNdllx8X27wM7Rq3jll0vKbBjZ/svQa4yps73Jr7TYhuzLX1Nqm0T3zK2Q/qM3fkOOGoT39pEbuk7iIvim/KCPlWWoe2kyyh1JyQn7M2dbhxaNp2MxWhpI8lxE1Mmtn+NaJ7LtNTxUB2Z+E6Lbcy29DWptk18y9gO6TP2me+AI3QyYiVyWnbih/zULKB8Y9e28VFjXU8FLW1Sw7hjzRna58zc5OyjU6+7nPiUSUPbaat7DXNurXU3x8R3WmxjtqWvSbVt4lvGtonvTIfvZKQ1kdOwINWKb93lquNQu1oXdAal+r2WcT8lSs9ZUxK/MTYly2/rTVkYfZc952n3XyPzMpn4TottzLb0Nam2FwntXGLXN4Yh29LxpNoO6TMmvgOO2h47X1amfCegFgG3jIlgNw5WG0n715Bgsuu0FDnKya67Rf7Z/WvIv5aPSaUwpc0kH39a+3iMLdZG/xwT32mxjdmWvibVtolvGdsmvjMdJr51wBbAxjAaBPCytnvuZMzGXThsYSkBe9Nq6v5z9BEt/a7muYAdO3u+NfGdFtuYbelrUm2b+JaxHdJn+uZmE98Dx7KIbw0CKiYuYzGsRHYKbVdLMsaC2cZa+hdbQErCrlO2/9Is87qqaXxoqA8NmPhOi23MtvQ1qbZNfMvYDukz9rbzgIMtvksvCiwBpUX8MxKCXHWsJaFg7+bHwK47tv9QmG3HEr9a2ihHOUNssv0b8Whc75jjdtn7nYnvtNjGbEtfk2rbxLeM7ZA+Y4+dBxylxDd7QfKNr0bx62MzZyJdo/gsiQYRo1XA1dwnWLFr6E8lYJeT7d8nNk2bQcbhdOupdH9it5Okf6m6M/GdFtuYbelrUm2b+JaxbeI70zGvrJrF57ISsyBpXBBzoyXOvrpni99STGncs8fdFKipPjTFWmo8D/kpPZfkqHt2e7L9xxDS73L20UV1t8i3ie+02MZsS1+TatvEt4xtE9+Zjvkz+uzkvFa0iBsmtSQT7DsRfbEsy12QXKQmYzl95/afCqNPaK6PEErV3ZAftv/cNnP0kylsmrHjCfHfdy6735YW3zu3HTz0b4zPLkP2YsX3zm0He2Mbi3vIdvua7vXta8bOk4wnRnz7+vEtw5C/sfpJFd++tn3LauI70xHz2DlzAWAvPkNojUsKDUlzrjqeetvlhFV3of2R3caa5sxSY3nMD7s9YtFQd7WiRfyyxH9KnIx4JOueXZ9z/6XFd4hw6bve929j4lLivO7fpMSu9niG/KTa9r1mjJg2Ti3rIkx8BxwhkxFzAmVP3t04tIuN3HGUTIamXPZU/9YfuW2SQu7YF7VRiv+Qa1kCasr+U2DHw/YfAmPOHRu3JepuynO7ie+487p/Cy13zO80xDPkJ9W27zVjxLRxalkXsXfv3i3j1sT3wCH1wrWpi4ApL0i1tF0tcZbyXzKmobpPbRPf69n9XtJ/6f5Uc+wp/jXHyhJwGtawEuRoe3Z/Ks0U11sT33Hndf8WWu6Y32mIZ8hPqm3fa8aIaePUsi5iYI253XnqUbogLnmkim8tCxJroagZLW1XI4y6Y/TxXOX0tctOorWMEeb81ufb5lt/2nVV88aLFv+sTbOa0TKPhZCj7Ux8x53X/VtouWN+pyGeIT+ptn2vGSOmjVPLugi78x1w1H7nOxSNcWqMKReSZdWQUCxT2+XAt/7Y9azxLlDumDSMr3YcLAGXA7b/FHxiZ2+aaUDjplVJ/+xx23euie+487p/yyV2tcUz5CfVtu81Y8S0cWpZF2Gf+Q44Sn3PN5tFC3epRantp7ZkIoWcZWUnNDVjdVcfpecNjRsPJW0u8xiZ4nrF2rQqXXcs8cset2PnmviOO6/7t9Byx/xOQzxDflJt+14zRkwbp5Z1ESa+A46S3/M9NilOKcEL9VN7cpe6G70saCr7VBJpo040jYUhtIyReRwrKyvF4pnieqVh04qdZ5W0ye4nff5NfMed1/1baLljfqchniE/qbZ9rxkjpo1Ty7oIE98BB+N7vjXuppdaKDQuSKm22G3ni8ZkiN0fjHBq6/easLrzZ6iu5iK8RJ2x56dl9p+6XqXGzlovc7Fmd77Vi11t8Qz5SbXte80YMW2cWtZFmPgOOJblsfMp47Mg5kx6tS/IQ2VnioCSIkSD4GFt+mjp9+xEdu6r5N3Trm9Nm16abPr6lPLBmq+1jNuUWEtsfLDXK81zZopPwL7nO/a87t9Cyx3zOw3xDPlJte17zRgxbZxa1kXYC9cCjqmIb0ZCoTVBqCkRZDO18oyRo6yLbE4tkQtFayLNFBFTaHu2/xjY61U3jhJ+cwg4Zt2VRLKdNGy8rNmd7+jzun8LLXfM7zTEM+Qn1bbvNWPEtHFqWRcxkNvYV431HTWJb3Yi246hbb/GZCLW7zJtNNQAq+9Ze6SjRZTFwBKfNfU7rbHW3O98ySngaq67muLPEauJ77jzun/LJXa1xTPkJ9W27zVjxLRxalkXYY+dBxwhk9HYgsYWoLn9sxOpnP5rSqQZyYPWti8VE7v87RgkfbL6vQTLugk3BUq33dTmzJrGbdf/Mo1bdt33YeI77rzu30LLHfM7DfEM+Um17XvNGDFtnFrWRZj4Djhi7ny3J1VLxsrCFr850LhI98GOcxn95+ijITa1jZHSn9keKn/Jl37lgCHgSvelXP5Y4lfLWPRhKNZl2CyV9h9rr6/vmfiOO6/7t9Byx/xOQzxDflJt+14zRkwbp5Z1ESa+Aw6px87ZwsBYTtj9ju0/FWb8NdUdK1Yt4ncq/aTmjZe5X219MTSOqfQl7Uxt48O3PGNzponvuPO6f8sldrXFM+Qn1bbvNWPEtHFqWRdh4jvgqOkz31OgvYBoWNBKoWU3XIoY/5oSP2b9sdtOCk3tWRs+dZezn4S0nTaxW3rcSIl/5pxZ+5yjJf4a57x23Zn4jjuv+7fQcsf8TkM8Q35SbfteM0ZMG6eWdREmvgMOLeK75KQ+91XyEc6xxZNRdklfzEQ2dTd8mcRmX13V3vcYaGnPFLQJylABxuxLpX1Lid9YvzZn8p86GIqnJl+h9nL4N/Edd173b6HljvmdhniG/KTa9r1mjJg2Ti3rIgY2iO1t530HQ3y3J9WSi+yQr5KPcLLEb4561pIghaAladfQ70uLByn/IfamVvbUOLR8ZrxE23evSS2jlrb0RSpetuBkMFR3tY4bpu9QeznLbuI77rzu30LLHfM7DfEM+Um17XvNGDFtnFrWRdj3fAccJcX32KRacoGfSjKhJRmssT6Xse6kfbHbPcR/TbHm8Ns9av/MuI+9XGM8tCza+h47npKklpVdd8w5m71e5Kh7E99x53X/lkvsaotnyE+qbd9rxohp49SyLsIeOw845pVVswhgwy5PzW23THU3FbRsXNROzeO2JpZ942NRPDX0idDYtZaVJd5LP/EiSWxb9tW1ie+487p/yyV2tcUz5CfVtu81Y8S0cWpZF2HiO+DYsWNHdZOylt3omhe0Nj71J53MSC6opWALmD7/TAHHGne1b/zE9H1tdc8eCyks+3qRWv7Q6yXrm+k7BlbbS6/XbZu+azSrn4/5N/Edd173b6HljvmdhniG/KTa9r1mjJg2Ti3rIuyx84Aj5s63tqSVvaDV+plxCREgFYPmBX3Md4mx4Nvvc8UhXfeh9pj+tSaS7DmvdH1IjLPYtmTNeaXiCfXLGrc1kavsoW0/pXETStf/monv6PO6fwstd8zvNMQz5CfVtu81Y8S0cWpZFzGQH9gL1/qOkMlIy2KqbVIv6TNH3bPrsxba9TSFscBI5HLay+lfW6yl42G1fY5xxvQdwzwO1p3z1L6X2nck+x57zguF3faSsOqyPY5NfMed1/1baLljfqchniE/qbZ9rxkjpo1Ty7qI7p3v+c/OU4/SBXHJQ+qFa+xFKoWaYq8p1hKw66MmAdeNo+ZETgNa2jMGDYlwbXfOS8Mep5L+Y2wx/Q+dX+opN63+S7V9+zqpsq5lvPO9c9tBt3PbwdFruud1fwYe+rd9zVA8Y9fECLOhMvTZaF/TF0OsAPSJp+0zdzxD5U617XvNGDFtPPS7sTr1jce5hz7z3R3zzlOPFhfAzCNVfEtM0suaCNpudrpf9oLuw1isNYqCWHIkUyFtLjXO2KIoBvac022rlL4Qcm2OtlqmMStNbXWnbdyUtsXwn3N+zSW+c4qw1HiGrve102dDolw12Aktt3Q8Y8S2ca54nNs6vuZj2TnF4hvAowG8H8DnZv8eM3DeNwBcOzsub/1+N4CPA7gZwDsBPNzHL+POt7YFrVRCMLSo1PiZcS3iV8OCHgMjHlbiq0X8MhN/bXW/THfQ2tdKiO7Ufle6L2jzX9IWa70ZOp8xD2hb+2KRqDsT3+F2+mxIlKsGO6Hllo5njNg2zhWPc1vvfM/+1f3CNQCvA3De7OfzAPzmwHlfHfj9nwL4idnPrwfwX338avie7xoTQYk4SiYEucpem/jVkAyNxZPTB6vtY8/PbY9Z97V/zzbTP7ssvgy1fak5UKv/GH+httjrDbvuu3GsraU/ZRVzvcRYjW3LPt8mvsPt9NmQKFcNdkLLLR3PGLFtnCse55wb+vYs53SL75sA7Jj9vAPATQPnbRHfABoAdwI4Yvb/pwK4wsdvSfE9h508sf1LEbMo1SBYSvhnJ2cMpNq+9o9LMNteMpEsSdc/O54USsfOrjt2W2naeGHXfSn/knNcSp4hOc/61t2Q75WVFRPfEfH02ZASc9rthJZbOp4xYts4VzzOPbS51c0RndMtvu9t/dy0/98570EAGwA+BuBHZ797LICbW+d8B4AbRnydO7Oxcfzxxzvn+At0CNpiXYYFPZdgSV1QS/cBZt+bQiInEYeU31B7jLYfSySZbV+6L0jUfUo/XsZx3/Uv0e4xsTPbXtucW7ru2tfH2mKPu7Z/E9/hdvpsSJSrBjuh5ZaOZ4zYNs4Vj3OKP/MN4AMAbug5zuqKbQD3DNg4bvbvHgAHAJwQKr7bx9BjAmOTHSsRYSei3ThK3wHMIYJYAkQqGSoFs+9NSQCl+C1dXi3+2zFIzTlMMRkCu+6Z/tnjPofojskzJMvs2+/Zde8TR84xz841co07E9/hdvpsSJSrBjuh5ZaOZ4zYNs4Vj3P94wsVfObb67HzzjWXADgbAo+d+0yMJn51lV9iIWQKinYc2kVAFy31l0JtYprdV9r+NcUScx2z38bErqW+2XXXjiXGL7vuU/zH1r1kfTH7IWPMaxl3sXNu9xoT3+F2+mxIiTntdkLLLR3PGLFtnCse57a+cG2ujZzTLb4vxOEvXHtdzznHAHjE7OfHYvPN6KfM/n8ZDn/h2s/5+I35zDdL/OYidFKXXpDYC1wK7NjZbRcK2387Btu0ircRUndMwaut7tn1wBKQTNh1L0lI3TPHXTeGWPE4Jf+pNiTmXBPf4Xb6bEiJOe12QsstHc8YsW2cKx7n6n3h2mMAfHAmqD8A4NGz3+8D8KbZz98P4HoA183+/dnW9XsA/AM2v2rssrlIX3RIvHCttmRkDmtxZm9eMBZE6bpm+5eKlyk+S49bKX+1tX03DkYinOov9nrJupdMwpeh7XPMOSGxa6z70j7Hjpzx5Kh7ibYvPQd1cywT3+F2+mxIlKsGO6Hllo5njNg2zhWPc5U+ds46GG87Z8MSIUMLEvvlSaUW5JjztfuPoXRSqiUJlial7Vn9oLa2kEqiJcV/jC1W20uLMG1CMkSIaejjqX0nxV+Kb1bdS4x/DXPePAYT3+F2+mxIlKsGO6Hllo5njNg2zhWPc5U+ds46lumrxjQsAu04WMkI278GNPSF0u0gKYBy2CtBSrtLxltaBKQikYRL+k0RQiG2pPznEmGMuq9xnmS2vWS8NfsPacdcdW/iO9xOnw2JctVgJ7Tc0vGMEdvGueJxrtLHzllHSfE9NKHW+NlPJuyFmYl02/na0yDWx+LIGcuYzxj/oXWZo+41JIK+aBvvqWOwto0HTf5Lr5Vt36ntLSV+S/edKdT9WuKmT6h/qTlTuu5NfIfb6bMhUa4a7ISWWzqeMWLbOFc8zm39nu+dO3c6E98Dx969e4snFt0JVUNCGQIrfnYSLilCNAiwGFhtwG77dgxS/kLtaRFAsYmslH8N4yAUydhrFO+xSIuYGucsafFequ6GrltZWYnyL1VnNY076bo38R1up8+GRLlqsBNabul4xoht41zxOGd3voMO1oIWw9hiViIGtv9uHBL+2IlsbQIsNRapZERD+WtDou5i5j/mnMmOJYfoZtU9238K8ziW+e5tatljyxG7ST+Wb+SOeVEMpda91LazF64NX+9rp8+GRLlqsBNabul4xoht41zxOLf1M9+z43bnTHxvOWIfO2eKgO6EXDqxYYtfCZhJ4TIKSG1JuKQY8r1uGft6Xxxays/cdEtBUszFXBNzvdRaFTvmpPp+ybqXir328c/oO+y6H7ou9KmBrj0T3+F2+mxIlKsGO6Hllo5njNg2zhWPc3bnO+hI+cx37YsaC0kBJBVLSdEtUWYtfS+U1CQ+1S8jodLS7hrGHbPfxva3sXqrYczNial7tnhl172U/xr7ffd6xlMDEqSId3bdpW482J3v4et97fTZkChXDXZCyy0dzxixbZwrHuc273z3zfXOmfjectj3fJdLCDQk/+04UnxKiCCJMvvaWpREmgDzu04iAS/Z7iViye1f27xR46PLqbbYAizW/1Dfif3cMePR7dj5MnWeXbRmxPpPvXtbsu1ZdT9kL7XTbTZGAAAgAElEQVTsJr7D7fTZkChXDXZCyy0dzxixbZwrHudMfAcdrO/5Zia/Xd+lY2ElkjlEX211174+JRFki4DY+FNh+lzGzRKfOJibCCHE3MXSXvehYoDVTqzH3mOvkbQjuWbEIH33tlTfkxx7qTGk3jmfbziY+A6302dDolw12Aktt3Q8Y8S2ca54nDt8fLXmD/vMd99RWnyPJZC5E6spiM+u35iysJORGFvsJJwtfJjjRhJmv02F3Qf6Ygnxy35HRveIfXFUSNml543QemfPW0PxlBBiWsrO3HhIQWLcdG2lCOfYTZeYul+03sVeb+I73E6fDYly1WAntNzS8YwR28a54nGuf3MLwIZzJr63HIyvGuvCWtRSEzC2EAtNRBfZ8j1XosyxtrT0VQ1tn2qjZPySiWRqDBLllBg3tdX93E7sXajU+pf47KrUY9slxGubKWyclK771NhTBWDXjtTd2xBy1WFIGdo2Yq+Tit/Ed7idPhsS5arBTmi5peMZI7aNc8XjnInvoIMlIlJhiDCGaMnlP8UWS8RIXKsl9tKwNw26ccT6jOm37HHbjWNNYNMs1X/Mdaz+Iy0AUpL41LKG2pEQv87xHl0eK0Mp8ZradnO/27dvD6r71HGTOmdL1Ttr3OWI38R3uJ0+GxLlqsFOaLml4xkjto1zxeOcie+gI/bON0t4LFrQSiaDUxBwUmKoZN+pUYClJlLScZQWEVKkJOJSySx7rKaKkNoEqNR1NYv32LYfirvUEye5BGAJAbco11hkQ2rNaduJfVqFIcCHNnxSr/etg507d2651sR3uJ0+GxLlqsFOaLml4xkjto1zxeNcuvhuNs9fDvbt2+c2Nja8z9+/fz/OP//83r+tra1h//79QpH5M48pxn/KtbGw61CizENlGLMZc400jPbu89+HT0zt+AEUL8vq6iquuuqqLb8PjSG0HaT7Toh/LeN1iNx1L4VUG8bGLznvpfbblZUVrK+ve/tNHXfz60P9zmmXI7beu4TYYftv24mNO8Z3yvVSa03MtRLXz5Hqu2tra7jooouwa9euhdfccccdOPbYYwEAt99+O774xS9ix44dePzjHx/sP5Z2DCzYMbD9WwxhMRw4cAB33nnnYb9rmuYTzrl9Xk58VfoUjtgXrkneySt5Ryl1NzuX79Q7IrnvAkj4T7lGkph60Np27L7LuhNTos7Hro+Jf34t4+uaUq7rXh9adqm+I/G555T5KsVvbOypdSc13qTqPaXfSpchpv1inxiYP7K+fft272vG6t4njtS2k2571nofA+tbgCwGXf4thvQYYI+dy4pvCXKIwVDfzO8tlRC9KYvq2lrYZ0+l24u9KEsm4qX7bWjbda+vVQDG2mH23bE+E1MGLeKllHiWaDtpG7X4di7t8d1cAi617/naSH10OcejzwDczp07va6fkzJvpvSdZaVmsTOlGNj+LYb0GEx8KxHfbPGSilQiLRFDrABr20hJqFKFCyMJ77NX8nop8RmKtABktZ1UMs96eVOMDbb4jY176HqJz6xLiN8S/X7ITsh1qQKwG3+o8OvGEOJ37HO/PnYkyt62IzVmYp/4qSHHMeoWO1OKge3fYkiPwcT3UGHJAqzWxSg1kUzxKSn4U9pBSkTEJrCpX90iWY+LkBAAknGkCqCS/b7tVyoJZm8exNQb69HlVKQ2TFLXKqbwTrGR41rf9peat2I3TlLRMG6N+rj44ovZIVgMCvxbDOkxmPgeOELfdp5DAMbAEgFSlBS9ua5PTWZL+2eLkEVxjMXPjl3LxgnzepaAkkJq3JWuuz4bKfOmVOy+dtiPPnftlH5Pg2EYhrGcmPgeEd8xtBO5krvCY4lQjADUcgevREIjnUSx7gZo2XhhbIJIPTpca7+X3niJFe8sEcMQkKltJ11uqY2PUtfbo8uGYRjGMmLiW1h8OyebVNUmAqTiYL34KgUpn6F2pAVUivBiCsCYMkj3+9Q6ZHzmWqOAk2g/pn/f63O99KvUW7/bNmqaqw3DMAyDhYnvDOI7hqmIXynxHEvKHdDYRFRKPEp95lpKgJZ6fHMshhICqm0jtr9K3Xkv3ffYGzepMaSK7zmxfTf1rc3Sc0fsxy1MABuG4Zxzd911lzvzzDPdiSee6M4880x399139553ySWXuBNPPNGdeOKJ7pJLLjn0+x/+4R92p556qjvllFPci170Ivfggw8WjeFrX/uae9aznuW+8zu/051yyinu5S9/ebD/1Bicc+7Xfu3X3BOe8AR31FFHBfn9m7/5G3fyySe7E044wV1wwQVb/n7//fe7c845x51wwgnuKU95ivv85z9/6G+vfe1r3QknnOBOPvlk97d/+7dBfiViuPPOO93q6qo76qij3Itf/OLi/t/3vve5M844wz3pSU9yZ5xxhvvgBz9YPIaPf/zj7rTTTnOnnXaaO/XUU9273vWuXvsmvpWI7zls8RoLe/NASkC2bZW6kyMtgGLtSL+4KkWIlS5710Zq26WKx5RHt0vWHVv85+rzJTeeDMMwtPCyl73skNi44IIL3K/+6q9uOeeuu+5yu3fvdnfddZe7++673e7duw+J0/vuu88559w3v/lN99znPte9/e1vLxrD1772NfehD33IOefc17/+dfe0pz3N/fVf/3XRGJxz7qMf/ai7/fbbg8T3gw8+6Pbs2eNuueUW9/Wvf92deuqp7sYbbzzsnN///d93L3rRi5xzzr397W9355xzjnPOuRtvvNGdeuqp7v7773e33nqr27NnT9TGR0oMX/3qV93f/d3fuT/4gz+IFt8p/q+55hp32223Oeecu/76693jH//44jF87Wtfcw888IBzzrnbb7/dHXvssYf+38bEtzLxnQr7DoaUcE1NxksKv+71pTceuv5T/cXYYYnfIRsSsZcSgakCMId4lri+xFujpTeuWPOmYRiGBk4++WR3++23O+c2xcPJJ5+85Zy3ve1t7txzzz30/3PPPde97W1vO+ycf//3f3fPfvaz3Tve8Q5aDM4599KXvtS94Q1voMUQIr4/8pGPuGc84xmH/v/a177Wvfa1rz3snGc84xnuIx/5iHPOuQceeMA95jGPcd/85je3nNs+L4SUGOa85S1viRbfEv6d29z8OeaYY9z9999Pi+HWW291j3vc40x8hxypyeDaWt0vXCudhErdAWzbShVOpV/8EyskNMZfk/iVuL5ro9TGxVjdlXz0mdV3DMMwDDm2b99+6OdvfvObh/1/zoUXXuhe/epXH/r/q171KnfhhRce+v8znvEMd/TRR7vnPe95UXdfJWJwzrl77rnH7d69291yyy20GELE92WXXeZ+9md/9tD/3/rWt24RsU984hPdwYMHD/1/z5497o477nAvfvGL3R/90R8d+v3P/MzPuMsuu8zbt0QMc1LEt4T/uZ2nP/3plBg+9rGPuVNOOcUdddRRIo+dPwxLxN69e7G2tgYAWFtbg3MO+/fvHzx///79aJoG559/PgDg/PPPP+znpmlGr+/aWV1d9b5mfp1z7lDMKysr3rEPxd80zaHDN46uvdj453Gvr68H+wyt967vOVdddZX39Sl1171+zsrKinfbOecOtblk/CF9th1/SJ9PZf/+/VvqDtjsQz7+V1dXe69fWVlJKn+pss8n6Hn7z/vNgQMHgm20j5D45zZiy9yOoUS9GYZhLCtnnnkmnvSkJ2053vve9x523jwPCOWKK67AF7/4RXz961/Hhz70IUoMDz74IJ73vOfhpS99Kfbs2UOJweBw44034uUvfzkuvvhiiv/v/d7vxY033oirr74aF1xwAe6///40g74qfQqHxFeNxVw3dJR6jHJ+XehnziXjj4ld6vHTWP99cZSq+yE7ode3H38ufee6ayfkrn2q/9S+I/W5YcMwDMNgIvnI96WXXhp1B1Qihp/+6Z92P//zPx/sWzIG5+yx89L+Dx486E466ST34Q9/OMq/RAxtfuAHfsBdffXVW34Pe+xcVnxLISGgUkVoDCkCsubHX6UfW46xIb3xw4idIZ67dkpvehiGYRiGBn7lV37lsBeNvexlL9tyzl133eV27drl7r77bnf33Xe7Xbt2ubvuust95StfOSRYH3jgAXfOOee43/u93ysag3POvfKVr3TPfe5z3Te+8Y1g31IxzAkR3w888IDbvXu3u/XWWw+96OuGG2447JyLLrrosBd9/fiP/7hzzrkbbrjhsBeu7d69O+qR/5QY5qSI7xT/99xzjzv11FPdn//5n0f5lojh1ltvPfQZ7wMHDrgdO3ZseSTeORPfasV3KJJ3ftv2UoRc6TvHKddL3L1lCUiJ2FO/MqkbS+mNi1jfhmEYhmFscuedd7of/MEfdCeeeKJ7+tOffkhMXn311Yd9DvbNb36zO+GEE9wJJ5zg/vAP/9A559y//Mu/uH379rnv/u7vdk984hPdS17ykt6XTeWM4eDBgw6A+67v+q5DX/n0xje+sWgMzm2+Lf24445zTdO44447zjsv+au/+it30kknuT179rjXvOY1zjnnfv3Xf929973vdc4592//9m/u7LPPdieccIL7nu/5nsM+z/6a17zG7dmzx5188slRb3iXiGHnzp3umGOOcUcddZQ77rjjtrwlPKf/V7/61e6Rj3zkoXY/7bTT3Je+9KWidfDWt77VnXLKKe60005zT37yk9273/3uXvsmvocKGyEGpEVEyrWlHxtPFYC57pyW8p/66DH7+jkmYA3DMAzDMAwjDya+B469e/cWv4uXS0DGiNjUO+Ypd01TNi/aIjTmM7fSn3sucddc4nrDMAzDMAzDMPJi4nuosEThou3R6xJ3f3N913HJjQsN2J1rwzAMwzAMw9BJiPheqq8aA8K/cmnO/KuHUr9qac3zq5L6/M8bLebrgrZv3w4A2L59e7CNWNbX17d8VRaw+XVZq6ur2f0PEdsGLFK/8skwDMMwDMMwDAX4qvQpHIh4dDn17unQ3V/f68di8Lle6qVb83LEftVSyt3b1KcGDMMwDMMwDMMwcgC78z3OVVddVewO9vr6OtbW1qL97Nq1C+eff/6W3+/cudPL/wte8IKg3w+xvr4O5xzW19eDrpuTcvc29q6/YRiGYRiGYRiGFpZSfIewf//+XvF8/vnnewnB/fv394pnX/F+4MABOOewc+dOAJui2zmHAwcOLLx27r9v18VErGEYhmEYhmEYRjlMfC9gSDyHXO+cOyTg19bWosTvXIT7im7DMAzDMAzDMAxDD83mY+rLQdM0Doh74dZchNf2si7DMAzDMAzDMAwjD03TfMI5t8/r3GUS3/v27XMbGxvsMAzDMAzDMAzDMIwJECK+7bFzwzAMwzAMwzAMw8iMiW/DMAzDMAzDMAzDyIyJb8MwDMMwDMMwDMPIjIlvwzAMwzAMwzAMw8iMiW/DMAzDMAzDMAzDyIyJb8MwDMMwDMMwDMPIjIlvwzAMwzAMwzAMw8jM5MV30zTnNk2z0TTNxh133MEOxzAMwzAMwzAMw1hCJi++nXNvcM7tc87tO/bYY9nhGIZhGIZhGIZhGEvI5MW3YRiGYRiGYRiGYbA5gh1ASQ4cOIB9+/axwzAMwzAMwzAMwzCmwRm+Jy6V+N61axc2NjbYYRiGYRiGYRiGYRgToGmaa3zPtcfODcMwDMMwDMMwDCMzasV30zTPbJrmpqZpbm6a5ryBc85pmubTTdPc2DTN20rHaBiGYRiGYRiGYRg+qHzsvGmabQB+H8APAfgCgKubprncOffp1jknAXgFgP/DOXdP0zSP40RrGIZhGIZhGIZhGONovfP9FAA3O+dudc79O4B3ADirc84LAfy+c+4eAHDO/WvhGA3DMAzDMAzDMAzDC63i+zgAB1v//8Lsd21OBnBy0zR/3zTNx5qmeWafoaZpzm2aZqNpmo077rhj0OH+1XU0zea/hmEYhmEYhmEYhiGJVvHtwxEATgKwCuB5AN7YNM3R3ZOcc29wzu1zzu079thjtxiZi+7zr1oFsPlv0wBNA6wefe3CIObX9x0hQn716Gu9fRqGYRiGYRiGYRh1oVV83wbgO1r/f8Lsd22+AOBy59wDzrnPA/gsNsX4FuYvbwsNYvX0e0MvCWbXEV9A0wBX3Xc6gM1/Q8T7XLR3D18RP7R5EPoEQMrmQepTB/bUgmEYhmEYhmEY2tEqvq8GcFLTNLubpnk4gJ8AcHnnnPdg8643mqZ5LDYfQ7+1a6j18rb/EBLA2so69q+vBgceev2BB5+AtZX1aD9DGwRX3Xe6lxi95MMnBv2+y9HNfb2bB0c39y28duypg5CNh9jrtWCbB4ZhGIZhGIYxfVSKb+fcgwBeAuAKAJ8B8KfOuRubpnlV0zTPmZ12BYC7mqb5NIArAbzMOXdXj7lDL2/r87V/fbVX/J5/1aqXGEq+fnX9kHhskyr+fXnB024O+n2b/avruA/bt/x+bWUd97qtv5cm9ckEqbv+86cXdh3xhaDr5hsX3c0Dn42LNvbkgGEYhmEYhmFUgHNu0geAswG8yTmHvXv3ui5rK1c6wG05nr/93VvO7WPoemDzbz48f/u7o67PGbtv/EM2Uq4NqbsU/yvbP5nkf+e2g+Lx+1435n/ntoNe1w+Vf2X7J6NijylD20bsdbG+DcMwDMMwDCMVABvOV5v6nljrsUh8z4kRwBrEb2zsOeP3vX5OWwSWFGCp4j/XxkNK25Xa+Bi73ke8p258pF4vJd7ndmKvs80DwzAMwzCMugkR3yofOxem+/K2Xi6590d7U/mxR7/3r6/CORx67HxtZR3ObdryYX79/Oja8X3sfNfpmy95X9l+bdD1Xf/zIzT+7mP3l973o16PMc8fd55/Xhx46NHrlEegQz4y8Pzt74nyMfRxgRD/OXj+9vcU+bjCEGsr61i/9/SF56V+ZGD93tOT3pWwfu2WL0YA4N92848adD8y4PvRg5R3LYx9w0KJb2iQ+riGYRiGYRjGsrEM4vvQy9u6fxhKIleb9ahEsv3CrxDxOT+GxNyi6+fXzUXsgWvDhM0Ljn5PVDLd9T8nVPzHfma+73pv37PYL73v8I2G529/T9TGxXzjY2X7tVHXh268pG58DJH6roHUdyX4Mrb54UOK+N+/uo5/+sYTev/m+66EvuvXVtZx4MF+u4ddP1J3Jb6hYYjzr1r1Ev9D39Dg22/nGx/dw3fjI/UbIqSwr5c0DMMwjCXE9xZ5zQeAZwH47Nhj5zGPgUo9dj23M3+UttQjrNKP3kr596m/RY9t+5ZD+pH9Zb++xLsStHxcQmPfYX/koMQj/6n+U991kHL9WOw+72qQeE9G2459XMIwDMMw0oF95rv/GBLfsYmIFNJJfGw5QutBevMhJu72tSF2tG2cpLYZy39s35WIIdW39KZRqeu7dmLaPpcAzi3e2XWf+q4Dze9aSLm+1EsaJda8tg3fuCWRmvNtw8MwDEMPJr4Hjq74HlrIV3BlkYVRq3iOTYhS45aqhxJI1V3XHmvjI0UISN098x13Wu58szZOtD61wBD/8zf+h4qo1I2bs7b9RdL1sS+Z7Ls+pOzspw5SvqEh58ZHiacOcr1kstTGR+q3axiGYUwZE98DR6nHziWTGoaID0Wy7lJiltj4SNl4iYk1td9I3Hlux5N6943R70vftWdvvHSvi33qIaXvtGOW6DulviGCvfGQ8857DWtNrqceUuetZbg+18clYjacQv33xSGx6RRqh4099WAYejHxPXCMiW8tMCZXKQEUE7v03dOY+FcQX/5UamvvRTZLbxZJ9N3UR/ZLi18J8S8tnkP9S31kILbPpvZBxqaXROy5xK+PiBm6/qxtf+Fddufinzpgbhywr5faMOza0VB3KU8tpG4c+NpI3XiQeuogdd6cl6OmDQvDKIWJ74HD97HzUiIk5Zr2dSnxM31LxMLaCZYSIX02cyeRUrYk615CAKY+tp4q5ErceezzyRDPsUjVPes9GUPXs+/c19DvU+NIrfs5Ek98SMUeuvGQuuljL4mc1vW+7Z7r4x7Mj4uU2jjp2ondeJDaMC6d6xr+mPgeOKQfO0+9nimi2OKZLQLacaTc+ZaYEDUl1Cnxlho3kkiO29jYaxo3qRsfPrZKzZlte6n9tUTb910Tc73UUwdS7yoIFc9de+yNkxJ1L1V3sW23KA6W+JcYt9rFd86Nj9T42XVX4iMTQxsXvtenPvWwHff2Xr8d93pdL/FxD+fKb7bWiInvgUP6sXO2gNWCxMSckjzHiGfmhMDuN1PyL9X3So07reK5xrpP8c8QoKltL913WBsPse02Ff8xsAVYro2L0LpLfdGh5OZD6XGjceMide5jivdSGzcpd941173PUw+p366R+nGL0i+pNPE9cOT6zLdE4h7ayNICiu2/bTNlUij1wrRuHCUFXJ/vVBuS7RjqO7Tuci2mJTfN2JtssZtWEn4lfLL6joQdDW2fMmdJb5aw73ynrpklNl5ifPr4L/XtGLnEe0j8sXOe9KZP6W+3mCMt3n0/MsEWkM7Jfy1patul1p1vv0995J6da+Xa+Mj17RgmvgeOnN/znboolUgAfK5nJIZMARiLVDKVyzfDf6lHj7vXatj0Sq1737Iw+92Y/xofO5dq+1o2/FL7jlT52d8yECuC5tdKbVqlbnzEXM+6e9q1U7LupfptN3apcccS77VvvJSoe/b1c1hfjZkqfmu+PqbfTkJ8A3gmgJsA3AzgvJHzfgyAA7BvkU1N3/MtLTilEsla/ccimUyF+BybkGP9l944kU6GSsQ9NqGGxCC16ZWaDEsJsJi+xhQhzOsl/OW4A1dy3GkYw7FxMwRcrrYLrfsU8euc/B3Ekv2WNe66dmLnx9Q8gb3xEuNfqu5T0faiwxpe8Dlkq9SmEWPjpHrxDWAbgFsA7AHwcADXATil57xHAfhfAD4WI759KlqreJ0K2hLZknexSovlrt++Sa22Phc7bqTqnj1vpMCIhSkAc5RXYuOjljvnUn5T658p4FLRVvclxo3WcVd6ndcy7mM3Xrp2StZ9ro2L2Hmj5MclnOO9JHOsDLk3HlKvZ2waTUF8PxXAFa3/vwLAK3rO+x0APwJgPVV8a8F3ktEi/qUTCFb5Y2JMmdRz+C/V9lMTUBKU3kiZ+5P4vumY2CXKy2r71LqL3fCTQsI/W8BKrDfSCbmvmND0rgSJcRDaZ+bnp1wvIeBKlV3SP2PcLYo/xnepskteH4NU+Wu8851r46LkfC15vc/5UxDfZwN4U+v/PwXgos45ZwD489nPg+IbwLkANgBsHH/88V6VvUwwEpgS9lJiKJWMdO3ETswSyVAMbAEoAVv8S/kv9dQCOxHOga9/6WRCSoQw7qCV/siB1rpnzVcpmw9SMcTURc0Cil33KeNOIl6Jdi8952lp+/k1jK/4k4pdqu1840/deOjamb85PfVN52OxT158A3jYTHDvmv0/+M73WGdO6aC+nUtrEp+6mJROplJilJiUJeIoLd6Zbc/ud0PnszYuUts+1m/fghbrny2eQ9EmWkrNORoEpHTd17DejPkvEQt7vZOseykRUpIcbc/s9zVuWvXFxMw1meKXOe401H3OMTcF8T362DmA7QDuBHBgdtwP4PZFAnzRY+caJgrppL4UsXWXEm/foA7xX1tdTQmputey8ZAr3txxSDy1EOpTKhFlt72WtgxlbaX8HbTUumILSJ9YcgkoKWI3/KTLGzrnDPkv9cSHxo2T2M1S9pzZtpkiIEuNeUn/UnXP/mYR5rfaxMyZ0mvWWOxTEN9HALgVwO7WC9eeOHJ+8c98Ty2RY4jnWMZiZeyshSYzUn6ZfS9HWX1s5honoeVhiFct/qXbvrQIiLWndY4uEQt746R7nZZNu9ivq5JOBEvOOVLrXeycm+Iv5eMSKSJAqq5Y681QPCHlZ39Fn1TbhyIxZ0mKZ/Z6xf6GiJzlr158b5YBzwLw2dlbz185+92rADyn51zaC9cY4rPtV7pjsRLhUP9MpBPR1DikFuRU8SudWJbcQElNwtkLWonPfPv2+9Ljt7QISEVy3LLn61BYAk5q3EjPcSXu3tqmlb71hZUrlBb/Oeo+pCwaxx17Do6BMYYk2y42/tBxk118A/g9AL87dMTYLHFofNs5W2wy/fftJC/DAp1LQNW0EZQj1phFmT3uNDz2XesYm4oIKPkVf4x+1/bLantN1Ba7VLxSGy8axXSOjW4Jf6kCMFddh7b92kr5bxnIJZ5LbxiO2fLJ0bpHysZFzJivqe1LiO/njx0xNkscvi9ciyXEJjsZYfpnJx9j/kuKMhNg9Y87qVhZ37HO3NFu+yi5cSI1xtl9qRtHjN+aNuza10nFm5oIM+fsWN/supfKVUp87lnLfM3aNBuKo1TfS/GXq+1iNg6Y603bf6z4lRxnJfota9xO4rHzHEffne++jpkyKZcSEQY/iZ8KKbuiknVXY9tpEa8lyLFpxZ5z23ZjBdgyPPKfS3ym1n1qAp2SyIbE72tP6tycsMV7CDnmrJQ4SvcbrXMmow9oedqH/VGXlDlayxzkS2zbx9ZdMfEN4FgAvwXgrwF8aH6k2Mx5+D52XtOCKO2/hrKzE9FuHKEbNzn8l7I3VQGWI9YYu6XrPjVWdnukwBARqRuGbFJFhLY1o+R4Ya1XuTaNato4ydHvUubsknOOhD3pzYIa1juptvMpj8T5oeWKHbcl5k8t4yZUvJcU3+8D8LMAPgNgBcAfAvjNFJs5D42f+Y6FuaDlmBRqSuKnsChIxllT2/VROpmTFK9aEtEQak8kY9AqwNj+Swqw9nWMvqdl3Gl4aVbbbmzdLcOGo/TGCVsApq5XjPUuZuMgB4xcQSrm2KcOYuueNWeVFN+fmP37qdbvrk6xmfNY9Ni5FOwFObSDahJJy7Cg5vLvU3e1C+WaYde91k2jUokc279WGPOGlHiWTqxzx58So89Rar2SsOMTe0tf6yMAACAASURBVI56Zvhn1B0bdqy+4yZXPLn6jnYBOuZ76u+2KSm+Pzb79woAPwLgyQBuSbGZ8/B94VqJBZm5qExlQSsRa2n/GjdEJFn2vqcNLfVRy8ZRX5zMjYvS9cHYMGyfJ1XWGucMVt8bioNdHz6w11r2uNWwaSZZzzX1vTnzmLU8cRKLxg3HXJtgsZsHJcX3swFsB/AkAFcC+ETf93BrORY9dq6ts9cISzwuS9uxxWtOQvoOIxEdqqeV7Z8sUn+aE7kSG5bda6R28H18axl3qf0+xxhhbhiW9C3dxzWMWwm7pTfM2AJQCkbfDRGAmvMC5sYJ6+5tN66ca62WcTtko1Tdh44be9v5wCH5mW9m59Q8KZb0KykCJPyXbJOhcqaUv4Zkiu2/fb5k3Ydcz0pGxmJhz0Xa0TpnlU5ipPxrEWDaNwyH/LPn3G48Mecuw1rP9i8No99JbVhKfW45Fi1zng9a17vJfNUYgLfMXrJ22JFiM+eR44VrzAVd2jdT/Nc0sWjx3xdLqQW5lNDMAbvduv5LtR1bgHXjkPCrYcMyVUSwYPSH3JuDY9dJJoLsumP7l7BTUoCl2tS0cRLqf1k3ndgbF8z1Vsu40UJo7LFlLSm+f6x1/D8A/gzA76bYzHmUeuHaIrR04qGyT10YsSfldgysumcIoNBzpWGPO7b/bhxakqEQEbSs4lXDnNWOo/aNE8acpWnzIBUtc5kvNYvnVJ+1j5uxOLT2tz6kNn2k4vDxy5pz2P67ccx9LfJNe+wcwMMAfETSpuTh+8K1WGJ3V6Q70SK7uRdOtv+UOFkLIvtzwzUviOz+xPafAjt2pgDT4D82Xk1jLDWmGhPpENiJJHPOZ6837HGrZdMsBg05cvua9ngpUXfMcaul7iUp2fbSZfW1xxTf3wngZkmbkofvY+e1JhO1DS7JemKXvXY01J9vfxg6j53EL/PGDbvuU0nteyk+a52zbLM5HnZMWtouBnbddeNgCbBY/xrqr+TGiWQ+z6w7pvjMGWtpco7bko+dfwXAl1v/fhbAj6XYzHlIve08V8fS3GE1oXlHku1fyn7JRJY97rr2SyfxlghPH/bGxZD/Em03xXGjpd/nvlHAbruc9ZwiAJltX9t6wfI/xTmvbdvHFnvOY/e9vlhyjptJvO0cwDMB3ATgZgDn9fz9lwF8GsCnAHwQwM5FNqVfuMbuWFO7k6AlofGhW0elYx9qo6n2yZwsS9tpGF/SZdSQxLft19Tv5/jGPrX1RjrO3H41CcCaKdWf2P2WnacxN+p97eRui9Q8kb2u9Plf9s3isfJnF98Azhg7Ymx27G8DcAuAPQAeDuA6AKd0zvkBAI+c/fxfAbxzkd0cbztnwJ5Uc8OecJjElp0tQjQsKtqTeLb/bhwlN45yJ021JFOS/msXEew5o/ScmZrIaloX2W3na1fDnMueM4biSe33rDmX7VvCP7Pf+sQ+hY0TxnpRQnxfOTs+CuABABsAPjH7+aMxNjv2nwrgitb/XwHgFSPnPxnA3y+yOxXxnQp78u/GwVgIuwf7c7Ol/HfjYLU5c1JnJYK5yZ0Q5KCWTSP2nDnmf0pjmUHu+huqJ+Z6o6HflrTLnpv7YMfEEDEh7cbsu1rytEXxhfgtWZ/M9Yq5aVTyM9/vAvDdrf8/CcCfpdic2TkbwJta//8pABeNnH8RgP828LdzZ5sDG8cff7xzjr8gsP13z5/abnTIzp70jqZkjAy0xtVGm9hYho0b5oJWAnb8JfxPbb5nr7c1kbreTa3vpMRYKqYpz7nsPIstAHPbzdlHQ+pOUx8toY9Kiu8bfX4XYddbfAP4SQAfA/CIRXa7d777KpexO6ShY0rArjsNC3UppPsOe+PGx7+GTZuQ83LB9t8XyzKMuRQ0b5yUIrXfsvs9c8NWWgCyk3j2euNjV6rsy7hWx8QpCXujvBsHY85IYaj+StQdu+1S+m1J8f12AG8CsDo73gjg7Sk2Z3a9HjsHcCaAzwB4nI/dkMfOS0zKpexOCS11pHU3PDds/zmYYpm6aCkjI4lu/32q5U+JRftcwl5vNW+caOpP2hiruxJ9n9127PHdjSNH3dbW72uZ87rna2o71k0Sn7orKb6PBPBLAN49O34JwJEpNmd2jwBwK4DdrReuPbFzzpNnL2U7ydduLW87ZyWS7ImhBtgLamxcQ+ezduNzwdg0C42NkcR3Y9DeP9l2NfrvazsJ/+yNC3YizfZfAvZ8z8qVcvqOhT1ndePQOO7ZayXbfzeO3EK1BKX6PXN8TeWrxp6Fze8NvwXAK2e/exWA58x+/gCALwG4dnZcvsjm1F64xlzQcvhnL0rMRFrKd40LqoTvENtax83UhLGkby0CkNFGPmUvEZe2flsDY21XYtyxN4unuunWjYMx7lLt+dYd238OSolaVq5Rw5pemhJxlXjb+Z/O/r0em9+zfdgRY7PEUUJ8a+h47InBBx+RllP0shJZdjLkG19NyQQb5qaN79+k/E5N/JYU/8va79l9h+3f95ySsAWYr12tIoK5caLljds+aNtQZt85T83z2PoixH+uDY7cGycpdVxCfO+Y/buz74ixWeKYi++SE+dYp5T2z06GQoRtDQuHRth9p31uiURDU99Z5kSwG4emdhmKSwvWdsP+Jez5xs72L+FrKptu7LYLsat1bmHHxchxa4fd76XyLMacw37k36deSn7m+ygAD5v9fDKA5wD4lhSbOQ+ft537/M3goSWRDY0tly+GwMlZPnYyxPRfok1Z8xo7ic/ddzWvF+xkKhVm22leU9ixteOrrd+UXMs09p3230Pj0V6uHL6msl527WvOs7T6GLNbUnx/AsAjARwH4ACAywD8SYrNnIfPY+dSO0OxsCc2XzQvujmppX1KU1O99PXdUoud5kSw5gWRBbvfa+k7Jewy7gJJ+V7Wfj91ERELc95g57hdHzVterEf+WfXiw/ac52c80FJ8X3N7N+fB/Crs5+vTbGZ86jlbeeLbDOTIfakrAVtyVjJRDKVHP619F3fODX1bQ310o5DWyLNrh/NGycSdaNxTEihPRFtn1PTplsNYzLEjkYBuii+VJslyjXVOYvdb9jlj6HEZm9J8f3J2Xdyf2z+VWAArk+xmfOwt51z7fr6rXlS9vXLSIbYi/mUFwV23bZjqCmJbtv0GRPS9bvsm1YlsLbTSS31p3lOr3nTqwTL2nZD/kPunKfGl+N6y9HHKSm+VwBcDuDls//vAfC7KTZzHiXFt9ZJhz1p1+Bfa9uVjEHbIs7Gt21y15/mBUl73/G5WzDFMa9hXmnHUXKzWKrsGvtOCf/MjZOcbccWEbltsze6tcw5qdQ8Z03Zv0+7SLedT1zFv+cbwCMl7OQ+Ql64FkvJRcUnjiGbrLLn9L8ssNsuB8s8bkLi0pjMaI7NOX58bP81oHW9GjuHvXGipV+ltA1744Dlv1TbLWuukNMHu/wpsGNnt11uSt75fiqATwP459n/TwPwP1Ns5jxKftWYkRf2bnZobJJ2l2HinKq49dnxZSWiOcnpn1k2dr124wj1y94wXeR/ynNOCKkxMkVYDfXLglE37DHvY1vLvDoGs1/7+J56LpVCrropKb4/DuA7AHyy9bsbUmzmPEIeO1/2jmt3AMP9a44thx+NGx8+aEt4StYdOxFmbT5IoHHjZOp3EmrHp+6muuk21Q23Ev6nXD522bpx1HSTJGQ+YddvKjVu9hYV37N/2+L7uhSbOY8avmqs62NoF5k16bMnlhJoFwGLYPWdMd/mXy/sccecc/riYIybWtHSdrHxlULjhqV2/9rja5+zbDchFsGOj71h2Y5B43ri029Zc5bmtltESfH9ZwC+H8A1AL4FwK8AeEeKzZxHTV81ptl3bkqUjZkMsSflRfWbu/4ZO5q5YfpnL4i1M+WytZnieuXbdrXOOVOfV9p+Sq5HIWWrMdfScpMkZ93V2C5ttPb7Gm5SaN30Kim+HwvgTwB8CcC/AvhjAI9JsZnz0PS2c1YyMuUFNSQuzcnMMtZNN4bQHdlScWkW91PftEqFnawt852EVNjryZj9qY879rhJhdF2teRhWm37+M1Vd+w8rZY5eQjmesNuuyLiG8A2AL8Uez3jKCG+a5l0p77o5ISdCLJg76Zr2JFlJvlGP9rnHC0bJz4xauv37PVSyj+zfZd1rWf7b8egLVewtvOPIXZOYOcK2tcUBrn7Vck731enXL/A9jMB3ATgZgDn9fz9EQDeOfv7xwHsWmTT3nY+bdi7amz/pdA+6cfArlsNfcd28uNgC8RFf5PwOdU5jVm+qdStVgEp7WdK467rp+RarqXf19p2pfLQvvphz9e5SS1fSfH93wFcBOD/BHDG/EixObO7DcAtAPYAeDiA6wCc0jnn5wC8fvbzTwB45yK7Pt/zraVz1ShgSqClfZjE7siyFwUm7NjY/jXHxu63qfEx/WuOTQPa43NOv3hliRR222kYd7Fr/aLrc8enGc39qiQpfWvqc0Js3ZQU31f2HB9KsTmz+1QAV7T+/woAr+iccwWAp85+PgLAnQCaMbsSXzXGFjDL7j8nWibFVBi72SHk9K+97DWiZVyw71RYIhuOlvViinWbG3ai6/v33P5TbGoVCVJ+mSJpqmOa3XY5kfLN6veL/BcT37kOAGcDeFPr/z8F4KLOOTcAeELr/7cAeGyPrXMBbADY+O3f/u2U+jYmxAtfODwg//Hv78ju/4wznHv9C68+7HdXvuXzDnDuttse+t3GxvQWl42NzZnn4otl7QKb7drmT877lKwT59za2tY2ue0fv9xbpt967t+L++9j4/LbHLBZt4diui1P3ylVpily8cVuSzt9+Y77NxfytcPP7c4PMXT7/wtfOFv1O6ytXOkuvzzZ3UIkylSS2/7xyw/9fJvrbaczztg82lz5ls8n++6O3csv3/TfXZ/65j1jaxv0tdPamtuy5rbbPDfPfrZzO3YUc0dj4/LbFp8UajNTHrG2cuWW8fTsZ29d9+Zrbsn+0mZoLq+FHTvy5GdMTHwPHJreds72r/1Rt6n5DvG/jG3TF0ffY07a7yRM/e5sbbGFxFcqDk2baey60XAHre0ndr1kPs3DQsu415rraIY97sbss+ekRWiJj333dywmdt0MkTu+KYhv+mPnsWie1Er4D42zpkfJ2NSSiKb6HSsfW9zmYgqP6bGSgVpEQG7bbP857dc87lltN/U5zdou3Td746LmOWuR36nm2Mw8TYrUXGXo+imI7yMA3Apgd+uFa0/snPPizgvX/nSR3b17905+YLBh129O/1o2NqacqOZG+4LMSuSsbdP9MuYctv9a+g2jb7DbrutDW5v4ssxtlxIfG63z8dTzNF/6/IfUDSNXYff7Rf6Lim8A3w/gPwH4f+dHqs2Z3WcB+OzscfJXzn73KgDPmf18JIDLZl819g8A9iyy6Xvnm93AmtEuIkrAnjSHYNcP238NsWntO3M0Jrq5247tfwqw+3XqnYxc/jXD7vds/yVg9wvGRvwU2i0n7H4fsrGUo82mvOFY8m3nfwTgIwD+J4Dfmx2/m2Iz5yHx2Dl7YGiZ2BiTupHGsuzUaxSQNaOlbLnbVeudGkkfYzZr3DBl901227H9a7fPqrtl6JdtP8vUdjXUbQ2bPoz1JnfblRTfn1n0OWtNh+Rnvmvo3Cl2p5hoh+z4MRdkdrLDWlClbDMT0Sn2W6kY2TDGVUi9LGvfaccwNBcyYmPXC7vvSMZXGs2xOcePb8x/yXWU5V8CVh6lpe5S1zuNpMZfUnxfBmBHio2SR8m3nS+CJd5LCUCfXcupbVykwp642P590D5u2LD7NmNBZu9219I3NMLekAzZnAj1rUU8szZzl2XcpdSvxk2nkkxxw5E9p6XArruujzGbjDlzUdlLiu8rAdwze/P45fMjxWbOo5T4Zu5MsQe+ll05Nhon1hSmvhuupW+ykpGc/kvYLmGfATsZ0jIucsPq9+y205JIp1w7RQHX9aFVnDM2W1NiizknV1ya64e1lkqNO1auUVJ8r/QdKTZzHm3xPcVErc0Uy8deEGvwz0QqvmXsu+wkWEvf0pYQ1FAvbDQnQyV8G3Fo2aifYt+xzWrdthf5LJEHsNpuyjly6bedfzuAZ8+Ox6Xay3lIfNWYlkWBida4SqG1/OyJpxsH6y4BO5mbGlNvOy19g3UHT9pXyXHPHvNT3jTTMi5SqKHupiYgU6nhJkepeS2237LaXUu/l4oxlJJ3vs8B8E8ALgXwVgCfB3B2is2ch+RXjZWYMBn+2cmMFmpctMbQ0nYl6pVxJ2PKSbiPf2OcGtpumds3deOAvXGiNZHVGlfpOFjjflFcrDyPnWNLMRQjK8+ZStsx88QU3yXF93Xtu90AjgVwXYrNnEfoZ741Dv5SE/aUF03Nu+FakgataO+XloRz+223/Oy42P59YMc45H9l+yctkRSAkciW7FM5y6c5V5CA3TdzwMyz2HNpSVi5Drvtxs4rKb6v7/z/Yd3faTo0ve2cAXtiYIsIdvm7cYz5ZSyK7N1o243nJZI50dB2rH4r7WOqImCK1LTeaRVhNfT7Kc+rvjFoqpcQ/9rajr3hqKFP1UJf3ykpvi+cven8BbPjbwD8ZorNnMcyvO18kf/caBAwpXyU9M++k8D2XxKtGx8abcfEUTqRlkBbklY62a2h7box1jBnseuOKQI0+G/HoGWuCYXR76ee4/r2iVx9p9Y+GZL/S7edr92cfaf0C9d+DMBvz47/O9VezkPihWshaN4VzM2UE0Gm/0X1ahsv8bFN0bcvWmIc6h+5+40GEVA7LPG7yE+JtYi13oSck8u3Zj+stZopQrr2Y3OFGtZq6RilBBxrvWK3XTc+zXNWjlyjqPiu6ajtM99s/13YCfqy+w+BJWIWxVMiSZ1a/1jmDUN2m0phIqC+NmOjoe1CY9WSK2mplxpg1l2u9WbKeU6fP+m2q1k8p/r1rbs+/9nFN4APz/79CoAvt46vAPhyjM0Sh8TbzpkiovRdGKaA07aYl7bLnlhKxZWDqbWdj92pC7hY2HGF+Nc6tnLHpWW9841LW/uMMfW2Y7bRFDZbWbDrTksda5vzmWt9attpmHOqvvMN4NEA3g/gc7N/j+k553QAHwVwI4BPAfiPPrYlP/PNHDSsBbXmBc3XttaJhZ1wavkMHmPcsdskBG2L+Rz2nMX2nxP2nCUFa7M3V9+pYb3pnq9ls5s952rYNFtkV/ucV6JPsfttLOw8a4rrVdc+o0+UfOHaH/n8LtDm6wCcN/v5vL4XuAE4GcBJs58fD+CLAI5eZNvedl52wGlbUA3djPWPEn2HvShoSMSlFy72nCNljyViNIgAyRgZ/tkJOtv/GNpFQM66Y8/3oef5Xs+ecyX8a18rtfQdjX40z3fO5W27kuL7ms7/jwDw6USbNwHYMft5B4CbPK65bi7Gxw72286XYUHT4D+Hj5qScA1on4BLwu47OWIs7X8Z5ixp2G3ajaN0IskWISVt5qpjtv9UfOJirdXs8cme84b81zRnadvwZGuMmubbHOtFic98v2L2+e4HO5/3vgvABTE2W7bvbf3ctP8/cP5TAHwGwMMG/n4ugA0AG8cffzx9wnNO70I1Bdg7kmz/i85bBhEzxSScBbvuNMzXEjDnDZZvKbvaEtwSIqp2AccWAez3BUhgm1b5bbI2XqSQzPNiYpesPy1zXkrfKXnnO0poA/gAgBt6jrO6YhvAPSN2dszulH+fj9/2ne8pJci5YE/KQ/HUvKDmRmsyUqLt2MKfvShMUcBJoV3AseNk++7zX6pP5Zw3aul3ueMoLSBL2mQJOC1tPASj79dSd+xcpRuHljm/BsbarsSd7++a/XtG3xFjs2Xb67FzAN8G4BoAZ/vaTn3b+bLs5mqZGHLAFhFs/zWzLHcChuKpoU9oE1Ba5kwJ2z53ICT9s9tOY//2JaRMtmnGn3Pb/msRcItgbTbXPOeWbntt62Wp9WIKbddHCfH9htm/V/YcH4qx2bJ9YeeFa6/rOefhAD4I4BdDbEt9zzdbfLL954Y9MbTPL72bnct/KJp2rbUs5qxkJtWfhiSR3Z9T8Y1fspwx7ZajnrULOPa80Y2D1fYS/qYgAtj+2SKgdK7BmHO0+GdrhJhNI0m/fb5qXeslxk3tXzX2mJmw/tzs8fRHz36/D8CbZj//JIAHAFzbOk5fZHtZ3nbOFhHdOGIX9FoHcU6mvpvdjiFXoqd9Q4NVfmYizE7Cu3GUFiE5WBYBN+R/0e+l/eYop0/sbP8h55VAy5jVXnfstX7If4pvdttr2LQquZnC3nDUttlc8jPfPw7gUbOf/xuAdwF4corNnMeyvO28G4e23eyUAaM9GdGym50LzQJuKEZ2v2d/3j6UvjauZcMu1e8Ukzbtc2bu61PQJCoXwYiVPeflFCExcZQUAblhzfmlbGrdbNa2GZMjjtTy59i4kaCk+P7U7N+nAVgH8CMAPp5iM+ex41tPLto47MkzF5oW+VK7Yuzk3JecGx8xcbQn06kLqG4cucq3yC6r32sWcAzYc1YMmoQue97QkIhqspkSx1THbQ4R5euf3cbscSNF6mZzSh9n5Eltv+x2mtrGS0nx/cnZvxcA+E/t32k85ne+a94VKwkrGRryXwoNIkK67KFl0riTz07ktPdHrfPG0O9y+OweU7gDVyoRHLLFrDsp21rHbN81mhJR1ritWYSw52G2/3YMU57zNGqE0vHk2DxgzNlSsZcU338J4GIAtwI4GsAjAFyXYjPnEfPYOSORHPIzhWSI5Z+dDNUioJiJ2Jh/Zr+XEnCL6m+Z+70U7NiXMRFc5H/qAo6NlnkjBfZmb02bNLliKJ3jpo5bDXXHjkfjhl2qX2bb+9bnkP9H4bivOFdGfD8SwHMBnDT7/w4Az0ixmfNI/cy3lsHOSOKlYC1yDP9sISCF5v6UA+k+Elp/U1pQY2JkiCitZa9JQLH9T2ncsDd+QmEJuLFYahVBpdp+yptWzPUuVcAxc7ra2n5ejudvf3dU7NJzVNG3nQM4DcBLZsdpqfZyHiU/862hc3c7VqnBrqHsuWCLGPbmxSLYCX8tMdUGu9+V8j/FO3DsOSuE1GQqxeeU1qtlWevZGx/std4E3OH1lLJxwRJwjDmv67v0phF7vcnlv+Rj578A4AYAr5od1wP4+RSbOY+Qz3xLoWlHuLT/KSWS7MnCl6ksiKl+me00pQVN6i4MY85lJzO193sN8c/bMDWxLb3xwR63ErGm1n2Kb4k5J8V/e/zW1PcYfYmVz+Yqq295tPpnrzcl+z173HT9F33bOYCjWv8/av4GdI1Hjd/zzUrm2L6HYmFPLCWRXtRq3/TRnkjn7DessofA3vjRKCI0bHykwtrwTEFLPCXGonRZp1J32teL0HNjYvC1w9yw7IujpH+2gEulG3+OjShf37GE+s611qdufJT8zPf1AI5s/f9IANen2Mx5hIjvnDui2v2zF98pJrIaFmTpOEv6LxXT1MYdu9/HwE4E2f6nAGujeCpzZk3j1nfOLiWgSvYFbeJZSnCVEDE51tpa8qwx/yU2i6X9s8VzbFtKz5kl73z/MoDrAOyfHdcC+MUUmzmPqbxwrWa0JPYlkzIpX9qSq9r6PaP+tCTRrGQoJkZtyUiJRJot4NgiQkrASfXT1PqQGvcx5WHN191YU9uihnETEmsO3+yND7b/dgysMc/2ryX+GFvSc4Yvufpt6ReunQHgpbPjyan2ch5aHjtnCMBleoFNzuSDkRBILchsEcHa+CiZjOYSkCF1l2MxZSSiUpSOJ2XOZfVbn3gY/lKTuVC/2ubM3L7Hzq9p3KT6lFqvNAigHPZy+4tpe/a4YW885Mo1Uv3H+NWS46bGm/2x89nj5b8I4CIALwJwRIyd0kdJ8a1VgJYamNKwRQB7sMfASGbG4mAnUxJ2c4uAITvMZCRHrCX9s5OhGgWcFhHhy9TWO+f4Gw+1jht2rhBiT2vds/0zH31m5wqlc421lSvdCuLrou0/ZcMqpd5Zbd+NPfudbwDvBPDHM+H9HgC/E2On9FHyq8akWMbdaJ94UhfmZUxkQ+yxkugx/yVjYvd7ZttLIpEIs+Y8lv8UWLGzk3jfeFKTK+nzx2ywRURs3KXnzBwbL6niuZSAW/a27/qPEYDa+m2pPDG17/jEXzLPbtss1fYM8X196+cjAFwTY6f0EfJVY+xJjZ3M5FjQUn2XTGja15QWQMy+59vvcsWTyz+r7tmJdIg9m/Py+Gf0PXa/69rVngin+meJfUlbrCS+a4f1fcspZWFv2EmPm9Q5q8TGx5j/EgKuhvWyxPyT2tfXVuLuvA+VfwVXFlsnuse34mTnXF7xfc3Y/1MOAI8G8H4An5v9e8zIud8G4AsALvKxbS9cK78opPhnx6oFLf2uhk0r7fGUQmrsTKH+WPOIRN3Vkoimwu5nzI0Ptv8cAkoi3hoFXG2bXjVseIZuHpUedxo2jVKIFb8Sfvt8hopnVvxt/w/53Oucyyu+vwHgy7PjKwAebP385RibLduvA3De7OfzAPzmyLn/A8DbSonvbmWHTOy17eRL+WVM6tIL2lQW1JKff2zHWjKx1lr3y9D32P1OayJZSsB1r5UQ3an9rvRnrrWtdyU2PthzTvc65kfUmJs4KeOOLeAkrpf63HAq7LoI9ZO6VvXlWqU3nfpiyX19avyL6j/Uzua/Bd92Ln0AuAnAjtnPOwDcNHDeXgDvAPCC0uLbB+YioMG/NCm7mswFScMiMLW+4ENs3bEFnDSMtmcnkrFMqe1ZY16b+C119zTlmiEbqeOGLSJC6156zi616TV0Tcrjr6kbL+xxV6LsY/7ZbR8ay9zOyvZPJpe99Dov4T+lHaXy7JC6H445853vnAeAe1s/N+3/t37/MADrAJ6wSHwDOBfABoCNxz5id/TgWtZEcArJVOjAlk5c2f6l4i0Rj7Z+L+UnNZmSzU33mAAAExtJREFU2oBh+Q+JUbrtQ9tSm4iREHIpyRzzM3Ts9SbGN1vASa03NdZ912bpfi/Z9qXG/fx8TY8eh/qPjV9rrvX87e+m+Y6p+/m5jI2TWDvSdb9pT7n4BvABADf0HGd1xTaAe3qufwmAX539nOXON3tB6sYhlQimJuElv6845vyctmq7niUgc/mPofTiKjVvaOhrWpKZ1DmLMWczH8FktX0OSosI9pzFHHepuUZsEu4Ti+81NY+7tg2JtvcREVIbD5J1v4wbJ9ICkln3sf5l7jyHi2fZulcuvkcD8njsHMCfAPhnAAcA3Dn7vPlvLLIt8dg5e3EOZR6vljvXbP8x/kJtSQsQtn+peJntzvrsaaq/2tq+HQdLwMXWfWoiJ5mI1fb21zH/zHFfSkRoGndzv7ECNvaa1HaXFgEl1vqxa1LngNDrUj/mk9JmrHHXjYMl3hl132cnVMCmxt8XQ6p4DvV91ra/EK37tDaoW3xf2Hnh2usWnF/VZ77ZLx9iJgOp15dKJqZG6s6eRN1J9oOc/qQ3jZh1L5lISsRRMhlKgbVxoFVEpAiHkiIihRz9bgoCstZNG8aco2HzIIXUcRcjADWK9xCk2k5avKdeLyGgS+VI3cP3zvfQ9Wdt+4uE6+sW348B8MHZV419AMCjZ7/fB+BNPed7i29gb9GB2b7WXj4k73+qiTB7MdZa9yXrojvuSm0esNu+HQf7EU4pAVxqDpXst1oEVEzd1ZrIpiDV9ivbPyl65537CGb69SmPTtc27lgipGtH6vHf0HqIGbdSZZfaeCg9brp2dm47eKgNU+L2tZEqviXGzry/xsTvnPTGR8XiO+exd+9eyo5oDGzx241DIoErHTvTf46+w9qICfXNbu92HKUFHFsAsfsdc84c8x+bFMQ8xic5TlPFb+z1kgIwdAxI3wUqJUIWxaFZwEkTOwYYIkhqztIinqX8l6j7lOty+mZfn3r3NrQO2wK25JyTKv5Thfd23Nt7/XbcGxm7ie/eI+Wxcy2LWiyl42cn4d04WJsHDP9SAkSCGjc+JOovtd0lNg5q67dj16Q8AioRc2piUlq8S9Z92ttf0/traiJaOpHt2mOKiNS6T/Vfqu4k+i5TPObwn3q9b90NCaDv3Xa1Z8nzCbiU6yXGTu74U32niteh60v5n9/p7x47tx30ul6+7U189x4lP/PtHFcEjU2osX4lksIYJBPJlCRAQlAxFvPQ2NkbJznGDUMEMfttLFJ1z958YDx6PI87tu5ybRqxRUAp8T4nte0lH3+NrXvWi5PmfudJban4pcR7206JTQ+f+LWL5zkpfSdFROUScBL+fa5PFYC1X59j46S0xpACwIZzJr63FjbyM9+SlBYBsdcyNw7G/Nf2FRIptlKFP1sApVJr/EwRkmMxk/BfS91LiwDpeTfnxoNW8R5b94yvrmE9Ms/u97muLyF+Ja5PLQPT/5hvHwE2dn3q54ZTri/Rbm3mItZXtHaZz1e+d327pOZLRjomvgeOmj7zPeY/ZYKIjUEieU9ZlFIE2Px66YS45J0Qhu9Y2P1WqvxSd09D+52ECIndeNA+55VKqGIFHNu/RN+XTuJL3YHL0XdK1JtP/LkFXE7x7Vv+lLunOQWgT/xDdw9Tr/cVcimfXXVObs1MFZApSOaKhhGDie+BI/ax89hEtmtDYnILjVsiGZH0Xdud61TxnprEpyJZd1L1GBszu++y3qBaWvjNbTBfusUUn87JC8C0ry8JK4fEZqf0OpdSdxJ3b33iT338NKd4Zj6+W+Lzl2zxLLF50LZjAs4wlg8T3wNH6J3vVNh3kVIx8Z5eZvYjoF17Ja5nbDT5+JcSEqXajvG9q1LxS/sOjeGsbX9BabtcdxBL3T3NGUNuAZhLgKXeufWNP1X85oo/9C5m6uO3hmEYNWLie6iwgZ/5lhKA0newYpP5WKSEW8mv7ZG+8106iZ4jLSJS64F595T91mX2xkvJts9x9zR27EsIkFruPKdezxaQ7Jf/5Hp7b4gAbbcBY5Pd7r4ahmGUx8T3wMH6qrEU8ZlyPVu8axGAknXH/u7NWP+lN34k4tf02U8J/74CsGsnZdNKUsCVEoCp/lMfv81Vd6mP3zIf3y29cWUC0jAMw6gJE98Dh7avGit953oZxbtUMjkV8Z56fS0CsM9GKfHHrvtlF8/s7w7t2rG33xqGYRjGtDHxPXBIfOa7ZEIj/fhtahyxZWa8eIr96HBqGaTij/WfGgPz0eNF/n3tpLS91pcPsa8vIf7nMN+8axiGYRjG8mDie6iwQp/5Tr2+1q9eKf3iJgkBV/PnbnPFz3z0uNT17M+epvZ9qZcfGYZhGIZhGHkJEd8PwxKxd+/WdHb/+urg+fvXVxdIb7/rn7/9PYf9/tL7fhRNA+xfXR+Nd//qOppm8/wYuvGvrWz6W1tZXxh72//5V22ed9V9pwPY/L9X/Ourh3y2Of+q1YXXtuPvxu0T+zz+lLrri73Y9QNt79t2Y6xfe3T0tRLXl/Bx4MEn9PadAw8+Iej6le3XAtj8N+T6obnDt93W7z299/r1e0/3ut4wDMMwDMNQiK9Kn8IReufbOR2PUOb47GoNZWf7Z9893Y57e6/fjnu9rpd+dD2Gmj7mYRiGYRiGYRihoObHzgE8GsD7AXxu9u8xA+cdD+B9AD4D4NMAdi22vTdagLSFTMq1UgKylABNefw19Wtr2C9ummMvTjIMwzAMwzAMo48Q8a3xsfPzAHzQOXcSgA/O/t/HWwFc6Jz73wE8BcC/hjjxfvS58+j1/Fqfx64BYPXoaw+7NpTUx5cv+fCJQb+XZP3e0wdjXz393iL+ndv66LBzYY9tzx9B9n3keCiO2EeG548wpzxqbhiGYRiGYRgGlyPYAfRwFoDV2c+XAlgH8PL2CU3TnALgCOfc+wHAOffVgvEB2PwMqY8YWj39Xlx1VbyfXUd8Af/0ja1+dm77gpf/FzztZpx/1VbR+IKn3QxgsZgcFox+QnL/+ir29/5lNeFav+vnPFQG+7ysYRiGYRiGYRgcNN75/nbn3BdnP/8LgG/vOedkAPc2TfOupmk+2TTNhU3TbOsz1jTNuU3TbDRNs9H9W8pLnc6/ahWrR1+78LzUl4bN77p2j1IvfjIMwzAMwzAMwzDSaTYfUy/stGk+AOB/6/nTKwFc6pw7unXuPc65YzrXnw3gzQCeDOCfAbwTwF8759485nffvn1uY2OLBjcMwzAMwzAMwzCMYJqm+YRzbp/PuZTHzp1zZw79rWmaLzVNs8M598WmaXag/7PcXwBwrXPu1tk17wHwfdgU5IZhGIZhGIZhGIahCo2PnV8O4Pmzn58P4L0951wN4OimaY6d/f8HsfnGc8MwDMMwDMMwDMNQh0bx/RsAfqhpms8BOHP2fzRNs69pmjcBgHPuGwB+BcAHm6a5HkAD4I2keA3DMAzDMAzDMAxjFHVvO3fO3QXg6T2/3wDwn1v/fz+AUwuGZhiGYRiGYRiGYRhRaLzzbRiGYRiGYRiGYRiTgvK2cxZN03wFwE3sOIysPBbAnewgjKxYG08fa+PpY208fayNp4+18XJg7byYnc65YxefpvCx88zc5PsaeKNOmqbZsDaeNtbG08faePpYG08fa+PpY228HFg7y2KPnRuGYRiGYRiGYRhGZkx8G4ZhGIZhGIZhGEZmlk18v4EdgJEda+PpY208fayNp4+18fSxNp4+1sbLgbWzIEv1wjXDMAzDMAzDMAzDYLBsd74NwzAMwzAMwzAMozgmvg3DMAzDMAzDMAwjM0shvpumeWbTNDc1TXNz0zTnseMx8tA0zYGmaa5vmubapmk22PEY6TRN84dN0/xr0zQ3tH736KZp3t80zedm/x7DjNFIY6CN9zdNc9tsLF/bNM2zmDEaaTRN8x1N01zZNM2nm6a5sWmaX5j93sbyRBhpYxvLE6FpmiObpvmHpmmum7Xx+bPf726a5uOzHPudTdM8nB2rEcdIG1/SNM3nW+P4dHasNTP5z3w3TbMNwGcB/BCALwC4GsDznHOfpgZmiNM0zQEA+5xzd7JjMWRomub/AvBVAG91zj1p9rvXAbjbOfcbs820Y5xzL2fGacQz0Mb7AXzVOfdbzNgMGZqm2QFgh3PumqZpHgXgEwB+FMALYGN5Eoy08TmwsTwJmqZpABzlnPtq0zTfAuDDAH4BwC8DeJdz7h1N07wewHXOuT9gxmrEMdLG/wXAXzrn/owa4ERYhjvfTwFws3PuVufcvwN4B4CzyDEZhuGBc+5/Abi78+uzAFw6+/lSbCZ4RqUMtLExIZxzX3TOXTP7+SsAPgPgONhYngwjbWxMBLfJV2f//ZbZ4QD8IIC5KLNxXDEjbWwIsgzi+zgAB1v//wJsQZgqDsD7mub/b+/uQ/Ws6ziOvz/bbMRGG+UQ0mQ5JkuWrqGrdNCKMnuAKE2NFftDyMUyFfrHCAxRSMwsEu3BapRrYS0fSHALe5oWbWjTmStjM/9Yc4NsSQ8Kbd/+uH+j2+N2Omvn3v1w3i+4Odd9Xb/rur73+fHj3N/ze7jySJKP9zsY9cxJVbWnbT8LnNTPYNQzn0zyeBuW7nDkEZFkPvAm4DfYlkfSmDoG2/LISDI9yTZgH/ATYCewv6r+3Yr4HXvIja3jqjrUjm9o7fiWJDP7GOLQmwrJt6aO5VW1FHgPsKYNZ9UIq868Gf8rO3puBxYAS4A9wM39DUeTIclsYANwVVU9333MtjwaDlPHtuURUlUHqmoJcAqdkaWL+hySJtnYOk6yGLiGTl2fA7wacHrQMZgKyfdu4HVd709p+zRiqmp3+7kPuJvOHwaNnr1tfuGheYb7+hyPJllV7W1fAA4C38C2PPTa/MENwLqq+lHbbVseIYerY9vyaKqq/cDPgLcCc5PMaIf8jj0iuur4gjatpKrqReDb2I6PyVRIvrcCC9tqjK8ALgXu63NMmmRJZrVFXkgyCzgfeGL8szSk7gNWte1VwL19jEU9cCghaz6IbXmotUV8vgnsqKovdh2yLY+II9WxbXl0JJmXZG7bfiWdhYx30EnQLmrFbMdD7Ah1/Puuf5KGzpx+2/ExGPnVzgHaoy2+BEwHvlVVN/Q5JE2yJKfR6e0GmAF8z3oefknWAyuAE4G9wLXAPcBdwKnAM8DFVeWCXUPqCHW8gs4w1QL+BFzeNTdYQybJcmAzsB042HZ/hs6cYNvyCBinjj+CbXkkJDmTzoJq0+l03t1VVde171/fpzMc+bfAR1sPqYbMOHX8U2AeEGAbsLprYTYdpSmRfEuSJEmS1E9TYdi5JEmSJEl9ZfItSZIkSVKPmXxLkiRJktRjJt+SJEmSJPWYybckSZIkST1m8i1J0nGU5DVJtrXXs0l2d73/1XGMY36SvjyvNcnLHlPT4vlXkm3/49x1SZ5LctF45SRJGjQz+h2AJElTSVX9hc6zj0nyOeDvVfWFvgY1OHZW1ZLxClTVyiRrj1M8kiRNGnu+JUkaEId6hJOsSPKLJPcm2ZXk80lWJtmSZHuSBa3cvCQbkmxtr/MOc83pSW5qxx9PcvlhysxPsjnJo+11blccv0xyf5I/JPlqkmntmmuTPNHiubqVX5DkgSSPtOstavtfn+TXrez1E/xdzGr3fazd55L//zcrSVL/2fMtSdJgOgt4A/AcsAu4o6qWJbkSuAK4CvgycEtVPZTkVGBjO6fbZcDfquqcJDOBh5NsAqqrzD7gXVX1QpKFwHrg7HZsGXAG8AzwAPAh4Gng5KpaDJBkbiv7dWB1Vf0xyZuB24B3tDhvr6rvJFkzwc9/AfDnqnpfu8ecCZ4nSdJAMvmWJGkwba2qPQBJdgKb2v7twNvb9juBM5IcOudVSWZXVfec6vOBM7vmSM8BFgJPdZU5Abg1yRLgAHB617EtVbWrxbEeWA48CJyW5CvA/cCmJLOBc4EfdMUzs/08D7iwbX8XuHECn387cHOSG4EfV9XmCZwjSdLAMvmWJGkwvdi1fbDr/UH++/d7GvCWqnphnOsEuKKqNr5kZzK/6+3VwF46ve3TgO7rdfeQA1RV/TXJWcC7gdXAxXR64vePM2d77HXGVVVPJVkKvBe4PsmDVXXd0VxDkqRB4pxvSZKG1yY6Q9ABaD3XY20EPpHkhFbm9CSzxpSZA+ypqoPAx4DpXceWtTnb04BLgIeSnAhMq6oNwGeBpVX1PPB0kg+3+6Ql6AAPA5e27ZUT+WBJXgv8s6ruBG4Clk7kPEmSBpXJtyRJw+tTwNltIbUn6fRCj3UH8CTwaHu02Nd4+ci324BVSR4DFgH/6Dq2FbgV2EFnrvfdwMnAz9tjwe4ErmllVwKXtev8DvhA238lsCbJ9nbuRLwR2NLucS0woYXaJEkaVKk6qlFgkiRpikiyAvh0Vb3/ONxrPp253YsnUHZtK/vDHoclSdKksedbkiQNggPAnNbTfURJ1gFv46Xz0iVJGnj2fEuSJEmS1GP2fEuSJEmS1GMm35IkSZIk9ZjJtyRJkiRJPWbyLUmSJElSj5l8S5IkSZLUY/8BkaG6DAqmuU0AAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ " \n", " # Set variables:\n", " # -------------------------------------- #\n", " tmax = 38.0 # Maximum of time range fitted\n", " filename = \"data_HarmOsc1.txt\"\n", " \n", " # Load time and distance, assign uncertainty:\n", " # -------------------------------------- #\n", " time, dist = np.loadtxt(filename, unpack=True)\n", " time -= time[0] # For ensuring that time starts at 0.0s!\n", " edist = np.ones_like(dist)*0.0037 # I have estimated the uncertainty from a calibration with no swings.\n", " \n", " # Check loaded data:\n", " # -------------------------------------- #\n", " if verbose :\n", " for i in range(Nverbose) :\n", " print(\" Time = %6.3f Dist = %6.3f \"%(time[i], dist[i]))\n", " print(\" Number of entries read: %d Time of last read: %6.3f\"%(len(time), time[-1]))\n", " \n", " # Sanity check\n", " for i in np.where((time < -0.001) | (time > 100.0) | (dist < -5.0) | (dist > 5.0))[0] :\n", " print(\"Warning: Strange value for time and/or dist!\", i, time[i], dist[i])\n", " \n", " # Plot the data:\n", " # -------------------------------------- #\n", " fig1 = plt.figure(figsize=(16, 10)) # Make an empty figure\n", " ax1 = fig1.add_axes((.1,.3,.8,.6)) # Add the top subfigure\n", " ax1.set_ylabel(\"Position\")\n", " \n", " # Make a graph of the data:\n", " ax1.errorbar(time, dist, edist, fmt='k_', label='data', ecolor='k', elinewidth=1, capsize=1, capthick=1)\n", " ax1.set_xlim(time[0],time[-1])\n", " ax1.set_ylim(top=ax1.get_ylim()[1]*2.5)\n", " \n", " # Fit the data:\n", " # -------------------------------------- #\n", " mask = time < tmax\n", " \n", " # Fit this graph with a simple harmonic function:\n", " def fit1(x, p0, p1, p2, p3) : return p0 + p1 * np.cos(p2*x+p3)\n", " FitObject1 = Chi2Regression(fit1, time[mask], dist[mask], edist[mask])\n", " Minuit1 = Minuit(FitObject1, pedantic=False, p0=-0., p1=0., p2=0., p3=0., print_level=1)\n", " Minuit1.migrad()\n", " chi2 = Minuit1.fval\n", " ndof = len(time[mask])-len(Minuit1.args)\n", " prob = stats.chi2.sf(chi2, ndof)\n", " x_fit = np.linspace(0, tmax, 1000)\n", " y_fit = fit1(x_fit,*Minuit1.args)\n", " ax1.plot(x_fit, y_fit, 'r-', label='simple harmonic oscillator')\n", " draw_fit_parameters(Minuit1, ax1, 0.05, 0.95, 'Simple harmonic oscillator:','r',chi2,ndof,prob)\n", " \n", " # Now you should try to produce a more advanced fit, which includes additional effects:\n", " # As inspiration, I could ask you:\n", " # Is there any visible damping?\n", " # Are the period and/or phase constant?\n", " # Are there more than one exponential/oscillation in the system?\n", " \n", " # Judge your additions by how significant the added parameter is in the fit (i.e. distance from no effect, that is zero)\n", " def fit2(x, p0, p1, p2, p3, p4) : return p0 + p1 * np.exp(-p2*x) * np.cos(p3*x+p4) # Add to function!\n", " FitObject2 = Chi2Regression(fit2, time[mask], dist[mask], edist[mask])\n", " Minuit2 = Minuit(FitObject2, pedantic=False, p0=0.0, p1=0.0, p2=0.0, p3=0.0, p4=0.0, print_level=1)\n", " Minuit2.migrad()\n", " chi2 = Minuit2.fval\n", " ndof = len(time[mask])-len(Minuit2.args)\n", " prob = stats.chi2.sf(chi2, ndof)\n", " x_fit = np.linspace(0, tmax, 1000)\n", " y_fit = fit2(x_fit,*Minuit2.args)\n", " ax1.plot(x_fit, y_fit, 'b-', label='advanced harmonic oscillator')\n", " draw_fit_parameters(Minuit2, ax1, 0.55, 0.95, 'Advanced harmonic oscillator:','b',chi2,ndof,prob)\n", " \n", " # Calculate residuals:\n", " # -------------------------------------- #\n", " dd1 = dist-fit1(time,*Minuit1.args)\n", " dd2 = dist-fit2(time,*Minuit2.args)\n", " NlargeRes1 = 0\n", " NlargeRes2 = 0\n", " \n", " for i in range( len(dist) ) : \n", " if (abs(dd1[i]) > 0.020 and NlargeRes1 < 20) :\n", " print(\" Large residual in fit1: t = {:6.3f} d = {:6.3f} dd1 = {:6.3f}\".format(time[i], dist[i], dd1[i]))\n", " NlargeRes1 += 1\n", " if (abs(dd2[i]) > 0.012 and NlargeRes2 < 20) :\n", " print(\" Large residual in fit2: t = {:6.3f} d = {:6.3f} dd2 = {:6.3f}\".format(time[i], dist[i], dd2[i]))\n", " NlargeRes2 += 1\n", " \n", " # Draw the residuals:\n", " # -----------------------------------------\n", " # Draw residuals as function of time in bottom subfigure\n", " ax1.get_yaxis().get_ticklabels()[0].set_visible(False)\n", " ax1.get_yaxis().get_ticklabels()[1].set_visible(False) # Remove bottom y-tick on top subfigure to prevent overlapping ticks\n", " ax2 = fig1.add_axes((.1,.1,.8,.2),sharex=ax1) # Add bottom subfigure for residuals, and have its x-axis follow the top figure when zooming manually\n", " ax2.set_xlim(time[0],time[-1])\n", " ax2.set_xlabel(\"Time elapsed [s]\")\n", " ax2.set_ylabel(\"Position residual\")\n", " \n", " ax2.errorbar(time, dd1, edist, fmt='r_', ecolor='r', elinewidth=1, capsize=1, capthick=1)\n", " ax2.errorbar(time, dd2, edist, fmt='b_', ecolor='b', elinewidth=1, capsize=1, capthick=1)\n", " ax2.plot((0,tmax),(0,0), 'w--', lw=1, zorder=10)\n", " \n", " # Draw histograms of residuals in a new inset figure\n", " axins = inset_axes(ax1, 3, 3 , loc=5, bbox_to_anchor=(0.9, 0.5), bbox_transform=ax1.figure.transFigure)\n", " plt.yticks([],[])\n", " axins.hist(dd1, bins=120, range=(-0.03, 0.03), histtype='step', linewidth=1, color='r')\n", " axins.hist(dd2, bins=120, range=(-0.03, 0.03), histtype='step', linewidth=1, color='b')\n", " axins.set_ylim(top=axins.get_ylim()[1]*1.5)\n", " \n", " axins.text(0.40, 0.95, \"Residuals\", transform=axins.transAxes, fontsize=10, verticalalignment='top')\n", " axins.text(0.01, 0.90, nice_string_output({'simple':\"\",\n", " 'Mean': \"{:.3f}\".format(dd1.mean()),\n", " 'RMS' : \"{:.3f}\".format(dd1.std(ddof=1))}),\n", " family='monospace', transform=axins.transAxes, fontsize=10, verticalalignment='top', color='r')\n", " \n", " axins.text(0.55, 0.90, nice_string_output({'adv.:': \"\",\n", " 'Mean': \"{:.3f}\".format(dd2.mean()),\n", " 'RMS' : \"{:.3f}\".format(dd2.std(ddof=1))}),\n", " family='monospace', transform=axins.transAxes, fontsize=10, verticalalignment='top', color='b')\n", "\n", " # Finalize the figure\n", " if (SavePlots) :\n", " fig1.savefig(\"Fit_HarmOsc1.pdf\", dpi=600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at the plot of data from the file \"data_HarmOsc1.txt\", there is little doubt\n", "that it is oscillating, and looking closer you will also see the slight damping. Put this into the fit, and afterwards other effects if you can find them.\n", "\n", "---\n", "## 2nd Dataset\n", "\n", "This dataset was acquired with the help of an overdamped oscillator (a cardboard panel was added to the weight, thereby increasing the atospheric drag of the system)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Time = 0.000 Dist = 0.179 \n", " Time = 0.010 Dist = 0.182 \n", " Time = 0.020 Dist = 0.198 \n", " Time = 0.030 Dist = 0.207 \n", " Time = 0.040 Dist = 0.217 \n", " Time = 0.050 Dist = 0.229 \n", " Time = 0.060 Dist = 0.238 \n", " Time = 0.070 Dist = 0.240 \n", " Time = 0.080 Dist = 0.247 \n", " Time = 0.090 Dist = 0.251 \n", " Number of entries read: 3616 Time of last read: 36.150\n", " Large residual: t = 0.000 d = 0.179 dd1 = 0.035\n", " Large residual: t = 0.010 d = 0.182 dd1 = 0.023\n", " Large residual: t = 0.020 d = 0.198 dd1 = 0.026\n", " Large residual: t = 0.030 d = 0.207 dd1 = 0.023\n", " Large residual: t = 0.040 d = 0.217 dd1 = 0.022\n", " Large residual: t = 0.050 d = 0.229 dd1 = 0.025\n", " Large residual: t = 0.060 d = 0.238 dd1 = 0.025\n", " Large residual: t = 0.070 d = 0.240 dd1 = 0.021\n", " Large residual: t = 0.080 d = 0.247 dd1 = 0.022\n", " Large residual: t = 0.090 d = 0.251 dd1 = 0.022\n", " Large residual: t = 0.100 d = 0.251 dd1 = 0.020\n", " Large residual: t = 0.320 d = -0.043 dd1 = -0.023\n", " Large residual: t = 0.340 d = -0.073 dd1 = -0.021\n", " Large residual: t = 0.350 d = -0.087 dd1 = -0.021\n", " Large residual: t = 0.360 d = -0.101 dd1 = -0.021\n", " Large residual: t = 0.380 d = -0.125 dd1 = -0.020\n", " Large residual: t = 0.400 d = -0.147 dd1 = -0.023\n", " Large residual: t = 0.410 d = -0.153 dd1 = -0.021\n" ] }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ " # Set variables:\n", " # -------------------------------------- #\n", " tmax = 36.0 # Maximum of time range fitted\n", " filename = \"data_HarmOsc2.txt\"\n", " \n", " # Load time and distance, assign uncertainty:\n", " # -------------------------------------- #\n", " time, dist = np.loadtxt(filename, unpack=True)\n", " time -= time[0] # For ensuring that time starts at 0.0s!\n", " edist = np.ones_like(dist)*0.0029\n", " \n", " # Check loaded data\n", " # -------------------------------------- #\n", " if verbose :\n", " for i in range(Nverbose) :\n", " print(\" Time = %6.3f Dist = %6.3f \"%(time[i], dist[i]))\n", " print(\" Number of entries read: %d Time of last read: %6.3f\"%(len(time), time[-1]))\n", " \n", " # Sanity check\n", " for i in np.where((time < -0.001) | (time > 100.0) | (dist < -5.0) | (dist > 5.0))[0] :\n", " print(\"Warning: Strange value for time and/or dist!\", i, time[i], dist[i])\n", " \n", " # Plot the data:\n", " # -------------------------------------- #\n", " fig1 = plt.figure(figsize=(16, 10)) # Make an empty figure\n", " ax1 = fig1.add_axes((.1,.3,.8,.6)) # Add the top subfigure\n", " ax1.set_ylabel(\"Position\")\n", " \n", " # Make a graph of the data:\n", " ax1.errorbar(time, dist, edist, fmt='k_', ecolor='k', elinewidth=1, capsize=1, capthick=1)\n", " ax1.set_xlim(time[0],time[-1])\n", " ax1.set_ylim(top=ax1.get_ylim()[1]*1.5)\n", " \n", " # Fit the data:\n", " # -------------------------------------- #\n", " mask = time < tmax\n", " \n", " def fit1(x,p0,p1,p2,p3,p4) : return p0 + p1 * np.exp(-p2*x) * np.cos(p3+p4*x)\n", " # Perhaps make a list of functions to try out...\n", " \n", " FitObject1 = Chi2Regression(fit1, time[mask], dist[mask], edist[mask])\n", " Minuit1 = Minuit(FitObject1, pedantic=False, p0=0.038, p1=0.19, p2=0.104, p3=-1.0, p4=8.97, print_level=0)\n", " Minuit1.migrad()\n", " chi2 = Minuit1.fval\n", " ndof = len(time[mask])-len(Minuit1.args)\n", " prob = stats.chi2.sf(chi2, ndof)\n", " x_fit = np.linspace(0, tmax, 1000)\n", " y_fit = fit1(x_fit,*Minuit1.args)\n", " ax1.plot(x_fit, y_fit, 'b-')\n", " draw_fit_parameters(Minuit1, ax1, 0.70, 0.95, None,'k',chi2,ndof,prob)\n", "\n", " # Calculate residuals:\n", " # -------------------------------------- #\n", " dd1 = dist-fit1(time,*Minuit1.args)\n", " NlargeRes1 = 0\n", " \n", " for i in range( len(dist) ) : \n", " if (abs(dd1[i]) > 0.020 and NlargeRes1 < 20) :\n", " print(\" Large residual: t = {:6.3f} d = {:6.3f} dd1 = {:6.3f}\".format(time[i], dist[i], dd1[i]))\n", " NlargeRes1 += 1\n", " \n", " # Draw the residuals:\n", " # -----------------------------------------\n", " # Draw residuals as function of time in bottom subfigure\n", " ax1.get_yaxis().get_ticklabels()[0].set_visible(False) # Remove bottom y-tick on top subfigure to prevent overlapping ticks\n", " ax2 = fig1.add_axes((.1,.1,.8,.2),sharex=ax1) # Add bottom subfigure for residuals, and have its x-axis follow the top figure when zooming manually\n", " ax2.set_xlim(time[0],time[-1])\n", " ax2.set_xlabel(\"Time elapsed [s]\")\n", " ax2.set_ylabel(\"Position residual\")\n", " \n", " ax2.errorbar(time, dd1, edist, fmt='b_', ecolor='b', elinewidth=1, capsize=1, capthick=1)\n", " ax2.plot((0,tmax),(0,0), 'w--', lw=1, zorder=10)\n", " \n", " # Draw histogram of residuals in a new inset figure\n", " axins = inset_axes(ax1, 3, 3 , loc=5, bbox_to_anchor=(0.9, 0.5), bbox_transform=ax1.figure.transFigure)\n", " plt.yticks([],[])\n", " axins.hist(dd1, bins=120, range=(-0.03, 0.03), histtype='step', linewidth=1, color='b')\n", " axins.set_ylim(top=axins.get_ylim()[1]*1.5)\n", " \n", " axins.text(0.40, 0.95, \"Residuals\", transform=axins.transAxes, fontsize=10, verticalalignment='top')\n", " axins.text(0.01, 0.90, nice_string_output({'simple:':\"\",\n", " 'Mean': \"{:.3f}\".format(dd1.mean()),\n", " 'RMS' : \"{:.3f}\".format(dd1.std(ddof=1))}),\n", " family='monospace', transform=axins.transAxes, fontsize=10, verticalalignment='top', color='k')\n", "\n", " # Finalize the figure\n", " if (SavePlots) :\n", " fig1.savefig(\"Fit_HarmOsc2.pdf\", dpi=600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The fit is not that bad, but clearly the residuals still have a lot of structure, which are thus features not included/encompassed in the fit. So you should try to add complexity to your fitting function, such that (some of) these are included.\n", "\n", "----\n", "\n", "## 3rd Dataset\n", "\n", "This set corresponds to a set up in which the oscillator is __slowed__ by sliding constantly along a metal plate." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Time = 0.000 Dist = 0.614 \n", " Time = 0.001 Dist = 0.606 \n", " Time = 0.002 Dist = 0.600 \n", " Time = 0.003 Dist = 0.596 \n", " Time = 0.004 Dist = 0.579 \n", " Time = 0.005 Dist = 0.568 \n", " Time = 0.006 Dist = 0.560 \n", " Time = 0.007 Dist = 0.561 \n", " Time = 0.008 Dist = 0.545 \n", " Time = 0.009 Dist = 0.539 \n", " Number of entries read: 13700 Time of last read: 13.699\n" ] }, { "data": { "text/html": [ "
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FCN = 4318787.674641833TOTAL NCALL = 100NCALLS = 100
EDM = 7.2719223664830026e-06GOAL EDM = 1e-05\n", " UP = 1.0
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ValidValid ParamAccurate CovarPosDefMade PosDef
TrueTrueTrueTrueFalse
Hesse FailHasCovAbove EDMReach calllim
FalseTrueFalseFalse
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+NameValueHesse ErrorMinos Error-Minos Error+Limit-Limit+Fixed?
0p0-0.5092040.000129739No
1p10.7368830.00018331No
2p20.6771660.000436776No
3p39.288049.01178e-05No
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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " Large residual: t = 0.000 d = 0.614 dd1 = 0.549\n", " Large residual: t = 0.001 d = 0.606 dd1 = 0.546\n", " Large residual: t = 0.002 d = 0.600 dd1 = 0.544\n", " Large residual: t = 0.003 d = 0.596 dd1 = 0.544\n", " Large residual: t = 0.004 d = 0.579 dd1 = 0.531\n", " Large residual: t = 0.005 d = 0.568 dd1 = 0.524\n", " Large residual: t = 0.006 d = 0.560 dd1 = 0.521\n", " Large residual: t = 0.007 d = 0.561 dd1 = 0.527\n", " Large residual: t = 0.008 d = 0.545 dd1 = 0.516\n", " Large residual: t = 0.009 d = 0.539 dd1 = 0.514\n", " Large residual: t = 0.010 d = 0.524 dd1 = 0.504\n", " Large residual: t = 0.011 d = 0.525 dd1 = 0.510\n", " Large residual: t = 0.012 d = 0.508 dd1 = 0.498\n", " Large residual: t = 0.013 d = 0.499 dd1 = 0.494\n", " Large residual: t = 0.014 d = 0.495 dd1 = 0.495\n", " Large residual: t = 0.015 d = 0.487 dd1 = 0.492\n", " Large residual: t = 0.016 d = 0.477 dd1 = 0.487\n", " Large residual: t = 0.017 d = 0.467 dd1 = 0.481\n", " Large residual: t = 0.018 d = 0.459 dd1 = 0.479\n", " Large residual: t = 0.019 d = 0.447 dd1 = 0.472\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ " # Set variables:\n", " # -------------------------------------- #\n", " tmax = 12.0 # Maximum of time range fitted\n", " filename = \"data_HarmOsc3.txt\"\n", " \n", " # Load time and distance, assign uncertainty:\n", " # -------------------------------------- #\n", " time, dist = np.loadtxt(filename, unpack=True)\n", " time -= time[0] # For ensuring that time starts at 0.0s!\n", " edist = np.ones_like(dist)*0.0139\n", " \n", " # Check loaded data\n", " # -------------------------------------- #\n", " if verbose :\n", " for i in range(Nverbose) :\n", " print(\" Time = %6.3f Dist = %6.3f \"%(time[i], dist[i]))\n", " print(\" Number of entries read: %d Time of last read: %6.3f\"%(len(time), time[-1]))\n", " \n", " # Sanity check\n", " for i in np.where((time < -0.001) | (time > 100.0) | (dist < -5.0) | (dist > 5.0))[0] :\n", " print(\"Warning: Strange value for time and/or dist!\", i, time[i], dist[i])\n", " \n", " # Plot the data:\n", " # -------------------------------------- #\n", " fig1 = plt.figure(figsize=(16, 10)) # Make an empty figure\n", " ax1 = fig1.add_axes((.1,.3,.8,.6)) # Add the top subfigure\n", " ax1.set_ylabel(\"Position\")\n", " \n", " # Make a graph of the data:\n", " ax1.errorbar(time, dist, edist, fmt='k_', ecolor='k', elinewidth=1, capsize=1, capthick=1)\n", " ax1.set_ylim(top=ax1.get_ylim()[1]*1.5)\n", " \n", " # Fit the data:\n", " # -------------------------------------- #\n", " tmax = 11.5\n", " mask = time < tmax\n", " \n", " # We again start from \"just\" plain oscillation\n", " def fit0(x,p0,p1,p2,p3) :\n", " return p0 + p1 * np.cos(p2+p3*x)\n", "\n", " # Now try to put more into the function:\n", " def fit1(x,p0,p1,p2,p3,p4) :\n", " return p0 + (p1+p2*x) * np.cos(p3+p4*x)\n", " \n", " # One can expand the function to include a change in the function, for example from linear to exponential decay.\n", " # In this case one should think about how to make sure, that the function is both continuous and perhaps with continuous derivative!\n", " # Remember to also \"vectorize\" the function...\n", " def fit2(x,p0,p1,p2,p3,p4,p5) :\n", " if (x < p5) :\n", " return p0 + (p1 + p2*x) * np.cos(p3 + p4*x)\n", " else :\n", " return p0 + (p1 + p2*p5) * np.exp(p2*x) * np.cos(p3 + p4*x)\n", "\n", " FitObject1 = Chi2Regression(fit0, time[mask], dist[mask], edist[mask])\n", " Minuit1 = Minuit(FitObject1, pedantic=False, p0=-0.5, p1=0.7, p2=0.67, p3=9.3, print_level=1)\n", " Minuit1.migrad()\n", " chi2 = Minuit1.fval\n", " ndof = len(time[mask])-len(Minuit1.args)\n", " prob = stats.chi2.sf(chi2, ndof)\n", " x_fit = np.linspace(0, tmax, 1000)\n", " y_fit = fit0(x_fit,*Minuit1.args)\n", " ax1.plot(x_fit, y_fit, 'b-',zorder=10)\n", " draw_fit_parameters(Minuit1, ax1, 0.70, 0.95, None,'k',chi2,ndof,prob)\n", "\n", " # Calculate residuals:\n", " # -------------------------------------- #\n", " dd1 = dist-fit0(time,*Minuit1.args)\n", " NlargeRes1 = 0\n", " \n", " for i in range( len(dist) ) : \n", " if (abs(dd1[i]) > 0.20 and NlargeRes1 < 20) :\n", " print(\" Large residual: t = {:6.3f} d = {:6.3f} dd1 = {:6.3f}\".format(time[i], dist[i], dd1[i])) \n", " NlargeRes1 += 1\n", " \n", " # Draw the residuals:\n", " # -----------------------------------------\n", " # Draw residuals as function of time in bottom subfigure\n", " ax1.get_yaxis().get_ticklabels()[0].set_visible(False) # Remove bottom y-tick on top subfigure to prevent overlapping ticks\n", " ax2 = fig1.add_axes((.1,.1,.8,.2),sharex=ax1) # Add bottom subfigure for residuals, and have its x-axis follow the top figure when zooming manually\n", " ax2.set_xlim(time[0],time[-1]+3)\n", " ax2.set_xlabel(\"Time elapsed [s]\")\n", " ax2.set_ylabel(\"Position residual\")\n", " \n", " ax2.errorbar(time, dd1, edist, fmt='b_', ecolor='b', elinewidth=1, capsize=1, capthick=1)\n", " ax2.plot((0,tmax),(0,0), 'w--', lw=1, zorder=10)\n", " \n", " # Draw histogram of residuals in a new inset figure\n", " axins = inset_axes(ax1, 3, 3 , loc=5, bbox_to_anchor=(0.9, 0.5), bbox_transform=ax1.figure.transFigure)\n", " plt.yticks([],[])\n", " axins.hist(dd1, bins=100, range=(-0.10, 0.10), histtype='step', linewidth=1, color='b')\n", " axins.set_ylim(top=axins.get_ylim()[1]*1.5)\n", " \n", " axins.text(0.40, 0.95, \"Residuals\", transform=axins.transAxes, fontsize=10, verticalalignment='top')\n", " axins.text(0.01, 0.90, nice_string_output({'simple:':\"\",\n", " 'Mean' :\"{:.3f}\".format(dd1.mean()),\n", " 'RMS' :\"{:.3f}\".format(dd1.std(ddof=1))}),\n", " family='monospace', transform=axins.transAxes, fontsize=10, verticalalignment='top', color='k')\n", "\n", " # Finalize the figure\n", " plt.show(block=False)\n", " if (SavePlots) :\n", " fig1.savefig(\"Fit_HarmOsc3.pdf\", dpi=600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "Questions:\n", "----------\n", "\n", "1. Look at the data file and plot and see if you can by eye (or simple fits) estimate\n", " the size of the uncertainty of the points. It is not easy, but you should be able\n", " to get it to within a factor of 2-3. Try for 5-10 minutes and discuss it with your\n", " neighbor before reading on!\n", "\n", " - - - - - - 5-10 minutes (success or failure) later - - - - - -\n", "\n", " If you didn't know how to estimate this uncertainty, then try to zoom in on a very\n", " small part of the curve, where it should be possible to fit it with a line, or \n", " possibly a 2nd or 3rd degree polynomial. Do so, and since you know that for a small\n", " enough range of the data, this will be a reasonable PDF to use, extract the error \n", " from the RMS of the residuals, which is roughly equivalent to choosing the errors,\n", " that gives you a reasonable Chi2. If you want to check this, then using this error\n", " for all points, see if it still fits well in some other range. Compare the error you\n", " got to the one I put in.\n", "\n", "\n", "2. Once you have tried, set the error to 0.0037, and try to fit a damped harmonic\n", " oscillator. You should write the function yourself. Do so and run the fit\n", " before reading on.\n", "\n", " - - - - - - 5-10 minutes (success or failure) later - - - - - -\n", "\n", " Did you manage to write the fitting function? Also, did you remember to put in a\n", " parameter taking care of the offset from zero? Anyway, run the fit...\n", "\n", " - - - - - - 5-10 minutes (success or failure) later - - - - - -\n", "\n", "3. Did the fit converge? I imagine that it didn't (thought it might have), and my first\n", " guess on why (apart from obvious bugs in the function) would be initial parameters. You\n", " need to set the initial parameters quite accurately, for the fit to work. Think about\n", " this, i.e. in a 5D parameter space, how hard it is to find just the correct frequency\n", " when all you got is a Chi2 value, and being just 5% wrong or so will give you nothing\n", " of value?\n", " So now try to evaluate what some good initial values for the fit would be. You can\n", " start by simply making educated guesses, but if that fails, you can instead draw the\n", " function choosing some parameters, until it starts looking like the data you have.\n", "\n", "\n", "4. Try to fit only the range 20s-22s, and see how significant the damping is. Would\n", " you from only two seconds data be able to tell, that there is a damping, and if\n", " so, by how many sigma?\n", "\n", "\n", "---\n", "__Now consider the data file \"data_HarmOsc2.txt\":__\n", "\n", "5. See that the uncertainty on the distance is 0.0029. Again, make a simple harmonic\n", " oscillator fit run. Now your job is to expand on the fitting function and \n", " introduce terms to include various effects and thus reduce the Chi2.\n", " Set your fit to the range [0.005,36.005], and see how low a Chi2 you can get.\n", " \n", " - - - - - - 15-30 minutes (success or failure) later - - - - - -\n", "\n", " At the bottom of the program are a few suggestions of extending the function. See if\n", " they match your own additions, and/or how well they work, and if you get the idea of\n", " (slowly) adding more complexity to the fit.\n", "\n", "6. Can you see a change in the oscillation behaviour at some point? There seems to be a\n", " point at which something changes (damping goes from turbulent to regular?). Does your\n", " result improve, if you divide your fit into two parts around there? Three? Twenty?\n", "\n", "7. (Advanced) Can you detect a change in the distance uncertainty as a function of time?\n", " I.e. does the errors needed to get a reasonable/constant Chi2 get better or worse\n", " if you fit small ranges of time early and late in the experiment.\n", "\n", "\n", "---\n", "__Now consider the data file \"data_HarmOsc3.txt\":__\n", "\n", "8. The data file \"data_HarmOsc3.txt\" contains a different type of damping in the\n", " oscillation. Fit this, and determine at which point in time the oscillation stops.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " ### You need to write this functional form of a damped harmonic oscillator:\n", " \n", " $d(t) = A \\cdot\\sin(\\omega t+\\phi) \\cdot\\exp(-\\gamma t)$" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "#def fit1(x, p0, p1, p2, p3, p4) :\n", "# return p0 + p1*np.sin(p2*x+p3)*np.exp(-p4*x)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Possible additions to especially the 2nd dataset could be:\n", "# def fit2(x,p0,p1,p2,p3,p4,p5,p6,p7) : return p0 + p1 * np.exp(-p2*x) * np.cos(p3+p4*x) * (1.0 + p5*np.cos(p6*x+p7))\n", "# def fit3(x,p0,p1,p2,p3,p4,p5,p6,p7,p8) : return p0 + p1 * np.exp(-p2*x) * np.cos(p3+p4*x+p8*x**2) * (1.0 + p5*np.cos(p6*x+p7))\n", "# def fit4(x,p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10) : return p0 + p1 * (np.exp(-p2*x)+p9*np.exp(-p10*x)) * np.cos(p3+p4*x+p8*x**2) * (1.0 + p5*np.cos(p6*x+p7))" ] } ], "metadata": { "executable": "/usr/bin/env python", "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" }, "main_language": "python" }, "nbformat": 4, "nbformat_minor": 2 }