{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "a38fac8e", "metadata": { "tags": [] }, "outputs": [], "source": [ "import numpy as np \n", "import matplotlib.pyplot as plt\n", "from math import exp \n", "from scipy.integrate import solve_ivp\n", "from scipy.interpolate import interp1d\n", "from scipy.stats import linregress\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "id": "a5b7ec98", "metadata": {}, "outputs": [], "source": [ "from sympy import symbols, exp as sexp, diff, Derivative, Eq" ] }, { "attachments": { "bc547-pulse.png": { "image/png": "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" } }, "cell_type": "markdown", "id": "9a5dc2ed", "metadata": {}, "source": [ "![bc547-pulse.png](attachment:bc547-pulse.png)" ] }, { "cell_type": "markdown", "id": "ae0f8575", "metadata": {}, "source": [ "The object was to measure the voltage at the base of the transmitter (and later on at the base of R2) to determine the characteristics of the transistor. Specifically to estimate the thermal coefficient $V_T$ and the scale current $I_{ES}$. The capacitor was to produce a comparatively slowly changing transistor base voltage with hopefully enough time for me to make measurements using an Arduino. (This has since become slightly more complicated because the Arduino analog inputs have a time lag of 100 $\\mu S$ which may add some measurement bias)." ] }, { "cell_type": "code", "execution_count": 3, "id": "17ce4b69", "metadata": {}, "outputs": [], "source": [ "r1, r2, c, issym, vt, vin, vout, vbe, vc, t = symbols(\"R1 R2 C I_{ES} V_T V_{in} V_{out} V_{BE} V_C t\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "771d4afc", "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - C \\frac{d}{d t} V_{C} - I_{ES} \\left(e^{\\frac{V_{C}}{V_{T}}} - 1\\right) + \\frac{- V_{C} + V_{in}}{R_{1}} = 0$" ], "text/plain": [ "Eq(-C*Derivative(V_C, t) - I_{ES}*(exp(V_C/V_T) - 1) + (-V_C + V_{in})/R1, 0)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ " Eq((vin - vc)/r1 - c * Derivative(vc,t) - issym*(sexp(vc/vt)-1),0)" ] }, { "cell_type": "markdown", "id": "09b9a562", "metadata": {}, "source": [ "The above is a differential equation for the R1, C and base-emitter junction. $V_C$ is the voltage across the capacitor. Vin is a choice of 0 or 5 Volts as it is connected to one of the outputs of the Arduino digital pins. By turning it on or off I was hoping to sweep through a range of voltages controlled by the time constand of R1 $\\times$ C. In my case R1 = 6K8 and C = $100 \\mu F$. I think R2 is about 5K.\n", "\n", "It's basically a non linear differential equation which is impossible to solve using analytical methods. Hence the attempt to solve it below using numerical methods." ] }, { "cell_type": "markdown", "id": "29143ef7", "metadata": {}, "source": [ "Now I try to build my theoretical model using the equation above and some scientific libraries to integrate the equation to find what the solution would look like over time.\n", "I am basically plotting the voltage across the capacitor as function of time." ] }, { "cell_type": "code", "execution_count": 5, "id": "3ddce293-9367-492a-bef1-70f908de1302", "metadata": {}, "outputs": [], "source": [ "r1val = 6800\n", "r2val = 5000\n", "cval = 100e-6" ] }, { "cell_type": "code", "execution_count": 6, "id": "4e3423e0", "metadata": {}, "outputs": [], "source": [ "def model(t, y, vin):\n", " vcc=vin\n", " vt = 0.0321850033399526\n", " isval = 1.602564611659814e-12\n", " r=r1val\n", " c=cval\n", " \n", " vc = y\n", " try:\n", " vcp = (vcc-vc)/(r*c) - isval * (exp(vc/vt)-1) /(c)\n", " except OverflowError:\n", " print (vc)\n", " return np.inf\n", " #print (vcp)\n", " return vcp\n", " \n", " " ] }, { "cell_type": "code", "execution_count": 7, "id": "6b52e0bf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[56.81583729]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/splat/.local/lib/python3.8/site-packages/scipy/integrate/_ivp/rk.py:109: RuntimeWarning: invalid value encountered in true_divide\n", " return norm(self._estimate_error(K, h) / scale)\n" ] } ], "source": [ "teval = np.linspace(0, .4,100)\n", "res = solve_ivp(model, (0,.4), (0,),args=(5,), t_eval = teval, first_step=0.001)" ] }, { "cell_type": "code", "execution_count": 8, "id": "c446244e", "metadata": {}, "outputs": [], "source": [ "x = res.t\n", "y = res.y[0]" ] }, { "cell_type": "code", "execution_count": 9, "id": "013ad3eb-5890-4d92-a3e2-59b98d6ae5f5", "metadata": {}, "outputs": [], "source": [ "max60idx = np.argmax(res.y > .61)" ] }, { "cell_type": "code", "execution_count": 10, "id": "04001485", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Charging of $V_C$ over time(t)')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.plot(x,y)\n", "ax.grid()\n", "ax.set_xlabel(\"x (secs)\")\n", "ax.set_ylabel(\"Vc (cap)\")\n", "ax.set_title(\"Charging of $V_C$ over time(t)\")" ] }, { "cell_type": "code", "execution_count": 11, "id": "13fc3ea0-b3d6-44a9-998f-032e82536dab", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "LinregressResult(slope=6.835735444183038, intercept=0.007932451484825798, rvalue=0.9996269961182911, pvalue=2.5047519270349017e-34, stderr=0.04075386421266013, intercept_stderr=0.002115122684003866)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.plot(x[:max60idx],y[:max60idx])\n", "ax.grid()\n", "ax.set_xlabel(\"x (secs)\")\n", "ax.set_ylabel(\"Vc (cap)\")\n", "ax.set_title(\"Charging of $V_C$ over time(t)\")\n", "res = linregress(x[:max60idx],y[:max60idx])\n", "vcslope = res.slope\n", "print (res)" ] }, { "cell_type": "code", "execution_count": 12, "id": "ca4f45a4-8841-4674-86b1-b921486165cc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0006835735444183038" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "capcurrent = vcslope*cval\n", "capcurrent" ] }, { "cell_type": "code", "execution_count": 13, "id": "5b459d43", "metadata": {}, "outputs": [], "source": [ "teval = np.linspace(0, 1,100)\n", "res = solve_ivp(model, (0,1), (.7,),args=(0,), t_eval = teval, first_step=0.001)" ] }, { "cell_type": "code", "execution_count": 14, "id": "a829b00b", "metadata": {}, "outputs": [], "source": [ "x = res.t\n", "y = res.y[0]" ] }, { "cell_type": "code", "execution_count": 15, "id": "c46ad600", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Discharging of C over time(t)')" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.plot(x,y)\n", "ax.grid()\n", "ax.set_xlabel(\"x (secs)\")\n", "ax.set_ylabel(\"Vc (cap)\")\n", "ax.set_title(\"Discharging of C over time(t)\")" ] }, { "cell_type": "markdown", "id": "7fae56b9", "metadata": {}, "source": [ "The results are unsurprising as the capacitor charges up to ( or discharges from ) 0.7 volts approximately. Anything higher and the transistor conducts so the results are at least realistic." ] }, { "cell_type": "markdown", "id": "551150e0", "metadata": {}, "source": [ "Now I look at the results obtained from direct measurement via the Arduino analog input pin." ] }, { "cell_type": "code", "execution_count": 16, "id": "ea25cc0b", "metadata": {}, "outputs": [], "source": [ "measurements = np.array([\n", " [ 0, 0.00, 4.98], \n", " [ 4, 0.03, 4.97], \n", " [ 8, 0.07, 4.98], \n", " [ 12, 0.09, 4.98], \n", " [ 16, 0.13, 4.97], \n", " [ 20, 0.15, 4.98], \n", " [ 24, 0.18, 4.97], \n", " [ 28, 0.21, 4.97], \n", " [ 32, 0.23, 4.98], \n", " [ 36, 0.26, 4.98], \n", " [ 40, 0.28, 4.97], \n", " [ 44, 0.31, 4.98], \n", " [ 48, 0.34, 4.98], \n", " [ 52, 0.37, 4.98], \n", " [ 56, 0.40, 4.97], \n", " [ 60, 0.42, 4.98], \n", " [ 64, 0.45, 4.97], \n", " [ 68, 0.47, 4.97], \n", " [ 72, 0.50, 4.96], \n", " [ 76, 0.52, 4.95], \n", " [ 80, 0.55, 4.90], \n", " [ 84, 0.57, 4.81], \n", " [ 88, 0.60, 4.54], \n", " [ 92, 0.62, 3.82], \n", " [ 96, 0.64, 2.05], \n", " [ 100, 0.67, 0.06], \n", " [ 104, 0.70, 0.04], \n", " [ 108, 0.71, 0.03], \n", " [ 112, 0.72, 0.02], \n", " [ 116, 0.73, 0.02], \n", " [ 120, 0.73, 0.02], \n", " [ 125, 0.74, 0.02], \n", " [ 129, 0.74, 0.02], \n", " [ 133, 0.74, 0.02], \n", " [ 137, 0.74, 0.02], \n", "\n", " ])" ] }, { "cell_type": "code", "execution_count": 17, "id": "c3d98428", "metadata": {}, "outputs": [], "source": [ "dfmeasure = pd.DataFrame(measurements)\n", "dfmeasure.columns = ['time', 'v1', 'v2']\n", "# ADC is the measure obtained from Arduino analogRead which returns a value from 0 to 1023.\n", "# I divide that by and multiply by 5 to get a voltage." ] }, { "cell_type": "code", "execution_count": 18, "id": "043b7b5a-a7f7-43b4-9161-d324e2ed7d0a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "plt" ] }, { "cell_type": "code", "execution_count": 19, "id": "79933ebd", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Arduino measure response transistor base')\n", "\n", "x=dfmeasure['time']\n", "\n", "f1=interp1d(dfmeasure['time'], dfmeasure['v1'])\n", "f2=interp1d(dfmeasure['time'], dfmeasure['v2'])\n", "\n", "ax1 = dfmeasure.plot('time', 'v1', kind='scatter', ax=ax, label='base')\n", "ax1 = dfmeasure.plot('time', 'v2', kind='scatter', ax=ax, color='r', label='collector')\n", "ax1.plot(x, f1(x),'b')\n", "ax1.plot(x, f2(x), 'r')\n", "ax1.set_xlabel('Time (mSec)')\n", "ax1.set_ylabel('voltage $V_C$')\n", "ax1.set_ylim(0,.8)\n", "ax1.legend()\n", "ax1.grid()" ] }, { "cell_type": "code", "execution_count": 31, "id": "1540f085-7bd3-4d8a-b58b-aaf4e468d8ad", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaEAAAEWCAYAAADPZygPAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAABWyklEQVR4nO2dd3xUVfr/38+kN3poJhIUBVGKAjZQKSq464IF2yr21V0F146u7q7r6q7159p392tbC1hABRULKqgIShEEaYoYIKGHAAkkIeX5/XHuwBCSMBOSmUzyvF+v+8qce88593PPTO5zz7nPeY6oKoZhGIYRCXyRFmAYhmE0XcwIGYZhGBHDjJBhGIYRMcwIGYZhGBHDjJBhGIYRMcwIGYZhGBHDjFAUICIvich9Qeb9t4j8ub41GXVLJL83EVER6RKJcxtGbKQFNBVEZDrQC2ivqiX1dR5V/X191d3YEZFs4GpV/TTc5w72e4ukRsOoD6wnFAZEJAs4CVBg+H7yxoRDU2NHROr8Aas+6gwn0aI/WnQadYMZofBwKfAN8BJwWeABb6jtWRGZIiI7gEEicrSIfCciBSLyBpAYkP9yEZlRqY7dwymBQ3ciMlBEckTkFhHZKCLrROSKgHLNReRlEdkkIqtE5G4RqfI3ISL3iMhbIvKqp2uRiBwuInd6da8RkdMr1f28d85cEbnPb2BF5FAR+VxE8kRks4i8JiItAsqO9coUiMhyERlS+doCry8gne2VXQjsEJFYETleRGaKyFYR+V5EBlZzfa8ABwPviUihiNwuIlle214lIquBz728b4nIehHZJiJfisiRlb7Pp0XkA0//tyJyqHdMROQxr722e214VBXfWxsRed/TvEVEvhIRX1UavfzDRWSxl3+6iBxRU5tUdf3Ar0Rkpfd9POz/HRzAd+UTkTtE5Gev7Jsi0qqatvf/TseKyHrgxZrKi0ii9zvM8655joi0845NF5F/ishsr40nBZ43iLa6VUQWet/tGyKSWNN34h3rKCITxf0f/SIiN1TTxkZVqKpt9bwBK4DrgD5AKdAu4NhLwDagP+6hoBmwCrgJiANGemXu8/JfDsyoVL8CXQLq8+cdCJQB93p1/QrYCbT0jr8MTALSgCzgR+Cqaq7hHqAYGIobxn0Z+AW4y6v7d8AvAfnfAf4DpABtgdnAtd6xLsBpQAKQDnwJ/Ms71hVYA3T00lnAoZWvLeD6cgLS2cACIBNIAg4C8rzr9nnnzAPSq7nGbODUgHSW17Yve9eR5O2/0muzBOBfwIJK32cecKzXTq8Br3vHhgLzgBaAAEcAHar43v4J/Ntr1zhcL1qq0Xg4sMO7tjjgdtzvLb6qNqnmuhWYBrTCGbkfcUN+B/Jd/RH34JXhlf0PML6a8w/E/U4f9PIm1VQeuBZ4D0gGYnD/V828Y9OBXOAo7zubCLwaQlvNBjp6bbEU+H1N3wnudzUP+AsQDxwCrASGRvq+Ey1bxAU09g0YgDMibbz0MuCmgOMvAS8HpE8G1vpvOt6+mdTeCBUBsQF5NwLHe/+8u4DuAceuBaZXcx33AFMD0r8BCoEYL53m6WgBtANKCLjpARcB06qp+yxgvve5i6fxVCCuUr7d1xZwfZWN0JUB6bHAK5Xq+Bi4rBod2VRthA6p4ftt4eVpHqDxuYDjvwKWeZ8H427wxwO+6q4N99Awyf+d7kfjn4E3A9I+3E14YFVtUs01KDAsIH0d8NkBfldLgSEB6Q64/4PYKuoc6P0WE4Mpj3sImAn0rKKu6cADAenuXt0xQbbVJQHHHwL+XdN3AhwHrK60707gxZra3LY9mw3H1T+XAZ+o6mYvPY5KQ3K4p0k/HYFc9X7NHqsO4Px5qloWkN4JpAJtcE90gXWvwvUeqmNDwOciYLOqlgek8eru5NW9zhu+2Ip7km0LICLtROR1bxhnO/CqpwdVXQHciDN6G718HUO43sC27ASc59fg6RiAu6GFwu46RSRGRB7whom2425c+PV7rA/47G9vVPVz4Cngady1/VdEmlVxvodxT+ifeENkd9SgrSMB36GqVnh6A7/HNZULVUFgnlVevQfyXXUC3glo96VAOe4BpSo2qWpxQLqm8q/gHiZeF5G1IvKQiMTVcC1xnuZg2qrK747qv5NOQMdKv7E/1XCdRiXMCNUjIpIEnA+cIu4dwnrcMFsvEekVkDXQ4KwDDhIRCdh3cMDnHbhhCP852tdS3mbck2WnSufJrWV9gazB9YTaqGoLb2umqv53J//AXXMPVW0GXIIb2gBAVcep6gBPm+KGaaDStQNVXXtgW67B9YRaBGwpqvpANbqrCykfuP+3wAjc039zXG+JQP01oapPqGof3BP64cBtVeQpUNVbVPUQnCPLzf53LVVoXEvAd+j9bjLZ+3sMJlR+ZsDng716ofbf1RrgjEptn6iq1f2+Kmustryqlqrq31S1O3AicCbuvWt111KK+70H01ZVi6v+O1mDG4YO1Jmmqr/aX52Gw4xQ/XIW7umtO9Db244AvmLvf5pAZuHGx28QkTgROQf3fsHP98CRItLbe2l6T22EeT2YN4H7RSRNRDoBN+OedA8IVV0HfAI8KiLNvJfMh4rIKV6WNNxQ3jYROYiAG7GIdBWRwSKSgHsHVQRUeIcX4F6gt/KM7437kfIq8BsRGer1YBK9l+AZ1eTfgBvTr4k0nIHNwxnEf+wn/25EpJ+IHOc9te/AXV9FFfnOFJEu3k1yG+435M9XWeObwK9FZIhX7y2evpnB6vK4TURaikgm7n3MG97+2n5X/8b9tjp5edNFZEQIeqotLyKDRKSHOEeX7TgjE9iOl4hIdxFJxg2jTQj4vdeqrWr4TmYDBeKcKpK839lRItIvhGtt0pgRql8uw40Nr1bV9f4NNyRzsVThqaSqu4BzcO9+tgAXAG8HHP8R94/1KfATMKNyHSEwBnczXOnVMw544QDqC+RS3IvaJUA+MIE9w2B/A47B/TN/QMD14V5CP4B7cl2PG8K70zv2Cs4IZ+OM3BvUgKquwfVa/gRswj213kb1v/t/And7wyq3VpPnZdyQTq53bd/UpKESzYD/w7XHKpwhe7iKfIfhvt9C3EPJM6o6rSqNqroc1zt5EtdmvwF+4/2OQmES7gX7Atx38ry3v7bf1ePAZNzwVQGunY4LQU9N5dvjfk/bccN0X+B+G35ewb1jW4/zLL0B4ADbqsrvxDNuZ+IeMH/x6n0O10s2gsDvcWMYhhH1iJsU/qqqPhdpLUZwWE/IMAzDiBhmhAzDMIyIYcNxhmEYRsSwnpBhGIYRMaI+UKDP59OkpKRala2oqMDniy47HG2ao00vRJ9m01v/RJvmYPTu3LlTVTXiFxX1RigpKYkdO3bUquz06dMZOHBg3QqqZ6JNc7TphejTbHrrn2jTHIxeESmqMUOYiLgVNAzDMJouZoQMwzCMiGFGyDAMw4gYUf9OqCpKS0vJycmhuLi4xnzNmzdn6dKlYVJVN9Sn5sTERDIyMoiLi9t/ZsMwjDqgURqhnJwc0tLSyMrKYu9g1HtTUFBAWlpaGJUdOPWlWVXJy8sjJyeHzp0713n9hmFEHyKSDRTgAraWqWrfuj5HoxyOKy4upnXr1jUaIEpL8RUVQWnpgZ2stBR27Ki5nmDyBHmuOtFcBSJC69atXe9x0yaYM8f9rY5g8gRDXZ2rDvWkLVt24PUYTZK8whK+X7OVvMKSBpGnjhikqr3rwwBBI+0JATUboLw8WLXKLUyTkwOdOkHr1vvmKy2FXbsgPh6qGqLy6kEEVKuuJ5g8IZzrgDXXcFxEnLHs08cd37ULnn8eLrpo7zrGj4errqo5D+y5oR95JKSn73s8mHrqKo+nh+xsyMqqUU8vnw9uvrnqevZXR7jzGA2GSQtyGTtxIXE+H6UVFTx0bk+G9z4oYnmihUZrhKqltNQZhYqKPStzZWdDebm7Kft8EBMDBQWwdu0e49GxI6Sluc+qrp7sbPc5sJ7i4j1lVGHDhn3zBJ5LBAoLYd26PeU6dIDUVKiocFtpqTM8qvtqjo119fh8+9aTkQEtWuw5/9atkJu79zUFnqesDDZvhqIitwFceil89527dp8Pdu6Ehx92ef15LrvMXWd6OiQlQWIizJwJDz/sbug33gh33w2nnLKn7g0bYPRod22B55o3z2kScfsffXTvc116KSxbtkfPjh3w97/vXc9ll8G2bdC+PaSkQHIyfPkl/O1vrt1LS+GOO+DEE135HTtg/Xq4804oK9vzT3HZZZCf7+pJTnbX9NBDe+p45BE455w97e/zwTvvwA037DGI//d/cMkle/8G69KwGg2CTdtLuPHfKylY3ZHyHQloWQxXTi/i8v5lJMe7X9TOXWW89HURZRVddpe7+tvtLH27Da1TEwDXuxk7cSHFpRUUe0sk3T5xIf27hJYnSGJFZG5A+r+q+t9KeRS3nIYC/6ni+AET9bHjUlJStPJk1aVLl3LEEUdUXWDHDvjxR3cDr0ey167lzJtu4oc3alzypsGxdPNmjjjjjEjLaFwkJDhjmJrqDPRPP+39YBITA1deCW3auDyqzmAGDrsmJbmHp8o9ok2bmDdxIn3OPTdqeksNaeJnXmEJOflFZLRMqvYGnldYwuxZMzj2hAG785SVwfz57tnmq69g+hcVbNsa+HbDfb9uQEZ276t8u41vtZPZC0rpldkCgO/XbOWS576loKRsd560hFhevfq4kPIEOVl1p6qm7CfPQaqaKyJtganAGFX9ssaKQ6Tp9YTi49nnlyAC3bq5vxUV7mk/J8d99uPzwUEHuZuBP9+KFXvXJQJHHeWelFu3djccf68jME/Xrq4+VWcUqzpXZqZ7+vb53LFly/atp1u3Pcd37oQ1a/auR8Q9xScmQkmJe9qvfJ6MjL3P8/XXe7dNUpLrdbVp445v2ABdurgenx9/zyclxfVGvvsOxoxx1xZYz8MPQ+/eLn9REZx6qtMVWM/q1e5cqrBxI3TuvO+5lizZO0+PHvvm+fxz93fnTne3GDvWffaTnAyPPw59+zrdxcVw7LH71jN9utM+d67r4QReU2Ii3HQTHHywa5vsbHjyyb3rSEiACy6AZs1cT3XNGli50t3F/FRUuJ5PcfHe+wMpKYHrr4cRI1wPLisLXn99/8OHRrWEMuz1+0PLufa6BZyUegSbVjRj5sw9P4XDDoMzf6N8tnUhvvZ5xDYrRmIrSIzz8fXYwQE9mF30f/Bzikv3/A8mxvnIaDl4dzqjZRKlgf+jQGlFBRktk0LKU1f4l2NX1Y0i8g5ulec6NUKoalRvycnJWpklS5bss28vNm9WnTdPK+bNU503T3XzZt1cUKwLVufr5oJi1V273P45c/Zs8+a5/VXUo999t7seP7/88ot27dpVf3vuudotK0vPHTJEd8yYoX8bO1b79u2rRx55pP7ud7/TipIS1Xnz9PFbbtEjOnfWHl266AWnn666a5cWFhbqFVdcof369dPePXrou48+upfmvdif5iCvacmcOapJSarNmrm/48bt237jxtWcZ+NGt3/PoKRLb9wYWj11lSdEPaUpKfvWE0wdB5qnokK1uFh1+XLVhIS98/h8qsnJe9Lp6W7f/q6pATJt2rRIS9D5i4u17bAfNPmIHI1ru1VjWxZoXIsdmnlwhWZkqHbooJqeXqExSSUqCbvUF1PuNXOFHnlUuY4erfrmm6pr1+6pc9L8HO169xQ96i8fade7p+ik+Tn7nDdceYJpY2CH1nBvBVKAtIDPM4FhNZWpzRZxI3KgW62MkKq7yW/YoLprl75b1Rdag4GpXI8WFu5zM//ll18U0BkzZqju2qVXjBqlDz/wgObl5e3Oc8kll+jkyZNVN2/WDm3aaPE336jOm6f5P/+sqqp33nmnvvLKK6qqmp+fr4d16aIbVq7c1xj62Z/mIK5pyZIl7kY2e3bNN7T95anphh5KPXWVJxhj5tUz99lnq64nXEazujylparz56s+84zqGWfsa4QSE1W//LLaJmoohMsIBT5Ylperzpql+qc/qfbosafJYprt0KRDNmjyETnavEeunnluiV5xherVV6uOvLhYW/VdpWl9Vurpw5dr+rmz9YjbPtUFq/ODOmck89SREToE+N7bFgN31ZS/tlvTeycUQEFBAbskvsou8tdjB9M6wVezp1kNZGdnc/LJJ7N69WoAPv/8c5544glGjRrFQw89xM6dO9myZQtjxozhjjvuYNjQoaQmJXHWWWdx1siRpKam0rdvX4qLi4mNdaOmW7Zs4e2336Zv3xo8JQ/AOw6Cb7ugaGjvK4L0NqtxPL2heMdt2uQ8JP3OGH6aNXMOFdde67wSgz1XGAnHO6FJC3K5bfxiSrLT2bo8HVnTgW1bYoiJgQEDYPDpZbyU8zUVzQp3l9l3+Kxk973hlh5lPLoodp88DZW6eicUDpreO6FK5OQXEefz7fYyAYjz+cjJL6J1ZouQjU8gld3ERYTrrruOuXPnkpmZyT333LM7qsMHU6bw5Zdf8t5773H/gw+yaNEiVJWJEyfStWvX3XUUFBTUfNK4uJo17+94XZKeTkG3bg3ixgc4HQeqJZg6wpEnPd29A7rqKsp8PmLLy+G22+Dnn+E//3Hvpvr3h5494cUX3bupRuRlV51DwZo18PqEUv72dDw7sodAeQySUErqoRv498PpnHdWHK1aAcTSe0EXbq/0TiiwrtapCTx0bk9un7iQGBES43z75DEOnCZvhOrzJd/q1auZNWsWJ5xwAuPGjWPAgAHMnDmTNm3aUFhYyIQJExg5ciQVFRWsWbOGQYMGMWDAAF5//XUKCwsZOnQoTz75JE8++SQiwvz58+nSpcv+T2w0DS66CE49le8r9zYffxxeegmefXaPo4nfWeKqq5xDSEN5MKgFgQ4Fu8or+F23Pmxb3pb33oPvvweII75VMmnHrCL50I0kZGyhWXIMx592HK1atdhdz/DeB9G/S5saveP8eWbPmsHXwweYAaoHmrwRCnzaqe6JqLZ07dqVp59+miuvvJLu3bvzhz/8gfz8fI466ijat29Pv379ACgvL+eSSy5h27ZtqCo33HADLVq04M9//jM33ngjPXv2pKKigs6dOzN+/PgD1mU0IqrqbbZpA7feCiedBIMH7+0VGBfnhuai1AjlFZZw2/jFbF2RTtGKthT93JbbdiTi8ykDBggPPwwDBu/i8ne+3GuIvboHy9apCfv9X2+dmkBSXIwZoHoirEZIRIYBjwMxwHOq+kCl448Bg7xkMtBWVVvUt65gnohCJSsri2XLlu2z/7777uO+++7bZ/+MGTP22ZeUlMR//vOfvfbtdzjOMPwccsi+0xFKSty7oQZMVUNtOTnw/vvw2ls+VnwxBPWG2ZI6b6LVEZt57W+dOLlHc6+GeB7y1c+DpVH3hM0IiUgM8DRwGpADzBGRyaq6xJ9HVW8KyD8GODpc+oJ5IjKMqCLgvRExMW6eUosWbk5YA8U/1BYrPgrXpnJ8TA9+nNOM+fPd8c6HxNKiTzZxh2wgMWMLEqMkxvk4snPXveqpjwdLo34IZ0/oWGCFqq4EEJHXgRHAkmryXwT8NUzaDKNx4r03IjvbhWQ66yw47zz4+OPwOagEiT8czZalbdj61eGUbmzOKlGOP76CBx/08ZvfQLduwnvfx3P7xHzifDE19nLswTI6CJuLtoiMxE10utpLjwKOU9XRVeTtBHwDZKjqPvF1ROQa4BqA2NjYPlOnTt3rePPmzYN6gV9eXk5MTEwtriZy1LfmFStWsG3btjqrr7CwkNTU1DqrLxxEm+ZQ9Lb7+GOOeOABckeM4Kcbb6xfYdVQnd6i0nJefLUtE145inYdCzhl6EqOOXYdPQ6JJylu7998eYWyq7yC+BgfMb4aghXXs+aGSjB6Bw0a1CBctMM2qRQYiXsP5E+PAp6qJu9Y4Mlg6q31ZFVV3b59e1D5GhL1rTnYtguWhjA7PlSiTXPIem+7zc3UfOaZetGzP6rSW1GheuMtpS7ww2HrNPPmKdpp7Pva9e4pNU7YDBeN8TfBfiarhmsL53BcLpAZkM7w9lXFhcD19a7IMJoi//yni783ZoyLPzho0P7L1CNlZXDNNfDii7EMPXcHv3RdQHysj9IKzKGgCRBOIzQHOExEOuOMz4XAbytnEpFuQEtgVhi1GUbTISYGxo2DE06AkSNh9mw49NCISNm5E84/Hz74AP76V/jrX1PYsmOQORQ0IcLmJqOqZcBo4GNgKfCmqi4WkXtFZHhA1guB173uYpPgnnvu4ZFHHgHg8ssvZ8KECSHXkZ2dzbhx4+pamtFYadYMJk92n3/zGxfZuy5Wpg2BvDwYMgQ+/NDNq73nHhf4vXVqAr0yW5gBaiKE1VdTVaeo6uGqeqiq3u/t+4uqTg7Ic4+q3hFOXY2B2hihsuqWDTCaBoceChMmwPLlcPjhcNppLh5dPU6Izissoai0nAVLSujf362yMWEC/P739XZKo4HTcCcMhJtNm+r8SfDll1+mZ8+e9OrVi1GjRpGdnc3gwYPp2bMnQ4YM2R3ctDrmzZvHKaecQp8+fRg6dCjr1q0DnAfbqaeeSq9evTjmmGP4+eefueOOO/jqq6/o3bs3jz32GMXFxVxxxRX06NGDo48+mmnTpgHw0ksvMXz4cAYPHsyQIUPq7FqNKOWoo1z3o7zcrUZbVOTmFdVDj2jSglz6P/g5M+b56He8kpNbwSefwNln1/mpjCiiyYftAeplKeXFixdz33337Y4Vt2XLFi677LLd2wsvvMANN9zAu+++W2X50tJSxowZw6RJk0hPT+eNN97grrvu4vHHH+fiiy/mjjvu4Oyzz6a4uJiKigoeeOABHnnkEd5//30AHn30UUSERYsWsWzZMk4//XR+/PFHAL777jsWLlxIKxfJ0WjKZGe7Bf4CI3HUQ2gf/xygrStb8Ni7fVFfOem//ZojjzkWsGG3powZoU2bnAEqKtoTFr8Ogjx+/vnnnHfeebRp0waAVq1aMWvWLN5++20ARo0axe23315t+eXLl/PDDz9w2mmnAW5+UIcOHSgoKCA3N5ezvcfHxMTEKsvPmDGDMWPGANCtWzc6deq02widdtppZoAMR1bWvqu5lpbWeWifnPwidi5vz4a3e9Ku3U5ih88htW2pi1Zv736aNGaEsrNdDyhwXZYGEORRVTnyyCOZNWtvJ8G1a9cecN0pKZGfn2Y0EPyhfa64wsWVi4tz6Tr+7X8yMYU1b/UmvuNWbvzzLP6drZRW+OplSWojurB3QllZbggukDp4Ehw8eDBvvfUWeXl5gFuQ7sQTT+T1118H4LXXXuOkk06qtnzXrl3ZtGnTbiNUWlrK4sWLSUtLIyMjY/cwXklJCTt37iQtLW2v4KYnnXQSr732GgA//vgjq1ev3mtdIsPYzUUXuYV4srLg+OPrdL0hVfjLX+D2m+Lod3IxnUbNplmzMlubx9iNGSH/k2BSknNbTUqqkyfBI488krvuuotTTjmFXr16cfPNN/Pkk0/y4osv0rNnT1555RUef/zxasvHx8czYcIExo4dS69evejduzczZ84E4JVXXuGJJ56gZ8+enHjiiaxfv56ePXsSExNDr169eOyxx7juuuuoqKigR48eXHDBBbz00kskJNg/vFEN6elwwQUwaxZs3VonVZaVuQVe//5319Ga+VkSs+4eSOf0FL4eO5jhvQ+qk/MYUU6kQzYc6FZnYXs2blSdPdv9bcBY2J76J9o015neWbNcOJ/XXjvgqnbuVB0+3FX3pz+5sDx+oq19VaNPczSF7bGekJ/0dOjXL2oX+zKMA+bYY6F9e6jGYzMY8gpL+HLRNgYOquC99+CJJ+D++50XuGFUhRkhwzAcPp+LnvDhh85JIUQmLcjl2D/N5PQhMcyZC7c+sAXPQdMwqqXRGiFtOlF/6gxrM4MRI9zid97k5mDJKyzh+n+uZ9WLx7NrWwJtz5vN5IJvySsM3ZgZTYtGaYQSExPJy8uzm2oIqCp5eXnVzjsymghDhkBKCkyaFHSRlSvhnLN85L7ZB19CGe1/+w2JnfKI8/nIyS/afwVGk6ZRzhPKyMggJyeHTfsJPVJcXBx1N9361JyYmEhGRka91G1ECYmJMGyYM0JPP13jUuDFxfDQQ25liJiYWNKHLCPp6JVIjHv4K62osHlAxn5plEYoLi6Ozp077zff9OnTOfroo8OgqO6IRs1GlDFiBEycCHPnOmcFj7zCkt1LLMz+KoExY+Dnn91SDI8+Kny3OY3bJ8p+l902jEAapREyDOMA+PWv3ZpDkybtNkKTFuQyduJCdHsyaz/uSuHy9nTtClOnughXABkZB9G/SxtbC8gICTNChmHsTatWcPLJzlX7/vvJKyzhtjd+YNPXh7BtVhcQpc3g5Ux7K4sOrfY2NK1TE8z4GCFhRsgwjH0ZMQJuvBFWrODNb9qz6r8D2LUlheSu62g5eAkt08vYuKPdPkbIMEKlUXrHGYZxgIwYAcD/zpnEdaNSUaDt+d+SftZ3xDYrNqcDo84IqxESkWEislxEVohIlaunisj5IrJERBaLiK1XbRhhZtcueOD1LBZKLw5dPIn774fxH26l5eFbSEuIteCjRp0StuE4EYkBngZOA3KAOSIyWVWXBOQ5DLgT6K+q+SLSNlz6DKMp4/d8+3lBMn+6LZ7ly6FztxGc/+N9DPjdJkg/iIHdzenAqHvC2RM6FlihqitVdRfwOjCiUp7fAU+raj6Aqm4Moz7DaJJMWpDLcX+ewcnDijh3eDzbdpYxZQpc8NoIpKICvNV6W6cm0CuzhRmgJoSIxIjIfBF5v77OEU4jdBCwJiCd4+0L5HDgcBH5WkS+EZFhYVNnGE2QvMISbvz3SrKfP5GCH9vSfMBy0i7+jGNPKoGjj4bMzJCiJxiNjj8CS+vzBBKu0DYiMhIYpqpXe+lRwHGqOjogz/tAKXA+kAF8CfRQ1a2V6roGuAYgNja2z9SpU2ulqbCwkNTU1FqVjRTRpjna9EL0aT4QvXO+S+Ovf+5BXFwF1972DZlZ24gRoXN6CklxMXR54gk6TJnC1+++S0UdReqItvaF6NMcjN5BgwbtVNVql1kWkQzgf8D9wM2qembdqvQI15oRwAnAxwHpO4E7K+X5N3BFQPozoF9N9Va1nlCwRNsaIarRpzna9KpGn+ba6n3rLdWEhAqNb12gB/3+M+009n3tNPZ97Xr3FN1cUOwyTZ3qFgV6992I640k0aY5yPWESoC5Ads1uvf9eALQBxgIvK+1uO8Hs4VzOG4OcJiIdBaReOBCYHKlPO96F4yItMENz60Mo0bDaBI8/rgLt9Onj/D8hAJS25RU7fl2yinQvLkNyTVOylS1b8D2X/8BETkT2Kiq8+pbRNi841S1TERGAx8DMcALqrpYRO4F5qrqZO/Y6SKyBCgHblPVvHBpNIzGTkUFjB0LjzwCZ58Nr70GSUkdOKNvq6o93+LiXBif99+H8nIXzsdoCvQHhovIr4BEoJmIvKqql9T1icIaMUFVpwBTKu37S8BnBW72NsMw6pCSErj8cnj9dRg9Gv71rz02pcZwOyNGwLhx8O23cOKJ4ZJrRBBVvRP3ygQRGQjcWh8GCCxsj2E0evIKS1iSXcyd16Xx9Vc+HnwQbrsthCW3Bw92fz/4wPWMsrIgPb2+5BpNDAvbYxiNmEkLcuk39htOG+Lj66/hpvu3cPvtIRgggDZtnKv2Aw/AaadBp04wfny9aTYaFqo6XevLMw4zQobRaNm0vYTf/3kL2c+dSOm2RNqeN5spRbVYcnvTJli71r1Q2rYNiorgqqvcfsM4QMwIGUYjZMECOG1wDOvf70F82+10uPJLkrJqueR2djYkVHpfFBfn9hvGAWJGyDAaEVu3wg03QJ8+kLsqhva/WUi7335DbLNioJZLbmdluV5QIKWlbr9hHCBmhAwjiskrLKGotJzNBSW8/DJ07QpPPw1/+AP8+KPwn3tbkxTvO7Do1+np8MIL7kVSbCwkJcHzz5tzglEnmHecYUQp/iW3z01J4tyrdlC0JoHjj4cPP4RjjnF5hresoyW3L7oIXn4ZVqyAmTPNABl1hhkhw4hC8gpLuH3CQjbN6sSDX3RD40tpf+YiJr92OOnN6mnJ7cMPh6+/dt5yhlFHmBEyjCjklw1FbJjci22LOtKzzzq29F9EixbK2m2Z+xihOiMrCwoKID8fWrWqn3MYTQ57J2QYUUZhIdx+bTO2LepIi5OWc9WNs4lJKq3/Jbf9jgjmFWfUIWaEDCOK2LgRBg2CL6f7GPPXfNqdspJYn4RnyW0zQkY9YMNxhhElrFwJQ4dCbi68+y6ceWZL8goHM3vWDL4ePqD+Vzzt3Nn9/eWX+j2P0aQwI2QYUcD8+XDGGW56zmefwQknuP2tUxNIiosJz5LbLVq4ZR2sJ2TUIWaEDKOBkldYQk5+ESsXJnPZRfG0aAHTpsERR0RQVFaWGSGjTjEjZBgNEP8coB1LOpI7qQeZWaV8PT2OjIwIC8vKgp9/jrAIozFhjgmG0cDIKyzhtjd+YN0nh5Pzdi/iO+YTf9Z0klqEGHi0PvD3hNzyz4ZxwJgRMowGxhvvlLLqvwPYPvtQUo/Opt0F35KYUhF64NH6oHNn5yOeZwseGyAiPhE5oJUOzQgZRgNh1So45xy4/tJUFKXt+d/S+vTFSIzW/xygYDE3bSMAVa0Anj6QOsJqhERkmIgsF5EVInJHFccvF5FNIrLA264Opz7DCBd5hSV8v2YreYUllJTAP/7hHA4+/hj++U8Y/+E2Wh6+5cACj9YHZoSMfflMRM4VCWmpxN2EzTFBRGJwFvM0IAeYIyKTVXVJpaxvqOrocOkyjHDjdzqI8/nYtrIF5V8dw9pVcYwcCY8+CgcfDHAQA7vXQeDRusaMkLEv1wI3A+UiUgQIoKraLJjC4fSOOxZYoaorAUTkdWAEUNkIGUajJa+wxHm9bY9h6/RuFC48mLgWO3nzHeW8s+L3yltngUfrkubNoWVLm7Bq7EZV0w6kvGiYvFxEZCQwTFWv9tKjgOMCez0icjnwT2AT8CNwk6quqaKua4BrAGJjY/tMnTq1VpoKCwtJTU2tVdlIEW2ao00v1K/motJyZn0vPPXA8WzLT2Twr37m1+f8SNeMRJLiYmpVZ7jbuM8117CrVSsWPfBArcrbb6L+CUbvoEGDdqpqSl2cT0SGAyd7yemq+n7QhVU1LBswEnguID0KeKpSntZAgvf5WuDz/dWbnJystWXatGm1Lhspok1ztOlVrV/NH31Wor6kEvWlFGn7S7/STmPf1653T9HNBcW1rjPsbXz22ardu9e6uP0m6p9g9AI7tG7u7Q8AnwFXettU4J/Blg/ncFwukBmQzvD27UZVA/0+nwMeCoMuwwgLH3wA550XT7s2ZSQOn0lK6xJKKxqQ00GwZGU5DwpVt9qq0dT5FdBbnaccIvI/YD5wZzCFw2mE5gCHiUhnnPG5EPhtYAYR6aCq67zkcGBpGPUZRr3x/PNw7bXQuzdMmRJLTPIJDc/pIFiysmDnTti82VZYNfy0ALZ4n5uHUjBsRkhVy0RkNPAxEAO8oKqLReReYK6qTgZu8MYWy3AXdHm49BlGfaAK990Hf/mLi4A9YQK4ofoG6HQQLIHRtM0IGe49/nwRmYbzjDuZIHtBEObYcao6BZhSad9fAj7fSQjiDaMh4g882j4tib/ekcB//gOXXgrPPQdxcZFWVwcEumkfe2wklRgNAFUdLyLTgX7errGquj7Y8hbA1DDqEP8coJjyWFZP7Enhj+244w43GbXRvD7p1Mn9tblCBiAin6nqEGByFfv2ixkhw6gjds8B2hbLpol9KVnbgrZDF3PrXV0QidKht6po1gxatTIj1MQRkUQgGWgjIi1xQ3EAzYCDgq3HjJBh1BGr84ooWHAw6z89jIrSGNqM+I62vTaTk39Q9L7/qY6sLJuwalwL3Ah0BOaxxwhtB54KthIzQoZRB8ybB9f8vhlr57YgISOPVqcvJj69gNIKX8MIPFrXdO4MixdHWoURQVT1ceBxERmjqk/Wth6Lom0YB8CWLfCHP0C/fpC7xsdN922h02WzaZ1R1LACj9Y1tq6QsYcKEWnhT4hISxG5LtjCIfeEROSfwJ89l2sfkKqq20OtxzCiEb/nW8fmSUx+K4GxYyE/H264Af72N2jevBV3FQ6O3jlAwZKVBcXFsHEjtGsXaTVGZPmdqu5ezkFV80Xkd8AzwRSuzXBcqqqWeSerEJHHgKtqUY9hRBV+z7eyDc3JndKd4twEBgyAp5+Gnj335GuQgUfrGr+b9i+/mBFqpHiOB18CCThbMUFV/1pF1hgRES8UkH/FhPgq8lVJbYbjKve/C2pRh2FEFX7Pt02zM/j5uRPYlZ9E++Hf886Ukr0MUJPBP2HVPOQaMyXAYFXtBfQGhonI8VXk+wh4Q0SGiMgQYLy3Lyhq0xP6TkQeAf4FlANta1GHYUQVa7YUseWLw9ny1aEkHbqBNmcuoHlzyN3aiTZpjbzXUxU2V6jR4/VsCr1knLdV9RJwLM5T7g9eeiou9mdQ7NcIicgRqro7hpuqvuRZw7tx3bT7gj2ZYUQjZWXwyJ/T2PRVC1J7rqbV0B8QnzZez7dgSE2FNm3MCEU3sSIyNyD9X1X9b2AGb2htHtAFeFpVv61cifda5iXcqgfLQxYRRJ4PROQL4K+quto76TfAN6GezDCijZ074cIL4b33Yjj/6u0saLeY+JgYSisqGq/nW7D4PeSMaKVMVfvWlEFVy4HenvfbOyJylKr+EJjHi/f5MO49UGcR6Q3cq6rDgxERjBHqhutqfSEik4H7VHVTMJUbRjSTlwe/+Q18841zPrjuumbkNQXPt2DJyoKFCyOtwggDqrrVC1A6DPih0uG/4lbOnu7lXeCtlhAU+3VMUNVd3kSkI4A1wGwR+buIBLV+uGFEI6tXw4AB8N13LvL1dd6sh9apCfTKbGEGCJxzwqpVUFERaSVGPSAi6f75PyKSBJwGLKsia6mqbqu0L+gJZEF7x6lqsao+AhwFFAHzROTWYMsbRjSQV1jCkh8TOe54Zd06+OQTOOecSKtqoGRlQUkJbNgQaSVG/dABmCYiC3HrwU3VqpftXiwiv8W5ah8mIk8CM4M9SdDecSKShRua6wocjHPN/gfwSLB1GEZDZtKCXMb8vzVsntiH0pgSHn1+GyefbHNgqiVwSYcOHSKpxKgHVHUhcHQQWccAd+Fcusfj1oz7e7Dn2W9PSEQWikge8A5wGW7VvM+AS4HUYE9kGA2Z7LUlXHHtLta8ehzNWhTT7uKZPLPwO/IKSyItreESOGHVaLKo6k5VvUtV+6lqX+9zcbDlg+kJnQX84p8NaxiNCVV44w244Y9x5G/MIrX3am76w2KeXanE+WLJyS+y9z/VYXOFmjQi8h41vPupM+84VV0Zgi7DiBqWL4frr4fPPoOevSHp17OQtvkkp5QBsZRWVDTdeUDBkJICbduaEWq61MmrmLAu5SAiw4DHgRjgOVV9oJp85wITgH6qOreqPIYRKv7go60SkvjPEwk89BAkJ8NTT8Hvf+/jg0WduH3iNmJEGncE7LrE5go1WVT1i7qoJ2xGyJt5+zTOzS8HmCMik1V1SaV8acAfgX1m5hpGbfEHHy1a0Y51H3ajdBuMGgUPP7wn/ubw3gfRv0sbZs+awdfDB5gBCoasLJg/P9IqjAggIouoejhOcFF/goqqGIp3nAAXA4eo6r0icjDQXlVnB1nFscAK//CeiLwOjACWVMr3d+BB4LZgtRlGTeQVlnD7m4vIfe8odvyQSVzrAjIv+ZbHnum9j6FpnZpAUlyMGaBgycqCd991c4V8tjxZE+PMuqhEgvU3EJFngQpcVNUjvDXFP1HVfkGWHwkMU9WrvfQo4DhVHR2Q5xjgLlU9V0SmA7dWNRwnItcA1wDExsb2mTp1alDXUJnCwkJSU6PLwS/aNDcEvXnb4O67u7Psh7YMPWs5Q89aTkIcdE5PISkuZp/8DUFzKERSb8dJkzj8X/9i5ptvsis9Pagy0da+EH2ag9E7aNCgnaqaUhfnE5F2gN8WzFbVjUEXVtWgNuA77+/8gH3fh1B+JO49kD89CngqIO3DhX3I8tLTgb77qzc5OVlry7Rp02pdNlJEm+ZI612/XrVn73JFyrX1GQu009j3tdPY97Xr3VN0c0FxlWUirTlUIqr3ww9VQXXGjKCLRFv7qkaf5mD0Ajs0yPt3TRtwPrAK+B/wMvALMDLY8qG8Eyr13uv4Fy5Kx/WMgiUXyAxIZ3j7/KThojFMdyN/tAcmi8hwNecEoxasWAFDh8K6dT7+/Phm3ty4ljhfrAUfrUsCJ6z27x9JJUbkuAvnRLYRdtuGT3HOZfslFCP0BG7CalsRuR/Xs7k7hPJzgMO8wHa5wIXAb/0H1cUeauNP1zQcZxj7Y+5c+NWv3KuKadPguOPa8EcLPlr3+OcK2YTVpoxP9x5+yyOEkHBBGyFVfU1E5gFDcN4PZ2nAOkNBlC8TkdG4kA4xwAuqulhE7gXmqurkYOsyjJr4+GM491xIT4ePPoKuXd3+JrHsdrhJSnLuheam3ZT5SEQ+xoXsAbgA+DDYwiG5aKvqMqqOohps+SnAlEr7/lJN3oG1PY/R9PDPAZr5UQo3XBfHkUfChx9aSLOw0LmzGaEmjKreJiLnAAO8Xf9V1XeCLR+Ki/bNVezeBsxT1QXB1mMYdc2kBbncPmEh2749hA2fdqXnscV88UkizZtHWlkTISsL5syJtAojQnivWKao6tteOklEslQ1O5jyoTj29wV+DxzkbdfiFjj6PxG5PSTVhlFH5BWWcPuEhaz7uCsbPu1Kcre1FA3+grIYCzwaNrKy3AJM5eWRVmJEhrfY20mt3NsXFKEYoQzgGFW9RVVvAfoAbYGTgctDqMcw6oyV64vY8G5vCuYeQlqfX2gzfD4J8ZCTXxRpaU2HrCwoLYW1ayOtxIgMsaq6y5/wPscHWzgUI9QWt16En1KgnaoWVdpvGGFh+3a45epmbFvcgRYDl9JyyBJEsMCj4SbQTdtoimwSkd0Rs0VkBLA52MKhOCa8BnwrIpO89G+AcSKSwr6hdwyjXlm3Ds44AxYv9nHj37fwYUm2zQGKFJ07u7/Z2XDSSRGVYkSE3wOvichTXjoHF4wgKEJx0f67iHwI+Gek/T5gDs/FwdZjGAfK8uUwbBhs2gTvvw9Dh7bibpsDFDkOPtj9tZ5Qk0RVfwaOF5FUL10YSvlQo2j/jBvCSwSSReRkVf0yxDoMo9Z8+y38+tcuVub06dC3r9tvc4AiSGKi84W3CatNmlCNj59QXLSvxi2xkAEsAI4HZgGDa3NiwwgW/xygJd+mcPVlcbRv7yakdukSaWXGbmxdIaOWhOKY8EdclNRVqjoIOBrYWh+iDMPPpAW59H/wc349eg2/PT+GDp12MXOmGaAGhxkho5aEYoSKVbUYQEQSvOgJXetHlmHsmQO04cvO5E7uQWKnPHxnTic2xZwxGxydO8OaNVBWFmklRpgRkWQR+bOI/J+XPkxEgl5rKBQjlCMiLYB3gamel9yqUMQaRiis2lzE5k+OZOuX3UjpnkvbkXNISFKbA9QQycpyBig3d79ZjUbHi7hpOid46VzgvmALh+Idd7b38R4RmQY0J4QgdYYRCsXFcM+NaWyZ04Jmx/5Mi4HLbA5QQyZwrpA/srbRVDhUVS8QkYsAVHWntxJ3UATdExKRB/2fVfULL+p10NbOMIJl61a3DtB7k2K48patdDj9R5olxpIY57M5QA0Vm7DalNklIknsWWvuUEIIYBCKi/ZpwNhK+86oYp9h1JrcXDcHaPlyGD8eLrywBXk2B6jhc/DBIGJGqGnyV+AjIFNEXsPNJb082ML7NUIi8gfgOuBQEVmIW0sI3EqoX4eq1jCqY+lS1wPautUtwzBkiNtvc4CigIQE6NjRjFATRFWnish3uGk7AvxRVes0bM9ruDWA/gnc4Z1EgQJVzQ9dsmHswT8HaO3yZC4+P574ePjiCzj66EgrM0ImK8smrDZBROQY7+M67+/BItIcN51nv+6SwRihXJzRESDQ7U5ERFW1WSiCDcPPpAW5jJ24kKKf2rFmYi86dCxjxvTY3aHIjCgjKwtmzIi0CiP8PAMcA/hHyo4CFgPNReQPqvpJTYX365igqmmq2izgb7PAdF1cgdH0yCssYezEhWyacxCr3zyauPQCks79gmbpNgcoasnKgpwcmDXLBfYzmgprgaNVta+q9sEFMliJ8yN4aH+FQ5kndMCIyDARWS4iK0TkjiqO/15EFonIAhGZISLdw6nPCB9rthSR/9VhbPm4J4mdN9Huwm9ISiuzOUDRzMaNbmG7oUOdm/b48ZFWZISHw1V1sT+hqkuAbqq6MpjCIRkhEeklIqO9rVeIZWOAp3Eedd2Bi6owMuNUtYeq9sZZ0P8XyjmM6KC8HP71tzQ2ftGFlKPW0Pacufjiy20OUDSzaRP873/uc0EBFBXBVVdZjyiKEZFMEZkmIktEZLGI/LGarItF5FkROcXbngGWiEgCbt25GgllntAfcU4Kbb3tVREZE2x54Fhghaqu9Fbeex0YEZhBVbcHJFPw/M6NxkNREYwcCf97IYaRVxVw0IgfaJYcY3OAop3sbIivtJhmXJx5y0U3ZcAtqtod5/l2fTWjU5cDK4AbvW2lt68UGLS/k4hqcPd5zz37BFXd4aVTgFmq2jPI8iOBYap6tZceBRynqqMr5bseuBm3POxgVf2pirquAa4BiI2N7TN16tSgrqEyhYWFpKam1qpspIg2zYF6t2+P5a67erB4cTPGjFnB2WfnUl6h7CqvID7GR4wv6EnW9Uo0t3GkiNu6leMvuICYXbtXeaY8IYFvXn+d0hYt9srbEPSGSrRpDkbvoEGDdqpqSrB1eqHanlLV2t1wq0NVg9qARUBiQDoRWBRC+ZHAcwHpUd4FVZf/t8D/9ldvcnKy1pZp06bVumykiDbNfr2rV6t2764aH6/61luR1bQ/orWNI864caqgGhenmpTk0lXQYPSGQLRpDkYvLqrB3IDtGq3+fpwFrAaaVXHsMGACboXtlf6turoqb6FETHgBt7z3Ozg3vBHA8yGUzwUyA9IZ3r7qeB14NoT6jQZGXmEJRaXlfDFrFxefF09BgVsHaODASCsz6oWLLoIHHoCUFJg0CdLTI63IqJkyVe27v0zeiqkTgRt171cmfl7ERU14DDf8dgUhvOoJxTFBgNHAFiAPuEJV/xVC+TnAYSLSWUTigQuByXudQOSwgOSvgX2G4ozowL8O0AefJTNooI/i0nK++soMUKOnc2fYvt0MUCNBROJwBug1VX27mmxJqvoZ7vXOKlW9B3f/DopQekJpwL9xRugNnG940KhqmYiMBj4GYoAXVHWxiNwLzFUXEHW0iJyKe6GVD1wWyjmMhoF/HaDNczJ49tMjiW1TQPML53HQIf0Bczxo1GRmwrRpkVZh1AFeJOzngaWqWpOncomI+ICfvHt8LhD0C7RQlnL4G/A3EekJXAB8ISI5qnpqCHVMwYUACtz3l4DP1bkAGlHEtFkl5LxyHDtXt+KInhsoHDyf5GZCTn6Reb81djIzXU9o+3ZoZnPZo5z+uHf3i0RkgbfvT959PJA/AsnADcDfcUNylwZ7ktpMVt0IrMcNybWtRXmjkbJ9O9x8M1x4Rholm1JpNWwh1976Db4EmwPUZMjIcH9zciKrwzhgVHWGqoqq9lTV3t5W2QABZKlqoarmqOoVqnoucHCw5wllntB1IjId+AxoDfxOg3TPNhofeYUlfL9mK3mFJai6yfHdusG//gVXXy28NCWP9L65xMWIzQFqSmR6vkdr1kRWhxFO7gxyX5WE8k4oE+cdsSCEMkYjxB94NM7nY8emJNLmHcvC2Yn07eucovr1A+jAGX1bMXvWDL4ePsAMUFPBb4SsJ9ToEZEzgF8BB4nIEwGHmuEmugZFKO+EgrZsRuPFH3h0507YPusQts0+BF9sBQ89VsrNY+KIidmTt3VqAklxMWaAmhIdO7rF7awn1BRYC8wDhnt//RQANwVbSSg9IcMgJ78I2ZnIhteOYdeG5qQcmUPm0J84/dyjiYlpEWl5RqSJj4d27cwINQFU9XvgexF5VYNYN6g6zAgZIbFrSxI/v3AcZTviST93DsldNqJxPnM6MPaQmWnDcU0AEVmEF9/TeXPvTbA+A2aEjKCZOxd+/asEEimn5SXf0iyzgNIKczowKpGRAcuWRVqFUf+cuf8s+8eMkBEUU6fC2WdDmzbw1ccxtDmoDzn5RWS0TDIDZOxNZqb7wai690NGo0RVV/k/i0g7oJ+XnK2qG4OtJ6yL2hnRybhx8Otfw6GHwsyZ0LWrczroldnCDJCxL5mZUFjoJo4ZjR4ROR+YDZwHnI+LMToy2PLWEzL2Ia+wZHcv53//TeCWW1zMt3ffhebNI63OaPD4J6yuWWM/mKbBXUA/f+9HRNKBT3GRtfeLGSFjL/xzgGLFx9qph5H/zSGMHAmvvAKJiZFWZ0QFgRNWjzoqslqMcOCrNPyWRwijbGaEjN345wAVFUHeR0eyY3EGLfqs4unn2pOYaMNuRpDYhNWmxkci8jEw3ktfQKUYoTVhRsjYTU5+EcW/pLN2SjfK8lNpcdJyDhqYzbrtzWnb3IyQESQdOtiE1SaEqt4mIucAA7xd/1XVd4Itb0bIANz94s9j0lg1qS+xLQtpe963JB2ymTK1OUBGiMTFOUNkRqhJICI3A2/UsN5QjZgRauLs2gWPPQb33guqMVwyehvfpn5DQjw2B8ioPTZhtSmRBnwiIv615t5S1Q3BFjYj1MQI9Hxb8G0C118Py5fDWWc5Y5SV1Zy8woE2B8g4MDIy4IcfIq3CCAMHutacGaEmhN/zjcIk1n7SlYIlHTj0UPjgA/jVr/bka52aYMbHODAyM+HDD23CatOiVmvNhXWyqogME5HlIrJCRO6o4vjNIrJERBaKyGci0imc+hozfs+3/J9a8uMz/Sn8sS2tT/mRL74p2csAGUadkJkJO3dCfn6klRj1zIGuNRe2npCIxABPA6cBOcAcEZmsqksCss0H+qrqThH5A/AQrntnHCA5+UXsWNKRje/2IK5VIennzqVVu1I2F7XlIKzXY9QxgW7arVpFVotR3xzQWnPh7AkdC6xQ1ZWqugt4HRgRmEFVp6nqTi/5DZARRn2NmvfHpZLzdi8SDsqn/cWziGtRZEtuG/VHYNQEo1GjqnceyGKnoqp1KKeGE7lYQsNU9WovPQo4TlVHV5P/KWC9qt5XxbFrgGsAYmNj+0ydOrVWmgoLC0lNTa1V2UgRquaKCvjvfw/hjTcO5oT+Gzj/6jnEx1egQEbLJJonxdWfWJpGG0eahqg3YdMmTjj/fH686SbWDh++17GGqHd/RJvmYPQOGjRop6qmhElS9ahqWDZgJPBcQHoU8FQ1eS/B9YQS9ldvcnKy1pZp06bVumykCEVzSYnqJZeogur116uWlaluLijWBavzdXNBcf2JDKCxt3FDoEHqLStTjYlRveuufQ41SL37Ido0B6MX2KFhuv/XtIXTOy4XN3boJ8PbtxciciouIN4pqloSJm2NjoICGDkSPvkE7r8f7rzTOSmZ55sRFmJibMKqERThNEJzgMNEpDPO+FwI/DYwg4gcDfwHN2wX9HoUxh7yCkv4/sdibr46jR8W+njhBbjiikirMpokmZlmhIz9EjbHBHVrkI8GPgaWAm+q6mIRuVdE/IPGDwOpwFsiskBEJodLX2Ng0oJc+o39hjNOjWPhIuVPj202A2REDouaYARBWCerquoUKkVXVdW/BHwOaoatsS95hSX88als1ow/HlRod9E3vLlxO38sHGzDb0ZkyMiAyZNtwqpRI7ayaiPhzUmlrHn5OCS2nPYXzySh41bifD5y8osiLc1oqmRmQnEx5OVFWonRgDEj1Ah49VW44fIU4lrtpP0lM4lrvQPA5gEZkcXWFTKCwIxQFKMKjzwCo0bBSScJL75VSGqrUtISYkmMswjYRoSxCatGEFgA0yilogJuuQX+9S84/3x4+WVISOjI6Ue3tgjYRsMgcJlvw6gGM0JRSEkJXHYZvPEG3HCDW4LB5/VpbR6Q0WBo1w5iY204zqgRM0JRRF5hCXlb4bShFXz1hY8HH4TbbjPHI6OBEhMDHTtaT8ioETNCUcKkBbnc/OJySt7tQ24O/PHeLdx+u0UnNho4NmE1ahGRF4AzgY2qelR9ncccE6KAvMISrvvHerL/bwCbNqTQ9ty5fLTrW/IKLaqR0cCxCavRzEvAsPo+iRmhBs4vv8DIc3ysfasPsc2KuO3vX5B0yCabA2REBxkZzgiFKVq/UXeo6pfAlvo+jxmhBkpxMfz979C9O8yZGUv6kGW0H/U17ToWAjYHyIgSMjOdJ82mTZFWYuxLrIjMDdiuiYiISJzU2Je8wpLdrtWzv0pgzBj4+We44AJ45BHhu81p3D5RiBGxOUBG9BA4YbVt28hqMSpTpqp9Iy3CjFADYNKCXMZOXIhuT2btx10pXN6ebt3g009hyBCXJyPjIPp3acPsWTP4evgAM0BGdBA4V+iYYyKrxWiQmBGKMHmFJYyduJAti9PZ/N7RIEqbwcv4/K3OdGi1t6FpnZpAUlyMGSAjerCoCcZ+sHdCESYnv4jCRRlsercPcenb6Xj1F7QfsIqNO8zpwGgEtG0LcXFmhKIQERkPzAK6ikiOiFxVH+exnlCE+WVRMrnvHUniwZtJP2cevvhySit85nRgNA58vj0eckZUoaoXheM8ZoQiyIoVcNWoeDI6lZJ47gISk4XSCnM6MBoZGRnWEzKqxYxQhNi2DYZ768lOnxpHi3YnW+BRo3GSmQkzZ0ZahdFAMSMUAcrL4cIL4aefYOpUOPRQAAs8ajRSMjMhN9eFfvfZa2hjb8L6ixCRYSKyXERWiMgdVRw/WUS+E5EyERkZTm3h5Lbb4KOP4OmnYeDASKsxjHomIwNKS2HjxkgrMRogYTNCIhIDPA2cAXQHLhKR7pWyrQYuB8aFS1e4ef55t/TCDTfANRGZn2wYYcbWFTJqIJw9oWOBFaq6UlV3Aa8DIwIzqGq2qi4EKsKoK2x8+SX84Q8wdCg8+mik1RhGmLBlvo0aEA1TYEFveG2Yql7tpUcBx6nq6CryvgS8r6oTqqnrGuAagNjY2D5Tp06tlabCwkJSU1NrVTYUyiuUVTnx3DSmH82bl/HMM9+RmlpWq7rCpbmuiDa9EH2aG7reuPx8+p9zDj+NHk3uuec2eL1VEW2ag9E7aNCgnaqaEiZJ1aOqYdmAkcBzAelRwFPV5H0JGBlMvcnJyVpbpk2bVuuywfLu/Bw99MZPNaFNgfoSS/TZd9cdUH3h0FyXRJte1ejT3OD1VlSoJiSo3nqrqkaB3iqINs3B6AV2aJju/zVt4RyOywUyA9IZ3r5GS15hCTf992dWvXwcu7Ylkn7OPP41d76tA2Q0LURswqpRLeE0QnOAw0Sks4jEAxcCk8N4/rCyYwfcPlbJ/s8AKnYk0Pb82SRmbrF1gIymiU1YNaohbEZIVcuA0cDHwFLgTVVdLCL3ishwABHpJyI5wHnAf0Rkcbj01RWqMGECHHEEvPBMImlHraXj76aTmJEP2DpARhPFlvk2qiGsk1VVdQowpdK+vwR8noMbposaAtcB2pzr1gGaOhV69YLx4yEvRbh9YhlxvlhKKyosJI/RNMnMhLVr3UxtwwjAIiYcAP51gGLKY1n/xSFsn30IycnCE084V+zYWAC3DpCF5DGaNBkZUFYGGzZEWonRwDAjVEv86wBtX5vCpnePoWxLKs165PDNu+kccci+6wCZ8TGaNDZh1agGC+RUS3Lyiyjb0Jz1r5yIlsTS9oJvOPjsxeyKM6cDw9gHm7BqVIP1hGpJbEkSq14/Gl9iKe1HfU1sWomtA2QY1RG4wmrr1pHVYjQorCdUC4qL4apLEogpTSDjgnm0bFNOYpytA2QY1dK6NSQm2nCcsQ/WEwoRVbj6avj2W5g40ccpp/czpwPD2B8ibkjOhuOMSpgRCpF//ANeew3uuw/OOQdsHSDDCBKbK2RUgQ3HhcDEiXD33XDxxfCnP0VajWFEGRY1waiCRtkTKi0tJScnh+Li4hrzNW/enKVLlwZV565dkJoKn38O7drBsmV1oTR0KmtOTEwkIyODuLi4yAgyjGDJzIR16xCbsGoE0CiNUE5ODmlpaWRlZSEi1eYrKCggLS1tv/Xt2gVLl0KHDi4cTyTv94GaVZW8vDxycnLo3Llz5EQZRjBkZkJ5OfFbtkRaidGAaJTDccXFxbRu3bpGAxQMZeUVFBaX8dMKpbwcunSJrAGqjIjQunXr/fb4DKNB4LlpJ9gy30YAjbInBBywAdq6cxc5+UWU5idTXgwdMstITm54zXWg12kYYcObsGpGyAikUfaEDpSy8gpngLYnUF4cR0xaMfllOygrb5SrjhtGePAboU2bIizEaEiYEaqCkrIKSrclUb4jEV9yCTEpJQiwKwQjlJ2dzVFHHVV/Ig0j2mjRApKTzQgZe9HwxpcihH9Jho7Nk9i6IZ7ynbHEpBQTk+betygQH2M22zBqjTdhNdGG44wA7K6KW5Kh/4Ofc/Fz3zLgwc/5YNFa2rQvI65ZCTEi+ETIaJlEbIhGqKysjIsvvpgjjjiCkSNHsnPnTu6991769evHUUcdxTXXXINb6h2eeOIJunfvTs+ePbnwwgsB2LFjB1deeSXHHnssRx99NJMmTarzazeMsJKZaT0hYy+avBHyL8lQXFpBYUkZJeUVPPvdQtJalNOtfRqd01Po1j6NFsnxIde9fPlyrrvuOpYuXUqzZs145plnGD16NHPmzOGHH36gqKiI999/H4AHHniA+fPns3DhQv79738DcP/99zN48GBmz57NtGnTuO2229ixY0edXr9hhJU2bUhcuxbMEBkeTd4I5eQXEevbuxniY3xuf4yP5PjYkHtAfjIzM+nfvz8Al1xyCTNmzGDatGkcd9xx9OjRg88//5zFi90K5j179uTiiy/m1VdfJdathscnn3zCAw88QO/evRk4cCDFxcXkWOwtI1oZPx4mTCBu2zY4+GCXropNm2DOHDNUTYSwGiERGSYiy0VkhYjcUcXxBBF5wzv+rYhk1ZeWsvIKKlRpFpvArrK9HQ5KKyrqZEmGyu7TIsJ1113HhAkTWLRoEb/73e92z/H54IMPuP766/nuu+/o168fZWVlqCoTJ05kwYIFLFiwgNWrV9O1a9cD1mUYYWfTJrjqKigrQ8CFor/8cvjqK9i4cc+y3+PHQ6dOcNpp7u+BGKo6zJO2bFlwRjHMuhqDsQ6bERKRGOBp4AygO3CRiHSvlO0qIF9VuwCPAQ/Wh5atO3exbH0BW7f5yFubyJjjepIY6yMtIbZOl2RYvXo1s2bNAmDcuHEMGDAAgDZt2lBYWMiECRMAqKioYM2aNQwaNIgHH3yQbdu2UVhYyNChQ3nyySd3vzeaP3/+AWsyjIiQnQ3xlYa0d+2Ck092cbDi4qBNGxeYsagItm1zfy+9FG69FR58EJ58El54AcaMcRNfBw1yf//5T/jxR8jNhfx8KCmBceP2b8yCMXhenl633lqzUQyxvrDkOUD212mos/P4b3D1jYicANyjqkO99J0AqvrPgDwfe3lmiUgssB5I1xpEpqSkaOX3JEuXLuWII46oMn9ZeQXL1hdQtjOOsm1JSFw58a120rZ5HOu3ldTZkgzZ2dkMGzaMvn37Mm/ePLp3784rr7zCP/7xD8aPH0/79u05/PDD6dSpE3fddReDBg1i27ZtqCqXXHIJd9xxB0VFRdx4443MnDmTiooKOnfuzPjx4/cJNVTT9Uaa6dOnM3DgwEjLCIlo0xwVejdtcjfLooCVh+Pj4amnnNHYuBEWL4bJk6GsrO7PLwKHHw4xMS5dXu4MV+CtpTZ5/NS2Pp8P1q+H9HSXrqqdkpJg1aqQ8gTzmxCRnaqaUs2xGOBH4DQgB5gDXKSqS2qstBaE0wiNBIap6tVeehRwnKqODsjzg5cnx0v/7OXZXKmua4BrAGJjY/tMnTp1r3M1b96cLl26VKmjQpWS0gpKimMo3J5AyzY78fkgIc6HLwqiD5SXlxNT6R9gxYoVbNu2LUKKaqawsJDU1NRIywiJaNMcLXrTP/uMbg8/TEVMDL7ycpbddhubhgzZfTxu61aOv/BCYkpKdu8rT0jgm3HjKE9OJqakhGY//MAR999PbMANuDwhgdW//S27WrXCV1xMck4OHaZMwVdaujtPRUwM23r1otR7gIsrKKD599/jCwimWps8u7XXtr7YWOY/+SQF3boBkLZsGb1uvZXYgAfrspQUvn/kkZDyBPObGDRoUE1GaL+dhjpDVcOyASOB5wLSo4CnKuX5AcgISP8MtKmp3uTkZK3MkiVL9tnnp7SsXBflbNXv1+Tr+s35+v2afF2Us1VLy8qrLdOQ2L59+z77arreSDNt2rRISwiZaNMcVXo3btS5zz6runFj1cfHjVNNSlJt1sz9HTdun/KalKTq+hNuS0rau75w5mmguoL5TQAlwNyA7RoN4X5dV1s4HRNygcyAdIa3r8o83nBccyCvLkXExvjIaJmETwSBWs8BMgyjFqSnu6d1/9BSZS66yA0rffqp+3vRRfuU5/nn3fBTs2bu7/PP711fPeQpS0mpOk+EdVWbJzjKVLVvwPbfUCuoC8IZMWEOcJiIdMYZmwuB31bKMxm4DJiFs8SfexY7ZFS12uCeLZLjSU2IZceOQrq1SI1qA1TL5jGMhkt6es031IsuglNPdc4OWVlV563jPN9PnEifc89tcLpqzHNgBNNpqBPCZoRUtUxERgMfAzHAC6q6WETuBeaq6mTgeeAVEVkBbMEZqpBJTEwkLy+vxuUcYmPcO6BoN0B5eXkkJiZGWophhJf9Gao6zlNj7y2CuurB+PgJptNQJ4Q1dpyqTgGmVNr3l4DPxcB5B3qejIwMcnJy2LQf//ni4uKou4FX1uxfWdUwDKOuqK7TUB/napQBTOPi4oJaaXT69OkcffTRYVBUd0SjZsMwoo+qOg31QfSORRmGYRhRjxkhwzAMI2KYETIMwzAiRtgiJtQXIlIBFO03Y9XEAvUQI6ReiTbN0aYXok+z6a1/ok1zMHqTVDXiHZGoN0IHgojMVdW+kdYRCtGmOdr0QvRpNr31T7Rpjia9EbeChmEYRtPFjJBhGIYRMZq6EYpIrKQDJNo0R5teiD7Nprf+iTbNUaO3Sb8TMgzDMCJLU+8JGYZhGBHEjJBhGIYRMZqsEQrX+um1RUQyRWSaiCwRkcUi8kdvfysRmSoiP3l/W0ZaayAiEiMi80XkfS/dWUS+9dr5DRGJj7TGQESkhYhMEJFlIrJURE5oyG0sIjd5v4cfRGS8iCQ2tDYWkRdEZKO3UrJ/X5VtKo4nPO0LReSYBqT5Ye93sVBE3hGRFgHH7vQ0LxeRoQ1Bb8CxW0RERaSNl24QbVwdTdIIeeunPw2cAXQHLhKR7pFVtQ9lwC2q2h04Hrje03gH8JmqHgZ85qUbEn8ElgakHwQeU9UuQD5wVURUVc/jwEeq2g3ohdPeINtYRA4CbgD6qupRuOjGF9Lw2vglYFilfdW16RnAYd52DfBsmDRW5iX21TwVOEpVewI/AncCeP+HFwJHemWe8e4p4eQl9tWLiGQCpwOrA3Y3lDaukiZphIBjgRWqulJVdwGvAyMirGkvVHWdqn7nfS7A3RwPwun8n5ftf8BZERFYBSKSAfwaeM5LCzAYmOBlaWh6mwMn49axQlV3qepWGnAb42bCJ3krDycD62hgbayqX+LWAwukujYdAbzsrTj9DdBCRDqERWgAVWlW1U9U1R914Bvcwm7gNL+uqiWq+guwAndPCRvVtDHAY8DtQKDHWYNo4+poqkboIGBNQDrH29cgEZEs4GjgW6Cdqq7zDq0H2kVKVxX8C/cPUOGlWwNbA/6RG1o7dwY2AS96Q4jPiUgKDbSNVTUXeAT3lLsO2AbMo2G3sZ/q2jRa/hevBD70PjdIzSIyAshV1e8rHWqQev00VSMUNYhIKjARuFFVtwce85Y+bxA+9iJyJrBRVedFWksIxALHAM+q6tHADioNvTWwNm6Je6rtDHQEUqhiSKah05DaNBhE5C7c8PhrkdZSHSKSDPwJ+Mv+8jY0mqoRCtv66QeCiMThDNBrqvq2t3uDvyvt/d0YKX2V6A8MF5Fs3PDmYNz7lhbe0BE0vHbOAXJU9VsvPQFnlBpqG58K/KKqm1S1FHgb1+4NuY39VNemDfp/UUQuB84ELtY9kyobouZDcQ8n33v/gxnAdyLSnoapdzdN1QjtXj/d8yS6EJgcYU174b1PeR5Yqqr/L+DQZOAy7/NlwKRwa6sKVb1TVTNUNQvXnp+r6sXANGCkl63B6AVQ1fXAGhHp6u0aAiyhgbYxbhjueBFJ9n4ffr0Nto0DqK5NJwOXeh5cxwPbAobtIoqIDMMNLw9X1Z0BhyYDF4pIgoh0xr3wnx0JjX5UdZGqtlXVLO9/MAc4xvuNN9g2BkBVm+QG/Arn8fIzcFek9VShbwBuyGIhsMDbfoV7z/IZ8BPwKdAq0lqr0D4QeN/7fAjuH3QF8BaQEGl9lbT2BuZ67fwu0LIhtzHwN2AZ8APwCpDQ0NoYGI97Z1WKuxleVV2bAoLzVP0ZWITz/Gsomlfg3qX4///+HZD/Lk/zcuCMhqC30vFsoE1DauPqNgvbYxiGYUSMpjocZxiGYTQAzAgZhmEYEcOMkGEYhhExzAgZhmEYEcOMkGEYhhExzAgZjRoRaS0iC7xtvYjkep8LReSZejrnjSJyaYhl7vKiYy/09B1Xi/Omi8hHoZYzjEgSu/8shhG9qGoebi4QInIPUKiqj9TX+bzIBVfiIi8EW+YE3Kz8Y1S1xAvBH/JyDKq6SUTWiUh/Vf061PKGEQmsJ2Q0SURkoOxZ8+geEfmfiHwlIqtE5BwReUhEFonIR174JESkj4h8ISLzROTjaiIRDwa+Uy+gqIhMF5HHRGSuuPWK+onI2+LW1bnPK9MB2KyqJQCqullV19Z0ThHpIiKfisj3IvKdiBzq1fUucHE9NZth1DlmhAzDcSjOgAwHXgWmqWoPoAj4tWeIngRGqmof4AXg/irq6Y+LbB3ILlXtC/wbF67meuAo4HIRaQ18AmSKyI8i8oyInAK7YwdWd87XgKdVtRdwIm72PLjoDycdWFMYRviw4TjDcHyoqqUisgi3WJz/3coiIAvoijMcU13YNmLYc+MPpAN7L+oHe+ISLgIWqxe3S0RWApmqukBE+uCMxyDgDXGr/c6t6pwikgYcpKrvAKhqccC5NuIibBtGVGBGyDAc/qGwChEp1T3xrCpw/yeCMyAn7KeeIiCxqrq9ukoC9vvrRlXLgenAdM8QXobrUe1zTs8IVUeip8EwogIbjjOM4FgOpHtOBIhInIgcWUW+pUCXUCoWka4icljArt7AqurOqW6l3RwROcvbn+CtJwNwOC64qWFEBWaEDCMI1C0DPxJ4UES+x0VVPrGKrB/ilgwPhVTgfyKyREQWAt2Be/ZzzlHADV7+mUB7b/8g4IMQz28YEcOiaBtGHSMi7wC3q+pPETj3l8AIVc0P97kNozaYETKMOsZbJK+dqn4Z5vOmA/1V9d1wntcwDgQzQoZhGEbEsHdChmEYRsQwI2QYhmFEDDNChmEYRsQwI2QYhmFEDDNChmEYRsT4/65WlOi43a9HAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Arduino measure transistor base response')\n", "\n", "ax1 = dfmeasure.plot('time', 'v1', kind='scatter', ax=ax, label='base')\n", "ax1.plot(x, f1(x),'b')\n", "ax1.legend(loc='lower left')\n", "# ask matplotlib for the plotted objects and their labels\n", "lines1, labels1 = ax1.get_legend_handles_labels()\n", "ax2 = ax1.twinx()\n", "ax2 = dfmeasure.plot('time', 'v2', kind='scatter', ax=ax2, color='r', label='collector')\n", "\n", "ax2.plot(x, f2(x), 'r') \n", "lines2, labels2 = ax2.get_legend_handles_labels()\n", "\n", "ax1.set_xlabel('Time (mSec)')\n", "ax1.set_ylabel('voltage $V_C$')\n", "ax2.set_ylabel('voltage collector')\n", "\n", "ax2.legend(lines1 + lines2, labels1 + labels2, loc='upper left')\n", "ax1.grid()" ] }, { "cell_type": "code", "execution_count": 32, "id": "fa1bfc4e-6e46-4250-935f-3272f831434a", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Source Current')\n", "x = np.linspace(0,130,200)\n", "ax.plot(x, 1000*(5 - f1(x))/r1val,'b')\n", " \n", "ax.set_xlabel('Time (mSec)')\n", "ax.set_ylabel('Current $I_b$ (mA)')\n", "\n", "ax.grid()" ] }, { "cell_type": "code", "execution_count": 33, "id": "9548f86f-81b0-4e83-bb3b-b6458256e688", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "6.6576923076923045 0.0006657692307692305\n", "0.67 mA going into capacitor per second\n", "or 665.8 μA per mSec\n" ] } ], "source": [ "df = dfmeasure[dfmeasure['time']<100]\n", "res = linregress(df['time']/1000, df['v1'])\n", "capcurrent = res.slope*cval\n", "print (res.slope, capcurrent)\n", "print (\"{:.2f} mA going into capacitor per second\".format(capcurrent*1000))\n", "print (\"or {:3.1f} \\N{greek small letter mu}A per mSec\".format(capcurrent*1e6))" ] }, { "cell_type": "code", "execution_count": 34, "id": "baaa9f83-1ed8-418b-b3f6-95c3b495c181", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Base Current')\n", "x = np.linspace(0,130,200)\n", "ax.plot(x, 1000*(5 - f1(x))/r1val-capcurrent/1000,'b')\n", " \n", "ax.set_xlabel('Time (mSec)')\n", "ax.set_ylabel('Current $I_b$ (mA)')\n", "\n", "ax.grid()" ] }, { "cell_type": "code", "execution_count": 35, "id": "280bd7cc-5a6e-4aa2-8df9-9850caec75be", "metadata": { "tags": [] }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Collector Current')\n", "x = np.linspace(0,130,200)\n", "ax.plot(x, 1000*(5 - f2(x))/r2val,'b')\n", " \n", "ax.set_xlabel('Time (mSec)')\n", "ax.set_ylabel('Current $I_b$ (mA)')\n", "\n", "ax.grid()" ] }, { "cell_type": "code", "execution_count": 36, "id": "b946f07b-1e0d-4df1-b8bc-d6aa3b99d0e7", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Arduino measure transistor base-collector response')\n", "\n", "df=dfmeasure.drop_duplicates('v1') \n", "xi = np.linspace(.5,.7,100)\n", "f3=interp1d( df['v1'], df['v2'], kind='quadratic')\n", "\n", "ax1 = dfmeasure.plot('v1', 'v2', kind='scatter', ax=ax, label='5K')\n", "ax1.plot(xi, f3(xi),'b')\n", "\n", "ax1.set_xlim(.5,.7)\n", "ax1.set_xlabel('voltage $V_B$')\n", "ax1.set_ylabel('voltage $V_C$')\n", "ax1.grid()" ] }, { "cell_type": "code", "execution_count": 37, "id": "0bbcde3e-495e-4171-8644-6145f7ae7d9c", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Arduino measure transistor base-collector response')\n", "\n", "\n", "df=dfmeasure.drop_duplicates('v1').copy() \n", "df.loc[:,'bcurrent'] = ((5 - df['v1'])/r1val-capcurrent/1000)*1000 # (convert to milliamps)\n", "df.loc[:,'ccurrent'] = 1000*(5 - df['v2'])/r2val # 1000 * (convert to milliAmps)\n", "xi = np.linspace(.63, .734,100)\n", "f3=interp1d( df['bcurrent'], df['ccurrent'], kind='quadratic')\n", "#f2=interp1d(dfmeasure['time'], dfmeasure['v2'])\n", "\n", "ax1 = df.plot('bcurrent', 'ccurrent', kind='scatter', ax=ax, label='5K')\n", "#ax1 = dfmeasure.plot('time', 'v2', kind='scatter', ax=ax, color='r', label='collector')\n", "ax1.plot(xi, f3(xi),'b')\n", "#ax1.plot(x, f2(x), 'r')\n", "#ax1.set_xlim(.5,.7)\n", "ax1.set_xlabel('$I_B mA$')\n", "ax1.set_ylabel('$I_C mA$')\n", "ax1.grid()" ] }, { "cell_type": "code", "execution_count": 38, "id": "5cb596cb-9200-4aae-8165-3035e5f30e40", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
timev1v2bcurrentccurrent
00.00.004.980.7346280.004
14.00.034.970.7302170.006
28.00.074.980.7243340.004
312.00.094.980.7213930.004
416.00.134.970.7155110.006
520.00.154.980.7125700.004
624.00.184.970.7081580.006
728.00.214.970.7037460.006
832.00.234.980.7008050.004
936.00.264.980.6963930.004
1040.00.284.970.6934520.006
1144.00.314.980.6890400.004
1248.00.344.980.6846280.004
1352.00.374.980.6802170.004
1456.00.404.970.6758050.006
1560.00.424.980.6728640.004
1664.00.454.970.6684520.006
1768.00.474.970.6655110.006
1872.00.504.960.6610990.008
1976.00.524.950.6581580.010
2080.00.554.900.6537460.020
2184.00.574.810.6508050.038
2288.00.604.540.6463930.092
2392.00.623.820.6434520.236
2496.00.642.050.6405110.590
25100.00.670.060.6360990.988
26104.00.700.040.6316870.992
27108.00.710.030.6302170.994
28112.00.720.020.6287460.996
29116.00.730.020.6272750.996
31125.00.740.020.6258050.996
\n", "
" ], "text/plain": [ " time v1 v2 bcurrent ccurrent\n", "0 0.0 0.00 4.98 0.734628 0.004\n", "1 4.0 0.03 4.97 0.730217 0.006\n", "2 8.0 0.07 4.98 0.724334 0.004\n", "3 12.0 0.09 4.98 0.721393 0.004\n", "4 16.0 0.13 4.97 0.715511 0.006\n", "5 20.0 0.15 4.98 0.712570 0.004\n", "6 24.0 0.18 4.97 0.708158 0.006\n", "7 28.0 0.21 4.97 0.703746 0.006\n", "8 32.0 0.23 4.98 0.700805 0.004\n", "9 36.0 0.26 4.98 0.696393 0.004\n", "10 40.0 0.28 4.97 0.693452 0.006\n", "11 44.0 0.31 4.98 0.689040 0.004\n", "12 48.0 0.34 4.98 0.684628 0.004\n", "13 52.0 0.37 4.98 0.680217 0.004\n", "14 56.0 0.40 4.97 0.675805 0.006\n", "15 60.0 0.42 4.98 0.672864 0.004\n", "16 64.0 0.45 4.97 0.668452 0.006\n", "17 68.0 0.47 4.97 0.665511 0.006\n", "18 72.0 0.50 4.96 0.661099 0.008\n", "19 76.0 0.52 4.95 0.658158 0.010\n", "20 80.0 0.55 4.90 0.653746 0.020\n", "21 84.0 0.57 4.81 0.650805 0.038\n", "22 88.0 0.60 4.54 0.646393 0.092\n", "23 92.0 0.62 3.82 0.643452 0.236\n", "24 96.0 0.64 2.05 0.640511 0.590\n", "25 100.0 0.67 0.06 0.636099 0.988\n", "26 104.0 0.70 0.04 0.631687 0.992\n", "27 108.0 0.71 0.03 0.630217 0.994\n", "28 112.0 0.72 0.02 0.628746 0.996\n", "29 116.0 0.73 0.02 0.627275 0.996\n", "31 125.0 0.74 0.02 0.625805 0.996" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df\n" ] }, { "cell_type": "code", "execution_count": 39, "id": "8c97bc44-fe91-4b4b-b018-850f8a46d06c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LinregressResult(slope=-8.760011429659974, intercept=5.864425402266887, rvalue=-0.6656341317602029, pvalue=0.01814338092082274, stderr=3.1057741062899575, intercept_stderr=2.049408351480763)" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1 = df[13:25]\n", "linregress(df1['bcurrent'], df1['ccurrent'])\n" ] }, { "cell_type": "markdown", "id": "ccebc7b4-2619-4eca-b5ec-4bad21b30222", "metadata": {}, "source": [ "This doesn't look like a particularly good regression so I look at the graph." ] }, { "cell_type": "code", "execution_count": 40, "id": "394ae27f-e6e1-4215-86df-2c3a029e4578", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "ax.set_title('Arduino measure transistor base-collector response')\n", "\n", "\n", "xi = np.linspace(.64052 ,.68, 100)\n", "f3=interp1d( df1['bcurrent'], df1['ccurrent'], kind='quadratic')\n", "\n", "ax1 = df1.plot('bcurrent', 'ccurrent', kind='scatter', ax=ax, label='5K')\n", "ax1.plot(xi, f3(xi),'b')\n", "\n", "ax1.set_xlabel('$I_B mA$')\n", "ax1.set_ylabel('$I_C mA$')\n", "ax1.grid()" ] }, { "cell_type": "code", "execution_count": null, "id": "79e2c595-d3d4-4879-bbae-384c4c789c0c", "metadata": {}, "outputs": [], "source": [ " " ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }