{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Simulation of a Kerr-Black-Hole\n", "by **Florian Hollants**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This Jupyter Notebook simulates a rotating Black Hole in SageMath using the Kerr Metric. The Project is based on the work of Florentin Jaffredo. The parameters for mass and angular momentum can be altered in Cell 5 by changing \"m_val\" and \"a_val\", while the \"Angle\" can be changed in Cell 18. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# n_cpu = 4 # 4 Go Ram minimum\n", "# n_geod = 100\n", "# nx, ny = 180, 90" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "n_cpu = 8 # 8 Go Ram minimum\n", "n_geod = 1000\n", "nx, ny = 720, 360" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# n_cpu = 36 # 144 Go Ram minimum\n", "# n_geod = 30000\n", "# nx, ny = 4000, 2000" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "%display latex" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}t :\\ \\left( -\\infty, +\\infty \\right) ;\\quad r :\\ \\left( 4.20000000000000 , +\\infty \\right) ;\\quad {\\theta} :\\ \\left( 0 , \\pi \\right) ;\\quad {\\phi} :\\ \\left( -\\infty, +\\infty \\right)\n", "\\end{math}" ], "text/plain": [ "t: (-oo, +oo); r: (4.20000000000000, +oo); th: (0, pi); ph: (-oo, +oo)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "M = Manifold(4, 'M', structure='Lorentzian')\n", "\n", "m = var('m')\n", "a = var('a')\n", "\n", "m_val = 2\n", "a_val = 1\n", "\n", "C. = M.chart(r't r:(4.2,+oo) th:(0,pi):\\theta ph:\\phi') #check that minimum radius is bigger than singularity in g[1,1]\n", "C.coord_range()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{2 \\, m r}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} - 1 & 0 & 0 & -\\frac{2 \\, a m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} \\\\\n", "0 & \\frac{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}}{a^{2} - 2 \\, m r + r^{2}} & 0 & 0 \\\\\n", "0 & 0 & a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2} & 0 \\\\\n", "-\\frac{2 \\, a m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} & 0 & 0 & {\\left(\\frac{2 \\, a^{2} m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} + a^{2} + r^{2}\\right)} \\sin\\left({\\theta}\\right)^{2}\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[ 2*m*r/(a^2*cos(th)^2 + r^2) - 1 0 0 -2*a*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2)]\n", "[ 0 (a^2*cos(th)^2 + r^2)/(a^2 - 2*m*r + r^2) 0 0]\n", "[ 0 0 a^2*cos(th)^2 + r^2 0]\n", "[ -2*a*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2) 0 0 (2*a^2*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2) + a^2 + r^2)*sin(th)^2]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g = M.metric()\n", "g[0,0] = (2*m*r)/(r^2+(a*cos(th))^2)-1\n", "g[0,3] = -2*m*r*a*sin(th)^2/(r^2+(a*cos(th))^2)\n", "g[1,1] = (r^2+(a*cos(th))^2)/(r^2-2*m*r+a^2)\n", "g[2,2] = r^2+(a*cos(th))^2\n", "g[3,3] = (r^2+a^2+(2*m*r*a^2*sin(th)^2)/(r^2+(a*cos(th))^2))*sin(th)^2\n", "g[:]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\begin{array}{llcl} & M & \\longrightarrow & \\mathbb{E}^{3} \\\\ & \\left(t, r, {\\theta}, {\\phi}\\right) & \\longmapsto & \\left(x, y, z\\right) = \\left(r \\cos\\left({\\phi}\\right) \\sin\\left({\\theta}\\right), r \\sin\\left({\\phi}\\right) \\sin\\left({\\theta}\\right), r \\cos\\left({\\theta}\\right)\\right) \\end{array}\n", "\\end{math}" ], "text/plain": [ "M --> E^3\n", " (t, r, th, ph) |--> (x, y, z) = (r*cos(ph)*sin(th), r*sin(ph)*sin(th), r*cos(th))" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "E. = EuclideanSpace()\n", "phi = M.diff_map(E, [r*sin(th)*cos(ph), r*sin(th)*sin(ph), r*cos(th)])\n", "phi.display()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## One Geodesic" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try the following for circular Orbit" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "Graphics3d Object" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "p = M((0, 14.98, pi/2, 0))\n", "Tp = M.tangent_space(p)\n", "v = Tp((2, 0, 0.005, 0.05))\n", "v = v / sqrt(-g.at(p)(v, v))\n", "\n", "tau = var('tau')\n", "\n", "curve = M.integrated_geodesic(g, (tau, 0, 5000), v)\n", "sol = curve.solve(step = 1, method=\"ode_int\", parameters_values={m: m_val, a: a_val})\n", "\n", "interp = curve.interpolate()\n", "\n", "P = curve.plot_integrated(mapping=phi, color=\"red\", thickness=2, plot_points=5000)\n", "P += sage.plot.plot3d.shapes.Sphere(4, color='grey')\n", "P" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try the following for light at different Values for a, aimed directly at the Black Hole" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# p = M((0, 20, pi/2, 0))\n", "# Tp = M.tangent_space(p)\n", "# v = Tp((2, -1, 0.000, 0.00))\n", "# v = v / sqrt(-g.at(p)(v, v))\n", "\n", "# A=[0,1,2,4] #list of values for a\n", "# Color=[[\"red\"], [\"blue\"], [\"green\"],[\"orange\"], [\"black\"]] #color for different Geodesics\n", "\n", "# P = sage.plot.plot3d.shapes.Sphere(4, color='grey')\n", "\n", "# tau = var('tau')\n", "# for i in range(4):\n", "# curve = M.integrated_geodesic(g, (tau, 0, 200), initial_tangent_vector=v, across_charts=True)\n", "# curve.solve_across_charts(step=0.2, parameters_values={m:m_val, a:A[i]})\n", "# interp = curve.interpolate()\n", "# P += curve.plot_integrated(mapping=phi, color=Color[i], thickness=2, plot_points=10000, across_charts=True)\n", "\n", "# P" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multiple Geodesics" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "import multiprocessing\n", "from ipywidgets import FloatProgress\n", "from IPython.display import display" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def chunks(l, n):\n", " \"\"\"Yield successive n-sized chunks from l.\"\"\"\n", " for i in range(0, len(l), n):\n", " yield l[i:i + n]\n", "\n", "n_batches_per_cpu = 3" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "curve = M.integrated_geodesic(g, (tau, 0, 200), v, across_charts=True)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "args = []\n", "start_index = 0\n", "\n", "for chunk in chunks(range(n_geod), n_geod//(n_batches_per_cpu*n_cpu)):\n", " args += [(loads(curve.dumps()), start_index, len(chunk))] #\n", " start_index += len(chunk)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left[\\mathit{dt} = \\frac{2 \\, {\\left(a^{3} m - 2 \\, a m^{2} r_{0} + a m r_{0}^{2}\\right)} y - \\sqrt{-2 \\, a^{2} m r_{0} - 4 \\, m r_{0}^{3} + r_{0}^{4} + {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}^{2} + {\\left(a^{6} - 6 \\, a^{4} m r_{0} - 6 \\, m r_{0}^{5} + r_{0}^{6} + 3 \\, {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}^{4} - 4 \\, {\\left(3 \\, a^{2} m + 2 \\, m^{3}\\right)} r_{0}^{3} + 3 \\, {\\left(a^{4} + 4 \\, a^{2} m^{2}\\right)} r_{0}^{2}\\right)} y^{2}} r_{0}}{2 \\, a^{2} m + 4 \\, m r_{0}^{2} - r_{0}^{3} - {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}}, \\mathit{dt} = \\frac{2 \\, {\\left(a^{3} m - 2 \\, a m^{2} r_{0} + a m r_{0}^{2}\\right)} y + \\sqrt{-2 \\, a^{2} m r_{0} - 4 \\, m r_{0}^{3} + r_{0}^{4} + {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}^{2} + {\\left(a^{6} - 6 \\, a^{4} m r_{0} - 6 \\, m r_{0}^{5} + r_{0}^{6} + 3 \\, {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}^{4} - 4 \\, {\\left(3 \\, a^{2} m + 2 \\, m^{3}\\right)} r_{0}^{3} + 3 \\, {\\left(a^{4} + 4 \\, a^{2} m^{2}\\right)} r_{0}^{2}\\right)} y^{2}} r_{0}}{2 \\, a^{2} m + 4 \\, m r_{0}^{2} - r_{0}^{3} - {\\left(a^{2} + 4 \\, m^{2}\\right)} r_{0}}\\right]\n", "\\end{math}" ], "text/plain": [ "[dt == (2*(a^3*m - 2*a*m^2*r0 + a*m*r0^2)*y - sqrt(-2*a^2*m*r0 - 4*m*r0^3 + r0^4 + (a^2 + 4*m^2)*r0^2 + (a^6 - 6*a^4*m*r0 - 6*m*r0^5 + r0^6 + 3*(a^2 + 4*m^2)*r0^4 - 4*(3*a^2*m + 2*m^3)*r0^3 + 3*(a^4 + 4*a^2*m^2)*r0^2)*y^2)*r0)/(2*a^2*m + 4*m*r0^2 - r0^3 - (a^2 + 4*m^2)*r0), dt == (2*(a^3*m - 2*a*m^2*r0 + a*m*r0^2)*y + sqrt(-2*a^2*m*r0 - 4*m*r0^3 + r0^4 + (a^2 + 4*m^2)*r0^2 + (a^6 - 6*a^4*m*r0 - 6*m*r0^5 + r0^6 + 3*(a^2 + 4*m^2)*r0^4 - 4*(3*a^2*m + 2*m^3)*r0^3 + 3*(a^4 + 4*a^2*m^2)*r0^2)*y^2)*r0)/(2*a^2*m + 4*m*r0^2 - r0^3 - (a^2 + 4*m^2)*r0)]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dt, y, r0 = var('dt, y, r0')\n", "\n", "p = M((0, r0, pi/2, 0))\n", "Tp = M.tangent_space(p)\n", "v = Tp((dt, -1, 0, y))\n", "\n", "sol = g.at(p)(v, v).solve(dt)\n", "sol" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "def calc_some_geodesics(args):\n", " \"\"\"\n", " Compute nb geodesics starting at index n0\n", " \"\"\"\n", " curve, n0, nb = args\n", " res = {}\n", " r = 100\n", " posi = [0, r, pi/2, 0]\n", " p = M(posi)\n", " Tp = M.tangent_space(p)\n", " for i in range(n0, n0+nb):\n", " dy = i*0.006/n_geod\n", " v = Tp([sol[0].rhs()(r0=r, y=dy, m=m_val, a=a_val).n(), -1, 0, dy])\n", " curve._initial_tangent_vector = v\n", " curve.solve_across_charts(step=0.2, parameters_values={m:m_val, a:a_val})\n", " res[i] = (p.coord(), curve._solutions.copy())\n", " curve._solutions.clear()\n", " return res" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "fef6a25ffd99454da6f5a0bada40f10b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "FloatProgress(value=0.0, max=1000.0)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "geo = {}\n", "pool = multiprocessing.Pool(n_cpu)\n", "\n", "%display plain\n", "f = FloatProgress(min=0, max=n_geod)\n", "display(f)\n", "\n", "for i, some_res in enumerate(pool.map(calc_some_geodesics, args)):\n", " f.value += len(some_res)\n", " geo.update(some_res)\n", "\n", "pool.close()\n", "pool.join()" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "Graphics3d Object" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "P = sage.plot.plot3d.shapes.Sphere(4, color='grey')\n", "\n", "for i in range(0, n_geod, 5*n_geod/100): \n", " curve._solutions = geo[i][1]\n", " interp = curve.interpolate()\n", " P += curve.plot_integrated(mapping=phi, color=[\"red\"], thickness=2, plot_points=150, \n", " label_axes=False, across_charts=True)#\n", "\n", "P" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8.46600505906165\n" ] } ], "source": [ "Angle = pi/20 #angle used in the actual calculation\n", "\n", "Xi=a_val/m_val\n", "Z_1=1+(1-Xi^2)^(1/3)*((1+Xi)^(1/3)+(1-Xi)^(1/3))\n", "Z_2=(3*Xi^2+Z_1^2)^(1/2)\n", "#calculating ISCO\n", "\n", "disk_min = m_val*(3+Z_2-((3-Z_1)*(3+Z_1+2*Z_2))^(1/2))\n", "print(numerical_approx(disk_min))\n", "if disk_min<2*m_val:\n", " disk_min=2*m_val\n", "\n", "disk_max = (50^2+disk_min^2-12^2)^(1/2)\n", "#disk_max =25\n", "#keeping area of accretion Disk the same as in original work of Florentin Jaffredo\n", "\n", "#disk_min = 4\n", "#disk_max = 50\n", "alpha = -pi/20\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "Graphics3d Object" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "D = sage.plot.plot3d.shapes.Torus((disk_min+disk_max)/2,\n", " (disk_max-disk_min)/2).scale(1,1,0.01).rotateY(-pi/20)\n", "\n", "P + D" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "Graphics3d Object" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "P + D.rotateX(pi/3)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "#now begins the part where we calculate intersection with accretion disk and visualize the image\n", "geo = [list(geo[i][1].values())[0][0][1].tolist() for i in range(len(geo))]" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "def intersection(curve, alpha, beta):\n", " \"\"\"\n", " Return True if the curve intersect the disk comprised between dmin and dmax\n", " tilted of angles alpha and beta\n", " \"\"\"\n", " n = len(curve)\n", " r, theta, phi = curve[0][2:5]\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " x, y, z = x, y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta)\n", " z = z*cos(alpha)+x*sin(alpha)\n", " for i in range(1, n):\n", " # done in 3 lines for speed consideration\n", " r = curve[i][2]\n", " theta = curve[i][3]\n", " phi = curve[i][4]\n", " # conversion to cartesian:\n", " x2, y2, z2 = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta) \n", " # rotation around the X-axis:\n", " y2, z2 = y2*cos(beta)-z2*sin(beta), z2*cos(beta)+y2*sin(beta) \n", " # rotation around the Y-axis:\n", " x2, z2 = x2*cos(alpha)-z2*sin(alpha), z2*cos(alpha)+x2*sin(alpha) \n", " if z!=z2: # needed to prevent a division by zero next line\n", " t = z/(z-z2) # if 0<=t<1 then the curve intersect the disk between the points i and i-1\n", " if t>=0 and t<1 and curve[i][2]>disk_min and curve[i][2]=0 and t<1 and curve[i][2]>dmin and curve[i][2]>> from scipy.misc import bytescale\n", " >>> img = np.array([[ 91.06794177, 3.39058326, 84.4221549 ],\n", " ... [ 73.88003259, 80.91433048, 4.88878881],\n", " ... [ 51.53875334, 34.45808177, 27.5873488 ]])\n", " >>> bytescale(img)\n", " array([[255, 0, 236],\n", " [205, 225, 4],\n", " [140, 90, 70]], dtype=uint8)\n", " >>> bytescale(img, high=200, low=100)\n", " array([[200, 100, 192],\n", " [180, 188, 102],\n", " [155, 135, 128]], dtype=uint8)\n", " >>> bytescale(img, cmin=0, cmax=255)\n", " array([[91, 3, 84],\n", " [74, 81, 5],\n", " [52, 34, 28]], dtype=uint8)\n", " \"\"\"\n", " if data.dtype == np.uint8:\n", " return data\n", "\n", " if high > 255:\n", " raise ValueError(\"`high` should be less than or equal to 255.\")\n", " if low < 0:\n", " raise ValueError(\"`low` should be greater than or equal to 0.\")\n", " if high < low:\n", " raise ValueError(\"`high` should be greater than or equal to `low`.\")\n", "\n", " if cmin is None:\n", " cmin = data.min()\n", " if cmax is None:\n", " cmax = data.max()\n", "\n", " cscale = cmax - cmin\n", " if cscale < 0:\n", " raise ValueError(\"`cmax` should be larger than `cmin`.\")\n", " elif cscale == 0:\n", " cscale = 1\n", "\n", " scale = float(high - low) / cscale\n", " bytedata = (data - cmin) * scale + low\n", " return (bytedata.clip(low, high) + 0.5).astype(np.uint8)\n", "\n", "def toimage(arr, high=255, low=0, cmin=None, cmax=None, pal=None,\n", " mode=None, channel_axis=None):\n", " \"\"\"Takes a numpy array and returns a PIL image.\n", " This function is only available if Python Imaging Library (PIL) is installed.\n", " The mode of the PIL image depends on the array shape and the `pal` and\n", " `mode` keywords.\n", " For 2-D arrays, if `pal` is a valid (N,3) byte-array giving the RGB values\n", " (from 0 to 255) then ``mode='P'``, otherwise ``mode='L'``, unless mode\n", " is given as 'F' or 'I' in which case a float and/or integer array is made.\n", " .. warning::\n", " This function uses `bytescale` under the hood to rescale images to use\n", " the full (0, 255) range if ``mode`` is one of ``None, 'L', 'P', 'l'``.\n", " It will also cast data for 2-D images to ``uint32`` for ``mode=None``\n", " (which is the default).\n", " Notes\n", " -----\n", " For 3-D arrays, the `channel_axis` argument tells which dimension of the\n", " array holds the channel data.\n", " For 3-D arrays if one of the dimensions is 3, the mode is 'RGB'\n", " by default or 'YCbCr' if selected.\n", " The numpy array must be either 2 dimensional or 3 dimensional.\n", " \"\"\"\n", " data = np.asarray(arr)\n", " if np.iscomplexobj(data):\n", " raise ValueError(\"Cannot convert a complex-valued array.\")\n", " shape = list(data.shape)\n", " valid = len(shape) == 2 or ((len(shape) == 3) and\n", " ((3 in shape) or (4 in shape)))\n", " if not valid:\n", " raise ValueError(\"'arr' does not have a suitable array shape for \"\n", " \"any mode.\")\n", " if len(shape) == 2:\n", " shape = (shape[1], shape[0]) # columns show up first\n", " if mode == 'F':\n", " data32 = data.astype(np.float32)\n", " image = Image.frombytes(mode, shape, data32.tobytes())\n", " return image\n", " if mode in [None, 'L', 'P']:\n", " bytedata = bytescale(data, high=high, low=low,\n", " cmin=cmin, cmax=cmax)\n", " image = Image.frombytes('L', shape, bytedata.tobytes())\n", " if pal is not None:\n", " image.putpalette(np.asarray(pal, dtype=np.uint8).tobytes())\n", " # Becomes a mode='P' automagically.\n", " elif mode == 'P': # default gray-scale\n", " pal = (np.arange(0, 256, 1, dtype=np.uint8)[:, np.newaxis] *\n", " np.ones((3,), dtype=np.uint8)[np.newaxis, :])\n", " image.putpalette(np.asarray(pal, dtype=np.uint8).tobytes())\n", " return image\n", " if mode == '1': # high input gives threshold for 1\n", " bytedata = (data > high)\n", " image = Image.frombytes('1', shape, bytedata.tobytes())\n", " return image\n", " if cmin is None:\n", " cmin = np.amin(np.ravel(data))\n", " if cmax is None:\n", " cmax = np.amax(np.ravel(data))\n", " data = (data*1.0 - cmin)*(high - low)/(cmax - cmin) + low\n", " if mode == 'I':\n", " data32 = data.astype(np.uint32)\n", " image = Image.frombytes(mode, shape, data32.tobytes())\n", " else:\n", " raise ValueError(_errstr)\n", " return image\n", "\n", " # if here then 3-d array with a 3 or a 4 in the shape length.\n", " # Check for 3 in datacube shape --- 'RGB' or 'YCbCr'\n", " if channel_axis is None:\n", " if (3 in shape):\n", " ca = np.flatnonzero(np.asarray(shape) == 3)[0]\n", " else:\n", " ca = np.flatnonzero(np.asarray(shape) == 4)\n", " if len(ca):\n", " ca = ca[0]\n", " else:\n", " raise ValueError(\"Could not find channel dimension.\")\n", " else:\n", " ca = channel_axis\n", "\n", " numch = shape[ca]\n", " if numch not in [3, 4]:\n", " raise ValueError(\"Channel axis dimension is not valid.\")\n", "\n", " bytedata = bytescale(data, high=high, low=low, cmin=cmin, cmax=cmax)\n", " if ca == 2:\n", " strdata = bytedata.tobytes()\n", " shape = (shape[1], shape[0])\n", " elif ca == 1:\n", " strdata = np.transpose(bytedata, (0, 2, 1)).tobytes()\n", " shape = (shape[2], shape[0])\n", " elif ca == 0:\n", " strdata = np.transpose(bytedata, (1, 2, 0)).tobytes()\n", " shape = (shape[2], shape[1])\n", " if mode is None:\n", " if numch == 3:\n", " mode = 'RGB'\n", " else:\n", " mode = 'RGBA'\n", "\n", " if mode not in ['RGB', 'RGBA', 'YCbCr', 'CMYK']:\n", " raise ValueError(_errstr)\n", "\n", " if mode in ['RGB', 'YCbCr']:\n", " if numch != 3:\n", " raise ValueError(\"Invalid array shape for mode.\")\n", " if mode in ['RGBA', 'CMYK']:\n", " if numch != 4:\n", " raise ValueError(\"Invalid array shape for mode.\")\n", "\n", " # Here we know data and mode is correct\n", " image = Image.frombytes(mode, shape, strdata)\n", " return image" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img1 = toimage(data)\n", "img1" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{2 \\, m r}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} - 1 & 0 & 0 & -\\frac{2 \\, a m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} \\\\\n", "0 & \\frac{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}}{a^{2} - 2 \\, m r + r^{2}} & 0 & 0 \\\\\n", "0 & 0 & a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2} & 0 \\\\\n", "-\\frac{2 \\, a m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} & 0 & 0 & {\\left(\\frac{2 \\, a^{2} m r \\sin\\left({\\theta}\\right)^{2}}{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}} + a^{2} + r^{2}\\right)} \\sin\\left({\\theta}\\right)^{2}\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[ 2*m*r/(a^2*cos(th)^2 + r^2) - 1 0 0 -2*a*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2)]\n", "[ 0 (a^2*cos(th)^2 + r^2)/(a^2 - 2*m*r + r^2) 0 0]\n", "[ 0 0 a^2*cos(th)^2 + r^2 0]\n", "[ -2*a*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2) 0 0 (2*a^2*m*r*sin(th)^2/(a^2*cos(th)^2 + r^2) + a^2 + r^2)*sin(th)^2]" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display latex\n", "g[:]" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{2 \\, m - r_{0}}{r_{0}} & 0 & 0 & -\\frac{2 \\, a m}{r_{0}} \\\\\n", "0 & \\frac{r_{0}^{2}}{a^{2} - 2 \\, m r_{0} + r_{0}^{2}} & 0 & 0 \\\\\n", "0 & 0 & r_{0}^{2} & 0 \\\\\n", "-\\frac{2 \\, a m}{r_{0}} & 0 & 0 & \\frac{2 \\, a^{2} m + a^{2} r_{0} + r_{0}^{3}}{r_{0}}\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[ (2*m - r_0)/r_0 0 0 -2*a*m/r_0]\n", "[ 0 r_0^2/(a^2 - 2*m*r_0 + r_0^2) 0 0]\n", "[ 0 0 r_0^2 0]\n", "[ -2*a*m/r_0 0 0 (2*a^2*m + a^2*r_0 + r_0^3)/r_0]" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "r0, phi = var('r_0, phi')\n", "p = M((0, r0, pi/2, phi))\n", "g.at(p)[:]" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "# default frame\n", "fr = C.frame()\n", "\n", "# create an automorphism field\n", "aut = M.automorphism_field()\n", "\n", "# some symbolic variables\n", "a, b, c = var('a, b, c')\n", "\n", "# let's try with the simplest matrix possible\n", "aut.add_comp()[:] = [[a, 0, 0, 0], [b, c, 0, 0], [0, 0, 1/r0, 0], \n", " [0, 0, 0, 1/r0]] # only b is off-diagonal\n", "fr2 = fr.new_frame(aut, 'f2')" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{b^{2} r_{0}^{2}}{a^{2} - 2 \\, m r_{0} + r_{0}^{2}} + \\frac{a^{2} {\\left(2 \\, m - r_{0}\\right)}}{r_{0}} & \\frac{b c r_{0}^{2}}{a^{2} - 2 \\, m r_{0} + r_{0}^{2}} & 0 & -\\frac{2 \\, a^{2} m}{r_{0}^{2}} \\\\\n", "\\frac{b c r_{0}^{2}}{a^{2} - 2 \\, m r_{0} + r_{0}^{2}} & \\frac{c^{2} r_{0}^{2}}{a^{2} - 2 \\, m r_{0} + r_{0}^{2}} & 0 & 0 \\\\\n", "0 & 0 & 1 & 0 \\\\\n", "-\\frac{2 \\, a^{2} m}{r_{0}^{2}} & 0 & 0 & \\frac{2 \\, a^{2} m + a^{2} r_{0} + r_{0}^{3}}{r_{0}^{3}}\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[b^2*r_0^2/(a^2 - 2*m*r_0 + r_0^2) + a^2*(2*m - r_0)/r_0 b*c*r_0^2/(a^2 - 2*m*r_0 + r_0^2) 0 -2*a^2*m/r_0^2]\n", "[ b*c*r_0^2/(a^2 - 2*m*r_0 + r_0^2) c^2*r_0^2/(a^2 - 2*m*r_0 + r_0^2) 0 0]\n", "[ 0 0 1 0]\n", "[ -2*a^2*m/r_0^2 0 0 (2*a^2*m + a^2*r_0 + r_0^3)/r_0^3]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.at(p)[fr2.at(p), :]" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "c = sqrt(r/(r+2*m))\n", "a = sqrt(((r+2*m)/(r)))\n", "b = -2*a*m/(2*m+r)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "aut2 = M.automorphism_field() # new automorphism field\n", "aut2.add_comp()[:] = [[a, 0, 0, 0], [b, c, 0, 0], [0, 0, 1/r, 0], [0, 0, 0, 1/(r*sin(th))]]\n", "fr3 = fr.new_frame(aut2, 'f3')" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{4 \\, a^{4} m^{2} \\cos\\left({\\theta}\\right)^{4} + 8 \\, a^{2} m^{3} r - 2 \\, a^{2} m r^{3} - r^{6} - {\\left(a^{2} - 12 \\, m^{2}\\right)} r^{4} + 4 \\, {\\left(a^{2} m^{2} - 4 \\, m^{4}\\right)} r^{2} - {\\left(4 \\, a^{4} m^{2} + 2 \\, a^{2} m r^{3} + a^{2} r^{4} + {\\left(a^{4} - 12 \\, a^{2} m^{2}\\right)} r^{2} + 4 \\, {\\left(a^{4} m - 2 \\, a^{2} m^{3}\\right)} r\\right)} \\cos\\left({\\theta}\\right)^{2}}{2 \\, a^{2} m r^{3} + r^{6} + {\\left(a^{2} - 4 \\, m^{2}\\right)} r^{4} + {\\left(2 \\, a^{4} m r + a^{2} r^{4} + {\\left(a^{4} - 4 \\, a^{2} m^{2}\\right)} r^{2}\\right)} \\cos\\left({\\theta}\\right)^{2}} & -\\frac{2 \\, {\\left(a^{2} m \\cos\\left({\\theta}\\right)^{2} + m r^{2}\\right)}}{2 \\, a^{2} m + r^{3} + {\\left(a^{2} - 4 \\, m^{2}\\right)} r} & 0 & -\\frac{2 \\, a \\sqrt{2 \\, m + r} m \\sin\\left({\\theta}\\right)}{{\\left(a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}\\right)} \\sqrt{r}} \\\\\n", "-\\frac{2 \\, {\\left(a^{2} m \\cos\\left({\\theta}\\right)^{2} + m r^{2}\\right)}}{2 \\, a^{2} m + r^{3} + {\\left(a^{2} - 4 \\, m^{2}\\right)} r} & \\frac{a^{2} r \\cos\\left({\\theta}\\right)^{2} + r^{3}}{2 \\, a^{2} m + r^{3} + {\\left(a^{2} - 4 \\, m^{2}\\right)} r} & 0 & 0 \\\\\n", "0 & 0 & \\frac{a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}}{r^{2}} & 0 \\\\\n", "-\\frac{2 \\, a \\sqrt{2 \\, m + r} m \\sin\\left({\\theta}\\right)}{{\\left(a^{2} \\cos\\left({\\theta}\\right)^{2} + r^{2}\\right)} \\sqrt{r}} & 0 & 0 & \\frac{2 \\, a^{2} m r \\sin\\left({\\theta}\\right)^{2} + a^{2} r^{2} + r^{4} + {\\left(a^{4} + a^{2} r^{2}\\right)} \\cos\\left({\\theta}\\right)^{2}}{a^{2} r^{2} \\cos\\left({\\theta}\\right)^{2} + r^{4}}\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[(4*a^4*m^2*cos(th)^4 + 8*a^2*m^3*r - 2*a^2*m*r^3 - r^6 - (a^2 - 12*m^2)*r^4 + 4*(a^2*m^2 - 4*m^4)*r^2 - (4*a^4*m^2 + 2*a^2*m*r^3 + a^2*r^4 + (a^4 - 12*a^2*m^2)*r^2 + 4*(a^4*m - 2*a^2*m^3)*r)*cos(th)^2)/(2*a^2*m*r^3 + r^6 + (a^2 - 4*m^2)*r^4 + (2*a^4*m*r + a^2*r^4 + (a^4 - 4*a^2*m^2)*r^2)*cos(th)^2) -2*(a^2*m*cos(th)^2 + m*r^2)/(2*a^2*m + r^3 + (a^2 - 4*m^2)*r) 0 -2*a*sqrt(2*m + r)*m*sin(th)/((a^2*cos(th)^2 + r^2)*sqrt(r))]\n", "[ -2*(a^2*m*cos(th)^2 + m*r^2)/(2*a^2*m + r^3 + (a^2 - 4*m^2)*r) (a^2*r*cos(th)^2 + r^3)/(2*a^2*m + r^3 + (a^2 - 4*m^2)*r) 0 0]\n", "[ 0 0 (a^2*cos(th)^2 + r^2)/r^2 0]\n", "[ -2*a*sqrt(2*m + r)*m*sin(th)/((a^2*cos(th)^2 + r^2)*sqrt(r)) 0 0 (2*a^2*m*r*sin(th)^2 + a^2*r^2 + r^4 + (a^4 + a^2*r^2)*cos(th)^2)/(a^2*r^2*cos(th)^2 + r^4)]" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g[fr3, :]" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left(\\begin{array}{rrrr}\n", "\\frac{\\sqrt{r}}{\\sqrt{2 \\, m + r}} & 0 & 0 & 0 \\\\\n", "\\frac{2 \\, m}{\\sqrt{2 \\, m + r} \\sqrt{r}} & \\frac{\\sqrt{2 \\, m + r}}{\\sqrt{r}} & 0 & 0 \\\\\n", "0 & 0 & r & 0 \\\\\n", "0 & 0 & 0 & r \\sin\\left({\\theta}\\right)\n", "\\end{array}\\right)\n", "\\end{math}" ], "text/plain": [ "[ sqrt(r)/sqrt(2*m + r) 0 0 0]\n", "[2*m/(sqrt(2*m + r)*sqrt(r)) sqrt(2*m + r)/sqrt(r) 0 0]\n", "[ 0 0 r 0]\n", "[ 0 0 0 r*sin(th)]" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "aut2.inverse()[:]" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin, sqrt\n", "\n", "cpdef tuple spherical_to_xyz(float dr, float dtheta, float dphi, float r, \n", " float theta, float phi, float alpha, float beta):\n", " \"\"\"\n", " Convert spherical coordinates to cartesian and apply the \n", " two rotations at the same time.\n", " \"\"\"\n", " cdef float dx, dy, dz\n", " cdef float ca, cb, ct, cp\n", " cdef float sa, sb, st, sp\n", " \n", " ca = cos(alpha); sa = sin(alpha)\n", " cb = cos(beta); sb = sin(beta)\n", " ct = cos(theta); st = sin(theta)\n", " cp = cos(phi); sp = sin(phi)\n", " \n", " dx = ((-cb*ct*sa - (sa*sb*sp - ca*cp)*st)*dr + \n", " (r*cb*sa*st - (sa*sb*sp - ca*cp)*r*ct)*dtheta +\n", " (-(cp*sa*sb + ca*sp)*r*st)*dphi)\n", " \n", " dy = ((cb*sp*st - sb*ct)*dr +\n", " (r*ct*cb*sp + r*sb*st)*dtheta +\n", " (r*cp*cb*st)*dphi)\n", " \n", " dz = ((ca*cb*ct + (ca*sb*sp + cp*sa)*st)*dr +\n", " (-r*ca*cb*st+(ca*sb*sp + cp*sa)*r*ct)*dtheta +\n", " ((ca*cp*sb - sa*sp)*r*st)*dphi)\n", " \n", " return (dx, dy, dz)\n", "\n", "\n", "cpdef tuple xyz_to_spherical(float dx, float dy, float dz, float x, \n", " float y, float z):\n", " \"\"\"\n", " Convert cartesian back to spherical\n", " \"\"\"\n", " cdef r, dr, dth, dph\n", " r = sqrt(x**2+y**2+z**2)\n", " dr = (x*dx+y*dy*z*dz)/r\n", " dth = ((x*z*dx+y*z*dy)/r**2/sqrt(x**2+y**2)-sqrt(x**2+y**2)*dz)/r**2\n", " dph = -y/(x**2+y**2)*dx+x/(x**2+y**2)*dy\n", " return (dr, dth, dph)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ -cos(beta)*cos(theta)*sin(alpha) - (sin(alpha)*sin(beta)*sin(phi) - cos(alpha)*cos(phi))*sin(theta) r*cos(beta)*sin(alpha)*sin(theta) - (sin(alpha)*sin(beta)*sin(phi) - cos(alpha)*cos(phi))*r*cos(theta) -(cos(phi)*sin(alpha)*sin(beta) + cos(alpha)*sin(phi))*r*sin(theta)]\n", "[ cos(beta)*sin(phi)*sin(theta) - cos(theta)*sin(beta) r*cos(beta)*cos(theta)*sin(phi) + r*sin(beta)*sin(theta) r*cos(beta)*cos(phi)*sin(theta)]\n", "[ cos(alpha)*cos(beta)*cos(theta) + (cos(alpha)*sin(beta)*sin(phi) + cos(phi)*sin(alpha))*sin(theta) -r*cos(alpha)*cos(beta)*sin(theta) + (cos(alpha)*sin(beta)*sin(phi) + cos(phi)*sin(alpha))*r*cos(theta) (cos(alpha)*cos(phi)*sin(beta) - sin(alpha)*sin(phi))*r*sin(theta)]\n" ] } ], "source": [ "def print_formulas(): # enclosed in a function to prevent altering the namespace\n", " alpha, beta = var('alpha, beta')\n", " spher. = E.chart()\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta) # normal Spherical->Cartesian transformation\n", " y, z = y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta) # first rotation\n", " x, z = x*cos(alpha)-z*sin(alpha), z*cos(alpha)+x*sin(alpha) # second rotation\n", " spher.transition_map(E.default_chart(), [x, y, z])\n", " print(list(E.changes_of_frame().values())[0][spher.frame(),:, spher])\n", "\n", "print_formulas()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport exp, erf\n", "\n", "cpdef float profile(float x, float disk_min, float disk_max):\n", " cdef float y \n", " # we really don't want negative values\n", " if xdisk_max:\n", " return 0\n", " y = (exp(-(disk_min-20-x)**2/400)*(x-disk_min)**2*(disk_max-x)**2/10000 +\n", " exp(-(32-x)**2/70)/2*(x-disk_min)**2*(disk_max-x)**2/150000)\n", " return max(y, 0)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "Graphics object consisting of 1 graphics primitive" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "plot(lambda x, d1=disk_min, d2=disk_max: profile(x, d1, d2), \n", " xmin=0, xmax=60, ymin=0, ymax=1.4)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin, acos, sqrt, abs, atan2\n", "cimport cython\n", "from __main__ import profile\n", "from __main__ import xyz_to_spherical\n", "from __main__ import spherical_to_xyz\n", "\n", "@cython.boundscheck(False)\n", "@cython.wraparound(False)\n", "cpdef tuple intersection(list curve, float m, float alpha, float beta, \n", " float dmin, float dmax):\n", " cdef float x, y, z\n", " cdef float x2, y2, z2\n", " cdef float r, theta, phi\n", " cdef int n, i\n", " cdef float t\n", " cdef float sinalpha, cosalpha\n", " cdef float sinbeta, cosbeta\n", " cdef float R, G, B\n", " cdef float dr, dtheta, dphi\n", " cdef float dx, dy, dz\n", " cdef float th\n", " R, G, B = 0., 0., 0. # return values\n", " sinalpha = sin(alpha)\n", " cosalpha = cos(alpha)\n", " sinbeta = sin(beta)\n", " cosbeta = cos(beta)\n", " n = len(curve)\n", " r, theta, phi = curve[0][2:5]\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " x, y, z = x, y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta)\n", " z = z*cos(alpha)+x*sin(alpha)\n", " for i in range(1, n): \n", " r = curve[i][2]\n", " theta = curve[i][3]\n", " phi = curve[i][4]\n", " # rotations\n", " x2, y2, z2 = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " y2, z2 = y2*cosbeta-z2*sinbeta, z2*cosbeta+y2*sinbeta\n", " x2, z2 = x2*cosalpha-z2*sinalpha, z2*cosalpha+x2*sinalpha\n", " if z!=z2:\n", " t = z/(z-z2)\n", " if t>=0 and t<1 and curve[i][2]>dmin and curve[i][2]= 255:\n", " R = 255\n", " return R, G, B" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "def render_row(x):\n", " \"\"\"\n", " Render a single row of the image\n", " \"\"\"\n", " res = np.zeros((ny,3)) # result row in RGB format\n", " for y in range(ny):\n", " beta = atan2(y-ny/2,x) # beta angle \n", " r = sqrt(x**2+(y-ny/2)**2) # pixel distance to the center of the image\n", " ind_geo = int(r/400*n_geod*720/nx) # index of the geodesic to use. values are obtained by trial and error.\n", " if ind_geo" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display plain\n", "data = np.zeros( (ny, nx, 3), dtype=float )\n", "render()\n", "img2 = toimage(data)\n", "img2" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": [ "from six.moves.urllib.request import urlretrieve # valid for both Python 2 and Python 3\n", "urlretrieve(\"http://www.cvrl.org/database/data/cmfs/ciexyzjv.csv\", \n", " \"ciexyzjv.csv\")\n", "ciexyz = np.genfromtxt(\"ciexyzjv.csv\", delimiter=\",\")" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.plot(ciexyz[:,0],ciexyz[:,3], label='Z')\n", "plt.plot(ciexyz[:,0],ciexyz[:,2], label='Y')\n", "plt.plot(ciexyz[:,0],ciexyz[:,1], label='X')\n", "plt.legend(loc='best')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport exp\n", "\n", "cpdef float blackbody(float nu, float T, float doppler):\n", " \"\"\"\n", " Spectral power emmited at frequency nu by a black-body at \n", " temperature T per square meter par steradian\n", " \"\"\"\n", " cdef float h = 6.62e-34\n", " cdef float k = 1.38e-23\n", " cdef float c = 3e8\n", " cdef float h_sur_k = 4.79710144927536e-11\n", " return (2*h)*nu/c*nu/c*nu/(exp(h_sur_k*nu/doppler/T)-1)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "verbose 0 (3835: plot.py, generate_plot_points) WARNING: When plotting, failed to evaluate function at 171 points.\n", "verbose 0 (3835: plot.py, generate_plot_points) Last error message: 'Unable to compute f(3000.0)'\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "Graphics object consisting of 1 graphics primitive" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "plot(spline([(l, blackbody(3e8/(l/1e9), 10000, 1)) for l in ciexyz[:,0]]), \n", " xmin=5, xmax=3000)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from __main__ import blackbody\n", "from libc.math cimport exp\n", "import numpy as np\n", "cimport numpy as np\n", "cimport cython\n", "\n", "DTYPE = np.float\n", "ctypedef np.float_t DTYPE_t\n", "\n", "cdef np.float_t[:] cielamb\n", "cdef np.float_t[:] ciex\n", "cdef np.float_t[:] ciey\n", "cdef np.float_t[:] ciez\n", "\n", "def init_arrays():\n", " global cielamb, ciex, ciey, ciez\n", " cdef np.ndarray[np.float_t, ndim=2] ciexyz = np.genfromtxt('ciexyzjv.csv', delimiter=\",\") \n", " cielamb = ciexyz[:, 0]\n", " ciex = ciexyz[:, 1]\n", " ciey = ciexyz[:, 2]\n", " ciez = ciexyz[:, 3]\n", " \n", "init_arrays()\n", "\n", "cpdef tuple temp_to_XYZ(float T, float doppler):\n", " cdef int nl = len(cielamb)\n", " cdef np.ndarray[np.float_t, ndim=1] sp = np.zeros(nl)\n", " cdef int i\n", " cdef float x, y, z\n", " for i in range(nl):\n", " sp[i] = blackbody(3e8/(cielamb[i]/1e9), T, doppler)\n", " x = np.dot(sp, ciex)\n", " y = np.dot(sp, ciey)\n", " z = np.dot(sp, ciez)\n", " return (x, y, z)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": [ "def xyz_to_rgb(*args):\n", " # constants\n", " fact = 3e-8 # arbitrary\n", " gamma = 1/2.2\n", " mat = [[3.24047, -1.53715, -0.498835],\n", " [-0.96256, 1.8752, 0.041556],\n", " [0.055648, -0.204043, 1.057311]]\n", " # conversion\n", " r, g, b = np.dot(mat, np.transpose(args)/fact).tolist()\n", " # gamma correction and clipping\n", " r = min(1,max(0, r)**gamma)\n", " g = min(1,max(0, g)**gamma)\n", " b = min(1,max(0, b)**gamma)\n", " return r, g, b" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "image/png": 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vV4uZulzC8ZvA7WrB5Lr3HcPrIPD2rrUYfocXAweGvyefAJ62EbXwURCS1JTfBJakpgwASWrKAJCkpgwASWrKAJCkpgwASWrKAJCkpv4PGKvpEAj5UWoAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from matplotlib.patches import Rectangle\n", "axes = plt.gca()\n", "axes.set_xlim([1000, 6000])\n", "for T in range(1000, 6000, 200):\n", " # plot a rectangle at a color obtained from the temperature\n", " axes.add_patch(Rectangle((T, 0), 200, 1, facecolor=xyz_to_rgb(*temp_to_XYZ(T, 1))))" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin, acos, sqrt, abs, atan2\n", "cimport cython\n", "from __main__ import profile\n", "from __main__ import xyz_to_spherical\n", "from __main__ import spherical_to_xyz\n", "from __main__ import temp_to_XYZ\n", "\n", "@cython.boundscheck(False)\n", "@cython.wraparound(False)\n", "cpdef tuple intersection(list curve, float m, float alpha, float beta, \n", " float dmin, float dmax):\n", " cdef float x, y, z\n", " cdef float x2, y2, z2\n", " cdef float r, theta, phi\n", " cdef int n, i\n", " cdef float t\n", " cdef float sinalpha, cosalpha\n", " cdef float sinbeta, cosbeta\n", " cdef float X, Y, Z\n", " cdef float X0, Y0, Z0\n", " cdef float dr, dtheta, dphi\n", " cdef float dx, dy, dz\n", " cdef float th, doppler, factor,\n", " X, Y, Z = 0., 0., 0. # return values\n", " # 20 percent speed gain\n", " sinalpha = sin(alpha)\n", " cosalpha = cos(alpha)\n", " sinbeta = sin(beta)\n", " cosbeta = cos(beta)\n", " n = len(curve)\n", " r, theta, phi = curve[0][2:5]\n", " # rotations\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " x, y, z = x, y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta)\n", " z = z*cos(alpha)+x*sin(alpha)\n", " for i in range(1, n): \n", " r = curve[i][2]\n", " theta = curve[i][3]\n", " phi = curve[i][4]\n", " # rotations\n", " x2, y2, z2 = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " y2, z2 = y2*cosbeta-z2*sinbeta, z2*cosbeta+y2*sinbeta\n", " x2, z2 = x2*cosalpha-z2*sinalpha, z2*cosalpha+x2*sinalpha\n", " if z!=z2:\n", " t = z/(z-z2)\n", " if t>=0 and t<1 and curve[i][2]>dmin and curve[i][2]" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img3 = toimage(data_rgb)\n", "img3" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "eqs = curve._equations_rhs[C]" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "dt, dr, dth, dph = curve._velocities" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}0\n", "\\end{math}" ], "text/plain": [ "0" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display latex\n", "# d^2t/dtau^2 = \n", "eqs[0].subs({th: pi/2, dr: 0, dth: 0})" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}-\\frac{\\mathit{Dph}^{2} a^{6} m r^{2} - 4 \\, \\mathit{Dph}^{2} a^{4} m^{2} r^{3} - 4 \\, \\mathit{Dph}^{2} a^{2} m^{2} r^{5} + \\mathit{Dph}^{2} a^{2} m r^{6} + 4 \\, \\mathit{Dph}^{2} m r^{8} - \\mathit{Dph}^{2} r^{9} - 2 \\, \\mathit{Dph} \\mathit{Dt} a^{5} m r^{2} + 8 \\, \\mathit{Dph} \\mathit{Dt} a^{3} m^{2} r^{3} + \\mathit{Dt}^{2} a^{4} m r^{2} - 4 \\, \\mathit{Dt}^{2} a^{2} m^{2} r^{3} - 4 \\, \\mathit{Dt}^{2} m^{2} r^{5} + \\mathit{Dt}^{2} m r^{6} + 2 \\, {\\left(2 \\, \\mathit{Dph}^{2} a^{2} - \\mathit{Dph} \\mathit{Dt} a\\right)} m r^{6} - 2 \\, {\\left(\\mathit{Dph}^{2} a^{2} + 2 \\, \\mathit{Dph}^{2} m^{2}\\right)} r^{7} - {\\left(\\mathit{Dph}^{2} a^{4} - 8 \\, \\mathit{Dph} \\mathit{Dt} a m^{2}\\right)} r^{5} + 2 \\, {\\left(\\mathit{Dph}^{2} a^{4} m + 2 \\, \\mathit{Dph}^{2} a^{2} m^{3}\\right)} r^{4} - 4 \\, {\\left(\\mathit{Dph} \\mathit{Dt} a^{3} m + 2 \\, \\mathit{Dph} \\mathit{Dt} a m^{3}\\right)} r^{4} + 2 \\, {\\left(\\mathit{Dt}^{2} a^{2} m + 2 \\, \\mathit{Dt}^{2} m^{3}\\right)} r^{4}}{a^{2} r^{6} - 2 \\, m r^{7} + r^{8}}\n", "\\end{math}" ], "text/plain": [ "-(Dph^2*a^6*m*r^2 - 4*Dph^2*a^4*m^2*r^3 - 4*Dph^2*a^2*m^2*r^5 + Dph^2*a^2*m*r^6 + 4*Dph^2*m*r^8 - Dph^2*r^9 - 2*Dph*Dt*a^5*m*r^2 + 8*Dph*Dt*a^3*m^2*r^3 + Dt^2*a^4*m*r^2 - 4*Dt^2*a^2*m^2*r^3 - 4*Dt^2*m^2*r^5 + Dt^2*m*r^6 + 2*(2*Dph^2*a^2 - Dph*Dt*a)*m*r^6 - 2*(Dph^2*a^2 + 2*Dph^2*m^2)*r^7 - (Dph^2*a^4 - 8*Dph*Dt*a*m^2)*r^5 + 2*(Dph^2*a^4*m + 2*Dph^2*a^2*m^3)*r^4 - 4*(Dph*Dt*a^3*m + 2*Dph*Dt*a*m^3)*r^4 + 2*(Dt^2*a^2*m + 2*Dt^2*m^3)*r^4)/(a^2*r^6 - 2*m*r^7 + r^8)" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# d^2r/dtau^2 = \n", "eqs[1].subs({th: pi/2, dr: 0, dth: 0})" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}0\n", "\\end{math}" ], "text/plain": [ "0" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# d^2th/dtau^2 = \n", "eqs[2].subs({th: pi/2, dr: 0, dth: 0})" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}0\n", "\\end{math}" ], "text/plain": [ "0" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# d^2ph/dtau^2 = \n", "eqs[3].subs({th: pi/2, dr: 0, dth: 0})" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left[\\mathit{Dt} = \\frac{\\mathit{Dph} a m - \\sqrt{m r} \\mathit{Dph} r}{m}, \\mathit{Dt} = \\frac{\\mathit{Dph} a m + \\sqrt{m r} \\mathit{Dph} r}{m}\\right]\n", "\\end{math}" ], "text/plain": [ "[Dt == (Dph*a*m - sqrt(m*r)*Dph*r)/m, Dt == (Dph*a*m + sqrt(m*r)*Dph*r)/m]" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "eqs[1].subs({th: pi/2, dr: 0, dth: 0}).solve(dt)" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "p = M((0, r, pi/2, 0))\n", "Tp = M.tangent_space(p)\n", "v = Tp((r*sqrt(r/m)*dph, 0, 0, dph))" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}-4 \\, \\mathit{Dph}^{2} a m \\sqrt{\\frac{r}{m}} + \\frac{\\mathit{Dph}^{2} {\\left(2 \\, m - r\\right)} r^{2}}{m} + \\frac{{\\left(2 \\, a^{2} m + a^{2} r + r^{3}\\right)} \\mathit{Dph}^{2}}{r}\n", "\\end{math}" ], "text/plain": [ "-4*Dph^2*a*m*sqrt(r/m) + Dph^2*(2*m - r)*r^2/m + (2*a^2*m + a^2*r + r^3)*Dph^2/r" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.at(p)(v,v)" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}\\left[\\mathit{Dph} = -\\sqrt{\\frac{m r}{4 \\, a m^{2} r \\sqrt{\\frac{r}{m}} - 2 \\, a^{2} m^{2} - a^{2} m r - 3 \\, m r^{3} + r^{4}}}, \\mathit{Dph} = \\sqrt{\\frac{m r}{4 \\, a m^{2} r \\sqrt{\\frac{r}{m}} - 2 \\, a^{2} m^{2} - a^{2} m r - 3 \\, m r^{3} + r^{4}}}\\right]\n", "\\end{math}" ], "text/plain": [ "[Dph == -sqrt(m*r/(4*a*m^2*r*sqrt(r/m) - 2*a^2*m^2 - a^2*m*r - 3*m*r^3 + r^4)), Dph == sqrt(m*r/(4*a*m^2*r*sqrt(r/m) - 2*a^2*m^2 - a^2*m*r - 3*m*r^3 + r^4))]" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(g.at(p)(v,v)==-1).solve(dph)" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin, acos, sqrt, abs, atan2\n", "cimport cython\n", "from __main__ import profile\n", "from __main__ import xyz_to_spherical\n", "from __main__ import spherical_to_xyz\n", "from __main__ import temp_to_XYZ\n", "\n", "@cython.boundscheck(False)\n", "@cython.wraparound(False)\n", "cpdef tuple intersection(list curve, float m, float alpha, float beta, \n", " float dmin, float dmax):\n", " \"\"\"\n", " Return True if the curve intersect the disk comprised between dmin \n", " and dmax tilted of angles alpha and beta\n", " \"\"\"\n", " cdef float x, y, z\n", " cdef float x2, y2, z2\n", " cdef float r, theta, phi\n", " cdef int n, i\n", " cdef float t\n", " cdef float sinalpha, cosalpha\n", " cdef float sinbeta, cosbeta\n", " cdef float X, Y, Z\n", " cdef float X0, Y0, Z0\n", " cdef float dt, dt0, dr, dtheta, dphi\n", " cdef float dx, dy, dz\n", " cdef float th, rho, doppler, beta_rel\n", " X, Y, Z = 0., 0., 0. # return values\n", " # 20 percent speed gain\n", " sinalpha = sin(alpha)\n", " cosalpha = cos(alpha)\n", " sinbeta = sin(beta)\n", " cosbeta = cos(beta)\n", " n = len(curve)\n", " r, theta, phi = curve[0][2:5]\n", " dt0 = curve[1][1]-curve[0][1]\n", " # rotations\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " x, y, z = x, y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta)\n", " z = z*cos(alpha)+x*sin(alpha)\n", " for i in range(1, n): \n", " r = curve[i][2]\n", " theta = curve[i][3]\n", " phi = curve[i][4]\n", " # rotations\n", " x2, y2, z2 = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " y2, z2 = y2*cosbeta-z2*sinbeta, z2*cosbeta+y2*sinbeta\n", " x2, z2 = x2*cosalpha-z2*sinalpha, z2*cosalpha+x2*sinalpha\n", " if z!=z2:\n", " t = z/(z-z2)\n", " if t>=0 and t<1 and curve[i][2]>dmin and curve[i][2]" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display plain\n", "data = np.zeros( (ny, nx, 3), dtype=float )\n", "render()\n", "data_rgb = XYZ_to_RGB(data)\n", "img4 = toimage(data_rgb)\n", "img4" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [], "source": [ "beta = var('beta')" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "thp = acos((cos(th)-beta)/(1-beta*cos(th)))" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/latex": [ "\\begin{math}\n", "\\newcommand{\\Bold}[1]{\\mathbf{#1}}-\\frac{\\frac{{\\left(\\beta - \\cos\\left({\\theta}\\right)\\right)} \\beta \\sin\\left({\\theta}\\right)}{{\\left(\\beta \\cos\\left({\\theta}\\right) - 1\\right)}^{2}} + \\frac{\\sin\\left({\\theta}\\right)}{\\beta \\cos\\left({\\theta}\\right) - 1}}{\\sqrt{-\\frac{{\\left(\\beta - \\cos\\left({\\theta}\\right)\\right)}^{2}}{{\\left(\\beta \\cos\\left({\\theta}\\right) - 1\\right)}^{2}} + 1}}\n", "\\end{math}" ], "text/plain": [ "-((beta - cos(th))*beta*sin(th)/(beta*cos(th) - 1)^2 + sin(th)/(beta*cos(th) - 1))/sqrt(-(beta - cos(th))^2/(beta*cos(th) - 1)^2 + 1)" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display latex\n", "diff(thp,th)" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "aberration = abs(diff(thp,th)) # abs needed if we want negative angles" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "Graphics object consisting of 10 graphics primitives" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "P = plot(aberration.subs(beta=0.), [-pi*.99,pi*.99])\n", "for i in range(1,10):\n", " P += plot(aberration.subs({beta: 0.1*i}), [-pi*.99,pi*.99])\n", "P.plot()" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin ,sqrt\n", "\n", "cpdef float focalisation_factor(float th, float beta):\n", " # uses an other expression stricly equal, but faster to compute.\n", " return (cos(th)*(cos(th)+beta)+sin(th)**2)/\\\n", " (sin(th)**2*sqrt(1-beta**2)+1/sqrt(1-beta**2)*(beta+cos(th))**2)" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": [ "%%cython\n", "from libc.math cimport cos, sin, acos, sqrt, abs, atan2\n", "cimport cython\n", "from __main__ import profile\n", "from __main__ import xyz_to_spherical\n", "from __main__ import spherical_to_xyz\n", "from __main__ import temp_to_XYZ\n", "from __main__ import focalisation_factor\n", "\n", "@cython.boundscheck(False)\n", "@cython.wraparound(False)\n", "cpdef tuple intersection(list curve, float m, float alpha, float beta, \n", " float dmin, float dmax):\n", " cdef float x, y, z\n", " cdef float x2, y2, z2\n", " cdef float r, theta, phi\n", " cdef int n, i\n", " cdef float t\n", " cdef float sinalpha, cosalpha\n", " cdef float sinbeta, cosbeta\n", " cdef float X, Y, Z\n", " cdef float X0, Y0, Z0\n", " cdef float dt, dt0, dr, dtheta, dphi\n", " cdef float dx, dy, dz\n", " cdef float th, rho, doppler, beta_rel\n", " X, Y, Z = 0., 0., 0. # return values\n", " # 20 percent speed gain\n", " sinalpha = sin(alpha)\n", " cosalpha = cos(alpha)\n", " sinbeta = sin(beta)\n", " cosbeta = cos(beta)\n", " n = len(curve)\n", " r, theta, phi = curve[0][2:5]\n", " dt0 = curve[1][1]-curve[0][1]\n", " # rotations\n", " x, y, z = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " x, y, z = x, y*cos(beta)-z*sin(beta), z*cos(beta)+y*sin(beta)\n", " z = z*cos(alpha)+x*sin(alpha)\n", " for i in range(1, n): \n", " r = curve[i][2]\n", " theta = curve[i][3]\n", " phi = curve[i][4]\n", " # rotations\n", " x2, y2, z2 = r*sin(theta)*cos(phi), r*sin(theta)*sin(phi), r*cos(theta)\n", " y2, z2 = y2*cosbeta-z2*sinbeta, z2*cosbeta+y2*sinbeta\n", " x2, z2 = x2*cosalpha-z2*sinalpha, z2*cosalpha+x2*sinalpha\n", " if z!=z2:\n", " t = z/(z-z2)\n", " if t>=0 and t<1 and curve[i][2]>dmin and curve[i][2]" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%display plain\n", "data = np.zeros( (ny, nx, 3), dtype=float )\n", "render()\n", "data_rgb = XYZ_to_RGB(data)\n", "img5 = toimage(data_rgb)\n", "# img5.save(\"my_home_made_black_hole.png\") # uncomment to save\n", "img5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img1" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "data": { "image/png": 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jyewIk+YjnootIgdozPAm5V6ZymgZykuwkuYdlXsllX+Ay/UoynQ5QucIPDwE4Qg8KLSejJlnDDXP6FCNpcxI2saumA3QUhla9znVZSHK8p3qa+iLGe6ytQleAZxl8KzBtkTEEgubaTnHdtljS0+2KlSNl1WrdohiIR6WqfatoP7+7JFEkVR/H0zem1WHCMEj8JAQhCPwQODauVSr2Rx7kWpiYamGfXUFpSqQBVLswfWVKBbSecK2ptQSF5sp6FONVfLhJuC9VeFioB3tyVqWxsRiY5+s5m8nJWprq7zaV85R0aCB+MeuJhkwtMNlHuqP31AOFFJH4MEgCEfgQUGxDdY2RNDe0Re9dvXq6HlSBqonGZNmBQZLNSRhn/XVc7xKWz3DwhKIDtXgTbNpuSrWP66F+qOyRF0ESiR6udQ9fdSV2A60cCmCy97sJejvolpuc3IJI13o6VS+BsbDb6EdNrBDvk+6wP2nt6AagQeDIByBew9X21Dvvo61M4VDRPeGarDnxUaJojZaaDAMkI10hY2WkXNNb+tJ12UblmR0OAfqHJdz2ONa2LNTkoYsB/oieKoTyeRjjXO4pKGlr8D0tq1qi9QhOkcqQsVc04W5FBvqr55zDfxns1P93yuZLo2lqoHAPUUQjsD9xka2kWq24VKNoSYc6hOiiSyZegyVBrTsgXq85vJDvcmaQCs2tDSMPtWYze6zV4k6qY3OFIY8rysGICc4G7cUax5W5nHJB6925A21SZV3r4tFR+pIpd8GuqBDHZmBml6MhnygftUW9Edx0jymXIHAPUUQjsB9hUs1hHBYbWNn2MZAoRv7BtUQXwzoKOqBW0nfUrjzOA5julR+NpnW/dEhHPbPO1DHB8xeJSAbqRqwyjzYL8DnZbmF5RxD/YGKVFfoQnGFVjeemuDV1sVSp8aNmcm9Iic11h8eRT0+hYssAgnrHPCIYEgdgfuLIByB+w2XbSSPbYx1rMbCNvZG3hjpOXUwRoVhXex21W2tarmFtStK52gxCcU5WlRDCSGgTagT2w2b7KLsMXMLXs7lMqFOy0Wc68vKKojA5XZ9GtFPWHS4CC8zNXsunSwhHSijcUkfSM+QC6E0D/HUcE4oHIF7jSAcgfsHpTeg5hmpDtcQwrGvhQ3lUkn1ywVDbeqysW2usJ9NYdR7iequcpIpaR0cHUrRybRUA/R3Htaf0nKmrNo5dcoDSR2sXkjJgViFoh2JOmcwVyERC+SjM0tTx7KNVJ4sW5IzO1Up9pNpHA6lw3d0LBbeDjRQDyT8JPPGbPaYB4J8BO4bgnAE7hn6bEN5Utyvle+JaijNY6SqQPW7bCPVq5yDurxqvH0yxprx2MgqOKGCNvhD2jCcY6YlN+bsGI6JTnygZaK0MIyZiMVMl5JNOPOMuV4F1dyCaozNV5fDrVaRDJeO8PAQx8pAHxjNVP5AdARF5OCRINdF6EuqKwnOEbhHCMIRuE9QbIPFdo4PVaGgomeMJaG+usHOF1DQhrI9lm3AK+Y2u2/YWrTDChiZHnk7bIM5R+dnOQe3gdnGSTEcyg8l9lLYRq7/tD3RqjCJbDiHIh+zYQ98ULtqeZ66yrm+Uu7unTpRX0RRLCSYg4M2RpMe6aSOtFRfBlO6V3COwD1CEI7AvYF6oGSqkWjKHki6EFZh2caefCjyr2ws4DPU5K4EfLVJdrH1qNOxtIMTLj+Y69UlMdVsQ4zTTOQD5n1LNHQObsl2hUOe4Af6Z1TOYbYBWhWGwelccgay3GMtiggF6XtYUI8cu4o6H12dw9KUVkLR01S4xZI+AHvTgFz+k0UGAPd/ouvFuwTnCNwXBOEI3ANYUyFsQykc6q2TkdjGvvEerPwBLActusjGlvT5RAuZTkSRDIHrNFHLuZGfGzyDiQjqAtwAN2L0JIVD+S9Y2xDvCYh8DCXNBYZy7m5aykikCNMOJX60yEfrGnW4iGW9rdpSabM0cigxpKJtSADHgbjy4oKRqI4D0UE+ZTmvljwWCNw1BOEI3HW4D5dMNTgCQ31OQySN0dM2JFx0oC+XK+Ed3kMkr65qGB1sd6AsMgZrGJZt2ITlGS1hQ7GNFg3qQKwgX6+pdq+wjsJSR6ZM4RxzKSNKRibmkYkg5lr8sC3f4iXhrfasOxSEV9XgEc4xlhNfNk1mpKFu+c701VzIinSLCiNttTwQuDsIwhG403DdKIk0CQ6/4KCNSyIZY+1VsdoG2nEbC1a1jZbakYwZUEo7NtAOGwo6tblFJ585h/WtqDRMs21T5RxRnz4bUSVvsLYhkQ3MFZhbwCR4VTK5BkWVLC3oOFZSYy94JXnZETy430YKIFU6hwRzjKXYAkvj5kI+hHsJLDMOBO4UgnAE7ihabpRUfzk0EeG4KDSCVY1VbSM12IbVq1ucQ2xhamy1tEM2cdr+mFi4bENy5gbhQM080IjkkLTiHDjRgHEHMsNgtUPSwjYkJlQe6FMdnTPQ5c7U4aMRPEROUAypQxdAV4dlhuQtbSUdtgHaMQEzKTEwOofqOhRqMtCh1biaaBc7XAOBu4YgHIE7DcU22JMiCse+dqAwz3hUCvS1DTmEekZUagQnVg0Yb1U7si0Ue8lpK1FMlJjrfDewo888UGfC4xyojdaqAbMdMte9YRUOEOdAHbrBxALULUMhGTNxDm6eDBV1FC6QG5ds+zVVp+ySYznWQOcyr+kcKlZGTn8u/wknBaxvJRSOwB1HEI7AnYM717MUwVSDP6SxyBiXJf/COFM6bAOGc/CTIj+nutO6NWkCNjmKfLBpb1ENK2ZIjhU2+jWg5hxsulC3R5m988DRG6kYSDlfEL1AfSG4x4RbzJQ5kiUWo664afKCRWQXlyJYHtm6prwjTELRLK5hUTh2JG8ciUMDOBaWvJCSp+VlFhEzJuBQnw5q2sEI8hG4UwjCEbhbsE+ZTDVEV5e3UUTYGChuY2Eb+5qFSLSHyzYslHxtNW3LTpRJs4qIFQ9ybVkt7WAZ40ic40i7TLUKwjWgZh6cgzpHcJ7pst3IDAOkcCQKuZipr+ZiaFPtT0k1w8jFZs/lFY9dTURYD8skq1jaIS13yQFqWgPvisPUY0UOLpOJPE3lNCdgBJ7VzOOq7DLVSk8qfbu8xjLRqcnJdnhSIPACEYQjcFfQ0qWVR5+/0yXvuCqqsaQvqMCOyIqrbciU7coboK2qkTBGRSq0MYyMFtVQGkYmJWMihtEqlg3DUMxDUQ1OwGvwSRZL9Q//Db0NWZjJxAoFUfxDWMtMXbpUIv96g9oRAwoKQU1r5HQsPUr1YOAD9a+1zXTZBpMVq3MsJE++94XSeygnOJWWT7ScS51Wo0LJUUw3EHiBCMIRuBNwJ+tUsw1xiAzEJB41qMa+ZiTCNnbGHshxeVLOnk1aPQU2Zqk2gQps7G34hdAIJV2w1DFTOhuqoVZhVA0lbLicwza4f/q2mGukOWhGntf5CX4gJiHVDiRsqOAMPrTSVPigc81L3OvLUgePyf7pq9PsJECnkwu9YDbGSt4icija8dQcUQjKXKgMgzsqEHixCMIRePFosQ3++qewByEQTDXk4+UXdeZQ/1UK6+1yRNY2GNakJS/TnosSS+QEWTMQqqFcJ5I+1vmz0TmU5qFIxkTNYKkDlK8SqBvZyXHhKgeKciVP6oCRE+ZyxWePKPCbKSMlhvoy7erLITXz5bADD3XD5EJ3zkvRVq6wo3OgtHxPHhZVCYh2yF/OotCOgeI/jnXXiZ+FB15wjsALRxCOwAuGnaP5UU84x74WNtSLryJ1XBDVkL+el3pSbQnkuC2KYOdo1Vq7VRERK3Iw22DaMXt8QoI2mHaw4OHGbcxUOesZdhWNhMV5Cge8DgF1b6p5wEyZuWYbQj6EZ3BaDrRUNRDlYiLCVWXTNssPUEsmUsxlV6ChZemLq3NIG2S0j4U9jEQdxiJssP/oUNcPYhtj7T7jbg/OEXiBCMIReGFoTcqJfCiDYRujidi4qKkGf3hDvkAqdYJoAdtd9xEWVB5mNVFVspetxBp7pXCwdJFpqRwronlwJMdsMi3VcHlGi2ScbZBaO6b6WKwuZO/SM+FghUM+BbtgJibBys1YOjCZo6gmqT5RbMMVPyxBUQMDZscW/8jkGJqJKwg/XviESBrL8qpk5toztUgdB3KfyZKhNI9A4DkjCEfgxcBO6Ozv4P83ER/Knjwp8m8pj+idWPVPsANFbIzGiqCmDh3ygYaZ6RszVS0nbNCG9ZIIyZiNwmH9LxOZT5dwoE6jNjm3an5crsZblTlXP9lrLuNB0rkoHIO5gqxtsNrBfGKuSYniHKgbgHr3jmCQvESqDw2zlNdzWKcZy6soi+YhX047luVQfCsgDso186iQTm61PBC4bQThCLwAdNgGB80tmoR8TkNedt2RtrGrY0VZDkmUgJmIYR64pUktPcMKG0osUfvykzfqqZ/dH/ajXhP9rGNFvZPC/7FiOQcoAS/xPNE6KHesJBKFbgilkMAOFNqB2kiLzrFgoivFr4Qk+uin1V2Y+6qBYfkE6gHAmZZkuEORBQ/5t1imHVel/QAekc6xMI8rEjmu6GR5vMmrOtzbwTkCzxlBOALPFfZhka0Le7LltZRd7SsR/vG4/q7XBYVuLPXsG8/K2DDbKmOg9kVtpVSFuV5NJmzT1TaOhmTMbdoxE2VpyRuoE6gTLxxuS6ztZ9qhGIBEV8y0qr5rnol8DLUAoDhHrsM1WhShf/VdUtJhHiDHytKGPZDLn9crz4gEcCxndKRXe9hXeKSOmsrwm+lAtqsDgeeDIByB5wf7eCdzqBAOYRuKZ7CkwaEbu5qF8Nuz8mSM2gb0TZ3bZtR6BurCqbbr8mwqlsxlGyxaqJjQFu1Qu+Q6PpTjBO8y1VBoMTZJsORwrKM6mAIqqiE5zDXZBrucgymF8I+0dvVV2hIOrgR1AnRElOt4UT58vic95qoM6WUkXNGnw66Agf7jfiLaIS+/5FIVx3YochwI3CqCcASeBzrCBlMNVjUGCv8ci+tECMcrhZqM9Vc3xIcy1gcStOZWpUmATI5Vy6UqNlSoC+f6x2xDqMNEuoUlHDZTBZZyYm5QjftiS2w7mXYI51DsZDbKBFMNUGHhK6if/i3nyPWY4SE0UG1u+5X+wTX0E1IJc5qxMM5E5ziU91BAUR0oVOxAshC/KzuRy4k1lVT3cyBwqwjCEbhduM9/imow2xA9g19IWdiGpOWdlOX3qN59Vx8i0cQqzejQDhiGkUz+KgWR1UwPlEIdQA6URQM/Ev9gbeNYk4y5FjbghYiiXt47ZLO69PNMFxSkeYC6XXFE6RDhH/JxTwD7ci2Ens5mbLj8gAeG4hm8l0249chSqECuB9JUWigkg4eK3DtXhXPk2nkkvIrdK6p73bMIBG4cQTgCt4iWtizWQhwfwh4Gz2myRGzwh8yFcHCgaCoiB5sleKK9bSeX4WdixS14guba1CFyvVVFXbCjxCaEgmTKF5KhaIelGg/DYPAjOOhyKMMsz/dTXXKxqXsyt6jZZyrhmXPtXpGjW+9JiyXw2JDMbMqoHTtqh0gRPAiXzMfFk7JQpWeFW4hr8ljIxxX1lYwraYCiwrb9gcBtIAhH4LbQmq+FcLCwsSd94qKWMdiZorjIWL8EO9b1q5ZsoR1c2JoWtaqqcp0CimpIzrF2pnB6qpmHSztUFKrSNh4SrODBL1wsYMeKEkJkSHC++i5nrrcmOEimgB3eSkJrsW14VfFBJRhFnCniEFmWQjhycbssDOyKIjyGEsZxLJXACGOoRw6P/Ic3kAJ3AUE4AjcPO9WK3tASNvZ1emd4xiUpHBf0KqyEfUi1oNlcmWFrFVwxmR+dYQrkel/UmaiJBYsQwi3kzy+OxDyOpHywBJJrVUNoBzyz8SChTo1fuLCXTwaYsIolsaNuX/7wXVYTXdDZDB6YQcUFFElVzVY3Aus0MGleskbCkttcPs4hoaBH8rYsZ31VhpNSOEAJO1b5oLlxRoHANRGEI3CTULqCmlj5xVd+nUREDqVnXBa2sSPmcVHcKEw4pE773AnvMc5tc+oWyDSD24m481BoQ0GFXqhVG0CqXqCFF7TxklgFtsHytoUVJAZ6+hdtY4HysPCftcqwUURTYNlGovd10bbQrtThJpIpyYN2Km+syDvAY3l1hUM35HY40p+wLFt3tFXqYZFMNbtzUoHAeQjCEbgxuBOrYhvq3VcWNpSYoQjHJZXZ0+6smqD+IAE8PYMdK2pah2dvmG2g3t3O1HIIZgn8ZopIHUfiHJLoMA9Q3AaMJ+XlgVKhWNWY6UVZEM/YkR7A8x0LGxJQOdWD1vawDGZFGtDlHKDyqFf7OgeKosMaDICxnNQSsSEKx1inhzKcEvFdPtOZes/y11y3JBC4JoJwBG4AdhoFzcuutmE5x4URMy7rHMU2JHRDGQAYxVg1laVjyXEfbfnp2VaojmUhFoJdKvwqinrllZnHVCscuTYJik7dEr6oWLVfQWdkIb30QQDACHzgNlvFlEJMJozaMRqekci4KmIhDNKVrwRqF9QJ20LV7O1SB+rxiRK5woxzLO6VsURvXJVMUTvcxM7EkCrOYYNJQ+oI3AiCcASuhWTSStXgJftQ2IGyK2+37ujvUVyXylD8KRy6kdpKOOrnVEUyUnsvVYYJChpPflbbsKziQGUmwzYmj23wFxRum238WmACfhkA4KcBAN8DAPhLAIAfbe/4Hkp/IfAe4HMAAH8TGIFvu+l25kbnKyR6e2VnSMbSvQeT6XIRVa0krD6R11gLV9KiGrxJIIRAGs9ixlWJ4TiSsKEUDgkjZZ0DZYAJ50A9zBT1CdoROBv9KTcQaKJDNVCTDP7ShryNIjxjX9OLPXBpMkfzWgq/k8LHZU7AUycbacUbWqeW2rWpV06mmkCwo8T+DiVxVYeLHkn5UOGiqJ3unZafh38N+KeAnwJyYRgLtzicW+ESlbmwkC8EEvC5wPcDf/m6La3A5nmgV0PHoqWN9OqT/FKtou3rrfyTj75wVaLVsYCHmh+ktctkpQ7UwziZMrn+TUSYltFyVUbdMxppz8p448ypDL+p1GADhrKhuep0gnYEzkAQjsA56MyYStWQWE6mGsoGKG1jXxOOsSYc4kYZ6wl6gaIILc6Bxoy5Wpv8FNVgicISjkOZ93k5G6qhNI9M76TchrDx64F/AvhJ4LsBAD96DYbRx76Qj18FfD7wd4FvubnK7diz70CNZsgNxDb2ZtRZwrGjwaxoh6K8MOOn74dqsY1ObTwwjjXhmGpusYy0pyXnqRlyTDsyDeZcL0/i64FAC+FSCZyG/sNZormYIy0SMYbL8pR5STxjMCKHmvcldGNXH0upEawDz5QvTVWzpHKsJLNVEkw1sinfoibqzVieu5XykQ3bsKEbN4J/G/gC4CeA7wZ+APjwrfEMwQH4IQDAjwK/AADwW4CfA/wI8J9du3LulrnEOgx1IIJ1i+zLvlsuFrwrjlrkcCmCbWE2W62DBhT7DG+Eq7dYx+IikW+Pij9lKCEdY/kvw2MRPOQVG/6qx5FcLckTOeyJBO0IbEcoHIFNcB0oMFQjFTKxzJjyVS4OC01ELB4BCXhUHi4flWmRw0VZ0255UtAQM1oPZ6vnKJAalBuF4zCOpwgbvGSXCn9+Y6YD3SDb+M3AzwV+AvgA8GO3zzM62AM/H/gi4OcAfx/4szdRp6W8A5FUUThS7Uxxly2pY1cPReVeQT0gGVsGXl/q4HHu+lYmkjqEVWTgUISNJZGBp+RnyeRekRG4DIy5jM9seBi8GyqYR2AVoXAE1mEf3ZTJ53dThXAkigzdFW1jqH0oF8Q8WOTgT4FdkFICOgrqWTjRMtdpKQNatYaBn9j4gXL5yUNzopJ2/nXFDHdTLtM9CxvKj35TbOO3AZ8P/H3gm27TdbIdB+BDwI8B7wG+CPha4CeBP3W9OqWX5nK9UK7UROld40LglIuIxvhnfpDpoPYKqnGo7iyY2lCPdhS2sWQeC7u6Khx9KDGkGXgEzMDTIn4sN6aElO6KzrHkiNox10fJhv7mxi0TCLQQCkegCVf7ZdVXHuyGBtVIRCl25iFyT9rGvn7KHEv0xlBrG53XX2G0DZvfP0HJdG0Mqw4q3kL0iatavWCF42C0DeVNl6fV6UbZxu8C3gl8BPhO4O9dr6rbwz8OvBf4ecAngD94vaoUDxhpcKowDndAKoVjX79IxTGkLHUozgEzPhVao9FKHW6+Gp9zrXPMJZJjqhW1A+kc7oA8lDGc6zeqjjQ44YWU2jMK5hFwEQpHwEHHgQITpS/v5u0K1UhFmRDnyFBUjaGQDPXbFffKjv4VVl4xQC1fqxa6PINFDlXYnmaqbYMlHBIW4HIUfq9Eys+1DXB1C/7dBtv4OuBHgb8M/AhwvF5Vt4q/B/wI8AXAe4GvA77qGlVxj3EYx9jodnWlBu9KTTTwFPhGsOOTB1g2Awx1GV61jhWYNsj4HEh+W8jrWLSKZ+VN8qflox1LYSEcT4FdiScdi/6R6b/fDkUIAQWLSBDJTLcY3zUtXSfwkiMIR6BCh2pYDVlIAFONHVGNVCJAB+IWj0u+JB7V2sbOPEGOpQ3u9zYUvYAJF4WZ+3juVoxE1clsw+4+kwTNBxLZQySQY/3EKb+OG+U68/XXAB8F/izw4btNNQTHQjt+AfDbgM8Dfu+5Vanrzo6wyethNbCFN+y9y5rq16NQarA6hzuoeNTZManSKnS0RXrmUlKaNxXCMZCv5Fi8KhfAk5IYCqVYaMSzmkBc0bkLHbFsw55L0I6AiyAcAcCb7FDPdDDvuwoVGIlt8L+csDp9AezJvXJhRGwVoycf7VgObYM2UBsDpW0MXjE5KZ4NZTnXxZRNmj1DYhURkabZ/6Kkjs4T9k1Fif5x4EPAn74nVINxBH4I+DDwW4E/Dvxvz61Hek8uK18+1f9K2JBrdyg7jnWd2atTkRVLDgajnMHQYpg7UckbySs2lArFwB8K7Rjr11WGMj4XnrHIGIsb5VA+V7orH0M7lPv6ij5pysFGQjuYfNgLYe+XwEuLIBwvO1pUwwobQ5nadmUWFsLB8f8q4J+5xQA8psxEfpbLwleWyX1fjjWWmXowMxcbFVZ01VYrYMipseUYaC8rb8hRBHM9gUqEP+vw7ue/DqRtqHDR62sbf7Is77gPpY8j8KeBLyin89vPqoQHwGzGuepnO85HGgDHMra5wpH2RSOYQ7FkPpwapVKgRfdZ84BX89KkZVBdFsK0L++tXADPSqzoU+CibD0ATwrJ2BfasSvBpMdCO3LNXeaiFR3J1cijN1FCTjMEj0AQjpcXHarB0xxPoxK2KfSC2caj8ki0NyRDllbeUMKGisVrKcl2vraPj6o8z9FKBeEyYmZY3kDdkpl2yfT2oCgWx5pJuAKGep6+pqoB4BuAHwD+2h0ODt2OxcPyp4BfDXwD8JXXqIo1Kl62FCb5lMVYX69jYSEoFY7ezaIinJJHeaU9oBFryySzHEyOYCyjeiT+MZUm8UlxMIcQiCfAnsjHoSSW2p6WHcUzOBLbEIlIRjIM/5AzDdrxMiMIx0uH1uM+aOpUk6Y886X6u42pDuYfytutQikuPKohjpU9UY1UNA85kAr7FyhikelhFDSRqdnNnaOZZuW6zkS6sWqGklLkm49CNY5kuqaG1MF0hD+8gXPn4j8D/B3g60tMycPA3wU+BPx24M8Av+X03eVKcQhO8roo1QZ4JGFjJF440Vu1oCuV6t9gRq8wD2mY9fq5hhl1DSoB7+5gxiz8Q9QO9f7UnpwpEqt0VQpcAZcUT3ooiX3hHFNx3MhgHoilzfWdxSdrVZ/Ay4AgHC8LXD0DZiJb5kHxnow1A1DCxr4wCYnSGIhV2FWhIPJCCmsbKN9/3BHvyd7cpEx+i22Ani9luhfXiTvjq99A86OyGTDaRq4ljYn4x5GMln2w7mszq/gvgTeAPwj88MNiGwsm4E8CvxD4RuAV4N88cfdMYyDXDHIwolQqDGMinsEkI5fHelV/SxG0eqFAFA7RzzK1E3X5PufghHBllNaiDr8QUrW8urKEaDDt4FW1dVfikw4UjrorfSLjfzInaE+NWyvpwIOHlfECDw0u1XAljaFOi6Qx1HrGUH+2i1nFQP++dlGCM9i98oh2F7YB8qTIZC2N5KnKyhvYYKrtvOw+F4IeDWeaQPl9E/5ogTwIHuiPsiT+7lm9VZjHM8/nkqkNJ+EvAG8AXwN86PR97xd+EfB7gVeA/9Xp+yrtQSS6of6IPrsCL2uufFlvvai/1THWdbJEN5h7TWD58eoY7ogciey3Hczy/XIlts3A08IhZBiLyPGsMAwZ1TN9b+ZIlDpTWFI2op0S8FqPB/0eCDwABOF4sHDdBzxhKWFDJA3FNjggdCBh46JwDiEZi/dkJHnjkmbnRM4U+UrYSPKGfG8DZnY+lW2wqiEJpW3I7Mzx9qipxly/4Ko+oHRVT9NXlCnfVroqNOUp+b+nenaez3WmvA94Hfjq8k8lDx7/E+D3AW8CvvzEHYVVcygSv4O9K5+HGUmNe1T7AS89wiGewZFqG2ragXLc1tgDDcJcJ+xZ9DmHQG6QZWgtUgc7+DIR6KvidrkiziGj9wkw1+TjWMgH/w1h9r5il0nwmOvbdvUWDjw8hEvloaGvZ6C26OxASXWUxkC0gL0nA/EMVjIuyjsmF8Q/2JkylAl9aFONjielwzZQp1lCF+Uc3qQMOlwmT3+mGT/VLVHPjiKzs4uE30DJ9Df07EnJtbyB02fYvwr8NeD//dKwDQA/BHw18C8DfxX4slN2FEdDpvEvAaRDMbcZeFT8DiPFjcpl3dF1VEMRtQNF7qmhvuPU8JMoVG6VcgNJ5ajTfc4hpzzSWR9LJIfQjh0wAfvCHsSHMpe3WsSxsitsYw88Ay4ok/0syrciER4DEWtmHrN3suFqeagIwvEQYI2oOxO5DpSxZhscpbEvm9gnwvRCOMdlmWteKZxDYkWtG0U4jRwu0YQrS9eTsupDsdyi8wgoD5cgEwIyQpZz8O6ZGIOSQ4S4HGiriiS9jpL8fuB14P8F/PCJO953/BAwA18IvB/40lN2VDZMgl0GujS5hDuAruZIr6uox3RGh20of6VqDOrxPJgcV4Xuqx1SP9cm5EN4xo5WFy7ytLCNJ4VnPALeKJ/pe1bYxmVNQS5Kvx2Ai0I+OMJjJDFPvdIiEd+Kc7inH+TjviNcKvcYruIqaZdnoDEb7mi5J314TyFmQiwuCh25LJxDmMdo4jn2pU7FNlBrztxOK65mk7ZTD0/iqZ58B7OVKwQ9s6p4TxW3cUVelWd1uMZV+T0lmfpJ2V1ymJFwsMhJ+GvA68BXvQRxGy38IuDrgDcBv/rEHVM9+MUJwm9OjcDj+m8FL8rv0vOwSDDTrr53hvoFbxWZBO+ZfqbMbLbac0HNhi0zlhuKFQXhW0J8JSwpl+HKcRsT+VlkeShf+JgpemkmP4vcO5kcLkrkY81DtVOxOjsnBO4jQuG4f2jxDPu4Y1UNtvQjzYmpTJF7SlwQ21BixmXhHDvDPCSAY0+17eigcmg0JmJ4hCB7+dwJua5HqIbqHAZrG4lmPSEoybRK/WZiD8qZIn+CNdEmJcWfwTYAPAN+10vMNgB8CPhdwB85fcdM8pWspvKehbzEcUUD9Vge5eVa22EgUDqHovVK5+BWLUsRV6y2l7wxz4lkBrkroizt35V+EKlDHCv7wjn2ZblQikf06bDFLyOZO5I95pI4UG076kbxtjDvsd5Ml3bIiaR6NXBfEITj3mCVZ8ATM5ZVDptX8RlDzQnEmSIBGUNJjIVz7MoT3lB4xgXtxaEe+3KUsQw1noJRW3Qlb7gMQ2XaPpEcJg22ci7D3mXUnhQLsTfWmcK+EvtxDlbjp3OpRgL+K+B3vHyeFIsfAv4j4P3Av3R6T+ZyuRNdpiONhEzBB/ZrsHM9DCyUb2UwtKOlQ4CGnxqQqv28o8szOreVSB2Lq2i5MdmxsqOojkclbmMq/pSZIjyOtZPlkpwsV0UFke9/zLTcmfAO4R/Sq0K8XL4VzOM+IgjHXUfqpjs8Q2Y3lhZ2ZZMiGRLRKSEaQjJEunhE2sYlTUysbXCF6qMdKA9watptuVFQz5K2jOoT7grWJ5KZm0Bzbq4Ly1bLOUT5yLW9kYc20PKKWIjSkKfGw/EWfA/wF4EPn7jXQ8WHge8Avgf4lafsxYNqKleZI2wWhn1VBq1c08lQjUyjQsBUg0VEq3PYAZloYAy0qppt0eccnMm0Rkz7RCKELGfiGVeFmjyiL4Y9I53jaVE7ZiIfV+VemIrgcTTkI9MrMzu6O2aSPVj8sMwDJb/TP4E7giAcdxEbxQxZsglnIVc9Y0mIRqojQAePZ7DrhHnGWDtQ+C2VgSoXqpFqfcX1ZKOeJlwxAzQptzoneau5PiLP4EP9sAua1EBNtTwj1yaqJXLM9cSq2Map+BvANwN/tPFU/RJiBv4oAOBvAP/cifvKVZjKsGSRYyoelmXrRPlzTTsU80DNJ5h5iLio2LbiAcmMELuqTgTdRxGVb0m8SB2L3nBB781KVAdziEPtZHlUFI5n5R0fzhS145KCPOSV2kwOl5FaohREvgG55W5vWBoXuDsIwnFXYAX8Ds9QMxo8npFIYxBJQ5SMgb7idVFTCkUv1OpFvRQHyp6OIlQj1VEjVk9usQ03wXspBSJ5PWOpBh9FprNlKz+5psYuYqJybXss7Zhr5qHISkewaeHdwBXwrcE2aszAtwJfDrwb+NjmvZRdF6sm12sgf4qlGhyCMNIFlcpRPwAMNe1QzBulPGhgsLbBz/egtPusn9oJdEc1awy7Qjt2RdiQ5b4wBqYgzDxmQ0EkfUFKybE+BHtbMoWXKuYx0n0E8rnYrrA8LMjHXUAQjheJDslAbSxTbVMlrcy55Rli/gejalxSpMXOCBiPyhRpVY3Luh4hHHxooRoSrjHUp5Mb059NJDN9uKpGMn2VKcGHkOdR4Q2yaTbSt3q0cuUNjoOz/CPXxc5QOH4x8J8CvxH40VP2eknwI8C/A/xl4N8DfnDzXvx8LzKGLJUDRQSPlsiBWudgqsEiB9OOFv9mMsHclBMtUs63FdY4R6I6QZRiuW2nMieI+WfaYXkGL6fayXJZlkf6UJjEgojawaEee495CMOTUI/B3JguCQvycXcQhON5w5IMmKmhZUGtnpHIwAvbaPEM8ShflJf3mFvsKAjjkgooJ8uFYRupZhv8GAdqpDpN94nEprmLsqnKdhFn8l5SsyINieYvnsJU24R5oNbe2Vdif9l8E6x1dn18C/CNwI+dvuNLgh8D/gLwLcA/eeKOudCLuSTkoxFDfSmH+oF7KCVR81cFq3CMlGk5hzKZLs/ghKy6hhYe1eBVPtBI9wVIz1icLMfysY3L4lKxCgenp5pnXNafUX9W5A35yNhEzGP2mMdM/IPdLqx5tLqIL7ftiiAfzxNBOJ4TOmKGNcZsO5U8wK4K1jPY/I91UIU4UIbaY6JUjbFwDk6MnqrBcaaJnt6YaiRqszpBBTspJG9qUFMn16+OohIspTDbGIzkMNdu+Fx6XigFmxwlsLMbRUqqMEPU0+JG/FbgPwX+aMyMbWTgjwAZ+K3Anz5lL9RyglzNwVxNFf/LIgePjaHUqQj3UP/UndIaq60E6kHFp8MJxbYls98bqv6RbPyyvCi0YFeIxZVxoEwlcypfr5mM2jHV3/YQ5iFfARGB8FB6m/mHhENN1GZpuZxLrvvW7SWVE7g9BOG4XXTu9mSWykLzfMROE/XWieTs6SlKyIF4TFyewaqGJR+yo7z1ymzDqsSdl1Dcac4VP+0saTUMXk1e72VKgCwKEwtX3mDNdqj3GsvzWaKZ0dqkydCOmY576qT2J4EvBP71mA3XkIG/BPwl4JcAv/3EHWeilWLMklE4JH0oN5eMhEf1UOHHAxiFQ+4ayznUcJUEjO+A2YZ6uOdTczkHuvejstbLcVXc0lgSxyKBHCg49Fi0ECYZU612TMQ8HtM/GsqXP3Z0T12UCNOJOIcNo5lK5+e6u1BuW8U51IkH83gOCMJx89goZrSohhIJUv08tKP5S33N8IIyL4gZtHiGEIhHRa7gYI6hRJWKmMEHleMmwzbkRNSJt+72fh+qvnIZRkvqgDcpC9vg/LHkc82ordFU3paUqVa8KigzI2p9Xj0TnyFv/HrgDwA/fsouLy1+HPhzwO85hXDItZjLpReFI9UXdyhb2Z8yl8EzlduBOSWPz1S/HMu3jyLoqIeuK2zA4x+olzjlXnOf/tla8/fBMo3tffF9iMOF/4dWKMWjolI8Ld/qOHjMYyLm8Yj+nHam+26iTLkTMzXSUvxMFxeNvuITTyYncFMIwnED6D9AWNtpzaeiGopnyPOQcmHwiyHCNsYSdbEjbqEiM3aFZwgpkTAOpWqwO0axjVQ3UpnqZBJn9CQzCZUevMxcGmMnUCYcc2n88heaczkRsSvynDTQhDXTTIramWJDN5QzxQrgW/DDwM8A74tZbxsy8D7gK4EfBn7hiTtmegiWKzvSNWWFY6YxcCzkQ9QIHjkoI0p5QvmxwTpWQCRgpgRqtjF7mZzmEzypN1RiLqfARj0bziGJqXhSLupA0adELDj9SpFAWP+QvwKYPP4hoR4z6R/M7Jl5zPWlURSN5wr1RGTFobgTr4kgHOdjlWe4VEM9oPN8xMKG0g/2lClsYyR6IdShzy1kk3ywS/KFYUjYBwsbQ/0GisyeILZhT5l7I3urlpkpaWTYsFQihz1irmefuagR7J9GfV342WiiHQdyoBwAlDkxGWeK4hzuE1UfPw/4ncBHTtnlJcdHgK8vH+fYCLE3TDvkCsplvSAR61DEjKk8r4uR21M9MNqbaIHiXrG+FZTCyvLByBud5Uh72YHnGlerPrJUI5Uw59gBuXwETDiHsIGL2u0o/EMkjUNJS/c+pTITsRDWPNixxULLTG4X1mD43hcNUpaWfyTKT6YrbE7gJAThOA1bxAy7VB4TK2bwckezElt9fja6ILbBhMNlGOIxGWuGwXrGrj7KRf00xm0DzZIgY496xmx1V6v3bHdJQpapzlEFWDripxarbYDyJRpuIsMjTZpKVUcSOVBmLtYz5Jco/2xPytK8vwv8xRP3CvxF4Ld5z6Z9KMKRi6rBf+Y+UD7KGBB5Y3mPIxfzydWyFshhT0N9m6e1MYzaWPJq9pgHyKyCRuDqULTMg9WOXJj6XPiH/E+K8I9l/Ms30efCJGYjY4i8cQBeAZ6W/IlelFU58mPNY6JoVnmoyPVLLiOl+cZU3at63u2cZHICWxCEYx1bSAZoplB6Bqdl3mGSoZy74rBQQaA2OGNnOASzCvk8xkXNRThEYyhpl2fIPDjWDXZPsNUtqz2pakh1zYpnML9xpQ47WbAhYUo00jQNuig8L8vDbq45x0wyu2jI8KgGy7ynTkx/DPjoibsEPgr8sVPeVQEZGxkDLFosA2aqVQ2JJNgVtrEjs8dDyEoXzDbUvW9vBx7PLUrBbCOT1bSP72iMQ3dkWlEk114JuYNG6i7+kNfOYx7PiHyIvCGsQkjDoQSTikwi6ojIHpeGdlyUo3CQ6Uy/iXopkyLCkobqNL4EbhcF+diOIBw++vayTzJAM1df1eA3WmUOSvT26VBzC6tkWLbBhMMWG4yw4SooTIZS+3RUJ3R6z26VHCtaMNUQhjGarWppb3t+bB2K8ZA5Zaaap/p02A2cKNRDfCgo86AUO9TRG1M9bZ2KRd741rP2DXwr8B+dLnIsyGSHZorkOJD5PNQix6EMThY5hOMuWBI8hhXhGM0tBm9IW84hDEP8BZkymVIrpmKf4PtExMokmSgISwhTUT4U85jLSygidXB6Ii4iJEMkDeEcj4lzcHgHO18W5jHTPzYrFyf/28BIncYzhuIcknDJh+QE+egjCMfP4lSSwcvOz7pLlJgh6QuahqzHRFEN6zpxnSaWbQw1oZEGMNXYmelvqM/U7YdWZ7a6TtU2UIK7DmWmHuuS1pOywGUbM5XJ5cTFnAxlKklUfvA4h8ybqNVdUTuOtcgx17L2dnwd8NMn7hJY8NPA1wHfeMouuVx6lEsmDHVXx3BMNc+YPLZxSaMoFRPFvHk0M8BYTxT9UY1a0kCRFqZSZq4NJ4het2QP1AnpE9VLdilqx2zS/J2uY2EhbP5ZnDjSR8OOhl6wyLEzrpZLcrLwZbqoDyQix45WpZ2sfAx1R7U6TchH8vowyIfFy044+iSD066G4a5aN4SsKj+uqAs7b+lKGpZVuEoGO1DsWydjLWyohslZqLlvaHRIp9PcfoOpljmNmpdbBK4DPlCmeX/BXM5UsQ0YS3Msy2VyXzgHU41MIofIG6n2p+B0neMrgO8LeeN6+Fbg+4CvAL558y5yjdgXluorm+kj3EI75EOcc0kci6m7qBmnO7aV1JEaw1vdbmOpk6WFHckzIM1DTkqNSUsdUI9Vl3+4HGWujfRMOTOxBNEbDqQucEDGrqyygMEs5AA8qt0rzEXEyaIEjz2lbZyHCDPM0iZKq+6yqy0E+VB4SQlHn2e0nsjRJhnK9cBeCfVT75uon/1yBvMGG6XRFzPGtqQxlqc3bqqcCIykYRnDar+B9mpVyDyD+dlQ923rkq2CW57p2YWJRa7LT7RcSAa/CgvgCkCZ5kCGR56rZMJ1J/FV/D+BrwA+cdb5BhZ8Avha4JtPJByJTE4insEulX1ZvaAvc6PBNiYKIJVDgMa8EjtPHeRyd4CkDrGgY21BFfNQhpNdLfZhndlGqrfyI778BmI2UyEWrpNFlpckeDBdcCWNA+Uz4RCOor7q4coek+EfLHuM9V3MjMSSD+4NNaWonoTpwJcKLxHhOIlkoJ4aLM9Q7gZlLOW3qycUyWn5TazTxAoY+3qrkBjrOuHPZuyMkGslDasiuDzD9pVbwNIyyVHH4vlX8YwbQSIvyUjPXqmeIKaGwgHiE3MpiTpuQ5ZHb2bfjqXw+2/mvF9qLH2Y61HaBz+giyNgNA/oh2K05GvcE0kd8j1N8a2Ip4PHm/B7nj2ug2V3mdCn+nTYW8T5YiaHeri2jCiLHMmcFKiGodSfaqlA7r6JDPxUf0nvWC8vC3WQeFIhFvxuLXORI3GLo+dtkdtZon3n+uhz3V0yJFTvWeYx192lEqAEX/GXhHw8cMLRJxmc7lhK1LTDGkWWQ1veWStp2PdNmGEMa1TDLvlLoztzaKY+VtJwf61u2dh1aFTb4mqyvA0MNKWqeX+ZIObSgCMtD3VazVagCU6EjURbzyAcAL6z7B64DibgO4H3nrILX6+FdMrbnsIqRvNy5kTfzbysnSzHclfyGFMjkDn3DUL4OocmzLWlVGn38R3eUtnRFvNIteYhOsFA9lt+Ixn+naEdI8lL9nXZC492zDX/uKQKLf9grUVeqGG3i6RRcoa6A1FYXaq7jqmGxctGPh4m4bA8o0MyJOHSC2sp7dKGQdglfwnUkoztkoZdjsQ2ZJUZj5VtlSTDadsbLs+wmVuohlA01YfXf7zbApn3eRaQaFCZDTNNTKkEbRyKweAZh5e5hJ5JhTwTbcQjAMDXAm/czBm/1HgD+FrgveWv0jdCzPCCReE4lvAIdd1RLFMqPEPYhnydYir7zqXCXW2eb49kL1gqH8lqMvMYjaegQztyuU+tHXU5R6r3tYKHkLmZ5A2x/UzsLmqKcPSWq4KH+qSHct9c1bSDl+rSj+YU5ppUKQqSG92iYMnHw2MeD4dwuBarwzOscW1Zyj7PWHpQfZFT6QqSw4RDvCFuHEZrq6UsI5VniqMYBmsbim24naCWrX5Do+uwQcm47anWQibExVqIA0UyZwpZZwkXNN8JBcmUZlcLzzIn4QkA4LuvdYqBn8XSk09OpLNsLcSfMpdwUVle0IsqV2V1V5YzMdep/iaYDBVhHs8HqcwVylIOdQ5TLjafqTuk7Yko8gGKKcnk4pS0kKGJxA82/ENNOOYGjRAyYckHix8HUwN/mmym2WCm2UD9dVxfPVJ6T1/24A58wLLHvScc1+cZoBgCrJlJK2Yo78loqIZkWt5wCaD9ykmfZww1cbFUw3pPrLDhMgbVS/2us2zDduNdoBoLJnOry0QgGmyqp6SpWBTQnHhVdmHOweLHXE8x2/Fn6fE6cE3MwJ8FfvMpu4hJEOMnkYk7Wu4pYnS5XleFfMy12iE5OzMehObeYLjSFoiCm70lEwLUIznVCYsOf1LP9yx1yBQx06Gtn2WsicLcZh7s0rqsRY5n5VXbC4+vKDYz01sz0gCJ+VCyR8dphXqZTZ+3+lBpSDbz3uFeEo5rkgx4z+LoUg2x3P0Qjc7bran9jqvKGeplS9IYqQyLGaNps7L9iWacjqTR6kOXq1lu0eEZz+2RTkFuVJ4m5L1WUTgksl2YR6LnLVY4UB53DqX+Y6kfp88LS/k/VioJXB9H4I8Bv/l0IWG5FlPxpyyE4FAcJRdEKeRtCxknEs+xA56VAqlwF9lFghLwgkyITHpzvRR7aZ/OczlHBWs+FY8RsH1NJHKkWvawgsdE9v5APGBHm9g/ws8M/JLLnvZiqnFVHiQU4bCaBy9HOgVus/Wz8CzK/Qmz7JA56TebeV9wnwjHqTwDdJk7ZrJlIJdZZleWLZ7hShrWh9IK12j5TSzVYNcMH4JpkKIa9gStIIETl5axWTZz16jGguXmlBgL1J8KZZ4x1z92qbCT5UAkI5PCgbO0DZQ6AzeI8/pTLp9Yu2UeONZelR29Hyv8g0dOMsyDfS4obOYFmo1UGpDMcvYIh1jQPtwKFf+QqqwBTkQ7mItMlBZNQgw/0w5hJ4peWAqifDGSoxiMcI7JYx5zKQN66mDmwc4jOVMrePT7U9J8+WzmXcY9IByn8oyWmTzJQLo/K2aM5tcPC131mLgMQ1wnqQ4QYd3FPRH3B0ps7HyXo6QNylCiRr5YiFgqDOOKpgNOzOYhyfKMmf4RW+oXznG2P+WjwIdu7IwDAPAh4KPA552yi5i9mZ6tRY2Yi6a1q3UOu2T3vxpmV1Tzsdw7z9mxwmDaMXtLdhCkbSLH6hFR29EFQ33vJKp2qMnHSLRgT32+KzmyZG7h5ruBpcpTsyO2weEdVvDgpRU8uDMt31pVO+4787i7hONUniEJa1ZbJMMaRZdkpLaeMXr0QnlDlJekL2Yo+rLMcSpKI9VLdQqWbcCkVXd1ltzbnN/ypLi87S6An9WEeSz6xJHkjZne+J8M25jJF8vURHgM6KnljOb9zps510CF3wn8l55t60OeQUXhkDdW9mYkHEqsgGIhz8gKPgMSSRrHYk7YxrxYyJTCY5jpF8hBwMUSlZSq+iJHroupHeWhf6YywnUGYDL8Q5Yot+3oLWdDLCRffeRDciwFYXqhNI9cax6WcbLIweRDEY6HqnncLcLRmhE6PMNdinUc6mXHOioHitjLU6nGqnphNY9Ugjz2Zal0FG4JCxur3hNQh7T6syV49vvTPaJt1R1hG8eaPQjnuCqEYzEAh8ZnB5V7hWci0IMOSEc9Dx+7mdMNVDi7V8W2sRqxLwTi0HCj2AGTgF1hHqxn7MpW8fvchelYniWEUYktFzM5GEvPdk5ZymyWKIewljJTGuVAM9ELRXSUEjNQWsJ1c1lKrHeLjsjy2KApblrRDnEG5a6TRREO6W3QCd6I5gGzywvEXRjhQINqnM0zkvmdJGm4y1ZAqArnbOkcW0I0mNbw0v25xn6Vaixw6cXGa6QqbxG4u8M2UIsZ8mOV4kAcYgaeAof644bqQ4cgjQT11CBH3A4R/L/nBs41oCG9+nnARzfvpeZxda2PxpnyrKT3wLNyF+yInYh4IKNuechZbpPdXbIKYraXtimRQzGD1Wdxi46o06cdoOkl11MQ9y2TD5FDJGc0ioV1ptiXZu0us7dU4R0c0zpSC3OdyNTn0p92eklmqXrVZR6qV18sXiThaFm7Ds+QhEs1Vh/E7SO4Crp0SYaSNzaGa7Q4x2h4xs4ct+M9sUbd8oxO325BS+ewXd353R22oYSNXISNK+NMEVKS6xlhMuKnrB67Tycb8ZMAgH8/IkZvBwfg3wf+78BPbr4v5NqJnQCNkJ2nh8/0CMvDQ4wlO1bkJ8/Qcun3N3z2Z2KorX5ruaBlBa9j4bgqmdWVxIJ6wpkay6HWqEYK9WB/mQR/qHCQXS1pWDmEeQyHdzDLmWufS6bMoQyYVA8nGKljY3/eZc3jxRAO97Y/iWco+wdDMmCs8tmqxugRhRbV6Oe4SslGqmElhGR60ua4vLizdC+EyzncfGnhHYE8mlht42h+StKYCimRt1Ey/b8UajfKkj7jNv6Rkvjo3XgEeXjIJGz8CPAFp++OOnR0otjDK0ovhmoJCBXBQ0jGUPwpy3JPA2m5X2TWGm/gpG8AbC9bcwW6T96SPnUpsI/mPMVJC91Klrlo7i6FgighZKpzWvTiWFMN5VWxL7NYCsJqhzCPTIOhRT5AJVvzxh3UPJ4r4Wg9XnSoBq9uf9S25lnpGanc1WdQjRshGS2q4f5aVEPRrwVKn0BjRmjNIErM7FxKeyHUphcOoRqWc0hglyojs4Z6eJUfjM7JkE2dWUDhFwAAfhT4yM2cdMDBR4AfBd5TensLlLEUqBkfxnjIbyK+K8NsoIEns9BAy+XeuQucI1En8P2u5ooO+AY5g22oHDkoTy+DVwNb6LSBdgj5UIRjJpLRyRnI1TJRvtU5hIigVjta4R2sfKR6dMl1ac027pTu0g63528Jz4NwnMQzQCPbLl07t0o1xGyvOlDgUQ2rbXRcKlv0DBuokQzhSHXCPVkLHmTJG5SrbOMkrnBHiIULDhS9MmlZziRd2K1TLW+o2VOg+NZ2fLAkvgv4vvPPNbCC7wO+C3gPAOCDwK/YvGOHRvNgyJ7IIcsBuCJ9XnJSWR5K+oLqvCvhdQbbyfSC8zhH616TNthVFjzgzZZW85i65GOq01b/GE3+5NEOeBEeVjqaG2KSIrKKcyjyYTs/NdJuf94287jdUe1Ovu5YkYS72qcag0mfSjVcVSOthYh2QkfHDSTjDFVjI1pso3OZlLDRGo4bj34qcblx8G2vFA6WNCaaAtTTqntvs/dETVKop4l5QyM/B/jlJf23nuNDxkuIDPwt4DcBAH458DnAT2/YZajvHXvFlTdN/ZQqxvZpokmJvSrKw/JidY58+pi0t4yqihNq2VrdApltmHPY3WcqzNakRT4Gj3Zw+mjyOUZkosiP5OkcinYIR3Fphwyqls7RYmbSq/JUyT3mTvW3NxfdCuFoGZvkpVsMA/WYkMRtUA0mHLwcPALRcq+4NXSiNFjbUG1WxHwVamhyJ2+ROuDtqOqXzM6jSaJh/QIxbfjJDT+b1dakucAOwtS+cP379qdK4tuAb7rhPghofBPwrwK/FgDwU2ujdOMldu9Ql3bYITfU5GOqpy+Uml+4b4WJQushG42bpfUsvpFztIhIH8p2DO1NdilUclmyTZlNuqWCCMkQ8uESjlNpx2zSLdrh2gILO6urjtre59txw4TjBqmGIhmc3kg1htqotwjH2CAcaYNLZfDylV7C6VRTjZaSkerO6fMPyyHgDTg7/iznQJsmoy7mgsl4v+QtIVMkF3+5ywZwHA0FyRS6Aa+v3OGndKlMj8W2Eoao+q8D3wa8evOdEajwKvBtwBcCbwIA/AryZ1mkxvUd6kvfuTfZxCptQykci0UUkrHsKGYvl2LPGbl9L7gl1V4dRuKSDzRWYfaycHvepR3cKi4gNEJypP8TMUIuqTjiXI+WqRxCqWJy6VW+ohdS20m0A/XZuX2lDITqLvf5qtXt5+FmCMcWnsGrJ1ENtdqhGq0JYvAIh0sImDFYGtEnGS7VsE4TSzX6PxdMaZM3wlJdRuV3uIjiK3bA9Z9RePmcZ8lsRIvOL1NCdmcoeiHXbqLlEkGWaQmS0GfTz4JfCXygpL8F+B/KdBa4PUzA/wB8C/DvAgC+C/gi4L/xSspFH820oO50e4/3+QfqgeeOTLZnKMPp+XMOlzqs/vhkLQtBnXCXNtFiHi0rmExacQtLO2QeGOvCQkHkZ8nHUJMPGQaKrChS0iIcNid583yLdqS6t8+jHTB7tfLPwHUJx/OkGpZkJLrAy5LdE0pRkNFgCcGuO7/03SWnxmpw4+3ZdUgGaHzwKhOI1ghbxRZeIgeVJYuB6F7T24bwjA7VcCdHgTvGhGQM9fXd1f77Jb3cS5meb1BmBMYl8L5S+GPAB4Afu7VuCTB+DPgA8GXAu4Ed8D7g5wDP6jJDPWnI5ZYE/9TzCd/pfJu7d4Eaja7VSfX3wYbb7yJQe9xl9m4le2cxLchmFe3lloS6eTsznjsjyb05UMBHqzDKPW7zW84XoSbyFJHKBYV3idWlZw0s1XpJpr3kQsD08zVpB8wq1vK343zCcatUg9PKDFjawbZ8rJcu7WhNE9uJxUaSodpmT8fmd6DGhyUElnasEpEzCIq65+WOtXMHez1vFbkmFipWw7INPpEF6qKoobJYl0yxYLl+AGXZE/U8JYLHcrhfAHwz8E4AwGeA9wM/APzMLfZN4GfxM8APAO8Hfh3wVuCdwAeBrwA+DKAeAMwz9mW5DIM9pYV2KArSkj0EPAgV50i1hQPt+xzo+yqfWGUbfRZiE6o3+on+agvK1izzFesHcumlWmYnXIm6692lsk1CNWSKSPWFngu9QF1eqIY0SeqZ63x7XUBHvFO04xzCcUtUQ1Zbv462YQmHtRyD2WqdIP2fq1u4SoalFO5zT6czFTpsYztpOINeuC0BkQlJo75LXRXnNsA+lKm+8VDffqBGwlwaGQDiKJF/B0V5LVZyEk0BMlOgfstA5g7hPe8C3gd8VinwHcAHgJ+oH7JfAd64uc4JcH8+A34C+ADwCvBvAAPw+cD7gPcCH/eePZhqXNBy4RwXhn/s6WeDutRssEDdFGrcZpLHlvzb0zkspVCJ2StzI4QDjdUtiY2cQ8BWX0gGz2NDOcFEJgP15MkzMD9pTN2lkBJ5rWnBQDMJO3FmKsZt5pkn1+TD7XZ7+hbPjXacRjiuSTVAFw+eQeJVnrUt4diibbR+bvRGX73oeG1doUJNLslL235ogemF7fncSNgyrZrd/IFGub0t7cWa6xzhHOr63iztcH0lc/d+k6uTPZKxLN1pggfY8rHIZZAsovcz2jqZ5Qz8S8DvBT4b+GwAwPcB3wP8IPCpup3ff/qnMAMdcH9m4FPADwJvBb4A+KeBzwUG4P3A1wD/VUPbEGJxWdKX9XJf0vuG/sGzx+jNGwo8kpMZ27hpzuHePi696HhV5DaR+26uK7dpWdoE3xH9Mm5tLuwDmzwqzGYeY9rBs7ccZfQIhz2cXVpKMZv281TJm3ivZHZUw2am2rjbbT+4bOOWaMdWwnEq1eB0q+ut3bK/DuEYTE6qb2ZX52hpFav5dprocBrb+NTokD6YQ7SWoIS6FtvHAd8zzKAXsMeR7z25OWc6QXVZs9lr2Hz6/QZnQzhc8NHnMpUsxGIZ/RJ7ITxJGjnSpM+sayzLVD4fuSvfQd/R2zHyqbFfA3wt8KbCNn4A+CDwg8A/BK7q1r7net0SUFD9eQX8Q+AHgQ8CA/BLgM8GDsD/FdgB3wFc1G6UsdY2eMm0w+Zf1CrIjmQPfsjhuatDx9mQLLg+d2da0GftW9KtH7w06uXGhM10l1smPTt/JjNRCO1wDzSbCU0d15rzqc6HyYc3DKyvhGmHSzhA85XqkI5RcA3KjdOOdcKxkWqgvhk4sUo4pIutqpGM/e6TjA7VcJfuYwdX2yEWyax2fqdCXe8O21CXYDvJ4GOlRnrwlmjoHNKwoUE1mGXzvqe21p3RYG4tNYqGwjNAt2uiOdfOEUuz5X36sf6Tp+XvV46kc6i/g1r4yh8Afg3wduBtAICPAz8AfAj4KPAqzQvS7MANItXpBLwKfBT4EPA24POBdwH/CPBp4A8B3wH8fmAgijDWpOHxGsmwzheph1UT1+HSmjF4kCdiHufNLco4qRCEDu3o5MBbdjiHWvYT/cxWbWdMg+6kzRMInwtPaJye6Y5u0ZGWmwZmuApsx6oZVfK5ATJUWCrbApkAFf/ghp1HO3qEozOUU3tVdZxlGDaRvGIbSUZqO1NaThBLFCxT6Ttl+iSj03WtCcLSCHu9W2TiNpiHcIK5seSfkAyUPkGjDC/dwSDLVvNg5rs+2+B7XrQNmPaw+2PnUYfBIxbqq4LyT2/Hom28GfgPgC8DRuARAOBV4IeBHwJ+HHi1EBcWsf/e6Vct0MHfMzPJEXgV+HHgrcB7gAvgLcDbgEvg3wLeCnw98BpFb0gMR0ftWJaPTEmhLIpquG+42FlFIAO1dVNvuWvgMYD+T0YmbjpuY5VwbMy0q5Z22PlBILOTu8mdqRT5QJt8LMuR0nO9r/AGtOdAmy9VwZzgXOQZd3d7dgI7P3OmOrRbgzpia6A2CcdGtuGmW5yjwzbsryVsWMLBJfvCg6tntO55twbULVfdYgeH6gSGva7qYsO7qJaX5HrT2VBsAJTe8st0yht3RE1QbKfZFqK+XVtsQxqw3M+jaZUc2n6OaYnPGD2S8Yj+ZkW4hf37lTeACXgb8JuAf6U+hSvgJ4EBeB14BDwqhGMuEenfW/6PNJGPNnASxCSMwPcCj+iCDoX8vQ4MwE8Cv7DstTDCrwBeAf4c8GlgBF4hxqCYxK7OV64TFXBqCcew9lYL6huB73qVic23DIhAbOcN16EaLZJxEuFopTvVdsqo2hYoy6qWqudb5kAmHCYT3A9MPqy9VzWgVJKNbqG6QnjGQCUl3EcqQb1j8hKdVdRpeAMSa5scwtEau3ZT8tIt+8EXT6WTuWYqPZh8W6AlYHSYREel6LeQz9oOPu4Ne/3slUu0lWu2WzsXeAty3fhsKlebUp126QLqPrSFLWMbynnxOdqhApNGg3OownLTot6UCrGQtAwGRSwu6v9+k6VIF08AAE+AqRSW5QRcAu8A/i/A200zPgZ8DPg0cAVcAq+UCeJpoR2/AfjflPnChsSqHnjJ4U4sqb61fwPwO8rqo9Lbl8AV8OlyOd5VV/uvAF8I/B+BT9a8gZnEYwDA43qrCv7YNZb8U/EcW6QOTrvTgk0rM8zDyZKPPr1wnSZbqEbH8J9EMuzuq6fZ4SK50SSYvuUBxmVOtR1KHZlNjjojbrBQCnWgwXAO1LSjDzX5g05cmSF4adVydDdpwqEO3NlkrYJrdLn3beLUX0fhsIKHmn36DKNPPlqjSqCY4Ko9ULQjmRpg5hF081uFW0dPZlUyE62qi4WaLvDurZ91wbjxHzCZfGrcVE64vc2Nd5kH6GF3Km+gzOWb6PLt8xl4Rp8W5WjQfaEaipQsibcBX+3dShn4BLADngLvAJ4C7yqHe0xfCvo84LWieQjnmIwx4DcCWpPmfUdrSlG3+ZIe6UZeTPibAQBvMzb+ovT/DviEN+G+Hfh64PcBny7sYfQohaUXS/qSBAz33Te1dCcomFaxAVDGgMuotKUCnHnGD9veRlEJbltnuLbS/fLuMnePuHGKbt1Tp5qt3JgnB3OsXG+dqYzIFaqRcz1gWpOnPcHWAFNL3iTVcod0rI/atOMNLaT2qt3LnnnHtPQvkp1Ztl/gs9mDm7kRrUtl74e0bdD30bnMtlUqrSYs23I3kegTeHyOp14g7mGVdpedU4PXCcteA52gGldy9x4oNmU09GJXeACzkENZcv5UBI9fBPzGRmtfAx4DGXgn8Cng3cBTqvZY5u7HwAUwA09LI6fCfsayXP7i/FBO5FDrNPzMNHmPUHayULMPjw23b9UlsDlqcPJYslXJtZ7rkLoZ2NFyXy7WkhA9aSo2fix7PSqrKB8+YS/GI+Ax8E4gA4+B14C3eKf5+4FvAj5UJA0lVOyBoSxbAoYK1BjLLqmOPLOPT+780zLAbrG+Db4O2+jkoJFQSzexeoJuybNPtpPfavN2rFqWLSYM9cSrZkV3/hSCkunt2Q6UOZCEWvIpSIdw2q6q3pBNO85ysWWTnThQd4cqs9EUcSUdZcLdag/ktr913FXY0e8OX6uYWX+bqjZ56VaZ60DVY4catg101XtDe2vn0ti0HJQT7lmoBJfPdT+nRhis/CZvuQRnJOBZMXtTsXnMOR4D/yjw69pNPZQI00vgbeU9FyErI/AE+GLgbaXmNzf+HUY+dZpJAlH+lyU9AoeyXFbVhCtL9aQ1lkOMZXWiYiixtAuWqW2k2NuxJPg68gyoLvpSUjpWvF18myshsxUkPtRmfunPx0VGGsvnMV4pr5YsbrIWfiPwrcA/MKxCCRiXQC6xGlbAaHlMlECbzL0j4EGubAAaxdAlBKt2V7beiPfENeTopvurnWpXz5pjYLe8hpPXmt3HRiuzOkmy1bDFhtJyGR5qCm1BCsucbw0Bb0J3BK5u2vXblNqr1hikxhLbLE3/pypxm91pQKabWeWftOSnYRmgI+WgcU+CrgRXtX3g3hRyffqpHkatoWYvQeuCziZnKEt3r1a17hImLSfCiWxOCoX5SY7covJCyly/zsqcg22hsJCJlIkJ+CzgS7o9/6jQiEvgnUU+WXZ/CzABbwUS8BbgpwzjsZxDXC2Wc3BCTaPL90J2ZZXTqBO7sjyQEJoLZ1qwpBOt7kvU7bFxcZdIF04fadLkhCUZwieSMeRi2tnGfy7warn3x5oovBW4LJTuUfeq/Trg24Gfod0Vp+kzjF0Ze4vcsqtP0J3lUI9e6XnehEbaXbYsMa92gjM6OSqxuuy0/6RVt87Wadr2b/9JtUxTMqVnrwFb+kFNbrPJV3MvQ5XhhCrvTpUti983BGgk+KRQD1rb7F3r2Lat/dM4z070c9x6OhTETXCxM6DGX/IyWze5pJWewddjLlNPbrSzPz42buqs8kmpYaQ6s0U1Wmm+l2TpFuBVywtbl7gDe2+rHmDtcU8XKJcEW27WFcTYH4AEXJEa8d61Vi2vrvyPwLsBAJe1M0W4xSvA1wNfCczAk+JNmLzVp2V1ptVs2p898WP57SitZud9Y2yjfOIdpA3YEXJoXOJEDEMZ3RbPOBYXyVB8Ro/Iri/akl39BuB312+CsGPlEfBu4AJ4WxFvOvgS4DvLu7IDcFH6Rw6ajIyRTNo9WXUjyOjlWbs1fautLdtmOUR/tV/ATasjtlbVuajz6q/2a2s1Rp1FS71oqR2rPzQOdAbU5M/TnZqTeTZTDEDxA9TpLTm2Hltna6/OIQTnvBa7vZgyUZJ2O7dTzO6l0jCrqm2t898ypOzoHLwcXuZynyt/ioz7VDtTZtPa5OXkdofbTdnrgeSt8pBVCVDCXboJRR1a19GmVcKugsgZZ1q4cxyfDl/E5ZSHolSxt0Imo12dv6flBfDL2y0RvAW4AN4FvAZ8FvBpog5jeVFlAr4aAPB2YAbeWksdb22LHPtSwxKUmr3Evp5YWzPsvjGDLzzjqqQXtnEBoKTtJTvUF92a24GKPSpcRCUG4FGJU3HlDVdaAPCfAL+vZD4q4SzL6tuAS+Bd5Tscq3gv8N+W0BnrFhnpXFQ+PCXDzoGoB6o7xauSS5nZZFqjaxN2ZlOb5kZh9xBq2U+otF1dzVF1usvW7M2TdmeTuke2+186R+QyFpzvzsC5zldpLiM75jqtKII6tFvMor91tZhPOOw8bvmBTdilSqhqlb3pFOvAbs11d3OOrMqvld8aQ+IHkbS7RLFey75DvUzGFWd/2aTtUp1aXusrtytQd5c7KFvXt8MMpB8Uk7DpFi9x64TRHm3aPWtOqHubsVyjka4XTzc78sKkokw8Bv6p7tG5GUsYwTuBT5IfZ/m9qawC+MPAu+ut/V/2Qjrs1CnpPaXtbw88A/bAVU0+UHIAXBTmcSicQ67RknMALtuEY7kFDpQeTFrpHCq+sv8bgT8M/O+BdzXYyfKiyljCeFdvHAC/HPh+4EnRSLLnH+lwCx7hMh5SPTj7s3n20tlbuokl3WISnX3d1c6y1VSVbuXYzO0n7p5O62fJhHvvtJbZpDs/dTqt/FZCsGoN7eTGEzsbi04xLq+Wtox7aDcHWz5tjvokXSaxuhdndspvMSFbpgZQ5/LFy+VpUtLMEoY6R4TWkXJGMnj8UgMvRbpgMymVc77MsLleJmr8dThHpsN1MjnHHUAu81AnAu/s3K1q09Qow11nM21j7Jla2JnL3ni8KqRQyVcStTMCP2/toFzhCLwNeL0sl9qW52Z5CQXAZwFPiE8s+bmwirGEr+66iQw8I5Ikq625cl/K7EvPcFr1lT01WS5UQ6UV82DDfCxlUvGJXJb8oTieWomJuMhlufuW3/KpjDfTayxzCR9Z6N2+vDG7cUoB8B7gI42YVpQcGA7dJxnY0IDOuGXLCuITnGlXXdvcKtOqsNUYm7arbs5qMfe4nfZzn8hSjX/LyJlwMJtXS8v1M4mR2dRmj4g63erJDloM1c7erWLuptVqN3IOi9M+/NWBNTm8ydZpc3Lj0MrKKkPLN3CufyiTNcsS7k+exWVVeABvZZvX0SfcPkG9O7zyqsdS40zVWXMC3hSmRp7KVDtKjjuMUiPRWkpiqDd1uIibbzNVfq5dVGfM4DCnmckjJu2XaWvZ9I7ysYeNWL56+ZZS5zJnLbbwUVl+C/AY+HeA/4JmqFfqCetNJfHmzU9gS8IGbchPAkhR30SyXNwo+/qMDiW/NbZTHShqf8fafttAh86ytfobgG8GvgV4W6PYHngLkNYiRhXeXNQpHtVD46xlEKq5y70fXfAo5UmMN1lD62ZuyWeyYqtC49Cqna10K6eT379JO82zVoCX6tbYQjj6KohVE1dX3R+3055F6xK4+avda8lBywooc3MS7F7rH/6yFrRf3t2aTT15w/3WQqbd7W1s7yXLNvjutemB0txmnkSG7pJPn62XmMZME2s2S0U4XMPMPaAS0gmqh91MUNclL0cNQZt2yYdanU2OdIJ7gmife/9AMCeououRG6ude5gb/wj4PFNnHwl4DLxRPmp+oMlroNV/FfjWovYPdTF3ohzL10EW9e4KyKTkXZVEh21IgQMtczn0vqT39UsrR2IhqdCOfaER+/q9lc5PCggvmWh1KhRhMrxErcqHOr4V+Argr5h8WR3Ln7GdOgt9HvAUeFbPBoJcp+X2sWPS7sh8wlZoLU1rubpJdNx+PZ3jwpyp2+ZOTn9TvxPQPllO9H/2JrLL7T9bPlOmOqhNuy1vnRdM+gzw4FR92+cWLlPp7KtyNrlU3KPeank0blRVIDdoh1rKDZbKKlMKCbZY0uJJGehAnNO6pXkkjeUocx0QwA9DuZ4xWz+YRKZVUEJdeJhVdTqrm+D1/xbO0UnIcqKl2qq4iLvsZ7ba2QIbhs7cyld8AH7+WrUWF8AFcAmAvuslP35D9THlXzQmqSPVwJse18VeWZvaciEZY9l0qNUO1Q9MOKQDOSGEY1mdGrQDa4Off3KnzCV4wm5Slb/SruoRcFkux6n4+cCHzJyDepU7xA6tFlwD4A6/Tuay3M4qWld5SwLeSfVPs7M1t1f7Z+0mWr+WyOH6R3LXt6JIhs13w89n0xIrTLp3K0y61Y2rI81iy/i8TvkFZxIOe+zVnC1Q9yrnWzKR6GoNdbqzZAz6OP//oydTzO1cljSY90iOSqvlUKdRz5swsyTqfO4ou6p6khuvzs6e19kUZAsX2ZjfWjIXyXXn9xNuy1X+lqlQEu9sF+5giahYIi7HelTz7wPAHngv8NcbU8/yuzA7ym8ok11nd5T+nErQg+QfiXwsS45Skk64rPP5Sk1lcpHhOtOXQCW/NdrFE7rlp3b/YuA7gQ8YXiIllxvtonCXM/A24BMl7Q42hdUx5prwVkLE1xvUKjoHbWW2crZvbRXY2MhszrQ12vv+lL6XxCUfLtVoiR/2CzquQNJZ5jrdOlm3J1cvgQtr8s5jGArV7XZTvAG1ZbWb+jXLWamnB1CdraGG+vLI3diB6kemFyof5jLz/A5q2HYOlOpoxNX5FBuW3IHqTNVJucU6o6oz5txj9ROoW95JbCymQm7dY7VWN2I5/ctt71JaHMqnIIbaorMJAbAH/jngu6hMIu1tprvApmVAqjvCTUym5IJUalswFJUCRZ4RzCX/Ed1ricJfUI/huZyUGts2wYRDsXNOLxhptvku4L3A3ygv60oZuUn5sxyHszjHW4DPlAjf6wwkd5UnvWwoRSfhWuVWsX6ZfguxedPGkqu9sbpsWWI2B9hm3V1BokU1WuTDUpA+ZbHkY/VnT992Qv9auAXsIDkJfaZywr3Wpwj9u04K2JJu49g0crqzXMbTUKdnymmRj0zTeqYcld8axCMtZe5OVCZ1l6An3Y3PcKgTaukmQIezm/pj67ySNpOvbIsHbKEpJyVQiyIL1Gqn8Ra5GKpXtpW3YOogdcrVWZohlpKnDyYfqMuDBu1MtfHu8JY7qlN2zHW1KCOcqQmfjtxZe9OkVOoczNV3l7y6KzuqMeMGIMOUPNTXNNXnBZJkzsArwK68SbR95Ciofe0clW864aZ5+LntbGW6OLuk20iVaI1qm279llvvVMLBIscW3tDyvLT2lUOrNmST7vxQd4vqKFWs09UbrxfDkowWbsal0kdu3JNqxuTCson7SPI7msEC5T0RA6PCMrgBnMOFW1d3phfqeEqdy8OTpFPJUU2VZzUu1uEcdlLuT9+qb1U/98kBY/sM0qnEblUGYJWCYK3wxhoSXeVcN2Oj5diVT4WegVxCOEFf7kJjYv1ngcfA/6e0Td0IPOoYY31erjnJZNsSjUZVAKWMy3VAq6zWDHVhe4/A4x8w5WG4hbtEnf4XgCd1I+XE+Vrv62txBt4NfJqiWPrgXlWdr8zAanp7ZqfwKsNwazgbbiX2Atl0bi/dRGe6tkZd5c/e6nVohyIfW2roHLe1tKevusV2e+ua3si17uMWCUeuZwTJUbMV2uc51/OpHZHuUu5kAacz5ajwCzRIhnAI9ctEIPg3m7SiFMqTwnNQh3agm3aXbgIeIVWG5AZhrbiyhZ3C21c3bnIpxVCPTLkuglx341vKNx7Ow1yWuY6HUInvAv5F4APeJtRjHo0LZ/tZrQ71sFd7oYxw3qQyMw1C1Ak7DleJsl1lqNnDzU/AB4AvAr7LaxK3RK7C2XgMPAY+aQy5gJ+CFM+wp7Ca3r5py6rbk27hG4R77Wx6I9vopC3VcOlFf2mtfitny1aXZLg5ruyx/YfuXtzb3G+rV+qmcALh4NtJTWGqjC0p0wHvKOjUwMXsc9i8weLm+l2AoZEjj2iz8ZJwYZWvxIyhljRcksGUYklwfNxA6c4P2whHZx7v84/nA9euuJlu/k3lwOgEQ/mQNoj1Sh/uymg5A0/LLHMs/5xiJwLGBHxxCR21ZfpztK3Qlt+YZvCN37pY6v7lAdZK845cAGYYu4klvfQVaqeVKrP8jqXzn57rHRtLCIj0eSKqOpdRxIdeZRs3m9PJfyH3O9YGmzuM3WU26c6PDfBU55xEODjdYgwdGWOjpJG9VbVsnR1PJi6Z6BRrTR22hv6l7GOFcOT2nHJGyVYZbq7ctDORA8ZcW2XlpEDX1grDkJs/m61SPhOZYJJhJQ3LMDpsQ6L6hVdlmgeHOo1tzAONHNsPbkKlnz9OOnq/8Ha+0tqkrCCTjwy84sV/bMRc//XrVD6OzuBDfzvwjwPf1tjamgha6U6B1Chmy9iSahjbQyRTErTJplcLdDZ9G/BPAN/eLolyi0315Tjvmg7ACLxRDuGSjM5lwrZN/dn8JOrwoniGPbodb322kRs57g+esGEZxsJKO18F3cg5OnJFJ6dFNVqEw+UcLv9AvbQko3Ndtly765S8AZeKTCLZzD7uckHnQUdWeWzxjMBSB/MMRTuYTCzLga7BUJhENjTCyhhKwJCtqf7fJvsfTsuj8FjmOP4+h6t5qDQzjxb/QCOxuuQE2jkW9mreBZzKmdzyraHIo+Jscibzy2LkWOSwWDJ/LvADwJcBf9Ur5s7RqgC3Vhqfaat7KXNd0j3ogtYQymaTpSZSsuXAUnX2x+3SS0uPuWVAN+mujuY7j3AkYi3Ke8JlOtd3O+7avbZ9Btg4bjtLN2EZBtYEgJZgMJVqhYLMpkA/7VITd6vlHJZhTKbx26mGmgpUL3XSq0v3Up6K1HlucHP6DyXuvNCyhW6C7WjnEd9aaLHKafPSTdgy/WJql4XBje0K3aVLNSzzcH+o09xpuVaJ1NVxr6C7+tzwYmdVRS/EhMjqCLwF+GeAN51V/6vAZ4DXgM8AT4Ar4ECavIsMfDnwPpPplnQzmXajcA42/IqFKIICjyjIsZhb5LoDVcOYW6jygynZ4gqrmV8OvK87ehOwB/bABfAYeCvwZuCt577k/DrwvcCrJJOoAeNSkOePO3I7u3aLTdpMA1IxCddSdn5ze7VFO1zGAODY2OqKHK5o0Sq2pTHCJLZwjlanqa5TCXfVXp3+FWytqpx1hSNvGK/Zm3rUKh/V3oHJnANPhe4RZapiVYPTqI9ulzM5TZTqMDRyUvGJ7OpK1DTqChhnMw+Vg5pVKP2De0BWbbegkeikVyEX8dQZdmPhs2dtNQJbo1Eu31RfzYmG9JuvoQrKlCEKx7FMZ/1T+2zglxnaAe+27/d89m4EuQtg9k2l2e5dzMVk6zIOJ1MA9bFUG/oUIVMlMOkFXw78TQDd10b4hhKFQyb0M7AD3gx8qrDG/hwI04F2TJ7NDDbu+PxvZzft2rOW/VNGdDY5HQN8Es+wyw5vyGWktWQMN8etVi1ta91z4RNv/dBNw1ttXR11KVtYLaMnT3fQc+ZqunW/tZiHtFLdfv3Wsx1NNNlxWuayoc7heVZRCm62anOud8kN0rBR0lAko885xvLlR8mZTXqiHJg0vFWsJVS6lXNN9MfodbaqMnZYbq8E5UKcHS6KErSRC9uYN4RxAPjzwL8F/HngS4H3t1u7saPULbB0wrF9Wa0i4lYuW49t90Qm9jZ4dfaHVmtrAr4U+Aull/p7iaPzSGZjMnttx1iu4/ZRtMDOkG6D+5Xc+NYzYE88e+lWomX5+ibT/iYaXa6F5pxTacfGfFusQ0dyu0mt9m//odF1aPS2WrZWt6dbmec8rWXvtuG0Oz3ZzM4tmuvnHlnt/zKZak4LpHlShrlI9ljIdhpxKs/YEY2whINXxUO82gPwVtHIUUuV4It1e7SjPwbO27SRSaxaCFUgFU/KeQ/Eag7KxVB1wjgY7wT+yloL3YNuzM/mmgodUXeu7RZVRihFp/6J9rVYHV2qwF8BPgfA2lcxUpEnZfpmb/oZQ3oZCXvgjUa39BuzZWu/YTe+6SS4owg0GKy56tg5awWtvez/OhZakYBkHCVblmdTE3cpu6C0Cmu0Y/XX6jc3Ya9IK9OWbw2AVTiEwx3iKjM3bonsTUBLs9Qq6nQLuWYeKHNZLiY503KBlT0ypVO5ikPdpERsYwtjaG2SKFH249plImWiJW9Yx0qqHShSQHJa/AO0e6bC7tKudtIKW+ayLcNUDZWNmzqVXz9/V0bOeR/hEJoiY1Isn305VjXjzwG/CfhG4F8o3wFrNVJ6JterbrWdAqpkJxwheWXQpmVqBugUSKY8lxEsffJrgT9X72h3SaWRrLKgtPYM7epxuYLwZJJT6dQZ+XP7ZFubNlbO6IyQvinK3iovZSZs2UW2nexHmCnHNcmrTootaseW11j6NaweK3fT6ozUKas+4b7qJzrL1mo/bVdbmb7CkW+Uc8CY9uzNI2oKAO2oDjq3JzVlieVYiSgFp4WdKOow0/uruS7vSiCyZDLhekw6LpXtaWmVfIJ9WuMcnJ7qVawRDptwV90cvo6tS+9CjXu1aeP4vmYm5wx0258BmaG4ZpkjpjpT3WgA/gzwW4BvAP554L9rtzOZHDT6PJVDJ1OeC4AGTOeqqTIdliD3o9sel9fasxP888B/DXwl8Ge8MrkeyaOZdkFm4zwo49RqZ4sWXD+zc+FWT0pmqv5d2b8veLVvtFqWT90LnJac5cZhv0lac6B00hspwqlLGQmpTVP6LVQ/RTJkafunk+a9Ohelcx37abvayTzNpWKnwi2cQxJ2WK9SkFTXoAgEm89slmyqQe6VjjHOhltkqmSVLnQiM1q7LM/NWxwrnCMRGxMt5US2Mw9sW4JqVpN4NiVR73Ie+nPl2TOjZCZz/7gTruSIeX57t2Ed8D2c6E9MZLppRRJwq94OfNDL55pl0+rdx2Vax121RgJVslOt2qRuWy6TGrvIpg+Wv+2d6nyLkXobFPQtrToPbwf+YT3Fu21I5izE2Ftsv5X6t9jN3oB2UMnqXO/SsmRq2bGUkuPaV2WS+zls7NmZkjfQi9Zqfxc3xy2gCqNLPjq91OrMLReltarGQCttV/toEo7WTKTyeZUnGjt3qMnIbWX2Zp/Vxqj2MEtIpsKZ+AfLG9MGaaHl9RA3CqsmrnfGJqaaQLQ4B8zR4XGRDudYuoX/qDPXTpktS/6/KzV7uul+5hngUWTz0R5XClaosDm8lxCOA3A8K/Qp07+l2wmaJxp3XwB/CvhtwH8OfNprYWuv1qb+PdjKdHfp0ILWnWsNsFvn6ta3AV8B/KnuXtLn4nVdzkJu/92Jk6bgWN5PkSvYab/tcDcHjWJud61240lYvXfc9KpJU8tMssqSOZULpOxoh21Y8+wa7I600OcQNtFyr7Rqs+ktDVa/Vidgc7qzPDWxZXU1vzdzLvusTiKqmJqbLMlIdZnUXdrjJkrAGFreyqaXl3Ihl1X1Z1eppiyDd1ymL7Kc2qxiNT6jxXWU/rE0flfvu/oD8Q/lTOE02qvuUo0Nzkz1qHCnxTNmydYgXtBydrh72cx+TiKL0m9GB+q67ICrUiFPT51m/AngdwB/AvilwN9ea7m6gyTdohpuGR7q7r68aTY7ShkXrTJcp91laecvBf428L8G/oRXQOWoMWnvoPMg48H6ZVot7+e0MtG9ap29OnBnVx7hqR6Q7lhaNWytVTe9qmfYn7xg5WoYuc0Acps3rJKS89K5tBA0Ws5wmrid2elzd9labV1olW7ltDIFZ36Hw2ZyjoxXzrfT0EbIndA/ouUEiXiAdbvY1VSrDqqejaEVKIncdpS00naT3D+cP5ld0F4m84PZPVNCCSGry35Cpe3qxk0utgwknkb7+Z2SoDDP5csZ+xObKtjXl2xHX8LORvlQbVjwxwvn+J+WT2patCaC1D5NBVH7mVKjwepaJdWE4O7Yuru5ZotfAnwv8DuAP+5VaHNE21j6nAXCsy8lymDg146kzdwMe4KtU051v3VwgzdLbq92rNEWqzbRGc3llK2Skc0PbUvcj3jYYvVXXRu5jsPA6cEiPB7cTe4Pa2wDJrOVs7p0E61Mu+rmtDIZm7Rh995Yqk7tnFzfe5Z/cGK1oapORS9gErYYb7J2WlWY68KpKCKSlkpmKjMRZUn1po2cw/WSiOMml6VEAOzq9q/SCzfTdtpEmTDd6y43Jrg2vvSDNzauie2TrGS2dlkeYR8VznFeY5bfRfn3DemBsZ5o+i0EMABvAr4f+MXAD55ymnbGsdbR7pvbZfol7S723nfr5znE1vCLge8H3lLuvlZ5dayh/gOj5XdRz9enYmEbj4BPdQWwVid3Bvk1x3+mM5VV1qiSd9YdU+ReYmv2UKdbZrK12slcfsspiKpxpMlW/Sub2uukdH/TxpxO+13m1OmZTpf2r4habkx00q2cfj5jqzM6N+4Bm5/N/a9oh0oIkjnP1D4uH0glMk0onEZtZTNxAsUMNv5sIIV8oQv1f8C2uAU2s41U7i5ZLruLi+QMzsESiCTkn3JzqTOT+KFoB+rVVf7RSU/1KhrFzsOWOwGNkSlDaOEcE/D03C9hy8C7AA7AU2AwF05mpU7L/wjwvwO+Afg73im0zFumU5NEp2f4bupUC+/u60wXrcYkU0zd3bLp7wBvAX4z8EdMtao98BTEZdhfFLaRrjHAntZ/yJJNa1N9Lqu4vaGe26tuWiU61ktMqUyksirqsjWTLe+Jm8nWOjcMNhfrZ7rhFHYXCdpIRuHoHH3Lb/XEbRpmU+vSuNfIXju3jErbVTenn6+w234/9CeR1nyhduQpBmaqYvDkletVteQJi22nSgy1SiFbV21z62fJCn+hyzo+WvW47huUAA7JVG4a1Dvi2r6VZZVpDefDW11d2lUU+gJqtsTTZLNqd78N9O+WXC70dI0PU3K47vLbl69+PfOmoX5T/xDwfwC+HnjDtL8zR7hTTOsQoFb1d+mU71w4dy87jXBi2foK8JXAH6oz3ZoTdeay3JX/UlEj/7wPyMp44BiOTkc9n2Esd81M0xGvgnrbstvO1dxo51aNaMfodjwpvAtbfcsJUpEhT5IiTmIwJ/1aJyv1p3r8tHq1k9m/cPAKqK2twp2cLZtUsZ2kNnKOBa2bvEU71I6yySakMRvPgcsz88imtmx4ALpUw+YIG8i1+bcspLUjusxD8Q9FWSwVSGuUwv1JSfbRgFbdblEJrGXKsrXKCZvZf8uxP1bVAOB8d1DxeEv1WOVhKeTg6bkvquxKuCJI24D551LQtNLBHwR+F/AnC+fonFRrq8q5DXC19oidaaS19RXgPwD+IG1ttTxRVy/fpN+V/IFumd25f45zBJ4Cz+hzsVgbRa1p1l4pnr46aI1nAX/Edovt6RitjVZQ2VcQIQBNa1b22GK2z1AXVgufUSd/jKC1oz0vtNOKrbr9uXF5akKl7aqb08/vFN7xen8eVzu7hW2+3Gx2le/DM5DpHrZLvr1TN7+TdnNmszzvx5QltxnMTf1geMnCXQ6NVT5x2z9YW5W4BF5d2MxMD5SJZCdQpkq4q53Mkwr0IcNmAq5KnOCz061UpltuR8aPO5ZLbrntvw74KuD/BjwBfj7wo93yq9PKavs7Pbll9uifUTL5vPU9wI8Bj4HfDnyd1z+t6YgLcFfzVXB7exXPymC4qj+Xfv3xdkaB1sVVdmUmfRH0tUDxfcguatVaPrvqGktretWqWFybf1M/5gfZU0TO+7kNds+uk7Y91ulktexnuolO2q52Mjv5/cI7m7vxhmkVdvNVJq+6aXUyyXRTMqt2icayZSkHr4BN29WOUe/81De7lrCM4yk+EfnJm728OlKrcoPKdM4LGzI7q8c681hn8r+FqYTLPGwxlS8jRETjwQwndxNotNgEqGMH4DXgCnhKr5Zshwxg6czFpXIoz8eH+qB5w60+A38A+D3AHwU+DPxjwI/TLXBqw65ZcmM9renF7i438j8GfBh4BPyHwB9ojAo7Y3A6EcNQLpWTGs9YonCugNfoD3HsyGkllobJgOSIzv6mlpHoG5WWEVo1YKtWsGVT3cyOqZ6oc7JHC9IaS8Bmj8z2X3/fznmhXQkahTcuW6s2f2ParnYyO/lbCvv/pYL2vLCxsBwmtTPz5nTn6O6h09oSngXNjXzXNqu3SSXK0moeMDm86TxviPopP8sBGGqtgm18v0IAO5rjUhEnloEyl63seVEJu7SZG1c50cp0c5KJtOCcThBGa9hLxy5m5mn57P1JSPR+5oKZEmyoMqmsksn18OrXAL8X+MPAh4GfC/x9c9DVmwjmdrN3jS0Dk+nuZct0YFv7c4EPA4+B3wl8jal2rvfl9NAoybvAqGsbMZVhcCjfgjteY4JmLaGzY6eAO1T69sld7ds/lZjqZ6SjCREdyjPGdju90dL3K+yX7FfrbuKwvLkM79ZrJq1EP7+z7Ge6iTPS/czVTRsLn/yl0U7Vbnl3kzt/tWbGzoyZTPfZNmRvHkxUuEMvWvmJlAlh0InMRsuiq9Wx3KW59q1gjYicuslmdhp2rFcPdSZ7Xvr9ZjMlMdbXXWyDfK01GVeLTcy1yU+NdCunn6/KSFc8Aw7AE+AZ8MqGfRdwXGEqUQXyzD2V5Vg/582bb/6vBn4f8LeBv7y5SQrzepHrwuUrq/hx4F8Dfinw1V5trQMNlBjr3l5+I72EJe8fbWeQz4AnNB6OtaHto1XG5rdsw0TM1bU64jqZyTmS6hGVDNHp28KOBXXLWOPdX20Zezdzy6a59NVylflTBVO3no2n0OqWjf3WWfYzO/mtzNXVTubqppPKn/Ol0TPKu5tUJt8JvJXzba/ZwolWlzS/8tBfgpZbaEcnsYV5cFio+nsUVd6tQcSGpfEsRZzNNvon0tna7zS1PJocFIuuiEWHcKS6HnTTwmnYsYK1TJR8+fzJJ4B3lKfb/bbPRs1Fcp8bHMIa+2V6Yo7Cm5KX/j8D7wL+ZeDbgSvgHyn/8ZFKbfzEb9tg61T3hWqGbfDqXp2DiiWQfZf2XwBfAnw38L4NPSCrwiQU3H4WtjGUfVchKtdT4BNF5JC4UR42idLDWqZ9YaSTXk1sWe0sV1f7Fnc10111C7BwkkhWOaOq7QU2nmYr4a6uLlHugkw5qgDMpu3pVk4rc3XTGeU3fWl0QWe6seXdwm5Vtjzn8C5uGiYzmzlupjJqqVblncyZHpJ42Vo9NbHR6vd5gHyHNFHiuLlaWZVPhghlmYviMtexIG5iy2ons3Ut3E0bEyrd37QlZyrPxM+AjwFvBV4F9iUTQKbIQZAHCjXhkLGdinlTn+KQaY4FW/YBJapEJX4a+O+B3wP8fuAjwOcDP0n30UxpC2sFU7mVciErnakkldGi9rI0zj2uuuU/H/gIcAn8HuDrgZ/ecO6oDzRTmzu9LYUnarPUI3R2KHfB0kVPgVeBN4CPAc+AZyVuVJ3glrm+Yxv6NmY14dqzjsHbktla5cRUep4dLlPp29bLKWikV1fdNpxabed0VhOt3lPvFmy5Fq2qYMrYTJW2qxtztm89r/AJsfbZm5f7h2+Vt1uluamRw6tuGiaz1eBM06JaVYHZcvTWcjDp7H3qo5NYzdxSYEv5zu6HOnH0Mi11UDTFrqY62gO1AAPTTpUPk9/a6iZWM7escs5cCMdT4GPAm8oHQy/LmTKl4K+RZnpz0n4nKtMYnuqcmb6fiHpAuqM3A/8A+N3AfwJ8J/DtQAY+D/ip7v0FYgbSDIXzPj2igmbUUdw7/XOBjwL/APgS4L3A767Pzt62aHTLQD050YHkJ1dhIrYx1wNAah6IwTwD3gCeAB8rr8VeFYVDnQ4aOZ3VvlFZTbgmzW5V+ceaESrGwFxBdrfUAfXqqkXvpLeUP7v+fqZNyJDge9ASiP5y46rNd8t00nbVzWllbtx6nfIn/z09TqcdaOzlbu3MjKcyDz5QZ5rmVdRTmxy0teQyc51QhYdyo+Z6dTs1kcRJdORGMluN6ee7mRz8Ia/OKrICYi3w6MuWhBx0e7q/upilZ8DrwBPgE8Aj+rR8plcVUC6ugLfKmElFIFE/GUVz2bEfzGHxVcA/CfyLwHcDPwF8LvBTdQEl4011/iqEN2ws7B7FHutzgZ8ALoBfBXwE+KoNlTOWe3YsXSefyFM/9fZWJicm86HZDNRlBD4rV/8J8HohHFdth0h/dTWt3lztJLLJEZ6nSMNQD1S77GeekX/bmRvZgyTkauaSSHSXqV06fdJZtlZX8zmxMW1XN+Zs33pTe53zzRvLCbbv1dpllWfYnFXmsYWFdLgIqMB2CiKtVbZ2pmUyq66RZqOb68+Nq71curClTKfwqWzDXeXMToGDl9NZleVIb6gmk2D6gprK2EyVtqvLGHgCPAKeAJ8BHgF7ujSLnWMdHlRVLqGF8o9fHNUxEx3J1FEscmTPSLPx5uX3AQn4PwHvB74bOBrawSNQVWVrg3do3l0VU/sevWbz7kvbfgr4VcCXAn8e+L7u2dkeSDWbT+WGFUox0zWayoUYSAs5epcMJZ53qXMCngGfAD4DPAGeAk/Km9Iy6jiSQ6266U4mPCM00J8Mq2V/tbNctawbV23+ll3Oq0cSc7k0yyVQ3xQ56URafbK67Ge2irXKbEzb1Y05pxa4kV0WnMQZbrKK/l6travPo9kzPK10v6QlEBtXz16elCkxgEJEMrETXt3IQvoFtqx2MlvFVktu2XR2QtL8eogqw18wG4FL4HOAdwCfA7wLeBfwuLyukosZkznF5RxH4FAei5+V2EN+6+Gq/A5kGsVCd0x7rnMADMCvAL6s0A4A7wY+Bg2OtOD6YThHC6pJndoUpD0L1firwAfNoeUBtEWDJPBiV95J2Zd/S7kALoE98Bi4BB4Bj4DLsmlPn39VF0tG2lC+24HiTPk48HHgp4FPAj9dPjaaSxtc30ouY8zmXz+x0f7ZAifRkZuiIFsK8BslalW9cXN2g89enreKRuYqscjFrqFR0q6u5m/ZerN7CW6AcFyzotUd3QJbMl0D08rfmNmxgv3VLUtevVl2gvpf2VDLJ6cSi1Nbdc2uaGVuz3cTp6YXwnEBvBn4fOCzgc8C3g68Bbigjj3Whlm845kYyZFYxdOafDwrmUf6xsNcyyHZY0ioDzrXiS8G/pfA7y8Px4uZT2QdUzGWqbbruQyVXOtA6gSnbTUsWPpKqMYF8B8D/zXw1xuNt+AeSOQrGejTXjvgUSEcTDIeEReRV2QTjV51+STqaAKugFeBTwE/A/yPwE+Wb8FNp5iQVnojsVjNP4l5XIdzuJu2rLIIkdY0iVMzWwXOOPH+6pYLd1LmlvzzMk8qcOM7Mm6McFy/xvOYh5vfYhgbN53EOTqJUy3oNSlIf2kz+f9seZXVkbkbBHqDDOMMnnEG2zhjK29aHp1fAd4BvAv4ecA7gDcDj6m7ZjKu2URyiNvlUHSOZ/R7Wr6b/qx84GGi70ox4cilSdlrastUfynwK4H3A/99cUW9G/iZ0rZECauUdOQNdVDFNrhaAJ9VeMYe+F8AXwr8N8D7uxUy+IFPWMJQmMGuvDq0By7Lb1cIh/wuiJRw3MwCJW8MRKqeAK8BnwQ+Anwc+CTwRrlMdjreaGlOIh9nrN4s84Ax5DbIlDnoXO4CG3Par/aarVotf0bmqYnVzJM2tXL6+dsL3PiOLm6ecFy/6htkHm4mG5W8Zniw2TI9HyLS2XSDS/bXzF0uAspJ3fzV427JbK3a/E4ZN7ElPRTC8RbgXcC7gXcBbwfeWlT3TJzDrUpiCMSxciSd42mhHRNJIFJYdA7mHO5R+vhy4JcC3w78zRI9k4HPAj5OhlzgEpoOstl9qfBdwM+UY+2BXwZ8CfC36w9srNbMYLYxlkuzKyrURZGdHhWFQ7SNHTlTRuIT9igD0ZEMHIDPAJ8CPg58DPh4eTn2QJe7ZTxOYhVu+etQkFNtsIqH6ORbVsHSxbx2xJtanrqpn3lqYjVTFUiN8q2cVmYnf3uBG9+xj1skHNc/xpYdb4p82K3PjX9I4ozV26AprU0uCwHREftqiSRull6c3aWd9EbmMQKvAG8F3ll+7wDeClwSzeK3UVQluRSYTDDHVGiH5Ryz51tBd1JYvXd+PfCLgQx8G/C36D3ezwJQZI9rQlW1A/7nwK8FEvCDwLes7b56dtaTMnhsY6EaowndGOs3VmAuWaKhu4SLfgb4JPCJ8vsM8IaRN7bzjH6B7TbvBilI6xUY9z2XjdzCzbwp6nCdrjg7sZqp0v1Nbk4rs5N/apmb3XEjzvtn5tMg53Aq83Cn7I1lVMelRia3ba7Nz7zW4FxPVXyIZBLwbNt1DOeppGR7prtpNF83PxYWwgkUczh6idRmJKipyeqJby+wulVd5f5eC+sSGeNxMWaZ/np0pqU0UoZHphcl+JXXYz1aOPZwJqoxEadh2nHqzfVNZa9/E/giIAPfAXwv8LH6IyLvpCZ9sl3bO0oiAZ8o6Y+WPvlngF8DJOBHgP/43EmNT3Og/kSxhXzDTsT/lrE6Us+nOs2XRnYZaAngWCJGnwA/Qy+q8Auxq0bILbPRnp1qO3n1pFdqD3VCUYqhwS1cLwm8kicRoM4pn90z/cRq5pZ0ru9ltar26meubjqpzG3sexJOnabuxFG37N4pYzdZk5Mbhseubtx0qhWU9Embrs9O+qsicvTVDpDsMVAi1/7y1dbO28p3Ktlefkt6MU5LfACLHG8H3lREjmSCLZhzLJ22bJWXYw8kZrDUMZVgjqnEfMxlORPt6EwWJ91o/zYA4B8FMvDXAAD/37Lp6O+hIY8v/zMAwK8GEvAPAAD/2Skt6Z9Rqr+xsS/LfZExLotjRQkbF6XMWL+ZkgzbSFR/LhfideBTtbyxxNnk2rS4Z7Hdnp1nFHl1pttzi1WePT6hxAwYSpHKnZ5q4nsSS7gmh9jSIZ3dt2Sq9EmbUrdAK2fLppPK3N7uZ+B5KBwWcp7nMQ/uplYNnTJ8dDsskhmydtyo2lJjVaVVVamRaZt9fRN7HgVpFbBzkDz0yGwlE5/VOUCJ1TZMJ57XGcU2pmV1sb7Ld5/YjIFuJ47ksJwjl/6ZKCA0m4E3UUJ2ycUEzqbzz0MqB/3GOv/fBX4R8LnUpL/eruSLqarlax//D+CDVCDTga7TVAkpkNCKuSRE1WB5A9R1x3o11VeEG8mxogCOwFPgdeA14LXy5bflTWb7pqtaPY+CXJOU2LdmbMmO2jFTwhKLjVTDJjbSiFMT27duKbB9k11197W7dAzKcyAZN1LD2XgxhEOwhTpcv4bc2Jq9repi9NmG7NLhHLbyVKddZrOdhbiZ16cmNtPKGyJa2Mcj1AmZuVTiZlt4dmYnbTfxG6pit6YicrBjZTbjky+9OEom4hzovu/KNfNPSEwLZ9xc33BK4Q+uF1lHv/2sOiyn03d6LhdlR2wj0Y6ibcB0nTrKscgbrwKfBD4OfBp4FXhSXzX3FM5jG9fM3JiYG/QCGxJ95nEjLTxj6zXTp666Oa1MNBq8uteWrVvwAkkG4wUTDsZNkY8+7WCk9tYO/3AzXRq7ZdVSEFVhavfMeUbUKgqZHvUkYV+JzETP1WyVvATqeQqNqWp7U88+/e1kYrVYKo1PJVDx9aLhL0/VxzrOI5urL2n2jMzli2HKVzLTjtn8hLJksnzbZxYZdefdbmcg00E3QkYpO9cG0xUCFoGEAR8L/0DJF/VCmR9Fa+bi4XoDeB14vURyPC1vGPHRz2AbrU3XZCcbi00moYq5pEQlcpuCpHrSkMT2pp50+idtOnX11MxOfn/T2SVvdt9bwh0iHIzrkI8WdTjpKBv5Bzy20TqW5Tcu7VCrzDzUqtpkWwszR8uOzCe4beqZL9FkpLpraiRsm1X6NjKvme6v2k3yeXKZVWdP5Mhk/2ydijQI58CaYRaDqkSOiXa/Dka6pu7IVLDjNtf1nA1hG+q7/hMdRUG1YWEbO3I/DcSq7V6JCsDIG58EPgW8Wr6YYp1Z51m7G0nfUqZQ3mM74e4+mzFsqQkPsLne3aa3bzp1dWNOP7+/aXXrqcVuaffbxh0lHAw7WZ+xu6BVj8sktmxtbbopFmIrdOf3ZFZR5ugFbEIylZnqOtHI7zzx28xW+ja4wm3widVVFjkuy+csx3I7iU/E+juSqZC9M65/xHJBWap9M0kjqGmlYCg7trD8Pc31ucKWetzG8PsmqbCNiSQH0Hdd1S3Dt4bwuUSUTn11A+bSJCqTC+F4oygcb5TojauaHaoKN64+Z0ayJX12YTc/tyuZ26x69oZ66q66h9ie08rs5Pc3rW49r+TzqedWcQ8IxwLuzbPJB8xV2ah/2JInURBsFkJaO2aagldXQbflbKqSRp5ngzduOoMH3GwDTlq1w6Cfk+o3WsW2zW2RYyDTK4aNg/uO3suuXN62it9RnOlaS7XH7qizXjNhCQcqJpGYfahiB8M57OFc8MkKgRtIohtMed5rgfRJrqnzVBgMK0+oX6pqyRufAj4NvAY8Le8KddjDas5t0JQzKMvGYjfbAFltcRc1PIQ+psYq2vRlI+Ho5G/ZuqXAGSWfZ1XPB/eGcDC2k4ZTq+rU1qIRbgHWG9ytdq8+X0F9i24h+JbinG2Pr7N6F+rpFFDfb2DIezQq3ETtONAfduzK17Iz8YlMz3OJ9A+20MxgmDoMJoZ0LE/q7luLcqBcbC2b1UzWWhgGCi1ACUA51uTgWBJ9SDHeUZZ8lENdIfe/SBrcVyxLcCLRNUKphKuda7Ekl1Oe6O2SRSw51GxjLB6uZ+XbG8vvDXpR2RpFPrrLz3JNtk41jTdCSl5IPaeutnJWeYm7Y6vCfmbnEfEkM3+znODeMQyFe0k4FG6Qf3Btwpe3qCAt/cPlGdcfNLZVit+4bbOnxm1b7cbtVnzL6qkFhnYLh/op1moJyctBzSSsQVU2w7Z2IpPGBn4un9BW+QIx9snbnRkDt02oBsgowrwcdCTiIpCHwpn2QlllK3ioO1A+AyUxEBbcdaq8qo3/Ap55DF8U0PuZQ/mQaK4Lj9QzQjtkK/eh0DX5iDvLHmqoCNGRP9h7Dfg08GngU8BngNe3RW/AG8yzOWu5KNKNNoflrg5ZSeZyK9weubntnJMyz8jf3pIt87bcszfFDO47w1B4CIRDoUUCzq5nS4XusGixELfMqQPLZUKWdriZlgbZ+Ws1xx6IcxIZNvXEILMtyvyeaat6Chc7dKz7ivnHVNfJNILNdv9MZ8qxaHVIqv9u7SnwCJiBV4BL+laE2DlLOwRMCFioGMrrnXN5Olffkk+1KRImwapJpkPA0BHVkv6qxUm7Kx8ff+szlXPh73pJSZYfJIGyukxkA/Ubd0iLoAtPTWbfZ+V/Up7S9ZVvtdmnbXg5bmb2ujTTRW8VO9RnMdeF7YB3y0jLFeeWTJXTOgWL67CHGym8umljgY1lWuVvhCI8MJ4heICEQ7D6zHHNClfrPJuFoJ4mWgU6d+NGLpJq8wwz0XROsNMA0KaJpkKVg7oGfsBtHcKWQS1g2JLnZW7M529yoHTmW+iZW75ApTgHT/F8mioI1B1yYnr5N3pmjCu34ahu/c8BqR5vYu/VJi4/eqc8eIWlq9kASz2t/mfP2lQIx9PyZ/SfAT5d/CmHup9v5Dl7e+ZGJ4JtocsGLKVwFZRT6QWzH0tc7E19BqtY3bqlwEnFrrnLC6nzDuIhEw6FU+nCeXWuVrtxF2uJlfnv06nWVnurKzbA01PrKceVCuBNJa1M2+BTM2+kcCd/4yahayPwpKYdE3Bp1AX+KZKX6mIckcoCwGId96XYjnYZaEfLLUCrs7cVjdUF/UjP1lZLcCWRSJdyeyCXmgcSPOQP5fc18QKNNCEcmSi1NX7MXTjU41jYxqcL1Xha3kw51HG4Wwj39k3X5ygnFb69w6Ht+kF3FJ3NMOw8dkb9N7XLC6z27uMlIhwWt0FBVLUbK9zIHjqWuzOCV6WIViOFdrj5MFvds2i1+SSudk1aYGEjQrbsZbemWuFI5f9QPl0elJf/+ECtggjhYIcIW7653iWVNs8lyDGRdsLBrbnc0kyJROdIdGiYHGWkFc3l91Ysppo9oBAgqVMcFslLoKZTErqxo9WxZI61V4XVERS2MdaBIJnaoxoj+0pk6wF4ArxWSMaz8jf0z8yXvlCO2EFnmJ1nem+bylxn0zW3XqfASTzpmm144RXeX7zUhMPiDK6wvULGGSpIa8fVwtcc7i3aoY7OBZKZl1vNbu3Fkkxq7CKrnQKp0f6JCrTonXvK6qRyIRkoRmsxJG8HroAMPC72LxntQaqy3zLPxXBKWqyjxI3OpWYpsxxFojuXI0qQhHAj6RORJZjiyDlmSrR6gHuJH2pTXVuiZuc6MkMYxlBTDeYWsmlHDGMk5UPoS6bjpnoV5HebqU9yqeRYvjH/pPyd3qeBV4HX6NsbaPSJRccutii+DNTsZfLuKkdWVeVqU/9Ats1uSzrYMs9snItOmrLOnt9ulQcEyXARhKOJkx7Bb6TyLfX3x3HLdqoCasprFVs9bqsSa7O3PBS2ashrE1+n8lYDuPCWa9rXUYbyUoNYo6XZbwLm8rqsWNlsAjlV/Yk2KfPGcshID+47MuRqL25SIuqjqAZLIKgPetIzqx1gqc6XwAuhEWgwD/Xb0TspI+2iLvFsTko1NdVHXFblS6/LNzZeBz4DfKb8W5t4UuzLKZ2u6JTpV9If4ass0I3zOLUNWwqsYnXkbHwiuqbxvm3bH9xiO4JwnAb3AfeW6sfpla/uvmpFbkQUUYfrnIVLDloF3GLXOZHtJ9u/EOxVeUaWewbeXDjHaAiBiiHlYymuwE+uiTwCHJS62ONDKcOhBixviE9BVIdUG2k5I9AI7w8byy2ECUnmUJZs6fskY1dOcG/0D0UXWMxIpiUC6WrpQ+nVufxnyhF4DXi1/Ja4jWeNV2EVtt81z18MeCHFVgt3HgOug9uWLqw4FNiIIBznw30OuFX+oXBNOcStYeONdBIv6dMyZV/7JbHh/VXUxTp1bu+fVWJ0rO3ZAXi1PIs/AnLhHHyy7DEBTWRsLJkHiEqRDHdZysu3JY5UA//lylT3jzADNtKuNuD2qmCoVxP9QFQDhmegdqAIpRAZY2eiNyzt4E6b67db3V4FXalMvfS0KBxvAK9SMMfyZkrr31vcIXS2NXL7vH+I1TvRPiNtKbkFN3KaL6qG6xwr2MbZCMJxw+g/cN/qsZKZSU+tAZvb2X/S3Vge3gzYnxBTvbrlQGc8jmyc69UucxEYlgJvAV4tqwvnuKSHctEtOGzCbQMflDlNonBRVhRk96GYSeYZI4VuDIWIDLQUFsKtkhz+sqdtsJU6mB7JUlENeKEbKlA0EdXgV2Rhnjjd/xrkVrGog3IJnhW28VoRNl4FXqf3YHODbPVxhmXqi0lu+VOVleu06gycty9f1uejKASNeA4IwvGccKtCiDpEa1o5j4K42Oj+WK3hvIeqk3rvjJ7vtKojlojVf1abw+X3GMjABTlBYL6NwWenWGOrDAdgut8mSSU9kMgh2olwDn7cl7ahPZY6ncPCRqp/A9GOHdGmgRKDkTTUqtIqhD1wX7myWaKzlr6dgCtgKm+mvFpoxxvlE+bTmjPlmobq+dvy6+97UzX0qzqVe93IQQO3iiAcLwZnmLRbPeipR1+tKtVz/ak1KI3Bfdzfsrut4TqMCvWnGxWYEzwtlYzAa2WXfeEcMG4ImM9FsFl1W644R/KMayqP5mMxnOw3WRosny5F/f1y9SWx1ef7wUuLmMHppWE7I3UMHvMYzNbU6BZLuJlFDWaX5WSvSqDG6yU+9HX6hLn8o14LHSnx+mT6mjWcLS3gRkWFF2vXg1XcKQThuHNoKROdqe1Wj46zjrvx6WTjZL191mgJJ+fN3fBauPqwu1ypp8XIPSpb31RsvPgFUHI4gFSiKNBVldmaslQgEaAiYIjywQXGEgjJn0sfa/4xUns6zhSGpR2jl5YvkSuvCgdz2FgN1EtQp9mO4lURNnivqcgbx/KXsK+VGI6nwFScKatM6+yxuqW2MypcLb+lwuuQleeP3L7xA3cKQTjuATrG+zlQEPe4LZzanvMmiM5RbmTGuc5T5kIdlmCONwAYkQPARaEd2TAJMZbquIMppiiRhJFKpvpl4iKZ3CjCMIQM2WhWbFY4WF9BTRdY4RC5YqC0YhtDXUw5TSxsC61bCuXEF73nqvxhirz++gbwRmEbrf9M2Y7btn/Px77eNSve978E7jKCcNxvtG6zVY/GLaHTnudwlJs64nVo0GKijsV4L5bysmxd/CkzsAP2ZESZZ7CZ39IkJYAlIzOw1DHSGytjackigbA/hcNBTgqW5ENbbUPlDCbNgaVW21BEsN9FyjOlevhQokRfL/8K+0b5ovkVhW60Kn8OeBmO6OLGfTqBu4MgHA8TfY/Gc2YhuAUl45aOaBuwnbfxEcUt8ox2X0zmG+UJW3wrraqypxUnk6laKBGRiV5I4VXRFcSbw8xDdA7UFpffzmXwcVGnhS4wz+A3Y5PRMKykwZxDCUJWHwKdu9U2liV7Ut6goI2r8hLsvCFQ1MXdsZQvvAEbseqdDDwwBOF4GdHXIV6INOJiddK57Ub2eVsL4r84kr2XT4wvfzK++FYG4MJoEnJE5cuwJMMelyHaBq8mEjmYbSz7jkbhaPGMztHliGO9OtScQ+kZqd5k2QY3w14XRcjg7bWc8hUwl++XLzzjdeBJ+duUA3XOlrO2eA6W8l4YY74K96LBgeeAIByBn4UNJmjhLtAR3NxEdhseH2EMSzyHfIxrWV18Kwvt4G9LZO8quMZPtdndKmpHLuSDRQ5+QZQDRWdP4ZiwApZqhkZCyRvCtLaQDIUW5bLCBkqvirbBVOOqxG0cC9vov5ZyHTwwu7vldB7YKQeuiSAcgXOwGlIgxe4INenjjGlxo5NlIgP/hBSOZSmvyF6S0bWVKCeCarObY3t+rKsStjETyVAvxPKbsRvfUkGXbaAWM0A8A4ZtKL2tJTmoM7UdKIrFs6JtLFTjUJZPihzl/hlsCw/VlOYNbC8QOA9BOAI3jO3RjgvuBSOx2D4R5yJvLDLGsVANUTv2RWMYydwyWPmwcRtbtCh2NAgdWepkqUNedRGFY9zsXGCWMJhMzrdKhiIZMEd0BxUzLdtv7Eax2sYbJWjjUKJExf/1sE1syBKBF4ggHIEXjIfKSBYstlDiOSSY41iTjwzsgIs6oGGBCpOUOtHuOjdukeMuFYNR+oFsGii9EWz4FY1wGQbaXME9C8ZsaIoSe3KRN67KOylCNZZwUfu9jftua+97+wMPG0E4AncdNzKHvkDWwqb9qsgYk3GvTEXnSOWz37K7wHoWbICk3YvBtKNVrStpuHpDx5eRNi87ze4LG/a4ijwdi7zxrHzdS9woT0nbmAo1ebEIrhB48AjCEXgpcOpsfuMEZa6NvegcQ/n79SWAdFfuSRvSkTyrbz0saHAUC1u5FU6UptKHpRFWe3DrUdEnKhPeKbS4Ti7sIZewjGNxnbxRIjaORds41u+k3CyCQAQCCkE4AgEH54WR5ppVgJ65ExlCFP6x/J/IoRCOI/AI2AOX9B1S+8Zsi0PwN9H5RFLDooPK9ynFSfSrRQVcPUO1zcoMLQnHZnLQxlyEjUPxpBzKqyhPywspE313BPWVgncFA4HANRGEIxC4GbjOjlb+slzeNb0gwpHKQ/nj8mcic+MNkVUxgDmEmO15mx1NXUu/BbZyRXqWmmfvRCz7UY1xt6IQiIm+tDGVoA1hHs9qbQNrVwrBNgKBG0IQjkDg+UHMvHxHnN0rC+HYk/4hnyJNRi3gyMo++ZACynDO5mleKr8RuFoLapKRazKkWg5DMjrxobn8uevCJ56RsHEozpSJPrahDhQIBG4bLzCWLhB4SbHcdUPNKi6BC2APvAnYA3vgcQnvkDLyWql9KF+N9JRDW6/Bc8aqt6IVf2o5h7hRJtItDkXekBBRETamEkn6MN5JCQTuF0LhCASeNziM41jsZSoWEcAFcFEcK3tgKpxjT2RlgSUQHY9AInXhxYYmzJ7aAY8JtdgGSl/l4jo5FgFDvq5xRX/GdlV8KDPxs0Ag8DwRhCMQeDHgIMdc3pidimvgAFwCAI4lvGP5czV5nwXtF0Rb1pTlkBceCMkOnRaSOUcWcubiHzkS2ziU/2A70Jc25N9fc7CNQODFIVwqgcALRiq/XXGgXJb/r2cPy6JwSJmh/mS4IJulmzi1hf19VwusVm4TVtJAcYXM9C01eeWEfSiHEsYhZYJqBAIvHKFwBAIvGOoliyXC4IJiDoR2HAv5ECcL/xk9THyDdbW4zKDPJLbY6c5rt6q21morJhREnqRzOFxD2MbrhWcsy6uiaoSwEQjcEQThCARePNi9MtNz/FQ8KUfiHEfiHMs3SeVPWGbzPybZkA+c4k851UhvL98XNgQTkR7xN7EDRdiGUI2J/vo1B9sIBO4MwqUSCNwhJPrty6c49uRh4RdYxsI25B2Wgd5kUei8N2vT7o4b27+a76ZbDZZITwnFyHVw6IF8KIeiahyCagQCdw9BOAKBuwV+L2NXOMdYqMaO4jkuSs5I7MT+7TsakkaHbdyIkV51oKitTIlyLfPM9CrKoXxgYyKecaDIUP6X+WAbgcDdQRCOQOAuQujCQBrGWNwo+/o30l+xiNohXwxz36FdsMozzjDYLplorar3ZeTT71P9dQ3UkaGsahxJ/JjoAxtBNQKBu4YgHIHAHQVLHfyJMEU7UNOOffkfFvWhUuVq6d/5t6FwtA7B8SsgkpFMoMYBQINqqPdQgm0EAncQQTgCgTsNph1DHbQxFtohfpYLIBPtQE07Bqonm/dp+x/9XDXhnZK25rmEuLL3hPUMYRipvG9yqMNCOaRjDqoRCNwHBOEIBO4BFO0YitNkR7QDnvIxFgoyln3llRYUzpEb+of6AOgq7AdDOZ+/Lgp68WSmOFBRNVArGajfQJkomDSoRiBwXxCEIxC4NxDaMRB7AJGPXXnTfW9oB+oXW3IpKTqHTXRedbGtcovNjYR4TDIxDEU1DqXkkUgGiKPMQTUCgXuFIByBwD2Diu1gwUPcKKx5LImR+AfoNVrQ13iYc/DUoJwvLai/e7Vs41hW5f9ahWHIKusZ4l6xkkZQjUDg3iEIRyBwL2FpB+r3U8Za8EAtdSxL0TlS2QTiH5Kz0a7LbCJ//n6knFxyEvEM1MIGSM8AvauCoBqBwP1HEI5A4B6Doy4SKRMDeU84enSgVdSaB4hhSA6o8CqO9eqhJKY650CFhVKwmJHJgaJiQhFUIxC4twjCEQjce9ivg8vnv0T5ENkDhUAw57CrIP5xKiZKM71Qq0cqPJGSIZ/8UmJGUI1A4F4jCEcg8HCQ6qWoHfy/sqNZioAhCaVwbGQeU70qCsexTkxmyf8BC+M3CZ4RCDwMBOEIBB4glKsFRD4kc6QcG7eBzZ4UC/atqHgOedNEWIWQDITrJBB40AjCEQg8ZNh/MOH/WGHlgxNMO9Ipb6kwS5gonxOy6kaABs8IBB4qgnAEAi8ROn8KzxIITPokzCZtuUUoGYHAy4YgHIHAy4j+X6yprWd8hwNrukXwjEDgZUMQjkAg4E8EZ88OLpkIhhEIvOQIwhEIBFZw6n+pBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCgUDgBvD/AzAMiG39l2zFAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img2" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img3" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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GMswf2mW6tjIbUXw0MaOW8Wjdn9SPLoxB9vJ8rGjUWqKWInsquLJY+mgLtWxYZzftiAzpyXE0X+rdZQ/Ukzn1fVWM5WpJQ5cRFlp9n1qHoLCOZtS1D7u1HhZxtUONfrGqQksjFgCxUQ1RpZb9AhHRiNh4wTAQYyl1DKVjYKDDMI0ODADNrdHKbFRmYEOJuYZOevtnqBpmC+Uc5KMuU1NkI4YSvtNWYOMEFqmezRSxLD+1zHTtbaHBV06t3w3cm4d0+dXsHaHBNAdr93a/HF58rL+v9nT0FGc948T0qx5r7WjrNXQn6dIuKipSO6EVqRXQSzfcVkH0yVIrrNvFGHmzAwNLDMIxMNCIRl9go2oSySMpbAUzppyDanC1iDLzZuqme+ENpiAoBEocho2a77rKQDEs2UBjDCeoxvJrxTza2gticLTw6WVrJOcqsnIX8gGsllpNiM0vPrrv5RVZ3q6YeHTxTuQPnzDDtGPrGJtrGlbsS1a0Q0uJYXh4pVEQ6Vb0cmHoeMfyeg4MPMEYhGPgicainFdYOLlW74InlZi8YaKFpby6npGNcCQPqXjhDZpyBpBzMp5Rc1BqqVDf+yqt4QoFYsU8dNGCHXEO1AyKI+nhpFSyWuSYo3RT7ko+TtbqqA18v0Zb7gTruHJwgXVspY2f0o2WucXtyOol7WmHAChFVbW4kiGRRhsURDWIiPMPCXWkSR095xhSx8ATj0E4Bp5cLIUNUzWYCGSdoUTFcRM2qkXDSIbpGVazy6yjsYCpGolr1VHuO13rYihh2WyNkFGFPjJyQuTopq84x4qntGn9UqcYykrhuHbsSC9ZLNdmLM5tGW1pB7eYtpiyuC7HY9fHVtrIqQfcurCHdrRJugiLh1fkJO3QUkTgJdI7wuH6h6IvTrq4NYNzDDyxGIRj4ElE79VA5IlwpKIws9GFlEy94MycKqtgyinlbnSaMgArJOo9pFgwhZthw6IoejrftTXkS2FjxTyO262++bqKSBxtcbHQVXGWK5nH0QEvZvcDMXxq2inWcdXIcnCNu7k67lKndbGLuL7HtKMUARalwEpQjVLrhgUdsfronc6x5ByDdAw8qRiEY+CJw4JtRI0NjqhHjsLjKXFmK6rBNdl1SThqSKXZSD0D1oQSrrpGq61hg6dCGEd2jUY62hoLNeJIqz/iD0eqyHLlfuljqnHy8K7a+V2kDpwgHPV0ThCNteZRcX1b3cVSaP2xetjVWX2gow+CaEcXOoto83DUQqWlUg2LuURhsSp7YC11jPDKwJOIkRY78GShD6OAUDs6sY5ejW14j2sp5cRWJNT0jM00Wf/yXn4jpxpGYSKrz8FeFsz5C1RDRAEA1ZbFCkC9YoM1dJ6W6jKIlcYkL7rhg17TEraQ1eSo+bzaCSiR1qFWdzN2pNbdiMZ072Wk7hOeXtsKdHT9sywyYu8VK/KxnHpPm2iD7Uq0GVqphZ9//bCL2yiJWmETRKEw22TNjYYqyCtvWK8qSrUmaVExc7EqCgk8g5b9uolYNVJikEIEajfeb6BaNZWRNDvwpGEoHANPCjp/aCS+dj2oMXNiyimBYEqG942S0mSqRu7kjeS+0dT7Nrp+VWo3r8eJKCetFFXNWAX6Vbvl0TXbndrRxIBF4KUuuFbyfcpK5zhWOeKlvHvtPyGYnNI56gn1AzHcH/BazDgRRFkHV47G1jjpJF3IG4tUZOr+R3/QcG+HGTE8yNKiJy51tDDKKs6iEWRBdEXr27FtnlCnBgYeewyFY+CJAC3pBkVvJn1RL0t8zZymKXkhjZymFj0J5pGS1dXIKfVUw7JeOdiMNqbRKQg+VeN1ORSFXsKog9B44Y7VAHSv9L37UV1KqTNNu6iTFKua2xR1N/uAwnKDWM2oQzUWs2o0l3xoRZK6/2PWYsvH+zrVEi/nrgQXWi2wkjdC+lBFpR0Kq4CuiAwiAKRaiYppIH21M0LrfqW4XgWrFWYDIkqqhQRgUWFmj8oA7EXWK9V7BVXqBwYeNQzCMfCYo2oMfZmNFdXgVtQrmWNjygnAZposejLllHPuFA5PRYFqSi2L1rF6iW4NbY1iUNfcawtbeEcfNXZyImbQTdAF5ahbjHa4kpYofKneqlo4pc25XjMIIQbBL1ZixmkPB3rGslIyVmzjpLBxYvyUzLFa3BnBctxjUH4J0NMOIurW6tb2H0wNUhFDFcQMEWWmGmEhsagKiLSIECUimSEAWaSFhEVUI6AmujpGbbcDAwOPOQbhGHjcsSyzYYVDLYZShY0URUJNvajEYsoub0zdRCteXitzJK6GDddPXEw4Qi9fVNJhSgdMEdHgEHREMuxUUBnEia0HjQnh5IhZNDGlL3N+qqFrIRVUnnHS01pn9LGBK6nGlRZRHFOLG4ZRjmWOOhKRkkYomtpBlXT0WgdWV76JIlVhIia7wiJqWU0iksBg920AnIEiyswZKFAiFRFickMp1Dpgsbsl1U8zslcGHncMwjHw2KK3a3RlMJxqcFCNKmy4dSMnZrZIyhTBlBz+0BZGSZyYVdX4BtfqoUTezHWxg6pWOOeInk8oHKTONqj6FyOUUl2lq1MzoQIakZTYVxurfKNTUY62o91An0yByNQID0OcydLlsfKcLEIrV6gYNyIbR4PLaSuScVUrrbFo5QxVFDLiFTGvuAVwvtGuf2y9u19O1wispp4QsSpIIKRFlEhXgkcRJXOVCogh2pyk2kiNji7fBh57DMIx8HjiuKiXRT1SKz3e0ll7YWPKKafs2kYwj5wSoCm5tyMxW/1QTolq3mvvoIgm0c0A1lwhskoWcn6o7c1T4Ku3c4HP8YALuQmAQJ1W4UqGViWjCvWEVTO25AKVZCzZRpfFeYJqnPScok4DFhO7nV2lXRxNpcUSJ4MnN0K9Bp2nwwMo6m6ZGGr7bvtv9zPuix0Pg1TBTBARaEpMUhNYkpAQkYgY3S0EmysqpCQiYKilD0W+rO1ldPk28BhjEI6BxxBLtuFeDctDib5RWuLrQtjIKadUPRzZR80imlPi2jc9MyvUfRv1NbVq85HAauEPe4XWzrjoOIqcVCHCG7Y2vvR4VoISBKYL5cSLsyeCnhQKnFo4qdA2ack03HNwzDgWyTX1M6SDOrza52mZZXlkJ4buCl2QMuBEPCroWvtYOzmajQad4tTgeyAiVWJStfAViJlURZUZACBcIClxSB1URIi4kBK5pQNmBiHv3V4B8YPsImA3P/2BgUcEg3AMPFaoYRSLoLBVK3ffBkKc8BKiuakXSMw5O9WwrFcb8JIbKWWLocDYBjFx+EKOaQMiJ6Srm1FfobW9V69fo7sSHb4OnD35SpHjQH1QwQMmCBdArfFwZG5wNuGNnBELK8AtWsWMxkR6iaMjIcfkwz8seKOLaEo7RhBUVtGQe7mt1+MaBWS9snMPjZBKzedZRl2qp4b6TTX5yVUQJSJSmG5ByZ2kogoGwIAAXESYwCkVEiKlKNQBtlRbYi/4UdnqsHQMPIYYhGPg8cGKbVT1gamloqSon2EaBjNZ//KWhzItDRzORRJnc4pW/4cbPan6Nqi2vgCFYyJqa9U35dqAHflKO5KwoCUeDVkYRf1F3ChBpTE1dEBKCglWgeAZfgQILUNb3KQpG0E2amhFFkTjlNJR960e6IndYJ0BI4uvG93Qem5XMg66KRehE4OqC1uonY8Va0OLqwQF6bykUA/V1YvMAJhFNTGRBVBEwULEQjVd1sqFqesfolAhuECC7veBzugzMPDYYBCOgccEfY0Nr/UZxTYq2zCqQa5SsIVLppzdH8rsoxFhsUrnlpcSySjuDuXa9+tKercma+1HXOggFJJ+xyO8SaNIMEGkk0iUpVzI7O2tfFEW1Bv/tXXC1xBV4xARDqjEw/tHPUk1Vn6OK4WO/siWw8vDiWDRMid3YZCAh5A6qtbd6MXXukWmk4P9Fqi7E6FBVb5IzcALxTrjqG2xKVQUBwtyN6gaI3WpQxQklBJBBESQAogqEYg0EQsUqmSdzHJc/zi2dmQDA48+BuEYeBywMG0gEl+p+jaiTzXycqI5pyk5z5hyrlTD1I7c1Sy38EpfKywySxCtJPVWAITIgZ5n1AJf3lC5fu9+Unhz2Bwetn0iVWV/463tdM8h6g5Xc9AxhV7PiOCIqjrz6EgH+imNS1QKctKx0X2iC6yE2NPxLPUgT5UPBCDx0c5jUT2utKYTsWRboWcA/bVA29rREstL1nMOIPhbpRstLrbgKW1z4eyomUiW/qoARUiFKBURsLEQmJm0QIlQRMlEMCYSD8CgHdWwdAw8VhiEY+DRRg2jtNzXWkWUOXnBjFTDItUHWknGlPM0xWjKOXpLqbmvFLVEbfuwPjOiWYyjsBaz9pWCpe5Rj7XaQN394dSCayPuvCTUfLVqVdGUo7btLoSg2STqfqrOLxbmUEjjHljyDNWua9PQPxRRxruyCblLMKW9lkulC4B0+bhhaLGrI90xU8RMqJ5P9HKyaGhbQKqRj7iyeiX5WFORymr6DSs6j82CagBR0gRY5CDHVmLfpFFIFAIlqIASCaGIAlytG+bqINIiIGghYUqiQoBYUEqga+YxLB0DjwMG4Rh4hNGbNrBmG+Q5KTUi0rENM21MU+7kjVSDLBT1NoJn+GZba9MFRNwL4MWunfqcaBwi8A/3gkZMoUkabmNURWcapGYAhWdSNBupr+pYCRquU0jTLdpARzrcNCqNeXR2jko7Tv7XYib9V5yCH5QFErRWPoXRkHZVpKaHqDSRh7zZRos2Odta338gipPXS1Nn4mgMVXMCFuGSFqUKzlELpHRhmEX8rO1eg3aY8YYhCmWoAmwiB5EIgYlUokqHkw/hQkIgDn1DCAAYKtpVuR+WjoFHH4NwDDyq8Pa/4xnBNlpRr8QpW1+vbgXNzjamNOWcmK10ec65FhXNOeWoIur5tN5Biu0UVevvTYUajgqgRRGohkJqLMD4QrSNUk2itcioemTIw/wtuuAO0SouoFMyfJrbNj100isZEl/R7xhav2LwHBUflKAafVilM3nE/nuxo7MbwFI9F+YM0RYe6YSaeh872aa/tjVeEYvUNRbkg1rwhILMAbUTlBo4WXEOtJu3+Flpt4Jqkzfq3T4lXQUN1PB9Wj/BqgoBJSZRD684Y1QiKiRmJrXYiqoSlELqEAUraeMYw9Ix8MhjEI6BRxL+zK8W0apDVLbB17ENW2Az5ZoK61QjpZQYCpdEvIBoaCjkvXpdUd9iTTTgr/sUA3UBj4kEzYgW1t+UoapMpFpjDbHt1ti0A1BtbXnnz4ApGQuq0XV26tyi4xl1iips9Gq76IpxwElL+DxV+0N062scd6hCQRkjlNTOzwwRdp3qIp241Dkagq20CEvEozodowkfa25x5M3oZQ10Oket2kod5Vg6SoF6RsG4iJ2igEHUwitFhEkRhTuMixQxNYSVhU3qaMRoWDoGHgcMwjHwiKELo6DjGey5r16qPMpspGRdrgXVyFNOiZMpHEY1zNjRfBtu/rA8R4ompIVuLJZBzXAQ7+F92UrrIHTx+t0VmCJeTomtefDEMh60yQHaN7A1LIHwgbqeYb2gV5Ihipio0UO6BpOQsuIZC0UEPfmwA+jEjuOQSrAPGxYPBVVxRjsJApWyEaARNqFmwnA/rTpPICcvVRbq3BYL2rcUOaIfPJ/ousNJzoGaR1RPpU2oQla0+J3Y1Jbuj8CJlKctW6zPp5tv1CUNC7IQW7jFqqGLKpFCUFNXlOxGhHbVjmNlqB0YeAQwCMfAowaKbBSHd/0aLlFmpswpnWYbOSWectrkPE3ZcmXNKFo7VUnWN4oRDmtLiLhKDGix9GZWoOXrs3GUSJql9va9TPZ0wlIXUPMSusOhNnmLiEJlAGhUoEoRlWSoikg1atig6RsiQSRUiwjCt1FUapylpxerwMppkcPPRUMVgKKaHts7OnkMyT8b1fJVaxPufohawqTFWZYXu5IvhO20TzBRVJ0k1A7jdC3MEnCLDC0mVPvGIktFo3THgqJUxQ39UbmhB6JIShHJQmgbAjCsxjlc6lATOWzLAuFgZn6ruzQmF16G1DHwKGEQjoFHBovc12awIPN4slf0agU2LFySmKcpb3JlG3kzRYGvqCtK1g0sMzMD6jU3/FU1ej5ZvVH2gQDU4fD11eWDsrhHwZNj+3TQxSuzCJg8ZRRH8fqOZABOG6BOMrr0kxgqVfRQLUv+AQu4OMNwLoJgGxZH6ehGzK3H1Gkbne4PAJDohaxdqM7EIe5NMTNpO1WvxB7Rq65Kh9EvVz46W0swtz7G0Fp71KuraEmrpyQNP8iVMaNqGz5WbRwRiAlLzTKm0j6jhgcxSKHsVFmJQFGrQzwz1pykRCQqWkAEKaQk9jMRMR1LIpwSneasq7MMDDzcGIRj4BFAvH/2bAOWhGKmDfa+UbhVJV+xjSmbaWNqzMNLmHPizJxSIrLCo4mCavjerfkkrip216z5I5+7Pl1tTWmvo5EC6y+mFO6N4BnqxbtUwZ4fy2h+iL7ldrbhhCAySiQsGp2YoSKqokVFpTIPrXONVFTlI4iKV7yM3JSFV/R6YaNXOOwog2Vp2Gm7yu2xQeouD6GzZwaNsaXJHRGeMxwxGe1jFt3PxYuFusgR+a1dtnFQlwWOSUfcscp6aoZqnCXVCFC3rqs2Vbyx2hvqZIvBYBFBqrXPBVXzKCqJAZAKQGy/LVskMalaPnENVoWx49RfzcDAw4ZBOAYeBYSBgsJXwV5ovBUStW7YNtNkZKISC2cbMRDJKSnnzOxdxRJhmQMbTWPzP7Yoh7dWXT9k1d3hARICFImo1RH1c6DaOlepo25WFs2dhtUB4WeANrbh0ZMS9EIqmTBVQ7Q4/QhJQ1REiggACYnDaErVNqpR1IpeBgmBnXFX5Bw4MdApHPW61FOKNBU3gFZbTHV4GDnz66XVLmMtatwNiLtdKDgH+u24ptBuTJ0WCkeEWahe4S7fJJgFUO91jWo1uaJqHYsiqH1B0hZb6X66ai5gBrkxg4lUvC97si7smYhITNAwtUNIRRUFYLN19D8SO/WaQjMcHQOPAAbhGHioUXkGqKaioFpEiclSW3NOicm6lefEK7axmZrUkRLnRVoKV6ModcU2iBmAeimneIdfHtcyltLe3lubEP3EI5YmrsUoWmjCIiwMrxZV99A1IhSaRA2jVDbRLJ9BLIKCFBWVErwjvB0KaGlxFRdIYquVfLRCX1eEUDplox+p6Luoi3nUrWkXTfpLGSYF8rom4XXpTC81TYOos5dSRCuu+AX1fKF3naqbSGI9bWSjP5NVYKVeh541Nq9Nt2qYiBvFcgIGJLiFo+ocojYAqLSO3xQAk8AIioqy9T/cqnTEvgfnGHjoMQjHwMOL+qIbRKCZNqyKV+0SJaeUmHJOOeeceMr5bLvJqZKMtLlG20jWi1vv24jmI3T9aCNbo9G94rI3l7RQ9yNOUOMnviVRZS/p7S4NNbYRNUZ7ngG40mB7rLyguJ7hvo0SVCM0j6pwNG3DqYZ42MSICKLAaNGmaHRmDlS+UYMsvarR0Y+WltKkBydbof4TibZxClcHkfEOjYntk+IiU+gNVUWwPuKbyQOx4zB2LFNjalCn6gFBNDopYzXYTsU9Iy2wUkWSGhGjqn3Eoo18OrsxTqSsRJbAoiShc5iZg1vtc51RFETWhz0snOd9zIpCpOlDcWDU346BgYcQg3AMPKSgrvlfVtrgnJi8tJfxDCcfZ5tpmnJOyZyhKfFmmty6MXmZr1pR1LWNlMjYBoeY4hGT1kx5axmvkR0J8WPUcIDWV15Vz3CpC1f6kijcDIgynABACqkBh84W4ekoHgRRSNg/g1BoES3FKUURR1CQlg1bQyo15oKo7rUoAqaKFlWph3Akb6CFTvrhgHYtNuAmjNYXncZbv/kkCVSliwip1DhL9FFC6j+GaPGpgDiYROSzKEwD6LplccsHKIppKCLFg2qQZ6VqHMOJRGcY7Wb0DtIrttR5Suw6AFAGRa1zL8WRrDKp/VLCszJDSABisATxACmJiLOwPmt3sI6BhxWDcAw8dKgvhdZlSV/UK6dENQM2JUtL2U7TVIMmU06cNkY7pny+3VhgJXmP89nqbdh2EjMIVtwrrBshWFT3RnSNUstxt0AJ13dcotpiWnw+FuMIBijA7OF51VBFmMOBGS/H5lQwPaP7lFbLS6QpHDqXUuWNjmpIcBGp9MKyTmwugEhRcVnDGIY4ufGEFCMfaB4OoGkchjba7BBV4Ij7SK2aeTVzEEElXuG7fko0bkO0zWELtXZ9zTmkemaUw1khdbc108X20ZGa6ILX9ZDKOXqRQ4/OqcNizTb1KJkFETyKo/AFEpGpU6REJCT2OwxdybOKyeMsCiEl0rmogqwymADMLng0xqFOjgfnGHgIMQjHwMOFFkZpgFXI4CjwZdEQZtpuJuMZ1bGROJ2fbTbTlBNv8pQiqmKpK9GdChPxcb0NMiECwS/63E5v8vwRD2aNAqLU0Qt77W0ZK9EBhiW4KDQxgSrt8JdV1Na61wzgDX7ETRBBE61W0XnuAijOLURESpFwjy6iKiZnlLBsSJQx730boXBoVeu7xmvVji2MG6q1jTXrB6jGMaqbAdHudgPebMNNGFWu6HJC3A7iXES1lppXz+sBkWknjTFykIG11GGj1NXPatyj4xt+H3pbxpJ1tJkr+8ZVEofvuGol5sYQqOWtqJKJHFPiQiSsVGguBQxVJlVAEpKqaoGySVMKkLl/RLSKR8vspoGBhwWDcAw8RGjtPlzSIJA5Q6M/Nkt8pc2UOXGO/lDMFnp+tk0pbSOYUr2iiXm72XS+DUqJLZKCLnbjLVL4ChbpCKrgmqqJmpy70NaJ2PIYa0wmZqgl1Yp6S8P2CtrCKLUhbEYJNWGjqhqiqsYkjHbMs4hKCUGjiMxzqcGUqnMoUIo4z4hIinEOKCxpFlgqHCotmlKDIl7adIkumuJuhkbRPA/EEoRbf201WTSuMsWtb5faiBxgtIAiJoXgEMU4B/mBRbqsix9CoXNUgrH8lTknaHrAorTXdSSj0y16shQOjghrrCSOzmSB+KLIqal5K0WU2dyjhEiEjbtg9829pdkiK0WIWVRFAFjybK8uDdIx8NBhEI6BhwKha1jT4j2YGLLnkLANGI3IOaWUNjmllKbJLKLJhY1pSok3UzbO4WU5Uq4RmZTY/Keun0QT5LGUoxJfrvnD37JRZfOOU1RVIxFXQyjVuqHqL+YaPgZgSWhqPkOLpKgA6pmuKhJJsEWK6FykaAuaVKpRirOQYCdSqrgBLUVrUXNzntpATUlReLVzdGpGBFOABZlog1guv4C2ImDRPtf4S5hkEaoIUbV8uugRMoStyFS9NFE5LVp3D2DxWuHgRZRsQW6CBFT7RdM4qqljzRyuxDKyckrkaGwjCEq1dXDUPxUFUaq92JMCSqLISMp6mEtN3SWByWxeq1RhxmORo/jRqNIx8NBgEI6B1x+ha5hI4ESjlhCtCkeK+qHey2viacrn263ZOCwVJae02eTm6sjOTswoWjtMYab2Fh3vwd0bq03wGqP1BTi8Gn7MlVXYWVhU3tR+5x8KTWbfsDCKN+rsZr+aC2Nv1haI8GwUUag7M1TV63oVkaLqwoZqKUVED8Y2gl6YIlJ1DrXhVmAUUbfDnRxaHRrxXyUYPYdQPaIdq3aMFoMtdKFRSpTqxMgYqbGVmF8lBlpFKVSJqER/Z9T9gxtRAQDSPBxmp5ToOm5VuSNMozBnMKonOJSU02GR5awuJzaEhRapQZe/srxOLX0Fzd4a5c41gnLR0xu8ZJgCKSXmQymASPxU7LdlgTmGmuZR2eyo0jHwUGEQjoHXGb1pAxZBiZrl1rFJioSUKafJJI2cUkrnrmoYyXBtY+vyhpX/crZhy3MrF8ZLuhCsIsLxfYwj3qEJAHF1GNioNw61BeLYbDg8ALC14sTWNReJCIgJYrqGaG0FPYyiqmKmzqhRXiyG4qkoMs+liBQpIjrPswTVKJVfqC/TmzaKEw21blOMxBjF6IpuVGLRMlxPtVZaP1bTwhqK4BVK3dlRN7cWQWutc7z/Q4UoMns6OkJREN3NGR5G8eJglWo0bYPcScrUDowr0yPlyFlBq/xRHSO1qzZcyz/686e7jvaTjHe4LcV+dQwVJaYiFu8TolTg+URquSpIwjTPQqRFhAggJrcAk0DZjUHhLNHoVXBIHQOvNwbhGHg9QdUPAbhpwxkH5ZRqGIWZtptchY0Il0w58WYzWY7r+dlZi6dEtylTzrWrFNsXe2aKyRstlmIMQSPm3heD0k7Jj8MmAMxkzUNM5HpeNTnWBuOZr2odyUro9fH+7VTDAhwKbbW83CVaLRlzkbmYM1TnMpuHYw7OMc+zWDBFutiKOzYin1al5r7aEUpkoFQPxiqqYiP9jTtuuqif0bkntMoPHppyBUPDvaE9+fCbYM1+RKaqLhH6B3eygvGSPoyCRj5c/BDnK8SkEl2lwdwlrcOWxjn6qqJ1sCML/Yj2p157e0PzukZUaRmW6WJJLrW58EIqomBYfopVRyVO81zALFCFkDISZhFEmqwrPQpWqIIURdDdg+aMHZxj4HXEIBwDrw+iKXFhgyOMYiJEioLlJk1sNlPitJmS9eZ6vg1zaE7badpuplrUfBN1OKYpW+1RZkpevJxXfcDagYSroKsKGrEPayIZDESRbYBr5/JM1nbZlEg8qf1rkLMGdgLBIAlhg6JyB9xpadIGTD2vVUEjwURL8AwPrJTi5Tc6qlG6FBUTOmqEpdU5d5dGUzUq2ZAVpbjHtmm18mpWfcd2qtCa6RpgqaMI3aNWQrMrhuACVics1CltNLGnGtYpDbN3nGaIaIulDUVApd7p4BzVPELLk1idMp0avVroWJxz+yS/YBSnygzyYmAd7chJRWdqXdsQ0QGFxKriKhHNRTTynthNyl0gaWTMDrzeGIRj4HXAKhvF5AYrVc5kARSOhBTvGMUUi5zS+dnWJA3TNm6db3NKkZySNpYEm7iW3DDdJGcvJxoH0IqJGqXQyEMJcaI9nD1K0rJnfSPMtWWp0Rl0VhB7SVdVVbbeyZWEzQyKzrRhLUgkpLiLs5owSuUcIqXIYZ7FB4qozCKllC4/pavDEdGUatowemHVxrzTNjRm8UBbomZBjYsVrKOmydarF6//jcM0UmIsTaMLt1qlo/NttI7vKDKQnaCwx1MQmgd6e4cxYF1xjjXv6M7h6By7tJSoKtJZOfq1Gr2KnVfea2EsAoSJlVSNeRn3sN+eiHjIiOhQipk8RJHAIkJeh5SE3QBMBLFL0KS2V3Y7BwbuC4NwDLzWiDAKWqoIvBs2Dn9oTqlWLt9up8zJSohuN9NmmnJmG95uNrlzjG6sLEczihITTzkh5BM0WgAyk79bLhCyt79PVofHKowC0zOon0K1qKg3MjU+YZxDVUQZKBZDoaqge0MqsbyX85IaTAnTRhEb9n+leHJKKWbpmEtRVfsspVg1MF12HgtE//W13sYDJhlXwQ0dvawQnhHtyAWFLlInRCrGEe3oM1MAdMEUApEqs7W6KgzLoW3RL3T1weokioBKDXo0ElFP4hTpODrT5UKL+EpofHE+qFzAAnZOSImoWPSEVItMiWcAkKhXyjPEbBwEnc2qYYYhIbsgkQ0UYkpkDg3WMfAaYxCOgdcOS2HD2/Paa5oV2PB+X3M2nWPKrTMUs4huN9noyK2zM6sZGrNaEqxxl02erHGv3aQw10yJrrPWvhEI+TkCLtr0jEo4qkzCbVZ9IVcPmIdiYW+opAqhaFIQrgATVNQKiUr1h7oDtEQwZZH7GrGVuXiR0YP7NoqIFR4tXX/03aczoNeNZxwjLppq/W14GZP4MkoRxAQKiSvI/Xb6YIqSkPUCbwRFFWSCBhFYWpWOqna4lbSZeHzvzoO6gqRX8AxXatCzlLZkmDevJigLFmPCTFSe9SvEkSULVlEiwgwJp2lS6wjXnRxFAAUpCCyiatdLoDX+1BUeeTh+CANPCgbhGHiNQOEA9AQEIiJKbJ9MTCmxlcrwXtamXPNdtyZvbDfbaTKSsd24daPmwRo7sd7q8yItBZ77Yq+UHAaDmrkaia5a35GpNhbUswpbK5gHcbOLukwCmCoPVWVr3MVe4EWFQdZzigdTYN1+Otto5USDZKhrGMVIRlM1LLAS8sY8W12vIocyV6phxb5qSq12bOPhREtZQWgeVBkcRfWJ2p+eR080MocsMsJo99BcN0JE7EZRWzPyalUqayFCJO+aeKXBeBAhlWv4QvVlnF6gUVhPgcKiN/v+Kyitai3rwkEXKLH3eGO/m5zmIuY6YqK5CBEV+4GRsGhRJWh0Qguq5984B0LdGVLHwGuEQTgGHjhaJMP0hnBtsNXgIq41QBNTZ9pIORJSnGSYPzSnnNJT52c5WXcqi2AKN6OoV/TgWpMSiDSEcNF59mRrh1VBHLEStcTXhbBBPdEwkUNjy55sYu+U1gsoACu05bqOb81f3y1N1SWHsugPxdiG1CQUEzbMrhG0wyQNKaWIqplG3SxafRtFau7rg7/PrwKciHl+T0gb1d7Q5bKo9XwGDTcGEM6M6gy17BWI5b6Co+Ra5yEl7kSOdgCIeqi1xpverVbHMSVpushyiY6CVCxWDW3FFAwFiCFKYDE1TcW1DbW0WLBCSUDEBQK4Z6XYtTLvrahAFKQElUrXWnd2j8bvY+ARxyAcAw8WwTSqP9TSX7n1Mu/1uGoMxfNNjIKcb7fGMM62G5c0QuEwFSOndHa2jawWsu7pQz5h0zYQbgA1cVpdXmZziUbURLsDNnDzh8aLcfNwVKkD1WHgqSYwSVwlrIvNo2pv8VS1DX8JNYvoLGJZrx5SCW3DVA0zZ5iwUUrpAitu4OizUaxmBx6a6Mk9IVp97RweiMvcpKQgEoYWf3HfBrUeY6n2WdMN2K11nSMIozI6P0dYPZfJsvVYFojR9vNpC+ipkS7U0twci6QVOw6r0U4KVp4hpBAY63CfM5FSwQyhSLOK357/FF3M0ejpjbxDXSx8sY8OLR14ZDEIx8CDQpU07L8qbBgVMEensQPjGTmnzMlSWy2Mst1upmAYt863OeVpGU8xb0et8VW7kK27TcwtOsIe+NB44Hq+ZZcqGNo9AJj2YpO9VBgAaqZRqCsckdGq1uyJKEOFlUSYLAOmdRNi9sNIGKmVNszN6T3Iz3M5lCJFZpG5qRoyz84/DodZVOfDPEtRqWW+3FKqaiGCRxsRY9HIeu2qd7TYSjV16ooASEgavJwSwZQ6qxXLqvkpPedwSUWje9lFwkkb6CIqp8MvvdFjNbWCjllLZPAaVcrMRZTYfrCpkJAo1WMSK16CIlKKmjxCqmqJK95Djhtb3NfRdZ9bO7MbGHhAGIRj4IHgyLGB3h9q9tCc2FJRUuIpTxYi2Uy5KhnbzTT5wOZss6nyxtnW+4O15bkFU1LTNk4lmGh0LtoqOkXWYl2sZaN46IRA3XBnGkUlKME54DWoLUdAiJlU3EVqykb1bQgsLTV6mTd/qJZaSLRIMWIhjWQE7TCdQz2wop6uUiuEvRY3+LVCtXZ4+TQXIFZNfnN4VA8Hd7myDO9pRbriYMxrzoFKSlou7Gme8IrP6QTt6JQR/631hFjJi3rB/ch+Ztb5G6kg8UxKIibYmchBsC54YG4QUaUo8QLUn38LrgAYro6BB4dBOAZeZQTTcL89olcU71zeKm0krumvKaUpe+6JeTIq4TjbbLabybpe2242OacppZQ9OdZLmDOb7YOoEQ4AFrXpn5vkiSFaD9ADDqG79GfBXMuUg6NiWJ1SU1dqPq2G5ZOgzArrGFalbtwWE4V1N28XqBILAMWLksNYhYgcopLoXGQu5dBconX67D3BFsuo1ceMbVSEd8O9HYt8EI3uyqIh7/pP6SQNIhG1kvJmvBEBE4TdRho/FY/n9KtHmEIj9NLV57jCinElPwmCdBSe8Q110ZWFzmH0QwGyPntUAVaIVyIRiwupMJUi7t0Qy8tmURXSQhokF4icW8+oCqHDTSujJunAg8EgHAOvGlYqgSWG1FQUZkrsia+WuZrYoyc5+bALG9O03W6mnM62W1M4ppysP1iTPSwnJXGycqJGY1LiFPXLWyaJi+ThO9To/qtFQLBiGy5mUAujMFcfaVM4TIZ2wlEzYEnJC4ZLxNfJyIWlLkYaLFkqisVTFGS6xWEuRcrsvg3picU8l3meTdWY5zLPNZLiHo7HlWr0aJbSmsbiZlJU7kct+cKpBoVNmJnE6r2KMsHKh7M454iklZa/AXTd1qNZRe9agbRiMePYyLF2lZ5ckfyU+1ASh8nDKpt5QgoI6jYOgogWOz+x4nNiNf29FLqSE2TA3KjNJdPOdkgdA68yBuEYeHWwrLFBROBgHJGhapU22FNemVPi7cY0CwuUTObSONtuppynnM4205SzCRtnmynntJkmd5Uyc1g3LFhTBzyEY6hP55oN64q6wpXn+joJAMZeUMsyhY2jqiZxsgyzYrghA7AIuorAS3maxSMe3zUIQOYStepe1rnJPBu9EAXmIofD7NGT2bnFvo6WcjgcRK2QeQn/aHkN7u/DAw1jR3hGWzwFQFULNBJla9Zr7UvWDRwCsEfEqo3DPyn4h7awS91RdFi/4guNUCxIRPzCFg7jm4C6Hye6Hm1tK248spCK56p4eIUEYLESc4WEVNS7fxNSVjWaogqYvUhJWJqrw0NIVcipl3hg4JViEI6BV4o+hoK+fmh4KXqqEcEUmsLnuZ1yTtmMGlNYNKaccs7GPGyKKR/WMaxtJDHnnDm0k7p3qnmwTdtoPW70FtHaCETkxyMp9aRSYoBSxFM6rdt66mhlu2D7U3g1TIUyxHo9jb2IGtVoZb66Sl9FVA/zfDjMcymqMHpRRA5ltnLmh3kupczFdI5ZisxlfqDC9y//+l9QRKD42q94t3ZGlWX5sLicqh/91OcBMNPf+tEPP8DDqiQu3I7oXR2hbdiNrkko8OFqi3TO0YVUYquhJ3S1OOpuUCUO3z9hwSHWRoy7n0pXv7SLqhyxkkj2QjVzKEDJart4mVHrPJaEa0gFCiIhYVWYEFLCyCwi5mcSVbYEFomyH9VMqnHuQ+oYeDUwCMfA/SOega7uNm0jsl6tOHki9gFm4xkppVrCy+lFSucmceR8HgqHd5sSi0VlDvdtVOtGZTZxJBHqtyLlvbZhH9Ylub8VespJlNlo/yVOCM6BONM4cYqWSU2ytjxYEhAJtVrnliVAaiJH7Z5VodDaPcpssRWLlRjbKOUwl8M8h8hhCsds01XEXaOvNt34xl/yC4vI13z5uxX63Au3VfUDH/2kqn7u+RdV9RPPPNeuYsAO4d1vf1M9mK/9Oe/6xvf+Xe94y5sA/cQzzyfm/+WHf/LVPc66a0JvqNCa0GJM034JLlF0nKNOsZsCD6n4L0UEYS91qwgAdFktRnQoSnQsNIsj/YJWM46YyenV6ur9j86XjJMhUiWwkBKTFiiZu4OViERUWEAQIWEFkYgIKxUIqagWgntBRNVsLgzr2TiqdMTuRt7swKuEm7HwgYElFlSjEo7IQyEgypRbgQ1KkbC6mboMlJxzStOUrdLX+XY7TT6Qc/KoSrNubHLzbTAzt4Ibtt/+sJatorY34trjOUWWK7CwiBIZ1YhPtOWoulD9/bLWLxcVjV7WPN+kVB/GYZ4Pc5nneX8oh3neHw6Hw7w/zJf7/f5wKEV2h8N+f9jtD/vDfrc/zPO82x/2h0MpZX847PeHInI42MLlMM/mEn0V2cY/+su+/iu/9B3PvXhbFT/64Y9D9WOf/rwCu/3+/jY45QTgnW95I6Bf+3Pepapf8rY3f/6Lt7/zBz74ah1zRb2dXfDCb1v/44yfitFisAlh7HIYV2uz+Y3sx0xNq+NaHNc0vPjBo//9L/4s0B1Lb2+qi4C6nxy1wXb83eprN0hoTNE/jmqJmrKesGTd8XjvfWruYi8up9JmeVFardzDtTeEEboJWs43hpt04L4xFI6Be8NVVCOeyxRUg71s6OQ2C+vNNZJdc87J4iVONXKaJhvI05Q2OeeecKRkfcMy82bKRmXMGmJPem5VuNDT6PqgpJaG0Dk84O1KfcYnZjS9xKf2ebAIQ4aHZkRFlcnSBUTdtlHMpmhL2r+qZ5ikcXDjBc1FyuwVvYyymLZxOMxFjKwc5rnsD/vimGtL8Arxv/uG9/6cd7392Rdu/+iHP/7xzz7705985mK3e+WbBXCYC4BPff55AJ/6/BdzSu98yxsA/ENf/7Xvftubn7998a3f92Ovyo5Qwyu9hFB7fEW9Twt9wt7tASvJacZgwAwcekLtQFeT1HhFEM5q5AjHw9IE2rON5bSjV726na7weSxZ82S7LUcBVOtKVpUgouynTaQsoXmIzJBMySqjW4SF6qwilFiCuVDrBgjmJ63Rwk7OGbRj4D4xCMfATbF6QeMjqmGGDdMfiGjyGhtpM2UmsrxWC44w0ZTT2dnWZIxbZ1sinqZ0vt1MU54694aV93LrRgRl6rspc0tL8aPUpnFUHQItwcEX6yqHLsIxRji6100yDyli6Uo1/D3Qkw9hvYerenaKZSvWV26/fhSVPwAAh7nsD/P+MO8O834/W8qrs415DkvH4TA7DvPhVclG+Q2/6pe+50ve9uwLL/+dD33sZz79+Q9//LMXl5evcJvXYy7l0194AcDnnn/pHW9+GsAv/7qveffb33L7Yv9Xv+dHXpVdKKzCFWr5qlrQSpx9kKgSITJjqTp8KoOwFWO6l6WITFwjL/UdP1xCqzSTqy2hi9gKHU8/OfNoMfth+mJabcnWzbEzBmLxoVaWQ8RCLRAhIZ1RSMGU/LKo2GZKUbB61X2CqheDp943U8t1DNoxcI8YhGPg7uhUDUQpr4U5lL1IueeJGNUgIivPlbPnu55tN1NKzHS+3Vok5fxsy8Rn2+0mRqecieh8u7G1agnzlFIt3dGbUnsVGvEEdFGDowFZqxqtp3pmrue0cJ5GeKheAFshRAtLNdTOrFfVesC66gQEXnWj9o0yzyZglINnpniCiUIt8uIpKsVFjv1htsyUwzy/crbxW/7xf+hdb3vzsy+8/J0/8OMf/vin71w8WJ5xjLnIZ559AcDnv/jS29701Nd82Zf8hl/53t2h/KX3vf+Vb3yRWkFwd4fNoZbhIQpGJBIRoqKK37BjtcN+PhFNoNrNe2OzkYm6Opb206kzVwz0mhNZTgiJozM5t217lyuWkOO/SfuBQhInsX7s2WregxlzKSZ4zEVyZhEtBZRURJGElKQIJVLVIsIgEIlKX+mkukkH7Ri4JwzCMXAdVlSj0g2vGBrCRk4JRIlpyplgGSiJCNsoD+om0O3G6IgRi2nK22mygVtnWyLKKZ9tt+YhtYTY2mGsrQjASm440VkGO+KQ/SFI1KcxLBNgjaw0tkJE3t8bllSmrkjEUUijEg6AxFR1BYmCFcKWmlgj/AR0/9ooAEBR+cfhUPaHeZYyl7I/zPv9frffi4ixjVLmV3Iff9uv+4ff8ZY3PfvC7e/4gR//qY996uWLi1eytVeOucgzz7307Asvv+0TT/28L3/nb/iV7y2C//E7f+AVbvYE54DHVsTuX7BG171qGgYQFVua2mElN+0FX13f8rQXV/siatP9zK6WOFrIJ8aWvKOteWposWYdCvNzDX+Y99NKmedkWa9IiZPqDBCRiBJg/MPzY8kTZYVUlES0oCZ7M4AiwmCQila9x3zQTuloFCcduBkG4Ri4EjWwYE9XJoKpGqgRDUopESgx5ZyJaDO5ldOUCSK2JJTNlKecp5w3U7agiZlGb51vp5w3OW+myZwdpmzklM42m7TQNsjEj2oUNetGf8AhhrczOD4lriuHpNG5/4x2pMatAADMHF4QlzfCXue1sy12w+pVvKzGl6W/RtZrVAudy2Ge9/O8P8y7/WF3OOz2+91+f7nbWwmvw2E+HA6Hw2F/OKjK4bCf58MrYRu/4zf+mjc//YZnX7j97d//wR/64E/d93YeBOYizzz/0jPPv/TOt3zua778nb/hV743pfTn/ufveyXbXHMOyzpVaPQrS13Vc+76cuvlDZenIpiWtPbh5nzFZJLOdlwDDfWjDURELSaeMGSsp1yDXuXg2k9ukABLX1HLmTIRjrzoi5k2CisKSPxwjXmASEiFRFRnGDfTIkpkeVWsUBEv+i6LKmGotK2FmwYGrsAgHANrHAVQmqvBkkHMrQmClRKfciZC9WpsNhMThVeDz8821tGJqRrMfOtsa53OGwvZbKZNzlPO52dbIuSUa2aK1duYpgkKZqppKS5KdNaNk4+5ziXKoWxHKIXITsRDMzbQRYtsAU6pPlztaSoKwMs7wmsdWLff6pWXyMX60DbgNUYV0Rk91QPucl70cJj3h0P824vI/nA4zId5vn+28f/4v/7GL3zx9rf97Q984CM/e+f1VjWuweeef+nZF15+25ue+Xnveedv/JXv/eZvf0VSxzHnWMga1dDjebWRfBG2CB91v6TRC0+3Ta24Orwz1kUs5ZS8sZzQ2UiXMxvpWCglq83FUmty07GNkGcIrGRlVJioiBBA3s89CUsRYtG5FKbEJDOEOXkPw0Ap4j/MIpyoiBCbdQnM3reLNju2SzxD7Ri4HoNwDDji8bZIz6tqgCcQMnmGSKvilYiwmSZTNSy8UqkGEW+mdH52xkSVZNw699Fb52fGV26dmaXDiopaJMXqnbu4kVOyg/JgSneEdvDSTIKuG8ciMEFGowuVagutSS6iajpNkA9uSbPewNRERLeLEimsn2+QKrFCRJmVxCQYqRmGnisr3uP8PMv+MO/2884Ujt1hf5j3btc47M0hWoqIHg57M4ze3938t/65X3+xL3/te3/0gx/52Zfv3HklP4zXBkXkc8/ffvaFOz/1yWd+6S/8qp//lV/2TX/lu+57ayc5RxQH89bQBI+akyL2Il9TVAQaHh6r76HmrzTa4RuqjWvvEVocSJcru1YyjoUNOhposyLyU5dYLEOIhp+CdpBCwRx9FZOwzkUIqqxzgQ2YQFfIrdCz71wJUEaRQuCapyLiNdGt9zhLjgn25iKPtuMazGNgjUE4BoC+be5e8N0nQV1LHB2kOdvwquRsSSjMdLbdGIewEIlZNKwD2GmatqZqTNkGNtNkPGMzeRLslL1rFTOKTnmy+hq1V7aqtfhRw2LvEpWdfEYyYZy4vQyGfJGSkY9QNchPyiiLnWZNMLFgirntbNvedQWplXhM3jEHE2vQDKMi/gYcURjnH1KlGHsThRaREiXM57ns94f9fr/b7ywx5f7u5h/4V/7ZZ55/6U/8xe+4/fLL97eF1wtF5AtffPn5Fz+mqr/pV773z78CqaPnHCDv9qZmpcAtGG6/qBaNaFxJye4lwJqIq1sSUBEkrvYJNPIRUYWwVZyI6MXAUZxlsdips9Fe1+j9HL3CQpa1Ui0dpDALqf0cCSysZiMtLCJKmYoIExUWKZbiIkU020+dkhpNyakU4ZSkq3TnmcVGwJ2T1esOYJQLG1hjEI4nGn2ma3MyWI4GAV6RwiqHeukLImxyJiJzWuSUKlcwm8WmWjSmvMnTdjNtprzZTJtpYqKnzs98NGciunV+ZoGSs+2WgO12Y2KGlRMFYHPVwh/18bpIOSHjGzj1jmnLt2TXDjklVTXCkXpCE4GX6kg1thGBcCMcAmJFEVHmJAoUUXRbiOZJilo/Kf5vLrv94XJ/uNzvLSd2vz/sD4fdYb/b7/f7/e6w2+/3h8Ph/hJS/oPf+U9vpukvve/9f+dDP/3IsY2KIvoDP/GzH/nk53/Tr3rvm55+w3/1//0b97edyjmMA3jGa+vXzRWO2kJ6uQ7v/hfwZptElAiUQswARJFqSAbhNrUtgVZcg1afNafllKvj6Ed8rQu1M3RotXS4XGG0g8jiIEpFhBOJaoEwEwsVEmFFAbOyUCFlkULEJMJkBcSKaAYp1LrbJRUiqMD0DVFNDGlJxSEk+ZFjVCkd6DEIxxOKKmkgHAc2sStxQYB1U2JFNdyoYWLDdpqIyTqON08oM5+fbZkoBAynGsz81PlZfNJUKUjYSKco/xXd03P8x1xLl1YisHzC2jErtwCKqLqTtDu1JteEQqOq5ml1jaPFU5JRLhFxryiivwlWERU2Mx0pJCmEwQoUYWIiqUfoJR1FBejDK8WCPYAqohppma2EeZkPZbZCkKpi3Y3dE/7gv/bPPvvi5d/60Q9+z/tftbJarxeK6BdeePnbv//Hv/o9b/+X/qlv/KP/w3fc33aCc3hb2CaFB7QZOCI4oKLCBHgZrZqoImIdIEOhRME5AKAKGp2P8hRLWFCKdarrNbxifUInslcqTe6WdNpBsDgIEYsCKgTT84SIi7gJY56FWecCZhUJ2YOUSTRhLoXNWKqez2J023udtXwtEQ1Wd0w7OrfMYB5PLgbheIKwdGn00RNrc8ExxOxGDavhZV4NExtc2MhpkzMxu54xTdOUmempszNmDkoxbTcTMz9164yJN1Pebja9XbQWNbes2u1mInOkMkfxsEY36kH7SUTEGujeMBXJxQnroc0NGWouDVrwF4661kSUU6Zm5oiAeXNvhLzBSqJWnzIpqVJKWkSZmViJGEQiMAOJWudZ6kWm56jodbnbX+x2+8PB5A3LUtntd7vdfr/bHebD4bC/D3njP/+3/4VPf+GF/+LPf8sj4di4Ib7wwsvPvXgHwG/+Ve/9c992n+EVt95Q18u8p1OYwmFqBzhMoK6JgFRU2cMr9muTcAJpeIcTE/w1vlGaNXousIyhdJ/1r7NOPMlaljwDGn/FR8tRZVVkbMl0D1YWAqma1YhJnENnX1ShpQgzFVEWUeVDKRvKRcTyZguJmZZMNLLsFRElZjEntXrNPV0kjtWolHbcY+DJwiAcTwSOQif+iGvNOYiZPHCCVsXLjBpTShZDmXI2DcPqamymiZmsOqiRjORsY9puN9spcx3dTJvwbTDR+fkZxwZr92wANtMEwKIzCmROCk3MkdsRD1cXN5bJKd1Jxiclj5tQzh5AsfroojqltOAz1OqN2ubUOYda2zOLiEgha1ZIQayAONUgqgUt26NWFRFMKUWsM3rvD71UYcPqioqKbX+e75Vt/NF/918k5j//rd/3Qx/8qceJbRhE9Qd+4uMf+eTnf/Oveu+XvO0tf/jPf+v9bikcG840nB00faP5Rr1zNo1omjt4rNCFgN3A4TZSNgkBQKup3sIrsWc/iN660dOLjme0eUuKckLb6EDdym2S+1ZU7Q+Kw+dJrtIIUyoqRCrskaMiHj1hkkJURDaURYTIcluUmbqiHcIEt1GrS3PaCR8Le0c9i3YSI9TyZGEQjscZVNtgoIoZNq2TNJiA6PokUSS7psSR9ZqsizUmyjlblGQzTZuca9DE+MTZZmLmzWY622w2Uz7bbuospxrMVuBrmmq9jZxzMmHDjKhV2qhcQFXNa786ueVgp9pQn2LDoWbUjS623+2HAErJMgOJmGGBDymqZOW8RISKAAItqiY4M5MSM0yv9lRYUjjVsMBK8UAKipTLy93ucNjt7d/O5I3Ly8v94bA/7OZ7LLnxX//ffztR+tN/7Xvf9/0/fH8/kocfovrsi3f++vd94B/9pb/wX//Nv/o//XP/871uoZoZj5NWjHoEg3XfqABc+/gliIJC5PB00DBwqJtEUAUFjchNtP6K/s+wVzVqOKWS3CUvWVGLq0IuldS0XaxyWmrqKkGtPF0EWaCAIJEW4xDW1b0V+xJiERYrOWpmUkqsIlpIhLSIJqYiSqocZlIrcirBbCRklqp5NMGjN5bWCQOPNQbheAzRXvWBKmfw0s/Q7BGAGSbMq5FzMqODVRA3BSJIRmZmM4Qyk8VHtptNYq704g23zpn5bLPZbDITn203GysnOk3MtImkFdvLlHLOVtcrEWHKGUBOSdGkF6MQqkrs2SUd81ifKOIMLYbCNpCzBeOzCSeqOWcmFlWrJCbu5yAR5ZRsy7V/lKSpeN+bUoQVxd6AWcEuCqkVsaSObVhnrqotLeVyt7+43O0PsyjcseHahlje7DwfSlQ6vyH+xO/7ncTpv/uW737f978KpcEfcjz/0sVf+1sf+Ed/6S/8Xf/0r/5P/uw9cw4gUj00mAWRW0dV2WMQzh5AERQIFU0UBETGqW9qyWGIGsvodIhe3jgZTzme2+KG155MJTS9HtLTmNhKO+lYmX0qqWomFlFiVdFCanZRplRIiSizHoowaalcxAIuRVJCEbEQiogqQ8Q7p2XAvEhkCcYrztEylMPhAQxv6ZOAQTgeH9SnDvVRBW+DAQuaRDlwoxcpej+xAMqUclhBrZR4ZiYvzzVNidl6UKs8Y7udttNUlYyzzYbZSMZ0tp2YeLOZzN6x3UxERji8Vpj1HJs5IaiG+TYUSJwAZU61eEZ9hHacowuxdOKNKCz9xIIpzJxzVlUnWGFEDQMHG/+yf+yMAYAHRZI5/EWKqJAoSkqwQl4zqfWJ672RrtmG1jJfl/vD5e5gj9F5dpfo4TBf7naXl7uLy4v9Yb/bXR4O+3vqA/a/+/3/6sc/9+Lf+IEP/I3v+6FX4+fzCMA4x1d/6dt/9z/za/7jP/PX73X1MHNU50MXm/MsUEqMSjtqMMXNCkCtly6qVn406l+5M4SiFpZttt9xT43r3COS0UdU2sCSfKyiKoukmOOB/li8RzpttAkKVhIjDeSlRY2pEykzFZENk4Sfw82kIol9WFmLqLqZGiTKBFExGi6imlRUYb0cWn5QJzBFKnIwjxpqwdA8HkMMwvFog9b/L1JOqp4RoQVrcCvbSLwMnViXrWbwnCJ6Uk2gTjI2zjzONpuU+Gyz2W6cc6RQOLbbTSJ66ta50ZlbZ2dGXCyBtiooINpMlWqwKrjLGkGLpLRHr+f+o1KrxjXs2zIgOf5rAZowwIIZzP7Ay9n7IU/J32E5IUo321OZRVmEPMGErE6SJHARYxs1HNNrGxIUZLc/ALD3QstJ2e32l7v95W5nua8i5XA4lHm+J7bxZ//A70rT9J3f/73f+bdeaf8jjxaef+niI5/6ws//ymd/92/5Nf/xn75nzlHRzBzuYvTiGaJgT7LQGkzREP/de2o+jzbcIiw9U1BFs4qsd95Ppd7SgcXPG+2z4w1X8I82sDBX1+Ox36gXXq0HbL3FwlNnIQxSNhnDgyZzESatDKPQim1IYhSx5aFsTlKyuv6W28VqBlwS0RrO8uvpF7YLtQChMw3N43HDIByPJE6EEpZ6RiUZIPI65F5Uw1JOrHynF/EkIrNo1NCJKRBBMiiiJEEythvjHOfbLTOdbbcphI1koZbNdLaZiNg6TLHQjP0jQs7ZkkfMsWH1Nno3RTwSLfs/3BtxvtXSUclVhFEqXwmuQcZjlKcMBZjBBOLGOYirvOH2CxFMk73wAoRSrMhAmovVD62dtDELs5piYttRN5NCYP1W6OX+oEARtQzY3f6w2+0P83yYDxaj2c/7w+Gw318WuYdgyn//h/7NnDd/7H/4jieNbRi+ePviW77nA7/2l/2if/O3/Jo/dI+cw0WIvhqYhRZCm/D3/9q/LMLnCw0LpFk3XP+w4RphiciFbV9P9l7fZIwVh6C2cBu4IvGlbu2qMazHusAORXCJoKqJSJSi45WkqkWVLWOWVMTzWYoIcyoiyXQO93b4KFkmLVsvQpbPEmzDhi2xJannsKjvz+hOH2qhcJYqEGU8UOWOQT4eaQzC8Shhocl2Yga8ZzUwMQgclSXs7d4qeFteqFUFzdkdoMy0ydlaZssf2WymzWS+jcnEDE4cPGO7naazs01iNpJhPbRVhcMqmp9tp2mamCx7JVvV8+g/1spguEUUoW1UsmE0groohX1GwwBVZWJ7XFZ4AAWo4RIweS7BlMmpRv0XnMPqWefsr7FxgUPeAESQEmaBKoh5nhNIMYsXMmdzwmjcCgBzkagrisv9AaAiOpcyF9ntD2baOMwHET0cDhe7y8vLy8vd5b1aN87Pb/2Rb/62b/ueV9TJ2SONL96++Cvf82O/9pf9ovtYt8Y3jlIlvCWGlzA3i4GXMzf+ITUgo03bcKKi0UBWa8cyptIfw4JYUMc5bKB5SdEPELAmEdUJEU7VoyUW2+lWarvQKGJmTb8ISMkST0RVSBUq0hQOj7m4tsFFhIiIxAykqpZrazlZVrfG0miNjqhVorHivaLqFXrhdF4XnGPNPADXPDCYx6OJQTgeARx7I5c8w3pw7VrgTsyw0Zy8hAYRVcmh94HmxJvJVI3J2IbJGGfbjSkiZ9ttSny+3Ww3m5zT1uUNdm1jM2VOm022AufbaeOqxpSZaIqEFDsR22BKCbCi4AxVD/l4lSZCZNNV2lELCvkyFLaLSGdFDZcwQxXTBFUwg1ObDj2tcBi3KFKfb044RMGCWUACIKHYBE7KLMxCRNZdOUBQ76QesM5cyPpPKUV2+731kmKWuovLy4vLi8N+fzjs76m3FGb6q3/0//Wf/Jm/9q3f9b2v5i/sEcQXb1/8/777R//ZX/1L/sy3/kArGH8zhGofIgfVV+jmtHCNAm4v1ciQ1lrEM1pHXyQEg5oi4haFiAy0VrTqHACOIyZXDiyXb6dC66H12BV0xykVxdlHY88Uqg6JqFq9O7Iyu6ZrqCa3joooM3FxtpFYVd3SweYgtYzcCLKIqMdfjLhYz0TavFl2IesVPql5xOUcPo9HD4NwPKRYxHFjxBtf9qdT5Rl9vgkRZY5OT5jIi4QueEZmnqacEm/ylBJvpiklNotGzzOMZCTmc2cbW058bgGUs8122uTMxi3CN7qxUhzTZF3VT7Zfq7RB3jurpeCaLdSNJYgHdeUTiDAzGruqUWjyYQ7GYAyjsgrr6MKHUzc3LRhJ1TaqV3QCABRxjUK8j3mgoBSASCkJJGkRJS6mcJBHUojYc1VEcbnfi7MNc4mWeZ5d2Li83B/2+/1+f9hLubeKon/5//17f/Ljn/vuH/yRV+139ijjxTuXH/jpT/3uf+ZX/0f3YeboSp7bKKjaMKqwQZ6FEjzCYwFdSMV0tWgo0dKoqLaSUMB+40vnRkcmln/tC5LRhV3WpKOnKaecHMdqR7d6T0dsU7UaulWeaWdjnSIzVEiVIaoq3tm9ckuOTaqliAI2kBKXIgrlogotxZUSDVOqeFgFNtCMpbB82mAetGYezWHa6Ec/Y+DhxSAcDxHo6P/+P15YQVufaqFnIIImyQqT15Kd1hGaZaVa5og5LZj5bDOZkaL6MFJQivMzJxlWZvT8bMOczs82xj+Ym5PDklOsqKjFZWrRjmoRhffCCqu1oVCykAdTIxDkCm/U9mp+DqASDopVGFCPjKCyjQTrAMVoRz9a56qCTJNgMLk4AWmPYFb38c8FRayiNUBAgSKJW+EsEtQ0ErjkLi4a0yxaisxFLnf7wzyL6mFesg0p+8Pu5j+Pv/7H/p8f/tTz/+4f/uN3Lh636l73B1X8yEc+paq/57f8mnvlHGHmcPuo/7qCbSBEDrN7WM+rIWa4yRHhPIi0DlvZJQMT5K6LdVQtBLbfBZ9YDyyHT0RNmnTihhJyaYbqvhZ7qmvFdM8II/NdRzKwwN4ATJBIhKJCUbRUrRopq4gwwyIsbuxgLtJkj1IkMUoRs5QWEbN6KOCWUp8DL1NqXtZ7ZB4YssdDj0E4Xn+0kO1yxLM0rTwXPB2Du4hJhEuanmEmUPZgCm/MCrqZmJwQ5MQb81MwbyyI0kSL4BnM52fbnJKzjaAdZ0FEKtuoRThSSpNpG6ag5GSyCgE5JwujgBPgzs04xyXbqEpzJ2y3d8CVsIFO0lA0YWMzQYHF7hLAQAIUMILC3ca5XntA4h1JQIopIxXMBVSgsKAJWJiVWMwxUuUNa3vUNREtzjaKKua5iCI6oN/v93uRUkrZ7S5v/iN5zzvf+qY3vumvfvN33Hnsaom+Eqjipz/z7Gc+/+w73vL0559/6T420Le+2tiGtX3RsFlT6KRX1TuRBaKdC/OBMWSru4maJ9tEu6M9Akc0olo6qKcFOB4+oh2dO6VVHTuiPOYwOV6b6on7G44xczek1MCHsmUFs8dHLIBCVedQDcGDqSawpOUCRl+UyT0iqppg4od7O0Qp0TXMY+X2QKOOQ/Z4qDEIx+uDVcSEOrJhkQWEX6FKGVzZhhXPICZu5gxL/rRSFhv3Z0zMlFOapikn7oImi0BJzvnMMlaTsY1k2satszNf7KzxjF7b2G43ZtLcbia2AArTlCcm5JyJiHMC4EENUEQ6mojcsY1o/uuAfXLMtZjIKnqC4BPWG30/4AwDHdWwifZPg2echNEOARScMM1ONZQgQEpkCbEub7C/W3qv9CSq5tvwjtnKLKqHw2F/ONy5uNjt96WU3X5/Tx2mfN3P/6o//h/8G//eH/nmv/6+77rHH9rjjxdf3v3F7/rRX/fL/57v+/GPf/gTz9x8xSoH1L7d2su+CQShemiYPsJZCQQ1US/g7TGaFnoBqvHI7CAnZQlgEVup3yu76FL57Mex7HLlZDxFvZYqrZbsNtdveMlUKOwd5G5oQiS41iSUIsoMCXqhqsEzFjqHqLJpgMmDL274sARacpOpKsw4smAeSgyYJbsyD0Qwq7pvVrJHkC8/48E8XncMwvHaYUUyYsSETB9ycgEwM+INmlN4I6OzUyspkbP3cTZNmcnrglsPJlaM3ASMs82GUzrfbsyqmXM622ys6JbHTc7OcuIp5+12M+WcmG+dbVMVPzr3hqeiMJ9tJsstMfnEYyhTBgg5g4CU/GFZiUKcceMNLVai7bOnIBawQFU1IjhiVMBGrTYoGbEwkpE6klEH1rfianBsRIECIkwMHNzVkSeehUimnPeHAhCnZI2QKqJLWMtMKaq4uNyHtnHY7/dSZL/fH/a73e4egil/9Pf+Sz/0Ex//m9/3JCbB3gQv3dn9nQ9/8p/8hq//g3/qHs0cq3bZpIhgvRr5EOpBEreFKiFaXNcEVMPJAe+g1byQIDCc1Cwrka4TZntV44htNPEDy9/uid9xFTLMhtnTjMjW7RSQa3weBE++CfNKK4vuzhXRSHk1fkCpqDAnERFFtZSq8Qw1YiGiZjhlFS0q1s1iSm7vKLGksCW8eD6L/U8KVWJo7ZdWg+WZ5Vc7ouQxsCp2DNnjIcAgHA8Wp0lGlS+aqFEzWmvBDFDPMELTsIrjiTlnEyDIlAzzaUTcxHlGSukseIaFT4xAmHphhMS4hX1OOZuNY8rZSMmxtsFMiWux88mOCjmFQ5PACRSsguDyRiUflUbEW+CCedSgSf+5oBrwYVqRiXQ0cD2ruOHdywCDCBkoCgGKEieiQpSaewPhMfUK6DIXgdJhLod53h8OVuOrlLKzrmEP+5s/8f6F//0/8uM/++y/8h/+55f3EoJ50vBjP/0ZVf21/+DX/ZXv/pGbrxUxj67ddSdHHWuVbaPJC0mjkzdEQaqMmtcSXogo7UFdsOLaLFbtHhVoHwuq0U/rJx1toUkb2rljaw1xO4omdfQUSLXutXq43bOSIspRy4U15qHJyqKbCbSm1FoBPyvUYbEVK4XO4oVK2WMrSKzm7ShBNJRRRACr7uoOU7YBKExZdLoY/GMhk56UPeISDObx2mIQjlcftP6/yaLkKgaqnmHMIsqAkvMKwkLMYMop1/7ipymnqmdUhmH1PZmnbD28mgM0TTmfWUXxlMyZUXmGqSBnG8uETZn5/Pysyhs5p+1m07iLxVCYU/AMMCNnt3DmDCJXNVJoD3barm0sFQ5gwTl6W2jlGbauxhY8OFJDIT3DeKA/YwYyGJgURcGCnGk/E5EVaLBUWCvOUYrORS0t5VDmwzyLyv5wKCK1G/r9fnc47G+47z/0r/+f/slf/Q//y//Rn7y8vHiQ5/jIQ4GPffa5v/drvuz/8uu+4b/5i3/znlak+GqOT+cFQCgWNTm2dgsCeNMliuyznHomtOautvVu5tBFYgxQ+YfSUavfnhvdAR/HZo5W6XWNXvGopdnDeVKPZdkeIxTG8HNEy+w2buXKmyKlpea4MqWadeK9qxBERBXGM6z7t5reIqo5hA0zXJvoQbWbe9WUyEiJKtjTW2CxFxVl16I0+m6xu7XwznRujwiytPRaYJCP1wqDcLw6OCIZ9f3Ard9Vz6iGjBoxISLvOY24TzBhkzqYLMxh06ozwz2byfSMFDkmoWScbTOnaUopJdMzNsYzzs9yKBkRc1nIGyacmG8j57S1TYRjA8yYJqzYRupiKB7gWPIMVBrBjWT0n9VRFySlEQuqAQ4E4aBXT8O4IYxzKCbFLKBEzAKacr7c7VXBnES8UEEpZZ4lpXQ4lMM8H/bzfr/f7/e73W63u9zvdvdUVPTX/8p/8H0//FPf9l3f8+DO7bHBSxf793/o47/uG/6+e16zOjxrk9Mqmoc4T1SNiiCIgkPhsP7ZGQRV77yeajJLtPCmlLSoBlaCRQ9aTl4M0NGSlS4dnxJqaAgRSWmMI2gI6itRbXVrVKUxjbprE29qlRx3eNRkHlIoSQQ+xCoFQ9g6UtFCyuq5tex1Okz5cOmiREWwlFRqJi3cO+rhFoX9tbWYi/rOnaPEPbNRIEw2TWVaBVfWtT0wyMeDwSAcrwirBJMYcCXDFgiyAWYmNMJBXd9pC1sGkcVKLOOjlsmqfafVeIqFP9zvuXXSkJJ1rraNQl75zGp1BdswYcOISE5sjlITP0zVmHKqMRRLfsE0ITGIsZk8VpKTR0ZyzzOqV6OjGos0kJPPUrtU3C3cyxjo7J+vIyyrVqxuWEqZ6ACy/BRPiC2iHkwB5rkc5sN+fxCVIrLb7Xb73W6/m8t8c3nju77pD9x6w5v+h2/73sPh8CBP7fHBxz/3xY99+nN/8Hf+H/6tP/IXbr5WWEKrX7IPQniTbB5SioJUQJM3SK3z1c4s4VuAaR6+rRZC7OqY2oZoeTS9YtHTkmOKcsw/2hYaz0C1bdS3e43DaefYuWZta36ejYfZMXi0hZrVVrsCHqowm6dGMq2ZXzz3lVyfEBENLSRH9op4nXVnJGJdrzBEIwoT8oZoreQB2yYUVv8tGIlf+PB/eC33sHqghnLXssfCb9quxsCrgkE47g296LkMmay9n8CCYRiScwuqDCN4RouYmEliCo+G9dxqCSamSEzJ3BibmozqGsZUq3gZt+BIUXGqsVnyjJzSeTVzeDaKcY6JUtTI2mxczzBto0ZPXNswH0OvN6x4BscfrI3qkn/UBXoZY7XAw4MMFmwmHGYiBqgIOCV7uk15ul0u5yJzKWHdmPeHg4VRLve7UmYLpoSX7e74u7/m5/6l7/rAX/+b73ugZ/U44fbF/od+8hNf/WVfch/r9ukq8Fa2aQKh24NM3mhe0TBUhoxvi4kSR1TCpA4BEpHCtBAolKkLfHhdU+oZR/wNtCzWxV/FcfDlaES7yEG0qQAWCsciO6d7xF31M6WOc9g+akio0Q7AUkjc5mm9LnuUxLJaUh1WW8KlDhWxi6lFvBS6AioqC81DizRLRyUZTm/gFdPtlmiUTu1G0XymLkQ12YOcUy5lD1QJaOD+MQjH3XEULqmMg2r0xIbC67kgGY1nROcmXAtmsIsZKTETp5SYqbNlJLNtNiXDoiQhSLj3wjhETpbbusk553Tr/LwyjKfOz0zqMOZhQogFVramg3DKOU2bjRs/U+UZCSZvGOeobMODGhTPtko4VmwDS2JxPIrVo/JhhyXc5onokFJWkCoxcxGYvFGK5JQP87yfZ1Xd7/e7/V6K7Ha7y90OwDzfVKv43N/8U5TP/8y3/I2bZ88OAPjE5774Ux/79P/n3/2t/+f/8JvuYbVeV3CLKBCCRJgf3DXplgECQKLKANS7dY+21sIt8fasqNXAyEuEefPMdSK0VwWPjqnXQWpYYEktlvNjpRhfmSaDE1DVN6rcgdreHjGfeizUs5OIswRf85QchVSHaXQOF73s+nDNrTW64IU6uEoXpnCoKixppdiKrnloGDtiddViHMOXchUEXis2lBjPNYq72QIuId/UO1ivYly9EXN5hRiE4zROKxmo9KKFS6qk4aYMIHXmT6cXxMRk8ZMpp5rCapKG2zJySsw55bBleKGtPlBS/RYmY1QOkVsfKAu2YQrH+XY7+bAnyt46OzNbaOaUzrYeInE9I5JNpqnrcyR3fCLHVenZBsJdgdc79vEgQQmcALJw0maa7lzs3C4qQkSHUg6lALQ/HPb7gwVTLne7y93lbne5399DKuw73vnO//av/K1v/65ReOPecGd3eP9PffIXfNV77mmtarPsWpHoSwU1jOKOUXBkQXtmCiRIQ8uVIFUlgaYIWihIIiGGNMqIqRK3gqQRyGnBmfYYWtCPU5W7sG4g4wW9m+UNZzzSgmssIivxpNO2XnCLK1A1D40TsxacQQpN8OtgmpDAu2upBCUyXKx4qYbnFNYJXNUwJMp7VDHDkl+kn2JsA21i8uodHmSRhbG0BVwQSpVTv+6Sd/yzp2wt5oJBPm6MQTgWqH+JaPqFk4xeyagMoyv4Gc6MyjOis7Tk/aGaAbR6MqxmxsSJc8phy7BUVa/N5TrE5GpEzmb/TOb2ND7x1Pl5zpV/TDmnnNJTQUFSFTzOzlK/qc0GOSGlTs+Ibkc2E7jW4mQgB7dYCRt07SPo8UWeQHvkrKC5aEpJBMS8289zEQId5lLZhohc7nalzES0213eXN4oP/KXLvf0p/7ydzzQU3lc8cnPv/CBj37iT/ze3/rb/oNvuqcVe0tnfeX1phnhw3DHqCL6NLZWTZUsbKAKgVKwDWvSKDpasRwW9RIXQLWStvzwFl5xNaU5DXrBQa/+A+zoRjSR6JfWyiX8RaoP83WRksWK2u/8iv3WyEolSjZmpd8tGpVaImtkoniHeFoURMRBL1TJTaaVgmgrVxpmDu+cdjFFlSlp7bpFI/c5tCQJraUPuFSfqQ023Slkj7gNGr8JWl/joXzcDU864TgKl6BXMhDJJmHGiFgJFt5PYuboyqTPLvFwCTOzh0s205Q8mOLGzyknC5dYfyUt3mF9xOecskdMcsomYNQOXXNuhCOnZKXKnzo/99Vz2uTm50g5IyXkjMTYdqpGtWukTZCMyjOiH9Qnll4cwwqMCnKaFJeiKKoiOuVpLrcPc7m4uNwfZlXd7feXu91ud3m5u9xdXu73u/6xfpedvOfLvvlPfst3fPeQN+4HF/v5h3/qk7/oq7/sntZaGCiimdfKNmruZfg8JER7oBYEI4WKIlnLSmTlvxSIV3ylNsuUwGAdTeWIgEmnTqyCJSfmnD6h/ptWDKIqHz3ZoBZu6VAPrN/staD+era0VFdzUvV5IAicQpTIKQKpJ9kiAi4mgcAGjKb09ELZ6UjPPFSdBBrz8KxaqFpKbdALVQv6hPvEKZ/dkRA/epIWv4y17AF4H7sYzONKPKGEo+MVp0lGUzIi46QrybUQMyJcwrTkGZHL2npQ44iVWDKqmSfOzrbRd6vTi02ecnbC8ZQHRyZnFXnBM7aNZxgXyX14xbtMqSTj7AzJclmDakybrrhF5Rk8uMVdkCfQToGU0mEW5jQXmUUAPsxzynl/2O/2exHZ7XZEfHl5cbm7PC6fcBV+06/55eXzL/3Xf+FbHuQ5POb41Bde/KGf/Nj/5u//u/7GD/3EPaxWs2F7VUC9fFb4N8KHAWssnUm4a0E0JQrO4TkX1r7Hkvairxxpt17OM/qScyLg79fkTMdiHFHHKw4KK+XjLue2HNTlWsugSp14amo3yzYU4aGjHfVqR7VLdEELDiMLyCIfRNycFtVq6l27ids+NIylx8KGnAiyqCoJBQXpOI0i3B7aV3VzjUNqWnO4PdC7PRaJwU5GlorHkD1O4AkiHItwCbq/mCXPoPaBvirXOmLC1lfaMs0kpVqSq5MxXMzocllNxuCwVoT9woazxURyZRhTTjn76LYRjrZAJSVGOJJlsebJGUZKcKNGBleGYZ/TYBj3BntopjwXVUVKSUSZ+XK3n+dimSmq2O33u93ucnd5ubsopez3l/M833APf+6/+f3/9Z/6ju/9gb/9QM/j8cbuUH7kw5/+vb/t194T4WjWQHTvsN6UdtZRD4K4VhExAc9DEdHEEEH7BOyd3qt3AJU9RGVu4zLdK3PkwkTjBkLt0rbjH/XA219wHbpe/8CqEVySitpWHrs3Ts/qVz8iHr5kZR5+Kcm5lufSWq2OWu8rrnjVlJQi0GH2XKWCqne4BcT5BKfaFYtbbTwsQ0H1NNwbkQXjqFk2FuWpRMQCMUvlpnGJYB697NHIx0L2WF/3JwyPOeG4mmR4WATdZ8826ldKDCCx9fnOFEW6IoWVVzzD6EXUF0/bzVRdnzU3JPX0wp2eIU5spillC45sTbrYTJMLG/mpW+dTlTRsGTNqRCVRpISphk5C22CzOm46qjFCJK8A04SLy5ynw/yyJfjNRYj4MM8gunPnYrffJ06Xu8tSysXl5T2VJP/C+/40vuzn/bE/+y8/uMN/QvDZ529/4jOf+5P/t9/2z/37f+IeVqvGjVA1+nTVqrJraBXxOg6NOEs6+mS0QmFSLREKAbH7J6xRqu/CLrqKd3xfe0Xxl2oK2mHcZal06Mnhm0XzOrJCcTWuXfSarS7pzKK1pUomXNTxmIuxMe3SawEI1XoeEKcX8LCLVfJoUkdNgYF3BUed+GEFxCqx8DJh5P4RbYVNFxEWD7KQ/xcRp+ozRSd7LIJdcYNWske9M9dfvccVjyHhWFsy0DgFvGR2xzFOkQxmJoJpGVXJIKMUXmvchnkzZQAb936amJGr99O4ReSYeF5JipBHZRhLbpGrpLGdzN85TSFpbFtUxeWNaZqCZGScbxdUo4VIctd76sCrAc6iSCmLYHeY5yLzXEC03x9Szrvd7vbLL4vI5e5SSrknu+jbftl75UM/s79xcbCBq6Cq3/tjH/3yd739nldc1iCvUoQ1K7X4ub8iR9OoV7CNyFJp9R4EyiEJCJRRxwAFuLEDW5hquILIWrFaLB1Arc/ldb18uG/jr2zZutd0v2QLfeQEq6A6ozKYq19cKrM6cRirGEtc4r7EhypICazQKNdjy1uwQ3wJqHtgtFdIjFIwWv6LRjHTqDymCq+MXtNYjIJwiB/dXVaNnaJWXqk9TgZNDcfPMuByWvaIDzxZ5OMxIRyVT6AjG82WsZIxInwSDtBFsglXVSMlJlc23PhZqUaNmHSejObMqDKGezJalc+VG2OqgZLNJqdkFUFjeMo5v+HWeSdybGqEhaYJObuYYZzDLBrI0bdItWUMvNqYAFDOU1FwSnMRI6UXlzsQXr5zRxWXu8uLy8uLy4vLywur4HyTDT91fob05v/0T3/Tj3/oXpwHA6cwF/nAzzzzG6Hn2+lid1PCV1uHVgqqNi2hfniOScx32iGeLpG8l1RYmXPLyGBABcIEFWb2/FgA7miAANb3G7UMFtSG155X2mhH19orBS3oWvYlb2hGg1Pnuxju+hzp1qb14o3XLLZwVDN1vUCddfQHoZGm01U+qWwCNZGla+ZDkxCf4sm2qlS0ovKPRRUyVRUnKaowqgESqTbS9ommc/hO7eijgFiYTOPTojM1syj8N/31dRmkK8OGJ0b2eIQJR08yYtDHV7ESnI6YWN8gref3WvrTTKBsmgZRLS6+4Bnhz9huNwCsZsY0TTnxZK7PvM4oWcVHTNUwYrFt2kZ+6ta5T7G4SQgb02ZCypgm5CAZlXAgAduuP7OBBwkB8nSYJae8P8yJ08X+cDjMAO33Bygud5cicnl5IaVc7i7m+aZyxe07HwTe+p990595oIf/5ODZF+988KOf/Au//1/8tb/7j9zTilXk8LyNKEpBBIGmSFa1cInavzBzRBzE3sW9XdJk4j7MfQCgCJKlqcRORZWZRRWkTOQhFArfg8KGtWr3VfDASmegdat1us3v57X1xWX/pqH0XGWxH+3H16rKapXjGdr9X5fUI59H02Gofqk01uE3QNCCIEYsoqp6Fz3pxA+7u0FGLEDDLmaYI3XBOTw0A2OWXSitZx79wTpTJYoq8u5E6S55ZW/UfT/mssejRziujpigVzWImk+jKhn25RXHg2swUUoJQE4JIOtJ5F7FDKMXUeuz83IufBibKaeIm2ymnJ66dQ7gqVu3JhM2IoyybTwjp82ElHDMNjiFnrF9fe7EE4sEiOY87eeSUr7cH5j44nK3PxwAutzvVHFxeVlELnf3IG8AAM6f/+Hv3e1GPOXVgSq++0c/+g2/+O++t7Xq62b3Xgq4XZFAYQLtinn7e623QyIgd4ySmPmzCJxEhJgBtcVUNbFHDESEmKyGB3nkJPbU0w50BoLaEDuoNlqdunHlmbYrtYRcsdJq6k2MYNf/+nvao10z24QDQq2fQUQChV02I0WKBAjV8h6WkNLpGV4K3VJtSUQBLZUIhuYhlZf4FqqC0oqDsUkdqS0ZYRe7NV3RdF2ktyxvQQuvqHuBewbymMsejwbhOCIY8QHc3P5ZezbpO0tjrpkmRi8sqXXRZVqXY8K5t2XYsBXM6EpvdekkLlrcOj8jIs9lNWKxmaacawxlaoKHT6GcMG2cXjjJyJiMYUwPvk/2gWuR86FIztPuMKeULnd76+j35Tt3oLj98m1Vefnll0Tk5tVFVT4EvPvf/y9/3zOf/+wDPfYnB6L6kU899/FPP/O+P/Z7fsVv/4/uYU0PnqyYRzOQimoK70G0K1aNw0tumPhRIleFeDkFYAujKACyMrVMIIAEBLVnlQbtoEo74ugQZTu6AIvPrM1b/aSrQyroG7PKYFbTr7lOq5WrK/8e0W9Gj6Y1ZSM6ZLFTMs1Ao6Qpg5QixzVuh6oXNjUJxIIv5GaOKnkQiclOGqkpixIdEukynSDixh2bgjbFfyhN8yCLwXgl27hvNQ6ztnpoRzaAxy3J5aFutNY8A1XCaKoG9TSjeTM6i8baBLrkGUt/hvVvYjUzNtOGgM1mItB2u0l9tYyl/dOMn32gxCSNnPN2WlKKnK8ZzjklqwHaqEZ2PcNJxnSzl4qBBwzBlDf7Q0lputwfOCXidOfiEkQv37mjqheXFyK6213eg7xB7wawP9w0e3bgJlDV7/47H/klv+jn3/OKXVQFUVQy3laViARgqLiFIloxALUaWM1uBYpoYja7aOUcBGjxwAo6AymIRJSs6Kl5GqK/WQ6FPpooF+apUzlOBC/8DTqyats5nobcR5sWl+HkqqeeWQu3xzoEtN6KroaNay2TXPw2taBKc56qF2VbRF78hnluC1dO47GYKopoq5iu4Vet2oa6mRRhKQ2VS8N80zOP6jBdhqPih9WVXEGllUvNo34/orTjYSQcC/0CPcm4ygG6iJusHKC0LJhxTDJOxU1yVP9smSa1s7RNSBoRN/EM1c3GIiabqbN/Tjnb9OAWmzw1eWPyJJTMxjBWbIPzEDMeUmQciuRpIk4pZeZ8ebkj5jsXFwpcXF7O8xzxlJt3vfY0gP/iT/7xB3fUTyBeutjfvtj99Cc+dU9rrbQNoL2ZNiISKoN46W7VyEAxkiFwi8GKhSD4h7U/RdSeXImpqDCReThM4gja4fZvMbbT4v1UD68e6pVvJM1zujjTFQWhIDMn27Qaplnv55hpdPNbFOHYf3r1fo5oiP/fEYyF+kF9wdZQD5rfwk0fTqekm6Lh+YAXh61BEzPihG9Uu93oglhQmE5Um8OjxlZ65oEl86i5LXF9NAJKTeu4UvPA0f176PEQtWS9GnfsyagL2B8neiVjYc6g2pfJsgwop17VSCkxrX2gQTWsSKjRi+lYz1hSjZo/0hOIVdxkWokZW5/CyUhGxibEjJyRpi5uMvBQIiPnKaXpcChEabffM6eLy0siutxdFimXlxcqst/ftAKH6m0A3/7nhl301ceP/vRnL3f7v/3H/53/1T//B+5htRpV0WjRbKpSFDe3SIoamdDINLEMFBsuIr2wwaRg6xLWwygJqCH+ImrMghRCbhG1FoeZisYotT48mPqy2nXIz+AELUATIU56O/yM1k099Qvghs1czKdTzOOG6ESbdfSm20GEK4ItAXDLDU5wE4aq99jSCn5U5mEbDJIRZccWtMPoS+fwoH56S2lpsZWOWxwPdMyjXuqV5tGZTXvNI6Y3++k9Xt7XHq8z4ejFjBhcmDPCooHKMBZUY10GlLmqGveiZ4CwnTYgnG02IDrbbEAIi0aQjEXoxJWMpmqsoySb5gPdbKapTbfSGsjZ9Yzzc4BwfgYQcAbgdb8pA3eHIk/bueg0bQ5zIUqXux2bwiF6eXmhiiLlXuyiTwH47Beef3CH/MRifyjf/Xc+8vO+4t76j0UVM2r+QdPvq4EUXZImEK2TtgbS35jBrnlAzEmgTMSMYhoGEfsnxAQPi6GQeshYYE2oHYBVHY3J8KOqgkz4Ao6k+9XZXTfaT7ra/nHDy+i472BwTzWu4Dr+0t/Oto1UDcQb/uv+1YU6IrKiHdAgH/0CzRli083j2pEPQEIIqUQEQUeOmEfTgarPA0Cdc6R5tCvwkGser0/bdq05Y/3fyXyTddzkKKm11ulKntraiRneEXztNY1zVwO07521s4Iuim4tzJ7TlINPrLWNba9tbJKTjNAzjHDwZpgzHj1sIUp52uZpk/Mm5Yk4ETFzsqZIVG5u4Pi57/kSG/h9f/g/f5AH/YTi+dsXz79052c+8el3vuWNn3v+xXtbubZgy4Y7OAcAFRADIspMFjYRtbduTYAImCAC82NYgooJIRCPmJAq2IuOurABH2ACgJA3vCoFEWAWUmt2yKuiIvq6XQZEFr2m0NFzZv0bfdVfl+sGl+k0uPEj7wS/0KtGfLveOa9GWGXZp0vliGtlIkp6UKdeiMs+ZDXEWqpzX7QDS/KxDLgg8ptWCbRVdelSalVRe9FB8wn7b4PgrGOleaBZOx5uzeM1JRz3oWcY5bD0EvYZd62fwVypBlO2rJMgGdyKgaaUUvaSoFE/oxKOnl70dbqukzTic7vpmMdmypm2wTBS8IxsPGMzeMYjiu0W2+15keenaXuYS87Tbn8g4ovLS4AuLy9OPAevwEc/+VkAz/zI+z/5qU88yEN+QlFE3//hT/9DX/fVf/zf+c3/29/zX91wrZ5gaO1LLawYroB7A99cGj4Qz3lzhhKZrxAMc4NCSZlISZnY1A4RISKC+TmayCHu56jyhsabWIQSgNqjG1N9zwX6J4u2Ca3DlsWsQKfoX39x7gke3OmDBlfv/GaSjHb/L7ag/WdNK+o4R3NQBAUh72PvhNXUFhVCf9lOMpXTwz7Qdtw5PKxautOKpRy1+PX5TaUYjndzrdVMl5qHbdwvyEPGPF4LwnFTPQNH/gxnF51FoyMZYdRgJxypprZyYgZhkycQlqW6cqS29nXHm0UjPKHVB7qqvnUUK1nSizP3hLYpnZjRSxp5xE0eedwCXkhnZ7eKPrvdns9Fct7kPFnszuS4m2zmY9/639rAJ5957nJ38SCP+MnFbj+/74c/8vY3v+nf+63/2O//pr96H1vwZkuj1Q7mIVCOCIaZRq1xpcjVhLs3/PFH9k9BDIAE4u0OEZOCiGFjCiJ2xWMlbyiivro/LoP6FAVq5dH1+119VT59dkdDVy9zz1jmVWjfGhwvhhYdOFrsJIfvDv5Kjt/7TCMSVuUWgtVq65v5Xovpy6tTVONo9OJKseQ07UCbDiAoDhbGjnAMXRNqCbbkl+X6eh7ri/v64QE2e2s9o5/UDZzMa8VRT62NZNg/XrtB+9CJVdHIKXFfP6OjGhY0IaKpc4NOnVHD6ot7ka5m11i7Pq9SNVLO2HYkY9ogZ9BmFAN9fDDhqafyxeXTb3jqTRcX+7OzW9vt+WGep2na7/cp5Rv2n/IVv+r/aAMf/PDHHuDRPtm42M+f/+LtF166/fd+9bvuYbU+uo76FkmLd05/z27afRM8PNqi8IwVj6owAxHRbwEUxI7IWzhQ8Jp4QDJ540P+auzahk9EKAldeGXRAldb6Q1U1fttllYSw6mNLXI0+iUXi+kyNHDl4emJiXHWp1e2UJRHKLQaXlo5cngI5FSGbf2MvKQFq1gzjLvQDvSax1HqrK6vTHiYAYu42A8xiEfYS2PBk6GW7vv1wQMhHItQSQw3PQN9/GQZQGk+jS50Eo6N44JdtcvWKD1OVqorLfSMKNvVVwXtQydd4gkRRehkpWq09JOa3Xp2SufglZ5hw62n1oHHB9u34i1y64Xbb7nY7Z966o23Xr5zfvbUdnt+dnZrml5ivjuz/Olv/VN1+F/6t3/XgzzYJxovXeyfffHiB378Y19X9Lf/+l/+x/6n73rFm7RnvyWpuuwAqxDq8kZU9wpWYf2qsNUhJVJRpo5zRE6Kr0/wkl+xDIJ5HMVWWrQFXq0DQC1SAXTaRkjwr2Jzs+IuevR5tLi9d+vx8ovtUXVCXov1AitX6XLDGlJHN0oRmejiPmsKUtlRMw5bV/VyzXB8rigIFt7SeiTOXWoUqAsHVadoZwZui/g597QDcZ972uHLtct7xQV8wHg1CceaZ8RoRy6OQycnSEYnanSFNJZVQZtLg9bZrYuOWz3HNcqQe+Wu6Li1Zrf2tUGjixMm2mx63WI6VjKuphpBOGABlBup6wOPGAjbM7zlzW9/+WL3jre/+4WXXnrLW9/x3Befu/XU0/qFz07TdndtiORrv+I9X/Wrfksdffnllx78ET+5ePHO7uOfe/7Lv+QtP+cdb3zr07eee+nO3dcha6P9nbC2+/6Us9bCS3v1DVJwEY+wEJsJUADyTkCoEzxC1AjygY6FdAPolkQdiDYxRI4wFsIOR5dPYldjOrn55tevLbpsou7SYC32UNlQ93XFAuj40tUbPSVvtClLxWS1gWrqiO1Ru6O1ae80LpOglJwc8PWfXvVtkSUbKkhjMKFk1KM6QTviRp2mHYrOKNzRDrSsqjj5U/m0eM2Zx6tDOKj78TaKsRw4lXWyIhzEEUepPMPGm1ejUzWYObtvw2InYQtNaUqJK9WYrKjGlBJ3VCO7V2NtDm29qeWcc8rXODZa+sk0VI0nFOlpvPsM+/lLRfDFF188HOZnn/vC5eXFU089fXHx8u3bL1zzh/yhj32yDv9rv+PfeU2O98nFF168eNNzt3/so5/6yi99+z//j/+SP/Tn/+ZN1lq1yq2BjPBK+Enh/g4PZHRBA3i+g22pfxxIRzWsooZ1VM9eUmJJRFqQpTkSun14Y12Fja7J8+OFkxZU3tHOcXnGi4a4nfr9oIV6aE0BukvakboTOEqsuduxHG3mhAmWVo05IfJIEBGVY5VhQUEqaXA9o+aedLbQSkBtWxJbjGXMlxOhmThaeiW0AwiaTHEprhY8gPqL6H8nDw6viHD0kkY/2osZlVygEza4mjU89ySCJktDKFnv8D5Iy3IaRwGURjXSlFNi7/Ek6ne1DBQjGdMUnbVGF2utd/hsCgcv0l+3m+OclLzwamTvYs1toYNqPBmY8BVfS0+/8T2CfH7rjfu5bDbnFxcXROnOxcsv337h5Eq/9Z/8x/rR73jft78mx/rkoog8d/vyk59/8elb25wvv/Jdb/3YZ5+7Zvn6BnidCqChgujiPZMiwmIPcgn2gTBzNOtGDFeuQLFBX4DCsdGW99BJs5F6uxWHG3IIIjnCDrWxj3qCNfzQiFXf4tyw9blWJ7nyDZoWyxzN7Y72qpyZdmuuONBF3Obqk6GIdURTfZJzYB3oIO9JDq0nl1PqRf+PPYzSKEjPM6q6smAbPZds9+hq2uGRlmvjLLhC8HjwtON+CEdIGR3V6FjsInqy8ITiOkPoCarBRJTYhY411eCUEjfC4T24dqVCV/XI85Ry2uScc54iD8WsoCfNodb16+aIXkQVrynnzOsAihUJHRkoTyLe+i58/VNf8s53fslm+9Rb3/IuovzUG95cyvzMM5/84hc/v1r4d/yWf+qP/Km/0E/5wAd/8DU82CcRqrhzefj8Cy+/6QvbN73h/L0//0tF5OOf++LJheMJdjQxNta9I0a+7CLa4mqHPeBdWm8UJFo2hFhxYv+tkdMwddRshPqySt0U7VaLQ6Su7SCt77RVZveddbaA63AVsdCTM5sUdHrT7V1bFav1o8TJemNLwenKnJS26vESempqu05V6eiFjOrdXXIOIxmVCqw9H1jex9NE5CryQZ1wodXsoQrydNp2WU54OxCSxxW0oxO+Qg5rIw+UdlxLTk8uvZY0uklXUg1nGzemGkE4gmpEPXJOxCdKeOXMVleD0yIPpdM2jh0bfRjFCEdOKa8cG8vQSVU78rFXY2Oqxqjf9aTji8/iE5/Ej33gB3/24x/50R/9vo9//MMf+tD7n3vuc7VTlbe86Y3PfXEpexxAm/GzeeCYEt/a5i9961Nvf+P5rfOznNP//IMfncuJzm7I20J/utXHmk9fDBN1UyJG3E2Pp1+oGrRYZjWM9fJ2LFUlpvXTNaZEoxJHvnoL7OhTP7QYXVyAjrqcmnn1jOt+x6tX1Cu2SavxEwd5z38sre3sUmfrkKKSMVcgtA6or9RP0fhS1BpftS83dNNtrbos+tG6APolY5fdXN91O8j+YIB+YpsUZ6ft/PqzXvKxTmNZ0Iy7KEP3g5u+iy9+vPdONSj+qq6nGtWrQYRWLbTTNtIijNJ3GX+1tlGrhS67dbXPKSejIIuiXmlBL1bWUTqmGsmoxhA2BvDmt+HNb8NXfOUv/tjP/uL3fNnP+5mf+Ym3v+NLP/axn/zQh96/u7zzT3zjr/hL3/43V6v8N3/yO16PI33iMItcHsrzty8BvJ0opfQr/p6vfP9HPvP8S83bS8sBovX0HqfbvSp/1C/1NEZtisZK56ivxL1UEWIGeZEFXYRe4tW1WzBiEyGtNJ0DXYZKleZ1cbyLs7E36hPSC2HVPq2En9OqxGKrQGvr6zKLEhNt1xRHujiUWmiim3R0qO0I29jp4MzpJnUpQK3uAWB2D88Qilt2nGKymIWVCrJQL+J2aq+aIO5kVyVsEWGpN92OI8JACtArVDvioi6LqLxS3J0qnqIa/fj9qxp91ydE0adrzUCJSl6pVdeoARRXOCbXNrxzV5Mo8qke12rlUGZe1g91klF7lt8uaonG9BimnmTYcDJtY1TXGFhDgY99DD/4Qx/+yEc+8Lf/9rel+bn/8S//+ePFfsHf9d4P/aSHVN7zJe/41DPrEMzAfWOT034udTQx3drmN5xN73jj+VPnG3tc/O0PferO5QELPQBLtQAhN4DqM289vNIwmgjB1J6NRyLHSuHwPfkycRTUPWZ7ZWVxPO2Q44HcE6YTyvTR112HVjimFHdf8Gpp4/iwliuf3s0NxQ5dfQON9XQ6gY/3CkEVOaqU4It0qkOTPVYqSF1GlrpFr3Og1zbqijG10zzWKkvMQKgq0Hb4ndSxOLvXWe24mwC2/pn29ONqqoHOsrG0hfaco6WieAmvvg+UY21jmY1Sq2uEOfS4PxQzdmymKYIpvbaRttOm74OtEYtppW04+Zg2G6w7d92A0zBtDNwVuwO20+lZf+N9t//hb3i6jtY6TwOvCr7x67/qO374Z+ooAZuJz6b0lqe2T59v3nBry8zTNH3smRd+9rPPd9L9im20Rr1zpDUGsOAEXeyjMgx/71pMXxMOLEbbU/Vop92UOLx2wMs3Qlp8tcX6C7Jqyk8xgpv+IFc7u26xa4Iqd2Eep1a+AY4byxXhqMuo9u10H23pGvgrSMA9hVrQmMcJsnLl9iv7WU5pVKMNLiIv7WOp9PQFWpci1atPO063lNdRDVyjasQfSHxRcI4rwijRB0qYQxd5KM0iytm7eM2rGhsWRjFuUWlHDaxsppxSTX+1VFirIuo9yy88HClvnIK0gEt1eyRmpISckRNSQspICWxlQwfbGLgLrmIbAP7Ff+FXvIYH8sRhv1/Ue1WgFN2TvLybQUiJt5sM0Fe+841Q/fjnXliIHF1bbo++K7SNRk8IjS5Qp4r46uikC6ya0ytwLMyblG7pKogM2rr4WnEPNd0PUN2hGcdQ26P6kF83J9EE3YRM1Pasnt5JatDttG2w7tdyM2ztNnG5RFP8b3wV11Nu2mxG9ApAi7DU2Fe1t1KEJmqoRePo+lBLpVPtLvrRdKGWOMlIPmpdv8WOCcuwWldotgVOtO1OvQqpBaNqDdo4lzZWT+N0UIVq5OU+ace6sbxXqlHnV0nQvloYBTViEp8chTZaIa/Wjzx1/chH/dDFlEXP8jklXvSK0vX1mvseX6dKILy6aHg4jFLYsjnlFP9yqhpJSolSRs7IGT6QkPJgGwOvHL/zX/3PfuInvv+//CP/xqsXJx1ouLPbr6aIYi66OxQmbPIBAG0Js37Vu9/8tjfd+jsf/Yw9pheywVJjOKk3LClIz0CWKshCL2kbQSdvNPEE8eSNz1XjumQjMbeSkSXn6FbWCPMvNhX2katZwpJMnDyk1Rqq1y1p79q0nBftLQCth1Jb79USPSkBTlyf00emd11k2aa31rgxkGh3KxXw61fTZmvbbdvqLrlGGoq7QuqmXeBsN6/nFr7j2guutvxroiiZrjFCtSZMUIqwodgm7Zgq50DwuM7Yod2lqEyonfa1l+/qq9oN9dTi1P9XChs1ihLEw74iitL17xpFynttowoelVgwrbSNxNb2H5cqr53LT71dtFbdyK5zbKyKl1OQUDjCwxFhlFzDK10RsDRZAGVqlTY2E8iqiI5iGwOvFAL87Cfx/vd/5qMf+bHf87v+kb/n637FB3/se0TK3dccuBu+5t1v+vBnXqij9gRLRJvMm5zecD7d2uanb203OZmF/KWLw4c+8YXLfbN0dDpFoxr2FVPWYRQsuUXbzqkQyZqmdATlVPTkROik4zZtVv9//5Rv7f96yuIiXTHr1GLd2NXLX7/NK1nOyRl0YuTaIz1CTzh8sAsWaD9tYd1oEYpFCOOawMcq0+SKYAoiSqK6HsUVfpHOwNEiKdeHV4IuXhdhucbV0TZwYvpN0dOLK4SNFdVofyELwlFJBh2Bu4F1MOVEh/JOO3JPOHJuqkaK0MlS2/DAynSin5TU9ZbS9wQbhb+8nLlX4+h9HptNNt9GSpgm74YtJWymkQQ78IDwyc/gW77lB55++k3//Tf/Z5/4xId+6kM/dPul51/vg3okQcC733rrM8/dWTaHlBiJeTvx2ZTecL453+SnzizomrdTfv7l3Uc+9QWzkXKwB2AtYwBL9hALNM0jqAbXB+bVVAPrKUu20e0O3R5PsY3uMU7L73759ZTVZVsM3p1GLMeuYg5X7xGvmHPcH+FYt64xHAYIdI30qv1eWD4rG7iCLpwiGSu7qMaidfTINHq8l0p0et9Jx37q8Xc2jd6h0j7Wro7Vhbk77bgh56DV7Twmx/3vuPtj61hHRFKO2UY4Nmw4Ml9rOS+2bJRFGKWVKnfTaN83yqrfV68omqec+SqFY90924pw1CJgOYqArShIMj3DSEbKTjtyJRwDAw8Edy7w3HP45CfLs88+84lPfvTZL3z2E5/8yLPPfvZTn/zo889/7plnPv7y7Rf2+8vX+zAfLiwfZCDgd/z6f/C/+J++u7bxpoQzExE2iaecntrm821++nyzmfJ2yiml8+1mP8sPf+TTdy73rVFvGgYAYoaqKbjAsYyxWL6SiaoM101WFrImMcttxqZjelt40Rw3srF+jHcX5G58Yj33aIFTS1639okZr5xwLLZ4jyLHaYtkTzhOtMqnraNhBl0283XWij0ckYbj0Z6gnFJK1jxmtV+sD2Zx5CsnKdoydcHVVboZ5+hm3ZV25CuFDdSf9uJnHX82jWfUr55z9ObQhbbhI62X+fBxtCIczFSnhZODE6ej6qJRjcNrjTa0TQaV6VBJUNtfndWOxvUXgvUJ3f8bqsbAg8etc9x6D77sPenypS998aUv/cKz8uKLL3zh2WdeeumFLzz7uZduv/Dcs5+7/fKLzz/3+dsvv3TnzksvvPDcxcXtl26/sLu8uLi4fTjs5/nwWMZljlqaxXffNp1vp5cvLpj7KIQvl9xyiSKiqvu5bKYkqhOhSHnD+eYX//z3/PCHP32x2596+oEAYt/esWgRebCLWSvFYsUeqD1n0QVxjngG2gO5a7mvpRptyRtTjaOxIxzNfgXbuoZt3Gh1vZdH8k3exO+2DNVFCOFuICxsDwCa18P7tQmfbO9BdW+H+qh2fcrZLdLaQa22/nlW7g0srBv9RD+svps6rTvqDh3wMh+VSrRl6vl2p0er8hwxi+528XJdfvn/8sfdBVNWYZT486Bojhf1NnryQZWCLLWNnha4wsGJ+4yVFM1/EIbGTqiyk8pgyAufW5/1pzkH+5KxBadJEUOtd3sBZ3wal1Tv8Zc+MHA/OHsaZ2/AO97En/ncW77snW/8zOee+blf/iWfeeaz+Hlf9enPfubOnZeZ9dOf+XRO/OnPfmrK+TPPfHo7Tbv95Z07L+/3u899/rNnZ2eHw2G/vzzMhzLPh8OhlLlIKWUWkWnaiJTLy8ucs6qqiqqmlFRVVROzVgBQJY4aQgpARY7ef/Royg1Ascqiqaw5F+Ga8wdmZ4K0RzEvVvPW63CYSymZuZ9I8RzL8ZdfREvRUiSz2AUQkTfe2v59X/Oej3762c9/8TYBzItH4oJ/rDkH0BZYqBRXRVLWL3VX8Iy6pbrxxdVb8YxGQdY8Y3GlVmOnFzi15NWTT2yuGztNVV7Jc3R566/HPf0mr9/piR5gYsayH9puuDeW1jJtvl7lC36Pq/NTl87Vrhe2Vh7/mHOYHTU+Wmd+PbmpNtI4wAWvWHEOYO0kRX8NOs6Bq69zRrtf/V+U73D5B9axjaXSYX/A0bnrWtugaOCPKEg3rTN69PzCho4ZQzpJI1yVqFU+lkAX/PHRuGy95rn8CzU9y+mF6mJ0EI6B1wYEOsOXvgO3X0ybd735xZdevLV550svvfj0+XsuLi5euv3SW95wdvvll9725qcuLy/f+dY37na7Oxcv7/Y7JrzrHW9PTF988Yv7wyEzHebDfr8/zIc5mMdc5lJKYi6lFClSShFJTKXI/rBnZhFhpsNhVlUmElVVZcJcxFRaEVGAiWxAo5RIn99/PLqYZTygvX7ZScdUIP5GsWh46zgjWmH0QwT8hfd9IDE5Kek0CYK/pRCgCiIUUSIiaEqWhoi3v+mWHfEXX7pzFO9AYxUAM62238/ttI1TZOKu0xfnS+tzrwGVxdeaZ1xJCZZj98AzThOHu4xdtdLJ/dLRcZ/Y+r2wjWOcjqecXOZ6EConWLTb1CsMtNhYG1sMIQiL/Wpr2w+tQgmterX1jJiOc7T9rzhH+/O6UudAxyN6zoE4m+UVWXOQ66WOXH+yK5JRp55kG94uhyoQX2jNeUwkIu5a+UhVqfJCJ1d0oZVKGCpt4WARANjkULsJcVh1ChP73eqWiRsjhKQiSElUgCQ2LIKUSpGUVKRAuT6CMzOkQBmlgBmlgBilIBEwD9/owGuEBGzwhjdgAjY03U7pPJ9fXtLLG3n6TF++Q296Ku12l3cu7ux22zsXd/b7891+d3Fx8fStab/fv/Gpzf5wOBwOBH3p5ZeZ9HCY5/lw+84FE+Yyz/NcSplLQEoiKrJhot3+wEyyFcNhLkwQ1SnrXMT6UreQchFhoiICQERPvgGKKkcbqf0DMkBHI9RN7tuXOomO5tpAYmaiUqTfju3c7BcpmaWMFEhMIsKcGchMqgLol739jU+fb3/0o5+6fbHrnoJtU9QdwJo6dFoI4qnFywdux0xQZ3TnVRfpLskJlrGmF0dX8obN/7WTT825Ieu4crErGcUN2Ma9U42rGe96wasmWWOqIXefnN05Ttsndb6HvjGmrpb9ItrSNfKk67+RNWgtNbRmr+ccPq/9yVEIJCtS0R/A9ZyDuguCxQZOc458gm3UDfWcO2YvhI0aWznSKQCXEKh+gNowHU/yT/ZrwoC7u/29gRhdyKbXL+xoqf4JU3sbWv0g+99AlYU7xVhVVNk+VExcViFhiIDskyCCQmABEVCANDjHwGuBDNC83UoGktCWmYpu3jBdTrJN826LF2/Ptzbn+z1fbGm3z/vDdHme94f9fn+43G0Oh8PhcNgf9re26TAfDof5MB/e/PT5PM+HeTbG4R+llLkQw6jH+XYSkSIVygwRFZV5LtJHXLSl9ZUShGNlR/Myz/7Ivv4vx+aKRUzicWSUpT62tDIYIurm/vZf9w/8V3/5b6kq59Q0j3hGEMFk1ykRM2VmVaTEdvD+9gQw4a1vPP+7v+rdH/yZz1zuD/4kWuol9bF5rFV03KMjEL1E0T1++zeofu7iatQn9fFluoJh0Lo22Kk1bzznNKG4Ytp1dOQaqkGn59Bi6L4euSfbwGuWO73wNbNuuPsrjuOaw2vUICjISq/wdtPlutP8pNv/SnOpNOKI+QB34xz99u56QouQyuKPpKPt/tfSOMhC2Aidg+rSdAor0YJjxQVpwanVUefVvaKxFLSV4yA7aHXbVoNuTzE8Ym1fLBa9JRERap+JCgoDJZLkGFAwIdVrNsp/DTx4iCLNSCXhsM1aDuUNZ7TbkxahLW9TZp32ey2TJpRNVil8m2V/ID3Lt+/o4cCq0+EwHQ6b/X5/mGcPrMyOw1xM6mCiucylSGmCh5QizChF9odZVJjocJglZyZSlUMpwdmb+V4VRaTZ59szSbF83RQRAMxkjpDjgcQk3Qr9C3L/F19bIgJKKV/31V/ygY95xzTM/l5nayQmADlxYpoSt2gIkBIzIScmKDNtpvSON7/ha778nR/95OfnUtA9KDsa0dEOtMepNfbcnqzdW1G/btvA8kXpmF4suAU5Z7u68W6X6WjS3Sac2swN5lzHQa47zqtoxnKb1yz0ytDiKSFeXEM2rlz3VTkUCqfoUidofKAtiObkOGrbqRc5FnRlsZ0WkTmiED2JWHGOxZEdj58eBDyk4huMHXV0nLpXh07dqLLI4pfUN/o9D1gGXBqrr0SkpxVr+kH9z3S11zZQCYW9O/WiBdBRCxJ16UJESUSFdEUv7LMQpVIKwMwEYi4goFBcqgR7zZkQ13PoHAMPGnvgANkhzZtUJAuJYi60oQy6VHnDNu05Xe5mupUPB93vkWi7P/DhcNikW7v97nCYD5kOmfVs6tlG5RzzXOYyE3C52xP5Z3N2SNkd5ltnk4gSYX+YVXQ/z8zkYqCqqs6lMNFcJDHNpXQ5e2vqYcEXvfrxHjj98tQPrloiAv7st//w17znLdup9qrYmjR7jtgrUGJKiXLiKScQpcSwv3qC+1eI3nhrI299en+YP/vsC4e5wOMjWp9kqwOoskXPG+5GkpakRI9a4MVGji/D4nrc75PofljHiaM8mnAdz7h+9nLBV4LjX5kuvq5eCyff3oEFab4LP7k/LnJSq+jIQoiE6xDGkeKwpC226RNxmmNSc9WBreIux6tewTmyH149zu6Pp37Wdr5GQrBSOCoHCUpR5cXKECp5CCLTfmqNWoSS2Q6nO8PV71Ljh6AaOoaGq7PTMUQ8RKIqojSXQkRltmfiTASaQUSYZ1pufa+6IejBLxPrKiynmBSqyBrzePQZO/BgIMAeckC5BGboAXJIVCYuM4uyUkaZCRmJWIUYPHGaWAnzJuGQcci0nejO5e5MeJ7TYZ4PB5oTHxLPmeeZ55mBzTzPl/s9AdtNLqXkRIATDilSRM62RYqIaFGZclKRc5mMbEgEVw6lMJE6+UiJSVXnYtxiQT8AKFCKmIsCAFSLqOkNa9mDXOQ4HjCk1SjTb/pH/td/8E9/qy1mh+RbVkuL1ZyYiabEOZFJHURkE038yImhmhO/7U23UuL9Yf7iS3fWWsvitWs1FBPiaaf1uXqqpV4+79Yj997mXrvCjbd2Ez6wmnbXHV91LldewVcbemq43tgVO9Furs1ahFU6T8disJt5cqDf4+ljuzbCcjR4YnTJWY55Ql1kMa0ud43IcX+cIy/JdWMJna2C+mV6stDPoPYG0XGRFgPpdJNK3cmbafXPdpdtWFQYKYaVVUWEmUWUSUWEiYsIMRWbXoSZSynmFGOqw0YvinEjEzBYhEDCUoi4FAAzEwhc/MwViWbKrDNBVSYoqwCKJKjkiBUAkiApkAAdUsfAq40DsMfhgHJA2aEcoDP0wDozSiZRFiXZJCXBQbHNxMoHECnRdtodlJEYwpQSbUTKPPNhTvOU5jnNJR3mNM95LvNud9hk3kypuke3U6ryRinFVA0iSJGiIqIicphnJjrMxRiHqJ7pCphLOdtS+Ds6o4cqvBIGujjL6q1y+Vjvp1yNb/z6r/7OH/7oH/7m79xOJ7uLAgAiYiAxJSarYkxEmYlAiYki7EIMVZ2m/Kanzr7iXW89zOXObk/wYDniJV21Ch6rnWE98b7UCKrx+dcUN6IsdzumuxOmkxzsng7oPsMZJ8SL1j67aN7Rh94uWqcvPKTdcsfuUT3eytV7OrXIcuRomYrW1i8YzTrwcmL0OkZxKrByPY44R24/g2t/PXQ0z8OTIF12KEJwnUdrBzWN89qM+mfTbU5jrL/dShEiQbW8N4Nnb8MgFRVSEqMRImRueQKLEkkRARH7FDZiQQAVQnWnEsH65/NPJSJNCjKbG5JoBiACVaQEAFwggsTIAmakCRAgATxox8ArxgwcoHvMMw4zDnvMB5QZhz3koDpLOQAFWgiFIEyaWDeJtECZKBEpEdJOC8AEzpzmGQxlUqbEpMxgQmYuhabEqro/HKB5dzhApyJlvz8USQBEyv4wb6e8P8w0wdyjh3k+2+TDXLabLKJzKSoeOJ5LsXAMEZXq8AiPh9OO+K+4/gFmfxzXVFtgkXZr12X5CtjGqubxXT/2sS9929Off+HOanodVVUipxRTTkzY5DRlhikcTDklZsqJCR55eep889Y3PvWedxw+8bnn5zkqqt30lXz9mF3P7h6Bd93GDXHl67E/4uLi3W3f9/gg8xfKu7Kj7v32+sWu25UPtL7ETp+0nhg9avSXzfspVUPblJXXYylvrA5DT92Lk4LH8QHfvW0/EiaW6HnDcoGrvKU3xt1FjiPkumAvb6w2WhdYcZKlwaJbYa1/nPzNaCUm0TMgVFWJfMBLrFWysXhpElWybyFlFRERJhjTIBGCaxgoVADvgo+JoMrEgNYODuB6hpVBUVWdJlWVKWdVnXJW0ZxVRKacRSTnzCLIGVKQMqQgZ5Tukzk4Rx69uw3cOyz16TYwY55xOGCOgTJjnjEfZJ5lnqXMWg6QOThHIS0ENeahokxIjE1mRkqk8wyCEhKREsCkiZAIMxfNdDiQqiYmKYVgPICmxC5yCE85SZEpJwKKiKjMcxLRzeTqhkhuTo6ZKQIrpbC9AHSqR2McqsC0jLXUx7f/l9A90sW1hCNdezny63/F133TX/v+xbOvf9gSAES1QOTExJQS55RAxMywwkIAEYkqgRLzW54+f/lyd+dy/+wLtxdC9RXom/K78okbtus3byOu2SCtHvb383J0F93itAXlvjWMo4bpxDq6GKpYaA9rthqDvSDQvdziJNvA0fQ22rkJETHExVGsFJT1wDXU5Kq1jifc8EdyDTU4oW/cH5Z0JNN6rpOFK+IplU+sVlrziuUiejzNpQvyu6jwyqpOLUw/XDIM7j6pCIEKhIjmgkwopRBQCgg0A5lonmfkjHkGMjAjAwfVnBWYNFUasZkmVZ00q2ieVFkBSGIAoqpA8qcpq2piUZUkKauiMLKiMETACSJg9s+UkBiQMHYMwWPgrihAAQ5AAWYcZkzvxOUnMB8wFxQjHAXzLPPB3J1lniP6MWspKkVFVAuRMpSgBCEoEZiUCcxIQspQJSSCcprADCJVIYYV0kBh2KOyMIlIYSlCAOZ51oy5FBFhIRFKzADmuRChpsga+0hs9N6QVNXUDlUN5hF8o2MWlXAQIaqIAe3BXpcEUFuH9fAv/Mp3fuBjz/yZb/3BKfGJh3I8jSzga+qFixlu3fB/5H1cG+cQKOeU3vHmN9y+2F/sD5e7g3rf4uH+P4U6me79wX1yjftWOV5Jw0HX5daeWv5m6sXpRa7nFldj8fK+ohlHbKN/ue9pxIptLNdpA0tego4t9/vUflPafuGLn/WCmvSEu4uwHK911clfw0LuHfdDN64XOdw0ehfh6uTgFdNcrKt/ijD1ABpFfjSiFaKalEQlEYsoJRURSlREMlFRgRKJEqkFSgoKASX2SUykECEAUuxVxIhS8U97E4r3IYLFR7yMoCS7twwgWakiZgCaRKEiSVWdajCrahJW1cJFNbM9cxNni6dIBhdIAjPmgpycc/CMlDrBYzCPgRUEKMAeUKCg7KGKUgDB9j14/qOYDygFpeBwgAiKlQeVUsphPrjZwmtnzJa+KlJUikiBCqAEZagQ2DkGklERJSSeiyRmpFSoRB8gSoREdCiFhUohJsrKcymUs4ikRObeEBFRNYOUqOTERjmMcGwmLCQNVc2qiiIyIVWRI/SOEDW7/zyHBYpI6RPV+HN2SymRWUr9eWJL/+QnvvDmN5xf7Od5FnSFjgiwOuz2gGK22j7ITjhSTuyJKtHNEyKsY/avnHi7md75lqdv39mVIuaERXubP/2Q9ak3eHovVJomD9+9Eblyw3d5dt8Djlbvmo0bb/pIPH+wD8OebfSXqJIJbXNPsI2OVXStf8zrp/cTm/Kx4Ap3n3Jiravljf54dTXrakKy2tY1v8crlY97tXFg8RPOtu1jT8Xp1aw7g57r1hvXc2D1UEnsy8qqRlRPNfgHXNpwGqBq5lD7FLgzQwhQIiFlUYUKKZGChAgoRIhPsSMsFE8o3y4IaqqsMgBlBpCUoRBlEc1ZRCSnNJeymaYiklMuUqacpZScc5GSk/n2c7EppeScZi45pZRmShkzO9UoCcwd7YhPMsLBQT4G8xh4CbIHgP0epfiAFCiwBV5+CaoubKjuD4coiiGH2WlHEZnngxcHjQ9XPcT5h9k7Ldbh0iI8k4yJQKoEMKuVP1YCSMATUIiYSITmUjJYmUSoiBDEVxW13JAioiKJ2YyjoqKqLN7SS9QeFdWsHGEXBOWIN736wmfKorKo+hMl3hFFhUCAamIVBSElQCGqKVRRIvzqX/IL/uJ3fWDKrlMSXLRZuM0IRMQEJsqJiMiEDXQlB5kZdhHUE1WnlM4309ve9NTl/qB6aC+zwFWcgmrDduIvvjUYq4A16oyVNryecLTEYqvA3RqHqPtAiGf1qS3eG9bhlLtt7fr5N2ncju0Ip9lGL5C1uQvR4Eq2ofUjWvqlttHkilhixaG1bqQxjOWUTqpYUYmOJHV394iAXH+R1ivdO1bX+V4jL1XhuP8DiP0eTWpflX2oVq+EPx1gDx1RmwkVVYaqKDwrhUjg9MLeJxJQnEkmaP3M0Bk5QXXWlBSarQMq65IqqajklEU1pySqWZKIZMmS/LUM8WRMhTVrEVYRTklEOKWSJCX2z2KfiZlLzok558LMXFKLp5QMJqcaNpEYicEMNrZR+QcNq8cTisMlLu6gFEiBiIsZNvB2wZd9HYDDB98nUkqR2epvOZ0QGy4i81zqcP0UETHKISJSTJJo5XM75gHY88JfWyLP3QIxpAQi5MRiDlBmIhIiIRGleCUQpiSWv6oCIlYqIlVaEH8rkGQlz1UToCotarqmHjj5nyoSqMnL3J7CHM/nr3jnmz73/O2XdppTskczt4c31XalhovNw2FdK4CQuk4ioWgFgUAiojlNmTdTPt9unn7qbC6luGZiCYSnOEWd2lSQXvDvrA56tDJh+RgPsnE89WjF/kju+oBfFEa4MRbqyb2IHKep1912dPPX8UYelq3wIuah3fwqbOC4Ya8Shn8sbUZLthEb6QlKxyraunXF5dbW4ZVGU1aH3VGQjhj1M48P/m4X8TXBvZTIDOZA62mLz/a31GqskkCYWBQMWGqriqj3C8UiwmCBeyCIuBRBIhRJyV/87NGhAIjUSw/7A8SVkoKkCvinXWp7DAmzQl3SEK6qrw0XYQAWpWZbkpOopMKScyplZp5ynpmrpHFIc04pMeecD/OcU0ozp5QS+yelBD4s5I10TDsYzKAcN4JHwOWJw+Uet1+CiJMMEYioMYYP/C+bX/gNt3/4W72seAgYNlqlDiceQTWCa8RoTLBSof4h4n8BHvIQLLlHD/L3ewBkf6pWfxNgqAhAQolTUUnKREqCCJJwZRL9+491qy0qZuxAUI2l5IFuDPGMXv1Hy0eqf3/i8y9+49//Nd/+gz/FTIrWs6YPO13x06QocE4WQyFWUBdD4e6CkIJUlDKfb6ez7XS2mc42mzu7ve0eBAKvBXDtoy19U0txXN0196dnt4U1BQkfyFpAWO6yH1ssVutZN0njOryaIkc/g0gXROs6tMbk+vlHU7C6lGu2UTe8oiPd3LuEUXTFRY4IShNOuk2fYBtYbzYOvmMbWg/7SKBZ7KQ7u/UlW/0yVifeb/GKK/hqINc9UftaoxPcTLDQ+pdM1mva4rHSpMHKFcn1C/8LWj1TxJZ1VVVEiBkiAiYSe6ECemcqc6G6OrAgGarKCrVK5Tkli5WISM6pHA2XUqZpKqVspskyUEopOaW5cE55nkvOKTEXkcRcSkrMs01JmRPnUpjZyEfKTjhsin061aCgHaZ5UPfJhDyBD6AUUgcN5eMhgMTF3wMJONirMjADT71qO1HGyy9j0VOJDRcR2QAXF5fv+Af+iU//L/9jpR2VNPT0QrotzPO82pox7FjUvtVnibaP2u4vX4i8hY589tpRJSkxAf7CEOnxzKZcoHZrDyizquW8AiIgeHgUpKIhdlr0k7oAC0IGsTLLpP7kqZ+wLjTtCQXFu9769Geeu/2Lvvbnfuf7P+KCau26G9GlVTxEqfONeveQ3Dqw9paZzKBRH18w4vX0+faFzTRNiffuSws20UQJRXWPwR+aRPXShgbRPeT96dlJHsexlFMNwP+/vXf/9WXJ7sI+a1V/9z7nvmau7RmPDQ6MSWyPnTh2ggHl6YhAFJQnJCJKpDxIRF5CkYKI8g8QIchTJIQYCCBA2IYQQlBibF4iBAO2A9hjnNhj4wcDtsf2PO6cs/e3u2ut/LDqsaq6vt+9z507M/fO1Ofe893V1fXq6u5an15rVVUT1wrynj6+KU1GhwdyPsYz4/Hze6vKHgMR2sa5jr9GNcqPl9BF7I6UBzqKrxTEE4tKIw6kxCvq4JINSIwnK7mWLlJLoGEb/srH6o0LFEIvHVx/4vRyoiGKhuMC1yhkw973QtIz9UChGnmmGiHz+jwK1Anf8NNSKuEAoKLmgQGGSsy6CVaNZlVVhkKDQu3LSNUMJiEEVdEQRDQEVuEQgohKCIGTt7yqcvkVjSyAMjNUJQQFQt66yTQucTELijBzlMDMS4yZagTejWHshWGk362wDS6cI6Rf5sQ5CKcTVHE6pb1nzc+UKPESIyXMLfmgNjC1IC+K/BWRAv5/IJnqSgwDG6AmBsEB+4bAUMW24fYWWIDbt6Zd5/X58+fioZU9vPHn/8iXfeOv+lt/+g+3XKRBHB8Wp86aIMak2BCRKFFVYxRNc0Zy6uzrIdXwkkfJ3EdHEBVThVKWucdn1PiavYmwJXxULZbyjpjpc89pBRh5f+9MF9IXDkqYktWC9Kc++uzJzfLbv+U7/Lrgl+zL5mTOyZODizUJ1a7k3rW8GI/aAh4hvPrSk48/u1+WUNbksO+uNPZVoZ5IRl4lzA3RWZQWFtBIhKF6Y/TqO4YyHvi1pky6Dc00qB/5P/1Dy6XbcQXH9J2cu0o18l/XueXzvqMO/mSn8OhYhY/EmFjUatRnObKNVtvhiUVb3UHhUWVoc/Ft1W1PNJfYnBjclEPURUXTo5GcRv0zm6lE5u1tC/JzqvlFypu/p2JIACZoMp8ADAvCHndRMNTG+KzKYOYowmxOGubIJcSAgOuMe4W5fGqetAcwqQKspApmUQQbJ21Qk7xAsqJaWwpHCSHEGEMI0ZQTkUMIO/MSwr7zsiwb8xLCtvMSwsa8LIlqVAXGXsJU6EVwJCMwn04nQG9OJyZW6M3pRPsOZthv8z+BW85B7e+AduR+/XwhIp40DA87VnEhrP5/QAUAbFEpZuxbPcuMbYcqAmPbsCzYVrzCbxHh2AA6r/u63juZb/LfvDAFePnu/v6r/7l/53v/+O/2RCKFcqYY9y6mlAXbOciSSVTVHIDEqEi0QyTbVyT7fRpSCNX3AyVQR6QcGEmTxmCgKVxoSfkpo1Ato7PWNmQENTbpX9/zrpd/+mPPfsOv/RX/5R/8Nv8maPFob6rJqyETilbDA6aNMPVGbn8ipETMtCzB1u2IUcpgn0dMqtcKdctToWgtqE9V+iizrf5t1qwQ6VHjLmgOqAlT+T2cvIi3dmR5POc4SrgLVKMVoi7dRapRhLQXuk7sOxZSmIFPX5QTba4X5h+1gXoopFxLp/BoLrLEVrZRGjbshIud2pTne/GtQ+/DoeXFqi+Jkv8vUxGkia9UWIghT0FLQwmlzyMCVKAEsCZttQCsmpgHEcCJrpAAzBB7uQGwEhS2cXwIqirMgZ32QliXJYjosgS1+XeJWGym8FgCG71g5kUkMgeRwBxELIaZF1NphMjMu6k0Qqi/MbBN0E+solFjJJ5BdHNzwoqb08k4x7bvIYRtszJ432NReNhSysm2Ul06aMw2/G+aYMBmXgK63yWvdko5IJ/VTV68zJD8oRtza/Xy72NYBTKBKIH8TpXv5fQedzyjzVLoxb7nwNYe7qnzbxa88t63qGMiBPfrdn93l7QL2fxRQn/tj33T1//qX/9d3/o78nxTx0e0sory4w6LMkMkO0SLqsSoQIwRQIyiULHfrOGAuZWm9iTHzsxCitojkY4C1O4+DFKKVsRQ3ojS9BQg04oWmwfSxtt1d9eqK81LZObZ9n5U+sjHn3/DV/78/+oP/SmT+prn4SfvT01mjdwI+z/pHYxDwBhD+oIicuYX+yOiCFDgtITA/MrT22d357RsIKpHarpmo1jOyEIo+o4uFVyqfKLvx0doOFLux4mJ7GFXrWX66Vw6vW3Vg5zjcBENM4PPPqIa2vxpUh2pxkA30LGBA9VAIROlkJy44x9DUnKJf1xnG467XGm/v+hSJ+qPDs4dyEVbhuu3puP7CFfLBSwuXZnymv9lJYf6Z1rzJFfK/ZI+V3J7WnObJLWHcJI3JEJMLKSUXERNp2lLZpGKmjJAlZVVwaJq0+0CAlEkQG2beJvqljtjB5gJuzKzMjOz7dgkoswkGpgSyYjJF8OIQgyBd07qjRDCdlRXEC0h8JZiqtKC2cwuIcRCPqJEJt5jNE/3hc2FNJEVYg7MnH4pcCCmwMUvnlpVB+XfEeEwakKEZYGtfAoCk3035ztxDPib1H759Gi+Ei88P9qGjUaWAOVfn/hx3KK+gh05KAFHLAqrGISLGsPFFCZx5Blxt80zUmDfbVvguO/MTMx4+m5gA55e6JAXwf09zmdRujuvMUathKOIe7V9y77+a79u+cr3//nf/4fKMhdtShWVGGNaiCIRBVeKFg9RiVEAjSLIe8dHESDZUMrKGUnfAZRN2SRRD6f8qOQDkrq2ISGFf/TCo9GOUL6X3k5SnobWeJIyFXVqZhuqr7/60ieen3/p137Fd//gh/NQZDaY7PeRLDLIct7oRZ2HYrpVW3s0r+lTH17RtFWSiIZAAEyv+eTmdF733K4yibc+89npBbXmes5dVGNAIcvZgUrfXUAegR9NGkrKbO/BQa2EQ+BxdOZyXUe512L0Ae4Fpk/ZirwDk8iBnjeU6i9QCifaG64wTH9V1eHYSaUaXWQuTcsFVgpyveq+qY7EdFcPbY4GPdN0oe/VBm/q5rtMiw5UGm2M0Y9WzaHVplo2ua2EGdqbH5ElD6ewEIhFhCgzAwgIwkQACwurecQjvfuUZ8bvACuJaGBlFrZ/zCwSAgsxB47EIas0osTAIUb7TZqJEJmZg0RmDtEsI5GZT8sCQE6nwCxOEZK0I8mfdA8h7DGGEAJRMaAwc+AQHL1w8TwkHCkuTcQzP3lK6Zi4cI7TAhGcTq16I4e3DSCsGzh/sxHqWZQwWn3qUaf6Jj5u+KCruBzI78IFMtEdej5xDFxnGPmQyVawaIgFG5+I6YE1MWobnHYSs7gyQFUU0CWE220F1hfvqBFihKqC96jn+/u6ZpaqIwz6Z/7n3/bLf91v+vbf9Vt+5b/6L/+f3/xH/das0vx3jB/ESCUZiXBInROuWbvhL180TSpBnsha/28X9up4hpabhhwuFKQMbFVm+KcDWdVRlBtF0ZEcNhoK8u5Xn/7cG3df++Xv+x/+6J8Dyic7smIkS+88U99qNF5h/4xnUH5xqLqpU5GUmm0aVuLNaQn5M0M0qpaS3fKjrf0iMY/8WlQnj6oOyX1RvPR70JGI1HN9xEFEPw7Dr5Nj/BEPV1Vb1FOXo5Tz1KBLqj75kGfkA/VlFGbQnz3QC5e8yPur/EP1yABcFu2ytFTjSG4aXnJsbVuX6xa4TmjZRtuHD7CNAx8cscBDoY94AJbKLDS7hWpWcti6WSDnaOSVmKrVKVTTm5UoR33hHKiLSoYVm68fhZmVhIlUSVlFiVt/T1ENyiLKzEyqqqzEqiyZcqgy2fQ8iyMRIebTAkScFrDKHrEsS2QOzFE4MEeWJbAIJ14Sgs1JyS6ftIRgFhBnDXF+G1zjjwyjNaDUMBOdTidVvTmdTMlBRKFwjbTFQ2IhtK1MTNvWsA1TbxCDAOLKKlJMxzZKGGmgK19whXzUcYUA1GXaH4B/Nt040AS0Ptc6+n1hkpEDRJAI4kQsjGGYUs6ytMQiMQoU2Zkl64FpHI8JeOnJLbYVcn4rJg9tkLiv67bt2x7vz6sxhE7qG18APvaBr/iqP/EHv7nVP9Qt4T1ZKcEucSncX1s5SO4etbTaQV1ftIew4dSUK5IP7VTq6dLx6Z6kR0HLuFifniagJdCOl+0RAfqxT94vgf/hr/5Ff+OHfzKfJD81Jdt2i/mivApEZSpK1nZYXB4WoZoMu/VBVwVsXgsx82kJpiXKTa2ExkVavfVF84N7L9qLZym1YlmLVantr4voqntLcFE38Ri2cUxzgWegE6ZoxWMnSuvDdBClF6nGSKhfkuiD+PYxbglES0ou8A+f0hd4qaJLVMOfas76LnL9U9K0vT4axfv02ices41rHGSxmI60qrd5Zr8uN/XEHDOqhTQ7j8MpPLo6yVYEEmcQILJJ70ps3p/5g6OcUJR10MsvEwEqIBZz/JRlCTapX0SyV4eqmpJEQ7D4IJlGGGUxqW8Wk2hrZ1QdRIrvGEao9hFaOFD6dTSC+ea0qOLmtHS0o5hNAifmsW4bB163zbQcKZ4ptYCywiOF7Qus0pESruYVHH8PzCMEiCCEscKj4xyPQveYuZegCTzuVzVN3oEmGkEEkfxFq1CkSDhlBgqfyDJtABwVGNfRCVpmWgK9dF7Bp9FL84LQHeezqD55+jI++rNbjPu+pXql/av6x3/7f/sv/Ybf8Ff+n+/+Nf/sr/zWP/ltOnDqzLoIQOqK4kmNoU2GpnAoxFOS8eUDOHKyQiNyGp+69DUS46ijcBlwy6DffKTlgKcV3skgi+BCIV576cknnt1/xZe95/f+yf+7tbq0BoFi2ahmhKQ6TfyektNGIR5Z25HbYKXkGhT69Pb0sU/CJrlElZzKSzxC+zIVSVDft8bUkLO5QbTmttKrHWRo4PCjNfKnYNGx9Kkv4XLCdkbtUPIcS+vP9yJM25Mj6dhkeSTPaCRref7y+ZFEr7m0BMbsoRYyohS1RZeohquoNmIc31bXRneV+p641EtNR7lOddU4XGQbY1xjGwosqLzC2IRbciOdy5wiTWvP+g6n9/CcY9gE0vz5DS0f5qpkKg3SyMwxRmZWs6OKqTnNq4OYWFWyWiOrPdIWr4xdiVhYmFiynaVoCKIwE0c2p4oky82Hg5mZ98CBeT/aO06nE1RPp5Pti81MwkJMIQozxSBMtHNxB0m/27aFELZ9S+ykFkuBQ6qaHPkoTU3GlIZnFObhwkREp9PJNEO2ge1pWdKoCfN9o8vmFWRFMdrfTueR8TDz0DaofdgCZQ6wsQcUonBkHm1kE9MwjCz2Oi4xJhYA/Cc7skBFRyygjfVAayAw3yyMdUW8RzgDTx7qmavYVqSG0XK6FdF9j1FiWfS7tMoiv/m3/Zf/2m/8D/7Qb/sd//wv/8b/7Tv+rKMl5SfJ90Y1onAWE59DawxwoBzI0Wk4FRV0BhT4f4V0oGEYKezvp1aS4djGkXx2z5QbjpvH7tWnt594dv6KL3vP3/zRn3ZaeieI6zeQ1y8kLsHmfzaaogJvTcll+dqTFiS9ns5FQTN/d0K+vA1NI/w1VT3HkIXUmjtn0sP72ZGSS1eA2leVzA0SPkAlUpoR82nHgxzTiLjmpGp/fx058OlLwtKzrYhVJ7Dr2VZSP0LMHzQKvbDPSX2rtMml7pEe1dVwHV+Xu6YXUWwcuqLp1atsw/e1uwsuy+VQW8gF2LkyLfbAORQKr+fQ6kCqvUdHfnQdMQGKDaUl4iksmYInr0KTQ2k5ZCIiZSuPiUhZS7xkYwkzkxCTCFP6j5nlILCZlrAgqm0rb9YXVSWSEDi5izAJMzFHohA4EnOaqBJsusrQ9+KgwKg2EWuDM6N4/1DipMhgZro5nUT05rSk2BRNpfH2X7DPqKTFpfO6Wqp1Xcuv5xyE6vxGfkRNaiTU4bQQkZ55jEYrDpAIdnNeJDZml+4B1QuBRrZcpB1ZlqHhFSXcEAugPTzSjiwJ0+OZRDJBogVIYrThN0o0k2EJKFQD7/uOp7eIEWH9VAkHEyTGuEeJzOHm9uVnz591nKBz0QTOX/4L3//H/tSf7q5LnJYDLvuQYDk2Bcvre7XWlf02UmKoamVsdrtKV4rWIvKNa0ZGPzSXYTff+wZ6+K2oo0glFp+4Oy+Bv+4rfsH/9xMfgcJoQJ0Ck5IfpGn106CiLzSEwEW1Udh54eBiezIBTIltPL29+eTd2fImXkPpYova1/3rJW5l9wOGoWhVHWhzDLoo9/iVrwSXpX3NqxfJJZnSFzQ8e5BQrlkjoaTaZqrd04vAIjqdTG3StAnqQRHuHTNAFtktCWga5bQXreDP5WvHDC6X9rj42ge1YNeSpq6arGtz2x3HZF3Ka7emib70ZIxyHx5lAK3T6IFzwLhvOaeJTgAH/9GxKeXQACUtIrCEifKBZinJZUdZ0sAsghBY8+ig9sKbeYVZlZTTykFmgpHsxCGH3+SPmbQb1U+i0zqEqiNJ8WZ/MR7Q2UduTouaLoT3UAlJo95oqq6eobyuGzOv2zpUbHBedNn4xgXDSu3GbkGB0plEWJYlRjnZLlVkHE+WJRgDcTwkDz9Ok9vqPB64x4dnrQ+7V9S9d/6N0yKwtJxUBRGJRCIyb0cLmJJNYrRH00RfjEJ5b/SSvwLlT+PJMUjmZKwE3k4Lzmecz7jZHnrYr2O17ebVtkpjZubldPvs2Ru+/s6K8Xv/i9/57/zGX/f8m+9+5Md/9GGvEx1cmVw6hz4S7l+O8lnqTWnYoLujjmSkqHbE7h+QdnQsf7tP516HsTD/i//E133rn/megXqDiPIj1j7NmWznd6S8QVzYeba3WDkKcCbjhQMksx5QErtBkJwQ9yK1YRh1mB6wAKCZB6tJFeH7YKTe0FGs79xiZxqjmqIuMYquPDQ8YSRj2g7w2RsZ2FKIknJMMtz3S5NgSEFGp7RWmotwg1MX/3ieMaixZxKuxZdacnxV1PfhgW34XmvKOfS2vxOPYBuH29yHmmqPsUc4H47Hcw7A2VOQ34D0q1Cue7S2RdR3Rd2bpAxSkE1ytUWSxSwuybdDiUh3tQ/8pNRgTp/yReFRJbFwWqh46AnByxJ0j+b1CWBZ8oZNRMwcmZg5ZtLgGUmIkrQUlL1AmZh533dm3vY9e2MUXpJ5hreV1HBx3XAMgxKtCMTEdLMsUeVmOSUNDlEUuTktHecgrlTjwiJGROeViM6rM1ATaE0co3COyjzqKF2HaztfwxfAzCKxPLjBZgtzWrEN2VM4nfcvZPtb32Uv1g5Eoob6g05MKjohehCyA1RxGrZt1z3SvgM2V+X0EP+6hA2yYwkmpmKMUWwGLO/7ak1uPT0Tvum3fNOv//f+9R/6ph/+xl/2DX/2O//qMYn1jzOVDK4R3qrSXSi6zgGya4hLVY7KjUEuGKWH7daXkTcH8vjkR/eMMjRksZd3S3DBgldeuv3k3fkXvO/1/+XP/7WcpCzd4efOORaQ/xixyPQC7GlHeT9QQ5S1HY06QuHfu6ze9ZeC1Br4x6SO5NT+lL5Bk8DV6JxJU/LDsD62bVBZ5eMgRjpcZhnHnDr48aeHYs8FfS6XWAf/LvOMVuIWqV/FuzvtRXspvKEFR+rwovEuNK40Z7zQGB9XS28ux/fDkS74njze9CZx02kY5bocaosYxQ6PjnupjDkH0rwUULu+qJEPP1WWtFl7oS1fq2nEnEbNemLqjeIvSpSUH7aQhlJgBpTBSmqTM1RNq0lUdSFlhi2JGVZsBQ5ngmEhZjHhx0Im9qIIt8K+EAJvH6m6B88SilMIMzOdlpOpV25Oi6jenJZMMExV26guSrFFi+FVGnbqvK5MvPLmFRvrtjqagYZ5pGTepAJ/xEQ24CKPp7a5DIBlWUTiEpYocQkL8kjpDCxu5PTUY4xWlvjhqnkl/NvqXtXBf4UvdIdVTDo6UsUiiMxUQbYbsOnAJC1nHmPa1DSK2AexiIBqKaUwIqzbtu7b7bZBVvAZQN71Bi+y680OROw7ICdbQMrmQ4VFAVsMtKvde3z+j//TH/gP/61/9b//fd/yj/5DX/9/fff3uJSttgYpZ+kczRTEOkYuM4xaBJo/jnxVkpF/0IyI3XjrnoUc9F8pDaiuzOFTuiykL9/ePLtb3/++L/iRv/NzRjVQNljId8tzDl9WdiYjAnF+fQzBawv7p7s51nzVqoUzEI7chrJIcPagxrzS9oGnIE2fNQlKN1J7XOs+SIASSzo62VbiamgK9ie6H1+Il32DMwdZWVL6f1UYdmOF+nP+eWuLcPL7yqlG6jtZXoejJtK1yI9XhwRdyeNTXcNcQ9BmQpsJbZ2jxE3PX3oB21t1KPxwZhB3vP/HiO50nRbr/jjOgbKul/EPJJeoOicWl1Qd9XfkT2rnqDsGNG8nTc7Isqs6I4vYBpZMTJIsBklOixTRO1QAFJ2HCVpgX8Ki2G3iaxX2TIVtVJZAzEw7c2DaqaRpqMO22fJQtMediPZ9p6xWKfNQuBKawm/6uhznqM2/OS1R5OZ0KkoOiXIybUf13chXmihd9ePIR70/R+Ue60pEQP1NymdHLvLRQ6qO8ZjXvASBKZqpK0Y1pUiMxAzA3IfL+zj6LX8Lx2gCWT5WutBKYndc5GgWyU5c1yAAqJxeebqu2+264f6Ml9b8BiE/ywycjpd9gCDutiV93HcAT25vz7dP3uBAFFRha413DWia+8rpi7/ovX/hr373L/36r/3O/+evdymstXKI8QfjeN91lbp11A6Zb9RxLpdTxmInEIa3/xBZB48ckwaXLB/JuTa+/OTm2f0WmP+Bv/fL/tZPfjSNLWWQobz/G7lBDNmSkiwgICJizzaKwsMfEsE5XGdLjDEayWPazbKc1z3rWFy/5DzZGtMP/XlkzSNv20END6FWeo9xNdEFonHMcPhk7hmEXk7tT+vxdCM3W8HZtLCmakTpFYHtHkI4WTqgCK1sz3lrNQ1daPgCtObuuEJzrUcScyi2vyLXC00tTXDEFMo518O1g90/NH/7O+wztvn70KGoCydG54AySwUA6m5s6d2gwsOdG6lXdQBoZq80dhZ/JXVea/E9zS4c6Y+9rPbCK5IthW2fp+LEVSGpCCIi4yIplp2qoxIOSZ7kbJEiZM6nRNGmnEQpop3L/Hpq7TLVg7PTQxDZdFZbWkPEppDY9JbCXeiQuGEzTTgxBm4O+byunN1Fz+tql3be1jR4Hjw5nANHSz565gGUIRi0LHmmcTQPD6RtdUUWW2GxU3vYT+vmcRnd89gMP/3L072eXppV8eeO4eLagBebnZSlrP8AmRspyFbEggL5lJEr1W2P277j/h5p+S9y655RXk6+3y6gRQR2QMGw2b92I5j55nRzurnZ99t9f2Z7nXQ0onCj/+6/+/3/yX/0b/zhb/n2v/Q9f/1II+xPawdRBbwGxJ1qSVrL3RyHqN1/UGy4+1qG44t3HR0brVoLv0cbumGk+qWD9Pn9Fpj+2V/2Nf/7X/zesVbDaxvcs1lUC5ReTCKgvDde1YHkltFZPCrSDGTx47nXxFTXUX/hpg9OKV02pEu20HCgLmaRg8jPGEf2seMiOlHUn2+vYyjSuqvyGbx8rdV4meflZc7s5LFjBoOzY0LQkokrpwY8ow4l7Z7kl0lGd416oXl+cBtRDc/nrlKNwbDprsgX0v/tstde7aN1EDqUduHE6FzCoi3fqMH8bgxUHXnBYFRVB+B8Rw/k44LmAymoZUfasvKHGK2JlUZgbBogkDQWBBOxQlzCKRBC2Pe4hCBEydRSTRJSHceKPqMI+8bBYhiTAlt25ii/NQETXVJgOA2K18SYSqPkTjNgTycilOkq/hpzyUXZ4QB0x+UnfcSVFGcQEVYQiNZ0zyvHyEyDehVHDT/IPELgGMsGrQjMMQoHhsKsXRKFmQDY5ZcH0L2xPdtwv/nP4a8PXKEgXt4WGU+ALmHbtnXbsO3Y9ryEfHCqugDswC0QLtAOATZb8gsSwbQsfDoFiVEk2v1XQNOinwOqUY7+69/+B/7Tf/9f+33f8qc+8rM/07MNfy3dxRw6wiXJg2wO5BOlT2vA/zQ3xKERGNfgLRE4KMeyJaAOJURM/8wv/eo/+Zc+2Go1Ws7hsqAwhjRiuHeBkQYH/8LYJgnVFbRQ8sY6k3rMNRTH2TDUdwzVreBGQ/qlIfviGD/oZB0n9dKskVjHtK3g61rV3v6cQd1hK3xd8rapY/nqOI+T07lU14LSr7YonyfHZFv7HsR8KeLIALStprwUTTtdA7unXtsD7Wu51v5H8YymJ/u75ilgd/dHZTToM3QHhwzjYvTKUYPeaXRkXkGlHdWrQ7Oez74xoNWri8poQyh8vvz6dT7Sb9q4BWm5DkBNDUIpRiMRlUkyFgYRI7t9pF9jIWnui9YzRCTZV0Ok4SIDyc3MhKIyaDkBEdGyLKp6WoKo2gIYnNUhueTiCtJkbxQYucDENQ6J2Sa7cm2GaTXOFglqrqJYTnoKYtQEgEuT/5yWJcZ4Oi0xCgjpcFmcwqPhGa1LRwpQ69jhPwivu3j0D+dajv270o0D5e2s0e5Vv8ZCNE1yEePFtmMZFfeOQ6CLtJht38/n9e7+/un9Pc5n3NrK7pSVHEXbccrr6Ab3eazJewM79h0isJ3SYry5Od3c3Nze3Ky3T7Z92/c9rcnR8I2GTKnqb/sdf+g3/fpf+7u/9dt/5ud+Fp1KA46hpEiMotFGtzzMj7pFopTkaYhHvTfqSEYjWGoaxfh3oPQof+o6GgRVZvqVv+Sr/8/v/ODhQcplVBbSsN8SSq8AQASG+X037wUxo89KJVAuWWwvGxF3DR1bOl6bD5Zxss/QU4iR3qHndyPi4ORjl3lQQCM6XWov65q7ql15XRk9yWhks5PGTmo2LWj5Ry29ff3TefFyNa146wp0eQ6t8sXlJ961pzlV2lCytSoQ3yuHdnZ91NTVdXCXxvdbR2AfRTV80ZdSA83x4aGsBV04cTlfg4PTKIr/RokpeofcAVXVgTKBBX79r0RCoHmJsLQBAmBOH+qMLJpNLfY9UAQcpY9rosMf+/wlIWZSIDArEJgkLVxaIVn1wZl2EBFLDjMRhLkoRCwqJp2HJxyVjdAeIxPZzJR9jz5ByxgwpBElfFoWUTktCxOJ6OlUl/BqjSllGGxbMqAX3SG6U3VUBRHRPZ2J6H5d7TvuTCsR7s/JeyPfgEo5HP9w/znlRlVCE9K23eU5s01tQgBg68eXUzHGcFhAvSXkA9pRInR0WH9bCZl/XQj+M38c1KTE0/O6rtu27fvT84rzGcxYlmrgT8wj5u15Q3YpLXva7cAGFagACol5eS6ltOk5MwfiQMTSTz2p4cwa8Fv/p2/+z37dv/I7/8i3/+zHPvrVv+jLv/+HfrhJUqhFDlziGS3Z6Dqh7cJR7zaywEkr/1vu6yGq3GzyY3qHp7en5+eNmX/FN3zVt/3l74fjF91fHA6Qn8nsvVFNKr0iML0ilSvTiDUXtqGAZvNKoV/dtXoW0v3peuYoKdoCh5SiSaRX0h4+cRtZlUfn2rRWW9Oxga7IkXz00raVekWiN3J4lKCptB50wruT3HrhlOMfJrNqte4hrv8uNsZHS1OCb5aiLfPQR12DfZpBMl9He+98B/r0g1veZx+8msMMg7JHEaMXt4ffLRZIJCMtHJP3R8k9Vk2T0LSWXfWDorztigLea9ypQg9vZNtWrwJRp+1IzqNpv2glIo1p5JBIlPe0tSkzUoaM+kEvVdBmGEdZmBUgQuCg0CUEghBTmWTbynUutgzq2IBXinChAc38kXoqKy3WbWOmddss+rxtzHTe3IQUHGagMHW6DcPNabHZFkbFbk4nU12UBDHG02K2mMYg5ZQZVHoJjvBVmuE0yjnSE44aKBoPP2ifD3fcKUba5+D4B7gwqtXXmdnMNCmg0OqOaut2IGs4VH0MbH4KEaCmA1O1WbsmQlREEsFWfePZ3asvP70/r69tOz7xSYQFWhb/z96FIQAC3GQNB9dLKOqNuEMiiALTEvi0hLQWfuAQwhIWDksIp3U9F5rR8w5AVVXwm7/pW/7zf/fX/A/f8u0f/MEPfeWX/8If+OG/VZUaRwLR0I+OdPRnG3oCV3s+1f5Cy1jcn3N8JN/IksXd5fHwp8DT29PdeWOif/obvurb/srfHKT2pRwGmQHbaPmF/ebIkonS5xSgNjQl7SsA3aOoQkRFdI9Rh1dylCPa/hzP9VIH3ibTCZyuv7rhtWcITSHH7+aDPNM+rw5yt7nyPydK+5Z1xMW/ydquVu0MJanMeuioQUdSW/KRb0t7LQoYU/Bn3WW2BY54hnYVoG2VT1CKbW+ZaiV4Ry5SUz54W12h3Wh5eA/67C71MdRFjArTYfABuM3bXM6BVwdyp2ahkjowSx3NXegUGblL8wb37jevmJ4fIyp/FM4rtU65tQRERGbWSb6mTlTCUQrArTCW6IfnHDYhVqKYwUFYADLR4oR7/tO6RCTDSgjml7osQUWXJajqEgLVzyZOS4WAqCUoTleBxletT+Dis1X52BIiKj6k7pDvu8jz6khYvk7XacheMqclmJHFYs3UsiwLEfYop+xV6g0s1Jtb7JmpvOPqF6NP0D/Dx/EsHw0oSP/xU4ef4eH495JIlcDMdF6353f35/v72yc3OJ/T1nHpGhhM4IAlgnfQjdNwaFJySMS+I9rvvu+7SBSVPcbC8EzLb0tp2BJnmqaz9hzCgr/5d33rb/q3f/Xv/CPf8Tc/9MO/6O/5sh/60R9vE+Rs7urgTTD+Onu9hjvjurYhIUk+1arcwbDv4ZIcBvT2k1CBJ6fl+Xljol/+i7/qTxnbuPA5exWt0Q/Iaoxk1jTy3SVOTxMl9pFrTsNdVNu1BuZXrM3j536a5h1jeuHQiarxE4+2sv7lGImugxAacQVX8YWMXm6Kpj080wequ4Moo73XJFyQr+WWZ1NIOi9tJ0qbrSn24iNR2bBvnH/A/OChTRm1GuM7/QU29XRDz6GWQe/hGO3j2ptVg/7aa1T5+yaoxihD//gcTlzOeg1llkoz4Oe3CkBSc1i52dZijR8bWVBnzyZK4f3I075v2e00uZYau82Uovm1ZcSyqYWZbD0FKsYTLV/pF5gHETmf0ypuTQki9gVseg0nn230Z6JIzESR/KwPJpv4ykSIMRLB5sFu+96yBEvsavYKD6IlW1VEZFkW+/JOVpWSGgP+0R5mncUhDVU1htNqUHbraHujNPL+DNd12chyNj9SOp/NAGNPwMHaUvQcB4rh/tBS/EYJMINLjABCCMXgEmMM4bhoeg3FKDZ7tsb611+vBYZEpD3R/BKgysx8Pq/bvt/dn2/PK54/x9OnbmV3AjM4YmcsCzgiMPiUL1sRFXtM6g01fQwCU2A6BV6WcDotN6fTdjptpxvz5JB9c6uPV8bRKSN+y+/5o7/x3/yXfuBH/+6f/PPfmU/gSB36v03KnNr9Hs4cCAquHXj2kIZyn7Qedmmb+3K3bl/yBa99zZd/6bf/1b/ZJu7veSPJ2hGNkgaKuteEubBjp5hr+Eb1MFNNtZtiw6xhItX25cb6Vlx4aTZ4VktsK0cuUwr3dVdSNKlVm+mCuWAakBZtGlBF46iV7ZsEAGI04CDRh13RCGDX6I4c9Cl9plEzOq2Je3jas6rI9Mg9eJdL6B4tHSTwvf5InjHkmnqMavK2wea+HyrweV21ffwguos7nHs44mEs1ibbJBFAeU+1HOQUjeIDj6cdqB7kqFmOPEy9FiTNuVciEi2bMpPG4uSRVOKtyh+VdRCZSQIKE9hKTQIiEhAlPw+SGl3/pFhLF4mZELP3JRMhVkLQWGxsLDPVSrGMDGjBuu9MtG07Ea1bIivbtmW/k0G5nmeclsUIiilsbOWutJEbVWbhcnvGVXlGT0FKh9beHXf1wM5SQkDRfl0mHylLZ3BpE3VPyfDN0fbg8OoDTCxiC36YxyiYCVmFwMwloGmvdltZzvY1s1VDmIh+7uNvvPry07vz+vL9+cQMBW5vmtYsC4gRBYHBARyrzUWQdBvZqhJjFJEYo6p/Ifz9DnGNqNRCRYoflH31mRTR3/r7/thrLz/9lf/oN/yF7/ngJ589+wU/730/+rf/ThlYC2HI9KEykYP4T78dabjMLmrivpCaApXNlPvSipmOGN6elvt1I6L3vf7qG3frd3zXD2hzvhWWnUQqd4MGD1Fry3NEwywuzXNlJWZHUagqKTSqRtUYNYrcb7uklVsbltHIGKRx7ZCg6tVd2xuyUq61aZW2aUbyLLlONm9ItSN0NZWUvqYrotRluSp6WxF5vEudLmHQFUjkSVzvkAmF/nloqhyTGGS/m6vXrhgmcGzMn2lrr+EL96W90Pae9uV3VR2yNCU16N6DwcEo27FRj454LJzTqJXRajtKubbohqcdKIq0IlOu0o4y1zblrLNnUTQfmXL019ZtUW/8o0TAJqYgbSwNLeIyKf0kLwLkBWoTk8UrMyvU9rgPIbTSujIP03xYRqf4qELeBx3Z6PUcngpcpheuzDb9um7EtK5biltt8fItt8Rn8oc9sTgt5gKSAssSoshpCQTaozEYuOSVR2Re12g1ugRwARr8q9aWnPkBDNlqfla6F8q/2NrHdvJvHEglbmn7HjkF/pmPfvzlp7dvnJbXQyAmiCQlhyVdNzDj9hbMYOMcDDXCoYiSlBwxQkTVJsuATDnivXWIQ1ho30G071FF0uhCkKj5tTA2DtvW9ec+/snv/Osf/Lf/hX/y9/yvf/aHf/zDf8+XfPGP/Z2ftO5SqYN8WWwURXLlk1K+4lXtkCjtq5i/4l1OdGOnFi7kPiLtw9IaUXO0Y25Vb9iJJzfJaeMbv/4rvuf/+4mPP7s7SuP2Xh0eCW0Hle4xO7wX5fFR6sZ4Mp4hmnzfVSGi+y5R5O68RZGk8NDuc73/OcivdDD8zO0e5VYN0f31dXTlNPRcfc0Xcw0UEm2W/sVq06e7n08k07l1DlHmDQPhWqhp33J7En2PJJ3fOKV/JPq+GyfoBHzbDBcepB90YD5St+DlgcaVlM1D241e2qRug11Rg0L6kzoIdRHD8vroC4kei4PTqF1l+xUwOpuPcmR+samq7RKhSFlKON+GAbfoaqyqjqL8GDGPwj9Q/Eyp8o/yWV7EY5a23nCQDyWS+XbkabQlsxfSJRxCUNUQCkEh0c08OTw5aGlDx1Gac54WHElJmxBFNKXr4iZvueq+GU1yENH5vFlksp6sFpmYwzmtQNorPGyJMADFqyPGCKJTCHuaXot2lXTEvJhYp+FA/tNKhZLk+mMyPNLDHz929EILzbjfDqr5mIkAPS3L3Xn9yEc/8eT25uZueZlAN5K8NzQ3nhlRwIzAWE5pc10jHCLYBXvEvsd9jzFKTHoOEU2qDgDAspzWbQcxUVDd9uTMgeOvj/jpn/v4f/MH/sR//Gt/1Qd/5MN/7q/8NQV+3nvf87d/6qcv5bWro7QyaekSTzqg0PptrN1/XXFlykbbnWpvMmpznaTwFd/eLPfr/vx+fd8XvPqB93/pn/6uH3j49lwaZDX1OrQMJOWDSuFIRhGQlDyF2wSJbJEqBFDVGI1trFEkRr/ZTa17+EU7Pn+BT7h/jyjE92dNNCYlVQDnu0NuUbFKEPOI68tPY36+0X2DtcS4B6Q+PJ6djDUTzYVcavahasX4GrU5OXxmmqL1cKxFEOWc1FwHDtdRTtS1QOrp9koPWfqb3ge7B+ByIYODUbaL5R3ihpW+CYyHcycDBgnoyh+XqxUkIyVmFSdEPpn/jHaBseq++e30/I5u+Pj6U7/1veGgnC/fP15Uk0taTg4kerZTmOxfQhCVJQQRJXdYGtBzi4aHXGA8B47ik6H4bbgL8NlRrre5zHJQD0vKq0oOp+podR7dXSu3v1CWRFaAJYQ9RgKFhWOUpZ1GG2O0mF3iwrYKagw1wACiiJ9kq+1PiWsGocG/fhC1gebmtLz89Mm7Xnnpi15/13tef9cXf9Hrr7z09MnNieosXwIBxCDCsoAZISQ9hxrnEERFjNjitm3363Z/Xu/O6939+e7+/Ozu/vnd/fP7++d398/v7u7u77dtu7u/P5/vt32LcUcV7y7Y/tqw9Au/5D0//0ve910f/MG7+7svfe8XffinPuKTZc1f2mu3/Ceap7M3/3W15P3oy0eDpyroyUFJWFJWZ0M0fX17s9yfN2J677tfDsvpb//Uz3V3YySu+g/08nSVp5SIzHPbpsKGPCG27NkY8qk66dy9dMx5g2giENm0lGf367O79ZN39/fn7X7b9z1qI9g6Ifc4PtE9r7mr7d1pBX+OKVQpaWLStYtWvzmXN38MFuPOSFHhbmM5rglH96Iv4NAT1+lF3xvXGEb+1yVuG38ssLtY/xKl3rAHdNwb3SX5Eps+6dvdDTleZnfFaZ/hU+UZrnGjXBeyDOPeKqphGC/DXB5P4Lq2oybI9y73Zfreo6zi0EIfNCcgIFlbXOeU8c5mwsKvHlb1GrkSK4KKnylMy1F+j5TkEvloxGelESgaECeD879W2+FFtyMfBAIT7Xskwr6bJQa2zYr9emWD5wS2rZpND4kiSzDf0tDTiwMFqVqZtoVo0g9SOppRuUhH4OpZHBlez0Xckd1hlwzAmh+stTATpMTrmM+WZOb2EUK4jysuYAm8RwFgzqfJLzW5ayAEVhdZEnDiK2pkKO3qAnOaV2a6OS135/MnPvnsdApLYFWx1dIAqJkViJZlCdWNg0EE4vSYiyDKvkdb4WuPBtljtH3jCGTzY0MI67YRM4eAfRdRm81bxIUq0gr9qlwtIEpEH/qJn1Tg3/hV/9j3fehvf/f3/1CM8r73fOHf/emf0Sa7AlpG1zR1y3QdRGob3Un67hcVe7HUU4t8KJI8xC29zWk0YgFoZjbIA7IqGmn45Ga5X7e78/bFr7/ygfd/6Q9/+Gd+7O/+DODKcXMEyA2CmhpbDynPZfXroVf5azqMPGQlgmZzoQmcNp5UAghkU/TJvCFy9aJ63vZ1i1Ekiu5RRCTdFwCaPv3LGJWuk3yYUv952V/6Amj0Cqm36iVTcdX05R+lfM3VS3DtvrwvfK8f23Vs6DB9L+CHfKW2qy1lQC9q+kED3ATaQr8OHYi2wJbu5BYcKVR7yVdJRnM5g0YecvmLQxM7rO9qOSVEozIPSS9QiE8z1TDQY1McaEefnw5Hbf4uhpwMoUG6+iHc6DryHxtWOPMPIyLMpKpcpWIr+/wnuJOUHfnwMhi90O20AlUEN/yjZy1jOlIrcszAc52GFTTsAQRaFtvlNQUqO7HdT2zmSwgXiIWjHaVZ7iJbVtEzj3pHmm6zMbqlGu6epe/OcmNrAN1PeTIaGjJ6vKg5+UIvSPM2c2BjGz7S3viQV/gAUWC6OZ3e8/q7XnvlpS96/bXXX3vlC1579emT25eePrGnTlWjKOWJRUtYOHDgwDYdgm2RDxXVLcq27eu2n7f9/rzer+vd/Xpek6rj+f357v7+7v58Xs/ndV3X9f583rZ12zabFaXIVEOUCVFsX+W0SVDiDVAm+pov/7Jf8g98xfd96Cf+6vf9vwq85wve/ZGf/ajTkkCzV4dx/UIOqoNI4Q1ScvRCzHpfVcj59yELA2SlCB0+u82GAtX3vv7qB97/JR/+yMd/8Md/0qexAomqIGmalL/prSH52dHy+qRZ6W4P+qTbIGLm4Jb/ak2cCVw0HEREFFVjlPt1v1+3Z3fnu/P2xvP7Pdr0WMCIWvdRny4E+RIGgrk+dK2Q015A9ZL4IMi7TK3w7lo15hZH9UanjWhaeaQLF+mFT9goG3zWFPQU0zfJmFoOdEX2HeWvfNxR7jov9P/xZEnfDCAtL+lYR3PUNazJOyi4PXeBZ2B8cIx74PTlRG8ZHiYcTbrue3NY0JB5HGkHjvLlAeZxkYUcRFTLMA5SEGjPI/OBJu4odDum0sjyln/AkQ9PFxo+4WT9kbJ02ohKSB4iDZcYRmIkIUQRItg29KewNEyqqc5zMbgGjqhb06XupmTO0Jyoz0ilFA0F8VkGz1RPUZpH7BquUPvhh0HzbUSAqTdeevLki7/o3V/07tdef+3Vd7/68isvPb05LSEEIgrM0YR3FlHLsgQOIAQORKRIi1TuUfY9rntcjXas63ndnt+v9+fz3fn8/O7+/pz4x/35/ryu67qt27au5xhjjDulZdqtceUj18YqJSYRLQFV/fqvev/XfeX7//C3/d/35zOAL3r9XR/5uY8BkLr/mJYyubAWVWPwFrA7IuV7P+fS7JNK2bRPSOzHfClzILWRiJA9QwFlon/86/6+n/roJ7//Rz6MMgcBbm7CyMBPzo0gxZiMIpSXN1lSqLAKVAKRqUb5dXzDEY7CNpgAiGLf4/2636/rs7v1E8/uz9u2R+u262SiJyC+6Y0VAG1Jl0ro6MihhAMf8KmaSsayf8wt+mY09V7KcjCgFCKL9KgUetGqGS71Qyf7D6SqvejLl3/ogQN36sT1yFzSd0kp1Z0ejS+X2cuwnP7kgzwDh2u9nP96MW8lru9sWVH6i+ofGiTAFcdSAPl7x2RLeTJMdngP05r0uJ7YoWlli5csGNKolnSbRERqi0gmjwpAGqLhZGieZdMSC09lBrykTTbSGox1Bo5K5LwNf2hSjOrqSybyNfiKsIKIaKXNoldsy7Ks230ZnW2HWLRcJBbdSQgglCW/CgtpiEVLL9xPywtLsnreHeQnyyWvN7tno/5BeDHy4XFpGEDzzlJatJRAH/34G1A8ubm5PS1EJHq7BGEm1TxG5EVpl2W3dWg5BGbWtKWLRtFsTIkx7nuM5kFqjU+iXdV26UEWvQqymS1x36txA+5VUijAkulITDHf9f0f+q4PfugXf80v+uov/7Lv/aEf/74P/di276r4wne/9rMf+3irdMAO5ew6LSIRIKI6NcAJBZ+R8o4zRKQqRIixUKLKjZ7cnu7OGxTP5Pzed7/6gfd/yc98/Pmf/q4fyOdRpiSk8vzVjcL+PhLVbWfTy4y6YFTIj43ZUdJgYgajtCJs+nq2/82WJqJgkEABEdmjRJHn99vdedtjNAdSNwlozANwTSR3ErLt4pzclzCUpg0P6ERjJ6Mv6TZ6eXuZFblmaB6Vs/IpD8XetNF6jRBBpFSgsFWwxo08XlpHQnp5/0I6jCOFaDtklGLUOb5b+qPB6JIfu2Oxh0voT108OMY9QEMeSvdpwQuOzMdsB+bRpxn+aSO6SPIRXXafy8f5jAfBdhCEKTovKcb2LeiEYk8y4IQmHVK0LKQlH+Nkx1MNSRlxl5ZlHCjFpXrbjG2xx8JzjG19QqCyMX3Wi4TYbltvcsXoiP0nUcISqJuTkiso960/bu6jP0J/evTQHZ+YQ5Ijrr5o/ZgGAEy0LOHp7c0rLz15/bVXvvDdr73+2ivveuXl1155+bQE21MvD3912fvkcpgMKya8TXSp8Yxti+dtW9fsQ3p/Xvf9/rzenc/39+dt3+/P5/vz2baOW9fzHmOMu01scSNwI1l6MeO4wT/yD37l+3/+F3/fD/3E9//IT2zbZidff+3Vj37iDZdqWNjhDBox1eq3m9RZnwEz9Lz39Vc/8Au/5OPPzt/zA39rSCcOnOaiIId7HtKblZ92yu6i3oZChLS9YredSn65ysdATmApoIptj+dtvztvz+/X5/fr/bpte9xjWmvUPysjXnRVcDai/Ngf7tI7kfKw+eAhYnHoW6MOqF44KXnLLag40GQzR1lWC/AKqraKQaMecYEPXeOFvF3/HLrl0DNNazrp3qkxjrV3jeyDuXPoBUlGW8jx5MUKL6W4mu7TizdJOPr8l2lHm6ZJdiQf3Qcr+VTtIXUSxqeq6dxXdcs+qK7hASTmAU85FMrEpfSGf5RELrqlHMNTueqDsPepjwSl5yUDilPGyraoAwtp493BiDMd2dWRdsSkETFvEhR2gkxHAIiIrWji6uruiLs3pfuam97FjqOoPzeKf2H0b2Vgfnp78+rLT9/96ivvfu3lYlW5vTnZWrFah7iyCV+mG8wAmSIkcQ6RfZdt39dt32O8X7fzeTuv6/Pzum/73fl8f16Nalhg3/fzuu4xbttqU2qz5mP4Peg/lHsJ9o//Qx/4si/+QlH9Gz/44z/4Y39n2zdL8u5XX1bFx9745OUSBh/IPVFQBfD09kahd/droWvvff3VD7z/SwH95N32Vz74IZf20r8BiSm1+HtP+eEpbJ683wYRERpLChOnzQdsj/qG7lPd/CjxDShEdd3jed3uztvdeX1+v92v27rtkhUxXacPJatrfi/aHjIT9IYJFz5GDxnPkbT1vS2Zaqik/i1uNADI2UEucYsLFOGC6sKdGLCkwxU8gl4cU7XV+e54EwzjkOhIBQaS/VhQn3mQ7+rJh+q8HP1Z4RkFnyrh6At6DPM4JDsyj2PkiHy4lIevZHR04zIRMVfTTq4DZGqPcuSEZUcrerZxLKonLY4HoAp7F1m4SCITTSGXKEhp5iFNT5gGLKqlRcdLLmzD1wJKi5QTUQicnFgDH2lHUofYtNUaYALFGJPKJGtKmtte79TxqGcZ7vFBk+xF4NMXwWYjBgHEfEpKjqevv/bKz3vvF7771ZdffunJS0+eLEswmZX5BgCYjDPGYTN4zbBifg9RNEbZYkycY4/ndTuv2915Pa+r8Yzn9+dt2+/X9Xw+b/u+bfse93VdY4zbvomISFkWyY/LfXj4T4F/6hd/zXu/4F2q+r0/9OM/9OM/Cei+72X4fuXlp1nzrW88v3cjejN8P31yUxTkz8/nMqrZo/TFX/DqB97/pVDcrftf+hs/2LOTXnKMJdJRlOQq7B7VJ79xFGWyqeeOajBbmrHrBop6I5HFrN7YRcyB4+OfvHt+Xu/NhddWou21O8dLaS5zcJ8OV36RixwFZFvOkY5o3rhK23mzSJOqSuMIyEqLTDWS9sJsIgo0br9t87u2t1xnwA86AnDI9KnTi7YCV/5byjD6JFkVdIjv8g/OvwjJeFSKh5J+pvFYH44HUW5vng9rxzRIgzIkZxJdUvuHpHAI/yDa4KJUH5h6Y6ntVTPm1qrLngg2280su0yIMfnAF7WHKlSFiVRyQ+wbB70YLjTmKIm7Q0JNd+Ai3X9HRQOoy+zJBMYZDuVcL+FQXUuntm1L9MKxCgLFwKbDWLcNwJIDMUgUoTYgEkNeaQOEPDGEyqzCGKPnkIWU5FvasJGBwiM/MoPINupFWYgrmyRGqC4h3N2ff+Zjn4gie5Rtj09ubhZbe7QOK0QEdiBQmnabp7Qkt4A9SpR9j3ta+6uOS5TvkclNTaKBFKRKoohRRQXDr+zDUT8FUvEdf/l7Leqf/iV//3tff+3dr76kqt/3oZ9Q1R/58E+/8exOVWOM6vMcwm88u1OFbVYM6Pu+8F1QfOD9X6qq6y4Avv0vf/AgB9vhvw1fErfdyOke9TSR3jbXUYBBapOE2bwxbJo9VFQZAuLkupE9Oih5fpA9ZgoGqWpUACqiWxRTb+xR9ij7LruYjumC9DwwkMvK/BezI/jzB4E6knZanGjgPI1TVpGiokgjoQooEQublgyg2FBSKzptx6XnreuZx3GLEanq+qWmO/TTkV50lQ2r6VvrrqYt7hBsmqIXErj7SX0FFw+G0ZeZw6BNbzu8ZYSjwDGPfHT4FG2ZR03WUBX/KPbkoyYkdaTjIvloQaR5HmDMC3hYTVScm9Jy/ZaMkBZwR9mQLlGQJPi0CGlUNYEdlxM9+RizEBeivrQBrbnIZrpyGg5xqZy+rU0WAIRtIxACc+IfzOu2EVGIYmtIRBGJEkLIATavuhDYFtRcgsBpPmrRLU8oj0whJY5t+M7zGepRzt08d48nGQO27OT/xqxACPenJZyW5WZZTiEEJgBlI5usFED5fq5WFSIATKxQEUheuXJPDojmgqhQzfvbpTkj/vvbhn17ikUholHiSNM+OLykhP+2v/TXfQG/4pd97c977xe8/ORGkQTN933oJ0yaJLGjRWrpB97/pRZQxRYFwJ/9ru//sZ/82W5Q7z/5u2F69MncD/f9DVVnB0lr9kh5/xWgRDVMEtsy9KJgQARMiIlqlJV7jCNaKfb9TwpEkW2Pm00s2ndz3dj2WJY0bzv2eKVDDnE0NIy4SJPtSNIG9fU7kdZs9ccvKZbXgE3vkaim9aNTByqQVhZTG+80F5NDncDv7tpbwC1Gkv9Q1PGKu5r66AO9GNYzKm1YXJ/i+PiOoi8IqzdHMq436bOOt55wFLSs4gHmkZPBURU6nhqRD1d4OW1r/tQbSak8S5A/AVQzPU9y1pSISG9hFnLpLctjWOYYmYJUTX6mIJl+dKJ0QD4uqBNKoGcQLseDKpaWhTRF9Ikv5WpzBmZjFQsn84qwOW2wrc0dUkCDCMx7Q0IXSNqOHEDTCegr7Xo4pfUPATp0xKQ/Pzh1nYdoric/qkREJMl9Qq1DAESRl7bde3IgDy2ZcJDXc1DqTFLRKBqlLnFuy1Zq9gywqqtxjJLBwOSsURYBoiAtsl1F0jUB2Hwuu38l+H/8xb92PDuWK4of+fBHDuaA8eGjv/KvDedUHgLT/eQVupigbu9eETCTUqIatvRaYhtpUFDS8uol3QYDKhDz4BI145dRjbt1uzuvd+ftvG7rHu0Z8FfyGALR9l1OOxC6x6/5I4849mgj4n0JXXmZVVSViGYtkKhS2bEip/FcRPOTnR9R6OEKRmzgTXALXOix/PdYYHPmCps4FDGuos95jWEcmn2oa3Rwsf6HmcjVuLcjPo2Eo8A/W48xuMBrR2Aj7oF8FEtiEZjlibZPElB9lCgvRXe4heoakcLZEkNpOErhrD5MdMRTEKDVgoAyL0FLDKrkyAF04r8NeALSUIIhBem5SBmXL5EYAITAQSSa5t/WiwzMIsqBVQSozhli1hPmVdQCeecqBkFEgzAAUQmSvEQTq0izSQGUAMzzo97W5rLKna/sYshOurw5hf9zKKA9e51udEi9TZTWJw0UQri9u79ZFuMTIOxRbGFTP/qYJwCQ9BygtJ6pDdMN55AoIsWwkhQ8RSIifczDB2C2v7TCR1GQ4KJQuxjTC4nD8Kyd5DyO+CNCcUVwXpCj18bP8swTAapMyZICm1Cbt9IzZYamcSCbSglpaTP/v9b9mBJ/YbBASShbvrYYk4Zji9setyi2xmi1TPgr6EXIAwoJ4BojuSiqD6UMVEIXJLOmYN5c3iUzAqCaC6xcxP6m4dFiNHMRbYun5FXaMBKgjqTXLry/yOZ625hRB40uf1DbxVqu1vXI4oZRl8sacLNj+w70451CMjw+E4TDwz9PjyIfcAt7KLJeo5CS8oCnxzkxBleHleDNLUnxmk6Xd6rWS03BBDxMQbQaX+AoSM7a/mvlaPOniOBL/MN1WKON8CcHDCb5KkaAArNotH3YASirrfcgEkXFaIeIhPSpSLaOMoHsa97IRw7AFP5WcRuonMaHqY/qrrq9kmPatlzXrS6Bq6lJejg+UJce49O2IIetnBGFABUVFRHZ9ie3N6eyRY5Wi3r2VWTbYIfyFFlGUvWrOQTklbLznudaTfKpxZTEp41B5SGA2VYsm6T/LNPxG64ZSw8xnBYqdaevSsRhjOZy+jaM5OiDQqXc5fKamNMGEcRe8PS0mgh0L6KqpCWJVZF2viUkVw9SG1GoqDesO/Ma57D7ukVZt90mp9yvm82GTeuLats3ta+OLMoFr3WGL+cgsI5C+SqlKGf6krtmtX+axFLYiaZ8bl11pD7uSzPzS7GAay43Mw/re7elDrUX0PdP09CLrONTphejU1eqeIhhXC3uWnOGZx6V4e2OzzTh8Gipw2AxsUGy8nQ6ygG0Nhc4YVQnPV/kH445UnkTi4g70JGGghjVqR4cmcaTI/ItC7GcQ11ITz66cKcRYSLRJPxUlZmjKAEWYCIilajMbL0gUVWVmTSKqHK2I5l6I1EEgtjaU0SyR1/xRXLjW9oJ8hJBHWPouEJTjs/X0YbOgHKgIp6DHM65UxdYRsdyLoKsf0QUCIFv786n03JzWgKzuXLE0Cg5ND9PlGZpclmQg6joOdR4nhmbCjRvVprqRbYD5idbFcQMESMxth9LcgNRpbwjjEHTnreZLOZIF1Jm3iQyV64wUnQcRNiBJxDRLsJMpa6jrKTUGPXnmZr1G6gWWH4S1TDOwWXFLjuTxB/ZTwqYywuMalASmm6LaTLywSCFWVzStwsQRfc9qTfs/32Pe9rfdyTlj/LwqOY5kpK2czou0BR5/JY/qqaG3X2pjOO97GX1gIocJe+xGGliMi1pytJa2UHkq3eqK4NzORg+gIfGjWTzo7QXOFTxMJ24WuKwRx9M94iC30n4bBKOAkcpcseOyId/2MlHtKoSOP6R/l3iHyiPseMfNRL1wT5SkMxE1MrVYtVB3vYhE4o0FlJuWDosYaZMVGzXKCZzC2fbOovTS0dEapFKqqqcxt5IycxMgBJJjAQk1pCdLousLl4wKs18kI40HClEo4Q4KC/K8YB0NJK/sX4c6FVXVV+Oq7QtsC+zKb6NbNBnPia4fGKLvEvSIhRdhIhuT+PtzekUFj9dRVVDCMX3s6zMIbojMQ/KKnpE2xesKjia0SZ/ixMRBZsrZNoUe0iYGRoFpjXJOv9jMVAokxnLUOgFMW3bxsR7jPVtYFuFIqnfc3ZXEgBFWvzbsQci2jethRPZGugNmzmwl1iDadqLLV7JbAuYGisQBaVN9uwNVIBsN1Qq76emn2xMUQVsZkpaTttmrpGa8QUk4LzwqCWPIvsu657UG3fnRr0xYmK9lO+4xgVNT+3Go2gZ6DkuFX9kP32tucj2fFvIgaY0JbbRlzrgonRtOqBv+QUD3bFrtEtLuHDUXA717Tq2+0KrL0U9lja8ABN5XJ53Kt4WhKOgpRSuww/8o3sZRvzDZXEJHP8A0E57KZmuUZAaS+6QyAzIqXYiUhGTv3YIEeMYmmRofaOUy8rsNuolLhONQ0gq3nTrMa/9F2M3Naa0b2CXKYm6q+8+H7vwKC4XW/909Rwr7UrqszY/DTs5tniQ6MBOBiThoOuox8GE34hZlG3uvT6glMgkImKC8LSE27vl9nQKgUNIVhMWFhVkpfG677aKlIgtWI4QgukkbI2pmD0+zVIjapusIk0EyOMmExOJUQ2k3VvESEzMC3IwkSYWkshQ2gDFLXYnokA0Xcu+RXN0lahMtMteNBNMZNNfuO3Eo6yVTYCyE0rekIUpbuaso2IbKwLbJsg8xuK7osoSfMVHgpns4igtnq1p40ZO7D6/JMkzVPPG0eULWtW+GtQ8Ri1PrkejIBP45FVqZK/x3tjjuu972tdXh+qN8vi1F1U5Ffl1LNBL7KtcpRP49e+Ao4xij6U+hlIc2tjWeRgVuzxjqXndZjLKc0mBMcxSLr8radBRDeXpCcnj6cWwUY9M+rg8nyN4exEOjwOl6FjEg/zDRXcqEJdA28I659OUuOxs7VMAZWOYpi4bdmycKztHavGiSoV7QwzyJhUAvObDjtAcoiFEnfgd0IBjbC+UqfvMP3hgjgt8BB1pGtW2wdfbltY1ppZfP4sPxTOTuJvBzIUiECh/JddnxDOJPadj4q6F++4/tnsQgSNLzNufqSpg8xZE9GaPpyVQS1nMI5GIZNuYOdj2K5K+4zWrB4wi2JQV8wK1vmImxJSYgMAUicRmDzGTSGBWtf3Y0q4ulPRjYrvNq8K0HrBF7RQi0XiAJAdW7KLMJDE9dLsm314xj0zpR0XTupVDiSW9ApA9snmdKABErZ7CskfYDs/dw2JU25qN4l2bDIKiSlAizq+WaXtSSE1saFpPw6q1nZaKfj4toakoi3ZkIwtxfmFFYZN+tj3er9t53Z+f1/vzdl736r0xYl1F0Pmn2xJlJZPaw1MjSwobHBr5Sb4K880ckomaR92/ceP6k0c+4S9kUMUh55thFReyPUAsBhmutqHL/gCDeESSYbEPJr1yvz7P8PYlHB20DT2Sf5A/djqAcQJA/ZlmF6JMQdKQho4Ot4NmtTp2TSqDq9bayPOW6kNF6dCd67gIsiOJ5x8P0hH4ljaaiE610OsVOq3EgJr4RJwHbyb70G9iQNCYIlF2KVPAfQcTwXxQ7Ir2qGnjPYUpCZAfgz1qXnIK6IWiblHYn+41FukyBFfpxShKVQnY9v1+3W7X7byu96fldt1U9OmT29ubU0iTUwBAM++EzXMRiVGYKXM6orwpq6rawuead2G1vdA09Ywa1SBTb1Ckut9HsteE/JzEfS+GGdTN0GBroRTZVLrDOk5iosndFR++/lJE7N0MszC1o25obSlLbG+WdZb521rPJVuhpufHusqELjMh2zKJSYFAKZwIhb2YfLBK2CRPJbFpK7D+T5zLVEppdz3b1zemVTeSe03u0U5y+uGgVDh2dumGMyCrsdS/eMlPMyc2j9eSNfWGlecGoByfMlNNn7N7y5MZWTu9C3y57aUdrwXjJBdYzyHfIdn1TI+R048kDo+LunL+auoXox+fL3jHEI4OB+5QVysdJisH5KNHxhefRtuTSHPR2yc/MYOSdchCXPGtO4iNCUV0t8yHMndwY0PlIr4NxcXtMh1BZSRcpqslEkBlQoF9RBZPkUIIiKi0M5MndV2CapwiAKR5aUpBtCbHSCWm9IDkyOxTYgnqRYtWHuBoAll86d6WQrS8CtkT1iU4gMbRF2NT9J7X6rL+NPH5yktPzaySVt1wtzv789j8y1jSFEljaTRPUynrgGV5kMSDNSBzDDCR7WjDRGWNMHPysKqjKUs0u5s4VQrg5fElEYpHJ0BDVa4PruRe3KzOy2Qh04V8TrOOgjLNON6ZTJSofBoQTPlEZO8U5Y1k1RFmVTAqFQPMmLJHsa3azut2d7+et6TeaDxixuqG3Amjc45iHCKB62Vrw0AyI/Gptc+oJQ6OWjakyCta1GUZNP0awzjk0aJ2yvcVyDe4GysPpbxZYvGpRF0/P+nFW4B3KuEo6Ia2g+cHOonxAAVpiqiCon489IUnkVtfep9AxweaZGJbqRQ9gxJIkyacivjVJGmOo9DgzdXmW6i86SmlrUlJqNuGx2ySiGlXc+cpYjk7rU0/3B91JH2UC10Q/YMycIhquVOXsm3h6OzFoi/wigEaH1gRUzyEwM/vzskmIgJojGLrgMGJT1TpTsVQkgmHmT8AEwYCUbG1zzURmvoduwSWtJEemy8Jp5XZtO0Zsukcecqn2uQmJbg1JLQxEAwFpakQjgYVV40WjcnlMbZ7BkiRfD4IeXcBKPwuBEXVZlG2vRGQ91bskTsokw4T0KVUpZyE8lxaBdh8bvPNUWiMGkXMmHJ/Xrc9TYFOm9FfIlRtzx37MP8d05ArEu4B7nI9c3N8qaRhMSNKdIledecOLTtw2j7JYxnGOGk9Q+63OTkmOMPyXpiMPDrn5zve8YSjw4hPvAgFqbmQiIa9DFQe43RWq0qlNXu05WhO42pNKxG5TO6VSx5w2cOtyB8r0ulxSv5cXCttO9vvsaXli9I30/2zyEOHjUX0cdWL/nhIJXpHjmsZLhwMCzi2oT8q9p3HYFxOriI7WigAYlrX7XxaPvHJ5/ElFdVTlJvTQmT6hSTnsh47KTZCYBG1/Usl7+kDpNmtyeciswHK/JaZWEnEbCjJxSEEBoLuyC4ZMDmuZscCi4rdLTPQkXsU1bHU4hNTvJd0r4aX8StjGhq/YHaeV5V1ZkmrYB6dyf3T2EZ1m66002iBWQg47aNYVTspsSVKV1QbSJxX8yqCJm+ThEw+bLMVtq7Kj7wpgvYo67ZH2zMlyv26F/WGeK+L4ZfGxW7qUl58Ahu5fYUC9LHXHujRuRflE33TrhV3ofpHvnIXaNGD3VUPB9f7QE++GZJRRMLkGY/E5xrhOMIJZvdWjZjHIFddXkz9sQ2w/h0aqEB88Ve0IE1Ec5wE1KWGURtj/KCuUObzpFjPenCBKdHxXSfvZtJRk6bNJRFxWUqhkpr6GZkXYgKQF6JQUJoHUYzK6VNbASTXQncKlP1As3tGzcu5ziJwrUm+uWbfKfMp0KHt9vFIpblvIFHSBA2TfKL6rldfPm2bqj69VVHbKTfNXLUmKQCIyc4YIzPbaq6+Q02hkD6pVbPngaZJKIC5xJqSg4v3hqoGc5okiiACRaI03VQgaalvImJA0rZlEDF5XDae9f6J5ZloZG3XOcXoUzgKkplJiCi5i1bXBpLWXwFFqZHZQ9LMUEMvksLGfoybUNHi1MSZZ6itzJFVhrVGKrwD4OzkYczOzGQxyt262TJf67bb8huKXgF0Wci7dB2D0KSqPEQD7iVqnl73tnccJBvpXLgfaqi02ifrvvj7W6uDgq7hogXpQvJr5T469hH1XeAJbybb8MykGi+Ez33CUXDk851cfmH9h48efvi7xBeICIBHchF0I8SQjiDvq1QGqCTnkPQlVHQ3tiZj+TAV6b5QgTKMjbqBCn9xTSqtlHakswOt3RGr4Mk7qihi5XeFJKWsxbJzOIWyj2mu0Xv++nQ9rXONAQ4dOUh84TQJMdO2R143Wz9N8ySLV54+FZEntzcxSHXmqPoKOzLekCZVE5JjDWUfT0VaydQWES0UmJlIklQOgUWFhZRImFhJlZRIOalMiJkUTEohwPxx7Y6LSF7S28w6dWHZ1LTqsdAzjYvuC0A2XlgXpWZnYz6lhWty/5rkrx7VXdcncsts9ANU5s0SilNumzFRl6wuzPNXQPVNdbxE8iSytJGe6rrt53W/PyfCYcaUpGh6UFeQoo7jjT85FPUXZXa2fV2s2atdDqU0g0YdanSYxBc6ako99SiGoZ7l0LFh7SeWSzIYWa5X9Mi4F0kyycRbjs8jwnHEBTJxkPptqMuYFbZVyZHH0CTP81DglALdJ0o/WDZpnJwsA3j+e2Wy/SG7mrf/MUFiIyjCTN05Nx6Qrxte13Noe6P8qWeLkmmgPhiRPacgGkb3cf141qW8Sh3I/32AZBwzC+W5C6f781rpguDll56I6JNb21CWCqtDWjM+PyWSHw8CC6szrCiQmEf+U+plIlvshQkLMy1WNCMnVqUyB5gJMSKKKJvIpihik31ElRkqMJUAKJtUzLmyKs6Q2nHou+Mboe0zn/QN+VvddBMpfdJZFKVFMpFwVnJUqkEgc3UB2vQt68iMLxOM3JI8zaU0MrOgZOcy/991i+dtu1/3ssaX7Q0ro2vv0TCzh9JePH9B1F7hd5eOLg0Q15rl/j0aVzhK1X0MGjMcg0cnrlT6YNzjkgwY0cRbjc9rwjFEM3T6F/8h8tEPEn4t9hw7lpzaHOgoSU52QR2SE6t2mcYaiAMK1+gFfzd0eauMHgqqC6aW2tv2l1L9NLxsakmfnE7vrk48A2hsLqhipjEQc41s5z8chGK73NegMy/haIJRTRvNK8BEzLRu+yee3dkklSe3N6Ly5OZmCUzM9tGX1BXOh18VeT6wKBDM9SGvKaKAulklSLYGMJEyqbKyqlIInFmjwBa4jylZjP4SNG3IZ7YsESWS1CWKJIHrF3Phttr2e2GLpH33lrtvK2sV9wugmkusMKMOyJ4llGPLHJz8NzMPAuf5xFS4BpF/aIveRPPDVvw5ShounwqkqjBKse9x3ff7ddujxijrHtc92kpf/knx78UjhPNAHHdu49cEdvP3ME7Q8ehqc5zT8uPdmK4078qJF0z++IRvnlVcPz/Zxqcbk3Bcw4XPiysf3BcVIT5qIM2vchEMhpn6jVb1xcVcXdNoMp2AUwAAGSRJREFUTpN1m2ntgTIula/MJMgOIxa52vQK4SHPKIqWRrsE5TJys+oAmMe0Zixv8pe5M4OzGWUCjq/Ppbx4gx6v1YiHepOMFFm3LesW8NorL73x7DkUovr09uZO19ubJXDIkteUBe0yFE7BokSqsM9qgvnEaF6aI9EBytK/SGVmViCoIgQiilHyVYoqq4lysXiYkkMgREFEyBZfDyQiBFIjRWTWhsRA2N9a75VD6VQ2XaTHKIt5QiJqeqQaOQNlBUYNV8KR2QZnNVEmIcY7DrcxsSR7Oyr/yE9GTaaUdusV0S3Gddvv132PUvag32NsJiZfxAWhfFFmXiIqFz8o0L1Ro2RtI667kV5lCVc5y/H4mm7gcfTgQJUeKPUxhU8C8XbDJBxvBh0R6T+UOy3B9ewl6eVCB8dF++JnGSQlSvvOJiICuG+xZiY/GtVIy2jQjT+mNhheWP7wazUlaERAn6NlKIorfebW+Ric63Me+rNt5rgE/7ckfICHUO06VSFmBJa784o8yTW7XuqT2xtVvTlpWRvDaERNUeQiJfFsrp12cWUh7armyIZ78yE1VYcomKBJ7UFmPUk3mYgioojJ7j0iRlkCRzKPURZRMp8P5tSunDXXWXR2irxTSeqqbLlo+6toLuq/fF1l/fLsh0FUHUUtXaUgiV0webaBwjf8rdLkn6R5S11Ni3YUbwJ3hwmqYm65KGxj2/fzuq/bvu5p+ZK0S5vmah4Q+ocz12jFo3Hl+X+BAh6s+IVem3r6kc260lGP7aRPiYFMfJYxCcdbgOE3Te+RCgyE8KUS2igaVnJgIF1Gpz2+JKSPdY1jm1y9O30dgBsl7cC+U46KME9zB1CsJ5ITHbKVwtI3tBMeKpoXr+9UG7WyC73VdNpjRIm2cyu8rwxBVfS84uYU7u7P1pQQ+JPP7yzBaQmqenNakFbsViswT5FIrov20W/OtH61ierS4eRfNqykHjQtQCIKSdjahFJEEdvEPVCa+WLbnQBggogwQ0RYq3yNUtbBItG0An92jqjdZQ8FExeRRtl1KbGNrNKwSk3FkFQVWtQzWVtT+US2pBARZ9eNVv+R7yLlW9DdO/co5fTl7lm/i2gUiZIcRWOU87rfr9t520Vkj9k558ITYe4ioyflhSVf5nTF6+uh9HZZTQlt1HBgOqoSHnPicRfzAPH61Ip48bIm3naYhOPThYEao4pqRwrqZ+FhwLxSFJBHf5fqMNxelLPDQjvtSM3Sa3DaoGcYVS3gHE995d1oVqVmP6R3w3pfvbn/+ZbXyobj0XHsPdK4Ns0FTQ6aph7KzAaVGzw/rzYX98nNjZ1/+ekT8ztk5hA0u6SkIlVV3PwVk45CaldqC0uUBiQZmJ1JAVCaPMx5pVYiMAhC2QUEICKOFEUUdKKQDCtMEoXZFirlKMqkURSkxAHGP0hZQ1Kh5Qa3nZF8ZrLbDWzHE+RHzswvzIyi3jAOwEnEsqMdDefI9AIlEpVtNAwiv0LZXleVGlUL4vx+rP+yo+h+zl6i521ft11Ett0tInsZg9P98/oCIrKf9Xrx4FLc+Pti8OI+Kt/1HC+Y4c2mnQzjcwaTcHzmoIdAClXZ2as1hgfjosa5R984Azl6rf6LA1FXTp/qWM3FcjqXt6uon2GVfVBds/ng0NlE66HvL6Sm/rq71IdaLEIAjaoK2gDg2Z0SKDC/8fzekpyWANyeTouqhpCkr5r8c5Jc80anpR6bKKI1vVbaUVpQtQVmkYASwcwrIDOalAuUtDUaRVsQXZLCgwmiYktTiArSGloQ18RsSlGtNLPx7skqh1bDkW0qqOqGzFGqx2jRXqCnGlmBVZkG3P0e3nfK1VJDNbKxC1Fk22IUPW/7/bZFkXXbz+tm65qXLegta8MFkxbisaJwrGto2vmYpLWPH1XxmxLUD2V6i8nEC5Y48c7GJBxvCwxeuZZK9PRDy5B7VKxeKLDkS2PlNe0I0joJV7jJQx84w8UwagnXtSYP1No3Vsdhl/OBj9TuWh/23h98V9aAimCHTXwwm8jtzYkAAk6nBaBb0SXwSRciUN5qDPmbO1tYmpvUdFrOkDlAdiM1+Y1CO5SJiBkEIogoVChwBEiEhHmxmbEUY7anMIkIa7AtZ4OSwpbqQEDxNoFXdXSHxW8CgC3jSW56CBMp6oyVRDvUPDbSYZqt0xMOOO5RblvmECj70zcPNpWMIILnHBpFRXWPcd1jjPG87uu6m3pj22MUzWyjXNq1x+Oh4+u4yFsuP2WfSnWPz/SC5U5dxcRDmITjnYGjJqNdEtSiukxjFvKgdgTZZHONCF3URYx1K4dPuKsjz6OVI9eb8mDOUkB3rdQEr5C3wSGl/VWiQomWu/MKgAjP7kBEr9CTZ3f3AGJgVTBTCHXqjREOJ8LrclVAse4Dbl5xcSZV1xZSIsob74kyCMQgQWARATMTRRLRND/FdBtKIWk7VG3pdxO5TEFh+6iobelnJi3Yiq9Z4ZGZnU3Zzcu8FY5QrBtUbCypseamUogFU88zkHUbxTRSQ/396hJQ0XCULjIWYZaUbYtR5Lzt523boqz7vu5Rkp1FtBhorj8L+aYM070o9/hU8OlSKExFxcRbhEk43ql4SCmCRi9SVSE0GhkfpSAp6YqaBL2m5KJiI8c+yFOuVn88T3jMQDeqdaxiOURcKlwvHWpedCpGWbEHsfXLEaPYd/bptBDhtCTX0RukQLoZxTejeLgkHYaXsU2vF3cOy5b1X/bNr8nvkgEwVEyPYItwsIaoyW/D6jELS9DkVRpgrqaat393RpXeBFSUHdngUDaUJ0o8pOgzCOqWMynaCy0WlmxDqcyiIxjtHW06x3mSmmajTGexttpur7bX/Hnb9yjndT+v+x5l3eK+x7R/TUPjxiT5zSgcPhOU4s3W9DgVxQO8a2LiMibh+FzG4Dur8bW8riAZRA21I1c0JYdSLo5UDylOLhR5KG9YwKjWFxwzH9swAOYyaeJNAJy3DcAexT61b/aFiG6WHcASAlQ5cNC6QIUWpX120TBRLn69cMcmizKkZMoaEZPyhWiAQcQsojbxQ0ShrKJgYWLbsyWtxkEBUNtSzriPzVjRSjOo+c1UVlPbylrilDQdhSVlt1DrVc8nKgU5nCq3Yeij49KmX+dVSsgeF6oqCtvxdd32TDjiedvP224rima2MdLvvUVi9tOlYfiU8z0y+WQbE28ak3B83uGKzCeXoCqhh9/VWj8ljyceW2OG+1p/KGnK8BBxuVrJi517qNwLyRWACKAirETETM/vzkS07ZGItmUB0WkJBHCkm9OJyObKAk6FUJw0TGRK3vcLiZe0leZsRTGSCYpNLkXer0WZWEQCE6nt/mJbrqQJsYl8IPmWQkk1zVjxOhjfTh/MHqPZUdd2m8uNMZVD0YRkO0s654hIeZKK6mJ8mzzbKMYYzzdy42AreJluY826DXPgENG8F2zrivuC+Ezne/Gsky5MfBYxCcdExVhvcUGb0W52fwg/znhyzPwovBlaca2S8bkX0GoM1MxpXS8oRdpg+gwB4fZ0IsK2JMMKgZYlKBCYlwBQWvILWbHRCvjOjfHwEV4+zbOVw3mXpAvKXhqsIgRiJlUhJckbuhr5UIWo2GzYjLTPrPtFNqZkBYdmLuqmbeclSrOOg1C4RO1j7iOuT0BJSTwbyfYYP2fWOsp4xC4SRdZ932Mypqzbvse47btNSynbpby41eAzZyl562qdmPhMYxKOiTeJK4PdVc+K63SkFvDm8CaG4IuVvUBZg6R+7epdBNsuIsmZg2hfIhHdnCIR2YJgS2A1HkDV5qAo/KJaTY5sw1nM1Iey22k1WClgbpqiagGFKligwRQbhKAkKqpg5bQMhe1FVyrIvKb/Ly99UWbOWmuzraTxKYI/cNqMgYpsgEJcUGhHmdvia0jTX6PYyuW2rpcZU2KU87ZJohqVbbj+/KwZUd7S6icm3i6YhGPircfDA+XVFINFWi8nfRGMU78lw/rxm7haPkhVNJqMB8UgBDqdlmJeOS2BiGIIAAVWIoQQ6toVrUOBOmFfq6jXojVZDeYMaWF6zQaxaghjkCpsazmFMlihSuCyFqyVaMyD8sarivLLdXEOV7geF+W/0H2D4OXkrWLDG1Mc50AxkESRmPQZ7neXfZcosse8R03pwou387E4pp2+lhMTk3BMvO3wWEeOxyf1Bb957cm1zMeGOK0DAEQRIsK+izAR7RKZsC2RCDenhYhOy6KqyxJsQ3mi4vjYuZBWNYOtIdqvTVlTlZY0HqV6oCnFLyRtO2KLlVJe3yPNwSUjODYJR9Pck/KbD2zxDa1FH6btXumzvmED+Okoyf+jrByW2EbhPaa3iFLnpMSYftfNzChR0vpmgO/IC7fzU2EMk21MTEzCMfFOxZu0nhyyHT9lfTwd0x58a723wjig0DxvRVVpoyBMoJuTMNGe9Bxx3/cntzdLCAoNzLZ/CLPbd8y5M1ajRnbYcE41KbKKUHWnbRqLcyhNZ8qiXURs/MGZOdpOSNTDu/va2hvUJ7cNYoaOwa0XkFl70C5yV9M639Gs4egm0FoqzfoYUbUJKdsWd5G91XDYsuV1p5THLxo6MTHxZjEJx8TnER4jVPTqYR91/Ca+EDDpKja3dd9FGLbcBfT2dCKi0ynuSyCineMe45PbGyZhZhIEZkc06rd2cZ5onExTqt4boS4o5owsubws7P1llqU88loaebKrd8XQ7C6ajEcWTaX0uqFJIUaV0eUlw3NhFlkZzWGaSqEajZNo5XZS/VthWg1btjxG2UXWbd92W1pUouk2nN/GxMTEpxuTcExMfCZQxK/aTFkVUBQtbqTYY9yXZFs5iRDREpiJOKQt0KjI7Vpe77+hHbNAlefa6ke8pHULeADJP4PKvNockZlHmsWRN0dLzhyJnqS68/IXZoEx7qADhqH+b45s3T7R0I665nlJkAtVQCStjhpFzEW0qDSiJHfRPa0l+ilOgJ2YmHhhTMIxMfGZg2kCBEJK+w5hMjfSGOXJ7c3tKe4xvvTk9ua07DE+ublZlsAiMUpgZua0t3sqq1FLNDqORpPhiYUzurjISk7KCW1KvQrKBpoUIM1+Gy4SQLNumc97pWjPKZpFznN05k2qKqJGOKLItsc9xhjlft32KHuM6xbNdTS7iMrkGhMTn2FMwjEx8ZlG8hmwSajYRdhcSmOMNzGq6h5Pp2XZ9vj09mZZAjMtHELgpcxecfuWjYovfy5yjmbuSxurTimCzF68heYRktoZVWxejNdqtCqNtCVLPye20V+0a4lSU6oiqmS2ITHquu8xyh7jtsd1S8xj23ejI0Y1JtuYmPjMYxKOiYnPDoxuICv3z9jiEqKIAnuMp2W5vTkBOMWwhBCDLBJiFGYqtAPV5bOuJG6TSYZOkJVkODVGS0AGZKXkBh7FNQ5J1LWzDeaLQGtG6RQbNZH3SVXVtOcLoortJb/nZcu3Pe5RbE6KiFhYbDu6qdqYmPgsYRKOiYnPGkz82QSWKHoS2QObeSUbAraXnzw5LWFZws5xWcISQozCgUNZUDPPYOkK96IZRVEBzzuK/UX7w9xAVJeLzse0WR3EXdIxSAfu0rijNG6ozjM0HzdLmhempKq2o6ut2hVFY5Rd4nndd+e9YbvC7jGmLJNsTEx89jAJx8TEZxMKQDQSmGSPSY5GkSc3pxjDHsMe5bSEl57cnpZlj3Ja4hICC4v5dBTUApN/qoly27DELdPVsQlUmgHnBOLPAdU0k6NcwP9p4OpK+9UTvHIjNZnLXJd6YrRvSp6PY7yhGFCMcOxRzuu2Zy+NGGXdE9uw/+dslImJzzom4ZiY+CzDJLxAEaGqJCSiAE4iMUqMsu9h3+NLT41z8GmRJQSzrQS2tTo4aQbckh2pdPOaaM0YlQo4S8cFhxCgt4AcS2kiq8so2Ypg6bA1lyCrNhQg7ueldA1IRMiMT+YWKpLWD42iMcb7dY8x7ilG9phmo5TJKJNsTEx81jEJx8TE2wLmi6AgW73Kvsv3ICHGm2Ux4bos4bSE07I8uT2ZbcX2oTXeYbSDmdq1ySr8BNcyneQ4DfZRnhquVJe+TFQp01SAsj/8ICNg19stIlYVK0mrYdYTyet02aJeNt81GVCSbiNt+brtMZmrpmZjYuJtg+E3xcTExGcNaa1uIiY+LRxCWJhDCDensIRwWpZlCUvgJQTz7TiFwMxLYGIKzLZeaFJ5oHIP788BlD1Zin9H70vaOWs0NpTWmIKWIgDtwePhiipEQfOaGUWrUVw0yjTXKNF2RYnJmSOW5UMn2ZiYePtgEo6JibcdzD7CRGYuWUJYgk2LbXiGkY/TEgLzkracDcwUOK2LriirZPU4zljx01X6k/DcI6cDRsyjmRELXGEdzVLsdepJbk521NAYBUDiE1GqViOKLRkaq3mlrlU+qcbExNsNk3BMTLxNQWlRTTLn0NNSaEfwtAOApx3GOaAodhZAW79Sh8HM2N6BFAfagY6CdHHoSMZhOstIU6KqogBglCGKWtgcMmymiTGPzoxS0hQbyiQbExNvT0zCMTHxtoYxBWIy9sBES+DgFB5Z22GEYwHUIgMzVEPWeSjAeRZtcptwK407ZUO7/nkNwzETjOnH+BAtL0GhBEWbYbNVy8QTAKJJmQFgj9EIh00/8TyjqDQm1ZiYePtjOo1OTLytYZKUBEqqqkJp0Q6OtAc+BY1R4iIxigKnZQ/MyyInEShsZXQASwjJQGPMJS2FITZtFoV8pBobs0g3Z9XD74ZSprweDCVJl9EtclrmjxhXMAIBQEQLzyhTTgBEIxxJ4SFp2dA84XXaUCYm3v6YGo6JiXcGknrCSINNTmEOgQEEztqOEJaFARSbi9GOwBaZ9mNhYoVaZNFzmOoDajFpzgqcdqLVUnTeoa3TaF2xNFlpVNLposxQQG3uiUr10nBGk45nRBGJCtSFzMt818k1JibeEZiEY2LiHYbi21FoRyEfSwgAQuBTqGzjtARVmAkGgKUxv5DAZKeSpoKrwsM2htVc45FgtEK+VzL4ZT1tWREAWYdRvTRiUWZIoholxniGpbG1REWl7Ac7icbExDsOk3BMTLwj0bmUmpfGwhwCm+oiZA8PAKfACpifhwLJ1TSwAlnPAeZEO0JgE+Y2t7adgwI000vQ+o4miCSFhmkpkEmGZvKxx1jOiog/NM6RqEZatjyZWhKJ0apBmZiYeAdhEo6JiXcw8nYqtm5H8ioFEJg5MAHmYQoLMBOR6TOMiHidB5AZBrCE4JUYZrgBRuzC0ZGY6YUliOb/WfiHFkpR6EVaY0OKo4YkZxTz0gBgk2OzUmNAbiYmJt4pmIRjYuIdj+LeAYCTqcV8O0ogeXssIdg0FtNzaFZ+5FOJghhMHQLgYFApGJ5PDMMO971qLwDNnhmVeTi7SXXRQFZp5K3ljkaciYmJdxgm4ZiY+NwBlWmvZm0h0pZ2AJr9TKtVpZCMourwtKOYXfIRcEHNELMlxWBUA5lYINOOwjBQvTrSqhviJrBYLdN4MjHxOYNJOCYmPgdBecfVsuSXmUs4hZkIxe3Dcw5vPTG308HKXZeQExWGAWDP9pTiloHk0pEUIeJWOpVufsvExMTnECbhmJj4XIbZWZKrBxLzKKtuGAsJ2V2UC+1gLvTBdnV5DOWI0nhzFoWH1EBiFeWw39FlumhMTHzuYhKOiYnPC6RXvVCPwjnIe4CAq/Wk+pA+FpkrRK22lTIn1gLd8l/TZjIx8fmDSTgmJj7vUMhH+zeRD6DSkS7e48gTOu4gnlv0i5BOmjEx8XmHSTgmJiYKBUlmlzb2hdFPnO3YxsTExOclJuGYmJh4AJf2UukwtRYTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExMTExNvJf5/XL72EC/3IAUAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img5" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [], "source": [ "# img1.save(\"pi2/a_19/img1.png\")\n", "# img2.save(\"pi2/a_19/img2.png\")\n", "# img3.save(\"pi2/a_19/img3.png\")\n", "# img4.save(\"pi2/a_19/img4.png\")\n", "# img5.save(\"pi2/a_19/img5.png\")" ] } ], "metadata": { "kernelspec": { "display_name": "SageMath 9.3", "language": "sage", "name": "sagemath" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.10" } }, "nbformat": 4, "nbformat_minor": 4 }