Files
simpeg/notebooks/DC_schumberger_Inv.ipynb
T
seogi_macbook e0d9c27d87 Result of SimPEG hackathon
- Incorporate field class on DC
- Add IP forward modelling and inversion
- Modify notebooks
- change folder name form simpegDC to simpegDCIP
2015-06-03 08:29:05 -07:00

786 lines
216 KiB
Plaintext

{
"metadata": {
"name": "",
"signature": "sha256:29c8b78e5b8f768bcf861afb186d1d85bff67ec768eba74cf6c3e85da81d0c01"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"from SimPEG import *\n",
"import simpegDCIP as DC\n",
"from simpegem1d import Utils1D\n",
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"matplotlib.rcParams.update({'font.size': 20, 'text.usetex': True})\n",
"# matplotlib.rcParams.update({'font.size': 16, 'font.family': 'arial'})"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"1D DC inversion of Schlumberger array"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is an example for 1D DC Sounding inversion. This 1D inversion usually use analytic foward modeling, which is efficient. However, we choose different approach to show flexibility in geophysical inversion through mapping. Here mapping ($M$)indicates transformation of our model to a different space:\n",
"\n",
"$$\n",
" \\mathbf{m} = M(\\mathbf{\\sigma})\n",
"$$\n",
"\n",
"Now we consider a transformation, which maps 3D conductivity model to 1D layer model. That is, 3D distribution of conducitivity can be parameterized as 1D model. Once we can compute derivative of this transformation, we can change our model space, based on the transformation. \n",
"\n",
"Following example will show you how user can implement this set up with 1D DC inversion example. Note that we have 3D forward modeling mesh."
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step1: Generate mesh"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cs = 25.\n",
"npad = 11\n",
"hx = [(cs,npad, -1.3),(cs,41),(cs,npad, 1.3)]\n",
"hy = [(cs,npad, -1.3),(cs,17),(cs,npad, 1.3)]\n",
"hz = [(cs,npad, -1.3),(cs,20)]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mesh = Mesh.TensorMesh([hx, hy, hz], 'CCN')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mesh.plotGrid()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAADtCAYAAAAcNaZ2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c83c990>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step2: Generating model and mapping (1D to 3D)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mapping = Maps.ExpMap(mesh)*Maps.Vertical1DMap(mesh)\n",
"siglay1 = 1./(100.)\n",
"siglay2 = 1./(500.)\n",
"sighalf = 1./(100.)\n",
"sigma = np.ones(mesh.nCz)*siglay1\n",
"sigma[mesh.vectorCCz<=-100.] = siglay2\n",
"sigma[mesh.vectorCCz<-150.] = sighalf\n",
"mtrue = np.log(sigma)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(1,2, figsize = (18*0.8, 7*0.8))\n",
"Utils1D.plotLayer(np.log(sigma), mesh.vectorCCz, 'linear', showlayers=True, ax = ax[0])\n",
"ax[0].invert_xaxis()\n",
"ax[0].set_ylim(-500, 0)\n",
"ax[0].set_xlim(-7, -4)\n",
"ax[0].set_xlabel('$log(\\sigma)$', fontsize = 25)\n",
"ax[0].set_ylabel('Depth (m)', fontsize = 25)\n",
"ax[0].text(-7., 10., '(a)', fontsize = 30)\n",
"dat = mesh.plotSlice((mapping*mtrue), normal='Y', ind = 9, ax = ax[1])\n",
"cb = plt.colorbar(dat[0], ax =ax[1])\n",
"ax[1].set_title(\"Vertical section\", fontsize = 25)\n",
"cb.set_label(\"Conductivity (S/m)\", fontsize = 25)\n",
"ax[1].set_xlabel('Easting (m)', fontsize = 25)\n",
"ax[1].set_ylabel(' ', fontsize = 25)\n",
"ax[1].set_xlim(-1000., 1000.)\n",
"ax[1].set_ylim(-500., 0.)\n",
"ax[1].text(-1000., 13., '(b)', fontsize = 30)\n",
"fig.savefig('mappingDC.png', dpi=200)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAA6AAAAGZCAYAAACXL1z9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wdChVAKeWV3DQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10e1d9710>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# fig, ax = plt.subplots(1,1, figsize = (7, 5))\n",
"# dat = mesh.plotSlice((mapping*mtrue), normal='Y', ind = 9, ax = ax)\n",
"# cb = plt.colorbar(dat[0], ax =ax)\n",
"# ax.set_title(\"Vertical section\", fontsize = 16)\n",
"# cb.set_label(\"Conductivity (S/m)\", fontsize = 16)\n",
"# ax.set_xlabel('Easting (m)', fontsize = 16)\n",
"# ax.set_ylabel('Depth (m)', fontsize = 16)\n",
"# ax.set_xlim(-1000., 1000.)\n",
"# ax.set_ylim(-500., 0.)\n",
"# ax.text(-1000., 20., '(b)', fontsize = 20)\n",
"# fig.savefig('cond3d.png', dpi=200)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 11
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step3: Design survey: Schulumberger array"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src=\"http://www.landrinstruments.com/_/rsrc/1271695892678/home/ultra-minires/additional-information-1/schlumberger-soundings/schlum%20array.JPG\"> </img>"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"$$ \\rho_a = \\frac{V}{I}\\pi\\frac{b(b+a)}{a}$$"
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Let $b=na$, then we rewrite above equation as:"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"$$ \\rho_a = \\frac{V}{I}\\pi na(n+1)$$"
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Since AB/2 can be a good measure for depth of investigation, we express "
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"$$AB/2 = \\frac{(2n+1)a}{2}$$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ntx = 16"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"xtemp_txP = np.arange(ntx)*(25.)-500.\n",
"xtemp_txN = -xtemp_txP\n",
"ytemp_tx = np.zeros(ntx)\n",
"xtemp_rxP = -50.\n",
"xtemp_rxN = 50.\n",
"ytemp_rx = 0.\n",
"abhalf = abs(xtemp_txP-xtemp_txN)*0.5\n",
"a = xtemp_rxN-xtemp_rxP\n",
"b = ((xtemp_txN-xtemp_txP)-a)*0.5"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print a\n",
"print b"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"100.0\n",
"[ 450. 425. 400. 375. 350. 325. 300. 275. 250. 225. 200. 175.\n",
" 150. 125. 100. 75.]\n"
]
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(1,1, figsize = (12,3))\n",
"for i in range(ntx):\n",
" ax.plot(np.r_[xtemp_txP[i], xtemp_txP[i]], np.r_[0., 0.4-0.01*(i-1)], 'k-', lw = 1)\n",
" ax.plot(np.r_[xtemp_txN[i], xtemp_txN[i]], np.r_[0., 0.4-0.01*(i-1)], 'k-', lw = 1)\n",
" ax.plot(xtemp_txP[i], ytemp_tx[i], 'bo')\n",
" ax.plot(xtemp_txN[i], ytemp_tx[i], 'ro')\n",
" ax.plot(np.r_[xtemp_txP[i], xtemp_txN[i]], np.r_[0.4-0.01*(i-1), 0.4-0.01*(i-1)], 'k-', lw = 1) \n",
"\n",
"ax.plot(np.r_[xtemp_rxP, xtemp_rxP], np.r_[0., 0.2], 'k-', lw = 1)\n",
"ax.plot(np.r_[xtemp_rxN, xtemp_rxN], np.r_[0., 0.2], 'k-', lw = 1)\n",
"ax.plot(xtemp_rxP, ytemp_rx, 'ko')\n",
"ax.plot(xtemp_rxN, ytemp_rx, 'go')\n",
"ax.plot(np.r_[xtemp_rxP, xtemp_rxN], np.r_[0.2, 0.2], 'k-', lw = 1) \n",
"\n",
"ax.grid(True) \n",
"ax.set_ylim(-0.2,0.6)\n",
"# ax.set_xlim(-600,600)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 15,
"text": [
"(-0.2, 0.6)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAuQAAADVCAYAAAAfHeVEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noxWyVSEAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x1104a8b50>"
]
}
],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(1,1, figsize = (6,4))\n",
"ax.plot(xtemp_txP, ytemp_tx, 'bo')\n",
"ax.plot(xtemp_txN, ytemp_tx, 'ro')\n",
"ax.plot(xtemp_rxP, ytemp_rx, 'ko')\n",
"ax.plot(xtemp_rxN, ytemp_rx, 'go')\n",
"ax.legend(('A (C+)', 'B (C-)', 'M (P+)', 'N (C-)'), fontsize = 14)\n",
"mesh.plotSlice(np.log10(mapping*mtrue), grid=True, ax = ax, pcolorOpts={'cmap':'binary'})\n",
"ax.set_xlim(-600, 600)\n",
"ax.set_ylim(-200, 200)\n",
"ax.set_title('Survey geometry (Plan view)')\n",
"ax.set_xlabel('Easting (m)')\n",
"ax.set_ylabel('Northing (m)')\n",
"ax.text(-600, 210, '(a)', fontsize = 16)\n",
"fig.savefig('DCsurvey.png', dpi = 200)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAbEAAAEyCAYAAAB09O7HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJLXQiBFCCEkt/z8zAwkz3y21HgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10e2f0790>"
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We generate tx and rx lists:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"txlist = []\n",
"rx = DC.RxDipole(np.r_[xtemp_rxP, ytemp_rx, -12.5], np.r_[xtemp_rxN, ytemp_rx, -12.5])\n",
"for i in range(ntx): \n",
" tx = DC.SrcDipole([rx], [xtemp_txP[i], ytemp_tx[i], -12.5],[xtemp_txN[i], ytemp_tx[i], -12.5])\n",
" txlist.append(tx)\n",
"survey = DC.SurveyDC(txlist) "
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 17
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step4: Set up problem and pair with survey"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"problem = DC.ProblemDC_CC(mesh, mapping=mapping)\n",
"problem.pair(survey)\n",
"try:\n",
" from pymatsolver import MumpsSolver\n",
" problem.Solver = MumpsSolver\n",
"except Exception, e:\n",
" problem.Solver = SolverLU"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 19
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step5: Run survey.dpred to comnpute syntetic data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%time\n",
"data = survey.dpred(mtrue)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"CPU times: user 6.05 s, sys: 708 ms, total: 6.76 s\n",
"Wall time: 6.01 s\n"
]
}
],
"prompt_number": 20
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$ \\rho_a = \\frac{V}{I}\\pi\\frac{b(b+a)}{a}$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To make synthetic example you can use survey.makeSyntheticData, which generates related setups"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"survey.makeSyntheticData(mtrue,std=0.01,force=True)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 21,
"text": [
"array([ 0.0186522 , 0.0211157 , 0.02374998, 0.02677094, 0.02987307,\n",
" 0.03446037, 0.03920482, 0.04541832, 0.05344991, 0.062497 ,\n",
" 0.07516488, 0.09013051, 0.11364832, 0.1407387 , 0.18918521,\n",
" 0.27485483])"
]
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"appres = data*np.pi*b*(b+a)/a\n",
"appres_obs = survey.dobs*np.pi*b*(b+a)/a\n",
"fig, ax = plt.subplots(1,2, figsize = (16, 4))\n",
"ax[1].semilogx(abhalf, appres, 'k.-')\n",
"ax[1].set_xscale('log')\n",
"ax[1].set_ylim(100., 180.)\n",
"ax[1].set_xlabel('AB/2')\n",
"ax[1].set_ylabel('Apparent resistivity ($\\Omega m$)')\n",
"ax[1].grid(True)\n",
"# ax[1].text(100, 183, '(c)', fontsize = 16)\n",
"# ax[1].legend(('Observed', 'Predicted'), loc = 1)\n",
"\n",
"dat = mesh.plotSlice((mapping*mtrue), normal='Y', ind = 9, ax = ax[0])\n",
"cb = plt.colorbar(dat[0], ax =ax[0])\n",
"ax[0].set_title(\"Vertical section\")\n",
"cb.set_label(\"Conductivity (S/m)\")\n",
"ax[0].set_xlabel('Easting (m)')\n",
"ax[0].set_ylabel('Depth (m)')\n",
"ax[0].set_xlim(-1000., 1000.)\n",
"ax[0].set_ylim(-500., 0.)\n",
"# ax[0].text(-1000, 20, '(b)')\n",
"# fig.savefig('DCfwd.png', dpi=200)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 22,
"text": [
"(-500.0, 0.0)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAA94AAAExCAYAAACK4HpVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3X2QXFd95//31zY2JkZqSYB/sFUgjc1uQfEgj2TiPGAU\nS7JJFjaxpZH4VUhZqUgzAsLuEmyNtWTx7C9kNZLJJmAeNGNvqsIG//BIMqYSQmyNhNiFJCCNpBAI\nu9gaDdisH/an0UghWH6Qvr8/zmnNnZ5+uPd293TPzOdV1TW6t8899/Rt8O3vPed8j7k7IiIiIiIi\nItIcl7S6ASIiIiIiIiJzmQJvERERERERkSZS4C0iIiIiIiLSRAq8RURERERERJpIgbeIiIiIiIhI\nEynwlpYys4KZXYiv1SnKdyTKL21+C6edf1s89+4ZPm93K847U1p1XUVEREREZoICb2kpd58AjsbN\nrhSHrI9/T7j7WFMaVZ2X/G3V+eeaVl9XEREREZGmUeAt7WAg/k0TeG+Mf/c2qS0AFHvVy7w1DOwE\n9jTz/HOVrquIiIiIzEeXtboBIsAQIfgumNlqdz9QrpCZdQDXEXpFB8qVabBpva/ufgw4NgPnnst0\nXUVERERkXlGPt7Scu58h9Hga1Xu9i8PMR1s0zFxERERERCQzBd7SLopDjKsF3mWHmccEbQNmdiIO\nZT5tZkPlkrWZ2fpY5o64PRC3h+L2nsRQaCsdGl0tyZmZdcbjT8cyJ8ys38wWlvswsS17Stp9xMzW\nVbkGqcXrstPMRkrq31LjmFTXMsvnbvB1LbZpWZmyxe93R9zelvgsJ8xsd6XvQ0RERESkWRR4S7sY\nin8LFQLmAmWGmZtZJ3AS2AIsBU4DCwi94/vN7M4K5zMzG4jHOZPDnx9lamC/h/LzjqcMlzazbuAI\nsC6e/3RszzbgZGmQaGY742deV9LuTmCPmfVXaHcq8XqNAHcCy0vqH6gU4JLxWmb43Hmv6/oy9Rfb\ndKLKQwozs/1AP3ABOAEsA7rjdRERERERmTEKvKUtpBhuviH+LR1mvgdYSAjGF7n7Ene/FOiN7++s\n0FvbQwgwdwIrCAEZ7n6fuxfP5e6+0d03ljn+ohjk7iYEjdvc/VJ3XwJcS8jYXojnKZbvIATEDnQX\ny8d298Ri26qdM4WdhEBzhKnXpXhtu8v0GGe6llk+dx3XtfhAZk+xTcBiJoP4PeV6vgnfZyfQ6e5v\ndPc3Er5ngI5qvf4iIiIiIo2mwFvaSbXs5sV9F3tNY2/rMmC/u3/A3c8W33P3e0gEjGXq6yAEvdvd\n/XgM/PMq1j/o7p9MtOFkot3JntnO+HfY3e9PVuTu9xF6nd3MrqujTSvj396S67KPcA2LPcBA7muZ\n9XNntT3+3R8D9bOx/jMxiB8ufsYyxy4Eutz9eKJdx4BdcbOjjnaJiIiIiGSiwFvaRgwKofxw89VM\nz2ZeDO7KBdYA98W/5QLY06VBbx2Kw9WntSMGobuAweLcYnffCxTc/ZYa9dazpnXx2JvLtGlD7AU+\nmNid51pm+tw5FJPpVWpTcX+5EQ0TJZ+vaDT+LeRsk4iIiIhIZlpOTNrNXkLA1QUcgIvzfGH6MPNi\nr+VWM/tAlTrNzJaWHDtaqXAWcTg0AJUyrbv7XWX2XexRjnV0AGuAtYSe53qCbggPKAaAbfH6DRB6\n2Cst2ZXpWgITxR1ZPndGxetwpML7xbna5XqvKx0jIiIiIjLjFHhLu3mQEHhvALbGfWWzmTM5VHo9\n1QPVcu81JPBmMujLVF9MZLad6UOxi221ehrl7vfFgH57bOPOeN4zhGu8M/ZKF2W9lrk+d1olDzTO\nlivj7hNmViy/oKTcRLljRERERERaQUPNpa0khpsvTAw3X8f0YeYXDyEM2760wuuS+HesSU0uBniL\n0x5gZmuYzNR9ghAUryckArsUqNQrnYm73+Puiwm96IOEHuIFhMRjJ8rMIc9yLU/HY1J/7oxtzxQ4\nVwrORURERETagQJvaUeDxOzmMUiF6cPMISQhA1hSqaK4LnXT5vO6e805w2a2xsy2JOY6F+cm74xz\nrbe7+0PJRGANbuMBd9/q7tcTMo4Xk5Il505nupaJ3vIsnzurM7GeclnLi9nhQb3bIiIiItLmFHgn\nmFlnDBTWmdmdFZahkuYrru+8gcmkX+V6u0cIAXpPmfeKc8PHmVySqllGw+kqrim9h7hEV9wurke+\no0L5AnXM8Y4B8gkzmzbPOQbMxSzgKxJv5bmWWT93Vodjm9ZXeL/YVs3nlrLy/jc9y3Fmtr7S+/P9\nnlLj2qyJ1+ROM+svt8TffL9+IiIytyjwjmLvWX9cb3hfXEKpp1JvmzSPux8g9GIWmMycXTq/GyYD\n122lw6Zjz2yxR7fZgffFHuzS3t24TNdCQhb1sbj7JCGgvKa0IjPbxuR861zzvOMw7WVAZ4WgeG38\nmwxY81zLrJ87q2L920v/fxjnyBfXQq+U9Vzmsbz/Tc9yXByRM0iZB2Xz/Z5S49p0AgvjdJh7YiLG\n8WTwPd+vn4iIzD0KvCf1ArtL9g2gH/WtMqVntVzwFjN0FwPyETMbMrPuGLyeJASfI3UsG2axJ6Zq\nL0tce3uUkHDsZDym28z2EP435Uxdm3x//Hsg9uZ0xvL7gX7CQwejTMCZQXG96j2J61JsUz8lAWue\na5njcxelva4HCMPiC4Q56btj/QNMPjQYrrBsmEje/6bXPM7MlpnZbsL/L8YbfP5ZLeW16U7k8wAu\n5vdYm9g1L6+fiIjMYe6ulzuEHwhLS/YVgAutbtt8fBGGY18AzgN31Ci7O5ZNvs4TsncvKCm7Lr7/\nYI06h5J1JfZvifs+X1J+ISEYPF+mHZvL1P9omTY/BixPnOMC8Egs313uvBk+Q/J1Crit3muZ83Nn\nuq6JY8rVP+07rPX9VjuPXnPrlfe/6VmPAx4HbmrU+efSq8q1OQIsK7P/UV0/vfTSSy+95urL3Otd\nLnj2i0NpxwkZnc+WvHcB6PDmZcWWBog9w2sIgeAocLTe7ywO014GTHjKXvM4THsF4QfiUeBI6f+m\nKpX1RM9t4tzDXkfStXhdOoufgzB6oGoPcZ5rmfFz57muyTZNEK5L1TbJ/JX3v+l5jjOzxwk9uAfr\nqWcuKndt4v5+Qu6GtR4TNcah6Uvd/X5dPxERmYsUeHNxLtnj7j5t6H28ya+pFayIiEh7yPvf9DzH\nVQi8dU+hcuAd3ztCeCjYQ5jOstDj8HNdPxERmYsua3UD2kTTlpsSEZEZl/e/6Y26F+ieUoO7rzSz\nRwnzto8CyZwPun4iIjLnKLmaiIiIzKiYwXwbIaFaByGpozKWi4jInKUe75zMTGP0RUQS3D3XEnjl\nZP1vbCPPLc0Vs573F+dpx4B7D2HFh2vrrFv3ZhERaahG/cZQ4B2MApjZggoJoUbLHdTXzBbNA18H\nfqXVjZjldA3rp2vYGH0trLNMuVz/Ta/juGbVM+fExGkkk6O5+xngZjM7YmY3EYae575+yl0z9/X1\n9dHX19fqZrStuXJ92v1ztLp9M3n+Zp6rGXU3sk6zxj3X11BzwN0nmFyP+KKY4GVC2VNFRGbeZSlf\npfL+N71R9wLdU6paAZyo8N4AIZO5rp9UtWrVqlY3oa3NlevT7p+j1e2byfM381zNqLvV300lCrwn\nDQPXl+zrJAx9ExGRGXZlylcFef+b3qh7ge4p5Y0C11R4r7gcIej6SRXt+qO6XcyV69Pun6PV7VPg\nPbN1NoIC70m9QFfJvu64X5pgaasbMAcsbXUD5oClrW6AVPSylK8Kav433cwKZnYiJvpKfVwZ5cah\n6Z4STLk2iXW7V08pFHqzlyR6s3X9RERkTtE63glmdh2wEThMzLJaaa1QM/O+GWybiEg766PxydU+\nl7LsByucu9Z/0+N841Fgm7vfn+G4hcD2+N76WMcwsL+4FnWaetpVlbnVaY5Ne222EHq+T8VdE+5+\nX0ldma+fmbl+14iISKOYWcN+3yjwzkmBt4jIpD4aH3jfV7sYAFsafO75JGYUX09Y1mslU9fQPg0c\nIQzv3jsb5lYr8BYRkUZqZOCtrOYiItKWdINqHjNbR+iZ7oy7RoEDwDgwQQjAF8f31wK7zGwE2OHu\nD818i0VERGY3/a4REZG2VGX+tuSUWDO7E9gL9Lr7gRTHrQF6gL0xAO+aDT3gIiIi7UKBt4iItCXd\noJqi2Gu9MstB7j5MmKuNmW0jZB9f3PjmiYiIzE36XSMiIm3pFa1uwNzUEdfJzs3dd5nZYKMaJCIi\nMh9oOTEREWlLl6V8SXpZg+7SZb/y1iMiIjLfKfAWEZG2VOc63tIYJ82s38yWtrohIiIis5kCbxER\naUvq8Z45ZrbOzMbN7IKZPWJmO8xsqbuPuvtdQFer2ygiIjKb6TeLiIi0JfVmz6iNwGpgCWH5sJuB\nXjM7QUiqtqSFbRMREZn1FHiLiEhb0g1qRh1292Px38Xs5QVgA2HpsR2tapiIiMhcoN81IiLSltTj\n3VoxgZqyl4uIiDSA5niLiEhbujLlSxriPjPb0upGiIiIzFUKvEVEpC0pudqMcmCFmT1mZpuVxVxE\nRKSx9JtFRETakoaaz6g9wAQwBuwCCmY2AeyPryF3P9u65omIiMxuCrxFRKQt1Rt4m1knsAIYBzqA\no+5+oBHHZSizAThFyAr+YCKBWbvZ4+73FTdiYrU1hAzn24GdZMxsbmbrgdNlrstO4FFgJM4jr3R8\nru9PRESkHSnwFhGRtlTPDcrMOoB+d785sW/IzEbd/WQ9x6UsswbYVlLmiJl1VTt/u4gB8d74yix+\n/kFgfZm3O4E7Y7nS9064+xvzfn8iIiLtSnO8RUSkLb3ssnSvCnqB3SX7Bgg9t9WkOS5NmYEyZXYA\nPTXO3yrjZra83krMbJmZ7QaWEXqqyzlBCL47Sl49QFcsk/f7ExERaUvm7q1uw6xkZt7X6kaIiLSJ\nPsDdp3Vf5mVmfubl6couPDf93GY2DnS6+1hiXwEYd/eKD53THFerTPHfQEdJmQ7g8Wrnb6UYMD/q\n7g81qL7HgW53P1iyf0tyWHu5/XV8f67fNSIi0ihm1rDfNxpqLiIibenKK1IWPDd1MwZoxeD3Inef\nMDPMbGkyoMtyHCEBWa0yi+Pu0h7f8XieBe2WqMzMhgjzubvj8O9iUrVhdz/eyHOlCLpzfX8iIiLt\nrC2fuouIiNQx1HwxQJXgtqPC/jTHpSkzmqyvtP4y+9vBYXdfRGjbzcBx4P8GjprZBTP7fLNObGar\ngSOJXXm/PxERkbalwFtERNrTpSlf0xVynjHNcTXLxMRkw4SM3EkdJX/byUkzuxMouPuwu/e6+4o4\nrPtm4GgTz91Zku097/cnIiLStjTUXERE2tPsvkP1EJKB7QMws4WJ9yolHWsZd98LF3ufx0reG27W\neeOSYyeaVb+IiEi7mN0/a0REZO6qcIc6dC682pm7nzSzLjNbF3dNMDkEfbTCYS1RzGbu7sfLrLm9\nDhht4vrjdwE3NbLCTZs2sXTpUgAKhQLLly9n1apVABw6dAhA29rWtra1re2y28V/j42N0WjKap6T\nspqLiEzqo/FZzT3lgGwbnXruRFbxQuk8YTO7QEm28SzHEQLozHXH99cQsoa3xTSvOLQ8uTyXE9be\n7k1+NjPrJMwBLz+wv3L9ZbOaJ94vm6U87/cX31dWcxERaZhGZjVvi5u/iIjINFekfJWIc6xHKZlL\nHZfzmqgUtKU5Lm/dUSewp8r7MyYuHdZDWC/75vjaDlwLTJjZjmJZdz8KNOyhSsIawoOMKeq8xiIi\nIm1JgbeIiLSny1K+yhsGri/Z10lYIquaNMfVLGNm+81sc0mZbkKgWxczW1Dn8dcBuPu17n5PTKY2\n7O673H0tIav4STMbMrPNJfPTG+l6Ks/vzvv9iYiItCUF3iIi0p7yZzWHEOB2leybEviaWcHMTpjZ\nlizHpSxzGrg4X9rMtgG7s/bWmtkyM7vTzB41s/E41HoiLvF1ysweMbM74vrhaa1x962V3nT3CXcf\ndPcNhB76leR/YFCtp7yDyonm0lxjERGRWUNzvHPSHG8RkUl9NGGO98qUZY+UP3fs2d0IHCYEeSPJ\n+cZxLvEosM3d7097XMq6lwHrgSVx1+PJc9T8TCGp2XZCLy+xnccIgeoEYcmtxfH9ZbHMCLDD3R+q\nVbe770vblixi7/h2wjVZH9s9DOwvPWcc7u7u/oEKddX8HsocozneIiLSMI2c463AOycF3iIik/po\nQuB9Q8qyf9fYc7dSDNj3EALqvcBAaabxCsetIczZXkcIwLuqJCBrWuDdagq8RUSkkRoZeGs5MRER\naU+ZcmjPGcVe65T9/UFca3sYLg5rP0roERcREZE2oDneIiLSnupLrjZbdbj7PfVU4O67KMkIXuL6\ntAnazGxdfD1YT5tERETmOwXeIiLSnl6e8jWHxKW0ml3PILC3UvBtZqtjRvMhYDQOSy9NdCYiIiIZ\nzL2+AhERmRvm51DzsmKQXHXoeNqM6e4+amZ7CdnR9xCSly0BriGsrT0O9KSZWy4iIiLpzInA28zW\nA6fL/Ugws05gBeGHRAdwtLRcmjIiIjLD5sQdqj4x2dp+QubyasldnAyPKtx90MxGgZ1M9maPAr3u\nfl/J+bvieyIiIpLTrP9ZEzO5DhKWLSl9rwPod/ebE/uGzGzU3U+mLSMiIi0w6+9QDTFAfCBMYl3w\nMjKn8o4J2VakKLcL2JW1fhEREZk0a3/WxKfwvYQMsOMVivUCu0v2DRCe8G/IUEZERGaahppDGPp9\nNGuW80bRA2gREZHGmLXJ1dz9pLtvTQ6JK6OL0EuQNMLU3vE0ZUREZKbNz6zmpU4Shpo3hJn1p81o\nXqWOhWa2o1FtEhERmQ9mbeBdi5kVgAIlveHFTK9mtjRNmZloq4iIlKHAG8La3I18ELyIkFRtR9Z7\nnJktM7N+4HSsR0RERFKayz9ZFgO4+9kK73cAY2nLiIjIDLui1Q1oPXfvMbMRM3uEMAXqSJWyle5l\npfUNAPcBvWZ2ghDc7yckUJsgPIxeTHgw3QHcTBjyXpxrvlYJSEVERLKZy4F3oUFlKurjXYmtpYSk\nsyIi88FJpj6X/EbjTzGX71ApmdlCYCFwHbC2StHUWc3d/SiwIq7osR14H9BT5ZAJQnDe5e7H0pxD\nREREptLPmrr8SqsbICLSIsuY+rBRgXeT3EfoaR6l8VnNjxKXEosrfHTGcy0BTsVzHnV3LSUmIiJS\np5b/rIk3+7ROufuZpjVGRETah7KaQ+jlbnpW8xhcK8AWERFpkpYG3nFJsP4MhxwG7klZdjSeY0GF\neW/FuWy1yoiISCvUeYeKQ6lXEOYsdxAC2Jpzk9Mcl7LMGsIQcQi9yCdqrMRRScOyms8kM1sPnK50\nzeM13EDoXV8CDCSXL8v7/YmIiLSjlgbe8QbblLWy3X3CzEYJN+vjxf2xh33C3cfids0yIiLSAnXc\noeJ/x/vd/ebEviEzG622NnWa41KW6QQWuvs9iTLrzGxLxuB7iJDYbHuGY1ouPnQYpEJG9hiUr3H3\nrYl9A8S55nm/PxERkXY1Z5cTi4aB60v2dTK19yBNGRERmWmXpnyV1wvsLtk3QMgMXk2a49KU6Xb3\nfckCcbtagrRp3L0HOG1mj5jZcjNbUOmVpd5miUuO7SYkABivUKYADJYE3d3ATYlieb8/ERGRtmTu\nmfOxtB0zexzoKTPMbyGwp+SJ+aOEH0RjactUOKdDXyM/hojILNaHu1ujajMz9/8nZdmPM+3cZjYO\ndCb/Ox4DvnF3r/jQOc1xKcscIWQBn9I7a2aPJu83NT9bOFeaFTjc3dtqVny8N3e7+8GS/TuBC+6+\nvWT/0sS9Oe/353Phd42IiLQHM2vY75uWJ1fLKwbM2wnDxDuAATMbBvYXexnc/YyZ9ZpZP2F+eHHo\n2lixnjRlRESkBXLeoWKAVqCkxzVOQZoS4GU9jpAbJE3dw8B+M1ubGH6+hjB0PIs9KcvNpmhzC7C5\ndGci6M71/YmIiLSzWRt4x+zmd6Uodwyouu5omjIiIjLD8vffLgaokDQTwgPWsXqOq1XG3e+KgfYJ\nM+shLHy+0N3vT/MBiuJQ87mmAJwxsy2E4HoxoSe7ODQ/7/cnIiLStub6HG8REZmtLkv5mi7N0Oy8\nx6WuOy4BNkyYm9wf/12VmfXHnvUZYWa3zdS54vmKS4he5+73ufu+mGzu+hiIQ/7vT0REpG0p8BYR\nkfaUP/BuCzGQ3EZIqNYBjMRlNKtZBBw1s8fNbIeZLW9yM/ea2Xkz+/wMnAsmg+rS5TofRInTRERk\nDmvjnywiIjKvVRhqfuiHcOixmW1KVnFprB2JecvLCPO19wPXVjouDi3vicuRbSQExosJgeme0kRl\nDXBXPE/xvKcJy4ANNGke9WjJXyBM+TKzQiN6+zdt2sTSpaGaQqHA8uXLWbVqFQCHDh0C0La2ta1t\nbWu77Hbx32NjYzTanMhq3grKai4iktSErOali0lVKrt1albzYvZroFA6T9jMLgAdVZKrVT2OkFwt\nTZn+5HJZiTJHgN7SVTiqfr4wPHs9IUC+jhDAPwgMV5kHnUk8R088T7FXfiSeZzDPeapkNS/7HcT9\na4Cj5Pj+4vvKai4iIg3TyKzmGmouIiLt6YqUrxLuPkHoUe1I7o/B5USloC3NcSnrXgmcqPCpBsg4\nh9ndR919l7uvICQeOwB8AJiI63tvrncd73iOXne/Jrb/HkLP/C4m1xFv1Hzwadcv+V7e709ERKSd\nKfAWEZH2VN8c72Hg+pJ9nYSh3tWkOa5WmRPANRXqLxB6knNx9wl3H3T3tYQg/D5CT/jpvHWWOcdR\n4FFCbzeAEeapF+eD76jzFAPAiuSOOLT+dCKozvv9iYiItCUF3iIi0p7qC7x7ga6Sfd1xPxCGlpvZ\niUQ27VTH1SqTWLd7dbJA7LFdUm+PrZkti73PBXff6+5r3T3/4muT9a42s6E4nHs/4TMdJXyua4Gt\nhGW8es3s82mrLbNvkDCsPamfsL53UZrvQUREZNbQHO+cNMdbRCSpCXO896Qs20XZc5vZdYTe4MPE\nrOLJ+cZxTvcosC25vnat4zKU2ULo+T4Vd03EpbNqf6Zw7Bpgf0nbdhMC0KITwNq8wbyZrYufY31i\n9zHgS8De4kOEkmNOAEvLBftmthDYTrgm6wnXdzh+jn2JcssIQXRxdMBQnmtc5vya4y0iIg3TyDne\nCrxzUuAtIpLUhMD7oZRlbysfeM9WZjbEZCDc6+73xP1bCMO0JwhDzDuB1YADi3ImQLsQ/1kMtgfd\n/UyNY/YAy+I65W1FgbeIiDRSIwNvLScmIiLtaR7eoWIP9HpCL3FXSRBcHGa9IjGcvRvYTehl3p7j\nlHcRlg6rGmwnuXvpEHARERGpQXO8RUSkPeXMaj7LFZcgmxJ0x6HZHZQM/3b3QeAMYVh6HpmCbhER\nEclHgbeIiLSn+pKrzVbLCOtzlwbDxcD6QaY7QuXluWo5bWabqxUws34zO1WtjIiIiFQ3936yiIjI\n3DA/71AdlF8ya238O1zhuNRrg8fh7M5kxvEVZjZeqThh6PuitPWLiIjIdPPzZ42IiLS/uhfImpVO\nUr73ei1wosKw8A5CwrW0SvPF9zB9ea9SlQJ+ERERSUGBdx36lNVcRARo0hoP8/MONQqsMbMFxSzl\nMZv5QsoMM49Lbi0jW2C8IfHvIcK62tWOP+3uBzLULyIiIiXq/lmT/HEgIiLSMPMz8N5JWCJsxMx6\nCUO9d8b3BpIFY8K1PYnjUnH3vYk6DgB7FFiLiIg0V6afNfEmv54w5G0lcU6ZmQGcJiR42U/IujrW\nyIaKiMg8Mw8Db3cfNrN7gDuBvYm39rr7seKGmR0BriME5nvzBs7uvrZ2KREREamXuXvtQiERy3ag\nM+4aBY4B44R5ZQVgcXx/WSwzAuxw94ca3Oa2YGbe1+pGiIi0iT7A3a1WubTMzP0HKcu+qbHnbgdm\n1knIZL4E+I677yt5/wLhXrzT3e/LUO8FQmK1a9x9LLFd9TDA3b3tZ92bmaf5XSMiIpKGmTXsN0bV\n/oTEMLZOwpP33jRP1c1sDSFRy14zGyGsRzpWf3NFRGTemIc93kXufhQ4WuX9vMuBHiAE2qfj9r4q\nZaecMuf5REREhNo/a4q91iuzVOruw8RELWa2jfDjYXGuFoqIyPzU9v2rs0/p0HJ372pVW0REROaT\nWk/MO9z9nnpO4O67KL80ioiISGWXpXzNIWbWb2YL6qxjoZntSFn2DjNbWs/5REREpLaqgbe7Z1kX\ntOn1iIjIPDIPA29gETBhZjuyBsRmtszM+gnDyBelPGwXcMLMDpvZ5nqDfhERESkvVXK1aQeFG3PV\noeNzfU63kquJiEzqownJ1Z5NWfY15c8dE5StICQC7QCOpsxTUvO4WmXMbCfwKDCS9eFzrPs+Qtby\nE4SpW/sJydQm4jkXExKbdgA3ExKxdRCmdqXKxxLPtZ6Qk2V13OWEnC4D7n4wS7sr1D1tDXAz6yAs\njdZPmNK2GOgG9pdcw8zfn5KriYhII81YcrUyJ15GuPkvI2Q5rcTR7DwREalDPTm0Y3DX7+43J/YN\nmdmou5+s57iUdXcSlgQrLrmZdMLd31ipDTGx2ooYeG4H3kcIjiuZIATnXcklx9KIa3rvje0sBuFd\nQJeZnQaGCEH48Sz1xiSrg4QlSMtZzWSwPwFsLgm6c31/IiIi7SrrIL0BJp+oV3vqrMfNIiJSlxde\nXtfhvcDukn0DwE5gQ53HpSlzghB4l/Z2rwUO12g7cDEA74KLgWgn4R68BDhF6AE/6u6jaepLcb7S\nIHwjIRDvMbOqDwuK4gP6XkJP9nilUxF66I8AiyuMkMv7/YmIiLSlTEPN43qfR7NmOZ+LNNRcRGRS\nH40fav7Tc+lWzLrq5RemndvMxoHOZFBnZgVgvNpSXGmOS1lmS7n1tSvtbzdmtpAQ4PYQAv7MS5iZ\n2eNAd+mQ9Ricd1QbNl7H96eh5iIi0jAtG2oOnCQMNRcREWmq85elvUW9MGUrBmgFSnpc3X3CzDCz\npeV6WdMdsBpsAAAgAElEQVQcR+jBrln3bAy6Y0Bc7OnuTLy1l9DbPFPtyPX9iYiItLOsgfcw4aa8\nvQltERERuej8pbkneS8GcPezFd7vAMbqOS5r3Wa2mjC0uq2Y2XWEQHsdcE3irWKCtVRJ2nLoiAE2\nhOs+7u77Ett5vj8REZG2lSnwdvceMxsxs0cI86wq/oiocsMUERGp6Xz+HJ2F2kVyH5e37k53vyfn\nsc00kvh3s4PtonGARKBdTJxW3Jf3GouIiLStrFnNFwILCUucrK1SdEaympvZOsKT72vi34HkjTyW\nqXtZGBERmXkvzZHFMWKishOtbkcF+4DdM3nPc/czhOXSkgbia9/0I0RERGa/rEPN7yMEpqO0OKt5\nDLpHi4F2fCgwYmaLi3PoGrgsjIiIzLDzFW5Rf3PoRf720Isz3Jq63AXc1OpGlOPuXa1uQ3SSMPx8\nQb0Vbdq0iaVLlwJQKBRYvnw5q1atAuDQoUMA2ta2trWtbW2X3S7+e2xsjEbLmtX8NGH90ZZnNTez\nO0uH7ZnZFkKvdzGr7ADwiLs/lCizGuhx9w1py1Q4v7Kai4hEfTQ+q/movzZV2Q57asq5i9mvgULp\ntKe4OkdHleRqVY8jJFdLXXeaTNwzKbbRgWvcfSyxbVR+aG6Au2dbWb1KVvNt7r6rZF/x2ncS5m9n\n/v7i+8pqLtIG3J2zZ8/y1FNP8fTTT/PUU0/xqU99imeeeYbLL7+cDRs2cOWVV14sbzb19vHlL3+Z\nU6dOcdVVV3H33XfT0dHB1Vdfzate9Spe9rKXzfTHkXmslVnNoQ2ymscb9EYzG4xD1ooOxPeLGU+7\ngB0lh48QEsQVpSkjIiIzLO8c75j9epQQKB8v7o8jnCYqBW1pj8tY9xqmr+Wdmpndlnww3AAHCAH2\n6biddmh3Q6LZ4igzMxsquVaL499Rdz+b5/sTkZlz+vRp3v/+93PixAncnVWrVjE+Ps5TTz118XXp\npZfy2te+9uLrySef5Cc/+QkAe/fu5dZbbwVCkF7q6aef5oknngDgAx/4AFdffTXPPvssp06dYuHC\nhbzmNa/h6quv5jWveQ3f+973OHfuHIsXL+ZP//RPectb3jItkBdpB1kD7yHCj4iWZjWPP446gGUk\nbspJjVwWpvGfQEREaqlzjvcwcD1T7xGd1H54nOa4LHVfT33zu/eamQODhBFdZe95abn72pLtGR1q\n7u6jZtZT4QHFSKKHO+/3JyINdvbsWY4ePcqRI0cuvp555hkuueQSzp4N/5e98sor2b59+5RA+6qr\nrppSz6/92q/xk5/8hJUrV7J//34Khcp5FP/+7/+eJ554YlrZ8+fPMz4+zrPPPsszzzzDs88+y8jI\nCKOjo4yOjvKOd7yDyy67jDe96U28+c1vnvJaunQpl1zSFoOPZJ7KNNQcwMweJTz57iXM9S6rFVnN\nzawb2OHuS2Jg/ni54X1xqNoawnC2qmVKh8gl3tdQcxGRqI/GDzX/nl9TuyDwFjsx7dwx78eekvwd\njxKGPo/F7QJhhFN/IjdImuNqlkns3wMscPdbUn70KcxsG2G5r+virtNMBuFjlY7LUP+CZt2v41Dz\nnjIJTdcRkpgWc60UCIH25uKDhSzXuKRuDTUXqcM///M/c+zYsSlB9hNPPMHb3/52Vq5cefH1r/7V\nv+K9730vX/va11IF0gATExN0d3czODjY0LK/9mu/NqUd7s4PfvADfvCDH/CP//iPF18/+clPeMUr\nXsGSJUv4T//pP7F27Vpe+9p0U5pk/mrkUPOsc7zHSbfMR+a5YI1gZiPA/+vun4yZyo/UCLwnapVR\n4C0iUlsfjQ+8/97/Zaqyb7cflj13Yo3qw4RhyyPJ/6bHgG8U2Obu96c9Lm2ZWG434Z74gVQfpoL4\nMLmHMA1qWdw9AjwIDOYNnuO9rjv5+cuU6Qe2uPuSFPUtJIyK64htHSUE1ftLlg8rrkqyhPC7or/M\nQ4tU17jkGAXeIhk899xzPProo/T29vLEE09w7tw53v72t3PDDTdcDLLf/OY3c9ll0wfJZgmOmylt\nO375l3+Zb33rWwC89rWv5fnnn2fBggX84i/+Ir/0S7/EL/7iL/KWt7yl7GeV+auVgfdAyqLu7lvz\nNSmf2Nu9rtirMBOB97sS20uZ/CUkIjLXnSQMGSr6Bo0PvI/6m1KV7bQfNPTc7S7e3zYC3YQlPp0Q\n3A6kmQ8eg95iQrU9hGW8Kg3hNmAnIaFZ24/RVOAtUtv4+Dhf/epX+fKXv8yBAwdYsWIFP/7xjzlx\nIsyK6erqYmhoqMWtbLzSnvEFCxbwwx/+kL/5m7+5+HryySd55StfyRVXXMHrXvc6/uIv/oJFixa1\nuunSQi0LvJshPsVP61RJMrVkHUPJbOvq8RYRmTl9ND7w/o6/JVXZd9j35lXgDRdX3+giBN9JDuxy\n94q5WOL9Lavh5LDvdqXAW6S8J598kocffpiHH36Yw4cPc9NNN/Ebv/EbvOc972HJkiXTgtJW9mA3\nS5qe8VOnTvGud72L73//+wBcccUVbNy4kVtuuYW1a9fy6le/eiabLG1gzgTeZraM8CQ9rcOlS4jF\neoYIc8POJvY1fFmYkvcVeIuIRH00PvD+pq9IVfaXbWReBN7FpS6ZuurGUcJw832EB8q9hAFYA5WG\nt5tZ8vghwpzx4SqnPl06T7tdKfAWCYrznB9++GG+/OUvc/LkSd7znvfwG7/xG9x888284hWvmFK+\nXYaNt4PkQ4j77ruPv/3bv+WRRx7h61//Om984xu55ZZb+O53v8vZs2f5uZ/7OR544IF5f83mshkL\nvOO8rv9cT+KVON/rrmpP3+sR589NmxsW33scWJ/MAht7x4+4++K0ZSqcV4G3iEjUR+MD72/4O1KV\nfZd9Z84G3nFY+EamBtvHgC8Be4sJykqOOQEsTZNrxcz2E+6hsyKwrkWBt8xn7s6tt97KyMgI4+Pj\nLFq0iNtuu41bb72Vd77znZq7nFKlhxAvvPDCxSD83nvv5ac//Skwd4fmSzCT63gvAibMbCcZM6jG\n3uweYBvhaXrDmdkWSoLu2CMwGn+MNHpZGBERmSF51/GeY/bEv8Vge7DclKsSR5lcp7uq0uXFkpqZ\n8VxEGudnP/sZDzzwAJ/5zGf4X//rf3Hu3DkA/vW//td8+tOfbnHrZp9CoVA2kL788st517vexbve\n9S6OHz9+sVd8cLApYY7MQVUTpbh7D7ASuBkYNbPHzOzzZnabmS03s6VmtiD+XR737469yCcIw97W\nNiPRWmKo3GIz64yvNUBXogeglzAHLqk77idDGRERmWEvcWmq1xx3F7DI3Ve4+z0pgm7cvSuZ86QW\nM7su3tuXxu2FZnaE8OD9vJntyNt4EWmesbExtm3bxhve8Aa+8pWvsGvXLlatWgWggLDJHnjgAbq6\nuubsfHhpjtRzvGOysu2EYHphlaIThF7kHe5+rO4Wlm9Lcf52OSfc/Y2Jsg1bFqbkGA01FxGJ+mj8\nUPOv+apUZX/VDs3loeYL0wTbddS/mskRXp3ufjxO4eoGDhDuiUsJD7VrZkxvNQ01l7nO3Tl48CD3\n3nsv3/zmN7n99tv54Ac/yDXXXANorrZIo7U8uVqcA93J5BqcpwhrdR5199FGNKzdKfAWEZnUR+MD\n77/01anKvscOzOXAu6HrbJc59gjhfr62OM87nvNiFnMzOw087u7X5/kMM0mBt8xVP/3pT/nCF77A\nZz7zGS655BI+/OEP8/73v5+f+7mfa3XTROa0mZzjXVYMrudFgC0iIq3xPJe3ugktUbLONsAKM6s0\nyssIidfyLjTbQUjSVgy6r4v7BxJlhpia3E1EZshjjz3GZz/7Wf7bf/tvrFq1is9+9rOsWrUKszn5\nrFFkTlN6QxERaUvn5+8tak/Jdk98VVNtObBqCoQgv2hN/JtMMLo4lhORGXDhwoWLmbOPHDnC7/zO\n73Ds2DFe//rXt7ppIlKHefurRkRE2ts8zmq+IfHvZq+zfYzJYBtCgD9aks18NTBt2TIRaayXXnqJ\nm266icOHD/Oyl72MHTt2sG/fPq688spWN01EGkCBt4iItKX5Gni7+97iv83sALCnietsDwC7zewx\nQnLUDuKqHjHx2gCht1vpkUWaxN3Zt28fv//7v8/TTz/NuXPnOHfuHN/4xjf40Ic+1OrmiUiDVF1O\nTEREpFW0nFhYZ7uJQTfuPgjcA7wKWEGY731PfPtmQiA+7O53NasNIvOVu7N//37e8Y53sGPHDj71\nqU/xC7/wC4CWAxOZi9TjLSIibWk+zvGOGcUduMbdxxLbVQ8D3N1zPYVw915iL3eJAWBgvqxWIjKT\nvv3tb7N9+3Z+8pOf8IlPfIJ169ZxySWX8PM///NaDkxkjpp/v2pERGRWqHeouZl1Enpxxwk9t0fT\n9B6nOS5t3bHcBsKym0sIgWy1+dIHCIH26bi9r1Z7o4avoVVvwG1m60kx/9zMCkC/u28t2Z/r+xNp\nZ9///vf5/d//fY4cOcLdd9/Npk2buOyyyZ/jhUKBoaGhFrZQRJpFgbeIiLSlF+pYTszMOgjB3M2J\nfUNmNlot8E1zXNq6Y+C5JhlQmtkAVTKUu/vaku2ulB85lSo96sW1icoF8Jl71M1sDWFeeJplyHZS\nshxa3u9PpF2NjY3R19fHX/3VX7Ft2zYeeOABJU0TmWcyB94x2cp6wvIiFbn7xryNEhERqXP+di+w\nu2TfACHI2zC9eKbjapaJvbiD7n7xXmlm3cBN6T8CmNkdhHnXY1mOq6KpPepmtoxwfUYIPdW1yncQ\ngu7S+vN+fyJt5dlnn+UP//AP+fM//3M+9KEP8dhjj7Fw4cJWN0tEWsDc049OM7N1TF9ftCx3n9OJ\n28zM+1rdCBGRNtEHuLvVKpeWmfkf+QdTlf2ofW7auc1sHOhMBqwxGB6vdn9Kc1zKMjuBC+6+vaT+\npVmC6ESP9FFC4DlUstRX2zKzx4Fudz9YpcyW+M+17r4hsT/v9+dZfteINMuZM2f4oz/6Iz772c/y\n/ve/n//wH/4DV199daubJSIZmVnDft9kDY53xr9r3f2Saq9GNE5EROav81ya6lUqBmgFSnpc3X0i\nvr+03PnSHJeh7i3A4dJz5Oi53gAcJMx1HgROm9mDZpap5zwPM1vQ5PpXU2Z98rzfn0g7eO655/jk\nJz/JG9/4Rn784x8zMjLCpz71KQXdIpJ5qHkHYcibkpuIiEhT1ZFcbTFAlZ7hDmCsnuNSlCkAZ2KP\n7nise9zd0w7tJp5nL7AXLs4Z7wG6gC4zOw0MERK2Hc9Sb5KZXQd0AzvjvO+FhCHpnWbmwK7SnvsG\n6XD3A2ZW2pOQ9/sTaRl3Z82aNXzzm9+kUCjwla985eLSYCIikL3H+wwhM6uIiEhT1bGOd941eNIc\nV7NMnLcMcJ273+fu+9z9PuD6xNDqzNx9b1zX+xIme8J7gKNm9lieOmOv80isp/jZdgKdhOB7DNhm\nZrflbXeF866L16QcraEks8rjjz/Ou9/9bv7u7/6OF154gWeffZY//uM/bnWzRKTNZA28B4GNzR5+\nJiIicp7LUr3aUDFwLF2O60Emp2zVaz/wKGHuN8A1OetJTiEr9pp3A8MxyL8GOAs0rMc7DiUXmfWe\nf/55/uAP/oAbbriBNWvW8M53vhOAlStXMjg42OLWiUi7yfqL5T8TnoKPmFkvYU3NsYa3SkRE5r1K\ny4n96NAYPzr0oxluTSajJX8BcPdjZlbImmCtKGYMXw9sJNyLi/YSEq/lMWUKWRx2Tkl9Q6RbFiyt\nrpLe7oZmQ9u0aRNLly4FwprIy5cvZ9WqVQAcOnQIQNvarnv74MGD3H777bz+9a9nZGSEN7zhDbzp\nTW/i3LlzPPzwwxQKhbZqr7a1re1028V/j42N0WhVs5qXWd+zlmLZTOt9zkbKai4iMqmPxmc17035\nX9md1jfl3MXs10ChdJ5wvK91lAt80xwHTKSpu9J54v411TJ9l5S/jhBor2Nqr/ZewtzuunKuxPbs\nKS4BamZ3EnrBL34+M9sD3Jb1vl4uq3kxsHf3Y4l93YRrklyKLfP3F99XVnNpqmeeeYaPfvSj/I//\n8T/49Kc/za//+q+3ukki0kSNzGpeq8e70vyrWnTXExGRuuRdx9vdJ8xslBAoX0w6FudeT1QK2tIe\nl7LuYply5yodgl7NSOLfDQm2SxwD1iS2e4DRkoB3NXCyQedbCVxjZhsT+zqBDjPrBw67+748359I\nM50/f57BwUE+/vGP89u//dt8//vf56qrrmp1s0RkFqkaeLt7z0w1REREJKnO+dvDwPUkAjdCgLe/\nAcelKTNAWAIs2dvbCZzOGDjuA3Y3cTWRAWB3TM42QQh2e+Fi4rUBwpz1hkxYLZdQLfayr3T3uxK7\n835/Ig137Ngxtm7dyste9jIOHjzIW9/61lY3SURmoUzJ1ZRUTUREZkredbyjXsKyW0ndcT8QhjSb\n2YmSTOM1j0tZZpDQe5zUT1jfOzV372rmEp7uPgjcA7yK8KBgr7vfE9++mRCID5cExVmkGZ73qjLl\n0lxjkab6p3/6Jz7ykY9wyy230N3dzX//7/9dQbeI5Ja1O2HCzLrd/f5KBeJQsS3uvqS+pomIyHxW\nxzreuPsZM+stDl8mBJD9ZXqbF5GYHpXmuAxl1prZbuAEYX52f6253YncKtck5opfzJ9S6TDqyK3i\n7r2UD2gHCEPbUw+Nj2uAbydckw5gwMyGgf2la5jHZHG9hKXRFsZrNeDuxzJ8fyIN5+7s27ePf//v\n/z1r167l+9//Pq9+9atb3SwRmeVqBt5mto6pCdZWmNl4peKEzKeLGtM8ERGZr/LO8S6KCbyOVXl/\nAlic9bgMZU4CW1M1dtIBwj33dNzeV6XslNNlPM80cVTbYsJw+DNZAu6LjXA/A6TqHU9cn7LXKM01\nFmm00dFRfvd3f5cf/ehHPPDAA9x4442tbpKIzBFperz3lGz3MH34XKnhfM0REREJXuCKVjdhxrn7\n2pLt0uHWDRczjd9HmEPtwFrgYMxKvtvdP9nsNoi02vPPP88nP/lJ/st/+S/ceeed/N7v/R6XX15+\nSUMRkTzSBN4bEv8eIsxbqxZYn27mfDQREZkf6hlqPleY2YLSJbUaXP8yJjOnHyBkMC9aAuwys43u\nfn2z2iDSau95z3s4ePAgV111FV//+td529ve1uomicgcVDPwdve9xX+b2QHCep8KrEVEpKkUeAPN\nz61SnNu9grBk2MWpZO6+yMy2Af1mtsPdt+eoX6Rt/fM//zPbt2/n0Ucf5cUXX+S5557jE5/4BEND\nQ61umojMQZmSqyWHwMW5YCsJy4xMENb9HGto60REZN6qd473bDXDuVU2ELKWHzOzQumb7r4rrrm9\nnpA0TWRO+Na3vsWmTZv4+Z//eW688UYOHDjAypUrGRxsyMp5IiLTZF4kNQ5LGwDWlLzlMXNpr7sf\nn36kiIhIenWu4z2bzWRulQIh63o1o8C6nPWLtJXnnnuO//gf/yNf/OIX+dznPsett97KxMQE3d3d\nDA4OUihMe/4kItIQmX7VJOaCFYCjwIOEoWkdhGQsa4GVZrZCvd8iIlKPeTzUfCZzqxwjjF6r5jrC\nPV9kVvv2t7/Npk2beOtb38p3v/vdi0uEFQoFDS8XkabL2p2wkxB097j7fSXv7TKzbmB3LLexAe0T\nEZF5ar4G3jOcW+VBwhzuX6FMcG1mQ4SH67uadH6Rpnv++efp6+vjT//0T7n33nvZsGFD7YNERBos\na+C9BjhaJugGwN0HzayH6cPQRUREMnl+Hi4nVqqYWyXmVelITuUys82E+dljddRfnMN9ANgfd/cm\n7uWLCDlcUq3NLdJuRkZGuP3227n22mv57ne/y9VXX93qJonIPHVJxvJp54JZjTIiIiJVnefSVK+5\nzsx2E5KYlj70HgROmNmOeup39xXAXcA74q61QBfhN8Iud7+2nvpFWuGFF17g7rvv5ld/9Ve56667\n+PKXv6ygW0RaKmuP9wFq92avBo7ka042ZraG0J5TwDXASGlvvJl1EpZJGScMlztaOmQvTRkREZlZ\n8yGorsXMtgDdhGHg/SVvbyBkGu81sxPVlhyrxd13EYeTm1kHMO7uE3nrE2ml7373u9x+++287nWv\n4/jx47zuda9rdZNERDIH3j3AiJk9QpjnPVZ8I5HtHMKPhKaKQbcnh7+Z2REzK7j7PXG7A+h395sT\nZYbMbNTdT6YtIyIiM2++LidWoguYcPdpCdDiXPC9ZnaCcH/OHHjHwP6Uuz+UqHe0jvaKtMxLL73E\nzp07+ZM/+RN27drFpk2bMNMgTBFpD1kD723AYcIwtBNmNkEYWt5BGIZuhOFwe0r/Q+fu19fd2ql6\nCInckobj/nvidm+ZMgOE5G8bMpQREZEZNo+XE0taw/TlxUoNA1ty1j8AnAYeqlVQpJ394z/+I7ff\nfjuLFi1iZGSE17/+9a1ukojIFFnneG8kLDtyBjgbj782/j0b91vcl3xd06D2JjnTh70b4QdEURfT\ns7SOAOszlhERkRmmOd5AWLKz1sLCywgPwfO4H1hkZstzHi/SUufPn2fXrl3ceOONbN68mUceeURB\nt4i0pUzdCe6+qFkNycrdy/VGrwc+D2BmBcKPlfGS4ybMDDNbSuidr1pG65GLiLRGvUF13vwdjcgN\nEqcxDRDmZY8AiwnTsPZnzCEyDGwxs9uSw8ET51lNeAi9d9qRKbh7t5k9TphG1kPI0TLq7mfz1FfS\ntvVUWGO8UTlaZH774Q9/yKZNm7jiiis4fPgwy5Yta3WTREQqyj2OLy5tsphwUz3TuCblbk83cMTd\nPxl3LQao8uOhAxhLW0ZERGbW81ye+9i8+TsanBtkdXxBeNC7OUfg2EuY9rTXzPYTlvwqPjR+B+GB\n8wQ5h5qbWfHBsxGypBf3e7IYIadK6ichMbAepMzosUblaJH568KFC3z605/mE5/4BHfffTcf+tCH\nuOSSrIM4RURmVubA28yuIyxp0kkY7r0WOBifmO9OBL4zwszWxTa4u29MvFVraF7aMhV9PfHvpYSx\nfiIi88FJmv9Uss453nnzdzQqN0hxOtQRYHHe0VNxBNaKWHfxfpc0TEh2mvcBeNoHAV67yMVEq72E\nXv7xCsUalaNF5qH3ve99fO1rX+OSSy7hwIEDdHZ2trpJIiKpmHuqe2koHG6oxXW8DxCe5K9x94Nm\ndhpYSBgu1uhEamnatjC2aYu7H4tD1I64+7RHoGZ2gfCDaKJWGXc/WOF83tfIDyAiMov1Ae7esPTB\nZub/0v8+Vdkf2tunnTv25HaWrL5RICyTVbFrLM1xKcssAzoaOTQ6nqMjvor3r7Zd8is+kO8uvY+a\n2RBwwt23J/btBG4q/n6o4/vzLL9rZPZwd+6//34++MEP8tJLLwHQ1dXF0NBQi1smInOZmTXs903W\n7oTe+HcFocPj4tNsd19kZtuAfjPbkbyhVhOHk6V1qtJTfXc/Y2YDhOB7cYY6RUSkDeWd450mx0e5\nHuh2zw0Sg+yjTE8IOqs0IkeL8q/ML08//TSbN2/mf//v/80NN9zAN7/5TVauXMng4GDtg0VE2kTW\nwHsDMBx7lKcN03b3XWa2kXADrRl4xx6B/gznP8zkMLRyDgAFM7uJ+MPEzBZUmMM9SvgBVauMiIi0\nQB3reKfO8ZH3uJR1dyTulYsJvbX7qrR7GjPbTcph3u7+gSx1t4t6crTI3Ld3715+93d/ly1btvDQ\nQw/xs5/9jO7ubgYHBykU6poxKCIyo7IG3gUmh5pXMkqYh1ZTTJCSea5W7CUfAX7F3Y+XKVKIT8aL\na4wfLzl2ovi0PE0ZERGZeXXM8c77a7yRuUHGAZKBdkwORsbguztFmeJw81kVeNeZo0XmuImJCT78\n4Q/z7W9/m4cffpgbbrgBgMsvv1zDy0VkVsqaAvIYYR3vaq6j+cPgig8ASnuki8PWi+cfBkrnm3cS\nssKSoYyIiMywF7g81asdufuZ0uWxmEwOlsXiCq9rCQ+uTwKH3X3WTbFy933uvhW4K2Y1v67VbZL2\nMDw8zNve9jYWLlzIsWPHLgbdIiKzWdbuhAcJc7h/hTLBdUyY0gHsakDbKnL3o2b2IGGJk6ReYGei\np7oX2EPIwl7UzdQehDRlRERkhp2/UH6o+YuH/oYXv/G3M9yahjhJGH5eaXrTNFWSp00Ao2Y2HP+m\nzq3Sbhqdo2XTpk0sXboUgEKhwPLly1m1ahUAhw4dAtB2m27/9V//NYODgxw+fJj/+l//K5dffjmH\nDx9um/ZpW9vanvvbxX+PjY3RaJmymgOY2QihV3s/YYhYcU3RNcAiYNTdr21wOyu1ZQtwDXAq/j3i\n7veXlLkO2EiYH95ByLpemmG1Zpky51ZWcxGRqI/GZzVf+PxTqcqeueK1U85dzH5NmHY0JcCNK1Z0\nVEmuVvU4wv2uZt1mts3dd5W8X6y/s8I0qVxi0Lre3ZfkODb1Q4AcdZfNal6hbAfwOOG3xFFyfH/x\nfWU1n6UOHz7Mb/3Wb7FixQo+85nPsGjRolY3SUSkpVnNcfcVMXt58cl6cU3RM8Aud7+rEQ1L2ZbS\nYXzlyhwjDJGvq4yIiMys8y/lm+OdNsdH3uNqlYn/7jezoZJzFXtzG5240wkPvvOYMLPu0ofWSWbW\nT1iqM3NgX6auhuVokbnhxRdf5A//8A/5/Oc/z7333suGDVqmXUTmply/auJT/F1w8UY43s5riYqI\nyOxz/qXcWc1hMn9HMrhLk78jzXFVy7j7qJn1lAkQ1xBGVDWsh9nMVhOmRqUO5mNSM2dyutaKuG52\n2eKElUoa1f2YNUdL1u9PZpH/+T//J7/1W7/Fq171Ko4dO8brXve6VjdJRKRpcgXecS3TDsKwci25\nJSIiDVdn4F0zf0cc+j0C9CdGUDUqN8i4mS2Lq3cUz9UNbM7yIeLQ6mpjp4vBc5akbXtKtnviq5rh\nDMxg+e8AACAASURBVPUnTRme1+AcLTJLXbhwgXvvvZc/+IM/4BOf+AQ9PT2YNWymiohIW0o1x9vM\nFhKGlm8hPK1O/tfRCU+u9wI7mjVXrN1ojreIyKQ+Gj/H+5Knf5qq7IX/66qy566VvyMGw6PAtuRQ\n60blBok9yx3AEsK9sz/rMGkzq9XDOwF8KcsSZWa2PrE5BAxSPbA+7e4HUtZd/L3QQegpH4117y9Z\nWq0hOVrKnF9zvNvcj3/8Y377t3+b5557ji984Qtce+2MpAUSEcmlkXO8awbe8cZ3gMl1NY8Rkp4U\n518tJiRbAzgNrG5k0ph2pcBbRGRSH40PvPnRi+kKv+FlDT33fBID+/60gXW7U+DdvtydP//zP+ej\nH/0oH/nIR7jzzju57LJ8eRxERGbKjCVXi0+uR+LmLkKP9pky5QqEJ9x3AiNmtmi+9HyLiEiT1DfU\nXFJw97W1S4nU5//8n//D1q1b+eEPf8ijjz7K8uXLW90kEZEZV+tRY3HOWNVs5TGxWm+cn3NnPO4D\nDWmhiIjMTy/Nv07suARX1i5bA9zd35jznKuBLmBZtXLufkue+mV++8u//Eu6u7v5zd/8Tb74xS/y\n8pe/vNVNEhFpiVqB91rCzTzVEmHu3mtmdwIbUOAtIiL1eKnVDWiJaaPKCAFxIbF9kjDNa2HcPkrO\nJcriPPTSZGsidfunf/onfu/3fo/h4WG+9KUvceONN7a6SSIiLVUr8F7G5FDztI4BGkMkIiL1mYeB\nt7uvSG7HJTuPEILrLe5+LPFeJyHr93WERGZ5FEe2rZ0r87yl9d773veyf/9+Xv3qV/Otb32L17/+\n9a1ukohIy12SokzWp+haXkxEROr3UsrX3NYf/65OBt0QluaKgfpZYCBn/R3AoIJuaYSf/vSn/Lt/\n9+945JFHeP7553nyySe54447Wt0sEZG2kCbwFhERmXkvpnzNbWsIS3GVG4JeNBzL5XGG7HPKRabZ\nv38/b33rW5mYmLg4rHzlypUMDg62uGUiIu1B6ziIiEh7er7VDWgLRuiVrmYZ5eeGpzEIbDGzXq1G\nInmcPn2aO+64g+HhYQYGBnj3u9/NxMQE3d3dDA4OUigUalciIjIPpAm815jZgxnqXJ23MSIiIhfN\n/WHkaQwD68zsNnd/qPTNmBytE9ibp/KYFLWDsBRoL2Eu+XiFsgrMZYqHH36YD33oQ9x6661873vf\n45WvfCUAhUKBoaGhFrdORKS9pAm8FxGWGREREZk5CrwBeoF1wB4z2wvsJ+RSuYaw8sj6RLnMzKwY\nZBeoHrw7oIXVBYBnnnmGD3/4wxw/fpwvfelLvPOd72x1k0RE2l6twHvljLRCRESklAJv3H3UzFYS\nspd3Mf1BeDHb+cmcp0i7lJjmgQvuzhe/+EU++tGPsmnTJv7sz/6MK6+8stXNEhGZFaoG3u5+dKYa\nIiIiMoUCb+DivXhFXD6sI75GgdF679Pu3tOAJso88MQTT7B161aefPJJvvrVr7JypfpmRESyUFZz\nERFpT1pObIq4fNhed98V/zb04biZLTCzpWa2sJH1yux24cIFdu/eTWdnJ7/wC7/A4cOHFXSLiOSg\nrOYiItKe5v5SYamY2WrCEPNl1cq5+y0567+OMJS9kzCkfC1w0MweB3a7+yfz1Cuz32OPPcaWLVs4\nd+4c3/jGN3jzm9/c6iaJiMxaCrxFRKQ91bmcWByavYKQpbsDOOruBxpxXNa6zawA9Lv71oyfYR3p\n52FnZmbLgJG4eYCpK5MsAXaZ2UZ3vz5H3euB0+WuS/xcHYQkcR3AgLvvKymT6/uT+r300kv8yZ/8\nCf39/XzsYx/j3/7bf8ullyq3nohIPRR4i4hIe6pjGHlcIqvf3W9O7Bsys9FqicjSHJez7p2EVUKy\n2hn/rm1S0FnMhr4COEliKTF3X2Rm24B+M9vh7tvTVmpmawhrhK8v8946wvz0fXF7IWE5s8Xufl/c\nl+v7k/r9wz/8A7/zO7/DK1/5Sr7zne/Q0VFrGXkREUlDc7xFRKQ91TfHuxfYXbJvgMlAtp7jMtUd\ng8hF5MsM3gEMNrGndwMw7O7Hyr3p7ruAY5QJoMsxs2VmtpswLL7seuBAR/J87n6GcO0GEmXyfn+S\n0wsvvEBfXx833XQT3d3dDA8PK+gWEWkgBd4iItKe6gu8uwhLbSWNUDuATHNc1rpXE9bfthrnLucM\nzV3KqwCcqFGmuG54Te5+0t23FnuuS8Uh9xvLJHA7EN9fGrfzfn+Sw3e+8x1WrFjB0aNHOX78OJs3\nb8Ysz/9cRUSkEgXeIiLSnnIG3jG4K1DS4+ruE/H9peVOl+a4rHXHxGjD1T9oVYOEQHVBHXVUcwyo\nlaL6OqYHwbnE69RBlURxeb8/ye5nP/sZd9xxB//m3/wbPvaxj/GVr3yFf/Ev/kWrmyUiMicp8BYR\nkfaUv8d7MYC7n61Qc6Xxs2mOy1p3R5yTnKv70N17Cb3BI2Z2Wwz+F5R75akfeJCwRvivUKZn3cyG\nCJ+pnocHU7j7Ync/XrJ7DSER2xj5vz/J4NChQ7ztbW/jqaee4h/+4R943/vep15uEZEmUnI1ERFp\nT/mXEys08bjUdZvZukpDrjPUUez1LQB7qxR1IHPaaXffZWYbCcH9/ri718x6CMHwIkIitLuy1p1R\nD7Aj/jvv9ycpnD17lm3btvHVr36Vz33uc7z3ve9tdZNEROYFBd4iItKe6lxOrJXicOlGSLuUWO55\n4O6+ImYvL2YtXxv/ngF2NTvoNrNu4P/TeuHN91d/9Vds3bqVd7/73Xzve99j4cLSqfYiItIsCrxF\nRKQ9VUqcNnYIfnRoBhuSS1dJb3euwNjdexrUnlrn2QXsgotZ2MeLc6qbKZ6r291rzTNPbdOmTSxd\nuhSAQqHA8uXLWbVqFRCGVwPzbvv+++9n//79TExM8PGPf5yPfexjbdU+bWtb29pul+3iv8fGxmg0\nc29mstS5y8y8r9WNEBFpE32AuzdsgqiZOdtT3p922JRzx97mcaBQOk/YzC4Q5l2PlTlnzeOAiRRl\nFgEkl8yKvbpr3H1Dug9VmZktqDL/OWtdW4BT7v5QI+orqftxQlB9sEqZIWBz8vPk/f7i+67fNZOe\ne+45/viP/5i7776bl14KT7K6uroYGhpqcctERGYHM2vY7xslVxMRkfb0YspXidhTO0pJEq7YuzpR\nKWhLc1zKulcSMpH3F1+EZbA64/a69BfhYv13mtnjZnYemDCz82Z2yszuyFpXiQGgrnnoecX1vreV\nBtd5vz+Z5O586Utf4k1vehMjIyP80i/9EgArV65kcHCwxa0TEZmfNNRcRETa0/m6jh4GrgeS2bM7\nmUwgVs9xVcuUS6hmZncCK/PMlzazI7H+M8BBJoPSlcAuM9vo7tdnrTe6H9hsZsvLZBpvmtjT3p8M\nouPSa6MxC3ze72/e+/a3v81HPvIRnn/+eb7whS9w4403MjExQXd3N4ODgxQKyl0nItIKc6bH28wK\n8el56f5OM9tiZutij8HqPGVERGSG5V9ODKAX6CrZ1x33AxfvGydiEJj6uJRlSr2KHEuKxd7yTmDQ\n3Re5+1p374l/FxF6q1eY2Y7qNZXn7t3AXYTlyjab2fIGrxk+7TOb2fr4z8Xx/ttpZmsI8+JPxvfy\nXON57cc//jG/+Zu/ybp16+jp6eHw4cPceOONQJjrPjQ0pKBbRKSF5swcbzMbABYl58/FYWm73f3m\nxL4hoLd4c09TpsL5NMdbROT/b+9+YuO66v6Pv7/tg4RUEU/SR+oGpHgS2IEaJ2HNL3bySOzaOMkK\nqZUau0iwgD6JG1BRpEo/4hQWrBqn3XQDT+MmLNFT2yU/IbF4YicFwaJ64kkqEAvUOE6EhFCh39/i\nnJtcX9+ZuTNzx/Pv85JGztw5994zx27v/d5zzvdE5+nCHO+XCl6f3s6ff2VmB4BTwA1CD/Faer5x\nnEtcIwx3frvofkXLxHLjhGDxJDBGCJQX0vO/G4m93RV339+gzDohGVrLvd6Z5crS0o1vgLt70+XK\nzGyMkB29ShheXyP0Xi+5+9XU/O086+7+5dSxCrVx5vwjN8f7b3/7GxcuXODNN9/kO9/5DmfPnuWp\np57qdbVERIZCmXO8h2KoeQyed7M9a+wckO0FXwDmCTdBRcuIiMhO62yoeZLcrG6AG+cS72l1v6Jl\nYrk7wMvx1Y4Jmi8ptgy81ObxVwqWKxTNuvsDQg96vc83KTjarmgbj6p//etfvPPOO7z22mscOXKE\n3/3ud3zxi1/sdbVERKSOoQi8gUnCvK+jme0ngOzwuzXCU/hWyoiIyE6rP4x8lNwhk2Qsx8FYrmXu\nnh3OLQPg+vXrfO973+Opp57il7/8JV//+td7XSUREWli4Od4x/nYyznbK4Shc1uGtCXrkprZ3iJl\nulJpERFprrM53sNimTCHOzd7eZyfPkHOdbAsZjZpZm926/hS3O3bt3nuued48cUX+cEPfsBvfvMb\nBd0iIgNiGHq8q+6+YmbZsfd7ABqsdVoF7hYtIyIiOyxnqbARNAdMEbKXzxIC7HVgP2G01z7C2uJt\nJx2L87KniOuPZz+Oxx4Hvt3uOaQzm5ubvP7667zzzjucOXOGX/ziF3z+85/vdbVERKQFAx14m9nx\nvGVboiKpO5XeU0SkX3U4x3sYuPummR0k5B05TQi00y4TkoE+aOf4MfnbGs2vh1r8uQc+/fRTFhYW\neP3113nuuef44x//yDPPPNPraomISBsGNvCOw8R76tepf+8ldAeIiIyCO+zAcKDhH0ZeSJz+NAvM\nxmSiVcJ617USDj9PCLrnCInMFgiB+AKht3se+MTd200OJ21wd371q1/xyiuv8KUvfYnl5WW++tWv\n9rpaIiLSgZ4H3vEmoqh7qaf6JzK93Tu+fsj/2ekTioj0iXG2Pmz8f904yd+7cdDB5u612Ev9WUmH\nnAKW3f0NeLQ05wl3X4nvJ4GamT3v7tdKOqc08Ic//IFXXnmFjz/+mJ/+9Kd885vfZPtsOhERGTQ9\nDbzjzcOFFnb5H+AnZjYBrGYPl3lfi+fYVWcOd40wL65ZGRER6YURHmpuZscJ62Hfc/f/yHw8B0yZ\n2X3CMPO3tx2guAphznjiJqnrchzqvhjrosC7i/7617/yox/9iGvXrvHaa6/x8ssv87nPfa7X1RIR\nkZL0NPCO65u2s1b2QWCfmZ1KbZsAqmZ2Abjh7lfNrEYYkvdhUij2sG+6+934vmkZERHpgREdam5m\nl4CZ+DZvbvV7wNPAAWDBzA66e7uJz7LLla3GOjzr7sl1cZ0wv1y64B//+Ac/+9nPuHjxIt/61rf4\n6KOP2L07L8+diIgMsp4PNW9HXkI1MzsDHHL3V1Obl4HDpIJqQoC+1GIZERHZaSMYeMeh3TOEEVdH\n4wPqLdz9MnA5PiReAmbMbNHdP2jjlDeB583siLt/EHu4HxDmlCfB/CHiCDEpj7tz9epVzp49y9e+\n9jV++9vf8pWvfKXX1RIRkS4ZyMC7jn9n+3DzOWARSAfqMzzuSShaRkREdtpoLieWLAuWG3Snxfne\nR4Hbcb92Au854DiwZGYn4jzuK4REbnsIS4xNoazmpVpdXeX73/8+Dx8+5O233+bIkSO9rpKIiHSZ\nue94TrJSxXnic4Qh62OEAHrB3W/Fzw8Ap4AbhOF0a9legSJlcs7r58v9KiIiA+s84O6lZYAyM+dA\nwevTLSv13L0U521/4u5fbmGfNWBXK/tk9q8SrqOX3P1WXDVkhTCUHcLIsBPtLlm2k8zM+/m+5s9/\n/jM//OEPWVpa4vXXX+eFF17gySef7HW1RESkDrPy7jEGvsc79gi8HF95n98iLJHS6BhNy4iIyA4b\nwaHmhAfI/9PiPhvAs+2eMC5LNpt6vwkcTJbtjO+lAy+++CK//vWv+ctf/sJ3v/tdPvroI77whS/0\nuloiIrKDBj7wFhGRITWay4k9YGuysyIOUsIqHGa2izCfu0KY011TktFy/P73v+fjjz8G4E9/+pOC\nbhGREaTAW0RE+lOHy4nFpScPEnqEq8DNZH3qTvcrWGaKMD/6HrCPMI1pW3LQjFXgiJntLRL0xqlS\nFcJw8LbEKVsLsa5pbmbLhCXLPty+Z9PjTgP3G7V5ozLt/v760TPPPAPAoUOHuHxZ0+VFREaRAm8R\nEelPHQw1j/OWL7j7sdS2K2ZWa5S0rMh+BctMAZ5eacPMVs2s4u5vNKj6PDBJyFbecM62mY0RkoMC\nvNuobINjjANrhOD9ZjxOssTY0fg6FJcsu9vCcZOEbNPtlGn399evfv7znzMzM8Ply5epVCq9ro6I\niPTAE72ugIiISK5/FnzlmwMuZbYtEALbRorsV6TMLNst19n+iLsvA1eBfWZ2z8xeikPAHzGzMTM7\nzeMAedndrzY6bgPzhKB71t0Pufsb7v6eu19096OE/Cm7ad5uSd3G4zrk44Se6rbK0P7vry9VKhWu\nXLmioFtEZIQNfFbzXlFWcxGRx87Thazm/17w+vTJ9oyjZrYBTKR7aWOysA13r/vQuch+BctcAdbd\n/VyqzDxwxN0PN/tKseyZ+DZpiBqP538n3/eyu+cmFy0ifpeaux9qUGYN2OvuT7d47NvATKNVQuqV\n6eD319dZzUVEZLCUmdVcPd4iItKf/lXwlREDtAqZ3tQkO7eZ7c07XZH9ih7b3U+mg+5omoJDwt19\nDthPWCLzLiHQ3hd/3iUM0d7XSdAdVYD1JmVqPA70u67d35+IiEg/0xxvERHpT+3P8d4D4O4P63xe\nJQSvbe/X6rHNbAZYdfef1Nlvm+wyX12ywvakalmThKRvO6Xd35+IiEjfUo+3iIj0p78XfG3X7kTa\nIvu1dGwzOx7nMx9w91PtVaurZoEnzOy/sz3JcS72+/HtzA7WSROhRURk6KjHW0RE+lOHy4n1g5j0\n7GpMiLYKnHb3W72uV8pZ4AYhe/m6mW3yeC55hTDEfBNYNNs62rzIXHUREREJFHiLiEh/qpsj63p8\nDQ53f2BmC4Sh3Xt6XZ+UU4SWfhDfP0GYWw6QDPW21LZE32Ywe+GFF9i7dy8Qsok/++yzfOMb3wDg\n+vXrAHqv93qv93qv97nvk3/fvXuXsimreZuU1VxE5LHzdCGreeHYbmvG0ST7NVDJzhM2s8+Aat6a\n1EX2I/T+tnzs+HkVuA0cdfeVgl9uYLWb1bzd31/8XFnNRUSkNMpqLiIiUkfMfp1eegt4FPhu1gva\niuxXpIyZVc3svpk9W6eKY218ra4zs11mdsTMno8/9/aiHu3+/kRERPqZAm8RERlGy0B2DvIEsFTC\nfs3KJEt01TJlkkDyZpM67KhUErVNwnd7L/5cj0nX6j1A6KZ2f38iIiJ9SYG3iIj0qU8LvnLNAScy\n22bidiAMaTazdTM73cp+zcq4+03Cet3ZoWlzwHw/9dia2TiwRlhS7CahjieBV4EPCEnXVjro/S4y\nPC+vTJHfg4iIyMDQHO82aY63iMhj5+nGHO8HzQsCMJZ7bjM7QEgedoPQ27yWM5e4Bpx197eL7tdC\nmdPAPuBe/LmaPk8/MLMrwDQw6+5v5Xw+A1wCFossh2ZmY8A5QptME9p3GViKGd4LlYnlmrZxzvk1\nx1tEREpT5hxvBd5tUuAtIvLYeboReN8rWPrpUs89SsxsA6i5+6EGZdaAve7+9M7VrD0KvEVEpExl\nBt5aTkxERPpU3WHkUp5kPnojNWB8B+oiIiIytBR4i4hIn1LgvQNWCPO7G5kEVnegLiIiIkNLydVE\nRKRP/bPgSzowCzwRs5fvTX+QynYOIbGZiIiItEk93iIi0qfU470DzhKSlx0lLB+WXkO7Qsg4vgks\nmm2d4ubu2eW+REREpA4F3iIi0qf+3usKjIJTgPM4hfwTwP7474fxp6W2JZTBTEREpAUKvEVEpE9p\nGHm3ufvuXtdBRERkFGiOt4iI9KlPC76kW8xsr5mdMbP/7XVdREREBpl6vEVEpE+px7sXzGwcmCYk\nXhsnDDUXERGRDijwFhGRPqXe7J1iZmOEzOWngInURw+Ad4HFXtRLRERkWCjwFhGRPqUe726KwfZJ\nQs/2Abb2bN8E5tx9pRd1ExERGTYKvEVEpE+px7tsDYLtpGf7MrAK3FDQLSIiUh4F3iIi0qe0nFgX\n3E/9+w5hCPm77n4r2Zhdr1tEREQ6p8BbRET6VGc93mY2ARwENoAqcLNIL26R/QqWOR4/2xd/Lrj7\n1Y6+VHmWCEPJP+zWCcxsGrif1+ZltbGIiMigUOAtIiJ9qv053mZWBS64+7HUtitmVnP3O53sV7DM\ncaCWBNpxiPeame1x97fa/mKduwocB44CU2ZWA94jPBS4W9ZJzGyKMGx9OuezUtpYRERkkAzsOt5m\nVjWzJTObNLNKfH/BzCYz5SbM7LSZHY9rkU7mHKtpGRER2WkdreM9B1zKbFsA5puctMh+RcpU08O3\n3f1B/Hyhyfm7yt1PuPsThHneHxB64+eAmpn9r5n9ZyfHN7NxM7tEWIZso06xstpYRERkYJi797oO\nbYlPw2+nNm0CL7n7tUyZS9kn5oThdXeKlqlzfj9f1pcRERlw5wF3L21ysJk5FO0YPr3t3Ga2AUyk\ne3HNrAJsxMCz3nmb7tesTPz3MjAZA+6kTHLdqpbZu9yJWNeTwAkg/dD5PqHHuu2ecDO7Dcy4+weZ\n7R23cYNz+qDe14iISP8xs9Lubwa2xxtwYAqoEG5i9qSD7khP1UVEBlZ7Pd4xQKuQ6XF19834+d68\nsxXZr0iZ+O8qode3r7n7prtfdvejwB7gZeAWsJtwfVwvoyc8UVYbl1EXERGRnTTIgTeEHvuHDZ7G\nnyCsRZq2xtY5Z0XKSBdokl7n1IadUxv2s38WfG2zB8DdH9Y5cLXO9iL7FTp2fBicTVw2RUg2drfO\nvj2VCsIPEr7nq8CHhOHoZT2MLq2NRUREBsmgB9516al6/7vb6woMgbu9rsAQuNvrCkgDfy/42qbS\n5gmL7NfusSGsnf3jDvbfMTEIvxiD8P3AuZIO3e02FhER6UuDHnhXY0K040lytNRneqouIjLQOkqu\n1lfMbAb4xN1/0uu6tMrda+5+sdf1EElcv36911Xoa8PSPv3+PXpdv508fzfP1Y1j9/p3U88gB94b\nAO5+Nb7eAk6lgm89VRcRGWhtDzXvKzGp2oy7/0ev6yIyDPr1prpfDEv79Pv36HX9FHjv7DHLMLBZ\nzfPEZcAW3H2/mU0Aq3nZT83sM8Jcu81mZbLZWFOfD0/DiYiUoPys5u2dO8l+DVSyI5ri/9tzs4oX\n2Y9w3Wjp2HGljJcajK4aSnlZzbvVxqnPdW0WEZFSlXV/829lHKQTsSegqHvppVly3CEMP9/VYbWa\nKvMGU0REturk/7HuvmlmNUIQ9yjBWbzebNYL2oru18qx45rWZ0ct6K6nG22cOb6uzSIi0pd6Gnib\n2ThwoYVdbgBvxH3P5sw5S5KkVYFaLLerzg1PjfBUvVkZEREZPMvAYVKBGzABLJWwX6Fjm9lp4EJm\nLepJoObuo5xQv7Q2FhERGRQDOdQ8PvW+TWa4WWp7xd0fxmFu0+klXWKZVXffE983LSMiIoPFzMaA\nRXc/ltr2PmHo8934vkJYPvJCzBNSdL8iZaYJa2Gvpaq1h3C9ebn0L9yH4vV11t1XMttLaeMW6nEA\nOETI63IYmBvxBx8iItKBOKV5N+G6chSYL3Jd6flQ83a4e83MZnMuvlPAWqr3Wk/VRURGkLs/MLM5\nM7tAGC1VJdP7HO0GvJX9mpWJAf2VOlVbL+P79asYMJ8jtEkVWDCzZWDJ3a9COW3cYn0OpR6sTBKu\n7/s7+6YiIjLCloG9saN3D7BIeMDb0ED2eAPE7OU3k6cL8UZnmZDA5sO4bUefqovslPik7SBhekWV\n8N/CSuO9RkMcsbJAmMayRuhlnCHc+K+kyjVtw1Fq59hDez/v+5XVVqPUnlKudv8+42dX3H1/fF83\nuZuIiIyOTu570tOU43Hm3P1ws3MOZI83hGXE4vrd08DThK7+6VafmNcrAxwys326Ce2cAqFyxfa8\nkHlYdMXMRn3eaNpkfEHI5fBS5m+taRuOUjub2RRwGZjO+ayUthql9pRydfL36e434/6JQ4QbLQXd\nIiIjqtP7nsw1ZAaYK3LegQ28IQTfBcrcAm61UkY3oV2hQKg8c8ClzLYFYB44ufPV6TtOmHayCuyp\nM3KlSBsOfTvHBJdzhAdiG3WKldVWQ9+eUq6y/j4z/w+YAU6XWlERERkIJd73JMeaBt73OstPbzv/\noA4174bML2OOzPqjscwC8N/ufi21bZKQQOZkmWWGRWzXcRoEQmqz4sxsA5jIJBasABuesyb9qIl/\nb9VGIyGKtOGotbPlrLkct5fSVqPWnlKuTv4+U9tPE5YlvYaIiIy0Mq4r8bPjhFjkWPazLN3spMRh\naS8nSVjqOAHczGxbY2vveFllhom5+8MG8+bVZgXE//CTOYqPuHuyNN7ena/VYCnShmrnoKy2UntK\nN7TydxUf0q4r6BYRkXoK3tNUzexM6uMVYKrIvYwC7xboJrQ71GYt2QPb5pakVXewLv2sGnNAHDez\n0/FpZKJIG6qdg7LaSu0p3VDo7yrmBtlIejUs5IYRERHJKnJdGSfkF0tvu9+gc/GRgZ7j3QNFfhl3\nyywzRKoxeIbQjhupOfqltuuQqzQvMvI2YGsOiJgLINlWpA3VzkFZbaX2lG5o+ncVc4Osxn8nm9eB\n97pXLRERGVBNryvuvmJmlTh9aYOwjvdkk90ABd6t0k1oexQIyY5x9wdAdrrIQnw1TcgoIsPD3Wto\ndJ+IiJQok+C78L2lLkbSde7+IGfefJIdUGQn3CGMutjV64qIiIiIyOgZyh7vOLSsqHuxh0yaKLld\nFQi1pwZgZrvqDLuv7XB9+o6ZnXX3i5nNSW6AKsXacLNAmVFQVlupPaUb9P9DEREpU1evK0MXepX3\nPAAAChpJREFUeMelhC60sMsN4I2CZUf2JrSTdlUgVB533zSzGqHdPky2x4cim0USOwyzZK13M7uS\naYs98WfN3R8WaUO1c/G/N7Wn9IL+fygiImXq9nVl6AJvd79DanHzko89sjeh7barAqGuWAYOk2oH\nYAJY6k11+oe718xsNufvYQpYSz20KdKGauegrLZSe0o36O9KRETK1LXriuZ4ty75ZaTVu8HstMzA\ni4ltWgmE0kayzQqYI6xpnjYTtwtsxBEawKPl6maA06kyRdpwFNvZcraV1Vaj2J5Srnb/PkVERPLs\n6HXF3L3TYwwlM7tNCBhXMtvHgEV3P5ba9j4wk+qZLaXMsIhrKN+MveZJILQMvOTuH8ZtarMWmNkB\n4BRhSH+V8BDjg97Wqn/Ev7kqYZ3FCnAh+zdSpA2HvZ3jf1PnCN9tmjBlYxlYyqxCUEpbDXt7SrnK\n/PsUERHp9XVFgXeKbkK7R4GQiIiIiIiMKgXeIiIiIiIiIl2kOd4iIiIiIiIiXaTAW0RERERERKSL\nFHiLiIiIiIiIdJECbxEREREREZEuUuAtIiIiIiIi0kUKvEVERERERES6SIG3iIiIiMiAMLNFM/ss\nvsbqlJlJlcm+1s3sUr194/4LZnYhs20+7vuZmd1udgwR2UrreMvIMbMJYLVA0Zq77+92fbLMbAmY\ndPeePxgzswXgvru/WtLxKkANOOjud8o4poiIyCgxs89Sb2fd/a2cMjPAJWAduJn6qAIcAnYDm8C4\nuz/I2X8DmHD3u/H9OjAO3AeWgX3ARKNjiMhW/9brCoj0UHLxqGejmyc3s2ngCnDC3a+mPvL46qn4\ngOI04SJdCnffNLMfA4uEC7+IiIgUFO8dAJaAo8AssC3wTpl397dzjnMFmAbOAa9mPpsANlJB91lC\n0L3o7qdS5U4DC4Rr+rE2v5LIyFDgLaNsOX0B6aFskH2C8CS6194iXLAflnlQd38jDlc7nnngICIi\nIo3NEu4b5oD9wAEzG2ujx/nHhMD7QM5npwjBdPo9hIfxj7j7W2b2KjDZ4rlFRlLPh7KKCJZ+4+4P\nkqfMvRKfdh8gPMnuhvcIT9lFRESkgDhda5IwFe5DQnBswMl2Dhd/buZ8dhx4N/V+nDDtLO9B/M1Q\nNdvbRh1ERooCb5GCzKwaE5okiUU2zOyKmY3nlJ0xs7VUuVUzm0x9vkQYZg6QJEnZFT9bTM/figlO\nNuK/583sfiqxyfGcc1fiMZJyV+K2NTN7v+DXPQesZx8AZOqyEM9xP55jLLU9aaP389qHENBP1PlM\nREREtksC7PfizyQ4nm2wj9XZfo7Qc77lAbuZVYE9MbBPTAIH6xxnAvBedxiIDAINNRcpIF6IbhMu\nUsvA+4TEItPAlJk9SixiZvPAGcIc8uRp9DSwZGYH3f0WcIGQ8GSGcNFbyzxJ3jbH28wWCRe//4rH\nnCEE7UfdfSVVzzVgV6znJmEOWJJM7pOCX3kqnidPJQbwuwmJW47G7zdhZg/iua/E7VOEeWhbktS5\n+4qZEfd7o2CdRERERtmJ+HMBwN1vxetuo+Hmc2aWnn+dJFcbA2bc/YNM+Wm29nYT71u2iQlYx9k6\nLF1E6lDgLaPsaAxm6/mv1BzkOUIwfDR9kTKzM8A8IcBMys4Qeou/nCo3SQhAZ4Bvx8Bzd3y/5O7X\nmtS1AjwL7E0C9Fj3JcKFeCWWmydcTKeSesae6DWgSgj2G4rB+1g8dj3u7ofjv8+Z2e14/CV3P5ja\nvkq4IdiVM0StRgjOFXiLiIg0kBpmnh2N9i7hXmKG/OtplRAc5zlmZouZgP0UofOgWV3eIgxJXycz\n91tE8mmouYyyCvB8zut4/JnOun2JkH08+2Q4eQqcToY2RmbOVOyRniAExu2aSwevSS838YIaL4TH\nCcHvB6lyDwgPDoqaiD9rjeqSeZ8O/LPbDdiTc4xbKLO5iIhIEckw82zulcvxZ71ksTPu/mT6Rbgm\nzxF6t5Prd3IfcSDnXodUmRnCqi/HCQ/oD5adhFVkWKnHW0bZlmUxGonDrG7BowvTIUKAmjev6j1g\nOvYCLxCyp9/KzJdqx80mnydBbF4v/krOtnqq8WdewpVEvaC8yProiQ1KXKpMRERkiCX3GxfN7GLO\n5xNx2tudZgeKD+TfMLOjhOlyB+J9zknqDBuP9z7JlLf7wOkCo/VEJEU93iIFxORkC2Z2nxAwvk8Y\n4r2WLevuJ3ncIzwPJEnWLiUJyNrUbF3xJGDeVs7dGwXRWU8XPF+nNgGSpHIiIiKyXdITTQh4F3Je\nyYP56dwD1JeM2kuGop8gM787ZYUQdC+5+9MKukVapx5vkWJWeLy81kLSex3nbm+70Ln7G4SnybsI\n85hnCfOvDtG94dVJL/S2Yd3xol3UvdRxujl8rAKgIWoiIiINzcSfl91921KcqTwys7SWNyW5N9hM\nzSHPWy1lnnAPNJ93fhEpRj3eIk2knjQvuvu3M0PGLVO2Gpf8moQQVLr7VXc/RgjeJ7rYw5sE3sdy\nPmsl2E+O0+1h4HsIT+9FRESkvlPkLP2ViDlfHgDjOct05i4nZmYThKRo9wnTxKYIvdl5D8OTpLEK\nukU6oB5vkeLSCdSSgDxJJpa+sJ0hPDHesoQWYSi451zU6q2x2RJ3r5nZMmF++WRqibEKdS7WdSRD\n1qpAp/PSG5mgtTnhIiIiIyWuNHKA7dnMs5Ls5tllOrPLiUG4vh8gBPNz7v7QzGbJGWaeWunEzWzb\n9LrIgck6y5mJSKTAW0ZZs+XEkgvSnRjQTpnZFUKwuI8wF+pGLDtnZrW4TFhSdoPQy71BSFiyC0gn\nREl6e+fN7LC7v5r6rN1gfI4w73wp1uMBcU4WYQ5X07neMYDfJPScd3MO1zjwZhePLyIiMuimadDb\nnbLI1mXFPG4fJ385sTXCPU6SwfwIOcPMeZw/ZoywrGmWxXN5zmcikqLAW0bZGGHZsDzJheT/xvcn\nCL3bJwkXwTXgJXe/ZmaXCMO1poEVdz9mZhfi++cJwe5t4MfpZCTpID3unwTe2QtY4Quau98ys308\nXlvcCXPSz5nZCYonTEvqte0UderS0nYzS479XsH6iIiIjBx3v8jWh/b1yq2QmkLq7m8R1touep4n\n62xfRlNTRUph7npAJTIsYkC7nl1OJA4Vu03BxChmdoDwcGFfkaVJ2qjnIrDX3Q+XfWwRERERkX6j\nwFtkiMTlzu65+/7M9gVCr3q1yRyx9D6rhDXIX21auPV6fgZMazkSERERERkFCrxFhoiZnSbMA6sB\nV+PmKR5nZT/VwrGSueG7y0yYYmZngRPq7RYRERGRUaHAW2TImNlx4ByPE6KsE+Z5v93GsS4B98ta\nQiRmWK8BE0V73kVEREREBp0CbxEREREREZEuUpZCERERERERkS5S4C0iIiIiIiLSRQq8RURERERE\nRLpIgbeIiIiIiIhIFynwFhEREREREemi/w8BbuVB0qANuAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10e2d5d10>"
]
}
],
"prompt_number": 22
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step6: Run inversion"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dmis = DataMisfit.l2_DataMisfit(survey)\n",
"reg = Regularization.Tikhonov(mesh,mapping=mapping)\n",
"opt = Optimization.InexactGaussNewton(maxIter=7,tolX=1e-15)\n",
"opt.remember('xc')\n",
"invProb = InvProblem.BaseInvProblem(dmis, reg, opt)\n",
"beta = Directives.BetaEstimate_ByEig(beta0_ratio=1e1)\n",
"betaSched = Directives.BetaSchedule(coolingFactor=5, coolingRate=2)\n",
"inv = Inversion.BaseInversion(invProb, directiveList=[beta,betaSched])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 23
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"m0 = np.log(np.ones(problem.mapping.nP)*sighalf)\n",
"mopt = inv.run(m0)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"SimPEG.InvProblem will set Regularization.mref to m0.\n",
"SimPEG.InvProblem is setting bfgsH0 to the inverse of the eval2Deriv.\n",
" ***Done using same solver as the problem***\n",
"SimPEG.l2_DataMisfit is creating default weightings for Wd."
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"============================ Inexact Gauss Newton ============================"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" # beta phi_d phi_m f |proj(x-g)-x| LS Comment \n",
"-----------------------------------------------------------------------------\n",
" 0 2.61e-01 6.27e+03 4.48e+00 6.27e+03 8.80e+03 0 "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 1 2.61e-01 5.22e+02 3.96e+00 5.23e+02 2.50e+03 0 "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 2 5.23e-02 1.67e+02 3.91e+00 1.67e+02 8.21e+02 0 "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 3 5.23e-02 7.93e+01 4.08e+00 7.95e+01 2.62e+02 0 Skip BFGS "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 4 1.05e-02 6.35e+01 4.25e+00 6.36e+01 1.71e+02 0 Skip BFGS "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 5 1.05e-02 3.01e+01 5.08e+00 3.02e+01 2.36e+02 0 Skip BFGS "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 6 2.09e-03 2.33e+01 5.32e+00 2.33e+01 1.57e+02 0 Skip BFGS "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" 7 2.09e-03 1.01e+01 6.69e+00 1.01e+01 1.34e+02 0 Skip BFGS "
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"------------------------- STOP! -------------------------\n",
"1 : |fc-fOld| = 1.3195e+01 <= tolF*(1+|f0|) = 6.2702e+02\n",
"0 : |xc-x_last| = 7.9764e-01 <= tolX*(1+|x0|) = 2.6641e-14\n",
"0 : |proj(x-g)-x| = 1.3417e+02 <= tolG = 1.0000e-01\n",
"0 : |proj(x-g)-x| = 1.3417e+02 <= 1e3*eps = 1.0000e-02\n",
"1 : maxIter = 7 <= iter = 7\n",
"------------------------- DONE! -------------------------\n"
]
}
],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# matplotlib.rcParams.update({'font.size': 14, 'text.usetex': True, 'font.family': 'arial'})"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 25
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"appres = data*np.pi*b*(b+a)/a\n",
"appres_obs = survey.dobs*np.pi*b*(b+a)/a\n",
"appres_pred = invProb.dpred*np.pi*b*(b+a)/a\n",
"fig, ax = plt.subplots(1,2, figsize = (17, 6))\n",
"ax[0].plot(abhalf, appres_obs, 'k.-')\n",
"ax[0].plot(abhalf, appres_pred, 'r.-')\n",
"ax[0].set_xscale('log')\n",
"ax[0].set_ylim(100., 180.)\n",
"ax[0].set_xlabel('AB/2', fontsize=25)\n",
"ax[0].set_ylabel('Apparent resistivity ($\\Omega m$)', fontsize=25)\n",
"ax[0].grid(True)\n",
"ax[0].legend(('Observed', 'Predicted'), loc = 1, fontsize=20)\n",
"ax[0].text(100., 181, '(a)', fontsize = 28)\n",
"ax[1].plot(1., 1., 'k', lw = 2)\n",
"ax[1].plot(1., 1., 'r', lw = 2)\n",
"ax[1].legend(('True', 'Predicted'), loc = 3, fontsize = 20)\n",
"Utils1D.plotLayer((np.exp(mopt)), mesh.vectorCCz, 'log', ax = ax[1], **{'lw':2, 'color':'r'})\n",
"Utils1D.plotLayer((np.exp(mtrue)), mesh.vectorCCz, 'log', showlayers=True, ax = ax[1], **{'lw':2})\n",
"ax[1].set_ylim(-500, 0)\n",
"ax[1].set_xlabel('Conductivity (S/m)', fontsize = 25)\n",
"ax[1].set_ylabel('Depth (m)', fontsize = 25)\n",
"ax[1].text(1e-3, 10., '(b)', fontsize = 28)\n",
"# fig.savefig('obspredDC.png', dpi=200)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 26,
"text": [
"<matplotlib.text.Text at 0x11049df90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAA/4AAAGrCAYAAAB5QEygAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCxMAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x114071f10>"
]
}
],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# fig, ax = plt.subplots(1,1, figsize = (7.5, 7))\n",
"# ax.plot(1., 1., 'k', lw = 2)\n",
"# ax.plot(1., 1., 'r', lw = 2)\n",
"# ax.legend(('True', 'Predicted'), loc = 3, fontsize = 16)\n",
"# Utils1D.plotLayer((np.exp(mopt)), mesh.vectorCCz, 'log', ax = ax, **{'lw':2, 'color':'r'})\n",
"# Utils1D.plotLayer((np.exp(mtrue)), mesh.vectorCCz, 'log', showlayers=True, ax = ax, **{'lw':2})\n",
"# ax.set_ylim(-500, 0)\n",
"# ax.set_xlabel('Conductivity (S/m)', fontsize = 20)\n",
"# ax.set_ylabel('Depth (m)', fontsize = 20)\n",
"# ax.text(1e-3, 10., '(b)', fontsize = 30)\n",
"# fig.savefig('obspred_dc1d_mod.png', dpi=200)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}