SVS 13 Parameters.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You appear to be importing analysisUtils into python (not CASA). version =  3.8.5\n",
      "CASAPATH is not defined, so I am skipping a lot of imports\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append(\"/home/akdiaz/Documents/Trabajo/Scripts/Python_modules\")\n",
    "sys.path.append(\"/home/akdiaz/Documents/CASA_releases/analysis_scripts\")\n",
    "import analysisUtils as au\n",
    "from astropy import units as u\n",
    "import numpy as np\n",
    "import parameters as par\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "import matplotlib.pyplot as plt \n",
    "from matplotlib import rc\n",
    "from uncertainties import ufloat\n",
    "from uncertainties.umath import *\n",
    "from scipy import constants\n",
    "\n",
    "K = constants.k * u.kg * u.m**2 * u.s**(-2) * u.K**(-1) #Boltzmann constant\n",
    "G = constants.G * u.m**3 * u.kg**(-1) * u.s**(-2) #Gravitational constant\n",
    "H = constants.h*u.J*u.s #Planck's constant\n",
    "C = constants.c*100*u.cm*u.s**-1 #Speed of light in cm/s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Proper motions (DR2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in='/home/akdiaz/Documents/Trabajo/SVS13/Images/VLA/proper_motions/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_A = data_in + 'pm-A-all-final.dat'\n",
    "file_B = data_in + 'pm-B-all-final.dat'\n",
    "dataA = np.loadtxt(file_A, skiprows=1, usecols = [0,1,2,3,4])\n",
    "dataB = np.loadtxt(file_B, skiprows=1, usecols = [0,1,2,3,4])\n",
    "timeA= [i[0] for i in dataA]\n",
    "RA_A=[i[1] for i in dataA]\n",
    "E_RA_A=[i[2] for i in dataA]\n",
    "DEC_A=[i[3] for i in dataA]\n",
    "E_DEC_A=[i[4] for i in dataA]\n",
    "timeB= [i[0] for i in dataB]\n",
    "RA_B=[i[1] for i in dataB]\n",
    "E_RA_B=[i[2] for i in dataB]\n",
    "DEC_B=[i[3] for i in dataB]\n",
    "E_DEC_B=[i[4] for i in dataB]\n",
    "if timeA==timeB:\n",
    "    time=timeA\n",
    "    teo_RA_A=[0.0005987800990965202*t+2.538137709793499 for t in timeA]\n",
    "    teo_DEC_A=[-0.009186172096178849*t+22.29720008517562 for t in timeA]\n",
    "    teo_RA_B=[0.0006241789738361716*t+2.5099225057460672 for t in timeA]\n",
    "    teo_DEC_B=[-0.010789256173226411*t+25.52782804627961 for t in timeA]\n",
    "    difAR_A=(np.array(RA_A)-np.array(teo_RA_A))\n",
    "    difAR_B=(np.array(RA_B)-np.array(teo_RA_A))\n",
    "    difDEC_A=np.array(DEC_A)-np.array(teo_DEC_A)\n",
    "    difDEC_B=np.array(DEC_B)-np.array(teo_DEC_A)\n",
    "    dif_teo_AR_A=np.array(teo_RA_A)-np.array(teo_RA_A)\n",
    "    dif_teo_DEC_A=np.array(teo_DEC_A)-np.array(teo_DEC_A)\n",
    "    dif_teo_AR_B=np.array(teo_RA_B)-np.array(teo_RA_A)\n",
    "    dif_teo_DEC_B=np.array(teo_DEC_B)-np.array(teo_DEC_A)\n",
    "else:\n",
    "    print('check epochs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a=15*np.cos(31*np.pi/180)\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.tick_params(right=True, top=True,direction='in')\n",
    "plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "plt.ylabel('$\\Delta$RA Cos(Dec) (arcsec)',fontsize=20)\n",
    "plt.errorbar(time,difAR_A*a, xerr=None,yerr=np.array(E_RA_A)*15, fmt='ob', capsize=3, ms=10,label='VLA 4A')\n",
    "plt.errorbar(time,difAR_B*a, xerr=None,yerr=np.array(E_RA_B)*15, fmt='or', capsize=3, ms=10,label='VLA 4B')\n",
    "plt.plot(time,dif_teo_AR_A*a,'--b')\n",
    "plt.plot(time,dif_teo_AR_B*a,'--r')\n",
    "plt.legend(fontsize=18)\n",
    "plt.ylim(-0.1,0.4)\n",
    "plt.savefig('AR-dif.png',bbox='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a=0.2\n",
    "ax=plt.figure(figsize=(10,10))\n",
    "#ax.text(0.15, 0.7, '+0.2 arcsec', fontsize=15)\n",
    "plt.tick_params(right=True, top=True,direction='in')\n",
    "plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "plt.ylabel('$\\Delta$Dec (arcsec)',fontsize=20)\n",
    "plt.errorbar(time,difDEC_A, xerr=None,yerr=E_DEC_A, fmt='ob', capsize=3, ms=10,label='VLA 4A')\n",
    "plt.errorbar(time,difDEC_B+a, xerr=None,yerr=E_DEC_B, fmt='or', capsize=3, ms=10,label='VLA 4B+0.2 arcsec')\n",
    "plt.plot(time,dif_teo_DEC_A,'--b')\n",
    "plt.plot(time,dif_teo_DEC_B+a,'--r')\n",
    "plt.ylim(-0.1,0.4)\n",
    "plt.legend(fontsize=18)\n",
    "plt.savefig('DEC-dif.png',bbox='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def proper_motions(file, file_out, label, color, dec, extra_points=False, extra_plot=False):\n",
    "    '''Does a fit to the proper motion and generates two plots. File and label are lists (one component per source).\n",
    "    If extra_plot is set (must be [a1,b1,a2,b2]) a line y = a1 x + b1 is plot on top of AR plot and  a line\n",
    "    y = a2 x + b2 on top of DEC plot.'''\n",
    "    data = [np.loadtxt(f, skiprows=1, usecols = [0,1,2,3,4]) for f in file]\n",
    "    time=[]\n",
    "    RA=[]\n",
    "    E_RA=[]\n",
    "    DEC=[]\n",
    "    E_DEC=[]\n",
    "    RA_fit=[]\n",
    "    DEC_fit=[]\n",
    "    label_AR=[]\n",
    "    label_DEC=[]\n",
    "    label_AR_final=[]\n",
    "    label_DEC_final=[]\n",
    "    for d in data:\n",
    "        time.append([i[0] for i in d])\n",
    "        RA.append([i[1] for i in d])\n",
    "        E_RA.append([i[2] for i in d])\n",
    "        DEC.append([i[3] for i in d])\n",
    "        E_DEC.append([i[4] for i in d])\n",
    "        time_fit = np.linspace(min(time[-1]),max(time[-1]),10)\n",
    "        # lets fit linear for AR (a*t+b)\n",
    "        parRA, varRA = np.polyfit(time[-1], RA[-1], 1, w=1/np.array(E_RA[-1]), cov=True)\n",
    "        aRA = parRA[0]\n",
    "        bRA = parRA[1]\n",
    "        RA_fit.append(aRA*time_fit+bRA)\n",
    "        E_aRA = np.sqrt(varRA[0,0])\n",
    "        E_bRA = np.sqrt(varRA[1,1])\n",
    "        print(f'eq for RA: {aRA}*t+{bRA}')\n",
    "        # lets fit linear for DEC (a*t+b)\n",
    "        parDEC, varDEC = np.polyfit(time[-1], DEC[-1], 1, w=1/np.array(E_DEC[-1]), cov=True)\n",
    "        aDEC = parDEC[0]\n",
    "        bDEC = parDEC[1]\n",
    "        DEC_fit.append(aDEC*time_fit+bDEC)\n",
    "        E_aDEC = np.sqrt(varDEC[0,0])\n",
    "        E_bDEC = np.sqrt(varDEC[1,1])\n",
    "        print(f'eq for DEC: {aDEC}*t+{bDEC}')\n",
    "        # labels\n",
    "        label_AR.append(f': $\\mu_\\\\alpha$ cos $\\\\delta$ = {round(aRA*15*1000*np.cos(dec),1)}$\\pm${round(E_aRA*15*1000*np.cos(dec),1)} mas/yr')\n",
    "        label_DEC.append(f': $\\mu_\\\\delta$ = {round(aDEC*1000,1)}$\\pm${round(E_aDEC*1000,1)} mas/yr')\n",
    "    if extra_points != False:\n",
    "        extra_data = np.loadtxt(extra_points, skiprows=1, usecols = [0,1,2,3,4])\n",
    "        extra_time = [i[0] for i in extra_data]\n",
    "        extra_RA = [i[1] for i in extra_data]\n",
    "        extra_E_RA = [i[2] for i in extra_data]\n",
    "        extra_DEC = [i[3] for i in extra_data]\n",
    "        extra_E_DEC = [i[4] for i in extra_data]\n",
    "    if extra_plot != False:\n",
    "        extra_RA_fit = extra_plot[0]*time_fit+extra_plot[1]\n",
    "        extra_DEC_fit = extra_plot[2]*time_fit+extra_plot[3]\n",
    "    # do the AR plot\n",
    "    plt.figure(figsize=(10,10))\n",
    "    plt.tick_params(right=True, top=True,direction='in')\n",
    "    rc('xtick', labelsize=15) \n",
    "    rc('ytick', labelsize=15)\n",
    "    plt.legend(fontsize=18)\n",
    "    plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "    plt.ylabel('J2000 RA (s)',fontsize=20)\n",
    "    pp = []\n",
    "    for i,_ in enumerate(data):\n",
    "        p = plt.errorbar(time[i], RA[i], xerr=None,yerr=E_RA[i], fmt='o'+color[i], capsize=3, ms=10)\n",
    "        pp.append(p[0])\n",
    "        plt.plot(time_fit, RA_fit[i],'--'+color[i])\n",
    "        label_AR_final.append(label[i]+label_AR[i])\n",
    "    if extra_points != False:\n",
    "        plt.errorbar(extra_time, extra_RA, xerr=None,yerr=extra_E_RA, fmt='o'+color[-1], capsize=3, ms=10)\n",
    "    if extra_plot != False:\n",
    "        plt.plot(time_fit, extra_RA_fit,'--'+color[-1])\n",
    "    plt.legend(pp, label_AR_final,fontsize=18,loc=2)\n",
    "    plt.savefig(f'AR{file_out}.png',bbox='tight')\n",
    "    # do the DEC plot\n",
    "    plt.figure(figsize=(10,10))\n",
    "    plt.tick_params(right=True, top=True,direction='in')\n",
    "    #rc('xtick', labelsize=15) \n",
    "    #rc('ytick', labelsize=15)\n",
    "    plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "    plt.ylabel('J2000 Dec (Arcsec)',fontsize=20)\n",
    "    pp = []\n",
    "    for i,_ in enumerate(data):\n",
    "        p = plt.errorbar(time[i], DEC[i], xerr=None,yerr=E_DEC[i], fmt='o'+color[i],capsize=3,ms=10)\n",
    "        pp.append(p[0])\n",
    "        plt.plot(time_fit, DEC_fit[i],'--'+color[i])\n",
    "        label_DEC_final.append(label[i]+label_DEC[i])\n",
    "    if extra_points != False:\n",
    "        plt.errorbar(extra_time, extra_DEC, xerr=None,yerr=extra_E_DEC, fmt='o'+color[-1], capsize=3, ms=10)\n",
    "    if extra_plot != False:\n",
    "        plt.plot(time_fit, extra_DEC_fit,'--'+color[-1])\n",
    "    plt.legend(pp, label_DEC_final, fontsize=18)\n",
    "    plt.savefig(f'DEC{file_out}.png',bbox='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_movements(file1,file2):\n",
    "    '''Plots the distance and PA between sources as a function of time.'''\n",
    "    data1 = np.loadtxt(file1, skiprows=1, usecols = [0,1,2,3,4,5,6,7,8])\n",
    "    data2 = np.loadtxt(file2, skiprows=1, usecols = [0,1,2,3,4,5,6,7,8])\n",
    "    time1 = [i[0] for i in data1]\n",
    "    time2 = [i[0] for i in data2] \n",
    "    if time1 == time2:\n",
    "        ar1 = [ufloat((i[1]*3600+i[2]*60+i[3])*15,i[4]*15) for i in data1] #in arcsec\n",
    "        ar2 = [ufloat((i[1]*3600+i[2]*60+i[3])*15,i[4]*15) for i in data2]#in arcsec\n",
    "        dec1 = [ufloat(i[5]*3600+i[6]*60+i[7], i[8]) for i in data1] #in arcsec\n",
    "        dec2 = [ufloat(i[5]*3600+i[6]*60+i[7], i[8]) for i in data2] #in arcsec\n",
    "        sep = [sqrt(((a2-a1)*cos(d1/3600*np.pi/180))**2+(d2-d1)**2) for a1,a2,d1,d2 in zip(ar1,ar2,dec1,dec2)] #in arcsec\n",
    "        pa = [90-asin((d2-d1)/s)*180/np.pi for d1,d2,s in zip(dec1,dec2,sep)] #in degrees\n",
    "        sep_value = [i.n for i in sep]\n",
    "        sep_error = [i.s for i in sep]\n",
    "        pa_value = [i.n for i in pa]\n",
    "        pa_error = [i.s for i in pa]\n",
    "        min_sep = min(sep_value)-2*max(sep_error)\n",
    "        max_sep = max(sep_value)+2*max(sep_error)\n",
    "        min_pa = min(pa_value)-2*max(pa_error)\n",
    "        max_pa = max(pa_value)+2*max(pa_error)\n",
    "        #coor1 = [f'{int(i[1])}:{int(i[2])}:{i[3]} {int(i[5])}:{int(i[6])}:{i[7]}' for i in data1]\n",
    "        #coor2 = [f'{int(i[1])}:{int(i[2])}:{i[3]} {int(i[5])}:{int(i[6])}:{i[7]}' for i in data2]\n",
    "        #source_1 = [SkyCoord(c, frame='fk5', unit=(u.hourangle, u.deg)) for c in coor1]\n",
    "        #source_2 = [SkyCoord(c, frame='fk5', unit=(u.hourangle, u.deg)) for c in coor2]\n",
    "        #sep = [s1.separation(s2).arcsec for s1,s2 in zip(source_1,source_2)]\n",
    "        #pa = [s1.position_angle(s2).deg for s1,s2 in zip(source_1,source_2)]\n",
    "        # do the sep plot\n",
    "        plt.figure(figsize=(10,10))\n",
    "        plt.tick_params(right=True, top=True,direction='in')\n",
    "        rc('xtick', labelsize=15) \n",
    "        rc('ytick', labelsize=15)\n",
    "        plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "        plt.ylabel('Separation (Arcsec)',fontsize=20)\n",
    "        plt.ylim(min_sep, max_sep)\n",
    "        plt.errorbar(time1, sep_value, xerr=None,yerr=sep_error, fmt='-ob', capsize=3, ms=10)\n",
    "        #plt.plot(time1, sep,'o-b')\n",
    "        #plt.savefig('sep.png',bbox='tight')\n",
    "        # do the pa plot\n",
    "        plt.figure(figsize=(10,10))\n",
    "        plt.tick_params(right=True, top=True,direction='in')\n",
    "        rc('xtick', labelsize=15) \n",
    "        rc('ytick', labelsize=15)\n",
    "        plt.xlabel('Epoch (yr)',fontsize=20)\n",
    "        plt.ylabel('Position Angle (Degree)',fontsize=20)\n",
    "        plt.ylim(min_pa, max_pa)\n",
    "        plt.errorbar(time1, pa_value, xerr=None,yerr=pa_error, fmt='-or', capsize=3, ms=10)\n",
    "        #plt.plot(time1, pa,'o-r')\n",
    "        #plt.savefig('pa.png',bbox='tight')\n",
    "        print(sep)\n",
    "        print(pa)\n",
    "    else:\n",
    "        print('The epochs of the coordinates most be equal for both sources. Check them.')\n",
    "        print(time1)\n",
    "        print(time2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.2758508314296745+/-0.03403017722690808, 0.3639748735389158+/-0.056139954390629264, 0.34062318359129157+/-0.0340755777968727, 0.25538017692041054+/-0.026442885683786197, 0.2990979290761723+/-0.02804184462621362, 0.23736408786091315+/-0.02519876041376327, 0.30714698171854693+/-0.019590027548743526, 0.28769944194217884+/-0.011844293650950978, 0.2955666730535078+/-0.0013818762396468809, 0.2924344315740842+/-0.0028668387251684986, 0.29746861703291905+/-0.002866897501671497, 0.2833941948911687+/-0.007476210833051629, 0.29748039500595985+/-0.010337094675369718, 0.2962794016858921+/-0.0005734617553630383]\n",
      "[77.4372416119113+/-5.1164993601975395, 80.51167998486187+/-4.013024876591297, 78.14089715380987+/-4.132985608565368, 87.53133297756224+/-7.152695964416268, 99.62327843347533+/-4.629263006880528, 92.1729725721523+/-7.434251729977014, 93.92043823972035+/-4.347857023961591, 83.61393757898733+/-2.7046496986709756, 86.12002305088271+/-0.3063381806777459, 88.43238901411958+/-0.5390834445792225, 89.42215668339273+/-0.5007945457703082, 91.01093729866895+/-1.6299673038180151, 89.22956259088967+/-2.246080504058014, 91.54726231293996+/-0.1297133821724267]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_in='/home/akdiaz/Documents/Trabajo/SVS13/Images/VLA/proper_motions/'\n",
    "file_A = data_in + 'pm-A-coord-err_rel.dat'\n",
    "file_B = data_in + 'pm-B-coord-err_rel.dat'\n",
    "plot_movements(file_A, file_B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eq for RA: 0.0005987800990965202*t+2.538137709793499\n",
      "eq for DEC: -0.009186172096178849*t+22.29720008517562\n",
      "eq for RA: 0.0006241789738361716*t+2.5099225057460672\n",
      "eq for DEC: -0.010789256173226411*t+25.52782804627961\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#gaia EDR3\n",
    "data_in='/home/akdiaz/Documents/Trabajo/SVS13/Images/VLA/proper_motions/'\n",
    "file_A = data_in + 'pm-A-all-final.dat'\n",
    "file_B = data_in + 'pm-B-all-final.dat'\n",
    "file_extra = data_in + 'pm-GAIA3&2MASS.dat'\n",
    "a1 = 9.982287690504483/15/1000\n",
    "b1= 3.77027 - a1*2016\n",
    "a2=-13.016093571446266/1000\n",
    "b2= 3.73927-a2*2016\n",
    "proper_motions([file_A, file_B],'-final-gaia3',['VLA 4A', 'VLA 4B'],['b','r','g'],31,file_extra,[a1,b1,a2,b2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eq for RA: 0.0005987800990965202*t+2.538137709793499\n",
      "eq for DEC: -0.009186172096178849*t+22.29720008517562\n",
      "eq for RA: 0.0006241789738361716*t+2.5099225057460672\n",
      "eq for DEC: -0.010789256173226411*t+25.52782804627961\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/AsHAMybOmSMCSAaaAIczlTfB2Crlh0K2K4SwoFGjjNWyeU3TOjrCU08VX0ymBAYG8uGHH7JmzRpiYmK4fv06M2fONPsfquzWrFmD1pqVK1ea/Idy1qxZBAcH55lsJSYmEhUVxa5du9i1a1eO8+vWrWPdunUsXLiQadOmWaTPvJw5c4YmTZrkuBl99+7dpKWl5VhgYW9vT6tWrZg7dy6HDx8mICCAHj165NuPqYQsL5GRkXh7e+d6Pn1KNLPsU3L29va0bt064/X169c5ffo0/v7+Zv9DP2fOHObMmcPTTz/NqlWrrLL/Wtu2bdm7dy/ffvttxnQoGCtMz5w5Q5cuXfJ8f0G/U9YWFhaGt7c3u3fvzrJQ5vPPPzdZv0qVKowaNYpRo0ahtWbGjBksWLCAnTt3MmzYMHbs2IFSigEDBuR4b0BAANWrVyc4OJgWLVrw9ddf88orr+DgYOtUqXBsHfVXGCtdM+sNvAL0BX4qbMNa6ySl1EFgGPCvTKeGA0e1rKAVokSYOhVCQ/NP8CZPLr6YTHnwwQdp3bo1H3/8MVevXkUpxdixYwvVVlpaGiEhIbRs2TLHqr10Fy5cICgoiO+++y7XLVjc3d3ZsmVLjvKoqCieffZZevfuTWBgIK1atSpSnxERESQnJ+d5/1xSUhKXLl2idu3apKamZiS+8fHxBN273zh7grdv3z46dOjAP//5T37//XcCAgIYOHAgr732Wq79gOmELL/6eXFxccm4p8scaWlpvPDCC6SmpjJz5sws55KTk4mIiMDNzY26detmlM+dO5egoCCeeuop1qxZU+BVvV27djXrPsjhw4czb948li5dmiXBW7lyJQkJCYwcOTLPWAvynSoO9vb2KKWyXHtKSgrz58/PUi81NZW4uLgs/3FRSmV859JXJW/fvp1OnTpRrVq1HH05OjoyZswYFi1axJw5cwCKtELe1mya4Gmto4FDmcuUUt73fvul1jr+Xlk4cFhrHZipXh/AHWh973X6/gXfaa1/vvf7N4BDSqmlwA6MpLEvRhIphCgBfH1h61ZjK5T0bVHSOToax9atttkiJbvAwECef/559uzZQ9euXfHNI6j9+/dz586dHOWenp54e3tz9erVPP/xGDJkCEFBQQQHB+ea4Dk6OubYugWMRREAvr6+Gec///zzQvdpzjYp58+fJyUlhaioKPr27Uu/fv2Ijo4mNDSU+Ph4wNhWpkaNGtSpU4fffvuNcePGcenSJezt7alduzYTJkxg8eLF+SZ4BU3IiiI+Pp527doxaNAgfHx8uHnzJhs3buTkyZO89dZbdOuWdYzi2rVrNG3aFH9/fw4dOgTABx98wOuvv07dunXp2bMnGzZsyPKeGjVq0KtXr4zXt2/fZvv2vLZ4zWrQoEG4u7sD0LJlSyZNmsT777/P4MGD6du3L5cuXeK9997D39+fESNG5BlrQb5TxWHo0KG8+uqr9OnTh8GDB3Pr1i02bNiQsfAiXVxcHDVr1mTAgAG0adOG6tWrExkZyUcffUTlypXp378/sbGxHDlyhAULFuTa37hx41i4cCEbN27E398/x+0GpUpuN+fZ6sDEIgvgChCSrd4VTC8ZH5Ot3kDgPJCEsRXLE7n1XRyLLFL8u1i3DyGszJpPspg0SesKFYwFFRUqGK9L0gMWYmJitIuLiwb02rVrTdZJvxk+t6Nx48Z66NChGtDnzp3Ls79GjRrpihUr6oSEhALFaeqG+KL0ac42KatWrdKA3rp1q+7YsaN2dnbW3t7eeunSpXr9+vXazc1Nt2nTRsfHx2uttX777bf1wIEDs7SxYMEC3bZt2wJdq7UlJSXp4cOHa29vb+3s7KwrV66sH330Uf3555+brJ/+2ftnWlCXvnggt8M/2+K7om4Dk5KSohctWqQbNWqknZycdK1atfTkyZN1XFxcvrHmprCLLEwtCgGybNOTztQii5SUFD1v3jzt6+urnZycdN26dfX06dMztjp5/fXXtdbGn9OMGTN027ZtdZUqVbSTk5OuV6+eHjt2rP7hhx+01lqHhoZqQP/00095xt69e/c8/47ndW2WVNRFFkqbMeRbXvj5+ekTJ05Yrf2kbl0Y0Oo83Ye9wiudXrFaP0JY06VLl2jatKmtwxAlzPPPP8/y5cuJj4/PdZuOzCZNmkRCQkLGkyC01jz88MP0798/x7SnEJYwaNAgIiMjM7bzyU3fvn05evQov/32W6GfL20J5vysVUqd1Fr7mTpn833wyhM7oGqyIzP2z+D1g6+bdT+FEEKUBqdPn6ZRo0ZmJXcAjRs3Zu/evURGRnL79m2mTZtGTEwMkyZNsnKkorx6+OGHmTdvXp51wsPD2bNnD0899ZRNkztLsPUii3LFUdsRdrEJro89ztwjc0lITmBBrwVWWUklhBDFRWvNuXPn6Nu3r9nvGTduHGfPnqVt27Y4OzvTo0cPDh06ZNbWG0IUxssvv5zruePHj2fcq+jk5FTqnplsiiR4xcwexcoBK3F1dGXR0UU42TvxVo+3bB2WEEIUWkREBHFxcQVaWenq6kpwcHCWJwcIYSsfffQRa9eupX79+qxfvz7PbXVKC0nwbMBO2bGszzI83TwZ3HSwrcMRQogiadCggdxyIkq1kJCQjI2tywq5B89GlFIEdQ2iVY1WaK3ZdH4TyamWfBSvEEIIIcorSfBKgKO/HuXJT55k2JZhJKUk2TocIYQQQpRykuCVAI/UeYRlfZax8787CdgUQEJygq1DEkIIIUQpJgleCfFcu+dY1X8VeyP20m9DP+KSzHj6uhBCCCGECZLglSCBDwaybvA6vrn6Dd9c/cbW4QghhBCilJJVtCXMiJYj6FKvC7Ur1AYgNS0Vezt7G0clhBBCiNJERvBKoPTkbtcPu2i3qh3X46/bOCIhhBBClCaS4JVgro6uXI6+jH+IP7/e+tXW4QghhBCilJAErwTr7tOdvaP2cj3+Op3XdCYyNtLWIQkhhBCiFJAErzhERMCzz8JXX8Hhw1ChgvE6IiLft3as25H9T+/nVtItOq/pLNO1QgghhMiXJHjWtns3tGoFq1ZBaqpRFhdnvG7VyjifD79afhwafYjRD4ymhnsNKwcshBBCiNJOVtFaU0QEDB0KCSY2Lk5ONo6hQ+HcOfD1zbOpljVa0rJGSwB+/PNHbiXd4qFaD1kjaiGEEEKUcjKCZ02LFxtJXF6Sk2HJErOb1FoT+Gkg3dd2l73yhLCyYcOGoZTizJkzudbRWuPj40OlSpVITEzk0KFDKKVYtGiR2f3Exsbi4uKCUop169YVKeaEhAR8fHxQSvHcc89lOZceW+bDxcWF+vXrM3bsWC5dulSkvsuqf/7znwwbNoz69eujlMLb2zvP+mlpaSxZsoQmTZrg4uJCnTp1mDp1Krdv3za7z/j4eObNm0fLli3x8PDA09OTRx55hJCQELTWRbwiy8aaWV7fv9Ju0qRJ3H///Rb9/K1JEjxrWrfOvAQvLMzsJpVSrB+8nhruNXg07FEORh4sYpBCiNwEBgYCsGbNmlzrHDx4kCtXrvDEE0/g6upaqH7Wr1/P3bt38fHxITg4uFBtpJs9ezbR0dF51nnyyScJCwsjLCyMZcuW0a9fPzZt2kT79u35+eefi9R/WfSPf/yDAwcO4OvrS+XKlfOtP3nyZKZMmUKzZs1YtmwZw4YN47333qN///6kpaXl+/60tDT69OnDa6+9Rtu2bVm8eDGzZs0iNTWVsWPHMmPGDEtclkVizc6c719ppLVm586dBAQEoJSydTjm0VrLce946KGHtEUppTXkf9jZFbjp3+N+180/aK5d3nTRu3/cbdm4hcjDxYsXrdNweLjWEydq7eFh/N3x8DBeh4dbpz8zpKam6jp16uiqVavqpKQkk3VGjRqlAf3tt99qrbU+ePCgBvTChQvN7qd169a6e/fu+t1339VKKR1eyGs+efKktre314sXL9aAnjRpUpbzecX27rvvakC/8847heq7LIuIiMj4ffPmzXW9evVyrXv+/HmtlNKDBw/OUv7ee+9pQK9fvz7f/r755hsN6JdeeilLeVJSkvbx8dEVK1bM8/3pf84HDx7Ms54lYs0sv+9faXb8+HEN6D179hS5rZSUFH379u1865nzsxY4oXPJaWQEz5ruu8+y9TLxus+LQ2MO0dSzKQu+XlBqhoyFMCnzYqS4OOO/PgVcjGQNdnZ2jBkzhj///JNPP/00x/lbt26xbds2WrRoQdu2bQvVx6lTpzhz5gyjR49m5MiRODo65jlimJvU1FTGjRtH7969GTx4cIHfX6tWLQCcnJxynIuIiODy5ctmtRMQEEDVqlVzlMfGxqKUYsqUKQWOzdbq169vdt2NGzeiteall17KUj5u3Djc3NzMmoK/desW8NefSTonJyc8PT1xd3c3Ox5rx5quqN+/kJAQlFLs37+fuXPnUq9ePVxdXWnfvj3Hjh0D4PDhw3Tq1Al3d3dq1qzJG2+8kaWNuLg4Zs2aRfv27fH09MTZ2ZkGDRowY8YMErLdC3/nzh2CgoJo3Lgxbm5uVKpUiZYtWzJ9+nST8W3fvp2KFSvSrVs3tm3bhlKKVatWmazbvHlzGjRogNY647r27dvHG2+8ga+vLy4uLmzevLnAn1FBySILaxo1yvgHKq9pWkdHeOqpQjXv6ebJgdEHUBj30qTpNOyU5OyilLHgYiRrGDt2LG+++SZr1qxh6NChWc5t2rSJhISEjKncwggODsbd3Z0hQ4bg7u5Ov379CA0NZe7cudjZmf/3ecmSJVy+fJlPPvkk37oJCQkZ02iJiYmcP3+emTNn4unpyZAhQ3LU79GjBz///LNZ/5E8c+YMbdq0yVF+6tQpAJPnCiotLY2YmBiz61epUqVAn2VRfPfdd9jZ2dGuXbss5S4uLrRu3Zrvvvsu3zbatWtHpUqVWLBgAd7e3rRv357ExERCQkI4efIky5cvz6hr6rO4efNmxq/Zp0szfxaWiDVdQb5/eZkxYwapqam8+OKL3L17l8WLF/PYY48RGhpKYGAg48ePZ+TIkWzevJnZs2fj4+PDqFGjALh27RqrVq1iyJAhjBgxAgcHBw4fPsyCBQs4ffo0e/bsyehn0qRJrF69mqeffprJkyeTmprKjz/+yIEDB0zGtX37dvr164ejoyMDBgzAy8uL4OBgnnnmmSz1jh07xsWLF3nrrbeyTOVOmzaN5ORkxo0bR4UKFWjcuHGRPiez5Da0Vx4Pi0/Rhodr7eaW9/Ssm5tFpqBu372tu4V008Gngi0QuBC5s/gU7cSJWjs65v33xNFRaxtO93Tv3l3b29vra9euZSnv0KGDdnJy0lFRURllBZmiTUxM1JUrV9ajR4/OKNuxY4cG9GeffWZ2fD/99JN2c3PT8+fP11prHRkZmecUramjWbNm+tKlSybbr1evnjb+uchbTEyMBvT06dNznFuwYIEG9Pnz582+rtykX5+5R2RkZJH7TJffFG2LFi109erVTZ4bNmyYBnKd7s/syJEjulGjRlmuw8PDQ2/fvj1LvaJ8FpaK1dzvX17WrFmjAd2mTZssfe7cuVMD2t7ePuM2CK2N6WovLy/doUOHLGV3797N0fasWbM0oI8fP55RVrlyZd2nTx+zYrt48aIG9JYtWzLKXn31VQ3oCxcuZKn7zDPPZPlZkX5djRo1MmtaNnu/+SGPKVoZwbMmX1/YutUYfUgfiUjn6GgcW7dabFTCyd6JwE8DSUhO4Ll2ZWv1kijDCrIY6f33iyembAIDAzlw4ABhYWG88sorAFy+fJljx44xdOhQPD09C9Xutm3biI2NZfTo0Rll/fr1o3r16qxevZo+ffqY1c7EiRPx8fExe/pz/PjxDBs2DDCmqi5evMjixYvp27cvBw8epF69elnqX7lyxax201cbP/jggznOnTp1CldXV5o0aWJWW3nx8vLiiy++KFD94pKQkICzs7PJcy4uLhl1TE2FZ3bffffRokULBgwYwCOPPEJMTAwffPABI0aMYOfOnfTq1Qsw/VmcPXuWadOmsWjRIh544IEs5zJ/FpaKtaDfv/zaytxf586dAejQoUOW2yCcnJxo164dX3/9dZaydCkpKcTFxZGamkrPnvPHU4sAACAASURBVD158803OX78eMZoZcWKFblw4QLnz5+nRYsWeca0Y8cOnJ2d6d27d0bZuHHjmD9/PsHBwSxevBiA27dv8/HHH9OnT58c0+sTJ07Ezc2toB9HkUiCZ219+hhTS0uWwPLlxmbHFSoY07KTJ1ssuXNzdGPnEzsZvnU4z+9+nsTkRKZ3NH0vgRAlSny8ZetZweDBg6lUqRJr1qzJSPBWr14NwN///vdCtxscHEy1atWoXbs24eHhGeW9evViy5YtREdH55s8rlu3jr1793LkyBEcHR3N6rdhw4b07Nkz4/Xjjz+Ov78/HTp04JVXXmHTpk2Fup7Tp08DuSd4rVq1wt7ePkv5559/zmuvvUZERAQpKSm0a9eOffv25dmPi4tLlviLKjU1laioqCxlrq6uVKxYscBtubm58b///c/kuTt37mTUycv333/PI488wpIlS/i///u/jPInn3ySFi1aMG7cOCIiIrC3tzf5WTg4GP+0P/TQQ3Tt2tWqsRbm+5eX7Pc7pq9a9vHxyVG3cuXK/Pnnn1nKPvzwQ5YvX86FCxdyrAKOjY3N+P3SpUt56qmnaNmyJfXr16dbt27079+f/v3755jO3759O7169eK+TPfL+/j40LNnT8LCwpg/fz6Ojo5s3ryZuLi4HNO2AI0aNTLzE7AcuWGrOPj6GiMPnTqBvz/cvGm8tvD9RM4OzmwZtoXhzYfz8r6XeefoOxZtXwirsOJiJEtxcXFhxIgR/Pe//+Wbb74hNTWVsLAwateuzaOPPlqoNiMjIzl48CBRUVE0atSIhg0bZhzp26bkd5N7UlISU6ZMoW/fvnh5eREeHk54eHjGVic3b94kPDycGzdu5BtP+/btqVixYq73IJnjzJkzeHh40LBhwyzlt27dIjw8PEfil5KSwhNPPMGMGTOIiYkhJiaGd97J/+dWamoq169fN/tITX+KUC6uXr1KzZo1sxwvvvhiwT8AjIUR0dHRJCUl5Th37do1PD098x0RW7JkCXfu3MkYZU3n5uZGv379+Pnnn80eVbVmrJb8/qXL/h+A/Moze+edd5g0aRI1a9bkX//6F7t27eKLL74gJCQEIEvCFxAQwJUrVwgLC6N79+7s37+fgQMH0rVrV+7evZtR79dff+XEiRMMHDgwR3/jx48nKioqYwFWcHAwXl5e9OvXL0fd4h69AxnBK3Mc7R1ZP3g9tTxq0bdhX1uHI0T+rLwYyVICAwP58MMPWbNmDTExMVy/fp2ZM2ea9Q+PKWvWrEFrzcqVK6lUqVKO87NmzSI4ODjHCsfMEhMTiYqKYteuXezatSvH+XXr1rFu3ToWLlzItGnT8o0pJSXF5D/25jpz5gxNmjTJsU/Y7t27SUtLy7HAwt7enlatWjF37lwOHz5MQEAAPXr0yLefq1evmhzRyU1kZGSemxObmubMPsVmrrZt27J3716+/fbbjOlFMEbEzpw5Q5cuXfJt49q1awAmE9OUlJQsvxZFUWO19PevqMLCwvD29mb37t1ZRuE+//xzk/WrVKnCqFGjGDVqFFprZsyYwYIFC9i5c2dGcr1jxw6UUgwYMCDH+wMCAqhevTrBwcG0aNGCr7/+mldeeSVjBNXWSkYUwqLs7ex55zHjf8Faa7Zd2sagpoNkha0omaZOhdDQ/BO8yZOLLyYTHnzwQVq3bs3HH3/M1atXUUoxduzYQrWVlpZGSEgILVu2NDmdA3DhwgWCgoL47rvvct2Cxd3dnS1btuQoj4qK4tlnn6V3794EBgbSqlWrfGP64osvuH37Nh07dsxxLiIiguTk5Dzvn0tKSuLSpUvUrl2b1NTUjMQ3Pj6eoKAgIOcK2n379tGhQwf++c9/8vvvvxMQEMDAgQN57bXX8ozV0vfgWXLKd/jw4cybN4+lS5dmSZpWrlxJQkICI0eOzChLTk4mIiICNzc36tatm1HerFkz9u7dS0hICC+//HJG+Y0bN9i5cyeVK1fGN48ZoK5du5q14rkgsZqK15LfP0uwt7dHKZXl2lNSUpg/f36WeqmpqcTFxWX5j5VSKuP7mXlV8vbt2+nUqRPVqlXL0Z+joyNjxoxh0aJFzJkzB6BIK+otTRK8Mm53+G6GbhlKYJtA/vX4v7C3K9xogxBWU8yLkYoiMDCQ559/nj179tC1a9c8/5Hdv39/xn1MmXl6euLt7c3Vq1fz/MdgyJAhBAUFERwcnGuC5+jomGPrFvhrUYSvr6/J86dOncqY/k1KSuLChQusXLkSR0dH3nzzzRz1zdkm5fz586SkpBAVFUXfvn3p168f0dHRhIaGEn/v/slNmzZRo0YN6tSpw2+//ca4ceO4dOkS9vb21K5dmwkTJrB48eJ8EzxL34OXn7CwsIxpx6ioKO7evZvxOdWrV4+nMo0ut2zZkkmTJvH+++8zePBg+vbty6VLl3jvvffw9/dnxIgRGXWvXbtG06ZN8ff359ChQxnlL730EmvXrmXGjBl8//33dOzYkZiYGFauXMnvv//OBx98kDFKdPv2bbZv3272tQwaNChjH72CxGoq3sJ+/6xl6NChvPrqq/Tp04fBgwdz69YtNmzYkOPewLi4OGrWrMmAAQNo06YN1atXJzIyko8++ojKlSvTv39/wLhn78iRIyxYsCDXPseNG8fChQvZuHEj/v7+OW5PsKnclteWx8Pi26Rk5+9vHMUoLS1Nv3bgNU0QesQnI/TdlJxLyIUoCKs+yWLSJK0rVDCe7lKhgvHahk+yyC4mJka7uLhoQK9du9Zknby2IgF048aN9dChQzWgz507l2d/jRo10hUrVtQJCQkFirMg26TY2dnpatWq6UGDBmXZhiIzc7ZJWbVqlQb01q1bdceOHbWzs7P29vbWS5cu1evXr9dubm66TZs2Oj4+Xmut9dtvv60HDhyYpY0FCxbotm3bFuhai4O/v3+uf57+Jn6mp6Sk6EWLFulGjRppJycnXatWLT158mQdFxeXpV76n5OpNsLDw/XTTz+t77//fu3g4KA9PDx0586d9SeffGKyDXOP7FvGmBtrfvGaqleYbVJMPX0DyLKVULrRo0dn+V6mpKToefPmaV9fX+3k5KTr1q2rp0+fnrHNyeuvv661NrZTmTFjhm7btq2uUqWKdnJy0vXq1dNjx47VP/zwQ0Z7oaGhGtA//fRTnrF37949158JeV1Xfoq6TYrSZgzjlhd+fn76xIkT1usgfTVTpv+pFZf5X83n1f2vMqjJIDYO2Yizg+ml8ULk59KlSzRt2tTWYYgS5vnnn2f58uXEx8fnuvVGZpMmTSIhISHjqR1aax5++GH69+/PzJkzrR2uEPkaNGgQkZGRGdv/5KZv374cPXqU3377rdDPozbFnJ+1SqmTWms/U+fkpqxyYkanGbzb+13+88N/+O4383cnF0IIc5w+fZpGjRqZldwBNG7cmL179xIZGcnt27eZNm0aMTExTJo0ycqRCmGehx9+mHnz5uVZJzw8nD179vDUU09ZNLmzBLkHrxx5of0L9G/UH5/KxuozrXWO1W5CCFFQWmvOnTtH377mr9wfN24cZ8+epW3btjg7O9OjRw8OHTpkckWxELaQeYFLdsePH8+4X9HJyalEPmNZRvDKmfTk7pOLn9A1tCs379y0cURCiNIuIiKCuLi4Aq2WdHV1JTg4mOjoaK5du8batWsLvTWJEMXto48+4u9//zu3bt1i/fr1eW7DYyuS4BW3iAjjiRYl4N7Hb65+Q4+1Pfgz4c/8KwshRC4aNGiA1pp//OMftg5FiGIREhJCWloa4eHhDB482NbhmCQJXnFKS4Pbt2HiRBgxAuLibBbKkGZD2DF8B+f/d55uod34I/4Pm8UihBBCCMuSBK842dlBy5Ywbx5s3gx+fsZzam2kX6N+7Bqxi4jYCPxD/GW6VgghhCgjJMErbkrBq6/CwYPGCF6PHsaono30qN+DPaP2MLTZUCo4V7BZHEIIIYSwHFlFaytdusCZM8YInru7cU/enTtgg2XWnep2olPdTgBc+N8FHO0daVS1UbHHIYQQQgjLkBE8W6peHdIft7NqFbRpA99/b7Nw0nQaI7aNoMuaLpz/33mbxSFKPtkgXQghrMcSP2MlwSspGjaEmzehfXtYvdomq2ztlB0fD/0Yezt7uoZ05dTvp4o9BlHy2dvbk5z5ebFCCCEsKjk5GXv7oj07XhK8kqJrVzh9Gh5+GAIDYcwYm9yb18SzCUfGHOE+p/voHtqdo1ePFnsMomTz8PDg1q1btg5DCCHKrFu3buHh4VGkNiTBK0m8vGDvXnj9dVi3Dr7+2iZh+Fbx5cjYI1Rzr8bbX79tkxhEyVWlShViY2OJjo7m7t27Ml0rhBAWoLXm7t27REdHExsbS5UqVYrUnpIfzn/x8/PTJ06csF4HXbsavx46lH/d8HBo0MD4/aVLYIOHu1+Pv46HkwfuTu7yWDORRVJSEjExMcTFxZGammrrcIQQokywt7fHw8ODKlWqmPVcZ6XUSa21n6lzsoq2OAQFwZw5f71OT5Ref904Z0p6cnf6NLRtC6NHw7Jl4OZmzUiz8LrPC4C4pDj6b+zP5A6TCWgSUGz9i5LL2dmZmjVrUrNmzUK3EXQoiDmH5+Qof93/dYK6BhUhOiGEEDKCl4nVR/AKIyXFSA7feguaN4ctW6BJk2IN4cadG/Re15sTv51g/eD1DG8xvFj7F2Vb15CuABwac8imcQghRGmT1wie3INX0jk4wBtvwOefw/XrxtMvNmwo1hAquVTii6e+oGPdjozYNoKQMyHF2r8QQgghCkYSvNLi0UeNjZEffBAiI4u9ew9nD3aP3E0Pnx6M3TmWtWfXFnsMQgghhDCP3INXmtx/Pxw4YDzTFuDIEWPlbaPieeqEm6Mbnz75Kc9/9jwd63Qslj6FEEIIUXAyglfaODgYCV5aGkyYAA89BJs2FVv3Lg4urBywEt8qvmit2fXDLtkmQwghhChhJMErrezsjD3zWrWCJ5+EiRONZ9kWo43nN/L4xsf5x/5/SJInhBBClCAlKsFTSt2vlIpXSmml1H351K2olFqjlIpVSt1USq1XSlXNVifkXlvZj+JdhmotdeoYe+q9/DIsX248BSM2tti6f6LFE0x4aALzv57PS5+/JEmeEEIIUUKUtHvwFgLxgLsZdT8GGgPPAGnA28AOoHO2epeBsdnKrhQpypLE0RHefhs6d4Z//xsqVSq2ru2UHR/1+whXB1eWHl9KYkoiyx9fjp0qUf9vEEIIIcqdEvMvsVKqM9AbWGRG3YeBx4DRWutPtNbbgVFAJ6VUz2zVb2utj2U7incuszg8/jj861/GJsrh4TB1KiQlWb1bpRTvPPYOMzvPJPRsKOf+OGf1PoUQQgiRtxKR4Cml7IFlwFwg2oy39AH+0FofSS/QWn8LRN47V77t3g3vvAOPPAIREVbvTinFm93f5PuJ39PaqzWATNcKIYQQNlQiEjzg/wAX4AMz6zfBmHrN7tK9c5k1U0rdUkolKaW+Ukr5FyHO0uH552HHDvjpJ2PfvE8+KZZuG1U1tmtZd24dAZsCuJNS9gZKhRBCiNLA5gnevYURbwBTtNbJZr6tMnDDRHnsvXPpTgNTgf7ASMAe+EIp1a7wEZcSAQHGc2ybNIGhQ+Hjj4ut69t3b/PvH/5N/439uX33drH1K4QQQghDSVhk8RZwXGv9WQHfZ2oOUGUu11q/m+WkUruAi8A/gIHZ3xwVFYWf31+PdBs/fjzjx48vYFgliLc3fPmlMV07YIBRprVxn54VTfCbgKujK2N3jqX3+t7sGrGLCs4VrNqnEEIIUR6sWLGCFStWpL/0zK2eTRM8pVRz4O9AF6VU+vJPt3u/VlRKpWqtE028NRaoZqK8EqZH9gDQWicqpT7DGNHLoVq1apw4ccLs+EsFJyeYMcP4fVwc9OplvB6YI7+1qKcfeBpXB1dGbBtBz7U9OTL2CC4OLlbtUwghhCjrMg8+KaVyXbdg6xG8hoAjcNTEuV+BYIxtULK7TM7tUMC4/26HGf2WzxUAt25BaioMGgSTJ8P8+UYCaCXDmg/DxcGF09dPS3InhBBCFCNb34P3FdAt2/H2vXN9MfbFM2U34KWU6pReoJTyA+rfO2eSUsoVY5XtySJHXhrdfz989ZWxCGPJEujSBX7+2apd9m/cn9n+swE4e/0sv8X9ZtX+hBBCCGHjETytdTRwKHOZUsr73m+/1FrH3ysLBw5rrQPvve+oUmoPsFYpNY2/Njr+Smu97957KgL/AdYB4Rjz1JOB+4G/WfXCSjJnZ3jvPSO5CwyEZ5+FXbus3m1yajKDPh6EnbJj/9P7qVepntX7FEIIIcorW4/gmcsBYwVsZk8Ah4HVwFqMUblBmc4nAVHALOAzYAXG/Xn+WusydqNdIQwdCidPwkcfGa9v3YJkcxcxF5yjvSMbh2zkz8Q/6bymMz/++aPV+hJCCCHKOyUb0v7Fz89Pl7lFFubQGvr3N55ju2mT8YxbKzlz/Qy9wnrhYOfA/qf306xaM6v1JUqHriFdATg05pBN4xBCiNJGKXVSa+1n6lxpGcET1qQUPPUUfP89tGkDnxV0xxrztfZqzeExhwGY/9V8q/UjhBBClGeS4AnD8OHGlG3t2tCvn7GVSkqKVbpqVq0ZRwOP8q/H/wXIY82EEEIIS5MET/ylYUM4ehTGj4ewMLiR65aCReZdyRtXR1du3LlBt9BuHPn5SP5vEkIIIYRZJMETWbm6wr/+BWfPgqenMYr3zTdW6y4xOZE/bv9B73W9+SLiC6v1I4QQQpQnkuAJ0zzvPf1k2TLo2BFmzrTKlG1Nj5ocHnOYhlUb8vjGx/n3f/9t8T6EEEKI8kYSPJG3CROM/fLmzYOePeE3y29UXN29OgdHH+SBGg8wePNgSfKEEEKIIpIErxgEBRkLVbMfQUG2jswMbm6wahWEhsJ33xmrbA8ftng3VVyrsO/pffyt+d94wOsBi7cvhBBClCeS4BWDoCBjqzl/f+PQ2jhKRYKX7umn4cQJY5Wth4dVuqjgXIH1g9dTt2Jd0nQa+3/ab5V+hBBCiLJOEjxhvqZNjSTvwQeN1x98ANevW6Wr5SeW0zOsJ0uPLbVK+0IIIURZJgmeKBiljF9/+QWmT4fWreHAAYt388yDzzCk6RAm75nMvC/nWbx9IYQQoiyTBE8UTt268O23ULmysfhizhxITbVY8072TmwauomRLUcy88BMZh2YJRsiCyGEEGaSBE8UXosWxsKLkSONGwqHDjVuLrQQBzsHQgeG8kybZ1h8dDHhMeEWa1sIIYQoyxxsHYAo5e67D9auha5djRW36VO4FmJvZ8+K/iuY/PBkGlZtCBiPNlMW7kcIIYQoS2QETxSdUsZeeU8+abwODoa33oK0NAs1r2hWrRkAq06tYuzOsaSkWec5uUIIIURZIAmesLyjR2HWLOjTB6KiLNr0H/F/EHo2lBGfjOBu6l2Lti2EEEKUFZLgCctbudJ4nu3hw8Yq2y+/tFjTM7vMZPGji9lycQtDNg/hTsodi7UthBBClBWS4AnLUwrGj4djx4z78rp3h59+sljzUx6ewod9P+Q/P/yHARsHyHStEEIIkY0sshDW07o1nDwJ//kP1K9vlCUng6NjkZue2HYibo5u/B7/Ow528jUWQgghMpMRPGFdFSrAiBHG77/5Bho3hq+/tkjTo1uPZkanGQCc/v00sYmxpiuW6ocB31MWrkEIIUSxkQRPFB9XVyMp8feHhQsttso2ITmBPuv70H1td6Jum1jUURYeBlwWrkEIIUSxkQRPFJ82beDUKRg4EF5+GQICICamyM26OboROjCUy9GX8Q/x5/e43y0QrBBCCFF6SYInilfFirBlCyxbBnv3QmioRZp9rMFjfD7yc365+QtdQrrwy81fLNKuEEIIURpJgieKn1Lw3HNw+jS8+KJRFhlZ5Mec+Xv7s+/pfUTdjmLB1wssEKgQQghROsnyw2J28yZcvQp16tg6khKgmfF0CqKioF076NgR1qyBypUL3WSH2h049swx6leub6EghRBCiNJHRvCKkdbw3/8aec0HH1hsjUHp5+kJM2fCrl3GfXrffluk5pp4NsHJ3onohGh6rO3B2etnLRSoEEIIUTpIgleMlIKWLeHhh40Zys6d4eJFW0dVAigFL70EX31lZMGdOsG77xZ5yvbGnRv88OcPdAvtxrfXipY0CiGEEKWJJHjFICICnn3WyF++/dZ4wEP37nDhgjFgdeGCrSMsIdq3N+7L693b+LCKqEGVBnw59ksquVSi59qefFXxpgWCFEIIIUo+SfCsbPduaNUKVq2C1FSjLC7OeDzr3bvw1FN/3YoWHW27OEuMKlVg505Yu9YY2QsPhxMnCt2cdyVvvhz7JbU8avHYA+c4UvGGBYMVQgghSiZJ8KwoIgKGDoWEBOMJXZklJ0NiImzcaDymNTISfHzghReMBLBcU8rYFBlg6lRj8cX77xd6yvb+CvdzeMxhHoupQsNEVwsGKoQQQpRMkuBZ0eLFORO77JKTYckSY53BmDFGHtOihTHyJ4DVq6FXL3j+eRg+3FiGXAg17qvBtvPNqXnXmZS0FL7+xTKPSxNCCCFKIknwrGjdOvMSvLAw8PAw9v796itwd4e+fWHUKFlpS9Wq8Omn8PbbsG0bPPSQMTRaBAu/XkiXkC6sO7fOQkEKIYQQJYskeFYUH1/weo88YqwzCAoyRvXs5E/I+BBefhkOHYJGjaBWrSI190L7F+jq3ZWntz/NipMrLBOjEEIIUYJI+mBF991XuHrOzvD667B0qfH6+HHo08e4T69c69QJPvvMuD8vLg6mTYNbtwrcjLuTO/958j/0adiHCf+ZwLvH3rVCsEIIIYTtSIJnRaNGgaNj3nUcHY2VtHn5+Wdj6rZFC+N+vfTVuOXaoUNGBuznB2cLvpGxq6Mr24dvZ3DTwcw8MJPf4n6zfIxCCCGEjUiCZ0VTp5qX4E2enHedv/3N2BC5WzeYMsXYKPncOcvFWSr17w8HD8Lt28b+eStWFHiVrZO9Ex8P/ZijgUep5VG0aV8hhBCiJJEEz4p8fWHrVnBzy5noOToa5Vu3GvXyU6cO/PvfxrYqV64YM5XlXufOxg2L/v4wYQLMm1fgJhzsHGhZoyUA73/7PlP3TEUX8QkaQgghhK1JgmdlffoYo23jx4O9vVFWoYLx+tw547y5lIInnoBLl4zRQYA9e+DIEcvHXWpUr27sKfP223/NdRcyQfvxzx9559g7PLvrWdJ0eV++LIQQojRzsHUA5YGvr7G/3fnzxutDh4rWXtWqxq9aw9y58M03xgDW229DxYpFa7tUSl9lC8a+Mk88AY89Bn//u5EVm2lp76W4Orry9tdvk5iSSPCAYOzt7K0UtBBCCGE9MoJXiikFe/cao3krVxqPPNuxw9ZR2djt2xATA888A6NHG6/NpJTinz3+yZyucwg9G8rIbSNlulYIIUSpJAleKefuDosWGVupeHrCoEHlfMrWw8OYt54zx9hpum1bYwr32WeNpciHDxtz5M8+a3LDZKUUs/1ns7DXQjrU7oAqwAigVUVEmH0NQgghhJIRir/4+fnpE0V4sH1+unY1fi3qFG1ukpPhk0+MJ3opZUwJN29eoFnKsuXAARgyxHi8mYND1seKODoax9at+d4Iefr30zT2bIybo5uVA87F7t3GQ42Tkwt9DSVZ15CuABwac8imcQghRGmjlDqptfYzdU5G8MoQR0fj9jOl4OpVaNcOevSA8HBbR2Yj9epBUpJxs2L2Z8YlJ0NCgpE45TEKFpMYQ7fQbvRd35e4pDgrB2xCRIQRY0JCoa9BCCFE+SMJXhl1//3w3ntw6hS0bGkswEhJsXVUxWzx4vwvOjnZ2D06F1Vcq/BRv4/46peveHTdo9y4c8PCQeZj8WLzHmicxzUIIYQofyTBK6Ps7Ix1BhcvQt++MGOGsR/wnTu2jqwYrVtnXnIUFpZnlSdbPsmWYVs4+dtJuod2Jzoh2oJB5sNC1yCEEKJ8kQSvjKtVy7gv75NP4PHHwcXFKC8XjzuLj7dYvUFNB/Hpk59yKfoS7xx9p4iBFYAFr0EIIUT5IQleOTF4sLGwFODYMWja1FiDUKbdd59F6/Vu0JujgUeZ03VOEYIqIAtfgxBCiPJBErxyKH3hdI8eEBgIsbG2jcdqRo0y72HATz0FJ0+a1WRrr9Y42jtyPf46j4Y9SkSMlRc3FOQahBBCiHskwSuHHn4Yzp6FV1+F0FBjNG/bNltHZQVTp5qXHD30EPj5wcSJZt+k+Ef8H5z6/RRdQrpwOfqyBYLNhbnXMHmy9WIQQghR6kiCV065usK8eXDiBNSuXUa3UvH1NfaIc3PLmSQ5OhrlW7cao2SvvALLl0OHDvDjj/k2/YDXAxwac4jUtFT8Q/w598c5216Dr691+hdCCFEqSYJXzrVubdyTN2WK8XrHDvjwQ+ORrmVCnz5w7hyMHw/2954rW6GC8frcOeO8oyPMnw//+Y+xgeBDDxlJUz5aVG/B4TGHcbRzpFtoN85cP2O7axBCCCEycbB1AML2HDJ9C7ZuhfXrYcMG4/m2TZvaLi6L8fWF9983Hu0BuT9KpF8/OH3a2C06Kcmspht7NubLsV/y3O7nuN/jfsvEa4q51yCEEEJQwkbwlFL3K6XilVJaKZXnskClVEWl1BqlVKxS6qZSar1SqqqJegFKqe+VUneUUheVUsOtdwWlX1gYhIQY++e1bg1vvAF379o6qmJUty58+SWMHGm83r4936dE+FT2YdeIXVRzr8bd1Luc/M28BRtCCCGEtZSoBA9YCJi7odfHQFfgGWAM0BbYkbmCUqoT8AlwEOgD7AI2KqUetUy4ZY9SMHo0XLpkbK0ye7bxKNRyJX0aNDERnnsOHnzQ2EjQDK8deI2Oqzvy2Y+fWTFAIYQQoZjR6AAAIABJREFUIm8lJsFTSnUGegOLzKj7MPAYMFpr/YnWejswCuiklOqZqeprwBGt9Qta64Na6+nA58Bsy19B2VKjBmzcCEePwoABRtnBg+VsP11XV/j6a2jSxHje6wsv5Dt1+3LHl2levTkDNw1k26WyuDRZCCFEaVAiEjyllD2wDJgLmPMcqD7AH1rrI+kFWutvgch751BKOQPdgM3Z3rsJeFgpVdECoZd5HToYo3qxsdC/PzRvDp9/buuoipG3tzFl+9JLsGwZdO6cZ5JX1a0q+5/ej18tP/625W9s+H5D8cUqhBBC3FMiEjzg/wAX4AMz6zcBTG0+duneOQBfwNFEvUsY192o4GGWX5Urw5494O5uLNocNQqii/GRrDbl5ARLlhj34z3+ODg751m9kksl9j61l871OvPcZ89x486NYgpUCCGEMNg8wbu3MOINYIrWOp+nqmeoDJj6VzP23jky/Zq9Xmy288JMHTsai0xffx02b4ZmzeBGecpdBg40bkoE+OYbY2+ZXFag3Od0H5+N+IxDYw5RyaVSMQYphBBClIAED3gLOK61Luhd6dpEmTJRnv21yu39UVFR+Pn5ZRwrVqwoYEimBQUZ05yHDxuHUsYRFGSR5ouVs7MR9+nTMHMmVLqXu9y8adOwit+BA8aoXufOcOWKySqujq60qtEKgIVfL+Ttr94uxgCFEEKURStWrMjIUwDP3OrZdB88pVRz4O9AF6VU+jCH271fKyqlUrXWiSbeGgtUM1Feib9G7GIzlWWvAyZGAKtVq8aJEyfMDd9sQUGlM5nLS/PmxgHGQozHHjO2VHnuub8WoZZps2YZiy8CA6FNG+OZb+mrUbLRWnP6+mk2nt9IYkoir/u/jlLKZF0hhBAiL+PHj2f8+PEAKKVyvVnK1iN4DTHukzuKkZDF8td9eL9iLLww5TJ/3WuXWeZ78yKAZBP1mgBpwA+Fjlpkcf/9xkDWSy/BI4/A99/bOqJiMnQonDoF9etDQADs22eymlKKsEFhjG09ljmH5/DKvlfQ2tQAtBBCCGEZtk7wvsJY6Zr5SJ/H6ouxL54puwGve/vcAaCU8gPq3zuH1joJY/+7YdneOxw4qrUub5OKVlO3rvGUrw0b4KefjG3j3nrL1lEVE19fYyuVZcuge3ejLDU1RzV7O3tWDVjFs37PsvCbhbz4+YvFHKgQQojyxKZTtFrraOBQ5jKllPe9336ptY6/VxYOHNZaB95731Gl1B5grVJqGsaI3NvAV1rrzMMobwCHlFJLMTZB7nvv6G2tayqvlIInn4RevWDqVGPhabnh4mLMTQNcuwY9esDixcajzzKxU3a83/d93J3caVClgQ0CFUIIUV7YegTPXA5A9ju7ngAOA6uBtcBJYFDmClrrr4ChQE9gDzAAGKG13mvtgMsrT0/jdrRp04zXW7fCxInlaBFGUpKxQfLjj8Mrr0By1oXhSikW9FrA+IeM+yfOXD9Dcqq5i8eFEEII85S4BE9rHaK1Vumjd/fKvLXWY7LVu6G1Hqu1rqS1rqC1HnFvRDB7ezu01i201s5a6yZa603FcBnlXvoagsuXYcUKY0HGzp22jalY1K9vrDqZMAEWLIBu3f6fvTuPs7l8Gzj+uc7MMLaxZCtLWbIba7YwtkLWQpI9UmmhpH4lNUooaVU8liwJiYSEZBmEQpZCZBKKZN+HWe7nj/sM05jlnJlzzmzX+/U6r5k53/t8v9d4+nku93Jd8NdfCQ796/xfNJjagK7zu3I1KukOGUoppZQ70l2CpzKXV16x+U6BAraMXJcu8M8/aR2VlwUGwsSJdlPizp2JHqEuHlScMS3GsPC3hXT8oiNXIhM6MJ55hZ8OZ+DSgWw4vIGwQ2EEjQ5i4NKBhJ8OT+vQlFIqw9MET3ldnTqwbZs9eLFkCaxbl/xnMoVu3WDrVrsfD+D4cYiK+s+QZ+o+w+R2k1lxYAVtZrfh4rWs0ex32e/LCJ4YzJSfpxBt7KGUC9cuMOXnKQRPDGbZ78vSOEKllMrYNMFTPhEQAC+/DL//bmfxwO7PO3AgbePyuvLlIW9euxevdWt7AOPo0f8M6V+zP5/d/xnrDq3jky2fpFGgvhN+OpzOX3bmcuRlImP+u/8wMiaSy5GX6fxlZ53JU0qpVNAET/lUiRJ2f15EBDzzDFStareqxZvYynwCAmxrs61boXp1WLnyP5e7B3dnwyMbGFJ/SBoF6DvjNo1L9mBJZHQk721+z0cRKaVU5qMJnkoTgYE212nVyh42rVPH1gzO1Hr0sL904cK29cerr/6nZl694vXwc/hx5NwR2s1pxz8XfbhZMbafXvyXF1qwzNo166aZu/giYyL5bNdnHn+2UkplFZrgqTRz222wcCEsWADHjkG9enDkiBcelJ6aAVesCD/9BH36wNdfw7VrNw05ePYgqw+uJmR6CH+dd57A9fbvEBoKxkBIiH0ZY19e+DNydZ9hVtmPqJRS3iDaMumG2rVrG2/0olXJO3MGli+35xLA7s0rm9lrAZ8/D0FBcOECbN8OjRtfv/TD4R9o/XlrCuYsyKpeqyiVv5RvYmrSxH5du9ZrjwgaHcSFaxeSH5c9iHP/yyoFFJVSyn0iss0YUzuhazqDp9KF/PlvJHc//mjPJvTrZxO/TCsoyH4dOdImViNGXF+yvbvk3azqtYqzEWdpNK0RB05nntMoPYJ7EOAISHJMgCOAnsE9fRSRUkplPprgqXQnOBiGDrUdMSpWtKdtM/VE8/Dhdn9eaKjdm3f8OAB3FbuLtX3WUqVwFW7JcUvaxuhBQ+oPIcAvmQTPL4Bn6z3ro4iUUirz0QRPpTs5csCYMbBlCxQrZsuqPPxwJk7ycue22ezUqfDDD/aU7Y8/AhBcJJjlPZaTP0d+IqIi2HNiTxoHm3plCpRhfpf55AzIedNMXoAjgJwBOZnfZT5lCpRJowiVUirj0wRPpVs1atg8Z+xYqF/fnikwBmJi0joyLxCBRx6xBzBKl4Zbb71pyODlg2kwtQGbjmxKgwA9q/Wdrdn1+C4G1BqAn9g200HZgxhQawC7Ht9F6ztbp3GESimVsekhizj0kEX6N28efPQRTJ4MFSqkdTReYoxN+GJi7P68xx+HwoU5fO4wzWc259iFYyzptoSmpZp6/tk+OGRx0yOn22eu7eO7ZyqlVGaghyxUprJ7N1SrZnOfBKqMZHwi9usvv8CoUXYqc906SuYtybo+67g93+3cN/s+lh9YnrZxKqWUSrc0wVMZyoMPwt69cP/99mxCrVp2VTNTqlbNrlHnygVNm8Lo0dyaqwhhfcKoULACjyx6hCuRV9I6SqWUUumQJngqwylSBObOhUWLbBmVP/9M64i8qFo12/2iSxfbzLd/fwrmLMia3mtY3mM5OQJyeOQx1xtZhK21rzSsBa2UUir1/NM6AKVSqn17aN4ccua0P0+dak/dtmqVtnF5XFAQzJlj98dVrAhAvsB85AvMB8DrYa9TIqgEfWv0TfEjQkPta0e+JgBUP7s2VSErpZRKW5rgqQwtVy77NToaPvnE9rPt0QPeew8KFkzb2DxKxB62iPXaa5AzJ1FDnuWHIz/wXfh3XIm6wsC7BqZdjEoppdINXaJVmYKfny0hN3y4Xb6tWBE+/zyT1s6LiYF9++B//8O/4wMsvnca7cu358lvn+Sdje+kdXRKKaXSAbcTPBHJJiK3iUh+bwSkVEoFBsLrr9tZvDJloGdPe+I203E47JLt+PGwciXZa9djfonnebDygwxdOZSR60amdYTXXd/bF++le/uUUsq7kl2iFZE8wEPAPUBjoFCca1HALmA18JUx5kcvxamUy6pWtbN569dDlSr2vbVroVEjO9OXKYjAk09CvXrQpQsBLVsz++Af5ArIRcm8JdM6uuti9/alQXk9pZTK0hJN8ESkGDAc6A44dzpxFtgHnAZyALcA1YFawPMisgN4xxgzx5tBK5UcP78bScUvv0CzZlCnDkyZciPpyxRq1bJTlps24VeoMJ92+BSu2NIpu47vokrhKjhEd2IopVRWk+Df/CIyApvI9QPWA32AO40xBYwxlYwxDY0xtYwxdwB5gWbA29jZvc9FZLOIBPviF1AqOVWqwKxZEB4ONWvCq6/C1atpHZUH5csHrZ2tvebNg4oV2bdqHndNvosBSwYQHROdtvEppZTyucT+aT8UmASUNMbcZ4yZaYwJT2igMeayMWatMeYl4HagAxAAdPRKxEq5SQQeftgWSH7oIXjjDbj7bnvyNtO54w4AyrXuzov+TZi6fSq9vu5FVExU2sallFLKpxJL8MoaY54zxhxz52bGWmKMqYVNEJVKNwoWhJkzYflyGDjQLuMaA5cupXVkHlSnDmzfjtzXhtdf+o7RRysx+5fZdJ3flWvRmbGvW/L0oIdSKitKMMEzxhxN7Y2NMf+k9h5KeUPLlvDII/b7efOgfHlYsiRtY/Ko/Plh4UJ4913+9+l+PijSh6/2fsW07dPSOrI0ERpqE/mQEPsyxr40wVNKZWa6+1plaaVL23yofXvo2hWOH0/riDxEBJ59Fvbt45nHp7G291oeDWyQSQsDKqWUis+lBE9EHheRcBG5LZHrxZzX+3k2PKW86667YNs2GDkSvv7aFkj+4ou0jsqDSpcGICSqGI7ad3Gwexu6zn6AcxHn0jgwpZRS3uTqDN7DwLHElm6NMX8DfwE9PBWYUr6SLRsMGwY7d0LlypmoVl5cpUvDG2/w6/YVfLVvIS0mNuD0ldNpHZVSSikvcTXBKw/sTGbMLqBC6sJRKu1UqABhYdCpk/35gw9g7FiIygwHUB0OGDqUdlPWsXBlAX45tYcm46py/KJzTTo8HAYOpOq5DVQ7FwZBQfYkSniCh+eVUkqlc64meHmxRY6Tch7Q9mUqQ3M47PY1Y2DzZnjhBahbF7ZvT+vIPOTuu2m7eB/f7K9NeNS/hEwP4dSCWRAcDFOm4Ec0AnDhgq0KHRwMy5alddRKKaXc5GqCdwxIrnBxMHAideEolT6IwOzZ8OWX8Pffdq/e//53vUlExlawIC3m/MjyXiupE3ELBXo8CpcvQ2Tkf8dFRtr3O3fWmTyllMpgXE3w1gCtRKRhQhdFpBHQGljlqcCU8pSU1kETsbnN3r3Qp49drv3lFx8E7AsOB41KN2FGeDASEZH02MhIeO89n4SllFLKM1xN8N4CrgHfi8i7InKviFR2fn0PWAlcdY5TKl1JbR20/PntauW+fbaOMNjZvTNnvBWx78jnnyc/KDISPvvM+8EopZTyGJcSPGPMPuBBbBI3GFiGPVSxDBgERABdjDF7vRSnUmmubFn79cgRO6NXsSLMn5/BS8tdvOjZcUoppdIFlwsdG2OWAqWxfWoXYJdjFwDPA2WMMd96JUKl0pkSJewBjNtugy5d4P777T69DCl3bs+OU0oplS74uzPYGHMKGOelWJTKMGrWhJ9+slvTXn3VHsL44w8IDEzryNzUo4ddf45/wCKugADo2dN3MSmllEo1bVWmVAr5+8PQofbgxUcf2eTOGLuEm2EMGWITuKRERUGbNr6JRymllEe4nOCJiENEnhaRzSJyTkSi4lyrISKfiEg574SpVPpVtuyN4sjz5sGdd8KoUUlPiqUbZcrYjYQ5c96U6JmAAK5l82NTuRz2F5w+PW1iVEop5TZXe9Fmw56UfR8oA1wAWw/V6SDwCNDd0wEqlZGEhED79rb1Wa1asGVLWkfkgtatYdcuGDCAaPwwAEFBRPd7hIdeq0zj7tf4ol0p6NsXJkxw69bOBhls2GC7hGiDDKWU8g1XZ/CGAk2BEUARYErci8aYs8A6oKVHo1Mqgyla1M7iff01nDoF9erBm2+mdVQuKFMGxo/nl7wN2Zk3BM6dw3/CRKYPWU/94vV5uPJvzBjzEDz8sB3vwtHhZcuuN8ggOtq+pw0ylFLKN1xN8LoDPxhjXjfGxAAJ/e1+ECjpsciUysA6dIA9e+Cxx2yPW8iY5VSCsgexrPsympdqTp+IuUz8fQ5ERNipyiRq44WH2yLR2iBDKaXShqsJXilgczJjTgMFUheOUplH3rzwySc39ue99Rb06gUnT6ZtXO7KlS0Xi7stpmOFjhTIUcDWxBOxv0z//gn2bxs3Lvk9iNogQymlvMfVBO8KkC+ZMSWBs6kLR6nMKzoa5syxBZJnz05fM3qxe+UanltKzXOrb9orF+gfyFcPfsWDlR+EggXZ+8V4zLCXYepUqFvXtvmIY9Ys1xI8bZChlFLe4WqCtwO413nY4iYikhe7/+4nTwWmVGYzbBj8/DOULg3du9vKI4cPu/bZlPbTdUXcvXKXyIXBkeBeORF7rmrb0W0ET67JsKYGs2wZHDtmD2DEyVi1QYZSSqUtVxO8yUAJ4HMRCYp7QUTyAdOB/MBEj0anVCZTtSps3GiXJjdsgKNHXftcavvpJiYle+Vq3FqDfjX6MXrDaAabZZjt22HmTJtxXroEV65ogwyllEpjrvainQNMAzoBJ4AnAERkK3AM6AB8ou3KlEqenx8MHmwLIterZ997/33Yvdv3saRkr5xDHExoM4HBdQfz4U8f8tj214kuXcpefPxxqF+fHm3PJls/WRtkKKWU97jTi7YfttbdHqAQtg5eTeAA0M8Y87RXIlQqk8qb1349c8YWRq5Rw87IXb3quxhSuldORHi35bsMazSMyT9P5ss9X9oL3brBkSMMWdSYAEfUzTeLIyAAnn02FcErpZRKlFutyowx040xNYDcQHEgjzGmqjFmmleiUyoLyJ/fzt517QojRthEb+NG3zw7NXvlRISRzUayvPtyulbuat+87z7YsYMy1XIz/2o7cvpfJSDgv6dJAgJs44z58235vYzCm/sglVLK01LUi9YYc8UYc9QYc8nTASmVFRUqZGfJli2z29hatrQze97mib1yLcu2RETYf2o/jyx6hIhbC0FYGK2fr8Ku3HczoNtF/Pzs2KAgGDDANs5o3Tr18fuSt/ZBKqWUN7jaqiy/iFQSkezx3u8rIotEZLaI1PFOiEplHa1a2dm8xYvtzJ4xsGmT957Xo8dNLWhv4upeuc1/bWbajmm0m9OOS+YajB1Lmd+XM35GHhrdHcMz1cI4dw7Gj89YM3dKKZURuTqDNwr4Me54EXka27KsHfAQsFZEKnk8QqWymNy5oWlT+/2iRdCgATz0EBw/7vlnDRniWoLnyl65XtV6Mb3DdFYfXE2rz1tx/up5KFgQgJbHZ/LBzibw9NO+3WSolFJZlKsJ3t3AKmNM3JL1zwN/A42BB53vPefOw0Wks4hsFJFTIhIhIvtE5JXE6u3F+VxlEflORC6LyEkRmSAiueONmS4iJoFXBXdiVBlfRm54f9998PrrsHChLZD8zz+eLZBcpozdC5cz582JXkr2yvWu3ps5neaw+a/NtJjZgjNX7Drz94Uf5oviz9npu4YN4Y8/PPdLKKWUuomrCV4xbK9ZAJwzdSWAj4wxG4wx84El2GTPHbcAa4D+QGvgU2AY8G5iH3AWVV4N5AC6YhPNTsCsBIb/BtSP9/rTzRhVBpbRG95nywbDh8OOHVCpkm0Y8dtvnn1G69Z2T9yAAZCLiwgxqdor92DlB1nw4ALyBeYjm5/9t1qUIxsTyoyzmervv0PNmvDNN579RZRSSl3n7+K4HEBEnJ/vBgzwfZz3woG27jzcGPN/8d5a4yyk/KSIPG1MgnMVA53xtDPGnAUQkdPAIhGpbYzZGmfsJWNMcj10VSYVt4hvfJGR9tW5s01i0vuesIoVYd06qFDBJn0AUc4qJP6u/q84CWXK2Mm1/rPs/4Srn12bqvu1L9+eduXaISJcuHqBq9kukv3ardCxI2zfDg8/DHnypD5wpZRSCXJ1Bu9vIO7SZkvgPLAzznv5sT1rU+sUkNQSbXVga2xy5/QdNuFs44Hnq0wiszW8dzjgttuub2vjnXegfn3YuTPpz6WV2NZm3RZ0Y0eNRkRkP2QvlCpl68CEhADQJuwYRU9GJHYbpZRSKeBqgrcGuE9EnhKR/kB7YLkxJibOmLLAkZQEISJ+IpJTRBoCzwATEpm9AwgErsV7LwqIASrGe7+SiJwXkasiskFEQlISn8qYMnvD+zvvtL1sa9WCl1+GK57455UXDG88nKiAU+yo2ZgDpw/YN53JH6dO8fi8P5j82jZ7okQppZRHuJrgjQYuAh8Ak7DLtaGxF0WkMBACpLQ86yXnaz0QBgxNYuwBoJqIxN0SXgvwAwrEeW87MAR7yre78/rKpMq5nDhxgtq1a19/TZo0KUW/jEofMnvD+06dYO9e6N0bRo+GatVgczrckFC3eF2Cd6wm2nGJxtMas+fEnhsXb7mFx16rydFCgXb5dsiQ5LNyN2XkQzZKKRXfpEmTrucpQMHExkniE2XxBooUBTo7f1xsjDkc59pdwMPAbGPMFneDFZGaQE6gDvCq8z4DExlbAfgVW6IlFHtQYyZQDVhpjElwS7iI5MC2WdtpjOmY0JjatWubrVu3JnRJZUBBQfZAhSvjzp3zfjye0KSJ/bp27X/fX7UKnnjCzlrWSUVFyh357ANSuwcvviZN4FLO3fzVvAW35r6VbQO2XV/CbTK9CQGRMazcGQwff2yXblevtmvSqbRsGXTucM3uuYyz8yOAawQEwPxF2dw+RJLY/w2UUsrXRGSbMaZ2Qtdc3p5tjPkHGJ/ItS2A24ldnM//7Px2g4icBGaIyDhjzE3/xjbG/CYiA4D3gMewS7OTsHvwEq0UZoy5IiLfYmf0VBbQo4c9LZvUhFBmaXjfvLmdzYvtGDF8OFSvbmf50otclyuzrs86YkzM9eQuVmSAw57yCAmx2bYHkrvrh2wib97SG0m2DHXIRiml3OVqJ4scIlIysfp0IpLNeT3QAzHFJnulEhtgjPkUKAIEA7cBT2H3ALqyQOXBKmIqPfNkEd+MIDa5i4iAb7+1ycsDD8DRo2kbV1x33nIn5QuWxxjDiytfZN2hdf8d0KUL9O9vv//yS3jhhRQv2Wa2QzZKKeUOV/+Z/CqwD0isI2VubM25lz0Q093OrweTGmSMiTDG/GKMOQ70wP4u8xIb71yibQ1s80CMKgPwdBHfjCIw0O7FGzPGLlFWrAiTJkFMTPKf9ZVzV8+xeP9iWs1qxekrpxMetGULjB1r10SPuH9+K7MfslFKqaS4muC1Br43xiT4N7Hz/e9xsw6eiCwXkedFpLWI3CsiI4BxwBexy7MickBEpsb5TJCIvCUibUSkpYiMwe7HeyY2PhHJKyLrReQxEWkuIl2xJ4GLYduuqSwibhHfzNDw3lUBAfDii/Z3rFnTzlKmp5m8fIH5COsTxp233Mmv//7Kycsnbx709tswZ479JWrUcLsqdWY/ZKOUUklxNcG7A9ifzJj9znHu2AL0Ab7Ezr61A14C4u6K8seegI0VDdQAPgO+BpoDXYwx0+OMuQqcAF4BvsXu0TsLhMQrhKyygNgivg0b3tjilVUa3t95pz2v8NNPULy4bXM2Z04CM1uhoSBC9XNhVD8XZsuYiNj3vaRwrsKs6b2G3Nlys+fEHr7c/eXNgx56CLZtg2LFbN+2HTtcvn/uxNYbUjhOKaUyElcPWQRgDzMkxWBr1LnMGDMcGJ7MmDvi/XwJuDeZz0QAD7gTi1KZlQhUrmy/X7fONpEYMwamToXasWevQkMhNNTnJ0QL5ChAcJFgdv+7m0D/RP76KFfOrjkvWGBPjgBcu3ajpUcistIhG6WUis/VGbw/sHXuktIEOJSqaJRSCfJULbeQENsO9uRJqFsXnn8eLl3yTsyu8nf4E1wkmHbl7QH368WQ48qRw2ZsYFt3lC0LK1Yked+sdshGKaXicjXBWwzUEpEXErooIv8DamKXTJVSHrRsGQQH29mo6Gj73oUL9ufgYLe3ptGxI+zZY/chjhsHLVvapdu0FFs2JezPMCqMr8AHmz9IfHBgIOTNazdQvvLKjaa88WTVQzZKKQWuJ3jvYNuQjRaRrSIySkSedH7dBrwJHAbe9lagSmVF12u5Xb55qTEy0r7fubP7M3l588KECXbJdvhwu4wbGenxJhJuq1+iPh0rdGTwisGMWp/Ieajy5eHHH6FvX3jzTWjRAo4dS3Bo3EM2ubiIEJMlDtkopZRLe/CMMWdEpCkwC6iPna0zQGy10o1AD2PMGa9EqVQW5U4tt/EJliFPWqNGN75/5x1bmaRsWTujF68WsU9k88vG3M5z6fN1H4atHsblyMu80fSNmwojkzOn3UQYEmJbeEyYAK+/nuA9Yw/Z9J9lD/l7ukuHUkqlRy6XizfGHDTG3A3UxhYWHu78WtsY09AY86d3QlQq6/JlLbc2bezq59690K4dHD6c/Ge8wd/hz4yOM+hfoz9vrn+T78K/S3xwr16wfbudhgT4888b69ixnBsYq57bQLVz2oxWKZU1uNrJorGIVAfbVswY84kxZpTz68/JfV4plTK+rOUWHGzLzZUpA2vW2JO38xItHe4aZ/UVwsLsy9XqK34OPya1m8SihxZxb5kkD83bU7YBAXZjYqNGdlPhcWfXwjgbGP2ItksOqdnAqJRSGYSrM3hrgAHeDEQpdTNf13ITsfXydu+Gxo3hjjtSd7/QULvcG//lSnk9EaF9+faICL/++yuDlg0iKibhAxUA5Mljl2k3brTlVGbN8ugGRk+dZFZKKV9wNcE7CVzxZiBKqZv16OFaqQ9P13K74w5YuhTq1LE/Dxpkk7KrVz37HFetDF/Jhz99SPevuhMZncSadd++tqpzvnz2DyUiIukbu9iM1tMnmZVSyttcTfDWAg28GIdSKgHpoZZbdDScOgUjRti2Z5s2ee9ZiXm2/rO8c887zNs9j85fdiYiKonErUoVe1rE3z/5BrwubGD01klmpZTyJlcTvFeA8iLyhogk8/9ulFKekh5qufn52dXOpUvtrNUxKrbKAAAgAElEQVTdd8PTT9vvfWlIgyF8fN/HLN63mPZz2nM58nLig3PnvvmwRWKS2cDozklmpZRKL1xN8F4CfgVeBg6JyDIRmSYin8Z7TfVeqEplTXFrufk5uzKnRS23++6ze/OeegpmzLCzer428K6BfNr+UxziwCHJ/PXloQ2MvjzJrJRSnuJqL9o+cb4v6nwlxAD9UhOQUupmsbXcfv3V/uyrXrHx5ckDH34Ir74KBQvaAxNjx0KfPlC4sG9i6FujL32q90FEOHPFlt7MnyP/zQM91IzWlyeZlVLKU1ydwSvl4qu0F2JUSqUzBQvar3v22G5hFSvCzJm+a3kmIhhj6DC3A81mNuPEpRM3D/LQBkZfn2RWSilPcCnBM8YccvXl7YCVUulH5cqwYwdUqAC9e9sSdAcP+ubZIsKwRsP47eRvNJnRhGMX4rUrS2oDo4jLGxjT6iSzUkqlhsudLJIjIq1FZKGn7qeUyhgqVYL16+Hjj2HzZrj3XtfPN6RWy7ItWdZ9GYfOHqLx9MYcPhev/UacDYzR+GHgRgG7XbugaVN47rkkNxSmh5PMSinlrlQleCJSTESGi8ifwDdAe49EpZTKUBwOmzPt2QPTp9vDIJGR9lCGtzW5owkre67kxKUT9P66980DnBsYf8nbkJ15Q+DcObuhsUwZ+PFHm5lWr24LJCcgPZxkVkopd7md4InVVkQWAweBUKAEEAb08Gx4SilfSGlLsfiKF7dlVAA++MDmTcOGJV9vOLXql6jP6t6rmdrezYP8ISE2sQsIsN+/806CGwnTy0lmpZRylaunaBGREkB/4BHgNrBtHYENQF9jjJb5VCqDCg11P5lLziOP2Bm8UaPsDNekSTaH8paat9YEIMbE8OLKF+kR3INqRasl/8FateDnn6FfPxg6FI4ds8Xv4kkvJ5mVUsoVSc7giYhDRDqKyFLgD2A4UAhYCLRzDvtNkzuVnnlqdkq5p0ABmHZ7KAZh334hpIn45A//30v/Mnf3XJrOaMqWv7e49qF8+WwW+tFH8Oij9r34M3nO/5DWhtmX/oeklErPEk3wRGQkcARYALQGdgLPALcZYzobY5b6JkSlUic1De9VKjn/8C81bMnzxefy04/2Dz9yWKjXHlk0d1HW9VlHvsB8NJ/ZnA2HN7j2QRFbxblCBfsfSN++tj1FbKLn/F125A1hR94Q/Q9JKZWuJTWD9zJQBJgAVDXG1DbGjDfGnPZNaEqpzCKXXwTvlJlAnTr256eegk6d7GqoN5TKX4p1fddxa55baTmrJd//8b17N7h2zR7GeO45uP9+OHPGO4EqpZSXJJXgGef17sBTIlLXNyEppTIzY6B0advbtmJFOBbWxisFkosHFWddn3VUKlSJGBPj3oezZ4evvrIzeEuXQs2asMXF5V6llEoHkkrwbgfeAC4AjwEbRWSviLwgIom1KlNKqSSJwIsv2tOn1avD/ulD2fn2e14pkFwkdxF+7P8j95a5F4Cjedw4zisCgwfbIn8xMdC+PVy54vkglVLKCxJN8IwxfxljXgPuwNa3WwqUBcYAR0TkW59EqJTKlMqVg9WroVyfsUQcL4bDY2XX/8sh9sbrS52iQ9+f+HzX5+7doF492L7dzujlyAHG4DBRXohUKaU8J9m/Uo0xMcaYb4wx7bGzeqHA30Ar55AuIvKRiFT3XphKqczI4YBbQ5ZS5+2Huf12u3z77LOwdasHH+I8/dp3z680Omzo+VUPptRy8/RrgQJQvz4Aha79RfmL22DbNg8GqZRSnuXWv5mNMUeNMa8DpYA2wCIgF/AksE1EdJOKUsptDn87I/b33/DFF1C3ri1Jd/myB27uPP3atr4h8vBlWt7Zikfbw4etC6Todpf8ghBjoEED2wXDGxsIlVIqlVK0KGKsZcaY+7FdLF4B/gRqejA2pVQWU7y4bXfWv79tKlG1Knzv5gHYpPjF5ODrrl9zf4X7GbR8EJv/2uz2PS7752Vf7lrQooU9Dty1qz1xq5RS6Uiqd70YY44bY0YZY8oALT0Qk1IqC8uXD/7v/2ynCD8/6N3bs63Osvtn54vOXzC/y3zqFa+XontEOwJgyRJ46y1YvBh++cVzASqllAd4dFuzMcaD/9ZWSmVlISH2pO2KFRAYaEvTLV7smRXRAL8AOlXqBMC2o9sYvno4xt0bOxzwwgvwxx/QsKF9b8sWXbJVSqULCSZ4IjJERAJTelMRqSki2n5bKZUqgYFQpYr9fvp06NDBVis5csRzz/hq71eMXD+SJ7990v16eQC33Wa/bt4MdepA9+5w4YLnAlRKqRRIbAZvFBAuIi+KSDFXbiRWSxFZCGwBXOjyrZRyRWbspxu6NhQZIYQdCiPsUBgyQpARQuja0ATHP/IIjBtnS6tUrgyffGLL06XWyGYjeaHBC0zYOoF+i/sRHROdshvVqQMjR9pTIrVr2+lHpZRKI5LQsoSIlAPeBe4DooGNwAZgK3AMOAMEArcAFYB6QHOgKHAKeA34P2NS8s/htFO7dm2z1aP1GZRSADRpYr+uXZvqWx08CI89BitXwqOPwqRJqQ/BGMPrYa8TGhZK18pd+ez+zwjwC0jwPjvy2RtVP5vAjcBm4N262fZmn3xie9oqpZQXiMg2Y0zthK75J/SmMWY/0FZEGmBLoHQCGmHbl910f+fXfcBbwDRjjK5PKKW8olQpuy/vs8+gUiX73sWLkC2bfaWEiPBak9fIGZCTsENhmAT/qnNRSAjs2AE9eiRd5yU0FEaMuPn9117L2FOzSql0IcEZvJsGieQBGgMNgZLYmbsrwL/ALmCtMWa3F+P0CZ3BU8pLPDiDl5ABA2DjRpgyxTaeSE0I0THR+Dn8OHX5FDkCcpAzIKe9EB4O48YRPWESDqKRPHlsEjdkCJQpc/ONYmJurKV/+y2ULHljQ2FKAlNKqXiSmsFz6RStMeaCMWapMeYlY0x3Y0wrY8z9xpjHjDEfZ4bkTimVcXXoYEvRNWgAgwbZGb2U8nP4ERUTRctZLbnv8/u4cPUCLFsGwcEwZQp+RNtliwsXbEYZHGyvx+dw2OQuKsq256hTB6ZNS3lgSinlBi91f1RKKd9p08YWSH7ySfjoI3sIY7OzhnFKDqj4O/wZUn8IGw5voO+7jTGdO9vl1sjI/w6MjLTvd+5sZ/gSvJm/fXC9evakSJ8+cOmSB35rpZRKnCZ4SqlMIU8em9xt2ABFi96oXuLsVHbTK7ltbt2qduPLLl/SYuFOoq4m0zMtMhLeey/x60WL2lMhr74KM2fa2bzz59359ZRSyi2a4CmlMpUGDezsXcmSNpHr3t0eyEhJ/eH7K95Pvz05CEiuckpkpH1IUvz87KGK776Ddu0gKMj9gJRSykWa4CmlvCc8HAYOtNNqYWE2qRk4MPHlTA8R59n+c+dsWZVevaBVK/jzT/fvFXD5imsDXd3416IFjBljv9+1C/bvh+gU1t5TSqlEaIKnlPKOOAcTricwyR1M8LB8+WxuOX68PWVbuTK8/76b+VTu3J4dF9e6dXDsGGzfDr/95v7nlVIqEZrgKaU8LzzcHjxI6cEED3I47OGLPXugaVMYO9bNU7Y9ekBAwkWPrwsIgJ493QssPNwG5XDYQxcVK9rZPR/8mSilMj9N8JRSnjdu3M2JXXzJHUzwsBIlYMkS2LIF8uaFa9fsbF5ERDIfHDLEtQTv2WddDybu7GbcfmurVtlpRh/MbiqlMjdN8JRSnjdrlmsJXnIHEzxM5Mbp2uXLbU5WrZpdKU1UmTIwfz7kzHlTonfNAdE5Au31hIodJySp2U2Aq1ft9f37XbufUkolwKUET0QeF5FwEbktkevFnNf7eTY8pVSG5OoaaGoqEqdS+/b2QOu1a7a72BNP2EMZCWrd2h6IGDDAnoYFYvLkZn7D/GxdNtVed5Wrs5v16sHcua7fVyml4nC1Vdk6wGGMaZjEmDAgxhjT1IPx+ZS2KlPKQ4KC7IEKV8YlmlX5xqVLtjzd++9Dy5a2q1iS4rQWi21rBnD0wlFuy5Pgv4H/y9U/Gz8/exrk8cftUnZgYPKfUUplKaluVQaUB3YmM2YXUMGdwJRSmZS3DiZ4Qa5cdlJt82YYPdq+d/Ys/PNP8p+NTe7m7Z5H2Q/Lsux3F/bOuTpraQwMHQoTJ9rifgcOuPY5pZTC9QQvL3A2mTHngfypC0cplSl442CCl911l92PB/C//9lDrVOnulYguVmpZlQsVJEOczuwcO/CpAe7U3bl7bftyZBDh+DFF137nFJK4XqCdwwITmZMMHAideEopTKFJA4mEBBg33fnYIKPPfecTfb694fmzZOfPCuYsyCreq2i1m216PJlF2b/Mjvxwe7ObrZta+vkTZhgfz550h7EUEqpJLia4K0BWolIgnvwRKQR0BpY5anAlFIZXAIHEwgKsj/v2uXewQQfK1cOVq+GSZPg55+halX46qukP5MvMB/f9fiORrc3oufCnuw5sSfhgSmZ3SxZEgoXttOJnTrB3XfDH3+490sppbIUVw9ZlAd+BvyAT4DlwN9AMWxi9wQQDdQ2xuz1WrRepocslPKSOAcTMpqjR+1WuNGjbZ4VE9IUh5hEf5fLkZf5Zv83PFj5wcRvumyZLYUSGfnfE7UBAfY1f37iCfCiRdCnj032Pv0UHnggxb+bUipjS/UhC2PMPuBB4CowGFiGPVSxDBgERABd3E3uRKSziGwUkVMiEiEi+0TkFRHJlsznKovIdyJyWUROisgEEblpY4uIdBCRX5z33iMiXd2JTymlbrsNPv/cJnfGQNtfR/NC+GNcvpzw+JwBOa8nd5uObOLdTe/ePCg1s5sdOthpxXLl7GzeoEG21otSSsXh7+pAY8xSESkN9AHqAvmwBy82AzOMMadS8PxbsMu/Y533qgOEAkWBpxL6gIjkBVYD+4Guznu8DdwKdIwzriGwADvj+AxwHzBHRM4YY75LQaxKqSzu2jUonv0EY//qxlfBdgm3WbPEx0/fMZ1JP0/i/NXzvBbyGiJy42KZMrZJ7q+/2p/dmd0sVco22X3hBfjmG3j9dciW5L+LlVJZjEtLtL4kIm8CTwL5TQLBichLwEtASWPMWed77YFFwF3GmK3O91YAAcaYZnE++y0QlFg9P12iVcpLMvAS7U2aNGHNmeoMuPw+Bw5A377w7ruQL9/NQ6Njonl0yaNM2zGNoQ2G8laLt/6b5DnvB6T8z+b8eTv7FxEB69fDPfek7D5KqQzHE3XwfOkUkNQ/RasDW2OTO6fvAAO0ARCR7EBTYF68z84F6jtnAZVSKkWa5t/Brl22nMqaNeBI5G9SP4cfU9pP4cm7nmTsxrE8vexpYkxMwoNTKijIfn3/fbj3XnsEWJdslcryXE7wRMQhIk+LyGYROSciUXGu1RCRT0SkXEqCEBE/EcnpXFZ9BpiQ0OydUyAQ/2+vKCAGqOj8uQwQAPwWb9xe7O+cojiVUipWjhz24MWePTbHunbNbof766//jnOIg49af8Tz9Z/nn4v/eD7Bi/Xss/DUU7brRePGtnaeUirLcrUXbTZgJfA+Nnm6AMRdZzgIPAJ0T2Ecl5yv9UAYMDSJsQeAaiISt85ALewJ3wLOn2MLLscvznwm3nWllEqVHDns123bYPJkqFTJlqyLiZPHiQhv3/M2czvPxd/hz8nLJ4mMTqYfrbuyZ4ePPoIvv4S9e6FGDVillauUyqpcncEbil3yHAEUAabEvehcLl0HtExhHA2ARsAQoAMwPomxk4FCwEciUlREKmMPUkQ7X/8JLd7Pksj7AJw4cYLatWtff02aNMnNX0MplVXVr2/PS9StCwMH2km03+KsIYgI/g5/IqIiaDK9CV3nd+VqlBcKFnfubLPNKlWgWDHP318plaYmTZp0PU8BCiY2ztVTtN2BH4wxrwOISEIJ0kGgnbuBAhhjfnZ+u0FETgIzRGScMSY8gbG/icgA4D3gMezS7CRs0nbcOSx2pi7+tufYnxNsu1aoUCH0kIVSKqVKl4bvvoOZM+2KaZ8+sGkTxD1XEegfyGO1HuOZ5c9w/xf3s8ARTY4YP88GUrYshIXZBxtj15J79oQSJTz7HKWUzw0YMIABAwYA4MyZEuTqDF4pbDmUpJzmxhJpasQme6USG2CM+RQ7kxgM3IYtqVI2TozhQCRQId5HK2ATwv0eiFMplZWEhtqEKSzsRvIkYt+PQwR697arpDNm2J/PnIEff7wx5um6TzO53WSWH1hOm+BfuegXf/HBA2KzyoMHYcwYu2T77beef45SKl1yNcG7ws2zYfGVJJGZMTfd7fx6MKlBxpgIY8wvxpjjQA/s7zLPee0qtr5el3gf6wpsMsac80CcSqmsJDTUzobFf8VL8GIVKQLly9vv33zTLuEOHgwXL9r3+i/+i88WGNblPcug3BsSTRhTrXRpu2RbvDi0aWOP/kZFJf85pVSG5uoS7Q7gXhHJZoy56fy9s+xIS2CjOw8XkeXA98Bu7P65u7H78L6IXZ4VkQNAmDGmn/PnIGAYds9fFHZv4BDgUWPM6Ti3fwNYKyLvA19jCx3fB7RyJ0allEqtV1+1Zeo+/BC+/homToRWoaF0Dw0l3/6l1BpaC3IX9V4Ad95p14oHD4a33rKbA7/+2nvPU0qlOVdn8CYDJYDPnQnWdSKSD5iOPZk60c3nb8F2xvgSO/vWDlvEuGecMf7YE7KxooEawGfYxK05tk3a9Lg3NsZsADoDLYAVQHvgYe1ioZTytaAg27Ri/XrImdN2Inv/fXutTbk2FM1dlKiYKF5c+SLHLx5P+mYplSMH/N//2b5rjz7qnWcopdINlztZiMhUoC92b9sZ7EnW7UBlIDvwsTHmaS/F6RPayUIpL8lMnSxS6epVO4nWp4/tb3vhAuTODb/8u4v6U+tTPKg4q3qtonhQce8HM24cnD4NI0aAv8udK5VS6YRHOlk4l0gfAfZgkzsBamLr0vXL6MmdUkr5Qvbsdsm2ZEm7he+BB+C++yBvRDAreqzg2IVjNJ7WmINnktyGnHrGwIEDMGoUtGgBR49693lKKZ9yq1WZMWa6MaYGkBsoDuQxxlQ1xkzzSnRKKZWJGQPt29ul28qVYdvChnzXYxVnI87SeHpj9p/y4oF/EVuRecYM2LIFqleH77/33vOUUj6Vol60xpgrxpijxphLng5IKaWygtBQ8PODZ56BS5fsa/Bg6Fz/Lmbds4Zsftk4c+VMsvdJtV69YOtWKFzYTiUePuz9ZyqlvM6lPXgikh1oBtTBLs8a4ATwI7AmoZO1GZHuwVPKS3QPXqJi/2jWrIG5c+Gdd+z3OXJFEuBnOzIev3icIrmLeDeQS5fsg9u2tT9fvmxPhCil0q1U7cETka7AH8A3wKvAQOBJ4DXgWyBcRDp7LlyllMp6RKBbNzuZFhQEJjqATp3gxS+mUH58eTYd2eTdAHLlupHcrVhhu2GsXu3dZyqlvCbJBE9EegOzgVuBw8DnwFvA287vjwDFgLki0t27oSqlMhwXuz+oG2IbUPz5p61P/PZj98KlQtzz2T2s/XOtb4IoVgzy5rWHL0aMgGgvdNpQSnlVoku0IlIAO3OXDTtrN8PEGywigi2dMh6IAEobYzzRzSJN6BKtUsrXklq9vnjRnrh9f+ox/Pq2wFHgDxY9vJBWZX1Qr/3iRXjiCZg1yyZ6s2bZ9hxKqXQjpUu03YAg4Bnn6dmbMkFjfQoMwrYy6+aJgJVSStn6eO++C5tX3sqdG9bid6YCHed25Mi5I755+MyZMGUKbNgAixZ5/5lKKY9JKsFrARwDPnXhPp86x97jiaCUUkrdUKcO7NxUiJ+eWs2MjjPIFV2CGTNsmRWvEoF+/WDPnhvdL/bsgZgYLz9YKZVaSSV4VYH1xphk/5dsjIkG1js/o5RSysMCAqBKmfx0rdKVyZOhT+haKnefwYEDPnh4qVI22Tt2DOrVs+VUTpzwwYOVUimVVIJXEHuIwlWHsSVUlFJKedHQoVDj8Y/YW74PFXt9wtixEBXlgwcXLWrruKxdawsjr1/vg4cqpVIiqQQvN3DBjXtdAnKlLhyllFLJcThg45DPuadkO6JaPskLC8fxwgs+eLAIDBgAmzfbGnlNm8KYMT5YK1ZKuSupBC8lXS5S1BlDKaWUewL9A1naawFdKnWBls/jaPoGxhj++QeuXPHyw6tXtzVcOnWC8PAbtV2UUumGfzLXq4tILxfvVT21wSillHJdgF8AszvNJkdADo5H7SfGGHr2FA4ehMmT7QSb1wQF2dYbsWvDu3bBhQtw991efKhSylXJJXgdnC9XCLaFmVJKKR/xd/gzrcM0YkwMfg4HTw49xfNP5qdZMwf9+sHYsZA/v5ceLmJPfwD873/w3Xd2yXbIEJ3VUyqNJZXgzfBZFEoppVLMIQ4c4uBcxDmG7qtHo7eb8MCPE3n3HT+++QaWLoVatbwcxJw5tqTK0KGwbh1Mnw4FCnj5oUqpxCSa4Blj+voyEKWUUqkTlD2Ihyo/xMj1I+le5wqbfpzOGyP8KVfOXjfGixNrefPCl1/Cxx/Dc89BjRqwZg2ULu2lByqlkpLcEq1SSqkMQkR4o9kb5AzIycurXyYiKoL5C2eTzS8bV6/aPXm9etmDsA5vHIkTgaeesrXy3n0XSpTwwkOUUq7QU69KKZUGwsNh4EDbBSwszJ5ZGDjQvp9aLzV6ifdbvs+CvQt46fuXADh3zlY2eeIJCAmB335L/XMSVbs2zJ5t9+edOgWPPQZnznjxgUqp+DTBU0opH1u2DIKDbZvX6Gj73oUL9ufgYHs9tQbVG8ScTnN4qZFN8AoXhpUr4dNPYfduqFYNRo6EyMjUPytJP/xgH1qjBvz0k5cfppSKpQmeUkr5UHg4dO4Mly/fnFxFRtr3O3f2zEzeQ1UeomDOglyLvsbLq17m/NVz9O1r28l27AgLF/rgsGv79naa0hho2BA++EALIyvlA5rgKaWUD40bl/ysWWQkvPee5575098/MXbjWFp81oLTV05TtCh88YXtOObvD6dPw7BhcPGi5575H3Xrwvbt0KoVDB4Mo0d76UFKqVia4CmllA/NmuVagvfZZ557ZsOSDVnYdSG7ju+i6Yym/HvpXwDy5LHXly2DUaOgShVYvtxzz/2PAgVg0SL46CPo39++pzN5SnmNJnhKKeVDrs6SeXo2rW25tnzT7Rt+P/U7IdND+Pv839evde8O69dDjhzQujX07AknT3r2+cCNU7aFC9sOGPfeC+PHa6KnlBdogqeUUj6UO7dnx7njnjL3sLzHci5du3R9Fi9Ww4Z2FXX4cNuB7LnnPP/8/7h8GbJnh6efhq5d7TFfpZTHiHHhX04iEgI0A8oB+bAtyc4B+4HVxpgwbwbpK7Vr1zZbt25N6zCUUpnYwIH2tGxSy7QBAbZW3fjx3onhatRVsvtnB+DU5VPckvOW/1z/5Rfb3qx4cTh0yL53++1eCCQmBt55B15+Ge64A+bNg5o1vfAgpTInEdlmjKmd0LUkZ/BE5C4R+QVYDQwHugItgVbO74cDq0Vkl4gk+ACllFI3DBlyo31rYgIC4NlnvRdDbHL3/ub3qTKhCrv/3f2f61Wr2uQO4JlnoHJl+PDDGyVdPMbhgBdesKc9IiLs2nBMjIcfolTWlGiCJyIVgDVAZWAD8DLQBbgXm+R1cb73A1AFm+hV8HbASimVkZUpA/Pn26LD8RO9gAD7/vz5dpy33VvmXgQhZHoI249tT3DMhx9C48YwaJBdxt29O8FhqdOwIezYYVudORw22btwwQsPUirrSGoGbwSQDehgjAkxxowxxiwwxnxvjFnp/H6MMaYxcD8QCIT6IGallMrQWreGXbvsMqyfn30vKMj+vGuXve4LlQpVYl3fdeTKloumM5qy+a/NN425/XZYuhQ+/xwOHLD1ir/91gvBFCwIlSrZ74cOhVq1YOdOLzxIqawh0T14InIcWGmM6eHSjURmA82NMUU8GJ9P6R48pZSvNWliv65dm3YxHDp7iOYzm3Pi8gnCnwmnYM6CCY47eRLeeMN2wMiTB65csSdvPW79enjoIdvm7MMP4dFHfVCRWamMJ6V78IKAI24855DzM0oppTKQ2/Pdzrq+65jUdlKiyR3YSbYPPrDJ3dWrcNddturJ+fMeDqhRI3ukNyTE9rHt0cOLVZiVypySSvAOYU/OJktEBGgOHPZEUEoppXzrtjy30bVKVwBWHFjB4n2LkxwfHQ333AOffGJXVpcs8XBAhQvbCswjR8I338Dffyf/GaXUdUkleF8Ad4nIXBFJ9IC889pcoBYw28PxKaWU8iFjDGN+GEOneZ2Yt3teouNy5rTt1DZtsiVV2re35ew8OpvncNgean/8AeXL24LIa9ZoYWSlXJBUgjca2Ag8CPwhIntFZJGIzHS+FonIXuAP7InaTcAY74eslFLKW0SERQ8tol7xenRb0I0ZO2YkOb5uXdi2ze7N++svm/h53C3OOn2LF0OzZtCnD1y65IUHKZV5JJrgGWMisEu0w4C/gPJAO6CH89XO+d4RbLmUZsaYq94OWCmllHcFZQ9iefflNCvVjD6L+jBx68Qkx2fLBq+8AuvWgb+/PRvx0EMQHu7hwNq2hdBQ26j3rru8VLNFqcwhyULHxphrxpjRxpjbgTuBtkB356stcKcx5g5nuZRr3g9XKaWUL+TKlosl3ZbQtlxbth3dhitdj2JLvuzcaUupVK1qG1VERXkoKD8/eO01WLnSZpF16sCcOR66uVKZi7+rA40x4YCn/z2mlFIqnQr0D+SrB7/CIQ5EhLMRZ8kXmC/ZzzVrBnv2wJNP2pJ2c+bA1KlQvbqHAmve3BZG7t7dHulVSt0kyRk8pZRSWVuAXwB+Dj/+vfQv1SdWZ9iqYS7N5hUvDl9/bZtT/P03vP66hwO79VZYtcou2wLMmAF793r4IUplXMkmeCJSUsWG8dgAACAASURBVEReE5EwETkmIldE5LLz+zAReVVESvoiWKWUUmmjYM6CtCzTklEbRvHsimddSvJEoHNnm3dNmGDfCw+3B2E9Irb48aVL8NJLdl/erFkeurlSGVuSCZ6IDAR+A14FGgFFgOzYtmRFnO+FAr+JyBNejVQppVSacYiDiW0nMqjuID748QMe/+ZxYkyMS5/Nnx+KOHscvfGGXcLt3x/OnPFQcLlywZYtULMm9OxpO19cueKhmyuVMSWa4IlIG2A8cBkYCTQACmH702Zzft/Aee0KMF5EfNRBUSmllK+JCO+1fI+XGr7EpJ8nMXr9aLfv8ckn8MILMH26LZC8YIGHytoVKwarV9uZvClT4O67ITLSAzdWKmNKqhftGqAKUMsYk2SHChG5A9gC/GKMcan7RXqkvWiVUr6WHnrRpsTkbZPpXKkz+XPkT9Hnf/7ZzuJt3w6TJtlJN49Zvhz27YNBgzx4U6XSn5T2oq0BzE0uuQMwxvyJ7XxRK0URKqWUylAerfUo+XPk50rkFULXhhIRFeHW52vWhJ9+gg8/tDXzAI4dgxjXVn2T1qrVjeRuxQp44gmIcC8+pTK6pBI8P8Cd2nbXkrmfUkqpTGb1wdWMCBtBuzntuHTNve4S/v7w9NO20snVq3ZvXtOmdvLNY37+GSZOhPr14fffPXhjpdK3pBKyPUBnEQlK7iYikg/o7PyMUkqpLKJNuTZM7zCd1QdX0+rzVpy/mrJmtNmy2Zp5u3ZBtWowapSHttC99BJ88w0cPgy1asG8xPvrKpWZJJXgfQKUALaISC8RKRJ/gIgUEZHewE9AMeyhDKWUUskIDbVVPsLC7EvEvkJD0zoy9/Wu3ps5neaw+a/NtJjZgtNXTrt9DxF45BFbUqV9exg2DGrXtjX0Uq1NG7vZr0oV6No14214VCoFEj1kASAi7wDPAbGDLgLnnN/nBXLHDgXeNcY876U4fUIPWSilVMot2beEJ5Y+wcqeK6lYqGKq7rVoEXz6qT1l6+9vT9rGlr1LschI21ajZ097s2vX7NShUhlUUocskkzwnB+uDzwBNMXO0sX1N7AamGiM2eSBWNOUJnhKKZU6VyKvkCMgB8YYzl89T97AvKm+56lTcN99thtGy5YeCBLgwAG76e+996BTJw/dVCnfSukpWgCMMZuMMb2MMSWwM3bFnK/cxpgSxpjemSG5U0oplXo5AnIAMGr9KGpNqsWhs4dSfc9//oGzZ+3h2F69bMKXagEBtt1Z5872xO3Vqx64qVLph1unXo0xl40xx5yvy94KSimlVMbWvHRzTl05RePpjTlw+kCq7lW5MuzcafflzZkDFSvC7NmpLJB8++2wfj0MHmxrtTRqBAcPpipOpdITlxM8EQkQkfIiUldE6ji/D/BmcEoppTKmesXrsbrXai5HXqbxtMbsOZG6IguBgTByJGzbBqVKeegwbLZsdol24ULYv99+r1QmkWyCJyIPOrtaXMSWQdkIbHJ+f1FEVotIl5Q8XEQ6i8hGETklIhEisk9EXhGRJHe9ikhtEfnO+bnTIvK9iNSNN2a6iJgEXhVSEqtSSin31Li1Bmt7r8VgaD6zORevXUz1PYODYeNGmDHDnpM4cADGj4fo6FTctGNH2LED3nrL/nz4sD2AoVQGllQvWoeIfAHMAUKASGxStwnY7Pw+EmgCzBWRuSJun3G6BVgD9AdaA58Cw4B3k4irBPA94A/0Ano6v/9ORG6PN/w3oH68159uxqiUUiqFKheuzLo+6/iw1YfkzpY7+Q+4wM8P8jrPbkyfboslN2oEu3en4qZ33AE5ctjE7p57oHFjOJT6/YNKpZWketEOAt7DJnSvAOuMMdHxxvhhk7+RQF3gWWPMh6kKSORN4Ekgv0kgOBF5HPgYuMUYc9b5Xn7gJPCUMWaC873pQJXETpckRE/RKqWUdy3Zt4R8gflodHsjj9zPGLsfb9AgOH8eXn7Z1jbOnj0VN50/H/r1s5nkjBnQrp1HYlXK01J6ivYR7AxYU2PMmvjJHYAxJtoYsxpbQmU/0M8D8Z4CklqiDQCisEvGsS4630ttlSSllFJeEh0TzfA1w2k5qyXf//G9R+4pAt272wLJDz4II0bA2LGpvGnnznaz3x132KrLQ4d6qK2GUr6TVIJXFlhijEl2I4Ix5iqw2PkZt4mIn4jkFJGGwDPAhIRm75wWAJeBcSJSWEQKY2cazwBfxhtbSUTOi8hVEdkgIiEpiU8ppVTq+Tn8WNFjBWULlKXt7LZ8s/8bj927UCGYNQtWrLCzeWB72p5PWec0KFvWbvZ74gn44QePxamUrySV4EUABdy4VwHnZ1LikvO1HggDhiY20BhzFDtj2Ak47nw9ALQ0xpyIM3Q7MARoB3QH/ICV/9/efcdXUaV/HP88KYQECHUVy7JKE1lBFOwICKggYgVEAcHGruja0J+6NuzLKvaysqzSkSLgIgJKB7EhqyCICmIvoBTppJzfH+cG4yUJN8nNnZub7/v1mtdNZs7MPHd2Nj6cmfMcMzu+sGNv2LCBVq1a7V2GDh1awq8jIiIFObDqgczvN59mBzbj/PHnM3Fl+L/LS+eMM6BaNcjNhQsu8CVWXitpHlm5Mjz3HMyZ4+vm/fwzzJwZ1XhFimvo0KF78xSgTmHtinoH73WgNdDWOfe/ok5mZi2B+cAC59zZxQ3WzI4FMoDjgbuBsc65AYW0PQifCK4Eng+tvgY4BjjZOfd1Iful4weGfOScO6+gNnoHT0QkNrbs2kKXsV1odXArnuj0RJmc45134Mor/eCLnj3hySfhgANKccAbb4QnnoBbb4X77/dJn0iASjRVmZmdjO9Ny8aPpJ2Ff88u/1y0jYFOQE98D1nb0s5qYWaXAiOAhs65tQVsfwzfY9fIOZcVWlcJ+Bx41Tl3XRHHfhbo6pyrV9B2JXgiIrGzM2snaSlpJFkSv+7+lcy0zKifY88eX/3kgQegalVYuND36pXIrl2+MPILL8App8DLL8Ohh0Y1XpHiKNEgC+fcEqAbsBXoB4wFluITqc9DP48F+obadI/SlGXLQp+HF7K9CbAyL7kLxboH36PXIILjl6b2uYiIREl6ajpJlsQ3W76h6bNNeeKd6PfkVaoEd93ly9z16AFHHOHXl6jMXeXK8K9/wZgx/oDHHOO7CUXiUJGFjp1zr+KTpivxydwHwJrQ8kFo3RVAg1DbaDgl9FnYnDFfAUflL4ZsZmnAURRR4y70iLYzPm4REYkTB1Y9kBMPPZEbZ93IQ4seKpNzHHkkPP88pKT4V+kaN4bHHoPs7BIc7JJL/Cjbli2hfv2oxyoSDYU+oo3Jyc1m4osWrwRy8MndQOA151zPUJs1+Hf7rgj93hJfaPkN4Dl8aZRrgI5AK+fcR2ZWHXgNGI1PRusAN+Lf0zvFOVfgc1g9ohURCUZ2bjb9pvZjzIox3HHqHdx/2v0Uv3Z+ZH78Efr3h2nToFUrGDYMjj66FAfMzvbv5Q0cCAcfHLU4RfanpHXwYuF9/OPficAE/IjX2/GzU+RJwb/fB4Bz7gP8e3/VgFHASPwAjdOdcx+Fmu0GNuALNL8ODAU2498RVAYnIhJnUpJSGHHeCK485koeXPQgL3zwQpmdq25dePVVGD/ez0rWsqUvkFzi6c6WL/ePblu0gDffjGqsIiUVaA9evFEPnohIsHJdLk+9+xRXHHMF1dKqlfn5Nm6Em2+GzZvhlVd84eQS+eQT6N4dVq2CO++Ee+7xM2GIlKFS9eCZ2flm9qSZDTGz04to19fM5pYmUBERqdiSLIkbTryBamnV2L5nO4MXDyY7tyQvykWmVi148UXfm2cGn3/uaxtv3lzMAx15JLz3HvTr50uoXHVVWYQrErFCEzzzJgCTgL/h32GbaWb/NbMaBexyGH5eWhERkVKbsnoKt825jV6Te5GVU7ZTheWVtFuwAIYO9fna5MnFPEhGhs8Whw+Ha67x6/SUTAJSVA/eZfgyKd8CdwD/hy8UfDawODRFmIiISJno3bw3j57+KBNWTqDbxG7syi7pZEmRu/JK3xFXty5ceKGfDeP774t5kL59/Yt9ANdd5yfILfELfiIls78EbzNwnHPuYefco0AL4DGgKTDbzAqdIkNERKS0Bp48kGfPepb/fvpfzn35XHZk7Sjzc7Zs6ZO8f/wDZszwk1eUSE4ObNkCgwbBmWfCTz9FM0yRIhWV4DUDJjvn1uetcM7lOOduBm7A152bbWY1yzhGERGpwAYcN4AXz3mRletX8uO2H2NyztRUX/lk+XK4+26/btky+OyzYhwkORlGjID//AfeesuPsp0/vyzCFdlHUQleJaDAf244557Cv5fXHHizkHfyREREouKyYy7j02s/pX7N+jjn2L5ne0zO26iRn+IM/Gt1zZvDww9DVqSvBJrB5Zf7LsHq1eHcc0swgkOk+IpK8L4DCpyzFcA59yxwE3Asfp7a6tENTURE5DdVKlUB4I65d9D6pdZs2L4hpuefPBm6dvU18447DopVVatZM7/D9OlQo4YffLFly/73EymhohK8FcBpRe3snHsCX5j4OODaKMYlIiJSoDZ/asPqn1fTbkQ7ftj6Q8zOe9BBMHEiTJkCGzbACSfAwoXFOEDVqtC6tf952DBo2rSYBxCJXFEJ3uvAwWbWpagDOOcGA/fgZ5wQEREpU50admJGrxl8tfkr2gxvw9dbvo7p+c87z9czvv9+OCU0e/rPPxfzIMcfD1WqwGmn+We+ublRj1MqtqISvMnA1cB+X3Rwzt2PH3V7X5TiEhERKVS7w9rxZp83Wb99PR1HdmRPzp6Ynr96df+oNjnZJ3dNm/oax7/8EuEBjj7aP7Lt3t0fqEuXEmSJIoUrNMFzzm10zr3gnJsfyYGccyOcc/dGLTIREZEinPTHk5h76VwGdxxMpeRKgcVRtSr07w9jxvgCyS+/HGF948xMGDcOnnsO5s3zAzFEokRz0eajuWhFRMqvV1a9QsNaDTm67tGBnH/5cl8o+f33fYfcxImQnh7hzj/84F/yA3+Ali0hab+ziUoFV6q5aEVEROLd7uzd3PLmLZw24jSWfh/MP9SbN4e334bHH/dz3Eac3MFvyd2qVXDSSb6cSsTPe0X2VdRctDklWHaZ2ddm9rKZHR/LLyIiIhVXWkoacy6dQ/XK1ekwsgNvff1WIHEkJ8MNN8DIkf73zz6DDh183haRI4/0U2fMmgXHHAPvvFNmsUpiK6oHz0qwVAIOBXoAi8ysTZlFLiIiks/hNQ9n0WWLqFu1LmeMPoO56+YGHRLr1sGHH/pJLO69F3bv3s8OZnDttbBkCaSkwKmnlmKuNKnIihpkkVTcBV8q5WB8Tbxk4K4YfQ8REREOzTyUhf0WUr9m/bhI8M48Ez75BLp181PSHnusf4y7X61a+bnRunaF7bGZtUMSS5kNsjCzcUBn51y5mcZMgyxERBLD1t1bqVqpKmbG9j3b986CEaTp0+Hqq+GCC4rRKeecX5KSYO5cP2T3eL0BJV5Qgyw+BzLL8PgiIiIFqpZWDTNjzcY1NH6mMWOWjwk6JLp0gZUr4cEH/e9Llvikr0hmPrlzDm691c+E8cQTEdZhkYqszBI859zdoce2IiIigahbtS6Nazemz5Q+DFs2LOhwqFbNT2AB8OijcPbZcMklsH79fnY08wMvOneGG2+ECy+EzZvLPF4pv5SAiYhIwqpaqSqvX/I6ZzY8k6umXcVT7z4VdEh7vfyyH3gxaZIfPDty5H465mrVgqlTYcgQmDbNv9D3008xi1fKFyV4IiKS0NJT05l60VTOb3I+18+8nvEfjw86JAAqVYK77/ajbJs0gb59fbJXJDO46SZYuBDOOQcOOCAmsUr5owRPREQSXlpKGuO7jefB9g/S9YiuQYfzO02bwqJFMHasH4ABfuRtTk4RO510kn8XzwzWrPET4W7ZEotwpZxQgiciIhVCanIqfz/172SkZvDr7l95+t2niZfpOpOS4OKLfaHkzZuhTRufwy1fHsHO77wDo0f76c2WLSvzWKV8UIInIiIVzvAPh3PdzOu49vVryXW5QYfzO9WrwzPPwJdf+pztjjtg164idujdGxYs8I1OOgmee06jbEUJnoiIVDx/O/5v3HLyLTy39Dmu/O+V5OQW9Tw0tszgoov8Y9reveGhh+Doo2HjxiJ2OuUU/zJf+/ZwzTXw73/HLF6JTylBByAiIhJrZsbgjoPJSM3g3gX3sjN7JyPPG0lqcmrQoe1Vuza89JIvozJ9uh9EC/7dvOTkAnaoU8c3/Pe/oU+f/TSWRKcePBERqZDMjEHtBjG442AWf72Y9dv3V4wuGKef/tvMF59+Co0bw5QphTROSoK//AXS02HrVl9K5YUX9Mi2AlKCJyIiFdr/nfJ/fHz1xxySeQi5Lpdd2UW98BasPXt8seQLLvC1jn/4YT+N69aFv/4VevXyCZ9UGErwRESkwqteuToA18+4nrPGnMW2PdsCjqhgzZrB++/Dww/7p7FHHgkvvlhI49q1YcYMeOABGD8eWrWKcFiuJAIleCIiIiEn//FkFn61kDNGncHmXfE5FVhqKtx2m8/VWrSAjz8uonFSkh+GO2cO/Pqrn+ZMKgQleCIiIiEXN7uYCd0nsPT7pXQY2YFfdvwSdEiFatwY5s6Ff/zD/75okf85K6uAxu3a+VG2I0b43zdtgu3bYxVq6Qwa5IcWhy+DBgUdWVxTgiciIpLPBUdewNSeU1m1YRWdxnSKuzp5+SUl+SnPAF59FW6/HY4/Hj74oIDGBx4Ihx7qf+7bF447DlaujFmsJTZokB8k0ratX5zzixK8IinBExERCXNWo7OYfsl07ml7D0lWPv5T+eijMHky/PSTT/JuuQV27Cik8Q03+MJ6xx0Hw4fHMkyJkfJx14qIiMRY+8Pbc3bjswGYsHICX2z6IuCI9u/882HVKrjySp/wjR5dSMP27f0j2xNPhMsu80uh2aCUR0rwREREivDr7l+59vVrafNSGz79+dOgw9mvGjV86bt33oErrvDr3nqrgJkw6taFN9+Eu+6C2bNhW3yOHJaSUYInIiJShMy0TOZcOoes3CzaDG/Dip9WBB1SRE44wU9isXs3dOvmS6qMHx9W8zg5Ge67z3f7HXAAZGfD668HFrNEjxI8ERGR/Wh2YDMW9ltIalIq7Ua0Y+n3S4MOKWJpaTBzJtSrBz17wrnnwrffhjWqVs1//uc/0KWLf8a7c2fMY5XoUYInIiISgSPqHMHCyxaSmZbJ7C9mBx1OsRx9NLz9NgwZ4p/GNm0KX31VQMMrroC//90neiec4OdGk3LJnOan26tVq1Zu6dLy868yERGJvc27NlM9rTpmxq7sXVROqRx0SMXyxRf+Ue3tt/vft2yB6tXDGs2cCX36wK5dfqTGuefGPM691q71menQoZCT43sbe/eGgQOhQYPg4ooDZvaBc65VQdvUgyciIlIMNSrXwMxYuX4lDZ9qyMw1M4MOqVjq1/8tuVu92j+6vf9+P3XtXp06wf/+50fZ/vGPgcQJ+KnWmjeHYcN8cgd+Tt1hw/z6GTOCiy3OKcETEREpgQOrHsgBVQ7gnHHnMOWTKUGHUyK1avlX7u6+G4491o+83evQQ/0o22OP9b8/8gh89lnsglu71o8O2bFj3+k5srL8+m7dfDvZhxI8ERGREqiTUYe5fefS8uCWdJ/YnXErxgUdUrEdcACMHQvTpvlHtSefDDfdFDbSFnz15MGDoWVL/3w3FoYMKWTetXyysuDxx2MTTzmjBE9ERKSEalSuwRu936B1vdb0mtyLWWtmBR1SiZx9tq+Ucs01vnKKWViDAw+EZcugWTM/FHfAAP9+XlkaPTqyBG/UqLKNo5xSgiciIlIK1dKq8Xqv17mrzV20Paxt0OGUWLVq8PTT8M9/+t8XLIBevWDDhlCDevX8yptvhuefhzPOKKCrL4oiLbysAs0FUoInIiJSShmpGdx72r1UTqnMxp0beel/LwUdUonl9d598glMnOgLJI8aFcrlUlP9u3j//S9ce20BXX1RVLVqdNtVMErwREREouipd5/i8v9ezr3z76U8lyL761/9QNpGjeDSS/3A2i+/DG3s2hV69PA///vf8Le/+Skzoql3b59QFiU11ZdzkX0owRMREYmiu9rcRb8W/Ri0YBC3zb6tXCd5f/4zLF7sH90uWeIHY+xj3Tp45hlo3doX2YuWgQMjS/BuvDF650wgSvBERESiKDkpmf+c8x+ubnU1/1zyT66bcR25LjfosEosOdk/jV292o+tAF9+bvnyUIOHHoKpU2HNGl9SZUqUSsY0aACTJkFGxr6JXmqqXz9pUoUvdlwYJXgiIiJRlmRJPHvWsww8aSDTP5/Oxp0bgw6p1A45xCd7ubm+c61lS7jzztBg2nPP9aNsGzeGCy6AlSujc9LOnX0m2b+/PzlAZqb/fflyvz1Cgwb5VwbDl0GDohNqvNFUZfloqjIREYkm5xybdm2iVnotcnJzcDhSklKCDqvUfvnFJ3kjRsARR/jX8E49Ff8e3qxZcM45vuGOHb6nLRratfOf8+fHw2HiQtxOVWZm3cxsiZn9Yma7zOxTM7vTzCrtZ79WZvZGaL+NZjbbzE4ooN25ZrYidOxVZnZR2X0bERGR3zMzaqXXwjnHVdOuosfEHuzOjvJghADUrg3Dh8Mbb/icrk0b+OgjIC3tt+RuyRI47DB49dUAI624gn5EWxuYB1wJdAZeBO4AHitsBzP7IzAbSAEuBfqEfn7DzP6Ur11r4JXQ8TsD04FxZnZGmXwTERGRQpgZLeq2YMrqKZw3/jx2Zu0MOqSoOP10+Phjn+wdfbRft2ZNaOOBB/p5bM87z3f37a9osURVoAmec+4F59wdzrkpzrl5zrnB+OSut1mhxXW6ANWAC5xz051z04HzgarAWfna3QUsdM5dFzr2LcBM4O6y+0YiIiIFu+6E6/h3138za80suoztwrY9iVGgt0oV6NvX//z5537kbffu8GOVBr4X75pr4LHHfDff118HG2wFEnQPXkF+AYp6RJsKZAP5/5+xLbTOAMwsDTgNmBC278vASWZWPWrRioiIROjKY69k1PmjWPjVQs4ff365LqFSkMMO84MWpk3zBZL/MzoN9/QzMGGCH3jx8stBh1hhxMWbnmaWDKQBxwLXAc+7wu/6V4D7gCFm9mBo3d3AJmBi6PcG+ERwddi+n+CT2sbA+1H7AiIiIhHq1bwXlVMqU71ydQp/WFU+pabC7bfDhRfCVVfBlVf6nG7mzO4kn3ACHHqob/jJJ9Cw4f7r3EmJxUsP3vbQsghYANxSWEPn3Pf43rkLgZ9CywXAmc65vBnzaoY+N4ftvilsu4iISMxd2PRCOtbvCMD4j8fz07afAo4ouho3hnnzYOhQX/84ORmoV49ckmDzZv+49rTT4Ntvgw41YcVLgncycCowEDgXeKawhmZ2EDAJ+AA/eKJz6OfpZlYvrHl4L6AVsh6ADRs20KpVq73L0KFDi/1FREREIrV++3qunHYlbYe35dtfEyvZSUryvXj33ON/nz8fjjsOln1RA556yg+7bdHCV00uwvx2g3zBugUL/BIqYDe/3aDiBRQqhDd/gV/KayG8oUOH7s1TgDqFtYu7OnhmdikwAmjonFtbwPbH8D12jZxzWaF1lYDPgVedc9eZWVNgJdDOObcg377HAe8Bxzvn9nlEqzp4IiISa4u/XsxZY86iTkYd5lw6h8NrHh50SGVi5ky47DLYsAFuugnuveRT0vv28AWLb78d7r//t2LGBYhW/boPa/gDtdhcygPFgbitg1eIZaHPwu7wJsDKvOQOwDm3B5/Q5c1XshbICrUN3zcX+Cxq0YqIiJRC63qtmXPpHDbv2kyb4W347JfE/E9Up06wahVcfjk88ggcdeERzP/HO76bb80a3+VXVtq1Y601YIA9S5str3Lslrlk2hYGHDyVtft0JSWGeEzwTgl9ritk+1fAUfmLIYdGzR4FfAngnNuNr3/XPWzfi4C3nXNbohmwiIhIaRx3yHHM7zef3dm7eWPtG0GHU2Zq1vTv5c2d6/O55Z+n+xVjxvjHpWvW+OrJUTbj1vk0z1jLMK5iK9VxJLGV6gz7+TyaN9/vU+JyKdBHtGY2E1+0eCWQg0/uBgKvOed6htqsARY4564I/d4SeAd4A3gO/17dNUBHoJVz7qNQu9bAfPz7fFPxNfJuBjo55wq8e/SIVkREgvTzjp+pk+Ffq9qTs4dKyUVO7FSu7dwJlSr5p7KTJvk5bru/2gsbNw7uuMO/G5fvkW1JH9GuXQvNm/tZ0wqTkeGfFDdoUHibeBTPj2jfB/rhy5tMALoCt+Nnp8iTAuz9X9g59wHQCV/seBQwEsgATs9L7kLtFgPd8InfLOAc4JLCkjsREZGg5SV3y35YRuOnG/POt+8EHFHZSU//LX8bNgwuugh6bP4327v3gwcegI4d4YcfSn2eIUP2P4lGVhY8/nipTxVX4m6QRZDUgyciIvHg6y1f02FkB37c9iOvXfwabQ9rG3RIZSo72w+svfNOSEmBqeeP4LSJV2PVqsHs2dCsWYl78DIzYevWyNptKWcvcMVzD56IiIiEqVe9Hgv7LaRe9Xp0GtOJWWtmBR1SmUpJ8SNrP/4YTjgBOozsy3vPvO+fyzZsWKpjb4twRrhI25UXSvBERETi0EHVDmJ+3/kcUfsIznn5HN799t2gQypz9ev7MRZz5sAJl/8Zxo9n/H/T+evle3hv4U4WLHBkZsKAAUQ8+rVq1ei2Ky+U4ImIiMSpP1T5A/P6zuOmE2/imIOOCTqcmDCD9u39z6NGQc+eMPSlFHa6dMDYutW/sxfp6Nfevf2MaPVZyzMMYDOZ5JDEZjJ5hgHUZy2pqdCnz/6PVZ7oHbx89A6eiIjEs/Xb17Pwq4V0a9ot6FDKwOFcbAAAIABJREFUXLRGv65dC8ObPMy92XdgOPLP/ptFMntIo3faJB5d2VmjaEVERCT2Hlz4IN0ndue5958LOpQyF63Rrw2evoH7sv9OUlhyB5BKDlXYwUS60YDEqnisBE9ERKScGHz6YLo27so1r1/DY28/FnQ4ZWr06MgSvFGjingSOXcuPPnkPolduJTs3QlXJ0UJnoiISDlROaUyk3pMonvT7gx8YyAPLHwg6JDKTKSjWrf+6nAPPuQrJYe77rrIDpKT41/4SyBK8ERERMqRSsmVGHvhWPo078Oo5aPYujuCIm/lUKSjWiuzC7vzDna27wI///z7jStXRn7CBKuTogRPRESknElJSmH4ecN56/K3qJZWjezcbHJdAT1Y5Vje6NeipKZCy9bpXF/peWzBPLY1agFvvVWyEyZYnRQleCIiIuVQkiVRJ6MOuS6XS6dcyl+m/YWc3Jygw4qagQMjS/CGDzcGfv5Xbj75bbJT0+Hii2H3bgAirRPiIDp1UgYN8nVewpdBg0p/7GJSgiciIlKOGUb9mvUZ9r9h9J3al+zc7KBDiooGDWDSJF8KJTzRS0316ydN8u3q1YOnFx9D5mcfwGuvMXpiGvfckc331ZtGlOQ5DG68sfRBDxoEzkHbtn5xzi9K8ERERKQ4zIwH2j/Ag+0fZMyKMfSc1JM9OXuCDisqOnf2de7694fkZL8uM9P/vny5357HDJJqZELz5rz/PqQ+NIirtgze7zkccG/ag0UX04vQ3g68BfP9ElwHngod56dCxyIiUp498c4T3DjrRnoe1ZNxF44LOpyoatfOf86fH1n7t5/5gFP+dgx38AD3cQ/A78ql5GU/j3M9tyQ9QU4Un25/WKMdAC02z4/eQQtQVKHjlDI9s4iIiMTMDSfeQJXUKjSp0yToUAJ30rUtqXq744Ftd7OY1jzJ9TTj473bV3AU1/Mk82lPZmKNrwD0iFZERCShXNXyKk7906kAjP94PL/u/jXgiILTu4+RnOyYT3uOZgVJuL3L0axgPu1JTk68eWhBCZ6IiEhCWrdpHX2m9KHjyI5s3Lkx6HAC0a0b5OQUPY9FTg5ccEGMAoohJXgiIiIJ6PCah/NKj1f46KePOG3Eaazfvj7okGJu0qTfBmcUxgwmT45NPLGkBE9ERCRBdT2iK69d/Bqf//I5bYe35fut3wcdUkyNHs1+B084ByNHxiaeWFKCJyIiksBOb3A6M3vP5Ltfv+PNtW8GHU6x5ZUeWbDAL8UpPRLp7GPbt/kxtd98U+Iw444SPBERkQTX5k9t+Oxvn9G3RV+AclUMOa92cPgSSYIX6exjVStnMW8e1K8Pt90GO3eWJuL4oARPRESkAqhbtS4AS75ZQtNnm7Jqw6qAIyp7kc1n6+hzeSVatIBnTh3PG4OX0awZzJtXghOuXQsDBtBsy2KO3rLAV2UeMMCvjzEleCIiIhVIjco12LpnK22Ht+XDHz8MOpwyFdF8tmRx441Qs2oWf/n2LpamnkSvLc/Rvr0r3uxlM2ZA8+YwbBjJ5Piiylu3wrBhfv2MGaX4JsWnBE9ERKQCafqHpizst5D0lHROG3Ea7377btAhlZmI5rN9tZKfpSw1FZYsIaljB+79+Ro+bNKTo+r5GoJ5j4ULtXatr8myYwdkZf1+W1aWX9+tW0x78pTgiYiIVDCNajdi0WWLqJVei46jOrJy/cqgQyoz+eezzVPYfLbUqQOvvQYPP8zRn7/CFc+3gu3bGTECzj8fvvuukJMMGbJvYhcuKwsef7y0Xydimos2H81FKyIiFcl3v37Hk+8+yUMdHiIlKfFnL61Rw39u3hxB40WL4K234LbbeP753x73Dh7sk8Ok/F1kmZn+cez+ZGbCli0lCb1ARc1Fqx48ERGRCuqQzEP45+n/JCUphe+3fs+sNbOCDqlM5JVa2bLFLxGVWjn1VD+kFrj66CX8dEYfTm2xlauvhrZt4dNP87WNtB5LpO2iQAmeiIiIcOvsWzl73NlMWDkh6FCiLq/UStu2filOqRUAPvyQatPGMu3HVky5dzkrV8Lnn+dLHF2k9VgibBcFSvBERESEZ896lhMPPZGLX7mYkR8l4NQOpTFgAMydi23dynkPn8C39w7j7C6OPn2gXTsYQ2/2UPRw3T2ksrlrn9jEixI8ERERATLTMpnZaybtD29P36l9eWHpC0GHFF/atoUPP4RTTyXjuquYcffbNG8O8+fDEAaStZ8EL4tUnrDi1F0pHSV4IiIiAkCVSlWYdvE0ujTqwrPvP8vu7N1BhxRfDjgAZsxg7SOT6fbYSezY4Vd/QQO6MYntZOzTk7eHVLaTQTcm8fh/G8QsVCV4IiIislfllMpMvmgyc/vOJS0ljZzcnKBDii/JyQz54nyysux3q2fSmeYsZyj92UImOSSxhUyG0p/mLGcmnWM5xkJlUvJTmRQREZHfZOdm02NiD46scyQPtH8AM9v/TnFo0CC49959199zTzEGWuQTaVWUgvaLYpUUlUkRERGR4kuyJOpk1OGhxQ9x06ybKK+dQnmjaMOXkiR3ULJqJ6mp0Cd2YyxI/KqGIiIiUiJJlsQLZ79Aeko6T7z7BDuzd/Jcl+dIsordP1S1avF78FJTKd7ctqWkBE9EREQKZWY80ekJqlSqwsOLHyY1KZWnz3o66LAC1bs3DBu2/9nJwCd2qal+TtwGsRtjoQRPREREimZmPNThIWpUrkHbP7UNOpzADRwII0bsL8FzVK1q9O3re+5imdyB3sETERGRCP3fKf/HCYeeAMDElRPZlb0r4IiC0aCB75HLSN1DKnt+ty2VPaSzg6czbmXrVnjmmdgnd6AET0RERIppxU8r6DGpB+eMO4cdWTuCDicQnTvDqpnfMPuoG35XFmX2UTcwLeMiWqe+F2h8SvBERESkWJod2IyXzn2JOevm0Gl0J7buLkHNkPJuxgz+1LU5bT4dRiZbScKRyVbafDqMdjtep1rWL4GGpwRPREREiq1fi36MvWAsS75ZQsdRHdm0c1PQIcXO2rXQrRvs2LHvi3hZWSSTy2E7Vvl2AVGCJyIiIiVy0VEX8UqPV/jox4+Ys25O0OHEzpAh+x1Cm0wuNGwIZiUvuFcKmskiH81kISIiUnzf/voth2YeCkBObg7JSckBR1TGIp3KItpTV4TRTBYiIiJSZvKSu3nr5tHihRZ8tfmrgCMqY5FOZRHLyWfDKMETERGRqEhPTeebLd/QZngb1mxcE3Q4Zadq1ei2KwNK8ERERCQqTjz0ROb2ncv2Pdtp81IbVm1YFXRIZaN3bz89RRGyiPHks2GU4ImIiEjUHHvQsSzotwCHo+3wtny5+cugQ4q+gQP3m+BlJ8V48tkwSvBEREQkqv58wJ9Z2G8h/Y7uR73q9YIOJ/r2TmWRsW+il5rKzqQM7mka48lnwyjBExERkahrVLsRj5zxCEmWxFebv+Ktr98KOqTo6twZli+H/v0hOTRqODMT+vfnilbLea9250DDSwn07CIiIpLwrnn9GuZ9OY9Xe75Kx/odgw4neho08JPNfvyx/33+fAC+bxdYRHupB09ERETK1H/O+Q8Najbg7LFnM/2z6UGHEz2DBvlCxgsW+MUMzGi3YFD+X4Ooc6xCx/mp0LGIiEjZ+GXHL3Qa04kPf/yQcReOo1vTbkGHVO7FbaFjM+tmZkvM7Bcz22Vmn5rZnWZWqYh9BpmZK2S5PV+74YW0aRKbbyciIiJ5amfUZnaf2Rx/yPE8suQRcnJzgg4poQX9Dl5tYB7wCLAZOB4YBNQFri1kn2HAzLB15wG3AjPC1q8GLgtb92WJoxUREZESq165Om/0foNd2btITkom1+WSZHpbrCwEmuA5514IWzXPzDKBa8zsb66A58fOuW+Bb/OvM7O7gNXOuQ/Dmm93zr0T1aBFRESkxKpUqkKVSlXYnb2b88efz5kNzuT6E68POqyEE49p8y9AoY9ow5lZLeB0YFyZRSQiIiJRZWakp6Zzw6wbeHjRw0GHk3DiIsEzs2QzyzCz1sB1wPMF9d4VohuQCrxcwLamZvarme02s8Vm1jZaMYuIiEjJVUquxPhu47mk2SX8fe7fuWvuXWjgZ/QE/Q5enu1AWujnkcAtxdi3J7DMOfdZ2Pr/Ae8Cq4A/AAOBN82stXPuvYIOtGHDBlq1+m0wSv/+/enfv38xQhEREZFIpSSlMPK8kaSnpPPAogdISUrhnnb3BB1WXBs6dChDhw7N+7VOYe3iokyKmR0LZOAHWdwNjHXODYhgv4Pw7+Pd6px7dD9t0/HJ3kfOufMKaqMyKSIiIrGX63K5Y84d9PhzD4456Jigwyk34rZMSh7n3DLn3GLn3GP4R7RXm1kkE7j1AAwYH8E5dgKvA8eWKlgRERGJqiRL4uGOD+9N7iZ/MlllVEopLhK8MMtCn4dH0LYnsNg5900xjh98l6WIiIgUaPHXi7lwwoX0mtyLrJysoMMpt+IxwTsl9LmuqEZmdhhwIhGOng09ou0MfFCK2ERERKQMta7XmkdOf4TxK8fTbWI3dmfvDjqkcinQQRZmNhOYDawEcvDJ3UBgvHNubajNGmCBc+6KsN17AtnApAKOWx14DRgNrMG/hHgjcAj+sa6IiIjEqZtPvpn0lHSunXEt57x8DlMumkJGakbQYZUrQY+ifR/oBxyGT9a+AG4H/pWvTQqQXMC+PYE5zrkNBWzbDWwA7gQOAHYBbwNtnXMaRSEiIhLnrjn+GtJT0/nLa39h4VcL6dSwU9AhlStxMYo2XmgUrYiISHxZt2kdh9f0r+VrarPfi/tRtCIiIiIFyUvuZq6ZySkvnsLPO34OOKLyQQmeiIiIlAsf/vghbYe35YetPwQdStxTgiciIiJxr1PDTszoNYOvNn9F2+Ft+WZLcSqkVTxK8ERERKRcaHdYO97s8yY/bf+JU186lfXb1wcdUtxSgiciIiLlxkl/PIl5fefR4889+EPGH4IOJ24FXSZFREREpFiOPehYjj3Izzy6duNatmdtp/mBzQOOKr6oB09ERETKJeccfaf2pd3wdiz9XmXO8lOCJyIiIuWSmTHq/FFUr1ydDiM78NbXbwUdUtxQgiciIiLl1uE1D2fRZYuoW7UuZ4w+g7nr5gYdUlxQgiciIiLl2qGZh7Kg3wLq16zPAwsfQLN0aZCFiIiIJIC6Vesyr+88UpJSMDOcc5hZ0GEFRj14IiIikhDqZNShRuUa7MzaSacxnRi7YmzQIQVGPXgiIiKSUHJcDlk5WfSe3JudWTtpd1g7hrw9hNHLR7NtzzaqVqpK7+a9GXjSQBrUahB0uGXC9Jz6N61atXJLl2qYtYiISHm3M2snF0y4gJlrZlIpuRLOObJys/ZuT01KJTU5lUndJ9G5UecAIy05M/vAOdeqoG16RCsiIiIJJz01nSFnDCHZktmTs+d3yR1AVm4WO7J20G1iN9ZuXBtQlGVHCZ6IiIgkpGfee4YkKzrVycrJ4vF3Ho9RRLGjBE9EREQS0ujlo/fpuQuXlZvFqOWjYhRR7CjBExERkYS0bc+2qLYrT5TgiYiISEKqWqlqVNuVJ0rwREREJCH1bt6b1KTUItukJqXSp3mfGEUUO0rwREREJCENPGkgqclFJ3jJScnceOKNMYoodpTgiYiISEJqUKsBk7pPIiM1Y5+evNSkVNJT0pncYzINajVIuPlrleCJiIhIwurcqDPL/7qc/i37k5mWSZIlkZmWSf+W/Vlx9Qo6N+rMlE+mcOboMxNqsIVmsshHM1mIiIhUPGNXjOXSKZdy/CHHM6PXDKpXrh50SBHRTBYiIiIihbik2SWM7zaepd8vpcPIDvyy45egQyo1JXgiIiJS4V3Y9EKm9pzKx+s/pt2Idvy6+9egQyqVlKADEBEREYkHZzU6i+mXTGf2F7OpVqla0OGUihI8ERERkZAO9TvQoX4HAFb/vJq05DQOr3l4wFEVnx7RioiIiITJdbl0n9idNsPb8NkvnwUdTrEpwRMREREJk2RJjLlgDLuzd9PmpTZ8vP7joEMqFiV4IiIiIgVofmBzFl62kOSkZNoOb8uyH5YFHVLElOCJiIiIFKJJnSYs7LeQapWqcd+C+4IOJ2IaZCEiIiJShAa1GrD48sVUT/MFkJ1zmFnAURVNPXgiIiIi+3Fo5qFUS6vGtj3bOH3U6cxcMzPokIqkBE9EREQkQruzd7Nx50bOGXcOU1dPDTqcQinBExEREYlQ7YzazO07l5YHt6TbhG6MWzEu6JAKpARPREREpBhqVK7BG73foHW91vSa3CsukzwleCIiIiLFVC2tGq/3ep3ezXvT6uBWQYezDyV4IiIiIiWQkZrByPNH0qh2I5xzvLn2zaBD2ksJnoiIiEgpjVkxhjNGn8F9C+7DORd0OKqDJyIiIlJaFx91MbO/mM098+9hR9YOHu7wcKC18pTgiYiIiJRSclIyL577IhmpGXyx6QtyXS7JlhxYPErwRERERKIgyZJ49qxnyXE5JCcFl9yBEjwRERGRqDEzUiz49EqDLEREREQSjBI8ERERkQSjBE9EREQkwSjBExEREUkwSvBEREREEowSPBEREZEEE2iCZ2bdzGyJmf1iZrvM7FMzu9PMKhWxzyAzc4Ust4e1PdfMVoSOvcrMLir7byUiIiISrKALtdQG5gGPAJuB44FBQF3g2kL2GQbMDFt3HnArMCNvhZm1Bl4BngOuA84CxpnZJufcG9H7CiIiIiLxxeJhQtz8zOxB4BqgposwODObDtR3zh2Zb90sINU51z7futeBTOdc64KO06pVK7d06dJSxS8iIiISC2b2gXOuVUHb4vEdvF+AQh/RhjOzWsDpwLh869KA04AJYc1fBk4ys+pRiFNEREQkLsVFgmdmyWaWEXqseh3wfKS9d0A3IBWfvOVpEFq3OqztJ/jv3LiUIYuIiIjEraDfwcuzHUgL/TwSuKUY+/YEljnnPsu3rmboc3NY201h20VEREQSTlz04AEnA6cCA4FzgWci2cnMDgLaku/xbJjwXkArZD0AGzZsoFWrVnuXoUOHRhKGiIiISEwMHTp0b54C1CmsXTwOsrgUGAE0dM6t3U/b64HHgT85577Jt74psBJo55xbkG/9ccB7wPHOuffDj6dBFiIiIlJelLdBFstCn4dH0LYnsDh/cheyFsgCmoStbwLkAp8hIiIikqDiMcE7JfS5rqhGZnYYcCIFPJ51zu3G19frHrbpIuBt59yWUkcpIiIiEqcCHWRhZjOB2fjHqTn45G4gMD7v8ayZrQEWOOeuCNu9J5ANTCrk8PcD883sCWAqvtDxWUCnaH8PERERkXgS9Cja94F+wGH4ZO0L4HbgX/napADJBezbE5jjnNtQ0IGdc4vNrBvwAHA1vkfwEs1iISIiIoku7gZZBEmDLERERKS8KG+DLCQCKuESO7rWsaNrHTu61rGjax07uta/UYJXTukmjh1d69jRtY4dXevY0bWOHV3r3yjBExEREUkwegcvHzPbAHwVdBwRqgP8HHQQFYSudezoWseOrnXs6FrHTkW71n9yzv2hoA1K8EREREQSjB7RioiIiCQYJXgiIiIiCUYJXoyZWUMze8HMPjKzHDObX0CbGmb2opltNLNtZjbDzBoW0O48M1tuZrvNbJ2Z3VRAGzOzv5vZN2a208wWmlmLMvp6cSeA6/2lmbmw5ccy+npxw8y6m9l/zey70DX8wMwuDmsT0b1oZk3NbI6Z7TCz783sPjNLLsmxElEA17pC3tMQvWsdyd+hSI+VqAK41gl/XyvBi70/46dM+yy0FGQ8cCZwPXAJUBuYY2aZeQ3M7BRgMvAe0BV4ERhsZjeEHes24C5gcKjdNmC2mdWN1heKc7G+3gBjgZPyLWdF5ZvEt5vw99aNwDn4uaDHmtnf8rXZ771oZjXx0xc64FzgPvz0hfeGna8i39exvtZQMe9piNK1JrK/Q5EeK1HF+lpDot/XzjktMVyApHw/TwLmh20/Cf8Ht32+dQcCO4Cb862bBSwM2/cxYCNQKfR7ZWALcHe+NlWADcADQV+LRLveoXVfAo8G/b0DuM51Clg3FlgX+jmiexE/VeEmIDPfuv8L/e+RWZxjJeoSy2sdWlch7+koX+si/w4V51iJusTyWoe2Jfx9rR68GHPO5e6nSQv8vLwL8u3zE7Ac6BLWbnbYvm8ANfFJC8DJQCYwId+xtgPTgM4lCL/cifH1rrCccwWVJfgfcEDo50jvxc7ALOfcr/nWvQykA22LeayEFONrXaFF61pH8Hco4mMlqhhf6wpBCV78qQxkO+dywtbvBo4Ma7engDbka9cEyAE+D2v3SWibRPd657nczPaY2RYzm2Rmf4peuOXKycCq0M+R3otNgNX5Gzjnvsb3KjXJ10b39e+V1bXOo3v6NyW51pHQfb2vsrrWeRL6vk4JOgDZxxqgspk1c86tADCzdOAooFpYu+PC9j0+9Fkr9FkT2FZA8rIJyDCzSs658KSloonm9QZ4FXgH+Baf+N0DLAodf0sZxB+XzKwD/r2uy0OrIr0XawKbCzjkptC24hyrQijjaw26p/cqxbWOhO7rfMr4WkMFuK/Vgxd/ZgHrgBfM7AgzOwj4F1Ad/6+XPP8CzjWzq8ysppmdiX9BmrB2BVWytiK2VTRRvd7Oueudc+Occ4ucc0PxgzcOBi6LxZeJB2Z2GP7dmVedc8PzbYr0XiysXSRtCtuWkGJxrXVPe1G41pHQfU1srnVFuK+V4MWZ0L9AeuJf9F8NfA/UB0YCP+Vr+iI+6Xge/6L/ZPwoOPK12wRUCy97ANQAdjjnssriO5QnUb7eBR3/Y+BT4Nhoxx6PzKwWMAP4Guidb1Ok9+Km0Lpw1fmtt0n3NTG71vuoaPc0ROVaR0L3NTG71vtIxPtaCV4ccs69BzTEv1fQ0Dl3Kv5F03fytclxzl0L/AFojk9Q8rbnfa4GkkPHym+fd28qsihe7yJPE9Wg45CZZQCvAZWALqEXoPNEei+uJux9GjP7I3603Op8bSr0fR3Da12UhL+nIWrXOhK6r2N3rYuSMPe1Erw45bxPnXNrzawR0BH4TwHtNjnnVjjntgEDgCXOubybfQnwK9A9r33o/0Bd8f9CkpAoXe99mNlRwBHAB2UVezwwsxRgItAI6OycWx/WJNJ7cQZwppnlf//xImAnv410rtD3dYyvdUHnrxD3NET1WkdC93XsrnVB50+4+1qDLGIsdEPmFVM8BMg0s26h3193zu0ws7vw/yL5GWiGL+z4snPuzXzHORFoDXyIHzp+Mf4dgtZ5bZxzu8zsH8BdZrYpdMyb8In902X3LeNHLK+3mXXBP1J4Df+otwlwJ/5Rw/Ay+orx4jn8db4eqBW6Xnn+V4x78V/AdcBkMxuMf1w+CHgsr5yH7uvYXesKfk9DlK51JH+HdF/H7lpXmPu6qCJ5WqK/AIfhu4ALWg4LtXkC+A5fhmMNcCuQEnaclsD7+ErevwLTgWYFnM+AO/AjhXYCi4Bjgr4OiXi98Y9u5+ALb2YBP+L/WBwc9HWIwXX+MoLrHNG9CDQF5oba/ADcDySHtamw93Usr3VFvqejea0j+Tuk+zp217qi3NcW+rIiIiIikiD0Dp6IiIhIglGCJyIiIpJglOCJiIiIJBgleCIiIiIJRgmeiIiISIJRgiciIiKSYJTgiYiUETMbZGbOzNpF8ZiVzOxzM5serWMWcp4LQ7F3KMvziEjZUIInInErlGDsb2kXdJwxdh1+Ps67y/g8k4FlwGNmpv9WiJQzmqpMRMqDe4vY9mWsggiamVXBV/J/0zlXpnNmOudcaAqz8UBPYGxZnk9EoksJnojEPefcoKBjiBOXADWI3XyZrwKbgQEowRMpV9TtLiIJI/87b2bW18z+Z2Y7zWy9mb1oZnUL2a+RmY00s+/MbI+ZfR/6vVEh7ZPN7K9m9paZbQmdY42ZDStin25m9p6Z7TCzjWb2spkdUsyveAWwB5gadux/hL73pYWcu2Vo+7R864aH1tU3s7+Z2fLQ95if18Y5tzt0rlPMrEkxYxWRACnBE5FEdCPwL+Aj4AngU+AyYImZ/SF/QzM7DlgK9AbeBx4F3gF6AUvNrFVY+0rATOB54I/4nq2ngA+A84FTCohnADAa/zj5WeBj4CJgtpmlRfKFzKw60ApY5pzbEbb5X0Au8JdCds9b/0IB254E7gdWhH5+K2x73u8dI4lTROKDHtGKSNwzs0GFbNrlnPtHAes7Ayc45/6X7xiPAzcA/8D3hGFmBowEMoHezrkx+dpfBLwMjDazps653NCmQfhkZxrQPdTLlbdPWuhY4ToBxznnVuRrOxa4GDgXmFDol//NSUAyPhn9Hefcl2Y2A+hiZs3CzlM1dJ5vgBkFHPdY4Bjn3LpCzvt+6LMN8EwEcYpIHFAPnoiUB/cUstxWSPtR+ZO7kEHAFuCSfL1mJwNNgLfzJ3cAzrnxwGLgCKA1+Eez+N64ncBf8yd3oX12O+c2FBDPU/mTrpB/hz6PL+Q7hKsX+vyhkO3Phz77h63vBVQFhjnncgrY759FJHcAP4adX0TKASV4IhL3nHNWyFKjkF0WFHCMLcCHQGXgyNDqY0Ofcws5Tt76Y0KfTYDqwHLn3PfF+Ar79Lrhe9QAakZ4jNqhz02FbJ8BrAP6mFlGvvX9gRxgWCH7vbef824MfdaJJEgRiQ9K8EQkEf1UyPq83qjqYZ+F9Yrlra8R9vldMePZXMC67NBncoTH2Bn6rFzQxtAj5Bfw3+ki8IMr8EnstCIS0h8LWZ8nPez8IlIOKMETkUR0YCHr80bRbgn7LHB0LXBQWLu8RK24o1+jYX3os3YRbV4EdvPboIqiBlfkcfs5b9751hfZSkTiihI8EUlEbcNXhEahtgB2AZ+EVue9p9eukOPkrV8W+lyNT/Kam9nB0Qi0GJaHPgstVxJ6/28ScIKZnYJZudSjAAACM0lEQVQfXPEl8EYpzpt3vg9LcQwRiTEleCKSiPqY2TFh6wbhH1+Oyzc44i18CZXWZtYtf+PQ722Az/CDLQgNUngO/9jyX+ElTkLzxP6uDEsUrQQ2ACfup13eYIvx+MEVQ/ONAC6JvPPNK8UxRCTGVCZFROJeEWVSAKY658J7l2YAb5nZBPx7dK1Dy5fkG3kbmo6rL/AmMN7MXsX30h0BnAdsBS4NS5DuBU4AugKfmdlroXZ/BM4AbqEMZpoIxToF6G9mf3bOrSyk3Vtm9hFwNJCFf2xbGmfgey0LG4giInFICZ6IlAf3FLHtS/Z9fPg4MAVf9+4iYBs+6fq7c+5375I5594NFTu+E1/frivwMzAOuN8592lY+z1m1gn4K3Ap0Bcw4PvQORcX/+tF7Dn8qNhLgVuLaPcSvsDzq865wgac7JeZNcb34D1ZQHFlEYlj5tz+3q8VESkfQj199wCnOefmBxtN2TCzWfjeucOdcwWObDWz4fjEs6Nzbk4pzjUEuBY40jn3RUmPIyKxp3fwRETKl5vxNekGFLTRzP4I9MQPJCnxY1UzOwi4GnhayZ1I+aNHtCIi5YhzboWZXQ5Uy7/ezC4BGuOTuzTgLle6RzSHAYPx89OKSDmjBE9EpJxxzo0sYHV//Kjfb4AbnXOvlPIcbwNvl+YYIhIcvYMnIiIikmD0Dp6IiIhIglGCJyIiIpJglOCJiIiIJBgleCIiIiIJRgmeiIiISIJRgiciIiKSYP4fqPTQSZvv1sMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#gaia DR2\n",
    "data_in='/home/akdiaz/Documents/Trabajo/SVS13/Images/VLA/proper_motions/'\n",
    "file_A = data_in + 'pm-A-all-final.dat'\n",
    "file_B = data_in + 'pm-B-all-final.dat'\n",
    "file_extra = data_in + 'pm-GAIA2&2MASS.dat'\n",
    "a1=10.751250164259192/15/1000\n",
    "b1= 3.77040 - a1*2015.5\n",
    "a2=-13.75931971408278/1000\n",
    "b2= 3.7304-a2*2015.5\n",
    "proper_motions([file_A, file_B],'-final',['VLA 4A', 'VLA 4B'],['b','r','g'],31,file_extra,[a1,b1,a2,b2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0024646611090975044+/-0.0014098332974829013"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decA1=ufloat(4.020,0.023)\n",
    "decA2=ufloat(3.769,0.010)\n",
    "decB1=ufloat(4.080,0.028)\n",
    "decB2=ufloat(3.761,0.010)\n",
    "yr1=1989.10\n",
    "yr2=2016.69\n",
    "((decA1-decB1)-(decA2-decB2))/(yr1-yr2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0680000000000005+/-0.03889730067755345"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(decA1-decB1)-(decA2-decB2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Optical position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def coordinates_new_epoch(ar,dec,pmar,pmdec,epoch1,epoch2):\n",
    "    ''' Calculates the coordinates at a especific epoch2 using the proper motions pmar, pmdec, \n",
    "    from the coordinates (ICRS) ar, dec taken at epoch1 .\n",
    "    Input: ar, dec in degrees; pmar, pmdec in mas; epoch1, epoch2 in years.\n",
    "    Output: new_ar, new_dec in degress'''\n",
    "    f = (epoch2-epoch1)/1000/3600\n",
    "    inc_ar = pmar*f\n",
    "    inc_dec = pmdec*f\n",
    "    new_ar = ar + inc_ar\n",
    "    new_dec = dec + inc_dec\n",
    "    return new_ar, new_dec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def separation(ar, dec, new_arc, new_dec):\n",
    "    'Returns the projected separation in arcsec between to coordinates in ICRS'\n",
    "    c_icrs = SkyCoord(ar, dec, frame='icrs', unit='deg')\n",
    "    c_icrs_new = SkyCoord(new_ar, new_dec, frame='icrs', unit='deg')\n",
    "    sep = c_icrs.separation(c_icrs_new)\n",
    "    return sep.arcsec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#gaia DR2\n",
    "ar2=52.265707466745944 #deg\n",
    "dec2=31.267707198461785 #deg\n",
    "#ar_err2 = 0.5026056031603101 #mas\n",
    "#dec_err2 = 0.31342583907522475 #mas\n",
    "pmar2 = 10.751250164259192 #mas/yr\n",
    "pmdec2 = -13.75931971408278\n",
    "#pmar_err = 0.7515952479133767\n",
    "#pmdec_err = 0.631270289616431\n",
    "gaia_epoch2 = 2015.5\n",
    "#Gaia EDR3\n",
    "ar3=52.26570947602043 #deg Gaia EDR3 ID:121392513273556992\n",
    "dec3= 31.26770535228855 #deg\n",
    "#ar_err3 = 0.20383582 #mas\n",
    "#dec_err3 = 0.15332146 #mas\n",
    "pmar3 = 9.982287690504483 #mas/yr\n",
    "pmdec3 = -13.016093571446266\n",
    "#pmar_err3 = 0.25517997\n",
    "#pmdec_err3 = 0.19674583\n",
    "gaia_epoch3 = 2016\n",
    "#VLA_epochB_Ka = 2015.123\n",
    "#VLA_epochB_Q = 2015.181\n",
    "hodapp_epoch = 2012.844\n",
    "VLA_epochA_X = 2016.893\n",
    "VLA_epochA_K = 2015.489\n",
    "VLA_epochA_Ka = 2015.516\n",
    "VLA_epochA_Q = 2015.470\n",
    "ALMA_hr = 2016.692\n",
    "#ALMA_lr = 2016.899"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "epochs = [gaia_epoch3, gaia_epoch2, hodapp_epoch,VLA_epochA_X, VLA_epochA_K, VLA_epochA_Ka, VLA_epochA_Q,ALMA_hr]\n",
    "new_ar = []\n",
    "new_dec = []\n",
    "for new_epoch in epochs:\n",
    "    a,d = coordinates_new_epoch(ar3,dec3,pmar3,pmdec3,gaia_epoch3,new_epoch)\n",
    "    new_ar.append(a)\n",
    "    new_dec.append(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.00778171, 0.04911816, 0.01389814, 0.00795291,\n",
       "       0.0075327 , 0.00824861, 0.01076989])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#separation between epochs\n",
    "separation(ar3,dec3,new_ar,new_dec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "03:29:03.77027, +31:16:03.73927\n",
      "03:29:03.76994, +31:16:03.74578\n",
      "03:29:03.76817, +31:16:03.78035\n",
      "03:29:03.77087, +31:16:03.72764\n",
      "03:29:03.76993, +31:16:03.74592\n",
      "03:29:03.76995, +31:16:03.74557\n",
      "03:29:03.76992, +31:16:03.74617\n",
      "03:29:03.77073, +31:16:03.73026\n"
     ]
    }
   ],
   "source": [
    "new_coord = zip(new_ar,new_dec)\n",
    "radec = [au.deg2radec(ra=c[0], dec=c[1]).replace(\",\", \" \") for c in new_coord]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "radec =  ['03:29:03.77027  +31:16:03.73927', '03:29:03.76994  +31:16:03.74578', '03:29:03.76817  +31:16:03.78035', '03:29:03.77087  +31:16:03.72764', '03:29:03.76993  +31:16:03.74592', '03:29:03.76995  +31:16:03.74557', '03:29:03.76992  +31:16:03.74617', '03:29:03.77073  +31:16:03.73026']\n"
     ]
    }
   ],
   "source": [
    "#copy this in CASA\n",
    "print('radec = ',radec)\n",
    "#run this in CASA, gives error here\n",
    "# radec_J2000 = [au.ICRSToJ2000(coord) for coord in radec]\n",
    "# radec_J2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[52.265712, 31.267701029722218],\n",
       " [52.265710625000004, 31.267702838055552],\n",
       " [52.26570325, 31.267712440833332],\n",
       " [52.2657145, 31.267697799166662],\n",
       " [52.26571058333333, 31.267702876944444],\n",
       " [52.26571066666666, 31.26770277972222],\n",
       " [52.26571054166667, 31.267702946388884],\n",
       " [52.26571391666668, 31.26769852694444]]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#from CASA output, be extra carefull!\n",
    "radec_J2000 = ['03:29:03.77088, +031:16:03.723707',\n",
    " '03:29:03.77055, +031:16:03.730217',\n",
    " '03:29:03.76878, +031:16:03.764787',\n",
    " '03:29:03.77148, +031:16:03.712077',\n",
    " '03:29:03.77054, +031:16:03.730357',\n",
    " '03:29:03.77056, +031:16:03.730007',\n",
    " '03:29:03.77053, +031:16:03.730607',\n",
    " '03:29:03.77134, +031:16:03.714697']\n",
    "\n",
    "deg_J2000 = [au.radec2deg(c.replace(\",\", \" \")) for c in radec_J2000]\n",
    "deg_J2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([52.26571096, 31.26770165])"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(np.array(deg_J2000[1])+np.array(deg_J2000[-2]))/2 #Kaband A & B conf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([52.26571098, 31.26770163])"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(np.array(deg_J2000[2])+np.array(deg_J2000[-1]))/2 #Qband A & B conf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Toomre's Q parameter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Us"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$17.428462 \\; \\mathrm{}$"
      ],
      "text/plain": [
       "<Quantity 17.42846152>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M_star = 1*u.solMass\n",
    "M_disk = 0.06*u.solMass\n",
    "T_disk = 140*u.K #disk temperature\n",
    "r_disk = 300*u.au\n",
    "par.Q(M_star,M_disk,T_disk,r_disk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$2.3465347 \\times 10^{13} \\; \\mathrm{m}$"
      ],
      "text/plain": [
       "<Quantity 2.34653466e+13 m>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "par.H_scale(r_disk, M_star, T_disk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tobin (HOPS 370)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$7.0069443 \\; \\mathrm{}$"
      ],
      "text/plain": [
       "<Quantity 7.00694434>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M_star = 2.5*u.solMass\n",
    "M_disk = 0.06*u.solMass\n",
    "T_disk=180*u.K #disk temperature\n",
    "r_disk=50*u.au\n",
    "c_sound=560*u.m*u.s**-1\n",
    "par.Q(M_star,M_disk,T_disk,r_disk,c_sound=c_sound)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mass from kinematics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mass_from_binary_orbit(v,a):\n",
    "    '''v is assumed to be in km/s and a (separation between stars) in au'''\n",
    "    v_units = ((v*u.km/u.s).to(u.au/u.yr))\n",
    "    M = a*v_units.value**2/np.pi**2 #in Solar Mass, from P = a**(3/2)*M**(-1/2)=np.pi*a/v\n",
    "    return round(M,2)*u.solMass\n",
    "\n",
    "def mass_from_keplerian_disk(v,r):\n",
    "    '''v is assumed to be in km/s and r (disk radius) in au'''\n",
    "    G = constants.G * u.m**3 * u.kg**(-1) * u.s**(-2) #Gravitational constant\n",
    "    v_units = v*u.km/u.s\n",
    "    r_units = (r*u.au).to(u.km)\n",
    "    M = (r_units*v_units**2/G).to(u.solMass) #in Solar Mass, from v = np.sqrt(G*m/r)\n",
    "    return round(M.value,2)*u.solMass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.98 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.98 solMass>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(4.4,45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.222539674441619"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "4.4*np.sqrt(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "v1=(1.6/1000*300*u.au/u.yr).to(u.km/u.s)\n",
    "v2=(0.4/1000*300*u.au/u.yr).to(u.km/u.s)\n",
    "v3=2.2*u.km/u.s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$3.2157675 \\; \\mathrm{\\frac{km}{s}}$"
      ],
      "text/plain": [
       "<Quantity 3.21576746 km / s>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v=np.sqrt(v1**2+v2**2+v3**2)\n",
    "v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0423889623513025"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1.12/1000*v.value**2*90 #formula de Zapata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6047999999999999 0.05669999999999999 2.2113\n"
     ]
    }
   ],
   "source": [
    "m=1.12/1000*(3/cos(45*np.pi/180))**2*30 #formula de Zapata\n",
    "m_min=1.12/1000*(1.5/cos(45*np.pi/180))**2*11.25 #formula de Zapata\n",
    "m_max=1.12/1000*(4.5/cos(45*np.pi/180))**2*48.75 #formula de Zapata\n",
    "print(m,m_min,m_max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$3.86 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 3.86 solMass>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_binary_orbit(v.value,90) #for the whole system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.41 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.41 solMass>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_binary_orbit(1,90) #for the whole system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.21 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.21 solMass>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_binary_orbit(1.25,30) #case of two stellar components in orbit for VLA 4A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.3 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.3 solMass>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_binary_orbit(1.5,30) #case of two stellar components in orbit for VLA 4A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$1.01 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 1.01 solMass>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(30,1) #for Sun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.08 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.08 solMass>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(1.5/cos(45*np.pi/180),15) #case of circumstellar disk around 4A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.01 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.01 solMass>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(0.7/cos(45*np.pi/180),5.4) #case of circumstellar disk around 4A-lower"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.26 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.26 solMass>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(2.2/cos(45*np.pi/180),23.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.04 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.04 solMass>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(1.5,15) #case of two disks in A, for western"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.02 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.02 solMass>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(1,21) #case of two disks in A, for eastern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.21191984 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.21191984 solMass>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#comprobacion keplerian disk from Murillo+2013 (https://www.aanda.org/articles/aa/pdf/2013/12/aa22537-13.pdf)\n",
    "n=-0.5\n",
    "v = 2*u.km/u.s \n",
    "r=47*u.au\n",
    "a=v/(r**n)\n",
    "((a.decompose())**2/G).to(u.solMass)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$0.21 \\; \\mathrm{M_{\\odot}}$"
      ],
      "text/plain": [
       "<Quantity 0.21 solMass>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_from_keplerian_disk(2,47) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mass from dust emission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<Quantity 0.00251605 solMass>, <Quantity 0.00365233 solMass>, <Quantity 0.00062611 solMass>, <Quantity 0.00025798 solMass>, <Quantity 0.00022262 solMass>, <Quantity 0.0001374 solMass>, <Quantity 0.00022552 solMass>]\n"
     ]
    }
   ],
   "source": [
    "S = [s*u.mJy for s in [43.4,63.0,10.8,4.45,3.84,2.37,3.89]] #83,109,1102 en A, B, CB (whole); 45.7,47.9,10.8 en A, B y C; 4.45,3.84 en N-in, S-in;2.37,3.89 en N-out, S-out\n",
    "D = 300*u.pc\n",
    "k_nu = 1.65*u.cm**2*u.g**-1 #en cm^2/g (del polvo)\n",
    "f= 100 # gas-to-dust ratio\n",
    "wl=0.9*u.mm\n",
    "T=140*u.K #temperature of the disk\n",
    "#ErT=10 #error of T\n",
    "#T_d = [i*u.K for i in [T,T-ErT,T+ErT]]\n",
    "#M = [par.MassMA01(S,t,D,k_nu) for t in T_d]\n",
    "M = [par.MassT20(Si,T,D,k_nu,wl) for Si in S]\n",
    "print(M)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<Quantity 0.00251605 solMass>, <Quantity 0.00365233 solMass>, <Quantity 0.00062611 solMass>, <Quantity 0.00025798 solMass>, <Quantity 0.00022262 solMass>, <Quantity 0.0001374 solMass>, <Quantity 0.00022552 solMass>]\n",
      "[0.002516047592624914+/-0.0002577098208257801, 0.0036523271505845517+/-0.0003605317492653176, 0.0006261132258144948+/-0.006377254746574014]\n"
     ]
    }
   ],
   "source": [
    "s_err=[3,4,110] #errores del flujo\n",
    "S_err=[ufloat(s.value,err) for s,err in zip(S,s_err)]\n",
    "T_err=ufloat(T.value,10)\n",
    "nu=C/wl.to(u.cm)\n",
    "B = 2*H*nu**3/C**2 * 1/(np.exp(H*nu/(K*T))-1)\n",
    "B_err= (2*H*nu**3/C**2).value * 1/(exp((H*nu).value/(K.value*T_err))-1)\n",
    "d_val=(D.to(u.cm)).value\n",
    "k_nu_val=k_nu.value\n",
    "B_val=B.value\n",
    "factor = (1*u.solMass).to(u.kg)*1E36\n",
    "M = [((D.to(u.cm))**2*Si/(k_nu*B)).decompose() for Si in S] # of dust\n",
    "M_sun=[f*Mi.to(u.M_sun) for Mi in M]\n",
    "M_val = [(d_val**2*Si_err/(k_nu_val*B_err)) for Si_err in S_err] # of dust\n",
    "M_err = [f*M_vali/factor.value for M_vali in M_val] # of gas\n",
    "print(M_sun)\n",
    "print(M_err)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## M(dust) Eq(1) Tobin+2020 (hops370)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<Quantity 0.08259522 solMass>,\n",
       " <Quantity 0.04832493 solMass>,\n",
       " <Quantity 0.0954238 solMass>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Tobin (HOPS370)\n",
    "S = [s*u.Jy for s in [0.207, 0.533, 0.732e-3]]\n",
    "T_d=131*u.K\n",
    "D=392*u.pc\n",
    "k_nu=[k*u.cm**2*u.g**(-1) for k in [0.899, 1.81, 0.13]]\n",
    "wl=[l*u.mm for l in [1.3,0.87,9.1]]\n",
    "[par.MassT20(Si,T_d,D,k_nui,wli) for Si, k_nui, wli in zip(S,k_nu,wl)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculo N(H2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Plankiana(wl,T):\n",
    "    nu=C/wl.to(u.cm)\n",
    "    B = 2*H*nu**3/C**2 * 1/(np.exp(H*nu/(K*T))-1)\n",
    "    return B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "def column_density_H2(S,wl,T,k_nu,region,D):\n",
    "    ''' '''\n",
    "    f=100\n",
    "    a, b =[i.value*D.value/2*u.au for i in region] #semiaxis in AU\n",
    "    A_reg = np.pi*a.to(u.cm)*b.to(u.cm) #area of the region\n",
    "    Ang_sol = A_reg/D.to(u.cm)**2\n",
    "    B=Plankiana(wl,T)\n",
    "    M_H2=-1/k_nu*f*log(1-(S.to(u.Jy)/(B*Ang_sol)).decompose())\n",
    "    tau = M_H2*k_nu/f\n",
    "    m_H2 = 2*1.00794*u.u #molecular mass (H_2)\n",
    "    N_H2=M_H2/m_H2.to(u.g)\n",
    "    return tau, N_H2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "S = [s*u.Jy for s in [4.34157e-2,6.296531e-2]] \n",
    "region=[a*u.arcsec for a in [0.180,0.06]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "en A: Tau= 0.66 , N(H_2)= 1.1956343878565518e+25 1 / cm2\n",
      "en B: Tau= 1.21 , N(H_2)= 2.185811132289032e+25 1 / cm2\n"
     ]
    }
   ],
   "source": [
    "tau=[]\n",
    "N=[]\n",
    "for s in S:\n",
    "    t, n = column_density_H2(s,wl,T,k_nu,region,D)\n",
    "    tau.append(t)\n",
    "    N.append(n)\n",
    "print('en A: Tau=',np.round(tau[0],2),', N(H_2)=', N[0])\n",
    "print('en B: Tau=',np.round(tau[1],2),', N(H_2)=', N[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "en A: Tau= 0.56 , N(H_2)= 1.0154437648002502e+25 1 / cm2\n",
      "en B: Tau= 0.6 , N(H_2)= 1.0822185971815236e+25 1 / cm2\n",
      "en C: Tau= 0.11 , N(H_2)= 1.9367497782633825e+24 1 / cm2\n",
      "en N-In: Tau= 0.04 , N(H_2)= 7.730849474545838e+23 1 / cm2\n",
      "en S-In: Tau= 0.04 , N(H_2)= 6.651388749342978e+23 1 / cm2\n",
      "en N-Out: Tau= 0.02 , N(H_2)= 4.076205910242373e+23 1 / cm2\n",
      "en S-Out: Tau= 0.04 , N(H_2)= 6.739627391230494e+23 1 / cm2\n"
     ]
    }
   ],
   "source": [
    "region=[a*u.arcsec for a in [0.16,0.08]]\n",
    "print('en A: Tau=',np.round(tau[0],2),', N(H_2)=', N[0])\n",
    "print('en B: Tau=',np.round(tau[1],2),', N(H_2)=', N[1])\n",
    "print('en C: Tau=',np.round(tau[2],2),', N(H_2)=', N[2])\n",
    "print('en N-In: Tau=',np.round(tau[3],2),', N(H_2)=', N[3])\n",
    "print('en S-In: Tau=',np.round(tau[4],2),', N(H_2)=', N[4])\n",
    "print('en N-Out: Tau=',np.round(tau[5],2),', N(H_2)=', N[5])\n",
    "print('en S-Out: Tau=',np.round(tau[6],2),', N(H_2)=', N[6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.8367480711388617e+24 1 / cm2\n"
     ]
    }
   ],
   "source": [
    "D=300\n",
    "M_d=0.00062611*u.M_sun #0.0045 (high-res), 0.014 for A; 0.0059 (high-res), 0.010 for B; 0.060 for CB\n",
    "d_d=np.sqrt(0.16*0.08) #diameter in arcsec # np.sqrt(0.22*0.27) (hr), np.sqrt(0.31*0.39) for A;\n",
    "                                           # np.sqrt(0.20*0.32) (hr), np.sqrt(0.25*0.38) for B; 2 for CB\n",
    "r_d=d_d/2*D*u.au #radio in AU \n",
    "A_d=np.pi*(r_d.to(u.cm))**2 #area of the disk\n",
    "m_H2 = 2*1.00794*u.u #molecular mass (H_2)\n",
    "N_H2_d=M_d/(A_d*m_H2.to(u.M_sun)) \n",
    "print(N_H2_d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "def column_density_H2(m_d, d_d,D):\n",
    "    '''m_d: disk mass in solar mass, d_d = disk diameter in arcsec, D: distance in pc'''\n",
    "    r_d=d_d/2*D*u.au #radio in AU \n",
    "    M_d=m_d*u.M_sun #mass in solar mass\n",
    "    A_d=np.pi*(r_d.to(u.cm))**2 #area of the disk\n",
    "    m_H2 = 2*1.00794*u.u #molecular mass (H_2)\n",
    "    N_H2_d=M_d/(A_d*m_H2.to(u.M_sun)) \n",
    "    return N_H2_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for N-out (beam): 4.030748350521148e+23 1 / cm2\n",
      "for N-in (beam): 7.568067390592763e+23 1 / cm2\n",
      "for Center (beam): 1.8367480711388617e+24 1 / cm2\n",
      "for S-in (beam): 6.530751075640597e+23 1 / cm2\n",
      "for S-out (beam): 6.615825094683619e+23 1 / cm2 \n",
      "\n",
      "for A (beam): 7.381051228041291e+24 1 / cm2\n",
      "for B (beam): 1.0714427309358736e+25 1 / cm2\n",
      "for A (high-res): 3.034336311391686e+24 1 / cm2\n",
      "for A (normal): 4.3482114635947853e+24 1 / cm2 \n",
      "\n",
      "for B (high-res): 3.696319448076161e+24 1 / cm2\n",
      "for B (normal): 3.9526223003654853e+24 1 / cm2 \n",
      "\n",
      "for whole disk: 6.007985896555537e+23 1 / cm2\n"
     ]
    }
   ],
   "source": [
    "print('for N-out (beam):', column_density_H2(0.0001374, np.sqrt(0.16*0.08), 300)) #for N-out (beam, high resolution)\n",
    "print('for N-in (beam):', column_density_H2(0.00025798, np.sqrt(0.16*0.08), 300)) #for N-in (beam, high resolution)\n",
    "print('for Center (beam):', column_density_H2(0.00062611, np.sqrt(0.16*0.08), 300)) #for C (beam, high resolution)\n",
    "print('for S-in (beam):', column_density_H2(0.00022262, np.sqrt(0.16*0.08), 300)) #for S-in (beam, high resolution)\n",
    "print('for S-out (beam):', column_density_H2(0.00022552, np.sqrt(0.16*0.08), 300),'\\n') #for S-out (beam, high resolution)\n",
    "print('for A (beam):', column_density_H2(0.00251605, np.sqrt(0.16*0.08), 300)) #for A (beam, high resolution)\n",
    "print('for B (beam):', column_density_H2(0.00365233, np.sqrt(0.16*0.08), 300)) #for B (beam, high resolution)\n",
    "print('for A (high-res):', column_density_H2(0.0048, np.sqrt(0.22*0.27), 300)) #for A (high resolution)\n",
    "print('for A (normal):', column_density_H2(0.014, np.sqrt(0.31*0.39), 300),'\\n') #for A (normal)\n",
    "print('for B (high-res):', column_density_H2(0.0063, np.sqrt(0.20*0.32), 300)) #for B (high resolution)\n",
    "print('for B (normal):', column_density_H2(0.010, np.sqrt(0.25*0.38), 300),'\\n') #for B (normal)\n",
    "print('for whole disk:',column_density_H2(0.064, 2, 300)) #for whole disk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculo abundancia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rel_abundance(N,NH2):\n",
    "        return N/NH2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for A:\n",
      "for CH3OCHO: 5.555555555555556e-08\n",
      "for CH2DOH: 1.0569105691056911e-07\n",
      "for aGg'-(CH2OH)2: 1.4905149051490515e-08 \n",
      "\n",
      "for B:\n",
      "for CH3OCHO: 2.3364485981308412e-07\n",
      "for CH2DOH: 1.6822429906542057e-07 \n",
      "\n",
      "for N-In:\n",
      "for 13CH3OH: 1.3157894736842106e-08\n",
      "for CH318OH: 6.578947368421053e-09\n",
      "for CH3OH (min): 1.0131578947368423e-06 (N(CH3OH))= 7.7e+17\n",
      "for CH3OH (max): 3.6842105263157896e-06 (N(CH3OH))= 2.8e+18 \n",
      "\n",
      "for Center:\n",
      "for CH3OCHO: 1.25e-07\n",
      "for CH2DOH: 2.717391304347826e-07\n",
      "for 13CH3OH: 4.347826086956522e-08\n",
      "for CH318OH: 1.6304347826086957e-08\n",
      "for CH3OH (min): 3.3478260869565216e-06 (N(CH3OH))= 6.16e+18\n",
      "for CH3OH (max): 9.130434782608695e-06 (N(CH3OH))= 1.68e+19 \n",
      "\n",
      "for S-In:\n",
      "for 13CH3OH: 4.615384615384616e-08\n",
      "for CH318OH: 1.2307692307692308e-08\n",
      "for CH3OH (min): 3.553846153846154e-06 (N(CH3OH))= 2.31e+18\n",
      "for CH3OH (max): 6.892307692307693e-06 (N(CH3OH))= 4.48e+18\n"
     ]
    }
   ],
   "source": [
    "NH2_A = 7.38e+24 #4.3e+24 #from dust emission in A (normal)\n",
    "NH2_B = 1.07e+24#4.0e+24 #from dust emission in B (normal)\n",
    "NH2_C = 1.84e+24#(NH2_A+NH2_B)/2\n",
    "NH2_Nin = 7.6e+23\n",
    "NH2_Sin = 6.5e+23\n",
    "\n",
    "print('for A:')\n",
    "print('for CH3OCHO:',rel_abundance(4.1e17,NH2_A))\n",
    "print('for CH2DOH:',rel_abundance(7.8e17,NH2_A))\n",
    "print(\"for aGg'-(CH2OH)2:\",rel_abundance(1.1e17,NH2_A),'\\n')\n",
    "\n",
    "print('for B:')\n",
    "print('for CH3OCHO:',rel_abundance(2.5e17,NH2_B))\n",
    "print('for CH2DOH:',rel_abundance(1.8e17,NH2_B),'\\n')\n",
    "\n",
    "print('for N-In:')\n",
    "print('for 13CH3OH:',rel_abundance(1e16,NH2_Nin))\n",
    "print('for CH318OH:',rel_abundance(5e15,NH2_Nin))\n",
    "print('for CH3OH (min):',rel_abundance(1e16*77,NH2_Nin),'(N(CH3OH))=',1e16*77)\n",
    "print('for CH3OH (max):',rel_abundance(5e15*560,NH2_Nin),'(N(CH3OH))=',5e15*560,'\\n')\n",
    "\n",
    "print('for Center:')\n",
    "print('for CH3OCHO:',rel_abundance(2.3e17,NH2_C))\n",
    "print('for CH2DOH:',rel_abundance(5.0e17,NH2_C))\n",
    "print('for 13CH3OH:',rel_abundance(0.8e17,NH2_C))\n",
    "print('for CH318OH:',rel_abundance(0.3e17,NH2_C))\n",
    "print('for CH3OH (min):',rel_abundance(0.8e17*77,NH2_C),'(N(CH3OH))=',0.8e17*77)\n",
    "print('for CH3OH (max):',rel_abundance(0.3e17*560,NH2_C),'(N(CH3OH))=',0.3e17*560,'\\n')\n",
    "\n",
    "print('for S-In:')\n",
    "print('for 13CH3OH:',rel_abundance(3e16,NH2_Sin))\n",
    "print('for CH318OH:',rel_abundance(8e15,NH2_Sin))\n",
    "print('for CH3OH (min):',rel_abundance(3e16*77,NH2_Sin),'(N(CH3OH))=',3e16*77)\n",
    "print('for CH3OH (max):',rel_abundance(8e15*560,NH2_Sin),'(N(CH3OH))=',8e15*560)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('for CH2DOH:',rel_abundance(1.8e17,NH2_B))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# From line emission"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Methanol (CH3OH) column density and relative column densities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deuterated ratio = 2%\n",
      "N(Methanol) [3.9e+19+/-1.4e+19, 9e+18+/-6e+18, 2.5e+19+/-1e+19] for A, B and CB\n",
      "Ab(CH2DOH/methanol) [0.02+/-0, 0.02+/-0, 0.02+/-0] for A, B and CB\n",
      "Ab(CH3OCHO/methanol) [0.010512820512820513+/-0.005574302446250359, 0.027777777777777776+/-0.020541369813128957, 0.0092+/-0.0038707105290889414] for A, B and CB\n",
      "Ab(aGg’-(CH2OH)2/methanol) [0.0028205128205128207+/-0.0022875527670345895] for A\n",
      "\n",
      "deuterated ratio = 5%\n",
      "N(Methanol) [1.56e+19+/-5.6e+18, 3.6e+18+/-2.4e+18, 1e+19+/-4e+18] for A, B and CB\n",
      "Ab(CH2DOH/methanol) [0.05+/-0, 0.05+/-0, 0.05+/-2.407412430484045e-18] for A, B and CB\n",
      "Ab(CH3OCHO/methanol) [0.026282051282051282+/-0.013935756115625897, 0.06944444444444445+/-0.0513534245328224, 0.023+/-0.009676776322722356] for A, B and CB\n",
      "Ab(aGg’-(CH2OH)2/methanol) [0.007051282051282051+/-0.005718881917586473] for A\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def col_density(N_d,d_ratio):\n",
    "    N=N_d/d_ratio\n",
    "    return N\n",
    "\n",
    "def rel_intensity(N,Nmain):\n",
    "    return N/Nmain\n",
    "\n",
    "# using CH2DOH (deuterated methanol)\n",
    "N_d=[ufloat(7.8e17,2.8e17),ufloat(1.8e17,1.2e17),ufloat(5e17,2e17)] # of CH2DOH for A, B and CB\n",
    "\n",
    "N2=[col_density(n,0.02) for n in N_d]\n",
    "N5=[col_density(n,0.05) for n in N_d]\n",
    "\n",
    "# CH3OCHO (methyl formate) and aGg’-(CH2OH)2 (ethylene glycol)\n",
    "N_m=[ufloat(4.1e17,1.6e17),ufloat(2.5e17,0.8e17),ufloat(2.3e17,0.3e17)] # of CH3OCHO for A, B and CB\n",
    "N_e=[ufloat(1.1e17,0.8e17)] # of aGg’-(CH2OH)2 for A\n",
    "\n",
    "Nrel_d2=[rel_intensity(N_di,N2i) for N_di, N2i in zip(N_d,N2)]\n",
    "Nrel_m2=[rel_intensity(N_mi,N2i) for N_mi, N2i in zip(N_m,N2)]\n",
    "Nrel_e2=[rel_intensity(N_ei,N2i) for N_ei, N2i in zip(N_e,N2)]\n",
    "\n",
    "Nrel_d5=[rel_intensity(N_di,N5i) for N_di, N5i in zip(N_d,N5)]\n",
    "Nrel_m5=[rel_intensity(N_mi,N5i) for N_mi, N5i in zip(N_m,N5)]\n",
    "Nrel_e5=[rel_intensity(N_ei,N5i) for N_ei, N5i in zip(N_e,N5)]\n",
    "\n",
    "print('deuterated ratio = 2%')\n",
    "print('N(Methanol)',N2, 'for A, B and CB')\n",
    "print('Ab(CH2DOH/methanol)', Nrel_d2,'for A, B and CB')\n",
    "print('Ab(CH3OCHO/methanol)', Nrel_m2,'for A, B and CB')\n",
    "print('Ab(aGg’-(CH2OH)2/methanol)', Nrel_e2,'for A\\n')\n",
    "\n",
    "print('deuterated ratio = 5%')\n",
    "print('N(Methanol)',N5, 'for A, B and CB')\n",
    "print('Ab(CH2DOH/methanol)', Nrel_d5,'for A, B and CB')\n",
    "print('Ab(CH3OCHO/methanol)', Nrel_m5,'for A, B and CB')\n",
    "print('Ab(aGg’-(CH2OH)2/methanol)', Nrel_e5,'for A\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## M"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.111111111111112e-11\n",
      "4.2804878048780483e+24 1 / cm2\n",
      "0.04103806197386875 solMass\n",
      "0.0014591310924042217 solMass\n"
     ]
    }
   ],
   "source": [
    "d_l=0.6 #diameter in arcsec\n",
    "D=300 #distance in pc\n",
    "N_Sp = 3.9e14*u.cm**(-2) #column density of the species\n",
    "Frac_Ab_Sp = 1/45#fractional abundance of the species (13C/12C=1/45, 15N/14N=1/234 Crocket 2014 -> Tercero 2010)\n",
    "Ab_Mol = 4.1e-9 #abundance of the molecule respect to H2 (HCN=3.8e-7 hot core, 4.1e-9 compact ridge, 2.8e-7 plateu, 3.3e-8 extendend ridge, Crocket 2014)\n",
    "Ab_Sp = Frac_Ab_Sp * Ab_Mol #abundance of the species with respect to H2\n",
    "r_l=d_l/2*D*u.au #radio in AU \n",
    "A_l=np.pi*(r_l.to(u.cm))**2 #area of the disk\n",
    "m_H2 = 2*1.00794*u.u #molecular mass (H_2)\n",
    "N_H2_l = N_Sp/Ab_Sp\n",
    "M_H2_l = A_l*N_H2_l*m_H2.to(u.M_sun)\n",
    "M_H2=M_H2_l*(r_d/r_l)**2\n",
    "print(Ab_Sp)\n",
    "print(N_H2_l)\n",
    "print(M_H2_l)\n",
    "print(M_H2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Escape velocity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "M = 1*u.solMass\n",
    "r_min=0.1#arcsec\n",
    "r_max=6#arcsec\n",
    "d=300 #pc\n",
    "rad = [r*u.au for r in np.arange(r_min*d,r_max*d)] \n",
    "vel = [par.EscapeVel(M,r) for r in rad]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2999105224802598"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "par.EscapeVel(M,3.5*d*u.au).value/1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_au = [r.value for r in rad]\n",
    "x_arc = np.array(x_au)/d\n",
    "y = [v.value/1000 for v in vel] #en km/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.1, 7.690374361883924),\n",
       " (0.10333333333333333, 7.565319290061013),\n",
       " (0.10666666666666667, 7.4461729574192335),\n",
       " (0.11, 7.332484251349767),\n",
       " (0.11333333333333333, 7.223848849425254),\n",
       " (0.11666666666666667, 7.119903159007647),\n",
       " (0.12, 7.020319189438705),\n",
       " (0.12333333333333334, 6.924800191824539),\n",
       " (0.12666666666666668, 6.833076934213858),\n",
       " (0.13, 6.744904505563475),\n",
       " (0.13333333333333333, 6.660059562004021),\n",
       " (0.13666666666666666, 6.578337944840474),\n",
       " (0.14, 6.4995526124013),\n",
       " (0.14333333333333334, 6.423531838007715),\n",
       " (0.14666666666666667, 6.350117634518218),\n",
       " (0.15, 6.279164372532468),\n",
       " (0.15333333333333332, 6.210537564735628),\n",
       " (0.15666666666666668, 6.144112793279897),\n",
       " (0.16, 6.079774760729298),\n",
       " (0.16333333333333333, 6.017416448090319),\n",
       " (0.16666666666666666, 5.956938365935386),\n",
       " (0.17, 5.898247886694407),\n",
       " (0.17333333333333334, 5.841258647918086),\n",
       " (0.17666666666666667, 5.785890017766624),\n",
       " (0.18, 5.732066615198008),\n",
       " (0.18333333333333332, 5.679717878361161),\n",
       " (0.18666666666666668, 5.628777675573039),\n",
       " (0.19, 5.579183954001723),\n",
       " (0.19333333333333333, 5.530878421811131),\n",
       " (0.19666666666666666, 5.4838062600648305),\n",
       " (0.2, 5.437915861151291),\n",
       " (0.20333333333333334, 5.3931585908926145),\n",
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       " (3.31, 1.3366985734681662),\n",
       " (3.3133333333333335, 1.336026020684223),\n",
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       " (3.33, 1.33267841827809),\n",
       " (3.3333333333333335, 1.3320119124008043),\n",
       " (3.3366666666666664, 1.331346405533181),\n",
       " (3.34, 1.3306818951820591),\n",
       " (3.3433333333333333, 1.3300183788629794),\n",
       " (3.3466666666666667, 1.3293558541001451),\n",
       " (3.35, 1.3286943184263846),\n",
       " (3.3533333333333335, 1.328033769383112),\n",
       " (3.3566666666666665, 1.3273742045202879),\n",
       " (3.36, 1.3267156213963829),\n",
       " (3.3633333333333333, 1.3260580175783387),\n",
       " (3.3666666666666667, 1.3254013906415303),\n",
       " (3.37, 1.324745738169729),\n",
       " (3.3733333333333335, 1.324091057755064),\n",
       " (3.3766666666666665, 1.3234373469979865),\n",
       " (3.38, 1.3227846035072326),\n",
       " (3.3833333333333333, 1.322132824899785),\n",
       " (3.3866666666666667, 1.3214820088008383),\n",
       " (3.39, 1.320832152843762),\n",
       " (3.3933333333333335, 1.3201832546700647),\n",
       " (3.3966666666666665, 1.3195353119293574),\n",
       " (3.4, 1.3188883222793175),\n",
       " (3.4033333333333333, 1.3182422833856549),\n",
       " (3.4066666666666667, 1.3175971929220753),\n",
       " (3.41, 1.3169530485702452),\n",
       " (3.4133333333333336, 1.3163098480197573),\n",
       " (3.4166666666666665, 1.3156675889680949),\n",
       " (3.42, 1.3150262691205978),\n",
       " (3.4233333333333333, 1.314385886190429),\n",
       " (3.4266666666666667, 1.3137464378985377),\n",
       " (3.43, 1.3131079219736281),\n",
       " ...]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[i for i in zip(x_arc,y)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(figsize=(20, 10))\n",
    "rc('ytick', labelsize=20)\n",
    "rc('xtick', labelsize=20)\n",
    "ax1.set_yticks(np.arange(0,max(y),0.5))\n",
    "ax1.set_yticks(np.arange(0,max(y)+1,0.1),minor=True)\n",
    "ax1.set_xlabel('Radius (arcsec)', fontsize=20)\n",
    "ax1.set_xticks(np.arange(0,max(x_arc)+1,0.1),minor=True)\n",
    "ax1.set_ylabel('Escape Velocity (km/s)', fontsize=20)\n",
    "ax1.plot(x_arc, y)\n",
    "\n",
    "ax2 = ax1.twiny()  # instantiate a second axes that shares the same y-axis\n",
    "\n",
    "ax2.set_xlabel('Radius (AU)', fontsize=20)  # we already handled the y-label with ax1\n",
    "ax2.set_xticks(np.arange(0,max(x_au)+25,25),minor=True)\n",
    "ax2.plot(x_au, y, label='1 Solar Mass; d = 300pc')\n",
    "plt.legend(fontsize=18)\n",
    "\n",
    "fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
    "#plt.show()\n",
    "plt.savefig('escape_vel.png',bbox='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}