SP_viscosity.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt \n",
    "import scipy.signal as sps\n",
    "import pickle\n",
    "# from datetime import datetime as dt\n",
    "import datetime\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "import h5py as h5\n",
    "# %matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import scipy.stats as stats\n",
    "import csv\n",
    "import os\n",
    "import warnings\n",
    "import scipy as sp\n",
    "from scipy.optimize import curve_fit\n",
    "import itertools\n",
    "# %matplotlib notebook\n",
    "sns.set()\n",
    "import matplotlib\n",
    "matplotlib.rcParams.update({'font.size': 22})\n",
    "sns.set(font_scale=2)\n",
    "SPY = 365.25*24*3600"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "sb=True\n",
    "if sb:\n",
    "    sns.set()\n",
    "    sns.set_context('paper', font_scale=1.5, rc={\"lines.linewidth\": 1.5})\n",
    "#     sns.set_context(\"notebook\", font_scale=1.5, rc={\"lines.linewidth\": 2.5})\n",
    "    sns.set_style(\"whitegrid\",{\"xtick.top\":True, \"xtick.bottom\":True,\"ytick.left\":True, \"ytick.right\":True})\n",
    "# plt.style.use('seaborn-notebook')\n",
    "\n",
    "# pd.set_option('display.height', 500)\n",
    "pd.set_option('display.max_rows', 500)\n",
    "mpl.rcParams['axes.formatter.useoffset'] = False\n",
    "mpl.rcParams.update({'figure.autolayout': True})\n",
    "fontsz = 20\n",
    "plt.rc('xtick',labelsize=20)\n",
    "plt.rc('ytick',labelsize=20)\n",
    "plt.rcParams['axes.titlesize'] = 22\n",
    "plt.rcParams[\"axes.labelsize\"] = 22\n",
    "plt.rcParams['figure.figsize'] = [10, 8]\n",
    "palette = sns.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def k_log(L,kL,x0,xa,d,ic):\n",
    "    denom = 1 + np.exp(-kL*(xa - x0))\n",
    "    return L/denom + d*xa + ic \n",
    "\n",
    "def k_log_cf(xa,L,kL,os,rhoc):\n",
    "    denom = 1 + np.exp(-kL*(xa - rhoc))\n",
    "    return L/denom + os\n",
    "\n",
    "def k_log_cf_d(xa,L,kL,os,d,rhoc):\n",
    "    denom = 1 + np.exp(-kL*(xa - rhoc))\n",
    "    return L/denom + d*xa + os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/maxstev/Documents/Grad_School/Research/SouthPole/SP_PotsandTherm_new.py:287: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  viscosity = 0.5 * stress_holebot[ii]/strain_rate\n",
      "/Users/maxstev/Documents/Grad_School/Research/SouthPole/SP_PotsandTherm_new.py:288: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  viscosity_unfilt = 0.5 * stress_holebot[ii]/strain_rate_unfilt\n"
     ]
    }
   ],
   "source": [
    "run SP_PotsandTherm_new.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "run visc_rho_age.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "### load model results  \n",
    "# thenames = ['HLdynamic','Ligtenberg2011','Li2015','Crocus','GSFC2020','MaxSP','Goujon2003']\n",
    "thenames = ['HLdynamic','Ligtenberg2011','Li2015','Crocus','GSFC2020','MaxSP']\n",
    "# thenames = ['MaxSP']\n",
    "# thenames = ['Li2015','MaxSP','Li15B']\n",
    "d = {}\n",
    "d['SP50']={}\n",
    "d['SP50']['MET']={}\n",
    "fdate = '220825'\n",
    "for ii,name in enumerate(thenames):\n",
    "    with open('/Volumes/FirnSSD/CFMresults/USP50_{}/CFM_data_SP50_{}_{}.pkl'.format(fdate,fdate,name),'rb') as f:\n",
    "#     with open('/Volumes/FirnSSD/CFMresults/USP50200306/CFM_data_SP50_200306_{}.pkl'.format(name),'rb') as f:\n",
    "        dtemp=pickle.load(f)\n",
    "        d['SP50']['MET'].update(dtemp['SP50']['MET'])\n",
    "        d['SP50']['MET'][name]['rdaily']['temp_trun'] = d['SP50']['MET'][name]['rdaily']['temperature'][:,::20]\n",
    "        d['SP50']['MET'][name]['rdaily']['dep_trun'] = d['SP50']['MET'][name]['rdaily']['depth'][:,::20]\n",
    "        d['SP50']['MET'][name]['rdaily']['visc_trun'] = d['SP50']['MET'][name]['rdaily']['viscosity'][:,::20]\n",
    "#         d[site][datasource][name][fil]['depth'] = np.tile(d[site][datasource][name][fil]['depth'],(len(d[site][datasource][name][fil]['time']),1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df14D = dfp6.resample('14D').median()\n",
    "diff_visc = df_dc.filter(regex='visc').copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='TIMESTAMP'>"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diff_visc.viscosity12_11.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "### top and bottom depths of virtual holes\n",
    "# htda = [0.25,0.25,4.40,4.42,4.40,4.42,9.750,9.650,9.75,9.65,14.65,15.10,19.53,24.85,29.82,40.16,80.0]\n",
    "# hbda = [4.40,4.42,9.75,9.75,9.65,9.65,14.65,14.65,15.1,15.1,19.53,19.53,24.85,29.82,40.16,80.00,106.0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "midpoints = (np.array(hbda)+np.array(htda))/2\n",
    "resamp = '1W'\n",
    "df_re_ts=df_dc.resample('1d').mean().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.04532608e-09, -1.04346727e-09, -1.04130588e-09, ...,\n",
       "       -4.07333620e-10, -4.07782952e-10, -4.09798731e-10])"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.gradient(dfp4['strain12'],deltat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "TEMPERATURE STUFF\n",
    "In the SP_model notebook, I took the daily precip records, 1/1/2017 - 12/31/18.\n",
    "Converted to snow with density 300. 2017 gave ~30 cm of snow, so used that.\n",
    "2018 also gave ~30 cm, so multiplied the precip values by 1.8 to get a total around 60 cm (observed)\n",
    "These values are then used to adjust the depth of the thermistors.\n",
    "'''\n",
    "dft_monthly = dft5[df_re_ts[0]:df_re_ts[-1]].resample(resamp).mean()\n",
    "n_grid = np.linspace(0,41,329) #165\n",
    "temps_m = dft_monthly.values\n",
    "tm_m = dft_monthly.index.values\n",
    "ro_m, co_m = np.shape(temps_m)\n",
    "depths1_m = np.tile(tdeps.astype(float),(ro_m,1))\n",
    "hc1 = pd.read_pickle('HeightChange.pkl') \n",
    "hc_m = hc1.resample(resamp).mean()\n",
    "depth_adder_m = np.tile(hc_m.values,(co_m,1)).T\n",
    "depth_adder_m = depth_adder_m*1.1\n",
    "depths_m = depths1_m #+ depth_adder_m\n",
    "t_interp_m = np.zeros((ro_m,len(n_grid)))\n",
    "for kkk in range(ro_m): #put the measured temperatures on the grid\n",
    "    tif = sp.interpolate.interp1d(depths_m[kkk,:],temps_m[kkk,:],bounds_error=False,fill_value=\"extrapolate\")\n",
    "    t_interp_m[kkk,:]= tif(n_grid)\n",
    "dataT_m = t_interp_m.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "z1a = 'agemax'\n",
    "z2a = 'agemax'\n",
    "z1r = 'rhomean'\n",
    "z2r = 'rhomean'\n",
    "Q=-60e3\n",
    "n1=1.0\n",
    "n2 = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "### zone 1\n",
    "hole_no = [0,1,12,11,10,9,5]\n",
    "h_ordz1 = np.array([1,12,11,11,10,10,9,9,5,5])\n",
    "holediff_tops = htda[0:10]\n",
    "holediff_bots = hbda[0:10]\n",
    "dcsv1 = ['1','12','1_11','12_11','1_10','12_10','11_9','10_9','11_5','10_5']\n",
    "z1_diff_meanrho = np.array(rmeanlist)[0:10]\n",
    "z1_diff_maxrho = np.array(rmaxlist)[0:10]\n",
    "z1_diff_meanage = np.array(ameanlist)[0:10]\n",
    "z1_diff_maxage = np.array(amaxlist)[0:10]\n",
    "n_grid = np.linspace(0,41,329) #165\n",
    "dvisc_monthly = diff_visc.resample(resamp).median().interpolate()\n",
    "v1_dict={}\n",
    "for jj, hdi in enumerate(dcsv1):\n",
    "    i_up = np.where(n_grid >= holediff_tops[jj])[0][0]\n",
    "    i_down = np.where(n_grid <= holediff_bots[jj])[0][-1]\n",
    "    t_hold = np.mean(dataT_m[i_up:i_down+1,:],axis=0)+273.15\n",
    "    v1_dict[dcsv1[jj]] = pd.DataFrame({'holenum':hdi,'dep':holediff_bots[jj]*np.ones_like(t_hold),'agemean':z1_diff_meanage[jj]*np.ones_like(t_hold),'agemax':z1_diff_maxage[jj]*np.ones_like(t_hold),'visc':dvisc_monthly['viscosity{}'.format(dcsv1[jj])].values,'rhomean':z1_diff_meanrho[jj],'rhomax':z1_diff_maxrho[jj],'T':t_hold,'stress':dfp4['stress_holebot{}'.format(h_ordz1[jj])].mean()})      \n",
    "z1v_df=pd.concat(v1_dict.values(), ignore_index=True)\n",
    "z1v_df['rhoU'] = z1v_df[z1r] #rho to use\n",
    "z1v_df['ageU'] = z1v_df[z1a]*SPY\n",
    "tsl = len(z1v_df[z1v_df.holenum=='1']) #time series length\n",
    "\n",
    "#option to drop certain data\n",
    "z1drop = False\n",
    "if z1drop:\n",
    "    ### Drop the 11 holes\n",
    "    z1v_df.drop(np.concatenate((z1v_df.index[tsl*2:tsl*4].values,z1v_df.index[tsl*6:tsl*7].values,z1v_df.index[tsl*8:tsl*9].values)),axis=0,inplace=True)    \n",
    "    ### Drop the 10 holes\n",
    "#     z1v_df.drop(np.concatenate((z1v_df.index[tsl*4:tsl*6].values,z1v_df.index[tsl*7:tsl*8].values,z1v_df.index[tsl*9:].values)),axis=0,inplace=True)    \n",
    "\n",
    "z1v_df['term'] = z1v_df['ageU']**n1/((917-z1v_df['rhoU'])*np.exp(Q/(8.314*z1v_df['T'])))\n",
    "# z1v_df['term'] = z1v_df['ageU']**n1/((917-z1v_df['rhoU'])*np.exp((Q/(8.314*z1v_df['T']))+(42.2e3/(8.314*222.15))))\n",
    "z1v_df['k'] = z1v_df['visc']/z1v_df['term']\n",
    "z1v_df['arrT'] = np.exp(Q/(8.314*z1v_df['T']))\n",
    "z1v_df['modvisc']=z1v_df['k'].median()*z1v_df['ageU']**n1/((917-z1v_df['rhoU'])*np.exp(Q/(8.314*z1v_df['T'])))\n",
    "z1v_df['drho'] = 0.5*z1v_df['rhoU']*z1v_df['stress']/z1v_df['visc']*SPY\n",
    "z1v_df['moddrho'] = 0.5*z1v_df['rhoU']*z1v_df['stress']/z1v_df['modvisc']*SPY\n",
    "z1v_df['difper']=((z1v_df['drho']-z1v_df['moddrho'])/z1v_df['drho'])*100\n",
    "\n",
    "### Zone 2\n",
    "### To run this, you first need to run cells towards bottom to generate the rmeanlist, etc\n",
    "h_ordz2 = np.array([7,7,8,4,3,2,6])\n",
    "holediff_tops = htda[10:]\n",
    "holediff_bots = hbda[10:]\n",
    "dcsv2 = ['9_7','5_7','7_8','8_4','4_3','3_2','2_6']\n",
    "z2_diff_meanrho = np.array(rmeanlist)[10:]\n",
    "z2_diff_maxrho = np.array(rmaxlist)[10:]\n",
    "z2_diff_meanage = np.array(ameanlist)[10:]\n",
    "z2_diff_maxage = np.array(amaxlist)[10:]\n",
    "\n",
    "### Use monthtly\n",
    "# n_grid = np.linspace(0,41,329) #165\n",
    "# dvisc_monthly = diff_visc.resample(resamp).median()\n",
    "v2_dict={}\n",
    "for jj, hdi in enumerate(dcsv2):\n",
    "    try:\n",
    "        i_up = np.where(n_grid >= holediff_tops[jj])[0][0]\n",
    "        i_down = np.where(n_grid <= holediff_bots[jj])[0][-1]\n",
    "        t_hold = np.mean(dataT_m[i_up:i_down+1,:],axis=0)+273.15\n",
    "    except:\n",
    "        t_hold = 222.15\n",
    "    v2_dict[dcsv2[jj]] = pd.DataFrame({'holenum':hdi,'dep':holediff_bots[jj]*np.ones_like(t_hold),'agemean':z2_diff_meanage[jj]*np.ones_like(t_hold),'agemax':z2_diff_maxage[jj]*np.ones_like(t_hold),'visc':dvisc_monthly['viscosity{}'.format(dcsv2[jj])].values,'rhomean':z2_diff_meanrho[jj],'rhomax':z2_diff_maxrho[jj],'T':t_hold,'stress':dfp4['stress_holebot{}'.format(h_ordz2[jj])].mean()})      \n",
    "z2v_df=pd.concat(v2_dict.values(), ignore_index=True)\n",
    "z2v_df['rhoU'] = z2v_df[z2r]\n",
    "z2v_df['ageU'] = z2v_df[z2a]*SPY\n",
    "\n",
    "### Use just the median for all time\n",
    "# dvisc_Z2 = diff_visc.median()[10:]\n",
    "# d_Z2_shb = [dfp4['stress_holebot{}'.format(kk)].mean() for kk in h_ordz2]\n",
    "# t_hold = 222.15\n",
    "# z2v_df = pd.DataFrame({'holenum':dcsv2,'dep':holediff_bots,'agemean':z2_diff_meanage,'agemax':z2_diff_maxage,'visc':dvisc_Z2.values,'rhomean':z2_diff_meanrho,'rhomax':z2_diff_maxrho,'T':t_hold*np.ones_like(z2_diff_maxage),'stress':d_Z2_shb})      \n",
    "### Add an extra row with fixed viscosity\n",
    "# z2v_df = z2v_df.append(z2v_df.iloc[-1])\n",
    "# z2v_df['visc'].iloc[-1] = 3.9e16\n",
    "\n",
    "z2v_df['term'] = z2v_df['ageU']**n2 / ((917-z2v_df['rhoU'])*np.exp(Q/(8.314*z2v_df['T'])))\n",
    "# z2v_df['term'] = z2v_df['ageU']**n2/((917-z2v_df['rhoU'])*np.exp((Q/(8.314*z2v_df['T']))+(42.2e3/(8.314*222.15))))\n",
    "z2v_df['k'] = z2v_df['visc']/z2v_df['term']\n",
    "z2v_df['arrT'] = np.exp(Q/(8.314*z2v_df['T']))\n",
    "# z2v_df['modvisc']=z2v_df['k'].mean()*0.5*z2v_df['rho']*z2v_df['age']/((917-z2v_df['rho'])*np.exp(Q/(8.314*z2v_df['T'])))\n",
    "z2v_df['modvisc']=z2v_df['k'].mean()*z2v_df['ageU']**n2/((917-z2v_df['rhoU'])*np.exp(Q/(8.314*z2v_df['T'])))\n",
    "z2v_df['drho'] = 0.5*z2v_df['rhoU']*z2v_df['stress']/z2v_df['visc']*SPY\n",
    "z2v_df['moddrho'] = 0.5*z2v_df['rhoU']*z2v_df['stress']/z2v_df['modvisc']*SPY\n",
    "z2v_df['difper']=((z2v_df['drho']-z2v_df['moddrho'])/z2v_df['drho'])*100\n",
    "\n",
    "visc_df = pd.concat((z1v_df,z2v_df),ignore_index=True)\n",
    "# if Q==-60e3:\n",
    "#     visc_df.loc[visc_df['k']>10000,['visc','k','term','arrT','modvisc']] = np.nan #100\n",
    "# elif Q==-55e3:\n",
    "#     visc_df.loc[visc_df['k']>1500,['visc','k','term','arrT','modvisc']] = np.nan\n",
    "# elif Q==-50e3:\n",
    "#     visc_df.loc[visc_df['k']>20000,['visc','k','term','arrT','modvisc']] = np.nan\n",
    "# if Q==-65e3:\n",
    "#     visc_df.loc[visc_df['k']>8,['visc','k','term','arrT','modvisc']] = np.nan\n",
    "# if Q==-70e3:\n",
    "#     visc_df.loc[visc_df['k']>0.6,['visc','k','term','arrT','modvisc']] = np.nan\n",
    "# print('CHECK THAT THE K CUTOFF IS CORRECT! (LINE 88)')\n",
    "# visc_df[np.abs(visc_df.k-visc_df.k.median()) <= (2*visc_df.k.std())]\n",
    "\n",
    "# di = {}\n",
    "# for ii in visc_df.holenum.unique():\n",
    "#     di[ii] = visc_df[visc_df.holenum==ii][np.abs(visc_df[visc_df.holenum==ii].k-visc_df[visc_df.holenum==ii].k.median()) <= (1.*visc_df[visc_df.holenum==ii].k.std())]   \n",
    "# visc_df = pd.concat(di.values(), ignore_index=True)\n",
    "\n",
    "### Figure out the median value of k for the shallow holes\n",
    "if z1drop:\n",
    "    l2 = 6\n",
    "else:\n",
    "#     l2 = 10\n",
    "    l2 = 17 # this is all the holes: len(visc_df.holenum.unique())\n",
    "kmed = np.array([visc_df.iloc[tsl*kk:tsl*(kk+1)]['k'].median() for kk in range(l2)])\n",
    "krho = np.array([visc_df.iloc[tsl*kk:tsl*(kk+1)]['rhoU'].median() for kk in range(l2)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "for hn in visc_df['holenum'].unique():\n",
    "    xx = visc_df.loc[visc_df['holenum']==hn,'k'].values\n",
    "    ulim = np.nanpercentile(xx,75)\n",
    "    dlim = np.nanpercentile(xx,25)\n",
    "    xx[xx>ulim] = np.nan\n",
    "    xx[xx<dlim] = np.nan\n",
    "    visc_df.loc[visc_df['holenum']==hn,'k'] = xx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Fit curves to k data\n",
    "xa = np.arange(300,801) #sample density for fitting\n",
    "# rhodata = np.concatenate((krho,visc_df.iloc[-7:-2]['rhoU'].values))\n",
    "# kdata = np.concatenate((kmed,visc_df.iloc[-7:-2]['k'].values))\n",
    "viscdata = visc_df['visc'].values[np.where(~np.isnan(visc_df.k.values))[0]]\n",
    "VTdata = visc_df['visc'].values[np.where(~np.isnan(visc_df.k.values))[0]] * visc_df['T'].values[np.where(~np.isnan(visc_df.k.values))[0]]\n",
    "VarrTdata = visc_df['visc'].values[np.where(~np.isnan(visc_df.k.values))[0]] * visc_df['arrT'].values[np.where(~np.isnan(visc_df.k.values))[0]]\n",
    "rhodata = visc_df['rhoU'].values[np.where(~np.isnan(visc_df.k.values))[0]]\n",
    "kdata = visc_df['k'].values[np.where(~np.isnan(visc_df.k.values))[0]]\n",
    "if Q==-60e3:\n",
    "    p0g=np.array([30,0.1,5,510])\n",
    "elif Q==-55e3:\n",
    "    p0g=np.array([600,0.1,5,510])\n",
    "elif Q==-50e3:\n",
    "    p0g=np.array([7000,0.03,1000,510])\n",
    "elif Q==-65e3:\n",
    "    p0g=np.array([2,0.03,0.5,510])\n",
    "elif Q==-70e3:\n",
    "    p0g=np.array([2,0.03,0.5,510])\n",
    "elif Q==-40e3:\n",
    "    p0g=np.array([1e6,5e-2,4e5,510])\n",
    "# p0g_d=np.array([1e4,0.1,4e3,0.,550])\n",
    "\n",
    "p0g_d=np.array([20,0.1,10,1,510])\n",
    "popt, pcov = curve_fit(k_log_cf, rhodata, kdata,p0=p0g)#,method='dogbox')#, bounds = ([0.,0,5,500],[45,0.2,10,600]))\n",
    "\n",
    "# popt, pcov = curve_fit(k_log_cf, rhodata, kdata,p0=p0g, bounds = ([0.,0,10,500],[45,0.2,20,600]))\n",
    "\n",
    "# poptd9, pcovd9 = curve_fit(k_log_cf_d, rhodata, kdata,p0=p0g_d, bounds = ([0.,3.95e-2,10,0,500],[30,1,12,0.01,512]))\n",
    "# poptd9, pcovd9 = curve_fit(k_log_cf_d, rhodata, kdata,p0=p0g_d, bounds = ([0.,0.0,10,0,500],[30,1,12,12,570])) #\n",
    "### Use the following with the Arthern way\n",
    "# p0g_d=np.array([3e11,0.1,0.5e11,100.,550])\n",
    "# poptd, pcovd = curve_fit(k_log_cf_d, rhodata[0:16], kdata[0:16],p0=p0g_d, bounds = ([2e11,0.0,1e10,90,549.9],[4e11,1,1e11,300,550]))\n",
    "# poptc, pcovc = curve_fit(k_cub, rhodata, kdata,p0=p0g_c)#, bounds = ([0.,0.1,0,0],[35,0.2,11,0.1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([9.52224335e-07, 4.10522810e-02, 2.81958855e-07, 5.15634476e+02])"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots(figsize=(12,8))\n",
    "a1.scatter(rhodata,kdata,label='visc data',color=palette[0])\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd8[0],poptd8[1],poptd8[2],poptd8[3],poptd8[4]),label = '8')\n",
    "L5,kL5,os5,d5,rhoc5 = 22.13, 3.95e-02, 1.00000000e+01, 0 ,511.2 #Set cutoff to 60 for K values.        \n",
    "kM5 = k_log_cf_d(xa,L5,kL5,os5,d5,rhoc5)\n",
    "a1.plot(xa,k_log_cf(xa,popt[0],popt[1],popt[2],popt[3]),label = 'cf',color=palette[3])\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd9[0],poptd9[1],poptd9[2],poptd9[3],poptd9[4]),label = '9')\n",
    "# a1.plot(xa,kM5,label='CFM')\n",
    "a1.set_xlabel('Density (kg m$^{-3}$)')\n",
    "a1.set_ylabel('$K$ (kg$^{2}$ m$^{-4}$ s$^{-2}$)')\n",
    "# a1.set_ylim(0,100)\n",
    "# a1.legend()\n",
    "f1.savefig(f'/Users/maxstev/Documents/Grad_School/Manuscripts/Stevens_SPfirn/texfigures/K_derive_Q{int(abs(Q/1000))}.eps');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# a1.plot(xa,k_log_cf(xa,44,3.3284e-2,9.65,542.8),label = 'works pretty well')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd1[0],poptd1[1],poptd1[2],poptd1[3],poptd1[4]),label = '1')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd2[0],poptd2[1],poptd2[2],poptd2[3],poptd2[4]),label = '2')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd3[0],poptd3[1],poptd3[2],poptd3[3],poptd3[4]),label = '3')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd4[0],poptd4[1],poptd4[2],poptd4[3],poptd4[4]),label = '4')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd5[0],poptd5[1],poptd5[2],poptd5[3],poptd5[4]),label = '5')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd6[0],poptd6[1],poptd6[2],poptd6[3],poptd6[4]),label = '6')\n",
    "# a1.plot(xa,k_log_cf_d(xa,poptd7[0],poptd7[1],poptd7[2],poptd7[3],poptd7[4]),label = '7')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "# curve_fit(lambda t,a,b: a*numpy.exp(b*t),  x,  y,  p0=(4, 0.1))\n",
    "def logfun(xa,a,b,c):\n",
    "    return a*b**(xa*c)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "be, ce = 0.9,0\n",
    "vco, vcod = curve_fit(logfun, rhodata, VarrTdata,p0=(1,be,ce))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pot_length_unfilt1    0.082761\n",
       "hole_length1          0.082761\n",
       "dtype: float64"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfp6[['pot_length_unfilt1','hole_length1']].iloc[0]-dfp6[['pot_length_unfilt1','hole_length1']].iloc[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2a7fff5e0>"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots(figsize=(12,8))\n",
    "a1.scatter(rhodata,VarrTdata,label='visc data',color=palette[-2])\n",
    "# a1.scatter(rhodata,viscdata,label='visc data',color=palette[-2])\n",
    "# a1.plot(xa,logfun(xa,*vco))\n",
    "a1.set_xlabel('density')\n",
    "a1.set_ylabel('viscosity')\n",
    "# a1.set_ylim(0,100)\n",
    "a1.set_yscale('log')\n",
    "a1.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.3140193990966358e-07\n",
      "7.267220005598864e-07\n"
     ]
    }
   ],
   "source": [
    "print(kdata[:12].mean())\n",
    "print(kdata[12:].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "repmids=np.tile(midpoints,(tsl,1)).flatten('F')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'viscosity')"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots(figsize=(8,8))\n",
    "zzz = 'agemean'\n",
    "a1.scatter(visc_df[zzz],visc_df['visc'])\n",
    "# a1.set_xlabel(z2r)\n",
    "# a1.scatter(repmids,visc_df['visc'])\n",
    "# a1.set_yscale('log')\n",
    "a1.set_xlabel(zzz)\n",
    "a1.set_ylabel('viscosity')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'k')"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AAICtEF4AAICtEF4AAICtEF4AJIRKr0+byqrYnA7oApiwC8D2OB4A6FroeQFgaxwPAHQ9hBcAtsbxAEDXQ3gBYGscDwB0PYQXALbG8QBA18OEXQC2x/EAQNdCeAGQEDgeAOg6CC8AEsLmrdUq2VWrwoGZGjk0x+rmADAQ4QWA7T3y0ifaUFrV+uexw3rrodkXWNgiAEZiwi4AW9u8tToiuEjShtIqbd5abVGLABiN8ALA1kp21Uatl8aoA7A/wgsAWyscmBm1PixGHYD9EV4A2NrIoTkaO6x3RG1cYW8m7QIJjAm7AGzvodkXaPPWapXuqtUwVhsBCY/wAiAh5GSmyR8MKyczzeqmADAY4QWA7a1YXa7lq8oVDIXlcjo0dWKepkzIs7pZAAzCnBcAtlbp9Wn5qnLV1ftV3xhQXb1fy1eVq9LLqdJAoiK8ALC1fTU+BUPhiFooFNb+GsILkKgILwBsLTfbI5fTEVFzOh3qm805R0CiIrwAsLU+WR5NnZin7mlueVKT1D3NrWmT8jikEUhgTNgFYHtTJuRp/Khc7a/xqW82p0sDiY7wAiAh9MkitABdBcNGAADAVggvAADAVggvAADAVggvAADAVggvAADAVggvAADAVuJmqXR1dbWKi4u1Zs0aeb1e9ejRQxdccIF++tOfqn///id8/sGDB/Xcc8/pww8/lNfr1VlnnaX//M//1BVXXGFC6wEAgFniIrxUV1dr2rRp2r9/v7773e/qiiuu0I4dO/TWW2/po48+0rJlyzRo0KCYz6+vr9ctt9yir7/+Wpdffrn69u2r9957T3fffbe+/fZb3XjjjeZ9MwAsUen1aV+NT7lsUgckvLgIL8XFxdq/f7/uu+8+/eQnP2mtv/nmm7rnnnv061//Ws8//3zM5y9cuFBbtmzRgw8+qFmzZkmS7rjjDt1www16+umndfnllysrK8vw7wOANVasLtfyVeUKhsJyOR2aOjFPUybkWd0sAAaJizkv77//vnr16qWbb745on711VdrwIAB+vjjjxUKhWI+f+nSpcrOztYNN9zQWktPT9dtt92mhoYG/fWvfzWs7QCsVen1afmqctXV+1XfGFBdvV/LV5Wr0sup0kCisjy8BINBzZkzR3PnzpXT2bY5ycnJ8vv98vv9UZ+/e/duHThwQEVFRXK5XBHXzj//fEnS+vXrO7/hAOLCvhqfgqFwRC0UCmt/DeEFSFSWDxu5XK42PS4ttm3bpu3bt2vAgAFKSUmJ+pjdu3dLkgYMGNDmWk5OjlJSUrRz585Oay+A+JKb7ZHL6YioOZ0O9c1m3guQqCzveYklFArpscceUygU0vXXXx/zcQcPHpQkZWRkRL2enp6uuro6I5oIIA70yfJo6sQ8dU9zy5OapO5pbk2blMekXSCBWd7zEk04HNaDDz6oTz75RCNGjIjZMyNJgUBA0tHhpWiSk5PV0NDQpl5cXKwFCxZE1JYuXaqSkpLTaLl1Ghsbbdt2cP9OV2Ef6Y4r+8l72K+sDLeyMgKm/jy5f/bFvYsfBQUFEX+eO3eu5s2bF/WxcRdeAoGAHnjgAa1YsUL9+/fXb3/725jBRFLrcFJzc3PU683NzUpLS2tTnzdvXpsfysaNG1VYWHgarbdOSUmJbdsO7l9nqPT6lGbRUmnun31x7+LDxo0bVVZWdtKPj6vw0tDQoJ/+9Kdas2aNBg0apJdffllnnHFGu8/p0aOHJOnIkSNRrx85coRl0kCCY6k00LXEzZyXQ4cO6eabb9aaNWs0fPhwLV26VLm5uSd8XsvmdRUVFW2uVVVVqampSYMHD+7s5gKIEyyVBrqeuAgvTU1NmjNnjr788kudd955WrRo0Un3luTm5io3N1cbN25ssxfMunXrJEljxozp9DYDiA8slQa6nrgIL/Pnz9fnn3+uMWPG6KWXXlJ6evopPf/qq69WZWWlFi9e3Fo7cuSInn/+eaWmpuqaa67p7CYDiBMslQa6HsvnvFRXV2vJkiWSpCFDhuill16K+rhbb71VKSkpKi4ulqSIybazZ8/Wu+++q8cff1zr169X//799d5772nPnj164IEH1KtXL+O/EQCWaFkqvXxVuUKhsJxOB0ulgQRneXj58ssvW3fP/eMf/xjzcTfffLNSUlJalzcfG17S09O1ZMkSzZ8/X6tXr9ZHH32kIUOGaP78+Zo8ebKx3wAAy02ZkKfxo3K1v8anvhzMCCQ8y8PLxRdffErLo2I9Njs7W0888URnNQuAzfTJIrQAXUVczHkBAAA4WYQXAABgK4QXAABgK4QXAABgK4QXAABgK4QXAAmh0uvTprIqjgUAugDLl0oDwOniYEaga6HnBYCtcTAj0PUQXgDYGgczAl0P4QWArXEwI9D1EF4A2FrLwYzd09zypCape5qbgxmBBMeEXQC2x8GMQNdCeAGQEDiYEeg6GDYCAAC2QngBAAC2QngBgNNQ6fXpmwof+8oAJmLOCwB0UMvOvn5/UMvWVrGzL2ASel4AoAOO3dm30R9iZ1/ARIQXAOgAdvYFrEN4AZAQzD5Vmp19Aesw5wWA7VlxqnTLzr4tc17cbhc7+wImIbwAsLVj5560WL6qXONH5RoeJFp29v1sU4nOP7eQ4AKYhGEjALa2r8anxuZARK2xOWDa3JM+WR7ln8nuvoCZCC8AbM3tcsgfiJw46w+EleRyxHgGALsjvACwNX8wLHdS5FuZO8mpQDAc4xkA7I7wAsDWcrM9Sk12RdRSk12s+gESGOEFgK21rPrpnuaWJzVJ3dPcrPoBEhyrjQDYXsuqn/01PvXNZvIskOjoeQGQMJjlAnQN9LwAsD0rNqlr0XKqdGZvHz0+gEkILwBszcpN6lasLtfr73+jZn9Qr314QNdfnM+p0oAJGDYCYGtWHZBY6fVp6cpS+RoD8gfD8jUGtHRlKadKAyYgvACwtdxsj4LBUEQtEAwbvlT6q+1eNfkjX7fJH9KW7V5DXxcA4QVAQjJ+6m6s/XsdbOwLGI7wAsDW9tX45HJFvpUluZyGDxudPSRLKe7I101xuzR8cJahrwuA8ALA5nKzPXI5I7s7nE6H4cNGfbI8mnnpMHm6ueVOcsjTza1ZlxWw4ggwAauNANhayw67y1eVKxQKy+l0mLbDbsvmeJ9tKtH55xYSXACTEF4A2J6VO+z2yfIo/0x29QXMRHgBkBD6ZBEggK6COS8AAMBWCC8AAMBWCC8AAMBWCC8AAMBWCC8AcBpaTpXmTCPAPKw2AoAOWrG6XMtXlcvvD2rZ2ipNnZjHqdKACeh5AZAQNm+t1usffKPNW6tNeb1Kr0/LV5Wrrt6vRn9IdfV+LV9VTg8MYAJ6XgDY3iMvfaINpVWtfx47rLcemn2Boa+5r8anYCjyAMhQKKz9NT72mwEMRs8LAFvbvLU6IrhI0obSKsN7YKw6UwkA4QWAzZXsqo1aL41R7ywtZyp1T3Mr1e1U9zS3aWcqAV0dw0YAbK1wYGbU+rAY9c7EwYyANeh5AWBrOZlpch33TuZyOpSTmWbK63MwI2A+wgsAW9tX41NKcmQncmqyS/trWPUDJCrCCwBby832KBgMRdQCwbBpE2fZpA4wH3NeACSg8Ikf0gnYpA6wBj0vAGxtX41Px223olBYhg8bsUkdYB3CCwBbc7sc8gcih438gZCSXI4Yz+gc+2p88jX6I2r1jX7m2gAmILwAsDV/MCx3UmRQcSc5FAgaO3RU52tSKDIzKRiSDvuaDH1dAIQXADaXm+1RapvVRkmGT9g9UNsQtV4Vow6g8xBeANhanyyPCgZEbkg3bGCm4fuuWLk5HtDVEV4A2Fql16ey3ZFHAZTuqjV84uzIoTkaO6x3RG1cYW+NHJpj6OsCYKk0AJuz8nTnh2ZfoM1bq7V2fZkuGldAcAFMQs8LAFuz+nTnnMw0nZmdatpxBADoeQFgcy2nOy9fVa5QKCyn02Ha6c5sUgdYg/ACwPZaTnfeX+NT32xzDkk8dpM6SWr0h7R8VbnGj8rlkEbAYIQXAAmhT5a5JztbOdcG6OqY8wIAHWD1XBugKyO8AEAHWLW/DADCCwB0SKXXp83baiJq/9rq5WBGwASEFwDogC3bvWryRx5u1OQP6usdXotaBHQdhBcA6IBYxz6GjT0PEoDiMLwcOHBARUVFeuWVV076OTNmzFBBQUHU/1577TXjGgugyxoxJEsp7si30BS3U2cPybKoRUDXEVdLpX0+n+bNm6cjR46c0vPKy8s1ePBgTZ48uc21ESNGdFbzAKBVnyyPcnp2U0X1v+e45PTsxoRdwARxE1727t2refPmacuWLaf0vIqKCtXV1em6667TvHnzDGodAETavLU6IrhIUkW1T5u3VnPGEWCwuBg2euWVV3TVVVeptLRU3/nOd07puWVlZZKkgoICI5oGAFGV7KqNWi+NUQfQeeIivCxcuFD9+vXT4sWLdc0115zScwkvAKxQODAzan1YjDqAzhMX4eWRRx7Rn//8Z5177rmn/NyysjI5HA5t2rRJ1157rUaPHq2LLrpIjz/+uOrq6gxoLYB4VOn1aVNZlWn7rIwcmqOxw3pH1MYV9mbICDBBXMx5+d73vtfh55aVlSkcDuvZZ5/VpZdeqrFjx2r9+vVauHChPv30U7322mtKT0/vxNYCiDctpzsHQ2G5nA7TTnd+aPYF2ry1WmvXl+micQUEF8AkcRFeOioUCikjI0OFhYV64YUXdMYZZ7TWH374YS1btkzFxcW6//772zy3uLhYCxYsiKgtXbpUJSUlprS9szU2Ntq27eD+nQ7v4WYt+/tu1Tf9e8O4ZX8vVe+0emVlJBv++kmSxg/zKMlfo5KSmhM+HvGFf3vx4/jpH3Pnzo25EMfW4cXpdOr111+PWr/33nv15ptv6m9/+1vU8DJv3rw2P5SNGzeqsLDQsPYaqaSkxLZtB/fvdGwqq5IcFZL+HV4cDqc8PfuqsKB37Cd2Iu6ffXHv4sPGjRtb57CejLiY82IEj8ejQYMGqbq6Wo2NjVY3B4BBrD7defPWaq36wqvNW6tNeT0ANu95OXz4sLZu3arMzEwNHjy4zfXGxkY5nU653W4LWgfADC2nO28orWqtmXW68yMvfdL6uu9u+KfGDuuth2ZfYPjrAl2drXtetmzZohkzZuipp55qc62qqkoVFRUqLCyUy+WyoHUAzFDp9alsd+TeKqW7ag1fdbR5a3VEYJKkDaVV9MAAJrB1eCkqKlJOTo7Wrl2rdevWtdabm5v12GOPye/3a9asWRa2EIDR9tX4FAxFnoYYCoW1v8bY8MImdYB1Tjm8bN++/aQed+DAAd15552n3KD2FBcXq7i4uPXPycnJeuyxx+RwOHTLLbfo5z//uX71q1/pRz/6kd577z1NnjxZU6ZM6dQ2AIgvVs15YZM6wDqnHF5uuukmbdu2rd3HLF26VJMnT9aqVas63LBoFixY0GZ584QJE7RkyRKNHz9eH374oZYtW6akpCQ98MADevrpp+VwOGJ8NQCJoGXOy7HMmPPCJnWAdU55wm5NTY1uuukmvfzyy8rPz4+4tm3bNv3yl7/UF198oXA4rEsuueSUGzRlypSYvSWxllGNHj1aL7744im/FgD7a2/Oi9EBhk3qAGuccs/LQw89pNraWt18882tG/v4/X4tWLBA1157rT7//HP169dPL7zwQsQQDwAYwao5Ly1GDs3RxNFZBBfARKfc8zJjxgylp6fr/vvv13/8x3/o5z//uV555RVt375dSUlJmjNnju644w6lpKQY0V4AiGD1Pi8AzNehfV6uuuoqeTwe3X333XrwwQclSeedd54eeughDRkypFMbCADt6ZPl0dSJeVq+qlyhUFhOp0PTJuWZss8LAGt0eJO6iRMn6sUXX9Ttt9+u5uZm3X777QQXAJaYMiFP40flan+NT32zPQQXIMGdMLw8//zz7V6/4IIL9MEHH+j222/XT37yEyUnRx6Edtttt51eCwHgJPTJsia0VHp9+qbCp8zexk8QBnDUCcPLf//3f0ddbhwOhyPqDQ0N+u1vf9taa7lOeAFghkqvT/tqfMo1sedlxepyLV9VLr8/qGVrqzR1Yp6mTMgz5bWBruyE4eXOO+9krxQAca0lRARDYbmcDlNCRKXXp+WrylVX75ckNfpDWr6qXONH5dIDAxjshOFl3rx5ZrQDADrk+BAhyZQQsa/Gp8bmQEStsTmg/TUMHwFGs/XZRgBg1T4vbpdD/kDk6/oDYSW56KkGjEZ4AWBrudkeBYOhiFogGDZ8nxd/MCznce+gLufR1wZgLMILgARkfIBwuxwKRWYmBUOi5wUwAeEFMFil16dNZVWq9JqzXX1Xs6/GJ5cr8q0syeU0fNjIHwzruI195XTQ8wKYocOb1AE4MStWwXQ1Vh0P4HY5dNxUG4XC9LwAZqDnBTDIsatg6hsDqqv3a/mqcnpgOlnL8QDd09zypCape5rblOMBDtQ2RK1XxagD6Dz0vAAGaW8VDEtpO5cVxwPE6l9hW6yO27y1WiW7alU4MJNTutEuwgtgEE47Np+Zs03OHpIll9MREVBdToeGD84ysRWJ45GXPtGG0qrWP48d1lsPzb7AwhbheFbsYh0L4QUwCKcdm2fF6nK9/kG5AoGQkpKcun6SWXOLjo9LTNbtiM1bqyOCiyRtKK3S5q3V9MDEiXibv0d4AQzEacfGq/T6tHRlqZr8R9ctN/mDWrqyzPAddr/a7lUwylLpLdu93OdTVLKrNmq9dFct4SUOWLWLdXsIL4DBrDrtuKvYst3bGlxaNPmD+nqHsSHi8JGmqPVDMeqILSUp+tqR5Bh1mCsej8LgbwYAW4sVFg4aHCIy0lOi1nvEqCO2pkAoar05Rh3misejMAgvAGwtZojwGBsiRgzJUoo78i00xe3U2UOYsHuqCgdmRq0Pi1GHufzBsNzH9YK5k5yWbshIeAFga1aFiD5ZHs28dJg8qUlyuxzypCZp1mXDGCLsgJzMtDYr81xOh3Iy0yxqEY6Vm+2Jspu0tSsnmfMCwNZaQsTr73+jYDAkl8up6ZfkmxIiWiZkf7apROefW0hw6aB9NT45j1t27nQ62BMprlm7so7wAsD2rFzV1SfLo/wzmZR9Oo7OqYic3+IPhDhqIU60nh92zMT4lvPDWG0EAKfBqlVdlV6fvqnwKbM3vQQdFetIheqDHLUQD3KzPWpqDkbUGpuDDBsBgB2tWF2u19//Rs3+oF778ICuvzifgzc7oOJAXdT6nhh1mKu6tr7NUSfBUFjVtfUslQaA01Hp9WlTWZVpB1+2bI7nawzIHwzL1xjQ0pWlHLzZAYfqm6PWD/ui12GudSUHotbXx6ibgZ4XALZnxdblX0XdHC/EDrsdcGZOetR6v97R6zBXZoztCHpauKcRPS8AbO3YrcvrGwOqq/dr+apyw3tAOFW684wflSvXcb+NXE6Hxo/MtaZBiHD0/rRdyj5+lHX3h/ACwNb21fjajMeHQmHtrzE2vJwddX8ZF6dKd0CfLI9uumK4uqUkye1yqltKkm6ezNLzeHH0/hQqLTVJ7iSn0lKtvz8MGwGwtdxsT5tPhU6n8Rtote4v80G5mv0BJbuTNP1iTg3vqCkT8pTXv6dKd9Vq2MBMDmSMM/F2yCzhBYCt9cnyaOrEPC1fVa5QKCyn06Fpk8wJES2/cNeuL9NF4wr4hXsaVqwu1+sflCsQCCkpyanrJxk/bwmnJp4OmSW8ALA9qz4VtvzCbfYH9NGW9fzC7aCWlVstE6Cb/EEtXVmm8aNy4+aXJeILc14AJIQ+WR6NKeht2i+71qXSDX75A2H5GvxaurKMpdIdsCXqyq2gvt7htahFiHeEFwDoAH7hdp5DR5qi1g/GqAOEFwDogFjH0oWtPa/OlmL+yPhZIgbCC4CEYPYOuyOiLpV26uwhLJU+VbE2O+vZ3bpN0BDfmLALwPas2GG3dan0/5xtlOx2afol+Uww7YCzh2TJ5XRE7NfjcjrYMyfOVHp92lfjUy5LpQHg9By7w26L5avKTVmp0rLK6bNNJTr/XDZVOx1JrsjwkuRiq+J4YsUHhPYwbATA1qzaYRedZ1+NT6HjJguFwtzDeGHVERztoecFgK3lZnsUDEau+gkEw4bvsCtF7vPy2poq9nnpILfLIX8gMrz4A2F6X+JEex8QrOptpOcFQAIyfpkK+7x0ngO1DVHrVTHqMJdVR3C0h/ACwNasGnJgn5fOwwnd8a3lCI7uaW55UpPUPc1t2hEcsTBsBMDWrBpyYJ+XztNyQvexYZATuuNLvB3MSM8LAFvzB8NyJ0W+lbmTnAoEjU0R7PPSeVqWnaelJsmd5FRaapJmXVZg+S9IRDL7CI72EF4A2Fputkepya6IWmqyy/Dx+D5ZHuX07BZRy8nsFhdv7HYVDoWlcFjhUJgerDhk9kaQ7WHYCICttYzHL19VrlAoLKfTYcp4/Oat1aqojnwTr6jyafPWao0cmmPoayea40+V9geDWrqylFOl40i87fNCeAFge1aMx6/7+kDU+vqSA4SXU/RV1MnPIW3Z7iW8xAErN4KMhWEjwGDx1NWayMwej8+Mce4O5/GcurKd30atl8aow1zxuBEkPS+AgeKtq9UK8XQeSmcaPypXr7z1dcSqI4ek8SNzrWqSbVXV1ketV8eow1zxuM8L4QUwSDx2tZptxepyvf7+NwoEQ0pyOXX9xfkJFd6cxx0m6HSyMUlH9M5Mi1rPiVGHufpkeVQwIFMbSqtaa8MGZlr6PsawEWCQeOxqNVPrDrSNATX5Q/I1BrR0Zalhw2dmD89t2e5tc3+DoTCb1HVAwaBeUevDYtRhrkqvT2W7ayNqpbtqOdsISETx2NVqJjMnYVrRw3PwSFP0el30OmIbMSRLLqd07BFVLqfYMydOcLYR0IW0dLUey+quVjOZteW72T08LXqmM2G3cx3/F4MhuHgRjx/ECC+AQSq9Pm3eVhNR+9dWb5dZdXR21B1oO3/L9/Z6eIzUO7Nb1PrxG9fhxBiCi2/x+EGM8AIYpKsf3Ney5bunm1spbpc83dyGbPlu1aF+nITceTgnKr4x5wXoQnhDPrp5XF7/nirdVathAzMN2bzNqkP9OAm585wRoxcrVu8WzBWPc14IL4BBRkT9pdq1Du4zY5+blh6e1z8oVyAQUlKSU9MvNv54gLOHZMnpkI59T3c6xEnIHeAPhqP+LI0+XBMnJx7nvBBeAIO0/lJ9/xsFgyG5XE5NvyS/y0zYNXOfGyuOB6iurddxH0YVCh+td5V73FncLkfUn2WSi26seGDV+WHtIbwABrLil2q8MLuruU+WuT/fdSWcbdRZYs0Tqj7I/KF4EW/vZYQXwGBm/1KNF/HY1dyZMmMtlY5RR2zsmWMf8TKQR3gBDJaoZ/ucSDx2NXemvP49T6mO2Bgcin8rVpdHzCu7fpK157QRXgADdfWDGc3sajY7JDLU0XkyYvRW9aAXKy60bATZsvigyR/U0pVllp7TRngBDMLBjP9mdFezFSGRoY7O444xMZcJu/GhvT2rCC9AgonHvRHMZsaZQ1aFRI4H6DxbKw5FrW/be0jfP7e/ya3B8Q7FCuox6mZgh13AIIk+YfVEzDpzyKrTu806/qAraGwORK03NEWvw1wxh/U81gV1wgtgkJYJq93T3PKkJql7mjuhJqyeiFlnDuVme9R03C+/xuag4SGxZR+ftNQkJbmktNQkQ44/6ApSU6IPAnSLUYe5Wk79PpbVp37zNwMwULztjWAms7bPr66tVzAyIykYCpu2WZxDkkMOOdS1jn7oTAcPN0at18aowwoORc5es3Y+Ej0vgMH6ZHk0pqB3lwou0tFPZccPm7mcjk4fVinZVRu1Xhqj3lla5tr4GgPyB8PyNQa0fFV5lzk1vDNt33s4an3Hvuh1mCseT/0mvAAwzPGrRYxYPWLVoX5WzbVJRC5X9LqT31BxIR4PmY27vxoHDhxQUVGRXnnllZN+zsGDB/Xoo49q4sSJOuecczRlyhS9/fbbxjUSOAWVXp82lVV1uU/k+2p8ch03UJ7kcnb6L/fuUSYNOiRlGDyZMDfbo+Bx41WBYLjLTMjuTK4YKSXp+IkWsMSIqJPTrT1kNq7mvPh8Ps2bN09Hjhw56efU19frlltu0ddff63LL79cffv21Xvvvae7775b3377rW688UYDWwy0rytvUhf9l3uo03+5R9sjJCyr9ghh0ktH9M32RF0u3beLDbXGq3g8ZDZuwsvevXs1b948bdmy5ZSet3DhQm3ZskUPPvigZs2aJUm64447dMMNN+jpp5/W5Zdfrqwsli7CfGxSF03nBwp/MCx3kkP+wL+DgzvJoUDQ2CCxr8YnfyAynPkDoS61j09nKRp2hj76Yl/beuEZFrQG0cTb4oO46JN75ZVXdNVVV6m0tFTf+c53Tum5S5cuVXZ2tm644YbWWnp6um677TY1NDTor3/9a2c3FzgpXX1OxL4an4779hUKd/73n5vtUWpy5Oew1OQkw4dv6nxNUb4/6bCPHXZPFXvm2EM8LT6Ii/CycOFC9evXT4sXL9Y111xz0s/bvXt36xwZ13Ezvs4//3xJ0vr16zu1rcDJipdN6qyac+N2OaL2THT2cI5V++kciHG2UawzjxBby7CEp5tbKW6XPN3c7JkTh+Jp/l5cDBs98sgjGj9+vFwul3bu3HnSz9u9e7ckacCAAW2u5eTkKCUl5ZS+HtCZ4uFUZSvn3Jj5y92KLu3CgZlR68Ni1NG+eBuWQKR4m78XF+Hle9/7Xoeed/DgQUlSRkZG1Ovp6emqq6vraLOA02blG7LVc27M2qSuRZ8sc3++OZlpcjkVsUGey3m0jo4x+x7i5Fj9XhJNXISXjgoEjm4JnpycHPV6cnKyGhqif8orLi7WggULImpLly5VSUlJ5zbSJI2NjbZte1eQKqm2yqvaqujXjbh/31T45PcHI2p+f1CfbSpR/pnGv+GkhJqPDh0FIyfSJgdrVVJifbfz6fqmwtcmoDkk036+6By8d56YWe8lBQUFEX+eO3eu5s2bF/Wxtg4vKSlH93Fobm6Oer25uVlpadE/Bc2bN6/ND2Xjxo0qLCzs3EaapKSkxLZtT3SVXp/21fiU207PixH3L7O3T4s+2B9RC8uh888tNO3T0gf/qteG0n8nttF5Obrw/HNMeW2jBdzVCoT2RtZC0pDBA1U4NMeiVuFU8d55Yma8l2zcuFFlZWUn/Xhbh5cePXpIUsx9YY4cOcIyaVgq3saJzdyHpNLrU9nuyC36S3fVqtKbGEuJjy7RdkZMSnYnOQ1fog3EB2v/nsfFaqOOGjRokCSpoqKizbWqqio1NTVp8ODBJrcKOOrYceL6xoDq6v2mnn1j1g637b1+Y3NkV3NjczBhloofXaIducoxNdnFDrtIOFa/l0Rj6/CSm5ur3Nxcbdy4UaFQ5JLMdevWSZLGjBljRdMAy/d5sXqptllLpa1y7BLtVLfTtCXagNmsfi+JxtbhRZKuvvpqVVZWavHixa21I0eO6Pnnn1dqauop7RsDdCar/8Fbtf9Ji5adb49lxs63ZpoyIU/zf/Z93Tipr+b/7Pu69gdd4+gHdC19sjwqGBC5BcCwgZkcD3CyiouLJSliou3s2bP17rvv6vHHH9f69evVv39/vffee9qzZ48eeOAB9erVy6rmoouLh31erFyqnZvtkdPh0LFj406HtZ/WjNAny6P8M1nii8QVj/PXbBVeWpY2Hxte0tPTtWTJEs2fP1+rV6/WRx99pCFDhmj+/PmaPHmyVU0FJMXHxlvxtXdGYgwZAV1Je0PghJf/MWXKFE2ZMiXqtVjLqLKzs/XEE08Y2Sygw+IrPJindZKf/9/zXpJcDg4uBGzG6iHwaGw/5wVAfIrHNzwAp65lCNyTmqQUt1Oe1CTLJ6cTXoAEZ9VhalZPGAbQuUJhKRQ6+r9hi+fdx92wEYDOs2J1uV5//xsFgiEluZy6/uJ8UzfJmzIhT3n9e6p0V62GDczUSHaeBWyn0uvT0pWlavqfIWB/MKSlK0s52whA5zv+DafJb/4bTvztMAzgVH213dv6PtKiyR/Slu1ey8ILw0aAwSq9Pr2/frc+WL/b1KGb9t5wzGD1DsMAOofZJ8SfDHpeAAOtWF2uxe+Wtu40m+J2aualw0zpfdhbVRe1XhGj3tn21fjka/BH1HwNflYbATZz9pAspbidER+GUtwuDR9s3dmB9LwABqn0+rTk3ZKILfKb/CG9/oE5vQ+BUPQZdcfv12CUOl+Tjn+pUFg67Gsy5fUBdI4+WR6NPCs7ojZqaBarjYBEtGW7V82BtkHBHzDncMKh/XpErZ8Vo97ZDtQ2RK1XxagDiE/t7bBrFcILYJBY/RtmbZHf3ZPSZqzaISnDk2L4a0vSGZndotZ7x6gDiE9WHzIbDeEFMMiI/xknPt6VFw4xpbvV7XK0CVBhybRTnf0xDmBMpIMZga4gHjecJLwABumT5dHMS4epW7JLSU4pOcmpqROH6ubJw015fatPdY7HFQoATl08bjjJaiPAYOFj/os5lmSA3GyPUpOT5A/8e8VPanKSaZ+W4nGFAoCOibcNJwkvgEEqvT4tfLukdaw4GApp+eqtkkO6efLZhr9+y6el5avKFQqF5XQ6TP201LJCYUNpVWvN6hUKADrG6t26j0d4AQzyz3/ti7os+a8f7dCl3xlkyi/xKRPyNH5UrvbX+NQ329zTrSu9Pm08JrhI0oaSo2csEWAA+4iH3bqPx5wXwCC1R6LvZxIKhUyfpW/FFNmVn+yMOmF45ac7LWgNgI6yerfuaOh5AQxyXuEZ+vOH29rU3W6XafNOrDxbaF+MgGbl8koAp+5wjA9ihyzccJKeF8AgI4fmaOyw3hE1h6QbLsk3pavV6rOFxo/qG7V+wcjodQDxqa6+OXrdF71uBsILYKKwpH+V15jyWlZvLFUwsFfUTfIKBvYy5fUBdA6rjxqJhvACGGTz1uqIlTYtNpRWafPWasNf3+qNpfbV+JSUFPkWk5TkZNgIsJnzCs+IWh8Xo24GwgtgkHVfH4h5bX1J7GudpWWptKebWylulzzdzN1Yyu1yRBxKKUn+QMi0HX4BdI5oQ+DjCntbutcL4QUwSGb32GcI9WznWqcL/88WeeHw0f9rEqt3+AXQeUYOzVa3lCS5XU51S0nSiONOmTYb4QUwyPhRuXJG6WRwOqXxI3MNf/2WCbu+xoCa/CH5GgOmTtjNzfbIedxZAE6H09LzUACcupb3koamgPzBkBqazH0viYbwAhikT5ZHN08e3uYsn6KC3qYM3eyr8amxORBRa2wOWDznhF4XwG6snvwfDeEFMND4Ubnqlhy5nVLprlpTPrEcnXMS+YbjD4RNm3Oyr8YXdc4LE3YBe7F68n80hBfAQG988I3qmyJ7P8z6xOIPhtsMWzkdMm3OSZ2vScevpAyFpcMWbmwF4NT1yfKoYEBmRG3YwExLj/kgvAAGqfT69I8v97W94DDnE4vb5YgaHszqedlWcShqffve6HUA8anS61PZ7tqImlk9yLEQXgCD7KvxRZ3hcaFJh5lV1TZErVcfjF7vbD1irKjqkW7iSisApy0e588RXgCDRBsn9qQmaeokc84WqjhQF7W+J0a9s+X37xm1nhejDiA+WT1/LhrCC2CQPlke9fAkR9QyM1JMGye2ekvvo/u8RL7FuJOc7PMC2Ew8/lsmvAAG2by1WhXVkd2qFVU+U44GkKTzhlu7pXdutkepya6IWmqyeSdqA+gc8fhvmfACGCTW8QBmHA0gWb+lt9XHEwDoHK3/llOTlOJ2ypOaZPm/ZcILYJBYxwOYejTAccw8HiDyRc0/ngBA5wqHj65YDIctei85BuEFMMj4UblyRfkXVudrNuX1o51qbdaJ1pL1xxMA6ByVXp+WrixVfVNA/kBI9U0BLV1ZxlJpIBH1yfJo+KCsNvW/frTDlH/0f/vHzqj1t/8Zvd7Z4nF5JYBTt2W7V03+yN2ym/xBfb3Da1GLCC+AYSq9PpXsbPuP26x/9AePNEav10Wvd7Z4XF4J4NQdPBJ9V+yDddbtlk14AQzy1Xavjjvap5UZ48VZGalR6716RK93Nn8wrONjikPmHU8AoHP0jLGxpJXz9wgvgEEOx/i04nI6dPaQtsNJnS3luAMhW6TGqHe2Ol9Tmx2Gw+JsI8Buemd2i1rP6Rm9bgbCC2CQjBifVsaP6mvKEsPjd/dt4XSYM2xzIMbxBLGOLQAQn45uUhf5vuFOcrBJHZCIRgzJirra6Ixeaaa8fjDG2FTIpDWOKUnR316SY9QBxKejm9RF9timJiexSR2QqKL1frzzyS5TVhudmZMetd4vRr2zNcWY8NMcayIQgLjUJ8ujggGZEbVhAzPZpA5IRPtqfApG+T3d0Og3ZblwrAMQzToYsXBgZtT6sBh1APGp0utT2e7aiFrprlr2eQESkdvliHoIYihszqRVq+ecWH08AYDOsa/GJ1+DP6LmazDnQ1gs5iw7ALqg9kKCGQEi1rRck+brSpIemn2BNm+tVumuWg0bmElwAWyoztek4z+HmfUhLBbCC2CQWBs7SeYMnZw9JEspbmfEzpgpbpeGDzZ+mfaxRg7NIbQANmZ1L240DBsBBjli0hlGsfTJ8rTZhyEnM5VTnQGckjNi7PMSa/8XMxBeAINUflsf89qHmyoMf/3NW6tVUR05Jl1R5TPtYEYAiaG7J/qeVRkx6mYgvAAG6ZYae1S2vjEQ81pnWf/1gaj1DSXR60ap9Pq0qayK06QBm3LHOI/MynPKmPMCGCQzxg67kpSe5jb89XvEOHekRzvt6mwrVpfr//v7NwoEQkpKcuqGS/I1ZUKeaa8P4PQx5wXoQryHY5/eHIqyhLqz5Vu8z0ul16eFb3+thqaA/MGQGpoCWvh2CT0wgM3Ew8rF4xFeAIOMyY+9wibDk2z465fvORi1btanpX/+a1+bTfqCobD+uXmfKa8PoHPEGh6KdX6aGQgvgEEKBvaKea27weFlxepyLXm3NOo1sz4t7a0+ckp1APGJYSOgC/lquzfmNSN3pqz0+rR0ZWnMM4TMOsbeESMlOWN2QgOIRyyVBrqQw+1sUlddG3sZ9en6ars3YmO645n1aSktJfp6gLR2VmEBiD81h6LP3/PGqJuB8AIYpK6dTepyMtMMe92ynd+2e92sYaOzzuwRtT6kX/Q6gPh0qC76B7FD7XxAMxrhBTBIe5vUFQ6KPR/mdFW106tj5vEAgWD0FVXRDqsEEL/GDT8jan1sYfS6GQgvgEGq2gkvRs7Sj9WzkeRyaNZlBaYdDxArooTJLoCt5GSmyXVcWnA5je1BPhHCC2CASq9PFVWxV9UYOe+kZ4xN6BwyNzjE4yQ/AKduX41PzuM+cDmdDkMXHpwI4QUwwL4aX8yeB8nYX+CfbN4fte4PhrV0Zalpm8RtKq2KXi+LXgcQn9wuh/yByHc0fyBs6fEAhBfAALnZHvn9wZjXjZyl72v0x7zW5A9pSztLuDvTvhifyqz8tAbg1MXa8DJW3QyEF8AgoXbGaIzcqC29W/sb4Jm1QmD8qL5R6xeMjF4HEJ9qY7xnHGS1EZBYtmz3qr1FNU4D1yvn5pgzIfdEemWknlIdQHw6L8aqonGsNgISy4nmxYZO+IiOizVh12wlu2qj1ktj1AHEp5FDczR2WO+I2rjC3ho5NPb5bUZjq0vAACOGZB1d3RPjupFb5FecYEiqh0nhpnBgZtT6sBh1APHrodkXaPPWapXuqtWwgZmWBheJ8AIYorq2vt2+lfbmw5yujLTYc14cks4eYs4mdS2f1jYcs+rI6k9rADpu5NCcuPn3S3gBDLCu5EC714/fM6Ez9c2OPeclrKPByqyN6uLt0xqAxEB4AQzQ2Bho97qvIfZy5tN1uJ0zlSRpQ8kBU0NEPH1aA5AYmLALGOBE5/cYudHtV+U17V43cqUTAJiB8AIYoIen/b1W+vQy7kyQusb2e1769+lu2GsDgBkIL4ABzjyj/YBwxMBho/4neG0jD4UEADMQXgADnOjMj7oTzEs5HS5n+/+sjTwUEgDMQHgBDLCt4lC71wsH9TLstXPbWW0kcaozAPuLm9VGgUBAixcv1uuvv66Kigrl5ORoypQpuvXWW+V2u0/4/BkzZmjTpk1Rrz388MOaMWNGZzcZiOlES6EH9Mkw7LUH5cb+2k6HlOGJjx14AaCj4ia8PProo1q2bJmKioo0ceJEbdq0Sc8995zKysr03HPPnfD55eXlGjx4sCZPntzm2ogRI4xoMhBTRjsTdt0uR7t7sZyuA+0MC3m6uQ19bQAwQ1yEl02bNmnZsmW69NJL9eyzz8rhcCgcDuu+++7Tn//8Z61evVoTJkyI+fyKigrV1dXpuuuu07x580xsORBde0uhCwZmGrpJXEpS9NHgFLdL0yblmbZBHQAYJS7mvCxZskSSNHfuXDn+Zw8Kh8Oh//qv/5LD4dAbb7zR7vPLysokSQUFBcY2FDhJR+pjT8ideekwQ1+7ZGf0gw9HnpWla3+QZ+hrA4AZ4iK8bNiwQZmZmcrPz4+on3HGGRo0aJDWr1/f7vMJL4g3O/cdjnnt28ONhr521be+qPXDviZDXxcAzGJ5eGlublZlZaUGDBgQ9Xq/fv10+PBhffvttzG/RllZmRwOhzZt2qRrr71Wo0eP1kUXXaTHH39cdXV1RjUdiKmhKfbxAKs37jH0tc+IMSwUqw4AdmN5eDl48KAkqXv36BtrtdTbCyFlZWUKh8N69tlnNXz4cE2bNk29evXSwoULNXPmTB05cqTT2w20p72N4o74jNugTpK+M6JP1Pr5Z0evA4DdWD5hNxA4+gk1OTn66oyWelNT9C7vUCikjIwMFRYW6oUXXtAZZ5zRWn/44Ye1bNkyFRcX6/777494XnFxsRYsWBBRW7p0qUpKSk7r+7FKY2OjbdueiJzB2IHZe/BIm3vVmfdv957oe8zs3rNXJd0I8kbg3599ce/ix/FTP+bOnRtzEY7l4SU1NVWS5PdH/zTa3Hx04mO3btE31nI6nXr99dej1u+99169+eab+tvf/tYmvMybN6/ND2Xjxo0qLCw85e8hHpSUlNi27Ylo75Hd0npv1GspKSlt7lVn3r9127ZIOtCmHnJ15++IQfj3Z1/cu/iwcePG1vmrJ8PyYaP09HQ5nc6YQzstw0WxhpXa4/F4NGjQIFVXV6ux0dhJksCxRgzJinktt7exc08Ox1jpdLjBuCMJAMBMloeX5ORk5ebmqqKiIur1iooKZWZmqmfPnlGvHz58WJs2bdKOHTuiXm9sbJTT6TypXXqBztIny6O8/j2iXsvsnmroa+fmpEet98uOXgcAu7E8vEhSUVGRqqur2wSQAwcOaNeuXRo9enTM527ZskUzZszQU0891eZaVVWVKioqVFhYKJfL1dnNhoUqvT5tKqtSpTf6suB4cOE5/aLW+/U2NkTk9+8ZtZ4Xow4AdhMX4eVHP/qRJOmZZ55RKBSSJIXDYc2fP1/hcFjTp0+P+dyioiLl5ORo7dq1WrduXWu9ublZjz32mPx+v2bNmmVo+2GuFavL9bP5H+qJlz/Tz+Z/qBWry61uUlRZPaL3sGRlGNvz4g+G5T5ul113klOBYHv7/gKAfVg+YVeSxo8fryuuuEJvv/22pk+frvPPP1+ff/65NmzYoEsvvVQ/+MEPWh9bXFwsSa2TbZOTk/XYY49p7ty5uuWWW3TZZZepZ8+e+uc//6lt27Zp8uTJmjJlihXfFgxQ6fVp6cpSNfmPhtwmf0hLV5Zq/KjcuNv2PtbJ0tv3HtL3z+1v2OvmZnuUmuySPxBqraUmuzjTCEDCiIueF0n6zW9+o7vuuku1tbV69dVXVVNTo7vuuktPP/1065EBkrRgwYI2S5wnTJigJUuWaPz48frwww+1bNkyJSUl6YEHHmjzfNjbV9u9rcGlRZM/pC3bo6/ssVKP7tFPb+6Rbuypzn2yPJo6MU/d09zypCape5qbM40AJJS46HmRJLfbrTvvvFN33nlnu4+LtZRq9OjRevHFF41oGuLI4SPR9/s5FKNupe+OytWit79W8Jis5XJK40flGv7aUybkafyoXO2v8alvtofgAiChxE3PC3Ay7DRro0+WRzddMVzdkl1yuxzqluzSzZOHmxYk+mR5NKagN8EFQMKJm54X4GT0jDHk0jPGEI3V6AEBgM5Hzwts5ZPN+6LW//mv6PV4QA8IAHQuwgtsZfO26BNzv4rDCbsAAGMQXmAv4eizXsIhO82GAQCcDsILbCXWqncHf5MBoMvgLR/2EnPPHvbyAYCugvACW0lNjn5GVWoyC+cAoKsgvCBBMOcFALoKwgtspaEpGLXeGKMOAEg8hBfYS4zVRk3+gMkNAQBYhfACW/EHQ1HrgeDRE6cBAImP8AJbcTlj/5V94pXPTGwJAMAqhBfYysSx/WNe27GvzsSWAACsQniBrdx+3TlWNwEAYDHCCwAAsBXCCwAAsBXCCwAAsBXCCwAAsBXCC2zHGeMMxlh1AEBiIbzAdjLSkqPXPdHrAIDEQniB7SQlRe9iSXLR9QIAXQHhBbbT0Bj9EMZYdQBAYiG8wHZ6ZkQfHuqZkWJySwAAViC8wHZm/HBYjHqByS0BAFiB8ALb+f65/XVmjieidmZvj75/buxzjwAAiSPJ6gYAHfH/3nex1mzaoy++qdbo/ByCCwB0IYQX2Nb3z+1PaAGALohhIwAAYCuEFwAAYCsMGxls89ZqleyqVeHATI0cmmN1cwAAsD3Ci4EeeekTbSitav3z4L7d9dzPJ1rYIgAA7I9hI4Ns3lodEVwkacf+Ot3y2EqLWgQAQGIgvBikZFdt1Hr1wUat2bTH5NYAAJA4CC8G+ceXFTGvrd5IeAEAoKMILwbZvrcu5jWHOP0YAICOIrxYYFDfDKubAACAbRFeLFC2J/p8GAAAcGKEFwts2ea1ugkAANgW4cUCobDVLQAAwL4ILwYZNqin1U0AACAhEV4M8v/M+77VTQAAICERXgwUa0E0C6UBAOg4wouBMtKTo9Z7xKgDAIATI7wYaNrEvKj1qTHqAADgxAgvBrrm+0PVw+OOqPXwuHXN94da1CIAAOwvyeoGJLrFj16hv6zZqo2lVSoa1pvgAgDAaSK8mOCa7w8ltAAA0EkYNgIAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALZCeAEAALbiCIfDYasbES82btxodRMAAOiSioqKTvqxhJcEUVBQoLKyMqubgQ7i/tkb98++uHf2xLARAACwFcILAACwFcILAACwFcJLgpg7d67VTcBp4P7ZG/fPvrh39sSEXQAAYCv0vAAAAFshvMS5p556SgUFBfrss8/aXPvzn/+sH/3oRxo9erQuuugiPfnkk/L5fFG/zocffqjp06drzJgxuuCCC/SLX/xCXq/X6OZ3Oc8884wKCgqi/nf33XdHPJb7F5/efPNNTZ06Veecc44uvPBC3XXXXdqxY0ebx3H/4kesf3PH/nf8eyj3z94YNopj//rXv3TDDTcoGAxq4cKFOv/881uvvfDCC5o/f74KCgp00UUX6ZtvvtGaNWs0ZswYLVy4UMnJya2Pfeutt/S//tf/Uv/+/fXDH/5Q+/fv17vvvqszzzxTf/zjH5WRkWHFt5eQbrvtNv3jH//Qrbfe2uZaXl6eLrvsMkncv3j1zDPP6Pnnn9egQYM0ceJEHThwQO+++67S09O1YsUKnXnmmZK4f/GmuLg4at3r9eq1115TVlaW/vKXvygnJ0cS9y8hhBGXmpqawldeeWU4Pz8/nJ+fH/70009br+3duzc8fPjw8PTp08PNzc2t9f/+7/8O5+fnhxctWtRaO3LkSPi8884LT5o0KVxXV9daf+ONN8L5+fnhX//61+Z8Q13EhAkTwj/60Y/afQz3Lz59+eWX4YKCgvCNN94YbmhoaK2/88474fz8/PB9990XDoe5f3YyZ86ccH5+fnjt2rWtNe5fYmDYKE49//zz2rFjh8aPH9/m2rJlyxQIBDRnzhy53e7W+m233ab09HS98cYbrbW//e1vOnjwoP7jP/5D6enprfWpU6dq8ODBWrFihYLBoLHfTBdx5MgR7d27VwUFBe0+jvsXn5YsWSJJevTRR5Wamtpav+yyyzR9+nQNGDBAEvfPLlasWKHVq1drypQp+t73vtda5/4lBsJLHCotLdWLL76oOXPmaOjQoW2ur1+/XpI0bty4iHpKSopGjx6t0tJS1dXVRTz22CGnFuedd54OHjyo8vLyzv4WuqTS0lJJOmF44f7Fp7Vr1yo/P1+DBw9uc+3RRx/V7bffLon7ZwcNDQ165plnlJaWpp///OcR17h/iYHwEmeCwaB+8YtfaODAgZozZ07Ux+zevVvZ2dkRnwRa9OvXT5JaJxju2bNHktS/f/82j20Zv482GRGnruV8lNraWv3kJz/RuHHjNG7cON11113avn176+O4f/HH6/Xq22+/VV5enrZt26a5c+dq7NixKioq0l133dV6HyTunx28+uqrqqqq0n/8x38oKysr4hr3LzEQXuLM73//e5WUlOhXv/pVxKSxYx08eFDdu3ePeq2lfuTIEUlHf5EmJydHdIO3aPnH2/JYnJ6W8PL73/9e6enpmjZtmkaNGqWVK1fq+uuvV0lJiSTuXzyqqqqSJB04cEDTpk3T3r17dd1116moqEgrV67U9OnTtXfvXkncv3jX3NysxYsXKyUlRT/+8Y/bXOf+JYYkqxuAf9uxY4cWLFigmTNnasyYMTEfFwgEYgablnpTU9MpPxanx+VyqV+/fnryyScjupnffPNN3XPPPfrFL36hP/3pT9y/OFRfXy/p6DDBNddcoyeffFIul0uStGjRIv3qV7/SE088of/7f/8v9y/OvfPOO6qurtb06dPVq1evNte5f4mB8BInwuGw/s//+T/KysrSf/3Xf7X72NTUVPn9/qjXmpubJUndunU75cfi9Dz00ENR61dffbVef/11rV+/Xtu3b+f+xSGn82gntMvl0i9+8YvW4CJJs2bN0quvvqo1a9aooaGB+xfn/vKXv0iSpk2bFvU69y8xMGwUJ5YsWaKNGzfq4YcflsfjafexGRkZrRPKjtdSb+n+zMjIUFNTU+s/tGO1dHfG6kJF5xk+fLgkqaKigvsXh1p+hv369VPPnj0jrjmdThUUFMjv92vfvn3cvzh25MgRrVu3Tv369dPIkSOjPob7lxgIL3Fi5cqVkqRbb701YlfIhQsXSpJuuukmFRQUqKKiQoMGDZLX61VjY2Obr7N37145nU4NHDhQkjRo0CBJR39pHq+lFm11BU5NIBDQv/71L3355ZdRr7fcq5SUFO5fHOrfv79cLlfMT9mBQEDS0U/Z3L/49Y9//EN+v18//OEPYz6G+5cYCC9x4tprr9XcuXPb/HfOOedEXM/IyFBRUZFCoZA2bNgQ8TWampr0xRdfaOjQoa2TyYqKiiT9e8nfsT777DN1795dZ511lsHfXeILhUKaOXOmZs+e3Wbfh3A4rM8//1xJSUkqLCzk/sWhlJQUjRgxQvv379fOnTsjrgUCAZWWlqpnz54644wzuH9x7IsvvpAkjR07NuZjuH+JgfASJ6ZMmaJ58+a1+e/Y8DJv3jxlZGToqquuksvl0oIFCyK6M59//nkdOXJE06dPb61dfPHF8ng8+t3vfqeDBw+21pcvX66dO3dq2rRpreP96Ljk5GRNmDBBhw4d0osvvhhx7Q9/+IO++eYbXXnlldy/OHb99ddLkh5//PGIHpg//OEPqqys1I9+9CO5XC7uXxxrWdEXa8hIEvcvQXC2UZx7/PHHtXDhwjZnGz399NN66aWXdNZZZ2nChAnaunWrPvzwQ5177rl69dVXI2bIv/baa3r44YfVt29fXX755Tpw4IDeeecdDRgwQMuWLWszxo+Oqaio0A033KDq6mqNHz9ew4YN01dffaV169bprLPO0pIlS5SZmSmJ+xePwuGw5s6dq/fff19Dhw7VRRddpG3btmnNmjUaNGiQli9f3jq/gfsXnyZOnCiv1xtz+LYF98/+CC9xLlZ4CYfDWrp0qZYuXardu3crJydHl1xyiebOnRt1Atnbb7+t3/3ud9q6dat69OihCy+8UHfffbd69+5t5reT8A4cOKBnn31Wa9eu1cGDB9W7d29deumluuOOOyLuC/cvPgUCAS1evFhvvPGGdu/erZ49e2rSpEn66U9/2ho8Je5fvDr33HOVk5PTOocwFu6f/RFeAACArTBYBwAAbIXwAgAAbIXwAgAAbIXwAgAAbIXwAgAAbIXwAgAAbIXwAgAAbIXwAqBDKioqVFBQoEsuucTqpgDoYggvAADAVggvAADAVggvAADAVggvANp13333qaCgQOvXr9dtt92mUaNGafz48Vq3bl3rY/bv36/7779f48eP16hRo3TllVfq1VdfVbSj0xoaGvTb3/5WV111lUaNGqWioiLNmjVLb731VpvHFhcXq6CgQGvXrtV7772nqVOn6pxzztGFF16oRx99VA0NDQoGg3rxxRf1wx/+UOecc46uvPJKLVu2LOr3sm3bNt1zzz268MILNWLECE2cOFG/+tWv5PV6oz7+448/1p133tn6+HPPPVdTp07V4sWLFQqFIh47ceJEnX/++WpsbNT8+fM1ceLE1teYP3++6uvrT+XHDqAdSVY3AIA9/PKXv9TBgwd10UUXqaSkRIWFhZKkQ4cOaerUqWpsbNR5552nuro6bdiwQU888YSqqqp0zz33tH6Nb7/9VjfddJPKy8uVmZmp733ve2psbNS6deu0YcMG/eMf/9CTTz7Z5rUXL16sNWvWaMSIEbrgggu0fv16LVmyRDU1NXI6nVq1apXGjBmjfv366dNPP9WDDz6oQCCgWbNmtX6Njz/+WHPnzlVDQ4OGDRumc889V998840WLVqk999/X4sWLVL//v1bH//SSy/p6aefltvt1tixY5WRkaGKigpt3rxZmzdv1p49e3T//fdHtDMUCmn27Nn64osvNHr0aOXl5emTTz7RCy+8oJ07d+q5557r7NsCdE1hAGjHvffeG87Pzw8XFRWF9+3bFw6Hw+FgMBjes2dPOD8/P5yfnx+eOXNm+ODBg63Pefvtt8P5+fnh0aNHh5uamlrrd955Zzg/Pz985513hn0+X2t9586d4UmTJoXz8/PDS5cuba0/99xzra/xxhtvtNZLSkrCBQUF4fz8/PC4cePC5eXlrdeWLVsWzs/PD1999dWtNa/XGx43blx4+PDh4ffee6+1HgqFwr/97W/D+fn54enTp7fWKysrw2effXb4/PPPD+/atSvi57Fy5cpwfn5++Jxzzgk3Nze31idMmBDOz88PT5gwIbxt27bWellZWXjkyJHhYcOGhffs2XOSP3UA7WHYCMBJueSSS9S3b19JktMZ+dbx6KOPqkePHq1/vvzyy5Wbm6v6+nrt2bNH0tGl1X//+9/Vs2dPPfXUU0pLS2t9/MCBA/XEE09Ikn7/+9+3ee0RI0Zo6tSprX8eNmyYhgwZIkm66aabNHTo0NZrl156qSRp9+7drbXly5fr0KFDuvHGGyOWdjscDt1+++0aOXKkPv/8c33++eeSJK/Xq0suuURz587VgAEDItrywx/+UJmZmWpoaFBtbW2btt5+++2tbZOk/Px8jRs3TqFQSFu2bGnzeACnjvAC4KQUFBRErffo0UNnnXVWm3qfPn0kSYcPH5YkbdiwQZJ00UUXyePxtHn8eeedp5ycHO3Zs0eVlZUR10aPHt3m8b169ZJ0NMgcKyMjQ5LU1NTUWvvss88kSeeff37U7+G73/2uJGn9+vWSpOHDh+uZZ57RjTfe2PoYv9+vrVu36o9//KOCwWBr7XijRo1qU8vJyZF0dL4PgNPHnBcAJ6Vnz55R6927d49aT0o6+vbS8ou+qqpKktSvX7+Yr3HmmWequrpa1dXVreFHUkSvTguHwxG1XS31Y+3fv1/S0V6R9rQ8TpICgYDefvttvf322yovL9f+/ftbv5eW1whHmZDcEp6O5XK5JKnNJF8AHUN4AXBSooUCqe0QUke/jvTvoJOcnBxRbwlCHdXydSdNmhQxXHW8ll6c+vp6/fjHP9ZXX32ltLQ0jRgxQj/4wQ+Un5+v8847T7Nnz24dDjtee98fgM5BeAFgit69e0tSzF/60tF5MZKUnZ3d6a+9c+dO3XLLLRo7duwJH/+HP/xBX331lS666CI988wzSk9Pj7heV1fXqe0DcGqY8wLAFEVFRXI4HProo4/k8/naXP/000/17bff6qyzzlJWVlanvnZLYFm7dm3U6/fff7+uu+46ffDBB5KkL7/8UtLRycDHB5evvvpKBw8elBR92AiA8QgvAEzRv39/TZo0SQcPHtS9994bsWnbnj179Mtf/lKSIvZm6SzTp09Xt27d9Ic//EF///vfI66tWLFCf/rTn/TNN9/onHPOkaTWVVWrV6+OeOz27dsj9q05dlIwAPMwbATANI8++qh27typv//975o4caLGjh2rhoYGrVu3Ts3Nzbr22ms1c+bMTn/dPn366Mknn9Q999yjuXPnKj8/X4MGDdKuXbtUVlYmp9Op3/zmN63DVTNnztSKFSu0ZMkSrVu3TkOGDFF1dbW++OILud1unXnmmaqoqFB1dXXEMm0A5qDnBYBpsrKytGzZMs2bN09ZWVlau3atvvrqKxUVFenZZ5/Vr3/9a8MmvF5++eV64403dOWVV6q2tlarV69WXV2dLr30Ur3xxhu6/PLLWx87bNgwLV68WBdeeKG8Xq8++ugjHTx4UFdddZVWrFihH//4x5La9swAMIcjzKAtAACwEXpeAACArRBeAACArRBeAACArRBeAACArRBeAACArRBeAACArRBeAACArRBeAACArRBeAACArRBeAACArfz/QX5PyY7DXxkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots(figsize=(8,8))\n",
    "a1.scatter(visc_df['rhoU'],visc_df['k'])\n",
    "a1.set_xlabel(z2r)\n",
    "a1.set_ylabel('k')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'index')"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,(a1,a2)=plt.subplots(2,1,figsize=(8,8),gridspec_kw={'height_ratios': [1, 3]})\n",
    "# a1.scatter(visc_df['rho'],visc_df['k'])\n",
    "# [46:69,92]\n",
    "# a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[0:tsl]['k'])\n",
    "# a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl:tsl*2]['k'])\n",
    "a1.plot(visc_df.iloc[0:tsl].index,visc_df.iloc[0:tsl]['T'])\n",
    "# a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[46:tsl*3]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*3:tsl*4]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*4:tsl*5]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*5:tsl*6]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*6:tsl*7]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*7:tsl*8]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*8:tsl*9]['k'])\n",
    "a2.scatter(visc_df.iloc[0:tsl].index,visc_df.iloc[tsl*9:tsl*10]['k'])\n",
    "# a1.plot(visc_df.iloc[0:tsl].index,visc_df.iloc[46:69]['T'])\n",
    "# a2.set_ylim(0,50)\n",
    "a2.set_ylabel('k')\n",
    "a2.set_xlabel('index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.api as sm\n",
    "Y = z2v_df['visc']\n",
    "X = z2v_df['ageU']**n2\n",
    "X = sm.add_constant(X)\n",
    "model = sm.OLS(Y,X)\n",
    "results = model.fit()\n",
    "# olslist.append(results.params.date_ord*365.25)\n",
    "# olsnames.append(name+'_'+fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                   visc   R-squared:                       0.540\n",
      "Model:                            OLS   Adj. R-squared:                  0.540\n",
      "Method:                 Least Squares   F-statistic:                     803.9\n",
      "Date:                Thu, 25 Aug 2022   Prob (F-statistic):          1.55e-117\n",
      "Time:                        15:20:16   Log-Likelihood:                -26171.\n",
      "No. Observations:                 686   AIC:                         5.235e+04\n",
      "Df Residuals:                     684   BIC:                         5.236e+04\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const      -2.533e+15    5.2e+14     -4.873      0.000   -3.55e+15   -1.51e+15\n",
      "ageU        9.826e+05   3.47e+04     28.353      0.000    9.15e+05    1.05e+06\n",
      "==============================================================================\n",
      "Omnibus:                      716.834   Durbin-Watson:                   1.389\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):            41846.368\n",
      "Skew:                           4.815   Prob(JB):                         0.00\n",
      "Kurtosis:                      40.031   Cond. No.                     2.28e+10\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "[2] The condition number is large, 2.28e+10. This might indicate that there are\n",
      "strong multicollinearity or other numerical problems.\n"
     ]
    }
   ],
   "source": [
    "results.rsquared\n",
    "print(results.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['9_7', '5_7', '7_8', '8_4', '4_3', '3_2', '2_6'], dtype=object)"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z2v_df['holenum'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3518860552.341633"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z2v_df.loc[z2v_df['holenum']=='9_7']['ageU'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dep_ranges = ['15-20 m','15-20 m','20-25 m','25-30 m','30-40 m','40-80 m','80-106 m']\n",
    "hnos = ['9_7', '5_7', '7_8', '8_4', '4_3', '3_2', '2_6']\n",
    "f1,a1=plt.subplots(figsize=(10,8))\n",
    "for ll, dr in enumerate(dep_ranges): \n",
    "#     print(z2v_df['ageU'].iloc[ll])\n",
    "    age2plot = z2v_df.loc[z2v_df['holenum']==hnos[ll]]['ageU'].mean()\n",
    "    v2plot = z2v_df.loc[z2v_df['holenum']==hnos[ll]]['visc'].mean()\n",
    "    a1.scatter(age2plot,v2plot,s=75,label=dr)\n",
    "#     a1.scatter((z2v_df['ageU'].iloc[ll])**n2,z2v_df.visc.iloc[ll],s=75,label=dr)\n",
    "xx = np.array([(z2v_df['ageU'].iloc[0])**n2,(z2v_df['ageU'].iloc[-1])**n2])\n",
    "a1.plot(xx, results.params.const + results.params['ageU'] * xx,'--',label='OLS regression, r$^{{2}}$={:.4f}'.format(results.rsquared)) \n",
    "a1.set_ylabel('Viscosity (Pa s)')\n",
    "a1.set_xlabel('Age (a)')\n",
    "a1.set_title('Bulk viscosity in depth intervals at USP50')\n",
    "a1.legend()\n",
    "f1.savefig('USP_deepviscosity.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='TIMESTAMP'>"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diff_visc['viscosity8_4'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>holenum</th>\n",
       "      <th>dep</th>\n",
       "      <th>agemean</th>\n",
       "      <th>agemax</th>\n",
       "      <th>visc</th>\n",
       "      <th>rhomean</th>\n",
       "      <th>rhomax</th>\n",
       "      <th>T</th>\n",
       "      <th>stress</th>\n",
       "      <th>rhoU</th>\n",
       "      <th>ageU</th>\n",
       "      <th>term</th>\n",
       "      <th>k</th>\n",
       "      <th>arrT</th>\n",
       "      <th>modvisc</th>\n",
       "      <th>drho</th>\n",
       "      <th>moddrho</th>\n",
       "      <th>difper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1656</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>4.044677e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.198638</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>-15.701205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1657</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.987547e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>7.464982e-07</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.404231</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>43.144632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1658</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>3.842401e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.209095</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>-9.914960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1659</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.489525e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.539386</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>57.390939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1660</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>2.666145e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>1.001371e-06</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.301345</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>23.732787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.782334e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>6.694226e-07</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.450773</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>49.014922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1662</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.413411e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.568432</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>59.568261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>2.804669e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>1.053399e-06</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.286461</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>19.770211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1664</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.571770e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.511162</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>55.038264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1665</th>\n",
       "      <td>2_6</td>\n",
       "      <td>106.0</td>\n",
       "      <td>830.47986</td>\n",
       "      <td>977.100699</td>\n",
       "      <td>1.865422e+16</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>803.834785</td>\n",
       "      <td>222.15</td>\n",
       "      <td>-662706.584586</td>\n",
       "      <td>768.337289</td>\n",
       "      <td>3.083495e+10</td>\n",
       "      <td>2.662494e+22</td>\n",
       "      <td>7.006297e-07</td>\n",
       "      <td>7.790271e-15</td>\n",
       "      <td>3.495795e+16</td>\n",
       "      <td>-0.430695</td>\n",
       "      <td>-0.229827</td>\n",
       "      <td>46.638103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     holenum    dep    agemean      agemax          visc     rhomean  \\\n",
       "1656     2_6  106.0  830.47986  977.100699  4.044677e+16  768.337289   \n",
       "1657     2_6  106.0  830.47986  977.100699  1.987547e+16  768.337289   \n",
       "1658     2_6  106.0  830.47986  977.100699  3.842401e+16  768.337289   \n",
       "1659     2_6  106.0  830.47986  977.100699  1.489525e+16  768.337289   \n",
       "1660     2_6  106.0  830.47986  977.100699  2.666145e+16  768.337289   \n",
       "1661     2_6  106.0  830.47986  977.100699  1.782334e+16  768.337289   \n",
       "1662     2_6  106.0  830.47986  977.100699  1.413411e+16  768.337289   \n",
       "1663     2_6  106.0  830.47986  977.100699  2.804669e+16  768.337289   \n",
       "1664     2_6  106.0  830.47986  977.100699  1.571770e+16  768.337289   \n",
       "1665     2_6  106.0  830.47986  977.100699  1.865422e+16  768.337289   \n",
       "\n",
       "          rhomax       T         stress        rhoU          ageU  \\\n",
       "1656  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1657  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1658  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1659  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1660  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1661  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1662  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1663  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1664  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "1665  803.834785  222.15 -662706.584586  768.337289  3.083495e+10   \n",
       "\n",
       "              term             k          arrT       modvisc      drho  \\\n",
       "1656  2.662494e+22           NaN  7.790271e-15  3.495795e+16 -0.198638   \n",
       "1657  2.662494e+22  7.464982e-07  7.790271e-15  3.495795e+16 -0.404231   \n",
       "1658  2.662494e+22           NaN  7.790271e-15  3.495795e+16 -0.209095   \n",
       "1659  2.662494e+22           NaN  7.790271e-15  3.495795e+16 -0.539386   \n",
       "1660  2.662494e+22  1.001371e-06  7.790271e-15  3.495795e+16 -0.301345   \n",
       "1661  2.662494e+22  6.694226e-07  7.790271e-15  3.495795e+16 -0.450773   \n",
       "1662  2.662494e+22           NaN  7.790271e-15  3.495795e+16 -0.568432   \n",
       "1663  2.662494e+22  1.053399e-06  7.790271e-15  3.495795e+16 -0.286461   \n",
       "1664  2.662494e+22           NaN  7.790271e-15  3.495795e+16 -0.511162   \n",
       "1665  2.662494e+22  7.006297e-07  7.790271e-15  3.495795e+16 -0.430695   \n",
       "\n",
       "       moddrho     difper  \n",
       "1656 -0.229827 -15.701205  \n",
       "1657 -0.229827  43.144632  \n",
       "1658 -0.229827  -9.914960  \n",
       "1659 -0.229827  57.390939  \n",
       "1660 -0.229827  23.732787  \n",
       "1661 -0.229827  49.014922  \n",
       "1662 -0.229827  59.568261  \n",
       "1663 -0.229827  19.770211  \n",
       "1664 -0.229827  55.038264  \n",
       "1665 -0.229827  46.638103  "
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "visc_df.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Before running the following cells you need to scroll to the bottom to define dddf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Depth')"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6q++66y5ceumlOPnkk3HOOefgox/9KHbv3t3oZRERERF5lk7ba6pfs4jIB01zV1933XX41Kc+hYmJCVx55ZU444wz8Pvf/x5XXHEF9u/f3+jlEREREXmSPueJUeVErUZu9AIA4JlnnsF//ud/4owzzsBNN92EYDAIAHjTm96Ef/iHf8D3vvc9fP3rX2/wKomIiIhKcztPCsf2iFpOUxRPP/3pTwEA11xzTapwAoDzzz8fV1xxBebPn9+opRERERGVRTctCAIgiuw8EbWapiie/vSnP+HYY4/F8uXLcx675pprGrAiIiIiosoYhgVZEiEILJ6IWk3D+8lDQ0MYHh7GqlWrsHPnTmzYsAGnnXYa1q1bh49+9KPYt29fo5dIRERE5Jlh2kzaI2pRDb+zBwYGAABHjhzBZZddhgMHDmD9+vVYt24d7r33XlxxxRU4cOBAg1dJRERE5I1hWiyeiFqUYNu23cgFbN26FVdeeSUA4KKLLsLXv/51SJIEALj11lvx1a9+Feeddx6+973vZb3u+uuvxw033JD1tc2bNyMcDtd0vfF4PGtfFtF0/IxQMfx8UCn8jMx8v/zzEWzbN4kvXrnS92vz80EAAMuE8ofvwTzujbAWrM16iJ+R8kSj0VQt4tqwYQM2btyY9/kN3/Mkis6/zEiShM9//vOpwgkArrrqKvzkJz/BAw88gFgshlAolHps48aNOd/U1q1bsXZt9gfIb9u2bav5e9DMxs8IFcPPB5XCz8jMF3kqhlBAq8nfIz8fBABmbAJ77xhAj6KjZ9rngZ+R8mzduhU7duzw/PyG95Tb29sBAAsXLkRXV1fWY6IoYvXq1dB1HQcPHmzA6oiIiIjKw7E9qjXb0J3/r8UbvJLZp+F39uLFiyFJEnRdz/u4YRgAkNV1IiIiImpWhmlBlhv+Kxa1MNvQAACWFmvwSmafht/ZgUAAJ5xwAg4dOoQ9e/ZkPWYYBrZv346uri7MnTu3MQskIiIiKoNhMG2Passtnth5qr+muLMvv/xyAMDXvva1rA7ULbfcgsOHD+Piiy/O2gtFRERE1KwM04LC4olqyNbZeWqUhgdGAMD69evxxz/+Eb///e9x8cUX49WvfjV27tyJBx54AMuWLcOGDRsavUQiIiIiTzi2R7Vmm06zgcVT/TXFnS0IAr773e/ic5/7HADgv/7rv7Bt2zb83d/9Hf77v/87FSpBRERE1Ox0w4IsCY1eBrUwS+fYXqM0RecJAGRZxnvf+168973vbfRSiIiIiCpmmBbCwab5FYtaEAMjGqcpOk9ERERErYJR5VRr6eKJnad6451NRERE5CPueUp74eURfPWWR2GYVqOX0lJYPDUO72wiIiIiHxmGDYXFEwDguZ1DePRvhzE8xl/y/ZR5SK5t2w1ezezCO5uIiIjIRzqjylMSugkAGJ/SGryS1uJ2nmBb6f+muuCdTUREROQj7nlKS2gGAGBsKtHglbSWzIKJiXv1xTubiIiIyEeGwT1PLnaeasONKgeYuFdvvLOJiIiIfMTOU1pCY/FUC+4huQBDI+qNdzYRERGRj5ziiYfkAiyeasXWM8f22HmqJxZPRERERD6xbRuGaTMwIskd2xub5J4nP2XueWLnqb54ZxMRERH5xDCd2GjueXKw81Qb2cUTO0/1xDubiIiIyCfuYbDc8+RgYERt2IYGQQkCAKwEi6d64p1NRERE5BMWT9nYeaoN29AhhTuc/9Y5tldPvLOJiIiIfGIYyeKJY3sAgHjynKcJFk++sgwtVTyx81RfvLOJiIiIfKIniyeFaXsAMsb2ohosy27walqHbWgQg2FAlNl5qjMWT0REREQ+4dhetoRmQhQAy7IxFddLv4A8sXUNgqRAVIPsPNUZ72wiIiIin+gmx/YyJXQTPR1OsAH3PfnHCYxQneKJnae64p1NRERE5JPUnid2nmBaNnTDQl93GAAwPsniyS+2oUOQVQjsPNUd72wiIiIin3BsL01L7nfq6woBAMameFCuX2xDgyCrENUQ9zzVGe9sIiIiIp+4h+QqLJ5SMeV93U7xxLE9/zjFk7vnicVTPfHOJiIiIvIJo8rT3Jjy1NgeiyffWMnOk6CGYOsc26sn3tlEREREPkkFRjCqPBVT3hlRoSoSiyef2LYFmAZEOQAxEGLnqc5YPBERERH5hHue0tyxvYAioaNNxdgk9zz5wTacyHdBViAqTNurN97ZRERERD4xGFWe4naeAqpTPLHz5A/bcH6OgqJCCIRgM22vrnhnExEREfnE3fPEwIjcztMEiydf2HqyeJKczpNt6rBNo8Grmj14ZxMRERH5hGN7aenOk4zOtgA7Tz7J7DyJASfJ0NI4ulcvvLOJiIiIfKIno8o5tpfuPAVVCR0Rlec8+SS950mFoASdr2kc3asX3tlEREREPklFlbPzhEQyqtwd24vGDejJnw9VznI7TzI7T43AO5uIiIjIJwajylOmB0YAwESUo3vVSo3tJdP2AMBi56luWDwRERER+cQtnhSO7aXG9lRFQmdbAAAPyvWDWzyJcgBCwB3bY+epXuRGL4CIiIioVbhje5LI4imhm5AlAbIkpjpP49z3VLWsPU/Jr7HzVD+8s4mIiIh8opsWJFGAKHJsL6GZCCgSAKSKp7HJ2dl5un/rPsQS/sSJZ43tBdyxPXae6oXFExEREZFPDNNm0l5SQjcRULOLp9k4tndkOIpvb/4r/vfB3b5cz9ad7p2gqBAUJzCCaXv1w7ubiIiIyCeGaTFpLymhmQiozg6R9llcPLkdp2d3HvXleqmxPUll56kBeHcTERER+cQwLCgsngAAcc1Ije3Jkoi2kDIr9zzFk5Htz+8eSgWKVMPKOCRXUAIABO55qiPe3UREREQ+cTpP3O8EuJ0nKfXnjjYV47Nwz5ObOhhLmHhp/2jV10sHRigQBBGCGmDaXh2xeCIiIiLyiW5aUGSp9BNngYSeDowAksXTLBzbc8+7AoBnX6p+dM82EgAECJICABDVEMf26ojFExEREZFPDMOCLLPzBGQHRgBAZ1tgdhZPGeddPeNL8aQnu07O50xUgxzbqyMWT0REREQ+YWBEWmZUOeB2nmbfnie3eDp51Rxs2zMM3ahu35NtaBBkNfVnQQ1xbK+OeHcTERER+cQwbRZPSdM7Tx1tKsamNNi23cBV1Z87tnf62rlIaCZeeHmkqus5nad08cTOU33x7iYiIiLyiWGw8+SKJ0wEk1HlgFM86YaFuGYWeVXrcTtP69bMhSAAz1UZWe50npTUn7nnqb54dxMRERH5xAmM4K9XQG5gRGdkdp715HaeejuDWD6/s+p9T5aegKBkju0FeUhuHfHuJiIiIvIJ9zw5LMuGljO2FwCAWbfvKaEZkCURkiTihGN6sX3PMHSj8u6bbegQpMyxPXae6ol3NxEREZFPdI7tAQC0ZHEwPTACmJ2dJ7eIPGnlHGiGhe17K9/3ZBsaxGmdJ+55qh/e3UREREQ+MUxGlQPpfT7TAyMAYGyWHZSb0EwEkz+H41fOgShUd96TG1XuEtUgbC0B264uxY+8YfFERERE5BMGRjjcfT5ZnaeIO7Y3+4on9+cQCSlYsbC6fU/To8pFNQTAhq3PrnHIRuHdTUREROQT7nly5Os8tQVliKIw+/Y8Tdv7deIxfdixdyRVYJYrt3gKAgD3PdUJ724iIiIinxhM2wOQLp4yo8oFQUgelDt7O08AcNIxc2CYFrbvGa7oermH5DrFExP36oN3NxEREZFPdIOH5AL5x/YAzM7iaVrn6bjlPRBFoeJ9T/nH9th5qhfe3UREREQ+4dieI9/YHgB0tgVmX/GkmQgo6Q5cOKjgmEWdeG7XUEXXs3ICI9ziiZ2neuDdTUREROQTp3hi2l5CNwDkFk9O52m27Xkycn4OC/siGByJVnQ9W8+NKgcAm52numDxREREROQD27aTUeX89SrVeeLYXs6eJwDojAQwVsHPwbZMwDJyDskFOLZXL7y7iYiIiHxgWTZsG1A4tpfe85Sn8zQxpcGy7EYsqyGm73kCgK5IAAnNRDxhlHUt29ABAIKSL22PY3v1wLubiIiIyAe66RxSyj1PmXue5Kyvd0RUWDYwGdMbsayGiGcckuvqTJ55NTpZ3ghjqnjK2PMkJDtPHNurD97dRERERD4wTKebwrE9p2AA8o3tuQflzo59T6ZlQzesPGN7TudorOziyRn1y3vOU4Kdp3rg3U1ERETkA8Ng58mV0E2IopATntHR5vzSP1v2PWkFxhfdzlO5+57yFU+CJEOQFFg6O0/1wLubiIiIyAcGx/ZS3JAEQchfPI1Nzo7iqVBwRpdbPE1U33kCnMQ9m52nuuDdTUREROQDt3hSZEaV5wtJAJxznoDZ03kqGJyRHNsrd8+TpTs/N3Fa8SSqIXae6oTFExEREZEPdI7tpSQ0I6fbAgDtbU7QwWzZ85TQkuddKdnBGUFVRlCVyi4ibdPtPClZXxfUIPc81QnvbiIiIiIfcGwvrVDnKajKCFRQNMxUhTpPgLPvqey0vWTnKTOqHHA6TzY7T3XBu5uIiIjIB6niiWl7SOSJ53bNpoNyC+15ApzEvfL3PCWjyqXpxRM7T/XSNHf3ddddh9WrV+f9v3/8x39s9PKIiIiIijKMZFQ5O0+Ia2bOqJprVhVPJTpP5QZnpAIjlNzACD/2PGkDL2P/zZ+GFZ+q+lqtKv+nugF27NgBVVXxgQ98IOexVatWNWBFRERERN6lAiNYPCGhm6lEuek62wKzZs9T6ryrPMVTVySAXQfGyrpeobQ9MRDyJW0vcXgXtMM7oY8cQWD+iqqv14qapnh64YUXcMwxx2Djxo2NXgoRERFR2XTueUpxo8rz6WhTcfDoZJ1X1BiJIsWT03lKwLbtnEj3QtLFU3ZghKj403lyr29p0aqv1aqa4u6enJzEgQMHsHr16kYvhYiIiKgi6T1PjCovFBgBzNKxvQJ7ngzTxlTc8Hw9yygQVR4IwUr4WDxx/1RBTVE8bd++HQBYPBEREdGMZTCqPEUr0XmKxg3ohlnnVdVfuvOUO+zVmRxrHC8jcS8VGDH9kFwlCFgGbFOvdKkA0udI2RqT+wppirt7x44dAICRkRH8/d//PU4//XScfvrp+OhHP4pdu3Y1eHVEREREpTGqPC2hG4U7T5HZc1BuQnfPeco/tgeUd1CuE1UuAFJ2MSYGQgBQdffJNpy1WBo7T4U0xd3tFk8333wzIpEILrvsMpx00km49957cfnll2Pbtm0NXiERERFRcanAiFkeVW7btrPnqcjYHjBLiifNhCgKkKXcUc7O5M9hrJziydQgyErOHilBCQKovuhJj+1xz1MhTREYIUkSFi5ciK9//es488wzU1+/66678KlPfQqf//zncfvtt2e95vrrr8cNN9yQ9bXNmzfXvNCKx+Ms5qgofkaoGH4+qBR+Rmaul/c5yWm7d+/EyIBS4tmVmQmfD92wYNnA+Ohw3rWOHHV+MX9u20uIj4Xrvby6OnRkEIokpLaoZBqbckbstr+0F12yt9Q9eeAIRFHK+bmKg8NQAOzc/jzigc6KPyPywBFIAAYO7sOhJv+c+Wn61qENGzYUDLFriuLpy1/+ct6vX3jhhfjFL36Bxx9/HLt27cKKFenIxI0bN+Z8U1u3bsXatWtrutZt27bV/D1oZuNnhIrh54NK4Wdk5to1vBvAERy3ZnVqJMtvM+HzMRHVALyERQvnYe3alTmPh7vHgV/vR1fPPKxdu7D+C6yj+55LIBSM5f070w0L+NluhCM9WLvW277/wZ1/RFQNYeW060WVGA4/BixbNB+7J6yc93v6xUHM623D3J7ixergzj9gAkBPRwRzmvxz5petW7empuC8aPq+8nHHHQcA2L9/f4NXQkRERFQY9zw5UiEJBQ7J7Wxz9zy1/llPCb1wcIYii2gLKeXteTK0nANygYw9T3mCHuIJA1/54SO4/f6XSl7fTfPz48yoVtXwzpNhGHj++edh2zZOPvnknMfjcedDEAjU5l9wiIiIiPyQStub5XueUvHcBfY8tYedkcbZsucpWODnADj7nsYmvf8cLEPLSdoD0nuebC0GIPvxZ3YehW5YiCVKR6LbOs95KqXhxZNlWbjyyisRDofx8MMPQ5LSHzDbtvHkk09CluWmb1ETERHR7MbOkyPdecpfNEiSiEhIwdgsKZ4KFZFA+qBcr2xDgyjn7qfL6jwpnVmPbd12xFmLXjoaPh0YwajyQhp+d6uqite97nUYGxvDjTfemPXYLbfcghdeeAFve9vb0NHR0aAVEhEREZWmGxZEAZDE2X1Ibvpso8JFQzgoe+qEzHTO2F7hXkVXe/nFU7HO0/S0Pdu28cT2AWctWhnFE6PKC2p45wkAPvOZz+DJJ5/Ed77zHTz22GNYs2YNnnvuOTz22GNYuXIlPvvZzzZ6iURERERFGaY167tOABDXnKKo2LhaQJVTz2tlCc1AV3uw4OMdbSq27fbegbMNHaIayvm623mytTjQlv76/oFJDAw7I3ial85T6pBcFk+FNMUdvmjRItx2221Yv349XnzxRdx66604cOAArr76avz85z9Hd3d3o5dIREREVJRuWrN+vxOQseepwNge4BRWcQ+dkJmuWGAEAHRFAhifSsCybE/Xs/UCnSdZBQQxp2O0Ndl1WtgX8TS2Z6XG9lg8FdIUnScAmDt3Lv7lX/6l0csgIiIiqohhsPMEeBvbC6qypzGymc7LnifLduLdvcTbu4fkTicIAgQ1mJO2t3X7ESyeG8HCvggOD5UOgeDYXmm8w4mIiIh8YJg2iydkdp4K/xt9QJVmx9ieh84TAM/7nmw9f1Q5AIhqMGvcLpYw8NzOIaxbMxeqInkLjNBZPJXCO5yIiIjIBwbH9gB47TxJiCfYeeqIOIWQ17hy29QhSIWLp8zO07MvHYVhWjhtzVwEFMnbnqdk5wmmAdvQPa1ptuEdTkREROQDw7CgSLM7aQ8ofc4T4I7ttXbnybZt750njwcGW0U7T6GsjtET248gqEo4bkUPAqrkOW3P3VPF7lN+LJ6IiIiIfKAzbQ+A020RBEAt0oWbDYERmmHBtosXke4+p7EJj2N7hgYxT2AEAAhq0Enbg1O4bd0+gJNX9UGRJQQ8jO3Ztg3b0CC1OedEsXjKj3c4ERERkQ84tueIawYCigRBKNyFC8yC4snL+GJ7mwpBAEY9jO3ZlglYZt7ACMDtPDnFkxtRvm5Nv7MGRYJuWEVT/dyRPSmcLJ6YuJcX73AiIiIiHzBtz5HQi+/zAYBgQIZhWjBNq06rqr9U8VQkOEMSBbSHVU9je25xky+qHEAybc8peLZuPwIAWLdmrrOG5N9HsX1PqeIp2XniWU/58Q4nIiIi8gHT9hwJrfg+HyB9gG4rd58SurOnq1Qh2RkJeErbcwMcChVPohpKje1t3TaAxXPb0d8TBgCoyb+PYqN7btKeyM5TUbzDiYiIiHxgmBYUFk+eOk8B1enGtHJcebrzVKp4Uj2l7ZXqPInJzlNCt/DcrqHUyF7mGooWT8nryxHueSqGdzgRERGRD3TueQJQXueplQ/K9ZI6CDidp1EPgRHp4in/nidBDcHWE9h5YDIVUe4KePh5u9dPdZ5YPOXFO5yIiIjIB86eJ0aVa7qZ6iwVMivG9jx2nroiAYx72PNkJcfqih2SCwA7942lIspdXsb23Oun0vY4tpcXiyciIiIiHxiMKgdQ+mBYYJaM7ZXReZqI6jBKhGe4e57EgofkhgAAew+MpSLKXW4B5ykwItzh/Jmdp7x4hxMRERH5gFHlDjeqvBh2ntI6I04xND5VfN9TamyvQOdJSHae4tEY1q2dm/VYWWN7agiCrHJsrwDe4UREREQ+MIzaBUbsPTSO6372V5hFzulpFp6iypOdp0QLd57cwjBYYoQxdVBuicS90oERTudJFYyssAigvLQ9QVYhBkKwEvGi65mtWDwRERER+aCWUeXP7xnGH57Yh8lY83dqygmMiCWa//uplNeo8q6yi6dCh+Q6naf57Tb6u8NZj5UzticoKgQ1BEuLFl3PbMXiiYiIiMgHtUzbCyjOdUvti2kG3qLK3TGy1u08pcb2SvwsOtqcTtJoibjyUp0nDU5RtXxO7vt5GduzDKd4E2XVOTOKgRF5sXgiIiIi8kEtAyPcsSvdmAFje546T25gRCt3npzvTS1RUHe1O52n8ZKdp+KH5L54yCl2lnTnvp+nc56mj+1pHNvLh8UTERERkQ9qGVXuFk+a0dydJ8O0YFq2hz1PsyMwIqBKEITin4m2oAJJFDBaoniy9OKdp6f3TAIA+iO5BXa5Y3uiGmJgRAEsnoiIiIiqZFk2TMuuWWBEIBk7rZvN3XlKeAxJkCQRiiy29tieXroDBwCiKKAzomKs1NiemUzDy7PnybZtbN05CgCQLD3n8VRghIe0PUFWIahBWAnuecqHxRMRERFRlUzL6QjVas+T+8uv0eRje+65TV6KhqAqzYrOkxcdbYHSgRFFDsndPzCJAyPJQtTIvY4oCk6xWqrzJMoQRAliIAybY3t5sXgiIiIiqpKeHKer3Z4n57p6kwdGeD0Y1nmO3PKH5BYqIofv34yBu65P/bkr4qF4MjRAEAExt6u3dfsRWBABWQWM/B2sgCIVLZ4sXUsVZhzbK4zFExEREVGVjOQ4Xa2KJ7cYafbACK8HwwKzu/OUOLQTiQM7Un/ujARKj+0ZOgRZybuH6oltR7B4bjtENQghT+cJcD5Dpcb2RDldPNl6ArbVun8/lWLxRERERFQlN0K81mN7Tb/nqYzOU7DEL/MzXUIzC+79svUErIwo8M6IWjIwwja0vGERsYSBv+0axmlr5zoH5RboPKklOk+Z1xcCzplRTNzLxeKJiIiIqEpGcmxPqVHaXiAVVd7kY3tldJ5af2zPKPhzsPREViBDZySAWMIomYaX74DcZ14chGFaWLem3zkot1DnSZGKXz9rbM85ZNfm6F4OFk9EREREVUp1nmp9zlOLdZ5m69ierSdgGxps0ykeOyPOWU/FRvesAp2nrdsHEApIOG55LwQ1BKHQnicPY3vu9cVAyHlPHpSbg8UTERERUZX0eo3tNfuep4S3qHL3ObM1qtzWne6QW5x0RpyipVhohLPnKbt4sm0bT2w/gpOO6YMiiyU7T0UDIzKLJ9Ud22PxNB2LJyIiIqIqpcf2avOrlSQKkCUh1eFqVgnde1R5YBZ3nqxkd8jSnNG9rmTnqdi+J1tPBzq49h2ZwOBIDOvWzgWAknueSo3ticmxPUFl56kQFk9EREREVap15wlI/vLb7J0nrcyxvUQLF09ldZ6c4ml8qkjxZObuedq6fQAAsG5NPwAkx/aKpO15DIwQA9zzVAiLJyIiIqIqGTU+5wlwiqemH9vTy4kqb/GxvQKdJ9u2M4onp/Pkju2NThTe85QZ6ODauv0IlsxrR3+3U+w4Y3tFznkquucpwbE9D1g8EREREVWp1oERgFM8Nf3YXvKXc9XjOU+aYcG0mrsgrIRhOt9XviLSzihu3OIpFJChyGKJPU/ZgRFORPkQ1q2Zm/qaWzzZdu7P1EnbK/z5sacdkuusj8XTdCyeiIiIiKrkHpKr1HBsL6CIM6LzpMoiRLF0ZHsgGSrRit2nYuOLtp4unuxkcSIIgnNQbrGxvWmBEU+/OAjDtFMje0BybM+2YJt6zuudsb3CP2sr65ynZPHEzlMOFk9EREREVdLrMLYXUKTmjyrXzFRRVEowIKVe02rc86vy/SzsjD1JmWc9dUXUsqLKMyPKXe64nZ2nY6Qmx/bydaWcdaUDKQRJAUSZe57yYPFEREREVKX02F5tDskF3D1PzT22Fy+SMDddMPm8VkzcK7b3y9IziqeM4qQjEiietpdxSK5t29iaEVHuKrZXKaBIsOx0lzTn+npG50kQIAaCHNvLg8UTERERUZWMOqXtNX3nqUjC3HRuVyY+68b2CnWeAhgvUTy5naFYwsDgSAxrl/VkPSc9bhfPeb27lnyJe7ZpALYFQQmkviaqobzXme1YPBERERFVqR5pe4GZkLZXQeepFcf2inWeMvc8ZRZPnZEARifzhz0A2Xue3J9ZOJg9FigqybG9PEWPG+KRb4+ZG2KRORYoqKGs9eW8xjKROLy74OOtisUTERERUZXczlOtDskF3M5Tc4/tJXTDc+cpOEs7T5aeLmwyx+K6Iio03cw7xmhbJmCZ6eJJz399sUjQg/v3ki9xz9JziycxECq65yn6whM4cPMnoR3dX/A5rYjFExEREVGV6nNI7gxI2yuj8xSYpXue0mN7QlZnp6PNGZnLF1dup4obZ8+T+zMLKNmdJ0Fx9zyVObaX7DyJGedIlRrbMyZHnOsdfKngc1oRiyciIiKiKhnJoqb2h+Q2e+fJ+56nlg6M8BBVLobbszpEXe1FiqdpY3WJVJpf/s5Tvo5RoMyxPad4Ktx5sjWn8EscmV2jeyyeiIiIiKpUj0NyZ0pUedBrVPlsOOepSNqeHOmGnbXnySlc8sWVp4obZdrY3rTri8U6T0XG9uw8Y3ul9jy5I4fa4V0Fn9OKWDwRERERValeUeWGYRcMFGgGjCp3FNqTBKTPeZIiXdmBEcmxvXxx5ZbhHHo7PTBi+vUrTtubVpwBTher2Nie25VKHN4N227ujqifWDwRERERVckwLciSAEGoZfEkwka6UGtGCb2cPU+tHBjhfE/5unDunieprTsrMKIj1XkqPLYnlgiMECQFtiDmHdtLp+3lFk9WsqCbPrZna/GCxbq7dluLwRg5kvc5rYjFExEREVGVdMOq6cgekA4HSOQZu2oWCc37nidFFiGJQmtGlSe/J7Xg2J4AKdyR1XkKqjJCAan42J4bGJHIP7YnCAIgq0XH9vJ2nvTs4gxI7p+yraxzqbK+j0QUEJOfyVk0usfiiYiIiKhKTuep1sWTc30tzy+/zcA0LRim5bnzBDije606tucWh9PZugZBCUAMhGEbmnNAbVJHW8BbYESRsUDIgfxR5eWO7anJ/VOJ/KERlhZDYO4yQJSLFk9WgeJrpmLxRERERFQlw7RrGlMOpLsYzVo8FYvnLiSgyognWnFsr3AHztYTEBQVYjAMIPtMpq5IIO+eJ7vQnqd8UeiyWuKQ3CLFU2ZgRCB3fVmvSUQhhjug9i2GViBxTx8dwN7r/h6xl5/P+/hMxOKJiIiIqEpGHcb21CJjV82gaDekgKAqtebYXpG9X5aRgKgEIKrJcIesxL0AxvON7ekFOk/5CrRCnacixXf6+oHU19z1FToo10rEIAZCCMxbngyNyN0bFX3pr7D1BORId95rzEQsnoiIiIiqZJgWlJqP7TV55ylZBAXLKp7k1hzbK9l5csb2gOyxuM6IWqDzNC2qXDMgSyKkfJ+5AnueZEmAKAp5i2+r2NheoeJJi0FUQ1DnrYAVHYc5MZzznNjupyF39kPunpf3GjMRiyciIiKiKummBVmuXdIe4KTtAfnHrppBepTM2zlPgNOlasm0vSKdJ1vXIMiBdKz49M7TVCKni2NNC4xI6GbBItWWA3m7RYIgIKCIRcf2xGlpe876inWewgjMW+6sadq+J9syEdv7HELLT6ppCmW9sXgiIiIiqlI9x/byHXLaDDi2l1as82TpCYiKClF1Ok92VucpAMO0MRXPLijTxU0gff1CP2dZLdgtCihykbE9AZDShW+xPU+2ZcLW4xADIaj9ywAIOcVT4uBLsBNRhFacnH+dMxSLJyIiIqIq1SNtr+n3PBUJMSgkGJBbtvOU74wnIGNsLxUYke48dRU46ykdGJHsPBWLhJcDBQ+3VVWpYNqeICtZHaLUnqc8nSf3+mIgDFENQpmzENrh7NCI2O6nAQgILT0x/zpnKBZPRERERFWqT1R5k+95qqDzFGjRqPK4ZhQOjHCLJzV3z1NHxOksjU5ML55yAyMKjgUWSNsDnLj7gsVTxn4nABADhfc82clRQyFZYAXmLs/pPMV2PwN13gpI4fa8a5mpWDwRERERVckwbSizPaq8ks6TKs+6sT1bT6bt5dnz1JUsnsan8hRPggiI6bjxwp0n1Tk/ysr9uQaU/GOSlq5lxZQDgKAEAQh59zy5X3O/B3XeCpgTQzCnxlKPxw+8gPCKk/KvcQbzfJc/8cQTtVwHERER0YxVjz1Pzd95csbvyj8ktzXH9goHRjidJ0EJAII4LTDCKWBGp8WVO2N1amqsrtj1kdwXlW90L6AW2PNkJHKLJ0GAEAjl7Ty5o4buaF8qNCJ53lNs73OAZSK0vLX2OwFlFE/vfOc78aY3vQnf//73cfDgwVquiYiIiGhG0euy5ymZttekgRHu+F25Y3sJ3YRl5Z4RNJMVDYwwNKd4EgSIgVD22F6bU/jk7HnStdR+J/f6BfdUJYugvAflyoXH9sRpY3uAE1eeL7kv3XlyRg/VuU7xpCVH92K7n4EgqwguWpN3jTOZ57v89a9/PQ4ePIh///d/x3nnnYf3vve9uPPOOxGP55+pJCIiIpotjDpElac6T0aTdp4qHNuz7ebtplWqVOfJjQQXA+GswAhFFtEWUjA2bc+TZehZnaG4ZhQd2wPy71UKFEg3dDpbgZyvi2qhzlP22J4UikDu6k/te4rtfhrBJcdlFXytwnMQ//e//32Mjo5iy5YtuP322/HII4/g0UcfxTXXXIPzzz8f73jHO3DaaafVcq1ERERETakeY3uSJEIUmrfQSAVGlFU8Oc+NayaCAe/nQzUz07KhG1ben4NtGoBlOiN7QE7nCXAS98ampo/tJbI6QxWP7Sly/s5Tnj1PQLJ4yrvnKTm2l+w8AUBg3gokDu+GMT4EfegA2l9xXv71zXBl3eVdXV145zvfidtuuw2//vWv8b73vQ+RSAS33XYb3vWud+GNb3wjx/qIiIho1qlH2h7gdCaaOapclkRIZfwc0sVT6+x70oqkDtq601FyiydBDWfteQKcs57yRZVPH9srGEiRLJ7yjdupilhgz1OB4qnQnid3bC+55wlwRveMkcOY2vEIACC0vPXCIoAq0vZWrlyJT37yk3jggQfwi1/8AldccQUOHDiA66+/Hueddx7e97734b777vNzrURERERNyTCtmqftAYAiCU2bTle0G1JAILlvp1m/p0oUG1+09ORhtxmdJztP8TSaUzxlj9UV7zy5Y3v5AiMKpO3liSoHnCjyfEWYe/aToAbT1563AgAw9ujdkNq6oPYvzb++Ga6q/ujY2Bjuuece/Pa3v8Wjjz4Ky7IQCoWwatUqPPzww3jooYdwyimn4IYbbkBPT49fayYiIiJqKnodxvYAQJGF5h3bKxafXUArdp7S513l/pptG27nKb3nyRg5kvWcjjYV2/ZMH9tLd56KjQUCyBjby7PnSSlwSK6upfZhZXLGCnOLMEuLQlCCEMT0GtRk8WSMDSJywquzDtxtJWUXT7qu4/7778edd96JBx54AIZhwLZtvOIVr8All1yCCy64AJFIBAcOHMA111yDBx54AP/0T/+E73//+7VYPxEREVHD1W1sTxKhNWnanpMAV27x5Pwq2koH5bqFoJexPTGQO7YXCsiIJ7KLSdvQIAbbAGSOBZafthdQJOiGBcuyIYrp4qbg2J4aygq0cFmJWCoswiVHuiBFumFOjrTsyB5QRvG0detW3Hnnnbj33nsxPj4O27YxZ84cXHTRRbjkkkuwcuXKrOcvXLgQ3/nOd3Daaafh4Ycf9n3hRERERM1CN2zIUu3/pV2Whabd8xTXjArG9tKHvraKRJHIditZPIlyRmDEtA6RG99u23aqe+MUN10AihdnAIp3ntT0WWGZAR12gbG9wp2n3OIJcEb3oi9tRWgZiydcddVVzgtkGW94wxuwfv16vPrVr4YkFb5JVNU5zKu/v7/6lRIRERE1Idu2k3ueyiscKqE289iezrE9oHjqYE7nSQ3D1hOwTQOC5PxanopvzxjNy+wMlYyET4735UvJc1+TmF48FUjbE9QQYBk5gRVWIgpRDec8v/3kN0Du7IPc0Zt/bS3Ac/G0atUqrF+/HhdeeGFZ+5fuvvtuzJ8/v+yFfeMb38Att9yCTZs24cwzzyz79URERET1YCYPeK31OU+AO7bXpMWTVn5gRCuO7RXrPNnJwIjMqHLA6eRIoXbndckCJ55In+VkZRQ3iSJpfs7FRQhKELae55DcjOIptSbbgm3qBcf2UuvLKp7yd57a1pyJtjWt/Xu75+LpP//zPxEOh9HV1VX0efv27cPu3btTXanly5eXvahnnnkGP/nJT8p+HREREVG9GYazB0mpw54nZ2yvSfc86Sbaw7m/gBcTmGWdJysZGCFmBEYATjHiFk/BPKOMtqmnAh2KFWcuUQ3m7zzlu7ahZ61p+nWc9UUhhTvSr9GiENrKb460As93+Rve8AZ8/etfL/m8b33rW/jEJz5R8YI0TcMXvvAFmGbr/AsEERERtS7DdIqZ+gRGNO+ep4o6T4EWjirP13lKhjhkBkYAyAqNSHfj0gWlraf3JHk5jFhQg7DydJ4C+TpPbjcsb9pecn3TwiesRCzrjKfZpGDn6YknnoBt26k/27aNo0eP4vHHHy94sYmJCTz11FMwjMr/9eAHP/gBdu/ejVe96lV46KGHKr4OERERUT3obvFUj3OeZBFaslPQbCrZ86TKIgShxcb2inWeUoVK8pDc5Ohb5llKgYDbjcvsDmkQJGdszi3OiiUbimoodRZTJndsL3P00zYKF0+Cmrs+oPDY3mxQsHj6+c9/ji1btqT+LAgCHnrooZIFjW3beO1rX1vRYrZv344bb7wRH/zgBzE+Ps7iiYiIiJqeYST3PNWr89SkhUYlUeWCICCoSq01tqcVjhK3U2N76cAIALDimZ2n7NE62zQA20p1q4pd3yUW6jzlHdvLPnsq6zrunqyMzpht207aHjtP2T796U9jaGgo1X16+OGH0dfXh2OOOSbv8wVBgKqqWLZsGT7wgQ+UvRDTNPH5z38eS5cuxQc/+EF861vfKvsaRERERPVW17G9Zk7bqyCqHHCKgGYtCCuR0J1CMF8hmU7bc/c8uYEMhcf23D1Jbtqde/1SY3vm1HjO1/ON7U3vhmVK7XnKGNuzDQ2wzNRI32xTsHjq6+vDLbfckvrzmjVr8MpXvhLf/OY3a7KQm2++Gdu2bcPmzZuhquVtNiQiIiJqFLd4qkdghJu2l3kGUDOwLDsrWrscIVVGPNFCxZNmQhKFvMW0pScgSAoE0fk5iQHn4NvMcIdUdyhZ4Ewfq/MWGBGCMXok5+vFxvbEYnueMtbn/jfH9kq47777EA7XpsLcvXs3brjhBlx55ZU45ZRTavIeRERERLWQ6jzVI6pcFmDZgGHaUOrwfl5ppeKziwi04NheoZ+DE/yQ7vDkG4tLR5U7P1M3oS/deSodGCGq+Q+3zT+258anF97zlHngrp3skgnsPBW3cOHCmizAtm184QtfQG9vLz7+8Y97ft3111+PG264IetrmzdvxrZt2/xeYpZ4PF7z96CZjZ8RKoafDyqFn5GZZ9+g80vqoYMHsE0eq+2b2c4vvc/+7XmEKihUamUy5hQ/I8NHsW1beYWQbWoYHjFa5nN/eGAIkmDn/X7kwSMQIaYfs22oEDBwYB8OJb/m/iz37juAbe1TECYGoQI4NHAUB7Ztw/4DQwCA3btehCTmFtDxeBwjk1FI8amcNUzFzfS1O5wiSDy8EwqAvfsPwo5NKw0sEwEAAwdeTq1PGDkAFcDBgSFYLfJ3tnr16qw/b9iwARs3bsz73ILF0wknnAAA2LJlC5YtW5b6s1fPPfecp+f99Kc/xdatW3HjjTeira3N8/U3btyY801t3boVa9euLWud5dq2bVvN34NmNn5GqBh+PqgUfkZmHjs4BOBlLF+2FGtX99f0vR5+fhQAsHz5MejuCNb0vcoxMBwFsAtLFy/A2rVLy3pt9wMjiGtGy3zuw3+Noi2s5/1+juy4B9pEG1ZmPLbnN2F0tocxJ/m1eMIAsAtd3XOwdu0qJA4qOABg0bKVaDt2LR7b9TxkaRgnHH9c3vfftm0b5sxbiNFdj2LNmjVZ453OtXeip7cPa9euAgBMCWM4AmD5McciMC/3fNbdW1T0dkTQm1xfbI+BQwCWrFyF0NKZ/3e2detW7Nixw/PzCxZPbty4GxhRTfx4Mffeey8AFAyZePe73w3AGRtctGhRTdZAREREVCmjrlHlzi/CzXbWU3qUzPNQU0pAlTA6mfB7SQ1TLLLd1hM5wQyiGsoKjHD3JblR5e5In7v/yEskvKgGAdtyIs4zxgTda2eO7VlFxvbc980c23PDI9ykwHINjEQxPB5HT0cQ/d0zb/Sv4Cd8+/btRf/sl3e84x0444wzcr7+5z//GU8//TTe8Y53YOHChejo6MjzaiIiIqLGcqPK6xEY4YYQNFviXirEIFD+KGGw1dL2ytjzBABiMJwVyCCKQtY+sHRAQ7jk9V2pvUqJWCoW3b22Kot5D8nNFxjhXCuYXTylirnyAiN27h/Fd3/+JIbG4qnAk97OIP7hilOwclFXWddqpPL/ecBnl1xySd6vj4+Pp4qnM888s86rIiIiIvKm3lHlAKDpVs3fqxzuL/qVpO0FAy0WGKGbBTtwlp6AOK3DI6hh2BmBEYATc+4WOG5Xyi1WElrh67vciHE7z1lPqiJlF09FDsl1rpV94O70Ys6LnftH8aUbH8b4lJb19fEpDV+68WFc84FXzpgCquy7XNM0xOPpv4jx8XHcdNNNuOaaa3D77bfXbLyPiIiIqBnp9Rzbk5p8bK/itL3m+n6qUey8K1tP5HaeAqGszhOQffZV7the6fO0xIzO03QBVfKctpdaX960Pe+dp+/+/Mmcwsk1PqXh33/+pOdrNVpZnacbbrgBN998M772ta/hggsuQDwexxVXXIE9e/ak2m+/+tWvcMstt0BRlFqtmYiIiKhpGIbbeapHVLlToDVd8aSVjs8uxBnbM5ru7KpKJfQiY3tGvuIpDGMk+0ymgJJvbC+z81RqbM893DZP8TS986SX7jwZE8OpP1uJGCDKECRvv+sPjEQxNJbbAct0dCyOgZHojNgD5fmfSO666y7ccMMNME0zFSLxP//zP9i9ezeWLl2KL37xizjjjDPwxBNPYNOmTVUv7Atf+AJ27NjBkT0iIiJqao0Z22uy4qmKzlNQlWDZgG401yhipeJFihtL1/IHRuQZ20sHRkxBkNVUsRL3sOfJLbRsLf/YXubnxzISTjEk5r+mMK3zZCWiEANBz4Xu8Hg8VTsUYts2RsaLF1jNwvNd/j//8z9QFAW/+MUv8Na3vhUA8L//+78QBAFf/vKXcdVVV+Gmm25Cb28vtmzZUrMFExERETUTt3hS6ji213TFUxWdJ7cQaJXRveKBEfGcPU9iMJzTIQpmje3FsvYXFetspa6pFOk85RnbKzSyByT3PGWl7cXKStrr6ShdaAmC0FTR+8V4vst37NiBM844A2vWrAEAjI2N4emnn0ZbW1uqO6SqKk466STs2bOnJoslIiIiajbpsb16dJ6aNG0v1XkqP4ssmHxNq4RGFI8qz5O2p4Zh6wnYVvrvNDttL5qVbOdpbC/gFk+53Zx8Y3uFkvac9WXvyXKKOe/7nfq7w+jtLF4YzemcObHlnu9yTdOyDrF98MEHYVkWTj/9dIhi+jKmacKyWqPtSkRERFSKbjojSXUpnlKBEc31u5b7i36wwrE9AC0RV27bdsHOk53n3CUgPWKXWaAEVQnxRDowQlDL7Ty5Y3u5nafpY3u2oRXc7+Suzza0VHFnabGykvYA4B+uOAUdbfnfo6NNxUevOKWs6zWS57t80aJFeOGFF1J/vu+++yAIAs4999zU16LRKJ5++mksXLjQ31USERERNalGHJLbdJ0nzYQkChUVkK3UedKSXch8naHUeUp5AiMAZO17CqpyOqo8EYMYzCiePHSexGKdJzU3qrzY2F7qzKjktexENPU1r1Yu6sI1H3glVizoQEebivawgo42FSsWdMyomHKgjLS9s88+G5s2bcJnP/tZzJ07F/fccw9kWcab3/xmAMBf//pXXHfddRgbG8Pll19eswUTERERNZP6BkY079ieWsF+J6C19jyl9n7l6zzpCQC5qXZCqvOUWTxJSCSLSVuLQgrPS7+HbpYcjxQkBRDlwml7GT9rJ8Si+Nge4BRNCLbBSsQgd88r+PxCVi7qwnc/8ToMjEQxMh5Hd8fMGdXL5Ll42rBhA55++mnccccdqa998pOfRG9vLwDgox/9KI4ePYpXvOIV+MAHPuD7QomIiIiakWFYEAVAEmsfsy2JAkRRaLqo8ljcQDhY/n4noLXG9tLBGbk/C8twiif3AFuX23nKHLHLPPvKikfT3SnLhqabnsYjxUAwb9peQJGyDln2MrYHpMMnnD1YlRc9/d3hGVk0uTx/ytvb27Fp0yb85je/weDgIE4//XScfPLJqccvuugiLFiwAJdddhlUtfBfABEREVErMUyrLl0nV0ARs375bQbRRDXFU+uM7SV053vI33lyD6PNDYwAsjtPAVWGblgwLTtrj5HbcfSSaiiqoSJje+mftW1oOQXd9OsA6bE9J22vvLG9VlLWp1xVVVx00UV5H/vUpz7ly4KIiIiIZhLdtOqy38mlTktLawaxuIFwwNuhqdOlxvYSzfU9VcLtPOXrDBUa2ysUGAEA8YSelW5XznlaghosOrbnHkps6xqEcEfB62Suz7ZM2HqirLS9VlP2PxHouo7f/OY3ePzxxzE4OAhVVTFnzhyceeaZeO1rX4tAIFD6IkREREQtwjDq23manpbWDKbiOkJVdp4SLdB5ihc578pKFk/eAiOSxdNUFLCt1HPKOU/LOZ8p/yG5lg0Ypg1FFkqO7aUDI6Kp7lM1Y3szXVmf8m3btmHDhg04ePBgzknBP/vZz7Bw4UJ85zvfwQknnODrIomIiIialV7v4kluvs5TNG5gTmdl3YhgKwVGFOkMpTpPBaPKs8f2ACA+NZF8Trjk9acT1WDBsT33Wooswip1SG7ADYyIOaERQNlpe63Ec/F05MgRXH311RgZGcEZZ5yBt771rVi0aBFM08S+ffvwm9/8Bk888QQ+9KEP4fbbb0dfX18t101ERETUFIw6j+0FmrDzFIvrFe95clP6WqJ4KtIZKrTnSVCCgCDmHdtLTE0CSBcw5XSeBDUEa3I05+vuaxOagUhIKR0YkbHnyV0jO08e/OAHP8DIyAg2btyI//f//l/O41dddRVuuOEG3HDDDbjlllvwmc98xteFEhERETUjw7RTh9fWg6qITVc8RRNGxWN7oigk0+Vm/thesc5QKm1vWpdHEASIgRAsLfucJwDQo1NQkC5W0ocRl/5Zi2qw4CG5AFKhI7ahQfRUPMVSa5zNe548/zPJAw88gKVLl+YtnFwbNmzA0qVL8Yc//MGXxRERERE1u3qn7anToqYbzbJsxBKVB0YA7rlGzVUQVqJYVHk6MCI3H0BUQ1mdJ7f40qJu56mSsb3CaXuZ17JLnPMkyMkzoxLRdOdpFo/teb7TBwYGsHbt2pLPW7t2LQ4fPlzVooiIiIhmCt2o89ie2lx7nuKaAdtGxWN7gLPHpzU6T8WiyvPveQIAIRCetufJeb0Rdzs90wIjqkzbc65lwDYNwLbyrimTGHDCJ9w1svPkQXt7u6ei6PDhwwiHZ+8cJBEREc0ujek8NU/xFI07BUM4WF3nqaX2POUb2yuQtgcki5M8aXtGLBnQMD2q3GPaHkwDtqlnfT2QMbZnG8l9WEU6T+61nLE97nnyfKefeuqpePrpp/HII48UfM7DDz+Mp556CqeccooviyMiIiJqdvU/JLfZiifnl/NqOk8tM7anmxAEQM3TibT1BCCIgJT7cxID4WmBEc5zrMSU87hafufJPfh2+uhe5tiepXssngJBWIkYx/ZQRvH0vve9D4Ig4MMf/jBuuukm7Nu3D7Ztw7Zt7Nu3DzfeeCM+8pGPQBRFvO9976vlmomIiIiahmFYUOp8SG4z7XmKJtzOUzXFk4xYogXG9jQTAUWCIOQGiNh6AoKi5n1MDISnBUY4BU463c4pVoqdIzWdkCyepp/1lB7bM1Odp+khFrnXcjpPdnI97rVnI8+f8lNPPRVf+MIX8LWvfQ3XXnstrr322pzniKKIz3/+81i3bp2viyQiIiJqVvUf2xNTe2uaQTSWLJ6qCIwIqBImo3rpJza5hGYW7ApZupZ3ZA/IFxjh/Ipua1EIShCC6HaLjKzHi8lMycvkpu0ldBO24RThpcf2wrBiE7C0KAQ1vZ7ZqKx/Irjqqqtwyimn4NZbb8UTTzyBgYEB2LaN/v5+nH766XjnO9+J448/vlZrJSIiImo6hmnXtfMUUCQkmqrzlBzbC1XXeWqNwAizYFfINhJ5k/aA3LE9RRYhiQKgx7PCGRKaCVEUIHuIxvcytmfrHounQBDG2ACsRCw1Qjhblf0pP+644/D1r3+9FmshIiIimnF0o/6BEZZl173jVUgqMKLKqPJWCIyIJYyCXSF3bC8fMRCCrcdhW2aqqxNQJQh6LCucwS3O8o3+TScU6Dxlj+05hW+hdaXW5wZGJKIQA7N3ZA8oY88TAGiahh/+8If4xje+kfX1P/zhD3j729+Om266CZbVPP8SQkRERFRrThFTx0NyZTctrTmKjXTaXjVR5RISLdB5morpiITyF5GWnig8tpcskLJDIySIRjy7eCoyFphzzQJ7ntKH5Jqpg3tLdZ6E5FihpbHz5Ll4mpqawrvf/W58+9vfxn333Zf12NDQEF588UVce+21+Pu//3tomub7QomIiIiaUf3T9pz3apaznmLJtL1goNqxveb4fqoxGdPRVqB4snUNgpK/a5MqnrTMs57k3OKpyFhgzjULdJ5kSYAoCsmxvWRgRMmxvfQ5T7P5jCegjOLpRz/6EZ566imcc845+I//+I+sxy677DLcd999ePWrX43HHnsMN954o+8LJSIiImpGhlnfQ3LVjHN6msFU3EAoIDl7dCoUVCWYlg3daI7vqVJTMR2RcKHiqfDYnnuOkz2t8yRZiZw9T0GPnadCaXuCIDj75jLS9ryM7QE2zMkRCLP4jCegjOLpnnvuwfz58/G9730PK1euzHl84cKF+Pd//3f09fXh7rvv9nWRRERERM3KMCwo9ew8qc02tqdXdUAukE6Pq8Xonm3b0EcOY/L5BzF0308w9IdbYdu27+8DOJ2nSIGfhWUUGdtT843tyVCsBAS10rE9t/MUz3nMPSusnENyAcCYGJ71nSfP/dUDBw7g3HPPhaoW/uEGAgGcdNJJeOCBB3xZHBEREVGz00277oERQPOM7UUTRlX7nYD0uUZxzUTEh8aGpScw9shdiO/fjsShnbBiE1mPd515IaS2zurfKPM9LRvRuI62op2nQnuekoVO8lBcwCmSFUuDGJw+tuftZ+28l5AztgcAqiplje0VSgFMXcstmExj1u958vxJb29vx8DAQMnnjY2Noa2trapFEREREc0UjRvba47iKRY3qkraAzKLJ386T/F92zDyp/+G0rsQbceejsD8YxBYcAz00SMY+NW3YYwN+l48RRMGbBsFAyNsXSsaVQ5kd55CigAVWqrrAzidua52b2l3giBAUIMFO08JzYRV1tie+9+zO23Pc/G0bt063HPPPXjwwQdx9tln533OE088ga1bt+I1r3mNbwskIiIialamZcOy6tt5yoyabgZTcR2hKjtP7tieX6ERbhEy95JPQO1fmvGIsy/LGB9CYMExvryXayrmBGcUT9srFFXuFk/pwIiw7Oz/yu08eT+gVlSDWfuoXAFFTB6S6z0wYvpaZyvPn/Srr74av/vd7/DhD38Y73rXu/C6170O8+bNAwAcPnwYf/7zn7Fp0yYIgoD3v//9NVswERERUbMwTecX3LpGlSfT9pql8xSNG+jtrK4b4Xae/CoIbd3ptkwfk5M7egEAxsRR79eyTEAQS56tNBl1CpF8aXu2bXsb28sYsYvIThdOrHDPk/PaECw9T+dJlZ09T7oGQACk4iVBVueJe568OfHEE/HVr34VX/nKV3DzzTfjlltuyXrctm2oqoprrrkGp556qu8LJSIiImo2RrJ4UmZx2l4srqOtysCIYKrz5M/YnjuqlvlLPwCI4Q4IsgpjzFvxZNs29n3vI+g4/QJ0nXVR0edOxd3OU54ujmkAtlWweHIizIXszpPkXC+zWImXWTwJajBrFNAVUCRMxXTYhgZBUUsWhkLGz3G2p+2V1WO9+OKLcdZZZ+H222/H448/jsHBQRiGgTlz5uDUU0/FpZdeisWLF9dqrURERERNxY3WbsjYXrN0nhJG1WN7wUA6MMIPbjy3MG1/jiAIkDt6YYx7LJ60GIzxo5h4+g8li6fJqFPs5Os8WbpzGG2htD1BECAGQtnFk+j8LIQKz3kCnOLRztN5UhURw+PO2F6ppD1g2tieys5TWebNm4cPf/jD+PCHP1yL9RARERHNGIZZ/+Ip1XkyGl88WZaNWKL6wIhAamzPz86TkLcwkDrmwBgf8nQdc2oMAKAf3Q9tcB/UvsJNgmJ7nuxk8VSsUBED4ezACMEZA7Sk5HlNtl3B2F4QxsRwztcDioyEbsLSPRZPKvc8uXy505955hncc8892Ldvnx+XIyIiIpoRDNM5L6ghxVMTdJ7impMwV31Uub+BEbYeh6AG8o6jyR1zPHeezOhY6r+ntj9S9LmTscKdJ9tIFk8FOk+A02HK7DwFksWTITrFjZbscpbTeRLUYN7OU0B1D8ktHGKRdR0lAAjOZ3y273kq605/+OGH8e53vxt/+tOfUl/72Mc+hiuuuAL/+I//iPPPPx/XXXed74skIiIiakapzlMd9zwFkoERzTC2F407naJqD8lNRZUnfErb0+IQlfwhFnJHL8zJEScIogS38ySGIpja/nDR507FdIgCEArkFpJW8jylQmN7gFOU2BmBEUHBKcY0wXmNG6ZRdmBEnj1PqiKmDsn10nlyY8/da85mnu/0p556Cu9///vx+OOPY+/evQCA3/3ud7jnnnsQDAbxpje9CV1dXbjxxhtx77331mzBRERERM3CSHYDlDp2nmRJhCg0R2BENBmSUG3nyY0q921sT4/n7HdyyR1zANuCmWecbTq3eGo/+fXQBvZCHz5Y8LmTMR3hoAJRzO12pcb2ihVPavbYnmo5BVcCTnGTKp48HpLrXDOYP21PkVJR5V6KJ+daTtHEsT2PbrnlFhiGgS9+8Yu48sorAQC33347BEHAl7/8ZXz3u9/FbbfdhmAwiJ/97Gc1WzARERFRs9AbEFUuCAJURWqKsb1owu08VVc8SaIARRZ9DYwo1CGRO+YAgKd9T2Z0HADQccqbABQf3ZuK6VgdGsLUjkdz15MqnorteQrBSkyl/qzYCVg2oNnZSYTBstL2QrC1OGw7u9AOqDJ0w3L2PHkY23PXBwACx/a8+etf/4qTTjoJV155JSRJgqZpePjhhyHLMt70JucDNW/ePJx66ql4/vnna7ZgIiIiombRiLE9wNn31BRje7Fk8VRlYATgFAW+RZUXOVMpXTwNlryOOTUGMdgGpWc+AgtWFS+eonFcLNyHgbtvyBkJTKXtycXG9rI7T4qtIWEriCc7jO7fd7mBEUC6eHO5o5/G+BCkcKfHa4UAUYYgVf93PZN5vtPHxsawYMGC1J+feOIJxGIxnHTSSQiH0+27cDiMaDSa7xJERERELcVoQFQ5kCyefOrSVCOa8GdsD3C6If52noqM7cFr52ksVVy0rTkLiUM7oY8O5H3uwvFn0WFPwE5EkTi0K3s9hjOCV3Rsb1rxJJlxxG0l9TNJj+2Vt+cJAKxE9uheQJEQEhIwxwYQmLfc47WCEAOhkmdCtTrPd/rcuXNx+PDh1J//+Mc/QhAEnH322amv2baN7du3o6+vz99VEhERETWhRkSVA07noCnG9nwKjACczpNfBaGlxQoWT2IgBDEQ9pS4Z06NQQx3AHCKJwCY2pHbfbItE6fEH8W43AMAiO99Nvtxd2xPLREYocdTXSvJTCBuq6mfSSWdJyHVecoOjQioEhZKIwAAdd4Kb9cKhGd9WARQRvF04okn4umnn8Ztt92GBx98EHfccQcApEb2NE3Dv/3bv2H//v0488wza7JYIiIiombiRpUrDRjba47ACH/2PAFOSp17VlImY3wIA3ffkNp/5IWtJwoGRgCA3DkHxpiH4ik6BqnN6Twp3fOgzl2OqW25xdPkc39GF8axo++NUPuXILbnuazHvY7tAe4ZVYBoxBC3FSR052fsZ+dJVSQslp3OW2Cut85TxylvRNer3uH5vVuV50/6hg0b8Mgjj+Cf/umfADhdpgsuuADHHHMMAOC8887D4OAgOjs7eYAuERERzQp68qDaRoztNUPnKZZM2wvmiecu14qFnfjTkwdgmhak5M/TNg0c+dW3kTiwA22rTkt1f0opFlUOAFK7t7OezKkxBBetTf25be0rMXL/ZhjjQ5A7ep01WiZGH/wlDpg9mJpzHILBSUw8+TvYhg5BdjpyXtL2hFShMwUp2AbBiCNmKxCr6Dy53TdLm9Z5UiQskoZhh7tTxWEp4ZWneH7fVub5Tl+5ciV+8Ytf4B3veAfOPfdcfPzjH8c3v/nN1OMrVqzAG9/4Rvzyl7/E0qVLa7JYIiIiomZiGO4hufXdBxJoksCIqbiBUECClCeeu1yvOLYPsYSBF/eNpr42/IdbkTiwAwBgeIgWd9la4ahyIHlQ7kTxPU+2ZcKKTkBq60h9LT26l07Um3z+QejDh3BP9CREwipCy06EbWiIH3ghfS3d3fNUJG0v6HSebHffk5bc85Rw9zy5aXveC1W3ILO1aXueVAmL5GFY3Ys9X4scZf0zweLFi/Ev//IveR/78Y9/7Md6iIiIiGYMvYFpe1Px3BG3eovGdV/2OwHAScf0QRCAJ18YxJplPZja/gjGHtuCjnXnY/zJ38Gc9FY82ZYJ29SLdp7kzjmwouOw9ETBg2ut2CQAOyuNTu1dCKVvCaa2P4zO0y9wuk5/+SWk3sV4dngxXhVSEFpyHCCIiO15FqGlxzvX0uMQZBWCUPhzIqrJsb1U8RRF3J4DSZs2tudD50kVDETEMWgdLJ7KVd87nYiIiKiFNC4wojnG9qIJw5f9TgDQ0aZi5cJOPP3iIPThQxjY8j0E5h+D3vPeCynSDWNixNN13C5L8c6TM3JXLHHPjDoH5E4fa2tbcxbiL2+DMTmKqe2PQB86AJz8dtgQEAkpEINtCMxfifje9L4nW0+UPE/JPUfJSjip1ZYWgy4E0ml7egV7ntxrTu88TRyEKADx9oWer0WOgp/2q6++GoIg4F/+5V8wd+5cXH311Z4vKggCbr75Zl8WSERERNSs3OJJqfueJxGJJgiMiMUNX854cp28qg+/fmAHDt12OwRBRP/6T0CQFciRbs+dp1TgQpH9RW5cuTl+FOhdkPc55lT+4imy5pUY/fMvMLX9EYz/9R4ocxZhat7JAB5EJOz8LELLTsDoI3clU/9CzmG0RcIigMzAiBhs04CtJ2CIARgZnSdBKC+cRFDyd57ksX0wAcTa8n/vVFjB4umhhx6CIAipM5seeughzxed7fnvRERENDukznlqSNpe4ztPU3EdIZ86T4Cz70l+dBOMgT2Yd/nnoXT2AwCk9h6nw+OBpSeLpyKx2umzngqHRrjpftMPkVX6FkPpXYCRP/0MVmwS/Rd/DEfizt9FW8gpnoJLTwQeuh3xfdsRXnkKbKPweKArlYwXn0oVO6ac3XkKKFJZv2enDsmd1nkShl/GpBVAVGz3fC1yFPy0f//730coFEodjLtp06a6LYqIiIhoJpj1Y3txA72dhcfjyrV06jl0BF/CnjnnYsWqdamvy+09iO95tsgr0zyN7bW7Y3tFiqcCnSdBENC2+iyMPvQrKD0L0Lb2VZh86hAAIOIWT4vXAJKM2J5nneJJTxRN2gPSgRGWFkvte7LkYGpcL66ZZe13AgBBkiFISk7nyR56GfvNHlhG47uXM03B4ukjH/kI+vv7cfHFF+OSSy7BGWecUc91ERERETU9vUHFk6r4d6BsNWJxHW0+BUZoAy9j9Lc34ZC8GHeMn4jXZzwmRXpgJaJOBHmRogjI7DwVfp4gK5DauorveZoaAwQRYiiS81jk+HMw+vAd6H71FRBEKXU+ldt5EpUAggtXp8578rLnyRmxE5zv0933JIfSh+RqBgJlJO2lrhsIZXWebFOHObQP+401mNMEBfhMU/BOX7NmDQYGBnDjjTfiLW95C975znfijjvuQCwWK/QSIiIiolmlUVHlqiLBtGyYZmM7B9GE4dvY3tDvboEYCGPw5Hdj9+FJjIynf+GX23sAwNO+p1TnqUSnR+6YA2N8sODjZnQMUrgjb0Ke2r8USz92CyLHnwMAmIw5UeRu5wlw9j1ph3fBjE3A0rWSY3uCIEAMhGAlYqniyZaDiLt7npJje+US1WBW50kb3AdYJvabPU1RgM80BYunO+64A3fffTeuvvpq9Pf344knnsDnPvc5nHPOOfjSl76Ep556qo7LJCIiImo+hmlBloS67/cOKM6vcI0868mybMQS/gVGaEcPILTyVJxw/AoAwNMvpgsbqb0bADwl7qUCI0p0qKSO3pKdp8wznnJeH07vF5qKGVAVCYqcLm5Cy04EYCO+93mn81QiMAIAhEA4q3iCGkrveapgbA9wi6d0IZo4vAsAcAR9TXFW2ExTtMe8atUqfPrTn8b999+PW265BW9/+9thWRZ+8Ytf4O/+7u/wtre9DT/60Y8wPOz90DIiIiKiVmGYVlnpZ35Rkx0IrYGJe3HNgG3Dl6hy29RhTo5A6ezD8oWdaA8reCqjeJIj3jtPloc9T4DbeToK27bzPu50njrzPjbdZFTL6joBQGDBMRCUIGJ7n4VtlB7bA5DsPE2lDsoV1XDqcNxKO0+CGoKd2Xk6vBuCGsKk3MXiqQKe7nZBEPCqV70K3/zmN/HQQw/hX//1X3HWWWdh165d+MY3voFXv/rV2LhxIx544AFYFjeeERER0exgGFbd9zsBmcVT4375jcadX+r9KJ6cDpANuXMOJFHAScf04ekXBlOFjTu2Z0x4GNvTEwAAUSmctgc4xZOtxWHFp/I+bk6NQWzzVjxNxfXUfieXICkILl6L2J5nix7Gm0kMhGFr6c6TEKhF52k3AnOXQVFkju1VoOy7PRQK4eKLL8aPfvQj3H///fjEJz6B5cuX43e/+x0+9KEP4TWveQ2uvfbaWqyViIiIqKnoZmOLp0Z2DqJxJyQh7ENghDHmdJnkzj4ATmT50bE4DgxOAnDG2QQlANND8ZTuPJXY89RZPK7cjI5DChce28s0GdVzOk+As+9JP7of5tR4yT1YgNNpyhzbk4NhxBMZaXsV7XkKpfY82ZYJbWAP1HkrEFAkdp4qUNXd3t/fj/e///24++678Zvf/AZXX301RkZGcNNNN/m1PiIiIqKmZZhW3c94ApD6JbqhnaeEn50np4Bxz196xbFOEfXUC05RJQgCpEg3jMnSe55sLQYIIgSpeFGXPig3d9+TbeiwE1HPY3v5Ok+Au+8JgGV4K54CoXTaniBCCYRSBU5CNxGsoPMkZHSe9OFDsPUEAvOWI6A2R9z9TFP1p318fBz33nsv7r33Xjz66KMwDANtbW1+rI2IiIioqRmG3ZDOU6AJ9jxFY8niyYfACGPMKZ6kDuf8pXm9bZjbE8ZTLwzibec4ARJye6+3zpPuxJmXCvFIn/WUm7iXOiDX49jeZFTH4rm5B86qc5dBDEZgxSc9j+1ZiRgsLQYxEEYwIEPTTViWDU0zK4oqF9V0VLkbFhGYtwKqspdjexWoqHhKJBK47777cPfdd+Mvf/kLDMO5eU477TSsX78e559/vq+LJCIiImpGRsPG9pz39KNzoA8fAgQBSve8sl4XTbhjez50nsYGIbV1QZTToQqvOLYPf37qAEzTgiSJkNq7kTjwYslr2VqiZFgEAEiRLkCU8ibupQ7I9dp5iumI5BlfFEQJwaXHI7rjUY+dpzAszek8iYFQao9TQjeR0I2qospt23bCIiQFSu9CBJT9HNurgOdPu2VZ+POf/4wtW7bgvvvuQyzm/CXMmzcPF198MdavX4/FixfXcq1ERERETcUwLSgzfM/T4P/+ALBMLHj3V8t6XTowwofO0/jR1H4n1yuO7cO9j+zFi/tHsWZpD+RID6KTI7Btu2hXydLjEJXSxZMgSpDbe/LueTKjyeLJQ+fJsmxnbC+c/+cQWnqCUzx5iCoXkwfaWrFJiIFwqtMU14yKAyMENQRYJmAaSBzeBbV/KQRJRkCVEB3Xy77ebFeyeNq6dSu2bNmCe++9FyMjzgdWVVW8+c1vxvr163HOOefU/WwDIiIiomagmxZkuf6/BwV8LJ6s+JSzF8a28h4IW4ivaXtjg1DnLs362okr50AQgKdfGMSapT2Q2ntgGxqs+CSkUO6InMvW4p46T0A6rny6VOfJQ/EUSziR7fkCIwAgtOJkAIKna4mBMAAnVVAMhFN7nCajOiwbFXeeAMBKRKEd2Y22tWcDcApwdp7KV/DTfu2112LLli04dOhQKiZy7dq1WL9+Pd7+9rejs9NbG5OIiIioVbVCVLmtJ2DrcRgjR6D0zPf8ulgybS8YqK54sm0bxvhRhFedlvX1zkgAKxZ24qkXB3HFG1en4srNiZGixZOlxUsekOuSO+YgfmBHztdTnScPY3uTMefnUKh4UnsXYtEHv+PpZyuoTry6MTGEwPxjEEx2nsYmnfj1yqLKnWtqgy/Dik8hMG+5cy1F4p6nChT8tN94440AgK6uLrztbW/DpZdeijVr1tRtYURERETNrhX2PFnJc5ESA3vKKp6m4gZCAQmSWF3nzYqOwza0VHR4ples6sOdf9qJWMKAFOkGABiTw1D7lxS8nq3HIXrcqyR19MLYNpzTdTOnxiDIqqcO1lSyeMqXtudS5yzytB6382RFxyEGw6liaWxSA4CK0/YAIP7yNmct85wADidtj+ezlqtg8XTOOedg/fr1OO+886Ao1c+yEhEREbUaw7Sq7rxUIj22V/0vv7bhFE/akT3Amld6fl00riPkS9Je8oynjr6cx15xbB9u++NL+NuuIZw8z+08FU/cs7Q45K5+T+8td8wBLAPm5Bjk9u7U183oGKRwh6etKZMxp7CJhNQSzyzNLZ4A58wnt1gan0p2nio85wkAYvueBwQxVXg65zwZ1S551il4t//whz+s5zqIiIiIZhzDsBsaGOHP2J7zy792ZG9Zr4smDLSFfDzjKU/nae3yXiiyiKdfHMSpx6xynu+heBKUkKf3ds96MsaPZhdPU2OeY8q9dJ68EgPpdYvBcHpsb8r5O6pmbC+xfwfUvkWpREN3bK9UAAdlq//dXsDIyAi++tWv4rzzzsNJJ52ECy64AD/84Q9TMehEREREzUZv0NieIosQhOqLJ9u2YBvJ4mlgT1mvjcUNX8540ot0ngKKhOOW9+CpFwYhKgGIwQjMEgfl2np5e54AwJjIDo0wp8Y9j/5NRovveSpHducplDG253aeyi9W3bE929Cgzl2R+rqqSLBswDDtapY86zRF8TQ5OYkrr7wSt956K4455hhcddVVaG9vx7e+9S1s2LAhFVhBRERE1EwatedJEARf0tJsw/nFXwxFYIwNwoxPeX7tVFxHyI+kvfGjEJQgxFAk7+Mnr+rDnkPjGJmIQ2rvgTGRey5TJktLlF88jU0rnqJldJ7iPnae1IzOUyC952l8sprOU/pn4YZFZF6LiXvlqf+Qbh433ngjdu3ahS984Qt497vfnfr6Jz7xCWzZsgUPPPAAXvva1zZugURERER5GA2KKgcAVZaq7zwlwyKCC1cj+tJWaAN7EFpyvKfXRuMGeju9FSnFGGODkDvnFBwdO2GFU+C8uG8Ui9u7YU4U7jzZpg5YhqcDaQGnaBRkFWZGXLlt27DKGNubjOoQBSDkw963rM5TIHNsr/o9T0A6LCLzWgnN8KVrNls0RefpwIEDmD9/Pq688sqsr19wwQUAgCeffLIRyyIiIiIqqlFR5QAQUMSq09Lc4imw8FgAydAIj2Jx3ZexPWPsaN6RPde8XqegGByJQYr0wJgsvOfJ0uIA4LnzJAgC5M45MMbT3Sxbi8E2dU8x5YCz5ykcVCBWmToIuCN2znXEQCgVGDFWRecpMzEwMHdZ6r/T++aYuFeOpug8ffvb38779V27dgEA5szJ3UBIRERE1GiGaTUkMALw55BTN6Zc6Z4LMdxRVvEUTRgI+xIYMYjA/BUFH++MBCBLIgZHopDbe2BOjsK2TAhibiHhFoNeD8kFcg/KNaPjAAAp3OHp9ZMxHZGwP50bQRAgBkKwElGIgTAUWYQoZKTtVVI8ySogiM7fcUZni2N7lWmKzlMm27YxNDSEn/70p7j++uuxYMECXHjhhY1eFhEREVEOZ2yvccVT9WN7TkdDUIII9C9FwmPinmXZiCWqD4yw9ASs6Hhq71E+oiigryuEwVGn8wTbgjk1nv96budJ8V48Se3Tiqep5AG5Xsf2Yrov+51cQrLAEQNhCIKAgCqnO08VjO25BZk6d3nW1zPH9si7pug8Zfrud7+L//iP/wDgdJxuvvlmdHZ6+/ASERER1ZNu2A0c2/MjMCLZqVFUqHOXYfyJewp2dTLFNQO2DYSrDIxIx5QXHtsDgL7uEAZHYqk4cXNyOCta3OUWT2V1njrnON0sU4cgKeniqYyxPT/3DImBEEykY8uDqoRYwilwKuk8AcCcCz4EtTf7oN4Ax/Yq0nTF08KFC3H11Vdj3759uO+++3DVVVfhhz/8IY4/Pnvz4vXXX48bbrgh62ubN2/Gtm3barq+eDxe8/egmY2fESqGnw8qhZ+RmcO2bRimhdGRobr9nWV+PnQ9jkQCVb23cOQlqABePnAYgqFCMXXsePwvsDuKHzI7OuUkzI2NDGLbNr3q9z8wOgW7yPehCBr2Dkax76gKFcCe55+GNarlXm9wF1QA+w4dgW14+7mIUxoU2Nj+5GNAWw/E3duhANh1cAAYTZR8/fDoJPq7VN8+A4rpjIa9tPcAcGQMAtLFzc6XXoBY4kym/P8b0g0MTQFD6a8fHIgBAF7ctRuyPujL2meq1atXZ/15w4YN2LhxY97nNl3xdNlll6X++/7778eHPvQhfOYzn8Hdd9+dlcKycePGnG9q69atWLt2bU3Xt23btpq/B81s/IxQMfx8UCn8jMwcumEBeBHz5vVj7drVJZ/vh8zPR/dfRjE2majq8zIlTuAIgOXHHAsIAg5svQ2LIiIiJa758uFxALuxcvkSrF27sOL3H48fwFEAK086DUpn4YJt1V4BT760A8uOPwMH7wfmd7WhI88ap+Sp5PezGoEFx3haQzSQwOG/3oFl/V0ILVmLkaG/YQTAmpPXQZBLd5R0ay/mz+317b499NQcxIb3YfWJJ0OUVXREDmN4QoeqSDj+uONKvt7r/4aEu8YB7MPcuQuxdu0CH1Y+M23duhU7duzw/Pym2/OU6bWvfS1e+cpX4sUXX8TLL7/c6OUQERERpRim0xFobGBElWl7qbG9ANQ5CwFRRsJDaEQ0OUZW/djeICCIkCM9RZ/X1x2CZQNjRhAQxIKJe3YlY3vuWU/JxD0zOubsN/JQOAHAZMzwdc+TGAgBogxBcq7pjuoFKxzZK8RN22NgRHkaXjwZhoGHHnoIDz74YN7HFyxwKuGRkeKnSRMRERHVk1s8NXLPU7WBEW7anqioECQF6pxF0DyERkRjyeKpysAIY/wopEg3BKl4EdbX5ez/OTquQWrrhDmRv3gqN6ocyD0o1yzjjCfdMKHppq97nqRQO6RQJDVx5RZNle53KoRpe5VpirG9D33oQ2hra8Nf/vIXSFL2B2P79u0QBAGLFi0q8GoiIiKi+jOMZPHUoLS9gOpj2p7sHCqrzl2G2O6nS74umnD2OVXdeRobLBkWATidJwAYHImiM9IDo8BBubae7DyVkbYnqkGIwUjqoFwzOg7RY1jEZMz5OfjZeeo6+xJETnx16s/uQbmVJO0Vk07bY/FUjoZ3nmRZxhvf+EYMDw/j5ptvznps8+bNeO655/Da176WZz0RERFRU9Eb3HnyJ6o8nbYHAOrcpTAnR1KJc4VE407nKVR18XQUcmfp3/HmJDtPg6NO4p5ZYGwv3XkKlLUOuaM3lfxXTudpMuoUT352nuSOOQguWpP6c6BGnaf0IbksnsrRFJ2nT3/603jiiSfw7W9/G48++iiOPfZYbNu2DQ8//DAWLVqEr3zlK41eIhEREVGWRo/tqbLo2yG5guwUT4H+ZQCAxJE9CK84ueDr3OKpLVh50WDbFozxIUSOe1XJ5wZVGR1tKgZGYpDaexDfn3+Dv63Hs/YLeZV5UK4VHYOUUbwUMxX3v/M0Xa06T7IkQBQFju2VqeGdJwCYO3cufvnLX+Lyyy/Hjh07sGnTJuzduxfvec978Mtf/hJz585t9BKJiIiIsrhje40KjAgoEgzThmnZFV/DNhIQlEBqf406dxkAQBvYU/R1sWTREAxU/u/w5uQoYBlFD8jN1N8dwuBIFHKkB1ZsAraRG5FuafGy9ju5nOJpCLZtwYxOQGrr8PS6VOcpXLviKdV58rl4EgTBOSuMY3tlaYrOEwD09fXhn//5nxu9DCIiIiJPDNMpWmS5+Lk7tZI5dhWqsIixdQ2Ckh5xk8IdkCI90Eok7k3FDYQCEiSx8u89dUBuR+k9TwDQ1x3GgcFJSMnDcY3JEShd2fHmlhYvK2nPJXXMgRWfdEIjbKusA3KB6jpwpbiBEdUUqoX4EToy2zRF54mIiIhopmn42J4Pe1YsXUuN7KWuO3dpyc5TNK4jVG3S3phzMKuXwAjASdwbHIlCSsaa59v3ZOsVdp6S+64Sh3cCgPc9T7GZ23kCAFWVOLZXJhZPRERERBXQjeYonqr55dc2EhCV7OIpMHcZtKMH8o7FuaIJA22h6pP2AHgKjACcxL1YwoSuOiN1Rp64ckuLQ1TKC4sAnMAIANAO7QLgvXhyO09+BkZMl9rz5HNgBACO7VWAxRMRERFRBVKdp0ZFlSvO+1bTebL1RCqm3KXOXQ5YJrSj+wu+LhY3qj/jaWwQYrANYiDs6fl9Xc7zhg2ns5TvrCe7wrE9d99VqvNURlS5qkhQZP8LG1ewhp2ngFJ96Mhs0zR7noiIiIhmErd4alRgRHpsz6r4GraeyNrzBABq/1LnugN7EJi3PO/rpuJ69THl40c9h0UA6bOejkYlzJFkGJO5Zz1ZWhxye0/Za3FeIyBxyC2evAVGTMX0mnadACBQw87T289dkfockTcsnoiIiIgqYDTJ2F61e56m7xFSeuZDkNWioRHRuIHezvI7PJmMsTKLp4yznuZFevJ3nvRERZ0nQVIgRbpgTo4AgggxFPH0usmYVtOYcqC2nafXn7bE92u2Oo7tEREREVXATdtTGjW2p/qw50lPpA7IdQmiBLVvCRIDewu+LhbXqx/bGx/0HBYBAJ2RABRZxOBoDFJ7d5E9T5UVdW4hJ4XbIYjeCpW6dJ4U95Bc9jyaAYsnIiIiogroDd/zVH3nyT3naTp13nJoh3bCNo28r4smDISrCIywElFY8amyiidRFDCnK4TBkRjk9p68aXuWXtmeJyBdPIke9zsBzp6n2neeaje2R+Vj8URERERUAT1ZtDR6z1M1nSdL1yBOiyoHgPAx62Aloojtfib3NZaNWKK6wAhjLHnGUxnFE5CMKx+NQYr05HSebNuGXeEhuUA6cc9r0h6Q7DzVMKYcAIKB2o3tUflYPBERERFVwD3jp9adh0JUP9L2CnSewiteATHYhsnnH8x5LK4ZsG0gXEVghDGejCkvY88T4IRGDIxEIbf3wNbisBKx1GO2qQO2VXHxJKXG9ryFRQDAZFRHpIYH5ALAov4IXn/aYpy4sryfFdUGiyciIiKiCkxENYiiUFURUY1AqvNUTdqelrd4EmQFbavPxNSOR2EZWtZj0bgzypf5fVuJGPSRw57fN9V5Krd46gpjeDwOoa3buU7G6J6txZ21V7vnyWPnybJsROM62mrceVJkCf/4d6em0gapsVg8EREREVVgMhkWIAhCQ96/2rQ927ZgGxpEOf+hsm3HnQNbiyH20pNZX4/GnY5b5tje0XtuxP6bPg5j/Kin9zbGBwFRhtTeXdaa+7pDsG1gSmgDkH3Wk5Usniof23M7T96Kp1jCgGXX9oBcaj4snoiIiIgqMBnV0V7jrkMxVRdPutNRmp625wotOwFiuAOTz/8l6+vRRLLzlAyMMCZHMPn8Q7D1BIbu2+TpvZ2Y8h4IQnm/ivYnuy8jyYNyM/c9pTpPFRZPSs88CEoAypyFnp4/lRzbZPE0u7B4IiIiIqrARFRDJJS/8KgHNZnyV2lghK0nACDv2B7gRJZH1rwS0Ze2pro6ABCNJYunZOdp4snfA5aByAmvxtTzDyK297mS762PlRdT7urrDgMABjVnzWbGQbmWnuw8VTi2J4XasfSjN6Ft9Vment/oPW/UGCyeiIiIiCowGdVqnrRWjCAIUGURWoV7nizDKZ7EAsUTALQdfzZsPYHoi0+kvhZNJMf2gjJsy8T4k79FaMXJmHPBhyB39mHotzfDtgoXdGZsEvrQ/oqKpznJg3IHJmwIagjGxFDqsXTnqfD3U4oYbPM8hpnuPDWugKb6Y/FEREREVIHJmI72cGN/cQ6oUvVje3miyl3BxWshRXqyRvfcwIhQUMbUC4/BnBhGx7q3QFQC6D3vvdAGXsb41nvzv6dtYfCuf4eViKHj1DeXveaAIqEzoiYT97phTmR0ntw9T0p9ghUmY87Pj52n2YXFExEREVEFJqK1P+OnFFXxoXgq0nkSBBGR416F6M4nYcanAKSLp7aggvEnfgO5sw/hY04FAIRXn4nQshMx8qf/hjk1lnO9sYfvQPSlreg97z0ILjy2onWnznpq781O23PHECvc81Qu7nmanVg8EREREZXJtGzngNQGj2ypilT5nifD3fNU/HtoO+4cwDQQ3fEoACCWTNsTxw8hvvdv6Dj1zRBEJ7xCEAT0vul9sLQ4hu/fnHWd2J5nMXz/z9C29lXoOO2CitYMOPueBkdikCPd09L2nDOfKk3bKxf3PM1OLJ6IiIiIyuR2HRqZtgc4Y2wJrbLiydJL73kCgMCCYyB39acOzJ2KGwgFJEz99R4IkoL2V7wh6/lq32J0nvYWTDx1HxKHdgJwUvEG7rgOSs989L31I1XFu/d1hXB0NAop0g1jYgS2bSe/H3dsr/I9T+WYjOkQBSAUaMw5X9QYLJ6IiIiIyuTud4k0eM9TULaxdOKpogENhaTG3Aqc8+QSBAGR485BbPczMKPjiMZ1dAZsTDz3ANqOPxtSuCPnNd3nXg6prQNH770Ztqlj4PZrYWkJzF3/KYiB6vYk9XWHEUuYMINdgGXAik0430+VUeXlmorqCAcViGJjzvmixmDxRERERFSmyWhzdJ5W2ztx9uRvEdv9TNmv9bLnydV23NmAbWFq+yOIJgycru6ErcXRse4teZ8vBtvQ87p3InFgBw5u+iLi+7ah760fgtq3uOx1TteXPOtpMnlQrnvWk6UnIMhqaoSw1ibjjd/zRvXH4omIiIioTBNRp/BodNreQvsQAEAb2Fv2a72O7QGA2r8USu9CTD7/F8RiOtbZzyGwYBWCC44p+JrISa9FYMEqJA6+iI515yNy/LllrzGfvq7sg3LdfU+2Fq9b1wlwCmjud5p9WDwRERERlWki2hxhAXP1gwAAbfDlsl+bCowoElXuckf34nufx8LJZ9Ftj6Bj3fklXiOi78KPouucS9F73nvLXl8hbufpaPKgXDdxz9LiddvvBCAZGMLiabZh8URERERUpqkm6DyZ8Sl0GoMAAG2gguIpNbbn7XtoO+5VAGy8Jv4HxMVQ8s/Fqb0L0POav4Mg+1dkdLYFoMgiDk0513Q7T5YWq2/nKcbO02zE4omIiIioTBPuGT8N3POS2L8DAoAD9hxoR/fBNo2yXm/p3jtPAKDOWQR17nIoMLCv4xSIHl/nN1EUMKcrhIFxHWK4A0byoFxbT0BU6lc8NUNUPdUfiyciIiKiMk1ENYQCMmSpcb9KxfdvhwUBj+urAdOAPnyorNfbRgKCEigrNjxy4mug2xIG+s4od7m+6u8OYXAk6pz1lDm2x84T1RiLJyIiIqIyTUYbn7QW378dU6H52Kn1Aig/NMLWNU9Je5na170F/zz2DogdfWW9zm99XWEMjsYgtfek0vZsLQ6hTp0n3TCh6Sb3PM1CLJ6IiIiIyjQZ1dHewJEt2zSQOPAiJtuX4YDWDghi2cWTpSfKHr1LGDbGrDDCwcYeDNvXHcLweBxiW3d6z5Nev87TZKw5AkOo/lg8EREREZVpIqo1dr/T4d2wDQ2xrmUwIUHuWVBB5ylRducpGnf2VTW8eOoKwbaBhNIOc2oMtmXWNarcPeeLnafZh8UTERERUZkmY1pDk/bi+7cDALTu5QAAsXdx2XHldvJQ2XJE407REA40tmhw48qnhAgAG+bkaF07T6OTTthGZ4SBEbMNiyciIiKiMk00eM9TYv92yJ39kCI9zhe6F8MYG4QVn/J8Dcsof89TNJHsPIUaPbYXBgCMmk4RZUwMwdbK76RVamg0BgCYkzywl2YPFk9EREREZbBtG5NRrWEjW7ZtI75vO4KL10BVJACA1bUQAKAN7vN+HV0r+1DZaCxZPDW48+QWLUd1Z/36yGEANkS1PsXM0bG4s45OFk+zDYsnIiIiojIkNBOGaTdsbM8YPQJzahTBReniyeiYD6C8xD1nz1OZY3uJ5Nheg/c8BRQJXZEADkWd9etDBwGgbml7Q6MxREIKgoHG/hyo/lg8EREREZVhwg0LaFDxFN/n7HcKLl6DQLJ4SshdEALh8oono/LAiFCDiycAmNMdwsFxARBE6MNO8VSvPU9Hx2Ic2ZulWDwRERERlWEypgFAw/Y8xfdvhxgIQ+lbjK52p/gZndKg9i0pKzTCiSovr3iaciO6g41PmevrCmFgLA4p0pU6IFhQ67Pn6ehoDL2d9TuQl5oHiyciIiKiMkxEneKpvYHFU2DhagiCiN4O5xf44fE4Av1LoQ3shW3bnq5TySG5w+NxqLLY8LE9wEncGxyJQW7vSXee6jS2d3Qszs7TLMXiiYiIiKgMmWf8mGWk2/lCi0If3Ifg4jUAgI5IAKIoOEVN/xJYiSjM8aOeLlXJnqfRiQS6O4IQBKHspfutryuMuGbCDnXB1pwAh3oERuiGhdGJBHoZFjErsXgiIiIiKoO75yl05Dm8/J33wfBYrPhBHHLS9NziSRIFdLcHMDwWh9q/DACgDZQe3bMtE7aplz22NzweR09Hc4yruWc9aUp76mv1OCR3eNxN2muOnwPVF4snIiIiojJMJsf2pJE9sE0dsd3P+HZtbegAJp/7c8HHhaG9gCghsGBV6mvdHUGn89S3GACQ8BAaYRtOAVhu52lkIp7aZ9Vo/cniaVKIpL5WbvR6JY4mz3jq5djerMTiiYiIiKgME1ENsiTAGnVCCmIvP+/btccevhMDd34HE0//Ie/j4vDLCMxdnlUk9CaLJzHYBrljDrRBD8WTngCACvY8JZqn89TlHJQ7ZqaLmHp0nobGkgfksvM0K7F4IiIiIirDZExHJKzCSCa8xV/+m2/XdoMPBn/zn4gfeCHrMdvUIQzvRyA5sufq6QhiKHloq9q/1NPYnmU4xVM5nRpNNzEV09Hd0Rydp86ICkUWcVRPFzH1iCo/Opoc22PnaVZi8URERERUhsmojvaQDH34EAQ1BGN0wLd9T/rwIYSPPQNyey+O/PKbMCaGU48lDu+GYBkILppWPHUGMRHVoBsm1P6l0IcOwDb1ou9j687oYTmdp5EJp+DqaW+OjosgCOjrCuFwLJ16WG4nrRJDYzGEAjLCTRDXTvXH4omIiIioDBNRDXODGmxDQ+SEcwEAsb3Vd5+sRBTm1CiCC4/FvMs+CysRw5FffhOW4RQ6qcNxpxdPqbjyBNT+pYBlQjt6oOh7pcb2ZO97nkaSQQndTTK2BzihEfsnndh0QQlAEGr/qy0PyJ3dWDwRERERlWEyqmO+MgEAaFtzFsRgG+I+7HtyD3pVeuZD7V+C/gs/isTBF3H0NzfCtm3E92+H3dYNub0763Wp4mnMiSsHAK1EaISV2vPkvXhyU+a6myQwAnD2Pe0ftSDIal1G9gAnMIL7nWYvFk9EREREZZiMaeiTxgEAau8iBBev9WXfU7p4WgAAaFtzJrrOvRyTz/wR44//Gon922H1Ls15XW9n+qBcpWcBIMnQBovve3I7T+XseXI7T80SGAE4naeRiQSkSDeEeh2QO8oDcmczFk9EREREZZiI6ui2RyAoQUjtPQguOR768CEYEyNVXdcJixAgd89Nfa373MsQPvYMDP3uxzCnxmD1LMl5nVvMDI3HIEgy1N5F0I4U7zyl9jyVcc7TyEQCouAczNss+rtDsG3ACnVBVGu/LsO0MDIR5wG5sxiLJyIiIiKPDNNCLGGgwxiB0jMfgiAgtOQ4ANWn7unDhyB39GZ1gwRBRP+FH4XStwgAYOfpPLWHVciSgOFU4t6SknHltlF+YMTwuHPGkyQKnl9Ta25ceXT5a9F5xttr/n4j4wnYNjCnq3m6bzONMTaI+IEXYIwNNnopFZEbvQAiIiKimWIy6qTYhRNDUBY6wQ3qvOUQ1BBie/+GyPHnVHxtffgQlN4FOV8XAyHMv+ILmHrhcRxs6899XBRSB+UCTlz55HN/ghmbgBRqz/teViVjexMJdDVJ0p6rL3lQ7uH2NTju5NyunN/cM57YeSpf4vAuDG75HozxYQAWABFyRw/63vb/EJi3otHL84ydJyIiIiKPJmMaJJhQ4sNQeuYDAARRQnDxmqo6T7ZtQx8+CKV7ft7H5c4+dJ5+ASDk7/r0TCueABQ978k2KguMaKb9TgDQm9x7NDgSq8v7HXUPyOWep7IkDu/Coc3XQDuyB1ZsHFZsElZsHNqRPTi0+RokDu9q9BI9Y/FERERE5NFkVEevOAkBdirYAQBCS46HPnQAxuRoRde1YhOw4lN5O09e5C+eCo/uVRJVPjoRb6qkPQAIKBK6IgEMjtapeHIPyGXaXlkGt3wPVmwi72NWbAKDW75f5xVVjsUTERERkUcTUQ39yaS9zOIpuPR4AEB8X2WR5U5YBFLdrHL1dgRTe56kSDfEUKRo8WSVWTyZlo3RiUTTdZ4AYE53CAPD0bq819BYDAFVQluIB+R6ZYwNJkf1ijxnYmjG7IFi8URERETk0URUR780BiC70AnMWwFBCSJe4WG5+lB1xVNPZxBTcQPxhAFBEKD2LS0aV27rWvJQWW/hD+OTCVh2c53x5OrvDtWx8+Sc8eT150aAMTkCZ49TEbadfF7zY/FERERE5NFkTEOfOA4h1AEpFEl9XZBkBBevRqzCw3L14UOAKEHuzA2E8CJ1UO5EenRPG3wZtp3/l1ZbT5SdtAcA3U3YeerrCmNwNAbbtmv+XkdHY9zvVCY50o2SJYcgJJ/X/Fg8EREREXk0GdXRL01AzbM3KbjkeOiDL8OMjpd9XX34EJSufghSZUHIqeIpI67c1uIwRgfyPt8yEhDL2O80MpHIep9m0tcdQkIzMZFMQqylo2M846lccmcf5I6e4s9p74Xc2VenFVWHxRMRERGRRxNRDf3yeN7iKbQkue/p5W1lX1cfPpS1h6pcPckAg5Fxp8gplbjnju15NdLUnSc3ca+2+55My8bweHzWdp7ueOAlfOe//1rRa/ve9v8gFojNF0Pt6HvbR6pZWl2xeCIiIiLyKD45iQ4hlrfQCSxYCUFWESszsty2Legjhyre7wQ4gREAMOQm7vUtBlA4ca/ssb3kOGAz7nlyz3qq9b6n0Yk4LMuetUl7uw6M4bmdQxW9NjBvBeZf+SWoc5dDDHdADLVDDHdAnbsc86/80ow654mH5BIRERF5JE46Y3D5iidBUhBYtBrxMvc9mRMjsPVEVcVTW0iBKoupvUmiGoLcPQ/aYP7iyTK0smLKR8YTznsoUsVrrJW+rjAAYKDGnaeh5Ehk7yztPCmyBN0wK359YN4KLPq//+ak702OQI50z5hRvUzsPBERERF5pEaTxVNv/kIntOQ4aEf2wIxNer5mOqa88rE9QRDQ05mOKwcAtW9J0c6TWGZgRE9H83WdAKAzokKVxZoflHs02dmaM0v3PKmyCE0vkZrngdzZh+DCY2dk4QSweCIiIiLyLJwYgg1A7p6X9/HgkuMB2Ijv877vSR8+BKDymHJX5kG5gBMaoQ8fTp3plMkZ2yvngNwEutubc1xNEAT01SGu/OiYc/3eWTq2pygSdLP64mmmY/FERERE5FG7MYKY0lUwqS6wcBUESUG8jH1P+vBBCLIKqaO3qrU5xVO6gFD7lwG2Bf3ogZznWhVElTdj0p5rTlcIR2vceRoajUORRXS0eS86W4kqi9B1sy6R8M2MxRMRERGRB7Zto9seRSI4p+BzRFlFYOEqxPZ63/fkJO3NgyBU92tZT2du5wkAtIE9Oc+1dQ2i7K14sm0bI+NxdDVhWISrMxLAeFSr6XscHYthTmdo1h6Qq8giLNtJHZzNmqZ4GhwcxJe+9CW85jWvwQknnICzzz4bn/zkJ7Fv375GL42IiIgI0biOPmkcRqT4QbbBJcdBO7IbVnzK03X14YOQu6sb2QOcxL1YwkQ07px3pHTPgyCr0AZz48ptw3tU+VTcgGZYTd15ag+rmKx18TQaQ29X8/4Mak2RnbAQTa88NKIVNEXxNDg4iMsuuww///nPsXLlSrzrXe/CiSeeiC1btuDSSy/Fnj17Gr1EIiIimuXGh44iKOgQOuYWfV5oyfGAbSG+f3vJa9qWCX1kIO+5UeVKHZSb7D4JogRlzmJoR/bkvm8Ze56a+YwnVySsYDKmw6phV+To2Ow94wkAVMUpG3Rjdu97aori6frrr8ehQ4fw2c9+Frfccgs+85nP4Ac/+AG++c1vYnR0FP/6r//a6CUSERHRLDd12JmGkbqLFzqBRasBUUbMQ2S5MTYIWEZVSXsu96DczNG90JK1iO15FiN//kVqr4ptmbBN3fPY3kjyjKdmTdsDnM6TbSPVdfObZdkYTo7tzVaKzOIJaJLi6fe//z16enrwnve8J+vrF154IZYsWYK//OUvsKzZ/RdFREREjaUlgxeCc4oXOqISQGDBMYjvLR0aoQ+5MeXVj+2lOk8ZceU9r3snIie+FiN/+jkG7/wuLEODbTjjbV47T8PjTlpfs6btAUAkpAAAJqK1KZ7GphIwzNl7QC6QMbZXxVlPraDhh+SapokPfvCDkGUZophby6mqCl3Xoes6AoHm/RcPIiIiqp//vP0Z7B+YxN+/7XisWNhZl/c0Rg5Bt0W0zckfU54ptOQ4jD58BywtBlEt3K3QR9yYcv/H9gBAkBX0vX0DlN6FGLn/p9DHBtD3lg85j3nc8zQTxvbaw04hOBHVMB9tvl9/aHR2H5ALcGzP1fDiSZKknI6Ta+fOndi1axeWLFnCwomIiIgAALsOjGHLX3ZDFAX843X3482vXIZ3nr+25hHS9vgRHDU7sCZS+neS4NLjgYd+hfj+HQiveEXB5+lDByEEwhDDHVWvLxxUEApIGMoongDnHKTusy+B0jMfg3f9Ow7+9MsA4PmQ3OHxOFRZRFuw4b82FhQJO52nyRp1ntwznmb12J6ULJ58OCh3JmuKsb18LMvCP//zP8OyLFx++eWNXg4RERE1iZ/esx1tIQU3fu48vPWcFbj3kb344Nd/j1//ZRfMGh7iKU8OYMDqQCRcukgLLloNCGLJ0T19+BDUnvm+xV/3dASzxvYyRda+EvPf9c+pSHShwFlV041OJNDdEWzqiO7MzlMtDCUP4J3VaXsKx/aAJug85WPbNr70pS/h4YcfxgknnJC3M3X99dfjhhtuyPra5s2bsW2b9xO9KxGPx2v+HjSz8TNCxfDzQaXwM1LcywMxPPb8YZx/Wi+Gj+zFuatlrOpbgrseGcAPbn8Wd9y/Axe9sh8rF4T9fWPLRCA+hKPWcdj10gueXqJ0LcDwjidwZN6pBZ+jHtkLq3eJ57/zUp+PgGxh/+GR4tc79/9C3vEn7EsogIf33X94CEHZburP5UTUAAC8tHsf+kMTvl9/x65BSCJwcN8uHG7iIhKo3f+GHDoUBQC8tHMPhPiA79dvpNWrV2f9ecOGDdi4cWPe5zZd8WQYBr74xS/iV7/6FRYvXozvf//7UNXcfxnZuHFjzje1detWrF27tqbr27ZtW83fg2Y2fkaoGH4+qBR+Rorb/KeH0NGm4upLzkIo4PwasxbAa19l46FnD+Hmu57Df/7vfnxk/Ul4y6uW+/a++shh7IOFSaXX89/P0KHTMPboFqw+ZkXeETnL0LDnV2PoXbcGPR6vWerzsXhrFDteHi69xnWv9PR+AJC4+yAWzW1v6s+lbljA5l1o6+jB2rWrS7+gTP/7ZBS9XQkcf9xxvl/bb7X63xCpbQTAfixYuAhr1xaP659Jtm7dih07dnh+flON7cViMXzkIx/Br371KyxbtgybNm3C3Lmt85dDRERElXtu51E89cIgLn39qlTh5BIEAWeftADf//TrsWReOx585qCv760POUl7sUCv59eElhwHWAaiLzye93Fj5AgAG6oPYRGunk5nbM+NJffD8HiiqQ/IBZwY7VBAqtnY3tHR2KxO2gPSUeU8JLdJjI2N4T3veQ8eeOABHHfccdi8eTMWLPDvf0yIiIho5rJtG/91z3b0dATwllctK/i8oCpj7bIevLR/zNcCQh92UvG0cJ/n1wSXHA+lZwEG7vgOhn73I1h6Yto1nQJP9iGm3NXTEYRmWJiK+ROckNBNTMV0dDfxGU+uSFitWWDE0Gh8VodFABnF0yxP22uK4imRSOCDH/wgnn76aZxxxhm49dZb0dvr/V92iIiIqLU9/eIg/rZrCJe94VgE1eK7DlYt7sJUTMfhoahv768PHUQcAchlpOKJahAL3/dNdKx7M8Ye24IDP/wk4vvT40FuQebHGU+u3mSHaHriXqVGJ5yCr6eJz3hytYdqUzzZto2jYzHMmcUx5QCgJs95MmZ5YERTFE/XXnstnnzySZxyyim46aabEIlEGr0kIiIiahK2beO/frMdc7pCePNZS0s+f+WiLgDAS/tGy3gPC4nDu2Hb+f9VXR8+iCG7A+1t5XVgRDWEOee/H/Ov+v9gmzoObvonDN23CZahQR8+BKmtE1LQv3OJejpzD8qtxkw448kVCSs1Gdsbn9KgG9asTtoD2HlyNTwwYnBwED/96U8BACtWrMBNN92U93kf+MAHeNYTERHRLPT4tiPY8fIINlx2MpTkv34Xs3ReB2RJxEv7R3HuKQtLPl8bOoCjv/4PxPdtQ2D+SvS+8e8RXJy94V4bPoTDRmfqPKFyhZadiEXvvw5D923C2CN3IvriE4BtQ+72r+sE5D8otxrudbrbm/93sPawipePjPt+3aFkITrrx/bcqPJZfs5Tw4unp59+GrrutFhvu+22gs97z3vew+KJiIholrEsGz+9Zzvm9YbxhtOXeHqNIotYtqADL+0fLfo82zIx9shdGPnTzyEoAXS96hJMPHs/Dm76J7SteSV6Xv9OKN3zYOkJmONHcVhfhLkezngqRAyE0HfBB9G25kwM/vo/YI4fRWTRmoqvl4+7N8mv4sntPDV7YATgdp78H9tLHZA768f2kofkzvKxvYYXT+edd15Z8YBEREQ0ezz83CHsOjCGf/y7UyFL3ncbrFrUhQee3A/LsiGKuefyJI7sweCW70E7vAvh1WdizvnvhxzpRtfZ6zH26F0YffgOTL34ODpPfyvCq04DAAxYHVhZYecpU3jFK7D4/ddi9LEtaEte2y9BVUZbSPFvbG8iAVEAOiLN/w/YkZCCyagG27Z9PdA3dUAu0/YAJGPhZ7GGF09ERERE+ZiWjc33bsei/ghec+qisl57zOIu/ObhPTg8NIUFfem91LahY+Qv/4PRh++AFIqg/5JPIrI2feaRqAbRfe7laD/5DRh+YDPGHrkTY49tAQAMmh1oD1XeecokBtvQ8+orfLnWdD0dQd8CI4bH4+hqD0DKU4A2m/awCsO0EdfMnCj7ahwdi0MUBXTNgNCMWhIEAbIkzvqochZPRERE1JT+/NQBvHx4Ap9+12ll//J+TDI04sV9o6niKb5/OwZ//R/Qj+5H5MTXove890IKt+d9vdzRi/63b0TnaRdg6Pc/RuzIyxgwOyre81RPvR1B/8b2JhIzpmiIJEcqJ6Kav8XTaAw9HcEZUUDWmqqI7Dw1egFERERE01mWjZ/dux3L5nfg7JPKP/dxybx2KHIyNOL4Hgz/8acY33ovpI5ezLviCwgfc6qn6wTmr8SCd/0zHn32APQfP4H2KvY81Ut3RwAHdk36cq3h8fiM2O8EAO3JwnYyqqO/27/r8oDcNFWWWDw1egFERERE0x0ZjuLg0Sl85NKT8+5ZKkWWRCxf0AFt11+x7z//HebEMDpOfwt6XnMlxED5G/8nYs6o0kzoPPV0BDEyHvdl78/IeBwrF3b6tLLaas/oPPlpaCyGZQtmxs+g1mRZhMbACCIiIqLmsueQEzm9YoH3Q2kzGZOjuES4D/Mn/waxbwnmrv8kgguPrXg9kzEnxS0yAzpPPZ1BGKaN8SkNnVUEPZiWjbHJxIzpPEUyOk9+MUwLg6NxnLZ2nm/XnMlUWYTOqHIiIiKi5vLyYad4Wjw3/56kYib/9mccveeHmJeI4dfRV+Dit29AcH51c1yTUQ2iAIR93EtTK70dTmdteDxeVfE0PpmAZc+MA3KB2nSetm47Ak03cdIxc3y75kymKhJ0c3YXT94zP4mIiIjqZO/hCcztCSMcLG9MLvrSXzFwx3ehzFkI4eJr8Nv4Sdh5aKrq9UxENbSF1IpGCOvNr4NyZ9IBuUBG5ynmX+fpvif2oTOi4tQ1/b5dcyaTZabtsXgiIiKiprP38DiWzitvZE8fPYKBO78LtX8p5l/5ZSxdfSxUWcRL+0arXs9kVJ8R+50AZ2wPQNVnPY1MJJzrzZDOU0CRoMgiJn3qPI1PaXj8+cN4zamLyjpjrJWpMtP2+EkgIiKipqIbFg4MTGLpfO8je5aewJFffguwLcy99FMQlQAkScTyhZ14af9o1WuajOmpNLdm19PhdIqq7TyNuJ2nGVI8CYKA9rCCCZ/2PP35yf0wTBtvOG2JL9drBaossfPU6AUQERERZTowOAnTsrGi04RtlP5F2LZtHL3nJmhHdqPvon+A0p3e3L9qURd2HRiFadlVrWkiqs2IsAgAUGQJ7WG16oNyhydm1tge4AR6+LXn6b4n9mHZ/A6smCFpg/WgKCL3PDV6AURERESZ9h4ax0r5MBY8cA323/RxxPY8W/T5E0/+DpPP/BFd51yKtlWnZT22clEXYgkTBwerO/doMqqjPTQziicA6O0MVj+2N55AJKRAVSSfVlV77WHVl7S9fUcm8OK+Ubzh9MU+rKp1KLIIbZan7bF4IiKiWSW662mY8eoDBKh2Dr28D38f+RPkrn7YlolDP/3/MHDnd2FOjeU8N37wJRz97c0IrXgFus+9POfxVYu7AKDq0T2n8zQzxvYAZ5+SH4ER3R0zp+sEAJGQ4kvn6b7HX4YoCnjNqYt8WFXrcA7J5dgeERHRrGBpcRz+769i/LFfN3opVIBt6Fj+wmYERBPzLv8cFn3gOnSdfSkmn38I+37wUYw/+TvYtvMv32Z0HEdu+xbkSDf6L/oYBDG3Q7KoPwJVkaoKjbAsG1PxmRMYAfhTPI2Mx9HdPjP2O7kiYaXqwAjTsvHHrfuxbk3/jPv+a01hYASLJyIimj2s+BRgW9AG9zZ6KVTA0O9+hD79ILbOeRvU/7+9O4+PqjofP/65syeZmUz2PWwhYd/CLigIrhXFrdR9aavWgrW1trWtttJWW3/9aqu2tbbWDWlR66641V0R2REIe1hC9nUy+3Lv74+QYExCBkgyJPO8Xy9eyL3n3vvceCDz5JzznNRcdEYzyXMuI/e7/4cpfRC1bzxC+VN34q/aR/VLD6C6m8i46Mfo4zsvLqHX6xh2gkUjPL4gmnZkH6H+IDnRQkOz/4TWejU0958NclvZ4k00n2Cp8k27aqh3+qRQRCdk2p4kT0IIIWKI6m+ZrheoORDlSERnmje9h3P9W7zrHY1h6JR250ypuWRdeTdpCxYTrDvEoX/ehrd0MylnfwdzdsFR71uQ52DPoabjTiRaq7f1l2p70DLypKoaTpf/uK7XNK1l5KmfJU/WeCP+QPiEKsK9t+Yg1jgjU0dn9GBkA4PJKNP2JHkSQggRM1S/F4BgfWVEVdxE3/FX7KV25aOomSN43TuR/E72eFIUBdu4ueTd9BD24rNxzLoE+4T53d67IDcRfyDMoerm44qtdQ2NtR8VjGgdMTreintuX4hASO1XlfbgyOjg8W6U6/EFWbWlgtkTczAa+k+hjL5iNOgIyLQ9IYQQIjaofk/Lf2gqgbpD0Q1GtAl7mqn6733oEhLZV3g5KjoGZ3W9Qa4+3kbq2d8l+bTLIrp/Qa4DOP6iEa0fxPvTmqeU1o1yjzN56m97PLVqrYh4vEUjPtlUTiAYZt5kqbLXGZNRj6pqhGO4XLkkT0IIIWJGW/IEBGsPRjES0UpTw1S//AAhVwMZF99Oab2KyagnIzm+x56Rk27DYtKzu6xjtb5ItBYg6Fdrng4nPcdbrrzh8B5Pyf2t2t7hBPd4y5W/t/YgOWlWCvOTejKsAcOob0kdYrlohCRPQgghYob6lRLlgRpJnqJN0zTq31+Gd+8mUs/6DpbsAvZXOMnPtKHTKT32HL1OYWhO4nFX3GtyHZ62149Gnhw2M4py/CNP9c6WtVL9rdpc27S94xh5+njDIbburWPelDwUpef630BiNLakDrE8dU+SJyGEEDFDDbSsedLbUiR5ijLV56bqv/+Pps9fwTbpTOwTzwBgf2UzgztZ73SiCnIPF404xulG4bDKylWlZKUmkJjQf0ZhDHodiVbzCU/b62/V9loT3OZjHHn6Ymsl/7d8HaOHprBg9tDeCG1AMB1eBxbLRSMkeRJCCBEzVJ8HULDkDJdpe1Hkr9pH2b9+gmfnGpLnX0Pq2TcA0OTy09jsZ1BW52XHT0RBnoNAMExZteuYrntz1T4OVrm4fsHoHh0N6wvJdgt1xzltr97pw2TQEW8x9HBUvetIwYjIR5427azh90+tYWhOInd9exoWU/96575kNMi0PUmehBBCxAzV70FnjsOYlk+wvhI1eHxlnAciTdPaNp/tTc2b36f8iTvQgn6yr1qKY9r5bVOk9lc6ATqttHeiWotG7DqGqXsuT4Bn3trOuIJUpo3O7PGYetuJbJTb4PSTnGjpd9PX4i0GdDol4pGnbaV1/Obx1eSkWbn7hhnEW/rP1MxoaB15OpFS8P2dJE9CCCFiRkvyFI8pLQ/QCErFvTbONa9z8C83E6yv6JX7q6EANW88Qs2rD2POKSTn23/EkjeyXZv9FS2lxI9Wae945aRZiTPr2XMMFff+/c4O3N4g37lgTL9LIqCl4t7xr3ny9bspe9BSzt4aZ4yo2t7uskbu/ufnpNgtLL1xRr8qCBItrWueZORJCCGEiAGq34POEo8ptaUMsax7OsK17VNCTTVU/Ps3hFwNPXrvYGM15U/+guYN7+CYeRFZl9+Fwero0G5/pRNbvLFX9hbS6RSG5jjYFWHyVFbdzOuflHLGtEEMyU7s8Xj6QrLdQpPLT+g4ykrXO739MnkCsMYZu622d6DSyV1/X0VCnJHf3DSz3xXGiJYja54keRJCCCEGPNXvQTHFY0zOAp1B1j0dpvq9+Mt3E19QTNjdSOV/fteurPsJ3TsUoPI/vyXUUEnGpT8jee4VKLrONx89UNlMfqa910Z5CnIdlEZYNOJfr27FZNRzxdkjeiWWvpBst6Bp0Nh8bNNTNU2jrslHSmJcL0XWu2zxpqOOPFXUurnz759h0Cv89qaZpCf1XFn8ga51zVNACkYIIYQQA1/rtD1Fb8CYkiUjT4f5yraDppI49TwyLr6dQM0BKp+/Dy10fHvlfFXDRysI1h0i/aLbSCic0mU7TdPYX+nslSl7rQryHARCKgeqmo/absOOatZsq2LR/MJ+PSKRfJwb5Xr9IXyBcP8deYo3dlmqvK7Jyy8f+ZRgSOU3N84kO9Xax9H1b22lyoMy8iSEEEIMeK3T9gBMafmSPB3m3b8FdAbMuUXED5tI2nk349v3JdWvPHhCRSR85btbSpGPn0f80AlHbVvT6MXjCzEos+cr7bUqzHMAsGzl9i4TinBY5bFXtpCZEs/5p/bvktWtyc+xVtxrbd+afPU3LSNPnSf+L36wh3qnn7tvmMGgXkzUByqZtifJkxBCiBjSOvIEYErNI9RYLRX3AN/+rVhyhqMztqw1so2dQ/LpV+Eu+Yy6dx5H07RjvqcWClLz6kPorUmkzL+m2/YHKltGg3qj0l6r7DQr13xjFBt2VnPzH/7Hys9KUdX27/b26v3sr2zmuvNGYzR0Pr2wv0ixH9/IU2v7lAE48rRmWyXjClIZnpfUx1ENDEdKlcu0PSGEEGLAa5c8tVbcqy2LblBRpvo9+Cv2YBk0ut3xxOkXkDj1PJxr3qBp1YvHfN+GT54jWFtG2rk3obMkdNt+X0VLmfLeHg245PThPPTjuQzLdfDX/27mpw9/3PZslzfIsje3M2ZYCjPGZvVqHH3BbjWj0yltG95GqjV56s8jT25fiPDXEuPyGhfltW6mjMqIUmT9X9uapxietie7gAkhhIgJaigA4VBb8mRMa624dwBz1rBohhZVvoMloKnEDRrT7riiKCTPv4awu4n6959Bn+DANv70iO7pr9hD42cvYh03l/iCSRFds7/SSWqiBWtc7++zk5Nm5bc3zeT9dQf558tbufX+D7hwTgFef4hmT4DvnN8/S5N/nV6nkGQzH/vI0+Fpe71R9bAvWONb+pDbG8SecKT8+JqSKgAmj5Tk6XiZjIen7R1HBceBQpInIYQQMUH1tVSPa0uekjJBb4j5dU/e/VtAb8CcU9jhnKLoSFvwfcJeJzWv/w2dOYGEEdOOej8tHKTmtYfRJzhImX9txHEcqGgmvw/XoCiKwumT8ykekcHjr23l+fd2AXDG1HyGHd5QdyBItluoO46Rpzizod9uGNu6X5PLE2iXPK3dVkVehpXMlO5HQkXn2qbtySa5QgghxMCmBdonT4pOjyklJ+aTp5b1ToVt652+TtEbybjodsyZQ6j6730cevLnuEpWoamdf3hq+OS/BKoPkHrujejjIqtkFg6rHKxuZlAvrnfqSqLVzK3fmsQ93zuFeVPyuPrcUX0eQ29KtlvaRpIi1VKmvH9O2YMjydNXy5V7fEG27K1l8sjMaIU1IBwpVS4jT0IIIcSA9vWRJ2iZuucv2xGtkKJO9bnxV5bimHXJUdvpzHFkXbmU5k3/o+mL16l+4Y8YEtOwTzkX+/h5bWua/JWlNH72Ataxp5EwfHLEcZTXugmGVAZn9V6lve6MLUhlbEFq1J7fW9IccXy5pxZN0yKeiljv9PXbMuVwZNreVyvubdxZQyisMUWm7J2Q1iIqsTzyJMmTEEKImNC66etXkydTah7urZ+gBrzoTP1zQ9AT4W1b7zS627Y6k4XEKd/AXnw2nl1raVr9KvXvPknDR89iG3869uKzqHn1YfRxNlLOuO6Y4uiLSnuxKjM1AY8vhNMdINEa2RqmOqePUUOSezmy3vPVaXut1pZUkWAxMLIfv9fJQK9TMOgVWfMkhBBCDHSdJk9p+QAEasqw5AyPSlzR5Nu/BUVv7HS9U1cUnZ6EomkkFE3DX7GHpi9ew7nuTZxrXgcg45Kfoo87thGk/ZVOdArkZURv5Gmgyjq8vqeyzh1R8qRpGvVNvn5bphxoKzrSOvKkqhprS6qYWJSOQS8rVk6U0aCTantCCCHEQNeWPFm+mjy1VNwL1h6MyeTJu38r5txCdAZT9407Yc4aRvoFPyB57pU417+FYjCRUDT1mO+zr8JJVmoCZmP/3lept9W66znoriDNnUFqQmQjKJkpLf29os5D0aDur2n2BAmF1f49be9w8tQ68rT3UBMNzX4pUd5DjAY9gRje50mSJyGEEDGhLXkyHUmeDI50FIOJQM2BaIUVNWGvi0BlKUmnfvOE72Wwp5A85/Ljvv5ApVOm7B1FacNB/vrFU9R7GgmFQ6w4uJLkeAc3T72aIUl5R7024/DIU1WdO6Jn9fc9ngD0eh3xFgPN3paRpzUlVSgKFI+Q5KknmAw6QjFcMELGLoUQQsSEI9P2jqxtUnR6jDFacc93sATQOmyO29f8wTAVte6oVNrrD0obDvLbD/7M/sYymgMuvGEfzQEX+xvL+O0HD1LacPS+azbqSbZbqIg0eTpcma8/jzwBWONNbdX21pZUUpiXFPGaL3F0RoM+pqftSfIkhBAiJqh+D4rRjKJvP+nClJY34JInTev+g413/xYUgwlLduTrnXrDwapmVA0G9+EeT/3JX794iuZA54lPc8DF3754qtt7ZKUmUFnnieh59U4vACmJ/buAii3eiMsTpKHZx84DjTJlrwcZjbqYnrYnyZMQQoiYoPq97YpFtDKl5RFurkP1RfaT+ZOdq+Qz9j9w/eGRpa759m/FnFuEYojuRqgHKp0A5GdKsYivq3XXU+9pPGqbOm8jte76o7bJTImnojay/l3XNvLUv0dpbHEtI0/rSqoBmCwlynuMyaAjKNP2hBBCiIFN9bvbTdlrZUxtWTMSqC3r65B6nKZpNH7yPKq3mcpn7yVQvb/TdmFvM4GqfcTlR3fKHsD+imaMBh3ZqQnRDuWkU+9tREM7ahtN02jwNR21TVZKAvVOH/4I9uapc/qwxZva9vPpr6yHR57WllSRbLcwNCcx2iENGEaDnqCMPAkhhBADm+r3oDN3/IDeWnFvIEzd8x3YSqB6P45Zl6IYzFT8+zcEG6s6abcN0IgbPKbvg/yafZVO8tJt6KWEdAfJcQ4Ujr6xraIoJFmOnhhkfqVceXfqm3yk9ONiEa1s8SYaXX427Kxm8siMiDcIFt2L9VLl8i+VEEKImKD6PJ1O2zM40lGMZgK1/T95avridXTxdhynXETW5XeihYJULF9KyNXYrp13/1YUgwlzVkF0Aj3M5Q2yY189Q3JkvVNnUhOSSY53HLVNSpyj27LlreXKKyOYulfv9PX7YhHQMvLk9gbx+EKy3qmHmYwy8iSEEEIMeGqg8zVPiqLDlJpLsJ+XKw82VuHZuQb7hPnoDCZMaflkLvo54eZ6Kv/z27Zqg9CyOa4lb0TU1zv9971dePwhLjh1WFTjOJndPPVqbKbOpzTaTFa+N/Xqbu/RNvJU333RiIGSPNniW/YuM+h1jB+eFuVoBhajrHkSQgghBr6uRp4AjCdZxT01FEALBY/pGufalaDTYS8+u+2YJbeIjItvJ1BzgMrnfo8aChD2NBOo3o8lyuud6pq8vPLxXk6bmMuQbFmP0pUhSXn8cs4PGOzIxWa2Eqe3YDNbGezI5Zdzbul2nycAe4KJeIuh25GnsKrR0Ozv13s8tbLFt/xgYOywFOLMsq1pTzIadARiOHmS3iSEECImtKx56rz8sik1D9fmDwh7XejjrH0c2deEApQ//lM0VSXnmnvQWbovpKAGvDRv/B8JI6ZjsKe0OxdfMIm0BYupefnPVL/0J6yjZwFEfb3Tind2Eg6rXHH2iKjG0R8MScrjvrN+Qa27ng3bNzFxxPhup+p9laIoZKYkdLvXk9PlR1W1AbHmyXp45GmyTNnrcSaDnmAExUcGKhl5EkIIMeBpahgt6Ou0YAQcKRoRPAnWPRk2v06g+iDB+gqqXnwATe3+Q0rz5g9R/R4Sp57X6XnbmFNJOfN6PDtWU/vG31GMZsxZ0ZsqV17j4q3V+zl7xuC2KWWie6kJyeTGZx5T4tQqKyWh24IRdQNkg1yAokFJTBudyewJOdEOZcAxGnUEw7E78iTJkxBCiAFP9bds/KmzdD1tD6Jfcc+19RP0+9bhmHkhqWd9B+/eDdS/t+yo12iainPt65izCjBnD++yXeKUb+A45WJUn6tlvZM+euudlr25HZNBx6IzortBbyzJTImnqt5DWO269Hm9c+AkT0k2C7+8fhpJtv7/LiebWK+2J9P2hBBCDHitxRK6WvNksKehmCxRTZ6CDZXUvPEIanI+Sad9C0WnJ1C9n6bVr2BKz8c2bm6n13n3biJYV07aBT/othxz0mmXobcmR3XUaXdZIx9vPMSi+YXywbYPZaYkEApr1DV6SU/u/O9B3eHkaSBM2xO9xxTj+zxJ8iSEEGLAa02elC7WPCmKgik1L2rlyrVwkOoX70fR6QhO/SaKrmWD0pQzriNQd4iaNx7BmJyNJbeow7VNX7yOPsGBdeSMbp+jKAqJk8/utl1veur1bdjiTVw4J7pl0mNNVlvFPXeXyVN9kw9FAYfV3JehiX7GZNARCmuoqoZOF3v7Z8m0PSGEEAOe6m9Z69HVyBO0rHuKVrny+veX46/YQ9o3vg9f2ddH0RvIuOg2DPZUqp6/j5Cztt11gdoyvHs3YC8+K6rT8CK1aVcNG3bW8M35w0mIO/njHUgyU1uSp4rarsuV1zt9OKxm2bBYHJXR2PLDnVhd9yR/O4QQQgx4bWueuigYAS3rnsLuJsIeZ1+FBYBn9zqaVr+CvfhsEkZM63BeH2cj89KfoQb9VD73B9Sgv+2cc+1K0BuwTTyzL0M+Lpqm8dQb20h1xHHuzCHRDifmpDriMOiVoxaNqHf6BkSZctG7jIaW9CFWK+5J8iSEEGLA627NE7SUK4e+KRpR3eDhxQ9289Z7Gyl/8UFURy7BiZfgC4Q6jy0tj4yFPyRQWUrNa39B0zTCPjfNmz/AOnoWBquj12M+Uau+rGDngUauOKsI0+GfXIu+o9cppCfFH7VceX2TjxR751NbhWhlOpw8xepeT7LmSQghxICn+lqTp64/GJrS8oGW5CluUO9sILu7rJEXP9jNJ5vK0dQwN9veJWjw8cfqYqrv+wgAi1FHiuMQaY54stMSyEm3kpNmJSdtBI65V9D4/jIa0/JRjCa0oI/Eyd/olVh7Ujis8vTKEvIyrMwt7n5TV9E7MlOPXq68zumlcFBSH0Yk+iOj4fC0PUmehBBCiIEpkpEnvS0ZxRzf43s9qarG+h3VvPjBbjbvriXObOD82UM507KJ4JpKmPVtbs4opsHpp6HZx579FWCIp7rewwfry/D4joxGGQ16rncUMurDfxPSx2HJLsKcNbRH4+1JmqZRWefh7dX7Kat28fNrp8p6mijKTI5nx756NE3rUJkxGFJpcgUGRJly0btap+0FYnTaniRPQgghBjwt4AGdAcVg6rJNW8W9Hpq2FwyFeX9dGS99uJuDVS5SEi1c941RzM33Edj8Fu41q7COOZW0U89h6Fc+yJaUhBk5cmRL3JpGo8tPeY2bQzUuDlW72FydgqNyGdnhapbtz2XqFweYNyWv2zLlJ0LTNNZtr2bngQYSrWaSbGYcNjNJNgsOm5k4s6Gt3cGqZrburWPL3jq27q1r23h1YmEa08dk9lqMontZqQm4fSFc3iC2+PZ/FxqaB84eT6J3mYyH1zzJyJMQQggxMKk+DzpLfLcJhiktD/eO1W0/mff4gvgDYZKO8QOlyxvkzkc+ZXdZE0OzE7lt0VgmGEtxrfs7DatK0VkSSJx+Pkmzv3nUmBRFIclmIclmYfTQlLbjYfcY9q/9mMaNVv68YgPvrjnA9y4ex6BM+zHFGYnS8iYee2ULm3bVdtnGYtLjsJnx+EI43QEAku1mxgxNZfSwFMYMTSE33darCZ7oXmZKa8U9N7b89slTvezxJCJ0ZNqejDwJIYQQA5Lq96Azdb8Q3pSWR/PGdwm7mzBYHfzxmXVs3l3Lz6+ZyqQR6RE9y+ML8qtHP2NfhZM7Lh1GkXcTzZ8+Sb3HiTEtj9RzbsQ65lR0puP/kKpPSGToaefx+9ka7645wBOvbeUH//cBC08bxrfOKMJiPvFv7/VOH8tWlvDumgNY44zceOFYzpw2CLc3SEOzn8bmlmmGLb+3/NlgUBg9JIUxw1LJTOk+WRV9q22vpzo3hfnt1zbVN8nIk4hM68iTFIwQQgghBijV7znqeqdWxrSWYgbB2oNUeQ2s2VaF2aTnN//6nB9dVszsiTlHvd7rD/HrR1ehVezgdyOrsbz3NE2aRnzhZBKnfAPLoDE9mlDodApnThvEtNGZPPn6Nv77/m4+2niIK88egcNmAe1IW+0rf0hJjCM33Yqhk/VHvkCIlz/cw/Pv7SIUVrng1GEsml+I9fA0L5NRf8wjceLkkJHS8negs4p7rSNPkjyJ7hj1h0eegpI8CSGEEAOS6m+ZttcdU+qRinuvbdAw6BX+/KM5PPTsRv7fM2txegJ845TO9yjyNLt49h9Pcb5rPdm2BnT1Cdimnod98tkYHRk9+j5fl2g1c8uiicybks/f/ruJB/69odtrjAYdgzJtDM1xMDQnkaHZiVTWu3nq9W3UNvmYMTaLa88bRXaqtVdjF33HYjKQbDdT2clGufVOHwa9gj2h63WBQgAY20aeZNqeEEIIMSCpfg8GR/fT7vRWBzqLFU/lfv63RmPWhBxy0qzcfcMM/t/Ta3nkhc04XX6+dWZR2whSsL6c+i9WUr/+f5yq+Qk4ckg99VtYR89GZzT39qu1M3poCn/60Rz2lDWiHv6hcLuBLgU0Farq3ewtd7L3UCOrvizn7dX725oU5CZy2xXFjBmW2qexi76RkZzQ6chTXZOPJLsFnU6mWoqja93nSQpGnCSqqqo499xzWbJkCddee220wxFCCDEARDptT1EUTGl51O7bg9efzYJZLWXAzUY9d1wzhQef3cjyt3fgdAf49jkF1L7yJzy716GiY0sgn+xZC5g5/7SorvUx6HUUDUo+apuRQ5KZU9zy35qmUdvoo7S8CYDJIzPkA/QAlpWawOZdNR2O1zf5ZMqeiIgUjDiJuN1ulixZgsvlinYoQgghBpBIkycAQ2ouuoMfUZTnaLeoXq/X8YNFE7EnmHjpwz1kVH7CuIZ1bE6YwXNlOVxz6UxOmTaot16h1yiKQlpSHGlJ3RfUEP1fZkoC7687SCAYxmTUtx2vc/rITZcpmqJ7bQUjYnTN00mzU92hQ4e46qqr2LRpU7RDEUIIMYBomobq90acPFWrDuLwc/7UjtPWdDqF6xeM5ppzR5BV+wX71QweOzicKy+azpn9MHESsScrJR5Ng6r69uue6p0+UmTkSUTgyMiTJE9R88QTT7BgwQK2b9/O9OnTox2OEEKIAUQL+kBTI06ePtnfMmVtYlqg0/OKonDuYA9p+mY+8Rfx3YVjOGdm50UkhDjZZKYe3uvpK+uefIEQbm+QZNnjSUTA2LbmKTan7Z0UydNTTz1FTk4Oy5Yt44ILLoh2OEIIIQYQ1dfyE/ZIkqfyGhcflraU9FYbDnXZzrnuLfQJidxx502cP3tYzwQqRB/ITD6811PtkeSpwekHpEy5iExrwQjZ5ymK7r77bmbOnIler2ffvn3RDkcIIcQAovojT55e+7QUny4exWIjUHOw0zbBpmo8u9fhmLEQg7lvq+kJcaISrSbizPp2I0+tezylyMiTiIBer0OnUwgEY3Pk6aRInmbPnh3tEIQQQgxQasALdJ88eXxB3v3iALPG52BW87tMnprXvwOAfdKZPRuoEH1AURQyUxKorDuy5qm+STbIFcfGZNDF7JqnkyJ5Oh4PPfQQDz/8cLtjy5cvp6SkpFef6/P5ev0Zon+TPiKORvpH31OqdmECDlTWoAW7/tp/urUBrz/EmFwFd7kVXflGSrZta79RUjiEad1bqJlF7CqvhfLaHo9X+og4mp7oHwkmlQPlDW332barAYDaygO4G/RHu1T0A33xb4hO0aiuqR0w/1YVFRW1+/PixYtZsmRJp237bfK0ZMmSDi+1bt06Ro4c2avPLSkp6fVniP5N+og4GukfPSfsdVH7xt8IuRrJvvo3KErny3hdWj3VwNCikZjS8jtto6oaf375PQrzHZx12iSa1lZTt3c1w3MzMNhT2to1b/mIGr+bnDmXEj+0d/4/Sh8RR9MT/aNwt8qOsr0UFY1Ap1P4bNcWTMZ6Jo4fHdU9ykTP6It/QyzmAyRYEwfEv1Xr1q1jx44dEbc/KQpGCCGEEMfCX7GXQ/+6Hff2z/GXbce7t+ttLiJZ87RxZw2Halxtm+Ka0vIACNQcaNfOufZNjMlZxA0Ze6KvIETUZKYmEAyp1B2ertdaplwSJxEpk1FHMByb0/YkeRJCCNFvaJqGc/3blD/5c7RwmKyrlqJPcOBcu7LLa1R/92ueXv1kLw6bmVPG5wBfTZ6OrHvyV+7Ff2gH9uKzuxzlEqI/yExu+buw9LHPue43b/PJxkOkOGS9k4ic0aAjGKOb5PbbaXtCCCFiixrwUfvmo7i+/JC4oeNJv+BW9PF2bBPm0/jpfwk2VmN0pHe8zu8GFBRT5x8Oy2tcrC2p4rIzi9r2L9HH29EnJLZLnpzr3kIxmLCOm9sr7ydEXxmen8SIQUkYDDqG5iSS5ohj+tisaIcl+hGjQU8gRvd5kuRJCCHESS9Qd4iq//6RYM1BkmYvwjHrYhRdy8J2+6QzaPzsBZzr3yLl9Ks6XKv6PejMcV2OFr3+aSl6ncLZMwa3O25MyydY25I8hX1uXFs+wjrmVPSWhJ59OSH6mDXOyP+75dRohyH6sViutifzDoQQ4iRTWefmwRUbeHPVvmiHclLwHdrJoX/9hLCrgczLfknSqd9sS5wADPZU4odPpnnTe6ihQIfrVb8HpYspex5fkHfXtJQn/3qZZlNqHoHag2iahmvz+2ihAPbis3v25YQQoh8yGfUxmzzJyJMQQpwk3N4gz/1vJy9/tJdQWOX9dWWMLUglJ80a7dCiqv69ZehM8eRcdy8Ge2qnbeyTz8az8wvcJZ9hGzun3TnV7+1yvdP7aw/i8YVYMHtIh3OmtDy0gI9QUw3OdW9izinCnNmxnRBCxBqDQYfX3fGHVbHgpBt5uuiii9ixYwfXXntttEMRQog+EQ6rvP5pKTfc+y4vfLCbUyfm8MAPT8Ns1PG3/25C07Rohxg1voPb8R3YimPGBV0mTgBxg8diTM7Gue6tDudapu11TJ5UVePVT0oZnuegaFByh/OtRSOca14nWF+BfbKMOgkhBMi0PSGEEFGgaRprS6pY8n/v88gLmxmUaef+W0/jh5dNoiDXwdXfGMWmXbV8tOFQtEONmoZP/4vucFGIo1EUHfbis/Af2om/Ym+7c6qv8+Rp467D5clnD+30nsbUluSpae1KdPF2rCNmHOdbCCHEwGIy6AnGaMEISZ6EECIKSsubuOvRVdz9z88JhzV+cd1Ufve9mRTkOtranDV9MMPzHPzzlS24vMHoBRsl/sq9ePesJ3Hqeei6qJT3VdZxc1GMZpzr3mx3XPW70ZnjOrR/9eO9OKxmZo3P7vR++jgremsSqGHsE+ajGIzH9yJCCDHAGAw6AjLyJIQQoi98uL6MW+//gN0HG/nuwjE8fPvpTB+T1WGDSr1O4eZLxuN0+Vm2siRK0UZP46cvoJjjIy7SoLckYB09G9fWjwl7XW3HtYAXnbl9hbzyWhfrtldx9ozBGA36r9+qjSktDxQdtklnHN9LCCHEAGQy6mN2nydJnoQQog95/GEefelLhucl8ejP53P+7GFtewt1piDXwbmnDOGNz0rZdbChDyONrkBtGe7tn5NYfPYxlQa3F5+NFgrQvPn9tmOqz4PO0n7a3uuflqJTFM6eMeio90uceh4p86/BmNhx/yghhIhVLWueZNqeEEKIXvbW2lpcngDfv3Q8tnhTRNdcefZIHFYzf31+E2E1NopHNK56EcVgJHHqecd0nTlzCOacIprXv4WmqWihIFo42G7Nk9cf4t0vDnDK+GxSEjtO5/uq+ILiY45BCCEGOqNM2xNCCNHbdh9s5POSJr4xayhDshMjvi4hzsh3LxjL7rImVn5W2osRnhyCjdW4vvwI28Qz0CdE/nVqZZ98NsH6Crylm1H9HgB0piNJ0nut5clndV4oQgghxNEZDS37PMViNVhJnoQQog+oqsbfXthEQpyey88acczXz5qQzYTCNJ5eWUK909cLEfaNUHNDpxvZflXTqpdA0eGYfsFxPcM6Yga6eDvOdW8eSZ4OT9vTNI3XPtlLQZ6DokFJx3V/IYSIdSZjSwoRi+XKJXkSQog+8M4XB9h5oJFvTE3DGnfsVdsUReF7F40jGFJ57JUtvRBhz6iq9/DF1kr2HmrqUCHQvf1zDvzlJg48eAN1/3uSYENlh+tDzQ00b3oP27g5GOwpxxWDYjBinzAfz651BKoPALQVjCirdlFW7eLMqfkdCnQIIYSITGuhnVhMngzRDkAIIQY6pzvAk69vY9SQZCYV2I77PtlpVi45fTj/fnsHZ0zNZ0Jh3xYxUH1unBvewTrqFAyJaW3Hm1x+PtlUzofryyjZV9/umniLgfSkeKZb9jC96U28tjwcGZk0rX6Nps9fIW7oROzFZxFfMAlFp6fpi1fQ1DCOGQtPKFbbpDNoXPUSjZ+/BNC25mnr3joAxg1P6+pSIYQQ3WgtdBQIhUkgtrZxkORJCCF62dMrS3D7gtx00Th8TeUndK9LTh/OB+vL+Ot/N3PHNVOOae3UiQh7nFQsX0qgqpSGj5/DNuNitsYV88HGCjbsqCasagzKtHH1uSMZOyyVeqeP6gYPVfUekg5+zOSm99gZyuYf+0+hQJfB0u9/G8+m93BueIeq536PwZ6KbcI8nOvexjrqFIzJWScUrzExnfiCYjy71gC07fO0dW8dDpuZ7NTIK/gJIYRoz3Q4eYrFcuWSPAkhRC/aeaCBtz7fx4LZLUUiSk4weTIZ9Sy+dDx3/3M1t/zfB4wYlMQ5MwdzyvgczMau9ys6EaHmeiqW302osRrP5Kto2vY5WR89gyH0OmFlNgtPm8Jpk3I7JHKaptHw0X9o3PYeCSNmcOb5t2DaVMkD/97Aq+sauOT0b+I45SI8u9biXPcmDR+tAMAx86IeidtefNZXkqd4NE1jy55aRg9NkSl7QghxAoyHv98Ew5I8CSGE6CFhVeNvL2zGYTVz+ZnHXiSiK+MK0njirjP535qDvLmqlAf+vYF/vryFeVPyOXvGYHLSrD32rGBTNRXP3E3Y1cj/HBfz8tsKCXGnctGwiUxqfJdrPa9i1VykJF7V7jpNU6l7+3Gca9/ANn4eqefeiKLTM7c4jy+2VvHMmyVMKkpnaE4iCSOmkzBiOoG6Q4Sb6zGl5/dI7HFDx2NIyiTUUInOnEB1g5faJh8XDz2+tVRCCCFatE3bC8beXk+SPAkhRC95Z/V+dh9s5LbLJ5FwHEUijsYWb2LhacO44NShfLmnljc+28erH+/lpQ/3MK4glYvnDmfSiBNbExWoK6fimV8T8nl5PHA2W3abuO68kSyYPRSjQY8auIDGT5+n8fNX8OxcQ/LcK7BNnA+qSs1rf8G15SMSp51P8ryr20Z6FEXh5kvGU7KvjvuXr+P+W0/DdPgnmKaUHEjJOeGvTStF0eGYeRGNn72AzhLP1m2HABgtyZMQQpyQtml7UjBCCCFET2hy+XnqjW2MGZbCaZNye+05iqIwriCNcQVpNDh9vPPFAd78fB+/+scqTp+cx3cuGBPxZrxfFajeT/nypfj9Qf5UP49QYib3LZlMYf6R8t46k4XkuVdiHXMatW/9g9qVf6d503vo4qx492wgac7lOGZe1GGKnD3BxJJvTuTuf37O0ytL+Pb5Y07469AV+4R52MafjqIobNlThzXOyKBMe689TwghYoHpcLU9GXkSQgjRI1qKRIS46aJxfba+Jslu4ZvzC7lwzjBWvLOT597bxYYd1Xzv4vHMGBt5AQZf+W4qli/FFVD4U8N8RowbxfcvHU+8pfPRM1NaHllX3I1ry0fU/+9JwuW7STnruyROPrvLZ0wemcE5Mwfz8kd7mDoqk7EFqcf8vpFq/fpv3VvH6KEp6HSy3kkIIU6EMYb3eZLkSQghetjuskbeXr2fC04dFpVRDqNBz5XnjGTG2Cz+vGID9zzxBadOyOGGC8eSaDV3eZ2mhvHsWkvlSw/SEDTyiPssvnXJTOZHsCeSoijYxp5G/PDJhJpqMGcM7jbO688bzaadNTzwn/U8dNvcHp/a+FX1Th/ltW7OntF9XEIIIY7OKNP2hBBC9ARN0/jny1uwJ5j41hlFUY1lWK6D+289jeff28WKd3awaXcNN100jlnjj6wr8gdCHNq2meYtH2M+tB5TyEVVOJFX4i7kV9+dQ17Gse1LpbckoLdEVgbcYjbwo8sn8ZOHP+HRl77kh5dNOqZnHYute1r2d5L1TkIIceLapu2FZNqeEEKIE/Dp5nK27q3j+5eM79WRlEgZ9Dq+dUYR08dk8ef/rOcPT63lnaIDpKp1JNVtpCi8ixS9C4umY1swl72mmSSNncrd543rtdLnX1U0KJlL5w1nxTs7mTY6k5njsiO+VtM0XvuklINVzVx//mgspq6/pW3ZW4vFpGdYTt/siyWEEAOZTNsTQghxwvzBMI+/upXBWXbOmDYo2uG0MzjLzu+vG80Xr76MYd+rZOgaUFFwJhVQP3gqyWNn8I2c9LbKd33pW2cUsa6kioef28TIwckk2S3dXuPxBXlwxUY+3dyyb9a+Cid3fXsa1i6KY2zdW8fIwcno9boejV0IIWKRUd9aMEKSJyGEEMfp5Q/3UN3g5Xffm4j+JClKoAa8uHesxvXlh3hLvyQHDXN+EdbRF2MdORN9QvRHYgx6HT+6vJhb7/+A+5ev58dXFh91bdbBqmbueeILymtcXHfeKNKS4rl/+Xp++pdPWHrDDFIS49q1d7oD7K9s5tSJvVf1UAghYompbeRJpu0JIYQ4DnVNXp77305mjM1iXEFaVGPR1DDe/Vtwffkh7u2r0YI+DI50HLMvxTbmVIzJkVfe6yt5GTZuuHAsf31+E9+95x3Onz2MhXMKsH5t6uOnm8v583/WYzLq+c1NM9u+1vYEE797fDW3P/QxS2+YQW76kbVa20plvZMQQvQkKRghhBDihDz1RgmhsMZ1542OyvNDzjq8pZvw7N2Id9+XqB4nOnM81jGzsY09DXPuiD4rmX68zpo+mFFDUlj+1nZWvLuT1z4t5aI5BSyYPRSTQcdTb5Twwge7KcpP4mfXTCHVcWSEafzwNO65eRZ3/+NzfvrwJ/zqO9Pb9qTaurcOo0FHYb4jSm8mhBADS+sUbykYIYQQ4pjtOtjAe2sPcvHcArJSI6s0d6LUgA/fga149m7CW7qJYG0ZAPoEB/HDJhE/vJj44ZPRGY59g9xoysuw8dOrp3DpoSaWvVnC0ytLePXjvaQnx7HzQCPnzhzMdy4Yg9HQcW1WQa6DPyyZxV1/X8Uv/vYpd1w7lUlF6WzZU0vRoKROrxFCCHHs9DoFRYGgrHkSQghxLDRN4x8vbcFhM/PN+YW9/zw1TONnL9L4yfNo4SCKwYQlfxS28fOIHzoeY1r3ezL1B0NzErnr29PZvq+ep1eWsH1/Az+8bCKnT84/6nXZqVbuWzKbX/9jFb957HNuvHAcew81cWkf/L8RQohYoSgKRoOegEzbE0IIcSw+3niIkn31LPnmBOItvVuaPNhQSfXLD+I/tIOEkTOxTZyPJW9kvxtdOhYjBifzu++dQjCkts2x706y3cK9N8/iN/9azV+e3wTAGFnvJIQQPcpk0EnBCCGEEJHzB8M8/to2hmYnMm/K0UdE2mgq7h1f4K/YQ/ywiZhzC1GUoycFmqbh2vw+tW8/hqLoSF94K9bRs3vgDfqPSBOnVglxRpbeMIM/PrOObaV1jBiU3EuRCSFEbDIadFIwQgghRPc0TWNfhZOXP9pDbaOX2y6f1G1p8rCnmYZPX8a48R2qAi4AGj99Hr0tmYSRM7GOnIk5Z3iHRCrscVLzxiN4dqzGMmg06QuWYEiMbjW//sJk1PPza6cSCIajsn+VEEIMZEajnkBQRp6EEEJ0wukOsHFnNeu2V7NhRzUNzX4AzpkxmDHDUru8zl+5l7r3nsW7dy2KohF06fA1xaGYU8ldMJtQ3S6c697E+cVr6O2pWEfOJGHkTMzZBXj3bqTmtb8Q9jSTPO9qEqct6HaUSnQkiZMQQvQ8k4w8CSFE/6RpGttK60mymclOs/bYfZtcft754gCff1nBzoMNaBrY4o1MLExn0oh0Jhalk2y3dBqPe8fnNK1+FX/ZDjQVPLXgqYKQVwW8wEH2PP4qo+++i/QFS3DvWot726c0rXmDptWvoLcmE3bVY0zLI3PRLzBnDumx9xJCCCFOlEzbE0KIfqi6wcPf/ruZtSVVKApMGZnJwtOGMWZYynFXndtd1shrn+zlow2HCIZUivKTuOyMIiaNSKcgL+moU/SCDZXUvvko3r2bMCRl4nMl0bijAa2TmQ0hZzO7H/orEx74I7axp2EbexphnxvPzi9w71iNMeVUkmZ/E53RfFzvIYQQQvQWk0Gm7QkhRL8RVjVe/2QvT68sAeC680bj8QdZ+dk+fv63SoZmJ3LBacOYPSEnomIDwZDKZ5vLef3TUkr21WMx6Zk/NZ/zThlCfqa92+u1cIim1a/S8PGzoNOTcua3MecXU/Hjn3WaOLXy19bhr6nBnNayjklvScA2bi62cXMj+0IIIYQQUWA06qRUuRBC9Ael5U089OxGdh1spHhEOjdfPJ705HgALp1XyAfrynj5oz088O/1PPn6Vs49ZQjnzBhCnNmA0+3H6Q7Q5PLT5ArQ5PZT0+Dlow1l1Dv9ZKUk8J0LxjBvSj7WuMhKj/sO7aT2jUcIVO8nvmgaqWd+G4M9heYdO0Hr5huLphGob2hLnoQQQoj+wGTQ4/YGox1Gn5PkSQjRb/iDYf7z9g5e/GA3tngTt19ZzOwJOe2m55mNes6aPogzp+WzYUcNL3+0h2Urt7P8ze2oWuf31SkwoSidJd8cyqSidHTdVM5rpfrc1H/4b5xr30RvSyLjkp+QUDSt7bwpOQm6K/CgKC3thBBCiH7EaNARkH2ehBDi5LR5dw0PP7eJilo3Z0zN57oFo7HFd705rKIoTBrRUtjhQKWTjzYcwmDQkZhgwm41t/yeYCLRasYab+q21DiApqkEKvfhLd2Ip3QzvoMlEA5jn3wOyXMuQ2eOb9fenJaGOSWZkNPZ5T3NqSky6iSEEKLfMRp0BIIybU8IIU4qmqbx/Hu7eHplCZkpCfzuezMZV3BsyUZ+pp0rz+l+3VLHZ6uEGqvxHdiGp3QT3tLNqJ6WRMiUPojEyediHT0bc9bQLu9RcMv32fqrpYSczR3OGew2CpbcfMxxCSGEENFmMuoJhiV5EkKIk4YvEOLBFRv5eOMhTp2Qw5JFE7CYeuefLTXgJVB9gED1fgJV+/BX7yNQfQAt4AVAn+AgfthE4oaMJ27IOAzWyKbaWYcOZfTdd7H7ob/ir60jHAqiNxgxp6ZQsORmrEO7TryEEEKIk5XRoCMo1faEEOLkUN3g4XePf0FpeRPXfGMUF88tOO7S411RAz6aN7+Pc/3bBGsOAi2LonTmeEwZg7GNm4MpfTCWnOEY0/KP+/nWoUOZ8MAf8dfUsHP9BgonTZSpekIIIfq1ljVPMvIkhBBRt2VPLb9/ag2hkMpd357O5JEZPXr/kLOWprUrad7wDqrPjTl7OEmnfQtT+iBMGYMw2NN6PFGDljVQhvw8SZyEEEL0eyaDXjbJFUKIaHvjs1IeffFLMlMS+OX1U8lNt/XYvX2HdtH0xau4S1YBkDBiGolTF2DJLeqxZwghhBCxwGjUEQyF0TStV37geLKS5EkIcVIIhlQefelL3ly1j8kjM/jxFcUkRLjP0tdpaphQUw3BunKC9eUE6yvwl+/GX7EbxRxP4tTzsE85B2Nieg+/hRBCCBEbjAYdmgahsIbRIMmTEEKcsKYGL81OHza7hcSkuC7bNTT7+P2Ta9hWWs+l84Zzxdkjuywdrqlhwm4nYXcDYXcTYVcDYXcjIVcjocaqlmSpoRrUUNs1ijkeU0oOKWdej23c6ejMXccihBBCiO6ZDHoAgqEwRkM3exoOIJI8CSF6XEVZE6+s2ERzk69tON+WaOH8RePJyk1s13b3wUZ+9/hqnJ4gt19ZzKkTc9udDzZV4y5ZhXvHaoL1FaieZloLO3yVYrJgdKRjTM0joWgaxuRsjMlZGJOz0cXbY2pKgRBCCNHbTIcTplhb9yTJkxCiR1WUNbHs0dV43YF2xz3uAM88uporbpjWlkB9sL6Mh1ZsINFm5r7FsxiW6wAg1FSDq2QV7pLP8JfvAsCUOYyEounorQ4MCYnoE5LQWx3oExLRJzjQmSx9+p5CCCFELDMcHnmKtY1yJXkSQvSoV1Zs6pA4tfK4A7yyYhPf+eFsnnp9Gy98sJvRQ1P46ZXFJPiraVz9Ee6SVfgP7QTAlDmU5LlXkjByBsakzL58DSGEEEIcRZLdjE4BQwytdwJJnoQQPaipwUtzk++obeobvdzz13dwl+3kluFBRlnX0/jo32gItFzXkjBdQcLImZIwCSGEECepKSMzeORn80myxdbMD0mehBA9ptnZssbpq/SESDLUkaqvxWGoIclQQ0qTC2xAgx7NOBjbuLmYcwqx5BZhdPTsnk5CCCGE6HmKopCVmhDtMPqcJE9CiHZOZL8Gq81Eoq6ebFMFqYYaUgy1OPQN6JSWhKpRjedAKBXL2PkMnzwZU+ZQdEZzT4YvhBBCCNFrJHkSQgCghUPUrnwUV8lnxOWPIn74ZOKHT8ZgS+72Wn/VPlxbP8a99RPmm2rBBH7VRG04lW2+MWwPpXAglIpRS2B8hp2FF87p9fcRQgghhOhpkjwJ0U9omobbG6TR5afJFcDp9pOeFM/g7MQu90SKlBrwUfXCH/Hu2UB80TQClaV4dq+DlX/HnDWM+OFTiB8+GVPG4LZRqWBjNa6tn+Da+jHBmgOg6IgbOgFl7Pn8938uNnss1B6+fyoKg1BISjCz6PKJJ/iVEEIIIYSIDkmehDjJqKpGyb56PvuynLJqF43NfppcLb9C4Y77G8VbDIwYnMzoISmMHprC8DwHJqM+4ueFPU4qV9yDv2IPqefehH3iGWiaRrDmIO5da/DsWkvDRyto+Og/6O2pxA+dQKC2DH/ZdgDMuSNIPvM7eLMmcKhZx+dbKvjAdwAVjUyDnjyDgTi9rst9noQQQggh+gtJnoQ4CYRVjZLSOj7dVM5nX5ZT7/RjMujIz7KTbLcwLCeRRKuZRKsZh9WEw2bGGm+irKqZraX1bN1bx9PbSwAwGnQMz3MwriCNucW5ZKdZu3xusKmayn//hlBTLRkX/5iEomlAyyJQU3o+pvR8kk65mJCrEc/udbh3rsG55SOClmTKs89gizqUndUGyre5CYa+AMCg13Hm9EFccvpwzCg0O33Y7BYSk+J6/wsphBBCCNGLJHkSIkpUVWNra8K0uZyG5paEqXhkBrPGZzN5ZAbxFuNR71GQ62BOcR4ATneAktI6tpbWs21vHc++u4P/vLODUUOSOWNqPqeMzyHOfOSvfKB6PxX//i1ayE/mZXcSlz+q3b01TaOm0cvOAw3s2N/Ajv0m9pSNJhAaASjodApZKTpy0xMoHpFBbrqV3HQbeZk2rHFH4pakSQghhBADhSRPQvQxXyDE+2sP8vJHezhU48Zk1DN5ZDqzxuUweVRGuwTnWNgTTEweZmWM+RBOww7c9jLqvDoONYbY/wqUvm4kKzOJgsEZZCbH0/jxChSjhawrf0PQlsXeQ01U1Xsoq25uS5gamv1Ay2jWsJxEzpk5hKL8JAZn28lMScBo0PXkl0YIIYQQ4qQmyZMQfaTe6eP1T0tZ+VkpzZ4gBXkObrt8EtPHZGE5joRJ0zRCDZX4yrbjO7gdX9l2grVlAKgaeNFjBUbrQG/Vo4QDKPVAPdQDTfpknlW/wZ4/b8Hr39ju3lmpCYwfnkbRoCQK85MYkp0oiZIQQgghYp4kT0L0stLyJl76cA8fbSgjrGpMH5PFBacOY9SQ5C73U9LCIYL1FYSctYRdDYTdTYTcjW3/HXY3Em6uR/V7ANBZElBS89mj2qjxhWlU9agcubcl3sr519+GzZHO6k37+Wz9Pqp9RlKTbcwbHkd6UjzpyfGkJ8WRmZKALd7UJ18bIYQQQoj+RJInIXrBoRoXa7ZV8vmWSrburcNi0nPOzCEsmDW03W7cmhom2FBFsOYggZoDBGoPEqg5SLCuHNRQu3sqJgv6BAf6BAem1Fz0g8ZgSh+EJXcExrRcVjz0a2o9Cp39tfZ5XLz338f51i13M2fmSObMHNnbXwIhhBBCiAFHkichekAwpLKttI7VGw+xasshal07ARicZefac0cwf7QVo7eW0P5PqNtYSbChgmBDJaH6SrRwsO0+Bkc6ptQ8EoYXY0zNw+jIQG9tSZh0JkuXz29urMPlbDhqjC5nA82NddgcKT3z0kIIIYQQMUaSJyGOg6ZpVNZ52Ly7hg07ali/vRJj0EWmwclMk4uCZBfZJg9xFjehL2qo+/zIKJJiMGFIysDoyCR+6ERMaXkY0/IxpeagMx1fZTq3sxFN7bgHVPugVdzORkmehBBCCCGOkyRPQkRADfqpq6hg9/a9HNpfRmNVJQZ/Iw6dh1kGLwsTmjApR0aQwih4g/FoajrJY87CkpuPMTkTY1IWelsSitKzxRcS7A4UXefrp9ooOhLsjh59rhBCCCFELJHkScQ8TdNQvc2EmmoJNdUQctbgraukubqSYGM1Om89prAXgIzDv1AgnGBBb08h6E6gLGzCqZhxKXE06yx4MYOiYNIMnFpdwPgFp/bqO9gcKVjtSfjcri7bWO1JMuokhBBCCHECTprkKRQKsWzZMp599lnKyspIS0vjoosu4oYbbsBoPPpGoUJ0RVPDhF2NhFwNhJvrCDnrCDXXEW6uJ+isI9BUi+qqR/nKuiMAv2agQU2gPpxAs5KP0ZFGSlY2eUPzyB2cjykxBZ0pjqDTx5P/fIImnbvT5weUEGuatjHKORWjves1Sz1h3iXf5uXH/ojP0zGBssRbmXfJ9b36fCGEEEKIge6kSZ6WLl3KihUrKC4u5vTTT2f9+vU8+OCD7NixgwcffDDa4Yk+pmkawZCKLxDGFwjhP/y7qmpoACE/eJ0oXid4m8DnBE8jYXcjuBvB14je14Qh6Eah/VqgMDqa1Hgaw3E0qgk0qsNpUuNp0BIwJKaRmJFNTm4mg3MSmZplJ80R12VJ8Yaqerya/6jv4tX8NFY3kGbP6pGvTVfSsgdxwbd/zP+e/1dL8QhNBUWH1Z7EvEuuJy17UK8+XwghhBBioDspkqf169ezYsUKzjrrLP785z+jKAqapvGzn/2Ml156iffff5+5c+dGO0wRAU3TcPtC1Dd5cXmD+AJh/IHQ4d/DbX92+0K4vUHc3gAhjxO9txG934kh0Iw+7Eev+jETIE4JYmn7FcCq82HX+bAowQ7PVjXwaHE41ZZfTWoWTi0OFwn4DVZCZgc6axJmexJJdgsOmxmH1UK+zUxyooW8DBtmo/6Y3tdHgG7KNKABPo6eYPWUtOxBfOuWu2lurMPtbCTB7pCpekIIIYQQPeSkSJ6eeeYZABYvXtz2E35FUfjRj37Eyy+/zHPPPSfJU5Ro4SDe/dsADX2CA4M1iYA+jgNVLkrLnRysbqa+yUdDs5/6Jh91Ti9aMECcEiBB58eq+LDqfFgV/+Hffdh0PtL1XhJ1XmyKBz3qkQcaaOuVqs5I2GBBM1jAaAFjEprFhma244mzo5ntaBY7miUR1WJHZ7ERH2cixWzAYjYQf/h3g75nizN8lSPj8Ea3R8mgFEUhMT2512LojM2RIkmTEEIIIUQPOymSp7Vr15KUlERhYWG74xkZGQwePJg1a9ZEKbLYpAb9+A/txLX1E1wlq9D87dfzhDUFt2YhTo1jECZGGcLE64KYlQAmux+dFu7izgpKnA1Dgh2DLQu9NRmDLQm9NRm9LQmDNRl9QiI6SwI6UxyK/qTonkdlt9uxO+zUNtR13cZhx26392FUQgghhBCiN0T902kgEKCyspLx48d3ej4nJ4fS0lLq6+tJTu7bn96fLDRNAzWEFgygBgOofjeq34PqcxPyeXA5XbhdLrwuNz6Ph4DXRzAYJBgKEwyphEJhgqEwoWCYUDiMpoFOp6Aoh3/pFPSKglkXIkupIylciw6NAEY2+/NYHxiMVzOSZ1cZlKiRGR8i2egnGQ9G1Y/OHNeS8Jjj0R/+XWdOQBdnRZ+QiD7ejj4+EV2cFUV3bNPi+oOzv3EOzz/3PD6/r8M5i9nC2d84JwpRCSGEEEKInhb15KmxsREAm83W6fnW483Nzf0meWpubGLjKytQfS4IBzEqYQanx6HXwmhq6CstFdBUtHCIsLsJT005aBqqokdV9ChaGJ0WQq+F0HWzskYPWA//Cmh6NBQ0RYcCoCigKChGBUwt/42mAdpXpptphNFTQwol2gT2+FMIZ45gVEEWlw9LoSDXQbxFqh52JiMjg0suvYS3336bZqeTUCiEwWDAZrdz5plnkpGREe0QhRBCCCFED4h68hQKtSQTJpOp0/Otx/3+9gvuH3roIR5++OF2x5YvX05JSUkvRHmEz+fr9hk1+/aReuB/6NAIYkBFh8tjQWcwwFdHXjQNFB3o9KhGC5u1AvxB0CthdJqKptOj6Qxoip6wzoiqM6DqjKgGMxxeB6SYLFjizcTHxxFvjcNmtWCNN6LXKXy9Plx3hQ10HNnHaMpXrwrWsr+09hi+SrFp8uTJeL1enE4ndruduLg46uvrqa+vj3Zo4iQSyb8hIrZJHxFHI/1DdEf6yLErKipq9+fFixezZMmSTttGPXmyWFr2vgkGO1ZPg5ZpfQBxcXHtji9ZsqTDS61bt46RI0f2QpRHlJSUdPuMkSNHwjnHPlWrsPsmoh+IpI+I2CX9Q3RH+og4GukfojvSR47NunXr2LFjR8Tte68MWYSsVis6nQ6Xq+PGntAyXQ+6ntYnhBBCCCGEEH0h6smTyWQiOzubsrKyTs+XlZWRlJSEw+Ho28CEEEIIIYQQ4iuinjwBFBcXU1NTQ2lpabvjVVVV7N+/nwkTJkQnMCGEEEIIIYQ47KRInhYuXAjAAw88gKq2bJiqaRr3338/mqaxaNGiKEYnhBBCCCGEECdBwQiAmTNncu655/LGG2+waNEipk2bxoYNG1i7di1nnXUWc+bMiXaIQgghhBBCiBh3UiRPAPfddx8FBQW8+OKLPPnkk2RnZ3PLLbfw3e9+F0X5etFtIYQQQgghhOhbJ03yZDQa+f73v8/3v//9aIcihBBCCCGEEB2cFGuehBBCCCGEEOJkJ8mTEEIIIYQQQkRAkichhBBCCCGEiIAkT0IIIYQQQggRAUmehBBCCCGEECICkjwJIYQQQgghRAQkeRJCCCGEEEKICEjyJIQQQgghhBARkORJCCGEEEIIISIgyZMQQgghhBBCRECSJyGEEEIIIYSIgCRPQgghhBBCCBEBSZ6EEEIIIYQQIgKSPAkhhBBCCCFEBCR5EkIIIYQQQogISPIkhBBCCCGEEBGQ5EkIIYQQQgghIiDJkxBCCCGEEEJEQJInIYQQQgghhIiAommaFu0gesq6deuiHYIQQgghhBCiHykuLo647YBKnvpCUVERO3bsiHYY4iQmfUQcjfQP0R3pI+JopH+I7kgf6V0ybU8IIYQQQgghIiDJkxBCCCGEEEJEQJInIYQQQgghhIiAJE/HaPHixdEOQZzkpI+Io5H+IbojfUQcjfQP0R3pI71LCkYIIYQQQgghRARk5EkIIYQQQgghIiDJkxBCCCGEEEJEQJKnCIVCIZ544gnOPfdcxo0bx7x58/jLX/5CMBiMdmiiD9XU1HDXXXdx2mmnMWbMGE455RR+/OMfc/DgwQ5tX3rpJRYuXMiECRM49dRTuffee3G73VGIWkTLH/7wB4qKili9enWHc9I/Ytcrr7zCJZdcwvjx45k1axa33HILpaWlHdpJH4lNDQ0N/OpXv2L27NmMGTOG008/nfvuuw+v19uhrfSR2FBVVUVxcTFPPPFEp+ePpR988MEHLFq0iIkTJzJjxgx+/vOfU1dX14vRDzySPEVo6dKl3HvvvTgcDq6++moyMjJ48MEHue2226IdmugjNTU1XHrppaxYsYJhw4Zx1VVXMXbsWF577TUuueQS9u3b19b273//Oz/96U9RVZUrr7ySESNG8MQTT/Dtb3+bQCAQvZcQfWbz5s08+eSTnZ6T/hG7HnjgAW6//Xaam5u5/PLLmTp1Ku+++y6LFi2irKysrZ30kdjkdru5/PLL+c9//sOQIUO46qqrSE9P57HHHuO6664jFAq1tZU+EhvcbjdLlizB5XJ1ev5Y+sFrr73GjTfeSF1dHZdddhnTp0/nxRdf5Fvf+hZOp7MvXmdg0ES31q1bpxUWFmpLlizRVFXVNE3TVFXVfvKTn2iFhYXae++9F+UIRV+48847tcLCQu1f//pXu+Mvv/yyVlhYqN14442apmnaoUOHtFGjRmmLFi3SAoFAW7s//elPWmFhofb000/3adyi7/n9fu28887TCgsLtcLCQu3zzz9vOyf9I3Zt2rRJKyoq0q688krN6/W2HV+5cqVWWFio/exnP9M0TfpILHvssce0wsJC7be//W3bMVVVtdtuu00rLCzUXnjhBU3TpI/EirKyMu3CCy9s+17y+OOPtzt/LP3A5XJpU6dO1ebNm6c1Nze3HX/uuee0wsJC7fe//32vv89AISNPEXjmmWeAltKPiqIAoCgKP/rRj1AUheeeey6a4Yk+8u6775KcnMw111zT7vj5559Pfn4+n3zyCaqqsmLFCkKhEDfeeCNGo7Gt3U033YTVapX+EgMeeeQRSktLmTlzZodz0j9iV+v3kqVLl2KxWNqOn3322SxatIj8/HxA+kgs+/LLLwG4+OKL244pisKll14KwMaNGwHpI7HgiSeeYMGCBWzfvp3p06d32uZY+sHrr79OY2Mj1157LVarte34JZdcwpAhQ3jhhRcIh8O990IDiCRPEVi7di1JSUkUFha2O56RkcHgwYNZs2ZNlCITfSUcDnPjjTeyePFidLqOf21MJhPBYJBgMNjWH6ZMmdKujdlsZsKECWzfvp3m5uY+iVv0ve3bt/Poo49y4403UlBQ0OG89I/Y9dFHH1FYWMiQIUM6nFu6dCnf+973AOkjsczhcABQXl7e7nhVVRUAycnJgPSRWPDUU0+Rk5PDsmXLuOCCCzptcyz9oLXttGnTOtxn6tSpNDY2smvXrp58hQFLkqduBAIBKisr234i+HU5OTk4nU7q6+v7ODLRl/R6Pddccw1XXHFFh3N79uxh79695OfnYzabOXDgAKmpqe1+stMqJycHoNPF4aL/C4fD/PznP2fQoEHceOONnbaR/hGb6urqqK+vZ/jw4ezZs4fFixczefJkiouLueWWW9oVnZE+ErsuvvhijEYj9957L+vWrcPr9bJ69Wr++Mc/YrPZ2kakpI8MfHfffTcvvfQSkyZN6rLNsfSD1n9j8vLyOrTNzc1t11YcnSRP3WhsbATAZrN1er71uPyEJzapqspvfvMbVFXlm9/8JtDSZ7rrL10t/BT922OPPUZJSQm//e1vMZlMnbaR/hGbqqurgZYRhEsvvZRDhw5x8cUXU1xczFtvvcWiRYs4dOgQIH0klo0ZM4bHH38cn8/H5ZdfzoQJE7j66qvR6/X8+9//bvuQK31k4Js9ezZ6vf6obY6lHzQ0NGAymdpNGW7VmnxJn4mMJE/daK1s09UHodbjfr+/z2ISJwdN07jrrrtYtWoVY8aMaVsLFQqFpL/EoNLSUh5++GEuv/xyJk6c2GU76R+xyePxAC1TZ+bPn8/zzz/PHXfcwaOPPsovf/lL6urquOeeewDpI7Gsrq6O+++/n5qaGubOncv111/P1KlTKS8v56677mqriCZ9RMCx9QPpMz3HEO0ATnatGXpX+zm1loGMi4vrs5hE9IVCIe68805eeOEF8vLy+Otf/9r2j4/FYpH+EmM0TeMXv/gFKSkp/OhHPzpqW+kfsal1raRer+fnP/95u58oX3HFFTz55JN8+OGHeL1e6SMx7LbbbmP9+vU88MADnHvuuW3Hn3jiCe69917uvPNO/vznP0sfEcCxfT+RPtNzZOSpG1arFZ1O1+VQZut0va6GTcXA4/V6ufnmm3nhhRcYPHgwTz31FBkZGW3n7XZ7l9M4pb8MTM888wzr1q3j17/+NQkJCUdtK/0jNrX+P83JyWkrCtBKp9NRVFREMBikvLxc+kiMqqysZNWqVUyZMqVd4gRw7bXXUlBQwNtvv43L5ZI+IoBj+35it9vx+/2d7gHW+hlX+kxkJHnqhslkIjs7u93mhV9VVlZGUlJSh2+GYmBqamrimmuu4cMPP2TUqFEsX76c7Ozsdm0GDx5MXV0dPp+vw/WHDh1Cp9MxaNCgvgpZ9IG33noLgBtuuIGioqK2X0899RQAV199NUVFRZSVlUn/iFF5eXno9fouf/LbOkU8Li5O+kiMqqioAGDo0KGdnh82bBiqqlJVVSV9RADH9nlj8ODBAJ1+nm091lklUNGRJE8RKC4upqampkMVkqqqKvbv38+ECROiE5joU36/nxtvvJFNmzYxdepUnn76aVJSUjq0Ky4uRlVV1q5d2+H6jRs3UlBQ0GllHNF/XXjhhSxevLjDr/Hjx7c7b7fbpX/EKLPZzJgxY6ioqGDfvn3tzoVCIbZv347D4SAjI0P6SIxKTU0F6NA/Wu3fvx9FUUhJSZE+IoBj+7xRXFwM0On2OqtXr8ZmszFs2LDeD3oAkOQpAgsXLgTggQceQFVVoGWNw/3334+maSxatCiK0Ym+cv/997NhwwYmTpzIP/7xjy6/MS1YsAC9Xs/DDz/cbnj8kUceweVySX8ZgC666CKWLFnS4ddXk6clS5Zgt9ulf8Sw1oqcv/vd79qNQP3rX/+isrKShQsXotfrpY/EqLy8PEaPHs0XX3zBu+++2+7cc889x/bt25k1axYOh0P6iACO7fPG/PnzSUhI4J///GdbJWmA559/nn379nHppZd2uo+l6EgKRkRg5syZnHvuubzxxhssWrSIadOmsWHDBtauXctZZ53FnDlzoh2i6GU1NTU888wzQMuUin/84x+dtrvhhhsYOnQo119/Pf/4xz9YuHAhc+fOZffu3XzwwQdMmjSp7QOUiE3SP2LXxRdfzPvvv8+7777LwoULOfXUU9mzZw8ffvghgwcPZvHixYD0kVh2zz33cNVVV7FkyRLmzp3LkCFD2LFjBx9//DFpaWn86le/AqSPiBbH0g8cDge33347v/71r1m4cCHnnHMOVVVVrFy5ksGDB3e5N6HoSNE0TYt2EP1BMBjk0Ucf5cUXX6Sqqors7GzOP/98vvvd73ZZ+lEMHO+++y7f//73u223Zs0a7HY7mqaxfPlyli9fzoEDB0hLS+OMM85g8eLFsiAzhvzud7/jqaee4qmnnmq3q7v0j9gVCoVYtmwZzz33HAcOHMDhcDBv3jx+8IMfkJSU1NZO+kjsOnDgAH/5y1/49NNPaWhoICUlhTlz5rB48WLS09Pb2kkfiR0vvPACd9xxB3fccQfXXnttu3PH2g/eeOMN/vnPf7J7924SExOZNWsWP/zhD9v1LXF0kjwJIYQQQgghRARkcqMQQgghhBBCRECSJyGEEEIIIYSIgCRPQgghhBBCCBEBSZ6EEEIIIYQQIgKSPAkhhBBCCCFEBCR5EkIIIYQQQogISPIkhBBCdEJ28hBCCPF1hmgHIIQQIvasXr2aq6++usNxvV6PxWIhKyuL6dOnc/nllzNs2LA+j+/LL79k6dKlPPfcc23HysrKmDdvHvn5+bzzzjt9HpMQQojok+RJCCFE1MTHxzNv3ry2P4fDYZqbm9m+fTvLli3j2WefZenSpVx44YV9Gtdll11GMBjs02cKIYQ4+UnyJIQQImqSkpL44x//2OG4pmn85z//4be//S2//OUvyczMZMaMGX0Wl6qqffYsIYQQ/YeseRJCCHHSURSFyy67jFtvvZVQKMQf/vAHWYMkhBAi6iR5EkIIcdK67rrryMjIoKSkhI0bN7YdD4VCPPPMM1x00UVMmDCBSZMmceWVV/L22293uMdDDz1EUVER7777Lq+++ioLFixg3LhxzJs3j/vuu4+mpqa2ti+88AJFRUWEw2EAioqKOP300zvcs6KigjvuuIOZM2cybtw4zjvvPJ588klJ8IQQYoCT5EkIIcRJy2AwMHv2bABWrVoFQDAY5KabbmLp0qWUlZUxefJkJk6cyObNm1myZAkPPPBAp/d6/vnn+fGPf0w4HGbOnDkEAgEee+wxrrzyShobGwHIz89nwYIFKIoCwIIFC5g/f367+zQ1NXHJJZfw9ttvM378eMaNG8fu3bu55557Op2CKIQQYuCQNU9CCCFOakOHDgWgtLQUgL/85S98/PHHnHLKKdx///04HA6gpRreddddxyOPPMKUKVOYNWtWu/u8//77XH/99fzkJz9BURR8Ph+33HILH374IQ8++CB33XUXkydPZvLkybzxxhuEw+FOk6GmpiYmT57MX//6VxITEwFYuXIlt956K8uXL+cHP/gBJpOpF78iQgghokVGnoQQQpzU7HY7AA0NDQQCAZYtW4bZbOa+++5rS5wAcnNz+cUvfgHA448/3uE+hYWF3H777W2jShaLhXvvvRej0ciLL75IIBCIOKalS5e2JU4A55xzDtnZ2Xg8Hg4ePHg8rymEEKIfkORJCCHESa01qVEUha1bt9Lc3ExBQQGpqakd2s6YMQODwcC6deva1i21Ouecc9Dp2n/bS0lJYeLEiXg8Hr788suI4klMTOx076nMzEwAnE5nRPcRQgjR/8i0PSGEECe11oIOiYmJVFRUALB161aKioq6vCYUCtHU1ERycnLbsUGDBnXatjXpqa6ujigem83W6XGDoeVb6teTNiGEEAOHJE9CCCFOatu3bwdaKt+17r+Um5vLxIkTj+k+Xx91atVaIU+v15/QfYQQQgx8kjwJIYQ4afl8Pj7//HOgZUqe2+0GIC8v75gr21VVVXV6vLy8HDgyAiWEEEJ0RX58JoQQ4qS1bNkympqaGDVqFGPGjGHs2LFYLBa+/PJL6uvrO7TfsWMHZ5xxBkuWLOmw59LHH3/coX1NTQ2bN28mKSmJ0aNHtx1vLSohhBBCfJUkT0IIIU46qqry/PPP86c//QmDwdBWRS8+Pp5LL70Ul8vFT37yExoaGtquaWho4I477uDAgQNkZWV1SIA++eQTnn322bY/ezwefvaznxEMBrnyyivbTdtrLTXe3Nzcm68phBCin5Fpe0IIIaKmoaGBH//4x21/VlWVpqYmtm/fTm1tLSaTid///vdMnjy5rc1tt93G1q1b+fjjjznjjDMYN24cBoOBtWvX4na7mTBhArfeemuHZ+Xl5XHnnXfy7LPPkp2dzbp166itrWXGjBnccMMN7doOHjyYbdu2ceWVV1JQUMD//d//9drXQAghRP8hyZMQQoio8Xg8vPrqq21/1ul0xMfHk5eXx/nnn88VV1xBbm5uu2vi4uJ48sknWb58Oa+88grr169Hr9czaNAgFixYwGWXXUZcXFyHZ1100UVkZ2fzt7/9jQ8++IC8vDyuv/56rr76aoxGY7u2d999N3fddRe7d++murqaxsbGXnl/IYQQ/YuifX1SuBBCCDGAPPTQQzz88MP84Ac/4Oabb452OEIIIfoxWfMkhBBCCCGEEBGQ5EkIIYQQQgghIiDJkxBCCCGEEEJEQNY8CSGEEEIIIUQEZORJCCGEEEIIISIgyZMQQgghhBBCRECSJyGEEEIIIYSIgCRPQgghhBBCCBEBSZ6EEEIIIYQQIgKSPAkhhBBCCCFEBP4/rbviz+pFe6cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots(figsize=(12,10))\n",
    "a1.scatter(106,3.9e16,s=75)\n",
    "a1.scatter(106,diff_visc['viscosity2_6'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(80,diff_visc['viscosity3_2'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(40,diff_visc['viscosity4_3'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(30,diff_visc['viscosity8_4'][:'2018-12-15'][:-1].median(),s=75)\n",
    "a1.scatter(25,diff_visc['viscosity7_8'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(20,diff_visc['viscosity5_7'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(20,diff_visc['viscosity9_7'][:'2018-12-15'].median(),s=75)\n",
    "a1.plot(dddf['dep'],dddf['vSS_sm'])\n",
    "a1.plot(dddf['dep'],dddf['vSS_f'])\n",
    "a1.set_ylabel('Viscosity')\n",
    "a1.set_xlabel('Depth')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_hole_labels = visc_df.holenum.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "sl_s = (df_dc.index[-1]-df_dc.index[0]).value/1e9 #series length in seconds\n",
    "mean_hole_visc2 = [-1*(visc_df[visc_df.holenum == kk].stress.median())/(2*(df_dc['strain{}'.format(kk)][-1])/sl_s) for kk in diff_hole_labels]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>hole_length8</th>\n",
       "      <th>hole_length4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIMESTAMP</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-02-09 12:00:00</th>\n",
       "      <td>24.649893</td>\n",
       "      <td>29.569887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-21 00:00:00</th>\n",
       "      <td>24.464676</td>\n",
       "      <td>29.381548</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     hole_length8  hole_length4\n",
       "TIMESTAMP                                      \n",
       "2017-02-09 12:00:00     24.649893     29.569887\n",
       "2018-12-21 00:00:00     24.464676     29.381548"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfp4[['hole_length8','hole_length4']].iloc[[0,-1]]#-dfp4[['hole_length8','hole_length4']].iloc[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_hole_visc = [visc_df[visc_df.holenum == xx].visc.median() for xx in visc_df.holenum.unique()]\n",
    "# mean_hole_visc[-1] = visc_df.loc[236].visc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2a581c9a0>]"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots()\n",
    "a1.semilogy(amaxlist[:],mean_hole_visc2[:],label='max')\n",
    "# a1.scatter(ameanlist,mean_hole_visc,label='max')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1666"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(repmids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1666"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(visc_df['visc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# htda\n",
    "# hbda\n",
    "f1,a1=plt.subplots()\n",
    "dcol = 0\n",
    "a1.hlines(mean_hole_visc,htda,hbda,label='Field measurements',color=palette[dcol])\n",
    "# a1.hlines(mean_hole_visc2,htda,hbda,label='Field measurements',color='k')\n",
    "a1.scatter(repmids,visc_df['visc'],color=palette[dcol])\n",
    "# a1.plot(dddf['dep'],dddf['vSS_sm'],label='Steady-State derived')\n",
    "a1.plot(dddf['dep'],dddf['vSS_f'],label='Steady-State derived',color=palette[2])\n",
    "# a1.step(hbda,mean_hole_visc)\n",
    "a1.set_yscale('log');\n",
    "a1.set_ylabel('Viscosity (Pa s)');\n",
    "a1.set_xlabel('Depth (m)');\n",
    "a1.legend();\n",
    "f1.savefig('SP_viscosity_SSvData.eps')\n",
    "# f1.savefig('/Users/maxstev/Documents/Grad_School/Manuscripts/Stevens_SPfirn/texfigures/SP_viscosity_SSvData.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "dCO =dddf.copy()\n",
    "dCO['vSS_f'][dCO['vSS_f']==0]=np.nan\n",
    "dCO['Vmean'] = np.ones_like(dCO['stress'])\n",
    "ssHD = np.array((0,4.4,10,15,20,25,30,40,80,106))\n",
    "SSvmean = np.zeros(len(ssHD)-1)\n",
    "for ii,DD in enumerate(ssHD):\n",
    "    if ii==len(ssHD)-1:\n",
    "        continue\n",
    "    else:\n",
    "        dCO.loc[(dCO['dep']>ssHD[ii]) & (dCO['dep']<ssHD[ii+1]),'Vmean'] = dCO[(dCO['dep']>ssHD[ii]) & (dCO['dep']<ssHD[ii+1])]['vSS_f'].median()\n",
    "        SSvmean[ii] = dCO[(dCO['dep']>ssHD[ii]) & (dCO['dep']<ssHD[ii+1])]['vSS_f'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n",
      "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots()\n",
    "dcol = 0\n",
    "a1.vlines(mean_hole_visc,htda,hbda,label='Field measurements',color=palette[dcol])\n",
    "# a1.hlines(mean_hole_visc2,htda,hbda,label='Field measurements',color='k')\n",
    "a1.scatter(visc_df['visc'],repmids,color=palette[dcol])\n",
    "# a1.plot(dddf['dep'],dddf['vSS_sm'],label='Steady-State derived')\n",
    "a1.plot(dddf['vSS_f'],dddf['dep'],label='Steady-State derived',color=palette[2])\n",
    "a1.vlines(SSvmean,ssHD[0:-1],ssHD[1:],color=palette[2])\n",
    "# a1.step(hbda,mean_hole_visc)\n",
    "a1.set_xscale('log');\n",
    "a1.set_xlabel('Viscosity (Pa s)');\n",
    "a1.set_ylabel('Depth (m)');\n",
    "a1.invert_yaxis()\n",
    "a1.legend();\n",
    "f1.savefig('SP_viscosity_SSvData.eps')\n",
    "# f1.savefig('/Users/maxstev/Documents/Grad_School/Manuscripts/Stevens_SPfirn/texfigures/SP_viscosity_SSvData.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['HLdynamic', 'Ligtenberg2011', 'Li2015', 'Crocus', 'GSFC2020', 'MaxSP']"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "thenames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_plotdeets(modelname):\n",
    "    palette = sns.color_palette()\n",
    "    if modelname =='data':\n",
    "        colo = 'black'\n",
    "        legname = 'Data'\n",
    "    elif modelname =='HLdynamic':\n",
    "        colo = palette[1]\n",
    "        legname = 'Herron & Langway (1980)'\n",
    "    elif modelname == 'MaxSP':\n",
    "        colo = palette[3]\n",
    "        legname = 'This work'\n",
    "    elif modelname == 'Ligtenberg2011':\n",
    "        colo = palette[2]\n",
    "        legname = 'Ligtenberg et al. (2011)'\n",
    "    elif modelname == 'GSFC2020':\n",
    "        colo = palette[0]\n",
    "        legname = 'GSFC (Medley et al., 2020)'\n",
    "    elif modelname == 'Li2015':\n",
    "        colo = palette[4]\n",
    "        legname = 'Li & Zwally (2015)'\n",
    "    elif modelname == 'Crocus':\n",
    "        colo = palette[5]\n",
    "        legname = 'Crocus (Vionnet et al. 2012)' \n",
    "    return colo, legname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 0.0000000e+00,\n",
       "        0.0000000e+00, 0.0000000e+00],\n",
       "       [1.7096029e+08, 1.6153273e+10, 2.3672752e+10, ..., 4.5394368e+16,\n",
       "        4.5400764e+16, 4.5407159e+16],\n",
       "       [1.6232560e+08, 1.6264398e+10, 2.3772129e+10, ..., 4.5394755e+16,\n",
       "        4.5401150e+16, 4.5407545e+16],\n",
       "       ...,\n",
       "       [1.2783808e+08, 7.1612850e+10, 2.6673057e+11, ..., 4.5691812e+16,\n",
       "        4.5698276e+16, 4.5704740e+16],\n",
       "       [1.7979251e+08, 7.3117606e+10, 2.5655997e+11, ..., 4.5692396e+16,\n",
       "        4.5698860e+16, 4.5705324e+16],\n",
       "       [1.9281021e+08, 7.3192948e+10, 2.4748732e+11, ..., 4.5692826e+16,\n",
       "        4.5699290e+16, 4.5705753e+16]], dtype=float32)"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['SP50']['MET']['GSFC2020']['rdaily']['visc_trun']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,axes=plt.subplots(2,3,sharex=True,sharey=True)\n",
    "shortnames=['HL','LIG','LZ','CRO','GSFC','This work']\n",
    "dcol = 'silver'\n",
    "axes = axes.ravel()\n",
    "for i2,vv in enumerate(axes):\n",
    "    axes[i2].vlines(mean_hole_visc,htda,hbda,label='Field measurements',color=dcol)\n",
    "    axes[i2].scatter(visc_df['visc'],repmids,color=dcol)\n",
    "    name = thenames[i2]\n",
    "#     print(name)\n",
    "    colo, legname = get_plotdeets(name)\n",
    "    for ijk in range(len(d['SP50']['MET'][name]['rdaily']['visc_trun'])):\n",
    "        axes[i2].plot(d['SP50']['MET'][name]['rdaily']['visc_trun'][ijk,:],d['SP50']['MET'][name]['rdaily']['dep_trun'][ijk,:],color=colo)\n",
    "    # a1.step(hbda,mean_hole_visc)\n",
    "    axes[i2].set_xscale('log');\n",
    "#     axes[i2].set_xlabel('Viscosity (Pa s)');\n",
    "#     axes[i2].set_ylabel('Depth (m)');\n",
    "    axes[i2].set_xlim(1e12,1e18)\n",
    "    axes[i2].set_ylim(0,85)\n",
    "    axes[i2].invert_yaxis()\n",
    "    axes[i2].set_title(shortnames[i2],fontsize=16)\n",
    "    if ((i2==0) or (i2==3)):\n",
    "        axes[i2].set_ylabel('Depth (m)')\n",
    "    if i2>=3:\n",
    "        axes[i2].set_xlabel('Viscosity (Pa s)')\n",
    "#     axes[i2].legend();\n",
    "f1.savefig('SP_viscosity_SSvData.pdf')\n",
    "f1.savefig('/Users/maxstev/Documents/Grad_School/Manuscripts/Stevens_SPfirn/texfigures/SP_viscosity_SSvData_model.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "2017-1021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "usp50_ts[151:743].bdot_ie.mean()*1.08"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "usp50_ts.iloc[200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# f1, ((a1,a2),(a3,a4)) = plt.subplots(2,2,gridspec_kw={'height_ratios': [2.5, 1]},figsize = (16,10))\n",
    "# plt.subplots_adjust(hspace=0.0)\n",
    "# a1.plot(usp50_ts['tau'],usp50_ts['Depth'],color=palette[0])\n",
    "# a1.set_ylabel('Depth (m)')\n",
    "# a1.set_xlim(0,usp50_ts['tau'].max())\n",
    "# a1.set_ylim(0,usp50_ts['Depth'].max())\n",
    "# a1.set_xticklabels([])\n",
    "# a1.invert_yaxis()\n",
    "# a2.plot(usp50_ts['density'],usp50_ts['Depth'],color=palette[2])\n",
    "# # a1.get_shared_x_axes().join(a1, a2)\n",
    "# a2.set_ylim(0,usp50_ts['Depth'].max())\n",
    "# a2.set_xlim(300,820)\n",
    "# a2.set_xlabel('Density (kg m$^{-3}$)')\n",
    "# a2.invert_yaxis()\n",
    "# # a1.tick_params(labelcolor='w')#, top=False, bottom=False, left=False, right=False)\n",
    "# a3.plot(usp50_ts['tau'][2:],usp50_ts['bdot_ie'][2:],color=palette[1])\n",
    "# a3.set_xlim(0,usp50_ts['tau'].max())\n",
    "# a3.set_ylabel('Accumulation \\n (m ice eq.)')\n",
    "# a3.set_xlabel('Age (relative to 2017)')\n",
    "# a4.axis('off')\n",
    "# f1.set_tight_layout(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = usp50_ts['bdot_ie'][150:]\n",
    "X = usp50_ts.index[150:]\n",
    "X = sm.add_constant(X)\n",
    "model = sm.OLS(Y,X)\n",
    "results = model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "69.31/917"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(usp50_ts['bdot_ie'][2:]).rolling(10).mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "usp50_ts['bdot_kg'] = usp50_ts['bdot_ie']*917\n",
    "txp = 0.85\n",
    "typ = 0.9\n",
    "fig = plt.figure(figsize = (16,10))\n",
    "fig.set_tight_layout(False)\n",
    "gs = mpl.gridspec.GridSpec(2, 2, wspace=0.1, hspace=0.001,width_ratios=[1,1],height_ratios=[2.2,1]) # 2x2 grid\n",
    "a1 = fig.add_subplot(gs[0, 0]) # first row, first col\n",
    "a2 = fig.add_subplot(gs[0, 1]) # first row, second col\n",
    "a3 = fig.add_subplot(gs[1, 0]) # full second row\n",
    "a1.plot(usp50_ts['tau'],usp50_ts['Depth'],color=palette[0])\n",
    "# a1.plot(usp50_ts['tau'],usp50_ts['Depth'],'.',color=palette[0])\n",
    "a1.set_ylabel('Depth (m)')\n",
    "a1.set_xlim(0,usp50_ts['tau'].max())\n",
    "a1.set_ylim(0,usp50_ts['Depth'].max()+5)\n",
    "a1.set_xticklabels([])\n",
    "a1.invert_yaxis()\n",
    "a1ylim = a1.get_ylim()\n",
    "a1ty = (a1ylim[1] - a1ylim[0])*typ + a1ylim[0]\n",
    "a1xlim = a1.get_xlim()\n",
    "a1tx = (a1xlim[1] - a1xlim[0])*txp + a1xlim[0]\n",
    "a1.text(a1tx,a1ty,'(a)',fontsize=22)\n",
    "# a1.text(900,10,'(a)',fontsize=22)\n",
    "a2.plot(usp50_ts['density'],usp50_ts['Depth'],color=palette[2])\n",
    "# a1.get_shared_x_axes().join(a1, a2)\n",
    "a2.set_ylim(0,usp50_ts['Depth'].max()+5)\n",
    "a2.set_xlim(300,820)\n",
    "a2.set_xlabel('Density (kg m$^{-3}$)')\n",
    "a2.yaxis.tick_right()\n",
    "a2.yaxis.set_ticks_position('both')\n",
    "a2.invert_yaxis()\n",
    "a2ylim = a2.get_ylim()\n",
    "a2ty = (a2ylim[1] - a2ylim[0])*typ + a2ylim[0]\n",
    "a2xlim = a2.get_xlim()\n",
    "a2tx = (a2xlim[1] - a2xlim[0])*txp + a2xlim[0]\n",
    "a2.text(a2tx,a2ty,'(b)',fontsize=22)\n",
    "# a2.text(758,10,'(b)',fontsize=22)\n",
    "# a1.tick_params(labelcolor='w')#, top=False, bottom=False, left=False, right=False)\n",
    "a3.plot(usp50_ts['tau'][2:],usp50_ts['bdot_kg'][2:],color=palette[1])\n",
    "a3.plot(usp50_ts['tau'][2:],(usp50_ts['bdot_kg'][2:]).rolling(10).mean(),color=palette[3])\n",
    "a3.set_xlim(0,usp50_ts['tau'].max())\n",
    "a3.set_ylabel('Accumulation \\n (kg m$^{-2}$ a$^{-1}$)')\n",
    "a3.set_xlabel('Age (relative to 2017)');\n",
    "a3.tick_params(axis=\"x\", direction=\"inout\",length=8,width=1,color='k');\n",
    "a3.spines[\"top\"].set_linewidth(1.5)\n",
    "a3.spines[\"top\"].set_color('k')\n",
    "a3ylim = a3.get_ylim()\n",
    "a3ty = (a3ylim[1] - a3ylim[0])*0.82 + a3ylim[0]\n",
    "a3xlim = a3.get_xlim()\n",
    "a3tx = (a3xlim[1] - a3xlim[0])*txp + a3xlim[0]\n",
    "a3.text(a3tx,a3ty,'(c)',fontsize=22)\n",
    "# a3.text(900,0.14,'(c)',fontsize=22)\n",
    "# a3b = a3.secondary_xaxis(\"top\");\n",
    "# a3b.tick_params(axis=\"x\", direction=\"inout\",length=8,width=1,color='k');\n",
    "# a3b.set_xticklabels([]);\n",
    "# a4.axis('off')\n",
    "fig.savefig('SP_DD_DA_BDOT.eps')\n",
    "fig.savefig('/Users/maxstev/Documents/Grad_School/Manuscripts/Stevens_SPfirn/texfigures/SP_DD_DA_BDOT.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# f1,a1=plt.subplots()\n",
    "# dcol = 0\n",
    "# a1.hlines(mean_hole_visc,htda,hbda,label='Field measurements',color=palette[dcol])\n",
    "# # a1.hlines(mean_hole_visc2,htda,hbda,label='Field measurements',color='k')\n",
    "# a1.scatter(repmids,visc_df['visc'],color=palette[dcol])\n",
    "# # a1.plot(dddf['dep'],dddf['vSS_sm'],label='Steady-State derived')\n",
    "# a1.plot(dddf['dep'],dddf['vSS_f'],label='Steady-State derived',color=palette[2])\n",
    "# # a1.step(hbda,mean_hole_visc)\n",
    "# a1.set_yscale('log');\n",
    "# a1.set_ylabel('Viscosity');\n",
    "# a1.set_xlabel('Age');\n",
    "# a1.legend();\n",
    "# f1.savefig('SP_viscosity_SSvData_age.eps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1,a1=plt.subplots(figsize=(12,10))\n",
    "a1.scatter(106,3.9e16,s=75)\n",
    "a1.scatter(106,diff_visc['viscosity2_6'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(80,diff_visc['viscosity3_2'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(40,diff_visc['viscosity4_3'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(30,diff_visc['viscosity8_4'][:'2018-12-15'][:-1].median(),s=75)\n",
    "a1.scatter(25,diff_visc['viscosity7_8'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(20,diff_visc['viscosity5_7'][:'2018-12-15'].median(),s=75)\n",
    "a1.scatter(20,diff_visc['viscosity9_7'][:'2018-12-15'].median(),s=75)\n",
    "a1.plot(dddf['dep'],dddf['vSS_sm'])\n",
    "a1.plot(dddf['dep'],dddf['vSS_f'])\n",
    "a1.set_ylabel('Viscosity')\n",
    "a1.set_xlabel('Depth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_visc['viscosity2_6'][:'2018-12-15'].resample('28D').median().median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %matplotlib notebook\n",
    "f1,a1=plt.subplots(figsize=(12,10))\n",
    "diff_visc['viscosity2_6'][:'2018-12-15'].resample('28D').median().plot(ax=a1,drawstyle='steps')\n",
    "diff_visc['viscosity3_2'][:'2018-12-15'].resample('28D').median().plot(ax=a1,drawstyle='steps')\n",
    "diff_visc['viscosity4_3'][:'2018-12-15'].resample('28D').median().plot(ax=a1,drawstyle='steps')\n",
    "diff_visc['viscosity8_4'][:'2018-12-15'].resample('28D').median()[:-1].plot(ax=a1,drawstyle='steps')\n",
    "diff_visc['viscosity7_8'][:'2018-12-15'].resample('28D').median().plot(ax=a1,drawstyle='steps')\n",
    "# diff_visc.resample('21D').median().plot(ax=a1)\n",
    "# a1.set_ylim(1e14,3e16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "visc_df.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfp4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dfp4[['hole_length2','hole_length6']]-dfp4[['hole_length2','hole_length6']].iloc[0]\n",
    "diff26 = (dfp4['hole_length2']-dfp4['hole_length2'].iloc[0]) - (dfp4['hole_length6']-dfp4['hole_length6'].iloc[0])\n",
    "sss = (diff26.index[-1]-diff26.index[0]).value/1e9\n",
    "sr26 = -1*(diff26[-1]/26)/sss\n",
    "v26 = np.min(stress_holebot)/(2*sr26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v26"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sr26"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sr26"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_viscZ1 = diff_visc.iloc[:,:-7].copy()\n",
    "diff_viscZ1 = diff_viscZ1.resample(resamp).median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_viscZ2 = diff_visc.iloc[:,-7:].copy()\n",
    "for kk in diff_viscZ2.keys():\n",
    "    diff_viscZ2.loc[:,kk] = diff_viscZ2[kk].median()\n",
    "diff_viscZ2 = diff_viscZ2.resample(resamp).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1,a1=plt.subplots(figsize=(10,16))\n",
    "# diff_visc['viscosity26'][:'2018-12-15'].plot(ax=a1)\n",
    "# diff_visc.resample(resamp).median().plot(ax=a1,drawstyle='steps',logy=True)\n",
    "diff_viscZ1.plot(ax=a1,drawstyle='steps')#,logy=True)\n",
    "# diff_viscZ2.plot(ax=a1,drawstyle='steps',logy=True)\n",
    "# a1.set_ylim(1e14,3e16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ---------------------------------------------\n",
    "# Age and rho for viscosity analysis\n",
    "# ---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "usp50_ts['bdot_kg'] = usp50_ts['bdot_ie']*917\n",
    "usp50_ts['stress']=usp50_ts['mass'].cumsum()*9.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1,a1=plt.subplots(figsize=(8,6))\n",
    "a1.plot(usp50_ts.density,usp50_ts.Depth)\n",
    "a1.invert_yaxis()\n",
    "a1.set_ylabel('depth')\n",
    "a1.set_xlabel('Density')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1,a1=plt.subplots(figsize=(8,6))\n",
    "a1.plot(usp50_ts.density,usp50_ts.tau**(1/2))\n",
    "a1.invert_yaxis()\n",
    "a1.set_ylabel('Age')\n",
    "a1.set_xlabel('Density')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1,a1=plt.subplots(figsize=(8,6))\n",
    "a1.semilogx(usp50_ts.stress,usp50_ts.density)\n",
    "# a1.invert_yaxis()\n",
    "a1.set_ylabel('density')\n",
    "a1.set_xlabel(r'$\\sigma$');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "z1_vmed = np.array([visc_df.iloc[tsl*kk:tsl*(kk+1)]['visc'].median() for kk in range(l2)])\n",
    "z1_vmean = np.array([visc_df.iloc[tsl*kk:tsl*(kk+1)]['visc'].mean() for kk in range(l2)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# f1,a1 = plt.subplots()\n",
    "# a1.scatter(z1_diff_meanage**2,z1_vmed,s=75)\n",
    "# a1.scatter(z1_diff_meanage**1.1,z1_vmean,s=75)\n",
    "# a1.scatter(z1_diff_maxage**1.1,z1_vmed,s=75)\n",
    "# a1.scatter(z1_diff_maxage**1.1,z1_vmean,s=75)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ------------------------------------------------------------------\n",
    "#    COMPACTIVE VISCOSITY, STEADY STATE\n",
    "# ------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$Ag \\eta \\ln(\\frac{\\rho_{2}}{\\rho_{1}}) = \\frac{1}{2} (\\sigma_{2}^{2} - \\sigma_{1}^{2})$\n",
    "\n",
    "From Maeno and Narita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "def den_fit(dep,a,b,c):\n",
    "    return a*dep**(b) + c\n",
    "\n",
    "pp1, pp1cov = curve_fit(den_fit, dep_c, den_c,p0=np.array([40,0.5,400]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "dddf = pd.DataFrame({'dep':dep_c,'den':den_c,'den_sm':den_c,'stress':stress_cu})\n",
    "dddf.loc[:,'den_sm']=dddf.den.rolling(12,win_type='hamming',center=True).mean()\n",
    "dddf['den_sm'][np.isnan(dddf['den_sm'])] = dddf['den'][np.isnan(dddf['den_sm'])]\n",
    "dddf['den_fit'] = den_fit(dddf['dep'],pp1[0],pp1[1],pp1[2])\n",
    "layer_mass_sm = layer_thickness*dddf['den_sm']\n",
    "layer_mass_f = layer_thickness*dddf['den_fit']\n",
    "mass_sm = np.cumsum(layer_mass_sm)\n",
    "mass_f = np.cumsum(layer_mass_f)\n",
    "stress_cu_sm = mass_sm * 9.8\n",
    "stress_cu_f = mass_f * 9.8\n",
    "dddf['stress_sm']= stress_cu_sm\n",
    "dddf['stress_f']= stress_cu_f\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "A=69.37 #kg/m^2/a\n",
    "g=9.8\n",
    "den_f1 = dddf['den_fit'].values\n",
    "den_sm = dddf['den_sm'].values\n",
    "dddf['vSS_sm'] = np.append(0,1/2*(np.diff(dddf['stress_sm'].values**2)) / np.log(den_sm[1:]/den_sm[0:-1])/g/A/2)*SPY\n",
    "dddf['vSS_sm'][dddf['vSS_sm']<0]=np.nan\n",
    "dddf['vSS_f'] = np.append(0,1/2*(np.diff(dddf['stress_f'].values**2)) / np.log(den_f1[1:]/den_f1[0:-1])/g/A/2)*SPY\n",
    "dddf['vSS_f'][dddf['vSS_f']<0]=np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "xar = np.arange(0,110)\n",
    "# den_f = den_fit(xar,pp1[0],pp1[1],pp1[2])\n",
    "# layer_mass_f = den_f.copy()\n",
    "# mass_f= np.cumsum(layer_mass_f)\n",
    "# stress_cu_f= mass_f * 9.8\n",
    "# vSS_f = (1/2*(np.diff(stress_cu_f**2))) / (np.log(den_f[1:]/den_f[0:-1])*g*A*2) * SPY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10b923a30>]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "f1,a1 =plt.subplots(figsize=(8,6))\n",
    "# a1.plot(smooth(den_c)[1:],dep_c)\n",
    "# a1.invert_yaxis()\n",
    "a1.scatter(dep_c,den_c)\n",
    "a1.plot(xar,den_fit(xar,pp1[0],pp1[1],pp1[2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x125895790>]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1,a1=plt.subplots()\n",
    "# a1.plot(dddf['dep'],dddf['stress'])\n",
    "a1.plot(dddf['dep'],dddf['vSS_sm'])\n",
    "a1.plot(dddf['dep'],dddf['vSS_f'])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py38",
   "language": "python",
   "name": "py38"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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