docs/Examples/Mantle_Melting_Lee_Wieser/Complex_melt_changing_SCSS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculating sulfur and trace element evolution during mantle melting with changing SCSS and KDs\n",
    "- This notebook shows how to use the mantle melting model of Lee et al. (2012) adapted by Wieser et al. (2020) to model how S, Cu and other chalcophile or lithophile elements evolve during mantle melting\n",
    "- For more information on how the math works, we direct you towards the supporting information of Wieser et al (2020) - https://doi.org/10.1016/j.gca.2020.05.018 - Where the equations are typed out in detail\n",
    "- Here, we do the more complex example where silicate modes change and SCSS and KD change"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import PySulfSat as ss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 1 - Non fixed S content\n",
    "- The examples in the other workbook assume that S is fixed throughout the melting interval\n",
    "- However, we know the concentration of mantle melts changes with increasing F, so ideally, we'd calculate how much S those melts can hold\n",
    "- We can do this using an output from a melting model (here, Thermocalc). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load a generic dataframe\n",
    "Thermocalc_df=pd.read_excel('Thermocalc_Melting_Path.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We have replaced all missing liquid oxides and strings with zeros. \n"
     ]
    }
   ],
   "source": [
    "# Load a dataframe for calculating SCSS for these melt comps\n",
    "Thermo_df_ss=ss.import_data('Thermocalc_Melting_Path.xlsx', \n",
    "                    suffix='_Liq')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate instanteous melts\n",
    "- This dataframe contains aggregated melt compositions, we need instantenous melts for calculating the SCSS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>CaO_Liq</th>\n",
       "      <th>MgO_Liq</th>\n",
       "      <th>FeO_Liq</th>\n",
       "      <th>Na2O_Liq</th>\n",
       "      <th>Fe2O3_Liq</th>\n",
       "      <th>FeOt_Liq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48.30</td>\n",
       "      <td>15.09</td>\n",
       "      <td>10.22</td>\n",
       "      <td>12.50</td>\n",
       "      <td>9.40</td>\n",
       "      <td>3.88</td>\n",
       "      <td>0.54</td>\n",
       "      <td>9.885892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48.20</td>\n",
       "      <td>15.07</td>\n",
       "      <td>10.35</td>\n",
       "      <td>12.57</td>\n",
       "      <td>9.41</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.877896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>48.02</td>\n",
       "      <td>15.01</td>\n",
       "      <td>10.59</td>\n",
       "      <td>12.71</td>\n",
       "      <td>9.43</td>\n",
       "      <td>3.62</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.879900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47.84</td>\n",
       "      <td>14.98</td>\n",
       "      <td>10.86</td>\n",
       "      <td>12.88</td>\n",
       "      <td>9.45</td>\n",
       "      <td>3.47</td>\n",
       "      <td>0.48</td>\n",
       "      <td>9.881904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>47.66</td>\n",
       "      <td>14.90</td>\n",
       "      <td>11.08</td>\n",
       "      <td>13.00</td>\n",
       "      <td>9.47</td>\n",
       "      <td>3.31</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.883908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SiO2_Liq  Al2O3_Liq  CaO_Liq  MgO_Liq  FeO_Liq  Na2O_Liq  Fe2O3_Liq  \\\n",
       "0     48.30      15.09    10.22    12.50     9.40      3.88       0.54   \n",
       "1     48.20      15.07    10.35    12.57     9.41      3.80       0.52   \n",
       "2     48.02      15.01    10.59    12.71     9.43      3.62       0.50   \n",
       "3     47.84      14.98    10.86    12.88     9.45      3.47       0.48   \n",
       "4     47.66      14.90    11.08    13.00     9.47      3.31       0.46   \n",
       "\n",
       "   FeOt_Liq  \n",
       "0  9.885892  \n",
       "1  9.877896  \n",
       "2  9.879900  \n",
       "3  9.881904  \n",
       "4  9.883908  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Inst_Liq=ss.calculate_inst_melts_Thermocalc(Thermocalc_df=Thermocalc_df)\n",
    "Inst_Liq.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TiO$_2$ is very bad from Thermocalc, lets calculate it using our melting functions here\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "KDs_TiO2=pd.DataFrame(data={'element': 'TiO2',\n",
    "        'ol': 0.07, 'opx': 0.07, \n",
    "        'cpx': 0.07, 'sp': 0.07, \n",
    "        'gt': 0.07, 'sulf': 0.07}, index=[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extract the modes from Thermocalc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Modes3=pd.DataFrame(data={'ol': Thermocalc_df['ol'],\n",
    "                        'cpx': Thermocalc_df['cpx'],\n",
    "                        'opx': Thermocalc_df['opx'],\n",
    "                        'sp': Thermocalc_df['sp'],\n",
    "                        'gt': Thermocalc_df['g']*0})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_TiO2_Thermocalc=ss.Lee_Wieser_sulfide_melting(F=Thermocalc_df['liq'], \n",
    "                        Modes=Modes3,\n",
    "                        KDs=KDs_TiO2,\n",
    "                        S_Sulf=330000, elem_Per=0.13,\n",
    "                        S_Mantle=[200],\n",
    "                        S_Melt_SCSS_2_ppm=1000,\n",
    "                         Prop_S6=0)\n",
    "Inst_Liq['TiO2_Liq']=df_TiO2_Thermocalc['TiO2_Melt_Inst']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lets calculate the SCSS using ONeill (2021)\n",
    "- Wieser et al. (2020) show that the calculated sulfide composition isn't very reliable at mantle PT, so we use a fixed mantle S composition of Fe/(Fe+Ni+Cu)=0.634"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using inputted Fe_FeNiCu_Sulf ratio for calculations.\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SCSS2_ppm</th>\n",
       "      <th>LnS</th>\n",
       "      <th>Ln_a_FeO</th>\n",
       "      <th>Ln_a_FeS</th>\n",
       "      <th>DeltaG</th>\n",
       "      <th>LnCS2_calc</th>\n",
       "      <th>SiO2_Liq</th>\n",
       "      <th>Al2O3_Liq</th>\n",
       "      <th>CaO_Liq</th>\n",
       "      <th>MgO_Liq</th>\n",
       "      <th>FeO_Liq</th>\n",
       "      <th>Na2O_Liq</th>\n",
       "      <th>Fe2O3_Liq</th>\n",
       "      <th>FeOt_Liq</th>\n",
       "      <th>TiO2_Liq</th>\n",
       "      <th>P2O5_Liq</th>\n",
       "      <th>Fe_FeNiCu_Sulf_calc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1044.741097</td>\n",
       "      <td>6.951524</td>\n",
       "      <td>-2.187206</td>\n",
       "      <td>-0.532776</td>\n",
       "      <td>6.105676</td>\n",
       "      <td>-0.808582</td>\n",
       "      <td>48.30</td>\n",
       "      <td>15.09</td>\n",
       "      <td>10.22</td>\n",
       "      <td>12.50</td>\n",
       "      <td>9.40</td>\n",
       "      <td>3.88</td>\n",
       "      <td>0.54</td>\n",
       "      <td>9.885892</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1103.032862</td>\n",
       "      <td>7.005819</td>\n",
       "      <td>-2.246978</td>\n",
       "      <td>-0.531748</td>\n",
       "      <td>6.098787</td>\n",
       "      <td>-0.808198</td>\n",
       "      <td>48.20</td>\n",
       "      <td>15.07</td>\n",
       "      <td>10.35</td>\n",
       "      <td>12.57</td>\n",
       "      <td>9.41</td>\n",
       "      <td>3.80</td>\n",
       "      <td>0.52</td>\n",
       "      <td>9.877896</td>\n",
       "      <td>1.860432</td>\n",
       "      <td>0</td>\n",
       "      <td>0.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1116.546495</td>\n",
       "      <td>7.017996</td>\n",
       "      <td>-2.245749</td>\n",
       "      <td>-0.531987</td>\n",
       "      <td>6.091909</td>\n",
       "      <td>-0.787675</td>\n",
       "      <td>48.02</td>\n",
       "      <td>15.01</td>\n",
       "      <td>10.59</td>\n",
       "      <td>12.71</td>\n",
       "      <td>9.43</td>\n",
       "      <td>3.62</td>\n",
       "      <td>0.50</td>\n",
       "      <td>9.879900</td>\n",
       "      <td>1.613651</td>\n",
       "      <td>0</td>\n",
       "      <td>0.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1131.497103</td>\n",
       "      <td>7.031297</td>\n",
       "      <td>-2.244104</td>\n",
       "      <td>-0.532091</td>\n",
       "      <td>6.085093</td>\n",
       "      <td>-0.765808</td>\n",
       "      <td>47.84</td>\n",
       "      <td>14.98</td>\n",
       "      <td>10.86</td>\n",
       "      <td>12.88</td>\n",
       "      <td>9.45</td>\n",
       "      <td>3.47</td>\n",
       "      <td>0.48</td>\n",
       "      <td>9.881904</td>\n",
       "      <td>1.396916</td>\n",
       "      <td>0</td>\n",
       "      <td>0.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1146.297359</td>\n",
       "      <td>7.044292</td>\n",
       "      <td>-2.243501</td>\n",
       "      <td>-0.532328</td>\n",
       "      <td>6.078288</td>\n",
       "      <td>-0.745169</td>\n",
       "      <td>47.66</td>\n",
       "      <td>14.90</td>\n",
       "      <td>11.08</td>\n",
       "      <td>13.00</td>\n",
       "      <td>9.47</td>\n",
       "      <td>3.31</td>\n",
       "      <td>0.46</td>\n",
       "      <td>9.883908</td>\n",
       "      <td>1.206812</td>\n",
       "      <td>0</td>\n",
       "      <td>0.634</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     SCSS2_ppm       LnS  Ln_a_FeO  Ln_a_FeS    DeltaG  LnCS2_calc  SiO2_Liq  \\\n",
       "0  1044.741097  6.951524 -2.187206 -0.532776  6.105676   -0.808582     48.30   \n",
       "1  1103.032862  7.005819 -2.246978 -0.531748  6.098787   -0.808198     48.20   \n",
       "2  1116.546495  7.017996 -2.245749 -0.531987  6.091909   -0.787675     48.02   \n",
       "3  1131.497103  7.031297 -2.244104 -0.532091  6.085093   -0.765808     47.84   \n",
       "4  1146.297359  7.044292 -2.243501 -0.532328  6.078288   -0.745169     47.66   \n",
       "\n",
       "   Al2O3_Liq  CaO_Liq  MgO_Liq  FeO_Liq  Na2O_Liq  Fe2O3_Liq  FeOt_Liq  \\\n",
       "0      15.09    10.22    12.50     9.40      3.88       0.54  9.885892   \n",
       "1      15.07    10.35    12.57     9.41      3.80       0.52  9.877896   \n",
       "2      15.01    10.59    12.71     9.43      3.62       0.50  9.879900   \n",
       "3      14.98    10.86    12.88     9.45      3.47       0.48  9.881904   \n",
       "4      14.90    11.08    13.00     9.47      3.31       0.46  9.883908   \n",
       "\n",
       "   TiO2_Liq  P2O5_Liq  Fe_FeNiCu_Sulf_calc  \n",
       "0  0.000000         0                0.634  \n",
       "1  1.860432         0                0.634  \n",
       "2  1.613651         0                0.634  \n",
       "3  1.396916         0                0.634  \n",
       "4  1.206812         0                0.634  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SCSS_fixedSulf=ss.calculate_O2021_SCSS(df=Inst_Liq,\n",
    "T_K=Thermocalc_df['T']+273.15, P_kbar=Thermocalc_df['P'],\n",
    "Fe_FeNiCu_Sulf=0.634)\n",
    "SCSS_fixedSulf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now we are ready to model S-Cu\n",
    "- instead of inputting a single value for S_melt_SCSS_2_ppm, we input the pandas dataframe. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "KDs_Cu=pd.DataFrame(data={'element': 'Cu',\n",
    "        'ol': 0.048, 'opx': 0.034, \n",
    "        'cpx': 0.043, 'sp': 0.223, \n",
    "        'gt': 0, 'sulf': 800}, index=[0])\n",
    "\n",
    "Modes=pd.DataFrame(data={'ol': 0.6, 'opx': 0.2, \n",
    "       'cpx': 0.18, 'sp': 0.02, 'gt': 0}, index=[0])\n",
    "\n",
    "# Lets run the simple model for comparison\n",
    "S_Sulf = 38*(10**4)\n",
    "df_Cu_200S=ss.Lee_Wieser_sulfide_melting(F=Thermocalc_df['liq'], \n",
    "                        Modes=Modes,\n",
    "                        KDs=KDs_Cu,\n",
    "                        S_Sulf=S_Sulf, elem_Per=30,\n",
    "                        S_Mantle=[200],\n",
    "                        S_Melt_SCSS_2_ppm=1000,\n",
    "                         Prop_S6=0)\n",
    "# Now lets change S\n",
    "\n",
    "df_Cu_200S_Thermocalc=ss.Lee_Wieser_sulfide_melting(F=Thermocalc_df['liq'], \n",
    "                        Modes=Modes3,\n",
    "                        KDs=KDs_Cu,\n",
    "                        S_Sulf=S_Sulf, elem_Per=30,\n",
    "                        S_Mantle=[200],\n",
    "                        S_Melt_SCSS_2_ppm=SCSS_fixedSulf['SCSS2_ppm'],\n",
    "                         Prop_S6=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1500.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2, ax3)) = plt.subplots(1, 3, figsize=(12,4), sharex=True)\n",
    "# 100 ppm\n",
    "ax1.plot(df_Cu_200S['F'].iloc[1:], \n",
    "         df_Cu_200S['Cu_Melt_Agg'].iloc[1:],\n",
    "        '-',color='m', ms=10, label='Cu, S=200, fixed SCSS')\n",
    "# Lets add a cross to show the point at which sulfide is exhausted\n",
    "sulf_out_200=np.take(np.where(df_Cu_200S['S_Residue']==0), 0)\n",
    "ax1.plot(df_Cu_200S['F'].loc[sulf_out_200], \n",
    "         df_Cu_200S['Cu_Melt_Agg'].loc[sulf_out_200],\n",
    "        '*k', ms=10, label='Sulf out')\n",
    "\n",
    "\n",
    "ax1.plot(df_Cu_200S_Thermocalc['F'].iloc[1:], \n",
    "         df_Cu_200S_Thermocalc['Cu_Melt_Agg'].iloc[1:],\n",
    "        '-',color='c', ms=10, label='Cu, S=200, O2021 SCSS')\n",
    "# Lets add a cross to show the point at which sulfide is exhausted\n",
    "sulf_out_200=np.take(np.where(df_Cu_200S_Thermocalc['S_Residue']==0), 0)\n",
    "ax1.plot(df_Cu_200S_Thermocalc['F'].loc[sulf_out_200], \n",
    "         df_Cu_200S_Thermocalc['Cu_Melt_Agg'].loc[sulf_out_200],\n",
    "        '*k', ms=10, label='Sulf out')\n",
    "ax1.set_xlim([0, 0.5])\n",
    "ax1.set_xlabel('F')\n",
    "ax1.set_ylabel('Cu (ppm')\n",
    "\n",
    "# Plot S in melt\n",
    "ax2.plot(df_Cu_200S['F'].iloc[1:], \n",
    "         df_Cu_200S['S_Melt_Agg'].iloc[1:],\n",
    "        '-',color='m', ms=10, label='Cu, S=200, fixed SCSS')\n",
    "\n",
    "ax2.plot(df_Cu_200S_Thermocalc['F'].iloc[1:], \n",
    "         df_Cu_200S_Thermocalc['S_Melt_Agg'].iloc[1:],\n",
    "        '-',color='c', ms=10, label='Cu, S=200, O2021 SCSS')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "ax2.set_xlabel('F')\n",
    "ax2.set_ylabel('input S in melt (ppm)')\n",
    "\n",
    "# S in source\n",
    "ax3.plot(df_Cu_200S['F'].iloc[1:], \n",
    "         df_Cu_200S['S_Residue'].iloc[1:],\n",
    "        '-',color='m', ms=10, label='Cu, S=200, fixed SCSS')\n",
    "\n",
    "ax3.plot(df_Cu_200S_Thermocalc['F'].iloc[1:], \n",
    "         df_Cu_200S_Thermocalc['S_Residue'].iloc[1:],\n",
    "        '-',color='c', ms=10, label='Cu, S=200, O2021 SCSS')\n",
    "\n",
    "ax3.set_xlabel('F')\n",
    "ax3.set_ylabel('S in residue (ppm)')\n",
    "fig.tight_layout()\n",
    "ax1.legend()\n",
    "ax2.set_ylim([0, 1500])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 2 - Variable KD\n",
    "- We can be even 'cleverer' than this. So far, we have assumed the KDs stay constant, but that isn't the case. We know from Kiseeva et al. (2015) that the KD of Cu in the sulfide depends on the FeOt content of the melt, the sulfide composition and the temperature. \n",
    "- Following Ding and Dasgupta, lets calculate KD using 5 wt% Cu and 20 wt% Ni in the mantle sulfide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate KD using Kiseeva, using a fixed sulfide composition. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>S_Sulf</th>\n",
       "      <th>O_Sulf</th>\n",
       "      <th>Fe_Sulf</th>\n",
       "      <th>Ni_Sulf</th>\n",
       "      <th>Cu_Sulf</th>\n",
       "      <th>DNi</th>\n",
       "      <th>DCu</th>\n",
       "      <th>DAg</th>\n",
       "      <th>DPb</th>\n",
       "      <th>DZn</th>\n",
       "      <th>...</th>\n",
       "      <th>DIn</th>\n",
       "      <th>DTi</th>\n",
       "      <th>DGa</th>\n",
       "      <th>DSb</th>\n",
       "      <th>DCo</th>\n",
       "      <th>DV</th>\n",
       "      <th>DGe</th>\n",
       "      <th>DCr</th>\n",
       "      <th>DSe_B2015</th>\n",
       "      <th>DTe_B2015</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28.951975</td>\n",
       "      <td>2.040467</td>\n",
       "      <td>44.007558</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>468.888700</td>\n",
       "      <td>423.437545</td>\n",
       "      <td>387.173238</td>\n",
       "      <td>24.179410</td>\n",
       "      <td>2.000184</td>\n",
       "      <td>...</td>\n",
       "      <td>13.909661</td>\n",
       "      <td>0.009705</td>\n",
       "      <td>0.069138</td>\n",
       "      <td>31.618608</td>\n",
       "      <td>33.696187</td>\n",
       "      <td>0.213793</td>\n",
       "      <td>1.418172</td>\n",
       "      <td>1.365763</td>\n",
       "      <td>1194.743950</td>\n",
       "      <td>11164.888225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28.954668</td>\n",
       "      <td>2.038823</td>\n",
       "      <td>44.006509</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>467.544755</td>\n",
       "      <td>421.716344</td>\n",
       "      <td>385.632376</td>\n",
       "      <td>24.167264</td>\n",
       "      <td>2.003319</td>\n",
       "      <td>...</td>\n",
       "      <td>13.914218</td>\n",
       "      <td>0.009722</td>\n",
       "      <td>0.069545</td>\n",
       "      <td>31.714442</td>\n",
       "      <td>33.678820</td>\n",
       "      <td>0.214521</td>\n",
       "      <td>1.425514</td>\n",
       "      <td>1.369429</td>\n",
       "      <td>1195.816660</td>\n",
       "      <td>11175.374871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28.954331</td>\n",
       "      <td>2.039029</td>\n",
       "      <td>44.006641</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>465.786726</td>\n",
       "      <td>419.721374</td>\n",
       "      <td>383.854833</td>\n",
       "      <td>24.132319</td>\n",
       "      <td>2.004770</td>\n",
       "      <td>...</td>\n",
       "      <td>13.901989</td>\n",
       "      <td>0.009734</td>\n",
       "      <td>0.069894</td>\n",
       "      <td>31.771584</td>\n",
       "      <td>33.629184</td>\n",
       "      <td>0.215073</td>\n",
       "      <td>1.430966</td>\n",
       "      <td>1.371968</td>\n",
       "      <td>1195.682200</td>\n",
       "      <td>11174.060687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28.953993</td>\n",
       "      <td>2.039235</td>\n",
       "      <td>44.006772</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>464.050446</td>\n",
       "      <td>417.753198</td>\n",
       "      <td>382.100957</td>\n",
       "      <td>24.097713</td>\n",
       "      <td>2.006208</td>\n",
       "      <td>...</td>\n",
       "      <td>13.889863</td>\n",
       "      <td>0.009746</td>\n",
       "      <td>0.070241</td>\n",
       "      <td>31.828280</td>\n",
       "      <td>33.580030</td>\n",
       "      <td>0.215621</td>\n",
       "      <td>1.436388</td>\n",
       "      <td>1.374488</td>\n",
       "      <td>1195.547751</td>\n",
       "      <td>11172.746524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28.953656</td>\n",
       "      <td>2.039441</td>\n",
       "      <td>44.006904</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>462.323330</td>\n",
       "      <td>415.797345</td>\n",
       "      <td>380.357852</td>\n",
       "      <td>24.063208</td>\n",
       "      <td>2.007645</td>\n",
       "      <td>...</td>\n",
       "      <td>13.877764</td>\n",
       "      <td>0.009758</td>\n",
       "      <td>0.070590</td>\n",
       "      <td>31.884979</td>\n",
       "      <td>33.531021</td>\n",
       "      <td>0.216170</td>\n",
       "      <td>1.441821</td>\n",
       "      <td>1.377008</td>\n",
       "      <td>1195.413312</td>\n",
       "      <td>11171.432383</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      S_Sulf    O_Sulf    Fe_Sulf  Ni_Sulf  Cu_Sulf         DNi         DCu  \\\n",
       "0  28.951975  2.040467  44.007558        5       20  468.888700  423.437545   \n",
       "1  28.954668  2.038823  44.006509        5       20  467.544755  421.716344   \n",
       "2  28.954331  2.039029  44.006641        5       20  465.786726  419.721374   \n",
       "3  28.953993  2.039235  44.006772        5       20  464.050446  417.753198   \n",
       "4  28.953656  2.039441  44.006904        5       20  462.323330  415.797345   \n",
       "\n",
       "          DAg        DPb       DZn  ...        DIn       DTi       DGa  \\\n",
       "0  387.173238  24.179410  2.000184  ...  13.909661  0.009705  0.069138   \n",
       "1  385.632376  24.167264  2.003319  ...  13.914218  0.009722  0.069545   \n",
       "2  383.854833  24.132319  2.004770  ...  13.901989  0.009734  0.069894   \n",
       "3  382.100957  24.097713  2.006208  ...  13.889863  0.009746  0.070241   \n",
       "4  380.357852  24.063208  2.007645  ...  13.877764  0.009758  0.070590   \n",
       "\n",
       "         DSb        DCo        DV       DGe       DCr    DSe_B2015  \\\n",
       "0  31.618608  33.696187  0.213793  1.418172  1.365763  1194.743950   \n",
       "1  31.714442  33.678820  0.214521  1.425514  1.369429  1195.816660   \n",
       "2  31.771584  33.629184  0.215073  1.430966  1.371968  1195.682200   \n",
       "3  31.828280  33.580030  0.215621  1.436388  1.374488  1195.547751   \n",
       "4  31.884979  33.531021  0.216170  1.441821  1.377008  1195.413312   \n",
       "\n",
       "      DTe_B2015  \n",
       "0  11164.888225  \n",
       "1  11175.374871  \n",
       "2  11174.060687  \n",
       "3  11172.746524  \n",
       "4  11171.432383  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Sulf_KDs_Kis=ss.calculate_sulf_kds(Ni_Sulf=5, Cu_Sulf=20,\n",
    "        FeOt_Liq=Thermocalc_df['FeOt'],  \n",
    "        T_K=Thermocalc_df['T']+273.15, Fe3Fet_Liq=0)\n",
    "Sulf_KDs_Kis.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now lets make a dataframe of KDs\n",
    "- You could also set the silicate KDs to vary based on any other Kd models you have for them in the same way as above/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "KDs_Cu_Kis=pd.DataFrame(data={'element': 'Cu',\n",
    "        'ol': 0.048, 'opx': 0.034, \n",
    "        'cpx': 0.043, 'sp': 0.223, \n",
    "        'gt': 0, 'sulf': Sulf_KDs_Kis['DCu']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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q1Utzf2RkJJ4+fYoGDRqo7jM3N0fNmjVx6tQpAEBISAiSk5PTLOPs7Ax3d3fVMh9LTExEbGxsmpshqFChAgIDAxEREYHu3bvD1NQUx48fR926ddGqVSvcvn1bdkQi+gzWSFKX6OhoLFiwAG5ubqhTpw78/f0RHByMZ8+eqc423qpVK0yYMAFbt27F9evXER8fj/Pnz2PlypUYMmQI6tatCwcHB9mrQgZM0zUSkFcn7e3tsW7dOigUCqxcuRLBwcEa+blElDla03QHBAQgJCQEM2bM+OSxp0+fAgAcHR3T3O/o6Kh67OnTpzAzM4Odnd0Xl/nYjBkzYGtrq7rly5cvK1ZFZ5QoUQIrVqzAnTt30L9/fxgbG2PHjh1wc3PDyJEj0+xyRURysUaSOly+fBm9evWCi4sLfH19ce3aNVhZWaFHjx5Yvnw5/v33X8TFxamO3548eTLatGmDYsWK8WzjpFVk1EhAbp2sVasWBgwYAAAYOHAgkpKSNPaziShjtKLpfvDgAXx9fbF+/XpYWFh8cTmFQpHm30KIT+772NeWGT16NGJiYlS3Bw8eZDy8HsibNy8WLlyIS5cuoX79+khKSsKsWbNQvHhxrF+/HoKXcieSijWSstrJkyfRtGlTeHh4YPny5Xj79i3c3d2xaNEiPHr0CMuXL0ePHj1QsWJFZM+eXXZcoq+SVSMB+XVyypQpyJ07N65du4bff/9doz+biNJPK5rukJAQREVFwdPTEyYmJjAxMcGxY8ewYMECmJiYqL6Z/PibxqioKNVjTk5OSEpKwuvXr7+4zMfMzc1hY2OT5mbISpUqhb///hu7du1C4cKF8eTJE3Tq1Ak1a9bEpUuXZMcjMliskZQVlEol9u3bhxo1aqBGjRrYu3cvjIyM0K5dO5w4cQKXL19Gv379+HsmnSOrRgLy62SOHDlUW/cnT5781a3yRCSPVjTddevWRVhYGC5evKi6eXl5oWPHjrh48SIKFSoEJycnHDx4UPWcpKQkHDt2DFWrVgUAeHp6wtTUNM0yT548QXh4uGoZ+jaFQoFmzZohPDwc06ZNg6WlJU6cOIHy5cujf//+ePXqleyIRAaHNZK+R0xMDObPn48SJUqgSZMmOHnyJMzMzNCrVy9cv34dmzZtQvXq1b+5xY9IWxl6jezWrRu8vLwQFxeH0aNHy45DRJ+j7jO6ZdaHZ50UQgg/Pz9ha2srAgMDRVhYmOjQoYPIkyePiI2NVS3Tp08fkTdvXhEcHCxCQ0NFnTp1hIeHh0hJSUnXz9SlM3Rqyr1798QPP/ygOlutvb29WLJkSbrHlEjb6eq8Z42kr1EqleLSpUuiT58+Inv27KoabmNjI4YPHy4ePXokOyLpCF2d9zJqpBDyxuv06dOqeX7q1CmN/mwiQ5beOW8ip9XPuF9++QXv3r1Dv3798Pr1a1SqVAkHDhyAtbW1apnffvsNJiYmaNeuHd69e4e6deti9erVPNnLd8ifPz82b96MI0eOYNCgQQgPD0ffvn2xYMECTJgwAT/88APHl0gLsEYaruTkZFy7dg0XL17EhQsXVFv6PtxNtlSpUhgwYAA6deoEKysriWmJ5ND3Glm5cmV0794dK1euRJ8+fXD27FmYm5vLjkVE/0chBM+S9V5sbCxsbW0RExPDY9o+IyUlBUuWLMGECRMQHR0NAHBzc1M130ZGWnG0AlGGcN6nH8dKO1y8eBEnT55UNdnh4eGfPWuxqakpmjdvjgEDBqBmzZrcfZwyhfM+Y2SO1/Pnz+Hm5oYXL15g6NChmDt3rkZ/PpEhSu+cZ9P9Af5hSZ+YmBgsWLAA/v7+qua7WrVqWLx4McqUKSM3HFEGcd6nH8dKnpSUFAQGBmL+/PmfvWawtbU1ypYti7Jly6JcuXIoW7Ys3NzcuKWLvhvnfcbIHq9du3ahRYsWAIATJ06gevXqGs9AZEjYdGeC7EKpa6KjozF//nzMnj0bb968gbGxMXx9fTFp0qQ0u2sRaTPO+/TjWGneq1evsHz5cixcuFB1KSJTU1PUq1cPnp6eqkbb1dWVexuRWnDeZ4w2jFfPnj2xYsUKlClTBiEhITAx0ZmjSYl0DpvuTNCGQqmLHjx4gCFDhmDbtm0AABcXF8yfPx+tW7fm7oyk9Tjv049jpTk3btzA/PnzsXr1arx9+xYAkDt3bvTt2xd9+vRBnjx5JCckQ8F5nzHaMF4vXrxAsWLF8Pr1a8ybNw++vr5SchAZgvTOeX4tTt8tX7582Lp1K/bt24dChQrh0aNHaNu2LZo1a4a7d+/KjkdEpBOEEDh69ChatGiBEiVKYPHixXj79i08PDywcuVK3L9/H5MnT2bDTURflStXLtW1uydMmMBrdxNpATbdlGUaN26M8PBwjBs3Dqampti7dy/c3NwwZcoUxMfHy45HRKRVUlJScPnyZaxcuRL9+/dHmTJlULt2bezatQtCCDRt2hSHDx/GhQsX0K1bN1hYWMiOTEQ6omfPnvDy8kJsbCyGDRsmOw6RwePu5R/Qhl2C9MXVq1fRt29fHDt2DADg6OiICRMmoFevXjA1NZWcjuj/47xPP45V5qWmpuLatWs4f/48QkJCcP78eVy8eBHv3r1Ls5ylpSW6du0KX19fFC9eXFJaov+P8z5jtGm8zp07h8qVK0OpVGLz5s344YcfpOYh0kc8pjsTtKlQ6gMhBDZv3oyxY8fi9u3bAIAiRYpg6dKlqFu3ruR0RP/hvE8/jlXGnT59GrNmzcLBgwfx5s2bTx63traGp6cnvLy84Onpifr16yNnzpwSkhJ9Hud9xmjbeI0bNw7Tpk1Djhw5EB4eDhcXF9mRiPQKm+5M0LZCqS+SkpKwfPlyTJ48GVFRUQCAXr16Yfbs2bC1tZWcjgwd5336cazSRwiBoKAg+Pn54fjx46r7s2fPjvLly8PLy0t1K1KkCM86TlqN8z5jtG28kpOTUa1aNZw7dw7t2rXDpk2bZEci0is8kRppDTMzM/Tr1w+3bt1Cv379AAB//vknSpUqhb1790pOR0SUNVJSUrBx40aULVsW//vf/3D8+HGYmpqiR48eCA0NRUxMDI4fPw5/f3/89NNPKFasGBtuIlIrU1NTLFu2DEZGRti8eTOCg4NlRyIySPxrTxpjbW2NRYsW4ejRoyhSpAgePXqEpk2bomvXrnj9+rXseEREmZKYmIg///wTJUqUwE8//YTLly/DysoKw4YNQ2RkJJYvX45y5crB2NhYdlQiMkBly5bFgAEDAAD9+/dHYmKi5EREhodNN2lczZo1cenSJQwdOhQKhQJr1qxBqVKlsGfPHtnRiIjSLT4+Hv7+/ihUqBB69+6N27dvI2fOnJgyZQru3buHOXPm8PhJItIKU6ZMgaOjI27cuIG5c+fKjkNkcNh0kxTZsmXD3LlzcfLkSRQrVgxPnjxBs2bN4OPjg+joaNnxiIi+KCYmBtOmTUPBggUxbNgwPH78GC4uLpg3bx7u3buH8ePHw97eXnZMIiIVW1tbzJkzBwAwdepU3L17V24gIgPDppukqlq1Ki5evIjhw4fDyMgIa9euRenSpXnMERFpnVevXmHixIkoUKAAxo0bh5cvX6Jo0aJYvnw57ty5A19fX2TPnl12TCKiz+rYsSNq1qyJd+/eYfDgwbLjEBkUNt0knaWlJWbPno0TJ06gcOHCePjwIerXr4+BAwfyuCMikk6pVGLy5MkoUKAApkyZgpiYGLi5uWHDhg24evUqevToATMzM9kxiYi+SqFQYPHixTAxMcHOnTuxe/du2ZGIDAabbtIaVatWxaVLl1RnOF+4cCFq1qyJx48fS05GRIYsPDwckyZNQnx8PDw8PLBlyxaEhYWhQ4cOPDkaEekUNzc3DB06FAAwfPhwpKSkSE5EZBjYdJNWyZ49OxYtWoT9+/fDzs4O//77Lzw9PXH69GnZ0YjIQCUkJAAA8ubNiwsXLqBt27a81BcR6axx48YhV65cuHHjBlavXi07DpFBMJEdgOhzGjVqhHPnzqFly5YIDw9HrVq1MGjQIIwaNQo5c+aUHY+I9FRqaiqWL1+OyMhIJCUlITk5GY8ePQIAmJiYQKFQSE5IRPR9rK2tMXbsWAwZMgSjR49Gq1at+NmKSM0UQgghO4S2iI2Nha2tLWJiYmBjYyM7DuG/S/L4+PggMDAQwH+7RR06dAhOTk6Sk5G+4LxPP0MYq+PHj6NmzZqffaxcuXIIDQ3VcCIiuQxh3mclXRmvhIQElChRAvfu3UO7du2wadMm2ZGIdFJ65zy3dJNWs7KywpYtW7Bu3TqMHDkSERERqFmzJg4dOoS8efPKjkdEeiY2NhYA4OjoiK5du8LMzAympqYwNzdHs2bNJKcjIsoaFhYW+Ouvv+Dt7Y3Nmzfjl19+gaenp+xYRHqLTTdpPSMjI3Tp0gXVqlVDnTp1cOPGDXh7e+PQoUNwdXWVHY+I9FCBAgXg5+cnOwYRkdrUqFEDnTp1wrp16zB69GgcOHBAdiQivcUzwZDOKFy4sOqyYpGRkahevToiIiJkxyIiIiLSSVOmTIGpqSkOHjyIQ4cOyY5DpLfYdJNOyZ8/P44fP45SpUrh8ePH8Pb2RkhIiOxYRERERDrH1dUVffv2BQCMHDkSSqVSciIi/cSmm3SOs7Mzjh07Bi8vL7x8+RK1a9fG8ePHZcciIiIi0jljx46FlZUVQkJCsHXrVtlxiPQSm27SSTlz5sShQ4dQs2ZNxMXFoWHDhtizZ4/sWEREREQ6xcHBASNGjADwXwOenJwsORGR/mHTTTrLxsYG+/fvR9OmTZGQkICWLVti7dq1smMRERER6ZShQ4fCwcEBt27dwrJly2THIdI7bLpJp1laWiIwMBBdunRBamoqfHx84O/vLzsWERERkc6wsrLCxIkTAQCTJ09GXFyc5ERE+oVNN+k8U1NTrFq1CkOHDgUADBs2DKNHj4YQQnIyIiIiIt3Qq1cvFC1aFM+fP8fs2bNlxyHSK2y6SS8YGRlhzpw5mDFjBgDAz88P3bp143FJREREROlgamqq+hw1d+5cPHnyRHIiIv3Bppv0hkKhwKhRo7BixQoYGxtjzZo1aN68OeLj42VHIyIiItJ6rVu3RuXKlfH27VtMmjRJdhwivcGmm/RO9+7dsXPnTlhaWiIoKAi1a9fGs2fPZMciIiIi0moKhUK1a/ny5csREREhORGRfmDTTXqpSZMmOHLkCHLmzInz58+jSpUquHbtmuxYRKTl3rx5AwAwMTGRnISISI7q1aujZcuWUCqV+OWXX2THIdILbLpJb1WqVAmnTp1C4cKFERkZiSpVquDYsWOyYxGRFrt8+TIAoFSpUpKTEBHJ4+fnBxMTE+zduxeHDh2SHYdI57HpJr1WrFgxnD59GlWqVEF0dDTq16+PM2fOyI5FRFoqNDQUwH9bvHnJHCIyVMWLF0e/fv0A/HdVGKVSKTkRkW5j0016L3fu3Dh06BAaNmyI5ORkrF69WnYkItJSefLkAQBs2LABBQsWxK+//oro6Gi5oYiIJJgwYQJsbGxw6dIl7NmzR3YcIp3GppsMgqWlpeob26NHj8oNQ0Ra648//sDq1atRrFgxvHr1ChMmTECBAgUwbtw4vHr1SnY8IiKNyZkzJ/r27QsAmDFjBoQQkhMR6S423WQwvL29oVAocP36dTx+/Fh2HCLSQqampvDx8UFERAQCAgLg7u6O2NhYTJs2Da6urvj1118RGxsrOyYRkUYMHjwY5ubmOHPmDA4fPiw7DpHOYtNNBiNHjhwoV64cAG7tJqKvMzY2Rvv27XHp0iVs374dHh4eiI2NxYQJE1CoUCHMnj0bb9++lR2TiEitnJyc0KtXLwDA5MmTubWbKJPYdJNBqV27NgDgyJEjkpMQkS4wMjJCy5YtERoais2bN6NEiRJ4+fIlfvnlFxQqVAi///47EhMTZcckIlKbUaNGwczMDCdOnODnJ6JMYtNNBoVNNxFlhpGREX744QeEh4djzZo1cHV1xbNnzzBo0CAULVoUf/75J5KTk2XHJCLKci4uLujduzcAYOLEidzaTZQJbLrJoNSoUQPGxsa4ffs27t+/LzsOEekYY2NjdOnSBdevX8cff/yBvHnz4sGDB+jduzdKliyJdevWITU1VXZMIqIsNWrUKJibm+PkyZM8tpsoE9h0k0GxsbGBp6cnAG7tJqLMMzU1Re/evXHz5k3MmzcPDg4OuH37Njp37ozSpUtj69atvK4tEemND7d2T5o0iVu7iTKITTcZnDp16gBg001E38/CwgK+vr64c+cO/Pz8YGdnh6tXr+KHH36Al5cX9u7dyw+nRKQXRo4cya3dRJnEppsMzofHdfPDMBFlhezZs2PkyJGIjIzEpEmTYG1tjQsXLqBp06aoWrUqDh06xHpDRDqNW7uJMo9NNxmcatWqwdTUFPfv30dkZKTsOESkR2xtbTFx4kRERkZi5MiRsLS0xJkzZ1CvXj3UqVMH//zzj+yIRESZxmO7iTKHTTcZnOzZs6NixYoAuIs5EalHzpw54efnhzt37sDX1xdmZmY4evQoqlevjsaNG+P8+fOyIxIRZZizszN+/vlnADyTOVFGsOkmg8RLhxGRJjg5OWHevHm4desWfv75Z5iYmCAoKAgVKlRA69atERYWJjsiEVGGvD+2+59//sGhQ4dkxyHSCWy6ySDxuG4i0qR8+fJh6dKluHbtGrp06QIjIyNs374dHh4e+Omnn3Djxg3ZEYmI0uXDrd08tpsofdh0k0GqUqUKzMzM8PjxY9y8eVN2HCIyEIULF8aaNWsQHh6Odu3aQQiBjRs3ws3NDT169MDdu3dlRyQi+iZu7SbKGDbdZJAsLS1RpUoVAOCJQIhI40qWLIlNmzbhwoULaNasGVJTU7Fy5UoUK1YM/fv3x+PHj2VHJCL6Im7tJsoYNt1ksHhcNxHJVrZsWezatQtnzpxB/fr1kZycjMWLF6Nw4cIYNmwYoqKiZEckIvqskSNHwsLCglu7idKBTTcZrPdN99GjR/kNLRFJValSJRw4cEB1hvOEhAT4+/ujUKFCGDt2LF6/fi07IhFRGjyTOVH6sekmg1WpUiVYWFggKioKERERsuMQEaFmzZo4fvw4goKC4OXlhTdv3mD69OlwdXXF1KlTERcXJzsiEZHK+63dp06dQnBwsOw4RFqLTTcZLHNzc1SvXh0AdzEnIu2hUCjQsGFDnD17Fjt27EDp0qURExOD8ePHw9XVFXPmzMHbt29lxyQiQp48eXhsN1E6sOkmg8bjuolIWykUCrRo0QIXL15EQEAAihUrhpcvX2LEiBEoUqQIFi1ahMTERNkxicjAcWs30bex6SaD9uFx3UqlUnIaIqJPGRkZoX379rhy5QpWrVqFggUL4smTJxgwYACKFSuGFStWIDk5WXZMIjJQ3NpN9G1susmgeXl5IXv27Hj16hXCwsJkxyEi+iITExN07doV169fx5IlS+Ds7Iz79++jZ8+ecHNzw/r165Gamio7JhEZIG7tJvo6rWi6lyxZgjJlysDGxgY2NjaoUqUK9u/fr3q8a9euUCgUaW6VK1dO8xqJiYkYOHAgcuXKhezZs6N58+Z4+PChpleFdIypqSlq1KgBgNfrJu3FGkkfMjMzQ58+fXDr1i34+/sjd+7cuHXrFjp16oQyZcpg27Zt3NJEBoU1Ur48efKgT58+ALi1m+hztKLpzps3L/z8/HD+/HmcP38ederUQYsWLXDlyhXVMo0aNcKTJ09Ut3379qV5jcGDB2P79u0ICAjAyZMnER8fj6ZNm/Jbf/omHtdN2o41kj7H0tISQ4YMwZ07dzB9+nTkyJEDERERaNu2LTw9PbFv3z5+8CWDwBqpHX755RfV1u6DBw/KjkOkXYSWsrOzE8uXLxdCCOHj4yNatGjxxWWjo6OFqampCAgIUN336NEjYWRkJIKCgtL9M2NiYgQAERMTk+ncpHvOnj0rAAhbW1uRkpIiOw5pmK7Oe9ZI+tjr16/F+PHjhZWVlQAgAIgqVaqIQ4cOyY5GOkxX572MGimE7o5XVhk8eLCq9iiVStlxiNQuvXNeK7Z0fyg1NRUBAQF48+YNqlSporr/6NGjcHBwQLFixdCrVy9ERUWpHgsJCUFycjIaNGigus/Z2Rnu7u44derUF39WYmIiYmNj09zI8JQrVw42NjaIiYnBhQsXZMch+irWSPqSHDlyYMqUKYiMjMSIESNgaWmJ06dPo27duqhbt+5Xf9dE+kKTNRJgnfzY+63dp0+f5tZuog9oTdMdFhYGKysrmJubo0+fPti+fTvc3NwAAI0bN8b69etx+PBhzJ07F+fOnUOdOnVUl0p5+vQpzMzMYGdnl+Y1HR0d8fTp0y/+zBkzZsDW1lZ1y5cvn/pWkLSWiYkJvL29AXAXc9JerJGUXrly5cKsWbNw+/ZtDBw4EGZmZjh8+DCqVauGJk2aIDQ0VHZEoiwno0YCrJMfy5MnD/r27QuAx3YTfUhrmu7ixYvj4sWLOHPmDPr27QsfHx9EREQAANq3b48mTZrA3d0dzZo1w/79+3Hjxg3s3bv3q68phIBCofji46NHj0ZMTIzq9uDBgyxdJ9IdPK6btB1rJGVUnjx5sGDBAty8eRO9evWCsbEx9u3bB09PT7Rp0wbh4eGyIxJlGRk1EmCd/Bxu7Sb6lNY03WZmZihSpAi8vLwwY8YMeHh4YP78+Z9dNk+ePChQoABu3rwJAHByckJSUhJev36dZrmoqCg4Ojp+8Weam5urznT5/kaG6X3TfeLECV7vlrQSayRlVv78+bFs2TJcu3YNnTp1gkKhQGBgIMqUKYOOHTuq3idEukxGjQRYJz/HycmJW7uJPqI1TffHhBCq3X4+9vLlSzx48AB58uQBAHh6esLU1DTNt2lPnjxBeHg4qlatqpG8pNs8PDxgZ2eH+Ph4nD9/XnYcom9ijaSMKlKkCP766y+EhYWhbdu2EEJgw4YNKFmyJAYOHIi4uDjZEYmyDGukXB9u7f77779lxyGSTiua7jFjxuDEiRO4e/cuwsLCMHbsWBw9ehQdO3ZEfHw8hg8fjtOnT+Pu3bs4evQomjVrhly5cqFVq1YAAFtbW/To0QPDhg3DoUOHcOHCBXTq1AmlS5dGvXr1JK8d6QIjIyPV1u7g4GDJaYjSYo2krFSqVCls2bIFISEhaNKkCVJTU7Fw4UK4u7vzwzHpJNZI7ePk5IR+/foB+K8B56XXyOCp9yTq6dO9e3dRoEABYWZmJnLnzi3q1q0rDhw4IIQQ4u3bt6JBgwYid+7cwtTUVOTPn1/4+PiI+/fvp3mNd+/eiQEDBgh7e3thaWkpmjZt+sky32Lol3kwdEuXLhUARNWqVWVHIQ3ShXnPGknqFBwcLFxdXVWXGfPx8REvX76UHYu0hC7Me22pkULoxnhpysuXL4WdnZ0AIP7880/ZcYjUIr1zXiEED7R4LzY2Fra2toiJieExOQbo7t27cHV1hbGxMV68eIEcOXLIjkQawHmffhwr/fXmzRuMGzcO8+fPhxACjo6OWLRoEdq0aSM7GknGeZ8xHK+05s2bhyFDhsDR0RE3b96EtbW17EhEWSq9c14rdi8n0gYFCxZE8eLFkZqaikOHDsmOQ0SkMdmzZ8dvv/2GU6dOwc3NDc+ePUPbtm3Rpk0bPHnyRHY8ItJR/fr1Q9GiRfHs2TP4+fnJjkMkDZtuog80atQIAHhcIxEZpMqVKyM0NBTjx4+HiYkJAgMD4ebmhtWrV/MMxESUYWZmZpg9ezYAYO7cubh3757kRERysOkm+kDDhg0BAEFBQfyASUQGydzcHFOmTMH58+fh6emJ6OhodOvWDY0aNcLdu3dlxyMiHdO8eXPUqlULiYmJGDNmjOw4RFKw6Sb6QM2aNWFubo4HDx7g2rVrsuMQEUnj4eGBM2fOYObMmbCwsMCBAwfg7u6O33//HUqlUnY8ItIRCoUCc+fOhUKhwIYNG/Dvv//KjkSkcWy6iT6QLVs2eHt7A+Au5kREJiYm+OWXX3Dp0iXUqFEDb968waBBg+Dt7Y3r16/LjkdEOqJ8+fLw8fEBAAwdOpR7E5LBYdNN9JEPdzEnIiKgWLFiOHr0KBYvXgwrKyv8888/8PDwwIwZM5CcnCw7HhHpgGnTpiFbtmw4deoUtmzZIjsOkUax6Sb6yPum+9ixY3j37p3kNERE2sHIyAh9+/bFlStX0KhRI9XxmZUqVcKFCxdkxyMiLefs7IyRI0cCAEaOHImEhATJiYg0h0030UdKlSoFFxcXJCQk4MSJE7LjEBFplfz582Pfvn1Yu3Yt7O3tceHCBVSoUAFjxozhh2gi+qphw4bBxcUFd+/exYIFC2THIdIYNt1EH1EoFNzFnIjoKxQKBTp37oyIiAi0a9cOqampmDFjBsqWLYt//vlHdjwi0lLZs2fH9OnTAQBTp05FVFSU5EREmsGmm+gz3jfdPJkaEdGXOTo6YtOmTdi+fTucnJxw/fp11KhRA4MGDUJ8fLzseESkhTp16gRPT0/ExcVh4sSJsuMQaQSbbqLPqFevHoyMjBAREYEHDx7IjkNEpNVatmyJiIgIdO/eHUII/P7773B3d8eBAwdkRyMiLWNkZAR/f38AwLJly3DlyhXJiYjUj0030WfY29ujYsWKALi1m4goPezs7LBixQocOHAABQsWxL1799CwYUN069YNr1+/lh2PiLSIt7c3WrduDaVSieHDh8uOQ6R2bLqJvqBRo0YA2HQTEWVE/fr1ERYWhkGDBkGhUGD16tVwc3NDYGCg7GhEpEVmzpwJU1NTBAUF8Rw6pPfYdBN9wfvjuoODg5GSkiI5DRGR7rCyssL8+fNx8uRJlChRAk+fPkWbNm3www8/4OnTp7LjEZEWKFKkCAYOHAjgv7Oa87MW6TM23URfUKFCBdjZ2SE6Ohpnz56VHYeISOdUrVoVFy5cwNixY2FsbIytW7fCzc0Na9euhRBCdjwikmz8+PHImTMnIiIisHz5ctlxiNSGTTfRFxgbG6N+/foAuIs5EVFmWVhYYOrUqTh//jzKlSuH169fw8fHB//73/9w//592fGISKIcOXJg0qRJAIAJEyYgJiZGbiAiNWHTTfQVvHQYEVHWKFu2LM6ePQs/Pz+Ym5sjKCgIpUqVwqJFi6BUKmXHIyJJfv75ZxQvXhzPnz9XXcObSN+w6Sb6igYNGgAAzp49i5cvX0pOQ0Sk20xMTDBy5EhcunQJ1atXR3x8PAYMGICaNWvi+vXrsuMRkQSmpqaYM2cOAGDevHmIjIyUnIgo67HpJvqKvHnzwt3dHUIIBAcHy45DRKQXihcvjmPHjmHhwoWwsrLCyZMn4eHhgZkzZ/JkSkQGqEmTJqhbty6SkpIwatQo2XGIshybbqJv4C7mRERZz8jICP3790d4eDgaNmyIxMREjBo1CpUqVcKlS5dkxyMiDVIoFPD394dCocDmzZtx6tQp2ZGIshSbbqJv+LDp5tl2iYiyVoECBbB//36sXr0adnZ2CA0NhZeXF8aNG4eEhATZ8YhIQ8qUKYMePXoAAIYMGcJzPZBeYdNN9A01atSApaUlHj9+jPDwcNlxiIj0jkKhgI+PDyIiItC2bVukpKRg2rRpKFeuHE6fPi07HhFpyK+//ors2bPj7NmzCAgIkB2HKMuw6Sb6BgsLC9SqVQsAdzEnIlInJycnbNmyBdu2bYOjoyOuXbuGatWqYciQIXj79q3seESkZk5OThg9ejQAYNSoUZz3pDfYdBOlQ6NGjQAAe/bskZyEiEj/tW7dGhEREejatSuEEJg3bx7KlSuHM2fOyI5GRGo2dOhQ5M+fHw8ePOAlxEhvsOkmSoemTZsCAE6ePIlXr15JTkNEpP/s7e2xatUq7N+/H87Ozrhx4waqVauGMWPGIDExUXY8IlITS0tL/PbbbwCAWbNm4erVq5ITEX0/Nt1E6VCoUCG4u7sjNTUV+/fvlx2HiMhgNGrUCOHh4ejUqROUSiVmzJiBChUq4OLFi7KjEZGatGrVCk2aNEFycjL69evHE9mSzmPTTZROLVq0AADs2rVLchIiIsNiZ2eHv/76C4GBgcidOzfCwsJQoUIFTJ06ldf1JtJDCoUCv//+OywtLXH06FGsX79ediSi78KmmyidmjdvDgDYv38/kpKSJKchIjI8rVq1wpUrV9C6dWukpKRg/PjxqFq1Knc/JdJDrq6uGD9+PID/jvN+/fq15EREmcemmyidvLy84OTkhLi4OBw9elR2HCIig5Q7d25s3boV69atQ44cOXDu3DmUK1cO/v7+SE1NlR2PiLLQsGHDULJkSTx//hxjxoyRHYco09h0E6WTkZERmjVrBoC7mBMRyaRQKNCxY0eEh4ejUaNGSExMxLBhw1C7dm3cvn1bdjwiyiJmZmZYvHgxAOCPP/7Av//+KzkRUeaw6SbKgPe7mO/atYsn9SAikszFxQX79u3DsmXLYGVlhRMnTsDDwwNLly5ljSbSE7Vq1UKXLl0ghECfPn14HgfSSWy6iTKgbt26sLS0xIMHD3Dp0iXZcYiIDJ5CoUCvXr0QFhaGWrVq4c2bN+jbty8aNmyIBw8eyI5HRFlg9uzZsLOzw8WLF7Fo0SLZcYgyjE03UQZYWlqiQYMGALiLORGRNilYsCAOHTqEefPmwcLCAgcPHkTp0qWxdu1abvUm0nEODg7w8/MDAIwbNw6PHj2SnIgoY7676e7atSvmzJmD/fv38xtlMggf7mJOlB6sk0SaYWRkBF9fX1y8eBGVKlVCTEwMfHx80KpVKzx79kx2PPoC1khKj549e6Jy5cqIj4/HkCFDZMchypDvbrp79+4NKysr7N69G23atEGOHDlQpUqVrMhGpJWaNm0KhUKBkJAQPHz4UHYc0gGsk0SaVbx4cZw8eRLTp0+Hqakpdu7ciVKlSmHr1q2yo9FnsEZSehgZGWHJkiUwMjLCli1bEBQUJDsSUbqZfO8LVK1aFVWrVlX9+/jx4zh06ND3viyR1nJwcECVKlVw6tQp7N69G3379pUdibQc6ySR5pmYmGD06NFo0qQJunTpgkuXLuGHH35Ahw4dsHDhQtjb28uOSP+HNZLSq2zZsvD19cVvv/2G/v37Izw8HJaWlrJjEX3Td2/pjomJSfNvb29vXq6D9B53MaeMYJ0kkqdMmTI4e/Ysxo0bB2NjY2zcuBGlSpXC3r17ZUej/8MaSRkxefJkuLi44M6dO5g+fbrsOETpohDfeXYRDw8PvHnzBsWKFYO7uzssLCywY8cOXL58OasyakxsbCxsbW0RExMDGxsb2XFIi129ehVubm4wMzPDixcvYG1tLTsSZZIm5r2+1EnWSNJ1Z8+ehY+PD65duwYA6NGjB/z9/fl+/grWyIxhndSMbdu2oW3btjA1NUVYWBiKFy8uOxIZqPTO+e/e0n3p0iVcv34dc+bMgZeXF5ydnbn1j/ReiRIlUKRIESQlJeHAgQOy45CWY50k0g4VK1ZEaGgohg4dCoVCgRUrVqB06dI4fPiw7GgGjTWSMqp169Zo3LgxkpOT0a9fP16hgLReprd0BwQEIDU1FR07dszqTNLw20nKiGHDhsHf3x9dunTBmjVrZMehTFLnvNe3OskaSfrkxIkT6Nq1K+7cuQMAGDhwIPz8/JAtWzbJybQLa2TGsE5qzp07d1CqVCkkJCRg3bp1evU+It2h9i3dU6dORaNGjT65f8OGDVi3bl1mX5ZIZ7w/rnvPnj1ISUmRnIa0EeskkfaqUaMGLl26hD59+gAAfv/9d5QtWxanTp2SnMxwsEbS9yhUqBDGjRsHABg6dChev34tORHRl2W66VYoFMiZM+cn9zdt2hRz5879rlBEuqBatWqwt7fHq1ev+CGNPot1kki7WVlZYcmSJQgKCoKLiwtu3ryJGjVqYNSoUUhMTJQdT++xRtL3Gj58OIoXL46oqCiMHTtWdhyiL8p0021hYfHZb5RsbGygVCq/KxSRLjAxMUGTJk0A8Czm9Hmsk0S6oWHDhggPD0eXLl2gVCoxc+ZMeHp6IjQ0VHY0vcYaSd/L3NwcS5YsAQAsXboUZ8+elZyI6PMy3XT3798frVu3xvPnz9Pc/+rVq+8ORaQr3u9ivnPnTp7Egz7BOkmkO3LkyIE1a9Zg+/btcHBwwJUrV1CpUiVMmTIFycnJsuPpJdZIygq1a9dGp06dIIRAnz59eMgfaSWTzD6xa9euSElJQcWKFVGlShWUKVMGSqUSGzZswNChQ7MyI5HWatiwIczMzHDr1i1cv34dJUqUkB2JtAjrJJHuadmyJapVq4a+ffti27ZtmDhxInbt2oU1a9agVKlSsuPpFdZIyipz5szBnj17cOHCBSxevBiDBg2SHYkoje+6ZFjPnj0RHh6O+vXr4/nz50hISMCff/6J7t27Z1U+Iq1mbW2N2rVrA+Au5vR5rJNEuid37tzYsmULNmzYADs7O4SEhMDT0xNz5sxBamqq7Hh6hTWSsoKjoyNmzJgBABg3bhweP34sORFRWhm6ZJhSqcTq1asRGBiIu3fvQqFQwNXVFW3atEGXLl2gUCjUmVXteJkHyozFixejf//+qFq1Kv755x/ZcSiDsnre63OdZI0kQ/T48WP06tUL+/btA/DfWc+3bt0KBwcHyck0gzUyY1gn5VEqlahSpQrOnj2Ltm3bYsuWLbIjkQHI8kuGCSHQvHlz9OzZE48ePULp0qVRqlQp3Lt3D926dUOrVq2yJDiRrnl/XPfp06fx8OFDyWlIJtZJIv3j7OyMPXv2YPny5bC2tsaJEydQqVIlREREyI6mc1gjSZ2MjIywdOlSGBsbY+vWrWy6Sauku+levXo1jh8/jkOHDuHChQvYuHEjAgICcOnSJQQHB+Pw4cNYu3atOrMSaaW8efOievXqEEJg8+bNsuOQRKyTRPpJoVCgR48eOHv2LAoVKoS7d++iSpUqOHjwoOxoOoU1ktStXLlyGD16NACgb9++ePbsmeRERP9Jd9O9ceNGjBkzRnX86ofq1KmDUaNGYf369VkajkhX/PjjjwCAgIAAyUlIJtZJIv1WokQJ/Pvvv6hevTpiY2PRuHFjLF26VHYsncEaSZowfvx4eHh44OXLl/j55595dRnSCuluui9fvoxGjRp98fHGjRvj0qVLWRKKSNe0bdsWRkZGOHfuHG7fvi07DknCOkmk/3LlyoXg4GB06tQJqamp6Nu3L4YMGcITrKUDayRpgpmZGdasWQNTU1Ps3LkT69atkx2JKP1N96tXr+Do6PjFxx0dHfH69essCUWkaxwdHVGnTh0AwKZNmySnIVlYJ4kMg7m5OdauXYtff/0VADBv3jy0bNkS8fHxkpNpN9ZI0hQPDw9MnDgRADBw4ECec4ekS3fTnZqaChOTL1/W29jYmBejJ4PGXcyJdZLIcCgUCowbNw4BAQEwNzfHnj17UKNGDX64/wrWSNKkkSNHokKFCoiJiUHPnj25mzlJ9eXK9xEhBLp27Qpzc/PPPp6YmJhloYh0UatWrdC3b1+EhYXhypUrKFWqlOxIpGGsk0SGp3379ihQoABatGiBixcvomLFiti9ezc8PT1lR9M6rJGkSSYmJlizZg3KlSuHv//+G3/++Sd69+4tOxYZqHRv6fbx8YGDgwNsbW0/e3NwcECXLl3UmZVIq9nb26Nhw4YAuIu5oWKdJDJMlStXxr///otSpUrhyZMnqFGjBrZv3y47ltZhjSRNK1myJKZPnw4AGDZsGO7evSs3EBkuoQUWL14sSpcuLaytrYW1tbWoXLmy2Ldvn+pxpVIpJk6cKPLkySMsLCxEzZo1RXh4eJrXSEhIEAMGDBA5c+YU2bJlE82aNRMPHjzIUI6YmBgBQMTExGTJepHhWbdunQAgihYtKpRKpew4lA66MO9ZI4l0Q3R0tGjYsKEAIBQKhZg5c6bO/y3QhXmvLTVSCN0YL0OTkpIiqlevLgCIWrVqidTUVNmRSI+kd86ne0u3OuXNmxd+fn44f/48zp8/jzp16qBFixa4cuUKAGDWrFnw9/fHwoULce7cOTg5OaF+/fqIi4tTvcbgwYOxfft2BAQE4OTJk4iPj0fTpk15NlHSqObNm8PCwgI3b97EhQsXZMchPcEaSaQbbG1tsWfPHvTv3x9CCIwcORK9evVCUlKS7Gh6jTWSvsbY2BirV69GtmzZcPToUSxcuFB2JDJEmvkOIOPs7OzE8uXLhVKpFE5OTsLPz0/1WEJCgrC1tRVLly4VQvz3zbKpqakICAhQLfPo0SNhZGQkgoKC0v0z+e0kZYUffvhBABDDhw+XHYXSQVfnPWskkXZbsGCBMDIyEgBE7dq1xatXr2RHyhRdnfcyaqQQujtehmDRokUCgLC0tBTXr1+XHYf0hE5t6f5QamoqAgIC8ObNG1SpUgWRkZF4+vQpGjRooFrG3NwcNWvWxKlTpwAAISEhSE5OTrOMs7Mz3N3dVcsQacr7s5hv2rQJSqVSchrSN6yRRLph4MCB2LVrF6ysrHDkyBFUrlwZt27dkh1L77FG0pf06dMH9erVw7t379C1a1fuxUAapTVNd1hYGKysrGBubo4+ffpg+/btcHNzw9OnTwHgk+s6Ojo6qh57+vQpzMzMYGdn98VlPicxMRGxsbFpbkTfq3HjxrC2tsaDBw9w+vRp2XFIT7BGEumeJk2a4J9//kG+fPlw48YNVKpUCcePH5cdSy/JqJEA66QuMTIywooVK2BjY4PTp09j7ty5siORAdGaprt48eK4ePEizpw5g759+8LHxwcRERGqxxUKRZrlhRCf3Pexby0zY8aMNGfNzJcv3/etBBEAS0tLtGzZEgCv2U1ZhzWSSDeVKVMG//77LypUqIBXr16hXr16WLt2rexYekdGjQRYJ3VN/vz5MW/ePADA+PHjER4eLjcQGQytabrNzMxQpEgReHl5YcaMGfDw8MD8+fPh5OQEAJ980xgVFaX61tLJyQlJSUl4/fr1F5f5nNGjRyMmJkZ1e/DgQRavFRmq97uYb968GSkpKZLTkD5gjSTSXXny5MHRo0fRtm1bJCcnw8fHB+PGjeMhSFlIRo0EWCd1UdeuXdG0aVMkJSXBx8cHycnJsiORAdCapvtjQggkJibC1dUVTk5OOHjwoOqxpKQkHDt2DFWrVgUAeHp6wtTUNM0yT548QXh4uGqZzzE3N4eNjU2aG1FWqFevHuzt7REVFYVjx47JjkN6iDWSSLdky5YNmzZtwujRowEA06ZNw48//oh3795JTqafNFEjAdZJXaRQKLBs2TLY2dkhNDRUdR1vIrVS7/nc0mf06NHi+PHjIjIyUly+fFmMGTNGGBkZiQMHDgghhPDz8xO2trYiMDBQhIWFiQ4dOog8efKI2NhY1Wv06dNH5M2bVwQHB4vQ0FBRp04d4eHhIVJSUtKdg2ecpKzUq1cvAUD07NlTdhT6Cl2Y96yRRPpl1apVwtTUVAAQFStWFE+ePJEd6Yt0Yd5rS40UQjfGi/6zceNGAUCYmJiIkJAQ2XFIR6V3zmtF0929e3dRoEABYWZmJnLnzi3q1q2rKpRCCKFUKsXEiROFk5OTMDc3F97e3iIsLCzNa7x7904MGDBA2NvbC0tLS9G0aVNx//79DOVgoaSsdOjQIQFA2NnZicTERNlx6At0Yd6zRhLpn6NHjwp7e3sBQOTPn19cvnxZdqTP0oV5ry01UgjdGC/6j1KpFG3bthUARKlSpURCQoLsSKSD0jvnFUIIoemt69oqNjYWtra2iImJ4e5B9N1SU1Ph4uKCZ8+eYc+ePWjSpInsSPQZnPfpx7Eiylo3b95EkyZNcPPmTVhbW2PTpk1o3Lix7FhpcN5nDMdLtzx//hzu7u6IiorCqFGjMGPGDNmRSMekd85r7THdRLrO2NgY7dq1AwBs3LhRchoiItI2RYsWxZkzZ1CzZk3ExcWhadOmWLhwoexYRAYjd+7c+OOPPwAAs2bNwpkzZyQnIn3FpptIjTp06AAA2LlzJ96+fSs5DRERaRt7e3scOHAA3bp1g1KpxMCBA+Hr68szmxNpSMuWLdG5c2colUr4+Pjw8xqpBZtuIjWqXLkyChQogPj4eOzYsUN2HCIi0kJmZmZYsWKFatfWBQsWoHv37rzkJJGGzJ8/Hy4uLrhx4wZ8fX1lxyE9xKabSI0UCgV8fHwAACtXrpSchoiItJVCocCoUaOwbt06GBsbY82aNejQoQOSkpJkRyPSe3Z2dli7di0UCgWWL1+OgIAA2ZFIz7DpJlKzbt26QaFQ4NChQ4iMjJQdh4iItFjHjh2xZcsWmJmZYevWrWjVqhWv5U2kAXXq1MHYsWMBAL1798adO3ckJyJ9wqabSM0KFiyIunXrAgBWrVolOQ0REWm7Vq1aYdeuXbC0tMS+ffvQpEkTxMXFyY5FpPcmTpyIatWqIS4uDj/++CP3NKEsw6abSAO6d+8OAFi9ejVSU1MlpyEiIm3XsGFDBAUFwdraGkeOHEGDBg3w+vVr2bGI9JqJiQk2bNgAOzs7nDt3TrXlm+h7sekm0oBWrVrBzs4ODx48QHBwsOw4RESkA7y9vXHo0CHY2dnhzJkzqFOnDp4/fy47FpFey58/v+o8PHPmzMH+/fslJyJ9wKabSAMsLCzQsWNHAMCKFSskpyEiIl1RoUIFHD16FA4ODrh48SK8vb3x6NEj2bGI9FrLli0xYMAAAECXLl3w+PFjyYlI17HpJtKQHj16AAB27NiBFy9eSE5DRES6okyZMjhx4gTy5s2La9euwdvbG3fv3pUdi0ivzZ49Gx4eHnjx4gU6d+7MwwPpu7DpJtKQsmXLoly5ckhOTsb69etlxyEiIh1SrFgxnDhxAoUKFcKdO3dQvXp1XL9+XXYsIr1lYWGBTZs2IXv27Dh8+DD8/PxkRyIdxqabSIPeb+1esWIFhBCS0xARkS4pWLAgTpw4gZIlS+LRo0fw9vbG5cuXZcci0lvFixfHokWLAPx3ZvOTJ09KTkS6ik03kQb99NNPMDc3R1hYGEJCQmTHISIiHePs7Ixjx46hXLlyiIqKQq1atXD27FnZsYj0VpcuXdCpUyekpqbip59+wqtXr2RHIh3EpptIg+zs7NCmTRsAPKEaERFlTu7cuXH48GFUqVIFr1+/Rt26dXHs2DHZsYj0kkKhwOLFi1GkSBE8ePAAPXr04N6KlGFsuok07P01uzds2IC3b99KTkNERLooR44cOHDgAOrUqYP4+Hg0atQIQUFBsmMR6SVra2ts2rQJpqam2LFjBxYvXiw7EukYNt1EGla7dm24uroiNjYWgYGBsuMQEZGOsrKywt69e9GkSRMkJCSgefPm2L59u+xYRHqpfPnymD17NgBg6NChuHjxotxApFPYdBNpmJGREbp16waAu5gTEdH3sbCwQGBgIH744QckJyfjhx9+wLp162THItJLgwYNQtOmTZGUlIQff/wR8fHxsiORjmDTTSRB165doVAocPToUdy+fVt2HCIi0mFmZmbYsGEDfHx8kJqaii5dumDZsmWyYxHpHYVCgVWrVsHFxQXXr1/HwIEDZUciHcGmm0iCfPnyoUGDBgCAVatWSU5DRES6zsTEBCtXrkT//v0hhMDPP/8Mf39/2bGI9E6uXLmwfv16GBkZYfXq1dyzhNKFTTeRJO+v2b169WqkpqZKTkNERLrOyMgIv//+O0aOHAkAGDZsGKZMmcIzLRNlsZo1a2L8+PEAgL59++LmzZuSE5G2Y9NNJEnz5s2RM2dOPHr0CH///bfsOEREpAcUCgVmzJiBqVOnAgAmTpwIPz8/yamI9M+4cePg7e2N+Ph4/Pjjj3j37p3sSKTF2HQTSWJubo4uXboAAH7//XfJaYiISF8oFAqMHTsWs2bNAgDMnTuXe1QRZTETExOsX78eOXPmRGhoKHr37s29SuiL2HQTSTRgwAAYGRkhKCgIV65ckR2HiIj0yODBg2FjY4OXL18iNDRUdhwivZM3b15s3rwZxsbGWLduHebMmSM7EmkpNt1EEhUqVAitWrUCAMybN09uGCIi0iumpqaoV68eACAoKEhyGiL9VKdOHdVnuJEjR2Lfvn1yA5FWYtNNJNnQoUMBAH/99ReioqIkpyEiIn3SsGFDAGy6idSpf//+6NWrF4QQ6NChA65duyY7EmkZNt1EklWpUgWVKlVCYmIilixZIjsOERHpkfdN95kzZ/D69WvJaYj0k0KhwMKFC1G9enXExsaiRYsWnG+UBptuIskUCoVqa/eiRYuQkJAgOREREemLAgUKoGTJklAqlTh06JDsOER6y8zMDNu2bUO+fPlw48YNdOjQgScwJBU23URaoHXr1sifPz+eP3+OdevWyY5DRER6hLuYE2mGg4MDdu3aBUtLS/z9998YOXKk7EikJdh0E2kBExMT+Pr6AgD8/f15yQkiIsoyjRo1AgD8/fff/PtCpGZly5bFmjVrAPx3ub61a9dKTkTagE03kZbo0aMHrK2tcfXqVfz999+y4xARkZ7w9vaGhYUFHj58iIiICNlxiPTeDz/8gHHjxgEAevXqhTNnzkhORLKx6SbSEra2tujVqxeA/7Z2ExERZQVLS0vUrFkTAHcxJ9KUyZMno0WLFkhKSkKrVq3w6NEj2ZFIIjbdRFpk0KBBMDIywsGDBxEWFiY7DhER6YkPdzEnIvUzMjLCX3/9BXd3dzx9+hStWrXCu3fvZMciSdh0E2mRAgUKoG3btgCA3377TXIaIiLSF++b7mPHjuHNmzeS0xAZBmtra+zcuRP29vY4d+6c6lreZHjYdBNpmfeXD1u/fj2ePn0qOQ0REemD4sWLI3/+/EhKSsKxY8dkxyEyGIUKFcLWrVthbGyM9evXY/bs2bIjkQRsuom0TKVKlVC1alUkJSVh8eLFsuMQEZEeUCgUqq3dPK6bSLNq166N+fPnAwBGjRqFffv2SU5Emsamm0gLvd/avXjxYrx9+1ZyGiIi0gc8rptInn79+qF3794QQqBDhw64evWq7EikQWy6ibRQy5Yt4erqipcvX+Kvv/6SHYeIiPRAnTp1YGxsjBs3buDOnTuy4xAZFIVCgd9//x01atRAbGwsWrRogdevX8uORRrCpptICxkbG8PX1xcAMHv2bKSkpEhOREREus7W1hYVK1YEAJw+fVpyGiLDY2Zmhq1btyJ//vy4efMmWrVqhcTERNmxSAPYdBNpqZ49eyJXrly4ffs2NmzYIDsOERHpATs7OwBAUlKS5CREhsnBwQG7d++GtbU1jh07hq5du0KpVMqORWrGpptIS2XPnh0jRowAAPz666/c2k1ERESkB8qUKYPAwECYmJggICAAo0ePlh2J1IxNN5EW69evH3LlyoVbt25xazcRERGRnqhXrx5WrlwJAJg1axYWLlwoORGpE5tuIi1mZWWF4cOHAwCmTp3Krd1EREREeqJz586YOnUqAGDQoEHYsWOH3ECkNmy6ibRc//79kTNnTty8eRMbN26UHYeIiIiIssiYMWPSXEqMJznUT2y6ibSclZUVj+0mIiIi0kMKhQKLFi1CkyZNkJCQgGbNmuHmzZuyY1EWY9NNpAM+3NodEBAgOw4RERERZRETExNs2rQJXl5eePnyJRo3boyoqCjZsSgLsekm0gEfHtvNrd1ERERE+iV79uzYs2cPXF1dcfv2bTRt2hRv3ryRHYuyCJtuIh3xfmv3jRs3uLWbiIiISM84OjoiKCgIOXPmxLlz59ChQwduaNETbLqJdIS1tTWGDRsG4L+t3ampqZITEREREVFWKlasGHbt2gULCwvs3r0bgwYNghBCdiz6Tmy6iXTIgAEDYG9vz63dRERERHqqatWqWL9+PRQKBZYsWYKZM2fKjkTfiU03kQ75cGv3lClTuLWbiIiISA+1bt0a8+fPBwCMHj0a69evl5yIvgebbiIdw63dRERERPpv4MCBqo0t3bp1w+HDhyUnosxi002kY2xsbNIc280TbBARUXrx2FAi3TJr1iy0a9cOycnJaNWqFS5evCg7EmUCm24iHTRgwADkzJkT169fx4oVK2THISIiHZCcnIyQkBAAgJOTk+Q0RJQeRkZGWLNmDby9vREbG4sGDRrg2rVrsmNRBrHpJtJBNjY2mDBhAgBgwoQJiIuLk5yIiIi03Z49exAVFQVHR0fUq1dPdhwiSicLCwvs2rUL5cuXx/Pnz1GvXj1ERkbKjkUZwKabSEf16dMHRYsWRVRUFM9qSURE37R8+XIAQNeuXWFqaio5DRFlhK2tLf7++2+4ubnh0aNHqFevHh4/fiw7FqUTm24iHWVmZqZqtufOnYsHDx5ITkRERNrq4cOHCAoKAgB0795dchoiyoxcuXLh4MGDKFy4MO7cuYN69erh+fPnsmNROmhF0z1jxgxUqFAB1tbWcHBwQMuWLXH9+vU0y3Tt2hUKhSLNrXLlymmWSUxMxMCBA5ErVy5kz54dzZs3x8OHDzW5KkQa1bJlS9SoUQMJCQkYN26c7DikJqyRRPS9Vq9eDaVSCW9vbxQrVkx2nCzFGkmGxNnZGcHBwcibNy+uXr2Khg0bIjo6WnYs+gataLqPHTuG/v3748yZMzh48CBSUlLQoEEDvHnzJs1yjRo1wpMnT1S3ffv2pXl88ODB2L59OwICAnDy5EnEx8ejadOmvJYx6S2FQoG5c+cCANauXYvQ0FDJiUgdWCOJ6HsolUqsXLkSANCjRw/JabIeayQZmoIFCyI4OBgODg64cOECmjRp8sn7nbSM0EJRUVECgDh27JjqPh8fH9GiRYsvPic6OlqYmpqKgIAA1X2PHj0SRkZGIigoKF0/NyYmRgAQMTExmc5OJMNPP/0kAIhatWoJpVIpO45O0cV5zxpJRBkRHBwsAAgbGxvx5s2bDD1XF+e9rBophG6OF+muixcvihw5cggAom7duuLdu3eyIxmc9M55rdjS/bGYmBgAgL29fZr7jx49CgcHBxQrVgy9evVCVFSU6rGQkBAkJyejQYMGqvucnZ3h7u6OU6dOaSY4kSTTp0+Hubk5jh49ij179siOQ2rGGklEGfH+0pIdO3ZEtmzZJKdRP9ZIMhQeHh4ICgqClZUVDh06pLqeN2kfrWu6hRAYOnQoqlevDnd3d9X9jRs3xvr163H48GHMnTsX586dQ506dZCYmAgAePr0KczMzGBnZ5fm9RwdHfH06dPP/qzExETExsamuRHpogIFCmDw4MEAgBEjRrDg6jHWSCLKiFevXiEwMBCAfu5a/jFN1kiAdZLkq1SpEnbv3g0LCwvs3r0bXbp04SERWkjrmu4BAwbg8uXL2LhxY5r727dvjyZNmsDd3R3NmjXD/v37cePGDezdu/erryeEgEKh+OxjM2bMgK2treqWL1++LFsPIk0bPXo0cuXKhevXr+PPP/+UHYfUhDWSiDJi/fr1SExMRNmyZVG+fHnZcdROkzUSYJ0k7VCrVi1s27YNpqamCAgIwM8//wylUik7Fn1Aq5rugQMHYteuXThy5Ajy5s371WXz5MmDAgUK4ObNmwAAJycnJCUl4fXr12mWi4qKgqOj42dfY/To0YiJiVHdeMkl0mW2traYNGkSAGDixImq3etIf7BGElFGCCFU1+bu0aPHV5tHfaDpGgmwTpL2+N///ocNGzbAyMgIK1aswNChQyGEkB2L/o9WNN1CCAwYMACBgYE4fPgwXF1dv/mcly9f4sGDB8iTJw8AwNPTE6ampjh48KBqmSdPniA8PBxVq1b97GuYm5vDxsYmzY1Il/Xu3RvFixfHixcv4OfnJzsOZRHWSCLKjJCQEFy+fBnm5ubo2LGj7DhqI6tGAqyTpF3atm2rulLB/PnzMWHCBMmJSEWdZ3NLr759+wpbW1tx9OhR8eTJE9Xt7du3Qggh4uLixLBhw8SpU6dEZGSkOHLkiKhSpYpwcXERsbGxqtfp06ePyJs3rwgODhahoaGiTp06wsPDQ6SkpKQrB884Sfpg586dAoAwNzcXkZGRsuNoPV2Y96yRRJQZPj4+AoDo2LFjpl9DF+a9ttRIIXRjvEj/LVy4UAAQAMT06dNlx9Fr6Z3zWtF0v39TfHxbtWqVEEKIt2/figYNGojcuXMLU1NTkT9/fuHj4yPu37+f5nXevXsnBgwYIOzt7YWlpaVo2rTpJ8t8DQsl6QOlUilq164tAIhmzZrxEmLfoAvznjWSiDJqwYIFqlpx/PjxTL+OLsx7bamRQujGeJFhmDFjhmouTJkyRXYcvZXeOa8Qgjv7vxcbGwtbW1vExMRw9yDSaREREfDw8EBKSgq2b9+Oli1byo6ktTjv049jRaQbAgIC8NNPP0EIgV9//RXjxo3L9Gtx3mcMx4u0ybRp01Tzf/z48Zg8ebLen9tB09I757XimG4iylpubm4YMWIEgP9OLBMXFyc5ERERacLBgwfRpUsX1XHOY8eOlR2JiCQZO3YsZs2aBQD49ddfMWbMGJ5cTRI23UR6aty4cXB1dcXDhw8xceJE2XGIiEjNzp07h1atWiE5ORnt27fH/PnzuVWLyMCNGDEC8+bNAwD4+flh+PDhbLwlYNNNpKeyZcuGxYsXA/jvDJYXLlyQnIiIiNTl+vXr+N///oc3b96gXr16WLNmDYyM+DGPiABfX18sWrQIAODv749Bgwax8dYwVmMiPdaoUSO0a9cOSqUSP//8M1JTU2VHIiKiLPb48WM0bNgQL168gJeXFwIDA2Fubi47FhFpkX79+uHPP/+EQqHAwoUL0bdvXyiVStmxDAabbiI999tvv8HGxgbnzp3DH3/8ITsOERFlodevX6Nhw4a4d+8eihYtin379sHa2lp2LCLSQj179sSqVaugUCjwxx9/oGfPntwgoyFsuon0nLOzM6ZNmwYAGD16NJ48eSI5ERERZYV3796hefPmCA8PR548eXDgwAHkzp1bdiwi0mI+Pj5Yt24djIyMsGrVKnTt2hUpKSmyY+k9Nt1EBqBv377w8vJCbGwshgwZIjsOERF9p5SUFLRv3x4nT56Era0tgoKCULBgQdmxiEgH/PTTTwgICICxsTHWrVuHzp07Izk5WXYsvcamm8gAGBsb448//oCRkRE2bdqEv//+W3YkIiLKJCEEfv75Z+zevRsWFhbYvXs3ypQpIzsWEemQH374AVu2bIGpqSkCAgLQoUMHJCUlyY6lt9h0ExmI8uXLY9CgQQD+O5nGu3fvJCciIqLMGDNmDFauXKn6IrVGjRqyIxGRDmrVqhW2bdsGMzMzbNu2De3atUNiYqLsWHqJTTeRAZkyZQpcXFxw584dTJkyRXYcIiLKIH9/f/j5+QEAli1bhubNm0tORES6rFmzZti5cyfMzc2xc+dOtGzZEm/fvpUdS++w6SYyINbW1li4cCEAYNasWTh37pzkRERElF4rVqzAsGHDAADTp09Hjx49JCciIn3QqFEj7NmzB9myZUNQUBAaNGiA6Oho2bH0CptuIgPTsmVLdOjQAUqlEj4+PkhISJAdiYiIvmHLli3o3bs3AGDEiBEYNWqU5EREpE/q1auHgwcPIkeOHPjnn39Qq1YtPHv2THYsvcGmm8gA/f7773B0dMTVq1cxceJE2XGIiOgrgoKC0LFjRyiVSvTq1QszZ86EQqGQHYuI9EzVqlVx7NgxODo64tKlS6hevTru3r0rO5ZeYNNNZIBy5syJP/74AwAwZ84cnDlzRnIiIiL6nJMnT6J169ZITk5G+/btsWTJEjbcRKQ2ZcqUwcmTJ1GwYEHcunUL1atXR0REhOxYOo9NN5GBatGiBTp37gylUomuXbvybOZERFomNDQUTZo0wbt37/C///0Pa9euhbGxsexYRKTnihQpgpMnT8LNzQ2PHj2Ct7c3zwP0ndh0Exmw+fPnI0+ePLh+/TrGjx8vOw4REf2fa9euoWHDhoiNjYW3tze2bNkCMzMz2bGIyEC4uLjg+PHjqFChAl6+fIk6dergyJEjsmPpLDbdRAbMzs4Of/75J4D/LkPzzz//SE5ERET37t1D/fr18eLFC3h6emL37t3Ili2b7FhEZGBy5syJQ4cOoU6dOoiPj0fjxo2xc+dO2bF0EptuIgPXpEkTdOvWDUIIdO3alddmJCKS6NmzZ6hXrx4ePnyIkiVLIigoCDY2NrJjEZGBsra2xt69e9GyZUskJiaiTZs2WLt2rexYOodNNxHB398fefPmxa1btzBmzBjZcYiIDNLr16/RoEED3Lp1CwULFsTBgweRK1cu2bGIyMBZWFhgy5Yt6Nq1K1JTU+Hj44P58+fLjqVT2HQTEXLkyIHly5cDABYsWIDjx49LTkREZFji4+PRpEkTXL58GU5OTjh48CBcXFxkxyIiAgCYmJhgxYoVGDx4MABg8ODBmDRpEoQQcoPpCDbdRAQAaNiwIXr27AkhBHx8fBAdHS07EhGR3nv16hWmTp2KQoUK4fTp07Czs8OBAwdQpEgR2dGIiNIwMjKCv78/fv31VwDA5MmT0bt3byQnJ0tOpv3YdBORyty5c+Hq6oq7d++qGnAiIsp69+/fx+DBg5E/f36MHz8ez58/R8GCBREUFITSpUvLjkdE9FkKhQLjxo3DwoULYWRkhOXLl+N///sfN9Z8A5tuIlKxsbHBpk2bYGpqim3btmHx4sWyIxER6ZXLly+jc+fOKFSoEObPn483b96gbNmy2LBhA27evImKFSvKjkhE9E39+/fHjh07kD17dgQHB6NatWqIjIyUHUtrsekmojQqVKiAWbNmAQCGDh2K0NBQyYmIiHSbEAJHjhxB48aN4eHhgXXr1iE1NRV169bFgQMHEBoaig4dOsDExER2VCKidGvWrBlOnDgBZ2dnREREoFKlSjhz5ozsWFqJTTcRfcLX1xfNmzdHUlIS2rVrh5iYGNmRiIh0TmJiIjZu3IiKFSuiTp06CAoKgpGREdq3b4/z588jODgY9evXh0KhkB2ViChTypUrh7Nnz6Js2bJ4/vw5ateujc2bN8uOpXXYdBPRJxQKBVatWoV8+fLh9u3baN26NRITE2XHIiLSCffu3cOYMWOQP39+/PTTTzh//jwsLS3Rv39/3Lx5EwEBAfD09JQdk4goS7i4uODEiRNo2rQpEhIS0L59e0yePJnnBvoAm24i+ix7e3vs2LEDVlZWOHz4MLp06QKlUik7FhGRVlIqldi/fz+aNWsGV1dXzJgxA1FRUXB2dsbkyZNx7949LFy4EIUKFZIdlYgoy1lZWWHHjh0YMmQIAGDSpEn48ccf8fbtW8nJtAObbiL6ovLlyyMwMBCmpqbYvHkzhgwZwm8tiYg+8OLFC8yaNQtFihTB//73P+zZswdCCNSrVw/btm3D3bt3MWHCBOTOnVt2VCIitTI2Noa/vz+WL1+u+uzo7e2NR48eyY4mHZtuIvqq+vXrY82aNQCABQsWYObMmZITERHJlZiYiEOHDqFz585wcXHByJEjERkZiRw5cmDIkCG4fv06Dh48iNatW8PU1FR2XCIijerRoweCg4ORK1cuhISEoEKFCjh37pzsWFLxNJlE9E0dOnTA06dPMXToUIwePRpmZmYYOnSo7FhERBohhMDVq1dx4MABHDhwAMeOHUuzy6SXlxf69euH9u3bI1u2bBKTEhFpB29vb5w9exbNmjXDlStXUL16dSxcuBA9e/Y0yJNHsukmonQZMmQIXr58iWnTpmHYsGFITEzE6NGjZcciIlKLFy9eIDg4WNVof7x7pKOjI5o2bYqff/4ZFSpUkJSSiEh7ubq64tSpU+jSpQt27tyJ3r1749SpU1i0aJHBfUHJppuI0u3XX3+FmZkZJk6ciDFjxiAxMRETJ040yG8siUi/JCYm4tSpUzhw4AAOHjyI0NDQNOewsLCwgLe3Nxo0aIAGDRrA3d2dtY+I6BtsbGwQGBiI2bNnY8yYMVi9ejUuXLiArVu3okiRIrLjaQybbiJKN4VCgQkTJsDMzAyjR4/G5MmTkZiYiOnTp/PDJxHpFCEErl27ptqSffTo0U/OslumTBlVk129enVYWlpKSktEpLuMjIwwcuRIVKxYET/++CMuXboET09PrF27Fi1atJAdTyPYdBNRho0aNQrm5uYYOnQo/Pz8kJiYiLlz57LxJiKt9uEu4wcPHsTDhw/TPO7o6KhqsuvVqwcnJydJSYmI9E/t2rURGhqKdu3a4dSpU2jZsiVGjhyJqVOnwsREv9tS/V47IlKbIUOGwNzcHP3798dvv/2GpKQkLFiwAEZGvCgCEWmHxMREnD59WrU1++Ndxs3NzdPsMl66dGl+eUhEpEYuLi44evQofvnlF8ybNw8zZ87Ev//+i4CAADg6OsqOpzZsuoko0/r16wczMzP07t0bixYtQmJiIpYuXQpjY2PZ0YjIACUlJeHKlSs4fvz4V3cZr1+/Pho0aIAaNWpwl3EiIg0zNTXFb7/9hipVqqBHjx44evQoypUrh82bN6N69eqy46kFm24i+i49e/aEmZkZunXrhuXLl+P58+dYt24drKysZEcjIj2WmJiI8PBwhIaGIiQkBCEhIbh8+TKSkpLSLOfg4JBml/E8efJISkxERB9q164dSpcujTZt2uDq1auoVauW6mS9+rYBh003EX23Ll26wMLCQnVJiGrVqmHXrl0oUKCA7GhEpAcSEhIQFhaWpsEOCwtDcnLyJ8va2tqiYsWKqq3ZpUuX5mEvRERaqmTJkjh79ix+/vlnbNiwARMmTMCBAwewbt06vfocyaabiLJEu3btkD9/frRs2RKXL19GhQoVsH37dlSrVk12NCLSIe/evcPly5cREhKiarLDw8ORkpLyybJ2dnYoX748PD09VbdChQrxuGwiIh1iZWWFdevWoVGjRujfvz9OnjwJDw8PLF26FD/++KPseFmCTTcRZZnKlSvj7NmzaNGiBS5evIg6depg2bJl8PHxkR2NiLTQ27dvcenSJdXW69DQUFy5cgWpqamfLJszZ054enqmabILFizIBpuISA8oFAp07twZ1apVQ8eOHXHmzBl06NAB+/fvx8KFC2FtbS074ndh001EWSp//vw4efIkOnfujO3bt6Nr1664cuUKZsyYoXfH5xBR+r158wYXL15M02BHRERAqVR+smzu3Lk/abDz58/PBpuISM8VKlQIx48fx6+//opp06Zh7dq1+Oeff7B+/XpUqlRJdrxMU4gPr51h4GJjY2Fra4uYmBjY2NjIjkOk05RKJSZOnIipU6cCAJo2bYr169dr3dzivE8/jhWlV3R0NMLCwtI02NeuXftsg+3o6PhJg503b1422FqC8z5jOF5EWefEiRPo1KkT7t+/D2NjY0yePBmjRo3Sqo046Z3zbLo/wEJJlPU2btyIbt26ITExEcWKFUNAQADKlSsnO5YK5336cazoY4mJibh69SrCwsIQFhaG8PBwhIWF4eHDh59dPk+ePJ802M7OzmywtRjnfcZwvIiyVnR0NPr27YuAgAAAQNWqVbFmzRoUKVJEcrL/pHfOc/dyIlKrDh06oHDhwmjdujVu3LiBypUrY/bs2Rg4cCA/aBPpCKVSiTt37qia6ve3mzdvfvb4awDIly8fypUrl6bB5uW6iIgoI3LkyIENGzagcePGGDBgAE6dOgUPDw/MmjULffv21ZmrU3BL9wf47SSR+rx8+RLdunXD7t27AQDNmjXDqlWrkDNnTqm5OO/Tj2NlGJ49e/bJlusrV67g7du3n10+R44cKF26NEqXLg13d3fVf3PkyKHZ4KQWnPcZw/EiUp979+6hW7duOHLkCACgXr16WLlyJfLlyyctE3cvzwQWSiL1EkJg4cKFGD58OJKSkuDi4oINGzbA29tbWibO+/TjWOmX+Ph4XLlyJc2W6/DwcDx//vyzy5ubm6NkyZKqBvt9c+3i4sK9VvQY533GcLyI1EupVGLRokUYOXIk3r17BxsbGyxYsABdunSR8reITXcmsFASacaFCxfw448/4saNGzAyMsKECRMwbtw4KSfG4LxPP46VbkpOTsaNGzc+2TU8MjLys8srFAoULlw4zZbr0qVLo0iRIjAx4VFphobzPmM4XkSacePGDfj4+ODMmTMAgObNm2PZsmVwdHTUaA423ZnAQkmkOfHx8Rg4cCBWr14NAKhWrRr+/PNPlCxZUqM5OO/Tj2OlnYQQePXqFe7evYvIyEhERkaq/v/u3bu4ffs2kpKSPvtcR0fHT7Zcu7m5IXv27BpeC9JWnPcZw/Ei0pyUlBTMmTMHEyZMQHJyMnLmzInffvsNnTp10thWbzbdmcBCSaR569evR58+fRAfHw9TU1P88ssvGDt2LCwtLTXy8znv049jJU9sbGyaZvrjxjouLu6rz7eysoK7u3uaLdfu7u7InTu3htaAdBXnfcZwvIg07/Lly+jSpQsuXboEAKhTpw6WLFmCYsWKqf1ns+nOBBZKIjnu3buHAQMGYM+ePQCAwoULY/HixWjQoIHafzbnffpxrNTn7du3aZrojxvs169ff/M1nJycULBgQbi6uqr+6+rqisKFC6NAgQI6c4ZX0i6c9xnD8SKSIykpCf7+/pg8eTISEhJgZmaGMWPGYNSoUTA3N1fbz2XTnQkslETyCCGwfft2DBo0CI8ePQLw3+XG/P394eTkpLafy3mffhyrzEtMTMT9+/c/u5U6MjISUVFR33yNnDlzpmmoP2ysCxQooLG9Q8iwcN5nDMeLSK47d+6gf//+CAoKAgAUK1YMS5cuRe3atdXy89h0ZwILJZF8cXFxGD9+PH7//XcolUrY2trCz88PvXr1UsuJ1jjv049j9WXx8fF48OABHj58iAcPHnyyG/jjx4/xrT+3NjY2qib648a6YMGCsLa21tDaEP1/nPcZw/Eikk8IgS1btsDX1xdPnz4FAHTu3Blz5syBg4NDlv4sNt2ZwEJJpD1CQkLw888/IyQkBADg7u6OmTNnonHjxll6cgzO+/Qz1LGKjY1VNdMPHz5U3T78d0xMzDdfJ1u2bJ/dSv3+/3PkyMFLb5HWMdR5n1kcLyLtERMTgzFjxmDJkiUQQsDW1haTJ09Gv379YGpqmiU/g013JrBQEmmX1NRULFq0CJMmTVId01q7dm3MmjULXl5eWfIzOO/TT9/GSgiBmJiYLzbS7//9rZOUvWdjY4N8+fIhb968KFiw4CeNde7cudlUk87Rt3mvbhwvIu3z77//om/fvrhw4QIAoFSpUliwYAHq1Knz3a/NpjsTWCiJtNPr168xY8YMLFiwAImJiQD+O9572rRpcHV1/a7X5rxPP10aKyEEoqOjv7mFOj4+Pl2vlyNHDlVD/f724b9dXFy0fkyIMkOX5r024HgRaafU1FSsWLECY8aMwcuXLwEAbdu2xdy5c5E/f/5Mvy6b7kxgoSTSbvfu3cO4ceOwbt06AICZmRn69++P0aNHZ/rSR5z36acNYyWEQHx8PKKiovDs2TNERUXh6dOnn22q3759m67XtLe3/6SJ/vDfLi4usLKyUvOaEWknbZj3uoTjRaTdXr16hQkTJmDJkiVQKpWwtLTEqFGjMHz4cGTLli3Dr5fuOS+0wPTp04WXl5ewsrISuXPnFi1atBDXrl1Ls4xSqRQTJ04UefLkERYWFqJmzZoiPDw8zTIJCQliwIABImfOnCJbtmyiWbNm4sGDB+nOERMTIwCImJiYLFkvIlKPkJAQUbduXQFAABCWlpbC19dX3L9/P8OvpQvzXt9rZHJysnjy5Im4dOmSOHjwoFi3bp3w9/cXo0aNEt26dRNNmjQRFSpUEPnz5xcWFhaq33t6brly5RJly5YVzZo1E3379hXTpk0Ta9asEYcPHxY3btwQb968ydJ1IdI3rJHpr5FC6MZ4EZEQly5dEjVr1lR9XnB2dhZ//vmnSE5OztDrpHfOa8WW7kaNGuHHH39EhQoVkJKSgrFjxyIsLAwRERHInj07AGDmzJmYNm0aVq9ejWLFimHq1Kk4fvw4rl+/rjqja9++fbF7926sXr0aOXPmxLBhw/Dq1SuEhISk66zH/HaSSHcIIXDgwAGMHTtWdbI1U1NTdO7cGSNHjkSxYsXS9Tq6MO91sUampKTg/v37qq3RH26Z/vj/X758+c0ze3/MysoKDg4OcHBwgKOjY5ot1O+3Uru4uMDCwiJDr0tEabFGpr9GAroxXkT0HyEENm/ejJEjR+LevXsAADc3N8yYMQPNmjVL13lYdGpL98eioqIEAHHs2DEhxH/fTjo5OQk/Pz/VMgkJCcLW1lYsXbpUCCFEdHS0MDU1FQEBAaplHj16JIyMjERQUFC6fi6/nSTSPUqlUhw4cEDUqlVL9W2lQqEQGzZsSNfzdXHe60KNvH//foa2SBsZGQkHBwfh7u4u6tatKzp06CB8fX3F9OnTxfLly8WuXbvEv//+KyIjI0V8fHxGhouIvgNrZPprpBC6OV5Ehi4hIUH4+/sLe3t71ecSHx+fdD03vXPeJKPfCGjC+0uv2NvbAwAiIyPx9OlTNGjQQLWMubk5atasiVOnTqkuK5ScnJxmGWdnZ7i7u+PUqVNo2LChZleCiDRCoVCgfv36qF+/Pk6fPo0ZM2bg0KFDqFu3ruxoaqMLNTJ37tzIli2bakv0h1ulP/f/OXPmVMt12InI8OhCjSQi7WFubo4hQ4agW7dumDlzJubNm4emTZtm6c/QuqZbCIGhQ4eievXqcHd3BwDVRc0dHR3TLOvo6KjaFeDp06cwMzODnZ3dJ8u8f/7HEhMTVWdCBv7bPYCIdFeVKlWwa9cuREVFwcHBQXYctdCVGmlhYYE3b96ke3kioqygyRoJ8LMkkT7JkSMHZsyYgUGDBsHJySlLX9soS18tCwwYMACXL1/Gxo0bP3ns4/3qhRDf3Nf+a8vMmDEDtra2qlu+fPkyH5yItIa+NtwAayQR0ddoskYCrJNE+ihPnjzpOp47I7Sq6R44cCB27dqFI0eOIG/evKr733/T8PE3jVFRUapvLZ2cnJCUlITXr19/cZmPjR49GjExMarbgwcPsnJ1iIiyFGskEdGXabpGAqyTRJQ+WtF0CyEwYMAABAYG4vDhw3B1dU3zuKurK5ycnHDw4EHVfUlJSTh27BiqVq0KAPD09ISpqWmaZZ48eYLw8HDVMh8zNzeHjY1NmhsRkbZhjSQi+jJZNRJgnSSi9NGKY7r79++PDRs2YOfOnbC2tlZ9E2lrawtLS0soFAoMHjwY06dPR9GiRVG0aFFMnz4d2bJlw08//aRatkePHhg2bBhy5swJe3t7DB8+HKVLl0a9evVkrh4R0XdhjSQi+jLWSCLSepk8s3qWwhcuIbNq1SrVMkqlUkycOFE4OTkJc3Nz4e3tLcLCwtK8zrt378SAAQOEvb29sLS0FE2bNhX3799Pdw5e5oHI8OjCvGeNJCJZdGHea0uNFEI3xouIsk5657xCCCE01+Jrt3Rf3JyI9AbnffpxrIgMD+d9xnC8iAxLeue8VhzTTURERERERKSP2HQTERERERERqQmbbiIiIiIiIiI1YdNNREREREREpCZsuomIiIiIiIjUhE03ERERERERkZqYyA6gTd5fPS02NlZyEiLSlPfznVdP/DbWSCLDwxqZMayTRIYlvTWSTfcH4uLiAAD58uWTnISINC0uLg62trayY2g11kgiw8UamT6sk0SG6Vs1UiH41aWKUqnE48ePYW1tDYVC8c3lY2NjkS9fPjx48OCrF0M3ZByjr+P4fJu6x0gIgbi4ODg7O8PIiEfcfE1Ga6S66dP84bpoH31ZD+D71oU1MmNYJ7+PruUFdC+zruUFtDtzemskt3R/wMjICHnz5s3w82xsbLTuDaBtOEZfx/H5NnWOEbfepE9ma6S66dP84bpoH31ZDyDz68IamX6sk1lD1/ICupdZ1/IC2ps5PTWSX1kSERERERERqQmbbiIiIiIiIiI1YdP9HczNzTFx4kSYm5vLjqK1OEZfx/H5No4RfYk+vTe4LtpHX9YD0K91oYzRtd+9ruUFdC+zruUFdDPzx3giNSIiIiIiIiI14ZZuIiIiIiIiIjVh001ERERERESkJmy6iYiIiIiIiNSETfc3LF68GK6urrCwsICnpydOnDjx1eWPHTsGT09PWFhYoFChQli6dKmGksqRkfEJDAxE/fr1kTt3btjY2KBKlSr4+++/NZhWjoy+h977559/YGJigrJly6o3oBbI6BglJiZi7NixKFCgAMzNzVG4cGGsXLlSQ2lJU+Li4jB48GAUKFAAlpaWqFq1Ks6dO/fV52jreyOj69K1a1coFIpPbqVKldJg6k9l5neyfv16eHh4IFu2bMiTJw+6deuGly9faijxl2VmXRYtWoSSJUvC0tISxYsXx9q1azWU9v87fvw4mjVrBmdnZygUCuzYsSPN40IITJo0Cc7OzrC0tEStWrVw5cqVb77utm3b4ObmBnNzc7i5uWH79u1qWgPKqG/9zj/0888/Q6FQYN68eWnur1Wr1if15Mcff0yzzOvXr9G5c2fY2trC1tYWnTt3RnR0dJbn/Vx9q1y5cpplEhMTMXDgQOTKlQvZs2dH8+bN8fDhQ7XkzarM2jTGAHD16lU0b94ctra2sLa2RuXKlXH//n3V45oc46zIq8nxVQtBXxQQECBMTU3Fn3/+KSIiIoSvr6/Inj27uHfv3meXv3PnjsiWLZvw9fUVERER4s8//xSmpqZi69atGk6uGRkdH19fXzFz5kxx9uxZcePGDTF69GhhamoqQkNDNZxcczI6Ru9FR0eLQoUKiQYNGggPDw/NhJUkM2PUvHlzUalSJXHw4EERGRkp/v33X/HPP/9oMDVpQrt27YSbm5s4duyYuHnzppg4caKwsbERDx8+/OJztPW9kdF1iY6OFk+ePFHdHjx4IOzt7cXEiRM1G/wjGV2PEydOCCMjIzF//nxx584dceLECVGqVCnRsmVLDSf/VEbXZfHixcLa2loEBASI27dvi40bNworKyuxa9cujebet2+fGDt2rNi2bZsAILZv357mcT8/P2FtbS22bdsmwsLCRPv27UWePHlEbGzsF1/z1KlTwtjYWEyfPl1cvXpVTJ8+XZiYmIgzZ86oeW0oPb71O39v+/btwsPDQzg7O4vffvstzWM1a9YUvXr1SlNXoqOj0yzTqFEj4e7uLk6dOiVOnTol3N3dRdOmTbM8r4+Pj2jUqFGaLC9fvkyzTJ8+fYSLi4s4ePCgCA0NFbVr1xYeHh4iJSUly/NmVWZtGuNbt24Je3t7MWLECBEaGipu374t9uzZI549e6ZaRpNjnBV5NTm+6sCm+ysqVqwo+vTpk+a+EiVKiFGjRn12+V9++UWUKFEizX0///yzqFy5stoyypTR8fkcNzc3MXny5KyOpjUyO0bt27cX48aNExMnTtT7pjujY7R//35ha2v7yR870i9v374VxsbGYs+ePWnu9/DwEGPHjv3sc7T1vZGZdfnY9u3bhUKhEHfv3lVHxHTJzHrMnj1bFCpUKM19CxYsEHnz5lVbzvTIzLpUqVJFDB8+PM19vr6+olq1amrL+S0ff3hVKpXCyclJ+Pn5qe5LSEgQtra2YunSpV98nXbt2olGjRqlua9hw4bixx9/zPLM9H2+1HQ/fPhQuLi4iPDwcFGgQIHPNt2+vr5ffN2IiAgBIM0XLadPnxYAxLVr17I0r4+Pj2jRosUXnxMdHS1MTU1FQECA6r5Hjx4JIyMjERQUpNa8mc0shHaNcfv27UWnTp2++ByZY5yZvELIG9+swt3LvyApKQkhISFo0KBBmvsbNGiAU6dOffY5p0+f/mT5hg0b4vz580hOTlZbVhkyMz4fUyqViIuLg729vToiSpfZMVq1ahVu376NiRMnqjuidJkZo127dsHLywuzZs2Ci4sLihUrhuHDh+Pdu3eaiEwakpKSgtTUVFhYWKS539LSEidPnvzsc7T1vZGZdfnYihUrUK9ePRQoUEAdEdMlM+tRtWpVPHz4EPv27YMQAs+ePcPWrVvRpEkTTUT+osysS2Ji4meXP3v2rNb8jY+MjMTTp0/T1FRzc3PUrFnzq393vvT5Jb1/z0kupVKJzp07Y8SIEV89BGX9+vXIlSsXSpUqheHDhyMuLk712OnTp2Fra4tKlSqp7qtcuTJsbW3V8j44evQoHBwcUKxYMfTq1QtRUVGqx0JCQpCcnJzmPens7Ax3d3dVFk3n/Vbm97RhjJVKJfbu3YtixYqhYcOGcHBwQKVKldLs0q1NY5yevO9pw/hmFpvuL3jx4gVSU1Ph6OiY5n5HR0c8ffr0s895+vTpZ5dPSUnBixcv1JZVhsyMz8fmzp2LN2/eoF27duqIKF1mxujmzZsYNWoU1q9fDxMTE03ElCozY3Tnzh2cPHkS4eHh2L59O+bNm4etW7eif//+mohMGmJtbY0qVarg119/xePHj5Gamop169bh33//xZMnTz77HG19b2RmXT705MkT7N+/Hz179tRA2i/LzHpUrVoV69evR/v27WFmZgYnJyfkyJEDv//+u4bTp5WZdWnYsCGWL1+OkJAQCCFw/vx5rFy5EsnJyVrzN/593czo3+YvfX5J799zkmvmzJkwMTHBoEGDvrhMx44dsXHjRhw9ehTjx4/Htm3b0Lp1a9XjT58+hYODwyfPc3BwyPL3QePGjbF+/XocPnwYc+fOxblz51CnTh0kJiaqspiZmcHOzi7N8z58T2oyb3oyA9ozxlFRUYiPj4efnx8aNWqEAwcOoFWrVmjdujWOHTumyqItY5yevID2jG9m6f+n+u+kUCjS/FsI8cl931r+c/fri4yOz3sbN27EpEmTsHPnzs9OEH2S3jFKTU3FTz/9hMmTJ6NYsWKaiqcVMvI+UiqVUCgUWL9+PWxtbQEA/v7+aNu2LRYtWgRLS0u15yXN+Ouvv9C9e3e4uLjA2NgY5cuXx08//YTQ0NDPLq/N742MrsuHVq9ejRw5cqBly5bqD/oNGV2PiIgIDBo0CBMmTEDDhg3x5MkTjBgxAn369MGKFSs0nD6tjK7L+PHj8fTpU1SuXBlCCDg6OqJr166YNWsWjI2NNZz+6zLztzmzf89JrpCQEMyfPx+hoaFf/X316tVL9f/u7u4oWrQovLy8EBoaivLlywP4/GdVdbwP2rdvnyaLl5cXChQogL1796Zpor6VRVN5gfRl1pYxViqVAIAWLVpgyJAhAICyZcvi1KlTWLp0KWrWrPnF58oY4/Tm1ZbxzSxu6f6CXLlywdjY+JNvRqKioj75Nvg9Jyenzy5vYmKCnDlzqi2rDJkZn/c2bdqEHj16YPPmzahXr546Y0qV0TGKi4vD+fPnMWDAAJiYmMDExARTpkzBpUuXYGJigsOHD2squsZk5n2UJ08euLi4qJoqAChZsiSEEJ+cdZN0W+HChXHs2DHEx8fjwYMHqt14XV1dP7u8Nr83Mrou7wkhsHLlSnTu3BlmZmYaSvtlGV2PGTNmoFq1ahgxYgTKlCmDhg0bYvHixVi5cmW6tvKrU0bXxdLSEitXrsTbt29x9+5d3L9/HwULFoS1tTVy5cql4fSf5+TkBAAZ/tv8pc8v3/p7TvKdOHECUVFRyJ8/v+qzw7179zBs2DAULFjwi88rX748TE1NcfPmTQD/vQeePXv2yXLPnz9X+/sgT548KFCgQJosSUlJeP36dZrlPnxPysz7ucyfI2uMc+XKBRMTE7i5uaW5v2TJkqqzgWvTGKcn7+do03s4Pdh0f4GZmRk8PT1x8ODBNPcfPHgQVatW/exzqlSp8snyBw4cgJeXF0xNTdWWVYbMjA/w3xburl27YsOGDdKP6VO3jI6RjY0NwsLCcPHiRdWtT58+KF68OC5evJjmGBV9kZn3UbVq1fD48WPEx8er7rtx4waMjIyQN29eteYlObJnz448efLg9evX+Pvvv9GiRYvPLqcL7430rst7x44dw61bt9CjRw8NJUyf9K7H27dvYWSU9qPG+63C7/cEky2jvxNTU1PkzZsXxsbGCAgIQNOmTT9ZR1lcXV3h5OSUpqYmJSXh2LFjX/3b/KXPL197DmmHzp074/Lly2k+Ozg7O2PEiBFfvSzrlStXkJycjDx58gD47z0QExODs2fPqpb5999/ERMTo/b3wcuXL/HgwQNVFk9PT5iamqZ5Tz558gTh4eGqLDLzfi7z58gaYzMzM1SoUAHXr19Pc/+NGzdU5wXRpjFOT97P0ab3cLpo9LRtOub9pYxWrFghIiIixODBg0X27NlVZ48dNWqU6Ny5s2r595cMGzJkiIiIiBArVqwwiEuGpXd8NmzYIExMTMSiRYu+erp/fZLRMfqYIZy9PKNjFBcXJ/LmzSvatm0rrly5Io4dOyaKFi0qevbsKWsVSE2CgoLE/v37xZ07d8SBAweEh4eHqFixokhKShJC6NZ7I6Pr8l6nTp1EpUqVNB33izK6HqtWrRImJiZi8eLF4vbt2+LkyZPCy8tLVKxYUdYqqGR0Xa5fvy7++usvcePGDfHvv/+K9u3bC3t7exEZGanR3HFxceLChQviwoULAoDw9/cXFy5cUF1m0c/PT9ja2orAwEARFhYmOnTo8Mklwzp37pzmChH//POPMDY2Fn5+fuLq1avCz8+PlwzTIt/6nX/s47OX37p1S0yePFmcO3dOREZGir1794oSJUqIcuXKfXJ5qDJlyojTp0+L06dPi9KlS2fqcktfyxsXFyeGDRsmTp06JSIjI8WRI0dElSpVhIuLS5r3aJ8+fUTevHlFcHCwCA0NFXXq1Pns5ayyIm9WZNamMRZCiMDAQGFqaiqWLVsmbt68KX7//XdhbGwsTpw4IWWMvzevpsdXHdh0f8OiRYtEgQIFhJmZmShfvrw4duyY6jEfHx9Rs2bNNMsfPXpUlCtXTpiZmYmCBQuKJUuWaDixZmVkfGrWrCkAfHLz8fHRfHANyuh76EOG0HQLkfExunr1qqhXr56wtLQUefPmFUOHDhVv377VcGpSt02bNolChQoJMzMz4eTkJPr375/mSzpdem9kZl2io6OFpaWlWLZsmYbTfllm1mPBggXCzc1NWFpaijx58oiOHTt+9VrrmpLRdYmIiBBly5YVlpaWwsbGRrRo0ULKZWiOHDny1b+lSqVSTJw4UTg5OQlzc3Ph7e0twsLC0rxGzZo1P/nbu2XLFlG8eHFhamoqSpQoIbZt26ahNaJv+dbv/GMfN933798X3t7ewt7eXpiZmYnChQuLQYMGfXJ5xZcvX4qOHTsKa2trYW1tLTp27Chev36dpXnfvn0rGjRoIHLnzi1MTU1F/vz5hY+Pj7h//36a13j37p0YMGCAsLe3F5aWlqJp06afLJNVebMiszaN8XsrVqwQRYoUERYWFsLDw0Ps2LEjzWtocoy/N6+mx1cdFEJoyf5dRERERERERHpGOw5CIiIiIiIiItJDbLqJiIiIiIiI1IRNNxEREREREZGasOkmIiIiIiIiUhM23URERERERERqwqabiIiIiIiISE3YdBMRERERERGpCZtuIiIiIiIiIjVh001ERERERESkJmy6yaB17doVCoXik9utW7dkRyMiynLfW/NOnTqF//3vf7Czs4OFhQVKly6NuXPnIjU1VbXM3bt3oVAocPHiRTWtBRGRfJ+rpR/eunbtKjsiaRET2QGIZGvUqBFWrVqV5r7cuXNLSkNEpF6ZrXnbt29Hu3bt0K1bNxw5cgQ5cuRAcHAwfvnlF5w5cwabN2+GQqFQV2wiIq3y5MkT1f9v2rQJEyZMwPXr11X3WVpayohFWopNNxk8c3NzODk5yY5BRKQRX6p5u3fvxqRJk3DlyhU4OzvDx8cHY8eOhYmJCd68eYNevXqhefPmWLZsmeo5PXv2hKOjI5o3b47Nmzejffv2cHV1BQCUK1cOAFCzZk0cPXpUI+tGRKQpH9ZRW1tbKBQKfp6kL+Lu5URERAbu77//RqdOnTBo0CBERETgjz/+wOrVqzFt2jQAwIEDB/Dy5UsMHz78k+c2a9YMxYoVw8aNGwEAZ8+eBQAEBwfjyZMnCAwM1NyKEBERaSFu6SaDt2fPHlhZWan+3bhxY2zZskViIiIi9flczXv27BlGjRoFHx8fAEChQoXw66+/4pdffsHEiRNx48YNAEDJkiU/+5olSpRQLfN+V/WcOXNyqw8RERHYdBOhdu3aWLJkierf2bNnl5iGiEi9PlfzihQpgnPnzqm2bANAamoqEhIS8PbtW9V9QojPvqYQgsdzExERfQGbbjJ47z9wEhEZgs/VPKVSicmTJ6N169afLG9hYYFixYoBAK5evYqqVat+ssy1a9fg5uamnsBEREQ6jk03ERGRgft/7d0ha+pRHMfh74YMZaBgMAxlcX0gmIxaBIsbvgKT1TRY2er+Yc13YBaDIGPvYSYx+kLubYPLZenyZxf2PPmUEz/ncH7n9vY2h8PhywPIwWCQZrOZl5eXv6J7vV7neDzm6ekpSXJxcZEkf3wjBgA/megGgB/u8fExo9EonU4nd3d3OT8/z8fHR/b7fZ6fn3N5eZnlcpnpdJrZbJb5fJ56vZ63t7csFotMJpPc398nSVqtVmq1WrbbbdrtdqrVahqNxjfvEAC+j+nlAPDDDYfDbDab7Ha7dLvd9Hq9FEWR6+vrzzWTySTv7+85nU7p9/u5ublJURR5eHjIarX6fNNdqVTy+vqa5XKZq6urjMfj79oWAPwXzn59NRUFAAAA+CduugEAAKAkohsAAABKIroBAACgJKIbAAAASiK6AQAAoCSiGwAAAEoiugEAAKAkohsAAABKIroBAACgJKIbAAAASiK6AQAAoCSiGwAAAEryGwlMc4Nrkj7AAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2, ax3)) = plt.subplots(1, 3, figsize=(10,4))\n",
    "\n",
    "ax1.plot(Thermocalc_df['liq'],\n",
    "         Sulf_KDs_Kis['DCu'], '-k')\n",
    "ax1.set_xlabel('F')\n",
    "ax1.set_ylabel('D$_{Cu}$')\n",
    "\n",
    "ax2.plot(Thermocalc_df['FeOt'],\n",
    "         Sulf_KDs_Kis['DCu'], '-k')\n",
    "ax2.set_xlabel('FeOt')\n",
    "ax2.set_ylabel('D$_{Cu}$')\n",
    "\n",
    "ax3.plot(Thermocalc_df['T'],\n",
    "         Sulf_KDs_Kis['DCu'], '-k')\n",
    "ax3.set_xlabel('T')\n",
    "ax3.set_ylabel('D$_{Cu}$')\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_Cu_200S_Thermocalc_Kis=ss.Lee_Wieser_sulfide_melting(F=Thermocalc_df['liq'], \n",
    "                        Modes=Modes3,\n",
    "                        KDs=KDs_Cu_Kis,\n",
    "                        S_Sulf=S_Sulf, elem_Per=30,\n",
    "                        S_Mantle=[200],\n",
    "                        S_Melt_SCSS_2_ppm=SCSS_fixedSulf['SCSS2_ppm'],\n",
    "                         Prop_S6=0)\n",
    "\n",
    "# Lets also model Selenium\n",
    "df_Cu_200S_Thermocalc_Kis=ss.Lee_Wieser_sulfide_melting(F=Thermocalc_df['liq'], \n",
    "                        Modes=Modes3,\n",
    "                        KDs=KDs_Cu_Kis,\n",
    "                        S_Sulf=S_Sulf, elem_Per=30,\n",
    "                        S_Mantle=[200],\n",
    "                        S_Melt_SCSS_2_ppm=SCSS_fixedSulf['SCSS2_ppm'],\n",
    "                         Prop_S6=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,8))\n",
    "figure_mosaic=\"\"\"\n",
    "    AB\n",
    "    AC\n",
    "\n",
    "    \"\"\"\n",
    "fig,axes=plt.subplot_mosaic(mosaic=figure_mosaic, figsize=(9, 3.5), sharex=True)\n",
    "\n",
    "axes['A'].plot(df_Cu_200S['F'].iloc[1:], \n",
    "         df_Cu_200S['Cu_Melt_Agg'].iloc[1:],\n",
    "        '--',color='m', ms=10, label='Cu, S=200 ppm, simple')\n",
    "# Lets add a cross to show the point at which sulfide is exhausted\n",
    "sulf_out_200=np.take(np.where(df_Cu_200S['S_Residue']==0), 0)\n",
    "axes['A'].plot(df_Cu_200S['F'].loc[sulf_out_200], \n",
    "         df_Cu_200S['Cu_Melt_Agg'].loc[sulf_out_200],\n",
    "        '*k', ms=10, label='Sulf out')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Kiseeva KDs, O2021 SCSS\n",
    "axes['A'].plot(df_Cu_200S_Thermocalc_Kis['F'].iloc[1:], \n",
    "         df_Cu_200S_Thermocalc_Kis['Cu_Melt_Agg'].iloc[1:],\n",
    "        '-',color='b', ms=10, label='Cu, S=200 ppm, Kiseeva KDs, O2021 SCSS')\n",
    "# Lets add a cross to show the point at which sulfide is exhausted\n",
    "sulf_out_200=np.take(np.where(df_Cu_200S_Thermocalc_Kis['S_Residue']==0), 0)\n",
    "axes['A'].plot(df_Cu_200S_Thermocalc_Kis['F'].loc[sulf_out_200], \n",
    "         df_Cu_200S_Thermocalc_Kis['Cu_Melt_Agg'].loc[sulf_out_200],\n",
    "        '*k', ms=10, label='Sulf out')\n",
    "\n",
    "# FixedKD, O2021 SCSS\n",
    "\n",
    "axes['A'].plot(df_Cu_200S_Thermocalc['F'].iloc[1:], \n",
    "         df_Cu_200S_Thermocalc['Cu_Melt_Agg'].iloc[1:],\n",
    "        '-',color='c', ms=10, label='Cu, S=200, KD=800, O2021 SCSS')\n",
    "# Lets add a cross to show the point at which sulfide is exhausted\n",
    "sulf_out_200=np.take(np.where(df_Cu_200S_Thermocalc['S_Residue']==0), 0)\n",
    "axes['A'].plot(df_Cu_200S_Thermocalc['F'].loc[sulf_out_200], \n",
    "         df_Cu_200S_Thermocalc['Cu_Melt_Agg'].loc[sulf_out_200],\n",
    "        '*k', ms=10, label='Sulf out')\n",
    "axes['A'].set_xlim([0, 0.5])\n",
    "axes['A'].set_xlabel('F (degree of melting)')\n",
    "axes['A'].set_ylabel('Melt Cu$_{Aggregated}$ (ppm)')\n",
    "axes['A'].set_ylim([0, 170])\n",
    "\n",
    "\n",
    "axes['B'].plot(df_Cu_200S_Thermocalc_Kis['F'].iloc[1:],\n",
    "               KDs_Cu_Kis['sulf'].iloc[1:], '-b')\n",
    "axes['B'].plot(df_Cu_200S_Thermocalc['F'].iloc[1:],\n",
    "               df_Cu_200S_Thermocalc['F'].iloc[1:]*0+800, '-c')\n",
    "axes['B'].plot(df_Cu_200S['F'].iloc[1:],\n",
    "               df_Cu_200S['F'].iloc[1:]*0+800, '--m')\n",
    "axes['B'].set_ylabel('K$_D$ Cu')\n",
    "\n",
    "axes['C'].plot(df_Cu_200S_Thermocalc_Kis['F'].iloc[1:],\n",
    "               df_Cu_200S_Thermocalc_Kis['S_Melt_Agg'].iloc[1:], '-b')\n",
    "axes['C'].plot(df_Cu_200S_Thermocalc['F'].iloc[1:],\n",
    "               df_Cu_200S_Thermocalc['S_Melt_Agg'].iloc[1:], '-c')\n",
    "axes['C'].plot(df_Cu_200S['F'].iloc[1:],\n",
    "               df_Cu_200S['S_Melt_Agg'].iloc[1:], '--m')\n",
    "\n",
    "\n",
    "\n",
    "axes['C'].set_xlabel('F (degree of melting)')\n",
    "axes['C'].set_ylabel('Melt S$_{Aggregated}$ (ppm)')\n",
    "fig.tight_layout()\n",
    "fig.savefig('Complex_Models.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x17dd803baf0>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_Cu_200S_Thermocalc['F'].iloc[1:],\n",
    "               df_Cu_200S_Thermocalc['S_Melt_Agg'].iloc[1:], '-c')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
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  "toc": {
   "base_numbering": 1,
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   "number_sections": true,
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
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  "varInspector": {
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
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     "varRefreshCmd": "print(var_dic_list())"
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     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
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   },
   "position": {
    "height": "572.5183715820312px",
    "left": "1345.481689453125px",
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   "types_to_exclude": [
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 "nbformat": 4,
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