{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "038b70f6",
   "metadata": {},
   "source": [
    "# Advanced Physical Modeling\n",
    "\n",
    "In the previous tutorial, we simply modeled the chemistry of a static cloud for 1 Myr. This is unlikely to meet\n",
    "everybody's modeling needs and UCLCHEM is capable of modeling much more complex environments such as prestellar\n",
    "cores and shocks. In this tutorial, we model both a prestellar core and a shock to explore how these models work and\n",
    "to demonstrate the workflow that the UCLCHEM team normally follow. In tutorial 2a, we approach the modeling in a more\n",
    "classic approach, by writing the outputs to files, before passing them to the subsequent model class. In tutorial 2b,\n",
    "we calculate the exact same models, but take advantage of the model objects in order to perform all calculations in\n",
    "memory, bypassing the file system entirely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ccfee969",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:23:09.023032Z",
     "iopub.status.busy": "2026-06-19T14:23:09.022812Z",
     "iopub.status.idle": "2026-06-19T14:23:09.410074Z",
     "shell.execute_reply": "2026-06-19T14:23:09.409100Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "55f31663",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:23:09.412557Z",
     "iopub.status.busy": "2026-06-19T14:23:09.412285Z",
     "iopub.status.idle": "2026-06-19T14:23:09.807235Z",
     "shell.execute_reply": "2026-06-19T14:23:09.806229Z"
    }
   },
   "outputs": [],
   "source": [
    "import uclchem"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d2883f5",
   "metadata": {},
   "source": [
    "## The Prestellar Core\n",
    "\n",
    "### Initial Conditions (Phase 1)\n",
    "UCLCHEM typically starts with the gas in atomic/ionic form with no molecules. However, this clearly is not appropriate\n",
    "when modeling an object such as a prestellar core. In these objects, the gas is already evolved and there should be\n",
    "molecules in the gas phase as well as ice mantles on the dust. To allow for this, one must provide some initial\n",
    "abundances to the model. There are many ways to do this, but we typically chose to run a preliminary model to produce\n",
    "our abundances. In many UCLCHEM papers, we refer to the preliminary model as *phase 1* and the science model as\n",
    "*phase 2*. Phase 1 simply models a collapsing cloud and phase 2 models the object in question.\n",
    "\n",
    "To do this, we will use `uclchem.model.Cloud()` to run a model where a cloud of gas collapses from a density of\n",
    "$10^2 cm^{-3}$ to our prestellar core density of $10^6 cm^{-3}$, keeping all other parameters constant. During this\n",
    "collapse, chemistry will occur, and we can assume the final abundances of this model will be reasonable starting\n",
    "abundances for the prestellar core."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e98c8134",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:23:09.809318Z",
     "iopub.status.busy": "2026-06-19T14:23:09.808994Z",
     "iopub.status.idle": "2026-06-19T14:23:41.184460Z",
     "shell.execute_reply": "2026-06-19T14:23:41.183496Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element conservation report\n",
      "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%'}\n"
     ]
    }
   ],
   "source": [
    "# set a parameter dictionary for cloud collapse model\n",
    "param_dict = {\n",
    "    \"endAtFinalDensity\": False,  # stop at finalTime\n",
    "    \"freefall\": True,  # increase density in freefall\n",
    "    \"initialDens\": 1e2,  # starting density\n",
    "    \"finalDens\": 1e6,  # final density\n",
    "    \"initialTemp\": 10.0,  # temperature of gas\n",
    "    \"finalTime\": 6.0e6,  # final time\n",
    "    \"rout\": 0.1,  # radius of cloud in pc\n",
    "    \"baseAv\": 1.0,  # visual extinction at cloud edge.\n",
    "}\n",
    "cloud = uclchem.model.Cloud(param_dict=param_dict)\n",
    "cloud.check_conservation()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "429d7afa",
   "metadata": {},
   "source": [
    "With that done, we have run the model and stored the outputs into the object `cloud`, while also storing the final abundances by using: `param_dict[\"abundSaveFile\"]`. We can pass this value our prestellar core model to use those abundances as our initial abundances. Of note, the parameter `abundSaveFile` has been removed from param_dict by creating the `cloud` object."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9248a786",
   "metadata": {},
   "source": [
    "\n",
    "### Running the Science Model (Phase 2)\n",
    "\n",
    "We need to change just a few things in `param_dict` to set up the prestellar core model. The key one is that UCLCHEM saves final abundances to `abundSaveFile` but loads them from `abundLoadFile` so we need to provide the `abundLoadFile` parameter to make the abundances we just produced our initial abundances.\n",
    "\n",
    "We also want to turn off freefall and change how long the model runs for."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c3a46df0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:23:41.186350Z",
     "iopub.status.busy": "2026-06-19T14:23:41.186177Z",
     "iopub.status.idle": "2026-06-19T14:29:43.150132Z",
     "shell.execute_reply": "2026-06-19T14:29:43.149146Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At T(=R1) and step size H(=R2), the                                             \n",
      "[last_model]  corrector convergence failed repeatedly                                         \n",
      "[last_model]  or with ABS(H) = HMIN.                                                          \n",
      "[last_model] In the above message, R1 =   0.2370212948534D+12   R2 =   0.3130566111195D+03\n",
      "[last_model]  ISTATE -5 - shortening step at time   7500.0000000000000      years\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At T(=R1) and step size H(=R2), the                                             \n",
      "[last_model]  corrector convergence failed repeatedly                                         \n",
      "[last_model]  or with ABS(H) = HMIN.                                                          \n",
      "[last_model] In the above message, R1 =   0.9541554838671D+12   R2 =   0.2551642813477D+02\n",
      "[last_model]  ISTATE -5 - shortening step at time   30000.000000000000      years\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.9542232218789D+12\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.9568818232382D+12\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.9616396512796D+12\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.9694901437055D+12\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1106075551200D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1264045644538D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1422170248583D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1580000410007D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1738000375250D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1896001005645D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.1896002187262D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.2370038412954D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.2371822431098D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.2372940445267D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.2474141452171D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.2553322614923D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.3004328172319D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.3161751627171D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.5101703863098D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.6564703382924D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  At current T(=R1), MXSTEP(=I1) steps                                            \n",
      "[last_model]  taken on this call before reaching TOUT.                                        \n",
      "[last_model] In the above message, I1 =      10000\n",
      "[last_model] In the above message, R1 =   0.7902775370342D+13\n",
      "[last_model]  ISTATE -1: Reducing time step\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element conservation report\n",
      "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%'}\n"
     ]
    }
   ],
   "source": [
    "# change other bits of input to set up phase 2\n",
    "param_dict[\"initialDens\"] = 1e6\n",
    "param_dict[\"finalTime\"] = 1e6\n",
    "param_dict[\"freefall\"] = False\n",
    "# freeze out is completely overwhelmed by thermal desorption\n",
    "# so turning it off has no effect on abundances but speeds up integrator.\n",
    "param_dict[\"freezeFactor\"] = 0.0\n",
    "# Set the tolerances we need to solve the model effectively:\n",
    "param_dict[\"abstol_factor\"] = 1e-18\n",
    "param_dict[\"reltol\"] = 1e-12\n",
    "\n",
    "p_core = uclchem.model.PrestellarCore(\n",
    "    temp_indx=3, max_temperature=300.0, param_dict=param_dict, previous_model=cloud\n",
    ")\n",
    "p_core.check_conservation()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6affe035",
   "metadata": {},
   "source": [
    "Note that we've made two changes to the parameters here which aren't strictly necessary but can be helpful in certain\n",
    "situations.\n",
    "\n",
    "Since the gas temperature increases throughout a prestellar core model, freeze out is much slower than thermal\n",
    "desorption for all but the first few time steps. Turning it off doesn't affect the abundances but will speed up the\n",
    "solution.\n",
    "\n",
    "We also change abstol and reltol here, largely to demonstrate their use. They control the integrator accuracy and\n",
    "whilst making them smaller does slow down successful runs, it can make runs complete that stall completely otherwise\n",
    "or give correct solutions where lower tolerances allow issues like element conservation failure to sneak in. If your\n",
    "code does not complete or element conservation fails, you can change them.\n",
    "\n",
    "### Checking the Result\n",
    "With a successful run, we can check the output. To easily work with the output, we first retrieve the pandas dataframe\n",
    "version of it, then we can plot it up."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "db901fab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:29:43.152049Z",
     "iopub.status.busy": "2026-06-19T14:29:43.151828Z",
     "iopub.status.idle": "2026-06-19T14:29:44.543562Z",
     "shell.execute_reply": "2026-06-19T14:29:44.542646Z"
    }
   },
   "outputs": [
    {
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rHnroIY0fPz5itaJylf08GBcXp7S0NP/54uLioK9Z586dTa+WBdD4VPc74+bNm/3H7777rpYtW6ZVq1ape/fumjFjBq+MBxq56q4Ry5cvV2FhoRITE/3rTqdT5557rv+Yx5WAxivcx5VatWqlSZMmaeTIkVq5cqW8Xq8GDhyolJSUiNYLILKq+zni+J7evXvLYrHoo48+0ttvv63du3friSee0OjRoyNab0NDiCuKjreMOz7/s6K4uDjl5uZK8iWiZ8yYEdHaAERfddcIwzBUWlrqb4k/aNAgDRo0KKI1Aoie6q4Rku8Ju4p+97vf1X9hAGKC2+2WpJDdtI536HO5XP61hIQEnswHmpCa/hxhtVo1efLkyBSHsFX3dTz+NUxLS+NxJaAJCvcacdzQoUM1dOjQiNQGIPrC/XmwYojr1ltvjUxxAKKupo8rJSUl6ZxzzolMcQCirqaPKzkcDl166aWRKa4RsEa7gKYsOTlZUvATrJJUVFTkPw+gaaruGmG32/0BLgBNT3XXiIp7ADQ9x1/xeOzYsaBzx9dSU1MjWRKAGMLPEY0DjysBqArXCABV4edBAFXhcSUAVeHniPpFiCuKMjMzJUk7d+40rbvdbu3du9d/HkDTVNk14vga1wigaavuGtG8efOQrWwBNA09e/aU1WrVtm3bgs5t3bpVVquVETlAE9a6dWs1b9680p8jJPH7RgNQ2c+DR48eVUFBAV9DoInjcSUAVanuGtGxY0c5nc5IlwUgRvTp00eSKn1cKSEhQV26dIlsUQBiRrdu3WSz2XhcqZ4Q4oqicePGSZKWLVtmWl++fLnKysr85wE0TWeffbacTmfQNWL37t3asmUL1wigievfv7/atGkTdI0oKirSqlWrNHbs2ChVBiAWJCcn65xzztGSJUvk8Xj86263W4sXL9Y555yjpKSkKFYIIJosFovGjh2rVatW+VvgH/f555+rTZs26t+/f5SqQ7gqe1zp888/N50H0DSNHj1aVqs16Bqxdu1a5ebmco0AmrghQ4YoOTk56Bpx+PBhrV27lmsE0MS1a9dOAwYM0KeffmpaLyoq0pdffqnzzjsv5KhFAE1DQkKChg0bpq+++kper9d07vPPP1evXr3UqVOnKFXX8BHiiqKePXtq8uTJmjdvnvbv3y9J8ng8uu+++5SRkaGrr746yhUCiKaUlBTdeOON+s9//qP169f712fPnq1mzZpp2rRp0SsOQNTZbDbdfvvt+vTTT7V06VL/+l/+8heVlJTo9ttvj2J1AGLB7NmztX//fj3wwAP+tfvuu0+HDh3SPffcE8XKAMSC22+/XcXFxXrkkUf8a4sXL9aSJUt0++2384B8AzB48GCNHDlSjz32mPLy8iRJZWVlmjNnjrp166bLLrssyhUCiKZ27dpp6tSpeu6557R9+3ZJkmEYuueee5SamqobbrghyhUCiKaEhARNnz5d7733nr777jv/+v333y+bzaZbb701itUBiAX33XefsrOz9fjjj0vy/Rzx5z//WWVlZbr77rujXB2AaPvTn/6kPXv26Omnn/avvf3221qzZo3uvPPOKFbW8FkMwzCiXURjdN1116mkpEQffPCBSkpKNGXKFEnS008/LYfD4d9XUFCgyZMn68cff9TIkSO1Zs0aHTlyRG+//bYGDhwYrfIB1LMZM2Zo165dWrx4sbZv365f/vKXkqQ5c+aobdu2/n1lZWX65S9/qfnz52vcuHHasWOHNm3apJdfflnjx4+PVvkA6tncuXO1evVqffPNN1q7dq0uvvhiJSUl6ZZbbtFJJ53k32cYhqZNm6Z//vOfGj9+vPLy8rRy5UrNmzdPP//5z6P4EQCoTw899JDefvtt7du3T9u3b1efPn2UnJysO++8U5MmTTLtffvtt3XDDTeoWbNmknyvmHzyySc1efLkaJQOIALmz5+vN954Qzt27NBnn32mYcOGqVu3bpo0aVLQ//2XXnpJ1113nQYNGqTU1FQtWLBA1157rR577DFZLJYofQTwer3+F/a9/fbbstvtmjRpkhwOh+nBUUk6cOCALrjgAu3YsUPDhw/Xt99+K4/Ho/fee88/AgVA43PzzTcrNzdXCxcu1KFDh3TFFVdIkh577DGlpKT49xUVFenSSy/VsmXLNGbMGGVnZ2vv3r16/fXXNXz48GiVD6Ce3Xvvvdq8ebO++OILbd68WVdeeaXsdrtmzZplGn/m8Xh07bXX6vXXX9e4ceO0b98+rVmzRs8995wuuuii6H0AAOrVXXfdpUWLFmnXrl3avXu3Tj75ZCUkJGjOnDk655xzTHtffPFFTZ8+XWlpaSotLZVhGHr66ad5fgpoxN544w3Nnz9fmzZt0rJlyzRq1Ch16NBBl112WdD//b///e/64x//qOHDh8vhcOjjjz/W7bffrtmzZ0ep+saBEFc9efnll+VyuYLWf/7zn4d8NeuqVauUnZ2t9PR0DR8+XHFxcZEoE0CUvPvuu/5XSld00UUXmR5sO279+vX64YcflJycrOHDhzP+CGjkPvnkk5CzxMeMGaP27dsHrW/dulUrV65UfHy8hg0bprS0tEiUCSBKtm7d6u/kW1H37t2Vnp4etO52u7Vx40ZZLBZlZWXJbrdHokwAUfLjjz9q1apVQev9+/fXqaeeGrSel5enpUuXqqSkRIMGDVLXrl0jUSaqYBiGnn/++aB1m80WMqhvGIZWrFihLVu2KCMjQ8OGDeNaDzRyb7zxhgoLC4PWL730UiUkJASt//DDD1q3bp3S0tI0fPjwkHsANB7z58/XwYMHg9YnTpyoli1bBq1nZ2fru+++U2JiooYPH67mzZtHokwAUbJp0yYdOnQoaD0rK0stWrQIWne5XNq4caNsNpt69uwpq5VBX0BjtmrVKv34449B64MGDVLfvn2D1g8ePKgvvvhCHo9HZ5xxhjp06BCJMhs1QlwAAAAAAAAAAAAAAAAAEEVEZQEAAAAAAAAAAAAAAAAgighxAQAAAAAAAAAAAAAAAEAUEeICAAAAAAAAAAAAAAAAgCgixAUAAAAAAAAAAAAAAAAAUUSICwAAAAAAAAAAAAAAAACiiBAXAAAAAAAAAAAAAAAAAEQRIS4AAAAAAAAAAAAAAAAAiCJCXAAAAAAAAAAAAAAAAAAQRYS4AAAAAAAAAAAAAAAAACCKCHEBAAAAAAAAAAAAAAAAQBQR4gIAAAAAAAAAAAAAAACAKCLEBQAAAAAAAAAAAAAAAABRRIgLAAA0aK1atZLFYqnR25QpU6Jddp3q2bOnTj/99GiXAQAAAAAA0ODNmjWrxo81WSwW7du3L9ql15nHH39cFotFK1asiHYpAAAATQohLgAA0OC9+uqrMgzD/7Z+/XpJUsuWLU3rhmHoxhtv9N/O4/Ho9NNPV+fOnRvsA21r165Vdna2LrroomiXAgAAAAAA0CgMHTo06DGlUaNGSar8cajjnnrqKSUlJenJJ5+MRul14u2331aHDh00aNCgaJcCAADQpBDiAgAATZrX65XX6412GbX29ttvS5ImT54c5UoAAAAAAADg9XplGIY8Hk+0S6mVQ4cOaenSpbrwwgtlsViiXQ4AAECTYjEMw4h2EQAAAHVpw4YN6t27t1q2bKlDhw5Fu5x6deqpp6qsrExr166NdikAAAAAAACN1ujRo/XJJ5/o1Vdf1WWXXRbtcurNv/71L11zzTX69NNPdc4550S7HAAAgCaFTlwAAAAN1NatW7V69Wq6cAEAAAAAAKBOvP3222rVqpWGDx8e7VIAAACaHEJcAACgSXrppZdksVj8b2+++WaV5+bNm6devXopPj5e3bp10z333COPx6N9+/bpqquuUqtWrZSamqoRI0Zo5cqVId+nx+PRk08+qcGDByspKUnNmjXTySefrDlz5qikpKTGH0O4oxRXr15t+ngsFov69evnPz9v3jzTuSlTptSqZq/Xqw8//FCXXHKJevToIafTqdTUVA0ZMkSPPfaY3G63aX+oz/P8+fM1ZMgQJSYmymKxKCMjQ5JkGIb+/e9/a8iQIWrVqpXi4+PVu3dv3XLLLfrxxx9r/LkDAAAAAACoa6mpqf7HOUaMGFHluQ0bNmjChAlKTk5WWlqaJk6cqI0bN0qSnnzySfXu3VsJCQnKysrSnDlzKh3P+N133+myyy5TRkaG4uLi1LZtW11++eW16tp+9OhRffLJJ5o0aZJsNluVe88666ygx5sWL17sP2+3203n9u3bV6uat23bprvuuksDBgxQSkqK4uPj1b17d11zzTXavHlz0P7Az/OhQ4d09dVXKyMjQ1arNehxQAAAgFhCiAsAADRJV111lQzD0B/+8Idqz82dO1d5eXn64osvtGXLFp166qmaOXOmpk+frquuukrXXnuttm/frnfffVdr1qzRuHHjlJeXZ7pPl8uliRMn6sYbb9Tpp5+uzZs368CBA7rppps0c+ZMjRs3TmVlZTX6GN5++2116dJFp556apX7TjnlFBmGodGjR0uS3n//fa1Zs8Z//rrrrlNBQYGSk5O1bNky/wNZNa35yy+/1HnnnSen06lFixapoKBAX3/9tbKysjRt2jRNnTq1ys/z/Pnz9eabb+rFF1/Url27NHHiRP/eGTNm6Ne//rUuv/xybdy4UXl5eXrmmWe0cOHCaj9+AAAAAACASMjPz1dOTk615/bu3atbb71VDz74oPbu3at//vOf+vDDD3XOOefojjvuUF5enj7//HNt2bJFJ598su6880794x//CLrPN954Q4MHD9Z3332nd955R0ePHtWHH36onJwcnX766fr8889rVP8HH3yg0tLSsLq+f/HFF3rnnXckSePGjZNhGKbgmtvt1vXXX6/LL79chmH4X6hX05ovvPBCPfvss/7P1a5duzRr1iy98cYbGjhwoLZt22baX/HzXFJSop///Oe67LLLlJOTozfeeKNGnw8AAICIMwAAABqZ9evXG5KMli1bVrv3D3/4gyHJeOO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      "text/plain": [
       "<Figure size 2400x1350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_p_core = p_core.get_joined_dataframes()\n",
    "species = [\"CO\", \"H2O\", \"CH3OH\", \"#CO\", \"#H2O\", \"#CH3OH\", \"@H2O\", \"@CO\", \"@CH3OH\"]\n",
    "fig, [ax, ax2] = plt.subplots(1, 2, figsize=(16, 9))\n",
    "ax = p_core.plot_species(ax, species)\n",
    "settings = ax.set(\n",
    "    yscale=\"log\",\n",
    "    xlim=(1e2, 1e6),\n",
    "    ylim=(1e-10, 1e-2),\n",
    "    xlabel=\"Time / years\",\n",
    "    ylabel=\"Fractional Abundance\",\n",
    "    xscale=\"log\",\n",
    ")\n",
    "\n",
    "ax2.plot(df_p_core[\"Time\"], df_p_core[\"Density\"], color=\"black\")\n",
    "ax2.set(xscale=\"log\")\n",
    "ax3 = ax2.twinx()\n",
    "ax3.plot(df_p_core[\"Time\"], df_p_core[\"gasTemp\"], color=\"red\")\n",
    "ax2.set(xlabel=\"Time / year\", ylabel=\"Density\")\n",
    "ax3.set(ylabel=\"Temperature\", facecolor=\"red\", xlim=(1e2, 1e6))\n",
    "ax3.tick_params(axis=\"y\", colors=\"red\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a031b007",
   "metadata": {},
   "source": [
    "Here, we see the value of running a collapse phase before the science run. Having run a collapse, we start this model\n",
    "with well developed ices and having material in the surface and bulk allows us to properly model the effect of warm up\n",
    "in a prestellar core. For example, the @CO abundance is $\\sim10^{-4}$ and #CO is $\\sim10^{-6}$. As the gas warms to\n",
    "around 30K, the #CO abundance drops drastically as CO's binding energy is such that it is efficiently desorbed from\n",
    "the surface at this temperature. However, the rest of the CO is trapped in the bulk, surrounded by more strongly bound\n",
    "H2O molecules. Thus, the @CO abundance stays high until the gas reaches around 130K, when the H2O molecules are\n",
    "released along with the entire bulk.\n",
    "\n",
    "## Shocks\n",
    "Essentially the same process should be followed for shocks. Let's run a C-type and J-type shock through a gas of\n",
    "density $10^4 cm^{-3}$. Again, we first run a simple cloud model to obtain some reasonable starting abundances, then\n",
    "we can run the shocks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "73d5383d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:29:44.545528Z",
     "iopub.status.busy": "2026-06-19T14:29:44.545329Z",
     "iopub.status.idle": "2026-06-19T14:29:52.062696Z",
     "shell.execute_reply": "2026-06-19T14:29:52.061783Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element conservation report\n",
      "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%'}\n"
     ]
    }
   ],
   "source": [
    "# set a parameter dictionary for phase 1 collapse model\n",
    "\n",
    "param_dict = {\n",
    "    \"endAtFinalDensity\": False,  # stop at finalTime\n",
    "    \"freefall\": True,  # increase density in freefall\n",
    "    \"initialDens\": 1e2,  # starting density\n",
    "    \"finalDens\": 1e4,  # final density\n",
    "    \"initialTemp\": 10.0,  # temperature of gas\n",
    "    \"finalTime\": 6.0e6,  # final time\n",
    "    \"rout\": 0.1,  # radius of cloud in pc\n",
    "    \"baseAv\": 1.0,  # visual extinction at cloud edge.\n",
    "    \"freezeFactor\": 0.0,\n",
    "}\n",
    "shock_start = uclchem.model.Cloud(param_dict=param_dict)\n",
    "shock_start.check_conservation()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de157715",
   "metadata": {},
   "source": [
    "### C-shock\n",
    "We'll first run a c-shock. We choose to crate a 40 km s $^{-1}$ shock through a gas of density $10^4$ cm $^{-3}$,\n",
    "using the model we just produced. Note that c-shock is the only model which returns an additional output in its\n",
    "result list. C-Shock models include an additional variable that can be accessed, the dissipation time. This can be\n",
    "retrieved like so `cshock.dissipation_time` where `cshock` would be the object created using `uclchem.model.CShock()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a320a662",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:29:52.064667Z",
     "iopub.status.busy": "2026-06-19T14:29:52.064468Z",
     "iopub.status.idle": "2026-06-19T14:30:08.890873Z",
     "shell.execute_reply": "2026-06-19T14:30:08.890057Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[last_model]  Cannot have freefall on during cshock\n",
      "[last_model]  setting freefall=0 and continuing\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element conservation report\n",
      "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%'}\n"
     ]
    }
   ],
   "source": [
    "# change other bits of input to set up phase 2\n",
    "param_dict[\"initialDens\"] = 1e4\n",
    "param_dict[\"finalTime\"] = 1e6\n",
    "cshock = uclchem.model.CShock(\n",
    "    shock_vel=40, param_dict=param_dict, previous_model=shock_start\n",
    ")\n",
    "cshock.check_conservation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d61c755d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:30:08.892756Z",
     "iopub.status.busy": "2026-06-19T14:30:08.892589Z",
     "iopub.status.idle": "2026-06-19T14:30:10.076728Z",
     "shell.execute_reply": "2026-06-19T14:30:10.075741Z"
    }
   },
   "outputs": [
    {
     "data": {
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+B+EFfB7CC3L6edjZmbmVMF1VNeaNhBs3blTgw2u+8+fP5+tkV6ZNG35vOzqcuUnTIfxdiJzad98Rl+fH49pg7II1ln//d+mCC4a6cb38svT//p90wgnSffdJ4fDQPju7CY402rS2VnrppeHtiezrU74Mcb399tv6/Oc/L0naZ5999MYbb+jcc8/VIYccol//+temfX/84x/r4x//uH7729/qpptu0p577qnnnnvOlVGKqVRKra2tmX+EI5GIIpFIzusAAAAW6bT01oPSE9+V2taMvW8gJNU0SDP3lGbuMfzfGXtIFTNyUi78K2ntxBWhE5fjnLhe4pFOXCFLiCvZRYgL8INYLJa5qS2RSCgUCrlbEBxXXFysLVt8MtbbBel0OvM1E/DIv9EoPHwewm18DsIL+DyEF+Ts83BgQLPj8czmtoEBpcb4nr6mpkYHfziubNasWXz/vwvTS0u1M37S8d576s+j94u/C5FLMwYHR1wf9+felVdKe+wx3E3w3HOlvfaS/uEfpJ/9TPrnfx5a3/n3XdEI8aRwWEokhn4PFwhMbF+f8mWI66CDDtKqVavGvf/555+v888/38GKxqe9vV2NjY2Z7WuuuUbXXnutewUBAABp/fPS4/8qbRwt3R+Q9v87ae/ThwJbNVGpaJx3KAATlLS0/w5WVblUiY/5+Ic/KzpxAf7U3Nys7373u5ntWbNmuVgNciEej6uurs7tMvLWzjvc6+rq+CUJXMPnIdzG5yC8gM9DeEHOPg+3bTNtztp9d8lynWannp4erVixIrO9cOFCvv/flZkzMw+nBQKalkfvF38XIqfeemvE5ffKysb3+o9/PHvt7/9e+spXpAceGA5x7Qx59fZm79/dLVVVDV+Xn8i+PuXLEFe+qqmpUUtLi6kTFwAAcMnWN4c6b/3tkdH32f146fhrpdn75awsFLZUp3WcIp24HGdL63Jvtj8nxAX4U1NTk5YsWSJJWrx4MZ24CgQX96cmEAhkPgC38HkIt/E5CC/g8xBekJPPw64u4wkVqKwcNZTw/vvvZ4I9oVBIc+bM4WtkV6YNXzMNdHXlXeCDvwuR18rKhj6MU0X22mvov+vXZ++/fv3w8xPd16eCbheAYcFgUA0NDZkPQlwAALhgcEB64BLp5k+OHuCqP1D6wv9J5/+RABdyytqJKzSt2qVKfCwXF0c8cgEmWFlh2k71EOIC/CASiWSuK4TDYQWDXPoBAAAAAE8xXuOrrh7zWtHGjRszj+vr67lRZzyqDddMjUESAPZZvXq405bR+vVDXbR233147bjjpJISydBVMHOMrVulU06Z3L4+xZU8AAAAowf/WfrzbVI6lf1cTYP02V9J//CU1Hh0risDlDTepSfGKeaEHZ24bOnmZb+Q5fMn2UWICwAAAAAAwHHWENcYNmzYkHk8f/58pyryF+N7arkpFoBNduyQfvYz6fHHh9f6+6XLLpOCQenrXx9enzZNamqS7r5b+utfh9aSSek735FmzJj8vj7FOEUAAICdNr0m/fXO7PXymdLRV0gfXyIVFee8LECS0omE0pY58KFpjFO0XSF14qpgnCIAAAAAAEDOGbtDEeKyn/GaKSEuwBl77SVdcIF01lnSwoXS9OnSqlVSKCTdead01FHm/a+7Tmpvlz75Senww4c6dqXT0iOPSDNnTn5fHyLEBQAAsNOy68zbRaXSEZdIn/yGVELHI7jL2oVLyu6kBCf4txNXsJIQFwAAAAAAQM5NoBOXcZzivHnznKrIXxinCDhv5kzpf/5HuvFGac0aadMmadYsab/9pKIRYkhFRUP7X3PN0GjEadOkj31sKPQ1lX19iBAXAACAJG14SVrzqHntqG9KR13uTj2ARXKECw7BXVzkwSTkokmWVzpxVVaYtpM9hLgAAAAAAAAcxzhFZ9GJC8id0tKh4NZ++41v/zlzhj7s3tdHCHF5SCqVUmtrqwIf/lInEokoEom4WxQAAIUgnZaW/Zt5rXymdNjX3KkHGEHK0okrUFKiYEmJS9UUEDu6aHm0E5e1k1uqixAX4AexWEyxWEySlEgkFCqQuxQBAAAAIG8Q4nKW8T0lxAUgzwTdLgDD2tvb1djYqGg0qmg0qubmZrdLAgCgIBS//7wCrSvNi5+6TCqpHPkFgAuSHeYLDiG6cDkikIMuWd7owyUFKxinCPhRc3Nz5rrCmjVr1NbW5nZJAAAAAAAjY7DI2DVqBIxTnATGKQLIY3Ti8pCamhq1tLSYOnEBAACHpdOqfOnH5rXqudLBF7hTDzCKVJc5xMUoxfyR9mgnLus4xXQ8rlQ8rmBxsUsVAbBDU1OTlixZIklavHgxnbgAAAAAwGvG2Ymru7s702lZohPXuDFOEUAeI8TlIcFgUA0NDTm5+x8AAHzob4+oeOtr5rWjvyWFS92pBxhFstM8TpFOXE4xfy/uSADLI9/vhyqzuw2menoIcQF5LhKJZG4KC4fD7hYDAAAAAMg2zhCXcZRiUVGR6urqnKzKP6zjFNNpz1yPA4BdYZwiAAAoXKmUtOw681pNVDrw792pBxhDstPaiavKpUowYd5sxKVgVfbnECMVAQAAAAAAHDbOENd7772XeTx37lw6LY+X8T0dHJT6+tyrBQAmiBAXAAAoXG/8SYGtq81ri/5FCtG1At5jHacYqp42yp6YEutdeU4EsDxy51+gpEQqMjdnTnV1jbI3AAAAAAAAbNHRMfx4jBDX+vXrM48XLFjgZEX+Ms1y3ZSRigDyCCEuAABQmJIJ6anvmddqPyrte7Y79QC7kOywhLhG6KIEj3JiJKMNAoGAQhUVprVkF524AAAAAAAAHDWJTlyEuCagtNR84yIhLgB5hBAXAAAoTH+9S9qx1ry26DtSkJbU8KakpRNXcNroF3gwBVmduBwIYHmkE5ckBS13JiY7O0bZEwAAAAAAALYYZ4jL2Ilrt912c7IifwkEzO9rB9e7AOQPQlwAAKDwDA5IK35gWkrP+Zi016kuFQTsWiqrExchLkxdyHKhMMWdiQAAAAAAAM6iE5fzjDcucr0LQB4p2vUuyJVUKqXW1lYFPrwzPxKJKBKJuFsUAAB+9PKvpc6N5rVjr/JUdxzAKtnVZdoOVTNO0RGOdOLy5jhFKTvEZR3bCSD/xGIxxWIxSVIikVAoRJdRAAAAAPAUOnE5z/i+EuICkEfoxOUh7e3tamxsVDQaVTQaVXNzs9slAQDgP/Ee6ZkfmpfqD5UaF7lUEDA+1jF3wTEu8MDjPBQYtY7lTNJeHsh7zc3NmesKa9asUVtbm9slAQAAAAB2isel/v7hbWPHKIPBwUFt3Dh8IzKduCaIcYoA8hSduDykpqZGLS0tpk5cAADAZi/eIvVsMy11Hdqk6R4KVQAjSXVaO3ER4soJOzpx2dLNyxmhavOFQmtYEED+aWpq0pIlSyRJixcvphMXAAAAAHiJpdv+aJ24Nm3apGQymdmmE9cEMU4RQJ4ixOUhwWBQDQ0NmRAXAACwWV9MevZG01J69xOUqP+4O/UA45ROp5W0XGwgxOWQXHwr7qHv90OWuz1TjFME8l4kEsncFBYOh90tBgAAAABgZg0UVVaOuJtxlOLMmTNVXl7uZFX+wzhFAHmKcYoAAKBwPPdTqd/SZebY77hTCzAB6d5eyXDnncQ4xdzxeScu6zhFLmoBAAAAAAA4x3jtpapKCo7863pjiItRipPAOEUAeYoQFwAAKAzd26QXbjavffQMqf5AV8oBJmKkYA2duBySiy5Z3mnElRUGTHJRCwAAAAAAwDnGay9jXN977733Mo8JcU0C4xQB5ClCXAAAoDCs/LGU6BneDgSlRXThQn5IdnaZFwIBBUdptQ57pW3oomXHMZwSqjaPU0x2EuICAAAAAABwjDFQNEaIy9iJa7fddnOyIn9inCKAPEWICwAA+F/H+1LLL81r+58rzfqIO/UAE5SyBGuCVVUKjNJqHVMTyEEnroCHWnFZxymmOrioBQAAAAAA4JhxhrjoxDVFjFMEkKf4zQ8AAPC/p38gJQeGt4Nh6Zgr3KsHmKBkl7kTV6iqyqVKCpAdTbS824hLoWnWTlydSqdSLlUDAAAAAADgc5PoxEWIaxIYpwggTxHiAgAA/tb2rvTKb81rH/uCVNPgSjnAZCQtFxqC00a/wIOpykGXrBx0+xqvkPViYSqlVE/PyDsDAAAAAABgasYR4kqn04xTnCrGKQLIU4S4AACAvy3/Lyk1OLxdVCoddbl79QCTkLJcaAhVEeLKmbQNbbTsOIZDgpZOXJKUZKQiAAAAAACAM4zX+Ua4LiNJ7e3t6jHcZEcnrklgnCKAPFXkdgEYlkql1NraqsCHd+ZHIhFFIhF3iwIAIJ8NdEur/mheO/QfpOp6d+oBJinZaRmnOEardUxRLrpkeagTV7CiQgqFpGQys5bq7JA0172iAExJLBZTLBaTJCUSCYVCIXcLAgAAAAAMG0cnLmMXrrKyMs2YMcPpqvyHcYoA8hSduDykvb1djY2Nikajikajam5udrskAADyW9cmKZ00r33yEndqAaYg2Wm+WyxYXeVSJQXIli5a3u3EFQgEFKoyfz4luTsRyGvNzc2Z6wpr1qxRW1ub2yUBAAAAAHaaYIhrwYIFmQYgmADrOEUPd8oHACM6cXlITU2NWlpaTJ24AOD/s3ff8U7V9x/H30lu7gZygcsG72UoKopVqqgFRxXFhasqjkqtWq1VcY9qcds6Ueuq2qo4K26xrv5UFKlibRVcRbhX9roDuDs35/z+uJCbk9wL93KTnJHX8/G4D/L95tzkAyR3JO/z+QDogtgxipsV9E5/HUAXGQmduNputY4kyLBOXJIU6NFDkU1deyTGKQJuN3XqVE2ZMkWSNGHCBDpxAQAAAICTxJ48106Ia8mSJdHLjFLcRrH/toYh1dZKhYX21QMAHUSIy0H8fr9KSkpIUwMAkCzxIS5fwHHhCaAjInEtvwN04nIXh5/p5w/1kFpP8FSkusq+YgB0WSgUip4UFgwG7S0GAAAAAGDVyU5cQ4YMSXVF3tQj7iTYDRsIcQFwBcYpAgAA74oPcfnJr8OdjLgQl7+dF3iQBPE5z1QEsBwWJs0q6mlZN1dW2lQJAAAAAACAx8V0Q1c7U5noxJUEOTlSdnbregOd5wG4AyEuAADgXRFCXPCGxE5chLiQPIFe1hBXpJJOXAAAAAAAACkRG+KK7xa1SWwnLkJcXRD7GmrsGEsAcDBCXAAAwLvoxAWPiGzcaFkT4kqhhC5ZSejE5fBxilk940NcdOICAAAAAABIidgwUTuduBinmCSxITk6cQFwCUJcAADAuxJCXAF76gC6yIg7U8zfjRCXqzlrmqIC8eMUqwhxAQAAAAAAJJ1pbnWcYn19vdasWRNd04mrC2JPhCXEBcAlCHEBAADvig9xBYL21AF0gdncLKOuzrIX6EGIK1V8cZ24zCR00UrGbaRSoGeRZc04RQAAAAAAgBSorZUikdZ1GyGuJUuWRC/7/X4NGDAgDYV5FOMUAbgQIS4AAOBdRsS6ZpwiXCh+lKIk+Qu72VAJksXnsFZcjFMEAAAAAABIg9guXJJ13N8mZWVl0cuDBw9WMMiJyduMcYoAXIgQFwAA8C7GKcIDjJqahL1Ad0JcaZOMLlpO78SVME6xyvHdwwAAAAAAAFwnthtUbq6Uk5NwSHl5efRyaWlpGoryMMYpAnAhQlwAAMC7jLB1TScuuFBCiCsQkC83155iMkIaumT5HNaJq5c1xKXmZhm8sAUAAAAAAJBcsZ242hilKFk7cRHi6iLGKQJwId7JdBDDMFReXi7fpjd1QqGQQu18AwcAAB2Q0ImLH33gPvHjFAOFhdGfF5EGyWhI5fCmVoG4cYqS1FxZqUAbLf0BOF91dbWqN70xEA6HFQjQiRQAAAAAHCE2xNXO6y6EuJKIcYoAXIhOXA5SVVWloUOHqrS0VKWlpZo+fbrdJQEA4G5GxLomxAUXiu/E5S8stKmSDJGOgJzDQnj+3Fz58vMte5GqKpuqAdBV06dPj76usHDhQlVUVNhdEgAAAABAsnaD6kAnrpKSktTW43WMUwTgQryT6SBFRUWaN2+epRMXAADoAjpxwQMSQlzdutlUSYYyM6AVl6SsoiKF6+qi60hlpY3VAOiKqVOnasqUKZKkCRMm0IkLAAAAAJyCcYrpxThFAC7EO5kO4vf7VVJSwngcAACShRAXPCB+nKK/sMCmSjJEBnbiklpGKoaXL4+umwlxAa4VCoWiJ4UFg0F7iwEAAAAAtNpKiGvjxo2WbsqEuLqIcYoAXIhxigAAwLsIccEDjJpayzpQSCeutEpGJ66kdPNKrayePS3rCOPXAAAAAAAAkis2xBUbMNqkvLw8ejk7O1v9+/dPfU1eRicuAC5EiAsAAHhXJGxdE+KCCxk1cZ24GKeYWhnaiSurTx/LunntWpsqAQAAAAAA8KjYIFEbnbhiRylut9128vt5K79LiopaL1dV2VcHAHQCX/kBAIB3GRHr2h+wpw6gCxinaLcM6cRVXGxZh9essakSAAAAAAAAj9rKOMXYEBejFJOAEBcAFyLEBQAAvItxivAAximmWTqaZDmvEVdiJ641dOICAAAAAABIqq2MUyTElWSxQbmGhpYPAHA4QlwAAMC74kNcgaA9dQBdYCR04iq0qZLMZLqgi1YyJIa46MQFAAAAAACQVFvpxFVeXh69TIgrCWI7cUnWf38AcChCXAAAwLvoxAUPiNTWWNb+boS4UsnnS36bLDcEwRJCXGvXyjQMm6oBAAAAAADwoPXrWy8zTjH18vKk7OzWNSMVAbgAIS4AAOBdRsS69gfsqQPoAmOjNcQVoBNXeqUggOVz4DzFrD7F1o1IRJHKSnuKAQAAAAAA8KItdOIyTdMS4iopKUlLSZ7m81m7cRHiAuACtKMAAADeZYStazpxwYWMmrhOXIXdbKokU6QgYOWGTly9ekl+vxTTfat5zRpl9e5tY1UAAAAAAAAeEhvi6tHDclVlZaU2btwYXdOJK0mKiqTVq1suE+IC2lVdXa3qTV+j3DBZwsvoxAUAALyLcYrwgEhciCvAOEX3S8HIxq7yBQIJga3wmjU2VQMAAAAAAOAxDQ1SY2PrOq4TV3l5efRyQUGBenNiXXLQiQvokOnTp6u0tFSlpaVqampSJBLZ+ichJQhxAQAA7yLEBZczTbONTlyEuFIqPmCVjJOOXHLiUlafPpZ1MyEuAAAAAACA5Fi/3rqOC3HFjlIsLS2Vz4EnAbpS7L8zIS6gXVOnTlVZWZnKysqUnZ2tQCBgd0kZi3cyAQCAdxlxZwoQ4oLLmPX1UtwZL/5ujFN0PYe+CJcQ4lpNiAsAAAAAACApYkcpBgJSfr7l6vgQF5IkthNX7P8BAItQKKTQptAjIVJ70YkLAAB4F5244HKRjTUJe/6CAhsqySAJnbiS0EYrGbeRBsF+fS3r8MqVNlUCAAAAAADgMbEBolAo4TWo2BBXSUlJWkrKCIxTBOAyvJPpIIZhqLy8PJpsjE07AgCAbUCICy5n1CaGuAKMU3Q/h57JFBw40LIOL1tmUyUAuqK6ulrVm94cCIfDtL8HAAAAACeIHafYxvu/dOJKEUJcAFyGTlwOUlVVpaFDh6q0tFSlpaWaPn263SUBAOBukbB1TYgLLmNs3GhZ+3Jz5QsGbaomQyWli5ZLOnHFh7iWL7epEgBdMX369OjrCgsXLlRFRYXdJQEAAAAA4jtxxSkvL49eJsSVRIS4ALgM72Q6SFFRkebNm2fpxAUAALrAiFjXfjpRwF3ixyn6u9GFK+XS0SXLsZ24BlnW4VWrZDY3y5fFr42Am0ydOlVTpkyRJE2YMIFOXAAAAADgBLEhrh49LFeZpkmIK1UIcQFwGV6NdxC/36+SkpJoiAsAAHQR4xThckaNNcQVKOxmUyUZLBmduJLSzSv1goOsnbgUiSi8arWy4/cBOFooFIqeFBakeyMAAAAAOMMWximuWrVKDQ0N0XVJSUl6asoEsf/WhLgAuADjFAEAgHfFh7gCvJEJdzFqrOMU/YV04kq5dJxP4dBzNgKhkPz5+ZY9RioCAAAAAAAkwRbGKZaVlUUvFxUVqUdcpy50QWwnrtj/AwBwKEJcAADAu+jEBZeLxHfiYpyiDTKnE5fP51NwoLXrVnjZMpuqAQAAAAAA8JAtjFNcvHhx9DKjFJOMcYoAXIYQFwAA8C4jYl37A/bUAWwjY6M1xOUvIMSVaukYbe7k8enBQYMsazpxAQAAAAAAJMEWOnEtWrQoenn48OHpqSdTxIa4amqkcNi+WgCgAwhxAQAA76ITF1wuYZxit242VZK5TJd00UqW+E5cTUuW2FQJAAAAAACAh6xf33o5LsT1ww8/RC8T4kqy2BCXxEhFAI5HiAsAAHiXEXdWDSEuuEz8OEV/YYFNlWSQFHTJclMQLLukxLJuimnnDwAAAAAAgG0UO8pvC524hg0blqaCMkRhoRSImdDBSEUADkeICwAAeBeduOBy8eMUA4V04kq7lOSvnDtOMWfYUMu6saxMpmHYVA0AAAAAAIBHVFa2Xu7Z03IVnbhSyOezhuYIcQFwOEJcAADAu4yIdU2ICy5jxHfiYpxiGqQgYOWeRlzKHmo929Osr1fzypU2VQMAAAAAAOAR7YS4NmzYoLVr10bXdOJKgdiRioxTBOBwvJMJAAC8i05ccDnGKTpAKkYhpmBkY7Jk9SmWv7DQEiBsXLxYwYEDbayqfeGVK1X76acym5rk8/sln7/l39fvs6x9fp+0ee33yefbvN58nK/1uvY+z6eW6zatfX6ffMGglJUlXzBbvmBQvuxgy5/BoHxZWfLFtusHAAAAAACZyTTbDXHFjlLMy8tT//7901lZZogNcdGJC4DD8U4mAADwLkJccLn4TlwBOnGlXioCVqkIgqWIz+dT9rChavjyq+he46JFKhw3zsaq2lb/5Zda8uszE54njuL3t4a6Nge7Nl/ODkrBoHxZrWt/Xr78+Zs+8vLkL2i57MvLkz+/oGW/oECBopCyevZUoGdP+XNy7P5bAgAAAACALamtlZpjXquOCXHFjlIcNmyY/H4GaSUdIS4ALsI7mQAAwLsIccHljI0bLWt/QaFNlWSwDOvEJUk5Q4dZQlxNMWeEOkXzunVadv4Fzg5wSZJhyGxslNnYmLK78OfnK7Ap0JVVVLTpcpGyevVWcPAgZQ/ZTtmDB8mfn5+yGgAAAAAAwBbEduGSLKGi2E5cjFJMEUJcAFyEdzIBAIB3RQhxwd3ixykGuhHiSrmUBKzc04lLknKGW18wbPjue5sqaZsZDmvZ1KlqXrPG7lIcwairk1FXp/CyZVs8LlDcW9mDhyh7yBAFhwxuubzdEGVvt50CPXqkqVoAAAAAADJQbIirsFAKBqPL2E5cw4cPT2dVmSMUar1MiAuAw/FOJgAA8K6ETlwBe+oAtoHZ3Cyzvt6y5y8kxJV2GdiJK3ennSzrxu++k9nUJF92tk0VWa2+/XbVf/5vy17WgP7KKi6WDLOl+5VptGTnDKOddctxMs2W64zYtRk9Ln5tmmbLY8IwZBqGdRSCw0XWrlP92nWq/+KLhOuCgwcrb5ddlLvrLsrbdbRyd9pR/txcG6oEAAAAAMCDYkNcMaMUpcRxikgBOnEBcBFCXAAAwLviQ1yBYNvHAQ7U1pg4f7duNlSSYVLSiMtdnbhyd97ZsjbDYTX8b6HyRu3czmekz/rXX1fVkzMse1kD+qt05kxlxb0Img6maUrhsMzNH83NrZc3r5vCcXstfyZ8XmOjjPp6GbV10e5aRn29jLpaGXV1MuvqZdTVKbJxoyJVVS3BsiQJL12q8NKl2vDmmy0bWVnK2X6E8nbdVXm77Kq8XXdR9tCh8gUIQwMAAAAA0GmxwaG41y9ixynSiStFYkNc1dW2lQEAHUGICwAAeFdCJy5+9IF7RGpqE/YCdOLyBod34gp0767s7bZT048/RvcaFiywPcTV8O23WnntHyx7vuxsDbrnXlsCXJLk8/mk7Oy0dykzDUPGhg1qrqxSpKpSzZWVisRdbl61Sk1Ll6p59erO30Fzsxq/+VaN33yr6ueel9TSCbBgn31UuN9+KtxvvLJ6907y3woAAAAAAI9qpxNXfX29li1bFl3TiStF6MQFwEV4JxMAAHiXEbGuCXHBRYyajdYNv1++/Hx7iskkCQGrJHTRclknLknK3WUXS4irfsF8FelE2+qJVFdr2fkXyGxosOz3mzZNebuMsqkq+/j8fgVCIQVCIUmlWzzWaGhQeOlSNS1dqqYlSxReskRNS5aqaekShZev6PBISKOmRhvfeUcb33lHUstjpHD//VS43/7K3WlH+fz+Lv6tAAAAAADwqNgQV0ygqKysLHo5KytLQ4YMSWdVmYMQFwAX4Z1MBzEMQ+Xl5S1nc0sKhUIKhUL2FgUAgJsldOJiDBTcw9hoDXH5CwujPyfC5Vzw35g7amdteOON6Lp+3ue21WJGIlp+6WUKx5yZKkmhyScpdNyxNlXlHv7cXOWMGKGcESMSrjPDYTUuWqT6r75S/VdfqeGr+Wr84YcOjWpsmD9fDfPna919f1ZWcbEK9huvbvvvr4K995a/oCAVfxV0UHV1tao3jYcIh8MKMAYTAAAAAOzVTieuH374IXq5tLRUWVm8dZ8ShLgAuAjfCRykqqpKQ4cOja6nTZum6667zr6CAABwOyNsXdOJCy4SqamxrP2FhCLsYCahi1YybiPd8n/6U8u66ccfFV6+XMGBA9Ney9r77lPtxx9b9vJGj1a/q65Key1e4wsGlTtypHJHjlTRCSdIkozaWtV//bUa5s9X/VfzVf/VV2peuXKLt9O8dq3Wz3xR62e+KF92tgp/fqBCxxyjgn32kY8XoNNu+vTpuv7666Pr4uJiG6sBAAAAAFiCQ+2EuBilmEKxTVMIcQFwOF5NdZCioiLNmzfP0okLAAB0QUInLn70gXsYcSGuQGE3myrJLOnoduZzQSuu3B13VCAUUmRTNx9Jqp07V6Hjj09rHRvfe08VDz1s2Qv07q2B994rX3Z2WmvJFP6CAhXsuacK9twzuhdevUa1H3+smg8+UO2cOTLq6tr9fLOpSRv/8ZY2/uMtZRUXq8eko9TjmGOUw4vRaTN16lRNmTJFkjRhwgQ6cQEAAACA3drpxLVo0aLo5eHDh6ezoswS24lr/XopEpH4XRmAQ/FOpoP4/X6VlJQwJgcAgGQxIta1P2hPHcA2iA9x+QsLbaokw7mviVZS+Px+5e89Vhv/8VZ0r2bOnLSGuBoXl2nFFVdaN7OyNGj63Qr27ZO2OiAF+/ZR6LhjFTruWJlNTar7/HPVfPihNn7wgcI/Lmn385rXrlXFo4+p4tHHlLvrrgodc7S6H3aYAj16pLH6zBMKhaInhQWD/OwDAAAAALbrwDhFOnGlUGyIS2oJcsX8PwCAk/jtLgAAACBlEjpxcXYN3COykXGK9kjBCRUuDYIV7L23ZV3z4WwZ9fVpue9ITa2WnX++jNpay37fK65Q/pgxaakBbfNlZ6tgn33U96qrNPzttzX0H2+qz5VXKH/sWGkLoxMbvvpKq66/QQvHjdfyiy9WzUcfyTSMNFYOAAAAAIBNYkNcMYEiOnGlSY8eUmwTlZjO8wDgNIS4AACAdzFOES4WH14J0InLHmYKElgu6bzb7YADJH/rr4xmXZ1q3n8/5fdrmqZWXnWVmmJeyJSkHpOOUtGpp6T8/tE5OaWl6jVlirZ7/G/a/uOP1PcP1yp3l13aPd5satKGN/+hpWedrbLDj1Dj66/LaGhIY8UAAAAAAKRZVVXr5U0doMLhsMrLy6PbhLhSyO9vCXJtFvv/AQAOQ4gLAAB4k2kS4oKrGXV1lrW/gE5caZGKgFUqgmBpkFVcrIKxe1n21r8xK+X3WzXjKW18913LXs6OO6rfddcxet7hAqGQep58skpf+LuGvv6aev76DAWKe7d7fFN5ueruvEuLfn6Q1j7wgJp5ERUAAAAA4EVtjFP88ccfFYlEJEk+n0+lpaV2VJY5Ykcq8voDAAcjxAUAALzJiCTuEeKCi8R34vLn59tUSYbL4E5cktT98CMs65qPPlJk/fqU3V/D//6nNXfcYdkL9OihQffdK39eXsruF8mXM2KE+l52mUa8/74GPfSguh1yiHzBYJvHRiorte7e+/TDAQdq1Q03qmnJkjRXCwAAAABAijQ1STU1retNIa7YUYqDBw9WTk5OuivLLKFQ62VCXAAcjBAXAADwpvguXJLkD6S/DmAbJYS46MSVHnTisuh28EHW4E04rA3vvJOS+zIaG7Xi0stkNjVZ9gfccbuyBw1KyX0i9XxZWeq2//4adM90DZ/9ofpee41ydtihzWPNhgZVPfOMFh06UcsunKr6L79Mc7UAAAAAACRZfGBoU4jrhx9+iG4NGzYsnRVlJjpxAXAJQlwAAMCb2gpxBdruAAI4ESEuh8jwTlyB7t1VuP9+lr0Ns95MyX2tvetuNf7vf5a9nlOmqHDcuJTcH9Ivq6hIPU85RaWvvKzBjz2q/H32aftAw9DGt99W+YknqfzUU1X7r0/TWygAAAAAAMkSGxgKBqVN3fZjO3ENHz483VVlHkJcAFyCEBcAAPCmNjtxMU4R7mHU1VnWhLjSJCX5Kvd24pKk7ocfblnXffqpwqvXJPU+aj6eo8onnrDs5eywg4ovviip9wNn8Pl8Ktx3Xw157FF1e/QRdT/ySCmr7e/R9Z//W0umTNGSM89Sw7ffprlSAAAAAAC6qLKy9XLPntGT+2I7cRHiSoPYEFd1tW1lAMDWEOICAADeZEQS9whxwUUSOnFtOksP6ZbZnbgkqXD//a2PP9PUxrf+kbTbb66q0sqrrrLs+XJyNPCO2+XPzk7a/cCZsoYP14Db/qTh776jnr/6VbuB1dqPP1bZMcdq+WWXq2nZsjRXCQAAAADANooPcW2ycOHC6GXGKaYBnbgAuAQhLgAA4E104oLLMU7RJqkIWKViJGMa+XNz1e3ggyx765M0UtE0Ta289lo1r11r2e9z6aXKGTEiKfcBdwj276++V1yu4R+8rz6XXaqsPn3aPG7D669r0cTDtOrmW9Qc+0I4AAAAAABO1EaIq7m52TJOcfvtt093VZmHEBcAlyDEBQAAvMkIJ+75A+mvA9hGhLicwUxFAMtdjbgkSd2POMKybvjqKzX9+GOXb7d65kzVvPdPy17BuHEqOvWULt823CnQrZt6/frXGv7eu+p33TQFinsnHhQOq2rGDC06eILWPvBAwtdLAAAAAAAcIzYwtCnEVVZWpnC45fVrn8+nEZzIlnqhUOtlQlwAHIwQFwAA8CY6ccHljLo6y5oQV3r4UtCJKyVBsDQrGDtWgZiW/5K04c2udeNqLCvT6ltutewFioo04JabU/L/AHfxZWer6KSTNPztt1U89cI2vwYatbVad+99+uGQQ1X59NMyw20EuAEAAAAAsFMbnbi+++676FZJSYlyc3PTXVXmoRMXAJcgxAUAALzJiCTu+YPprwPYBmZzs8zGRsuePz/fpmoyXEoacbkvoOQLBtX90EMse+vfmLXNATUzHNaKyy6XWV9v2e9/883KKi7e5jrhPf78fPU+5xwNe+9d9Tz9dPmCid/LI+vWafWNN6ns+F+o/quvbKgSAAAAAIB2xIa4NgWJvv/+++jWyJEj011RZiLEBcAlCHEBAABvohMXXKyt0WB04kqTVHSA8kAnLilxpGLTokVqjHnRsTPW/vl+NSxYYNkLnXSiuh14wDbXB2/LKipS36uu1LC3/qEekya1+Vxt/P57lZ94klbdeJMiNTU2VAkAAAAAQJytdOLaYYcd0l1RZooNcVVX21YGAGwNIS4AAOBNCSEun+TnRx+4AyEuB0lFAMulowLzdttNWQP6W/Y2vPFGp2+nbt48VfzlL5a97NJS9b3iii7Vh8wQHDhQA/70R5W+8rIK99sv8QDTVNXTT2vx4Udo43vvpb9AAAAAAABixXZ92hTiohOXDeJDXB456RKA9/BOJgAA8Kb4EBdduOAibYa4GKeYJu4MWKWDz+9Xj8MPt+ytf/NNmYbR4duIbNig5VdcYX2hLBjUgDtulz8vL1mlIgPk7rCDBj/8kIY8+YRytt8+4frm1au17Hfna+nvfqfwqlU2VAgAAAAAgNrsxBUb4qITV5rEhrgiEWnjRvtqAYAtIMQFAAC8KUKIC+5l1NVZ1r68PPkCAZuqQZd56MS+7nEhruYVK1X/n/90+PNXXX+DmlestOwVX3C+8nbeOSn1IfMU7LmnSl+cqeJLLpYvJyfh+pr3/qnFhx+hyhlPyYxEbKgQAAAAAJDRYkNcRUWqrKzU2rVro1t04kqTHj2s69gOaQDgIIS4AACAN9GJCy4W34mLLlw2YpyiRc4OOyh7+DDL3oZZszr0uZVPPplwbP6ee6rXGWckrT5kJl8wqN5nnaWhr7+mgn32SbjeqK3V6ptvVvnkk9UQc7YzAAAAAAApt25d6+XevS1duLp3766+ffvaUFQGCgalbt1a17HhOgBwEEJcAADAm+JDXAFCXHCPSHyIq6DApkoyUCoCVqkIgtnE5/MljFTc8I+3ZIbDW/y8De++q9W3/tGy5+/eXQP+9Ee6zCFpsocM0eDHHtWA229TYNOIilgNX32lsmOP09oHHqArFwAAAAAg9cJha8en4mJ999130eXIkSPlc/HJfq7Tu3fr5dhwHQA4CCEuAADgTXTigosldOIixGUfOnEliB+pGKmqUu2//tXu8fVffqkVl12e8G/Z/4brFezfPyU1InP5fD71OPJIDZ31hnocd2ziAZGI1t17n5b86gyFV69Jf4EAAAAAgMwR3+0prhPXDjvskOaCMhwhLgAuQIgLAAB4EyEuuJhRV2dZ+wsYp5g2KQlYeacTl9TS7Sh3110texveeKPNY5uWLtXSc38rs6HBsl984QXqfuihKasRyCoq0oCbb9aQJ55QdklJwvV1n32msqOPVs2HH6a/OAAAAABAZli7tvVyXp5UUJDQiQtpVFzcejn2/wYAHIQQFwAA8CYjbkwSIS64SEInrnxCXLahE1ebehxh7ca18d33ZMQFtSLV1Vp69m8UiTvrtMfxx6nXOeekvEZAkgr22lOlr76i3r89V4ob3RmpqtLS35yj1X+6TWZTk00VAgAAAAA8K7bb06YuUHTishGduAC4ACEuAADgTUbYuvYH2j4OcCDGKdooJY24vNWJS5K6HXqo5G/9ddKoq1PNBx+0rhsbtfR3v1NTWZnl8wr23Vf9p02TzwNBNriHPydHxRdcoO1mPKmsNkZ4Vv7tbyo/+RQ1LVliQ3UAAAAAAM+K7fZUXKxwOKxFixZFt+jElWaEuAC4ACEuAADgTYxThIsZtfHjFAlx2cVMxShED+SXgn36KH+vPS17G2bNkiSZhqGVV12t+s//bbk+Z4cdNPCe6fIFg2mrE4iVv/vuGvrySyo86OcJ1zUsWKCyY47VhjfftKEyAAAAAIAnxYa4evdWWVmZwuGWk4/9fr+GDx9uU2EZinGKAFyAEBcAAPCmhBAXoQG4h1Fn7cQVIMSVNqnoEGV6sBOXJPU43DpSseaDDxXZsEFr756eEITJ6ttXgx9+SIHCwnSWCCQIhEIadN996nvtNQmBQqO2VssvvkQrr71WRn29TRUCAAAAADwjtttTcbFllGJpaalycnJsKCqD0YkLgAsQ4gIAAN5kRKxrOnHBReI7cfny822qBKkYhejzQisuSd0OPtgSgjHDYS2/+BJVPPKI5Th/QYEGP/yQgv36pbtEoE0+n089TzlFJX9/XtklJQnXV78wU2W/+IUaY0ZcAAAAAADQaXGduL777rvococddrChoAxHiAtoV3V1tcrLy1VeXi7TND17YrIbEOJyEMMwok+M8vJyVVdX210SAADuldCJK2BPHcA2MGrpxGWbFHTiSkUQzAkCPXqoYPx4y17txx/HHRTQwOnTlTtyZBorAzomd8cdVfriTPU4+uiE65p+WKTykyar9l//Sn9hXRT7ols4HJZhGHaXBAAAAACZKTYo1Lu3pRPXSF4rST/GKQLtmj59ukpLS1VaWqqmpiZFIpGtfxJSghCXg1RVVWno0KHRJ8f06dPtLgkAAPdKCHHRiQvuER/i8hPisk8q8lepCIrZpMcRh2/x+v7XX6fCcT9LUzVA5/kLCjTgj7dqwJ/+mND10Ni4UUvOPEvVL75kU3XbJvZFt4ULF6qiosLukgAAAAAgM8UGhYqL6cRlt/hOXB498RLYFlOnTlVZWZnKysqUnZ2tQIDGCHbh3UwHKSoq0rx58+Tb9KZOKBSytyAAANwsErauCXHBRYw66zhFQlzplIpOXMm/Saco3H9/+fPzEx6zktTrnN8odPzxNlQFdF6PSZOUu+uuWn7xJWr89tvWK5qbtfL3v1fT0iUqvvDC6O/rTjZ16lRNmTJFkjRhwgRedAMAAAAAu9CJy1liQ1yRiLR+vcT78YCklmzK5nyKG17/8jI6cTmI3+9XSUlJ9IMQFwAAXWDEtXolxAUXSejEFdcdBmmUijPyPPRLsD8vT4UH/Txhv/uRR6r4wgttqAjYdjmlpSp55ml1O/ighOsqHnpYKy69TEZjow2VdU4oFIq+rhAMBuX389IPAAAAANgiphPX+uxsrYsJddGJywZFRVLs78iMVATgQLySBwAAvCl+nGKAEBfcg3GKNkpFwMrjrdmLTjjBss7fc0/1v/kmztiCK/nz8jTwnnvU84wzEq7bMGuWlvzqDDVXVdlQGQAAAADAVUzT0olr8YYN0cuhUEh9+vSxo6rM5vdLvXq1rmM7pQGAQxDiAgAA3hQf4qITF1yEEJeD0Ilrq/LHjFH/m25U3h57qOjkyRr0wP3yZ2fbXRawzXx+v/pefpn6XTdNihtFWP/FFyo/8SQ1lpXZVB0AAAAAwBU2bpSamqLLb+O6cHHym01iRyoS4gLgQIS4AACANxHigkuZzc0y48Z1EeJKI15A2yah449XydNPqd8f/qBAYaHd5QBJUXTSSRr80IMJX4PDS5box5Mmq27ePJsqAwAAAAA4XmxAyOfTV8uWRZeMUrRRcXHrZcYpAnAgQlwAAMCbjIh1TYgLLmHU1SXs+fPzbagEkpLTicvj4xQBLyscN07bPfO0svr1s+xH1q/XkjN+rfWvv25TZQAAAAAAR4sNCPXsqe8WLowuR44caUNBkEQnLgCOR4gLAAB4kxG2rv2Bto8DHCZ+lKJEJ660SkcjLrp9Aa6Su8MOKnn+eeXstKNl3wyHteKyy1Xx2F9tqgwAAAAA4FixAaHevfX1119Hl4S4bESIC4DDEeICAADexDhFuFSbIS46cdkoGV206MQFuF2wbx+VzJihwgMOSLhuze23q+Kvf7OhKgAAAACAY8V04or06qVFixZF16NGjbKjIkiMUwTgeIS4AACANyWEuIL21AF0UnyIy5ebK18WIURPoREX4Er+ggIN+vN9KjrttITr1tx2myoefzz9RQEAAAAAnCmmy9PG7GyZZstJfrm5uRo6dKhdVYFOXAAcjhAXAADwJiNiXdOJCy5h1NVZ1nThSi9fKkYdmnTiArzCFwio3++vVp/LLku4bs0f/6TKJ56woSoAAAAAgOPEdHmK7fe04447KhAIpL8etCDEBcDhCHEBAABvSujExS/GcIf4Tlz+ggKbKoGk6FmSyZSSoBiAtOr16zPU5/LLE/ZX3/pHVT45w4aKAAAAAACOEhMQWtrQEL28884721ENNmOcIgCHI8QFAAC8KSHERScuuAMhLpulIGCViiAYAPv1OuNX6nPZpQn7q2+5RZVPPW1DRQAAAAAAx4gJCC1avz56mRCXzejEBcDhCHEBAABvioSta0JccIkIIS5nSUn+ik5cgFf0+vWv1efSSxL2V990kyqfJsgFAAAAABkrJiD0bUyga9SoUXZUg81iQ1zr10vhcPvHAoANCHEBAABvMiLWNSEuuIRZV2dZ+/PzbaokU6UgYEUjLsDTep15poovvjhhf/WNN6nymWdsqAgAAAAAYLuY4NY3MYEuOnHZLHacokQ3LgCOQ4gLAAB4U/w4xQAhLrgDnbgcJhWjEFMwshGAvXqffZaKp05N2F99w42qeu659BcEAAAAALBXTDho86X8/Hxtt9129tSDFvn5Ul5e65oQFwCHIcQFAAC8KT7ERScuuISREOKiE1dapSJglYogGADH6X3Ob1R84QUJ+6uuu15Vz//dhooAAAAAALYIh6Xq6uhyc0+unXfeWX4/b8/bLnakIiEuAA7DdwkAAOBNhLjgUokhLjpx2YpOXAA6ofe556r3+b9L2F81bZqqX3kl/QUBAAAAANKvosKy3BwTYpSiQ8SOVIwZewkATkCICwAAeBMhLriUUVdnWfvz6cSVVnTiAtBFxeedp96/Swxyrbz2D6r7/HMbKgIAAAAApNXq1dGLDX6/Nr/aR4jLIejEBcDBCHEBAABvSghxBeypA+gkOnE5DJ24AGyD4t+dp96//a11MxzWst+dr6alS+0pCgAAAACQHqtWtV6MeR2IEJdDEOIC4GCEuAAAgDfRiQsuZdTGdeIixJVe5KsAJEnv83+nnqefbtmLVFdr6bnnKlJTY1NVAAAAAICUiwlxLYtEopd33XVXO6pBvNhxioS4ADgMIS4AAOBNCSGuoD11AJ0U34krQIjLXknpxMU4RSAT+Xw+9bn8MhXsN96y3/TDIi2/5BKZMS/kAwAAAAA8ZOXK6MXNca5evXppwIAB9tQDq9hOXGvX2lcHALSBEBcAAPAmI+6NUTpxwSWMOmsnLl9+vk2VZKh0jDqk2xeQMXyBgAbeeadyRgy37Nd+OFtrbr/DpqoAAAAAACkVO05x05+jR4+WLx2vO2HrGKcIwMEIcQEAAG9K6MQVsKcOoJPoxOUsZjK6aCWlmxcAtwoUFmrQgw8qUFRk2a98/HFVvfCCTVUBAAAAAFKmjRAXoxQdhHGKAByMEBcAAPCmhBAXnbjgDvGduPx04kqrtJwRyVmXQMbJHjRIg/58nxS0jndedf0Nqv30M5uqAgAAAACkRDuduOAQjFME4GCEuAAAgDdFwtY1IS64gGmaMuvrLXu+PEJctkpKIy46cQGQ8vfYQ/2vv9662dys5RdcoKYlS+wpCgAAAACQfDEhrpWb/qQTl4PEj1PktTsADkKICwAAeJMRsa4JccEFzIaGhD1/Xq4NlWSwNHTJ8olOXECmCh17jHqd+WvLXmT9ei0951xFNm60qSoAAAAAQFLFdeIKBALaaaed7KsHVrHjFBsbpdpa+2oBgDiEuAAAgDfFj1MMEOKC8xlxXbgkyZ+XZ0MliErGmXiczAcgRvFFF6nwwAMte02LF2v5RRfLbG5u57MAAAAAAK5QXy+tXx9drpK0ww47KDeXEzUdo2dP65qRigAchBAXAADwpvgQF5244AJGXWKIi3GKHpSGbl8AnMsXCGjAbbcpZ4cdLPu1H3+s1X+6zaaqAAAAAABJEdOFS5LWSBo9erQ9taBtWVlSUVHret06+2oBgDiEuAAAgDcR4oILmQ1tdeLiLL30igtYJaUTF624AFgFCgs0+IH7FejVy7JfNWOGqmfOtKkqAAAAAECXxYS41kpqlrTrrrvaVg7aETtSkRAXAAchxAUAALzJiFjXhLjgAvHjFH3Z2fIFAjZVg5ShExcAScGBAzXoz/fJFwxa9lfddLMaFy+2qSoAAAAAQJfEhLg2X6ITlwP17t16mXGKAByEEBcAAPAmI2xd+wnCwPnixyn68/JsqiSDpSJgRScuAO3I/8lP1P/mmyx7ZkODVlx6mcymJpuqAgAAAABss5gQ18pNf9KJy4FiQ1x04gLgIIS4AACANzFOES5k1NdZ1r78fJsqQVQqAlh04gIQo8dRR6no5MmWvYZvvtHa++6zqSIAAAAAwDZbuTJ6cZWk3r17a8CAAfbVg7bFjlNcs8a+OgAgDiEuAADgTQkhrmDbxwEOYtbTict2KclX0YkLwJb1ufxyZQ8bZtmrePQx1f7rU5sqAgAAAABsk7hxinvssYd8nNDnPP36tV6OCd4BgN0IcQEAAG8yItY1nbjgAkZ9g2VNiMsB6MQFIA38ubkaeMftUjAmdG6aWnHFFYpUV9tWFwAAAACgk+JCXLvvvrt9taB9sd3RCHEBcBBCXAAAwJsYpwgXShinmJdrUyUZjIAVAJvk7rij+lx0kWWvefVqrZx2ncxUBEoBAAAAAMlHiMsd+vdvvbxihX11AEAcQlwAAMCbEkJcAXvqADohcZxivk2VYDMzGaMQCV8A6KCeU05X/t5jLXsb335b619+xZ6CAAAAAACdYsQEgjaPU4QDxYa46MQFwEEIcQEAAG+KhK1rOnHBBYy6+BAX4xTTzZeOTlw0+wLQDp/frwF//KMCPXpY9lfddJOafvzRpqoAAAAAAB1imtLq1dFlXffuKikpsa8etC92nGJlpdTYaF8tABCDEBcAAPAew5Diu+cQ4oILGA0NljUhLgdISiMuOnEB6Lhg377qd9ONlj2zrk7LL7tcZjjczmcBAAAAAGxXWSl/c+uEiH677ZaeEwbRef36Wdd04wLgEIS4kuzVV1/VPvvso8GDB+vYY4/VsmXL7C4JAIDMEz9KUZICwfTXAXSSUV9nWfvyCXGlXRpeWOPFOwBb0/3ggxX6xfGWvYavvtLaBx6wqSIAAAAAwFatWhW92Chp+z33tK8WbFl2ttS7d+uaEBcAhyDElUSffPKJJk+erCuvvFKzZ89Wjx49NHnyZLvLAgAg87QV4vIH0l8H0Elm/DjFXEJctktGFy06cQHYBn2vvFLZ221n2at4+C+q+/xzmyoCAAAAAGxRTIhrlaQ9xoyxrxZsXf/+rZdXrLCvDgCIQYgrif7+979r4sSJOuqoo1RaWqrbb79dH3/8sb766iu7SwMAILO0GeJinCKcz6iPC3ExTtEG6eiSRScuAFvnLyjQgDtul7JifoYxDC2//HJFNmywrzAAAAAAQJvqysqil1dJ2n333e0rBlsXG+KiExcAh/B8iKuxsVGNjY0dOjYcDnf5vnJycqLrgoICSdL333/fpdsFAACdRIgLLpUQ4mKcov2S0omr6zcBIDPl7bKLis8/37LXvGKlVt1wo00VAQAAAADas/I//4leXpeVpWHDhtlYDbZqwIDWy4S4ADiEZ0NcpmnqgQceUO/evXXhhRe2e1xNTY3OP/98FRUVKT8/X0OHDtUDDzywTfe5//7766233tL3338v0zT15z//WX6/X1VVVdv61wAAANuCEBdcyowLcfnoxJV+vjR0yUrHfQDwjF5n/lr5cSM4Nrzxhta//oZNFQEAAAAA2lL1zTfRy5HiYvn9nn0r3hsYpwjAgTz5nWPx4sU64IAD9Prrr6umpmaLxx577LF67bXX9NFHH6mpqUk333yzzj//fN15552W43bYYQf17t27zY9LL71UknTCCSfojDPO0O67765u3bppyZIlGjJkiHr16pWyvysAAGhDmyGuQPrrADopoRNXLiEu2yWlExetuABsO18goAG3/Un+bt0s+6v/+EfGKgIAAACAg4QXL45eDpaW2lgJOoRxigAcyJMtKV555RVdccUV+ulPf6ri4uJ2j3vttdf07rvv6rnnntOoUaMkSZMnT9abb76padOm6de//rVCoZAkae7cuTIMo83bydvUIcHn8+mOO+7QbbfdpqamJtXU1Ogvf/mL9txzz+T+BQEAwJa1GeIKpr8OoJMYp+gAdOIC4EDBAQPU//rrtPziS6J7kYoKrb3nXvW79hobKwMAAAAAbJazenX0cq/Ro22sBB3COEUADuTJENfFF18sSVq3bt0Wj3vhhRfk9/t12GGHWfaPOuooPfXUU5o1a5ZOOeUUSVLPnj23er8LFizQLbfcoieeeELNzc266KKLdMwxx2jw4MEdqru8vDwaJmvrtgE4k2ma0Q8ADhFpVnxEwvQH2uyGw3MYTmLU11nWvtw8HptbkJrnr/W2knH7phl/MghfcwCJ78Gd1W3iRBW+8YZq/u/96F7Vs8+qxzHHaMyJJ7T5OYsWLdKwYcPSVSIAAAAAZKy1a9eqT2NjdL3dz35mYzXoEMYpAnAgT4a4OurLL79U37591S1uJMH2228fvX5ziKsjRowYod69e6tPnz5qaGjQscceq0cffbTDn2+appqb2+gcIml1THIbgLOYpqnq6mpJLR35ANgvUL1K8b04V6+tkPyJP/rwHIaTRGqtIa7qhgbV8nNgu1Lx/G1cv96ybm4Od/ln8fraWsu6obGRn+8B8T14W/jPOkv6eI7U1NSyYRha+oc/KNLcrLaicATkAAAAACA9PvvkEx0as+4zZoxttaCDYkNc69a1/K6dnW1fPQCgDA9xrVu3Tj169EjY37xXUVHRqdvLycnRvffeqzvuuEM+n0/BYOfGNpWWlurbb7/lxWvAZTa/MdK3b1+ev4BT+CoTtvr2G9DmCDOew3CS6piz9SSp18AByuvb16ZqnC8Vz9/1PUKKjdJlBbLUt4v/B2vzC9QQs87Nze3ybQJewPfgbdC3r7LPOUfr7r03uhX55hvNvelmhY4/LuHw9rp9AwAAAACS69t//lOHx6x9HZzUBBvFhrgkafVqif83ADbL6BCXz+dr86zUzXvb+iJydhcSuj6fjxevARfa/Nzl+Qs4hBHX2dIXkM/vb/dwnsNwAjMSkRkX4grk5fG43IqkP3/jb8bX9Q5BCZ/O1xsgiu/Bndfr12do/auvKPzjkuje2jvvVLeDfq6soiIbKwMAAACAzLVs7tzo5br8fOXn5dlYDTokN1cqKpKqqlrWK1YQ4kLGqq6ujnbMp7O7vdp/NzMD9OnTJ/pAjFW16Qt1nz590lwRAABIivgQVxtjFAGnMeobEvZ8efk2VJLZEoIk/L4KwGH8OTnqd821lr1IdbXWTr/HpooAAAAAILMZhqENX38dXUcGDLCxGnRK7P/VypX21QHYbPr06SotLVVpaamampoUiUTsLiljZXSIa/fdd9eaNWuioa3NvvvuO0nST37yEzvKAgAAXWXE/XAZ6NyIY8AOZn1dwp4/nzP2vIAzlwAkW+G4n6nbhAmWveq//1318+fbVBEAAAAAZK7vv/9evevro+vc7be3sRp0SuxIxRUr7KsDsNnUqVNVVlamsrIyZWdnKxAI2F1SxsroENfJJ58s0zT16quvWvZfeuklhUIhTZw40abKAABAlyR04uKHTTif0ZDYictP2/X0S8NIN8bGAUiGvlddKV/s9wnT1Krrb5DJmZIAAAAAkFb/+te/FDuELzh0qG21oJNiQ1x04kIGC4VCKikpUUlJiXw+H69h28iTIS7DMFRTU6Pa2lpJUnNzs2pqalQfk4CWpJ///Oc64YQTdMUVV+if//yn1q1bp3vuuUcvvfSS7rrrLhUWFtpRPgAA6CrGKcKFjLr6hD1fbq4NlcAiGV206MQFIAWC/fur92/Ptew1LFig6hdesKkiAAAAAMhMn376qSXEpcGD2zsUTsM4RQAO48kQ16effqp+/fpp5513VkFBgZ577jn169dPxx57bMKxM2bM0Pnnn6/zzjtPO+ywg5577jm98MIL+tWvfpX2ug3DUHl5efSjuro67TUAAOAJhLjgQvHjFH15eZztYoe0/Jvz/wogOXqdfrqy487wXn3XXSr7739VXl6ucDgswzBsqg4AAAAAMgMhLhdjnCIAh/HkO5p77723ampqOnRsdna2rrnmGl1zzTUprmrrqqqqNDTmxddp06bpuuuus68gAADcihAXXMiI6xrLKEWHSEonrq7fBAC0xZedrX7XXqMlvzojumdu2KinD52oa1evkiQVFxfbVR4AAAAAeF5tba3mz59PiMutGKcIwGF4R9NBioqKNG/evGjHhVAoZG9BAAC4VUKIK2BPHUAnGPUNljUhLrukoUsWHdYAJFHB3nur+2ETteHNf0T3jguFNPmvf9XEqRcqEODnIAAAAABIlU8//VTBSER9YjcJcbkH4xQBOAwhLgfx+/0qKSlhbA4AAF2VEOIK2lMH0AlG3DhFfz4hLkdISicuWnEBSK0+V1yhmg8+lFHX+r3E98gjCgb5GQgAAAAAUumjjz7SoNgNn88aDIKzxXbiWrNGam6WsohQALCP3+4CAAAAko5xinAhM26coi+XEJct0nFCBSdtAEiyYN++6n3++Za9xm+/VWT9epsqAgAAAIDMMHv2bOsoxQEDJE6ocY/YEJdpSqtX21cLAIgQFwAA8CIjYl0T4oILGHXWEBfjFB2CTlwAXKLnqacoZ8Rwy16kosKmagAAAADA+5qamjR37lxriItRiu6Sny/16NG6XrHCvloAQIS4AACAFyV04grYUwfQCUY9IS5HSEeTLDpxAUgBXzCofn/4g2XPNAybqgEAAAAA7/viiy9UX19PiMvtYrtxrVxpXx0AIEJcAADAiyJh65pOXHABoyFunGI+IS5nSEYXLTpxAUiP/J/+VN2POtLuMgAAAAAgI3z00UeSpCGxm4S43GfAgNbLhLgA2IwQl4MYhqHy8vLoR3V1td0lAQDgTgmduAhxwfnMhHGK+TZVktl86eiSRSMuACmUe/bZUk5OdG3QjQsAAAAAUmJziItOXC4X24mLcYoAbEaIy0Gqqqo0dOhQlZaWqrS0VNOnT7e7JAAA3Ck+xBUI2lMH0AkJ4xRzc22qBLFMMwldtJJxGwDQQfc99ZT+urL1ReeKigobqwEAAAAAbzIMQx9//LGkuBDXkCFtHg8HY5wiAAehLYWDFBUVad68edGz/0OhkL0FAQDgVkbEuvYH7KkD6ISEEBfjFO2Rhk5caen2BSBjTZ06VVVHH62GKb+SJPXq1cvmigAAAADAe77++mtVVVVJohOX6zFOEYCDEOJyEL/fr5KSEt7UAQCgqxinCBcyG6whLl8eIS5HSEojLjpxAUifUCik0G67ac3pp0tXXiG/nybsAAAAAJBss2fPliR1l9Qj9gpCXO7DOEUADsIreQAAwHsIccGFjLq4Tlx5+TZVAgDwgl6/miIfAS4AAAAASImPPvpIkrRd7GZ2ttSnjy31oAsGDmy9vHSpfXUAgAhxAQAALzLC1jUhLrhAwjjFvFybKslw8V1xU9JFi867AFIvEAopEArZXQYAAAAAeI5pmtFOXMNjrxg6VOJkGvcpKWm9vHatVFtrWykAwHcRAADgPUbEuvYH7KkD6IT4EBfjFD2EaYoAbEKICwAAAACS75tvvtHKlSslxYW4hg9v83g43IABUjDYui4vt60UACDEBQAAvCdhnGKw7eMABzHr6ixrxinaJQ2duOK7fQFAqnAGOAAAAAAk3bvvvhu9PLZXr9YrRoywoRp0WSAgDRnSui4rs68WABmPV/MAAID3JIS4GKcI5zMaGixrfz6duDwjJSMZAQAAAAAAYIfYENfogoLWK+jE5V6lpa2XCXEBsBHvaDqIYRgqLy+Xb9OZ+aFQSCFGHwAA0HmEuOBC8eMU/YxTtEd8lyw6cQFwmerqalVXV0uSwuGwAgHGSgMAAABAsjQ2NuqDDz6IrgfGvqZHiMu9YkNcjFMEYCM6cTlIVVWVhg4dqtLSUpWWlmr69Ol2lwQAgDsZEevaz5uXcL74EJcvlxCXZ9CJC0AaTZ8+Pfq6wsKFC1VRUWF3SQAAAADgGXPnzlVdXZ0kKZSTo9y1a1uvZJyie9GJC4BD0JbCQYqKijRv3jxLJy4AALANImHrmk5ccDgzHJbC1sct4xRtko4mWXTiApBCU6dO1ZQpUyRJEyZMoBMXAAAAACRR7CjFX+yxh/TJJy2LYFAaPNimqtBlJSWtlwlxAbAR72g6iN/vV0lJSTTEBQAAthHjFOEyRkNDwh7jFB0iGV206MQFII1CoVD0pLBgMGhvMQAAAADgMbEhrsNGjGgNcZWWSlm8Du1adOIC4BCMUwQAAN4TH+IK8AYmnM2oq0/YI8Rlk3ScUME5GwAAAAAAAK5TWVmpzz//PLres1ev1isZpehusSGu9eul6mrbSgGQ2QhxAQAA7zEi1rWfMUJwNrO+LmHPl59vQyWIZyoZXbToxAUAAAAAAOB2//znP2Vu6rjet29f9a+pab1y+HCbqkJS9OkjxZ5USzcuADYhxAUAALyHcYpwGaM+rhOX3y8fI7BskZbR5oxPBwAAAAAAcJ3YUYoHHXSQfD/80HolIS538/mkkpLWNSEuADYhxAUAALyHEBdcJj7E5c/LS0+YCFuXhCZam8/QBAAAAAAAgDuZpmkJcR188MFSbIiLcYruFztSkRAXAJsQ4gIAAN5jhK1rQlxwuPgQly8/r50jkXJpCM8R0AMAAAAAAHCXb775RuXl5dH1wePGSUuXth5AJy73I8QFwAEIcQEAAO8xIta1P2BPHUAHmQmduPJtqgQJktFFi0ZcAAAAAAAArvbKK69EL++xxx4a0NjY+rpRVpa03Xb2FIbkiQ1xxQT2ACCdCHEBAADvSRinGLSnDqCDEsYp5ubaVAnS0YlLohMXAAAAAACAm7z66qvRy5MmTZIWLmy9srS0JcgFdyspab1MJy4ANuG7iYMYhqHy8vLoeJVQKKRQKGRvUQAAuFFCiIsfeeBsRl18Jy7GKTpGMjpxAUAaVVdXq7q6WpIUDocVCNCRFAAAAAC6Yvny5Zo3b150ffTRR0vvvtt6AKMUvSG+E5dppumETwBoRScuB6mqqtLQoUNVWlqq0tJSTZ8+3e6SAABwJ0JccBmzwRri8uUT4rJPCl6YIQgGII2mT58efV1h4cKFqqiosLskAAAAAHC11157LXq5tLRUo0aNkn74ofWAESNsqApJFxviqquT1qyxrxYAGYt3NB2kqKhI8+bNs3TiAgAA28CIWNd+OlDA2YyGRsvan8M4RcdIRQCLM/gApNDUqVM1ZcoUSdKECRPoxAUAAAAAXRQ/StHn81nHKdKJyxuKiqQePaT161vW5eVS3762lgQg8xDichC/36+SkpJoiAsAAGwjOnHBZcxGa4jLl5NjUyVICTpxAUijUCgUPSksGAzaWwwAAAAAuNyGDRv0f//3f9H10Ucf3XIhthMXIS7vKCmRvvyy5XJZmbTXXraWAyDzME4RAAB4TyRsXRPigsOZTXGduHIJcdkm/nwKOnEBAAAAAABkrH/84x8Kh1teb+7Zs6f23XdfqbZW+vHH1oMYp+gdsSMVy8rsqwNAxiLEBQAAvCe+E1eALhRwNqOxybL2ZRPi8hQ6cQEAAAAAALhS7CjFI444QllZWdL8+a2v9xQUSEOH2lQdko4QFwCbEeICAADeY0SsazpxweHMhgbLmnGKNorrkmUqFZ24kn+TAAAAAAAASK6mpia9+eab0XV0lOJXX7UetMsukp+33D0jNsRVXm5bGQAyF99RAACA98R34vIH7KkD6KD4cYq+nGybKkFq0IkLAAAAAADAbT744AOtX79ekpSbm6sJEya0XPHll60HjR5tQ2VImZKS1st04gJgA0JcAADAexJCXHTigrPFj1P05+TaVAl8cZ24UpK/ir8PAAAAAAAAOM7TTz8dvXzwwQeroKCgZUGIy7tiO3H9+KMUibR/LACkACEuAADgPYS44DJmY3wnLsYpeolp0okLAAAAAADATWpra/Xiiy9G16eeemrLBcOwjlPcddc0V4aUiu3EFQ5LK1bYVgqAzESICwAAeA8hLriM2dhgWTNO0UYJnbiSH8BK6PYFAAAAAAAAR3n11VdVW1srSerevbuOPPLIlivKy6WNG1sPJMTlLYWFUp8+reuFC+2rBUBGIsQFAAC8hxAXXCZxnCKduDyFTlwAAAAAAACuMmPGjOjl448/Xnl5eS2L2FGKQ4dK3bqluTKk3E47tV7++mv76gCQkXhH00EMw1B5eXn0zPxQKKRQKGRvUQAAuBEhLrhM4jjFXJsqQUInrtTcSRruA0Cmqq6uVnV1tSQpHA4rEAjYWxAAAAAAuMyqVav0zjvvRNennXZa65WxoxRHj05jVUibUaOkDz5oubxgga2lAMg8dOJykKqqKg0dOlSlpaUqLS3V9OnT7S4JAAB3IsQFl0kMcTFO0TGS0UWLRlwA0mj69OnR1xUWLlyoiooKu0sCAAAAAFd59tlnZRiGJGnIkCEaP35865WxnbgYpehNo0a1XibEBSDNeEfTQYqKijRv3jxLJy4AALANjIh1TYgLDmfEhbgYp2inNHTJSku3LwCZaurUqZoyZYokacKECXTiAgAAAIBOevrpp6OXTznlFPn9MX1RYkNcdOLypvgQl2nyeh6AtOEdTQfx+/0qKSmJhrgAAMA2SujExZuXcLbETlyEuBwjGZ24ACCNQqFQ9KSwYDBobzEAAAAA4DLff/+9vvjii+jaMkpxwwZp8eLWNSEub9p559bLGzZIy5ZJgwfbVw+AjMI4RQAA4D2RsHVNJy44HCEuB0nFCRUEwQAAAAAAAFxh5syZ0ct77LGHdtxxx9Yr589vvdytm1RSkr7CkD6hkDRoUOuakYoA0ogQFwAA8BbTlMy4cYoBulDA2YymJsuacYoOkooAFp13AQAAAAAAHCcSieill16Krk899VTrAV991Xp5l10kP2+1e1b8SEUASBO+swAAAG8xIol7dOKCg5mmKbOhwbJHJy4bpSJfRScuAAAAAAAAx3v99de1YsUKSVIgENDkyZOtB3z5ZetlRil6GyEuADbhHU0AAOAtRnPinj+Q/jqAjmpulgzDsuXLJsTlFKboxAUAAAAAAJAJ7r333ujlY489Vn379rUeQIgrcxDiQoaprq5WdXW1pJYTz2EfOnEBAABvaTPERW4dzmU0NiXs+XMJcdnFl5KAFb/0AgAAAAAAONmXX36pDz74ILqeOnWq9YBIRJo/v3VNiMvbYkNc33zT8v8PeNj06dNVWlqq0tJSNTU1KcJj3jaEuAAAgLcQ4oLLmE2NCXuMU3SQVOSvaMQFAAAAAADgKPfcc0/08pgxY7T33ntbD/jvf6Xa2pbLWVnSLrukrzik3447tnbTb2iQFi+2tx4gxaZOnaqysjKVlZUpOztbgQATbuzCO5oAAMBbCHHBZcyGhoQ9Qlw2SkEnLtpPAwAAAAAAONfatWv1zDPPRNcXXHBBYrf22bNbL48ZIxUUpKk62CI/Xxo2TPrhh5b1ggXSiBH21gSkUCgUUigUkpSqaRXoKDpxAQAAbyHEBZcxGhM7cfkJcTlHCgJY/BIMAAAAAADgHA8//LAaN71G16dPH51wwgmJB334Yevl8ePTVBlsFTtSccEC++oAkFEIcQEAAG8hxAWXMZuarBt+f0tLdngHnbgAAAAAAAAcqampSffff390ffrppys7O9t6kGFIH33Uut5vvzRVB1sR4gJgA0JcAADAWwhxwWXMuE5cvpwcOjXZKf7fPiUBLP5/AQAAAAAAnOCFF17QqlWrJEnZ2dn65S9/mXjQggVSZWXLZb9f+tnP0lghbEOIC4ANCHEBAABvMSKJe4S44GBGQ4Nl7Y8/0w/uRyMuAAAAAAAAxzFNU9OnT4+uTz75ZPXu3TvxwNmzWy//5CdS9+6pLw72iw1x/e9/UtzJuACQCoS4AACAt9CJCy5jNlrHKfpyc22qBC3S0ImLTmsAAAAAAAC2e++99/T5559H1xdccEHbB374Yevl8eNTXBUcY/vtpWCw5XJzc0uQCwBSjHc0HcQwDJWXl0fH54RCIYVCIXuLAgDAbSLhuA1fS4trwKHMpsRxivCYlIxkBIC2VVdXq7q6WpIUDocVCATsLQgAAAAAHMgwDF155ZXR9YEHHqjddttNq1evth5omtZOXPvtl6YKYbtgUBo5Upo/v2W9YIG0yy721gTA83hH00Gqqqo0dOhQlZaWqrS01NK+EwAAdFB8J65A0J46gA4y49pw+3MYp2ir+C5ZdOIC4DLTp0+Pvq6wcOFCVVRU2F0SAAAAADjO3//+d33xxRfR9a2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      "text/plain": [
       "<Figure size 2400x1350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cshock = cshock.get_joined_dataframes()\n",
    "species = [\"CO\", \"H2O\", \"CH3OH\", \"NH3\", \"$CO\", \"$H2O\", \"$CH3OH\", \"$NH3\"]\n",
    "fig, [ax, ax2] = plt.subplots(1, 2, figsize=(16, 9))\n",
    "ax = cshock.plot_species(ax, species)\n",
    "settings = ax.set(\n",
    "    yscale=\"log\",\n",
    "    xlim=(1, 20 * cshock.dissipation_time),\n",
    "    ylim=(1e-10, 1e-2),\n",
    "    xlabel=\"Time / years\",\n",
    "    ylabel=\"Fractional Abundance\",\n",
    "    xscale=\"log\",\n",
    ")\n",
    "\n",
    "ax2.plot(df_cshock[\"Time\"], df_cshock[\"Density\"], color=\"black\")\n",
    "ax2.set(xscale=\"log\", yscale=\"log\")\n",
    "ax3 = ax2.twinx()\n",
    "ax3.plot(df_cshock[\"Time\"], df_cshock[\"gasTemp\"], color=\"red\")\n",
    "ax2.set(xlabel=\"Time / year\", ylabel=\"Density\")\n",
    "ax3.set(ylabel=\"Temperature\", facecolor=\"red\", xlim=(1e-7, 1e6))\n",
    "ax3.tick_params(axis=\"y\", colors=\"red\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd7d8a9a",
   "metadata": {},
   "source": [
    "### J-shock\n",
    "Running a j-shock is a simple case of changing function. We'll run a 10 km s $^{-1}$ shock through a gas of density\n",
    "$10^3$ cm $^{-3}$ gas this time. Note that nothing stops us using the initial abundances we produced for the c-shock.\n",
    "UCLCHEM will not check that the initial density matches the density of the previous model. It may not always be a good\n",
    "idea to do this, but we should remember the initial abundances really are just a rough approximation.\n",
    "\n",
    "By default, UCLCHEM uses 500 timepoints for a model, but this turns out to not be enough, which is why we increase the\n",
    "number of timepoints to 1500."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "acd3aec3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:30:10.078556Z",
     "iopub.status.busy": "2026-06-19T14:30:10.078389Z",
     "iopub.status.idle": "2026-06-19T14:30:26.079432Z",
     "shell.execute_reply": "2026-06-19T14:30:26.078516Z"
    }
   },
   "outputs": [],
   "source": [
    "param_dict[\"initialDens\"] = 1e3\n",
    "param_dict[\"freefall\"] = False  # lets remember to turn it off this time\n",
    "param_dict[\"reltol\"] = 1e-12\n",
    "shock_vel = 10.0\n",
    "jshock = uclchem.model.JShock(\n",
    "    shock_vel=shock_vel,\n",
    "    param_dict=param_dict,\n",
    "    previous_model=shock_start,\n",
    "    timepoints=1500,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d02da0c",
   "metadata": {},
   "source": [
    "This time, we've turned off the freefall option and made reltol a little more stringent. The j-shock ends up running a\n",
    "bit slower but we get no warnings on this run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "32a1f740",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T14:30:26.081606Z",
     "iopub.status.busy": "2026-06-19T14:30:26.081408Z",
     "iopub.status.idle": "2026-06-19T14:30:27.421842Z",
     "shell.execute_reply": "2026-06-19T14:30:27.420855Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Element conservation report\n",
      "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%'}\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1350 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_jshock = jshock.get_joined_dataframes()\n",
    "jshock.check_conservation()\n",
    "species = [\"CO\", \"H2O\", \"CH3OH\", \"NH3\", \"$CO\", \"$H2O\", \"$CH3OH\", \"$NH3\"]\n",
    "\n",
    "fig, [ax, ax2] = plt.subplots(1, 2, figsize=(16, 9))\n",
    "ax = jshock.plot_species(ax, species)\n",
    "settings = ax.set(\n",
    "    yscale=\"log\",\n",
    "    xlim=(1e-7, 1e6),\n",
    "    ylim=(1e-10, 1e-2),\n",
    "    xlabel=\"Time / years\",\n",
    "    ylabel=\"Fractional Abundance\",\n",
    "    xscale=\"log\",\n",
    ")\n",
    "\n",
    "ax2.plot(df_jshock[\"Time\"], df_jshock[\"Density\"], color=\"black\")\n",
    "ax2.set(xscale=\"log\", yscale=\"log\")\n",
    "ax3 = ax2.twinx()\n",
    "ax3.plot(df_jshock[\"Time\"], df_jshock[\"gasTemp\"], color=\"red\")\n",
    "ax2.set(xlabel=\"Time / year\", ylabel=\"Density\")\n",
    "ax3.set(ylabel=\"Temperature\", facecolor=\"red\", xlim=(1e-7, 1e6))\n",
    "ax3.tick_params(axis=\"y\", colors=\"red\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87028d47",
   "metadata": {},
   "source": [
    "That's everything! We've run various science models using reasonable starting abundances that we produced by running a\n",
    "simple UCLCHEM model beforehand. One benefit of this method is that the abundances are consistent with the network. If\n",
    "we start with arbitrary, perhaps observationally motivated, abundances, it would be possible to initiate the model in a\n",
    "state our network could never produce.\n",
    "\n",
    "However, one should be aware of the limitations of this method. A freefall collapse from low density to high is not\n",
    "really how a molecular cloud forms and so the abundances are only approximately similar to values they'd truly have in\n",
    "a real cloud. Testing whether your results are sensitive to things like the time you run the preliminary for or the\n",
    "exact density is a good way to make sure these approximations are not problematic.\n",
    "\n",
    "Bear in mind that all model objects can be passed as inputs to `previous_model`. This lets you chain model runs\n",
    "together. For example, you could run a c-shock from a cloud model as we did here and then a j-shock with the c-shock\n",
    "object as the previous model."
   ]
  }
 ],
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