{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# END-TO-END COST BENEFIT CALCULATION" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Contents\n", "\n", "- [Introduction](#Introduction)\n", "- [What is a cost-benefit?](#What-is-a-cost-benefit?)\n", "- [CostBenefit class data structure](#CostBenefit-class-data-structure)\n", "- [Detailed CostBenefit calculation: LitPop + TropCyclone](#Detailed-CostBenefit-calculation:-LitPop-+-TropCyclone)\n", "- [Conclusion](#Conclusion)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-10-20T07:58:34.931387Z", "start_time": "2020-10-20T07:58:34.855569Z" } }, "source": [ "The goal of this tutorial is to show a full end-to-end cost-benefit calculation. Note that this tutorial shows the work flow and some data exploration, but does not explore all possible features.\n", "\n", "The tutorial will start with an explanation of the mathematics of an cost-benefit calculation, and then will move on to how this is implemented in CLIMADA. We will then go through a few end-to-end calculations.\n", "\n", "If you just need to see the code in action, you can skip these first parts, which are mostly for reference.\n", "\n", "The tutorial assumes that you're already familiar with CLIMADA's **[Hazard](climada_hazard_Hazard.ipynb)**, **[Exposures](climada_entity_Exposures.ipynb)**, **[impact functions](climada_entity_ImpactFuncSet.ipynb)**, **[Impact](climada_engine_Impact.ipynb)** and **[adaptation measure](climada_entity_MeasureSet.ipynb)** functionality. The cost-benefit calculation is often the last part of an analyses, and it brings all the previous components together. \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What is a cost-benefit?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A cost-benefit analysis in CLIMADA lets you compare the effectiveness of different hazard adaptation options.\n", "\n", "The cost-benefit ratio describes how much loss you can prevent per dollar of expenditure (or whatever currency you're using) over a period of time. When a cost-benefit ratio is less than 1, the cost is less than the benefit and CLIMADA is predicting a worthwhile investment. Smaller ratios therefore represent better investments. When a cost-benefit is greater than 1, the cost is more than the benefit and the offset losses are less than the cost of the adaptation measure: based on the financials alone, the measure may not be worth it. Of course, users may have factors beyond just cost-benefits that influence decisions. \n", "\n", "CLIMADA doesn't limit cost-benefits to just financial exposures. The cost-benefit ratio could represent hospitalisations avoided per Euro spent, or additional tons of crop yield per Swiss Franc.\n", "\n", "The cost-benefit calculation has a few complicated components, so in this section we'll build up the calculation step by step.\n", "\n", "### Simple cost-benefits\n", "\n", "The simplest form of a cost-benefit calculation goes like this:\n", "\n", "$$\n", "\\textrm{CostBenefit} = \\frac{\\textrm{cost}}{\\textrm{benefit}} = \\frac{\\textrm{cost}}{N \\cdot (\\textrm{AAI without measures} - \\textrm{AAI with measures})}\n", "$$\n", "\n", "where $\\text{cost}$ is the cost of implementing a set of measures, the AAI is the average annual impact from your hazard event set on your exposure, and $N$ is the number of years the cost-benefit is being evaluated over.\n", "\n", "Note that:\n", "- Whether an adaptation measure is seen to be effective might depend on the number of years you are evaluating the cost-benefit over. For example, a €50 mn investment that prevents an average of €1 mn losses per year will only 'break even' after $N = 50$ years.\n", "- Since an adaptation measure could in theory make an impact worse (a negative benefit) it is possible to have negative cost-benefit ratios.\n", "- CLIMADA allows you to use other statistics than annual average impact, but to keep thing simple we'll use average annual impact throughout this tutorial.\n", "\n", "### Time-dependence\n", "\n", "The above equation works well when the only thing changing is an adaptation measure. But usually CLIMADA cost-benefit calculation will want to describe a climate and exposure that also change over time. In this case it's not enough to multiply the change in average annual impact by the number of years we're evaluating over, and we need to calculate a benefit for every year separately and sum them up.\n", "\n", "We can modify the benefit part of cost-benefit to reflect this. CLIMADA doesn't assume that the user will have explicit hazard and impact objects for every year in the study period, and so interpolates between the impacts at the start and the end of the period of interest. If we're evaluating between years $T_0$, usually close to the present, and $T_1$ in the future, then we can say:\n", "\n", "$$\n", "\\text{benefit} = \\sum_{t = T_0}^{T_1} \\alpha(t) \\bigg{(} \\text{AAI with measures}_{T_1} - \\text{AAI with measures}_{T_0} \\bigg{)} - N * \\text{AAI without measure}_{T_0}\n", "$$\n", "\n", "Where $\\alpha(t)$ is a function of the year $t$ describing the interpolation of hazard and exposure values between $T_0$ and $T_1$. The function returns values in the range $[0, 1]$, usually with $\\alpha(T_0) = 0$ and $\\alpha(T_0) = 1$.\n", "\n", "Note that:\n", "- This calculation now requires three separate impact calculations: present-day impacts without measures implemented, present-day impacts with measures implemented, and future impacts with measures implemented.\n", "- Setting $\\alpha(t) = 1$ for all values of $t$ simplifies this to the first cost-benefit equation above.\n", "\n", "CLIMADA lets you set $\\alpha(t)$ to 1 for all years $t$, or as\n", "$$\n", "\\alpha_k(t) = \\frac{(t - T_0)^k}{(T_1 - T_0)^k} \\;\\; \\text{for} \\; t \\in [T_0, T_1]\n", "$$\n", "\n", "where $k$ is user-provided, called `imp_time_depen`. This expression is a polynomial curve between $T_0$ and $T_1$ normalised so that $\\alpha_k(T_0) = 0$ and $\\alpha_k(T_1) = 1$. The choice of $k$ determines how quickly the transition occurs between the present and future. When $k = 1$ the function is a straight line. When $k > 1$ change begins slowly and speeds up over time. When $k < 1$ change is begins quickly and slows over time.\n", "\n", "If this math is tough, the key takeaways are\n", "- Cost benefit calculations take a long view, summing the benefits of adaptation measures over many years in a changing world\n", "- CLIMADA describes how the change from the present to the future scenarios happens with the `imp_time_depen` parameter. With values < 1 the change starts quickly and slows down. When it is equal to 1 change is steady. When it's > 1 change starts slowly and speeds up.\n", "\n", "### Discount rates\n", "\n", "The final addition to our cost-benefit calculation is the *discount rate*.\n", "\n", "The discount rate tries to formalise an idea from economics that says that a gain in the future is worth less to us than the same gain right now. For example, paying €1 mn to offset €2 mn of economic losses next year is 'worth more' than paying €1 mn to offset €2 mn of economic losses in 2080.\n", "\n", "In practice it provides a way to future monetary values to an estimated worth today, called their *net present value*. Note that this is *not* an adjustment for inflation.\n", "\n", "The choice of discount rate is a contentious topic in adaptation finance, since it can strongly affect a cost-benefit calculation. The most widley used discount rate in climate change economics is 1.4% as proposed by the Stern Review (2006). Neoliberal economists around Nordhaus (2007) claim that rates should be higher, around 4.3%, reflecting continued economic growth and a society that will be better at adapting in the future compared to now. Environmental economists argue that future costs shouldn't be discounted at all.\n", "\n", "To illustrate, with a 1.4\\% annual discount rate, a gain of €100 next year is equivalent to €98.60 this year, and a gain of €100 in 15 years is equivalent to $ € (100 * 0.986^{15})$ = € 80.94 this year. With a rate of 4.3\\% this drops to €51.72.\n", "\n", "We can add this into the cost-benefit calculation by defining $d(t)$, the discount rate for each year $t$. A constant rate of 1.4\\% would then set $d(t) = 0.014$ for all values of $t$.\n", "\n", "Then the adjustment $D(t)$ from year $t$ to the net present value in year $T_0$ is given by\n", "\n", "$$\n", "D(t) = \\prod_{y = T_0}^{t} (1 - d(y))\n", "$$\n", "\n", "With a constant 1.4\\% discount rate, we have $D(t) = 0.986^{t - T_0}$. With a discount rate of zero we have $D(t) = 1$.\n", "\n", "Adding this to our equation for total benefits we get:\n", "\n", "$$\n", "\\text{benefit} = \\sum_{t = T_0}^{T_1} \\alpha(t) D(t) ( \\text{AAI with measures}_{T_1} - \\text{AAI with measures}_{T_0} ) - N * \\text{AAI without measure}_{T_0}\n", "$$\n", "\n", "Note:\n", "- Setting the rates to zero ($d(t) = 0$) means $D(t) = 1$ and the term drops out of the equation.\n", "- Be careful with your choice of discount rate when your exposure is non-economic. It can be hard to justify applying rates to e.g. ecosystems or human lives.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## CostBenefit class data structure\n", "\n", "The CostBenefit class does not require any attributes to be defined by the user. All attributes are set from parameters when the method `CostBenefit.calc()` is called.\n", "\n", "After calling the `calc` method the `CostBenefit` object has the following attributes:" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-10-20T09:19:16.170229Z", "start_time": "2020-10-20T09:19:16.143316Z" } }, "source": [ "| Attributes created in `CostBenefit.calc` | Data Type | Description|\n", "| :- | :- | :- |\n", "| present_year | int | The current year |\n", "| future_year | int | The future scenario year |\n", "| tot_climate_risk | float | The total climate risk in the present scenario, evaluated according to the provided risk function (annual average impact by default) |\n", "| unit | string | Units to measure impact |\n", "| benefit | dict(float) | The benefit of each measure, keyed by measure name |\n", "| cost_ben_ratio | dict(float) | The cost benefit of each measure, keyed by measure name |\n", "| imp_meas_future | dict(dict) | Dictionaries describing the impacts of each measure in the future scenario. Keyed by measure name (with 'no measure' for no measures). The entries in each dictionary are described below. |\n", "| imp_meas_present | dict(dict) | Dictionaries describing the impacts of each measure in the present-day scenario. Keyed by measure name (with 'no measure' for no measures). The entries in each dictionary are described below. |\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each dictionary stored in the attributes `imp_meas_future` and `imp_meas_present` has entries:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "| Key | Data Type | Description |\n", "| :- | :- | :- |\n", "| cost | tuple (cost measure, cost factor insurance) | The cost of implementing the measure, and the cost factor if risk transfers are being calculated |\n", "| impact | Impact | Impact object calculated with the present (`imp_meas_present`) or future (`imp_meas_future`) hazard, exposure and impact functions |\n", "| risk | float | A value of annual risk used in the cost-benefit calculation. A summary statistic calculated from the Impact object. Most commonly the average annual impact, but can be changed with the `CostBenefit.calc`'s `risk_func`parameter. |\n", "| risk_transf | float | Annual expected risk transfer (if calculated) |\n", "| efc | ImpactFreqCurve | The impact exceedance freq for this measure calculated from the Impact object (if calculated) |\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dictionary will also include a 'no measure' entry with the same structure, giving the impact analysis when no measures are implemented." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The `calc` calculation\n", "\n", "Let's look at the parameters needed for the calculation:\n", "```\n", "CostBenefit.calc(hazard, entity, haz_future=None, ent_future=None,\n", " future_year=None, risk_func=risk_aai_agg, imp_time_depen=None, save_imp=False)\n", "```\n", "\n", "These are:\n", "- `hazard` (Hazard object): the present-day or baseline hazard event set\n", "- `entity` (Entity object): the present-day or baseline Entity object. `Entity` is the container class containing \n", " - `exposure` (Exposures object): the present-day or baseline exposure\n", " - `disc_rates` (DiscRates object): the discount rates to be applied in the cost-benefit calculation. Only discount rates from `entity` and not `ent_future` are used.\n", " - `impact_funcs` (ImpactFuncSet object): the impact functions required to calculate impacts from the present-day hazards and exposures\n", " - `measures` (MeasureSet object): the set of measures to implement in the analysis. This will almost always be the same as the measures in the `ent_future` Entity (if set).\n", "- `haz_future` (Hazard object, optional): the future hazard event set, if different from present.\n", "- `ent_future` (Entity object, optional): the future Entity, if different from present. Note that the same adaptation measures must be present in both `entity` and `ent_future`.\n", "- `future_year` (int): the year of the future scenario. This is only used if the Entity's `exposures.ref_year` isn't set, or no future entity is provided. \n", "- `risk_func` (function): this is the risk function used to describe the annual impacts used to describe benefits. The default is `risk_aai_agg`, the average annual impact on the Exposures (defined in the CostBenefit module). This function can be replaces with any function that takes an Impact object as input and returns a number. The CostBenefit module provides two others functions `risk_rp_100` and `risk_rp_250`, the 100-year and 250-year return period impacts respectively.\n", "- `imp_time_depen` (float): This describes how hazard and exposure evolve over time in the calculation. In the descriptions above this is the parameter $k$ defining $\\alpha_k(t)$. When > 1 change is superlinear and occurs nearer the start of the analysis. When < 1 change is sublinear and occurs nearer the end.\n", "- `save_imp` (boolean): whether to save the hazard- and location-specific impact data. This is used in a lot of follow-on calculations, but is very large if you don't need it.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Detailed CostBenefit calculation: LitPop + TropCyclone" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We present a detailed example for the hazard __[Tropical Cyclones](climada_hazard_TropCyclone.ipynb)__ and the exposures from __[LitPop](climada_entity_LitPop.ipynb)__ .\n", "\n", "To speed things up we'll use the CLIMADA Data API to download the data as needed. The data download roughly follows the __[Data API tutorial](climada_util_api_client.ipynb)__ for Haiti. If this is a problem you can build tropical cyclone event sets, and LitPop exposures following the relevant tutorials." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Download hazard\n", "\n", "We will get data for present day tropical cyclone hazard in Haiti, and for 2080 hazard under the RCP 6.0 warming scenario. Note that the Data API provides us with a full event set of wind footprints rather than a TCTracks track dataset, meaning we don't have to generate the wind fields ourselves." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:35:22,192 - climada.hazard.base - INFO - Reading /Users/chrisfairless/climada/data/hazard/tropical_cyclone/tropical_cyclone_10synth_tracks_150arcsec_HTI_1980_2020/v1/tropical_cyclone_10synth_tracks_150arcsec_HTI_1980_2020.hdf5\n", "2022-03-03 05:35:28,402 - climada.hazard.base - INFO - Reading /Users/chrisfairless/climada/data/hazard/tropical_cyclone/tropical_cyclone_10synth_tracks_150arcsec_rcp85_HTI_2080/v1/tropical_cyclone_10synth_tracks_150arcsec_rcp85_HTI_2080.hdf5\n" ] } ], "source": [ "from climada.util.api_client import Client\n", "\n", "client = Client()\n", "future_year = 2080\n", "haz_present = client.get_hazard('tropical_cyclone', \n", " properties={'country_name': 'Haiti', \n", " 'climate_scenario': 'historical',\n", " 'nb_synth_tracks':'10'})\n", "haz_future = client.get_hazard('tropical_cyclone', \n", " properties={'country_name': 'Haiti', \n", " 'climate_scenario': 'rcp60',\n", " 'ref_year': str(future_year),\n", " 'nb_synth_tracks':'10'})\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the hazards and show how they are forecast to intensify. For example, showing the strength of a 50-year return period wind in present and future climates:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:35:28,479 - climada.hazard.base - INFO - Computing exceedance intenstiy map for return periods: [50]\n", "2022-03-03 05:35:36,986 - climada.hazard.base - INFO - Computing exceedance intenstiy map for return periods: [50]\n" ] }, { "data": { "text/plain": [ "(,\n", " array([[41.84896948, 41.98439726, 41.62016887, ..., 49.52344953,\n", " 51.35294266, 51.51945831]]))" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:825: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(multi_line_string) > 1:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:877: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.\n", " for line in multi_line_string:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:944: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(p_mline) > 0:\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAAGYCAYAAADSoFNIAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOy9d5wlWVn//37qhr6de3p6ctiZ3dnILpsTLLDooqCYE/6+goiK6Bf1S1RQYBFB8qqIyKoICGZFJOe4CMvC7rI5TY4902k63b6hzu+Pqrpd91SdW3VDp5nzeb3u9FSdc57zVN26VZ960hGlFBYWFhYWFhYWFmcPnJVWwMLCwsLCwsLCYnlhCaCFhYWFhYWFxVkGSwAtLCwsLCwsLM4yWAJoYWFhYWFhYXGWwRJACwsLCwsLC4uzDJYAWlhYWFhYWFicZbAE0MLCYk1ARJSI/EqbMrb7cm7ujFYWFhYWaxOWAFpYrBBE5IM+GVEiUhWRwyLyYRHZ1qScL4rIB5dIzdWELcB/rMTEIvLV0HcVfL4a0+8FIvKIiCyIyEMi8ssroK6FhYVFIiwBtLBYWXwDj9jsBP4/4Erg31ZKGREprNTcJgQ6KaWOK6WKK6jKP+F9V8HnZ8ONIvKTwD8AfwNcDvwd8I8i8qPLrGcqiEjXSutgYWGxcrAE0MJiZVHyic0RpdTXgduBp4jIQNBBRJ4tIt8WkXkROSQifyUi/X7bB4EfBn41ZJm6WUR2+f+/KTyZiOwXkT8ObSsR+X0R+RcROQ18UEReKCIVEblJRO4RkTkR+a6IXN3oQHwr2QdE5K0ickpETovI7WFSKR5eJiKPikhRRB4Wkd8TEWmkU2j/r4T6bfH7TPrn5qsico2m07NE5AF/rjvxCHarmPe/q+AzrrX/AfCvSqnblFIPK6XeBXwM+EPD+XJEZK+IvEbb3y8iMyLyPH87zTn7ff+7mhGR4yLyr2FLsn9NKBF5rojcISJF4NdEZEBE/sEfs+BfX+9o4xxZWFisEVgCaGGxSiAiW4GfB6pAxd93C/CfeCToMuCXgBuBv/eH/T6eFfHfWLRMfavJqV8PfBOPHL3O3+cAbwFeClwNTAH/KiKZBFk/D6wHngb8H+CngT8Ltb8R+F3gFcDFwGuBNwC/nUKnGnzy89/ARcBzgeuAE8AXRGTE77MN+B+883El8CbgthhZ+1O60H9GRE76BOyvRGQ4JCPv6/BZbcxngRvjzptSygX+FviNMJnDswQX8cgjpD9nr8S7Rn4G2AH8c8wxvBN4qy/nE8CfAlcBPwWcDzwPeKTBObCwsDhToJSyH/uxnxX44JG6CjADzAHK/7wj1OdrwFu0cTf6/Tb4218EPqj12eX3uUnbvx/449C2Av5e6/NCf/9VoX03+fvOa3A8X/XlZ0L7XoxHZnqBHv84f0Qb9xrggUY6hfb/iv//H/a3Lwm1dwHHgNf722826KOAm0P7vgT8WcJ39ZvAs4BL8Vy/DwHfA3J++1Zfrn5sPx7+rmLkbgJKwA+F9n0XeLf//1TnLEbuVf682/ztm/3t52v9Pq5fO/ZjP/ZzdnyyWFhYrCS+A/wqUAB+EbiFeovXNcD1IvJ7oX2Bteh84GQHdLgzZp8C7g1tH/H/bgKeaCRLKVUNbd+BR8zO8/92Ax8TERXqkyXqjYjTKYwnAWNKqQdrCiu1ICLf8dsALjHoUwel1A8nzIVS6m9Dm/eLyL3A48Cz8SxpiSIMck+IyMfxCOaXReRyvO/8V/0uTyLFORORp+FZBp8ErAu1ncPidwfR8/rXwH/6rvMv4VksP6c866SFhcUZDEsALSxWFvNKqcf9/98vIhcAfwX8hr/PAd4G/GPM2CMx+wIED3DR9udj+s7GjdeIU0A+mg0bCeZXobG/ADyaMC5OJx1xpEoM+3V92oJS6gkROQVc4O86hWfN3ax13QwsABMNxP0N8CkRWY9HBO8IEdvEcyYiO/GI20fwXLqngO14lmH9+647r0qpz/njfxTPSvgR4B4R+RHt+7ewsDjDYAmghcXqwq14RPBvlFJ34bkZLwmRxDiUAD3GLLAMbg12iMgWogSl07hWRDIh8nAjHgHai0e+isBupdSn25znAWBERC5SSj0MtazW6/CsWgAPAv9fjD5tQ0R24MU6HgNQSpVE5Lt4FsEPh7o+G/h2Apn6MnAIzz39f4D/F2p7gORzdi2eq/j/KaXmff0aJuyEobxkln8G/llE/gH4Xzzr6X1pZVhYWKw9WAJoYbGKoJR6WEQ+hRe/9qN4wf6f8zMzP4IXD3YR8BNKqRf7w/YBzxSR8/CSNaaUUvMicgfwKhF5CM8S9BY8MrGUWA+8V0T+AjgXL/Hi/UqpWQAReSvwFhGp4hGfLrx4ta1KqT8zyIzDl/Hcmf8kIr+Ld9yvw3Olv8/v8z68xImwPq/WBYnIl/Bcxa/R2/z284BfAT4NjAIX4lll9+MlogR4O5479U7gM3jJKT/r/zVCKaVE5HY869088O+htpkU5+wxPKvnK0Tko3glaF7faM7Qsb0Z7yXjATyr8a/gxaQeTDPewsJi7cJmAVtYrD68HfgREblZKfUlvLjAa/GyWe/GI4fHQv3fhef2uxfP8vdUf/+L8Fx+/4tXw+69eARmKfEfwDReBu+/AJ8kVAZFKfVGPBL2f/EsTF/Fc3fva2YSpZTCyzB+DPgUXuLEJuBZSqlTfp/DeNmtTwfuAf4EjxDqOA8ve9qEEvBMPFL3KJ7L9k7gqUqpuZBO/w38eujYXgy8QCn1mRSH9A94FtKPhmX6chueM6XUD/CyhH8Lz+r5SuqtiI1QxDsv3wPuwktyeY5SairleAsLizUK8e6jFhYWFu1BvJUxHldK/UZSX4t6iMiTgPuBK5VS96ywOhYWFmcBrAvYwsLCYoXgxy2O4NVK/IolfxYWFssF6wK2sLCwWDn8Ml4CyG6ihZ0tLCzWIETkVomuHa60PteJyLf81X2OisibUxTa7yisBdDCwqIjUErdvNI6rDUopT6Iv9SdhYXFGYX9GKoOiMh24At4qzz9Jl5N1w/4zX+0HMqBJYAWFhYWFhYWFp1GVSl13ND223jJcr/hF11/wF+68m0i8mY9EWypYF3AFhYWFhYWFhadxXYROSwiB0XkYyJySajtJuDz2oo7n8VbMvOq5VLwrLUAPvvZz1anTp2q21cqlSiXy5RKJRYWFiiXy2QyGbJZ7zQ1WlMvl8vR1dVFV1cXhUIBx0nHrYvFIqdOnWJoaIi+vr6OH+dSQSlF/fr1Fp2EPb9Li2bPb6VSYX5+nrm5OcrlMoVCga6urtr9IZvN4jgO952Kf+G/bMRcf7tUKjE9Pc38/DwDAwP09/ev6e/eXrtLi7Pl/H7ve9/7nFLq2ab2H31mrxobX5nFar73g4WgQHuA25VSt4e2v4NXU/MRvCSvVwDfFpEnK6X245Wd0pelDG4ejUpSdRRnLQE8evQof/3Xf83Bgwc5dOgQx44dY3h4mB07drBz50527NjBjh076O7uTpRVLpc5ePAgjz32GI8//jh79+5leHiYPXv2sGfPHoaGhmoPiVwuV/v/vffey6c+9Sl+/dd/nQsuuCBxntWE6elp+vv7V1qNMxb2/C4tks6vUoqjR49y7733cs899zA5OcmTn/xkLr/8ci666CJyuRwAu/72HV5//3m8WbSyWv7+YFmW2nPb77f/hX9Q6zo6OsrHP/5xDhw4wE/8xE9w7bXXpn6RXE2w1+7S4mw5vyIy0qj91HiV73xu+3KpU4fclieKSqlrTO167U8R+SbwEF69zrhapLC4hOWy1eY7awng2NgYe/fuZceOHVx//fVs27aNQqHQkqxcLsd5553HeeedB0C1WuXQoUM8/vjj3HXXXczMzFCpVCKfwcFBXvGKV7Bx48ZOHpqFhUUbGB8f52//9m+Znp7m8ssv5+d//uc577zzyGQWE/R23e4Rv5ZXFvYZ464Pvq1Ozv7f/AMef/xx/uu//ovPf/7z3HDDDVx33XUMDg62OJGFhcVKQylVFpG7WVw7/BjRZTkDy58pbrDjOGsJ4JYtW3jBC16wJLIzmQy7du1i165d3HLLLUsyh4WFRefxile8gvn5eX7mZ36GW265peZq2/X+d9Z37LRhzn/n3/UhnxBuUgxPu+w6fpw/+ZM/4dxzz+X666/nyU9+Mvl8vsOTW1isRSiqdSF0qxd+eZfLgK/7u+4AXiAiTigO8Nl4S33evVx6rT3/goWFhcUS4TnPeQ4AO3fuXNk4KxHGBwo8//nP5y1veQvXXHMN3/rWt3jta1/LRz/6UZ544gnsKk4WZzMU4KJW5JMEEXmXiNwsIrtE5Brgn4FdwF/7Xd4HDAB/JyJPEpGfwls3/T3BuunLgbPWAmhhYWGh45ZbbmH79u38/d//Pbfccgu//eg9VDPO4quyHuPXJALOVuOWQfCgLjewCH74bYs7huDu5/8Rd955Jx/5yEdwXZfrr7+e66+/nvXr17ell4XFWoTLqrUAbgU+AmwAxvHW2n5KsNKPUuqQiPwIcJvfNgG8H/jj5VTSEkALCwsLH7v+2nP19m4Z4tEvf4GbZ+c5MDLIgZEBytlQkf6Ar+lGQp3QmfqZYOzv7bjyE+/3NnfnGZwpcfHp07z1rW9l69at3HDDDVx55ZUtxzJbWFh0BkqpX07R59sYCkUvFywBtLCwsNAw25Xnnp2b6C2XOHd0imc8fIgTg72cGOzhVH8BN012rlLkKy7lrIPqtDtZhKn+Lp73vOfxcz/3c9x///185zvf4T/+4z+47LLLuOGGG7jgggvWZBaxhUUaKBRVGwbRFiwBtLCwOOux673v8v/nEzXHe7DMduW5b8cGHiutY/PULLtHp7j8wElODXRzsr+bqZ48M4U8ON44x3XZNDXHlolZ1s0WcVxFJeOwf+MAh0b6KOc8K2KiK1h/ron2H1/Arn98a63L/pf8IdPT03z3u9/lYx/7GNPT0zz72c/mpptuskTQ4oxEmng8CzMsAbSwsDjr8KyP/gMnKuXFHVp9vhr8zWI+y/4Ng+zfOEi+UmXj1Czrp4vsHp2ip1RhppAj67oUSlXG+gscXdfL/TvWs5DLMDBfYtfJKZ55/xGmevJM9nYx2ev9Xch7t+C0MYFRl/PivhoZVMA24es3v4R///d/54477uB5z3seu3fvbvo8WVhYnLmwBNDCwsKiCZSyGQ6vH+Dw+gEQheO69BfLVB1htiuHcqTG4wBO93Txg10beKhSZWh2gaHZBXaenOHJ+8eoOsJkXxeTvV1M9XYx1Zv3kk46gJ07d/Lyl7+cO++8k9tvv51LLrmEn/7pnz4righbnPlQQNVaANuCJYAWFhZnDXa/x3P1bsrm6qxnEegWN6NLFlzHYaqnq25/zZMb6lfOZjg52MPJwR6/UdFTqtRI4eaJOfqKJUYHezgy0sepgUIo+1jXK7TDYB2sZRAryO4Z4G09PbzpTW/ix3/8x3na055m3cIWax7WBdweLAG0sLA443HuX3rEz8T3FkPv4nysMQNrz53GWb8RuWHXrghzXTnmunIcXe+tA54rV9k6McsFhyd4crnKkZFejoz0MtOdr9cjQgRZDCyMHBxUcg6vmHmcvt39HPj0f3P7J/6L97z2DQwPD8ePsbBY5VBgk0DahCWAFhYWZyTO/Yt3L24EuRMmImey3CmDCTCyO2X5l4QYv3Iuw4GNAxzYOEDffIntYzNc9/AoxXyG0aFuZgs55ruyzHVlKWWdWvKJJ1NXKqrETE+e752/kWfec5in/uv7mC/kam37f+3VWFhYnD2wBNDCwsJiFWKmO88jO4Z5ZPs6Rk7Ps366yKaJOXoWKvQsVHBcVSOD811Z5grB/zPMFbLGWMJzRqcZXddTR/4sLNYiVm0Z6DUCSwAtLCzOKJz751HLX23T5DEyWAIXmxMsgbWO8ZbAqEExXbav5+ESTg32cCqIHfTHZasu3T4Z7F6o0FOssH6qWNuuOlIjhhP9XRxZ34cS2HX8NN+5eFPkFJzzgbfXbR94kbUIWqxeKJRNAmkTlgBaWFisaZz37nfX7xDtL8QSM1ENXMK6LBNM/Q0Ez+hiTkUE68vFVJwM0z0O0z35qA5+EeqeYoWehTIbJ+a54NAUM4Us4/0FP6YwJlMlNPc5f/eOWN0O/LolhhYWZwIsAbSwsLA40yBCKZehlMsw2d/F0ZE+8qUqW8dmGR3qXmntLCzah4KqNQC2BUsALSws1iTOe5fB8hdAxbRp1q64ci1xMhYdwBLfoM/ZcrKJrlj9OOMKIg3GBCjlMuzfPOCNSfPg1JQU3TLo48BvvCqFMAuLzkJhYwDbhSWAFhYWawLnvfPd8Q0m7iQ0XlJNSa1zIhE0wegC1nYYgg+N85qWhtOIYP3USf5srdXUbKp9GDRrT91dtweuYu/Pfc97ScN5LSw6A6GaGKNh0Qi2EqiFhYWFhYWFxVkGawG0sLBY1djz9tuA+prHYC7RFza6GfuoYJ/mEtY66uMjruDUa/Y2dh23agms6xpJUE5pHamVDWzRmhKM8+Xc8q8f4ES1XNN5/4uti9ii81CAa2MA24IlgBYWFqsKe952m6GlngxF4+ii3RP7RJZ8S1c3JrpySIQhxqpunNcwnTFbuNGDr4GbOFYHfXjSuKRzGQRn+Yx919+8s67b/pe8MmECC4t0sC7g9mAJoIWFhcVSQykK5Srd5TKFcoXuUoV8pUo141DJOJQdh0pGqGQcZgo5irls1ORpYWFh0UFYAmhhYbEicF2XhYUFuru9siTnv9V39Wr9ota7Ji2BxBj4AhdwCjdyrOxGSipFT7nC8Ow8w7NF1s0VKZQrlDMZ5vNZirks8/kspWyGjKsolCr0uS7ZqiJXrdI/X0YBk71dTPR2MdlbYLI3j+s4Kd20TfrFTDKNRbObdS37f/1hu96nWQR/21oELZqHwloA24UlgBYWFiuC577mdWyZPc2dm3ZQzJqXJTN5Z3W3aCxZS6jakjaLN4gNNIXyiXLZfHqWjTOzDM8WUcB4bzfjvQX2bhhirivrEThdgTh/q1J0lyoMzS0wNLfAxUfG6CuWme3KMdFbqBHD+XwW5cQ8AE0Ezehf1pojrl2J32+C+B+9vxuv166/1gjh71hCaJEObqtxqxaAJYAWFhbLjAvefBsb5me4YG6aw72DXHXyCN/dsINKJlPXL6k0XqilrkNsGRiduCkD96p1V2yenmFgYYF8tUpXpUJXtcp0V55jA32c7OtBAQPFEtsnT7Pl9AyT3QWOD/Ty6Mb1zOUzngtXX5XEFHMYVkaE+a4c8105jq3rA8BRLoNzJYZmF9g0NctFR8cRpZjsLTDR08VkbxdTPV116/8aCbN+9pq19KWJLWzQJzKfNs+u976rbnv//31FwoQWZyOsBbB9WAJoYWGxrOiulLl4cpR71m/hdL6brHK5+uRhjvQNMpnvJudWKVQr5N0KhUqFjHIpZnPMZXNMFLqZz5mthW1DKbZMz7BnfJyFbIaTvb1Md+UpZTOUshkGi0V2j01y2bFRFnwX7uGhfu44dwfFXHaRyyRmUjQH13GY6Csw0VcABmsxhUOzRdbNLnDh0Qn6iyVmu3I1C+Gxdb2e1dHCwsIiBpYAWlhYLCku+NPFrF5HuVwzfox9fcOcznWDgsf6R9iQm2VjcYYdM5OUnCzFbJZiJstsLk9VhEK1wkhxlgsmTzGXzXG8p48Tvf0sZLPR2MBgS7n0lUusK87TUy7TXSmTc13KjkN3Xx9drsuJ3j5K2SwIOK7L9YcPU3UcHti4gfGenogF73Shi0NDg3RVynSXK0x0F+otfTqSXMyNLIGN5CAUc1mOD/VxfMi3ErouA/MlhuYW2DoxywXHJnl46zDHh3rSJZQYLYGGdlN/V4zuXog5VL18jba9+68WLYL7XmqtgRYeFELVljJuC5YAWlhYLAkufFN9Uocol4unRpnP5DjcMxhy1Qonu/s42d1H/YB6ed7CHYrh4hyb5qY57/Q4M7k8M7ku5nI5KuIgKPJulf7SAuuK85QzGSYK3czk8owXuilnMmTdKltyOYYmJzh/fJzx7m4e2LCRTbMzLGSzfH/LlvjYuhCKuRzFsCUyqU5gYqxh6CBjjj2CGKLoOo6fMFJg/4ZBhqfnueTIGDtPneahbeuZ7s4nCNV0SCSE8TGE4rRnAI26iBen2v2eevfwvt+1hPBsho0BbA+WAFpYWCw5+soLXDJ5nPlMjgeHNrVc4kSJMNbdy1h3Lw/jMlScp6dSpqdSIuMqlEA5k+FETx8PD29kIRcfVyi5HKP5LjLK5bzxca47chhHKe7b1Lpuqw3j/d3cceE2dp6a5ronjnFioId9GweZLaQkghYWFmc0LAG0sLDoKALLHwBKcc7sBDtnJ3msf4TjhX5w4i1HtSEGubq31MVhvNDLuGmFkLAwLUEkQFUcHl0/QjGXZXhunslCoa6fKeEkkhWszRexBEYUSoCp3IwxJToGolAiHNgwwNF1vew6eZobHj/GZE+BfRsGGe8N3NemZUjSqRxnsWu2Ek3d8IiLWKJz+DvO/ct31Y2xFsGzBzYJpH1YAmhhYdEWLnpj/codwS25u1Li4tMncEX47vAOFjI5rzpIwioZSYtdJFGqWI6kl4yhfqm4g4NDHBwcWhTY7nMllG0cVkot/qcxmvGhGuMPFxvKmSyPbR7miY1DbJuY4dLDp8i4LicHehjt7+FUfzeuk6BbiyuLRNRthRxGagpqLxH+5rl/8e66Sfb+niWEZy6EqrIxgO3AEkALC4uOQpRi6/wUu2fG2d83zOHuwTPGrbrW4ToOh9YPcGi4n96FMhtPz7H75BRXHBxlvLdQI4Tz+SXMtLaw6AC8FQctAWwHlgBaWFi0hIturbf8Zd0q2+an2DY/xXwmx/eHtjOX9ePNwmXuNDmGJN6mXcN6v7paxAbXacTa2CRPTfKe6kqlFR+xFOonI87NHddmggizXXn2bcizb8MQ2arLyPQcG6fn2HNiklLGYbS/h5P9PUz0FFBhAu8fbJIlL6neX1MwudpN59/X99w/f3fd7r3/7+Wt62CxbBgdHV1pFc4KWAJoYWGRChe9QXP1+g/fnsoCO+Yn2VCa4VS+l/sGtjCTXYylS/R2+n9jKp3EzmeUF8MvjARPSZBWnKBdgnLN+jPTukkjw4xnqTEDTolKxlksKeMqBucX2Dg9x8XHxlAifGf3FqqSiR+c6BpuciWRtHJDENfUUK/CubdphPBllhCuRnR1daXqt1ZiAEXkh4AvAPuUUntC+38beCmwG5gCPg+8Wil1Yjn0sgTQwsKiIS5+nV7OBVCK9eVZthcn6amWOFoY5DtD51B2/FtKKI4ucT1dg3UsyTKYnIARGhOzLw0SLXyBNcwgOam8n6m/fo4WiWzMSTMRvrQHG0Nup7oLTHUXeGzDOp585CSXHx7l+9s3g8QkZMTIa9inWcthGujnTfsrej8f5727nhA+8XJLCFcD+vv7E/sotTZiAEVkE/AhPAIYJn8/D/wl8NvAF4FtwPuAjwDPWg7dLAG0sLBIjYxbZcvCNNuKk1TE4UhhiNF8P0qkLQ+fxSqFCPdv3cB1+49x4YlxHtm8fqU1sjgL4JwhK9iIiAN8FHgvUCBEAIGbgB8opf7O394vIu8D3r5c+lkCaGFhUYdL/jjq6i1US2xfmGJT6TQT2R4e7t3E6UxhMblDpc/ONbXrHZPi88zu3Wj3pr2iSQNSCmx7RTijdS90sCbzZlqzpzHr1xPgivC9HZt5yr4jzOVzHF43kFJuY9eveQ3iBLlN9A2XkombVH9pOe9dmkXwFdYiuJrhrn4X8OvwrtK3A6/X2r4JvFhEbga+BmwEfhH41HIpZwmghYUFAJf8kU/8ag9NxVBlnu0LkwxUixzPD3BX/04WnOgKGHUwuD11omZ0DZv6aftrm0mxgTFjFmvVaXX9TP07hQQzaer6gmmSQJolfoYEGRRUnAzf276Z6w8cZT6XZay3J6p7y0Qzpb7NzGUaoJHSSHK6Jvi8d2qE8JWWEC4HDh48mNhHwapeCk5Engm8BLhSKeWKdrEppf5DRIaATwM5PD72GeCFy6WjJYAWFhZ1cJTLptI02xYmEeBw1xAP9m7GldV7s7VYesx25bln2yauPHKcx0aGObhuwJb3segYpqenefzxx7nrrrt49NFHU4xY0RjAERG5K7R9u1Lq9mBDREbwYvlepJQ6HidARJ4KvAl4FfB1vBjAt+PFC/7SUikehiWAFhZnKS55rZ/c4Rs9utwy20pTbC6dZjrTxd7CCBPZntpDPsnq0qpLN9ESWN+9ubIxprk7hSUyGUaOxeDerltpRD/IJEugyeJXa48OGe/t5tvnbOPSYyfZenqG+7dsYKZLX1pOGlo6JcHil8q616GA02j2sNSJ1/ntnrf7VnJfycdfZS2C7UApxT333MMdd9zBvn37OO+887jkkkt4/vOfzzvf+c6VVq8RTimlrmnQfimwFfhEyPLnACIiFeAFeNbB/1ZKvddvv09EpoBvicgblFIPL5HuNVgCaGFxhqNSqaCUIpfzXLdP+sNQVq9SDFSLbCtNsq4yx4l8P/f0bGc+E3qoN1m6pONEMK3LN6ZfI7LYqN2IpoMJDeONiBcccQ2Hk4B1v7DpBBlIUxIh0/vN5fPcuXMrOyZPc/2BIxwYGmLv8DqUtsRfatducCxp9G2SwTftKjbpoh+a/1Df87bb6toff/XLmpzw7EW1WuWf/umfOHDgAD/yIz/Ci1/8YvL59OtUK1Z1IejvApdp+34HeC7wY8Ah4OWA/gpS9f8ui2ndEkALizMMk5OTfOxjH+Po0aNMTU0xPz8PQDabpa+vj6tmZsjgklUuGeVSkixH8oM82r3RXOvNwiIMEQ6tG2S0r5dLTpziGXv3c6K/j2P9fTAQlAJSbJ2e5vxT40wUCjyxfpjZJh7wFmculFL8x3/8B+Pj47zyla+k4K/B3Syqq7T0gFJqFrg/vE9ERoGSUup+f/vjwGtE5E4WXcC3+ePS+MDbRioCKCJPB14BXAHsBN6olLo11J7FY7O/DpyDx27frZR6X4LcDcDbgB8FhoH9wPuUUn8Z6rMJ+Hvgarwiib+llCr6bR8EfhV4h1Lq1aEx230dnqmU+mqaY7SwOBNwzz338C//8i889alP5ZZbbmFwcJC+vj5EhGKxyE2vfw/ZQg8uDhXxPi5Sl81rRNK91pSokDYduNXkkASLYZxu0XZDMogm0lwPUO9omigBSRPHmLSi58F0guLHpXbF6nIULGRy3L11Cz2lElumZ3jSiZMMTU3zeMZhoLhA1nW5b9NGhopFrjt8hLGeHvYPDTGdz2P8NmKyh1vOpm5xXOTcRJJF4rfPf+ttdbsf+0NrEdShlOLLX/4yjz76aFvk7wzAW/Asfq8F/gaYAL4KvEYpVW0wrmNIawHsAx4E/gl4V0z7rcBvAS8G7gVuBG4XkQWl1AcayP0HPML4i8AR4BbgfSIyppT6qN/nTb7M1+CR0JcBfxaSUQR+T0Teq5Q6kPJ4LCzOOHzlK1/h3//931m3bh0HDx6sy6T7+sP7AK8IVUUyPFzY1HwAf9LD1OSqNUyTehm1NtCwaLRKQexMMBGDTgUZJmSnxg4xEUGTqDaIn465fJ4nhod5YniY3UqRGR/neF8fhwa9RJHxnh4ODg5xzuQkVx47RsVxONrXz7G+fhayjR9DdfqkDUdolzCK9lc7Z9HsYU1MQAj/TCOErzn7COHk5CSf+9znOHr0KJlMhqmpKarVKr/7u79Ld3d3y3IVsqqzgHX4RrNbQ9tVPBL4lhVSKR0BVEp9Gi9VGRF5c0yXFwLvUkp9zN/eKyLX4dXAaUQAbwJep5S6w9/+OxH5TeAGvOKJAOuAryil7hORR/3tML6FR1DfAvyfNMdjYXEm4vLLL2dkZCS27V/2TgCQVVUuLp7gYTYtp2oWZxFm83lG10cLRlcdh73Dw+wdWse6YpGt09M89fBBprq6ON7bx0Shm/lsjmUKf7JYBhw7doy//Mu/5Prrr+c5z3kOrutSKBTYtWtXR4o9u2tgJZDVjE7FABbwLHFhzAO7RGSnUspU1OebwM+JyL8Bo8AzgEuAN4b6vBn4lIh8GHiE6BIpCngl8DURuU0pdRcWFmchhoeHGR4ejm2bl0+zrTzFxvJpjmUHWrKQpLaSJSVKdCqRIp2nszmd9LqASVbNdo+lXajo3LqOab/rSNHk8ByNtmPkNLTaiTDR3c1EoZuH1o+wcXaWjXOz7JmYQFBMdHltVXFYPz9HRrncu34LaZehawnNHqNh7eHaOa91rP97wVvqLYKPvvbMtQiOjo7ynve8h5/+6Z/m+uuv77h8xequA7gW0CkC+Bk8N+wXgQeA64AX+W1bARMB/GXgg8BxoIL3nf5f3+IIgFLqHhHZCWwATiilIj9NpdQ3/IDKdwI3d+KALCzWOpRS3PSKt7CtPMkV1SLHcwN8r2cnpaCQs+khl+CyrclPiOVrXuE2xzcxh54FbCwx04n4w2bQyviEbOlIv2blphzfCjlzHYcTff2c6OsHF7orFdYV5xlamCfruowVeth1eoLBUpGprm6zrHZj/TqEpHOu/2YueLNGCP/ozCCEY2Nj/OVf/iU/9mM/tiTkz6Iz6BQB/H28IMZ78S75o3iJG39INM05jNcB5wHPwYsBfAZwm4icUEr9T9DJ95XHFlMM4Q+AB0TkJ4HvJymslGJ6ejqpm4UBs7OzK63CGY12zm+lUuHX3/1+NpemuSrrcqIwzL5ML644DLajVELMvqmfsV3StafVq5EeSpM5nMvG7o9ua9kjSceWUtfU+xdnSt+/2bhEnfU2GyOoYX0Q02fqpyfkhE9iV55KTw+nQvPM5fI8qVLi8XyM5TpE6JcFTVpTk34bOm56x1/V/v+Zl/xqbJ/Vfu+tVCr8wz/8A894xjO4/PLLl+w5q5BVmwW8VtARAqiUGgd+UUTyeOvZHcUrcgiwL26MiJyLVwH7BqXUd/zd94nIZXhZMf8TN66BDo+KyPvxsoqfk9RfROjv729mCgsN9vwtLZo5v/v37+fUqVOMjo7yjW98g/xsiR8U1jHp9kBZoFxlscRUi2iWAKYkeKZ24709bf8GBBBgtFROJoDOKiGACWvYNpSV1nKnZ9+2SAABRsvlZAKY4HIO2icyeZ5y8hiOcjjR0x+r45lCAMP9G/3+V/O993/+53/o6enhlltuQV/+rNNYxXUA1wQ6WgdQKVUCDgOIyC8DX1dKnTR0DxaTjCuE2OpV80bg+XjZyBYWZwUmJyd5z3vewyWXXEJ/fz8vfelLefa7/w2qfrZikw/H1KVOgs02s31N7UuSJazFppk8uEk1lZuKP1wCNJy31Zg/A/EzkqtG++PaWozfK2cyfG/DNq48dZRCpcyBvnXNZ7AnzLG+OMuW4mkcpRClUCI83j/CXNarW9gqwUwqJxO55kP/v/BN9e7hR163+t3D+/fv54477uC1r33tkpM/i/aRtg5gH14FCYA8sFlErgBmlFKPi8i1wC481+tGFmsG3hSScR3wYeAFSqk7gYfxkjr+SkRejmc1vBn4NUKp0s1AKXVSRN6K51q2sDgr8KUvfYkbb7yRn//5n/eWd7vn32innHPqWL/agCVqbzLerhEpapqo6W7R2HXmzM21bu3GSRoEt0M427aWpR2fZEGMqfdX3764PZvr4rsbtnPFqaMUqhUeGdjQOCkkLYkFNhanOX/6JE/0jVARByVCd6XE1WOHeXhgI6e6+syDTTB9z5q5I5IsEvq//h1f+CceIdxYyDG6UF6VhPD48eOce+65DA62FWySCkqxkmsBnxFIawG8BvhKaPu3/M/X8EhbF/AGvHi+El5V66cope4LjekBLvT/opSqiMiP4ZVv+Q9gCDiAR/7e0crB+LgN+G1gRxsyLCzWBI4dO8a3v/1tXvva1660KhYWS4qFbI67NmznyePHePLEMe4f2oyS9gjAQGme86dPcu/QNmZyXYsNXb2cznfz5Imj3DeYYSrfer26swmXXnop//Zv/8YnPvEJurq6ap8tW7ZwzjnndHg28YrYW7SMtHUAv0qDd1al1DfxFj9uSoZSai/wvDQ6GGS+MGZfEW+1EguLMxqu6/KRj3yE5z73uaxbtw6ATFCMyZTF2ggJLtoAnXb1pm03op0MXC3EL5IFHGzqruAEa2Rk3Cp4ThkLPDfr+tURl5gRM9YY8xdpj98GqEqGe4a3ccnkCa4eO8K967ZQzmiPMaW8MWELYaxLWrFn5hRP9I4wk+2KhAdMO12AYsHJNu9WD8lJhVA/YymZYNP1Phe9sd5F/PAbVt4i2NfXx/Of/3yOHTvGzMwMY2NjTExMMDExwR/90R91dC6FtQC2C7sWsIXFGsVXvvIVstksT3va03jSH3oPg9rtMMnNGgfTwyrJ1ZpEwFptb9EVXDe+UVuD9mjsn/j/qvr9JqLdLuFLYF8SQxhSo1U22iS5SbuiSCqiWddXeHBwE+dOj3HN2GHuGd7KvB+rh6t4xuheRCmOdg9woHeYUpgg1uQoNhdPk3Vdjnf1x+qyfmGWuUyeBSe3dPUHNUjcNRn3u3Cj7RfdqhHCW1eGEF555ZVceeWVte2DBw/ykY98ZEV0sWgMSwAtLNYgRkdH+exnP8urX/3qjlTUt7BYUxBh78AIxWyOq8cO84N1WzmdL4AIU7kCY129FKplrh87wHi+hwUnS9nJUJYMg+V51pfmWMhkeaR/ozGhZNPCNCe6Vm+27VrB1NTUksUE2kLQ7cESQAuLNYbA9fuc5zyHp/2V92adX/Ab4+Pq4y0UzSZEpOxvdJemlJtk6Wu4vm9IXKNkEJMuSa7giI4J/RLRAddwWtd6BElJGgn9TONEl5HW8mdy/apoX0e5nDs9zulsF4/3j3D5+FGPBOYKHO0eZPfMGHcO7+Rg9zqGS3Pk3Cp5t0q3KnM6V2Bfz3oWMrnF+WLkj5RmOdg93PD4215zuBmZwWn0XcCR/YHowCL4Bs0i+MaVsQjmcjkmJydRSnU0M1ghuKshtmINwxJAC4s1hq9//eu4rsvNN99M5nP3xvZJ4lzRjSYGN+uS1WPLgt0J7tPURLCR3m26p02u4KSs4NSkuZ34RQ2JS8CZHpbNkpjUcW3xxC+1vAYuYqVgy/xp1jsZClVvEamBcpHT2QJVhL5qCVFQcrIcLxgKSIf2Rb5OJRwqrOOK04c50jXEoe51VMMJJwoyyqWnWqK3ukBvtURPtUROVZnNdHGoMMRcposI2nEVB+ej6n2MrmLD13zx6+sJ4UN/sjyE8IILLsB1XR5++GEuvvjiZZnTIh0sAbSwWEM4deoUn/rUp/hyboS/v/Uvapa/JDIVt2l8FiURw5QWOSOB08UlJKykrSITt7+RVUxUCt0Sdog20NTfeKxGYmpicclIG3uXiCYtf3XzhefUz22S5bHRvLU2hyPdg+TcKo8Nb2D9wqyfyKF48tRRFpwMGxemGe3qR0kTutR0EPYX1nMsP8C582PcOLGPBSdLycmgkBrZm8vkmXXyzGXyHO0a9FzMlXmumD7CgcIwR7qGGh5zKxDlWwANlj9T8oi+ffHrNEL4pqUhhI7jcMstt/CFL3yh4wTQuoDbgyWAFhZrBEopPvrRj/KsZz2LT37zgZVWx8JiRXGke5Drxw6wt2/9Yq0+pTjZ1cfIwixPmj7BWL6XirReFXPByfFQ72aybpUuVSHvVnBQzDp5ik4uNn7wdLab0Xw/l88cIauqHOgapiMmXhOUotsta5xbqDgOFaediqCdw7XXXssnPvEJDh06xI4dnanQpgDXZgG3BUsALSzWCO644w6KxSI//MM/TOaLPgHULEwBGlrVdEtBg66xHdK6ZPXuCda2iB4J8ySpFbsvyUppgDnusF6ppHIxxvjEDrqCI7rpcxi2O57pmtLalmgRNMxdymQ51dXL1rkpDvYOB6M43D3EutI8dw9upSqZWPlmy198v6pkmJMMc05XrV9c7GBNN3Lc07OdJ88dIee6HMyvo+ykfNym+R78T1ZVubB4gv5qseai9nRW5JRL0ckynu1lItfDZLZQVzdR566X/JFvEfT3P/innbMIZrNZnvnMZ/KFL3yBF73oRR2SKlRtHcC2YAmghcUagOu6/Nd//Rdf79rIB2/9y8WkjwBJpCrO99vAPRwHpf8nrUvYRFIN8yR4hKMdNYGpiGASDLLMclokgiYFdabYaKmRJBbbLPFrx/Wbqp9BYAoXsO4mPtw9xGVTxzjcPYQrDijFZVNHebh/E9PZQkR2Wl2M7ugmSHBZsvygezt7Fka5buYApRhLpBKokmEi282h/HCqtW2D8IXB6hwXFk9wKtvHQz0xRbGVYsAtMlSdY/f8GD1uialMgYlsL+PZHuYz9RZM/fd6yWs1Qvjm9gjhTTfdxOtf/3rGxsZYv359W7IsOgNLAC0s1gAcx6GnpwdVtW+8FhYBpnMFxvM9XD1xiLGuXqayBZQIGdXBoLs2UJEMDxe2IMqloCqxffKqwpbyFJfOH+UHhW2xbuUAWVVlfWWB9cVxBqvzPNq1iYlsb3xnEU5nupnKdnOgaz1ZVWVdZY511Tl2zE3gAjOZAkUnS9HJMZ/JMefkKfrZ0eAlumwrTgLwzW9+k+3bt7Nt2zZyuVz8nA3Q3d3NU57yFL70pS/xi7/4i02P12FdwO3DEkALizWAC990G5fMl1lXnWchl6+VgYgYXVK4WVMnIiSJbtESmJjF26LFME4tkzu65kZrJqM4LMd0bGktgc2ikY+6U5Y/o/yU/ZpEqqQPv71RKZuH+zayvjTHQKXIjvkpL7kn1G4a13A7oX+zVlOFw7zkY9vmJc9UvpvLike4pHiMA7n1zMZkEGdUlcvnD5NzBtjv9LA3t4GyZOtLwhC9HGpubDKcyvRzKtsPeUWP8jKXC6pMb3WB9eVZ+twFxrK9PF7YQBaXy2aPMJfx4h3f9e+fpL9apNstM5vp4iefdgMjIyNks1kymQzZbLbu/7lcjp07d9LdvbiM3vXXX8/tt9/e+GQ1AesCbg+WAFpYrAFkFqBIju5ymWx1cX9Spm0cOUscY4IWO5hIBLXdevek2EHD9FE5jTp0+vmQluSaAhZTym0pJjAl2WnaJashdXmZlPL09oanLI40ijCe72U831vfL9QnbS3EJFJqam8/flJ4KL+VLZVJLise4VSmj325Ec+tDaAUF5WOM+V0czq3gZOVilFuYh1B5W3MSRdz2a669oyqcv3sfk5kB+h1F5h1uni4a5NnlfTHO8qlv7rA3//v/XSpMo5SCPCTV1xItVqlUqlQqVR48MEHAdi0aRPnnHMON9xwA+effz6Tk5MUi0UKhZCL3mJFYAmghcUaQUmy9FBM7mhhYbHmUBWHw7lhjmcHObd8kisXDnIgu55Zp4vN1SnyqspD+a2MLKHVa6g6z7yT47RTYENlmulMV8Ql7YrDVNZzLYfxa7/2a3Xbr3rVq7juuuu48cYbeeKJJ/jXf/1Xuru7yefzHD58mD179rSlq1JiXcBtwhJAC4tVjAvf5AVi54tQrWTIUfXi/jW3T2IWcIx1LiGhNYKIcVFPMk1hfQzLN1oCk3Rvwj2b1rqYGh1+9qbNQk4nzP/b7sG2a/nzrW+psnvbRJI1s+mkDx0JurY6zggFFTI8mtvM+uoMm6pT9JUXmMj08lB+Cyr4ktPITzCZh5tFKda705xbOsVj+U2AMOt0MVyZ5WhuXd34tNfqk570JO69915+4Rd+ge3bt/O0pz2Ne+65hy9+8YssLOhZbK2haglgW7AE0MJiFeJH/+5DjJbK5H2Dn1OGkspSUGXvzq0/7A0391g3b8ryKjoSY/q0/iotgWsydtCIJtymkULQLcIYg9mywA7JCSMtMWyXsDVLhpJiAMMu4U7H6LXr9k6pR+L+BhjL9DGW6Wt+oGHOnKpwWelILTZW+WXMM3gJKjNOFw/ltzCd6UYUjGb6Oac0zrbSBEeyQ7U3PtOleemrvZfV+9/uZQs/61nP4s4772Rubo6enh4cx+Gqq67iqquuav2YtMNzbQxgW7AE0MJijWCWLnJUyKsKZfvTtbCwaAJlvFVMTmV6OZXpQ3x7ooswLzmUU29Nc8XhnsJ2nrRwjO3lCaacbqYy3Uxkeyg68QktYWzbto1CocCXvvQlfuInfmKJjsqiHdiniIXFKkSm5CV+ZOa9bc/TIUxVexhSs4zKILBomUhdey+cGttqEojW35SMURNvmM9opTRZArUJjbX0GqFJS0xtbt3d3a7lL+2xJiHOjNmmxS8sur5/ymzjFpHKypYmUSSmv2m7aReuaf60FkYDmvnaww6A5iYR9uY2cEHpOIcz6xYTTAK4fmawW6JHlZh18oxl+7m7awcFVWbQnWewOs/u0hj3FHYwl4kngZe+yrcEvuNl7Nq1iwceeGCJCKBYF3CbsATQwmIV4fy3ejfPbQs5ssXojX7C6WGDO80pp9+7geukKslNq8xtiTDE+KV1DbdNBLV5m0ESmYzINHGdtHO3mv3bbPsSoF13Z+BeXxa0SOjajg00jUsi1QniUslK4xI3TH7a6WbGKXBx+RjTToEFsjgohtw5Bt15ypJhTvLMS57d5TEGq0X25UYoSp5iJs+JzCAXlI4zVJ1jPoUV8IILLuALX/hCC8omQwFuR4Jnz15YAmhhsYqQ8WOjnTI4C6Hnv3+fO5npZ1DNc2X1AI9nNjIlfumLgCy5dZuxpKrlMjABWi33EuxvkQi2hEZxhypmf9MWOH074WQmxEG2ZNXsaCZJDJKWlNPUMKFlUpiC8LS6mknsXA32N3sMqb+R5SDM/hyPZzcy4k6TVxUG1TyIF2+4N7eRkixSgsNqHReWj3PpwhEezm+mLFlQiqHqPEcy6xJ1vuwVt1FwS1y7ME+lUiGbtXRjtcF+IxYWawiuODya28y6yix7qqMskOOws44pDKsBWFhYWIRQkQzHM0OLOwwstSoZHsxtZWdljKsWDrI/u56qOJQkw6wTLVQdhyBWcGZmhqGhocadW0A1xdJ5FmZYAmhhsQpw/p95rt+8H/NHDnBYLL0QWCD8m/VkppfvO7tYX51hjzvKQVnPSWegdjNPFbu2XN6Tdl3C7cAkwxRI1WGXa+pYwYTvLdo/hcnIYKlV2vdgbK+dC83CaAg7iGAJrFpNWxFbdP02KzfJGp44Pjw2hdu5Ey72RA+AACIczI0wnunj3PJJCqrMI7nNXiZxkg4Cjuu5JAYGBtpXWINCrAu4TVgCaGGxgjjv3e8GIFf0Syz4q3yovHeDjtzeQs9iJcIp+pl1uri0cpiqEsad/th5YolFp+6dSvuLYkd1nEmnh2mnO9mluwxxbsbnRKfm1J7IzRK/RHTiHKV54Ifak+pCtoyU8lKtCNKi7LbmbgdL4SZvMYQjbbQCwIwU+EFuu7fhSFiMeZzy1jkGby3zpYC7RiyAIvJDwBeAfUqpPaH9PcDrgecBW4ATwAeUUrcuh16WAFpYrHHMS56HnK1c4h7FdRwmZeXcwaJcLqweJ0eVzZUp9mdGGM12/u3fwsJimaFXfk+BLlVeMvK3ViAim4AP4RHAMPnLAJ8CBoCXAI8Aw8CG5dLNEkALixVEZt67qWaCFd7CljqJGn5qrmDqG2acAg/JFi6uHuOYM8i49FImS4kM4XU8w6/t7XpPRFMuo6pcVD1GRTLcn9lGQZW5uHKMflXkUGaYkuPfbjR3dthioOvYEK24jJfY4taq5S+167cRkhaBbdIVbJSfdKLTZqkuV6YwLWTzpkVa128riTPNZgGncMk20y/tikCRcaFdXapK2VVc9orbuO9dL0uYuDkoBdVV7gIWEQf4KPBeoECIAAIvAK4G9iilRv19+5ZTP0sALSxWAOe9y3P95hfqb2DB/cxz8cY8nBu4T6elm3tlBzurY+xxR8lTQQGnpZspp4d5yVNBqOJQFQdXOVSRmksnNQIegCKLS5cqU1AVtlfHmZEunshuBBHm6OJex9PnyvIBjmWGOJIZoiqZOjkmIihK4aCo+hYEE9Fr5RkQnN+WUSNspid7wrYJSe7ZWr8W/LOma8fUr814u5q4JSR6LccfptWpXd07TfyCv8vhKtbRAjHMqYq3WscSXQNrIAbwdXhH/3Y8V28YPwfcCfxfEXkhUAW+AvyBUurUcihnCaCFxRmEBcnxWHazt6EUXVQYVHMMqnk2uKfJoMjgklEuDi4ZFG6IFFb9/7vi+Pv8NhxcEXKqSkFV6FJlulQZEIqSZUFynHT6OZoZqnMVVSTD3uxGjmTWsbMyxjWlAxzLDHAiM8iC5IzH0e8WuaB0nILySOy8k2cqU+C0081kruCVq2jBJWVhYbF8yKvqmbpc24iI3BXavl0pdXu4g4g8E8+1e6VSypXo/eo8YDfgAr8E9ADvBj4hIk9RKjHNpm1YAmhhsQIIXL9Oyd8RhMmELX3hF2ft7TuyX59AASIsSI5RBjnhrxwS6ay8FUEDUpip+//iPsf//7zkmHR6WJAcRckuWvMSsCA5HsttptstscWd4orSQWakwPHMABOZ3rpVCdZVZ7mgdILH8xsYy/ThiEuPW2LQLbKhMs15pZNklcu8k+NUtpcTXf3MZWLKUjSw8tXWAo47Jy2gWUNEy4aLVlzTCa7bprOCm5y2U/2WA0aDblLyhr6jWTktWAQ7fd6MWcEpk4fi9MkoF4UsCQX0soBXLL7wlFLqGlOjiIwAHwFepJQ6buiWwTt7z1NKjfvjXgjcDVyLZx1cUlgCaGGxjNjzDj/r13f96vcv440yIUbMeM+Oi/2r6ygoEVwcyqa5kyZLCRGYz+TZm9nAvux6RtwZtlSnuKBywlt9wMnT6y6QxeWh/BZOZ7sBrx7ZdKab6Ww3sA4l4CiXXlViQ3may2eOUhaHE139jOb6WcjmFvVsM7YubdjbUtdiXpxoCWQ16wrWgj9bTlDWXP+RJQbDxHSFsnLb7u+jKeKXIlM4Vp7pJpASpvOfKLdB+7RTYGN1esm+v+rqtS5eCmzFs+YF+xxARKSCF/93FMgH5M/HA/7fc7AE0MLizMDu97wLgHzRj2fzV+yIJAOEN+JIm8ESqHsXTJYtFbNvuUqRhB0aShxGMwOMZgYQXPrdBbopcSQ7xKzThRKJkNfwtisO0xSYzhR4onuEweo8m0rTXFM8yFwmz4l8P6Ndfd7qBZjPh46m1x82mT/aPFepoaQF01wwNioq3Kwfg4moNVKtmf4NoeuAtt1pgtGhGMJW1xpOJaMFWQ2hXaupCaE+PtQ+Ri/nM0quWmlSmWQoVnUM4HeBy7R9vwM8F/gx4BBwMXCjiAwqpab8Phf6f/cvh5KWAFpYWKwolDicznRzWrpbEyDCVLaHqVwPj6mNDFdm2ViaYff8GKezBU509bOQybBt/jQZXE509eN2DXf2ICwsLCJwnSxuVRhWMyutyrJCKTUL3B/eJyKjQEkpdb+//dfAS4EPi8gf4cUAvge4A7iLZYAlgBYWy4DMvGf5C9b6TbIMJWYB65a9tO4fMbclujkbN5uRZA3TLXym/SncuUqEsXwfY/k+BJeR8iybFqbpciscLQywkMly7swYkoOT2T6UdDaGqGVX8EoaMpqM/Vq0FMa7gmvX2CqK7UtCxyyItQz2xu1p9reUKdwOEu4hRougPl7bXyTHiDvbpnJxWNEYwLahlDrmF4h+N567dxL4LPCq5UgAAUsALSyWFOf+ReOYP2MdMS0JRLSHccRdlxZht3JaV3Cb8W1JwxKXrTO5gvUJtHYlDqNd/Yx29dfJmsj1cH11iqsmjvCDoS2UMsm3QVPyzbIj7iGb1teasKRborgkF+BawBIlsrQ8bzPEb4mTQYyErjZR43lNLuIjzjrOd09QKpXI5/NtalmPtZRh7K/ucau2727gmSuhD7BG1lGxsLCw6BCqjsPjfRsYy/dy7dghBkrzyYMsLCxawsnMAFUc/vu//3ulVbHQYC2AFhZLCCdY49ePgdbfso0v3bobTbNuRYLgTQoYxscNMpZMMclOQlrLYZOWPVMSizFpJE6WI+zrH2Y6n+fyyWM83r+eYz2DEd0j44NN3SKYVCU3ENtqAk5EUIyMVi2BETmaOH3OSEKG5grWwheWLFGjHXQocSLx60s5T6qsXn3uDp/P1C7eyMDk8cecQb701a/xp3cc4gd/8Yp21FyUr1b/SiCrHZYAWlgsAc7983rXbyvlW5QQWSVDdwVHyI7BpRxbDiaJjCyx6zeiR4sxgI2yhRvKEjhV6ON72TxPHj/KYKnIvv5hillzgep2EeFey5UtXDephuV27Tbreg6P0YaavNqRjil1aPlcpO2fpl8K4peK/CUdewISCaE+T4P2gwyzjQm2uKfTTZ4SazkGcDXAEkALC4uzGnPZPN8d2cHumXGuO3mQia4ejvQMMJnvxs3YB4yFRdtwHMZUHzuq48l9U8IrBG0tgO3AEkALiw5i11+/E4Bc0Vsho2ah8HlE0pt7xAWcZPHT0NClHOwzWdxMQppFs5bDDiWBNLIUJiWaVDIZHhvcwN7+9WydO8250+P0VxaYzeaZzHdzoH8dC5ms0fWuu4IDt2jk69asXKlrq9UUjtkfUcY0SUqktY6ZXMH+dWs6R6mTS0Lyjb+blBa7Vlc7abaW4VKtlpKqb6tWyCYtgmkvJ73/3swGrqvs46GHHuLiiy9OJ8RiSWFfby0sOghnwfE+JW+ZN+X45C94KGqfOpJHdDuxn/YxyU81p9bXNMdSfYznJkGvpP1xx2waU804HOof4q6NO/jalnN5ZHADrgjXjx5g1/Q4jnJpCUr7tIs4WZHt4CA7DP36WQY5xmuyxX5LjoTvJvVqHo36muZqFvq1mSCvoe4NxlUkyzQF/vM//7MNZevhIivyOVNgLYAWFhYWMXDFYaqrm6mubo70DXD+5CluOH6QR4dGONndS2T5FQsLi4bYm9nAwNFDnDx5kg0bNrQlS7GqVwJZE7AE0MKiA9j1Xm+pt1wx8PUaOmr7jfHTviVDW3Y14spsyqVs0sGga9OewxYTGtrK7g2PM/Q3ztXIOqQdy3w2zw9GtrJuYZYLJ06yfXaKR4Y2MKfXNdNOeM0VrM+jwr3aNNQZfa1tyAyL1+SYvmcV7iCq1iG1K9gEwWhZSnLtppIdN860v000U+OvYy7fVpFwHSUtm6jfoxQwKwVGRkb4l3/5F373d3+3bRVtEkh7sATQwqIN7Hq/F/OXWfDX+K16+40xeg3inCLtYYKS9NCNb44d37FSJBpafh4ZCFuq7N407aa2mHNhJDf+9nihl29v7mHHzCTXjh7maG8/eweHqTqZ+nl0FUMPQZOOK4Ym4+uS4uIU2stLs+qkfLlpCvrvrDZZB+eIQxOEL0Aq4rfUeuvzhWH4zaR9ifmpn/opPvCBD1AsFikUCm2rZ9E6LH22sGgDUhakLGTmvU+NtDn+p0FcWqROXUzMWlJcXES+H3PYKBYwScZKfZLiF5PG6Ra9puIJY8bEfk+AEuHgwDr+d8tOcq7LU48dYMvsadRyPJX1Y4HIMUS2TbFdJiLRarxiRI+k4LWE8TFtab9PY7xrwtyJYZP6vPinyDRPs/vPJBjiHq+++mq6urr4/Oc/36Z8Lwt4JT5nClIRQBF5uoh8XEQOiIgSkVu19qyIvFpEHhGRoog8JiK/nULuV3154c9XtT6bROSTInJMRD4kIoVQ2wf9MW/Xxmz399+c5vgsLCwsmkUpk+XB9Zu4Z2Qr26eneOrRA+w4PUnGbTFRxMLiLMGmTZvYv39/WzIUNgmkXaS1APYBDwKvBo7EtN8KvAr4Q+ASf/udIvKiFLL/CdgS+vys1v4m4F7gR/C+85dp7UXg90TknBRzWVh0BLv+9h3s+tt34CwIzoIYLXBprV41mKw5CVay1PM0mMtk/Ur6mHRtSbcm9idZ8VLNZdLdhJi5pgoF7ty8nQfWb2LdwjxPO7KPC8dP0l0uRXXqNBpdOyYkWf5MU6n6T+p5Dee+aStdJ9Ds3KbfqQGdOKYlu1aWGGkNvpf//m1s3ryZU6dOLb1SFg2RKgZQKfVp4NMAIvLmmC4vBN6llPqYv71XRK4DXgd8IEH8vFLqeIP2dcBXlFL3icij/nYY38IjqG8B/k/CXBYWHYH4yR5OybtTm2KR05bc0mMAg4dA0koHSeFbjRoiD5lWH1itDYvMa9RHbzfoGWmPO9aQrLiHbNpElqiuwmShm8nubgqVMjtOT3H9sUNMFgocHBhirLsbRNKf44RjXVQkRZ8msaqWbNMRfH/1mzUk5sMkHZsuv8PnovY7Nil6JiLmWHfv3s3dd9/dtugzyR27EuhUEkgBzxIXxjywS0R2KqUONhj7MyLyU8AY8EXg9UqpcLnwNwOfEpEPA48Az9LGK+CVwNdE5Dal1F3tHIiFhYVFOyhmczw2PMITQ8NsmT3NRWOnUMDBwUGO9vfjOjb02uLsxoUXXkipVMJ1XZwWfw+2DEz76BQB/AyeG/aLwAPAdUDg/t0KmAjgR4H9wDHgAjyyd6OI3KCUKgMope4RkZ3ABuCEUiryrqSU+oaIfBx4J3Bzh47JwiKCXbe/A4Csv9JHUhWCJItd5PYVfluOcSNFLn7dopBiHpMlrdl7aatlX3QYLXttWv4i7mm9b91JiRlDzHk1HWvMftdxODIwyJH+AdYtzHPO1CTnj49xeGCAA0NDlLIxt99mz2Wa/klWpqAkjUrol9b83KoeunjDtR3bJ9KQTpdlywo+kyx9bWYFi/JiAAFOnDjBli1bWlbFEsD20CkC+PvA3+DF6ingKPD3eDGBxohopdTfhjbvF5F7gceBZwOfCPWrAo3cxAB/ADwgIj8JfL+FY7CwMGLXP3h5Ro5P/Gp3N6cxQ0gifBHviIGUpfEExk0UKT8SamvXBdyxZ1kSIU0iqilcxVGS6AcsJfjWE58vEV3iCroJE4UeJgo9FCplzpma5CkHD/HIyAjH+vuILSidRm5amA7CRPxMF22rKmiMIHLKE+YLh0Kk1Umfo22il+R6VvH7U5+7tUwQ074Iav26urp45JFH2iKAFu2hIwTQd9n+oojkgY14BPAlfvO+JuQ8ISKn8KyBzerwqIi8H3gb8JwU/Zmenm52Ggsfs7OzK63CsmKT4xX8lawf+5c3LO4bYXD1m5EHmeEhPJzLNmxPjbhxaePLlhvtEsAG4/R963MakdeR9jw3SdRUPsd4Tw+l8gKXj41zvlvlifXrKWW0AuJNm7RSKJny2ksduGrAet+yGT2Eej2CecVkItBKiDTqY/x9qIR++n6T3JTzNa1HA5j6rCus0vK9TXgUpqen2bhxI4cOHWr5Oaw4s0qyrAQ6eiUppUrAYQAR+WXg60qpk2nHi8gOYD2eS7gVvBF4PvDiFHPR39/f4jQWwFl1/k4UKwBkZ70HdSP3Rh0MhFDvV3sIhtpHF8qJ4/T2pP1ho5fJ5ZqIdq0UusUgpUWyWVdxnAt4kXXkGC2Fzm9kEoPOBt3SWugC8aPisH94mD0T45z3xBN8e8d2FrLZKAHsRBaC6aUkLQHUYbpOQuNHy2Xzb8EwbyJ5Ivn6TyR4TfZrenxKfQKYCGbDPsCpuei9YcWRlgCK9+zo6+vj6NGjbT1HzqSSLCuBVARQRPqAPf5mHtgsIlcAM0qpx0XkWmAXnut1I/AK4ArgppCM64APAy9QSt0pIucBv4KXXTwKXIhnvdsP/HcrB6OUOikib8XLPrawaBu7Pvg2AJxiDiAx5i/KE+KZQ+SerbusRHN9GYw42vBEqLjOTby5NzNX/ORESE472b1x7bHy/BMZ5iDh41w8zwaLrvFhVt8/KYYwDNdxeHRkhIrjcNXRY9y5fRvVTOMLLI3Bo9OZq5GYrqat0E1eMXF+W02HVZ2pHIeEEAOJOdZa16RjXqXu46Sl4rZv3863v/3tZdXJoh5p02+uAe72PzuA3/L//3d+exfwBuB+4LP+9lOUUveGZPTgkbwef7sEPBMvgeRRvBjCO4GnKqXmWjwegNsAW2DIojOYz8B8BqniLfMm3ieo91eXrCFEVgCJ1qxT/idmrG6xintuGsYZa/Sl+DQ7xjRX0sckx3SsSeMS68qFitYZj02bK1IexlT8Tts2lZUxyg1h77p1TOfzPPn4CYjmuDUN4zHoMJ43Yr8PYx3AJETOnSZf1yOun+n3kPJYkq+VDo0n9JKV8L2HUdcv6feQcA4S7y2rBOeddx5zc2086hV2JZA2kbYO4FdpcAkppb4JXNqMDKXUIeDmNPM3kPnCmH1FYGc7ci0sLCyWDSI8sGkj1x0+wjmTUxxYN7TSGllYLDnOP/98qtVqy2sCK2wWcLtYpdGkFhYri3M+4GX9Zha8n4jJTdmsS3bR01PvHzHKNwgyZkUa5ovrluR6NaLFe67J7R3RR28Xrd00rva33t0bJ8ukQ2I5mLSmr2B8yu5KhPs2beSGQ4cZ7e1lviuXbmBDmb4qpougVVeuLzCp3EcEpmxgQ5hDW27R1QrD9VbblOj50PsGlsCmjz1h7qVC3HVyxUtvA+Amx+Hxxx/n0ksb2o+MsASwPVgCaGERwq5/fCsAUtR+GmmDJfTYnsbdIkQw4hpLGK8jiRiqBm21PmlJZ7NIms9AzvR2M1FUsf2NsuvYsKFfAiE06mLaboC5fJ4n1g9z9ZGj/GDrJk6HrCKr4jlnOGg9zlVIea00Inz6/oTvxTg2fliEAyf1a3p8kARiOsYAMWQ8kbhr/WrNK00ITSejAXp7e3niiSdaJoAW7cESQAsLC4tVggNDg5QyGa4+fIwjg/1Md+WpZBzKGYey41DJOFScDBVHiK0faGGxhtDb28vY2FhLY20ZmPZhCaCFRQiq5Jn6MmXf5KcXeo6g8Q0oyVNbe2nWLAU1N0/C7Enz1eZt8HZuvIdq1olW77Umy0TUddu43WwpNFj+Qv103SNutCZNQE1b/tJaV0Q4NtDPeE83uycm2DA7R67qknVdsm619v+Mq6g4DgvZDAfWDXJo3QDKQAgXjcuNzdOJpyKtO5v68xO1ZMWfRJPlqyV352qHyYSYxhIY9O+0WzzJXdEm4r52pRSZTKZlmcoSwLZgCaCFhY9d//hWpFbuJW2sV308VFpCGOml3x19F6WKeTAkz9Jg3pgHjFFou/fWJOKY0rVrivGrTWMgfrExgLqKJjdaWkKoI+lYdXkGLOSyPLxxQ5TcBuKUIuu69C6U2XNqnK2np/n2OdsaWgU7RgQNypu+5+R4yvq3n4haZxD5M7msY0962t9P2v768NQvJQntupwmXMHtrAVs0T7smbewsLBYY1AilDMZJnsK3LVjC6Jg8/TZtTqPxdqH67ptWQBdZEU+ZwqsBdDCwodayOAEK3I06Q6JWFdqiI9K140gtfEh61WdG80wX7OWQRV2HaW1+C3V/S7BtZsqu7euvYG8OEtLCmtLokVQl693M7nlDPNELq9UFkfh0Y3DPOn4KU709xpdwRGd2rQE1lRo0kLX8ezkTqJpa6i2rbtlg/1JxxbXbhgTuTc0cCM3QttJJC2izgvRhgtYKZsF3C4sAbQ467Hrw17mr1PMJa70YbzdmAhEkj/E9ATRCErSc6PWrxViaHLBtohG8YZhdCS7N268qZ/e1ogMN0sI9eEmMqvLSYI/MLiO1s/OUahUmOguMJfPeWRPYKyvh/lclu1T0xxaNxB7LCYdI0SwpmT98CbfiaLQrs0kIhqe16jDanMPp3T1p7qumrzWEq/NhHPVcUKYQv92LYA2BrA9WBewhYWFxRrB1qlpLjt2kqsPHeOWR/Zx4YkxHNd70j66cZg9J8dxXDdBioXF6kC7BHCtQER+SESqIvK4of0SEZkVkcpy6mUtgBZnLc77l7d4/1mISfxo4H6p/099d2NmnqFBd/3WWQLrXsHj33RbsQwa2zr0Mt2sRaid7N6G7WlMGEm+PW1/kpXEaMVM6pcSh4cG6K5U+M4528hXKjzp+CmuO3CEH2zdyFR3gcnuAjsnptg3si6iwuLk8bpErNWNNxuHEjQ6PpOrsunK0msQCddDw598q+ELSfIMSG0RTHI9N7AEtpcFvDbKwIjIJuBDwBeAPTHtPcC/AV8GnrOculkCaHHWolrybzyVkOsp9f1Ey0QlcNXFd4vcTCOEz990FnfXxwCmpXpx2tX3Tooza7vcS8rxHcnujWk3xgrWTaERbFPl7iYJYUQn03aL7rVSxiFXrXr/z2a5e/smdo9NceP+I4z3dOMoxXmnJjkwPIjrZ1cmZp4Gm0lEMNKvM2i7fEmdME1WszI7Fc8YIDiFqm4z1YuBkcCZwhcSXjLSrh6UGDLQISKYV2Wmp6e56KKLDAOSsdpdwCLiAB8F3gsUiCGAfts3gW9jCaCFxdKiZvnzS740jBlLDZ90aEJMlsHFWD+pa657QIREmWP7mieGRgtg46GJaPr5nUTYTMTP2M9M/Go6hmTU1wFMyXKSAu7TnrsmH74BypkMuWrIxSvCvpEhDq0bYNP0DFlXcbKvJ50izRLBBFUTiYE+MIkwpED6WEqtv75t6G+eOGW/JDSQk8htDC+RUUHx8pr+vjoIJXCeOsE8WX7hrz/FvX9+QecnWR14Hd4ZfDvwer1RRF4AXOt/fml5VbME0MLCwmLNoJxxyFeriFJ12b6VjMORoYEGIy0sVg/ybplB5nkgu7VlGYoVzQIeEZG7Qtu3K6VuD3cQkWcCLwGuVEq5omXni8jFwLuAZyql5vX25YAlgBZnHaoLvus3uHk0LPqc8KM0BkYFWxLbbIr9q7NypbgftGIZTHIBd34pAVN3Q4yfJi4xu7eRBbHVOKcki2Bad3ezlr4Eea7jMNFdYPPpGY4N9seadJMKMqctv5I2NrDWPyyv0XGktJ6FrXURl64+1uT6TbL0aeNbRtIxmVzB+vg4xHxfjUpERcalDF9IvdJLB1z2ezhBkSxTTm/rQtTi+VwBnFJKXWNqFJER4CPAi5RSx2Pau4B/B/5YKXX/0qnZGJYAWpw1OPef65M+dOIXu+RUywXaalL9f+OJoO4KDusSG8OWdtaGxNAgJYULtcGwpp8InUruaOjCbtKdlZoQGtmPYd64lV4M47eePs2m6Vnu3bIJNxMt1DDa38u6uaJHAMNjU35vHSOCMbovFxJdtybilxQj2OaxpCVHTX1lSe+gSd+nadJmYwbbhS9/hzrJIPPcL9vaPt+ruCjzpcBW4BMhy54DiJ/p+3rgScB7ReS9frsATtCulHrLUitpCaCFhYXFKsKOydM4SnHd4SPct2UTs/l8ra1QLrNlaobjA21YTiwsVgrKZRuT7JUNTDs9K63NUuK7wGXavt8Bngv8GHAI+B+t/aeANwJXACeWWD/AEkCLswAX/OebAHAXvAdppNhz6FVXT+KodYnsSXiHN7iGa5bApLd1x//ob+nxszVnGfT9JqlLmCTJTDl3BJplr53s3oZyCB2r7mJv1yKYlBKrn+QE13JXpUJvqcRXz9vF9qnTXH/gMBM93UwVuiiUK2yemWHf8BD7hocaK54CicWIkyyBhi/CZL2OzGPQJ3Jqw/2TLHomtJv0sURIug3EQnexN/460q07HKeMrlQHztEOxqkiHM8MtS1LwarNAlZKzQJ1rl0RGQVKIZfvlNZ+jT922VzClgBanPGo+DF/qqo9UWLvHfF3OWN2b7O3cGM4VcyTTRq4aw1idTQTWmTMrk0S0Oo92BTjp8/fLPGLKe+SulxLSkKYHCsY76Y2hhj46C6XmcvncB2Hg+uGODbQz8jMHAMLRWYKeb4zvI3ZrnzDc96xcnqtuoSblV8T3JqYhmiT8LUdDpvSzU7j3ZE+dXcG0+k3EekmXcNNw0A0lcAmNcVJ+qN9W5xoLdQBXM2wK4FYWFhYrBLkqi6lUGHccibDscF+Htk0wsF1gx75s7BYgxh0Z8nickBGVlqVFYFS6lalVFwdwKD9g0qpZTXKWQugxRmLwPVbLXZ5O4I34UYvjcHbauQtWLPo6EkdkX4JiRaaKzjO/akkxjJYe7tu3TJoHGlKwkjXvWm0ld0bK0ez7CqiJpyQRTC26G5Kq1TaZBG9X1Kgfb5aoZxxjKanht+JdgytWgLTFo6uQe+Y4F43WUM7nnQQUqlZS1zHdEmytrUh15QBa7IMGo3PSZZeQ7/URbD9v+eoMaYpUM1k2j/+QJUVct2fKbAE0OKMw8UfeyMA5aJnLakRPpPrN+YmIlqnaJd6Irc4zjRCixVL+XA1xvW0QQyNXCetC7jTLsY4120DfaL7Dd9rTJzUYl/fxW5wEacmPwZdmy2pURsHdfX9WkKTRNDU3ikC0KpLsWHs3xIhdYxgp13D7cgKoOr+RLul/f6a/Z4NWKxE4HKeGqWXBe5zti2+IND+PWS1xgCuFVgCaHHGoVr1l8Aq+xEOjoEgNET93c5MCFNaBvWHqGYJ1B/Waa0oOpohhsb7eVoi2C70c2GaR39YRExH2t8wkiwuDSyEcVNE5BrQ6nNpuivPjskpY0JEU0hJBNt+CNcu4dDvLHztprSqrko0q2twrQabrQTnppkj9uVG66cMzSaCp8trNH/ceP36Es/te746QRaXh5wttcxfY9xvE1Dq7CaAItIL7AS6gZNKqUPNyrAE0MLCwmKV4HQhT99CGcdVuM7Z+3CzWNvocYtcwHG6KTMhPTwmm6g4lm60CxHpA14APB+4GshQcxzISeDTwPuUUt9NI89+IxZnDC77nzcAUJrv9nbUUpwSXmlNQTN1qH+9Fe1NX+8XcQ0by4bEWxBrMWom90tblsEEYmFysaYdnxatWv5MFso4C4jJ+mS0ojS2CDYbK9gsXMdhNp9j48wsxwf62nezg9ESWGtOmKPpmMAAafudwRbBxNIsTYwJt9cVrW90jYe2kyyB6Ps1eUmuYCWQdStcqI4xQJEZuviecw4LGS1xKeb4Ln3VbQDc/46XxQs34GzKAhaR/wvcChwF/hv4E+AwUASGgScDNwNfEZGvAr+nlNrbSKYlgBZnDOaL/gofhod5QMKMboNwRLExDqtJ17BO+PSbrsm3GMSo1fZqhNKgXSpi6MutiXd1HeNj8Vpd8cOElpM7jATQRLKJccGTzk2pyUyMFdTH6zrqiDmVD24e4fIjJxiaL3Jw3SALmQxVRxpck81hqZ6Zi3Lr4ys7Gvemo0kymnQJL3Vcoz5PJ2QkruiSkghGzk2T13TeLXMFB6ji8ANnOzOZ7th+4Rfbdm8pZ1kSyI8DP9bAuvcd4G99K+FLgB8F3tdIoCWAFhYWFqsIEz3d3LF7BxefOMW1B4+Sr1QRYDafY+/6IY4N9HWMDFpYdArb1TgAdzm7wLEV5joNpdSPpew3A7wzTV9LAC3WPJ708VsBqCwUABBtjV/9DTRadNlDnZVNf7Vs0iKoWwJrySGGtX8j0F2UuqtY9P8sDkuhZt1Q/XwZDaQtco7ERAbd1asP1C1/SS7qmELQ5iQQbdvk5kybLJKUdJJy/nI2ww+2bartdpTLurkiF4yOs3Fmjnu3byKCBKuVyWKU9nttuTxM2npCBr1i66Gb+hq6pU7GaGBErhdo6J/2+18Oy1WnLIEp28edHja6pyFYv9po0Q8dfpvvMWdzEkgY4i04fAlwUCk1nXacJYAWaxaXf/J1ABSL8cRPDHd983JvZpdrjRCaiJt2V4wQQf1u6yQ8HCME0IQ2iGHK53O76Fh2b1K/yMQxfeuK/2l9G8mK9GuSEMZMH9vP0F51HE719zDeW+AZjx1kcL7IZE+hXn6HibsJadykdTFqS4BmS5OYvNFNl0BJIlVJXDcteU6B1Oe3WSIYNOskWOuoTz9BLwL0qXlmnO50ZaVML38poJCzlgCKyNuAR5RSH/DJ3+eBHwamReTZSqn/TSPH2mktLCws1ghcx+GxjcNceGLsrAuAsljlcBxKZNhSnVq2KdUKfVYBngc85P//R4ErgRuBfwTenFaItQBarFmUyt7lG6zxK7rL0IDFjNz6/WGrn+4mrrU16RquWQJTZgHX6d7Wy22yZdCkQmfmj5FrdAkZvjeT5c8kR+vWMMtX/P8n+g4N2ya5mlLNulcDNPKeHhnq59xTk4zMzHOqvyfdBA0Qrd+2TKbhJUCi6zaA7s7U+7VqCTQqliAn3C/B3d0y0loCTceu6xPzez2YWc+e6ijH1ECt5p8+LHasRbPYBAR1/54N/LtS6jsiMg7cmVaIJYAWaw5XffqPASgt+DeY4AZlchEaHmTRZ4LZBRy0te4ajlfFeB8MCIrese2HcvQYjRS2zalMLqXFDhqhMxLA+n5GOTGkKzEmy3StpCZ+pv0muYanuXZQi91d+hZKDBRL5KtVMq7CUYrpQp4LR8c41V9o8BJSL8xYSqjdS6oD7kxocIokhewkHXTCl/C1tx3rl9K1XGtu9NJimqJJN7gRpnOXRARj9DmRHWRYzXJp+SjflnNxw8kgMS+3bRWEVpy1LmBgAtiMVwbmh1i0+glebcBUsATQwsLCYjVBKdbNFTnv1CTrZ+eZy2eZLuRZyGapOIIrQsURypkMWdelkkl9v7ewWHI8lN3MdaX9XF4+zN1dO5d2slXij10BfBav5MvdwG7gc/7+JwH70wqxBNBizWGuWF9YNEj+MCd9xKPRer8mF3DTruGI69cwPqqc4a3Y4DJuY62w2rGZXIFNizW4P9Mmeej9I9YCg14xZp2GlpZGLuK0ruHU+xPOZaj9/NFxtk7OsHdkHd8/Z2O9FSUOKb+m1BajlOnCHbNApUC7SR+JYQ4J1q/UFrxm5cYh4fLWSoQ2j4RrVymtm+70SJCrxOHe/HauKR1gd+Uk+3IbInJ0y9/Za8hrGb+HZ/XbCfycUmrS33818G9phVgCaLFmcMWnvKzfcjnI+nXr2k2esMUC0PX7o/dmibbVPLzxLmCza7jWoU636M3TQFol/qZovk8mBNw1hHYMKWMpk+RFYHTxBn/jCWJirKBp+phyMCokM3Y1hdQ+Qr1/Z/YPz86zY2Kab+7ZTimb6VCanom1aJtJoX9NxgYunjKdYSQM1L+U+jez+jkMQ1p1nzab9auPq6nZAVKcWkZKV36i29lABKOKJUwnUMzkeTi3iYvKJ1DA/vwGrRh9vMxmcba5gEXkIqXUw36pl9/T25VSf9yMPEsALVY9rvvsawGY9+v8OSnLvURhehpHt6L1/IL9KS2DtZtp/RNFtzoab7aG13xzCZuY8d4Ac0/9xm+646e9x6aNKTMRP/3hbmg3hls2iqMyWYcbc6KlJ4ThiZXi4mNjPLh1PaVcJtreNuItvubuBpZkIoJpddR4XZKVriMlZRr/9I0WvtRJH0mXh4rvF0Hczz5uO05OkpVT7276+tISyoR3zlO5AR4WuKh0AgeXJwqLtStNvO2S194GwINveVnjyU06nPm4W0QOAP8F/JdS6q52hFkCaGFhYbEKMDIzj6MUxwd6V1oVC4uO4FR2gAdEeNLCcZyi4rHC5o7JVpx9FkBgBG9JuJ8Gvigi03jrAn8M+KpSyjUPjcISQItVj4WKZw1R/pq1erkX3QJouinoVrqaW1bpr/fhl+B6WSaLYMQyZ7QYxL+y6vOIgDhxb7gGS1YzlsFGVsFUQtqEwbKXlCWclOWtWwaVwmyp0S2smos4cT3Udi2COhScd3KSJzYM+V++YVysKazZL8gQzrDS1hTdMhjj+k1rNWwoK4TmVzcxtKd0PRsRXOoqui92u4FbvFUkZflGkNLlPJ7r535xuLR4FKeoeLh7S8dcwGcblFKzeDF+/yYiOeAWPDL4USAnIp/EI4OfU0oVk+RZAmixanHj5/8QgPkF3yKiET6jN60Wr1eP5BVAor7D6H3eJwrakBoRrJERpfVLwQDqJvIISmqXcRPEMLongaW07GI3dTMQP0MMYIT4Rch1MiGMuIfF/+gyklb06BQh1LBubp5CucKxdX2LusXJ1SENhDZaZSasTFLNwoQMjFgSFTq3bccCNrLypCR6pnGtxgq2TfgCMWlcuSncxvVC004eL6dto5r+IiYwnuvlXtnK5fNHceaO8mDf1kifWJ0aQdEBZdculFJl4DPAZ0TkJcBT8cjgu4CPishLlVIfbCTDrgRiYWFhsYIYnCty5YFRHtkyjEp8UbCwWJuYyvZyd/d21ldnuWzmCLhNeStjodTKfFYblIdvKqVeqZTaAzwFeCBpnLUAWqxazC545V50i1/qpI+UqXnxiRzxr/hJrmHdErgoJrBepbWS0dC6045lMJrJrPXVzR5pjZdpvxeT5U8/pIT2VNY4g3s4IiPBkrdUFsHuhTLX7DvOfTs2MDoYiv0zlcyJg7HNoGSSHzWtVSXBapo8Pp06SAsWPg1JZWGSXMGpLYGtupDjYLgEdOO1ES1+H63CnD2++N/pXDd3Ozu4YvYwN03v5Xi+nycKG1BBqSP7/pMaIpIBLgQ2Um/MU0qpr6SRYQmgxarDDZ97DQClcjcATkAAtbvvYgxfOrmLXMx/YNXkBO5eCfVt/IQ3uoa1yaIxgor6jjUloso2vBmmI4Ymylu/FRBgrT3GlRM/Z3NInd2btFJITaChXYVkaJOLP19s5nCdzKUlhIPzC0x35xfJX1IpnBSI6pKSCLZq2YghgkqMnubF31bCBRV76kykEW1/i4Qs7YItLcdLNjPOcMtQupiEayMaW5vQ3ipSzjPtFPjGwLnsXJhgR2mSraXTnMr18mjPRsqZJinJKrTGLQdE5Ca8uL/txP8MUlWHtwTQwsLCYgXQWyxxwfEJRgfaX8/XwmJNwXE42L2egz3r2bRwmt3zYzxlah+nMwUe6d2YUoicjVnAAd6Pt+bvTwHHaZEKp4oBFJGni8jHReSAiCgRuVVrz4rIq0XkEREpishjIvLbCTKHROQ2EblPRGZF5IiIfEhEtmn9NonIJ0XkmN9eCLV90Nfn7dqY7f7+m9Mcn8XqwNO/9Cqe/qVXMbuQZ3Yhj+O4/kfhOMpLjhTIOIqMo3DE+wT7ox/V+AP1n1BbsDM6Ll52LWlDaw8Q7a9P7stA+0T6JX1U3Ucc/xM6L6YxteLT/kdpH112AL1f0mdRRnCOA700+bqe+rmpnVy9X8z+2j7t/GjXTLLMdOcgjZzB+SLljMPDW9dF5OnfgXH+BrpEdTCcV5OO+py6vKR+SdDmNRU/X5L0ZNMxtNovQMQ814K8RtexxOwzjDeez6R5m/04/ieY1/E/gQ7+tmn8icIA3163m3v6tpJRLteePsif/MmfpNM55pa5LJ+VxznAa5RS9yiljiulToQ/aYWkTQLpAx4EXg0ciWm/FXgV8IfAJf72O0XkRQ1kbsFbw+71wBXALwAX42W0hPV6E3Av8CN4p/5lmpwi8Hsick7KY7FYpSiWcxTLOVwluEoiRC/juGQcN0Kmgv1Bv5aJIaH7koGoRYlgvcwaEm6aJh2WgxhGSKHjfaJEMIGQNSIjDT/BOUAjfgbd9WOuIQUhNH0ftf31pGU5CeHxdb30LpQplKuRdiPxM+kT830kEgATgUjbP+Gc6C8UAVrSSz8vCbqbzruZZDapY6cR0q/VsYnfp+kYW/w0S/Qi45z638hkVy/fHT6H7wztpK+vr4UTcVbha8Cl7QpJ5QJWSn0a+DSAiLw5pssLgXcppT7mb+8VkeuA1wEfMMh8CC9lOcBjIvJS4DvABcDD/v51wFeUUveJyKP+dhjfwiOobwH+T5rjsVhdeOaXXwHAfMn70WciS7y19splertxa3fBqNxaGZfa5PV9TCt/BCNU0D+QE6xaonVPKkmjE8po/3i5qZNMYgaL4x+DIagyEnPZ4gPSmNwRkafi9xtORczJMPcNHki1bf0Lknpdg92mY0+QExcz6DoOR9f1snPsNI9uHY7tl5SIExvHqOlijPE0xuAl/N5MP59mrwcxnExtt2qgkrF2XaetNNoxtx0L2MyccfsTyG8jOZGSK6b2VvRqQg9T37lcFy9/+ct4xSte0VgPxdnsAv5N4EMishv4AVAONyqlvp5GSKdiAAt4lrgw5oFdIrJTKXUwpZwB/+9kaN+bgU+JyIeBR4BnaWMU8ErgayJyW7tLo1hYWFgsF/ZtHOSpjxzl4MgAxbwNybawaAqrwx27EtgDPAn44Zg2xTIngXwGzw37RbzaM9cBgft3K5BIAEWkB3g73vp2x4P9Sql7RGQnsAE4oWLME0qpb4jIx4F3Aje3eSwWy4Qf/srLAZiprfGrW/68v472mu2aK9Zq430LiNY/sAy6ZlNSaFeM6YYYi1xgqKlZbCSueVGMMT9Xwp2a6x+eqSXLoG99DKyZ8YfSnJExDkbLn6Z0YGUxmFkipXYiYsLjDH2btOR12iI4V8ixf8MAFx0Z5+5zQ8HvBstf3LmP6BTpkWAJDJva4mCy0CZZV03zJljRYku2aNZC0+lNhHaokUvP7BxoSn47xCTJMJvaPd2u5a9VS18z/QxjL7r1NoNQCx/vx/OWvpk2kkA6RQB/H/gbvFg9BRwF/h4vJjCx2qOIdAH/6evzG3q7UqqKd5CN8AfAAyLyk8D3m1HeYmVQdT0qVna9lxWd8Jke/BkDsYsSugDxcnQXsVvnE9QkJLiGaw8Ww1Mtbd2+GtETVUf6klcx0fRNQwyNTK6eCHbcz2UifhGyY3B/6mQ72B1HCCNkMNQnrt9yE0LgiS0DPOOBo6yfnmNsoDvSHjfPYkNInqZTVJcEImiaxEQATYi4KBsTwTSuYOPpMxE60xSNdA4PCDb1n4CJ4CURv7TyG6BZ16yR0CURw1blakhLDBvOnYh230bXLM4BfkIp9Xg7QjpCAJVS48AvikgeryjhUeAlfvO+RmN9y99/A5uAH1JKTbSow6Mi8n7gbcBzUvRnenq6laksgNnZ2bZlDLvewy6rCnX7nRoBaXxXjBBAwx0nYjMOrDARAhm9fyvDXdPUzxWp206C6QjXS07bk/Bw1uWa7r51ExoeuLW/q4QAmsZriD3miAivz3onl9Avab/hWjN0b3gpZ+DEuVu4cfQ0dw0OoJyQ7BhOW4cYAmicUvteRf++HW1b0yEt1mdy2nwJ89bmq2dz4obaa+9FWh9NRuSSaXF/BM2ON7Ub5EXOSQOsKxge2+0StQ4TwKaum5i+j6QZ1+Fb01JBRH4I+AKwz1+pAxH5NeD5wGVAHrgf+FOl1GdSiPw6XtLsyhPAAEqpEnAYQER+Gfi6Uuqkqb+I9AGfAvrxyN9Ymyq8Ee+Evjipo4jQ39/f5nRnN1o9f8/5+u8DcKLsj3fmgcUHvpPyV+3qblbDQ1knhgEh1PsrJREr4uJ9OX6uxWebxO5flJPyLhnaHKVkGBPVI9qQor+BHEUfzEuEmo85+BM/ocmVvyjHJL4RIVSccEuYn4rxu5smhCnP4Yleh95KiZ5jp9i7eXDxnCRZ/hrJN1z3yYTM9LKRcDChcScqoZj0YJhrmC8Q78Zff6Ko+ZFE1zGJCLZJENMStWbnM46PaYtA4GSxHNmdSMySLH/LYelL09ZIZqRjyn4rCBHZBHwIjwDuCTX9EJ7x61XANPDrwP+IyNOUUt9OEPsh4N1+Esi9RJNAvpVGt1QE0CdqgeJ5YLOIXAHMKKUeF5FrgV14rteNwCvwSrvcFJJxHfBh4AVKqTtFpB/4HDCMlw2cE5HNfvcppdR8Gt3CUEqdFJG34mUfW6xSTJe6gCjhaza2zIn4T71tncTFu3oh7u7RTF9vt2Ylq01tckal2RvjRQued/ohp3YBx/SvydSEx61K0lFoxM8Y76YabifFANZlUadOF20ss10XsREiPHjOME956BhHR3op5rRbc5PW0Hrlgq76y4lPrE0u4bRzxZ0DiRFjykqOjI+xTGvcMHE1kbTQ5Zqsn2n3azAa0bXxdf2aPKSmXb2Gfqmzhw3tRqTod6Ym8/ol7T4KvBcvWbZGAJVSz9e6/4GI/AQeH0oigB/1//55TJsiZRJI2jqA1wB3+58dwG/5//87v70LeAOeCfOz/vZTlFL3hmT04K1bF5S9vxq40d/3EHAs9PmllHrF4TbgVBvjLSwsLJYdc4UcBzf0c8nB8fSmQwuLsxUKmq5C36lPerzO1/TtSR19sthLfRUUE3Y3+JybVrm0dQC/SgMer5T6JglFCXUZSTJT6vXCmH1FYGc7ci2WBj/+9d8DYKHs1/sLLIAJlp4AaZM+dMtgzbPkj3cMlsJGFsGkvrqFSbfMiaZDozkbtTWdTBKRGD1nkfWKI5bADpMRg+Uv8r0nWJyaSQKJuJF1E6uK/EdTNl6H1rMO4vH41gGe8tBxzh09zb4tA+aOae6c+tcXJFeltgT6rQlzRZolmCvhC9Rd1AZrmZIYa6E2uf51tPr1xGYgp9AxghZ/OkrSedrrTl1ay52hn6m9WZeyCU3xpWatnyv3njQiIuGSc7crpW4PdxCRZ+LlQlyplHIl2R3wB8AQ8JGkjkqpA82pGw9beMpiyfET3/hdACYXPONvxglcvvW/Xp0I6tDTyZMLPfv9/LuEq/3+mskCTnINi/ZkSJu1ayKGgor0XZwtTm7rxLD24NfiypR+wjvkpjESP/0Q9AdSwlM9lhBKfJ+g0HZzpWTCShv6t3mO3KzDXRds5CkPHGeukOXEup5kuU3PaSCCNZLcrLSYa0/CkvUv0v9jIltxrmBtV8uuYH28iTlq/SN6JMhvGNtRp0C0f2rClETo9H4JxLDlGMJOoJOylgenlFLXmBpFZASPyL0oXNauQf8X4q2K9nNKqcOGPlcope5Jo5xfWWWXUqphLk1aF7CFhYWFxTKg2JXlexds4JID41z12Cg9MQH/FhYW+G7gFfgk41K8GsifEJGKiFTwCN55/vb/F3QUkRcD7wN+0V91zYRPiMh/isiPasvl1iAi20XkNXjZwU9LUtJaAC2WHCW/zl+QjdvqUm9RK1zafr7rN4VrOFVx6NAc1Vqwv27WSO+ChRjLoIpawBrp04xlMMkqWLMIOvVu01aX5ItRql5ebVvvV39OW7EImpM/NB1qMjtkEWwTU/1dfO2Krew6Ns1THjzOiXU9HB7pZWKgy3RhxOgWqGjwkwbW0GC/IYPdCN2MFoyXBFembvJL4QpOcs2mdgWnPLhmKyAl9e9oRaWahTW0TeQ0dtzyt6SJGq1a0Fdv9sh38cq7hPE7wHOBHwMOAYjI7wFvBX42RfmXi/DcxB8BCiJyN3AEbxW2YTzSuQv4KvA8pdQdSUpaAmixZPi5b/0OADMlr9yLTvx0l2+QDWyK7dMJn7kgdD1McXxxruFms4DFFCfXZCkNnRhKUAg60r25h3/c3iR3sR4TuFic2jB1kzASP2Oma/y5TUMII+RW1TWGGjTd9P6pCWGM7AbdGsF1hL3bBji8sZfto7Ncun+cjOtyaGM/e7f019cLbIjawaXqF7k+Gks174n6dmO7p3IFJxG+Dr2bNB2712z/JDktjGmV+CXqkET82rjG9ffliIy0Hv1Ofe8dhlJqFi8ptgYRGQVKSqn7/e1XAn+Gt2ra3aEqKCW/tnKczNeLyJvxah0/A4/wrQNOAn8FfEYp9XBaPS0BtFgynPbLvUSIXyQOrn47ExAQ/e5guCkkxQa6xv1Ry2CzCSNBu24JNNauS0kMgxjAOGIYmr5uRDwSH9MhCfUWoAgRTHm3TbQYGohfknzTKisNCaH2gF4kn/75baKUTL0O9d0Tz01Et/RP/FI+w97tA+zd1s/AbJnzD0/x1Ptn+cF56zndl08txxjcFyGGBiIX2S31YsPfpyxeux2xBCYRPi2YL9ESqO9vkvClHmciiO0Sx7jLp0nilzo5pNGcLaCuWlASETyz8VI8DvZhbf/XgJtNg5RSC3j1A/+7XQVsDKCFhYXFWoAIp3vzfO+CEfZuGeDah0YZniqutFYWFisDtYKfVtRV6tZgFRB/e5dSSmI+N7c2Q/OwFkCLjiNw/ZarXgbjYqFnzeXbbNZvoiXBMC5x/6KAtBnDUYtfOgtcWstgLcynCZdxzHTEv7Y3dhebLIENRYYGGNfwreka/Kf+ujCdQqXLre1Ptgga4wRrujTn8k1dqiYBETlNWqCObuwlX62y7eQs44OFeJmGsbUpIwXAa8o1Hl+bpt5lXHeuhfAFpA3UzGhBa0NXsG5608aGuy4Flso13KhfwrWV5NJddsufbm1v4rswWgKTJly9MYBrApYAWnQMv/S/3vLPQbmX2kofTRI/IwJ3rPajjxBDAyFM4xpOShipTSH1Dz3TMZniGZOJYRADmM5lvCg1DTFsrJOJCC7KbDQ6uZ+J+JnImCnWL5EQKulMKZlQ/44lwujQQg+SuytODHez5/BpHsCtLUUYlpVGBkSvmcQ6MAaXcTS2tF6+iQfqcuJcwXq5lrSu4HZdrM0Sy5aTQZrgMbU6gGkJnDb3crl8G54LwzUQ9H34DS9D3vDy9hSwSIR1AVtYWFisQRQLWYpdGYZOL6y0KhYWK4M15AJejbAWQIuOISj3EiBryPrVrWW6Ra9ZmFzFNWteLZFD6xczPjFjWJOZpHraYtWLCKwp8YWgF7u1bhlMdhfHWwKT5kjdz2T5011I7VoE6zbqx4r4Xsoki6Ax7mBpkJhxHdK3u1ihsFClWMjW9U+drKMn96j6/eaBtRMeq5z4TUrbHzUJxftxYy1HRhNg/diIqhLfzfB1N+1CTlueRp8okt8WGpd4O9Stf7oFz+TyjZMT195hr2rssSZYKz/5yU+mFN6yWhZYAmjRATz/O78BwEzZK/diJH6GX6s507Y11Fy7LbiG02YMBy7hwBW86MJNp2MSMQzu8c3KbYYYmtzFNT5Q+1vvnk4bi2ciIkbiV+sQUbThvI0IoTFOUNMl2mDYv9RI4l61/ygueWKS/dv6KHZn4l8WTORIP/8a8Wv44hHqZySCfhawHkKQmiylIXeGvq0SudQwMcc2xzUkfXG/j9C+VmP9EudpF4bvr9EydvlKmavGj/DZzz6Rbo6zlACKyIPA7cA/KqXGWpVjXcAWFhYWawTd8xV2HZ7m+ntP0lWqsm9b/0qrZGHREeyYmeCpJ/eDwJ/+6Z+utDqrHf8JvBw4LCL/7K873DSsBdCibZwue1mIEcsf8S5fI7Ru7VoGW3ENp84YVvU6orf7aNUy6Kh62e3KjTUxJLiLJcEUI0ZTjjaNbiCKFII26NFijb7F9ZUbWSuT9W4EYzZ3GxClWD+xQM98hWzFJVtR5Cou2YpLrqLoWqiSq7iMjhTYe84AY0Nd4EjyYUTOf/324rdc/72Yji2SPKJbAmsWqnifbrSuZLw/NFxHcPFrq5dpTqqolx2ZyWB9jFgQW7QsJq780cxlE2PZa2RFS2v5SywM3SqadCln3QpXjR2hr1Liib5h9g+sZ2hoKHkeRQp/+ZkJpdTrROQNeAWhfwP4nIgcBP4W+KBS6kQaOZYAWrSMwPVbcevLvZhi/VpGUlxNSqRxDafNGA6eeUnlYhbHN0fgBFVHXjoltw4J7mIzEdS6J3wfptIpNZezrpZhXFpCGOca1uMEayutpISxMkpEx9Qia+iZq7Dt2BxbTsxRLGQ43ZejknUo5R3mejJUsg5lf3umNwsi9dnitf8mfREGNzj15zUSU6m78LTrIkoE/Y/GCxfd1yz2C+9oFLCX1l2sz2FAoju6SZjkGcMeWyCGSbF6S0X8OrqMnSazp7zAdacOURGHOzadQzHXRGHzDuu01qCUcoFPAZ8SkU3Ai4FbgT8RkU8C705aDs4SQIum8Wvf/TX6yn1MVruBKOFLW/al1eSP2pJxJkKQgIb1BcXQx/9b1chFUrkYfXxUl3gCh6uMlrF25DZFDI1EsEkYLICibdeIm66O1q+230AYwv1McYISsy9W9SafMIvWx8bCMxWXTSeLbD02R898hWObuvn+FeuZ7c3Fzh89N1G9Eg2BRouv1i+wmhlIixiui0jySAIbiqwUEiF1i/30OnFJhCpiMdQtge0Sh1YJZ+N3qdgxkTl9gp2YvBFci01a5EzzN0pcSTNen39kfponjx9nKl/grg3bwHE6b408CyAi5+NZAV8IzAD/CGwDviwib1NKvd401hJACwsLi2WCuIqLHp1i08l5Joa6OLCjl1PrC02s62thsfbRvzDP5ePHOdIzwMPDm1onfmepBVBEuoBfwCN+TwPuwIsJ/A9/qThE5NnAvwKWAFp0DiU3S1llcaQMNLD8Jf06W3Xlauv0tusiDqx9SsmizhLfp1bcura/vqNuEayNb9IyKFJvoep0lnEqmQaLTbPQLU+65c/Ur2mLYMTXZbZ6GcvsdIiHmVb6yCiXrcfnuOPGjSwUFssmJVlXo+fKF6vSf59mi6d+HrX+mqV10dOru4DDElRkwkRXcCN3rsE6GIkF1IYmuVqTPMiJsYDRSy5ejwR1dL3qxsRY8JoqBJ1wTacqO1M3oLV5AjjK5eqxI4x19fDQ+k11Y8/SkL5WcBzvsfQR4HeUUg/G9Pk2MN5IiCWAFqnxku89H4C5ygC5So5szitAqxO9lUr6iMhtwzWsxwmaEkciRCtwIUdWK2mSGIqKPY/Rc9PcK3AcMUyU2WYQUOQ5EYrDi0NSuZkkQmiMFYzTbbmCiILrIi8UuzNkqy4Lkknht01qjhMQPyipLE84rjAMo4tY10FzUUZ8yCY/rsk/GmZbxnhVbbtdV7B2CtKoFqdHAu+M6NcQcUQr9ENum/ClJYCm+2qTLuWrjx+mKsLdG7agguNo8ZZ/FscAvgz4F6WUcTFwpdQksLuREFsGxsLCwmIZMd2Xo2+mstJqWFgsO86dOkV/eYG7Nu7wYv4sWsXTgZy+U0R6ReQDaYVYC6BFakyVvaSPrLhkxCUresFn1/9b/1pmTvYw3ABadOl20jUcdguHZeqWPz1ZBK1dnzutZVAkPgkkrdxmLINmmf7f2snokAu4ZgGs75e0xm+SRdDkGq6b2//roJJDFJYACpjuz9I/XebE5u5E60qShTLOLW90J6e0Jqa1CJqSRYJr15ykQ904Y0ZuaJzRaGgqC6MfXFpXsMkt3ew4A5r6CRn6JpWBSZyzRQteI33SYHBhnnNPT/DQug3MduXrZbZqyjt7fca/CvwhMK3t7wZeALwojRBLAC1S4SXfez6u6gUg61TJOm6E8DW/0kc6+tRu1m8NLbiG9dIxtZU6tFhA0zgdaQmcqHiCkjqWsJPE0P+PviJIs9CJX+26aHaJN40QmlzDcWNDUhLj7jqJ8DmbGsxxyYOnOXRODwt5/xZsIH6JZzrm+Eyxms2SyYjbVPs+dIIXOZ81EqUxP50JmvytYflJxKxFV3DCZkScyWXcxrtmBEnZszUXe9rxCdstc6gmxjmuy1Unj3Cq0MPhwaHaiYyUpGnmJ6ma7H9mIfyr8HZ4y1LdBJxMK8TaYC0sLCyWEZPDXRzd1s1V3x8nV6qutDoWFkuOa08cpioOd2/YstKqrGmIiCsiVTzyd1xEqsEHqOCtEPLPaeVZC6BFQ/z+3b8MwFS5n6yz+LASUTUXcOeTPhLsZ+2+brcwftH1q2L362jXMpgRRcZR7SeT6DukeatgNOO5xWQQzfJXk28IGUiyCJpcw4vzNXIF11sAk2oCtlLg2RunW9U87N/dh7iKq+4e5+6rhinlMr4e9Za/xESZuEZj5nMCDFnVJksgNV21/X7XWpZws67gOGufoXZgu67gZlfsiNw6mkwCSUQT97JES6Fhu9Xs3cR5DXjSqeP0lRe4Y9tOyApKVFQn/yYjphukUZkm+699PB/v7H0YeCkwFWorAfuUUnelFWYJoEVDzFe9WI1wvJ8jiixuHSFMh3Zj/gy5twmu3UhsoGn+Bje2mgxDxrNOYtslhl4ZGLUkWcatuotNpW/SIjhXSaQmLSHU9UtT2LnW1/+kfnkxnqN46F9HnLt6/7l9OAqu/P44d189TCXnGDOkdbLUiNy27KLXxxsLgdczuZomIZeuEBcDmOAKjvwO9f4xfRLuHZHuBldwsx7miPxO+oAD2QYZylkkTI3mTL1ySFqk7R86GRedGmXr7DTf27SFuXDcX/CV6y7gJnU627KAlVIfBRCRQ8C3lFLlduRZF7CFhYXFSkCEvef1MTGc54q7J8hUmjV/WFisXuwZP8WO6dPcu3ET4z29SzOJWqHPCkMp9bV2yR9YC6CFAa++9xcAWHAHgKAunfeAyogi67hkDMkfZgtRi0kfAWqbhoXaOuka1sbqWcA69LqB7VoGxa8DmLa/6ZzHWQbTuotNLt9W3xpN1q2kLF+TRTATWdQ5vQ4Zpcg07W+ids3rOuq66fMZ3dUCT1zQx/mPTHPF3ePcd80Q1axjtkymuqYNv5+UCJJ9XDfwyzW2BEYMe5quqV3BBjdv3TFHdKkTZU7yIH53kiUwQJKTwJAw3TwafWUS//+0ruDk5JD2lA/L3z0xzu6pSe7bsJET/f1189UVsa791a4RiwhEpARsU0qdFJEyDa42pVSqRZUtAbSowyvv/SUAxkp9AHWkL0z0HBRZiXcB11yFmp+i1Zi/iPs1co9YAtewNjbJVdhpYhiU0kjrMs4YbqBxxDCtu7hTsX8B9CzgZsu+BNBJWJo5o0i31rIJpkzkxXmDfvF66GRp3yW97Hlwhsu+P8kD1wziZhufA5Oc8JxObTut29rrVyt67nhXWRIRjPPgSkz/GLYWvx2XJWyqFaMdW8TFK2mJXTwRpG5v+++YETQQYHQBi0aiksYZCaL2u2v1YLRxOyYnOX9inAdHRjg2OBCVX0cAVV1bM2Ec3sBmlV3T+E3gdOj/bR+9JYAWdagG1hXNuudoMYAZp5oifspAi/QAFuOPPoHYRcZ33jKok0S9dEnieMP+JGIYrATSbixhHDFMay0MCGGnk0BM22ni21qZJ7ZPyn46jKVQfER+EwlzhK2iey/tYc99s1zy/SkevnYANyPG31iac6TX8TNds/r7gP591+YyxQZGSFmgZP3uyFJ1Ui9PTyap43wJZEdXoQb9GovfbbYg6mLrVY7+EvRrPJ6nmpGinzEG0CQjieh1iPgBbDl9movHTvHo8DCH1g3V9wuRvtQJLI2mV20bLdcUlFIfCv3/g52QaWMALSwsLFYDRHj8sl5KXQ4X3jWNVM+ip5vFmsfG6WkuGx1l77oh9q0fXml1zmiIyGYR2RzavlxE3iEiL2xGjrUAWgDwRz/4WQBmK168hu7edUSR0VzAmSRLUKJlL5Dl7zVaBg2WvQBGV29rruG6mWomn4R+HbYMBitVLEWWcVp3cfD9qpqrz2uvuq29N5qsWeYs3/bkNhxD/FrLJug6mrJ8k5DkCnYc2HtFL+ffM8NF3z/NE9f0ojJi7N94snqLm2iDdZevMdbT/09kRRjRfxth+apm0YvEdzXj+g3m0wMCa5tNxgSaptb216ySuukv0g+tnyYv4ftqeS3g8D5TVn1qV3AKHRrJBYZnZ7nixAkODg7w2IaRerkNLJCqPrqAvb//8vaVOTvwz8BHgL8XkfXAV4DjwG+JyAal1DvSCLEE0AKAmWoXQKS0S0ACdBdw1omWgYmQH5OfIiUxXLw7xPcLCGPy0m/pXcOR8iqJsjuLRU3rY9Q6nWQS1zeJGNbIsB8b1mzAdtokj1blNYKeqCQpYwAjSwFqRLBVd7V+zIsryyjIwP6rejj3rjn2fH+Wvdf2gCOx/RvpvNjZ/xNcyv7fwMWvf+9urV/Q0b96DERQj7sLaiwukqR64reYFKK1a5tBs5Lwz00nifX7E+sEJhFBnXvWdje+ARgrKDV7n0hzTYpCNUqASkn8OuGWdlyXy46fYPPMLEcG+nlo88ZULufFeMD6761pnL1G8suAb/v//1lgr1LqGhH5GeCtgCWAFhYWFmsRyhH2XtPDnu/Osvt7c+y7OkoCLSxWAtlKhe2np9k0M8tgsUjVcbh762ZG+/uWXZezKQZQQy+LCSE/BHzS//9dwI60QiwBPMtx6/0/BYCrvB+vbvELWyrC2ZcOKjEb0/HdyK1bBt34/kvpGtb6GjOFTYeuu/SadA0vjqufcynKz6RNJNGTAgJLoKmcjAm18j56ckGT49OikbvUUfXXr+7S1XVcKmtlcEz6KikiChzYd103535njt13z3HwmkKMtUzFWPzq56qVzfH3By78jGaJMyX9BNnAJktgJGlEBWpq1jrdXetfvCq44ExJIaIiLt7FxbkNlkBHswQGzbprN7BiqrrhUddwxLesu4g1LIXrN7w/ri2tpa9JV7DjumyfOs2m6VkGFopkXUXVEaa78jy8cT0HhwbAcWplfJLkehnMtVgXD25rv6uzGPuAp4vIx4FnAe/1928AptMKsQTwLEVA/CbKPUCU8OnkzonE7bmRfUja2LBms4OX0TWskcZsUAojLYHrEDEMsoCTkJYYxt3c09cYrN8fcQk3ibREbiljAvXzGxzTYgkVTUaHTA2RmL8w4SOqu+QUB24ssOtbRXZ8v8jRa/JRIQmxlRHXvubCD45dj/mslWFKSQRrXj3HX2bPXSRw3n4JFPPnqXcNN14pRCOPtWOPPXRz/1Zdw6ZZOm2UTUsMJcXcqYlf9PrJVSpcduwkQ/NFcq5LVYSZrjx7h4c4vG6AUrYBdYgjfOF5wgTW0b6QZnH28sZ3Ax8EZvDI4B3+/qcD96cVYgmghYVFe3AVvZNVCrMuXXMuXXNVnAqUu4VSwaFUcCj2OcwNZlpndWcxVEbYf2OB3d+aZ+v3Sxy9KoYEWlh0CLvHJjj/5DgL2SwHhwY4PNRPMZ9fffkW6ux1ASul/k5Evg/sBL6gagG77AVuTSvHEsCzFFXNSrZY90+z9AXtof1VnHgLlTLYlDTLYM0VFbmjNGfpWxrXsJPQx5fYrGu3Scug4zaXpaojkuCBZgWKmds01tH2B9tdp13WHyoxfLhEpUuY78+w0OswPZLFzQq5eZd8UdFzukzvo1WUAyfP6WJse45qPmotXo5kkMUx8e7TTvOqpDp+SRbAmiUyB4ee2sU531xg6z0lTlyZNSobSVwhsPQFMondprY/sAjW99Dd4rVC05rrOEgCqRn4/L+Lblip9fP/47fHH49I+OcT70Y2xyO0aQmMuH413Zq89FoiUTERNO3UAWyky01PHKS3VOaxkXXs3ZBQyiXJ0qf3C/d3VHTfGQwR+SHgC8A+pdSe0P7rgD8HrgLGgX8AXq+Uil9lIQSl1PeB72v7/qcZvSwBPMvwZw/+GADzrlfuJefH6ekPnuDmH/cAc6iSFbeOFAIE1SqqEcKVjhhG0STR64hrOOib8fqagoIM6BQxFI1gtxpLqKOuHEwcKYRoHGSgg/83f7rK9nuLdM26jO/I8+hT+ij2ZxoTOKXoG6sysr/E1ofnmdqcY2x3jtnh5q2C7RBjHaK9AC0VjFm/4ezfmPa68Xk48rQc279eYvMPFKeuqD93tWtDPxa3/ncRIX7atRWNFdRG6K5fzWUrPveLru5Q7+JdJITBn/qYxHBMYC0esHZQGrHTy8REkI4ImmIE9exgtOa20YycsAsVmiJ4DeG69JXK/O+ubUz1FCLNPQsldkyeRgFVx6EqQjGX5dhAr1e/SI87MbmggwuEuGukSawBC6CIbAI+hEcAw+Rvu7/vP/FW9jgf+IDf/Ecp5O4GbgY2ob3HKaXekkY3SwDPMsxUvB92UOdPJ3GLFsHG66Q64pofxDrhMxE9Q7+qZsFYVstgYM1oMenDhGYJXFAHMGm+ThDDJGthMEe1Kmx8pMT6vRWOX5zn5K5FV6R+HcXpPb/R4dDGApmFPOsOVth5dxEExnblmNiZo5o3WYA6d5cPL+HWSSKpw5j0oRG+WKLXaLtLcfwZWbZ+tcLIfYrxJ6cg0H7sntSukfria0mxgiYiGHTLaP08whay59VMjj6J05I8EpNDHKnFDRqJYC3pQ3u5C5SsbWskM7geatv1wyLlX2pEsMnfWyevtaQyMMZx8bsXLwuP1A0Ui0z2es+JvvkF9pyaYGRmnpzrUso4KBFEKURB1nW5cDTDt87bRimTjZ8nHPsXzBexEp6ZMYAi4gAfxUvSKBAigMBv4yVs/IZSygUeEJFtwNtE5M1KqbkGcn8Fz1pYAk5SfyYUYAmghYVFZ+CUFLu+UaTcLTz6Qz2Uu52WzR/VLodT5+c5tSdH71iV9fvKbH54gdObs4ztyjG73sYKNoKbF44+I8vWr1RAqoxfZs+XRWdQzGW5YHSC809OkKt6Tv/5XJZD6/p5YsMgFS35I1up8NS9R3n6o4f54qW7ll3fNRAD+Do8QvZ24PVa203A533yF+CzwF/huYS/2UDuG4HbgNcqpSqtKmcJ4FmCdz70o/7/eoFF12+AwOKXNkPTKwOTLo/UwVAORrcMBr+DZXYNhzVdLPuSYC2syTao2Obz2JgF3GQsYScsg1JR7PxWifn1Dicuz+GKZw0STXbYupYKAnMbMsxtyJBZUKw7WGb7PUUAxnflmDonS7Urvf56mZn4OX0LN27NcrWUMLl2TZY+k1Uy0r+gGH2mw4ZvuGz/fJnJSzLMbHNIVyuwPgs4KVZQae2BVSzjd6gG5WBC8YyCisQaah7kRReyITu4zhIY9FH1LlpVi/0zuHgT83lN4+pHR7AamUeShS/SP3oMT2wYYvPUDNOFPOO9BcZ7unEzhvunQCWf5RsXbOdH7t/PrlOT7N8wFLH4RfQQVbvFL7r7V+H5bIwREbkrtH27Uur2cAcReSbwEuBKpZSrr8QDbGExezfA8VBbI2wG/qYd8geWAJ7xCIjfVMUr95LTVu8IHlA6mYsSoPql2jKiaiSyGiFiKQuMmFzFy+waroZInxNZXd7X3FTTsE1iaCJqgpkMtDNfK9j2nRLlfmH0iiwii+VfIjUHU+ob+5JRgMkLskyen6FnzGVoX4VNnysxsznDxO4scyNOxMpldLOmUMPoYm8RSaTXRPCM+4nvV4duOHGLQ/cxxdADVYbvrzJ9rsPsNodKf/SL1681/W9tGUK/X8W/tjN6+RcfwZ0keLAtxlN694eAGNZeFDRi4OixhA2IYKRWYLCplRFRRhdvi65hErCEvzsj/BjA5DIwCTF5MTgy3M+R4f7G/bX9blY4PNzH+ccn2L9pMKbuYP33LsLixVaNv9+uAZxSSl1jahSREbyl2l6klDpu6hcDLRjBiK8AV+Bl/bYMSwAtLCyMyM24FMZdnnhu1/K4GUWYG8kwN5LBKSmGDlTYcncJFEzszjZtFTzjIcL8VmF+i9A1qug9qNjypQpuHk5f4DB9bpQ4W1h0Gg9uX8/2iRl2nZhk3+ah5Zt49RoOLwW2Ap8IWf4cQESkArwAOIZnyQsjsPwlkcYPA28XkR3APUA53KiU+lYaJVMRQBF5OvAKPMa5E3ijUupWrc9vAy8FdgNTwOeBVyulTjSQew7eunXPBAaA/wX+n1LqvlCfTcDfA1f7Mn9LKVX02z4I/CrwDqXUq0NjtgOHgGcqpb6a5hjPVARWO6PLV7PWZRr9okJ9RdxYKyFgrlGQ5FY1uYCX0TXsmjKEI7I8LJVl0Ftr2W0761efzxHV2EWqoe+4y+xWByfDonlETx5Yoruw6oKJC7JMnJ+he8xlaF+VDZ+bZ3azw+S5GeY31JMbtykXdLq1gE1Iss4mJnMYsn+TxsXN4/qL5ZY3C5ObhXEXuk7B0L1V+ve6nLo6Q2m9+bdjsgwuutQ9RMq/1IxvgenQ76e8cxs8+IIC0m6tgLTfP3Adp7AE1tzBkdNR7wJOzBbW9htNT2KYLyFjvmm0cA0qx5AEktJiZ9Ylbb+oZdHNOBwa7uP845Ps2zIYK6/2U3VUvTWQDmZTrx58F2+93jB+B3gu8GN4/ORS4AUi4oTiAJ8NzAF3J8j/F//vbTFtCsikUTKtBbAPeBD4J+BdeqOI/Dzwl3hZLV8EtgHvwzOBPitOoIj04KVA7wWeAxSBVwJfEZFLlFKjftc3AfcCr8EjoS8D/iwkqgj8noi8Vyl1IOXxnPH4q4d/CICy8ly/OuHTH9pGMhdG2AWMWpRhcB+7OhFLdBU3dgEvtWvYRULnoV3XbnvEUAIX5RLE9sWRQoiPnVMFRXZB1cUkGpfH89H8snfJD8HyRuHkxixjCxn6D1TZdHcFcWHqXIfpXRmqBWnKZZ5VqrbKSztomghS7/JNHfPXzPfuCOWNcPIWh559ik3fqDK/zWXiCgeVk0UXbKJMvfxLfbavRDLAQ1nAoiLZwUlEUK8XGCaCiwSuntDVetcG18cItu0a1qZZFbFqEvok9Yvd3+IxmGL6fDy4c5gd4zM8ef9J7jt3Q3S+WgygYV+zUKvj64iDUmoWbUUOERkFSkqp+/3t9+EZzf5ORN6FlyH8JuA9/vhG2N0JPVMRQKXUp4FPA4jIm2O63AT8QCn1d/72fv/g3t5A7FPw6t48PfCRi8iLgZ/GY8q3+v3WAV9RSt0nIo/622F8C4+gvgX4P2mOx8LCIh3mNjmM3FXFKSlcQ5mW5YTbJUxdkGXqfEVhTDG4t8rwZ0rMbXaY3uEwt9lBZVdez1UBEebOFWa3wfD3XTZ/scrJp2YoDdjzY9F5uI7DXedt4NrHTzLfleXxbfqjegmwSglgGiilDonIj+BZ8b4HTADvB/44xdiOGLs6FQP4TeDFInIz8DVgI/CLwKcajAkqTRaDHUqpqoiU8NazC/Bm4FMi8mHgEaIWRYVnOfyaiNymlLoLC6Zd7/TqFr+mXL46wi5g1KKs1C5fDUaL4Aq5hpVjdhfXsDyWwZrFLbXcJbIMFmD2HIeReyucui5bN5eOJMugCa3W46tshLGNGcYWMvQddBl6osrmOyvMbxRmtznMbXWoFuLPR9q1ltPqmpRQolv80rp6TS7iZtz4bpcwcYPQ+wRs/lKV8WsUcztC11uCqNoqUzV3XeDy1SyCtexgVZcEktYSqLuW61zCEUud/yfIAo6sI0xdx9SuYT0ExJAU1jLx0C2K+v60MhquBGJQLul7bsMFDN6pP7Wul/vOqXLZgXFyVZeHdg1Hx0l0bMuu9DVEAP2wuVu1fd8GbmxFnog8G/i/eJbDH/EJ5W8Ce5VSX0ojoyMEUCn1HyIyhGclzPlyPwO8sMGwbwOTwLtE5GXAAvAqvKDIqZDse0RkJ7ABOBFa8y48/zdE5OPAO/EqY5+1eP8jzwAgg+f6TevyNRXyDa/qUSvfoBwyKFyDC7iG1NnBWv8OuYajSHINu7V95gft0hBDXa5HUNy25XaCGJ6+AjZ/WtF/uMr8DrOcZkhJWLd24XYJc+cLc+d7iSOFo4reIy4j91QpDcL8doe5bVKXGZsRl2yasAcD0rpu9f0tZfvGIdwt4bQHMufPFyrDMPxNl/yk4vRlQt06awY5QVzs4qprGmHTdJaaC9jbbpYI6rGBSqlaBvKiqvVxhzVCmBQjWNv0CWEQZ6jtNxJCXWyraGd82IXaQGbLhC5BboRja+MPb+6nnHe48rFT9BbL3HXhiPdlBkTRWXyxVbUM8pS6WgAgIr+EVwj6w8AteLwLvNi/VwHLRwBF5Kl4vutXAV/HiwF8O97yJ78UN0YpdUpEfhb4Gzwi6OIVQfw0mn/bXxcvKSvmD/Aqaf8k2vp4hvmZnp5O6rbmkFnw3rjyvgWw9laeQAD1NYAX90cJiKscsuWBUJ/4X6++tmdV21YaQQxi+XQiEcQS6iSmVrcsst9J10+bz1US0UnXpWq4V+rjTONN+/Xl2Hr9sj0m4mbab1pPNdzfPNYAByo3wfbvukz0OFSG4rstRexfGtTNmwF2QGUHTFcVXWOw7oRiy/8q3BwUNwrFzUKhL7rUVTMwrvGb0D+yJFyLBDB8zPp33vCaGYTiLbDhOy6D9wvTF0uo/l8QL1f/e6nUau352/61Xuvn1vcfVF117bU1v4NtzRoXVAxc3Jb6v7JIFKJnp95CV/sdmWL6qN8fOVX6yiC1/ZGJVwzrM7n4huUigEnjBRjJ82hvL1c8fopNj5/mexeMoJwgdlQtfl+1l3tvRzPPZBMPPkvwGuC3lVIfEpFw6Nu30ayMjdApF/CfAf+tlHqvv32fiEwB3xKRNyilHo4bpJT6CnChiKwDHKXUmIjcCTzRrAJKqUdF5P3A2/CSShpCROjv7292mlWLv3v0aQBM5vykD7wYUvGJXpADHFj6FldZUnXbOuIeJlUcHHGpdk34feLJj0749H7VGvHSiWA8CYvsrz1Q4vfrRLBqIoC+3CoSQxLTETtdduJ4U//AJSWKmexMg4d5a3Ib9W1I4EZg7skug1+D4tVQ3EXttb1V62Knl2KLHE9WvEIMWwGlyI9B92FF93cUPVmX6W1zTF8gqBSxjc1a/PT25GxfwwuYwYIb/v5NL0bG9qxw+ibF+i8rWBBOX+1ZAuNeiAAqbv0LWFV7IQuWYQsse6oK41LEDUibBO31BDPoX+tXk+fpqUL9F3lcfd8AOvGLEEG0bY0gRrN969t1mL72tD+Fti59gRNuKTpnxEoZ76qNwOQ919qN8nQLcnAyu+HwhYM8/d7jPOl7M3z1mi24joOIWvxutZeLpp/JZy8BvAD4asz+08BQWiGdIoA9RDlErU5o0mCl1ASAiFyIV+7lN1rU443A84EXtzh+zaKkvK8yl7DGb4DEtVsDxLlTlYuDW5ORqZHMJrN+jS5ffb7lcQ1XVSbmgZ7Ovd1pl3FQqHhJXdGaSP3Y9Zi+8g6Y7IHBb0H3IZi53kUVFh/gadHJAsxh6HpEiM9GmN0Is1cJ7gTkHlJs/YRi7nyYvQhcQ7xgGM3GAC5a/hr/HpPkNA4Z0K7FoHyLKX4NoAvGfljY8AVF3z6YOy/Upj3Qzb8Jp25rsRC0IuOoWkPwjF+sh6ZZQ8OuXmJcwiokJOL6rZn+6nUPNtPGCNbE6xZFFde97bIlqcabLPVC/Hq6AXSLnWmuFmMFo+0xsX1410O5K8NXrt3CM797lBt+MMr/XrXJ0ycos+Mrt/8Ff5AwqYWGUWAXcEDbf33MPiPS1gHsY3ER4zywWUSuAGaUUo8DHwde41vvAhfwbXhp0I/6Mq7D81e/QCl1p7/vhcBjeAURrwT+3B//4bQHEIZS6qSIvBVv/b2zAv/42A0AuH65l0i9P40omJZ8M7kqMzVyFA4ad+KD6COESxNmIoSG/YGVI5PQr9mkkcAymNH0z1GNWtaMN8OlJYZh8ufJ1Xp1ghgm8bCAAIQ6uuth6scVPfcIw5+CmRsV5W3pCF2qUkNtIO67061aAdQATD8V5qah50HY8AmYP1cxdzG4vSGdE4hddH9jotesvEWFte3Q4eiJRa4WxxqMDc5B7drJC5NPgeEvKRY2E6wSGZnTpJueHBIkhYhLXQzgIl+MjwEUzSIY7K+5mCFcYcZv80UHP3XNrZw6RjBSe6b+nEmE1dARRGMVY2CMP1T+R9ut65aW4CWbaBr2j9TTlPr9SoRvXbGJZ9x1nI1j85za2FULmWmnFudqLgOzDPgIXv7E8/C+oG4ReQ7wDry1hFMhKX0ywDV4hQnvBnYAv+X/Pyj78hbgT4HX4tUL/Dc8YvdcP34PPCvhhf7fAHuAfwceBt6NV2fwx0NjWsFtwKk2xltYWDRCBuauVkw/TdF3h5CZXGmFWke1H6avh7HnAgLrPwX934bMmRceHIvKOmHmImHoOyolK7GwaB7F7izTvVl2HJ3prGC1Qp+Vx614XOtRvDJ4PwA+ibdYRqPye3VIWwfwqzR4T/AJ21v8T2oZSqk/JkXNmwYyXxizr4i3WslZgWm3GzCv9BHAtOZvrb//N7Kub4DwOOXJi7iRNYubg1byxGQRXGHXcNU/es/SYdBFxxJbBqMrraRz7aaxDEYsRAZE49a0Y9uiKF4t9H89w8yPVxbz0FLK6zRc7XhcJSzWEq4/f5Es4F4oXgMLl0LhYWH4s1DeCvOXKqpDyTF6kf0txvwFVuloTKluzV78r27Zi16DwXWv7fanmLsEug9D3+OKuQuiOmV9eRVNBz07OGz58Vac8Y8pwRKou4QXr11V096t7fFjZIM2zX28mN1b389YSFq3YkbMW/Eu4HZhjreLaYix9NXdapNi/cxP7pT9gnlTWgINlskTGwvsPjjr6a+HaLaK1UHGlh1KqQreKiJvwAubc4Dv+x7Z1LBrAa9R/NPj1wOQl3zdfv3Bs+jyTRvzZ9gfeoA6UiUj1RjiZpJpImRR2d7+JJevWbf6fulcw41qIRrr9i0xMcyI7qJuM+YvxmWYBFNdv/A1Vt2jcI8LPXc6lG6q+P2X1tW7qF/j2Lfwsnf697hYZkdDNyxcCeVLFV2POAx8waG6UVF8ssJdn96Fm0TwIuMTH8a6a9nfqxzjd714rFrMnrbUGxnh9FNg+POwsEWBIQ7fXJPQ3w7EOa5X8iVI8gjUCpaGC1bl0Ahf4PpdHLdIBDVP7mKyVDQDIXyoiTGC0aSRJEJIe0giLHHXR0oXsDE2z9ju706ZLJJMAGP0DI07tKOXPftm6CqVmc/mDYMs0kBEXg+8Uym1D9gX2t8NvEop9Sdp5KR1AVtYWFhEIVC8oYoz6pB94gy6neRh4TKX6Z+rUNmk6P1ylp4vZMgclTPS6lAdhJknweD/QrAGr4VFJ+FmvftDrtS5F8QaF17mzyrAG/Bcvzp6/LZUsBbANYZ/ffxaAIquV2vL5NoNLH4mi4MRupUuQEzGaNRqoblWgyQO4i1vixY5XYfGruEqumUj5XjNNRxkLddZRxNXFfElLbFlMMgCbnW80drTBFKvVtHlUn6mS9dnuyBfQs4xWwzbge7WzmiWzMU1of3+yom1CnpjUxaCzkLlkiruRRWyTzgU7spABaoXVqnsqUB3fXf992a2GKYMbwigff/VOuue4btOsAQuzuX9mb9IKByGvkdg7pKo3o5mHQvWUq5olr7g2jUVjA6+R30N4caWQP28BjL9/9ROZ70lcNE+GJ8koruGI/UE9e+v3UvZ+DtuYAlLiAZoNUnD2J6gUlKySSAv6Ffb9k3E2aoK9WnzhK4OMrYSiP4oPJyPV1c5FSwBXGMoKi/QyuTaDR5A0TIw8Q+caGyU9zda0iVKMHXSGYkjTHIRr7RrOM4lbCTAy0sM9RjAWhhVk1nKjtZuqh+YBg3dmusV1R8ukv9mF+qxDO4NJZz+qja+tbv1IrExtdfHNC4SxdD502IB9SzrRELmgHuhS+XCMnLSwXkkS+G/CqitVdSFZdRWV3OzNxczGHNU+vR1+td/742JncmdHIkFdWD6Rlj3WWFhGzBYr6tO+MxlYrwHfI18B2pohFB340b2h/rrcYGLUwVK1Lt49WzhWoygaUURjfjViInBvd4s9LqFMT3i54uDwQzVNNFLcuGG54vbHSF+jecRvK8ro9TiXNYD3BREZB+LqSh3idS9BWfwVlL797TyLAG0sLDoDDa7VH9mHvlBjsz/dKMuX4BLymdWoImA2uhS3Viiej1knsjg3JmHyv/f3nvHyXHX9//Pz2y73ev9dOq9d8kqtuUK2NgYmw7GAUOoIQVIQkj9kgRIJ4QfAUwLJQQMGBdssI1tuclNrpJlFauXu9OdpOtly3x+f0zZ3c/u3O7e7RXpPk8/1qud+cxnPjM7t/Oad/sIzEVx5MI4RM5fs4RZDr2rrFqPZ9/EhfXdaSYcCfgSOR62Cuns/P1TGynfwZLNf49VNSU1rTqKFQ94Z76daQF4nnDXoTUAGFhTWKmuJp9r8VGtcjn+2DyTPtR26XcC6wk/h7vYwwI3eVzDmRbIfC2gLmNkGcxaZ9HqIb2ds9SZncFxr3k8tatu02yoGagFuTX9wLoh5LwoxtMl8EIImuKIZutFjenOCZsv6owu7jg9EjzU+ZytPpzzYrX1GyYBw/tc5HJbG8KEELAsgVwaxegQ+PYG4Y4wNMdhSRSmJ7yTPpRrNNMSL9OOMcONm/J9J/fhYdlzjF8e2cJq+6FFUHIcyvZA/wqyhn+k9qtaBg1htfGqE+jW+0vv1p05wF1u/8M0M62DnpZAp/acV5KIc+0p09Ml60QrlrhRWqgyLIoZDZTPeezPmWu50GSNfC18XmNVt8/X4uh+/YZlJfcnUtt4jClPJkk83rghpfwigBDiOPAzu+rJiNECcJJzx8G1AAza82sGhepWs2P9PFzBOck35g8z7SYlMDMmgc/oM28Bp+57nFzDXjFRWfftlW07NsLQKrOT5fxmuHQztxs1zr0yVxkYd7n6MCKhGri2DzkoEC0G8pQfc28EBgU0xzGaY/inRxFVpnsT8JpOT81aVl3Cqls02zlVvw2fSODPQwznctn6sG/EDUDDAHLzAPJgEPlcCJ4UyKVDGKuG3GP07i+7IPQpLsqM9mkF2rP3lXzQURZ7tTcM+rZC5b22K7g6fQyZBeDTlzsPL15lYpKxgGmjSxZ3FunLMZIFn72EoFt0OLV4NMMIQTVG0F0s0pqNtjRiTuGnPg+mXLPesXnSjafL1ke+MXpe7QuPCZRZm6lxfkLYLmDTTCkZo2MAR4KU8gfF6EcLwEmOI+QCxNOXeyR5JJM/0q1tXrixUflYvNJ+ALLUAXTbjVDAJbtO70cdU7Esg8PWG1RLjHhY8MZIGPoNE7+RyG0xVETPaPCKtctLBJF5fg0hrZy0+cD8KD4hMfsMzJN+EicDDL1cASb4mmP4psfwTY9ilGeeN/XaVGvlOcduKDNhpP5tqPNSqxZWr1JAuWIDM85NCbB8ALlsANnhI7EjAkOCwOb+YfvJrP+X61pOWvFS4xoB95pIeCR/5JUsUgb96wwqdgjOXQP4ku1z1T50zq1XmRg1OcSrTEyqEFT/DNwrQhm78+Ohlo1RczoyYwRJW5G03GU91JEz3PR8aQPx3rcQ9jBHK+zyFX7q/jPGk30c6kOPEBIpBP54Ml521EkgUxQhRC1WweergUaUn20pZTDbdipaAGo0mnHDKDUxFkXxL4oipInsNkicCpI4ESD6bCkEJL7mqCUIm6MY52k8nRAg6hP4r+lh8FeVxCsT+JcOTfSwCmJoPgSPQWQ39K+e6NFoLgSiIYOKrljR+pvC+vG7wDrgW8BJRmgL1QJwknLf4RUAJJysX8Xil5n96+UKVkqz5F04OJdb1MQn4tn7HKEFLxmn5bi3PMZUbNdwNiupp+VnfCyDBtLDjZ8etzVcEeuC8bA45Gsdy3AFe1in3XYCqErgrxqAZQNICeY5H4mTQeIHQww9UUZw8SChDX2IYEo8n1ruRZnbOSGztFXG7hdmxuw5+RyDeiw5KYHwtV0M3F2FUR4nODOatjo5V3Gm1TJt/Mq1nG4J9LJsq4MpMFvYMOnfAhX3+IgukJhlztYe50QmLT3ZYliTFkkPF7CSxe30l0CkWLO8vg/nCEcWI+jOTKHE7BVrdrxk/9k7zGZx9I7FkwhpjtrCl8uSl22/2Zenf84oH5US89tb5aPibDzFSjjaIMvRbX4ecwVwrZRyx2g60QJwkhKT1lejCr7M0itOOZh8/xLyi/lz+k1zIaeKlNRSBJ6CTN3H5HINO8udm2taIH4+U+KlUVxhaGBa37ndXr15eiaVjIaMWUmyC7zMmnrZhZ66nYNPEYJpUwXWmFATg5V9mAMGA0+V0/uzGiIXdxOYa8XSqYk66rlOFYbq2FLPoyG8RHbuY1CPZViqExhvOEffA1UEbziLryY1Ct7rb8Kz6I3dPjP2b7hEEWBkySKlEJ0vCe+DvvXWetV17OBem3YdQPWcecUE5lMmxqtEjKqnMl3D9rvyE6G6hr3KvxTbBezVXzZd6CW41BqshQq7XK7ibPvLB6/afqn9n2sIUn8qmhEnqCmYcxRQ788LneSv0WgmJUbYpPTKLkqv6mTguTJ676sm0e3LveEkJNAcI7ylh97fVGP2n18/u4NLTIKvC0Q0d1uNZjjONgQQEoKD8dyNcyEn8DXxfAn4KyHEqIx42gI4yXj4yGIADKysXy/XrtcMILnIKNbskodlUKb+UyKUMi6OdSVZ3kXpa5K4hp1WGa7N1MLL2ayCWfrKtm06o7QMOmP1skAV4QlaTTzI5QbN1+KXWYxc7cexaqvjST8XoelRgu/sYPCVUnruqKVkVR/hNb0EfOnnMqOflO9XtQ76SRAQibwteyMtYp1KeMkAsttH3/1VlN1wFuHLLIWUdFln/9vKVsJFzRT2sgS6uOcpv2xhsxzizZLwazC4xsxop5aXcZNAMrLIFdevYgkcLjs4IzPYPQIvd4PS3hmyh5dUKu9qYehCydeyNVyZGE8LIDksgDksfOq1PJyruRC89pOWoR0QJHzQeHqQE7NLR2ViFXjn0kwB3glsBE4IIV4D0gIrpZRvzKcTLQAnCQ8eXgpADCvmL2jH16k/oklBOPxN2Kt2mks+cXB2T+q+ExhIYSJUQeYl7Nx9OsvVsYyva9jw+tnIIxZwvIVh3rFmo0Fkjz/zuqYyYvls8hV8uWvsKWVfEOCHsnU9hBf20/N4JV2311G+rZPgjGiG8HP7SY0FVL5zNQbQa6zu+iI99pdd1M25E/XIkwGCcwaTYlemi2E3rlY659r6qP5dGyIlU1zJfk5mPo8+RjC6IU7ktwGICKKLrfMWN31260wXpCFkxtRxGS5hZ2+OkPTIDvYZKdEmOCJRie1UXL75uoY9BWGu+n1FYrj+vYWZmfa3WajAy9cFXOhDj9qvel04In4w4qP6bJSTcyKjf7CaHNa4ieCE/RoVWgBqNJrzBl95gqo3n2XocAndj1QTaIpSdnEXvsg4COUiIASULO5n8ECY0JxR1XAdV2Qp9L0hTumDfnwtgsENCavEj0ZTIH0VfirOFi8TeCoipby1GP1oAThJUN2bmckeztPx8Fm+yfa56gCqtdWsp3q1Xlp2y5aJScpTaC7LntvXxLqGHauKZ+ZstnNZsGVvZNur35NXlqqKZ1Z3HjjXSEy1lng9lct0y5+azOH2m8N6NtKwhVQC8/qIzOynZ2cF537aQPlFXZQu7027hAIikTIvdfr2fiNBwEh4WvbyHWPOOYQVTGlQtqCXtqebIQaBgG35tc0wznhdi7A9cDXhxbFipya6ONnPGYWyUTOH063NGXMpKzUJXetjpcHAjVH8u32U/9rP4GLJ4HITv30XiZPsJy0LWJLWv4qzH79jXbfPhbCXJ0wjIwnE+RvO3yKY4oZMOzdjk/WrMhpLomqh85FurR8rF7AXuazhnvuz/1QMU2IaVmb3aC2sOodkdGgBOME8fmSB/S/rNpcx04dn9m+eV77nbBheG+Rwt4ItalLjUIYXdhklLibKNSzTz2Vm+ZoCysFkTN3lIaC9UESsgxpHlQuD0ReAzhBoHm5nxz05UsGXOU2hhyDI8xwaQajeeo6yxb2ce7SWgb2l1F7WQagxma2gimin76ARB8PbClHU8jqp/YoEgUiCUNMgiWMBAgsG7f1ZGIqgcc+5Iu6SrmKZmf2cETeYvVC258wpqiBMdSUHIL4GEgsSBHb6qbzLR/96k9gc6YpSQ0r8/RKzxExTA57CwXDCKpztSRsfhpl0ybpTt4m0NrlcxF4zh3j15+Ui9mKkoWz5/I1nCDopk9PBDTMGNQYvY9+q636UAXVewjKZ7W9d5YGoSTxg7ey1m/5udDudYgJQCPFAPu10DKBGo5kSBGpj1N/UyuDeUtrubaR0fj9Vm8/hC01et3Bw2hDR9iAlC84fN3AqsgwGL0vgazMpedZPyW7rXuzrh7IgBIcgWiM5txXM0BQO1ddkEIhK+kvOz2z+ScDJYnamBeAE41jHAoolxzPZY4Tm+sys0/wsg6obyd1WyBTXqxq27bTL3udYu4bTxplPPzY+YeZnFUztWyVPy2DS1ec8JWfO8Vyoq3SkqHX9HLymE/RK5siwBHqFMeSaXi1jfNm/g7R+BASXdVM6r5ezO2o49ZPpVKzopqR5gFDjEIGA1Tbg7sNEDuNiHysLoHMdlFRF6TtY6loo1ekKnWN2rxOR3VWMNAtOHHGzvZ1PavKIWu/Rbuc4Yh0Xccz0IZskfdfF8bUJTD+YEYj5JN0+SfhlQcNvJGe3mkQbRUZSiBfZsoTdhJDUjFJSLaLpy1WLoFNwWN1OtQiqLuKxSjPN5bbNvo39LrMX2lb7ymXhy7V9oeTrWi7pT9DaXFKUzPqpZgEsVuyfgxaAE8Rzx+YAEFBESfImObxbrmD3WYb48RhYXsLQcgEny094lJuYINewKq4yhKDaT9rYssdYFksYJlzX3vAiKCBMzGEESsK9aY9cJDp9BAw17EA5UQUKvsyHlhGGL7j7yc/NbQiTQDhB81VtDLSF6DlQzrmnahjqCBGqHSI8bZDwtAH8ZXHCfoGQEl/IzHd65uxjKzBL2xFRocooXV2VrgB0Y/pyFSnPIggLziT2cBHnnU3sjsH67PcBzSCldRRGVGL4JH1rBbFGqNkh6Vsq6Vrs9G93lyP71Exx+yZjHtN9vqoLV81jVmcVySgn47p8vX5sikPuWTaS/84597bycJiv0BuusPRIKLQ/Q0gC/SZGAtpmhEafYS11DOBo0QJwnHGEn/vkqgi+XEIv5x+r52pV2FjvntO4qaTexCXI1CQQjMw2MPksg14xgsONQe3bJl9h6CXIc1nBhDCHbVNo8sGw5BKTyvpcgi6X5c9LNBWa0DKc+CprHKCscQAAMy4YOh2i72SEnn3lxPv9hGQlPV3lJIZ8+IImwaoo4aYBIk0DhBsHCVZFiz4LBOBeR5GqAWKdAQT2lF6q8LOb5yUIlXqKuQRhtkQSq50t+HIkkziRk4411fnsxBj6DBO/kQATzOlw9lqDmvshHjQZmJdyUhUhmDEzTAquBdBJ/lBj9pz1GZZAoXx2dj18rOBok0LyvXbysZplCDxpxV8XmtxR6PpCyRSiynchJPVHhogHBDIk3Gn4RoUWgKNCC0CNRnNBY/glpdMHKJ0+4C7zD1UTD51DmpAY8jF0NshAW5juQ+W07ajHjPoINw4Qbhok3DhApHEAf+noE27cMYVMzISBTAiE/8K+i5kROHcFVP9OkiiFwQYdEzhVqTkRo6fuwpcdQoj3AZ8F5gEh4Ahwm5TyP1PafAL4FDAX6AIeAP5cStk2XuO88L+JSYpq8ctl6cvXbZbptrHJ0zLobQFLbWMiU90Q7jqvGLzJ4RrOmTWcrU+174z22felxq0ZimXHCzceK9XFPlZ4WPS8UF28hVsCs5eNcdsrcbBe8xyPal5ed1/Sam+AP2wSmTFE9Ywed32sz09/W5i+tjDnXq7iZNs0jKBJpMkSg5GmAcINA/gChbqzrfehwQC+gEnAbx+z4prMsPx5LRdm3vGCGcXGxfDLkxbBdBewavnzuYN3LIvOXMD2GKVAVkHXJYKaJyRnr04QrxQpZWiUuLw89GG2OMGs6+33hNe15FgCM86/Y7XKPZa0/gqM7RtJJq6QVruxtvgVWvzcq3/nuwj3xAkMSE5sLSmadX0Su4DbgX8A9gGDwDbgv4UQCSnl14QQ7wD+C/gE8DtgOvAN4MfAG8ZrkFoAjhO7js8AwKfUossl9JLtrM/mSC94rz84pT8fHuVMUgWQTN/Msw7fJHcNZ50Wr9CyOcq+Ehnnc2Txbv4cSQqjwf1ucyRXJJMDEmnLHQoVfIXGy3nN8JFcX5jgS982kZF4k0qoNEZoXozqed2A5Qoc6gzS1xahrzVC6xMNDHSECVUNEWkYIBCJ4wsl8AUT+CMJyqb1ESzLnO/UrevX4yNQHkuJAVTcn4UIwnzjBQsoLZO6XI0djJnO2KwVfle4J2cGMYTE7xZ+s97iTT761kHNw4LOyyTRmozTY4+btHNgjSG7ezhDCDq47vB0l67q6nVcvF5CMF9ylVrJJXiGE2Nq3z4kPiPz2i9U8I1W4OXav0rz7iGipYJoqQ9jxDcyhUkqAKWUDyqLDgshbgSuBL4GXAK8IqX8jr3+iBDiG8C/jN8otQDUaDSanAgBJdVRSqqj1C7pBMBMCAY6Sug/HSY+4CMx6GOoK0isP8DR302nZnEnMy87hZGl4kWsN0CgbOrNhjA0D0w/VD8MXeslg3O1O3gqEOwyKW9LcPSi0EQPZdwRVgr6RuBi4B/txU8AHxVCXA48CjQA7wLuHc+xaQE4TjhPrgEPK0qmNYWsyzMnvPf4AZWZT41Z2+dpGUyz1gkDIbK4KD2TLIrjGk7dv7V8lK5hdTs8rIKQ0zKYnGXECbxPb19ogoORIwlkVHgkxeT6Pr1dv2o2sHrtpZ8TL8uDWhQ7F6OZYcQQMu348p1zObWkis8PgaY+Kpr6MtrFhwwO/mY2h++bzaIbDidX2Oc+3umnpDyaaT33dMs647THkWKdVTOIVYttMqzAIqF8/2ryiNcsJMlsYvu3zG4Xcyx/9m+O3zAJGAliylzBfttFnJht0F0B5dsNgl2S7lUy+YOXimOdEzL3taFaCD0tfyifh7cE5sLrWi40E1dtNxzCowTMSC1++WbjZvRXgP911hNDDNQY9M70Y8Qzi1iPlAl0AdcJIXamfL5NSnlbagMhRCVW3b4g1p/fF6SU/wUgpfyFEKIKuA8rqsIP/Ab44NgPPYkWgGPMgRPNAASUXwTVtZuxPM/+kzMHKHj5HPIuba9ul/rBngpO/etzxZDjUiquazh5g3KE4ihdw+p2WfbpoN48vW5I+ca3eZHMvDQLdpkOt/+0/pWYSE+h6bHeS/BlZLDnWT4m2W86XtMYJvvN//z4MtxjiRG52H15fo9GyGTJDQd56QfL6DkeoXJmr7VcmMSHDNpeqGPRW45k1IFUp3B03bWKWzYtC10Rfm5NQXsspvLwl7PWYHIKDvv/6UJPFX4+Vz1ljwF0bjLx1BHVQPe1UPaEoPEOiDZLYpUCDDB9IH2QCAjilRAtFcm/3RzCLPn3I9PaZwo/9XN2IeiF189rrtkwMvvJ/Xuc7YEqmws4Y7s8BV++Qm6kArD2lRj+QTh4ddDOXpY5z29eSCbSBdwhpdyQo00PsAZr1uytwJeFECellN8VQlyMFSP4Z8BjWDGA/wL8AHj3mI1aQQtAjUajGQOEATM2tXLi6WlUzjzgLj/xzDSq5vRQNq1/mLm6L3xkCfRcLaFHEDwFRh+QsHSkSIAYlAS6QUQlvfMl3YsNzBLtMj6fqHkpTtU+k9NrfZjBMbjWJ2kMIICU0gRetz++IoSoBr4IfBf4MnCnlPLr9vpdQoguYIcQ4u+klHvHY4xaAI4R+443p31WLX4ZLl+n3Uh/3zL+EDz+MpRH16RlIUf/qZtJK1A8w0LlulrVbSfGNezWPfO0RCrbpfWdPubM2RQsvK2cI8P5/n3CRIxFEogwUOdEdsgItHev1ezZu4Va/Aqx2Fn7G769z8PymA8C06plOUI3u9fsJMmxWe/NS9s5+UwT3QfLqVvQSdfpUtr31LDm917DSNm/e315JW6Qfk2n1vQzlXX5ZhLnchWr8xI7uJY/10drX6e2y9epYalmC2ezBAKY5QbRxcnfINN1adtu3B4ofQ2a70vQP9Oke4lBtDz9/Kuz2XhlCedrCczFSDNwi5F561hY82WkBaCHK+ics13cZNrDCULn4PRFPnrn+hCJ/M7BBYwBlNj/jpDpuHN+8MftKUcLwDEiX9eue8NHFWbp5LxNZdycLdSs1HyF4bCuYoFdRkNt4+Watccy3q7hvIs3q+PIdgzqTVb9ERxerBUa3+YTpnfc4WiQeLrCHZFhujf47Fm8GcIxT8HnJdhGWgA6H/HmLQ4TIDKzdDNLn3j0m2Pf7jH5YMk1B9l99yJOvthPb3uEhVccpbR0KK2d41o2SBeEnnF7Ka7iXG5idwo3D1expwvZ3j5m+tP2neVsWP07Ll9hEhBmZpkY0l3CrtBTHjxMJczCrBB0bzToXQmRfdD0uwSDDSbdSw0Ga4a/dnIJQa9YQZV8RZSXECyGYJM5rkkvpHKM+aKK6nxdwBV7EtTsNjEDcOpag2iFkXb8QmQWsR4JgslbBkYI8QXgceAQVozfNuBzwPftJncBnxdCPEvSBfwVYDewf7zGqQVgkTlyYhqQ+hRtoVr2fEqcjrvc4y8jeSPwNGN5LM4ep5eJsiKHIPSR5QfA/ThJLIOjmdXDFa1G1raFkmvqc3VqNysJZGzKwGSU/hFJMWHte2wFnyrc1O3ymvs3bXwjuAsICUJ6WiWz5SRkw9MynBIr2DCji03v2UX36VJq53XiC5gpDxKK9U0pxZKcri1dGKbG7bkPF/Zp8Jr5w9NSqMYIOsud78GwhLIqBF3BZm8XcJoLK/7Pq0xMht1NEWfZ1htCQhh6Vwv6lkH4INQ/kSBeZtK1TNDf5EsbkxdqbKBUrh13z3nG7OVKtMjVPtd4xxKvOcAdCrXUhU6bNDyVwDcIXUsEPasAIzkHdKqQzCeGMS8mqQAEKoBvYgm7QSwh+Hl7GcCXsCx+f2kvOwdsBz4vpRyjH/5MtADUaDSaMaa0ZpDSmsGclkVNbmRA0LtY0LtQEj4KNc+ZRBokZ9b5cj9paYqOMWjS8GSCknYYbBScvFZA0JjKrl6klJ8GPj3M+gSWCPzSuA0qC1oAFolDtuXPeXoO5HDtqpY+I+/YE+epW7W+5WcZVC0Mye3V7YaxCNpzUWaWDfHqa3jXcHL74rqGC4r5A5Cmpzsyac1Kfzgr1g09u1Ws+C5gAyMlJkz9/tLPvxrTl2kJLMzil2+sXi4rq2rxGy620KsvKRKIbC7gAt3TuY5JTfJQY4AT2bJ6wdOal81V7BWzp2YUe5WY8XIVZ1jeFUtgwI39s95iTkigXaZEzRb2u2O396O421XXb/LbSboQ0yxmhmBgLgzOMKh+RlL9iknHuuzfl/MtSSVL2FSupYxrK0eBZ4eclsEcVrbhLIHFshKO1BU8HBV7EtTsMomXQOvVBtE6R/hllqpJdYcXywIoRjpZswbQArBolGQIunQcwacKvaQr2EPY5YvXb0S+LuOcrmKZEhtkvTxnufBM1sjuGnZvRK57pjiu4YJi/oBEFvNBrht8rqSdQuPbHKw4meL/uJluhF8WMpIG0oXfaAWfz70BKIkPeZK5/8KEZSomppWEkePvLe/yPR5/gF4CNOmGdURPusBLZLhr013F7nRtJPJyE1tt0wWhKi7V5KDk2OxzJO0rRxGCzo3dEXx+EgREwrNsjPs74B4L6cvt/ToziZhCuqtM5XfWlAIZEJxbJ5h2X4LOFSZmSHiKJudvSuZyf45S4BXD+jVe7uFCXcHO56rX4lS9IulcJehe5rOEf4rw89ruAikDc0GgBeA4kzAFu19t5sDBBk61VjE4GCAeNwgGE5SEYoRCcULBuPteEooTDMYpCcUoLx9ixrROamr6xjFPSKPRaCY3ibAgUQqhs5KBafrHcawpO5Sg6mXJ2bUGvYsnrpTRFPYyFwUtAIvAqZPNOV27jqXvt9uXcPBwPRetOcYVWw9RFo7h95tEo34Gh/wMRv0MDVmvwaifgUEfg0MBenrDHD9ZwwOPLGFwMEDztE5mTOti+rROpk/rpLpqACGyuHbztgzmYxFMLrOe9HL1qXQ97q5hZT82qmUw1U3nWpOKdA8ptPRJkuxZqiPFLfqbcmAZGa+ue9LCcC2pagLQyCx+qjXMy3KXqwB0xv6HMQN4WuCE6Wa9po8pe1+eM+6422XH61gcy6LntSgUi+Aw7lovS95oS8yohdWdsi6OJdBUzq07I4iHC9j57FooFfenc0zJCfJSk0CcDGPHPZx+XsPHJUYchhpJs0KpmGrWr+N0KNBlm+/njO2V68sk3fpmSm/rZbHI5QrOdezBzgR1z5p0LRf0LjYyLH7qezYL40iT6TTFRQvAIhAQAkzB2XOlnG4vp72jnPLSKLNnnqWxts8NnzvVWsGLr8zkMx99nIpS5eYeSQBDOfdlYtLbF+RYSwUnTlXy0u4Z/PqBFQT8CTZvOMr61ccIh/OYYzQjK9kimWWcRRCm/C4YpMQxpbiGgdxC0GGsXcNuO6VmmKe7LuUHKofrb+yD+YscA+iKu2xi16tsTrqLN9eMICMVfCpeNwev7GPPUIRhsWJY8xXo+do4VLd2NpEJmSVYcglC52/LVMSZT2RmFPsUITfiEjMeWbrOQ60rCN1jt7N+hTkqF7DTrxOfFzN97nefraxKsFVS9RycuVy4J8pLmCVLzTgPPcO7K1XynV4tX9S4zeEE5ERJJvWcNz5uEq2BnlVGVpfvcLF/2daPCm0BHBVaAI4CKSWHDh3i4d+tYc9rzYTDURrqe6iv66Wjo5ztTy5gaCjA7BlnKS2NcuxENVdefJCy0ij531IyKSuNsnh+O4vnt7vLjp2s4qnn5vCvT1zJyqUtbN5wmGmNPUU4So1Go5mkJCSVT8O5rYJYrZg4lTRFKN+bwNcPbW+cHG527QIeHVoAjoCuri6eeeYZnnj8RwBsWNPHNZ98hPKyoaTL1zb7dfWEOHK8muhgiGXzzrJqSRs+fPi8MlFtEu4TvpH22Uhxs0CyttfcGV3MnfEynT0Bnn1xFj/46SZqq/vZsuEIyxe3Inx5/jJ6WvFE2l+bIVIlrOp2Hr6GYOa+1BVFcg0r7XJNu1WIu3a0deJyYtepc/c3wjubajGy5nD2sKS6bseRWfySy9MtSV6Wu0KnQfOy+I0kC1iIOP4UF3u+VsTcrmAli1iqFkH7nLiJGOlW9FwWweQ5TSaPqG7ipKUuPXGk0BqDnhZ3ux/Hz6BaBA1hpp33DBew+5tmd2jPIJKRDJIyF7WhjNX5HD4kSFTC0DTFgiZJ+5zN1ZpKoZa9fC2Gudy56tzF+RWMtxLERloYOhfOmPxG+t+vEUtQ/bKke6nALBnG9esRhpTa7sHLvzImY9cUhhaAeZJIJNi9ezc7duzgwIHnWbakhXe+5TizpncihCP4DPeH2flRbKgwaVh+xl2eb6EqQxE/zmdH8CXdN+nZwzXlCa7ZdpirLj7E7n2N7HhuDvc+uIyL1h1l07pjtvUxD7LG96XEjyGSGbAZv30egnAcXMOmCScPNNB9ppRgSYxQJIavJEEoEsVfkiBUGk1xh2Z3VcLIs3dVRpKhCt5lSgrvyH53r6csfSrfoxrTl6vsSr6CTxVZqnvUS1x5Cb5MF3P+5gBpty/UHZWvyy9ZYiW7Czg568bwgtCNx5TpAiFVGKpu4mKVmIlJjxlAHN3mxuA6Ll57rNhZnh4xgsnYQqe8jL1f97csPRbQh3DdwaobMbJX0L0lt8tXLSMz6li+sTI9pf/MAt4iUs1ozpdc1QW8hF394xIzBL1rRHbXr/p36iHGtQt48qAFYA5M0+TZZ5/lnnvuoaamhq1bt/KWa79MKJggNImrjvp8ktXLWlm9rJVTreU8uXM2//aNy1m64DRbNh5hxvRzEz3EohKL+ji4azp7d86hJBKlfuY5+rrCDA0GGBwIEh0IMNAboqKuj2WXHaKmuXuih6zRaEZDAny9EKud6IFc+IRaTUKnof0NEz2SFNKdJJoRkJcAFEJsAz4LrAFmAV+QUv4/pc0ngE8Bc4Eu4AHgz6WUbTn6Xgl8EWuuvABwAPiElPIpe30j8F1gvd3nx6SUg/a6/wE+APyrlPLPU/qcARwHrpBSbs/nGLOxb98+7rjjDvx+Px/60IeYP38+AH0tgtRTZ2AQED7332OJ2r9qGVRdxSaSGU19vPP63Vx31T6ee2kGP/3VOkojUbZuOMKKZacI+E3XgqgWrnYRpFnwjNS2HjUEnef/pKVubFzDR15r4ukHltM48yyXXvcytTO6gKQry7EoDCV8HHu1iZ13L6OqsYdl2w5RUdufdQi56r8VOrdvoTh16kaNkzyQYmHKqMOnZHuqlr986++pdQMLcdVa64fHs99h7gKeFlhh1apLtivsTpLTFaxm5irjybTGZbcIJq1squXf6dfMy01sLS+sxqBjLVbDGJztAo412bYUur8hRgLTiHvOIexpCXRxxm+7IkmQcOqopriCjQEwSwTGMBfOcJmo2dp5ffbs3yOr12v/Xq7ntPG5v5/Du63HCtWi5+9LUPcYDE6HWH0W169HckcyhES9Z2kL4GQhXwtgGbAH+Anw7+pKIcQ7gP8CPgH8Dmv+u28APwY8nxmEEKuxJkz+PvAF4CywEDiT0uwfgJex5tH7LNb0Kl9OWT8I/JEQ4utSyqN5Hs+wtLS08Ktf/YrW1lZuvPFG1q5dixCC7lOzAAgJ67T53Mr6E1cHycF1PSuCkBRBWBE2uWLLUS7bdJS9r9fz+HOzufehpVy05jhb1h+lqnJwmLmGSXNNGEKkHHX2EjLJm5Wzojiu4eSNzGrQerSWVZsPsuyiI2nLVUK+BAtXnWT20lZef3EGT/x0LUu3HGbB+hPZ9z8M+c7t67YvsOyBV5mSvLdXZklJuKIuZRz2+XQKYAdFugswVxZvvoJvtCUfvARfRkxiQS5gk0CWcal9eF1LuVzByTCF9O/QHbt9zTvCJinGnGNzXMHZBWFSMIqkC9gts6KW9UmPuczlKsZ1/SplZex9B+3QhKh9+3C+ZycGUNgZ1l5zCLvnCOfYHSFhfc6WPex+VymXtTBA4MNvJIib6bHR6j4KLc/iLh9liICpxmV6CMJsIi9f8Zovhbp+/YaJ0WfSeC8kKqBzG26JH8gt/JLL0z8XpQi0pijkJQCllPcB9wEIIb6YpcklwCtSyu/Yn48IIb4B/EuOrv8LuE9K+ccpyw4rbaqBR6SUu4QQ++3PqezAEqhfAm7OeTDDIKXk7rvv5sknn+Saa67hIx/5CIFAstjBZBR+uchMIrGemJctamfZonZOd5Sy4/lZ/Mdtl7Jwzlku3niU+bPPIt1A/eSPc3LSeIkBBFyxqfwAqBbAjOBzu50Tl+OuT4/X8SnCMHmzdISj9RaJDCLjImnRcWYs8EgSKQmYrLjoMBUV/Rzb28TS9cnnhhEnbSiMRrxZZJlqrxCUWVKyWe1ci5FH+ZZcMX3uZ7Jvn7G+wEB5tb1rmczTAjjc+ZPKeq+2ub4Dz7hFNblD6S95zm3xJZX2YnhBmBR9I4sbBFJis7DbpVv+kr9v/rTlTmygWjMzGbNnIkUiY+YQMyPpR7VAO5bF9LIxPindmoOO18EU0hqWaX3/fiP731vmPrOTkRjlLs9P6A/Ts/WmdjPMZrn6tGZikphS4O83KT+RoLTdJNQl8Q9KpA9iEcFglUF/rUHfdCtpw7s/RfgJk8AZk8q9kpITkKiQdF4LhiEAmbfwc383siSBFAOBdgGPlmLFAD4BfFQIcTnwKNAAvAu412sDIUQdltv3r4QQ9wCbsdy23wJuk9K9+38RuFcI8UNgH5kWRQn8KfCoEOIrUsqdIz2I7du3s2vXLv72b/+WsrKykXZzXtFQ18eNb3qNay7fz/O7pnPHb5YjhGTrxiOsX3kSX6B4xYjHipJwlJ7OSMHbCUNimrl+wDUazaTEcPNPphRlJ+JU7x7EN2AJINNvCb6+BoP+eoNAvyR8xiTSblJxIoF4ARAQD0GsVDBYY9DfYNDXIMCfFIahdpPq1xKE2yUiDoky6F0Kg6vJHZ8xUei5gEdFUQSglPIXQogqLCthwO73N8AHh9lsvv3+11ju378BtgD/iXW5fcPu+yUhxCygHmhLEYap+39cCHEX8G/A5SM5BtM0ueOOO/ibv/mbDPE31DIPOL8sf8n4H48nW+URNBIyuXTDcS5Zf5wDR2p44rnZ/PaRxWxYdZKlC9sJBeMEAjGCgQS+QByZCOArMTAEaZZBsNzD1r4di59i7VA0l7uda7EgrV3S4qdYQ+z9RCJROlqqUmIN0yed97LiBH1xhEy3WOXK2i20dMlIkXnGAHq6V9UMzpRToFqEkpa1sbH4jXY+ZW8XsGohzP9m4BeSQBbzQaEzgXi5s0w3XEEde/p6d78jtgiKpCXP2XcWNzGQ4Sr2sghmFAZ3s9HTLYEu7nbOu1VqSJ05xLkW3XIxrgfANUGm7d/nrjfd8+L8RhjCtIaTsCxWXjG5Zp4mopG6JdUyM1lG4O4BMrOSs2X8erp+4ybTH49T1++jrdaga4ZBX5ORJuIczqWOMZEgcloSOW0SOiupOJ6g+vUESOurSZSAb9D62YyVQ89S6F0M/hJre79nlq8SEuLlGlY8PmOWQa0pmKIIQCHExVixen8GPIYVA/gvwA+Ad3ts5ngq7pVS/rP975eEEIuBP8QWgABSygTQmmMYnwNeFULcALxQ6DEYhkFDQwMDAwPusvNR+HmhuoK91iNg6bxOls7r5ExnCU/unMlDjy9gKOojGku+/P4KursH8AcSBAMJgsEE05u6eOcNLxEIWjcIx12TGZeTLgxRhGG+rmJHEFZW9nHyaB1H9jcxd1FLSnyeI1AyjzcW9XHqUB0+Iz0WLJf7ZfSu3fyICxP/aGIAlRtPWvyVEh+I29JxTxYW0+fl4lVdtiMNZs8l+LxqMg4nCBOKiz3XX3bOmD913+q1qozJWe9+E4pgdJMePARhcnsjY0YeNeYPD0GYq+age3tIqSEJJMsxuclE6SEZQiRAJFyXsJcQdLHHEXDcuKbz5vx+CPf4zVQRabuAAyLhnkh1hp7RuoBz4fbvdXm4w8meEKEmfGQfm8TfZdL8oHWcbZf7OF3tt8TiMDt3/x4NweB0weD09H37hxKET0nC7ZJohaB/kQS/YcX+kfx7z3VuvISfW19SZo/PLAZaS46OYrmAvwzcKaX8uv15lxCiC9ghhPg7KeXeLNucst9fVZa/Cnyk0AFIKfcLIb4F/DNwbR7t6elJnylj2bJlPP/889TU1AAQHWgAcBMrzkcBqFoATQ8BqNYdBAiG4IqLu4CutO1MoH+wllConXjcIGaLwh3Pz+and13JW699BZ9PprRXBaAzlnSLn4MjAFUribudEwdkr6+tE1x5zXFefHY9r71ksmrjQeqndWX9UZUSjh5oYvfOOdQ3dbHpskPEBhtT1k8Ol3B8aHS1LdQM6FQh4gage2XZuL+qUllrfQNSuSG4Mj5D6DuCIv0GUWgGddLqlX25lwAcTrRFh+qUtqPD6xaZkRXqkTWaea078a5KO6W/BIZ7zaqPC6aaSexuk56AoO5TuhZBJ1vXWi7sb8CRHYZ0YvSc9ta7iFambe+MQyjXonTmp1auR5+d0OF3hCE+4qb177i9zNnWKC8hHvWnCMD0cyDzFIBihAJQuufYwwLpHqvHOZfOObfe42byComnjD3cbVIeMjl5hY/yQITqhJFHrODw6kgEJMyG+Gzr9FUJ0yqtY6Y/CDoFoT37UQWg/e6c04R9HcTs7zWU8Gfce0eERGcBj5JiCcAI2e7jFl5X6VGsmL8lyvLFwJERjuMLwC3AR3M1FEJQXl6etuzKK6/ki1/8Itdccw2RSIR4Xwdwfgo/FS9XsMpwx5rah18YREo67OXWX+H0a0/wnf/bwN69YTavO8ae1+vp7gmxbFEbFeVDGa7iZL/pFkEvQaj+uJvuesHCxS3MW/gqe3fP5NHfLKWmrory6j7ATjYWEkPAqWM1GIZk2zXbabJrIab+kHq5+lLLeSTiBuc6yujtjDA4EKC2sZvaxm4MX/F+jYSQBEqGraA0/PbuzdW5iVqYGBkuQQfV8udd/qUwi19yfWHuVdda5uFGzbRQ5o9fQDic6VTwLINko167nu08mmWEP7gWIKf/7ILQ/c4U8ZZ67pxrVBUG6vedei1kW++IFjfP3wkncMSKmwTi7M9nb2+9S0CGzuJ8I+5yR7y5x+CIOmd763PMEQz2e1z6iJlG2jauiBwsRxq9ECRtvcNIHza88OrPFbHq/hVxmykA04WtKYUrdlPbds8E/wtxQjsF3ZcYnPNlL1+VdiwFZj47Qs95D9rJO/n2o1r+HJxjjNoCcNAIZNx7R8ooCwxMefKtA1gGLLA/BoEmIcQaoFdK+TpwF/B5IcSzJF3AXwF2A/vtPi4Cfgj8npTyWSmlFEJ8GfiaEOIPgN9ixQB+AviTkRyMlLJdCPFPWPGEBVNdXc38+fN5+ck3snFl6wUh/BzUY1EFYT7HmtrGqn3o1P+yXQWGycXrjvOrB5bw6FPzqa4coLJikPsfWcL6VSfZtuV1KsqT0+VlZA97xA56uYiTmyddHctXHWfh0pMceG06A4NBpLRvONLq5aKt+5m/qCWtJGEi5YMaGwmW1bD7TCknDtdz4nA9LcdrKK8coKKqn0BJjL0vzKa3K0L9tHM0zTxL44yzNDR3Egh6u3Bzx6slCOaoRZh9K8VSlHUWh3S38EizeHNl5XoJOJVc63MJPq8YwuHEXAKBD1HwX3i26wOGcwGr50wM286Ng1VcyGpmfKqLWC05o5aWcYaguoDdmE9lFpKoY/lzXb4eMYC2EHT6CzihfMK0rq30P1/XJeyGICgxgcPiWvic82R1GjMkPlO6VqiEaoUuskVfvV6StROtN/ccu/tV4ytzj8tLcHVsMmjcbmJ2JTBqvf9mCp3GTl2eIeg8rNZewk+dOShZBsY6F36t2iYN+VoANwCPpHz+mP16FCvp4ktYFr+/BL6JFYO6Hfi8Hb8HlpVwsf0OgJTyG0IIP/AZrPqCB4FPSym/PbLDASzh+Qlg5kg2Xr16NbteeJCNK3OFHGqysWzRaUwJddX9NE/rBqCzJ8D2p+bxlW9dxtqVJ7lsy0EqKwbHbAx+v8nSlcc946+yoWhNhgYCnDhax/HD9Rw/1AAIZsw9zaKVx7ni+hcpCVu3M2cfQ4MB2k5U03qihucfX8zZ0xXcdOvjVNb0FfvwNBqNgw9v//sFxlCTwUCzpOEpk67NJtG6C8dAMWK0C3hU5FsHcDvDVC6yRd6X7FdBfUgpvwZ8LZ9xZNn2g1mWDWLNVjIi5s2bx/33VVxQ1r9sFPP4UotQB/ywfnk7kHwKrimP87Y37ufKrYfZ/tQ8/vO2bSyYc4aVy04xo7mTgD9BIGDi88fTYgdzWQTdWDXVEijSn1BVUoXg8WO1PPbIclpPVSOlIFRiCTtpCppnnmHW3NNsuOh1Kmr60q2GylNwIDxE2cJW5i+0Hhzu+OElxAf8WYsN50PqXJuFkFAzB9UuUi0zzveWUf+vuBY/rxi9XCQtk8pyobYTWdtl7dP+EmNCEMhh+R0O1Xqtxieqme/q/tV2XlZuNTNevbZ9UnrWx/SyCKrz4qqZ4kHF+ugsdxOLnIQy+7PtfSXqGuJNDJFI/v2p1i+nHyVTXT1XaW5Te5XrPbDHEPNJ/NJEivRrxVSsmsVCfag0bIufqbqAPSyCrss3JWcbkhbNbJdhajbwmcsMyp8WND+UoPUKSbQh86rPd7YTdXmyALRTRSH774BXNnDmnOHO73H6Z6+ajSNBJ4GMDj0XsEJtbS1nO0tIJESaGNHkj9esJFVlMW58wz7ecMkhdu1tYOdLs/nNQ8uIxgzicR+xmB2jFLAEod+foKpygKbGLpYvPcXsmWcRInnzdQpO57ppegmDtlPV3HPHJq5648ssWnwKw5D0DwZACoKhWNr37xWb5aBmYgb8Ccy4kYer16u/wsqaOCSFSfrN2kWSccP3En75Cr7kmJ3tyb5dxliz4yX4VPdp0gWcXbwNJ+oMe31mn9nDE1TU7VRXr/rwovavZsjnKpk0nCD0cg97uo+zZBKnoTwgOPt2ZwCxhZsjFKN2a0cIxjGtEaqn3xWCTixiuivZKd/kuIod13TASGQUtXbGJExbUCiHMOyMRiMgWb5FXZ4u+HIJQuebSzrTnd/KpFjONXtJ50aBLw5Nj5icvlwSbTKGbe+QSwA6rtmMqd5yPMT6PFzF7nZKXKQuAzN50AIwBSklTzzxBE31fRiGvkjHitJwjM1rT3LRWmsKtuQ8xpJEQhCzxeBQzODsuVKOtVRy172r8fkk11/zCrNmnRmu+7zo6grzy19s4s3XvcC8hUl3fzgcG2ar/Gg5Uc25M2X4fFPEN6U5bzFNONtRTkdLJW2nqunrChMMxwhFooQi1rsvnCAUiRKMxAhGYshA5rTeo0Wa0PlCFfEBH+FF/QQborm3kSAHDETETGYuTxHOXOKjZkeChu2S9m0mQ81T6/gBO9tI36dHgxaANj09Pfzv926l41yYW9+2u+g/cFOZfOYpttZLAn4I+hNQkiAhJXXVgyyad4arth7i1f2N/PSXG7lq2142rj+afKr2cA2rbjnH6jI46OdXP9/Cls2vs2RRGyDo7w+yd980Tp6qpqenhJ6eMIMDQcrKB6is7Keyuo/pM88wY047Pp/k5NEahCGpqu4lHIliGBAd8vPk9mUc2DeNy9+wi1kzz4z4OjI9ChV7tnfcdIrrV503GWFkJAWMtcXPO0ljePK1+KlWteFw2voxCKSIBrXPnNnAUj1W1X3pnLPsY1U/m4r11bUc5mERdB4z1NqCmcWk7TcpeeW5eRzeP42OtkoiZYPUT+ukdloXcxa1MjgQZLAvSF9/iL7OCgb7Qwz2BxnsDzLUH0CaBqFIlEAkRjAcIxiJE4zEMMIJgpEYJaEIRlkvhCX+SAyfX00qsj47cwkHiNN9uJze/WWUL+yl/e5GaradIbzIynQ1pZF0WzsucCkxBwxEUBL0J1JKRznWs7RdZpTCKRTVvZkMtbD/hjwsfqpFMHnVp7t+U2vm5ZoyUWBdJ50XG+AzqX9UcmZbgthMD0u4l+XPw2KXdP16JXXk2c84zAWsjYmjQwtAIBqN8uUvf5kNy/q59e27CPj1VTWWFCII3fUCVixuo6l+Bz/42QZOn67kujfuxudLxspFTZOOjnISEmpq+gj6My1we/dN477frGbpkha2XnSIF1+azauvTefEyWoWzD/N7FntVCwaoKx8kJJwlK6eEjo7I5w9W8YzTy7mvrs2MHd+KwcPTKOyqo/u7ghIqK7ppa+3hDnzTvOhjzyUYUks1BZoUOBcwPaN0Z0/2cv9hompnF+v8i35Fl5WY/W8YvTyJdMF7Ljfsos0L1evl2vYWecTIsP96SXkMsaYITBUkWO7KhWhmDwW9dpP338hgjCzTJJ011lt7X3b2z7/3Hz2vTKTi696lYamTnwlyowhSjkZJyvYEVH90QDR/gAD/SGG+gP095UQHQgw1B+k+0wJ3fEaujsjxPoDRAf8GIbEH4njD8cJROL4wwn84ThG2MQfiSMNaH+mjtqLzlCxqJdw8wBtDzdg9htUre3CRKYIpGQcY2zAwIgkMITEKWadrU6i1X50cWdq1q46f7I7H7OSpZwhCJW/T1MRRYaQGcWhM+fcTf7mdW8RCJ+k9jHoulQyNDtz7F6CK1u/qe9erl0vVOGXnJkpfX1R0bfqUaEFIHDo0CFqamq48erXJ3ooU5JCBOG02kH+8EM7+L871/C9/93C269/hZqaXqJRH7+4ay0nT1URCsXp7AqzbMkpLtn6Ok31vXT3hHj40SUcOlLHze/YyeyZ5+jsKuXBh5dTVTHAn3xsO2UVAxmxWFWVA8yecY4Ekm3b9tLbE2L//mZAcO11L+DzmQwMBDl3tgzDZzKjuTPt2LxixXLViYuLZFmN4VBv+p4/sY7lSApr5gTGXvDlitHzitMqVPCpomo4ktZCA3+KDdKXpRC61S476ow6htLS9Dh3SeGWXgQ57WGHlGN1Y9+yC0If3rGw2WbSeX1/Ey8+s4D3fOAxyioG7PbKeVVi9XyKSA0F44SCcSKVQ/ZYHKFol4UabICSDqLSh5QQG/IT6w8wOBAk1u9nsD9oicOeAINtJcRjBvVrzlC5qAshoGJGL+GbBjn8i9n4QwnKlvVmlI4B6D8ZJFAbc69n6xgVoTZKF6FbYkf5HlVhmUyoSReEMWe4zvjtBIi46fymZbMEKqVjHFwhlZ4g1rdJgg8qH4eeBAzNS7YbDlWwuQltGUkgedaQVX5H1BjAYifkaEaPFoDAvn37WLRo0UQPQ5Mn4ZI4H3zXTrY/PZevf+9i/H6TeMJg8YI2PvOp3yF8JgMDAZ57fg4/+PFWBgYD+H0m69Yc4w8+sp1IyE5KqRzgTz72CA9uX8LXvn0ZmzYcZtOm1wmXxD33XVY+xLr1h1m97rC7LBKJEomcHfPj1mhGQ1trJfffu44b3/0UFZUDnglNxUQI8IdM/KEhgtWWVTzmUfg5tdh6oDzO9Lee4sSvpkNQEpk/kNavjAt6Xyyn+vrRxwNfCPRtsHRW+Q7AhKEFOTc57xFoF/Bo0QIQ2L9/P295y1smehgaG9eS41qt1DIRBoYBV249zLZNR+jpC2CagorKAXd9IJzgqksOcsXFByHhQwiZktWbfJyvLIvxjut3cWbrQR56YgH/8dU30djYzcwZZ1iz6jh19d0Z21gfPaxXOUqSOMfgFs31aOfLkqGaFXXC9Yy4SItk8d/kcq/yLaO1+LnLPSx5yf17uG494uQyY/+yu2+9rHnp+zbwCSMvq6HX9qlkuoAtVEuhOq+4avVOTovmuM+GtwgmkMmSI87YslgEe7pLuPPnm3njtS8xs/mc1Yd7rSgH5+wzVziBu71j4bGnCkQiMDOyhDO2U1Esj6U1A8y+4ThH75yJITsoW9CLIQRmVND9QiWhhiEiDdbfvFv2xe7CEZdGjvm0c80UkjlzS3aXspqd7FgEA0oBa2zLH8q8x6lVYZzHT9fNnOL2tsZkZi2mPLgehA/KnxYYpiS2JPuvi1dZl8xC0Gos3/Colr+MGEB7/W0bfpBXfzmRUieBjJIpLwAHBwc5eeIAc0pvnOihaBRyCUEDH34fBCusn8yYzCIUBO4dMdNNl/yBbKgd4F03vMKN17zK8VNV7NrbxH2/Wc2HP/Ck3TbdNazexbzET3J95o0mkRB094SIRv2ES2JWMonPcb94i8h03Mh+a5wyPf7LPSdk3sy9hF+u+nv5Cr5CY/8ccgm+TBdwuqjKbx8jF39e/WVdnocYTd0+lyBMxp45rkOZMcWiWoJGxgW//PkWLtpwmNVLW1JctrbLT6mh5wi/qD2WoFPLP6cQtN+Eac0Da38ejRCMNAwy8y0nOPW7aXS+VAnA0JkQoYYh6i5vT17DyiwnXtORqeRKRFKnS1QFpTt/sRLjpwpCd0+u8LPjKhWBbwqJ3/5ukzGA6fu0XMDZxd3QWjD8gtJnDQYkxJZlCqTMpA3F9asIuICbyDL8tZxLMI5FDKC2AI6OKS8ADx48yKxpPQQDumSHBoLBBPPnnKGsfIAf/vSiUfcnJRw7XkN7eyWdXWE6u8J0dUXo7ArT1xeirGyQYDDO4GCQ/oEAhiEJl0SpqirB8J0hXBIlEo4SDkcJh2P2u/WKhKOE7OXoskUaD17ZNZOSkihbtxyY6KGMiEjTIHPed5TeQ2WIoKRk2qBbOjCXKJmKDK0ykQaEn/MhTJPoCn1v02RnygvA/fv3s3DOuYkehiYPPF17tmUwINKf53PP7qD0l/KEaiCIxvzIhIE/tSC44m7z7lnQdrqc3z64gs6uMHNnn6GqcoAlC05TVTFAVeUAFeWDBOyOTCRSwkDMYKA/SGdPM4lYF/0DQQYGg/T3B+jtCdN+upL+gYC1fMASjYODAYLBBOFwlJLwEOFwjJJwlJJwlFCJ9e9QOEpJSZRgOEZtTS+hkljRLX7uciWpYLhs3OHPYfEsfucb3hbBdJ+hIdKtgVbb5PVqmrDjqUW89bqXCRpGxnpInVvbsRJb5zto78uxBPqcfeewBPpJWC5SxTJYqCUwtVyM3zCpWtCdFieY7Vgysrhd9/TwrmB1hg+3vxxWK6f/hJKk4rqOnc3d7tMtf8myRAnnAIg5CSLKsSUTUrK7gFOJr0gw5JOUPOtDJCSx1WaWrF81kSl7UpjqyvVCzR72Wl9UJulzrxDifcBngXlACDgC3Cal/M+UNhHgb4H3ANOANuB7Usr/N17j1AJw/35uvEwH8E9m1JIZGTf+PEVZBlL9QUv221TXT3NjN/fev5Krt+2ntGzQ3ke6a2co6iMYSLj1/nwI+vqD/O7Rxex+bRpXXnqAzeuOuvGH6WIo+W8fAgQEQ1AZihIJ9VMaPutZhsSNNUJiSugf8DMwEKR7IGALwyAD/dZ755kyBgYtwTjQH6TzXCllZYNMaz7H9JlnWL78OMFgIu8ZNwoVfIUKNa9YvgtZ8OVieEGYFIOp6wLAy3unURaJsnDWOaTyvTlxqK7x2HEF20IwpghBVdB5CcGEkFY8oBuLaAs5ZQYRd2o5dyYQ51it5TG3fdxzGjun7+R6+xzkEH4ZU7plbZXE04Us0t2mqiAMKLF+jls34A7Ueos5lQ6kTG7jjFWpbegTibTp1LzGlliWIOqThJ7yY5iQWJ9emkot8+LW/bM/O/vwKcIuIdUvPr0/B+d7TGaTF1+tTWIXcDvwD8A+YBDYBvy3ECIhpfyaEMIH3AtUAB+329UA9eM5yCktAPfv309raytzZnRN9FA0k5B3Xv8KDzy2kH//5mUsnn+a+XM6ONcV4cy5CGfPlXLmXClDQ36mT+tk28UHWDD/NE/vnMsjTy5k9fKTfPrjj1AW8c4oLhaGwHYPxyhXSoA4EjdtKjspONNRzumT1Rw+2MiTjy5j/cbX2bDhECXDZEBrzi+khIeenM+bLt+HEJPWWKIZQ+KLTaQvTugJP8KUxDfqv+/xQEr5oLLosBDiRuBK4GvA7wHrgQVSytNOm/EbocWUFYDnzp3j+9//Pr//+79PwH/vRA9HkweegfYjtQxlWDBSLYIG1RUx3nn9bq67ai/PvDSTw0frqKnuZ8n8dqqrj1Bb00ckHOXVvdN4+NEl/PxX65kz8ywfu+UpGut7gfwTGVT8wpfm0lazTDOsl27GoPM5PTs4tTiwISTNDV3MbOxi/bojnOso58kdi/jmf7+R9euOsPmig0Qi0VHX48vtgk9HW/zyJ9UiqLqHnWSnPa/XIaRgxcIzCOHzdhUrc0Mnr510S2AyK1htnz62AAlrBholS9iZSzjpxk3OiJt6TOrymPSnZEObSh/O+VDcpcrfS2b77OSy9HmRWcDbtmKafvuznVBhu3pjbta+cm6NRMY8wqrrNCAkAWGmJKDkKHK9KEHcn8C/PYRhgtycPs1eRj1AZQYQQ/3t8QjFUdsl5zceoxhECeNSy2iUCCEEsBG4GPhHe/HbgWeBPxBCfBBIAI8An5NSdozX2KasAEwkEvzVX/0VZWVlmK2522suPDJmY/BoUxY2uWJL+sNZajbw6mWtrFraytnOCPXVA7Y7eHgxlKtUiZGxjeoGV2KdMuL41OzgZC+qq7ehrpebbniBrnOlPPHUQr7+jatZt+YYF28+SHnZ0IgF31SI1ZsMqO5hsK1/TyzgTZceJWg4dfccV6It7OzsXndKvBxCMNMFnF0ISmHiF4kUF7CTpSyU9orwU5b7Uq4bdSo3VfD5cgq+4YWC6lLOF3c/isvZSPqz7R1Yb46rN6CUkUm282VMI6cihIkh8p/czpQGzEuQ8A3ie6gEWRWHpUlLoJrtGzCc3xiPrN4cgk6dYcgRjBfYTCB1QoidKZ9vk1LeltpACFEJnASCWBFKX5BS/pe9ej4wF+vKeDcQAf4DuEcIsVXK8alvM2UFYE1NDZHedZi9Ez0SzWTBJ4yMum0OqljMSGwQ0FAzkLfgyyWK/MJPQPgzZkXB42bt7C/h8YsYSBF9XjF9jTWDvP26Xbzhktd57On5/Od/X0VVxQDNjd00T+uisbaPRMIgHvcTixvEYz7icYNY3Ecs5iOe8BGL2etjBrG49TJNQSQcp6w0SnkkSllpjLKI9e/6mgFqqgaHPReawtm5u4mhmI+1S9syBGJMWjd/x8KsTkc3UiHoWLFMkUibnSPhWh7TyzoZbskitYaiTNvO+rdHfJmNl0B0rWSqQFQsfV7zVeciuR/FMukeazK5w24IDC8EDY8YO8ci6BcmgSxiyjuRxd7H3ASsNBBPl8C8Hnwl2cvBqMJPPXdeFkAHnyocpYeQLAITGAPYIaXckKNND7AGS9xtBb4shDgppfwuliAUwHuklGcBbEvgi1jWwmfHaNxpTFkB2N3dTe7QX41m6lFVOcgNb3qV667ew+mOMk62VnKqtZJDR+rw+UyCfpNAIGG/m/h9CUKhOBWBKAG/STAgCfoTBPwmfr+JYUj6BgL09gXp6QvS1hHhYH8VvX0BWtrLqKseYMPKVtYvb6W8NJZ7gJph6ekLcMcDC/nEe1/C0D9xmlQ2DcFrQdgXgNXR3O01I0ZKaQLO/LKvCCGqgS8C3wVOAUFH/Nm8ar/PRgvAsaW/vx8om+hhaCYB2VzBakyP2ta7r+JmsKrFsFVLYEKxILiWSaVgdarVTy3U7JW9G/AbzGrqZ1ZTP9AyJi7eREKw91ANO3c3ce8j85g7o4sNK1tZvaSdUDBHbJMmKz//7WI2rW5hVnNP1vUBYc/Z62bbOsvtBgVaAh3LX8K+fuKkW6ic68PNAvVyDdskM3qT15V6jfmUz14WQtUymO8MIV6oM4eoMYmqRTCZ4Zy/JdAU6pjTC0L7DVPJAs5epim5XumvzITTvgyXrBvzp1j+MmcOUeY/VkiWg0n/rQqM8JwPy/k1E4gBlNj/fhzYIoSolFI6WaiL7fcj4zWgKSsAa2pqSKlIpdEMi1fMnbp+rOLevISgI9pMdQoxm0CWRA4v4ae6r8cjKcPnkyxfeIblC88wFDV4ZV89O3dN4xf3L+Kqzce4YvOxohRpNyWc6yqh5XQpLe1ltJ2bzolTcxAC5s3sZN7MLubN6KS6cqgIRzVxvLKvnuMtFbz/hj052xrujdn6PFIh6Ewp51wdcSRBTE+B6FCIa1gtIZJQ3JLuQ5wbi+e0G951XChekXfuNG0eSSqFCEF1Ojl1akY/lovdGYtX3T1VOLq/EQETeo2Mun3OuVGFn3dcpFfCjBNDmJ40NBYCcLKWgRFCfAFL5B3Cqsi0Dfgc8H27yX8DnwJ+KIT4Kyw38deAJ4GdGR2OEVNWAJaUlKAFoEYzeQgFTTaubGPjyjZOnwlz98ML+Puvb+X6Kw6ycUVrylzO3kgJXb1BWk6X0dJe5gq+lvZSwqE4TfV9NDf0Mru5m0vWHiOREBw+UcXzuxv5+W8WE/CbtiC0RGFzYy++82SWlf5BP7fft5gP3LRbz2ykycDsg8RDZdDhx/+m7NZhTdGoAL4JTMeqA3gI+Ly9DCllixDiSqzEj2eBTuC3wJ+NVwIITGEBqNFkw7F6qfMOq0xUxqvTv2oBUcfllpfIKHgrclr8JkPWbkPtAL//zl0cOl7J3Q8v4M4HF7J+RSurF7dTUTZEuCSOENDaXsopW+C1nrb+7feZTKvvY1pDL7Ond7N5zSmm1fcRCSczH3sGGigPdwMwf5blgZESTp+NcOh4JYeOV/HYzpl0dYeYPb3LshDO7GTOjC7Cocnnmu7tD/C9X6xk5eJ2Fs7pLGjbkVoCVStbsoC0JCCka1GKeWSR53INR6VlFUstBK1u65AtcSR7O9V17IwhP8GsWhTdoshKyRu8rGb5WAJd6372Lqy5gKXrinXIcMkqFvyhOysBCL21C19jclvnewq4Ra3TLX+eGdQex+jVvuhJIJJJW9xSSvlp4NM52rwIXDE+I8rO1BWAsd3ArIkehWYSkXazyDMrcKLEkiPWTOm4bzx+dLPE901m4acyb2YXf/KB52k/G+a5XU38+pH59A0E6B/0I6WgsbaPpoY+mut7Wb+sjWkNvSNOJBECGmv7aaztZ8uaFsASVodPVHLoeCW/fXwux1vKqa8ZYN7MTtYvb2PB7M4iHu3IONlWxm0/W8Wapae54aqDI+4neV2kx24515ZaLsapUmkogjAqbPHoESuofo7a2chBW9CoIi6BSKldmF6uRRVwyXheZ7ndp+fMIWoGcnZR493eeSBLd6PmLNIyjBA0VVe5EsNnZQFnxgAmBbkz1qTr1+w2oN8g8r6zGOUesX0ews/TBexZM1GtWTq6uEsvBCDOrxjAScfUFYAajea8ob5mgDdfdpg3X3Y4d+MiUhaJsXJRBysXWbVZ4wnB8ZZyHnhiLk+91JwhANvPhnlxTwOvH60mYQqkFAQCCdYvb2PtstME/MV1zb64p4Gf3beEt79pPxtX6oKmmuwkTgWsEjPlF1howAV2OOONFoAaTRYmozUsFdVt5+AU981nBpLJbPmbrPh9krkzuonGDDavaUdKS/S9vLeBF/Y0cq6rhDVLT3PJhpPWHNFIegeCPP3SNO54YBFL55+hqb6PafV9NNb1UVc9MKIYw2jM4IEn5vDMK9P4g5tfZOa04sV0OVnCar1AtXC06w513Z9OIoSw57ZOdw2bbjvbCudmrNvH5Mx8oxaKlkbGfN9uNq9j5SLdFesmY7jWJ+x26ZZBLzItfdldv0lrmfM35M+rf5cslkB1PmHVcmYIMz1BRvkNcM93imXQt7CfoUfLocUg0JzdQu5l+RtpAecxKfysKSpaAGo05zGq2y7f2TlS22gKY2DQx4Ej1QwM+fnRXcspCcVZvqCDG686wII5nVkF3frlbXScC3PgSDWtHRGefKGZto5SunpC1FUP0FTXR5MtCpvq+mio7XcTORyReeRkJUdOVnL4RCWt7aUsnHOOP//9Z8esdqJ7rUgnRiy9cLQ6pZzjQvQLQUCITNewdGaccNylDumxhQnlGk5dlxxbegmZpDs63VWshnLkG+unkktQuuWZbNFqKpnNDp7xdNIpzSNdF7uXgAoIEzO10LbqinWncktZFgSjKsHQy6WEpp9LP7Ycwk8Vv8ntHJd99ngZn5IF7NXPaNAu4NGhBaBGo9EUgN9v8q4376O+pp/pjb2URfITYHXVA9RVD6Qti8YMTp+J0NpRSmt7KS+/1sD9HaV0nAtTWT5EVfkQp9pLCQUTzJnezZzpXaxf3srMaT0601dTECVL+uh/poLexyqIbO3GON/v/pM4CeR84Xy/BDQaDanWGo/lNtrqN3oCfskl608Wpa9gwGRGUy8zmtLnpEwkBB3nwpzrLmFafS+V5eNfsipXEfKkZce22NnWGD+CAMk6czF7u6BQpit0rXWk9ZdMLnCsaqlZvulu42RLrwQVxSLoHsHIlIOa4KAWrc7IRnZdvPnvw6vyQHIquASmSLjnQrUUZhR+tj9XrOvBEJK+nRUM7Y0Qmj1AyfwBfHMHMPzelr9ADkufVzKIoXyf2iU8+dACUKO5AMi4WavLNecVPp+ksa6fxrr+iR5KMpzAyTx33aFK8XHXlSjSRYy7nRMT6Cx3/pFeBia1H7CyhZ34wGTB5ZEJQi9yuSdVV3NCEamZ2cXDP3gls4WFsp05THatPRMIJlIkMoRisgh2umBLFV7V6zupXNtJz3OV9B0oo+tIGEwwSkwC9VHCc/uoWNKDEUxupwq5DDyE3di7gOX5NhPIpGPqCsDACqB7okeh0RQVLfg0401SiDgCxK416XVvduLnnJg/19KkCMGU9kGpWKEUi3dGPJoiCEeLKizV/amCMMNYpiS2OLfeQJZkETNHnKIhTOvltPcSfmq/TjsDajZ1UrOpE4DoGT+9e8sZPB6ma0cNnY/VEpnfx/RrT2EYyfhHVeQmjy0/C+Cnlz4w7HGNhMk6E8j5wtQVgBqNRqPRTHGCtXFqLj4HWMkhQy0BWu5s5tjtM5nznuMTO7hcaAvgqNACUKPRaDQFo86a4yAwMDBIKNYtdVYatYSRZ5awJCUO0VmYnunqWqXUWUtGSIaLOXUsaXhY35Si1xnbizheOMeSYWmz8YsEiERKmRfV/ZyOaiHMRaA5wez3H+PoD2dz5skami5pV45BKZHjYRn0eVlDNZOGKS0Ajab9AJitiyZ4JBqNRnN+kJxtQ512TS05lO6O9e7PKT+C0j4popxZQ5IlYuz4Q3f6M0dspM9ekjE9mrPPPH2Haj+qiEoo5WHUBJmk4FM6zkMIepeskfgwh535I62fEYjhQGWc5stbOfVIE9WLO4nUDyVXCg/Huhyd6C4YOWqdP+WZsgFDicTkm89To9FoNJrJQM2qTiLT+zl0xxzMySq0pJyY1wXClLUA9vQUr3K+RqPRTFW8XMHJ9U6ihOPaTS8Hk2EpzEgGkdZEzZB581Wshu7cv2qyiDOWkRaCVl3NKUOz9pNu8XNbqVZND0ugOYy7VC307BMJDJFIzousWCHVmUEy+sth90k9R/NvPMKrty3h8K9ms+gdh9OPRWWyWAY1eTNlBWAsNjbV8zUajWYqoLqCk1MLOiIv+wwVjhBUYwIzxJwrumSW6eTSN1VnBlEFYaE4LuIMd6rSnzpriVd5mpxC0EH6s5RyckrGOOV4LN9nxrR4HjF+ag3EfEWwgYQALHnX6+z5v0Uc/vVM5r75GAFDmX7PHbtHR17CsBhcOMa4CWHKuoDjce/YC41Go9FoNBCpH2LhjYfoPFzBK99ZSm9LeKKH5CKknJDXhcKUtQCmxgDqZBCNRqMZGRlFjoVhWQMzXH8eCRIqrrUsxVymuIWNjDYefeQgV3HiDMuiipKVrNYn9EwGUT4nq/rFk5ZVxaXruMyFSCBFwi3EnTETSEY27ugwMKmb3UXFx3Zz4J657P3ZAqoXdDL3muNp08k5FsiRWhxHxAUkxiaCKSsADcPg8OHDzJ07d6KHotFoNBcMhv1fZrxb9qnkvDRYYhhxlpxlQnVD5icICp2VwqssjM8tWZOctQSSrmGkLb/sY3WnaXM/O7GKKQWipdfsItZniYnMkgWcHOvwbu+ER2a0ekwq4ZIYq965n45DFRy4by4vfWs58990jJqFXekNM2IWdQzgZGXKCsDy8nIeeOABPvaxj030UDQajeaCwytG0EsImop486UlfjhCKUuCSCpuTN7YWIbUfk11NxkWPluMuULQFnruHMEJpX2KBdCNK7QTW1zhlgARzxCGKuqcwA65kkRUVAtj47xO6j/5Invvn8eBX8+hbFofi284RDBiH5tHDGPRkTCWxsWpwJQVgGVlZRw8eJC2tjYaGxsnejgajUaj0ZwXGAYsvvYI09e3sueuBTz/rZWEKodoWHGGpnXtaa7hsUJwYcXjTQRTVgAKIbjmmmv4yle+whVXXMG2bdsI61hAjUajKSoZ81O7VjInu9Vp52GaEqTHA0IWS6DDOAsCj/I0rhvVtsIl1PF6WAINKTNcv8ksX6upKSQI6enqTSgzhHjhVQ4mV8ye028AKGmMsuUjr9DbXsLhHTM4+UwTx3c0U1rfT/P6NmoWdRL06Zq7k5UpKwABrrzySpYsWcL999/P3/3d37Ft2zYuv/xyIhM9MI1Go7lAcQShM4uGkSMm0ExZkJQsihC0URMeEjn0oOoOzdVexZ0pRKSPz3ENO8IvKC0RFBX2CBUhaLgJHzJjOrmMWECRQKTMIKLWCTQ8dHRmcsjwwixf161PSEoaY1TfuBeA1oO1HHt2Ggd+Oxdxv6RqZjezN5+EBXl1VxjaAjgqprQABGhububWW2/l9OnTPPjgg3zhC19g86oFXLXlGBVl0Ykenkaj0Wg05w2187qonddFzDRo211Hy4v1vPSzZfzpPX/KLbfcwurVq4u3My0AR0VedQCFENuEEHcJIY4KIaQQ4v9lafMJIcSrQoh+IUSLEOIHQohhg+uEEP8shNgrhOgVQnQKIZ4QQlyjtGkUQvw6pc+SlHX/Y4/nX5RtZtjLL8/n+AAaGhq4+eab+fznP08i9EG++K1rOXKyIt/NNRqNRlMAPrtcjIHwdv9iuYZ9QiSTQnCKTVvFpFNfmfsY/lVoe69XcjwSHxJDWJa4ICZBTAwhMYQ9h2/aZ/slTHzCxMDMskxiIAmQIEDCbpN8BUU87eVsp74CIp71ZWDtV13ubJer/+Q2CftlfQ754sxa3cqlt77EVX/0DEuXLuVb3/oW//Zv/0Z/f/+orx83CWQiXhcI+RaCLgP2AH8OnFRXCiHeAfwX8BVgGfAOYC3w4xz97gH+AFgNbAaeAO4RQqxLafMPwMvAG7G+8k8rfQwCfySEmJ3nsQxLTU0N73rXu7j55pv53q+uob/shWJ0q9FoNJpR4iUE3fUeQtCzvxztVYGZS3B6CUFX1LkvS7wlRZNJQJgEUwSUI/iCwnqpgtDr5WyXKhKHe7nCTlmeFJzZ+8/YjysIrWNyxm1gEgzG+fCHP8znP/95Ojo6+Ku/+itaWlry/p40Y0NeAlBKeZ+U8vNSyp9hCS6VS4BXpJTfkVIekVI+CXwDS9QN1+8PpJQPSSkPSin3Sin/AugFLk1pVg3sllLuAvbbn1PZgSUQv5TPseTLmjVrWLt2Ld/+9reJxoo/YUrfgJ/jLeVpFuxd++o421nivZFGo9FoNOcpM2fO5B//8R+ZMWMGX/ziF2lvbx9Vf3omkNFRrBjAJ4CP2i7XR4EG4F3Avfl2IITwA+/DsjY+nrLqi8C9QogfAvuANyibSuBPgUeFEF+RUu4c4TFkcNNNN/GjH/2Ib/7y49xyyy3U1tYCI88SlhIOHa/kyRdmsGt/HaXhGKYpWLesjXA4zqPPziSeEFy0spXNa04xo6m3WIei0Wg05y2Oi9hJCPF5FIB2vHOOdc4pJp3LKphrvbcJIHsyilqn0PUauokuao8pM4l4zSKSkizjEwnv2Uls1LmC80XNHlaLZmcUw3ZGpyStRO0MZ7U/v9/Prbfeyl//9V/T0tJCfX19QeNL4wISYxNBUQSglPIXQogq4D6s7HA/8Bvgg7m2FUJcD/wUCAPdwE1SStfvKqV8SQgxC6gH2qTM/MallI8LIe4C/g24fLTH42AYBrfccgv33Xcf//RP/8RFF13ENddcQ/kIysUcOFLFLx9YRDTm4+J1J3nbG/dTGo5xsq2MF15tZN+hGv74A88TCiR4bOcMvvXTNUTCMTatbmHjyhbKS2PFOiyNRqM5b/AhXCGnxgpmCEIPIVgo+UqmjKxk96M9Dq+p69zMXmfc1puPhDuLiJMdnZyFJDkTiJGR05uZ5evgEyMrw+KVBex5btxjtFoEnQznLKV5vvGNb9DY2MiqVatGNDZNcSiKABRCXIwVq/dnwGPAdOBfgB8A786x+SPAGizX7juBHwohrlZEYAJozdHP54BXhRA3ADkD96SU9PT05GoGwGWXXcb69et54okn+Nd//VdWrVrF2rVrqTMacm7b3RvkoR2zOd5axtVbj7J0/lmEAEk1vYNQWQlXbO0BerCMn3DFlh4u29zD0RMVvLJ/Ov/6vZXUV/czs7mH8tIoM5t6mNbQl9fYx4q+wZoJ3f+Fjj6/Y4s+v2NHvufWmSHElI4Yst9dESdT2ma39KgSxVQE4EgpNOhH3Z8jWOPSWW9bMJXPjjRLnT83uc4ahZTpbRNDtR5jKG6okizwLCZsW6AzvV3ymKyDdu63u3btoquri09+8pN534O9RqgtgKOjWC7gLwN3Sim/bn/eJYToAnYIIf5OSrnXa0MpZR/wuv3xOSHEaqxkk/cUMgAp5X4hxLeAfwauzdVeCEF5eXne/ZeXl/POd76TK6+8kieffJLvfve7VFXdwJYtW1jR9Akqy5MlY2JxwetHq3n1QB3P7Wri0g0neM+bjxAMFPYHtWrRaVYtep1ozODw8UoOnaji7LkAD++YzvWXH2LL2lMF9VdsysOnJ3T/Fzr6/I4t+vyOHYWc25i0LEVxd8ozZbo15LDzAjttsm9bGKqEynA1e+C1X2fcMacuoCIEVXdqAuEKqIQiBJ3lPsBf0ubpAi7U5atSqAvYbSfTp7Bz2l05Z5/bJh6Pc/vtt7N27VrmzJkzqnEi0QJwlBRLAEbI9hBkUagN3gBGmgnxBeAW4KMj3D4ntbW13HDDDVx//fXs2bOHp556irvv/PzjIAAAKIlJREFUvhafz8esWbMQ0Uc4cLSaafW9LF/YwZ/9/rPUVWfLm8mfYMBk8bxzLJ53DoD5szrZuatpwgWgRqPRFBtHdKWKKi9XboZrWG02QoHgJfxyuaCdMTsSLOFu5w7IHmf2GUSsdelN0+IDAWGXkPHUxDlmAMmFKvgMJb4xcz5k59x7xCym8OMf/xghBDfffPOoxpjceXG6KTZCiPcBnwXmASHgCHCblPI/s7RdBjwHhKSU41qbOa+dCSHKSNbxDgJNQog1QK+U8nXgLuDzQohnSbqAvwLsxsrcRQhxEfBD4PeklM/aNQI/iRU32ApUAe8FrsIqI1MwUsp2IcQ/AX8zku0LwTAMVqxYwYoVK5BScvbsWY4dO0Y8vpFbfn8pkd51uTsZIbObu7n9viXE4gYB/yT9C9BoNJphMHPcvZNxfd5tMpJDlOSPXOYH1XKnCr/h6hNm3b8iBF3hqsQE+hQhmLE8deyKEDTtsiuOIMzA43x5Wu5yCL5cU8O54/BMXrFoaWnhueee48Mf/jB+/wU/B0U7VljcPqzKKduA/xZCJKSUX3MaCSEiwO3Aw+ThuSw2+X4LG7Bi9Rw+Zr8exUq6+BLWw85fAt8EzgHbgc/b8XtgWQkX2+8AUazYv48AdcBZYBfwZinlb0dyMDZfAT4BzBxFHwUhhKC2ttbNEgYwxzCBt7ZqkNnTu3jyhelcftHxsduRRqPRaDRF4Jvf/CYzZsxg3briGUcma0kWKeWDyqLDQogbgSuBr6Us/zpWFZWnmawCUEq5nWGepWyR9yWGqcWn9iGlPAe8Nc9xevX5wSzLBoFZo+m3GBh2prDDSEvHePGWKw7y9f9dS29fgGu3Hcbnm5x/CBqNRjMcavyeT8mCRZgZ6zIY4c9fguz95rL8qXhZAk1FoATsbpNzDisuYch0CyuWwIRdTFr1fybnCs7uolUtfe7Yc1j8vLZzLIo+xUWdYQkEtm/fTkdHB1/84hez9jViJqkATEUIIYCNwMXAP6Ys/z17+UZyJ8uOCRe8HXayYIygdMxwzGjq5fMfe4b/vWcp//DfW9iy9hSbVrVQVTFUlP41Go1mIkgopVIMjIy4NkONL8tIXLBFZJaEEihc+OUqJ6PGIpruZ3eAynjtcalCELzjA5UuMoVZfoLQC0fI5XIJewvKdCHoxApGo1HuuOMOrrjiCqqqqvIay3lAnRAitebwbVLK21IbCCEqsWZOC2Ll7nxBSvlf9rqlwL8DV0gpB0SeyUbFRgvA85iKsigff8/LHD1VwY4XpvOlb25GCElTXR+N9X001fXTVNfLwjnnCPgn/5PSZOfXj8zD75Ncs+3wiLYfHPLxwJNzQMKbLz+EvwCrrZTQcS7MvsM1tHaUIqVVHkJK6wfZ+YzyOfVdGFBROkRlufOKUlU+SGX5EKGgjiXVaDTF5zvf+Q6hUIi3ve1txe1YkgyeHH86pJQbcrTpwQpziwBbgS8LIU5iTZH7c+CvpZS7x3SUOdACcJwptiVQCJgzvZs507t57/Wv0d0bpLWjlNaOUto6SnnptQb+954SLr/oOJesP0G4ZGRFQac6dzywkIefns0Vm465y3r7A+w9VMPs5m7qawaG3f6l1+q5/TdLWDLvDAODAb7xkzV86v0vkuvB7+CxSp55uZl9h2uIxQ0Wzz3LjKYefIZECIkQeL4byudEQtDdG6SrJ8Sxlgq6ekLuy+eTligsG6Kqwnpfs/Q0s6d3F+P0aTQZJGQyqcF6z17s2VqWPeEh2dYjIULNiE1xo2bvJ518C0mryScZWckZrkplBhG3PmBmgoi6rYFMs8rltMjZOBZBr6QOL8tfRr9ep8RNZLHL+SBoO1nJ7t27+cM//EMMo9hTqk7uOoBSSpNkibtXhBDVWDObPQQsB74uhHBK5wnAEELEgb+VUhZ1alsvtACcIMYiRlAIqCyPUlkeZfHcc+7yE61l/G7HbP7uaxdz3eWH2LbhRE7hoUmy44Vmnnh+OoYwuf6Kg0RjBv/9k7WcaC0nkRC87y2vDSsAozGDn9yzjI+95yXmz+rClPClb25m3+Ealsw7m3Wbc10hfnrPKo61lHPlpmNcsfkYTXV9Rf3ehqI+du2vo7c/yOCQj+7eED29Qc6cK+G1gzUMRn1aAGqKjir4HJdvwHUdOu+2sEnJdlWFoOm6LbH7UsWNh6vYrlkXU8YyVniVickmBHPZ4n1YosyJwTPcDONcU8ONUvh5tHfJKMEDD/1qAwsWLGDp0qXDjm3ETGIBmAWnxN1JYKWy7q1YZezWAG3jNSAtAKcAM5p6+eDbXqWtI8IP71zOqwfqeP8Ne6goi+beeIoRT4g01+yRExXc/fACls4/S3XlIKFggu3PziQUjPMPf/w4f/PVS1m2oGPYPl/ZV8+s5m7mz+oCrGmh3rD1KA88MSdDAPYP+vntY3N5Zf9CtqzZwwdu2l1wAfF8jvH23yzmxT2NzJvRRW31gOtKDodjlJTEqa8dYHmO49JoNMMjJQwN+ZOzY0iZ8hAnMfwm/gu0lNfOJxYy0B/i4x//+EQPZdwRQnwBeBw4hDU97jas2cq+L6WMYZXIS22/AWC8XcJaAE4Siu0azkZjXT+fuXUnv318Ll/+1ibec91eVi9pH7P9nW/c+bsFPPzULOpqBpg/s5M5M7r49SPzee/1r/HTe5fwJ1e9TjwheOipWXz47bs4dLyK6Y09lIbjw/b77MvT2LS6JW3ZhhWt/Hr7PJ7b1cT6Fa2c6yph1/567n98DisXt/Ox977MtNqTY3KcL73WwKm2Mv7mk0/phwDNuOFY6xwrXkg474ER95mZDKI08LAIOnPzuq5bZfo5x5WrWinNtF5SdiOhqytCe0cZHWfKOdNRTkdHOe1nLC+BYUi7ncjYbuHCVlasPMacue1JS+A44GnJK0I/g/1+XtixiPUX7yMSiWTZqkhMXgtgBVZJvOlYdQAPAZ+3l00atACcZIy1EPT5JNddfoil88/wwzuXs/tAHW9/435KQjo2sP1shPe/dQ8zmnp4ZW8D//frZXz03S9TGo5SWT5EY20/T780jfrqAebM6ObQ8Ur6Boa/eXWcC3PkZCUffucract9PskHbnyVX9y/mJ/cs5RwSZx5Mzv51PtfZHpjLz0DueeZHilPPj+dbRtPUFEWxZTQ1x+guzdEV0/Qeu+14gK7e4N094ToGwhYx1/XR2NtPw21VoJRVeVgcpJ7jSYHXnF8Y7qPAgWhK1IVQei4RaMJOHu2jNMdZbR3lNHeYYm9M2fLKCmJUVvXQ21tD/VNnSxZcZy62h4ipUOu1U+NFezvC7Jnzwwee3Qp9/56HUuXn2DZymPUN4x96EWyjMvIRJS6nc8Vz4L7frmJSOkQGy85MLpBDsfEJoEMi5Ty08CnC2j/P8D/jNV4vNACcJIy1nUE583s4i8++gy/fGAR/3TbJn7vxleZN7OrqPs4n4gnBPG4Qf9ggOaGPpobDnPllqMEAyb3bp/HknlnMSU8uGMO77rGmtp6zowuhob8HG8pZ+a0Hrp6gtz/xFx6eoOsXNzOhhWt/PbxuWzbeDxrlu2C2Z187iPP0DcQoCwSG7djDZfE+em9S7j7oQX09AUJheJUlkWpKLMygyvLhqiv6WfBrHNUlEUpjcTo7A7R1lFK25kIr+yr5/SZCP2DAepr+mms7aOhtt8ViI11/YSC+oHiQuOpl6bxwquNrFrczrrlbTkt3yqmhLOdYU6dLuPUaStJbSjqwzSt+W9N08pWT5gG0sRdlvqetjxjO4FMWyZImFZmvBASw0hPlLKSpOzPKUlVqcsNQyKQICSmadDVU0JVxQB1dT3U1/WyaH479ZsOUV3TQyiUPB/qXMBO3b+kZdEiEImyesMh1m44xJmOMnbvnsUdt2+hvGKAzZfsZdbcpIfGS6ipsX9eM354UagQ9LmiOPv6Q6/Xc+pELX/+559jzszvFzQWzfiiBeAUpiSU4Oa3vMbLe+v59u2ruHjdySlZVPpsV4jv/WIVZaVRNq9Ozq/sxN6d7SphWn0v37l9FVXlgyyyE2wMAW+69DBf+9E6VizqYM/rtWxec4qVi9t5YucMHnhyDj29Qf7uUzs89y0E4yr+AD767leIxgx6+4KUl0Xzmk5wWn0fS+enxysODvk4fSZC25kIbR2l7NpXz+/OlHL6TITScEwRhda7thqen3R2h/j5b5bw7jfv5dUDtdzz8AI2rT7FGy4+mhFGICV09wY52VZGS3sZLadLOXW6jJb2UkrDcaY19NLc0MvieWcJh+KuGDMMS3BZ/5a2aLNfIrlOGNLNgk9bl7LecLcFgURKgSktV67zbykFcVMiTexlgoSdWCptEZmQpiUkbRFZWdmP3296uohHQ21dL5devoeLt+1h/2vT2f7gSkIlMTZdso9Zc0+fN4l7D923ltnz25gzZ84Y70lmsehqCkELwPOEsXQNr17SztwZXfz47mX8x/c38Hs3vUpjbX/R9zMZefVALT++exlXbTnGVVuOZv2RHYr6uPvhBVy28QRvvfpAWptL1p9kxcIOnn55Gm+85DBNddZ527iylVcP1GJKg0iBlpLxIBgwqakaHFUfJaEEs5p7mNXck7bclNDZVeIKw1xWw/mzOqmp1AXMJzPlpVGkhLXL2ti0uoXOniC/2zGHf/zGZjavbqGhtt+27JXR2dPIwIAl8qY19DF7ejeb15yiuaF3AstQSXxY0fjJossyYz5iNYtYzQ52oxg9XMRuezfb18lktvt316ePLmkxFGDAwuWnmL/0FAf2Tuexh1YQDMbZdMleZs87nfcRF4vMLOHs6xMITp2opr+3hCtv3T4+g5u8MYDnBUJO0RO4YcMGuXPnztwNJyljIQSlhMd3zuC+R+dx3eUHuWT9Sc+nzp6BBsrD4/9jVCwSpuDeR+bx7K5p3Pq2XW6GbjZ2vNBMaSQ2rgkz5/v59SLVanj6TCmt7aXsP1JNY10/N71hP3NnjE/ZmQv1/I4lX/7WJt73lj3MThH8nT1BHn5qNgODfqY19NHc0EtlZZimGu/fjslMvoIws11+SSTJfkhrl+xHEYNYv8v7X2vm2R2LGRwIsGjZIHMWvkr99HOkltZzXMGFuoAdfIqY9YrxSybQKGNH8NMfXEos5uPmD29n8cxTjAYhxPPDFVuuDDbKrU3vHdU+Rspvj3912LGdL2gLoMZFCNi28QSL5p7lB79awe4Dddz8ltcuuEzRrp4g379jJX6fyec+8gzlpcO7YLeuG90PmSZJNqthIiF4/tVGvn37alYsaueGKw+Ou1tck5vmhl5OnS5LE4BV5VHe9sb0QP+egYbzUvxNVoSAxctOsXDpKc52lPH6/hU89sAq+vpCzFvUwrwlLTTPOuNdoHmcME1oOVnDW9/11MQORJM3WgCep4xlkkhTXT+f/dBz/ObRefzTbZt4z3WvsWrxhVETbt/han7wqxVcuv4Eb7r0MEUvTq8pGJ9PctGqVlYuaufe7fP54jc285YrDrJ57SkdLziJaG7o5VRb2UQPY0zJP4s4e4FpdQ7ifF3Erj1RSLeotaGUnkEI6up7KS87wuaLWzl7ppTX9zXzzCNL6e6KMGdRK/MXn2La7DP4fHLEySCuYc/D0ufFqZPV1sxU88fRsj5FPZjFQgvAC4Rixwj6fZK3XHmQZQs6UsrFHDhvsztPtpWy/ZlZvPp6HR+4cTeL553LvZFmXAmXJHjHNfvZtLqFn923mMefn8GCWecIBRNEYz6GotYrFvdRGo5RWT5EdYU1l3FVhTW/cWk4pq1PY0RzQy97D82a6GGMK56CMM8ZR0YiCFPFoNUHaX3EkPiQ1Nf2Ur91PxdtPUBXZ4QD+6bxwpOLOHt3ObMXtDF3cQsz5rYjRjkPfL5Zwq0naggE4+P70KYF4KjQAlAzLPNndfEXH3uGX96/2C4Xs3vc4rRGiynhtddrefjpWbS0l3HphhP85cef1u7FSc7MaT185kM7ee31Wlray4jGDCrLhwgFE4SCCfw+k97+AF09IQ6dqKKz26pb2NkTIh632laVD1FZMURV+SBVKQKxqmKQygsspMELU0L/QIDevgDdfSF6+wL09AUzXrG4j8ZaK35vwexzzJvZlVVENzdaLmDN5KOyqp91Fx1k3UUHOdsT4fC+Jl55dh6P/Hotsxa0se6S/VRUj21i3+m2KkpLR5dYphlftAC8wBiLbOFwKMH7b9jDS6/Vc9vPVnPNtsOsWzF5b6LRmMEzL09j+7Oz8PtMrth8jPXLWwmM8klYM34YApYvPMPyhWcK2m4oatDZU0JXtyUIu3pCdHSGef1YtSsUe/qC1NaECAXO0Fjbx8I551g05xx11QOTznp46HglUkJJKE6kJE5JKM5g1E9Pb6aQU199/QFCwQTlpVH3VVYapaI0yoymHirKopRFovh9krYzEU61lfF/9y4lHjfYuLKVi1a1uHNcSwkPPzVr2DmvpwKuRTDPAtMuBVgEkxY/7GVOH9YCv4CASNYWdHy2TqZxXUU/dRsPsWbDYfr7Qux+eTZ3//Bilq49yuotr+O3y1sl7DF6zRHsJJU4Y3PnHvawBEaHAvgDiaLNMJIbqS2Ao0QLwAuUsYgRXLO0nRlNvXz9f9fQ1RPlLVdMrtpUnT1BHnt2JjtenM7cGV28+9q9LJxzblKNUTO2hIKmVXdwmDJGpgmtZ6cTG+rh5OkyDhyp5r5H5yEELJxticGFc85SVz3x1oz/+P5GIuEolWVRBob8DA76CYXilJfGKC8dct8ryqJMb+zNEHv+PGt6zp5uWfXfevXrHG8p59lXpvHv39tIQ00/tdUD9PQF6e0P8ke3PD+Wh3veMNIZR5LtvQWhmxnsxuDZPdiLowhrO8VFnCkIJSVlA1x88T5WrTzG9t+t4JffuYytV73K7IVt7hhUIai6fB0h6HNEqhsjmN6uobGTllNzmTcjfdrLMUNi/TFrRowWgJqCqKse4LMf2sn37riUH921jPe95bW8bzJjxfGWch5+ehavHqhjw8pWPnPrczTUTm1LhcYbw8ASTnXdzJ7ezda1p5ASTp+NcOBINXsP1XD3w/Opqhhi06oWNqxsnbCwgcs3HaO8NMqbLjkyLvsTAjdL+6Y3HGDvoRp6+4P4fCbL5p+ZlDUtNbkprxjgmpt2cvxwPY8+uJI9L81m89V7qKzpK9o+Vqw+yjM7FtPR0UFdXV3R+h0WbQEcFVoAThGK6Roui8R4/w17+Nm9jfz8N4t57/V7R93nSHj1QC0PPjmHM51hLrvoOO+8Zp++QWlGhBC4lsNL1p/ENGHf4RqeeXka926fx8I559i8poXlCzrGbKacV/bV86sHFzB3Rjdve+N+yiIxFs05y6PPzhw3AZiKzycLdsFPVYppEVTdw6pF0C8EASEyXMRqselsFsGF89qY+eF2XnxuPvf8aCtbrtzDopUn7O1G5yqpre6nvHyAu+++mw996EOj6kszPmgBOMUolms4EDD54E27+cv/2Mbb37TfnTZtvPjdjtk89twM3nr166xZcnrKTV+nGVsMA5bOP8vS+WcZGPTx4p5GHtoxi5/cs5RtG49z1ZZjRcuIP9tZws9/u5jTZyK84037efX1Ov7ff11su3BNWjvK6O0f3/miNaNjVIIwV7wgdvkYxUWcLDadffYRRxBG/CYXbznA/AVt3Hn7Zvo6w2y+dC8xkb0mlldMny9lPA4r1xxh5zNVWduPCdoCOCq0AJzijMYyGC5JsGjOOX714EJuvPoAoeDYi0Ap4d7t83jxtUY+fetOqiv0FGKasSVckmDrulNsXXeKtjMR7nt0Hn//9S28+bJDbF7Tgs82xcTigt0H6nn25WkcOVlBWWmMCjs+r6LMeY+6y8pKozz9UjO/2zGbKzYf40PveIWA37K6ve2N+znbWUL/YIBozEekRIu/85nCBOHw8YJ+DAIYGRZCQzg1BdXZR7ILwqb6bm75wKPc8YvN9HSWcvV1L+L3m8RkemxfxrGoU8GlfL546wGeemI5r7zyCqtWrcq6ffGQKQGJmpGgBaBmVHzgpt389N4l/O1XL+GS9Se5ZtuhMcu2lRJ++cAiXj9azZ98YGfOGTw0mmLTWNvPrW/bzdGTFfzqdwt55JlZXL3lKEdOVvLCngZmNPaycVUL77x2LwODAbp7g3T3hujuDdLZHeJYSwU9vUF3+dwZXfzZ7z9HXXV6zKrfJ+04Vh3Lqhk7SsuGeM/NT3Dv3ev55U+2csM7nsE/ijAav99k1qxZ3H///eMgADWjRQtADTByS2AkHOdD79hNx7kSbr9vCb/47djFBD63q4l9h2v49Ad3EinRsX6aiWP29G7++PeeZ/f+Oh5/fgbzZ3XyFx99hprKFIt05RDTGydujJrJy7AWwRzxgj4hrJeHi9jdKk+LoC+Y4G1vf5aHH17Oz354GW9/9w6qqvsyYgJVi6DqMHbGs2nTJu68807GHAky41xpCkELQE0aI40RrKse5NZ37OKfb9vEC3saWLesuNMB9fQF+NWDC/n4e1/S4k8zKRACVi7uYOUFMk2iZuJIE4Q54gUFhtJ++JhBdx8egtCJJ3zjVXuorhjkjp9t4QO3PkoglN3D4lNdwPZ+m6dbc6aXlXdz++23Mzg4SElJidchFwftAh4VeiZUTdEIhxLc+rbd3H7fEs50FvcP/44HFrFxZWvaRPQajUajKR4bNx5i7rzT3H3nhhGX2KuoqAAgHh+HB3UpJ+Z1gaAFoGZYjKb9GVbB4Zg9vZurtx7hf+5YQSJRnArMe16v4dDxKq67/GBR+tNoNJrJiqH85xPpLycLOPlS21su4oAwrJedNOKzC0g72znrnfZWv3DN1buJx/w89dgygkLgE6S/7H6cl4oj/CKRyLieN03haAGoyYtCROCVW45REopz76PzRr3fWFzws/uW8q5r945LlrFGo9FMJlSBZ2QIQpGXIHSFXw5BGPTDu9/+HLtfncne15oJIAhkEXyG8nLo77dm4TGMMZYXUlozgUzE6wJBC0BN0TEE3PLWPTzz8jT2Ha4eVV9CQEXZELsP1I2p5f3Q8UoOHqt0Q0pa2ktpPxseux1qNBrNJKW0NMq73v4M9/12NW1tFQVt61j+tAt48qMFoCZvHHew0bQfo+43w7atKIvy/hv28KM7l9PTFxjxPv0+ySdvfpHjLRX88v5FY/K39/Leer7z81X85J5l/OjO5dz98Hy++oP1/Pv3NvLsK03F36FGo9GMEMey5+BYApPrLYue2t7NHs5hEXQ+z2ru4c1v3M3tv9jE0GDQ0+Ln9Ofg91u5pWfO6FlkJjtaAGpGTK74wKXzz7JxZSs/vmv5qJK1wqEEn7z5RQ6dqOSOBxYWXQRuf2Ym737zXj730Wfo6w/Q1lHKX378af7g5hf51YMLOXKisCdgjUajGWtyxwrm5xpWBaHz8iFYt+IUK5a08Ms7NmJIX1rMoCr8UvH5fLS3t4/5OZCmOSGvCwVdBkYzaoarIXj9FQf5yv9sYPszs7hy87ER7yNSEucPbn6Rr/1oHXf9bgFvvfp1PH57CsKUcORkJWWRgwQDJp+8+SV3XUVZlHdeu4/bbl9NPEtCiyGgJBQnXBKnomyImU09zJzWw6zmbj1DiUajGRUm2YWGaf/nkBhhLbzMWoRKP/aD9jVX7uN//u8ifvfwMt589R43DjDhMVMIWFbAsbcAXlju2IlAC0DNmOLzST74tl3823cvYsGsc8waRRmX0nCcT73fEoHGI5K3XHFw1CLQEPDBt+3m27ev5pa3vsryhek/WuuWnWblonaGopl/KqYpGBjyMzjko7O7hOMt5Tz5wnR+cs9SFs45x41XH6CuenB0A9RoNJoJxGdI3vu2F/j/vncJzY1drFl5Muc2wWCQzs7OsR2YRNcBHCVaAGqKhlcR6brqQd557T6+f8dKPveRZygJJUa8j7JIjE+9/wX+60fr8RmS6y4/NKoxA6xe0k55aZTv/HwV119xkK1rT6WtD/glAX/2oqgVZVEAZjf3sHqJ5fKIxgweemo2//Kdi7jpDQfYsqZl1GPUaDTnH15WPJV8rHhOAee4NIlJ79/Q/PeZn3gykZSEo3zik1/iq1/9KvOWfopZs2YNu83g4CB1dXV59a+ZOLQA1IwZqa7h9cvb2Huohtt/s4Tfu/HVUfVbXhrjj255nq/+cD2GIbl22+FRj3XezC7++APP842frOFcVwlvvuzQiK2LwYDJtdsOU1/Tz4t7GrUA1GjOMwopezVsP3m2K+RGHO/pIVxePpLhjIoq4L3vfS+33XYbn/vc5yj3GENvby+xWIy1a9eO/aD0VHCjQieBaMaNd7xpH0dPVRQls9YSgS/wzMvTePVAbRFGB421/Xz2Q8+x5/Va/r8fr6XldOmo+vP5tHtCo9FcOKxdu5ZNmzbx7W9/m0QiuxXyhRdeIBgMjnkhaAlIU07I60JBWwA1Y47zNB1qXcSH3r6Lr/1oHXOmd9FQOzCqfivKorzp0sM8tnNGRuzeSCkvjfGZW3fy+PMz+OoP17N2WRsrFnYwe3o3ZZHsbuBsHD5RwW8fm8vS+boUgmZyUiwrV0a/PT0YE2Ch0owP1113Hd/85jf5xS9+wbvf/e6M9Y8//jgzZ86cgJFpCkULQM24YTTtZ2YTXNf5KN+/ez6fueV/CPhH9zS1fnkbv3pwIWc7S6ipKk7Chc8nufyi42xY0cr2Z2by0FOzOdZSQbgkRnlplFAgQSiUoCQYJxRMEAom8PtMegcC9PSG6O4N0tkT4qY3HGD98raijEkzMrxEjhYpGs3IMAyDW2+9lX/5l3/hySef5OKLL3bX9fb2cvLkST772c+O/UCknLQuYCHE+4DPAvOAEHAEuE1K+Z/2+luBW4CVQBDYDfyjlHL4ArtFRgtAzbizbds2XnvtNR56ajbXXHpkVH0FAyZrl57mxdcauGrLyMvMZKMsEuP6K6wkE1PCmXNh+voDDEV9DEb9DEV91r+H/CQSBjMre6goO0N5aZTmht5RJbtoNBrNZCUcDvPxj3+cf//3f6e5uZm5c+cCcPfdd1NaWsr8+fPHZRyT2B3bDvwDsA8YBLYB/y2ESEgpvwZcCdwJ/BnQA3wYuFsIcamU8unxGqQWgJpxRwjBFVdcwV13dfPmd/551vqBhbBk3lmefqm56AIwFUNAfc0A9TWjc1uPFWPlztNoNJpsNDY2csstt/CNb3yDa6+9lssuu4ydO3dyySWXjN8gJqkFUEr5oLLosBDiRizh9zUp5S3K+s8JId4C3AhoAai5sJk3bx4tLS0MDAwQ9igfo+IlchaX9fK/v/5bZP3/4fP5ij7WiUC7KDUazWRn5cqVfPazn+XHP/4xjz/+OENDQ1x//fUTPaxJhRBCABuBi4F/9GhjAKVA5/iNDIScopW0hRA7J3oMGo1Go9FostIhpbzGa6UQ4rfARBUbLMFy7TrcJqW8LbWBEKISOIkV4+cDviCl/PtsnQkhPg/8BbBcSnlibIacZb9TVQBqNBqNRqPRjAW2VW8eEAG2Al8G/lRK+V2l3QeBbwBvl1LeN65j1AJQo9FoNBqNZuywrXx/LKVsSln2UeCrwLuklPeM95h0IWiNRqPRaDSascXAch0DIIT4I+A/gbdNhPgDnQSi0Wg0Go1GUzSEEF8AHgcOAQGsMjCfA75vr/9TLJfwh4AXhRCOVTAqpTw7buPULmCNRqPRaDSa4iCE+ArwFmA6VrLIIeB7wDellAkhxBFgdpZNH5VSXj5e49Qu4CmGEOKIEEJmeb2ape0yIUSfECKeZd1fCSGOCyF2CiHW28vCQoghIcTHlbZ/bu/j95XlfymE6BJCnDeW6FznTwhxtRBihxCiQwgxKIR4XQjx90KIQI5+t2fpc7vSplEI8WshRIsQ4gdCiBJ7+YeFEDEhRLnSfo/9fUSU5fuFEF8vygkZR4p17qfqtQt5ncNbhRAPCyHa7eN7UghxbR796ut3GIp13qfytXs+IaX8tJRygZQyLKWsllKul1J+XUqZsNfPkVKKLK/Lx3OcWgBOPTYC01JeC4AB4Kepjewf3duBh9UOhBBbsQpW3gT8K/ADACnlAPAUcJWyyZXAMY/lj0opMwTmJCbX+esB/gu4HFgM/CnwceCf8uj7J0rfb1PW/wPwMvBGrLnQP20vfwgrnGOb01BYLoVFwGng0pTl04GF9jbnG6M+91P82oXc59CZoeAau+0TWDMUbM6jb339ejPq866vXU2x0U8AUwwpZXvqZyHER7BiFL6rNP061o/Q04D6JFoNtAC7gC6sApYODwF/LIQQUkppW18uAf4E+GLK8hBWavzni3Jg40Su8yelfAZ4JqXJUSHEZVg/urkYkFK2DrO+GnhESrlLCLHf/oyU8ogQ4hDWD/29dtsrsW62z9rL77eXXwWYwPY8xjOpKNK5n7LXLuR1DkczQ4G+fj0o0nmf0teupvhoC6DmY8A9UspTzgIhxO9hPYV+2mOb+7Ge4PuAF0n/MXkIqAXW2J83Af1YT6thYIW9fIv9+Xx7klfJOH+pCCGWAG8GHsmjr5tsF9BeIcT/J4SoUdZ/Efg3IUQMeB/wlZR1D5H+pH8llvX2kSzLXxzPQOMxZCTnXl+76eQ6h4XMUKCv3/wZyXnX166muEgp9WuKvoANWD8ob0pZthRrIusV9ucPAnGP7euBEmWZH8sV91n7898Ct9v/vherDhLA3wOtE30Oin3+UtadAIbs9d8CfDn6+gjwBqwf6rcBrwHPAwGlnQ9owk7gSln+HizLSL39+RCW+GkA4kCNvfwo8M8Tfe4m+txP9Ws31zlMafN5LGvTjBx96et3nM67vnb1q1ivCR+Afk3glw/ftn9onWzwELAb+FhKmw/iIQCH6fde4D77348CH7f//afA3fa/nwT+d6LPQTHPn7JuLrAceD/WdEBfKLDv+fZN4i15tm+wb6DvAuYAMaDMXrfbvikvtPt8w0Sfu8l67qfKtZvrHNrrP4gVp/bmEfStr99xPu9T6drVr+K8JnwA+jVBXzxUAL3AX6Qsm2P/wMZTXomUZX+ZZ9+fsfuuxLLELLKXr8d6qq0EosCHJvo8FPP8DdP2vfb5Ky1wH+3YT/R5tn8Fy+L1YWBHyvKvYcV0fsz+PsITff4m67mfCtduPucQ+KgtQvIScB596Ot3HM/7VLl29at4Lx0DOHV5P9Yk1d9PWXYSWIkVR+K8/hZLBK7BenLNh4ew4lc+A7RLKffby1/Eesr/DFYA9Pkch5Lt/HlhYLm+gvl2LoSYiRXT01LAmJw4Kid+yuGRlOU7pJU1eD4zlud+Kly7MMw5FEWYoUBfv56M5XmfKteuplhMtALVr4l5YWXY3Z5Huw9SuAtYYJVv6AZ+qKy7y17++kSfg7E4f8Bngeuw3FULsGKbTgJ3pbS5CNgLXGR/ng/8HVbizWysMhkvYrmJIgWM6Xosa203cGXK8losEd8N/PVEn7uJPPd59H3BX7s5zuGfYrlfb8GK1XNeNSlt9PU7Aec9j76nxLWrX8V7aQvgFMSuLbUKy91SdKSUEuupvZzMOoLO8vP2KTTH+Qtg1eh6Cesm+NdY7qv3prSJYNWpcwrcRoErgN8A+4FvYpW/uFhK2V/A0B7FcncGgR3OQinlGazSEef1eYeinPthudCvXch5Dj+FlVDwQyzrnfO6I6WNvn5HQBHO+7BMhWtXU1z0VHAajUaj0Wg0UwxtAdRoNBqNRqOZYmgBqNFoNBqNRjPF0AJQo9FoNBqNZoqhBaBGo9FoNBrNFEMLQI1Go9FoNJophhaAGo1Go9FoNFMMLQA1Go1Go9FophhaAGo0Go1Go9FMMbQA1Gg0Go1Go5li/P+LidGHkKNyFgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot the hazards, showing 50-year return period hazard\n", "haz_present.plot_rp_intensity(return_periods=(50,), smooth=False, vmin=32, vmax=50)\n", "haz_future.plot_rp_intensity(return_periods=(50,), smooth=False, vmin=32, vmax=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Download LitPop economic exposure data\n", "\n", "The Data API provides us with economic exposure data:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:35:52,700 - climada.entity.exposures.base - INFO - Reading /Users/chrisfairless/climada/data/exposures/litpop/LitPop_150arcsec_HTI/v1/LitPop_150arcsec_HTI.hdf5\n" ] } ], "source": [ "exp_present = client.get_litpop(country='Haiti')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For 2080's economic exposure we will use a crude approximation, assuming the country will experience 2% economic growth annually:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import copy\n", "\n", "exp_future = copy.deepcopy(exp_present)\n", "exp_future.ref_year = future_year\n", "n_years = exp_future.ref_year - exp_present.ref_year + 1\n", "growth_rate = 1.02\n", "growth = growth_rate ** n_years\n", "exp_future.gdf['value'] = exp_future.gdf['value'] * growth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the current and future exposures. The default scale is logarithmic and we see how the values of exposures grow, though not by a full order of magnitude." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-10-20T15:09:07.000153Z", "start_time": "2020-10-20T15:09:05.634377Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:35:52,895 - climada.util.coordinates - INFO - Raster from resolution 0.04166666666666785 to 0.04166666666666785.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/pyproj/crs/crs.py:1256: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems\n", " return self._crs.to_proj4(version=version)\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:825: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(multi_line_string) > 1:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:877: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.\n", " for line in multi_line_string:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:944: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(p_mline) > 0:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:35:59,536 - climada.util.coordinates - INFO - Raster from resolution 0.04166666666666785 to 0.04166666666666785.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/pyproj/crs/crs.py:1256: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems\n", " return self._crs.to_proj4(version=version)\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:825: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(multi_line_string) > 1:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:877: ShapelyDeprecationWarning: Iteration over multi-part geometries is deprecated and will be removed in Shapely 2.0. Use the `geoms` property to access the constituent parts of a multi-part geometry.\n", " for line in multi_line_string:\n", "/Users/chrisfairless/opt/anaconda3/envs/climada_env/lib/python3.8/site-packages/cartopy/crs.py:944: ShapelyDeprecationWarning: __len__ for multi-part geometries is deprecated and will be removed in Shapely 2.0. Check the length of the `geoms` property instead to get the number of parts of a multi-part geometry.\n", " if len(p_mline) > 0:\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "exp_present.plot_raster(fill=False, vmin=4, vmax=11)\n", "exp_future.plot_raster(fill=False, vmin=4, vmax=11)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then need to map the exposure points to the hazard centroids. (Note: we could have done this earlier before we copied the exposure, but not all analyses will have present and future exposures and hazards on the same sets of points.)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:15,405 - climada.entity.exposures.base - INFO - Matching 1329 exposures with 1329 centroids.\n", "2022-03-03 05:36:15,421 - climada.util.coordinates - INFO - No exact centroid match found. Reprojecting coordinates to nearest neighbor closer than the threshold = 100\n", "2022-03-03 05:36:16,026 - climada.entity.exposures.base - INFO - Matching 1329 exposures with 1329 centroids.\n", "2022-03-03 05:36:16,042 - climada.util.coordinates - INFO - No exact centroid match found. Reprojecting coordinates to nearest neighbor closer than the threshold = 100\n" ] } ], "source": [ "# This would be done automatically in Impact calculations\n", "# but it's better to do it explicitly before the calculation\n", "exp_present.assign_centroids(haz_present, distance='approx')\n", "exp_future.assign_centroids(haz_future, distance='approx')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define impact function \n", "\n", "In this analysis we'll use the popular sigmoid curve impact function from Emanuel (2011)." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-10-20T15:09:51.503229Z", "start_time": "2020-10-20T15:09:51.499628Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,069 - climada.entity.impact_funcs.base - WARNING - For intensity = 0, mdd != 0 or paa != 0. Consider shifting the origin of the intensity scale. In impact.calc the impact is always null at intensity = 0.\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from climada.entity import ImpactFuncSet, ImpfTropCyclone\n", "\n", "impf_tc = ImpfTropCyclone.from_emanuel_usa()\n", "\n", "# add the impact function to an Impact function set\n", "impf_set = ImpactFuncSet([impf_tc])\n", "impf_set.check()\n", "impf_tc.plot()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Rename the impact function column in the exposures and assign hazard IDs\n", "\n", "# This is more out of politeness, since if there's only one impact function\n", "# and one `impf_` column, CLIMADA can figure it out\n", "exp_present.gdf.rename(columns={\"impf_\": \"impf_TC\"}, inplace=True)\n", "exp_present.gdf['impf_TC'] = 1\n", "exp_future.gdf.rename(columns={\"impf_\": \"impf_TC\"}, inplace=True)\n", "exp_future.gdf['impf_TC'] = 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define adaptation measures\n", "\n", "For adaptation measures we'll follow some of the examples from the __[Adaptation MeasureSet tutorial](climada_entity_MeasureSet.ipynb)__. See the tutorial to understand how measures work in more depth.\n", "\n", "These numbers are completely made up. We implement one measure that reduces the (effective) wind speed by 5 m/s and one that completely protects 10% of exposed assets." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from climada.entity.measures import Measure, MeasureSet\n", "\n", "meas_1 = Measure(\n", " haz_type='TC',\n", " name='Measure A',\n", " color_rgb=np.array([0.8, 0.1, 0.1]),\n", " cost=5000000000,\n", " hazard_inten_imp=(1, -5), # Decrease wind speeds by 5 m/s\n", " risk_transf_cover=0,\n", ")\n", "\n", "meas_2 = Measure(\n", " haz_type='TC',\n", " name='Measure B',\n", " color_rgb=np.array([0.1, 0.1, 0.8]),\n", " cost=220000000,\n", " paa_impact=(1, -0.10), # 10% fewer assets affected\n", ")\n", "\n", "# gather all measures\n", "meas_set = MeasureSet(measure_list=[meas_1, meas_2])\n", "meas_set.check()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define discount rates\n", "\n", "We'll define two discount rate objects so that we can compare their effect on a cost-benefit. First, a zero discount rate, where preventing loss in 2080 is valued the same a preventing it this year. Second, the often-used 1.4% per year." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "from climada.entity import DiscRates\n", "\n", "year_range = np.arange(exp_present.ref_year, exp_future.ref_year + 1)\n", "annual_discount_zero = np.zeros(n_years)\n", "annual_discount_stern = np.ones(n_years) * 0.014\n", "\n", "discount_zero = DiscRates(year_range, annual_discount_zero)\n", "discount_stern = DiscRates(year_range, annual_discount_stern)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create Entity objects\n", "\n", "Now we have everything we need to create Entities. Remember, Entity is a container class for grouping __[Exposures](climada_entity_Exposures.ipynb)__, __[Impact Functions](climada_entity_ImpactFuncSet.ipynb)__, __[Discount Rates](climada_entity_DiscRates.ipynb)__ and __[Measures](climada_entity_MeasureSet.ipynb)__.\n", "\n", "In this first example we'll set discount rates to zero." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "from climada.entity import Entity\n", "\n", "entity_present = Entity(exposures=exp_present, disc_rates=discount_zero,\n", " impact_func_set=impf_set, measure_set=meas_set)\n", "entity_future = Entity(exposures=exp_future, disc_rates=discount_zero,\n", " impact_func_set=impf_set, measure_set=meas_set)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cost-benefit #1: adaptation measures, no climate change or economic growth\n", "\n", "We are now ready to perform our first cost-benefit analysis. We'll start with the simplest and build up complexity.\n", "\n", "The first analysis only looks at solely at the effects of introducing adaptation measures. It assumes no climate change and no economic growth. It evaluates the benefit over the period 2018 (present) to 2080 (future) and sets the discount rate to zero." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,236 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,238 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,258 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,259 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,295 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,296 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,332 - climada.engine.cost_benefit - INFO - Computing cost benefit from years 2018 to 2080.\n", "\n", "Measure Cost (USD bn) Benefit (USD bn) Benefit/Cost\n", "--------- --------------- ------------------ --------------\n", "Measure A 5 4.74132 0.948265\n", "Measure B 0.22 1.10613 5.02787\n", "\n", "-------------------- --------- --------\n", "Total climate risk: 11.0613 (USD bn)\n", "Average annual risk: 0.175576 (USD bn)\n", "Residual risk: 5.21385 (USD bn)\n", "-------------------- --------- --------\n", "Net Present Values\n" ] } ], "source": [ "from climada.engine import CostBenefit\n", "from climada.engine.cost_benefit import risk_aai_agg\n", "\n", "costben_measures_only = CostBenefit()\n", "costben_measures_only.calc(haz_present, entity_present, haz_future=None, ent_future=None,\n", " future_year=future_year, risk_func=risk_aai_agg, imp_time_depen=None, save_imp=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's take a moment to look through these results.\n", "\n", "The first table gives us a breakdown of cost-benefits by measure. We can see that, the Benefit/Cost for measure A is very just under 1, meaning that the damage prevented is slightly less than the cost of preventing it (according to the model). In comparison, the benefit of Measure B is 5 times the cost. (Note that Benefit/Cost is the inverse of Cost/Benefit: larger numbers are better).\n", "\n", "Let's explain the three values in the second table:\n", "- **Total climate risk:** The impact expected over the entire study period. With no changes in future hazard or exposure and no discount rates we can check that it is 63 times the next term.\n", "- **Average annual risk:** The average annual risk without any measures implemented in the future scenario (which here is the same as the present day scenario)\n", "- **Residual risk:** The remaining risk that hasn't been offset by the adaptation measures. Here it is the total climate risk minus the total of the 'Benefit' column of the table above it.\n", "\n", "#### Combining measures\n", "\n", "We can also combine the measures to give the cost-benefit of implementing everything:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Measure Cost (USD bn) Benefit (USD bn) Benefit/Cost\n", "----------------- --------------- ------------------ --------------\n", "Combined measures 5.22 5.84344 1.11943\n", "\n", "-------------------- --------- --------\n", "Total climate risk: 11.0613 (USD bn)\n", "Average annual risk: 0.175576 (USD bn)\n", "Residual risk: 5.21787 (USD bn)\n", "-------------------- --------- --------\n", "Net Present Values\n" ] } ], "source": [ "combined_costben = costben_measures_only.combine_measures(['Measure A', 'Measure B'],\n", " 'Combined measures',\n", " new_color=np.array([0.1, 0.8, 0.8]),\n", " disc_rates=discount_zero)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note: the method of combining measures is naive. The offset impacts are summed over the event set while not letting the impact of any single event drop below zero (it therefore doesn't work in analyses where impacts can go below zero).\n", "\n", "#### Plotting benefits by return period \n", "\n", "Finally, we can see how effective the adaptation measures are at different return periods. The `plot_event_view` plot shows the difference in losses at different return periods in the future scenario (here the same as the present scenario) with the losses offset by the adaptation measures shaded." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = costben_measures_only.plot_event_view((25, 50, 100, 250))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that the Measure A, which reduces wind speeds by 5 m/s, is able to completely stop impacts at the 25 year return period, and that at 250 years – the strongest events – the measures have greatly reduced effectiveness.\n", "\n", "### Cost-benefit #2: adaptation measures with climate change and economic growth\n", "\n", "Our next analysis will introduce a change in future scenarios. We'll add `hazard_future` and `entity_future` into the mixture. We'll set `imp_time_depen` set to 1, meaning we interpolate linearly between the present and future hazard and exposures in our summation over years. We'll still keep the discount rate at zero." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2020-10-20T09:59:49.351752Z", "start_time": "2020-10-20T09:59:49.340451Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,478 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,480 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,498 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,500 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,534 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,535 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,572 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,574 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:16,592 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,593 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:16,615 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,616 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:16,637 - climada.engine.cost_benefit - INFO - Computing cost benefit from years 2018 to 2080.\n", "\n", "Measure Cost (USD bn) Benefit (USD bn) Benefit/Cost\n", "--------- --------------- ------------------ --------------\n", "Measure A 5 13.9728 2.79457\n", "Measure B 0.22 3.65387 16.6085\n", "\n", "-------------------- --------- --------\n", "Total climate risk: 36.5387 (USD bn)\n", "Average annual risk: 0.984382 (USD bn)\n", "Residual risk: 18.912 (USD bn)\n", "-------------------- --------- --------\n", "Net Present Values\n" ] } ], "source": [ "costben = CostBenefit()\n", "costben.calc(haz_present, entity_present, haz_future=haz_future, ent_future=entity_future,\n", " future_year=future_year, risk_func=risk_aai_agg, imp_time_depen=1, save_imp=True)" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-10-20T15:09:51.515128Z", "start_time": "2020-10-20T15:09:51.505127Z" } }, "source": [ "What has changed by adding climate change and population growth?\n", "\n", "- With growing exposure and more extreme events we see about a 3-fold increase in total climate risk. Remember this is the average annual impacts summed over every year between the present and the future. The average annual risk has grown even more, by over a factor of 5. This represents the unadapted annual impacts in the future scenario.\n", "- Greater impacts means that our adaptation measures offset more in absolute terms. The same adaptation measures create larger benefits (and therefore cost-benefits), which have increased by about a factor of three. Measure A is now clearly worth implementing in this cost-benefit analysis, whereas it wasn't before.\n", "- We also see that the residual risk, i.e. the impacts over the analysis period that are not offset by the adaptation measures, is much larger.\n", "\n", "**Exercise**: try changing the value of the `imp_time_depen` parameter in the calculation above. Values < 1 front-load the changes over time, and values > 1 back-load the changes. How does it affect the values in the printout above? What changes? What doesn't?\n", "\n", "#### Waterfall plots \n", "\n", "Now that there are more additional components in the analysis, we can use more of the CostBenefit class's visualisation methods. The waterfall plot is the clearest way to break down the components of risk:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,647 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,649 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,665 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,667 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:16,695 - climada.engine.cost_benefit - INFO - Risk at 2018: 1.756e+08\n", "2022-03-03 05:36:16,696 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,699 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,714 - climada.engine.cost_benefit - INFO - Risk with development at 2080: 6.113e+08\n", "2022-03-03 05:36:16,715 - climada.engine.cost_benefit - INFO - Risk with development and climate change at 2080: 9.844e+08\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# define this as a function because we'll use it again later\n", "def waterfall():\n", " return costben.plot_waterfall(haz_present, entity_present, haz_future, entity_future,\n", " risk_func=risk_aai_agg)\n", "\n", "ax = waterfall()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The waterfall plot breaks down the average annual risk faced in 2080 (this is \\\\$0.984 bn, as printed out during the cost-benefit calculation).\n", "\n", "We see that the baseline 2018 risk in blue. The 'Economic development' bar in orange shows the change in annual impacts resulting from growth in exposure, and the 'Climate change' bar in green shows the additional change from changes in the hazard.\n", "\n", "In this analysis, then, we see that changes in annual losses are likely to be driven by both economic development and climate change, in roughly equal amounts.\n", "\n", "The `plot_arrow_averted` graph builds on this, adding an indication of the risk averted to the waterfall plot. It's slightly awkward to use, which is why we wrote a function to create the waterfall plot earlier:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,803 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,804 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,820 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,821 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:16,849 - climada.engine.cost_benefit - INFO - Risk at 2018: 1.756e+08\n", "2022-03-03 05:36:16,850 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,851 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,866 - climada.engine.cost_benefit - INFO - Risk with development at 2080: 6.113e+08\n", "2022-03-03 05:36:16,867 - climada.engine.cost_benefit - INFO - Risk with development and climate change at 2080: 9.844e+08\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "costben.plot_arrow_averted(axis = waterfall(), in_meas_names=['Measure A', 'Measure B'], accumulate=True, combine=False,\n", " risk_func=risk_aai_agg, disc_rates=None, imp_time_depen=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise**: In addition, the `plot_waterfall_accumulated` method is available to produce a waterfall plot from a different perspective. Instead of showing a breakdown of the impacts from the year of our future scenario, it accumulates the components of risk over the whole analysis period. That is, it sums the components over every year between 2018 (when the entire risk is the baseline risk) to 2080 (when the breakdown is the same as the plot above). The final plot has the same four components, but gives them different weightings. Look up the function in the `climada.engine.cost_benefit` module and try it out. Then try changing the value of the `imp_time_depen` parameter, and see how front-loading or back-loading the year-on-year changes gives different totals and different breakdowns of risk." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cost-benefit #3: Adding discount rates\n", "\n", "Next we will introduce discount rates to the calculations. Recall that discount rates are factors used to convert future impacts into present-day impacts, based on the idea that an impact in the future is less significant than the same impact today.\n", "\n", "We will work with the annual 1.4% discount that we defined earlier in the `discount_stern` object. Let's define two new Entity objects with these discount rates:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2020-10-20T09:59:49.355854Z", "start_time": "2020-10-20T09:59:49.353112Z" } }, "outputs": [], "source": [ "entity_present_disc = Entity(exposures=exp_present, disc_rates=discount_stern,\n", " impact_func_set=impf_set, measure_set=meas_set)\n", "entity_future_disc = Entity(exposures=exp_future, disc_rates=discount_stern,\n", " impact_func_set=impf_set, measure_set=meas_set)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And then re-calculate the cost-benefits:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2020-10-20T09:59:50.233588Z", "start_time": "2020-10-20T09:59:49.357688Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-03-03 05:36:16,969 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,971 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:16,988 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:16,989 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:17,024 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:17,026 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 42779 events.\n", "2022-03-03 05:36:17,062 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:17,064 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:17,079 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:17,081 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:17,100 - climada.engine.impact - INFO - Exposures matching centroids found in centr_TC\n", "2022-03-03 05:36:17,101 - climada.engine.impact - INFO - Calculating damage for 1329 assets (>0) and 16808 events.\n", "2022-03-03 05:36:17,123 - climada.engine.cost_benefit - INFO - Computing cost benefit from years 2018 to 2080.\n", "\n", "Measure Cost (USD bn) Benefit (USD bn) Benefit/Cost\n", "--------- --------------- ------------------ --------------\n", "Measure A 5 8.46661 1.69332\n", "Measure B 0.22 2.20086 10.0039\n", "\n", "-------------------- --------- --------\n", "Total climate risk: 22.0086 (USD bn)\n", "Average annual risk: 0.984382 (USD bn)\n", "Residual risk: 11.3412 (USD bn)\n", "-------------------- --------- --------\n", "Net Present Values\n", "(0, 0)\n" ] } ], "source": [ "costben_disc = CostBenefit()\n", "costben_disc.calc(haz_present, entity_present_disc, haz_future=haz_future, ent_future=entity_future_disc,\n", " future_year=future_year, risk_func=risk_aai_agg, imp_time_depen=1, save_imp=True)\n", "print(costben_disc.imp_meas_future['no measure']['impact'].imp_mat.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How has this changed the numbers?\n", "\n", "- The benefits have shrunk, since the values of the impacts prevented in the future have decreased. This means the benefit/cost ratios have decreased too. Nevertheless Measure A still has benefits that outweigh the costs.\n", "- The total climate risk has decreased. The risk is the sum of impacts (with no adaptation measures) over the whole analysis period. Since future impacts are all smaller than they were without discount rates, the sum has decreased.\n", "- The average annual risk, the unadapted annual risk in the future scenario, is the same (although it would be less if it was converted to a net present value).\n", "- The residual risk has also shrunk. It has been discounted in the same way as the offset impacts.\n", "\n", "Take together we see a slightly more optimistic outlook for climate change, as the future risks are smaller, but less attractive investments in offsetting these risks, since the benefit/cost ratio has shrunk.\n", "\n", "#### Additional data exploration\n", "\n", "With scenarios like this, the `CostBenefit.plot_cost_benefit` method shows a 2-dimensional representation of the cost-benefits." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = costben_disc.plot_cost_benefit()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The x-axis here is damage averted over the 2018-2080 analysis period. The y-axis is the Benefit/Cost ratio (so higher is better). This means that the area of each shape represents the total benefit of the measure. Furthermore, any measure which goes above 1 on the y-axis gives a larger benefit than the cost of its implementation.\n", "\n", "The average annual impact and the total climate risk are marked on the x-axis. The width between the last measure bar and the the total climate risk is the residual risk." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise**: How sensitive are cost benefit analyses to different parameters? Let's say an adaptation measure is a 'good investment' if the benefit is greater than the cost over the analysis period, and it's a 'bad investment' if the benefit is less than the cost.\n", "- Using the hazards and exposures from this tutorial, can you design an impact measure that is a good investment when no discount rates are applied, and a bad investment when a 1.4% (or higher) discount rate is applied? \n", "- Create hazard and exposure objects for the same growth and climate change scenarios as this tutorial, but for the year 2040. Can you design an impact measure that is a good investment when evaluated out to 2080, but a bad investment when evaluated to 2040?\n", "- Using the hazards and exposures from this tutorial, can you design an impact measure that is a good investment when `imp_time_depen` = 1/4 (change happens closer to 2018) and a bad investment when `imp_time_depen` = 4 (change happens closer to 2080)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally we can use some of the functionality of the objects stored within the CostBenefit object. Remember that many impact calculations have been performed to get here, and if `imp_mat` was set to True, the data has been stored (or ... it will be. I found a bug that stops it being saved while writing the tutorial.)\n", "\n", "So this means that you can, for example, plot maps of return period hazard with different adaptation measures applied (or with all applied, using `combine_measures`).\n", "\n", "Another thing to explore is exceedance curves, which are stored. Here are the curves for the present, future unadapted and future adapted scenarios:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Measure Cost (USD bn) Benefit (USD bn) Benefit/Cost\n", "----------------- --------------- ------------------ --------------\n", "Combined measures 5.22 10.6616 2.04245\n", "\n", "-------------------- --------- --------\n", "Total climate risk: 22.0086 (USD bn)\n", "Average annual risk: 0.984382 (USD bn)\n", "Residual risk: 11.347 (USD bn)\n", "-------------------- --------- --------\n", "Net Present Values\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAEWCAYAAABsY4yMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAABIgUlEQVR4nO3dd3hU1dbA4d9KgRBC74QSepESIAFpigJiFwXFgpeIotjQ+ym2q6Je9VqwXPVasGHvIIoNW0BUakB6B+mdkJCE1P39sU+SSUhCApmcmcl6n2eemTl1zUmysmefXcQYg1JKqcAT5HYASimlvEMTvFJKBShN8EopFaA0wSulVIDSBK+UUgFKE7xSSgUoTfCqQomIEZG2bseRS0QaicgcEUkWkWfcjkep8hTidgCqfInIFqARkO2xeKox5hZ3IvJ51wP7gZpGO4WoAKMJPjBdYIz5ye0g/ERLYFVxyV1EQowxWRUck9/R6+SbtIqmEhGRV0Tkc4/3T4rIz2IFi8h9IrLRqa5YLCLNne06isiPInJQRNaKyGUex6gqIpNFZKuI7BGRV0Wkmsf6iSKyS0R2isjYQvGcJyJLRCRJRLaJyEMe66Kc6pwxzrH3i8i/PNafULyFzj8VGAPcJSJHRGSIiDwkIp+LyPsikgTEiUgtEXnT+Rw7RORREQn2iGOyE98mEbnZiTvEWb9FRIZ4nPMhEXnf4/2pIvKHiCSKyF8iMshjXbyI/FtEfnc+4ywRqe+xfoDHvttEJE5EYp2fQ4jHdiNEZGkx16CaiDwjIn+LyGERmessGyQi2wttm/dZirhO94lImojU9di+h3NdQp33Y0VktYgcEpEfRKRlUTGpcmSM0UcAPYAtwJBi1oUD64A4YCC2aqKZs24isBzoAAjQHagHVAe2Addgv/H1dPY7xdnveeAroC5QA/ga+I+z7mxgD9DFOc6HgAHaOusHAV2xBY1uzrbDnXVRzravA9WceNKBTicTbxHXZCrwqMf7h4BMYLgTVzXgS+A159gNgQXADc7244E1QHPnGvzqxB1S1M/DOf77zutI4ABwrnOuoc77Bs76eGAj0N6JIx54wlnXAkgGrgBCnc8e7axbBZzjcc7pwB3FfP7/OceNBIKBfkBV52ezvbjfrWKu0y/AOI/tnwZedV4PBzYAnZyfy/3AH27/vQT6w/UAjgkI3gL2AitKse1pQAKQBYwstG4MsN55jHH7c1Xg9dsCHAESPR6ef3S9gYPA38AVHsvXAhcVcbxRwG+Flr0GTMIm1hSgjce6vsBmj5/lEx7r2uOR4Is41/PAc87rKGfbZh7rFwCXn2i8xZxzKscm+Dke7xth/7FU81h2BfCr8/oXYLzHurMofYK/G3ivUDw/5P6+YhPv/R7rbgK+d17fC0wv5jPdDXzgvK4LpAJNitguCEgDuhexbhDHT/BzCq2/DvjFeS3Yf7SnOe+/A64tdO5UoKXbfzOB/PDFOvipwEvAu6XYdiu2NHqn50Lna+IkIAb7x7ZYRL4yxhwq10h913BTTB28MWaBiGzClkQ/9VjVHFtaLKwl0EdEEj2WhQDvAQ2w3woWi0juOsGWBAGaAos99vvb88Ai0gd4AlvCr4ItOX5W6Py7PV6nAhEnEW9pbSt0vFBgl8dnDPLYpmmh7Qt8xuNoCVwqIhd4LAvFfgvIVdbPD/A+sFpEIoDLsP/wdhWxXX0grITjHM+2Qu8/B14UkaZAO+zf3m/OupbAf6VgSyXBfnMoyzVTZeBzCd4YM0dEojyXiUgb7FfJBthf8nHGmDXGmC3O+pxChxkG/GiMOeis/xFbXfCRd6P3fSJyMzaR7gTuAv7jrNoGtAFWFNplGzDbGDO0iGPllgBPMcbsKOJ0u7CJKFeLQus/xP4zP8cYc1REnscmndIoc7xl4HnDdRu2BF/fFH0T8XifMQX7TzBX40LHfs8YM+4EYtyG/TZ2DGPMDhH5E7gYuBp4pZhj7AeOYq/jXyXF7dxzaFD4VIXOmygis7D/VDoBHxmnuO7E+5gx5oPjfC5VjvzlJusU4FZjTC9saf3l42wfScHSxXZnWaUmIu2BR4HR2D/8u0Qk2ln9BvBvEWknVjcRqQfMBNqLyNUiEuo8YkWkkzEmB1tH/pyINHTOESkiw5xjfoq9SdlZRMKx36o81QAOOsm9N3BlGT5OmeMt4+UCwCn5zgKeEZGaIhIkIm1E5HSPzzhBRJqJSB3gnkKHWApc7sQRA4z0WPc+cIGIDHNu1oY5NzeblSK0D4AhInKZiISISD2PnyXYb8B3Ye9xTC/ms+Vgq9GeFZGmTgx9RaQq9l5NmNgb4aHYOvOqpYjrQ+AfwAjnda5XgXtF5BQAsTeuLy3F8dRJ8PkE73zN7Ad85rQEeA1ocrzdilhWmdo4fy22VUjuY7rTquJ94EljzF/GmPXAfcB7zh/0s9hkNQtIAt7E1jsnY+uVL8eW+ncDT5L/x3439ubZPKc1xU/YG58YY77D1qv/4mzzS6E4bwIeEZFk4EEKVhkdz4nGeyL+ga1CWgUcwlZF5P4Ovo6tN/8Lez9oWqF9H8CWkA8BD+OR9Iwx24CLsD+HfdhCyURK8XdpjNmKvTl7B/aeylLsjeZc07HVItONMSklHOpO7M3qhc5xngSCjDGHsT+fN4Ad2BL99uIO4uErbPXMHmNM3rcCY8x059gfO78nK4BzSnE8dRIk/xuU73CqaGYaY7qISE1grTGm2KQutrnbTGPM5877K4BBxpgbnPevAfHGmEpfRaO8y/nd3QyEFlOlU5GxbMS29tE+EZWUz5fgjTFJwObcr3PO1/Hux9ntB+AsEanjfG0+y1mmVKUgIiOw31oLf2tSlYjPJXgR+Qj4E+ggIttF5FrgKuBaEfkLWIn9WotTt7oduBR4TURWAjg3V/+N/dq5EHgk94arUoFOROKxN1ZvdurZVSXlk1U0SimlTp7PleCVUkqVD59qB1+/fn0TFRXldhhKKeU3Fi9evN8YU7iPAuBjCT4qKopFixa5HYZSSvkNESm2J7BW0SilVIDSBK+UUgFKE7xSSgUor9bBi8g/sUOIGmx36GuMMUfLcozMzEy2b9/O0aNl2k0FgLCwMJo1a0ZoaKjboSjll7yW4EUkEpgAdDbGpInIp9jxQaaW5Tjbt2+nRo0aREVF4TFcqwpwxhgOHDjA9u3badWqldvhKOWXvF1FEwJUcwa6CscO/lQmR48epV69eprcKxkRoV69evrNTamT4LUE74wPPhk7Kccu4LAxZlbh7UTkehFZJCKL9u3bV+SxNLlXTvpzV+rkeC3BO4N8XQS0ws56U11ERhfezhgzxRgTY4yJadCgyLb6SikVeEwOHF4NG9+CVU955RTevMk6BDs35z4AEZmGHdf9/RL38kHBwcF07dqVrKwsOnXqxDvvvEN4ePjxdyxH8fHxVKlShX79+lXoeZVS5STjEOyfD/vnwYF59nVmol1XrSl0uhOkfMvc3kzwW4FTnZl80oDBgF92U61WrRpLly4F4KqrruLVV1/l//7v//LWZ2dnExwcXMze5SM+Pp6IiAhN8Er5g5xsOLzSSeR/2qSetMaukyCo1QVaXgb1+0K9U6Fm+3JP7uDFBG+MmS8in2NnuckClmCn3vNrAwcOZNmyZcTHx/Pwww/TpEkTli5dyvLly7nnnnuIj48nPT2dm2++mRtuuIFdu3YxatQokpKSyMrK4pVXXmHgwIHMmjWLSZMmkZ6eTps2bXj77beJiIggKiqKMWPG8PXXX5OZmclnn31GWFgYr776KsHBwbz//vu8+OKLDBw40O1LoZTKdXQfHJifn8wPLICsI3Zd1fo2ibe62j7Xi4XQGhUSllfbwRtjJnHsPJwn7PbbwSlIl5voaHj++dJtm5WVxXfffcfZZ58NwIIFC1ixYgWtWrViypQp1KpVi4ULF5Kenk7//v0566yzmDZtGsOGDeNf//oX2dnZpKamsn//fh599FF++uknqlevzpNPPsmzzz7Lgw8+CED9+vVJSEjg5ZdfZvLkybzxxhuMHz+eiIgI7rzzzvK9AEqpssnJhMRlNpHvd0roRzbadRIMdaKh1Riof6otoUe0BpcaDPjUYGO+Ki0tjejoaMCW4K+99lr++OMPevfunddGe9asWSxbtozPP/8cgMOHD7N+/XpiY2MZO3YsmZmZDB8+nOjoaGbPns2qVavo378/ABkZGfTt2zfvfJdccgkAvXr1Ytq0wlN8KqUqVNqu/ES+fx4cXATZaXZdWGObxNveYBN63V4QUrH350riVwm+tCXt8uZZB++pevXqea+NMbz44osMGzbsmO3mzJnDN998w9VXX83EiROpU6cOQ4cO5aOPip4itmpVOz90cHAwWVmuTuupVOWSnQ6HlnpUtcyDFGewxqBQqNMzP5nXPxXCW7hWOi8Nv0rwvmzYsGG88sornHnmmYSGhrJu3ToiIyPZv38/kZGRjBs3jpSUFBISEvjXv/7FzTffzIYNG2jbti2pqals376d9u3bF3v8GjVqkJSUVIGfSKkAZwykbitY1XIoAXIy7Prw5rZ03uE2+1wnGoLDXA25rDTBl5PrrruOLVu20LNnT4wxNGjQgC+//JL4+HiefvppQkNDiYiI4N1336VBgwZMnTqVK664gvT0dAAeffTREhP8BRdcwMiRI5kxY4beZFXqRGSlwcHFBVu2pDmd64PDoG4MdJjgtGzpA+GR7sZbDnxqTtaYmBhTeMKP1atX06lTJ5ciUm7Tn786IcZAyuaCdeeHloJxqjwjWtsWLfX72qqWOt1tFYwfEpHFxpiYotZpCV4p5f8yj8DBhfnVLQfmwdG9dl1IdajXGzpNzK87D2vobrwVRBO8Usq/GAPJ6wrWnR9ebrv+A9TsAE3OyS+d1zoFgipnqqucn1op5T8yDtuOQ54tWzIO2XWhNW19ebP7bTKv1xuq1nM3Xh+iCV4p5TtyB+Da/2f+zdDDq7FzBoktjTcfkd+JqGZHr3TxDxSa4JVS7kk/YAfdyk3mBxZAptMcuEpdm8hbXA4N+kLdWKhSy914/YwmeKVUxcjJgsMrCrZsSV5n10kQ1O4GUVc5rVtOhRrtfLoTkT/QBF8KucMF5/ryyy+JiooqcttAGNb3oYceOuFxb5YuXcrOnTs599xzy7TfoEGDmDx5MjExRbb2Uv4obY9TMnceBxdCVopdF9bQVrG0vsbp4h8DoRHuxhuANMGXQnFDFRTlRIb1rYjhhivK0qVLWbRoUZkTvPJz2RmQ+FfB0nnKZrtOQqBOD2g9Nr9lS/UoLZ1XAL07cYKioqLYv38/AIsWLWLQoEFs2bKFV199leeee47o6Gh+++034uLi8gYgA4iIsKWU+Ph4zjjjDK688kq6du1KdnY2EydOJDY2lm7duvHaa68dN4bcYwF8/vnnxMXFARAXF8eECRPo168frVu3zjv/kSNHGDx4MD179qRr167MmDEjb//HHnuMDh06MGTIENauXZu3/PXXXyc2Npbu3bszYsQIUlNT884xfvx4Bg4cSPv27Zk5cyYZGRk8+OCDfPLJJ0RHR/PJJ5+QkpLC2LFjiY2NpUePHnnnTEtL4/LLL6dbt26MGjWKtLS0E/kxKLek7oCtX0DCnfDjAPi8FvzQGxZPgL2zoW5P6DEZhs6FS5Pg7AUQ8wJEXQERrTS5VxD/KsEvvt32RitPdaKh1/MlbuI5mmSrVq2YPn16kdtFRUUdM6zvm2++WexxSzPccO5olWW1a9cu5s6dy5o1a7jwwgsZOXIkYWFhTJ8+nZo1a7J//35OPfVULrzwQhISEvj4449ZsmQJWVlZ9OzZk169egF2ZMtx48YBcP/99/Pmm29y6623ArBlyxZmz57Nxo0bOeOMM9iwYQOPPPIIixYt4qWXXgLgvvvu48wzz+Stt94iMTGR3r17M2TIEF577TXCw8NZtmwZy5Yto2fPnif0OVUFyD4KB5cUbNmSut2uC6pqR1Bsd1N+y5bwZu7Gq/L4V4J3SVmqaMqiNMMNn2iCHz58OEFBQXTu3Jk9e/YAdsTL++67jzlz5hAUFMSOHTvYs2cPv/32GxdffHHeNIQXXnhh3nFWrFjB/fffT2JiIkeOHCkwWuZll11GUFAQ7dq1o3Xr1qxZs+aYOGbNmsVXX33F5MmTATh69Chbt25lzpw5TJgwAYBu3brRrVu3E/qcqpwZY0dPzJtW7k84tMSOgQ62aqXBgPxu/nW6Q3BVV0NWxfNagheRDsAnHotaAw8aY54/4YMep6RdkUJCQsjJsT3njh49WqrtjDFkZGTkrSvtcMPFEY+vuYVjyB1yOPfYAB988AH79u1j8eLFhIaGEhUVlbefFPOVOS4uji+//JLu3bszdepU4uPjizx/cccwxvDFF1/QoUOHEuNXLslKsQNwedadH91t1wVXs7MPdfw/J6H3gWpN3I1XlYnX6uCNMWuNMdHGmGigF5AKFF234YeioqJYvHgxAF988UXe8ho1apCcnFzkdjNmzCAzM7PI4+UON5y7ft26daSk2BYHHTt2LHKfRo0asXr1anJycoqtNvJ0+PBhGjZsSGhoKL/++it//23HuT7ttNOYPn06aWlpJCcn8/XXX+ftk5ycTJMmTcjMzOSDDz4ocLzPPvuMnJwcNm7cyKZNm+jQocMxn3/YsGG8+OKLef9klixZknfO3OOtWLGCZcuWHTd+dZKMgeQNsPk9WHgzfNcLPqsFP50OS++GxBXQeCjE/A/OToBLD8OQ2RD9BDQfrsndD1VUFc1gYKMx5u8KOp/XTZo0iWuvvZbHH3+cPn365C0vPKzvuHHjuOiii+jduzeDBw8uUGr3VNxww/v376e4ET+feOIJzj//fJo3b06XLl04cuRIiTFfddVVXHDBBcTExBAdHZ33j6Nnz56MGjWK6OhoWrZsWWAo4n//+9/06dOHli1b0rVr1wLJu0OHDpx++uns2bOHV199lbCwMM444wyeeOIJoqOjuffee3nggQe4/fbb6datG8YYoqKimDlzJjfeeCPXXHMN3bp1Izo6mt69e5f62qtSykx2uvjPy68/Tz9g14VE2C7+ne/JHx43rL678apyVyHDBYvIW0CCMealItZdD1wP0KJFi165pcpclX242JkzZ7Jp06a8+mpfERcXx/nnn8/IkSO9ep7K/vMvNZMDSWsLJvPEFdgu/kDNTvk3QeufCjU7Q1BgNM2t7FwdLlhEqgAXAvcWtd4YMwWYAnY8eG/H42/OP/98t0NQvijjEOxf4NGyZT5kJtp1obVtEm8+Ir/uvEptF4NVbqmIKppzsKX3PRVwLlVBpk6d6nYIlUdONhxe6dEr9E9IclosSRDU6gItL8tv2VKzvQ7ApYCKSfBXAEXPLq2UOtbRfXBgvsfwuAsgy7m/UrW+TeStrrbP9WIhtIa78Sqf5dUELyLhwFDgBm+eRym/lZMJicvzk/n+eXBkg10nwVC7O7Qak19/HtFae4GqUvNqgjfGpAI6+r5SudJ2eyTzP+HgIsh2hmkIa2yTeNtx9rluLwgJdzde5de0J6tS3pKdYXuBerZsSXFaiQWFQp2e0PaG/HlCw1to6VyVK03wpeDPwwXHx8czefJkZs6cWeZ9ExMT+fDDD7npppvKtN/JDDfst4yx47McmAf7nGR+MAFy0u368Oa2VN7hNlt3XrcHBIe5G7MKeJrgS6GyDhecmJjIyy+/XOYEXylkpdku/p4tW9J22nXBYXZ88w635nciCo90N15VKWlbqhPkC8MF33jjjcTExHDKKacwadKkvOXff/89HTt2ZMCAAUybNi1v+YIFC+jXrx89evSgX79+ecMCT506lYsuuoizzz6bDh068PDDDwNwzz33sHHjRqKjo5k4cSIATz/9dF6MnucsbrjhgGAMHNkEWz6ERbfC97HwWU34aSAsmWirYRoOgl4vwrCFdnjcob9Bj6eh+SWa3JVr/KoEf/v3t7N099JyPWZ042ieP/v5Erfx1eGCH3vsMerWrUt2djaDBw9m2bJltG/fnnHjxvHLL7/Qtm1bRo0albd9x44dmTNnDiEhIfz000/cd999eePo5MYSHh5ObGws5513Hk888QQrVqzI+/Yya9Ys1q9fz4IFCzDGcOGFFzJnzhyqV69e7HDDfi9lG8wdaZsqAoRUh3q9odPE/LrzsIbuxqhUMfwqwbvFV4cL/vTTT5kyZQpZWVns2rWLVatWkZOTQ6tWrWjXrh0Ao0ePZsqUKXnHHDNmDOvXr0dECgx8NnToUOrVsw2eLrnkEubOncvw4cMLnG/WrFnMmjWLHj16AHYCkfXr15OcnFzscMN+be9cmDvCVsf0fB4aDYJap0CQ/tko/+BXv6nHK2lXJLeHC968eTOTJ09m4cKF1KlTh7i4uOMO/fvAAw9wxhlnMH36dLZs2cKgQYPy1pV26N97772XG24o2K3h+eefD7yhf9e/BotvheqtYPBsqFX0iJ5K+TKtgz9Bbg8XnJSURPXq1alVqxZ79uzhu+++y9t28+bNbNy4EYCPPsrvRHz48GEiI219cOGhBn788UcOHjxIWloaX375Jf379y9y6N+33norb9TKHTt2sHfv3hKHG/Y72Rmw4EZYOB4aDYFh8zW5K7+lCf4ETZo0idtuu42BAwcWaAFzwQUXMH369LybrOPGjWP27Nn07t2b+fPnlzhccOfOnenZsyddunThhhtuICsrq9jhgrt3706PHj045ZRTGDt2LP379wcgLCyMKVOmcN555zFgwABatmyZt89dd93FvffeS//+/cnOzi5wvAEDBnD11VcTHR3NiBEjiImJoV69evTv358uXbowceJEzjrrLK688kr69u1L165dGTlyJMnJyQWGGx4xYkSB4Yb9Stoe+GUwbHjVDqN7+tc6SJfyaxUyXHBpxcTEmEWLFhVYVtmHi62I4YKnTp1aYB5VX1JhP/+Di2HOcDteep837eTQSvkBV4cLVidHhwuuAFs+hPnXQtWGMPR32wlJqQCgCV4RFxdHXFyc22FUvJxs+OseWD0ZGp4GAz7TJo8qoPhFgjfGBF4rDXVcXq0+zDgEv18Bu36AdjfZCd2DQr13PqVc4PMJPiwsjAMHDlCvXj1N8pWIMYYDBw4QFuaF8VoOr4LZF0Hq39B7ih29UakA5PMJvlmzZmzfvp19+/a5HYqqYGFhYTRr1qx8D7p9Bvwx2vZIHfwrNOhfvsdXyof4fIIPDQ0tsTenUqVicmDFo7B8kh0I7LTpEF7O/zyU8jFebQcvIrVF5HMRWSMiq0WkrzfPp1SRMo/A3Ettco+6GobM0eSuKgVvl+D/C3xvjBkpIlUAnZ5GVawjm2x9e9Iq6PksdLhdJ9VQlYbXEryI1AROA+IAjDEZQEZJ+yhVrnb/BHNHAQYGfQ9NhrodkVIVyptVNK2BfcDbIrJERN4QkWP66YvI9SKySEQW6Y1UVS6MgTXPwa/DoFoTO0a7JndVCXkzwYcAPYFXjDE9gBTgnsIbGWOmGGNijDExDRo08GI4qlLIPgrz4iDh/yDyIjjrT6jRxu2olHKFNxP8dmC7MWa+8/5zbMJXyjtSd8CPp8Hmd6HrwzDwcwit4XZUSrnGa3XwxpjdIrJNRDoYY9YCg4FV3jqfquT2/QG/jYCsIzBwOjQf7nZESrnO261obgU+cFrQbAKu8fL5VGW04Q1YdBOEt4Azf4Lap7gdkVI+wasJ3hizFChyGEulTlpOJiz+J6z/HzQ+C/p/BFXruh2VUj7D53uyKlWko/ts56W9s6HTndD9PzpXqlKF6F+E8j+HltrOS+l7oe/70OoqtyNSyifplH3Kv/z9CczqB+TA0Lma3FVAOJJxxCvH1RK88g852bDsflj1hB0BcsAXUK2R21EpVWaHjx5m8a7FLNyxkIU77SNIgth82+ZyP5cmeOX7MhLh9yth13fQ9gbo9QIEV3E7KqWOKy0zjaW7l+Yl8oU7FrL2wNq89a3rtKZvs77ENo0lx+QQJOVbqaIJXvm2w2tgzkV20LDYV6DdeLcjUqpIWTlZrNy7Mi+RL9y5kOV7l5OVkwVAk4gmxEbGMrrbaGKbxhLTNIZ64fW8GpMmeOW7dnwDf1wJQVVh8C/QcKDbESkFQI7JYcPBDQWqWZbsWkJaVhoAtcNqE9M0hon9JtI7sjexTWOJrBlZ4XFqgle+xxhY9R/4636o08NOzlG9hdtRqUrKGMOO5B0FkvnCHQs5nH4YgGoh1ejZpCc39LqB2MhYYpvG0rZuW5+YYlQTvPItWSkwbyxs/RRaXgl9XocQnUZAVZwDqQcKVLMs3LmQ3Ud2AxASFELXhl0ZdcooWzKPjKVzg86E+GgfDN+MSlVOR7bAnOFweDn0eBo63qGTcyivOpJxhIRdCXnJfMGOBWxOtK1ZBKFD/Q4MbT2U2KaxxEbGEt04mrAQL0wE7yWa4JVv2BMPc0fa5pCnfwtNh7kdkQow6VnpLNuzrEA1y+r9q8kxOQC0rNWS2MhYxseMJ7ZpLL2a9qJm1ZouR31yNMErdxkD616ChH9CjfZw2gyo2c7tqJSfy87JZs3+NSzYsSAvoS/bs4yMbDupXIPwBsRGxjKy88i80nnD6g1djrr8aYJX7slOh4U3waa3IPJC6PcehPp3iUlVPGMMmxM3F6gzX7xzMSmZKQDUqFKDmKYx3N7n9ryboC1qtfCJm6DepgleuSNtF8y5BA7Mgy4PQtdJUM6dPFRg2n1kNwt3LMwrnS/auYgDaQcAqBpclejG0VwTfU1eMu9Qv0O5dyDyFyUmeBEJA84HBgJNgTRgBfCNMWal98NTAWn/fPjtEsg8DAO/gOaXuB2R8lGJRxNZtHNRgdL59qTtAARJEF0admF4x+F51SxdGnahivZyzlNsgheRh4ALgHhgPrAXCAPaA084yf8OY8wy74epAsamqbDgBqgWaedLrd3V7YiUj0jNTGXJriUFboKuP7g+b33bum0Z2GIgsU1j6R3Zmx5NehAeqk1oS1JSCX6hMeahYtY9KyINgRJ7n4jIFiAZyAayjDE6+UdllZMFS+6Etf+FRoNhwCdQ1bvdtJXvyszOZMXeFQXam6/Yu4Jskw1AZI1IYiNjiYuOy+vWX6daHZej9j/FJnhjzDcl7WiM2Yst1R/PGcaY/WUNTAWQ9AMw9zLY8wt0+Cf0eEon56hEckwO6w6sK1DNsnT3Uo5mHQWgTlgdYiNjuaD9BXn15k1qNHE56sBwvDr4McBtQAdn0WrgBWPMu94OTAWIQ8ts56W0nXDqO9D6H25HpLzIGMO2pG0FOg4t3rWYpPQkAKqHVqdnk57cFHNTXjJvXad1pWjR4oaS6uD/AdwO/B+QAAjQE3haRChlkjfALBExwGvGmClFnOd64HqAFi10vJGAsvVz+HMMVKkNQ+ZA/d5uR6TK2b6Ufcd069+bYr/YhwaF0r1xd67qelXeTdBO9TsRHBTsctSVhxhjil4hMg+43BizpdDyKOBjY8ypxz24SFNjzE6nvv5H4FZjzJzito+JiTGLFi0qQ/jKZ214AxaMg/p9bUuZavqV298lpyfnTVSxYOcCFu5YyN+H/wZst/5ODTrZRO4k8+6NulM1pKrLUQc+EVlc3P3NkqpoahZO7gDGmC0iUqreKMaYnc7zXhGZDvQGik3wKkCkbIWE2+3N1EHfQLD+kfubo1lH+Wv3XwVatKzZvwaDLRC2qt2KPs36cEvvW4htGkvPJj2pUbWGy1GrwkpK8GknuA4AEakOBBljkp3XZwGPlDE+5W+Msb1TjYE+b2hy9wNZOVms3rc6r8584c6FLN+znMycTAAaVW9EbGQsl3e5PK90Xj+8vstRq9IoKcF3EpGi2rgL0LoUx24ETHdunoQAHxpjvi97iMqvbP0Udn4DPZ+FiCi3o1GFGGPYeGhjgTrzhF0JpGamAlCrai1imsZwR9878m6CNqvZTG+C+qkSE/zJHNgYswnofjLHUH4m/SAsngB1Y6H9BLejUcDO5J22VO4k9EU7F3Ho6CEAwkLC6NG4B9f1uC5vbPO2ddtW2m79gaikdvB/e74XkXrAacBWY8xibwem/NCSO22b9zNmgbaUqHAH0w4e061/Z/JOAIIlmK6NuhYYPfGUBqcQGhzqctTKm0pqJjkTuMcYs0JEmmCbSi4C2ojIFGPM8xUUo/IHu3+GTW9D53ugjn5x87aUjBQ7UYXHTdCNhzbmrW9frz1nRJ2RNx9odONoqoVWczFi5YaSqmhaGWNWOK+vAX40xvxDRGoAvwPPezs45SeyUu34MhFt7ciQqlxlZGewfM/yAu3NV+5bmTdRRfOazYmNjOW6ntflTVRRO6y2u0Ern1BSgs/0eD0YeB3AaRWT49WolH9Z/jAc2QiDf4EQLSWejByTw5r9awpUs/y1+y/Ss9MBqB9en9imsVzc8eK8m6CNIhq5HLXyVSUl+G0iciuwHduD9XsAEakGaMWdsg4ugTXPQJtrodEZbkfjV4wx/H347wLJfNHORRzJOAJARJUIejXpxa29b81L5lG1o7RFiyq1khL8tdh260OAUcaYRGf5qcDbXo5L+YOcLJh/HVStbyfJViXac2TPMd3696facfiqBFchunE0Y7qPybsJ2qFeB+3Wr05KSa1o9gLji1j+K/CrN4NSfmLtf+FQAgz4FKroUK6eDh89fEy3/m1J2wA7UUXnBp3t6IlOMu/WqJtOVKHKXUmtaL4GPAeqMcB+4FdjzPveDkz5uCObYNkDEHkBNB/pdjSuSstMY+nupQVatKw9sDZvfZs6bejfon/eOC09mvQgokqEixGryqKkKprJRSyrC4wWkS7GmHu8FJPydcbAgvEgIRD7MlSiOuGsnCxW7l2Z16U/d6KKrJwsAJpENCE2MpbR3UbTO7I3MU1jqFutrstRq8qqpCqa2UUtF5GvgMWAJvjKavN7sPtHiHkJwpu5HY3Xzd4ym+lrprNw50KW7FpCWpYdiql2WG1im8ZyV7+78m6CRtaMdDlapfKVeVodY0y23sWvxI7uhYR/2mGA293odjRelZyezB2z7uD1hNepFlKNnk16Mj5mfF69eZs6bbRFi/JpJdXBF/W9sg7wD2Cl1yJSvm3xPyErGXq/DgE8Zskvm39h7IyxbD28lYn9JvLIGY8QFhLmdlhKlUlJJfjF2BuruUWU3Jus8UBgF91U0XZ+B39/aHur1j7F7Wi8IiUjhbt/upv/Lfwf7eq2Y+7YufRr3s/tsJQ6ISXVwbeqyECUj8s8AgtvhJod4ZT73I7GK+ZunUvcl3FsPLSR2/rcxuODHyc8NNztsJQ6YcV+xxaRASXtKCI1RaRL+YekfNKyByDlb1s1E2CTeKRlpnHHD3dw2tunkWNyiB8Tz/NnP6/JXfm9kqpoRojIU9ghChYD+4AwoC1wBtASuMPrESr37V8A616wN1Ublvh/3+/M3z6fuBlxrNm/hvG9xvP0WU9rG3UVMEqqovmniNQBRgKXAk2wU/WtBl4zxswtzQlEJBg7zPAOY8z5Jx+yqlA5mbDgOghrDN3/43Y05SY9K52HZz/Mk78/SWSNSGaNnsXQNkPdDkupclViM0ljzCHsKJKvn8Q5bsP+UyjVRN3Kx6yeDInL4bQvoUott6MpFwm7Ehjz5RhW7F3B2OixPDvsWWqFBcZnU8qTV9u5iUgz4DzgDW+eR3lJ0jo7FHDzEdDsIrejOWmZ2Zk8FP8Qfd7ow4HUA8y8YiZvXvSmJncVsMrc0amMngfuAmoUt4GIXA9cD9CiRQsvh6NKzeTAgushOAxiXnQ7mpO2fM9yxnw5hiW7lzC622heOPsF6lTTAdJUYDtuCV5EjmkyUdSyIrY5H9h7vPlbjTFTjDExxpiYBg0aHO+wqqJsfAv2zrbDAFdr4nY0JywrJ4v//PYfek3pxY7kHUwfNZ33Ln5Pk7uqFEpTgv8TO+HH8ZYV1h+4UETOxba+qSki7xtjRpc9TFWh0nbBkonQ8DQ7kYefWr1vNXEz4liwYwGXdr6Ul897mfrh9d0OS6kKU9JQBY2BSKCaiPQgv0drTeC4DYSNMfcC9zrHGgTcqcndTyyaANlp0HuKXw5HkJ2TzfPznudfv/yLiCoRfDLyEy475TK3w1KqwpVUgh8GxAHNgGfIT/BJQGB2ZVSwfQZs+xy6PQo1O7gdTZltOLiBuC/j+H3b71zU4SJePf9VGkc0djsspVxRUjv4d4B3RGSEMeaLkzmJMSYeO4aN8mWZSbDwZqjdFTpNdDuaMskxOfxvwf+4+6e7qRpSlfcufo+rul6loz2qSq003797iUjt3DciUkdEHvVeSMo1S++FtJ3OcAT+M33clsQtDHl3CBO+n8CgqEGsuHEFo7uN1uSuKr3SJPhzPCbczu38dK7XIlLu2Pc7rH8ZOkyA+n3cjqZUjDFMWTyFrq90ZdHORbxxwRt8c+U3OumGUo7StKIJFpGqxph0ABGpBgTWaFOVXXY6zB8H4S1s3bsf2J60neu+uo4fNv7AkNZDePPCN2lRS/tRKOWpNAn+feBnEXkbOyb8WOAdr0alKtaqJyBpNQz6FkJ9e6AtYwzv/PUOt39/O1k5Wbx87suMjxmv1TFKFeG4Cd4Y85SILAcGY1vS/NsY84PXI1MV4/AqWPkYtLwCmp7jdjQl2pW8i+tnXs/MdTM5reVpvH3R27Su09rtsJTyWaUaqsAY8x3wnZdjURXN5NiqmZAa0Ot5t6MpljGGj1d8zM3f3kxaVhrPDXuOCX0mEOSHbfSVqkjHTfAicirwItAJqAIEAynGGB0d0t+tfxX2/wGnToWwhm5HU6S9KXu56Zub+GL1F5za7FTeGf4O7eu1dzsspfxCaUrwLwGXA58BMdhJt9t6MyhVAVK3w9J7oPEQaPUPt6Mp0hervuDGb27kcPphnhzyJHf0vYPgoGC3w1LKb5S2imaDiAQbY7KBt0XkDy/HpbzJGNuhyWRB7KvgYzcoD6Qe4NbvbuWjFR/Rq0kv3hn+Dqc0DMxJvpXyptIk+FQRqQIsdabw2wVU925Yyqu2fQE7voLop6BGG7ejKeDrtV9z/czrOZB6gH+f8W/u7n83ocGhboellF8qzV2qq53tbgFSgObACG8GpbzE5MDal2BeHNTpAR3/6XZEeRKPJhL3ZRwXfnwhDas3ZOG4hdx/2v2a3JU6CaVpJvm3U4KPAqYBa40xGd4OTJWzpHUw/1rYNxeaDIM+b0CQt+d7KZ0fNvzAdV9fx67kXdw/8H4eOP0BqvjRUAlK+arStKI5D3gV2IhtB99KRG5wmk4qX5eTDWufg2UPQFAYnPo2tBrjE/XuyenJ3DHrDl5PeJ3ODToz7bJpxEbGuh2WUgGjNEW4Z4AzjDEbAESkDfAN2i7e9yWuhPlj4cACiLwQYl+B8KZuRwXAr5t/5ZoZ17AtaRt39buLh894mLCQMLfDUiqglCbB781N7o5NwF4vxaPKQ04mrHoKVjwCoTWg30fQcpRPlNpTMlK456d7eGnhS7Sr246518ylb/O+boelVEAqTYJfKSLfAp9ix6K5FFgoIpcAGGOmeTE+VVaHlsK8a+xzi1EQ84LPdGL6fevvxM2IY8PBDdzW5zYeH/w44aHHnRxMKXWCSpPgw4A9wOnO+31AXeACbMIvMsGLSBgwBzvyZAjwuTFm0skGrIqRnQ4rHrUDh1WtDwOnQfOL3Y4KgLTMNB749QGe/fNZompHET8mntOjTj/+jkqpk1KaVjTXnOCx04EzjTFHRCQUmCsi3xlj5p3g8VRx9s+3de2HV9kbqD2fhap13Y4KgPnb5xM3I441+9dwY8yNPDX0KSKq+PaIlUoFitK0omkF3IptJpm3vTHmwpL2M8YY4IjzNtR5mBMNVBUhKw2WPwhrnoVqTe1wvz4yImR6VjoPz36YJ39/ksgakfx49Y8MaT3E7bCUqlRKU0XzJfAm8DWQU5aDi0gwsBg7ds3/jDHzi9jmeuB6gBYtdMKGUjEG9sbDghsgeT20vQF6PAWhvjH+W3ZONqM+H8WMtTO4tse1PHPWM9QKq+V2WEpVOqVJ8EeNMS+cyMGdsWuinTldp4tIF2PMikLbTAGmAMTExGgJvyjGwJFNsOeX/MfRvVC9FZz5MzQ+0+0IC7j7p7uZsXYG/z37v0zoM8HtcJSqtEqT4P8rIpOAWdh6dQCMMQmlPYkxJlFE4oGzgRXH2VwBpO4smNBT/rbLqzWBxkOh0Zm26WOIbw0LNGXxFJ758xluib1Fk7tSLitNgu+KHY/mTPKraIzzvlgi0gDIdJJ7NWAI8ORJxBr4slJtj9Od30LSGrusSh1odAZ0mgiNBkPNDj7Rnr0oP236iZu+uYlz2p7Dc2c/53Y4SlV6pUnwFwOtT2D8mSbAO049fBDwqTFmZlkDrFTWPm9vmDY5G9pcaxN6ne7gBzMXrd63mpGfjqRzg858PPJjQnxknBulKrPS/BX+BdSmjL1XjTHLgB4nEFPllJkMq5+BpufBIP/6P7gvZR/nfXgeYSFhzLxyJjWr+sbNXqUqu9Ik+EbAGhFZSME6+BKbSaoyWvc/yDgIXf2rL9jRrKMM/2Q4u47sYnbcbFrU0pZQSvmK0iR4/8o4/ijzCKyZDE3OgXr+M5qiMYZrv7qWP7b9wWeXfkbvyN5uh6SU8lCanqyzKyKQSm39y5B+ALo+6HYkZfLI7Ef4cPmHPH7m44zsPNLtcJRShRSb4EUkmaJ7ngq2o6pWtJaHrBRYPRkanwX1T3U7mlL7cPmHPDT7IeKi47hnwD1uh6OUKkKxCd4YU6MiA6m01r8C6fv8qu79962/c82Mazi95em8dv5riI8221SqsvP99neBLCsVVj8NjYdAg35uR1Mqmw5tYvgnw2lZqyVfXPaFTq2nlA/TBO+m9a/aIQe6+EfpPfFoIud9eB7ZOdl8c+U31Auv53ZISqkSaG8Ut2Slwuqn7JADDQe4Hc1xZWZnculnl7Lx4EZ+vPpH2tVr53ZISqnj0ATvlg1T4OgeGPCp25EclzGGW769hZ82/cTbF72tk3Uo5Se0isYNWWmw6kloOAganuZ2NMf13LznmJIwhXsH3EtcdJzb4SilSklL8G7Y+Doc3Q39P3I7kuOasWYGd866k5GdR/LomY+6HY5Sqgy0BF/Rso/a0nuDgdDQt6s6EnYlcOW0K4lpGsM7w98hyA8GPVNK5dMSvDdlJMLBBDvrUvJ6SF5n501N2wl93/XZYX8BdiTt4IKPLqB+eH2+uuIrwkPD3Q5JKVVGmuC9JTMZvu0Kqdvt++AwiGgDtbtBh9tt6xkfdSTjCBd8dAFJ6Un8PvZ3Gkc0djskpdQJ0ATvLWuetcm93wfQYACEN/OLcd2zc7K5atpV/LXnL76+4mu6NermdkhKqROkCd4bju6z48s0HwFRV7odTZnc/dPdfLX2K14850XObXeu2+EopU6C14qUItJcRH4VkdUislJEbvPWuXzOyschOxW6+VerE8/5VG/pfYvb4SilTpI3S/BZwB3GmAQRqQEsFpEfjTGrvHhO96X8bYf/bX0N1OrodjSlpvOpKhV4vFaCN8bsMsYkOK+TgdVApLfO5zOWPwSI34wvA/nzqXZq0EnnU1UqgFTIXT8RicLOzzq/iHXXi8giEVm0b9++igjHexJXwuZ3ocOtUL2529GUSoH5VK/Q+VSVCiReT/AiEgF8AdxujEkqvN4YM8UYE2OMiWnQoIG3wyl/WamQthuS1sPSeyAkAjr7xwQYnvOpfnXFV7Ss3dLtkJRS5cir38VFJBSb3D8wxkzz5rlcse5lWHRzwWXdHoWqvj+MrjGGsTPG6nyqSgUwryV4sdP8vAmsNsY8663zuGrXD7Z9e+d7IbQGVG0ITYa6HVWpPDL7ET5a8ZHOp6pUAPNmCb4/cDWwXESWOsvuM8Z868VzVqxDCXY8mfY3uR1JqRljeOevd3ho9kOM6T5G51NVKoB5LcEbY+ZiJ+gOTEf32p6qdXq6HUmpxW+JZ1L8JOb8PYfTW57OlAum6HyqSgUwbQ93og4m2Oe6vp/gZ2+ZzUOzHyJ+SzxNIprwwtkvMK7XOJ1PVSmXpKfD4cP5j8xM6Nu3/M+jCf5EHXISfJ1oV8MoyW9//8ak+En8uuVXGkc05r9n/5fre11PWEiY26Ep5beysiApCRITCybpsrw/erTgMRs1gt27yz9WTfAn6mCCHR2ySm23IznG71t/Z1L8JH7e/DONqjfiuWHPcUOvG6gWWs3t0JRyVU4OJCeXPSF7vk9JOf55wsOhdm2oVcs+6tSBVq3y39eqVXB93bre+bya4E/UwQSoF+N2FAX8se0PHop/iB83/UjD6g155qxnGB8zXsdyVwHBGJtcS5OMi9smOdkepyRVqx6bhJs2PTYpF36f+7pmTQgN9e61KC1N8Cci4xCkbIa217sdCQDzts9jUvwkZm2cRYPwBkweOpkbY2/UxK58hjG2WuJEqjNy3yclQXZ2yecJCTk2AbdpU3RCLup9rVoQFkA1mJrgT8TBJfbZ5RusC3YsYFL8JL7f8D31w+vz1JCnuCn2JqpXqe5qXCrwZGSceH1z7vvMzJLPIXJssm3eHLp0KX2CDg/36YnSKpwm+BORd4O1h9dPlZqZyo6kHWxP2s6OZPu8PWk7K/etJH5LPPXD6/PkkCe5KfYmIqpEeD0e5X+ys0tXfVHS+7S0458nIqJgwm3YENq3Lzkhe76PiIAg358Tx69ogj8RBxMgvDmEle/YOYlHE3k4/mHWHlibl8gPHT10zHa1w2rTvGZz/jP4P9zS+xZN7AEsJweOHDm5FhtHjhz/PNWqFUy6tWtDy5bF1zMXVe8cHOy1y6BOkCb4E3EoodyrZ4wxjJ85ns9XfU73xt1pVacVA1sMJLJmJM1qNqNZzWZE1ogksmakJnQ/YQykpp5ci42kpOPfFAwNPTYJN25ctnrnKtolIiBpgi+rzGRIWgcty3cqvveXvc8nKz/hsTMf476B95XrsdXJ2bULtm07sQR9vJuCQUHHJtySmtMV9T4sTOudVdE0wZfVoSWAgbq9yu2Qmw5t4uZvb2Zgi4Hc3f/ucjuuKhtjYMsWSEiwjyVL7POePcXvU7NmwYTbtCl07lz6BF29uiZn5T2a4Mtq53cgwVC/fPoVZ+VkMXraaIIkiPcufo/gIK3IrAjZ2bBuXcFkvmSJLXmDrU/u3BnOPht69IDWrfMTc+5zjRp6U1D5Nk3wZWEMbJsGDQdB1fLpevb4b4/z5/Y/+fCSD3XCDS/JyICVKwuWyv/6y9aPg+3Y0q0bjBplk3nPnrZpXjXt+Kv8nCb4skhaDcnroMNt5XK4P7f9ySOzH2F0t9Fc0fWKcjlmZZeSAsuWFUzmK1bkt8GOiLBJfNy4/GTesaPv9DxUqjxpgi+LbdPtc7PhJ32o5PRkRk8fTbOazXjpnJdO+niVUWJifhLPfV671jYtBKhXzybwf/7TPvfsaXs1arWKqiw0wZfFtmlQ71QIb3rSh5rw/QS2JG5hdtxsaoXVKofgAtuePcfe/Ny8OX99ZKRN4Jdemp/MmzXTG5iqcvPmlH1vAecDe40xXbx1ngqT8rdt/x791Ekf6tOVnzJ16VTuH3g/A1oMKIfgAocxsHXrscl81678bdq0gZgYW83Ss6etamnY0L2YlfJV3izBTwVeAt714jm8LyPRVs3s/Ma+b35xqXdNSk9iS+IWUjJSSMlMISUjhcPph7nt+9voHdmbB09/0Dsx+4mcHFi/vmAiT0iAQ07n3aAg6NQJhgzJry+PjrYtWJRSx+fNKfvmiEiUt45fIbIz4Nez4cB8kBBb916jbal2Xbp7KYPfHczBtIPHrKsTVocPLvmA0ODKc2cvMxNWrTq2JUtuN/oqVaBrVxgxIr+KpWtXO3iUUurEuF4HLyLXA9cDtGjRwuVoCvnrXpvc+74LLa+AoNJdrhV7VzDk3SFUD63Oy+e+TK2wWkRUiaB6aHWqV6lOk4gm1Khaw8vBu2vTJpg1K79Uvny5ba4ItnNPdDTExeUn806dtLu8UuXN9QRvjJkCTAGIiYk5zqgbFShxJax5FtrdBK2uLvVua/evZci7Q6gSXIVfxvxC27qlK/EHgq1b4dNP4ZNPYNEiu6xOHZvAJ0zIT+Zt2+rAVEpVBNcTvM9KWmWf295Q6l02HNzAme+eicFUmuS+axd89hl8/DH8+add1qsXPPUUXHyxvSGqLVmUcocm+OKk/G2fq5fcu9QYw5LdS/hq7Ve8nvA66VnpxMfF07F+xwoI0h379sEXX9ikPmeObfnSrRs89hhcdpktoSul3OfNZpIfAYOA+iKyHZhkjHnTW+crdylbIbQmVCm+ycZPm34i7ss4diTvQBD6Ne/HS+e+RJeG/t8qtLCDB2H6dFv98ssvdiyXjh3hwQdtF/9OndyOUClVmDdb0fh33/vUrRBe8k3ff/3yL0KCQph60VTObXcuDaqX7wQgbktKghkzbFKfNcu2hGndGu6+2yb1rl21+kUpX6ZVNMVJ+bvE6pkVe1ewYMcCnj3rWcZEj6nAwLwrJQVmzrTVL999B+np0KIF3HabTeq9emlSV8pfaIIvTsrWEocEfnvJ24QGhTK62+gKDMo70tJsMv/kE5vcU1OhSRO44Qa4/HLo00fHb1HKH2mCL0rmEcg4WGwJPiM7g3eXvcuFHS7022qZjAxb7fLJJ7YaJjkZGjSAMWNsSX3AAG3KqJS/0wRflNSt9rmYOviZ62ayP3U/Y3uMrcCgTtzBg3Zyi/Xr7WPtWpvcExNtO/XLLrNJ/YwzIER/I5QKGPrnXJQUJ8FXLzrBv7XkLSJrRDKszbAKDKpkSUn5CXz9+oIJ/aDHaAlBQdCyJVxwgU3qQ4dqD1KlApUm+KKU0AZ+R9IOvtvwHff0v8cr0+sdPGgna05NLflx5IgdLjc3iReeN7R5c2jXzg6f266dfbRvbyd0rlq13MNWSvkgTfBFSd1q510Na3LMqgd/fZAgCeLanteW2+mysuDrr+F//4Offy79fo0b26R9/vn5SbxdO9t7VAfpUkppgi8sMxl2/wLhzaBQCX3e9nm8tfQtJvabSOs6rU/6VHv2wBtvwGuvwbZtdoKKSZNsKTs8vORHtWpataKUKpkmeE85mfDTaZC4DGJfKbAqOyebm7+9maY1mvLAaQ+U6bDG2J6fmZn2sXy5La1//rl9P2QIvPCCLYnrTU6lVHnRdOJp09twaCn0/xhajgLgYNpBZqyZwbcbviVhVwIfjfioxKF+c3Jg3jw7ANe0aXYwrtwJnz3VqgU33QQ33ggdOnjp8yilKjVN8LkyDsHyh23nphaXAfDh8g+57fvb2J+6n9phtbkp5iZGnTIqb5fERNvc8MABe3N0xw746iv7XLUqDBsGV10FoaG2ZB4aah+NGtmRFqtXd+mzKqUqBU3wSevspB4bXoP0fTBwGojwx7Y/uGraVfSJ7MO3V35Lr6a9CJL87pwbNsA559jnXBERcOaZ8OSTthlizZoufB6llHJU7gS/9kVYPMG+DomAPm9C/T4AfLPuG0KCQph19SxqVi2Yqf/80yZwEfj+e+je3XYY0uaHSilfUnkTfHYGrHwcGgyE2JehZqcCrWZ+2PgDfZv1LZDcjx6F55+Hhx+2LV6++07HPldK+a7Km+D3/wlHd9vWMrULjt++L2UfCbsS+L8ej/D++7BmjR1l8csvYcsWuOgi27yxfn1XIldKqVKpvAl+7xxAoNHpx6z6efPPGAzP3nwWZrvt3l+9um3t8sYbMHhwxYerlFJl5dUELyJnA/8FgoE3jDFPePN8pWIMbPsCNrwKtbtBlToApGelsy1pGy/Nf5mPl32GHK1Dz8a9eOsbOOUUHVlRKeV/vDllXzDwP2AosB1YKCJfGWNWeeucx8jJhOQNcGQjJK4g/dBf7N31O3uTt7FbIvghfQQ/PXQpydn72Rn8BzmSAdmhsGkwEatu5fNpwURFVVi0SilVrrxZgu8NbDDGbAIQkY+Bi4ByT/Bd/x1BKhlkY8jxfIghG8g2kGngiPHc6wjwIhxuSVBqE6ruH0+d7I6c3vRchpzZkjMfRZO7UsqveTPBRwLbPN5vB/oU3khErgeuB2jRouQ5UIs9kTQik0yCTAhCMEESjJhgMFU4mlWPzJzaHM1qRBXTmBpBjagV0pBawY3o3bkJccNbEhqqc9AppQKPNxN8UVnTHLPAmCnAFICYmJhj1pfG9/dvPJHdlFIqoHlzps3tQHOP982AnV48n1JKKQ/eTPALgXYi0kpEqgCXA1958XxKKaU8eK2KxhiTJSK3AD9gm0m+ZYxZ6a3zKaWUKsir7eCNMd8C33rzHEoppYrmzSoapZRSLtIEr5RSAUoTvFJKBShN8EopFaDEmBPqW+QVIrIP+PsEd68P7C/HcPyZXouC9Hrk02tRUCBcj5bGmAZFrfCpBH8yRGSRMSbG7Th8gV6LgvR65NNrUVCgXw+tolFKqQClCV4ppQJUICX4KW4H4EP0WhSk1yOfXouCAvp6BEwdvFJKqYICqQSvlFLKgyZ4pZQKUH6f4EXkbBFZKyIbROQet+OpCCLylojsFZEVHsvqisiPIrLeea7jse5e5/qsFZFh7kTtHSLSXER+FZHVIrJSRG5zlle66yEiYSKyQET+cq7Fw87ySnctPIlIsIgsEZGZzvvKcz2MMX77wA5DvBFoDVQB/gI6ux1XBXzu04CewAqPZU8B9ziv7wGedF53dq5LVaCVc72C3f4M5XgtmgA9ndc1gHXOZ6501wM7i1qE8zoUmA+cWhmvRaHr8n/Ah8BM532luR7+XoLPm9jbGJMB5E7sHdCMMXOAg4UWXwS847x+BxjusfxjY0y6MWYzsAF73QKCMWaXMSbBeZ0MrMbOB1zproexjjhvQ52HoRJei1wi0gw4D3jDY3GluR7+nuCLmtg70qVY3NbIGLMLbNIDGjrLK801EpEooAe25Fopr4dTHbEU2Av8aIyptNfC8TxwF5DjsazSXA9/T/Clmti7kqsU10hEIoAvgNuNMUklbVrEsoC5HsaYbGNMNHYO5N4i0qWEzQP6WojI+cBeY8zi0u5SxDK/vh7+nuB1Yu98e0SkCYDzvNdZHvDXSERCscn9A2PMNGdxpb0eAMaYRCAeOJvKey36AxeKyBZs9e2ZIvI+leh6+HuC14m9830FjHFejwFmeCy/XESqikgroB2wwIX4vEJEBHgTWG2MedZjVaW7HiLSQERqO6+rAUOANVTCawFgjLnXGNPMGBOFzQ2/GGNGU5muh9t3eU/2AZyLbTmxEfiX2/FU0Gf+CNgFZGJLHdcC9YCfgfXOc12P7f/lXJ+1wDlux1/O12IA9mv0MmCp8zi3Ml4PoBuwxLkWK4AHneWV7loUcW0Gkd+KptJcDx2qQCmlApS/V9EopZQqhiZ4pZQKUJrglVIqQGmCV0qpAKUJXimlApQmeOVVIpItIktFZIWIfJ3bTruE7YeLSOcKCq/MRCRGRF4o4z5bRKR+EctFRH4RkZrlF2GR5/9YRNp58xzKN2mCV96WZoyJNsZ0wQ6QdvNxth+OHdWv1EQk5ARjKxMRCTHGLDLGTCinQ54L/GVKHlrhpIhIMPAKdjwWVcloglcV6U+cwZtEpI2IfC8ii0XkNxHpKCL9gAuBp51SfxsRiReRGGef+k63c0QkTkQ+E5GvgVnO+2nOMdeLyFNFBeCUpp90xk1fICJtneUNROQLEVnoPPo7yx8SkSkiMgt4V0QGFRpX/EsRWSYi80Skm7O8nojMcsYgf42ixzgBuAqnF6WI/Fucseyd94+JyATn9UQnpmXijPHuLP/SuX4rReR6j+VHROQREZkP9AV+A4ZU1D9C5UPc7mmlj8B+AEec52DgM+Bs5/3PQDvndR9sN3KAqcBIj/3jgRjndX1gi/M6DtuLt67H+01ALSAM+BtoXkQ8W3B6PAP/IL9344fAAOd1C+zQBwAPAYuBas77QR77vAhMcl6fCSx1Xr9Afi/S87A9besXEcvfQA3ndRSQ4LwOwvamrAechZ0YWpzlM4HTnO1yP3s1bM/Ves57A1xW6Fw/Ar3c/n3QR8U+9D+68rZqzvC1UdhE+aMz8mM/4DM7lAxgJ1koqx+NMZ7j4v9sjDkMICKrgJYUHP4110cez885r4cAnT3iqSkiNZzXXxlj0oo4zgBgBIAx5hen5F4LOyHLJc7yb0TkUDHx1zV2DHuMMVtE5ICI9AAaAUuMMQdE5Cxskl/i7BOBHSNlDjBBRC52ljd3lh8AsrGDr3naCzTF/gxUJaEJXnlbmjEm2kl8M7F18FOBRGOHtT2eLPKrEsMKrUsp9D7d43U2xf9+myJeBwF9CydyJ+EXPk/e6hKOXZoxQLJEJMgYkztW+RvYbyKNgbc8zvEfY8xrheIahP2n1NcYkyoi8eRfn6PGmOxC5woDivonpQKY1sGrCuGUrCcAd2ITzWYRuRTyWpN0dzZNxk69l2sL0Mt5PbKcwhnl8fyn83oWcEvuBiISXYrjzMHWo+cm3P3G3jD1XH4OUKeY/ddip5vMNR07vG8s8IOz7AdgrPOtBxGJFJGG2KqoQ05y74idmq8k7YGVpfhMKoBoglcVxhizBDvn5eXYBHitiPyFTTy5Uy1+DEx0blC2ASYDN4rIH9g6+PJQ1bkBeRvwT2fZBCDGuZG5ChhfiuM8lLsP8AT5Q9A+DJwmIgnY6pWtxez/DbZOHwBjp538Ffg0twRujJmFvT/wp4gsBz7H/gP8Hghxzv1vYF5xQYpII+w3qV2l+EwqgOhokqpScVrhxBhj9vtALE2Ad40xQ533QUACcKkxZn05nuefQJIx5s3yOqbyD1qCV8olTon6dRGp6XTu2oC9UVxuyd2RSP4k06oS0RK8UkoFKC3BK6VUgNIEr5RSAUoTvFJKBShN8EopFaA0wSulVID6fwqJ+kZNs8hTAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "combined_costben_disc = costben_disc.combine_measures(['Measure A', 'Measure B'],\n", " 'Combined measures',\n", " new_color=np.array([0.1, 0.8, 0.8]),\n", " disc_rates=discount_stern)\n", "efc_present = costben_disc.imp_meas_present['no measure']['efc']\n", "efc_future = costben_disc.imp_meas_future['no measure']['efc']\n", "efc_combined_measures = combined_costben_disc.imp_meas_future['Combined measures']['efc']\n", "\n", "ax = plt.subplot(1, 1, 1)\n", "efc_present.plot(axis=ax, color='blue', label='Present')\n", "efc_future.plot(axis=ax, color='orange', label='Future, unadapted')\n", "efc_combined_measures.plot(axis=ax, color='green', label='Future, adapted')\n", "leg = ax.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "\n", "Cost-benefits calculations can be powerful policy tools, but they are as much an art as a science. Describing your adaptation measures well, choosing the period to evaluate them over, describing the changing climate and picking a discount rate will all affect your results and whether a particular measure is worth implementing.\n", "\n", "Take the time to explain these choices to yourself and anyone else who wants to understand your calculations. It is also good practice to run sensitivity tests on your results: how much do your conclusions change when you use other plausible setups for the calculation?" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }