{ "cells": [ { "cell_type": "markdown", "id": "034f532a", "metadata": {}, "source": [ "# Example of a coordinate transformation from z levels to density levels\n", "\n", "## Rebinning `ty_trans` to `ty_trans_rho` density levels\n", "\n", "This transformation is commonly used for the purpose of decomposing the residual meridional overturning streamfunction into mean and eddy components. The mean is taken to be the time-mean Eulerian transport (time-mean in z coordinates), whilst the residual transport is the time-mean in density coordinates (density surface move in time). The eddy transport is the difference between the residual overturning streamfunction, and the Eulerian transport **transformed from depth to density coordinates** via the time-mean density.\n", "\n", "Binning is the discrete version of this transformation from depth to density coordinates. We define target density bins, and for each bin we add the quantity to be binned from all cells with a density that satisfies that bin. In its simplest form, binning is creating a histogram.\n", "\n", "We use three different binning methods:\n", "1. `xhistogram`, which performs binning in exactly the way MOM5 does and is thus most appropriate for calculating eddy quantities (define edge of bins)\n", "2. `xgcm` conservative binning (define edge of bins, but vertically interpolates so looks smoother than `xhistogram`)\n", "3. Using density coordinate binning method of Lee et al. (2007) (define isopycnals to bin onto i.e. centre)\n", "\n", "Compute times were calculated using the XXLarge (28 cpus, 128 Gb mem) Jupyter Lab on NCI's ARE, using conda environment analysis3-22.10" ] }, { "cell_type": "code", "execution_count": 1, "id": "7a700f6b", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import cosima_cookbook as cc\n", "from cosima_cookbook import distributed as ccd\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import xarray as xr\n", "import glob\n", "import cmocean.cm as cmocean\n", "import xgcm\n", "import logging\n", "logging.captureWarnings(True)\n", "logging.getLogger('py.warnings').setLevel(logging.ERROR)\n", "from xhistogram.xarray import histogram\n", "\n", "from dask.distributed import Client" ] }, { "cell_type": "code", "execution_count": 2, "id": "e049d1c1", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "client = Client()\n", "client" ] }, { "cell_type": "code", "execution_count": 3, "id": "76feaa74-52a1-4f27-9f1b-557a321de297", "metadata": {}, "outputs": [], "source": [ "session = cc.database.create_session()\n", "experiment = '01deg_jra55v13_ryf9091'\n", "\n", "rho_0 = 1035.0 # kg/m^3 reference density\n", "g = 9.81\n", "\n", "# reduce computation by choosing only Southern Ocean latitudes\n", "lat_range = slice(-70, -34.99)" ] }, { "cell_type": "markdown", "id": "74e94e0c-00d9-4552-bb2b-74a7a538a700", "metadata": {}, "source": [ "### Step 1: Load density and quantity being binned \n", "(you can choose any other quantity instead of `ty_trans`, e.g. `dzt`. Interpolate density to whatever grid that variable is on)\n", "\n", "For the simplicity of the demonstrations here, we will **only load two months** of monthly `ty_trans`, `ty_trans_rho` and `pot_rho_2`, then take the time average after we weight with the number of days in each month." ] }, { "cell_type": "code", "execution_count": 4, "id": "bebe18ab-8929-4e8b-985c-551be4f02ea8", "metadata": {}, "outputs": [], "source": [ "start_time = '2170-01-01'\n", "end_time = '2170-03-01'\n", "time_slice = slice(start_time, end_time)" ] }, { "cell_type": "code", "execution_count": 5, "id": "99345a56-cc65-44da-8721-aea5467a74ca", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.34 s, sys: 635 ms, total: 1.97 s\n", "Wall time: 8.5 s\n" ] } ], "source": [ "%%time\n", "ty_trans = cc.querying.getvar(experiment, 'ty_trans', session,\n", " start_time = start_time, end_time = end_time)\n", "ty_trans = ty_trans.sel(time = time_slice).sel(yu_ocean = lat_range)\n", "\n", "# weighted time-mean by month length\n", "days_in_month = ty_trans.time.dt.days_in_month\n", "total_days = days_in_month.sum()\n", "ty_trans = (ty_trans * days_in_month).sum('time') / total_days" ] }, { "cell_type": "code", "execution_count": 6, "id": "4b5de409-b4d4-4067-a7ab-3f465a0efe1d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 494 ms, sys: 65.6 ms, total: 560 ms\n", "Wall time: 6.28 s\n" ] } ], "source": [ "%%time\n", "pot_rho_2 = cc.querying.getvar(experiment, 'pot_rho_2', session,\n", " start_time = start_time, end_time = end_time)\n", "pot_rho_2 = pot_rho_2.sel(time = time_slice).sel(yt_ocean = lat_range)\n", "pot_rho_2 = (pot_rho_2 * days_in_month).sum('time') / total_days" ] }, { "cell_type": "code", "execution_count": 7, "id": "9d40759b-a5de-4827-bfda-490704bc93e0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 290 ms, sys: 18.2 ms, total: 309 ms\n", "Wall time: 602 ms\n" ] } ], "source": [ "%%time\n", "ty_trans_rho = cc.querying.getvar(experiment, 'ty_trans_rho', session,\n", " start_time = start_time, end_time = end_time)\n", "ty_trans_rho = ty_trans_rho.sel(time = time_slice).sel(grid_yu_ocean = lat_range)\n", "ty_trans_rho = (ty_trans_rho * days_in_month).sum('time') / total_days" ] }, { "cell_type": "markdown", "id": "00cb7a08-4c4a-4742-ad36-6db0e648f434", "metadata": {}, "source": [ "Create an `xgcm` grid for interpolation, and then interpolate density onto the meridional transport grid" ] }, { "cell_type": "code", "execution_count": 8, "id": "eb10c7cd-02e8-4bb5-952e-a4e081606a78", "metadata": {}, "outputs": [], "source": [ "ds = xr.Dataset({'ty_trans': ty_trans, 'pot_rho_2': pot_rho_2}) \n", "grid = xgcm.Grid(ds, coords = {'Y': {'center': 'yt_ocean', 'right': 'yu_ocean'}}, periodic = False)\n", "\n", "# interpolate density (t-grid) to ty_trans grid (xt_ocean and yu_ocean)\n", "pot_rho_2 = grid.interp(pot_rho_2, 'Y', boundary = 'extend')" ] }, { "cell_type": "markdown", "id": "71635773-a64f-4803-b842-4184be71d4e3", "metadata": {}, "source": [ "## Method 1: `xhistogram`\n", "\n", "We use xhistogram, described in https://xhistogram.readthedocs.io/en/latest/. It is a xarray aware method for computing histograms.\n", "\n", "Computation in xhistogram occurs via the same method as in MOM5 online binning. It is thus most appropriate for an comparisons between offline and online binned quantities.\n", "\n", "### First, we define the edges of the target bins\n", "Output will be an array with coordinate density the linear centre of these bins. If we choose `potrho_edges`, the end result will have coordinates potrho, which is the same as online binned `ty_trans_rho`." ] }, { "cell_type": "code", "execution_count": 9, "id": "e514b3bf-dd47-4c36-a28e-ff002c2843c6", "metadata": {}, "outputs": [], "source": [ "targetbins = cc.querying.getvar(experiment, 'potrho_edges', session, start_time = start_time, end_time = end_time,\n", " n = 1, frequency = '1 monthly').values" ] }, { "cell_type": "markdown", "id": "9b43345e-4748-45a7-afbe-3a24f3ad031c", "metadata": {}, "source": [ "### Now apply the histogram over the vertical dimension `st_ocean` inside the target bins. \n", "We include the variable we want to bin in `weights`. This quantity should be extensive, since grid cells vary in sizes, which is true because `ty_trans` is multiplied by the cell size in x and z directions." ] }, { "cell_type": "code", "execution_count": 10, "id": "66f8cc4c-a88b-4111-bed6-7b16a84d6594", "metadata": {}, "outputs": [], "source": [ "# Make sure the variables have a name, otherwise xhistogram doesn't know what to call the bins\n", "ty_trans = ty_trans.rename('ty_trans')\n", "pot_rho_2 = pot_rho_2.rename('pot_rho_2')\n", "\n", "ty_trans_mean = histogram(pot_rho_2, \n", " bins = [targetbins], \n", " dim = ['st_ocean'],\n", " weights = ty_trans).rename({pot_rho_2.name + '_bin': 'potrho',\n", " 'xt_ocean': 'grid_xt_ocean',\n", " 'yu_ocean': 'grid_yu_ocean'})" ] }, { "cell_type": "code", "execution_count": 11, "id": "5f662b5a-9f4f-4e27-b883-66f2002e10b6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 12.8 s, sys: 2.76 s, total: 15.5 s\n", "Wall time: 40.5 s\n" ] } ], "source": [ "%%time\n", "ty_trans_mean = ty_trans_mean.load()" ] }, { "cell_type": "markdown", "id": "b2d3e7bd-246a-4c25-a724-8300ff0bbdd9", "metadata": {}, "source": [ "### Now define meridional overturning streamfunctions as a cumulative sum of transport from the bottom of the ocean." ] }, { "cell_type": "code", "execution_count": 12, "id": "919e537e-c139-46ac-bfd1-b599480687f2", "metadata": {}, "outputs": [], "source": [ "def cumsum_from_bottom(residual):\n", " cumsum = residual.cumsum('potrho') - residual.sum('potrho')\n", " return cumsum" ] }, { "cell_type": "code", "execution_count": 13, "id": "380adee2-f0b2-4670-b01d-36ac7ac3cbad", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 4.4 s, sys: 928 ms, total: 5.33 s\n", "Wall time: 7.79 s\n" ] } ], "source": [ "%%time\n", "psi_avg = cumsum_from_bottom(ty_trans_rho.sum('grid_xt_ocean') / (1e6 * rho_0)).load() # .load() since we'll use it a few times in this notebook\n", "\n", "psi_avg_mean = cumsum_from_bottom(ty_trans_mean.sum('grid_xt_ocean') / (1e6 * rho_0))" ] }, { "cell_type": "markdown", "id": "4bbe9e23-c487-4769-a6d1-14f2b3096e75", "metadata": {}, "source": [ "### Plot streamfunctions of the residual, mean (what we just computed) and eddy (the difference) streamfunctions" ] }, { "cell_type": "code", "execution_count": 14, "id": "8f4ed670-6a0e-4b52-a8ec-a6cef918f0f5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 176 ms, sys: 44.4 ms, total: 220 ms\n", "Wall time: 229 ms\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%time\n", "fig, axes = plt.subplots(nrows = 1, ncols = 3, figsize = (15, 4))\n", "\n", "levels = np.linspace(-25, 25, 26)\n", "\n", "psi_avg.plot.contourf(ax = axes[0], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "psi_avg_mean.plot.contourf(ax = axes[1], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "p = (psi_avg - psi_avg_mean).plot.contourf(ax = axes[2], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "cbar_ax = fig.add_axes([0.92, 0.15, 0.01, 0.7])\n", "fig.colorbar(p, cax=cbar_ax, label='Transport (Sv)')\n", "\n", "axes[0].set_title('Residual')\n", "axes[1].set_title('Mean')\n", "axes[2].set_title('Eddy')\n", "\n", "for ax in axes:\n", " ax.set_ylim(1037.5, 1032)\n", " ax.set_xlim(-70, -35);" ] }, { "cell_type": "markdown", "id": "eaaafc08-1df8-4e26-9663-624b5fb8cf65", "metadata": {}, "source": [ "## Method 2: `xgcm`\n", "\n", "Use `xgcm` conservative binning, described in the tutorial available in `xgcm` documentation: https://xgcm.readthedocs.io/en/stable/transform.html\n", "\n", "This method results in a smoother vertical distribution than `xhistogram`, as it is not quite a histogram but does some interpolation to the top and bottom of each vertical cell. We have found that the computation currently has issues with interior land boundaries: `xgcm` isn't able to compute partial cells at the bottom of the ocean in MOM5. We thus add a correction after the computation to ensure that vertical integrals are preserved and thus that streamfunctions calculated are closed." ] }, { "cell_type": "markdown", "id": "9e46418e-89b7-449f-bab7-1f259239a55d", "metadata": {}, "source": [ "### Load vertical grid bin centres and edges" ] }, { "cell_type": "code", "execution_count": 15, "id": "964e2221-c7fa-43ec-aea7-8030eb4c9a6c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.36 s, sys: 180 ms, total: 1.54 s\n", "Wall time: 2.24 s\n" ] } ], "source": [ "%%time\n", "\n", "st_ocean = cc.querying.getvar(experiment, 'st_ocean', session, n=1)\n", "st_edges_ocean = cc.querying.getvar(experiment, 'st_edges_ocean', session, n=1)" ] }, { "cell_type": "markdown", "id": "58336fe8-d59d-4489-903a-af25ad35024a", "metadata": {}, "source": [ "### Define edge of target density bins" ] }, { "cell_type": "code", "execution_count": 16, "id": "874a9140-cbe8-49e4-a7b5-8a06aaf4b3c4", "metadata": {}, "outputs": [], "source": [ "pot_rho_2_target = cc.querying.getvar(experiment, 'potrho_edges', session, start_time = start_time, end_time = end_time,\n", " n=1, frequency = '1 monthly' ).values" ] }, { "cell_type": "markdown", "id": "93d9620f-60be-482a-932a-ebaf72524cce", "metadata": {}, "source": [ "### Calculate vertical regridding into density coordinates" ] }, { "cell_type": "code", "execution_count": 17, "id": "bac76fee-60cf-447e-8ffc-7aa443680285", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 32.9 ms, sys: 559 µs, total: 33.5 ms\n", "Wall time: 29.8 ms\n" ] } ], "source": [ "%%time\n", "\n", "ds = xr.Dataset({'ty_trans': ty_trans, 'pot_rho_2': pot_rho_2})\n", "\n", "# Note: Quantity must be extensive, e.g., ty_trans, vhrho_nt, uhrho_et, tx_trans but *not*, e.g., v, salt. \n", "# If not extensive, then we need to multiply by dzt or dzu.\n", "ds = ds.assign_coords({'st_edges_ocean': st_edges_ocean})\n", "ds = ds.chunk({'st_edges_ocean': 76, 'st_ocean': 75}) #xgcm doesn't like it if there is more than 1 chunk in this axis\n", "\n", "grid = xgcm.Grid(ds, coords={'Z': {'center': 'st_ocean', 'outer': 'st_edges_ocean'}}, periodic = False)\n", "ds['pot_rho_2_outer'] = grid.interp(ds.pot_rho_2, 'Z', boundary='extend')\n", "ds['pot_rho_2_outer'] = ds['pot_rho_2_outer'].chunk({'st_edges_ocean': 76})\n", "\n", "ty_trans_transformed_cons = grid.transform(ds.ty_trans,\n", " 'Z',\n", " pot_rho_2_target,\n", " method='conservative',\n", " target_data=ds.pot_rho_2_outer)\n", "\n", "### change name to fit previous bins because default xgcm naming is different\n", "# pot_rho_2_outer is actually the CENTRE of bins (I guess the convention was defined for linear interpolation not conservative)\n", "ty_trans_transformed_cons = ty_trans_transformed_cons.rename({'pot_rho_2_outer': 'potrho'})" ] }, { "cell_type": "code", "execution_count": 18, "id": "b1719dda-a93c-481e-b75d-a481ec7bafd0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 10.6 s, sys: 2.49 s, total: 13.1 s\n", "Wall time: 24.9 s\n" ] } ], "source": [ "%%time\n", "ty_trans_transformed_cons = ty_trans_transformed_cons.load()" ] }, { "cell_type": "markdown", "id": "10e2fd59-083b-417b-af83-812d202ce0da", "metadata": {}, "source": [ "### Now account for partial cell at bottom\n", "We do this by finding what is missing from the vertical integral (residual). This is what was in the partial cell. We then add that residual into the densest cell that currently exists in the transformed data. This is only an approximation, because the density of the partial cell may be denser than that of the cell above it. However, this correction means the vertical integral is preserved under the transformation." ] }, { "cell_type": "code", "execution_count": 19, "id": "71a9b5c8-6c18-4aed-9c3e-d23fd470f310", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 605 ms, sys: 729 ms, total: 1.33 s\n", "Wall time: 1.24 s\n" ] } ], "source": [ "%%time\n", "#find residual from vertical integral\n", "ty_trans_residual = ty_trans.sum('st_ocean') - ty_trans_transformed_cons.sum('potrho') #this is positive definite" ] }, { "cell_type": "markdown", "id": "115208ff-07d1-45f4-bcfb-6e7a0290de7a", "metadata": {}, "source": [ "### Find bottom density of `ty_trans_transformed_cons`" ] }, { "cell_type": "code", "execution_count": 20, "id": "e2d07412-6377-4fe5-be5f-530b3ea8b87d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.12 s, sys: 1.06 s, total: 2.18 s\n", "Wall time: 2.01 s\n" ] } ], "source": [ "%%time\n", "# select out bottom values:\n", "ty_trans_transformed_cons2 = ty_trans_transformed_cons.where(ty_trans_transformed_cons != 0) \n", "dens_array = ty_trans_transformed_cons2 * 0 + ty_trans_transformed_cons2.potrho # array of isopycnal value where it exists and nan elsewhere\n", "max_dens = dens_array.max(dim = 'potrho', skipna = True)" ] }, { "cell_type": "markdown", "id": "1096b59c-b87e-47cb-a291-6eb479020d5d", "metadata": {}, "source": [ "### Add residual to this bottom density in array" ] }, { "cell_type": "code", "execution_count": 21, "id": "4af3a264-5894-4d9d-afbe-7341b6697073", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.93 s, sys: 1.25 s, total: 3.17 s\n", "Wall time: 2.93 s\n" ] } ], "source": [ "%%time\n", "ty_trans_residual_array = (dens_array.where(dens_array == max_dens)*0 + 1)*ty_trans_residual\n", "ty_trans_new = ty_trans_residual_array.fillna(0)+ ty_trans_transformed_cons" ] }, { "cell_type": "code", "execution_count": 22, "id": "e33d083b-19b6-44fb-a8e5-cda294438b48", "metadata": {}, "outputs": [], "source": [ "# rename coords to match ty_trans_rho\n", "ty_trans_new = ty_trans_new.rename({'yu_ocean': 'grid_yu_ocean', 'xt_ocean': 'grid_xt_ocean'})" ] }, { "cell_type": "code", "execution_count": 23, "id": "b6547622-cbfa-436a-9a19-7eb7154838c3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 8.28 s, sys: 2.9 s, total: 11.2 s\n", "Wall time: 28 s\n" ] } ], "source": [ "%%time\n", "\n", "ty_trans_new = ty_trans_new.load()" ] }, { "cell_type": "markdown", "id": "75c9d270-47d1-45c1-8796-32944e6b2fb3", "metadata": {}, "source": [ "### Plot streamfunction of result" ] }, { "cell_type": "code", "execution_count": 24, "id": "8ea61ffe-980d-45b9-823d-2db8422ea105", "metadata": {}, "outputs": [], "source": [ "psi_avg_mean_2 = cumsum_from_bottom(ty_trans_new.sum('grid_xt_ocean') / (1e6 * rho_0))" ] }, { "cell_type": "code", "execution_count": 25, "id": "6535bf5b-83d4-40ba-8296-0618ba4366e9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 159 ms, sys: 18.7 ms, total: 178 ms\n", "Wall time: 155 ms\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%time\n", "\n", "fig, axes = plt.subplots(nrows = 1, ncols = 3, figsize = (15, 4))\n", "\n", "levels = np.linspace(-25, 25, 26)\n", "\n", "psi_avg.plot.contourf(ax = axes[0], x = 'grid_yu_ocean',levels = levels, add_colorbar = False)\n", "\n", "psi_avg_mean_2.plot.contourf(ax = axes[1], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "p = (psi_avg - psi_avg_mean_2).plot.contourf(ax = axes[2], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "cbar_ax = fig.add_axes([0.92, 0.15, 0.01, 0.7])\n", "fig.colorbar(p, cax=cbar_ax, label='Transport (Sv)')\n", "\n", "axes[0].set_title('Residual')\n", "axes[1].set_title('Mean')\n", "axes[2].set_title('Eddy')\n", "\n", "for ax in axes:\n", " ax.set_ylim(1037.5, 1032)\n", " ax.set_xlim(-70, -35);" ] }, { "cell_type": "markdown", "id": "ce8152ad-8c28-467a-b867-fe7408a01023", "metadata": { "tags": [] }, "source": [ "## Method 3: Bin `ty_trans` (mean Eulerian overturning) into density bins\n", "\n", "This uses the method by Lee et al. (2007) and which is is described as follows. Firstly, cells in the model output with a density $\\rho$ between two prescribed densities ($\\rho_\\text{heavy} >\\rho> \\rho_\\text{light}$) are selected. Each cell is assigned a proximity to the lighter density $\\rho_\\text{light}$, which is the 'bin fraction' $$f_b = \\frac{\\rho_\\text{heavy}-\\rho}{\\rho_\\text{heavy}-\\rho_\\text{light}}.$$\n", "\n", "Here, a bin fraction of 1 means the cell density $\\rho = \\rho_\\text{light}$ and $f_b=0$ means $\\rho = \\rho_\\text{heavy}$. The quantity being binned, such as the meridional transport $vh$, is then multiplied by $f_b$ and added to the lighter density $\\rho_\\text{light}$ bin's meridional transport, followed by the $vh(1-f_b)$ being added to the heavier bin, $\\rho_\\text{heavy}$. This process is repeated for all sets of consecutive bins, meaning that density bins have input from model output cells with density slightly lower and higher than it. \n", "\n", "> Lee, M., Nurser, A., Coward, A., and De Cuevas, B. (2007). [Eddy advective and diffusive\n", "transports of heat and salt in the Southern Ocean.](https://doi.org/10.1175/JPO3057.1) _Journal of Physical Oceanography_, **37(5)**, 1376–1393." ] }, { "cell_type": "markdown", "id": "063607a5-1bd7-4c8f-8cc1-0d89bf2f02d0", "metadata": {}, "source": [ "### For this method, we need to get rid of NaNs" ] }, { "cell_type": "code", "execution_count": 26, "id": "fed405b2-ff26-47cc-96d5-e8326aeafa57", "metadata": {}, "outputs": [], "source": [ "ty_trans = ty_trans.fillna(0)\n", "pot_rho_2 = pot_rho_2.fillna(0)" ] }, { "cell_type": "markdown", "id": "1645e9d1-f09f-4e3e-b087-383ec4bfb6a6", "metadata": { "tags": [] }, "source": [ "### Load first to reduce computation time" ] }, { "cell_type": "code", "execution_count": 27, "id": "e105a23e-9179-4e73-aa26-93d1dd1056f9", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 9.4 s, sys: 2.98 s, total: 12.4 s\n", "Wall time: 18.4 s\n" ] } ], "source": [ "%%time\n", "pot_rho_2 = pot_rho_2.load()\n", "ty_trans = ty_trans.load()" ] }, { "cell_type": "code", "execution_count": 28, "id": "bdb54ac7-92e9-48f3-b20a-d07810f2625d", "metadata": {}, "outputs": [], "source": [ "# choose bins (in this case, default ty_trans_rho pot_rho_2 bins\n", "rho2_bins = ty_trans_rho.potrho.values\n", "\n", "# set up a zero array to be filled in by the algorithm\n", "ty_trans_binned = np.zeros((len(rho2_bins), len(pot_rho_2.yu_ocean), len(pot_rho_2.xt_ocean)))" ] }, { "cell_type": "markdown", "id": "e830e801-f679-4630-af97-814159fa59d3", "metadata": {}, "source": [ "**Note**: the following cell takes a while." ] }, { "cell_type": "code", "execution_count": 29, "id": "42324e61-50c2-4cb7-8ed3-b9533ab0f4a3", "metadata": { "tags": [] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "dbec20d9ccfa44b389b4bb738efae259", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/79 [00:00 rho2_bins[i])*0 + 1\n", " bin_fractions = (rho2_bins[i+1] - pot_rho_2 * bin_mask)/(rho2_bins[i+1] - rho2_bins[i])\n", " ## bin ty_trans:\n", " ty_trans_in_lower_bin = (ty_trans * bin_mask * bin_fractions).sum(dim = 'st_ocean')\n", " ty_trans_binned[i, :, :] += ty_trans_in_lower_bin.fillna(0).values\n", " del ty_trans_in_lower_bin\n", " ty_trans_in_upper_bin = (ty_trans * bin_mask * (1-bin_fractions)).sum(dim = 'st_ocean')\n", " ty_trans_binned[i+1, :, :] += ty_trans_in_upper_bin.fillna(0).values\n", " del ty_trans_in_upper_bin" ] }, { "cell_type": "code", "execution_count": 30, "id": "398b5155-b1f8-4da3-ad31-adfcbbd918d2", "metadata": {}, "outputs": [], "source": [ "# convert numpy array into xarray dataarray\n", "ty_trans_binned_array = xr.DataArray(ty_trans_binned, \n", " coords = [rho2_bins, pot_rho_2.yu_ocean, pot_rho_2.xt_ocean], \n", " dims = ['potrho', 'grid_yu_ocean', 'grid_xt_ocean'], \n", " name = 'ty_trans_binned')" ] }, { "cell_type": "code", "execution_count": 31, "id": "690ddd63-0ffc-497b-8dbe-bed29d59d980", "metadata": {}, "outputs": [], "source": [ "# find streamfunction\n", "psi_avg_mean_3 = cumsum_from_bottom(ty_trans_binned_array.sum('grid_xt_ocean')) / (1e6 * rho_0)" ] }, { "cell_type": "markdown", "id": "35ddc3b8-5d15-413e-8cb6-d5e8073841f8", "metadata": {}, "source": [ "### Plot streamfunctions" ] }, { "cell_type": "code", "execution_count": 32, "id": "58a7fe12-4fcd-49ca-a553-e7f4e185212c", "metadata": {}, "outputs": [ { "data": { "image/png": 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dISIiv7GtISIiSi6hXZW+srIS27ZtQ0VFRey2rKwsnHbaaVixYoXpRURdXR0WLFiAHj16oKyszHLfVVVVaNeune3x6+vrUV9fH/u9qakJu3fvRlFRESKRiItnREREetFoFDU1NejUqRMyMoIfwMB2hogotSW6nQES29awnSEi8lcY2hnyLrTB6LZt2wAAJSUlcbeXlJTgm2++ibvtwQcfxLRp01BXV4cjjzwSS5YsQatWrUz3u3HjRvzP//wP/vjHP9oe/84778TMmTM9PAMiIhKxefNmdOnSJfDjsp0hIkoPiWpngMS2NWxniIiCkch2hrwLbTCqMX6bGY1Gm902duxYDB06FFu3bsW9996LUaNG4Z133kF2dnbcdt999x3OOussXHDBBfjVr35le9ybbroJU6dOjf1eVVWFrl27YuNna5Gfn+/xWYXD/oxs542IiBSqbmiK/X9tTQ0G9j0y4Z+pYWtnNnz5ZcJfE5WqdH9zIqIg1dbU4PijfxSKz9REtDXp0s4QEQXBeE1b0CoDNTU16FVezs/UJBfaYLS0tBTA4W9ZO3bsGLv9+++/b/aNa0FBAQoKClBeXo6TTz4Zbdu2xaJFizB69OjYNt999x2GDBmCgQMH4uGHH3Y8flZWFrKysprdnp+fjzZt2rh9WqHSksEoEQUsWt88JEvUcD62M8FoYjBKRAmWyGHjiWxr0qWdISLy296GJuQb4pM2rX4YOs/pSZJbaCdB6NGjB0pLS7FkyZLYbQ0NDVi2bBkGDRpk+9hoNBo3n86WLVswePBgHH/88ViwYAHnfiAiSoAqk1A0kdjOEBGR39jWEBElt738kj/lJbRitLa2Fhs2bIj9XllZiTVr1qBdu3bo2rUrrr32WsyePRvl5eUoLy/H7Nmz0bp1a4wZMwYA8NVXX+Gpp55CRUUFiouLsWXLFsyZMwc5OTkYPnw4gMPfqg4ePBhdu3bFvffeix07dsSOp32DS0RE/kpUKMp2hoiI/Ma2hogovRS24hdTqSShwej777+PIUOGxH7X5sAZN24cFi5ciGnTpmH//v248sorsWfPHpx00klYvHhxbP6G7OxsLF++HHPnzsWePXtQUlKCU089FStWrECHDh0AAIsXL8aGDRuwYcOGZpPhRqPRgJ4pERElAtsZIiLyG9saIqL0wVA09USibEmFVFdXo6CgAN9vrkyZOXm4+BIRBcGqWrSmphrH9uiMqqqqlPlc9UJrZ7Zv25ZSrweHHxFRotRUV6N3105sZ/5PqrYzRER+MbuO1Qej1dXVKCktZTuT5Bh1ExGRb8I2rygREaWPqvrGRJ8CERGlEFaLpib+VYmIyBcMRYmIKFH2HmAoSkRE7hmrRRmKpq6EzjFKRESph4EoERElEkNRIiIiEsXIm4iIlKiqb2IoSkRERERESU9fIcpq0dTGilEiIvKEYSgREYUFq0WJiEiVMAeiBw4cQENDg6vHtmrVCtnZXIxbw2CUiIhcYSBKRERhwlCUiIjSwYEDB1CUk4d9cNfulZaWorKykuHo/2EwSkRE0hiKEhERERERBa+hoQH70Iix6IxWkjNkNqAJj23bgoaGBgaj/4fBKBERCWMgSkREYcRqUSIiSjetkCEdjFJzDEaJiEgIQ1EiIgoaA08iIvJqb0NTqOcLpcTiO4OIiBwxFCUioqAxFCUiIlX2NrA/Q+YYjBIRkS2GokREFDSGokREpIIWiLJilKzwnUFERJb8DEWr69npJSKi5hiKEhERUVAYjBIRkSk/Q9EqhqJERERERBQAVou6d+edd+LEE09Efn4+OnTogHPOOQeff/553DYzZszAkUceidzcXLRt2xZnnHEG3nvvvQSdsTy+O4iIKFAMRYmIyAqrRYmISBUuuuTdsmXL8Nvf/hYrV67EkiVLcOjQIVRUVKCuri62Te/evTFv3jz897//xdtvv43u3bujoqICO3bsSOCZi+Oq9ERE1Ixf1aIMRYmIKAg76g6iru5Qok+DiIgoqb3yyitxvy9YsAAdOnTABx98gFNPPRUAMGbMmLht7rvvPsyfPx9r167F6aefHti5usVglIiI4jAUJSKiRGC1KBERqcJV6O1VV1fH/Z6VlYWsrCzHx1VVVQEA2rVrZ3p/Q0MDHn74YRQUFKBfv37eTzQADEaJiIiIiCihVIaiO+oOKtsXERFRWHXObonsiNxUAQeiTcABoKysLO726dOnY8aMGbaPjUajmDp1Kn7yk5/gmGOOibvvX//6Fy666CLs27cPHTt2xJIlS9C+fXupc0sUBqNERBTDalEiIiIiIkpmWrUo5xe1tnnzZrRp0yb2u0i16OTJk7F27Vq8/fbbze4bMmQI1qxZg507d+Jvf/sbRo0ahffeew8dOnRQet5+4LuEiIgAMBQlIiIiIiJKB23atIn7cQpGr7rqKrz00ktYunQpunTp0uz+3Nxc9OrVCyeffDLmz5+PFi1aYP78+X6dvlKsGCUiIt8wFCUiIiccRk9ERKqwWlStaDSKq666CosWLcKbb76JHj16CD+uvr7e57NTg8EoEVGaY6UoERERERGFkUzQyQWX1Pvtb3+Lxx9/HC+++CLy8/Oxbds2AEBBQQFycnJQV1eHWbNmYeTIkejYsSN27dqFBx98EN9++y0uuOCCBJ+9GAajRERpjKEoERElEleiJyIiK/qg0ykgZSjqj4ceeggAMHjw4LjbFyxYgPHjxyMzMxPr16/Ho48+ip07d6KoqAgnnngili9fjqOPPjoBZyyPwSgRESnFUJSIiBKBw+iJiFKHVdC5t6GJw+QDFI1Gbe/Pzs7G888/H9DZ+IPBKBFRGmKlKBERJRqrRYmIyMhN5aff1aJWYWwVq1RTAmN2IqI0w1CUiIiIiIiSlVMQqrKilEP0Ux8rRomIUphfIWjz4zAUJSIicaqrRTmMnogo+cmEkAwsSRUGo0REKSSoIDT+mO46t9tqGxSfCRERERERpSs/5x7l3Kapi8EoEVEKSEQg6sXWmvpEnwIRESUI5xYlIiIjrxWg6RhadmvdAq0zMqUes6+pETjg0wklKQajRERJLpGhqJtqUYaiRETpy00oqg2TL85taXs/EREll2QfDl+QhmFsKmIwSkSUxJItFCUiovTltVJUH4BahaRERJQckiEUTYZzJO8YjBIRJalkDEVZLUpERDKsqkFZJUpElLwYOFKYsO6XiCgJJWMoSkRE6YvzihIREeBPKJqO84uSOnz3EBGRMC+hKKtFiYhIBqtCiYgoTFjpmpo4lJ6IKMkkqlqUoSgREQWBgSgREYlitSh5xWCUiIiIiIh84zSM3q8g9LvaA77sl4iI3GHFJYURg1EiInLEalEiIlLNz8rQLTUMRYmISL29DU2sUk0xDEaJiJJIIhddcoOhKBFRejOrFuVQeSIiIgoLxtxEROQLhqJERGTEUJSIiFRh5SapwIpRIiKy5WUYPRERUdA4jJ6IKHyCml80o24XAKAptyiQ4yVS+6Ic5GZmSj2mrrER2O3TCSUpxutEREkiEcPo3YairBYlIiIjVosSEVGyY5Vq6uFflIiIlGIoSkREREREiZAOlaKkFoNRIiIyxSH0RETkhdnCS37jMHoiovRgV7nJcJRkMBglIkoCQQ+j5xB6IiJSicPoiYjSV1Dzi+ppc42qxGH0qYl/VSIiisNQlIiIkhGrRYmICPghFPUjHKXUw1XpiYjIEwaiRERERERElIwSWjH61ltvYcSIEejUqRMikQheeOGFuPuj0ShmzJiBTp06IScnB4MHD8ann34at83EiRPRs2dP5OTkoLi4GGeffTbWr18ft83IkSPRtWtXZGdno2PHjrjkkkvw3Xff+f30iIiUCHIYvWy1aNhDUbYzRESJoZ9fNNWH0bOtISIiSl4JDUbr6urQr18/zJs3z/T+u+++G/fddx/mzZuH1atXo7S0FEOHDkVNTU1smxNOOAELFizAunXr8OqrryIajaKiogKNjT9cjA0ZMgRPP/00Pv/8czz33HPYuHEjzj//fN+fHxFRMknFxZbYzhARpYdEDqNnW0NEFC5cfEktpy8AI5GI6c8999yTmBOWFIlGo9FEnwRw+IVctGgRzjnnHACHv1nt1KkTrr32Wtxwww0AgPr6epSUlGDOnDmYOHGi6X7Wrl2Lfv36YcOGDejZs6fpNi+99BLOOecc1NfXo2XLlkLnV11djYKCAny/uRJt2rSRf4IhtD8jO9GnQEQCgqgYdROKeq0WrautwXkDeqGqqiqQz9VkaWe2b9uWMu0MkJjJ9oko8YKoGHUKQ/fV1mDCT44KrJ0Bwt3WpGo7Q0Thp/p6MKhFkPTnbXbM6upqlJSWBtrOaMctKCjAovJ+yM3MlHpsXWMjfvnlx1Ln/PLLL+Odd97B8ccfj/POOy+unQOAbdu2Ndt+woQJ2LBhA4444gip80uE0M4xWllZiW3btqGioiJ2W1ZWFk477TSsWLHC9CKirq4OCxYsQI8ePVBWVma63927d+Oxxx7DoEGDbC8g6uvrUV//Q6e/urraw7MhIgqvRISih/eR2EUy2M4QEYVbKiymlMi2hu0MERFZMbYJWVlZyMrKMt122LBhGDZsmOW+SktL435/8cUXMWTIkKQIRYEQr0qvJc4lJSVxt5eUlDRLox988EHk5eUhLy8Pr7zyCpYsWYJWrVrFbXPDDTcgNzcXRUVF2LRpE1588UXb4995550oKCiI/VhdlBARpRsVoWgYOrtsZ4iI/CFTLbql5oDlj1dbqvZ73odXiWxr2M4QEakRVIWqrDZd26CgW4HUT5uuh6tEy8rK4tqIO++8U8k5bd++Hf/+978xYcIEJfsLQjj/ujqRSCTu92g02uy2sWPH4qOPPsKyZctQXl6OUaNG4cCB+Iup3/3ud/joo4+wePFiZGZm4tJLL4XdLAI33XQTqqqqYj+bN29W96SIiAT5PYw+6MWWVHV2VWI7Q0SUGH62B5v3Jj4U1UtEW8N2hoiIrGzevDmujbjpppuU7PfRRx9Ffn4+zj33XCX7C0Joh9Jrpbjbtm1Dx44dY7d///33zb5x1RLu8vJynHzyyWjbti0WLVqE0aNHx7Zp37492rdvj969e+Ooo45CWVkZVq5ciYEDB5oe366MmIgoHakIRcOE7QwRUeKErU3wSyLbGrYzRETehLVSVIU2bdr4Mi/q3//+d4wdOxbZ2cmzpk1o/8o9evRAaWkplixZErutoaEBy5Ytw6BBg2wfG41G4+bTMbsfgO02RESpTqZaVMXw+bBhO0NElJrCVC3KtoaIiNLF8uXL8fnnn+NXv/pVok9FSkIrRmtra7Fhw4bY75WVlVizZg3atWuHrl274tprr8Xs2bNRXl6O8vJyzJ49G61bt8aYMWMAAF999RWeeuopVFRUoLi4GFu2bMGcOXOQk5OD4cOHAwBWrVqFVatW4Sc/+Qnatm2Lr776Crfddht69uxpWcVDRBQGQaxGLyKZ5xRlO0NERH5jW0NERATMnz8fJ5xwAvr165foU5EiFIy6WcFQpCT3/fffx5AhQ2K/T506FQAwbtw4LFy4ENOmTcP+/ftx5ZVXYs+ePTjppJOwePFi5OfnAwCys7OxfPlyzJ07F3v27EFJSQlOPfVUrFixAh06dAAA5OTk4Pnnn8f06dNRV1eHjh074qyzzsKTTz7JoSVElLZEq0WTORQF2M4QEYVRotoF9mmIiBKjsFUG9jaEo+iD5Dl9AQgcbmOfeeYZ/PGPf0zUaboWidqtDPF/MjIymk0ObrvTSARffPEFjjjiCE8nFybV1dUoKCjA95srfZmHIRH2ZyTPnA9E6civitEgh9DbdX7319Zg8pBjUFVVlTKfq15o7cz2bdtS6vXgRTBRehFZkT6oRZcO1NXgtp8fH2tn0r1Pk6rtDBElB5XXhGGZ+7O6uholpaWB92e0z/PXT/8p8lrIDQSvPXQIp7++XOqc33zzzbgvADXaF4AA8PDDD+Paa6/F1q1bUVBQIHVOiSb8Cj777LNo166d43bRaDQ25IOIiNwJwzD6VFtsiYiIiH0aIqLw0AJOfpEeboMHD4ZTTeUVV1yBK664IqAzUksoGO3WrRtOPfVUFBUVCe30iCOOQMuWLT2dGBERqRfUEHqGokREFDbs0xARJY5xOL2+6pND7SmRhILRyspKqZ1+8sknrk6GiIgSXy3KUJSIiPwS1DB6M+zTEBElll2FKMNRSpRwTMxARES+k5lb1C2GokRE5NXmvfubhZxOoScRESWPRM8RmlG3Cxl1uxJ6DhQeUrO07tq1C2vXrkW/fv3Qrl077Ny5E/Pnz0d9fT0uuOACHHXUUX6dJxEReRDEEHqGokRE6U2/8JIZkXZCH4BahaNlhTkuzu4H7NMQEYWTaNXo3oYm6XDVLAjNqNuFplyx6VUodQkHo6tWrUJFRQWqq6tRWFiIJUuW4IILLkCLFi0QjUZx11134e2338bxxx/v5/kSEaW0RA6jdxuKMhAlIiKvZCpC9dtqIano49mnISKiVFHQpQB5reTmws5sOOjT2SQv4Yj95ptvxgUXXICqqir8/ve/xznnnIPTTz8dX3zxBb788kuMGTMGf/jDH/w8VyIickGkWpShKBERmdl7oNGxEjSRzIbd22Gfhogo/dgNm+eQehIORj/44ANMnToV+fn5uOaaa/Ddd9/h17/+dez+3/72t1i9erUvJ0lERP5hKEpERGb0gajXcNSuzQhy/lD2aYiI0otI8MlwNL0JB6MNDQ3IyTk8VKVly5Zo3bo12rdvH7u/qKgIu3bxzURE5JYfw+j9WnCJoSgRUfqxC0fdBqdBL6rEPg0RUbiJzh3KFexJFeFgtKysDF999VXs9yeffBIdO3aM/b5169a4iwoiIgo/N9WiDEWJiEgFq1D0m537fDsm+zREROlDphKUVaPpSzgYveiii/D999/Hfv/5z38e+7YVAF566SX8+Mc/Vnt2RETkG4aiREQky2zOUZVzkGqhqF/hKPs0REREpCe8Kv306dNt77/55puRmZnp+YSIiCicGIoSEaWvwmy56/wddT+semvWfqgcQl9WmCO8P/ZpiIjCjUPkKWjCwaiT1q1bq9oVERERERGFhFUo6udq9d3ai/UtygpzYv9VEbayT0NElJ6acoss79PCWtH5Tym5SP9V9UNPiIgovPxaeImIiMgPssPntVDU6nc77NMQEYVPoqpF7UJRSn1SwWhlZSV+8pOf+HUuREQUEDfzixIRUfqRHUKvgki1qFUIqr+9c4H5NuzTEBElhl3w6UcoqiLw1J+X8RyrOOw/JQgHo5988gl++tOfYvz48T6eDhERhRHnFyUiSj+JCEVVsQpO2achIkqsZJ9DdG9DU+yHUoPQHKMrVqzAL37xC/zmN7/B73//e7/PiYiIiIiIyBWrUJR9GiIiMhKZWzSscju2R152K6nHRA80+HQ2yUsoGK2oqMCECRMwa9Ysv8+HiChtFWRloKo+fI0vq0WJiCgIsgsuyWKfhoiIiIyEhtLn5uZi69atiEajfp8PEREpwIWXiIgozNyGm16wT0NEFA7GoehuKzO9VnRy0SUCBIPRt99+G++//z4uu+wyv8+HiCitFWRJrYnnChdeIiKiZOUlUGWfhogoccxCzCDm6mzKLWoWgJrdRulLqAdeXl6Ot99+Gx988AF++9vf+n1OREQUEhxGT0REfnEKOcsKc+K28Vplyj4NEVH60sJQ0UA07POLkjrCpUmdOnXCW2+9hY8++sjP8yEiIiIiojRhFXYaA1FVQ+/ZpyEiCp6fISMDTPJKaPElTdu2bfH666/7dS5ERATvizBxflEiIgpKYXYmAGDvAfdtT9DzjbJPQ0QUTnsPNMbaFan7GppQ2Mr/KckoNUm/c3Jygp8onYgo3fg116jM/KIcRk9ERKKsOqthxT4NEVG4iHzBZreNm8pRbY5T42NZhRrvrbfewogRI9CpUydEIhG88MILcfc///zzOPPMM9G+fXtEIhGsWbMmIefplqeed21tLaqrq+N+iIiIiIgo9YmGoZ3zs30+E2/YpyEi8o+KkFF0VILoYk4MQ+XU1dWhX79+mDdvnuX9p5xyCu66666Az0wNqaH0AFBZWYnJkyfjzTffxIEDP1QTRaNRRCIRNDZyCCcRUaJwGD0RESVKYXZmrPNanNsSO+oOxu7rnJ8dqpEI7NMQEYWHzHQsdkPqHR/rEH4yHDU3bNgwDBs2zPL+Sy65BADw9ddfB3RGakkHo2PHjgUA/P3vf0dJSQkikYjykyIiIiIiIvIL+zRERP5zNbzdEHx6mcPa67mkMuPoiKysLGRlZSXobBJLOhhdu3YtPvjgA/zoRz/y43yIiCgEwlTVQ0REyUNfNRpm7NMQEflLNIj0o80wLsaUqqFoXlkH5OfIhZnR/YfXnCgrK4u7ffr06ZgxY4aqU0sq0sHoiSeeiM2bN/MigogoZDiMnoiIZAXZcVQ9nF6bu9TNPtmnISJKPKdQ1Op+meH0qRqKerV582a0adMm9nu6VosCLoLRRx55BJMmTcKWLVtwzDHHoGXLlnH39+3bV9nJERERERGRP/ShqPa71oFUEZga5xn1i5vAlX0aIiJKZ23atIkLRtOZdDC6Y8cObNy4EZdddlnstkgkwonKiYiSQMf8LGytqU/0aRARUYIZQ1Gn26X2HcBweq8r3bNPQ0SUWF7bCaeqUVaKkijpYPTyyy9H//798cQTT3CiciKikFA5jJ7zixIRkZ6+kjRVsE9DROQfL22GFnYag9MddQdRnBtf3e9lhXoSV1tbiw0bNsR+r6ysxJo1a9CuXTt07doVu3fvxqZNm/Ddd98BAD7//HMAQGlpKUpLSxNyzjKkg9FvvvkGL730Enr16uXH+RARkY9YLUpERHZUDqUPM/ZpiIjCLVkW80sH77//PoYMGRL7ferUqQCAcePGYeHChXjppZfiRmBcdNFFAJJnQSfpYPRnP/sZPv74Y15EEBGlKNWLYxARUfLxKwwNSxvDPg0RkXp+f5FmVjVK/hs8eDCi0ajl/ePHj8f48eODOyHFpIPRESNGYMqUKfjvf/+LY489ttlE5SNHjlR2ckRE6aqqXvyigqvRExFROnMTtLJPQ0SklmwoalYRKjssnsPoSQXpYHTSpEkAgNtvv73ZfZyonIgo9WkLXoSh4oeIiORZLbAU1JD5MFSNsk9DRBQeDDgpkaSD0aam1JtjiIiInBlXAA5Dx5aIiJKbvm0Jsk1hn4aIKBwYilKimX9dbGLMmDF4+umnUVNT4+f5EBFRyHTOz24WiurvIyKi9GG2EEZhqwzLKlQrZm2L6jZlS9X+ZrexT0NEpJ7bEQduQtEddQddHYvIivAVzI9+9CPMmTMHxcXFqKiowJ///Gds3rzZz3MjIqIE0TqnDD6JiJKDFk46hZSyAaZeGFcHtqoy3by3eSgKsE9DROTV3oYm6SA0jO1HKmhV0gmtOnaR+ynplOjTDh3hK6Pp06fjgw8+wIYNG3DOOefgpZdeQnl5OY4//njMmDEDH330kZ/nSUREJvxceImhKBFRcjALO70EoLLcdJKtiLY9dsPurUJRgH0aIiJVtM/+oOanJvKL9BVTly5dcOWVV+LVV1/Fjh07cOONN+LLL7/E6aefjm7dumHy5Mn49NNP/ThXIiIiIiLScaoO1VeQBhmWemE3hYuelzlJ2achIpIXhhC0OLdlok+BUoynq6P8/HyMGjUKjz32GHbs2IG///3vyMzMxLvvvqvq/IiIKEVt2cuFm4iI3JKd19NpW6fObioPg2SfhojIP6ncflBqkF6V3kpmZiZOP/10nH766ap2SURECm2tqU/0KcR8u8d6mCMREdlLlspPrzrnZwe6Uj3APg0RkZUwVIsSff3111i+fDm+/vpr7Nu3D8XFxejfvz8GDhyI7Gx3U8FJB6P9+/dHJBJpdnskEkF2djZ69eqF8ePHY8iQIa5OiIiIiIiImktUIOq22icRKwfbzS+qxz4NEZE4t6Eoq0VJlccffxwPPPAAVq1ahQ4dOqBz587IycnB7t27sXHjRmRnZ2Ps2LG44YYb0K1bN6l9S19dnXXWWfjqq6+Qm5uLIUOGYPDgwcjLy8PGjRtx4oknYuvWrTjjjDPw4osvyu6aiIgk+LnwEhERhYPISvNhkwwdYfZpiIjEsFKUEu3444/Hfffdh4svvhhff/01tm3bhg8++ABvv/02PvvsM1RXV+PFF19EU1MTBgwYgGeeeUZq/9JXWDt37sR1112H5cuX449//CPuu+8+vPXWW7j++utRV1eHxYsX45ZbbsEf/vAHx3299dZbGDFiBDp16oRIJIIXXngh7v5oNIoZM2agU6dOyMnJweDBg5tNgj5x4kT07NkTOTk5KC4uxtlnn43169ebHq++vh7HHXccIpEI1qxZI/vUiYjIhOzq9UEOo2c7Q0TJKtnC0GTDPg0RkT2vK87rvyQrzM70fD7FuS3jFl5SsU9KDn/4wx/w/vvvY/LkyejatWuz+7OysjB48GD85S9/wbp169C9e3ep/UtfbT399NMYPXp0s9svuugiPP300wCA0aNH4/PPP3fcV11dHfr164d58+aZ3n/33Xfjvvvuw7x587B69WqUlpZi6NChqKmpiW1zwgknYMGCBVi3bh1effVVRKNRVFRUoLGx+TfV06ZNQ6dOnUSfKhERKRb03KJsZ4goGYUpEE1k9aef84uyT0NERJQcfv7znwtv2759e5x44olS+5eeYzQ7OxsrVqxAr1694m5fsWJFbKLTpqYmZGVlOe5r2LBhGDZsmOl90WgUc+fOxc0334xzzz0XAPDoo4+ipKQEjz/+OCZOnAgAuOKKK2KP6d69O+644w7069cPX3/9NXr27Bm77+WXX8bixYvx3HPP4eWXX5Z70kREAaqq53AVVdjOEFGyCVMomsrYpyEiIko+Q4YMwcUXX4zzzz8fBQUFSvYpHYxeddVVmDRpEj744AOceOKJiEQiWLVqFR555BH8/ve/BwC8+uqr6N+/v6cTq6ysxLZt21BRURG7LSsrC6eddhpWrFgRu4jQq6urw4IFC9CjRw+UlZXFbt++fTt+/etf44UXXkDr1q2Fjl9fX4/6+h9WcK6urvbwbIiIKGwr0bOdIaKwYSj6A79Xo0+HPg3bGSJyi/OKUlgde+yxuOWWWzB58mQMHz4cl1xyCYYPH45WrVq53qf01dctt9yCv/3tb1i1ahWuvvpqXHXVVVi1ahX+9re/4eabbwYATJo0Cf/85z9dnxQAbNu2DQBQUlISd3tJSUnsPs2DDz6IvLw85OXl4ZVXXsGSJUtiL0o0GsX48eMxadIkDBgwQPj4d955JwoKCmI/+osSIiJKfmxniChMEhmKynaAw7q4kuiK9EB69GnYzhCRE7N5RFWHopwL1D8t2ndCi+LOcj/tk3sqlgceeABbtmzBiy++iPz8fIwbNw6lpaW44oorsGzZMlf7dHUFNnbsWLz77rvYvXs3du/ejXfffRdjxoxBNBoFAOTk5MSGoHgViUTifo9Go81uGzt2LD766CMsW7YM5eXlGDVqFA4cOPwt8//8z/+guroaN910k9Rxb7rpJlRVVcV+Nm/e7O2JEBGlsbBVi+qxnSGiRAtrpWiiAlC/q0U1qd6nYTtDRHb0AagWkLJSlJJBRkYGKioqsHDhQmzfvh1//etfsWrVKvzsZz9ztz/ZB9x5552mtzc2NmLMmDGuTsJMaWkpADT7JvX7779v9o1rQUEBysvLceqpp+LZZ5/F+vXrsWjRIgDAG2+8gZUrVyIrKwstWrSIzSM0YMAAjBs3zvL4WVlZaNOmTdwPERGlDrYzRBQGYQ1FU1069GnYzhCRFb8DUO2LNb+qRVmFSsDhtvUvf/kL5syZg7Vr10qN3tOTvhKbO3cuHn744bjbGhsbcdFFF2HNmjWuTsJMjx49UFpaiiVLlsRua2howLJlyzBo0CDbx0aj0dh8Og888AA+/vhjrFmzBmvWrMF//vMfAMBTTz2FWbNmKTtfIiIV/Fx4qWO+8wIS6YTtDBElWpChaKoMl1eFfRoiSldBVIWGPbgsbJUR90PJo7q6GgsWLMDQoUNRVlaGhx56CCNGjMAXX3yB9957z9U+pRdf+s9//oMzzjgDhYWFGDVqFA4ePIgLL7wQ69evx9KlS6X2VVtbiw0bNsR+r6ysxJo1a9CuXTt07doV1157LWbPno3y8nKUl5dj9uzZaN26dexb3K+++gpPPfUUKioqUFxcjC1btmDOnDnIycnB8OHDAQBdu3aNO2ZeXh4AoGfPnujSpYvs0yciSmr6cHRrTb3Nluokchg92xkiCit2xBKLfRoiSkccKm/e/ha2yuBrkyRKSkrQtm1bjBo1CrNnz8aJJ57oeZ/SwegJJ5yARYsW4eyzz0ZWVhbmz5+PjRs3YunSpc2Ggzh5//33MWTIkNjvU6dOBQCMGzcOCxcuxLRp07B//35ceeWV2LNnD0466SQsXrwY+fn5AIDs7GwsX74cc+fOxZ49e1BSUoJTTz0VK1asQIcOHWSfGhGRJzlNP8yJtj9DzZxkVqrqvVfyGCtIgwpKg8R2hojCKEyhqJ8dweLclthRd9C3/dv5Zuc+NOyz/mKOfRoiIn+FvWqUktOLL76IM844AxkZ6q6lIlFtdnFJL730Es477zwcddRReOONN9C+fXtlJxVG1dXVKCgowPebK1Nmfh6/gxuidKEPRPXc/BsTHUqvIhi1IhuQOi2SYVUxeqCuFnf+cgCqqqpS5nPVC62d2b5tW0q9Hvz2nSheIkJR7d+h2bHN/o06DaN36uwaHy8TjnpZeElblf6bnfsAAA37avG3S0+xbWfSqU+Tqu0MEYlLtusyq/bIbejq1AbLvj411dXo3bVT4P0Z7fN815tPo01ea7nH1u5D0eBRKdMHW7ZsGerq6jBw4EC0bdvW1T6EKkbPPfdc09uLi4tRWFiIK664Inbb888/7+pEiIiSkVUomsw65mcpqx4N82r0RESpIqNuF5pyixJ9GjGF2Zlxndni3JYA5AJSP7BPQ0TpLNlCUSK9e+65B7W1tZg5cyaAw/NwDxs2DIsXLwYAdOjQAa+//jqOPvpo6X0LfWVdUFBg+nPmmWeiZ8+ecbcREVHyC2Khps279/l+DCKiMPGjWjSjblfsv9r/iwq6k6wFpH7QqkXtsE9DROSPZFjEyO35pfpihE5mzJiBSCQS91NaWhr4eTzxxBPo06dP7Pdnn30Wb731FpYvX46dO3diwIABsdBUllDF6IIFC1ztnIgoVYlUiuY0HUjqKSu8Vo7aVYt+s4uhKBGlFz9DURLDPg0Rpat0rBbV2l0Vz33vgca0njP16KOPxmuvvRb7PTMz+NeisrISffv2jf3+n//8B+eddx5OOeUUAMAtt9yCCy64wNW+pRdfIiKixCvIyvR1nlE/MRQlonQThioa4zlYdRTtKmPSuVNIRETJQ9/mccV571q0aJGQKlG9gwcPIivrh1GN7777Lq655prY7506dcLOnTtd7VvoKu3444/Hnj17hHf6k5/8BFu2bHF1QkREYZbTdEBqXlHZOUgLssQ7zwVZyddBZShKRKSO6LyiKoLZZAlFtYWXzLBPQ0Tkj70NTQwfk0x1dXXcT3299UjBL7/8Ep06dUKPHj1w0UUX4auvvgrwTA/r1asX3nrrLQDApk2b8MUXX+C0006L3f/tt9+iqMjdfOtCFaNr1qzBxx9/jHbt2gntdM2aNbYvKhFR2JgFmKqGwfs5pN4sHA2yktTL6sFEROkgyGpRPxZgCjIQ9btNYZ+GiNKRVWBp1j6lQrhp9rzCMHLDD5F2HRHJz5N7TKtaAEBZWVnc7dOnT8eMGTOabX/SSSfhH//4B3r37o3t27fjjjvuwKBBg/Dpp5+6DiLd+M1vfoPJkydj+fLlWLlyJQYOHBg35+gbb7yB/v37u9q38FD6008/HdFoVGjbSCTi6mSIiILkVM2p3a+Fml5WoA9yvlEtLE3kUHuz+UVZLUpE6SaIjphfq9HLBKL65xn2TjX7NEREqRsUkrjNmzejTZs2sd/1w9T1hg0bFvv/Y489FgMHDkTPnj3x6KOPYurUqb6fp2bixIlo0aIF/vWvf+HUU0/F9OnT4+7/7rvvcPnll7vat1AwWllZKb3jLl26SD+GiCgofg6HD4tEV5MSEaWzZO50ug1Fjfswzle6o+6gp/Pyin0aIiJ7YZqPU3Q1+GRubxOpTZs2ccGoqNzcXBx77LH48ssvfTgrexMmTMCECRNM73vwwQdd71coGO3WrZvrAxARhUkiQ84wrFIfhmpSIqJUlG4dM8tANAGd6s17m49SMMM+DRERkTf19fVYt24dfvrTnwZ2zLq6OuTm5vq2fXpdwRFRWgtD5WcYzgFQs3CT1VxwHEZPROkmlUJRkWrRVHq+RESpzOyLqlT6DE+l5xJW119/PZYtW4bKykq89957OP/881FdXY1x48YFdg69evXC7Nmz8d1331luE41GsWTJEgwbNgwPPPCA1P6F5xil1BOG6jWiIIQljBRVkJWBqvpwDGEhIiLSC7oTqlWDlhXmSD3uqx21OLi/zo9TIiJKGm4+s+0q/7X9hWW4Pfnv22+/xejRo7Fz504UFxfj5JNPxsqVKwMdhfHmm2/illtuwcyZM3HcccdhwIAB6NSpE7Kzs7Fnzx589tlnePfdd9GyZUvcdNNNuOKKK6T2z2CUiFJasoWimiDC0YKsTA6pJyLyIJkrVdwMeff6fItzW7qeZ3Tz3v2m4ah+GP03Ozk6gYhIBX0bkcxtnWZvQ1NKPI9EePLJJxN9CvjRj36EZ555Bt9++y2eeeYZvPXWW1ixYgX279+P9u3bo3///vjb3/6G4cOHIyND/u/MYJSIUlKYA1HRau1EV45uram3vM9qGL0ZDqMnolSSrh2rRDxv49yhbqtHiYhIXqLbO7NF/LTbw6IgTa8JEqVLly6YMmUKpkyZonS/0n/F8ePH46233lJ6EkREKoU5FJVVkJWBgiz7j2ptG6ftgmA2vygRUbIrbJUR+0lHYXvem/fuj/2Y+WpHreM+2KchInIvbO2CHa3ylcP/yYr0u7mmpgYVFRUoLy/H7NmzsWXLFj/Oi4hISk7TgdhPMpA9T334afwx285PMtWiRETJLpk6f7JEnluinr/oSvNusU9DRBR+QVeHWrV5YapSJfWkr3See+45bNmyBZMnT8YzzzyD7t27Y9iwYXj22Wdx8KC7OYOIiLxIljA0SKJVpCpWp7djN4x+M4fYE1GIpUuFqGUnMMWfP/s0RETeBNVGWIWSVsfXV4aySpREuHonFxUV4ZprrsFHH32EVatWoVevXrjkkkvQqVMnTJkyBV9++aXq8yQiaiaZKkQTSWUFqV21qMww+m92iq0UvHHjRlx11VU444wzMHToUFx99dXYuHGj8HGIiMiZvnPpdyBanNvSl/26WXiJfRoiIm/C/CWaWSiaakFpY14RGvPaS/4UJfq0Q8fTO3jr1q1YvHgxFi9ejMzMTAwfPhyffvop+vTpg/vvv1/VORIRxUmVQDTI5yAbjtotvOSVaCj66quvok+fPli1ahX69u2LY445Bu+99x6OPvpoLFmyxLfzIyIKayfPT2Hu3MoQmV/UiH0aIqLUwPlEU9+mTZsQjUab3R6NRrFp0yZX+5Relf7gwYN46aWXsGDBAixevBh9+/bFlClTMHbsWOTn5wMAnnzySfzmN79RvlIUEaW3VAhDjURXqA8DFdWioqEoANx4442YMmUK7rrrrma333DDDRg6dKjwvoiIRCVDOJhRtyv2/025rPxwg30aIiLvGEBS0Hr06IGtW7eiQ4cOcbfv3r0bPXr0QGNjo/Q+pYPRjh07oqmpCaNHj8aqVatw3HHHNdvmzDPPRGFhofTJEBEZpWIYapRM4agMu/lFRaxbtw5PP/10s9svv/xyzJ0719O+iYiSkT4Q1d/mFI4mW5Dq98JLAPs0REReuA1EjV8+JkOwyoWXwiUajSISiTS7vba2FtnZ7vrU0sHo/fffjwsuuMD2gG3btkVlZaWrEyIi0qRDKKrRP1enkNTqdUlUuOpHtSgAFBcXY82aNSgvL4+7fc2aNc2+ISQiUiHM1aJmoaj+PqvA0/g4kSA12biZX5R9GiKiYJm1sdptyRCQmqlK0vNORlOnTgUARCIR3HrrrWjdunXsvsbGRrz33numX3KKkA5Gly5dinPOOafZRURdXR2uuuoq/P3vf3d1IkREmnQKRM24ff7a4/wISO2G0fvl17/+Na644gp89dVXGDRoECKRCN5++23MmTMH1113XeDnQ0SpS1UgagwhVQWQdqGofpum3CLhbQG155dsYSv7NESUiszagDB8Pju1s4WtMpI2HKVgfPTRRwAOV4z+97//RatWrWL3tWrVCv369cP111/vat+RqNmspTYyMzNNx/Pv3LkTpaWlOHTokKsTCbvq6moUFBTg+82VaNOmTaJPR5lUHL5LySsMgWimycVEYwguJmRZ/duuqm9+wVFVHz8Pi9nCS1bBqF21qHEovbFi9ND+OiybdhaqqqpMP1ej0Sjmzp2LP/7xj/juu+8AAJ06dcLvfvc7XH311aZDKJKZ1s5s37YtpdoZXuRSmKmsEPWzMyoSdrrl9RzNhunHFr84YD7P1466g81u07czZkPpv9m5D93at252u3Yf0HzhpYP76/Da1ArTdiYd+zSp2s4Q0Q9UtUX66zcVw99F21urfevbE/3Qdjfn5nQuMs+vproavbt2suzP+EX7PN/x1Wdo83/zYgs/tqYGxUf0CfycVRk/fjz+53/+JzYfuArCFaPV1dWIRqOIRqOoqamJ+3a1sbER//nPfzi0MQml6tyGlDzCGoY63Z+MYWmQnEJREZFIBFOmTMGUKVNQU1MDAEobQCJKb0EMm1dRSelnKKrtX+Ycg64O1Q+TNwtHrYbR7965D4cONL+PfRoiSlVW7YXXz+29DU2BTTUThsrRMJwDmTt06BD+93//F9dffz2OOeYYZfsVDkYLCwsRiUQQiUTQu3fvZvdHIhHMnDlT2YkRUWpLhkDU6bFW4ai231QJT91Ui6rGQJSIVPCrY6civPQ7AFVBO0eZYfuq6cNRN3OLsk9DRGTPLBT0EhQGFaoyzEx9LVq0QLdu3VytPG+7X9ENly5dimg0ip/97Gd47rnn0K5du9h9rVq1Qrdu3dCpUyelJ0dEqSlRoaiXINTN/sIWkIoMo1fB62r0mu3bt+P666/H66+/ju+//x7GmV9UN4hElNrCGoqGIRCVXdneT/ph9FbBp1MgutvmfvZpiCjdhGGOUSJVbrnlFtx000343//937g23AvhYPS0004DAFRWVqJr164pN7cbEfkvkVWiqkNR2WOHJRxVRaZa1GoYffVu+47t+PHjsWnTJtx6663o2LEj2x0iChXRoFBmxXhRmbU7Y//fmNdeanvRx6Qq9mmIiIiS1wMPPIANGzagU6dO6NatG3Jzc+Pu//DDD6X3KRSMrl27FscccwwyMjJQVVWF//73v5bb9u3bV/okiCj1pUqVaLISrRY1W3gpUd5++20sX74cxx13XKJPhYiSnN+LLCWSU0hqDEW124zb+hHgmnFaeMkt48JLZtinIaJUpfJzOuxzbO490BhbgEmb/zTM5+unptbt0JQrt4BSU2NLn84mGOecc47yfQoFo8cddxy2bduGDh064LjjjkMkEmk2pBE4PCcPhzYSkVEiQtGwBaIiVaNO55yIqlPZzqroMPoqge3KyspM2xoiIlGqh8+77XiahY4qqkVl7jPbNsyVo27mD3XCPg0RpZtUGEavX5He9P40DUXT1fTp05XvUygYraysRHFxcez/KbVwZXryU9ChaNgCUT2rOUdFz9m4nZeg1Eu1qNdFl0RCUQCYO3cubrzxRvz1r39F9+7dPR2TiNKLH/OJqphLVKSDmshh7zIrF4etclYE+zRERD/QAkU/F0cKauElSj8ffPAB1q1bh0gkgj59+qB///6u9yUUjHbr1s30/4mI7AQZioY5EDVSda6ic5eaDaP3g1m1qNX8olbatm0bN99bXV0devbsidatW6Nly/hhH7t373Z3okSU0sIYioruT3TYe5D8Hkavp194SYZ+GL3dwkvs0xBRKpL9nParwlI/xN31Pnyu/mRQm/y+//57XHTRRXjzzTdRWFiIaDSKqqoqDBkyBE8++WTsC1AZwosvaR599FG0b98eP//5zwEA06ZNw8MPP4w+ffrgiSee4EUGEQEILhRNpkA0LESrRVXM+dbs2A7VonPnzlV+TCJKH2EZOu9mf6qGyMvwM3TVD320C0T9aGtEsE9DRKlOdASANk8nUTK46qqrUF1djU8//RRHHXUUAOCzzz7DuHHjcPXVV+OJJ56Q3qd0MDp79mw89NBDAIB3330X8+bNw9y5c/Gvf/0LU6ZMwfPPPy99EpR4HE5PKvkdijIMtefnv2WrYfSic4s6GTduHADg4MGDuOKKK3DrrbfiiCOOULJvIkpNfnXmghoq7lfoqRfdtSXu90hRZ+HHNuUWmb4WWofb6XVyqhI148f8okbs0xBRqrD6nCZKRa+88gpee+21WCgKAH369MGf//xnVFRUuNqndDC6efNm9OrVCwDwwgsv4Pzzz8cVV1yBU045BYMHD3Z1EhQODEdJBb9C0bCHoTLzsgXJOIzeS7Wo17lFAaCgqLXQHKMtW7bEokWLcOutt3o+JhGlrnQNRY1Bp5EWfDptJ8rY6da3d17avqBWozfDPg0RkTkuZkRh1tTU1GyKNeBw/7Gpyd17V/pqMi8vD7t2Hb4wWrx4Mc444wwAQHZ2Nvbv995pJqLk5Ucomlm3KxShaEbdLtsfq238JLv4kpcFl+xYVYvKzi9q9Mtf/hIvvPCCp30QUWoqbJXh21yifqwWH7Tori22oaibwLQptyj2Y0e0Q20MRUXmF/1qR22zH7fYpyEiIlJv1qxZGDRoEFq3bo3CwkLl+//Zz36Ga665Bt99913sti1btmDKlCk4/fTTXe1TumJ06NCh+NWvfoX+/fvjiy++iM3L8+mnn3LV4BTAqlFyS2UoGnQQ6meAaVdJandctxU4Mv9+rUJRv6pFZfXq1Qt/+MMfsGLFCpxwwgnIzc2Nu//qq68O/JyIKPHCViWqD0T1/+80d6ebIFVVBajxPPyaZ9TNMHoroiFou/atbRdg0rBPQ0QkT8UCS3YKW2WwYjXJNTQ04IILLsDAgQMxf/585fufN28ezj77bHTv3h1lZWWIRCLYtGkTjj32WPzv//6vq31KB6N//vOfccstt2Dz5s147rnnUFR0uPP+wQcfYPTo0a5OgoiSW7KGokENldSOIzP/j4qh+fph9GbVoiq4mVtUG07fpl1r2+0eeeQRFBYW4oMPPsAHH3wQd18kEmEwSkRKiH4uywaZbgNHP8JPq+PIzDUqQ7/wkgh9tajZ/KJeKkOtsE9DROSO3+FoGDCgdW/mzJkAgIULF/qy/7KyMnz44YdYsmQJ1q9fj2g0ij59+sRGfrghHYwWFhZi3rx5zW7XnjwlP1aNkgxVoWgqVYmqOqaf85Ymulq0oKg1Du23H2pfWVmp/LhElNwSsep8kEPkgwpF/eJ2GL0dN6GoSNUo+zRElEpULcCUymGgXyNOklV1dXXc71lZWcjKykrQ2cgbOnQohg4dqmRf0sEoAOzduxerVq3C999/Hze5aSQSwSWXXKLkxIgoPfgViHJlRnmyoahdtajX+UUB4Pbbb8f111+P1q3jK0v379+Pe+65B7fddpvnYxBR8nDbofHSHngNRa2G1pvt169Q9NCOH/bbotifClEv7KpFvVSKtmvfGt9/a98WsU9DRCQv1atFk0lVQxOaJMPsmv/bvqysLO726dOnY8aMGapOzVevv/467r//fqxbtw6RSARHHnkkrr32WtdVo9LB6D//+U+MHTsWdXV1yM/PRyQSid3Hiwii9OKlWjQZA1F951KEnx1Qs4WX9JXedsPoRVeh96Jb+1zP4ejMmTMxadKkZsHovn37MHPmTAajRGnETSiayEBUdJ9BV4ge2rFFadtkV1mkn1/Uqo0RWXDJi7ZF1lO2sE9DRNSc0xByv0PRVK5YDZvNmzejTZs2sd/tqkVnzJjhOKJi9erVGDBggLLzszJv3jxMmTIF559/Pq655hoAwMqVKzF8+HDcd999mDx5svQ+pYPR6667Dpdffjlmz57drLNKqYPD6cmJ21BUVSDqRwAqG3yK7k91QOoUitqRCUXdVouqEo1G4zqqmo8//hjt2rXz/fhEFA6pEIoa2QWiThWeIm1VEJWhVp1X4/yiol+8qawWFcE+DRGlGv1wepnpuMI+xLwwO1N67molxxWYZ7Qg5K+dnTZt2sQFo3YmT56Miy66yHaboBYuvPPOO3H//ffHBaBXX301TjnlFMyaNSuYYHTLli24+uqreQFBRFK8BqJ+VYKqDkPtjiHbURW9oDGGolbVoipC0SAC0bZt2yISiSASiaB3795x4WhjYyNqa2sxadIk38+DiBJPtrPmta3wMxQVqQ41tklu2yjVlaFGKip6/K4WdcI+DRGlIpH+g2NVqMKFh/Y2NIU+eCVn7du3R/v28gtK+qG6uhpnnXVWs9srKipwww03uNqndDB65pln4v3338cRRxzh6oBElPxkqkVVVIgmcyhqdjwvnVWzalErTivRhzEUBYC5c+ciGo3i8ssvx8yZM1FQUBC7r1WrVujevTsGDhwYyLkQUeIEGYp6CUT1gae2yrubIfJ+tElm+/Qamtp1lrWKHm0YfVirRQH2aYiI0gnD2eBs2rQJu3fvxqZNm9DY2Ig1a9YAAHr16oW8vDzP+x85ciQWLVqE3/3ud3G3v/jiixgxYoSrfUoHoz//+c/xu9/9Dp999hmOPfZYtGzZstlJUmrgcHoyE2QomohAtHH7Jk/7zizpKnV8mc6pyBB6fbWonrFaNKyhKACMGzcOANCjRw8MGjSoWTtDRKlPpgMThkDU7jYzQX8xJ8qu0kjlvG92Cy4FhX0aIiJrbqtG9x5oTKnFmVRWz6aL2267DY8++mjs9/79+wMAli5disGDB3ve/1FHHYVZs2bhzTffjBXLrFy5Eu+88w6uu+46PPDAA7Ftr776aqF9RqLRaFTmJDIyrC9UI5EIGhuDn/shCNXV1SgoKMD3myuF52FIBQxGSS/ZQ1E/A1E7TmGpVThq7KAag1Gzf59aMGo3hD6oUNRu8aVu7XPRsK8W/zvhVFRVVVl+rjY2NuKFF16IrTjYp08fjBw5EpmZqXPBpdHame3btqVUO8OLSXJDNBj1OxRVtTiSTBDasPXb2P+36thFyfGNtHZHq3BtzDs8PM4sGBWpEDWyqxg1DqH3s1r04P46vDa1wrSdScc+Taq2M0TJzmq4ufHzV2XVo37fVvuVvYbT2gSzYFT03EXnr5YNX728dnavQ8aBWpSUltr2Z/ygfZ5/sek75Eset6a6Gr27dgr8nFXp0aOH0HaRSARfffWV0LbS746mpibLH9kLiLfeegsjRoxAp06dEIlE8MILL8TdH41GMWPGDHTq1Ak5OTkYPHgwPv3007htJk6ciJ49eyInJwfFxcU4++yzsX79+rhtunfvHpuvTvu58cYbZZ86UVpL5lD00I4tlp3Sxu2bfA1Fg2RVLarnZqEl1bq1zxXabsOGDTjqqKNw6aWX4vnnn8ezzz6Liy++GEcffTQ2btwotA+2M4nHoUskS+Q9k1G3y1VbkVm7M/bjREUoatf+mNGHoma/By2ZQ1En7NMQUdgFcQ1ld4xUuYZLledBh1VWVgr9iIaigItgVO/AAXerUmvq6urQr18/zJs3z/T+u+++G/fddx/mzZuH1atXo7S0FEOHDkVNTU1smxNOOAELFizAunXr8OqrryIajaKioqLZBc3tt9+OrVu3xn5uueUWT+dOlE5EQ9HMul2eQlG3HV0rbgLRA1u3W/4kklO1qOgQejN+rT5vFoCKhqLA4aEPPXv2xObNm/Hhhx/io48+wqZNm9CjRw/hYRFsZ8KhsFUGL0pJiGgoKkIfgoqGoRqvoahIINqw9dtmP1bbJYLqau9EL7Zkh30aIkokp3CS11HxZKpF+bqlPm0e0z179rjeh/Qco42NjZg9ezb+8pe/YPv27fjiiy9wxBFH4NZbb0X37t0xYcIE4X0NGzYMw4YNM70vGo1i7ty5uPnmm3HuuecCAB599FGUlJTg8ccfx8SJEwEAV1xxRewx3bt3xx133IF+/frh66+/Rs+ePWP35efno7S0VPbppj3OM0oyoahbflSI2jEGoqKhp3G77I4lcidmQnQYvQyrRZdEF8FQSSYINVq2bBlWrlyJdu3axW4rKirCXXfdhVNOOUVoH2xnwoXzNJEdVaGo15XlvYSiZu2PX8Fmw9ZvXQ21V7FavVO1qJFZKJrIalGAfRoioqBCQxXHKczOtGx7/Dwuhc+1116LY489FhMmTEBjYyNOPfVUvPvuu2jdujX+9a9/uZrHVPqdMmvWLCxcuBB33303WrVqFbv92GOPxSOPPCJ9AlYqKyuxbds2VFRUxG7LysrCaaedhhUrVpg+pq6uDgsWLECPHj1QVlYWd9+cOXNQVFSE4447DrNmzUJDQ4Pt8evr61FdXR33Q5Ru/AxFterQIENRsypRL5WgohWlXofqu60WFRHkEHpZWVlZcdU0mtra2rj2xy22M0TJJcyhqFmFqF0VqCyrIfYqQ1f9F3JehtAD8V/EJaJS9IjiPBxRnIceNl/OpUOfhu0MEVkRDQ2DrlZlmElOnn32WfTr1w8A8M9//hNff/011q9fj2uvvRY333yzq31Kv+v+8Y9/4OGHH8bYsWPjFr/o27dvs3lwvNi2bRsAoKQkviKrpKQkdp/mwQcfRF5eHvLy8vDKK69gyZIlcRc411xzDZ588kksXboUkydPxty5c3HllVfaHv/OO+9EQUFB7Md4UUJEh8mEon6FoRqZxZXMwszaLTssf0TIDrlXUbVjZLXokptq0SBXojfzi1/8AldccQXee+89RKNRRKNRrFy5EpMmTVKyWjDbGaLwcOoIObUbskPlzXgJRfW8BKI1m7bHfoychtzLMi68pJEJRXfUHYz9mLEKRf2sFj2iOE9ou3To07CdISJVwhJYptKK9ypU1Tdi7wG5H6vRhcli586dsZET//nPf3DBBRegd+/emDBhAv773/+62qf0UPotW7agV69ezW5vamrCwYPmF0VeRCKRuN+j0Wiz28aOHYuhQ4di69atuPfeezFq1Ci88847yM4+XFU1ZcqU2LZ9+/ZF27Ztcf7558e+cTVz0003YerUqbHfq6ur0/ZigsPp05PMYkt2VM8ZqtGHil6HzosEn/pt8joX2257YOt2T8Ps7YbRB1UtmuhQFAAeeOABjBs3DgMHDkTLli0BAAcPHsTZZ5+NP/3pT8qOw3YmWBxOT7JEQlGvVK0+bwwtzQJOUTWbtiO/q/cpW1QxC0XNOH0RZwxFEyUd+jTp2s4QpQORVeVTjeq5Rfc2NKXNa5dKSkpK8Nlnn6Fjx4545ZVX8OCDDwIA9u3bF/dFpwzpYPToo4/G8uXL0a1bt7jbn3nmGfTv39/VSZjREuBt27ahY8eOsdu///77Zt+4at+ClpeX4+STT0bbtm2xaNEijB492nTfJ598MoDDKx5bdVizsrKQlZWl4qkQJR0VQ+hVBKJ2gafoKr92oahoJahR7ZYdvoejXjlVi3oZQv/Nzrq4uUO/2VkHwNt8omYKCwvx4osvYsOGDfjss88AAH369DHtyLrBdoYoHOw6JXZtiVMgKhJ2Roo6K59TFPAWiPrJ7UgF2XndAPEh9ImoFgXSo0/DdobIf1pAmciALUwBX7JUdGp/tzC9diTmsssuw6hRo9CxY0dEIhEMHToUAPDee+/hyCOPdLVP6WB0+vTpuOSSS7BlyxY0NTXh+eefx+eff45//OMf+Ne//uXqJMz06NEDpaWlWLJkSezipKGhAcuWLcOcOXNsHxuNRlFfb70S80cffQQAcRcnRCTHz1BUNPS047ZKVKYy1AvRzql+flGnalFVwyKcqkWNAajqQFRv/vz5uP/++/Hll18CAMrLy3HttdfiV7/6led9s50hCje/Q1GZ7czo2yp9pahZKCryhZpbbhdh0tNGKhiruWUXWUpktahMKAqwT0OUTLT2QHRxUtnt3dJ/ZgYZsImMvMmo2+X789ezai/CGjrqRzAxHE0uM2bMwDHHHIPNmzfjggsuiH0BmJmZiRtvvNHVPqWD0REjRuCpp57C7NmzEYlEcNttt+H444/HP//5z1hSK6q2thYbNmyI/V5ZWYk1a9agXbt26Nq1K6699lrMnj0b5eXlKC8vx+zZs9G6dWuMGTMGAPDVV1/hqaeeQkVFBYqLi7FlyxbMmTMHOTk5GD58OADg3XffxcqVKzFkyBAUFBRg9erVmDJlCkaOHImuXbvKPv20xeH06cOpWtRpTtFEh6JmCx05haJ2IanbjqzbatEgL2DC7tZbb8X999+Pq666CgMHDgRw+DN9ypQp+Prrr3HHHXc47oPtTDhxOD1prDoibkNRVUPi7ZjNKarRh6JWbY3qgNQuFG1R3Dl2vvov5KzmF/XCzVzWKsgGohr2aYiSh+z1cRDX02bXMUEFbMbrKLu21OtroT2nZLpuk/0bMBRNPueff36z28aNG+d6f9LBKACceeaZOPPMM10fVPP+++9jyJAhsd+1OXDGjRuHhQsXYtq0adi/fz+uvPJK7NmzByeddBIWL16M/Px8AEB2djaWL1+OuXPnYs+ePSgpKcGpp56KFStWoEOHDgAODyF56qmnMHPmTNTX16Nbt2749a9/jWnTpnk+f6JU4yUUTaVAVLXMkvgOi1m1qNlFSyKqRcPkoYcewt/+9re4IYQjR45E3759cdVVVwkFo2xnwivZLrIpOFbtSSICUbu2yW4+0aDaFxHGNscYispWi4aJ21BUwz4NEaUi1Qvdpur1GgPR5PX666/j9ddfx/fff4+mpvj359///nfp/UWi0WhU1cmlsurqahQUFOD7zZVo06ZNok8nIVgxmtoSEYr6MWQeUB+ImlX32FX8GKtF9cGom1AUiP/3Z7bgkjEY9TrHaBCLL5VkN+HOXw5AVVWV6edq27ZtsWrVKpSXl8fd/sUXX+DHP/4x9u7d6/s5BklrZ7Zv25Y27UyqXmiTGLMOiVl7omrYvAjRdkm0StSKaNWoyOJLVhWjVlO2OAWjIoGo2VB6Y1tjnGPUahi92zlGRULRhn21+Nulp1i2M+kmHdsZIj84Xb8EEbjZVYwa21IvVaMi12r6dkM/x6ib10HFtaEfr7/VeWUcqEVJaWng7Yz2eb76y83Iy5c7bm1NNU4sL0vatnHmzJm4/fbbMWDAgNg8o3qLFi2S3qdQxWjbtm2bHczK7t27pU+CiBLLywr0oqGoihDUyCkUTVSFqAzZUNSMXSgaRt2KWgMADtTZd4YvvvhiPPTQQ7jvvvvibn/44YcxduxY386PiMIjqCpRN4EoYB2KVm3a2+yxBV0LXZ2bSipCUTOJGkYvi30aIvIqnb7UlQ1FiYLwl7/8BQsXLsQll1yibJ9CwejcuXNj/79r1y7ccccdOPPMM+PmfHv11Vdx6623KjsxCh/OM5qaREJRq2pRp1DUjzAUMA9EAetQ1CoQ3ftNVbPbCrsVeDy7eMZh9HpuQlGzatFkooWioubPn4/FixfHVt5duXIlNm/ejEsvvTQ2VBFAs/CUkgOH06cvkWpRq1DUTSBq1h5pFZUibZVdIAo4h6JGfi7GBJhXi2qhqMZqCL0sP0NRfVWovrLU7RB69mmIKFVo11BO1aJ+kg1Fg1oUi1JbQ0MDBg0apHSfQsGofhLT8847D7fffjsmT54cu+3qq6/GvHnz8Nprr2HKlClKT5CIEstNKBpUdaieaChqFoYa7/cSjtotumS3Er0xEAXEQlG/5hbVB5iqhtXLhqKffPIJjj/+eADAxo0bAQDFxcUoLi7GJ598EttOtPqHiJKfXSgq2/aorhIF7EPRqk1746pG/Q5HrVgtuCTawbVakV41Y/gpG4Z2a98aB+rinxP7NETkhegXSVzl3Hl4f7Lhl/nh8atf/QqPP/640i8xpRdfevXVVzFnzpxmt5955pm48cYblZwUEQXD7RD6oEJRpzAUsJ9PNIxD5zX6b0pVhqLGYfQqKnm6FbV2DEdlQ08RS5cuVb5PCh9eaKYX0VXozapFVYaidoxBqMauShQQqxQNgptqUZmqn+LclkLhaFlhTtw8o93atzadZ1QLPLWKUK8LKnVrL9YesU9DRDKsrlXcXMcYtw9jiOrm2kw/v2hQx6T0c+DAATz88MN47bXX0LdvX7Rs2TLufjcjCaWD0aKiIixatAi/+93v4m5/4YUXUFTEkuhUx+H06cWsWtQqFPVrISUrxkAUUBOKGqtFjdU8ZtU9VlWiVosuOYWiIrxWinZpm+O4AJOeH8EnkYbhaOqz6/Q5haJWgajq0QmigSjgPRQVqRTVL7ykLbBkdY4au5EJgHW1qBed87Mtv4QzC0cB84WYggpENezTEJEKXkNR/W1hDEitqJ5bNOzXgVbnVxXy805Fa9euxXHHHQcAcaMIAfcjCaWD0ZkzZ2LChAl48803Y/PxrFy5Eq+88goeeeQRVydBROETVCgqE4YCzoGo2e8izIbP6zuuxk6s3ZB547yiVqGoFX75QOmI4WjqCnsoahY2moWhgLdAVBtG7zYUNf6/kdMq9EZeF1zS65x/uN0yC0iN4ShgH5DKkA1D9dinISInqq9LnPZnd7+xLY19hrsYtu8UxKp+3k7D6P14nVWGzGG+Pt1Zdwj7M+SmuKmrO+TT2QTDj1GF0sHo+PHjcdRRR+GBBx7A888/j2g0ij59+uCdd97BSSedpPwEicgfXlai13PqnMoGn1ZEAlGr25zIhKIi1aF6XucVBZoPo7eqFpVdjV62apSISFZYQ1G7ykunIfMar0Pn9eGnFbsgVE8kFDWuRO8Hq+pRs3AUsB5eb9zGD+zTEFEyCcu8pcmyCn1YXi9KDtLBKACcdNJJeOyxx1SfCyUJDqdPfaLVonad06ADUbvb9UQWVhINRe1WnAead1Rl5xUFxFehlw1FNV3a5gCAkoBUJmjt0jYH+1sm97eVpB6rRlNLWEJRp+HnGpFA1GsYqrUpMqGovi0xe/6ylaJ2tLlDi3NbOmxpzU04qlpZ4eG2bV8L+3aGfRoiAsxDNKfrEW17mQWZkp1oKGrX/hu/nPPzdVERjqbC3y0VrV69Gs888ww2bdqEhoaGuPuef/556f25CkaJKHV5DUVVBKJmYajGzbB5bSV6t6GoTCBq1kE1XgAYQ1GZLxpEFlxyQwtI9WRCTrv9EBHpyYaiVu2NXeDZqmMX4UAUsF5pXtWCSvrV6K2YVYca2xSnOUQ1xlDUWC1qNoxev6DSjrqDvoWjAEwDUhW0/RMRiXIzJN3t0HVVvOzP7WODrBTde6DRciEnu/tMt2flaMp58skncemll6KiogJLlixBRUUFvvzyS2zbtg2//OUvXe2TwSgRKeM1FLULRAHxUFQLQs1utwtHnUJRu7lDrXgJRUWqRVWEolb0IacxJGUASn5h1Whqc5pnzMhNKCpyv57VfKJWoWiVRRtTIPDlG/BDtajTMHmtjYkUdbasoDXjpVJUlMjK9E6LMmm8hKQMQonIC6vrDZm5Pu32rfqaJojroyCvwUwXorIJYLX73ISjQPMqX7u/Ja9Fw2v27Nm4//778dvf/hb5+fn405/+hB49emDixIno2LGjq30yGCVXOJw+OdnNK5rISlGnQBRQs8CSHZlQVLRiR2WlKOBuJXq7BTFkMAglIhEqh8+7DUVFOC2uJBuKypIJRfX/lQlINcaV6J0WXfJSKWqktUGAdTskUkXKAJSIghCmys50pG+XnMJPYxsmEpTy75EaNm7ciJ///OcAgKysLNTV1SESiWDKlCn42c9+hpkzZ0rvk8EoUYpzWmRJxerzTqGoSPBpxc0CSyJD5vVEQ1GRYfJWZENRs2rRgqzMZuFox/ysuN+tKkhFOqde2VUHEVHqcqqeMWtTEhWKiq42b0WrCtUHpE6VovrV6M3mFpWZI9QYkBqrSa2G0AP27ZVWAWoXimqdTq0zqm1rfJxVJanTF3VWVaRuQlHtWHWQq4QlovTheki5zdBsjnox15RbhIy6XZ4W/3Mayi9bRUrJq127dqipqQEAdO7cGZ988gmOPfZY7N27F/v22S/oaIXBKLnGqtFwUxWIellgyW0gatdBVVkpqg9EzX4HrENRt4Eo4H34vB0tKLUbYq8PSQHvQal+f6r3TemJHYvk4EcgCqhZdd7IKhAFmrcrIvOKioahGn370qpjF8eRB1rAqQWbxtdNH4BaDZ03Voo6EQlF9f9vDEiN+3EKSDV2c5HKMO6XiMgvZtcoWpuYitcwKuYXdeo7mR1DCzuDnN+UvHnzzTcxZMgQ0/tWrVqFE0880fMxfvrTn2LJkiU49thjMWrUKFxzzTV44403sGTJEpx++umu9ikUjJ577rnCO3SzAhQlL4aj4RNEIArYh6J+BKIqmQWgZqvPm4WiMt90ql55XkbH/Czh+UftOpN2waZIJ9Rum7oIK3nIWip2LFKJzJB5jZtQ1KlC1C7wtGPV3nhdbMlukSWrlehF5gRtzGvf7PVz2l7PuOiSDLcVOMbA1G0lqRU3QSj7NESUymTn8TaSnfPTbj+qFjxiKJpcBg0ahK1bt8bdduutt+K1117DgAEDlBxj3rx5OHDg8DXDTTfdhJYtW+Ltt9/Gueeei1tvvdXVPoWC0YICuWGpRJQYfs4hqlFdJSoahnoNTc3CULP7rEJRs0DULPi0YwxF/QhE9USqR52YDcFnVQ5RerPq7IgGooDz0HmRIfN+h6Iyw+UB61DUqlrUKRA1hpui4ahspagdYyiqX7jCbsVgMyKVpE7hqNf2h30aIvJDIlY9175Alj22zBfPfoaSfnz5zeH0ideqVSuUlpbGfj948CBeeuklTJ48GZFIxPP+Dx06hH/+858488wzAQAZGRmYNm0apk2b5mm/QsHoggULPB2EUhurRsPBKhQ1C0QB8VBUdFGlZAxEjfeLhKKyYSigtkq0IMu+sTdboEk/D6mqkJQoCKwatabvCLmeJ+3/OjwynQiZUNRNICpKZShqF4jqb7MKR80CUWPbY6wWNQtFzQJNrf3RXl+zbfSvs90+ZMUNnzf83e3+bToNe7SrJLWrHlXRBrFPQyRHZPVuK8Z2wcv8kqnITRus0Q/b90uyVmq6WZTJTDpcg1ZXV8f9npWVhaysLIut3XnppZewc+dOjB8/Xsn+WrRogd/85jdYt26dkv3F9qt0b5S2GI4mjh9VorIrzLtZVV7VtlZkAlEgfrElwF0oqv0b0P4mVv8m/KwU1YJTqxXsVVSRWjEuBKXnx/GI6DDZi3djp0G0wkI0FBUJRAH3CyypCkXNhs3LrjpvN5eoRgtFtWpR4/yhVvTtj7ZwhRmr/RhDCJn3iNeKG+M8pHacKkkB51DUan7UnCZ2dYhUkK1MNPu80m5jQBp86Oh14SM37N4zYQgcRd7PyRCOfld7AK1hPUe4mX21h/uqZWVlcbdPnz4dM2bMUHVqAID58+fjzDPPbHYsL0466SR89NFH6Natm7J9urpaePbZZ/H0009j06ZNaGhoiLvvww8/VHJilHz0AR1DUv84zSEKeK8STXZWoajV7WYr0AM/XLjJrijv5+JKosxWsNezCjHdBJh2gah+G4aj5EYyXJQGzWuFiGjoJbu4kswcmKnQ9tjNJ6rRh6J6MmGm9newC0ed9mPGrLLT7L0hsvqyfoi93f6cKkm1cFQ/rN5tKCqCfRoi0rgZieF2dXrt8zcdh30HfU2Xrq+ziM2bN6NNmzax3+2qRWfMmIGZM2fa7m/16tVx84h+++23ePXVV/H00097P1mdK6+8Etdddx2+/fZbnHDCCcjNzY27v2/fvtL7lA5GH3jgAdx8880YN24cXnzxRVx22WXYuHEjVq9ejd/+9rfSJ0CpyalijpyJBKBGVoEokPhQ1BhK2lWF5nUudlU16rSokp6xQhSwXoFez+t7uiArI9BwFLCuHjVjDDmdwkyRUFS/LcNRcsMqdElHbjthXvevJzpsHjCvFPUqv2uJq6pRY9uiBZv6ylE3c4k6DZvXmLUt+rBTZTWPWXWQ2XvEqbOofz/o/+7avmWG2MvyMxAF2KchkiH7hZzVFzlhqhY1+3JHfx8Qf92hei5PL2GdbAWv/nW3Oif97aoqWlUuwuTpPFyGo6l+3dmmTZu4YNTO5MmTcdFFF9lu071797jfFyxYgKKiIowcOdLtKca5/PLLMXfuXFx44YUAgKuvvjp2XyQSQTQaRSQSQWOj/PtXOhh98MEH8fDDD2P06NF49NFHMW3aNBxxxBG47bbbsHv3bukToNTGIfbW3ASfRnZBqMaqusQqFJUdRg/8EDLKzDPqNvy02pfd74B5EKrRV4kah9Drq0X9fi8XZHm/cDALXZ2qR+1YDb2XCURF9kckggGpPbehlJsV5jV+BKKtOnZxHE5vDB9Fg1Kztqega6HQavT6QNRuyLzGWCUKHJ5bVKsW1dqZMAUFGuN7wvg+sBuW6TT/qJ6x862vGrXjNRQF2KchEuEl1DKGo2H8rAPsn6PnERoK5gO34mb+Vz+vn1KtKpPXmvHat2+P9u3FF3eMRqNYsGABLr30UrRs6b3NBoBHH30Ud911FyorK5XsT086GN20aRMGDRoEAMjJyUFNTQ0A4JJLLsHJJ5+MefPmqT1DSnrGADCdglIV4aeeSBCqsevM+lUpmt2xRFk46jRHqMhjrMJQfRCqZ7cCvcr3rYoA1G7fVuEoIFc9qqev9nQbihr3t6G2xvN+KD2Fec6qRLN7bUQ7TyLDtUXnETUj2wbpA0arwNSqSlOjD06twlGNFpK6WVTJLAwFmleLBhEQWFWNmrGrihIdvm88jsi/R5m5SDUqQlGAfRqiIIQ1DE0Ev77cdTvliui5uPmclj0GpZ433ngDlZWVmDBhgrJ9RqNRAFA6t6hGOhgtLS3Frl270K1bN3Tr1g0rV65Ev379UFlZGTtRIjupNMxedfBppCoI1Th1Rt1UixqpDEdlmK0ur7EKQgH7zqqbFejDQAteVQekKgJRvdK8Vkr3R+RnZUayk50v1Mhu/lCRQNRLGGq83ama1Ixx+L1d2+MUiJqFsGbna2xf9NWibrgJKEWJLqxlvE9V6OG0kr1GVSgKsE9DRP6u6m53TLNqz7Bct+g/i4XnJE+CalHONRqs+fPnY9CgQTjqqKOU7jcSiSjdn0Y6GP3Zz36Gf/7znzj++OMxYcIETJkyBc8++yzef/99nHvuuX6cI6WoZB5m72cgKhqGynSQgl7kwhhMOgWlWofTbUCqPd4pELWbOxSwDkWT9X1qN5+pl+H1RMkgFRdtUtmBs2tDRBdRcgpE/Wp7rMJRp8pSs3BUz9gGOa0wb8aqndFWogeCraDyEl6KXGcYt9EfS/bfoBaOig6n94p9GqLk42b4uIigh/ybnb/ZbSquY7Tnk2rXRBRujz/+uC/77d27t2M46mY6HOlg9OGHH0ZT0+F/VJMmTUK7du3w9ttvY8SIEZg0aZL0CVB6S8bqUb9CUadAVLZSRLRDqqJK1InZkHaZqlIrVlWiZnOGGtld9DiFovqwUcWweJXvKeP5OoWjGoaklIo4J2lzXgNRqzDUSwjaorizsopSs/v1Iandwk12U7joq0T1+xYJQjVeqkW9sFrcySrUFFlcy+q5GINYldVQKqtFAfZpiJJN3OJAPi7qY/eFklWA6lew6teXvFbVk3aV+1aV/azCpCDNnDkTBQXOC2XKkg5GMzIykJHxw4fQqFGjMGrUKKUnRelHHwyFMST1IwxVPUzeb1rYqCpINRtyLzqs3m4uUauV5UUuUoxD551CUTuiFdF+T8cA2IejP2zDkJRSV5gCUtmOnMrqGL9CURW0z2yzgFT/ee4mgNWCTC0gFV3V3m7IvFkgahaGaowLLon+XVVXCduFn35fa4Stipt9GqLkYfbZ4Vf1aNio/uwUnSs0lQPPVH/PpLKLLroIHTp0UL5foWB07dq1OOaYY5CRkYG1a9fabtu3b18lJ0bpKywhqcrASiYENSM7kTZgP2xc37G0m3/TjOz2Vhq3bzIdci+76JKqUBQ4/HfSh6Nm4aYWMtpVimrvHav3kLZPP0JRq0BWJBz9YVt3IanXBZ6I/JbIgNTtRbjZ4xL1ZZk++DOGpE5TlYju1+nC1M1xtDZPH5A6LdakZ6xONZs7NCwya3faVqaG4YvWRGKfhij5OLXZdgGp2WeeU7/A7n6r+/wefq8yHBWd05kobPyaXxQQDEaPO+44bNu2DR06dMBxxx2HSCRiOil5JBJBYyP/kZE6QQ+1VxVUeQ1C/ealA+snt39lkaHzKomEonb8rhJVEY7+8BjnuUj1QSpRMlAVkBo7YVb7C3tlguiconpaGChbRWoMEY0hnuiniXZcu1BS28ZYcWo2DF8/3N5umL5+X6KBqIoh9CKBpvZ3dApH/aZyUSaNqmH07NMQJQ+vbbTV56bdZ1SQc0DLspqDVH+71WgA2eeVytWiosI2yoHg68KIQsFoZWUliouLY/9PFDSrgFQ2YPL6eCtBBKFOVaNeG/IgJh3XH8MYYB7asaVZNapx2L5TtaqKUNRYNSojiGHxiSC7UBMrRylZyAakIsOe9fvyIxCVCcj0tKDMTQhqx021pD60c9PeZNbutJ3DU3uOZhWuVkP2ZRZTclshygUwEo99GqJw8/L5qA8JZavjwxyI2pG5ztBfo1gFn07VpMb7VQaoZsfW799rlWuqhr1bqvYj+5DcDJkH6vb7dDb+0uYF94PQK9itW7fY/3/zzTcYNGgQWrSIf+ihQ4ewYsWKuG2JVPMaPIVpeLwI44IJso22XcBnPH+zfbsNCK2OZ3f+xg8js6DUjptFlkSEaa7QRDILR50qRWUDVaJEEakKEO18+FkdauzoyYScqgNRWVZhqPF1L7T5zNaev1M1ZLMqVEOQGt21xfUXaU6hqP7YQVZuGv++ia4ataL9W3NalMmvlenZpyGSZ7XQkdcFkPRD4EUCUS0Ykw249J+P2ueiSBWl2zlMm7VrJp93ifriVERYAkQv58HpAkiW9OJLQ4YMwdatW5tNeFpVVYUhQ4Zw2AmlNFVhqGzDJTsEQiTQFA09vUxjoA8LnUJa4/OT/nAyCPKb3zCGoiqH0//wWAadlLoSPWRKtl1IdNBpRiSIa8otil9ZWHQRiFYZ0p/rZkGqWbWp2XQAKobJqwom3XZ2RcNR7b1kta3q95pdIGDWmVW9Gr2GfRoiZ9rntdUXGirCQ5lQVPt/u9BM/5np9ksj4/lZPT+hcw/42sIsCE42XkNR7b+eq0w5nD5tSGcP0WjUdNLTXbt2ITc3V8lJEYWJ1zA0yIUORFZVd8MuSLMN2rLEjp9jOG+n6lKg+euqMggVWYRJf19Y+RWOym7PMJWShdUFsF9VoF4CLyt2c356XSTITQfL+Nkc60wfaLStCNQ6NloHWKZjov299Me2CkkB+dclWTuaZvTvpbBWmfqFfRoiOXafwzLVo7JBk1m4JVI96vZLHbPzMwuAVQ37V8HqeiLZPtftwkwvQWdYqmApvISD0XPPPRfA4cnIx48fj6ysrNh9jY2NWLt2LQYNGqT+DIkSKOyLKOnZhaJWIZjVIkIyoZndtmb3mR3TuEq7/rlY/Q1Eg1CZ4KHJcFxjOKqdq0gYqj9vlVMSyPIjHJXFcJSSid8LJfn5ZZnsQkgyRDtWdp/NZqHolhrnz1PZ4ZNmHVjtvPSvv9mQe7Pbg2L2hZ/X94tspzgRnWirLyT8qhRln4bIH6JhX9xclw5Box/Dod1+zqm8PvDrWsMqDPZjUTy/wkYV1aIq9hXbB6tG04JwMFpQUADg8Ler+fn5yMnJid3XqlUrnHzyyfj1r3+t/gyJEkBlIGrWGXO7D1EioajxPn1gqf9/p2pRs33ardquZxUwOr3+fgULxosGs4WY7EJRq/M23u4UlFrtx+px2vZW99uFo8APf2Pj7yqZVZpmNPDbW0ovKj679J0eP4NQjUzn0U2nq3N+drNw1CwQk+ncmHU47appRG4T0ZjX3nbhK62NMZtn04zZOZsNkXR7vn5Ox+BHJ1wV9mmIxPgZBpl9/pnOxemwII8X2ueUcQFas4UZ7c430aGZzLWFipAv2efvdBNK271uBT5/oU7BEA5GFyxYAADo3r07rr/+eg4xoZTjd3WoSAfBuNhSGIiGnE7by1ZZGqkMQ7XViM0W3xAJR83IvH/cvtecHmcXkNpNB2D8mxl/D6qylCgV+fVFjmwoareKOyAXkolUhWqsOiD6xXU659tPu2LWCRbt2Ni9/qqDQav9iVQnibxPglpgKdFDL0VWRdaT7aCzT0OkhtNcn14YV1CXGTmghZ1WX1YBP3zO2X32ull0USR0dBPMBTk1m5FpUJygoenG9oFD5EkV6TlGp0+f7sd5EAUqrEPk3Qai+iBMtFrUC6/zaoq8/k4XAFq46YVxH1pQKhOOhvG9ZHW+duGoHadKUtEKY6J04VcHRmWQZwy+zDqQxm1EV/A13iYSjupv0yRLICrCGDaqGkYp8lwSFXTKVI06VTHZdX7198mEpOzTEImx+3flFFgaqzHdkplKxcvnq9dq9yDmDZXlpQ2QeT5m23quTrUIZd2G8l7+PhxSn9qkg9Ht27fj+uuvx+uvv47vv/8e0Wg07n6u4EhhFMbwKmjGOR6dFtFRsaiQigBUT0UY6rR/u3A0magORwGx6mE/h+MThZ3qxZSsql28DqG36iDph2bLhKJWq8w3m+tLG0Kuq/gwC0fNHqs93o7XMFT/umoVtk6vtezCTWadbjfVon5TFaa6DRncdnyN22faTNnCPg2RNf2c0G4ZP9tkPw9UB1HGz3irLwODnArELDj2Y2FGbb/66VwA++kA/J5z3XgMuxEnxvdCIitFja9LdXjX4SUJ0sHo+PHjsWnTJtx6663o2LGj6WqORImWbCGWH/TBlNnCN1X1jZbhqFkoquI1lW3onYLQxu2bvJxOTGZJ17hjWoWjosIyJYIf4agoBqSULmQ/12QCLj/CMH3YZdUJcwpFrTqqMh1oYzhqvK/Z9oaOiKow0Sr4FA2fRbbTwtNED1HXM7422vPQB72q3n9u20S/O77s01C6Ub0Sety+Bb/IcPpyyHifWThqFqbJLtIX3bWl2Rdb+s/oIK7lzYLjoDQLGgXmS3UTVNs9xvhetFqUSxUV+wwiLKbEkA5G3377bSxfvhzHHXecD6dD5F4yhaGNuUW+nK9s2GUXjmqsztNr4+2m+lNVEGq1Xy0gdROOmr0eqoYPeSETjuoDcVXBaUFWBsNRSkl+BqJ29EGc/nPUbM5kO/rPJJnVz0VC0R11B1Gc29Kxo6zd51Rlqud0nqKvcxALV+mPpe+Ay37p5ne1aJCvRZiwT0PpwPiZLRI8iYRfWqW/8YstLXy1+6zWfwZahYNWn5F2YZod0c854xdYZgs0OXHbb1DJ7MsuI6cFsGSoCgzt9sOh7OQn6WC0rKys2VATokRLhlDUGE41+jhM26la1I4+HDM7LxUNud9D4lVTMaQmkSv02oWjVrT7VASkVkPwI/X81pWSi1/D28JM+9wSrRLVOstaOGpkWv1jMmxadGX5ZHltrcJR43Py8nzMpgLQ7zfR1aoigUeQnV72aSgdyQRY2ue72XQnGqvP+kQTWYCJ0kcqV3pu3rUfrfbLjbBo2Lffp7NJXtLB6Ny5c3HjjTfir3/9K7p37+7DKRGJScYwVHY7kecoegwzdtWixmOnQyDauH2TadWoE9HXJpHhqFsqA1KiZOXm88+vjlikqHMsABP5jNIHZFowZvY5JFU1ajFk3q7zrGc2DNIuFFURiHqpirRqu2SrdAHzoZr6+9zyq+rTj1AhLNPNsE9D6cDvQMgqFLVrU9yOWLCjn57FbMoAfdtpx+oLpER/XsmSnf/aKz+naSAKgnQweuGFF2Lfvn3o2bMnWrdujZYt4z8Md+/erezkiIySIQzVeAksjfswe97G/ZsFV6LVolpFn1UFYTqEok5UhZp+hKPGv4/Z/q2qRkXpA1KGpZQuElEhatUp0+/TqoNn1xEyhqJmc4sZOVWLqmCc10x/Lm4C0TAPCzeb0y5sxwryHM3aQ6uqUav3qJf3Jvs0RPL0C+bJVop6vf6VDd6Moau+7TT7nDNrf5MpEJX9IssszPRzjs9ESaXnQv5xVTFK6c0qnJQdGm4X0iRTAGpk9bxkQyR9SOkUaOn3LTqfo2i1aFhCUb/mF/XKzeujMhyVOb7XcBSIf18ag3QGpZRKgqoSFR3erF8xHhCvBjFbbMkqTNJ3Iq0+o7ysUGwnrIGoXftlN7LA+Dj9dmbD2mXeO8aOvdu585xo2wY9FFVmAQ4vw+/ZpyGSowWhooGoSJti3M5pWzf0n2Gigagf52Hcd5CLLVlJ1JydomGl8f0j+5nPUJRESQej48aN8+M8KAk4hZWyYWYiwk+zBkhloydSxSlK/1i7uSDDHEaFtUr0wNbtAIDsjiXN7tMPpzcyBpqJvKARndTeSEU4asXsfRrm9yeFi7FTZPe7KKfPd7OOWKIWVRJlF1LZhV52oai+asRuBXq7UNQ4jN6s4ywyrFK/TaKrQ0XaMGM4Ktru6UNKtwtGOT1/q1WXvbJ7n6may1SmMyuymrIZ9mmIxIgGoWYL7on2s5zaeZHPBLPF/uz2G+Zh826ve8yuEdx8JttVkwbFaz+LoSjJkA5GAWDjxo1YsGABNm7ciD/96U/o0KEDXnnlFZSVleHoo49WfY6UYMlYvSnzQeq1es9NhahIVad+wRptX06rhrupFjUOoxetFg1L6KmFnIB50Gm3/YGt220fY1YN5GZ1ykRIVDhqlNN0gOEomXIK90W3dXsMt9uqDELdBkjGjo9IIGqkhZx2q8abbe8HmQrRMA+VF6ku1YeVbqpEw0x7PjLhqMoRFG6qR9mnIQqW3TQuZp8FbsM4Y7An2m6GIRQl7xiKkizpd8yyZctw7LHH4r333sPzzz+P2tpaAMDatWsxffp05SdIiZUsoWhG3a64n6CIhqJV9U1xPyLMtt2fkR37Mds+/ndvnVir1/HQji2hDEXNfnfaXuQxZlS8x7wEPTKLPVkJ8t+2XcUzpaewf7FgRVUo2pjX3jE4asotivux2odxP3aP0zqYoiGn1+oQfehqrATV/+gZb4vu2hL3Y0Vrm4w/bsk81q92UeR5B8Xq/aYx+zsmQmGrjLifApvOMfs0RP6wajv8qjgUDcH004MYWbW1frI6nna72/MR+WIqUUPozZj1bbxUDzMUJTek3zU33ngj7rjjDixZsgStWrWK3T5kyBC8++67Uvt66623MGLECHTq1AmRSAQvvPBC3P3RaBQzZsxAp06dkJOTg8GDB+PTTz+N22bixIno2bMncnJyUFxcjLPPPhvr169vdqx///vfOOmkk5CTk4P27dvj3HPPlTpXCqegg1A9kVBUJAitqm+M+2l+v2gVaIbh90zLH217q2pR42uqopPpVuP2Tabzi1oFmge2brf8sWK8T388N89Z9LUSDfP9Cv21v3dm3a5mP6mC7QypojIUtWPVOXPqIFkFofofwN/KTzPGDorZ62gVkooEgk6ft6Kfx6KBasPWb9Gw9VvH/VkdA7B/XqrDUJWhqtnfKJmxT0PpyumaUvvcFh1REHuc5PZmjOelfcmhv1/0mlhr9/Rto4oFloztqluqruvN2n+zL7PcPE+z/5dlF1TqXwOZkUREqkkHo//973/xy1/+stntxcXF2LVL7g1bV1eHfv36Yd68eab333333bjvvvswb948rF69GqWlpRg6dChqampi25xwwglYsGAB1q1bh1dffRXRaBQVFRVobPzhwv+5557DJZdcgssuuwwff/wx3nnnHYwZM0bqXClcvIRExmoamUaiMbco9mPGzSJIemYLIhkDT/vHZwhtr9/GLhR1G4ZqYaaKHzNuqjydqApH9dvKPM5Y9awqDHV6vFUImirhKNsZcsuuqtENpypRkfbIrP2yepyKahB9Z0br8BZmZzb7AQ7PQaf/MasWlZlLUzQUFWXWnsl86WcMREXCUe0x+m314ajsnKF2/P4CU/+3S5VwlH0aSkfGIMrqWtMqHDVrA/Rtgf6xXs5N5H4VYZmbqszYa5MGlYmiAbCq10JkLvIgzoO8mTVrFgYNGoTWrVujsLCw2f27du3CWWedhU6dOiErKwtlZWWYPHkyqqurgz/Z/yM9x2hhYSG2bt2KHj16xN3+0UcfoXNnsRVSNcOGDcOwYcNM74tGo5g7dy5uvvnm2Dehjz76KEpKSvD4449j4sSJAIArrrgi9pju3bvjjjvuQL9+/fD111+jZ8+eOHToEK655hrcc889mDBhQmzbH/3oR1LnSonlteGTbfTczL/odh5Fu9XhjSGn6CJMIuGofl9WoaiVRK0Q70cgaty/1ZyjdqsPa/c73W73+DDye6GmgwEMsWc7Q7ISMYeoaLBpd8Ev0nFxUy0at0K4RTVQYXam6b4LW2WYhqJmAWCkqLPjUHknxrCyVccurvZjt0+z+4zHMXtMw9ZvTc9HNgx1syCU2SJMXjktHuXlvR8U9mmIfmC2erz2+a+iElT2XMI+16fXAC7dKiDN5oC2eg3cvjYMRcOjoaEBF1xwAQYOHIj58+c3uz8jIwNnn3027rjjDhQXF2PDhg347W9/i927d+Pxxx9PwBm7CEbHjBmDG264Ac888wwikQiamprwzjvv4Prrr8ell16q7MQqKyuxbds2VFRUxG7LysrCaaedhhUrVsQuIvTq6uqwYMEC9OjRA2VlZQCADz/8EFu2bEFGRgb69++Pbdu24bjjjsO9995rO6l6fX096uvrY78nMr1OJ340EiINq5fwx8siSDKc5mk03m8V1JoFooB9KKoiCLVbCV70sUa1W3Y0uy2vc7Hwfmu37Gi2vT4cNa5QbxaOuqkmTbaAVLWwzDnKdiZxErWAmV+Vbm4WUXJT5al6TrBYFajAfF1Ox9bCUbN9OoWiVreLfr5ahZdWYaQo0SHzMtu16tjF8Ys2I7dTugTR1iRz9Wg69GnSuZ0hd7yGkqLhlHE72WpRledCwVLxdzFel/Bv7Y6xTcjKykJWVpbn/c6cORMAsHDhQtP727Zti9/85jex37t164Yrr7wS99xzj+djuyUdjM6aNQvjx49H586dEY1G0adPHzQ2NmLMmDG45ZZblJ3Ytm3bAAAlJfEhSklJCb755pu42x588EFMmzYNdXV1OPLII+PmCvrqq68AADNmzMB9992H7t27449//CNOO+00fPHFF2jXrp3p8e+8887YHzSdNeYW+Tqk1u+OsV3DLhuGqlxZu6q+0bZSFDAf7i7D6TFmoaiXQFS0mtO4nVVQarc/s0BU5D677fUBqVM46pXqgNR4Tsb9ernIVV01GpZQFGA7k6qCDmpkQlG7f4d2waPoCvIq5g81qxoCxKpVjeeXUbfLMhS1q6b3GogatxEJR0XDzZpNh9um/K7yX/Lpz8euHVA1HF4fjnqpGrX6NxXmUFR7T9bY/LtKhz4N2xlyQ98OiAZOMl/cyYZYIv1Fpy/wZL6QtWoHw87uOSbbc9GzOneZ95HxdUnm18OocmcdWubIPebg/joAiH3xppk+fTpmzJih6MzEfffdd3j++edx2mmnBX5sjXQw2rJlSzz22GP4wx/+gA8//BBNTU3o378/ysvL/Tg/RCKRuN+j0Wiz28aOHYuhQ4di69atuPfeezFq1Ci88847yM7ORlPT4Q/Im2++Geeddx4AYMGCBejSpQueeeYZ029pAeCmm27C1KlTY79XV1c3e+OQO4keOiAS8qgMQd2wC0Vlg2rt+Zo9zqpK1CkQVTmkXWZfsqGnDLPqUY0xHFXFS0CaiIWwUhXbmeQX5oDG6eLb2JGzCzf9XjjJbBEEkc5D3HD7/+uoGNt6q1DU7HcRMgsgWQ15l92PForq/98pIHXaLp0/y/3qmIoGNOnQp2E7Q17IfLEuElLJBllBji4xO45fQ/oT3RdOFJHRJ35I19dbxObNm9GmTZvY7yqqRWWMHj0aL774Ivbv348RI0bgkUceCfT4etLB6O23347rr78eRxxxBI444ojY7fv378c999yD2267TcmJlZaWAjj8LWvHjh1jt3///ffNvnEtKChAQUEBysvLcfLJJ6Nt27ZYtGgRRo8eHXtsnz59YttnZWXhiCOOwKZN1uGPVRnx/oxstMzIDlXVUzIJ8oPJrCETWTTJC7sh9FqVqNnK83p284O6qd51CkQB51DUSxDqdbi73X5U04ejdvONqmYMSK1+l9lfGIfrh+1zM6ztDInzMxC1mgdTlEhnSiYUFbGj7iCKc1sKbSs6jF7fXhg7qca56IyP0f4+2mvpJQBt1bGLZYipDyz1jGGkyL5k9q/dZzyO2fb6gNQuqBVld/76/XqpGtXPIyrDzWMSIR36NGxn0o/xSyqvrD7zVfIy16Q+vDT7kk5P206mP5oM850mE6svT/3CUNRemzZt4oJROzNmzHAcgbB69WoMGDBA+Pj3338/pk+fjs8//xy///3vMXXqVDz44IPCj1dJOhidOXMmJk2ahNatW8fdvm/fPsycOVPZRUSPHj1QWlqKJUuWoH///gAOT+K6bNkyzJkzx/ax0Wg0Np/OCSecgKysLHz++ef4yU9+AgA4ePAgvv76a3Tr1s31+emDtLB19sMqrB9MKqtDtVDTLCDVhs6LrjxvNRcooO61tAtERcNQN4Gl/jF2IanbIfNuglf9fs3CUZmqUf1rmVnSNfa70+NVVFGFVRg/J8PezqS6RM0zqpJVAOQmFBWxo+4gADQLP7Xbtf+3CkebrS4s2UGxWhFY/3xFQlGZUNLuMXaBpf5+q4BUhNMxRLcxIzMHqmyFrNV+jeGo0+JPYa7G9op9Gko1flfjpcpw5FS4/rBi9tyS9e8E+BvGJ/PrkgiTJ0/GRRddZLtN9+7dpfZZWlqK0tJSHHnkkSgqKsJPf/pT3HrrrXFfIgZFOhg1G/YBAB9//LHlPGpWamtrsWHDhtjvlZWVWLNmDdq1a4euXbvi2muvxezZs1FeXo7y8nLMnj0brVu3xpgxYwAcnmvnqaeeQkVFBYqLi7FlyxbMmTMHOTk5GD58OIDDKfikSZMwffp0lJWVoVu3brFJXS+44ALZpx+I/axIDZT+tZYJSe0eJ7IqvN3+NFaLI2ncDsW2m0vU7dyebrmdE1RkG6uA1G0Vq13AaTX9gP52v4bkkzW2M6SKTKWdyDB0LZSMWzzAYg5RrZLUKvC0qxK1XEneJBR1E4I15rVv1j6pDkX1rEJI4+e6/jNd/xizIe0ywaboF3tWjBWm+tdDH2Z6fZ304ajsKvV+rGJvlOhh9AD7NJR6gh6qbFdNGtQ8nVb739vQJFw1G+aQ1CrEtXtdkyHwEwmnvT6PMP9dk1H79u3Rvr1/I0Ki0SgAxC0YGCThYLRt27aIRCKIRCLo3bt33IVEY2MjamtrMWnSJKmDv//++xgyZEjsd20OnHHjxmHhwoWYNm0a9u/fjyuvvBJ79uzBSSedhMWLFyM/Px8AkJ2djeXLl2Pu3LnYs2cPSkpKcOqpp2LFihXo0KFDbL/33HMPWrRogUsuuQT79+/HSSedhDfeeANt27aVOl8rWiimIsxM9NyWfkmWDya3f0PRFeFFjmdXHWpVQei2stCpSlQ0tHQbmMquIC9L5jH6SlGnIfUyi1IZiVaPqpau34wmYztT1dCEJokLevJHpKhzLNhzGxKJ/LszC0ibbfN/4absUHurClH9+QHmgaixktDqNbAKU42hqD7oc1thaSQ6qsAqJPV6LLu5qc0eo22ropJVhFM46obXfxNhwD4NpbJEzuPoZqi6Ha+VnTLhaJjZTWPjRiLeH7LSsc+SSjZt2oTdu3dj06ZNaGxsxJo1awAAvXr1Ql5eHv7zn/9g+/btOPHEE5GXl4fPPvsM06ZNwymnnCJddapKJKpFsw4effRRRKNRXH755Zg7dy4KCgpi97Vq1Qrdu3fHwIEDfTvRRKuurkZBQQG+2bLVch4G1cFoGKpGVaxIn6hQ1OoDVdUK2/rXxus+nYbKy6wW72a4t2wgqrpyVKay02/6c9H/v1/zjfoVkJpVEbu9yFC5Kr1edXU1OpT1QFVVlfD8NqlMa2e+2PQd8tu0SYmLeSde24dED/P1MpeizL9H0U7M3gONphWiVoEo0Ly60w1jSOZnKOqlXQjD/NbGc3C7ur2eU0WsvhJVdISJ1d/UbhuNyL+LoCpGa6qr0btrp7h2Jp37NFo7s33bNra7KcwuEExEv8zp37tdRaRMVaFZWylyLeV35WKij6fnVyjq5prV6nVQ9fxF3usqjlVdXY2S0tLA+zPa5/kZ9y1Gy5xcqcce3F+H16ZW+HbO48ePx6OPPtrs9qVLl2Lw4MFYunQpbr75Znz22Weor69HWVkZzj33XNx4440oLCxUfj4ihCtGx40bB+DwPDmDBg1Cy5Zik/unEy9D4M0qDM1uC0NYKiNsoSjwQwgpGvaIhMPGbZz2LbIgEiC3Urzsdhp9KGrsAMp2CPd+UyW0XWG3grjfVR3HuN9kkKgKUgq/RFU6qF64gcw5VX8YF5QAnDs0dhWiVsPdAfsV4520KO5sGpoZQ1FjIKoqcKzatNf2/oKuhc2OaQwng/wSzlhlKrq6vZ7TYlCy+zOjH07vJTQ3k+hKIPZpKNV5bb+19sHqSw6n+4MiOp+3l9cj6M+rZAxFVQoyFNVvl+h2KdUsXLgQCxcutLx/yJAhWLFiRXAnJEB6jtHTTjsNjY2NeO6557Bu3TpEIhH06dMHI0eORGam+TxWZM7NsHnOP6qOl2pYp0mtRfftFIYC7hZFEqlu9BqIioagTo8VDTNFjqdt47RPs31pj5EZUm9F/9pmdywRemwQAanK4fSyXwaQO0GHo/qL5mQYgtaY115p1WgQcyuaEVmRtym3yPLvYezsiFSIAt4CUePjtEpEs/lE9UGeihDSKQw129YsIFVxXP1+RZkFtMawU2Slezv6uUzthtTbcQpEE/XvRRX2aSiZqWij3QxV17chQQSkKhZKSobrmWTn5jUO0yJYolMVqJzSgMJFOhjdsGEDhg8fji1btuBHP/oRotEovvjiC5SVleHf//43evbs6cd5ppxUnUtULywfdCo4PRfR1f+s9uMmDLVbAEJ0RXnjfsw6i7IBaPW3NZb3temSb7l/Y5jpNXg1C0ft9ql/jNW8cU4Bp9nrrt2m/VckIGX1KNkJ8gI/XapH9QFQGMIefcdT63DafbFh9/exmkdU5cJIrTp2sdyPFugZ2xeZSk+7basc2oqC//tcNwtIRdkef9Ne4XM1Ht9uoUAV87CqCEedyP57CVNHkn0aSnZ+Xw9k1u6MCz2tvoh0Ckjt2i/ZhYWSTVgqEsNaLaoPRxP9Gmmszsf4Xk3X9RtSlfQn6dVXX42ePXti8+bN+PDDD/HRRx9h06ZN6NGjB66++mo/zjGpiASeqkPR/RnZsR8Kz4eqkcqg2OuQ90SxC029BKFBkgmdiVQwu5hVdYFrrBC12874Q80rZ4w/ZtuLbGP1u0w7klG3y3J71UOjrViFe6IVn1Wb9noKRYMmU8lKicc+DSUrlW2waL/Jjzm9zQpLzM5H5DbVr4nVuSQj1ddssgtBOkml15qSl3TF6LJly7By5Uq0a9cudltRURHuuusunHLKKUpPLllZLaCkKri020+YFm9KVHm86m9vEvEcMku62s4Vmte52LZiVKXCbgVSoaVZVajIMexukw1NrYbSa7fbDaUH7F9Pu4pPbdh8WPl10cFh9P5zCkdlK0ZEA1GnfYShklTFcHovFaJ2x9ZX0ThV2ojS2ji74Vx284n6zazq1M2Xd2EKGQu6Fgqdj1PlqFm1qp/tt55+AaZECVvHl30aSkZeQy6Zf4f6ClDt/43tiZfF1mTOxW5bkdfE7prF7WeTyKgaq1A3WStl7ULRsFwXqiDyd0uGvxeJkw5Gs7KyUFPTvOqrtrYWrVq1UnJSqSSRVZwq5iNtzC3yNBen/gMjyIAx0aXtqo9vFriJdqa0IM9LYKdymLvTvu22cTqu6HylotsZX2OROUbtwlGRx6sYRq9qiKRd4MkwNFxkQlKVlQNeh9qr+gLNqsMWFl7Pyzic0Ww4lygV84oaacO0Va4+nyyshuYbw1TjdqJtuDYUPh1ez6Cn7mCfhsicXdgpM59oEH2xoEew2H1RLfPZpb02dsPIwxw07j3Q2GzBx3QQxjB0z659aJEdkXrMoQP7fDqb5CUdjP7iF7/AFVdcgfnz5+PHP/4xAOC9997DpEmTMHLkSOUnSN5owWyiq0cB54qWMFJ1jm7241Q1KkIfxIlUMxorUa3IVpFa7SOIx8iy6qyKLrwku62en3OLyjbkDD6Tl9WFtJ+dhzBfvKcjqyDWzyH0VvOT+jXVi+jconG3uZhfVP9Y2SpWq+PJhqLa/8uGo15XpnfDKjSRaYOCCkjZp6Fk41c7rnKUXxiDI42XaxWvValWrF4v7XheRgeRO2F+D5N/pIPRBx54AOPGjcPAgQPRsmVLAMChQ4cwcuRI/OlPf1J+gqRGGFez97uaVGQiZz/DWdGqUdGKHdlh2m7DOVGiVZxWj7OiXxHeK9Gg13hs4//7/VoC/oaiMhiIpoZEzAEahnBU9Sr1iaIPMLVh/saqUStuQ1G3Cy+Z8bu60S4UNQtEVdGHo15CVhGJCDUTScVnluw+2KehZJKoub2NlY1h4uY1Ef3iJYzTDCV6QUyRuUXDcC0IhGvFe0oO0sFoYWEhXnzxRXz55ZdYt24dAKBPnz7o1auX8pMjtdyGo16H04vwM7w0BqTJ9CHptmrUKsizGpLvJYQUnQvULhA1q57xEpBaBZx2+wpqnjczfoeiIgF9kIGoVsm+P6MhsGNSMNxWS6j8XE72cFS0qtNs5XqZ561qGL0ds89cP+cOtQtFVQWZXvcj0tZYhaLJOqzey/x9fnaw2aehZOE2ANT+/Yj8W3Jqi71W0bkJ9eweY3xNtNBOdHi31b5Vf0mj37/oZ5rTORjvl55nXvK1SjS3bQHDUZIhHYxqysvLYxcOkYjcnAaUOGGsHHWiagh+GBeCku2YBrG4j5eg1M1Qd6dOokiwKRpqutkuiGpRlVTNL+qXRM67TMEIQ7WAFo7ahaQq5yU1q/D0uh8zVs/J+HtQq87LUhGKWlWL+lkpqopZG+SmMlRkWH1QFade3u8igqiQYp+GUpl+SLaqYd5ujm/2u935yCwSqa9klJ370u9KXKvnb/XcvYbgfpFZiT7Rla16DEdJlKt36/z583HMMccgOzsb2dnZOOaYY/DII4+oPjfySbIHE025RSkx94df1TrJFOTJVmnmdS42/fFLKgyhD1u1KFFQtOCzMa+96Y9+O7Pbk1VYQ9FE8nvYuxv5XUs8hZfJMtRe1fWaX+EF+zSUiqz+vRjDRuN2qvtXIpWPXv9tywR2qcxVoMrXjihGOhi99dZbcc0112DEiBF45pln8Mwzz2DEiBGYMmUKbrnlFj/OkUKAwYk7YQxwRcK+IIaVJ3Louh2R8wrLfKCq+D1Vhl6yVayTO7IX6GH8rJShVc35XT0HqKlwTZSCroW2q7jb3R/bzmxRpSStFvXKKlw13taqYxflxzbj9xcLdp8rbkIB9mko2YlU5Om3EdleK0DRt8tWK7Gr+MIiDFWFYRLk6yFTWZvIYfduX5OMul2uqkVZYZqepIfSP/TQQ/jb3/6G0aNHx24bOXIk+vbti6uuugp33HGH0hMkSlZ2c5qKVosa5xf1exg92Qt7IBrkMPrMul2uvzDRwtFqlSdElGBBhKJORKtFg5hf1I5j+Gm43zgEv6BbgeOq9E5ULvQnS3W1p+z+VLUViXjPqxwyyj4NJYvCVhme55U0bi/6eOPq6GbnYndMu21V/FsuzM4UrnyUOfdkw4A5nqpwU2QxZ0oN0sFoY2MjBgwY0Oz2E044AYcOHVJyUuQ/N3ONBrEIE4WH2VyjqjqSyVgtagxFjb+7WSRLZdDqtaNr9m/b+G9eC0JVfQ6wepT0OA+UPFXD5lWuSK/ndXE/jX41+NhtHqpEjQv0iSzM5+V5hLXNc6IFn2bvM5FQNKiOpNugg30aSib6UM9rKOpFsgaL2mtgFY7qF6oK6lzs7ld5Hn4Ewk4VpIkMalVcSxr3of+dIWlqkn7HXnzxxXjooYea3f7www9j7NixSk6KyEnYO88qPjD9rBYVnTvTqjOXLJ08L+cpO7+oTMiZWdJVSSjaorhz7McPxgA0s25X3G38ooQocexC0UM7tsRVhWq/G2/3ix/zX7qdJ9TL/KLGANXYpojMd228PVnmBtUHn5Gizs1+jIKcn1dmURY77NNQsilslRG6ykCnf4/Gc9Z+FwkH3TAL7JyqZcP2mpJ7ThlBZu3OZj9ujhH2LILkuVqVfv78+Vi8eDFOPvlkAMDKlSuxefNmXHrppZg6dWpsu/vuu0/NWVJosGrUu0QPYZRl19lTPQRRZAV62X2JVvvIVIuGQVhWn/cypJ5Sm9sVcNP5YjNS1NlzFagxEKV4Zp/1diMkRB4vcp9b2vygbqt6jfOLBtV2+F1Ro6r6iX0aSlUqwj7Rf2ci24UtfLSrHA1DVazslAVBkJm2IBHcXj9m1u509eVeRt0uVo+mEOlg9JNPPsHxxx8PANi4cSMAoLi4GMXFxfjkk09i20UiEUWnSJR+3AzL1hzYul262tFtyKkyHDWrxFEZvNrtT1VnNrOkq+3fTlWVaNgwHCWV0j0c9SLVg1CzIfVO24sK40gIfajZqmMX36Y8SFfs0xCJ0cIwkQV4VM4DrILduSTiPMP02vjF7+dovEYUvW70Y/HKw8dtqXy/Mmr3HEBmltxr3ljP6cyMpIPRpUuX+nEeRKGg/9aHHXMxxs6kl8pMs239XhjD7Hz0wbJsmKltrwWkYaw2JaLkpmpu0SCIzuEJ+L8QUqLDT7PV4mXCTq/Vo6JkF1UyVtokSwUN+zRE1mKLLukqBPX/n8hVytNFWKpX9cJeNUrkVup/ZUGW9mdku3pcGCrDRC+6m3KLpLZ1cwyn/bjhJUwTrRaVrSoVleiOp905GOeB8/tcvfwdjXOH+jWXaGNuUezH6j6n38PwmUCpJZHBSpBzJbqViNXAnbTq2KXZsG0nbj6DRatAvcwtGgTttbJ63exeS9HXOVHD6GWFreNPlAr2NjQp+bdlOmcnQ1HXlC+ClIiq1wT//bX+vb6fL9LnT4brO0ocV3OMEoV9rlGVIWe6VI6qHhYvOl+byH0y5yXS0Q4ivPUaipr9vyy7971VECqyLYNQEhW2IXWprkVxZ1fD6f0Ypp3ftQQ1mw4vGijaJljNCS3aDtiFoWH40s6ObKjs19D6oKtFGYoSJZdEh2IqaZ8/vE5JHU5998a89nFD6lWEpRn7dnveByUePwXSnNuqURW8hitW3wyprjTyur8gK5+8VoGq7DiKrNYbRn5V0opQVRVq960pKzxJ1t4DjbEfV49P8eCjMa+95YW13X0iwlgZasY4F6ZXTpX9ZgFo2CtE9cPoVbxGTvuRrRa1Wm3eT6n+2UCUCMZ/V1b/zlT++7NbZV6rXPXz37tdWOvm+asMStMtdA3D8xWpHPV6fUaphxWjhP0Z2chpkp+A10vVqMpgJlnmspJlXMgnu2MJDmzdrmRfdvsMYl5P4/FEthE5p2QKYI38HuIYxjA0kV/MkDOzIFRmAYa4xyVZ5aixosBqG7vfw0D7XAnDokyyn89OC/LJLsSUqrzOO+olDPVSLcpQlCj1aHNi2oWRbq8FjI+T+QzRHzcMnz2qromS6boqaFw3hGTxX1MKqKpviv24tT8jO/bjN+McheQvbUi3zNDuMFZ6Op2LH+dqfM38mudT5T6T4YuCoD5ryD2n6lA31aOyFSOJfi/bBZ2yIWgqVybYVS0aFxtSraBrYezHjlX74Pf5BXkcba5SmbleRUJRu2poPdF/ryKfA1zYgyh5JEs453fVqp1keY1SVaKvJyk58F9pkjOGoV4DUiDYkDRZuF3AKUgiQ8DNwlGnx4V9SHwizktVQKo6aLUbPm9F/+9c/2/f6UeUl8dSYoiGEl6G1oehYkOE6jDTGJCaDefyYzhz0IvuqBoqbqTqsz6/a4mSsFLbj92+zFaiD5rZ318mFDV738oS/Xevfa4wHCWSJzpsPLbifIjbYv25yQSLqfbZoU1TYHwNGLZSmM2aNQuDBg1C69atUVhYaLrN66+/jkGDBiE/Px8dO3bEDTfcgEOHDgV7ojr8F5Vk9NWhdgGo13BU4xRkyFZ8yiz4ErSgVtiW6aAag0wV81+6CUf1EhmOGuedC/JcVAcLsvtzmk9XNhTV/9t2E1iqDlAp8dzMI+qlAxJkh8zLl1YqQiGnfaqkfbYYP2P8qngPmurPfZGAVB+AWoWhItu4of3dVP7t3FaKWr1v7f59yXwRYvw8SbWAg0gT5kDSb+n03BleUrpqaGjABRdcgN/85jem969duxbDhw/HWWedhY8++ghPPvkkXnrpJdx4440Bn+kPOMdoknATdFbVN6EgS80Hstt5SDVOYWMiV7m3CmuN5xOWFer184LaBZp2Q+et5hwVZbVysNv9+P0YUfrXU//6WXVIg5i/zyn8lF15HuDcnulAZi7QRIYPTvNsqfzc1f6tuN1f2IbCR4o6I7rL/LPHLkSzWrleZJVzu2pHq89D/er0YSAbVgY13N6MWbgNyLU5xn14GT4vQzb8sPoccjuvMRG553d46edq8G4+K4KYB12bf1WWH/O1phsv15Fh6f8nm5kzZwIAFi5caHr/k08+ib59++K2224DAPTq1Qt33nknRo8ejenTpyM/Pz+oU41hMOoDVdWaycIp1BStwNRvp9+f1e0y+zPS9mO3jWxYaxdQGT9UrTqmZsxCTKcKT5H5RFUs7qQPKWVD0iCqPfWvk9VzM3stZeZjBZp3PJ3+tqKVP56q3BiKph27xZKMCrMzlQWiew80egot/L64N/478hqQBkUkwLILR+24CUdFQlGrfakOR2UWCdS3NVYhp9X5qQ5FzV5Dq7+Fm3DbiR/TNBj/fbnq+At8FokEpGb7qa1n1SmFUzIGW6q/oEjG18AL2XDUcT7mNHv93PAaiur/a6mmxvUxEq26ujru96ysLGRlZfl+3Pr6emRnx/dJc3JycODAAXzwwQcYPHiw7+dgxGBUkbCGoYmuGnU7LN3qcaJhpUiFqhtawKliLlFj5YdduCZT4SkT6qkIRzXGoNOu02oWipoFlG7OxSo0djsNgZvhi2ZVPTL78fr+Yiia+ryGmmEbomp3cS/zbb0x9JT5wirRGvPaI7N2JwC5ACuIcFRmXkyr/WohY82m7aaBY6KrSoOubNW3CaraGbtjiJKpFg0qFPWyPRHZcwrXwvBvLpUCQLeVo1b8rL5NdkFd4zW1bhfIcazU7NyNjFb7pR7T1HB4+7Kysrjbp0+fjhkzZqg6NUtnnnkm5s6diyeeeAKjRo3Ctm3bcMcddwAAtm7d6vvxzTAY9SisgaieynDUillg6ddcnaoqVN0eSzS0Mj7WqhNuN0xbNhw1C0X1+xepMLEKEL1WkwZdIeqWbLWoHRXziMoKeyiq/8ysSaN5plQJQwfFjNeqUcBbOGpVFepERfVoGCpQ/QhHZfZhxSxktava1HMKKUWqRmXbHT+Hzfu16JLo8HqnsF12+LyXUDSsn2NERID/UwkEHWKGfV7XDEN/WfU+3UiXlew3b96MNm3axH63qxadMWNGbIi8ldWrV2PAgAGOx62oqMA999yDSZMm4ZJLLkFWVhZuvfVWvP3228jMTMzUOQxGSYpd1agWBAaxmJJ2jKDCWFlW5yFboSQ75N7s8Wa/u6lGVVlNatyvimP6EYqadfj1DaXKIMTPBjjIUDQZvixKVmEPE1SEo3asPj9V/NtxWz1qNQewVcWqn+GpVTjqFJq6HZatPVb1PjX6Ck59tame1XQuZm1OIucKNYaifiyC5TQKxYpdIGr1/nUTiob984soERJRCSkyPDsdhe15h+18/OLlushqFKfdPrWROZqwzR8ftDZt2sQFo3YmT56Miy66yHab7t27Cx976tSpmDJlCrZu3Yq2bdvi66+/xk033YQePXoI70MlBqMeJFMAEETVKBB8MBlUCOt2blPVizhpwZ0xyBQJRY33uQ1HAXdD3P0URChqtfCRiqBDVShq9u+BoWhqSJZQwe/5Rv0c/u7HQk+qjqFduBsv6I2MIajokHyZINOqbdGOZQxhRRZ1smK28rtVJalsdagWVro9N/0+NF6mILCi/xuKVAWb/X3M3gdOnUHRxf4sFwZx8Zm1o+5g7P+Lc1tKP54oGaXSMPFES+dF2ty8j/z+QtsvdtdRVvc5XT+Rs/bt26N9e7VBciQSQadOnQAATzzxBMrKynD88ccrPYYoBqMuJWMAEFQ4ms78CGrNOqxOw71FKkW8VPSILGokux8/9qF/nayCX5FQ2WmeQiOZ4CORoaj2OabicyEZPxOTRbKEokFROdez1b5Ft3V7DD2Zzwv9PKQy3A61N3IKRfXH0rcxXsJRIzdzgRoDVn1gKXpuIiGnyDYy1aLGQNMqfJblZ4WM288rfSiq/c5wlCgYqsLZdKly9BtfR0p2mzZtwu7du7Fp0yY0NjZizZo1AA6vPp+XlwcAuOeee3DWWWchIyMDzz//PO666y48/fTTHEpPwVARjrpZhCmR7M7XLjjSP0akalRmwSizOensAjbROcRkh37rO652YatdNambRZNkAlE34anZcxGdO1QmFLXiFJb6sdq8kWgoavx/QCwo9RqEVtU3crVgAckYigaxSr2fU0+ITJeh8viyVaRO4ahVlahT5aFTOyMSitoRCQ1Vhaey52EXjqqcG9SpmlP7uzi9pjIBqX5fIoGo6HvbrOMu+3llDENF73cKTLXHMVilZCEaTOoX2pENM1UsjmbWvnsNVc0WDzL9fLE5jnaeyVoBqQoXYrLm9otlcue2227Do48+Gvu9f//+AIClS5fGVpx/+eWXMWvWLNTX16Nfv3548cUXMWzYsEScLgAGo64ke2WU/vzdhqSJCEdlj6kPhtwMJzYezyocFQmqrOZEdeqAGDvMVlWeToGo2W0yoavVEH4rxiH3IuGmWXApejyrx8sQfQ31f2+ZKRZkFu3ywuy9LvuZ5fYzrkoXdBZkZTa7jeQkYyiqCSIcDUJQk+/bhaNmYZbXC3y7kFTfzsjOhamdl1nVqAjR4e0yVaP6alG7kNMsHPUzFDULP0VDZrPtreaX1cjMJaoRDVJEP6ucglBRovvZUXcQdXWHlByTKEz8qCiU3ae+nbd7rOj1gNQCbgqO54XxM0/2ePrzD3yO2SS+tvRK9NopXRZe8tPChQuxcOFC223eeOONYE5GEIPRNOemUkyWUyjpFHaaBZx2j/FzTkWR0Mp4fJnKU7PQzSwcdSLygW63X6uOrDF8dAou3Qai+vtEwlGrfRhfK5nOvv41tKsGjjsPl/MT+hGGAv5/iWMXejIQ9SYVLlzDWLlh1pnys1Mi2/lJREWD2TB70UDULHgzPgc307YYA1KzwNTNkHrR46okOuenGasw0+w9YrdP435ErhG8hKJuAtAtNc2v6zrnBzdHNhHFs7oOkbk+UX0tk5DFqv7vOcRCYJnnb6jwtdrGqVqW1NFfo6T7wksUj8GopOqGJuRnJfos/GMWpFiFpSIVnCIhpdtqTk1O0wHfwlAvVapW+7CqODSGY/oQ1WzovRljZ8cscMs0GdJtNsReT1VQ6vR4t9sY2a2ULEIkFDUjW00qG4jKvM9FQlGGlyTKGHSIDlG160A4haYyHSAvHQkvQ8/cVLio6tSZXdDbrbYqMvxedO5KYwhndi76wNUsHBX5Ms4YVBqrOu3CUbt5RfXHdzPXtpdV5b2Govr7REJ02VA0DIGo1X0MSonUMQZ+yULkM8qP52Z3PeP0RXCQYWcYRtuEnVX7ykrR9MZgNIGsQgltCKrqx7llt0CLVXAY5ErYXo4lsviMaDhqdx5W+3AKxowVplbDLZ2GfJvdbhaQAubhq2gH0mmxI6/D3Z146axqrEJRu0pgM16qQN2+p63CUD8D0K019c1u62jx7ZFx27raBl/OKdlV1Tcir1Viz0Fk7j+v8/eJdFycwkSVnQ2Z4NJrECvacZGtZrCrOBUJSe0WabIK9OyG+hvDUSsyIaVZOCpLfy4iFa0q2hZALFCWIRp8a+w6fV5Wl5cJRO2CUD8eu682eebEJwojt3P26j87wjiCJExYJXqYl2DS66KcDEWJwWgCOIUU2v3GoNPt41SxWrgpyBBUluhQYqdKWdkFnMwCV9lpALTtzMJRO6KBnMi8p1aVpCKdV9kQVKTjKbsoiKpFjqwqgY28zLurIuBvfnuwgajIfRQMu6DCqnOjav4/WfrOk1XHSXRxBiXnYzP8XdUxzY5hN8+o6KgBQCxsM26jD9XMwlGRKkerc7QLW428VHHa0VeLmrUXduGoH6GoaCBq1YaZvQ+c9mncl9N7WcW8oTJB5ua9++N+LyvMEX4sEanldQi82ePdhKMij/FSySly/LCTeY7J8HzckFnAksgKg9EAyYYUbkMNPwNSFavaB3FsFXMrGo9nDDZF5nU0O2fRKlv9dlYhppExFBUJ7+z2LTrUHnDfkZXpdMps62coakUk/LZ6jAiZ97XM5weDzOQnE2qqXABF9arPQQxHEwli/TieXeirD2Dtqj5lV7AXZTym7HBv/eetdo4i86VaDeE3BpVu5ik141S1ajfc3y23VaJ2bZhMUG7cl5+BqJuKTmMganU7g1IidVQtmOZnJWiyrTTv93l6XfBJe4zMNZD0/jmMPyHqdnyDSAu5uR6jh9j3M2Iw6oOwzNtnPA9VQanI8HPjtqo4LRblx/HMgk2RczPebhay2u2jICujWdBmFmKaVYg6DevXM+5bzzjHqcZuuL2esWMrw2l4v9W2VrzM5ynyvhL5+zpRsRq8nqrAc0vNgbi53bwMhdTbzyGOriSqstOM/lxUhaRu5gZzWwXhdR4y2UUoZMJRjeiXPDJTrdhVHMrOW2kM3QpbZTQLR52CVrOA1Nhm6KtJRVevt6oUNZ6P03B/2dXizbhZAAmwXzBM5gtA436c3ruinzMi7YFV+Gn0zc59sf/v1r61q30YHahz9zgiv4guwiPyuCCHYIt+GaqiglNlZWOyBKuijM8liC94w05//ePXF8iU+hiMKhKWMNSOinPUh6vGEM94WxDsjufl+Zo9T6sg2HgOVoG02etl9niz41oFpHrGMM7pb6Gdg11VqdWq606dMa1Bkl393cs2GpUrvNsNUW8+1YXYwmWy/0b8qPx0E2yaPebbPc07nF3aOlf1aI87UMdgVFSYwlArZueo70TJLuDkWD2quOOk8TJsT/Q4VscQuaA3VgsaqzVF2IWlMvNeavvRd7zMwlHAfmEo7X59AKkPSfXBqVlA6kR7jFXA6XRcK7JzhJq97m4WErF6jNPUD3bvXa9D4mWDS30I6uZ+UQ37GIxSeDhWbCdghXJjW6t9Tvh13aFySL3xM81qPlTt8fr9OI7m8HHYua+Vtrr3kNf3T2GrjFAHq26uf4isMBj1IBnCUNWs5z91N8ehWRWryOtqV/2q4u9i9jydAi2r44ruy+zxBVmZcVWrZkO17QJRq32anYNdxaNTUCo7D6qR1zDTiqrKTbPXUWQRNLfvGTsi4ads8GkWcLqlcl+UHIGoHbvzt7pP36FR3TERCWetQlI352LXSdMrzM40rRYyBo/6+1VUHJodS3Z4dlwoqnU+DeEo4BwiGgNUs1DSKiC1YlUl6jTHqtl5uSU7t2dsO4s5+szYBaZWwYEVL/OCamRCza921Aptd0RxnvA+iUgd46ghWWaVpmbtrNf2XmTYv9lxzEJKL6NQZOb7lA1HVYapdvvSXyOEPRwlUoXBqEthCUWNIYnVatCqOc1jKvr6eJ1HVYTMcGLj62dWGeh0LlZ/E/12P4ST1kOgO+ZnxY5vNd9p/Hk4h3lW52H2+MP3m1eVmgWlVqGpHadA1G7RK7NtZckE+k7vI7O/syivQ95FOrJuAstvdqmp2LHSsM/f/SezsAWiZu8xLx0lOzIr4Hp9nZyOpWq4schxtE6KsWpUOEgzLOhk9zin4dmiQ/Jj+zNZfVgfjgLxgatoxWpm7U7TlddFV7vXaGGnVcjppkpWljFAFuH0/tLeT7LvU6c2Q3X1JyAWgO7W7aedYSi9aIBqdHB/navHUXow+9JJ5DFu5lKU+SwPOoyy+gJF9ov2RFVZGj/jvMyBLvIc7Nr0IEe7WB7D5r3jFK6avbfDGI46zcPN4fQki8GoC2EIRa2CFLuARR/6eQli9PsReS1Ez0nkMaLBr9vnpz1O9jnaHVN0n8bHm4WjGqupC5xCWj1t31aMx9Qf1ymEzGk6IFwF6rQv2cDTzXQOTn9j4+uov1DUwiHR96zse1PmolQ0/FQVeH6zs3mHs1v7XOHHHNrPYNTMzrpDyM1P7DmIvO+0bfwMSLVOh7ET4iUQNTtvmTDWy/FFO2tWF/xWHfJmQ6YdhlCbDknU7Vsk/NOOYRx2WZzbslk4KrJPswDVGFjqq0qthr8bmYWiovOuipy3RmZIvBXRBY20967M+9BsP27m/rQjE17udtin0/2iDh1gO0PmvAQ9xseqXnQmiBBKpt3Tqkatqj9FA0uV/JpOx8j4nPXPyapNFx36H7b5T53ex34GpDJfOnLYPPmBwaik6vpG5LVy91jRQEQ2LFR9fNH9OIWUIseTPSeRYzvt067Dbwy5RIJYu9DMbJ/6/Zqdq77T/sP9WVJD8fX7FTkf/TmZ7Q9oHpTaLb5ltTq7vgJUdk5U4zFFA1DrOV/lFiyyet9Yvb52+/OyeJFT+PnNrn3oVtS62W22jzEJON1SuS8S4+b9ZBVmqpp/1guzwNLqd+Px7UJa43m6CUhlO3l2x9DETR1gFXzq50UzVDhZLuThsACGkRZk6vcd9xibzpBZR1Efjhr3aTdHpsgc1sYV70XnAhVZ6d2Km86g2eusYlEjq/uM73/jdk5BqJt5Pe3CUJFws2a3WDib346r0pM6bsOdoB/n6lgeFxXUyLTtIl/6yI7MkA1h/eSmAjVsoadXWhuuYv5SsznS/XgMkYyEBqNvvfUW7rnnHnzwwQfYunUrFi1ahHPOOSd2fzQaxcyZM/Hwww9jz549OOmkk/DnP/8ZRx99dGybiRMn4rXXXsN3332HvLw8DBo0CHPmzMGRRx4JAHjzzTcxZMgQ0+OvWrUKJ554oi/PzUsIqSrAVMWq02kVHopU13k5rtkx7B4rwziPjlmYaXcOZsc16xiLPNb4OJGh+HaBqNntTudkVuVqNUepkX7RKD27xY2cpi5QsdiWU1Wt8fWRXXRI9L2nai5Os9DTLggVDS6rfB5GDwCNAVTypFo7oyqEVB1mqiRaiWr3eSt7POOx9OGVXZWq6PHsnpMxSNQzm7/T7D7tfiuic6s6Le5j9hjjkEt9VZG+g251vsbn5FSxYlzUCWi+sJOeMRS1HWLosHhR3H0S1UqyQ9k1ohWdZYXW7Y9xH07hp9sh66pC0Oodu9CmuHnHVzRANWqsD+azLtXamlTlV0Dpdnh9IpgNm7dbKNHIyzB1WU7zk2rb+Hl8u3Oxux0wtKsWbYZddWkqBatEYZfQYLSurg79+vXDZZddhvPOO6/Z/XfffTfuu+8+LFy4EL1798Ydd9yBoUOH4vPPP0d+/uFxhieccALGjh2Lrl27Yvfu3ZgxYwYqKipQWVmJzMxMDBo0CFu3bo3b76233orXXnsNAwYMcH3uiQ4vg+zU2gU48VWNPxCtrhPl5nEqF4Exe56igRlwODRzeg5WYZv548ynRdBv69ciOFtr1M1lax5Sut+3m3+XVn9H/WtvfC31waNWnWn3t9fvV5bMsHeZas0ggs8wSOZ2Jgzhpexcg6qUFTp/ZgLm56eFRDLb2n0R5zbUMmNVYW4MEvXM5u+0ut/IqsNodrsxyDQjMg+d2ZDLuIDUZCihxixANTIu6gQ4zxEqEora3e8lBDVy+77WAs1uhrk3zbYvK8yx3YcVt6EocHhOUKdwNL9djmPAaRaKJoNkbmuSndM8oULTXAgEmyqrRZ0WUrPcl8RnkUzboH1eGz/Ttc8RrU02TuMhM7pCJlA1BpJWx7L6wlJrg/TsvuQ07lum7TS7XXYRSbvQ1Op3t6Gp3dQ6VlNEuJ3r3IrTavJm5yFbKRpUZenehibUhGz+VXInEo1Go4k+CQCIRCJx365Go1F06tQJ1157LW644QYAQH19PUpKSjBnzhxMnDjRdD9r165Fv379sGHDBvTs2bPZ/QcPHkSXLl0wefJk3HrrrcLnV11djYKCAjz3/gbk5rmf/E3fqKjo9AaxArQWzBiH5wLxoY9eUCtTa8c3O56XeRRFnqvoMe32ZRe46R+rP7bdUDn9/kSev9m5WZ2rnmjlr8yUB1bBhMw8hn4PURfl9LrKvje/2VkXm7vT7VB12SDUrvPqdUijtu/WrZvw0V3noqqqCm3atPG0TxHJ0s7Mf3sdWgu2M0EGl2ahillII/pYK6L7dOubnftMj2EVqFq12W5ee6tjaMfROlP6ANGsetWMiqoZmSoguw40EP+ZLdLp1G/jZnEIjdkiTzILH8V1El2Ezma8rPRu929H5t+Kn6GoRnReULfVn0YibdGhA3X4YNY5gbUzQLjbGq2d2b5tW2CvhyrG8NKP6k8v4arZPmQq++P2YfIlkiiRuUN31B20vL42fqZrygpzmm3rFFaaHUO0HXM7TY7IY2QYR5XILkYpMjd6UBW4dtwErSqC2iDILq4mq6a6Gr27dgq0nQF++DwvGHIDIi3kCouih+pRtXRO4OccZqGdY7SyshLbtm1DRUVF7LasrCycdtppWLFihelFRF1dHRYsWIAePXqgrKzMdL8vvfQSdu7cifHjx9sev76+HvX1PwQ31dXVptsFPR+bVXjj5+rRboMYv1e07lbU2jFYBPyZ89DquRmP1a19rmnYaRVgOp2rVQWptj+zfVXt2ocCgQDUitmclVpFpSy7977+NdH2Lxuwqwjkvc7HafY3l92HzGPcVH7W7N4f61C66aCq6tTW7ElsRWSytDNBV23KhJgy2xqDlyOK8xz3aRf8uJkP0e4YxmBP4yUQNR5HpGpVX7mpDx+tFr6w62zJXG+YVdg4MetAb96737K6yI5x8SYrZlWl+k6PsUrEuEiU1TFj23uYF1SjatV3p/e4yL8Vq32oCEKDlMxzjCayrRFtZ8Iu9u/Y58osFftXUXmuokrdrmLSrMpfz+ozyritaPtj1R5YDeE3m17MLHy0mj7EOOpEJtiUmabH7FjGfcq0fyL8ClGt5h4X3daPalancxGdbiDIOX4peYU2GN22bRsAoKSkJO72kpISfPPNN3G3Pfjgg5g2bRrq6upw5JFHYsmSJWjVynyFpPnz5+PMM8+0vMjQ3HnnnZg5c6bpfaqHN6oaXuvXoida8PKN4Xa/AiARdsc2HtNNcLTWIUy0C6n0j9NvF6v4c/jb6c/X+Jpbno/2N9KFoZqa3fvjgrC4x4nuX1exqD+mFpiahad6Iu9x4+viNlhXEcg7VWiavae0v7vX97zXIe6ioadTuFm7s/mcfXnt7YerJpswtzOyYagx/NCHJF4CRMC/AMVpv0cU57mqcrMKXK22NQ5Rtgsv9ffJvq5WIZZxqKKRdpvV8EDjdm7JVOfrt9fOX/86GjuLTosCaYzPz2ouVMB++J/VYwDrIZ6yvFSBivDy/rLjZyAqMpwegNQXc8kciGoS2dbYtTPJIBUCDdnKc68jA6xCRNkv0aym7xBpK6zaMqepaoyPdWof9dsYb9N/yen0ee3l89zpS1WnkaKyla0iFcFOjzWSXRjL6VzcVjvbEZ1uQJRdoCq7z1rBdS78UrfzW0Qy5VYHjzY2+HQ2ySu0wagmEonE/R6NRpvdNnbsWAwdOhRbt27Fvffei1GjRuGdd95Bdnb8B823336LV199FU8//bTjcW+66SZMnTo19nt1dTXKysqwteYAcvLi//H7PWxcNAAEfgjmgghXREM1q3PRB4hO52sMKe3CJ5Hn7qbiba3Da2u3z4Ki1o6BmTHMzG+XYxlKGxmDVe1c9OFW7U5vwZbZOeiPaxWeCu1bIEzUtjEew2y7ZudhElA7HdcqrDYy/q2MtPeul3+Tsu9XkdDT+F4wC0LNHqfxGpLW7tyJnHx/h0yLCls7s6VqP7Jz44fS+xWSGHldYVqVdu1bCwc4u3fuQztdx00m+NG2NQthzcJLwH2VrD6wNTuWsdLSaY43jV2HTjaQE53b1bh//fPRpipw6tCadSaNHUm7TpxodYvZlARWx7MiGzp7qfI2vjfs3s9WXwJYCVuVqN2co6kQiBoloq2xamfCTnUgajWvopsV3M3mTJatkLMLKd1Oi2Ks0DQyBnRWgd7mvfstP9ONn9d2VZz6z0HjyAirz1yzUNTqXK0+Z41tkNVzNLKam9mK04gQu0Xx9PSviXHKPbu2SeWiU7IBvfExdlXAMgt7ueX0ZYLdl6xEmtAGo6WlpQAOf8vasWPH2O3ff/99s29cCwoKUFBQgPLycpx88slo27YtFi1ahNGjR8dtt2DBAhQVFWHkyJGOx8/KykJWlvVcDarDUC8BkjFw0X73Mtz1cADSXvf/iP0uS38e+gtdp7BJ/xiZUEnkeYuEQGbP127fZq+T9nzdhLXG3+3CVWOoqp1L3Y5NcdvV7diE3OKuult+OFen0Es7H7vOimhYrvGjmhcQDzy1c5D5MsHsPWDXsTPuV9UwdI3Ye1nucdr7Rv9eMb53nI6rvYdsj7N7l+V9QQh7OwN4r/bUyAYiViGo1ee5/j4v0zRoj5cNYd2Gtlqgqg9INWYVntptbgImu+pWY8fTaYi6Fa/TLlh17Oy2M74mxipcY4fWqtpGv43dc9RXlYpWqdgN0XQ6nh23nWhRTu8z0ekpwhaI6qViAGqUyLZGpJ0JCzdhqMjwXadhv9rvsuGmcWE8s3NwqlbXk63ElF2zwil0tGM1N7doFaexHXD6ks9sJILVuZp9thrP1ylEtdtG9Hj689TvzynMNbZ7TgE34H7+VLMqVqt9WYWlTu9js4W93DAGxtr/ixxT9H7R6myn511Xd8j2+JQcQhuM9ujRA6WlpViyZAn69+8PAGhoaMCyZcswZ84c28dGo9G4+XS02xYsWIBLL70ULVt6n5vDbtEfN8yGIZsu5GMyvNcq1NF3TvUXniKdVX0wZgzJzC5ijUGV/nzcXPR6uVAWWfU0r317y8BG5Plq9MfRP87qMVaBXtWufabnbbUf4/vA+B7Qnl98CBrP+DytKgBF/xZe5jEV2Zf2/FQeR78/u7+NntW/JdHXSWQ7mTlA/Rzebvc5oDELx/S35bcrs3w+jfXBVSCaCXs7Axy+yFYRjuoDk6921OKI4jzbsEQLDI2Bo93713ifU7sj+m+mncXciXZhqMhjjNuYhUrGjqD293B6/axoj5Ot9Asbs8oa43PSv3Z2i055YbcSsNU2KolUIWncLJSk6n2S7O83Lw7uT/was8nQ1oSBm4WVjJWfro8tEYpqlaLGBZKc9uFUOScSdqlaUEhP5HPM7vPLbH5OszZCfxzR5yHyuWncxirENTsvN4s9Gr8otduX8bWVrUrVU/G3N+7Dj/eTW1YhsFVQ/P/bu/eoKOv8D+DvIWVmuMtFQAVJ09T1Z2RuirUqXYRqS7e9dLGS1nA7RWDZsVwtEdK1jpZmZVoGldbasWzV1kuWmuYlM0zyuiiCIbpKCqgp4Hx+f7gzzsDcmZnnGeb9OsdznHlu3+/zHeY985nn4om2N/+R1dnr9VLbpGhh9OzZsygrKzM9Li8vx65duxAdHY3k5GSMGzcO06dPR48ePdCjRw9Mnz4dISEhePDBBwEAhw8fxpIlSzB8+HDExcWhqqoKL7/8MvR6Pe68806LbX399dcoLy/HmDFjWtXmxHAdQsOu/Mrizg1onOXSzWfsXA+xecHHk4Ulm6c1Ozhd2dqpzrau6ejo1OnmKk6dc9jHy4VI+6cSObOfHM3jdNtjQ+2227ie5gX0rjEhVwroZutwpn+A7csZONN3e30ztsv8GqRWuTK2Lr4OPMbOafn29pOt/ePMZQPM1+vpQrA9xteAvdeOo/ZYm26rP02/6lDWYm7P8sec6RypR0jYlaPrPHmXdmNRD/BtscT82oO2ipbW2GujteKkoz7ZK0za28/mRzu2ZjyMy9r70mbvMWD/FERvFSCtcbQtW9OdaaOjLzyuXFut+ZEenvgyZesLnCf2v6f/5n3NUz/meEqDj5rij1mjZs3vIu2oUGqvKOmNu2Ub1+lo3bbuLu/oJnq23uPcLai6wtr7mPE5R9syPxLRmfwyL0g5Wtae5qf521u+te/TxsJm8/dpZ9frSq474srp7p5av6MiorunzrfmdezKTSltLWPrOWfoDao91pBcoOgofv/990hPTzc9Nl4DZ/To0SguLsaECRPw66+/4oknnsDp06cxcOBArF27FuHhl6+9ptPpsGnTJsyePRunT59GfHw8hgwZgi1btqBjx44W21q4cCEGDx6M3r17t6rNCWHBCAvXorr+oqK/stgqmtq7AY5Ra25O48z63VnGfB53tmFtXXb76UKRzV57rB7V62b7rbW7+bqsFeLNXwumQmmzwrRTBVor87jaF/P22fo/4Jkjrb3xo4Qz7fLU67M1PHGDKas89HfhjIqa84jX6bGxVWtxzB9zxpynCl22Psj7kquFWGePFLF3dIgr63VmX7d2PIzL21qPveu1OfuFVE1a2yZ3v6Q0P4rMnS9N9rjTL0eXBzDO48vitrc4cx1AX23zwjnfXEfO37PGGUHnLl/+xhAa49PtAi0LpUbmBVNXi6mubMfd9QH2r31s5Ox7nTPzuXPasCPW3vPsFW/tvUc6KrbZukO8sz8KOlvENV+/J/PT01ncmnHz1h3snV23N7evxu2Sf9OIiPLnmPiBuro6REZGorS8CoZg3x65Vl1/0e701t6JtjVcCR17yzrzhcEZ7u4LY0HMG8U2V+/w68l1WCv0eaqPavwS7guuvMZcuUlKIPr1bD1y0vuitrYWERERSjdHccacWbWrHKHh4Y4XMGPvw31rXne+KmqYU6ow5Op7mjv71Zlt2DvawpN3oXW0bU+t25nT213dbmuuBegrPPXuCk9lnzufO87V1+OO1KuZM/9jzJmTh/ciLCHFqWWMBVFXKVFA9ZUzDQZEBQe1KJa2pjjr7I2cms/njfc3d27G4w57fXCUE86+xzp79K352QWeuGGQr4pztm4C5onXhTt3bvfm69IWe9f2dXaZ1qivq0PP5E4+zxnj+3m7/xvl1l3pm0oXMxvN8LhfN0RqPX9Khv3thaD2ou0/8MRwdV9U3Zn2eaoPrqzHvOBs7cO2r/erJ7ZnXIexb46+RFjbZnX9RdW/ppTUmn2j9v3q6EcYT7f/bL3G8UwBKDa0HcJcvFaivb91tf6IobZ2eepLjL3TzFzdhq35XfkS4Il+2fqy5e667S3nzdNevcHWvucRK1e4erqnJ/cdT3G0LehcDQyhMW4XPp1ZvzP8sYBqLIDaO8LU1nRbxVJn36eaz+fN97fWbMeV669ayzRH7wOtfZ9w9lTq1m7HUbHSE+NnbR3efl24Oqa+pOS2yX/x04KLIoKDEKG1H4LeEPm/bdZedO80Dm+LbLZP1NpOc5Fa359S2nw/Ac7vK2vL2lpPa/rWumVd+9uw13fzdTWfz9XtuMMfXsOe5uu/iaAGfnCxJlJ7FayVWpQotDhzB1Jry/grb31B8dS6Xd2mv2/LHkcFCXPungLrVDtUsj/8mTf34VXMGbu8VRRVSxvUWHR15b3Lm4zvi9aOcnX1b9K4DotLGzgqnNk5uratvq96vVhpZRw8tU5z3sxUX3Hn79B4pLj5Y2rpyJEjKCwsxNdff43jx4+jU6dOeOihhzBp0iQEB185slWjaXmAzLx58/D444/7srkmLIy6SG+4AL3BtUOVPbr99sCvQY6PstEbfHzKbrP3Bb3/fi/2Livvn07vKwfvvarY5y7mg902m62rxXw+yCFV7M82LqRdg9JNUC1/+VLgL+10l73r2tksgJodSdT8QzQpg2MQuII49gHN20XX5tddVfI6rK6y9b7YmvdLpZYlS97el4E6Vs37bXzMnLG0f/9+GAwGzJ8/H9dccw1++uknZGdn49y5c5g5c6bFvEVFRcjMzDQ9joyM9HVzTVgY9UM+L3oSEVHA8pfipy8/qDu7rUD98kBE1NaZF12bF2AdFWT9oXBKROSOzMxMi2Jnt27dcODAAcybN69FYTQqKgoJCQm+bqJVLIwSERGRKrGwSEREasKiJhGpyqVGuHw39UuXL5NVV1dn8bRWq4VW6/l7YtTW1iI6OrrF8zk5OXjsscdw9dVXY8yYMRg7diyCgpT57M/CKBERkYpEBgchwsMFQTVeB4lFTyIiZRhComEIjVDFNUbVwtqp8UREahUcHIyEhAQc3/uJW8uHhYUhKSnJ4rkpU6YgPz/fA6274tChQ5g7dy5mzZpl8XxhYSFuvfVW6PV6fPXVVxg/fjxOnTqFyZMne3T7zmJhlIiIqI1zpgjp6eIpC59EROrmyQKgWousrvSRBVEi8hc6nQ7l5eVoaHDvng0i0uIGSPaOFs3Pz8fUqVPtrnPHjh0YMGCA6fGxY8eQmZmJP//5z3jssccs5jUvgKampgIACgoKWBglIiIi5TgqZPJGQkREZIs3iopB52pYrCQiskGn00Gnc3xjbk/IycnB/fffb3eelJQU0/+PHTuG9PR0pKWlYcGCBQ7XP2jQINTV1eHEiROIj49vbXNdxsIoEREROcSiKBER+RKLokRE6hAbG4vY2Fin5q2qqkJ6ejpuuOEGFBUVOXXd0JKSEuh0OkRFRbWype5hYZSIiIiIiIiIiIjcduzYMQwbNgzJycmYOXMmTp48aZpmvAP9ihUrcPz4caSlpUGv12P9+vWYNGkSxo4d65WbPzmDhVEiIiIiIiIiIiJy29q1a1FWVoaysjJ06dLFYpqIAADat2+Pt956C8888wwMBgO6deuGgoICPPnkk0o0GQALo0RERERERERERNQKWVlZyMrKsjtPZmYmMjMzfdMgJ/GCYURERERERERERBRwWBglIiIiIiIiIiKigMPCKBEREREREREREQUcFkaJiIiIiIiIiIgo4LAwSkRERERERERERAGHhVEiIiIiIiIiIiIKOCyMEhERERERERERUcBhYZSIiIiIiIiIiIgCTjulG+AvRAQAUF9fr3BLiIjaBuP7qfH9NdAxZ4iIPIs5Y4k5Q0TkWcyZtoGFUSfV1NQAALr36adwS4iI2paamhpERkYq3QzFGXPmmh49FG4JEVHbwpy5jDlDROQdzBn/xsKok6KjowEAlZWVfvuCr6urQ1JSEo4ePYqIiAilm+Myf28/wD6oBfugDrW1tUhOTja9vwY65ow6sA/K8/f2A+yDWjBnLDFn1IF9UAf2QXn+3n6AOdNWsDDqpKCgy5djjYyM9Ns/WqOIiAi/7oO/tx9gH9SCfVAH4/troGPOqAv7oDx/bz/APqgFc+Yy5oy6sA/qwD4oz9/bDzBn/B1Hj4iIiIiIiIiIiAIOC6NEREREREREREQUcFgYdZJWq8WUKVOg1WqVborb/L0P/t5+gH1QC/ZBHdpCHzypLewP9kEd/L0P/t5+gH1Qi7bQB09qC/uDfVAH9kEd/L0P/t5+oG30gQCNiIjSjSAiIiIiIiIiIiLyJR4xSkRERERERERERAGHhVEiIiIiIiIiIiIKOCyMEhERERERERERUcBhYZSIiIiIiIiIiIgCDgujDmzYsAEajcbqvx07dpjmq6ysxN13343Q0FDExsYiNzcXDQ0NCrbc0hdffIGBAwdCr9cjNjYW9957r8V0a/17++23FWqtdY76oPYxSElJabGPn3/+eYt51D4OzvRB7eNgdPHiRaSmpkKj0WDXrl0W09Q+Dkb2+qD2cbjnnnuQnJwMnU6HxMREPPzwwzh27JjFPP4yDq3VVnIGYNYojTmjLswZZTFnrmDOqGtM/TlnAGaNmjBnlMWcaTvaKd0AtRs8eDCqq6stnnvhhRewbt06DBgwAABw6dIl3HXXXYiLi8PmzZtRU1OD0aNHQ0Qwd+5cJZpt4dNPP0V2djamT5+OW265BSKC0tLSFvMVFRUhMzPT9DgyMtKXzbTLUR/UPgZGBQUFyM7ONj0OCwtrMY+axwGw3wd/GQcAmDBhAjp16oQff/zR6nS1jwNguw/+MA7p6en4+9//jsTERFRVVeHZZ5/Fn/70J2zZssViPn8Yh9ZqCzkDMGvUMg7MGfVgziiLOXMFc0Y9Y9oWcgZg1qgFc0ZZzJk2RMglDQ0N0rFjRykoKDA99+9//1uCgoKkqqrK9NzHH38sWq1WamtrlWimSWNjo3Tu3Fneffddu/MBkGXLlvmmUS5ypg9qHgOjrl27ymuvvWZ3HjWPg4jjPvjDOIhcbmevXr1kz549AkBKSkospqt9HETs98FfxsHcv/71L9FoNNLQ0GB6zh/GwRv8LWdEmDVqGQfmjPJjYMScUR/mzBXMGWW0hZwRYdaoZRyYM+rDnPFfPJXeRcuXL8epU6eQlZVlem7r1q3o27cvOnXqZHouIyMDFy9exM6dOxVo5RU//PADqqqqEBQUhOuvvx6JiYm44447sGfPnhbz5uTkIDY2Fr/97W/x9ttvw2AwKNDilpzpg5rHwNzLL7+MmJgYpKamYtq0aVZPBVDrOBjZ64M/jMOJEyeQnZ2NDz/8ECEhITbnU/M4OOqDP4yDuV9++QWLFy/G4MGD0b59e4tpah4Hb/G3nAGYNWoZB4A5owbMGXWMgznmjCXmjDLaSs4AzBqlMWeUH4PmmDP+jafSu2jhwoXIyMhAUlKS6bnjx48jPj7eYr4OHTogODgYx48f93UTLRw+fBgAkJ+fj1dffRUpKSmYNWsWhg4dioMHDyI6OhoAUFhYiFtvvRV6vR5fffUVxo8fj1OnTmHy5MlKNh+Ac31Q8xgY5eXloX///ujQoQO+++47TJw4EeXl5Xj33XdN86h5HADHfVD7OIgIsrKy8Pjjj2PAgAE4cuSI1fnUPA7O9EHt42D03HPP4Y033sD58+cxaNAgrFy50mK6msfBm/wtZwBmjVrGgTmj/BgwZ9QxDkbMGeuYM8poCzkDMGuUHgfmjPJjYI4500YoebiqkqZMmSIA7P7bsWOHxTJHjx6VoKAgWbp0qcXz2dnZMnz48BbbaN++vXz88ceKtn/x4sUCQObPn29a9sKFCxIbGytvv/22zfXPnDlTIiIivNJ2b/RBiTFwpQ/WLF26VADIqVOnbK5fTeNgTfM+qH0c5syZI4MHD5ampiYRESkvL7d66klzahoHZ/qg9nEwOnnypBw4cEDWrl0rN910k9x5551iMBhsrt8X4+BJ/p4zrvSBWaN83lvDnPF9H5gz6hgHI+YMc0ZNf1tqzRlX+mANs8a37WfOqOtvoa3nTKAI2CNGc3JycP/999udJyUlxeJxUVERYmJicM8991g8n5CQgO3bt1s8d/r0aTQ2Nrb4lcNTnG1/fX09AKBPnz6m57VaLbp164bKykqbyw4aNAh1dXU4ceKEX/RBiTEA3HsdGQ0aNAgAUFZWhpiYGJvzqGUcrGneB7WPw0svvYRt27ZBq9VaTBswYABGjRqF999/3+qyahoHZ/qg9nEwio2NRWxsLHr27InevXsjKSkJ27ZtQ1pamtVlfTEOnuTvOQMwa9SQNcwZ5oynMGeYMwBzxhv8PWcAZo0asoY5w5whBSldmfUXBoNBrr76ahk/fnyLacYLAx87dsz03D//+U9VXBi4trZWtFqtxUW+jRdcN/+1srm5c+eKTqeTCxcu+KKZdjnTBzWPgS0rVqwQAFJRUWFzHjWNgzXN+6D2caioqJDS0lLTvzVr1ggAWbp0qRw9etTmcmoaB2f6oPZxsKayslIAyPr1623Oo6Zx8AZ/zRkRZo1axqE55ozvMWfUMQ7WMGeYM0prizkjwqzxNeaM8mNgC3PGf7Ew6qR169YJANm7d2+LaU1NTdK3b1+59dZb5YcffpB169ZJly5dJCcnR4GWtpSXlyedO3eWNWvWyP79+2XMmDHSsWNH+eWXX0REZPny5bJgwQIpLS2VsrIyeeeddyQiIkJyc3MVbvkVjvqg9jHYsmWLvPrqq1JSUiKHDx+WJUuWSKdOneSee+4xzaP2cXCmD2ofh+asnbah9nFozlof1D4O27dvl7lz50pJSYkcOXJEvv76a7n55pule/fupg8J/jYOnuDPOSPCrFEac0b5MbCGOaMM5ox1zBnl+XPOiDBr1DIO5pgzymDOtC0sjDrpgQcekMGDB9ucXlFRIXfddZfo9XqJjo6WnJwc1fwK0NDQIOPHj5eOHTtKeHi43HbbbfLTTz+Zpq9atUpSU1MlLCxMQkJCpG/fvjJ79mxpbGxUsNWWHPVBRN1jsHPnThk4cKBERkaKTqeTa6+9VqZMmSLnzp0zzaP2cXCmDyLqHofmrIWw2sehOVvXFVLzOOzevVvS09MlOjpatFqtpKSkyOOPPy4///yzaR5/GwdP8OecEWHWKI05o/wYWMOcUQZzxjrmjPL8OWdEmDVqGQdzzBllMGfaFo2IiC9O2SciIiIiIiIiIiJSiyClG0BERERERERERETkayyMEhERERERERERUcBhYZSIiIiIiIiIiIgCDgujREREREREREREFHBYGCUiIiIiIiIiIqKAw8IoERERERERERERBRwWRomIiIiIiIiIiCjgsDBKREREREREREREAYeFUWqTUlJSMHv2bNNjjUaDzz//3Ob8w4YNw7hx41q9XU+tx5qsrCyMHDmyVetISUmBRqOBRqPBmTNnbM5XXFyMqKioVm2rrTHuN+4XIgKYM7YwZ9zHnCGi5pg11jFr3MesIWqJhVEiN2zYsMFqEH/22WcoLCw0PW7+YUYNCgoKUF1djcjISKWborji4mJoNBpkZmZaPH/mzBloNBps2LDB9Fx1dbXqxpKI2i7mTNvAnCEiNWPWtA3MGqLWYWGUyIOio6MRHh6udDPsCg8PR0JCAjQajdJNQWNjo9JNQLt27fDVV19h/fr1dudLSEjgBy8iUhxzxjXMGSIi1zFrXMOsIfJvLIySz1n7xTE1NRX5+fmmx2fOnMHYsWMRHx8PnU6Hvn37YuXKlabpW7ZswZAhQ6DX65GUlITc3FycO3fOY21ctGgRBgwYYArcBx98EP/9738BAEeOHEF6ejoAoEOHDtBoNMjKygJgedrJsGHDUFFRgaefftp0ygIA5OfnIzU11WJ7s2fPRkpKiunxpUuX8MwzzyAqKgoxMTGYMGECRMRiGRHBK6+8gm7dukGv1+O6667D0qVL3epvcXExkpOTERISgj/84Q+oqalpMc+KFStwww03QKfToVu3bpg6dSqamppM0/fv34+bb74ZOp0Offr0wbp16yxO9zly5Ag0Gg0++eQTDBs2DDqdDosWLQIAFBUVoXfv3tDpdOjVqxfeeusti21XVVXhvvvuQ4cOHRATE4MRI0bgyJEjpukbNmzAjTfeiNDQUERFReGmm25CRUWFU30PDQ3Fo48+iueff97FvUZEasWcYc4wZ4jI25g1zBpmDVHbwMIoqY7BYMAdd9yBLVu2YNGiRdi7dy9mzJiBq666CgBQWlqKjIwM3Hvvvdi9ezeWLFmCzZs3Iycnx2NtaGhoQGFhIX788Ud8/vnnKC8vN31QSEpKwqeffgoAOHDgAKqrqzFnzpwW6/jss8/QpUsX02ke1dXVTm9/1qxZeO+997Bw4UJs3rwZv/zyC5YtW2Yxz+TJk1FUVIR58+Zhz549ePrpp/HQQw9h48aNLvV1+/bt+Otf/4onnngCu3btQnp6Ol566SWLedasWYOHHnoIubm52Lt3L+bPn4/i4mJMmzYNwOUxGzlyJEJCQrB9+3YsWLAAkyZNsrq95557Drm5udi3bx8yMjLwzjvvYNKkSZg2bRr27duH6dOn44UXXsD7778PADh//jzS09MRFhaGb775Bps3b0ZYWBgyMzPR0NCApqYmjBw5EkOHDsXu3buxdetWjB071qVfj/Pz81FaWur2hzAi8i/MGeYMc4aIvI1Zw6xh1hD5CSHysa5du8prr71m8dx1110nU6ZMERGRNWvWSFBQkBw4cMDq8g8//LCMHTvW4rlNmzZJUFCQ/Prrr1a3AUCWLVtms01Dhw6VvLw8m9O/++47ASD19fUiIrJ+/XoBIKdPn7a7Hmt9nTJlilx33XUWz7322mvStWtX0+PExESZMWOG6XFjY6N06dJFRowYISIiZ8+eFZ1OJ1u2bLFYz5gxY+SBBx6w2Q9r7XnggQckMzPT4rn77rtPIiMjTY9/97vfyfTp0y3m+fDDDyUxMVFERFatWiXt2rWT6upq0/Qvv/zSYr+Xl5cLAJk9e7bFepKSkuSjjz6yeK6wsFDS0tJERGThwoVy7bXXisFgME2/ePGi6PV6WbNmjdTU1AgA2bBhg81+21JUVGTq5/PPPy89e/aUxsZGOX36tACQ9evX25yfiNSLOcOcMcecISJvYNYwa8wxa4j8F48YJdXZtWsXunTpgp49e1qdvnPnThQXFyMsLMz0LyMjAwaDAeXl5R5pQ0lJCUaMGIGuXbsiPDwcw4YNAwBUVlZ6ZP321NbWorq6Gmlpaabn2rVrhwEDBpge7927FxcuXMDtt99usR8++OADHDp0yKXt7du3z2JbAFo83rlzJwoKCiy2lZ2djerqapw/fx4HDhxAUlISEhISTMvceOONVrdn3o+TJ0/i6NGjGDNmjMW6X3rpJVM/du7cibKyMoSHh5umR0dH48KFCzh06BCio6ORlZWFjIwM3H333ZgzZ45Lv2QbPffcczh58iTee+89l5clIv/CnGHOMGeIyNuYNcwaZg2Rf2indAMo8AQFBbW4toz5Bav1er3d5Q0GA/72t78hNze3xbTk5ORWt+/cuXMYPnw4hg8fjkWLFiEuLg6VlZXIyMhAQ0NDq9fvqP/OMBgMAIAvvvgCnTt3tpim1WpdWlfzttja3tSpU3Hvvfe2mKbT6SAiTp/mERoaarFeAHjnnXcwcOBAi/mMpxkZDAbccMMNWLx4cYt1xcXFAbh8PZ/c3FysXr0aS5YsweTJk/Hll19i0KBBTrUJAKKiojBx4kRMnToVv//9751ejojUhznDnDFfL8CcISLPY9Ywa8zXCzBriPwVC6Pkc3FxcRa/ftXV1Vn8KtqvXz/8/PPPOHjwoNVfWPv37489e/bgmmuu8Ur79u/fj1OnTmHGjBlISkoCAHz//fcW8wQHBwO4fEFxe4KDg1vMExcXh+PHj1sE765du0zTIyMjkZiYiG3btmHIkCEAgKamJuzcuRP9+/cHAPTp0wdarRaVlZUYOnSo+53937q2bdtm8Vzzx/3798eBAwds7vNevXqhsrISJ06cQHx8PABgx44dDrcdHx+Pzp074/Dhwxg1apTVefr3748lS5agY8eOiIiIsLmu66+/Htdffz0mTpyItLQ0fPTRRy59iACAp556Cq+//rrV6ysRkf9gzjBnjJgzROQtzBpmjRGzhsi/8VR68rlbbrkFH374ITZt2oSffvoJo0ePNv2SBgBDhw7FkCFD8Mc//hFffvklysvLsWrVKqxevRrA5dMDtm7diieffBK7du3Cf/7zHyxfvhxPPfWUR9qXnJyM4OBgzJ07F4cPH8by5ctRWFhoMU/Xrl2h0WiwcuVKnDx5EmfPnrW6rpSUFHzzzTeoqqrCqVOnAFy+s+PJkyfxyiuv4NChQ3jzzTexatUqi+Xy8vIwY8YMLFu2DPv378cTTzyBM2fOmKaHh4fj2WefxdNPP433338fhw4dQklJCd58803TBb6dZfxV8pVXXsHBgwfxxhtvmPa10YsvvogPPvgA+fn52LNnD/bt22f6FRMAbr/9dnTv3h2jR4/G7t278e2335ouVO7oV9f8/Hz84x//wJw5c3Dw4EGUlpaiqKgIr776KgBg1KhRiI2NxYgRI7Bp0yaUl5dj48aNyMvLw88//4zy8nJMnDgRW7duRUVFBdauXYuDBw+id+/eLu0H4PIvxVOnTsXrr7/u8rJEpB7MGeaMOeYMEXkDs4ZZY45ZQ+THFLiuKQW42tpa+ctf/iIRERGSlJQkxcXFFhcqFxGpqamRRx99VGJiYkSn00nfvn1l5cqVpunfffed3H777RIWFiahoaHSr18/mTZtmml6ay9U/tFHH0lKSopotVpJS0uT5cuXCwApKSkxzVNQUCAJCQmi0Whk9OjRVtezdetW6devn2i1WjH/c5s3b54kJSVJaGioPPLIIzJt2jSLC5U3NjZKXl6eRERESFRUlDzzzDPyyCOPmC5ULiJiMBhkzpw5cu2110r79u0lLi5OMjIyZOPGjTb7ae1C5SKXLwbepUsX0ev1cvfdd8vMmTNbXJB79erVMnjwYNHr9RIRESE33nijLFiwwDR93759ctNNN0lwcLD06tVLVqxYIQBk9erVInLlQuXm+9Bo8eLFkpqaKsHBwdKhQwcZMmSIfPbZZ6bp1dXV8sgjj0hsbKxotVrp1q2bZGdnS21trRw/flxGjhwpiYmJEhwcLF27dpUXX3xRLl26ZHM/GFm78HhTU5P06dOHFyon8mPMGeZMc8wZIvI0Zg2zpjlmDZF/0og4cTEOImoTUlJSMG7cOIwbN87r2/r2229x8803o6ysDN27d/f69nyhuLgY48aNs/ilm4iIrmDOtA5zhojIMWZN6zBriCyxMEoUQFJSUlBdXY327dujqqoKkZGRHlv3smXLEBYWhh49eqCsrAx5eXno0KEDNm/e7LFtKCksLAxNTU3Q6XT8EEFEZANzxn3MGSIi5zBr3MesIWqJN18iCiAbN2403S0yPDzco+uur6/HhAkTcPToUcTGxuK2227DrFmzPLoNV/3mN79BRUWF1Wnz58+3eXF0a4wXkze/dhQREVlizlzBnCEi8g5mzRXMGqLW4xGjRNRmVVRUmD40NRcfH+/xD1JERBRYmDNERORtzBoi72JhlIiIiIiIiIiIiAJOkNINICIiIiIiIiIiIvI1FkaJiIiIiIiIiIgo4LAwSkRERERERERERAGHhVEiIiIiIiIiIiIKOCyMEhERERERERERUcBhYZSIiIiIiIiIiIgCDgujREREREREREREFHD+H9QDU6wOkNLkAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(nrows = 1, ncols = 3, figsize = (15, 4))\n", "\n", "levels = np.linspace(-25, 25, 26)\n", "\n", "psi_avg.plot.contourf(ax = axes[0], x = 'grid_yu_ocean',levels = levels, add_colorbar = False)\n", "\n", "psi_avg_mean_3.plot.contourf(ax = axes[1], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "p = (psi_avg - psi_avg_mean_3).plot.contourf(ax = axes[2], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "cbar_ax = fig.add_axes([0.92, 0.15, 0.01, 0.7])\n", "fig.colorbar(p, cax = cbar_ax, label = 'Transport (Sv)')\n", "\n", "axes[0].set_title('Residual')\n", "axes[1].set_title('Mean')\n", "axes[2].set_title('Eddy')\n", "\n", "for ax in axes:\n", " ax.set_ylim(1037.5, 1032)\n", " ax.set_xlim(-70, -35);" ] }, { "cell_type": "markdown", "id": "4b64145b-4b4c-4480-972a-51112c466756", "metadata": { "tags": [] }, "source": [ "### All three methods yield similar plots of the decomposition of the meridional overturning streamfunction. \n", "\n", "The exact numbers resulting from the transformations differ, due to the different numerical methods. `xhistogram` is exact when compared to snapshots of MOM5 model output, and is hence most appropriate when comparing between online and offline binned quantities. `xgcm` and the Lee method can still be used to compare quantities binned offline. For example, if we were to instead bin the daily transports onto isopycnals and calculate eddy terms directly from the correlation of velocity and thickness fluctuations, `xgcm` and the Lee method may be better as the weighted binning onto isopycnals leaves less chance of 'gaps' between density layers. The Lee method has no issues with partial cells, but it is **much slower** than `xgcm`.\n", "\n", "The difference in the mean streamfunction between the three methods is presented below." ] }, { "cell_type": "code", "execution_count": 33, "id": "8d5f00b8-a2de-4328-b665-195eb75c2842", "metadata": {}, "outputs": [ { "data": { "image/png": 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t8dvf/hZvvPEGRo0ahZycHCiKgjVr1mD27Nk477zz0L17d1P/n6JccsklhtfDar9LL7200bXevXsDAFq3bo3TTjut0f0+ffoA8PauucHJu7927VqsWrUKOTk5jg7oc8uCBQsAAL/61a8a3UskErj22mtTwum59NJLkZWVOrXJzs5Gr169AATf1oQQQghJb5qGXQBCCCEkiuzatQsAUFhY6Hten376KQBg2bJl+NnPfmYY5ttvvwUAbNq0qdG9iooKNGnSpNH1//3vf6ipqUFOTg5GjRplmK6iKKbpAkB5ebnh9Xbt2mHNmjXJdgKQPDTm6KOPNoyjR613TU2Nab1ramosy+cGqzoBSKmTU7Kzs3HOOefg4Ycfxvz589G5c2d89tlnOOmkk9C2bVvTeLt27cL69esBAFdccYVlHjU1Nfjhhx9QUlICAFixYgVOPvlkbN682TTOtm3bDK8XFxejqKio0XUvbTF06FAMHToUe/bswQcffID33nsP8+fPx6JFi7BhwwaMGjUKH374IQ466CDHaRcXF6O4uLjR9bDar23btoZ9hPqszd419b6Xd80NTt599Xs+5JBDUFBQ4Gu5fvzxR3z33XfJ/Iw49NBDAezv14zw87smhBBCCNFDhSohhBBiwIYNGwD8NBn3E/WU7I0bN2Ljxo2WYffs2dPompHFmTbduro6vPvuu5bpqopL0bRVSzBVIQsAVVVVAICWLVta5qUvX1VVlW35jOrtFid1csPFF1+Mhx9+GHPmzEHnzp2T16xQ2wKAbVsAP7VHfX09zjnnHGzevBmjRo3CDTfcgEMPPRQtW7ZEkyZNsHbtWlRUVCStZfXYtYUX8vPzceyxx+LYY4/F9ddfj3feeQcjRoxAdXU17r33Xvz1r391nKbduw4E237NmjUzvJ5IJITue33XnOLn9+wFrbLTrM9VFeBmuwb8/q4JIYQQQrRQoUoIIYToaGhowNKlSwEARx11lO/5tWjRAgBw00034fbbb5eebocOHfDNN99IS9cM1Yrtxx9/FAqvlm/gwIF45513/CpW4Bx99NGoqKjASy+9hJYtW6KwsNDUpYGK2hbAfgV4dna2UF7vv/8+1q5di86dO+Nf//oXcnNzU+7bKeiD5Gc/+xmuvvpq3H333Xj//felpp0J7QfYK2Krq6ul5eX0e/aC9vlt3boV7du3bxRGtdL321qWEEIIIUQE+lAlhBBCdDz//POorKxEdnY2hg8f7nt+6hbXzz77TGq6FRUVyM7OxpYtW0y3LMtE3ZK7bNkyofBqvT///HM0NDT4Vq4wuPDCC1FbW4tvv/0WZ555JvLz8y3DFxUVoaysDACwcuVK4XzUbe59+/ZtpAwErH1/hkG3bt0A7Fd6alEVhW7JlPZTrTDV7fF61q5dKy0v9XtetWqVsC9pt8+xZcuWSTcIq1atMgyjPtfu3bu7yoMQQgghRCZUqBJCCCEavv76a1xzzTUA9h9+06FDB9/zPOmkk5CTk4P58+fjiy++kJZus2bNcOKJJ6KhoQEPPPCAtHTNGDVqFLKzs7Fs2TKhbdcVFRXo2bMntm3bhr/97W++ly9ILr74Yhx//PE4/vjjMW7cOKE4Z5xxBgBgxowZwvmoilrVek/L3r17HaXlle+//952W/WSJUsA7H/2WtR6eHHtEPf2E0FVSC9fvrzRvQ8++ECqAri8vBw9e/ZEXV2dcP/h5TmeeOKJAIAHH3yw0T1FUZLX1XCEEEIIIWFChSohhBCC/cqgBx54AP369cOWLVtwyCGH4L777gsk77KyMowfPx579+7FiSee2OgUdEVR8P777+MXv/iF45Oqf//73yM3Nxe33347/vCHPzRSdGzZsgV//OMf8cgjj3itBtq3b59URp9xxhmNTuPevHkzbrvttpRr06dPRyKRwC9/+Us89thjjU5f/+qrr3DHHXckT3CPC926dcNrr72G1157DQMGDBCKc8MNN6B169Z44oknMHHixEZbrbdt24bHH388xS3E0UcfjaZNm+Ldd99NUUrv2LEDF154oaGi0C/mzJmD3r17469//St++OGHlHs//vgjfve732HOnDkAgJ///Ocp91VF4eLFi13nH/f2E2HkyJEAgL/+9a8pbhO++OILjBkzBk2byvXmpbbV1KlT8cADD6T4kt29ezcee+yx5OFVANC1a1cA+61Mzaxozfj1r3+Npk2b4oUXXsC9996btFqvq6vDddddh88++wxFRUX4xS9+4bVahBBCCCGeoUKVEEJIxjFt2jT87Gc/w89+9jMceeSR6Nq1K9q2bYvrrrsO33//Pc4++2y8/fbbhqd3+8Udd9yBiy66COvWrcPQoUPRvn179O/fH71790ZRURH69++PRx55pNFWaTt69+6Np59+Grm5uZg8eTJat26NPn36oH///ujUqVNSmatuffbKnXfeidGjR2Pr1q048cQT0aFDBxx11FHo2LEjDjjgAEyZMiUl/KhRo/Dggw+itrYW48aNQ+vWrdGvXz8ceeSRKC0tRXl5OW6++WZs3bpVSvmizAEHHIAXX3wRxcXFuP/++9GuXTscfvjhOProo1FeXo7i4mJcdtllKa4hSktLMX78eADAmDFj0LlzZ/Tr1w/t27fH888/j/vvvz+w8icSCXzyySe44oorUFxcjG7duqF///7o3r07SkpK8Pvf/x6KouD666/H6aefnhL33HPPBbBfwd6jRw8MHjwYQ4YMwSuvvCKcf9zbT4QRI0bghBNOwI4dOzBgwAAcdNBBOOyww3DQQQehuLgYZ599ttT8Ro8ejTvvvBP19fW47rrr0LZtWxx55JHo3r07WrZsiXHjxqUondu2bYvjjjsOu3btQnl5OY4++mgMGTIE5513nm1evXv3xgMPPIBEIoHrr78eZWVlOOqoo1BSUoIHH3wQubm5ePLJJ1FaWiq1joQQQgghbqBClRBCSMbxxRdf4N1338W7776L1atXY9++fTjhhBNw0003YdWqVfjHP/6B1q1bB1qmpk2b4u9//ztefvllnHbaaQCAFStWYMuWLejevTuuueYaLFq0yJX/wNNPPx2rVq3Cddddhy5dumDNmjVYtWoVmjVrhtNPPx1PPPEEbrzxRin1yM3Nxbx58/Dkk0/i+OOPR01NDT7++GNkZWVh1KhRhlv7f/nLX+Kjjz7C5ZdfjrZt22LlypX44osvUFxcjPPPPx///Oc/cckll0gpX9QZOHAgVq1ahZtuugmHHHII1q1bh08++QRZWVkYMWIEHn74Yfzxj39MiXPXXXdhxowZOOigg1BZWYmvv/4aJ5xwAt5++22MGDEisLJfffXVeOONN/Cb3/wGxxxzDOrr6/HRRx9h06ZN6Ny5My655BK8/fbbuPvuuxvFPfbYY/HUU0/hqKOOwqZNm/DWW29h8eLFqKysdFSGOLefCIlEAvPmzcPEiRNRVlaGdevWobq6GpMnT8aCBQuED+Nywo033oglS5bgnHPOQbNmzfDxxx+jqqoKRx55JO6++24cccQRKeGfeuopjB07FoWFhfjvf/+LxYsXC/tV/sUvfoG3334bp512GhoaGvDRRx+hWbNmuOiii/Dhhx/ipJNOkl4/QgghhBA3JBQ7Z1eEEEIIIYQQQgghhBBCANBClRBCCCGEEEIIIYQQQoShQpWEyuzZs5FIJJBIJBodwgLsP4jlwAMPRCKRwJAhQ1zl8fDDD2P27NmNri9atAiJRALPPfecq3SdMHbsWHTp0sU23DvvvIPLL78cffv2RW5uLhKJhDS/hnqmTp2KRCKBrKwsw0NuqqurUVhYiEQigbFjx7rKY9q0aXj++ecbXVef+wcffOAqXScMGTLE9t2pqqrCHXfcgSFDhqC0tBQtWrTAYYcdhunTp6Ompsb3MhJC/INyJhXKGfmIyBkAuOmmm9CnTx+0bt0aeXl56NatG6644gp8/fXXvpeREOIvlDU/UV9fj/vuuw8jRozAAQccgGbNmuHggw/GjTfe2OiwQBlQ1qRCWUNIcFChSiJBQUEBZs6c2ej64sWL8eWXX6KgoMB12maDjyjy+uuv47XXXkOnTp1wzDHHBJJnixYtMGvWrEbX//nPf2Lv3r2e/LGZDT6ixoYNGzBjxgwcccQRePTRR/Hiiy/irLPOwtSpU3HyySeDnlEIiT+UM/uhnAmPH3/8Eeeffz6eeOIJvPLKK7j++uvx73//G/3798cPP/wQdvEIIRKgrAH27NmDqVOnonPnzpgxYwbmz5+PcePG4dFHH8XAgQOxZ88eX/KlrNkPZQ0hwUGFKokE5557LubOnYuqqqqU6zNnzsSAAQPQqVOnkEoWLLfccgvWr1+PefPmBXbwwrnnnosnnngCDQ0NKddnzpyJ008/HTk5OYGUI0y6du2K9evX47777sOpp56K4447DlOmTMHvf/97vP7663j33XfDLiIhxCOUM/uhnAmPP/3pT5g0aRJOOeUUDBkyBFdffTVmzpyJb7/9Fi+88ELYxSOESICyBsjPz8e6devwl7/8BWeddRaGDBmCiRMn4tFHH8WqVaswd+5cX/KlrNkPZQ0hwUGFKokE559/PgDg6aefTl7bsWMH5s6di0svvdQwTl1dHW6//XYcdNBByM3NRdu2bfHzn/8c3333XTJMly5dsHLlSixevDi5DUe/TWXv3r246aabUFZWhsLCQpxwwglYs2ZNo/wef/xx9OrVC3l5eWjdujVOP/10fP75543CzZ49Gz169EBubi4OPvhgwxOtzcjKCv6TvPTSS7Fx40YsXLgwee1///sf3nnnHdO2r6qqwvXXX4+uXbsiJycHHTp0wPjx41FdXZ0Mk0gkUF1djSeeeCLZ9vptKjt37sQvfvELFBcXo02bNjjjjDOwefPmlDANDQ246667ks+5Xbt2uOSSS/DNN9+khFMUBXfddRc6d+6MvLw8HHHEEfjPf/4j1AbNmzdH8+bNG10/6qijAAAbN24USocQEl0oZ/ZDOROOnDGjbdu2AICmTZt6SocQEg0oa4AmTZqgTZs2ja77Pa6mrDGHsoYQn1AICZFZs2YpAJTly5crF198sXLUUUcl7/35z39WmjdvrlRVVSmHHnqoMnjw4OS9+vp6ZcSIEUrz5s2VW2+9VVm4cKHy2GOPKR06dFAOOeQQZffu3YqiKMqHH36odOvWTenTp4+ydOlSZenSpcqHH36oKIqivPnmmwoApUuXLsqFF16ovPzyy8rTTz+tdOrUSamoqFD27duXzG/atGkKAOX8889XXn75ZeVvf/ub0q1bN6WoqEj53//+16g+o0ePVl566SVlzpw5yoEHHqh07NhR6dy5s6O2ufvuuxUAyrp165w3rABTpkxRACjfffedcuyxxyrnnHNO8t4NN9ygdOnSRWloaFCaN2+ujBkzJnmvurpa6d27t1JcXKzcd999ymuvvab88Y9/VIqKipTjjjtOaWhoUBRFUZYuXark5+cro0aNSrb9ypUrFUX5qZ26deum/OpXv1JeffVV5bHHHlNatWqlDB06NKWcV1xxhQJAueaaa5RXXnlFeeSRR5S2bdsqHTt2VL777rtG9bnsssuU//znP8qjjz6qdOjQQSktLU15d9y00ccff+wqPiEkfChnzKGc2U/Qcmbv3r3K7t27lQ8//FAZOHCg0r17d2Xnzp0uWpgQEhUoa8Tb6IUXXnAV3wzKGmMoawjxHypUSahoBx/qYOCzzz5TFEVRjjzySGXs2LGKoiiNBh9PP/20AkCZO3duSnrLly9XACgPP/xw8po+roqa36hRo1Ku/+Mf/1AAKEuXLlUURVG2b9+eFKJaNmzYoOTm5ioXXHCBoij7B0RlZWXKEUcckRTAiqIo69evV7KzsyM90Z01a5aSm5ur/PDDD8q+ffuU9u3bK1OnTlUURWk0+LjzzjuVrKwsZfny5SnpPffccwoAZf78+clr+rgq6nO/+uqrU67fddddCgBly5YtiqIoyueff24Y7r333lMAKL/97W8VRdn/jPLy8pTTTz89Jdy7776rAHClUP3444+V/Pz8RmkSQuIF5Yw5lDPBy5ktW7YoAJJ//fv3VzZt2iQUlxASXShrrPnmm2+UkpISpV+/fkp9fb3j+FZQ1jSGsoaQYOCWfxIZBg8ejPLycjz++OP49NNPsXz5ctPtGf/+97/RsmVLnHLKKdi3b1/yr3fv3igtLTU8XdOMU089NeX34YcfDgDJkxCXLl2KPXv2NDoVsmPHjjjuuOPw+uuvAwDWrFmDzZs344ILLkAikUiG69y5cyAHfzQ0NKS0RX19vXDcs88+Gzk5OXjyyScxf/58VFZWmp6C+e9//xs9e/ZE7969U/I78cQTTU82NcOu7d98800AaFSWo446CgcffHCy7ZcuXYqamhpceOGFKeGOOeYYdO7cWbg8KuvXr8fJJ5+Mjh074rHHHnMcnxASTShnvEE5413OFBcXY/ny5XjnnXfw17/+Fdu2bcPQoUOxZcsW4TQIIdGGsiaVbdu2YdSoUVAUBc8++6yt6xnKGsoaQuICFaokMiQSCfz85z/HnDlz8Mgjj6B79+449thjDcN+++23+PHHH5GTk4Ps7OyUv8rKSnz//ffC+ep9/OTm5gJA8gRK9TTE9u3bN4pbVlaWvK/+W1pa2iic0TXZXHrppSntcPzxxwvHbd68Oc4991w8/vjjmDlzJk444QRTof3tt9/ik08+adTuBQUFUBQl9m3/9ddfY+jQoWjatClef/11tG7d2lF8Qkh0oZzxBuWM97Zv2rQp+vXrh4EDB+Lyyy/HG2+8ga+++gp/+MMfhNMghEQbypqf2L59O4YNG4ZNmzZh4cKF6Natm20cyhrKGkLiAr0Sk0gxduxY/O53v8MjjzyCO+64wzSc6vD7lVdeMbxfUFAgrUyqgDRa0du8eTOKi4tTwlVWVjYKZ3RNNlOnTsU111yT/O20DS699FI89thj+OSTT/Dkk0+ahisuLkZ+fj4ef/xx0/uy0Lb9AQcckHLPSdvrnfab8fXXX2PIkCFQFAWLFi1qlCchJP5QzriHcsa7nNFzwAEHoKysDP/73/9cxSeERBPKmv3K1BNOOAHr1q3D66+/nrTatIOyhrKGkLhAhSqJFB06dMBvfvMbrF69GmPGjDENd/LJJ+OZZ55BfX09+vfvb5lmbm5ucnXQDQMGDEB+fj7mzJmDs88+O3n9m2++wRtvvIGzzjoLANCjRw+0b98eTz/9NCZOnJjcIvP1119jyZIlKCsrc10GEbp06eJayAL763nppZdix44dOP30003DnXzyyZg2bRratGmDrl27Wqbpte2PO+44AMCcOXNw5JFHJq8vX74cn3/+OW666SYAwNFHH428vDw8+eSTOPPMM5PhlixZgq+//lqoXTZs2IAhQ4agvr4eixYtcuUqgBASfShn3EM5403OGLF27Vp88803jbaLEkLiTabLGlWZ+tVXX2HhwoXo06ePcDkpayhrCIkLVKiSyCGyFeG8887Dk08+iVGjRuG6667DUUcdhezsbHzzzTd48803MXr06KQAPeyww/DMM8/g2WefRbdu3ZCXl4fDDjtMuDwtW7bELbfcgt/+9re45JJLcP755+OHH37Arbfeiry8PEyZMgUAkJWVhd///ve4/PLLcfrpp2PcuHH48ccfMXXqVOEtGt999x0WL14MAPj0008BAP/5z3/Qtm1btG3bFoMHDxYutxtmzpxpG2b8+PGYO3cuBg0ahAkTJuDwww9HQ0MDNmzYgAULFuDXv/51ckB42GGHYdGiRXjppZfQvn17FBQUoEePHsLl6dGjB6644go8+OCDyMrKwsiRI7F+/Xrccsst6NixIyZMmAAAaNWqFa6//nrcfvvtuPzyy3H22Wdj48aNwm2/devWpF+hmTNnYuvWrdi6dWvy/gEHHEBrVULSCMoZyhmVoOTMJ598ggkTJuCss85Ct27dkJWVhU8//RT3338/2rRpg+uvv164zISQeJCpsmbPnj048cQTsWLFCsyYMQP79u3DsmXLkvfbtm2L8vJy4XK7gbKGsoaQQAj1SCyS8WhPxLTC6FTLvXv3Kvfcc4/Sq1cvJS8vT2nRooVy0EEHKVdeeaXyxRdfJMOtX79eGT58uFJQUKAASJ5MqZ6I+c9//jMl3XXr1ikAlFmzZqVcf+yxx5TDDz9cycnJUYqKipTRo0crK1eubFTWxx57TKmoqFBycnKU7t27K48//rgyZswYoRMx1TIZ/bk5qd4K7YmYVhidarlr1y7l5ptvVnr06JFsj8MOO0yZMGGCUllZmQz30UcfKQMHDlSaNWuWUgez567W/80330xeq6+vV6ZPn650795dyc7OVoqLi5WLLrpI2bhxY0rchoYG5c4771Q6duyo5OTkKIcffrjy0ksvKYMHD7ZtO6t2B6BMmTLFMj4hJLpQzqRCOROOnKmsrFQuuugipby8XGnWrJmSk5OjdOvWTbnqqquUDRs2WMYlhEQfyprG+Zr96ft7r1DW/ARlDSHBklAURZGtpCWEEEIIIYQQQgghhJB0JCvsAhBCCCGEEEIIIYQQQkhcoEKVEEIIIYQQQgghhBBCBAlVofrWW2/hlFNOQVlZGRKJBJ5//vmU+4qiYOrUqSgrK0N+fj6GDBmClStXpoS58sorUV5ejvz8fLRt2xajR4/G6tWrk/fXr1+Pyy67DF27dkV+fj7Ky8sxZcoU1NXVBVFFQgghIUI5QwghxG8oawghhJDMI1SFanV1NXr16oWHHnrI8P5dd92F++67Dw899BCWL1+O0tJSDBs2DDt37kyG6du3L2bNmoXPP/8cr776KhRFwfDhw1FfXw8AWL16NRoaGvCXv/wFK1euxP33349HHnkEv/3tbwOpIyGEkPCgnCGEEOI3lDWEEEJI5hGZQ6kSiQTmzZuH0047DcD+ldyysjKMHz8eN9xwAwCgtrYWJSUlmD59Oq688krDdD755BP06tULa9euRXl5uWGYu+++G3/+85/x1Vdf+VIXQggh0YNyhhBCiN9Q1hBCCCGZQWR9qK5btw6VlZUYPnx48lpubi4GDx6MJUuWGMaprq7GrFmz0LVrV3Ts2NE07R07dqB169bSy0wIISQ+UM4QQgjxG8oaQgghJD1pGnYBzKisrAQAlJSUpFwvKSnB119/nXLt4YcfxqRJk1BdXY2DDjoICxcuRE5OjmG6X375JR588EHce++9lvnX1taitrY2+buhoQHbtm1DmzZtkEgk3FSJEEKIBkVRsHPnTpSVlSErK/j1PcoZQghJb8KWM0C4soZyhhBC/CUKcoaER2QVqip6Ya8oSqNrF154IYYNG4YtW7bgnnvuwTnnnIN3330XeXl5KeE2b96MESNG4Oyzz8bll19ume+dd96JW2+9VU4lCCGEmLJx40YccMABoeVPOUMIIelN2HIGCEfWUM4QQkgwREHOkOCJrEK1tLQUwP5V3fbt2yevb926tdEKb1FREYqKilBRUYGjjz4arVq1wrx583D++ecnw2zevBlDhw7FgAED8Oijj9rmP3nyZEycODH5e8eOHejUqRM+/98XKCgo8Fo9EhNyGupQl2VsGaDeB4C6rJzk/7VYxRXJwy7/dEG0nbUYtbnZc7C7J4o2DX151Tpo83D77MzysAprVFYZGLWx9p5RPvrvwqwsO3fuxMHdK0LrU6MqZ75cvTI2csbuu1Kfvf49MPt2teGN0tFj9H5pv0X9N2tXVqvvW18fs/hO+xqzfsOq3EblMErHqA3Mym9XLruwekT7bSfI6MdF0zV7X0Xkvde6O3lvneYj+qzs8tDHEy2nSDiR91T0e9u5cyfKDzo01D41TFmTDnKGkHTCrn83k+VW6ZjlA7jrp9MZP9ogCnKGhEdkFapdu3ZFaWkpFi5ciD59+gAA6urqsHjxYkyfPt0yrqIoKdtbNm3ahKFDhyZPzxQxxc7NzUVubm6j6wUFBSgsLHRYGxJXqFANBipUU8kUhapKWNsOKWe8Q4WqcR3SUaFqV3c9VKja52FWljzYjy+s4lOhmpoOEJ6cAcKVNekgZwhJJ6hQDRc/24BuVDKTUBWqu3btwtq1a5O/161bh48++gitW7dGp06dMH78eEybNg0VFRWoqKjAtGnT0KxZM1xwwQUAgK+++grPPvsshg8fjrZt22LTpk2YPn068vPzMWrUKAD7V3GHDBmCTp064Z577sF3332XzE9dMSaEEGKPncIgilDOEELiSFQnvlaLG7IQUZCqYaLSRpQ1hBBCSOYRqkL1gw8+wNChQ5O/1S0pY8aMwezZszFp0iTs2bMHV199NbZv347+/ftjwYIFSXPqvLw8vP3225gxYwa2b9+OkpISDBo0CEuWLEG7du0AAAsWLMDatWuxdu3aRj4tFEUJqKaEEELCgHKGEHlERXmVLri1arZKzyj9KOGmPHHYqUNZQwghhGQeCYUSWIiqqioUFRXhmy2V3CKTQXDLfzBwy38qcdjyL1pGq2dbVVWFA9qXYseOHexX8ZOc2bppQ2zag1v+jeuQrlv+nfQ33PJvnYf+2zB695y+T6Lvjt33KJKHm7huceumoC4rBzU/fo92HTpRzvw/cZQzhKQT3PIfLn60QVVVFeVMBmPv5I0QQgghhBAihShMar0sxoVddkIIIYSQKECFKiGEpBFRs2iOWnkIIcHAbz8VIyWk6OFMfpXDjWI0CspU0TJEoayEEELiQV1WTvKPNOatt97CKaecgrKyMiQSCTz//PMp9xVFwdSpU1FWVob8/HwMGTIEK1eutE137ty5OOSQQ5Cbm4tDDjkE8+bN86kG/kCFKiGEEEIIiQyZOJkx29ZOpSAhhBBCwqa6uhq9evXCQw89ZHj/rrvuwn333YeHHnoIy5cvR2lpKYYNG4adO3eaprl06VKce+65uPjii/Hxxx/j4osvxjnnnIP33nvPr2pIhwpVQgghhBBCQsaJj1szRP0P+0WYynBt3pmolCeEEEL8YuTIkbj99ttxxhlnNLqnKApmzJiBm266CWeccQZ69uyJJ554Art378ZTTz1lmuaMGTMwbNgwTJ48GQcddBAmT56M448/HjNmzPCxJnKhQpUQQgghhESCMBRhYVuBusmfCkNjuF2TEEIICZZ169ahsrISw4cPT17Lzc3F4MGDsWTJEtN4S5cuTYkDACeeeKJlnKjRNOwCEEIIkYefigFOUgkhxBlOrE5zGuqEFYJO+nqnZfCDMA7ioswihBCixU4Ohb3A6pSamhrU1bkrs6IoSCQSKddyc3ORm5vrOK3KykoAQElJScr1kpISfP3115bxjOKo6cUBKlQJIYQQQgiJAKpSNcj83MaLkjWxvixOlNOEEEJIHJWpbfJbYDfqXcVv0aIFdu3alXJtypQpmDp1qusy6RW0RkpbGXGiBBWqhJDIENYEjRBCiDnp1i+HYS1ph1F5jMppVfag65Tu+RFCCCFRpa6uDrtRjwvRATkOPXnWoQFP7tqEjRs3orCwMHndjXUqAJSWlgLYb3Havn375PWtW7c2skDVx9Nbo9rFiRr0oUoIIYQQQiyhMiscglBmy7Tk5HtCCCGEBEcOslz9AUBhYWHKn1uFateuXVFaWoqFCxcmr9XV1WHx4sU45phjTOMNGDAgJQ4ALFiwwDJO1KCFKiGEEEIIsSWKlp2ZgF27u3kufsYxC+f2/XEah+8oIYQQIpddu3Zh7dq1yd/r1q3DRx99hNatW6NTp04YP348pk2bhoqKClRUVGDatGlo1qwZLrjggmScSy65BB06dMCdd94JALjuuuswaNAgTJ8+HaNHj8YLL7yA1157De+8807g9XMLFaqEEEKkoHXZQPcNhGQ2VGp5J8x+1Ej5KfpMvT57EcWrGoZyhhBC0gcu3EaXDz74AEOHDk3+njhxIgBgzJgxmD17NiZNmoQ9e/bg6quvxvbt29G/f38sWLAABQUFyTgbNmxAVtZPm+SPOeYYPPPMM7j55ptxyy23oLy8HM8++yz69+8fXMU8QoUqIYQQX+BklxCS6ciYGGrT8GOiGde+2uwgKkIIIfEkaspUKnh/YsiQIVAUxfR+IpHA1KlTLQ+1WrRoUaNrZ511Fs466ywJJQwH+lAlhJA0JAzhr53I8nRlQtILfs/WOOlzZfbP6nNR+1yr5xT2M/RTLnHCSwghhJCgoYUqIYQQQgghEUGGpaVT602ZPk8JIYSQdCAOMrBVdhPkJpzZSdYqCWCvTwXKMGihSgghhBBCbInDxCJd8NLWZopTNU0RZW2UnrWd5W2UykoIIYSQzIEKVUIIIYQQklGEvf097jhtP79cIrg9OIsQQgghxCtUqBJCIkMcJrhxKKMfZGq9CSHpAf06N8auPXjIEyGEkEyAYwTiFipUCSGEmGI2uOCggxASV8I6QMoNsvOPct9tVDb9NZFJb5TrSAghJDycyAfRsJQ5mQ0VqoQQQgghxJKglJBBKTDDVpSqyJqI5TTUJf+0v9X/m8XxSpATST/dDBBCCCFaRGUIZU1m0zTsAhBCCIku3PJJCIkTRifTe+nD1LhBTZiMyhpUP6xvO5EdCn63i5u6c3JLCCFyMJKphJCfoEKVEEIcwEEFIYQQP3DrYiVOlqZWk3Mn1kCc5BNCiL+ko0FFOsqNNjlZyEs0cRSnRgGw15/yZBrc8k8IIYQQQjKOdJws6nE7eYxq2zitTzpOngkhhMiFsoK4hQpVQggJGT+EeFQnw4QQYoefExv2jdaItI+b58N2J4QQQki6QYUqIYQQS7STZ6uJtNE9rvgSQqKEX30SFYb+YXe4FiGEEOdQbqVCGUPcQIUqIYQQR4goTrUnTBNC4k06f8uiE8p0m3iyzyaEEKIn3WQdIX5DhSohhKQJdVk5HAgRQkjAyOh3ZfbdQShG3fgy1dfRS52p/CWEEEJI2FChSgghIRCnyaCbSTCVu4SQsHDa9/jlN9QsL+2faP6yEKmHWp44ySlCCCGEkKBpGnYBCCEkzhhZ3aQTVspUUcUqIYREibqsHEfKwqAVi1GSK3FUqjp9voQQku4YyRSefZAetMppgvxEE0dx9igAqv0pT6ZBC1VCCPGI28GHkQ87Qggh3tFagBr1tVFRWGpx68c06LqE1XZO8o3i8yWEEEJIekGFKiGEhEwmWNPwwBNCSFBo+xo7xVpU+yXRBTfZ5Q+yPfzOi0pVQgjJvL4w0+pLwoUKVUJIZIjqxNYtcZ7oEkJIFHGqIFV/x3lRR1sH9V/R+ohu89Tfd9tWXieydvH98I9LCCGEOIGyhahQoUoIITEgTEWAm9OcReLHVblBCMkcZPZTMiZgZuWJ0+QuTmUlhJA4w/7WP9i2BKBClRBCiEeoGCWEpAOyJkdm6bCvtIcLcIQQQsKEOyGIE6hQJYSQGBAnYa0va5zKTgjxjvZAKJnESammtoFfbRFVrA78CsuNACGEZCpxkptxhW2c2TQNuwCEEELk4YdQ109mjSbMTie8OQ11qPFcMkJIuhHGIX1hHMQkW0nICR0hhBCSefKwTU5TNMtq4ijO7oaET6XJPGihSgghLglaYMfBSifTBjGEEBIVVBnht6yIej+fDgeREUKIKE4PayRyYLsSgApVQgiJBFFXloqcCk0IITJJZ8WgH3kb7R4QzSeqMkhbLidtRplECMkEotp3xx0qqVPp0qULEolEo79f/vKXhuEXLVpkGH716tUBl9x/uOWfEEJiTBjbY71g5V+PEEIA7/2a2sdEvW+Utf3f73pqn4fZ/4MsDyGEkMaIyM64zRvCgHOVxixfvhz19fXJ35999hmGDRuGs88+2zLemjVrUFhYmPzdtm1b38oYFlSoEkKIJDJxgOLE+ikT24cQEg5xsqr3Mnlz2rc6VTZblctN/6/WVYZMiIvinBBC/IBKP/9QZRXly370itA//OEPKC8vx+DBgy3jtWvXDi1btvSxZOHDLf+EEBIDoiDQRcsQhbISQsJBxvdvlUYU+hdVIahVDIZVLjf5ht2G9G1KCCEkDlBp3Zi6ujrMmTMHl156KRIJ68Ot+vTpg/bt2+P444/Hm2++GVAJg4UKVUIIEURkG006obUo0l9TMfJvl27tQAhxjhuFWZB9hx95RUFJ6LdlbhTqqIcyhxCSzrCPI35RVVWV8ldbW2sb5/nnn8ePP/6IsWPHmoZp3749Hn30UcydOxf/+te/0KNHDxx//PF46623JJY+GnDLPyGExBgrZWeQcFsMIUSFfYEcgmzHIP2wEkII8Y6RuxgqXzOP3JZ5yGvSxFGc+vp64FugY8eOKdenTJmCqVOnWsadOXMmRo4cibKyMtMwPXr0QI8ePZK/BwwYgI0bN+Kee+7BoEGDHJU16lChSgghPmPnHy+o0579goM3QkhcSUdFX5TrY9bebn3Buo1PCCEk83AqK9JdrmzcuDHl0Kjc3FzL8F9//TVee+01/Otf/3Kc19FHH405c+Y4jhd1qFAlhEQGKubkEuVTKlXfg4QQIoOoKNS0ZXByaFIUyu43Mp6RUfwoyzpCCPETkf6P/aM7MkEuFxYWpihU7Zg1axbatWuHk046yXFeK1asQPv27R3HizpUqBJCiEuiMoEnhJB0QMRPtaw+10wx5wazclml57UuUZU/bsrlZrJvdAJzVNuEEEKCQPbiUrouVlFWuKOhoQGzZs3CmDFj0LRpqhpx8uTJ2LRpE/72t78BAGbMmIEuXbrg0EMPTR5iNXfuXMydOzeMovtKqIdSvfXWWzjllFNQVlaGRCKB559/PuW+oiiYOnUqysrKkJ+fjyFDhmDlypUpYa688kqUl5cjPz8fbdu2xejRo7F69eqUMKeeeio6deqEvLw8tG/fHhdffDE2b97sd/UIISQjidIghXKGEP/we6Llti+JUh+UDoi0p9GuA1nvh1n+UTookrKGEBIWdot3ItcyDbaBc1577TVs2LABl156aaN7W7ZswYYNG5K/6+rqcP311+Pwww/Hsccei3feeQcvv/wyzjjjjCCLHAihKlSrq6vRq1cvPPTQQ4b377rrLtx333146KGHsHz5cpSWlmLYsGHYuXNnMkzfvn0xa9YsfP7553j11VehKAqGDx++39Hu/zN06FD84x//wJo1azB37lx8+eWXOOuss3yvHyGEkHChnCEkOPw8YV5k8iPbMifKRLV8fpXL7bMNatJMWUMIIfKh4jM6DB8+HIqioHv37o3uzZ49G4sWLUr+njRpEtauXYs9e/Zg27ZtePvttzFq1KgASxscCUVRlLALAQCJRALz5s3DaaedBmD/Sm5ZWRnGjx+PG264AQBQW1uLkpISTJ8+HVdeeaVhOp988gl69eqFtWvXory83DDMiy++iNNOOw21tbXIzs4WKl9VVRWKiorwzZZKR34mSLwRPUzI6pAFL3mk61YLPW4ObTJqc6stHLK3d4jmr17T10//7uj/Ve9pwxu1kV8WOm7ebaNyW92vqqrCAe1LsWPHjkD61bjIma2bNsRGzth9V1ofkvr32SgdM5+TTvpIq+9JdAu21fdqVD59HZwermPld9OsX9GXw2z7s1G9RC0OReM5SdcLdn287DKIvo9u8ozLlkPRdhWRf27ks1W/YZdOXVYOan78Hu06dApMzgDRljVxlDOEpBN24xK7MYFZOH14O+Igf2TidiwkQlVVVeByRs23qKgIz/fog+ZNmjiKW11fj9PWrAi8zOlIqBaqVqxbtw6VlZUYPnx48lpubi4GDx6MJUuWGMaprq7GrFmz0LVrV3Ts2NEwzLZt2/Dkk0/imGOOEZ7kEkKCIZOEe7ptwTEapKh/ZuHDft6UM4SkDzL6E7/7YCfKQa/pywwrQtj9uZ4oyVPKGkJIlIhaf60liL47CnMQmTRrk4dmxfnO/trkhV3stCGyCtXKykoAQElJScr1kpKS5D2Vhx9+GC1atECLFi3wyiuvYOHChcjJSf0Yb7jhBjRv3hxt2rTBhg0b8MILL1jmX1tbi6qqqpQ/QgiRidmgwU9fdDKIUlm8QDlDiDjpNPnIBIJ2kWCE13fGa/mi8s6GKWsoZwjJHNJlfJ4u9SCZQWQVqiqJRCLlt6Ioja5deOGFWLFiBRYvXoyKigqcc845qKmpSQnzm9/8BitWrMCCBQvQpEkTXHLJJbDydnDnnXeiqKgo+We2OkwIIXZkysAgqG2/sqGcISQaGC0mRRG3W/yDwi4v2f5I4/DMokAYsoZyhpD0x6nbtKgSJ1kSp7ISf4msQrW0tBQAGq3cbt26tdEKb1FRESoqKjBo0CA899xzWL16NebNm5cSpri4GN27d8ewYcPwzDPPYP78+Vi2bJlp/pMnT8aOHTuSfxs3bpRUM0JIXMkU4en0tNC4QjlDiL9E/SChqOUtA7/KH5a1aJyUAWaEKWsoZwiJF077vLjLLELiTmQVql27dkVpaSkWLlyYvFZXV4fFixfjmGOOsYyrKApqa2st7wOwDJObm4vCwsKUP0II8YOoToDTHcoZQvzB62F4ccDOT3S6IkOuOE3DTTtH6bmEKWsoZwiJP1HqzwghqTQNM/Ndu3Zh7dq1yd/r1q3DRx99hNatW6NTp04YP348pk2bhoqKClRUVGDatGlo1qwZLrjgAgDAV199hWeffRbDhw9H27ZtsWnTJkyfPh35+fkYNWoUAOD999/H+++/j5/97Gdo1aoVvvrqK/zud79DeXk5BgwYEEq9CSFENnE7MTooKGcIiQYy+6g49HdOyxgXlylG5Yt6mYOAsoYQQgjJPEJVqH7wwQcYOnRo8vfEiRMBAGPGjMHs2bMxadIk7NmzB1dffTW2b9+O/v37Y8GCBSgoKAAA5OXl4e2338aMGTOwfft2lJSUYNCgQViyZAnatWsHAMjPz8e//vUvTJkyBdXV1Wjfvj1GjBiBZ555Brm5ucFXmhBCYorRCdUiCtKchrrQrGUpZwgJjzgp2qJg0e+1vUT7Wn04P5S5WoWyml8QVqZhKaYpawghhJDMI6FYnZhBklRVVaGoqAjfbKnkdpkMwm5yolUqGQ3evSqbwlREBYl2smVUX7O21V+3mrDJsGjSpiGav98KR7vyeElTn66oQtXqeWknu1VVVWjXoRN27NjBfhU/yZmtmzbEpj3svivt8zZ6f/TpmClDnPSR+v7Erp82qotRmvr6mMV3Y5mo/+b0eZq1h9m3alYeJ8omp21nl65Iuxi9B26foVPM3s+gLGuDtrq1+qaswom+O/qwQdTP6BlSzqQSRzlDSDrhVI5ZjYuMxk1mYyL9taji16KYnzIoLDmj9udvjRqKFtnO7CR37d2HQfPfpGyUQGR9qBJCMo+oK49lKSzTmUw50IqQTIPfr3OctJnoRC/o56C1MjXCqjz6e3VZOZ7K7zU+IYSQzCTKSmQSb6hQJYQQCaTrJM+vAQgnxoQQM9L1RHgZuyTCwMkOHPbrhBASLaIuGwmJM1SoEkKIT8R1YmlXbg7MCCF60rVfYL3MiZqMs7OmJYQQEh6ibtCi2odHTeaRaECFKiGEpCGiQj+oQUtUB0eEEDH4DTcmKpMrmeXwu05+v0d8TwkhxBtRkW2ExAEqVAkhGQEnWYQQIo62z3R6yJZfhN2Pc5LZGNFnEvazI4SQdCSd+9aw3YMZ5c1xANFDhSohhHggbGGvoh9QhTHASudBXRSIwntGoo9ffZKMNJ2m4ec77zZtPw6aCiu9oNP3C+0ziYpMJoQQ4g724yRONA27AIQQopLTUOdJgEZhMliXleNLOczaxmt++jRFnoGMOkbhWRFCgsevPtINMsoSRn1kldvvuDLbRUT+cQJOCCHeUecCYSwKRqUftypHlMYxAJDfJh/5OdmO4tTX7fWpNJkHLVQJIUQQdcVUtrD3mp6s8sgeHJiVK0qDkDjBdiNRJiqTIBGsLBoz7Tszqq+RnFN/ixxaaNaGfrStyAIgIYREkaD7JycHPmWaLCTELVSoEkKIBPRWMuk+iXNbPw7QCCHkJ4KWFUHJpzCsdq1+E0JIpsL+UBxRGZkJcz0iBhWqhBDiArcHtgRJEOXykkdU240Q4p6wv+uoWyzaWcSKWIAGRRTayoqw3zVCCIkL7C/tcXMIFRWrhApVQghxSdgHhJht1TQLq4Z3suXHSXkIIelL1BdoiHvcLhAG8bwy3SUDIYQQ/6FSlLiFClVCCCGEEOIaVcllNSFxu5ATJfTlD6s+bsvhZsIYVesb0S2ZhBCS6cRd9hISZahQJYQQl/g9WXOydVWd9JoNmpxOikVPVHaSptOtraQxbDOSznjto7T33PRPIpNOrxNTNzsPjHDTF4goYuPUx8SprIQQQpwT1IG5hLiladgFIIQQlTgJOb0yU6bAF7H2EsFpfCOFKVe1CSFOCLPfsPJ/ZlUmK8Vi3PtAP+rhZ5vIfH/i/uwIISRMwp4H+JW3m3pFeY6a27oQebnOyre3lvJRFrRQJYQQCYRtrWqHDKsnJwqJKA88CCHhIqt/iOJ2dBnlkVWvqLWNFU7LSmUpIYSIE3V5EIS/bKOdfU7jEaKHClVCCBEkihM4WX4JrVwF+JkvIUQumfhdcrLTGLs28XO7v5vdEfp/3VrWZuL7TwghYSJbBgfdj3OuY8/UqVORSCRS/kpLSy3jLF68GH379kVeXh66deuGRx55JKDSBgu3/BNCSBriZJXX7r7MLT9hbx8ihMQfff8mezLnt4LW7z7QjTJVhLD7bln+ZwkhJNNQZaWTfjKoPtVvy1TRvN2WIVNkz6GHHorXXnst+btJkyamYdetW4dRo0Zh3LhxmDNnDt59911cffXVaNu2Lc4888wgihsYVKgSQjKCMBV5Xib8figL3OTlpP2oNCUkXILsN5wi2jeY+ZKOar3iQtSUqW7dzBBCCElFa9kfF1kZl3ICqTJJ29Y1YRUoYJo2bWprlaryyCOPoFOnTpgxYwYA4OCDD8YHH3yAe+65J+0UqtzyTwghkon7JDDu5U9n+GyIGXF7N9xMoqzi2KXndtJm52ctau3uZfEuaGT6Bo/acyCEkKCJ+xb1MA1f1H+NyhDnNpXJF198gbKyMnTt2hXnnXcevvrqK9OwS5cuxfDhw1OunXjiifjggw+wd+9ev4saKFSoEkKIZGRaVInGtRL2bv3ZiaLP2+7wqjitRhMSF+L4XQVdZjf5hbn1z4uSWObEmpNJQgiJLn4qAUXkZhxkhJWfVO2/mUZVVVXKX21trWG4/v37429/+xteffVV/PWvf0VlZSWOOeYY/PDDD4bhKysrUVJSknKtpKQE+/btw/fffy+9HmHCLf+EkMigV7ZR+eYMEf9yXk+PlntoSaZskiEk83Dr+kMbT3tIkVvFpowtkGFOtJwezmS1wOWnOxZ92jLy0qbh/l2q8lQGQggJm6i5avEDr+OFoPKMIrlFLZCb59B4pmZ/3Tt27JhyfcqUKZg6dWqj8CNHjkz+/7DDDsOAAQNQXl6OJ554AhMnTjTMI5FIpPxWFMXwetyhQpUQQmJOED5L9emreZpdd5MmISS98dJXuV1sM1IwhnkAhhFe+3CR+H4sTopa0Do9BEWfLnc9EEIIMZJ1buVnFGR/FNi4cSMKCwuTv3Nzc4XiNW/eHIcddhi++OILw/ulpaWorKxMubZ161Y0bdoUbdq0cV/gCMIt/4QQ4gC7bZRROJ1SxckhUrLztoMDGULSExkKU7/jybCcDBNt/k7KEqQ7AjdhZcksVU5TzhBCiHv8lnUi6as762TtrnMrG9JVnhQWFqb8iSpUa2tr8fnnn6N9+/aG9wcMGICFCxemXFuwYAH69euH7Oxsz+WOElSoEkIiQRQFVdCTZjMfSEG2jVNLIr/zIISkB06sDp2i3xZulnYQ/ZtbROWNmTWOiJLRDr/rLLoAGKbfWkIIIcFi1ocbyQytKyCrcEZ5UFa45/rrr8fixYuxbt06vPfeezjrrLNQVVWFMWPGAAAmT56MSy65JBn+qquuwtdff42JEyfi888/x+OPP46ZM2fi+uuvD6sKvkGFKiGECOC3clXUT5zRgMDKGb3bVVgOOgghQeHFt2nQB0oYTeZkp22mMA3bMtYLcS47IYREDRkyz8lCXhD5yILyRj7ffPMNzj//fPTo0QNnnHEGcnJysGzZMnTu3BkAsGXLFmzYsCEZvmvXrpg/fz4WLVqE3r174/e//z0eeOABnHnmmWFVwTfoQ5UQQiQTR59uQfhhJekH35loEbfvWKsMjXqf6aeFrT4fL24TZJRLfR5+1DFu7yghhGQqsmSz1a4R2bI/6mOJuPLMM89Y3p89e3aja4MHD8aHH37oU4miAy1UCSFEED9Xcp1YPTk5gMRLWUhm4NYfI0lvvL4LYWzbFj0kKYiyeMGonEGVyQ+L37DbkxBC4oqT7fCy0g4S2e7DZNWJ42EiCi1UCSFEMqowlyWMzRRedn70wjisJAqDM0JIPLFyZ+L0ECS/JqFh9nFxsOQ1w2nZ1fBGz5JyhhBCgiNKfa6Vm7NMJa91IfLzxQ6TUtm7p9an0mQetFAlhEQCPyeJIlZLdhZBsk4fdho3apPnTB+0EEK8IatPi0tfZOX71OtBGk79XfuxyGeHVfm8PMOoyUZCCCHxJQ5zMBJNqFAlhGQsbg750MeJy6Rej4j1lt3WTw40CIkWce2P/ECkf4/CafJWZbTqe+P4rONYZkIISScydeyeqfUm/kOFKiGEeCSuk0SRcnNrDSEkCji1xswkotouTmQMJ7uEEBI9wnZzY7Vb0M0uDStZY3T+BGUTsYMKVUJIZImyEBMR4kEPQtLBcpYQkv5EuW/3i6jU2c3ODCPsJrp2ZZBBVNqUEEKCJpPG+UEuqIZx/gSJN1SoEkIyDk7CrOEAIbPg804PZD/HdHwvvNQpyPaIuzWuSNnT5YRqQgiJClGZ38hauHNLEOdeEKJChSohJLI4nSw5PQXaK1ETxHY+T62IWl1IuPB9iB9hPTM3+XpVhAVVV699adS+IxkKSNE6RW0HByGExAG/lIFu5VEYMj5ovLZN1GQ9CZamYReAEELihN7fm0whmtNQJ3RAibryqx2wOD2kxGu5RS2QtGWO2wArU+HAkDhFr0T081u36yf9jm9FkJMro/413b5dygxCCAmHMBdp49T37y9vVahlyClsgZxmec7iZGf7VJrMgxaqhJBY4mYFN+ztJ1ZlljV48JJOuk3GCSHhILLdz01/E+U+KihrISO87E6Qmb8ep9asouH1ymRCCMlUglrACxK/8/OaPuUO0UKFKiEko/BLCJopTJ36wnNrZSqaNxWuxAg+2/QgqOfoZQugF+WfleIuXd5h/c4DK9zU24t/VqO8ZCtx/VDEE0JIOuJkEcqPdONAOtWFRBMqVAkh5P9xOyn3yyrI7QnKsvJ0Cgct8SdO26xI/JD5fpn1N6rCkO+yf4rmIN3LEEIIIX7C8QLxAhWqhJBII9OSJlMJYqDA9k4fOLAkQSLqlsXOIt+IqL7Lsg52CgKZfTvlBCGE+EcYMsNq4c5Lnx+0vHDjSi4KMpqEDxWqhJC0I2xfqemQByEkXrg9kV6GVX469El+uoOJO7LbJh3ahBBC4oLfB0WaXfeSbxhygrKJuIEKVUJIpPFj1TNu6AW8TF9ITtwKcKCRvrhVkGXSd0iMiWu/oD3UKEjfs07yEglvd9ih1+cj+/l6mXxnsh9AQgixQ9/nBdUHxnUc4Aa9n/NMqjsxpmnYBSCEED/JaaizPUgjqpMuo3JxQkkIiSJmfa0VbvsnfTw3eUcVuwmatq5xmMg5LaNIeLOFQE5uCSGZhFV/ly4y0Q/STU5kFbZGVvN8Z3Ga7vGpNJkHLVQJIWlBEAOHIA6fchInapZHhJDMJsw+JaithW4sWv2w8mT/TQgh8SOMA2e9EpdyGuHnol6c24XIgxaqhJDYI7IlMp1Wao0EuFfLHC9x06ltMxladxGnOH1nzCwrRdMJ+x31Q5GqdT1ACCGE+IF2LqTKUiuZGrSsjaoM5Lg4fVi/fj3efvttrF+/Hrt370bbtm3Rp08fDBgwAHl5ea7TpUKVEBJZoipciRgchBCSeThdwBIJ79TvaBB9j1E+Xrbj6ye7UUOGmwHKBEII8RcZ8iOd+2rRuqWbMU4m89RTT+GBBx7A+++/j3bt2qFDhw7Iz8/Htm3b8OWXXyIvLw8XXnghbrjhBnTu3Nlx+qFu+X/rrbdwyimnoKysDIlEAs8//3zKfUVRMHXqVJSVlSE/Px9DhgzBypUrU8JceeWVKC8vR35+Ptq2bYvRo0dj9erVhvnV1taid+/eSCQS+Oijj3yqFSEkykRtq6RZWWRMXmX4YJVBmAMSyhlncPBIZOHWlYkdoofsuYnvBTfbON0eBkeiB2UNIUQGQR2UGKXxnrYsUZinOfXlTaLLEUccgfvuuw8XXXQR1q9fj8rKSvz3v//FO++8g1WrVqGqqgovvPACGhoa0K9fP/zzn/90nEeoCtXq6mr06tULDz30kOH9u+66C/fddx8eeughLF++HKWlpRg2bBh27tyZDNO3b1/MmjULn3/+OV599VUoioLhw4ejvr6+UXqTJk1CWVmZb/UhhBAZBD3ISedBAeWMM/zwNUWCw+/nYXQYlAz8Ur6axYujD7sgCWpCLxO7wyf9hrKGEBJ1oirvolouEn9+//vf44MPPsA111yDTp06Nbqfm5uLIUOG4JFHHsHnn3+OLl26OM4j1C3/I0eOxMiRIw3vKYqCGTNm4KabbsIZZ5wBAHjiiSdQUlKCp556CldeeSUA4IorrkjG6dKlC26//Xb06tUL69evR3l5efLef/7zHyxYsABz587Ff/7zHx9rRQhxg5mljsytoF5XHN1sJdVamupXYNVJq5c8tfetwlq1k59bZMOelFPOkExB1Krd67ceth9TO2SUzWsdo95GfqGXR7LTjjKUNYQQGbiRHUaLnVa71KK8nV2G/AW87/DLRBmejpx00knCYYuLi1FcXOw4j1AtVK1Yt24dKisrMXz48OS13NxcDB48GEuWLDGMU11djVmzZqFr167o2LFj8vq3336LcePG4e9//zuaNWvme9kJIcEgYzAQ1QGFEbL86/kxSIjjwINyJpU4PkPiH2H3jWHn7xS9VafZ/7XfmT5MHGSayCKnWRj9dbs6x+0dMIOyhhASNH4eNhWVvtlNOUTnUlGpowhZBUXIKmjp8K8o7GIHztChQzFz5kzs2LFDarqRVahWVlYCAEpKSlKul5SUJO+pPPzww2jRogVatGiBV155BQsXLkROzv6PQFEUjB07FldddRX69esnnH9tbS2qqqpS/ggh0cfphM1tujLiy1JguSmbH3mLphmVQUqc5IyZckYWUXkmJH0w6ntl+UYLS/nvZoeC177fSb+a7t+xnz7H/SRMWcP5DCHRRcbcwm0aURuzmy022iG6gCd6j6Qvhx12GG6++WaUlpbizDPPxPPPP4+6Ou/jhsgqVFUSiUTKb0VRGl278MILsWLFCixevBgVFRU455xzUFNTAwB48MEHUVVVhcmTJzvK984770RRUVHyT7s6TAgJDr3AdzJ4iKrADGrS50R5YaSIFg3rxs1AlIiDnKHPRxIGfk/UnOQf9HtvVvcofX+qPPS7rw3Doiku8sMJYcgazmcIIW7RWnMGJW9k49USNW719Ys777wTRx55JAoKCtCuXTucdtppWLNmjWWcRYsWIZFINPozO2zRbx544AFs2rQJL7zwAgoKCjBmzBiUlpbiiiuuwOLFi12nG1mFamlpKQA0WrndunVroxXeoqIiVFRUYNCgQXjuueewevVqzJs3DwDwxhtvYNmyZcjNzUXTpk1x4IEHAgD69euHMWPGmOY/efJk7NixI/m3ceNGmdUjhASMDH88+vTs0gz7kAy3iGyHcTrAiGK9KWcIEcePSUUU+wUtQZ207PSwr0ye4BktskadMGUN5Qwh6Ydov6f1aR2HvtJI9gUlh4k1ixcvxi9/+UssW7YMCxcuxL59+zB8+HBUV1fbxl2zZg22bNmS/KuoqAigxMZkZWVh+PDhmD17Nr799lv85S9/wfvvv4/jjjvOdZqhHkplRdeuXVFaWoqFCxeiT58+AIC6ujosXrwY06dPt4yrKApqa2sB7NdE33777cl7mzdvxoknnohnn30W/fv3N00jNzcXubm5EmpCCHGCLEfpstKxSyOoA1CcWJBaYZSPkzr4vfU8SChnSLohW0Hp1wFDbssRBmEdTqGXYfpyiDwTs7JbKXBlPWsjGexGLof97skgTFlDOUNItJEtY5wsOsncfWAla/yWoTLbMB1kjh+88sorKb9nzZqFdu3a4b///S8GDRpkGbddu3Zo2bKlj6VzTmVlJZ555hnMmTMHn3zyCY488kjXaYWqUN21axfWrl2b/L1u3Tp89NFHaN26NTp16oTx48dj2rRpqKioQEVFBaZNm4ZmzZrhggsuAAB89dVXePbZZzF8+HC0bdsWmzZtwvTp05Gfn49Ro0YBADp16pSSZ4sWLQAA5eXlOOCAAwKqKSEkrshQzEb5NM10h3KGEHOsJiBeJydhW58GrQiVJSvc3NNjpYiNA3GUl5Q1hBC3WC1+RbX/durnVHY9jAxN1N2Dsg7xJeaoBzu1bt3aNmyfPn1QU1ODQw45BDfffDOGDh3qd/EMqaqqwty5c/HUU09h0aJF6NatGy644AI888wzyR0fbghVofrBBx+kNOjEiRMBAGPGjMHs2bMxadIk7NmzB1dffTW2b9+O/v37Y8GCBSgoKAAA5OXl4e2338aMGTOwfft2lJSUYNCgQViyZAnatWsXSp0IIXLRC2ERiym3QtvqREy77e9qmLAm8KKTeSMrJ32ZZSgGojKIoZwRI6oDdhIdvFqruukf+V4Gg9+TXTdyPG5Q1hBC3CKz/42yElYm+rmKm/GF3e6/TDCI0R9UKLKrQVEUTJw4ET/72c/Qs2dP03Dt27fHo48+ir59+6K2thZ///vfcfzxx2PRokW2Vq1+UFJSglatWuGcc87BtGnTPFmlakkoiqJISSnNqaqqQlFREb7ZUonCwsKwi0MCwq4j1U4K3Pp9scojEzpywHh7il5ZqEdUoWqn7BQVxiLbVsy2ZDpNV0Sg6yekonU0i2tXF6v0jNKw21Ka01CHqqoqtOvQCTt27GC/ip/kzNZNG9KmPcwU/k6/eSd9pPZb0L7HdpMMfVh9mvr6mMV3Opmx6zeM0jPrN+z6PrcTLdE03PYpdnmKpC8zPzufpk7fU6O0RPtRUflnN5YQia+/ZyeXRMpllL7d9yRaD6vyqlDOpJKOcoaQuGIn09zOL5323XblE0HWln+jcaPIfMSp6xqz8ZLRfTvCkjNqf75t6QsobNHcWdxd1Wg9YHSj61OmTMHUqVMt4/7yl7/Eyy+/jHfeecfx7ohTTjkFiUQCL774oqN4MliwYAFOOOEEZGXJPUYqsj5UCSGZjSxFsqxVWpm+eWSvHLtVkMhMM1NWxAnJdLx+50H1FXGz+HGSvpnyVHQRViScUXlkLPIaWaqahTHb0qn9bXafMokQQuRiJXvMwjtBv7PBSbmcYLQzL1PZuHFjihLYzjr1V7/6FV588UW89dZbrlzNHH300ZgzZ47jeDIYPnx4yu/FixejuroaAwYMQKtWrVynK1c9SwghMUI74ZKhJND+6ySOrHCidZBt9aydwGaCRXUUCKudjfLlMyd6zLbRyXhX/Jj4+LGAl9NQF8okzUm+bsoYlYkn+x1CSKainbsE1Sfr50thyTg9Zot/VvfdpAnIHctEhcLCwpQ/M4Wqoii45ppr8K9//QtvvPEGunbt6iq/FStWoH379l6K7Ji7774bU6ZMSf5WFAUjRozA0KFDcfLJJ+Pggw/GypUrXadPhSohhEhCZHBhZ+ETByFtV8c41IGQdCRKinaRe0HgNn+3k0aj8FGybpWFqNsdWXDhjhBCfiIKC3hGRKV/1reJrDZKR6WqCL/85S8xZ84cPPXUUygoKEBlZSUqKyuxZ8+eZJjJkyfjkksuSf6eMWMGnn/+eXzxxRdYuXIlJk+ejLlz5+Kaa64JtOxPP/00DjnkkOTv5557Dm+99RbefvttfP/99+jXrx9uvfVW1+lzyz8hJGNw4pfNb5wKYhFfQiJpuMmbEEJEkLElXJuWyDUrZG4ZdLuFXKuYddPvy8RqV4YspXhUJvWEEBIHZPaZMmWwVXp+uP5xU24nuzG8kulzpz//+c8AgCFDhqRcnzVrFsaOHQsA2LJlCzZs2JC8V1dXh+uvvx6bNm1Cfn4+Dj30ULz88ssYNWpUUMUGAKxbtw6HH3548vf8+fNx5plnYuDAgQCAm2++GWeffbbr9KlQJYTEFicDB9mDDL9wWs6oTl7px85/2LZEhLDfEb/6XpHDI0TyduqmxUt7+uE/Owi5Fpb8FPX1anSgCCGEkOjBfjqeiJxjP3v27JTfkyZNwqRJk3wqkTh79+5NcWWwdOlSXHfddcnfZWVl+P77712nzy3/hJBYY7SlIyycKHetymm0XdQv5VmUlAOEEG84tUKXPbGJ80TJzO+rih/KUK9bEO223YcpH2VbBDk9tZkQQtIBL3JVnTu47Rszqd8VWbxLl7pmGgceeCDeeustAMCGDRvwv//9D4MHD07e/+abb9CmTRvX6dNClRASKbwMHET9l/q99d1K+anfcmnlhkD2th2/iLMShZB0w4/vUcYJul7L5XXLvWgeommG0e+F2deK+IUNcjGQEELiiNHinVM55cQoI2j8WHyMEpHcDdGsJdC8hbM4Ddm+FCWK/OIXv8A111yDt99+G8uWLcOAAQNSfKq+8cYb6NOnj+v0qVAlhJAQCesUaCC8yXnUBkdxInKDOPB5xhnts4uz4stN2f10Q+BVAU3EMPMHa3aNEELSATcyz4/FRafodx3EtZ+Oa7kzlSuvvBJNmzbFv//9bwwaNAhTpkxJub9582ZceumlrtOnQpUQEkvcnqLshxA0GnjYbR8lxC1hK8QJ0SO7//VzoiXzu4nzhJAQQoh/uJUPmSpXghrbZmLbEuCyyy7DZZddZnjv4Ycf9pQ2fagSQmJDXBRIsoR11NJxkyYHLoSEQ9S+vTj4t7bDyh+pn/KpLivHMv24yMagYbsQQqKE0z7Jq5IxSuOAKPfH2t0lUWoz4p3q6mpfwwNUqBJCYkIYfgFl5SnDL2zUDqRyQqKuGok65wIq07FTonDQR4wI6r0IYkug33n5RdzK6ydB9lN6OcM+khASBn7IMf2YMB0OlTTKM8h+m4uV6c+BBx6IadOmYfPmzaZhFEXBwoULMXLkSDzwwAOO8+CWf0JILIikE3AXBD1QkHXSspN0RMLaDWLIfty6tvCLsPMn5og8G5FFpLCfsWhf70Ym+Ok3Nd2wehf8cp1j5gs17Ek3IYREnSjIb0KixqJFi3DzzTfj1ltvRe/evdGvXz+UlZUhLy8P27dvx6pVq7B06VJkZ2dj8uTJuOKKKxznQYUqISQ2BD1QiNLAJEoDJaOyWJVNyWlOyyEfiNI7AUSvPOlOGFbr6jO2UyK6PZzJDUZbIv1aiNC/4+my0BcFZCwI6OGzIYSEgVPZYLeAJZqW3/7H022MZ9e26VbfTKRHjx745z//iW+++Qb//Oc/8dZbb2HJkiXYs2cPiouL0adPH/z1r3/FqFGjkJXlbvM+FaqEkNBxe0Jz1ARdkFtt/Zh8iuTh1lJIyWnuKl4mE7bPST6feJJJSqRMVW6mS12t+hl9/dzImZyGOtS4Lx4hhMSCOMiDqMottVxxHvMquc2h5DaeZ1nGqVN8Kk00OeCAAzBhwgRMmDBBetr0oUoIIWmOyPb6dHB4TwhxhtsDMvT/l10Wv/oVNwdOhD0BNLP2Tee+140ylRBC4kxQrrDClGlODrT109LWKD9C3EKFKiEktsgcFMg4OEpWODPCntiT6JAOhxGQ9MMPhaubd1P2AlEQWwJF8/BT2ex3Hl4U+IQQEgVUxWcY46ag5hF+n3avpm+XR1CHBzuB42WihwpVQkhkkXWgkmxkpekmnTCVFLLgYISQ+BL3rXF2uFGqihLVvs9ImermGUe1foQQEmecKDij3g/7ubvFb6LetiQcXPtQ/fLLLzFjxgx8/vnnSCQSOPjgg3HdddehvLxcZvkIIRmO11Op/RLcRoeTpAtmdQtjIEFZEw5u3ud0+gZINPDS53g55CNsX29WJ97HCW09ojwRpZwhhASNn3ImnRY+nZzpEBTp1L7EO64sVF999VUccsgheP/993H44YejZ8+eeO+993DooYdi4cKFsstICCFCRHnCJlPwej1sSv87qj6bKGuMifJ7TqKBSB/BrXLhEOVt7zJki9dnHPQOEMoZQogfUOEmD44diAw2bNgARWl8GJeiKNiwYYPrdF1ZqN54442YMGEC/vCHPzS6fsMNN2DYsGGuC0QIIW4wE7Z+rCKKrCrrw2T6aqabulPWBAMHqsQJIj7PRN+psPpFL5aTIpavbuuklxky044KUasD5QwhJAjMZKNTS1U72SWSntWcSZtHVLCSuUET9g4W4p6uXbtiy5YtaNeuXcr1bdu2oWvXrqivr3eVrisL1c8//xyXXXZZo+uXXnopVq1a5aoghBDiliAHAEEKb63j+6hZKQVh2UpZY4wfCwRRGzwTeUTp4Iyg3zORust+/52mJdqXxmUCJ7Mtg6gz5QwhJEhE3Llo5YKIjNDLMa3Sz80hWmEdumVEFMenUStTQ24LNOQVOPvLbRF2sQNHURQkEolG13ft2oW8vDzX6bqyUG3bti0++ugjVFRUpFz/6KOPGml8CSHEL8JeJRRVdFqtSosQZQfufip7KWsICQYnCj2tdYzfisgw+3grKyAjC1cnsiAqE9U44PeCKeUMIcQJMuSS6OF/dr6+7a7FUdY4mVvZpaMPL+u5kXgxceJEAEAikcAtt9yCZs2aJe/V19fjvffeQ+/evV2n70qhOm7cOFxxxRX46quvcMwxxyCRSOCdd97B9OnT8etf/9p1YQghxClhK1WDJKqC3K8JL2VNsLh5jlHbvkv8JV2etZN6RO1QpTC/uTgp0UXLSTlDCHGL0z4xzjJUtOyy3N7IJioynATPihUrAOy3UP3000+Rk/PTu5CTk4NevXrh+uuvd52+K4XqLbfcgoKCAtx7772YPHkyAKCsrAxTp07Ftdde67owhJDMRUQA+z2R1KcvomCiQuknZLcFZY05mbSQQKJBuvdzTi1vo9L3R6EMonjpt4ysjWRAOUMIIda4cWUTJ9lE0ps333wTADB27Fg8+OCDKCgokJq+K4VqIpHAhAkTMGHCBOzcuRMApBeMEJJ5aCdMRopNLWEcNOUlPBDsAEPWlhkv+XqtL2WNPRy0Ej1OFoC8KLiCeu+iZiGqJYouZ5xeD4qo9lOUM4QQp8RhUdtva/+wZQohTti3bx/mzJmD66+/Hj179pSatiuFqhYOOgghccVIuaBH1mAhDoOvKENZIx8R5RoHzNFExjPhc5WD03YMWxaEfYqzkY+/qLyLlDOEEGJPlPptQkRo2rQpOnfujPr6eulpZ7mJ9O233+Liiy9GWVkZmjZtiiZNmqT8EUKITIysVc2sWa3i+lmuOBA3hS5lTbA4PQGWxB/RftQurt95GvX7fiJ6KrJbGeBVdjg9qEQWfqWtrU/QfQvlDCEkLET7u6jNN6ysVkUwCxflHSkk/tx8882YPHkytm3bJjVdVxaqY8eOxYYNG3DLLbegffv2SCQSUgtFCCFm1qNmk1zV6ifoLfV2ylwvCosoDKBkt6mTQRJljRh+PKMovHskGIK2mAxKcesmL9n5WxFku4chG+MyIaacIYSEgehCoZe+O8y+OOzdEGZErTwyUHKaQclp7jCOfEvNqPPAAw9g7dq1KCsrQ+fOndG8eWqbffjhh67SdaVQfeedd/D222+jd+/erjIlhJA44Hbi79chVk7ipsOAgbJGDLqlyFxkKcrcpOEl36D6QT+R1e6ik2kZ32ZQBy3qLU71u0y8WvaKtIVoPpQzhJBMx+7cChGiNn6ktSvRc9ppp/mSriuFaseOHaEoiuyyEEIyBBmC2y5d2dhNzpxul/Z762TQVqV+DFwoa/zH67sYBcUWcUZUFJKykdX3hLGwoO8/zfx5e9nxYJSGTNymrcYL65BHyhlCiBu89Key+mE3hhb6vIMeD4QhX6lUlcfDDz+Mu+++G1u2bMGhhx6KGTNm4NhjjzUNv3jxYkycOBErV65EWVkZJk2ahKuuuirAEv/ElClTfEnXlQ/VGTNm4MYbb8T69eslF4cQku5EZSLvVbj6pRS2I+qDArtDvpxAWWOPLGVo1N8rQmQR5DZ7p9i5kfEb0S2oYfcXMtuIcoYQ4ha/+2s/0lflTFDyJmx5oSUqc9C48uyzz2L8+PG46aabsGLFChx77LEYOXIkNmzYYBh+3bp1GDVqFI499lisWLECv/3tb3Httddi7ty5AZc8lf/+97+YM2cOnnzySaxYscJzesIWqq1atUrxK1RdXY3y8nI0a9YM2dnZKWFlO3olhKQvslcO09X6yg9kbsUUyUsEyhpxgtjqzW8pM9H6wYzjO+D1wIwgsWvfRF21Y99oQWJUviAsgry8l5QzhBAz4ir3zHBzfoObHQNRhlaqcrjvvvtw2WWX4fLLLwewf0Hy1VdfxZ///GfceeedjcI/8sgj6NSpE2bMmAEAOPjgg/HBBx/gnnvuwZlnnhlk0QEAW7duxXnnnYdFixahZcuWUBQFO3bswNChQ/HMM8+gbdu2rtIVVqiqDUEICQ52/tZEZdAjQ1DLrEtYJ0/LgLLGG0F8E+yX0h+/Jx9R6GviRNSVqk4QcWfgN5QzhBAjtFb6cZFTfpZVdrqiLsQ4zowedXV1+O9//4sbb7wx5frw4cOxZMkSwzhLly7F8OHDU66deOKJmDlzJvbu3dtoAdNvfvWrX6GqqgorV67EwQcfDABYtWoVxowZg2uvvRZPP/20q3SFFapjxowBAOzduxdXXHEFbrnlFnTr1s1VpoQQokf2wRtBD4T8HgDoD/lQ8zQqhxluyhj0wIayxpqwrYi1756ZH644TUSIGH4/06ieBuwVGe2mVaRGZaKprVMY1qmimJWDcoYQYkSU+i9ZREm+htW+HJeaU1VVlfI7NzcXubm5jcJ9//33qK+vR0lJScr1kpISVFZWGqZdWVlpGH7fvn34/vvv0b59e4+ld8Yrr7yC1157LalMBYBDDjkEf/rTnxopfp3g2IdqdnY25s2b5zpDQgixQkTgydjO6WYLjOw0RTGrl5/1lYGoPz4jKGvcIdsNgNGz46A0Pnj5BvVpBIGbw4n8KIMRen9zXttU+6e/HgWiUA6/ffxRzhBCooybfthOvvghZ2TPqTjOdIb+2Yr+AfsPZiwqKkr+GW3d16J1lwMAiqI0umYX3uh6EDQ0NBhaxWZnZ6OhocF1uq4OpTr99NPx/PPPu86UEJK5eFXQyBSyTtNyctq9zDSjiIznYFd3yprg4OA1fYhrnxIkZhNKv9vOKt+gnpuTb91JmbRhzfJI1FW7Lpcfi6AA5QwhmUYQfa1Vn242DwryoCi/0B9M63QnHQmejRs3YseOHcm/yZMnG4YrLi5GkyZNGlmjbt26tZEVqkppaalh+KZNm6JNmzZyKuCA4447Dtdddx02b96cvLZp0yZMmDABxx9/vOt0hbf8aznwwAPx+9//HkuWLEHfvn3RvHnqdp9rr73WdYEIIemHfouHyNYL/X39lhU1Tbu0vGzzCGKLSBwGFmZbdNy6EBCFssZf/Hi/qcwLD1nPMwpb47SHYjnBaRw3sshp/LAtgawwc+Ehc1tmkO+S0fOwqwflDCFEi9f+z+l8RzQ9O1kkEzdl1s7PvKYVN+I89i0sLERhYaFtuJycHPTt2xcLFy7E6aefnry+cOFCjB492jDOgAED8NJLL6VcW7BgAfr16xe4/1QAeOihhzB69Gh06dIFHTt2RCKRwIYNG3DYYYdhzpw5rtN1pVB97LHH0LJlS/z3v//Ff//735R7iUSCgw9CSCOMlKrqdStkDGrc+A8Ke6uzWZn98D+kWg15OfTEaRvvD19jGYaypjGZMDAlzhCdsFn1G0ZpBOnrzCgvt9aR6m+nhx+Z+QQWyTvq36XbybHMBTMr61Qn6ciGcoaQzMNuzCp74crufIO4EAd5pyfOys6oMXHiRFx88cXo168fBgwYgEcffRQbNmzAVVddBQCYPHkyNm3ahL/97W8AgKuuugoPPfQQJk6ciHHjxmHp0qWYOXOm68OfvNKxY0d8+OGHWLhwIVavXg1FUXDIIYfghBNO8JSuK4XqunXrPGVKCCGy8TIZ9xv9ACQqgxEvK9BB5EdZI0ZUBrhurQpJeEThvZFFmHUJWyFtVgY3YaKIn2WmnCGE+I0sS1WZcsZpmbRGKnGRIxyPyuXcc8/FDz/8gNtuuw1btmxBz549MX/+fHTu3BkAsGXLFmzYsCEZvmvXrpg/fz4mTJiAP/3pTygrK8MDDzyAM888M6wqAACGDRuGYcOGSUvPlQ/V2267Dbt37250fc+ePbjttts8F4oQkhnIEsiyBKaIDzg/sLMciwuy24yyRhy/tueKHsam9ZVlFEdrDUKlq1yc+qB2ssU9bJ9ucfcnFzXYlo2hnCGEBIndeMlP9ux1f/BOHAmrndOZq6++GuvXr0dtbS3++9//YtCgQcl7s2fPxqJFi1LCDx48GB9++CFqa2uxbt26pDVrWLz++us4+eSTUV5ejgMPPBAnn3wyXnvtNU9pulKo3nrrrdi1a1ej67t378att97qqUCEEKLFrWWnm4m4LL8/braOutl25NRXnJ+YldNLmShr/EXW+62/R2WpP/jVrlF4XkH6f7Pqa2UqkMNoVzdb9M0WQKLwXrjBabkpZwghYRBXORM3qEwlKg899BBGjBiBgoICXHfddbj22mtRWFiIUaNG4aGHHnKdrqst/4qiIJFINLr+8ccfo3Xr1q4LQwhJJR0tuVTBZlUvUeFn1D5Gh2vY5SdKkNtczJ6913oYpevFd6qXcthBWSOO+lyDej/d+CUmwWC2MCTqZzQqRLlsRkS9PYPAqg2UnOaO/KiKputVJlLOEELiglc5k5/typYOQHrOSdOFmr0NyHZofVyTYdbKAHDnnXfi/vvvxzXXXJO8du2112LgwIG44447Uq47wZFCtVWrVkgkEkgkEujevXvKAKS+vh67du0K3YyXEBI+ZhN4PyabTgR82BNes3Jm6iTcrN6UNc4I+v0JWnlL5GBlmRnnSVIQcsYpYbSnX/LVSVi7ekdp8Y5yhhDiB0ZzID8OBgxLzsR5vEAym6qqKowYMaLR9eHDh+OGG25wna4jheqMGTOgKAouvfRS3HrrrSgqKkrey8nJQZcuXTBgwADXhSGEpC9eFTBeJ4tBDQKi6rQ9CuURLQNlTXQJ+x0iznBi7U/EsHK1IipjtGnIlkte+nrZcjLIk7KdQjlDSObil8yT3U956ZP9mvdwvJDK/jauCbsYRIBTTz0V8+bNw29+85uU6y+88AJOOeUU1+k6UqiOGTMGwP4Tu4455hhkZ2e7zpgQkjkYCfR0FMhGW2q94MYPoIy0w4ayxh1unmkUFO2EOMHp++r3O+7ErUyUvzVRH+L69kzUVdtanoqECRrKGUIyE7/GSn4tRukVo05kjUy3Z6QxbNd4cfDBB+OOO+7AokWLkgumy5Ytw7vvvotf//rXeOCBB5Jhr732WuF0XTnSGDx4MLKysjB37lzcfvvtuOOOOzBv3jzU19c7Suett97CKaecgrKyMiQSCTz//PMp9xVFwdSpU1FWVob8/HwMGTIEK1euTAlz5ZVXory8HPn5+Wjbti1Gjx6N1atXp4Tp0qVLcluP+nfjjTe6qTohaY3sE5VlpZVOVlZeLIecpqH6q3N72FbYAwUZsoZyRh5hvw/EmigdUifrcCQn8f0MryLD97eseIBYO7t5Fm5xe4ikX4iUgXMaQohbtLvS9EShDzRCL28zbWyXafUlPzFz5ky0atUKq1atwsyZMzFz5kysXLkSLVu2xMyZM3H//ffj/vvvx4wZMxyl6+pQqrVr12LUqFHYtGkTevToAUVR8L///Q8dO3bEyy+/jPLycqF0qqur0atXL/z85z/HmWee2ej+XXfdhfvuuw+zZ89G9+7dcfvtt2PYsGFYs2YNCgoKAAB9+/bFhRdeiE6dOmHbtm2YOnUqhg8fjnXr1qFJkybJtG677TaMGzcu+btFixZuqk5IxhInvzl+D2K0K9VBWPhFdVDmNzJkTabLGb/eTzeLHHHpP6JKuvYD2nfUqTUN3yniFc5pCCEqRmMmyhlC0oN169b5kq4rheq1116L8vJyLFu2LHkC5g8//ICLLroI1157LV5++WWhdEaOHImRI0ca3lMUBTNmzMBNN92EM844AwDwxBNPoKSkBE899RSuvPJKAMAVV1yRjNOlSxfcfvvt6NWrF9avX58yCCooKEBpaamb6hKSMfg1aAjSf2kQWzvjgrrFMiqnezvNU4asoZwRR6/8lGE5Z5UGJynholdeRnF3gihW72tQ9XL7Pvv9Hfj9LLRb+b0uNoaxcMs5DSFExUmfFcUDEUVQ+2b9QmZUiIIrKr0sA6K1C4jIob6+Hp9++ik6d+6MVq1auU7H1Zb/xYsX46677koOPACgTZs2+MMf/oDFixe7LoyWdevWobKyEsOHD09ey83NxeDBg7FkyRLDONXV1Zg1axa6du2Kjh07ptybPn062rRpg969e+OOO+5AXV20Og9C/CRsweSlDFE9IMMtVtuD/MxP/b9I/tpwYeK3rKGcCUfxFYV3K92JwoTECU4mpuo7FNZ75KUP98PPqh9tIdsNgZX/VCdl9+OZc05DCPGKbP+qWjnjVdYYxc/0cZhZ/fXzJKM5VBTbrnpfA6r3Ovzb1xB2sQNn/PjxmDlzJoD9ytRBgwbhiCOOQMeOHbFo0SLX6bqyUM3NzcXOnTsbXd+1axdycuS8ZJWVlQCAkpKSlOslJSX4+uuvU649/PDDmDRpEqqrq3HQQQdh4cKFKeW47rrrcMQRR6BVq1Z4//33MXnyZKxbtw6PPfaYaf61tbWora1N/q6qqpJRLUJcE4Ut927KEIR/ODpd9x/12TtR1Hh9Z/2WNekmZ8JWosXVWiOuBN3f+f18w3p/3eSrnXB56efs4oX9TTtB2xZ6pbOIsiFon+sq6T6n4XyGEDm4tbpX4wZNnOdEfrlWszMmkZEOiS7PPfccLrroIgDASy+9hPXr12P16tX429/+hptuugnvvvuuq3RdWaiefPLJuOKKK/Dee+9BURQoioJly5bhqquuwqmnnuqqIGYkEomU34qiNLp24YUXYsWKFVi8eDEqKipwzjnnoKamJnl/woQJGDx4MA4//HBcfvnleOSRRzBz5kz88MMPpvneeeedKCoqSv7pV4cJIcFhtCoY9iqhWd5WJyN7xcnAzEr5ERcFdFCyhnJGjLgodoizZ5Uuz9XLYp+RWxSZ+erz8kN+yU7Taxv4tZgqu93SfU4TNzlDMpuwx/Z6vMgGu7Ts0otSO2jxs1xm7R3VtiDx4vvvv0+6y5k/fz7OPvtsdO/eHZdddhk+/fRT1+m6Uqg+8MADKC8vx4ABA5CXl4e8vDwcc8wxOPDAA/HHP/7RdWG0qJVVV3VVtm7d2miFt6ioCBUVFRg0aBCee+45rF69GvPmzTNN++ijjwaw3xG9GZMnT8aOHTuSfxs3bnRbFUJCJQi/cmQ/ospUq60monlEbZDhRzn8ljVRljOi7akNx2+a+IUfWwb9Uio6wS/XAjL804VhnZqoq3YUPiryxwvpPqfhfIbEkShsr/YyVpeRT6ZjN3diuxGnlJSUYNWqVaivr8crr7yCE044AQCwe/fulIMfneJqy3/Lli3xwgsvYO3atVi1ahUA4JBDDsGBBx7ouiB6unbtitLSUixcuBB9+vQBANTV1WHx4sWYPn26ZVxFUVK2t+hZsWIFAKB9+/amYXJzc5Gbm+ui5IQ4I0iBYORgO4oCyWoiGaUtklZWqrLbNVFXbemHLkys6uvlWfgta+IoZ/Tvd9SUqFHtU9INtnH8EPk2ovY9i8hTv9wdiOJ1x0W6z2k4nyFRIU4uTOzwuy5Ox1J+7zyLypjDTKkq8iyiUgcSHj//+c9xzjnnoH379kgkEhg2bBgA4L333sNBBx3kOl1XClUAmDlzJu6//3588cUXAICKigqMHz8el19+uXAau3btSllRXbduHT766CO0bt0anTp1wvjx4zFt2jRUVFSgoqIC06ZNQ7NmzXDBBRcAAL766is8++yzGD58ONq2bYtNmzZh+vTpyM/Px6hRowAAS5cuxbJlyzB06FAUFRVh+fLlmDBhAk499VR06tTJbfUJiR1RU8KIDEbUAYXV1sx0IOwVeKPT3fU+AlWCfne8ypq4ypmwv1E/8rebIPhl9eHERUZQFimZjldLUrv3KMyJbpC+QOOygBF1RQrnNISkN279nwbVv8ryzypa5ij3xyJGGqLjuri4OCPBMHXqVPTs2RMbN27E2WefnVxsbNKkCW688UbX6bpSqN5yyy24//778atf/QoDBgwAsF/IT5gwAevXr8ftt98ulM4HH3yAoUOHJn9PnDgRADBmzBjMnj0bkyZNwp49e3D11Vdj+/bt6N+/PxYsWICCggIAQF5eHt5++23MmDED27dvR0lJCQYNGoQlS5agXbt2APavzD777LO49dZbUVtbi86dO2PcuHGYNGmSm6oTEihBCIAoCpu4HEwCWLtUcKLIsQtvZJ0qYq1rVC5RnNZBNjJkTbrLmSgpKqJSDidEqd8zw6hdzb5NI9/JMrbmy8ZJuby840F+H2bPSSReVL5jOzkThTLKhnMaQogZVrLKiXWk7LyDNnTwc66oN+TQ56kNY3bPLn2r6+ko14g5Z511VqNrY8aM8ZRmQlEUxWmk4uJiPPjggzj//PNTrj/99NP41a9+he+//95ToaJIVVUVioqK8M2WShQWFoZdHBIQopYoZpOhKEzWRQWF6FZEp34+zQSi2wmkXyuvTsojOsF0s11HpDyi76T+ulGaVu+uyETfy2S7qqoK7Tp0wo4dOwz71UyTNaqc2bppg6mccfrdhKGosRqkin4TohaJZoNwURcUbvtoL9+MWTx9mUS2Wsuqj4rTZyb74CEztzRuy+Vky7pVW4r0xW63HHpVqHpdOHOSrj59swmwlew3S9/o2ZuVw+p90N+jnElFRM4QoiIyFhWVX076YxVZ4xcv8w8Z8w4zWeFUzojkZRRHj1fZLTO+12fux1jIKVVVVTigfampnPEz36KiIrz3v41oUeAs3107q9C/e8fAyxw2r7/+Ol5//XVs3boVDQ0NKfcef/xxV2m6slCtr69Hv379Gl3v27cv9u3b56oghJB4YDVhMsJuMObWKlSmsAxb8S27fWTkHQUoa1IJ+z0VRf0+7d7fuGxXJsaE3XeIWA4FUQa38WRafsr8lpzIHb+sloJ8tyhnCPGG1W4JfR8h2r/40QfoyxkXC0Vt/y6jrDLkTZRwYq1KMptbb70Vt912G/r165f0oyoDVwrViy66CH/+859x3333pVx/9NFHceGFF0opGCEkOhgpUd0qQvU4VRpq8/dLcMpSZNpZ2Dgpv5u6emmjKAyYKGuskfGe+qW0F7XuJ9HGz8mJ0TuSCZMh2e++LCthrzLVaguq2c4IbX5WShkv2KVBOUNINAiy/3e6gyxs2eS0n4+iklHf38tcWIxKHUm0eeSRRzB79mxcfPHFUtP1dCjVggULcPTRRwMAli1bho0bN+KSSy5J+g0C0GiAQkimEQVBHDXSpT3iphTys7x+pU1Z442ovaNRKw8xJw4KcRnyNay6RG1sYKfcdEqirtrQJ6sMZC8EUc4Q4owo9V1xIMz+PgwZp3fbYxWGkKCoq6vDMcccIz1dVwrVzz77DEcccQQA4MsvvwQAtG3bFm3btsVnn32WDCfLjJYQ4owwBLedHzij1ciwsSqLVV1k1UOmMkBfXqsBlKyJrt/PkrLGnKC+ozB8sJLwEOmng34fovD+iX4Hibrq5P+N+lg7y0236fqNne/BKDwjrasR9bcIlDOEhI9MFygkXGQvzhEii8svvxxPPfUUbrnlFqnpulKovvnmm1ILQeJB1JRhJD749d749U6K+oAMijC/Oz/rb1cvypr9GLnaiMJ7CfivcLV7R8L6Nvyst1P/lUHmHZX3ToudHJDxrKJYbzNkuNYJk6DLSTlDiDkyDQtED13yAxFLSTuf79qwXohTf+wG6gtIVKmpqcGjjz6K1157DYcffjiys7NT7rvdheJ6yz8hRIx0ECpe/HD6XX8vfoKsymc12JHVHiLbYNzmZeXvNgwLJ63lWzoPJP1AthJV5jcpq0xGhy54efeDIC4HWoiit3A382kps752zzrs/iIqE0OvfbZoG+7Z24D87KxG141839khUmb985ftQ2//tRrXaRJC5BAFORmV/pwYQytl4jeffPIJevfuDQApO1AAb7tQqFAlJGT8FPBRE0hBrUI7DS9rld1JfrLawm5yG8Q7ELX3jBgThhsQJ+E42fGOU2V0VL5dGQciyX533CxkhLFY5Raj9jJSptql4eYdEjm0ykkZnFwnhMjB7rt1MgZws2gTdbT1yLQDGL3K5HR5B4JiZ+0+NOTscxSnutZZ+HTArx0pzkZOhJBIIKJAs7Ow1P45IUq+9WTlH7TSUXSiLlquoAZqWj9+Tkj3gWOc0Q727foDt/dkxiFi5DTUpfyZ3bdLwwjR55YJz9dtn+hHeiLPVCZ+Pl8zGRn2GIMQYo6oH3+7uH5i5cIgLILuu+OC07mqkbww+iNENlSoEhIjZAgC821x3tKIE15XTdMZs/qpE30nFgjp3lZRIZ3a2c/BbroOpEUmG9qJhJN2kNlmUXtPve4U0Cs/vSpXZStnrTCq9569DSn/eknLC2btkK7fLyHphCylVdTkhRO0skXmjrRMx2z+qndxZvcOUpb4z/r163HZZZeha9euyM/PR3l5OaZMmYK6Ouu2Hzt2LBKJRMrf0UcfLbVsy5cvx6RJk3DeeefhjDPOSPlzCxWqxBB2NsHgdeu40/hOhLpb60in6WTCu+akjk58ujpJ12qy7nYir80/UVftSFnPAaY1YbZPEHkHVT+7wbVs/7RRR8b2bCforUtkHehhh51S0Kmf6kRddfLPKWZxRNOy67tlKWJFtvur7er2OVq1hVlduGhHSGYQRT/xeoIeK3iRPemOVzdBtFj1j9WrV6OhoQF/+ctfsHLlStx///145JFH8Nvf/tY27ogRI7Bly5bk3/z586WV65lnnsHAgQOxatUqzJs3D3v37sWqVavwxhtvoKioyHW69KFKSEwIY+KfST4Nrdo1UVed9I2nVyIqOc0D9/XjxzZIbR3dxBUhU94lEi+MfLg69UUaFlEtX1TLBfhjUSnSd2rDqX2mXVzRcF4QlfN6JbX6W6uItZKJXhXLaticnGi/X4SQ4PBr/C2SrtkhfmQ/bueQRrJFxY++Py7jvTgxYsQIjBgxIvm7W7duWLNmDf785z/jnnvusYybm5uL0tJSX8o1bdo03H///fjlL3+JgoIC/PGPf0TXrl1x5ZVXon379q7TZS9ASMyROZDgSp08/FpNFlWmhvEs+f5EGyd+pJxuU3Nr+Ri1Lf5ey+PGfUo6fDcy+ju/2iEd2jdInCgIzMLKbnM+Q0KIGWEpwqhMlY/Zwl0QUM74y44dO9C6dWvbcIsWLUK7du3QvXt3jBs3Dlu3bpVWhi+//BInnXQSgP2K2+rqaiQSCUyYMAGPPvqo63TZExASE7xumXS7NT9TtuxbtY+ZZZCVxZBMa6Ig2tjIAtcMfVs5rStXgYlTP55B9TNhu1pwosjWhvPLQke0LHZ9gNsdFm5dnVhNdPWLCkbpmdXbqJ7qNTs5of5bl5VjG8cq7ahs/TRqYzcy0Yn80IdNl/EHIVElKBdAMn2NOpm3WB3cGAX82pkQVVS5ov83KKLy3IOkqqoq5a+2tlZ6Hl9++SUefPBBXHXVVZbhRo4ciSeffBJvvPEG7r33XixfvhzHHXectDK1bt0aO3fuBAB06NABn332GQDgxx9/xO7du12nyy3/hMQIv5SpdnjZ+m8XL0oWWm7L4taXrVF+btpan46RWwK/lb9GaXAbjb/I+q7VCYVVelbvbBzQlzvq9XBSPhn+rv38VoM6BMvoHXazIGjUBrImtdq09WmKKBy1ylQvilVtW4k+8yhZYxnJO8oZQvzBD3kZ9vfqVdYAP9XBqRsup3VPB6Wqk7lNlGRNXPixZh/qmu51FGd3zT4AQMeOHVOuT5kyBVOnTjWMM3XqVNx6662W6S5fvhz9+vVL/t68eTNGjBiBs88+G5dffrll3HPPPTf5/549e6Jfv37o3LkzXn75ZU+HRqkce+yxWLhwIQ477DCcc845uO666/DGG29g4cKFOP74412nS4UqIR7xemK8TIsdJ4cCOUWmP9Wo+WZ1Uhanihmj8G6JsgJIhKg996hSl5WDPN1vwP479/p+WD0fs3t+KyatLOe9vktOyx7n91dkYcvqnoy6m7W1qhiUMWnUfiN+95dRmuTKbEOg8bOS9d7ry6dd8IuK5S0hxD3a8YrR/9MJtzLG7/YwU/S6Rd83O5UzRn7qo4zW2ABAo/+nGxs3bkRhYWHyd25urmnYa665Buedd55lel26dEn+f/PmzRg6dCgGDBjgakt9+/bt0blzZ3zxxReO4xrx0EMPoaamBgAwefJkZGdn45133sEZZ5yBW265xXW6VKgS4hPp2Ol6QYYlplNEJtUiigS3aTvJyyhNvkMkaPTfpd4SzOnp6H6g36rt1CpRi+h3HNfFjDCekZcT4P1SCDqNK7vd3MoZLUYKx6ya/VvXGvIKkmFE29DMole07l4nmEaTdFlWt4SQYNF/e1EYK+iRvfDkBb/6K6t2F5WL2nYy6pOdypk4YrbrLx3lTGFhYYpC1Yri4mIUFxcLhd20aROGDh2Kvn37YtasWcjKcm55/MMPP2Djxo2eDoxS2bdvH1566SWceOKJAICsrCxMmjQJkyZN8pw2baoJSVNEtne6xckWU7f+D51Y2xr5XpIxqDCLH4ftz2aDoDCIahsRY6LwvJwMWGVvrzMbSLvJO0zcDvrdHgIh0wdeVJFVP6/pyOrLjd51q3da73/WLLxZ+azKTQtVQuJJHPr9dO9fZMlfJ25lEnXVyT9RtDLESJ44wUtcLxgZCEV5LBgGmzdvxpAhQ9CxY0fcc889+O6771BZWYnKysqUcAcddBDmzZsHANi1axeuv/56LF26FOvXr8eiRYtwyimnoLi4GKeffrrnMjVt2hS/+MUvfPERSwtVQtIYI+EalDI1TKK0Mu50S3GirhrIsy+zfqVdXTF2u5psFSZKq/qZhJ8uPEQI+lu38gVsdc3qutP8ZaUd9mKLk/fESIG6Z29DIz9mRhaJstwBqGj7ITd9krb/i1N/FeT7UpeVg9ya7Zbto29fo2dsJINq81oht2a7Zf5eLZHNrKe0aaajFREhUcTrwp2Zv0yZ29XNXI2Y3RdJU8UvOSMqE7y4LNPjRDGqD+u1X49rnx2HOXEYLFiwAGvXrsXatWtxwAEHpNxTFCX5/zVr1mDHjh0AgCZNmuDTTz/F3/72N/z4449o3749hg4dimeffRYFBQVSytW/f3+sWLECnTt3lpKeChWqhPhEGMIh3Q5qECm7X/VzemCHaHoiOH12sgW61cBIZl4ciIgTp7bSKtmC9GnpBD/7Z6eLKLLxqkwFUie5RtYYIvecTN6yanambFvXhrE64d5uIUkEt5NAIz91Iu+8Xlmt/vbjGxGZ5Np9C2oabsvmtl4y2oKWQ4QYE6ZMttoF4bRMIjLGTj7oFax6rO45UULq+2K73QBEDLZV9Bg7dizGjh1rG06rXM3Pz8err77qY6mAq6++Gr/+9a/xzTffoG/fvmjePPWbPPzww12lS4UqMSTOSrggsfOLJkpQylc/J++y0vZTQapX8liF85qPrPTM0nCiBDAKq09TG8bo9GkZ26X070qN5xSJn5j5UnXzjTp1ExIEan9g5tJDdjmc1i2IttBbB7nd7m/mj9MMM3+gqlJVNI7+uupTVItVmkbpOlUeirib0Vtj7dnbAGT/f7h6d23uFieW34C1rDGSG1bywi4tp3JGH8fsmyaE/IQMt1VevrH87CzLXRB+ofc5rUfUVYkbOaNPx8pq1ohM6NPiaqVKos+ll16KGTNm4NxzzwUAXHvttcl7iUQCiqIgkUigvr7eVfpUqBISEUQEiR/WgU4GVnaKSLswRuH1/xeJZ2XB6bcw9tORfE5DnemAyunA1ygd/TUnacZp+2zcUa2qRL9Jt++j2bdv5atYNE21bF7KFTZG7W/Xb4ahhJXZXmbbL0VwW3ft5NRIqSqiZNNPcBO11VBymxve02OUn5Fyz07RKqKMNgpj1+ZO+36z8htZ+8ru19VyqulavZtmClS7Mhkt+FmVhRDyE04XELWLFDK/Kb+VqVZKUFlyRvSeijZPK2tXo7G6EXYyx0i2WD1HWcYTXtCOaalgFWdH7T7szd7nKM7uWmfh48wTTzyBP/zhD1i3bp0v6VOhSoiGKHTesstgl572fth1F8WtwsfKkkgWooowo3h22A2EnFwXTVcWUfi24oboMwlCccBnZ49Xy3are1ZWhX71Y35hN2GzsyLShwP2K1Ab5aO7pipYRfJz4otaO6mt3tuA5tlZyX+11wGkXFPjelFimxH2pFgUUeUoIcRfrMaBesvvdFisEJEzRkpSI1mjxUzO2OWpd3tj1hc62UVi56c2qqTD+0WihepaQLbvVBUqVAmJEHb+6GSmTfzHyFpP9iEuVhitdjvJ18yZvz5NEn/C8qcWtm9Vt99iHBYIgphMGR1MZIRZf6FOMLWTVJEJaUoZtBPcaoMDkZq3ahxOX77c5oaTXW1+dgpeVWmq/9cojCxEtpkC8hSsZhN9o+tmO0j037uVnAEoawiJGvpv2+3CkFvZ77Z/UGWAUxmjjQvAk5zR5qH23+pvO7c3yewt5Ih+0Q5o/Hz8Uoz7tevBSJb4PW4Me2xK5JNIJHxLmwpVQiKIUx9nbtLzC9lCSMTCVs1XFqKuF7zk6UYho29XWf5ZjdISceKvom4TEjn8hMhDVntGRTnoVznilq4M3PpCBdy9V0FYRBpt60+im+DW7/gBTYrapN77/wmvESIuArJqdqIBxhN4dYK7Z5+Scj2/aSJ5Lb+pvMG86MTbCaLyxO2kOahvJcrfJSHphhdZIwMj1yx2frX1/b2tn21V1hgoUpOyRnvPRNZo89WXTb2nlseon92ztyFFmWokW7T3jZSrWszOZ4j6Dgc/zqUwui7iDoPEh+7du9sqVbdt2+YqbSpUCSGhTUCiOPGRVSa9j1hV8IpY54iUJ8x20w9AnQ6+/FjFzjRkKlODxq2VdhiLSulspWA2oQDELNGdfPdG37yRdar2dxYELTCrt6N+xw+NLmuvNZrw6mneqtFkV182I6umPbrJbZXGJ1lhbtMUBeuefUqjia/dhFeLjImulR9Vme+5F/mk1lG/BVZF65/V7uAzyhlCxHEq70SUqSKKKxHc9H12bmGswjeK9//yw0rWNFrE0/P/cgZIlSfqNSMZZIR+4c5s0U5ExvgxxnGyk83prjdZrpXMlKdW8610HQtmCrfeeiuKiop8SZsKVUJs8HNLKDtna9KhfaKoNCbEL/i++0NQit1Q+9zq7ZZWpF5IsViViHpatRVVtftQmBud4XYY1kdODrTLhXj5zCa66u+oW1oRkomkw9jeCFlyxo8dCJmO6LjU7tBjs3eX497oc95556Fdu3a+pB2dER4hESYTlQQip3WLTpLMBJTIIVJBnnAtmp4s5UZOQ52tdWoUacgr8GT5Q6sh9+h98crA6KR6r+4sRPK0u6ZXlhhZFIj6mXZywJddP6UPE0XrBSNFX5hyTPvNq5aWSf9x6g2dZY7dhFLJbb7fsqd5KzQRKYSNstbIMkjEWghQt1Y2QD+s3m8x1NRwu7+odarRe+V2sq33deumL1bj+OUrT/9+2OVl9d0pOc2Bmiqp5SQkDERlfpBKH5EFpSDR9k36PsSst3UiZ1C93V5h6lLOaC1o9WVS+8af/KCKtbmIjDF6V9zuhnAjG6IyHzBalMu0eX8646f/VIAKVUJS8GMLqiyH2n5aKIkqNt0KFy9CyQ+Bpqbp5YRlkXKZbfOXgdnz0CsurHBa/6gMfIgcrL5pP0+Ql4nX8hktHKnt4nYhyC6/oBSv2m/brG5W2H3vbiZdat7atM2mhnrln36SmVWzMzk5FRkqiypHk+XKKxA6lEqrVBDxk+pkm7/Is7J7Dk4PCrNK0yyO/rqXnT12+cl6fwmJC2a+7q3ChyFnAP/GDlpf/UZ+U83Cq/9vQOPDoPRh9X1+8r5WqWpXTodyxiqe3iWL2qaqDBH1l2r2jGQSt/7Wy/xdJUouoX6s2YvaJnsdxdlT4yx8nFEUxT6QB6hQJcRH9JNYO6wsncLutJ0MjqIkZGThRKnsx8qm2TvhV1u7VZao5SLpgex32U1asvK3+lbMtgwHQVSU1trJm1vLRbOJrpFFr0qOTfXN+iLt5FdkEqu1rNf66dTeN4qjL0uy3BrFgXbC2niSK+4r1UqR7wV9G0Zp8mumDLEiKt8MIemCnax3OhaIgtJOb2DQoPm/3krfSM4kd1FoFu/sMFr4MwpjdvihFTkNdUD2TwYhdnLFyGBC9LnYzQGiJEPCQPs97P+3JtwCEUsaGvy1pKdClZAQCPMgGP01tTxhbJ13QhS2X4SVv8z3RduOXq1zRcrFg0GiTxD9UdjfLuDvAoQdVochWCGiXDPr183uGyHL16TRRNUOs/Ka9TMi1q1mZUummYNGW0Ldkixfdo7hJNds0uum/9UrhP0kDv02F++ICHFb5JdRXjcucezylClrvLqNMkvHsp45P4UxW8gTWVgzs3Q1Ko+ZjDJKU0QeNd7+L4ab98npTgU/kDF29HP8GYWxLQkfKlSJJXHZ9imDoBR2YTq09lOBKosol02P2wGvjAGl1zKIIGolZORTUlsuKlUJSUXE4l3v11aUIBUHXiZcRr738rOzTF2ZGPUjTvoVrauXnCapcWVNGt0uUrl1DeS3rzovfbd2AcPMZ7JV/bjjgfhF3BSsbhGpp5GS1OmCnyh+LwSZydOkrMluPE6162eMFrGs/Dvr3QiJLoKZKVONdn04nUd6edejMnaPwtyQflaJGVSoElMyYbDhBD87ziC2tDrNz2l9vfgjdZu/XZ4ynplRGnv2NqCoyT7Haeknp3a//cJqocRucFmXlfOTv8D/b3sOKKKDHxPFKA0aZVruhF2nqFi8aydsMhd7gMb+qrVK1GqBw0zM+nd9PyUiK1DfkMw3Pzs1vpvDmvQTXSOLJ5EttDK+VzvlcFjYudKQVf+oujMg7ghS4elGcR9E+WTl4dbNjuz66fulIMa7VvLGbPFOi+iZBNp0UhYKNXJGVh9t5T823eftYdQvzJ1NJD7I034QElPcWgH5SZS330fpRE8RrJ6pTAUwYHzADSFRxut7KmMBJwxLtKCVmTkNdVIUwXHAj0my2QS0LivHsF327G1I+QP2T6jVSbV6zcwaVhZ2z13m+CNRVx0ZZarMcsTlvSeZRVTfy0wae/qtkDXqx1SZo/0zw0rOyCxjVPp9P5AxdtKn4TQ9OxmeSd8cMYYWqsQU7YpMuncWTpUCdtvUZLWXE4tT2c/IbABgpoT0Uzlphuw8RcuRn53lzHmfCV62r4aNaNvHqU5xI+xV86Dz9uKCRlSp6wU32yvN8jYKJ8tSQp+GG7+nomj9iwJIWqna9R/q/ZyGOkMLWquDrMz8y2ktZLXp67GynLKauFrF82sLbVQRfY9E6isShnImvQjyO5C1q8spolvO3eQtQ85oyyfTil6mrNH3ufqdJ3o5YHXavdlBhWoeIrIHQIpbAat8ZEPXWvb42a+ki+wm7qBClVgS9oTdb8wGEwBSBhR2cbzkZ5W/E5yE15bDboU1bKKwNdcJVoNFLydoB4ne912jld3sxhMANz7yiDVRbr+olisdsGtbqwm40SEhIi4OjPzAWaXv5vmrZcjPzjLsR6zKZzTJNSu/ZdmyjRdGjbaj6tMVQebWc5E2ljmJduqj1qvfWVnKVCvS2XKLhI9dPykS3wir/trtuECfpltFsl3d7NL1e/xrln9OE9gaQmjljPpbL2/s+pScHGMDnCD6Iiu5pb8X9mFTRC7bq/diD5z1CzXVe30qTeZBhSqxRdakPmqKsTgoBMwGaqKr2npFmEzfqWbh7JRsdvi1bV5UUa1XIlqFN1Q2GiBz0uvke5RlCSBqeadtqyh96+mGvp29WG66we++M+j6hI1If26E/ru0mvy6meCLfPdGkzIj39CqVY9Rf6mmkYvG/WSirjo5yU3UVkPJbd5o0mukYDVDb11kF0+GrzsRa1c3FrHaMFYLeLIJ2td3kHmSzEC0nxXpN8NwWRM0TsadTnbWqejD69OQsVBl15dm1exEola3UGcib8ziq7LIqZyRjd1OCrt77GsJcQYVqiQQojbQiIrZv1tltajC02vYIJTgThSwdmFFlLwi7WK1DUq0rGFj5vtJ1rsftW+a+EsYzztKi3B+K3llbOMPMp4ZVpY82sma9l6K9en//6uG0U9y9RNeoPFhAA15BY0mwfr0zdBbwlqF0d43uqaiVwa4nexa4UXx6ia+nwoCO+Wp6DZktYyJut1Sy0eIFTL7VNn9sxc547Ussupi1veIKEy1GPXfjdIUkDdGeYh4BNPKDFUZq/3XqJxBQcUqIc6gQpUQE6Iymfdj9Vt0wqLN1+s2HxGctLmVEtjoull8bVinfu6CeD+MnpXR6r3dwMdpWa2ehd6yzO70Uypf/SWd2jjq9XAqF8I8fVz1VWrks9TunVHjWPWNokq1rJqdyQmm+n/thFE7ac3CTxanjSyGqrfv/7d5q5/+DyCB/ZZE2vyM0tamry8fLK6r6Ce66uTXLC2j+3pFstvJsplS1yw9KyWE1/fSaT1E8rRT3ka9nyCZRzrJYSfo/VID3nbOOA1v1D/o+24RxWiitjpFrgBIlTXNW6Wkpcocq7RFlLbqdf2/2vthKFUB7gwgRBQqVEnG4deARz+AiOLAykgZ4ESJqJ9ci1qK6NOwi+ek7czSMlMAGA0O3ChytZjVRT8pVP9vFN6qPeIyqInKIkQmErV2j2of6AZZ9TBSEon4qHTz7e/RnWYvEl57aJMRTt8xvfIR2D/5zAKMFaUAEtXbkdX6AMN79Tt+AAA00fwfAJo0b2U4qdXHB/YrX80sjMwmvKL3jcLaKWvVf+s1FrlqeCurV6t8/Zh8/2Tt6e/WVbeHfjlJh6QnMowPwpRbTtx0+bEl3isihw3qwwNILtyZjYmdLNwZYagoxX5ZAOxXjOrlR/2OH9CkqE1qPBPFaso9TdpG7gLCxq18MBuLGF2PwrtISND4f0Q2IWmA3UQyasoMlSiWy4/Bqizr2CDysfNp6PczM/NblS7Kr3QiU56JVT3j1gYi328Yyp49extMlaUiytcoypIkBpPldCNqE/MgSNRVUzFKHOFVXkRN3rgpj4xvxsztlR12C3iqHBJd6POK6UKbFzJA3hBCnEELVWJK1AYWTpBhKefXBNKtc3cZK+de6uQlblQGuUGvlmrzM8pb5FAZs7hOCcJNgVvrZ5JeiLrbEO3Twn6PzA6fc/st2fnR1IZzi521KeCs/G5kqmoJo7WKsV3F/3/rH6PfTTSXmxS1MY9jkZ7WNYAeK9+rIve1Ycy2/BuF01+3+7/Rb+01J++NaFj1nRV9d/WIfsPa9J1Yc1ulQ0jYMkQEqx1bTvpeP8a5+l1pIsja6i/6LRttr09an6pyQGdlqsoDvZVqinzRYiZrrGSQB2TvNnCbntk7ZXYYYlx21REiCypUSWywE+Sik1w3W9SdpuX0YCo/wqrlMLKIdCro/FDCWbVRmNuu9AMBu3L4bbmlf1bqM9W2kdXztHvWIq4SnD6LOExe0pkonDps5+NY//84EsZEV9RNilouO8WqE0shfX2NJrpGdTRSBmoVq4nU4CmK2BRMJq1WSlIjCyUrX6lGB4KY/bZSllrdd4rZdkp9GP09URnhFaf19FoW0f7tp4l9M0/5ERIlgpKbIjtH6rJyhBbv/MTI17JWhqQoSzUyRC83lNzmjWSRYX4G8kYrZ7T3w/J96hWvfTSVqcHz3c5a5NZnO4pTu7vWp9JkHlSoEl8xUtaIWuWZpeE0T6/oJ5FulX0yyyXTAtervyn9b5npxQVtnc1WbAHx+sl4NjIsdEQmrCpxfXaZgJmbByfxvS4sxF15arV4JvLuBz3ByGmoA7KdfZNOJ8ZW/UtdVg5yclLDKjnNDU8/Vie8+omqXvEKICWc9v9mSlijNPXYWX86sQ41w2rSrw1j12dbHdRkhNF4y8hCXM1bxLJIVJEuCy+yTMlpDtRUSS4RiSJxlzFWiC8e+C9njPy8+qFUFXmedvVVF8DsdiYAjZWvVnG0aRuF9VuR6vY503KUEH+gD1XimJyGOk8DFy8WcDIOMRJBZOuynS9ML3mLpOnF0kuvsBPNU42T7sozkclbEG2gzcOLctSrQo1EB6cW7XYW9l7L4qTvCAOv8ko0j6DyEsGurwjSh52KOolTcprvV6zmFST/gP0TUu1vFf01NZz6fzWMPrzZn7YMsiaWZq5dRPMxim8X1+ie9prdd281ftG+P2Y7W0QOU5OJSL3oc5VkMrL6syh8R27kqFmfaSRXjK5r5YpetpjJEis5oy+XVXmd/rmFylQSJF26dEEikUj5u/HGGy3jKIqCqVOnoqysDPn5+RgyZAhWrlwZUIndQwtV4htelaR2caI8iQ+LKEzm3eL2eco6UVJk5dav1V3RujvN32irqB+ncZqVP0grpkzFaV+oWqX55QctDILwDyxaBiOc+B+zQvsNG/UF2u8tUVcN5DVuD60iVft/0dOZjeqp9QVqZRFphoilZopS1cDS1a1fWr3PTn2fKGoxandNn6ZTizKzdjTzzS0S16xsZumY5S3S7nZ+UL3I1rCVPyQ9MXr/rWRnnMffKo1kCIy/WW24nBzxrf9aObNnb4Ow3HFqpS6yI8AI0d0HVrJXlryPCjTIIF647bbbMG7cuOTvFi1aWIa/6667cN9992H27Nno3r07br/9dgwbNgxr1qxBQUF0XWiEaqH61ltv4ZRTTkFZWRkSiQSef/75lPsiWuorr7wS5eXlyM/PR9u2bTF69GisXr26UV4vv/wy+vfvj/z8fBQXF+OMM87ws2pphxvfnTKQ4c8xavhVfn26+lVmq4GO3uG80+27MhQZMqy7vE6snMS3KqvXFX7ZFmRGZVXLl1WzE1k1Ow3Lq6+HSL3s2iVo0lHOqN+K9rt1gozvVcSftdlvv5DtVkXfzjLRL2zYfRtGE12ja3qCansnikE1vN7axuy3lTWm9p4Tyx695aWZZahVOa3KLhOjb83smtl3aXRPlozRWo+ayRGj/4uixnGy8BgG6ShrrNC/U3FYfPOCH32pnzJGFvrvyckOCDd9jN3ipLZv1mK0Y8bOutPsnlMLURnWo0Y46c/Nwpj9icazS1N2+dzipq4y0o7DTq0wKSgoQGlpafLPSqGqKApmzJiBm266CWeccQZ69uyJJ554Art378ZTTz0VYKmdE6pCtbq6Gr169cJDDz1keF/VUj/00ENYvnw5SktLMWzYMOzc+ZOPrL59+2LWrFn4/PPP8eqrr0JRFAwfPhz19fXJMHPnzsXFF1+Mn//85/j444/x7rvv4oILLvC9fiR9Eek4o9a5iq4Eu0FvkeS17lEeXLrBSZuE6dzfDVF7z/Wkm5xJt2/DT9y4RYn65DbqmFlwWfWB6kTUbHu5XglrNIERlcl2293tsLMIFSmTmULAKI6oMtUJZlbKftPokDET4mrJlW6yRpRMUyako6GHKCKLFepcQ3bf4qRfsHofRRSj+rS8/rlNxyyeSNlE2kiGUtCufG7Sc5O32zLKLA9pzPTp09GmTRv07t0bd9xxB+rqzPvKdevWobKyEsOHD09ey83NxeDBg7FkyZIgiuuaULf8jxw5EiNHjjS8p9dSA8ATTzyBkpISPPXUU7jyyisBAFdccUUyTpcuXXD77bejV69eWL9+PcrLy7Fv3z5cd911uPvuu3HZZZclw/bo0cPHmhG1A3J7oJTfHVhd1k/bXo0OyjIKLztvv3GyRcbNBNOveng9iMkLTrcVadG+807LoVdCyFZ+12XlIBeNt98n6qpT/ArqMVrNF8nL7BmGMVGmnPEHq62PQfVxRvjlDsbJoVxWh9QZtY3Zd6ENa7Q1XfR7RL2/SjORrZSiz0U/dhCZKIkg451w03/p85Vx0IpXtPIlPzsLhieFwd23ZCVDrd4TOzcJTvIMSyGbabLGj51KcUGGnImLElZvuWk1Rm7UtwRQJiNkHL4pe96XiVg9B7O2dvLsnH6HIuOKTHxWVVWpBzfm5uYiNzfXc7rXXXcdjjjiCLRq1Qrvv/8+Jk+ejHXr1uGxxx4zDF9ZWQkAKCkpSbleUlKCr7/+2nN5/CSyh1K50VJXV1dj1qxZ6Nq1Kzp27AgA+PDDD7Fp0yZkZWWhT58+aN++PUaOHBkLB7dRJSqr0XaWRKITYBGLEKd4sYCRidmgQ9t2YZdRJchyGK1UmvmJcqpgNaqH1y3aKm5W6P1uV5HtWX5uh/UC5QzRImuCK1NGatOx+o6sFj/0k1z1t4wJr5WMMcOvPslKwe8nTiyhnSqArZRWdmnpy6VPy+z5y+6r9QoZp3FEw0dVzgCZIWvioiD0G6Nxnkw3OH72Z24W0Y3wIluiMichYhjJGac7fdzEcWK4pU/bKE7c37vtu2uxrdrZ3/bdtQCAjh07oqioKPl35513muYzderURgdN6f8++OADAMCECRMwePBgHH744bj88svxyCOPYObMmfjhhx8s65JIJFJ+K4rS6FrUiKxC1UpLrd5Tefjhh9GiRQu0aNECr7zyChYuXIicnP0fxldffQVg/wtw880349///jdatWqFwYMHY9u2bab519bWoqqqKuWPRJOoD+KMJkBmgsDvunjdzurHxNErRhMprSLUrT9TozgyJmuylKki6dgpY5z6PTQj6t+gGZkoZ9wOdL3k5xQZlj9m2zLNBu5+THDdKFZFt6Rp/Va6Qa9UdbM9U6T/MGtXo3o6ccsgCxlbHt3k6Uc8GVuR3co4vayRla5R+nEkTFnD+Yw77L4dqwVyK6WqDFkju78yGitGdXHCC0btZdSOIoYRmYrV2CqueDFASYf3YuPGjdixY0fyb/LkyaZhr7nmGnz++eeWfz179jSMe/TRRwMA1q5da3i/tLQUABrJxK1btzaSnVEjsgpVFREt9YUXXogVK1Zg8eLFqKiowDnnnIOamhoAQEPD/knCTTfdhDPPPDPpnyiRSOCf//ynab533nlnirZeXR3OZMK0dAszzTAG8lFrizAFhVX7h326r5WyQCSuWfwghXO6DpydEHc5o92qZqY09OOd0uclY7tcuvS3WrxuS3ez7VqPlcWQE2sio7L43X/4+d6aEZWdOE5xOrkTVRrJwO498WvxIUqEIWs4nzEmqPfGiSGCGVbvuZdvwE1cNxbnWpws3jkpn1Xfp03HagHN6FrclWUyMRpnhl0Wr+EyVYmqpbCwMOXPart/cXExDjroIMu/vLw8w7grVqwAALRv397wfteuXVFaWoqFCxcmr9XV1WHx4sU45phjPNTQfyKrUHWipS4qKkJFRQUGDRqE5557DqtXr8a8efMA/PTQDjnkkGT43NxcdOvWDRs2bDDNf/LkySna+o0bN0qpFyFm6FevRbcxiIRRw4kqIN0KiTCUtkEpVYPwubNnb4OlcsNvf4FGbSm6cmukTIv6ZDcd5IzIc4njoC+I90ZG23gpp933YTbxdGtNofYtZnUWnejalTunoc60X3azpU8UfdpuJ8Z22+r97teMyi0LL8qdIGRtnBZinBCmrOF8xhzRxW8396KMkz7MKKx+Id5pO9jJGn2eUf++0xG98pTsh20hxtKlS3H//ffjo48+wrp16/CPf/wDV155JU499VR06tQpGe6ggw5KyrdEIoHx48dj2rRpmDdvHj777DOMHTsWzZo1i/xh8pFVqHrRUiuKgtra/X4h+vbti9zcXKxZsyZ5f+/evVi/fj06d+5smkZubm4jjX0mEnWFiEyiWle32yLN0E6KZKYrA9kTNifpRfHZi2JXz6CerQwLxSBJNznj9Dl7sbAmjdtpz96G5J9RWKuFBvW3Pq76W29Ro59s1mXlpExyvbrpsFO+GpVdlCD7I7VssnariO6Y0D9P/b9ucbLgqpbHSsHtxiWOlbLcTAEtEt8rUe63wpQ1nM80Jqp9lhGy32sn6XlVasp2zxJkPMC8/FGYL9lhNhYRwcplBSEi5Obm4tlnn8WQIUNwyCGH4He/+x3GjRuHp59+OiXcmjVrsGPHjuTvSZMmYfz48bj66qvRr18/bNq0CQsWLEBBgf3hp2HSNMzMd+3aleJHYd26dfjoo4/QunVrdOrUKamlrqioQEVFBaZNm5aipf7qq6/w7LPPYvjw4Wjbti02bdqE6dOnIz8/H6NGjQKw34z5qquuwpQpU9CxY0d07twZd999NwDg7LPPDr7SMSIoX2LspO2FtpeBRBjWpjLRtkFUymSF2aTSDO1p3XrrVJkKSiPFgmib2lnOiuQd1rOjnDEmDspUmcqwoNFOZNx8O14VbyKYyRerfsjot9P8gsRpf+w3fp58LQt9f62VUXao7e30WUfpGbmFsoaEich3Z7fTSuaYU6uU06Yl48AqveyK4xjBb/KzswIZR0QJvgfR4YgjjsCyZctswymKkvI7kUhg6tSpmDp1qk8l84dQFaoffPABhg4dmvw9ceJEAMCYMWMwe/ZsTJo0CXv27MHVV1+N7du3o3///ila6ry8PLz99tuYMWMGtm/fjpKSEgwaNAhLlixBu3btkunefffdaNq0KS6++GLs2bMH/fv3xxtvvIFWrVoFW2FiiF8CMWoKOCcDGT1uJ4VO/aMZ5aNOpvxoS329rSZtRvnbTfKUnOaNrGHM2tHKiscsf69o87N6xmo7md2XceBHTkOdaTqiA2Crtg2LTJIzMvq8qCmg4oJ+4iLyzegtKPWTTreTIaMt43bP1Ki8Ru+SH/5Mg4hv9W24eedF89Uf/iUS1+q+k10lInIhSP/ZdnLGKo7IMwp7vJdJsiZdCPudkYmoCzC38j2ObSXDECGO9VaJwwKeLPx+TnF+D4j/JBS9apgYUlVVhaKiInyzpTJjt8v4MekQmfiJbjk08p8mWmYzSx2nFqJuwosqlGUIdlWBZzShMbJC0Sr8nJ4I7/a5yUBfT23djJ6NWgZ9fa3aS8WLvzt9+nZWpNp3WnTSraZnlrZduZ1M4J0qVKuqqtCuQyfs2LEjY/tVLaqc2bppg3B7+OFv0ct36dWNiD6+Wd+uJayBrrYcdgpVP7bOm6VtJ8eMymLVL9ph9IzMrBrV62bvmJGVlFV5nbSr1/7La19o13eLPp89extQ1GSfZf5ajOSMnfywslA1erZGcsqo/CJyy+r5W30jlDNiuJEz6YjoOMrquw1C4eZ0/uE1Pbv5kEjaojLGLSJzRVn5eRkbx21xOhOVhm5kihFhyRm1Pz/unlfRNN/ZAum+PdV44/oTKRslEKqFKiFmeLWS8jIxdRLXzuJFprWXSMfuZGueXTpeCGqAKZqPSJsY1dnvbY4y8Zq/qCLDKr4VIsppkkpY75SMPN2mIap0siKsSa7f1iBGCis/rMKdxnUaPlFXjRyTx+jHc3OSppXM1re5mz4tp6HOdV+oli0/OwtwYbwsa7eJXbmtlLFOEbW60+anQllDrHD6HZgp9/3cdu6HQk7WPMdrWLO4ojLey32viI4xRBeDRHFqtOM0XT1hz2vCINPqS+RAhSrxHb87ZCvBYrad0gqzsEFM0GXkYTeBsbJCtYqr3pOltI0CesvUrJqdaMhr7Pg6yEGFX/kYWZAhz/hgHFmDNg5M3BM3ywaZOLVuMbrn1VJWBrLyDaL8XizrjZAlI6x2cchuFzU92ZNWtQ5uZKdeCWo2PomLXA56gu7XAVgkc9B+b1GVyzK/qTDqqC2/k0UtLX6VW1af5URpaZen1W4A9brb8jhJIx2wa0tCRMgc5xrEE147mbos69NxteFEw3ixQtVPnOKO1Qm+WqwmXFk1Oy3T8oJVmkEKbT+ULEbpqPW1OkE5zImePm/9duWwV/+JGHwOcrH7JlU55ne7a+WTUf+in3y6Rdbp7l7iq32km9PmRfMIE/1YI1FXjayanciq2WlYVq0Fq0hdZLWb1z7faMHOa7ncfmd+jmUICQIncsbPRXi/dgzo/4zC6MOGiZ9uhuxkvNs09e1m1+aiZUtXMqmuRD5UqEaMqH3QMhSpZr9lTEq9pGGlVI3Kc9BPCGRNnkTSUid9dogONGSVW/8Omb1TTq111LqK1Bmwr48bZYXIe6ffbhqWUs1pvpzkkijjRImlxezgKBkTItlxRfpmvYLTqj3swmn7CO0uAKN8rfBbaSxTrgLWfWNWzU4kao3luh+T3CD7W9G8RJVF+q38Vm2k3heV34SEgey+xitBKiyd5hOVeZhKFBewRd0OeGnLKNabkKhBhSohJoQtzL0MutzGlTkZ8XPQuGdvg2OrSieEvXUyqAGMH0obKzjZFSOuA1i//L15xc/2NDrFXQQz60S/5Y5V+rL7bLO8zKwz/SxLkFjV20/cLgoEQdjjKULcEvS7G1f5T4gK32GSadCHasSIWicUtfKouPGH6tQRuz4dGej9/1htQTdS6pkp+vTXRRSCahjt5MvIf6hTVD802jL4oaC0UmBo83PqF0dtA7t4suukTU/kXXVyYJYdZm3p9pvZs7ehUZpqu4atrCb+4aWPNSMov1Z8L40R9ZMqqsTT9gNWcdw+DzNZaPUe2eUl69AZte763lZtC30Z7drIDFnvsl/fnts0lZzmpv2LWucGg2uoqXKVH8lsjFyr2Pnytnu3KWe84fd4QJu27IOF4wYXwQgRhwpVIoRsIebEX5dI3qLb9oMUEFaHSMg+9MIMowOozAZ0+omumXJVr6y0w+hEaqvnYOWgXY2vV9aZlcOo3c3erYa8AmkWRHpltewDQ/bsbUBOk/3/17uuEHkmIhN1EYf4RuXS4ufpt+lM2O0lo7+XKTOs3mn9gQJxmfzo+4gwJ9pq3tpDB436By+HUBkt4DnF6p2S3deI9qNO0suFuU9zkf+r6chQumrT84K2PCnK6xy5lrJOvw8qrogfBDV2D5uwxyB6/D4YzM6Pq9YIRv0dhTaKSjlI+FTvqkPTfdmO4uyr4bsjC275J4EjQxjabY00WlmOKkE7XPfDKkhFxuTMa9pG1r9eTgQNe+Ds5F228mer91unPmu7hQcnfl216JWrSk5zQ+UAiQZRfxZe31M/+yY3+OFTWmb6Rt+rDLTpiuyscHOgoZVvbSvsDry08/1pJmeC+Lb8dicgY4wie6yjyhjtYXF+vbeEaNEf8BP1eYYIVudKhElQh0ASQohbaKFKYkPcV+Kium3VzLWAfiJrlbb+2VgdRmb02yxNt9hZtOkn27nYb5XVAPmWLVk1Oy1dKTjNL6ehDsjOSd3b6BEZK+5mh/MAxlbK+6lxnV8mIGKZb+U2RBQj5ZNsC1NZChm7tIys271i1MZ6i0iv+ci2YvcTo3J6fcZu624lW4zkkt+KdztUOeMHWTU7Ue/SitiJexs/XQGItL/WpYyRexm1jE7SJISY9wNh7TZy8u2K9PVux0t6K1Xtv2HNS6NSDkIILVRJwGRqh6/WW3/Cp5f2CGqSIGrxEadJi4i/Wjvs6uv0xGG/LM1E03RriWqFVskalKVWuhBUX+nnVjqzZy5iyRfHd8WptZJfhwdp0/VzRwKQ+tyCsuI1y8doUUd08c5p2bVWkUaIvgdBtZl2O75dXNFyh/mNap+1lZyJYz9CMpeg3lcvi69hf/tG6OtjVj8/rIm18k+0bbRh3cofkWvEP9jeRAsVqsQ3RAVcVBGdlALOO1a9YtUtXjp0ff5+DZSsLBeNcPqeOElftM3t2sDovlW5zU61FlVo+Hkitsi76JflKgkHt9+4SP9gZ+Eics/KdYUMOWJVD9G20U/MnChRzb43rzJBX3aj9JzINS+YnTgfFTnjJn+zPETTcuPyxOpbUPGy3d/J9yRbzojIHtE89+xtoKwhaYvVYp3bvlT0209HxZFfSlXtb6djDL1iVkY5iBz0i3R+LSKT+EKFKvFMUIrSOCtk/QhvR1AdvdUkRr0ne6KjfRfMTqh3g/4U4TCFpduVdD/9eVmt+ruhhhPgSOFksub02zBSPkbJ0iVKZXFL3GSkH4jKGr8n1HqMfEqHhZGS1s34w0jWGLWDWyW+mVLeDipWSdQRkTVmY7mg+3nKlf24GVs7nU/IdlHkNnzYYyER692ojNmiarVNgoUKVeIZ0Qm3zM4miI7L6qRdp/GN7okcyOEFO8FvlF/YvoC0+HF4hdV1Mz9EbrcTatu3Ia/AV7cJos9SO3F2aiWtd1uhj5+fnWX6Z0aeRGV4piJbgW61s0B2/6Atu/7/QGMfYfr/u8Fqi3YQqH2/rMNznPi+1F8Lok8S7Zu87tqQubCmov+2nOahtp2dgs9oMuZkgmblo9uubE7Cmb0vIla0WowsVfVxraxZ7WSNH+8CIUGQLgdcySKKbeG2TFE99EuEMJSFdi6UgvxW4vjMSLDwUCpiC536Rw8vk1wvlrNOFQDagyNkY/deGh1WobdAdYKbeG4muqKYKYCNwtiFA4wPxdFfM9tCbKU0Yd8RDF4sJ/TxRdJyEsatmwA9esWq1zqLliWIwbRfFotO0w37YCy1j1EVzkYuA6KGKmv27G0AsnMsZVNdVg5yTKqwZ28DcpoYL0bbvYOqrJH5/PQHsdjtUNCW241yXJUlVnHNDp7R/58Qp7iRKW6xy0dEHgep5KFCKRXZYxtZ8VRkvssydABBflt+o3/2UVGU1+6pw76GbEdx6mvT45lEAS7jkrTAyp9JUINrkXzcWCXJtsgyyz8MoeBG0WpkQWe2kiniV23P3gbTNvbLZYFXzLZmm1n3eEFvjZpVs7ORz75EXbXpc9BfD3vQQbz5t3brhsJrHCMrVf22ML1vKy9uCYJChqWqyPduZgEqy5834EzJrg9r5gfU7SKeFW6slO36MBEZYbaIoZVTbvzu2bWR1/fLqNzqbgf13XH6rZlZqVrJGT1mSifKGeIW0e27YSvtM+n9jnJd9fIsiLLKnBM62f3jxZVAlJ+hWyhniBYqVDMAGR98WFY7fuQRlB+bqGPn60zFalLj9fmITH6NtgI7OY3YDSLpikyArba9yrIksrJU1V8TVZyIKFnMFKtGf0bl4kAkGvjxHMJ+tpnQfxvhVTlq9q3aIWolb5WPmzB63G71NuqPnFiQBYWb99qrnHFaT1XRCogpRe1wImf07z/lDPGC2YKdmSsavmuZiZlS1W6Bzm/076fogrOVnLEyXpIJvyUSN6hQJVI7/SCs0My2WgQxiXabh5+nKas4KZuoNa0eowm700lsTkOdqTWPm3dRVIkQlpLFrB2Bxiu4Mr8bKz91ZhNdq3ZU4yRqq5GotT49XJ+HTCu4TCSqCkI64rcmyLZJh+9L7TNElXBW22K1v53sMND2w2q/pbfGtMPtc6/2sBPCyNLZakHLDfp6iT4rbRi78F7kjFkYQvyCMjAYjHY6RXnBJKrlsiNsgyN+TySuUKGaoZhtmw4rf6v7XspltpomsgLnNA+3GA3+/RIoVum6UcDZob5XqtLVjYLerJxmkyZ9nGqDg6dE4hlNwmVu/Tcrv5kfOqPwRlayibpqy2dlNLnVKz/14Z2kpw+v/T8nuplD1CYUUZ+AucWNtadVHLt7ZtvWte1q1s9aKSWtlGd2dfRqRavPzw1elKHVexuS8dXt/0ayxqwObq2AjcK69X2q/b+ZzBBRpgLG74I2Ta2cURWvetljdNAVIcQdVjuOwiau37d+951IPdzMT8NUklI5SjIFKlRJYER5a2mQnb7dlolMEEBaq1a/BkNeT/rVxq8W8MUqC6v2iOJgVgQzpWpcB8JBIrM/SHefVk4w2+lgh1/PI53w+92y852pV/JG5dR3KxnSPKAyij6bKMkaIwUrIYQQOfjlgzoO48x0HYeRYGkadgFIMOQ0WJ/SZ3kibUB+TM3KKFIGo7hBHVBl17Z2ExMvPs5kWHxqy6Etq/a309PqjdokKH9C+nytJqrJk5k1GJ1ab5RGEJN0sy2c6nUjy18lpzmsVL9Gz9LshOhEXXXynlYpquQ2bxRX+39tWKfvDvkJ+qnyBy87ILzumNDH9ypjzU5F137LRn27VXpW+PHOKDnNDfsUKx/Ufr+7ThWKIgpRrcxIpp+Xk4yrTUNUvpi1g/aZG71jepnhNS9V5lvJH60s0OapHWdk1eyEkts8RYmq5DY3lSNmskhNV5avckKsSHdZaiZniDz8mp+Kpm03R3M6Vkn3b4IQLVSoZihOTvZTwzjdjmCnaNTiZlLrRPgYpS9TWRxlIaP1B6edXBiVQz/50E+O1PtmbSeqqJDRBm4nSvqtqUaT3ERdNZC3//3SKl29KFHVtI3K7eVdtJrkOsHs4Cy9Ul1tAStFqZ0SlQNzku6ki9WD075JRM5oUcPKXnhRy6EdK9gdFuJWphgtzGknskb3teH26IbiXhfrjBSJTp6jaP/s9pkZjTPUfO3kjH5Moi7emZWFsob4SSYpjbg4IReReZTdvSDHGUHMczPpe5LNnp170aTOWfvV1+71qTSZBxWqGY6ZYlI7GZBxqp/TTtIPIRGXCa6VJYlfeVihnexocTJB0yp1tWn6jX4ia1Xeuqwc5EK3HT07mIPORNsxq2an7SS2LisHOZpiq2mrylEvilbthNfsvlF8U7+JdbsdlSXTcLpwJJKeTLRyIioDYRFfnkGibZsw28jsu9d+n0H1y//X3pnHSVGc//8ze8zssOwuC4ssyMJ6IRDiyU8FT6KCRxD1m3hGIRpMXoaveBCPGCMeGDXemsQjuHgmGo98UaOIB0YFFQlEggiiyyFZRA7ZdVn2mvr9sVu91TVV3dU9PTM9u8/79drXznTX8VRVTz1dTz1V5ZaP08SdH+NuNuud/4aV3qmd8HuZ2KPblLxdDWiPFjv+huR29OP1qkrPTc+ImBh1Sc8QBBEm5HG1POlniun7jspTNSzvbNkkDO+IRPcgHBtLEWlF12GkOshzMsTqvqeDTCqF7qyA3A7H0nlWApk/1MyNdMjjdd/XaKLF+FAVHXxCQ2wHk8PBdL95p0GumJcqXzm+6lRpfk38c8uX6J74fVHVPXsyJvorW31Srr2kB/379HIIliiDqk9xGwD6ycsPOrnEfVr9Hr7IkT1TVXpMdTCMeGCM1/KL2wI4vSuqPKP86BkxrpOeEXWHk54xzZMg3FDtv2wSliCCINXnSX5+c/n5TNfe9k56hwiWBQsWIBKJKP8WL16sjTdlypSk8IcddlgGJfcHeagSjph4SLnt0eJ3xs3rfqpel064kW6vq1TS9uq5Jhr2TAceqexBq/J4Up0kHMQgSExDJZ/opSrn67YvEL8uL8kU43J0dasb4AZRdt12Dk6oDBSm+ytHEy2eDR5EOAiTF6kKkwk6Hs7LxF2YyxwUspepvNdyNjEx8MltqvruJW1Z15gY+AD3bXB0HpmqbQXE9nDy5I60NForCmRP1myhm7Rz20pAvi/XiZd9/J10jc4TVvwduG0FQBA6TLeuIgivpGLEM32Hc3sfCvu7oEgq4wuxnGQ8zTxjx45FXV2d7dp1112HN954A6NHj3aMe8IJJ6Cmpsb6Ho2Gv/3IoEr4wsmgl8oy1aCNom5kQ7G4DfD8Ghu9lkMegAPqAYvXtvTjIWQ66PVjnFcNUsX8dGmK9WM6yBXTleuBD/DaBc+aptaEo2xJ6Tc32g7hUOXjVA4ZsW1VsjiFd7ovv8SIdWyybQFhjt+lYrlKLpbTtO8KyghqeoCIaX4teVHEdm03ypv/vr2kLf6Xr+twK5/Yz8j9croNzTrZnHSNiUy6dOU+lX933m7FRW80uz8/os5QbQmk+myKifFVp2dEg3DergbkNX/nOX+i+6Ey2juRi7qGCCepGvTCvPVTuvDidcr/B7nHbC4ZnsNINBpFZWWl9b21tRVz587FtGnTEIlEHOPGYjFb3Fwg+1PhBOFAT1Qi6cJkqXgmEOXws0SxO+HXG8ntd9HUmnAM09Sa0O7Xp7rndW8/k+U0YXkeuwvZnIH307eSx0BmyXZ9h6GfdzJ0enmG01WXXveHlTHtUzPZFipdIv7p7plAyzYJU+g58Y+u7vwsy5YnWnpKu7h5jeru95T6kTHVhSYraMW/VOmp7REEc+fOxZYtWzBlyhTXsAsWLMBuu+2GYcOGYerUqdi8eXP6BUwR8lAl0kKQxsvuOksUdLnc0nM65IF7sviRx2scUQ4vnkJu+XhRdCb5pnKoBv8sDlzFcqs8kpyWqfL9WLl3qugFzvPRtb94wAvHqyE3iGWoXE5eD4miEqCFjKpOePXyCpO3arq8f3JBH5is0lDdT6fnZKp1ZuzJ2vn7Vu176cWQJ9dhKnpGlEHEz7Nk8jv0WlZVHy3Dl8CrVhzY+lThv+netToiLY1AUbDepYD+EK6g9EwC9iX/Ie8uiAyQyso5whu6flXVBmHX5UHip/zdtX6Ceo9TbbdjGl68pgtrcq07UF9fb/sei8UQi8UCzWP27NmYMGECqqqqHMOdeOKJ+PGPf4yhQ4eitrYW1113HX7wgx9gyZIlgcsUJOShmoP43ZO0p5Et5e320mZywrHb8myvmBwO5HRPNcunm/FTHRghD+xSNRz43QfWbb9VP/A60A2Ktcv3O+skiGdSNr5yTMsoDmzlw1VM5QvyhOqeTjo8N7qjHgiqTGHwOPRKqnrGb7pe8XI4naq/Ea+JKxq8HHjnty5M917NNKnoT6fDJ/nEHYCkrWV4vmJYrida8qJWO8t14mQk9XrQI2CuZxJFJbS1DGEjaG+1nkAqZykQztAz6Izp79SLQVS+3p3aoLmpBbt2evtrbuoof1VVFcrKyqy/3/3ud9p8Zs6cqT1siv99/PHHtjhfffUV5s2bhwsvvNC1HGeeeSZOPvlkjBo1ChMnTsSrr76K1atX45VXXkmtgtIMeagSjnjdw8QLbjPG8v2gjKMmm1TzvNPt8eV3ls5PffvZkzWde/952TMu1dN8xb3edMbqdCtWr15LqRC0B2qQ+xKJsGivQNIhzMgF785sEXTdqNKS8wjSa8qpf3HzXtfhVzavE3cqI6qffFTlT9WY6uVQK/5ZnmTzgtte1iYTslzmMGyzIKMqmzhJC7gfSmay3zfhnzCtdCDCgUoX0PPhn2zWXa69B6ZiVA0qfHdnw4YNKC0ttb47eYJOmzYNZ511lmN61dXVtu81NTXo168fTjnlFM+yDRw4EEOHDsXnn3/uOW4mIYNqDpHJDsDvAUDpIpMzopmsZ3nQ4NW7UNdO4nWnl2O3dnab4fNz2IefQaZXg63p85up50rnTeUkoyibbusAk4FPOsqoe05NB7pWPeyqdw5I+CLXXpg5JpNd6co3nV6qbr9T099xEJNvQR/cIKdhOlFmdChg53JzP4ZBL/pCTF8Vz5f+idq/A6mdUqy6J6bpNOkYhpU5XtAZ2HV5yOHlrRFYtD0w2bojJntk5qI+IVIj3e+OPRG/7xqm2wgFWb9e9E8m5CHSR2lpqc2g6kRFRQUqKiqM02aMoaamBueffz4KCws9y7Z161Zs2LABAwcO9Bw3k9AUbxaRl0+L/03i6tIyxc8eb25ymOInXlAds2qptZ+0U/H+CPpFxeteizqcTgQW/8SwfuohiGfPDybpigd7OA00nAwTftojb1eD46Ei/F7ergbHE5WDgi//lNtdFc4pDRHddhYE4Vf3BUnQv6OweAgGPchSffYazuT0+VwYjHl5ZsRVL3J/H4ZltHKbcPm43F5WCXlZrmmiZzimnqmka8xI5yo0IhyoJtWI7JEtveZVV3mNE0S+RPfjrbfeQm1trXa5//Dhw/Hiiy8CAL777jvMmDEDixYtwtq1a7FgwQJMnDgRFRUVOO200zIptmfIoJolnIx5qs42k4bLbJHJJSVBDnR1A0en5ZfZQB4UybL6qRMnA6CqnH5Odvd7GrxqmWAQ6bgh5qMb0PEypWKUdsLLQDfovU/lU5pzqQ/qCcj9Fb3sBo9Tf+q1zlVp6eKrDl0KAi+/Ybl8JnrGaZIu0tLoOtkkk4qeMTH0esGtDVT7jsrx3TyK3QyHOkOpCalOfuveZ53SDctEBKHGrQ8jnRIOdO/7qjBuW6A5fSfCTyq/SSed7paX6aqCXMRrvfRUZs+ejbFjx2LEiBHK+6tWrcKOHTsAAPn5+Vi+fDkmTZqEYcOGYfLkyRg2bBgWLVqEkpJw74lOS/4JIs2key+z7tihB61s44V5ngyHebsa0C4NUoPYty0bS2B4uWXZ07XM2bSOyJhHuJGtJWPpzDed2wuIpCMPr14runB5uxoCOzAolbbK5UGdrI/EJZhBP79Ozyy/p9MzfvGzL7sK0jPOBN0fiX2E05ZWRHZwGi9kuo3oecgcfldkprIlnBu53ifksuyZ5Omnn3a8zxizPsfjccybNy/dIqUFMqhmCZO9SXThvXRC2e6wVPus6PbydIrvFMYJXdm9vKj7TUO1p5mXMqRj4C23g5i+H8Ov10GxSXj5mfU78PazH20MjZ7y47J6bSeeh9sz5GTEdcpXdZ2nZeKJ4GdpEBEc3IPLb92qPNpy6eUvU0ZHOU/VZz/4nURTtVM2li1bsheZ61+n9xNZz+imtlT15hRezNcU3W9B1ye71b9Ozzj95tzKJOOkZzL521bJoJNJRqXLnOTW1XvQKyoIs0MnTfpHL+8jRObJlPOFSX+Ua+8kYcCtvoKeREs1n0zKGwa6W3kIb5BBtQeQiuJ080xIN34MPG6IL+qpliHVlwIv8fleYwBsA12TeG6YGodFrxH5NOFUjdSmy1j9EE20oKmzu/PjXSUO4sTPsoFSvOd3EsSNRFGJ7UAXp8G22+BTd1+UVVX/uu0UxAGzU3lpgGVGkP2fF0NIGF4MvRqQwjZAc9IzvGx+20CMb9KXpqtuTLcnUl3THaIk6hov6A7u05GK8drJMyddfZvXyVgRtzrlxk6niYBM/rbEdlCV21TPEP6Qn2O/dRy2Prm743eCX5UGkJ2JTYIg/LGrfhvyCps8xUm0egtP6KE9VEOAyT43KtI5QPKadphemsLwAuDVwy9oo7XfeG77uem8d/x44JrKwzFJm3v2qcqv8/RU7XnK/5t4w8h7hoo4eQTIdZkoKkkyBDQKaeuMBLKHlFM9cVllmXXyOxkYVOm4EYbfZi7i9FyLfbYujEwut0OYdE0qBFUO0yXNfvRM0BOacv/KcTOe+jlgyClNVV+cqjHVLU8nWeRJOo6uf5WvBdE+qnxUOsdt5YeTXhG/q/bT1bWDH11DpI6pPiGyj58xpNe0w5YWQRBEWCCDasjJJZd5Ew+oXEY1IHXzwtMZy70MDExeak0PAZIHME7LFcXwqWy3IOfpNug09V4V61cnn+nJwSqjKr/m1Famg0cZp8G7alDJvwe176ATbofpiHXd2JpAo6KcYeqXuis9ebCbqm7JhUNvvOgar+GDmMBz0zOpeJgC6j7Sq2HVTQZZTrF/Mz0ITEwnb1eDUqfya7JOkMui0ye6iTAVovyprO4QdY3qsDCTiTv5sxO6lRBOcXtq/5cJgpzwUX0mUiddRlSTbaEIgiCILsigGgCpLvk2TTMdXoymitjUczVdL0zpVOKmRrdUEAdW2XohMSmfH89aP21uOtBVpW+6JFEMJ55qbDK405WJx1UZEZ3Ce83HK5GWRuWgXSen7rpq4Ayol/jr0shWH9FTUPUhNMjxjtzvm/b/qUwyuaHT+5n8zaT6LJnWo9tEmBzWb56p6nbVpKj47KjS9rLNjsnEXSp4Mary8qmMqU54ld3EeC6imrijPo/INmF4l8mUDEGNXeh3SxBEd4QMqmkg1xWG2/I/P+VLt9I3GTQF4SkJpHdpjRPcAwawy5bqYMYr6Rzg68piWkZV2URjqpf03IymjYJxVfwzwYsxobE1oQzrx1CgktFNZq1xuY1Zf0RukymjXTb6TJPfiCqMKq4unF9MJx+cwsn7Nvvdt1CMw/tMcaJGF1aE14UYX2V41D0HTqtcgvBK5jKo+n83b0gn8nY1IG9XAyLNyc9MJveSNm131UoHWQ+o9KYb8rY6TrrFqjMX47mchpyHn0kRInv43eIsVxCfwUw4aaSbXB/PEgRBZAIyqAZMkMon24osF/dRzfYLGp/FTWW/L69l0O0Nmg74C6LKGzLTRlYdKs/USHOj0Qw7f9k3ybO4s96LC/Nsf2J76E41NpGF3y92aV8/L+3cCGpqAJbxG48IH172Xg0ir3SS7f4/FVLRt350jVtdiQa1bOl23VL5INIMw/uKSFyjO1TX+Z9YBlW5THVDvFN3meBklBblTlVH2LZI6py48zJhSWQe0z2+w/ob9Equy68jEytgumvdEQTRMynItgC5iG6pvKmBxOvLHs8v3S8hXg4zCZsyNFnWptuX0ikNE+8ccdDilIbY7jojqNuBUOJwQkw3VaMqz5ef9qtCNqZGEy1AoZk3lNeTm50OhTJtJ6DDEydvVwNYzB5HVUa57PIAU47jVufygJej2ttOPF1ZvGcyyJVPZm7sLIebEUIcnDY6tLuK4sI8NLW12+KbDsiJzGOqs7xsA5NNdP2y6rAhXZ8j/s5UYXR7eHpdruwXXd8h5htNtKAJBdq+JpX2lL0Y5fcQL3F1hwuaDtzl8slyyP2nm56JF+ahBVHEkL7tG2R4W3nJz1buQvu7l/wuJpeZG8R5L697TiMtjYhGYcnGkdtQpZ/80NSaQEwhg+oZ0R3IFS/Ms54BMV66fouEOWKf010Mp17IxeexJ7UPQRBEOiCDagYI6yDVadmdyvNBFTeTijhd9ag7DCGVWVoTg5YpbnXtZaALdA04ebndjLhOeZvmJ+fNEQdp3EDbAn9LVk0RDYc8T6e2UrWlzoABdD07usNN+DWrzJ2IdcPvi7LK7SbCosU2z1rrfxsDYGbsVA10AW+/u6bWRNLAnxPGPrAnoRro6sKFAXFZaNAyOU1oeI3rhInspnqGb/mSysF0ut8y71e4vDwPcSJM7q9UeKlH13LCv0HCSY5ISyNQFLXCeSGaaDHeQiKq6O5Uk1a6VQxiWgCs9OTv/JroUSw+I6bPTCZXuqSKbFRVkY5+gyDCQqrjIfptELlAqocr9iSav9uOvMImT3ESrbvSJE3PgwyqHulQQkU+42UGE0Xr1QjnJW8vsjgN8tP1QhyUMViML3qDiJ2/zjDt5q2cStlTrbeg6txJDllBmihNbqwzkc/v3lWi4VS1/NJtOaVodJAH33xgy//rPFVt6Rcle9y5lqGNobhQv/fclqZ2VTQrfdmom5R+Z7rxgojr/qk0qCVSxevzo/JeDBsmvwudR6Csa/jvWvd7lXWwl5Uy8uRXqnWpy5P3O9o9aovcT64Psp1b8qJKg6iIaKjk/bobqvch1buYatuahOa7eE38HmnufH5i+tUhYlq68lphikpsk7CNu9psy/uLJX0p7jEuT+ixaDFguEdrR9yE7726xSXmRGbItfrO5feUVPUj0XMJarWN7l3FafUm1+Ve9rgP47scQXByZ0q6G5Kqx5abodILYVGwJnWSrgNUTNJVDfrcBlKpeuyIsGhxktFNdXCIqhxyXBnZC9Okjp28l8XPqrp1OvDFrS2c7jm1h+5EZifvHNWyNdEjiB+uIR+wwcPwP1E20wM/+GDQaZsJoOtAFXEQGyQmz2aj5B1rMqkTln6np5ArdZ4Nb2Y/3opOmB68pEJn/Io0N1qGMlW4VE+0d0Ls30zyMKlPt0MExW1mxLBBTIaq0tDpgXT/blTGVFFvRJq7dAl/Bmz11HlN/BPvucHb1uu7jWqveNN60nnNard9KIgAUOuZVH5rBJGr+OmTckH/E7mD6SFsqgMqvb6rqA64JIiwQAZVn7gt03PaO0gVVnxhz7bCS7fXalgIcsArDnIy0dmLSsXPabwcp73K5Px0p/K6KTjZwKoaaPMymDwrTnvwmWAyOOZL+lWGTF4XVnsLg1hxYCrf4wNb1YBYzkM+JVsHX6YrUt/c5loHKvwYYfkgV07D7XkKa59AEH4J6kVf7teT0mzcnmQkiyZakvoTcfDh5/cm9tMqI6eT7Cp0elX2xjTpH+X05M+6vEQjpVtYE2SjpkpO/tnJA1e+LxpSZb2Bxu0df2J5+DXhHgBbOBVi+qbvEdY7g0+P0SBQ6RkynhJ+II9NoieiXQ0ifReNn6bepJkwepJRlQgbWTWo/vOf/8TEiRMxaNAgRCIR/P3vf7fdZ4xh5syZGDRoEOLxOI455hisWLHCFubnP/859tprL8TjcfTv3x+TJk3CZ599Zt1fsGABIpGI8m/x4sWZKKYj6TRedveXBJ23oZs3nwqTk90dDZjyQEaII3t/qBSO37ZSDboz0e66uuekureT6Pkieg2lsi+tLDP3etIZHMQ2Ej2kxOWUtgFup6FDHAzLA12nQbeM6M1q+vIgDnLFz5ncH082zNpOaw7Yc9YE0jPBkAueAX76PqeJNfmen37NdNWDapl3Uv8u6BjZOKgML8DrxqQdk5bnqbwiU3wWvMbXGfycVkEAqS8T1O716mCIdGoHwLkftHkiy4bSxu1o37EV7Tu22nQQvwag478QVvVeIsutM2LrvFtl+b0cSNjYmrC1k+nkoSodlSwm73LpgnQNQYSbsL/DpBs/73G68GGoy2x6rQbxfkh0H7JqUG1sbMT++++PBx54QHn/9ttvx1133YUHHngAixcvRmVlJY4//ng0NHS99B188MGoqanBypUrMW/ePDDGMH78eLS3d+wTOHbsWNTV1dn+fvazn6G6uhqjR48OpBx+f0ReBn+5Zhw1OdhKhdcDPMT8/JKuTtCPESsdXspu5eMHPPA/WZYgcRtIypjUodGeqsLgNzDFqxmoBhnX1GtIXO4PdBlTZQ9Sfo1fLy7M8zQYBrrahMdT5eEWN5Pkop6hFzNzvNQV1WuwOO2Jmg68rsYw2nPawPiWjsGaqdEvyVjqEjZoTLYMyBZOqyqyYVQlXZNbhK3s6drOjCAI73iZbCeIrB5KdeKJJ+LEE09U3mOM4Z577sG1116L008/HQDw2GOPYcCAAXj66afx85//HABw0UUXWXGqq6tx8803Y//998fatWux1157IRqNorKy0grT2tqKuXPnYtq0aYhEzA0BMqqZiWwYSOV85RPGxbxUhyGYpKki1RMmTdDJwPOWB0u6utDFT8rH5cAjxw20i8u1eej2CuMHGJm2ixPiCfCix45TeI7KyMXTcovvd6DJD/0Q44v1FC/MUx4QJQ+S3OQUvUnlwbhKBhHdSeCJohLkNzd2tTn/L3mPsVgxtD2M9LzIMslDQafDq0TiBRHUN+uNnOJhITZxrGfA2yC0WJGebKDN9mRQruoZ1e83W3WpOqRH17/o9lWWD99R9c+qNL0cImiy77JON6oOBzLNI5posR3Yw7H6q0KHa9LBcyiKIiZ85X16DEB+Z7/BYsVoL63sSq8wiphwaJCTzGI7WnUbFTz7CpPDtpdVWrKIcZtaE2gSXiPjRV39WlNrwvre1JpA466OrUh4n1HRS+oDi6KICjpW3s4k2lleS872zrzbNX2WIItVjs70xa1u5P6Lfy8uVJdLrBOxPvjhTyxabDucsiUv2lG2zudqy077lixRqc3ahTrIixUjr+/gjnTR1f48v0RRCfIA5A/a27oWaW60ZMkvLrc9K7Znt6gcsV3bbbo8qc4V7d24qw1NbQzrvm0CELfJHm9NdNRbe0JaLdF1ECLfkqaiV7nVRnxSl3/mz0pXfKbcyqY0VgAgYW+zdmlyEQVoaM/MUCfXdE1LXhRFSB43ZFtnp4KqDG5jFZP93k30sWr85YewGGsyMc7zittEieukvaxvNenqxhxBkg0HA7n8jodUaurK+H6aaWpNAPllXRf05+36o93+fiNet2QQ7u/K0soIIhxk1aDqRG1tLTZt2oTx48db12KxGI4++mgsXLjQevkQaWxsRE1NDfbYYw9UVVUp0507dy62bNmCKVOm+JYtDArG74E9TnFMXqJSMcIGJYMsh9MgPIg8xQEeYD/tVoVtkKUwwuriuhkHZXn5wC1JVhclZ1rPqnKL353QGicK7dZCJyM138eUy6zKQyWvE5HmRkBj4JaNuE6IA1fLg0djJNWG18CNV3L98fI1F5U71kvHIFOPm0eqaJzXIdeViZdrGF/Ow6xnVGRyvzfdpKHfwanKoKkLKxpYdGGdJs/kQbWbTKZhdLKKk3FcdpWxDug69dyxr5EMk2hPIBottgybolzc+BTtNIbpyiwbcm35F0bV8gpGX7ntefimNpZ0YBDQYQSL82XZCuOabFgEOg1ifIDUDpthjRs4VcY2FXFbWTo88eOFeUBR1Mqbx21qa0e8ICKlpWu7DjlEIysAxDr1ith/c+NgcWGeNfASjYtNbe1APLm/5mnLxlbA/p7QkZe+nxaNpPw5srdxCbCr41NxYVnHgLRdPNhQ/A224evGVmxvagUA7Ghu6zSqdlEeL7T0j3yPs6O5q+75c9PUxoCmZKMrh+cps72pFeXxQgAdeo/XLY/PZfluV9Ajbe+EXdfIfWG69Ixp3xxUPulMK5WxRyr4NfK5TX4nodIVnaiMgekyPqr0qKrfjxdEAjuQ1W86slxOK7iCPjxWhVsbWwbBJN0Qbkz38K5vbkNprMD6n06yrWda6rciUhBzDyjA2prTJE3PI7QG1U2bNgEABgwYYLs+YMAArFu3znbtj3/8I6688ko0NjZi+PDhmD9/PqKyO00ns2fPxoQJE7QvJ5zm5mY0N3c9aPX19X6KkTFMlLjJ4DKVPehU8d0MM15ePkSDWTqWFIr7ZJoYlUS4R4joZWni6aTdn03Imw9kxbpK15JKkbxdDVrv2qAxzYe/xKkMjaq0rH3oAMtbNG9XQ8dQ2cHw3NSaQDTfWRbe5m5YnkvCf5VRVfSasjyvCrsMGTF07eeq9ILrRFzO74Zuf1qT54sbjVT5iMZwkbB5vvRkPeNkfHOKAzgPnJy8LmRPNNN4XmRzum46MATUEwAqr3nrOjc+tttPPu948dd/d4MPcuKFdk9HMY+OMF19hnxfTot/Fj3MuXFUJ5vsDdrYmsDXjR2GrnrFO7lo7OLfRUTjm5VHm31AIhrWxLAmB+/JMpXGCiwjK5eby1QeL7TCi9c4A4oLO+VjlvFVrMviwjy1N2dnnfI4XHY5D9GwKKYtesla5JdZnjgdxtrkMLxtuWF2y8422wBUlIEjGia5cVkOt0P4vq2xBX2L7b+PHc1tKOtsp7Uag+q2xhZsb2pFdZ+4Mt4OTduKz5NYfzyuyujKr+38bpcyzUySTV0ThvGMaoLOFC/9Ng/vZe/9dHoK6vI2ydNNbjcDmJvRSeyXnLaJ8mpoC9IwJ/dbIrKOUemhbGMqk6wLdbrPK7JOdcLvgbZOupnf85u2Dt0kG6DXIZyyNBlWw6BniOwRWoMqR17CwhhLunbuuefi+OOPR11dHe644w6cccYZeP/991FUVGQL99VXX2HevHl49tlnXfP93e9+hxtuuCH1AngkyEM1/KZnil+PM52h0qsxNkjcNt3O29WA9mix0qMyUVTiaW83J08rp0MsVC9gqS69l2WQZRPLnQqWfEVRrQFelYcYT/W8uRp9Ow/myC/r17Uk39AQqkJc9m/S5ipDO98OQEWTYNyw6DSQ8Pzao8VJB3aZvMCKW1uoiBfmJdlS3CZZuFFVNJJ5GZyExWO1O+oZE894I+9LqJe/yQYlOY5bmm7XnYyvAGyGQ3nwLD+DpjLFC/OSnnnR41QVR7dkHBA9IO0DW/m77FGnMixadVxo90ztSkstR1MbQ0U8P0lO0XjKDX/1zW22AaA8kBMH29xb0ckAtvbbJqURjMcrixUk3ZcRjW08nHxNFUdGzEtn7OPx3PJIrqNEh8Eb9ueia2k8bOXk+exobkN1n7gtPf6Ze1w6edbI9+RBuOghLBpHuWF0W2PHc963OGrJxOXh7SeyrbEFmwVhN9c3Y7fSmO0zN7KKYcUw2xqb0bc4ZuXNEeOJ18Tvchxu1HUaXANAU6O6vbNBNnRNtsYzgH8d71ePmN7XhfV6CKpK95jEC8rL1ErPwfAokjxhVCCFF/uarv5DNrw6TQqKxlmVUdeLt2C90CcD9r7dSf8EhawDUsmvLFZgiy/rNR1u/ZsTosHZJE2v5dNNZsn5yPrULR/ZWK5KU0bWD07Ik4FBECY9Q2Se0BpU+R5BmzZtwsCBA63rmzdvTprhLSsrQ1lZGfbZZx8cdthhKC8vx4svvoizzz7bFq6mpgb9+vXDKaec4pr/Nddcg8svv9z6Xl9f7+ptpCLdSzSzsYxWXgquui9OpqsMo27GUp6HXH/cqJSAfemzjFO9yMviVacrtxss6efpx+BsYHNa1q6rB8uLEvp6TsezZTPu8lOEUzBsmxh6VfUjl8upnF49aeVl/37LxtucG0d1S/lNZBOf1S5PMaBjoO7siSEiGrZM9oBy8lA07VfiijzD5omqIxf1jJtnO6CfnFDt82mCzpCquubkGc0951Tp6OKp8nYLywe2JuW0eZNqJgRk46nNgCwMNlXfuSFLHhzwZWiAfYCgCru9qRVbOj0HxXx4+h3GN9Ypm70PqW9ukwa2Ceu6+ApY39yGtd82KY2IXL6hglehaHBTDWS4MW34wBLLuLZbacz2mRvy+EBTrAduLOP/RWOnyjuSww22KoMdT+OLLY02Y91eFcW2tHXoDLVD+8STnhFuxOTlksvpVAaeLs9TZ9h1GqTKxmrZu5QbN3lbDB9Yaou7o7kNC9dsseW3WXK36mjPrmvcWMo/i9fF+B15Jy9N7DC0NlufxfzEtMXvXH7RuCvL2rzzu6S8Mk02dU1Q45l04fSO4jRZbHqgppc0vBo6dRNtcv5eD/+U49vy0BgpOSbGMifP7i5E70LZ07AgyZtVNXEo6ji3yTNduB2SnuR9tPybDxLeN8uy6vptJ70hpyVOZJmiMy5ydAZIUwOprHtNMJnM8puHPBknX+9Kx79bsqhPOKrnSc5TRxj0DJE9QmtQ3WOPPVBZWYn58+fjwAMPBAC0tLTgnXfewW233eYYlzFmW97Cr9XU1OD8889HYaFzxwR07G0Ui6Wno06VdBpQ3dL26kFpiokBxusJv275qbwdObKRNdLc6Nmw6BTea33pwpoYVeX78p5/qvi6uvaSXxBGNZ2B27Qt2ndsRaLhW9u1/OLyjnSlPfA4/OVXdXiNX2yyGjzH/CU0XlCIptYEyvLbbAbuxkSHkVa33N4Jk4PadP2A04FD8mfZuJfuLTv8kCt6RvYUzQROS8ad9glTGUrlpea2fKRlzmK8IOBLr1WGXJM8VINhJ29PefApetFwYx9HNnQBHQMg1SCoK92OfETPR9Foq1pabl92p/ZoVHkAiTLJA9213zYleSyKgxvVdZXxbfjAEsvAyOOIRjUeTmcsk5FlEuOInpJiGD6w/ayuIUk2Ed2ycrHeRUP22m+b8MWWRltYUT7Zq1Msg+ixqRt4y+HEQajKCC3Wb+3GBuza2YKmhhZsLYnaZOHheZiiXh157NrZ0bfz77UNCkN6SUcejYp7PD4AbP3aPvgs6hVFLTrqv7hTHpHGhhZgd1j1Jtaf6vkSw7U1pbaCJwiyqWuCHs+4OVV4wY8xVaczHPMRdJasr7zoGrdJPVVY+TNHl4YfL1RZh6jw6+ko6ywAtkk8nUxieK7X+GSNbqJINvqqjKiqyRovyIY0OQ1xMkeld0wNbHI8OT8uh86IJ15XGSBlr36d178KOaxOjyfnqdbDfFLLC0758LQ+q7OvcBBx0zEcrq+S8ihxniCUZXEjDHqGyB5ZNah+9913WLNmjfW9trYWy5YtQ9++fTFkyBBceumluOWWW7DPPvtgn332wS233IJevXrhnHPOAQB8+eWXeOaZZzB+/Hj0798fGzduxG233YZ4PI6TTjrJltdbb72F2tpaXHjhhRktYy6TyQNQcgW3U1CzYSgS99cMlMbttoOWUjHku3mRBllvTh7BTkQTLWhCgdGLsiWvYBzVLeOXy+Zli4imNoZid7scAHQduhIwYVmW75dc1DPRRIvNSC22q5t3qvxZDsOixcrTicW0eZ4qD+jG1oTSU1IMI6PzSgX0e/7yMns5LE7egoJfczLyOqXfUR/q3xSXV16en46DD/iek7JBNMj0VcieQXI42QAqwgc720qbkwaHdkNYl14QPRmdBjfbGt09k5wGa7K3Y8e15N+VyTVx0Krbs5DXk5NhVHfNbTCnMzSow9rvNzW0YNfOFsRLomhsaMFm2I203OBa1CtqDVT5dxWqwawbTQ12Iy3Q9ewUl3RdEz+rcPJWa/wuM++xuaprAHM9b6JngK73Hrf0nfpfeTLOiiPoH5W+cYsj5+EFL+FV8pvEF8OI8XVL6DOF2P97WbYvG0lVn2VPe/G7qi/UGfOcJt74PZN+kuuHZMNmsu5QpSl66qvCi+jKovPS7Mqzq19T9X/y9inyNTlvVTmS81SXU6enTAzebjpOdd/UmCpfd9IzJs+QjsaGFqT5zCsi5GS1+T/++GOMGzfO+s6XpEyePBlz5szBlVdeiaamJlx88cXYvn07Dj30ULz++usoKel4AS8qKsK7776Le+65B9u3b8eAAQNw1FFHYeHChdhtt91sec2ePRtjx47FiBEjMlfAbojOWCUOYGUDUlDGMq97laaSvngoVQIdQ2qncvBwTvcjLY2uL61y/WbVk8/h1HqvpHK4lSquab3kl/Wz/Q9CHjmddDyTfDmwOAjQHWYFOL+kZ9KrUUTXRpl+pruTnpG9f/2g8u5WbbEhG3IBKA8h4wZ/lTHTL+LWESo5+KFnuntimVryosrJBvGaKLt8OKFYXqVHeJJBWNQEHa9Y4oE/HP65PF5oDR7lJXvco7UsVmCF5/k5pSl/5gNx3X0dsketKN+O5jbLg1Ncvm0NQDq9CYcPLEXfYvtApW9x1+BPTJMvOxfvc/iAsGOpfrJXpygjDyPTNaiM2a6VxwttcvC8+VYA4vJ71bJKsW26tnwoQFmsAH2Lo1Yedvnsyz7lA7zE7zy+vP+hGE4uM48j7tvH63dzfTOwe8dAcuvX36HfgN6d3qkxq8wA0G9Ab2CA5CE0QD/Ad0M5OO1c7a5KUzZEcGOD6rr8jHXE77i2qbAVH/qS2Bu5pms6+sgi4bOdVPUMkGxYlVH14RzdoZecoN5tvKRjephik6Enq9uEoTwZ2fVOqO+/5X5bB98WRNfHyzpCvicfpqeTyUQele6TP/N+U/y9c1RGS9Ml3U6IekanV5zStfdHXfKr0ne6JiPrC1Ucla6St1OQDa3yntjyZxVi3rLB1q2+Vf25CdtK1YZONwOoiZ4xvSfLUxxpxVtGoYnuSIQxlr3prhyivr4eZWVl2LxxPYr6VCjDuHn9uGHqESovRfZ6KJWcjyo+T9fpJYtFix0PWOJhnfZP1dWRaklRpKXR5unI91DVLc3m8uuWh4t5y0v820srrXg83/bSSlscWXaTfWGbO5eZ88F7bNd2Zf3wcqr2PFTN+IvldGsTuQy6NraW25dWamXgYYGu58HpkK1maZm9SjZd2rLsAJBfv8lmHJWfl/wdm+yeto3bwfoORqKoRLkHLz+dGYBnr0Brf99OeeQ2VMXhMssnkW9p6vB6ixdEUNGrANFEC/LrO04Jbi+txI725BdXP0v9RUxOfXfqT7z2dwCw5btdGDywEjt27EBpaal7hG6OqGd09eE0yBWfQZWh381L3G0pp5uucdNhXrydTXSULg9dn6fLR9WXAurfJqA+uIRf27KzzTYIVi015QNQcXk4kHxarrhUn580z9MW+wgxTVXeukOpVMvUReR9XsU9VPmSdhHVHml7VRQnDdhFw6A4qJc9Yvl10ejMw3g9lMoJ3QnzsqFbZxQY2ieurGPx4C6nvU6dcDuAS5UmT9dpL0JxH1W+pULf4iiqhTZ+beVmAMlLLgM1qHaiHugGszriv5u34eZJB5Oe6UTUM2VF+QCS+/xUDzrV4WVCVfW+zTF5n/GDm97JBk7b79jCGSzBF1EdaCdPxKnSFe8p5XXY41XUKXJ+unC6A6n8otqj3Om+fJhUqiQfDOZOUHpCFU+Frn69yOxEKu0H6PdgVekYN32Vqp7hssTRjCuO2y/jeob35wXfPxeRfG9lYe0taFv+FOnGACAHZcIzXl6IVGFN4uvCcINAOr3cVHkE4dEopscH307l9FrGsOxLKeN3Cb4JOmOqDdHTtvOzU1359XqQnxHxu2jkMakP1TJolZHM5OApIveItOxEpCXfNZzOO9rtuqo/Uy3llJ/VqMO7WqSl0XXrEaf4OnnkLQrcJsqcDioU44u/SccJE+EAQ1Xf4OT52oFqz9YOzyt+gFS8IHmQIl6LFxQmb4mQtOxVtbTUnrd9v8CEYgsH+ythvCDSsY9zp3erfRBdYBnf+OBIHNDxgVdZrCBpoCd+F420qvuiYZCn63QCsBhGdV2UV+cRLN/jg37ZGMCvqfrrxtaEzQtZjG9SBllmk3Cy7Dq5eZ12DCRLrDj8Og8/Zs++SV6wXmSSEb1fOU7GBadlwF6ItffyFa+7E2nZaR3QaTJR5wdZ13h5F4xGu8LH0Jg0Ye6EHN4PQWx5ZjoZ6GS8NVkp0oHkPSvpFae9z1U6SL3qQr6nQvU+WmDTM3qDrLgSQ+0hy1dtBIUuLZWXrMr4amIcFNPSrUhJBb9pyZ6uHNP61eXrVieptJ9upQig1jFupPoscVkKW7OzGpAIB2RQJXIGN0OU1nvOYBCvOjjHNF85jVRJpwHSiwymJjq3rRDcwqSSvlMYFi1W7msa1HJ/nofJPmJe7jsZdLnsumXORPcmqO0lTNJJFJUkPds6j2xjuVz2UlYhb4EiepCa9pOiDpCNqLJhVk7T1BPKCldoN8Dq9nVV4bT80+k3rkpbHHQ75V2sMf7a76mWrybAXyFV2weoPJ6UsncOrOMFhcZ78qmX2Hchb2+giy/LIMdTDfqdDQ/ytYRlkBbL6ZaP7D3s5A0mxnFKU67f+uY2VPeJ2wymdqN5h8Fc9FitVhi/U8UpTZ3HtleibU3ugQiLILcxcktL1geiXhFXSgEwOtDTlran0OZ4eZ81Ncp6WcnopD8A/QS76X78Ju+TqjBO2xyIeTvLkUjSO7zP5QbhdOxTbooqb6/y+JHfTR/wujHRFXKcVOTSkWpaOi/megdjaiq4yavSP1xGLk9jQ2pet92RWbNm4ZVXXsGyZcsQjUbx7bffJoVZv349fvnLX+Ktt95CPB7HOeecgzvuuANRB+NNc3MzZsyYgb/85S9oamrCscceiz/+8Y8YPHhwGkvjDBlUQ4QXxRuWpSiZJt1emE77PmayztNdzlw5bMyPQVIkSOOpXxn8xFG9rIbB0A7QYXWZIK/5O+TtCiYt3b678p688uSD20CYx83XpK/Dj+k/ofCicvK2lXH73Zjc1xld+Tsfv6Z6B4zmQzu6j4qOyAnpeyfK31yhPSN571j5vhhG/ux0zem+08BYd9iYE6YDfrc4ftJJJZ5bvcnpuuVjbnzwFk4Mw9tngBSRt1dxobfBebqRvbRNTmfny6L7+23Ybk6QegbQ6xoRUz3Dr5ukqcOrrpEnB3W6JZ3vYbqtF9z2ohXhOsRtezftlluyrlLoEhVB7p+ugn7G+joISndmm669gtXC6a4Hhe6QO7dVRADQkAhhhWaZlpYW/PjHP8aYMWMwe/bspPvt7e04+eST0b9/f7z33nvYunUrJk+eDMYY7r//fm26l156KV566SX89a9/Rb9+/XDFFVfghz/8IZYsWYL8fPfVfemADKo+MTFqejE6eDVS+Nk71Y9cTgRtYCRDTbhwM/plq7285CkeLhYk2Sp7WLd1INJHKgNKL+l6yqdxu/98xT2NFai8yp2Mu6betqqBsolR1s0b1smLNyhUWym4rbwIsn+yjLyJ5GtOp3f3dMJcB3690MKCF/mjbTTUMSFduialPFLRNQ73TPSMV09dU4OsE6Z6xgRZb7htyaO772WrniCRJxd7qiNRTyKMOsdUJtIzydxwww0AgDlz5ijvv/766/j000+xYcMGDBo0CABw5513YsqUKZg1a5ZyX9cdO3Zg9uzZeOKJJ3DccccBAJ588klUVVXhjTfewIQJE9JTGBeo9T3SkhftPBMz2DRV370eUGUS1m1/Oa/4PYxGFT9oUjE6u6WbSny/mNaV38NcTNMNqr0yVX86I6TJXouZwosXgXxPd2CZ6rOYh+pkd51cJvtNut0LIjzR/XHymvWLyUA51YFwpknHRJEfvP6GVXvYyvf4Z1U+8vuGKo6cviqOKU7vOCYH8nk5qM1JPtU+wk6HB5q8+3ipS9P4uvREnOrNzzuOTkZ+j/SMO5kwpnomBWOqG9nSMyK5oGfChB9d4xTP7QBLpz5KpcOMPYA1n1XpiddV4VQ6z7Qf1tWTKh2dvE5lVdWhU3+tS1tOx088Jx2nk1OVl9s7BuGNRYsWYdSoUZYxFQAmTJiA5uZmLFmyBOPGjUuKs2TJErS2tmL8+PHWtUGDBmHUqFFYuHAhGVSJcBKkJ56J4dUkP7HjMunETAZuug5Wl49OkabjxT0oo3kqabi9OJima5oXkJph09SI6DU91bPn9EKmum8aJt0EUR/i93Tl1dMJarAHeFuS6Ri2uNw+2FV9NyTI8gH+B6m5NrgNgzGVIIjuQVD9sKlhNhA9w695yC8ock1f+CVX9QwZuIgeR3srmHuopDgAUF9fb7sci8UQi8WCkcuBTZs2YcCAAbZr5eXliEaj2LRpkzZONBpFebm97x8wYIA2TiYgg2oPhIwbBEEQ4SUR6+3tsCdDvAwqncJGmhuTB7JpNKKKS/R7ykBWR64OcAmCCBfp0DNe+3a38EnL9tM8WSfWR0/WNaRnCCI3iEajqKysxKZPn/UVv3fv3qiqqrJdu/766zFz5kxl+JkzZ1pL+XUsXrwYo0ePNso/EknenIUxprzuhJ84QUIG1RDjtDSOIAiC6N4EOaDL5qDZCS9lzNYAV3dQiFt4+UARgiCIsJEtPWNizA1K1+SingGcdY3qoETSNQTRsygqKkJtbS1aWvzZiVSGSCfv1GnTpuGss85yTLO6utoo78rKSnz44Ye2a9u3b0dra2uS56oYp6WlBdu3b7d5qW7evBljx441yjcdkEE15NCyBYIgCCJVgh4kynuOygNjfi3Tg9NMDChN86DBLUEQPQmv/b1b+J6sZ7zkQ7qGIHouRUVFKCoK+oQfNRUVFaioqAgkrTFjxmDWrFmoq6vDwIEDAXQcVBWLxXDwwQcr4xx88MEoLCzE/PnzccYZZwAA6urq8J///Ae33357IHL5gQyqISWdhzURBEEQ4YVFewU6QErHyfPyAFY1oDUZ5NJAkCAIIvOQniEIgiDSxfr167Ft2zasX78e7e3tWLZsGQBg7733Ru/evTF+/HiMHDkS5513Hn7/+99j27ZtmDFjBqZOnYrS0lIAwMaNG3Hsscfi8ccfxyGHHIKysjJceOGFuOKKK9CvXz/07dsXM2bMwPe//30cd9xxWSsrGVRDgOpUP36dG1VNDuohIyxBEAQhQ4NJgiAIIp2QniEIgiA4v/3tb/HYY49Z3w888EAAwNtvv41jjjkG+fn5eOWVV3DxxRfj8MMPRzwexznnnIM77rjDitPa2opVq1Zh586d1rW7774bBQUFOOOMM9DU1IRjjz0Wc+bMQX5+fuYKJ0EGVR+kaz/TdBtDaR9WgiAIgiAIgiAIgiAIIh3MmTMHc+bMcQwzZMgQvPzyy9r71dXVYIzZrhUVFeH+++/H/fffH4SYgZCXbQF6AmHyGg2TLARBEIR/xP7ctG/Plg5oyYsq83aSR4yji+81P12ebtfk9Ny+m8roFacyqf5M09Bdk9vAi1z0vkEQ3Rs//V4mMOmzMiWD+N1r32yqN03aISh941V+t/RN3mNUulYXL4zPI0EQ3RsyqBIEQRAEQRAEQRAEQRAEQRhCBtUchGbfCIIgCIIgCIIgCIIgCCI7kEGVIAiCIAiCIAiCIAiCIAjCEDKoEgRBEARBEARBEARBEARBGEIG1ZARTbRkWwSCIAiCIAiCIAiCIAiCIDQUZFsAwn1P1GiiJSmMbHjl98kgSxAEQRAEQRBEtmjJi9KYhCAIguj2kIdqN4IOqyIIgiBShXQJQRAEkU5kPeOkd8R7pJ8IgiCIMEEGVYIgCILoIZDHEEEQBEEQBEEQROrQkn9DGGMAgIaGBmtA6rYMn+O27EVMR7WUX1zyzz/7XfKvCqeTzy1NlWxe804lHRkvZRDLLH9WpSdfl+vMr+wmxg1d26tkVcnl9uw51Y3qmsnz6lQOMa6uHuUyyfHcMC2XUzydvDK636IcT1dOOQ2T8srPhBxW93yr4quQ7zs9V07Pgyq8SENDA4Cu/rWnI+oZE9za2S/pWKpp0hc7xfG6rY1T+FT6PdPvpjJ6rWc3fS2TavnFdNzaykudetEzYjmc+iY3XalL2wmnZ8/k3cXP+5+bnpHzdZJZd1/Mx6QuTePr0hNxqjeTtjGpC/EZID1jx6uecSLVZ9/0fdWrrnPqZzKFl/c+tzhufauJ/glK33hpc9P+z7TPEOPo4pmOGUx1npyG7tlyy9dp3KlLT7yuCqfSeaZ1KsutkkdOW3VfV1ZVHTr117q05XT8xHN7TlRyqvJyqhPSMz0bMqgasnXrVgDAiGH7ZFkSgiCI7sXWrVtRVlaWbTGyDtczew3/XpYlIQiC6F6QnumA9AxBEER6ID3TMyGDqiF9+/YFAKxfvz5nfyj19fWoqqrChg0bUFpamm1xPJPr8gNUhrBAZQgHO3bswJAhQ6z+tadDeiYcUBmyT67LD1AZwgLpGTukZ8IBlSEcUBmyT67LD5Ce6emQQdWQvLyO7WbLyspy9sfOKS0tzeky5Lr8AJUhLFAZwgHvX3s6pGfCBZUh++S6/ACVISyQnumA9Ey4oDKEAypD9sl1+QHSMz0VanWCIAiCIAiCIAiCIAiCIAhDyKBKEARBEARBEARBEARBEARhCBlUDYnFYrj++usRi8WyLYpvcr0MuS4/QGUIC1SGcNAdyhAk3aE+qAzhINfLkOvyA1SGsNAdyhAk3aE+qAzhgMoQDnK9DLkuP9A9ykD4J8IYY9kWgiAIgiAIgiAIgiAIgiAIIhcgD1WCIAiCIAiCIAiCIAiCIAhDyKBKEARBEARBEARBEARBEARhCBlUCYIgCIIgCIIgCIIgCIIgDCGDKkEQBEEQBEEQBEEQBEEQhCFkUHVhwYIFiEQiyr/Fixdb4davX4+JEyeiuLgYFRUVuOSSS9DS0pJFye288sorOPTQQxGPx1FRUYHTTz/ddl9VvgcffDBL0qpxK0PY26C6ujqpjq+++mpbmLC3g0kZwt4OnObmZhxwwAGIRCJYtmyZ7V7Y24HjVIawt8Mpp5yCIUOGoKioCAMHDsR5552H//73v7YwudIOqdJd9AxAuibbkJ4JF6RnsgvpmS5Iz4SrTXNZzwCka8IE6ZnsQnqGKMi2AGFn7NixqKurs1277rrr8MYbb2D06NEAgPb2dpx88sno378/3nvvPWzduhWTJ08GYwz3339/NsS28fzzz2Pq1Km45ZZb8IMf/ACMMSxfvjwpXE1NDU444QTre1lZWSbFdMStDGFvA86NN96IqVOnWt979+6dFCbM7QA4lyFX2gEArrzySgwaNAj//ve/lffD3g6Avgy50A7jxo3Dr3/9awwcOBAbN27EjBkz8KMf/QgLFy60hcuFdkiV7qBnANI1YWkH0jPhgfRMdiE90wXpmfC0aXfQMwDpmrBAeia7kJ4hwAhPtLS0sN12243deOON1rV//OMfLC8vj23cuNG69pe//IXFYjG2Y8eObIhp0draynbffXf25z//2TEcAPbiiy9mRiiPmJQhzG3AGTp0KLv77rsdw4S5HRhzL0MutANjHXIOHz6crVixggFgS5cutd0Pezsw5lyGXGkHkf/7v/9jkUiEtbS0WNdyoR3SQa7pGcZI14SlHUjPZL8NOKRnwgfpmS5Iz2SH7qBnGCNdE5Z2ID0TPkjP9Dxoyb9H5s6diy1btmDKlCnWtUWLFmHUqFEYNGiQdW3ChAlobm7GkiVLsiBlF//617+wceNG5OXl4cADD8TAgQNx4oknYsWKFUlhp02bhoqKCvy///f/8OCDDyKRSGRB4mRMyhDmNhC57bbb0K9fPxxwwAGYNWuWcslCWNuB41SGXGiHr7/+GlOnTsUTTzyBXr16acOFuR3cypAL7SCybds2PPXUUxg7diwKCwtt98LcDuki1/QMQLomLO0AkJ4JA6RnwtEOIqRn7JCeyQ7dRc8ApGuyDemZ7LeBDOmZngkt+ffI7NmzMWHCBFRVVVnXNm3ahAEDBtjClZeXIxqNYtOmTZkW0caXX34JAJg5cybuuusuVFdX484778TRRx+N1atXo2/fvgCAm266Ccceeyzi8TjefPNNXHHFFdiyZQt+85vfZFN8AGZlCHMbcKZPn46DDjoI5eXl+Oijj3DNNdegtrYWf/7zn60wYW4HwL0MYW8HxhimTJmCX/ziFxg9ejTWrl2rDBfmdjApQ9jbgXPVVVfhgQcewM6dO3HYYYfh5Zdftt0Pczukk1zTMwDpmrC0A+mZ7LcB6ZlwtAOH9Iwa0jPZoTvoGYB0TbbbgfRM9ttAhPRMDyeb7rHZ5Prrr2cAHP8WL15si7NhwwaWl5fHnnvuOdv1qVOnsvHjxyflUVhYyP7yl79kVf6nnnqKAWAPPfSQFXfXrl2soqKCPfjgg9r077jjDlZaWpoW2dNRhmy0gZcyqHjuuecYALZlyxZt+mFqBxVyGcLeDvfeey8bO3Ysa2trY4wxVltbq1wiIxOmdjApQ9jbgfPNN9+wVatWsddff50dfvjh7KSTTmKJREKbfibaIUhyXc94KQPpmuzrexWkZzJfBtIz4WgHDukZ0jNh+m2FVc94KYMK0jWZlZ/0TLh+C91dzxDO9FgP1WnTpuGss85yDFNdXW37XlNTg379+uGUU06xXa+srMSHH35ou7Z9+3a0trYmzaoEhan8DQ0NAICRI0da12OxGPbcc0+sX79eG/ewww5DfX09vv7665woQzbaAPD3HHEOO+wwAMCaNWvQr18/bZiwtIMKuQxhb4ebb74ZH3zwAWKxmO3e6NGjce655+Kxxx5Txg1TO5iUIeztwKmoqEBFRQWGDRuGESNGoKqqCh988AHGjBmjjJuJdgiSXNczAOmaMOga0jOkZ4KC9AzpGYD0TDrIdT0DkK4Jg64hPUN6hshBsm3RzRUSiQTbY4892BVXXJF0j2+Y/N///te69te//jUUGybv2LGDxWIx2+bnfCN6cXZU5v7772dFRUVs165dmRDTEZMyhLkNdLz00ksMAFu3bp02TJjaQYVchrC3w7p169jy5cutv3nz5jEA7LnnnmMbNmzQxgtTO5iUIeztoGL9+vUMAHv77be1YcLUDukgV/UMY6RrwtIOMqRnMg/pmXC0gwrSM6Rnsk131DOMka7JNKRnst8GOkjP9DzIoGrIG2+8wQCwTz/9NOleW1sbGzVqFDv22GPZv/71L/bGG2+wwYMHs2nTpmVB0mSmT5/Odt99dzZv3jz22WefsQsvvJDttttubNu2bYwxxubOncsefvhhtnz5crZmzRr2yCOPsNLSUnbJJZdkWfIu3MoQ9jZYuHAhu+uuu9jSpUvZl19+yZ555hk2aNAgdsopp1hhwt4OJmUIezvIqJaXhL0dZFRlCHs7fPjhh+z+++9nS5cuZWvXrmVvvfUWO+KII9hee+1lvVzkWjsEQS7rGcZI12Qb0jPZbwMVpGeyA+kZNaRnsk8u6xnGSNeEpR1ESM9kB9IzBGNkUDXm7LPPZmPHjtXeX7duHTv55JNZPB5nffv2ZdOmTQvNrENLSwu74oor2G677cZKSkrYcccdx/7zn/9Y91999VV2wAEHsN69e7NevXqxUaNGsXvuuYe1trZmUWo7bmVgLNxtsGTJEnbooYeysrIyVlRUxPbdd192/fXXs8bGRitM2NvBpAyMhbsdZFTKO+ztIKPbNynM7fDJJ5+wcePGsb59+7JYLMaqq6vZL37xC/bVV19ZYXKtHYIgl/UMY6Rrsg3pmey3gQrSM9mB9Iwa0jPZJ5f1sVSa4gAAFFNJREFUDGOka8LSDiKkZ7ID6RmCMcYijDGWia0FCIIgCIIgCIIgCIIgCIIgcp28bAtAEARBEARBEARBEARBEASRK5BBlSAIgiAIgiAIgiAIgiAIwhAyqBIEQRAEQRAEQRAEQRAEQRhCBlWCIAiCIAiCIAiCIAiCIAhDyKBKEARBEARBEARBEARBEARhCBlUCYIgCIIgCIIgCIIgCIIgDCGDKkEQBEEQBEEQBEEQBEEQhCFkUCW6JdXV1bjnnnus75FIBH//+9+14Y855hhceumlKecbVDoqpkyZglNPPTWlNKqrqxGJRBCJRPDtt99qw82ZMwd9+vRJKa/uBq83qheCIADSMzpIz/iH9AxBENlm7dq1iEQiWLZsmTbMggULXPt4giCIngAZVAnCB7oXiRdeeAE33XST9V0ecIeBG2+8EXV1dSgrK8u2KFlnzpw5iEQiOOGEE2zXv/32W0QiESxYsMC6VldXF7q2JAii+0J6pntAeoYgiFyiqqoKdXV1GDVqVLZFIQiCCD1kUCWIAOnbty9KSkqyLYYjJSUlqKysRCQSybYoaG1tzbYIKCgowJtvvom3337bMVxlZSUZBwiCyDqkZ7xBeoYgCMKMlpYW5Ofno7KyEgUFBdkWhyAIIvSQQZXIOCpvmgMOOAAzZ860vn/77be46KKLMGDAABQVFWHUqFF4+eWXrfsLFy7EUUcdhXg8jqqqKlxyySVobGwMTMYnn3wSo0ePtgaF55xzDjZv3gygYynMuHHjAADl5eWIRCKYMmUKAPtSzGOOOQbr1q3DZZddZi3jA4CZM2figAMOsOV3zz33oLq62vre3t6Oyy+/HH369EG/fv1w5ZVXgjFmi8MYw+23344999wT8Xgc+++/P5577jlf5Z0zZw6GDBmCXr164bTTTsPWrVuTwrz00ks4+OCDUVRUhD333BM33HAD2trarPufffYZjjjiCBQVFWHkyJF44403bEtg+RKiZ599FscccwyKiorw5JNPAgBqamowYsQIFBUVYfjw4fjjH/9oy3vjxo0488wzUV5ejn79+mHSpElYu3atdX/BggU45JBDUFxcjD59+uDwww/HunXrjMpeXFyMn/70p7j66qs91hpBEGGF9AzpGdIzBEH0dBoaGnDuueeiuLgYAwcOxN13323TIdXV1bj55psxZcoUlJWVYerUqcol///4xz8wbNgwxONxjBs3ztY3OtHY2IjS0tIkvfHSSy+huLgYDQ0NytUYy5YtQyQSMc7n+eefx/e+9z3EYjFUV1fjzjvvtN1vbm7GlVdeiaqqKsRiMeyzzz6YPXu2df/TTz/FSSedhN69e2PAgAE477zzsGXLFuv+a6+9hiOOOMLSlz/84Q/xxRdfWPd5nb3wwgsYN24cevXqhf333x+LFi0ykp8giNyFDKpE6EgkEjjxxBOxcOFCPPnkk/j0009x6623Ij8/HwCwfPlyTJgwAaeffjo++eQTPPPMM3jvvfcwbdq0wGRoaWnBTTfdhH//+9/4+9//jtraWmswW1VVheeffx4AsGrVKtTV1eHee+9NSuOFF17A4MGDraWPdXV1xvnfeeedePTRRzF79my899572LZtG1588UVbmN/85jeoqanBn/70J6xYsQKXXXYZfvKTn+Cdd97xVNYPP/wQF1xwAS6++GIsW7YM48aNw80332wLM2/ePPzkJz/BJZdcgk8//RQPPfQQ5syZg1mzZgHoaLNTTz0VvXr1wocffoiHH34Y1157rTK/q666CpdccglWrlyJCRMm4JFHHsG1116LWbNmYeXKlbjllltw3XXX4bHHHgMA7Ny5E+PGjUPv3r3xz3/+E++99x569+6NE044AS0tLWhra8Opp56Ko48+Gp988gkWLVqEiy66yJNn1MyZM7F8+XLfhgKCIHIL0jOkZ0jPEATR3bn88svx/vvvY+7cuZg/fz7effdd/Otf/7KF+f3vf49Ro0ZhyZIluO6665LS2LBhA04//XScdNJJWLZsGX72s58ZTw4VFxfjrLPOQk1Nje16TU0NfvSjHwWy2mLJkiU444wzcNZZZ2H58uWYOXMmrrvuOsyZM8cKc/755+Ovf/0r7rvvPqxcuRIPPvggevfuDaBjq5Wjjz4aBxxwAD7++GO89tpr+Prrr3HGGWdY8RsbG3H55Zdj8eLFePPNN5GXl4fTTjsNiUTCJsu1116LGTNmYNmyZRg2bBjOPvts26QgQRDdEEYQGWbo0KHs7rvvtl3bf//92fXXX88YY2zevHksLy+PrVq1Shn/vPPOYxdddJHt2rvvvsvy8vJYU1OTMg8A7MUXX9TKdPTRR7Pp06dr73/00UcMAGtoaGCMMfb2228zAGz79u2O6ajKev3117P999/fdu3uu+9mQ4cOtb4PHDiQ3Xrrrdb31tZWNnjwYDZp0iTGGGPfffcdKyoqYgsXLrSlc+GFF7Kzzz5bWw6VPGeffTY74YQTbNfOPPNMVlZWZn0/8sgj2S233GIL88QTT7CBAwcyxhh79dVXWUFBAaurq7Puz58/31bvtbW1DAC75557bOlUVVWxp59+2nbtpptuYmPGjGGMMTZ79my27777skQiYd1vbm5m8XiczZs3j23dupUBYAsWLNCWW0dNTY1VzquvvpoNGzaMtba2su3btzMA7O2339aGJwgivJCeIT0jQnqGIIieRn19PSssLGR/+9vfrGvffvst69Wrl6VDhg4dyk499VRbPN6PLl26lDHG2DXXXMNGjBhh6x+vuuoqpX5S8eGHH7L8/Hy2ceNGxhhj33zzDSssLLT6U5WuW7p0KQPAamtrXdM/55xz2PHHH2+79qtf/YqNHDmSMcbYqlWrGAA2f/58ZfzrrruOjR8/3nZtw4YNDID2HWHz5s0MAFu+fDljrKvO/vznP1thVqxYwQCwlStXupaBIIjchTxUidCxbNkyDB48GMOGDVPeX7JkCebMmYPevXtbfxMmTEAikUBtbW0gMixduhSTJk3C0KFDUVJSgmOOOQYAsH79+kDSd2LHjh2oq6vDmDFjrGsFBQUYPXq09f3TTz/Frl27cPzxx9vq4fHHH7ctQTFh5cqVtrwAJH1fsmQJbrzxRlteU6dORV1dHXbu3IlVq1ahqqoKlZWVVpxDDjlEmZ9Yjm+++QYbNmzAhRdeaEv75ptvtsqxZMkSrFmzBiUlJdb9vn37YteuXfjiiy/Qt29fTJkyBRMmTMDEiRNx7733evLS4lx11VX45ptv8Oijj3qOSxBEbkF6hvQM6RmCILozX375JVpbW239ZFlZGfbdd19bOLG/VLFy5UocdthhNo98uf924pBDDsH3vvc9PP744wCAJ554AkOGDMFRRx1lnIabfIcffrjt2uGHH47PP/8c7e3tWLZsGfLz83H00Ucr4y9ZsgRvv/22TT8MHz4cACwd8cUXX+Ccc87BnnvuidLSUuyxxx4AkvX1fvvtZ30eOHAgAFhb+RAE0T2h3aaJjJOXl5e0T5t4aEQ8HneMn0gk8POf/xyXXHJJ0r0hQ4akLF9jYyPGjx+P8ePH48knn0T//v2xfv16TJgwAS0tLSmn71Z+E/gSk1deeQW777677V4sFvOUliyLLr8bbrgBp59+etK9oqIiMMaMlz4WFxfb0gWARx55BIceeqgtHF96m0gkcPDBB+Opp55KSqt///4AOpYOXXLJJXjttdfwzDPP4De/+Q3mz5+Pww47zEgmAOjTpw+uueYa3HDDDfjhD39oHI8giPBBeob0jJguQHqGIIieBe935X5T7o/F/tIpnVT42c9+hgceeABXX301ampq8NOf/tSSKy8vLykfL/pKpRvEtEz0/cSJE3Hbbbcl3eNG0YkTJ6KqqgqPPPIIBg0ahEQigVGjRiXp68LCQuszl0neFoAgiO4FGVSJjNO/f3+bZ0d9fb3N42e//fbDV199hdWrVyu9hw466CCsWLECe++9d1rk++yzz7BlyxbceuutqKqqAgB8/PHHtjDRaBRAx6EeTkSj0aQw/fv3x6ZNm2wvAOLG72VlZRg4cCA++OADa/a2ra0NS5YswUEHHQQAGDlyJGKxGNavX6+dcTVl5MiR+OCDD2zX5O8HHXQQVq1apa3z4cOHY/369fj6668xYMAAAMDixYtd8x4wYAB23313fPnllzj33HOVYQ466CA888wz2G233VBaWqpN68ADD8SBBx6Ia665BmPGjMHTTz/taaALAP/7v/+L++67T7lXIUEQuQPpGdIzHNIzBEH0RPbaay8UFhbio48+svRMfX09Pv/8c099+siRI62D/zhy/+3GT37yE1x55ZW47777sGLFCkyePNm6xyet6urqUF5eDsCur0zke++992zXFi5ciGHDhiE/Px/f//73kUgk8M477+C4445Lin/QQQfh+eefR3V1NQoKkk0jW7duxcqVK/HQQw/hyCOPBICk/AiC6LnQkn8i4/zgBz/AE088gXfffRf/+c9/MHnyZMtLBACOPvpoHHXUUfif//kfzJ8/H7W1tXj11Vfx2muvAehYMrdo0SL88pe/xLJly/D5559j7ty5+N///d9A5BsyZAii0Sjuv/9+fPnll5g7dy5uuukmW5ihQ4ciEong5ZdfxjfffIPvvvtOmVZ1dTX++c9/YuPGjdZpkccccwy++eYb3H777fjiiy/whz/8Aa+++qot3vTp03HrrbfixRdfxGeffYaLL77YdvplSUkJZsyYgcsuuwyPPfYYvvjiCyxduhR/+MMfrEM2TOEeN7fffjtWr16NBx54wKprzm9/+1s8/vjjmDlzJlasWIGVK1daHjoAcPzxx2OvvfbC5MmT8cknn+D999+3Dgtx8yiaOXMmfve73+Hee+/F6tWrsXz5ctTU1OCuu+4CAJx77rmoqKjApEmT8O6776K2thbvvPMOpk+fjq+++gq1tbW45pprsGjRIqxbtw6vv/46Vq9ejREjRniqB6DDC+qGG27Afffd5zkuQRDhgfQM6RkR0jMEQfQ0SkpKMHnyZPzqV7/C22+/jRUrVuCCCy5AXl6epwP1fvGLX+CLL77A5ZdfjlWrVuHpp5+2HfhkQnl5OU4//XT86le/wvjx4zF48GDr3t57742qqirMnDkTq1evxiuvvII777zTOO0rrrgCb775Jm666SasXr0ajz32GB544AHMmDEDQIeOnDx5Mi644ALrAMgFCxbg2WefBQD88pe/xLZt23D22Wfjo48+wpdffonXX38dF1xwAdrb21FeXo5+/frh4Ycfxpo1a/DWW2/h8ssv91R+giC6MZnftpXo6ezYsYOdccYZrLS0lFVVVbE5c+bYDgthjLGtW7eyn/70p6xfv36sqKiIjRo1ir388svW/Y8++ogdf/zxrHfv3qy4uJjtt99+bNasWdb9VA8Lefrpp1l1dTWLxWJszJgxbO7cubYN2hlj7MYbb2SVlZUsEomwyZMnK9NZtGgR22+//VgsFmPiz+1Pf/oTq6qqYsXFxez8889ns2bNsh0W0trayqZPn85KS0tZnz592OWXX87OP/9867AQxhhLJBLs3nvvZfvuuy8rLCxk/fv3ZxMmTGDvvPOOtpyqw0IY6ziQY/DgwSwej7OJEyeyO+64I+lQjNdee42NHTuWxeNxVlpayg455BD28MMPW/dXrlzJDj/8cBaNRtnw4cPZSy+9xACw1157jTGWvMm9yFNPPcUOOOAAFo1GWXl5OTvqqKPYCy+8YN2vq6tj559/PquoqGCxWIztueeebOrUqWzHjh1s06ZN7NRTT2UDBw5k0WiUDR06lP32t79l7e3t2nrgqA7/aGtrYyNHjqTDQggihyE9Q3pGhvQMQRA9jfr6enbOOeewXr16scrKSnbXXXexQw45hF199dWMMXV/repHX3rpJbb33nuzWCzGjjzySPboo48aH0rFefPNNxkA9uyzzybde++999j3v/99VlRUxI488kj2t7/9zfhQKsYYe+6559jIkSNZYWEhGzJkCPv9739vu9/U1MQuu+wyqw/fe++92aOPPmrdX716NTvttNNYnz59WDweZ8OHD2eXXnqpdRDX/Pnz2YgRI1gsFmP77bcfW7BggfJARLHOdAcPEgTRvYgwFsDGKARB5ATV1dW49NJLcemll6Y9r/fffx9HHHEE1qxZg7322ivt+WWCOXPm4NJLL7V5cREEQRBdkJ5JDdIzBEGki8bGRuy+++648847ceGFF2Y076eeegrTp0/Hf//7X2tLG4IgiFyHDKoE0YOorq5GXV0dCgsLsXHjRpSVlQWW9osvvojevXtjn332wZo1azB9+nSUl5d3m32Gevfujba2NhQVFdFAlyAIQgPpGf+QniEIIkiWLl2Kzz77DIcccgh27NiBG2+8EQsWLMCaNWtQUVGRERl27tyJ2tpanHnmmZg0aRJmzZqVkXwJgiAyAR1KRRA9iHfeecc6ObOkpCTQtBsaGnDllVdiw4YNqKiowHHHHedpD6R08L3vfQ/r1q1T3nvooYe0B5So4Bvki/swEgRBEHZIz3RBeoYgiGxzxx13YNWqVYhGozj44IPx7rvvBmpMPfHEE/Huu+8q7/36179GS0sLZs2ahaOOOgrXXHNN4On/+te/9pwmQRBEUJCHKkEQ3ZZ169ZZA3uZAQMGBD7YJwiCIHoWpGcIgujJbNy4EU1NTcp7ffv2Rd++fUOdPkEQRCqQQZUgCIIgCIIgCIIgCIIgCMKQvGwLQBAEQRAEQRAEQRAEQRAEkSuQQZUgCIIgCIIgCIIgCIIgCMIQMqgSBEEQBEEQBEEQBEEQBEEYQgZVgiAIgiAIgiAIgiAIgiAIQ8igShAEQRAEQRAEQRAEQRAEYQgZVAmCIAiCIAiCIAiCIAiCIAwhgypBEARBEARBEARBEARBEIQhZFAlCIIgCIIgCIIgCIIgCIIw5P8DZ3xhV0lDdAgAAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(nrows = 1, ncols = 3, figsize = (15, 4))\n", "\n", "levels = np.arange(-10, 10.1, 0.5)\n", "\n", "(psi_avg_mean-psi_avg_mean_2).plot.contourf(ax = axes[0], x = 'grid_yu_ocean',levels = levels, add_colorbar = False)\n", "\n", "(psi_avg_mean-psi_avg_mean_3).plot.contourf(ax = axes[1], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "p = (psi_avg_mean_2 - psi_avg_mean_3).plot.contourf(ax = axes[2], x = 'grid_yu_ocean', levels = levels, add_colorbar = False)\n", "\n", "cbar_ax = fig.add_axes([0.92, 0.15, 0.01, 0.7])\n", "fig.colorbar(p, cax=cbar_ax, label='Transport (Sv)')\n", "\n", "axes[0].set_title('Method 1 - Method 2')\n", "axes[1].set_title('Method 1 - Method 3')\n", "axes[2].set_title('Method 2 - Method 3')\n", "\n", "for ax in axes:\n", " ax.set_ylim(1037.5, 1032)\n", " ax.set_xlim(-70, -35)\n", "\n", "fig.suptitle('Difference in Mean Streamfunction', fontsize = 16);" ] }, { "cell_type": "markdown", "id": "eed3d00b-224e-448d-8cbd-c8198244fe87", "metadata": {}, "source": [ "An alternative method to calculate the decomposition of the residual meridional overturning circulation into mean and eddy components is to bin `ty_trans` (or `vhrho_nt`) into density bins using daily data (both density and transport). Then the transport $\\overline{vh}$ can be separated into a mean component $\\overline{v}\\overline{h}$ and an eddy component $\\overline{v^\\prime h^\\prime}$, where the overline is a time average and primed quantities the deviation from the time average. Quantities are calculated within density layers, and $h$ is density layer thickness, calculated by binning `dzt` or `dzu`. This calculation, since it uses daily data, is computationally expensive and is difficult to do efficiently in a jupyter notebook. The resulting streamfunctions are similar, but not identical, and may be more intuitive for isopycnal flows. An example of this method can be found at https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Figure_Code/Fig5-Overturning.ipynb." ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:analysis3-22.10]", "language": "python", "name": "conda-env-analysis3-22.10-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.15" } }, "nbformat": 4, "nbformat_minor": 5 }