Context. Space weathering is a process that changes the surface of airless planetary bodies. Prime space weathering agents are solar wind irradiation and micrometeoroid bombardment. These processes alter planetary reflectance spectra and often modify their compositional diagnostic features. Aims. In this work we focused on simulating and comparing the spectral changes caused by solar wind irradiation and by micrometeoroid bombardment to gain a better understanding of these individual space weathering processes. Methods. We used olivine and pyroxene pellets as proxies for planetary materials. To simulate solar wind irradiation we used hydrogen, helium, and argon ions with energies from 5 to 40 keV and fluences of up to 1018 particles cm−2. To simulate micrometeoroid bombardment we used individual femtosecond laser pulses. We analysed the corresponding evolution of different spectral parameters, which we determined by applying the Modified Gaussian Model, and we also conducted principal component analysis. Results. The original mineralogy of the surface influences the spectral evolution more than the weathering agent, as seen from the diverse evolution of the spectral slope of olivine and pyroxene upon irradiation. The spectral slope changes seen in olivine are consistent with observations of A-type asteroids, while the moderate to no slope changes observed in pyroxene are consistent with asteroid (4) Vesta. We also observed some differences in the spectral effects induced by the two weathering agents. Ions simulating solar wind have a smaller influence on longer wavelengths of the spectra than laser irradiation simulating micrometeoroid impacts. This is most likely due to the different penetration depths of ions and laser pulses. Our results suggest that in some instances it might be possible to distinguish between the contributions of the two agents on a weathered surface.

Context. Airless planetary bodies are studied mainly by remote sensing methods. Reflectance spectroscopy is often used to derive their compositions. One of the main complications for the interpretation of reflectance spectra is surface alteration by space weathering caused by irradiation by solar wind and micrometeoroid particles. Aims. We aim to evaluate the damage to the samples from H + and laser irradiation and relate it to the observed alteration in the spectra. Methods. We used olivine (OL) and pyroxene (OPX) pellets irradiated by 5 keV H + ions and individual femtosecond laser pulses and measured their visible (VIS) and near-infrared (NIR) spectra. We observed the pellets with scanning and transmission electron microscopy. We studied structural, mineralogical, and chemical modifications in the samples. Finally, we connected the material observations to changes in the reflectance spectra. Results. In both minerals, H + irradiation induces partially amorphous sub-surface layers containing small vesicles. In OL pellets, these vesicles are more tightly packed than in OPX ones. Any related spectral change is mainly in the VIS spectral slope. Changes due to laser irradiation are mostly dependent on the material's melting temperature. Of all the samples, only the laser-irradiated OL contains nanophase Fe particles, which induce detectable spectral slope change throughout the measured spectral range. Our results suggest that spectral changes at VIS-NIR wavelengths are mainly dependent on the thickness of (partially) amorphous sub-surface layers. Furthermore, amorphisation smooths micro-roughness, increasing the contribution of volume scattering and absorption over surface scattering. Conclusions. Soon after exposure to the space environment, the appearance of partially amorphous sub-surface layers results in rapid changes in the VIS spectral slope. In later stages (onset of micrometeoroid bombardment), we expect an emergence of nanoparticles to also mildly affect the NIR spectral slope. An increase in the dimensions of amorphous layers and vesicles in the more space-weathered material will only cause band-depth variation and darkening.

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Context. Our knowledge of near-Earth asteroid (NEA) composition is important for planetary research, planetary defence, and future in-space resource utilisation. Upcoming space missions, for example, Hera, M-ARGO, or missions to the asteroid (99942) Apophis, will provide us with surface-resolved NEA reflectance spectra. Neural networks are useful tools for analysing reflectance spectra and determining material composition with high precision and low processing time. Aims. We applied neural-network models on disk-resolved spectra of the Eros and Itokawa asteroids observed by the NEAR Shoemaker and Hayabusa spacecraft. With this approach, the mineral variations or intensity of space weathering can be mapped. Methods. We built and tested two types of convolutional neural networks (CNNs). The first one was trained using asteroid reflectance spectra with known taxonomy classes. The other one used silicate reflectance spectra with assigned mineral abundances and compositions. Results. The reliability of the classification model depends on the resolution of reflectance spectra. Typical F1 score and Cohen's κC values decrease from about 0.90 for high-resolution spectra to about 0.70 for low-resolution spectra. The predicted silicate composition does not strongly depend on spectrum resolution and coverage of the 2-µm band of pyroxene. The typical root mean square error is between 6 and 10 percentage points. For the Eros and Itokawa asteroids, the predicted taxonomy classes favour the S-type and the predicted surface compositions are homogeneous and correspond to the composition of L/LL and LL ordinary chondrites, respectively. On the Itokawa surface, the model identified fresh spots that were connected with craters or coarse-grain areas. Conclusions. The neural network models trained with measured spectra of asteroids and silicate samples are suitable for deriving surface silicate mineralogy with a reasonable level of accuracy. The predicted surface mineralogy is comparable to the mineralogy of returned samples measured in the laboratory. Moreover, the taxonomical predictions can point out locations of fresher areas.

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Space weathering can be defined as the combination of physical and chemical changes that occur in material exposed to an interplanetary environment on the surface of airless bodies. This process results in alterations in material spectroscopic features. Eventually, it can lead to misinterpretation of remotely sensed data in the visible–near-infrared wavelength range. This study simulates the solar wind effect on asteroid spectra through low-energy 1 keV H+ irradiation of meteorite pressed-powder samples under three fluences, 2 × 1017, 5 × 1017, and 1 × 1018 H+ cm−2, and evaluates changes associated with reflectance spectra. The meteorites subjected to the study are Bjurböle (L/LL4), Avanhandava (H4), and Luotolax (howardite). The most prominent changes in all three meteorites are (1) a decrease of 550 nm reflectance, (2) reddening in the 1 μm region, and (3) a monotonous decrease in absorption band strengths in Bjurböle. No significant changes were observed in the 2 μm region. The results imply that at short timescales (102–103 yr), radiation damage as amorphization and vesicle formation caused by low-energy solar wind is the dominant space weathering factor in all three meteorite compositions, causing spectral changes predominantly in the 1 μm region.

<p><strong>Introduction:</strong> Solar wind ions and impacts of micrometeoroids are the leading processes that weather the surface of airless planetary bodies in the solar system. As a result, key diagnostic features of their spectra get altered. The most prominent changes in the silicate-rich bodies in the visible (VIS) and near-infrared (NIR) wavelengths are increase in the spectral slope, reduction of the albedo, and subduction of the mineral absorption bands (see, for example, Hapke 2001).</p> <p>Our work aims at understanding what are the similarities and differences between the effect of the solar wind ions and micrometeoroid impacts on the final spectra of the silicate-rich bodies. Our study is based on laboratory simulations using planetary analogue materials.</p> <p> </p> <p><strong>Methods: </strong>We have used two different terrestrial minerals, olivine and pyroxene. Each material was ground and dry-sieved to sizes smaller than 106 μm. Subsequently, we created pressed pellets from potassium bromide, which served as a base, and 100 mg of the mineral, which created the top layer of the pellet.</p> <p>Ion irradiations were conducted at two different laboratories. Hydrogen irradiations proceeded at the Accelerator Laboratory of the University of Helsinki, using 5 keV ions with varying fluences from 10<sup>14 </sup>to 10<sup>18</sup> ions/cm<sup>2</sup>. Subsequent spectral measurements were done out of the vacuum chamber after surface passivation of the samples. Helium and argon irradiations were done using the INGMAR set-up (IAS-CSNSM, Orsay) with 20 and 40 keV ions and with fluences from 10<sup>15</sup> to 10<sup>17</sup> ions/cm<sup>2</sup>. Spectra were measured in the vacuum chamber, where we irradiated the samples.</p> <p>Individual 100-fs laser pulses were shot into a square grid on the pellets’ surface to simulate the micrometeoroid impacts (as in Fazio et al. 2018). Various densities of the pulses per cm<sup>2</sup> simulated different weathering stages. Spectral measurements were done outside of the vacuum chamber.</p> <p>The spectral measurements covered, in all the set-ups, wavelengths from 0.54 to 13 μm, i.e. VIS to mid-infrared wavelengths. After the measurements, we evaluated the evolution of the spectral parameters estimated using the Modified Gaussian Model (Sunshine et al. 1990, 1999).</p> <p> </p> <p><strong>Results: </strong>Variation of the spectra in the VIS range was similar for H<sup>+</sup>- and laser-irradiated samples, but we have identified a difference in the NIR wavelength range. Laser irradiation caused greater changes in NIR than any of the ions we used, see Fig. 1. The reason for such difference in behaviour may be the different penetration depth of the irradiating ions and laser pulses. While laser penetrates approximately 100 μm under the surface of the pellet, our ions did not penetrate deeper than 150 nm. Spectra of the laser-irradiated samples thus bear information solely from the irradiated material, while spectra of the ion-irradiated samples are a mixture of the top-most altered layers and the unaltered underlying layers. The relative contribution of the irradiated material is then smaller in the ion case.</p> <p>Otherwise, we found that the original mineralogy of the pellet is more determinative to the evolution of the spectral parameters than the space weathering agent (ions or laser pulses). While olivine and pyroxene showed albedo variations of a similar order, the evolution of pyroxene’s spectral slope was negligible when compared to olivine, see Fig. 2.</p> <p><img src="data:image/png;base64, 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//rXv1BSUoJZs2YZXCcpKQlz5syxSp6JiIhsRbUHxeXk5MDYWXtD96dbk1arRUBAAFauXIkuXbpgyJAhePXVV7FixQqj60ybNg35+fm6v9OnT9doHhs6PhqWiKh2VHtQXKtWrZCbm1tp0NqlS5fQqlUrlJaWKkrH398fjo6OOHfunN70c+fOITAw0OA6QUFBcHZ21ju9HhYWhrNnz6K4uBhqtbrSOhqNxqLR90RERLas2kfoImLwWvnVq1fh4uKiOB21Wo0uXbogOTlZN02r1SI5ORnR0dEG1+nRowdOnDgBrVarm3bs2DEEBQUZDOZEZBjvNiOq/yw+Qi8b3a5SqTBjxgy4ubnp5pWWliI1NRUdO3ascprx8fHo2rUrunXrhmXLlqGoqAijRo0CAIwYMQJNmzZFUlISAGDs2LF4++23MWHCBIwfPx7Hjx/Hv//9byQmJlpaLCIionrJ4oBeNrpdRHD48GG9I2K1Wo3IyEhMmjSpSmkOGTIEFy5cwMyZM3H27Fl07NgRW7Zs0Q2Uy8nJgYPD/04qNG/eHD/88ANefPFFdOjQAU2bNsWECRMwdepUS4tFVL/V9pPheFhPZDOq/frUUaNG4Y033qjRe+tqEu9Dr9n70Hlfeu1RqXjfOZEtsun70Mtbs2YNAOCPP/5ATk4OiouL9eY/9NBD1d0EERERmVHtgJ6dnY3Bgwfj8OHDUKlUulvYygbKKR3lTg0DD/CIiGpGtUe5JyYmolWrVjh//jzc3Nxw5MgR7NixA127dkVKSooVskh2ifelExFZVbWP0Pfs2YMff/wR/v7+cHBwgIODA3r27ImkpCQkJiaafDQsERERWUe1j9BLS0vh6ekJ4PbDYc6cOQMACAkJQWZmZnWTJyIiIgWqfYTevn17HDx4EK1atUJUVBQWLlwItVqNlStXonXr1tbIIxGZYsGtaroxDLzqQWQ3qh3Qp0+fjqKiIgDA3LlzMWDAANx7773w8/PD559/Xu0MEhERkXnVDuhxcXG6/4eGhiIjIwOXL1+Gj49PlV6fSkRV87/nCxARWSGgG+Lr61sTyRJRXeP9hkQ2y6KAPnHiRMybNw/u7u66Z7obs2TJEosyRkRERMpZFNAPHDiAkpIS3f+N4Sl3IiKi2mFRQP/pp58M/p+oqvjkOCIi66jWfeglJSXo3bs3jh8/bq38EBERkQWqNSjO2dkZhw4dslZeqCHjobpytf2KVCKqF6r9pLinnnoK77//vjXyQkQmVOfx9yL8rURk76p929qtW7ewevVqbN++HV26dIG7u7vefI5yJyIiqnnVDui///47OnfuDAA4duyY3jyOciciIqod1Q7oHOVORERU96z2pLg//vgDOTk5KC4u1k1TqVQYOHCgtTZBRLWNF96J6o1qB/STJ0/i4YcfxuHDh6FSqSD/3QGUnW4vLS2t7iaIGjaOaiciBao9yn3ChAlo1aoVzp8/Dzc3Nxw5cgQ7duxA165dkZKSYoUsEjVM1RnVTkQNT7WP0Pfs2YMff/wR/v7+cHBwgIODA3r27ImkpCQkJiaafDQsERERWUe1j9BLS0vh6ekJAPD398eZM2cAACEhIcjMzKxu8kRERKRAtY/Q27dvj4MHD6JVq1aIiorCwoULoVarsXLlSrRu3doaeSSiKtKNZeMpe6IGo9oBffr06SgqKgIAzJ07FwMGDMC9994LPz8/fP7559XOIDUsDfkJsA257ERUfdUO6HFxcbr/h4aGIiMjA5cvX4aPjw8fLEOWa8jRjaPaicgC1b6GPmbMmEqj2X19fRnMiYiIalG1A/qFCxfQt29fNG/eHJMnT0Z6eroVskVERERVUe2A/u233yI3NxczZszAvn370KVLF9x1113497//jVOnTlkhi0RUa/haNqJ6SyVi3W/vX3/9hU8//RSrV6/G8ePHcevWLWsmb3UFBQXw9vZGfn4+vLy8qp2e7tIvKl8DNjWvJudXnK7677XZ6ny2ZlqmPttzcKnJdtHVW8WxCOY+E5HVWTvOGFPtI/TySkpK8NtvvyE1NRWnTp1CkyZNrJk8ERERGWGVgP7TTz8hISEBTZo0wciRI+Hl5YWNGzfir7/+skbyREREZEa1b1tr2rQpLl++jL59+2LlypUYOHAgNBqNNfJGZFdq+uy2CPggGaIGrNoBffbs2Xj88cfRqFEjK2SHqAHgfeZEVAOqHdATEhKskQ8iIiKqBqsOiiOi/+HrT4moNlX7CJ2IzOApdiKqBTxCJ5vGo1wiImV4hE5kJfXyGS31KrNEZEq1jtD//PNPbN26FWfPnjU4/8yZM9VJnuh/6tOhei3llU9pJaLyLA7on376KUJDQ9G3b1+0bt0aH330EQAgJycHCxYsQFRUFFq0aGG1jBIREZFxFgf0efPmYfz48Th8+DAefPBBjB07FjNmzECbNm2wdu1adO3aFV9++aU180pERERGWHwNPSsrCxMmTEBISAiWL1+OFi1aYNeuXTh06BDCwsKsmUcim1Qvr5kTkd2yOKCXlJTA1dUVANCsWTO4uLjg9ddfZzCnhoe3pRGRDajWoLh169YhIyMDAODo6AgfHx+rZIqIiIiqxuKAfu+992LWrFm466674O/vjxs3buCNN97AF198gT/++MPm34NORERkTyw+5f7zzz8DAI4fP460tDTs378f+/fvx4cffoi8vDyo1WrccccdOHTokNUyS9SQ6a7V15O794iodlX7SXFt27bFE088gYULF2L79u24fPkysrKy8NFHH2HAgAFVTm/58uVo2bIlXFxcEBUVhb179xpddu3atVCpVHp/Li4u1SkOkVH16VZ4o3jzOpHdqpEnxbVq1QqtWrXC448/XqX1Pv/8c0ycOBErVqxAVFQUli1bhri4OGRmZiIgIMDgOl5eXsjMzNR9VtX7PS7ZPA6CIyIbZFPPcl+yZAkSEhIwatQohIeHY8WKFXBzc8Pq1auNrqNSqRAYGKj7a9KkSS3mmIiIyDbYTEAvLi5GWloaYmNjddMcHBwQGxuLPXv2GF3v6tWrCAkJQfPmzTFo0CAcOXLE5HZu3ryJgoICvT+qP+zitDcRUQ2wmYB+8eJFlJaWVjrCbtKkidFnxbdr1w6rV6/Gt99+i48//hharRbdu3fHX3/9ZXQ7SUlJ8Pb21v01b97cquUgIiKqCzYT0C0RHR2NESNGoGPHjujVqxe+/vprNG7cGO+9957RdaZNm4b8/Hzd3+nTp2sxx2Q1DeBQnePXiKgqbOb1qf7+/nB0dMS5c+f0pp87dw6BgYGK0nB2dkanTp1w4sQJo8toNBpoNJpq5ZUaBj7alYjqE5s5Qler1ejSpQuSk5N107RaLZKTkxEdHa0ojdLSUhw+fBhBQUE1lU1qiBrA2QAiqv9s5ggdACZOnIj4+Hh07doV3bp1w7Jly1BUVIRRo0YBAEaMGIGmTZsiKSkJADB37lzcc889CA0NRV5eHhYtWoQ///wTY8aMqctiEBER1TqbCuhDhgzBhQsXMHPmTJw9exYdO3bEli1bdAPlcnJy4ODwv5MKV65cQUJCAs6ePQsfHx906dIFu3fvRnh4eF0VgYiIqE6oRBr2FcKCggJ4e3sjPz8fXl5e1U5Pd90VlS/AmppXk/MrTlf994Eo1flszbSq87kmL3DXRL2Z+qwrS8WL91X5zAv/RDbH2nHGGJu5hk5ERESWY0An+i+OfSOi+owBneo1BmEiottsalAckU3gy1eIqB5iQCeqI3y/ORFZE0+5k33guXciauAY0ImIiOwAAzoREZEd4DV0atBUqtp7BkutXDPnA2WIGiweoRMREdkBHqGTXbHoyae8TY2I7ACP0ImIiOwAj9DJPtnAS0p4nzkR1SYeoVODwtvViche8Qid7JrRA3VeNyciO8OATg0DAzgR2TkGdCIrqbNr5rz3nIjAa+hERER2gQGdiIjIDjCgExER2QEGdCIiIjvAQXFEFuKDY4jIlvAInYiIyA7wCJ2ovuFtakRkAI/QiYiI7ACP0KlGVbzOzOvOREQ1gwGdrMqeA7Y9l42I6j8GdHvEa6xERA0OA3pDUhborXiEWd2jVh71EhFZBwN6A2Tuura5ICtifB4REdUNBvQGoLpn4HkUXcd4CYWIFGBAb8gYKIiI7AYDOpERPDNBRPUJAzrZFAZRIiLLMKDXRzxVTkREFTCg2xHGeTvBhiQiCzCg0/8wkBAR1Vt8OQsREZEdYEAnIiKyAzzlTjatNke9c4Q9EdVnDOhEdY1jF4jIChjQyTgGGqpjWq0WxcXFdZ0NIpOcnZ3h6OhY19lgQCci21RcXIzs7Gxotdq6zgqRWY0aNUJgYCBUqrq7ZseATsrxiJ1qiYggNzcXjo6OaN68ORwcOH6XbJOI4Nq1azh//jwAICgoqM7ywoBOVNv4w8isW7du4dq1awgODoabm1tdZ4fIJFdXVwDA+fPnERAQUGen3/mzlywjUieBqY42S7WstLQUAKBWq+s4J0TKlP3wLCkpqbM88AjdFjFi1RoR8DY1G1aX1yOJqsIW+qrNHaEvX74cLVu2hIuLC6KiorB3715F63322WdQqVQYPHhwzWawDtn00alNZ46IyP7ZVED//PPPMXHiRMyaNQv79+9HZGQk4uLidIMNjDl16hQmTZqEe++9t5ZySmYxwBMR1SqbCuhLlixBQkICRo0ahfDwcKxYsQJubm5YvXq10XVKS0sxbNgwzJkzB61bt67F3FKVNOQA35DLThZ5+OGH4ePjg8cee0xv+tKlS3HXXXchPDwciYmJEPYrKsdmAnpxcTHS0tIQGxurm+bg4IDY2Fjs2bPH6Hpz585FQEAARo8eXRvZJBvDWEn2aMKECfjwww/1pl24cAFvv/020tLScPjwYaSlpeHXX3+tke2vXbsWa9eurZG0qebYzKC4ixcvorS0FE2aNNGb3qRJE2RkZBhc55dffsH777+P9PR0xdu5efMmbt68qftcUFBgUX6pfuLz2qk+iImJQUpKSqXpt27dwo0bNwDcHk0dEBBQyzkjW2YzR+hVVVhYiOHDh2PVqlXw9/dXvF5SUhK8vb11f82bN6/BXJJRPLQmO7Vjxw4MHDgQwcHBUKlU+OabbyotY8ng38aNG2PSpElo0aIFgoODERsbizZt2hhdfuTIkQYHCaekpEClUiEvL68KpaL6wGaO0P39/eHo6Ihz587pTT937hwCAwMrLZ+VlYVTp05h4MCBumllj4h0cnJCZmamwc4+bdo0TJw4Ufe5oKCAQd2OVDwCr5Mjcv5QadCKiooQGRmJp59+Go888kil+WWDf1esWIGoqCgsW7YMcXFxyMzMNHnEfeXKFWzcuBGnTp2Cq6sr+vXrhx07duC+++6zSr6Li4vRrVs3AMDly5cBAMuWLQMA7N27l88EqAdsJqCr1Wp06dIFycnJul+VWq0WycnJGDduXKXl77zzThw+fFhv2vTp01FYWIg33njDaJDWaDTQaDRWzz8R1bzavtXXkt9m/fr1Q79+/YzOLz/4FwBWrFiBTZs2YfXq1Xj55ZeNrrd9+3aEhobC19cXANC/f3/8+uuvVgvoarVad/my7Pr5yJEjrZI21Q6bCegAMHHiRMTHx6Nr167o1q0bli1bhqKiIl3HHzFiBJo2bYqkpCS4uLigffv2eus3atQIACpNJyKyBWWDf6dNm6abpmTwLwA0b94cu3fvxo0bN+Ds7IyUlBQ888wzNZ1lqkdsKqAPGTIEFy5cwMyZM3H27Fl07NgRW7Zs0Q2Uy8nJ4UsaiKjeUjr4NzY2FgcPHkRRURGaNWuGL7/8EtHR0fjHP/6BTp06wcHBAb1798ZDDz1kcnsbN26Eh4eH3rSyx+qS/bGpgA4A48aNM3iKHYDBUZ/l8TaLeqw+X3euz3knm7R9+3aD0+fPn4/58+crTuf+++/Hu+++qzctNTUVTz31lMn1eKq9frK5gE5EZK+qOvi3utzd3REaGqo37a+//rL6dsg28Px1XeAtW0QNUvnBv2XKBv9GR0fXYc7IHvAInYjIiq5evYoTJ07oPmdnZyM9PR2+vr5o0aKF2cG/RJZiQCcisqLffvsN999/v+5z2XMv4uPjsXbtWrODf4kspZIG/nT/goICeHt7Iz8/H15eXtVOr+w+Wan0ZJNy8xp0jStUsbJq8nNV16Uad+PGDWRnZ6NVq1ZwcXHRTa8P96FTw2SszwLWjzPG8AidbBP3pGQAuwWRcRwUR0REZAcY0ImIiOwAAzoREZEdYEAnIiKyAxwUR2QOR2IRUT3AI3QiIiI7wCN0qh94lExEZBKP0ImIiOwAAzoREZEdYEAnIiKyAwzoREREdoABnagivq+e7MS1a9cQEhKCSZMm1XVW6qXTp08jJiYG4eHh6NChA7788su6zpJJHOVeixgjiKg2zZ8/H/fcc09dZ6PecnJywrJly9CxY0ecPXsWXbp0wT/+8Q+4u7vXddYM4hF6TeFRHhHVoePHjyMjIwP9+vWrtW3GxMTghRdeqLXt1bSgoCB07NgRABAYGAh/f39cvny5bjNlAgM61U/8wUT1wIIFC6BSqaoc5Hbs2IGBAwciODgYKpUK33zzTaVlli9fjpYtW8LFxQVRUVHYu3ev3vxJkyYhKSmpGrmvH0aNGoXp06fX+HbS0tJQWlqK5s2b1/i2LMWATkT1h0pVu3/VsG/fPrz33nvo0KFDldctKipCZGQkli9fbnD+559/jokTJ2LWrFnYv38/IiMjERcXh/PnzwMAvv32W9xxxx244447qlUGW1daWoqNGzfioYceqtHtXL58GSNGjMDKlStrdDvVxYBORGRlV69exbBhw7Bq1Sr4+Pjopl+4cAGBgYH497//rZu2e/duqNVqJCcn66b169cPr732Gh5++GGD6S9ZsgQJCQkYNWoUwsPDsWLFCri5uWH16tUAgF9//RWfffYZWrZsiUmTJmHVqlWYO3eu0fzGxMRg3LhxGDduHLy9veHv748ZM2ZAyp0Fa9myJZYtW6a3XseOHTF79myj6a5fvx4RERFwdXWFn58fYmNjUVRUBADQarVISkpCq1at4OrqisjISKxfv17x+mV15+zsjLvvvhtarRYLFy5EaGgoNBoNWrRogfnz5+uVcfz48XjhhRfg4+ODJk2aYNWqVSgqKsKoUaPg6emJ0NBQfP/993p5uHnzJgYPHoyXX34Z3bt3N1pWW8CATsTT92Rlzz//PPr374/Y2Fi96Y0bN8bq1asxe/Zs/PbbbygsLMTw4cMxbtw49O7dW1HaxcXFSEtL00vbwcEBsbGx2LNnDwAgKSkJp0+fxqlTp/D6668jISEBM2fONJnuBx98ACcnJ+zduxdvvPEGlixZgv/85z9VLPn/5ObmYujQoXj66adx9OhRpKSk4JFHHtH9SEhKSsKHH36IFStW4MiRI3jxxRfx1FNP4eeff1a0PgB89913GDhwIFQqFaZNm4YFCxZgxowZ+OOPP7Bu3To0adKkUhn9/f2xd+9ejB8/HmPHjsXjjz+O7t27Y//+/ejTpw+GDx+Oa9euAQBEBCNHjsQDDzyA4cOHW1wXtUYauPz8fAEg+fn5VkmvLDpQLatY8VX9TDbl+vXr8scff8j169f1Z/zv51ft/Fng008/lfbt2+vy3qtXL5kwYYLeMv/617/kjjvukCeffFIiIiLkxo0bRtMDIBs2bNB9/vvvvwWA7N69W2+5yZMnS7du3Sqtv2bNGnnppZdM5rlXr14SFhYmWq1WN23q1KkSFham+xwSEiJLly7VWy8yMlJmzZqll05ZWdPS0gSAnDp1qtL2bty4IW5ubpXKMHr0aBk6dKjZ9cu0bdtWNm7cKAUFBaLRaGTVqlUmy9izZ0/d51u3bom7u7sMHz5cNy03N1cAyJ49e0REZOfOnaJSqSQyMlL3d+jQIYPpG+2zYv04YwxvWyMispLTp09jwoQJ2LZtG1xcXIwu9/rrr6N9+/b48ssvkZaWBo1GU2N5GjlypKLl7rnnHqjKjRuIjo7G4sWLUVpaCkdHxypvNzIyEr1790ZERATi4uLQp08fPPbYY/Dx8cGJEydw7do1PPjgg3rrFBcXo1OnTmbXB4CjR4/izJkz6N27Nw4dOoSbN2+aPctRfjyDo6Mj/Pz8EBERoZtWdkRfNhahZ8+e0Gq1VS57XeEpd7IPPG1ONiAtLQ3nz59H586d4eTkBCcnJ/z8889488034eTkhNLSUgBAVlYWzpw5A61Wi1OnTlVpG/7+/nB0dMS5c+f0pp87dw6BgYHWKkolDg4Oeqe7AaCkpMTo8o6Ojti2bRu+//57hIeH46233kK7du2QnZ2Nq1evAgA2bdqE9PR03d8ff/yhu45uan3g9un2Bx98EC4uLnB1dVVUBmdnZ73PKpVKb1rZD5r6FMTLY0AnIrKS3r174/Dhw3pBqmvXrhg2bBjS09Ph6OiI4uJiPPXUUxgyZAjmzZuHMWPG6I4IlVCr1ejSpYveIDqtVovk5GRER0dbnPfU1FS9z7/++ivatm2rOzpv3LgxcnNzdfMLCgp0wdUYlUqFHj16YM6cOThw4ADUajU2bNiA8PBwaDQa5OTkIDQ0VO+v/G1hxtYHbo/kHzRoEACgbdu2cHV11auThoin3ImIrMTT0xPt27fXm+bu7g4/Pz/d9FdffRX5+fl488034eHhgc2bN+Ppp5/Gxo0bdetcvXoVJ06c0H3Ozs5Geno6fH190aJFC0ycOBHx8fHo2rUrunXrhmXLlulGa1sqJycHEydOxLPPPov9+/fjrbfewuLFi3XzH3jgAaxduxYDBw5Eo0aNMHPmTJOn4lNTU5GcnIw+ffogICAAqampuHDhAsLCwuDp6YlJkybhxRdfhFarRc+ePZGfn49du3bBy8sL8fHxJtc/f/48fvvtN3z33XcAABcXF0ydOhVTpkyBWq1Gjx49cOHCBRw5cgSjR4+2uE7qGwZ0sk/mTr/z9DzVgZSUFCxbtgw//fQTvLy8AAAfffQRIiMj8e6772Ls2LEAgN9++w3333+/br2JEycCAOLj47F27VoMGTIEFy5cwMyZM3H27Fl07NgRW7ZsqTSquypGjBiB69evo1u3bnB0dMSECRPwzDPP6OZPmzYN2dnZGDBgALy9vTFv3jyTR+heXl7YsWMHli1bhoKCAoSEhGDx4sW6J9fNmzcPjRs3RlJSEk6ePIlGjRqhc+fOeOWVV8yu//7776Nbt27w9/fXbW/GjBlwcnLCzJkzcebMGQQFBeG5556zuD7qI5VUvCjSwBQUFMDb2xv5+fm6L1h1lI0padi1SlQ9N27cQHZ2Nlq1aqU/uKyaD3upsgbyRY6JiUHHjh0r3Wduqx566CH07NkTU6ZMqeus6Bjts7B+nDGGR+hEVH80kABLpvXs2RNDhw6t62zYHAZ0IiKqV2zpyNyWMKATETVwKSkpdZ0FsgLetkZERGQHeIRuZbzER0REdYFH6ERERHaAAZ2IiMgOMKATERHZAQZ0IiIiO8CATkQ2q4E/yJLqEVt4QxtHuRORzXF2doZKpcKFCxfQuHFjvfd0E9kSEUFxcTEuXLgABwcHqNXqOssLAzoR2RxHR0c0a9YMf/31V5XfF05UF9zc3NCiRQs4ONTdiW8GdCKySR4eHmjbti1KSkrqOitEJjk6OsLJyanOzyQxoBORzXJ0dDT5zm0i+h8OiiMiIrIDDOhERER2gAGdiIjIDjT4a+hl97kWFBTUcU6IiMgelcWXmn6uQoMP6IWFhQCA5s2b13FOiIjInhUWFsLb27vG0ldJA38Uk1arxZkzZ+Dp6an4loOCggI0b94cp0+fhpeXVw3nsGawDLaBZbANLIPtsIdyVCyDiKCwsBDBwcE1ep96gz9Cd3BwQLNmzSxa18vLq952uDIsg21gGWwDy2A77KEc5ctQk0fmZTgojoiIyA4woBMREdkBBnQLaDQazJo1CxqNpq6zYjGWwTawDLaBZbAd9lCOuipDgx8UR0REZA94hE5ERGQHGNCJiIjsAAM6ERGRHWBAJyIisgMM6P81e/ZsqFQqvb8777xTN//GjRt4/vnn4efnBw8PDzz66KM4d+6cXho5OTno378/3NzcEBAQgMmTJ+PWrVu1VoaWLVtWKoNKpcLzzz8PAIiJiak077nnnqvTMuzYsQMDBw5EcHAwVCoVvvnmG735IoKZM2ciKCgIrq6uiI2NxfHjx/WWuXz5MoYNGwYvLy80atQIo0ePxtWrV/WWOXToEO699164uLigefPmWLhwYa2UoaSkBFOnTkVERATc3d0RHByMESNG4MyZM3ppGGq7BQsW2EQZAGDkyJGV8te3b1+9ZWy5HQAY/G6oVCosWrRIt0xdt0NSUhLuvvtueHp6IiAgAIMHD0ZmZqbeMtbaF6WkpKBz587QaDQIDQ3F2rVra6UMly9fxvjx49GuXTu4urqiRYsWSExMRH5+vl46htrqs88+s4kyANbbn1q1DEIiIjJr1iy56667JDc3V/d34cIF3fznnntOmjdvLsnJyfLbb7/JPffcI927d9fNv3XrlrRv315iY2PlwIEDsnnzZvH395dp06bVWhnOnz+vl/9t27YJAPnpp59ERKRXr16SkJCgt0x+fn6dlmHz5s3y6quvytdffy0AZMOGDXrzFyxYIN7e3vLNN9/IwYMH5aGHHpJWrVrJ9evXdcv07dtXIiMj5ddff5WdO3dKaGioDB06VDc/Pz9fmjRpIsOGDZPff/9dPv30U3F1dZX33nuvxsuQl5cnsbGx8vnnn0tGRobs2bNHunXrJl26dNFLIyQkRObOnavXNlevXrWJMoiIxMfHS9++ffXyd/nyZb1lbLkdREQv77m5ubJ69WpRqVSSlZWlW6au2yEuLk7WrFkjv//+u6Snp8s//vEPadGihV4erLEvOnnypLi5ucnEiRPljz/+kLfeekscHR1ly5YtNV6Gw4cPyyOPPCLfffednDhxQpKTk6Vt27by6KOP6qUDQNasWaPXFuW/93VZBhHr7E+tXQYG9P+aNWuWREZGGpyXl5cnzs7O8uWXX+qmHT16VADInj17ROT2zsTBwUHOnj2rW+bdd98VLy8vuXnzZo3m3ZgJEyZImzZtRKvVisjtDjhhwgSjy9d1GSruhLVarQQGBsqiRYt00/Ly8kSj0cinn34qIiJ//PGHAJB9+/bplvn+++9FpVLJ33//LSIi77zzjvj4+OiVYerUqdKuXbsaL4Mhe/fuFQDy559/6qaFhITI0qVLja5T12WIj4+XQYMGGV2nPrbDoEGD5IEHHtCbZkvtIHL7RzoA+fnnn0XEevuiKVOmyF133aW3rSFDhkhcXFyNl8GQL774QtRqtZSUlOimmWvDui6DNfan1i4DT7mXc/z4cQQHB6N169YYNmwYcnJyAABpaWkoKSlBbGysbtk777wTLVq0wJ49ewAAe/bsQUREBJo0aaJbJi4uDgUFBThy5EjtFgRAcXExPv74Yzz99NN6L5355JNP4O/vj/bt22PatGm4du2abp6tlSE7Oxtnz57Vq3dvb29ERUXp1XujRo3QtWtX3TKxsbFwcHBAamqqbpn77rsParVat0xcXBwyMzNx5cqVWirN/+Tn50OlUqFRo0Z60xcsWAA/Pz906tQJixYt0js1ZwtlSElJQUBAANq1a4exY8fi0qVLevmrT+1w7tw5bNq0CaNHj640z5baoew0tK+vLwDr7Yv27Nmjl0bZMmVp1GQZjC3j5eUFJyf914s8//zz8Pf3R7du3bB69Wq914/aQhmquz+1dhka/MtZykRFRWHt2rVo164dcnNzMWfOHNx77734/fffcfbsWajV6ko74CZNmuDs2bMAgLNnz+o1XNn8snm17ZtvvkFeXh5Gjhypm/bkk08iJCQEwcHBOHToEKZOnYrMzEx8/fXXunzaUhnKtmkoT+XrPSAgQG++k5MTfH199ZZp1apVpTTK5vn4+NRI/g25ceMGpk6diqFDh+q9eCIxMRGdO3eGr68vdu/ejWnTpiE3NxdLliyxiTL07dsXjzzyCFq1aoWsrCy88sor6NevH/bs2QNHR8d61w4ffPABPD098cgjj+hNt6V20Gq1eOGFF9CjRw+0b99etw1r7IuMLVNQUIDr16/D1dW1xspQ0cWLFzFv3jw888wzetPnzp2LBx54AG5ubti6dSv+9a9/4erVq0hMTLSJMlhjf2rtMjCg/1e/fv10/+/QoQOioqIQEhKCL774wmodoza9//776NevH4KDg3XTyn9hIiIiEBQUhN69eyMrKwtt2rSpi2w2KCUlJfjnP/8JEcG7776rN2/ixIm6/3fo0AFqtRrPPvsskpKSbOIRmE888YTu/xEREejQoQPatGmDlJQU9O7duw5zZpnVq1dj2LBhcHFx0ZtuS+3w/PPP4/fff8cvv/xSq9u1JnNlKCgoQP/+/REeHo7Zs2frzZsxY4bu/506dUJRUREWLVqkC+i1xVgZbHF/ylPuRjRq1Ah33HEHTpw4gcDAQBQXFyMvL09vmXPnziEwMBAAEBgYWGmkadnnsmVqy59//ont27djzJgxJpeLiooCAJw4cQKAbZWh/DYN5al8vZ8/f15v/q1bt3D58mWbapuyYP7nn39i27ZtZl8LGRUVhVu3buHUqVMAbKMM5bVu3Rr+/v56fac+tAMA7Ny5E5mZmWa/H0DdtcO4ceOwceNG/PTTT3qvd7bWvsjYMl5eXlY7gDFWhjKFhYXo27cvPD09sWHDBjg7O5tMLyoqCn/99Rdu3rxpM2WomD+gavtTa5eBAd2Iq1evIisrC0FBQejSpQucnZ2RnJysm5+ZmYmcnBxER0cDAKKjo3H48GG9nVrZjjs8PLxW875mzRoEBASgf//+JpdLT08HAAQFBQGwrTIAQKtWrRAYGKhX7wUFBUhNTdWr97y8PKSlpemW+fHHH6HVanVfsOjoaOzYsQMlJSW6ZbZt24Z27drVymnesmB+/PhxbN++HX5+fmbXSU9Ph4ODg+40dl2XoaK//voLly5d0us7tt4OZd5//3106dIFkZGRZpet7XYQEYwbNw4bNmzAjz/+WOn0vrX2RdHR0XpplC1TlkZNlgG4/T3u06cP1Go1vvvuu0pnSgxJT0+Hj4+P7kxJXZfBUP6Aqu1PrV4Gi4bS2aGXXnpJUlJSJDs7W3bt2iWxsbHi7+8v58+fF5Hbt4q0aNFCfvzxR/ntt98kOjpaoqOjdeuX3aLQp08fSU9Ply1btkjjxo1r9bY1EZHS0lJp0aKFTJ06VW/6iRMnZO7cufLbb79Jdna2fPvtt9K6dWu577776rQMhYWFcuDAATlw4IAAkCVLlsiBAwd0I8AXLFggjRo1km+//VYOHTokgwYNMnjbWqdOnSQ1NVV++eUXadu2rd7tUnl5edKkSRMZPny4/P777/LZZ5+Jm5ub1W41MlWG4uJieeihh6RZs2aSnp6ud4tL2UjX3bt3y9KlSyU9PV2ysrLk448/lsaNG8uIESNsogyFhYUyadIk2bNnj2RnZ8v27dulc+fO0rZtW7lx44YuDVtuhzL5+fni5uYm7777bqX1baEdxo4dK97e3pKSkqLXV65du6Zbxhr7orLbpSZPnixHjx6V5cuXW+2WL3NlyM/Pl6ioKImIiJATJ07oLXPr1i0REfnuu+9k1apVcvjwYTl+/Li888474ubmJjNnzrSJMlhrf2rtMjCg/9eQIUMkKChI1Gq1NG3aVIYMGSInTpzQzb9+/br861//Eh8fH3Fzc5OHH35YcnNz9dI4deqU9OvXT1xdXcXf319eeuklvdswasMPP/wgACQzM1Nvek5Ojtx3333i6+srGo1GQkNDZfLkyXr3TYrUfhl++uknAVDpLz4+XkRu37o2Y8YMadKkiWg0Gundu3elsl26dEmGDh0qHh4e4uXlJaNGjZLCwkK9ZQ4ePCg9e/YUjUYjTZs2lQULFtRKGbKzsw3OQ7nnA6SlpUlUVJR4e3uLi4uLhIWFyb///W+9YFmXZbh27Zr06dNHGjduLM7OzhISEiIJCQl6t+OI2HY7lHnvvffE1dVV8vLyKq1vC+1grK+sWbNGt4y19kU//fSTdOzYUdRqtbRu3VpvGzVZBmPtBECys7NF5PYtjx07dhQPDw9xd3eXyMhIWbFihZSWltpEGay5P7VmGfj6VCIiIjvAa+hERER2gAGdiIjIDjCgExER2QEGdCIiIjvAgE5ERGQHGNCJiIjsAAM6ERGRHWBAJyIisgMM6ERERHaAAZ3Izr388svQaDR48sknFS0fExMDlUoFlUqle+FETRk5cqRuW998802NbovI3jGgE9m5adOmYfHixfj00091r3Y0JyEhAbm5uWjfvn2N5u2NN95Abm5ujW6DqKFgQCeyc97e3hg9ejQcHBxw+PBhReu4ubkhMDAQTk5ONZ63unifO5E9YkAnagBu3boFNzc3/P777xatHxMTg8TEREyZMgW+vr4IDAzE7NmzKy0zfvx4vPDCC/Dx8UGTJk2watUqFBUVYdSoUfD09ERoaCi+//57K5SIiCpiQCdqAKZPn46rV69aHNAB4IMPPoC7uztSU1OxcOFCzJ07F9u2bau0jL+/P/bu3Yvx48dj7NixePzxx9G9e3fs378fffr0wfDhw3Ht2rXqFomIKmBAJ7JzaWlpWLFiBfr371+tgN6hQwfMmjULbdu2xYgRI9C1a1ckJyfrLRMZGYnp06ejbdu2mDZtGlxcXODv74+EhAS0bdsWM2fOxKVLl3Do0KHqFouIKmBAJ7JjWq0Wzz77LMaNG4cRI0bg+PHjKCkpsSitDh066H0OCgrC+fPnjS7j6OgIPz8/RERE6KY1adIEACqtR0TVx4BOZMfeeustXLx4EXPnzkVERARKSkqQkZFhUVrOzs56n1UqFbRardllyk9TqVQAUGk9Iqo+BnQiO/X3339jxowZWL58Odzd3dG2bVtoNJpqnXYnItvFgE5kpxITE9GvXz/0798fAODk5ISwsDAGdCI7VbM3mRJRndi4cSN+/PFHHD16VG96REQEAzqRnVKJiNR1JojIdsTExKBjx45YtmxZrW1TpVJhw4YNGDx4cK1tk8je8JQ7EVXyzjvvwMPDQ/GT5Sz13HPPwcPDo0a3QdRQ8AidiPT8/fffuH79OgCgRYsWUKvVNbat8+fPo6CgAMDt2+Dc3d1rbFtE9o4BnYiIyA7wlDsREZEdYEAnIiKyAwzoREREdoABnYiIyA4woBMREdkBBnQiIiI7wIBORERkBxjQiYiI7AADOhERkR1gQCciIrIDDOhERER2gAGdiIjIDjCgExER2QEGdCIiIjvAgE5ERGQHGNCJiMgia9euxdq1a+s6G/RfFgf0mJgYvPDCC1bMCpljaZ2XX69iGiKCZ555Br6+vlCpVEhPTzc4jfQpqaOG+B0xV+aaqpP6Xte1mf9Lly4hICAAp06dqvFtPfHEE1i8eHGNb4duMxnQR44cCZVKVenvxIkT+PrrrzFv3jyrZ2jHjh0YOHAggoODoVKp8M0331iUzoULFzB27Fi0aNECGo0GgYGBiIuLw65du6ybYTNsbUdTsd22bNmCtWvXYuPGjcjNzUX79u0NTiN9rCOyppranxoyf/58DBo0CC1btgRwez8/ePDgSsulpKRApVIhLy/P4m1Nnz4d8+fPR35+vsVpkHJO5hbo27cv1qxZozetcePGcHR0rJEMFRUVITIyEk8//TQeeeQRi9N59NFHUVxcjA8++ACtW7fGuXPnkJycjEuXLlkxt9ZRXFwMtVpdK9vy9fXV+5yVlYWgoCB0797d5DRL1Ga5apu16qgm2XP9V5Wt10XF72VNuXbtGt5//3388MMPFqdRXFyMbt26AQAuX74MAFi2bBkAYO/evXr13L59e7Rp0wYff/wxnn/+ecszToqYPeVednRb/s/R0bHSkWdhYSGGDRsGd3d3BAUFYenSpRYdnfbr1w+vvfYaHn744aqWRScvLw87d+7E//t//w/3338/QkJC0K1bN0ybNg0PPfSQbrmYmBiMGzcO48aNg7e3N/z9/TFjxgyICABAq9UiKSkJrVq1gqurKyIjI7F+/Xq9bWm1WixcuBChoaHQaDRo0aIF5s+fD+D2L9+ff/4Zb7zxhu7sxqlTp3TbfeGFF+Dv74+4uDgAt4/6evbsiUaNGsHPzw8DBgxAVlZWlcpeVFSEESNGwMPDA0FBQZVOd5Vvk5EjR2L8+PHIycmBSqVCy5YtDU5TWheGyqV0vcTEREyZMgW+vr4IDAzE7NmzFdezkm2sX78eERERcHV1hZ+fH2JjY1FUVGSwDm/evInExEQEBATAxcUFPXv2xL59+3TzjdWROUra11Q+zZXTWL+yJB9K2sRcXzNGq9UaTffDDz+En58fbt68qbfO4MGDMXz4cMXbNVQX5toVULYfU9IO5urOUH7Lb0NJXi3ZzubNm6HRaHDPPfeYXM4UtVqN9PR0pKenY+7cuZg7d67us6EfTQMHDsRnn31m8faoCsSE+Ph4GTRokMF5vXr1kgkTJug+jxkzRkJCQmT79u1y+PBhefjhh8XT01NvmaoCIBs2bKg0fc2aNWIq6yUlJeLh4SEvvPCC3Lhxw+hyvXr1Eg8PD5kwYYJkZGTIxx9/LG5ubrJy5UoREXnttdfkzjvvlC1btkhWVpasWbNGNBqNpKSk6NKYMmWK+Pj4yNq1a+XEiROyc+dOWbVqlYiI5OXlSXR0tCQkJEhubq7k5ubKrVu3dNudPHmyZGRkSEZGhoiIrF+/Xr766is5fvy4HDhwQAYOHCgRERFSWlqqy6+5+hw7dqy0aNFCtm/fLocOHZIBAwbotUP5NPLy8mTu3LnSrFkzyc3NlfPnzxucprQuDJVL6XpeXl4ye/ZsOXbsmHzwwQeiUqlk69atiurZ3DbOnDkjTk5OsmTJEsnOzpZDhw7J8uXLpbCw0GAdJiYmSnBwsGzevFmOHDki8fHx4uPjI5cuXTJab8b6V/n2Mte+5vJprpzG+lVF5vKhtE3M9TVjdWIq3WvXrom3t7d88cUXunXOnTsnTk5O8uOPPyrerqG6MNeuIsr2Y0rawVzdGaqX8ttQkldLtpOYmCh9+/bVm2ZsP//TTz8JALly5YrR9NasWSNr1qwxOl9E5Pvvvxe1Wm1yX0zWYTagOzo6iru7u+7vscceExH9DlhQUCDOzs7y5Zdf6tbNy8sTNze3GgnoX3/9tbRr187kuuvXrxcfHx9xcXGR7t27y7Rp0+TgwYN6y/Tq1UvCwsJEq9Xqpk2dOlXCwsLkxo0b4ubmJrt379ZbZ/To0TJ06FARuV1ujUajCyyGGArCvXr1kk6dOpnMv4jIhQsXBIAcPnzYaFrlFRYWilqt1tsZXrp0SVxdXQ0GdBGRpUuXSkhIiF46FacpqQtD5arKej179tRb5u6775apU6eKiOl6VrKNtLQ0ASCnTp2qtH5FV69eFWdnZ/nkk09004qLiyU4OFgWLlyom2ao3ioy114V29dUPpWUU2m/MpePsrRMtYmSvmaIuXRFbgfsfv366T4vXrxYWrduLVqtVvF2K9aFknZVsh9T2g7mymioXsq2obQPWrKdQYMGydNPP603zdB+3t3dXVxcXKwS0A8ePKj4+0fVY/Ya+v333493331X99nd3b3SMidPnkRJSYnuugoAeHt7o127dtU5eWDUww8/bPaU/KOPPor+/ftj586d+PXXX/H9999j4cKF+M9//oORI0fqlrvnnnugUql0n6Ojo7F48WKcOHEC165dw4MPPqiXbnFxMTp16gQAOHr0KG7evInevXtXuQxdunSpNO348eOYOXMmUlNTcfHiRWi1WgBATk6OokFXWVlZKC4uRlRUlG6ar69vtdtBSV2UKV+uqqzXoUMHvc9BQUE4f/48ANP1rGQbkZGR6N27NyIiIhAXF4c+ffrgscceg4+PT6X0srKyUFJSgh49euimOTs7o1u3bjh69Gil5avCXPuayqfSujTUr6qajzKm2qQ6fc1UugCQkJCAu+++G3///TeaNm2KtWvX6gboVmW75etCSbsq2Y8pbQdzZTSlKn2wqtu5fv06XFxcKk2vuJ8HgNTUVDz11FMm81p+X2qMq6srgNvX76lmmQ3o7u7uCA0NrY28WJ2LiwsefPBBPPjgg5gxYwbGjBmDWbNmKeqEV69eBQBs2rQJTZs21Zun0WgA/K+jWsLQD6OBAwciJCQEq1atQnBwMLRaLdq3b4/i4mKLt2MNSuqiTPlyVWU9Z2dnvc8qlUoXaEzVs5JtODo6Ytu2bdi9eze2bt2Kt956C6+++ipSU1PRqlUro2lbm7n2NZVPpXVpqF9VNR9lTLVJdZhLt1OnToiMjMSHH36IPn364MiRI9i0aVOVt6OkLqpKaTvUVN1VVNXt+Pv748qVK5WmG9rP//XXX1bJY9nAucaNG1slPTLOKg+Wad26NZydnfUGbeTn5+PYsWPWSN5qwsPDKw2ESk1N1fv866+/om3btggPD4dGo0FOTg5CQ0P1/po3bw4AaNu2LVxdXZGcnGx0m2q1GqWlpWbzdunSJWRmZmL69Ono3bs3wsLCDH7xTGnTpg2cnZ31ynTlypVqt4OSurDmehWZqmel21CpVOjRowfmzJmDAwcOQK1WY8OGDZXSa9OmDdRqtd7tjSUlJdi3bx/Cw8MV57kipe1rLJ/Wqktr9DOg5vpamTFjxmDt2rVYs2YNYmNjdWW0dLtK2lXJfsxa7VDdvFqqU6dO+OOPP6qbxSr5/fff0axZM/j7+9fqdhsis0foSnh6eiI+Ph6TJ0+Gr68vAgICMGvWLDg4OOidzn777bexYcMGkwHw6tWrOHHihO5zdnY20tPT4evrixYtWgAANmzYgGnTpiEjI8NgGpcuXcLjjz+Op59+Gh06dICnpyd+++03LFy4EIMGDdJbNicnBxMnTsSzzz6L/fv346233sLixYvh6emJSZMm4cUXX4RWq0XPnj2Rn5+PXbt2wcvLC/Hx8XBxccHUqVMxZcoUqNVq9OjRAxcuXMCRI0cwevRoAEDLli2RmpqKU6dOwcPDw+jtKT4+PvDz88PKlSsRFBSEnJwcvPzyy8oa4L88PDwwevRoTJ48GX5+fggICMCrr74KB4fq/W5TUhfWXK8ic/VsbhupqalITk5Gnz59EBAQgNTUVFy4cAFhYWGVtuXu7o6xY8fq+nKLFi2wcOFCXLt2TdemllDSvqbyaa26tEY/A2qur5V58sknMWnSJKxatQoffvhhtberpF2V7Mes1Q7Vzaul4uLiMG3aNFy5csXgJaeasHPnTvTp06dWttXQWSWgA8CSJUvw3HPPYcCAAfDy8sKUKVNw+vRpves1Fy9eNHsb1m+//Yb7779f93nixIkAgPj4eN0jBvPz85GZmWk0DQ8PD0RFRWHp0qW661HNmzdHQkICXnnlFb1lR4wYgevXr6Nbt25wdHTEhAkT8MwzzwAA5s2bh8aNGyMpKQknT55Eo0aN0LlzZ700ZsyYAScnJ8ycORNnzpxBUFAQnnvuOd38SZMmIT4+HuHh4bh+/Tqys7MN5tnBwQGfffYZEhMT0b59e7Rr1w5vvvkmYmJiTNZXRYsWLcLVq1cxcOBAeHp64qWXXrLKQx2U1IU116vIVD2b24aXlxd27NiBZcuWoaCgACEhIVi8eDH69etncFsLFiyAVqvF8OHDUVhYiK5du+KHH36o1g5QSfuay6c16tJa/Qyoub4G3L52/eijj2LTpk2VHnpi6XaVtKuS/Zi1+nR182qJiIgIdO7cGV988QWeffZZK+XWuBs3buCbb77Bli1banxbBKhE/nvTtZUVFRWhadOmWLx4cbV/VdaUmJgYdOzYUfdQBCKyHb1798Zdd92FN998s87yUB/2Y1W1adMmTJ48Gb///rvVzqgY8+6772LDhg3YunVrjW6HbrPaEfqBAweQkZGBbt26IT8/H3PnzgWASqe4iYhMuXLlClJSUpCSkoJ33nmnVrfdEPZj/fv3x/Hjx/H3339b7bq/Mc7OznjrrbdqdBv0P1YL6ADw+uuvIzMzE2q1Gl26dMHOnTs5EIKIqqRTp064cuUK/t//+381duurKQ1hP1Zb75cYM2ZMrWyHbquxU+5ERERUe/g+dCIiIjvAgE5ERGQHGNCJiIjsAAM6ERGRHWBAJyIisgMM6ERERHaAAZ2IiMgOMKATERHZAZMBPSYmptaeKGRoe9bafm2XozZZUjZ7ro+GjO1a8yytY1trGxHBM888A19fX6hUKqSnp9tcHqnqTAb0r7/+GvPmzautvFR7+8Y6ZF2VY+TIkVCpVJX++vbtW+t5oeqprZ2d0u1w52ub6ku7bNmyBWvXrsXGjRuRm5uL9u3bW30b9aUujOnVq5dun61WqxEWFoZ169bVdbZMMhnQfX194enpaXBecXFxlaZbwtT26yIdS/Tt2xe5ubl6f59++mmd5KUmWbPdiZRiv9OntD6ysrIQFBSE7t27IzAwEE5OVn2tR70nIjhw4ABef/115ObmIjMzE3379sWIESOMvgLbFig+5R4TE4Nx48bhhRdegL+/P+Li4kxO37JlC3r27IlGjRrBz88PAwYM0HsXelFREUaMGAEPDw8EBQVh8eLFJrdvLs2RI0fi559/xhtvvKH7VXXq1CmD6dy8eROJiYkICAiAi4sLevbsiX379ultNzExEVOmTIGvry8CAwMxe/ZsxZVankajQWBgoN5f+Xcam6snrVaLhQsXIjQ0FBqNBi1atMD8+fP1tqHVaquc11u3bmHcuHHw9vaGv78/ZsyYgfKP9TeXL2PtXpG5/FujLZQso9VqkZSUhFatWsHV1RWRkZFYv369orya6lvr169HREQEXF1d4efnh9jYWBQVFRmsC3N1amo75ZlazlxfUFIPFbVs2bLSK4Y7duyol3ZZfzDWp8zNV5q3qvQ7U2kp6TNK9lHlmWu/mmgbQ/VhLp2RI0di/PjxyMnJgUqlQsuWLS2qQ1PfbWN1Ye47UFYmJd9nY9u2pB4rOn78OAoLC9G3b18EBgaiVatWGD16NEpLS5GZmVmltGqVmNCrVy+ZMGGC7v8eHh4yefJkycjIkIyMDJPT169fL1999ZUcP35cDhw4IAMHDpSIiAgpLS0VEZGxY8dKixYtZPv27XLo0CEZMGCAeHp66rZXcfvm0szLy5Po6GhJSEiQ3Nxcyc3NlVu3bhlMJzExUYKDg2Xz5s1y5MgRiY+PFx8fH7l06ZJueS8vL5k9e7YcO3ZMPvjgA1GpVLJ161ZT1VVJfHy8DBo0yOQy5uppypQp4uPjI2vXrpUTJ07Izp07ZdWqVXp1VNW8lrXZhAkTJCMjQz7++GNxc3OTlStXKs6XsXavyFz+rdEWSpZ57bXX5M4775QtW7ZIVlaWrFmzRjQajaSkpJjNq7G+debMGXFycpIlS5ZIdna2HDp0SJYvXy6FhYUWtbWpPlyeseWsVQ8VhYSEyNKlS/WmRUZGyqxZs/TawFSfUtLnlORNab8zl5aSulKyj1LSLkq3Z0nbGKoPc+nk5eXJ3LlzpVmzZpKbmyvnz5/XpVW+bObSMfXdNlYX5r4DSuvK1LYtqceK1q1bJz4+PqLVakVE5PTp0/LQQw+JRqORv//+W3E6ta1KAb1Tp04GlzE0vaILFy4IADl8+LAUFhaKWq2WL774Qjf/0qVL4urqajKgm0rT1PLlp1+9elWcnZ3lk08+0c0vLi6W4OBgWbhwoW75nj176qVx9913y9SpU82Ws7z4+HhxdHQUd3d3vb/58+crKlNBQYFoNBq9AGiobFXNa69evSQsLEzXWUVEpk6dKmFhYYryVZaGuXY3l39rtYW5ZW7cuCFubm6ye/duvWVGjx4tQ4cOVZRXQ30rLS1NAMipU6eMVYFJFevU2HaU5sca9WCI0oBuqk+Zm680b0r6nZK0zNWV0n1URab2QTXRNhXrQ2k6S5culZCQEKN5N5eO0n2Tub5s7Dtgqq5MbdvSeqxo0qRJ4uDgIO7u7uLi4iIAxNXVVdasWaM4jbpQpQsnXbp0UTz9+PHjmDlzJlJTU3Hx4kVotVoAQE5ODkpLS1FcXIyoqCjd8r6+vmbffWwqTaWDOrKyslBSUoIePXropjk7O6Nbt244evSoblqHDh301gsKCsL58+cVbaO8+++/H++++67eNF9fX0VlunbtGm7evInevXub3IYleb3nnnugUql0n6Ojo7F48WKUlpbC0dFRUV0b6w9ljh49ajL/1mwLU8ucOHEC165dw4MPPqi3THFxMTp16qQor4ZERkaid+/eiIiIQFxcHPr06YPHHntM75JKedbov+ZUtx6qw1SfMje/Knkz1++UpmWqrrKysizaR5lSU21Tvj6s1cbm0rHk+wIo/w6YqitT27ZW+ffv34/nn38eiYmJyMvLw6RJk9CjRw+MHDlScRp1oUoB3d3dXfH0gQMHIiQkBKtWrUJwcDC0Wi3at29frUEsNZGmMc7OznqfVSqVrvNVhbu7O0JDQ43ON1UmV1fXWs2r0nyVMdYfyijNvzlKymdqmatXrwIANm3ahKZNm+otp9FoLM6ro6Mjtm3bht27d2Pr1q1466238OqrryI1NRWtWrWqtHxt9N/q1oMhDg4Oete6AaCkpMQa2dWpSt7M9TuladXE98aUmmgbQL8+qpNOeebSycvLU5xWeUq/A6bqytR31Vrl379/PxISEnT77nfeeQcdOnRAQkKC0TEHtqBGHixz6dIlZGZmYvr06ejduzfCwsJw5coV3fw2bdrA2dkZqampumlXrlzBsWPHLE4TANRqte5owJg2bdpArVZj165dumklJSXYt28fwsPDq1rUajFXprZt28LV1RXJyclW33b5ugeAX3/9FW3btoWjo6OiulbCXP5rqy3Cw8Oh0WiQk5OD0NBQvb/mzZsryquxvqVSqdCjRw/MmTMHBw4cgFqtxoYNGyotp7ROlfThqixXnpJ6MKRx48bIzc3VfS4oKDA40tdUnzI339K8WbOc5VmyjwIsaxdr5bk201Gyb6pYF7WxX7FG+U+ePIm8vDy9Mwbh4eFo06aNzd+2ViP3Kvj4+MDPzw8rV65EUFAQcnJy8PLLL+vme3h4YPTo0Zg8eTL8/PwQEBCAV199FQ4Oxn9fmEsTuD0aNzU1FadOnYKHhwd8fX0rpenu7o6xY8di8uTJ8PX1RYsWLbBw4UJcu3YNo0ePVlzGt99+Gxs2bDAbbG/evImzZ8/qTXNycoK/v7/ZMrm4uGDq1KmYMmUK1Go1evTogQsXLuDIkSNVyqshOTk5mDhxIp599lns378fb731lm4Ur5K6VsJc/q3VFuZ4enpi0qRJePHFF6HVatGzZ0/k5+dj165d8PLyQnx8vNm8Gupb+/btQ3JyMvr06YOAgAC