Impact of Agroforestry Leaf Mulches on the Growth and Yield Performance of Sorghum in a Semi-Arid Region

Impact of Agroforestry Leaf Mulches on the Growth and Yield Performance of Sorghum in a Semi-Arid Region | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of Agroforestry Leaf Mulches on the Growth and Yield Performance of Sorghum in a Semi-Arid Region Olufemi Zaccheaus ADELEYE This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7411848/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Soil nutrients are essential chemical elements that support plant growth guaranteed by agroforestry systems with the production of leaf mulch to improve soil properties. Adopting agroforestry as a sustainable soil management practice has the potential to improve soil property and structure. Existing studies in the use of specific agroforestry tree leaves as mulch for its soil fertility improvement potential in sorghum cultivation are inadequate. This study assessed the effect of leaf mulch from selected agroforestry tree species on sorghum agronomic performance. The study adopted a 3x3x4 factorial layout in a randomized complete block design. Three varieties of sorghum seeds (NGB05843, NGB05731, NGB06187) were planted on 39 raised beds (12 treatments with one control per block), evenly overlaid with fresh leaf-mulches of uniform age from four agroforestry tree ( Leucaena leucocephala, Artocarpus altilis, Sesbania grandiflora , and Moringa oleifera ) species at application rates of 1.50, 2.00 and 2.50 kilograms. Data collected were analyzed using descriptive and inferential statistics at 5% significance level. Findings revealed that the control plot had the highest sorghum seed weight (68.50 g) against treatment plots ( A. altilis (65.00 g), M. oleifera (57.30 g), S. grandiflora (52.00 g), L. leucocephala (42.67 g)). Sorghum variety, mulch type and application rate significantly influenced growth and yield. The study concluded that, agroforestry mulches significantly improved sorghum growth and grain yield. A. altilis and M. oleifera mulches were more effective in promoting sorghum development. Farmers are encouraged to adopt the use of agroforestry tree species leaf as mulch to assist in soil nutrient improvement. Agroforestry Mulching Sorghum Crop yield Organic amendment Sustainable agriculture agronomic performance INTRODUCTION Sorghum is a drought-tolerant cereal widely grown in semi-arid regions of Africa and Asia. Despite its resilience, sorghum yields in smallholder systems remain low, mainly due to poor soil fertility and inadequate management practices (Wortmann et al., 2009 ). Organic mulching has emerged as a sustainable technique for improving soil health and crop productivity. Agroforestry trees such as Moringa, Leucaena, and Sesbania offer locally available biomass that can be used as mulch. This study aims to evaluate the effects of leaf mulch from selected tree species on the growth and yield of sorghum in a semi-arid environment. Agroforestry has risen to prominence as a land-use strategy to help address global climate change and provide other environmental, economic, and social benefits. However, systematic knowledge on the human environment impacts of agroforestry practices and interventions remains lacking. Agroforestry is promoted for its potential for carbon sequestration, soil erosion and control, improved nutrient and water cycling, as well as other socio-economic benefits and greater agricultural productivity (Akinnifesi et al., 2007). While researchers and policy makers have long studied and supported agroforestry practices in low and middle-income countries, particularly in tropical regions, recognition and promotion of agroforestry in the temperate climates typical of developed countries gained prominence in the early 21st century (Jose et al., 2012). The production of Sorghum in sub-Saharan Africa has been comparatively low due to biotic and abiotic stresses (Teshome et al., 2018) such as drought, low soil fertility, and high soil acidity as the major abiotic stresses capable of causing significant yield losses in sorghum and biotic stresses (diseases and insect pests) (Amelework et al., 2016 ). It is a known fact that cassava and maize are staple foods in South-Western Nigeria which might bare the occasion to wonder; what is the importance of sorghum to the south west, Nigeria? What is the growing interest in sorghum cultivation about? The cultivation of sorghum has traditionally been majorly in Northern Nigeria because of the favorable agro-climatic conditions. But, over the time, there has been an increasing interest in the production of sorghum in the South-West Nigeria due to such factors as Industrial demand, supply-chain efficiency, national production deficit, increase in population and regional migration. These are parts of the major driver for this shift in sorghum production. The demand for Sorghum as a result of growing industrial need in South-West, Nigeria for breweries and beverages has grown significantly in the recent years. Sorghum grits are widely used as substitutes for barley in the production of alcoholic and non-alcoholic beverages by many beverage companies, such as Nigerian Breweries and Guinness Nigeria. These had increased the demand to source sorghum locally so as to reduce costs and comply with government policies on raw material sourcing (Blueprint, 2024). Sorghum is a key ingredient in food processing industries for the production of composite flour which is used in the production of food such as bread, biscuits and noodles. Increasing consumer demand for this food and produce in South-West, Nigeria has become one of the major drivers for an increased demand for sorghum (Daily Trust, 2024). Sorghum is also used in livestock feed, aluminum ore refining, and construction materials. This has further increased its industrial relevance, increasing the demand for its production in the south west, Nigeria (FAO, 2023). It is a well-established fact that Nigeria is one of the world’s largest production hubs for sorghum, but the current production levels do not meet domestic demand. The Minister of Agriculture and Food Security recently noted that national sorghum production is insufficient to meet both food and industrial needs. This was noted to be as a result of low productivity, poor seed quality, and post-harvest losses (Daily Trust, 2024). Increased industrial reliance on sorghum has created supply gaps, making localized production in the South-West, a strategic move to supplement existing sources (FAO, 2023). The South-West, region hosts a significant number of food processing industries, breweries, and animal feed manufacturers. Establishing local sorghum farms will yield several benefits such as; Reduction in transportation costs: Local production would remove transportation expenses and ensure a more stable supply as against sourcing from Northern Nigeria with its high logistics costs (Blueprint, 2024). Insecurity, Political instability, climate change, and infrastructural challenges in the North occasionally disrupt sorghum production and supply. Cultivating sorghum in the South-West, will ensure a secondary production hub, thereby causing supply stability (Daily Trust, 2024). Nearness to processing plants will enhance product freshness and efficiency in industrial processing (FAO, 2023). While sorghum cultivation in South-West, Nigeria faces significant challenges related to awareness, pest control and market access, the Nigerian government has implemented various policies to promote sorghum cultivation, aiming to meet rising industrial demand and achieve national self-sufficiency in grain production. These initiatives focus on improving productivity, financing, and seed quality to support farmers across different regions, including the South-West. Agricultural Transformation Agenda (ATA)- Launched in 2011, identified sorghum as one of five priority crops for development. Its aim was to; Increase sorghum production from 9.3 million metric tons to 11.3 million metric tons by 2015, focusing on modernizing agriculture through public-private partnerships (Aderemi, 2023). Encourage private-sector investment in sorghum processing industries, particularly in flour mills and breweries. Agricultural Transformation Action Plan (ATAP)- Introduced in 2011, emphasized agriculture as a key driver of economic growth and planned to recognize sorghum as a strategic crop, with a focus on: Production of fortified foods for the Home-Grown School Feeding Program and the World Food Program. Expand the use of sorghum in the malt industry for beverage production (FAO, 2023). Anchor Borrowers’ Program (ABP)- launched by the Central Bank of Nigeria (CBN) and the Federal Ministry of Agriculture and Rural Development (FMARD), provides: Zero-interest loans and farm inputs to smallholder farmers cultivating priority crops, including sorghum and provide training and support for modern sorghum farming techniques. In 2021, the program supported approximately 1.2 million farmers nationwide, with plans to increase beneficiaries to 5 million by 2022 (USDA, 2022). Seed System Enhancement for Sorghum- the Nigerian government, in partnership with the Institute for Agricultural Research (IAR) and the International Maize and Wheat Improvement Center (CIMMYT), introduced improved sorghum varieties such as: SAMSORG 52 and SAMSORG 53 – high-yield, drought-tolerant varieties suitable for Nigeria’s agro-ecological zones. The Farm and Community-Managed Seed System (FCMSS) approach has strengthened access to high-quality seeds, increasing yields and reducing dependency on imports (CIMMYT, 2023). The government of Nigeria provides incentives, such as tax breaks and subsidies, to industries using locally grown sorghum for production and encouraged partnerships between research institutions, private companies, and farmer cooperative societies to boost production, processing and storage facilities in regions like the South-West (Aderemi, 2023). Efforts to boost the adoption of sorghum in South-West Nigeria include awareness campaigns highlighting its nutritional and economic benefits. Agricultural shows and exhibitions have also been used to promote improved sorghum varieties, and partnerships with industries such as flour millers and breweries have explored to increase demand (CGIAR, 2023 ). The reviewed literatures showed that application of mulches has been addressed but, existing studies in the use of specific agroforestry tree leaves as mulch for its soil fertility improvement potential in sorghum cultivation are lacking. This study therefore, aims to fill in this missing gap in literature. The word mulch has been derived from the German word “ molsch ” which means “easy to decay,” and mulches have widely been used for vegetable production since ancient times (Lightfoot, 1994). Mulching is referred to as spreading various covering materials on the surface of soil to minimize moisture losses, reduce weed population and to enhance crop yield (Kader et al., 2019 ; Nalayini, 2007 ). Mulches could potentially minimize water runoff, improve infiltration capacity of soil, restrain weed population via shading, and act as obstacle in evapotranspiration (Rathore et al., 1998 ). Mulching also has some other positive environmental effects such as temperature regulation of soil and plant roots, minimize nutrient losses, cut down soil erosion and compactness, and improved physical conditions of soil (Ngouajio & McGiffen, 2004 ). Mulches got attention in the late 1930, though in a negative sence when it was observed that these materials could alter the surrounding conditions of agricultural lands, forest areas, and horticultural lands. Some earlier studies showed a number of such damaging effects caused by mulches (Bedford & Pickering, 1919). In 1941, deep mulches were used for trees and shrub plantation (Pirone, 1941), because these deep-type mulches give protection to drought stress such as frost injury and freezing damage of crop plants in harsh environmental conditions. More water conservation was achieved when the same quantity of material was used as mulch compared with what was incorporated into the soil (Singh et al., 1991 ). The by-products of agricultural and forestry domains have been used as mulches in the mid-1900s (18th century) (Clifford & Massello, 1965 ). Other materials gained popularity and were used as mulch such as trimmings of trees and shrubs, wastes of animals, stubbles, and residues of crop plants. Landscape mulches were also seen in 1957 but there was no scientific research work carried out on them. Mulches could be of organic, inorganic and synthetic origin. The organic mulches consist of animal and plant residues. The most commonly used organic mulches include straws, husks, grasses and cover crops (live mulches), saw dust, compost, and manures (Rathore et al., 1998 ), A mulch is a layer of material applied to the surface of soil for the sole purpose of soil moisture conservation, fertility improvement, weed management, erosion control etc. There are three basic kinds of mulch: organic, inorganic and synthetic: Organic mulches include formerly living material such as chopped leaves, straw, grass clippings, compost, wood chips, shredded bark, sawdust, pine needles and even paper. In addition to weed suppression, organic mulch improves the soil as they decompose. Inorganic mulches include non-living materials such as stones, pebbles, slabs etc., while synthetic mulch includes black plastic and geotextiles (landscape fabrics). Inorganic and synthetic mulches do not break down to enrich the soil (Dan, 2022). Mulches have been widely used in agricultural lands, orchards, forests, and landscapes in many parts of the world (Smith et al., 2012 ). Generally, mulches reduce competition from weeds, maintain soil temperature, and reduce evaporation from soil (Jose et al., 2012). Mulches protect the soil from wind, water, and traffic-induced erosion. Mulches also improve soil properties by improving moisture retention capacity, releasing different nutrients, and enhancing biological activities (Garrity, 2004 ). Therefore, with the improved soil properties, plants grow better (Jose 2009 ; Jose & Bardhan, 2012 ). The capability of mulching in the control of nutrient level absorption, temperature and water level of the soil makes it multifunctional (Petrikovszki et al., 2016 ). But for mulch to yield effective results in agricultural practices, some basic requirements must be met, such as the source, allelopatic effect, decay efficiency, etc. Mulch, most importantly, should help conserve soil moisture and improve nutrient obtainability as well regulate soil temperature (Manzello et al., 2014 ), even though various types of organic mulch have different effects on weed control, plant growth, and soil properties (Jodaugiene et al., 2006 ), unfortunately, little or nothing has been done in assessing the problems faced by agroforestry adopters which could be a strong determinant of food security and soil sustainability in Nigeria. This study therefore, was carried out to determine the effects of different organic mulches on weed presence in reference to sorghum agronomic performance and soil characteristics. MATERIALS AND METHODS The study was carried out at the Teaching and Research Farm of Babcock University. Babcock University is situated in Ilishan-Remo (latitude 6°53’44” N and longitude 3°43’18” E) 80m elevation in Ikenne Local Government Area of Ogun State. The Local Government was carved out of the defunct Remo Local Government in September 1991, it is bounded in the West by Obafemi-Owode Local Government, in the South by Sagamu Local Government, in the East by Odogbolu Local Government and in the North by Remo-North Local Government. The inhabitants are mainly of remo origin, trading and farming are their predominant occupation, with a population of 202,980 according to National Population Commission report of 2006. (Adeleye & Okezie, 2012 ) Experimental Material Seed Collection Three cultivars of sorghum Seeds (NGB05843, NGB05731 and NGB06187) were collected from the National Centre for Genetic Resources and Biotechnology (NACGRAB), Ibadan, Oyo State, Nigeria. The accessions represent part of the institutional working germplasm collections which were grown locally by farmers in Nigeria. Mulch Collection Fresh leaves of four agroforestry ( L. leucocephala , A. altilis, S. grandiflora, M. oleifera) trees species were collected. L. leucocephala , A. altilis and M. oleifera were collected from Forest Research Institute of Nigeria (FRIN), Ibadan Nigeria, while S. grandiflora was collected from the National Horticulture Research Institute (NIHORT). All leaves were from trees of relatively uniform age, because they were collected from plantations. A total of 18 kg of each species of mulch was used for the experiment. Methods Field Preparation, Experimental Design and Cultural Practices The experimental field of 40.5 m 2 was manually prepared at the onset of rainy season in May. The layout of the experimental plot was set up using pegs, lines and measuring tapes. The field was divided in three (3) blocks consisting of thirteen (13) raised beds per block, measuring 0.18 m 2 with inter bed distance of 0.6 m and inter block distance of 0.9 m between blocks respectively. The study consisted of a 3 x 3 x 4 factorial experiment laid out following a randomized complete block design and replicated three times (Table 3.1). The factors in the experiment were varieties of Sorghum namely NGB05843, NGB05731 and NGB06187. The levels of mulch applied were 1.50 kg, 2.00 kg, 2.50 kg, and the agroforestry tree species were L, leucocephala , A. altilis, S. grandiflora, M. oleifera serving as treatments. The control plots were without treatment. There was a total of 39 raised beds (13 per block including 1 control) of which each agroforestry species leaf was used to mulch each raised bed in three (3) replicates in the weight of 1.50 kg, 2.00 kg and 2.50 kg, evenly spread in not less than 2cm thick (measured with a meter rule), for each of the 3 varieties of the sorghum crop planted (Table 1 ). The agroforestry tree species leaves were applied to the prepared raised beds and allowed about three weeks before planting to allow onset of decomposition so as to prevent nitrogen depletion and soil acidity, allowing proper air and water flow (Addai & Alimiyawo, 2015; Thompson & Myers, 2021). Mulch Volume Determination In the establishment of the volume of fresh mulch application, 5 cm depth was applied as recommended by the USDA Natural Resources Conservation Services (2017). Therefore, Mulch volume was calculated as follows Volume = L x B x W (where L and B are the length and breadth of the raised bed and W is the recommended width of mulch). Therefore, V = 0.30 m x 0.60 m x 0.05 m = 0.009 m 3 The density of applied fresh leaf mulch = D X V. where D is the given density and V is the volume derived. The standard volume for fresh mulch application is 200 kg/m 3 ∴ 200 X 0.009 = 1.8 kg Table 1 Experimental Factors in the Experimental Design Sorghum cultivars Mulching leaves 1.50 kg 2.00 kg 2.50 kg NGB05843, NGB05731 and NGB06187 L. leucocephala (LL) LL 1.5 LL 2.0 LL 2.5 A. altilis (AA) AA 1.5 AA 2.0 AA 2.5 S. grandiflora (GS) GS 1.5 GS 2.0 GS 2.5 M. oleifera (MO) MO 1.5 MO 2.0 MO 2.5 Control (CON) Statistical Analysis The collected data were subjected to descriptive and inferential statistics where percentage and standard deviation were evaluated as well as analysis of variance (ANOVA) to measure the level of significance between the means of mulch type applied, the rate of application and the interaction between them. Then, the means were separated with Duncan’s Multiple Range Test at 5% and 1% probability to test the specific significant differences between means (compare treatment effects). Statistical Analysis System version 9 (SAS) tool was employed for the analysis. RESULTS AND DISCUSSION Effect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance The results in Table 2 shows the different treatment groups across various growth and yield parameters of the three sorghum varieties across six key parameters, using both means and standard deviations to draw insights. Days to germination revealed the mean values of all varieties to be 4.00 ± 0.33 days across all treatments. The mean leaf count for the 12 weeks treatment period ranged from 2.13 ± 0.6 to 12.57 ± 0.80 leaves and 2.67–12.67 mm for the control plots. Mean leaf length value, ranged from 64.89 ± 1.72 to 929.60 ± 19.03 mm across all treatments for the 12 weeks treatment period. Whereas, the control plots had the range of 65.33–875.33 mm for the 12 weeks period. Furthermore, the general mean stem girth had 0.38± 0.04 mm to 23.20 ± 2.47 mm range for the treatment period. The average week to fruiting is 12.23 ± 0.57 weeks while the actual fruiting period ranged from 11.67–13.50 weeks for specific plant treatment plot. Then, maturity was attained at the average age of 17.31 ± 0.56 weeks. Whereas, the actual maturity and harvesting was done at 16.33–18.00 week according to individual plant readiness. Of the three sorghum varieties planted, variety 1 attained maturity fastest (12.21 weeks) than variety two (13.64), and three 3 (17.93 weeks) which recorded the slowest to attain maturity. Variety three showed the most consistency in growth and maturity characteristics while others are highly variable. The dataset is presented in the appendix. The interaction effect of application rate and mulch type on growth and yield performance revealed that, among all treatments, M. oleifera at 2.50 kg mulch rate was conspicuous, recorded the highest stem girth (31.13 mm) and the highest panicle weight (196.00 g). This could point to the superior nutrient content of M. oleifera mulch, which is known for its rich mineral profile (Khalid et al., 2015). Enhanced stem girth under this treatment may reflect better vascular development and water transport, which aligns with the findings of Olasantan ( 2007 ) and Agele et al. ( 2011 ) on the impact of organic mulch on crops vegetative growth. On the other hand, A. altilis at 2.50 kg application rate also produced high seed weight (67.00 g) and number of grains (1830.50), which in comparison, was better than the control. Revealing that A. altilis mulch may contribute to improved grain filling, possibly through gradual nutrient release and sustained soil moisture. Adediran et al. (2004) similarly observed enhanced grain characteristics when organic mulch was integrated into cropping systems. In contrast, L. leucocephala at 2.5 kg application rate resulted in lower seed weight (37.00 g) and grain count (1185) compared to the 1.50 kg application rate and other treatments. This may suggest a threshold beyond which decomposition of L. leucocephala mulch may lead to allelopathic effects or nitrogen immobilization, as suggested by Kumar et al. ( 2019 ). Even though, the control plots generally showed good yield performance but were not consistently superior across traits, reinforcing the value of mulching not only for weed suppression but also for sustainable sorghum productivity. Above all, these interactions highlighted the importance of selecting the appropriate mulch type and matching it with optimal application rate, of which, M. oleifera at 2.50 kg and A. altilis at 2.00–2.50 kg appear to be the most promising combinations for enhancing both vegetative and reproductive traits. Table 2a: Effect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance Values followed by different letters in the same column are significantly different from each other at p < 0.05 . Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Table 2b: Effect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance Mulch Rate (kg) Wk. to Fruit Wk. to Harvest No of Tiller/plant No of Panicles Panicle weight (g) No of grains (unit) seed weight (g) A. altilis 1.5 12.00 b 17.00 bc 3.00 ab 1.67 abc 99.33 ab 1705.00 abc 61.50 abc 2 11.67 b 17.00 bc 3.67 ab 2.00 abc 115.00 ab 1987.50 a 66.50 ab 2.5 11.67 b 17.00 bc 3.67 ab 2.00 abc 143.00 ab 1830.50 abc 67.00 ab L. leucocephala 1.5 13.50 a 18.00 ab 3.00 ab 1.00 c 83.50 ab 1423.00 abc 47.00 abc 2 13.00 ab 18.50 a 4.00 a 1.00 c 129.00 ab 1322.00 bc 44.00 bc 2.5 12.67 ab 17.67 abc 3.50 ab 3.00 a 159.50 ab 1185.00 c 37.00 c M. oleifera 1.5 11.67 b 16.33 c 3.50 ab 1.50 bc 118.50 ab 1920.00 ab 70.00 a 2 12.50 ab 17.50 abc 2.50 ab 2.50 ab 169.50 ab 1609.50 abc 52.00 abc 2.5 12.00 a 17.00 bc 3.00 ab 2.00 abc 196.00 a 1537.00 abc 50.00 abc S. grandiflora 1.5 11.67 b 17.00 bc 2.67 ab 1.33 bc 92.33 ab 1367.00 abc 46.00 abc 2 12.33 ab 17.33 abc 2.33 b 1.67 abc 59.33 b 1765.00 abc 58.00 abc 2.5 12.00 b 17.00 bc 3.33 ab 2.33 abc 159.67 ab 1589.00 abc 52.00 abc 12.33 ab 17.67 abc 3.33 ab 2.00 abc 142.33 ab 1804.00 abc 68.50 ab Mean 12.23 17.31 3.19 1.85 128.23 1618.81 55.35 SD 0.57 0.56 0.5 0.58 38.54 244.99 10.67 Values followed by different letters in the same column are significantly different from each other at p < 0.05 Effect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Table 3 shows that mulch type significantly influenced key agronomic traits including days to 50% flowering and harvest, panicle weight, and number of grains, while mulch application rate had a significant effect only on number of panicles (p 0.05), indicating that the effect of mulch was mostly independent of application rate. Among growth parameter traits, leaf count at maturity was significantly influenced by block effects (p < 0.05), likely due to environmental heterogeneity, while leaf length and stem girth were not significantly influenced by any treatment factors. Days to flowering and harvest were significantly reduced by mulch application (p < 0.05), suggesting that organic mulches may have enhanced soil microclimate and moisture retention, accelerating crop development as reported by Teasdale and Mohler ( 2000 ) and Adediran et al. (2004). Mulched plots generally outperformed the control plot under yield parameters, with increased panicle weight, number of grains, and seed weight. This aligns with findings by Olasantan ( 2007 ) and Agele et al. ( 2011 ), who opined that mulching improves soil fertility and structure, which in turn enhances nutrient availability and crop yield components. Ironically, while mulch type significantly influenced grain yield (p < 0.05), the rate of mulch application had no significant effect on seed weight or panicle weight, suggesting that mulch quality (chemical composition, decomposition rate) may play a more significant role than quantity of the mulch applied. This observation confirmed previous studies which emphasized the importance of mulch type over mere biomass quantity (Kumar et al., 2019 ; Narayanasamy, 2018 ). Table 3 a: Effect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Source of variation df DG L. C wk2 L. C. wk4 L. C.wk6 L. C. wk8 L. C. wk12 L.L.wk2 (mm) L.L.wk4 (mm) L.L.wk6 (mm) L.L.wk8 (mm) L.L.wk12 (mm) S.G.wk2 (mm) S.G.wk6 (mm) S.G.wk12 (mm) Block 2 0.16 2.07 2.47* 11.47** 36.69** 37.36** 311.44** 248.77** 1081.80** 1965.60** 10056.65* 0.10** 87.15** 601.70 Mulch 4 0.37 2.41 1.47 2.08* 1.94 1.41 17.53 61.64** 555.42* 1285.69** 6423.55 0.00 0.56 698.78 Rate 2 0.09 0.87 0.47 0.60 4.62* 5.49 9.69 60.01* 254.87 741.60* 698.22 0.00 1.98* 632.19 Mulch x Rate 8 0.37 0.39 0.88 0.38 0.51 0.79 2.20 15.52 79.09 133.49 157.26 0.01* 0.52 700.08 Error 28 0.32 1.02 0.73 0.71 1.14 2.33 9.67 13.06 189.18 216.93 2449.11 0.00 0.59 687.27 Values followed by * in the same column are significantly different from each other at p < 0.05 Values followed by ** in the same column are significantly different from each other at p < 0.01 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Table 3 b: Effect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Source of variation df Wk to Fruit Wk to Harvest No of Tiller/plant No of Panicles Panicle weight (g) No of grains (unit) seed weight (g) Block 2 40.74** 74.76** 16.11** 5.02** 91437.16** 1621312.82** 2815.35** Mulch 4 2.20** 2.12** 0.87 0.19 4446.00 411571.25* 960.20** Rate 2 0.21 0.69 0.29 2.22* 11057.61 44146.95 56.85 Mulch x Rate 8 0.32 0.24 0.61 0.86 1824.57 75568.14 130.48 Error 28 0.55 0.55 0.67 0.56 4132.30 110926.14 164.49 Values followed by * in the same column are significantly different from each other at p < 0.05 Values followed by ** in the same column are significantly different from each other at p < 0.01 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Effect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum The mean effect of mulch type on growth and yield parameters in Table 4 revealed that the use of different mulch types significantly influenced certain growth and yield parameters, even though not all differences were statistically significant. Among the mulched treatments, A. altilis, L. leucocephala, and M. oleifera showed favorable trends compared to the control. Although days to germination did not significantly vary across treatments, mulched plots exhibited slightly earlier emergence (3.78–4.11 days) compared to the control (4.33 days), the phenomenon which was explained by Teasdale and Mohler ( 2000 ) and Olasantan ( 2007 ) that mulches may enhance soil moisture and thermal regimes favorable for germination. At maturity, leaf length was significantly lower in the control (87.53 cm), while mulched plots showed higher values of 93.83 cm in A. altilis , indicating better vegetative growth under mulched conditions. M. oleifera mulched plot notably recorded the highest stem girth (4.21 cm), which may relate to its richer nutrient composition and favorable decomposition rate as clearly reported by Kumar et al. ( 2019 ), thereby enhancing structural growth. Considering the reproductive development parameters, L. leucocephala resulted in the longest time to flowering and harvest (13.06 and 18.06 days, respectively). This may reflect delayed senescence and prolonged vegetative growth; it however did not correspond to superior yield, as L. leucocephala recorded the lowest seed weight (42.67 g) and number of grains (1310) when it compares with other treatments. In contrast, A. altilis and M. oleifera mulched plots consistently outperformed others in panicle weight, seed weight, and number of grains per plant, indicating their superior agronomic potential. M. oleifera in particular, produced the highest panicle weight (161.33 g) and grain counts (1688.83), while the control plot, despite having fewer tillers, recorded the highest seed weight (68.5 g) which could possibly be due to reduced intra-plant competition. The variability in yield attributes among mulch types could as reported in literature, be attributed to differences in nutrient release patterns, mulch decomposition rates, and allelopathic properties (Agele et al., 2011 ; Narayanasamy, 2018 ). The mulch treatments likely enhanced soil structure and moisture conservation, translating into improved crop performance across most metrics. Table 4 a: Effect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Mulch DG L. C wk2 L. C. wk4 L. C.wk6 L. C. wk8 L. C. wk12 L.L.wk2 (mm) L.L.wk4 (mm) L.L.wk6 (mm) L.L.wk8 (mm) L.L.wk12 (mm) S.G.wk2 (mm) S.G.wk6 (mm) S.G.wk12 (mm) A. altilis 4.00a 2.78 a 4.56 7.89 10.56 13.11 a 66.11 157.22 449.78 769.78 938.33 a 0.37 12.61 22.49 a L. leucocephala 3.78a 1.56 b 3.89 7.44 9.78 12.56 a 66.33 157.17 462.33 769.33 938.50 a 0.37 13.29 23.09 a M. oleifera 4.11a 1.89a b 4.33 7.56 9.67 12.00 a 63.39 152.56 448.67 750.89 932.67 a 0.39 12.97 42.11 a S. grandiflora 4.00a 2.11a b 4.56 7.78 9.89 12.56 a 63.56 152.78 442.22 753.33 927.00 a 0.38 13.05 22.39 a Control 4.33a 2.67 a 5.00 8.67 10.67 12.67 a 65.33 152.00 457.33 742.67 875.33 b 0.37 12.87 21.77 a Values followed by different letters in the same column are significantly different from each other at p < 0.05 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Table 4 b: Effect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Mulch Wk to Fruit Wk to Harvest No of Tiller/plant No of Panicles Panicle weight (g) No of grains (unit) seed weight (g) A. altilis 11.78 17.00 3.44 1.89 119.11 1841.00 65.00 L. leucocephala 13.06 18.06 3.50 1.67 124.00 1310.00 42.67 M. oleifera 12.06 16.94 3.00 2.00 161.33 1688.83 57.33 S. grandiflora 12.00 17.11 2.78 1.78 103.78 1573.67 52.00 Control 12.33 17.67 3.33 2.00 142.33 1804.00 68.50 Values followed by different letters in the same column are significantly different from each other at p < 0.05 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Effect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Table 5 shows the mean value of the rate of application on growth and yield performance of sorghum. Although there were no statistically significant differences in most measured parameters across mulch application rates, trends observed suggest that increasing mulch rate may offer slight agronomic advantages, especially regarding yield components. For example, plants treated with the 2.5 kg mulch application rate exhibited the highest panicle weight (160.10 g) and number of panicles (2.27), suggesting a potential positive relationship between mulch quantity and reproductive output. This aligns with findings by Agele et al. ( 2011 ), who noted that higher mulch quantities improved moisture retention and nutrient availability, particularly in tropical soils. Stem girth also appeared to increase with mulch rate, with the 2.5 kg rate recording a much larger value (33.87 mm) compared to 1.5 kg and 2.0 kg rates (22.53 mm and 22.72 mm, respectively). Although this was not statistically significant, it may show cumulative improvements in soil structure and nutrient availability at higher levels of mulch (Narayanasamy, 2018 ; Kumar et al., 2019 ). Ironically, the 1.5 kg mulch application rate recorded the highest seed weight (58.60 g), slightly higher than the 2.0 kg (57.80 g) and 2.5 kg (54.90 g) treatments, which could be due to lower intra-plant competition or more efficient partitioning of assimilates under lower mulch density, a phenomenon previously observed by Adediran et al. (2004). Generally, while the effects of mulch application rate were not strongly pronounced, the 2.5kg rate generally enhanced yield traits, supporting the idea that optimized mulch quantity improves soil physical conditions and nutrient release dynamics (Olasantan, 2007 ). Table 5 a: Effect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Rate DG L. C wk2 L. C. wk4 L.C.wk6 L. C. wk8 L. C. wk12 L.L.wk2 (mm) L.L.wk4 (mm) L.L.wk6 (mm) L.L.wk8 (mm) L.L.wk12 (mm) S.G.wk2 (mm) S.G.wk6 (mm) S.G.wk12 (mm) 1.5kg 4.00 a 2.40 a 4.60 8.07 10.73 13.27 65.70 154.37 454.87 760.00 914.50 0.36 12.65 22.53 2.0kg 4.13 a 1.93 a 4.27 7.87 9.93 12.13 64.10 152.33 447.33 749.20 925.93 0.38 13.36 22.72 2.5kg 4.00 a 2.27 a 4.53 7.67 9.67 12.33 65.03 156.33 454.00 762.40 926.67 0.39 12.87 33.87 Values followed by different letters in the same column are significantly different from each other at p < 0.05 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth Table 5 b: Effect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum Wk to Fruit Wk to Harvest No of Tiller/plant No of Panicles Panicle weight (g) No of grains (unit) seed weight (g) 12.23 17.20 3.10 1.50 107.20 1643.80 58.60 12.37 17.60 3.17 1.83 123.03 1697.60 57.80 12.13 17.27 3.37 2.27 160.10 1589.10 54.90 Values followed by different letters in the same column are significantly different from each other at p < 0.05 Note: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girt CONCLUSION The low soil fertility and shortage of water as a result of climate change is generally making food production becoming extremely difficult. The rising demand for Sorghum as a result of growing industrial need in South-West Nigeria for food, breweries and beverage has grown significantly in the recent years. There is therefore the need to look into repairing the damaged soil structure and depleted soil nutrient by the adoption of organic mulch and use of beneficial crops that are tolerant to low soil nutrient until full restoration. This research addressed part of these challenges through soil management (mulching), by determining the effects of leaf mulch from selected agroforestry species on sorghum yield. This study evaluated the effects of different mulch types and application rates on growth and yield performance of sorghum. The results from this study on the growth and yield performance of sorghum showed that the mulch type significantly influenced key agronomic traits including days to 50% flowering and harvest, panicle weight, and number of grains, while mulch application rate had a significant effect only on number of panicles (p 0.05), indicating that the effect of mulch was mostly independent of application rate. Mulched plots generally outperformed the control plot under yield parameters, with increased panicle weight, number of grains, and seed weight. Also, although mulch type significantly influenced grain yield (p < 0.05), the rate of mulch application had no significant effect on seed weight or panicle weight. The mean effect of mulch type on growth and yield parameters revealed that the use of different mulch types significantly influenced certain growth and yield parameters, even though not all differences were statistically significant. The 1.5 kg rate recorded the highest seed weight (58.60 g), slightly higher than the 2.00 0kg (57.80 g) and 2.50 kg (54.90 g) treatments. M. oleifera at 2.50 kg mulch rate was conspicuous, recording the highest stem girth (81.13 mm) and the highest panicle weight (196.00 g). A. altilis at 2.50 kg application rate also produced high seed weight (67.00 g) and number of grains (1830.50), which in comparison, is better than the control. The findings from this study highlights the importance of mulching from agroforestry tree species leaves in planting as it was highly effective in increasing panicle weight, number of grains, seed weight and completely suppressing weed growth. Declarations Author Contribution The author (ADELEYE Z. Olufemi) confirms being the sole contributor of this work and has approved it for publication. References Adeleye, O. Z., & Okezie, G. N. (2012). Non-timber forest products and poverty reduction policy framework in Ikenne Local Government area, Ogun state, Nigeria. International Journal of Asian Social Science 2(9),1401-1420 Agele, S. O., Iremiren, G. O., & Ojeniyi, S. O. (2011). Effects of tillage and mulch on the growth, development and yield of late-season tomato (Lycopersicon esculentum Mill.) in the humid south of Nigeria. Journal of Agricultural Biotechnology and Sustainable Development, 3(7), 112–116 . Amelework, B. A., Shimelis, H. A., Laing, M. D., Ayele, D. G., Tongoona, P. & Mengistu, F. (2016). Sorghum production systems and constraints, and coping strategies under drought-prone agro-ecologies of Ethiopia. South African Journal of Plant and Soil , 33(3): 207-217. CGIAR (2023). Sorghum goes pop: success stories from a nigerian initiative. Retrieved from https://www.cgiar.org/news-events/news/sorghum-goes-pop-success-stories-from-a-nigerian-initiative/ Clifford, E.D. & Massello, J.W. (1965). Mulching materials for nursery seedbeds. Tree Planters’ Notes 72, 18–22. Dan Diclerico. (2022). How to choose the best types of mulch to keep your garden beautiful. https://www.goodhousekeeping.com/home/gardening/a20706549/how-to-mulch-your- garden/ Garrity, D.P. (2004). Agroforestry and the achievement of the Millennium Development Goals. Agrofor Syst 61(1–3), 5–17. Jodaugiene, D., Pupaliene, R., Urboniene, M., Pranckietis, V., and Pranckietiene, I. (2006). The impact of different types of organic mulches on weed emergence. Agronomy Research , 4 (Special Issue), 197-201 . Jose, S. & Bardhan, S. (2012). Agroforestry for biomass production and carbon sequestration: an overview. Agrofor Syst 86, 105–111. Jose, S. (2009). Agroforestry for ecosystem services and environmental benefits: an overview. Agrofor Syst 76(1), 1–10. Kader, M.A., Singha, A., Begum, M.A., Jewel, A., Khan, F.H. & Khan, N.I. (2019). Mulching as water saving technique in dry land agriculture. Bulletin of the National Research Centre 43, 1–6. Kumar, V., Yadav, S. K., & Meena, R. K. (2019). Mulching effect on growth, yield and soil health in various cropping systems. Journal of Pharmacognosy and Phytochemistry, 8(3), 2530–2536. Manzello, S.L., Suzuki, S., Kagiya, K., Suzuki, J. & Hayashi, Y. (2014). Ignition of mulch beds exposed to continuous-wind driven firebrand showers. Fire Technology . Nalayini, P. (2007). Poly-mulching a case study to increase cotton productivity. Senior scientist. Central Institute for Cotton Research, Regional Station, Coimbatore . Narayanasamy, G. (2018). Organic farming for sustainable agriculture. Scientific Publishers . Ngouajio, M. & McGiffen, M.E. (2004). Sustainable vegetable production: effects of cropping systems on weed and insect population dynamics. Acta.Hortic . 638, 77–83. Olasantan, F. O. (2007). Mulching for sustainable crop and soil management . Journal of Sustainable Agriculture, 30(3), 87–103. Petrikovszki, R., Körösi, K., Nagy, P., Simon, B. & Zalai, M. (2016). Effect of leaf litter mulching on the pests of tomato. COLUMELLA: Journal of Agricultural and Environmental Sciences , 3(2), 35-46. Rathore, A.L., Pal, A.R. & Sahu, K.K. (1998). Tillage and mulching effects on water use, root growth, and yield of rain-fed mustard and chickpea grown after lowland rice. J. Sci. Food. Agric . 78, 149–161. Singh, S.B., Pramod, K., Prasad, K.G. & Kumar, P. (1991). Response of Eucalyptus to organic manure mulch and fertilizer sources of nitrogen and phosphorus. Van.Vig . 29, 200–207. Smith, J., Pearce, B. D., & Wolfe, M. S. (2012). A European perspective for developing modern multifunctional agroforestry systems for sustainable intensification. Renewable Agriculture and Food Systems , 27 (4), 323-332 Teasdale, J. R., & Mohler, C. L. (2000). The quantitative relationship between weed emergence and the physical properties of mulches. Weed Science, 48 (3), 385–392 . https://doi.org/10.1614/0043-1745(2000)048[0385:TQRBWE]2.0.CO;2 Wortmann, C. S., Mamo, M., & Shapiro, C. A. (2009). Nutrient management strategies for dryland sorghum production. Field Crops Research , 112(2-3), 109–117. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7411848","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":515021727,"identity":"3f9a62b5-472f-4762-8600-60c0b881211c","order_by":0,"name":"Olufemi Zaccheaus ADELEYE","email":"data:image/png;base64,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","orcid":"","institution":"Babcock University","correspondingAuthor":true,"prefix":"","firstName":"Olufemi","middleName":"Zaccheaus","lastName":"ADELEYE","suffix":""}],"badges":[],"createdAt":"2025-08-19 21:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7411848/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7411848/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104399891,"identity":"98fdce45-8ab0-46c4-81e4-de6d75064ac1","added_by":"auto","created_at":"2026-03-11 12:08:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1516313,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7411848/v1/8791e8bd-cc12-4c93-8aaa-78e848c9a976.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Agroforestry Leaf Mulches on the Growth and Yield Performance of Sorghum in a Semi-Arid Region","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSorghum is a drought-tolerant cereal widely grown in semi-arid regions of Africa and Asia. Despite its resilience, sorghum yields in smallholder systems remain low, mainly due to poor soil fertility and inadequate management practices (Wortmann et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Organic mulching has emerged as a sustainable technique for improving soil health and crop productivity. Agroforestry trees such as Moringa, Leucaena, and Sesbania offer locally available biomass that can be used as mulch. This study aims to evaluate the effects of leaf mulch from selected tree species on the growth and yield of sorghum in a semi-arid environment.\u003c/p\u003e\u003cp\u003eAgroforestry has risen to prominence as a land-use strategy to help address global climate change and provide other environmental, economic, and social benefits. However, systematic knowledge on the human environment impacts of agroforestry practices and interventions remains lacking. Agroforestry is promoted for its potential for carbon sequestration, soil erosion and control, improved nutrient and water cycling, as well as other socio-economic benefits and greater agricultural productivity (Akinnifesi et al., 2007). While researchers and policy makers have long studied and supported agroforestry practices in low and middle-income countries, particularly in tropical regions, recognition and promotion of agroforestry in the temperate climates typical of developed countries gained prominence in the early 21st century (Jose et al., 2012).\u003c/p\u003e\u003cp\u003eThe production of Sorghum in sub-Saharan Africa has been comparatively low due to biotic and abiotic stresses (Teshome et al., 2018) such as drought, low soil fertility, and high soil acidity as the major abiotic stresses capable of causing significant yield losses in sorghum and biotic stresses (diseases and insect pests) (Amelework et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIt is a known fact that cassava and maize are staple foods in South-Western Nigeria which might bare the occasion to wonder; what is the importance of sorghum to the south west, Nigeria? What is the growing interest in sorghum cultivation about? The cultivation of sorghum has traditionally been majorly in Northern Nigeria because of the favorable agro-climatic conditions. But, over the time, there has been an increasing interest in the production of sorghum in the South-West Nigeria due to such factors as Industrial demand, supply-chain efficiency, national production deficit, increase in population and regional migration. These are parts of the major driver for this shift in sorghum production.\u003c/p\u003e\u003cp\u003eThe demand for Sorghum as a result of growing industrial need in South-West, Nigeria for breweries and beverages has grown significantly in the recent years. Sorghum grits are widely used as substitutes for barley in the production of alcoholic and non-alcoholic beverages by many beverage companies, such as Nigerian Breweries and Guinness Nigeria. These had increased the demand to source sorghum locally so as to reduce costs and comply with government policies on raw material sourcing (Blueprint, 2024). Sorghum is a key ingredient in food processing industries for the production of composite flour which is used in the production of food such as bread, biscuits and noodles. Increasing consumer demand for this food and produce in South-West, Nigeria has become one of the major drivers for an increased demand for sorghum (Daily Trust, 2024).\u003c/p\u003e\u003cp\u003eSorghum is also used in livestock feed, aluminum ore refining, and construction materials. This has further increased its industrial relevance, increasing the demand for its production in the south west, Nigeria (FAO, 2023). It is a well-established fact that Nigeria is one of the world\u0026rsquo;s largest production hubs for sorghum, but the current production levels do not meet domestic demand.\u003c/p\u003e\u003cp\u003eThe Minister of Agriculture and Food Security recently noted that national sorghum production is insufficient to meet both food and industrial needs. This was noted to be as a result of low productivity, poor seed quality, and post-harvest losses (Daily Trust, 2024).\u003c/p\u003e\u003cp\u003eIncreased industrial reliance on sorghum has created supply gaps, making localized production in the South-West, a strategic move to supplement existing sources (FAO, 2023).\u003c/p\u003e\u003cp\u003eThe South-West, region hosts a significant number of food processing industries, breweries, and animal feed manufacturers. Establishing local sorghum farms will yield several benefits such as;\u003c/p\u003e\u003cp\u003e\u003col style=\"list-style-type:lower-roman;\"\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eReduction in transportation costs: Local production would remove transportation expenses and ensure a more stable supply as against sourcing from Northern Nigeria with its high logistics costs (Blueprint, 2024).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInsecurity, Political instability, climate change, and infrastructural challenges in the North occasionally disrupt sorghum production and supply. Cultivating sorghum in the South-West, will ensure a secondary production hub, thereby causing supply stability (Daily Trust, 2024).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eNearness to processing plants will enhance product freshness and efficiency in industrial processing (FAO, 2023).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eWhile sorghum cultivation in South-West, Nigeria faces significant challenges related to awareness, pest control and market access, the Nigerian government has implemented various policies to promote sorghum cultivation, aiming to meet rising industrial demand and achieve national self-sufficiency in grain production. These initiatives focus on improving productivity, financing, and seed quality to support farmers across different regions, including the South-West.\u003c/p\u003e\u003cp\u003eAgricultural Transformation Agenda (ATA)- Launched in 2011, identified sorghum as one of five priority crops for development. Its aim was to;\u003c/p\u003e\u003cp\u003e\u003col style=\"list-style-type:lower-roman;\"\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eIncrease sorghum production from 9.3\u0026nbsp;million metric tons to 11.3\u0026nbsp;million metric tons by 2015, focusing on modernizing agriculture through public-private partnerships (Aderemi, 2023).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEncourage private-sector investment in sorghum processing industries, particularly in flour mills and breweries.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eAgricultural Transformation Action Plan (ATAP)- Introduced in 2011, emphasized agriculture as a key driver of economic growth and planned to recognize sorghum as a strategic crop, with a focus on:\u003c/p\u003e\u003cp\u003e\u003col style=\"list-style-type:lower-roman;\"\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eProduction of fortified foods for the Home-Grown School Feeding Program and the World Food Program.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eExpand the use of sorghum in the malt industry for beverage production (FAO, 2023).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eAnchor Borrowers\u0026rsquo; Program (ABP)- launched by the Central Bank of Nigeria (CBN) and the Federal Ministry of Agriculture and Rural Development (FMARD), provides: Zero-interest loans and farm inputs to smallholder farmers cultivating priority crops, including sorghum and provide training and support for modern sorghum farming techniques. In 2021, the program supported approximately 1.2\u0026nbsp;million farmers nationwide, with plans to increase beneficiaries to 5\u0026nbsp;million by 2022 (USDA, 2022). Seed System Enhancement for Sorghum- the Nigerian government, in partnership with the Institute for Agricultural Research (IAR) and the International Maize and Wheat Improvement Center (CIMMYT), introduced improved sorghum varieties such as: SAMSORG 52 and SAMSORG 53 \u0026ndash; high-yield, drought-tolerant varieties suitable for Nigeria\u0026rsquo;s agro-ecological zones. The Farm and Community-Managed Seed System (FCMSS) approach has strengthened access to high-quality seeds, increasing yields and reducing dependency on imports (CIMMYT, 2023).\u003c/p\u003e\u003cp\u003eThe government of Nigeria provides incentives, such as tax breaks and subsidies, to industries using locally grown sorghum for production and encouraged partnerships between research institutions, private companies, and farmer cooperative societies to boost production, processing and storage facilities in regions like the South-West (Aderemi, 2023). Efforts to boost the adoption of sorghum in South-West Nigeria include awareness campaigns highlighting its nutritional and economic benefits. Agricultural shows and exhibitions have also been used to promote improved sorghum varieties, and partnerships with industries such as flour millers and breweries have explored to increase demand (CGIAR, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe reviewed literatures showed that application of mulches has been addressed but, existing studies in the use of specific agroforestry tree leaves as mulch for its soil fertility improvement potential in sorghum cultivation are lacking. This study therefore, aims to fill in this missing gap in literature.\u003c/p\u003e\u003cp\u003eThe word mulch has been derived from the German word \u0026ldquo;\u003cem\u003emolsch\u003c/em\u003e\u0026rdquo; which means \u0026ldquo;easy to decay,\u0026rdquo; and mulches have widely been used for vegetable production since ancient times (Lightfoot, 1994). Mulching is referred to as spreading various covering materials on the surface of soil to minimize moisture losses, reduce weed population and to enhance crop yield (Kader et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Nalayini, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Mulches could potentially minimize water runoff, improve infiltration capacity of soil, restrain weed population via shading, and act as obstacle in evapotranspiration (Rathore et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Mulching also has some other positive environmental effects such as temperature regulation of soil and plant roots, minimize nutrient losses, cut down soil erosion and compactness, and improved physical conditions of soil (Ngouajio \u0026amp; McGiffen, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMulches got attention in the late 1930, though in a negative sence when it was observed that these materials could alter the surrounding conditions of agricultural lands, forest areas, and horticultural lands. Some earlier studies showed a number of such damaging effects caused by mulches (Bedford \u0026amp; Pickering, 1919). In 1941, deep mulches were used for trees and shrub plantation (Pirone, 1941), because these deep-type mulches give protection to drought stress such as frost injury and freezing damage of crop plants in harsh environmental conditions. More water conservation was achieved when the same quantity of material was used as mulch compared with what was incorporated into the soil (Singh et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The by-products of agricultural and forestry domains have been used as mulches in the mid-1900s (18th century) (Clifford \u0026amp; Massello, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1965\u003c/span\u003e). Other materials gained popularity and were used as mulch such as trimmings of trees and shrubs, wastes of animals, stubbles, and residues of crop plants. Landscape mulches were also seen in 1957 but there was no scientific research work carried out on them.\u003c/p\u003e\u003cp\u003eMulches could be of organic, inorganic and synthetic origin. The organic mulches consist of animal and plant residues. The most commonly used organic mulches include straws, husks, grasses and cover crops (live mulches), saw dust, compost, and manures (Rathore et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e),\u003c/p\u003e\u003cp\u003eA \u003cem\u003emulch\u003c/em\u003e is a layer of material applied to the surface of soil for the sole purpose of soil moisture conservation, fertility improvement, weed management, erosion control etc. There are three basic kinds of mulch: organic, inorganic and synthetic: \u003cb\u003eOrganic mulches\u003c/b\u003e include formerly living material such as chopped leaves, straw, grass clippings, compost, wood chips, shredded bark, sawdust, pine needles and even paper. In addition to weed suppression, organic mulch improves the soil as they decompose. \u003cb\u003eInorganic mulches\u003c/b\u003e include non-living materials such as stones, pebbles, slabs etc., while synthetic mulch includes black plastic and geotextiles (landscape fabrics). Inorganic and synthetic mulches do not break down to enrich the soil (Dan, 2022).\u003c/p\u003e\u003cp\u003eMulches have been widely used in agricultural lands, orchards, forests, and landscapes in many parts of the world (Smith et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Generally, mulches reduce competition from weeds, maintain soil temperature, and reduce evaporation from soil (Jose et al., 2012). Mulches protect the soil from wind, water, and traffic-induced erosion. Mulches also improve soil properties by improving moisture retention capacity, releasing different nutrients, and enhancing biological activities (Garrity, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Therefore, with the improved soil properties, plants grow better (Jose \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jose \u0026amp; Bardhan, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The capability of mulching in the control of nutrient level\u003c/p\u003e\u003cp\u003eabsorption, temperature and water level of the soil makes it multifunctional (Petrikovszki et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). But for mulch to yield effective results in agricultural practices, some basic requirements must be met, such as the source, allelopatic effect, decay efficiency, etc. Mulch, most importantly, should help conserve soil moisture and improve nutrient obtainability as well regulate soil temperature (Manzello et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), even though various types of organic mulch have different effects on weed control, plant growth, and soil properties (Jodaugiene et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), unfortunately, little or nothing has been done in assessing the problems faced by agroforestry adopters which could be a strong determinant of food security and soil sustainability in Nigeria. This study therefore, was carried out to determine the effects of different organic mulches on weed presence in reference to sorghum agronomic performance and soil characteristics.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThe study was carried out at the Teaching and Research Farm of Babcock University. Babcock University is situated in Ilishan-Remo (latitude 6\u0026deg;53\u0026rsquo;44\u0026rdquo; N and longitude 3\u0026deg;43\u0026rsquo;18\u0026rdquo; E) 80m elevation in Ikenne Local Government Area of Ogun State. The Local Government was carved out of the defunct Remo Local Government in September 1991, it is bounded in the West by Obafemi-Owode Local Government, in the South by Sagamu Local Government, in the East by Odogbolu Local Government and in the North by Remo-North Local Government. The inhabitants are mainly of remo origin, trading and farming are their predominant occupation, with a population of 202,980 according to National Population Commission report of 2006. (Adeleye \u0026amp; Okezie, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperimental Material\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003eSeed Collection\u003c/h2\u003e\u003cp\u003eThree cultivars of sorghum Seeds (NGB05843, NGB05731 and NGB06187) were collected from the National Centre for Genetic Resources and Biotechnology (NACGRAB), Ibadan, Oyo State, Nigeria. The accessions represent part of the institutional working germplasm collections which were grown locally by farmers in Nigeria.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eMulch Collection\u003c/h3\u003e\n\u003cp\u003eFresh leaves of four agroforestry (\u003cem\u003eL. leucocephala\u003c/em\u003e, \u003cem\u003eA. altilis, S. grandiflora, M. oleifera)\u003c/em\u003e trees species were collected. \u003cem\u003eL. leucocephala\u003c/em\u003e, \u003cem\u003eA. altilis\u003c/em\u003e and \u003cem\u003eM. oleifera\u003c/em\u003e were collected from Forest Research Institute of Nigeria (FRIN), Ibadan Nigeria, while \u003cem\u003eS. grandiflora\u003c/em\u003e was collected from the National Horticulture Research Institute (NIHORT). All leaves were from trees of relatively uniform age, because they were collected from plantations. A total of 18 kg of each species of mulch was used for the experiment.\u003c/p\u003e\n\u003ch3\u003eMethods\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eField Preparation, Experimental Design and Cultural Practices\u003c/h2\u003e\u003cp\u003eThe experimental field of 40.5 m\u003csup\u003e2\u003c/sup\u003e was manually prepared at the onset of rainy season in May. The layout of the experimental plot was set up using pegs, lines and measuring tapes. The field was divided in three (3) blocks consisting of thirteen (13) raised beds per block, measuring 0.18 m\u003csup\u003e2\u003c/sup\u003e with inter bed distance of 0.6 m and inter block distance of 0.9 m between blocks respectively.\u003c/p\u003e\u003cp\u003eThe study consisted of a 3 x 3 x 4 factorial experiment laid out following a randomized complete block design and replicated three times (Table\u0026nbsp;3.1). The factors in the experiment were varieties of Sorghum namely NGB05843, NGB05731 and NGB06187. The levels of mulch applied were 1.50 kg, 2.00 kg, 2.50 kg, and the agroforestry tree species were \u003cem\u003eL, leucocephala\u003c/em\u003e, \u003cem\u003eA. altilis, S. grandiflora, M. oleifera\u003c/em\u003e serving as treatments. The control plots were without treatment.\u003c/p\u003e\u003cp\u003eThere was a total of 39 raised beds (13 per block including 1 control) of which each agroforestry species leaf was used to mulch each raised bed in three (3) replicates in the weight of 1.50 kg, 2.00 kg and 2.50 kg, evenly spread in not less than 2cm thick (measured with a meter rule), for each of the 3 varieties of the sorghum crop planted (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The agroforestry tree species leaves were applied to the prepared raised beds and allowed about three weeks before planting to allow onset of decomposition so as to prevent nitrogen depletion and soil acidity, allowing proper air and water flow (Addai \u0026amp; Alimiyawo, 2015; Thompson \u0026amp; Myers, 2021).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMulch Volume Determination\u003c/h2\u003e\u003cp\u003eIn the establishment of the volume of fresh mulch application, 5 cm depth was applied as recommended by the USDA Natural Resources Conservation Services (2017).\u003c/p\u003e\u003cp\u003eTherefore, Mulch volume was calculated as follows\u003c/p\u003e\u003cp\u003eVolume\u0026thinsp;=\u0026thinsp;L x B x W (where L and B are the length and breadth of the raised bed and W is the recommended width of mulch).\u003c/p\u003e\u003cp\u003eTherefore,\u003c/p\u003e\u003cp\u003eV\u0026thinsp;=\u0026thinsp;0.30 m x 0.60 m x 0.05 m\u003c/p\u003e\u003cp\u003e=\u0026thinsp;0.009 m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe density of applied fresh leaf mulch\u003c/p\u003e\u003cp\u003e= D X V. where D is the given density and V is the volume derived.\u003c/p\u003e\u003cp\u003eThe standard volume for fresh mulch application is 200 kg/m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u0026there4; 200 X 0.009\u0026thinsp;=\u0026thinsp;1.8 kg\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExperimental Factors in the Experimental Design\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSorghum cultivars\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulching leaves\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.50 kg\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.00 kg\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.50 kg\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNGB05843, NGB05731 and NGB06187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e (LL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLL 1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLL 2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLL 2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eA. altilis\u003c/em\u003e (AA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAA 1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAA 2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAA 2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eS. grandiflora\u003c/em\u003e (GS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGS 1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGS 2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGS 2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eM. oleifera\u003c/em\u003e (MO)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMO 1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMO 2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMO 2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eControl (CON)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe collected data were subjected to descriptive and inferential statistics where percentage and standard deviation were evaluated as well as analysis of variance (ANOVA) to measure the level of significance between the means of mulch type applied, the rate of application and the interaction between them. Then, the means were separated with Duncan\u0026rsquo;s Multiple Range Test at 5% and 1% probability to test the specific significant differences between means (compare treatment effects). Statistical Analysis System version 9 (SAS) tool was employed for the analysis.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance\u003c/h2\u003e\u003cp\u003eThe results in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the different treatment groups across various growth and yield parameters of the three sorghum varieties across six key parameters, using both means and standard deviations to draw insights. Days to germination revealed the mean values of all varieties to be 4.00 \u0026plusmn; 0.33 days across all treatments. The mean leaf count for the 12 weeks treatment period ranged from 2.13 \u0026plusmn; 0.6 to 12.57 \u0026plusmn; 0.80 leaves and 2.67\u0026ndash;12.67 mm for the control plots. Mean leaf length value, ranged from 64.89 \u0026plusmn; 1.72 to 929.60 \u0026plusmn; 19.03 mm across all treatments for the 12 weeks treatment period. Whereas, the control plots had the range of 65.33\u0026ndash;875.33 mm for the 12 weeks period. Furthermore, the general mean stem girth had 0.38\u0026plusmn; 0.04 mm to 23.20 \u0026plusmn; 2.47 mm range for the treatment period.\u003c/p\u003e\u003cp\u003eThe average week to fruiting is 12.23 \u0026plusmn; 0.57 weeks while the actual fruiting period ranged from 11.67\u0026ndash;13.50 weeks for specific plant treatment plot. Then, maturity was attained at the average age of 17.31 \u0026plusmn; 0.56 weeks. Whereas, the actual maturity and harvesting was done at 16.33\u0026ndash;18.00 week according to individual plant readiness. Of the three sorghum varieties planted, variety 1 attained maturity fastest (12.21 weeks) than variety two (13.64), and three 3 (17.93 weeks) which recorded the slowest to attain maturity. Variety three showed the most consistency in growth and maturity characteristics while others are highly variable. The dataset is presented in the appendix.\u003c/p\u003e\u003cp\u003eThe interaction effect of application rate and mulch type on growth and yield performance revealed that, among all treatments, M. oleifera at 2.50 kg mulch rate was conspicuous, recorded the highest stem girth (31.13 mm) and the highest panicle weight (196.00 g). This could point to the superior nutrient content of \u003cem\u003eM. oleifera\u003c/em\u003e mulch, which is known for its rich mineral profile (Khalid et al., 2015). Enhanced stem girth under this treatment may reflect better vascular development and water transport, which aligns with the findings of Olasantan (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and Agele et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) on the impact of organic mulch on crops vegetative growth.\u003c/p\u003e\u003cp\u003eOn the other hand, \u003cem\u003eA. altilis\u003c/em\u003e at 2.50 kg application rate also produced high seed weight (67.00 g) and number of grains (1830.50), which in comparison, was better than the control. Revealing that \u003cem\u003eA. altilis\u003c/em\u003e mulch may contribute to improved grain filling, possibly through gradual nutrient release and sustained soil moisture. Adediran et al. (2004) similarly observed enhanced grain characteristics when organic mulch was integrated into cropping systems. In contrast, L. leucocephala at 2.5 kg application rate resulted in lower seed weight (37.00 g) and grain count (1185) compared to the 1.50 kg application rate and other treatments. This may suggest a threshold beyond which decomposition of L. leucocephala mulch may lead to allelopathic effects or nitrogen immobilization, as suggested by Kumar et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEven though, the control plots generally showed good yield performance but were not consistently superior across traits, reinforcing the value of mulching not only for weed suppression but also for sustainable sorghum productivity. Above all, these interactions highlighted the importance of selecting the appropriate mulch type and matching it with optimal application rate, of which, \u003cem\u003eM. oleifera\u003c/em\u003e at 2.50 kg and A. altilis at 2.00\u0026ndash;2.50 kg appear to be the most promising combinations for enhancing both vegetative and reproductive traits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2a: Effect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA/QAAAIXCAYAAAAyghX6AAAQAElEQVR4AezdBZxlN/UH8PyKFS9evLhD8eJb3CnusHjx4g7F3d2Lu8sfp8XdXVvcoTiltP/55jWzd96+2Z2deW9mdjbzaXrvTXKTc345OTnnJPftbkf3v45AR6Aj0BHoCHQEOgIdgY5AR6Aj0BHoCHQEdjoEdis79NcrdwQ6Ah2BjkBHoCPQEegIdAQ6Ah2BjkBHoCOwHhCYrUO/HjjsNHQEOgIdgY5AR6Aj0BHoCHQEOgIdgY5AR2ADIrCuHPoNiG9nqSPQEegIdAQ6Ah2BjkBHoCPQEegIdAQ6AjNBYGd26GcCSG+0I9AR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCOwMCu5BDvzMMR6exI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCS0OgO/SL4dTzOwIdgY5AR6Aj0BHoCHQEOgIdgY5AR6AjsI4R6A79lAanN9MR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCHYHVRKA79KuJ9pa++l1HoCPQEegIdAQ6Ah2BjkBHoCPQEegIdARWhMB2Hfr//e9/5Ygjjij//ve/e1ozDDr2Xf66DHQZ6DLQZaDLQJeBLgNdBroMdBnoMrCRZYDfffTRR++Qg79dh/7HP/5xudKVrtTTzoRBp7XLa5eBLgNdBroMdBnoMtBloMtAl4EuA10GdjoZ2CFvfq7ydh36c57znOWTn/xk+fSnP93TBsWgj22X7S4DXQa6DHQZ6DLQZaDLQJeBLgNdBroMrK0M8LuTzLnpS/9vuw790pvqNXcRBDqbHYGOQEegI9AR6Ah0BDoCHYGOQEegI7AOEOgO/ToYhI1NQueuI1DKUUcdVY488sia/C6H545LR6Aj0BHoCHQEOgIdgY5AR6AjsDIEukO/Mvz629NGoLe34RDwwx5/+tOfyne/+93yne98p149bzhGO0MdgY5AR6Aj0BHoCHQEOgIdgVVGoDv0qwx47266CPTWdg4Efvvb35YnPvGJ5RKXuER561vfWn7/+9/vHIR3KjsCHYGOQEegI9AR6Ah0BDoC6xiB7tCv48HppE0dgd7gGiCQpJz73OcuV7/61cuxj33scqtb3ao+rwEpvcuOQEegI9AR6Ah0BDoCHYGOwIZCoDv0G2o4OzPTRaC3Ni0EkpRkYZpW272djkBHoCPQEegIdAQ6Ah2BjsCuikB36HfVke98Tx+B3mJHoCPQEegIdAQ6Ah2BjkBHoCPQEVhFBLpDv4pg9646AkME+n1HoCPQEegIdAQ6Ah2BjkBHoCPQEVgJAt2hXwl6/d2OwOohsGF7OuKII4p/ym7DMtgZ6wh0BDoCHYGOQEegI9AR6AjMCIHu0M8I2N5sR2BtEVhfvR911FHVaW9XDrz0n//8p3zhC18oRx55ZDn88MPLf//736LO+qK+U9MR6Ah0BDoCHYGOQEegI9ARWJ8IdId+fY5Lp6ojsLoIzLC3o48+uvz9738vP/jBD+oP4/3yl78sLR100EHlIx/5SDnWsY5VnvKUp5Q73/nORf0ZktOb7gh0BDoCHYGOQEegI9AR6AhsGAS6Q79hhrIz0hFYPQR2tKef/exn5WxnO1t59rOfXX7yk5+UD3/4wzUd5zjHKTe+8Y2rQ+96t7vdrey2W1dLO4pvr98R6Ah0BDoCHYGOQEegI7BrItAt511z3DvXHYFVQyBJucAFLlBuf/vbb5Vud7vblfOe97x15/5CF7pQudjFLlbvV4243lFHoCPQEegIdAQ6Ah2BjkBHYCdGoDv0O/HgddI7AjsLAsnCf4M+WfiMj2SUV4qnnjoCHYGOQEegI9AR6Ah0BDoCHYHtIdAd+u0h1Ms7Ah2B9Y1Ap64j0BHoCHQEOgIdgY5AR6AjsIsi0B36XXTgO9sdgV0Vgc53R6Aj0BHoCHQEOgIdgY5AR2CjINAd+o0ykp2PjkBHYBYI9DY7Ah2BjkBHoCPQEegIdAQ6AusWge7Qr9uh6YR1BDoCOx8CneKOQEegI9AR6Ah0BDoCHYGOwOoh0B361cN6w/Z01FFHlWHy74hLG5bhNWIMpg1n99JySPHeMC2njY3yTsNhiOtyeGvttOuS25hSRf2ulAektHZcJXmrmfQ55MPzcvr33jAtp43lvKPPIf3bamNY1zuet1V/qWXakharr5+WFquz1PzWjv4kz9t6V7l6kvtt1V1qmbb+97//le21p1xaaruL1dOGPiX30rbqKldXcr9Y3R3J1472pG29p15L26q3vTJt6MtV2lZ95dJS62+rrVbW2tNmyxtelQ/TsGw5960t/Umet9WOcvUk99K26i+lTBtLlevx9rzb0njZSp5bm65LaUe9YVrKO9uqA19psTrT7Gu8jx1te1jf/Xh7O/qMb2l77+mrpe3V7eUbC4Hu0G+s8Vx1biiYI488sgzTf//73+rgUyqrTtAG7RCW41h73lF2tcNIMEaSNiT5O9rWRqiPdzg0+fW8o1io7z3tSPD1PAt8JrWp/0a/KxrkTaq7rTw0o10bkufltLOtPrZVpr9h/42Gbb0zqQzN2oGDNjxr23VS/WnlaV9/w6Tfxdofr4/mxeouNf+II44oX/nKV8prXvOa8q9//Wur1/SpH9i4et6q0g5kaENbjWf8Ltam/FbP1Xvq70B3W1XV5mGHHVZe+MIXlt/+9rfbdOr1pb60VUNLzPCudtAvbY8H9dVrCV7eX2J3E6tp89BDDy0vetGLyq9//euJdWSqpy99u3qWv6PJu9qQ8Ou6WFvy8djqtbryd7TfYf0///nP5b3vfW/56le/OnGMta8v/erf8/D9Hb0f8qzdbbWpL+XqSWjw/o72OayvTTy/4x3vKN/85jcn8qy+flryLHlXHjrQ417+SpN2G5+u2pW3WLvK1EOHpL4kf7F3tpX/n//8p3zpS18qb3jDG4r78bra1R+eXT2P11nus7a02dreHh+tPr4l9SX5y6EBv9vivbWpfXTq033L79ddA4Hu0O8a4zwzLn/zm9+Uvfbaq+yxxx7l9Kc/fTnrWc9aLn7xi5enPvWpxYK0PaWinLJynRmRG6Th+9znPmXPPfcsJz/5ycsZz3jGauAslTX4Wox++MMflgc+8IHlLGc5S7nUpS5Vnv70p5dXvvKVExfIpba91HpoMNaHH354+dOf/lT+8pe/lH/+85+1b4vQUtuZZj38k9sTn/jE5cxnPnN5wQtesEPNWzh///vfl0c96lEVU/+O/iMe8Yjypje9qXCu8LxDDS6z8rWvfe0qF6c4xSnK2c52tmKcSylLag2NnL+PfOQj5eY3v3mdw9e4xjWqfL34xS+uwbklNTSFShe5yEXKKU95yproFU7aUpvFB8w/97nPlVvc4haVjytf+crl9a9/fTnooINq0HGpbS2nnr7hZ36e6lSnKmc/+9mrA7JYW1/+8pfrPD7ZyU5WTne605Vb3epWi1Vdcr759cEPfrDOafQMX4QPBxCNZzjDGcr+++9fHcKVzL3nPOc5VSfR/+bPK17ximGXC+71fY5znKOOLXyucIUrlH//+98L6izn4dvf/nZdb+iUxd7H4//93/9V3cewXqzeUvKf8YxnVJ6N85nOdKYqW4u996tf/arKoTE+zWlOUy5/+csXOmOx+kvNbzz/8Y9/nPgKHv/2t7+V5z73ueWyl71suclNbjKx3lIyDznkkCqndMtpT3vacre73W3R18jYAx7wgGJ8zWMy8fa3v33R+kst+MMf/lBlGt/j7+D185//fLnc5S5Xdd+d7nSnQiejZbzuUp8PPvjgYmxPcpKTVLtmWzzr/973vncxvsbZ2vrud797qV1NrJek8vDyl7+8fO973yuTeLGeo3OfffZZoNvoAPOSLWaNh426EztaYqb584Mf/KDc9ra3rescft/3vvcVbY/T5pmMCyze5S53Kec5z3nquDzxiU8sX/va18qPfvSjJfa6sBq+3v/+99dg5STd9otf/KLc6EY3quN1z3ves7BN0b2wlR1/0sZyeL/zne+8Fe8//vGPd5yAuTe2xftccf0PJtq/3/3uV853vvOVT3/60zW//2/XQWC3XYfVzuksELDAU9zHPvaxy0te8pLy05/+tO6WPOUpT6nOEeWuX1cLH+Xo2p4pfrtJrvIk5a2ed3saIcCQfPjDH14Xd5hf5zrXGRUs4f+Uvcj25s2byxWveMXyne98p3zqU58qHB4G13e/+90ltLL8Ksb05z//eWHsPfKRj6zG2atf/eryute9rniehmG/HOruf//7l4MOGjl7X/ziF8vd7373kmRJTZFRztO+++5bzn/+89edlC984QvV6GHsGKMlNTSFSnZyOJCXucxlCuOD47SUZs03QRVj8PrXv7489KEPrcGAt771rVXO3vzmNxfG9FLaWmmdJIWTe9Ob3rQaJIx3+mWp7f7jH/8o9I7gygEHHFBxYFgL2OxooGapfQ7rHfe4xy2vfe1rK+3mJsNVgGJYZ3h/0YtetAYb6M7nPe95dS4My4f3xskcInOukntJmeT+hCc8YSGP7d3xehzuW9/61pVOQR+OimBOq7+jV4b9gx70oIL3j370o+UOd7jDovNH0OL73/9+EfRCw8c//vFy/OMff9EuG+2uEv4k941fVxhzvDTkWbl67iXPnCKBHbIuT93lpCSFbNFjaBcEu93tbrdoU2SPHOy9997l9re/fVEfVpNeQBda0e4quZfcDxMMT3SiE9U56j11pFaHfhe4we+rXvWq8pa3vGVSl0vK27RpU/nkJz9ZA4ZOBQjyLfZikhokhsmFL3zhus7c8IY3XFQmJtE+5AM/njmnF7rQheb5bfnKfvnLX5aHPexhhWz/5Cc/KZe+9KWLtUXbi9G5vfx953T6wXNO/UlPetLy0pe+tNo0i71zrGMdqzzrWc8qmzdvLo3n613veotVrwFSdEtDPjx7SZ4kMHvBC15wK56V4e2vf/1rdY5/9rOf1Ta9K73xjW8sJzjBCWpQedPc2JE7AQ5ly01///vf69ptXMnzQx7ykPKBD3xgYnOCBzAzJvSBUxXsQkFnecZr+CJe8IR/V8m9pExyT96vdKUrzb86rOeenN/xjnesY/+Nb3yjztNp2BWNdzg23gUHk8zT0m7wzg7GJ1rGeRd0aHVd8YZ2/LlK7iVlkvvFeFdf4vBbq+lz8m++sgX00dOug0B36HedsZ4Jp0lqZDpJXbQtbpe4xCUKI4syo5B0TClRroxHRgYlRPlZhD/2sY/V46HqyKec1HOV5/1dPSUjfBkYMLZbsttuS5++Fv3HPOYxdefS7qt2GKTGyS4Ap2JWGJMBAZsD5pwsu0Z2xe973/uWe93rXoWBwBg37rPqf1vtwtBOW5K66+Z5W/WHZQwqDuR1r3vdcrOb3awavLvvvns517nOVZ797GcX4zSsP6v7JNWAO85xjlMdJOOaZEndwV3wgRHIOWOQet+OK74YJ8kibS2ph6VXSlLgz3ix08U5TZbWNxkTQGFYOyFhZ4pRBKChxQAAEABJREFUS84Z58985jNr22WGf0nK8Y53vAI7yfgni9OfpDgZoh4ZdF2MPONEJzIuBefoRgEMiY6kS+lV1zaXYaKu9+heO1Z2MQUbBPLog8MOO6yeklms3+3lo9n8dYV1sji/2lJPfbuZ5koyuT7aG4/opz/wKuFJW/hVJ8n82OJffntHO+apdYaBnUzur+zAHxnFK5yNn+fFXk9SaSPTeCYfyeI04AeP6McnXjzjv8mAsYRj61e+et5RT8Kr3UqBB8G9JHV9Lsv8MxeNlwCbfpNMbClJ5ffUpz51lW3vJZPrGhu04g/t+HUl4674god7dek3V0kenpV732kvc07ZXnvttSJey9wfHtFuvLbH81z1yrPTc+SB3vG+/EmpySi63ePFvav6rhL+yViS6rDLwzOc1KMjBZLh4llSRxDJKQWOnYA1WXVSRPlykz4PPfTQuraRPZjYBUffeJsC4+TO+u70gPmunoCMQAu6jVN7D5/oNu76aWMKE2VkBN+warx6X13vmQ90m+DFta51rXLVq161PPaxjy10m/LWz3Kv+sH7Oc95zrqm4x1vcBhvU0DfCUjlk3in59He3sMfGlfCO/0vEC4Yz+4QQDP/ksnzrvXdrxsPgd02Hkudo7VAgJKiWByzt+P7ta99rVz96levCx16OO33uMc96hHA/fbbr0b87dja4bSjKPJvURb9lx73uMfVY4Ii7trWRk/LQwB+nB0L3I1vfOO6KA1bYohc4AIXGGZN9d6iJWL82c9+tu6gWtyT0WLj/q53vWt1SKfa6Ywbg6lovZ0AxtOwuyRFwMWnJ8mIz2H5erpnPDklQQbsCA1pY5Ta9Xd8dpi/3PtZvkfG7H4yHhmyyULcObKTDLBZ0jTNth2tFgQ773nPWz70oQ8VJw8cZb3+9a9fj+Z+61vfKgxa86z1S0btJAngMfTw75h7krrrZ+w5e5zN9s56upJLzpkTF4LDgmZ2LPFkvB3/ff7znz9PMn59oiGA8+AHP7j49MKaZD0yR5OFMjH/4jq6scvomDqHhM5up1XINv5ud7vbFTy7R7Yrno2rXVM6VoDW5wccIu04bQMvdb2zntLXv/71KreCh74RfsITnlCPuj/5yU+uMup6m9vcpgjKNLo5dz6pkY+3s5zlLOVqV7taYVe87GUvK44db968ed72aO+tlyvbaN999y0Ca+RaYI3uxasxggH6jR+a5bknC/K3ddpCMPYqV7nKPO/knwPqEz1tLTcJCrAd7JD7jMOpLQ6uU0bJlnlFzgSI9UsmrSH6xAPHXDt0mHryJacHBAcEJ5zaMV/pJf2xJ2FEf5Nt9SXtvfOd7yzXvOY1q00p2OTTkmShbhOUUX8lCc2CY0vlHW+L8U5nK2/0rJR3n1bAyOlNJy/Z2Y9//OOLwMKwn9Zfv25sBHbb2Ox17lYLAVFMxgYHwK4lZeuIUjJS9pTx3nvvXXdlOToiihYZ3xRScnZvfWPp22PvMch856mt1eJho/Zj8ROhp+A5mqvNp/4ZqoIGdlHG+xe15myM56/3Z6ceGC6c4fVO62L0cer8poGdD8bgYvXWIH+HuyTjxiIZ6ZwdbmAdvyCo4lg+49IJEI68b+7txMhjuNqh4SgkKeSSseizBQYyfapuY5Fx/ba3va0w/tbjuCepR9Q5DIJ+rna+yKmjpEmqE2cnOhkZ8U7/+KzI5xUCGOr55ta33Jw++g8urnRSw2K9XJMU/Fgfk9RPE3wPi38nTtDNcfVdcjLimXNLtzpJ43SKYBYn1y4tx47T6HMaji7e1wuv6EhSjKtAFVl1L3gjaMM5N0ZsgAMPPLDsscce1cHHg0AN2efYuvqEAY9OFwlqcHDsrHtfP+stGV+fdnGK8cyhtzY2ngV0fFpntx/t5qpdb/aVY9V4Trav4/Dv0wu/n2AOaGu5ybxzjNzc8omab7TJGdr009p1b7fc1UmFYb5PbuzO02Uc91bm5IpNHIFF7XLkBWzIsDw4kAtOvXfIwO9+97v6eSc7k15gQyjTL1sUTt7h6MtfScK78RBIa7zTncvl/eCDD54nZ6W8OwkBU0FO6wLszBWfNPmkCh7znfWbDY9Ad+g3/BCvDoMWVYaF6KwjUJwEBkjrneKxqPgBNotTy09Sj8clqd/u2oliuPrVYos5h7/V7dfJCFDaLU2qkaQaRKLldjrUnVRvlnlr1e9KeCK/28KqBUf+8pe/rKSbmb6Lfnws1gljhdHDOOHcL1ZvrfPxIS1GR5LCseXU4XdbdRdrY5b56JGW2oe6+Gj1k9STNQw13+k7omlXj/Hsm1S7khyFJMUfp+aWt7xlOfe5z13nfpKqZ5UxiAVUfWMtAJtE9lTTOP3ba7zVd2116asnPelJ9Zet8ZOkWBMY6051CWI4kZGM6Oe0moscQu/6XtURXzt8dj/t+NsdtYNtjWr9TPOKfmkpbaonDesKbKJVANwaio+99tqr4JmBLviC5/aOk21kHs9J6g+Mmscce/LByTXOcLDL296b1hX95NR1e22qo+6wXpIi8ODY8SGHHFJ/pNFOreAEW0CQn7ObjMaY3PpxNcGaJFWm8f+0pz2t2LEXvPJ7In6XZ7yvYb8rudcuXpbahrpSq5+kHgvHM+cOj3ak7bIKbHBWYZCkvuLkAv6MaZLKcy3Yxv/Q6Jg43eDbdXK0jepLKsJD2wXm4D760Y8uHHH6pDWQpJiXSYoAq3damd/sEZwSeNROy09STxQIPBx00EHFeMID/bCg2/bZZ59aJ0n9TRd1bQRx9pMtmOCbfWlTiPwnKdP4w4cdejvgeD9wLsgkiLZU3p2cwrugiKBroylJ5Qs/y+HduMIIDk5iCZYIFjmVIfBV+t8uhUB36Hep4Z4+sxQdJarlJPUX7kWQLa6O0/nuSR3fclm47EBYjNVvSblE4VFQ6oq6+rEl0cdkOkq59bczX+E0TLC3qDj+bSF0L2/IY5Lidw0Ywz5xMCbqaMdVcj98Z5r3SYrv5xio433ptyV9Du89zzq1/oZXNEocAjLrHq7qNHqSFEY0h8lOkXL11HGVhvftub0/7au+JO26Svpk3H/mM5+pu1ueJXVasotygxvcoP6rA+3EgTrt/Un37d1ZXPWrXdeW0ABfzpjAA/lVpl5LSYpPfHzGY1dKfe+p59qSZ2VHH310e3WqV+23pE/3rvrkbOjMvTxlkjzXlpT71Mjuq3qSsiSF0cY5Yxzjl5Fvt8g/bcWIa23Rm/SnnXnOrza14cpAdiTTEdXWtveWk7Qpebe15Sr5DMBV0q866rYk372rZHxdW1Kf3sALp5x8Mojx66ipY9rJaKdaO47Fvuc976k/zkpGBKs4DhwMjrBdW+uL4LP62l9uau+7toRH44B+967K9OE6TMrQ6JMd+e5dkxQOLKddWxwyO41+48IOoSPGw/bw/K53vav+cJs2BOecxGh6S12Oj6v2XZeTvDue8Ei/WHvwIw3r6Kc9K1MfrfLdy0tGv8HDAXO6gpNEZj/xiU8UGwT4U7+1Y0ebTLAP6AJtmO8+T1C2adOmegTbZynKvLuc1PrzrntttcQRx7N8mLtOSurjU4DBfUvq7rnnnsVJC0EmTjGbB89+68HRenKqniRQZwxtiuhPm/LHE1ol/QigCwKxxeh4ecqWm6zdnFJ92g3nNPrBOwE3eRK6klGAhi334Q9/uP76fuvbPBSwEnjFn3zJu54FHgSoBHasSX7fxykA+oqjqp5kY0hQgJxw+vUr31XQy5xqJ1rkL5fn9t4k3smrwJL2JX0no0ANHn0iY6zwp51Z8m6Xn64TpGz9+axB//ruaddBoDv0u85Yz4RTyozxYGGnXHXilzYdDdx///3rL6nbGWCQUDgWQt9y+9VTkUXK2dXRUIpJe95zJIvh1nZBtbsrJ7hQ1nagLB6MCgYNTEWkHblitDIeRJHVHeIl4u2fvfMJA6MK5t7nODCC7fQN60/z3gLHALAw6ttCgx99oJPjLM+9nbhWpnzWCZZ2gvRDTmFClhnTjEvGB0OL0z5Ol6NtPhXxTSEny46E436McP9mMr60z+jRxvj7+pxG0q4dW7RL6HcV4PGtNUcG9n6McPxfM2BI2cHzzZ/vbf0zRNoiX3bDnLjhWDoeig/tToPmSW3gA16MUWNBJvTnHh1+IR29jD5GvPqtnSRln7ldHAFDP0jE+DRXvC+w6Og1PBh85gA5a+8u5bqUOugxH7VtDBr9ZILhzuGGLWOU0am+cVFPfbRK9CiHBBYcFbirk6Qw1Hy65KgpR9eRar8o7VfPGXXaNKe1x9l3BNlRXXjI80v0aNGGoIBnQZCl8DepDrrwgFbto1+CuaCBOU0n0eVoa/XJl3qS+YcH2CnHr7HTH93h8wKYMfDJKT7tWtuV0qb+yQjHxTy0A89J4hT7fQ7H1iWOkh1r396rq/0dTfrDqzF2NbZ4kOykCjzgmb4w9/CjHtkzj9Tzjm/c8UwelDt2Te7RQ8YdncWzoGELvDhSiyc0eF97nq2tjkLjG67eM1cEVNDp18jhoK72dzTpD53alvAgCbA46q5dazoaGr/WE/LgWV3JumTd0b85KLjsXvIbB2g2Pv65OM4dmRWETlIdQ/2RCzKtff8sGJ3LhqBzyRts2SOwgqO2l5OMIZ7JJJ4bH+YKPUl+zFO63/hJaMFnq4sW2Bsr5U996lPrv3IAT3JNV5EXzqdPQsi5OckOQjMarCHGkDOPZzjhT5lE9vVDvrQr0XF0PQy0B0fOtTaXm/BFXq0P5pp+BQrRnKSwQQRg0ORH6YyRz17oGnR7H17oS1J/5E9b5jq8klGAnLzTfea2gJ3AHZkQIPAu+9GYOLlJzwtYCFiTNfJkLji2j29OtTFZLs/tPbTvCO8CDU6Y+Fc1FuPd7vm0eCdb9JtTKWTNuODbSYCkb4a1cdwVrt2h3xVGeYY8WlxExjmTfsiOM2+BZ3TLY5gwVih3x+gZooxPytyCy/HnLDB+tEMJO3bmGyqLlJ3lGZK/UzXNIRcV5qBZrBk+/jkf/0QOZ8Gix2Fj0CcLFTkj2Nj45IGxaZdD1F8EnMFox2CWYIiwOzbIsLSQWXAYZxx8hl6SwuiwO8U4myUtw7bRJNruW72GKePKMVDf/NnxYkgyjpOFmJJfP9RFZhkQ5NeOPTlnhDBGGW6CU9pIFr4/pGOl9wwrfTBuODtkw48WMZxhb9EXuGGkjveFd8a4Nux8eY/jJOhmR5DxymjEB37G35/WM4MNbhxAeBsHfAhGMX45szBnPHICk4V44oNscWgY3eSb/hCYYNzQS5wmuoYROS26Wzsword+9KMfFTz4Fhb9ruSM3tMvmafz0OVYPEztdqkrMfDxb1fHD57BHd/6sbvMeLODhV9Hc/2yMwNXuV1uu9gMX3LN0HXvSKd89NnppZclO4Po9u5yEsOV85CkOHmFV4ncoBXdeKGXzHljKZghWKYefvHgXyZgzMMCv3BCT5Li21lBCeOvXMAX7Us+uWUAABAASURBVMoleo3TY8eT7uME2dX2a8/WkCT1mDJ66EE0eW+5yb+YgG+GPt2JB4kD0trHs6CT9ZEc4x/u5ia+OR1oxDN6OF3mKJqSFPPP5xXq4VlA1G61uklK45k+xTNsHQWmj+gxYyJwYcearBh372p/R9PBBx9cx4Du0A5epUte8pLFPwfIAeX00oHatk5xZsg33tXFM+fLCRN1Pv3pTxd0u5cE7gVHOYNJChlXl4wrd9rECRc/GOeTPI4LfdbmFHuD06s/wTv1l8uv/qxJsDM3zB30S/QJh8l6CQ+fRtBbaOe8CsChofFsDAQnjKGdZzo1iS6KgJz551+cUO63BMybxrMygWFH2/FH5zWezWlBMu2TG9/fcx7hwumnz13JjLliftROl/k/Noc5aMzop2Y/mAdwZrPRy0nqP2HJqWVrkGv1YSfP+KE1GR3JN9fxjix9GDfrkDVH0PHqV7961SvK2Yxk3Lxquk3wwjw/8MAD6ycXZAO/kqCCOerdlSR06c9JAbygiy5qvAtSDXnXL94F8dXHuzUJ72y1ZLq8C2LQfT4xoEvpecEjcrgSvvu7Ox8Cu+18JHeK1xMCnB4OGAOV8WlnBH0irBYwiwwjm+Eqik+xMUYoZ06o6LrIukg/xe64IKefIUSJytNeT6WIVls8LJ4MOIarBCuLWpL67/FayJOR0dBwS1K/wbUQO9rofYYJB84RumRh/TLlP4s+w8YuFgPQ9652lDi9jFDjzBlmyDF0ptz9os3hn4wylsgxPCWYMpbRzbAWlEq2xgjdFmwRfJgytAS2/OBjkupI2HHQRpJF6Vhpgd0Jc5B8oF/Cj3mGPmPMMGeQjveVpAhcMILMWe/aQfCMvyTFDxThAx7j70/rOUnhCOFBQj9aJGMk2JOkMJY4eeP9JimCWoIxgkPGg1PBWeYcJ6k/wsWZEOQYf3+lzxxGRrZxoAsb/a4cbc7eHnvsUf9tbkfBHaUlZ7///e/rt8P4lNBt5w8vDPxx3PHOiU9SGP+CpcYJ/QIi5jUd4VQD59c9/AR30OW+JTuEDEHvLieZr9rUBz7RL7lvMk+3c9jJkDXA2HpHPUld9OAFH/gdjg8dwaFNUr83ZfBzjJPU+WWs9U92OAva1odTS4I4Ze4vGZ3g4IwnmctZ3n9JCscRvfo0VniQ3DddRl8w7NGujEx4B6+eXdGJ5yR157bpvSSF/rBOwiNJ/Rdf4NeoHvLslIb2tccBtPZytsmc4Am9u5J5KxjW5BQP6JfkWauT0ckR6wqZJY/wl/CprqQ+PPAgqEa/upfQ5wQF2j0b3zbmnn1frj2J88aBavgLYJB7wUz9cX7Ns2T548zJNp5wRTf6JXmC4OjlPDWeBWvgjyY0qOsKL+ud+uajUwXJiC557KKmm/BszOXjmcOoPW3gmS7zrF2BMYEGZTDhOAsyND2PFmUtqavN5SbzyDfkAjpO3wge+2V6441eegoGSeqcJLdsDeuiIACaObgcT3M7SRFoMteTzJMliNKCOvoUHNeWCk5gcarxS37ufe9713/hA49+3HOcZzJi7fPuShI66GtjhXc6bMg7Xbw93q2rQ97Za9PinZ61eSao1ORTUN64rITv/u7Oh0B36He+MVtXFCcjI5pip3ibEklSja+WJ3947znJvPIff251S/+rCCSZxxPWwzTEquFYFvlLMt9Oey9JWY2/JEXUmFFjd4ozwMEUAU9SLL52KRi5q0GPPuAFhyGe7uUlqfKZpGJWFvlLUsu9I2mzHPOXbGnjmKypX5LUYI2+0T5M8pIRDehKUhb7S1Lb8X57rxzzl2Qei2Oypn5JUnHU/3ga0rNUPrwjJSntL0ntI9mSV6b0l6Tip8/t0d94GK/XnpWXub8kW+GeY/Lmiut/yaiOhyTzNKBDO67D1PpoeUnKcv9a+63NdtV2knna1dOH/FZneJWvPNnyjmcpGeW5l5Itz0nqeGpLG8OkzySl/bXnZEteK9uRq3b0N570rUxbrkkqbfLH63pudZLUMUu20JWkYleO+Uu2PCep9bUracd1Upvyk5SV/CWp/Wl/mLSt7zL3l6TSm2RRnof1vSeVwV8yakNWsuXes7rel9o9Wjwno7ruJeVJvLbslGSbPCep/OovSeUZPZNSMqqbjK5l8Jdk8FRqm2XuL0ltU/st4Wt4n2SeRvlJ6vvqDelQJq+s8C/JApqGbSajsiSl/SVZUL/RkYzqJKn0JintL0nNm/ScpPKrHUn/rsPU+G55Sco0/pIs4EXf5Zi/JLUs2dJXMsprdLh6JxnVSVL5TFLaX5KaN+k5yaK8a7fM/bnqR0oyl9P/29UQ6A79rjbind+OQEegI9AR2GUQ6Ix2BDoCHYGOQEegI7CxEegO/cYe385dR6Aj0BHoCHQElopAr9cR6Ah0BDoCHYGOwE6GQHfod7IB6+R2BDoCHYGOQEdgfSDQqegIdAQ6Ah2BjkBHYK0R6A79Wo9A778j0BHoCHQEOgK7AgKdx45AR6Aj0BHoCHQEpo5Ad+inDmlvsCPQEegIdAQ6Ah2BlSLQ3+8IdAQ6Ah2BjkBHYPsIrCuH3r/nedRRRxXXxUhXpo60WJ2ev7YIGCPJGElLpcY70lLr93qTEYAh3KXJNdY+F43+/VzXtadm6RSgF66uS39r/dXEg7Sz8YHenVFuJkkAXiblrzRPu9JK25n2+2iSZtjutJtecXv4lVbc0FgD2mxprGjNH9E1CyK0K82i7Wm2iUZpmm1qS5uS+/Wc0CjNgkbtSrNoexptok2aRlvjbWhXGs/fFZ7ZKtKs+de+NG1MtSlNu93x9lbs0AP5v//9bzniiCOK+/EO5Cn7z3/+U7ZliGHWvy/59re/vfz85z8fb2b++d///nf5/Oc/X5N35gv6zZojYDzIgn+j9B//+Efx78L6t3CXShg5+eY3v1mMsbaW+t5K6+nryCOPLGRU3+jAR0tkWJ3Wj3uy3MpdvS9PWau3Vtc///nP5aMf/Wjx77KO0+MZrXjEr3t5q0mr/vz7vu9617sK7LbVN/ok72yr3mqUocG/L+zft0a/50n9khd8SWRiUp21zDPu5uXnPve5rYKneBrS33iQv5Y0t77/9re/Ff+e8Y9+9KOtaFcHnTAnM/iQJ7mXR+4lddRVttpJv/r/3ve+V+jJaff/xz/+sdDB+ph228tpD7/wt76jbTltbOsd8uzf3sevvrZVd2HZbJ9Wg2d9rBee0WKOkb1p06Q97f7rX/+aOO9nO5JLax2NZPC73/1uQefS3lp6LWsO2xjOS39rdWuijU6DwSx6/ta3vlV1pn5m0f5K2kTTRuQdX+yAlsi4PPI+jpc85fRAq+9e8s54/aU8a++nP/1ptWn/+c9/TnxF2+rpBw0qucq33kvo8axsPLW6v/zlL8tf/vKX8eIVP5ML6z0a9bXiBhdpYMUOPcPwute9brnYxS5WGLvjxP79738v17nOdco5znGO8qhHPaqMl5fB39e//vVy17vetVicB9kLbn//+9+XF7zgBeXd7373gvz+sPYIENbnPve5dTH79a9/XZ72tKeVj3/840sm7DjHOU45xSlOUd7ylrdsM/iz5AaXWNFku9nNblbOec5zlrOd7Wzl3Oc+d03XuMY1yjOe8YzCCG2KgPzi89vf/na5293uVi5wgQuUC13oQuWFL3xh+clPflJ+85vfbFPGl0jSiqoddthh5SEPeUihBMcbQv973vOecuELX7hc5jKXKYccckjFerzerJ/N8fvf//41iLJYX2j9zne+U3UChbxYvdXKt1jQd/e4xz3Kr371q4ndkhO0vupVrypXutKVtqvzJjYy40wBH3Psda973VZBWJgLBN3xjnesc+BGN7pRWcx5njGZWzWPNrg/9alPLV/+8pcnzjN1vvjFL5ZrXetaxXi1RoyLMbngBS9YrnnNaxaGobxWvppX/b73ve8tf/3rX8vuu+8+9a5PetKTFvPm0EMP3Wp8p97ZEho0JnSoNfvEJz7xEt7YsSrWDTp5kjzvWEvbqb0DxXhmq7z//e8vJznJSXbgzaVVPe5xj1uDoW984xvXzRhbRx/wgAeUYx/72EtjYgdqJSnHP/7xy/Oe97y6XsF3B15flarmNb1qU+B4xzve1PvcY489ivWHbaWvqXcwhQbp3De96U3lzGc+8xRa27qJs5zlLOW1r31tderXmwxwGDca7+RMEJ09ae28xS1uUWy6HXTQQVutv8ZDfTYwX++Sl7xktSEe+tCHVruYzbz1iG4/x3z67Gc/Ww488MC6Zupn/K3DDz+8PP/5zy9veMMb5ulSzxp4k5vcpNr2z3rWswp/VP74++j+8Y9/XD796U+XE53oROPFK36muwSe3/e+981UX6/Yob/IRS5SrnjFK1YnbpxYwFnQ7AQxDB/5yEeW3XZbvMvznOc822X2DGc4QznTmc40P2grRro3MBUEGFQm+VnPetY6ic9+9rNX53hHGicbpz3taash/uEPf7gu3Dvy/nLrmsAU8W1uc5uy55571oDSD3/4w/KEJzyhfOUrXylXuMIVqgNh0pPpl7zkJYXhcstb3rJ86UtfKt/4xjcK2b3Tne60qKO3XNqW854gA+U7/i7aGQQU8jOf+cxy9atfvdzqVrcqAmnjdWf5nKRc4hKXKGQlycSu0ErBPvGJTywipp4nVlzFTI4DWSDrk7pFo0CFBYT8vOhFLyp0XjKZx0ltrEbeqU996rJp06aJOlQE/D73uU+5/vWvX+yykPMnPelJE+uuBq3DPpLUwPAk2W717GI5wfXVr351wVrytre9rc7N5zznOWWvvfYq5i4ns723mtfvf//7NfgnCH6sYx1r6l2TU22b44Iz9NbUO9mBBjm2+++/f7ne9a5XZuHowFAQlsHEIFtsfu4AySuqSg/gWeBPUJjzvaIGJ7xsrTzf+c5XT7N98pOfXPP5yZF75StfWW5/+9uX05/+9CWZvs471alOVS5/+cuXxz3ucZXvCbCsWZY5ZgeO/hHgJ5PTJsa85iQ95jGPqQ7StNtfaXvk/tnPfnY53elOV054whOutLmJ72v3/Oc/fw3s6G9ipTXIRIu1heyjcRYkaHe1eedMswHYDGxdG3ZsZSdQ8Dzk0xxgL9/61rcu7H82PDvodre7Xbn3ve9dBNqH9Zd6j28B+sX0ukCKzbQPfOAD5U9/+tN8s+5f8YpXlNve9rbl0Y9+dKGfXvziFy+wC1plQTJ2ztWudrVinrX8aV3pA3Y5POgJWE2r7WE7i3vXw1rbuRd9EIUBHtANtCQaQsgpOJMcUAREsoulLgPSQqx+smUR8KxcPfUlz/KR42ogCVZ7X35Pq4+AsTB5HPNmwKAgyYKJYfzaWCs3di2PnChjFCQpl7vc5QpjyOKo7mqkJPNR5SQ18HTxi1+8vOxlLysnP/nJy5Of/OT6WQmDkaNPyTEuBAPsSAhqqTuLHagy9wdjmNkFgRuZJ/uezRHYuco3TxgL37/nAAAQAElEQVSR3qE41FfX+wxNDtuVr3zl8ohHPKJc9KIXLY7CznUxlf/0byz1hyb3knz0oAWd7uGmU/XUV889mvHwsY99rNz85jefiXGo35b0BxtYNvrQ4hmtaGr5jWb0t3y0u7fj+sAHPrDsu+++RYT6XOc614I50Pqb1RVm6EQ3ftzjQ1KGF+OgjGOVpC5u8tVRJpl3DBM82mkhS8kW3TwL+tEER3TA0j0+8IAOdEn4sI6gwb0873jfOJ7ylKcs5i3+1JG0YZ7aZSD3Iv2MBMdXla9WwgeaybTFnVMmDw8SHvCNXmMiNd68JymXr34r8+wdZTDAD53F4Xv84x9fx1jeWiT0MADZAIxC/OITvcbZVcKDfDzgDa/edS8pw2+7d/WsDW0mKZe61KWKAKC8teC19YnuV73qVfXUIicUfWhCc0tkG0/4xv+//vWvGsDGtzryXZVJ3neVvKevJFXWObje04/8tUh0H4NdYFv/6Gk8uBor/DQ+jDM+YKVcUo6/VibPvat6yYhfJ88cv19LfvE4THixe+nkm3mNXnn4GfIFl/bsqg318Cipj2dl8tu999Q9zWlOU3cbOc76kLceElo4c05lChajSR5+8II3Mu+KL3lkgjyoJ6/VdcW3MvU8uxrvJPVEpFOGArfe1ddaJjQ4Mfb0pz+9bv6gRV6jG887K+/GxSaF05zWXTqcjcNBJed4bYlT7DS2jSJOvTVIHcHWV7/61cW11XUl08aV/e8qwUky9vqGoav1PBnZIMrIhzL3bDLri9MbZETbEtxt0gkk27hikzm5pmyYjJX5tPfeexenYLShz9a+q6Q9+fpGK/q9q8yzcrS7SvLIuHr6S0b66+53v3vdtJQ37TQVh96giWwg3DfwrkCxY+9YLYMQ4Y56YuaMZzxjXbwogOa8AUadlrzvG2yOFOfJsX4RmFbPrp2jN3bDtOlYSHu3X1cfAWMlsGOiD3s3juSBoy/K9uAHP7geFaT4fV4hcueo+w1ucIPCgUtSI/wmzY4c1x/2udz7ZKQw2vtJ6vGbu9zlLgUtghaOdZ7gBCeoxhq5V5dM4pFcc4DwLH/aiZHIEdhvv/3q7xPYZfSJACwpxTvc4Q7FTph7faPDDt1Vr3rV4oSMuXmVq1ylCDokqUcjGQgUr/rTSI41UdwUuggtBW9HVbDD/CcHAgloS0YOpZ14fFG63qE03/zmN9cTHhTsNOjaXhs+4/FZEDl0rBvdxvKlL31poZQdQScHQ2wFRy572csWuAv0fPCDH6w7rxYXR78OPvjgbX5SsD2allNOHzrl4hMQ0XTY081OZti1vvSlL11grG1jIFno8HHAAQdUedeGhZCs+70AEfZk4dzw/jTTpz71qXpqQ5AMbnQ6/F31IwhlbDgOntFN51sXJLzKT7JVAGj33Xevx+wt/MkWuYeTd1YrodkuB2dEsCdJsY75hMDOJiPVvDEWH/nIR+rnPj4PeNjDHlZ1ppNu5rKj64KKDBB8O31gjOhXQQr90E3Gnl6eZsBuR7FicNHr+Gjv4tNO0zvf+c7COGQDOMlH3sjdDW94w4oLXtzbLKD7yDF5OOSQQ4o8QVR6Gb/aFsxhVPqNBc9rleivD33oQ1XmjAM68CzA8o53vKOwiYyxefia17ymGHMnYuiWww47rOD54Q9/eMEzfe3TLjyRAwGpEc9Ha7YGmx1xpX8aDrVgFf+nXztf5lPjlxNws5vdrNDjjsKa1+g3zuw5ji+MGL3kn9ENI3LsUyWybjMI/045MZobS3vuuWfxyYp1t+Wt9dU8I69sGbQ4/WPHz3qMVlgYc/Paem0e07vmB91nftC1gjPkBJ6O72/evLlc+9rXrp+zaleyvjiCzB6Bvby1TsaCXjKOHD902TU1Z+kqm33G9b73vW/9FpoMkGU+ALuA3WD9JwPmA6zoDfmwoSe0iU92JpytsfCTt5YJ7+i2Dg15N8YCjHinq/Bu/Hcm3gW+yR85fPnLX15PuQmO3/nOd94KcvrM0XfjxQ9IUk8OGSPPTo2xk9uL1m/6fK+99ipOk8HQmiUgTy586kdPOBHrHeMPa7pun332Kewxcy6J4q3WfZvIbDo6KUnxKRp7ORnV95I2zSPBIRsx8tBLtpyG8TtP97rXvQp5pHeN5U1vetMCD/XQSEfRYWxcbRhf43y/+92vkHEneNGdpPAR7NDjT1/TTlNx6BHF8GasU1IGlaKm1ExigKrDcTBBKWRAGjhGmnvlwwQACwEF7ztmR10pvCYQScqNb3zjuuiJulAKk9oZttnvZ4eACCWDqo1168k4WpwZLAw4Y+kor8WOYeObOM4TwScr3qOwGbyMX89rnSywIm7o9jsRlBOnvtHFYGag2p1Ql/M0bVlMUpWI+SASKWLqE4eTnexkhbFA8ZpXcPXNpv4lyoRisUtGEbXxUUYZclbR3nhZ6ZXjRcE5ciVSy2C1S8VhQSujj8JrdJjPPgFwPJ1BzwBgHJElcx49aCVH7meR0GJh4bT7hMhCwFGCKRo4hDCijxq26KHs6TNHuRisDHB803Mi2caFzKN/FnSPt0kuzS+7605ecNCddGEAcv4sbvCVktSdWwEfcmMxNhcFXx1RE2wzlk7dmIvjfU37edOmTeWe97xnpcmiCH+Yy4OfxVUgiAzpG/70PuOPk4RW46hsUkpGi7i2HHlneOJ7Ut1Z5embketqTuiHPDF0OCxkyJymT+hTY+d47etf//pqGDFuktFnB+YQQ4MMMjbgxUDyHmySFOPGwdWevtYimd+cVAa4/pOU8573vMV67ZMbAXsOLINov/32K4xG9dgQ5qHgI13rVIMdMHJqtwYuApoMp8Yv2TBXOUjaWKuEHrvI5lsykjuy7OQLg5KOxmvjmZHIXrK7Qz+SCbrHji98bGTA4LGPfWzV9Z7JEP7YXcoYuS1P/lZpxhmO/fv9mzYH95oz0o2HsWL8M9YleugpT3lK/V0lgRlBNjrTOmT9F0ClPx1NZbDbtKGDBDuwkKR+qtXGXd56SG1eW7eS1J0+OsvGBH1mjM0DOssmhoAUXpPUzYEkRSBc0APfxpgTaF1kcwjGNj7ZGeY1R6TlrfWVzB966KGVhyTVuRKQNR/JKD3NsecoGV+OLptPUIes8wXIP13GgXPPDhDMMtff+ta3Vh2IzyT1ZKFvssmNvLVMeDffjV+yhXd27B577FEDdvjFuzninqzvDLybn9ZgASYybI2y206vj2Nu/OkgOruVeWbfk1l630ZDK4ONdYvNbP0XEHGKjo5UH1Z0oPmQpI4/rP3+DXvW/GELt/YmXZPUbPTCm8+YjPJqwdz/6BZ2UGsLzzaYzC80270nnwKM1iFrlB/P06Z36DgyzW4SkLOG2yiju8mzftGdpMinI4fzeY6Eqf03NYeeMekbYkYFx5vRZGDlD6nFjNTygJcsBLiV2SkTVRH1ogAB6l45YRApogyARHDk97Q2CFC+4z0bExEsTgZHlDwkKRa9Peei7MoIujH12whDuWDwmjDjba7Fs90GyrlNXs49g7PRQv4oOQEsOyuMlmSyTLd3lnM1lwRGGDh2tRk9FA5DiYJhQHIkk5Hys3NH+XBKzZNkRJNxsdPpBA2HlEG4HHomvcMhZGhbvMxfY6x9tAiIWBAov/auheILX/hCjYDCWNTTuzBHu90NxhJnGd3tvWlfYcvoYJgaR06QoImdMYodtoyTJHW39MADDyww5zhT6OjBH6w50KLaFkIYr6Yck1ELKHnkJJpT5MVYcP7sguAVvXgUaBHtZnzLt7soCIFXRrNTCE7VmKfemVVKUgSAOHp0iZ1rToEgg7lG3i2qrX/BPo6RXRDrQDKS7VY+6YoHhjDZ4kTCZlK9WeaRZXQkI3phTu7NEY4cXtDlXp71L0k9+WFumcfyvKMu3Umvqk8OGTuNfmNqzkgtb7WveDV2eGp9o9Mz+sgZXhqv7vFjB4NtoFw95VIycpbUo+vUa/xpFx6rOd8aT8Or/o0zHls+2jyzW/CEfuNn3NwbU8EY8qAcz/Ibz+3Z2kn2h+3imd5sedO47mgbdq+SkUx7l6yii1HeZBYGjQ/rv7kIK/nWBHjg3TOcvMcuYGxzjLUrwQq/bdzlrXWyFqMnGWFgHI2dRJ7xYvzbeOMPzZx8OOEdX/h3DwN11TMPrC3qS7DSl+R5PSTz3HqYjPhHE77w08YcBvIbn2TDSQO4kHV1G1bwwz/8XD03jFsb+lwPGJDhxXg3fnhrvHvG587CO3yNo6AUO4JNI7DKzhWENBYt4TNJEbj0nnxj65SO9VwAx0aB/JbIOafdOs+uZrOY2+aF4Bd719irL8jDadamYDAdI397SbtOT9rIEFhOtsiodzn0dJF2PSepv/Wi3zZe+jKG5JNM4tUnRrAxnurJUwfvTcbN1WGw1btJ6gl1fU077TaNBjGgHRE5g2NHgfPNQEtGzoXyltSX2oR031Kr4+poYhtgdRkG40KknuR9157WBoG2e9TGoV3tFlJeHAfBHuNoF8IE5hT5cTQKX3RubSjf0mujueWglTLgHImoMi6cQqGcGJIUj3eS1F8yphBM7Pb+tK/JKIoveikKaCfKUTTHxR0ZEtFvfSYpdsrNFzvI+ECrhG5BN0d0GYjypPbuSq+OdRt3O6dotNOITjsyFHIyUqj6dLwblpxIziQMvcuR5IS6ot2CuVK6tvV+kvpjm8ZPIIFjabfEDpETBBz6ZKTLKHp003OCKejTtkCOQIkF3jNnv/HkeTUS/OwACURIFjBRYgFRuxl2bdEBe4uNBZPDLoiBbnwL8ghuOK3gGNmsosnoGCY7svo13+wGOKLIiHDKwycjeFMf7aL6jq89+tGPrr9tYa4qWywpt3Db6XFywsIsb7H6s8hPRjKWjOR/2AeeJHntmmxdT/l4SlJ3xOS3d12lZEuZ8tVO5opxGu8XbcO87T0P6w7vvSfJa9ckHtcs4dkP9yKg0TR+73mYhvXkjz/La2lY5l5K1pTnss8++1Ty0FJvJvxvvGz8ecIrNWu8XntO1pbnStwx/2P70k+NNtnD+2QyrcM63kkm11PWknekZPt12zuzvuJdkAZd0rC/8edhmfvFyhfLb+8kmdd78tYqme941/+Q5uG9sklpsTqL5WtDWbI6vHOibXJYK62ZbDmfwFij2WZoYU+6sj8Fn3xWI8876PWeq0AVrNRlayhPUo+l64MN6LSaID2bllNvXiXxev1XLpykVOYULNuqFizyv9aPwIDAARtenjR8hRNuA3E8f1in3ScjWjwvpf54ncZzsqUdbU0rrdihBypjkPONWAPunjEIJAMruspQZPia+AbWUWC7dyIjrdxVGwxPQGhDJEjk2neV3iEQnBS7NoSCw6/t9s60gOnt7BgCJqLInPHzpnE3RsbcUSvHxhyn4QwbL9+WcTLssnEsOWztXTJll47Rrq1ZJ7JGluxYJqk/WIEGEWGOKNodXxaNs/vMCXJsioOKR/LoXbItoxppuwAAEABJREFUzZJeCtPRYzvXHEbfHDGY7b4KlCSpvwCMniT1nw7k0DslIaACf8f40OjenPIr9zCQN40kmmnMOYMcMdFdUXbH0pTpw7yFHbwcJeWEopPcmPM+3ZF8ny6AwblOZqME0SNR+o7do9sCzSi3C+gUAcdYnSbjIsT+ySjyC3v8kG/BCTtKeLM773uyZLZ0o6ulJIUcOMLmpINTBhZB3yNy5uFtrH13S98KwDrl4XMMO9dkXFDDokyujQccktnzQLdbP5zYaMfuRPXhiAY80hHGAF3wFmx50IMeNP9PSypnhJi/bU3AL/1iXB2LFBi2kz3c6dT2rFOS4gSFMTA/9Yde6yf5wZMrevHgGQ+u8o0X3elKX6mDT0m5ayvThnltDRYw1ddaJGPKKPPdoP7RhW58C7A03uSRN3zJx4e1Azae1Wvl6qpHn8lTT7vkAl7sBn2tVTK+xhnP6JLQ6oovvKNb8M8VL/LxhRd84Fm+MVXf+zBoV+9pr+HTAuprwXOSesIKLWhFA9rxQA/KQzeajc///ve/Yu3BG57goJ5ydWHgWRl5xyf5VubebrUAApz1tR4SfZWkNCcHreZ4o7tdYQIb440X+e5h56oMRrCAT8vzrAyvAqzWJbuASWSteTLP6eihzKMZX+Qa7XiFS+NJvjz14OaqnvF3hRUZaPneg5lkA4PdY8dzrZknh03HoU1C8yTejS3edhbejZcddj4YmtFOrn0mw48zbn7rAc/sUXafjRybHewgY8nHgxEZUc9azAbVXpL6CY3NX/3YOLERZc2HoT68Y3PHfKDb2b/sNKeCtK8cXXQGeUKzPGV25tnKbBprvhMh9E2TmWT0O1nmE7tAvnfpK20aLzKob/KoTc9kUZn+xsfZ+8q97yp5Xz5fAn3sEH1NO63IoUeg76MMjp1LP7pld03e5s2b65FUP3jjWxe7XoxfBqPdLckAOq5slxDDvjkAlu8hDbZvrQiDXT0C1fpgqDrCywnwLaRojW/xRXSmDVBvb/sIJKm/7mnMCKs3fN9iYttp82MpJrFvpMmDQI5jyb43MbaOv4rKMeTJlMmrDXmus04mphMETpWY1IITlBPnwi4mpeAkQZIaJfTdj+/S8eiItaPAZJvT2erNkmY7wRxdGDrm4zsz8i/SqF9zTwCMIyfyKc9cYgRxniWBCkeznYxQV51pJcrb94M+waH4OfOcL4EbZWQEbvQCRS6ooG8BHjS6V08SwJCS1TFcLCbkTqDEYoJmesaxKkred8vkHMYcZwoa/r5pZlSTZzpJ0MfOOD2XrA7tcJOSFI66RQ8PvgfzyQu5Ue47ZPSSa0fgLDiOj/lMwCLpSJ25SpbJCYc5mT0PyehzHDQJhBh3v7NhPET56Qaya5ed4YBGC6rTKuSJXmEI+ObOGPm8gFHBeRBA9A5MmtyTP3isVkpG/1wj46J9b+gEgrEQHHSc0fd6DBO7EIIwfiQOL05RkE27Dea69Y8eEtAgn3SpgIydE3VghT8ySU5Xi8fxfoyheeCkDprMfbrTem8uMcz9NgUnDY92UQRzGW3GzHu+qfUdop0hxhj7QJDNt7V4pDf0y7AiJ3DyvFaJjbNp06aCdvzi2xgx8ASGzTU2E70neCngKY+OJPt0NkzIhlNsxh9W3jHOnCZrjXY5vOY43OjLteIZ3Ww1/KKBLBszp2wE0tBnLuLVWinPumNOwoCTavxhYPzxLZmrhx9+eCHzrW22hOe15BePwyRwysFu81pAFO8+WzL2fi+Bg+LKqWAjmwN0q51NssC+FSQ2zmwh9gds4Mp+9hmHMeeYmNeCdUMa1vLeWKAf32iU/Asb9BOezXO6m31vDrALyTjbfb/99iuwUgdW+BdwNsetUfS4tZdOIO+cKu3aXDHX1pJvfXNUJ/FunNhdxpKuarzbuKDfdwbek9GncGSPLcM+YyPz9cg7h946bLzhQA8YN7+bxbZkSxsnY8g2gpcNX7Y2veY5SaHP6EzBZxs47Ec2VJJiI0gb5ha7gD3p9582b95cyJY1QbnfnXDyV9vocUKRDUqe6Av0mE9sOf225AQx20iA33vWEWuUdukxa7PTA+TTD1qa6+SPrDpRaA0i63xU+lm7ZJxdQs/Z5CHr2ubbWI/9iyzqTTutyKFPUkxMRi1jwm6cCQYEzoUjyoQWQBgxIS3wgOB8G0RK/FnPelb9tysxz5ixM0pYRD0ByUBh9IjGOS5pME14g8fo8Y0rg0BUfNoA9faWhoDFxaQg1ATXxLYQWXw5E4ceemj9ISS7RhSbCcuIMY5kwbFadb2rDTvgIrBL631ltcgqQ5iMklU0kluLCSPSbq0Fq/XCieb8iEIyRNTlSDA01U1m6/xQnPpivKKJ4hMUcS+JmOKD4hWoQJ9nCwxnrWEOd4nyGfKnjZUmGHF0tStxTHw/n6Sg3xhztMxtxg1ZEfmFp/JyzB85sWCMK+Fjiqd+sUtvQSITSQoHkEOiIwsJRwrdfiOEfoMlQ5VzRbcZCws4Y9wPqKwW3ehrKRntmHFyk1S8GVMCp0mKb8mMO7zJMGOx6V0LnwWV08zIFJSzKCezlelyzB9Z4ZBzepPUH3Zj7JEJZY7Yo5s+sXZYZOl/i6roPgfA+oEfc9J8ZCSI0nsP3xIjgUFwTLerdnFCRUDanOTgOYGAXjJkHARQGK2MHoEMckbe6CKOjntzxjroajfXZyGcJHPcWizQJ0jDqKK/rMmrxuBYR0kKY846bUySFIaXe3OEcWQsjaFfOubMMhKND9sCf7BgyPm8BTa+SRSs9J5yQRDrBhtAAMjcHSNjVR/JKb2LT46IZ84tnjl4jDk2jPFycgo/7unrV73qVfW0iXEU7CS3xlxwgIMHF3XpcTyzuwQ01kLPDEG1MWPXyRqKLkY03cgRYFTTJcbOGoReaz2dzwA2jniiQxnMbfwZyZxfuHkPjtoXZHdiKpmsk4Z0rdY925QNw3jHPz1krMxrPwTGocMHWbYOmteeybS1kPybzwKx9AFdRRaMM2zoLMFxu4TsJnIOj9Xib3v9JKM1h9Nk/UtS6GpjDgfzvM0BuoCONweMtTkhSOXenOdMwcMcgKN5bQ7AythrzxyiO5O1l4FkxDtajU2ykHefIAqiG2+8s3d2Ft7ZmGxdJ/isp+Sbv8aWIH9O99mwsz6TETYQe4HMW5utc/S8d9gVSYqxM950hncktj6bVpva8qN3+lDmNKS1j0xY5+lFc4J80CV8RTavuWZ+tXbIB5zlmT/0DFrYeNptSZ/eEQAwvzj41iGyS/8KRuqLfAo40mX6N4dtSpNNeo6tqn3jbLzpvfae+UoveJdzzz5u/U/zuiKHHiFJCkCkZDS5ksx/2yK/pSTFX5L6TrLlmqS+M6ybjMrlJSn+ktR3W55rS6X/rRkCJqFAjklh4iCkjUuS+TGTR4FzGFwtZnYFGbmb5nY1TAa7bqKB6pZV+kuygEZ9S0mqXJaxvyRb1U9SVuMvyQKakq2f0S4lWUBnsvC51Skz+Esy32qSrWjWt5RknsYkZfiXZMF7w7JZ3CcL+0u2fkazlGQrupOt88oa/CVb093ISDJP9yQ+ki3lycJ2yir8JVnQS7LlOck87UmqbDQeki3PLa8c85dk/j1lUpKyFn9OPjBWGDX6R4uUZJ6f9uw6npKt6yWZ54/hIDC2//771+OMScpa/gl82ali+KEtyTytyeR7PCdLKytzf4w2J60EQZK15TcZ/fNEgixtxxI/LSWZ519esvBZnpRkUXkoc394tlauB54Z8k6N2R1j7M6RN89jkvn7xpfreEq25jcZvVvm/gRHOHU2gjjQc1nT+G8qbSSpvyMgsOKkkEYbf8nWfA3L2r1rkkWxKnN/HEabW34wdO5xXf2XpO6Ycrqcpkgyz0uy5X4Sn/KkZNtYaZfNKPCpflknf0kKHSfwhMYkG4b3ZDQmyYinZPRc5v6SVD7L4C8ZlRuflpJRnmrJ6D6Jx5qSVF1XH+b+lyx8bu24Jql9tvsy95dkm3nqtlQm/AmW2YQUcJnVGsXpt8HgRG+SCVSsPGvFDv3KSegtbBQELLKiqxbexXhKUkTD7DYwduyGiuSL4Ila2aWwSzgeRVusvZ7fEegIdAR2JgQYFnY87AAIYE6bdjsJvgn0qUUyG8NhR2jGr99v8LmVndkdeXcpdZ1GgKXdTScglvLOatSxI2V3zi7NtPvDs50hge/1wjOZ89mkXfRp86s9O3CO7bbTO/JWPy3eo00NJ9HQ6bju4jWXV6JdO5lOJ5hTy2tltm+xAek2J0pm0ZNApVMAAqKzaH8lbToZtKvyvhLc1sO75hNH29zij0ybJj4Rfe0UBz0x7fZbe92hb0j064oRSFIc7/T9cTLZkExSHOOxMPtkwhEr36F4j0J0XEeUe8XE9AY6Ah2BjsA6RYABwcHlnEybREcZOdDJZB087f6W0l4y+kFAP5y1lPo7UocT4ZviZP3wi/5k9jyTI32th5Sk2Knf1vq/XDqTFMY2G2G5bazGe8bDkXrHgGt/U/yf3T2fFSXrS86HLCYpdJrPvYb507pnH2p/Wu1Ns51k1+V9mjiuVVtJiiCsf21n2jT4XFPAIJnt3O0O/bRHrrfXEegIdAQ6Ah2BjkBHoCPQEdgBBHrVjkBHoCOwXAS6Q79c5Pp7HYGOQEegI9AR6Ah0BDoCHYHVR6D32BHoCHQE5hHoDv08FP2mI9AR6Ah0BDoCHYGOQEegI7DREOj8dAQ6AhsZge7Qb+TR7bx1BDoCHYGOQEegI9AR6Ah0BHYEgV63I9AR2KkQ6A79TjVcndiOQEegI9AR6Ah0BDoCHYGOwPpBoFPSEegIrC0C3aFfW/x77x2BjkBHoCPQEegIdAQ6Ah2BXQWBzmdHoCMwZQS6Qz9lQHtzHYGOQEegI9AR6Ah0BDoCHYGOwDQQ6G10BDoC20OgO/TbQ6iXdwQ6Ah2BjkBHoCPQEegIdAQ6AusfgU5hR2AXRKA79LvgoHeWOwIdgY5AR6Aj0BHoCHQEOgK7OgKd/47ARkCgO/QbYRQ7Dx2BjkBHoCPQEegIdAQ6Ah2BjsAsEehtdwTWJQLdoV+Xw9KJ6gh0BDoCHYGOQEegI9AR6Ah0BHZeBDrlHYHVQaA79KuDc++lI9AR6Ah0BDoCHYGOQEegI9AR6AhMRqDndgSWiUB36JcJXH+tI9AR6Ah0BDoCHYGOQEegI9AR6AisBQK9z45AQ2C7Dv3//ve/csQRR5T//Oc/PXUMugx0Gegy0GWgy0CXgS4DXQa6DHQZ6DKwc8lAH6+dZLz43UcffXTz1Zd03a5D/9Of/rRc//rXL/vtt19PHYMuA10Gugx0Gegy0GWgy0CXgS4DXQa6DGxoGeh+335rNL787iV58YNK23Xoz372s5f3ve995f/+7/966hh0Gegy0GWgy0CXgS4DXQa6DHQZ6DLQZaDLwBYZ6FhMDQt+d5KBu7792+069NtvotfoCHQEOgIdgY5ARx/63CgAABAASURBVKAj0BHoCHQEOgIdgY7A9hHoNaaLwMwcemf/pZWQe9RRR9XvPf773/+W7bWl3Hf+vjvw3f9K+u3vLg8BY9DStlpQxxi11OrKN+byXVv+rK7605fkfnv9qIOuVt+z+2FSLn97bS23XNv60KfrttpRt9Vz3+q6924ra/mzuOpHf9tqW7l66HEvtWd5LW2rjWmUTeoTLYu1rcw7knvJfaPX1bP8xdqYZv5ifel/sbJh/+o0mof53pcvuR+WTfNe22gYtilPv9J42bBeu1dfvZbke3c8qadsLRMa0IVW90Na5C1Wpp76yiX38loavtvy1uKKrpaG/ctDd0uelTe6W75rK1PekrxW17XluyrznuRe3mon/aLLtfXtHk0teW5l7Tr+TstvV+Xed215rtqSN6lM+axS61O/LaFFf+25XdVtZcolz/LdT0rK2/vuh3W8p8x1mL/a9/pvdAxpdL9YWaOx1XFteZOuyltbyj3rc5iUK1tvCV3odN0ebfhqqdX17F1tuG/56/WKRvQO6ZOHfmm8bLye8kn15I0n7Q7f30j3DQc8D/isfqA8SZ3FePaOcvUkz8O6rcx1mL+z38/EoQfgH/7wh/Lvf/972fgYgK9//etl06ZN5Va3ulX9YT6NyZfcGwzJs+tlL3vZcv7zn78Oujx0uKrb0+wRMN4/+clPyh//+Mc6BpN6NB5/+tOfyhe+8IXy+c9/vnzxi1+sQRv5Ajc/+tGPype+9KXyi1/8ohi/SW1MI09/f//73wsZ+/KXv1zQRIYWaxstf/vb38r3v//98rWvfa3885//LOh133hx/d73vld51772XBdrc0fztSVo9e1vf7ugGUb6mNTOkUceWX71q1+Vr3zlK+UHP/jB/PxRF90//vGP53FWV/40E1q1C9+//vWvizaN/n/84x/FuOPJO4Jy7uEpkRNXbS7a0AoLtP3d7353Xi71CTvjPN60uugmD7Bt9eD6jW98o7aB3s997nNVXsbfn/YzesgFDOndYfvK4I9O83NYNryHubnb5h7+vCsZn29961vlq1/9avnzn/9c5Xv47jTu9UeepdaevmFqTsHzl7/85TZ1gjb+9a9/FXyQnzanx8f1a3PzVz3te8e19bkaV/3RJ7///e/Ld77znTqX5enb1RzAKzoPPfRQ2QsSmg8//PBC1swvekyeSt79zW9+U9s05sZVm8pWM6HHOmBuuB/2TZ7ofXPMFS/q/OxnP5ufO8rMn3GZxQtZh1uTVVhqXxlZhxtZ1b92la1WQgOarRPu9es65Jks0x3KWjJu5pj51fLa1fvK6XNy/cMf/rDqc/mSOWLuw+PXv/71NudIa3OlV7haQ4wTflyNpbEwPu7lScbRM1pbv95H689//vOWteCq/C9/+Utdn8k5/OSpBAvvjmOhbLUSXvBKX+HNmoxv+ZJ1gxwqUwfNQ9rUMTfpNu0My9q9OsrIMXnHrzxYaBfuEnzJW3tvPVzRCQO40AF4aOM3iT718YXHVk+e+UzHSeZMK5vUxlrnGSs6jO5utODBOMPBXFA+Lgutrnnc1ioyoz1leDb+xlobkjmhXeUbLcGHXsAv3Nr6BksYkXUYWOdhIH8cA/V+8pOfVBv3m9/8ZhnKjne8S1/CGb6T2hhvc2d4nolDz5C6+c1vXhgsywUqSbnwhS9crnCFK5SLX/zi5XjHO17F8wMf+ECh6LX7zne+s9zjHvcoBiRJufvd715uf/vbl912260anTe+8Y2LRae+2P83UwRMkve85z3lute9bvnkJz9Z8Z/UobF6zWteU+53v/vV9JSnPKWOn/F829veVp72tKcVBsvmzZurwy9/UjsrzaMsn/Oc55RPfOIT5alPfWq5613vWiiSSe2igUK9zW1uU170ohdV51NdiuXRj350eeUrX1kOOuig8sIXvrC84AUvqPxoXx1X709qd0fztAPjQw45pLzsZS+rP0ZDMckftuWZoXCf+9ynYvnEJz6xvOQlL6l0KUOrPD94ea973as6FfKHbaz0XnsHH3xwucY1rlEo1EntqUNXmLfGHZ7kw2J14IEHVlxhq+xhD3vYpCamktfouOc971le+tKX1rHUr0AiXTPeifpoJQ/Pe97zasDEWNM1j3rUo+bpfvGLX1zImPrjbUz7+c1vfnO50Y1uVGA+bJuD//znP7/c9ra3LRy9YVm7hzm9+qxnPaswOMgN5wLdHN9HPvKR5f3vf3+dj5s3by6//e1vi7L2/jSuH/vYxwr8X/GKV8y3jS744enVr351ucUtblF5mNS3vN/97nflgAMOKA9/+MOrI0AnkS955gu5N653utOdCkNR+8ZtmnN0KVjo9yMf+Uj9sdk3velNxRh5Dw+cQfJOH9FNjGJlw8RYecQjHlE+/elPlw9/+MPlgQ98YNVd3mcQ3v/+96+BpCc/+clVX+Fv+P6s79FBL5nDV7va1RY4mMrwft/73rfq/wc84AHV2JKPb+NkjCRl4w6uemSVvLzqVa8qN7jBDer8w9Nf/vKXquc+9alPVRkgT4IFylYrwRofxsS9ftH8wQ9+sPJr3cMXI1W+cvLA6bn2ta9d55i8YVJPgMK79M5jHvOYgnftS3T7M5/5zLoumbvWT+8M25j2PefL2m2cJHrzIQ95SJVDxjY9eNBBB1Vd+KQnPal4xmejA93WHu9OopWMm8fa8vtN8DRXtWF9aFg8/vGPLy9/+csXyFjrY5ZXNLMJ8Gb+0lv459Sj07rAFqA7r3nNa9Z56p1GE/7VIaOT5rh66n/mM58pN73pTQubqelvul6/sJOsjeTBO+sl4e/Zz352eetb31p1MVuck2b8JtEon46/6lWvWmUI7+Y+XX3InL3z8Y9/vDzoQQ8q5G7S++sh70Mf+lDZf//9y+tf//p5cuBgfOgE+tgc56jib77S3I1nax299trXvrbc5CY3mV9n+VHknZy3OWVNW89YzLG0rP/gIFj10Ic+tNrS9Ds9wA4hI2yUJzzhCeXpT396uda1rlV/3807452ZI+qZMwcffHChJ4yFutZM+pI8WofYp/LLeCM74fPUHXoGCQeJsjv5yU9eku1/1A9MYFPilKGBk0fRmRxXutKV6iQ3AIzkE5zgBNU5MTlMgubAf/azn60OpXHQxhvf+MZy1rOetRqI2h+2rU5P00PguMc9bsXeBFqsVWPKkLYAUk4m1lve8pZy/OMfv5iwFicTmeFuoj3jGc+o+Yu1t5J8ssTJsaCa+Azhww47bKsm0cxRYyiRNzRZnE5ykpNU54JBzpG3OO+7777l8pe/fJVVRjW5taCTxa0aXkZGkuJHKu92t7sViwPjgbJC47A5ci7wILjCGKDMGBx2cQ499NBiDqEPHxw089XcG7axknv8Mq7hZg5PaksdYwDTc5/73IXTectb3rKQI/ObIQBXRhE6BeomtTOtPA6IACHDFC2c+X322aec5jSnWdAFukXgyc3Vr371wmi52c1uVk560pMW2NI56JbIw6UudakaYCwz/kPLpC5OcYpTFAalCPW4nKgvj3PBQbz1rW9dnUyL6F3ucpcaOOVAcO7Jy53vfOeqTxkccPD+tBKszna2s1W93trkjF3veterwTYLufWEMd/Kh1fyxmnYY489CvrIy2lPe9rq7L3jHe+ojp5xNR+MyclOdrLCMbriFa9YjJ+5NGxvVvfw5qTom4w8ei4gaOySVKeEfmEYksN73/ve5XznO99Wa6g10dzBo4A2Zw/PxuS5z31uNXToUEE7eoBsz4qfSe0mKWc5y1nKxS52saoLh3Xoebsu9CXHnKF++tOfvgb/8cI5NecZXOc973kLPTt8P0k505nOVAP5HEp4WkfUEcC5wx3uUMusJXYu7eQqW43ExuB8nO50p6unt/SJPrJlDuELz3Q22UxSbRM60s4k+r0zntq40o/Glb4my3ijY9lA5ic59svI9L13xtuZ5rP5RmeQL3Ksz0tf+tLl2Mc+dtWFAoDy0XnlK1+5BuuanQYP753whCes/E+ii4NqV3fzXACR48+xZaTji4wLXsLCOghX82FSO7PKY+fSh/SToDUH6w1veEPdIDCedJl11ppCHt797nfP6zY8cOro5sXGnCx97WtfK8aVXmOjWCv1e65znavY/ICveXSGM5yh7LfffrNidYfbJfPkgwwIcmyeG8NNmzYVug1f4w3KMz84VmxB5TCCGZkR8KcL2Y1sfGXqrLd0latcpRgL/DfabKxc7nKXK/SRMXOKmDPayttV8IIsse3oPusTPJSzTd/+9rdXu818MsfNNTaH8o2WzGWyDTNzm84U1GB3neMc56jBTHa3TWN6ZJx/tqz1kD40Z6z5ggTkhq3Dx6BLzZkb3vCGRdCIrTHezvae12P51Bx6Qmxi2kFkPJ761KcuJzrRibbLM+fD5Odc2ZUQobJQGxRRawMoGViCbAfJAk5ZUuiMH30bLA4LJcmw1taDH/zgom2DJcIlyqtNbZT+N3UEkmxlfI538t73vrdOSBOJYWKc1TEu7k95ylNWB4jRbUEjS8qnnRicFlqyw8DgvFHGw36UkSsGxUUucpFCCaBRvnoUuAXoWMc6lsfyute9rlC0SQrDkkFK1lr9WmkF/0tS9t5772oYMAScWrFQJlnQKszsgl3wghesWJ7qVKcqu+++e7FoMqaPc5zjFAaHxXKvvfYqDF+L5YJGlvmAV0b74x73uCLaniykrTULVws82jiPniXlnJghro5FOamTTG7LOytJSarzwXkwlknqjjQHw/OwbfqKPJznPOcpdug903vqcMzQDdckRRDFYq5s1imZjE2SKgNlkT/jRefig/zj12dLFlWOICOkyZGyS1ziEoVD4r1FmlxWdpKtdAcHXgBLXzCmG8yp8Q6UM3gFkel5vJAl+fTIiU984oL2JIVzf8c73rH2JYggAIdXa8R4u9N+Ro+gocCJtcu6Rp+gVeLoc1oYKQw6fIzTYN5zeo2RwBenCCZ+EZdRaCdYGX7NLfOeQajv8bZm+ZyMxjMZOa2tL0YqY4uRZceN06Zszz33LBwVdCepp7zInfmkvKUk9eQefugZOpAeVs7mgBssBY7hy3FWNuuEHjrU7rgA5LA/QShrAyeUMdl49g4H7bGPfWwhi8Zq+J57dezEOfXWxhWfeNSXo8jkmx6H3ZnPfOZiPpMF72pjFomuEFjRJ33nNMmFLnShOs+Mm3xJGVya/kYTm+2c5zxnHcdJtJFxBj1+jT870ppgp549R/9c4AIXqH2Rcf34vETbk9qbRZ6NC8EUczBJIWdotJbqz8kUdCm3GZBEdg1g0DUcjHE5qRWO+Z9gDUeDk3fRi160BvuMORm5zGUuU3mHrVNJ8IH9Ma+u+QWd5vgZz3jGeTqtg444G9shgcbM+k5/sa/wpFw+XcaGkJekkBn+hfbVWW8pGY3xkC7BSk4lWZA2bdpUMRnWcT9c6/BnjrMxlJk7xtj7SeoJgCFW6mw1YiXyAAAQAElEQVSUlKTgl07Dr4A7Wx1/MBI8ky/R+9Y/ZcOkjH4Q7CJb9KT5SI4EkMlgk01zVqCArTNsYwb3q9Lk1Bx6QkhJWbBNvD322GO7DJi0HB67YXa87FZY6DlYwHekkBNPqTvKwgET8TSolJ0+7O5p513velcxeUStLDSiMwbKu9phHDHEOfXa2S5xvcJMEKCIGJjGwW6mnTfjx5i1O2vcdWwhtFiZfMrlTTsxpkX/RIAtHMnWCpk8ow0NFlcRVoaFd4f0fG0umk6uyKAyskzeyOKw3krvk9TfHRCwMlcYNONtCmyZQ3ZLlCUpnHiOC8OHEZyMeKX80GuuqLvSxPHiNNm9YFxqD3aS+5boC3OWQ8Wh91mN42Tmaavjymhn3EziU/m0UjLCQ3sMLpFcQZxkS74yARHGK8Nqv/32K+SBMYLuZFQXrwxtRq+Fw3vrNaGVw0EOmryYh3DneNhJwmujn+xwStvzalztQDuCSAYs6sM+0c+4NgZOY9nJEVQTADYHktGYeIdjQdYZv+TU7h5jixOofNaJzHNG4IpmBolTNIwJ8iOQLSBtF4ZcmRc+GcBjo41D4336seUZHw6cgAZ92cZRuXtGzbAN+WuVzHM6FY/sBePFqUVPMhorWBg/J0vaeqC8JbzY0aYDr3Od68yfoklGwQP6h/NMr1v/23uzuqJHENUxaIHqZMSHfH3i2djYWbaWWBeME3mwOcFWYTOp6x3JfUt0NkyGWJivbCdOpfFPRn3KJ+N0Znt/Ftdk1B9a9ScIdclLXrIGypItZfg019CorjlI9gUwktF4yW80uifzZHw4dt6XD0dtNiySVAfJ2ubdskp/dBFb044xPWO90LVAEueLQ+IZ78aYfYFmwRkBHPrMmqwOuiX3LdF59IJ8R4sFi9kYrdxVmfUIlvSyvPWQ0EXPNZqS1E9mjTs8hjTCTgCKrqPTvNuSsZaXjOTJusR2VD5sYz3fW1vMSTSa7z5zpJeSEU/yh8kYC/Rw6L2rLNlSl51GpwviJlvy1dsoyanIZKQbrF1wMN/MK3oAn2QAlvR8shAH80zglKyx0ZycYY8mqZ9/Km9zj0yxdegW7a6ftDxKdlveawvfAi4jmPEHSIMg8rGw1sIn7zhGwUkyme38UJCApqDUtmur3ABQ8Ca/Op4NgB+J4dSbKI5nMAAMkLZFZyz2lIroKQNbvt0NE0L7Pa0uAknqbqGJuXnz5nps3C49OTA2ZcJfsnCyTqiy7CwTnoIQzXOaQ/Ru2Bi5YjiSObtqnAafAti5FfVrddWzaDdFjRdy6Kicxcq8kNfqr/TKKOBsOmrpeBaDaqVtTut9R8yMrx0jdMGmpdYHLBhgDDMKVzTf93OObTJElbe6ovSMXePU8mZ51TfaRMeTrWWPHmFokgeBnSYPQ0MDv+hW1hbzWdK80ds2JnbaOWr0/Di/1gEGNceILDm9xWE0J1tdbQh0OYkjz9wnfwKKDE27R+oom1XSvlMydjAFsNGHHgYcHtBgd8JpA8dN1aUfOXNo8r7rzpys3dZfwQxj+dGPfrQwYoc8MdSs604RJVvPwST1W1pH+o0zjIxna0MfdnY4/DCdNW7Gx3g5LuuUj2c6QNI3evDMKeP4GndBDQ6bQICTCYvpysbTjl6TrXHb0TaWUh9/AoL0vWD28B38C9raaYeBoJPxYpd5z5gNr8N31/u9Nc6xX6cNnNTyiQB71amQZIQ9/mHjZJEdQs/WBaf3BCbJCf7luzae3fvUyc4kR8Q77GBrjuP8rZ6r9chvTcHX83pM+JlEl3z62iksO63kARaSsvF35CUjbMfLdoZn64wAhbVsMXrxaE1wxJ5NBItWV5k1wYZmsvPi0PjZ3pWs+00Vn/bAbVifz2CdEOxKtsaC3SWwb21lp/mEk3wN29hQ98cwMxWH3qIEdArOQioiIoJ0TB8TLwTVbrtFmSPu2U46Y1mk12AaANEZis93gxwvilRdi6IFn7MlamVx9M1ykmLiiFxTojq3I8NxsOA62pdsLQDq9bS6CGzatKl+c2ecOW2uxhYVomYCMQIyyWzGi5IgM45+M6QtzvpuKUlhWDLGLMCudtRE4QWtWj3OhJ0HTrY8MmqhMh/8QBMFnkyPBzQLQKBbsECgS78tOSlAoZk38iwEDEbzhdHlXp4yddS1u+l5pckuox99MlcZcvpyAkdgpLWdpH5naWyNseCHACBjSECg1fOuwBw5aXmzvpJBuwucrmTrMaNvyAF5YERZXO0w2rVumKKbg8bQSrZuY9Y87Ej7SQpj3LzDOx44ugwsuwSMLc/abGXyPK9GSkafQ5B3P44jqDberzXDmKDXlb5nRHPmWl282U1TlqTgzxpirVLPOCazHatk1C+9Q6+Qf46t9UtA3Dxo+XjxjaDd2YY/XugW78szHvLcWyfNYTKJ11ZmfnMMktnyho4dSUkKHWH9R297lxzaubfz0vLGr0kKneCUlx+bolusF+olKXbJ5TPmOM7yZ5noX795wI6h8xyRZsvsvffe9V8aGfZNrzSe6e8DDzywkEnvWUNsbvhcavgOfZ6MdqzauMLMPGTP0DfyJfn0uZNhyezH3HgxmNGt3yHdcHFqwRHxJMX8cyrP8Wv8OiHjJIYj6Xho79rdNqfJNZ7ka8vpFbJMxuW3hGeyn8yeX7RIyejTDyf8fE4hkEOnmM/JaKzIpPWMnOLHewI6bFH8k39BACc4rB/KW9KWeY5nesFJNnY2XdH4tu54n65o762Ha5L62x/GFK1oMn5OrNHPnuU7genTitvd7nZVF5i39KDfXLCB53TbUAa0BzPjr42dJTVeybrPvWxaTqI9Ga11PkWyGUS2vNvq0uWCn83ObPkb8WpOs8Ns/A03V+DhlJoAmt+tMO/G+YeTOcePhKUgIruUvDk1SmdpX1vky1xzAmC8nZ3xeakO/UTeAGO3kKCKJPpBGMqdgrLYKAeu5H7YCDAdK3L0SJnJardEO8pEdilvV31w6AULtOHZIDnGpC6lyWmiFCkOi7hFkpHjmxuDZ0eEgnSMRxs9TRcB42AcYe3qWQ/uKWf5knGWyIRfyzb+jBIOtXfUVWa3nEFkcdfOtJM+TGY0WSAYQIwC/cinNNDO+HJ1vNE7nHc0WWzURbMAksWqGTRJ6kkEzxawZDqGBjrINzr0a35Y8C0Q+ICnOvBkNJF1dTmX3hNkY2wKlpkryuxaMo45qmUKf44T2q1qCW0MN0oZbWjRL8cFZnYiPCvj4NitQgb+7Hr7pIYukbcaCTZ2RBgOyWjcyCtjG42cdOMKN3Srj+699tqrHjdFt50o45KM3l8Nuo0/+vQvtT7lodNVfkvkocm4nUM8MRbV5eAKrpgPvvV2rFP7cPC5AYPLnGl9TOOqfanRp03P5iKa5DuKJ/DTytCPJg4PmXec2TNDVx3rkKtk3irHV5I6VnjAtznqXr1ZpiTFSTTrE+MCf9YyRgb5YdAqw7Myp9AEOs0h9OOLY8AAtlPjXQawd/yQoeCYNdJ6CAdzzdWcSjJL1rZqm7xJ+DB2kkp4k4yp8aNLzSllkvp0k92VZESzPDpWe97Dk6s26UDBNWMoryVtkV8y436WyZj4kdem8+wG4cnvT9ADaGo8c8oEZTj2TjO2d1zZKwx5hihe8Yx3si2vjat5ysnDO3mCo/UJLjYy7FrpY5Y8t7b1iSd0JKPxamVkFA7W1iTFmsSew6tkp/pmN7tZ/fVy81A79BI7zSeV9A79ij9tCaab6wIE1gZ9k/Fk9GOxycL+Gx2zuJI9Y+Qq6OZX6O0mGhP51gt57FJjSAbU5dDjXYKFdVHg3xirx/5Rj8NvnG0ceBcugvFSkvo7Omxtu7nm0Cx4XG6bdKnxa7QbJ2uqOU1uBTroNvNWgIeNDgs/MIsXc0mZkxxO8HgfNmwFMqD95dI2y/fQaOyNn6u+5Jn7Tmo62dn0lDrGlWzjT3315HmP3iIbyRaZtgawO5oMqLfRElzg4be2OOvmO1zgKCkj99ZK66Jn2CmDpXlCvshKkvqbFYJh1kD2sU1e7zmFCWvBYPaltWIjYLlshx7wJiUlxoBleACXoj300EPrP8XD2JB8pwj0IWDJaLdCFMZCxRChvCl/USg7c4RfNJPSdhSXg6Iv9y2PAvRDJAx/fRgs73t29NIOJqVhgNFMUQzp6PfTQcCEgjWMyYBJpWVGqN0vY8yItUtMYTNAKGu/+Jmk/pqxSerYtd0NuxeOTM7qqLVf17dg2EG3c0Bp6A/9ZMVC6Z48+mdHHH9iVKDLbiEFgT+Jsub4z3qhYeBxphgDjtrhAW0cSkbwvvvuW39lFx2O/4ti4o2TbbeKsQF/u18iln5oSR11GVR4WWninFiIWrKAc1YYmI4fMlTQjkZ4o5+jRY8INlDgyUgRm8ecl2nRthTe0MLwZFy3+mSVwdrkgYySB/pIYNGJBI5mMqJbZJ0hl2xZjFtbs7rCiv5EU5t7+uL0kQF55BoP8o1Bk3HRaT8mx7C0O+q4H/mwoAqqKWecclC0z3lMpsubT1g4I/QEOUcneRHoc9Te3BNoEHlPUg1a9HtHMMpOoHlh/PywnLlA7+BVolN8l44nz2uRyLzTNRLDHpYMWbu76DIXOALkR0CTPvWNOfn3a9HWRHQ7aaYtJ4qcBGKM+D0NeeobK78K7nc87PKbf95brWTsrMvGT5/G1FXijKHLiTrrMiPeDokyyXrhBJSAn2fJGBs7PJEN+JFRMuzqdCAdSE4EoNSj29gK5CCZrqyiaZiMD6Ow6Ty2B/qtEfQfZ5wOdkSUbNoAEQQQFG7vuMqjP8kznmGFF+PKGTD+5NhJFaeeOIH6otutozZUzFGf+iSz5bnxz8lwGiZZ2B8ZMBf9SnsyKsMXevEq0fUcF4HdJPUX3dls2ibHjHM2gjVKMJregYXfIDBnYOFfkfG7PJwc761Wwp/5ayzNPacMbDAlqf8kpmfOlx1oNHpmH1t/8d6Sec92ZueQX7zQ2ewJ9gl7Q8DOuPoUR7ADj+wtsmQth4m89ZKSFLItoMrW82v3TkNx8s0VJxrMCfa9AGvDgh6DA4zMG58ZWHvpSO3gnY2QjORpvfDb6KDn0CsQRY+TEU7kfvvtV+h0n0eSBXaPuvwVa5jj43SljRXj7H3rsDV5OLbWBEEROLQ+N9oVZj7FMt4CPdYKa74gKYfdCQfOPj0h+GmjllPesGQjsDXJjlNacBRMoitt8tJVdu3NHXXh7ZMt72wELJft0GOeQ0+RmrgUDKNRVM6CY2IaAEBxgExk77REUAmsd3/wgx8Ui5FfxmY8ymPcWIxNbINBcTK0OeQWAT8wYxfNABk8yoBi0K4ItcXUN0eUiHwTSEScsmg09Ov0EDD+FiILLewZZlpnaJkwDBVjRZnbtRB9ZnwZX/WMm3+GafPmzYUh5gfSGPPKZpEsvgwDyhSNjEILTJKCVgsxmU1SyBG6GKFOFOy///71h3jQlYyOSa3GMSg7cI5o4Zf7kgAAEABJREFUUl52Mxj5DKRk9Cu7jDpKC5Z2RhgD+OMAmGtJ6s4kBQlrwTanYjhtSbAz9cRRZ7Akqb+s79kijkZY+qe1GOnwo2gF5BCRjHYzZ0mbfsYT50cQYZhP//jtDTRLjCgywGCzWDM+kxF+SerxQQu1usN2ZnnPCXISQsCEHm59cfIdybS4tfwkxRgMZZzjx2AWdONkGY8k9V8qISMwoHs5UOQwGfHb+lnplUNvnpEJRpD2yA1HKEmxljjWiw5l5ib6mzNgbUAn+vFm/TCf1ZWsD3h0v5bJukhHCmDjmaHf5iwnEE9J6s4CXQlrcmQdE/BMRj9wybnDH13LuHGfpBg3wRhrM7wEm2C12jzT4YxPhhnZbP0z1ugmhu9+++1XjGeyRZasI5vn1oCmB7xnjMkk2eYEMvJgQiboshZME+wkQ4IJggT0yTAwp63VSNYTdMEdnRxSO/KCrn7kF8+T6MAjWUhSf+DXMxsnGe1um99wJTMtCKsPhi2n0vpL57c1YVIf087Dn4BCsmUMWx9knCPensevdsuaTCep/zwlWy4ZyTgbz1pn3IcyTrc2LBj09C8cxtuf9bOdefxxGIY7x3Qu2ea0cswlGJGLIU2w4+AJ5CSp/+QtveVZorPJC7vDmrRp06a6frc2BHnMjWRr7FudtboaD3JJF5vLHFo6OEn912+MZ7KF7mRkdxnzpsvME0Fmc5ndTufZwV8rnrbXL3lwwtjYs7vUF5RyEoVPwq8hCwI1cMEnfW9dtdb5p0zhZo5z+vk5yRaMvEMetLtRU5L6T//R4zZR4GWHXRDXjjpspYaloD0bEW6w5OslKWxetoONXz6oNZEcJilsDPORnSHIIkhkLm4ETJft0Ccjo5BClkw6guleYhwyjjlsHLNki2ACLkldzNWVCLcoPCUPXELveySDYFGm6A2wMpFe5RS7ZwOqDZM9SbF4ehb95JwRCs8GLllIB1p6WjkCFiuTC84Sp12rJpoJaVIZS2Os3HWPPfZQZT7tvvvuxc6mxdGORzK7sSKrvnlEC+VgAW2EkCOLJ9mSRzYtzmR6kgzJ8466s0xJCiMJzegzL1p/6Hd0uuXBnWFnAUCfedjquoezOWWhbHy28mleKd8mCzBCj6s+0NjmrrmMB/lSkvrPWJErz6uVyB1DYtgf3WZBSUbySB7IDHmgW5JRvneSFGV0j+fVSEnqd8PkQiLbrV9GgTwJvcmIVnOPDLWxNzfJhPEiE8monnbUNVfI17BtZdNK5jwapb333rsarg13edaQYd/oRj+9goZkJC/op2+GsqTcXBDYcL/WiUwLVuOLkYYXNCWjNREPsBYAbfkcOydsPEsC39ZAcjmUNW3h1Twjm8ZV/dVMyWgs8CcJtiQjeeJ8y0O3eZaM8ht91nZOUnt2tSNF/sgh/oy7NmA4lAnlMIEfW2FcBrS1Goleazwnqd8ToxfP5uNiNOCxleOZE4An9fENO+MqIDIcV/rcekqfkxF1vbMaiW7fa6+96nwd9peM+E4Wju+wDl3bxjpJ/S0B9lqrAws8WfPamqEMf96DhQDWEAvlq5HQQJ8KItnUSrbwKehkvIeJTvLOkLZk9FsQ1hP59JNxbM/G1Xva4aiQK/UkZeq6X6+JbmbPk2O8NTrt3hvT9tyuZN1p3iFO9Jz3+QJDPdfeWU9X49QS+UxGv09DTlq+q7XOGCej8bcemO/0g3JrnXk1zpvA1qT88Xo783OSMvQj4GGe45sM0e3yWqIfzH8yY11o9q/5we71Lhls+bBRn72pLToo2TJ3le/MadkOPaaTVEWejK4tD7jJKC8ZXZWNp2RUlix+9U6ypXz8OVlYNiw/5r7S2GiS19NsEEhSvx0fxzpJaX9Jap1kS14Z/CXZZnmZ0l+SReUiGZUNu0pGeUmG2fU+2TqvFszgf0nm8UkW9pts/Tw+FuWYvyTz7ZQZ/iWpOLcuksnPSVqV+Wuydd584Yxukiygt3WTpN3Wa5JaL0l9Xuv/GWcpSaWr0ZOkjvN4WbKwXpn7S0Z5SeaeFv6XpLabZGHBlJ6SLKCzHPOXpOYnqf2XwV+yMC/JfN0y9pcsrDtWvOqPyYieJAv6TlL5TEbXVphMfk7Sqsxfk8y3MZ+5yjdJ6lg0uSvH/CVbaEtyTO6WS7J1ntJkS36S2naSymc55i8ZPY/3eUzxql6SzPeXZCK9ZewvyUR+WrVkVJ6kZc1fk9R3k8znrdZNsnifybbLki3lSSoPje5k9JykZc1fk9S6SebzVvsmyUQaklE+OWwpyUTykoX5ydbPSWo/4w0kGc9ad89JKu1J5mlLUvPmMwY3SQZPpdZLUq9lnf8l2WqeJ6O8JgeuSYq/JJWvJB7r/bC8Zg7+l6TWGWRtyNskFUdYtJSMeG/P7ZqktL8kC/BJUttJFuaXub9klJdk7mnj/Lcih37jwDDkpN93BDoCHYGOQEegI9AR6Ah0BDoCHYGOQEdg/SPQHfqVjlF/vyPQEegIdAQ6Ah2BjkBHoCPQEegIdAQ6AmuAQHfoVxn03l1HoCPQEegIdAQ6Ah2BjkBHoCPQEegIdASmgUB36KeB4uza6C13BDoCHYGOQEegI9AR6Ah0BDoCHYGOQEdgIgLdoZ8Iy86a2enuCHQEOgIdgY5AR6Aj0BHoCHQEOgIdgV0Fge7Q7yojPYnPntcR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCOy0C3aHfaYdu9QnvPXYEOgIdgY5AR6Aj0BHoCHQEOgIdgY7A+kGgO/TrZyw2GiWdn45AR6Aj0BHoCHQEOgIdgY5AR6Aj0BGYIQLdoZ8huL3pHUGg1+0IdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2BHUGgO/Q7glavu34Q6JR0BDoCHYGOQEegI9AR6Ah0BDoCHYFdHIHu0O/iArCrsN/57Ah0BDoCHYGOQEegI9AR6Ah0BDoCGw2B7tBvtBHt/EwDgd5GR6Aj0BHoCHQEOgIdgY5AR6Aj0BFY9wh0h37dD1EncP0j0CnsCHQEOgIdgY5AR6Aj0BHoCHQEOgKrj0B36Fcf897jro5A578j0BHoCHQEOgIdgY5AR6Aj0BHoCEwBge7QTwHE3kRHYJYI9LY7Ah2BjkBHoCPQEegIdAQ6Ah2BjsAkBLpDPwmVntcR2HkR6JR3BDoCHYGOQEegI9AR6Ah0BDoCuwgC3aHfRQa6s9kRmIxAz+0IdAQ6Ah2BjkBHoCPQEegIdAR2VgS6Q7+zjlynuyOwFgj0PjsCHYGOQEegI9AR6Ah0BDoCHYF1g0B36NfNUHRCOgIbD4HOUUegI9AR6Ah0BDoCHYGOQEegIzA7BLpDPztsd6mWjzrqqPLf//63HHHEETV5ngTA0UcfXY488sha13VYz7087bh6ntTGtPP087///a9Ik9pWjp5GFx7Uc1UmX1JH/iyT/vQDZ32iYVJ/8tVTx9V7rZ57eZPKWp2VXPUNy//85z9F0pe88TblKWt0HH300bWKfDTKl7QlrxbO8H/60V9LaBjvDh3y1TEG6JennmtrQ5l7ecpmndCEFn0O+5KPVkm552F5u/eeOuhWr9Htqky+cvftnWle0aVfqbWrb/n6bf17buXj12F97aBVXntfGy1tq53xdmfxrH80oq3RqR/5aDRvXD3LHyY8ece7knt56ri2dpVNel+9WSd0oAst4zTIxxse0ehZfffyJWXS+LvoltfqjrevrVbmXrveWa2kv0af+2G/ntGEZvme3eOz8Yx2dZQPkzbVVU8d7yp3VV+eMnXkzzrpV1/bor3RjDY0evaeZ7S6yp9Eq3rK1JHcy1PXVd/yJe3KX+00TgcaGw3KPMNHQq885fLRDQP3LV9ZS/KUDeuNl3lfWiv+Gz2TruhHF77x4LpYvXE+vauuq/e8L2lP/npN6EOv1GjEg3zjJC2FD++o6z3ttGd5LS2lHe/ujAm/MGy8kg95EkzwrszV8yQe5Ssfr6eNlq+sJfUntbOz5XWHfmcbsXVIr0ly+OGHl+tf//rl1Kc+dXnAAx5QnXb5Q3I9m5yveMUrymlOc5py85vfvPz73/8u8qU//elPZf/99y9nPOMZy5Oe9KTaxvD9Wdzr99e//nW57GUvO7E/5X/729/Kfe5zn3L605++POEJT6j15Evf//73y7777lvOfe5zl49+9KM1KCBfoiSkadGtzZ///Oflqle9atlrr73K0572tKJ9+eN9/Otf/yovfOELy1nOcpZym9vcpsBWPcn9Pe5xj3K6052uttHGYLyN5T6j6TWveU05+clPXk5xilOUm970pnWMh+2hA67wPNOZzlTuda97FTIkX/r9739fbnWrW1U5efWrX10DQMP3R/fT+78+v/3tb5crXelK5bSnPW25wx3uUDHDy7AX9X784x+Xy1zmMlUe3vzmN9cxV4dsv+lNbyqnOtWpyuUud7minvrKZpn0QYbvfOc7l3e9613zXcn/4x//WG5/+9sXGJMHNM5XOOZGvW9961vlYhe7WDnb2c5W3v3ud8+Pl4X1la98ZZ3XV77ylctPfvKTY96a7gVdT3/608tTn/rU+b7R9Yc//KFc97rXrXL08Ic/vPz973+fLx9SoK6xOuyww8oBBxxQ5R4W8q5zneuUU57ylDWRx7333rv89Kc/re0o9640bG+W9/qC69vf/vZytatdrcpbo+OHP/xhOetZz1rnDpo/9rGPVTqH9Kj72c9+tlz84hevY2bs5GnXvH/xi19c+W/zXtnw/dW4N57vfe97yznPec75+aFfNH73u9+tPBsLPH7iE5+oPD760Y+uc0eedLKTnaz87Gc/89p88v6vfvWrcu1rX7uc+cxnLk9+8pOrPlZBGVwucIELlPOf//zlfe97X9WPylYroeEXv/hFud3tbreAb/0bh+c+97lV53pW95GPfGSVS/w2PH75y18qnk/qybvGNa5R9f5TnvKUypd8Cc/4xff//d//1bL5l2d0wyimb9AtNdqNuy7RRcbf8pa3lKtc5Sp1vPEv72EPe1gdZ/aC8VXXO8Ok7ic/+cly4QtfuFzykpcs3/ve9ypf6v7zn/8sz3/+8ysWcP7zn/9cy4bvz/oeHZwB+orNc/WrX7389re/rXKsb/RbG9oaiFeYyf/IRz5SznWuc5WLXOQi5VOf+tRE2rVvXpz3vOctF7zgBatt4V1tw/iZz3xmOcMZzlBucIMblN/85jfz/SpfDwn9dCxb5RznOEd5z3veU+eD/CF9nj/0oQ/VuQyPr3zlKxUP+XQZ+8B6eqMb3ahY4xoGwzbWyz3ZfvzjH1+e9axnzZOEj9/97ndVz5sjytlb8xXGbtTXzl3ucpdqPyjGM/kyz1raZ5996rgr30gJ/+b3Yx/72KoX6bzvfOc78zLBdr3xjW9c7YH73e9+xdz3zjgG8q1/ML/rXe9a2JPqSWSp4ajcGqWP8TZ2xufu0O+Mo7aOaDZBTECK6k53ulN5wxveUD73uc+VO97xjhUPvF4AABAASURBVPOGViPXQsSIVX7ooYeW/fbbr1zvetcrf/nLX6rD9qhHPapc/vKXLww+RhuH1SLY3p/2Fe0WjWc/+9mFweR5vA95D3rQg+oCjGZOKDopZcrlgAMOKM973vPKxz/+8cLQYlBRyBYwSsniTSGPt7vc5y996UuFwf6qV72qOuyMVjQO24MzY0Kw4Zvf/GZdTIwHJffXv/61cOb3nnNqOJwWm4MOOqgqzGEbK7k3dhbml7zkJeWlL31pYbTutttCVYNG4+tKmZ7nPOcpD3zgA+uOPpoYQDe72c0KzD/96U9Xg2Cczx2mcRsv2EURVBBIQj85vNvd7rYVLjA8+OCDq5zDzZgzqDSNVgbcV7/61RoYuOENb1jgrWzWCYYMYHi2vsydhz70oYUxQBbQxWkmn62OK6dZmbn5jGc8o3hHHrx/9KMfVcPZeF7oQhcqt73tbYv5Xqb8J5iiD/OxNW1+MVzvfve7F/LMwH3iE5/Yihdc8f2Od7yjWLyNnXmy35x++frXv16Mw/vf//5ibr785S+vzi4jXHuPe9zjiiDMNOfoAsImPAhc3fOe9yyHHHJIdUgZqsc61rGqrH3xi18s9IZ5Y/7gJcmCVuhHOMDkta99bWH8wc940b+CAvgWyDBeZHZBA6vwwICi540hulqXcDbO5BB/0qUvfek6T/aaC1LSZx/4wAfqWBm/k5zkJO3VetXWF77whfKc5zynvPGNbyyCw+985zuLfPOW3BrnhzzkIeXBD35wOWwuwFNfXKX/cebJrEAamlq37s0xwTLzUr517+xnP3vB7wc/+MEiAMJBG+dZXTxzYgVKyYb1RZtkB9bev+9971se8YhHFDQo896sEpw3bdpU9It+c+8Wt7hFaXoeb+aiYAM933QkbDip5uOJT3zics1rXrOO/Ti95Jkugpc5S47JPfmx9gkEWNs4jNY2c2pWvE5qlw4VTDr2sY9dnQXzuQU80ci556yTb+N14IEHFnV/8IMf1E0MdoGAiCDlP/7xj626ILcw/PCHP1zXazaHcYYTW+OiF71osS7SY4IK9N9WjaxhBnpsgtBTZOAFL3jBRD1rzrKl8CI4wwlr+oqeIB+f+cxnKnYwEERZQ7a22fU3vvGNYt3Be6tozNgINrmsM+YtuTaOrc7wij+B989//vN1PVBPm7e+9a2rTqTbyJSAEFtj+O5GuMcvHs8ytxElIG9NIBf0DVuKDvQsUGiNe8xjHlN1/5B3NjqdwXF/29veVgMj5p85S68IEtA/+mHDCYzpZ9jGznq/0MreWbnodK8ZAkmKRcqCxoAUjWdYcHrGibK7ZhGjpE94whPWyP2Xv/zlwrDmxDEAOfh77LFHufe97113G70z3s60ni28FMQVrnCFumMw3q7yr33ta9VosVjvvvvuNSL+ute9rhqKFILosd0Ru/dOHLz1rW+tDg/jjSPCaKekxtteznOSegrCLqodYDtYjMNkocFPceHLInDSk5607pCLltvl4PihbfPmzeVEJzpR4TQLEHhnOTSNvwMzO7qMbEaN8Tzf+c43Xq0uVha4+9///gWNnBIyY7wZLAw2O7OMPrvmDNVp4bgVMXMZFlKnHxjT+nFKxMKcLMTWImr33oKzz1yUXKT3uMc97lwLpe6sMjC9e8UrXrFYhDhqtXDG/9t7773L8Y9//AW9mE/GetOc4Q1HY20hNNfw2CrjgSGFJ84VuWB8Kj/3uc9d8GI31NzmoM2CJ7uLFlZ9tsQJ4JTRF3AlK4y8Vj680iOcOA6DYJB5maTu8BkvJyrs9OGd02Qu20lhHDgBwgEbtjeLe5iTKScmzBOGuB1ITpAyhuyj53apObV25dB5nOMcZwEp6glC0DecQbpnzz33rEE+bQtOcqzohpvc5CbVmKGfvbegoRk/cDTIjm6GfZsTgr90J5nFo/lDB8CljRP+yDO51UZLScp+++1X7PqRVePcdKATR/SN0ygw8M6wb8+zTHQI/c/xGPbrnuPCsTWHGg3GaPPmzQUfdAn6yeUknsm08YaPXaVJPDvRpC/tJwv1lrxpJjKnv0td6lJFokPMX7JMDukT48eZ2XtONyWpp2uMmzLvCByad9KQNjwIAtNHe+21V/G+9q0r5g2Hh4O/x5ydYJw5+oKp3hu2M8t7NFtjrcN4pqPoTAEINLIRrIE2CqxjgqHqccQ806dsIXUn0YnvJst0lHpJSpIaLGazwOda17pWDYJre1I7a5GHVoEI40G/0QV4td6T2yFN5nnjE0+CxXBMUueFwAWZ4YQJfKwnPod8uCen5gW+PUvsGEEN9DuNZZNAgELZeIKbNdsJLXpdeZJ6Eou80xOXuMQl6qkltja9qc5GSkkK/UdHkAdzHX/G3tqx//77F7yzB+gIDrryYRLccyqUzmQ7Cry1k4VwJYv0KHtAXXbRCU5wgmETO+19d+h32qFbP4RTZBYoyjZJPVrFCUiygEiGJaXlSHOS6sglKSLtIv0WbQZsknpE2CSk4IcKckGDK3hAh4iqxYIzkSykVdP6tWNGcXL0ktSjsJxOEXSLVuMlSaHMHX/l8FhsOQx2ULSjvWkkGMOE4UgpWSjG20Ub5ccxS1J3TRjMlB+HHp3aSVKdQErNTmyZwh9eHQW2AFnAGRx2h+W35t07HSCIgA4pSYFbo5Ez0PIpeIaR5N0ygz9YOWHi9IKdP4EcuwpoGHaXpBpVDDrRX4sLw7KUUnFWl3HJYcE/o1berFOSrboQKNO/4FmSekyNQ27XYFg5SeWJs8sI5Vg1eU9Sq5q7jka+7GUvK+ZDzZzi/5JUGoZNWnzRYQySkV7hCAzruLfY2wFRXzDIiRnBK3M8SR2XJHVnzG6RyH2Z+2NI2uEl/7OSq7lu5v/ThwCf3TnyjU476k6HKEOHXc3jHe94hTPOKZA/38Dcjd0HOxMM/oYLR9CuvDEytsa7lcGPwzP36qr+l6T2l4yu9WHuf3gUvEOfcRBg4gAmmR8nPHPeOGt0Qhn8Jaly4iQHHegzEXNQlSR1t0YgiCMpkMPJVDbLhF6y1ugZ0tzKOHp21oZlSeZ5LnN/dotgMqwzl13/gxe9T+cwRDmQCpIRHtYZPHP+rEnKZpnQIyWp3aCdke2BfJuHAs8CTPQpR44sCsYM3yPH1v1k1I73yQgZF5hpdTl+5Fuiw+i1VkbeV1vGyaz1S6DGvXFGr3Fwz4F3coA+dULKuiY/GcmoNZpDwrnAC76HKUmVc0FmATA6WTBZHXzr2xrlkxwbB/LXSzIXyHsb1yT1kws2BjkY0pmkPlrb7V4LkliLZeJTW4LS+PSpxqS5oe56SMmIlyEtbCHrZZI6nvhx6mpYxz3ZoLvJN0c2GdVXBgcpSd0scvKDXZVE8YZKSeonpY1fQVLrG5kQ0BQcUoZpc4D+dz9MdEXzR9RVT4DcfZJ5nUsWnYS45S1vWcembIC/7tBvgEFcaxaSLYrF5LFbxrgYV74Mb4qr0ZuMFjfGGQd0WKYOQ5cCdD/tZDeModGMEH23NOzLsbfhczJyLNDGARqWuWd04VMwwpEzzrN8bbtOI1H4DH/HHC3q4203mpMt46JftDGW3I8nZeN5y3k25oIMjkIJ0hhbTtM4jcZ7UvuCJdKkMkfzJuVPIy9J/Y7f4uG0CblrBtR4+45+cTaMryOwZKnVceydwS0YwGHDfytbeJ39k6AD3JMtcmB+WsjGeyfLdkt9XuJIKxnyrsRAtztgHB1lMw7yx9uYxXMyot14mFOM5GE/6GD0MgidBBFtl8fhkdfqymN82zESIHJ6BJ92/T23erO8okFAQX8MPSd6HMc1V/DHAXK6CV0CFO7x4D10ucKeA+F5mIyp8R7mtXsy6N32vJZX3yviy6kI80wADY9DmswvpxT23XffanwNy9zDym6XAJzPRBj8jT9lnCmfzjjCzvnzziyTvhmGjM8WcJInGSu8+j6Y4ylPQmejyTO97Oi633Jp+eNXu012qOj9Ic/eZ7A68dF4ljf+/iye9UPu6Ai4e+ZwOH3QZNwum1MleE5G81k9O5Vo5ug32uQvR8atX95t7cz6al2ni/wmgrXMJxHWYnxzHNgVjvkK7KLLKTiygC44wMb64OgvuZE/nrxHX9kYMB/MC3nqWVvJg/VHH9qUvx4SGgXVxmkxrsrG823oOOlAFjj0gpatjk+KYCkwQu6tX61sZ7kmI5k3RnAxh5NRHh5gQkf7/MLnYbvvvnsNTKqvTB3JvTWQXrSGJFvaUL5RUjLiC//k3Pg7lYS/ZEsZuXHCKRnlKZeS0TO8tOHUA7uAbapcUmZtsPFmsysZvaNsZ07dod+ZR2+d0W7BEkm1Y+IoZLJwklBUyZY8kyoZHbFpCkoetlwdg3H8yvM0k4WF8mQE+57JwkrRWpzHvz9khA37RpdTBGgbGiKtjjy82HmwOHm2Q93Kp3F1aoBBZ0G32ONn2C7aPKPVtSWKq5W1PNdkdFrC/bRSMmqTMctZpFiHbYu4Dp/do5cTTU48jyfvJFvkZ7x8Jc/6toNmsWUg2TlkkE0ytuBooWGQotcx79a36DtnUbDIJwS+DWxlK7ou4+WGF97a63YLJuHrRyoZ4uavOcfRNGZJ6qcx5gdn3s6bgN2wzdb2rK7mKYNONF7AJVkoA4x5hp7dTQa13SwGgDFsNOHFt4i+301SfxDSJymOQTMYBAVa3VleBX8cI21HrAWFXvSiF9Uf1Gr9wl9wxS6+nceGdZJC9yQL+feeXX26xn2r716Sn2z9jrK1SniEv89TnC4Y0kG3OTKZTKaZYSZwxqBzEmyoA5UJEJh75MJ1HI9hX9O4p3/pDmuHQDaZ8omTtYWecNrAaS5BBvPHPLODSWb1jz5GJzzgIm9SEgziNDq2r21OgHocSMEqvKLFHNamslkn80ogQnAG7foVDDRXHQ+2W+a3SezUWwfQo44TNHZwBQrltZSMZBxPLa9dhzLe8tqVTk4my0urM80rOfNbF06i0YtklsON70Z7kmLuOWnDeWAfocG79I0TT07MkWOYKBsm7RhXP7YLO+tNK/ejkHb5rT3sDO21srW+JqmnL8fpsB7haTxfMMp8MSfoO0GpVsfRayfeyA99DodWtrNcjS07wom9TZs2VZkY0q5cmfljI4CeMD/oFHO+1TXX2H7mVcvbqFeYOK1gvRQ4M2car/SmQJjfXXLCNpk87803epfTLtjY3nfVPjuGne55o6Tu0G+UkVxjPkweuxQMCrsMJkxLJqB73waZmBYpz44YUVKMbFFHkX7GuzIKzbEZx9GSyRN2uSxr3y6qKDsHhyJFl8UmGZ0aQJf27axQxhZreYxFTj5DFM0cHe0pc6QML9q0EAka+KE3ecnKedAPnJPUH/bicDoNIK+VuVJyHHeRbs/KYc5BcCyZ4SlPGb7UnZZi0yYsXOEHYws2bOW1fu2mum9JGQPVDh46BUG0o5xcOEbK6dTmtJO+LR4Mb9iRDbvRnEgLivImw2iSkhQ6gjZsAAAQAElEQVSfajDo4Ikm+eqSJQYXpwy+ylY76c8nGeajEw9oY/QxfDm76JQntftk9M05x8LRUW20cjLtmzSnL8hcsnJ51v4woWP82fgzYhy1YwwpVw9dknufPAhSGCvljGjGI13iWdKOXTTy7zlJ/SVyv83ghy052fJnmZLUfxmBgYruJMX84KSTL/xIysxJwQtzIUn9zQk84NVOvm8zPUscYnnmFN3EkZWvLfrJUcVk+uO1LazwoLxd3UtoktzT7Y7Em3OeJXQztDj0niVtyHf1riSfznJsecivOmSV3raDb+db3Vkm852RrV9jaT3RH51HDumCVqYuGpPMH/P0TDbtInnHu/LwjNd2n6Tg2Tf6jedWpn08+8yAQ62N1UhoFIwQREtST1SQ2ybjZe7PM77VxQ+ZtLMs8C8fD5IydQRJ2Qr0lWeJfibHZHz3uR1Ma4V877AjlCWZ6231/jPWdCX9waH3OzsCTI0XV9RYt6wVeEWvfLJvnfE9PWdfPfl4clXPvSCGIIETYU2/KVOHLrejS4dY67WxHhIZtk44uYBWyfgZU3PDM97Q6h4vSeq/FuTUEjzktTr0uXXWp51Dne799ZTQPE6PPDz6/I2MDk/wyJfUYU/CxzwmV9qBVbJFpuFB19OXyZZ8dTdSgon1UGCSToQHjCQY+HzF/BGITzJ/msF7EizUE/DSDj1DJr2vTJIvoGbdTzYOlt2hN7o9rQgBk0gU2W4kw5sBbheC80sBO25m0RWRt5tiIplQ3mGE2GmmpNyLvDHCRCctVna7V0TchJcpAwuE47aS4+vo9i2aHQU7rCLCFICdNI67HSFGlCiyYz4MaP98hrocecaHI2F+KIjyGKZkOgqDc/j617++/vMtnDQ4+pYKPxZ72FJiFgI7f77P9Y7dYhFKxhDnWtKOdxxZhYF3JkC1w1kMLW1zwhmWjswZ3yR1F9LxYgYd48a3S3A23o5l+qbZeDtO64QHWbC4w96vWifTwXGcqST1RxEZin5XgWxyWhlKHCs02AkhD8a68YdugQe7+tpEpx04Ms+gJf8MfWWzTmRTv67mo/7gLorN4EarsWaA4gttsFf3u9/9bv0VeeMlMb4EpLThm2/GiLYd9yMzjFNl00wWYDLNMEUTrPVJBuw8Jin0CnzJjzrop1cYQ4INToN4344XY5cx0Gj0mw3aN7+TVGcqSXVAzNUkZdZ/SeoP+uDLzoGrXTfyw+lx1N5YyRcctROLN1g4ctt2a+wCGwtOvR1bfHEqzCkBxOG8p1MFFGfN27B99Ep0j6ugkqs6Tn44KWGOmS/mPKdemUQOyKqgUzIaE7rErjcdq03zTxAN39aQpgPtdpIX75MLurAZ0NqeVeJ0+V0AelSie60Prk7syGvJ51ISI9N4NZroG45LMuKZzsGzMSbTdnkFZdUjO41nxi3ZgEvj2a53MmqntT+rq0/PrOt4SVLnlXUbnQxy48wuIJ/0Dn1JBjh8AjcCGXQu+bC2ek5SrGX0EJ7JCxnyg2L6gauAAJ6tL8aYszQrHie1i168wV9QyfrpdwTQR4aNF4eWLAoUc/aVmd8+TzCm9Jg2zFF92J3WBkzNaycf1LMrbWwFAOgG6zlM1POO4/vkTRvrIdGnTkvByMYMPulmawqH1bhbT9FqvJ2IM77Gml7jqCnDv0CJDRVz2+krdoGy9ZiMO7knl9Yn/KPdxgA+jLU1zLwwnupYw+gxa7V/ho2ecKWzBefYn41Xc8c7dGPL22hXmJn3NsPsrFvLrZHmGdk3d+BJjswBtgFbBi6wpC/VY7eYSwLcMPfMJmt4WRvY7vpI0rJ3+mt36Hf6IVxbBkxAjqXIqh9vYagwNji2Jhkl58dOKC2KXqTZLqyJxOn3T1OYdBZEC6NFnRNkZ+qAAw6oP5Q2Cw6TzBvz6NK/BbfM/XFq0IE3ZQwrRondPT9848dZ1LeT4BdMOaaMGL9QbRfRO3PNTP0/ODGGfFdncWQIMCTRwpGmwBiC+jcebWeAQnOUi7PMaHTElyEMZzs+dsO8Mw2CjbkjiJw+eDDYRda1zTjxWYMFT3++10Yvfiz6nH3RWHSTGU4+49Suh6BKMjvFayz157gb4xAPjDKYkV2LCHmwYKsjOMKw5DTaCcefBcLxMMYVp8oxOqdMlM0yoctYcnIYBH5QSh65IJ/4YPSRTd8so4WTRMaNF56MFeffQspwbpFrC6S5bD46CunkwulOd7pquGtnWom8wIsM2zVHP73CqOHAkiN6xbMgi3L0kyV8kh00mqN2MC3uQ+w5PcaqzfFp0b0j7SQpZMMxbAEqOhA9fu3bfHAqwm6u7/8FTvCajGSeM8+g0x9jzzf2Al+u5Fa72jBWgpPwZAgJjJrz3lvNRN8YB/rfTjk50z8ZxZ+xpLPs7MJAmWQHyvjSdZ4lQSrzESaCl2SEfNJxgpPkFe/a86+j0Df6hh8ckhGG2ppV0v8w0WOek2y1zpBXZWXujxzj2RgJKM5l1R0nPPsBSjzDw7yj7601jWftmLuOu+PZHBZsVp7Mnme0c9isicmovyT1XyAwd62bZNxY+hcoBGQ4a/7JQj+ORwbIO8dXWwI8AqbuzWO6is6ikzjF2oKbH/6jl/HJOfTJnJMQsFutRJ7tqMLeDjoajKH+0S/ggAe045H+lY9XQVXv+GyCvFrvvGcNtO6ZMwIBfjDPmNPh7m16kCsBEHPI2mhtZ3eREW2sl2RO+3VxdAveWOudRjB+xpjdBw98svNg6dMBeoMeV2ZsyYhAhnvrwGqP847giQfrDH1sbL3rRyzpP2PUbGPP9BgZsoYJZiSZ1xOwM86uyWhelbk/bZk38uceN+R/xp2PYBPQWmb8BYfYjtZAc18wSABfGX1Hv3gPlgIlnH/rCluTXd7qDWWH/astOnQjAdkd+o00mmvAS5LCsDSROGcWLEk0zO4SI8WuicU4GX0fJwLJsGNsmoyNbLtndl8YCRY6Sq2VzfJqd4yy0F+SYkERRW2TXWSYQeE7L06ceuixOFlwLaqihXZe5CmbRUKPiCTDn4NpoWvKHQ8cOc5xkmKBZ0SJRFooGfmNJvd2NhiSjCaLSytb6dV4UpaiphQvumCSjAw9jqR/uidJ/ZbMwgfXJzzhCcVx4iTVWfQeB5ITw3BvmK+UvsXeT0bHzdHOiWVMM7SS0b+4wNiENcOZQWUMyAQnOElt1okNO8EwF/SBazIqqxVm9D/42t1gHAkqoDHJPI4MAVHvtoAlKU5skHG4Mi4tgtoQ7OEcJqkGhsARPBhhggV4Kjv6t4T6dproD/LB+MGThZiRK59Okezg2H03F9Av+JKM9IrdaXrHSRmBqiTzPdM5dkHmM9boJkmhF+0+0YH0nB1esmW+4pEzxAkwNsiEBUwYKUnquNjxoyftWBhLdcrcn3nvn/ozZua9Ha1kCw5zVWb+X5LC0cGLgItADf50zOm044h/v/5tHOW3JFghwJFsoRleeOXA2ZmBD7ng/HBqtJGkkGM6jYyQYwGdhktrfzWu5gj93Hge9mn9IKctLxmtN3hu9ZORjJiz5jL+yDqdw2i1I61ukiKQR3/SOxwJPCdbsGv9zOKapP6TWvTKEOckBR1OEpBxawxZZgPQjYIUZEMiCwK23hcAYMQnqTLOETSeAmACqOqUuT9rjKCftgTGnBBIVofnue7rf/A3x5wYsj6Ry1ow9z+8km/jxalwAgXtEqdOPnm29vmULEnV1YLWTlGZwwIZAiBkoLWRjOpx8OHG5jDPBDeSzPW8fv5LUsxldhW7xFyHGQoFVu2YJqm/aG6NZy/gS2A9SR1/wRD5drfpPnoyWV98lsGf8SLb1jDrTZJCNsj5cA0zV40ZOTGv2WODZirvTmtZh4f5gpQ+Zx3mbbR7c4RcD/EyX5xUcNqJPhmWWe/Z501HWgOsh9aAYT06kp5oeNkIo1/a80a5dod+o4zkGvKRpCohk3GYktSFSl6S0v48S0lqectPMt9OsrCszPAvGfWVpPaSpNKVZMFzo7lmHvO/JAto/n/27gLOspv6A3h+5Q8UX7z4Fi1e3KF48eIOxYtLcW1xd9fi7u4t7u7a4k5xivU/37zN7J03b7bb3ffeSDOfpvfeJDc555eTk3NOct+WGf+hQUpSaWzdJal0JCn+ktTybdWdVObdnUlJKh0rtZ2M6Cpb/pLU+knK8C9JzW/tlDn8JVnsc9hvMsovC39JFuskqRiXLX9JViwrM/5Db0tJFntLMpGmJJX2ZHQdvpuktL8kE98vU/5LsqSfsvCXZDGv0edaFv6SLNK/8Lh4r1xKInsxJal1FjNW8SbJIl9JSvtLMjG/LPwlWUJ/km3WhYGUpKzGX5KJ9KGppWQ5bUmW8FkW/pLUtpJR2fD9JKX9Jan1lCdZ1k6Z01+SSkeZ8JdkYlmSMv6XZJEHPEnJ1jz1k9T2JpWVOf0lWdZTkiV0lYW/JIt56G0pSeUzGV3Llr8ki/WTlOFfkhXLypz+klQaklT6y5a/JDUff8nRL0tG73hfSkbPZctfkiXtlzX6l2Qinckovyz8JVlSJ0lpf3hvKdma38rX2rXR6pqM6E2yyJ/8lsrCX5IqN0kWnpb+p16yND9Jrb+05sZ7wvt4Ska8j+d7hkAyKk9GV/njKYmqNSXZkFh2h74Ob/9fR2BVEOiddgQ6Ah2BjkBHoCPQEegIdAQ6Ah2BHUagO/Q7DF1/sSMwbwR6fx2BjkBHoCPQEegIdAQ6Ah2BjkBHYCsC3aHfikW/6whsLAQ6Nx2BjkBHoCPQEegIdAQ6Ah2BjsCGRqA79Bt6eDtzHYHtR6DX7Ah0BDoCHYGOQEegI9AR6Ah0BNYXAt2hX1/j1antCKwVBDodHYGOQEegI9AR6Ah0BDoCHYGOwCoj0B36VR6A3n1H4JiBQOeyI9AR6Ah0BDoCHYGOQEegI9ARmDYC3aGfNqK9vY5AR2DnEegtdAQ6Ah2BjkBHoCPQEegIdAQ6AkeJQHfojxKiXqEj0BFY6wh0+joCHYGOQEegI9AR6Ah0BDoCx0QEukN/TBz1znNH4JiNQOe+I9AR6Ah0BDoCHYGOQEegI7AhEOgO/YYYxs5ER6AjMDsEessdgY5AR6Aj0BHoCHQEOgIdgbWJQHfo1+a4dKo6Ah2B9YpAp7sj0BHoCHQEOgIdgY5AR6AjMCcEukM/J6B7Nx2BjkBHYBICPa8j0BHoCHQEOgIdgY5AR6AjsKMIdId+R5Hr73UEOgIdgfkj0HvsCHQEOgIdgY5AR6Aj0BHoCCwi0B36RSj6TUegI9AR2GgIdH46Ah2BjkBHoCPQEegIdAQ2MgLdod/Io9t56wh0BDoCRweBXrcj0BHoCHQEOgIdgY5AR2BdIdAd+nU1XJ3YjkBHoCOwdhDolHQEOgIdgY5AR6Aj0BHoCKwuAt2hX138e+8dgY5AR+CYgkDnsyPQEegIdAQ6Ah2BjkBHYMoIdId+yoD25joCHYGOQEdgGgj0NjoCHYGOxxR64gAAEABJREFUQEegI9AR6Ah0BI4Kge7QHxVCvbwj0BHoCHQE1j4CncKOQEegI9AR6Ah0BDoCx0AEukN/DBz0WbB85JFHlv/973/lv//9b71uqw911Wup1ZW/vW20d6Zx1W9Lk9pT1uhyP6zjGR/K3Q/LZnWvr9bnSn2gZaV6wzL3K7UxjXw0bKsP5ZN48c5KZdOga1IbrT/0tISOSXXlKfOO5F5y39519Sxf/VmnSX3pW36jZSUahvXcD+t5bu+7H5ZN817baB22KU/f0njZsJ77Vlc99/JakjfeRitbrSsaG03uJc/DhG754zTKV891vFxeKxt/b57P6Gpp2K889LXkWXmju+W7tjLlwyRfuXfctzL38pS5b/nzvOoXDa7j/cpT1vLbM3rle25l41flrd6wzDsrlQ3rTfu+9YmmltCin/bcruq2MvfyXVued8aT8pXqDcvG35vn85COIS/uW5n7IU14Gib1xuuoL0+Zuq7yWlImX3Lf8tfaFd1odF2JNvSrI7lv9dzLG6ZttdPeW80rmsdplNd4GC8bp1W5uq7eG5bLa2XD/I14P+R1iIP7Ydn28K6+94Z15W1ELLtDPxzlfr/DCPz73/8un/nMZ8p73vOe8rWvfa069uOTSOPyfvWrX5V3v/vd5V3velet//e//73IP+KII8pXvvKV8v73v79873vfq214Z5ZJv//4xz/Kxz72sYn9Kf/LX/5SDj744ErXz372s0ormiiFn/zkJ5WHj3/840U9+ZL3lLt6nkbS1t/+9rfyiU98orz3ve8t3/zmN8u//vWvRXpaH+r985//rOPxvve9r3z3u99d5E3ZH/7wh/LhD3+4fOhDHyq/+MUvjjIA09o9Olf9kAm46W/83VaONuNNZhovysjC5z//+conjCnf8Tam+azPz372s1UuyaYEn+GYtv7UNbaHH354+cIXvlA+8IEPlD//+c91LPDrXYl8f+5zn2uvzeyKHjL85S9/uY5n60g+HL/4xS9W2f3Rj360KAetjqt6f/rTn8pHP/rRysvPf/7zRZnC56GHHlplnNz99a9/9crUk36+//3v13nfGkcXmWjj8oMf/KD85z//acVLruTjxz/+ceWT3ODb+5K58KUvfamW/fCHP6zyLl/Sr+uSxiY/TC1Xf+ilSz71qU8VcxQdZIjcDJN5Md6xurDyHp2LP22qRw7gpezb3/525VX+vBMaf/nLX5YPfvCDy2jAJ/1lflgvfvvb31Z5Q6/nxv873/nOYm0Yp50MkAXzzriSkVbHuJsH+IeRuq1sHlfjYAzoBffDPmFC/qxt8pXj79Of/nTVc20Nka98mPDh3cYzPtWT8I9nmJrj6g7fncU9+dVnG6s2lvLxPxzHVoZ/6Vvf+lbVJ/SSNWISferBCU/kGY94lbQPM+uG9UPdSW3MMg8deG00fvKTnyzoki/Rkwcv2AzGi15SFz3mKrrHcRvnQRvGGEYwoINbG+paUw855JCqs61D8rS/VhL6YQAXOoAukDdOn7xf//rXVTd/5CMfKX/84x+rvpD/u9/9rq5HDSv6gI5QNt7OWng2Pt/5zncK3dToQatxpOfxMZSFVqddvW+O0130mrnhfYlsWdfI06EL6/FaG+/GwzSu9Bcc4UV+2CYwkOgB+kDZ17/+9QLbbfUJJ3YyGWv1vGNdhbP5q462W/l6vnaHfj2P3hqh3WR4znOeU57//OeXN77xjeW6171uecMb3lAV8ziJJs+rX/3q8pSnPKWm1772teVYxzpWNejca0Od2972ttVx1XaZ4Z/2Tewb3vCGE50F5Y997GMLQ+ktb3lLueUtb1mdIvkW0te//vWFA/TQhz603Pe+9618KKOcKSZXz9NgQTsvfOELy6te9apy0EEHlX322afew2vYvnoMKkpLoAJvlJ86lOOLXvSi8tOf/rQ873nPK7e//e3L73//e0VTTWiwkN/4xjcuFuHxxlv5/e9//yonD3/4wwss8QKzAw88sLzpTW8q//d//1fuc5/7lN/85jcV2/F2pvGMFhg86EEPqgYEw0LA4573vGdhlIz3ob5F4nrXu14hy2hGp4X82c9+dvG+xBAzVuqXGf/p5+Y3v3lhOLSu0GU+ohF9d73rXWuwrZW3K/qe8IQnFMaGMbjVrW61KONwf/Ob31zl5YEPfGB58IMfPJNxIK/3ute9yute97rF9tH/uMc9rsoPOb7ZzW5WBAPR22hvVzJ2j3vcoxz72Mcu9AjZ8b66eHrNa15T9czd7na3ioEyadpztNFTysp3+mWQXP3qV6+BwlOc4hSV5xe/+MV1DpAd8vfMZz6zMNrVH7bGkaJfjded73zn8ra3va2+j1fttnl/gxvcoAb9xt8ftjWLe3Rwps3pm970plWWWj/K6IUnPelJVf8/7WlPq+VotIYwWAWW8K+M89/edfU+Y3f//fevPD/1qU8tz33uc6sOUfasZz2rvOAFL6h64973vndhGMr37jxS0130l/thn57vfve7V70mH130OZ5PfepTF4bqox/96MKQV94SbBjzdKU24IJH99LTn/70Qnaso3Dh5Gq7vT+Lq0CEtZqsGi880H3mE2fbGqNMopvwiVYBTg6+9fSOd7xjDfhMopUjS++Q8Tvd6U41+N/qveMd7yiCAtqmg839VjYLXie1qT/zzFiYv5xNY8thxyedI2DHZjDPD11wwryDL1igXaKrjKUxHvajjcc//vF1faG7jas1WxswfsADHlD1tXmmX3nD91f7Hv3WlBakuva1r13pRf+QNvXIro2FZzzjGWW//far+kA96ycc4UQfwMncVzZsY63ck0vry1vf+tZFkowrPchxxMctbnGLJRs/ixUXbtho1tgTnOAE5SUveUndXPA+fl/2spdVPe+ZbUzm3S+8tqH+wysbhv6kJ9giZN9GFn4f85jHVH1PLsgUrOVPAkG+OWj+0Z/qaN8aST8d73jHK3TqWpYpNB+dtMvRqdzrdgTGETBBTBrGxEtf+tJisWJIHnDAAdXIGtZXVwSWA/zkJz+5KqxXvOIV5bjHPW4xYTkeHGMTkBJkqDAchm1M896Ep0QtFqc5zWkmNs2BoKRvc5vblEc+8pE1gnzYYYfVunaWGBt3uMMdCmeCU8JhFkWkKDizj3jEI5bhUHbwj7FwkpOcpDCc4HaVq1ylUGiit8Mmk5SznOUsBV3637RpU3Uy1cGz/Fvf+tZ1rBhGFlNl00r64CAbZ9HQSe1ayPFBTq52tavV4ALDnBzY3RKwYJBf+cpXLpe73OXKQx7ykEnNTC2PDDPKGBWcDYvFpS996XKqU51qSR94Y2RyPi2sAlN77713sQhzfsmwPOmCF7xgucQlLlF22WWXJW3M4kFw5zjHOc6SpsknjMnoFa94xSKwwxAcD1IY/ybjFlLRbMajxjhUDG9tCAgwsuQpm2YiA+c85zmXzBX9kFNzz0J+hjOcoTqo4/2Sf4s+WbnCFa5Q0GoMGdF2soypsYKBoIAA0eGHH14e9rCHVUzMU22MtzuLZzrQyQ+OKKdcgOQiF7lIOeKII8qlLnWpYl6THfzq3xwflx9zynuM37vc5S6FIandJHXeC9LRoxwNRqR25pmSlLOe9azF/DHPh33T5wISdKlABEeQM2ucjAudb+yUa+NEJzrR8PUadBWINJ5XvepVi7rmnLHmyL785S+vRtqVrnSlQnY4RfNydvBqbM9//vNXp6QRbmzIF+ePPvGsjC5xIu12t7tdoSvMQWuL8VXeknpkmN42T8gHg59+5Si4N6/JCvmGnXfa+7O4OrlEd6PFWs4RIcecz912262uS8qe+MQnVh2INzYCHKyNdMn1r3/9GvifRB8MtEnG4UNWGm70hPFnI5zwhCesp+ta2aS2ZpGHD3oRD/i2/tsYENxACz0kwAobNoRxRsfJT37yyjNsyO7lL3/5uk7DRnlLggWcuKbXrnGNaxT8avughWC+teYmN7lJIePWLg5Ke3e1r2hEnyCsOW1tsslD540Hq6ylxnjfffctxtuOrPUnSTnvec9b8AUrOF74wheusjSuD1eb39b/ta51rXLmM5+54L/lsXcFXa1hdBFbjJ5q5a7q04vqsX0vc5nLVJmwwWAddlLBmFvX6DzrFXvIO97faMn4C/KwB/HNwYcBOb/YxS5W5NHz5MYcmcQ/TNni2mEXJKnjYjzoLRtzl73sZYsAi3bkT2pnveXtst4I7vSuLQSSlJOe9KTViLYo2SGzmLlPsozYt7/97XWH4kY3ulHhbDZjixNnEp7sZCerDtDFL37x8tWvfnXiDumyRncgQ1+czoMPPriIcDNEJjVz2tOetpzudKerysBidNGLXrSc/vSnr1XPfvazlxOf+MTVCeEgiCZ6TlIYMLBwhEpf9YWd/B9MOWXaFQShlCxuyVKckxRGpe4ofY6excazsYIxmhjRHP8znvGMiqaStMvYseBYnJKltOlEHcqWMXqOc5yj7pwydClVBq0dHnQJsuB58+bNhbOt3LvamGZKRnhxHvSXpB4JZaR5HvZFXi28e+65ZxG4YsRL6uy1115F1LeNCUPboqFs1ilZjjPnm1xzmNDEQPL5AkdgiCN5JufyBKM4lmQezWc729kKXDgIZJyR6lnZNFOSkmRJk2R188LYowvGjOFzn/vcS+oo48yZZ5e85CWr7uDI4pdzxWE0X8iXsTzf+c5X1GccGD9BAphwUJY0PIMHtNqZ5HAzJHbffffqoML2+Mc/fmGsoFESZDEv4Z8sxQWfSarTKADGwEtGdcgl0gX/jL15n4zK5M8rJanjmYwMqdYvZ96uJd1FRwo6KTvlKU9ZgxF4T1JPJnCUzCflLdEb9MO5znWuxbHGp8Ck9YLBbEyN/5nOdKZ6YqX10dqYxdXYcmLI0jWvec0lXSiz7tEFnNFWiEayypEx3gI8HDyy0Op4l2z6tMK78PGOcvqT4yfIi2dlZMauqLXNu+rNItHNdIQ+8WEdvdCFLlR1eaOzlRkzOkU9OhI95jOnnbPueTwJBskzN6xh9E4ykil6DG/WGXNbkCOJ6nNLnHRrFflMUgO/dJOdwCTF3EYj3ulL9kySYr2zHjdsyIz5DJtGvPfYQ3Ryw5gsO6rP2eHQwEAQmazAm66HZ2tjNa/GTJCtySRejb/TCWyoIW2Cds0eIefsG7ogSaHLjC9skhQ621o2fH8t3SfLZdBcbWsYXGBCp4/TzcknT+YQfgXF2BqCImwfMrRp06aq8wT/1OfkjrezEZ4FYwXqmtyYS/iyhnPO5Us2etRTNp5gbb44wWOOKjev6CkyyObRhnWE7rUuq7PeU3fo1/sIrgH6TSoOZjIy3kSjH/WoR1XlM06eSKVjkKKVdsbtRJlolD3DjDLzjvYoLA6GcnnTTBY/E54xYFHUtn4k98NEAdghYFSc5zznqc698iT1uLoIskVWJJoi0bYdNDslIrbqTiPBhGJPUoMI6OeUNIU13ofFgPMgskQduYcAABAASURBVO095Ukq/SKc3t13330LA0PZNJJFiMFuF4bRp02YSu5bIgPykq2LYJLCIBaV3nXXXVvVaiSSA0bqYuaUb5KtdHBcjTkDLdmar0sGNFmFGVnea8GJd2xS/WRUF1+OcVksGgbenXdCa5KKX5J6HJ0DyHAqY3/wdcQVTxe4wAWqfKmSpJiHdtocW+cg4k/ZvJJv969znevUUxCM2PF+OWz4MiZJFvWO3R8YWLibXqFjnFAgS+aoHS6BgjKHP7qBQaF/DgHjlfP3jW98o87JZKn8KEf7JNIYt4Jm5prgV6uTjJxhuznGkW4+8sgjW/GqXzkvxsRJBPNccIzDhrBkxL+55Di33ag2bsoln7XQMQ2XJFW+4SGo02SgLPypoy1YLzzO7D/zQbDRDjwDMhnxId+Y4xMd9HAy0r/KktRgMrrtrgu0kUd0D4nFMwc4GbWrDC7qk/Ehz/Lhw/FTb1YpGdGCD7rDyTwBmCQ1kKNfZZxu9Fi7ksiu3xjbuWUncFpr5oT/WQsEO6xzHNpWJUmxE26H3G7mJJ3Q6s7qyrHkdJnPgmfWDOs+PZSMxtjJGYErvLY1Ohlh0LDxXlubG63K8D7EzLiSIbJA1pS1+pxep5n03/JW84p+O+3oQkcyWnsEL8ixvJaS1CPogt9Oh7HHhmXuzSGnH21SNFtN/npKTko5ycfBb7g0+uHlNwbMI3NZftMB5IC94TlJnVveFygyt9TdSCkZbRAmozlEvwnwcObNoYYPzMwFp1SSLIGAjAlqmg9sOIXqkyOfKphL7AD5rm3+el7vqTv0630E1xD9Jg3jjDPG8DdxhuQlqca2BdgOPafed5MMLu+WOf3py1F1xoQdDQYHJWDCKxsnI0k9QipyyHn3bU+rRyGIvmvL96J2TZRpz1EeCxHlIm+83R191hYjUMSW0T+Oc2vX4mGX3HfUFkt8tjKRccYnY4PDpM1WtjNX35ajSySaAQLTlobtTqu/YZvTuEeXSPkee+xRF8/xNu0CMiqcxrAL4agroxPf3lUfv45f+gbfQixvrackxYkTAQq/GYH+xg8Z9+mARZWBaiFtZfPgi+HMoWfYO4K5PX0mSxf58XeS1G+VjR/HiAE6a560T0442o4c+87fjixdyMlvNNIddgzs1iST+WDc2PUy1wTlGPTtffOeM2xX2CkohmIr277r7GrRVQxSuyvG0nFKu/bDHvEuEGZnK1nKPwyHddfCPb1qF81JL86Z8aMDJE6MTwToYfkSHtoV/T4F4cj7ZE2gQ5n8nUnJUtx2pq1tvYsXjrldYvN0WBf/Ak4cMePeyqz/TvFxfq2ZKzkm9CyHnT1B3w4DkYx8DpJvaW0KzFvG8eBEhaC5oJyjv3Cw+5qMsCfDPt1yVF7AH1YNA9hw+J0YMh9a/ka4DvncHn6skXvuuWfZcyH5lMJplOF7HDNHp60BQzka1lnr905asLfofHN8ezFKRrK01vmbBX18CWuE+WO9G/YhYOmknQBQshUjuAqC2HX3OQxdaq65SsM2NuJ9d+g34qiuAk8mksgx48Uu31EtUknq91AibhS63czmACKfgctJtpgnWyessp1N2raY+kabM25BFgnksPumHi/DPvDCKPFNk+OtftSp1dm0aVNxlNKCY6fPj9RY7P24lyO/js5xkpLp8cCwYQTbfYfPkNZ2n6Q4TaCO71IdSWVAKU9SGEoUpZ08UUv500i+e/JtsuPDkjH17Sd6h+3vvvvudVcSjpIyCpcc2P1Aa8vXhh0Ji2IyPRz1OZ7QYPfHeCfL+zLG5NXOJ+PC2DIm7RAO6bWrDf9keRvjfc7qmYOOJg6HK8PZJyGOOI73aR4yqHx77XtHp2e8ox4Zxyej1fvmSitTPsuUjAINdnI5p3Y6xvvDj3kg0o6uxi/8GdiejasyGOCHbnEc31wmm/vss8/EAM54XzvznKQ4Hk1+6Ah6xTz06QvHr7XNOWeQqNvyxq+cds6CH85j+DBiWh3HcR1l9gNxdsPNpVY2k+sONJqkHj8WtIBHa4Lx5dgyY6zlDa8CsOadMZWvvvnnKLMgovE1zpJ8GNM16s4q6Ye+F8Sm84wpp0TAxckugShOu7WGfnT6wDzjqPg23jp0v/vdrwgMOiVj921IK76S1FMz+FJGJ5JtOrHJvTK4CMDZ0U5mr3vg77i3dWQ4jmhEl2+fncpIRrQkKeYeHeObasHTlQL6AoicODLOtqBjtSvRz9YVZWTcuMufV0pG8ot3SSDH2uCkRZK6cWG8/daKMbb+wqps+TP25ie9moyw2VJU9ZDgiHltTCXjTUdbH+lg/Mr3jnr6FgDxvNrJ/LSW4BGNEhrNXbI5Th9d6FNGJ1zwRx8P69BtdPy8ZHrY9zTukxQBLwE/Gyg2eYbtJikCVHSVOaPMeLvusbCx4F3zmvzA0tirT+bU2YjJes0GsSnmlGsymiP4d7pOIA+WZGecf0Fiv0/hsx362IaW36Kgi7QFR3hqC97aoGvG21mPz92hX4+jtsZoNjEYjRwh34ZaWCgkE0fi3LiapPIlE8rOmB0/yolTzCBwfFYZw52xNwulhT7GhB0sO/WOezGaXvnKV1Yjk4HGgEAHmj27t1Ch1aJjCORZtPDGoWCoUAzq4cXiJSUjZeSdnUn6ocwYj4xFCzza5KPTsa123zA2NowDCyKnGM2S+mjxLZGdBPfTSD4zYMS2ZJHyS+UWJbQ5fqpvNDkOZccSrXbljAH87Foy9Bhw+HPqgfE2HqWdBr3jbZBju9OcomQ0bugjl+h3bNaYogmOgkNwdew5SQ1SGCPffyej98f7mMUzTNFnvCV9cIrkkwu0+hVtsssJgOu2ZJwhoQ3vqatt+HuXM5lMlzd0SmiX9O1Z367yyLAdrVaGfmMDe/TaZUcvZ9jcsEvNUfe+iL4y319z9MmaOSoZT3NWu7NMSQojX9DQmKCL/KB/OAc5dQwRcoUevAviMeTc41lyb0zgYt4YI/oIn8oExoyVOtqZZ0KLhEe0SPo3nhIaBTI4J4x/ZZL6DHgGfjKSMXnGVHv4ZKjBUBv0ifETvIIZnAScvGOOCtbOYg1Ba0t0v52kpvPs3DqFwZB0+qLlW2usd364jjFK9px2QSt8fNK1efPmxd9VwLMya44gQdOV8LGGMU7hRIbwTCYElO0EMlIbfbO8GktyaQyT0Xi1/pxmsk7RGUlqQAKNxs1YGnvBNboS/wJZDGz36knu8aIeWfbeUMatI/LbXGl9z/qKLrS4Coj7HMnOK6dVPtrxiQ555DbZio93yIiyJHXdMNbWGW2ScUE+66C2jCvbClY+NfCZDll3ZF+wwNFj80B/q53oUgEe9h0M0C/oQYbpZc49mxCdyiWYsRWMJ0yUSfI5+PhLtuKnbK0l44de4+eKPnnmiKt8gRfBqGT0GyjWMPyzhcxnG0Ce7T6bHwI+eGeXqAtLp0J8R0/u9bGREozw6CQDWbAuNvxgqExAhI4jL55hrQw+dIMfkBzqXKejfJ5GJp3qIYN0KJzhLRjsxOpGwLE79BthFFeRBxOQA2MHzRFkx3UZK37wiCK2QDOqfDNtsWJ4i8QyyBjXjsslqd/HOn7n2ZF2BpJjqYylabPHkKIoGE+SBYSBxMhnGDAELagUBefO8UBHBw855JB6TBdvaPJdscXVkXrGGmNdSmaz8Fi8Rfzh5p+EEXX0w20MPwrKLpDj83BGs+8aPdshgive7Epy9BwRda9NPzSSTIdmShimLVGesIavMbeYuVr0yYx/pslpCQpXNJbzYbFivNjBoJjtwOA7mQ6Nxm6lJLrLEbSYtjqwdeScrAvaiPT6p5jIg09GDjjggEKuk5FhRn4Zssns6W00CoAx8PyzUAxj+RZ8v4Lu9xLQhF6nMowJTJuMKyMDsPZNaJJibLRhPrsn4xxNfAm0JdPlzY4mw9SxVU4OrBmtDBoBN+Pi2T8NiS5zE/0+PaEjBI049Oaro8vqMZ4YwHZGjJd/rgZOft+DnGlnnonMO2rutyv86wMMM8aJ0z2NHgaKgJ3TQo02WJgfdnc5T3Y3fSoAE2Pn5AKnjx4WDDPvYaFtnzW1tlt7s76iVzDOmOqLTLpKdJTf1/AbE+TJDuuQPoarNDidUAT7BHzpPbqbnuA84Z3+cFzdvLRjTW9YXwRrlZN/7+h7Vkn7AqNN59lJdILHuiLY4rmVkUmJg8cBg4exdFKEjO622271h1bJNQcIhuTGmkOu6e0DDzywOHmlDTzvu+++9Z8ANH/JvzUhme78XAk7pwnIXrK0PzLgpMVQbws84Im+FFzk5JF9zrr24WDdJ+PNCDfmxtF6R59xBK1tsLC2kXHzmQ7QxrwS/sxfn+DRj06ltZMIZB/9Ajo2OayzZNY4NvroOadokq24kVkBH/IvoOwzA7v7xhUOPuFKUuTDXOAIDgKUHJzW9mpfk9GPBO61117FGk6fsQXJrLniN2esIzA03k49Os1IP3OsnDxqPKjDvoFHy1urV/Jo7eIkCsSg3RxgO9BX9LV8Jz3x0NYwMs0+MtbkBRZ0Abm2ftEXdJyxJiPWYqd52HPa2UgJZmQGr+wWJ5foPvY1u9b8cE8f8DNs9AgcNiytK9aOoc6FIb1Kf9A15qq5wy6mL83h4Rq0nvHsDv16Hr01RLvFieHMWOUwWnREHSkdRwwdezShTEY/nkOxizxyLrBhsWOMMQAoMN+cUYTKZpmSFHQxlkX8ktR/eoRCZXAxJB3fsdvFMaVE0I5ePLdFiiPPIEm2LtDTpjtJ8Y0ZbOEs6Z9hx6B1JFrU3zOlCH+GJQPPzmyS+nmAxQDPlB5+GJ3TprW1xxhBR5LC+PRsNw1+HGcnJdBLQTNK5MOdoW4nC1/qoLe1OcsrwwHGwz7sMDnihTbJ0VpOCXmx0BqDZDTuSQqninGn7rCdWd6TTXNG8Kz1o39zzLyCn3nI+EtSBCCajDOQOX6MRI4JZ9i7kgWTw0DmGWHkJRnx2vqZxjVJIZeCVMmofXJCjl0FWOBMVpLUH0JDPxlORv9KAUfOYs6J4/SiXyJHMMCfT4LaXCir8MfxIM+ClzAlR+YHOhs5Akb0TXtOUhjz3mH4+YTGUWTy5xtCzr+2jLEAk/bgRR87GZOM8GztzeOapJA9BqgxaX0ybJ2awK91oo1nKzf3OT94a3kCrU5PCQZ6T0BJIIDeEuggF0nqUeX999+//gsj8FOH7CRpTc3las0TCDMm4x3asSeP8vGCV0fuyYVApjngHs/kG89J6r+AwPAkw3imo7Qvma+cyqYr6dlkPjzbPcdPsrw/Mgp/vEpOStBRTV7pew5+ksWx85swZJwc22kjD3QanYpX/NMJdtXIFezcJ9HFXBN6BGQEpB21N54IMHbG33igVwBDcEdZSwKo1pr2nIzWDZsE+Nc2x4Pu1Q6dQTcnox+Y82xus0/cD+dLa3M1r+hnD3HqyQC7DwZJivF0oiFJ4czT+WSeXvYpijFvtMOULjefk/nqCqDgAAAQAElEQVSPcaNje654Ntb0bqvvRJk1h/1LXu0SmwfK1TfH6THP9Bq5Mf7WWbvJ+JfYmvQlW4Sdt1oyj85ZpiSF7UQP0gV4tnabL3wFm3zwZftKdL951LBs9k2jMUnxjtNb8pIU6w+7xnhYS40RjJWv99Qd+vU+gqtMf5LCAbew2H1qifHPsDHRGCUiYBS1yaeOK2dzSL4Jyxj1LsWVzEeBo5MyTUb9Uah77rlnNTIoX846/iw4+EBzMopCo9VOYXMslM0qiS7CriU0oRtueHD8Er2UE8yVMxIprkYTA0ygBM348V4rm8VVP5wLbcOVAefqmWyIyMtz3MyzfAlPxgC+40a/8lklctcW2NYHYwOOyUg+0LnHHnvU3yEYX1iT1B+Xazy2NmZ5TUaBmiYXDW99wtGCBcfdFnb/khEP5h58k9R/lq7JOCMRv95NUrxjDKVmkCmbdkIf+sksmUhS/wlAuMsnz0O+yDj6h/ORIY1OY0PXNBphQN/oQ+AjGWHQyud9RY/AG16bkd5oYJjjC38tLxkFGdEuzxF97xoz8trqJqN/6kmZ9ofz3nvzSkkKWTFuEvlLRphv3ry5yKO3zLNklN9oo5/o0vbsSkfhlcx6Nv/UoTc4r8Oxhh+jro11w8Z7E9MMMtE35HnYBRlFe8vbddddC9lumDR5lj/kGR+cgpV4Xi35NifJZbJ0HJMUY51szU9SP2nDKwObbklG5UnqP1vIcYONcSXHMODQ4l9+kkK2lbnqX/68E3qMhU+wBNKSER/oUCYfjeRg0lpgfpBV9Vuyk2gcyY885WSDLMMl2dqHuc3xMY/MGfXXWsI3m8QYsl0afdZzet0znvEBK3q/8a5MSlI3WIZzXP5aTHgg265N9s1nG1jyyQL7rNGepND11gN5yWjOkCvyP8SCDlQXVvBTfyOmJIXMwKsleJjnZMX63vJdPZMNcw4+Q3zhk4w2kqw1niX12b7atX4mW+eV8vWcukO/nkdvjdCepP4IjEnVUpLqEJeFvyQL/x/9l6TWTbbmlcFfkm2Wlxn9JVlCb7L0GV9JlvSepNI6qazM4C/JYn/6lJKtNCVL71t5sjQ/GbWTbM0vM/pLsoirLpLJz0kUL0lJ6rtJluTP8iFJ7XO8jyRLspLUsUiW5peFv2R53kL2TP8z1lKSZfQnWUZrMqqXpPhLsqxOWfhLUvNb22VGf0km9pOM8pNM5CtJaX9JahvJ1ryy5S9JfT/JlpzVvSTZJq1l7C9JpV92ksV3k5ThX5IVy8oc/5JUOsblJknlIxldy9hfsjw/mZw33nZrKkntO0mZ9t/2tpdM7jtJ5X/YTpJFepOU9pdkSd1k9JykVVm8Jql1kyzmzesmWbnPZGlZkom8loW/JJWHhdt6beObRNZiSrJiG2WOf0kqnUmW9Zpkkcaywl8y+b1h9SQT+0i25icZvrKm7pMsoz8Z5SE0Gd23sZa3XlOSOuZDXpKV+UtGZUlK+0tS20i25pUtf0mWYbmlaENd4DeekhHvk/Ib88moTntu12R5fjLKS9KqbYhrd+g3xDB2JjoCHYGOQEegI9ARWEMIdFI6Ah2BjkBHoCMwFwS6Qz8XmHsnHYGOQEegI9AR6Ah0BFZCoOd3BDoCHYGOQEdgxxDoDv2O4dbf6gh0BDoCHYGOQEegI7A6CPReOwIdgY5AR6AjsAWB7tBvAaJfOgIdgY5AR6Aj0BHoCGxEBDpPHYGOQEegI7BxEegO/cYd285ZR6Aj0BHoCHQEOgIdgaOLQK/fEegIdAQ6AusIge7Qr6PB6qR2BDoCHYGOQEegI9ARWFsIdGo6Ah2BjkBHYDUR6A79aqLf++4IdAQ6Ah2BjkBHoCNwTEKg89oR6Ah0BDoCU0WgO/RThbM31hHoCHQEOgIdgY5AR6AjMC0EejsdgY5AR6AjsG0EukO/bXx6aUegI9AR6Ah0BDoCHYGOwPpAoFPZEegIdASOcQh0h/4YN+Sd4Y5AR6Aj0BHoCHQEOgIdgVI6Bh2BjkBHYP0j0B369T+GnYOOQEegI9AR6Ah0BDoCHYFZI9Db7wh0BDoCaxCB7tCvwUHpJHUEOgIdgY5AR6Aj0BHoCKxvBDr1HYGOQEdgHgh0h34eKPc+OgIdgY5AR6Aj0BHoCHQEOgIrI9BLOgIdgY7ADiHQHfodgq2/1BHoCHQEOgIdgY5AR6Aj0BFYLQR6vx2BjkBHYIRAd+hHOPT/dwQ6Ah2BjkBHoCPQEegIdAQ2JgKdq45AR2DDItAd+g07tJ2xjkBHoCPQEegIdAQ6Ah2BjsDRR6C/0RHoCKwfBLpDv37GqlPaEegIdAQ6Ah2BjkBHoCPQEVhrCHR6OgIdgVVEoDv0qwh+77oj0BHoCHQEOgIdgY5AR6AjcMxCoHPbEegITBOBqTj0Rx55ZPnvf/9b/vOf/9T0v//9r8jbHkJ/9atflUMPPbT89a9/3Z7qa6rOv//97/KTn/ykHHbYYZX/7SEOLr///e/LD37wg/KXv/xlu3HanrZXuw7etmfs1Wvy4uoZ7a7eJ0eunuXPKmlf/5L+jqqfYX33knfR25Jn+UfV1s6Uax+90lG10+qiS33P7hu9rp7lH1Vb21uuLW1qW59H9d6wvnupva8NyfNRtbOz5cN+9ed5Upvy8YUu12EdZd5V5n5YNst7faHFddiPZ/nocR2WTbpXH/2Se8m7w9TKJr2/M3nok4Zt6F9/0njZsF67V1+9YX3386C/0bC9V7SiDb3upSGd7lvZeJvqelcdV/VaHffyJPVa/ryv+kaL67Bvz2ibRLt6yr2n3L288SRfuaQtz+q4tnddPcufZ9LnkKbWt3w0KXP1LHnGh7xWd9JVubrSsLy1IV+dYdks7/WF7paG/btv+a6e0YkeV8+Se3mTkjJ1JPfDOvqWL42XDevN8l6/6BjnT5/K0KZMHc/ypZavTPI8LFdHkqdMHcm9fKmVyXMvb60ldKFPgsFK9ClTR/LOsJ5n+dKRC37GsGwt3uNFGtLWeDCG42Xj9ZSrN85va2M8f/j+RrqHA14lvDfe3MuT1Gn541f1lE/CUt1WtlK5OusxTc2hf8xjHlPuec97lnvf+97lpS996XZj8aUvfanst99+5be//e12v7NWKnLoX/WqV5UrXvGK5Ygjjthusr71rW+V2972tuWXv/zldr+z1iuaQH/4wx/K61//+vLVr351xUCFel//+tfLve51r5ruc5/7lD/+8Y+1vqDOK1/5yvKABzygvPe9793uIMmOYGNCC8Y88pGPLA9+8IPLN77xjW32R4EI3Lz4xS8uD3vYw8ovfvGLGoR61KMeVWWe3EsvetGLKi/41IfrjtC3rXd+97vfFXL3m9/8pvY1qa5+9S949IY3vKHy+KMf/aj885//LE972tMWab7XwjgYA3UntXN08/RLrh/96EeXhzzkIeWTn/zkUeL685//vBj3Bz7wgeXvf/97DXQZE3hKaJS0fXTp2d762kbHU57ylHK/+92vvPzlL6/jK3/Yhud//etf5Y1vfGOt9853vrMGMdVRZkye/OQnl4c//OFHKVPemUbS75/+9Kfyile8onz5y19ebFK+OfWyl72swPbggw9epHWx0uDG4vbjH/+4kOEDDjigCLYefvjhxRwxDi3R79oevLrTt+bXBz7wgfK+971vsS19oP+5z31u1RUf/OAHC+wXK4zdaMPceN3rXlce9KAHla985SuFXD/72c9elHc8HHjggXW90b5y17GmZvqoP1h/4QtfKE9/+tPLfe9730on+UPfMOFF/XGCzOtHPOIRFRf1v/a1rxX14HPIIYfU8TZOf/vb32rb4+/P+hmu1oGHPvShy/qnO/F8rwXdg/bvf//7i+QYQ3JHvxlDa8Ni4ZYbbdPX3tXGE5/4xKoz8E9e6BJz+EMf+lCxRm95bS4XtKHZnENP69S9MbeuWT/e9a531fEir0960pOqvH7kIx+ZOD+9y7748Ic/XMfVPDeu8vXXeIbpRz/60W3OkUbPzl7xAmdjIBkHV+NHZ7hvSdn+++9f5QC91n/6Ed/4x8c4Pdr53ve+V3XPYx/72GoreVddWOCTTjvooINKw2K8jVk+owMG9BXezGM6WL5Ehq2B5FCdf/zjH3W8//znP1f7ZojNSuuvdqwzre473vGO2gZsrOVwYX/89Kc/rdjOkt+j2zba2fRwYQfQBW38hm3JYw+z+awzbCx56rhaj+Co7NCFjT95yrYnzbsOeXj3u99drFOtb/TauGs2l3Ly28qHV++bU+bxy1/+8tJkBpbmAl16wMK6/N3vfrfKwfDdjXKPV/jQj/QG+bEuwlGZuf7CF76wrufbwtIcefOb31zuf//7l+c85zmlzU04aedNb3rT4tppbOa9TqBjFmkqDn2Sco973KN85zvfKbvttlu59a1vvd20Xu5ylyvHP/7xy2lOc5rFdwAuLWYs3Iw/L2Qt+U+5NMz03NIw3/1R5SsfrydPki8d73jHK8c5znHKLW5xi8rDsEy5JK8lz0nKRS960XKiE52o7L777iWJ7DpBWz3XmrmO/seQtODc9a53LZTwSjyYaOoxeg4//PBywhOesJz0pCetC9KznvWswjC9293uViiut7zlLTV/FjCYwM985jPL5S9/+Yr9LW95yxWDMhQtJX21q12tCFrstxCAIucMEw7cHnvsUc5xjnOUU53qVKUtrvhjuOJxJSx2hC/tcSIZu4yhldqgAC2O173udQvjx5wkb/J+9rOfVXrRfMpTnrIGVNRfqa2jk08OBBCudKUrleMe97jl2te+dtULk9rQJ2P++te/fvn2t79d7nKXuxRzilNKccNVkscQmtTGtPLQQoed+cxnrkakBZQMyh/24Rl/MOVQcTze+ta3VjkVLGHcnf70py83uclNCnn55je/WeVr2MYs7hn5HIUf/vCHi82ba5xhgStGI3o5BZPkkYwzPK95zWtW5+iOd7xjlWfzkSwbB/JirjJWJ7Wx2PEO3Jjrj3/848tnPvOZRbzQhCf9nuc856nyQX4n9W1cjNk+++xTOHK3utWtyvnOd746Hz/2sY+Vs571rFXmjS8Mjn3sY1c+zVHOsfd3gOwdeoXuecELXlBudKMbVd33uMc9rsrPS17ykrJp06YC67Of/eyFIcO4Ge8ErYIB+DU2jJXNmzdX3ATQBJTufOc7F4Yy41B/423M8tn46PsJT3hCIX/ksPWHdvj/+te/LnSZeX3a0562Fisjv9e73vVqYIoMwqMWDv6HH0YYXayN//u//6t6Qz8CgZwHjhRH/7Of/WzFtszpz3jRAQxG9OgWHpwbfMHjGte4RpHkMzovfvGLF3qYPNB93hkm9aw/jFvjao6Yy3CQOEPw1i8n+XOf+1yVhWEb077npAiYmZvk1bzCozH81Kc+VfuXrzxJdbqVCdiSyZve9KbFuF/nOtepQWY8Dmmk/zmydKi5f+Mb37i2oR7d+9SnPrXAwoYQhxEO1MCviQAAEABJREFUw/dnfY8XcsyWobfQZa0jz/SWPOufNQHt1gl1Pv/5z1c7Ay4SPYRXZUOaPXPovEfOzfGzne1stQoM7373u5dLX/rS5RKXuES1PwV1auEa+R/ZF3A5xSlOUemDDdnG15BE84Xu32dBb3PYzQE2hHrsFO9d9rKXrbzSB3S1smEbU7rf6WZsZtnYNC9aY+SSf8BWY+vuu+++hf02zgOZobusb9og1+xT+drg4JsLZIE8yW99bLQrXSeQdYYznKFw3vddwMy8IlPmFTv2/Oc/fzEH2ODjWKpnfTj44IMLPWmNEPiCo7rGwty1diqz1lpDNgKOu0yDiSRVSVFeIiLASUaO6lG1LxLD2OIYq0tRGhAC694AtGf3wzrupVbu2uq4el87w3z1lclrZfKk8fz2rO6wLffqU6yf/vSni8VJHamVKfcstX6USSb86U53uiXOvHrD5P31lCxeN7vZzRZ5mkQ7PDkXMLvqVa9aOPAmWpIaQbN7QX4Yp894xjOK3fBZLVQWUbsEFguGQZJioo/TjeZPfOIThaF00EEHFYsURbPLLrtUhwed3r/Tne5UgzsWWQsSY9JC5T1jPt7ujj4zcG9+85sXNKzUBpp90nHDG96wWAQtDOc85zkLmi2wIvucZ3QLLglqHOtYx1qpuaOVrx3OFEMDVngX5BhvRD7DlAMp8owmijpJdWgoZPQJnjBkzLHxNqb5TM7s+lkoBBCucpWrlEmLBfkls7e5zW3KiU984nKHO9yh7rg4lcCQphMYJec973mLwJRdUrxOk9ZJbcGHsz0sIwMcBuOx20KgVbCNsWAhIyOtrnu7g4xkhgODW1CCvLjKNxZkXPD1Upe61DbneWv36Fw5Oxe60IWWvGIBJhtXvvKVC7wvfOELF0bekkpbHgQRRfTxSG+c+9znLmRR8Wte85q6+JMlTsTee+9dA7B0DSPMaSkOirqzTrCm9xgtnG98WfvIiHE68MADq6MiAMehFxhLlq6laDVO8BAMEAg4yUlOUp0ozjy5o0O1dcghhxSB9lnzNWw/SaFv9l7AeZjvnmNizb/kJS9ZdSraGbr4Z8Qy7MkfvckuIIPeawl+cOM8kpnnPe95hSNrrM1XwRzjSt7JA71i/W3vz/KqH8G929/+9ku6kW/+XOxiFytOXOAdvXgTcLWpIZhInwhoLHl54QE21hkGv3G1tlgr6SI8v//97686iGyTf0asdxZendl/Saqx3NaRa13rWjVgxva7wAUuUNCLZzpDoNvcM3acbw46Z9b4WYftSo7Ta1fWJg+d0IIfgmDqWRvICCyMr7k0CbeZMb/QMAeDfNG7bB/z2Hwl2002ySEcYCAAh3Z6SWAGbjCxjpv35GGh2cX/OLqCmcZUMNY88W6SYo6bM/Tw5Rc2JE5wghPUU3eLL6/yDT4FmMinwPYeCxsebAF6j04fkkeX4Y+9ABMBVk6WNswVp18vc5nL1I0XWDnFRY6GbazO/fJeOdrW/SF9NirIqESmnWIWfB++rb55jF/zl/1BhzgpxyYhazZw4ECW6FBr+LCNjXTPD8K7OS74IfiLX3rUnOM72IDba6+9asB+yDss2QivfvWr6ylJG6cCAoL67DN16U42+u1ud7saMGCD0sXK1nuaikNv8pnAhBkwyVIDZCWQDBzDhFOVpB4xsfvDgBc1sVgzkBmhItgcLu84Fsu50q+I3YELRtC5znWuYlEx8OqoawGkBBkWlIvBJhR2zRhKFhXHMeRpy+QzuBQQZWziMM7PeMYzFsc7rnCFKxSOuPe1JVqGN0avCbv7wo47A0pbHARCpC3OgUg0QUKb43gUcZJ6JJAzwJBhBJnwFLV212NKtj32Fl8TzmQ1KSkrfH784x+vRraFKknZc889C5wt+LBWZ5rpZCc7WT0lYWJbRBhWDIhhH/q1AJn4lIixN1beUcbgFGEn82SIc8BYk2d3gYJmTKs7bHdn75Ns06EiYxSiXRNybi6QR/2e/OQnrzijOUl1WhmanpXvbGLQcSzhYT6hASbj7ZojDDO4XvCCFyyUtrkOq1Of+tQFhmhSz5zmvCQZb2ZqzxQ/OugS8vC2t72tOKqNhmEndvyMP52QpAZWyLBjcHblznSmM9XASZIiOGBXAg/DNmZxnyzHxlxjbBpzfNCreCPDjQZ444dxSQeZA3SwPGVnOctZFsfCXLAjNYuxSLJMpgUP0E6WyIA5a9e90d6u5N18YxSTNfw1WTIeMMC/cTCu5nOS+kmI4KKAk2B0a29WV3jaPXZ8VLANPU74oJ9Tb/1Ap3TooYcWBou1JckSkswrYyRQZ23jLGjDekTeyKY2GPqcRHpU30samfFDMqI5SQ00tO7wz/ERiLD75pQBHCTOj7XPjjVcjKH89m67OtUjWMVhNJawUMYoJr/kJEmhR/CuP+WzTPBFk3FgB7W+PAsoWfMYlnQFh0V9dTi75Nu76DWe8ltSj41jHbH+tHEl02wuBj+e6Vxl2oODOeDd1s60r5s2baqnSfSZpNpHHA7PgimuUpJ6QgImxvO1r31tYaspwwPn3hyEQaNRPYFI9awD5gY7SiAHX8bUvNAGGacnzIlZ8ttoa1djIhlf/Vo/0IsOtiqbFn1oF5DkpHk2xvSU+2R0csE6kYzmS2vfXNa+YI013FpER9m1p4Phpm2JrWzTQVl7fzWv8GALtTHCKx7NfWvIkDbyavwEMARlOfc2HbTBfuboez9JodecIpukE4ZtrtZ9snQM0YFvcrHLwgYQPsgx/pQNE31nfM2DZKS71CdP6rOLldNlNhHkDd/fKPdJqh9HNySpp5jZkObMrrvuWpo9QIfKsyE1znvTsWQtSd14gd8Xv/jFWpWPZr4INvHb1CNvtXCd/28qDj2lxjG2ECfZLkgAeNhhhxXKXBTWJBXBsxvEuaPADADwKUGKi3In8I6Bitz5joijzBCnLEQzDaZoLUeBUrXgccoZC/qgDDnrggUWDcaBfA47Z5qRJMrqPUpaVA1/aPGunZMDDjig8ijPZEU3p12AgBI28TisjldJjtkx+NVRTtkRRBjYxRXddTwRXxZu9NUONtj/ktQdTU6RyBv2KCc4GAfPyUh+ktQjscZb/iwSWTGWdugEDsYXRHTZRRbYSVKPSjHK7ICM16UgBIMY0AwS7TLkKPBZ0L6tNskrx8VCzyBw/FTkl2Pf3sMb/kUtRb5b/jSu2rZr5iSBuQ2/8XbNOQu2gNt73vOeepxaAI4jOaxrvqDbDuQwf9r3SYrjXAxvukNwjYOVjOSx9WdBxV+yNR8vsGRgq5eMypLUkyfK5c870Y9DWpPRSaqh7Cp3RJb8kxs6zhFBeo8eG9J88MEH188IyHgy4nFYPqt7AVC6kzFvbg37Qb8xozcFH6wX5MhOhiDAsK73OfgcDgEuzqAxt74M683qnhxY26xlDFjrgDny9re/vTo9rV/1OOl2MFve8GrtEKzBKwfQjrxdQTjAY1jXMxxch/mrdW9NRrcjj4Iz1tNGn91166nAt+OU1lByOaQ1Ga0h1koBNDwL+MNTsGq8Lr61P8yf9r0+zDW78+yRJDWIId+csqPOuaHvyJs6dIVyyUkxp9vIL303Tp/NiPE873H6yLT78fJZ89z607e5ZK0ThE+yGJhThkZXxjea4JGkvp6MrsaYzMtUly5lZHtuST59xOlz3/KTEdatn5Y/66vgCnvX51d2mQXgBAaTLAZ00UkunRiyk89BS0Y8K0Mz7Dj7ZexPkMbpLgE6NrF7OkF9bQ6ra0veOGbDOvO8R4+gSzLiNRldjWsb5yE95q2dV/OAvYcX5fB0bSlJ/S0F7be8tX5NUuWhLPzhnZ3Lvk9GmCxk1//YiZxVa531mb/g6h0V6Hef1gh4sJHMhfWEAx62N7V5gj8yz44drtF0jc8P2GIwGm/X3GG7OQljbtLNdA8sk9Rdeb7b85///MJO1p6y8XbW4/NUHHoTkuPDeE9GgmowtgUIABk3jGfRJkqdg81ZEp3hXNs1ZcgRYPeMeo6Twdm0ECH2fYXjSnbmKUVHsihaA8VQMuh2DJPU7xEt/gxViyqDnUHB0RcdszPnKJPoPjqufvWr14XJ91p2Yikb/VM46MEfZ9zEE+lBj2gaB6VFEU0+7zBC7RwlqQEMO2WiTiYlHvTnPYKsvpMA28JuPZfhUaSNUXrAAQcUR6gYLPKHfMFXXjKSp2HZtO45Jo5PP/CBDyx2Dny3M9623Q6KlsHFSSA/TocI+LS6ZILjzDhNUnc0OaF22Bjr5AE/rf6srwJaDCdyaX40Y8DcaXSYfwxnNIqQT5smp2jMJ3PEKZzWr37cc8BETdHHsWIYwZ9hpFw9ySmHi1zkIhVTz7NM5NCxPwEQR705t3Aa9kkmh8/tXj6jtT274kN+MjsZ1s9KSd/K0NGuSRYNjLLwp8wnQHZKGJ126sk4w8IYLVSp/zEWBV44+zVjjv8TcKOnBYAt0uNd26GlY8kReRJ15/BxsFpd48iJ4nTIE6y1uycwzIniIMNC2SwTg44jAEdGLMzRPQx6mbuMWetOslx2jKt1zRpiXUKv3Uv57seT/GR5O+P15vGMFrQLfluHGWWcFuuodd+6bbzpY4F1+ePjog3BfcEBJ5EYZ5yjZDmPSZbIe5nBn7khQC3YSw7pfnnkim1kLNkojuTSi8aXreKapFiDnFZiD7nKH5KJ3+Fzu5cvtefhdVwXDcumeW9s2H7sODbQsG180CPW+iTVnlLuneF1nIdka131pGSUN15XmSQ/idu5JDYMGeVosXt9NmDdJdfJiA58WnPJtDVsSBh95FgwXWA+DMvcJ6mfDLFH2RXmBFuirPCXZBHfFarMNdt4tA7h4F5eErdLko04G3g2d+gEwT4V1HdtSTvzkuvW57Suxpt/wNlk/w/bTVIEmvkB9Aj735UOcRJDXac+6A72ic1IazE8lJVSNtwFb/w89p81ThC8MWk+2Xil82GibitLUviTbV2AJaddW/SQemSI7S+waqPLhqzxUbbe00479MAkfCIoIilJ6m6DHXPKbiWAvGd3HqDufVsl+mjwCCxl59spQGvLt8DaM1Ai2ZwQRgyH3wAlqQu3RUS7jvMlqb8aK/K/zz77FMaUCSUaVhb+kpFy4ZyJ/HJ8REO1z7AVKfSuHZ8k9QfRGL+cf7TYabArK4jA8eeUEyYGsV13ComzJ7LG+MCn3WmOvnuRW99c48Wz9vDieYG8Df8fxWZiOS5owRPUMX4YdwTbESuBmmQ0TvKnmYyPxdTRf4kcjLe/efPm+ivtlGuS+kNb7kWbW133FA565aGZgyoyKCBAjpPZ8KC/8WQ3CG9kL0k1DMiZwFXZ8ke2KTq7gOpuyZ7KRXsMbkExMm4syXdrPBkdpUKfvCTVGHE8jQEsT336wC6muSNvVklfaOTEO/JrwRCMsPPnaNewXwabZ7LqKgJs7MkJjOXTWcrgzSkzpz3PO/mWFcYtAGlRY3TTUY2WZLrLNRkAABAASURBVDQW5h25TlK85x28qQcf75qr0z7Nof1tpSRVfsmAo+rDIEPZ8kd/MLA5U8nouKLAaJMl1fBnXSBjSYp5L9hE79PJxjyJqjNNTgfAUidJ6rfm5spQzuy6eoa3eiulJAWfAtPWIDKoLXPbmHlPoIDMJrPnTX/bm5KR4WU8BJPQbt6gO0ldyzlKgjVlG3/Wase56VxzjZGnDYk8kAv522hip4vMMXLpVIHTEj7/sENpUwIdAkdo0RHdyBaxZihLUuWb4ek7acEA7ZXBHx69J987iuhGpxkEdYY82yTAsx2qZPZjbl6xkQSl0Ii2lvDIoXdsOhmNN8ekyT9eBHSMPblt75nPrZ46EjmwrrGxzF26Sr5ET7Hpktnz22hMUoyrILRAIR2PBptIycgGpn/MP8Ec5e1dVzQLAtBrybbpTlLwbRPKfGdrCxbhXWKLcorRo+3VTuQAX2QUfRIayaqxG6dPfeMvwAk/dlMy0o1Ntr1DJwqAqO95vST8kxG/EWKdGZeFxof5LKjnJI/NR5tIdJvyZLRmCXrc4AY3KJMCneptX1r7tegVG2F+O8DGTzKaI0mqvqRT/M6KIH+Z8EdnCgxZ880VG1c+LR1WTVJ/oNy8TUbtD8vX4/1OOfQElWKyy2oiElSLjjxOq+giMBkY4+BYvE1WdUTY1eOci1Y7rmuBFtFiWFocOUsE3cJp8dO3Mu1Q7voUzUlSfzU1Sf3nW0T5TQ4KRj3Osis6OXCiqoxwDiVH3A+RiOTYrbOIWJQIg77s2BEKUTNGoIXHLqgyO7S+6fMO54Dhph878Cay707VE60Xzea8EziROcIr2KAtxjQcx/Fa68/GA6Z4cfWMZs++D4SFZJwZN+oYS7vjDFeKmizYoYWTycxBUqadaSc0WCDQhEZ9Glt0K2Poky3fBXLYyKK66GNsMJLRpD6lIlDUxi1JdVAtPFISVaeS9Ac7tKDbs4Y9myf4IOPmo90Bz4w8vJLrZEQLp4EiI6fJKE87O5vMdUaMa6PTQp6k/l6EgJgy85usO8aNRnkWdZ/PJKlHVgXyBMzgvbN0bev9JPVHPckmIyRJcZQZ/RL82re+vofkPAnUoNvc5lDRCaLn9An58Y7PeLRDBrbV/zTK0EkeJHKrTZ8awZR8opWxQMYZxmhsMt5+z4MOIkcMKvI8dITwxUmYFS/objygn1yj2RpBNpTJF3DBm2f0O3JnbRAcpDPUNY7qmgPqStpxfM9Cn6TOzyTVccRTkjLrP/04EUDvwRoPjH5rDx5a/37ZWj1jJw8v1hWOEFzMZeuSsRI0oiO14dSBEwp2TOFgfbNGMRS1M8+EZvwZV/fo1r9xMMeUWZfpH84KfcBIs8Ybd/R7hz7AJ17kew8O5Fc+LDk6AlUXv/jF63jSMeq62tnUtr5nlbRvh9GOreREkpMgHDYBMBsCPm3CE7oY93iFi7GUjy9lnFtOj2c8KzOuAq82MDw7fWIOm494Jid4pXPoTJsRTjvMit9hu2jWPz6TpXOIXceBIYNJ6m+3+LTQiQy0kn16hd2TjI5TWzu05/Se9cyztcpct0lC1p108JkQLOhhDq75P6Rr1vdk0/jRP2w5p93Ymk7zyadD2X5sVfYl+9RcaHQZQzuEbJ5ktN7BBB7qaddcgS8+2ZS+pYcNm4k9Qs+Z/95he9Ivrf3VvCYpNuqMGz7Qb/OAPmZL4YtNiEa6wBiby3BTlz5IUoyzzUK4SNZgTu5a4RP9w2TOSsYPL2TEszlu/gvs4I/uli+Ra3mtLjxsGNJv5kAy+m0xOg9G6sGCfkmWzrchLVO9n2Nj+MO7k3jsQ7rV3CFH5gIc8N8wbjZtwxJ+sFdu3tHL1n2bM+RGG+QP5vC0VvoEQtkc2ZxZVzvl0JtgdtR9J25xdlxeEkGSCDJDl/Ia58DAWHwsUowR7ajHqXaMgqHPEJEHfDtmFimTgTI3wBSExVKfdu453pwqR5QcXXN0luNtUBmodgNMIFEf72jbwshpo1Ts0OnfLz6LhFpQOOCCDKLuoucCFYSOonGqwOJLSCgvSkr/FBIBsqOkXbzri6BZgOxaotUpAicRTFzOl8WqGXreWU/JeDguhUcGKXlAP2z8YqcFztgZM8+MHYuUY+zqwdEv/Rp7ssAYgLkFTPm0k0XYDrLJ7Ag9R4fM6oeMcIaMM2PKwmw3zzi5t5NCbtRNUr+t90nFPJQCzMgWuRShNAfRSf4sgHBDByzJnNMhfoBKEMl8SkaLgPFoyhAf00oMDIaKuedYKbkwH7VPthk4aEajuWsH3nwkO+qJxqorMWiNibqeZ5kYpAxh37vSDY54u9rNhq0fMdO/+e03MRhwyhlWPvFBI6eCAYt3vDHOYZGMMPf+rBKZsFDRJwxl/ZhTjAO6UaCSLjK3ktQIPxlXj97xGyi+JSPj6hs7OlO55Ei6OYJPz9NOxt+cFBx2nFD7DFU60q6neWexZigmIwMY/eaBdcGxObJHh9P9dAdnUDsSZ9/YMCg9r0ZKUtBExug5WHPEYE2u0MSYEegVzPTckvXP+Hgmdz5Bs65Zq8xx7ycpdkqtMeSPnBpvO+Dem1eij6xnnNskxck3efo3fvSUOaOOsWq048PYc1joLJ8jCOZZSzi07AXtMOq1w3E2/5ozY5cSv074kQN63Mkr7et7VikZ7Z5Zq1oiZ+afvgUV0GatYV8I4uPBWOPLziSa6Xb2hTlGro0xnj3TTfAyrrBje3CUtcvOIAt4thGx77771oDVrPgdtkvXCMokS3WccUI73lt9fAjQCvCilUzjg12WpBhzO97qC4Q6oWE86QbBUnaiNpzWZHM2LLTFkfbevBL+zENj6qg0m46s6l+QSWDN7qBgBT1FXjkQyiVrm7JkK27mvVMd1kw2Lgfe2GqfzLA5khTBPolu93mRz3fYH9pdCylJ3UU1Tua0MTY+5qLxE/ho66lNMmuk9cl8Ni/YCEnqL9vTl/SB5KQjHJKtmJU19Gc8yCX+nNhFGmdSwJzNaLzJgn+mV4CWDHnmC3n2vs1MusMcty4nKdYuwQDy7hfy2a3saFjqY62lnaEHJjCw1tGL1go2INvAOgAvusDa5nSPedX6U8Zn42dYX7XDZ7PRS08mKYKp5IvNaX2yGSNtFCx3yqEXFeVU2AFicFFwkkWZoyb6aBAo5gZ6u1J+DA8GiEXPjifBpcAIruNrSQojklNuIbQYcAYoMQ43g4hjaCJQhAbNIsqZEeGxYFgkRHoMmHIRGfneZeCJAKHFYtnyLULy7LrrC00MfIa6/DbhCJp2N23aVOx+WYztejL2CRy6KDSGpr7snNrRUy9J0Q+e0SL6zOFhTDNQG07r5eqYn7F3tMqizEFCu3xH8nyOQR4schxoyt14Gi/1ktFCRfEJoJCn4Q6hOtNMHFy7QYxrMmgs0ZKMjnqROXKZpNgVZHAZT/Utnsa90cOgsPC051le7Uagg8HnOCNckxSLPQPKjg3azE00m5/kl3wN5YqxYFFIprs42r023j5dYWhz0o17MsKVfAh4oVFAAQ92bcwBxq0xgF+SIvDT+JM3y4QejiPnCl70DXrIACNCoCRJ3QFkgHKAySk+7ZSVhT+0M6aV4YkhypBZKJr5f+ighwWe6Dkd4okxQRdx+NUxL5MUEX4yrk6S4p/OYkSQLTJD7yrTTpJCxtvxP3nTThZY9DBkGSzatyYI7KJ/v/32q/88KL2vzLioT86TFDvvcKevjR2jSR11JfqGg+h+NROHz1yk32AtmbvJaB5ajwRPGp9oTVLoHRgkKcbRukFeGTzNoUpGn09w7sgfPMzxNo7amlcSJGcHmO9sgWTEn2Cv3Tq8oB2fSeq8okM5RnilD5TDa/PmzYXj7pSbOcZgNk/NNUYyzMrCX5LCObCGWPcZdW0uLBTP7T/0+P0GuCepR7PJpOAF3cJJFSjmkAtg+R6UkUouBF+SFDxzDDmxSeo/CWd+GlfzgUOnfTKOZ3aDMgnPyQjvWTNtjUZ7srS/JIWdMwwKogW9MDDGbLQmG0mKZzZRMgqQsAONIXm3lhj7JEWfMMArGXeyExban2cyd9FsnaUbGw1sQA6IE1ocVklQa7j+kn98NHqT1B8cNTccnae36Tc2FRk3n2CnPhzYonCBDz0gT9laSbCgc+ki6wnb2lqYpAhAcHzRijf6zvxghwli4TNJ/XVya6x5g1dyxp703lpM5Jp9z67ca6+9KonmL145+DYByQK9SOfj0xib83Q4nUeWBDfYUUlqYM789j6dxiaytsG3drD+/7eEgySFPuSn0fPwcjXH6US+Fd3PkRf84Y8lqesHLOEtEMKZpyPID/sMXknqvzxkPOgO8sm2V1Y2yN9OOfSAoEgsusMkT1mSCrT7MvYnzzuEOhkJrveGeV5RLl9KUiN/3k1S25YvyStb/tzL05b7Ldn1oj35ypPUvCRL2ioLfyLPJiZFra6ULK2fbH1Wrm39SfrwPCkpX+ii8uI9KRktYuono3bVWS8JT2jHt+QZ7Ukqn0mqcpKvXF33ZfCXZHEclCUps/rTPhoaLcnWvpS1pP8klQfj5J1ka92y8KdusjRvIXsm/yWptKAbPfouC3+uUjKiI0mtpw6alZXBX5KKdZnyn3701/pNRvToJkntU52y5e+o6iZb39/yyswuSZZgloz6Ri86k9FzMrleWfhrdfHvfiFr5v8lI90xLhM6TrLI05Ae9y2Vhb8ki/WGvJYtf+omI/63ZE31os8h/UmqrLR8VzSULX/uW5KV5CjpV7+sgb8kK9KapPKdbMU6GeU1+l3Jl+Q+2Vq3LPzJUwazZGnZQvHM/0tS+TOe0pCOIW3uy9ifvHHa5UlJlq0hSZa0kKTip432TpnzX5LKf7KVNrSgCRbuy8JfklqvYdTyy8JfksrHMM99ayPZ2naS2o62pTLHvySVzmQrPWXLH3qlLY+LF3njfCSp7SgrW/7ct3rut2TXi+dWlizvu1aa4f/0L6HBddiVZ/nGtSXjkmylUx1p/L1WT5k2pJY3XreVqTssWyv3SRblckijezyVhT/3+JDcJ1sxWiiuMqGu8mRpmfK1lNBpvNHaeJHnWX5LntGtTktJJmJVFv7U8Y7kPlnbOCyQvMP/JVttmYaXK76lYx3rWPUHkuHquXXkfpiUS/JaHddk1P5GxXKnHPoGUJK60CZLr63cdVJKsiQ7yWI7w4JklC8v2Xo/fE7icTElqW0tZmy5SUb5SbbkjC5Jav0kxXEou4ftGEwyKhvVHP0/yehmy/+Trc9JFttKRvdbqi3mT3pOltZtddbLNRnRn2QJycnW5yTLMBhWTkblw7xZ3SejvpIcZRdJtkn3UTYwxQrJZFqSLOslSaV7WcEMM5JRn0mW9ZIszUtS6UtylHWXVZhBRpKJ9CRZ0luSWm9J5paHZOWyLVWmfklGfSZZ1naSFWkdVk5G9ZIMs+dyn6TSmIyurdNk9JykZW3zmqS2s81Ka6AwOfp0Jql0J6DHAAAQAElEQVSUJ6k8JqnP4/9Lss3y8fqzek6W05Eszxv2n0wuT7JYLck2+UtG5YsvrMJNkmW9Jql0DwuSUV6SYXa9T5bmJanvJ6nlw/8lqWXDvLV8n0ymN8kSspNM5CsZ5SdZUn+eD0mOkrZkVCfJdpGWbK2XZGL7raFk2+Wt3mpek8k0JlkkK0nlM8li3vAmSS0f5q3F+2REZzK6NhqT0XOy9drKhtdkVD7Ma/fJqCxJy9qw1yR1vJOt18ZssjyvlQ2vyaheGWZuuU9GZUm25Gycy0479BsHiq2c2JX3LZpvNBzp31rS7zoCHYGOQEegI9AR6Ah0BDoCHYGOQEdgoyCw3vnoDv2EEXRMw5EMybGNZONFciaw3bM6Ah2BjkBHoCPQEegIdAQ6Ah2BjkBHYGUE1lxJd+jX3JB0gjoCHYGOQEegI9AR6Ah0BDoCHYGOQEdg/SMwew66Qz97jHsPHYGOQEegI9AR6Ah0BDoCHYGOQEegI9AR2DYCO1DaHfodAK2/0hHoCHQEOgIdgY5AR6Aj0BHoCHQEOgIdgdVEQN/doYdCTx2BjkBHoCPQEegIdAQ6Ah2BjkBHoCPQEVhnCBwNh36dcdbJ7Qh0BDoCHYGOQEegI9AR6Ah0BDoCHYGOwAZGYHYO/QYGrbPWEegIdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2B1UZgzTj0qw1E778j0BHoCHQEOgIdgY5AR6Aj0BHoCHQEOgLrCYH16tCvJ4w7rR2BjkBHoCPQEegIdAQ6Ah2BjkBHoCPQEZg6AscQh37quPUGOwIdgY5AR6Aj0BHoCHQEOgIdgY5AR6AjsKoIdId+Evw9ryPQEegIdAQ6Ah2BjkBHoCPQEegIdAQ6Amscge7QT2GAehMdgY5AR6Aj0BHoCHQEOgIdgY5AR6Aj0BGYNwLdoZ834qX0HjsCHYGOQEegI9AR6Ah0BDoCHYGOQEegI7DTCHSHfqchnHUDvf2OQEegI9AR6Ah0BDoCHYGOQEegI9AR6AgsR6A79MsxWd85nfqOQEegI9AR6Ah0BDoCHYGOQEegI9AROEYg0B36Y8Qwr8xkL+kIdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2B9YlAd+jX57itFtW9345AR6Aj0BHoCHQEOgIdgY5AR6Aj0BFYIwh0h36NDMTGJKNz1RHoCHQEOgIdgY5AR6Aj0BHoCHQEOgKzQqA79LNC9hjW7n//+9/yr3/9q/zzn/8sRxxxRPnf//43EYEjjzyy/Pvf/651Xb3XKv53oQ153nddqY1Wf2eu6NB3o/k///lPkbdSm8rUUb/R5n38DhPa1V2pnWnk6xct0krtwQ6djV7vtLruh2XqtrJpXLWvX7joZ1vtwwof6sNO3eH72pCUqTsN+ia1oW196Kslz2gZr4/GRu84f+q3MnypO/7+LJ/1p180SO4n9YdfZXiU0C1PXW3gS742PMufZdIHevTb+kEPutBhTLZFS3tfXfW819pRpl35rtptZat1bTShF9+e0eUq7x//+EfVpZ7lD+n07B38qItXeeq44lGZNOl99Wad0IFGtKBh2B960Y1HV8/qq4dmea7yhu+1e/W0q56r91uZe3ned1W3lc3jimY0oG28b/loQpt7ddWRp76r/El0qqvcu5L35Enu5bU25E1qY5p5+kCPedkSGhr9jSZjLJEF77R8dSVtyB+nTZ531MGXduWp5+o9ZZI25SmbZ9LvkA70tv7RizbYqKNuK1NPWUvDslYHP/LVwb825Cl3be0rcy9P2VpJ6EEX+qUh/ZNobPVh471Wxz0eyRAsPbeytXY1XviUGm2NLxjgQ5m8Vj684k25eup7bnXdK5Pv2vKH72+Ue7zh0XjDAu/yJBjDQL46nifxrcz7LalPttT1jnLtSNqVvxFSd+g3wiiuMg8mxCc/+clyi1vcolzucpcr17ve9co3v/nNZU69en/729/Kwx/+8HLnO9+53OlOdyqf+9znqiNtkrm/293uVu5yl7vUssMOO6yWrcTezuSj5fWvf33Zb7/9ypWvfOXy2Mc+tlAck9pU91e/+lV56lOfWu5617uWe93rXuXnP/95Qd/ee+9drnKVq9R0hStcodKOF0l7kvcntbsjeRTTpz71qXLNa16z/OAHP5iIj/5+8YtflAc96EHl7ne/e7nd7W5XDj744FpX2Sc+8YnKB17ufe97F3Xl7wg94+/g94Mf/GC5xz3uUWBjPP/0pz+NV6vP+vz73/9eXvCCFyzS4xlfl73sZSumsL3UpS5VLnjBC9Z3ZvU//e6zzz5VFvRJJs573vPWMR72aVzRd5/73KfKAfx++tOfVmwtGG95y1uqTMH2oQ99aFmJ92Gb07qH5x/+8IfyqEc9qtzznvcst73tbcuzn/3sYs6N9/H73/++PO95zys3vvGNy5WudKXyzne+s/KgjS984Qvl0Y9+dLnWta5Vrn/9668oZ+Nt7swzTM2rJz7xiZUObaHlXe96V9Url770pcsNb3jD8p3vfGexXJ2Wfvvb31Z51wb9gQdjpY3Pf/7zVR7Nhf3337+Yy8ok8uqqXmtr1lf9fe973yv3u9/9qh4kQ/qXPvvZz5aLXvSi5XznO1/Zc889y9e//vVl5KDZnMEP/fXiF7+46i7v00sPechDinl3+9vfvnzkIx9ZpoeXNTiDDPL1jGc8o+y+++6VttYFGukfvDUev/Wtb9Vi+cbn6le/etVZZFn9Wrjlf57Nt/vf//5Vt5Fx78mXDjnkkKpLyMB973vf8utf/3qivJQZ/aHBXLIWGmfdyGM4fuhDH6pyeMc73rG84x3vqHR9//vfr3PVWOKF3KrvvZY8H3rooQXPbVwbz/r46Ec/WsebznnAAx4wF54ZyjCmK6UrXvGK5QIXuMDiWDOYb3rTm1Y5Ns7vfve7K7/GlNybp3h5xCMeMVE/kXH6CS7shJe97GW1bVj85Cc/KQ984AMrz2T8Yx/7WJHf8JrHFe6//OUvqy2DF2vsm970prpZocyY0MFXu9rV6nrwxz/+sZLFMWVrGCvvWUd+9rOfLaNfGx/4wAcqj+qa07DDJ2xe+MIXVvk3/93Lqx2skf+h0zxg55ETtggM5E8iUf573/vecsYznrGOc6tz2IIN2PQhO+C73/1uK1pzV2sTfum9Rhy+yD6ZN0/YRWSglQ+vdLWxth6YG+SJHEjmuzxJW7/5zW+WycywrfV6D68f/ehHxbxgTxvzl7/85XUDEE/s2Ic97GHFvLr1rW89Udexw9TxPszZcmc5y1mK+aR9a6q5Zyz0w/6FsfbXe9plvTPQ6V9dBEwQCw1HhvPw9re/vRzveMerBtn4IuP58Y9/fCXYYn2HO9yhGukWNAbAk570pOrIM1YvcYlLlMc85jGLE7m+tHP/W/I2Q+qc5zxndXgoYM79D3/4wyV1POCPU0bRchqe8IQnFPVPd7rTlS996UvlVa96VXWG8M34QDc+OXPnOte5ypOf/OSpGtTHPvaxi3Z/97vfFYoLjeOJcmIAnfa0p638UVoMAsa+hQBtN7/5zctzn/vc6jQ87WlPW7KIjrd3dJ6N48lPfvIa/HjpS19aXvOa1xSL0XgbcLWw3epWtypf/epXqwP5/Oc/v5zgBCcoFn6LGYNAsoAx6sbbmNYzWhjSxlV/jG1yevazn72c/vSnX9INzNGy1157lWc961kVP1gKtKCbcWXMYWuheMUrXjG3hde4H3TQQeU0pzlNeeYzn1me85znFHIpAITHxoh7i+YNbnCDKr/Xuc51yuMe97gafDAmeOQ8mBPGQxvabu/P4rrbbrvVZuFYbxb+x3CnG+gKxh5aHvnIRy6ULP0PP+g1N/DNuCbzxgPdnEQOlvEyb5UJ4JC3c5/73NUBNGeXtjq7J3oEjWTo6U9/eh2rYx3rWFVOGIVvfvObCyflkAXnVFApyRJiPvzhD5f3vOc9NQgpAPKiF72ovP/97696hvyRWbxy7uBi3i9pYA4PJzzhCcvxj3/88te//rXS1bqEMyMd/R//+McLHo2BcmNFv77kJS+p/DOEja2yltTB71nPetYq34xf+ozjzsHi6NEpZOZsZztbxVaf7f1ZX+ky6S9/+UsdT/2h+ZWvfGWVM8482q573etWXKyZjFb6grF+4IEHFu96ryXvm8twMq4CFfgkR3SMZ/KkDbg85SlPWey7tTHtq345k3Qlnfna1762CMTsssvIpDS+eDW+9P81rnGNShN92PSTdYcTYx0dH2fGtzLyQMbNEwERWMDP2MLC2kDOBemmzeO22iNTbAJBDHQYAw68sac/yb8NAOvwG9/4xsLBx+NXvvKVIuCtzHvG1FqHr2F/5oj2YGxcral0mzraetvb3lbtIzYThwfeytZCwid8rIPGDt2CymRY/jiN6tPVr371q+uc8KyOq3df97rXVX1Ax53jHOdQtCYTe4v9Y/wbgfTSyU52srq+0uvf/va3y5e//OVWvHi17lmnbnnLW1abjcMpMK8tssF+I29k5sQnPnENJAkSLjawQW6M+Wc+85ka5KRXBOzYYnAkI8c97nGLIKA58+c//7kcvGWjasi+YDL9av3QBhv94he/eN1shCUcbVbAco899ij8EHbPsI31ej/SvuuV+k73qiOQpBptjKpTnOIU5ZSnPGXdUTOpxonjTJpEdtv+7//+r5hMDGuTkiFr0lqolYnA2a0aN27G29zRZ87angs7YLvuums50YlOVPTL0Nja3uiOguFEWKBd1WV8J6m7lxwECpazwbi55CUvWZ3jC1/4wkWU0MKsjVFrO/9/BhNaYLRSazBlROy14HSqJ3BhIXVq4hvf+EY1GCk4ZQwSztK0cKZw8Q7Xk570pAWtmzdvXkYqxUoWfvzjHxe4WvTwpuLFLnaxMsTVjtxVr3pVRTNJSYoTAWTgJCc5SaWZs8EghdGw009/+tNF4GfPPfcs5MDJAbvLFmrBizOd6UyFPHAuGbjagf2wjVndw5QRbF6hDfZ23znkQxlMUi5ykYuU3Rac6F0X5B/PDEsOmCQo5Sqd6lSnqnMjWepUTpsH84fsDNuF/W1uc5vCmJVucpObLNvNw9ehC7uXdIVovHc2b95c68GCY2Cx3n1hp1jZZS5zmWpQcUjsMpI9YycoOex7Fvdo1Y8Ail2Dvffeuzq9+lJGruzeCRAx2MlQshR3ssQZYNiaM3QuXSb4Yt4zfunX4xznOEUdBqZdLe3rZ14J7eRnvD8nE5z+uNnNblaDTcY8SUlSnO4ij5s2baq40FtJljSBR3r28pe/fDGegpvytMtQZuSSbfJPt8FRUGFJIzN6OPzww4uTaozx1oU5KXgmWOi0iXlmbJSjW+CGLKD3/Oc/fxGUEIAZjhdjH8/w8S6eBZnpTg6icjoX5gJAjF1t62NW6cxnPnM9NUV30HfmkGACPgSbjTGHlI5HK92epJBXJ2Y44Ax079OZQzrJOEfe+CtnU5Blmwb4cqWvYaEOIVHqJwAAEABJREFUZ9HcGWI2bG8W98ZJoFTwLElBh11AQQe8WsPIdpNleKGDTqavBDE4a2STnHpHuYQPTg35ts60ceW4W6cFN+BBJ0ruzXvteX+1E5m3Flpf2EtwcKKQrJuf4/SRAzpt3333LXhVDgM7qeTeGqC9JFVPKF+LydiSySFtMBCws8ml3AkE69OwjnvjT5/DiIyzhZ16SVLoDeVsIvjYeXaa1Tzz7kZKSeqpHvOF/ShQCUM6wTP7GpbsBQEU9ZIsgYDN4lSHuUf+zBn2rrERYBQINWfoKvlsYrp0SSPr9GGXdUp3J3sNIUBJWagpHWQxSES92rM8ieND2ZtonpvBxxiz60ThmWTKLFQcOUY35S5vmilJ3TFg7DLqRe0oimEf+mWM2V2hbBleInvoxUeSusAkKT9c2N0XMaQolHGiTn3qU9fTCsM2p3GfjPpdqS04U2KMY3WSVDqcSuDUM5KSKCqUnAVkWgotGeEqeGMnlCHLUa6dDf4HIxF5kVSOMwPdzoP8JIu4era4WcySDFqY7m2SxT6bgSiIkGRJRwzoJNXpV0BmOE12ku0gWEDIfZJCzskPHtSddUpSjK3F3gIomWOM3fG+k9TdEMEcyU4KA1K9JNUhttNHNhgW8meZklT8h30wluGbpGZbiH0WUR8G/+Ocm3sW/CRVpo2BsWJ0k3EpSQ3eMSC19bWvfa2oh29zfdDkTG71QcbNQbgy9OxAuFdGxt/3vvcVBqzdLU6R/CExhy84jRwC+jZJxYyc0bkME/OeAZ2MyuBHHwzbmMd9ktpNMrrWh4X/WSvw6MSEnReJnC4UVV6MjU+y7LxzcOUPE30NLzzKN370nHxH9+npJLUtdcxleKk7q2SM8OCUi53otobpz9y3684ptSMt2OLK+TJeruonI5rJouC2dyVt401QijGfRHaVcfpc3Sb3yUj28ex0i3dr5Rn8L0nFOEldR+0ic7KT1IAmp5v+sA462kpHJilOBeHXOupTEafxyESSRSoFvYwZGyBJ7YeM07Eww1/DIkkxzvOWcbaKsWMLGHvjTPasVckIE5saThBwVgVhkpHj/+AHP7hwXu3ICvCQiSSL/Bs37ZKZJJV/PNJxZNxaPZz/dL75T0YWG1nFG/Q7MWAtTEb0o9GYwmpImmdBEPYiR2xYJkDUyswZuLEHh3XW0n2SZeQkozxrlACXYKOxG69Ins0FgRlYCHrZiU5SbHjRcXRDMppf1i+6fryd9f6cpJznPOep63KSullIjpqOwx/9YI2AowCmvGFKUudMMro6fSngmaS4h6N1MUm14+gT83bYxnq932W9Et7pXjsIJKnEUOQULmXjuynGVi3Y8j/Ke8vtkovF0IK/JHPhQb42F25n8h/j0XEcC43FlaE97EjfFKvFlKHGEBXR44QyLlpddDLUHZlkrODFrgWjykKrrrZafddZJv1Pah/+jJCVyibl70geXi1GePcZAmzkDdvimFjkGDN2HhwtZMQzgob17FQwbERkh/mzuken3SMGmEU2Gcl2628Sft6BrZ2yVq9dyYby9jzLK9njIDIKHOUVYHDkzAI5qV+7RHbzGImMCAuleuhlkFn8GFQ+nZC/GikZGcd2suxIcOiTpWMCezQP6fMsf9JcUEb+BAwZwXSWOTp8fxb3+rWLvHnz5uq0O3qrH8cs7VyRcbt8Alw+B6CbjI331HPFk6vnYSJnk3hVR9mkd5TNO3GE7KqY72TUJwJ2dxsdTihwzhhsjqiivZW5Tpp/8uEyiX98j7eh/jST9s01p8oEZTy3fhmLdhmd5MGbI8SCnHQefaFeslyeh/StxLN8aVi33cOj3c/yin4BQ3OIA6YvwTO77vBw3J7jQdbVtZY6gcKRpWPsSA7HTR20u2prmOQN6w7LVnpnWGea9xxUpw98QuBYvcCFQCq+9YNWpxbZABw58iGPjrYxcO1rX7sew4cL3abMey2tNK74H6/rHXmS+7WQyPY4HW1eDPPJB0ycjlTekjqC0XSF4Ic5JDjLplC2npJxsc6SBZ8d4HkS/QLYfkfD2mTdbqc7rQ3j9eGk3fH8jfCcjPQhvq2BNtvY0403c82a8YY3vKE4gdXyJ1214dSUU2xJ6m9cjNeDIzzH89fjc3fo1+OorVGaTQqRej9WIaqWjCZmI3dSXpJiJ9uxGvVMrnYV8Z7kVCmfRrIDYBfsrW99a7EQO9Y13i56GNoMEFcOKofPrkmry5ixU2KHQh7l49tVzqr29SN/J9LRerVFM9E+fNERJTsdwzz3SYoy99NIFmgOCYOc8daMmdY2uihaRpGjUej142xos2uqXF1XuzyOmCVLZUn5LBIZZjg4aTGpfbQmIyezlYv4GmPGvDx0t6tdh/HAlrJZpCRlr732qkf0HHE0puRSMCpZjp/dAt8rMx58+8mRQleScqMb3ag4QcHp8vkGXJStRmIcOmbqR7bohHEaGH70hPyGPczt/AkGyR8m81jZQQcdVH+AjnPFkR7WmdU9x8Pxf84PeefMOwY4DCig3acB5gYDtvGUpNipMb/G6cPTuA5tdRjLyfLxb+WrccWDEzB+MG24O+Jkgs8H7OrSH8Z+SN/4+DdszD14DusqS1J/U2KYP+17JwbswjM8HZ923JoOcWXEJ6NdJ/TZKXI6wZh7TpbqErSRTdeWxnlu+RwAOrQ9D6/GfPg8q3t6wbeqeDemw37IMfp8XmHHmezDxdppd14Q3Q42R1g73k1ST5ONt6VMMKjJuOdhouuS+ck4+nwCRHfQudYzssoGwLfytgZy0gQv8C+IKPAvYMWZ96kQPdT4x1OSepLIPRl2bYlsWG/ac7vSgXRDe17tq/k4ToMdVbi0fKf4/B6NnXcBL2uOoLL1yqZQq+cdp3XYAWytlr9eruRBUMc66oddBYLGx9Wz+UAfclTZjuxowbChzKuHbzbmWhpvNE0zmQ/mBrmwTsBQ+0nqj/3atGBjmzsNE+XDpA0BdPOu2QHsNHWG7wgy0lPy13vqDv16H8E1Qr8FzTervvOz6JhMJo3E4HFlxEpt10kE0mTjWDjWK1JNgalr4edUWcRnwSL6JG0zmBjQrS802blDh51aUXELjGeOA0XKGPOuPDuHFjD58igfxpaj5iLM2k2mZ2zoU9JXS3iBn/zNmzfX754Zk559w4hG31Zf6EIXKhZSC6cyjgScOZ6trZ25okPSNr6dZqAwk5Hh6tigMv0xQuCqvj4tUoI77tVxtNDVd4Ty5pEYZb671mcyGjPyYKcNLY5Jk4GGLSeYLJBrDqd89dUlwxZoBsk8aNcH2YOhBcp3qPA3v5LUfwatGURohDvaOJi+TcMXupW5GjeGFBlORljoYxZJf9Kwbc9occLDUV1GuzwJ7eaocvQra8Eg8q2cUcQYUM9pHHUFLugnDk+bo96H17DvWdwnoyO3TgLRc/qAPyNDsBPNEv7QyknnACapPw5KD6nntwLsUNC5xtO3pvSXcTLHBQG8b67hm2wmsx0/vAwTHjy3q3sJXY1H9MOdjKmnTB16QUCK/CWpn4bASx1jtXnz5sIx8ky34ZMOgxV9hmdl6jidwpHQ7qwSvW/33WcrkiAu3e96hjOcoTjVZRcbTZL65iiarT2+x5aPbtjgD62NZ8FmST0Y4ZdMG28BBCed7Oopc093tcCjdmaZyKR13O+FJKnH7/Eg4UnfdJLfjUhSnMgwvpxSusm/otHsAbrXzrR1wO9LCEaSETJubtNReBZ8wyd+YWHdk5dEd3NL+KJ3HN/lrPkld+OB78a/Oexf/SHLCHMqCt3WRjLAmbVj295ptpJ1mszgT32yTI7Ik/kPM3jBxmcI5r+TEfpY7USnCeSbi3BAv11S89waQ2bwCQMnVgTtrVWcXnkcNXrOe96HDZ7MgeaYeV5rqdE5pAv9+FBG7gVp6Xt1lJnHytlB7A76gMz4XNFcMOd9nmJ+k3PvfPGLXyx0urra2WgJj+Y+m5VDjz/4yYeVezpUmfmnXBksYeZZUtfJCKcPyaT5Kvgmv9kI1mK2AJvAO+s9dYd+vY/gGqDfZHKM0E4sg1nUzE69b1gtOiL0vvejpP1CrR/5oNTtiNuh4nCIQorAil5arA844IB6LJUSnAWLjnD5LMBuu++cLZ52GSgLTpoosXsGIRrtVlIY6Oe4cdQaXX4oTT0Ko+Ulqd8ByUumZ2igiRFL2aHdc1n4s3gyHEQ19en4uuNddr98p0qRMSD9eI/F33d93jFO+++/f/2Bt4Vmdvo/OzFw5NgyQsiCnQwNc0LQwRhBo1+jFpXGi11iQZF2NApfFi5jRBl7fx6JcUTBk8dkNG4cJMdH0cRwbLuHDG6/r+A3GNS3O4NWx9RFhpWRHbzOg3b0mW9+iM/Re06F73oZCPr3a9B2xNQjE34tnEzbKeIAOIViLPzTO47CMiYdb2N0JyMstDOLZJFl1JBX92hkrPp1X7+vwSC0G+ZXnY0RnWOO+lyGYcOYpk98siF6bydEME5Sj3xp24kEOHgnyUzmaFnhL0n95ybJF1o5K04H2ZVGj6AF+oyhfD+uJh8WHEZHezVNN5JJ84gRmKT+01jkzPi2eW/s6VTz3nvzSug1PvSTKzmSp39jYV7g3U68nUo80vmO1jLkGFt2cO3ecYQ4jI4o+wQEj3Y4OQHG0y9B++FHjj5H1g86WkPoHlj6NXhzUt+zSpwUONMRkiASfeDKOTUe5FeAEn++L/djT3jzewmOZjPc0crxhQe5Zsg3nukcTg9Mfc7EgebccSA5uo1nMuLHWOE0K36H7ZJVDkqS+t2qMjRwzsxFNgD8BSnQxNGz9uKDDNOTDHPv0aNkI0n9BXfrsrXYCQAGPMy0YW2zfhl/JyPgbPy1Ma9ErskwvSL4ZEMCXUmKtc8nJcYQj4IYbR1gJ5ABn++xgYyvOYFuedY7zq7AMVy8qz2OiX/1J0khL3inB+lG+tKc0MZaSEnqySdBezahdd9pBY6VQA75N08EQnx+QJY9s0vk+T0dc8Ma5XMveFir2Fxr2aHnTNooMZeNCZ3HhrEW0dXK2GfmZ5IaqDT25ok570QPnWXzQACLs0qu8U0ezAOyQDeSNfb0WhjvadJgXpFp+p2OsE6yuekMNro1wmewbGD1zLNkK5b8D7ijSR36iX9BbyQp7EsnH9g1xoOuMh5rWa7wsr2pO/Tbi1SvNxEBk8eiTQGZgI4S2lGza8TgSFLsnNiJMancczYYayLUJi4lL4lKMg4YaQx5itA7EzveyUyGvkWDcc8BYzBTqprlADlp4B5dIsYieI7bq2MXxrvKkxQGq8U3iayZJk44g1603vd7TYGh2Q+EwBRmDEwGEBzt2jEGRfAlmFss7CAxBPDqne0lfFv1jDkjltHp6BgjRGTeO5xG9676gydDnROCL2OAPnUlGDPQ1fU8j2RxFWgY9smY5KzrnzwwTBioFlWGGjlNUn+Zm3NmoeF8MtCMiffmkcxF35xxBo2rhWq46MOe08lb9mgAABAASURBVIMWO0AWRnPOIupIOz4F0MwNhgVeOAsciyEe3p924ryigzHjn8DCC4OV4TrUK4x8uxPKyS160cKoFojgFHGmOBTGKkkhXwwsxj9M7P7Nmh80jackhf7gBJAzOtBuG4MWPeROIMW8FHizm5OMdApDRDBJm3QpB86PKBlDwUZzThucW0d8Gf1wMteHc8r780hk3xpgfjOajJd+0WZ+0AtkUeLwGTM6VhBCfXLJwMeTXTvziIPgmfHPKKPbOLTWC041PuFCv9Al5ue89EeSxeAQWugLtEp2lY0pno2VTwkEWfAt2C2QQy6NnQCnfPOWIc/Q1MY+++xTOMPqDXmmIzlL5gHsyL21IRnJTZnhnzEVfOFsJFv7Y0Azpo0L54Zc40HiwJF78skpZ6zTRUnqv8pAxrXr1JNyGwXkSPAHJtrgBGlTG+QC3zCfIavLmkYjfWP+wZ++NRYqWlvZMdZpDgkc8Ih2/AnCsZHgYI76BEMZ+Tfv6S26WHCD3uLYskHwmqT+8KkgEWfXZoJ65r++10oiw4KvTh9wQDlkbD98CtzT3UlqEEieRDdaa7yLD3IuEGbukClBk1amfK0lzqWABEcRv+jDqzFmf1lT2WROGigjQ3Cgt4w5ORKEZxcJyhtX8xo2ZN1cg6l5IeghXzsbLfmRXo64E47miaCXeUE+6E2fAdLzZGW4RsLS2tjwEDCjK4YyAzP40i82AWw+CaIO67T31+O1O/TrcdTWEM1J6j9fw7mkgFoSWXbU0SLH8OJoJqk7wSYih8eCSJmVLX8MMYYcxcZom+UkYyAzFtBNEVuAk9EC4yguh5SSRRpn2YJtAeXMoSuJoprk2XWrDzP+H4fZrjqcYWjRS1L/aS/Gu4hukvoryI40NpoZQ4009xwoY2R3YzgGrc6OXmFl8UKbf5t3t912q4ZuMvqWlbFukUtSvwdmmKtrB6qNgb4pXs7AUEHLn3Uid5yMYT8cCUYZmuQztuykwJYskwf5SQqjzDiQLYGU9o7yWSd9CZbpm6OIzmSrnHKmGBRJCqeWoWWutUUvSTF+ZMO8YEgJVGl31rQ3mSbXgiT6ZMTBWF5LnFhGEwPeHGU8J6l6hbwwmugVfJSFv2T0rw1w6sm7QJe2F4pW7T96Du3kHvb0DBnitDXcOQDyEIlejh+DNkmdT05TcIbIJZ2QjMbZXNYO3Py4Hmc4GZWVOf0lKeZFGzPOCB507ztZPNqNpbtaPl7JmzLHkAXMkhHdnFpHcxnCSeqvmnOC8Uim8ahtiWPDKSYnHGRyIn+eyZonsIQn/eJRYMFpJc4ZAz8Z8WaOcujIrSu5TUb/vBue6XNtGFeBw8Zzq5eMvrcm33gmI/PiOUn9tGvoXCSjf3bKONJDAm14TEb8wsSJH1gwyunaJFWmOekCIcnoWQASTxzjNs/Lwh8stAEL+qxhsVA0t//woX9BGmPruXWOPkEGGJB9tJMB5cnosxsBVPPfmKuv3O69DYaGF1nmdMAALvSENtQVdOXUmzPWnGSEr/K1kJLR7/LY/CDHLRiBNp9Cmf/uW0pSf8cIT/jEo0AnewGW9GGytnhstLcrmabzjDvbK9mKgTxjaz4nIz7MU+vApk2bahNsHQE57ZB5NmWSGvRgG3Hq6XwBNPjUlzbY//AlYAHHlsgAe71hAEsnu8wB9UFAZmA51K3wY+ckUWUxWS/Ym+wf9l5rY7HCOr7ZZR3T3klfQwgkqYonGV2HpCUZPvb7KSCQpOI9habWWBNrk5wka5OwDURVkmUynYzyktF1A7E7kZUkE/PXY2aSZeO5LT6SbKu4l3UEOgIdgTWNQJKjpfPWNDOrSFwywjEZXVeRlHXVdXfo19VwdWI7Ah2BJQj0h45AR6Aj0BHoCHQEOgIdgY7AMRiB7tAfgwe/s94ROKYh0PntCHQEOgIdgY5AR6Aj0BHoCGwkBLpDv5FGs/PSEegITBOB3lZHoCPQEegIdAQ6Ah2BjkBHYE0j0B36NT08nbiOQEdg/SDQKe0IdAQ6Ah2BjkBHoCPQEegIzBeB7tDPF+/eW0egI9ARGCHQ/98R6Ah0BDoCHYGOQEegI9AR2EkEukO/kwD21zsCHYGOwDwQ6H10BDoCHYGOQEegI9AR6Ah0BMYR6A79OCL9uSPQEegIrH8EOgcdgY5AR6Aj0BHoCHQEOgLHAAS6Q38MGOTOYkegI9AR2DYCvbQj0BHoCHQEOgIdgY5AR2A9ItAd+vU4ap3mjkBHoCOwmgj0vjsCHYGOQEegI9AR6Ah0BNYEAt2hXxPD0InoCHQEOgIbF4HOWUegI9AR6Ah0BDoCHYGOwGwQ6A79bHDtrXYEOgIdgY7AjiHQ3+oIdAQ6Ah2BjkBHoCPQEdhOBLpDv51A9WodgY5AR6AjsBYR6DR1BDoCHYGOQEegI9AROOYi0B36Y+7Yd847Ah2BjsAxD4HOcUegI9AR6Ah0BDoCHYENhEB36DfQYHZWOgIdgY5AR2C6CPTWOgIdgY5AR6Aj0BHoCKxlBLpDv5ZHp9PWEegIdAQ6AusJgU5rR6Aj0BHoCHQEOgIdgbki0B36ucLdO+sIdAQ6Ah2BjkBDoF87Ah2BjkBHoCPQEegI7BwC3aHfOfz62x2BjkBHoCPQEZgPAr2XjkBHoCPQEegIdAQ6AmMIdId+DJD+2BHoCHQEOgIdgY2AQOehI9AR6Ah0BDoCHYGNj0B36Df+GHcOOwIdgY5AR6AjcFQI9PKOQEegI9AR6Ah0BNYhAt2hX4eDthZJ/te//lW+/e1vl8997nPlRz/6Ufnvf/87kcwjjzyy/OEPf6j1PvOZz5TPf/7z5Ygjjqh1tfHDH/6wfOELXyg/+9nPVmyjVp7i//T/rW99q/znP/+Z2Oq///3v8uMf/7jS9dOf/rT873//q/Xw8ve//7184xvfKF/+8pfLH//4xyKvFs7gf9r+5z//Wb75zW9W3A499NCCNvnj3cH/l7/8ZfniF79Yvv/97xfYtjrujRGcf/7zn88MZ3h+/etfL3/+859b14tXNP/jH/8oytH4i1/8YhE7ZYcffnj50pe+VL7yla8U9/IWX57BjfbJ72c/+9nSkjH929/+tqQ39Yw5usnub3/720V5IBee5X/ta18r6qm/pIEZP6DhN7/5zSJ2sJ9Eg3rkA63kiVypJ5GpH/zgB3WOknvjOGOyK4Zk0bxvfaGFrJqbxoS8r0QLfn71q19Vef/ud7+7TN7x0+RM3dbHal3R8Lvf/a7OZXLuudGCR1iQfTzDoZW1q7lDPpsO/f3vf1+LhvP+e9/73or6oVbe6f+t3AB+0PTVr351mX7BDzrpUjz85Cc/qXMfT3QpmTzssMOqPlZ3vBfv0hfG07iSkVbHfVtD1FG3lc3jil5zCfYwGPZpXBvP5FzdVo5Ocm4NaXnDq3L8NJ7NUe9L7uFAn6sz3u+wnWnd6wPO5mVLxg2P+qCzya8846u+fPRa/5UZazpS/nhS709/+lMhP3QpPSxPvSEW1jb8tzLl80roMI54NHbGvfWNX/Pb/JS+853vVB2nnL1BPowXXa2u/GHCD1nGn3p0W6unjF6HC3z++te/1vkzfH+179FoPsOFfoOFvHG65JF5ck0m/vKXv1Re5Bt/+U2+4EiWlI23sxaemzyYg40etBpHOLCNrbltHFuddlUXZuay+eNZmatnOMLIvTxlGzHB0TjDi20ynPv4Nn/oHuvLtvhX15xkw1hn2Gbqmy/mDtlaSS7VW4+pO/TrcdTWGM0mzqtf/eryuMc9rjz5yU8u173udct73/vexQVsSC5l9qpXvarc6173Kve5z33qOyaw/Le//e31fc7S7W53u2qca3v4/rTv9fvRj360XPWqV11meOpL/4ccckilixP8gAc8oDrw3qNY8PzWt761fOpTnyq3vvWtS1t48cTQYOBoQ1s7m7QD56c+9anlUY96VLne9a5X9C1/2LZnTs1973vfSutjH/vY8tKXvrSOB7q1gW4OrHFgbHhn2MbO3uvn4x//eNl7770rDZPae9vb3lY+9rGPlWc+85nl+te/fg3ioIPifdaznlWMyz3ucY/y6Ec/ejHoM6mdnc3Tp0VSXy94wQvKi170ovLCF76w3OxmN6vBhGH76j796U8vH/7whwsa73SnOy3KjcWYbCuD68Mf/vDFsjKHP7RxhB784AfX4Nq73/3uQgbwpmxIAkP0TW96U52n5hpejJk65uEHPvCB8trXvraOi4Vv/H31ppnIAcxe9rKXVYNO2/p84hOfWJ7whCfUdJ3rXKeQKfnKh8kC731y/9znPre8613vqtjj6Z3vfGd5znOeU8i5MVbH/JSmPUeHNK10r1+yfaMb3ahibCzUxRcZMhZ3u9vdqowZO2XDpB4DBb90qMQolo+3+9///nXOPf7xj6+yDIPh+/O4J4fm7VWucpWqd2qfC/9DIx6tE+iHA+dE/kEHHVTMrQMPPLDqNmMof+G1xf88cwT333//GgxR15zDo6SNJz3pSVX+733vexdy4Z3FBmZ8g4anPe1pxRi4153+Oa7oQtPBBx9cOCvKJOVfWQhcXuMa16hBNHnDpJzjZi7jfZznl7zkJcWaQJ/DZR48G0Nzk6588YtfXJ73vOct8sxhv8lNblI+/elPF4GpRzziEXUc4EH2H/KQh9Tg+Bve8IbiXh4ehzybl/TnJz/5yWL+PuhBD1oM8MAAvq5kzJhre/j+rO/1R5/AwPyFAz45EHhRbryMt/mJ15ZP9tX3vrIm/0OaYUKPPfvZz66yrC2OojbYFAcccEBdH9///veXBz7wgRWb4furfY9/Ovd1r3tdHeub3vSmRTAL/UPa1CO/9IB16373u1/V2+q8733vK+YM+YIXWfnQhz6kaE2mj3zkI+Uud7lLYV81AvH7lKc8paAbD7e5zW0Kh7KVj1/f+MY3VvvZ3PGuclf2CIyM+z3vec8iT9lGS/hibzzsYQ+r9tUNbnCDgmf6pvHK5r3xjW9c5b/ljV+1Y+2kQ9jsgkF0sHzrKxvNuLDfyOD4++v1uTv063Xk1gjdJoioo4WbYn75y19eLnWpS1VHwqI0TqZom4n2yle+shqsFNjxj3/86rBReBT6vvvuW+5617sWi6UFcryNaT2jXfTuNa95TTnpSU+6TEkqpwQsyhQIB/ra1752oZTxcOihhxYGhwX1jne8YznrWc9aOCQishZqOFjkp6UwGDnwsNCj+ZznPGeBIxqHmMD9+c9/fmFM3/KWtyyPfOQji2cBCYsqI+FeCwGVm9/85sVCC2fvDNvYmXu4MVIYLCLuK/F/nvOcp+y3336FYmWECop41zsMU7jDk/KVtzM0HdW7HCEOLhmElTG+0IUuVE596lMveZXxxljlGKKbkeVdlUTWBXUYX3e/+92LuSACrGweCc7ov/KVr1zH1VwyNz/4wQ8ukW0Yk1/zjKHMoX/9619fT1KQr3Od61x1XDiEMDjkkEOWvD8LXi596UvY9T3AAAAQAElEQVSXM5zhDHVHubVPJvbYY49CrzAMr3CFK1THpZW3q3lBntFqbO5whztUmTc29A2j33iawwJ3DCLyZF5c8pKXrFiZs629WV5hb6floQ99aDVWD1xwXq91rWuVXXbZpTq+jI03v/nNNchF/vfcc8+SZAlJaGXwmbeMXobemc985sX38WhuP+Yxjynmunm/pIE5PJzxjGcs5zvf+apeJ5etS/ecz3e84x2VNuN27nOfu56o+L//+79Ctwkk7b777oVhTB7bu670FOdxn332Kbe4xS0KHj3Ta3Q5/IyvYBxdLRjkHe/OOuHNXDn5yU9e0G2s9SnfWL3nPe+p44o+PCep84qx2gxOdb0zTPIEPcmvcTUvPZvb5ogAgvWGLidL5L31PWxnmvf0Gt0hAEpfoslcIsfkm/7fd999yzWvec1ChgX4jYO5LBBuXTL2b1sI6go8jtNrXRMc1wa8BPw4xbAwxoJ7sBCY9mz8p8nfUbWFB3rmale7WiFnaBRYYA/gxXiSYfaNAA5nNEk9yWfsOH50Ff1mvGAz7FNwxrjCyLjSj/SVtulqO/z0NjtJsOcVr3jF8PVVvUejgBXHi5NO917iEpco+BGMGBKHzyYL5IleoLfVsR7gi3yZ4zC4zGUus0wfqrsW0l577VVOdapTLQYk0GRzgt0oQEtOya8NK2WT0uUvf/lizYKhclenNMg6WeDosofY28o3WsKv9cocsQllrbDB4CRL45UdQI5g2fLGrzC06cXOEfDluFuTBJrNJ/YbnUX+9Kff8TbW43N36NfjqK0hmpOU4x3veIXxySA7znGOUxfxSSSagBZwyvnqV796ddjbQiYqxzCnEJPUoICFiuE9qa1p5NnVoiw4Psc+9rGXNWmSW4wZZ2c605nKsY51rMIQs+BYUC3WnpPUMgYNwwOfFtuLXOQihQLRTpnCH6woIxjD/M53vvPEVmFmh5UhlaQuMupbSOxqGCfBhySFI8CRtvBMbGwHMgUYGCkci2SpM9KaS1I49EmqE3fCE56wXPziF6+L9VnOcpYqU+oydjkGJzrRiTzOJCWpfZ/4xCeujpVO7A5yyhmonluyKDDUPBvn8573vBVDz+gUGHKPbjuwJzvZyTzOJaHHMTUOhQ7JKwOIQ++5pSQF3TBPUncMOAKeyYlAUTIaN7J7sYtdrI5Le38WVzgnoz5b+3QBYxkf5qdABdlv5a7osyCbj3hNRvKepOCbI+FdgRl9XOACF6i7hQyiy13ucvVkjuN9Fn7tzTKhleNhDjPQyL8x06ersePEMmTQK0/ZeHJ8Ux3yxVDUpjrmHX6NLczgt+uuu9YdPn2rM88E72TpmH7iE58ojHYBSXLa6MKr3RhjJcBr7k2ilaNIxzbdBif9fPvb367OEhmm05IUeoSDzfmc1Na08+hQcshRa23ji361zghKneIUp6hOfCu3tnDUGPLmXstvV/jY0cNzG1c8WwsY+tbIE5zgBGX33Xeva9DmzZtroNza5t3WzrSv9GBbE+EPZ/rPvTLBXA4dOuFPv3CC7U6bg9YgOt04mqfqNRoFrOzumh8wwZ91lmybpxyahgUZ1yfcZ8lvo61dBVPgb81IUk572tPW9YxDjxc8cUboL3PVOKPPLu45znGOcrrTna6uNWc/+9kLueAAt7bVc4wfbw1j42tNgqXdWnjAxVyhr51igFtrYzWvZF5ABu3Ghi667GUvWz8THKfRGOMzSQ3+CQC1Z0EA+kAbkmC6stXkbVt9J1m2TpqrxjhJfRUmxr8+jP0vybL3kxT1yVeSehLDOqjdsdc3xKNxFhgxr+gIvNJpQ+bUGT6P35s/z3jGM6oetEOvXF6Soi1jkKTq4Yte9KJ1IyGJaus+dYd+3Q/h6jPAibG4JKNJwmm0AzU+8ZIUhqzF3jEYxquJZ7KJaDPW2zsWql//+td150b5tLkUPLC4irBv2rRpmSLVn37xgiYLizw0WpwZbww1BnMyUgbuOQcMF8eEROFFmb03jQQTDmKSuhvHyGMoMXqG7TM00NBoTlLco81uMjqTEc0WW1hYLIdt7Og9Y4bxaveCEZKM+pnUXpJ6LFPwgzww8Fs92IusWuBvdatbVWO1lc3qmqTKAadBUOTCF75wNbrG+8MjA5bhLmiTpFZJUrxnV8HOlV2bWjCn/5HTs53tbMWOlwi1oAJZZXyOk5CkMI5FwgXZYJyM+FDXbif5xQ/j0XjIn2VKtvavn5Oc5CTFfEtSF18nYpyAUDZMovecHvMgSZWVJIWRb7eQjEtJynGPe9w6Ruav45xt/s+DP33YTde33UdOHPmGtTloF9f8tqvOmHV6ZZJjxnFy5N4JEKdC7M5y5t2b9wyhZISlew6/vssc/5JR/+Nd2jUxzzl2eLTDiEe6zTqSpOo2ODmCTlcN2zCmnAJ8yU9S3B922GH1t0KaDCSjfHgIwKq7NE3vCbbkz2kAQQnzsLVOV3DYd9ttt/p5maClIIy5p4xzSo9wypLJmOGZfGg3GdUhz3g25kOe5cNn0pxvNE3jmqTqSm3ZLROkF/hDIx1kt5pOh8cVr3jFwskn947jG2vvSe6t89rwLKnj+1hlyagfciDPN7X4w2cyKnNvbTMO3p9HEpjhdLAByBh9q1+OeZJiJxVf++yzT70X3ODo0mH0WhLVq34zd2FTMxb+hw86odlUyUiW6XKyoO6wDDYwU77w+qr/h37zl65NRnyikUyS+XEC8e90HN1w29vedlGuktR77QmQcIwF7MbfXyvPSSaSgn7BWrYah9J8nVhxS2ayvB0yxq5yioG+SJbX2fL6ur8IViSpa77Au3XBfMNYkioT7ldK5oLgF7vF6Vl6yadc7CHv0DU+gXByRPAgGfWlbL2nXdY7A53+tYMAxUU5W9Qt5K5D6pJUY9uCxjD3bbdjLxbqMsc/dIr2W2QoWBPcQiNZdLeHFG2sVE+ZBddxQDtSTh/IW6n+0c3XFmPOe46WjuMsf7USg4MhJgrKCIWnBNtJNDF67NgIADEC1W318MkYZADj13Mrm9VVH4zDbRnYaMQPujkmTkM0eiwa+CfjFnDBlVY26ys54CAJQvkExC4Jh8FR9El9c9Y5kAxixx4ZXK2eoIbjoE514LHlr8bVmDBiOU2c4CQ7TYY5Tz7tdtn14iDvdKNH0QA+OCR2FwVLyI2gkZ1288CunFMGDFsOgO+qfdZB1oZNGy+BDrtedv8cGxQQHdZZi/dkimHr6Cy9j0eBMcfszSk0w8iJCwHIG97whkdpvHlnLmkbnRgfBqRjnXadyRZ+5AtW4JnhaD3guHB2HCPGJ0w4KmRR/Za20d2aKsInHcFhP/3pT19pM4aC5PS2OeuotQCG/FphG/9rddp1G1WXFSU7rxeWNbpCBsfSpyHmMF1rc4IOEcyghwWZOLQcCp+FcMbIxSS+kuV0T6q3AinrPpuzSp85tWDDx6mTIVMCOD6989tMsB2WrZd7PHAsBft9UnV06fY+vW+eWTvoFHPv6LazHuonIwebLWV989kGm2p7aDdv+BOSTx18gugzH7YQm18bdKx6HH5rLX3sWdl6T92hX+8juEboNyFEqe24i3xZzJLRQqVsnEzK6UpXulJ18CkrxyPbRFOXkrerQdEno3bkTyNxZBjyFCOnhYHJEXX8xqLc6E1SGCmem/K0KAsEiCI6tu5ZObrwYVeaUWcBooycAhju4qq3s0kknvGPfoGDZCk+cLPwwVNf6EOno6inOc1p6hF3ecrUURfdnncmadNulJ1px8QYN2gVUUbveNvqW6R9R8zAt9vBsFUvSbFrbOfHrpZxkT/rZJw5GY4CDvtCa3smk2TXjhz6fdvZysiFb10dKU5Sf8W/lc36mqR+EmLhsnvLWfSNrV2iZKmMoIVxILD2lre8pf5Il0CG/CTFUVi/Y2AhFJSCi7J5J7hzBsiBHWuG9DgNdsroG7KjfqPV3BZYkteSOuqb135QyoLve3Sfh4y3O4tnuoN+OOUpT1kYKXvvvXexayeowAmwE4FHRywF6wQA6MJJtJi35pmdbvOszfvGv3fMe0HLZPn4K59nMm/wiHd6i/z5/MCJLXQaI0acUxV0CHySpXTTX0nqLj7avUOHWT/MPeMrT5JvnSED6s4qodm65zdLOOcCNn68kcEoEIUGPOMHz4JnxpUxacdN8JCudNLk9re/fSGX6G/0Np6HeXgb51l9Y08u9JMsxU75tJP+/DaAYIZ+0cjB96N1vvnFi3XREXpybZ56bnSQW8eoyUXLU88uprFsed4RfCTLrR9l+oOFtc3zvBIarOt496Ntxtbcti4kI9yT1B14441HtJrfeHaPVjwKXpm7nuUnKeRFmWf5eCRH5EtfyuRLsNm0aVPVJ55XOyUpZNqcbrSgkcPexrnxpdy4WqM4XmTdZwvyW7IuJam/UZSMsG1l6+FKVgRq2TkC7j6xGPK/PTxYs2wQmEd+42YjOaGT+IcPHq2BTqTBcFK9SXlkzFrjdCw9Qh+7Z9epb57S1U7oufoEjB5Ttt7TLuudgU7/2kDAImUCWrwsLiaISSk5huZZsjC5yrcr5dfNGa92MOSLrCnjCJ///OcvjN9pc8iYdNTYD0pxfjgtDAUR97YQ2TlBh294KAiLCto5lpxfCytefc+qnjL844PysfhaqL3reRo86AeWHDDGBGxgJt+VU+DeoihI0WhzvNfJCQsBJ0/gBT/qOrJpp8+Y7SyNSeqxUpi2xICjOBm3+kMLrNy76jNJ4Xw5igsrvEjKPDPI8eR51gk2jFCyl4yMB4YJpxLN6EK3e2PMcCYL6JKv3D2ji7PFMPM8z5Sk/osBHHK/DwH7ZPStvB0ztAxpZUCjlTzhC7+u6jFAzYlkhIW8WST9ScO2PaPT8TiODkzhK9/VHEWrwJpkl1qZI9bGhnHNUOQQc5a8459Awg/jkmyZo5L7Yd+zuE9SzFv/ZA560Gpekm86xY6CMsa6Mru7HD30qYcPdMFEUoe8mmPmO6fBXPZZDVzMNe8Y22S244euYUKb53Z1z5BycoteajzSZ8bOeLm3g20niyFmvLzvyjF2b62AoTY8G2tYmIMCf9YPnw8pE6Slv52W0f+sErm089Z0nk9YnIqxK2tdcQLDuOIDXY6EopeBv+Wd+q9NmGvy/BYLWvHsnd12263Q221cnaSBF5mBBTlxNNWYC+D5jMSc1sask3E0D2FvDuHPiRHrnr7RKfBs19U4+N0XJ0+MmfF2ek1Qy7tkWXtod/TaSSN2hfbh5/MU81ZfDQsyrk/BjWS+Mo4/dDuFJYBqkwAd6DFukntjwykxT+kkAQ/zXzmsBK7x7LmtM4J0PpUx1sbVOs1WIiPqa4NOoM/hJLDcMEfXaiaY+OSOjWGcJScZ8ESXGVNjj0Zlknv40HfmuGcJfsZe4C+Z//iiYXsTWsfrGlP8KUtSfzvB+qOeMrKt3HNL6g7v1Wt1OKqCV+yOZG3j0Xg4ulf8ss3ZpHSc575FDwAAEABJREFUZwkuLWnTvaukHJb0B5uLnvBJqjrmj3Ly5wpL+eaLtdecTTYGlrsAo6eOwI4iYGLY8fYdp19fdZTQ92N+6du/n0p52/2ycFnEGDgisRYr30XZ2dC3CCSD1vE0EVpOIEOAEah8momRQVFQrBxJiwijjJHFkLRjZLceb5SD4+B2YRkirn7shnFiF5fiYMwx4hyDshttQUtSj4smmQrpaGHwOMLHcbErAGe4Mxjs8vmRL1FI/IkEOyVg95GRyJDGM+UFZ7vLdpHU8QNU3pkGoRQkXCXYWsCNOYOFUce5dGV0kwsLvR05O9p+eZSSdQR33333rT+iI0giAHPBC16w4jkNGrfVhjH0rxNYTJLR2DFMGNTGgAEOZ0fZBXcYXI6EadMnJGSW/PiRIguvusrmkdBnXvntATtmfgWcHDAC9C/P8VD1yJHdQfPSjztyQIyNOUo+nC7hNDke6MQNmdbGrBJHhNEKO4E+NApQMeQcZ/ZdOXnHDwPPomyOesfchb3dMjoH7eoJAtm1ZVySL/MGP+YDmUpSZSrJrNha0m6S4hOSvfbaq/6rE3ilN5wSEEyhZzhxAkp+jNOJFTvV5qbvkf1KMlyMj3nPYRXcM3/pT2Pkx0nNabz6FzacFjHvlxAy4wc0clrbOHG+5OmWfqerBGnw6eQOmeScCD6ZUxwjY40XMmCMObnWBVhwCp3YoNv86BGH2YkL+kYAx2cKdJudMDrFO/qeVdK+oASdJ6HDeAikWE/8QCj5FqS25tExZHKoK73HoZFnbcEzA5QMGFdjLAhtXB/84AfXX/gn397j6FkvnaSxPgnkJfORaQ6lQGwy6i9JEVwSZCCHxh7Pjt/T7XQOnWnszFPBGz+Qm6Sgm/1AVow9mYCZ9RWW1jBYGFPjDwtzho4w/rMa30ntcgzMX3SQP/QKTCSjH3ml960RbAafHNDFaIeNeuY8GSX/dLEyc9mOpHXeeueX/H37q565QgckKeSfzHF6bEKQA+1PonM18pIUcmzNZOuhk24m82TA5wkCUWiz1tsYYRPQCWSfPCuT4GxNsz55XsuJPvZpoNM39Dg5JqNknD0gX6KXk9Rfw7eGWXPxZU0TqHHiR5DGqQb55hFMrG1kAYY+TUhGc06djZKMN36tATCDlXWBjYJHmJIVPof5R0fI9x4sYcTW9BtW3ufUC6zSk9ZN94K88tUVQHOSyPzTznpP3aFf7yO4Bug3KRhcjq/YBWbQUGImEeXjGLYjL37cwnfSnHRRbYsXhw8LFiiOA4eYg2ohsNuUzEZpJanGvInsyBcFgFa0MA4spO6TFMqUMkAzx4Hi8B5jjSHlfe9SFt5N4tWpJ0qMkWcxhDN8RfwZVHbnGMuOFyUpDAJOuwXG7qYAC5olxyEZAAwr30cPd6N3lugkFdck9QflHBFj7JaFPw4up4SDIQrPMLPwidYzetVDH0OG0eOHgShnzhmsF5qY+X8CNI6hJ1nsS1CnBZ7sDjE87QwxZi02xl5li6xvvDklIuiwJdfK5pXMHZgx/s2nRpv+OQWSe2V77rlnYTjYPWIswn7Tpk2Fs8i5IDu+YyZzyVY8vD/tZJE2z+zCMeC0b7HmoHGCm7zDl9wnKeYoYzZJYfCRd44Tmhn5sE9SBIf8UzewIY/4xqs+5pmS1GOxjBX6kpyQbfPPOG1awN78YNAx6gVmzJNkxIMjl+g1z+kA+shRTvoWP0nqvPettiCUMW7j6r15JkEZfMHbHGeI6Z+uMm4cPgarHXk70HQbXvwuRRtrAT+OsTH2SY78ZPQvUuCRfMKPTONfEgjg+OmfY99kRd+zTEkW9Z4AGgeP/KHJ+mA+Ck7YLRJUEmhSlmx9z48iChInqb+aTp7Rrx5sjLtxxTMHWb4+rF3mCZ6tR95JspXdGd/ZHU5G/SWpu5CceHpTsJY+tZajVYKFuWgeCkzjA4l+HNXpgiT1R1zNBXJh3TBnzJEkhT6yDsNCkBLWrQ3tzCtx1jdv3lx/hNTcRJ++8SjQYI2gw4yJoGOSuiZyYvFgXsBi08K8T1L/ZR9rC/tIG+SB88HhI8vWlGSEjQAnB9Dc8AOsre+yRv6Mh7nIHjLPBcJtJiQpApp0AFLJjmQdggOe8a5MSkb1yVIykjH5/8/eXcDJdlN/AM+vf6R48eIt7hR3KO5Q3OHhDsWLt7i7a3F391fc3bXFneIO//1mXnbvzpt9OjMrzX6a3nuT3OScX05OzjnJnbcWE3lgV7GD2VZoFCSHAxvH/BTwF7xVlozWMDrOsyQQStcZV6er5PlxULay4Bg5YivBKFnbeKB9VxJ9yd6GHV3GlrXuaytJgS1HnzyxwVo+mbI555mNbl44wSVIZAzMEXqU/rShZDffZgxZTTYGlt2hN/o97TICSeo/+yDK6ihYSxxzjgWHvRlmnATGubquJm6yNJHsmpm4dpUYb5TWLhO2Ey/ql9I04ZMUgQcOpWfNoJtBwklgcFEA8pMUBqoFSWKYJkv8qDOtlKRQ8g1fVzgyJDi7sGbUoSdJ/eVnBrWFgPPASGi0qG9RNUYUZuOzlU/zCjPGa5Ji4UIPfI0tx90CKCghLxlhJ/jDOSYHDB+LWDIqmyZtk9qCByNkWGYB5mgad/gaa3TbhbFYJCPaGJ5oxiPHBI/JqGzY3qzuk5GxyzHGh7k37EswAp5JivllbOwuWTjxlqT+CjzZwJ85YSyS2fPACSfTEmc1Ge3ykAN5LcGXw0RmzVFGIB5hLZiFJ7tg5qz8ZORE0zfetdOHV2WrlegbjguM6RO0owVdjHbz0lw235NUJ0DAAu1J6j+P5V0yKTjW3i8Lf3ARoCGDTprAIZn9+C10vfhfMqKxjRns8aaCKycIff5JL4FIeQIXrb4r3Ub+0G/+kem2XpBr80sbZHpctwneGGuBDnjod54JfRwxfOnX1TiR5cZzsvWY4LHpHjLi2RFrbeBjyDNcktQgAv5hjGcyMpQH784ycbScbEuy2E2SGpBAPzklu42mZPRPRxk7jo+x9SKMzPtmkCepgQE82cE3z5NRH7AQDNAGfdaw0M68EnrpmpXmIJuHDJuD4+uXZ7qL7iUX2kpG67u1kPwkqf90K4xgINg9xJBuoDP13+bFvHjfkX6SFGNmjScHAuXJaPw4Yua2dsg7PsgJJ4xuT0b1lMOG3Btjz7uY5vIaeWy6iw5OUtgHMCALxtZ8Tkb8kWNyYK4j0PjSEQJg6ns3SWFXkhUY0XfsN/U3YjLe7Cs4toRv60SSqu88K3OVDwfYwZI+SlJ/m4sNZI5aa2GpbfiTR+9y7tmkScpG+dtjozDS+egIdAQ6Ah2BjkBHoCPQEegIdAQ6AruGQH+rI7A+EegO/foct051R6Aj0BHoCHQEOgIdgY5AR6AjsFoI9H47AmsEge7Qr5GB6GR0BDoCHYGOQEegI9AR6Ah0BDoCGxOBzlVHYFYIdId+Vsj2djsCHYGOQEegI9AR6Ah0BDoCHYGOwM4j0N/oCOwwAt2h32GoesWOQEegI9AR6Ah0BDoCHYGOQEegI7DWEOj0HJUR6A79UXn0O+8dgY5AR6Aj0BHoCHQEOgIdgY7AUQuBzu2GQqA79BtqODszHYGOQEegI9AR6Ah0BDoCHYGOQEdgegj0ltY2At2hX9vj06nrCHQEOgIdgY5AR6Aj0BHoCHQEOgLrBYFO55wR6A79nAHv3XUEOgIdgY5AR6Aj0BHoCHQEOgIdgY4ABHraXQS6Q7+7CPb3OwIdgY5AR6Aj0BHoCHQEOgIdgY5AR2D2CPQetkKgO/RbQdIzOgIdgY5AR6Aj0BHoCHQEOgIdgY5AR2C9I3BUoL879EeFUe48dgQ6Ah2BjkBHoCPQEegIdAQ6Ah2BjsC2EFiXZd2hX5fD1onuCHQEOgIdgY5AR6Aj0BHoCHQEOgIdgdVDYG303B36tTEOnYqOQEegI9AR6Ah0BDoCHYGOQEegI9AR2KgIzIiv7tDPCNjebEegI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BHYFgR19pzv0O4pUr9cR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCHYE1hMAWh34NUdRJ6Qh0BDoCHYGOQEegI9AR6Ah0BDoCHYGOQEdguwjsmkO/3WZ7hY5AR6Aj0BHoCHQEOgIdgY5AR6Aj0BHoCHQEZonAXBz6aTDwv//9r/z3v/8trrvSnvda2pX3+zsdgY5AR6Aj0BHoCHQEOgIdgY5AR6Aj0BFYSwisRYd+Ij6c8X//+9/lP//5z0479d713r/+9a+dfnciMT2zI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCq4zAVBx6DvPnP//58shHPrI84QlPKL/+9a+XsaX85z//eTnkkEPKYx7zmPK9731vWfmOPPz0pz8tN7/5zcsDHvCAMad8+dt28Tnv+lTi+Ytf/GK5/e1vX254wxuWww47THZPU0YA3r///e/Lu971rvKtb31rxTFS79vf/naVlYc//OHlUY96VPnDH/5QqfnLX/5S3vrWt5bHPe5xdZyMYy2Y4f/Q88c//rG88IUvLAI+k7r6+9//Xt75zneWxz72seXDH/5wPSminnd/85vflBe84AXlKU95Svnud7+7It/q727SH4xf/OIX13n0/ve/v6BN/njbf/rTn8orXvGKRZoblur+6Ec/Kk9/+tPLU5/61PLNb35zkZ/xNnbnWT//+Mc/ynOf+9yiv5XaUu+Xv/xledOb3lQe//jHl7/+9a8F7U960pPKIx7xiMVETtRdqZ3dzdf2L37xi/KiF72oYvvGN76x0iJ/vO1//vOf5d3vfnet96EPfagGGVsd8kCWnvzkJ1d5oH9a2ayuaCTDb3nLW8o3vvGNZd2YU294wxsqtp/+9KeX0bqs4sIDWn/84x+XV7/61eVpT3ta1ePmJllpY0HHv/71r5+6zJDPj33sY+UjH/nIAiWj//CF/pe97GVVX7zvfe8rZGpUuvz/6qEbfeaoMVJDG3jCgzH5zne+M9M5qs8dSfj92te+Vsxl+s5zew/NX/jCF6qucd/y21Xdj370o3Vuv/KVryx//vOfa5G65o48bX7wgx+c+jjVjnbgf2TJOkCO0Dt8xXxnBzT9/4Mf/GBYXMf40EMPLd///vcnjpWx/cQnPlFtjTZPWwPkwDzQvjor6fRWf9pXY2DOmHMwGLav7FOf+lQxdi3feL3uda+r6+Db3va28re//a0VLV69p02Y0JFsmNa26xFHHFF1OaytreovvjyjG2P65je/eVE/0w+PfvSjl62h6nzlK1+pOpU8ekaveUyfG7uV5rO6mzdvrjrWvLYuYAVvdB2dAAt1tKls3skGE32Fb2NjLNGAxl/96lflWc96VlFmvK3TrYydQBc94xnPKMZOfWXDhKcf/vCH1a6gu9jMrZ4yupI9Yo2Hx/DdtXCPVrbKS17ykmItty7JG6cNL3SysYQHO189Cf/8CbIl0RdsHu+Mt7MWnsnD5gWZ/eIZmesAABAASURBVPjHP75IDj7oZ3oeD9am7ekksm9usSU0hF/vW9u04cquWovjjt7dTfBhV+GT/JhLcJTogVe96lXVHuBrTNKX+ofhl7/85fLEJz6xvPzlLy9DrMzFd7zjHXX9HOpS7633NBWHHgjnOte5qgFsYlJS8loyQFe+8pWLhevud7972XfffVvRDl9PcYpTlOMd73jl2te+9jbfIQiXuMQligCCivq+3/3uVw466KBCEC55yUvK7mnKCDCyXvva15ZNmzYVhpzJN6kLyokcfOYznymf+9znisl6/OMfvzoaz3ve88p73/veOsZ3uctdynve856JBt2kdnc1D50Mqfvc5z4TjV/lDA8O/a1vfetlwQbK5M53vnPZc889y0UucpFyhStcoViE8Ei5M1bInzZ2lb7he9rhhH/961+vhsCNbnSjajTob7weB/nYxz52OdaxjlVuetObls9+9rO1yu9+97vqZJ/jHOconAZBMmNQC6f4P7S+5S1vqQG4n/zkJxNbVodxf41rXKOYt9e61rXKMY95zCIA99WvfrXiCtvf/va3hfMzsZEpZaLlnve8Z4HZne50p2JRZnSOY2uhsJAw2O9whztUxxft3rdQ3Pe+9y1JyqUudalCD63klEyJ7MVmBJXoVgGalkkGLYiCrWRFOacera1Ou+ILz5e97GULA+ua17xmOeEJT1hx/9KXvlTHwtiQecZZe29aV7rjgQ984DInFva3uc1tCseMcXODG9ygkKlx+j0fshAsJutovtnNblaGjo016axnPWvhOArqaleCT5ujnsuc/vTL6b7MZS5THbi73e1uVWZa98rvda97FQ55yxteOYUMEWsux1VbjX7z3pyR4EDHwmf4/jzuzdeHPOQhNYhPtlqf6OTQkTW0SSc5yUlacdXBnCRr9qS54/1PfvKT5cEPfnBdJ8iDeaoPZeRA+3Se4D+HUv5iBzO+0dc97nGPYt65H3bXxhV/8j1zwtkqt73tbcvzn//86sDJVz5M1swTn/jEdT00DxirxtXmyTOf+cxCFjh5Ni44UsN3Z3HPsIYznUDWkhQ0tb6se4ceemgh4+5hooxDY/0697nPXciH8cOHsmEiH8YZX5wY+qHhKaB4ghOcoPzf//1fodesF5PaGLY37XvyRpcKLNCrHNHrXe96RUDJ+HFGrG308dWudrVq+6Lx8MMPL5z5c57znOXtb397YXdYN8bpIxPWevxzYvXRAgbmvzVHmUAJh6VhM97Oaj2jhz6nX60pEizkD2mCCTm5wAUuUNdc+hl+6pAVGJIvckanwyCJ4jWXjMP973//ul414vBrvpJRc5X/8oEPfKAVb3VVH070F1sNPmSLDXq0ox2t2kdHP/rRC4c/WZs4bMXUTmTgFz6CO+TgoQ99aLnVrW5Vg9bKDjzwwGor0nE3uclN6qaV/PEurD98kQMOOKAI6NOR2oMvXcLP2LRpUw0MCLiZz+NtrMfnqTj0SWpkloLl2BHcBgZl/tKXvrSWU3gmp3qtfPwKcOBK7oeDZXKf5SxnqcaPfHVa8qz+pS996brLs/fee9fdS4vG6U53urLPPvtUo3SPPfaozqP31JfcS+4lbaHLvfyWPLcy5T0tIXCMYxyjmCCwWgkj+XZBKWaGBwUoepukTli78w960IPKmc50pmICinBbIJd6me6d8WRcoWefBflA37AHz+i1OOONQSXQwADnBFPS6GNUWJAoHo6VBZoxefDBB5eDF5J+hu3u6r3F7GxnO1sRmXci4I53vGN1gDhZwzbRffGLX7xwkOF8hjOcoQigqGNRsOjsv//+hcFgruJF2bSS/jnxjD7yMIl/dRiAl1lwahgrjJwzn/nMxfwU8BPcufe97104NgwXynta9E1qRxRdgOOCF7xgOe5xj1sEGRhO6BzWJw/G1ljvtddehVMvAABD/FiEOVLnP//5C1nBx3gbw/amdS8wg54h1hYycwytpz71qctd73rXYn4No9X6Rx9e6crnPOc5tY75YCwE2+QZBwGPE53oRDV45b1pJkYP7MlLa9dOlrlGD9ip4eQxoFt5u5L/AxcWemNG3sm+HS3lxsUcvNzlLlfImflqDOGEJ3jom6yqP+sEa2Ni15HDYg4LRMBaGfrM7wtd6ELVuZ1ED2eGDF7pSlcq+Ob8eFfdi170ooURIxByxjOesQbyWpnyeSUBQ44MnIf944/jaY7QlZwzgXp0qUcfCQizEzzLHybyYW0gC6c//enr7p/TMoI1HEU7L7Ah77DhDHpn2Mas7vXDQb3xjW9cbYxGvyvdLdhwnvOcZ3Fc6QrBqlve8pblZCc7WaGPGeoCmOM0coiuetWrFgFkmxvWHu1adxm99ChcyLt2lY23Mc1na5wd06ajOSBssybHbD68CCbe7na3q46IMvqDc3+Vq1ylnrjkrE6iiy4zxlde2AjCM6O78cTGu/rVr15PXZ7mNKcp+mhlk9qaRR45NneNtSCwgAy5tQkBf/QZFzLOSSXz5INc23E3nvQAPcXpHaeRAytYp55Az89+9rN6ck0985/eMv8FBMiQeaZsLSRjIRjHrtq0aVMNNhlLNgunakgjvpQZU/rZhojgrToC4nQhPW3tYcef97znrfa/8rWW6DS2inFutNmYeNjDHlbnNluXrbCSTQA3ekxQ1th61o71mp60WQCH0572tDVQRu6Ub7RkPXfyRNDWZpsgGJmwUUzPwI9csMsFOhtODQdrubl3i1vcolgjjIvgGSff2i8IRi5PetKTVpuIPtJ+e389X6fi0AMAiCLtpzzlKQunXp5kN8cCJeJ4sYtdbJuTkVKiCDjjksXRYMlnbFNkxznOcTRbKAbKzEJoN+nII4+sUSuLnUGn5C3qlKdFnrLVjsjmyU9+8iJx5hxd0RdlglaRU0EI/Rr8/RccH3kmIgUznKyVkOX/O8o+Jaljm2RFDGBqAorAMaIZnQ1PC57FzkKepDBoKUOGkPdWbHQ3CgSI7D6ig6M73pR+GRLkhiwxSDidjCaLFYOFgy1fkOp85ztfjTK750SIAuJBO+Nt78oz5+r6179+EaG14DPc9Z0sx1weY96V4aGuoIM+zSEpSRH5ZXhz+JVNKxkzzqMAHhomtWvcOWl2sq9znetU2YFTksJIQ7N35YnGXvjCF651JrU1jTxOPOVvN5cus4DaPUPDsH1OmAUHZknqaSPHYUXVRX61QZaSFA4qvYXXYRuzuB+nUx+MSwY/Han87Gc/exFoMe5wVUci35s2bSrG65KXvGRpZd5hoBgLMi3fyYRZjIW+kuVybK5xUPVN5gXNmvOH7pYYNtYdbcjjIKubpOp5gbgkdTfcDgl9n6SYo4IGjCjzxLuzTPAjJ4wyeDPMYN/6VM6YM8fN35Y/frUeNV45D5wJz0kKzNyTUZhxOJLluI63N4vnJHW+JlnWPOfDGuy0E/3FLlAB72gWBLM2WAvkjyf80tnwSVLoMuNNz8q3rktJCp1t/nEaxtuZxbN5RVexc4bt442BKvgnUNbK2CR0jfFKUvWeMvR6x72UpNA36gk8woYcJ6mnaNqcMLftfJOrZDnu2plmYgxL5qZkt14gDY0MZzJujM3LJuNJCodMHfzhRb1ka1rxoR6aYcp59pykGHv35izdZL4kW7fh3VkltqFEv+pDoALNZND95S9/+WIdMFbmoPskhX1qXiYpnNf999+/NJtWOy2xpek1zz5Zo8/occ/WbPy754jA2Rh4XgvJeAtYkkN0oZU9Zy4OfQO0WuvZfO7NbcEbcpWMdBncWhtwMLfVXYsJn8lyOSQTeMeDcTeObVzHeWAn0I30BLlKUnWo8faONrwjECSArz/PGyklqRtR+DX28KP7khQBHfYJHBqWTuQN+adXzEt+JH8NRtYI89Ap28MOO6xiSi8ps16qzwYYtrNe76fi0JvAJitjloNDychjvIjUyjcI2zIECbOIpMgLx1q0XcSac6Atu0SieAZSVFPk0uDahTL4lD4DQRRbdNQOGYedEeu4sau27QJb+A5c2NFhPDEeRL4oCgaw6L7BVGZXUITV0Uf82S0iBMqnk45arSQpomEmj8nVFLhJSFagkcSlTjqOksBNzZjy/xhSon/Xve5169G9Sc2jy6I7XibgI2pKRpMRveokKWSfzAoQcQopY2XTSEkWaUWDT0jsfjBoy9ifOeO7K4YfBwa9rYq5Rs7NF0aYtlrZ7l4t2OaYQBkneaX20Ld58+bCORF0M2ftEI/vVpjXFG5b9Fdqb3fzk9RTIRwDeoXh6Zh2sjS++hAlJhfJUj48BRQd71UnGZUlKWQcr/LnnRydH6fVzhrZb7SgjZNlrjGQ6WDGqBMTHKxWz9ViSO9aIJMRj/JnlehaSfswti4IFHkeT/iksxnIZMazpB7efMvKCCKTZMx8EOTCr/nR6qo/qwRrGDJUBLnJu51Ku5T0HH1ifeOwJNvGV12Ba46idqVGt3lPr1nTyOU8eGt9b+/qsyS6nswx+I1Jo9GnLHZPtiVf9DF+khE+yegqyGpdT0bP6EhSg1Ow9jyrhB59s3XYE8kSDcaFXiBjjMhkqcxuvbWC3eEqSExWV9LHz372s4txtRNOfvWLJ32wYQRGOQx0cCtTPsukH/rEJwZ0JlrYSxxtetsuGxl3fNocVt/Y27U2Fzj18ibRyDnmDAuc40nbrZ5dOlgIkMBspTZa/WlfBYusXY5CGzvjj188JqknzcrCH7rNR/yygRey6mYUO8gJOmM55Et5S/LtTlvDOTZDuTCHzB24J1k89dHeXc2rsXCCJFmSdfSY53hyP0xwY484OciZh9mwHKaC5ex/cjUsW+v31q9khAM+BPHwmYzyGv3Gli5nLwoItfzxq91qMiMwlCxvY7zuen02T5KRTDv1yJG3lsFSwhcsBQ6dPkyW40A3mpPJKD8ZXQVc+R7eT0Z5SeoGND0kf72nqTj0wDXhKHQOvag7w9HOOEOKM0wxM8qTEZBD4CgAgupYhGM5dlTUtYNK0E14kSsTmkJwtIwjw3mXzxiiCChV3+Qx6rRvgeTIEwaLh4XTUSXH+tBGGERHOZf65IRx4kXIHZNRx/HvJkQWkGRr+vU1l7TOO0lSFzoBGGPpOKQF0biVsT8yISuZPt7aZnwJMImEW0DIkES+9Lu9lEymK0mNzDMw7T6bF46E6nN7be5oORotDPvtt18xB5KtaUlSfwTS0SMBLYaVuaSPJMVRSUfd7JKbG9Oiz0JuLpq/HCe6QYKtvltCv8XZcSi0CH4ceuih9XunIS2cNHpFxLq9O6srR9BJHCc26AknSWC9I/0lW49B4yPZumxH2pxWnUZHay9ZTo/TTHZ/6D58032CLAIC7R3jRz/bWU6Wv9/qzOqKfjoCDU49JJP75ziQd9F53+C1sbODSbfbyeIU0et0EHo5mILCTtN4nnUi93Zs4Ej/ccI45gwNBp1j6vg0V80bV/yP02VnAa+cQm0xYlodzoNggbnDkWsDAAAQAElEQVTIUKbfWtlqX62lAhocFD9YBA/yx0FhMzBUG//oNoaT+B/nI5ksE8nk/PH3d+cZvYIRnDQBGWOGbvlsCWsNOZMvr40r2wMG5hvZ5fTimbOYbE23I6T0uI0KsqMtdCep32Jz6gVEnCKSP49kbKwvgqAcEXwbU6cUyCU6ybRAh4AhmpxkO/jggwubi6wKCMgfT2w32JB1zutQxs0ZMu5TIXVgO/7+LJ/t+LFd2Jhk2dqF76G9CAv0GVuB80ZPksKps+7Rty1I3MqHV2MqwVFgCN7KBf3wb+OKHSuoIX8tp2RrmUYvGwwO7Gvf3TsVKb8ldoQfmiVH9EfLX09X4+aEgTlCroe0KzOHnFZg05FlsuPa5rj68gS5fD6WTMZSvY2QYMLJ9iPF5jdbsfGljI/JQW++XitzTXYem2Tn39HXWktTceg53IzhU53qVPXIH0fcjrrjkgSSEFqMMG8wXIeJoIq4cvLsNqrDybCwUZx2ZkRDKTFRPkfxHZU00BY3EVCLI+XqmAWjQBu+LbTzZwH1/Yp+7BxaRBl8jCFGjzZ9f2kxTlJ/wZqSREuS+uNhImctcjSkfS3frxXajEWjpd1TzMbUuEmcNjuCxkpdO5t2cIx/Mt3JxrCwE+uTDZ9rMDwsqhwahiUaJXSIhqLJoiKPkuEMkHWLqbbkS+aAXV38kFFBKjJpIUqmw4N+7DjZobMAwjFJ3YlShuZ2RQfl7xtkhiXDSVmSwunmuDIWOBPem0bimJtrdv/NKQaqwAG8ta9/SdTV1Zxj4JtrjncbB/Uk9PpmWmDE8ywTTNFpB1qw8KCDDqo/2tSMSLTqn8HmSlZd0SjYQFYFiOTTM+qTB8fFjJG6804MTbLLMECPqLVAC0MaLfIktHtORsEoP/CIL3pRvuTeXDRunueV0McQEhRzHBPW+pbfkmeJDLXTBeadcZCfpP6gqmO7jucKMNPl2jRH7QJwGNSddWK8wpbMS9Ygfdq1ZLCb03SSOevzJN8pN92DX3VdzRvBcz8I59SBoEQrM+/JsbVOIISOUrYaCa3Dfj1L5oT1nd63Iy9wxymyayk56WR9b8a9d7Sz77771lNKZNqzMYYnI1kZx0ZdSYCAvLAb1J1VouM2b95cd8/RbgzJmJ1VQUG6WuDGuHLuBW4EUtHD5jHuTos5qcFeYfQrw4PU7o3zFa94xfrjeeYEXdPKnQBwVFfgim3U8r07ywR/x+2tJeaUcSXjZI58k1NjTA/RsWhhnNP1TkwaO/YieltSx72xM65O0WiLAd/KYCFIwm4k+7BQNq+ET8d9BTnpGrqH/HHek9F6bOOIbSxoARs8Sd4l+z43sE4ar0a3cveuSYpTHU4lCUa2AKsyuLI1fEdMp8PAe2shJSkCOsYWrZK1cJ999qmbHZ4ltLrCxueEnHprPRtMWUsCtOSAjCfTsaNa2/O44tGpYkE/tiZZ1q98yRyiAwTjyAM9wa8xn33ipq6kHl3CF/G8UVPDxPrMDqMPzRn8KuPMw5L9ziZJRvNNmTrWE4ntJs9awQ9ln1kz6aK2prKJ6BKy5d31nnbboQcYx7kZRHZDfOPBqW6TmmJjXBLIlobAacNROgtBkmLyWyB802nARPD9cIyjvMooUjt7IpQil3bltUEALKgG37OggIiXwbSYKHNs3mJKASYj550jx6hNUo8uWYwpEDRyhPDGMfK8gdNUWIP7sCHjzThzHSb1OJIMEBNWBJshagFUxrixk2ViDtubxr1+nASxGDOkHFuz2JBbiyQFQF70xRlXn+GPfpFUClXy7SpHFb2UBJrtmJM/i5RFV/Ksrd1N+kEXg5AsMyL0K19ivKOxJXlJ6o9B2oFVf1iGLspsmk4aBwOm5qqr+csgY8Chp+EIUzsv8EQTbNBjviapAQpHqjgmdInyWSV0Uf7mOl3B4LTwMko5BeSBDlOPEckhthuDbs4gp51+8/0v40wb6lp06A2yMCvaW7v6a/ftypCUjy9XepoDaSeAE0KW1BXlZhALpqjndIk5aU4ol2eu+nSKPMubdtKHNGzXM/l2CsuOHAMf5vJd0W9s3Evyk5G8G48kVZ9rQxlDyliQRbLmHj+S52Hfs7hPUmDNeOOQoUng0lpjB9PRYvNGIkuCD9Y4fDM8mhGCVykZBWDoSIa/9hqvyQgHp9MEIGfBz7baRMukcvShXbk5xRkhk3Ysmz6GA3118MIurgC9+tZrV3OP0+RHPrXB2KfDBF5tIJAHc1MZ/WFtp2sm0TKtPPjaVKDvjJ2gJieWMU5u5bVkY0MeY5T8JSMHxQYIeRbEoDPR33h233RKMhpXOpGeUgZTvCSp32NzLJNRu/JnmZpMCnQmqZ/K0XlsKA44+vBlzqHZGMpDk3nHlhNc9kwH00vK1ZOSkYyTE+8rw6+rd2BFxl09zzslqT/K5ySeMW6OAafD55qC2mjCyzChPxkFGq0frQ7dq55yfMpPUn+olf71rFxKlrAx/5WthUSXCkJYT9Apmdvkgsxaa9iEaFUmuScP5sQwAAcH9j9dmES1NZvQOk6cPOPoX0SwSYhH/Mp3NTdc+Tvkhw6xGeTEC53AB2pt8n3oNptJydrGotG8K1fY+CFIOrTNeRhJsHTCjjyQJXnqu8KS/mDfOAXk1J0y6ww6YClg6j3rr3esI3QTW1Sd9Z52y6EXgfOdux1vgmaSWlhFE0WnHUni9ACQcmPgikwCcggcBeCojUXAzrmF3G6KXyxWD+iioL4Ps1i52sFwDMduoEVBPTv5jptxErzDKKXoLPiOHoqOW3gd2adUGFMi65wG70toEcWxM6iefxKI86Y9C446PUFgeYKn46wmlHFvjrkF3+6E6LIJZ6JR9pQW58c3YlpitBpzn2gIuJiMyhjhyqeZkhT9MQJaomjdG390cdzIqf79OBojjaxbXMiF+pQNBSGyLFLOsONoa2Oa9GqLYmLgCS7Z9XHlsHE8GQ/K/CIw+bebavG0+07mzStzFM2CXHZ5RIPJuACcXc1kOgvEOK4WaPPfVXTZqQaGNoxEXy1axpvTz6nhnDR+Oct49K68WaUkhfMqSOhH8Yy3b8gdieRYCJT4FWnygBe6h/yqZ6Gmh9AoIMmAIw92VtW1iCTTwXYl/skGmixcnCFzT13yjBaLI4wFTdEFe2PQZJyx7Ii9HVL6F19k3MKoHYlTLcCWzIYXGPphTP2QUTxZU+hmgTZyThbsYHDijAX6BRrw5VeBOUmCXXQNHYNPi7+xsxvoh5rocp9/JbPhA1YrpWT0Y5/WOvMR1ni2Jhkr8uIqmUctac+aaBzpV04qpxBm+COr1kC703g1781t66Ay7WpjXsnY0ZN23TmiHFvjpX+71+g3FnQ8uaVj8YrvluSh27wSBKTP8GNMnaCxK0yH4c9OJ6dQUJ4MkF/z2Ok7toh39D2rlKT+inuj3bXxgw/PLeFJGV3MOEWnk0FsJwa9gAX8yDTZZ3cw5PHPhjEX8GW90Y5NDPrc/FbGueUMJPORbw4oHZmM+ktGu7N0O5roEToSbYIt5inHhq6xjnGE2Wd4pqsE19kM5ETww5FbdqN1gp6ytsFFAEib1jZyANdZje+kdskz3vBJdzopQP7UtRtrLTEHXOktdrC5a65bp9kS6Bewag69Tz/Jq0Aye8O4sm/VEzCxdsIQLuYQm5qjjH9yo++1kJLRfEAnXWdtx7txNxfxZgzRijcBOvOY7oaNZ2USnJ3g4Fd4XsuJLrO5SK/51IJMO51sY5O8N5vNGtYcSmsYu3hcT5jbZFp+45mzz69S1vI22tV4m9vsVnPL3KELzA060YaZ344SAFEGD76h92BJN5IxgVF2EB1kXKyJdDC9S9asP+ag8XEd4ryeMd1jd4gHEIXFqLDIUrgiHZwyQsdRYIRY2IHv2Y5mMlL+rW8DIEoPeIrKrrtFzmKujBJ0/EQwAPAWbIpCXT9ux0lMUv9NQs8iO5xKgy46n6Q4xsJYpGSacch5sIjqu9GSpP5zU3ZwtW8HGf0WUPy1ev26HAHjTWFxhhmrnJsk1XHm/JzxjGesv8grgGKyMTxNRuOpJeNsN9xko/gt5HaukuWyou40UpK6m5CkiKpTwmhJUv/ZPLKCpiSFgUSmyQ65EEFWhmfGJFklJxSDhTXJNEhc1kYy+sVuBg9sBE8YFPpkUInaOqbF6SKnHDt0kXtzp+3CMyBe85rXFHMD/nji1C/rbDcekizimqRQtgJwSYrTD54FzODnuCmnhBEDP7rEnNd9ksLxUjeJrJmmJIXSp3s4SxwDegKd9A4nM0n9DQgYM6LQy+BqxgZ5cCyc4W2HlT4zD8qM/5LUf87KYkY+BTJ1iXbGEZ5gzPAUuFDmc5cm4+oxtC1+MOc8ciDkq5uM2rfr7XkWyaJNF3P+GK76ELxl/FnAYSmRfTtVaEO/e7LteDpDQICNTHNskhQGorWAQW0utDFNZi9TeBimJNXx8601fWJ9sQOPT/wkWZw7yszfZJQnEGMMyRhD3hpo/pJVvytg3ji2Std6D68C4rDR9pCOedwLnHByODf0epLaLQOeHBoXuywCEY2+JJV/etgnCE4zJCkcJYHKts7TIxw8Osx6gddk9C7czEnjrcy7SWrfs/xfkkp7kuIklIAKvpKl/CTFb3TQdckoHw9+C0HASVCivWPcOMJ4ps/ZIALcAsb0OZ2kLpuKPifXAud+6JGDPEteh22jg+2XpGYnIxlHK5uJPsGf4CBbzFwUxBD4NE/plCQVO44fG4Ijw6A3fpwfehYOZJzNBgv62biTcW0nqf3P839443RYk61x6NM/TDgMZJTOkvBi7uLFJhE+6Tz8kXfvceDNj7YxoA0nU42rwPCee+5Z7SntmkPyzX/rEVnQxlpJ6CEXgjTWRDQ3nWzeswPRyi9oeMCCHHtXmZSk/tNi5kYy/zFGw44mukeAzbjZ9fUe20DQRbCCHEj8GTKLT2tYsxmT1HlAjtSzLmijJVjBqD1vxGsy+n0J6xgbFw4+HTM32LjmB33XytiPgl0NS74fXOhPdfgS1k6BALgmKexO6y/9w14SUPO+99Z72mN3GACCibb33nvXb3JFPySKB3gWa2WSevIZuMrG+9UWQ9Sk915TcvI9c1qSkcBbGLQpj/JTJxn9WqGdJ7s2jihSgvpKUg1xbUv60b7knqItW/6SVKNL+2i2OKPZoppkS61+GUcAznCCm9QwlU9hwVoylsYAnmQlWcK0lcPdGBvX8X5m8dz6Rav20Y7O9uyKXvLGWGp0JakLLL4l8p0s8aOtaSaGDmyHSb/ol+AMU/SiH87k23tJ6mKBN/jihXHkvSTTJHNZW/rSv0x9eUaDZzhyQtACX+XJiJZkdMwQL+rOOiWp8x6GjR59J6n/TCCc0YsO+ehVbygPyvCmLj7JQ3tH2axSkoIWcmHM0dD6gikZQM9QVxoTMoIXddVrPJGLcbqNkzrqziLBDP2SAFOS+qkIfuS1hE+0oRv9eEUXnIktSQAAEABJREFUHtV1xVuSRXn3joQvdWdB/860aY6iE03j8tPaMVYw95yM5oK6SYp8vMJsqCfhQn6Vab/hoI15pmR09LuNGblKUklotKPP/EhG+bVwy//wobzRDy+8uiap39CTEfiNj6nxJRfkfYhNmeMf+o2D63i3aEK7fDKML/Q2XuVLyrQhXzvqGdfxusrhII1joZ1ZJ2OCp2T5OMo3hugit3iQ0IgP/JBxeWhMUn/norU1rCev1XP1rja0j/9ked/am3VqdBijIR/6ZTOir8m/q3EzpspgQj7NBfKapOoqvOBJPXNDG+rBotXTvveUwWGIjbK1kpLRugkfdOI7SSUPXvI9yMcjTPCF92RUTzmc8Sjf81pO+DDWEpqTFLwaK3ktqYcvPJELc2XIVzL65yjH880jMjKsu9HukxTy0rBqV3y3OdHyXMkNHCVYqpek+nvGQLl886ds+XNvTVIGU2OxpWjdX/ZY9xwMGPCtqKigiIzdpmRJMQyq9duNh0DnqCPQEegIdAQ6Ah2BjkBHoCPQEegIHOUQ2DAOfZLiqKZfyHS8RbQv6Q79UU6id4jhXqkj0BHoCHQEOgIdgY5AR6Aj0BHoCKx/BDaMQ28oHJ1wnMLxi6Q78zDpaQoI9CY6Ah2BjkBHoCPQEegIdAQ6Ah2BjsAaRGBDOfRrEN9O0lEQgc5yR6Aj0BHoCHQEOgIdgY5AR6Aj0BGYBwLdoZ8Hyr2PjsDKCPSSjkBHoCPQEegIdAQ6Ah2BjkBHoCOwSwh0h36XYOsvdQRWC4Heb0egI9AR6Ah0BDoCHYGOQEegI9ARGCHQHfoRDv3/HYGNiUDnqiPQEegIdAQ6Ah2BjkBHoCPQEdiwCHSHfsMObWesI7DzCPQ3OgIdgY5AR6Aj0BHoCHQEOgIdgfWDQHfo189YdUo7AmsNgU5PR6Aj0BHoCHQEOgIdgY5AR6AjsIoIdId+FcHvXXcEjloIdG47Ah2BjkBHoCPQEegIdAQ6Ah2BaSLQHfppotnb6gh0BKaHQG+pI9AR6Ah0BDoCHYGOQEegI9AR2CYC3aHfJjy9sCPQEVgvCHQ6OwIdgY5AR6Aj0BHoCHQEOgJHNQS6Q39UG/HOb0egIwCBnjoCHYGOQEegI9AR6Ah0BDoC6x6B7tCv+yHsDHQEOgKzR6D30BHoCHQEOgIdgY5AR6Aj0BFYewh0h37tjUmnqCPQEVjvCHT6OwIdgY5AR6Aj0BHoCHQEOgJzQKA79HMAuXfREegIdAS2hUAv6wh0BDoCHYGOQEegI9AR6AjsCgLdod8V1Po7HYGOQEdg9RDoPXcEOgIdgY5AR6Aj0BHoCHQEKgLdoa8w9P91BDoCHYGNikDnqyPQEegIdAQ6Ah2BjkBHYKMi0B36jTqyna+OQEegI7ArCPR3OgIdgY5AR6Aj0BHoCHQE1g0C3aFfN0O19gn93//+V6QdoXRb9bZVtiNtz6IOmqRJbcuXJpWtdt5KdMmXZkWftqXtta+ONKmefGlS2Szy9DWeVuqn1ZtUvq2ySfVnkbejNKxUb6X8SbSuxTz0N7rcj6dWttpXdI3TIE8azx9/VqellcrG89f6c+PHdXu0bqvOtsq21+40ymfVv3alcRrlSeP5s37W5zAN+2v5w7zxe3XG84bPyqVhXruXL7Xn1bqiQRrvX540nu9ZvuR+W0kdaVId+dKksrWShz5pd+jxvrQ7baz2u+iXdoSOlerJl3akjY1QB6/SOC/ypPH8Sc/bqretskltrYe87tCvh1FaBzSaHP/5z3/Kv//97+LqeRLZ8v/73/9OrKfMu9trY1K7u5OnXzRJk9qR3+hy3+q09xq9w7JWZxbX1u+2+lMHXRLaPTdavCdPmfuWP62rNoftD/se9iFfvZaGZdpAnzL3w7JZ3etLn//617+K5HlS3/LUk9wP6fEsX8LfsGwe9/psNKxEf6NDOTpdvdfy3ctrZS1/SteJzegT3fodr6BMvvLxsvHnVld9qT3jxZi6yt+RtsbbnvYzGtAiuR/SKs/zSn2qrw5+JM+trvyWttVGqz+rK5qkSTTIQ+OwvOXhR5nnSbTJ996kesq8q0wdz5PamGWePtHgOt4PmpSN53uWr9z9pKS8pWHb7lu+66R3Z5GnL3OqJc+NflfPEvrG+5enrCXP43WGbbgflrf3XCe9O6w7q3v96p+suXpufaFXnjL3K5WpMyxr77vKV96SvJa02fLdt/y1dB3SvyM0qq+e1Phwj084Km/5a/GKvkbvkD75jQfXYdnwfrye51bu3rsttfyNesWnMXfFe+PTvbxW1vLHr+P1PLc67rXRkudWtt6v3aFf7yO4Bug3Ib74xS+WG9/4xuUCF7hAvf7whz8slNuQPPX+9re/lUc96lHlete7XrnNbW5Tvv71r9ddfWVf/epXy53vfOdywxvesNzjHvcov/jFL4avz+S+9bvffvvVIMN4J8rf8573lFvc4hbl4he/eHnsYx9bAxbq/f3vfy8vfOELy5WvfOVyuctdrrzzne+UXRPeKR1XbdTMKfyP8fS5z32uXPe61y3f/e53K3bjzerva1/7Wrnb3e5WLnOZy5Q73vGO5be//W2t9o9//KO84x3vqGN0iUtcojz5yU8uxqQWTuF/lORHP/rRitelLnWpctBBB5U//elPW7WMxk984hPl1re+dVHvXve6V60n/y9/+Ut59atfXW5wgxuUi1zkIuXlL3/5xLHZqtHdyDCWBxxwQLnwhS9cLnaxi5WLXvSi5exnP3shx8Nmjef73//+Srd6j3nMYxZpg+2hhx5ayMNlL3vZ8ra3vW1RVoZtzPL+D3/4Q3nCE55Qbnazm9U59rKXvazgbbzP3//+9+U5z3lOueIVr1iucIUrlA9/+MN1vsLfnHzwgx9cx+UmN7lJOfzwwyfK2Xibu/P8k5/8pNzvfvcrj3vc45Y187///a986lOfKle/+tWLebiscOyB3Lz1rW8td7rTncr1r3/9+h7er3GNa1Q5Ml4XWZAnOuqnP/1p5XcWc3SMrK0eydARRxxRDjnkkHLLW96ywBjuv/71r8s973nPKn/k5+1vf/uKuH/rW9+qsnrmM5+5nO1sZyvmkjZ++ctflkc84hHlRje6UZXRz372s5XPrYiYccaRRx5Znve855V999134hygJx70oAeVJz7xiZVHmODhtre9bcUDLvSp8Rkn1bpAPuFGf3zhC1+obeAfv9YQuuOBD3xg1Xvyx9uY1TM+zKWb3/zmW+HeeDY/h/2jj/zTPR/4wAeGRfVeOXl9yEMeUtdGGFlv9SXh+S53uUud7w996EPLb37zm4pHfXlG/zOv7riwrtCT5hXa6Us8/vnPfy4vfelLy7Wvfe06717/+tcvkwFjag27733vW3W8uuNkqkN3wdE4v+lNb6p6FhY///nPy8Me9rCKBRvC+MNhvI1ZPqMDzuYwu+emN71ped/73ldpRAtZJsPWtvvc5z7lj3/8YyXHGvHsZz+76md83fve9y7mrPZqhS3/g+MnP/nJqsus9Y985COLOaUebKyPbBJ9v/a1r639bnl1TVxg8MEPfrBs2rSpjpN1Egbon0Rgq3+6052uyop6ZOwlL3lJxQqfeP7nP/856fU1kUens1uf+tSnLtKDr4985CPVrjVXHvCAB0y0t/BLp9/97nev+u92t7td8ex9yXwx3+h1sm/99s5iRxvkBk90IVvgghe8YLVBzH3j3nAwZ9ji1nlrpneG7HuGl/lxvvOdr1zrWtcqX/7yl4t86Tvf+U458MAD6xp5//vffy76ckjfLO/3mGXjve2jBgKcCE7Xwx/+8PKa17ymMKwpJBNwiIDnZz7zmXVhetWrXlUVNcObgWaR4ixb5CzkDEHPJvKwjWnem9yczSc96UnFQou+8fYpl2Me85jlaU97WnnWs55VXvnKV5Yf/ehHVTlQDJS0BfWa17xmoWhgYTF+ylOeUq561auWF7zgBbXueLu7+pyknPzkJ6+OJud+Ujv4QuPBBx9cXvziF5fPf/7z5XWve12taiE45SlPWZ05xjSevv/979eyafzPOCYpz3jGM4qxZtQzTCa1bcGGExrgyhBW78c//nE5z3nOU4MlZEo5Y0DZLBK8GIWCD2984xsLA5QBQgZPdapTLeuSYb3HHnsUdBtbi80PfvCDWscCzFkkDxyKAxcWjd/97ne1bB7/I79wPPrRj14YQhz2QxcCDJ/5zGeWySB+jTln3ny95CUvWZ1Lc8GYWCQFWPAh2LMtx3JafKHZGOsffcN2j3WsY5VvfOMb1dAb5g/vyZ3xePlC8Ecgi5PAecc7R+gNb3hDHVeG8RnPeMZykpOcpAaNzFEGEuyG7c3ynkwwzk572tMWOs6Y6Y+jxzEwVy996UtXY95YKBsm+uUrX/lKdYbJ65vf/ObC+IGb8aavzPs73OEOxTjSr8P353H/f//3f9VwpQ/HsfUsOPOlL32pOiLolowZ5wcesMCDtWRIL97ln/CEJ6wyzmE4aCFoyLmCFSeRI/mKV7yiqPPc5z53K8d62N407/HwzW9+s2zevLnQs/hs7St797vfXQ3Lod6Wrx5n8IiFIA/+2jvtqvz5z39+OdnJTlaM761udasa/CJHnEF6xjqK5xOc4ASFw6jd9v4srmSKk0X+zC3r/1WucpXa1fe+970alDJOHF4OjvmpEC+CbgIxV14IhJuzmzZtUrQsfexjHytvectbqp4V5DNvOcn4EkTfa6+9CiwEN8iM8V/WwIwfjJN+T3/601ebgCOHlqan8Pv0pz+9rrMvetGLCqcO7QLtsLI+Gi86AIbKhiT/7Gc/q06gwKz5oBzf6ghwagMuAvL6IXPK1kJCK3zoNps36P72t79d4GD8x2lUn56AB3tPHXk2Bjjx+CPT7uGrbLyNtfBsDSOHxr7R45kOgwO9ToYFzFu5K37MYwEg+h8Ol7/85Qv9bU2GhwCm4JV13ZqsvaEe0c5GSR//+MdroI9eEYw/eMGOpdthceSRRxaBYFgevrDRQEbG+VaHQy+ga26d6EQnKuw5MglLa+JlFja6+BknPelJ6+Yhu2O8nfX43B369Thqa4hmyshkY1Sd9axnLXaMLGycHJNnSCrl9uhHP7owVhnpomcU2WGHHVYYAXZDz3ve85bjHve4dbdBvkk8bGOa9yYxg4KBpM9JbZ/61Kcudss4AKc5zWkKB4+CUPfc5z53Oec5z1lOfOIT150ojvaee+5ZgwPqc/Ap73EcvLur6WhHO1rZe++9C/xWaiNJDSYwAEW8GT/4UB+N5z//+SvN6Mf3cY5zHEVTScc4xjEKBxFG5MEzfMYbT1JxVe8MZzhD5YdyJU9nOctZyjnOcY6ijIzAEt/jbUzrOUndkXdiYd+FHUVGFsOB0WmRHvYDR4stnsiDhE514Hmuc52rOhIMPVgf+9jHVjSXZMHiKAkq7Lkgh8bfyRGLGlwbEUkKGTjTmc5UHVv4q2usyNX++w1nsz8AABAASURBVO9fjMUpTnGK0pzf9u6srvo//vGPP7F58s5BnFi4JVNghbEjOEd2jne84xWBFztkdhDbuArcMJKVcb44gAwIumlLUzO92L204+ZEkN1H+gRvjLQDDjig7rqjVVmSxVMrQ6IE6w5Z2N23G8tQNseNHQMPBgI1+BfQ4FgKNA3fn8c9nWKOJNkqmEQnMmzp1SSVHPLJ8EUrPuhmMjg+7+ULuAnE6ENA1ekjp5WMLSeXsUaO7eJwAv7617/WPmb9P/3YlWQwDvvCm9Nnn/70p6tuHJaZswJmsFpJV8BD4O1qV7taXRvxxeFj0AqKkF08w8OYC4wIUA/7mfY9mdPnPvvsU/ZZSGigT4yXYCw7AE8XutCFqi5JRnJgd52Bzpg2/nSnuZiM5ACd1ksOvHWADjUf9AED48/BFTywdhl/NoQApXfnlQQ0BGiscdYIOpe+pH+TVBsHb3AwN61hjTbvtsBwkopfK2tXQXA6wVpqXAXsBGjlCcRbX6xF1h/625jDrb2/mlfybs2hg2AiyORE5nvf+97CYR+njY0nOKEOLJVrg053MoscSbB06m2t8InOYbJOkUm0t3w6jKwaf+Nl3rhv5e1K79Hr5g55sWaREYEguFk3zC+yQA8I4NB77f2NdCXb5J1cW5/JEX3GPmB7wdSmFL0wCUv68jrXuU49YQkzwTZrC11r3bERZ/1lI9FB8ujSjYBhd+g3wiiuIg9Jiklj4U1Gi/KvfvWruvvOUB2SxmmnjCln+ZSTK8PaUUMTlkEgz6S1Y2EBGypIZdNI6HBU0UJMgSQj2sfbTkb5gg0izps2bapGVTLKR5vF126CRZUy1oYjPqLOjBXP80zJiDY7niL4lKBj1WhIRoYVA8gxTcaVhUbZNFIyal+Qx/EykVFO7qS2kxQGOOPNEStjkaQkozYYq5xqgREL5aQ2ppWXZLEphjmnw6mL8fFLRrRZfJ0e4Jzttdde9d0kdTfQiQiOBAPUolEL5/C/JEV/+tcd2YSbeed5mJIRrR/60IfKu971rmIXzc5uqwMDu5tkmAGRLOHT6qyVq4j84x//+KqHOLkHHHBA3REzx5Mlus0HusbOYJKCR45RslRnOzztVjF64M3xTFLsPpBtOo4uZMS1DhggAhMc/mQ5fXaeOUSOEtqFECS1KySIarzIQDJ6R7ucXX23tlfzik4BFAHgZEQjeswzpxbset7+9rcvnFxBi3EnFy+MWzy29zjvxtWctW4kqTpEHc4C3a3uLJO51nRtW8P0Jx/2dpKM1XBNVOYECQPUHIOBd4ZJHTyTVc5Oklpsrgrm4HvIs3w8Wzu9WyvP4H9JKsaa1g9dIVCfjPLxjDdHhOl2fDOo7SzSl07o0a+cVHW105I1gc4S5EtSsxnueDLG+LPOJqk0kBFGOjpq5Tn8T//GzTra+mUDcdZ1Lw8fdlZ9AiMwnaRYC8m5k4jWXraHtXk49vDg4HGGtZWM9LrgHP7JA+cxieIa+Haqjc6oGav8P/Sbv8Y5WaLRPDT/h+SpKwgmgDnUdfCjJ4d8cuwExbwzbGMt3ycj/gWdrE1sHM7oOM3kSZ45jXfzOEkh804u0uNt/sNVe3S9dzZSSlI/223zgUzjV0pGWJoHglrWQXiO808fmovJqD6cfBKUpNBJsKYzkhQyRZ8INI63sx6fu0O/HkdtjdJMEYnAOqbOUG2TspGrTJ32nKQuyJQ8g6XluyapR2yH9eVPK1kwHcuhECwQLU3qz4R37MsxQMYz40H9JPUIpTxOvW837VTgE50MTcpE3qR21ZllYkhw1hxXc0QJza0/3+oyBhnN+Jk2fYxyi69FTAR0pfYZN6LQDD1BnWE9xhBZgi8MG+2zvOrfYmnnpS2q4/1xwByZ5Jg4GgzHVseRSrjjXTBCcKuVzfpqvm1aCDg52ujYnhMuvkO20zWpbzLLCbHIcaTIqnpJiuP2jrz5vQCBCbgoW2sJXXYy7FbYjSfrnAjYG4tGr3qMXgu7BV0QQMCIwUj/zEa+Wu+jKxoEWxiufifETiNDwreAdEaSWpHjo55AFxmsmYP/2fFywsLOg7HmHNkBtns5qLZ4i7/Fh1W6wbtdFg6cHWZjQB+1hCy7U4KM9BFdYO4oV9bSSjxyrrTf6rWrfmfNv/FCrzFxogXN+nWlK3x6xNnl6MtT5h3zDa928NCrrCXPLe0sz96Dh+usE144HQJjdGbrDx8CnsaQHONBolM4tfSNAIedWcfH4eFd7Rkv73tuSb48eLa8dlWGX9eWN+urTQnBap8V+E0a66wNAnM7Gc1jR6StfT7poYvRxylzQshpMHqVDQIXZUOa6QPPyagt95K6cHA/TPLG2xiWz/ueI9b6TEY8GNdxGv0WhLoCG3hoST28tjZck9TTj+7XW/LJDBlwNebj9Dvd5zQde0w9n6UIQDuZMm4be9d8gZH7jZaSkbyY0+wQa7k1r/EpmG2+Oanl9ELLb9dk9D58yJBPVHySxD7y3Oq1q3rwbM/r+dod+vU8emuMdhPDLjVj1W57MppYjUy7hUkWj2CqL4m+i6qp57ldReUsgMnydpTvTrKAcDQd3/KtM4Vhx9VCy9FvNLQ+RPFEBBkjTiMwolsdR3ccDWNUO6Ytqiz6py1RVd9FJdOlv9G1vStjyckBv2dACbaFIUlxJM63twxQDvX22tqZ8iQFVvp2NJbBs9L7drLRwQmjoC366iZZpJEhzFhqmCufVdKHBcA4r9SH8YUtun1ywYlsdRmrsBVA4ehz7FvZrK8WLKcxOIo+G4Cb3ZwrXelKNXA23r8dYbJrDDj16rY65BZ/jHHlcGlla+1KZtDHoTfnHNOkU4Zyx1A0FsYrSf3kRDCGfsHj0GCYJX+cTrLlh+zsMMAZnRz7stAxPsifUzN0S7K17khSPydAO8fAsWa783hIlvRr2fJHtyZbt7OleG4XesZOrh1bRyIPPfTQ+v2xcTCG1g7HuOkN4yegR1cPCbQmeIbT8CowY82R15I6Seq35y1vFldGovWB4+77fcYjR8XpHXpAEMOPLzk5Qg+bnz4NIXfKrJfK7Dwx6I3/kM7G8zAvSf0tFWvTML/d291u97O8wtjR87ve9a5VJltfduTpFjoEX4JrnFT1fVZnfAXXHLMWNGS8t3edrPB+e3ZNUuhd7yVLsqy9ZIRFspTvnVkmupbD7tSeMbAbL9hApyap+tY6QJbJuiunwTz3SQbZlof3cf2apJ4CRD/+XFuyu0uvt2fXJPWTtUnBP+WrkczHRnu7+gQBbo0emAno+0yIHBx44IH1EyOfbJKZcbnXjnUtSWti3Vx99228nQ6zOYSXRnwyGm92BN1ofJ1wpM/MEfq71W3vsaXX0ng3+qZ1tV6zpX2i4CRak5sk9ceeYek3Boa2+Hjf1hT6V8CUnZukfg6pXsPRVXDZHJa/3lN36Nf7CK4R+k2ezZs31+9W/NptMlK6JkxbyEVhHSNjfMq3++pqgWfIiUhaFOWJYjJ8LeLTZpHCtBhzdP2wD2OKgmSIibzrn4Hh2vpmYPhejXKQp0xyz7C2u+TbVXnad8TO9zn7779/NbySER7q727ShzRsxzPDUp57V0rQIipo4V6+pAzNnAa8J1s7AersSmrtw8uiDudkqf02vtpWVz3HoyzinltSbsESoba7JV/erBNZZWSRyWQ0ZvqWr2/3rvCEnzH3LClLUmDLGeNIy59ngplov5Mndo84uc3INEcl9DRaGc++V7NrKl9Shj8OJxlmRMqfZdKntK0+huXu2xw1Zy3I7Ts4J2Ms0uhv7Rk/QQuOtDxyZ0cVf75TNZbyZ518F2hX1lxNUo/8od244ckRXrvtAjP0iDw0GTdGjnt5kpSkMHwZfoxdOsquqLrmGsOQHk1Gsuz9eSS06add3TOq/EChYCe9a475rIB8quc0CQPOGmEnyxhx6JXBSxu+m6RX8ChfkJLx7/tac84pDEfylTn+DO9ZO7fmO8fED1o5Ss1BR6N7c1Hw2L1knRD08627taT9qjU8yIB1kD5E/5BnPDiF0sbVWok37eEZTsqcLjLe444v7GaRzEGBS06r8dIH2pMU/NDfAk5JqpMqoIZetCYjR9zam2TxBxIFpugj84QTrA8/Amm+GmfYOlGjDTJu/GGRzE/Gk5Gep2eNgR1DDoZxTUZ00KHG0trmHi6CNeQTD+wkpxTsMuJTOT0FQ2367AB/+BQIgB35N19sPNAJsBEsQQe8vbvaCa9sKTSjHV/sObrXXMErPtEr0GVDhfxzduk8QTHrEhlwiqq1wW60nml/tXmc1D8+x/NbHprNYZ9X4FE9ZcbP1TMH3m9CWG99ssDBt4bBxWkeuk5d6wM9Se97b6MlPNIRbbyHeCmDpTXfGklX4F8+LMmKZ1eyY76YS3RTkiIAbt40XWqOCZjMa/1H2yzTHrNsvLd91EDA5PHjchwhTrpjMqKuFho7Uo5f+36KAqKkHCei0O3I+o7OAsUQNdkYcowSR7AZSBb7aaNoIaEkLSISp5aCcDW5GdX6piAcf/L5gGO9jhVSpo66Jqm/wm7HCY92kBlVFHIyWtCnTbf2KC7GHIXUjFr5aHPcWlQTfnZMGEGOFotSGgPBEfw4ws7YNSZ2kjg1lKR2djdRkKLRFDKaHP22QCcpDDTRVsaIMjsVnDD0irQy9Clv9DoKLoLPWGQAcViS2eHa+HbKAk4W1WTUn7EXFGGI+OzC+OMPhuRBVN37eLDj1uTBODFAlM0jkQ1OAKORg2G+wbHNIbt/Bx98cD0h45MBO4Xq2znFM4OLXPm+WRvoZ2z61jsZYTErPmCrbzJNn+BFX65kGKaMGmXyLcrmKPnhAPrcxa8pM/TJOH3CsVJXMhfgwahKZsuL/iYlc4y+48DTkXiiC32iQf/4ztpOr7GgG9VRjlf/yobxgod5Q78y9v0Il/lFXrXPQPYvS5hTdoHJ35ZPLiaRNJM8NBonNBhXnyzpiHNnTOhcJ3I44Jx6et+8Z6SaQ+r7DRI4SE5PGWt56jmW7zcfBCuclBHw49Bx+ARSzUH6xQkAsuwd/c8qcVLoNXxJnBkyadcRj3iVL3nm5OOZ8y6vJadL8MIIpV/wzCg1rnSO8aRz6G/BQgEc/HKY8WztpW8d8fbOrPgdtkuGyW4ymlPG2xha5znavvmmfzijxsHupE+VrD3WWbv4AusMbrJP92vfb2Iod2qIjCu3huHLeqwd8mX8HVW2WeC9eSUyzobxrxMIZhhX+jVJMXbkjtwaL3OVLOCBjmUX+S0N9oV762+S4ltpPwLGcSMfMBOU1Z6TDk4DJCl0OGfZuzZR0EE+5sX79voxRuSYg0oXW+/ZScbZXHEiyZwwt2HX5F+AS54TVmSG/Bt7fFqj8KyO9rdHw2qU09NknlyaB2SEzhLoYfsoYyeSjWQUwMKjNYu+tM45peT3BIynzSAyY37Tk2TNHDe/BAKtZ6vB5yz7hIN1kI5jm9iJhwnfgs5wigNgTpEFAAAQAElEQVSmbAGyJRiULGHJHjMf+CPWS58DWUc9s43NKSenBI+NhzXCnKOvZ8nXvNruDv28kN6g/VBajrKaeL77NEEkx9mb8Wy3QMSVIqakLG4UOUg48HbTKC7GqEnMGaX8/TuS3lFv2ilJPSKoXzt6DCMGR1n4Q48Iur4ZypwMUXaKhTJu38kxIjg8nD3Gh28BLWLJyLhZaGrq/1FQnBfGsQXeAmEMBCnQbSFseMOTkcHghzd+GIGUnkWGosOPnbNpEdrw0r5F3A/jCXJo32INb4arnQsBEN8Pc1YsYAxcNOKNccOAs4j53pLRqI1ZJ1FhgRF0tr7IBb6SFIrfwos2i4QFBqbqwtEP/FgwBAYYp/NedBnS/pk/c8w3nnBLRvLoXkIrh5fTKIjCoHBc2LiQI+NEboydHVQOSjJqw7uzSHYvBU7MIw7psA8YM4Q5K4w6ZUmKOUrmyYz5yTiywJuTHD67G+pKHANGpLqeVyMlqce/0cdINSedjkCXYAaa8Y9POlRqcicI4LQNuu1ckS2OvXynRPCVjP51C0EDeBhPgZs999zTazuZdq+648a+K7djyRGlo5JUnYtW84sDL3mWyBwcOP2MVkYd/tBvnOk29egzhj0e6RFOHbmlx8mOQAeD1/rRdEqZ4V+SRb7Qx2lpu0Keh4mu4LAP89q9oCXd7RnP2sFzkmIO2t2jd8g93d94hhUDlw7FM2eqzOmPg2F3OBnpB7QLrthhtAZwxBjMxkaZXWknFsgup10QjrOizFiT8ST1VBv9RQcx5q1VrayNPxuBPhMIIB9zYrl2Q57RIeDGwbaOGjOFxscagX/zT8DXKSA8Cq5xJsxx79NR+FBmraB7zQ1z1zf2nHm/d2PcG87sqqc85SnF/ODo0xNw0PdaSfjxKY1x82kJ54reSkYnNayjSZbNG7YTfWG99T6dL6BB1rVjbttwKWv0jz43D+l2n1Eg03zm3Jub8BC8wJeyZLSGGW+BaWMs+CEAZE0w/5NUjOhGjqxgloCdTxmT0ZwrG+yPPuO8k3+yzU6xg04+yIa5Bg+BMP5EkoqReUcnspEFggQT2eTa8FmQ0z1JCrtYIJKtwO5gN5C3sgH+ukO/AQZxNVlIUihhi5RjZ5J7Bh3la6FlcA0VOIPNgm+hV47+JPW7VoujiUw5mrzKZp0oXYuF/pIUzg7jmqLlpFEIosqMCwa2yS8xFn0rbpeBY6R+MlslywCGDwUFa9HbZISdhcBxS3QwltDMmHbEU16S+s/rWVzRTLExDvAyLYwZJLA0vsZS8EP7Seo/+Uc24CuP84lGpzHwJS9J/Te1BYgs4pw5Ro+yadG4rXY44zAd1uE0MMySFMYqnNHtJIKFBrbq2w1FMyOPYS1/XnTrX4IXeeXUNSNavsTJYVgkKXYUzVH04pnso5Uh6ftO/OEZFvhIZivX6CDTktMF6JWSFLRYoMk7PSIfTeYo+UpGx1/pFQYuA5DuwY+6kkVb0M79aqYk9VepnZwwRwReYM8YYbjgH5/mCb45/PjgvHJikxS6UZkgDOetGX5J6r9ywGgUUOUIcJK8P3OexzoQ5MQHfhj0yXL5SUZOKoMqSf3m2Dwzdo03zi/a6Sg6SwA1ST3K7bcHjDV5xmPr3hFMxp6Ah5MlbX1p5fO4Mio5o2gf74+MksXxfM+cAE6be/Lrd1nomyT1G2k80y0C3nhOUg1Zhq4foLMWMfT1n6TM449zQi4br0kKI9sY4kfwmf5ORvSYt/Qk/S6YL2DoXUlw1zFadKvnxAWeOK9tzUhSZdx6Cws6DRbe9968UpJijjkpgF9zOBnxaD62tc3pG7TjB23otEtoc8D85/STUfkCG+aK8fNMlskRvSCYo542tOWUB3zpaPNCnrK1ktBvTTfGghd4k5eksJvgNqQ1Ga2t5m3jRf399tuv/s4GPFsgbPjeWro3nvSdRK+hzfoEA/PB2Db7TBk+rWECOXhj1wnScDyVJSN5SlIDwQIC1kn4Dcu1tVFSksKht3ZI1kHz3A9uClo1u1YQzxyAA97JCixhR2fSG8ahteGZnkhS6Eu2GxtYUE0byQhrba3ntMd6Jr7TvjYQSFIsaMPUJkmS0u7Lwl+SaoSoO8wvC39JFstM0DKnvyS132Q0qfUtJamGJlqlcXrVkS+5T1Jm/Zek4qlPKRn1mYzyk1Sa0arcNUlpf0kW3x8vK1P4S7Ji+0kWcU6WZGacDliiXXKfLNFfZvyXpOI37CZJ5SkZlaEXba5JSvtDq3zJfbJU1urM8pqk4rtS/2iSysKfq3qS+4Ws+l+Syqt8/A3Lygz/9KVPSZ/JCLtkuZwoQ0aSymsyqlcW/pR5X1vJUv5CUR3TZHme/NVISRYxRnOSSh+60T9MyahMPaks/Lm2OkkWcpb/p1xbUrJ1+fLa039KUsem0TiJjmRUJ0nlvSz8JVnEZfhOktpekuIvSX3WPl6TUX5Z+Euy2Iaysgp/SSoNyRJdZcsfmqQtj8su8iWZSSqP7bks/LmHi7TwuPhfktqffHXKHP+SVDrL4C9ZPmcHRfU2GZWjN1nCCO1SrbTwP/fqSMlSvYWi2qd8KVlepnzWKUnFnAwmy/tPlsom0df48q77ZPR+MnovWf6sDfXK4M+zfCkZ1R8Ur4nbJBUjNKK3bPlzL2/L4+IlSR3XZImfVlf9ZCm/rME/NBpTCd1Jqm5r+a5JFilPUvltdZVLyVKdsuUvyUQsywb7S0a6AYbDNMRI/jhOSRaxVFe5ei15Tka4JqlYKlO3bKC/7tBvoMHsrHQEOgIdgY5AR2CDIdDZ6Qh0BDoCHYGOQEdgGwh0h34b4PSijkBHoCPQEegIdATWEwKd1o5AR6Aj0BHoCBy1EOgO/VFrvDu3HYGOQEegI9AR6Ag0BPq1I9AR6Ah0BDoC6xyB7tCv8wHs5HcEOgIdgY5AR6AjMB8Eei8dgY5AR6Aj0BFYawh0h36tjUinpyPQEegIdAQ6Ah2BjYBA56Ej0BHoCHQEOgIzR6A79DOHuHfQEegIdAQ6Ah2BjkBHYHsI9PKOQEegI9AR6AjsPALdod95zPobHYGOQEegI9AR6Ah0BFYXgd57R6Aj0BHoCHQEFhDoDv0CCP2/jkBHoCPQEegIdAQ6AhsZgc5bR6Aj0BHoCGxMBLpDvzHHtXPVEegIdAQ6Ah2BjkBHYFcR6O91BDoCHYGOwDpBoDv062SgOpkdgY5AR6Aj0BHoCHQE1iYCnaqOQEegI9ARWC0EukO/Wsj3fjsCHYGOQEegI9AR6AgcFRHoPHcEOgIdgY7A1BDoDv3UoOwNdQQ6Ah2BjkBHoCPQEegITBuB3l5HoCPQEegIrIxAd+hXxqaXdAQ6Ah2BjkBHoCPQEegIrC8EOrUdgY5AR+AohUB36I9Sw92Z7Qh0BDoCHYGOQEegI9ARWEKg33UEOgIdgfWNQHfo1/f4deo7Ah2BjkBHoCPQEegIdATmhUDvpyPQEegIrDEEukO/xgakk9MR6Ah0BDoCHYGOQEegI7AxEOhcdAQ6Ah2BWSPQHfpZI9zb7wh0BDoCHYGOQEegI9AR6AhsH4FeoyPQEegI7DQC3aHfacj6Cx2BjkBHoCPQEegIdAQ6Ah2B1Uag998R6Ah0BErpDn2Xgqkh8L///a+0tL1G1fvvf/9b6w/rym9pmD/r++312cpdx2mR19J42SyeW1+u22pfeUvj9Vq+63jZNJ61a3wl9yu1qayl8Tot33W8bBbP+pHQLLlfqR9lLQ3rtDzXYf487/U9TNvqu9Ubr9PyXcfLZvWsL2m8fXktjZcNn1sd12G+e3kteV4raZym9uy6LRqVtzRer+W7jpfN+3kSDfKkNsfcN7rcD1PLX+k6XtezdlvyvNK7s8yf1K88dLkO+/bc0jB/pftW11UdV0nbknv5s0760V9LnqXWr/th2TBfmdTyJl2VtzRe3vJdx8vm+az/lsb7bfmu42XtWZnUniddlbekvN03bF3lKduhNMdK6GppR7pVd1jPc0vD/LV6vxKtLd91W7QrlyaNqfyWttXGRihrfLpO4ke+NKlsmLdSHfktDeuv9/vu0K/3EVwj9FNAv/vd78ovfvGL8sc//nErR31I5t///vdaT13pP//5Ty3Wxh/+8Ida9uc//3mbbdQXpvQ//aPdBJ/UpHw8/fKXvyzjdP373/8uv/nNb8qvfvWr8o9//GPS61PNQ+tvf/vbitGf/vSnArNJHaD5r3/9a0HzkUceuayedxrOf/nLX6aOs77/9re/VRqN7+9///uJfaiHBzSix3PjBZ/e8762Wv6srvomAz//+c8X6Tam//rXv7bq0pj/+te/rtiO0+YZzWRCva1ennEGPswvmKJxEv2NBGXoxOc///nPll2v2pBP1oxFzZzh/9BNFqVhN/pGA0zJinrD8nYvv8k7ufFeKyPv5gBMtK9uK1utKxrICt7gjEZ5eMQreuVNok89eki9cV7xTY7xqq1J788jD41kiHyN82FeoA/90lBvekeeeQgb/KxErzJ6A37kVz/6835L+pG/UhuzyEeX8YNBa38lnuXjE73GdHu0qo9n9c1ffeEZXvJaGvbdaJjmVfuNjtYnrOXrxxUGrazNO/nkUr7ylfhVDx7qkfFhPTw3GVdHf6uR0IgvNBpDdDU6jI1xgQm9pG4rc/VM1r1Hfof8KR8m8wO/+vGett0PE4yG70zzflfbgkfjD6/ba4dsw2yIBV6tYzByv702VrPc2JAHaUhHw8F4kVf1huXDezipJ+HZu8rJgGdY0HXyNmqCT9MR5Lph0Pj1zB6HVcubdCVH6llntdnqkCM4mpvba6O9s16u3aFfLyO1huk0Wd74xjeWu9/97uW2t71tudKVrlQ2b968zIls5Jtkhx56aLnGNa5R061udatiwZP/7ne/uxx00EHlFa94Rbn5zW9evvrVr7bXZnZF+2GHHVYucIELFBN9vCPln/jEJ8qDHvSg8vrXv77c7W53K9/5zncqb5TsU57ylPLkJz+5PP/5zy93uMMdqnPvHUrHAuXquUzhD0avfe1ry73uda9yi1vcolz1qlctMJM/bF5/3//+9+t4vPKVryz3vOc9y6tf/erqVCszVve9731r3p3udKfy3e9+t5YN29idezzf5z73qeNrnJ/xjGds1RyaP/3pT5e73OUudbxh9/73v7/i6v0XvvCF5ZBDDinoxy+DZqtGppQBE4r/xje+cbnHPe5R8YLZpS996ercD7tB23Oe85zy3Oc+t9z5zncu8GtyYyF/0YteVMjE9a9//fK4xz2uqD98f9b3P/nJT8r973//Qk6e+MQnVrnF23i/5twjH/nI8tSnPrXycu9737tYPGHBOTAeL3vZy8qjH/3o8qpXvaqOy3gb03z+zGc+U7FEDxq0DTtYG5NNmzaVK1/5yuVTn/rURFk94ogjqrzj+yEPeUhpsqSt9773veXggw9elPcf/OAHlR8yaI66qqfPeST94eMmVmYqHQAAEABJREFUN7lJecxjHlPe+ta3Vp6+/e1vF3Pl8Y9/fDnggAPKxz72sZo/TtP3vve9Ws/4Xv3qVy8f/OAHKz942Lx5c3ne855XZeDa1752+eEPfzixjfE2p/1MDh/xiEeUc5/73MvmABrRSy9I17rWtcpPf/rT2r0ycx5P17zmNev8n2S8qscwVpeeeclLXlI4l2SA3Jq70u1vf/tiHsK7djCH/5FZ+FsH3etS/2QQvxLezDHl1jq03vSmNy1Xu9rV6lh6Z1Iyjx/+8IcXPL/0pS+tgfPDDz+8rrl0pITn61znOjMfc/rjfve7X9WV+rX26xdPaDdut1pY2/ErfeELX6g0fetb36qySzeScfNe/fFkjTUXnvCEJxTycNhhhy3KOPmBsTVMG8adTIy3MctnY2oePvShDy1vectbiita8Q2Dt73tbdUmsL5d97rXLca70eNdfBtz+tX7rWx4Ve+LX/xiufWtb13MpTe/+c21WP1b3vKW1Q6AvfYf9ahH1bI18L9KAgys4cb5xS9+cUEvDFYaJ7yyUc55znMWOlk9c9q69OxnP7vKDAzIXe1gDf7v4x//eB0rtkEjDw7sQ/ODzWaOf+UrX2nFy64wYD+Qd3PmAQ94QLVJ5ZN382HTwjpI7uUte3mDPBj3b3zjG4V+I9N8CfZq41f5O97xjmr7vvOd71yRa/Xe85731HXUvPGssiubgkyx3dhwxkjZRkjdod8Io7jKPIh2ff7zny8UN4P67Gc/e7nrXe9aF+AhaSaTiJiImUlpkWbMHve4x62K65nPfGY1Vhg4lB9jV/1hG9O8R48oncl9vOMdrxocw/aVc9bwwlhhLF7ucperwQYGpQXqXe96V3UWGDfHP/7xqyKyqFtoz3zmM9cy7Qzb3dV7Sg29lPsb3vCGcuITn7gaDfActqmeAMPFLnax6uQcvODMMP4PXzD+fvaznxUOA0NDcIJxqWxaSg2vn/3sZ8tZznKWQqF+9KMfLQ984AOH5NV7NHJ8b3Ob21QaGTbG24L9zW9+sxrz6LMQnv70py+Pfexjtxqf2tCU/vflL3+5Oq4MbIuJfhkXe++997IefvSjH5UrXvGKxWJLbhiokkrovuENb1iNLzLztKc9rZgbyuaRjCGD4CIXuUgNNjD+GQ/mmXFpNLj/0pe+VD73uc8Vzi9eOAuCQ+TdOJzoRCeq48KgetaznlVPoHivtTHt6/nPf/5y0pOetJg7rW3O6F577VX1CiP2POc5Tw2StPJ2xTedcYYznKHyfbvb3a6OD+y1h0eGEJm/6EUvWoNygi+MTXOUY82IbO3N8gpDAQWyfdBC8BLW5kCS8vWvf73QI2Rd8II+nEQLx59RZ84IQpnr2lV3jz32KMqe+tSnFnqBMdTKlM8rnfKUpyxnPOMZKw3D/uFsXNH14Q9/uNAP++yzT53bDLmTnexkhU4ls0960pPKMY95zK1IJqucxR//+Mc1mMrBPclJTlJPT9GNAlHmMNm93vWuV5Js1cYsMug0gRoyR74a3+QTz2QYzwI1pzvd6WqgQ90XvOAFhdF5tKMdrQh2yxvSp53GM/3NQcCzOaof7+NXwrMgxvD9WdzbQSRnDWs64lKXulTFGr30KGP5Ax/4QA1MXfziF69kCNKTcXNv//33L3Sk+rVw8D86Vfvmh8AUJ6nV23PPPRdlXBCSDdHKBk3M9JYcC9pc9rKXXQyokFdBanJwpjOdqdLIeSATxhxB6CQL1gc2grmunWS5jGqDfNNlbCFrNvvDnKYT3/72t1dbg7zQYdZx7a+FhEebHS9/+cvrOo7PfffdtwaPzYXlNJZqJwoAvu997yv/93//V3WBNgTBYEBPCph87Wtfq2uWsvE21sLzhS50ocIGHPJIV5/iFKcogo6CPHQdR3USD+ayNYtt/JGPfKQGZo9xjGMUelHgEwZsOboCLmuB51nQQHasiexSfNtQGPoB1nBYmSPb6v/CF75w9SuGWNvouspVrlJtUvanwJq8bbWznsq6Q7+eRmsN0mqySJw2yudYxzpWsQBzDOSPk0xZWZwsQAwQBmiSwqHizJ385CcvDBsGgOi0ozfjbUzjGW0iwKLCHJqjH/3oWzWrzubNmwsaOJXqcCosPhT1a17zmnLWs561LkLKLnnJSxb1LfaMKguxuttTPFt1vEKGxfxGN7pRYdAIglgoLR7oHL4i2CB6eb7zna9iaUExNhwGi6L6Zzvb2WoZJ4jxzDAatrGr9+hhbHAmb3azm1WnXl6y3GChkO3aOBkBu9Oe9rSFsSpIYjFDM8zRzTiyU4+vMoO/JMXYcQo4EOhhXDC6GBjDLvdZcD4YUPLJrvFnnKvTnFJlxpzjf4ITnEDRXJI+nSYxh9CAj8tc5jKFLBjzRoR7ASGOvzrm23nPe97C+GZQMEDNT2XkTLCLM+K91sa0r7CUhu0yXDlkxoTM290YlrtHEwOZbDtRgReyo8wYClK4l6eMvDmRIjDD4eTku5/lCRD9S2jlCDFSOOIwN074TlIEDdHYknreG09w8F5LDBR1kpT9F5wk+UmqnjD+yuadkpTGF77Llj8BJsEGPHBM6Xz11BEA5ODQcYxW8pws1xvyOAp0hR3RYx/72Iv9CMAJCpEXeoMhTMa1v6X7mV7oUOvYpk2bFvvBFycWr8YJ73hOUk+m2WEm2/QER1d9abGBhRvPguWOIwviHOc4x1nk+VznOlcNhOGZ3NjZtnYmy3FbaGaq/9HN5o9+JXrnHOc4R10LybjAitMCAlcCnUmqs29dRCcZdSXzkwijf9QxdurZtVQvGenqVsbeoLuVzTORP3yd8IQnrDxbv/Bv7UpSjAu60Y9Gz8bRsWk802t0UeMjyTLyjbVTinYoBUrUS1K0dYUrXKGQb4kN40Vrj+taSPhk253qVKeqNoZ1ROBDsGNSsIq8CEwI0sELD9qwbjmF6H38W3ff9ra31QCAOmstoTFJDUg02gTdBPnNEfNcoJY91MqHVzvwgnP0HyeWrktSyBX5Ik/q02nWePcbLSUp1kVyDk+2tI0pMoDXJHW+le38Jan6JsmymuxdeguWSYo149SnPvWyOuv5oTv063n01gDtSQrlIjKZjCYPo8IOQlPOQzIdDxN9Z9A68ityqdxCSOGZxJ61Z9EUmaPc5U0zUZZ2h+y42xVKRrQP+9CvoAKaLJ7K0Mix5nhyhDk8yehdxqVon2CGHQgLN0fCe9NIHCvtJaNFw6mIy1/+8nWRH7Yv2MBotIjIT1J3utDG8WEQJiOaKUoR0cMPP1zV3U6w4swfccQRdYfOIu3487BhuDJyjUGSqniVkxey4ygjQymJ7IJGzryF37s1c8r/S0Z9adZumPFlKKJJXktJqkHBcGdwcUyMu/IkdYeZIWJhfvrTn14NL2XzSEmKnVG7gIwGyXhweIf9w5DTPpQDPJAb37WadxyMJNVxgL95YLzKHP8EWMy31qXgmN309tyuxkrQrc1Fi7Uyso5Pc1deMjKIGcEceEakoBde1Z91gvuHPvShIoBgh4VhwclDS+sbbXYmBLsYfy1/eE1Sd6PtigqecXaanCYpcOIcymewJEuyPWxnNe7322+/+inVwQcfXOBvF5a+TFI/d4GLHRiOoNNe4zLHwOMs2H1h+Ar2aUe9ZIlPz5/85CcLAy5Zyp8Vz3hwEsT6RtaG/eDZmqcc7dZG9AlYWXvUJRtONu2///5b6Qx1OfQMeesmubEzbn4nWdSfaOA0wSSJZmeWkiz2iz7OCMM7Sdl7772L48eCgIJnd7zjHYt1PEmlh44R1KfnOafJKL8WbvlfkvpJgXYFyc2ToYyTEwFteDgRmGzdxpamZnIxdsloIwL/xoIOFRDVofG03lr/nKARAJGHF2uttcwpNnOck6/Mey05PSX4pW2frbBTrKnKk1TsvUPHKeMAKVsLCc121+GRpJJkrTFm5m/N2PI/uAkkO83B+U1G9fHmFBk7MBnl7bnnnkWe9re8vt3LalcwF6yfjQ5j6NRFex5e6Wx2keCHz+acVIJDknqah41Mbyqzpg3f3Uj3SerJLifU6HBH49kx0+AxSQ24mF/a9dnLRsJyj2mA1NvoCECA8uHsisKaKG0BViYlqQ4Cx5TBZlH3bfrQoC1z+EMnpwetjB+LSkvTWCy0wRkRrGCkWXT1OS3WtOW7U7ht2rSpYjqttne3nSQ1gmox55hYfByvhW8Z/OFh8LhmbtEF2205QowShqodCMfgfNPZGGCccaDJwP4LxjmjrpXN+mrRs+Ns4T/wwAPrN+OCC3aCxvvG53jeWn7240qcXTtWycjAa/TuCi/mPieD0WQ3zBxt7c3qik4GGwfEJwL6JGcCf+jRL2cfXWTIsUPBNvnjiUMAD8EnBqITL60Op05wQ0BJYJGj18pW+2pN4PA6feBYtuPSMElS9Qbj15yyE+301JCvsvDnkyMBHKdfOIwcW3qGoQ/fhSo14MYQtKslMChvlok+cJzWjrT+6Dq00AGuSepOpZNrPol505veVNpJKXSp4zMMMnCDG9ygOmvyW+Ik4pnzCy+4wYf8eLfVw7PdJjS0vFlf9Y8On3/BW3/JiF+70k7JWAvhAw/lZJuN4ATFtmRcYFGgzpiTcUFq70tOBAjEkW9HZ42B/HklNoxTY8aSI2ZMzDvBlmSknzi11gjfjzvNh3/jzpH3uyDk3m6kMR/yBlOBbWMpGCKYKnAveEE3DHkUWHbU27wa5q+l+2SExzhN+DSHbVLQV8YQRpKy8frJ5HbG6+3G80xftc7YZHGSLNmaF+u3ueu0q09NHM2nSxBlHgiACdwIagv4TsJI3Y2Q6EObOOa+T1Ksc9PiyxyCJb3kEyXBRzI3rfZXs53u0K8m+husbwqZk+5HXDh0ydZKK0l1QBl1fvjDRGK0MQYoKKks/FFkdi9Ez5Kt21mossv/UY6OdnJ+9tlnn+K4GgeNcT1UlMlot0FHjS70UsqOdqLZs3LJvTzRaFF5StkOmnaVTyvBmUFjh4JRkyzHB25JqmGrT7RLjoajG52elblPUuDgeRopSR1ji4/IO1koY392kseyauRUgMXuB7paOVoZLKLdyXJeW51pXfXLIeZ0rdQmmbQT5xt6OyyOALe6jDBH9R1ptwgxxlrZrK9Jih1nJyJ8z3nBC16wOBbKeUqWcEtS0AlXCV34totkF4Sx6llZS479JUtteGceSf8Wdk4b49aOzXi/6DUmQ5qTFLLEoJbvHW25V1++I95OCTmp41irOrNO9J45yIilJxwt5hAJIiWjI4CCnHYmOQh229E9ThfHwadC9IzdX05SqyNAQPdw+jhU8Gtlq31NUnUD49WOLt0rMFEW/pLUMvqVEWfHzjpQBn/GmYzaeYcfZ4ZTxKFv1YwxXOCQzF5mOeLkSJDhNKc5TT0VYCeWTm3jSn8Ze6cPBNjoBvQaWzwaa4b8uHwrH+fZ6QRrih1cbUh4dirImprMnmd9SvoVNLTbZUzlSXA3v1wAABAASURBVElqgMYY0T8M87Lwl6Q4sUDGBZyccoMRPheKl/3ncyaY+H7e+NrZbhU4wZx5Tg8ZZ0O0snlcjafPWXxCaJ7hU792V5UlqT/yiUc80DGwIgMcCeufd4yXk1HmufdbEtgSJKGnObtOKNjhFvCDlURuBHHaet/eXe1rkjoH8IsWtLq3fg9lhEz4Pp6Dym4SrHV6w5wWGHfy07vakPDrU8FkfvKt35XTjpXgwXz3o34CU/TXpDeTVP1HRtgVHE/vloW/vfbaqzjtYZMIVoJFrWyheMP9x/4iG/i0Ptq8mhaT7FKfQfh9C6cwX/e611Xbc1rtr2Y73aFfTfQ3SN8Ui50kC6sosgVLXksc6HZPsUue7bo5smzRspspak+hK2cQMVosZtOGyYT2TaPdDhF2uyYWWFF232lZOBgIaHSczQJtwZUvIt6MNgsRYxq9yjiCvl+kkC3IFLdkEUt2fxFCD+Mc3Rwszry+5Uu+4XTFC6NRkEK5yLAFhYHEgIaxHT5ljCQLqAVjGjjrX7uSe33rM0lVmsZcvkUJnfqHncUdPxb9S1ziEtUR9a4yu9x2t2YhC+M8M87Jsd9KSEZjhoahDKM/ST0aC1O8aKfxTF7wYgymhav2dyTpm+xZAO0CC1rZKUtSv9ltO0ECEoJXeMOPI2h2DhiHeHc0HD/mAdlhUGp7R2jYlTpoaKm97xkNAhR2PxnA8iT5aEO/QMS+++5bnIaRT5aSFPw4dk432eVUhk/OMIceTpxHc9Scbf3O6pqMnBk7c22uop9zz3hHn77hLI/sNJln3LWd9laPXjFeHF+OIFy0l4x2SB3V9T4+tTvPhJaWhv2iXVJm/Iwph9wz2luZuU/HKVfW8LKDZbzt4KibpBrBxr9s+bObbVwFt2C5JXtmF/LDmbbb6Nt/BiKn1ckkY4POlugXPJlj+KJX1POsHUTKlxrPdIngAF2pHXWMfeNZXU6xsdaO8nkla7axEhBrWKOxpWR0XNg342iS74p+c5DcolsebASr3Q/rtbkgEIdXcpKMZBzO8ucxf9HVUpIqd4ItsOdoOSnA4USjlKR+LiYAYy4nqf/qg5MJ9LM6eOG4CvJ5Jg9l4c8uvuPZsJWvnrmu7kJxXUsdVTfe5EPeWklJ6q+9C0CgW3KKzXpIF5EZfJrLTuGwZ8wbQWjBf7+Or4xTyw70PgzYWrNeh3YHQzRK2hhe0W+s7ne/+9XPI5VJZJwOVN6e5blnowmSmVOe5SejT8bIfJMDfW20hFc80RHWReuYeSavYdHuPbd7WDb90fKUt9TytJ+kfoZqjeF/KNsIaY+NwETnYfUQMFlMIlFoBg0HWeT8wQ9+cP0npjgQFntHzRyho4gob46punZSkhRBAArc99eOwziqLZpJwU+bO4sKJWG3pO0SMSwYgIwDEUHlFC2jw064I3Po92M/dgvRy1FlOOKbA4QfPwRHCU+bZu0x6B/2sIfVX3q18w9nx/0snJxe/KCDceOTBkELO3fGxu6RYAUH1NFN0WI7AxZRx/+8o4/dTQyVNt4CCoccckgRDU1S7FbbWfPtP4yMr91sxwvtyPkmnbErampc7ICTG7ySi92lbUfe5/BxgI1vMnLoYchQsxAwPhp/MLcDbky07agwWbHjaPdX4MiOjbJ5JHORoYTGAw44oP4av7FHh/43bdpU/7nDJIUMCOo4cm6Hzdj4ASL4m3uOMuONcYVfTlQywkNb004WY3LMiOW8Nl4cVxWl9yNB5F2QwhiZC+YoGTZ3yYc62rCj55QQh8epFN9am7/0ivlLJr0zbR62116S+s/tmIP0HjkRRHSPX/rHroF8Y2jXl75URq7oHXpz//33r/80IofPUWbzl56in3xnzXjm1HIyzXNjuj3aplmOXka7eWNtEGCRpw/ziM7Bh+/C/Ugch8TcYvD7zQOOq/WDDqOrjTFdK2DKyHPqBzbadxLGu4KSyUg+5TuirL95JDSij/6V0MIhcULG+mC86WI8+97ft6HWGTKMTwEea4jTbX5TQPCJTiQPdrDpSmNMxgUy/POpDFyGfTIKlHJ2zN9p6fEdxc1c3Wth9zAZYW8sjK8ArCC446wCFQK1nBRBenIpSMgO4ARzZr1nvMkDHQZHp1S8ox49JgDMebY2kAX35jO9Ows7YVsYoNc8NZ7mHD3lM8Mk9Z+BNRbGlc4x3tY3Y2MX2u5jm+fmv3L6yG9GOFXS+IeBH34UBKfb6C1zJRkFSfRtU4F8bIvWeZehR0CC/sWTOU3HcVDNFcEPjhQZNkfwKZFnsiJIYc1yCoP8mAPagYux1/68edqR/tBnTTVH6T86j4z4IUg62e9nWMN8Dkc2zH9rmHfoOHxb6zz7MVf2EF6tZ2wo8m7tIw9265PRnNsR2tZLHfPKZzh+HwafZNy6IKjXeLCe0KXwYKPLt87A0okVuGuHLQp/NoVy+XQnW5i+lMxPOhfO2lnvqTv0630E1wD9JowJx2GkpCltC3hT2hwEUTBOkoWMwWUX1CKoPhaSFLuJFjxlJjIHP5md0kpSv1dkkHAs0Z2kMI4ZT4zHJIWT7ngdh91RfQ5nksKI4HQyOmBg4dlnn31qm3iadqLo4SpqCTeJEoMrw9/3QDBPUhgZaOUMc2gYA5SWxBh2MkLUmKFpUU0yFXIZqhZubRtnixGHIhkd62d8WejRYZFy9NIiRkYYPfIZPhxK8sRwY9iRr2Q6NG6LUbRyfJOlvhicjnYmKQwP/3qBXWM7LfghN9pk0AlYkF04uOJF2bySTzEcVzTPyDQZbn3DVxAlSbFzCGMyxYEgJ2QL/gwL34f6nQnGp6Pd8ls7s7j6bIEcMvjxoA+0cWoEEzhG5N3uOpmHqzna5MLJGPLOMaI3OPRoTlL/KTtBGnqFYcnhSpbGV1/zSMloh4UTiieGrbmCbzqIsWeXUjl+HMdPUvUJ49buFPn0w0iMk7aza/fTOMNCwMNRbLqIPuBoJpkHe8v6QIOdV/PDcXL0qiBAlKQIWDg9Qde2cSJnDDIBVU6hOZSk4EvgUjBAXc6SY87aIBP0A1y0L9GPglDJ/PhOUscpSd35YXAbE/Q6AYYuwRdjyjH1LADjdA9nDh/0CHn3POQ5SfEeedeGukOekxS7t5ydJJqeWyKvxhGfOk1SyCP8BQs5aPSicjIuKMXxIePWVOtQkrrb7XSf9Z/cWKM4PGTcfBWghCfs/JOigsL+KTgy44RHMl++y8Kf+Ysmcw3teFzIrsfNrbnWCCf62AjWsmQ0/zmnHF7v08fWFO24OokEMw6tuUI30NOcQtgkIz45KPJmaW/gZVcTfuhjdArK0+kNAyfw2nqq/SR17pB5x6zNg2Rkh/mkQXCLLHCIzQ3vrMVkPMm9T73IJxoFmOlygWXzVoKDIB+MzGlBGnqADcTJ9E+pWaub/jNHbAw4+WPuCACRtSS6aGlDXJMUDj25Mfc584KZ+G0MshfNE047W0e+cliyvzxLbBq2O8wFF+UZH/NGwIR9ah0xDsnGwHIPTPbUEdhVBJLUBYwhOUyccwqJ4W0CWcxNLBFoEUoRfI6SiajvJMVCbuFm5DJETTRls076FVxo/TEIh5FviyujxQ4CBYPmJNUI4UhzHighQYtkdorBUX87dUOcKSz04QEN6ElSf4SJgcD4YQioU7b8ufddozGCswV0S9FuX7TFuKGE7QILeiQjTOxaGXv4JqmGr4UKro5HM2SS1MXde5wYu3Ft8dtt4nagAePL2RpWZUTAORkZznDGn+8fOcbkQX1GGnphbhEnT0kUzS2JPjMGOAac4GSpf7uWxgQxSeov4jMoBTAYU40PV04z+TBP8Z8steP9aSffx5NrTihDX/sMIzgPZR6++EKjOUqm1IU1w58scXyHsmRu0Dv4wZd3k9nyg6ZJKRnpOXPEXCBvdCSajI08+gSd5pI2ktHnA/KS0T9NByty2OZvkqqPBMm0waGgL7SbzJfXJIUjgkZj5/OOZESDeSHf2Jln6CsLf0mKemhnwDJyk9E75I8BZ71IUo8xa0dd40oGklHdhaaKIBR5Tpby5M8rGU9ObZI6Jo1WY96CmWXhj5EPCxi5SuqQb2vnHe5wh/ovyCSpn/e0dqyRQ56T1H8mreGz0PTc/oNzk0udJqPArbGhW8g3fpJUvS7YpkzAQ/AOVu09a0ELSPvUDR7mAofdXEhGbZBtbZD1YUBIO/NKyehfZbAuCDTRP0lq9+4FfdFPfw7XiGQ0/xsP5gkMkhROnTmAV/PCGkiO8Goth2PtYOF/9BvZT0Z9LmStqf+S0alLa4u5u88++9S5gEjzU5DHfUvJaG1l++FdfpJijpgHdqvJdytTvtZSW6vMZxsqSeo/OUcO5LlKeGQLkxN6UDDSWLtnOwjeNRspSaHHYUAOrOHqJrs77msNvRE9SYrAJBzoD7oFTskSv3BoeNqE8Ca5gB99lKTqGvXYEzC31iSp+lS7yqwz/JIkmtgQaY8NwUVnYlURSFJ/AMfC1FKbhMmoLEmdZCaeOq5JyvAvSVX63lVe5vSXpNKWpPaYZNmzTPRMoitJ5V1ZkjLLvyS1L/hJ+pSSVHrRmKT4S7IMy2SUXxb+kiyWJUv5ZQp/SRbbHtJTFv6S1LJkqU918OBaBn9JKq+TysoM/5JULIddJKm0JKMyNMEfzUlK+/OsTHLf8ud1TVLx1X+yRFfZ8ocmactj5VNdKVleXz35rq3+LK/6gqmrPpMs0ie/JeXoSEblSTzW5D3lrslSfpJFXJSVVf5LshU9ySgPn42HMvhLUt8pC394UEdKlvhcKKpyKl9Klpcpn1dCI14k98mIFvdok5JRHpqSLNKuTrK8bJiXpGKhjWF+2fKXpMrOlse5X5JUXpIUf2iEA3qTUV7Ll6esJXWTVPrbvbqSZ/WlJLIWk7Jked5i4QxvktSxKIO/JJV/dKKrbPlLUuvidbysLPwlqeVl4c976kjJEl9JFtseLytz/EtSaZ1EQ7JUtr1yfJYtf0lqm8mI3ySLvA7rlYW/JLVuWcN/SRbpT0Y8lYW/JBNpT0b5yfK6MJSSpfyyBv/QOC7bxq3lK5M8Iz9JnedJPFZMlHknGeUpSLKI43hZmdffHPvBIxwk98Ouk1QsGo6tPMkyLJNUPNWTkhR/Ser7re1klF82yF936DfIQHY2OgIdgY5AR6Aj0BHoCHQEOgIdgY7AaiHQ+10dBLpDvzq49147Ah2BjkBHoCPQEegIdAQ6Ah2BjsBRFYHO95QQ6A79lIDszXQEOgIdgY5AR6Aj0BHoCHQEOgIdgY7ALBDoba6EQHfoV0Km53cEOgIdgY5AR6Aj0BHoCHQEOgIdgY7A+kPgKERxd+iPQoPdWe0IdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2B5Qis56fu0K/n0eu0dwQ6Ah2BjkBHoCPQEegIdAQ6Ah2BjsA8EVhTfXWHfk0NRyemI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BDYOArPlpDv4EUN9AAAQAElEQVT0s8W3t94R6Ah0BDoCHYGOQEegI9AR6Ah0BDoCHYEdQ2Ana3WHficB69U7Ah2BjkBHoCPQEegIdAQ6Ah2BjkBHoCOwFhDoDv1aGIVOQ0egI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BHYSgZ106Hey9V69I9AR6Ah0BDoCHYGOQEegI9AR6Ah0BDoCHYGZIDBbh34mJPdGOwIdgY5AR6Aj0BHoCHQEOgIdgY5AR6Aj0BFYUw59H46OQEegI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BHYMgfXs0O8Yh71WR6Aj0BHoCHQEOgIdgY5AR6Aj0BHoCHQENiACRyGHfgOOXmepI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BI6yCHSHfqWh7/kdgY5AR6Aj0BHoCHQEOgIdgY5AR6Aj0BFYwwh0h35Kg9Ob6Qh0BDoCHYGOQEegI9AR6Ah0BDoCHYGOwDwR6A79PNFe6qvfdQQ6Ah2BjkBHoCPQEegIdAQ6Ah2BjkBHYLcQOMo59P/73//Kf//735pWQm5YR13PK9WdT37vpSPQEegIdAQ6Ah2BjkBHoCPQEegIdAQ6AssRmJpDz+mdlJZ3t/pPP/jBD8orXvGK8qlPfaqgd5wied/97nfLy172sprU5dSP11vTz6tEHOxa2hYJ6sBUct/quh+mlj/r6/b6HJa7H9LjeZiGZbO4b32NYzfe17bqbatsvJ1dfdYHGiX3K7WjrKVhnZbXrsOyWd23vtp1W/20Oq7Dep6HaVg2y/uV+hzmu98eDeq0pK57YzhM8pRNO2lXWqldZdL2ytWRWj33w9TyV/u6Ek3yG94r0ajOMA3rrZQ/rDOP+0bHeF/yG3/uJXVcJWWu8lZKyoep1RvmuW/587zqVxr26RlfLY2XKW9pWDZ+3+q4KnOVWrvtqmzWabxfz1Lr132jx/0w33NLLX/82srbdVje8lyH+fO+1/8wtf5bHv7dt/x2lSe1521d1WtJvXav7ZbkKVtLCU3DtBJtrQ5e3Ld67iX5LXlu5Wvxij5pSJtnCQ+uw7JJ9+oMkzrDZ/fyNnLCI7wk941X91LLd9/Kxq/KWhqWtbx2HZat9/upOPTA/eUvf1kufOELl3Oe85zlmc98ZvnTn/5UPv3pT090mlcTtJOc5CTli1/8YvnWt75Vd+n/85//1GujiaN/pzvdqfzhD38oT33qU8vmzZuXlbd6G+k6DV5Mjp/97GflkEMOKR/4wAdWHHey8uEPf7jKydnPfvZ69Z73jzzyyPKABzygnO985yvPfvazy7///e9pkLbNNvT7q1/9qlz3uted2J/y733ve+VqV7taueAFL1je/e53L8oD+t74xjdWHq5//euXH/3oR9vsa3cL0QKrG93oRuW85z1vecITnlDnmfxh255//etfl1vf+tblAhe4QHnGM56xyJuyL33pS+Wyl71s2X///cv73//+RX6GbezOvTF+05veVIyvdMc73nGrPtDx17/+tTz96U+vND7kIQ8pf/nLX6rcKPv9739f7nKXu5Rzn/vc5Q1veMMi/btD17be1adA3g1ucINynvOcp9z73vcuRy7Io/zx9/72t7+VRz7ykbXeU57ylEXa1D3iiCMKWbjEJS5RPvKRjxT6Zfz9aT/rlwzf//73L+973/uWNY+He97znhVjQcpt0aPsK1/5SjFel7nMZQq5p9cvf/nLl3Oc4xw10e/3uMc9thrPZZ3uwoO+n/e855XnPve5E9821x784AeXH/7wh1VGxit5/9WvfnWdo+QG33CR3N/nPvepGLzkJS+ZOu3jtOzIM3rpkjaXPaMVfxe5yEXq3IH1Rz/60a34VRdO++23X7nd7W5Xfvvb39Y63jfvb3Ob25Tzn//8df0yF3eEnmnXQeMHP/jBculLX3pxfrQ+zDP6i27A4yc/+clK/09+8pNynetcp+o28+rPf/5zzW/vtevf//73YhwvdKEL1Xn6xz/+sRXVOXvQQQcV2Lz4xS8u//jHPxbL5nFjDMyZe93rXotzXx6e6ZXG82c+85nKGx1oraOnH/jABxY8lxX+jCWM6EprERuGnXKNa1yjzs3hHFV3hWamkv2vf/2r3O9+91vsF1/nOte5FsfafKUn5EsvfOELK7/oOuyww6pcWHN/+tOfTqRHPRhd4QpXqGuvjRh5KhvTQw89tBh/us34w1jZPBMMnvOc5xR83/SmNy2/+c1vavdoQe+Vr3zlKsv02nBc8QEDOra+sI3/qfuhD32o3PKWt6wyrW162bxp4w1fOnsbzcy9CJ3G9sY3vnG52MUuVu0MeeOE4A8W5P9KV7pS+drXvlb1s7rG3xgP+Xz84x9fy8fbWQvP5IE9Q9YbPfj43e9+V+h5fCj/5z//2Yq3usLDHGcHw2Tz5s113tDx1jV4vOY1r1mzGGzF0E5mwIt+53uR8Zvd7GbVDoGLMvru9re/fdU7D3/4wyfav7pUlw35sIc9rLz97W9fxEv+d77znWJu8lff+973LpZ5b72nPabBAGPyIgtGyEtf+tLqLJ/mNKepzsLxj3/8aTQ/1Tb23HPPKiAMCs6RRZTiMdAmzSELDukTn/jEwqm/+93vXs561rOWPfaYCkxT5WMVG5vYtQX8G9/4Rg3mNMdsUkUT8wtf+EJhdJqYFNcpTnGKavw8+tGPLqc+9amr0/zxj3+8WCwZhpPamUaeMadcn//859fg06S+GAsUwmMf+9hyt7vdrXAMjjzyyOLdH//4x5WM1772teVEJzpRsXhRRnj8xCc+UV7+8peXz33uc1NTGPpkpDLg7nrXuxYLB6VmIamEbPmfepsXFoI73/nO1fHk0L/jHe+opQx+Tpug27Wvfe1y4IEHlsMPP7xM849h8653vavc9ra3LcaYUk6yrAsYMWQZPur+3//9X6F88UIR3/CGN6wBQny85S1vqc4xvpY1MsUH/Zrv5r2g3ulOd7rCWETnsBtyLpAi3xhz4BkZ8hlt973vfWsgwskesiJ4NUu6G21oEUQRSG15aHrEIx5Rzna2s1VHH84vetGL6lxrddpVkOJZz3pWERSw2L3+9a8v++67b/nqV79aBDnoRHzf6la3Kqc//enba1O7wtziyhkaxwsfjBj8MebHO1VfsOLNb35z5XO/BUf34IMPLuaiMvdnOtOZivYFG1/wghdUR888MEeNkfEcb3dWz/SjdYdTao4wXK0xaIUDp5ajbu4w6pLlcwe9dOahhx5aGIuMxEY/458MG3fzy7xvZbPiZ1K7jFJ9k59h/+4F+jlA+MOn8cI73UbW6C366XGPe9yig9j68L4gqiCA9k95ylNWHQZT849ehA0crCFvfetbp6Z/Gw3butKvj3rUo8q3v/3tukaoi+aPfexj1SnDL74FKuWTga9//et1zWObPPShD62y6b1hMgfMX+vmqU51qkLWz3zmMxf65ypXuUoxPyVG/2UWgnHDd2dxT0ez8/QpCXCyAVtf9PqxjnWsGnDCryCnMbbWCNawFe9whzuUa17zmoUdpqy966oeHMm2uUJe8Aozusk8sS7vs88+Vd8af+/NK7EV2A3G2xov4M8hJffWEvrIWEtsSgG4xuPPf/7zqovYQS1vnG75dHKbxxxCMk8OzH96Gu6S4A5Hb7yN1XyGj6A4/SbQam1/5zvfudVcZHMba3hx/I1zW8MENw888MAq29YemxB4TZbrw9Xkc9g3fSNIa260fLYi+b3qVa9aN6sEd6RWPrzCDEabNm0q7A92z6UudamK2YMe9KAaGCHz1kL2BVkYvr9R7t/znvcUc4hOEfBkc1jnzHG2FkdccJ9u92yuTOLdeNCT1oVWzp43RuRJEIyMChK08vV+3WMaDHz5y18uDPK99967HP3oR68RVZFVRlQyefIZBAJMKA2eK2UtuZfX7tVD5/CdVkdZu1e/Pbu2d+SrI4lqm2Qcx5Od7GSFwmQAqM+4c88APtrRjlYsoBRlM7bU0YakzUYPWluZq3zJvbrKJe+gaSMmeF3ykpesRgzel3hcupMPf4aoScTRs1AlqYapHU1O8clPfvJil4WjPJyMSy1N5w49aDnDGc5QyMKkVhkljCTRVY7OcY5znEUjk7xf61rXqg4Tw4SDb4w5EpSSCCOlrJ9Jbe9sHmcHxjATsWf8CaJMcnIYGHbp7K4yABke+jvhCU9YbnKTm5SzLgSqKDTvolfZNBL+Lc6MnBOf+MSFcW6hTpbrgVaPYnZqhoFC0RrvzZs3F3LCqd9rr73KlRd2OpRPC8dJfMLAzof5T4fZ9WBsjPeJLka4cT/2sY9drne969XTJE5n2JE0Dy5+8YsXhqYTEmQYr5P6nGaePtEzpJfBaIcXfsb95je/eQ0C4WvYt3csjhLeBIyMCb13kYVALaOM03DFK16xzlNG1fD9adxbpAUKxrFCG1mCq5M7nsf7E0Bi+NMd5AWdZMh71ib3jG0Y3OIWtygMcUFoAcQznvGM5UlPelIZGmHj7U/zGX92bxn16OB8kbckdXf5yU9+cnXS6BN6h5M33j+sjJGdQc4/XlqdNu8vd7nLFfMeNq1snlfr63777bfVesAwEziiK80hDjge4YFmjh+Dlm7j6Fo3h3RbUzlHnMSTnvSk9TSJE3ccSAGaz372s/VkkrEmD/D0zrCNWd1b650mEsgzzk1W2RuCK3gWRG3jii42h51uvJCLww47rJ64GNKoHUEQWAngNqc+STnLWc5SnWbz0zync+n84fuzuD/BCU5QOOT6ldDBCaEzOKIcWbryohe9aEG3zR2Y4NVaSj6c3iD7HD5lQzo5gAIGghZ00PGOd7yqu9QToNY+zKxhn//854vxH74/63tyLMgP62Mc4xjlgAMOqAFEQSZOPdk21ujj0MEC7egShFpJlymX1D1kYXNJsM98odPYIuxs6zfHF+4wJFfuvbcWEtoFsDhP7BVjzQ5gF4zP5+Me97iL9gjdRQ+bR/jwzNbBG/2Nf/KQLLcl1F0LyRqMV/w3er7//e8XgSm2rnETbGUbmtOtTrtaq8xv65E1l/5OUsj3l770pULWrMvsCoF5eqW9u5GudILNFGugIC9Hniz94he/qBuBHHy2IR0hsLcS7+xOemqINRkyBnQQfXnMYx6zBg9WamO95U/FoQcO4WN0i65ROpSdgVkJEEL/tKc9rVBMFmdCKvLkyI2dUMra4kaRWQwNijK7aOozxhiWlKd3OWWcGw4awdeWd/Qjj2K1YJpcnHRGEIXLyKWcHWNDj916x5A5QJSwoAQetM3IIEyMDo4aJ4DBINpuUSJgHFF9MvAdG9G+hY9iY2ygSXsbLSUpySitxBvejzjiiLrzynmDvyis+nbOGON77rlnbYeh7Ziiyew9daaZtGl8GRqOR5PZSe1brE16jqaIn7FnNCUplAMZp2goFpFXeZwPbTI88auvSW3vbN7eCwEzC7j2JXRwQN0P22JUCTxYPC2s5ga61UGv+hTkq1718R2DKgAAEABJREFUqno8nCOlbBqJ7AvICGbYYbPjZi4M24YHXIwtJxT26PLuN7/5zcIwZyDCXRnjnCww+r07bGta9wwLzhEdwTG3403vwHLYBycRDXhMUiyw9IBgAIfYGKE5SXXq6Q2G+7CNWdyP06kPOzmcJYuacrLCwRMYwoM6EsPAyQJ6k7yYm+RDGUOavHhfEI5j4XSTZ+XTStpLsqw5NOqTw2bxRceyCgsP6jBo6XBynqSg2RjgxRpCxuTpwzqFf4lzzwGDSTMiF5qc2X9otctm3nHKnRhAH/lQZu1hhNBLHAQB5UnE4EU+J4ahx2FKUvUmOTbvya8TFuZfEtXnmpJUepIs69d6zUGzc8/pofdV4OQwiI0xXWBekVfjqLwluoS+dSIqSaGf6TrtSQxqMp+kWE/s/rY1prUxi6vxM54wR1vrQz755Ngy2K15Tg8oRxd7yXgmI17wy87xnjoSvShgxakhq29729sWP+/CKwzItnecDDA/k+W4a2eaiW6W9JukkGkBGc/mrHUKPeSYLYgHzhp5t96oh1frPFyG8w8m1lr1yIN02tOeth7HJvNkiE7zPlmx5lo39DdNHrfVlp1DCa/qoYP+sduMVmOAPrSzZcl3MhqTJBPnhnZasgZygG2MwYzMWGfgZo5rO0kN/tGN+mjvrvbVONgZtRaiVzIvjBHdNKTP2MGO/jbmThwY22RJjyepQS42GL0wfH8t3eMzyTKSbKqw04yXZOx8erOs0sKDIBi/xnwg4+a4Ncq84Y/ABFbaEOiiU8ynhVc31H9JitMMZMLcwbM129X8ohNgoAyWNl4mAZBk4hyjK+mtpmP4n8ZnUhvrMW+PaRBNWXGgLbaMQgvVttolpKJUFJUIDMeHA02JUQIWrqtf/eqFonesmFNMiTNcRFfUJ+AG2GBs2rSp2OkQzeRIMYooW/2I9Nil4qw7tmKyMNztUKqrbUrCTj0+BApEBNGnHYqSASEiTNBExgQFGPuEilHCIGOMiaqJQHNUTE5RWDte6jva7TnJtqDZ0GUUHgyNn0i2QJAdTgsAwwvzyQifJIWSg638ldKu5nNYHN0TBU5Gfa7UFodH0MiYUq4WcTRLDHRHwfDEoLPjbeGxAIu2MjDVW6ntnclPUpWUd/RDtnynSEHJGyaybyeHwkIjx7KVw9RRLjtJ8qe5MJgT+hREM8bmrTmDnta/K+fcdTzBGr7j+TA0p8fzp/WcpB6JYyBz9DgJdFGSZV3Y3UZLspSPN7TRfyono7Iki78LIH/eid4a0pqkRqPJTqMF7QwphhZ+GRQCU+SdHLd6rna6RcY5yJ5nnRiwdKdIvfFYqT900q/KkxH2+CZHMJA/TOqSS8aj3TNrifrDOrO4b1gzRBi4djStOwK/ygTBBIgdKYe/nVz0T6LNbyVYJxn9gonDOtYhc5BTP+4czoKvnWmTMWsHyucTdtDpVLogyaJuM+4+i8A/w27YPjthyGsro8/NzfbsmqSeECAfnmeV0MNWIVOc2iSLXSWpv7VhjDk51jtja0OhjW2yVF9beFlsYOGGbBhvu5OCHPS5jQUG/0Lx4n/aY3tZc5KlNhcrzOAGvXS2o8L77bdfHUN65OCDDy42OawBjtdbZxjReElGtCWjq/GWjzztsZ+GDr58ybzFo/vxpG3vjufP6tk4CJL7LFCQxfjjkZ5KUnHQNxtGHTu07B95O5LMW/zSx/QE+aELhzy6F+wUPLHu7ki786iDLgH78b6skW2ch2UCmOxC9hI5Um9Y7h3+BZ+AQzYsW+v3yZIs4IOOsGGZZJF0eNnJ50OY43wTc9y6Z47LX6y85cacmTRHthSv60sywgZe7Gh+Gh8tyeK8YsMK4PL9kuwUv4JH3uNL0qv0rTHYqUbWaOXddug5AwChxF/5ylcWO552uQC+LZ4pIs6yaAtHngAbONFtykxEhvFImVGEFn6DQNiTFDsTIvqcGe9S6IwF0VHPdsQJA0XrOwvtWQwYo75LRJvdAREf93bPLSSiQSaKxZfjn4yiz2izq0Jx6ouyTVIcaxUIEATQt91EC5hTAGhgkKDBrkSyc4KHro2WktTPMoy976MoftFG4zPk1QQztsZ+mL+b9/V1Y2dxtDPC4BANNcmduphkMDL4LSgCAIwXxiZlk6SeNiADvvdRbgcXL3aH/D4Ap4Ks4qd2PoX/6Zu8OvkhKDIJoySFU03G7XYLVDEudK++nVaOgx0FO9LTpE/75om5hQaL1Xj7MELLMKljTFZatDnbw/rTvNc3OXCSB82CEIKAdMGwHzI5fHaPX7Qx5jy3pE18Jqsz71vf6ECTq3Ghkzy3JBBhPnIQHeM2N+hQOyqtjiAAh56R0fJmeUWr7wU5vwK/Pl3grDg9wABU3vrHkzHw3PKTFO8aF/nDpD6dLRAnACvKP+R1WHfa9ww064++Xc1hc5NTkKR+ukZ3bFoIUvsMiNFSJvw5uWaMrLWCAta2Vk2gz7wXIFA2biC3eqtxTbLII4PKnBliT7cJUAjEW+vbuJYtf5PmnyLtjJeRhSTFmq/OrJK5IbBC3pz4kAQpXAUTkizyTL+ghwyTzWQUdChb/pKR3G55rBfrI/7s7nOayQu7iw2Fx1pp4X92ydkh5HvhcS7/6Z+dJcAwxN+44dNOtWPTAuFsvWSJX+8ikr5PRjoySUF/MnpW3pJ8bbbn4RU+ydbvDOtM8x4tgm9OXvhsjI5iO7BBkxEdZNkpqcc85jHF5tOO9g8X8mNtt/tOT7CVbBoIBClvbbE97Ngmoz5b/mpfjcc4DU3ex/PZJ4LK+IMXHT+sw4bi6LPBk7XF55DObd2zI2wSGktr7Xhd9iefSZAIHsabremU1iSZN2fMp/F2NsozGecbOHEkAGK+Nd7gZJPWKUlrXLJzMsFHY6uzKay7NpX119pfz9fdcuiBQJkzCJPUHwazc+2bD6ArlyYBZGGzK2un0G4CA8TxIvUZMQRakIDQelbXwmCh8CuFrT6lySFhHFg8GDkMVsaQXQD5BlA9BjpDShscL44dw06fFIkdeTv+lKYFU+RTGUdP5N172hG4cBLBJNW3wAOjEK3e049fcE1Sf4CKQFL8yc4J3iTc1lse/GDmOkywFDwxNsZZcAZ2MFXPSQrBnOaUTJNvfejbosnZFkDi7JIzQR39j9L/6g6PvikUCwpDG22tPBkZjL5pZ2RTzAwbR5h9I+uopGNXyXTGHpb6Z+QJGKFNQo8yV0keeSSXIt+CbuRdWTL6XIB8+4SFUlN/Gkn7kraMsTHkJHqWWpnfqTAOQ5qNgcXMrkQLAqhvYbMI2hVJpoMjWoZJYMMPcfl8xtz23aLAHJlEAzrVt4C4R5N8u4L0jWAe3WL8lSvTJkMODt6ddxJUFMmHK3rIO2dRtNtzS8bIWNilJzPGhv7mqKBZPThYQL0rbx6JAcghMkcl2HL+OK9oaolcCARxltFlDuPFiSgY4B8O6sNA0Nj6IODmNIIfyDEXvDvrRNdZy8gErPfZZ5/q7HG60SclqYFxu/iCYmiSL7V77+PBKRz8kMNWpl3OsCAjOW3jqHxeaUjrsE/5UjI6Eo9/8qeOeWPe00fW4mQ019VX5uoTOPPNmLZ31MevZDdLPYnscCxa++rPIumL3SBw3xJ96x6dyqUkRXDYuNIXbZ6Ze8rxaLMAH+iUJ1mrktQfxzLuxpdex596kvfYMBx6z/NK9ATj2qkDtOkXzZJ7efg1D+lwzqf5q0wdBjsdaX31DAM2AXzMVXmSNU87+ObMkGn5EtknF9qcV8IX20RA0O65YCOZZcMmo7Fip9JDNoLUR+u26FOOf3XoNHKdpOoHeoNjR0+UhT91OTzq0AMLWWvmvyQFDtYMdErWQuM3HGcEK0tSN3nYzDbRjLuylnxut//++xdrVzLSCa1sLV3xMokeY2oDhV3IjzB/1VO/JTqcXJvTZMX4t/WPXMlnv2nLLr+1mC7RzkZLMKFXBAEFCs0zPMrHP3mg78iKtaCVKZc8r5RaOTnke7Lb6ZaWv9J76yV/txx6TIpM+jEzgEicI0axe0fgGS/u1W0pGTm6os12fbzDGSfwopwE2+RPRpOX0jKoyoHPSXKsjBGnfYMj8pWkMNBENk0KC4dFhBK0w0rBNsXPWGeAM/4svo5e+N7LZKOcOWEEiuCYOBZmC6+ou6OMvk30rj44eWjAn8VFf6L1lLkdEnkMs2TEj3obMcHIhKN4Gn8mpoCIKKty3xnDTD1RWYuh8TZmDBnGgXp2PBzDcuKjtTWtq4VRkMW3faLnfvdAYMcnGYw/C5EIHhoZiGTcWKOLMhVFTVK/6XO6hHyT0d///vf1n9NIUhdhMiGRxTKFP/3YvUKb+UJOBSHIG4VPxgWjPAu0kTtjgUbOP+MW/eYlXsi2+cPxmQJ5tQn9MSzRAzO73vqGAVx9QsMxM5fNN/NQ3de97nXFYmeu2Sm2mNEr5iaefY9vbtZOpvw/uMLG/OZQoJXjSr8YPzjBVj2Lq+AT2TW/BRb9QBnj3FF9+Au24NE4WXRmRfcQBrSYawzdls+4ZxhzhsmE0yg+ESLr5BV96jKWOA2CoTAg73aazEflEhkSaIGH52kn2HK6yaW2kxRHLNsctStJTu3ccr7VRz+9wil0coBuwb/TKwx/8kSWOBHohwF5ZDhaP4wLfiRjrt9ZJn3QaWSD/NAvxkagGv5kiYNjHM1raxpnB03WHOukcTa//GaD98magBkMYKcN8149PDNarEXamHdCjz7R4irZfWOQGT+7i+iz1nuGiTEVNKPb0E8mzD9BdDJLL3Ae1dO+UxzWDkdVOU4MYbtadI9PoJxgsL7oe1YJTYJD1hJyKoAqMOnKUMdzGy+76uTXOmMdoh+sdXhhWwj8M9bx7Jes6RPyac2xo0SG6WxXTnKSGnTWvt1cemxWfE5q13yzRpOxZEQLGaZLlJFFtDqhSOcLlNpMwZ+AB/1Ob5obfvPCyQXzkr4XvGMP+nFEa4dTmtpwtVljjOk08mKeJPO1r8is9ZQ9KphIRtmp8s1R40kuyTtezWsYKjferjBqeeYy2aWD4QUT89mz4/w2DMhNkhrcIR9+aI18aGOtJHTbpLOu44m+g42NL3ORfFjv0euePOBR8JG9xV5QJsEIdmTb81pOaDWe5N09WvFlLtB1dBP/BT94pb+bHiMn9AK5ZkORfYEtn4Ra2wQzzA2YquPTHUFEfWykBDf6TTCaTWVewULwyvyxXlrn2TVtjbAuNCzV1wZM1Id/m2vyzVd2pTGSPLMHkvnqDvTNIu22Q0+BMY7sXjJ2/QIppxqxdrxMVvfDBFiRFcqLEJvAwJXP4Cf4Fsn2DkMO8NqnCBiWTgXI04c2OAImCcVnoA0wBXLggQcWDrdFX3sWPkaCyUHpWlg4mBYKxkUyOkbvyD06TCRHUP1TK3g0GR1VNgEpauVDhcp4ZCATEsYboxgtFJf+N2piWFtcKCNH0BifxpMx5xsyk06ZExx2QBnmxpRWxQcAABAASURBVIzRDhMYcqwtUnBjmKgjX/m0k0WnJQZES/phRJFjCsECYxebjDHQOEQCQcno10d9B6qMXDqZsTOBG33taIKluaQ/8wtucPLPblDy8GdQWkCTFI4QOh3phTODE49483sQxoDStGAwHpLpKDRjLIjlNy186iK4x0jFp779cCalixanGMxXTpdTPX5U0oLPuXF8FJ6cZc4Z5zSZDo1oGaYk9V85YETCkB4gp44Amt8MEoEn85g8+gbYIo1H7XgvGe2+4ck3zHSP3VOGSDIbuvUtkQ3yQB+SUQawPDrWGPuEAH50FgfHO+SajOOJY2GOOtaIJ0ayQMvQYBDwFORMZsMLnOhV4w5fdLX52a5kRvp/9u4CTrabbAN4nn5I8eLFizsUL17coXjxFneKF29xp7hDcXf3FneKOxR3d//mn7nZPTt39truzN3dm/nd3HNOkpO8efLmtWRmk7FBi34Gv/EIxqGXE8+Rw//G71182OQKg9hvR2jHe/NMSQp9QFY0fWLdmiN00kfWI33FgCF3klSHjeOK59Rj0Fn7nEF5xsehUmbc1r0TcGQoXKypeY4T7/n1duuC/LeLSZaiQZDcGO284EEyHt2CjJwAp5rwsvGRFYwx649Mwd/qwke+uYaZMXMqzT97gOPrfc40R9g7+p5VSlL0MUzkhOcy+hiz9ScQQfaR2Ulq0NfvArFlyGPy3Q/vsn04sNZyGzMM2TdsC99PJ2fIybLpQ44KNM6Tr80zewodyVguyGMXwR1/4lXXhoegi/m33p2McdyVzjQMdfGBNgQr2BO+ZgATx9sZ+DAlX9mLMLPWyQs6ThvzSviZnrAxwAYmPzlg+rcpYa59bQsvGy/+9Y5ywWFz69nvRBiLfDYi/ucUCnJZQ57ZxzajyIlkjDOdLziEH5JxnjbWQkpSeZs+d0JWwJI+5ISaP7qebjfPeAVWbGsYwslGX9n0oQfs2O+1114L35/eVLTmLvgBP+Jpfozx0aU2/8hotgxe8LtdxmX+6TA+CF0lMJSkmFNrAx4CVTBjl7BBOPf8IbjOc63PC2yYCfDhe7vn8LLxQ0aSj/gIZuSCMjICjvCUz/5Fqzzl/DzYCYjLp3PIXHNlPeFJeMNY+XpPK3LokxQRaULLro7IB8OPgGdEYGxMPAQJ8IwrgpBDLyprkjCp6BXHwwQMAbajpEz7FBsn3TMHnzKn+NVnfIuEiXq5N1meKXiOhV1LBg4D1sKjaC0YbXGU0JykMKQwAgNWuyLA6qKVwOG0y/cr+4zl4cIi3EXc7RLpw2LmyGDOZG0J3uG8rPTebqbImYg8Zx5mSYpACUeB0mZ0uTcnlDBHD476TsbGLuzwkHmatZJOUpUE/mIYMzqSFI4PQ9G8mmOCRDleY2gk4/cIZkoVX/lxOlHDJIaz6ilJwY8UO8UvasmIs4bsJhsDXK0jmMtHt+/7MyYZ90kKZUmhOhljPHb6KZPVIlg/5o8A9Zcj7B7CMRnjyqC1e5Wk/lktih0tFB788INkh9i6tUNhR8a6Wi0ap7WTpJ4QcJoEPZSDIGCSgi5GGrokgT7KVj3Bq8anxim447ty8GfIzJpuY0lS8Cc5Y+0xfJNUJwPW5C0cyTWOX5JCHjYeT1K/40le42U/FmeX0FjL6JOkcM7a6aZR1qr/g5djmWQxJy8Zr6MkdY3ClpEkmJukGozoJ7+T1F+2Z/jLswvIcUd/kvqnvQQofD1K2w2DshM+xmGNCl7QZ4IL5KJ8Rr41bR4YbvQUEpPUP33ECTYmwQBBG20I2LW5or/sBk9b99qZZyIb6VDOOEMV3fq3ztFuLtkNZJUycpZxP5RtTlNYW9afd8gEdTnu7A42B/nReCJJwfscIXMteOX9JLqeeUpSedWa55yiVWKco58sZmQaM2KSlD333LOYT7KETsS3yVjmkPHkdZJijtlFTjEI6NKdeEY7UrOhknicS0rGckTgMhn3m6T+SrVNFfaA4DF7MEnFBh74mDy1a2scybiM3BHUSVLXN/lpPdMD5Kp3k/FfFmGMWz94i1xSVub4SVLMmTXIKceTjQbOKV7G/9azxIlvepZNiB8EbcwlfkG6AJX2rHtzS0b7YUFY+fFOR+uTqFrlncAgXkrGebVgjfyXpLDP2Xv0oR8F3H3TXzAyr9ZuksI2YY8YI9ufvmo4GkqSwo5owRJ5azXhR46nU36CFOjk/1gLAl/WM14wXuMxx/jbKeIkRZ7NQ9iQj2SZOvBgR+EhetyfAGRnJWtv3o15JSlJocNg1vBi0whW0hHWDXxbGfvbuoARLOnWJFXWkJWCQTDHi+hiv8OfvUSeOgXnXWUbIe220kFgOI4QYcWgcAWQ1O6TLHTDobfAOXwYWT3C2s4eQ1lb2lx4YXTjWduScu0SZN51L29UrU6iZ0mZfPdSa0Oee1fKhoPEABBFTlLbUN7aT1KVi74l72m7jD7qSe15lFWNaHXU1a/kXr0kqmzIBANjhZvk2UBdjd9VanVg5DlZxMSzcvVbuTZmnfRrfiR9uerfVRl6JHmekyzhEzS3Mu/PKukbtsOELvkSOlzR7V6Zq+cklSz38pQ1mpNxWa2wwv/0v1z7yfi7cmjQTTJ+Rot3kjEdSeo6ki+hMxmXlRl+0IUOfboaS5JKC8yTMQ3ylauHNs9l02fYhvtk/M6m4plcktQ/34VGNA3pcT+NVrQNaR/WU9/zkFj1J/OG5Su91yf6JX0lS3FLUuUwmsvogxb36o4e6xx5Nn5tKZcvuZcnqZMsbVudxTT7OzSjBa2NniT1x8CMX5k6yZjOJHXs8pPU75t613N7v4w+yZgPWtmwjVHx3P4lqfQaizSkEc3T6DNH6g6TevIl77mW0cdVm8qH+aOi2q88ZeokYwyVzSuhT/+uSZadV/Sog071XT3LT8bvmcPhs3rGp14yHlsyritP3XkmfaI7WaQFzY1O98m4DF3JmFZjkJS3fPfyhs/T2knGbbQyNHhnnkmfxo0GV8+tf+OQP+Rl42p1huXeTVLtCeWtXpIq07QjTz3lZdPHvbwkm3LW1iXJwlps9CdjWtv4y+hjDMYouTeuZFxvVFwxkCd5XsvJONucG2OSioGxtXxXz8m4zJjVLaOPMXpWri3Po+z6z708SZ1kEaNaYYP8l4x1GJyGCUYSbIb5npNUnOGiThl9Gl6CSOrLT1L5yTuS+uqVDfTZbd5jAaxIrCiJXXHJcUKOtchkMh9GdbTDRDvGYlfYLkkyn77njXnvryPQEegIdARmgEBvsiPQEegIdAQ6Ah2BjsBORmDuDn2SYifeMaqWHJUUMZknFiIzjjtJol7z7Lv31RHoCHQEOgK7HgJ9xB2BjkBHoCPQEegIdARWG4G5O/QGkKQekbBbL3Guk/nvju/Mvkv/dAQ6Ah2BjkBHYHkEeklHoCPQEegIdAQ6Ah2BrSKwUxz6rVLVK3QEOgIdgY5AR6AjsB0I9KodgY5AR6Aj0BHoCOyKCHSHflec9T7mjkBHoCPQEdi1Eeij7wh0BDoCHYGOQEdgQyDQHfoNMY19EB2BjkBHoCPQEZgdAr3ljkBHoCPQEegIdATWJgLdoV+b89Kp6gh0BDoCHYGOwHpFoNPdEegIdAQ6Ah2BjsCcEOgO/ZyA7t10BDoCHYGOQEegIzANgZ7XEegIdAQ6Ah2BjsCOItAd+h1Frr/XEegIdAQ6Ah2BjsD8Eeg9dgQ6Ah2BjkBHoCOwgEB36Beg6DcdgY5AR6Aj0BHoCGw0BPp4OgIdgY5AR6AjsJER6A79Rp7dPraOQEegI9AR6Ah0BLYHgV63I9AR6Ah0BDoC6wqB7tCvq+nqxHYEOgIdgY5AR6AjsHYQ6JR0BDoCHYGOQEdg5yLQHfqdi3/vvSPQEegIdAQ6Ah2BXQWBPs6OQEegI9AR6AisMgLdoV9lQHtzHYGOQEegI9AR6Ah0BFYDgd5GR6Aj0BHoCHQEtoZAd+i3hlAv7wh0BDoCHYGOQEegI7D2EegUdgQ6Ah2BjsAuiEB36HfBSe9D7gh0BDoCHYGOQEdgV0egj78j0BHoCHQENgIC3aHfCLPYx9AR6Ah0BDoCHYGOQEdglgj0tjsCHYGOQEdgTSLQHfo1OS2dqI5AR6Aj0BHoCHQEOgLrF4FOeUegI9AR6AjMB4Hu0M8H595LR6Aj0BHoCHQEOgIdgY7AdAR6bkegI9AR6AjsIALdod9B4PprSxH43//+V/7zn/8sJM9La4yf5P/3v/+t9Vw9j0tKcS9PO66eW9ksr/rZUn/K0SSp12iR71m+5L6VzfLa+t2W/tRpyXsSWv/973+XljzLX22atalv12lty9e3pF6rI9+zfMl9K5vlVT/6awkd0/qT3+p4x3Or5365slZnFlf9okUati9/W+hRz7vqunpu7biXLylr+at51Ye2pcl2t1Q2rW6j03uSZwm/u0ryJ9+d57P+jRUtrp4lzy3J3xJN6qujvqu6rp6NtSX1lM0z6RMtkvth354bja6eW7l770gtb/Kqjvck9Ty3Op7lS+6HZa3OrK/61L+rvlw9t4Qu+dJkmWf5k0m+91obnlsd9y1fHc+tbFZXfeir8ZgrGuQP+/Q8zPesbkvKtCN/8j35yqVhuftx2dje8Dx8d173+h3S4b71rQzdxinf87BMnjLJfSsbXr2jDUkdz63cs3xpmN/K18IVXY1O1+VoUmYckvthPW3Ih5PkeVi+lu7Rhn5pSJd8Y5CUeR6Wt3tl6hin5F5eK/csX5K/XDut/nq9GpfxGa/kuY3FvbyWPLeyaVfl6mrPfavjGY6S+2FZq7Mer92hX4+ztgZp/u53v1uuf/3rlzOf+czlNre5TfnVr35VHfRJUv/1r3+VJz/5yeViF7tYucUtblF+/OMfL1T53ve+V+54xzuWS1ziEuXggw8uf/jDH8qsPxbyd77znXKRi1ykoG2yP+Uf+chHyjWucY1ynvOcpzz72c8uBIB6//znP8uLXvSicv7zn7/su+++5eMf/7jsmSbC6Stf+Uq52c1uVr797W9PxbgRQFh98pOfLHe7293KpS996fL5z3++/O53vytXvepVy1nPetaaznSmM5UznOEM1blv763GFW4///nPKzZomGxT+Re+8IVy7Wtfu+y9997lYQ97WPn73/9eq8H1TW96U7nMZS5TLnjBCxb3DfNaYQb/oefII4+sPHzJS16y3Pa2t10WX7x9r3vdq6iHT//4xz9WirTxiU98ouy3336VH/DGP/7xj1o2y//0+/Wvf73c9KY3LW95y1sWupJvTRmL+X/0ox9d/vznPy+Utxv1rMO73OUu5VKXulR56EMfulAPv8HFPF3+8pcvL3/5y4v5ae+u1vW3v/1t5YHHPe5xBT2tXfdf/vKX67y8+93vbtlTr+iyBu90pzvVcbz//e+va/rqV796OctZzlL53dV6/cEPfjC1jXllGu/Tn/70ct3rXreuTTj/6U9/Kve9733L2c9+9nKlK1281vAQAAAQAElEQVSp4KXl6LEezNkhhxxSrnjFK1Z5Ke8pT3nKwlit8VOf+tRzkUuTdP71r3+tvEK+kEPD8s997nNlr732Kqc61anKaU972tLkg3pf+tKXyo1vfOPyk5/8ZPjKwj1++OY3v1nl3/nOd75yv/vdr/zlL3+p5d5/z3veU65whSuUC1zgAuWlL33pqsu12tEW/kMfuUa3mQ9VyYe73/3ulf/oEeOXL7Xx0nnXuc51ysc+9rEl/K+ONsntRzziEVUmHnjggcW6li9961vfKre//e3LxS9+8fKoRz1qYe16d1bJWrvd7W5Xx4TPrKvTn/70db21PtFm7ZJL5sbzhz/84Tr33pFOc5rTVHmjrL3nai2QV+YRLtarOpLx0n/W8X3uc5/yt7/9zStbT6tcw7yaE3NnHdOv5hyN5BD9hf/x6E9/+tOF3tU54IADKv9bA8961rMWbIpWSRtk+q1vfeuyzz77lCc+8YkL4/T+O97xjmqTkBPkorz27lq4oh+fX+961yv7jmwjdtM0XYjuN77xjdUevOhFL1re+c53LsEC35/73OeuWLEtra21ML5pNPz6178u97///QsZ3MrhYI3vv//+5WxnO1t55CMfuWSNtHrkP71ljNaFdNKTnrR84AMfqFWstxvc4AYVBzL9Hve4x9R2auV1/B+8fvOb31R9BovLXvay5YgjjqgbgMqsiRve8IZVhlgbP/rRjzaTl2347PlPf/rT5a53vWuVm29/+9trEawPOuigBSz5LdN4s1ZeZ//tts7o7eSuQQQoNgKbc/O6172uOumUvYUzJNczJ4dytkgJOQL/l7/8ZRVOhB3l/b73va8c97jHLYx7i3LYxmreExAMTwEGwQPKZbJ9Timl8sIXvrA85znPKZQvY9O7HGpGJXqvcpWr1GAEQ8Q4X/CCF9SAxate9aolCmqy/e191vYxj3nM8tWvfnWLxioB9YxnPKMwOAgswoxxxLCgdBgE8p72tKeVW93qViXJ9pKyxfoMuLe97W2FwJ2Gq5d/8YtflIYr/vngBz9YhfPRRx9dhe3rX//68oAHPKA86UlPKr///e+9MrPEKHzwgx9cBBY4sIIe9773vasiGXZqXPLPda5zVUVD6VIYFC4eYoSi981vfnN1ro0BrwzbmMU9R/2LX/ziEnrR+sAHPrBYY+9973sLJxI/yB/SgD5jojw5wbvttltVqAIsP/vZz6oRgpde85rXFMbXpNE1bGtH78kQDqo+J9vgsDVjebKsPVsXHLjHP/7xdd3hbQGIz372s4Xx41l66lOfWh3ek5/85OXNoznieDHAvN/amvWVPGG8WaMMdfymT3xz5StfudLFWbn5zW9eGInKhsl8cYI5vgy/l73sZeUxj3lMXSN77rln5bu2vjkVnObh+/O4NzZy0ppAb+sTzl/72tfquqcrXvva15YLXehCtVjZsY51rMJow6PD92qF0X/yBGCf8IQn1ICBOcWTo6JCnhzveMcrZK51+NjHPrb8YM6BG7RZ8+QVWo2Jk73ffvsV8nCvvfaqAQs8oOz5z39+XWsceXromc98ZqGTjKcl7Tzvec8r5L61d6Mb3ajytD4EF+985zsXepPxT9aq69ren8UV1saEzyTzSM6QHa0/QQdzbKzosY7pTEFH77z1rW+tgXQBmPZOu7IPOMnqCRRYG9pQLqBjnVvvnFnz38qUr1baUjv48yEPeUg55SlPWQT8OQjWI9roAo4EWwGN6KPfGo2f+tSnajAYZnhlmv4ldzksN7nJTQq9yMl5yUteUvUjWahtbeIfdtOWgn9bGsesyvA2fMglAXnzefjhhy/RT/rGIyc72cnq2sDH97znPetmkDJ8L+hprvGRRO8qW4uJrDv66KOXjJHOxROHHXZYlcvvete7Cvk3ST/dR/aTEXge3wjs2miCA91ufeEZONDr5MFkOxvh+UMf+lANypITNiJsnvARrAHYCJDhKfLv4Q9/eF0Tk+PGf9aWtUFeakswFZawFiRiz8CSTXDsYx97sol1+dwd+nU5bWuLaIYbQUz47L333nW3gACyeIaUWoCc/std7nLlOMc5Tt1RsLNPIf7whz+sgs4O4QlOcIJqlHNCOCrDNlbzXrCAk05QnvCEJ5zaNAP5Wte6VnElYDkCxz/+8WtdQoExeopTnKKc97znrQYXg5QxyzGh5CnfSRzKCj7aP+MZz1gDHsu1K//I0W4zZSjB9EQnOlFhbFGIHJ1znOMcRWJkOS2hbAVkLXmVsSPIwRBDi7SkwqYHCgx2giLG1XAVyUYTY8nuo+DO//3f/216azYXxhbDU0BGD8c4xjGKSHiyNNBh18EuE0cJzXiZE8yQZ7gxTvYaGe0nOclJikgyBa5tbc4y4QkKfog1Hvj+979fTzlwdCg0a4ox3uq5cg6tV+t39913L4IZdjo5Q4xuu0ynO93pirHZ7ZbnvdUcD16B2bR24Wn+p5U1GvAbo4mDjHf22GOPyu/7jHa3BNvOec5z1p1vxhXDG1becXrFHDEWWluzuqKfXGCk25kUCIKtsQko4Sk7bmi9wx3uUE9CMBK9N6SJHGXkCMwxVuzyWb8nPvGJiyCpk0RkFf70rnU0fH8e9+QNuvQvtT7pCg6uQKJ1ceELX7jKTeWMKnxMNwzfUdZSkoIH4Qcn89xkt/7IOjIFltozz+3dWV/NIYebwWlsxkB/kWFN5nJayBkBLOXuJQYoOUf3mcshreQpA98OnXL8zBGyPo866qhCd8LEGt93333Lc5/73BogH7ax2veCROQJHSLRpdZpo50OhIWALCz0jz6nCwSWvUOeGIed2WSpnL3mNa9Z9ZM5FdwiG7Qh6df8a2M4/8rmlTgYHAK00RWXvOQlC1rIEs44m8E65JDgdxsD5pt+ETxld7B96GO4JEvHz0EXzMM7yrUj8ChYwMElL52ss15cbSA0nOeFwXL9oIOOIH/sssLFKQ3OKj4Zvkf+WavWLHvKGqCDYPWNb3yjnrKBFbmp3Joevr+W7vG/sRp/owvfWrdsCadYzFWTV62OK/0qgGWMZLc22KVsIlgI0gliOqGgnExPlvKMdjZC2nMUlMb31s8hhxxSzDnZylY94IADCnnBz3DqieybNmY2moASh99JSrqxySb8xFb46Ec/WswZWZZsDCy7Qz+NG3rediFAsVKwDFPJwhO9T5YuEkflCKomjBgnSepuM0eDMGSAJak7tEePop12Kwi07SJoGyprk7PNEScg22KffDVJ3b2mkAlVO3oEcjLO954j8IwXRhclJo/B9pnPfKYeB9XXZLsreU7GfS/XBuNQ9H7fkXHniLTAAuGFDrS1lKQex2WUyFuuve3J14fdJg6SnZckU19PUvAKg9fuL0OXI1ZGnyTVGcMvAkUEN8VWZvhhSMCJscVw4vTa4ZvEhUJNUo23JAUPM7LwKh6gOIwrSRH8sSNlPmZIem062RxnSo0yZBAmY5o5g3b16kuj/6xHO0atnvEaA0eS82V3iLGVpM6JEwmO0ZrnsoqfJHWdTWsyybTshTxG8qGHHloddoYtnrG20Wg85sOVXBK4YGwnqQEbO2mcD3UXGpzRjT6OOOKIeqwaxk4OCEDgH/zN6UOrJI9cYtwkS8fPGVZuJ1tQwA69eUxS15SxltGHw+HrFmTq6HGu/5LU+UyypF+02bVj3ApaOKGD9lYpSX2vPU9ek3E5veBdzi3jTz1tJ6mnguxgWcscQmWzTuaWfuB4mb/WH10hSCNPao4J2YBejo7j8ui1oyTgzaFp72uX44fHm25JUo1c8y9Zn9qSvGuNc/a929pZ7au+WkpSrDvyXp5+Gc2CaZzd1neSBf5UTzBCQI3sTVKGH+Xkpt06etSJvySVN+Bo/l/84hfXnTyB4STD12d+jz7OqRNoxpuM5YkTcBwEjiw6Jbu0HPcklf5DRk7KTW9603oCkc4xliHB2uPMasf7+hLk4uDb3ZXYW/IlgRH6Z7KdYZvzvLeeOe+c2SRVb+B3fAyzMvigP0n9CsmrX/3q4oQKfaWK9zmxnFynFehlslrZWkxJNiMrSZ1zPMDO8RVCzv1kRTi0lKTQU77mZv7VtTlgDZDpnFo6HJ8o20gpSf26nHHDg55jc5CjgiF4Xb5yTj5nfXL81oHTvfQnmcp+9BUYfKkueSyPbeMUnDW7UbDczQB76gisBIFkLLS0YQFSRr6Ha9HJa4kxM1w4SepxGfkciMkywr8twtbGal1F9ixox4yTbLFZBpIdMQak4zlNiaNXJJ2T7/jugx70oMKRJ1Bc7T4lqd9pVHeLnaxiIUHn1ANHnaMs0um3CexONjpcGQEUzTQFs6PkmEfY2oUcGnPLtccYc2zQSQKOJbrUNe+UmDkSnICn/FmlJPUorMiv/uxsT/KvvjmFaEsWeQbN+N5OmzrJuCxJ3WVVLn/eiROg72SRHkayHb8hLep5Tsb13KtnTNNwt17VWQvJ+KxHATcnDKxBJz7sigimDGl01M6a5EAwiJysEPQyzwJLw7qzuEerAALj1ikIX3+wTgUgzEkyxh9/+aqAIAVah7SYF0aKHTprjKFrB5Azqf1W15xqw/piALX8nX3lpNiJEsigI+yiWGvbQxd8GLWOqNuNJiPa2OEjmOyIJeeAsbY9be9IXfSYR3NC5g7xTlINeu2qR8YJyJhX9ZzwIaMd/aRL5Kk7TMvxpnVI1wzrtvt5OT5wtyMtqM1p9cx4Ns+clySNpCVXWPhuMV5IptcRIGV4cw59Vc/ctkbwPQcP3ztpo99WNo8rx8IJGTxmTQs8WG/WdpI652iiX9kG1qq5FbizJtkTAt+CowKv6ja63dPh7bleN/2HF4Y4bMqux7yn5bfyeV7R33ThsF88qWyY515Qynrm0JPfAhdJ6tcZ8IcAoKClNI/1jKbVTMZM1vmaBD62UbGl9s2jcQpGJqkBEU6o37ghJ+gutqg1VDbgJ0kdFRwcrXcKTQBcZjIuY5sIbPktjWScpxzWTs+wCeh6v7HhBMgtb3nL+lWuJIXMFUx+wxveUDdkbNxsFCx3A0JPHYHVQMCiYGxyxOy2J4sLTfuMmGQxz+KTLxIrJUvL7H5ui1Ooje1JjCCKw/FpC9tODgFgx8zR6UZXa9NYXvGKVxTHkBkqjEhjTVK/NmAHgTKye+tehNmuEYeCwzDNKWptz+JKmcLOjp/oJuPH0TwGYxsb+n0nzw4Rh2a16CAcfYfVzqB+KXF5ggnT+nBygEHuiCWFzbFRj/HDUPIdSYar+0a78tVO2uZkiII7LugYOoON4hj2BddkHIhq+fATQWbkydNWu+KdZJGv5c8rtb6H9NiJt9szpMHxaM+tnnv1GJ9NkcprCU+1+7VwNUf4mZOMZgaAXUuGdKNPubVpt0eeU0KOAzOo7RIqlz/rxCBHA8cPvwi02XXhFLW+yRFlTqwkS3nHemLoCF44pun4IXmLZ4dOgN0wO6RJqnPR2l4L1yR1p9aRUl+vu8XvZAAAEABJREFUEVgs2/EhG2DGifYVA7vDbezWIqeZk4evJ52l7ehmm6vqm3MpiOAHYekUDq65ZXy3hvCfkwkCTvLwHFnJ8HRyw7ziSfpJeUtkTrsfXjmPdM0wr93Pa42SGY6Zc7xhby0KtHDCYSExvGHB0G70kfOwsV5b3uTVDiWdBVsODB3d6sDNV4oY6k4DCLS2snlcjdXuOjtCANuJCPPmhwmTVBJgw9FnL5A3NXP0X5LqpLF5nM6wG6tu2fRJUr9St+lxyUU7+l6SOXogr6XRbf23M/9LUr+eNUkDfWTtTub76oy5xDPkoEBOq5OkygpOmd3Yec9zWYVPkiKIZ43bQGJnDOd72IX8drpsuLaTVJ6x+eIrPU63qFs26MfYBPzIBzJ+yDc2+sh/p6EcmU/G661BoZws9dUcOsCJPHKXzFAnScUSP5JbZAxZXDbApzv0G2AS18IQLCAGFoVjlxNNFqVkgbn6vhTHh/LzTHi7OvYuasYR5bzJo+QcW5sMAmh3pYlwYEyKlPuFWt+Dd1SRkUyA6J/B4doSJYoeuz+USst3dRRSO1e72tXqjqwjrpxphrZ+GN7JUqGzkjHoUxq24Zkx5WoOjEMgIUkVXmhAV9n0UeaH9dCcrB5tcICRazNuODDwRVuj0T0hCldBEkGVYZly7/g6h+g0vthE+kwugi8Mcjihl5HIGcCTaGk8jFeSFMapfLu+HGSKheLA08aljLPo2JcxzoTorTTKeOBsmGv0CFZxAiTPeFwT5omj6HQF2n2vlbHpWCfs23pVxji3vpPV4xk0SGhyXS4Ny92j31XQgfFjVyMZfw0C7wwNXPMnKGQXMUldE4Ju1ijHwdouc/g4NsjZRjs5BGf8495YOAcCXNalYKY8iXyV1NWGscr3Hp4lg5LxnJgnQQHBxGScN4ehLekCbTLa1b2EtpaHZrzIoFe2XFJ/KBvUM247WJxnWKqjbWXaZcA5peE9ebNM5klfZJ4kEMOQFFBRhi6nEMwrnkN7o9eP+jlBRX4IsKK36Rf36hkLvWkda0u+U2N41rt4xvpV5qtO1i0dkMx+7q0rurrtQBsbnQcHiWxBOyyG+kdwQ9AKP7e5wd/G4Nk1SfGur1W4Gjc8lOnH11HMPxrkeW9eKUnBZ/Q8O8Lccjw4nUnqbxgICpNN1iu60N6S52T8NShfVfCszFjcm1fyus0rfcN+Mud+g4C+ghfedyKSDTWUd9rYjrSqVc0NG8DX1syLcXHOBO+sB3S3cSrTOR3pRIcfd6Sz5LV33WtTEBSentdiamMZ0iZPQj87By7NlpFv/lzbO7Dx1U04wES+8oZFkgIDfJfMfn3rf97JeNldghbWfpMb8uFAt1kL7HW4ypdgqVwAlPxlmyWpv9fFPrA+1FPHNRnLF3OSbAwsd5v3ZPX+Nh4CFoejQBwgStdRVjtGDFeC23Ej38cliBxR80uVBJeILMHE8WDQUP6vfOUr659W86u2FCTHdLURY+xbxHZj7SAwRhgXju8whAgCDiYa7eKLqNpNcHzO8TBHJJMUR3acSFCPc8zIImSSVIeB8iKUk9UTFrC2E8C4I/Q8l9EHfSK36NOn41l2BtDE4GIQwDkZ02KMngnEZJw3ambF/+y0252XYMvo4ehyOhieMLcj51gdXB2VRqPoKUMQZk5C2K13bJgzycC1i7Vi4pZpAIacA7zmGKT5RCtDTB7sDjrooPr1ELtr+MUuAsMDD9jhdQLCOBlgeIZT7PcLnICA8TJdr1o2nrDWYGY8GmZQ28FlbOJdGMOfE4U+PK4ebBml1q331cM/5syYOI+CEwxHa9eYktXjGTRQsgIKQ56WL9nVpqzxQRub+uhHGwfGkU3HGbXBWbBDb6fe+5JABN7iBCSpu9bmRZ714l69WSZ9CB5YE4JH+MxOsu9Nkzt2Znz1hOFrLvyuiLkzZs4enktS/NCPubDWrXunWDg2zTnSLmOI8T/L8WypbTS3ucSbra4daGNDo51dMsLYlXvHHJNt+FWeREY4ouyoKofVEVwOMl51CsN6JNPtzNvJ1S++4BD5kTxtzDKZTzSQeRJetHb8ejnD0lFsAUJOl7GbV8fSjddOOhlCbtCXdo20Z8y+imHMSeqfHqU74YJHBMDJJwFGjo5fEMcL9LC/1JFklkNeaBvdxpCkrinraYiFU1ocGVgYW3vRV9f8kJ81IQ8W5o7s5/D4dWo7mta9eaWvfaXB3PoLBuQXuWD+ySOBf+3MK6EXDwsSkqloo8/IErLJ9/vtOhuL+bajSD7bsTd/eBwPGw++SFK05bu/3sG3/oKFk3/0D7mL7+HlqzjsKU49bKwZ+inJnIa/5W7QyBHDx3ifvneKxg8iyjOveFsrZACs8BE86Hs2BHzZgmQbm5LssztNrntvLSbzTiZZo+hHo/VLXjtdgl/JZWNPUv/6ER3G/lFXEgSxKUAnw1E77AmnVLRNpjnt6IddlXtnIyXj5bDDjO3Fp+An2EW3fpyU5VvAmO5kf1sHsIclfNg3vgbr6zj0hdNSnHlymc70VTdrCs7mw+kh63Yj4Ngd+o0wiztxDBYgJWUBWmwWFYHle52UrIXGeXS1aByD4UiKxhJy3mGMMQT8MBDDm6In1B1H884shkcYtkTJMDo864tyIVjRzEimdBhQjo5TnHZdk9QIPQXMiecIGgthksxGscKa8IIh2hjxBJ58xgXs5BsHA4oz51iS74QzNowxSXVMYa88WV1a9d2SuROogWGSqsA4LWgV3EG7HStH2x2d5Dx6Fz84tml3mKEKc8o8WV1azbWUjHd1OYQMKPPJCOOQ42GKhPCHMz715+0oFA4zPkZfMo724hEBLEYeA5VhlsyGbrRL6LKja+7NM+dbnsg24w/Oyv0ADJy9M+TxZNFJtFvEucdb5g8/+0XY+973vsW69j3AZmxoZ7USPvX1C0qa4Wos2na1W4GHGPkMvpZvjZobdKINv1innCdHHDnv6kp2yxhB6nreGSlJsQbxFqPEThvHj5zDXwKF8q0H4+HE4jcYCIAx3M0rnmOU4DFBTzKXAd3GJBhlfQlSJrPlvdbn8IpGa8k8mAO8Y82r49lXmzh9dl0FOIzRO4ytNg58SqbKN35Gmat33NMP/vSf+hw6csMujH7xAacJhoIjyWwxSFIDuGiQjEeA0D1nRtCC4+n7nGgyX/hQsj7xvTXlx9Ic4TZG4zZOuGmHPHeSgbwUIGHgWxN2owQ/GcHkJzysde+UGX/QyLF2iioZY5xkCRbGSHajJxnXITuNy3jKpo+2GNmCpIxvcy2oSNcxyslc4xUgId/wjfm3IYBXYL6pqblc0GfO/GgbR1WQgQOicw6rgAXdZQ2bc2veO+rQC+aKrPMufec9mOAXWAh+cFa0Rf4JdrObkhSBHDISX9n40B65oo21ksw7XcQOvPWtb12PnFuX+IBjK2BlnA0PgSlBD+uXTFRGtgt2Ov1CD1//+tdf+IsYa2WcQzqMgYNIhtOT5psOFqjxdTB8YN6d4PGe+abDBK08S2xlstF7niW84C/owE9gg2MqLxmvJ3U2SoIZ/SeQw46CmbVvjQgOsQutC5tXyqw/OqVhKRiGxzjpNujIQza69UkOkZfWFLli3Tiht7P05CzmbLdZNNrb3HUQSMY/MmEXmKKVHK8SUbPQKOcmpJPU70NRRAQfpcSZLqNPkvqr4AxxBo4IG6UwKprpv2T84yt+fIMQTVLsbHHOGQmO6FK8xkdBUTZJ6m4Eo5KjYEeQMa7+LIlNUkTtOWgN56bk7XIR9o6LE2gEIKGGbpFKjnWSSl6SwuhjkCTjvFowg/9ElzkuSQoazLvjUuYW5o0+mKM7SfF9OcKbQc/gbTtAMyBvockkhfHPoRd0MNecIjRRBIwN98n4+41419jwcpv3ZDw/5oEBR8F7Z6GTGd0k41/F5QBYe45rJqk8Cjvzb0fQDwzBPUlhTOPx9sxQ5rjb8aEI0Z2M28BTFKzAlt1AZas9FGseT0t2cZPULvSFR4zN1U6YAnSjn3GbpJgDu6PWIkVN9nhXXUmAwgkg9zszJanfLxUsshYYZ+QOgxy/GycMJHMp0GGsnEHGR5LqMDnC7CtO+EzQaDhWp0Wsm2SMYZnzJ0kxF8ZgPE4KNfqcZjEu68w6b/nJmCfpDe+p044vc47tbHMczTMHFi84murrH9pIUvA92YiHBdbIRGVzHn4he/3Qp3kj8zjbcDAuCe0tmGpsHD95/sa0+miW73SGdZqktgk7cpGhy+lPUnmBcc+BsMbxSNOpZcafJIU84HAl03kNBvQ/Hm/k+JqJkwTKWl6SIqDPeU1S/FgiTMgcARtjSlLHa+0owwdNtyTT+y8z+pgj8t84OGvGkoxpEFRE33DO7VAbA53rPXNLJglCJamy2poWBBO40D794z1yAS4NQ2WCzk4A4Bl6K8mMRrpjzaKRnufcfuADH6i/NSRPa5xa6z9J/Xv8xgEvzjs81EtSBGpgxU6AaZKKkzbWYiLPrW9JsCkZ2zwwIM/oYfZkkko+WUaH0dE1Y/QfuSB4k4zrJClw5ITiA9/5FgRJxuWjVzbUP3NvzcOwJfYYOW99CI60fFf6gpPesGynXaxHcoMuICeaXKVn6Ux2u+DpRnLmMUJ36KHQ04oQSFIjpxROSxaYxZmMy5KxAEpSnXrlFp06ZdPHvXxJWTJ+Z1PxzC5JqqGg/zL6uOrfNUl1FhpN8kZVqmJxb7ytLJk9vcmYntZvMu4TLehIxs9JFnCWr7wMPklqeZnxp+GomyS1T7QkqTyDtmGdMvoob+ObLBsVz+yfftEj6TcZYykfPcn4OckSnkjG+QhT1/uS+2SxTPksUjKmB42t39YPGuRJk2PyrFxdV8+T9ZLUtSFfUqfM4KNd9EtoSca4JdPHpo53XJGTpPIWGqWWXzZ9PEubHnfqBR1olIwhyQLGxt+ScnWTcbm6ZfRJslB/WKds+nhH2vS4Uy76b+NAdzKeT/RK8tRJxvmITJbOdTIuU887Seq4vattV2XJ0nrqtrKyEz7JeBxJKr3oQW9Lnhvdrp5b8lxGnySVnyef1TO2ZDzmMvok4/6mlY2KZ/ovSaUzWaSnDD7JmLZkablxSa1qkoqVsZXRxxVek2NKspneSJa2PXp95v+S1HFP0ldGH+OSj/6WjEe+pExynyzS7ll+Ms5rz/K8n4zzk1Ss5EvqJeOysoY+6EKfhP5GWsv3LF+55D4ZjyPJAr7KvJOMy8rSz5p5Qn+b70avK/ol5Z6T8Tjct7w2iCR13GXwUU+7rY1k/P6gyoa5TVJtK+MdJhhIwzz3MElS18MQyyQVR+WSd5NUu729p36SspE+3aHfSLPZx9IR6Ah0BDoCHYGOQEegI9AR6AhMINAfOwIbF4Hu0G/cue0j6wh0BDoCHYGOQEegI9AR6Ah0BLYXgV6/I7COEOgO/TqarE5qR6Aj0BHoCHQEOgIdgY5AR6AjsLYQ6NR0BHYmAt2h345Br6oAABAASURBVJno9747Ah2BjkBHoCPQEegIdAQ6Ah2BXQmBPtaOwKoi0B36VYWzN9YR6Ah0BDoCHYGOQEegI9AR6Ah0BFYLgd5OR2DLCHSHfsv49NKOQEegI9AR6Ah0BDoCHYGOQEegI7A+EOhU7nIIdId+l5vyPuCOQEegI9AR6Ah0BDoCHYGOQEegI1BKx2D9I9Ad+vU/h30EHYGOQEegI9AR6Ah0BDoCHYGOQEdg1gj09tcgAt2hX4OT0knqCHQEOgIdgY5AR6Aj0BHoCHQEOgLrG4FO/TwQ6A79PFDufXQEOgIdgY5AR6Aj0BHoCHQEOgIdgY7A8gj0kh1CoDv0OwRbf6kj0BHoCHQEOgIdgY5AR6Aj0BHoCHQEdhYCvd8xAt2hH+PQ/+8IdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2BjYnAhh1Vd+g37NT2gXUEOgIdgY5AR6Aj0BHoCHQEOgIdgY7A9iOwft7oDv36matOaUegI9AR6Ah0BDoCHYGOQEegI9AR6AisNQR2Ij3dod+J4PeuOwIdgY5AR6Aj0BHoCHQEOgIdgY5AR2DXQmA1R9sd+tVEs7fVEegIdAQ6Ah2BjkBHoCPQEegIdAQ6Ah2B1UNgiy11h36L8PTCjkBHoCPQEegIdAQ6Ah2BjkBHoCPQEegIrE0ENnfo1yadnaqOQEegI9AR6Ah0BDoCHYGOQEegI9AR6Ah0BAYIrNihH7TVbzsCHYGOQEegI9AR6Ah0BDoCHYGOQEegI9ARmBMC83bo5zSs3s3OQOB///tf+e9//1tct9S/cvVaGtZtZa7D/Fnc66PR4H65PpQtV29LZcu1t9L85WgZtosuSV3XyTL50mTZsN5q3GtfWq4tNEiTdTzLl9wv9/5q5utrMk3rW16r535Ig+flyob1Znm/rTSoJ6HXdUiTZ/nSMH+W9/qUJvtAgzStbFhX+XL1tlQ2bGOe90Oa3OvbtY3BvbwtJXVaffXas7yW5Cmbd9JvS8O+5TXaXD23cvfyWvLcyoZX+eq4DvPdy1uuTPk8Ehqm9SNfamXupUav+1Y2eVWmnrRcmTqTZbN61hdahknesD/Pyl0lZa4tz/PW0mT99qyNluRtrZ1ZlOsXDa5S68O91Mpa/uRVncm89qzM+5L7lu/qWb7kXt5aTOiTtpVG9aQ2Fvfel1reWr6iV5qkEf3StLJhXeXqSe6nlU3mD+tslHtjhIE0OSZ5kjqTZdOe1ZOGZZ63p43hu2v5fo079GsZuk7bEIF//OMf5fWvf3057LDDygc/+MHq2A/L272F9L3vfa/We/KTn1yvf/zjH2vx3/72t/Lud7+7PP3pTy+f/OQnl22jVl7hf+j4xS9+UV7wgheU5zznOeX73//+soGI3/72t+Xwww8vz3zmM8u3vvWthXoEwle+8pU6hle+8pXlD3/4wxKq9LEkYxUeYPWqV72qPO1pTysf/vCHC9ynNfvXv/61zgcsP/7xjy/B8mc/+1kd9/Oe97zyne98Z2E809pZSd6//vWvittPf/rTqc387ne/Ky95yUvKs5/97PKFL3xhgQ64/eAHP6jz8sIXvrD86Ec/mvr+ambq841vfGN5ylOespCe+9znlt/85jebdfP73/++vPSlL618+o1vfGMJ3V//+tcrP7zsZS+r/KDdzRqYYYb+vva1r1Vexdvmernufv3rX1f88cFPfvKTJePA59bFa17zmvKnP/1puSZWLR/dn/70p8unPvWpJW2SCa973evqnOB3PLWkwqYH73/xi18sz3jGM8pb3vKW4r1NReXvf/97ecc73lHLPve5zy2MU7n3XOed9AvjV7/61eWpT31qpUneRz7ykfpszNb6lugif4zHGnnrW99a27COyODGx2TsPNbPJJ3G8t3vfrdYQ+6H5dYUuYQ2tP7whz9cKP72t79d5xr95Nw///nPhbJ28+9//7sYt7k2r+a3lbmnQ2D62c9+tvznP/9pRXO7Wi9vf/vb63wMO4UDuoc8/uc//7m89rWvrWN++ctfXsjE4Tvt3piNhw565zvfuUTuG7M8OkH78xgz3nvXu95V6TZXbS7lN5qN95vf/GahG82HZ+nII4+sMvINb3hD2RYe/8xnPlP1lf6871mfLen75z//eet2blc4m0s8bB0PZY55fPGLX1ye9axnFXIJ3ZOE0dFk1TQeV9+6tX6s7x+M9GF7XxlZab7pLO20srV0ZQ/BhX7fmp1hTPQRnePeOPD8xz72scorb3rTm8pf/vIX2Ws24X22Fv4cEml+4IBfleObYXm7xz9ve9vb6njVZ2c0LLTx5je/uer1L33pS5vJltbGRrgO5539QV80HMg6vADLD3zgA0vk4LSxe4/dwOdo5dbbe9/73mpD8zPUaWXr/bqxHPr1PhvrlH4L4pGPfGR5z3veU52vG9/4xoWTQMBNDkkeYWUxcvwZfcc//vGrw+kdhukVr3jFcvvb374699qebGM1ntGB5tOc5jSFU77//vsXgmSybf0ffPDB5eQnP3lheN7gBjeoRqJ8gobhdvazn70aHAceeOCCoCW0teeq7mS7O/KMZsYLhYHm61//+tVgkD9szzNjyZUDZD68ow6aGYWnP/3pC+fh5je/efnlL3+paFWTvimge9/73mVojLROlHOK4c9wufKVr7wQLIHzE57whHLGM56xGrvaoNDau6t9NT+COwwkBrYgCcXBYVA27M983uc+9yknPelJCyPyJje5SYGxOoxTyuac5zxn4dDDVn1l80hoxRf3u9/9ytWudrVywhOesKDP/Cob0sDYusUtblF23333cuYzn7nst99+dTzqcTSvd73rlUtc4hI177GPfWxdn8P3V/ueTEA3GYIG7cPuNre5TXn/+99fKGQ04qlWrk5LHNm73/3u5ZrXvGYNBjKmvY/PGMR4/epXv3pRhzEsX/lqr9FGz5au+n7FK15RLn3pS5df/epX5YADDqhy44gjjiiPfvSjCx6Exc1udrOaP60t6+Ge97xnud3tbldOcpKTlCtd6Uq17ote9KLqFDYe1ia+nNbGrPLMz5e//OXywAc+sCYYt76UmWOJ/EffiU50olqs7AEPeEBpuuHHP/5x2W23pSaKOp/4xCfK/e9//zpmfAMz+dKhhx5a6JBrXetaxTqdt/GLpw466KAajHRfB7bpPzgoMz5Z+OCJT3xi1Zm3ve1tC0Pzvve9b70qb8m48C88L3/5yxeBDmtS+9LDHvawwtnF33AhA7zT3p/FFY9yRslJvMbZMi/o0Z+xHX744eVSl7pU4Zjc+ta3Lmgy52Q7/iXXySD53plM6tzlLncpd77zncspTnGKsu+++9Y2tIun9av/I0brRhBl8v1ZPhsfOfL85z+/WL8CUWwDNMOAbqNj6T72jMDGkB518LpAh3EMy9wLgj/pSU8qe+21VyHz7nrXuy4EVuFsvpXhd32hx3trJRnfgx70oCqLLnKRi5TLXvayC/p9Go3o5/jDxDrBEx/96EeLgPmpTnWqYl3AQ7vT3l8LeeYBTwtYNXrQe6Mb3ajaWoIa9BN91sqH14c85CGFw3+rW92q4KN73ete1daEDduELLvCFa5QlNN38ofvb4R78w4fcpGtat7JDvIGluQnm/voo48u1psgqHemjV2+jTq6wEaLOvIECbTBxnnoQx9aBI02CpZLtaUR70KpD3XlCFggFs3Zzna26lwyrijhacJXXU4Q5XanO92pMGoPO+ywarRZsBQXJcBBJsA4ngTbyqncvAWGNEOII8kwplTtUk7WJFQ4/le96lWLesc4xjFKqyeiStFqw9UOCsNCW4wvAvqQQw6pRshkuzvyDCPYPO5xj6u7eIxABtIkRknKPvvsUzj8cOYY20nQJ/oJSYqBMcGRlZStVjLPDBL0EsLThGWSct3rXrcwUBmh//d//1fsLKOBk4l/OCkcs6NHwhvWymaVzJvdPgYFpXz+85+/wOjEJz7xki7tvDzqUY+qDjN+EIwSgFCJ4Xq3u92tvnePe9yjCKLIUzaPBGcG5h3veMdqCML3DGc4QzUIzUmjwT2+EZRQh6F8yUtesp7owEuPeMQjCkP7XOc6Vw0IMFC++tWvrhofNzqG1xve8Iblwhe+cDVgWj4jGf/a5RLI4qA50dHK2xWfKRNAYUQzsAUHBSacUODQy1NmfjjLTt14x3wzuDgkrb1ZXmFP7kkMc86KwAtnjjEnEGc9kH12DzgE3hnSxOA1R5wajvF1rnOdGpjBwwwecsfY8AGH+NSnPvXw9ZnfJynnPve5CwcTTw47NFec01ve8pZF8MGpLuM3RjxpPaGd0cWgJa+G75MnAm3qnPWsZy0MP+tWYBiPcuYFYPE9LODknWEbs7rXDycXL7s3Jn25Gjdaznve8y4Ex+QLVJHTxzve8cr+o6CyenjBey3BkKw2LnqWzrQzS+4YsyAiPibn6V7zr+32/iyudNzDH/7w6mjRJ9beOc5xjqrL9c25wctODOBD8+odTpoTCdagcdg9E9D1zpBOPE4/C5ZyXjlC9AIeN/fsBFdty+fwD9+f9T15oW8B0xOc4AR1A8JcWI/GwtngxJoLY+GYNprM5/ve976qQ5Sp38ra9VjHOlYN7tGBZLrglrErt14e/OAH1/UFA5hOa0PdnZHQwibkRHHG9t5770Kn2lU13kma4OGEibm2DryvzpnOdKaqhzhe7Kujjjpqs2CXemslCcCe5zznWaLDBNfwKnsWv9/hDneowb42xka7tUF2sTPNr0AYBx425p5tTIed5SxnqUFpa4OsaO9vpCsbxIaIMRo32c4OJyfISKdWyH3yhyyZxLJh4cSHcvpdnnr8D/azoIhAEf0ryK+uOus9dYd+22ew11wGAYbyTW9603LMYx6zUEScg2Mf+9hTa1PydigYdIS0RaaiKJl399hjj8KIE9W1yzMroXXKU56ynOxkJ6sGiCg/QWqBo2WYOD2MBYYxhWNXrRnIpzvd6QpDJUnd5WZAUu6cU0LcOI2BUB62uaP3+mIowIkRwxlDV5LNmmTsKuMImxdGpkqUhR0xZZwdBiLFqWy1EmOHkNxvv/2WbTJJgV+SwumFG8fSC+YG/ySppyIudrGLFeXKZpGSFIpSH7DFfwwMTjmchn3iB/QlqYobn572tKetVawDc+Qdu+KMGFjXwjn8Zy0xetCPBtcLXOACNeo/7F49R/sudKEL1bWGX50qsNNFseFZgRbvH/e4x63YMzZWi4+HtLR79CZL+dicOCWAf80Lh5/B195xNRZOr6CPuTAW69pVpN/ROu/KMx6OpvqMAw4Sh0rCs9qbZUKrYCa+YlA0vtEnGjlGxuee4+feOJQPE2eAEytoSF62MrzmtIX3jVUQzzxa863OvK5JSjJOxt36FaTAZ5whOsM6SVKDRejFl2QVB5Vcbu+1q0CM3Sm8ARsBN7KQ4exos5NUe+65Z+Vrp384lIKL7f1ZXY2RPEXfxS9+8SXdKHO90nz+AAAQAElEQVSSgHMj0DAsROOBBx5Y0MhQvfa1r12suWEd8vHzn/98PUljLRiz9cJhYvTjbWNWRjfBcbWDtEN63OuTXmy8RtfR++gSmKULjQtdxu8dMt284mvvcfTkmUflw+RrE9YvxxVftzL3ZzzjGaudgcfZDZe73OWqHm515nHlGJjvRr9TMpw58lf/5tW4BIDRzG6QL+ERGF3mMpfxODXhY3yQpJ7guOAFL1hPhalMhsE5SSGvyRL5ayXRE06RkG/mSLroRS9avyYzGazCG2Si4K2dVOMyjmRsH+DpJPWEFnmBb5SvxYT2JEtIM1fGbhxop8PIqyWVRg/KBG8E/ZyeE9y1GTQqKnaT2SZkPSxtNghWc3KVb7R0jWtco65nmJER1rsxshcFOmAl0ffL6TY8SJcIdluj3sdrAojKyElY2iCzjtkA6qz31B36mc3grtFwkmo8UV7JomEmGkvATaJgB4EwIvDtMNgxU0d027W9oz2GDAVgISpbzZSkHm1Fp8gqhWyhT/aRpH4H147ZfvvtVyhnjn2SarByDBgvouiMTDszIozyGHF2OSfb3NFn2BByydiZFH084IAD6u7csM1kPA+OI9n92WuvvRa+a5SMyygLAQGnC6aNe9je9tyLwNs9sqNEASVZ9vUkRdTaVwLswMC1VTbndnEEMAj1lj+ra7JIJ0XJ6IQbzId9Jqm7BHaABYGOc5zjVMdenSRFNN2uiXFRFsahbF6JwrPzyWi0fjivk84qmjgDaErG4zZORqoAmvFbf0kqjyepX5vwnnfmlShcdOhP33a57Nh7Hib0ClwZQzKmGU87ScNYHOYnqccZndARVGRACdAM25vVvTE47aB9Dhf+9tUIeWhkpChTj4PKAWQUJ5G9kJxYYMhwepzSYbTARoVkXJfc9N1lMqthqHxnJ6deOKGCEoxUc+CkQZJ6jJ5xZXzKyRDyZEgzw8vcwkt+Mh4v3qVP5CfjPPfqcnrUnVUyX/r3mxXk1RBvZXQbvWEu0YQO+e7pP46b3VyGPJksXx1JPWN29TxMgiH0T5K6TpUlY/luzNPeUWc1UrLYp8ALmSN4qE/OPQzIQkEqPM7xNq4hjwvAsAcY10mWkGXu6Q+BROsAj7MbVErGdfG4nTyOoP6UzSsJ/juR4EQG2WM9wxxNyXgO7CKaT/qNboMNueOECb1Nl2+JXvUFHfEU56XVTVI4wL6O5CQEHQTbVr6zr+gWSGs0Jan8SSexj4b0wc4JA3NM3g/LkhRrR2DIqR58MixfD/fG1HgTLvSRNZFkCflJipN/gmSCP8YtGAtD98m4fpKKpdMa1t2SRjbAQ5LCAU9SR2Ps5CZc4AhPBbBURn94HiY8xpkXFLOx1cq842sPSepGXhl94Ot0BDxHj+v+327rfgQbZQAbYBwWDIeAcyxqbrEMh5WkLiQGjO+VOZ7vaCWjpOyEDzooEgrDkShHF6eRQcA4guy4FMOFI81QVNcOhF0HkVe7TgzxJIWCZ6Qxqh0ZhI36q5G0xYAX/WXMTOKsjySFEcQgoAzRyKhQJqHVkVYOjR0zbcpfabJ7xkEigPUHp5amtc2wsZPNMPFDWYRxq+cEB4PXaQeKcLVobO1Pu+rDcUE7nclYqUzWY4g5aukUgvkVOGl18APMKWUGFzxa2ayvFB6aktSvXAhW+RqI3Z2V9p1Mx2Kl7W7r+2QEY9nuZ7JyWhjBnMWrXOUqxXxzjreVlh2th7fszPk6DEfcd4kZ/I4Rcmpbu9aAY4bmsuW1K6ePMW83xxoWWLL+HU80nlaPY2wNOjWSrByv1u5Kr2i1fvCk9c4oY/wnqbqBwycISR44vkyflMEHhoPHJbdbKltScZUf4G4XjTxtfIUW82jn3Xe+29cP5JGHruoYn9MxAqx+EAwmylZKYjKfOTcGMsbuvNNLxobHnazx+w6cWmM3p0Oj2Rg5/E6rJEtptauNx61NATyBErqEw+O9ho0Ajp1wBn+ytI1WZ1ZXtoPThoJT9DAaBUkF9Vuf5D/nTYDKOkU7nqbXBIzxDfzkw629165JirrkgO/62v1XX7lgs8CxkzycGsFb+espGQsZ6KSCXWs4tNTwgCd9yplnJwjerqcxDmkVXHe6xpwN89s9Hhck8rsIAlUSHODU6uxKV/LCRhk88Mdw7OQq+cGPSBbXPqwEQNVVhp/kuUryN3LqDv06nd21RrZFY5ERQr5Px7lIFhdaozdJjTAqJ9gYQJTb3nvvXX+ZmgBTVzSXMWohJ5G16olxaeeE0eCYp+88T+skSd2Z53wKAPjuq/GqyzjlxDFcCGNGhjGJ3BMsHFFHiJLVGwNsBA58NwiOyfS27YAx/J0usFvp5ACakxQ0cyoYHOiUvxpJgAYWAg1t153hwfCZ1j4Fx6kRKEFHE7pJivn3PXXjhOO091c7D/856okfk+m4Jqk/OCfI48cbBUwaHfhBZPjxj398cTrDUfBWNutrkvrjUQIMHCU7Znbx4JssjiVJsfbs3Dc+5lDKwzOO03IclZkPEWxOaLLYxqzH0tpHgzXlKxB28zh8raxd0cvA5hypz/E3j+bQMVjPzXhmJOA5QSfGNZ7Dm2RWa2+WV7Rah/jEbsP5zne++p1qu3v6VeZ3I+xqkk3JUszJSonx533BRidFzJd50gYMzL+vqiRL31e+s1OSQm5xxPCo0wZl9EmyoBvkO+Gi3qho4Z+vB5Hbxi/TWGFmrTmaiY/lSfCAj+CcurNK+OtDH/pQ/ZEmcs93fgUpnI4gS/CXNUgecu4FK8gHY7ATzWFxnNiPgmnHXA5pNa5kfCqr5dvZpG8c4W9jVoYWa6S9I2+WiXzwtRa6xLwkqUfDzQn+NH/m0libM6aMA8zR9xWlSfrkWc/WrDbMIR3KaTU+9c2vrwbtu+++lWfkzTMZqwCGQA5HHr30lXWrLEkhZ+yu+w0PMoxMcvLEXOMTSfBDHfp5Gv3WCIee7dFOKKhnjvG8IIf1o335ayEl44AyHjVPkrnba6+96mlONMrDD4IUgha+aiJ4Tz7bYBHUUW/33XcvAl5OdOIDMl7+ekrGKkDra1LGhqcn6bcm2KBkBLnBkRXscPLH+sH31pq2rHfBWvM+2c5GeTZWQXa/J0NnWlPGZvwwYQ+wXfFHEkULibxl8+IpeNqt93178pXM1DY8vYCfyBv2sOf1nrpDv95ncNvon2kti4xA8r0f3+dicFo0FJgyxqp7Sb7k3s4YIU7xieh7z862coaQ7x7NSmjpXwIM5UhZcGg8N+NDuYQe42CcECAErOdWlqRw4pURDOoR2q3dJoy0vZKkT1gKmhBUaG60oYVRoI57yb2+GRsUAPrUV4YOdMKXIeJ5NZKdJn9yi2Mv6cOPClLK6OHg6t89nF3RSKg6xuheOTqT8dc5ODYM1NWgb2ttUJZOVDReUJ9h6agkWhtt7s2xOXA6Qz00K3ePHzhtdpA8zyslqc4SA8L3T/24oF2OZPxbBQyrMvoIRvg+c6PZPQOTo2u3jRJUxsBytM+xUXMzenUm/+AmwVXSiWfY+7E0JyLgKU+5K4MQDzlWx3F3dF2+wCL8OQF2BtVnBBiPo7/WL0fI/LU1ik/1OcuUpNiNEoxz4gCtnDdrww4U+sg9jo41iW51XNs8oJNx77iygIxy4xUYMGb0y2Mo2wX3vDMSmiW0DPs3n8Yp3/yR/daauuayleFfc0onqGs3Rh2nvwQwOMzy1SM78IAABkON46OMs+T0A/k3pGG17+HOWHRyi8wTUPM9V04IZ408bGWcObzcdqY5Ymi1tjiDAhZwMFZjVuboud1q36OHnzHDTV1jVt+YlXEurW00rfY4p7UnaGLO4G8MktN5+K/pIzLHLjb5rq5AmgAHZ9U4jdGV7DV/1rkAgTY4hcphgcfJW3Rox/wK2nmed0KvPq1HgQXz66tmxqgMza7KBUmtb9g4gaEuPpEErehzdoN3BGBdJWNMUuU5Pc0hLqOPfClJPZ6MP/Q7KloT/4yTk07GoVPizDpCTt6yFdkx1rIfOW14CHJZ79YSnY+f4ZCkyGfDzHotrwRAtJrzlrQlzzjoV3KbzpGnjisZqByfw8t6wjPWkLFaE74SCjNBDlg6UWnd2zjQx0ZKcDFGAT96gT0Cp5aUCaIJmuIlz95RDkvyg/4cylz6wtfbyBQ2ATvYaQnv2sQjm8ivjYDjbhthEH0Mq43AtrdnMXHSRBcdLXPMjNHCkGK4ElQiZXZYCXGGjl1XAt6xcbu3Ser3wC04kTRKj0MhMt0U+LZTtG01fTfPkXgOj++6M44YQsaDLsqHoeT7gBwcv4zpF5kpIUcJkxRHmgkW0VS/Ws3p8V23ZGnEcNso2notRo3jdWiCM0FPSTheS0A5YsRhIdjQ70ezGJWEFvoJQDtAjEO0Oy4OX99rTVaHZsY1A4PBKTHOKGN94wcGmAgqB5nS8rULNDLeHFmlzOxioVGUlXHMsCd0k9WhcUtIwwfvojkZ9wdbR+gpDeWCT/5sFEPEeP1SqjZ9baPxA7oZ7na2lc0j4V284ZeV4eqkBCeBEaF/ToQAWpJiHuAqAONrFwIPxmW+KD885ZflrQ9HuynBZIyHtlY72bV08gW+AoPGwknB0wxeaw6/cwR8D87axOOcG+PD39Yt2cEYcEyPQYS/fWXDLpn5YXzb1TLO1R7D1tpj6OIHfG5uHMM1XrQJmpCF6D7ooIOKEwPkqDXK8DCnjmTrgwzgCDzmMY8pxiso4F3tK3eCR7DUjwgls5szfU1L5s56dkoJ7Rwda0ddXwMyNseV6QDfJyYblJMHxu+rT/jYV5yMySkKstqPvZEP9AT94HcqOAGcBw6RoB8ex7fK8JETVfhD37NKaOSA7LHHHnVX1r0xceTIkT1G+RJ5iCetJfnoojfpObIOT5hX7xuz4I8xa5+MgYuxkT14yA6xwJS596616vi7U0PJfOadHLeDloz7S1L/HKN5sMOIx51gsoY5JXibbDJn+ACPM77xiZMKdCn+MW+CWo3HvQsnWJhHzg0ZxZFNxn3Ln1dCI1rpWOOxDlvgFF3kFtqtX6dlyFDzzTFvvGCeySE6BF/jaWvbriFnnw60PugS9okfMeWwkINsFTLTGtM/XpjX2LfWT5K6wYG3fVWAbCajzKlxGpv1nIxPulkXMLFerBtrwzw7Ys/OYQ8Yq/fXshNL7wi6ObEi4IhH6Bu/a2MMdufNHR3GZm46TBCHXUnvmm8BDSd32JPkAXmB9+kvdhud5yuU+Glrc7HeymFGX8OLziMjnNDkxMPMRhZb26laWArYC2IKirAH4A4va6vxFRvAGsNX7slPNiesyVe6At+tN6ym0dsd+mmo9LztQuBUpzpVodwobQJHouDsPFlclA5lR+nYRXOMhvNgMVJoOiPAOf4MFoLMsVMReWWzSKJ2HHQCg9NDWRCQSQohyqD0TPGgn+NMwTIm0SoRKoxsdBsLZZzMzrgQoYYzgQ9jCV7yGe8it041ZqjmUAAAEABJREFUUA4MZkrAj96hk7ELR0YiA4EhJVpp3IwMZbNIdlEYIknq0TnC11FBRiAaKWz4o5VxBleOMF6yu8UBcCWIZ0HfZJvwQtMwn2GJb9FGOTO8KGd1XRsPM6QbP1DasGXADNua9b3TArDEI3h82D/FxShIUn9FlvOkLmeB0cWoMkbjxWf4mVIV4Ehmx9cwaVF1wTWReXmcFYrXLg5el/wSuCPU1qY16j5J8dcaKGjKn8MuSGUskpMHvmOO5zlO1oJ8fcw74WNHBQUuHa1ElzEwOMhFssY4W8L7aFUfXyapf3VAEIZTZK1wnMiANhbGDLmgr5Y376v5oAMEWayTZMw/HByOp6PS5DxZlaQem+awcnwYZtYS3ZGk4APOuRMHyfhP4uEDY4cT2ZuM28Cz8GDs4XW7mknmOnx041nzNtmx8QmqyU9S8CS+Nc8CGGS1eTNmAS6yUzt0oTVNX5lb8kW+9U03Wb/Grsy7yXzGbOfZXKGljQn9nHPBQjxOzqCJw8YBNs/mrSUy3vscYCf8krGjZx2TTeZZwGLozOFx9fWl352R0M3p5GAI1BkDOgSXOK10A90muEG3KRsm9dkgHI0khX1BN3s2v3Qgp1g/1opTF8ZLx8CDzMQ/w76H7e/Me2Mzd4JNbCZBS7gkKWQ0WyVZ5NEk9StqNh/I9iSFzBOsYKcYPzmi3Z05ri31jddtFJk3NqS67F4BTfZs43eyy3owTjoMXycp7AUy06YAOcHBVydJMX4n7gRyyAHvr2UsjH1HUpIi6CfIx16BGUysDbLGVzPhK1+yFmBNDsKSvBz2m4z5iE6Rn6QIttGfMKUj7M5vFCy7Q2+We9phBJLUY1+ENaUluXdUpgkjjrx7i0bUTLkrRyhZFOrqyGecMnDV32HCtvIixagfdDIO9J2MaUEXmvXvvtXj8HhOUg1QCtb7yhkr6m+l2xUViyLCDsaSe44xYSZRDOhDB0NZuXEYq7wk9U8LohfdxjMc94qIW+Zl/ehfsb48ozFJQa9ntLY89RjE8tFpbowtiaKZJ8aU/ocdoRutSeqfS3KPPvgN6bb7Jl9q/JvMh270JmNDGG76n8QNvVKra17UNR73yZjWJNXhNw7rcThG784ioQNPS9ZSknpqBw3yJPzsGS9LeBtt6PHsPeXGOBy7OnhMGVzU9c7OSvgJ7ehBM3rkDTEwVqnNi3p4E83q41Hvmzv38pRJxitIl4znU948UzLmH3Mm4aHWv3EYl/GjOxnTiH55xmT+4JGMy9wbp3ElWTiCrG6TD2XTR11zDcudNdfGQi4nY/o3kVYvaIKBhyT1O8Vt3N5pYzQOYyDz1cXP3oOdMStPUvWQe2OGBx7Rv3fmkdCrzyRLupNvPGgyZjSh0zOekIxFajyOZ8lQDamPP9Q39+7lKZO0r777nZGS8e+VGCOah7S5l29seB+tyVJ80NzquSapdpR59AwTY8cD5tv8J+M2jFvbcIHtsEy7ayElWdCVxmD+kjH98ILPJJ1wUtf4k9TAZcMAj7X8yffWyjNa8bVkXpLUP0FpruRJ7tUzFsnaty6MwRW/KJcPjyR1jbuXpwwWSbyyIRMegJUEL4kcbGtCviQfHvi/YalesohNkkKf4L8G1hBnMtW7rWy9X3db7wPo9O98BJJUI8vCaskiSVKF0eS9Oi2vDD5J6i8dK09SNn1mckmy0NckLUkq3cn4qhxNrmXwSbIw7iRl1p8kC/2hR0JTkkrv5P2wvGz6JFl23GUGn0ZTa7o9J1mWjiQL42z1y5w+yRjLYXdJKq1l9ElS77cF27ITPvCSkmzWe5LKJ60gSR3LtPrJYlmZwwcNMJXc6zLJAh/Il4ZlyebjaXWSlOHHe1KyNH9YZ173SSruaE3G9CSLefKlRm+SOm+ey6ZPktqGvCRl+ElS6w/z5n2fZGHuhjS6bylJGX7kD8fdypLUsSaL9ZPU9r2TLM2Xp51kMb/M8ZNkM3rLpk+SWlY2fZLUZ/SiO1mkOcmSeVTeUpn4tPwkEyWzfUyyhMbWW5KFcSUpPkkW8oxXQneS2kYyLi+bPklq/VanDD7J+J1B1lxvk2yRNjQPx1eW+aiXpJYmqW0mqXh4XxrWKaOP52n5o6I19w+tUpIF2pLUcZaJT5I67iS1xHvrZZwIbvSiORmPIUmVU/JaUq+MPkmWjDdJxUU9dZKU4UeelCzNH9ZZ7/dJFjCAQ0tJKlbtuV3hUUafZFyeZPS09J86ydJ8eVKyNH/pm+vvqTv062/OOsVbRKAXdgQ6Ah2BjkBHoCPQEegIdAQ6Ah2BXQOB7tDvGvPcR7kcAj2/I9AR6Ah0BDoCHYGOQEegI9AR6AisUwS6Q79OJ66TvXMQ6L12BDoCHYGOQEegI9AR6Ah0BDoCHYG1gkB36NfKTHQ6NiICfUwdgY5AR6Aj0BHoCHQEOgIdgY5AR2BmCHSHfmbQ9oY7AtuLQK/fEegIdAQ6Ah2BjkBHoCPQEegIdAS2HYHu0G87Vr1mR2BtIdCp6Qh0BDoCHYGOQEegI9AR6Ah0BHZpBLpDv0tPfx/8roRAH2tHoCPQEegIdAQ6Ah2BjkBHoCOwsRDoDv3Gms8+mo7AaiHQ2+kIdAQ6Ah2BjkBHoCPQEegIdATWOALdoV/jE9TJ6wisDwQ6lR2BjkBHoCPQEegIdAQ6Ah2BjsC8EegO/bwR7/11BDoCpXQMOgIdgY5AR6Aj0BHoCHQEOgIdgRUj0B36FUPYG+gIdARmjUBvvyPQEegIdAQ6Ah2BjkBHoCPQEdgcge7Qb45Jz+kIdATWNwKd+o5AR6Aj0BHoCHQEOgIdgY7ALoFAd+h3iWnug+wIdASWR6CXdAQ6Ah2BjkBHoCPQEegIdATWJwLdoV+f89ap7gh0BHYWAr3fjkBHoCPQEegIdAQ6Ah2BjsAaQaA79GtkIjoZHYGOwMZEoI+qI9AR6Ah0BDoCHYGOQEegIzArBLpDPytke7sdgY5AR2D7EehvdAQ6Ah2BjkBHoCPQEegIdAS2GYHu0G8zVL1iR6Aj0BFYawh0ejoCHYGOQEegI9AR6Ah0BHZlBLpDvyvPfh97R6AjsGsh0EfbEegIdAQ6Ah2BjkBHoCOwoRBYVYf+v//9b/nPf/5Tk/v//e9/OwWsf//73+VHP/pR+eIXv1j+9a9/7RQaeqfrBwF82tI0qpXhZ8n9sI5nPD+tbFhvNe/11frclnbVl9Cqvnvvt+S5lSlfjaS9bWlf3y0N+/V+y3c/LJvVvX70iW7XrfXT6qvrXnLv/ZY8y99aW6tRrh9p2JZnNKDH/bBs2r066kvuJe8Ok7Jp7640T1/SsB3P+tO/67BsuXv1JO+q4977LXluZcp3VkIDWiT36HD13Gj1LH8yyVdHXffDcnktDfPnfY+uloZ9y0PfNPqH+cN3Ju+1Me19+a0N95PvzeNZv2hwbf25lzdJc8uTL3lWt703vCpraZiv/tbeHdZfrXu06Lclz2gZtu95Mt+zd1yVD+tPu1dHXUm5q/eHSR1l806NFtchDZ6H9HlernyYP6RfvjYm31VnS2XK10pCu4Te5WhSpo7kvtVzLw8GLclr5Wvxij5pSJvnNg7XYdnwfrKe51buvYaBq+dheau3Ua7G19K0ccqTlhuvd+E0TK3+ZJnnVrZce+slf1UcemD89a9/LS9+8YvLNa95zXKzm92sPP/5zy8f/ehHC7BWAoa2pe1p489//nPt/4EPfGBB1/a82+vuegj89re/LXe+852X5VXBodvd7nbl+te/fvnwhz9cGj8SFu95z3sqz9/97ncvP/vZzxbAU6elhcwV3mjvl7/8ZbnnPe9ZrnOd65QXvehF5S9/+csCPWXio/6vfvWr8sxnPrPc8IY3LF/5ylfqevD+Na5xjSJd/epXr/SvdJ0Ou9bve9/73qJt6aEPfeiwuN6r8/e//7287GUvK9e73vXKU5/61EqbfOmPf/xjefjDH15pgzGs64sz+k+fP/jBD8o97nGPcu1rX7s89rGPLWiQP61LeH3/+98vj3zkI8sNbnCD8t3vfrfSf/vb377i2rCdNvZp7a007ze/+U15whOeUGVuawvtf/rTn8pjHvOYivGb3/zmZXncO8b0zW9+sxxyyCHl5je/eQ2KavfAAw9cGJNxPepRj1qO5zSzQ0nfr371q8urXvWqhffRbw4OPvjg2v8LXvCC8re//W2hfPJG/V/84hflaU97Wp2Tj3zkI5XO9j7apQMOOKCuVfVbmmxrls/6NF6y5F73ulflN3nST37yk7pWrRu69HOf+1wdw5Ae78Jpv/32Kw95yEPKH/7wh4U6v/vd7wq9d93rXre89KUv3eJ8lxl+0PiJT3yi3OQmN9mMBuuM/DJG83HUUUdV+snPu971rsW4XvKSl9T1BJNJMv/xj3+UN7zhDXWOrVMysNXB70984hOrfHz9618/94A+eq0Za849ulyN+VrXulaVicb85S9/ueLywhe+sPK2vIbHr3/9a68tSeT4ve9976qDzL02VXD96le/Wm5xi1uUW97yluVTn/pUxVLZLJNNE/IG3VKj3by3ftGGN8mLlu/KNsTbD3rQg4pxtfqTV++T+6973evq2PQnz7x6X7+Svsmtyfdn/WyziExCy61udauqX9FnjM94xjM2m1f6Dk3K8Si6pZe//OWbzZl2bEiRw9r+/Oc/v1DH+6997WvrOoGhNa++ttdKQs/Pf/7zQr7d+MY3Lh//+McX6B/SqN5nPvOZqp9ufetbl29/+9u1nnxrhG41xxKs8I6yYRtr5R6vkrn4tdGEVmsADsbA3sE3rXx4peusFfaH+nSB9823te/9lu5whzsUduvw/Y1yT76T/+b7Pve5T/nhD39YeaKNz7itH/q95U1e2RINq3Z93/veV9uhM1ueKx1FPk+2sR6fV+zQYziOwmUve9ny4x//uDzvec+r6WxnO1u5//3vXz796U9XEHcEHIrtOc95zna/f4ITnKCc6UxnKgQo+nak7/7OroEA4coxfuMb3zjV+GMsMrpue9vblstf/vKFIGU04iv8/tOf/rQceuihhRG3//771zaUMTCOOOKI8r3vfW+7+Xc55LXLOT/zmc9cLnWpS1XHi+HIuJp8h3KhKClERhPD95znPGc5+uijy8lPfvJqADICr3KVq5TTnva01bicbGNHnymwww8/vOy99941XfKSl9ysKWOB+4c+9KHy9Kc/veKERnQLyDFkTnaykxXYkynTHJvNGl1BBgw5E1e72tUKZaCp+93vflNxUZfSNt9oRD95g8bTne50C9he4QpX0MyqzX9tbMp/sHzHO95RnvWsZxUObavCEHjc4x5Xjn3sY5fnPve5FcvXvOY1U+mxDhgjt7nNbcpee+1VKMxTn/rU5aiRs3XWs551YUz47ljHOtZUXFq/235drPn+97+/OqDWjfEosfbMAX696lWvWvAHXmjl6rQk75Of/GQxJ/SGupe4xCWK9gQBbs+0T98AABAASURBVHrTm9YxcBYZCMc73vEKJY7/6C/vt7Zmff3nP/9ZGG4Mi0tf+tLVOdUnGj72sY9V3bX33nvXtXOuc51L0ZL0wQ9+sGjjAQ94QDFmMsG7Ej6AFSNFMKkZMUsamPEDOsg9MuDd7353PbHXulTGEDvHOc5Rx3fBC16w4C/5xnGe85yn7LPPPjUo8eQnP3nJu9pQ7+1vf3vh1Fl3AvaMPkagdNBBB1W9z9Hi9AgGese780i///3vy4Mf/OAaWLP+9Kl/fHbe8563jvkCF7hAHTPaBTEab5J5e+yxR0nitYXk/Xe+8501gIF/jfeIkW6R731rhwNgvd7tbncrgr4LL8/ohhOJB+kQidNmnZLfrUt6ABYCV2QmPDg03/rWt4oxH3nkkTXwwk5r7wyvAukC0W9961trwN0Y1RXA0J9+peMc5ziFTBq+O+t7Y3nXu95VT4G+6U1vKhwuDgjZwj4wdrRJNrhOetKTLshMju53vvOdsvfee9fErpikVzsf+MAHarsnOclJqmOMt9Qz93jH+qdzrAO8oGytJPjg03333bcGvdlN5lv+kEZjEoTCJ3vssUcxr+S+8Rw10j2Xu9zlqty2NujW05/+9FP117DNnXWPHw4//PAi0N9owAvsCnRf+cpXLmQyPdvK2xUud7nLXQq9RG7RCzaZrJuvfe1rtRo+wk8cfnqeXq8FG+g/805nfP3rX6/yjg0roEXeGKZyOo6tYx3Jm0wwhxnZAS+6ULCE3UwvsdXlKRP4Jo9OeMITTjazLp93WynVwLMYz3/+81cHnlI5/vGPXzDks5/97LLbbuMuTARhj0Exr2d9u29pWKauxWEiW748dV2l9r5ySZk8KVmqFOX11BEYIoBfODgUCb4dlrX7JOW+971vuehFL1p3zvA2haP8xCc+cT2NcqELXajuRBHkjBwOxCte8YpqdONh/ai/0sRR4Rzf6U53KgxX6+4LX/hCNWCHbVtbBNqBBx5YKH1RfMLs//7v/wqlyPigOG90oxsV+daqsmEbO3pvrIw2BgnD9dBRsIMiS5auR/Wc6OHYnOpUp6oOjh1kzjzFb1wHHHBADT5QYOZgR2nalvfMGeePY7777rvX+WZQwnL4Pro5JJwPc2xHHv1JqpEOb9hKlAinMlk69mF7q3XPiaOUhvRyVDl0TkAwtjnrjD8KbdivdyhJO0WMDQp0zz33rLL7fOc7X5XrxiM4hL85XMnqjknwg/OKlkYbh9u8O1HC2Dl4tFNP2bfy4fUb3/hGYUDC/5BDDilnOctZKv3GLTjBgaDgza0dNVf18Jv1wbActjere+Nj1DFYBBE5aMc85jGrE4dfBLCPcYxjFHzlhApnJVmKNV3LGLnIRS5SzJUgnXbRLCBlPVszeHkaD6s3y5SknPGMZyx4f7If+pxM5ICRY+bguMc9bnVCOTZOQpFP5oQMwG/DNuh5doUTUdYd/uAQOCFjR9NOIANaoA2/29X1zrCNWd3rx5yizXxI+sJbwzGTifiPzCXH8ab1Zd5OdKITFevYe8Nkd9+6swatzbZ7x9m74x3vWMhavE+OcfZa38M2VvPenFmX6JYudrGLVV1iTPphn5HnTjw1WuhNQZdHP/rRNfAm2GhHlmHe6nhXEmDUPkysCe1rmz0JMw6efvGM+qc4xSlc5pbQi+/oT3QJUMGEPWz9ohF9kiAo+4IDZvz401p3SsUax8fJ0jVObgnOmNeHPexhhZwSzDBAgSGnMax/u9p0LXqUrYWEFht57BV6iRwyl4Js5nVII+xsluw9Cm5wsryDh5PU0yx4G4ZsFXYaHYEHhm2slXubI/SO8Tea8Dd+JxPMp2RdDOuoCxf8dO5zn7sG4I0TFuqd8pSnrMFs+NBh6pPzdIP7jZbMr3VBt9lcIT8FyNo48RQ52Z4nr3TLwSNbwft4hwwhO21ckZeHHXZYtdthiafo4Gkyd7Ld9fA89rZ3kFLMRpiIwBJSTUmZEAuV4CF0MKsjuJQ1Y4pxRgET8HbpGCeikXZXGHbapMwpbkazI4QMNhEqzgJjh/Jy9OLxj398nRyRFsqbQN3B4fTXdiEE8C4eZHhwOPHstOFT0qKmlAwHiWFF2arrJAjhgQ9Fk+0oqU+hU9YUmEi8vtRfadKv9aF9TgDlIfLvedg2p9PaYfgLOlCujCZ1BCQoAu9Yo+gWrEiWGhTq7kjSt3ZhxihnVLe+W3vwcLqBcU+gogVN5ARHx9p3mkAbyhjnjPXJdlp7q3GFy5WudKW6M6h/O2qOTU7yBcPKbsNlLnOZ4nSGCLK8JIWhjR/QzHB729veVi5+8YtXZ201aNxSG5N0qkum7j4KTuAB5XYJRPbhaA7UkdDP4KIozYsxcQqS1IBKG5M1INhiVzVZHX7Rv5RkM5wYNYxBeErw9az+MHH67N5R1oxmR70ZQ+q0PO/jTQEOxnCSwlgUyICHNtSfZYL5Zz/72cJBudxo54k8+dKXvrSwc2f3gOFvx5XjJnA0jR5yQFvophc5xskYP+Ml07TNEGS0JJnWzEzzktT5TFLQ2jojDzkwds59hYlsUoZWp/zME9lm195Y8K3ylqw5gR4OnDL8TeY6nivBj9wgg8hGQVb12/uzuhqj0xJoZji2fuQbM7rwmvmwvpIUtDMkjVnyNQK7vMbf3ndNUqxhAQPyWrCEfknGbeB5a9guvjV8mtOcpmLv3VklmJOZ6Ia1QAaeNifGbF7NgwByo0F9zht6jdEcwku9VqddHbk9+uijy94jR88uNF2tzLt7jHZy9asvY4Yp/aF8XilJDfALgHI6OGmCF2QWbNgGaJR8RYJugROdd4YznKHqDoHWpzzlKfVU3yTd2oARx98JBXYHPaheW/9kuXVOHyVRtCYSOYuXyWtjls5+9rPXryTQ8UMi4WRO2e10vACf+U1SrF8YeB9/c+zwzPD9tXSPHyfpoSvJA3wgkXOCQJP1YGAejd8prSOOOKKwJ43dvCv3PhnQeH5af5PtrsdnMrCNFw+QIWwQY0lSA/VlCx91yRp4wY/8F1z2jLfIXfeagDN/cqNguSKHHiAMcEzmiL3nlpJU4JPU788wGH3f1FFV0RUKidGLwe0iUHi++0hIMaY5I6JQInN28ZQLADBiHOUXfWFwa4vj5AgGA/otb3nLEgOi9E9HYAoCFIRjm4RHMlaGDJEpVQtlw2EQDXfcDx+ql6QeSRZMwoOMa44BZ4gS971wxpe6q5GSFAIqSTUCBLccyyL8yuBjPVoLjGKRTQaHYJq1lSyOlXFBiRKYyTh/0MwO3aKPYmKECMZxWOxOTWLLcZzM06HgCLomyzybM1f1Vjslqcfh7IJwpsilabgwxtHIqFJXEJFCwBPJGEM02im088ZgWW1at7U9cpVxRVklqUY+/kR3a6PRimcZ1q6HHHJIPeLpPkmrWshlRqgxJYv5CxVW+SZJ1SFl9EGnExR4a/S48E8+XrITgt85s5wLwV8nEZJFOh1PVoeBxDh0wsXuF6eilLLQ5qxu0Op3ZRgUDAt8ZDdaUFsZ58VacYRX4FvAwddlptHD6CN3rDFHBludJPVEhR1MhgyHtpWtheuFL3zh4mSOMXIABfyMMcmCbMOj6lhXjLMy+JhDWCXjeU3GVzKDfFM1Gecl42ACp0j+rBJ6yH6Op106623YlzFz/IxZ0ILtMsmb5Ad9ZDcpGdM/bCNJsWniXUfqze2wHC+wsegq63ZYNov7ZJFGfVpz+Fdf+FFQjW5tWMAoyZL1zOl3WsV6TBbbK6OPoBcZS5fB1WaPjaNRUZVjrsYJU9+Dbf3In0fSH+fdnNh1pWPZqvKTxbHAhi3Qgub0Cp3BTrXu8blAFHwm6ZZnXp08wt/s5VbHbu5+++1Xv6ZE9rX8tXBFtyBWkkpOMr7Cgj6qmZv+S1KPqJPXTq6wr9o4k/F72nOS0tri4G96dV1ckizheUEqgZ9kPLYy+AjMkol24gV+ff1okp/Ic5ukdFayeRuD5tblbZIFPVBGH3pOUIQsGD1u079kERe8YxMClmzTZLGM/rUeBYngvE2Nr/FKK3bo2wKjhJcbq+/8OZIkMi9yIjJPIVGCIpEMRFEr5XbmCPEkdSGYBNEU7+lLpM/OpKuItx1LZRx+wo/iZNSV/ukILIMA/nIMV6RcQIrwZFAxMKYZf/hT8EjQSEScIiYoNC/w5Bgwx1odP16DTykuxhdlzYhv9b2z0qQt/diZYChMCiNKw5pRfsUrXrF+H1ogzI4fuvSvDcYQo2syIKB8R1OSKpC1iTYOiqDB5JqEUZny4exY81OKynLvTKu7I3mMUEr1SU96UsXMPE/STaFyfDn9dl0YpHbCzQdM9Yu/7ARzqpYbi3qzTtPwQo/U+sYPDHBKjYHotIoAKtlqbbR6dlbsHHPoW968rmg0N3Z86IdkUSmjgXPECLTzvu+++xbfu+ckcpCUS+YGHzo15tmOJ4PcO3ZJrX11lG1b2v5a2qf3rAtH4iVfixGgNgbr2JzZYXVEkzPrtIjxT/bmGK/1y/hz7JyT1+o4tcaJwKe+p8/xaWU7+zoco2OR+ErQr9EFI0Ez8+KrTOq3MldyzXUykTfLlcFxsv5qPrN94M2hpUvwKgfMFV8ag3kVIOScqU+PGCs6XM2z3XW6Rt60RP8I4ChzjFfb7iU7xJxgsogBq035s054k6PNmWXLkX2cW3PHERfYFDxzesEJn0aP9Um2sgWTpetZfSds6C72HQfIhpGvOeGX1oYTLTC3fpOlbbQ6s7rC15oVMKfjjdsGFLpbn+oYN2ysRflJCj4V0KM/rF+nVeCofJiSFPNq3H43YiijHCFW5nSrddSCWcP3d+a99TjZvzWQbD5PNj3IMoHkV77ylQUew3fZZGS5r1dYS8Oy9XJvftlf9JeTctPoJgc5mL5Db64f8YhH1I2bVhc/WVO+dplsjmOrt1GuvlbEdqbf8M72jgte7F6YOSUxfF+Zr6Wai2TjYLnbcJA7ck+gMkD8IMTk+0CTKB4RO+VJCmFmYQ4nKclC5FW9bUl2mkx6q2sxzPvoVeu7X9cPAgwqjiMBy/igGBkRdhkYGnh2OJpkrIQpYDvdAlGtTpLCkBGlF131vrYFDKwJbTqenWTY5IrufSWF044e62iyMetRPuMnSXWw7RIZY9n0YVwJRHDQ1N2UvWqXJDUgJ/gmOposHT/FxghqOJbRB02cLMeqOT6jrPqPQheRNq5kaTu1wgr/Q4PdbI6QaDBHy3fNGdBDzHRDMahPpiXj7817Hp4ewF9JCnmUrD696NiWJJKPFriikdNH9toRa+8nKXvttVf98TH8ghfMl/uhIyia7fgbp7q9O48ruile68r34RjDk/0akzVnBygZf02AY8TgbnU5D3a1OPRJ6ppw3NUa4CTZ5UtmOFdl/IGfeUhS14dAtjHhn7Lpk6Q4ecaJEXRMNqfLPAli+66uedHmptfr2AQaBabMGz3ZytbKFf3WtDFaU40u654Rxpl7o2UmAAAQAElEQVRTp+W3qxMW8LL+5DGUOc/kiSC/d/GMJEhLNnMY1J1VQgNZZheRPmGQ+2qAK9nV+k1SjBmdZFnLRyvnH39PG3OrJxBHPjn5hbcbBkmKTQ2nOughNpE223uzvFpXjq06aYF2/ZI5DQuBDnPiGRbKyVTBUnLWup2kj4OO/9VPUteJAJbxwrmMPtrx9QMOf7L5+hhVmek/cy7waR6taV9xw2sCGMp07srG8DUD2MhrKUkdF/63VpPNx5Ck/p6CjSqnA51EKps+2rMBJvBHzwzX/6YqO+2SpP6AsGCHeZLwpHVo7U4SlqQG622AOLlLFw/r8B04sYKwyeY4DeuuxXvjF/CHB543d5N0kmE2hQSkBWuc3GA7svVaXWuN7WlztOVt1Kux2hRxAkYwLNn+eYe7jQk8NekXat/XwAUek+1ve63iviKHPkkhVByHcpxeZJ1RBSzCWGQEA4qsWdAixwSyPELMD0CoSwG4KmN8MCRNhsg6RieslDEyLQplSYqIqGP6zWixo0R4Jql/8kZ97aq/Vieg0zV/BCxuOyV+HMP3lESGKWUKmnODdx0vxjsi7iLw+BI/MaTsaqOaU23HluJmPDLKGZwENuOL8hK08qz+SpN+RHFFsX0nSFTeLgXaOG0i24wl0XG7875rpcwaskYoimQsvKxHP7jDGUrGeSulz/vWMhrhgSY4tu+Rw0fwhIxg/NiR8l07dQU/KG30OFpnrBww79j1Eq2Gpz5mkbRN7jA+kxRKk/zRF/rsTpMjxsLJchSMTLLTZufNj8cl4yO+5sQRsWT1cEXHlhLexK/wR6e6jAfOO3lrLvCHIBAjFE+YGzgzIuBul9CYyG2GpqQd7ZGtgjP4Wt5qJ3Qw2CX9aR8tTg844SXIYG6sN/xjrOh3L8ruR7Ps8ngfb5tP3zvVjsTBcjTV+k5SjWljUW8112jZwidJwdvoY+AZg/HRY5xzDgpj1rh9ZxgPmgN44DNj9471ZTwwI48EBWBg7Nogv9RjDFrjnL0tkDWTIrSRPa7G0zrBWxwT9OFLdgC+Ug//Ca44wWCurSP8bF2SD3Q/ueF4LkNN+5xJAUA4eY/Rz87A73aOGYTkYet/Flft0yECRJLAoACDo9UceGM258bsayM2QdCcjOWD+SWfrcumK9BvzNapeXW6hCzUBr2jDXqMbaRNOMGDrGpBq1mMdbJNtKFDUAnt1pOvscBBol/NjQC3OvSpoIedeWsXLuba/ONrAZ0k9cdc8YNAnvnH12RXCwDAwbgFRyZpmtcz/WAu8LcAomA0mdL6N6/opAtg49lXRgQozZX5pK99zcI7xtr0inpkg3nFC67mVXvsEbjBDN9wlOkkbayFZKxOHhmbMZFHAjoCEzAzx06SoJUsIJeNyzjJM4FoZRLM8IFgVTJeL/LXYjIG82RNoBuNeIPuZMOYP7xOjlun6tNhxg0z9QUvzCu/SmArWRwz3WC9C+Aki/ne2ygJbmSEv1LDP7RG8ItxK5NgDDtXz8buGZb4p+XBldPOFm74qiuxncnlnSk/0LHaaUUOPWIoM98v9sN1nGvgOS4nAgtkgBFYdgs4TKLQhJZfVGZwMNQJKEra35gUFPCniSgw74lSMdQ4X8ooS45KkuJ47J577ln/BIof2rMIBA8IQv0zGPxZL3T21BFoCCTjiDDelSgZqRn2lCV+xr+MBvyMrxkndtspF22JIOJnR6sZKX6ZkxGezEbYMup9L5tDTzk6Im1HhqFLcfo+Lt5nVFgP8hz3Y2w6mmctJmPaKFHRSeNYzcRQcURSv3a4OYq+N5qkUEgUvXVPwKLXkSprn+CFufngnJABdqJE7a1rUdZkTPtq0qutJIUc8UOb5AWM0U5mcRAoE8e4KVrOETnFyVSPHPNbBhyyZOzQ25VqY9b+rBMFJpDJWGBEcwb1iZ/xpN93gKO5cHwtSWGIwtu7IuBOJJC1xsT48ucCGaLakexkO+Vh3jyvdrIDRa4L8JDd6BLQwefmwvrD74LHlLy1iX6Gr7VLL6AN/fSMr0IwCBqdHEDHW9VtefO+oo9Rh3/wlrFYC5wdZX4IDJ/jNd8ldZWPTl8lMwd40Fd7YGGNc16f+MQnFg4FTHyPmrMEG2vR91LxgTbmlcyd7wibN/Q6Hu6qf+sa7Y4Jc2x8JYC84syRA3jPnKvj9IG5ZnzZiWTsqttkiLlmG5Bv1qk1jA98zQe/M/hg7B19zyqZI3xFdknuObZwT1KM2bwaM7mLN73T6OHUqMsxlgc/YybbjZlTYPzmFV7qaEsf+IQOIt/ZSGymoUOk7iwTOUI+tz6My/jh0JKxSeQoWhnr9IN5hgtnB3+QOQKn2hKMFDgnF+xcOplgTpOxDqCj8YavCiXjPO/NKyWpf1JO0MmY0GhtD+W+tU3mwgRd5pVzired9PN7UoKp1m6SwsGADUfEva91GTPZLBAoYKAdpwG0oU96yDvaULYWUpJ6SogsYgsYq2C9tQgLgTb8Cw8y3rrHD/QUX0Jwtmz64At6TSB2U9aavZBH5DH7zNwan/nBy9am05DmDQ7NoSen2W+cd3XoP3qKjLDW2UJtwMq0YS21vI12hZnfyWED+A0VMoLcY/u2sbJ1BLThRZ7KxyewJC89S2QoWWhtJEtlBDlzwAEH1B8mTZaWeXe9phU79AYOMExoEvwYluMiIuMi5hYwRUXhMKoYu3bz7WqJ3IrUicBQ5BY+o9/uhQg0x4mDIt+OqnoEIkGvXcxO2PkBMEqTgy+CLzouaKAtwg6NPXUEpiGQpHDGHHlkICUpHF+OJkPQjiylw3AkMBwFlY//GBvqMbYpV7thyeyEg11Kip4B5Lt5aEYXx8uxVbsYnK4kxTNHgRIQaLOWGFoNA7uCdjyS1aWXw8s5RxdlLgCi32S86y3IYH3Cz2kGxgnlRzgzWOSbB19fgKtACSWv3Ub7LK765TSSTxQy7Bgh5truB7zV8UxukTd2EznQ6E7GOCapf3dXsET9WdA62WaSAm9KzpFPOzbq6J8hTB6j1Y/A4ZUkxc4o3jUe9fAug0o9YzdGZdpJUv+soGCV51kkxjwHj4PCYdOHEyV4WnAX/vgdzRw3POLe7m6SelKMrMcvvnPKsFZHOxLjgDHlfmcmNPmdAjyG18gUcyIf7sboz3kxZBw7RmuSItBEDzLmOMr0G8ee8cPYNVf0rFMYdnZhwRCyQ2x+tbOYZn8Ha98DtdsiqJCM14e5waOcfMYpfZ2kOOFCtwvat7kmuzhE1p9dLrxsLHayrTs2g/bkJ6lf2SOvBUbgy9F3QiXJ7Ac86ME8OIlkTtDb5suYObACaIPqhR3DgFdffpJizDYkjA1GgsfsJ23gDbhom3yFs3WLl8is3XffvWKhrVknQTNrCy3T+jIm9hn+tm7xpyB5m2P8zp5TT8CcA5ukwFC7gowCYPicndn6oN/wgHZb3jyvxstuMLe+343n0EhPJWN+I4c5teqiLUlxKo1zQt5xKJouVE4uGC/+oJ/pecFizu8+++xT/5yZ8dLn1hDe98OZTnvATxtrJRmzrzGRcdai4BynNUndgEN/kkJOuLeW2QvGaYxtHEmKv5ZDRiZjXFvZWrsaK94WnCR70ecrIXTaUIeR3cZjnHSY+yRFMA4facfvYQgEqKMdCS/hH/cbNSUpxs8WYHeTD/iDPk/G8z+0dZxOgwX+h2Wzf+VZf2zHZPyevJb4owIr7XmjXFfFoU9SjzBivpYAnIyBTJaWK7Pgk9QfCGGkeE/+8F4d+dKwTH4ZfZLUSKBySX6SBVq05b1kTEfpn47AFATwTUuK23274i0JL8lTJ0nlMzzWypLZ8lmS+l0zfbak7yTVgGv0JYvPyqUkZfgxDilZmj+ssyP32tSf1Ohp7SSp61WdMvokqc/qSckiLerIk9wni2VlRh/96A/tkmddJalyKhnTIF+5pL5n9aQkdS6GefJnmZIxfXgCTcO+3cuT3CeppLiXksVndVpKxvm18ug/daXR7Uz+wRH9kn6S1PWFHnkteU6ygLG6ZfRJUnlJubaSlOFHPWmYt7Pu0YFOqdGapI7XOOWpk4zHkIzL5JfRx9W70mQ9eZI6w7LRazv+bzvfTLIwljaeZDwWdDX6ktR5TMZXdYdJ3TYG90mKT5Ilc61O2fRxr33JfTJ+Z1PxXC761X+SOj7PxmUM7pMsoSNJHU+ymJ+M81p97UnaSFLbLaOPcvmSMs+j7Ln9S7IZ7WXwScayCV1Jal1YtITuZDwedYyhjD5JKg8pl5QlKe0z+dzy53lNUseDPnSjqQw+SWp5MqY7SZ039SXvJCk+SRbKtCOpI6nnWT3Js3xJfhLZayolqfOHVgmdZdPHPdo9ulfu2dWz/JY8J6nYtLy1ekV/4+tGt2vLa1f1kvGYlEvG5AoHaVhHmaQ8idsNm5KxvGhYtauxG3SyWA6nYb57ST0pyZL1VwafJJU/ywb7rIpD3zBJUkECarKU8ZLNy5LFvPaOq5SkLuJk8SpfSlLaJ8lmfSab55X+6QhsAYEkld9UScb3STxuxl81c/RfkmXLygw+SRb6sw5aSlJpT1KGnyS1fpJaXiY+SSZyVucxyUK/ZeKTZAktSZatOxxfmcMnSaVFv0lK+ySp+WXwSVLzksV6ZdMn2TxvU9HMLmhuKVnaf5LNaE1S5yFJaZ8km9Urmz7JYr1NWat6abS7JuO+klR65A1TGX2SLEu/uklGtRb/Jan1F3N23l0ypmWSziQL401Shp8kC/QnWbaeNltKUnbGR59JptKYbD2/0e9aRp8kC2MfPdZ/SWr7ScrkJ8myZWVOn0a77pJUeuQlm9NbRp9k8/wkC+P2bktJRm+M/yXZattlxp9kkZ5pXaFbfpIFWuW1lIzfT7Iw3jL6JFmon6QMP0mW1B2WzfM+ybI0ltEnyej/xX9Jlq2fZGFMyZbrTWJX1uhnGp3Jto2zDSlJu13T1zZW12RMc5KF+ZbfUhl9ktT5TjJ6Gv9LslA/Wcwvo0+SWn90u6H/NYyG1yQLY56Wn6Rik2Shnptk6bM8KUmt734jpVV16DcSMH0sHYGOQEegI9AR6AjMFIHeeEegI9AR6Ah0BDoCK0SgO/QrBLC/3hHoCHQEOgIdgY7APBDofXQEOgIdgY5AR6AjMIlAd+gnEenPHYGOQEegI9AR6AisfwT6CDoCHYGOQEegI7ALINAd+l1gkvsQOwIdgY5AR6Aj0BHYMgK9tCPQEegIdAQ6AusRge7Qr8dZ6zR3BDoCHYGOQEegI7AzEeh9dwQ6Ah2BjkBHYE0g0B36NTENnYiOQEegI9AR6Ah0BDYuAn1kHYGOQEegI9ARmA0C3aGfDa691Y5AR6Aj0BHoCHQEOgI7hkB/qyPQEegIdAQ6AtuIQHfotxGoXq0j0BHoCHQEOgIdgY7AWkSg09QR6Ah0BDoCuy4C3aHfdee+j7wj0BHoCHQEOgIdgV0PgT7ijkBHoCPQEdhACHSHfgNNZh9KkT+DeQAAEABJREFUR6Aj0BHoCHQEOgIdgdVFoLfWEegIdAQ6AmsZge7Qr+XZ6bR1BDoCHYGOQEegI9ARWE8IdFo7Ah2BjkBHYK4IdId+rnD3zjoCHYGOQEegI9AR6Ah0BBoC/doR6Ah0BDoCK0OgO/Qrw6+/3RHoCHQEOgIdgY5AR6AjMB8Eei8dgY5AR6AjMIFAd+gnAOmPHYGOQEegI9AR6Ah0BDoCGwGBPoaOQEegI7DxEegO/caf4z7CjkBHoCPQEegIdAQ6Ah2BrSHQyzsCHYGOwDpEoDv063DSOskdgY5AR6Aj0BHoCHQEOgI7F4Hee0egI9ARWAsIdId+LcxCp6Ej0BHoCHQEOgIdgY5AR2AjI9DH1hHoCHQEZoJAd+hnAmtvtCPQEegIdAQ6Ah2BjkBHoCOwowj09zoCHYGOwLYh0B36bcOp1+oIdAQ6Ah2BjkBHoCPQEegIrE0EOlUdgY7ALovANjn0//nPf8qf//zn8qtf/ar885//LP/73/+WAOb5T3/6Uy3/7W9/W9RfUqE/dARmiAD+++Mf/1j+8Y9/TO1F+d/+9rfym9/8pqj33//+d6Gee7yr7C9/+ctmvL1QcQduWtu//vWvyx/+8Ictrgt1//rXv5ZJGqyl3//+95X2ybLtJUkf2tLm5Lsw+te//lWsX+nvf//7QhVl1r18OMFZ3kKF7bzRv3bgIpErrpPNoFefylvynvxWFx1oJZ9a3o5etYVPzNWwDfn6QIsy9A/L2z260GEs+Mx7wzLzh378pm4r29Hrv//97yqXzVtrQ5/DuTIeea18eJWP5xq26JJnfMbQ8l1/97vfrera0A+64QSTSTyMDT2T+Y1+Y0STd4f1tNvmSrl67Z3Vuja6J2nzjD/gBT/YDvtEGx5Ybk60692WtIGfvKdt7bXxmqNh2zt6r219oKm1IU9fjQ74ylPuCl/Yep6W1CEj0GrNDOeglcnXhnmWN62dbcmDGZxaQjOeau+iQ5l8fcJNf/olC9FoTuS1d4ZXuMOn1fPcyrVhvpXBZLk2Wv2tXY0FJtozH609VzQaB5rVa22hx/woM27ja2WTV+0oV18fbV5aG/L0o97ku7N41q/+9Ismz9P6QXPDWf1GnyssGmZbamNau6uZh0ZrRkJXaxuPNPqUtfzJq/fNn3kcjgMm3se/ylzhJX+yjR15Xu130GW9oBWvGlfrAxby0L8lLFo9bWhLm60N7cGntTHEutXp147ArorANjn0FtU73vGOcvazn708+9nP3sywI4guf/nLl3322ae89KUvrU7JrgpoH/d8ESDQv/e975V99923vPvd796sc+U/+MEPyj3vec/ynOc8p9ztbncrr33tawsloeztb397LXvuc59b7nznO5fvfOc7m/H3Zo1uQ4a2v/zlL9c2b3vb25YrXelKRR/LvfqFL3yh3OpWtyqPfvSjK23qaeM973lPeepTn1rueMc7lhvc4Abl5z//uaLtTtp617veVa561auWH/3oR5u9z4B8+ctfXp785CeX/fffv9z1rnetwQ8VGcL3u9/9Kv1PeMITykMe8pAVrXFjvc51rlNud7vb1XSjG92oXOta19LVQkLvN77xjXLDG96w3P72t68JXde+9rWXBEbUe9CDHlQe+chHrnjevvvd75b73ve+m9HCoLr//e9f+QcOz3ve8xboHN585StfKU95ylPKAx/4wIJO9KNP+sxnPlPHgAdufetbl49+9KMrotd8feADHyhXv/rVy9e//vWFthg7hxxySLnTne5ULne5yxW899Of/rRM+1gDd7nLXcoVrnCFmshueR/60IfKda973Uov7Pfbb79yhzvcYQnu09rbnjyGOTrvc5/7lGc+85mbBeNe9apXlZvc5CbFeCbbNfYHPOAB5YlPfGJ52cteVszN5z//+YoBg/fggw8uL3zhCytPPOIRjyjqT7axo88M0te97nXl0pe+dOFMDNthpKL5ile8Yl3v5nxYDls4PutZz6q0TpYZ841vfOOKu7VxlatcpTztaU+r8gAvkV34x9ySW8P3d/Se0WyuX/Oa1yw0gc573OMelSfwhj7xsAo//OEP6/q/xCUu4XFqMgfkyGMe85hiDEObQduHHnpogcHDHvaw8qQnPam0tqc2tpXMN7/5zYX8gJdkPTz0oQ9deEvf5kOyFqxljuwznvGMKuuUw5OsnkaHNUYWwkD7X/ziF2vb6mrj4Q9/eLWJ8KOx1cId+M96IFef/vSnF4m+Iuv1Qy6h0Vqk5/C9fOnII48sePxFL3pRsZbxJqdnGgmCDocddli5+93vXlzNpTboGPNtjPTM1772tRXNybS+p+XBks6ll2H7vve9b7Nq6DMH6FX3ete7XvnJT35S61nX5ppOIgfMwSc/+cm50F4J2PSfef/sZz9b5RW+RrMiV+uU/r7NbW5Tddkvf/lLRUuSenQz3U9umWfvadfckynyYHTTm9606qfl5nhJw6v/sNUW8Y55Qi/ZYX0ZhzG+853vrLaMcbBlfvGLX2zWnnpvfOMbq92kDrtgyBfkFB2MV/Hxz372s83a6BkdgV0VgW1y6E90ohOVi1zkIuWSl7xkNb4mF5EFx5g5//nPX5XKCU5wgl0Vzz7uOSNAsTFIGGoUx2T3FAQli385axw/6eijjy4MJvcMZY7F9a9//fKoRz1qVQwCdHHuOCuUEKOZwTFNiaH5vOc9b9ltt93qCRjPLZ34xCcuHFZj+Pa3v10oxWnjbPWXuzLeBD7sdEx73/rlAHKynv/85xfBEY6iugySYx7zmNXZffCDH1y0w4Bcrq8t5ZsP2Lz//e+vgRXY3PKWt6wKfPI9NDHY1Xn1q19dgxqMcjipqy3BGWNipHuWv6PpTGc6Uzn5yU++xAE0/pe85CVljz32qONnQHJUjjrqqM34hNPFmYSX4Ker9+04MDoZOvjM+/gOzTtK6+67714ue9nLFm1LrR00cMAZuOQyR/e9733vZrSq/8EPfrBwdAQXOJ93HAWNtPV///d/hRENd04mvhCEaLh7d0eTORIAvuY1r1l5ncOKv41Hm8q/9KUvFY4mJ8ez/JY8f+tb3ypf/epXC17kbHHi3va2t1UH2xo73elOVw466KDq6MMAD5mH1sZKrnQhp8rcDdvE029605uK+f/Yxz5WPvWpT5VLXepSC10pf8ELXrBwUsc4FgpHNwIX1rp1B/dXvvKV5bSnPW258pWvXOeOYSwoyJg9dOQQP+5xjyvLyZJRc9v0D02vf/3ry6Ts/MhHPlJ1feMLWCapbcL2NKc5TbE2a8aU/zhc+Pyxj31sOfzwwwseasEP4+LwK+fQm3+yYEozW81CA1uDM0QOwI0cxf/wRcexjnWsgs/Nh/KTnOQkxRoxRg60YBBcrc/hfOqcXOE8Wxdwd3384x9f+cx6EYzgVBgL59JYJtvQztaSdzhw7Cr0WA/o5NjDTbtkCRyVm/sfjILUeBDdZOK97nWvyvPoM27jH/bLmVcHFuiG/ZnPfOa6zug868g4BJU9o2n4/mrf4z0BEcEYa0ZgxLhgPtnXcY5znAUdKDj51re+tQa56CHyzXpAPwfQWp8c+2R7q/1MLl7gAheoNJmvYf+nP/3pq5wStMCDRxxxRK03pME8clAFccyB4Aq+E0gnF+g+vOtqLZojfQ7bWAv3xi0ogW/x6k1ucpM6b/gRfac61anqMyzoT+t+ks/gZ44FNsh0c0/2WV9sNsErepQtx6bD/3hJ+z11BHZ1BLbJoQcSAXKLW9yiMOwZHRavfEYXw9+OlOdkrPgJKYua0fWGN7xhYXfH7iCFQmnZ9begOVYE1sc//vFCWFu03//+9zXXU0dgWQTwGGHPiONwNZ4cvkARiPhSuMc4xjEKpYKHOQTf/OY3q/N2rnOdqyg74xnPWI488shiF27Yxo7co81O7fGPf/y6Zjgw2sHv0+hMUpJU431YfrGLXaw6+kkKp8dzEk1tc7JGGe6CCsu9dNKTnrQwPqzzJOWUpzxlfXZklYPFkOfoHfe4xy1777133a3n/C3X3nL5SWpwkKENc/1R+Izq4TtJygUveMFyvOMdr+Knb7sVl7nMZSoeMLIrgj5Oqefh+ztyn4xxHbbFaWBs4R+0nuxkJ6u4fOITn6hzNeyHQYlO9YzNc5J60sEOIANEPpwZ5Byb4fvbc5+k8svkO2c4wxlK42cOomAJI2k4Ju/gCc4VA5Jcx/cMI/MiUIBO6wS+HD470km8uqKE/8n/JIWT1PBKxrwPb07HzW9+82X72WMUXKFHONDG1vhCoMCu36lPferKI8aPhxjCO8KryxGQbI4DI5SDwtjmXNCJybge7I2JcYoHknH+sP0TnvCE5RrXuEaVQ3Bvzvp5znOe+rUKjsCFL3zhAi8OtXGv5DQRPOjnvfbaq+w1SmhED3nJOeY43uxmN6uBHXyRjGlOxld1l0vkAzqtA3U8u0cz3W5M+Mz8uBd0wRfqbk8iiwQ84KU/DpA+4KQdPC14Rva++MUvrgEk+U7SkKVowufqw9fYlUvwEAS1Rm1UaJ9+sI7l4T3rjD7RxjnPec56gse68v72JH3hWwEcNElocmKGQyfgLJBknBe/+MXLKU5ximpPCWzZ8TUW9J373OeufC/wO+xf++glxwVr6SR9qMPOou/oUOPACxxPecpnlYxLUMR6QAv9ok+Yo7f1m6QGl9RJUo597GMXp0OSFMEc6wS/klP0Of2QbJ1HW/urdU1S5fGQdm033ke/ecJLSRQtJLvaZJf5VU8dz2SKe7JBmfkxRoFC9RYaWCM35kCgCH+h1bpDJ/mBxAtd6EKVP5NUW4ZsTgZYjCpZg04pmWe6XwADpuQDftH2Wc961ioHXQXCpgWBRk31fx2BXQ6B3bZ1xEkKo99ODQed4vQuhcJApVA8SxYwxU3gHnjggfUYKoedscZYpDQYCyKRDAsL0nExhrN2GJAtQKC9njoCkwgQ8gyP853vfFXhJ0sVg/rqMG4YWRQi5ZKkMCYZMhQpJStfooQoJc6Wd7Wxo4nxTuFoN0n58Y9/XI+777nnnlXxT7abbE5/kqoAKXbRezsZZzvb2cr2fKxFuzv77bdf0fdy7yapdDH6OFOOzNqthgklSnFa83CBpa/hMMqWa29L+TCRklTD1Pzssccem72ijpSkljH2BBo8oMXRcEfy1ZG30pSkYjBsBy+QR4yLJHU+4GG3ABZl8EEHo9QumXuGpzqcAAaJqvKTsfPKIFcuf0dSks1eY+yjtfVjp3taEIgzJBj26U9/uq4HR8E5Ohr0rpSk/qYC+b777rtvho2625vgQBdwxASYOCF4Sz5eFQB2rBZ9aJhsP0lh/NvNoz8cQT3LWc5SGPLWnMQ5o1e06dmcMBQn29rR52Rz3Dl2+hU84JwxRNGgD7uj+Mhu5LQxqZOk8lYrP+qoo4qxMWwFB8gl666MPkmq40+2jR63+x+eEwShn81D61ND5tna1z8n0tFZgThy36AAABAASURBVDPvKE+yVT5Iomo9TXTVq161HvFOUk8UCN5bP/qU0EC+mfv60nb+pw0pSeHsOOZrDJoRULMbT/Ydeuih1eHGE9aIUxTmxbOkf3R4ryXrFubal0cWmlPBYPiRj0kqHvhVQMF3e9Xd3mRH3u6yQDB69GXOOXb4Gw0SWcQxYkORhfDk1KJfwi90TZsvdLi3y89pd9xZ8MHaNxY6kD5MUvmP/aVf+tF7ZUYfega9+kuy0DeZWCY+xm2cgo9OSaBfFYEtp0Cstf33378I5OFnZWshJanjMh92lZ3WcwqsTHzIDniTU+YeLviOvjN2KRnrDPNl3EkmWtn5j9Yd+6TNqUC9+TAvSSoW8gSo6EgnRMrER/CCndLGjE/23XffGsghB8kkZV7D63wKwV3PPXUEdnUEdtseAJLU7/FSfG95y1vqDpXjNXZvLOLWFiXqWA2lKTJOcdiRT1K/r+w4KuVLeEmUE+Uh+uw7d743QwjKa232a0dgiAAjxpE7OxnJ8sptOR6SLw3bbPfL5bfybbkmqYaeuhQ0fm87k/K2Jzm1Qnnd+973Lo66WzPb8r5xfO5znyvWlZ3bJPU1+fVmyn+O9FPAdnadmGFY2klVlTHlKLejcoyKaU64etuTfF2CYje+5d5DL2eJMcRBo8R9j53BvqX3lmtve/L1LU2+My1PHb8PwDCDkeO4DPTl6sqXvLdaKckC35k/807eJlnSRTLeJTGPjkU7tu4Ux5AefKYNu0TJ0veXNLYdDwxzTokTGRx5jgb+sp7Nsd0ZO5XJ2IBFjzTsgkFnt5RzwomiY+gkBiVnlLPFyH/FK15RtCkgweEatrHa99YJ3rzoRS9afMWBk0RHCnr56s3Vrna16oS3fifH1PJdlXHW7cS1Z3nJeA6S8VWe8u1NnE5fqaC3k3Fb2tBeMuYLRrU1Zj4m+ULdrSU6346aHXibAHDQ/rT35EvTyrY1z/vWnuAVWyRJDVSZd4EfR3PJLnzGIWZncAI5WXavvU++DPuT5zlZxMizfGvDfbJYJl+Svz0JPwv2cIZsgFiP1gbnhSxOxn3okzx3esI7ggC+AmT9OOosmEQnaicZv4MOa4QzZL6dyoEDXSQguhy9y+VrbzWS9qVkkU7P0rT2nea0xnxNgm1Jp5pncsBXDgSF6UZ2Y7LY5rS25p3ndw0ErqwDwczJMdooI698z56jqw55do5znGOBVO/4Cgx5LiC2ULDGbpIx9ujljJPH5q2RaTPQmmRLkM/qtTLXJFV/yTeXeJctkoz1gTpSEpfqg6hbH7b8Xy/tCGx4BHbbnhEmKQxAxhgH3VE5SkXesB1ROIa24zcEMMUhqs3gokxFy0UgKdAkdQEnqQo4GRsUFNawzX7fERgicMghhxSGGuMfD4pcO+7KYBkKeLsow/fcK7fL5/i055bkuxdgcl2NpE1KbN9RlJlxtiNtUn4MT98z9HUXO0vb0o6+7WrYCYUDw4GzYw1StpNtJKnfO2ZQMuQ//OEPV4XZdlHt6tgBc+TUd9iSTDaxXc/o811yO9nJ8m1xDhjkjPAk9fvJvufpyJ45ZCihzakejsN2EbGVyoIWZBFaVXWVODyeJ9PlLne5YtfI8Ws7bhzY5eo6wZEsP+7Jtrf1GX2MITs8dobI4uXeNTaOqJ1YRrJ3W124+/0ATlmycjq1zdFlkNplsxvjx1TpD9+F9RUVc4xP7T76gSs6gpPiXXS5GpsTK3SLgJCgifWhHG8z/g877LCy9957178OgT8Y/8pnnZLUk2x+9BH+HDO8aw3hVXxL/5kXeE+jx3iMeY899qi60Y5ysmjQwsB7nBnX7U1+jwPWsIW176oKPvnebms7ST0W68fYksW+t7Uv+p2zSfaRPeaXU5MsbYuTSn4Pjf5t7WNYD902EBpWrSwZ2xV+WExgh+yEq/UpUMEZZJsoT5byuLa0o+3hlcOMh+VLrcwYjMXz9qRkfOqEI8fZdnpRQEcAt/Gtfsh+wU877UnqsWO8LZ+TT9bstddexbyWwQdd1p2dfnMg6OSkpJMkeFLbg+r1dkd5q768Df+RiclSXvCa8blOJs6uOaMv/GaCoK7fHOAIW0/WvHEKnuGpyfd35jNZJQhBXgn2katDetBt/ZlHv3PglII5tm6SMU+SFU7atWPsw/fX2j1afc1RAMnpAzqm0WicdDXfABZkXSsbXs0h+4Od4as5ylwbr7pK2mYDKl/d1FvrCKw/BHbbHpLbAqJwGM4i+AwTi2rYDmHt2JYj0Unqj4BQVJwuu2oEMEPOO9qU3PfUEdhWBChJxjJjVGKs+UEsjrM2fI0DX1EovqfHkaUkRHx///vf17/YYOcRHzOElDm6xUnkaCRjRaqtHU0UGyOTkccp0g6aJAaJcnmSPNdhkqdOMj5iy1lhkE2ut+E7w/skhWMzxAkefpxLpF/7DSf3+tI2AwMOdoi0J49h6fgnIx3Gvu+rbEeT/sgDdHBsWzvmwW6L8pbnOCLHg1OUpHDUOAptXIxZzrxdKkHD9t5qXDmWdlftcKEJXk5btJMhaEWzvtoVVgxiOxGSe4Yz/lLHLiGeGBps3t/ehJ7Jd+Q5Zs8ZtuuepAZl1NO3OVTHveRemXxGfrLI9+S3uRGIShbz1d+RlKQY9x577LHwlxaS1EAuQ56hxzC3nu1u26Hi5NAn6PQ1D1fOLl5NUn9f4eCDDy5HH310HWeSuhNundvtEuRjWCYrp7+NGQ3tvl1hKXlWzmi360rP4VPJSRtfZ/GbBeRXkvrjcu0970rq+ioR3vFMtjllQYZ5FlDzlZNJx03ZtiT960OCtRM8DG1fX0E7elyTFLJyawE3fXqHTPOee1dygyxBJ/4nT/Rt3Zs/8+k4v/lRVzs7kvTnRAzM9NHa0Ac6PBuHIC75py9rVLmv+VmXLXChLXW9Q9543waFZ4EkfEomCDxZH9aNdwQFzK2vu6i7vSkZ862AA/vIGnGCAK3a9xUIbTq1kYzXdJLq1BsLPeOkAaeRXCmjT6ONzuAgkqOj7Bok0ibn3xjxUtOBxkhX6T9ZvTWj32HSN0cMTTAmEwUd5KlnDtCozDwlqWOllwRTjNnXWHyVBkYCSPQ/+ssa+UzSvs8++5RmWyhzUsk1ST2ObhycXKfkyDTzVjZ9BAc94/FkdvOyqbsdvpgr68I46Wnja0lZMuZzJ2mMJxnzcsNCXTqVrMSH6jRi4AcH8k8eecgWGa55+Tsl9U47AmsAgd22hQbGiWP0IqOEvx+DERlmcFm4FiqFRphabPIZBwcccED91XDGix+uovAluyoilhSlXSwGMuFNseqLcnFdyY/+bMu4ep31i4BdEoZmSwQ/vmOwEfq+U+tYaZJip8PRXvzlZAljzPuMM84aA4qT4Hu5eJViXSky+NlpAT9CxBgTXbd7wBGltOyIOiqsH8+UGBoYMnhfHnp9B837juDZWRPBZ/h4b2spGTu/DSOGO4PTD7zBywkbDod+GBIMUo6Rte5UzX777VeNP/Q4em2nnyHl9zEYUFvrf0vlxscI5YwP8YYZOhi27X07SY6iJqn0iNRT7m1cnB27vIzTldClT7xj14DjjkbjFcSwm2dHyBFCO1z+4gdj0s6eo64cSAaI+dWOH2oy9wIRaHJs0JzD94CRXPS8rfPYcBhe0eboNEPY/OE3eWSwthk7+EtAx9F0ZXaAnK7CS3ZM8T56BCs4A04XDOeCw8fRGeYNadiRe20Zv0AwOe/YpYCHhC/bnJpfToVgHMcW/nSKAJy1S884YmsO/OCcdYIevIqv6Rvr23Fkc5hE8YoTnGGOP2DnWaOCSfgWXX5B3byTRXZ5rTvjchXA+n/27gK8khvZArBOHuVxHu+DZWZmyjIzc5bxW2ZmhiwzM2eZmZmZmZn5+ddd2e0be8ZjnqTuN5ruVkvq0lFVqaqkbuurQIl6dt/gE+Pj2lFgYwRj5HGKlbMryVjTAVbq8Hyy7/3iTKFnJM621VuBAyvDsKSLzMu+No0W44YWsoEGOON59Er6gEZ4kBcra7AQWOIAk9EkTZDF1njOmN0fxoie0fZ6k+dryzcHBp3yBN3YGuTErhk7nAT80Mi2QCO+J7PoUNeH9OCi/+i200I5Y+1oRZ8840XOJ/vFtyf0CQ9oYz39YENpx0o0W0rQlW2lLQ6esZdvHiHT5hL90Dcr176B4fVH8o0Guso5mU/S7MgQvIA7XU9P0P2CHF5xdF+frZx6x1kbnr1VCU/T6XiZzqUP/JUZAT88SO5tMWcjotPrG+ROHzi7xlGgiBzKo3PN93TYVtG8Wrt4jV6Cn/EwlvJgTU7JEZkxdmSEPjLWFhR8w8Q4+haV1yD0zXxifpmOAR2N5+Ql+y7zq9G+mfn6LADLtjdn6y9e9fFNY2y+wcN4D6/6eChZ0jeBGh+ahR05Ik/0uDYEqcxZysAF75vf6CZ4wXMz+1FtFQL7KwJrcugJmqgbZ4CRSKnc9KY3bRQyZWRSY8z6AA6DnJFFOTH8CZuoPCOCAiOgjAGTCEeKMSFKa4WAQnBO2WmfwS+AsL+CW3RvHQJJFqPa+JHTwmhsCz9GAefJtXsMNIbKM57xjGZS4bgzKCRbYBkMHAbnAgHqLDSzoX+MWRM6vuesm/DJBUOFzNipwsD3EHwvWMZwZqSTNXlWRpWzisZpIU+i3mRKvbUkfZkmDhqHOEn/GjoDkuNksrQDwORrgvV1aAZrksaxI4smWpO1FZJk40YFJ8KKw7Q/jHBOsrHRPzgwOtHmWkqybOwFGBmv+tnW+fMc71t7lo+ywVueNuXZjvyUpzylwZ8hgWbGCCcCbTBleMBOOWPJqdQPbQiA0mkMHkEMuMtfD7nosgpvrOjWD3/4w40RLJ+jIuCA16yAShwm9+DkuVY0OJWMTcYjAwtvMZIHPXS0lVPO88jbjKM+k01BNjhy1smd4IZ7I8HX6jqakjTOPofZNUcLTzL+GHfmHrvGkjQybgy0zQkyZyUb51V9hyHHzuqRPthFwMmQzxmhbwQo9IXcGvski7yqT1ZYGaX6qZ4gmTznbeFn3PSTHli49K/Xx0scZf0TsOFcaq8X2Mf/kvQ20SCh1dycpNkNgf/xKQcF33sloy380MjJEgykbxnc8iR90JeFYo3jwRnlZNN75naYuHfggQc2DijeNTa25pIj99ab7AbEyxw8/dEOmqzYcgQ5sPjNvOA+JxHfC1ywXaxoy1ePTuJ0sUvkCfDiLeUFBMi1cZXMGewTwU+7FeWpo519SWj1bjw9j68EA9FqfK2yk216xzxCniXzGBn1XGU57uR+YEnGyTqZR5N5jYzjHzwLfzoLzfQWe0x/9JEuTTZHZlbDQd/oJYEEMsO5MzehVRCMgy/IIigGf/0TnFHeXKW+cYOZ+ZQeMHYCLsnW0j7fJ+NAH5Ejc6OxNKbmTzvZjKf5k3Mr6KyP+qXP9DA9JjgpoCZ443WkMY6epS06z/i63q1JgI+jTQ4t3JF9PCs4S5+fvHx6AAAQAElEQVQJjpF3W+m9hmTXCCz0zUexjTf9Skck6X/dQxuCoINXBQLIgnYE1+lcbexWTIquQmA7EViTQ2+ytrLpC8QmHMrUhEcZUTy2FpoUGBwmQJMJoWSYqzcMGJM6Y0VUlvAygjhTJhNta4MBSWk7Z7hofzsBqWftnwjgSxNhkmZSZRyYUPWG0cI5Ec01qTBQk/TVXucMUAaybWDKqrPRxChhUOLjkVybtMmPLeLo9RwTknfWRznGlzzl9IsMcdw4+ElUWVfSJkPJ5JjMvofBeGWgk2eyy9kkl6OMB8EMPvQAmpL106A9KUk7+OCD+5Zp1yORf4bRGIckzbgcdNBBfbxGuemRkWTXRbJ+upL0v/k99JA+w8tz9FkgxvjhFfwln26i+6y2JmnOjRVMOZmjfpK+rZxxZ8XYdwjowmR99CZpxkuAAL3SMGxsmx985Oie56IF7zF4OVKcALyAHgY8xzpZogf+6umjvm5WSmZYcEjoeWNtvkiWnu1Z8MHz5hHX5gvzifwk/W+0o18bZEk5fRQE4EAyfvVB3c1KSfr7ycYYrmSCA5ykv8Ijz+omAxad889N0r/GL8CYpDvVaB9OV1v4GQc7GOZp1565knxyKpVbKL7Cv33PMgacpCR9S7DVXs8RoPecZDY2yUxm9VMiCzCX9EFfnDPU3TfPG2f8liy1Qe/RxcaXXKuz71Qv1aDDbU9PZs9wR5v0GP5wb4yTe+YFYygIQM8pK1/ieHC0BCSSNG1zPMmJOcQ4KCeRIfrZt1zorWk77q81JWlDvwjceGYy6wvZ0P6QZUe0241GNuHI4WWLTZ9v3Mg6mUcHfsJ38GBXcYaVT2Z9hBV+Vka7yez56m5V8m0PQRW85jj6PfrM6UWjwIQ+k23BVXlocjReQw/Q2aMN97crwZZda2wk8o828wY7BO0Cv2yCZIarHTy+b2Mc1DeObAD9S2ZlBv1JmqCxssnye6PMbjjqE/4i+3CQ9N2iBizMi67xKyc+mfWFHNEV8BEM0Ia6I+FjOkQfzb2whB2dBTv5lQqBQqC1A9YCQpL+/hLhoaiSdON6nDsS2Pn78iT3kzQ/15K8cXSu7rh2dC0/mdVTt1IhsBoCeEVyP0k3luev8ZW8ZImnknTeXule28AvSW8XH2t7pCSLsoOW9uefc2WUT9Jzk/Q25LufzPLbBn7aSmbtJOk4Jek0uSfNP8v1SvltA78ki89uk59nSUkWc5P0sm2VX5KOU9vgz3P1U3I+mkvSnz/ykxltySx/lHVfci0ls3Jt4ZdkxTbaOn9Jep/xi2cms2d57siTL8lrCz9HKckex3uhaP+XzMr1i038L8lesUhmZZI0P3RLydK1vkkjP8le220b/CVZFXe0SIOeNvdL0ulL0vFP0ttK0qa/JP3+fJ5299T+tPyazxcKaldaOO3P9QxJXhLZi0mee3jM+biRZLEv8pWRnCdLbSTpGLgnJUv32jp/SXqbbe6nfWklGuRLyfLnKysls/wkvW1lp/lt4edaGvcWstb9L0l/jvaS2bPbwi9Jz4e35FlSkj5Wyrt2TNLGL0mvJ78t/JL06z2VXele28JfkhVpSmb5aE/S+Wo12pI932/b8Euy2A9jlMzGIcmqtCfpdZLscRzbn39Jevm2y3/GCQaOI+1tHJP0viWzo3rTNkb9tvBL0ssqM81v9SsECoG1OfSFUyFQCBQChUAhUAgcuRGo3hcChUAhUAgUAoXA7kNgTSv0u4/soqgQKAQKgUKgECgEdjECRVohUAgUAoVAIVAIbAMC5dBvA8j1iEKgECgECoFCoBDYEwJ1rxAoBAqBQqAQKATWg0A59OtBreoUAoVAIVAIFAKFwM4hUE8uBAqBQqAQKAQKgY5AOfQdhvqvECgECoFCoBAoBI6oCFS/CoFCoBAoBAqBIyoC5dAfUUe2+lUIFAKFQCFQCBQC60Gg6hQChUAhUAgUAvsNAuXQ7zdDVYQWAoVAIVAIFAKFwO5DoCgqBAqBQqAQKAR2DoFy6HcO+3pyIVAIFAKFQCFQCBzZEKj+FgKFQCFQCBQCm4hAOfSbCGY1VQgUAoVAIVAIFAKFwGYiUG0VAoVAIVAIFAJ7QqAc+j2hU/cKgUKgECgECoFCoBDYfxAoSguBQqAQKASOZAiUQ38kG/DqbiFQCBQChUAhUAgUAjME6v9CoBAoBAqB/R2Bcuj39xEs+guBQqAQKAQKgUKgENgOBOoZhUAhUAgUArsOgXLod92QFEGFQCFQCBQChUAhUAjs/whUDwqBQqAQKAS2HoFy6Lce43pCIVAIFAKFQCFQCBQChcCeEai7hUAhUAgUAutAoBz6dYBWVQqBQqAQKAQKgUKgECgEdhKBenYhUAgUAoUABMqhh0KlQqAQKAQKgUKgECgECoEjLgLVs0KgECgEjqAIlEN/BB3Y6lYhUAgUAoVAIVAIFAKFwPoQqFqFQCFQCOwvCJRDv7+MVNFZCBQChUAhUAgUAoVAIbAbESiaCoFCoBDYMQTKod8x6OvBhUAhUAgUAoVAIVAIFAJHPgSqx4VAIVAIbB4Ca3bof//737ePfvSj7dnPfnZ77Wtf27797W/39Kc//WkZNW984xvbs571rPbMZz6zl1X+5S9/eXvf+97Xfv7zn7f58ssq10UhsA8I4MlPfvKT7fnPf357xzve0X7zm9+sWPtXv/pVw5fPe97z2oc//OFFHsSL3//+99thhx3WXvziF7evfOUrK9Zfb6b2v/rVr7YXvvCFXWbQsVpbyv7xj39sH/vYx9qLXvSi9oEPfKAX1cePf/zjDe3vfOc7229/+9uevy//weVd73pXe85zntM+8YlPtD/84Q8rVkeDZ5FfyfPkSaMfz33uc9unPvWphtYVG1lDpvZ+/etftze96U1dR3zpS19aHJOVqk/L64sy8tABF/h++ctf3mMb6uxLgvN73/vepr8f+chHmnGYrw/Ht7/97V3XwWvoPPnog9kLXvCC9rKXvaz94Ac/2FT6PGPwPhrQO0+fa3i5P/TwD3/4Q9k9ufee97yn9xHfrdTHXnAL/vvpT3/a3va2t60qs/CDO0yn2P7kJz/pOJp/yInxN/bw2AIy190kOo278f/c5z63R3lB/+ijufV3v/tdfy4M3v3udy/y14c+9KGev53/4Qk6E/+8/vWvb+QWXfM0wB8vKUfXTPXDL3/5y0VZJ1Or8ep8m+u5Rtt3v/vd9opXvKLzyWhD/mc+85muR1/3ute1n/3sZ+PWsiO6v/CFL/RyL3nJS5q21FXIPWNlTLWxGhbKbkZCIyzJymgPLT/+8Y/bq171qq47P/3pT6/KW+Rb/Xm9r43PfvazvY/4TfvyxjO264jP6R0yjM7V+AJv7U3XGQtzPF7bLvpXew4a0EIW8Mtq2Mo3xw4dR99pE5+xtY3bm9/85iUd6eZ+lr7+9a838sJGc67Pe+oCG+ktb3nLop3zox/9qPM5/SjByryxpzbqXiFwZEVgTQ49ISRk973vfduxjnWs9o//+I/tzne+c3va0562bNIE4jGOcYw+md7kJjdp//3f/91OcpKTdMf/ale7WrvRjW7UJx/tKVupEFgvAnhIkOjWt751+4//+I/2yEc+sj3qUY86HD8qJ6BkYuUAXu5yl+uBKfkMmcc97nHdSDX5XuMa1+iO13ppmtbTvsnplre8ZTvooIMaY/da17rW4egbdZS9xS1u0W5+85s35//7v//by5q8bnvb27b//M//bA95yEPaE5/4xC5Do97ejug49NBD21Of+tT2f//3f+1Wt7pVYxzJn68r7za3uU1/xpOe9KT2ta99rdPwjW98o8GN3B/72Mdut7vd7drnP//5+eprvmaw6Ctj5ehHP3q76U1v2n7xi1+sWh9dD3zgA9td73rXXs71F7/4xd4X+uaf//mf25WudKX2zW9+c9U29uUG+p785Ce3hz70oe1//ud/GvwFjDx32o4AJVwZX4wxQRhGBwP0ywsBhgc/+MF9LOnNe9/73h3Laf31nqMD76ML7z/mMY9pD3/4ww/HF8oJVAlYnexkJ+vOyXWuc51FDB/72Mc2dfEaOUK/Ouula631BBUESg455JDG+F2pHjrw+gc/+MEGW07l05/+9EZmOVlkiTH8oAc9qF32spdtjMWV2tmJPOPP8ORkcIIveMELrhos1M8hc3iOwysP3dq5293u1siie/TCuOf+VifPwvdPecpT2olPfOL2yle+st3sZjfr+nL6bOXe+ta3NuPB2bze9a7XgzXKkCW8KRhxzGMes9sNz3jGMw7Hq8puRqKzyC3eQpc2HQUq8Q89c4c73KHBU77708RBvuY1r9kXIIyLc31QBt+Sk3/5l39pb37zm9uNb3zjLeuHgJCA1VWvetVuPw1a5eN9js5RjnKUZn6hf8Z9dEqu4Y53ht7nPMun/40p2bvTne7UHv/4x2+abvLstSR0wBDG//Vf/9Xud7/7rWhPKmfuVI6ue/SjH93n+jEmnqWMfPOSMXItfyeSZ5MRcmNuwyMCF/Ln6SHfd7/73Rfle5R7//vf39gseNXc+NKXvnRd4zP/vO281l8B7Utf+tJNUFI/r3zlK/f5cDU61Ln//e/flNV35cyvr3nNa/ocYB4wv8LWvUqFQCGwHIE1OfQUD2fp4he/eDvNaU7TTn/603eh47Avb641k/YZz3jGdsABB7TjHve43RA45JBD+ioqwb7uda+7X0cc5/tb1zuDgAmdE3/961+/nfWsZ20PeMAD+s4Qhr2JYUoVPmQYcZYZD6LnykiMo8tc5jLdebMyYxKSP62/nnNtmJzIw9nOdrZ2gxvcoDFgXv3qVx9uctaXuy44qxxnjsDlL3/5hk75D3vYwxoj8sxnPnN32jg53/ve99ZEEho43gxohh+5ZKDe6173OpwhSsZNlqc61al6YMQKkMk4Sd/9wJg65znP2dw/wQlO0PPWRMQKhRj/VmVgctrTnrbrE0bQCkV7lgn8eMc7Xtcb+iRxLtBxilOcosGXkc1oh1mvtIH/rP4+4QlPaJypM5zhDN0J4ZTPt82hVwaekoDlqU996q774MnZvMIVrtDgr8/yNkDWYlV0HHrooQ3v4wvP4azg3cVCCyfKWZ2/2MUu1k54whO2K17xio1DYLeAsowlRjC+YDji182iceHxq/4zVoy7f/qnf1p1t4idM4LCDH3YMugFVwTHrLTqvyAJeTLXWOHDF6s+dBtvwJ0Tf4lLXKI7Kt/61re6QTpPAnrxBcfMGFpVNh5/9Vd/1Rj3HNNznetc3eDH7+bdJPPNbNm1gITAG/3IoXeODlhPH6ofaOa80C/0hNVFZTieHH28in48xpnUtvubnY561KO2C1/4wi3JMj2Lr8nqVa5ylXaXu9ylr3Abp+nzXeubIBjesvOH/uRI6CMdcMpTnrLrG4FRvGeX0bSNzTonG4Ko//qv/7pMRt7whje0f/iHf+gBVvPeRS960XaPe9yjFbmxTAAAEABJREFUoW8827mAJ51Absg3u+s+97lP32kEC3XI4D3vec/GYVJn1N+OI6wFE29/+9v3+VvwAV/gl+nzlSMHdCtdJ0hqIck8rxy6Bf3MT1b4XcvfieTZ5nj8Qw7MbQKp5EY/pjSRb0Hq85///E1wiVzhrSR9vM35bJarX/3qfYeXMZvW34LzTW0SFoJ4dBpZIifmHcEK9+YfJs9cdfzjH7/rPtd0xFnOcpYecDIHkN+/+Iu/aDCbr1/XhUAh0NqaHPokjeFMsZooCNu///u/N4ZikmU4Joe/JoScKsrJ9hsG2bJKdVEI7CMCJn4ripw6Bv2//du/NXxmFX7aVJJmUlXGhM/wvNSlLtUNPiu7+DhJ057dJ8c5znGm1dd9ztmzAjqebXXbOQN+fnJnGMonX2gaD+V8WX3hzP7lX/5l00d9YGSSwVFutaMy6h900EGNoZukHe1oR2tWATmt03roZYwIIFzgAhfok6jttkl6UM5EbNscnNBP9qf113qOJn096UlP2ndW6NcxF1buGM9W9+bbseLCyOYgTe+dYcHRtnLhnkCMfjH4kuX6Z1pnLefo+/LC6jqDywoL+gQu8dU8ZhxM9/CdBD9GHF6zk8ExSVOPk5NsjLZBv1VqwdEpXyRp9Cr6R7kkTRnBIg68LeAHH3xwDxZZifybv/mbzg/otIqHVzifo/5WHZP0oEeyOh4MdPIIVwnPwPbv//7vm6DJMY5xjGZsyNV5z3ve3l7bJT904R24GisBDPw6T56xsgOHg8Ix41wxYpX7zne+0zhv8s5znvP0V4KUd287kmfZ8SLhE30ReNAvgTP3Bx1JGtlTRh7ngwPm3Cs+tn67l6QH+WFil4X7m52SdN0+bTdJO/nJT77II/TMmAPmy3GiOdPGkM4kP0n6ThIOssCYe8qQcbp0isW0vY2cJ4fvh+fYKn/ggQf2PpILDhAeGiua45nGiGyQ6yRd/9Ph+IruNR7K0ucCT0lcblvi3NFX6E/S5wK8Pz+34RUYGwe4mwMRCQd4eC2BA32+851vcXzd34lkXvQqhkUvdgWM2b2CW3huShM9S745qec+97n7ivy4T1eom6TvprK71fW4vzuOe6YiSROMpPuMG7tGv/DsfE3jyNYRuDeOyYwX6R26Xh39N4/SP2y++TbquhAoBNraHXoRdtvnL37xi/cIt21bf/u3f7smDJN040uUn5Pgndk1VaxChcAqCHgvleFI2StC4UtWuV1Pk3xOs4ASA8IE436SbhhZ6bdtV0ri1oaTyYeBIoCQpD/nr//6r5uVRxPY9AEi2AwA2yOtils5sQLBaNHHZFY/ma06MbKn9fd0LgCnv8msDXiRQfRN6zH+7MJhUFldOPTQQ5uoOlph9ohHPKLZqmrVwIodg3Zaf63n2mPMmKyNS5JuiAlUMC7db3/+meQFGA455JCm/J+zO5ZWM2zttdXeapMVs7/7u7/r90a59R5hkMzwSmZH4wD3KX3J7F6S/s6fFW87GEa/BAXQZkytkq2Xnmk9zxfAMIbjOe4naXB1PlKSZoeAVT7GlQCYVW88qQ28oA3lnevjfBvu7URKlrDVV7LB8EWvccbTzt3jHJ7pTGfaCTJXfGYyk1OOOvztREHvfOEkffcNnXXHO96x7zCyM8Q4CBRxVKwOc/bpCDrP+M+3sxXXSforc/QSPWC7P90l8Ger9vSZSfol/vJKh/4MeeUA02VWUbXhniNHrVfagv+SGT3TppP0V068pmI3F0dret95kr76TRZc00fKnehEJ+qyRZ+7l6TrGecw2aoxSWbPQctIdLH33vECejjodOd0TNAz9D4ZSdKD3WSF3k/S5yGr4/TTTjhIAoroHPQlaX5emXCU3KeL0T3KyZfoYs68Vf4b3vCGTaAvmbXh/k4kcouuEXBJZnavgBZemtLkNSfb6snMhS50ob7L4ssLgWRlkjT62Y4XK/dkUP7+lJL0MTFu0u9+97tm3rEwON8P87zFDK88spGS2Tgm6XKmvjpeu+Lwa8d1pUKgEFiOwJpW6AkUo9C2QNtHRd059rYHL29uz1cUtKS9PZesu4XAnhHAR9K0lGtpmjfOrbxf8pKX7B+n8/0Hzta4d7rTna5vYZT/lre8ZWRv+IiWJMvakTfNMNFbTbGCa9u57XdWLmxBFPGfLz/qrpY/7o/jWsuRSZMp48EWQVuwORRoYLhqBz6MR9uCGVPjGft61Nbe6nguR8LqhCi/OpJ8dZM0Ow8EGqw+w25q1CqznuQZ+1pPHYaZHRjwm9Y/xznO0Tj08GS4TO+t99zzVqs7vZekv1phRU4wxke+ODN4f1pu2tZq+dMy23mOHsatHRhWTD07mcmUe94ztqPEKyrJLF+ZnU5oE3SyEmyrs7lS3pSuJI3MCYzjc7xsFwWHl8xxivXbO6VW6e2Qmdbf6nN0CUoIhjKkvZLDwbKjJlmOtb4JQrALOJm2tnM4ySjH0atNAqpWMOkQ/dpq+qfto09/9MPChC3oghPTMtNz5cmLfgjGuJ7e34nzJA0fCBLZSSCIaZsy3p/XO+iVVqJTPqfTzhY8KjC6EX2+0jP2locGKTk8H+2trvvq2p1lPO3mkWdukJzvVELXWp495Jss2U7u9QnyPeqb87w6YmVbQHt+B8ZanrHTZZLZ2BoTeoQuxHfJLB99+svmsojBx5CnvOSe65HYSeZY2I28OhYChcASAgcsna5+RrBM5KKgtq75oJF3fLwPJyq5es2lOwTUaoNJVdR+6U6dFQL7jgCDMJk5LGrjUYairXmu55OVFqu5jGYBqWHAJGkceu8aWr0cHw6ar7+v17YGWklk1I66tt3ZAjmuHZVh1DPeyYZ6HEArWaL4yuibo6SPVmmSpUlR/mrJ86aOLmeOgcqQWKlOkr4abjV0GEqMcDJv0mXU0wNW81eqv7e8JH3LNyxGWSsY+s4hSGb90mdGgN0AVrdt1zNu3p/j4KHHKpSt+FY1rQIywOmZ0e56jsnstQQ0jfraTNK3r4+86ZEOtJJiZ8PU2DCuDDXv3lqZsG1fv6Z113M+eN9zR318hseTGX7y3TdOMOOYWOXlnNkhhS/UUU6yCoZ2gS/XuyXBy+sFHEX0Tekiqwxehi+ent7b6XO0Mj6tstntsqexT9IdezJnS2myNIZJGtk4+9nP3ta7K2a9WCTpryvhGe9Z0z1eg1hpN4SAoFdQLnKRizSBf/21em1cOJ/ep/UKkm9zkFl6b710radeko6fnSrsFjuS6A/8Nd8eWbAKbrcN51/f6ELOCAxGebsMBJmSpfEa97bq6P35u93tbv21Kbs6vCZj7kqW00C+BYYGHfpkLIxfkv5hY0FkWHCk6NSVsBj1N/s45h+6dbSNxnnbcOA7LUc364f5QZDI3IAn2ah2s9i9sJ19GfTjEx+vHYFbNNCx5ktBl1Fuekxm8u07MMZ23GMHCFb4EC4++8om/wWe8ZztONLfxktwG0bTZ5qjBDvN88bRqzt4WrBJn2GovOCbhQ686nou1WUhUAgsIHDAQtrrP0Jn66utjUn69i2R4uEoULa2ag7ha3M/90XXfFHcJMRoUdZ7VI5zxeuyENgrAiZOzpJtWHjIdjWGL4fEtVUifOcc/zqaTEyUEuNMnnse5p5Jl1HqeqOJo+EjfAxZdDBuyYBJOkn/OJlnc+RtNTOJMWg8lyzZ5snB9SEp95TliFmJ4egnyw049eZTMgtWMOyGwcbQ9v47g1b/4eQoeYajZOsgfJPZu9kMWRiZUBnojKf5563lOkmDgS2XnuGZzmEFC9d2LSRpvlzsPXmJsy5YY4eQ/sMVXkn6X97wusR0u+ZaaFmpTJJmCyrjigGBHgYig4thBhvj4zjqM9rQwvhP0j9QZcylJF1fGjd6r23wl6R/S4FxxKFFnx0KHCRGMrqmY4rn0MHBtJIteGW1R4ABKV7rUMcY0Onb7TSiYSR04gn0jDznHC8rifhP/shDOxxGnnznO530Q0IHmo9ylKP0IJZrNArWue8c3zhKdJjdFHST+8ZWvsRJ4AhrYztTkr7t1fvXVhB9uIyORJPvWziiVXKuv3iI/pOSWf0k/S8qGF+LAdu5bRZd6JOS9OCJFVD6FZZ0G5kY5ehb8k/3ui9fn6xkD5kjY+TOR7uSKLbpyXOlacNJ+itK6BUs8h6/lc8kfTfO+GCq97j1i57WBr0v8KVfcJCSJSyMadvGH5mwODTmb/OTOZ1uR8bQsfQm3WtMyAMnTx/0W6DMjhbzg7/kIdDp1Rzf10i2ZkzQtlrC+wIKFq682gB3+lfAZci0uU0+/PVHW64tMBgf1+7JS9LodbtcBJTc25+SPphD6a6DDz64ky5vJPojSf+rBWMc7Qo0/3Ly8UIy42v5gppsvN7Qhv6ryoXAEROBA9baLROIlTBbHCXGthXNJD1azPinlG0BE81nqPiTPZStiL3Jx3v4431Cysxk6LhWGqpcITAQsNrgfU0Onj85Z/XRtk4TH4OZ0+hDWiZQRr9It5VmX7i37dgE6yNmJmCTh/fZRMIZzcnGjQGTOwNQEMxqMuOD486hStL/5JHVbv3xBXor575gb9WB868vnDAyY2VLWVtvXTOU1dtbStL/6oSVY18HhhXZtN0Uffqvv4xsDh2cYAEnBqAJNEmDEeNQHzjWZJw87+35q933cTP981oBmhjH9EKSRrdc+9rX7l+0N5YMv5E4/PKsfCvjOx5eUfChTYY2w3a1Z+5LPiPS2FlZh4dnoA9m/oQSA5OTOdo0XmhM0p0fBouVL1tj9YexqQ6jOcmotu4jOtCDJyQfTkMvgxjvW5HH+x5gV4r3Ezlj3vHHU1ZLrOAZA19a1kcYkif31dvKRCbRw2hHP/w8j/FnlcbrCzCUZ2WGXHKokvRgiY+AWdGxcuxVBlhIo456O5k4eoInnAs7N3zlHb8m6X8y0sovox+9VknJN71kDIyJMaCPyKOPReon3t8JR4W8061eG6BDBK3wnyAhfcbQNj7mcn8CzYe+6A994XiZ3+lngXw6BR7DUN+KMRLU8wz0kTuLDnQX+aD3fHVb8tE+usQY0EM+HEkH079WfQUulMFXaE/S/1IJudcfNo2xGoGxze4LTNFv5xEdYh7xDPLNDhMUIcfoGLJhVwEdaKFE8JDed5986zP55izqF37EY5J8uiPZuG5C41qS+RsNsKcDzG3wFGiGMX1J1+I1Y2CeUG6q6+hpQRm6VzDenK4f2xksmvY1SbNTwHdm2Mdwp+vwnn6QZVjjM/pvKt+cdnIhOGyXi1fIyBFeNoYWIabP2u3n5ApvsR30G8+xXYwlHsTT+NNui+k4GssxjnhEP8kvPSPgAUd525rqYYXAfoLAmhz6JM2kTiBt6xQJpZiGorKa6M9QMRKt4HnHliNvazBFayuhidIqHGU7hJKC3k9wKjJ3GQJ4iGHMUbcq7/1uDhRj2KTOeWFsmShts7eVC3/iW3ypPseSIWflFw/jbxNnsv6fMqwAAAc0SURBVHHDRvui6xwm9HkPjtGCPlCiV9DBOZnx57msQlq18KEfxqY2BMq0gWZbLa2OjzbU3VtSliHrvXjbGRkH6NG2VRxOhz5zFmAJC4mxbmJN0r+QDE+0wND72LYT7+3Zq92nA3yMyXj5UCbHmSGnPCOHruG0o3Ek/YAL49W5PviYoTFGr35ZtVFeOxtJ2vd6AUPeaoEAkECMttFL1zG+GC2S8bv85S/fnfnxXE4Bo4xhjc/cV3/c38hRO8YOX+i7d5QZkejGNwIQZMO1Dy75M13osOKIB8mEe3iSrtZHbQ1nbSO07a0uvIy/eYShB1djLd+8wtDDp6MdZeHoOPKUI9Mw1gfvn1sF08Yos5NHgRsBHbzC6YKxPDS5ZujqP3r1Aw8bH8EJTnCSJpiG78ilVXu7auCkje1K6EO31x3M35x2RnaSvspNTsmrnSt4Dq8xzsk1/ktmARg8aqwEltzXxlb1QeBDMMXW/qEP8I5gA53GARREUSaZ6XlBL45GkkZWvaaiLL7CX5yRJP1L7MbV2Lmvza3oC9zJJ/o5fug19vL1j+71cT9zl+BuMusH+eZIDvnmMHvPfsi3OUQ79AXn2dgaP+OWzNrYqnGZb5cOM58IEsNTwAifyadb6Vjy45qOoJ/QTyfTzfBJ0ncrKGMcBGHov2R7+9L+/EvSd2MJOpAB9JNhmKORHUz/Ojf346Uh38YAn1qBthvWfMGO4cQOuWv70Q+v4jt6geyTI/LEdnAPT/t2AGySLI6jcSV/7IFkNo7wwh98iWSW13bxr0grBHYKgQPW8mBCJnJmmxrjgoKlhIfBT/g4I64ZY955Fak0wUjDYDEZJTOBpIA5L45roaHKFALzCJgAGff4kaGMv5RxZPQwdkwGeBYfmmAZO/KS9K+wcowYcVN+1sZmJM8xCaHP5EY+tCsfvYyPcc3QVY5McFqVSWZfyTXpo9GWan1OZjKk7loSPBhD+sqgJXPJ7D1KOKFLYoR7juepM9om/+hT332GoLxxf1+PSfp7+sbFn6XRtv5qR3DBWMy37z5aGQDKuRZcQI82YCnPvY2mJN1h4Yhon4EJM+3SdfQZvJJ0J954GefxfEfGGJ5DGzzRnUQTm5LQM3if4T/aRxceQmeSjrOxR8s0HxHq6KNxnfbRva1KSfqXxPG61Xh0wS9J314KLw5iMsNKUEw/YYqmJI3zq655xlGC8TzPKL8TiYziVX0j9/qA/mT2viy89RG9ZEA5ASrG/KAXJjCCBz7X5ri3Xcdk5uCicSqjno//zPX0qXN8ZDzwmLL6NsrpLx7UJzjI36pED8CT/YEW8uCZMMQndJxzeCbpjgTZxT/yBHb1Q9mR6My28NOOssbFuNKRyYxPF25v2r8kfW4y9oMGtlcye91G/8wf8883FujXD8S4D3f409nGSR/IunbnsVBnOxM64U7HOtJHSZoxo2PpMPSgmw5QTr9HOfdGUsb8ru7I26kjORYcNX5kAebJ7COu+AatbBPjOB2DQa8+Gh8Y4D3lx7395ajPdBpZkvRHInv6g1fpD+fTPuEJ+cZ45DuHW7L5sjaesYPHenQhsGkIHLDWlpJ04zVZflQ/meVNzwl0MstPZkf3p0mZ6XWdFwL7ikAy460ky6om6fwqM5mdJ7OjPCmZXSdLR/mbmZKltpMsNp1kkT6Zyew6mR3ljZTM8pKMrH06JunPSmbHaeUk/TLJqmUUSPZ8X5l9ScnK7SWz/JXaSrIsO8keaV5WeB0XyVL7o3oyyxvX45hknPZjki2lzUOSpWe4HinJOO3HJCvSkqyc3ytt8X9JujOVpI1fkk7nuB7HJOO0H5P0cuaPkZL0e7vhvySdvmTpOKUrmeXLS2bnSVwupiTL2li8sc0nyRId849Olu4ly8+nZZOle9P8rThPZs/CF0kWH5FkVTyT2T2Fk3S+VF9Klu61hV8yu06ycLW1/5J0WpKlZyVZUz/awi9ZuWyycv5ClW3/lyzRMn14MssfecnsOsnIWnZM0nFZlrlDF8mMlmR2HGQkS9fJ7DyZHUcZx2SWl8yO8vbHlMzoJ0cjJeldSbLieCWr5/eKR/r/CoBCYHUE1uzQr95E3SkECoFCoBAoBAqBQqAQKAQKgUKgENgVCBQRRyoEyqE/Ug13dbYQKAQKgUKgECgECoFCoBAoBAqBJQTqbP9GoBz6/Xv8ivpCoBAoBAqBQqAQKAQKgUKgECgEtguBes4uQ+AAfz7Hn67yp44qnb8VBoVB8UDxQPFA8UDxQPFA8UDxQPFA8UDxwGbwwO5ugx/82te+tvkrDLvMT18zOQf4Muhhhx3WDqtUGBQPFA8UDxQPFA8UDxQPFA8UDxQPFA8UD+wUD2zzc1/84he3c57znGt2nndjwQP82Qh/FsKf+6h0YP+TKYVD4VA8UDxQPFA8UDxQPFA8UDxQPFA8UDywu3lgo+Pjz3zyh5PsRl99TTT9PwAAAP//O7IiyAAAAAZJREFUAwDNJWDnV1DFwgAAAABJRU5ErkJggg==\" width=\"644\" height=\"535\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2b: Effect of Mulch Treatment and Application Rate on Sorghum Growth and Yield Performance\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"880\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003eMulch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eRate (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWk. to Fruit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eWk. to Harvest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003eNo of Tiller/plant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNo of Panicles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003ePanicle weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003eNo of grains (unit)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eseed weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cem\u003eA. altilis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.67\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e99.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1705.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e61.50\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.67\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e115.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1987.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e66.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.67\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e143.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1830.50\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e67.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e18.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e83.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1423.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e47.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e18.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e4.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e129.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1322.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e44.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.67\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.67\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e3.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e159.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1185.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e37.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cem\u003eM. oleifera\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e16.33\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.50\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e118.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1920.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e70.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.50\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e2.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e169.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1609.50\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e52.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e196.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1537.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e50.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. grandiflora\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.67\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e2.67\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.33\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e92.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1367.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e46.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.33\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e2.33\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.67\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e59.33\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1765.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e58.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.00\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.33\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e159.67\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1589.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e52.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.67\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e2.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e142.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1804.00\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e68.50\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e17.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e128.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1618.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e55.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003e38.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 119px;\"\u003e\n \u003cp\u003e244.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 92px;\"\u003e\n \u003cp\u003e10.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05\u003c/p\u003e\n\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eEffect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that mulch type significantly influenced key agronomic traits including days to 50% flowering and harvest, panicle weight, and number of grains, while mulch application rate had a significant effect only on number of panicles (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The interaction between mulch and application rate however, did not significantly affect any of the observed measured parameters (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that the effect of mulch was mostly independent of application rate.\u003c/p\u003e\u003cp\u003eAmong growth parameter traits, leaf count at maturity was significantly influenced by block effects (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), likely due to environmental heterogeneity, while leaf length and stem girth were not significantly influenced by any treatment factors. Days to flowering and harvest were significantly reduced by mulch application (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that organic mulches may have enhanced soil microclimate and moisture retention, accelerating crop development as reported by Teasdale and Mohler (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and Adediran et al. (2004).\u003c/p\u003e\u003cp\u003eMulched plots generally outperformed the control plot under yield parameters, with increased panicle weight, number of grains, and seed weight. This aligns with findings by Olasantan (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and Agele et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), who opined that mulching improves soil fertility and structure, which in turn enhances nutrient availability and crop yield components.\u003c/p\u003e\u003cp\u003eIronically, while mulch type significantly influenced grain yield (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the rate of mulch application had no significant effect on seed weight or panicle weight, suggesting that mulch quality (chemical composition, decomposition rate) may play a more significant role than quantity of the mulch applied. This observation confirmed previous studies which emphasized the importance of mulch type over mere biomass quantity (Kumar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Narayanasamy, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ea: Effect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"16\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource of variation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDG\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eL. C wk2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eL. C. wk4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eL. C.wk6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eL. C. wk8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eL. C. wk12\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eL.L.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eL.L.wk4 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eL.L.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eL.L.wk8 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eL.L.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eS.G.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003eS.G.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c16\"\u003e\u003cp\u003eS.G.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.47*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.47**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36.69**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37.36**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e311.44**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e248.77**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1081.80**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1965.60**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e10056.65*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.10**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e87.15**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e601.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.08*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e17.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e61.64**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e555.42*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1285.69**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e6423.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e698.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.62*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e60.01*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e254.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e741.60*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e698.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e1.98*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e632.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch x Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e15.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e79.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e133.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e157.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.01*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e700.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eError\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e13.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e189.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e216.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e2449.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u003cp\u003e687.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by * in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by ** in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eb: Effect of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource of variation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWk to Fruit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWk to Harvest\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo of Tiller/plant\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo of Panicles\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePanicle weight (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNo of grains (unit)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eseed weight (g)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.74**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.76**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16.11**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.02**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e91437.16**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1621312.82**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2815.35**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.20**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.12**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4446.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e411571.25*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e960.20**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.22*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11057.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e44146.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e56.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch x Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1824.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e75568.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e130.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eError\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4132.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e110926.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e164.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by * in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by ** in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003eEffect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/h2\u003e\u003cp\u003eThe mean effect of mulch type on growth and yield parameters in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e4\u003c/span\u003e revealed that the use of different mulch types significantly influenced certain growth and yield parameters, even though not all differences were statistically significant. Among the mulched treatments, A. altilis, L. leucocephala, and M. oleifera showed favorable trends compared to the control.\u003c/p\u003e\u003cp\u003eAlthough days to germination did not significantly vary across treatments, mulched plots exhibited slightly earlier emergence (3.78\u0026ndash;4.11 days) compared to the control (4.33 days), the phenomenon which was explained by Teasdale and Mohler (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and Olasantan (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) that mulches may enhance soil moisture and thermal regimes favorable for germination.\u003c/p\u003e\u003cp\u003eAt maturity, leaf length was significantly lower in the control (87.53 cm), while mulched plots showed higher values of 93.83 cm in \u003cem\u003eA. altilis\u003c/em\u003e, indicating better vegetative growth under mulched conditions. M. oleifera mulched plot notably recorded the highest stem girth (4.21 cm), which may relate to its richer nutrient composition and favorable decomposition rate as clearly reported by Kumar et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), thereby enhancing structural growth.\u003c/p\u003e\u003cp\u003eConsidering the reproductive development parameters, L. leucocephala resulted in the longest time to flowering and harvest (13.06 and 18.06 days, respectively). This may reflect delayed senescence and prolonged vegetative growth; it however did not correspond to superior yield, as \u003cem\u003eL. leucocephala\u003c/em\u003e recorded the lowest seed weight (42.67 g) and number of grains (1310) when it compares with other treatments.\u003c/p\u003e\u003cp\u003eIn contrast, A. altilis and M. oleifera mulched plots consistently outperformed others in panicle weight, seed weight, and number of grains per plant, indicating their superior agronomic potential. M. oleifera in particular, produced the highest panicle weight (161.33 g) and grain counts (1688.83), while the control plot, despite having fewer tillers, recorded the highest seed weight (68.5 g) which could possibly be due to reduced intra-plant competition.\u003c/p\u003e\u003cp\u003eThe variability in yield attributes among mulch types could as reported in literature, be attributed to differences in nutrient release patterns, mulch decomposition rates, and allelopathic properties (Agele et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Narayanasamy, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The mulch treatments likely enhanced soil structure and moisture conservation, translating into improved crop performance across most metrics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ea: Effect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDG\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL. C wk2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eL. C. wk4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eL. C.wk6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eL. C. wk8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eL. C. wk12\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eL.L.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eL.L.wk4 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eL.L.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eL.L.wk8 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eL.L.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eS.G.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eS.G.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003eS.G.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. altilis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.78\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e66.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e157.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e449.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e769.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e938.33\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e22.49\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.78a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.56\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e66.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e157.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e462.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e769.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e938.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e13.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e23.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eM. oleifera\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.11a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.89a\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e63.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e152.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e448.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e750.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e932.67\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e42.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eS. grandiflora\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.11a\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e63.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e152.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e442.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e753.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e927.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e13.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e22.39\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.33a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.67\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.67\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e65.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e152.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e457.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e742.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e875.33\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e21.77\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eb: Effect of Individual Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulch\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWk to Fruit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWk to Harvest\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo of Tiller/plant\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNo of Panicles\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePanicle weight (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNo of grains (unit)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eseed weight (g)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. altilis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e119.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1841.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e65.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eL. leucocephala\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e124.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1310.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eM. oleifera\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e161.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1688.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e57.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eS. grandiflora\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e103.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1573.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e52.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e142.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1804.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e68.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the mean value of the rate of application on growth and yield performance of sorghum. Although there were no statistically significant differences in most measured parameters across mulch application rates, trends observed suggest that increasing mulch rate may offer slight agronomic advantages, especially regarding yield components. For example, plants treated with the 2.5 kg mulch application rate exhibited the highest panicle weight (160.10 g) and number of panicles (2.27), suggesting a potential positive relationship between mulch quantity and reproductive output. This aligns with findings by Agele et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), who noted that higher mulch quantities improved moisture retention and nutrient availability, particularly in tropical soils.\u003c/p\u003e\u003cp\u003eStem girth also appeared to increase with mulch rate, with the 2.5 kg rate recording a much larger value (33.87 mm) compared to 1.5 kg and 2.0 kg rates (22.53 mm and 22.72 mm, respectively). Although this was not statistically significant, it may show cumulative improvements in soil structure and nutrient availability at higher levels of mulch (Narayanasamy, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kumar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIronically, the 1.5 kg mulch application rate recorded the highest seed weight (58.60 g), slightly higher than the 2.0 kg (57.80 g) and 2.5 kg (54.90 g) treatments, which could be due to lower intra-plant competition or more efficient partitioning of assimilates under lower mulch density, a phenomenon previously observed by Adediran et al. (2004).\u003c/p\u003e\u003cp\u003eGenerally, while the effects of mulch application rate were not strongly pronounced, the 2.5kg rate generally enhanced yield traits, supporting the idea that optimized mulch quantity improves soil physical conditions and nutrient release dynamics (Olasantan, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ea: \u003cb\u003eEffect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDG\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL. C wk2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eL. C. wk4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eL.C.wk6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eL. C. wk8\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eL. C. wk12\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eL.L.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eL.L.wk4 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eL.L.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eL.L.wk8 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eL.L.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eS.G.wk2 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eS.G.wk6 (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003eS.G.wk12 (mm)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.5kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.40\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e65.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e154.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e454.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e760.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e914.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e22.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.0kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.93\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e64.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e152.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e447.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e749.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e925.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e13.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e22.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.5kg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e65.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e156.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e454.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e762.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e926.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e12.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e33.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girth\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eb: \u003cb\u003eEffect of Application Rate of Four Agroforestry Tree Species Leaf Mulch on Growth and Yield Performance of Sorghum\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWk to Fruit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWk to Harvest\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo of Tiller/plant\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo of Panicles\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePanicle weight (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo of grains (unit)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eseed weight (g)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1643.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e58.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e123.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1697.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e57.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e160.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1589.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eValues followed by different letters in the same column are significantly different from each other at p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003cp\u003eNote: DG- days to germination, L.C- leaf count, L.L- leaf length, S.G- stem girt\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe low soil fertility and shortage of water as a result of climate change is generally making food production becoming extremely difficult. The rising demand for Sorghum as a result of growing industrial need in South-West Nigeria for food, breweries and beverage has grown significantly in the recent years. There is therefore the need to look into repairing the damaged soil structure and depleted soil nutrient by the adoption of organic mulch and use of beneficial crops that are tolerant to low soil nutrient until full restoration.\u003c/p\u003e\u003cp\u003eThis research addressed part of these challenges through soil management (mulching), by determining the effects of leaf mulch from selected agroforestry species on sorghum yield. This study evaluated the effects of different mulch types and application rates on growth and yield performance of sorghum.\u003c/p\u003e\u003cp\u003eThe results from this study on the growth and yield performance of sorghum showed that the mulch type significantly influenced key agronomic traits including days to 50% flowering and harvest, panicle weight, and number of grains, while mulch application rate had a significant effect only on number of panicles (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The interaction between mulch and rate of application, however, did not significantly affect any of the observed measured parameters (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that the effect of mulch was mostly independent of application rate. Mulched plots generally outperformed the control plot under yield parameters, with increased panicle weight, number of grains, and seed weight. Also, although mulch type significantly influenced grain yield (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), the rate of mulch application had no significant effect on seed weight or panicle weight. The mean effect of mulch type on growth and yield parameters revealed that the use of different mulch types significantly influenced certain growth and yield parameters, even though not all differences were statistically significant. The 1.5 kg rate recorded the highest seed weight (58.60 g), slightly higher than the 2.00 0kg (57.80 g) and 2.50 kg (54.90 g) treatments. M. oleifera at 2.50 kg mulch rate was conspicuous, recording the highest stem girth (81.13 mm) and the highest panicle weight (196.00 g). \u003cem\u003eA. altilis\u003c/em\u003e at 2.50 kg application rate also produced high seed weight (67.00 g) and number of grains (1830.50), which in comparison, is better than the control.\u003c/p\u003e\u003cp\u003eThe findings from this study highlights the importance of mulching from agroforestry tree species leaves in planting as it was highly effective in increasing panicle weight, number of grains, seed weight and completely suppressing weed growth.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe author (ADELEYE Z. Olufemi) confirms being the sole contributor of this work and has approved it for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdeleye, O. Z., \u0026amp; Okezie, G. N. (2012). Non-timber forest products and poverty reduction policy framework in Ikenne Local Government area, Ogun state, Nigeria. \u003cem\u003eInternational Journal of Asian Social Science \u003c/em\u003e2(9),1401-1420\u003c/li\u003e\n\u003cli\u003eAgele, S. O., Iremiren, G. O., \u0026amp; Ojeniyi, S. O. (2011). Effects of tillage and mulch on the growth, development and yield of late-season tomato\u003cem\u003e (Lycopersicon esculentum Mill.) \u003c/em\u003ein the humid south of Nigeria. \u003cem\u003eJournal of Agricultural Biotechnology and Sustainable Development, \u003c/em\u003e3(7), 112\u0026ndash;116\u003cem\u003e.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eAmelework, B. A., Shimelis, H. A., Laing, M. D., Ayele, D. G., Tongoona, P. \u0026amp; Mengistu, F. (2016). Sorghum production systems and constraints, and coping strategies under drought-prone agro-ecologies of Ethiopia. \u003cem\u003eSouth African Journal of Plant and Soil\u003c/em\u003e, 33(3): 207-217.\u003c/li\u003e\n\u003cli\u003eCGIAR (2023). Sorghum goes pop: success stories from a nigerian initiative. Retrieved from https://www.cgiar.org/news-events/news/sorghum-goes-pop-success-stories-from-a-nigerian-initiative/\u003c/li\u003e\n\u003cli\u003eClifford, E.D. \u0026amp; Massello, J.W. (1965). Mulching materials for nursery seedbeds. \u003cem\u003eTree Planters\u0026rsquo; Notes\u003c/em\u003e 72, 18\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eDan Diclerico. (2022). How to choose the best types of mulch to keep your garden beautiful. \u003cem\u003ehttps://www.goodhousekeeping.com/home/gardening/a20706549/how-to-mulch-your-\u003c/em\u003e\u003cem\u003e garden/\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eGarrity, D.P. (2004). Agroforestry and the achievement of the Millennium Development Goals. \u003cem\u003eAgrofor Syst\u003c/em\u003e 61(1\u0026ndash;3), 5\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eJodaugiene, D., Pupaliene, R., Urboniene, M., Pranckietis, V., and Pranckietiene, I. (2006). The impact of different types of organic mulches on weed emergence. \u003cem\u003eAgronomy Research\u003c/em\u003e, \u003cem\u003e4 (Special Issue), 197-201\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eJose, S. \u0026amp; Bardhan, S. (2012). Agroforestry for biomass production and carbon sequestration: an overview. \u003cem\u003eAgrofor Syst\u003c/em\u003e 86, 105\u0026ndash;111. \u003c/li\u003e\n\u003cli\u003eJose, S. (2009). Agroforestry for ecosystem services and environmental benefits: an overview. Agrofor Syst 76(1), 1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eKader, M.A., Singha, A., Begum, M.A., Jewel, A., Khan, F.H. \u0026amp; Khan, N.I. (2019). Mulching as water saving technique in dry land agriculture. \u003cem\u003eBulletin of the National Research Centre\u003c/em\u003e 43, 1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eKumar, V., Yadav, S. K., \u0026amp; Meena, R. K. (2019). Mulching effect on growth, yield and soil health in various cropping systems. \u003cem\u003eJournal of Pharmacognosy and Phytochemistry, 8(3), 2530\u0026ndash;2536.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eManzello, S.L., Suzuki, S., Kagiya, K., Suzuki, J. \u0026amp; Hayashi, Y. (2014). Ignition of mulch beds exposed to continuous-wind driven firebrand showers. \u003cem\u003eFire Technology\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eNalayini, P. (2007). Poly-mulching a case study to increase cotton productivity. Senior scientist. \u003cem\u003eCentral Institute for Cotton Research, Regional Station, Coimbatore\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eNarayanasamy, G. (2018). Organic farming for sustainable agriculture. \u003cem\u003eScientific Publishers\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eNgouajio, M. \u0026amp; McGiffen, M.E. (2004). Sustainable vegetable production: effects of cropping systems on weed and insect population dynamics. \u003cem\u003eActa.Hortic\u003c/em\u003e. 638, 77\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eOlasantan, F. O. (2007). Mulching for sustainable crop and soil management\u003cem\u003e.\u003c/em\u003e \u003cem\u003eJournal of Sustainable Agriculture, 30(3), 87\u0026ndash;103.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003ePetrikovszki, R., K\u0026ouml;r\u0026ouml;si, K., Nagy, P., Simon, B. \u0026amp; Zalai, M. (2016). Effect of leaf litter mulching on the pests of tomato. COLUMELLA: \u003cem\u003eJournal of Agricultural and Environmental Sciences\u003c/em\u003e, 3(2), 35-46.\u003c/li\u003e\n\u003cli\u003eRathore, A.L., Pal, A.R. \u0026amp; Sahu, K.K. (1998). Tillage and mulching effects on water use, root growth, and yield of rain-fed mustard and chickpea grown after lowland rice. \u003cem\u003eJ. Sci. Food. Agric\u003c/em\u003e. 78, 149\u0026ndash;161.\u003c/li\u003e\n\u003cli\u003eSingh, S.B., Pramod, K., Prasad, K.G. \u0026amp; Kumar, P. (1991). Response of Eucalyptus to organic manure mulch and fertilizer sources of nitrogen and phosphorus. \u003cem\u003eVan.Vig\u003c/em\u003e. 29, 200\u0026ndash;207.\u003c/li\u003e\n\u003cli\u003eSmith, J., Pearce, B. D., \u0026amp; Wolfe, M. S. (2012). A European perspective for developing modern multifunctional agroforestry systems for sustainable intensification. \u003cem\u003eRenewable Agriculture and Food Systems\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(4), 323-332\u003c/li\u003e\n\u003cli\u003eTeasdale, J. R., \u0026amp; Mohler, C. L. (2000). The quantitative relationship between weed emergence and the physical properties of mulches. \u003cem\u003eWeed Science, \u003c/em\u003e48\u003cem\u003e(3), 385\u0026ndash;392\u003c/em\u003e. https://doi.org/10.1614/0043-1745(2000)048[0385:TQRBWE]2.0.CO;2\u003c/li\u003e\n\u003cli\u003eWortmann, C. S., Mamo, M., \u0026amp; Shapiro, C. A. (2009). Nutrient management strategies for dryland sorghum production. \u003cem\u003eField Crops Research\u003c/em\u003e, 112(2-3), 109\u0026ndash;117.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Agroforestry, Mulching, Sorghum, Crop yield, Organic amendment, Sustainable agriculture, agronomic performance","lastPublishedDoi":"10.21203/rs.3.rs-7411848/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7411848/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoil nutrients are essential chemical elements that support plant growth guaranteed by agroforestry systems with the production of leaf mulch to improve soil properties. Adopting agroforestry as a sustainable soil management practice has the potential to improve soil property and structure. Existing studies in the use of specific agroforestry tree leaves as mulch for its soil fertility improvement potential in sorghum cultivation are inadequate. This study assessed the effect of leaf mulch from selected agroforestry tree species on sorghum agronomic performance.\u003c/p\u003e\u003cp\u003eThe study adopted a 3x3x4 factorial layout in a randomized complete block design. Three varieties of sorghum seeds (NGB05843, NGB05731, NGB06187) were planted on 39 raised beds (12 treatments with one control per block), evenly overlaid with fresh leaf-mulches of uniform age from four agroforestry tree (\u003cem\u003eLeucaena leucocephala, Artocarpus altilis, Sesbania grandiflora\u003c/em\u003e, and \u003cem\u003eMoringa oleifera\u003c/em\u003e) species at application rates of 1.50, 2.00 and 2.50 kilograms. Data collected were analyzed using descriptive and inferential statistics at 5% significance level.\u003c/p\u003e\u003cp\u003eFindings revealed that the control plot had the highest sorghum seed weight (68.50 g) against treatment plots (\u003cem\u003eA. altilis\u003c/em\u003e (65.00 g), \u003cem\u003eM. oleifera\u003c/em\u003e (57.30 g), \u003cem\u003eS. grandiflora\u003c/em\u003e (52.00 g), \u003cem\u003eL. leucocephala\u003c/em\u003e (42.67 g)). Sorghum variety, mulch type and application rate significantly influenced growth and yield.\u003c/p\u003e\u003cp\u003eThe study concluded that, agroforestry mulches significantly improved sorghum growth and grain yield. \u003cem\u003eA. altilis\u003c/em\u003e and \u003cem\u003eM. oleifera\u003c/em\u003e mulches were more effective in promoting sorghum development. Farmers are encouraged to adopt the use of agroforestry tree species leaf as mulch to assist in soil nutrient improvement.\u003c/p\u003e","manuscriptTitle":"Impact of Agroforestry Leaf Mulches on the Growth and Yield Performance of Sorghum in a Semi-Arid Region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 07:06:28","doi":"10.21203/rs.3.rs-7411848/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2a36ce2e-5e31-47fc-8bde-6aa103a44f45","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T11:11:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-17 07:06:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7411848","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7411848","identity":"rs-7411848","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}