Coral Restoration in Palk Bay on the Southeast Coast of India

Coral Restoration in Palk Bay on the Southeast Coast of India | 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 Coral Restoration in Palk Bay on the Southeast Coast of India Koushik Sadhukhan, T. Shanmuagaraj, Ramana Murthy M V This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3680863/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 Coral transplantation via asexual propagation of coral colonies has been used to restore the structure and function of degraded reefs in Palk Bay on the southeast coast of India. Successful restoration programs in India are rare. Therefore, this study aimed to implement a coral outplanting method at two different locations (Thonithurai and Munaikadu) in Palk Bay, India. Twenty metal frames and 800 cement slabs were used to make artificial substrates to install 800 small coral fragments, and the installation was performed in two sets to understand the variation in the growth and survivability of corals. The branching corals Acropora muricata, Acropora hyacinthus, Montipora digitata , and Pocillopora damicornis were used in this study. Eighteen months after coral transplantation, there was significant growth between the coral species ( F = 8.0981; P = 0.0012 ), whereas, the growth difference between Thonithurai and Munaikadu was not significant ( F = 0.0105; P = 0.91875 ). The average monthly growth rate of A. muricata (0.60cm/month) was the highest among all studied species, whereas A. hyacinthus, M. digitata , and P. damicornis had monthly growth rates of 0.44cm, 0.47cm, and 0.18cm, respectively. The survival rate for each species was calculated, and the survival rate for A. muricata (> 60%) and A. hyacinthus (> 50%) was the highest, whereas that for P. Damicornis was the lowest at both sites (< 35%). A large number of fish assemblages dominated by Terapon jarbua (grunter fish), Pomacentrus trilineatus (damsel fish), and Siganus javus (rabbitfish) were recorded from the sites after 9 months of transplantation. The results indicated that the coral out-planting method could be an effective tool for coral restoration in Palk Bay, and branching coral species can be considered promising contributors to artificial reef formation. Long-term restoration and multispecies out-planting can enrich the reef diversity in Palk Bay. Asexual Reproduction Local Transplantation Growth Survivability Fish abundance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Coral restoration is considered an important conservation management tool to recover a degraded or damaged reef from natural and anthropogenic disturbances and to kick start the system recovery by introducing local resistant coral species into the degraded site. Recent climate change impacts and anthropogenic stressors have drastically affected coral reef habitats and damaged reef recovery potential, which in turn has led to a decline in the ecosystem and economic services provided by coral reefs (Cheal et al. 2017 ; Hughes et al. 2017 ; Ortiz et al. 2018 ; Woodhead et al. 2019 ). Several management intervention programs have been implemented to recover degraded reef diversity and restore the structure and function of reef ecosystems. Of these programs, direct coral transplantation method is highly used in tropical countries. Reef recovery takes several years under ideal environmental conditions, and most restoration work in the recent past has been relied on the asexual propagation of coral fragments either locally or regionally (Gilmour et al. 2013 ; Hancock et al. 2021 ). Several restoration technologies based on sexual reproduction of corals were developed as well to promote recovery, genetic variety, and logistic complexity in order to achieve effective restoration programmes. (Guest et al. 2014 ; Randall et al. 2020 ). However, the lack of long-term monitoring, high-cost technology, poor site selection, and high fragment mortality have become major constraints for successful reef restoration (Edwards et al. 2015 ; van Oppen et al. 2015 ; Rinkevich 2017 ; Hancock et al. 2021 ). Therefore, a handy and cost-effective technology is emerging as a high priority for mitigating global changes in vulnerable coral reef ecosystems. In India, coral reefs are also degrading at an alarming rate due to bleaching prevalence, macroalgal proliferation to the reef areas, sedimentation, threats from invasive species and local anthropogenic pressure (Manikandan and Ravindran 2016 ; De et al. 2017 ; Krishnan et al. 2018 ). Therefore, coral restoration is necessary to expedite the natural recovery of the Indian reefs and improve the ecological integrity of the reef ecosystem. However, In India, efforts put into coral restoration programs are minimal, and successful restoration activities are few. In 2007, asexual propagation of adult coral fragments was used to launch the first coral restoration program on Lakshadweep Island ( Babu and Kumar 2016 ), and in 2014, the Zoological Survey of India began coral transplantation techniques in the Gulf of Kachchh Marine National Park to restore degraded reefs ( Yogesh et al. 2017 ). In 2018, an effort to develop artificial reef formation was initiated in Palk Bay on the southeast coast of India (Balaji et al. 2019 ). However, Yogesh et al . (2017) reported successful transplantation of Acropora corals in the Gulf of Kachchh, resulting in a survival rate greater than 55% from 2014 to 2016. Other programs failed to recover degraded reefs or promote the growth and survival of coral species. To address the growth and survival of coral species and enrichment of reef diversity by coral transplantation methods, National Centre for Coastal Research (NCCR) has implemented a coral restoration program in the Gulf of Mannar Marine National Park in 2018 (Ramesh et al. 2020a ). Palk Bay is considered an important marine fishery resource area in India, comprising various habitats such as estuaries, salt marshes, coral reefs, seagrass beds, and mangroves. It is adjacent to the Gulf of Marine Biosphere Reserve, India's first marine protected area. This important coastal habitat is enriched by a high diversity of species (344 marine fauna, 186 wetland birds, nine seagrasses, and 16 mangrove species) including many unique and threatened animals (Bhatt et al. 2012 ). Over the past few decades, reef-building corals and its associated biota severe degradation because of recurring coral bleaching events, high sedimentation rates during southwest monsoons, and increasing fishing activities (Koushik et al. 2020 2021 ). Therefore, artificial reef habitat formation is an important resource for marine biodiversity enrichment, especially for important coral species in this region though few scientist or conservationists argued that artificial reef can introduce invasive species into the reefs and also express doubt on fish stock enhancement and reduction in fish diversity near to artificial reefs (Airoldi et al. 2015 ; Froehlich and Kline 2015 ). However, to address the prevention of reef damage, and recovery of corals and their associated biodiversity, the present study was undertaken at two separate sites in Palk Bay, Munaikadu and Thonithurai, using the direct transplantation method of coral fragments, from February 2020 to August 2021. The study mainly highlighted the growth and survivability of coral species with regular monitoring of water quality parameters and sedimentation rates at two different sites and also reported significant fish assemblages during the study period. 2. Materials and Methods Palk Bay on the southeast coast of India is an important coastal habitat that is home to the largest commercial fishing population and the highest number of fish landing sites and fishing villages in the state of Tamil Nadu. The Palk Bay region is situated between latitudes 9° 55′N and 10° 45′ N and longitudes 78° 58′ E and 79° 55′E. The coastline of Palk Bay remains within the Ramnathapuram district, and the 1.2km long Pamban straits separate Palk Bay from the Gulf of Mannar (Azzez et al., 2016 ). The coastal water of Palk Bay is shallow, upto a depth of 13m, and is enriched in marine flora and fauna. Patchy coral reefs and extended seagrass meadows are the major habitats for fish, dolphins, whales, and dugongs. The bay also encompasses a brackish backwater system that supports the lush growth of mangrove forests and the abundance of diverse migratory birds. Therefore, the Palk Bay marine ecosystem requires important conservation measures to combat climate change impacts and anthropogenic pressures. Presently, the region contributes approximately 70,000 tons of fisheries production annually, which is the highest in the state of Tamil Nadu (Azzez et al., 2016 ). 2.1. Methods and Sampling A coral restoration study was conducted from February 2020 to August 2021at two different sites in Palk Bay (Munaikadu:9°17.361′N,79°07.948′E; Thonithurai: 9°17.084′N,79°10.470′E) using a rapid and conventional direct coral transplantation method (Nava and Figueroa-Camacho 2017 ; Yogesh et al. 2017; Ramesh et al. 2020a ). Two different substrates were chosen to conduct the transplantation experiment: a rocky substrate (Munaikadu) and a sandy substrate (Thonithurai). The Munaikadu area receives minimum sediment deposition in both the summer and monsoon seasons, whereas Thonithurai experiences high silt deposition during the monsoon season. Asexual propagation of coral fragments was used to grow coral on hard substrates placed at 2.5–4m depth. Monthly water quality monitoring was conducted using a Eureka Multi-Parameter Water Quality Sonde Manta + 2. Photographic evidence of the growth and survivability of coral fragments was also documented during sampling using a Nikon Underwater W300 camera. The entire experimental process was performed using the following procedures. 2.1.1. Frames and Slabs Metal frames with a length of 6ft, a width of 4ft, and a height of 0.5ft were used, on which cement slabs were fastened. Twenty frames were used at the two study sites. Square-shaped cement slabs, 20 cm 2 in area and 5 cm in height were used to maintain the coral nubbins. The weight of each slab was 5kg, and a center hole of 2cm was used to fix the coral nubbins, which were tied with a nylon cable (16"). 2.1.2. Target Species Healthy adult branching corals, Acropora muricata, Acropora hyacinthus, Montipora digitata , and Pocillopora damicornis , between 5 and 6 cm in size, were used in this study. The live coral fragments were collected from two sites, known as donor sites (Site 1: Hare Island, 9°12.679'N, 79°5.088'E; Site 2: Manoli Island, 9°13.177'N,79°7.758'E). Live coral coverage at both donor sites has been reported to be between 50–58%, with rich macro-benthic community and high density of newly recruited corals (Koushik et al. 2019 ). These places were also close to the transplanting sites, which favored convenient access for coral movement and reduced stress (Fig. 1 ). The main criteria for selecting target species were faster growth rates, ease of adaptation to environmental changes, and sufficient availability of donor locations. Previous research has also shown that branching corals in the Gulf of Mannar and Palk Bay regions are more resistant to temperature stress than non-branching corals ( Krishnan et al. 2018; Ramesh et al. 2020b ). 2.1.3. Coral transplantation A total of 10 metal frames and 400 cement slabs were deployed at each site (Munaikadu and Thonithurai) in Palk Bay at 2.5-4m depth during two separate seasons of the year in February 2020 (summer) and November 2020 (northeast monsoon). The concept of two sets of transplantation practices made for the supply of the coral fragments for the next round of coral transplantation from the grown coral fragments in restoration sites. A set of five frames and 200 slabs each were placed in Munaikadu and Thonithurai. Healthy coral nubbins ranging between 5 cm and 6 cm were cut from the adult colonies. The fragments were transferred immediately inside a large plastic tub filled with seawater and carried carefully to the restoration site. Thereafter, each coral nubbin was placed on the central hole of each cement slab and tied with a nylon cable to fix them on to the slab. 2.1.4. Data collection Sampling was undertaken once every three months. The first set of the transplantation data covered 18 months (February 2020–August 2021) and the second set 9 months (November 2020–August 2021). Growth and survival were determined periodically using length measurements and in situ observations. Coral growth was measured by fragment length at the time of deployment and every 3 months (Lirman et al. 2014 ; Suggett et al. 2018 ). Photographs were obtained during each sampling period. Water quality parameters and sedimentation rates were monitored monthly to assess their effects on coral growth. Fish assemblage data were obtained by performing random visual observations ( Hill and Wilkinson 2004 ) from November 2020 to August 2021, as the observation area is short for a transect. Photographic evidence was used to identify the fish ( Allen and Steene 2007; Nair and Kuriakose 2014 ) at each restoration site. The rate of sedimentation was calculated from the collected samples for every month, and the average weight of the sediment from each site was divided by the total surface area of the cylinder, and the sedimentation rate per day was calculated ( Yogesh et al. 2014 ). 2.2. Statistical analysis Data were analysed using MS Excel and PAST 4.0 statistical software. One-way analysis of variance (ANOVA), two-way ANOVA, and correlation and regression analyses were performed to interpret the significance of the difference in the growth rate between the two study sites and among the different species. 3. Results 3.1. Growth and Survivability A total of 800 coral fragments were used to study coral growth and survival at the Munaikadu and Thonithurai sites in Palk Bay. The initial size of the installed coral fragments ranged from 5 to 6 cm. The average sizes of A. muricata at the Munaikadu and Thonithurai sites after 18 months were 16.49 ± 1.13 cm and 17.94 ± 1.17 cm, respectively (Table 1) . Among the four coral species, A. muricata, A. hyacinthus , and M. digitate grew at a steady rate, whereas P. damicornis had the lowest growth rate at both sites (Table 1) . Two-way ANOVA results revealed that there was no significant difference in coral growth between the corals at Munaikadu and Thonithurai ( F = 0.0105 , P = 0.91875 ), whereas growth rates differed significantly based on the months ( F = 35.55404 , P = 2.22E-17 ). Results based on coral species revealed a significant difference in the monthly growth rate in Thonithurai ( F = 8.0981 , P = 0.0012 ) and Munaikadu ( F = 12.505 , P = 0.00011 ). Coral nubbins outplanted during the northeast monsoon season reached a length between 7.39 ± 0.76cm and 9.54 ± 0.49cm in Munaikadu and between 6.65 ± 0.70cm and 8.01 ± 0.38cm in Thonithurai after 9 months of growth ( Table 1 ). Coral fragments showed significant differences in growth size between the two sites ( F = 8.5273 , P = 0.0063 ). After 18 months of successful coral restoration in Thonithurai, the average monthly growth rate of A. muricata was 0.60cm, whereas A. hyacinthus, M. digitata , and P. damicornis attained a size of 0.44cm, 0.47cm, and 0.18cm, respectively (Fig. 2 a). In Munaikadu, the average monthly growth rate of A. muricata, M. digitata, A. hyacinthus and P. damicornis was 0.67cm, 0.55cm, 0.52cm, and 0.25cm, respectively (Fig. 2 a). The cumulative growth rate of the coral species was higher in Munaikadu than that in Thonithurai. During the first three months of restoration, coral fragments take time for accretion on the hard substrata, after which they grow easily. However, the average monthly growth rate of P. damicornis from the initial date until 18 months did not vary much, and it showed the lowest growth rate (0.18–0.19 cm/month) at both Thonithurai and Munaikadu (Fig. 2 a). The average monthly growth rate of the coral fragments outplanted during the northeast monsoon season was lower than that of those outplanted during the summer. In Thonithurai, the cumulative average growth rate was less than 0.30cm, indicating that some stress factors retarded the growth of the nubbins (Fig. 2 b). In Munaikadu, A. muricata achieved the highest average monthly growth rate (0.44cm) after 9 months of restoration, followed by M. digitata (0.39cm), A. hyacinths (0.37cm), and P. damicornis (0.27cm) (Fig. 2 b). Based on monthly observations, the overall survival rate of coral species was higher in Munaikadu than in Thonithurai (Fig. 3 a-d). A. muricata exhibited a good survival rate during the first (72.5% and 57.5%) and second (80% and 70%) sets of restoration in Munaikadu, but P. damicornis had a significant death rate throughout both sets of restoration (Fig. 3 a & 3 c). The survival rate of coral nubbins transplanted during summer showed significant differences between the species ( F = 5.493 , P = 0.003 ), whereas the ANOVA result showed no significant difference in the coral survival rate between the two sites ( F = 1.88 , P = 0.177 ). The survivability of coral species was inversely correlated with the duration of restoration ( R 2 = 0.7273 in Thonithurai, R 2 = 0.6854 in Munaikadu), and the mortality of coral species increased during the first 6 months of restoration (Fig. 4 ). Principal component analysis (PCA) result depicted the influence of environmental parameters to growth rates of corals in both the sites (Fig. 5 ). The horizontal axis (PC1) was responsible for 46.617% of variance found in monthly observations of environmental parameters. The vertical axis (PC2) was responsible for 24.518% of variance in growth rates and the coefficient value of the independent variables ( P = 0.658 for pH, P = 0.505 for salinity, P = 0.885 for temperature, and P = 0.519 for DO 2 ) on growth rate was also greater than 0.05, which revealed that there was no significant difference in the growth rate of corals due to the water quality parameters (Fig. 5 ). The average sedimentation rate in the Palk Bay was ranged between 4.79 to 123.06mg/cm 2 /day. However, the sedimentation rate was the highest in Thonithurai during the northeast monsoon (October to December), ranging from 6.01 to 123.06 mg/cm 2 /day ( Fig. 6 ) . Levene's test for equality of variance showed an F ratio of 6.178, with P < 0.05 ( P = 0.017); therefore, the t-test result is significant, indicating the sedimentation rates in Munaikadu and Thonithurai are significantly different from each other. The mean difference in sedimentation rate was higher in Thonithurai (21.889mg/cm 2 /day) than that in Munaikadu (8.867mg/cm 2 /day). 3.2. Fish Assemblage Monitoring of fish assemblages at coral restoration sites for 9 months revealed a high abundance of Scaridae (parrotfish), Terapontidae (grunter fish), Acanthuridae (surgeonfish), Siganidae (rabbitfish), Pempheridae (sweeper fish), Pomacentridae (damselfish), and Lethrinidae (sea bream). A total of 1060 fishes were recorded during the survey, and at the initial phase of restoration, only the grunter fish T. jarbua (Terapontidae) was found to be dominant at the restoration site ( Table 2 ). Thereafter, during the 6 months of restoration, Terapontidae (14.00 ± 2.41), Signidae (19.67 ± 3.62) and Lethrinidae (17.92 ± 3.72) were found abundant, followed by Scaridae (5.58 ± 1.56), Acanthuridae (4.42 ± 1.00), Pempheridae (4.92 ± 1.29), and Pomacentridae (4.83 ± 1.24) ( Table 2 ). Box-Whisker analysis showed the variability in the occurrence of different fish families in Palk Bay (Fig. 7 ). Multiple regression analysis demonstrated that higher coral growth at the restoration site was connected with a large number of fish accumulation ( R 2 = 0.822 ), which emerged as an indicator of healthy reefs (Fig. 8 ). 4. Discussion The community structure of coral reefs in Palk Bay comprises 4% of the total marine fauna in this region, including the 13 species of stony corals A. muricata , A. hyacinthus , M. digitata , P. damicornis , Dipsastraea favus , Dipsastraea speciosa , Dipsastraea pallida , Favites halicora , Porites solida , Porites lutea , Porites lichen , Goniopora minor , and Goniastrea pectinata. To protect the natural reef from undergoing threats, coral restoration in Palk Bay is necessary to break the barrier of natural recovery and to accelerate the system recovery. In India, branching corals are the preferred option for coral transplantation to alleviate coral reef habitat followed by coral gardening and artificial reef formation ( Yogesh et al . 2017; Balaji et al. 2019 ) due to their faster growth rate than other scleractinian species. The present study transplanted four species of corals, and their growth and survival capabilities were assessed to measure the success of coral restoration on the southeast coast of India (Fig. 9 a-d). Earlier, the growth and survival of scleractinian corals by coral transplantation technique was studied as an alternative management option in Lakshadweep Island and the Gulf of Kachchh Marine National Park of India. The present investigation also demonstrated simple rehabilitation techniques and monitoring strategies to promote coral growth, survival, and habitat recovery that provide useful insights into the restoration outcomes. Preliminary observations on the restoration site revealed that coral nubbins take minimum of three months to reattach to the substrate through calcification and attachments are influenced by several factors such as competition with turf algae and sedimentation which results in slow or no growth for the first few months of coral transplantation. Similar observation was reported from the reef of northern Philippines and atoll reef of Lakshadweep Islands (Yap et al. 1992 ; Babu and Kumar 2016 ). Performance of growth rate of branching corals by direct transplantation method in Palk Bay after 18 months of transplantation attain high appreciation with 0.67cm/month. Yogesh et al. (2017) documented the average monthly growth rate of transplanted A. muricata (0.33cm), A. Cytherea (0.36cm), and M. digitata (0.54cm) from the Gulf of Kachchh Reef, which was comparatively lower than that in the present study. Other reports on different reef restoration programs revealed that the average monthly growth rate of Acropora sp. ranged between 0.16cm and0.67cm (Oliver et al. 1983 ; Clark & Edwards 1995 ; Putchim et al. 2008 ; Anderson et al. 2012 ; Xin et al. 2016 ). The restoration efforts in Palk Bay resulted in high growth rates for A. muricata and A. hyacinthus , whereas the growth of Pocillopora damicornis was found least in numbers. Massive corals are expected to have a higher survival rate than branching corals in general (Gomez et al., 2014 ), but given the regional extent of coral species' local adaptive measures, massive corals are more sensitive to increased temperatures than branching corals in the Gulf of Mannar and Palk Bay. ( Krishnan et al., 2018 ). Hence, this study explored the growth and survival of branching corals during the first coral restoration attempt in Palk Bay. Coral survival is another important factor in deciding whether prospective restoration efforts have succeeded. The coral outplanting method could be a poor option if few coral species show significant growth at the recipient site, and the majority may not survive due to environmental stress (Edwards and Clark 1998 ; Gann et al. 2019 ). Based on species, the survivability of A. muricata , A. hyacinthus , and M. digitata in the present study ranged between 50% and 80% during both the restoration processes, whereas P. damicornis showed high mortality during the 18 months. The mortality of coral species was higher during the first three months of restoration, followed by a steady survival rate at each site (Fig. 3 a-d). Yogesh et al. (2017) documented 79% Acropora survival in Narara reef and 69.0% in Pirotan Island in the Gulf of Kachchh during 12 months of coral transplantation. Survival of newly outplanted coral fragments is primarily limited by environmental stressors (bleaching, sedimentation), macroalgal proliferation and exposure of invasive species to the restored sites (Kamalakannan et al. 2014 ; Joshi and Marimuthu 2015 ; Thangaradjou et al. 2016 ). The present study reported higher growth and survival in Munaikadu than that in Thonithurai, which experienced high sedimentation rates during the northeast monsoon (Fig. 6 ). In Palk Bay, the Pamban Channel brings sediment from the Gulf of Mannar during the southwest monsoon (June to September), whereas local wind and waves transport large amounts of sediment during the northeast monsoon to Palk Bay ( Wilson et al. 2005 ). Hence, the lower growth and survival of the coral species outplanted during the northeast monsoon is due to severe sediment deposition, which ranged between 37.16 and 123.06 mg/cm 2 /day in Thonithurai and between 24.27 and 41.37 mg/cm 2 /day in Munaikadu (Fig. 6 ). The sandy sea bottom and the diverse, dense seagrass in Thonithurai accumulate more sediment than the rock-based benthic texture of Munaikadu. High sea surface temperatures also induced coral bleaching in 2016 and have become an annual phenomenon in the Gulf of Mannar and Palk Bay ( Krishnan et al. 2018; Koushik et al. 2021 ). Therefore, coral nubbins transplanted during February face immediate bleaching events, and mortality becomes high during the first three months of restoration. P. damicornis is highly affected by bleaching events and has a mortality rate of 70%. The present study did not report any direct impact of pH, salinity, DO 2 , or temperature on the growth of coral nubbins transplanted at the restoration site. Fish assemblages at restoration sites are critical components of social and physical reef resilience (Maynard et al. 2017 ). Increasing fishery resources or diversity via coral restoration efforts is not always practically accepted, and several biological stressors restrict the diversity of marine organisms in restoration sites (Ladd et al. 2019 ; Hein et al. 2020 ). However, the present study reported significant fish abundance with increased coral growth ( R 2 = 0.822 ) at the restoration sites (Fig. 8 ). Palk Bay serves as an important feeding and breeding ground for many finfish and shellfish; however, many commercially valuable fish species have recently been overexploited in the Palk Bay region, which has significantly reduced marine resources (Balaji et al. 2019 ). The present investigation revealed seven different families of fish that were cumulatively assessed at both restoration sites, and the family Terapontidaewas found to be abundant throughout the restoration process ( Table 2 ). T. jarbua is not a commercially important species but is used as bait for fishing by the local fishing communities (Balaji et al. 2019 ). Assemblages of commercially important fishes such as Scaride, Lethrinidae, and Siganidae were abundant after 3 months of restoration (Fig. 9 k-l). Fish assemblage observations have also reported that important herbivorous species such as Acanthuridae, Pomacentridae ( P. trilineatus ), and Siganidae ( S. javus ) were also abundant. These herbivore species contribute to the maintenance of coral-dominated reefs by removing sediment (Goatley and Bellwood 2010 ) and controlling turf algae and macroalgae in reef areas (Verges et al., 2012). Long-term monitoring of artificial reef structures and assessing the associated community structures, including fish diversity, will provide a better understanding of reef functions and processes directly linked to increased fish and marine biodiversity (Sala et al. 2016 ; Viana et al. 2017 ). Therefore, the present study provides significant insight into the successful recovery of coral fragments transplanted from the local habitat that can be used to enhance the development of sustainable and small-scale fisheries for coastal communities. Restoration efforts in India are confined to a few studies. As a result, long-term monitoring of transplanted corals of local species in Palk Bay reefs provides a comprehensive insight into the recovery potential of targeted coral species while also improving the structural complexity of the reef through successful growth of coral colonies to the restored sites, resulting in an enhancement of associated macrofaunal communities. Despite several debates on the restoration procedure and the effectiveness of large-scale implementation of this management strategy to recover ecological integrity, scientists claimed that coral restoration is not intended to reduce climate change impacts, but rather as a complementary tool to support natural recovery following disturbances in specific areas. However, in the context of continued coral decline attributed to climate impacts, coral restoration could be considered as a part of an integrated resilience-based management framework. Moreover, this conservation management tool also enriches the live coral cover in the degraded reef of Palk Bay and maintains a repository of local resilient candidate species which in future reduce the pressure of mass mortality of corals, support community-based ecotourism and environmental education. 5. Conclusion The restoration of corals has been a promising scientific practice to rebuild degraded and damaged coral reefs in the current climate change scenario. The present study mainly focused on a low-cost transplantation technique to recover the degraded reef in terms of significant growth and survival of targeted coral species by the asexual propagation of coral fragments. Although several restoration projects have been concluded to be successful based on short-term monitoring of growth and survival, the present study underlines the importance of monitoring the growth and survival of targeted coral species for 1.5 years. The NCCR research team is continuing to monitor the restoration sites and improve the data collection on fish assemblage and the seasonal diversity of reef fishes. The study also delivered a successful framework for improving fishery resources by deploying artificial structures and restoring coral reefs in Palk Bay. Declarations Acknowledgments The project is funded by Ministry of Earth Sciences, Government of India under “Coastal Research scheme" implemented by National Centre for Coastal Research (NCCR), Chennai. Authors thank Secretary, MoES for constant encouragement and support to carry out the work. We sincerely thank the Chief Wildlife Warden, Ramanathapuram, Department of Environment and Forest, Government of Tamil Nadu, for providing logistic support and necessary permission to carry out the research work in Marine National Park. Authors also express sincere thanks to the field assistants for their field support. We would also like to thank Editage (www.editage.com) for English language editing. Declaration of competing interests The authors report no declaration of interest. Author’s Contribution K.S. – Conceptualization and design of the study; Data Collection and analysis; Manuscript writing, reviewing and editing; T.S. –Design the sampling; Assist in Field Survey, Supervision; Manuscript Editing; M.V.R.M –Supervision, Coordination, Fund acquisition, Manuscript Editing Ethical Approval This declaration is not applicable Funding This study was funded by the Ministry of Earth Sciences, New Delhi, India. Availability of Data and Materials All data supporting the findings of this study are available within the paper and its Supplementary Information. References Airoldi L, Turon X, Perkol-Finkel S, Rius M (2015) Corridors for aliensbut not for natives: effects of marine urban sprawl at a regional scale. Divers Distrib 21:755–768. 10.1111/ddi.12301 Allen GR, Steen R (2007) Indo-Pacific Coral Reef Field Guide. Tropical Reef Research, Singapore, p 378 Anderson K, Pratchett M, Baird A (2012) Summer growth rates at Lord Howe Island, Australia. 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Coral Reefs 14:201–213 De K, Venkatarman K, Ingole B (2017) Current status and scope of coral reef research in India- A bioecologicalperspective. Indian J Geo-Mar Sci 46(04):647–662 Edwards AJ, Clark S (1998) Coral Transplantation: A Useful Management Tool or Misguided Meddling? Mar Pollut Bull 37(8–12):474–487. https://doi.org/10.1016/S0025-326X(99)00145-9 Edwards AJ, Guest JR, Heyward AJ, Villanueva RD, Baria MV, Bollozos ISF, Golbuu Y (2015) Direct seeding of mass-cultured coral larvae is not an effective option for reef rehabilitation. Mar Ecol Prog Ser 525:105–116 Froehlich CYM, Kline RJ (2015) Using fish population metricsto compare the effects of artificial reef density. PLoS ONE 10:e0139444. 10.1371/journal.pone.0139444 Gann Gd, Mcdonald T, Walder B, Aronson J, Nelson Cr, Jonson J, Hallette JG, Eisenberg C, Guariguata MR, Liu J, Hua F, Echeverria C, Gonzales E, Shaw N, Decleer K, Dixon KW (2019) International principles and standards for the practice of ecological restoration. Second edition. Rest Ecol 27(S1): S1–S46. https://doi.org/10.1111/rec.13035 Gilmour JP, Smith LD, Heyward AJ, Baird AH, Pratchett MS (2013) Recovery of an isolated coral reef system following severe disturbance. Science 340:69–71 Goatley CHR, Bellwood DR (2010) Biologically mediated sediment fluxes on coral reefs: sediment removal and off-reef transportation by the surgeonfish Ctenochaetusstriatus . Mar Ecol Prog Ser 415:237–245 Gomez ED, Cabaitan PC, Yap HT, Dizon RM (2014) Can coral cover be restored in theabsence of natural recruitment and reef recovery? Rest Ecol 22:142150. 10.1111/rec.12041 Guest JR, Baria MV, Gomez ED, Heyward AJ, Edwards AJ (2014) Closing the circle: Is it feasible to rehabilitate reefs with sexually propagated corals? Coral Reefs 33:45–55 Hancock JR, Barrows AR, Roome TC, Huffmyer AS, Matsuda SB, Munk NJ, Rahnke SA, Drury C (2021) Coral husbandry for ocean futures: leveraging abiotic factors to increase survivorship, growth, and resilience in juvenile Montiporacapitata . Mar Ecol Prog Ser 657:123–133. https://doi.org/10.3354/meps13534 Hein MY, Beeden R, Birtles RA, Chase TJ, Couture F, Haskin E, Nadine M, Ripple K, Lisa T, Willis Bette L, Reanna W, Gardiner NM (2020) Effects of coral restoration on fish communities: snapshots of long-term, multiregional responses and implications for practice. Rest Ecol 28(5):1158–1171 Hill J, Wilson C (2004) Methods for ecological monitoring of coral reefs . Ver.1. GCRMN. Australian Institute of Marine Science, Australia, p 123 Hughes TP, Barnes ML, Bellwood DR et al (2017) Coral reefs in the Anthropocene. Nature 546:82–90 Idrees Babu KK, Suresh Kumar S (2016) Survival and Growth of Transplanted Coral Fragments in Lagoons of Lakshadweep with notes on Fish Aggregation. Intern J Applied Pure Sci Agri 02(05):19–25 Joshi H, Marimuthu N (2015) Forbidding invasive species – a way to attain sustainability of the coastal ecosystem. Curr Sci 108(2):151–152 Kamalakannan B, Joyson J, Jeevamani J, Arun Nagendran D, Pandiaraja N, Chandrasekaran S (2014) Impact of removal of invasive species Kappaphycusalvarezii from coral reef ecosystem in Gulf of Mannar, India. Curr Sci 106(10):1401–1408 Koushik S, Ramesh CH, Shanmugaraj T, Ramana Murthy MV (2019) New recruitment of staghorn corals in the Gulf of Mannar – the emergence of a resilient coral reef. J Threat Taxa 11(14):14908–14911. https://doi.org/10.11609/jott. 4767.11.14 Koushik S, Ramesh CH, Shanmugaraj T, Ramana Murthy MV (2020) Assessment on Recovery of Coral Reefs in Palk Bay of India after 2019 Coral Bleaching Events–A Case Report. Environ Ecol 38(4):863–867 Koushik S, Ramesh CH, Shanmugaraj T, Ramana Murthy MV (2021) Recent Coral Bleaching Impacts in Reef Ecosystem of Gulf of Mannar and Palk Bay. Intern J Ecol Environ Sci 47:179–187 Krishna P, Purvaja R, Sreeraj CR, Raghuraman R, Robin RS, Abhilash KR, Mahendra RS, Anand A, Gopi M, Mohanty PC, Venkataraman K, Ramesh R (2018) Differential bleaching pattern in corals of Palk Bay and the Gulf of Mannar. Curr Sci 114(3):679–685 Ladd MC, Burkepile DE, Shantz AA (2019) Near-term impacts of coral restoration on target species, coral reef community structure, and ecological processes. Rest Ecol 27:1166–1176 Lirman D, Schopmeyer S, Galvan V, Drury C, Baker AC, Baumus IB (2014) Growth Dynamics of the Threatened Caribbean Staghorn Coral Acropora cervicornis : Influence of Host Genotype, Symbiont Identity, Colony Size, and Environmental Setting. PLoS ONE 9(9):e107253. 10.1371/journal.pone.0107253 Manikandan B, Ravindran J (2016) Differential response of coral communities to Caulerpa s bloom in the reefs of Indian Ocean. Environ Sci Pollut Res 24(4):3912–3922 Maynard JA, Marshall PA, Parker B et al (2017) Coral reef resilience for decision support. UN Environment, Nairobi, Kenya Nair RJ, Kuriakose S (2014) Field Guide to Reef Associated Fishes of India. CMFRI Special Publication No. 117, Director, CMFRI, Kochi, 156pp Nava H, Figueroa-Camacho AG (2017) Rehabilitation of damaged reefs: outcome of the use of recently broken coral fragments and healed coral fragments of pocilloporid corals on rocky boulders. Mar Ecol 38:1–10 Oliver JK, Chalker BE, Dunlap WC (1983) Bathymetric adaptations of reef building corals at Davies reef, Great Barrier Reef, Australia. Long – term growth-responses of Acropora formosa (Dana, 1846). J Expl Mar Biol Ecol 73:11–35 Ortiz JC, Wolff NH, Anthony KRN, Devlin M, Lewis S, Mumby PJ (2018) Impaired recovery of the Great barrier reef under cumulative stress. Sci Adv 4:6127. https://doi.org/10.1126/sciadv. aar6127 Putchim LN, Thongtham, Hewett A, Chansang H (2008) Survival and growth of Acropora sp. in mid-water nursery and after transplantation at Phi Phi Islands, Andaman Sea, Thailand. Proceeding of the 11th International coral reef Symposium , Ft. Lauderdale, Florida, 7–11 July 2008 Session No. 24, 1258–1261 Ramesh CH, Koushik S, Shanmugaraj T, Ramana Murthy MV (2020a) Seasonal studies on in situ coral transplantation in the Gulf of Mannar Marine Biosphere Reserve, Southeast coast of Tamil Nadu, India. Ecol Eng 152., Article 105884. https://doi.org/10.1016/j.ecoleng. 2020.105884 Ramesh CH, Koushik S, Shanmugaraj T, Ramana Murthy MV (2020b) Exhibition of Bleaching Resistance via Adaptive Bleaching Pattern by Coral Reefs of the Gulf of Mannar during Massive Bleaching Event 2019. J Mar Sci 2(2):1–4 Randall CJ, Negri AP, Quigley KM et al (2020) Sexual production of corals for reef restoration in the Anthropocene. Mar Ecol Prog Ser 635:203–232 Rinkevich B (2017) Rebutting the inclined analyses on the cost-effectiveness and feasibility of coral reef restoration. Ecol Appl 27:1970–1973 Sala E, Costello C, De Bourbon P et al (2016) Fish banks: an economic model to scale marine conservation. Mar Policy 73:154–161 Suggett DJ, Camp EF, Edmondson J, Boström-Einarsson L, Ramler V, Lohr K, Patterson J (2018) Optimizing return-on-effort for coral nursery and out-planting practices to aid restoration of the Great Barrier Reef. Rest Ecol. 10.1111/rec.12916 Thangaradjou T, Machendiranathan M, Ranith R, Senthilnathan L, Sasamal SK, Choudhury SB (2016) Coral disease prevalence in Gulf of Mannar and Lakshadweep Islands. Indian J Mar Sci 45:1755–1762 Van Oppen MJH, Oliver JK, Putnam HM, Gates RD (2015) Building coral reef resilience through assisted evolution. Proc Nat Acad Sci 112:2307–2313 Vergés A, Bennett S, Bellwood DR (2012) Diversity among macroalgae consuming fishes on coral reefs: a transcontinental comparison. PLoSOne 7:e45543 Viana DF, Halpern BS, Gaines SD (2017) Accounting for tourism benefits in marine reserve design. PLoSOne 12:e0190187. https://doi.org/10.1371/journal.pone.0190187 WilsonJJ, Marimuthu N, Kumaraguru AK (2005) Sedimentation of silt in the coral reef environment of Palk Bay. J Mar Biol Assoc India 47(1):83–87 Woodhead AJ, Hicks CC, Norstrom AV, Williams GJ, Graham NAJ (2019) Coral reef ecosystem services in the Anthropocene. Funct Ecol 33:1023–1034 Xin LH, Adziska A, Hyde J, Cob ZC (2016) Growth performance of Acropora Formosa in natural reefs and coral nurseries for reef restoration. AACL Bioflux 9:1090–1100 Yap HT, Aliño PM, Gomez ED (1992) Trends in growth and mortality of threecoral species (Anthozoa: Scleractinia), including effects of transplantation. Mar Ecol Prog Ser 83:91e101 Yogesh Kumar JS, Geetha S, Sornaraj R (2014) Seasonal Changes of Sedimentation Rates and Sediment Characteristics Status in the Gulf of Mannar Coral Island, India. Intern Lett Nat Sci 1:8–24 Yogesh Kumar JS, Sathyanaryan CH, Venkataraman K, Chandr K (2017) Studies on survival and growth rate of transplanted Acroporidae in Gulf of Kachchh Marine National Park, India. J Coast Conserv 21:23–34. https://doi.org/10.1007/s11852-016-0465-5 Tables Table 1 Detail Growth (Mean±SE) of coral nubbins during the study Table 2 Observation on fish assemblage in coral restoration site Additional Declarations No competing interests reported. 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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-3680863","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":261517947,"identity":"d78aac36-68ee-4b89-98c3-12ae61b6d159","order_by":0,"name":"Koushik Sadhukhan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYHACMwaGAweANGPjg49/bMCMA0RqYW42nNmQBtLSQKwW9jZp3obDYCG8WuTbD297zHPmjrw5A2Ob5Mwd5+3Wth8G2lJjE41Li8GZtHJjnhvPDHc2MDZbfDxzO3nbmUSglmNpuQ24tDDkmEnzfDjMuOEAY+PNGWy3k80OALUwNhzGqUW+/w1Yiz1QS4M0D9u5ZLPzD/FrYbgBsuXG4USgliZp3rYDdmY3CNhicONZmeScM4eTNxxmbDaccSY5wewG0JYEPH6R70/eJvHm2GHbDcfbHz74UGFnb3Y+HcioscHtMDhghlCJYJUJBJUjAXtSFI+CUTAKRsHIAAAdKW/pgW6yJQAAAABJRU5ErkJggg==","orcid":"","institution":"National Centre for Coastal Research, Field Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Koushik","middleName":"","lastName":"Sadhukhan","suffix":""},{"id":261517948,"identity":"8957fa6a-a3c4-471f-a099-8bc58efa6436","order_by":1,"name":"T. Shanmuagaraj","email":"","orcid":"","institution":"National Centre for Coastal Research, Field Research Centre","correspondingAuthor":false,"prefix":"","firstName":"T.","middleName":"","lastName":"Shanmuagaraj","suffix":""},{"id":261517949,"identity":"d25871f9-e7c7-484f-9336-e461cfd22a98","order_by":2,"name":"Ramana Murthy M V","email":"","orcid":"","institution":"National Centre for Coastal Research","correspondingAuthor":false,"prefix":"","firstName":"Ramana","middleName":"Murthy M","lastName":"V","suffix":""}],"badges":[],"createdAt":"2023-11-29 09:44:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3680863/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3680863/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50584195,"identity":"5a9f1923-91c5-469a-9fa5-9d4cbeac415c","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":447744,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Area map showing the location of donor site and transplantation site\u003c/p\u003e","description":"","filename":"F1.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/7b513010a69a0e26d47ed6ef.png"},{"id":50584291,"identity":"9a5dd61d-8f9c-4ce2-97e5-78c166c1341e","added_by":"auto","created_at":"2024-02-02 21:04:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77125,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly growth rate of coral species: A) – 18 months of restoration – 1st set; B) – 9months of restoration – 2nd sets.\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/e128ac8115617f092c21f82a.png"},{"id":50584199,"identity":"8fcdfeee-4add-4fa1-bb19-f329bb4feb1d","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39077,"visible":true,"origin":"","legend":"\u003cp\u003eSurvivability of coral species at different study sites.\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/fe72f40de534a35125986863.png"},{"id":50584196,"identity":"834b3bb8-208b-4ab5-89a3-a13db3cae194","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":46748,"visible":true,"origin":"","legend":"\u003cp\u003eLinear Regression curve for number of survivals during restoration.\u003c/p\u003e","description":"","filename":"F4.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/5ac41d8d089bdb49dc9bf3e5.png"},{"id":50584294,"identity":"469dace3-80e6-45ab-945b-68bd6ff80ae5","added_by":"auto","created_at":"2024-02-02 21:04:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":261776,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis of Monthly water quality parameters and growth rate variance of Thonithuria and Munaikadu\u003c/p\u003e","description":"","filename":"F5.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/8704732e08d9bf0980832381.png"},{"id":50584201,"identity":"cd6e1ffa-ba48-4283-b562-a86ae05abacf","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":73227,"visible":true,"origin":"","legend":"\u003cp\u003eVariation in sedimentation rate (mg/cm\u003csup\u003e2\u003c/sup\u003e/day) during coral restoration\u003c/p\u003e","description":"","filename":"F6.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/29e9cbc96c0f2c6af2de9949.png"},{"id":50584359,"identity":"134df1c6-273b-4faa-8652-4780b508cb5b","added_by":"auto","created_at":"2024-02-02 21:12:39","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":32502,"visible":true,"origin":"","legend":"\u003cp\u003eBox-Whisker analysis for the occurrence of fishes at restoration sites in Palk Bay. Boxes indicate the 25th to 75th percentile range, the band in the middle represents the median value, lower and upper bands indicate minimum and maximum values respectively.\u003c/p\u003e","description":"","filename":"F7.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/ecfae1e1a88444a7805ac699.png"},{"id":50584360,"identity":"6f8717ea-c51f-4fe2-9c32-1db5b8a7747c","added_by":"auto","created_at":"2024-02-02 21:12:39","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":100927,"visible":true,"origin":"","legend":"\u003cp\u003eLinear regression curve of fish abundance in response to coral growth.\u003c/p\u003e","description":"","filename":"F8.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/21a3e3956a5f4390a94db30a.png"},{"id":50584203,"identity":"25c11e7b-f1b1-4d68-bc1a-974e0a0a773f","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1044358,"visible":true,"origin":"","legend":"\u003cp\u003eRestoration activities in Palk Bay (2020-2021): a-b: Frames and slabs structure used in restoration studies; c-d: coral fragments at initial stages of restoration; e-h: coral accretion occurred after the installation of coral fragments on cement slabs; i-j: Coral growth after 18 months of restoration; k-l: fish assemblage found on restoration site in Palk Bay.\u003c/p\u003e","description":"","filename":"F9.png","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/aedc3d56c6b0ac1cea5ca09c.png"},{"id":55282715,"identity":"568e0765-caa6-4577-a226-a422ac58e16a","added_by":"auto","created_at":"2024-04-25 07:15:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3369436,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/ce1b5dbc-a5e1-433d-8774-06b4bd21cdcc.pdf"},{"id":50584204,"identity":"faf59ae6-2ccd-4d9c-918d-738808bbdac8","added_by":"auto","created_at":"2024-02-02 20:56:39","extension":"pptx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2290731,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarydataKS.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3680863/v1/459336e54c3366089393ae72.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Coral Restoration in Palk Bay on the Southeast Coast of India","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCoral restoration is considered an important conservation management tool to recover a degraded or damaged reef from natural and anthropogenic disturbances and to kick start the system recovery by introducing local resistant coral species into the degraded site. Recent climate change impacts and anthropogenic stressors have drastically affected coral reef habitats and damaged reef recovery potential, which in turn has led to a decline in the ecosystem and economic services provided by coral reefs (Cheal et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hughes et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ortiz et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Woodhead et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Several management intervention programs have been implemented to recover degraded reef diversity and restore the structure and function of reef ecosystems. Of these programs, direct coral transplantation method is highly used in tropical countries. Reef recovery takes several years under ideal environmental conditions, and most restoration work in the recent past has been relied on the asexual propagation of coral fragments either locally or regionally (Gilmour et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hancock et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Several restoration technologies based on sexual reproduction of corals were developed as well to promote recovery, genetic variety, and logistic complexity in order to achieve effective restoration programmes. (Guest et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Randall et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the lack of long-term monitoring, high-cost technology, poor site selection, and high fragment mortality have become major constraints for successful reef restoration (Edwards et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; van Oppen et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rinkevich \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hancock et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, a handy and cost-effective technology is emerging as a high priority for mitigating global changes in vulnerable coral reef ecosystems.\u003c/p\u003e \u003cp\u003eIn India, coral reefs are also degrading at an alarming rate due to bleaching prevalence, macroalgal proliferation to the reef areas, sedimentation, threats from invasive species and local anthropogenic pressure (Manikandan and Ravindran \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; De et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cb\u003eKrishnan et al. 2018\u003c/b\u003e). Therefore, coral restoration is necessary to expedite the natural recovery of the Indian reefs and improve the ecological integrity of the reef ecosystem. However, In India, efforts put into coral restoration programs are minimal, and successful restoration activities are few. In 2007, asexual propagation of adult coral fragments was used to launch the first coral restoration program on Lakshadweep Island (\u003cb\u003eBabu and Kumar 2016\u003c/b\u003e), and in 2014, the Zoological Survey of India began coral transplantation techniques in the Gulf of Kachchh Marine National Park to restore degraded reefs (\u003cb\u003eYogesh et al. 2017\u003c/b\u003e). In 2018, an effort to develop artificial reef formation was initiated in Palk Bay on the southeast coast of India (Balaji et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, \u003cb\u003eYogesh et al\u003c/b\u003e. \u003cb\u003e(2017)\u003c/b\u003e reported successful transplantation of \u003cem\u003eAcropora\u003c/em\u003e corals in the Gulf of Kachchh, resulting in a survival rate greater than 55% from 2014 to 2016. Other programs failed to recover degraded reefs or promote the growth and survival of coral species. To address the growth and survival of coral species and enrichment of reef diversity by coral transplantation methods, National Centre for Coastal Research (NCCR) has implemented a coral restoration program in the Gulf of Mannar Marine National Park in 2018 (Ramesh et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePalk Bay is considered an important marine fishery resource area in India, comprising various habitats such as estuaries, salt marshes, coral reefs, seagrass beds, and mangroves. It is adjacent to the Gulf of Marine Biosphere Reserve, India's first marine protected area. This important coastal habitat is enriched by a high diversity of species (344 marine fauna, 186 wetland birds, nine seagrasses, and 16 mangrove species) including many unique and threatened animals (Bhatt et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Over the past few decades, reef-building corals and its associated biota severe degradation because of recurring coral bleaching events, high sedimentation rates during southwest monsoons, and increasing fishing activities (Koushik et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, artificial reef habitat formation is an important resource for marine biodiversity enrichment, especially for important coral species in this region though few scientist or conservationists argued that artificial reef can introduce invasive species into the reefs and also express doubt on fish stock enhancement and reduction in fish diversity near to artificial reefs (Airoldi et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Froehlich and Kline \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, to address the prevention of reef damage, and recovery of corals and their associated biodiversity, the present study was undertaken at two separate sites in Palk Bay, Munaikadu and Thonithurai, using the direct transplantation method of coral fragments, from February 2020 to August 2021. The study mainly highlighted the growth and survivability of coral species with regular monitoring of water quality parameters and sedimentation rates at two different sites and also reported significant fish assemblages during the study period.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003ePalk Bay on the southeast coast of India is an important coastal habitat that is home to the largest commercial fishing population and the highest number of fish landing sites and fishing villages in the state of Tamil Nadu. The Palk Bay region is situated between latitudes 9\u0026deg; 55\u0026prime;N and 10\u0026deg; 45\u0026prime; N and longitudes 78\u0026deg; 58\u0026prime; E and 79\u0026deg; 55\u0026prime;E. The coastline of Palk Bay remains within the Ramnathapuram district, and the 1.2km long Pamban straits separate Palk Bay from the Gulf of Mannar (Azzez et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The coastal water of Palk Bay is shallow, upto a depth of 13m, and is enriched in marine flora and fauna. Patchy coral reefs and extended seagrass meadows are the major habitats for fish, dolphins, whales, and dugongs. The bay also encompasses a brackish backwater system that supports the lush growth of mangrove forests and the abundance of diverse migratory birds. Therefore, the Palk Bay marine ecosystem requires important conservation measures to combat climate change impacts and anthropogenic pressures. Presently, the region contributes approximately 70,000 tons of fisheries production annually, which is the highest in the state of Tamil Nadu (Azzez et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Methods and Sampling\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA coral restoration study was conducted from February 2020 to August 2021at two different sites in Palk Bay (Munaikadu:9\u0026deg;17.361\u0026prime;N,79\u0026deg;07.948\u0026prime;E; Thonithurai: 9\u0026deg;17.084\u0026prime;N,79\u0026deg;10.470\u0026prime;E) using a rapid and conventional direct coral transplantation method (Nava and Figueroa-Camacho \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; \u003cb\u003eYogesh et al. 2017;\u003c/b\u003e Ramesh et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Two different substrates were chosen to conduct the transplantation experiment: a rocky substrate (Munaikadu) and a sandy substrate (Thonithurai). The Munaikadu area receives minimum sediment deposition in both the summer and monsoon seasons, whereas Thonithurai experiences high silt deposition during the monsoon season. Asexual propagation of coral fragments was used to grow coral on hard substrates placed at 2.5\u0026ndash;4m depth. Monthly water quality monitoring was conducted using a Eureka Multi-Parameter Water Quality Sonde Manta\u0026thinsp;+\u0026thinsp;2. Photographic evidence of the growth and survivability of coral fragments was also documented during sampling using a Nikon Underwater W300 camera. The entire experimental process was performed using the following procedures.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Frames and Slabs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMetal frames with a length of 6ft, a width of 4ft, and a height of 0.5ft were used, on which cement slabs were fastened. Twenty frames were used at the two study sites. Square-shaped cement slabs, 20 cm\u003csup\u003e2\u003c/sup\u003ein area and 5 cm in height were used to maintain the coral nubbins. The weight of each slab was 5kg, and a center hole of 2cm was used to fix the coral nubbins, which were tied with a nylon cable (16\").\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Target Species\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eHealthy adult branching corals, \u003cem\u003eAcropora muricata, Acropora hyacinthus, Montipora digitata\u003c/em\u003e, and \u003cem\u003ePocillopora damicornis\u003c/em\u003e, between 5 and 6 cm in size, were used in this study. The live coral fragments were collected from two sites, known as donor sites (Site 1: Hare Island, 9\u0026deg;12.679'N, 79\u0026deg;5.088'E; Site 2: Manoli Island, 9\u0026deg;13.177'N,79\u0026deg;7.758'E). Live coral coverage at both donor sites has been reported to be between 50\u0026ndash;58%, with rich macro-benthic community and high density of newly recruited corals (Koushik et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These places were also close to the transplanting sites, which favored convenient access for coral movement and reduced stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The main criteria for selecting target species were faster growth rates, ease of adaptation to environmental changes, and sufficient availability of donor locations. Previous research has also shown that branching corals in the Gulf of Mannar and Palk Bay regions are more resistant to temperature stress than non-branching corals (\u003cb\u003eKrishnan et al. 2018;\u003c/b\u003e Ramesh et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. Coral transplantation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA total of 10 metal frames and 400 cement slabs were deployed at each site (Munaikadu and Thonithurai) in Palk Bay at 2.5-4m depth during two separate seasons of the year in February 2020 (summer) and November 2020 (northeast monsoon). The concept of two sets of transplantation practices made for the supply of the coral fragments for the next round of coral transplantation from the grown coral fragments in restoration sites. A set of five frames and 200 slabs each were placed in Munaikadu and Thonithurai. Healthy coral nubbins ranging between 5 cm and 6 cm were cut from the adult colonies. The fragments were transferred immediately inside a large plastic tub filled with seawater and carried carefully to the restoration site. Thereafter, each coral nubbin was placed on the central hole of each cement slab and tied with a nylon cable to fix them on to the slab.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.4. Data collection\u003c/h2\u003e \u003cp\u003eSampling was undertaken once every three months. The first set of the transplantation data covered 18 months (February 2020\u0026ndash;August 2021) and the second set 9 months (November 2020\u0026ndash;August 2021). Growth and survival were determined periodically using length measurements and \u003cem\u003ein situ\u003c/em\u003e observations. Coral growth was measured by fragment length at the time of deployment and every 3 months (Lirman et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Suggett et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Photographs were obtained during each sampling period. Water quality parameters and sedimentation rates were monitored monthly to assess their effects on coral growth. Fish assemblage data were obtained by performing random visual observations (\u003cb\u003eHill and Wilkinson 2004\u003c/b\u003e) from November 2020 to August 2021, as the observation area is short for a transect. Photographic evidence was used to identify the fish (\u003cb\u003eAllen and Steene 2007;\u003c/b\u003e Nair and Kuriakose \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) at each restoration site. The rate of sedimentation was calculated from the collected samples for every month, and the average weight of the sediment from each site was divided by the total surface area of the cylinder, and the sedimentation rate per day was calculated (\u003cb\u003eYogesh et al. 2014\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eData were analysed using MS Excel and PAST 4.0 statistical software. One-way analysis of variance (ANOVA), two-way ANOVA, and correlation and regression analyses were performed to interpret the significance of the difference in the growth rate between the two study sites and among the different species.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Growth and Survivability\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA total of 800 coral fragments were used to study coral growth and survival at the Munaikadu and Thonithurai sites in Palk Bay. The initial size of the installed coral fragments ranged from 5 to 6 cm. The average sizes of \u003cem\u003eA. muricata\u003c/em\u003e at the Munaikadu and Thonithurai sites after 18 months were 16.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13 cm and 17.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17 cm, respectively \u003cb\u003e(Table\u0026nbsp;1)\u003c/b\u003e. Among the four coral species, \u003cem\u003eA. muricata, A. hyacinthus\u003c/em\u003e, and \u003cem\u003eM. digitate\u003c/em\u003e grew at a steady rate, whereas \u003cem\u003eP. damicornis\u003c/em\u003e had the lowest growth rate at both sites \u003cb\u003e(Table\u0026nbsp;1)\u003c/b\u003e. Two-way ANOVA results revealed that there was no significant difference in coral growth between the corals at Munaikadu and Thonithurai (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;0.0105\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.91875\u003c/em\u003e), whereas growth rates differed significantly based on the months (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;35.55404\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;2.22E-17\u003c/em\u003e). Results based on coral species revealed a significant difference in the monthly growth rate in Thonithurai (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;8.0981\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.0012\u003c/em\u003e) and Munaikadu (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;12.505\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.00011\u003c/em\u003e). Coral nubbins outplanted during the northeast monsoon season reached a length between 7.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76cm and 9.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49cm in Munaikadu and between 6.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70cm and 8.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38cm in Thonithurai after 9 months of growth (\u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e). Coral fragments showed significant differences in growth size between the two sites (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;8.5273\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.0063\u003c/em\u003e). After 18 months of successful coral restoration in Thonithurai, the average monthly growth rate of \u003cem\u003eA. muricata\u003c/em\u003e was 0.60cm, whereas \u003cem\u003eA. hyacinthus, M. digitata\u003c/em\u003e, \u003cem\u003eand P. damicornis\u003c/em\u003e attained a size of 0.44cm, 0.47cm, and 0.18cm, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). In Munaikadu, the average monthly growth rate of \u003cem\u003eA. muricata, M. digitata, A. hyacinthus\u003c/em\u003e and \u003cem\u003eP. damicornis\u003c/em\u003e was 0.67cm, 0.55cm, 0.52cm, and 0.25cm, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The cumulative growth rate of the coral species was higher in Munaikadu than that in Thonithurai. During the first three months of restoration, coral fragments take time for accretion on the hard substrata, after which they grow easily. However, the average monthly growth rate of \u003cem\u003eP. damicornis\u003c/em\u003e from the initial date until 18 months did not vary much, and it showed the lowest growth rate (0.18\u0026ndash;0.19 cm/month) at both Thonithurai and Munaikadu (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The average monthly growth rate of the coral fragments outplanted during the northeast monsoon season was lower than that of those outplanted during the summer. In Thonithurai, the cumulative average growth rate was less than 0.30cm, indicating that some stress factors retarded the growth of the nubbins (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In Munaikadu, \u003cem\u003eA. muricata\u003c/em\u003e achieved the highest average monthly growth rate (0.44cm) after 9 months of restoration, followed by \u003cem\u003eM. digitata\u003c/em\u003e (0.39cm), \u003cem\u003eA. hyacinths\u003c/em\u003e (0.37cm), and \u003cem\u003eP. damicornis\u003c/em\u003e (0.27cm) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on monthly observations, the overall survival rate of coral species was higher in Munaikadu than in Thonithurai (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d). \u003cem\u003eA. muricata\u003c/em\u003e exhibited a good survival rate during the first (72.5% and 57.5%) and second (80% and 70%) sets of restoration in Munaikadu, but \u003cem\u003eP. damicornis\u003c/em\u003e had a significant death rate throughout both sets of restoration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea \u0026amp; \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). The survival rate of coral nubbins transplanted during summer showed significant differences between the species (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;5.493\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e), whereas the ANOVA result showed no significant difference in the coral survival rate between the two sites (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;1.88\u003c/em\u003e, \u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.177\u003c/em\u003e). The survivability of coral species was inversely correlated with the duration of restoration (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;0.7273\u003c/em\u003e in Thonithurai, \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;0.6854\u003c/em\u003e in Munaikadu), and the mortality of coral species increased during the first 6 months of restoration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Principal component analysis (PCA) result depicted the influence of environmental parameters to growth rates of corals in both the sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The horizontal axis (PC1) was responsible for 46.617% of variance found in monthly observations of environmental parameters. The vertical axis (PC2) was responsible for 24.518% of variance in growth rates and the coefficient value of the independent variables (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.658\u003c/em\u003e for pH, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.505\u003c/em\u003e for salinity, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.885\u003c/em\u003e for temperature, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.519\u003c/em\u003e for DO\u003csub\u003e2\u003c/sub\u003e) on growth rate was also greater than 0.05, which revealed that there was no significant difference in the growth rate of corals due to the water quality parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The average sedimentation rate in the Palk Bay was ranged between 4.79 to 123.06mg/cm\u003csup\u003e2\u003c/sup\u003e/day. However, the sedimentation rate was the highest in Thonithurai during the northeast monsoon (October to December), ranging from 6.01 to 123.06 mg/cm\u003csup\u003e2\u003c/sup\u003e/day \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Levene's test for equality of variance showed an \u003cem\u003eF\u003c/em\u003e ratio of 6.178, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017); therefore, the t-test result is significant, indicating the sedimentation rates in Munaikadu and Thonithurai are significantly different from each other. The mean difference in sedimentation rate was higher in Thonithurai (21.889mg/cm\u003csup\u003e2\u003c/sup\u003e/day) than that in Munaikadu (8.867mg/cm\u003csup\u003e2\u003c/sup\u003e/day).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Fish Assemblage\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMonitoring of fish assemblages at coral restoration sites for 9 months revealed a high abundance of Scaridae (parrotfish), Terapontidae (grunter fish), Acanthuridae (surgeonfish), Siganidae (rabbitfish), Pempheridae (sweeper fish), Pomacentridae (damselfish), and Lethrinidae (sea bream). A total of 1060 fishes were recorded during the survey, and at the initial phase of restoration, only the grunter fish \u003cem\u003eT. jarbua\u003c/em\u003e (Terapontidae) was found to be dominant at the restoration site (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e). Thereafter, during the 6 months of restoration, Terapontidae (14.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41), Signidae (19.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62) and Lethrinidae (17.92\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72) were found abundant, followed by Scaridae (5.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56), Acanthuridae (4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00), Pempheridae (4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29), and Pomacentridae (4.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24) (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e). Box-Whisker analysis showed the variability in the occurrence of different fish families in Palk Bay (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Multiple regression analysis demonstrated that higher coral growth at the restoration site was connected with a large number of fish accumulation (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;0.822\u003c/em\u003e), which emerged as an indicator of healthy reefs (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe community structure of coral reefs in Palk Bay comprises 4% of the total marine fauna in this region, including the 13 species of stony corals \u003cem\u003eA. muricata\u003c/em\u003e, \u003cem\u003eA. hyacinthus\u003c/em\u003e, \u003cem\u003eM. digitata\u003c/em\u003e, \u003cem\u003eP. damicornis\u003c/em\u003e, \u003cem\u003eDipsastraea favus\u003c/em\u003e, \u003cem\u003eDipsastraea speciosa\u003c/em\u003e, \u003cem\u003eDipsastraea pallida\u003c/em\u003e, \u003cem\u003eFavites halicora\u003c/em\u003e, \u003cem\u003ePorites solida\u003c/em\u003e, \u003cem\u003ePorites lutea\u003c/em\u003e, \u003cem\u003ePorites lichen\u003c/em\u003e, \u003cem\u003eGoniopora minor\u003c/em\u003e, and \u003cem\u003eGoniastrea pectinata.\u003c/em\u003e To protect the natural reef from undergoing threats, coral restoration in Palk Bay is necessary to break the barrier of natural recovery and to accelerate the system recovery. In India, branching corals are the preferred option for coral transplantation to alleviate coral reef habitat followed by coral gardening and artificial reef formation (\u003cb\u003eYogesh et al\u003c/b\u003e. \u003cb\u003e2017;\u003c/b\u003e Balaji et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) due to their faster growth rate than other scleractinian species. The present study transplanted four species of corals, and their growth and survival capabilities were assessed to measure the success of coral restoration on the southeast coast of India (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea-d). Earlier, the growth and survival of scleractinian corals by coral transplantation technique was studied as an alternative management option in Lakshadweep Island and the Gulf of Kachchh Marine National Park of India. The present investigation also demonstrated simple rehabilitation techniques and monitoring strategies to promote coral growth, survival, and habitat recovery that provide useful insights into the restoration outcomes. Preliminary observations on the restoration site revealed that coral nubbins take minimum of three months to reattach to the substrate through calcification and attachments are influenced by several factors such as competition with turf algae and sedimentation which results in slow or no growth for the first few months of coral transplantation. Similar observation was reported from the reef of northern Philippines and atoll reef of Lakshadweep Islands (Yap et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; \u003cb\u003eBabu and Kumar 2016\u003c/b\u003e). Performance of growth rate of branching corals by direct transplantation method in Palk Bay after 18 months of transplantation attain high appreciation with 0.67cm/month. \u003cb\u003eYogesh et al. (2017)\u003c/b\u003e documented the average monthly growth rate of transplanted \u003cem\u003eA. muricata\u003c/em\u003e (0.33cm), \u003cem\u003eA. Cytherea\u003c/em\u003e (0.36cm), and \u003cem\u003eM. digitata\u003c/em\u003e (0.54cm) from the Gulf of Kachchh Reef, which was comparatively lower than that in the present study. Other reports on different reef restoration programs revealed that the average monthly growth rate of \u003cem\u003eAcropora\u003c/em\u003e sp. ranged between 0.16cm and0.67cm (Oliver et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Clark \u0026amp; Edwards \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Putchim et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Anderson et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Xin et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The restoration efforts in Palk Bay resulted in high growth rates for \u003cem\u003eA. muricata\u003c/em\u003e and \u003cem\u003eA. hyacinthus\u003c/em\u003e, whereas the growth of \u003cem\u003ePocillopora damicornis\u003c/em\u003e was found least in numbers. Massive corals are expected to have a higher survival rate than branching corals in general (Gomez et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), but given the regional extent of coral species' local adaptive measures, massive corals are more sensitive to increased temperatures than branching corals in the Gulf of Mannar and Palk Bay. (\u003cb\u003eKrishnan et al., 2018\u003c/b\u003e). Hence, this study explored the growth and survival of branching corals during the first coral restoration attempt in Palk Bay. Coral survival is another important factor in deciding whether prospective restoration efforts have succeeded. The coral outplanting method could be a poor option if few coral species show significant growth at the recipient site, and the majority may not survive due to environmental stress (Edwards and Clark \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; \u003cb\u003eGann et al. 2019\u003c/b\u003e). Based on species, the survivability of \u003cem\u003eA. muricata\u003c/em\u003e, \u003cem\u003eA. hyacinthus\u003c/em\u003e, and \u003cem\u003eM. digitata\u003c/em\u003e in the present study ranged between 50% and 80% during both the restoration processes, whereas \u003cem\u003eP. damicornis\u003c/em\u003e showed high mortality during the 18 months. The mortality of coral species was higher during the first three months of restoration, followed by a steady survival rate at each site (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-d). \u003cb\u003eYogesh et al. (2017)\u003c/b\u003e documented 79% \u003cem\u003eAcropora\u003c/em\u003e survival in Narara reef and 69.0% in Pirotan Island in the Gulf of Kachchh during 12 months of coral transplantation. Survival of newly outplanted coral fragments is primarily limited by environmental stressors (bleaching, sedimentation), macroalgal proliferation and exposure of invasive species to the restored sites (Kamalakannan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Joshi and Marimuthu \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Thangaradjou et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The present study reported higher growth and survival in Munaikadu than that in Thonithurai, which experienced high sedimentation rates during the northeast monsoon (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In Palk Bay, the Pamban Channel brings sediment from the Gulf of Mannar during the southwest monsoon (June to September), whereas local wind and waves transport large amounts of sediment during the northeast monsoon to Palk Bay (\u003cb\u003eWilson et al. 2005\u003c/b\u003e). Hence, the lower growth and survival of the coral species outplanted during the northeast monsoon is due to severe sediment deposition, which ranged between 37.16 and 123.06 mg/cm\u003csup\u003e2\u003c/sup\u003e/day in Thonithurai and between 24.27 and 41.37 mg/cm\u003csup\u003e2\u003c/sup\u003e/day in Munaikadu (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The sandy sea bottom and the diverse, dense seagrass in Thonithurai accumulate more sediment than the rock-based benthic texture of Munaikadu. High sea surface temperatures also induced coral bleaching in 2016 and have become an annual phenomenon in the Gulf of Mannar and Palk Bay (\u003cb\u003eKrishnan et al. 2018;\u003c/b\u003e Koushik et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, coral nubbins transplanted during February face immediate bleaching events, and mortality becomes high during the first three months of restoration. \u003cem\u003eP. damicornis\u003c/em\u003e is highly affected by bleaching events and has a mortality rate of 70%. The present study did not report any direct impact of pH, salinity, DO\u003csub\u003e2\u003c/sub\u003e, or temperature on the growth of coral nubbins transplanted at the restoration site.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFish assemblages at restoration sites are critical components of social and physical reef resilience (Maynard et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Increasing fishery resources or diversity via coral restoration efforts is not always practically accepted, and several biological stressors restrict the diversity of marine organisms in restoration sites (Ladd et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hein et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the present study reported significant fish abundance with increased coral growth (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;0.822\u003c/em\u003e) at the restoration sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Palk Bay serves as an important feeding and breeding ground for many finfish and shellfish; however, many commercially valuable fish species have recently been overexploited in the Palk Bay region, which has significantly reduced marine resources (Balaji et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The present investigation revealed seven different families of fish that were cumulatively assessed at both restoration sites, and the family Terapontidaewas found to be abundant throughout the restoration process (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e). \u003cem\u003eT. jarbua\u003c/em\u003e is not a commercially important species but is used as bait for fishing by the local fishing communities (Balaji et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Assemblages of commercially important fishes such as Scaride, Lethrinidae, and Siganidae were abundant after 3 months of restoration (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ek-l). Fish assemblage observations have also reported that important herbivorous species such as Acanthuridae, Pomacentridae (\u003cem\u003eP. trilineatus\u003c/em\u003e), and Siganidae (\u003cem\u003eS. javus\u003c/em\u003e) were also abundant. These herbivore species contribute to the maintenance of coral-dominated reefs by removing sediment (Goatley and Bellwood \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and controlling turf algae and macroalgae in reef areas (Verges et al., 2012). Long-term monitoring of artificial reef structures and assessing the associated community structures, including fish diversity, will provide a better understanding of reef functions and processes directly linked to increased fish and marine biodiversity (Sala et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Viana et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, the present study provides significant insight into the successful recovery of coral fragments transplanted from the local habitat that can be used to enhance the development of sustainable and small-scale fisheries for coastal communities. Restoration efforts in India are confined to a few studies. As a result, long-term monitoring of transplanted corals of local species in Palk Bay reefs provides a comprehensive insight into the recovery potential of targeted coral species while also improving the structural complexity of the reef through successful growth of coral colonies to the restored sites, resulting in an enhancement of associated macrofaunal communities. Despite several debates on the restoration procedure and the effectiveness of large-scale implementation of this management strategy to recover ecological integrity, scientists claimed that coral restoration is not intended to reduce climate change impacts, but rather as a complementary tool to support natural recovery following disturbances in specific areas. However, in the context of continued coral decline attributed to climate impacts, coral restoration could be considered as a part of an integrated resilience-based management framework. Moreover, this conservation management tool also enriches the live coral cover in the degraded reef of Palk Bay and maintains a repository of local resilient candidate species which in future reduce the pressure of mass mortality of corals, support community-based ecotourism and environmental education.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe restoration of corals has been a promising scientific practice to rebuild degraded and damaged coral reefs in the current climate change scenario. The present study mainly focused on a low-cost transplantation technique to recover the degraded reef in terms of significant growth and survival of targeted coral species by the asexual propagation of coral fragments. Although several restoration projects have been concluded to be successful based on short-term monitoring of growth and survival, the present study underlines the importance of monitoring the growth and survival of targeted coral species for 1.5 years. The NCCR research team is continuing to monitor the restoration sites and improve the data collection on fish assemblage and the seasonal diversity of reef fishes. The study also delivered a successful framework for improving fishery resources by deploying artificial structures and restoring coral reefs in Palk Bay.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project is funded by Ministry of Earth Sciences, Government of India under \u0026ldquo;Coastal Research scheme\u0026quot; implemented by National Centre for Coastal Research (NCCR), Chennai. Authors thank Secretary, MoES for constant encouragement and support to carry out the work. We sincerely thank the Chief Wildlife Warden, Ramanathapuram, Department of Environment and Forest, Government of Tamil Nadu, for providing logistic support and necessary permission to carry out the research work in Marine National Park.\u0026nbsp;Authors also express sincere thanks to the field assistants for their field support. We would also like to thank Editage (www.editage.com) for English language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no declaration of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK.S. \u0026ndash; Conceptualization and design of the study; Data Collection and analysis; Manuscript writing, reviewing and editing; T.S. \u0026ndash;Design the sampling; Assist in Field Survey, Supervision; Manuscript Editing; M.V.R.M \u0026ndash;Supervision, Coordination, Fund acquisition, Manuscript Editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis declaration is not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Ministry of Earth Sciences, New Delhi, India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAiroldi L, Turon X, Perkol-Finkel S, Rius M (2015) Corridors for aliensbut not for natives: effects of marine urban sprawl at a regional scale. 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J Coast Conserv 21:23\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11852-016-0465-5\u003c/span\u003e\u003cspan address=\"10.1007/s11852-016-0465-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Detail Growth (Mean\u0026plusmn;SE) of coral nubbins during the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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hfjwM6xCMwfBT8gSwfz9rTk6R9hTGSnBrrYCj16fsy7kAG6T5WtU/Vy2bPbBk/ylvqvyWkwbF1/zkX8p95ICFSvXPAOByGI9PDL/ErLg9EqGkKyaGT+AZ+3TR10mrQVJcX9U2+1GlaUbO8sSXuHh9ngoY8ohC+4ATkACvopzhvncE59F7DW6hZs35uH5N/ElgjOn5Ad/uI84RYO9R4vm6IFzKngfLXV6pQ9dic+wk3RPw2cWDqUbB6c4e4/H3VlAs8jCSq9PCHgrPIx9PWgF6VuN0d4350d3i3B+hAflEWRh59EdqhsubgbH35pPd6fNHU9DkOXbLu9kNRqZS3kX+DmzDUt8X1Tb7UaVpRu7ygLjxgPs4lS69nEeHnBX2o1qovHgnycF9OFf1v9y2/xB7md6455ezpvAcWl89nIKJO/pb45REcgJ/Qm9fzy95uEe9/RPdSqjJi6/K12mjPgTmgIynmwWfTjfEUDML1MUO0Prgvf04ZmONThYwvE33MqnzddsnHPmJMhuEVrqMZxoxDa6fZ+MarvdmMR9ZEeRg3+4j3hvcb6jPQn55IAPHj18dhEf4JAwMsoN+BbXcJ2TIRevxHZ5Vb69sasS95EEB3zmwkmzeCULuTcB0RQPMPxZOOXoZgaCbbfXFzltDuQqryk4y7F4YwU/r3EuJKJr23vB5dHwnMbdpPf02yO5p7mSlEKe7YhsxxJdfjvgx24v9skv4enfDzvxP+3o+A879sMkyvBDl9HNV6iX5e1JZIHVHfyjOA7bb4XSDG0hSc93MxowGoGQhVHlXZNTRSCLHCSwPXtOT3nZ51YqHnBD8SnGl0QGfoxPvKN4MmsulNfvI3b/FMAF3gy2khlk8afm4hxB/2bDiAiuk6Y40MXQEmmBHu+nYpT76McJ2fcnKRLHqy5zehZcNRziytcSiAFbOJIpZlPFS7LdKkvCen9dF0TKDlHXvg+yUmObgU7UoEqHNgMCLk5vpM0Qg6Y10GLN2NFfR8w+3OhiDOyvs+bPrbdsPnzDmjj7RMfuPambT3BDQZZZtn6ZyILkFuycOFqZLKieTYR2e0lhAu+LarvdqLJ0Y2dZ1vvrYvs89nuv8OJsJv8nPfDZw7/DxvvrBIjIl2Trr9N7+ggvMvoegD95t5/JDXftn7Mf/T1gvb8unB9pf53JIk9A9tfJe5AAF2XrgTgX874J1l/3Hj6xv+5G++u4cNkneOMv4IcrS0t/HaTQtc8QbR3GvC+q7XajytKNXWVp99ctcPdqc9EWa6GvDtmFv70x/cHu8cPZjb7x4V5m5xtuzj/oPc1Rv7J7gTx79Z7GHST3dLyXY6s09PXXfSWdG/hBIjZM80s8pyEpJTPp2JmH8Ih5o0OI07XVe+pF+uv4Asj+OsrC/joJwP46kLG/TqLgxEeDFlC6vVFttxuTuI/sKHLgb/EKbT7YNZ32InitvXMrXLPQd807tgzhacNpvtXOt/lpc315KLaLpw7XPmNfn/R7I+w1OQPC8igJ445CFBeh3V+HNB5xWwqSgdu9/Gi3IwWQViq75Ajc4njUywP+OD2nBXjYUhY95Xe1bDARgCianTbyQHvgx24v1leWUPvrEtb76x71/snfIKVVCB+zYUdyr2iBNPrUX6fvYGq77K9bCCNXR9MDnNrmFA9ivb/O7yMDr2ii3L+uRArJ9828v+7cZGFq1l9X0gJcShsR11iJtcC7YZT76EXCRu54YUlFfG5fEZL2vHsU4Le8BI+pR75V8N1+F1w188eVzB+HgzNCOW08NBcwJVSbR6ccN46LkGW54E7gCLZ84OTz45MDRGQkyiPLqAXYG+KFkwPv4x0DnjGp0vvRMv6Ibt8ePClwP0ax3R9YFm97U+04R9vbumqztrfWHt5Y5mdx8T1sDmPtLZUSTJvmvbNeYtub3PhD21uaCkXb+8Im20ew7Q3cN7NDbXtLRSdnjLOLLDDulwKTKEOH1y7YuYzis5HGAFnwwJrJc85exwxiKtmzMX7owoNMEZ+NM302ltjaXuzZSFAvfKJZv6qBz0ZtMqZnY/zQdaP1FyKWz8YS28qS44cuoxwvRRbKgT/Yy2/4AEoNHIFIqQUleMWftyijaFWLh3/lT3O+3MdekMwMD7nY2FnhiSu2e5cbr5jF+q2XfFZc8Am2Qq9qL92Ygiz+bOQRf3w2yoXy2Sjt6PVn4+zGxsgo8Fycj/ts/I73EJ+NJgv7pQBzETbIjP1S6nvRfGHXea/tIos9l14CTKIMHV67YOcyit8bCZOFyzmlxx9woA3cRdHwJ1LtJ1FRmPN9nkfxeyPFUVlmVBk/INqb7XJlssRvkc3rD9zzBfXuLOh4xkP9Fsn5AfjbWZYcppd9MYosLxJmP6IoFMw5u9Q+8sFXaq5wHdq7vMBXwtbjOT80HUe/p4HzQHGncamyR2kkaapcQUOuXMgr5Rznst61vFriF+4beZOELI+rE7rPF+z0CEvt8Pg+oKL1QocGrmFDrBJPCtyPXW3Xk4/vangMcUV0+ts1HHjTB1xzn3u+CL1Hkcha0HJNTiTOzrLwe8nsO39vRDP8zUkTpFKTTWBY08GAWfaxiY5wMlehOZzb8+ia1xZ8Z5zDvH/s9QsfSi8EJlGGH1AvgvhsTO+N8lcIdqZeXkXM40V/ekqzW3/4baKFbWWJz0YCBzz/ZnwG+uAanTsnYvizMZs7Zx7yWOQP4/zYbXcNL0UWlgJk4UHb2Gf5e6KUEadjlcjfLmE7vB/26mf4CErYDD9TMSl5Z1RYygeQRD5iZffegTbxOCBWEWShYFzfp12Xw5PaD1OQxZPnCf74bFTncfzQwXchPK3g/bWF9mfjgdQo+TX+7ixLfDaSBH98/i2ld/0wysJ+hyMxS02OsGejxDLnSp+Nsz3quhwprb2wiyz2rS+hfm9MiGPa2AsFWViRxGegfUXiNZNSe7nFJXNQm7OvxMMAe7lFU3tnWeKYNvJriiEctuag8k/GtEUfn4NqPo9NOLqXMW3N/OxHb7sV3fjVxUZ8Z8dB/Isdh7BNmI2J/d927Md7O/Zisxw3rU8QndjKmtcX2FvHNmE2JrZ2U6xh412yWY6tlhlMos4Pm3m44RLnwKP1ZSg8LVx8DOcBVRZDXeUbOiR55kj34hxh2RpDgPgymhIDzUUni+sFPse4/OEVquYr7/wFol4eHpujM1aUcg1/MYjL0SvG0/USmg/nrKbp2a0X/uNgAoaIf4qkl0c0QvCwYD3ODZS79NKEC6Fiz424Dble5L8e5U/hepmH5iy84ZiCMojL0SvGE/UygJTnfmwTZmNiL/E+GsCU9XIK27PTHFUv0MtVs8KrdCHdmqjL/C3bsJbW79ZzuBYmXK+VQzvWoX2QcLT1gmaktYMjWnpZNAf2xSKiLccRK/ACO95HrAxbWMvzexutkmG9nDqo7RixllRLL3hucRx5jlIvtyHEbq6IlhygSP1Zilq/dGMPvbTm4XanZWOgDZ1hzuQN0dGRWJlSl15Kjg69lBRdcrQpnqaXw4PmdoYb8qE5Y1LZFU/rgTtsn3LQLa6eQKIUyMOg1dCcrpoFL4tA6W6JodspyQqGRNRLP0fUSy9FlGOIot5HXXhRe7m8IGy3rcznh63uo+8BgeOl+YB8xGvdVTjVt7s53zf50nXLLcTov+VNPDp+QL3g75HT4PnFXw6zMGftSL38HTr68jV8Pze9vHTU51E3ql66kfRye/dPdhbxjqM+CBV1cYfK8O7uYqktRxmpxEnqlhFNK3A45MmNfrxvZAA44xVhwIGAqFN0HiHOmoO77zSq0X3L10mc6Ti7+R3qX8QSCUQvvMQrH21HFw0SPnD5TdELZecVkNuQKibTfCt1vciBg7DjT1LT8LPHSOF6YUt1dq3NVX0TK/XC3i35WvyFRDmSzq15c2Sv1qkMFrgS3uoACLn4GIc8WBhpdpKUa5PZpZiGnoTf42eBq9IjKHvDSCxKQL0sdBQF62uNr9vHvD4U4WgvRyIYL1JQS2aGh943yDblMHYySmpCKm6liHoZgMs8hKSXfmwTZmNitX7pxjPpZYutqrb6Sry+edU6tgmzMbG1j81r2Pj1ebMcW+2aVe+jbnzWevE5CAlRRD1adX0UNEqYHcozYmmDUjQtedQwKOKc4SGAgz07iCgPHnav3jQ/w+PgqmnesneWjz9Nhr8ydG/RPNgQPpwh5ZkeqZeTpVJ/RBqMKT4ikhyhl3BkgnGlTz72JBnyUULIgYDCjtxYKhIVMpG01AsaA0Gf0/zGlPraJBoAyhteksyfxo9QhV4EzCjyzOe0PGcRXpQaw0hEfYTaAxSPzPmddgppYpCGazBQVD0DTvVIe1kYNRfxkiQkAYrEI+0FbQwKhjxQZG8OaOlTDgSM7HqUqFQHE6n3UTeqXrpR++u6sVV/Xb2PuvFZ66XjOa0PkSiqBFg9xoDyZMLD4IZVP6Bp0U9GPiPuGa4KxY0dLYzEeKux+OjCo0ICaBgmpmOn+diSpPl6qLHoBb3c8mmE4HwI66YxEuSsORLhoBfSyyOIL7H6nIZPTAZygEKi4mjjsunj+Ws9pz/Osue0P6hFOE2agqj7jDGRdHxe52WABx/inoGT+ebaYDzGMBoDYiKVK5XK8kloYmDAXW6PUkmRseQa7WWhlD7wUYM0nDKFI+2Fy4ESJxKRySNBiQTJKMdCE5Ck06M+5q/eR92oeulG1Us3ql66UfXSjaQXPI/+zBr6/fIW72ucN6A1PU+yX76MyfudPlXs5RqwtBgKTwLGtfdGnMXRVRpGiZAewvkLnbyzEvzl44Yn+nKo743iJKgXnEk860CWs/RopF7w9MGT7gA/5whizyO4JRrlQIQzBMdBUlMfRpLUCr08NGfn+pymcDEDKSNcbQV60Yd4mDUfRPwZE4x5hsdK0kacMzwSQ3OGeOxvJjQMWj4fuDzmT45F4LdXKoolw99jioJ4jA8sm5sDxvpahE16oeIjNZeliXtAq17gj9LFr+tFJGN/g+nFOJkaIRSSWq6XAWjKG6B5HsY2YTYmVuuXblS9dOO5692g9UZCq95dyKiLwL3OCRnZyfH5XH4A0LTEF3827pNzrJrl1zGzJg9csiyG+r7/jonjXOspeorzC10nPPq9xo+4RC+S6v03zaUO+iRHE74UVtNL+HKNgj9yFDnesNsRETMKBr7/NV25XrjVgL0ffXfNblPr31OuZiYz7XEubxZnR6ytDlGR6VXLMz2Yw8ODAwSScb5836CQgIb5s9TcFzwiDF5XbFBb0otAlzBfIIh8TLwMzeyeIdVeeHElH1mdY4W6XHIjeqGrRYEElULkCPd8MDSHOQUh/bL1PupG7a/rRh1f142t7qPvAajgHgOH9v6BdzcHj3FoHevNC/3+oTUHTrUJ+9z4wfTCf/NT+arFEdDQC39fUV24/BP22F2wlfqZ6eWloz6PulH10o2kl+3G1wW8ompzT4athes4Ss7S4iC5S92ek5AFVj8+cFwbYWHYiYE22ZtraUmxdmWUtPoFEtZBcR5GRAEZx/NRL6E5uUPFc4mr3BRAfNDyRJOMwkEviCCCgVyplIKn+KMcQeVcp7ijd6YX9jNsHF8XXsfVz3R8nZ4RWRmc6Au7ja9DBVv2M3AYHK9egCH2v6C5ySF5AEMeCTtJNIykIWQQi3pZSAy8bQR+ByGk8+QxNlZVKNWEjq9TF/tfkADl6KUw1db7qAtVL92o7wHdqN/tu1Hvo24Uz6M2ooh61Oo6jnLjQwa/eJr8hq6Ylg0xk74MG18HT+u/dnn4sDtA1e8D3ySAhuGvjHj72JzOlU/H18WRfdBLPr7uSh4mcXwdHlmil3Akw/fiEUngTCLx0z7kEAqCKUjWhGL5qKm1ntN43A+Pr0OetPPeP0rcLf8ix1QGMuQNicbxdRwEJynHMPaAzwa+IcDa+DptF/AoKcr4CUpAe0nj64Ks76xZg0h87xJ7ic9p/fNHPSLNVA5GwN8KTSJeNR+k2fpOMgBNeQOSXvqxTZiNidX6pRvPpJc6Dr4LdRx8N+p91I3B57Q+RKKo4uJTQR8n8nzgItb6uLO0+EiRIWHyPNLBYTfNrAhDuhmexWf2oOBFDnXTQLzq8cQHXvCU/3wthF7i+LqmubBlTCUICSkc9JKNr+PrJpLRAX0IBW/IEcfXIYJRyfg6XBVFtJ7TQ+Pr5CmJt2C0kung+/Ccuz5Ja8TLAKlCaMmQja9jeM2yhbkR4Ul+iOsSFGEsiCQmz1P42cg3ybTEYsuJ9mLj60R46faQICAU4WgvNr6OuQ8PEpZ6CZoc5bDxdfiJo/9EL82pPerrfdSFqpduVL10o+qlG1Uv3Uh6wfNoeHydVtcyMICQ90YEObWHV0oLTxN5Fth7o8TTSBZGXnrxeMBT194bxUdbCgwpL8uIF9/HeYCc+sZKvdh7o1xNQfB/wXDUC+j9Ke/JRF7KEfdDg5Pj7CI7JKHAhV6Gx9d93VyAiePnpXNZxtfx0qVctTzf/FJ7Fdh5YOPrEM8ktDBwIWbUi4yvkwnfclESu4VsjMcjIOPrwuzoJ9K1oXoRag7dYwALgiaVPWRJj5MPlEdf2yUZ4XO9XJJCUhC9CAXpSr0MQPWyAWYLg9gmzMbEav3SjaqXbjx3vRu0/kxo17vyrQ11wpK74NsIuqDD1ABNS+K8+6QD3uB8pfFs8xeTR2IexZgMehBWNrBNL4JBzmR8nvqRWa6JXji+TkbTSV3ng+NUKNGLDF3j0D7pBZSoSFAzIXIweVLY+DpWeAylkud62Wp8nczPAXR8HR33xfMIca64IFzznxBIxtcxnlb9FkbH16FivM/G14Hoo1xlYtLvubxmfB8cd/hmbXwdZce1bHCcDu8TvXB8HUhProNTIEHNhMihgl/YED3VS3NkVPU+6sZW/XX/bsdB/P/sOIRtwmxM7M6O/fh/7diLzXJs1V/3GWKr+2gdaCeFRROOL8Ihh4ChcpPBcuEC7TMS4mZAI4q3xAFqoRvUAkvxmN0ELs62OjgNxySYnSEmN6/hIm2vQCB+cJ5/g8hLcEr4cHwWvtATpgja+cEhI5ycggy8QnZ8s+QSeJRvgUA4CSdHB6faufJE7K4XLvfAxKmXFQ4z1JI39ALhCa/gP5rWOEjd+FY8ZPW+wPHGCIeIQRqoCIK6UQYdklT0Qk9kk//4cyOx9Zw5n4ODEfBYEj+QPYbD88B90RE93FyGMz6g8J/N1ydjR71MHvV51I2kF32bzWFTv6Ooao9oIMhblryOdfd7SwT4pn5vm/xtYXI63vxC4ER6Fb+4CYxabx2+DPP4/Hpp93uXeuGbOHAqVQZz3dfvjSxLhlK/t0WxMNKDTbUgFev3Rl1iOtDEeFW0INpTfViP9HPrZQCaqQ3YnNZ2YTYmVvXSjee+j9beG+1FLooqr1x8yVKnzsCKr2oxLblh8MoWXwJ73xsRzWZ06YvajbwFAvzVyVRBXiejn6f87HpZe2/Ud1UTR98b8ZKF9znA3huXqIR49LT4rolXtvDR52V1vzfqjC6EkRe1OasclUQTA5AOXP7Sh5Tz98Yh1PuoG6Po5V9+sRHBjoP4lR2HsE2YjYmd2bEff7djLzbL8b+qvXQiq18o0iuO+MPLyaP1FSn0uOD6uEsJQKfUKw+hWf0zXTGtr1BR2uh31CJ6Fg4PdGldC/NbxkfNyqN8wEBahzeNzgRQ8j99oz1gWi9J/YKg85//APWLtOsgrX4noZA2kSHqBflDHalvi3zhQw3MS/LoADQtXuRiRKvAepdnF/O7sytOcgA8DN6uJSbDSBTUu58sGfydfMs3wbuj5v6O9S7OTiTWNb+l1PqlG7V+6cbz30ctaBcPoEd5VZG2itwU8b2xXI+MFYB0SJ1vem/UlczieyMDSAJ2Fb8yOkpccqPxDpbjD1G/5O+N+lJIqKjxvdGc8b0xjm+2tKSm1LHUg++NCMCYabxUHJ4lIakifi/WaHIMcc/CZ9bLAFS6Ddic1nZhNiZW9dKN576P1uY3cjKhwETlq8+b68PLa3nBlGmDCGK3iKUlceBjcyPj/gE2g1DDyMRDBMzmN3L2dJrfKE7Oi+S2AkDcP0COP0j9Us5vlD5kQAWWt8iL5uZWK18dEoogxTgPicPKBXqxdh1ixhmEUR4q7ZRc2q5jm03qaYKJiVNrFXppu25lx3ofdePl6OUzRNVLN3bTy8nh2YLfF+1zIz+QNV8umnArOwA356E5+VIbG/zciBNUo7I6BZogDMLTG8SVUIiHKFyxQj4s8mMa/sObr6UHMjTs/JtwcMqI9k2SnEz1GH6rSEZyfnvUZJdsA7FpuNoph7vqZXHEb6QU9UoknJ9CHnhID+QyyBso6m5t0C3gIxuHce8wBOHGx/ygyBjyiXHVHFA99NHNrcUbejl4bM4QHoFPyH1h3yQBi41f8tLBiEJBpfFUvkfinTx+1ngK/tb80XYuH8BnuI/7/97GXlgEGzHV5xHaLzerrz5x6uTKOvmjAaqocltL00UaGnw/ahZBfQBNS1pqj2itILS9H2l1wJ8oD5osslAlXo3idzVGSe9HHJ4r8ehNL3gecHIs39B+iHbdqb03ajOs1AvbVwA85Xgj3xl5SYNpWogLcE4P9WLzYH2QjckjyuObdHqf5thZhSYmv0jH9EJ9sFohT23XdaPqpRvPfR+tvTe2+ndlXRy86+nub/reiEv29mdpxX3n8Hwk7L1RFrEBNIzsO4eY7X3nNIr8cic4viXKujr63oh0ZMWaH6R+Kd8b9UXORAVwv/NdL9YzaeUaIqUlb4mIk94brUqNYZBZnRHB+sXqFTg1GfnlTnB4S/T48GQ6fMuu91EPql66UfXSjWevd48g0gFu/rMDeKJ+ka9YhIq6YDc4vzJKm0TOWFeupAqIaWnleSRxz1Af4GK4fogNIgvzB9bUqKQQ9opVz2Fz9V2IyQkBf1DhWeUj9QubmnLth6h377/UevenlCDI/AieyO9X/Cz6ZmWDU3j2oXn/J21vAZbnL6FYUFpcqPJMoud6OWZMeDLjwP03iBJeeRT5+VIq/TQm5oDr734hrmfSS11fqgt1faluFPdR670RL4UKPUq1grdFfXvjmbzpxHX+NC3WHNx1HFUMQsh7Ixzx3UfD8E2z9d7IANo8lMSEAf/lSC944r1RvkD+IPVL+d5Y6kWqSnlblChyxtfEQi+sbWSqquhF3hslV0qhYR6l7mi9NyKAVlQMaZNd0a7j+yfO9L1RZ6w+s14GoJnagM1pbRdmY2JVL914/vuoBbvhXVQas6zTJojrtMlyaICmJXGubrjNKe4WfQtCRL5tARpG6UKxDypYpdaKV5GIrNMmLlsZDk7ih6hf0F6Q+kXfGGN1qaJyRTMAWZQcxHEMUpUAlhbiyNJpONp8e0SPm5VqGH3TpE96bxTdCCQxdaLmktLSeoXbq/FY76NuPJNeKioq9sZ/tw9Je2Ljpyxii0CbP5o9y3e35v8x9eyJraqpLQJtrlOfp1quaunAE9WifSH4QTMisDvE4Slxv6HoH87DqlnGNk4uzsLeqPDGA6JZIvI8aUNFzkoWD6vCoI2BoK+aYw8QKZYyGVlxxl58j+ly9InxVLWIMIHL+8q5+hJJLf/56Eqmgj9IqwhButRCFo5PIMOVLOtjcLVccGxHF4uHRft3+ZZDRtDEzAO4WnR0RDg/lBbio7UrAZejT4wnW8sBdCKCnLAD07yBpJbDEK6ad0iNrwpLvBJ0qeX0nHPLr5g1siSipJYg8+QD27oFi4flGoWL5uIAbe85rq6rpTm7CbQZ+QSGv3W19InxdGtZzTgQRymcplTL2RWH/5zj6pxvEh1qWYInzMKCmyiUREkt8HxcNLdrLB5W13V8nENnfCXpUAstgdNncYmx1tTSK8b3WOUe6MtVjnYgSGxnDldLL9aitLFGYW+4CS051sX4HtXSgS0CfR9qWcNGObZSi/UAf06o1tKFtrXYR/WnY8JquUXFbadPxqTVsoJauIKifLXoh8zCKtGR0rr8a4HWH1btPOnXkBwlraw3XXq1KN7Gue4JpRxpHWxHSy24iT6y23JQKexwbCfUoRb57FxiLZA0Lwusq6UdpOVmflLLiGhToPXaitOSAxStAOtquf+yefOpeR/n1HRCvqGVWFeLfgMr0BGojfU7oF0C62pp+ayrRXqhM6ypxT5MOdpV7nawhQlzrOV4Fif9ZVgLxM/8Jdp5em+LDyaUSrjVQeM5WhS4ei+zlhJKOWTZKd3HN2I3tXRgC0PYKtC6tbTRso11bKbYKEdVSyeqWjqxh1rO0rdHoDOl0KovuwJdlVVzV57KlDrUUnJspuiQo6R4olqWn94um/ndzUkI//Bd8yGT0FPCpZUsq4er4Z8+Lpvle7uSBfrA1w78f79s7q+Xq4sTW8Ii5WktpfB3uxIT7eXYTBHl6KV4qlrQuDpdccHYq74COMHTbnWLRiGu0lrO3unGlIQHOjxobtE2OsJlFlOY+aPN89ROyR9sUS29HJspohy9FLuoZcnG8BXaUDEVolTLCUJSDqrltEctzds3vHxOef5s/q08FSlFdeRq6eTYTJGrpZOiVrmdqGrpxC9Q41SsYyxrmRZGu4mmhR9GLQchyAb+ios4YErBC7BigN87NtYk3wt+KGthg+/wPDzIlGmbOX3erHhXi1rweJWGVuuF/7nwA6pFNiXljO+LW2Re1BLkaySvhyMYFD8ofsZq4U0UGtxW+EGjCpd/wiWo4P+5qeWFo6qlE6OpZWqt3KqWDlS1dKKqpRNVLZ1Iavm09sGslT5nQ1zeadsTaK04Zyl91OFWl7rmQFy6bmYfTCUQOZrlUpYUAGTtAK40IFE1T7Iq3bujfOE6xtL5GHDgklCG60gtQn2rwpECBwrWWqIgfIBkZyKHsyOO9uLKSnqIR4qkltPmJJxcX2hX7LekKj/LWl8cZIe/TQBhCN3S0NRC4ZrzOF9MZ5IwXq4W+054anNQJCh8JIKpRXd6PJJvl77+wINJwIDIQfw0jaMFkbk6EIkUlBFpg9w+GEoych2klEPZqQSmxpYj1UIixC3U0jS/W2lXrCifmc7BOT0c0YBr6+vwRbXg4tG8ORYCJMSLCFioRUZFfGHD73BJg0pUU8u7T1EtvpyfxJIkGaxTLdzZkVdVLSJYa+GG8PpQlhqMatFlI5harhYELNUiQxakK/YYPm21LM0IWBIIrNtQxu/imuPb5hHE80Z3lWx0P0vYaKEWcJx909xwq0hAtog8fM2odIpamkvdzTLMZFbj2ytLWaydJ6IW2YmSsSxI3InSrAWCnYGcggJdm1nOjny3TVXLat1a9oTmeAO2CKRqGYLkcgibKTbKUdXSiaqWTlS1dOIXzd9to7098R92HMQWgf6nHfsR7NiLzRQb5fhrtZYu1JuoE1Utnahq6URVSyeSWsohmsBHeV9LYHOeLemjWzb+5b2Mbxv/KhctJXn9ANdHpZPFGPBf3g0BEwet62XzyBdKcdh7oo4tkTzJ9vNoz2dLMXDNBR4lbGDLnfLoixS8OR+OIvEIihO8JlAw5MEa/5IMeEVCyIGAskQEcmOpMKqs7ID/uVpOTufNI5dCfrB1I0pNyWv4n76ZcSyzvSpyZwl9kbMc61YT0BvzxbcMyIJ4cU8fUwvULVvvyNuUvMP9NugLpKnlTPQOhcJT3gMPwXkrR5EaxDpiemmb/tBHRVK1UPMq2Kns/WPJgFckpBwICHbJjaQiPlI4UGmhlmYW7A1afEQ1GZCOrFdjaoGOWViaelSLRGJ25b1Pl6hgCNWwBqIIElASkJdAvMza6hZ2B5wqL95EvWOBaiEY60ipkR99yTa1QKSWWrj0Bc4tGfBKwqYW6VlAbiQVVQtUwvIp1XJ+rWqRHYWCdhM54Be4vdCdbAwXNyhq7rX7SnMMjxMxo+URwuhOR4wnIsVA0NjF8vqbq7uP+RZFBlHLivHgF+5kL0z+P79/ZaHwc/eJ56CWzRkYhD4UCUdSXIY7CnaBPEBkTwa8FJlyMMLd6RK5ianQ5xxlw/64WuV2oqqlE1Utnahq6UQdO9eNai1dqDdRJ6paOlHV0omqlk4ktay9QcsrXQa6ZnjR4DHuqtjcxKmympK8TJ3x7ULi6sRgbrKoVBJIYqR5umi8M2B8RZE8CQN3fkRyfFvBQWLxlZfB3/JzJSlxAa8aFoTj7egJikR/ZgKKj0TCf8gBCkblkeFAQZ+Yv6SWT3d8R8I70bJZnctLsHzDS8BTS1Ln0RaXltcfuWhqCdd4r31oziyuvuY+2tED8YdSQg57tY3blZtawCBvdb+Dt61RLbHk/ZMn9gb94UIWwI7LWFMxuEoKVYLkwag1wQeRjHIc2drZUMsfGFfFsfzl1sIJJvkbtPWAFEA0wtbERZJxqmzMsQiBXEhcmRgsBSCWoIE0BqSkoBaF78MaxO6AQ9sP8xTJSCcFY2niTOFIKOkOgcu4aD8Gyoowtag6VlFApiZyQDJVC6PyyA0yM7UQpVoa61iQNbJfK6/j/Z+aFRfKtkm6EPqM0thUWVULZDloll/HuLJ2N07jBGHT3ZfcpCmYHiTKJd+DJZCoBQzyddhm++rK3V9aRvGLyELNibxS5BKEJkfhQGHTgM8ohwoIH1lVXCSDHLSJOaULXCecwJnnr1a5nahq6URVSyeqWjpR1dKJqpZOVLV0oqqlE1UtnUhqWR+u3H4n4gIEkEk/c8koYG5PZoN9NSXZr4wjiNVThisjXtwxTQN9C9/lsrEt0mQcMTdISy135UQ8iY8zHviFSlKGIw5XTiOaZawxRcJVUgSl57BpG09NDkSS5CAHI9ALnNlwZUZiakktaPy3hit3QV5D+HJhrxqH2vZOBUAh5Y2OiAvfWzNfA9mXXH074Q+dkUbVosOVNX42Fll1y+DIgSQSRzSLD0VinkjBNyCcktzGU8sbGPe8hTflOOKwapE3H67c4BUBKNRSDlf2zOVgJKg7Dldegi9/VdQif4xxdbgyVaBHCSSjiiUgjwjKAzcOF4hadLiyxs/HIovyGDxXS/axdS4qN7WwQ+A4hDie2tQiyalajoRuXgxXPtHUSrWUw5VbuPklhEckvl7bcGX800y6WuSTuitUhisjHocdExKIo4rPQJIPV7Y3YEDUIsOVJZ72hMSxyKJ0V0s+ohlnkBqX8F/VQsozGTYd1SKSIbmoFnlVJGcarsxIHBdRq9xOVLV0oqqlE1UtnajDlTtRhyt3ot5EnUhqkRZ2joVs+5vAANLO0zZI4IbIy6/FB7CUll83zVef9GjfOfBzaQtTaqB3cHFQAI8Aw4RQNv7hbO5/rcemec/RauFLPUp4TRV/POgZO6/JahTSld2iQIJKIXLI6MeSAoF1e8ukFjTn3uHayeVbyMc8S7Mwgze9oZa0SWCk1Rxr1mZ2RDDIxHjWXJNAbH0CZ3bUbygHzT9qelrU0tREkw9H+9ohmwpKFE0Pv7KlobiEQz7BsXUsFOIqKSS2/FAO2eVeIiYKSZdqzK2FMbSVe3UNGWYzbR46LK/NEYcU6t6sSkmoWtSDvxwkcibfuA4P4iufBtKhj1c8cqyfNv7xl6tFvD4Kk8gF1a6+wXm8Jlhe4/KXzsGtO9hYVQrZyKOkYMJKQTlOEFteBTIK/skbQWEtUK6qRV9zUiNewQiMK4UimQOn+ACZWmIpsMhwH3IPRrvxJNCcZQh96REB+caIfOdqEctEejgypyhEvAeKCakI+sOCNRc4+F4pHy+FQt9SCwokaBRRWI2YKBBYQ9QqtxNVLZ2oY+e6MZa1TAuj3UTTwg+klnzLK4ArZimk7cUpGTzgJ9vn6jnxQ6lFt7ziknMPXH2uCTJiB61MebTfojUZwhWb2Z+XWmTLK6oFP4HLrD1yyblH9eALA5pYcva5qeUMarmlFpay+txClpyDB2+bvzdh/uXrz08tLx1VLZ0YTS1Ta+VWtXSgqqUTVS2dqGrpRFLLVuvOySAM9Zfl3D4+2OpxMSUuHpdGZcSBHOGDOC2QDeSwARRxIIctVcc84bqwexhJEmQyTgT/33EINry46yiPOgpDTvGnFCIYk9F15+RiHGICORCBcnZQMJ9JLesDObS7zEGpZb4+ovr0cOvNijnWBKTfj4gDOdTbAsWBHBYqDuTQo+Qp7S4VmSiKkEEIBkMOZmSayWgM9r4xT5CFwimFCXYaqSQ31t9IORABUTsomEChls3rzs0Og+QqLibAcwZNaqHLR2XEgRzhtViCBooDOWwIiHairjjmgs6oFrCDJA4ToSgkY1EzGHLAQ3grozFSnvKBHBLiiwsdceJqEclMLSz7NQpqoqWWjevOyXAKJGcDOW6bRxuOYWqRdeesmx+IAzmKiTNxIIcNAYkDOWypOs2TDhPxMPBBhhGIfvSR2S66aJznSReNg49SUDAubyfDO8QHlwtrAV8XBXuYa5XbiaqWTlS1dKKqpRO1578b1Vq6UG+iTlS1dKKqpRNVLZ1IaimHPgFd687F1d9s3Tm+Vlzpa4+mJK8fuGDvDbo43AHa3HzfcHHkKt4whEEXhJOWNyF5knXncDlbd46hueKd0GfrzjW/kSBx3TmSgOKEw29wHo9yhlB8mcBrM+RABBn1QQrk3Si4WF05ihvvRJvXnYurv8Ux/xD/MFeLTOn+bWgWup2lJh2apeTH1SJvO1zDjg55VUQAGaZkauGoeREYEtq6c3HFO81HWndumd7zKNJX0AEpqHkKFo96hkjyMks5UA5cDQ8efAsyCqQlqRVq2bzuHCjkN84QQSLsAgFMLYwkEx+kiGLHQvGqKCIgXL4gHAK0153TFRU4oF9SlNCZWoQaqrxb/iXmKXYhRLUwYDzqmUSCZKoWuud3KEh4FmppWcvmded09Tdfd06YNOeaY1l3DhdhNQij686RyrZt1UB4jWXMfEG4GMDUIuvO4UeY9KAr3vEi+LJ152AhDBLXncMpKS7D3RVCX+iRyeDMJAMF5IgUiAZ7c4p7WcmuVrndqGrpRFVLJ6paOlGnQnSiToXoRL2JOlHV0omqlk5UtXQiqWXtDVpf6RL4xspF3LgeXFx3jg1/FVNToh8849ZU8i6E8GiVCySQvdg8cpk4OeOBr+YSSPIks14Qj1f4toL3FMSyZdfh6evOLfCr86ARhIQUDhRp3bmLJsjbifgglJBCjrjuHCKQChT0YSTyJrVste4c39NPcbR15/hK+Qeqy9XCN+hj5lBkktdchs/VcvUdPCAdl4kDJCiXgJMYqhaZnsXVxGVFOJ31gliHMmmd1+IbdMAv86RBQMjESBHLjMrUo6jlSpOjHHiDploQgVTxVREJlu9EfFUcXndOCuRK1oOzaVZ8w+LrFqBqkTh4T9WCRrALFAfC52o51xdd5EpiStAQHrJP82SQeLoinJiXxJLOBwbTdec0q9SHBAGhJGZqETruOy0nEhY5iNYCCq47xwikimqx3JRqGVx3LnzJC7AG9RfloDDoA6havrJF5CyMLA5HSYLejxoovGrO3n9Sk6CT0s4bnQ2nagGDxLMV4XTdOby7S1Jkt3XncNTZf77uHK+C4tbWnZPF7PQm4rpzIZwyAOWgsmQxAaEi4LNibuq6c72oaulEVUsnqlo6UdXSiaqWTlS1dKKqpRNVLZ1Iatm47px83oJMsv4cWvlsGyLIt3w38ZQ4XHnJXYDkzVOGK3NlN8uKBJJtsoWILg365vqQI4sByZMMb2Y8HuGUCPLliCcysthHQiuLHL5le1opbN05ysPR0ZYM+CQZyMERz8wQByknCspGn6QWNP6H152Tljfa6UT8qshXDX2BUrVIAnijsRcc+YrHePbOYrqjIvGKolwSVGZuyo+qhT/2mmFfFfFaZ0Nb6WlfFQn4ZUvT8QMyKfgGhID4bx+OJRk5g3ooh75r8qjDlS1n8GyrZcO6c3zhzNQCJ4OE34tPVAsi4q3f36ApOwKKKwaSFz5XiwTl99ncWmR481yO/rH1nEOLeRF/fIM2tcBpQfjd/RuwmFqYDOSxob2SDPm4P7eqJf7pcGWVhpHW1DK47hzkluG83Js6rjvXIGB+E8lw5cCFSkRoGa4MhwgGRN2JWk0QGa4cZjoawdRy05xJvNgTgjd7yZ3w8IcjFkDNpengsiC3zWLGvgdVCy2L46llhLUlA75vKJmq5fA1pYMSRC1CYeS1yu1GVUsnqlo6UdXSifqxtRP1Y2sn6k3UiaQWa0UndK0717yxrxVwct05tHSLLm6NgwAaRjud8ZP3/Ot6c2h2WUwLk3dxi9/9NzEpLhZ3EFbtdefYpw95oh9XmJMOb6GQDnrEt/5riYoEJRMqB5MnhfiIQLJinjiTWtCc22LdOTTBeIwb8RwhlIYztfAH7TtLLK47d5irRRq5/8h4ElqCSpNQvg5Inujk4D79VCFNfmn7SVTNhvFrk1CTO5CsGYV8gUPSp/hnFExQMiFyWPJIVKh02buZUeXWwkS1ldu/7hzVcpCtO6fLtwGqFonz5+YMTW1A151jvFwtOsJywZi+4NvhG1npBpA8gQGiyIcthIBczA0EliAajkDBHMBA06JxmiehkHXnDtF+vj+LFCKqaI5yqOCg0HXnVEnxw19hLd7417fAmJkI6IFq4Tpytu6cgDRRLRLnsTnTccMoMt5TiJerRdebY2yJaUFRthJI8gQG/F5JfBql2ERQy4ixAOg8Wgs5cIuIv1DIq6QseSd5NwrNhAnLsCw24RKB8KdUtcrtRFVLJ0Zrzv2/dhzEFoHu7NiPf7djLzZTbJRjtObctDDaTTQt7KgWrfINM2me5AjyBIK/1ATneCp68FZIQq7Zw6/Ap8PmkRwdCEftCJmby9itFs3PwiET7khxI3ZXy2GYv8Jh0QRknwcuIvfxGM9mXP5ITUS1yIwDrhN2/qBLqvH0BgScpCMxcRlnxxfmx3wdI/IDnsngC+ffhINTRrQUScvVxxChWUUykq90v0lcPjk6OG0Whwgu9E/FHtaC3C24rgazz4PkmOvpESu0kKiWBdojoha2yziwjIGaCy7AhwwiDxKzOUHhP8qcEPpJcaPZgTiqFgbmUCJLkQKcSIRbLmCn10GOZqZ23KKxDrUcsGnGf0/HPmrh3oySKz3ICoOqFojHUTehYRBkZYkDPOh3cYtXF7gkmhGgARW+pcP8XC3I2BnCw3kSGNFSjAIgpPLSIQnSW9+Y5P/NZTiLTckn4Vmq3Fg/+O1P2XeHTGfaGqLFp+JZ1PLjw2hqmVort6qlA1UtnUhqKbviAB33nKA9ODpQenAUN2BDsmWoNcNbvSeB9GWfrSyJqQ8PfilOHQuKA3ntz3sF4nEYo6plbRS359Eg1f8fDjeP4qbgKrt0QyG87tNtgWQUtwBtGvatwMltwtVX84Rz9hwxybh7+B8OvTtqA0a2lvYo7pZatKx0oPTgKG5ctRELfCtgeN2n2wLpKG4Yi/KrtTSnFkXzBCNTo/IeR6Rjx+dXSzGKW7qRM3AUt4zZVm9RDqQX+4gpyShuKNX6q+Mo7uImklHcHF5tLyuM8v5T0cUNhg/s4ubu4ACHaDMdHIFSqg6MqpY9sTElYotAm/P0PGrBjVCxhmotXag3USeSWloVrFebDgmAP6349AsbJ6Lw62JMSb4qvvZPhENfFX0fLPnl+66cSJ74gZDpWAj9JGjHZ1bL2lfFdk+aPnGCLOVhD2g8YvXroquFP76tlDygGW/9q6I81aNC8Ozno0qiaJ6QBNPR5lx6MEvU51XL2lfFtVdy+vEpLQuVSHNuNruRI6ApyVfFSyhXSn/gq6K2VvyLIDtRVL2aJ15cBX5sRAhtxiFlNZ7nVcvaV0VpveWQ/EMoyO9fFR/j18WYEhQgH/REEf1fFakWzZ9+xkMYbfFpnsQyqSefn4mAJtDzqmVPbEyJ2CLQ5jxVtXTiedTyb78YBX+34yC2CHRmx34EO/ZiM8VGOX5VraUL9SbqRP4kauFjy0ufDmiU4EESl+PT9a8JTUkfVrNDiytr5uFBow+ZGIiXlng4Kb0sx9f8xh5omidZvu/tVbPEEwxPIs5v4Kp6r2RI2HOrpb0cnzWjImQd/sMbWRTPpkKgRXGg02gsJfbFSOeTxpV2y1crXfgOkEDnbCbPf34oR6oAaS3ncQU/yROX74O+Zba9TFJg0jc/WLulXI4vtjYiIJ4svmdqQeNGltDL2y3SGEntFp/dYpYhgWSRegS0xeql+4mL6kn7RfPEzk4xw6gWAsHk7PnVUi7Ht5RORQeX46PEdx/TcnyQWmYzxZR8Ob7lEVu5OFuK07Jiuls1F8trvPGs2MqV5fhgemJolqfwXuPdhVMmxf9cXc+nWQ1jVLXsiY0pEVsE2pyn51FLbbd0oLZbOlFvok5UtXQifxK1ER+uBj4o5AmJ52r6qqjHmJKcc7kmjTz0VfHGYsrzTQJk3VACJIb/sWOBSzz9AA/ota+K1nhx8Cl7ENAEQ2Mi+6poUppa+JTlck2qh4GvivDRmNKcQwBbikrzxEsf8PyHTuyr4ox7x0jRWIL9GNlaWl8V2WIoIGWl+yGlr4pxPnRMSdpkHGZODHxV5CB7iSnWIgFSc46Gw2T4Z52WSMrM7PnVUnxVbEO/KrpYsAuxengTmpJ8VVx+HW+U/q+KDGAxbW0oW4pK8oRi+cBPilzLCcBbAlR2U78qDuF51ALrrFhDtZYu1JuoE/kD2k4iFnf6vdBBeTgCW+XiQiUIouuBxJQkDncv1DBxoZKYFQkkGx5yh0RwAV0LlcCJONe6lAjOEJ1LiGjKxtWPUdWCJ1G5UIk20xIoFJ8o7Cuz/hYJIs/VqBb5hVr0RPpbkEMuBUKoWuS0OTQ/6W+R75fyI3mSM4CPde9vebDjs6ulta+idiVFSI8du464Foj1zkkQFTOmxDiulrhQCZcCISwQY5T7KrYWKpF9JQS+KwSk+8HUUixU8rUXmgGt1dlhkLVAbKESBCn3VYQHhHe1xIVKinaLbHiIf7awStdCJXDKKiSHr6WhG5cQoZ0+t1r2xMaUiC0Cbc5TVUsnflRqmRaqWjpR1dKJ3dQSHmKjTqF9C37baxeA9k7oz6OPOOuoGWTyXvuxR6A1eN4Rnphr71WO3I2rx2cfzx9OTtfDbYMd1RKam3DFxBfNlwtOiOMsu/NXobmQvpQvoRnubWyy3uCRvWQvTpjdQEVoARychmPOUpydBTzyoZZwy7lr59+gEcB4nLUItSAJCY88hi/0RK808wOZK3lyKr1DSnZ8gyY4+wKZ7COe6QcPnMX3jGqZ/5JfBW0yHrJzy7lxEErV0rw5DeGB2eNURRoC2mw6kXAlkysZh0ERCmdUy6NMYoQPg1EtzM2yeTjT8M3NsZzofEZQMl3Js/GSDNdCkBYSkqVa+PHuWdXCfzPIFdUCJVFAyMC3GHqFM5SbTFWUhmx4q77IAY4cWqdq4QxNCh5kLiLzJlGiWuQqf24ktp4zwBwcZOfER/og6qNMkKRa5AL/64EiPBHPUuW6YPHkvPyM+1Qwv9sjvkc8Bb9o/noxCt7bcRBbBPq/7diP7+zYi80UG+X441jWUlu5nZiqWtbvV33TdzAAF666/7U62Ul1Lj6EpSRrVmltB8TB7VyKipBA2muBPwliB3dKnmSdKwZTPx3U/sP0/J+2B7frIlIJ/HQlXR548qYls6wTxFISTaaR6nFwe/xAYuIgYyv80wzKowJR8rmKXOeK8cgUB7c/3tgOmc+rlvXB7S21aJ6RCxn2E5fMimJqSpJHHamOMGlwu2UlibO8RlBZq0q7oebN7J760zyFe2rVnv86uH0Oa/khhv3k3VDamG+rhUZAoXDsWzJL1MIA+hUxDm6PQWMgAnYkJ2iF4ZcjBsWZ5Qk0omAzUjxoazdUP6paOvE8asHNW7GGai1dqDdRJ5Ja1r4q2mc+h25/sNSjflWUZ68Gs5S4/QEEt7gD2x8s9esiHjayL8FdjCJ5Ek5EkvhyJn6asnH1Y1S1rH1VlGdoBjYr+Izm0b4qmg+hKYnI8g1RBqbEr4qt5pw+va0hKA9m8ZEokqdTJMDLjG+fzyQdoX92tbS+KmrxJUgjAsrA0b4qol1q3wZdLYjIb4jcZCB9VYxZ0UBsNkqLVnylOcegGkXy9O6TqoXxTS2SjijOuPoxulqKr4rS6ZhjaZsQQF1p+wP7NmgpyfYH0INsMoAc9G9/oF8XAfmqePg6RtE8XSLeW7SUYWX2VZHpqESRrBejqmVPbEyJ2CLQ5jxVtXSiqqUTVS2dqGrpxPOqRR5+JaQrycH2Bwekc4NgG9zOR4PuK2wppb4IiSuD23mGZzQhgawNg2iSQXmmy5lEkTzFjY+5YbJ1LEh68qh+XrVsvfExRbbB7eH6Ie4rbGqRKWQhxpVuKMTrHtxOImu3hD8c5oPbpbOTS3OJWqQbiqE43F1OhjGytWy38bGpRQe3I8/S8kspMQ6LXeJKpyXQObjdTEushTscaxTJE1u3sjSXqEXMC61qsZUfQi3F4Pa+jY9NDzK4nae5tcQlsyyuDG7nRsK5tfjgdnu3YJTjVTG4PW58HILcWDK4HcnrClotsdYxqlr2xMaUiC0Cbc7T86hFel0qWqjW0oV6E3UiqcVq0gzaY+CQAKgu9dueflVcfh23wtGU4pJZeH4T8qDFT+TWQLJkFnzMkwcEsH1/JE9S/SKeVcPxq+LLWDJLmhUJbJHgsZwvmcXM22PT1MIfNMbsi2T8qqiPZwvE5hGeLHgcSwblAY0A1hKUPMVddHhMXxVfxpJZa8nDj424bMksZqlQS1wyCyQIo18VDw+49JVAAsmHt9ZXRQSQqJanuIsOjgghzTl+VVSjW5OrjbGtBSagamndPgboQbIEM7GvimtqkXYpG2Na9vJVUXbDUcuTQLoRT+urIgNIj53kSTo7EU87Lc0ibyyl51XLntiYErFFoM15qmrpxPOope6r2IG6r2In6k3UifxJ1II1JBIgDwctsf0Sl8xiT4o8SCwljfMbPMjlsSJLZsWggAZiSh+bU4upS2bRKbA8MUxoHvEQw5NIp1fxzZ54brW0lsyyNawcD/C7xT9Or4yT8vjszTsWJM5yzhWx6NTRUKH5rWVFAulSWR5TP59xBx2JonmSR7hOUpPPZ1oUX4lenl0t7SWztHQM8zuRG5cgZvzYShFVzJgS4twt/yJNV3KqzuLcQwnkcxQ1jI6CQltNnZonCc5gXLld2ytiMYSmN4DR1VIumaXFlwDBz+9f4RpbubpkFtrmdx/loqaEOGiTztGI/YatXASTT4rlOxGXzArLI8T0JbNgefO71JcL55Ij5TjAH3H5X9QoNM+rlj2xMSVii0Cb81TV0onnUUtFRUVFRcUPi/8xSs/Cxrf9bfEff7WTffHXrbo6NuJ/7p+zMSj2z8wI+vgrWvCjtOc2trG2xd/Gakn9YqsG5kb8ZP+cjUGxf2ZG0AconsdabFEA7iQzjK2tRafH92NL7Wyi2aqoh0mez1qG1LuVPoYz8r1ayzzrmTBrWbLXbRZWzcHHnkUl1q3lJPx+1TQH4aqMcCK9QbfhtFl8aQPVCnRqJ/ym3VuyiWatqGWV9laxDJOsW4uNghIo1Ulozn/GfhnuwrMuRttalg/8NL240fE/jiH1dujjqdp4BmuBNqiKcNQE6d9tmivJ4xOs5RCChzO1FkTDiRui9UxtaS2Lh2YBfUAk0MBxJcoB+mnWreUCcbk19RmluN1Clh5rOQlfkgQWAhKFDT3cxlpQC1AOsRbkh//NBHvUu66PJ2vj+7eWGW8CFX4p0tD0o08HOq3lgF/wYSTIHKOFB9WS3ATEltYyD4SoFjS3n4IMDBmm6bCW5uoxXJzA/A94C9zAg+gn6bEW9tjiBNEPNOqB3U5bWQujI/WzAy6Ww1WJf6+p9Kp3TR9P18b3ai3/oDfd+7D6WXP++IbrVTM3BDQDdBROt7XIyA5Yy2wZfo6zman1VklE7eKRo8Na7KY7nIWPqO6g8deimEGaLmsBxz81s3tR74mVzgBJj7XgFuZI0vAHG547JEaHtTTUJ+J/Fb5bQKRb2A7Qr941fTxdG9+rteyEbVq5XnMPocNaShzfh0+be8PXi/rJGINiU2ZmNOJBbNDHNtr4cVrLVthoLdvhR2ItmzGCPqq1bEK1loRqLZtQrSWh31puP92hGXVib2UbUa2lH5+DtaB9HA5hLSfhmi2osEJDeY5zfb1qYwuFLFf2+jCIzdZyEu5azf1ObKGd8PF6492wqagvV9exv6UPwxTv+DKzKU/D1iIUB+FOlzjpwbA+hKIJ334YknXAWkL4E3IBbc5+d70S49HXs+4S32wtCzCcby7lreqWgy3MbrO1bGHhG62FknB3oiFsoNDFc4dZNtQtpDjYYPgb9CEUEGFIigFrkToE1nJ71pyvUKs0zb80y7dN81/kchvDCiEoznwka5GJNRuwnbVsJNpUtxyH8HZDkK2s5WQw0BbWQmifSze2sJZZOHw9VFH2W8sTsVHrVMemm5DYbC2XP9HJfhuw2Vpub5pf2seIfmyylp9Qx3begy2sZWP1tLmoLw/jHMZubGEtUEiz0F7yTjyjtWyJ2srtwktv5T4R1Vr6Ua2ljWot/ajW0sZTFbLse9Y/yVqGuoOepJ1ecZ5S1H0kY1Bsn5k+iifoY4Di+a3lCg2p3uLZ3lqQ5CjWMijOtkU9RDIGxXaZGaLYUh8bKL5Ha1meyovh4lQuh0OOzMKbuQh02sw6O03WrYWxlmfs2WB3zflDjAtOI+wkWtfORnGuOnoe20W9A8kYFK3M7EDR1sduFN+ntRw2B3hFvT2VF8TlEasCSCMCwXw743RYC2Lh/Q7y3yLiyWOMi/9GiCTWO3I6rGWzOOuv5mtF/XSSMSjaRf10ijVr2YniOayFQ6K+S4W7XLlAaxiyluZ14DJEFvdNODPCS3Y7tzFgLX3izJayylGB3qLenmQMir6i3p6i11qeRPHDtHJ78aRW7hDWrWUntIt6B4xBsX9mRtBHtZZNqNaSMJq1VHwGqNZSsT0+Q2vpmpliQ6C7LgE93p8fPjNr0dkd5ijBeQQbzKKYaqCO3imXk8Rnai3hxqYaqoP+0VrUhbM5AiEKzuhNcDDYqbiWN2468eLngM/WWmyqoTp6rKWxuZH0NhyE09uVnFVrmTyStdhUQ3PQf+k1jU7eo7XMZG5kNIjXS0ZpfrqUzkCEp/UAmwcETgSfYSu3YmfAWr7j7VFRsQX+z0h1i1XW+6P25Xah9vx3o1pLF6q1dKNaSxeqtXSjWksXqrV0o1pLF16stXB4zAbcvuVcpQK5QhaHdkLoBZ3TxB+OllRXDBaKGYy5tXCsnIGBOMhr/khXF9FsxcE9CS3tuICI45NAZacJXOGUTvyqd5Yq4EVNb50LqNmXIWdESULgJNeBUlgsl1KTcXfJIpmTxDSLai1R71FjGtwV0UlBt6Sg+mjJzumjOPe8CYUXbxJWpeiylk93d0ccsQkcrPJRsRe4aKZkdAkpeVzEu1ZUFmWYXS91z0EmuYTHXIpFg81W5XzX3FpCuNZFtiwQguvgvy6iqJWI0lpszqeKwj41kYjKOWEsja/enqrAreUKftGQmP2r8N0fJFpJwiOu5jqIFKq0KGVMJrOWjOVYlvFyzcW6RYo6asyCuyI6KZoP7HoEoj4K2VmgCOV5E2uJkgIinEvRZS00CBl295GC8QyRcRZVRThdRNSpIU5rV5sEn7jpIMuVyi/BoNW4LbKgsBb7ywJRnG4i17uhsJYoB6CicPSyKkfuMxc/DmpWF1A8RjgEkWD2ee/yb40kphV10Gct9pdZS2KhdEJu4ubW4sqw4K6ILgoRQty5tbjsulKh5Ery1mktgEoxZC3Nffgyt5bmp4HbRDMIk5AzR+78KoQvVVm3UpqvYzzBm7CCXB+4vB6DAb11S/OefeyqdQZ6Hz5ZcREtIlkAIhlFYS0qB4KqKLbAYMQ9axSkEr0l1Qi3luOl5AIklv3jsMrGrUYSS8szByiFxjIpwaLJtKR2lkuJ75qzJxED84TKIIUEN0VEtCi+iHlVfRSyk0KKzvJm0DBUCE+i0oAOa9kNkokxUFu5XXixrdzdUK2lH9Va2qjW0o9qLW1Ua+nHlKzlX/7tFyMg2HFv/P1XdrIvfvV3O9kPZ/vnbAyK/TMzgj5+9b9q3TKMWrckgKJayyCqtSRUa9mEai0J1Vo2oVpLQoe1sCcv6xLtwhf34dd2GpErhN9I2CEsfZHs0dQuR8OxrJMgZ9qD+KbosC+sJfYxSu/iRStdJ9L0+JVHen0NmXYsOiHLCTSX4ZO4FOpHvFP/fBx/KurUZaoRvuomsWCJ1Cn4QSdJHTNjaRokDBCDmTtaizqjxozCtGxoCxJ1GPUhFEl2LZsyLy6Fervau6xFev5v3q007MnNZXjLZRqyjALav51QWEvsh2YH9fKIvdD8a3/esY8uh+Xnndxa4mcZwr7w6seqkkjTa68uXN5LFh2/8t1Nv6e0vqzoNyh+6NDAArcWfneRj0spQheJBktuQCn+Ub6+FF+3oMSYpn6h0TCABXO3Wos5c42BQrWM8y5Bkg5VH86osqeySXlJYQD1tuLushbch7L0C1B8Vbz67vp6SXUBOnAgg5IqZs1sqZ9+Lle03OXqOgSZS4Fai/nST8fhUMuw31piCDnH30kIH6UOKYksvUPcTXQaSmuxK7Nwz29oS96NrJKA9NX26s/I6hmDZjxuLSfh+l4q3RQhHK2TaLDsU3CiYBkkqVWJmqaxWBjAg5k71i3qTBqTchAt9wjCc9Vh1Icx2kd5KRtzr0kBaDAr7i5roUHQRnBSWIt+EyW8CBNaPkpP89ZYejtR11dwyy1KQcRyB6zFQvDUNK/EJRFg2TEVCAprsehyGymjBJVbCW69vUiidVeWG7cWwqJqBO44RpQkBBy5O7eWJLUq0dMUFg0DeDBzd1uLUriWuwWJOiysJcpOsGyKvMRkorcXd4e17IZIuDdqK7cLL7aVuxuqtfSjWksb1Vr6Ua2ljWot/ajW0ka1ln5Ua2mjWks/qrW0Ua2lH9Va2qjW0o9qLW1Ua+lHtZY2qrX0Y8rWwrmK/2TnPViGZVsBhdt3zp0F6aMudtL1jX7vAERr7SpbWItHDN8ucVKm2yZq7SCcayelITvZXjKC933Pw519Mtdgy1WeSipqlUHAAOWmvG0Sk0lgFLqJrkt5Ga71s1MPiyQWFWDW0toN2PRRalCTATQl15npwy57qup+E66zT7hO0Sq/LmuhuCd/DkE3gj55j+RuV1Tu8tsPXhz+hcaQiZufyxcNd1M5/lWDsE9eeeTcWtyfkfQLjqbbRVS4gcxa8jTsE4h+2eNnEfmqIldTsOwLu1tLkgGB1FM/yPSRxE9bTsGkk5SLt/KF5vxMJ9+VLJaYRXRridLHr2cS0FMsP/JkKeEs6UMux1QBuucxv63vRK3y67UWKlM2gk5fFWWUiCTcNF+kW1PhjADPze2piVsKmcKZpPyi3d5Vtm0tSvQufPo9Y1u6XUS5m8isJU9DFWHTW6WIXCEebKlGIUh1S5SBEdRTNxruIzFVtazFpbz9pkH1Abc6SxZLjOfiLq3FZqkD1Ien2LKWmJLpLLcWT9XcYrb06LUWSXHIWmDb57m1UMZjCfINvGJiBpcf0J1z5UaR1HwnXeoaLLwzOKlS7tT2rrK5tTgRkr2EHJ5uF5G5HZm1WBoykVMUEQOKcpa4yW+YigVDMWZwazEZfDaobzTcSRKrISK3FpcaZWzxk7UkFktMFQDk1mLCQxDVR0wxL2pQWEqus9xaAKbqCoEwM3n6lBTt8uuwlt1gCtkftZXbhRfbyt0N1Vr6Ua2ljWot/ajW0ka1ln5MyVrq6soV26KurrwBtW5JAEW1lkFUa0mo1rIJ1VoSqrVsQrWWhGotm1CtJaHDWqTnfwNkSd4Cuds7vdPqvPp5i/48855+OIreeqBlLRoxEsV0SyJNr02UaUeCaoc3TuSrCT/FWUc3ztRF8KTInRc1U9Fvs5qep1+SWFpbrK5crnMsLL6ucSSPoqi1+GVNinFl2p2ttlxSWEoIo6FVH/FyXKBZ5fS8lRQA4+YUa9ayeXVl/Or1hNydLU9sqrGphNTt2tROX+hXUVqLRTQiT7ck0vTaRPm9dKyzNwU8+52FpHKKSahUWZk7t5a0urKm5+m3SDQtzhKNwkQKLYNoLeou1mg2P8DIXZRYt9hlTmUEEPE48BNeZi0eRlNKgkV98LJHMTl7V1dmSgVFZ93Cb4m9qytnS/I6Mv3KublVNWqZWshk0Xmu6s27iH8RhbXEiEqU0i2JNL02UWYt6eN9mtIpn4ipHLm7LR25nT0VQfEY0TEgGsHTL0lSWvJZjhiyFpe6LCclT6IU1pK0IgUlgaLZAkahKSXBcmvxKITJKXlrUUhKBUWvtTS9qysDEjtD4Y6LItvqvJKcwxdFNu9ykeLCWjREIgIyKifS9NpEmbXYQsMISh7Qlcs0+3rEPqwlS8WtJa2ubOmlFTqI1qLGm1dXVncptfqRxck1eXsSyeVz/p6SwrNhFQXhFFFncTkU1YelqlFAoXL2rK5sKeUUtZU7iKJu2Q1jUOyfmRH0Ua1lE6q1JFRr2YRqLQnVWjahWksCKP7414sREOy4N/79j3ayL/7473ayH/5l/5yNQbF/ZkbQxx//d61bhlHrlgRQVGsZRLWWhA5rkf6WYeTd2oZcIcXlxWlzEtg1CbDH5IB9DhJgrr1CgE54UeTW4iHmP5NVSd3dRcQwzgjk2okTWwj2ZkS3dEZxYk/sqSrEFRRFrYJ+dAJxlyTs+QxHzfJVWtm1gwIhuBplFLmTAqCsAreWdG1QCruUS+H6mD9CcXKmwXukIMDMZKhuos9aTpDa/BWJT8KXDbuEHqRrUItncX3dtpdCIdll7QC2vkGe89Q67L+yHigNY8itxUMA/ALh7h4i6xBXZNZy/tvYv6Q9fu6mfqRvNfbdFuIK8qJ2QU3b6m6RLP/EKSbz8PPI2UHB+MqhIndSeDJAqlviNWBACsthLoXrg+ElTgreKUVkTjOjeq0FxcDOwM6ef8Kt3pAphIiXrfxyawG99owzCv+KMi6txf6AJbtZ3d1NhN+smDNr8clVAAMWk61EVI3eEleQFXUm6DmVau6ShJ4LmTfmHfTdFOwdB0TkTgqXCnBr8WvEgBSaQ5y7FJk+rJCznHdIEZntkyExZC3n4bqwliZ8ularC5/an4myjMXLTEU/Cl7ehU93cZnbJqw4uRalz0m/yLd/OFQUTyIJAaLzcHd3h9qO7j6iK/yi2nTk2kF4yE+LU3sSd1weFuTwbYnLE0Eqar0KkrBakkbcayQn4dv3iMJ1aGMd0EUhsqrIfRS57acnkdFvkCLmOJPC9XG+uucq2aDQ4D1SmLDQxV1cVbzDWnaDK2Rf1FZuF15MK7fuZjWIuptVwmi7WVV8BhjtSVTxGaBaS8J5aIptJYD2uiOfOT4vazkJv8eLwkG46mt25hsTEYW13OYXzbH4MlvZafL43KzlEIUbzmAtNBjYApxqIfiV/3N9bcU57OGAIfiiSS/pfzoVx/ImmU61lqkC1nIQwiNNJVoLe2uaBQcV6v+TcGZO/FoIsxbgIJzewhuo1jJ5wFpk9S+ayrvwJbu4xFpmy/BzsRa2W8KNOhliwXW6PrKrCni9lD3ofrqUUblL6Z+UPi1e/CxQW7kV2wPWUlfkqNgWdUWODag9/wmjPYmqtfSjWksb1Vr6Ua2ljWot/ajW0ka1ln5M2Vq2GJebL9lgyBXi43I5Po0hhxbSaG8Rn1tLMVqPFENEMbGITDvFJelDsXOOFiOxDzCDgxd1IJBAi1pznJJUSUoe10oKxrOSAtDEPJmh5TQ8w2oternQGNLx5IYpVB9+WUtsOyliRrqsZfOKHJDOknRoeAW7rNRgdHUKRNLLzFJ7IQ0OhYvDu4jcWrKlPWQg2SCRJebI76XWihzFMhhpwQkeQYpzXVJdECsG5jglqZIML6dh5VBSADY0UpOZDS2nkTIc6xZeThqbXS9x4skNU0R92GX9wrGVFJ6RLmuJIy17V+QAnC7CFBIhwztt6OzwQhqEDFo3FNZifwBvnmGiNE5XkVlLdklW5OC5uKkcqSCyVAhm2pAXtSdpkhQ8gGklBos1VmEtqRqTZISor6h7VuTgMWoMN7NLNUxRWkvMKbBJiiTzkLX0r8jhyzok5E5d5YEGo6tTANnl1kIas3vpT3cU7Za4tEfnWhntFTk8MUVmLe0VOXA75Yt3yPD4lEq5XIc9RjTHKUmVZHA5DX9O5RRPXE4jZtieRHLZNAaK11ogvnoH0Uuh+tDLltMtpfCMdFjLboiEe6O2crvwYlu5u6FaSz+qtbRRraUf1VraqNbSjylZS50hMog6QyThV2PNEKl1Sz/qk6iNai39qNbSRrWWflRraaNaSz+mbC3syZMuwH58cR9+bacRuUL4nUh7pq2X8X3eXXscOMOfXZ0Ez4ph84W1pFV/34VPOTHRJnrd25crnZPsvewO6uJF7zTIPy9q7zK17F9SJEebJK0Y4xT8oONSJyUW2ZcwgAWLCojWIpezhNtuokURBYn64GV+alqpUzLrCjJEClsrKOaty1qk5//m3ar5ilKc3FyGt82S3J5RwLviDZl+0zdofs1YnKYPMTTC9HkH4NeKg8es07m0Ft8s377bOHEXEVk8l0B5L6XPM3nQ8jtR9F4ceeDMWjQz5mDisW+/i4T9//wTKMU/yteXQmoqMWZfvtBoGMCCuQLUWvyy9cW33F0USRDVh17OPmPHzKqCSormkN+JUt66rAVmdmTFU3xVvPru+jouE5R90ldokopZM1uKBk7C9X0404+8/4nmi1qLxaHfcUUf3BRf1WXIrSUcxkz8GUKcKXFcv6VN1Fyuio/ZpbW4fCmorViSfYNWBgTNcuPWopnRM1koZslKpI+EK6fEmJGCZZBLTSVq9o3FwgAWzBUQ6xa5LAkrkruPwgWJ+pDLh6gpxYVfP1mjoC0ju563LmuRugUZwklhLfYVF0g3qqPlk6wJF/BfzZu6lsWN1ObOo9Z6rQXpCjHp9HZW4i4inicRW9aiBQmUQeVWcvESQ5YbtxbCzy1/8tm/j8SrkNxaktSuxKxu0TCABXMFFNYC2HiD0t1JwTMRpLAWIFJopkxBJQWEFEuJeeuwlt0Qs743aiu3Cy+2lbsbqrX0o1pLG9Va+lGtpY1qLf2YkrXUr4qDqF8VE+pXxU2odUsCKKq1DKJaS0K1lk2o1pJQrWUTqrUkVGvZhGotCR3WwrmK/2TnPViGZVsBuXtxd3ennx+XK/3UmQePfjyF90m46/0GnYjCtx8Qlgv6S1+2oEXUzLjsf0KunTfhWj/QXa5kq4Lw7dK+OgAZ6wlFuQzX2Uf4VNQqg0DSc1Iikai3JSQwinfS1+5SL1fC0iNK9DbNmbUIRdKYUajYEZqMB3NK04ddTlGEItMl0KJowsdrEabLWsh98ucQTqC1i+bkPUzjdsXv2ctvPzilfoFI0Ewpim/Q/GYS7DLLIPoB0Vs/QhgKa4lE/KaiE7s0SjeRTqyLyKxlHr/YkGGm0xrlsxM/iyTW5vyM32y4Q0+MkFmLyiCQ9Jy0JFFvS0gRKfj1JZMaMlz0iRK9o4pi3WIfcJxaPmOr2OsfeRgsUUZ9yOUYxVJwqdYoGN8T67UW2tLsd9fFzFZ+oORF4It8NAThjAr96sZE5zcsRL0shSx+OEneXDjQ0XoSKdEsHL4O8vlco3QT9VoLC1+L6DiEtwj7Lnz6vReRs4KRhLffNNnt7taiMuDE0nPSksS8LSFBYS1RamBJEbpFUW9LCSitxWapA6QwsZUC0DAAgyXK3Fo8iqVAP/FYsxaWDaNHil5rgW2f59bCxI8lyDfwshxHCJvha+TiglaJGHYX6C+1Yn4+O/TyJ9Aszw25tTjRLVJbnDVL3PWSbheRacaRWQsKeobKFUF/wnPm4lLsQZSjrHITUmUSIEnk1mIyeHpG2iYxb01IkVtLklo3peoRxb1Nc7m1mEqdAlizFhFEXK6z3FoARvG8eEGVFFY2yPkvRbUd1rIbVLQRUFu5XXixrdzdUK2lH9Va2qjW0o9qLW1Ua+nHlKylrq5csS3q6sobUOuWBFBUaxlEtZaEai2bUK0loVrLJlRrSajWsgnVWhI6rEV6/jcgrtibkLv9Y6CtzqvzxgAe+WlloR7CIt/OtDNakFuLR7RICK5ztkqi4uOjo6UdvaQLB/uqwdLR7azWVw7IOqkKL2pJTwTV9NzdRcJfm6EWKTTpJLVnTuOVLEZOt7Cotfiyx5ZRpegRJJNXgqk+lCLNbI2U+erKTkHgxJPtspbNqyvj19kMuZszJK0AJa++SDKlTlM7leUK5644ILcWj6iR0hTLksjT0w8ihtJa3CA145m1JFZfLDnPTaoYjuNUVUsvujtJ8N8/NkUKJp2k9syp1CVLJP9gX29j3WLFZhltLSvdSaErMANRH6TIl7Sme5avrpxR4CgJWrJd1hK/KvaurpxW7E2ImjHAuPQoKdufFDJZZEBAxpKGibSsxf4skty260QE00v3g6CwFqvNAM14Zi2JlXej3JGpZsmspRhrgPSKr/zrJKpDQW4tSWqLEaUuWZRctCjuwlo8oxq8R5AkL2/40lrkiOtyhFuKguKWFLioerM4Q9bSv7oyYGyO3O2rK8cFfnX1Y0NrheK06IaiaLf46sq2Gka2zEVGpOnZusWO3Fp8MWEZdeFyGXx1ZV0smRdFv4JUt/gSzZqeuSNaJPkSzUqhSWfZl8y1pHYWJf8iLj1tTyKhSAs0m2J7BFHv17HQVB+mAF+g2aTCzSuGpXAK1ZuH6bCW3eA63Re1lduFF9vK3Q3VWvpRraWNai39qNbSRrWWfkzJWuo86EHUedAJdR70JtS6JQEU1VoGUa0locNatLt2EN7VnpArJF1e/it7weax94JdHAfs7rAAK8SaP2p3UERuLYlIuyQ400e6vEoiC6aJOXLteI/GSZDO1JgmO6MSq/WHf8zC50XtnuGIHRGefifJ8pWtHgoU1hI7xaQ/I4pcUhAI5moD3FrY0ar9q3q5JyvmnReU66PQOKSY/4xzOwChUA0B9CZFJlWftZxANfNXJD4JXzbsEnqQ/k8rnuvrTAxBoZB0Wftyv7KVZlnI7BbUru+TB8Zi5yb/IgpriUTnv2WHkZLRpySKwayD1pBZi0ZXMJqnSf0k1oPV9T/jYL2ZBi9qJ+FV/Hn6nSTz8HPVFZBbi2dV0zCRSwqAwVxtQKpbln+yeSF6uScr5p0XlOvDowCW0/TxAWDGFCerUqpea4Ea2OPZ2fNP8M7IkSmEiJc1MfvTQga9dEjPV3d34U7kyKuz1pNIiXRKl5yvExFyyVRvyKzFZoQJoi4kTVGxsxJ6658nJi/qnITq8PQ7SXDuHfSZtaQvWepnIrcpJBjPnSJmhle0Oz5d7smKalX8iEwfSeMxsFRXbWtZIscF5ZC1nIfrwlqa8Mnm9oZP7c9ESUZAL/PD5N19uEMlFe7CWVzmtgkrzlemJBLrfHWf1mwGcmtJRGK4kOguHK0TmTiamCPXjkZH0Mu78OnO0ozLwworU7nSab9htdS6XpCK2kkQjOvlSvp9JFymNlZniQJ1NcC8awoi8hqFBRO18QRIT6Lw7XuEAIVe7smKaTUvKNeHXXMpKPFHp1ANkSLc3UGfSqnosJbd4ArZF7WV24UX08qt/S2DqP0tCaP1t1R8BhjtSVTxGeAZrUWbUUftpTyAW2uJdVwCZjrCDCd3cVMXx/F9HDmDBh8TKIbKEN2cA8h3mykRxRR8UKmKETWbccLmse3H0IseCd7pTuXvZXuZ3DHfv1m0JZ61brlitsLFB2r9pyG8hePoHg6oBwW9sku/RCiUcThdvv3pku8VVuAHVjCyU5GEF+hxwbcj/M0YWEKcP76mcdEtI5N4Em7OV69hXyLB8TJJEOlmyxXLKhfOwgG4cv74xsxz+SCEZ3xrEX679Fr6SHQsVEEjmAcI6ilQHyxqldclOw+vw18QWLznK18GBuFPZ1DCib3JuIOZfxb8ENZCDTGDC9oHHVDfjFpXF0PhzGoUnqm18H4OZ9TQQTiS8ATe+eSAMLQW/FgIlomkgHNa2jwcgpm+CIvDLcwDUsCBNI2OBolLhXAWDsAViS5dJssH8N4i/pnx66UDVh7mU9AocLJ4yFK4wdVMXpWMZ4uVeUNsi4vIN2IcBxQ2dzDCs+CHspZb6ubBHMhtZi1wHeBMtCFVAv5HwCC0XK14z6FSAYuQ1vIGCoyXcMYUGJQ6v8VjUBQLPhxEmJim0fGwaAln4QBEkuhmLbhCF+xX+P3SFQpafAoaBU+Wd57CSbiHLWraSbIouXh7VKtENUjpSCJ+z5hKK5dKK7Huo8U8QcBongdTsZaK5wCspa7IUbEt6oocG1B7/hNGexJVa+nHlK1li7W4m7hYc0KuEF9C21eNthWlBbusxX2JE7TlylWy22txgyonyrXjy2br6tVGZ/DVqk2UnrW4UySNcBDu7lJvYZvE3cCkrYWZ3LQWdxoxY8gVko/YsvERepllkA1Lid4+BIMorCUj4sAjjuOS8uokSutLCzLt+LLZhM6/03FUa4NC6PBUBHlRaySL4DPPu0gK9/SthaoYWIt70FoAHaEBXEKtONfLUsiIKaWavDevxQ2BqH5fJbuLCO4+a8kHMskC2DY1WAuaKUQJKErPWtweKYsgVWwXSeH+LKzltnct7g3W4ktop3W29ZcFBRYO7+MsXvHeai1uiYKfuHBBFxHQZy2IaGtx2yhFG2Coo8V8AWwVJaUiSEWtkUCiES4Pm9fi00WSlsAGpmwtu2F/hRhqK7cL1Vq6Ua2lC9VaulGtpQvVWrpRraUL1Vq6Ua2lCy/WWuJUkwFwNp+8iiTkCvFuEpsFh9cR7eRgnPYUw3zuIpFbixPZDD2fRdhFtNVcxTT/TyYOyetMNhvv6jf6HiPdJYqiqCWS5afob8lmCWqee+cq7oaXbS0n0G//XEVgGfVvKHSazZDDayTfPPXtk4Us3SSiVw2W3IrCWpwoztCzV98uIuv0cGTaSXMVff6fTqVLXSXiuTzUd/D4gk3kRa2RLD8+s7FFInlu+uYq7ogXbi0ohoG5iux6KdHySDendGDJ5DUrZND7lD8EK9xA60mkRNS/ztDTWYRdRFZkjkw7qXeOYvLP+kKkoBlVxA93d0sZ45hnJitq70CJ+UkVVCIhkGecd81V3BUv31qG5irmn0gEuUJ8iqHOgtO5fb1TDNXtyK3FiWyGnswi3Guuok7w0x7i9TmCuECDUAM3pKLWbmWmJ7nSSYlrJJbn7rmKO6O2crtRW7ldeDHW8j/+/mEEBDvujf/4q53si7/+h53sh/+5f87GoNg/MyPo46+PtW4ZRq1bEkBRrWUQ1VoSOqyFAxPS208nvrgPv7bTiFwhbPnF5qYMUEpr7QDHwVfg4Lh8Nlr1BUNRWIsv1K2RynQTkQRrExXakZlcxHud7+huwvwIipuLnxf1a1/y2iJ4hwrhJJdKnZFO2lrknejm3ar5ivk+ubkMb9HEh2dWzuXSP0BhLbGjAe+0eMng26W+CDMOI9pgo8URrUW6TBJya/H1/1MkTbck0mBtokw7fK9TIMGTx+Tmy690rqj4Im4mPuFFzUuyyFaMoHvfr5GoA/9ldwVi6nXLkemTo1pwpm/QV99dX2un3EngS2KBXCGzZrZklcIxa6JjvE2G+OKbbaKhsQ7LicG5teC9WDstLJKk20GkwVpEmXau/ow8iJnNAqeZqtteftOWGSauiy9IRX250irSI9Ba1kiapVRBmpBi+nULigEnhbXkfWhpcJyhpRC/TPUDWgmwwKSjzZ9Tdsg6OAprQboSJEVS4pLIgxVEmXYYSSol60RzN6sFCqFVH2DiZrnzok69gTFCVrcUJBDDElJM2Vp2w/4KMdRWbheqtXSjWksXXoy11LmKFduizlXcgFq3JICiWssgqrUkdFjLNnMVi8mHgtztUwxtOh+cd+l6e4ph+PZDHjm3FidCIE7xGSbCC7a+0Shy7fhcRWMo0symFQrDMuS586JOcxV1MmM5ybJNUucqprmKcZZhQu727q3UYaZ9D3xpTS+iysKekjxyYS2RiJG0X66faNu5imDwNFtDU5xB38wFeVHbqC2fzGiv9/hrk3w2b9De39I7V5H9DG0FtNypw0K6QGyknRQyO9VYJsYyC4evvR8LaD2JjOhd+PR7xh4ggrvPWli2sbeIDJ6mFDRTEPGd4QutQwRZUdtcRZ/MaGPCukiSG/gsrAU3c+9cRddERO5OcxVtOp9WC1rIYOEt6VMMb1E+af/d0lqcCMlesnyGiIA+a4F12FxFZfA0pWPNpxkCZPgGFxNRKmqtST6ccTSwzGkU3x6SOldxCPsrxFBbuV2o1tKNai1dqNbSjWotXajW0o1qLV2o1tKNai1deLHWIu9EwyjHCwkKhcxv1GmvDfiVN0p5leGbrL4DpW6ZPHJuLR5ithKC27d8bQa6iULfO1ExUArxytcZiice7t0sOt6g01V9MyvnKjoJgZPcPWlr+XR3d2RdCXgjZCfD8oxn51ChmhKHALUMJlcIAqnzKnz3Bwb8YP0X1HIaxGQsv5MgjsJaUjpqbtLJAnQR4R2/11oQII71ZAdOlEsKOg1kcu88N17U2dVwHR4SaUnC41Hpnnzdwl6Wq4/Sy4Iz7W+JnR0C7VlIyBQyhxq1lHn7t7dDJIv2hALGkk+TbT2JYjrr1tImklTj/Q60tGPds3LDq1w4YUFLnSHiRe+sZsmK2iNJYPUV0pIEnhAsd38e1tLchy9za+HGFzqm+isfz+xoKQROlvOxbIzyxX0a0cxvNpyJ/OHMWGa634YjtxYNASJOsg1n2pts19aIgN7eORUAQe1xonJFyCDzJC4TMRsFUlHrVXbxveduIUYa4SS6QEA+cn3K1rIb9leIobZyu/BirKWOhqrYFmONhqr4DDDak6jiM8AzWgveONma/WUxodBxq/tB5ciGDQBv1lvWaVdFAI1gvklrMzxDybIFeiP4Bo+CZ99Y0XJ7LNvvFY5iENj3iWe0lpNALc3DVfCtE3XHwXd8t4GG8P8YuhdncxneMsTbqLqF2phscngFq7AyctPj3nMjbKyoyWqEuImiz4KlQL5J4g+xsSJk5MZ9siVg5uDOfM+CZ7WWw8XjLBxBRdQSVR/3kFNTOQ9mEjjnmYYwa+EsZN/kkBvNCdL7NItOtLjXxoqarEWQoDfGZmloaOIH2FiRuWUeF2TLHc9VuTyvtSCLNzQVqEO2ThQ1Lh9MQ/gfHs0Je7AQohrBiVgaYdbiuyoCVBiVt9/GippsuVOiXiFUILcW1nHwfK6NFTW3cqPdlA5GexZMppVLXZdY95GynCDM7r9/TMZaKp4BsJY//vViBAQ77o1//6Od7Is//rud7Id/2T9nY1Dsn5kR9PHH/z1S3TJaZVh7/rtQvxN1o1pLF172N+hhnAQOLimQKyQNc9LuLLxT6tsLG/kHfAGxACvEai/plFtLWme9taZ6SaTpccn0XIqWdnTEAt42bvGKoqurg5U/7ZXb80XXs6KePyI9OYv5M5k6STQhxeSt5QTFO7Ryu40zScgV4guu++LmpmYWMmPqIKYTvCRmYQy5tfg66+011UsiTy9ODxOU2tHBOYyuFDrZhwUtI2c0X5pKvuh6VtRkUBZLL8rURZISAqZvLSiGgZXbh60F0CqA0Hu6Y8H1+eruLtyJgm2kkqCwFvtbW1O9ICIkvWXR7VBox2eCIVsqGm5+K2i681RwngZNlkXt9S4iuUydJIAl9JlYS//K7Zd34dMdTxJyhRQrt6OYehZcZ0jouph83noS4Rqnp8s5A7GI14k0vXOUU9/K7To/lkF90fWP8lkJYETwplTyRdezoj5f3XORRk8PQOg+Ek1IMWVr2Q37K8RQW7ldqNbSjWotXajW0o1qLV2o1tKNai1dqNbSjWotXXix1rJF7xxQzLkBcoWkKYbq626++MqEHX0XlymN3ithyK0le2eP8xA1akmUegNzrpZ27JKk2TPNMHUUmoCEFzWFkddui+DplyQpP/56P2lr2TxXEWgrIHf7FEOb3udu6jZNMQQXYqUpgIrcWnRSIID3d1rL7Hqpr7YlUUovlg9RakfL2dLsmWZo3p6KwIuaXbVivhbB0y9JPD+2qhUw+bqFvSwDcxXbNQs0ZUeD9FbJ3aV3mLpJQBaZYmhTGlMYRWEt9gezAcQytLu2ICLIX9QsLe3E2kyIxLKkR5AFLZWBR9WOwqxTuChqWerQInj6JUnMTybNZ2Et/XMVqfKkT0GuEJ9iaNP7yqmNPsUQYKxy3mDZbpFJgWpprFteF6O0W3MVzylVrPqAXDv6ycbT7JlmaN5lKl7UtvsNSXQeoqYf0ZrwmD9gp2wtu2F/hRhqK7cLL8Za6lzFim1RV27fgFq3JICiWssgqrUkdFjLFiu3l2ubC3J3WnDdFld/Z++vgrTgevh4zcZ0ueB6bi1OZKuml+luIMq101q5PS3CTqRF1jVYz8rt+XLvEmCW73qeSDSYru6umLS1yDvR8Mrt8U0zIVeI95b5EBQbDkP1pWEpFqW14HphLdk7h3atWLrbEGXaaa/cDigdX37llUsoUrAsd17UfCW2c1u43lYgKkksmK/uDkzfWqjMvpXbgXxtc0FLIdo1RSOREsytJfpJlEB3r7UAsY/LekAs3W2IMu2w3NSwYPKSA6OTgmYKIr4H61y53Zd7lzGE9MmtxUksWFzdnfgsrOW2d+X2b+CVFwyQK+RrlIksuI4Y2u/AkgVYyOb34Yzrp/9S9N1rLU5kNJ7uNkSZdlCCxcrtRqcFnRZdt2Bl7ryobbl377QprCWRaDCOGD6OMadsLbthf4UYaiu3C9VaulGtpQsvxlr+5d9+MQKCHffG339lJ/viV3+3k/1wtn/OxqDYPzMj6ONX/6vWLcOodUsCKKq1DKJaS0KHtcg70SZwlmGB3J2PTuLLAd4z9CMwXyfMD7CZiMt/1VcLQ24tTsThI2DxOZJdRO1Jj7l2/Nu0itIzV9EY8l6erKhNBkDTc3dJAnd7wuPkrWV4riLeqgetJc4dlC6RB76u6isrC1n96IozEe1F1FBYSyRqln+65SCB/FW8TdSe9Jhp5/y3ttZxEqVrrqIxpFSJVNRRhih4dJckHRMep28tKIbeuYrZLENHSyHSt5l1t3J4jBWy+zEK//qtBVAilq0MaMqtZY1I/SIy7eS9cyZKqhYkBRdfGTRVgRe1y2Dpubsk6Zjw+FlYS/9cRaCtgNztcxVtOqHM21ufYqgzEZu7+5BPMcytxYlOwrfvQSdzJPuI2pMec+0gPOTnNMOhuYpxamWciijwojYZPD11981VzCc8TtladsP+CjHUVm4XXoy11LWhBlHXhkqoa0NtQq1bEkBRrWUQ1VoSOqyFAxOk6d8PNu2yhilRKiQu0qTD4svgx4ELW+grF5qHzWVc6lqRW0seUVqw7/Ox+m2itGi2oNBOvPTFffg1DmWakVWGZOD1yUb3K7yo41UnKcf8D5BM2lrknejm3ar5ijo9ubkMb9HEh2csnlb/laBQyOJInXwdxZ8HpxEW04D0jTSOHxAU1uLpHDzyRQPhZJpXJxFf3nJk2iku5WMW+PIrZ1ECvvXqKLuIvKj9nZgklrktSKZetxyZfjmqxd+gr767vtaxRLNmtsxfVoFcIThX50m4vkc9JcHji2+aYmiFvSy3e8itxdOZ47UVJ7NwHw77iK7+HK1PkWknXToJsgiPpGkvv2maIY96nsyiKGo7VRLN3DYk069bUAw4KazF+7eING9T0VJIcuqZBmeBSaeW2Bz7hxXaoa5otVs8HVhL6gLrImJI70AEMu0Ul4wxddqDMfbGSXnjSlbbZUUdrQGIJPzZSDJla9kN+yvEUFu5XajW0o1qLV14MdZS5ypWbIv/Y2ZTUVFRUVFRUVFRMSV8Z5+j98If/7ud7I1RxCFGIhqBZjoUTRM+jIC//d1O9sYo4hAjEY1AMx2KkfrVxuniI0br5huJaASaKVGMwFKtZRBTohiBpVrLIKZEMQLLFtai44h8K+x+bC1OtsZKJ7YkGoVmmGQEDW9HMajecTIyQl56rIVfFmLqeoLscFnbVdPMlsV0joR1cZYyMO6kPaIPTiZwypFwXXno8jvgdvMlnkozZ6j2zuTDJGs+/8DAdm5UYDi+5+rAHOcnPgVaXlAG9amaSRhU7zrrk7UBn3XPHdBtLXH8CqDWoksy3UKaxZfbW8sDpV/cICc5ZGDWDKo5+Li+rTzQ5Xe1ymUSPJUG1nKxZi3DJGs+82ykjIVfnjUfcf7AIlxnaFOchN9Dkwehtcv8oHrXWZ+sDfise+6AAWvBDcBUPgVf1O9KTPoJ1rJAzHBkdn94Dl27moR0q2ImwgUj8g9FTsGeTjMPCMaQ28uy5mPWIoOFz8NrbsOogxJZLXSK0fI6Cf8ZOrx6RNKsTB5E1XpD9qq3Q66naoMh7XQv9FsLE13eUIB5rPdUqidYi9SwrCUBZIz/7aa4Es8u/Xbl64DjNE9NP3D4bPon0ECWcIaQtyR5mNGEN8my5qPWsuRSfgj/cBxVceAaa6PldRIOESecqaEiAk68wupR7xrr07XBkHa6F3rbLacycPWRJUzRiKVm6wnWAr3Q4M6an+IOuGgWq0h1oiXVpd+ufF3h1kUMu5vCWyhd/J9CA2u5WiHkEvffYoXDbKMsaz7cnGLFeAfhiOHBI9By7hKj5QXBr4LMxWUNhWhQSCTpU+8a69O1wZB2uhf665ZbzQTkOVG18rEqPk+wFpjcEazlgOs9cB7y7zUUH7BEl3678kXDhWpVP7OwtCkMT6KBtTThN2Ytj4hjsQZI1nykGtDR6HiWubUstPLtEqPlhYJF9EfmBHEZITxIhTCg3jVWSf9J2mBIO90L/dYyRwm/humGw4WkNLdcPcla5EUknMHe3sBaQKZx9V7c2lpOWBrgmIfTW9a9wRaKeBINreUKMc7Dq2NkZWY74QyRrPnoQ0MVcc77wG5mLecuMVperAb4joiShtVyrWc0X+RKv3rbrDtoAz7rnjug01p0dgeeHngxDEdWQ8rsLNtHme421j257izXK4AevgrfcWukW70JbdqZ3KTrprdOxLsI/g+ovL9cXlDjMk3qaTS0FmmNvtGZLUst4yGSNUnUWmSLnOb8Eb90DorRoqDsl/BDjvCu/HOcxYXB+9XblmIHbSBGm2UndFrLTthGHK2lNmBTmCuujqsqHsII6nkOioNYp/RimGIrbYBihLw8s7XM+DTaiI1EaB6mCay9GEE9z0HBV7RhbAiwjTZAMUJenrtu2QojEY1AMyWKEViqtQxiShQjsDR1UtLngZGspdYtA5gSxQgs1VoGMSWKEViqtQxiShSDLOXKN/2o1jKAKVF0s8zCHRs11VpGoJkSRTcLV1O+uqnWMpKS98WLoehmobWcP9Balh+5BDXXmkZVk+3DWWALa0m7mg5ic6Y6doztwuYwvpPrEDbRhG99/8Q+DFJof/tyNZynLSjSTrnd2IIi32i2C6DoZoG1cACGanNxqqHO+UWvs8S3sBYwZMu59WKLIBBo00cRYCNRtlzYADYE4gJl+o2zH0MUs1Xc5oCfS3uxBUXH0pEFtqBAkHLThRZwvZtlFsIKlkpr+b+ul6esauwD547WkhaNG8YWQcR8N2IjUbHvby820FCSfLW7LgxTxPLRTXl6sAXFPtYSKbJtibsAim4WNQ9aS3iF+kTvw361bLaWYtXHAQxniphdL+N+C0PYSHQVvvvDZoE20HBTonGsZTDUFhQcpDCUm22k+DD8vRYU3SxuLbQT1CfhbfO64RYZusdvG1vULWItej6ELYKs70bdhY1EvI2KdTo7sYnmXfj0+zGsZTlIshVFWgC0C1tQ5JtYdwEU3SypbnkTPl6hur3nB+2f9n3W3mwtUjsNSyzYIggqKpVuEBuJaCn7Wwuwqak8TKFFPdhq2Y4CxyG1bKbY2FjAtWGWLbFFK1f3196IzeLgMdTeu7wLG4lss/AN2ECDqvZyr3civ6sHsQUFbuPlhkbHAEhRbHneBVwbZtkSW1gLaqdRmhvN661GMW1BdCwN+Q3YQFPsCdCDIQoZ2KgTpXatGIziq3JN8zVsQfHFfb6PwjpAsUEd22Eba9kOo4hDjEQ0As2UKEZgqdYyiClRjMBSrWUQU6IYgaVayyCmRDECS7WWQUyJYgSWai2DmBLFCCxPt5ZiN7ICTxJnqF/sKUT94jyBppdkShTbswzgSdaCFPuLZ2txrs5GspZBcbalGSKZEsWWLMOo1vJjKOptsIFiS5ZhdFrLyfuwDLcrfgLUEUzLD3Rch+t/OvnYN6Rp3Xf54VN4K8E5oOpGaZt/uP/u2ghPwvXfLWyGNaLN4iy/fb82FKJFswvJlChaLLuh21pWSPKMH6vkA94Dl8vi10qkyEvd46rWxUEsfvy2IVnh0OJK3SKE/Oi5jjWizeLgdw0tml1IpkTRYtkN3daCGk038ETa/G7FB4emyEss7nWsi4NY/OZ1q0OyFrKfLOLGJ1FoZsXGzBFrRJvFeRfeWtiEFs0uJFOiaLHshk3WgpI96RCoA+viIBYyg0zJoIflurXw+6CELLDmtY04t7jPSrRodiGZEkWLZTdssBY+SVDTdQi0hnVxEEuthYMe3uiew4jLClQJ/9yZiTWvjeIcnDZvW/pZo9mFZEoULZbdsMFaOMrARvkiuTfhTAWycAXWxUEssxbd/j/GXa6McBaXTCuwRrRZnEtd3rhAi2YXkilRtFh2Q6e17IRRxCFGIhqBZkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOi4JDMioptMIrNVXweqNZSsT2qtVRsj2otFdvjM7QWfqNvIW6A0HGJ6PH+/PA5WYvslBCOuq1lFv5po7VwQZJTPdXwOPRtDzlJfF51i2yb0W0S3MRsQyUiQSLM0bs95CTxOVrLJ9lSiPXMYRP+QAfqFrhWdomhYDe4dGOB1Ihm4SMP3LjsRsMT1VqmCrWWG1qHbotoDnkSsW4RV7SWcHjI4DizKucy0F7gOrHwRLWWqSI+iea+LaI63FrEFa0FZqD7OOK/4V14lG2ewlG1lsmjbS2yOeiAtdg+jvgfsZDNM4FqLZNHZi22LWJ0iLe5dKNBmsGJ7uPIS8DJ1w334kV7ZfZBwxPVWqaKXyZraXRbRHXQWt6wFaOXZKNBMQPdxzEaBlrEXE/nfVj9TMPbW7lc/ByAnH4+ma3YE9VaKrZHtZaK7UFrqajYEiPVLXWk5QCmRDECS7WWQUyJYgSWai2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTImixTILd3d3dt4H3Q82R24tB2DQbW7AdBeaE1mJMsI3+vVgXD8xIXdkW/BKoGI33TWid+XWVBmRygGYKOVmuMuVDbE173LjX6e5XF3bvoWW/fDxOknjJJpW0gGgFBbLpbRkCqmdRffaTZorKFxjGrzcOrlFAZ190NAFRZL9hCmkvBGpeEW4QgpLOYKLBW1A2pXWUVhL0mEj632xQPl7xR+cqSsGm98UEmSObAteCcQF0kS3nUS3bxd91gKoHADj+PamHP/GK7pjsHpnqRLRRW/dt9CyT2kEJYk6Ch0IRYwVpbRk3F2y4KLq2DZFzilcYxacYcWji0LckkJO4bLDe36T5Y3+qXhduCSFnjjUWpa3n8502/B8tdrraMORztFrLWqyB0LKQpYzSTIGC6UEmSPbglcC+W663USmlYiCNe0Wy3iFtZCVOo3erY1/Iw3jRUOS7Dt/SQIgrXVrsVgupSeTWUsmStxrVzVXUkSNafCkiC4KlrOGzinsHDg/g7WkvJHCJQWitbgUKaaAT6K/cCVVAmkv89VqY8WT6Azlkyj4nnhisb+zjXRZyCciLJ0W7NZ2Jo/IHGkLXg3ku+l2EnnWDAVr3M1URfHNcEm2RKy5FK56tzb+dRr4xaUzVeO4eSRaSaJp5TqIFKY0k9KTyawlY9G9dqPmCgrXmAZPiuikOI5j+zplR4HCWlLeSOGSAiJcLoWxRFjdwsvcNpxnjMz1R4FtrIWID2MQEJeSiFQJIixdRDiiu5Agc/gWvDFQ3E23iwg/A9ZicgAqSlbxMhY1JoB3a+Nfp4Ha35rD0xZ3mySm5Q2SPJZL6cmYu2TxvXZN3IwiKiMGT4roopiFw9da1rkUPBc3gjO0540ULilgwiUp9MSRrCVw2/DcWuS6INEZ2tbCChGw551pkIUsLM60OOVcLrvRFVkqVKYoNAskZtxFxB/NmiEjSnIAWphat1I5rK201gfg7akqchou9kiUGm+ReFqmA6cwpZmUnoy5C5b0dDFxM4qkDA2eFNFFQSE0N7kUHkW4JFeaN1K4pEBUqUthLBFuLZQC7RS3Fq5W2/wXCZPRGXJruTxsXiPuB6RM2ZvLn1g1x0K2jX6RFwsGFBJkDtuCl0Ti77vp9hD1W4vIwaAqim+GS2+ZSibiqndr41+n+QmvaCFI9m9vml+KGkoSy7NnDrATUxqlBIsnk1mLszAlCOqaa1HQCQoL7lsnd1FwgWRv9RKZ7JIXqVs0b4CE1DCidgpXSGEsEalu0W3Dk7U078OdUNp+sDlya5npPrFIjXLD/T58kngK2eiX6vLtZAsJcoduwZuspdxNt0XEOe155Oxc5WBQFaXcDPeNLPyOVMy73PjXaTQqSSz77/P1ZJ3E8pzvlas+GkulZDlpMqXUzqJ77SbN5RTqJIUGL7dOblHgIWJ5LShEdlKotRQlZGFAocIVUiRZ90D7SbQ7RhGHGIloBJopUYzAUq1lEFOiGIGlWssgpkQxAku1lkFMiWIElmotg5gSxQgs1VoGMSWKEViqtQxiShQjsFRrGcSUKMKHEfC3v9vJ3hhFHGIkohFopkMBa/nFCPjjv9nJ3hhFHGIkohFopkMxSg1Vn0SDmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTIliBJZqLYOYEkWLRUZl2nkfvgqf7CwitxbOpZERnxzvyaGhNnzUoH7EO6XhFJiEIm0LITLhwmWRbiSy9DgbKI6yJxJRjA68llGqX9yHX4tTcByCjcONA3+zibgZjQ9/1Qh9JBosuZ3ijQzB9uybEsvBxhoGsGDRXVC4xowiaRRoCxJ1WFAk2bVsyrx4qubtxQ2KpA6BjuIexPxnstZ5jsJabB4FcvWKCc8fUV50ylB9TqHTAFq2J6HfWvLSP1hJuiJdSWTp+QREQymhjljmTK1w1HDfGKHmkOgDjpKXuHPL+tVvuqwF8W5looBFIIkMqS5JNFhy00t+l//KMnCpTYkxTR1tr2EAC+bunMI1ZhSqZaBLkKTDnMJlt7Ip8pJSVe9U3PjVE4eN+Z+F09kyvOXZctW85Rls2Ae5a/EndFsLAqF8OKVF5taU04Bscs4/9k/siNN3BDrNIZldItrKWjQ6x7erqmUehyjHZ+DoXCXwPer0LUWkobmpyaUIaj0FiQVLYQClOOTUiSQ1QIelaeUkYYAYLLpzikJjDIj/Ml+xU5Ckw5wCUNm9bLK8pDCAeos8QqEnDrMW/NKyjnh2BVuBvS5gwzHtEwmVUFjL6vqf9Wwefo54zAD/pJBFEDH+899aVdlrLR4CMHl14kxJZOktrq8LeynyZdGb5Z9uhdHclIrJ61zQ8JVUy8vDLmthDI2VIuicrILEgqUwgFFQ4iQ1QCVamlZOej0LZu6cAkgaI4VqGegSJOmwpDDZvWyyvKQwgHpbcYPCWCL4kH+MJp/PVWzC9fV1NBKYUYGilXuIp6GczMI98nESru/Dme6BGdKs3as/I28xgwmZOB6C57TxJVsda0SW3qyZLbNSLvMV7/PLFXV3wk3M2NwBzljXmLUgq4HT2busBbfNtTZ+PAKq8XUSDZbcgFFQjZnUOCKQpBlZvJw8WCy3jAJIGiOFaLlPkKTDkkJn9lrZqHtNCsCCWXGDwlgi0uyzd4jaM7NVZ/plKKwF0NoNMaB+gpPXtEogvfixAPOpnYYsFQ8BRG+RuyQiND3xi8iI3MGqSXV3LmrgKaOmuZ+hCXd3y/AXugU5jeomRjixSyUJgGCF28JRjbnUokRNExCpYjl5sFhuGQXgGosUquUuQZIOC4ooO8GyyfOSUo3esbjhyuIRbi08KesWuU4sLHZC21qkUDPVyC8LmWdaqDRbqQR7rcVDIMN+n0ZrSUSEGr/dCYqMyKMnXWpQkosFwV9I9JborFsAraEsgt0HbRI6Lkq3BZQywLlJrUr0NMtyisEyN2HOqDGhSFruEiTpMKdw2QmmFd2lFObtxQ1nHhFwa2nCt/d53YKG8fW9aP0ct99dlEiRW8uVriUEg2Rl+A3eY+7xUmcPEEaGhmi0cCGty7vwKV+LKhdHQ9Cy1UgQ9eM6kaXHDVetihcURIyOoCfhW65JE1bLcOQVb1hxLSSkwkWWRF2d1iKJq+ASAWLffbdOosHMrVCKu/sApbnUpkRJ01k0DFg0mLlbFKqxRCFa7hckdmfkFCK7UEjZtPLiUmgwS0YplGVPtOuW3TGKOMRIRCPQTIliBJZqLYOYEsUILNVaBjElihFYqrUMYkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkQxAku1lkFMiUJ78CoqNmMUm6t1yyCmRDECS7WWQUyJYgSWai2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTImixbLFDr/llr2CwlrSFrm6fW2xZa7vR3uJdMJFYxvROnJxPKLuQNuzVbARlRvdFkQpDd28FhF0x19B77a6Ag+X7YIru+IuZWvSiBaJyaTQYJp0kjJuvdvNoom5AnKK5cqimKSlBn17Xk2p2J4XiJdjquYudit2inb5IY5Fi9Ax/5tQTDEAcmtJE490h1h3+8QOD4ATuqNwhF/LIvJEp3Ro1F4idwPZOS9J9LR5rc4ToZJ55vOz9HLOE0+TDPCzSQEarYckCSAnljQvi1tiQDtxu96CxRJzBRQUgM/ZIBf+q7/E9DD0lmiWG/mNl2Oq5rZ5OG2KVvmRws8VNkNkeIffbCaPIreWfItc0Ud0r00a46Q63Yg2IRPHIzKSyqzpdhEVbiI7z9JwXcrNQuVw9o3ajgdL+kk0SQbdFZfQiTs9JD5VMVIw6SSllTP+9HLBYoklTWYUhM5OBhjQU9QitzBZSjxrUaRtlcUdHSUFUJQfg3lIxTY7/PqWr47cWvItcpmau1nIa1M7bSNaRyZOIsIvt/br3iqYx6PSTeT5SmmYIqyWYC6zSagxGKdwRTiNySBKoLXMrpc6wbiHRDInMAomnUl5zE+6aVZfyaKJZQrgTypGc5o+YopFUceUhjcJNnexW3FKplV+jBOjGdLss4EdfvGstBNDYS2QXe8zSy26pUoQ4XgJGSKb72VryIgTETSrO9B2bxVMotwtyM6zNEwROhlclCO3j6QSg/HucPi5y4AIGv4LLaUekqgqp2DSScqZbL1Lt14uWTSxpICMArB7GaA+PHdFUaeUhjYJzsKJR0EBFOXHIDGaIVlL6N/h19UdkVsLmZVdU3M3C1lYjImP6FRhGrLznCguLSHpdhHlbkE6z9NQRdijXJTDZzYV4sHiRUXuUBlkpIecqUV0klgrRmAUTDpJqU+dtF1vwUIgsaSAjAJRYxBgeZpypylaUWf60LLKKPJtlSW4hy0ogKL8GMRYItxamBzaKW4taYfftOWro2zlpo15mZq5tZDTxryaHy5NU5Bl54lId6Dt2SpYidJGt4ZEZGmIWlURsVXHA2oSEvieuMrmcFe2w69UAHgMLSS9LpKCxU4laZe6vfVuwWKJ4c82G84pUJfwNO5XHFMsihoUmtKGTYIjZb5bcaJolR/jGEtEqlv6d/gtNoQV5NYC8WxjXtu+ttwyV9YToaDaVPsi3wsXyMVxIk2wZ6vg2OZLi70IMiJNA0HlaRp34Y1o7Yl7zjCp5vSgmrhoWKzldSiWACtJUjsUEApLOkldbr2rcBbLqWsup+DvSnKjoQoNWhhQaEobNgmO7ny34kTRLj+cC8u+KKxlL4wiDjES0Qg0U6IYgaVayyCmRDECS7WWQUyJYgSWai2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGwB6aiYhuMYnO1bhnElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkQxAku1lkFMiWIElmotg5gSxQgs1VoGMSWKEViqtQxiShQjsFRrGcSUKEZgqdYyiClRtFi2mNnK4cb5eGmgsJbWzNZilmea2hm9i0mVhThZRJ1iWaSb5ohaegNEce6nzfPsmZSK5GTCa5E7D5hmtmp65Uza1szWA2jRB8sqhc0XtZy4u3tOaSSPouQUPrO1Cd/q1JA8N+1pqS5YIUWMYnJms3YBp7CUcoosJUJHcW9AnNrpyK0ljZHWmZGEeMlQfZylKRg48UmVBr+mUGcksnRLIktvgIhBow4tcR1uzx9OfvDpHDIToshdpGEqOmfN0iOpnJUk9H7M9q0FJFScQxpVMjynNJJHUXIKQOeIMC4tIp8c256WWgiWLscoKmfKW0kBIKWCQqM5bMz/4MxWn9rpyK2lPbMV0Al4LGQZMx+TpHcr+Zbb5v8ZUUy3JLL0Bojy2bNW1pzOo8rx6aQE77Ayd5GG6WlcTS+lX5JoWuvWghhaBqYSc0d6YfEwkdxFKSlsRgETFYuxywUFwJSSYAVFjKJypry1KZhSQWEsEVvMbMXvkLW0Z7YCWvuykNdmtvqkSkMpTqy2hcjTLYksvSGibPYs5xz1TUqVG6yVO6dBEjozR9NL6bdIJC3uOufzVYzCyqBlLVHqopyMPIlSUpiT+4vDWorJsSmMppRNlhU/vexRTE7PW5uCwQoKY4lQg5B2R9/MVkgxaC3QVrxZVTU2y1OqBApiSYo3z3MRCnHS9FASebolkaU3QJTNbLVZq52TUpFt3Eat3DmNz2zV9FL6JUlKyy3dKKwMGFTgDM7iYexSEqWkiDNb34VPvz+jn15uFzVTSoJlFCkKATk9b20KplRQpGiCZC29M1tpNsVtXFoLLaW0FmsWsJCFxZjEO3ML8vMYESCRp1sSWXr9ROmhEVst0Q5Jz7rcnlPaVIipKHJKndmq6aX0C5IsLdbgAqOwMlCVAOIuWDyMkSdRCopiZuthOTnWKQCmlHKXUeQzW6OcmrcWhaRUUBhLhFsLJUY7xa2FUyV1ZiuQ331E2cotZ7Zq3gEW8tqEVJ9UacjF0RCJKKZbEll6/UQ291OCigfq3o5JqaoXIs+d0/jMVktP0wcKEkvr8rB57THtxMqAORGbEnfPnFInN1FyCp/ZeoyXGTVrvVxSaEomGFBKQScoTE7NG1BSaEoFhbFEpLqld2YrMGQt0FY5szWf5bk+ITWfVAnk4miIRFSm60Q287KfyGe22qzVnkmpppMea0kzWy29YiZta2brLJ9tKhQ2X1RzApbhOaVOnluLXeavzGw9XsZspLwmCtOZCgbkFOqkFCqnT38lEgVPkN+cIqW0Bwpr2QujiEOMRDQCzZQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTIliBJZqLYOYEsUILNVaBjElihFYqrUMYkoU4cMI+Nvf7WRvjCIOMRLRCDTToYC1XIyA7/5qJ3tjFHGIkYhGoJkOxSg1VH0SDWJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTomixyPdqO+8Bh+fJuIaE3Fr8slCR642NqRC892/578KnFCaiSJshiC/uw69zt6Ak8jAROVH8ti9f8S+SW3Acgiw13S1upMkEvWRyLcEjSRTrdVxpG+ig0EEApcgtiiirICXkuR6WQnPYJUU21EKDd0sRmb/KVA5nYhHo+JZBFEOUFYW15Jc5HmT5r6p+GcTEUc42hCeOLWMYRy6Oh/iI87Pk7iRimBieyIjmeQKL0+TmSI8DXSpfkYuryOVRQec/a86VQN0lyfIVrY0Da9sjLQVGoTtVuchdFER7+F12bVgKzWG3FBw5JlZowXukoGMlyaSYGYvCRkPNwulsGd7ybLlq3vIMZq0Dd55iLRwrKfuqAOUASdsUBEjjKYFMnBQCQAbd3UcUx74JMiKO7YqAOpKb4dNAQiAXV5HRJEFt3JS6SxJcQSFxEBNHPwvWKWgFagkqchcFQFkV+YleAwak0Bx2SkHjUgNLwbukAJTZkgFw4ucKsxb80uaOeHYFW4G9LWDWUjAHq+t/5jFDYS3ZZU0psxY5FeM9/63ViEkaInN4CGJ5mtxPJQpfxdFfqg53UxscjxjH/BfiKjKaxK+jIM1dkszDzynV8k86TJFYp6AQUkJDFLEQCafwa8CAFJbDLikYXuN48E4K905D6eFWLwefV4/x7stHcTfh+vpaIx7iuSsnjqKVm11WMyXBQp6DQW4Mye/Vn+FJAd2UBRmxhwA4d0PdfUQnIcC+EzIiBPPblEdxs3kFnGWTOzJxHbk8JujSWgNwr5PMwj2lulwlQ1+nOAnX93i0isi9FHlEP/Nrw1JYjjulWK6utaljwXukcGH9WUYKZ1GkcbnvELtzzD/hT1RFYS1AvKxxTP1SJZBefCmLTA0oBchcHoLqzd09RM15TzHz1JxyP7pb7iaIaqlYoD5ryU+pQXOXJPBEOTGZaOg9FBzpHEXuojBZFR4vXhMMSoG/PimskFPwLilijKXaDAGPnAVwa+FJWbfIdUMyOEHbWuzyuVppZi1k0acmawtWtRYmIkslhogKcnc3kZ45MiJIE21dbkx3CxlVKiXXEleRaHJBmb/oLkjMiHOl91HIr4rcRYE/rUSISJHuEaJXCsthjxQIKBaQgndIEZnz6SigyFmAVLeEb+/zugVt4+t7IbjSuec5cmuxy7RJZqdp7u7D3ak9QMByB1/WFXBJ3ku7y8XRECAKn2Ryt7j7iMJqWVBlRJyDzno/qkXcse5FRM4Sb4nLE0GikasgYf74zKN7nYT1/DcI9i2nBSvWKc5X93xPFZH7KArbd4pIv0GKmOMuKTSiKE6C90ihwkLLd64NRrHTvdCuW3bHKOIQIxGNQDMlihFYqrUMYkoUI7BUaxnElCjCL0bAH//NTvbGKOIQIxGNQDMdClhLRcWWGKWGqvg8UK2lYntUa6nYHtVaKrZHtZaEcNGE39q5Io3sqCA+L2tZyrfXE3Zwd4DWUn7QKK2Fg9liH/gs/JMcL/Vr7meCz8xaHljci5tuawGGrGWWxzLHwcfPqvr53Kxlwa9oR/x4dkFbOH9EfcHFU+WXdcsMBqNOXYnrihqSz7Az+YjXcIU/CSJfXz+vh9XnZi1zfrvmGF+zFuZf6hOaCq2FH2DFydpjkVsLnzqwFzhOOHbVKppqLZPF8gGGskTN0LKWn6JBo9YS+JlenCc4w+XMWjg+7FG/7B9Va5k+YC0L2kPLWg7Cl2IqrFuWoVHnAZo4bWtpFquZNnSrtUwfsBY0O5BlWMvjDGdqLSfh9E20loPkfGCIeTi9VWs5+bo5Zotl1cw+JAuq1jJZcEl1jkqDtaDNyjFsYi3NV+G7hVrLb9E6MSdCcIDnu/AlB5IBf9Bh0+/D6mecPsZhhPJcag0jnDA+L2up2A/VWiq2R7WWiu1Ba6mo2BIj1S11XO4ApkQxAku1lkFMiWIElmotg5gSxQgs1VoGMSWKEViqtQxiShQjsFRrGcSUKEZgqdYyiClRjMBSrWUQU6IYgaVayyCmRDECS7WWQUyJosUy4/Iudt6HmY1HTMit5QAMuqbrZbiWUUMn2Vd9rkOjI+ffhOvlYbNAcrbGqyAXR0MACHPHC0NEMbGIjMgvnSAOGcLHa1tSCViubIytpRK+tc3iBUqjOU5JmiQFj2tFg12STcY65BTL1dIEi8lEN5EU+07W2vEM5xSuMctNJhWwFYXlFNhCiiIjWTBC14YaxGxVrLVFFNbiCgS1hAy6q7EvACZJ2tpei7RcliATp1jpTlbEGiKiOxcri5xfYhxfK5JHEvvibHDwoupZIDSWY/IYrUhS8CStpGDZb7qsa3PFZOY3GqikuH3LxSUtGR75Y5dzjTEd/NfktqcAdIWx7aSwyPzVE4etJHb76Wz5kctQLT98Cm8DTW+OO9RsONI5uq2FCyBDNednqZDTwmlzHWM0YC0WQsFF2IaJNDFHRpRfom35JSqnXJwNlR3cbgYeljnOFn1TSQoeDcNDkkw1kVEQurRxTCbY5YICkHKKGS4oCmuRbcTt+vYUAPW5pRR5Rowlgk+ivzRLjQay5SnqMjnDb6x4Ep2hfBKFuO7mB9ZgiJQKOVu4NHz3BxYOQucGk4ljIQRchG2YSBNLyPOVXeIyfAF2L/lnLvM1P5kKF/jutpaUpElS8LhWUjCrojIKQp2WjK/+2FVOnuGCImnsd8x3Sm57Cs0psI0UQMqIsUSAHpDmwv91DVPxVQpl4fdtrIVQ+ttvZOD0UVbIElOSTAuX5svx5eKkEBAIN8EwkSaWkBFll2j5ckkuUzlUiClUUsHD+tPvVWuE0TC5lKRJUvC4VjxYXJY4owDsRtRk6KeXu8rJM9yiSBq7DCm5J1FIToEtpCgyYiwRyVrCK9pcZi1yXZDoDG1rYQ0X60hamdyCLGRhESbagdqChIvIUkkh9ME8SJQqZEM6zy7pA54/ckLlsB6x55S1NjT7BvNijlOSJom7CyV7sNgakiDxcr6i6PKQc9m0pugqJ7koZl5Q4OgaW2q5yPUnUHhOgU1SFBnJ4hFuLZQC7RS3lmb5tmn+i4TJ6Ay5tVweNq8R98MZtxc4FvpUJZAFDwNkF1dnqIK+hlemwFwcC/EBssZHQz9RSsyQzu2SBBWP25vml5IDsspcMoprqRwjB1YREUYjOfYkAUpS8FgY8GiwmFhJoSupgyIlo5dLilhOXRWDagwUlz+RHFtyT6HQnG4rRZ6ReGpIdcub8PEqt5bmfbiTe06eScobkVvL7F42RUFqX+iZCyyQRfmp8eOwwovgV9mmKEQujoYAkcs7QOSJGTIivYSg55RccqL7Wwh09xdPpdiNxmhijj1JkyTnsTBUsu47oK1ZIKfgr7RMUzJJ0ESh02qBvKjtsmoMFLP34RMLxLY5EGxHoTndVoo8IynYHmg/iXbHKOIQIxGNQDMlihFYqrUMYkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkQxAku1lkFMiWIElmotg5gSBXtgKiq2AazFNojYC3UPkQFMh2KUGqo+iQYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTIliBJZqLYOYEsUILNVaBjElihaLjMq08z58FT7ZWURuLZxPJENX44jR4xCyuavvbfisDPrkiM9y8fPC8S4mJONHM2KiTRTdhkQkWRJnZ9AkXvS2uaCCROPDXy9Fqi/uw6/VTbRJdLCvwijeyPhpTzoqsci+hgEsWFRATpEl3HYTLQoXJKfglCSbIsLMJgUpnEImW6W8IUguLKCjuAcx/9na8vaFtfiI+XDEEcAHHFRPiWWoPucNegCZSLIquHKH52guQjlxJ9HyVZZLoJRQh14TeVAORXfx3PvqN13WopkBmH2wcfcZka+LZP4IN52Eniz/VcopSu1KtOzLqHgNA1iwVKTyq5c94ba7iyIJUkjhluyZVQWVFCeB1pLyBgplcdiY/1k4nS3DW54tV81bnsFYfYR7UoWi01ooAP58wk45DQiQWS2Lo4Irc5y4Mej8nsJa1ojwX6btRWREgM90LoLSM80nMu+Dx3xmQaSxzCgs+zpvpYuEt4HcCuYFHHLqRCG1OGL2hUrCABYsKUDDxMuWcNvdRZEEySmStXhmVUEFRfOPMkOkyJuyOMxa8EubPeLZFWwFxrXAXRPFj7PXIgprWV3/s5xQYPwxRZk6ykIWQdRSVQ5opJAgc5z/Nlb+4SvWp07cSTQPP49OQcEquhMUQakcFy96Lw+7rMUyo9D5O+bsImEq/BNYLEpcSE0levY1sJWTBcsUIL/xsstRursokiA5xeL62mSIme2iAJivlDeEiSkb+Ax7tJu5mKvYhOvr62gkMKMCRSv3EA9LOVmurvE41InGfFQCadYuj/pXSJA5rv4MUTWnEAIXhLiPaBbuo1NQsNpkRMCD6r5U4SzNg1aG+UUxa8lpNDNyJhN6TrgVWh/JSbi+D6p6p6AaS6kRCde4I5KyeDlZsEwB/LHLkrAiufsokiA5xayZLSWPnlkoaI0CoKWkvImwBdLss3eImlmLGzRQzC4kCmsBvBYGHc9lgqpUCaQ3Jt6h89XdnU1qU2SpsIh1Zis99YIQdxHxXJ5sEfl5cpRBqUYXz7zD3d0y/IVuQU6T2nR6t5yLVrtICE7YExgF1ZhLTSWm7EuJxnKyYKUCgFiMmnDb3UVBqCAtCrmeMmtXCwpA6pY8bxYuwq2FJ2XdIteJfC6vom0tXvcgwywgL2SyqKA4jfeYHhSZg3PDrRY9wj0rfkLcRZRpR5Gfn8utQZRBSe7iJe/OugXIaijJn05e7yFJMe1EygDnJrUrUS+X5aTBMgWIr1/WhNvuLgo78981Cs1sVFBJASGRT88bKYwlItUt4dv7vG5BE/76XkjPuXyURHfk1nKlSxbh1sEJ68ywwrPNHiCMDFVzqQOXt5AgdyA8pAERlz86M+I+Ij4p0gzPFhELtxXUK14Rj6k4Q6e1aGZAQjHYplstw1EfyfnqPvUaKMXdfYDSXOqkxOxJpGHAosFMARKG0MuSsOQmc/dRJEEKik+cJE8KyywTW6e4vAuf7nBR8sZQkWVPtOuW3TGKOMRIRCPQTIliBJZqLYOYEsUILNVaBjElihFYqrUMYkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkQxypy+OldxANOhgLV8GAF/+7ud7I1RxCFGIhqBZjoUo9RQ9Uk0iClRjMBSrWUQU6IYgaVayyCmRDECS7WWQUyJYgSWai2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTomixbLHDb9wnN0NuLWmH37j3bPfGvOq9lB0+EzLH2lbBvhcv0SZqbEfbiJzVd+LVDW0vV9dxvgGQsYoo4Vt2cUf4abaDsKbXvU2weefbBCuF7pvrUpsSe0SJ3l3b8/omwV4OndvzWjCnzCmyKJJCpksgUWjZ+EbLcMRohjRnZgjFzB2gsJZcTRKwc2Ne906zTomMuCR6lEktEraTKG1Hq8iIfNYgT7hNGvQjCqG/s8KT+9yKOzE5DU588oWkF0lLEvXWhHgGCIXtm0uWSImTHlHcO6oopwB8dolwdW/PCyBYEqygiFEsBThUqnWKbCsxBvNzhc0QGd7hN85UcXRaS5xb070xb9p7VierGDJxkrVwBviFhGPu+4h6rcVPyXB7xqiqAirHWRkOvlRbZ1yRgdD0/EJJot6akJx6SJZBJrXI0CNK9O7bntd3I5O4fdvzMlhbMLsco2gKSao1CsRPGy0jiEWL2GaHX9lZtkD5JLIdfm1yJSJpnlnIaWqnec+ul/ksoFwcJ2p0i16fYtlJBBl7rSXuxMt1C1CIiKZbMDKXaeKmzbA7zhenyGjiNsGWXs82weptCSmMgmWQpAY4ratHFPX2nOUUhAtFCp8YqOllRQ3vYloqIZc9iqaQpCoptGzSRsuIYywRiA/Ic6p/h1/uLFug3cqVWlgSlVnzmmepEtQPcO8vrBQULWKtzn2rYI3SQ9RvLfZnG9rSHt6Km8pxVjLCdxYOX8fyBJzGtwm29Jy0IInempDCKMifpGaLAT/dopi3pQRkFEDcJFgoTGxAfS0MwGClYECUQp2agkQRjzYFy6aYX2ssEclaQv8OvwiAGi5D21pYAXo1SVDPLGTz40/0LhdsaIkjRFZT8maVh0EPETWTkBF5UEIbbLrYBZXjrLbPLVO0JxMR46XaWoK1tvd1kuRtCQHqFDUmqa2hAHSIQnD1BU0JyCiQzxhEWy0SimmRIoYBJFgpGMDLKYqcPCSpWhRSNlTGRmshBdopbi3cSVZ3+LWdZXPk1uI7/Ka9Z9W6Wchru+SiqlvIVUNG3N4qGHeS5KubaMBadCdeBLUNbX8CHilKKsdYudeqRELg2OolIo3JkNLr2SZYvYttgo1CysCl1pz0ieLemrOCwjcJNgpAT1RoCUNBJJjrrKAA4Ex58YIqKbRsIAk3WgYQx1giUt3Sv8Ov7SybIbeWtMOvL75leRaIXxL0dSg21M3FWdsqOF+ea43Id7Q15OeyThGC2oa2pfy+wy/ASJfFnsNO49sEA5Kf7m2C1bvYJlgo5EEeVQIW22y4RxT3Ns3lFPyVTYLjfsV5Xi0MKHgCYcuVxKIU4szyEguKSBRWNrqDMoA4KaU90H4S7Y5RxCFGIhqBZkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkQxAku1lkFMiWIElmotg5gSxQgs1VoGMSUK9sVUVGyDUWyu1i2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVGMwFKtZRBTohiBpVrLIKZEMQJLtZZBTIliBJZqLYOYEsUILNVaBjElihbLFjNbOTZYh4s6cmtJE1JtsqnPjCTaE1LLqZ2lOB7RInXPbLX0fMKnIXMgR3fqtEmbxSTY1qTU1rxdp/GZrZZeNtMVePLMVstcKXWa2arkPsk2p0hRlKJHEPVOuckpFlCIDrWNs1g7pTC9xTCkyIIROop7A+KES0dhLa4mnWzqQ9NlqD4ccW4EWXhRp3YaMnGKMe2IxGkKMhq/JMqmNMapE0RGBOgUB5u06ZNgSeasMptC4JM3AD9leiKopefuLhL+ukUKhSXNWOqWX0KlLlmUXNzCklMAGiUN5u8SxL0tNzmF79kaKfPJsYlCHSlZhNFgDhvzPziz1SdcOrqtRfPqMyNZyDLOXJP0SZVJcUB27hEtks/0KYky6+y3llh/WcYza0nzhzxGLpCf+sxWS8/dXSR0u/EZBZNOUqf5oip1yaLkLGeNnFEQtjG1UvQIkuRlmiVFth+0UuaTYxMFIHqLybo4ji1mtuJ30FqCT0iVUvGZkSzktQmpOC8mJ2XnHtEi9cxsTekVWSkcXn1ZxjNraU9KBXRujSLRxJmtMb3o7iLZPLO1mC8KlCxG7pNsMwpCnZGiWxDz9lnIOQV3G1RfdReTYzMK01uWrLFEWN1Crr6ZrVD1kLUQsRYWa4HQYqtSJTBhSdJYfGqnITv3iBaJZJJwSURIej7hU1Dky6dWWsYza3FWicE/3h0OP/eZrQTSc3cnycaZrZ45k7pkUfKZT7LNKACLYhQ9gri3zUIuKfz+iVLp5ZIi6i3GQRhjiUjW0juzlWajN6GjbS2szeSIlKkTtxZhEabEolM7DZk4HtEi8WaVyrUkIphe0WopiOKjG7CMUy6AynFWiYG/vNWSaNIzhFicJncnCSB3HGGxmHSSOmYuSl2wGHl6JmQUKYpS9AiSyatFXlDYdR7hLifHprxEVcQ4cBlLhFsLM4Z2ilsLpz/qzFYg2l5Ebi1pZquWis+MZCGvTUj1OZyGTByLCCKN5LM0SyJLD/dSgYxIFKBpWsYza0nTSXVSqibhiC5KqTNbNT1zA10k28xslcy51AWLkadJtjmFRnGKHkHMO81Czim+hiBoFmUKsctlXlRvRRhjiUh1S+/MVmDIWtKEVJts6jMjBa0Jqe1Zsrk4GpFi68zL7pmtlh7TElZDRqQGIPoFXC5Da1Jqmi8q8HA+s9XSs9m2hifPbLXM0TdJ7SxG7pNscwqNkih6BFHvNAs5p/hKeJNC4mWFU6jeijBZsN3RfhLtjlHEIUYiGoFmShQjsFRrGcSUKEZgqdYyiClRjMBSrWUQU6IYgaVayyCmRDECS7WWQUyJYgSWai2DmBLFCCzVWgYxJYpR9jate7YOYDoUsBbb7Hcv1P2gBzAdilFqqPokGsSUKEZgqdYyiClRjMBSrWUQU6IYgaVayyCmRNFike/Tdt4DDjXMxwYAubXklzlqTwaSiUvwPn1fl9Ho+TLQQJZ2RqQjAI5DyIY+RCIPpolF5JlIAwjeyFCNIk1n5fjDUw4TyKTNaJxEv+jnGVkneZ0t6B0pRLXikCETHHCUixwpPFimtiRFSlUvd2fFBkaAxwsqUcQoJsUX9+HX4laohmQgBL1znYMisQh0fMsg8mHahsJa/PJJEG3E0SIyiImDiy3A1W9gLRwRZGPBBJk4iWguQh3oGKQ2kQWzxBwZkUYnlv9KXXiaHLXhrDa2ef6z5jzTgdM4yVxHTHn6XSQcfysjwIhcwxyWolhwwLOJXFLQgWDZIJtEsXwVi1Mv92RFvYuCcopC45DiY+SSMSyqIYDeZ6VUoMjzAthoqFk4nS3DW54tV81bnuk4H2Bra/lHGaPmAylbAyQPHuc6iC5pEMjESUQ6aNGHAJZEFkwTS8iINDpxyJFdKU3qJw0sTPMmsrh+6iQyqlMHnsrFLhKO83LjzdjS1AsUQxK5pAAQrHv8KU5kJLhd7smKeXdaS4pCh/oyolmLaMgAoyqkQmAXRGHWgl8a1xHPrmArsK8FzNpEvP5nHjMU1pJdpjbOf2tVHwtZZFFjXR5Cp1R6Xji5OIkofMXKn2QyGL0k8mC91qLRBYyW0qR+nLVZXF9rqM4x/05CBd6epfQ7SZZ/SiM/M0lSVrWATOSSQoO52giPNg8/V+3p5Z6smHdRUJEiRQFUCnPKuSpWsTwtpCJFjGjgU/Mx3kj5KO4mXF9fq00e4tEtJ46ilZtdZmJXf8bxjM9zIE2RmF/oHbi6LtpJ+bkTIQLuAt6s84c1Ig9mqjdkRBpdILqQNPlQB86UlddmzWxJibr3EHGSk3B9H840/f/UR3K56ijq7DY1T4i8LocGU7WpO1HMwr1m2i73ZMW0mheUn+Qa5/EkhI8uRW4tnBaQS8XQzqJI43LfIXbnmH+C1XGGwlqAeFmsBVmXketSJZBemMLd3TL8hWdFU6kljhLRs3f2GSHB+q3F/oCoC01TbsjISlgV7U2OjCYjoTpS+l0krJ3Wizo7terLRG5TMJirjfB4OFGbTZd7smJaFc0QTgFEjcdK9Fy0ovK6tZwwRkEJj5wFUCLYCE/KukWuGzJ9Em1riZepDZqo1HgsZMmuyRrHgqcbDmiJo0T4hbFKETDza0QarN9aJLog6kLTFKkiK2GzbKL4gNNkJOKL/5p+F0lbyYbzeJdarZhbS0YhwVxtRKRINpou92TFtOpZSVL4tSiFZVsTixoyo8wp4ZOzAG4tTfj2Pq9bmnPUwJLbq3JeOZFbi11eXjSXd+HTHYj4HmcPELDcIQNit2ItcKKBlJCJk4g41xx5CSs8JNeILJgl5siINDrTvLsPd7B7pul1r7AylfCJk2pIl0nkNE5yvrrnS6Wk30dyEr7ltGBFkkSKjnJo8YjI6xRWwvBMd4Md5THyjVDo5b6sSB6KgkriyLUkRVgts4yohiQjsjiAUiqYqp3uhXbdsjtGEYcYiWgEmilRjMBSrWUQU6IYgaVayyCmRDHKOJA6vmUA06GAtdjAqL3w6f9vJ3vj3+24N0YiGoFmMhS0FqtmKio2oFpLxfao1lKxPaq1VGyP57MW7Sx8PF9PbmbrTHVcIm5j9/Sb4muf4F1cGeYqcNhOWl8moodzALaG2zqimALkhkn9MvW2boUle2l7UzB0Xz++l/EiyOXblqPdr/794fmsBaAaek1iY8meh1cz79lneHj9rLHV9kB9gpK4bGt6S2tROsGmslScBFnTLfy37fgj+Hl/R2v5iLxwMd/T43BWOp5+R+wKJPRsaZm1nMhtIUsWnT++oSNcXKFeOLVLuF2Q//nqbWDVgUAm4EJv42OO0ZLw4ryS44F8McJ9y2KXEE04+hBeSeSf8g5E5dPMQxNO4ftaJJCBiiqB012GtxQyF84GNAK4Eo5svMBJ4FCAeSCt8MdL7zlQQX1KGkH4rxDSU+DJ8ibK65KFC0ru3lzATYGK7BZKWNrXnehg5p8HyCz+PxPUWr7h/YB7bMEPg+q4sLolumgtKMDzLzWQxj6XB9FJ+HKGQF4ZLKT0YAdqLfixEKh0EEiYXh2HC9yHtDf4LsINk1lC2y6B0aH6ukXyhXAajuAVRuf5STjEtcUNrEX57RKSuHSfnEYRLhYPwiOXQH0QTpO8JplK7t4IrjhAdUJLkdsmd3iI7xvIuqriOcBcsezDDW8HKEod9GeBJJeUsdzDOKO34DU0J/fT4tGtZa4Pbd7i0VosBGg0BZyLnWgxCTkOM1gPpBDHTaRT1RfCWThe1eg0TLGWxeMsHCHhyC+XFrRo9SnzqCD5YZ4C4id5VTL+x8XonRpLHMIkBkIJcofTf99gWnb6/QNqUI3csGSTJuHfYS30oH3Q2/AmnMp4hYdYvAdsBwBuLTAyC6E6R2S7A68CDVDJcdBG96GlaXQMymooE87C8Sri4r9byzz8Ukrb+O3Se0isPmUeFQi0vPEUUHeg9ZPkVcn4Hxejt1vCgvmzxEpHCvM9g/LZ6fcPqEE1gjv2jAVrmoR/aS24Yah5qBJ+9DZAy7QLwIo3vpIwtFgLrMdC4ExTYFCofRZbmJIMykSeDpam0eFwwGqnEC4+RSRSZi24vW+kbmA4KW29hGpBfEoaBQKd4NFil/AoQs0V5U2SieTRO0Y9l5YVfeFVOBjnecD07PT7B3PlxcPncSwQKtrvQly6U2th4zNZy1LuNT7IRdfUl0yIoTpZtaMYdPgQj3jgf2JwRI4TpJYs95goD/S2NJUONCEsaLqZcBqOgJ9IynNaC+9vFJjx6yUKGX0KGgXcCBJTIDc9AcjrkoU/ZBmNUYWT1/lbOCTzzwMmaac/anh5OFgaBVgWk4TVQs+AqVjLusbWrMWaOD8MdHhoW6RxsH6nfF+YirVUPAeqtVRsD1pLRcWWGKluqeNyBzAlihFYqrUMYkoUI7BUaxnElChGYKnWMogpUYzAUq1lEFOiaLFss3u4byftyK0l7R6+lJ2B2U+eOpDS9tnqHcNEZI5EZNtY+2baRJuIVOIy5A7d0ZsBZWKw0Rl8s2wTpUgl0aRIGiHtwE20SdwNZGy74sVQtFjiYg0DSNtJOwprSR/ZoVN+lLPNxn1pBEsy7kHuS1cQmTgF0fmNLFogixJ0E8UdsA2Zw5cqACyOLoBAf2GNAXDiqShyTo1kEXwlqV6S6C7E2g0vhqLFYmssDO4entb4iOi3FsSIm423ll3xPch9xQciE6dcCEsX25HL3URxB2xD5sj9bVUNHYTA8hQJVRBxeCqKPK5GsgiFtbRJCndOsSNeDEWLZYvdwzdZS4i7ec+ulzhBpGQtaUkn89YwCZk4iQimynjH7B8COonWVpixI+DbggNckMTotKCzZZ1UlJiKIju3SBaBn37c5Nok7SWV9sWLoWixWN1CPfTtHr7BWoj4Ef2LcMFqPVmLxJQk3ZthElriRCLuaTyLm2l3EdFdxM0cPDUnLR/QLZK1WmDBiiAqiqeiyGgsUoqg5tNFkrtLsXbDi6FosSRrCX27h29hLayJBSccCwvwPmMhC4swuTfDJLTEMSJpbXj13kWUdsA2ZEQeVHn8IAXNRo2vTgVRPBVFoomRUoS0NlSbpHAnip3xYihaLG4tLA60U9xa8t3DB60l7R6OKnmhN6H8spDXdg/3MIZMnGwbcmmn+mbanURAkZXMoTt6I2i0eKEDeEBtQ28XN23ZLUg0EgkkFkF34Aa6SMytSBQ748VQtFhS3dK7e7g8k5I+idxa0u7hr4OtXu2VMqCrRHshexhDJk4iMs37ZtqCFhFQZCV3yEq/CCoD4U6zgiR8s2wTpUzFg2okpqcRdAfuiDaJrdctKFLbDS+GYgSW9SfR7hhFHGIkonGUvC9eDMUILNVaBjElihFYqrUMYkoUfJRXVGyDUWyu1i2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVG0WGwS7yC+KnYeJHJr4adj6WGNW/Pl/ZrsV9URTjFYsT1hIU4iskDljodtIvnwm5BnwrdElLV74jRiw3HaOZCzX2VydfzEk2iySJoffoOOX8MyEsvz66ynN5dkR7wYihaL9vwPgjsPtmIV1hK/1NuOfXPdh9A+77S3Q8z2WRRkxIlIdxP0HQ87ibbaV9HLV78YyJcfftIxa15ZJP8oWqrHPjPYvorxDihJNM8cT+GT2XOKHfFiKFos9p1oaF9FoPzS0mctwO2ZqF7UX3461mDJbcjOExE8ZTyLpdtFtNW+immvQv1uyJ/sc/HiSCPFr81EdmqRLD+FtWQk4uCHKzfenGJHvBiKFotZC355l3TuqwgUgwyAwlqy3fxYptQk/6SQ5eu13IUaLLkNmTiJyHcT1LFMXURAr7X4loi+V6FanRS0DEWRfMGW1FukNWQ0Fsny47swliQWrGdfxV3xYihaLHw+b9pXEZGKgmm1cn03P9mxD7/ch1BXGVjbDjFzK3JxnMh2E5QdD3uIgH5rQR7E6XsVoh5gcwfINiNEEI2URc3PrfLQ/OgGiuskmue+fRV3xYuhaLGkEQsD+yrqwI4MhbUA/uDXHftkwINWCaR3pkW2PaGhJY4SwdOeDmKmXUT86bUW+5PylpFOdlGqBUQVv/nq7k7GZGgFZmjRGCQ/KkNJQiDPpPBBMlm8XfFiKFosbi08KesWuU4s2sayZi1e99hYVonLQuaZKplAsMINtMQRoswy3FrWiIasJW6JSGn4IIn7G0o1w4KVwgckVF7VZTRpU8Tom0ZaFiTwLqwnk2RXvBiKFkuqW3r3VTznlKOoGkVuLWk7RNmxz/YhtAcII8PvxLdDVHdCJk4i0t0EdcfDPqKt9lVERLE8pBgfIrZzoFaXjGQGbkg0IiZIbF9F2UBxnUTz3LOv4s54MRQjsKzXLbtjFHGIkYjGUfK+eDEUI7BUaxnElChGYKnWMogpUYyyU97f/m4ne2MUcYiRiEagmQ4FrMW2WNwLdRfOAUyHYpQaqj6JBjElihFYqrUMYkoUI7BUaxnElChGYKnWMogpUbRYthkNVY5KInJr8dFJgIyD6R4NBbALthxU1BLH9x0bGg1lwYaIfDSUDVJKo6OA1mioXHwg0Xh6MUI+nqaOhuqDj0pKKKwl+57C4UXz7tFQcP+G1pJ/lAFycbz0NVLPaCgLNkDko6FskJK7+YmnPRqqGJ6T0eiILMAi+OirkqSOhtp5NJQML+IXNvnixkKWiBr54JFjhgYK2ccupUjJ7JKfBRsg4lcvgQ1ScjcLml8Z89FQfdaCExklESP46KsWiTjqaKh8NFTxUR8orMUHMenwImqSf1LIaRATykysJQ4qMmTi+NilFEnTLYks2ACRj4ayQUruplRpIJOKmw/mApzGR2R5hMxaEonZcR0N5aOhZFRSgaKV64OYlL1nNNT8Qu5AGVQkoRWZOD52KUbqHg1lwQaIEMyGx+ggJXGvD2RScZP4Aj+1EVnIfWYt6yR1NJRYiz4EIvyhrCisBZAnjw8vEmOzKoH0whTu7pbhLzzrG9/iY5e6xrckPw/WS8RTDYpgMCx3S7UA0crRUCa+wmlwoibnEfK6JfoRdTQU6xa5bthgLe0WnhxYyDzzQmXdwgOriYgsFfrLIyyL5NaS/FKwPiJEUlu3QnU3YxUDmSxSlrtIk1lnjJBZS0ECMQrriRR74MVQtFhS3dI7GkpHJRXIrSUNYgLA3jMaCqC1yKAiOgy5OAgPaUCkkXpGQ1mwASIfDWWDlMS9PpAJwEUTP8JpdESWpCcRZPTVOkkdDbUZ7bpld4wiDjES0ThK3hcvhmIElmotg5gSxQgs1VoGMSWKUcaB1PEtA5gOBaylomJLjFJD1SfRIKZEMQJLtZZBTIliBJZqLYOYEsUILNVaBjElihFYqrUMYkoULZZt9lVs8o0SBbm1pO0QdevBS25IGMd+SK+7fVARlstwHeLnNyITJxFdrq7D4Qaiptm8r6IxlGlmWyCSwfZejHAaRLV9FXXjxeUqT69FkrvbGt4FL4aixaLfiTYg7ojoKKxFCoZIA5QkEf8YaEkKC909HwOdiJ8A7YuhXO4karbbV5H+jCp09OfHP/tcHBkiL5Gd2ndCiSAfFHWtiS6SzF1S7IgXQ9Fisa+Kg/sq+o6Ijg3WokM/yoEGxsIBk15fAJk4TsRI+tF4gAiOLG5BlPuTwdNkeWafiyODfttW5HH1qyVtSX1ve0k+m2/QqP437KuI30FrCXE7RH4uFgXrCAAWchrEFFk+ZAtIApk4iQgRjuXCANHamAo7Avm+isIQ02Qu00AmY/jdH1RoRUYTB0Qcx2HueugiSW4go9gVL4aixWJ1C/XVt68iquEhayG0VAHRsK1SJ1WCFDJdxnL7TbOMaiVa4igRyuctLwwQ0V3EzRw8NacweJpSLbBgmZ3EcNmKa7B9FWdx40W7pbpI3E1kFLvixVC0WJK1hL59FWk2fq8q2tbCmlgglbo9wVnIwiJMypI9UBQtcZxIxmoPEG23r6IwpDRJx0aNPJcyBrMLItHE1kx8ysQVsrpI3E0kip3xYihaLG4tLI5iNFS2r2K6bwy5taTtEL8GEVQW7YyF3N4OkfMq9CFjyM4T0U8k3CARkfPkDt9XURlSmixoPGfpi1QAnFz+pBAonUpbGSS28aKP0u4iMbciY9sVL4aixZLqlt59FYEha0nbIdrWg9oYjGhth/iFhnZk4iSi9+ETUx4kAoqs5I64r6IxlGn6logAIs0sMYPTaOmTRDdeZB0iiQtaJOZW5JLsiBdDMQLL+pNod4wiDjES0ThK3hcvhmIElmotg5gSxQgs1VoGMSUKacRXVGyBUWyu1i2DmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoRmCp1jKIKVG0WLYYDZVGKTlKa/HBUjoKSUcPGXwQk7EsZTREQubI0nknXxdnnGsc0SYiFX8jMoeOygLieKo4OkqQBi6Jd99oqBTpTbheHiZSgZPAl4Om6mioiNbqSURpLXGwlI5Cki9wLGz5vIPk9PNcNgxGghkycVKI27ckmK34DQLoJuofDVUsGwV/lQvgUcQTD/fuHA3lV+0DkJOWJOoo3BnbrngxFC0W+040NBpqk7X4YCml9tFDLGT5riOuzFqE1aBxBHk6Ym7yxQroJuofDZVbC0ed+CWWZ/yknHmnD4KZp5/M9WtVYS2JBAioeAq3HffAi6FosWwxGiqNUnLk1oJA0Vp0FFIcPcRCToOYjGV2vSy4MnHydNasZY3IxjI5MoePygL4SPPRUcxlGrjk3lyNJcJp0tXwHcdLOWlJgiMkq6OhoJ3sWSyl58itBQWb1S2y2KOOHpIqQQoZfwJh+aIYPNcSJ6azXre0iOgu4pZEcdybjIbiJbks1QILVuSN3rw7HH4er8q4Fa03lLQkge5Qr+TuRLE7XgxFiyVZS+9oKIJVbYbcWmhVehcyRki1MgtZWJxJWYoNYFvixHTWrKVNNDQaCtCRDQjIsvWodLA9ogOXzDtvtWQ0dlXzotaipCWJRs/cGcXueDEULRa3FhZH92goG6WUo2zlym314cxGIdnoIS3kNIjJWPAMWYjqDRlxGg3VYS1rREAhVObQUVksWzV5lQsgcxrIpN4axOEuvQoS1JUzVHk21KtNoq3hOhrKR0PZKKUc3dZiK+zq6KGIOIjJWF6HbFlsIBMnjYa6Zb0B/QMsC0WLCCiykjl0VBatxcZTZSv/5gOZxPucqaSaM9H4kKrjsMKrsw31MjiJGUkdDTWAlrXsgVHEIUYiGkfJ++LFUIzAUq1lEFOiGIGlWssgpkTBx3RFxTYYxeYqPg9Ua6nYHtVaKrZHtZaK7VGtpWJ7PKO1fLBvR1k/acIMF/MxSIBsyeiY3a31HzfvpE9VcRX4qTtNvY0oWbZAf4Tb/CvUgX6T+mU2uXUbcMeIplyCZB3d1y2372Vvydwxf64SfE5rWX6ifs8fi3XDcgxaC6zpTTSzmVKc/wymFwsQGj5BSVy2Nb2ltdx6sC0jnARZ0yP8t6epjzuF7WYtltvlqlmE0rGRbzQwLTv9vrF8YK7CGYo6vGWhnD++4ZeXny75vQfXYC0fVuacLVcI8UtXxYHVSLI7K+oQu6OvYkV1AEuhtUixH8uGkOHoQ3glhf/TADcqH96F4RS+r+UzkXCpEFegJJMmqxFAIJudKRuQRAZOAjdImwfSFsHfU3z14a1/mMUBwn+FkMySXOLJ8ibK65KFC0ru3vyaK0BuZxBT8pk7Fvqt9fsH8or/z4LlAzR7gPKCtXDHIfz/5hiOj4f8FWs5h7rN+TgLQUpYrQUWwh2RcDPBHKxuARYsH4K1sWgRPyfhS4bAzYewSGceXh2HixOodrGi7yLcMAnlMiGsbtFkNYIGBaGwAUlk4CQc4mRxAxGL4Eji0n0epR7wOEC4WOCRGy9BBNwGSV6TTCV3b9OA5JZ51Dsnc1BNzwIWh51+31g+oAK4fcytBYnL04fqw//3ogY6qQNczqwFzZ5wxpsJJG4tc394MWS0lltUPLjdEBE0YOGtRzvRYpKkcTAuE0KtxZKNES6QQGNsAK5YaADWsoBpHSHhIviCH6bVh/WdSmBxAGbtkD/xEuIneSWoyIiL0TuOwJPcqoEg+7mD0Z4FFM9Ov2/gOR8eaCota8HNoxoKf6ZSxUk9qCp5wRCgf+IwWstBmgLg1jLnHQqIaWiBLLU0rwKuWdI4GJcJodZiyVoEBJXiFzYAVyy0BD2cBzwpkXARHI+Y6KOF2bYWPHo0f7iEjEArSV4JGq0leseokluLWDoY7VlA8ez0+wb0guYB0hNrkSoajhuo3TTEJxEeI3TSHjTEAS4YUAZqJtFasvcRfxJBi7QcAGcwD1DQEqB2PGOgYdDFMhESFcKsxZK1CAgDWmMDENRCAyInTnG5CA6gWhAfsqkEqcgR6AR3g13CowiFHeVNkonk0dujSm5jqNyRRPyewYTt9PsGrEXuCCjqFq+6HXULznGLihM31rc6/EnHp0HFqAgQBUAsUZYMkTJdsmqXMLzAI0zyE29NJCKDqOC9hGdWJsplQsy1lZuS1TAsfjqiYVlogNayQKIoqSL4kufmQwEtucxaEOTCLlEGegKxwuUh/EFqM/O2qJbbS/EsHPagfAZQPDv9ccPLw8HSKMCymCTWcvp9YTLWsl4br+mQFdsPBmmFfD/Fqs+/58BkrKXiGUBruRgBf/zvdrI3vrPj3hiJaASayVCMZS3f/dVO9sYo4hAjEY1AMx2KkZ5EdVzuAKZEMQJLtZZBTIliBJZqLYOYEsUILNVaBjElihZL7PkcxJt210VuLfwCo33y7GQ45cxWDuCJeJ+GNbFLzcI4irRlUIGAXWvSg5m6LCKRpffFffi1uA2JSLKkTp1wWgY9DhwfIJAOvNfFlNVEIzNpAc9f3t3XJvlMZrbqPOhhLP910Fr8q6kuiDP/WXMupDLZnfuOWYCr39BaXKmKXJzMjFbmL2sulESW3keE1+9HijJfnL8MUXRSPIMKNcMfsKfehGAqXBiGX5wMTgM/nUXt+TOZukgsIYWf7I4XQ9FisVnzs3A6k9E4y9ly1by1wT02qufQ1jpIGLIWQDXXWkjj4JGT6wesRbYkUiyOLE4HUUqv2GMkIwJ0WS/amq7xoeuC8SdbPENSoVBcrMcQaWhuanIxvShTF0lKCCgl2QkvhqLFYtaCX96BRzy7gq3wI9qr5o0pathaVtf/rGeL62u1BV1siYUsMfUuXB6KtcQwhkyc89/Gyh92o/5ayCVRSi/bhKqVL7vRGV0ozM1TWZhH8mWpLP/kWw8BkYYxNJal5zJ1kXhCRKTYAy+GosXCh/yjrMgB5Kv9NOH6+lpMyYoqR9HKPcRTW05mzWzJO5UNAf1QEtICYPMLuY0tjCMT5+rPKAZRuYuJ3zUiTy+u/6TIiPy+PwnX93hcnXAkng5wCWfZSmIa6XJlNipwmuXq2ho/mp787yOxhBQaay+8GIoWS1q/5R3U0LM21LC1AF4La+WtDQGpEugWpnB3twx/4ZmFUWSpsIhlEab56u5OhvPbgnAlEcH0TsqcFK7MwZVowCs5kGoB7jwVpuHLUZY0qU23OHWZOkkYRhMCSrl2wouhaLG4tfCkrFvkumCjtXgz0e53txayuHWwbuEhZ8tSoX9ZnWtdsk5Efm3SJOTOc3uCEuqvaZJcrCMrWC94RU7ja4NZ/vRaF0l2KCl2xIuhaLGkuiV8e5/XLXgzvL5Xrd/dh7uoGkVuLVe6PPHyQgYkHYr7Y3yAgOUOqtZ6gNaiYRJycRAe0uh4KPpLEa8RWXrhU7nmc0HEwkXQ89U9X3TDahmO4kMELo5l8FROwrdc+TXCTyUXWXr08idRm8QSUuSS7IgXQzECy3rdsjtGEYcYiWgcJe+LF0MxAku1lkFMiWIElmotg5gSxQgs1VoGMSUKbadVVGzGKDZX65ZBTIliBJZqLYOYEsUILNVaBjElihFYqrUMYkoUI7BUaxnElChaLFvsq9jaeZDIrSXbDlG2Iiy3YfTtEMlDlmKPw1Ic3cBQwM3XynTXNmhc9e6raHsdEpJmz5aI6t23r+Ll6to+UWiELCNA2kdR8hM3cFQfO+6BF0PRYknfWYfQ/oRXWIsXvn4SdLd/DLTIsv2ifzY0ZMTZV++4Z2IaDZWIstFX/tUPSJGJ+J1Q0iw2ueMVGysVvfPcxVMKo58iLQLcGq4kSflxEj/ZHS+GosViXxWH9lUE8uELRLe1aKDCWrKBBrr9Yosod9sGhkTcM1G/OpdEmXX2W4tVC5pmYS3pm3OyluyOiTT001xrhJR+SeLJ+kZ5LUl2wouhaLFssa8iYANNHOWTKG6HqFsRupuFnAYxgUusJW5XaMjEsQ0MARsv8TtzlkRZevJrKBw2KMLS5GdsIWIu00Am846pKJwGnsfi0Agp/ZLE86ODGohCkt3wYihaLFa3UA39+yrqgIMM7VZuGv+hIcUtVYIomV4L3X4xhVFk5z4aipHU/1IOJREh/Gbihpw0jsG0NIE0vkUGSapn9NZUFH56HFDH8kQjpPRLEnrxL9v+zyl2x4uhaLEkawm9+yrmz3VF21pYMyu1BhU3C1lYxI/Gh7swhVFk57QUsZZsz0Qp9pKIIH/RailJo8DCI3e+PmxY0Gxo+DAnewZlA3xzGh1WrhFS+iVJ9O4ZfrcjXgxFi8WtheooRkP5voqZ3UTk1pK2Q9StCH3fQxZy2g4R4N3oexwaMm7bwJB72In/5U/sWVASGX8+9JrIiLTpmdLs2RJRvT0VhZ/+hPKQxCJo+kBJYvnJdZSd7ooXQ9FiSXVL776KrZ0Hidxa0naIOqektQ1j3A4RkLq72OOwFEc3MHRrmckis47WvooUSlgNGZEWXUqzZ0tE9W6l4jTqTRKbWRYnJAicxPKTN7jzLO2IF0MxAsv6k2h3jCIOMRLROEreFy+GYgSWai2DmBLFCCzVWgYxJQo+7ysqtsEoNlfrlkFMiWIElmotg5gSxQgs1VoGMSWKEViqtQxiShQjsFRrGcSUKFosY46GsgFDs3zN9DSIKI516h3ElIgg0h33d+ocDbWZyEdc2SAlpYtoDWTqHQ0VruMaGzqM6136ypyRWLDw7QePWYi1G14MRYtFe/43of1dsbAWKRgCgRBwtpLvtfZ5R/2A+CUlDnQyZI5EBOjoEY36VKI0QglQf6WjP89aA5ny3PkpTiwfNozrLT88AyWJBhN3NKaMbVe8GIoWi30n2jAaSr+5JHRaiwQifWYt7udjneJAJ0PmKKxFP0Fruk8lyv1tkJLSsXz5+Vptx4PluXNPrnOnKemQKjeHkkSD0d48Zp78jngxFC2WbUZDleOFiPJJZKOTfMBQZi1pEJGNdbKBTo7MkYY5oZAZr3s01GaifMSVPj5sdBRzuTaQqWc0VPPBBtpCCWvWkkgs2LGtI0UUYu2GF0PRYknfoAdGQxXjhYh2K1fKRIyEAfO6JfrJjXoug4oKrhZxbBvYiJOu0VCbiXhqThukZHRSLbCgvW6RYJ2joW6/4YZcACKs1y1OosFm4fC121zGtiteDEWLJVlL/2goIBsvRLSthTWzNij4JyWrhex+UnGf32QDnRRFKkYEhugt6T6VyIOCTyrNSEfH+kCmIncWMnvySUK0m8xanMSCpSeTOPfGi6Fosbi1sDjQTnFrSaOhWuOFiNxa0mioOGAos5Y0iMnGOgEFV+ZIRNoA7RkNtZlIRyixIM3kY3uWh/ZApp7RUBwKBX+xhvW6xUksGKjS6LmMbVe8GIoWS6pbekdDtcYLEbm1ZKOhZMCQPMKi5rLRUDrWCSgkyByJSAu5ZzTUZiIdocSgOkjJbMbQGsjUNxrqC5EmWYusDC5XCCfRYHiYpQFXRWq74cVQjMCy/iTaHaOIQ4xENI6S98WLoRiBpVrLIKZEMQJLtZZBTImCj9+Kim0Aa/nFCPjjv9nJ3hhFHGIkohFopkMxSg1Vn0SDmBLFCCzVWgYxJYoRWKq1DGJKFCOwVGsZxJQoWizS82rn/RgeDeVfH3XrQ5sJakj7Ktquifx+m5ClvUZU7ufYIuJ6GunzTpmv42X4Wk5UlJ59FZUhS5VING3BkxsY2pxxszo34sVQtFi0538DZEfEHIW16Jd7QLc+nMc9BuXzTtpXUcv2JPRbixMtX4mhxP0cO4kGttybxzyZKD37KipDMaomozEZAI3r7pKkY3PGTJJd8WIoWiz2nWhwX0XdETFHp7WIjej3WPmUXH461uUtmn+MH+cMmTip3OBJ/cf9HDuJBqyFX70ELop9V+RP+gY9bC0mg6fn7pIE2cEV6sfvgkySXfFiKFosZi347d9XUXdEzFFYS9znUMo2HFKTUjgsZPPDj++a2G8tvmHiPPxc4mTWskY0sEFj+MqehS6KVnZS0DI0RfKlDClVgdNEGWJ67i5JdF/FYnPGTJJd8WIoWixb7KtoOyLmKFq5cZ9DG96mewzaJlTmhx/fNbHXWrINGsO9W0sf0cAGjQimI1qG91U0Bk9V4KdRBk+P7nUShGeUfHPGjG1XvBiKFksasdC7r2LwHREdhbUAUt3L132NxQEPWiW4nw55w0m/tQD63ICnFHdet6wTqV9ERsRTd4ooXfsqEsagqQo8Hk7U5Cw9dxckXZszOsXueDEULRa3Fp6UdYtcVwzWLYCPTjL1S1wWcvLj0Fh5KgxaixC5ZWTW0kEUR9sqMiKQZLYuvxqUsaRgo3UYgzdQE43LYOkl9xoJfAsTjBR74MVQtFhS3dK/ryI0NmAtaV9F3fpQ9xi0B0jaDpGfM5HW5V34lM9fysRJRNxdFxW77OfYRzSwQSOnHvH5s2FfxbQNZJY7p1EZUnriXicBEKTYnDGTZFe8GIoRWNbrlt0xijjESETjKHlfvBiKEViqtQxiShQjsFRrGcSUKMLFCPjur3ayN0YRhxiJaASa6VDAWj6MgL/93U72xijiECMRjUAzHYpRaqj6JBrElChGYKnWMogpUYzAUq1lEFOiGIGlWssgpkTRYtliNFRrvBDRspbYGaqTT8vgcRCRzAy9aI1MKsTJI64NMVojSkOeFHkm/NKljGPqHg0lOWcsG6WliDR+NZKU6/wPkeSS7IgXQ9Fi0Z7/QbRGgBCltcTBUuGIE489uHzeSYOYgMVpGplkyMTJ0ymGGHUS+ZAnQ0aURkP9rDnHec9oKDpwtRCnUI99l1ISzRywkaSl4V3wYihaLPadaGg01CZriYOlqDX8FdaSBjEB+g3XPgkaMnGydMohRp1E/LSVIyPKL9nnRU2TPzyzgUxI5ywOdorIaNJXZZBY5oCNJDnFjngxFC0Wsxb89o6Gao0XIgpriYOlWDCiVwvOQpavyPEu1CKz8jNkjpROa4hRJ5EPeTJkRPklfi32NJl+Gsik3j5KS5HRJEFBQod6bCTJKHbFi6FosWwxGqo1XojIrSUNluJnWgSU4GuDmHjEn4xMypATezr45YkMMeojwrnVVYrsPF1aSsunZzSUVg8+SkuR0cTKQ0kkc1uR5FLtiBdD0WJJIxZ6R0MRPphDkVtLMVjKmkESXKoEuo1Jb3PciCz4iJY4ErE9xKiTiOd55Oy8uCQtn57RUAzEwvahKWs0BiXRzG0kyeLtihdD0WJxa+FJ72goU5ejbOVmw1/sfpTgLGSy6OMep1Yz9A1iIjwd+HuRdBIhZGHQ2XlxSRk7R0Ods3bQwU7iJhKNXDUoiWZuI0ku1Y54MRQtllS39I6Gao0XIjqshcOL7viU0eDrg5i0wGRkkkRSZOKk0VAA/HWIUR+RDnlKyIh8NBQZ2RzrHg1lNgBPs0Ii0cjVjIS/W5FkkuyKF0MxAsuateyBUcQhRiIaR8n74sVQjMBSrWUQU6IYgaVayyCmRDECS7WWQUyJQttpFRWbYVZTUVFRUVFRUVFRUVFRUVFRUVFRUVFRUTEJfGdfACoqKirGwv9pmosw2lCDffGCRIn4W/iFnb0U/CL8zc5eAn7yIr5KvxQpXkLJvAz7EClq1TKEWrUMo1YtCbVqSahVy0bUqmUYtWpJqFVLQq1aNqJWLcOoVUtCrVoSfrRVyz8sra9Ip1c7znOfOaeaNs3xu/sQVn+SJZvEGdrzcYewTdVy8AGSPNhs7uaXcKx0LnQn9hVre9OBNjZy7ivNxpv6BEX1UWb5vlkrrgL7SLJH1dI2mSERN2BD1fJMZrKdfXzftvGjrVqQaS+jHIWdwKihmfOPP1NFMsKBTrXf7q4RbFO1IKFPyyjQeXj8b1okPdhXrK2rFigJGJCE2FeajTe1SPHIuqUonHXsI8kWVYtqA2jJUEilNxOTJ/TOn13yObaNNjZULc9kJlvZx/duG9OoWo7foew/cT08sZPXeDj8hVXsyTI9Fa7SIwJhtrtrBFtWLQ/xkUzjRGIstJ9SrtU3kBMe8eLN3mJtW7XACh7+88L48YykgqgfHERjxNne0mxTtfzXhdQtlnjz0/dI+dPbXC/LPfWyXdWSTCZDlEqQyTC7VRkOFh+/3FIbm6uW5zCTbezj+7eNKVQtKLDVl2IIrGGhkofDYzjKzLOyjRG2tBPDtlXLoRoKErphMUht/+Vhc4yEWUZmpV48ip3E2rZquWJiUVFmtWo+cLxVoSVgxE7SbFO1XIAZxJo43I+vRC8X4+nliVULqjIBicH/SRzSssoALUWvLbWxRdXyDGayjX18/7bxY65aBKtT1ClSDsg7DEHVs1Y4DO7a2NJODFtXLSIApIEUajMKlUhL0crQsZtYW1YtIGdilmZuPpCUViLmlWE3abaqWjTJmLjcsFpEmsz+enla1SKCSLGBGQ4KhMuxIlFAKC/FrWTYrmr5/s1kC/sAI1OwhOwgIoxmGz/mqsXsBLqIgI+WkNltBINkZrOVZhxbVy0iE9qWsBa1GaSjiMWXhBbsKtZ2VUumF6oiNx/KK3DDBnaVZruqRW5jSRwnkowWkTQ2VX2OXSTZrmoRrE4z1SAdVYnJ46CKklBbamObquX7N5PN9pEp4HuzjQlULVZABuSaOihKB3650WynGcf2VQslUWoRyTy1wOQeKspnd7G2q1pcLeCFHCoGbUTu7mwxesXO0mxZtTDRO55JZaLeVA+8V/dF0jtJ8qRWC0TIUlDNiCDuSSFbMm2jja2qlu/dTDbbx3PYxhSqFuZUAXWdh8c/yLlf1cISQB+pvt7GVIgnVC1euWvRiQkRtBmGiQVK7CHWVlVLKn6mpHc0cLekNNCeIqa2hzTbVi2qAJx5WuKrpaenxI6SPKlq4enqS6T1+gMSpgAPh9r3Y6B+UlEBW91M21Yt37eZbLSPZ7GNH23V8nzYpmrZClua52ZsVbUMwR5asJniYbQbtripnwFbSPEPeCWLz5vmp+9xC6/+9DOc4ml09AYufqJR7HgzbaxatsL+ZrKXfYxmG7Vq2YixqhaYTN7O3QN7Vy3yZCRWxaN5N/xoqpZnwAhVywhmspd9jGYbtWrZiNFaLaNh76plVNSqJWGMVsv+eBn2UauWjahVyzBq1ZJQq5aEl1a1/I/w9w8vDP8R/mpnLwV/Df9hZy8B/zMEO/sh8VKkeAkl8zLs46/cJfIFVS3/Ev7tFy8Mfw+/srOXgl+Fv9vZS8BZCHb2Q+KlSPESSuZl2Mevwv+qL0TDqC9Ew6gvRAn1hSjhpb0Q1aplC9SqZR21akmoVUsXatWyBWrVso5atST8WKsWG0703Zd0nCx90Os4qFXLFqhVyzpq1ZLw461aZJTeGxm0V6uWHwK1allHrVoSfuRVS3PO6RBWtcy+WsalmJrm9fug69o0zTGX/PF177bBSFWLJPzdUxLuxyhVyxeX99DQr821J8YxHV0/62tz7Y69b+o3XB0xjbLfDXtJ8WYZB8B+8dVe5bRX1eJSxJkFu46038s+ki7kTrbXkx2we9VyxalMWrXMP/ImnssA5ZOlLFj15rfU0CP93/iksC0wStWCooEMs6unJNyPMaqWOZcARG2857QMwxhVy3wkWfauWtRs8JrtcwN3wu5SwGL/Nd5OsZyy+YFPwu5VSy7FwWI/w93dPnIpTpZ2+5r7qdilagmf7u5sikH+QiR1Dq56qVyF766JbBG8jRijanEZpPbbG+O9EOXK2QcjVC0jvsnuV7UcLNQ64nFX7C7FPx7yIZjfPrvXc7tXLbkUP1zVkksx11mSqGGer2rJbEAtdPbOG3DZ1Z1upDGqlkw5Y9w/o1UtaEa9kJnPfDD/lk3/vd9DgP2qlmgl+1a7e0nRqlryFWGfhr1eiLKqZYUn8j/vXDR72UfSxXwZ/vTz22xC+NMwRtViPnrIbp/zHe6kMaoWr2dfUNWi80k/7vreWmKEquUq/Jmqwavj3u2o/aoWagY3Eqq5F1O16CvaThinamlmKJvZG1ldcxeMVLXMLrlI1w9atfDd9Fsah1y4xBHvS9QK/D/Rap5wg4/Tavn/2nsb7kiOG02XbN1Zi6b8cTjati2rl+uxZWtt7hEt0zrS1bpHmlaTs7a672i1Q7Xp/P+/4wKBiAAQQERmFtnNLArPOWpW5QfiDQTizSyKFZkV7uJtlrv7QASCdi5ayZ1YC93y30GKbmktGVVWO3Bn1gJWt/vH6DuyFmLnz4h3Yy35JmHnq896a3m93ImUmpTbVWvmDq3lFtdDyR1YS1ZyF7/9uRtrue3vxe7IWmAi3UbHnVrLztVyJ9Zy6wv0g7QWvF3CO6cdR6bhLqzlHAXBZyJ6iOBtuQNrgbqdcKnaO1gL6pbWcgqZgTve9D8Zb8HuKs6usP2XV1cwk/A++wq53O2itLu1SBVQLS9hbMSaeOvYvT6kCvyk+vnFM/hElHeu5GFay51yh3ctd8RdWMvdcTd3LbdlKyq2MDLbqI+wllnCWsaEtTBhLUxYyyxhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashQlrmSWsZUxYCxPWwoS1zBLWMiashQlrYb5v1rLD1/Jen7Xs+h3B11Y6Owl6LZN6tZKtqHgNI7NaxWupj91UfB+s5Zz+7HSHyfMarGV3MYm7L53bCLrbSb2rkq2ouMuR2VXF3dbHrVTspbUcXz89PLuebp4cHDyhHwitb5Te4AG/gj24rs8pfjkQH5wNCfp/ysaFLLGWuxCzfPmqBaXzBgXNTOo3pGQrKoYj84ZUzNTHm1Sxp9Yy3byHnjrhuk9pzbvyDZB3r9Fo8QDYk5eyqd4rNy5imbXcWkzetoRF1vLGBM1O6jeiZCsqZib1G1Exay1vTsWeWgumBHKS+p++OFu/bJeWVcgH5DTUBMmNi1hmLbcWc5rGexGLrOWNCZqd1G9EyVZUzEzqN6Ji1lrenIqHYy3wD5I2zidoGTtby1ox78BN5qLvL+5qLa9H0C6T+u6VbEXF+kl99yp2sZbXpOKhWAt0m77/nb4HviRBS9jRWnYSU7aM2c1aXpeg9ZP6dSjZioq1k/p1qFhvLa9NxYOxFsjMNOHiBfi5UefiZJpurtMvo5oEzbKrtawTA7ekLy6eL1sLe0dreU2CdpjUr0HJVlSsntSvQcUO1vK6VOyltbwxlljLm2WBtbxBZib1G2IrKrYwMtuoj7CWWcJaxoS1MGEtTFjLLGEtY8JamLAWJqxllrCWMWEtTFgLk1RcTkEQBHfLPw4O/jj92z9vhPc/+G/51Wb4lw9+nl9thZ9/8C/51Rb4rx98kF/dJ1tRsYWR2UZ9fDD9n01+CgmCYK/Z2u9agiB4EIS1BEHwGghrCYLgNRDW8iB59E3+JT3w6gen9PfbMxx+MaXv1xeWnZVpT4Ytj/EBgJezX5A9+pgeEB48MMJaHi7nxRtWmwR+dWTdWQY4+28/Qn9pv2dS4yPZAsNaHiBhLQ8XZS3Hz6fpM7qtwO/DTy+f4JtTuKd5/Ne8J3kJLhAE3PxUn/WbtGwQHXJwArufXMOGd3Blsps/15MZ8Az55TVewozjF+DMsJYHSFjLw0Vay/Tnt47gDgFuF07gI9KPDvAN7FR7yB3kXQvvy7HoEAiB/P70xXtvpUj1ZAbPnl7QxyFa1iwHVnctCBwZ1vIACWt5uKi7FvgBjvAUbyfSd+nptkLuyW/aD0S0r7UW8XsV2paPFrwLdzxA+gp+ukmhpsNavieEtTxcXGuBO4i7sJZkBvCOgG356IbH+NEHmiqAI4W1fE8Ia3m4uNZSZja8gXku9+Q3vrXQGzQJ+JGtBVwKb15oVz66gYwMhLCZhLV8Twhrebi41pKmdgI3qT38pv4atz3r6hq3ZWvBBgjYlo8ugKcQ6ZMT7CSyqdVf4/INTbjLQyOsJQiC10BYSxAEr4GwliAIXgPJWj6dvv79Rvj08n/lV5vh2eUf86ut8MfLZ/nVFvifl5f51X2yFRVbGJlt1Men038eHPzr9O3zjfAf25FS+Pv0dX61Fb6e/p5fbYF/n6b86j7ZiootjMw26uPr6dWmPhBt8LNZrI07JtbGZWJtXGZrv2sJa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIXZH2upX8NXy2zswuPrtAzRgJ6U8u37/GV8oKqib/O/ffbXaXr5W9rXcISLwV7+KL8DbLTT/tf6+9ZCK75+mN9lOBIuOksLxxrmFY1S5ZZOkw9CZsV2WjAryO1rwpvUbtdll/rhWiW6X91ONCpU+mwudfPdXJusHBy8mzbRwpy25hpr0YHbGlPRnaYKMyr0G6Spj9m8LypZN028yeZimbW41biW4+vpL70xrPStRSyZqHj0Dao7efFjeH0qSu68GCFU4xPoxLlYdNFEO7/53WprwcWn80tBjXSSVnODiVEn+nJFM6kaXpUoH4TKik3hckF+XwlrLbbrTZdMuJGSDPWrWwdShWrLyaVq3uwfaTm+foVT/HHqoK05ZS1t4KbGVHTb1GIV6g0h62Oc98SSkjW9AeQmJxcrreX4+unhx3j+4a/Q/aDPtO3serqBN0/oB5Ks9jNptT97C9KkxVlWWwtkvnYfs1LflKzUbeecsSYayjpZay3H144ijlRmuJjpyxXNpGpkLSofRG7PpnCxILevBWMtTtd1l2y4kRIi96tbB1KFSp/NpW7e7B9pyVUC07meUA9DpLXowPhS1piK7jS1WIUjSdbHOO8ACxuUrJdGZ5PKxWprIV86eYGmQS6H2+BuDJccA1s5zS6crVT3pRVn6VvLzcXFxS9NZlRnwNp57EpWapsnLEZHSxmXw67pWMvp9IdftbePIlIRJgQuVwSMUjWwFpUPomTFpnCxIK+vFWMtTtcTtRkbbqQkUWL16qBVodLX5NI0r/cPtZxcT5/95IuJlauaU9YCcGBTYyq609RyFUZSWx81xO4lm+DeVPQmnYtl1gKuAUAU7XvkOXlbboW2nU+XUAEXF9fVlBKOuIaulENo4/DxtdSOVC8HgwPw6RRwfRO8X+1cjo2MdpJCrLaW8+lL6jbPHxUJHffiAkZyen+tImSUqoG1iGsbwlkBuIm1gpy+MsZaZNfzlkTtkgi3RAlS+9WpgzXWYnqT9y/Kytl0Ax2jyamym+hZi60xFV2++ae1KtSbRM9adi9Z3MtxGN5kc7HMWsRdC/UPPhUlOtbSXq8KjriGGSlw0VJepWwSwEd25Zds+/mUU1OOaRd8/rwCIDNXX/HoCLrWQsXOYd1IInlLFeVX/VT1raXNByGyIptYLsj2VWCtJSO6nqhdsuHmlLT9Ep3IrLKWpnm9f6Ql65CTE3bz2R1rcSpDRXeaWqzCkdS3ll1LNtGkEWk3yVzsZi15C/3w7lpEHiSOuIYZKfQRrEKfvgRif81KzX3tRUFGW33Xkk+2LqojleEEVikapaprLSYfhMraLinq9hXpWovoeqJ2yYabUTIa58wKazHN6/0DLfWlrG+ppfuBKKEqQ0W3TS1V4UnqWUt3GOdLFml6g7SbZC52sxbox/Q53jnhDs9a8ICXeG8lSuLs6grOeHllngIs6Uk5xzPhNukpxoObr9R50RHYf4Pm++IHIITuqAjIDWi5gXPTsXSqikasthY4A7weQmP2iyIkRzqFRqG/+Eup1YpmUtWzFpGPGrVkRTWxWpDsa4u1FtH1mhrVJQ63QInqlzNyhFSh2pJvckDVG96/QAv8e/P5xTP4+AGbVHYJaS12EHNlZBUyunizVoV6Q8j66OS9qkgsKFknjXKTk4sl1vIm2ZCUQs9a7o+etdwP3buWN8pWVGxhZLZRH2Ets4S1jAlrYcJamLCWWcJaxoS1MGEtTFjLLGEtY8JamLAWJqxllrCWMWEtTFgLE9YyS1jLmLAWJqyFCWuZJaxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwScVl/qO7IAiCu+IfcdcyJu5axsRdCxN3LUxSEdYyIqxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwYS2zhLWMCWthwlqYsJZZwlrGhLUwYS1MWMssYS1jwlqYsBYmrGWWsJYxYS1MWAsT1jJLWMuYsBYmrIUJa5klrGVMWAsT1sIssZbDL3BtXeDnecNO4PLAuDBvb3Vroifl0TdTkiAffXuGa38/T4sC45ubzy+u3RXtT7DlST4zEh++Nr24uMiLiOOjT+rCzoautagYyFmSeAVt0drIU6+/VpHqn9dZiV86qvWMTNE6QaZ7eLo7ds6kdgZDtjAqBUeJiuYpRZQKOaD2hKZ5M4yMLQwdzexX1qL2mkO1ClXLmrmM2A6o+hANe3mXoUbjMtMB59Rl1mIGcmdg1nDhO/StxQx9fjpCepJAef6BXPu9jFI9jsdNPS4BuvfEeQ5CpWMt9pELBfkkCdnqSJHqX/fpo5nhVUm2LlOUWSqo7d7J9LTz0ANjLc5g+F3mUhgo0dGcOIRQoQa0e0Ju3g5j1eIUhorm7BfWovZ2ayyrqHHrIYszYjsg68NpODeZ8IZK7h/lgpBH6zcrreX4+ku4hcFnuoFRPqPr4/H1s+fTS3CsJ19MN/AjBQerRRc2ngR94cYdVlgL9AOfL52emlKexiLyXLLiPaiFnhkncLOW6ViLiVFQD/4Tj48ZKroza2la5xRllgpquncKeV1qLSWcGAyvBVkKAyUqmheHaFSUAe2fkJu3w1inE6ILw0ZrCqf5QKT2ujWWVdiBWpoRpwNtfTQNy7zrUITcP8hFRh6t3yyzFvpA9BU+mJUlFGHH9PTVvIu2nVITwpQy+YFNXfrWQl+mlI+rPTiCO8jcl/wg/yNrLd6TLc/hvMuLT6a6xc1apmMtJkamXgAOP7r45FoKHilS/XM7KxhYi7z8ICJF6wSp7tE4LrUWZzD8FjjcWAlH8/YTHWvpn5Cbt8M4mE42WlM4q62lJkEOFLI0I04HZqxFTUE7VGr/IBeZJpp4s8xaqkGUR5zBxl98BJ/vcIfziDMwo4y2Fu1MHjNS5MyBRmCavJs/Jx7BR8Hp5ZM/1QZKVmpCxMwoV4fexUfRtZYmBpGNNvM2fIau9TJSlFHO0NpEpW8tuvUmRchiQbJ7ef9ia7GDYVvQpTBMjYjWT133rsU/oTZvh3EwnWw0vX+ttVQVdqCWZsSrw5G1tFOwHSp/XBKjDiBN6B2t5Tw9Yo12+NYiG8nAxbhWdY8ZKfX2ULyUc5utr2alailjAJRT6qlO1iodazExEtBH3XMx2UeKMqJ/zRtJ11qa1jspWiRIdg8fupep6WUcayHEYLQttKWwIDUpWn9/x1r8E0TzdhgH08lGawpnlbWwCmeglmbE6cDAWtq8F8pQ9cYlMegAYELvZi25v6fppiRvyw0Xu0mfHQ+Ofo3/JuAcfnRkl56Usw+xDbB1lP/o+c37GC89nfMoTaejH8LLwzNR+jUrpOWQbtbSqfncw9/U2wKTNUH/17gcg8KmjaXZsz+jJFBXR3ykSPVPvXHoWYto3UnROkEmRc6dAmGtRQ0GhVMtQOymFEZKVDS1X9Kxlk7XuHnbT386Od1Im3XhLLIWq4JElIFKLM6I7UDXWlTH/VC9cUEGHXBO3dFaDg4e47Nh3zvvWcvBwTvP4Bp3leYIcUqXPef/G0p6Ug5/BQ1Ol++lN9Q1uLnnbUfPruG+TjQnQbE39DuGfCocD5s+S/9zF7KSkXlkOtaiYuSwEKq6weG7mIGOJKNI9U+9cehYi2zdSdE6Qap7xHJrkYNRwokWhqVglDRDK/ZLhIpmQE3ApnnTz4KK43TDKRxhLWqvE0qrkAPVMpcR0wFRH6ph1aQTajAucx1wTl1iLW+SDUkpdK3l3uhYyz1hreU+2IqKLYzMNuojrGWWsJYxYS1MWAsT1jJLWMuYsBYmrIUJa5klrGVMWAsT1sKEtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxSEQ9mDYLgrokHs84Qdy1j4q6FibsWJqkIaxkR1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxYyyxhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashQlrmSWsZUxYCxPWwoS1zBLWMiashQlrYZZYS10X8/28YTfS8p8vf5vfdRhIOfo4LeOZ3xGPy1NaAG8/gYuHTuIpp7zQJy0mmxaN7S5F27cW26JcuHXU3zlF7X5Nr3TcfpQUtU1onAZltLdxtd5OX7xJ7S9ge1oe3LkmNQAr6XeiUSEKY6ZrSBXW4Jyqe9ZWQGMtrMJJoE7CsAZlmSekMJvMpj702bavcn9/Ejkqxqcusxa7DO96Tl78GP6lhwD06Uo5sSceX09/qV0z++ti5I/Sk+kO88OcJPSMhuPrVzhGj8WS6IqetVhF9OAgKH8se9vfxYr6+wnfWrx+qBQR4hEkI0EqWumLe3Gx1qLywJzf/I6qel1qvH6JTmSkCtnrJQGrsMRIi+6ZrQBpLVKFk0CVBNvHqkLFIZQwm0xVH+3Zuq/N/v4kclTMnLrWWo6vnx5+jEEOf4UWBR2kbWfX0w28eUI/kOSrdp10GBXOrkNPSn2UgOBnb0GSc9fs/pKV2qJ5kAuMEO7JC9XD6KrEVTrWYlss9S7rXvZ3qaL+/oxvLV4/ZIqI3OnESJATDQ7z9Bhr8fKA7179QD0TYGlqHCWyExmpQvR6QcBW2ECL7plTk9JabO6dBOZGbB+LCieO16e6DZH1oc9u+6r39yeR15uZU9dbC5nTCT7hDBKCgXEb3MjhAyLBVk6TlUKT5MJNg+C0sl+WnpTT6Q94S9neZNeu2f0lK/WQ9tGcdTROrqfPfvJF9zGoHWuxLZaAYphVf5cq6u4v+NbS6UeNllAlOBRkozWPZiwYa3HykGtPVvXy1BglKnCmUVECzQc0wgZadM+cmmw+ENUQhE1gTYLpY1GR0HE8YWpeNfXBZ5u+Jur+/iRKNL1BBqcutBZwDQCiaHMiz8nbciu07Xy6vEBkLsGCgBedj5OZnpTz6UtqRBdV7ZrYD/8J3q9XAllcSPX8w7PpBtIisqLoWIujCE324gJCpU3c35WKuvsLHWvx+6ELgppYIshE6z0n1lhLk4cEPfS8VPW61Bgl4mpd6VjLbEAhbIEW1TOnAobW0iSQkwCwpEZF2qvjNMJUnETPWvQgVOr+/iRKu7WKhHdqeg8ss5ZqEMVa4FNRomMt3mUlc9op0EzfWqiaxOMnEdG1dj9ffLL65tTq8/mFzIqiay2uIkDkS/V3qaLe/opvLZ1+qIJQF7ehoDYaFDD112CtJSPyAJ/ErwCYBFdfpQJCFqbG9Et3ItO9axkHdITNDRNQrp+mAgbW0kkgJcH0sapIqDH0hcl51bEWdxCAGr0/iRJaRWJw6o7WkrfQD++uxY5GoXfty/Sk5NNaz6pds/trVuqw1V4g9MENGFQQ0bGWjiKgpDkh+rtUUWc/41pLrx+yILiJxEBQEw1q3psXia61qDwk9AVzWWpMv5pOZDrWsiQgIIXNDBNCPXMqoGst3QSmII6kqgKRYwh4wkQye9aS6d+12A6NVCCDU3e0FkjB9DneF+IOz1rwgJd458hVcA5Ho2O+aOUpulLwkeZXEAKV5wvA2dUVSHh5dYUN8n4YRQEcD1puYFeSV64dYiRg083nF8/gbjRvaOhYi6PoFNoBRen3ULK/axWp/Q6uteh+5KgqRdzEAkEqGo4mXvCuLkshCKy1qDyU/iG5qtelRinReRJIFarXswGRJGyBFtUzOIsrgJDWIlWoBFIoNR+EJKNCxqFTlTBnXsn60BWA5EHIodT+wSRyVHROLSyxljfJhqQUetZyf/jWcl9071reKFtRsYWR2UZ9hLXMEtYyJqyFCWthwlpmCWsZE9bChLUwYS2zhLWMCWthwlqYsJZZwlrGhLUwYS1MWMssYS1jwlqYsBYmrGWWsJYxYS1MWAsT1jJLWMuYsBYmrIVJKv44/ds/b4RPtyOl8O30QX61FT6Yvs2vtsD705Rf3SdbUbGFkdlGfXww/Z+Dg3+dvn2+Ef5jO1IKf5++zq+2wtfT3/OrLfDv05Rf3SdbUbGFkdlGfXw9vYoPRGPiA9GY+EDExAciJqkIaxkR1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxYyyxhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashQlrmSWsZUxYCxPWwiyxlsPyNExe93JXTjtPwKwMpHjPjCwPhqwSFz111Bw9ehxlx1p6Lc49BZNwnvipRQwV9UrHPtxTPQ/0Nk+KBXp98Sa192BW2SWv/xlnl+hXWbNVLDhNNCrUMKx8oqjEnNrK01lprIXP9p5s2yapPznGHTAZa+pDn61bafLpP1A306rQffJVzFqLGcgdaZ8KaelKsQ9+xNV/22dFikXO62LkkD1+jKUiH+2ElozvWtSy6q2i5U/81CJmFPnWcmwfYKqeB7rucagZ7l537Ky10MrY4E7CdGWXbHMjJapfj74xEgmpQg2DUyVqk8k1r2JvTzXymqxIa5Fnew9mbZPUKZa5DjgZk/XRnt0IVvm04zZSofrUU7HcWm71YFZc8988qaChJ6U8SkBinxUJHay5KFmBTNEr8+yKfLQXWjK0Ftni3FMwR4qUiDlFvrXUldpVSgA1x2vjwOIU2b4IjLUUO5KuK7vkNDdSovq1yFrUMKx+oihPJ3NqK89kRVqLbRhOr71qk9SGGqhQm7yMyfrQZ7etwAbuvjNuQxUJ6lNXxRprIY/f5cGsaRA75VnpSXEe/Ijo3tYOIiUr9RD5/DykHN0JXRlZi2oxwYpMf0eKlIg5Rb61dB7MikLq+OF1ZZmgRO3eaOyMtZSzZHJkl5zmhkpkv6DsLy4ufqlUJhoVPAyAekPUTTbXPJ0AfWojz2al+UDUNKwGQiepWyyJQQcaSYmmPvhsK1jm0xm3ORWlT10Vs9aCn8bSY0+Stgp5Tt6Wo9M258GsnadCNvSkOA9+RHRvyTLhGMH8g1k7oSsjaxEmnRFJrv1doEiJmFPUsRb/wazQSm4OrgHADk+KlX2xGGvBhtoHs8ouyeb+aYES1a9D+Pfw8bWRsqu1CGFNVtJufaqW52RlaC11IBIqSf1iSccOOuBlrGct3jDKfApJCzp571AAAFZmSURBVFVAsLStq2LNXQuduf7BrPCRFh/xBNWtnwrZ0LcWKvLBowHhGLmPL4RZfXNqPboTujKwFt1ioihy+jtSpETMKfKtpT5TT+UeyoWCFXZ4Uux47Ky1ZETdqC45zY1TY/tVj6vsbi1trgdXaiXPy8rAWsxAEClJg2JJDDrgZaxjLYNhVPkU4zajovapq2K1teQt9MO7axEtaDpXvkpPSnbH1rNkb5c/dRThozuhK31r8R4R2uRf9nekSImYU+Raize6sNHUcw6OLE4R0Rm7rrWUWYuoLtnmBkrcfolOZHa1Fpvr0XRyR05kpWstzkAQOkkcaqQCqZscSR1ryXjDqPIpJA1VyD71VKy/azld/2BWolOela4U+xjU5pmTNTvQYwEcD1qa52vqXNpnSiq61iJiuIqQ1N8lipSIGUWutWCg9sGsOAp4oUrPA73Nk2ITnbGz1uI9mFV1iZtboET1CzrxEnZPT1tPlyrUMCx/oqjR4pwq5REqK9Ja5NlqICiUfsZrwi+WuQ5YSbI+1KGJLJhCqXwKSQtUqD71VMxYy5tkQ1IKo9+13A++tdwX3buWN8pWVGxhZLZRH2Ets4S1jAlrYcJamLCWWcJaxoS1MGEtTFjLLGEtY8JamLAWJqxllrCWMWEtTFgLE9YyS1jLmLAWJqyFCWuZJaxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwScVl/qO7IAiCu+IfcdcyJu5axsRdCxN3LUxSEdYyIqxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwYS2zhLWMCWthwlqYJdZy+EVemOHnecNOPPpmSkH8R0QUelKcs8/Shqur/DgLXPhOrBYhOLlOS0nwIjXA42l6cXGRVppp4hi61iJiEMfY0HV9GIPZX5lRBHEmEcfQKx3TYNO1NYIWZ9eZ1E5GVZdGGXdSc4aLAz1Pq4Y0bwSLVMDZN59fXNMqQqMsz6jodsCxFiv4NrlQY9jLhVMfsuMZGX1dLpRmOFUWPbPMWlTndqS7Fruiby29s2nxMdD4RK+CVRfIyquTgTnVIfDWb+sujNexlu4acNAQVondv1KR3K3xraUrqKZojaBMObXNrqB7v2AzqhsQ+0dK6iZsX72RLFFRMiAXuZItLVaREaEz1lq6gnfKhRrDbmhTH17HnehLc5ERmnF3a40rreX4+ku4hcHlkcE7n5HTHl8/ez69BN968sV0Az9SE2B1aKjCk16TtYh1fnWOS268BRBp/WGFXOdZ07EWJwYB44h77P6ViuRigBrfWrqCctfWCSK62RX0JrWTUdUluX+kBKoWH0BDyyqqN5IlKkp0OUGlpMUqCKeD1lq6gnfKhRrDbmhTH07H/T6ypFW1UYtessxa6APRV7iiv/QuajY/AiHvom2n1JC834FEJNoF5zV9a/HP1hcgz1q8xcbxwSaXF59MvMWs1sh0rMXGyORlQu3+5YoOP7r45LqfKd9aeoJK19YJSvSzK+hM6iajpktq/1jJEdz018pVb5hFKvITuI5ohhlJK1QATQcT3u9arODdc9GMYScXtj50x5Em+spcAG1mG+NZai3VIMrauLDxFx/BRz6ylrQtl146GMwow9aS8QZEMCOlPVs+2aVjLXWrWMS0GH11YhWnoWstTQyimq/dv0rRwdvwSdpWTaJnLR1BuWvrBCGD7Ar8Se1lVHZJ7x8pgWKCkn+XflGg3kiWqTjCJ1G8fPKnOsNUlherQLwOOtbSE7xbLtQYdnPh1IfpuBN9cS4QpVnfcWR2tJbztDYv7fCtxTZFyJsuhxkpzdlwLyPaqVlIlNxULWVYgDK7yk8dp6FjLW2MBAQqjdj9axQhbvEivrV4IWTX7P6RIGCUXYE7qTsZrV1q9g+UqDty9UaxToWYjCLLS1UgfmhjLX3Bu+SiRhnnwq8PQHTcHfNluUCkZngtdxV2s5bcHj0/2LEW2JY+Bh4c/Rr/TZx9iEeBx3oyKj0p6uxHz2lh+NptwreWrCU/NpBOhROfvnVw+Jt8D9TEaej/Gpdj1LC46jzRtAEsVnT25x/CjqNv2pIp+KXjCEobS6vrBKlTkVXWIs6lcE2XmtgjJSQ7ndu8USxScYQiDs/oMm+zvFQF0HYgY6xFn3fbXORwNIatJMbWh+o4hVLRV+UCEJrhJRe9ZDdrOUiPtH/x3nnPWg4O3sFnPl8lQyAO8fmX0+V7+W2HnhR1du4gdKraFLzOlC4LxPP3S27wkdQ3+ZHUMo5Dx1pUDAp7miXkj4GyjYaxosN3MXkvRfI0vauSEdR0bZWgxdl1JrU8l8LpLo0ybpW8fSbGXr0RLFJx9OxaiBhleUZFrwPO71rkebfPhRrDXi4ca5EdL6FE9JW5kJqbomeWWMubZENSCl1ruTd61nI/uB9F3jhbUbGFkdlGfYS1zBLWMiashQlrYcJaZglrGRPWwoS1MElFLAUVBMFds62loIIgeBBs7QNREAQPgrCWIAheA2EtQRC8BsJagiB4DYS1PFge4ddi8x9PHxz8Bt60fy/Z5fCLdOapvzZQAXZ3/4708PEVNGj/UNSA35sbNRLsK2EtD5bja1xFJ3vL6fTq/3X/TH/E7tYCu/72I/SX1szQtFjFI1oqI6zlIRLW8mABa/nb4zz7T2BCn6dJDXcvT2AD2QIYzg/wGyKfJf955+Pr8mWRshtn/RGt6CX2HhyeXU83T+ggFTADliHvkI7w1Jd4FK43Asid1Ejw4AhrebCgtbxFfgJT/SlOa3gJ/6IFVO+Y/vzWEdw7wJ7TF++9hV9+Ta/ZWuAfvPNp9r76Ed5/4EEqYAHe4ddX02vQcfNeuV3Rdy1IaiR4eIS1PFiStYCpvPoBzOdXP+hYC76Be5o6u+UO+PeZvv9I28s9CR3kWsvBwbv4mx5sERpPRyclYS3fH8JaHizJWtA2/gafWchUhtYCb4i6A/79EqwgzXyxFwKn9TPooI61IPBx7OanYCkFkBPW8r0hrOXBQtaCU58mL1kLWQDOd/IO9INkLflw2lT/TR+IwEjk3mwPKkZ+oyEPonYzYS3fG8JaHizZDXDSp5sMmuI4t4GrtF4f2UK+a0kehNQdNOthL3yikXvzjcjnaeFCFTADTRMoAMMQ6CkQjX+NmwMB4S4PjrCWIAheA2EtQRC8BsJagiB4DSRr+XT6+vcb4dPL/5VfbYZnl3/Mr7bCHy+f5Vdb4H9eXuZX98lWVGxhZLZRH59O/7kpa7ncjpTCd9On+dVW+HT6Lr/aAn+cpvzqPtmKii2MzDbqI1nLhj4QbfCzWayNOybWxmVibVxma79rCWtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayFCWvxCGtZQFiLJayF2R9ryV+bbxfa2IHH1+nr/QN6UsrX7+WSZwfvPoMtYtX43tIfR+m4H+V3BK3X+iG8ckML+tbCMRI1T2nlgcRuimzPNL3SsWe9/au/Qszf5netYEErqO0LrqCbF8ZtaSa1GGOvlyonfT1OrXA0J9F9FU0KEm1vesPkqGg36VMba6mHejX29pkU5ucqs1JFUx/lUC9tsPcucuGFXmYtvVm3iuPr6S9WXEPfWtLSH5Lj61c4Eo9pNRLg/OZ3IivnxQhhWJ9AJ85p8RDiRAyyE1rRsxYZQ/Hom7JjR0WmZw2+tThnnbz4MfwLxZJaNoKHggjqy0mKCfUjSrIiJ7Uc405Qzklfj1MrXjROdF+FTkHC9KYzTI4Ks0mfqqxF58JktghLXbC9u40KWR/O2TJtd5kLQIZeaS3H108PP8ZsHP4KrzeQDtqWVng/OHhCP5Dkwp9JF/7ZW9CyVmJZYS0nlAKYUSkmxs6bEiUrkDZ6dc4T4/haFagJrehYi4ohgTKhBndW1PTM4FtL96xcOFbwSBBBfSkFIwuHkZNajLEfVOSkr8epFS9aTTTSUZHJKUi0vekNk1uxelN7qrIWeWi3xqhfTu9uo0LWhz1bpu0Oc4GoEVltLeSyJy/QNMjycBvchOMyZGArp8l4oUm6guqMtuIsfWu5ubi4+KWKdnI9ffaTLya6mUuF6mWltnnCYk6nP+BtMt0HeqElHWtRMQS1THZXpHtm8a2le9bxdRozK3gkKJH7UrpUu6ZoPoqUYG5QmZO+nkQ9P+FE02o6KjI5BYmmN91hSjRxEN5kTlXWAtRDezUG9yl4ttO726ho6kOfrdJ2d7lAVOiF1pI+RKGPpLYr5Dl5W26Ftp1Pl5DKiwsxoogjrqEr5RDaOHx8LTN4eDbdQG2m0jxJdp+yAtYpeL9exUWJn09fkuSUCie0pGMtOgZTLjy3UiR65tCxls5ZdAFQTSwQlCh9wavHxQXEbvqa6ExqL6jIyUgP7q1xCCeauhsaW0tJAaF60x+mdKxTsXWT6g3RsxavxkAGkJ6oInv3T7dXMbQWnba7ykVCh15mLdUgirXAp6JEx1q0fTGOuIYZKeXGDSHDh03QFnxsvwJgsK6+KpWXFdRTTjn7JQdikwqt6FqLjQFkVbdSJHvm4VuLfxbUTh5vK3gkCCl9KYhCEHTvWkxQnZO+noSuFRutETewFk6BIvVmMEwJp2LLJufUvrUQTo3hU+Z4+6JcJEYqRtbSjilx21wkmtC7WUveQj+8u5amRguOuIYZKeLy480H6d01K3XK1V6UMMoB9ZVN0LEWLwaKKRdVYhdFXs8UrrW4Z4HP1FllBY8EAW1f4DBvivYmtR8UyDkZ6EGaWmmjteK61iJToJC9cYcJcSq22SRPnbMWp8Zok83VbVQMrMWMKXEXuWhD72YtEGb6HG+jcIdnLXjAS7zREq2dXV3BGS+vzHOAJT0p53gm3CY9xXh0GcJ7uc8vnsEnADoESFmBWhJAbkDLDZyb5OUrGK4rD5tuMHMqtEPHWlSMcmE0tbOTIqdnCtda9FkUFUcBL0RXl5hzbmKJINmXU9gLY5d+wWaQk1qNsRcUKbU70CPj5FNlNCWO6KlQKShZMb3xh8lRYYtYzkRlLfJQp3xh0w3eIbxI/eDe3YEKWR/6UJG2u86FGZEl1vIm2ZCUQs9a7g/fWu6L5n7hntiKii2MzDbqI6xllrCWMWEtTFgLE9YyS1jLmLAWJqyFCWuZJaxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwYS2zhLWMCWthwlqYsJZZwlrGhLUwYS1MWMssYS1jwlqYsBYmqbjMf3QXBEFwV/wj7lrGxF3LmLhrYeKuhUkqwlpGhLWMCWthwlqYsJZZwlrGhLUwYS1MWMssYS1jwlqYsBYmrGWWsJYxYS1MWAsT1jJLWMuYsBYmrIUJa5klrGVMWAsT1sKEtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpgl1nL4Ba6tC/w8b9iJ42taZlgsD+zQk/LomylJkE/FPcNlpq/zyt4nGH6iB7A12F1nKdYVbMTlgwEQ1xXWtZbH0/Ti4iIvRE6ITZ7iwpyiM1zV/Hla7tjDLx3TqRVRney1R3dT5ExqNTIJPLuOvnrTMKfEhiaUCnyWTVkE2gY0ldjtmoxD6GimApS1iLPdHs/tL8yosBlR9SHO7pRk7b5TQYxVoTbZNC+zFjnQtwN658hm+tbSFlN5yAStJJ6fkAHhy1Sozzmwuwr1sRon01O1JLqiYy3iIRcFtckqXqyo7m+GsjC8KtVOMb2oI0Ht0f0UGWvRIyNRPZZvlirphxYqoF6fVN1OQAK25Epsula1qDiEiuZUgLAW52wlYmb/UhVeRkR9qLP9x8Oakc3hkZEKtclJ80prOb7+Em5h8Hl7YNfPyN2Or589n16C8z35YrqBH2nAwMTwSmM8CTJxR9ZSntmSciseT1PSUrLi7MrUB/GdQoTOvAE61kKPmlOoTX1rmVUEA4RPzvYf+wOMrEU8q7DQjToS1Bw9SJGxFjUyitoQIt8sVdIP3agoNe8FJGoltl2r0wnR00lHcyqg+UDUTEbZ48Rg/1IV5Y3MSFMf9WzXWszIygoaqEiUTToxxDJroQ9EX+GDWeWQUsD8PN28i7adUtaFKWXys5y69K2FvkwpnjqaH+t/hDn1ntuZhXafOlp8nkSuthZ8xvXlxSeTHAi5ySperAg6Bff/tnALA2uxl/NB1LEgcfQwRcZa1MgUDj+6+OS6JEO9QRYr8UInOtbSzTVESr2xXRtMJx3NqYCutZgeJwb7V6gwGelbCygGRDO2+6qCBioSZZOX5mXWUg2iPOIMNv7io/xIZ+cRZ2BGmXpmQjuTx4wU1e8j+Kg3vXzyJ4hZe81JKllxdiXKE8bz/s68AbrWQsUufNrZJBUvVYTpg9F/1/mNAtG3FvnY9Mwg6kiQPHqcImstcmQkb58JZ1Nvlirphu5ZSz/XFMDp2mA66WjOcA/vWlSPE4P9i1U4GelZS0aUZN4luq8raKAiUTY1khI7Wst5et4a7fCtRWrKgGnqzDrMSKk3XkxqvjZYhpuz4uxCQAxtxmf4ZahvLR1rKQUlCsvZJBUvVeTdXSq61lJDMKOoA0Hq6HGKHGsh+DpUUYUr3ixVUrChO9bi55or0enaYDrpaEWQEDb+QKS7Dwz2L1aRkRmZsRZRkqb7TQUNVCTKJk/SbtaSI52mm5K8LbdS7CZ9Pj44+jX+m4BzOs8ZlfSknH2IbcClC5U/eo7PLz36Ibw8PKOcUIOH4vNWzYraRacmNWU/Ia9bmv6vcZ+Cp/0mXQIorNqkFCeWKqIw0EFrFETPWkSnFkUdCPI0dFJkrUWNDCk5+zNug2gYQr1JLFaiQks61uLlGiK2lSi75k8nOlVFI2V5uImetageUyjE359YrMLJSM9anElE1O5Dl2S7QxXpVdmkJBG7WcvBwWN8UOx75z1rOTh45xk44VXqC3FK5th+RmroSTn8FTQ4Xb6X3lDXjp5dw41gbQEV3YhPkQKxK2cFUsiGn1htLSgAwn6W/kdeSbbYpBS3zCh6+2xwbtdaZIi1Ua0ge/Rya5EjQ+EO38V6yNvUm5axkmbQGaECOp3Bs21ApxLdrqk4WYuMpoabENaizlY9zhnp7tfMqXAyIupDt2InEVG6D0c306LgqFCbmsQgS6zlTbIhKYWutdwbHWu5J6y13AdbUbGFkdlGfYS1zBLWMiashQlrYcJaZglrGRPWwoS1MGEts4S1jAlrYcJamLCWWcJaxoS1MGEtTFjLLGEtY8JamLAWJqxllrCWMWEtTFgLE9YyS1jLmLAWJqyFSSriwaxBENw18WDWGeKuZUzctTBx18IkFWEtI8JaxoS1MGEtTFjLLGEtY8JamLAWJqxllrCWMWEtTFgLE9YyS1jLmLAWJqyFCWuZJaxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwYS2zhLWMCWthwlqYsJZZwlrGhLUwYS3MEmupi2DWtTR3Ii1x+vK3+V2HnpRH+REqamFdXJp0Ek+ZPO082bI9jqhHzwjrWIurKC1xWtaT9ZtNzCgCHpcnuzh0S+fo47ROan6HqBVLzfKlzJwg1TGNN6n9w0X/rNKCp0Qe3elEo0KkzwZ8G9eIrQO+Livt0brmGmthFbrJhNmkQ0naYtCnGpVNfeiznVZ4k18GGaNCz5t2SJdZy3Cl7IWcvPgx/EsPAejTtxazhjvMbVpEvOw5v/mdyFpdjNwcR9Sj54R1rcUoOr5+haPymBb5N80uVoTro/+lGUdJx1pOTBfoiTN5MWX1JrFYkOpYi7WWzuHcP6N0qEQebTuRkSpk+pyAZcDTpXJdVszRuuaUtUgVqknCbNKhqgqnGNSpjkpZH+3ZjWCkbrKhlqigwbHFt9Jajq+fHn6MQQ5/hRYFQmjb2fV0A2+e0A8k+Z9c7JyAUeHsOiy3lhopP/oEnyggF2YvWWmPI9qjB8KWW0sOmB4l5zS7XNHP6mPFXHxrkU+iIcoDZ9JP9YZYLEh2zGCtxT1chLNKR0rk0U4nMlKFSJ/fNQT2wJZ1WWmPlmOWkNZiB5GaVNRNbaiiol8MdKqjUtWHPtsIlpucUItU4DF2SNdbC5nTCT7hLHs4boNbX3xMJdjKabI8UEHXraZBcETVL0PfWm4uLi5+KaLVjtKzIFPfvLFpjiPM0QNhXWtpFUET19NnP0kP+/OaXaWoHuTgW8vp9Ae8TxZ366VW0k/1hlguSHTMYK3FO1yGs0pHSuTRTicyjYoSyO1agh4nti4rzdGmipS1ADUE0T7hDCibTKiiItHEIehUr4NNffDZVrDc5ISaVVHmjR3ShdYCrgFA4CSkQp6Tt+WGadv5dAnzLj+5NQMWBLxwP69XulIOoY3Dx9eclnpNTImgR3unFMFtneB9fRwhjgZmhPV+jWsUwduz6QYSjPmVzf7TWkWAN44F31rOpy8xGnS/1gO6/sUFKMJN4s3qFImOGRxrsYercELpAiWqX6pHko61eAETdFlcmxXVvBmzGWspTQrKJhGqUYF7mzhEPtVT2bMWR7DcJEM1JZs2tyogGQDNG6f4lllLNYhiLfCpKNGxFnENaDm1+ZXMSBH3rfUlPTr0Bh94D329+ionmC8+4jjCOXogrGcthFAE+U0tpPw6za5S5FVToWctWCUyakEMoHqzWJDsmMFaiz28DdcqHShx+6V6lOjetdiAAMwKClpYlpVCOtqrooG1mCbFJidUUZGwxVBP9VR2rMVpRW1yQs2oQGjeOIO0m7XkLfTDu2uxo1FwrFsyI0WeXQu4qoPd3GzNinMcoey7L2xsLeI0PTS22VWK/HEkfGvJShxb58/OgHizVJDuWIuxlv7huX9W6UiJ1y/Vo0THWtyugee1p6/KimpeVVHXWpwm7SYZqqpA2mKQpzoqO9aSUYKJvMmGGqogaHicQdrNWqBops/xvhB3eNaCB7zEO0c6HDmHo9EeXzjymJ4UOPvlFdwmpcf/ZsuGNm5gm+hvShHkXQA9lcfJa0dN6FhYx1ocRfDvzecXz+CTAB7Aza5VdHB2dQXJfXl1VatF4VsLnA0XH4iMg0tRT6EZCJR+MSbfrBWkO9Zg71rU4V7/WOkSJbJfqkcSqUKlzwaELbAPuIT967LiNF/6lJDWIlWoJh0VRAplVMg43qlSJSHrw5YSjykmN1H6wKEWqNDzRg4SscRa3iQbklIY37XcBx1ruSestdwHW1GxhZHZRn2EtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxYyyxhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashUkqPp2+/v1GuNyOlMJ306f51Vb4dPouv9oCf5ym/Oo+2YqKLYzMNurj0+k/w1rGhLWMCWthwlqYZC3xgWhEfCAaEx+ImPhAxCQVYS0jwlrGhLUwYS1MWMssYS1jwlqYsBYmrGWWsJYxYS1MWAsT1jJLWMuYsBYmrIUJa5klrGVMWAsT1sKEtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpgl1nJ4Nw9mRU67z57M9KSUtTp5beGEfFbkumd9Si2DR3MCfWuxLaqWBk+5NLt0/5zHeErc0qmjNPGap4h6nGb7bM2Kp1V0byTIm9TmwazN+A2e8zqj5C4ezLq4a86pSrnpRmMtrMJtRXZrXUbk0fa5wk19VBULJlF/irYqbL01xbXMWhotO+M8FbKhby28gHfhWD4r8qRNWF2MHBLaPG4yUbXQYuSQKTUjmZ61mBZ1S7bZkSLVP+cxnorhVUktQK9SpN4gwxTJ7g0FWWs5tg9mVf2z+5cr6Q2WVCE7ur5rIy1KudNNaS1ShZdAqWJdRtTR+vmoCVkfOhciCZm2KDqPh/XSSOR6M8W11lpu9WBWXPNfrX/usMZa5LMiy6MGmJIVKEN6pR4wwVrKVFRTUtKxFtuiaslpdqTI6Z8zfzIja4EayM0g6nGa5tmaI0G2ez1B1lrqmvHcmLZOs3+pkv5gSRWiozt0baRFKXe6Ka3FPspUJVCpWJcRp+F6GCLrQ6qYm0R4hP94WE8FUerN9na1tZA77vJg1pRLqdujby035jGoQO3Numd9Si0la2pwJB1rsS2qlpxmR4qc/jmP8cwMrMX2oraGqDdDQc6TNjuCrLU4D2bV/TP7lyrpD1ajogTaoWvDwlHKbTebD0Q1BKESqFWsyog9Gm4nxLxq6qOGmJtEcloQQxWIHIimt8usJX2iQh/Rhk+ek7flwLTNeTCr81RIh64U5zGoQO3Numd9Ki1oje6zPjMda7GPolQtyTcLHsxq+5cfGuUxsBZzVdEDnt8sSJHtXk+QYy3Oc1xV/3j/WiXdwepYy5quLdCie2a7ObQWnUCtYlVGdMOQEkA+V7hnLXOTqP94WFcFIutN93ahtVSDKNay/sGs8MkSH8oEaeDHWDrMSGlvhGtvShf5gX1suPkU3uVqEb3UdK2lbVG15DQ7UFSou6BeWo9g+taiLl6EGnA9+iNBbff6gqy11KfwmSqgluz+NUoQO1jdu5bVXRtrSS9JudPNgbW0CVQq1mbENAy7uamutRA1ZKbsd6bFXMlmJUTTzm7WkrfQD++upVHA7HzXQrRXztqbvEN4WskKD0TtRUZrKUNt6FiLbVG3ZJudV1SCQtF0xCS61kKfRjVqwPXojwTp7o0EGWupYWwVpKjO/uVKCDtYHWvZoWsDLUq5042+tdgEShVOqKUqCjlcYsZa5KFIs19Oi5mS1fXWxNnNWiDm6gezErtai/dgVvXMyXXP+kxkLd1nfWY61iJarGFlS+LNAkWqf5g8vH6IZ3YqetYiasZLEb9ZkiL9ONSBIHvXAhHaB7O241f2r1dy+wez9rq2QItQ3rwhpLVIFSqBjgoRaq0K/XzUhKwPqWJ2EiXStFgyLnBkepuwcZZYy5tkQ1IKPWu5P3rWcj9Ya7kPtqJiCyOzjfoIa5klrGVMWAsT1sKEtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxYyyxhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashUkqLvMf3QVBENwV/4i7ljFx1zIm7lqYuGthkoqwlhFhLWPCWpiwFiasZZawljFhLUxYCxPWMktYy5iwFiashQlrmSWsZUxYCxPWwiyxlsMv8mITP88bduLRN1MK0jy2oaEnxT0b17qrK0Y8nqYXFxd5PRnFyXVaakItYpMWnchrx5zh6hfXzipKRMdaXEVShN9swu5qoqmeGXql46RABhr0c0YQ5grXBHHX2vEmtVWiGr9Fas5wpaDnaQkRhVVxls66gmBpcRGk2dTPslXRnNqpNsdaPMHy7FWjoo52KxBx6sO2ojo0HGCTJjg6LRFDR/cGc5m1eDWwFm85cUvfWszZIOtJXdhKrUGWqAtk5bW4YCDkESfTU1oKqpzZrr1V6VqLo0g0YZsdKVLRVM8cfGuxKVCBnH4uFkQ0GSzYSW2V6MZvkZq6v81O964lnyGhTTbLMyWDlFPNDsJaiyNYnr1uVPTRzhARpj6cVgq5kYTsb1XRLUY4Gl22m6uV1nJ8/SXcwuAyvGC7z8jBj6+fPZ9egok9+WK6gR/J1cHK0KuFJ3UToVhhLUjtM60YLCm5cZf7gzfvwzm4oezvlstya5EinGZHikw0dzQzvrXYFCRKIKefqwSJwzR2UlslqnGnucVKoILxaTSzC1hW2nWiAbFJZ3lcMkg+tZNqz1ocwV6ZLBsVfXRnTjj14bSSUempLQJFRcItRggG/XBUZpZZC30g+gpX9JfaKGx+BELeRdtOKXvClGAH/R2NWP/coW8t7tm1z+ew7/Lik4kzVXLjLUZOuvIClvmxTUcm7Zn+B6JWkRThNDtSZKKttxabgoRIUdvP5YIOP7r45LozdHZSO0pk47dLzRF8uHBmdsdanOu03ORbi6ciUU7tpNqzFkewOnvdqKijO3PCq49ejddcmAEuKhJuMdJyud1cLbSWahBlbVzY+IuP4NMi7nDWxgUzyrC1ZJyxlsxIac8W84YGz7sQ1r6z+adNZcMRfJacXj75U5P2wvjXuFKRFOE0O1BU4Gj1IIeetbQpSHAg089Vgg7ePvOmtG8tVolo/DapgcqC+n/X/m7Ctxbn0Ulqk87ynIp6aifVnrU4gvXZ60bFqdV2Trj14de4To8a4KIiodOUKDcZ/RHb0VrO08LHtMO3FtUFgbzpcpiR0p5dO1YGmQe75KZqKSOKWajwgLNrNoytRSqSIpxmB4oKHM0ZzYpvLTYFiTaQ6OcqQYAzUQE7qTtKgNT4LVJT5ZjQrrXAdT0HruhNOjkzKvjUbgeNtXiCvbPXjYqqVTVECb8+gKbGTXrEABcVCVOMcGbW1Fe5m7XkePSg2bwtN1/sJn3CPDj6Nf6bOPsQjwL7bvOk6ElRZz96npZBx1elz6DoKRTtb9jBa25IS36+HJ9affboh/DP4Zm5DhY61uIoUiJUs4mRIpMdM5oCv3RU606KbD8XCzr7M5579A33RWAntaNENb57aihyklLOyHjWAkeXo0o+xCZEZ3lcMuJU1UGJsRYtmEKps9eNijra1EzB1oc6z+mQHeCqAqlpqh3ghxjYwczsZi0HB4//Ok0v3jvvWcvBwTvP4J7gKnWeOMTHUHaexc/0pKizawczKQv4kOkb/ZDpAorND8AsaUWKtTy7hntFobShYy2OokaEaLbFKFLRmp4Zelcl0bqTomE/ZwS9i6PZOdeb1EZJ0/jOqYG7dvmOcVRA7+uko1Bq0zDLRoU6tRloxvldixScQ8mz142KOlonRuBYizzPy0V/gFWa6NTTvCH/uqMzmEus5U2yISmF8Qei+6BnLfeD+1HkjbMVFVsYmW3UR1jLLGEtY8JamLAWJqxllrCWMWEtTFgLk1TEUlBBENw121oKKgiCB8HWPhAFQfAgCGsJguA1ENYSBMFr4OFby6n/zZeW5rCFZ2XWHT3i+Nr8VeOQu2u5yy5NvAFZb5TX3Z9z+2W7vechWsuj/I1Q5NUPFlYFHXYIY5wWvFpXS+3R5S8YTb3U+Aic1R4FzoJ/2gw/Mje/zXs6rNM5g1JX2aWJ7jnUs7yP3qS/T30tpO+KJae+bZrWnA/HJmhYy/fVUEZ/DxRM+52BvefB3rWcl2JYVVXoCanUb1WLNYrB7sEt1VvKbphzVGmPlfE43Epni6/7TptA7/xT7hNcAp7CMPmZugtg8uZV4W7bh9Xnl2HNJ8KP/A2Zzh6QWg54KHwvrOVlujqkoYN39c3p9OoT8QaOx5U0ABh5dVaOlQ6BIrjBs57qSLkxAqsHvxlOnORbELg6cXwGttULFk48VFmtpZSciIGy/0d6g4fkloUYeJliJNGnaW1B4BV+qT7vaYLVHLTqsBtE04Q6S8fLkCx9WAJ7+F++od6dww9oE62lGzzvaAX0T5BA8n4PB0ID8O8oTU1KbM7gaCqHJFweXcoBXipoWME90xnws6bV3eO7+l7zvbAWKhj4UQaQJqzcg//C8XWE1b4ciw6Bc6enbx3mKqZt9C9zeJZK7wVWU94Hcwoi2QqC2LyFmpPWQq9UDHiDO0FH2aO7RWprF3FmwKb8g8XWYNgi/dDq8juofdOEOkvFy9A2dRgBR/3tLQhC572Pkt4fBIfGUTigjhmokcBudFc4FP5p+pDf1AgqJdhmm7Mm5+Vo2CTKoQKnYXg4Bs9LScSm+3ty0AfE9+YDEZTAUzmedGdS9+Q3pfr0vhyLttEm4J2P6eIF2/LRirT4zqsfYOlkoOkaPwOCUgFniuiiM7/SMXJjog+6W+lfelmOlT/cYNQpra5EdZqQZ+l4GTpABScgDvQX+olroFJqcdm5XnD8F+6jPsRV+8QxgxMksAV24K9I0yH6rPQOegwvdRdyOPUjv0ln6qNtqwDEpmHVTY72QAs2zl7zvbUWriEqDnqz3FqwJN4r2/LRDalqqHgLevLiO7EzxUn1VXSmI9LlVhyWG4NjYGN6o7uFCv/2J2onHyt/uMGoU1qdKPq2CXmWjpehA1RwAuLAzIIoNDGNtTTBkcPfYJbUMeMTKrAFd8AHr9/hK30WnoafauEINyXqR34DEdoRta2mNOYjoKn0Ck5EQ+nvKS08IL5f1oJvXv0Il7zBKdTuwTflNLUP/n2FFZW25VrCOv3pwWO4CMG2fHTh+NsPfwi3LXACnYwedPjuczykygJgj5jJSKkzDA7FjysKpiNUDGgMjsI+1JbhX+4WHZFEFmHqRxsM9+ROSXVp399+VLoNbzqZU/EydIAOnsg9hE2kNVlLP/jxt0/ghqUYiDqmo0YCW5IkaKToEWlKPaN8w4EmJeoH/Ms5V0e7rab4CXgDTUKv0Uf6e5KYuuth8GCtBS51WBm1RHIJHOK6NXn5HLUnv0lmAeXWnAUfbl68B2UA2/Kmg8NfwZGXP0kr+ZWTC+9+AvvqIj3v4Do8N5/9OL3J8QEq7UQpzlJgWMPAzeWv05GAiIGNvQu9SIvv5JZltyhMuj6X3fpHGwx+lE6xOoS6DdfXtonmLNXBBB3QHIZka8Gn86SFysha+sHTEkW0XfVxoIaBLbgjHZH+r7pOE2gp9xBOStSPU8gn5iYveCSONq22w0pN4i/1+3tSGM77w+DBWst+AtVOnjAg1/wAMIOHdgl84JSPRw+JsJZtAd7SXHoNs9aCV8cZ83mooKlW9igH8de4QRAEi0jW8q/Tt883wsvv/r/8ajP83+/+d361Ff73d/83v9oCV999l1/dJ1tRsYWR2UZ9fD29Ojj44/Rv/7wRPt2OlMK30wf51Vb4YPo2v9oC709TfnWfbEXFFkZmG/XxwfR/NvWBaIOfzWJt3DGxNi4Ta+MyW/tdS1jLAsJaLGEtTFiLR1jLAsJaLGEtTFiLR1jLAsJaLGEtzP5YS/0rwlv/Gdbj67k/COtJKX+wIP/3f3rk5UuxVtKp+XtMAp+DWf7skalHmziajrVYReKvLdOfVIi/JG2ZUYT0OgN0S+cIvzH58sP8Dngbn91JXWvVaawgnZVBX8yk9lsSLXiDWZlT4qcurEWwT9ZyJ3/Pc3w9/eUW1mL+DvrkBf1ZdhV3fvM7MRvr87ChkOl51zpCPdrEaehaS+8vsx99g6GOr19h/T/mP69drAjRndF0SufEdKF0TV4USF1iJEhlxfZF0J3UoiXdgk3dYiWd1IW1SPbSWo6vnx5+jIOcvkHzEkaZtp1dTzfw5gn9QNLFRT1v+2f4jdc7tBYCLpFUlhg7PyA+Uaq1HnAur6Ht0XyYYa21QPVjpBwdZmVrLQsUGXkKv3Tqo/5boD1uJ6tLjAUheY/ti6A3qWVLuoW+tcwp6e8Pa2H21Fro4nGSFlE7SVcx3AZ3yvj1UrCV03xdypc5XUM4Y/LLDn1rubm4uPilmTtw/aIJmCaWnI2lWmubJ0KMObrGsXStpaOoVP/J9fTZT74o32gDlisy8jR+6ZxOf8CPPzfcYOb4uo4fq0OGgpCaFdMXQWdSq5Z0CzZ1S5V094e1CPbJWsA1ABhVfWUkz8nb8qjTtvPpEorn4kIUNVIro0tXCq7jdfhYfcMGPA14kX4BcJKuYmk2wtVS8H691IpqFEcDMo5D79e4jiKkXk8Pz6YbmOowHdcq0vIsfumcT1/SOIgpjdAFIEPqFgjSWeG+WDqTWt1XNC1w6lYqcfcnwlqYfbKWahDFWvDr9kjHWtQVS3ALayHkx/cMft8dKu3mCoAavPoqlxxfCPMpp3WqOkfnOB49ayFaRfXuJ78QM32pIleepGctNJc5KgLzUkxxfW82EFSgrNi+CPxJrVtyWxCpW6qkvz+shdlna8lb6Id312IrI3Fra1FXYEJukhf6Uq08L2ovMvq2wAlNjK2lOY0+DwLOJFipaO1dS1bSfBCRxsLqiHlBFLQ/oRF3UjctuS2I1C1V0t8f1sLss7VA5UyfX+AHe9jhWQse8PICjhAFdnZ1hf8T8eqqLRpJT8o5ngm3SU8xHl2JYdMNXtpf8NROs7G5x05acI32JE9exPPcdeIoOtbiKFKzBTbdfH7xDJc8WquIWGstcEJ6OMYNTlOKiqOAN0BXlynnVd0CQSoroi8Wb1LrPGD/ZAsidWuVqP2SsBZmf6zlTbIhKYXxXct9sI3SKWxlUoe1FMJaPMJaFhDWYglrYcJaPMJaFhDWYglrYTZkLbFey4hYr2VMrNfCxHotTFqvZUOrzP3HdqQU/j59nV9tha+nv+dXW+Dfpym/uk+2omILI7ON+kirzMUHohHxgWhMfCBi4gMRk1SEtYwIaxkT1sKEtTBhLbOEtYwJa2HCWpiwllnCWsaEtTBhLUxYyyxhLWPCWpiwFmaJtRx+kf9cHB+buzP4x+L499q9v14nelIefTMlCWJ5MQg4ccAz/FP0/EDhhhNseaLVIAgdze5XdKzFUYRPMv784nn6g/VGnmZOUfr6p/lb9kqvdB5P04uLi/xdDEJsOksNXEG79YsFFT8F2IUkf3SqM6m9w+X4eKkrWCXtOHOKJWEtzD5ZS2/WrQeqyqlOpm8tnmkAEBCqrHwnz/vGW/5OHR1IqGjOfkXXWoyiGoldQUZdrAgS/mT0TU6/dJyvm3vfQBdfMRwJAk6mp/p7TOJUQXdSi8P1+PSXguooAfKWur/NTlgLs5fWcnz9JdzC4LoacDF8Rlel4+tnz6eXcFl58sV0Az+SdcDFBy8uxpOgxu7aWrCN8k1YMZdKtdYvyYpKl9G8/Yrl1gLlj2vsyZVK5Fd0lypKrLcWWuVF4W7ihkaC8M376C75HWDWSCF6k1oeXlqg8elbS38w8h4nxURYC7NP1kIfiL7CpaDk1YSGOy9ilnfRtlMaenu/k78U36VvLfTdWLkY0eFHF59c5y15sdQjay3e6kEyWn91oUz/A1GNUTmCW/VS9VJeYqmivGGttZzD6ZcXn0yiG3aTuK0bC6Khk9aiThV0JrU+XI2PTd1ISZNImWJBWAuzT9ZSDaIsqgAbf/FRXkTOWVQBzCijrUU7k8eMFFPeb8Nn71RnR7g41csnfzLWUueoXaQgRRvsJ8a/xpWKoNswAd4Vv/Gp8pClihK7WAu1JC74ZpNcy3IoKG8SCvWpAn9St4eb8VGpm01NSaRNcSashdlrazmfcHFc2uFbC1dQBS5WdZr1mJFSb5gZVcNsfbVaqxZ7E52iDfYTY2sRiupLeTcv5C1VlF/VeWfwS6e0KlpvN8EIZA2JgSBc+yVDGW1OFbiTunO4GB/Z2SWpSYl0U5wIa2H22VpyBdADHBxrgW3pI/HB0a/x3wSc4y0k1NCTcvYhtgFXK6y4R89xuaOzP/8QXh99k4rsCF8fnomLWanWrKWs20ynymhqv0PHWqwi6GFaFwoktfISixUh662Fmj/8TboXoKhqU3pbJCRGgoh689CeKvAmtTicwqnxMZ0dp0YkkjpUUiwJa2H22VoODh7/dZpevHfes5aDg3fwYSFXqYaIU7oG9v8nb6In5RAXqy/P2MrzJj126yU1cfTsur42oNi80H0+VUZT+x061uIooodx5W1KXstYEUygTDN/Mr3SwQe03NADWrIguQnD1rncYgQRxVpGpzqTWh5O4dT4NOnX2NSoRMoUS8JamP2xljfJhqQUxh+I7oNtlE5hK5M6rKUQ1uIR1rKAsBZLWAsT1uIR1rKAsBZLWAuzIWu5xI/1QRAEd8g/4q5lTNy1jIm7FibuWpikIqxlRFjLmLAWJqyFCWuZJaxlTFgLE9bChLXMEtYyJqyFCWthwlpmCWsZE9bChLUwS6zl8K6WguoujcT0pDzyVw/CoBRw1VJQSD21E7rStRa78pJsadRfT5GINqeoVzpWkF44yVkqKnObFDmT2lmvSbfQX+rKKtGJdEInwlqYfbKWpuRuQedra5W+tbimURYrAvdLYZ0v05ZvsjUt11M7oZmOtZQmBU5L8vVIkYo2p8gvnZEgzIrdfzcpspNaNUuoFqCgmqWuZpQAeYsTmghrYfbSWm69FJT4tqvLKmvhxYpKWDF9SrX6X5YV6xztaC12mSWvJdnfkSIVbTdrcdZ9gvn4BH7Q14jt/rtJkZ3UqtmEbcG3Fl8JkvfY0JmwFmafrOVOloIySyN59K2F/gpHnE7Bc/GvWwpKneqEVnSsxS6z1LS0aikoFW1OkV86zlJQkBBeOMnuv5sUeZO6Xa/JtuBbi6ckloJayz5ZSzUIXm9jp6Wg9NJIHjNSxAee3F4u/lVLQTWnEnJNJ0XXWqgjfH11Wlq8FJSNNlDUsxYTAsYBZuS79Csou/9uUmQntWo2YVuoWxKj1CRiKagV7LW17LQUVKJdfaxhRkq9Ycbiq3CZsfXVaq1a+CbaPVWE1nSspcxQnqlOS6q/A0VOtIEiv3RsiBogbbL77yZFZlLrZhO2Bd9a3BQSsRTUYvbZWnIFrFoKyi6N5NGT4iwFReTL27qloIh8ql2YSNP/NW678pJqad1SUCranCK/dKwg2pJEtE0k7iZFZlLrZp3UIL61eEpiKai17LO10II965aCGi6NVOlJ8RZeShRrWbUUFJFPHS5MBHSsBduEsHrlJdHSuqWgVLQ5Rb3SsYL0wklyXaiGW6TImdSyWS819fNybYgxSmIpqLXsj7W8STYkpdC1lntjG6VT2MqkDmsphLV4hLUsIKzFEtbChLV4hLUsIKzFEtbCbMhaYimoIAjumlgKaoa4axkTdy1M3LUwSUVYy4iwljFhLUxYCxPWMktYy5iwFiashQlrmSWsZUxYCxPWwoS1zBLWMiashQlrYZZYS/3jSedvJ1dy6i+NxPSklO/e1r8L1pv47zu9v0XHv0KdzDJGrCX9uWf3j1871uIokn9KejtFwCBV3dI5+jj9TXJ+ZzQM+jkjKP0N7MvfptctZlL7XZeNv41/3dsJN5caf39Yi2CfrEVNn1twfvO77nwh+tbC3w7KeIuIiC/Q1a+lgAfQ11L04VXL8fUrLNTH7td6ga61mObpm8Ews8SM2kURMkpVp3RO2u+ZF0iD7ediQScvfgz/0lfGDN1JLbquGy/h+Fq1WElnf1iLZC+t5fj66eHHWGGHv8LrI4wybTu7nm7gzRP6gaSLi/6+Cn7LKH8ppcvtrAUKz1QrzHR6pb5MK7TkH3WpkJbF1lKmkpxSOylq3hj80hHf+tZkDbafKwQh9TBNb1LLrntJlha8VIm/HwlrYfbUWujKdYJrKuSrNG6D+1xcaQhs5TRdT6AY6CIlqj2Vfn++EH1rubm4uPilnDt2k6r9Uq1Yl+mFXF1IaTm5nj77SVoHxKVrLb3mhYwdFc2kyi+d0+kP+Dkjf7WPqRpMP5cLQuBWwRXUmdSq616S5fIaS5W4+xNhLcw+WQu4BgCjmka5Qp6Tt+VRp23n0yXMu7xWFEHrJ/bnC9GVcghtHD6+lqebTXQpg6ul4P16oRTVqLUcnk03MCdXWoujCE324gJC1Um1m6K5VPmlcz59idHUzQJSL/Dcz9Upgp4BL9xf03QmdXNfYZJM16WVSrz9RFgLs0/WUg2iWAuuyI50rKW5YiEn0w0uggklevWVLgrFjBT5WSPDm/RVlS+EeT+vHqS15NPMlCz0rIVwFHG+dlM0m6qetdBcblZJqhpsPxenKHPKv6YR+JNad900Dl4lnWepEmd/JqyF2WdryVvoh3fXYka+0L8UEzNSnCUU6yb6KFYp1cpVXXuRIS39as2MrcVRVK/XOyrK9FPll05W0th61eD0c6Ugr6+AO6mbrjeNg8OoW5rlSrr7w1qYfbYWqJDpc7zzxx2eteABL/GzgSowoD9fiJ6Uc4h3BbdJaY0xuuSpTaLum3vspAUfbZN2y6tl1oIfYz7HxxP8OW01dKzFUXQK7UBS0u+hgJ0VEf1UdUoHF52EqGnlpRJVuIHo51pB0NcbvG94UWJJvEmtm4VwonEqDrwTubr86erUyP2SsBZmf6zlTbIhKYXxXct9sI3SKWxlUoe1FMJaPMJaFhDWYglrYcJaPMJaFhDWYglrYTZkLf86fft8I/zHdqQU/j59nV9tha+nv+dXW+Dfpym/uk+2omILI7ON+vh6enVw8On09e83wuV2pBS+mz7Nr7bCp9N3+dUW+OM05Vf3yVZUbGFktlEfn07/GR+IxsQHojHxgYiJD0RMUhHWMiKsZUxYCxPWwoS1zBLWMiashQlrYcJaZglrGRPWwoS1MEuspXw9Uf0B+WrK3122f6GtGUo5resBZeTSR2vWOdJaRuscAR1r6fTncfkCHaLeSGYUIaazjF86NkQduLImU7NUlMBbYEkcPVq7yZ3UTku8aVgKrZK2E55SIKyF2SdrcWtgJd7KTZaRlHZ1pBNRm8er1jlSWobrHAFda7H9Ob6e/lLdRL1BFitC1i8F1U9w/saNzFdiJEgdbdduEjiT2rSkN1mlQyUEdaK7P6yF2UtrucVSUP3Kl/Sl4HeU1NdqyveZEnlP/dI9V2v9up74lr+jpflWn2CFtfwM1ysoCtQbZIUi01nFSmuB6YjtqXwlRoLs0XhY3S2wk9o5V22ySkdKCOpEf39YC7On1kIXnx2WgoKrTrN0kkdXSqpNNdv00ker1jmyWuA62JvIXWtx+6PcxLeWeUW2s4qetfgJLtPRLhU1EuQsLCXXbhLYSe2cqzZZpSMlidyJ7v6wFsE+WQt+0E3fNtXXI/KcvC2POm1zloLyFnOy9KQ4qyPppY9WrXOktYA3Av46R0Dv17h+f2rxI/nNWkW7LQXVS3C5wIt8LRBkF5YS32ZW2EntLErVDBa8JqULlCRyJ7r7w1oE+2Qt1SCKtaxfCqoAVyx2G0tHCnxS5/WA8rYyZdISIHUdj9owXwhzg3Y9FqXFX+cI6FkL0fbHs5bMUkVeZxXD0mkF1dsxla/ESFB7NPgvbTB41tK25G2SSudSUzrR2x/WItlna8lb6Id312JGvtK79mXGUtSFPEdKNuaUXKnWUpaikAtKS1fY2Fra0xZYy0JFq+9aiEYQr8mUdwjbHwnSR4Nld4zFm9S2JW+TVDqTGu5EN3VhLcw+WwuM9eqloJqVmzosspZ8BW2WPlqxzpHSMlznCOhYi4qRFZ1d4VJQL6+uMAX8Zq0iYq21eILk9BX5WiBIZRdHE2+kri6bCY04k9pZlEpuEkqXKFGdkPslYS3M/ljLm2RDUgrju5b7YBulU9jKpA5rKYS1eIS1LCCsxRLWwoS1eIS1LCCsxRLWwoS1eIS1LCCsxRLWwmzIWi7zb9GCIAjuin9s8lYhCIK9ZmsfiIIgeBCEtQRB8BoIawmC4DUQ1tJwmlYcejxNf8gbPOig18Ox+X7hmNephdilhdev6g3zmjt0LpazeSA8SGuB2QnkSqA3+Pfli6ASgn9H83tQZ4f5a+KmUg6hen6eX6cI/mEgF78cQaqRm+7yd8Sd1rwWmdmlhf45txmc1eDXC2gkb5umFefDoQka2yQBQBX9PVA25rsLe85DtZa//SmP36Nvpqfnq6sXamA3a0Fn8dty9uCmxlvKUdAFKjW4fzL2o1hR8/O48u+0hTsYnBXA7L0i9bftxNrzy9jm8+BH+TqdvweU8vftHgQP1lr+yzc0N8/hB1Uv/Ms1djq9+iRdMnA8YZN8nXaDtWANgMHIvbiJgINUwAwekJbJSpzkew+IAgcj2iZgY3OtQulYYdVaSs2JUNDiq/+R3uAhuXmhEl6mGEnfafo2H/CK1sFIe5pgNRONSNVb2YI6SYfLkCp9GOEPTj963tEq6J8ggeT9Hg6EBuDfUZqalNicwdEv05skXB59Mt1g46LzCRpbMM90AvysQ+/uwVy/Pou9Dx6stbwFVQWjneqKqpdKCLekos9FxCVRd+TdECCNPZG25/GHasCDVMDC4VmquRdYR3kPyIFGnNqBAO0mbBh/srXQKxUK3uBOEpj2lODkQySMXsNunBmwKf+APW0wbJF+KJGqt7oFdZIKl6Ft6rAMHGYHpx8dWkfhgDpmIEcCu9Fd4VD4p+lEflMjqJRgm23OmpyXo2HT9PQtXN1KAmdhdDgET0tJxJb7e3LMh8PDtZZUszT4+KqUSB7CPJBQFliM7+Bi80DdAf8Caejl3lIOdJAKKDnCi92rH2DRZOCsUtYVCJZKV5Fj1pbyKx0qtwgb4XqX3pTDaVP6l16WY+UPNxhlQolUvdUtyJN0uAwdoGJnIJAdnH50/Bfuoz58Sx8zOEECW2AH/o40HaLPSu+gx/BS9yGHUz/ym3SmPtq2KsZWtzjaAw2YMHvNA7YWKgAcvlS9ZdaqSkllgYP7nt6B44xFAKfJvaIM4CAVUJMOpKotNNaCb8XeAjaMP0vhpePS5VYcnFuEY2BjeiPqFH9Ct/72J2ouHyt/uMFogiiRqre6BXmSDpehA1TsDASyg9OPjhz+BnOljhmfUIEtuAM+eP0OX+mz8LSndKqbEvUjv4EI7cDaVjGL+QBoKb2C89BQ+ntKAw+HB2wtOOY0Ucha4O0rrApZKakssOB+evAYnKTugH/pcmz3/u1HJYYKmDn+9sMfwm0LbIRygwPQlQ7ffY4HZCciUJswmkopNGwViv9t/HiFx6lQoAKOOgJ59Ib+ffWjA9yUouIRVPC0W/9og+Ee2IbHK5Gwi3sLb7gFdZIKl6EDdGzCH5xu9ONvn8ANSzEQdUxHjgS2JE3QSBEk0pS6RvmGA01K1A/4l3OujjatwoYUPgFvoEXoNPpIf0/SUnc9CB6ytRzAvPwzvqfqTQv6vngPdlKlYNlQWaQnn1z+JC3SSDvy37VAALgqi705BpgOv6GAhXc/gaPro9beeQbvbj7Dp/hAUHiddFEhZXRZlgrDGgZuLn9NJ6hQqPFdWmO89uTwMWyo7WKYdH0uu/WPNhj8oEwokaWDpbeiheYk1c0EHdAclugNTi+6eHSd6uNADgNbcEc6Iv1fdZ0m0FJuIpyUqB+nkE/MTX5KgTi6bbUdW2oRf7Xf35Oi1LQ/DB6ktewzUO3kCQNyzQ/AG66HdQ184JSPRw+IsJatAd7SXHoNs9aCl8cZ83mooKlW9icH8de4QRAES0jWEktBBUFw12xrKagN3kDFApZjYgFLJhawZLb2gSisZQFhLZawFiasxSOsZQFhLZawFiasxSOsZQFhLZawFiasxSOsZQFhLZawFmZ/rOXwi/zEX7NI0Drwbzvn/hysJ+XRN1OSkP92EVGb8O8q8cHN3p+EnFynL8k3fziAZ6SjndCKrrU8nqYXFxf5KdiFGvYsBb3Ky4VorKK2M+kp1L2/b/FLx2vwDJ+Ezd8d2DVF+Kezn1889/8Mz5nUslnCJJlja+aVtKGJsBZmn6zlLv6cB6I8yY+cH9C3FlNM7iYu/vPy6pSKUu4DTnDVhLzDxFF0rAUM15loHDaTW0dGivzOdP7ka1g6osEiUT6OfacU1f3e8JlJ7Ter+9fkaakSLzQR1sLspbUcX38JtzDp+/AvLp7R9fH4+tnz6SVcVp58Md3AjzQf4OKDl7nGk16/tXCDpVrrNjHn8M37WLD4ckdrOfEmvghLnIjr60iRIwKm0Q7WIhssDUkX3DFF0xP4ce4KMpPab1b1r83TUiVeaCKshdkna6EPRF/9AG9MxZDSQB9fp+HOu2jbKRVhe79zG2uhv8LJ3w5D9KbDjy4+uZa7S7UeX+c2xaQjXTxvRBxLx1rwy7SXF5/Ib5WpsAl1dR0pckScy9mlGJSOvpyfUwNHNBF3TxGEgE9DHaezk1o3m1D9s3larMQJTYS1MPtkLTi2ieP6m4XDX3x0cZFMJW/LtpEOBjPK1DMTu1tLxt4Iy024BEEtf74Q1motpZw3ydp2QxNda6Gm+Ppqw2bXzQwUFViENnFNv3R0gzAFP4YxePnkTzXWbimC8QRPeNf5FQfgTGrTbCH1z0n/8sHqhQ5rYfbaWs7TArC0w7eWtqgStXK6zEipN8yM2iSmVqnWqoVv50/Q9AieK05oomMtxVLYWkxYuFTLNAwUFYoIOLPdJeiWTtNggS8IwA4pqqlRH1MK3UmtmiVSJCf9awfLhg5rYfbZWnIFnKabEsdaYFv6cH5w9Gv8t7K7tZx9iG3AdRMr7tHzG2hebTr78w/h36NvuPZLtWYth/T5gk4l8oVQxXHo/xr36Vu4ABp2yQlbs1QZKVIi4MS0lEmPXumIBinqESbl8Izm5O4poq6mc+sexk5q1azTP4JvTFYMlgotCWth9tlaaBWbF++d96wF18qBy8xVKigC6jPjlGelJ+XwV2IJHyo5tekwrRj0UrQnQLE39DsGp1pVHIeOtUCZQ5M3n6X/m+qExQ53zMpRpEScwstEzbumUzqyQYp6hAsWlaTcIkXwOaqfI8daZLNO/whpLYKxEhVaEtbC7I+1vEk2JKXQtZZ7YxulU9jKpA5rKYS1eIS1LCCsxRLWwoS1eIS1LCCsxRLWwmzIWmIpqCAI7ppYCmqGuGsZE3ctTNy1MElFWMuIsJYxYS1MWAsT1jJLWMuYsBYmrIUJa5klrGVMWAsT1sKEtcwS1jImrIUJa2GWWEv9O9r6p5E78Tb+QebL3+Z3HXpSyjdn9d+nHn2c/jYTXvn7M/hns+UBmMwpr0XEcRz61uKeVsOmv2Dt9Nco0vpnUuWWDv+1c/NHwEXQuhQ1ggZ98Sa1+JPagmrBH5GEt6smutvJsBbBPlmLW40rOXmRH6c7NKi+tZhvjRyciFli99evpcAkoa+l6CPOb36XPUDGcehZi39aDVv6yweNFCn9c6kalk77NcsqaF2KXEFunuykpu9vqy86qBZsc8PBchJtv0sa1sLspbUcXz89/BhHOj1j/SVUAW07u55u4M0T+oGkiw99wUai6s1hhbWob7/25w20SK/U94zxG0/5aykqjkPHWtzTRFiitg6MFDn966dqVDowN2uDgBC0LkW+IBm6YCY1f3271o1qwWlupMRJdNNJJKyF2VNroSvICa6pkK9OuO09LIYJLzin+br0Cg94LC8+iXZBkZa+tdxcXFz8UkY7nf6AnxvovtvuL9WavzaJallMKtc85VQch461eKfJsAm4/PKbkSKnf/1UDUqnmf5S0LoU2aNVXwRmUhcNQotqwWlupMQmuulkIqyF2SdrSR9u0Uf0FYQ8J2/LVUHbzqdLKMy8VpSgu95SoSvlENo4fCwftX4+fUntpjrj/bBB8L63cBktPpmnnI5j6ViLc5oKC3nB9l+A6y5QZPs3SNWgdMTVHtCCVqVIC+K+WOykxovNxQXYQU2NakG++ad5JTbRupNEWAuzT9ZSDaJYCy7Oj3SsxbusAFBytiY0M1LgWlq9qhSYXJ9I7OcLYd4k12y6wQU5YbpcffWWG0fStZb2NB02c8oOMVBUqLuGqeqXjr6xcAUtS1FBHK36IuhOalE3qgWnuZESk2j37imshdlna8lb6Id312JrFA8YzJbCjBR5Kc+vlY2J/aVaSyWqSZLIV3MvjqRjLd3Tyk0CsUpROXomVd3SoU+jLXcgiFBvKt1JLW8uVAu2uZGS3GpNtN/JsBZmn60Fhnf6HO94cYdnLXjAS7wn5irALXgNvbqsRePQk3KOZ8NtUlrtLF/ScWlDfGQNVpzY39ztp5bx0TZJnrwbKFNOxnHoWIs6zQkLitLDhF7gYrBJSsZVpPo3l6pe6Yip7wtakSIlSPTFYif1KRwNxZF+H1eUyBbEmyWDpcfH97ewFsH+WMubZENSCj1ruT+2UTqFrUzqsJZCWItHWMsCwlosYS1MWItHWMsCwlosYS3Mhqzl0+nr32+Ey+1IKXw3fZpfbYVPp+/yqy3wx2nKr+6TrajYwshsoz4+nf4zrGVMWMuYsBYmrIVJ1hIfiEbEB6Ix8YGIiQ9ETFIR1jIirGVMWAsT1sKEtcwS1jImrIUJa2HCWmYJaxkT1sKEtTBLrOXwjpaCGiwnVOlJKX+1yX//DTSrBj0u321rGa4uRJxO+U9zLR1rsYpqnmidolVLQQHLFXVLpwmhBDXqGmYErV0KKj0D1jzHVXZpzWCpaH7osBbBPlmLmtA7MlxOqNK3FvPFEZjbYtWg4+vpL6pa69dS9HFEu7oQrwtl6VqLUZShL8CsWwpqlaJO6bQhKuq7Qd43d+YErVwK6vg6L6mh3YO7tGqwVLRO6LAWyV5ay10sBTW891luLTUSfQvuZ/jNGK9am+MS5atQGTxRf4dPstZaYHZwF2V/70yRXzpNCEYJkm9WCEJkXwR2UmfldYWEhOzSqsFS0dzQSFgLs6fWQleuXZeCgstRb74QfWtpVyaqtVmX9vCr1R6HIuXqQmkW9Sdy11rM4k0JNQFVf+9MkV86vSWttCD5ZrkgpDd2zqQ+uZ4++8kXk1TSdmn5YOloTuhEWAuzT9YCrgHAqOtrGXlO3pargrZ5S0GBBQH+ckKVrhSzVFK9cLXWAtdlwfzqQnq9JEvv17hGEVGvt9zfu1bkl05vSStxA1DerBU0HDtnUh+eTTfgS2L+my4tHywdzYYmwlqYfbIWcddCI77bUlCIv5xQZUaK+EVBfVnXhqmXvARfCNvjeLbhJne9JEnPWgihKNFe2hcuBbVKUc9aOIRACdLqlgoqLF0KKrciTM52ac1giWg2dCashdlna8lb6Id319KUt6Cz3EZhRoo8u1ZZUedXqz2uhpEOuP6uhWj6Y9YpEvvvTJFfOk4IQAlq1K0UJPsiMJPa8wfC3rVkBkpUtH7osBZmn60FRnb1UlDD5YQqPSlqZSK4PcdLKrTBqwudXeHqQy+vrn7a3GPr4/KpdvWn1dbiKZKTT/T3rhV1Ssdbm0q5QX2zVtBw7Oykhgg3n188g48t9CYpQUqXVg1WG43fSMJamP2xljfJhqQUxnct98E2SqewlUkd1lIIa/EIa1lAWIslrIUJa/EIa1lAWIslrIUJa/EIa1lAWIslrIXZkLVc5t+iBUEQ3BX/iLuWMXHXMibuWpi4a2GSirCWEWEtY8JamLAWJqxllrCWMWEtTFgLE9YyS1jLmLAWJqyFCWuZJaxlTFgLE9bCLLGWwy/wb7KBn+cNO3N83V86jehJefTNlCTI5cdOrtPfhNO3EM7wD8Cv22/wJNRxmcfT9OLiIn9tAb9sKf4evqFjLZ6iM/z+w/P0B+tAP+yMIi+0pFc6qlMJmRVMPv61vjcAVpDSMBTkTGqdB0KK8/ZnvNTIwumdGtbC7JO1NAO9KyfT0/4XY4i+tYgJQ+RvqEHZv1+/RSe/w1OKTx6XUV+6g+490V+W03Stpa8Ig9mwixX1F7Aj/NJRIRJOVlSjI0FKw1CQndQqD4QSZ/ePlABcOE5oIqyF2UtrOb7+Em5hcF0NuAQ9o1VWj6+fPZ9ewmXlyRfTDfygr8Vdp4uL8qRTKJe7sxb3G7Gigku1el+WpdVDBLZUmeXWAhMC19gr6xG0YRcr2s1aTKdqQ3Je18aBkaDbWIvJg+lfu3+kBN/UwnFCE2EtzD5ZC30g+gqXgpJXEyqEY1rvKe+ibac09PJ+h17vbi30Vzi8BJBeNSgvpnpkrcVf52iaLi8+meqWnaylVQQcwa26qHrfWmYVuaEFfumYTuGm9Dpn5fCji0+uZdCRIKVhKMib1E0ejLh2/0hJUzgmNBHWwuyTtVSDKIsqwMZffJQXkXMWVQAzytQz8+5drSUjbu3rtKWQR7g41csnfzLW0hyXMOscaQ/QjH+NKz9sQLdh8r3Lv/HRYVcpAmRoRc9abAiTlbfPxLwcCcooDb4gO6lNHhpxdv9ASd6UNzihibAWZq+t5XzCxXFph28tpZYLuPxHpq0KyYwUcTtf25A3x2x9tVq948rsuwNrEYrs3bwOu0oRIEJr/NLxQhAiK/imRh0JyigNviAzqW0etDhn/0CJKhwvNBHWwuyzteQKoKdHONYC29JH4oOjX+O/Antd1PSknH2IbcDVCivu0XNcoIjayItBH/0Q/jk8k9fJXK36ODoV9D996+DwN/UqvIO1WEUUFbTU30H61jKrSIV28EtHhaCoKitnf8Z3IK6OwEiQ0jAUZCa1zoPtn83TUAlBheOcmglrYfbZWg4OHv91ml68d96zloODd/BhIVepJCW7WsshLi9fnmxVSg5F5CXnj55dw52/aY4Qx5VT8VkmN/QsEyjXTFOtmY61eIrSk8DytmHYGUUytEOvdEQIiqqycpgeDtbJkRGkNAwFOZNa5sHpn9rf4qQGKYXTOzWshdkfa3mTbEhKYfyB6D7YRukUtjKpw1oKYS0eYS0LCGuxhLUwYS0eYS0LCGuxhLUwG7KWWAoqCIK7JpaCmiHuWsbEXQsTdy1MUhHWMiKsZUxYCxPWwoS1zBLWMiashQlrYcJaZglrGRPWwoS1MGEts4S1jAlrYcJamCXWcngnS0E9mlnfiBhJOa7rARFynaNRdLu60Fk69go2/p7C9pZIQjrW0mmRRa5a70gpOnAWdZL0Ssecpbo26udtBNlJ3ZyL6MZXrdu1TElYC7NP1iIGemfmFiEhBlJO9EJSYHhp0tLXcW30+rWU/E02sIJ2ksvvuDm7M11rcWfGYNGixYpK13r4pdM9S7Uj39yNoO6kzlEF1IAeucTtlYS1MHtpLbdYCuq21tIuJFW+BEvF1reW/pdlxZog4jDDGmsZLlq0WJFd1Enjl073LNU1+eZuBPUmtUovQQ2V5oRN3F5JWAuzT9ZyF0tBwVRL0DfPevSkUCRpLTBpU7HROkc2eqlWb3WhRL1omiWSNP0PRE2Lrcg16x0liiJnUSeFXzreWaprq5aCSiwS1JnU4p4EkY2vW7crMaskrIXZJ2upBsErf6xdCqrQVFxLR0oOrqzFrnOkovOFMG/SJ4NsqU0tkaQZ/xpXtKhFQg5gIr27bL2jRFVU7nTMpTvTsxb/LNW1VUtBLRPkT2qdXqI2vmrdLmReSVgLs9fWsn4pqEK95fXpSBksJMVuB4jopVqrFvHRBDCf5r25kBhbi2hxbtGixYrKKe5MBvzS6Z+luibe3I0gd1Kb9BKNEuO6uysJa2H22VpyBaxaCmpufSNiLCVfy/JiJGqdIxO9VGvW0qwuVGsYTjVLJGk61qJatCuLQAPr1jsSiuhcsVJVg1866iyKqrq2bimo5YK8SS3OdZSsW7drmZKwFmafrYUW7Fm3FNTc+kbEGmtR6xyNotvVhaBCqwcNl0gCOtaiWiyTACn38uvWO5KKsG+wP6+bZOmVjlkKSnVt3VJQywU5k1qe6yhZuW7XIiVhLcz+WMubZENSCuMPRPfBNkqnsJVJHdZSCGvxCGtZQFiLJayFCWvxCGtZQFiLJayF2ZC1/Ov07fON8B/bkVL4+/R1frUVvp7+nl9tgX+fpvzqPtmKii2MzDbq4+vp1cHByQf/7Z83wvvbkVL4lw9+nl9thZ9/8C/51Rb4rx98kF/dJ1tRsYWR2UZ9/PyD/57vX4IgCIIgCIIgCIIgCIIgCIIgCILvCwcH/z+z0hJ7bYLVLQAAAABJRU5ErkJggg==\" alt=\"image\"\u003e\u003cstrong\u003eTable 2 Observation on fish assemblage in coral restoration site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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abundance","lastPublishedDoi":"10.21203/rs.3.rs-3680863/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3680863/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoral transplantation via asexual propagation of coral colonies has been used to restore the structure and function of degraded reefs in Palk Bay on the southeast coast of India. Successful restoration programs in India are rare. Therefore, this study aimed to implement a coral outplanting method at two different locations (Thonithurai and Munaikadu) in Palk Bay, India. Twenty metal frames and 800 cement slabs were used to make artificial substrates to install 800 small coral fragments, and the installation was performed in two sets to understand the variation in the growth and survivability of corals. The branching corals \u003cem\u003eAcropora muricata, Acropora hyacinthus, Montipora digitata\u003c/em\u003e, and \u003cem\u003ePocillopora damicornis\u003c/em\u003e were used in this study. Eighteen months after coral transplantation, there was significant growth between the coral species (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;8.0981; P\u0026thinsp;=\u0026thinsp;0.0012\u003c/em\u003e), whereas, the growth difference between Thonithurai and Munaikadu was not significant (\u003cem\u003eF\u0026thinsp;=\u0026thinsp;0.0105; P\u0026thinsp;=\u0026thinsp;0.91875\u003c/em\u003e). The average monthly growth rate of \u003cem\u003eA. muricata\u003c/em\u003e (0.60cm/month) was the highest among all studied species, whereas \u003cem\u003eA. hyacinthus, M. digitata\u003c/em\u003e, and \u003cem\u003eP. damicornis\u003c/em\u003e had monthly growth rates of 0.44cm, 0.47cm, and 0.18cm, respectively. The survival rate for each species was calculated, and the survival rate for \u003cem\u003eA. muricata\u003c/em\u003e (\u0026gt;\u0026thinsp;60%) and \u003cem\u003eA. hyacinthus\u003c/em\u003e (\u0026gt;\u0026thinsp;50%) was the highest, whereas that for \u003cem\u003eP. Damicornis\u003c/em\u003e was the lowest at both sites (\u0026lt;\u0026thinsp;35%). A large number of fish assemblages dominated by \u003cem\u003eTerapon jarbua\u003c/em\u003e (grunter fish), \u003cem\u003ePomacentrus trilineatus\u003c/em\u003e (damsel fish), and \u003cem\u003eSiganus javus\u003c/em\u003e (rabbitfish) were recorded from the sites after 9 months of transplantation. The results indicated that the coral out-planting method could be an effective tool for coral restoration in Palk Bay, and branching coral species can be considered promising contributors to artificial reef formation. Long-term restoration and multispecies out-planting can enrich the reef diversity in Palk Bay.\u003c/p\u003e","manuscriptTitle":"Coral Restoration in Palk Bay on the Southeast Coast of India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-02 20:56:34","doi":"10.21203/rs.3.rs-3680863/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":"63fc2cd3-6423-4423-ad87-3cd79957c407","owner":[],"postedDate":"February 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-25T07:13:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-02 20:56:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3680863","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3680863","identity":"rs-3680863","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}