Multidimensional Cultural Engagement and Mental Health in Chinese Higher Vocational Students: A Cross-Sectional Study with Implications for Education and Public Health

Multidimensional Cultural Engagement and Mental Health in Chinese Higher Vocational Students: A Cross-Sectional Study with Implications for Education and Public Health | 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 Article Multidimensional Cultural Engagement and Mental Health in Chinese Higher Vocational Students: A Cross-Sectional Study with Implications for Education and Public Health Benjing Chen, Huaixuan Su, Xiufang Su This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6500034/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Aims: The mental health of students in higher vocational institutions has become a critical concern, with traditional Chinese culture potentially offering solutions through its positive psychological influences. This study investigates the relationship between traditional Chinese culture and the mental health of vocational students. Methods: A random sampling approach was employed to select 432 participants from eight classes of the 2022 and 2023 cohorts at Shunde Polytechnic, representing diverse disciplines such as literature, engineering, and science. Data were collected via an online survey using the platform Questionnaire Star, complemented by interviews for quality assurance. The Beck Depression Inventory (BDI-13) was used to assess mental health status. Results revealed that most students had only a superficial understanding of traditional culture, partly due to monotonous teaching content. Results: Mental health assessments revealed a high prevalence of psychological distress among students, including symptoms of depression and pessimism. Further analysis demonstrated an inverse relationship between positive cultural identity and lower levels of psychological distress, while active engagement with culture was linked to better mental health. A multivariate linear regression analysis indicated that participation in cultural activities, such as drama, was associated negatively with depressive symptoms, and that engagement with classical literature was linked to a mitigation of pessimistic attitudes and other psychological concern. Conclusions: It is evident that strengthening traditional culture education and enhancing teaching methods through innovative approaches significantly may help promoting the mental health of students. Biological sciences/Psychology Health sciences/Risk factors Traditional Chinese Culture Mental Health Students Higher Vocational Colleges Introduction The intersection of traditional culture and mental health has garnered increasing attention in psychological and educational research, particularly in non-Western contexts where cultural heritage plays a pivotal role in shaping collective and individual well-being. Studies highlight that engagement with traditional cultural practices, such as Confucian values, classical literature, and communal rituals, may buffer against psychological distress by fostering resilience, social cohesion, and existential meaning [ 1 – 3 ] . For instance, Wang et al. [ 1 ] demonstrated that cultural identity rooted in Confucian principles correlated with reduced depressive symptoms among Chinese adolescents. Similarly, Chen and Zhang [ 2 ] emphasized the therapeutic role of traditional arts in mitigating anxiety, while Li et al. [ 3 ] linked collective cultural practices to enhanced emotional regulation. Despite these insights, research has predominantly focused on urban populations or university students, leaving higher vocational students—a group facing unique academic and social pressures—understudied. However, methodological and conceptual challenges persist in quantifying the multidimensional impact of cultural engagement on mental health. Current studies often rely on unidimensional metrics (e.g., frequency of cultural activities), overlooking the complexity of cultural identity, emotional resonance, and behavioral participation [ 4 ] . Furthermore, cross-sectional designs dominate the field, limiting causal inferences and longitudinal insights into how cultural engagement evolves with educational interventions [ 5 ] . Smith and Liu [ 4 ] critiqued the oversimplification of cultural variables in mental health models, advocating for integrative frameworks that capture both cognitive and affective dimensions. Similarly, Hu and Yang [ 5 ] identified a gap in culturally tailored assessment tools, particularly for vocational students navigating the dual demands of skill-based training and psychological adaptation. This study addresses these gaps by examining the relationship between multidimensional cultural engagement—spanning identity, knowledge, and active participation—and mental health outcomes among Chinese higher vocational students. Innovatively, we integrate quantitative (BDI-13 assessments) and qualitative (interview) methods to map how specific cultural practices, such as drama and classical literature, modulate depressive symptoms and pessimism. By focusing on a vocational cohort, this research extends existing paradigms to a marginalized yet critical demographic, offering actionable insights for curriculum design and public health strategies. Our findings aim to bridge the theoretical divide between cultural psychology and mental health interventions, advocating for pedagogies that harmonize traditional values with modern educational demands. Material and methods 1.1 Definition of Traditional Culture In this study, "traditional culture" specifically refers to excellent traditional Chinese culture, which is referred to herein for simplicity. Traditional Chinese culture can be defined broadly or narrowly. Broadly speaking, traditional Chinese culture encompasses all material and intangible cultural heritages created and passed down by the Chinese nation up until the Opium Wars. It is a cultural system formed and stabilized over a long historical process. Its core components include, but are not limited to, ideology, cognitive patterns, value standards, moral norms, ritual systems, folk customs, behavioral codes, lifestyles, religious beliefs, literature and art, education and science, as well as classic texts [ 6 ] . The traditional Chinese culture involved in this study covers these aspects and their extensions. 1.2 Participants This study used a random sampling method to select students from eight classes of the 2022 and 2023 cohorts at Shunde Polytechnic as research participants. The survey was conducted via the online questionnaire platform Questionnaire Star. A total of 432 students submitted valid questionnaires, including 224 males (51.85%) and 208 females (48.15%). The professional backgrounds of the participants were diverse, covering areas such as literature, engineering, science, medicine, economics, and art. All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants prior to their involvement in the study. The study protocol was reviewed and approved by the Institutional Review Board of Shunde Polytechnic. 1.3 Survey on Traditional Chinese Culture Education The study investigated students' understanding of "cultural confidence," their attitudes towards traditional culture, their mastery of traditional cultural knowledge, the state of traditional culture education in schools, and the frequency of traditional cultural activities on campus. To ensure the accuracy, completeness, and scientific validity of the data, the research team conducted interviews with participating teachers and students to help them understand and answer the questions in the questionnaire more accurately. 1.4 Mental health status Assessment The Beck Depression Inventory (BDI-13) was used to assess potential negative psychological symptoms experienced by students in the past week. Symptoms assessed included depression, pessimism, lack of satisfaction, self-reproach, self-disappointment, negative tendencies, social withdrawal, indecisiveness, changes in self-image, work difficulties, fatigue, and loss of appetite. Symptoms were rated on a scale from 0 to 3, where 0 indicates no symptoms, 1 indicates mild symptoms, 2 indicates moderate symptoms, and 3 indicates severe symptoms. 1.4 Mental health status Assessment Statistical Package for the Social Sciences (SPSS) version 23.0 was used for descriptive statistical analysis of the data. Descriptive statistics provided an overview of the sample characteristics and the distribution of the variables under study. Correlation analysis was performed to evaluate the relationship between BDI-13 symptom scores and traditional culture. Correlation coefficients were calculated to quantify the strength and direction of the associations between these variables. Multivariate linear regression analysis was used to explore the relationship between BDI-13 symptom scores and traditional culture education. Regression models were constructed to control for potential confounding variables and to assess the independent effect of traditional culture education on BDI-13 scores. The independent variables were factors related to traditional culture education, the dependent variables were the BDI-13 scores, and covariates included age, gender, major, political affiliation, and the major. By including these covariates, we aimed to account for possible demographic and educational influences on mental health outcomes. The significance of analysis was set at p < 0.05. Results 2.1 Current Status of Traditional Culture Education Cultural confidence is a significant manifestation of national identity, reflecting a profound understanding of one's own culture and a firm belief in future development [ 7 ] . In our survey of traditional culture education among students in higher vocational colleges, we found that most students have a superficial understanding of cultural confidence and that their knowledge of traditional culture is largely confined to its broadness, depth, and inclusiveness. The survey indicated that more than half of the students rarely read traditional classics each year. Issues such as monotonous teaching content, overemphasis on theory, and a dull classroom atmosphere were noted in traditional culture education. Most students favored setting up traditional culture as elective courses rather than mandatory ones. Additionally, traditional cultural activities on campus occur infrequently, although events such as knowledge contests, plays, etiquette lessons, and dance performances are widely popular among students (Table 1 ). These findings suggest that there is an urgent need to innovate and optimize traditional culture education to enhance students' cultural confidence and mental health. Table 1 Investigation on the traditional culture education of students N (%) The connotation of cultural confidence Know very well 143(33.10) Understand shallow meaning 241(55.79) Unclear connotation 36(8.33) Barely understand 12(2.78) Traditional culture is Broad 407 (94.21) Profound 389(90.00) Inclusive 296(68.51) Aggressive 130 (30.09) Unconstrained 88(20.37 ) Classics Reading (per year) Zero 152(35.19) One or two 228(52.78) Problems in traditional cultural education Monotonous teaching content 165(56.9) Emphasis on theoretical teaching 201(69.31) Boring class 131(45.17) The School Neglects 68(23.45) Traditional culture course Need not involve 31(7.18) Elective courses should be set up 299(69.21) Compulsory courses should be set up 58(13.43 Hard to say 44(10.18) Traditional culture campus activities Almost none 58(13.43) Occasionally 238(55.09) Favorite traditional culture campus activities Knowledge contest 255(59.03) Drama 283(65.51) Etiquette, dance, costume show 297(68.75) Poetry competition 162(37.50) Chinese Traditional Performance Arts 160(37.03) Evening party 168(38.97) Readings, lectures 127(29.40) 2.2 Psychological Challenges Identified Through the BDI-13 Assessment Through the assessment using the Beck Depression Inventory (BDI-13), this study identified that college students generally face significant psychological challenges (Table 2 ). Prevalent issues include depression (20.37%), pessimism (32.87%), and dissatisfaction of life (20.37%). There is also a notable lack of self-efficacy, manifested in feelings of failure (27.55%), guilt (26.62%), and self-disappointment (24.07%). Social withdrawal (25.92%) and hesitancy (25.5%) highlight social and decision-making obstacles. High incidences of feeling Difficulties at Work (26.2%), fatigue (30%), decreased appetite (22.22%) and distorted body image (14.12%) also affect daily functioning. Table 2 Assessment of students' negative mental symptoms Symptoms N(%) DE 88 (20.37) PE 142 (32.87) Sf 119 (27.55) DL 88 (20.37) FG 115 (26.62) SD 104(24.07) NT 42(9.72) SW 112 (25.92) HE 110(25.46) BID 61(14.12) FDW 113(26.16) FA 130(30.09) DA 96(22.22) 2.3 Correlation Between Traditional Culture and Mental Health Status The study shows a significant correlation between the perception of traditional culture and the state of mental health (Table 3 ). Positive cultural identity is negatively correlated with lower levels of depression, reduced pessimism, and other psychological distress factors such as self-reproach and disappointment (p < 0.05 and p < 0.001). Conversely, negative perceptions of traditional culture are positively correlated with these mental health issues. Furthermore, active engagement with traditional culture (such as knowledge acquisition and positive evaluation) is positively associated with mental health status, whereas negative cultural experiences can lead to a deterioration of mental health conditions. 2.4 Results of Multivariate Linear Regression Analysis The results of multivariate linear regression analysis indicate a positive correlation between boring classes and depression and indecisiveness (p < 0.05), while participation in plays has a negative impact on depression and pessimism (p < 0.05). Classic reading shows a significant negative correlation with pessimism, feelings of failure, distorted body image, and work-related difficulties (p < 0.05). Cultural confidence significantly reduces the feeling of failure (p < 0.001). Moreover, the introduction of courses is associated with dissatisfaction in life and feelings of guilt, while positive cognition correlates with negative tendencies (p < 0.05). Negative cognition, however, is positively correlated with indecisiveness, work-related difficulties, and fatigue (p < 0.05). These findings emphasize the potential role of traditional culture in promoting the mental health of college students ( Table 4 ). Table 3. The correlation between traditional culture and mental health status. Note: *: p<0.05, **: p<0.001 Table 4 The association between traditional culture and mental health status of students Ajusted β p value 95.0% CI of β DE BC 0.17 0.04 (0.003, 0.214) DR -0.14 0.033 (-0.394, -0.016) PE CR -0.184 0.007 (-0.175, -0.028) DR -0.227 0.003 (-0.475, -0.099) SF CR -0.126 0.02 (-0.346, -0.03) CC -0.483 < 0.001 (-0.629,-0.413) DL OCTC 0.124 0.041 (0.007, 0.315) FG OCTC 0.131 0.033 (0.015, 0.354) NT PRTC -0.167 0.011 (-0.358, -0.046) NRTC 0.154 0.013 (0.067, 0.575) HE NRTC 0.156 0.01 (0.091, 0.655) BC 0.153 0.028 (-0.016, 0.275) DR -0.127 0.042 (-0.340, -0.006) FDW NRTC 0.145 0.016 (0.057, 0.556) CR -0.119 0.045 (-0.125, -0.001) BC 0.163 0.034 (0.01, 0.259) FA NRTC 0.136 0.026 (0.035, 0.533) DR -0.124 0.045 (-0.301, -0.004) Note : Only significant results were shown here. *: p < 0.05, **: p < 0.001. Discussion In this study, we conducted an in-depth analysis of the current state of traditional culture education among college students and its association with mental health conditions. The survey findings underscore the complex relationship between traditional culture exposure and mental well-being among students. The survey revealed that although most students hold positive attitudes towards traditional culture, recognizing it as broad and profound, their understanding of its deeper connotations is relatively limited, and there is a marked insufficiency in the reading of traditional classics, with over half of the students showing extremely low annual reading volumes. This observation highlights a gap between appreciation and engagement, suggesting that while students may value traditional culture, they lack opportunities or motivation to delve deeply into its study. Moreover, there are numerous issues with the methods and content of traditional culture education, such as monotonous teaching content, overemphasis on theory, and boring classes, which require urgent resolution. These pedagogical issues not only detract from the learning experience but may also hinder the potential therapeutic benefits that traditional culture could offer to mental health. Despite these shortcomings, students still have a strong demand for traditional culture education, preferring to engage with it through elective courses and campus activities, particularly knowledge competitions, drama performances, and exhibitions of etiquette, dance, and costumes. This indicates a clear preference for interactive and experiential learning formats over traditional lecture-based instruction [ 8] . Simultaneously, the student population faces widespread mental health challenges, with depression, pessimism, and dissatisfaction with life prevalent, affecting a considerable portion of students. Feelings of failure, guilt, and self-disappointment are common, indicating low self-efficacy. Social withdrawal and indecisiveness are also frequent, reflecting impaired interpersonal skills and decision-making abilities. These symptoms collectively suggest a pervasive sense of disempowerment and a struggle with personal agency among young adults navigating the academic environment. High incidences of work difficulties and fatigue, along with decreased appetite and distorted body image, further highlight the potential impacts of mental health issues on daily functioning and physical health of college students. Such manifestations not only disrupt academic performance but also pose serious risks to overall well-being, including potential long-term health consequences [ 9 ] . These findings emphasize the multidimensionality and complexity of mental health issues among college students, suggesting that educational institutions and society at large need to adopt comprehensive measures to provide targeted psychological support and services. Given the intricate interplay between academic pressures, social dynamics, and personal development, a holistic approach that integrates mental health education, counseling services, and community support networks is imperative. This approach should aim to foster resilience and coping strategies among students while addressing systemic factors that contribute to mental distress. Traditional culture plays a significant role in this process, with its positive influence not to be overlooked. Under the influence of globalization, foreign cultures have strongly impacted the values of college students, leading to confusion about cultural identity. In a materialistic society, students often pursue comfort at the expense of spiritual pursuits. What appear to be cognitive and behavioral problems are rooted in differences in cultural backgrounds [ 10 ] . Cultural dissonance can lead to a sense of alienation and disconnection from one's heritage, which may exacerbate feelings of uncertainty and identity crises among students. Research has shown that culture can successfully alter individuals' psychological processes and behavior patterns 【11–14】 . Therefore, the construction of healthy psychology among college students should be based on the context of Chinese culture. To truly enhance the effectiveness of mental health education among college students and play its important role, the essence of traditional culture must be utilized [ 10 ] . These research results indicate that traditional culture is not only a bridge between the past and the present but also a valuable resource for shaping modern mental health. The preliminary analysis of this study also reveals the correlation between different dimensions of traditional culture education and mental health indicators among college students. For example, positive cognition of traditional culture shows a significant negative correlation with depression, pessimism, and low satisfaction, while negative cognition shows a significant positive correlation. This suggests that fostering a positive attitude towards traditional culture may serve as a protective factor against mental health issues, whereas a negative perception might increase the risk of experiencing such problems [ 10 ] . The impact of traditional culture education on mental health is multifaceted and can achieve its effects through multiple mechanisms. Cultural confidence manifests as a nation's deep understanding and high recognition of its own culture, representing full acknowledgment of the value of its culture and firm belief in its future development 【7】 . By instilling a strong sense of cultural pride and identity, traditional culture education can bolster students' self-esteem and confidence, equipping them with a robust foundation for personal growth. Enhancing students' literacy in traditional culture can strengthen this cultural confidence, further enhancing individual self-esteem and confidence, improving psychological resilience, and enabling them to more effectively cope with challenges and pressures in life, thus promoting mental health and reducing the occurrence of psychological issues such as anxiety and depression. Chinese culture, with its long history, carries unique national spirits [ 15 ] , providing rich guiding principles for daily life and helping individuals understand themselves, reflect upon themselves, and pursue the essence of life, enriching their inner world and resisting the influence of negative thoughts and values. The wisdom embedded in Chinese traditional culture, such as the Confucian emphasis on social harmony and the Daoist philosophy of living in accordance with nature, can foster a sense of balance and harmony within individuals, contributing to their emotional stability and well-being. The excellent thoughts contained in Chinese traditional culture continue to influence each generation [ 16 ] . With the continuous accumulation of cultural knowledge, personal inner qualities are elevated, better showcasing the unique charm of Chinese traditional culture. As students immerse themselves in the study of traditional texts and practices, they not only gain historical insight but also develop a deeper appreciation for the timeless values that underpin their cultural heritage. This process helps in building a stronger sense of personal identity and belonging, which can be a protective factor against mental health issues. The virtuous qualities embodied in traditional cultural literature can cultivate the emotions of college students and shape positive attitudes toward life, holding significant value for their holistic growth. Excellent literary works transcend the limitations of modern life, serving as a microcosm of traditional culture [ 17 ] . These works not only enrich students' intellectual lives but also serve as a source of moral guidance and inspiration, offering timeless wisdom that can be applied to contemporary challenges. These works can inspire and guide learners, optimize their moral qualities, and help them establish lofty life goals. Influenced by exemplary figures, college students become more demanding of themselves, forming positive attitudes, thereby gradually cultivating healthy mental states. Studies have shown that integrating traditional culture into the teaching of Chinese language and literature can improve students' thinking patterns and behavior, enhance their humanistic literacy, and enrich their spiritual world [ 10 ] . By incorporating elements of traditional culture into the curriculum, educators can create a learning environment that promotes critical thinking, ethical reasoning, and a deeper appreciation of one's cultural heritage. This holistic approach can contribute to a more balanced and resilient student population. Our research also shows that classic reading has a significant negative correlation with negative psychological states among college students. This indicates that engaging with classical texts can serve as a buffer against psychological distress, fostering a sense of calm and perspective that is beneficial for mental health. These findings further confirm the importance of traditional culture education in promoting mental health, suggesting that a curriculum that includes traditional culture can play a pivotal role in supporting the psychological well-being of students. Multivariate regression analysis eliminated the effects of confounding factors, providing a more precise assessment of the relationship between traditional culture and mental health. The results show that the relationship between dull classroom environments and depression, work difficulties, and fatigue is more pronounced, indicating that the dullness of teaching methods may directly affect students' mental health status. This suggests that uninspiring classroom dynamics can exacerbate feelings of isolation and disengagement, contributing to a decline in mental well-being. Furthermore, drama activities have a positive effect on reducing depression, pessimism, and fatigue, while classic reading has a positive impact on reducing feelings of failure, guilt, and work difficulties. These findings indicate that active engagement with cultural practices can mitigate negative psychological states, underscoring the therapeutic potential of participatory cultural activities. These results also reflect the existing problems in our current traditional culture education. Traditional culture learning is considered the task of humanities departments alone, with students from other disciplines often showing indifference. There is a misconception that traditional culture is only relevant to those studying the humanities, leading to a lack of interest and engagement from students in other fields. Traditional culture education is only set up as optional public courses within schools, often being phased out because literature courses are perceived as useless for employment. This neglect stems from the perception that such courses do not contribute directly to career readiness, despite their intrinsic value in personal development. However, classroom teaching often simplifies cultural education into rigid knowledge transmission, lacking vitality and appeal, marginalizing the rich humanistic spirit and intrinsic values of traditional culture, making it difficult to evoke a deep resonance within students and their perception of the meaning of life. Teaching methods that focus solely on rote memorization fail to capture the essence of traditional culture, which is meant to inspire reflection and foster a deeper connection with one's heritage. Thus, there is a significant positive correlation between dull classroom teaching and students' negative psychological states. Although this study has revealed a significant correlation between traditional culture education and the mental health status of college students, the specific mechanisms of action still require further exploration. Traditional culture education may positively impact mental health by enhancing cultural confidence, improving social skills, and increasing self-efficacy. Understanding how these mechanisms work together can provide insights into the holistic benefits of traditional culture education, such as fostering a sense of belonging and identity, which are crucial for mental well-being. Future research should focus on these potential mechanisms to gain a more comprehensive understanding of the vital role of traditional culture education in promoting the mental health of college students. Investigating the pathways through which traditional culture education influences mental health can inform the development of more effective intervention programs tailored to the needs of today's students. Therefore, strengthening traditional culture education, improving students' positive cognition and understanding of traditional culture, has significant practical implications for improving the mental health status of college students. By emphasizing the importance of cultural literacy and engagement, educational institutions can create supportive environments that enhance mental resilience and foster a healthier student community. This study uses Chinese traditional culture as the main entry point, extracting its excellent qualities to understand the impact of integrating traditional culture into literature teaching on the mental health of college students, analyzing the relationship between the integration of excellent traditional culture into quality education and the mental health of college students. By focusing on the positive attributes of traditional culture and their incorporation into modern educational settings, this study aims to bridge the gap between cultural heritage and contemporary mental health needs. The innovation of this study lies in two aspects. First, from the perspective of the mental health of college students, this study examines the impact of the excellent qualities of traditional culture on the mental health of college students, going beyond theoretical research to gain new insights. This approach seeks to translate abstract cultural values into tangible mental health benefits, offering a practical framework for educators and policymakers. Second, focusing on the combination of college students' mental health and traditional culture, primarily based on the positive elements of traditional culture, this study provides a new perspective on the research of healthy psychological qualities from the viewpoint of traditional culture. By highlighting the synergistic relationship between traditional culture and mental health, this study contributes to the growing body of evidence that supports the integration of cultural elements into holistic education models. Using quantitative analysis methods, this study obtained the significance of factors affecting the mental health of college students, tailoring education to individual needs to foster mental health among college students. The application of statistical techniques allowed us to identify key variables that correlate with mental health outcomes, enabling personalized educational strategies that address the diverse needs of students. However, this study also has certain limitations. Firstly, the design of this study was cross-sectional, making it difficult to draw specific causal relationships. A cross-sectional design limits our ability to infer causality, and future longitudinal studies are needed to explore the temporal dynamics of these relationships. Thirdly, this study only explored several representative dimensions preliminary and selected several topics as representatives for measurement, which is quite limiting. To fully understand the breadth and depth of the impact of traditional culture on mental health, future research should employ a more comprehensive framework that encompasses a wider range of cultural dimensions and thematic areas. We should deepen our understanding of traditional culture, create more dimensions, and construct more rigorous themes and detailed and in-depth research. Enhancing the depth and breadth of research will provide a richer tapestry of insights that can inform more effective interventions and educational policies. Conclusion In summary, despite certain limitations, our research results demonstrate that traditional culture education may benefit the mental health of students in vocational colleges. Our findings suggest that integrating traditional culture into the educational curriculum can have a positive impact on the psychological well-being of vocational college students, fostering a greater sense of cultural identity and self-worth. Further large-scale randomized controlled studies are needed to explore the relationship between traditional culture education and the mental health of students in vocational colleges. Such studies would provide a more definitive understanding of the causal links and help refine educational strategies that leverage traditional culture to support mental health. Abbreviations DE Depression PE Pessimism SF Sense of Failure DL Dissatisfied with Life FG Feeling of Guilt SD Self Disappointments, NT Negative Tendency SW Social Withdrawal HE Hesitancy BID Body Image Distortion FDW Feeling Difficulties at Work FA Fatigue DA Decreased Appetite PRTC Positive Recognition of Traditional Culture NRTC Negative Recognition of Traditional Culture PTC Prospects for Traditional Culture, VTCK Volume of Traditional Cultural Knowledge CR Classic Reading, CSTC Contemporary Significance of Traditional Culture OCTC Offering Courses on Traditional Culture ETCC Effectiveness of Traditional Culture Course FTCC Feeling of Traditional Culture Course PETCCA Positive Evaluations of Traditional Culture Campus Activities NETCCA Negative Evaluations of Traditional Culture Campus Activities TCKC Traditional Culture Knowledge Competition Drama DR CC Cultural Confidence UFC Understanding of Foreign Cultures IFC Impact of Foreign Cultures Boring Class BC Declarations Acknowledgments Su Xiufang is the co-first author. 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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-6500034","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":446041661,"identity":"4babeca9-37e5-4e29-9a6e-d3a5fd2a67d7","order_by":0,"name":"Benjing Chen","email":"","orcid":"","institution":"Guangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Benjing","middleName":"","lastName":"Chen","suffix":""},{"id":446041662,"identity":"c7adad98-6cd8-4d25-bc9f-b52fe79eb381","order_by":1,"name":"Huaixuan Su","email":"","orcid":"","institution":"Dongchangfu District Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Huaixuan","middleName":"","lastName":"Su","suffix":""},{"id":446041663,"identity":"adece431-9b0b-4a48-bd35-091a81b7b577","order_by":2,"name":"Xiufang Su","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYDCCAzxsDAlAmp+BsYFELZINJGkBAYMDxLqL73jvsQcPKuoSN58/3PbgB4OdnC4hyyTPnEs3SDhzOHHbjcR2wx6GZGMzQtYZ3Mgxk0hsOwDUwtgmwcMAZBDUcv8NUMs/oMP6D7ZJ/iFKyw0eoJYG5sQNDIlt0kTZInkmD+iXY4eNZ9wAapExIMIvfMfPHnv4o6ZOtr//+DPJNxV2cgS1oLuTNOWjYBSMglEwCnAAABo7R9lrgbEPAAAAAElFTkSuQmCC","orcid":"","institution":"Shunde Polytechnic","correspondingAuthor":true,"prefix":"","firstName":"Xiufang","middleName":"","lastName":"Su","suffix":""}],"badges":[],"createdAt":"2025-04-22 04:08:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6500034/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6500034/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-32007-9","type":"published","date":"2026-01-06T15:59:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":100069445,"identity":"489c4abc-222a-4cd0-9e64-2adc7c4360de","added_by":"auto","created_at":"2026-01-12 16:14:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":963276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6500034/v1/80d3c9bf-a5a3-45e8-8df9-4b04a22a6967.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multidimensional Cultural Engagement and Mental Health in Chinese Higher Vocational Students: A Cross-Sectional Study with Implications for Education and Public Health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe intersection of traditional culture and mental health has garnered increasing attention in psychological and educational research, particularly in non-Western contexts where cultural heritage plays a pivotal role in shaping collective and individual well-being. Studies highlight that engagement with traditional cultural practices, such as Confucian values, classical literature, and communal rituals, may buffer against psychological distress by fostering resilience, social cohesion, and existential meaning \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. For instance, Wang et al.\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e demonstrated that cultural identity rooted in Confucian principles correlated with reduced depressive symptoms among Chinese adolescents. Similarly, Chen and Zhang\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e emphasized the therapeutic role of traditional arts in mitigating anxiety, while Li et al.\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e linked collective cultural practices to enhanced emotional regulation. Despite these insights, research has predominantly focused on urban populations or university students, leaving higher vocational students\u0026mdash;a group facing unique academic and social pressures\u0026mdash;understudied.\u003c/p\u003e\n\u003cp\u003eHowever, methodological and conceptual challenges persist in quantifying the multidimensional impact of cultural engagement on mental health. Current studies often rely on unidimensional metrics (e.g., frequency of cultural activities), overlooking the complexity of cultural identity, emotional resonance, and behavioral participation\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Furthermore, cross-sectional designs dominate the field, limiting causal inferences and longitudinal insights into how cultural engagement evolves with educational interventions\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Smith and Liu\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003ecritiqued the oversimplification of cultural variables in mental health models, advocating for integrative frameworks that capture both cognitive and affective dimensions. Similarly, Hu and Yang\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003eidentified a gap in culturally tailored assessment tools, particularly for vocational students navigating the dual demands of skill-based training and psychological adaptation.\u003c/p\u003e\n\u003cp\u003eThis study addresses these gaps by examining the relationship between multidimensional cultural engagement\u0026mdash;spanning identity, knowledge, and active participation\u0026mdash;and mental health outcomes among Chinese higher vocational students. Innovatively, we integrate quantitative (BDI-13 assessments) and qualitative (interview) methods to map how specific cultural practices, such as drama and classical literature, modulate depressive symptoms and pessimism. By focusing on a vocational cohort, this research extends existing paradigms to a marginalized yet critical demographic, offering actionable insights for curriculum design and public health strategies. Our findings aim to bridge the theoretical divide between cultural psychology and mental health interventions, advocating for pedagogies that harmonize traditional values with modern educational demands.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003e1.1 Definition of Traditional Culture\u003c/h2\u003e\n \u003cp\u003eIn this study, \u0026quot;traditional culture\u0026quot; specifically refers to excellent traditional Chinese culture, which is referred to herein for simplicity. Traditional Chinese culture can be defined broadly or narrowly. Broadly speaking, traditional Chinese culture encompasses all material and intangible cultural heritages created and passed down by the Chinese nation up until the Opium Wars. It is a cultural system formed and stabilized over a long historical process. Its core components include, but are not limited to, ideology, cognitive patterns, value standards, moral norms, ritual systems, folk customs, behavioral codes, lifestyles, religious beliefs, literature and art, education and science, as well as classic texts \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The traditional Chinese culture involved in this study covers these aspects and their extensions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e1.2 Participants\u003c/h2\u003e\n \u003cp\u003eThis study used a random sampling method to select students from eight classes of the 2022 and 2023 cohorts at Shunde Polytechnic as research participants. The survey was conducted via the online questionnaire platform Questionnaire Star. A total of 432 students submitted valid questionnaires, including 224 males (51.85%) and 208 females (48.15%). The professional backgrounds of the participants were diverse, covering areas such as literature, engineering, science, medicine, economics, and art. All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants prior to their involvement in the study. The study protocol was reviewed and approved by the Institutional Review Board of Shunde Polytechnic.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e1.3 Survey on Traditional Chinese Culture Education\u003c/h3\u003e\n\u003cp\u003eThe study investigated students\u0026apos; understanding of \u0026quot;cultural confidence,\u0026quot; their attitudes towards traditional culture, their mastery of traditional cultural knowledge, the state of traditional culture education in schools, and the frequency of traditional cultural activities on campus. To ensure the accuracy, completeness, and scientific validity of the data, the research team conducted interviews with participating teachers and students to help them understand and answer the questions in the questionnaire more accurately.\u003c/p\u003e\n\u003ch3\u003e1.4 Mental health status Assessment\u003c/h3\u003e\n\u003cp\u003eThe Beck Depression Inventory (BDI-13) was used to assess potential negative psychological symptoms experienced by students in the past week. Symptoms assessed included depression, pessimism, lack of satisfaction, self-reproach, self-disappointment, negative tendencies, social withdrawal, indecisiveness, changes in self-image, work difficulties, fatigue, and loss of appetite. Symptoms were rated on a scale from 0 to 3, where 0 indicates no symptoms, 1 indicates mild symptoms, 2 indicates moderate symptoms, and 3 indicates severe symptoms.\u003c/p\u003e\n\u003ch3\u003e1.4 Mental health status Assessment\u003c/h3\u003e\n\u003cp\u003eStatistical Package for the Social Sciences (SPSS) version 23.0 was used for descriptive statistical analysis of the data. Descriptive statistics provided an overview of the sample characteristics and the distribution of the variables under study. Correlation analysis was performed to evaluate the relationship between BDI-13 symptom scores and traditional culture. Correlation coefficients were calculated to quantify the strength and direction of the associations between these variables. Multivariate linear regression analysis was used to explore the relationship between BDI-13 symptom scores and traditional culture education. Regression models were constructed to control for potential confounding variables and to assess the independent effect of traditional culture education on BDI-13 scores.\u003c/p\u003e\n\u003cp\u003eThe independent variables were factors related to traditional culture education, the dependent variables were the BDI-13 scores, and covariates included age, gender, major, political affiliation, and the major. By including these covariates, we aimed to account for possible demographic and educational influences on mental health outcomes. The significance of analysis was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Current Status of Traditional Culture Education\u003c/h2\u003e\n \u003cp\u003eCultural confidence is a significant manifestation of national identity, reflecting a profound understanding of one\u0026apos;s own culture and a firm belief in future development \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. In our survey of traditional culture education among students in higher vocational colleges, we found that most students have a superficial understanding of cultural confidence and that their knowledge of traditional culture is largely confined to its broadness, depth, and inclusiveness. The survey indicated that more than half of the students rarely read traditional classics each year. Issues such as monotonous teaching content, overemphasis on theory, and a dull classroom atmosphere were noted in traditional culture education. Most students favored setting up traditional culture as elective courses rather than mandatory ones. Additionally, traditional cultural activities on campus occur infrequently, although events such as knowledge contests, plays, etiquette lessons, and dance performances are widely popular among students (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings suggest that there is an urgent need to innovate and optimize traditional culture education to enhance students\u0026apos; cultural confidence and mental health.\u003c/p\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eInvestigation on the traditional culture education of students\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe connotation of cultural confidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKnow very well\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143(33.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderstand shallow meaning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e241(55.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnclear connotation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36(8.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBarely understand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(2.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraditional culture is\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBroad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e407 (94.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e389(90.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInclusive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296(68.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAggressive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (30.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnconstrained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88(20.37 )\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eClassics Reading (per year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZero\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152(35.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOne or two\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e228(52.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eProblems in traditional cultural education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMonotonous teaching content\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165(56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmphasis on theoretical teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201(69.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoring class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131(45.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe School Neglects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68(23.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraditional culture course\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeed not involve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31(7.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElective courses should be set up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e299(69.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompulsory courses should be set up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58(13.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHard to say\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44(10.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraditional culture campus activities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlmost none\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58(13.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccasionally\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e238(55.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFavorite traditional culture campus activities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKnowledge contest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e255(59.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrama\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e283(65.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEtiquette, dance, costume show\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e297(68.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePoetry competition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e162(37.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChinese Traditional Performance Arts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160(37.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvening party\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e168(38.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReadings, lectures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127(29.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e2.2 Psychological Challenges Identified Through the BDI-13 Assessment\u003c/h3\u003e\n\u003cp\u003eThrough the assessment using the Beck Depression Inventory (BDI-13), this study identified that college students generally face significant psychological challenges (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Prevalent issues include depression (20.37%), pessimism (32.87%), and dissatisfaction of life (20.37%). There is also a notable lack of self-efficacy, manifested in feelings of failure (27.55%), guilt (26.62%), and self-disappointment (24.07%). Social withdrawal (25.92%) and hesitancy (25.5%) highlight social and decision-making obstacles. High incidences of feeling Difficulties at Work (26.2%), fatigue (30%), decreased appetite (22.22%) and distorted body image (14.12%) also affect daily functioning.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssessment of students\u0026apos; negative mental symptoms\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSymptoms\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88 (20.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e142 (32.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119 (27.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88 (20.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115 (26.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104(24.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42(9.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e112 (25.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110(25.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61(14.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFDW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113(26.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e130(30.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96(22.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Correlation Between Traditional Culture and Mental Health Status\u003c/h2\u003e\n \u003cp\u003eThe study shows a significant correlation between the perception of traditional culture and the state of mental health (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Positive cultural identity is negatively correlated with lower levels of depression, reduced pessimism, and other psychological distress factors such as self-reproach and disappointment (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, negative perceptions of traditional culture are positively correlated with these mental health issues. Furthermore, active engagement with traditional culture (such as knowledge acquisition and positive evaluation) is positively associated with mental health status, whereas negative cultural experiences can lead to a deterioration of mental health conditions.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Results of Multivariate Linear Regression Analysis\u003c/h2\u003e\n \u003cp\u003eThe results of multivariate linear regression analysis indicate a positive correlation between boring classes and depression and indecisiveness (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while participation in plays has a negative impact on depression and pessimism (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Classic reading shows a significant negative correlation with pessimism, feelings of failure, distorted body image, and work-related difficulties (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cultural confidence significantly reduces the feeling of failure (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Moreover, the introduction of courses is associated with dissatisfaction in life and feelings of guilt, while positive cognition correlates with negative tendencies (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Negative cognition, however, is positively correlated with indecisiveness, work-related difficulties, and fatigue (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings emphasize the potential role of traditional culture in promoting the mental health of college students ( Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eTable 3. The correlation between traditional culture and mental health status.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cimg 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vKmA5aeYeY0YQzIKbTCui7phpQ1W32DmNmZQ8pqZHljRgcdd4E3TuLYhBnXJL258of/npTkShXhcADTnjcrshsk/UuTgLhamq6MjgWfL4UUUeGi82ZkmJFfRZ6CZb01GGV6Bj4vifffdx4FfCYOlC6+//rosVUUHBfWFgTvqB8mpOnXqyCwdkgi0QccPsY2lvqoXYhudO7/YxqwFLMXBZ+iEY9n1Sy+9xLctFwBcJwcPHiyxS4qGGTNmyEP8EecYMCLOUXbBBRfIIByzL82BOpKBWNr7/PPPS/24n+enzwXEA+nr1q0bueeekeiBxBQe4I+Yxksm0kncYSkgbnLiuorl8vj/F154Qd6ane+4tUHbAW0qV67sWBwHn6ENwvPqzOf9KfpcQLx0AX2WfG1X0FeDrrgp5rUCAdrh7er6jEQuQ03Np59+Gn/BB1bKoP/23HPPSb8D+uqS3/bt2/tqjrflY0k6Nc9+mPwjRYY+bB93p7DkC+COlt+LKID6mBsuhkggksLBT2NNXJH0QHIDz1zEYA9JEeiJJDc6d7hThvgnJQ+eqbNmzRp5hhrq6LrrrpOODuoPiSx0ap588kn5jBwDz/fDi1Qw4PjZz34W1wuDOtx5d89o0jcuQ2ssyQGTJ0+WzjoGQKRgYBkp6gLaksIHg3LEOZbSXXjhhaIz9MYgB0kRxL4Z57q0F3aYCYFBu/k5zgvMNEYZZgHyJTdFC95Qi+WP0Fs3JGcXLFggiVziDXTTN9fiHMDLFfASEPRbvJJTbtQf54K+XRnPuly1alVk3/YbFn0xhakNknbQBi++8tJGl/aiXTGf96focwFRhuRWvt5Mw4xqLC3FzEi/Zc9IYCNxhWWoXPrrz//8z/9Y5cuXl7jDknPE6bhx4yROzRepYLbpwYMHRdcgzZE0RJ+PS3+zm1KxiuaVkRBCCCGEEEIIIYSQCMLbyIQQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiJKKTuG8/+hKVWqlPN/hBBCCCGEEEIIIYSQbIUz/wghhBBCCCGEEEIIiSgFmvlHCCGEEEIIIYQQQgjJfjjzjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQkggy5Yts55//nnLtm2nhBBCCCGEEEJIrsDkHyGEkEA++OAD67XXXrP27dvnlBBCCCGEEEIIyRWKJfmHWSNVq1a1SpUqlbRNmzbNsTpGkO3w4cPFBgPQjh07Jn3u3ho2bGht3rw5cJ9qQwoX1JWX3u769iOMv1+9Ija8khS9evVKsoU/9pPLFJXWU6dOdSyOaV2tWrUkG2i9d+9ex8qS7zzhhBOS7LBB/3ycOTZixAhPTUx9g0D71KhRI/Hp2bNnoIZhbMPWpdrhdzZp0kRsdP/ZVpdBGqf6nX6+U6ZMSfCFHtWrV0+y69Chg7Vnzx7H6jjQqnHjxmKTqt5yFWh34oknJmni1s6PsP4jR44M/T29e/f2rM+hQ4daP/30k2OVW/gd/+TJk1PqDN/SpUuH9kXcNm3aVDTs0aOHdfToUecTb3Ctvfzyy8Ue19NFixaFqvtcYtSoUZ4aTpo0KVRMhfGfMWOGVaZMmSQbbKiHI0eOiB1Yvny5VatWrSS79u3bWzt37nSsogP089Jm4sSJofUP4w9da9eundR+uHVdsWKFr93333/vWGU3o0ePtsqWLZvw+7FNmDAh5TkP0vHfsmWL1aJFC9Gre/fu1qFDh5xPjjFz5kyrXLlySfvC5mWfjfjpMX78+JR6jhkzxvP4vXwHDBiQFMsNGjSw1q5dG293EZ916tRJis927dpZO3bsiFz7TArGk08+aVWoUCEhRrC9/vrrCdcbP/z8x40bZx0+fNixOmZXsWLFlHaffvqpVa9evaS4bdu2rbV161bGbWESE7PIWbp0qV2lShV72LBhTsnxMvyE2ADNKU3PVokNWO3YAMyONYD2pk2bnNLjeO0TxAZksk+//ZKCoXqjTlA3APWC+vGrI5Ow/qhP82+1QX266xp/oxx1HiUKQ+vYgE389+zZI2Xwadiwofhv3LhRylRr/Vtt3FrjPIo11nZsUO6U5Ddh9fVj+PDhoqe2U7FBoB0brDifJhLWFnbm7wG9evUS36FDhyb4aLnuE1uY312cQONq1aoladyoUSP5rd9++62UeWH67t69W8r8fKFbx44d43bAT7d06i1XWbZsmWgXG/Cm1M4LP//GjRuL/4YNG6QsrB2YNm2afeKJJ9pDhgyxY4MmKVNbtJOLFi3KuXrA8VevXl2Of9euXVLmd/xu/HybNGkivt98842UKSNGjBD9NG5jA287NghwPvVGNf/FL34hbd3ChQsjFevQsEaNGqLhzp07pWzz5s1206ZNRcP169cHHm9Y/+nTp9ulS5e2J06cGI9dP0aOHCn1r766P7Q5gwYNSllnuQT0q1mzpuj3/fffSxmOt1mzZqLfunXrUupfq1atUP6qq5apneoaG6iK3ahRo0LZZSvLly8XTdq1a2fv2LFDynAMzZs3F03Wrl0bqCn8a9euHcofWpUpUybepnTr1s0+ePCgfKbMmDHDLlu2rD1+/PicjF1Tj+3bt0sZ9GjRooXosWbNGl890/EdPXq06DRw4ED70KFDUgbtypUrZ7dt2zbuDzu08eqr+0N8mr4kf1mxYoVdt25diZutW7fG46R169YSd6tWrfKNWWD6b9myRWzxb5s2bcR/5cqVch0LawfGjh1rX3HFFXE7cOedd0rMP/roo/aBAwekjGROiSX/gJZj4KWJi3RsFfyNcgQSOrZu/PYJ9DNs+H+SOUiweemJxBAu/l71YJKJv9anV0xFLfEHCkvrJUuWOCXH0CReKq3diS0m/xJBcihIX3fSyET1hZZo15AwRH152adj64X6eyWp9DPEU9DvLSmgMX7f4sWLnZJjICmRSuMg3xNOOCHl8UIbJKZM3bRM6wLJsCgm/26//fa4duaxqXZIwAUdcxh/dArD2gHYIvbdCTEktWA7adKknKuH3r17y/G7E5c4fnei000q38GDB8d9NVEIjZDcx+ARcRs0GNdEIuxwriDuo5b869Onj+dxabIOGgZpFNY/neSfF15JsijQt29f0W/BggVJ+iGplCrZqf7z588vkL8mylLp6pVQy1b69esn5zo0MWNNk3BPPPFEYAJT/efNmxfor4ktJPVwMwjJQdxQiFryL0gPJOaCEm5hfTWBhzjUJJ/Sv39/2ccnn3zi23agLs4444x4kjFKbTRJnzvuuENuSs2ZMyfhnJs5c6ZdsWJF+7HHHgtMtiEph+uN23/WrFl2pUqV4v6p7FIl9ZA8POuss+wuXbrY+/fvd0pJppToM/9iAWGdeuqpMl15r7HczAu1LWzOPfdc649//KNMhX7//fedUlJQYhco6+OPP7bOOeccWfJmErvwWFWqVJGpvX5k6u+F1uv9998v/0aFwtB67ty5hao1OU6Y+vnss8+ckmTQNm3bts265pprnBJ/0rENS2xwJNPvO3XqZN1zzz3WjTfeaMUu2FLWM0uWsWoMn3322bI02QTLsqpWreobw6avu37gW9D4R1189913hVoX2YbGtmpXqlQp55PE2PaLkbD+7jpy26F+3efQ7t27ZZmZ+7uxT/jkEqpTmzZt0tZZtQvy/fzzz+O+aKewtOa6665LsA0CzwGNDSKtxx9/XJYlRw3EEfRv3bp1kobaRgTFOfxRB37+Gr9+/vlOKv00hhGDXpj+uD546R/kH0VUk1atWommuJ4r6WgKf2jq9jc1Rbu9ceNG6TtEsX0A0OOTTz4J1POLL77wPMdT+UJL+EJLtM24tmG5/0knneRYHeOGG26QzzZt2sS2hKRE4w5L8f3O4S+//NJ3ubr6N2/ePCluEZ8a84jHILtU30OKjuM1UYLUr1/fOvnkk52/vFmyZIm1Zs0a6bS6G75Mad++vQQrnjvBB9pnBhoFXIS86kkTuOgM+OmcqT8+QyLX9McAHn7wjxKFqbX7/DP9/RLzXlqT42RaP8UJnleDurzlllucEss677zzrP79+8vNGfx+HAuekTR8+HDr1ltvdaxKFtUYHRY/jdEB8dLY9PWLf/gG3ZiCbtu3b7duvvlmpyQ/0IGIl+41atQI1B2k8j/ttNPEf/Xq1dauXbtCf899990nHczbbrtNzi2AJPbDDz9sXXHFFRLTYRNb2YDq5NWG6PH7tSHwhXZ+vtA4k/Zn+fLl1uDBg+UZVPiOKJKqfdE49dMQ/n7xm6p9ShfsB204vitVfzpXSKVfGP2D6i+M/trP8Uq6mKhdtuuv7YLX8Wi7gBsHfppom+TnD02D/KOGqae73k09vfoRqXxNLcMk9VauXOmbtNX2Qestl66DpHDBzWk9hxF3ZixUr149ZdzBH3GLNtTtrzGPtlf7b352+B7Y4dzwi++nn35afgtuSuJZl6RwKNHk36uvvioJvSuvvDLwotqrVy+ZRdGgQQNr0KBBTmnhoZ2AMDMQSTgw28ANTn4kesNQUP833nhD/tUkBhovdMrgd/fdd0vjY25IZOQ6JaX1m2++KQ02Eh9mow6uvfbayOlcUDDrwE069VMULHO99OMf//iHNWTIEOvqq6+WvwE6Bs8++6z8VrBu3TppHx988MEEu2zAL4bx8OBUpBP/0A2dI7duuD5lkx7FBbRzH3c6sY1zw8vfXW9+55DbDrPXXnjhBWv9+vXWmWeeKftGrHbt2tX6+9//nnDnOZfw0wk6p4q7II1T+QaBh9Rj30j+5aquYfHSEH3WsBqm449ZPJglhXJsaF/CzIzQlwNgllXU6gP6uY8pHf0xs6qg/voCi1Sz18LaZQuZapqpvxc33XRTwotxMN47EuLFA9lAJjEGX7eN21fHqfPmzZNEnpksQcIZs6iCvgc3bqEl2hdoTEjLli2TYlb7Bu5yLxC37rZO49b0D2sHMFlHyxHPzzzzjPW///u/1vXXX8/kXyGSunaLACQCUKm/+93vJKGHjrkbfAYbbC+99JI1bNgw6+uvv5YBaWGjnWiSOXr3M4igJGsm/tOmTZNY6dChg7wdyOS9996zPvroI2vp0qVy0cS/mO2JOINfLpKNWmOgjTuP0Bjb1KlT4+e6+22yUSfT+ilKPvjgg6TfFrTEFQk/3MVDJzObQCcYM++CgMZ7PN7Gq3fCg3DXD3Rzf19BlgbnOhrb5gDETWG0PV999VUoO7N+f/3rX8vbUdHu5DphdNKkvJswdQRfr3MjFZhNifYfN9ROOeUUpzR6hGkjVEMvndPxv/LKK+XNh3rthMYYpP/+97+XRy9gBoUfM2bMsF5++WXrV7/6lVyPwwzccgHVL0wM++mf6voQ5K+6/vKXv5Q3pfrpatplu/6FpWlB/b1A7B88eFDssUFPvP0Wj2S67LLLsvoNyumc42490qkLzJS64447rG+//VbGzZocwYabXmjv/faDVW0vxdrrSy+9NDCOSX4Q5hzGDVTMDvQCM/FSxS38MRMVjyPym40KYGeeG7Nnz5aZhea+sYSYS4MLl2JtATShh39BUEIPn6Hy0alFgqEokzT4DgwgkABEIpAUHCz/QVItiCCdC+qPxghLvnBRRCcMdxVMEEO4iOJ5XAD/vvPOO/JdOlsw1yhJrfH8RHyGDkXQOYNkIBp2JP6wTGzVqlXOJ9EB7ZLZEcOGZ+IhUZZJ/RQlSOaZSVrckHnllVdkkOmXsMlG9I53ENDYK0FRkPrx0w3xjTiPGkhAmLOQNLZxzYZ2+NuPoNgO2/Y0bdo0lJ3WL9oYDJJw02HhwoVSV7fffns8trO1jjTRY+qMBCZme6Q6ftwl99JZNQ6qI/imm7xD+4/zADdts20GcEFBsgGzCtz6Y5ZvGP2hoZcOYdoYP/+rrrrK2rlzp3X55ZfLcwExkEKb4wbLplAfmOmK2a1YcpVrQP+yZcsm6N+9e/e4/l7aKqn0T3V98POHrg899JBVp04d68UXX/TV1W13+umnO59kJxqTmWpaUP8wIBmI5AT+xfMDg5azFgdInpUvX16OR7du3bpZhw4dyugcT7cu7r33XrmuoW1XHySbMbkB+/LaD+IT42f4YFZ85cqVA7+vpMFzpStUqCC/UTdofeDAAceCZEqYc/iss86SmaZehOn/wR/PE8QKo6BkM+zMcwM3FH/44Yd4H3vs2LHW5MmT5XqIZfJe10CSPsWa/NOEnm64YKYCSRwkc5DUQXIHHc/CBo0jMtxoHN1JI1IwvGbDaJI1DOn4IyZwRwt1iKWoXslk+LmTGjqNHnfMcvn5JMWt9X/913/JLAQkTXERSQXOKTxvC3eKoHXUOP/886V9MjGXQ7pfSADSqZ/iAEv3kCBHJ/LDDz/MuQusXwwj4Z+KTM4f6IbEH2YE5qJuqcAz8tyxjeVeCrRzH3M6se31sgOvevM7h0w7tOGPPPKItDdIAv7sZz+TcxADciRpUT9Yxl6Sg0g/VGezM+1uQ/x0ThVzQRqn8vUCL/nATVv0y8yEJRJQuMt/4YUXSoI4l+7Ue+lvLtX10hDxFlbDgvrrtRNJQMzWcNui74rBPxIl//rXv+JL3XMN6N+wYcNA/d3nbTr6e73AIsgfumKGFOIZjyfy0zWsXTaSqaaZ+qcCsY/EN/qaQbPaigNMFvCKTzOpkW6MmcDXbePni5eoYPYfvgufoe+BWZPoX7tfqoD4RL8OM6lwAwyJlmyPT8xihNbmcWB5ai4spc819GUyJto3cJd7gbh1X+c1bk3/sHZe9O7dW27c4iVD6MPlymMAsp1iTf4VFCRz7rrrLnk+IF78UdjgbbBoOM2H3ZOCEZRQC5NkTdcfNrhDj3LM5NOZfQrsYB9FClNrNPgmpr/OKsF3YFCHztjbb78tHXZyrH3Cklh0xHTDndZM66c40fMkVwYuimqMgbGfxkhQe2ls+vrFP3yDZmZiv2ES4LkKYhuzdc3YxsszUO6nuz4Q3k93oA979vNHGwP/Ro0ayYybMN+Dc3DFihXWJZdcklQnnTt3lgHFW2+9lVTX2QD01NktXjp7tSF6/H5tiD54288XGhdV+4OOOuoMx5ELoC3AEnNTfySSoU9Q+6Jx6qch9usXv6nap1Rgf5jVir4rZs5dcMEFOdd+K9Dp3//+d4L+WO4M/YP0C6N/UP156Q87DDiRUMWMXOjqNXMlrF22oe0CbuS6NdF2Ae2On6badvv5Q9Mg/1wEcaSJEo3PP/zhD3Lzw9TTfW0x9fTqR6TyDaslnueHxDP65BqDqJu+fftKYnrKlCnWz3/+85yIT2itySLV+k9/+hOf91aImC/1QNxBY8V8GQjizuuaAn/ELdpQt7/GPOpR+29+dvge2OHc8Lt2VapUSdroXIjdXCJn1NQ38o4aNSrpgpMJWLKHgbr72WWkYKDBwCw8ryWeYZKs6fgjDvAQUMxWwnIXd+JPwQwKr8SxvkEaSwtysaNSGFpjoOznj06tvsUUWuNBwe+++67MpEkn8QdfTOXH+YvOfL4QVD/6zD2vl6WUBKgjJAmwJAR1lCuDSI1hJH2QPDHR5/P5nQOmr1f9mPHvB3TDwDLXdMsUjW3VzuzUadsTFNtB/ua5gU6fWUduO62jVLprRxP7C0rmZhuqE2ZY+h0/HpLv1THW+PbzhcZ+vkE88MADcvcd+zO3ESNGyBIfLEvDzMBcnYVmgoEJ9McsJ7eGmIUQpD+AP+rAzx8D8yB/vXZiKSliV/VEOeIeNzz/+te/xme5Ro1U+kH/oBdsmP7uZdOqv+kPXXG9wM1NzBIOSvyFsctGVBMkWKCpOfMmHU3h716O66VpQYHGuFmD5EE2X1uhx8UXX+ypJ54zDj31JT5uUvlCy1Qv6MC1Ecl/JPe0jYB2eOM99MPbUjEbO1fikxQ9Gndffvll0jmsz9zD23XxKAYv1B83bNxxa/rjUQhh7IISu/v375c+NtoBJgELkdjFsMhZunSpHRv428OGDXNK/Amy7dmzp3wGG5O9e/faHTp0sBs0aGDHgsQpPY57n/o3Dh+bnx8pGFOnThVdzbqC9ihDHSpeZSCsP/4fZV6bWaf4F3+jHPsG+h25XveFoXWssyD+S5YskbKCaL1x40bRsWHDhnIu7tmzR/zwm6pWrSp22G++4aXv8OHDpaxHjx527GLoW2ai2qIevD43CbLVz8zfo2WoI7/vz2amTZsW13jx4sVSFlZj+MY6Eyl9oVGjRo0S7LQsSDe1yUVdU+HWDscH7VCG4z169KhjeUxTd3lYfy+7ESNGJNmhH9CpU6d43Wk56qBx48ZST5MmTcq5esDxxwaOcvyLFi1KOP7u3bvbR44cETuvMj9flJl2bqBZkyZNREc/GzfYb7Vq1eyFCxfmnMZBTJ8+3Y4NvkVDPbaRI0fGNTx8+LDYeZWBMP6bN2+2mzZtardv397euXOn+C1btsyODbIkbgcPHpxQD3369JG6xmfurX79+vb69esjUwfQLzY4tCtXrmwvWLAgrh807datm33o0CHH8lgduMtN//nz5wf69+3bV+rFT9d169aJf1i7bGXGjBl2bGAf1wRt5ahRo0QnaHLw4EGx8yoDpv+8efN8/U0Q482bN5eYNz/XcsT+jh07pGz58uV2bKAvbfkTTzyRcD5lI9CjXLlyCXqMHj1aNOratWv8eL3KUvkeOHBA7HB9u+qqq+wJEybE2wK1Q8ytWbMmHnP9+/eX+PaLT9OW5CczZ860K1asKHE3Z84ciamxY8fa5cuXtzt37mz/8MMPjqWdUL5//34pmzVrll2pUiVffy+72bNnx+0qVKiQYLdlyxa7TZs2Ml5UOy3Dtc60JZmTU8k/TXS4Pwub/HM3gtiwT1L4aF2Zm1fiyascpPLXOnfbmJsZJ14xkOuJP6UwtEYny88fWnfs2DHhc/emWvfq1cvz8ylTpsjn+YiXvhhUm50vtTHLzcSp1zZ06NAC2Xr9Hmzu35RLIMmRSmO18Sp3D6S9tPCy87JFXSAJ4rbTzayLXMdPO028KWrn/ixd/1R2ZgLQtEXbr8mvXATH7042uJN3auNXHuQLkGyqXr16gp25IQHl1tskqsk/oAk8Uw9N3Clq4y4HYfz9EnoTJ05M0B0xfvnll3va6jZo0KCk+s1lNIFnHqM7cQfUzv1ZGH/oesUVV6TUddeuXaHsciFhhcSR+bv9knxeCb0w/mYSz7TTTRN7/fr180ymvvnmmzkTx5rEM3+/meQDauNX7vbVxJ/ildRr27atvX37dsfiWBwjSeiXnMY2cODApHOH5B+aADRjw534A7BDAs+dgNPEntvfnaTLxM7PlmRGKfwnJi4hhBBCCCGEEEIIISRicPE0IYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEJIhnz66afWiy++aB0+fNgpISQ7YPKPEEIIIYQQQgghJEM++ugja9y4cdauXbss27adUkJKHib/CCGEEEIIIYQQUqKMGTPGKl++vFWqVKmE7Y033rCOHDniWPmzZcsWq3Xr1taJJ55ode3a1Tpw4IDzyXFWrFhhnXnmmdYJJ5yQ8B3t2rWztm3b5pmw279/v3XNNddYpUuXtqpUqWLNnTvXOnr0qPPpsdl+devWtd58802rfv36sm/8ljZt2ljdu3e3fvzxR8eSkJKDyT9CCCGEEEIIIYSUGEjKDR061Lr44oslCffTTz9Zmzdvtlq2bGn94Q9/sL755pvAmXRjx4616tWrZ33++efi68fs2bOtSpUqWatWrYp/R6tWraT8ueee81yuO2fOHOu9996zfvazn0li0Q2SfFdeeaUkHJEknDlzppTt27fP+r//+z9JaBJS0jD5RwghhBBCCCGEkBLjqaeeksTbY489ZlWuXFlm49WsWdMaNmyYJOhee+013+foIXE4ZMgQ65VXXrE2bNggyTzMvvPinnvusf7zn/9YDRs2jH8H/GrXrm29++671u7duxOSjJjB9/DDD1s33nijddNNN8nsPy+effZZa/HixTKrEPt9/PHHra+++spq1KiR/E1IScPkHyGEEEIIIYQQQkoEJNiwlLZFixZWkyZNEpJltWrVkqW2X3zxhe+MvrPPPluSfjfffLNvcq6gYMkxko7/7//9P6tcuXJOaSKzZs2yKlasKEuHe/XqJb/jgw8+kBmGmA3IZb8kG2DyjxBCCCGEEEIIISXC1q1bZcYdEn0nnXRSQvKvRo0a1qmnniqz/7CMtiheooF979ixQ2YBnnzyyfHvx7P8sBQZCT2d0efFOeecY/Xt29dauXKlVa1aNWvPnj3Wq6++ag0fPtzq3LmzVaZMGceSkJKDyT9CCCGEEEIIIYSUKFiu636mHpJxeJaf3zLewmDixInyQpEbbrghYebgX/7yF6tp06ZWv379AhN4SBrimYOYoYgE4fr16yUBiCXG1157baHPRiSkIDD5RwghhBBCCCGEkBIBM++2b98eOKtPE2qFDZbsvvzyy9Yll1xitW3bNp581PIBAwZYp59+uu+sPzdI+P373/+OP1OQkGyByT9CCCGEEEIIIYSUCFjuW7Vq1cBk2VlnnWWdcsopzl+Fg77MA9///PPPx3+D+ZIPvL2XM/dIFGDyjxBCCCGEEEIIISXK559/bh09etT56xh79+611q1b5/uyj4KCBF+nTp3kX8zwq1+/fjz5iJd8rFq1yvrnP/9pVahQQcqx3XvvvTJL8dJLL7V69OhhHThwQOwJyQWY/COEEEIIIYQQQkiJEPRSj6CXgRSU/fv3W/3795d9T5482brooovSfqbgvHnzrI0bNxbJC0gIKQqY/COEEEIIIYQQQkiJgBdm4Jl7X375pbwx10yozZ4929q2bZt1/fXXF8ryWyT+8AbemTNnygs9LrzwwqTEH57bh1l9+B3mNmbMGElCfvzxx9bq1av5XD+SUzD5RwghhBBCCCGEkBIDb9rFDD88Y2/+/PmyzBfJNjx776abboo/ew9v1S1fvrzVtWvXAi27ffDBB6233npLlhffeuut8hZfXdaLpb9ff/11QvKRkKjA5B8hhBBCCCGEEEJKjCuuuMKaOHGi9cMPP8gsQLx197777pPE39/+9jdJ+IHGjRsnzdRbsWKFdeaZZ0o5Zubh2YHm8/oGDhxoHTp0SGb9bdq0yff5gXi24Lhx46zDhw87JYREh1I209qEEEIIIYQQQgghhEQSzvwjhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhJCsYMWKFdYLL7xgHT582CkhhGQKk3+EEEIIIYQQQgjJCj766CNr3Lhx1u7duy3btp1SQkgmMPlHCCGEEEIIIYSQEgOz/c4880zrzTfftBo0aGCdcMIJ1pYtW6zWrVtb3bt3tw4cOOBYEkIKQimbqXRCCCGEEEIIIYSUIHfccYcs9z1y5IhTYln16tWz3nvvPat+/fpWqVKlnFJCSLpw5h8hhBBCCCGEEEJKlGeffdZavHixVadOHUn0Pf7449ZXX30lMwGZ+CMkM5j8I4QQQgghhBBCSIkxa9Ysq0KFClb79u2t3r17WzfddJP1wQcfWBUrVrS6devGZb+EZAiTf4QQQgghhBBCCCkxzjnnHKtv377WypUrrapVq1p79uyx/vWvf1kjRoywbrvtNqt06dKOJSGkIPCZf4QQQgghhBBCCMkKxowZYz311FPWjBkz+Kw/QgoJJv8IIYQQQgghhBBCCIkoXPZLCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYQQQgghhBBCCIkoTP4RQgghhBBCCCGEEBJRmPwjecWyZcus559/3vkrmHRsCSHEjbYhtm07JYTkHsuXL7f+9re/WT/99JNT4k86tiQc1LTkWbFihfXCCy9YR48edUpIUaA6HzlyxCkhYaBuhJCwMPlH8or333/feu2116x9+/Y5Jf6kY0sIIW4++OADa9y4cdbevXudEkJyD8QxroVh4lht9+zZ45SQTPnwww+lHaGmJQfqAHG9e/dup4QUBYz1gvHRRx+JboxPQkgqiiX5h9kPVatWtUqVKmX16tXLKT0OkisdO3aUTRMtpo97Gz58uNion5eNuTVs2NDavHlz4D7VhhQOqCMvnadNm+ZYpAb1gXqBn1fc+NWnGUdA7fDdTZs2lTLdt3u/6dhmC5lq7ec/depUx+I40MBtB72WLl3qWOQvI0aMsE444YQkfbx0dJOO7+233+5pO2zYsLydYRakXxhNcI43btxYfHr27Onr4/c9U6ZMifugDalevbp8d5MmTaRsy5Ytsv+gfWczOO4TTzwx8LiDSMe/d+/eSRqjjVmyZElOapcOI0eO9NRp8uTJoY4dcYzrFvTr0aNH0iwl83P3d+imfphtVrNmTfluPTfUH3Fs7tvLFjHvZZvNjBo1yipdunSCHtgmTZoUatYdjrlZs2Zx/YNm4aSyhaa1atWS727UqJH8DugPn1T7zlWgf5kyZZL0nzhxYuhZj9C1efPmomv37t2tw4cPO58cA7rWrl076Rxo3769tXPnTsfqGJhNBVt8v/ZFdf+oA/e+c4nRo0dbZcuWTdAA24QJE0Kfr9CiRYsWca0PHTrkfJJIKjvofMYZZ8h3q86IdfhAZ7/9Fjd+mo0fPz4tzVq2bCladOvWzfPYoEedOnWSYrRdu3bWjh07HKvjdvj+Bg0aiL3uH7odPHjQscw9xowZY5UvXz7h+LG98cYbKdu+sWPHpuULzVq3bi3X3q5du1oHDhxwPok2Tz75pFWhQoUknV5//fVQ1xc/fySh0TZu3brVOvvssz37NLp16dLF+uGHH5w9kmIj1qEscpYuXWpXqVIFPVf5F3+b7N271+7QoYNs+H+gPrEBrfwNzP3EBlZO6XF0P7FG0N60aZNTehyvfYJY51T26bdfkh6qs1mfqA/Ui1/duEEdaZ1gQx25gY25P/0O2AfVsW5+vyUd25ImU63hHxtYi/+ePXukDD6xDpj4b9y4UcqA1gn0iXXEnVIC0tHRTTq+aJ9iF0x76NCh8TpQW8TBkiVLpCyfgH7VqlVL0i82YBb9vv32WynzY/jw4aKpnuuxTrNnfJvfs3v3binz+55evXol7BNbmN+SjSxbtkyOOzY4TnncXqTjj7qIDWCkDmKDKac0P4BO1atXF5127dolZdCpcePGotOGDRukzI8RI0aIdhpvsUG2HevAO5+mZtq0aXask24PHjw4rn3v3r0T9omtfv369jfffCOfmwTZ5sL1AvrXqFFD9N+5c6eUbd682W7SpInon+o4Ro4cKfrpsUP/2ADI+TSRsLZ9+vTx1HT9+vWRuwZD/5o1a4r+33//vZRB/2bNmon+69atS3nM0LV06dJxrbp162YfOnTI+fQYsME5pfvT70B7PWjQoKR66Nu3b0JdaR2E+T3ZyvLly+1atWrZ7dq1s3fs2CFl0KF58+ai9dq1a1Me26hRo+wyZcokaH3w4EHn0+OEtevXr5+nzmF+S3EAzWrXri2abd++XcqgWYsWLUSzNWvWpPydo0ePtsuWLRs/vq5du3pqATu0O7pP/R7E6MCBAxNiun///gkxr7qF+T3ZCrSuU6eOaL1t27a4Bi1bthStv/76a99jM32/++67uG+rVq3Ed/Xq1Qm+Y8aMscuVKxfXrkuXLvaPP/7ofBpdVqxYYdetW9du27atvXXr1rhOrVu3Fp1WrVrlqzEw/bds2SK2+LdNmzbiv3LlysA+3KxZs+xKlSrZjz76qH3gwAGnlBQXxZr8u+222+RfdyInbPIPaLlpq+h+EHjoNLvx2yfQz7Dh/0nBQf166YjEBRpXL/1NtC5gj3pEfbpjxg/19YoP/Syd3xDGtiTJVGv1dyeNNMmk/tg/ElRh6yHfQLInSEczWecmHV/Y4nxwJxM1gTVlyhSnJH+AJojNxYsXOyXHQDIjlfaIaySmoJsmpPySf0HfgwG6+3t03zgPg35DtnP77bfHj9s8Bj3uIUOGBB5bWH9NEuZj4g8geQadFi1alKQTBsXQyU8XTRxOmjRJ2gYMHKFj2OQfrpWXXXaZ3ERwJ/Y0KYY4NhODXqRjm20g0Yb4W7hwYYL+06dPl8E1jsdPTz3uiRMniv5NmzYV/b0SerBFkiuMLVB71TSdhG4ugSQb9F+wYEGS/kgeITEXdOyq04QJE+SGAhJ6SKq6k39ewBfJMDPxaKLJMlxPvBKEuQYSbWgv5s+fn3COzpgxQ5JTTzzxROAxaiJs/PjxojWShtDancgKa6eoPXRO9RuKG9Vs3rx5SZoheZSuZkjmBWnhBv5nnHFGQvJR0c+gmzs5mIsMGDBA2tO5c+cmaD1z5ky7QoUK9uOPP+6rWzq+0A2JwjfeeENuriFBiOR0PiT/7rjjDtFpzpw5Ce0qdKpYsaL92GOPBSbl7rzzTmlv3f6a1Avy37dvn33ttddKfztVkpAUDcX6zL8LLrjA+vWvf2299NJLaS3/NIkFm3Xqqac6fxUe5557rvXHP/5RplTjWW+kYGzevNn6+OOPrXPOOUeW/5hgWn+VKlWsTz/91CnxBnURu7hZV199tVOSGYi12EXR6tSpk3XfffdZN954oxVr4KQsNqB3rI6Rjm1Jk6nW8I9dIEP545yItReiCUkkTD189tlnTkkiBfHFM12wTMENbOGTT2gMY2mBLrFVYh1tWS4adA6grfnuu++sa665xinxxvwedz3he8xzJTZYlWUOaEPuvvtuaUNiHSIp65ljy341PvW40Q4qZnz6HVM6/nrdRRtj2uUDqlObNm0KpDPaDyyxue666wqk3erVq2U55MUXXyzxDBDHWAKLx2j85je/sW666Sbr7bfflrIePRKXFKdjm42gPYX+WPrl1l/P71T6Yx/XX3+9LL0LArao71S2M2bMkCWw0DQ2UItrimWH0DQ24HIscx9oh/Y1SP/PP/88cOmv6nrDDTdIW1sYoA7KlSsnS4IHDBggbfk777wjZd09lhTnAqp1q1atRGszBsNqjfZ848aNokeQ1mHt0MdWnfv16yex/t5778V19loaW5xAs08++aRYNEsH6IblrdCtT58+ohuuo1iKiSXFB3Nw2a/GJ5Z8o09ntgV4DAK0/uKLLzy11nqCr7sd8fJFnWzYsMG6+eab5VqVL5g6QWN3PKPf/OWXX/pet9Ufjz9wnw+mzn7+X3/9tSxZR04I/Zug6yApGopd8fvvv18CA8/2MJ/LFhY892fNmjUSMCeddJJTWjigAcVvQ4NakN9GjjUKSE541Y8mbnEBLCp9sW8kcM3vP//8863+/ftb69atsypWrCi/D8/RGTZsmHXLLbeIjZKObUmTqdam/8knn+yUHsP037t3ryQ28DfKSSKZ1EO6vpoYQSxu2rRJypCw/t3vfmddeeWVkszKJ1Q/dFj89INOmbY35vf4nSv4Hpwr5513ngxg1q5dK78JDy7Hs4zQhtx6662OV26AhJKfvjVq1Eipbzr+SK6ccsopUm522vMB1cmrHVCdgtryTMHzlTAguvfee+MdcY1jdNRRL/h9eLYUnhGLODY77LDFddO0ffPNN+O22V6fxdWOpIPqj8TsaaedJu2IqWmUBkzQf9euXb764/iLUn/sGzecMXA1vx910LdvX4lrrQM8Dwt1cNtttxVaEqc4QVsDrd3HCtDW4DiRRC3OWEe/RWO9cuXKojOeG4ZnxWaDzqZm7uu/qRmu/0WFV4xCN8TnqlWrZOwK3fBSGo3PXExo6bVQj9O8dui1UOPTfTPGXU9uX7Oe/G7k5AO44a0au3XC86qDNAbwh85om/10Rpvup/PTTz8tiWncKESCnxQ/xd57QGOFGXa4q4O3OqUDZl5hhkaDBg2sQYMGOaWFh3byMGgrykY8H8AMBjdoJOrXr+/8VTTgga7ATNShgfvrX/8av2Bq/T700ENJswvTsc0WMtU6lf/+/ftl4Im/77nnHmnozQ0dDWLJrAU3YeshrC/azxdffFHiEokC6I82EXfH//GPf8jf+YhfDNerV8/5q3AIc66hDXn22WelHGgb8uCDD0obkot1hON2/+6wsQ1S+aOTiTYG9YUENxIbsNdt6NChgbMqogLaAT+d3OWFBWb8YeYe6sicLYE4fuaZZ6RPBHBDDIPLBx54QNoc8/fAFh160xYxj5u9sM2VRJWX/ugLFKX+fqA/Ck0xkAKqP86PXNI0HaC/+7igP9qFotQfN2fQvmDmlJloQh089dRTUgf4fo3rKNRBSWntBXT+y1/+Yp1++unyt8Y6bkZA52xJsmLmX0lphpfOYCYVZg5qUk91Q8JU41N1u/baa3MyOa1Aa/fvx7UQWqc677zqKaxvPqEvnjFJRyevOtLzwc8fE0kwwQovrnLPOiTFR4mojrfpIIGHCyiyy0FgRgsaNWwvvfSSzJ7AXTh0NgsbczBCCgYGcObbqLwoquQqZkAhRjp06GC1bdvWKU0ESbyw8ZOObUmQqdZh/dGZAEjYf/TRR/G3bi5dulSmh+McnRrijbZRJZN6KIgvEkhYPlrcHfRsRO+GB2HGcEHB9xSkjpHww2wGJGpzEY3PoLvkfrEN0vXHkiW0MYsWLZLB+LJly6xq1apZjzzyiLTvQfvJZcK0A5p4KGw++OAD+W4MGDFrzwsk/DC75Mwzz3RK/DFtc6WNCnN+q/4lEYNIoq5cudKqW7duJNt91T9IW01sFLb+WNqLfuMvf/lL6Tf6DUYxXkEdnHXWWTldByWpdRig81dffVUsCbWwhG0fikozJEsQo5deeqnEqFdSD+03dCuJGxWFCXIC6NMF6bh+/XrPPh18U8W2n28+gXgOozFmB3qRjs5um9mzZ8vMwTvvvDOetCbFT4kk/5BMueuuu2T57quvvuqUeoNkH4IHnS4kdZBowCCgKMB3YCCCxhOJQJI+GORi+nkQRaEvGiN0GpBUfvnll+XuQ9TJVOuw/jogxPmH8wNLYQBmoeEZREgAYjlS0IUgymRSD+n6ajIEbeDixYtFc8yIfuWVV+QZc0WRHMhmsEwM8ReEGcMFBd9TEu1aSaPxGdRBCzrudP3x6A30C/D4BfjgOV5oYxDzUW5jwrQDGAwXdnzhuonZfb/61a9kUJmvHfEw57fqz8FK4aP6B2kL/dGOF6b+WJqGm7xIVGNGvc6yjDIlpXUuE7Z9KArNEKMY9+Ia8cILL0jCJMogP4A+XZCOSMB79engmyq2/XzzCcRzGI11Jr+bdHQ2bbAs+7nnnrMuuugi6W/k03MWs40Sm2+JBxgjmYAp9eiApgLJHCR1ws4YLAj63Bc0svmQPCpKvB6yr8nVwgaxgDtiqDsMELN1pl5RkanWYf3xtzu5pEvlMXOlOJ8Rk43gmWVuwtZDGF/oixlQuKCizjQJ+/e//11ukmDWFJab5mMS1i+GcTe+MCnOdi2bwHG74yqd4w7rj7/dd+X1GTK4Wx31NsbrpRKqU1Gc13g+FGa3X3755ZFLXBcEL/0Rc0WlP0kE+ruX90N/tOOFrT/6++3atbO2bdsmkxCiOqvSj+LUOip4vdSjKDVDjGKcjJlSuMGb67NO0wFau18YoX06dx248aqnsL75hNeLU9LRyauO9Hzw8sdjubAqADd59VEKpGQoseQfkmtYyhBm9p9izhjE0sPCBoNnTGXNthc75BJByaCiSK7iO/DmO+wXb2HDbLR8IVOtTX80+CamP+zwL/Emk3pIxxcXTTyfC4lud4K7S5cucmMEb5V17yfKqH5eiSHVD3c5M21vzO/xO1fwPVFLoOgDtr301QdzB+kb1l/bmHztDKpOXu2A6uTXhhQUfA/aC8xYQfuRz8/eKa52hHgD/f0S/NAfD5cvTP3xHb1795alb3je5YUXXpg3bY/eTMFNc6+2Rl+YwFg/jqmZ+/pvalaY13/UDV7mgeT0lClTrJ///Od50UbrtVDj00yq6rVQ49N9zrrrye1r1lM+J57Ml3q4dTJfBuKlMYA/dEbb7Kcz2nRTZzw7HmN09GPwMhq8yZ6UHCXakmDaJ+5q/N///Z88TywM+kbegr4t2A99YyZ+D34XKRhoMJCcQJICyQqTwk6uov6vv/56iR3MfsqnxB/IVGv4X3LJJb7+6BjjFfgAD4P3Srrr27fxptl8nTkSVA/6PC3o6HURzcTXRAeohZ0gyHY0hlesWCHPYzKBfojhwmhvzO/xqifzXIkSGp963GYnT9uYoPhMxx8PoMcMKzxL1LTD3zo7LaqxrTphhqRbJ40vvIygMAd/eLYirp2/+MUvJLGSz2CgAv0xG8qtP15MVxT6k+NAf7SvQfrjRQeF8QID9BtxTcDjBPBytwsuuCDl9TVKqNaYtQOtzRk6ha11VIBmF198sa9mSNDdcMMNhaYZYhQJkrfeekte+oPkdL60PRqfX375pfTpzLYAz4uD1hj3eS0Z1XqCr7sdSeWbT5g6QWMznvWZfNddd51VtmxZpzQR9f/3v/+ddD6Y/maC7+OPP5b+xs9+9jMZp/BaWsLETo4iJ9Z5t6tUqWIPGzbMKTmOfoaf0qFDB3vv3r0J5V4+PXv2lM9gYwJf7KNBgwb2pk2bnNLjuPdpfjc2Pz+SHlOnThU9zTqC5ihD3SleZW5QH6gXLxuUad25t3ypy0y1hn+s4yv+S5YskTIvW2jZsGFDKZ8yZYqUqS+03rhxo5TlK146Dh8+XMp69Ohhxy6OvmVhfdG+dezYUerALPeqm3xi2rRpcf0WL14sZWG1N4GOjRo18v0c3xPrsKT8nqjhPm4cJ44bZTjuo0ePip1XGQjrr/ojjidPnix26os2ZsOGDWIXVXCsscGj6LRo0SI5/hEjRsjxd+/e3T5y5IjYeZWZQMcmTZqItl6fA7Qll112mV21atX4d+U706dPt2ODQtF/4cKFosnIkSOlTqD14cOHxc6rzGTz5s1206ZNRX+vz03SsY060D82WLQrV65sL1iwIK4/6qRbt272oUOHHMtjdeBVrkDXZs2aSR25P+/bt6/UH9oZ91a/fn173bp1kT8fZsyYYccG9qL1/PnzpQ0eNWqU6A9NDx48KHZeZW6gdfPmzUVrPxsQ1i5bgWblypUTzebNm5egWdeuXROOafTo0aKvu1yBFi1atPDVon///hLffjG6Zs2aSMfozJkz7fLly4vWc+fOFa2hKfSHpj/++KPYjRkzRsq6dOkSL4NvhQoVEny97NygTlq1aiWx7mcTJaBTxYoVRac5c+ZIX2Hs2LGie+fOne0ffvjBsbQTyvfv3y9ls2bNsitVquTrr3Zg37599rXXXmtXr17dnj17tm+/hBQfJZ78A5rECZv804SH+7OwyT+zIdUN+ySFh9aRuXklnrzKg+oJG+pd69rrc9384i1qZKI1wGdIYAT5A9QLBoumHRN/x/HSEYM6s5OmNn7lQb7ATACaG84XTRzmI0icpNJPbcxyxHS1atUS/Mxt6NChSftA4sW08aqnqOF33Jq4A2rjLgdh/MGyZcuS6iMfEn8KdHInJjBANDvLamOWQzd0rE0/cxs8eHCC1mqPOmBH/DiaADS1g85mYk5tzHLoWaNGjQQ/c4P+Zl3VrFnT0w6baZtvaALQ1MMrwad25meqq/s6oNugQYPsXbt22VdccUVSW2RusMuHRKwmAM1jdyf51MZdvnz5crt27dq+Wj/xxBOiYVi7XEETgOYxeCX41M78LJUWAwcOlFhGH++qq67yTVBjU9soowlA87jNxB/QRJ87qaflpq9X4g91UqdOHd86efzxxz2Ts1FBE4DmMbsTfwB2SPS5k3qaAHT7mzZgxYoVdt26daUO3J+RkqEU/hOrMEIIIYQQQgghhBBCSMTgomtCCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYQQQgghhBBCCIkoTP4RQgghhBBCCCGEEBJRmPwjhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP5JXLFu2zHr++eedvwiJPhrztm07JaS4oPZFz/Lly62//e1v1JhEFo3xn376ySkhxc2KFSusF154wTp69KhT4k1YO0IKE427I0eOOCXehLUj3nz66afWiy++aB0+fNgpIUWB6nzo0CGnhBQmTP6RvOL999+3XnvtNWvfvn1OCSHR5oMPPmDMlxDQfty4cdbevXudElLYaHxTYxJVPvzwQ2lH9uzZ45SQ4gZ1gHZm9+7dTok3Ye0IKUw++ugjaSNSxZ1pxxtm6aP67dq1i/oVIbNnz7Zef/11a+fOndS5CCiW5B9mP1StWtUqVapU0jZt2jSxwcC0Y8eOSZ+7t4YNG1qbN28WH/imsiElw/Dhwz3rRus7DKhD1CX8evXq5ZQmk8pO4w/f3bRpUylTn6D95gqZau3nP3XqVMfiGNDKbQMNN23a5FjkNyNGjLBOOOGEJI3cOvqBmGzUqJH49OzZ0/eCF+Z7EPPVqlWTsiZNmsjnun/UY9QupkGahDlWaNO4cWPx8dMemlavXj3pOzp06JAwKFc71R5s2bJF9h9Ur9kM9D3xxBOTjn3KlCmhj8etsdcsprDfg5lQNWrUkHLdJ/YPvf32nQuMHDnS8/gnT56cUucwvtAI10Cvc0W3Hj165O2spVGjRlmlS5dO0mTSpEmhYgrnebNmzURf6Bg0uyaVLWK8Vq1a8t16XUD9wSfVvnMV6F+mTJkk/SdOnJhSf9XLHdvt27eXAaQb6N+8eXOx7969u+dMHsySql27tny/9jHVD3WgPm477NPLLpsYPXq0VbZs2QStsE2YMCHU+R/Wv3///p7n1KBBg3Iuhv2Oefz48aHbTMRFy5YtJUa6deuWcmYTxsa//vWvRcMqVapY8+bNi58LiLs6derI9zdo0CAed9g/4u7gwYOBdq1atZLYV7tsYsyYMVb58uWTtH7jjTdCxQ2Or3Xr1nJN7Nq1q3XgwAHnk+NAlzPPPFP0ML+jXbt21rZt2+LXTcxCq1u3rvXmm29a9evXj+vXpk0b0c9r37nAk08+aVWoUCHh2LEh6Rb23Ny6dat19tlni85dunSxfvjhB+eTRMLYQed69erJ9+Nf1fmcc86Rc8Vv36QAxIK7yFm6dKkda7TsYcOGOSXHy/ATYoMkp/Q4e/futWODKjvWUNmbNm1ySo+DfcEX+8C+FOwL5eZ3keJF6xb1h3oEqEPUpV99utH61S02oHM+SSSsHcpNO2xhf0s2k6nW8K9atar479mzR8rgE+vAiv/GjRulTHU2zyuca7ELRYJvvhJWRz+GDx8uWmpsxjpudqyD53x6nHS+p1evXgn7xBbmt+Qa0KRatWpJmsQGzHK83377rZT5EVZ72EFn3Z9+B3yGDh2a4OOnfarfko0sW7ZM9I0Nou3du3dLWTr6AmgX68jFtYDGscGS8+kx/L6ncePG8j0bNmyQMuX222/31Nhtlyvg+KtXry7Hv2vXLikLOn4TP98mTZqI7zfffCNlQUybNs2OdcztwYMHJ9VNPgANa9SoIRru3LlTyjZv3pygoVe7oIwcOVL001iMDQrtw4cPO58mEta2T58+CecNttjg016/fn3gb8lFoH/NmjVF/++//17KoH+zZs1E/3Xr1qXUH+eK2qkv2ohBgwbZscGsY3nMtnTp0nFNYwNL+9ChQ86nifTt2zehrrQO3L8nrF02sHz5crtWrVp2u3bt7B07dkgZ9GrevLlovXbt2sDfDP/atWun9J8xY4ZdtmxZ+4knnojHt9qhHzNv3rycaWvMY96+fbuU4VhatGghx7xmzZqU9Tx69GjRQ+Oja9eu9sGDB51PvYGG5cqVsy+66CK5Pn7yyScJmvXv3z8hljXu3L8nrF02AK3r1KkjWm/btk1+H7Ru2bKlaP31118H/uYxY8aIZnqcXbp0sX/88Ufn0+PArmnTpvbq1avj39GqVStpcx9//PGEuhkwYIBdpkyZBP3q1asX9801VqxYYdetW9du27atvXXr1vjxt27dWjRetWpVyuMaO3asXb58+bgenTt3tvfv3+98ehzYVahQIaUduPPOOxPOEWzQeeXKlXnZLykqSiz5B7QcgzZNXChByT/18/qMlDxItKF+UE8mYROzWr+wR/2inr2SemHtFLUP8xtyhUy1Vv8lS5Y4JcfQxB78oS2SHmZyRUGSw8s/3/DTQXV0J4dMUHfoCE+ZMiWuNerFyz7d79F9IxaCfkMuA01wjIsXL3ZKjoFkRhjt0aFW7ZHQ8kv+eaH+ODc0YaXoZ7muPZJsqq95DNAXneQhQ4YEHpsm9SZPniyJZ9XY3ZEL8z1uH016QWOvz3OJ3r17y/EvWrQo6fiRVAg6vlS+qRJ66G9ddtll0vaESRRGESTaEKcLFy5M0HD69OkyaIaGZgLJRBOHEydOlBjHgBIx7pXQ0yRXGFug9ojxoN+Q6yB5Bv0XLFiQpD8G3e4EXhigHZJcZkJRyyZMmCA3LpAgRPLVL/kHNFmmiUS/ugprV9L069dP2s358+cntAteyTov1N+dvHP7ww7tvTuZOGrUKKnT8ePH50w8Bx0zEk2pNNPkIY4ZcYekIeIuKPmnyUXYof1HO+BO/gHs+4wzzpC4GzhwoG8sh7UraZBoQ3s6d+7chGOdOXOmJJHciTkTHCMSh2+88YbcMEMyD8l9r+SfF+qPxON3332XELdImJ155pmiX9BvyAXuuOMO0XjOnDkJ5yA0rlixov3YY4/ZBw4ccEqT0eThuHHjROc2bdpIMtud1AtrZwKfs846S3R+9NFHA38HKRgl+sy/WENmnXrqqVbswpDW83rw3LYdO3ZYd911l0zzJ9lD7GJlffzxxzJNF8uxTGIXHZm2jqm9QZx77rnW9u3brauvvtop8SasXWwAJFOZO3XqZN13333WjTfeaMUaOCnrlcPLfjPVGv6xi2tKf0y7xvNBUHbyySc7Fse4+eabrVin2ooNYpyS/CNMPXz22WdOSTKIYywxuOaaa5wSb9L5HsT8CSecIDF/zz33SMzPmjVLynrm6NJTLzSGsZxAl9gqWIZVtWrVwHMA2sc6eCm1T4fYYFWWNkD7u+++O649ynJNe4056IuYQ5upmDEXdEyIV2h87bXXJvibhP0eRTXGo0LQD7jpppust956S5ZGQeNYh92xzA30+LGMKF2dw/h+/vnngXW0evVqWTZ58cUXy3mTb+AaBw2xTMytIfRIFeeIcezj+uuvlzY2CNiizlLZzpgxQ5bAIsZjAzWJ8bfffluWHfaI2LJfaId2PEh/xHBhnNfQf9OmTdYNN9wgbUgQqINy5crJ0uEBAwZIW/7OO+9IWXdjqbBph2WuqCsvu2xAtcaST2htxmAYrU1/XHPd/rjmmv579uwRH/e5U7lyZbE36zpbwe//5JNPCqwZwLUN/WTEUKq4U3T55Z///Gc5791gHIOlsYi7Pn36SNxhfIylnFgmedBZzhvWLhvQ+GrRokX8kTUKxvvQ+osvvvDVGjpv2LBBxiboDxQG6L9VrFhRlgNjzAj98KzhSpUq+S4pzmY0nlVjr3P4yy+/DFzKjv7G+vXrrVtvvVWuU36EtQPow5100kmiM9pN1CGesYiyoCXFJH38ex7FSP369ZOSCn7g+QdoyNAAoCEj2QUaFU0U4YQ10WQvLoDF+fKB888/Xzpk69atkwYcvw/P0Rk2bJh1yy23OFa5R6Zam/7u8y/dulq5cqXzf/lHccV8Ot+jMY8bK7CFH55HhOc74iIcFVQTdFj8NMFAr6jaG+wbN6Lw/XoOnXfeeVa/fv3i2mPwg+cgob3JNe3xnBY/ffHMvcLSN9X3nHbaaQnfA40R32vWrBHd4asao03PhQGliR6/17mtOvu1Ial8oV2q9gfPV8Jg6t577w1MSEWVkm5HvNB2BIlZ1CHaETxzStvwKNUT9McD9P30d5//YYEPbhAjaeDebxhQB3379rW+/vrreB0gIYM6uO222+JJHNPu9NNPl1jysssG0F5Aay9NtL1ActpPa21v/Pxxrqj/b3/7W0nAIEHyzTffSAIQ47dHHnlEktrQLRfi2NTM3Vc2NUtnEksqVqxYYQ0ZMsTq3bu3PK/P65qGm5eIu1WrVsmYGPGJl81o3GnyK6xdNuCOL/O43fEVdEOroGDf6NOh3UFd4/txwwD6YZxTrVo1qedXX31V9OvcuXNW6RcG3IxVjfUYlerVqxe5xn5AZySn//Of/0hdQ+dXXnlFngWN5F+q5CEJT4m2ujh50Hm/8sorQ1+YEQwYVCE4cXKS7ATZfjdoZJDoLW7QwP31r3+Nx5jONH3ooYdSzhrMBTLVOpW/Dn4wMwKdaRMMONGZIJbMWnBTFDEf5nsQ888++6yUAyS+EfMPPvigxHyuJUdS4RfDeGhwUYKHT6NzhDuUilt7bW9yWXvo6/7dxRnb7nqExs8884x1yimnyO+CxhjQQGPM4szV+Mbx++mc6pj8fKFdkC9m/GEmJerYPesq3/DSEP2GMPoXNrjuPv3005JYAGjDEeNYvYAYj2KSFvq7jwv6p4phP3BDAEltzNQpSAIOdfDUU09JHeD79TrqroOwdtlEplqH8cdg/vnnn5ebDziHYH/VVVfJDZoXXnjBczZbNoOZf5lolg5/+ctf5IUxuMnll/RA3MEOsyg17tBG4CYOZtprzIe1yyagtft36fWsKM8n3CTHbEvMDNakHvQbO3asjHVM/bCqBvrlWvJP0RfPmBSHxn4g4YcbkUiwQmfMGITOuIkAnZn8KzyKv3ZjIFuOiv3d734nbx7CXaF0wYUEQUqyC1zkcdckCB0MlwRI+OHuLAaPuU6mWof1x9T23/zmN5KoR7IP565uuHOLO+v5THHFfEG/BwkRzB7BrIqooTM7goAm6EAUNkiYvPzyy7JEoW3btnI+uFHtcd7kIhpzQXd/izO2verxgQceEI0xOyJXCXP8mlBwE9bX7xzA8iX4YyCIZGo+gnYkrP7FORNCuf/++2XWCd446dXO5Dqqf5C2GsNh9cdS3Jdeesn65S9/Ke1zpoNZJPJQB2eddVZgHYS1Kyky1VqvuWH9MbkDj2LIxgRTWMK2D+nEZxCYHYnYvfPOO+PJ/1Sg/f7qq69S3qgIa1dSYMZZqvjSpFBhg+W96NNdcskl0mZ4xSwSfpiZ1tB5+3cuEuYchsaYHVhS4JE5WHrsXmZPCodiVRTJPpws+BdgiU5BEzGFMeAghU+YmWBM3BYOmWqdjj+SpkuXLpVnQSgdOnSwZs+enVCWjxRXzPPcSgYJzVTxB00KO6mBDioG5LhDik56VJMmGnNBndzijO2o6xwEYs1L57C+XtohjjGD8le/+pVvAjsfQDsSVv981agoUf2DtNUYDqM/lhGjz3LmmWdaL774YugESj6QqdZ6zQ3jj6WraJ8wmworR/AMMSxlx5LTK664Qp4XnQuEbR/CxmcQiF2MkTE7EisFcjlpWhCQD0gVX0ise13PMgG6P/zww/L9mK2a6jfkMmHOYWiMFV8kmhRr8g/JPmSadcPFOV3Q+cIgABlpnKwkO/F6yD6StUjaksIlU63D+uuLKfT8fffdd+U8xB1R98sW8hHzhQRKUcR8cX1PLuEXw7gbX9ggYYLZJDt37pTnOmFwE3WgL855k+KM7aKox2zE66USqrO73I2fL7Tz88UgHDdgL7/88ry6aeCHl4Z47lEY/UnmQH/3g/yhf1AMu8G4ALOx0VfBo4WiOlsyUzLVOpU//v9Pf/qTvFRi8eLF1s9//nOZwfPcc8/J6i8kA/E4nlx6cY3XSz3Sjc9UoE+Bmex41hle0oHYxYYZpYhtvJQJL/zJppd0FAXQ2v3CCb2euesgU6ArXtCGfzHzDzmGfGgzvF6cUlQak+wi5+ZS4vkKmEaOhAPeVkSyCzwbAXcLsBQJF0UTNKxIFmGwjHokmZGp1qY/GnwT0z9oUIgHkONCiRdM5CvFFfM8t5JRTbCMwU8T3OUsLE3wHXjbGxJ/eDNZ1ONeH7Dtpa8+mLsw9E31PX4vA4gKevxe57bq7Hdup/KFdl6+sMUyJ8xYwcO083lpTXG3IyQR6I/ZeX76hz3/4du7d29Z0obHMlx44YV5MYhPB7QX0Fof6G+i7QVmP/lpre2Nnz/OFfjj/zHz76KLLpK6M+sBL5lo1KiRvBG5KJZvFjamZu6+sqlZcd1AmTdvnpwrUbwh4Y4v8xjN+EJ8Fsa5vX//fnmuIvY9efJkideoXwvNl3ognk2NzZeBFJbGJPvIyQjHW34xBfuJJ56wli1b5pQeBwGNuyek+EGDcemll8pDxPFmKRMka5G0zeU37GYTmWoNfzzbws8fHWjzRQZucO6hg43fgH3lK0H1oM/Tgo6ZXkSL63tyCY1hDDLcb5yGJojhwmpv0BG98cYbZcYrHlaO511GHY056IuYMzuJ2sYUZmx7fU8+xLYeP2ZYeh0/4hgvLfAalKTyhXZevh999JH13nvvWb/4xS9kcJ7PIPkEDTGbya3hhx9+GKg/yRzoj3Y8SH+0vUFLINE+o61/++23ZUbZBRdckFfXwrCo1phZBa3NGT5htDb9cc11+2PGZaq6cidxsh0cM2bc+WmGY8YLIgpjiS6eyYdZfTgHzG306NHyOz755BOZGRjV2WkaX3jeG+LLbAvwmCFoff311xfKSzaQ+MPbevGMRbwQBTcL8qGN13hWjc14hsZIAF533XU590IekgaxE6vIWbp0qV2lShV72LBhTklq9u7da3fo0MFu0KCBvWnTJqf0ONgXfj422MEedrBHWc+ePR1LUtxMnTpV6gB1jroHWl9mvXiVudE6TVWfYe2iRqZawz/WgRD/JUuWSJnbFudWx44dxVZRG2i+ceNGpzR/8dJx+PDhUtajRw87dnH1LTNBHDds2FC09/o87PfkE9OmTYtrsnjxYikrqPaNGjXy/bxXr17ij7h3bzgPvv32W8cyWkDfWIc4ri+0gZYog1ZHjx4VO68yN6bGbhuv7xkxYkTKfUYFHH9s8CjHv2jRooTj7969u33kyBGx8yrz80WZaaegTb/sssvsqlWrxu3znenTp9uxAaVouHDhQtFk5MiRcQ0PHz4sdl5lJps3b7abNm0qMev1uUk6tlEH+pcpU8auXLmyvWDBgrj+qJNu3brZhw4dciyP1YG7vG/fvlIvXu1z/fr17XXr1iXFOfRv1qyZ1KW5/6gzY8YMOzawF63nz58vbeuoUaNEf2h68OBBsfMqA6b/vHnzPP3Rxlx55ZXSVpn+0Lx58+ZyLR0/fnxS25St4JjLlSvnecxdu3ZN0Gf06NGij7tcgQYtWrSQuPP63Avss2bNmvYnn3wS+WvhzJkz7fLly4vWc+fOlePF8UN/aPrjjz+K3ZgxY6SsS5cu8TIT6NyqVSuJP6/PBwwYIPXn1WbUq1fPXr16dWSvjdC4YsWKovGcOXPkPBw7dqzo3rlzZ/uHH35wLO2E8v379zulx9myZYvdpk0bqRuvz5WwdqToydnkH9D9uk/adL6HFA2alDI3r8STV7lfveqm9RvWLupkojXQhFKQP/42P8eG83PPnj2OBfHSEYM6s/OgNmY54hiDcNPP3IYOHeq5D9PG/T35hiYAgzRRG7f21apVS/AzN9Ue16NOnTolfYe5uespSmhizjxe6GgOQtTGXb5s2bJAjYcMGRLXLcz3RBkcvzuB4U7eqY1feZCvgjqpXr26aJsrg+/iQBOAbg3NxJzamOXQs0aNGgl+5jZ48OC4zrDFIN7LDptpm29oAtDUAwN3d2JO7fQztM9XXHFFUtthboMGDRJdoX+tWrV823LY5UMiVhN45rGbSTqgNu5yEMbfTACadmYCLZfQBKB5LF4JPrUzP1u+fLldu3Zt37gbOHBgYAI6n5J/QBOApkZm4g/ApkKFCgnJP+hcp04dX50ff/xxqZN9+/bZV199te8NA2xqG1U0AWgeszvxB2BXqVKlhOTfihUr7Lp16/rq/Nhjj9kHDhxIaffoo4+KHSleSuE/sQoghBBCCCGEEEIIIYREDD7AhBBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYQQQgghhBBCCIkoTP4RQgghhBBCCCGEEBJRmPwjhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIaRIWLZsmfX88887fwWTji0hhCjLly+3/va3v1m2bTslhEQLjfGffvrJKSHFzYoVK6wXXnjBOnr0qFNCSPag8XnkyBGnxJuwdoSUJJ9++qn14osvWocOHXJKSGHC5B8hpEh4//33rddee83au3evU+JPOraEEKJ88MEHbDtIpPnwww+tcePGWXv27HFKSHGDOkA7s3v3bqeEkOzho48+kjYiVXyadrxhRrKV2bNnW6+//rq1c+dOxmkRUOTJv+HDh1ulSpWypk2b5pQkg89ggwtrx44d5f+DtoYNG1qbN29O8A2yAZhZVLVqVfk9JlrutieZofXu3oLiwCQd/169eiXZoU5Rt/lAploDxH6jRo3ED3r64af10qVL5XNoXq1aNWvq1KlW06ZNpUz3DV+zEU/HNhcYMWKEdcIJJyTpg+NLRTq+t99+u6ftsGHD8vYiGaRfKk38fKdMmZLk66U9rh0bN250LKIJNDrxxBMTjhubl0Z+4Nxu3Lix+PXs2dNzFlPY78FMqBo1aki57hP7b9Kkie++c4GRI0d6Hv/kyZPz9twuTkaNGmWVLl06Sf9JkyaFiqktW7ZYzZo1kzaiR48egbNrUtkixmvVqiXfrddmxDh8Uu07V4H+ZcqUSdJ/4sSJoc9p6Nq8eXPRtXv37tbhw4edTxIJY4dZUrVr15bvRzuP36J+qAO/fecCo0ePtsqWLZuk9YQJE0LNbgzr379//6RzqkGDBta6detyrk3zO+bx48eHnhGK+GnZsqXEXbdu3TxnNiHu6tSpIzbm97Rr187asWOHY3XcDt8PTWGv+0d8Hjx4MNCuVatWEvtql02MGTPGKl++fMLxY3vjjTdStn1jx44N7XvHHXck1Wn9+vWtr7/+OvLX3CeffNKqUKFCwrFjQ9It7PVl69at1tlnny39li5dulg//PCD80kiYeww269evXry/fhX4/Scc86Rc8Vv36QAxIK7SFm6dKldpUoVO9Yhd0qSwWexBsnetGmTU3KMvXv32h06dPD8DMQGuzgzZf/4HiU24JNyfK7o7zDLsE/s2+1PMkO1Rt2hDoFq7VeXJun4awwExVeUyVRroBrq5qelqXWsI+6UJtOrV6+E/WHDb9m4caNjcZx0bLMZ1EPVqlWlHvbs2SNl0D42YEh5POn4om2LXZztoUOHxutAbREHS5YskbJ8AvpVq1YtSb/YgFn0+/bbb6XMC9N39+7dUubnO3z48CTtp02bZsc6KHb79u3j/lFj2bJlopF5jGH1VaAddNJzPDYwsWODJefTY/h9T+PGjeV7NmzYIGXK7bffLvXhbjvcdrkCjr969epy/Lt27ZKyoOMnhQv0r1Gjhui/c+dOKdu8ebPdpEkT0f+bb74JvO6NHDnSjg1s4rEYG1Tbhw8fdj5NJKxtnz59Es4bbLGBqb1+/frA35KLQP+aNWuK/t9//72UQf9mzZqJ/uvWrUt5zNC1dOnSca1iA0b70KFDzqfHCWsH+vbtm1BX2FAHYX5PtrJ8+XK7Vq1adrt27ewdO3ZIGbRu3ry5aL127drAY4N/7dq1U/qPGjXKLlOmjP3EE0/E43vGjBl22bJlE3xzAfOYt2/fLmU45hYtWsgxr1mzJmU8jB49Wo5d46hr1672wYMHnU+PA7vLLrss/j2gf//+ErMDBw5MiFUtd8en+/eEtcsGoHWdOnVE623btsnvg9YtW7YUrb/++mvf32z6fvfdd3HfVq1aie/q1avjvmPGjLHLlStnP/744/F6mDlzpl2hQgW7bdu2cf8osmLFCrtu3bpynFu3bo3r1Lp1a9Fp1apVKY997Nixdvny5ePx1LlzZ3v//v3Op8eBHTRNZQfuvPPOhHMEW7169eyVK1cm9RlJwSny5F+qBB7K8JlXwiHIV5Mefvt1o/aa/NN9I7AwoCaFB+oSWkNzE6+krBdh/bVO/ZJV+UCmWsMPiSfY4zxCEslLT7ULq7Xap/MbYIvESi6CJCbqwZ18g67uhJGbdHxhizbPnUzUxNSUKVOckvwBmiB+Fi9e7JQcA4m5MNr7+WLQrb44N5DsMpOEit8+ogKSbHp8po6q0ZAhQ3z1BZrUmzx5ssQtdPRK/oX5Hq+EIRJmaDu8Ps8levfuLce/aNGipONH8iHXjy/bQaINcbpw4cIE/adPny6D5sGDB9tHjhxxShPRxOHEiRMlxps2bSox7pXQ0yRXGFug9ojxoN+Q6yDJBv0XLFiQpD8SSIMGDQo8dtVpwoQJckMCSUMkVd1JPdgh8ZXKzkSTZbie4Hf41VWu0K9fP2k358+fn9CmaGLOTNZ5of7z5s3z9cfNCiQDkcx1J/n8/LOZoGNGAimVZpo8HD9+vMQdkoaIO6/knxfwP+OMMyRRfeDAAaf0GPoZ4tOdHDQJa1fSDBgwQNrTuXPnJmitiTkzWecmrK8mBM0koaL7+PjjjyPb3t5xxx1yjHPmzEk4RuhUsWJF+7HHHkuKMxNNHo4bN07O9TZt2kgy253UC2tnAp+zzjpL4vTRRx8N/B2kYBT5st+TTjrJuvLKK601a9ZYr776qlN6nNiAVz675ZZbnJJw4BlhmP581113ydKIdHn22Wet9957T5bKXX311U4pyZRYg2rFGkyZpovlWCaxi45VpUoVmdrrRzr+iAFw//33y7/5RqZag3PPPdfatm1bynMAWsfaC+u+++5zSryJDVRlqnanTp2se++917rxxhut2MVEppL3ci3l9bKdNWuWp202E6YePvvsM6ckkYL47t69W6bCu4EtfPIJ6Bfr5MlyAiz5NMFyrapVq/qeA6avW3v4mucP9IbuKD/55JOlTMG16/vvv5elv7kSs2HR+FSNcG4qZnwGHTdiO9a5tq699toEf5Ow36NMnz5dlo/gMSHoA9x0003WW2+9JcvLeubgsl89/ljHuMA6k4KD8xv6t27dOkl/bQuC9EeMYx/XX3+9XNOCgC3qO5XtjBkzZAksYhxL0xDjb7/9tixRw5K+2IDNscx9oB3a4iD9P//888DzWnW94YYbpG3wA3abNm1KaQdQB+XKlbPat29vDRgwQPoo77zzjpR1D1hSnM2o1ljyCa3NGAyjtemPa67bH9dc+KMucM3E+AzjQBPouGvXLqmHXGjTcMyffPJJgTUDuLahj4BjTxV3YUHfGstbEZ99+vSRNgJ9dSzlxDLJg85y3rB22YDGV4sWLSS+zLYAsQStv/jiC0+ttZ7g625H3L5YhooYRDn6dKYt2gY8XzVX4jNdTJ38zuEvv/wycCk7+irr16+3br31VrlO+RHWDqAPh7aiXbt20r7efPPN8oxKlAUtKSbp49/zKETQ4OCkQwO0b98+p/QYWIPfoEED6/zzz3dKUoN9YF/YJ/adLkg6/O53v5NBwkMPPeSUksIAjQou+BiwuC/4NWvWtE499VS5ALrjQEnHHwNz/I3yfCRTrdMhrNY4j/v16yfPc6lYsaL8PjwvB0l2JEnMCyxs8TyYtWvXprTNZjKph3R9kXyFLtAHHROg7RlusiCZm0+ofuiw+OkHnYK0h687oWf67g35IomVK1c6/xcd0EH207dGjRqB+qZDqu857bTTEr7nvPPOk7YDNw5Rd/DFs6Zyre1Q9Pi92gHVubDacpJMJu1IUYEYx7V09erVEv8YjL755pvyjF8MpIISh7kG9MdA3E9/9/lfXKAO+vbtK8//0jrA86hQB7fddluhJXGKEzPp4dfWInHnp7W2VX7+OFfgj+tmqsQJrpm5kFwxNXP3FUzNwvYVCsJf/vIX+R1ITOEmF0B/D/G5atUqGQ8jPvHsfI3PdO2yAXd8mddyM74Qn+7YcdeT2zfdeoJeQQndXAU3Y1Vjt07Vq1cP1LgowY0ZJKf/85//SH2hnl555RV5FjSSf6mShyQ8xdJ7QAYelbp8+XI5mRQEF+62XnrppRKEYUFAIGGAAEXHIB0WLVokD23v0KGDNKakaEC23w0aGTxINQyp/NEoYTCEv++++25pvMwNF7V8IVOtUwGt0fHG/u65555ArXEe//Wvf413CnGe4nxFkt09uxC2mIGL3wqCbHMBzFpwE7YewvqiE4fX30MrJAqg/zXXXCN3yf7xj3/I3/mI3zmAhwanIsz5owkA3JHGuWCCASs61FEGGrljK2xsp4PfeeCuR7QdzzzzjHXKKafI78L5gAHNgw8+KOdDrp4HOH4/nfP13C5OvPTHtawk9Eeb8/TTT8uAFeCGGmIcN4AQ41FK/inQ331c0B/nf0nEP+rgqaeekjrA96MO0EeJQh1kqnUqf03azps3T66ZZhIB10zMLiqJOs0EzPwrrvjUl3Tg+7Dv5557zvrzn/8sM+g16QyNMY6tXLmy2GgbgZU0BbHLJqC1+3dpXyDVeedVT25fTQbOnz9fxpJmfKJ/gT5drsVnuuiLZ0zCalwUoE7wopdq1aqJ9pgxiDj97W9/K3HK5F/hUSy1i8YRSzOxTFeXaoKCLvlV0CFDoKYDXnGO30GKBjSiqfTVJI8X6fpj6TamBS9dulQab/yLRhszoTAjKspkqnW6qNY4b1VrdOCg9VSPt9IiiYc75ujopSId22wjk3ooiC8So5i1HPWOSRgwqNi+fbvzlzfQDx0IN/ANqz06g7/5zW/kb3TIob1umB2CpfNRROMz6O6vX2ynQ9jzwKseH3jgAZkdhXrJVcIcvyYeSOETpi1Q/YPOhaIC/WfMkqpbt24k233VP0hbTViUhP4ACT/UwVlnnZXTdZCp1nrNTeWP1RxYKr1hwwYZqyGZoNdMXXpdUnWZLmHbh8KMT/S10a8w9xe0tBiJvK+++irljYqwdiUFJgWlii9NCrmBb6rYVl8kmhCfuPY2atQoKT6//fbbnInPdAlzDkMnzA4sKTCpB0uP3cvsSeFQbIpiiR+W95pLfwuy5NekIIMOLAvChkQGssmkcMFspFSzYIKStun6YwYnLrq63BH/4pks2AfiK8pkqnW6QGucc0h2AGiNZxAhAYjlSFG9UKYik3pI13fZsmVyVwyJ7cWLF4vmeD4ipsbj2Yn5lhzQGQRBQD/MEHMTZsaeqT1mlSHxDf0VPHYCnXSzLEpofAYNEgqjjQl7HnjVYxQIc/y4G19YbTlJJExboPpn44A511H9g7SF/jrTlxScTLXWa24YfyStsdoKPmqP53lh/IUbarlSl2Hbh8KMTyTp8Cw+9PGwjR49WvrZV1xxRcpEZC6DuEgVX0jAe/UFwszYM32xkmnBggXxG7qgbdu21rvvvptQFjXCnMPQCatdSDQptuQfTkos79WlvwVd8gvQAcNAAFlpPCskXTDLCDNnXnrppcjPDispvB6yj8QEkkdhCOvvlQDGFHc0Wrijo4nmKJOp1mGh1sG4X8wBwtZDGF/o+8gjj0jHBXWuSdi///3vckMDs6qxjDofk7B+5wBuDKQinfMHCW88L0U75BjEwBadcfcLR6IENHLHVdjYTge/8yBMPUYBr5dKqM75eF4XN176o92l/sUD9HfPbIL+OP+pf+GSqdZh/fVFF7BFOfopSGrhmul+KUO24zXzrrjiE89Cw8t/5syZY3344YeBL2OIAtDafYzaF3DXgRuvevLzRXxidqrG5wcffCAv8kF86ozAqOL14pSwGpPcplijGst7cUKh8ccMCiTvCvKmViwjxsPtdV8FYdCgQTLrEM//w2waUjgEJYP0odqY5YA69CKsP+zwbz6TqdZhgT/uFBFvMqmHdHxx0wQ3T7xumOBhuGjP8LZk936ijOqHZQx++iF2g7SHLzo8JqZvqtlWmGGMm1GYwR61O8VYGuOnrz6Y20/fdEj1PXiId2F8T7aix+/VDqjOhdGWE28yaUdI5kB/PH/LT/+on//FCdoaaK0P9DcxX5jgp7W2VX7+OFeC/AFezoQl7LiBmQvJFVMzd1/B1KwoZ2ZDT1wDojobTXHHl5lUdceXWwt3Pbl9zXoK0hEvHsTMP8RnLr7UJxXmSz3cOpkvA/HSmESDYm11zaW/eGg91tXjzk9B0DcIP/HEE57JOwT166+/7vyVDAIbU6jBww8/nHQRIwUDupozPE2QqEXCNugZj+n44yH0eGYkEskm+ixJJIiDOiC5TqZap0MYrYuy45PNBNUD7iKiHvDKeq+LaCa+Ju5EYb4A/S655BJ5OLb7bbvQD8818TsHTF8v7eEL7YPAtWfGjBnWxRdfLIPTqKHxqRqZnURtY8LEZyqCvied8yBX0ePHDEuv40cs3nTTTXz2TRGB5BP0x2wmt/6YZUP9ixboj7Y4SP8bb7wxkgPx4ka1xuwoaG3O8AmjtemPa67bH8+pC/JHG49r5s9//nO5ZuZCm45jxjXeTzMcM97CW5TxiTEqbg6dfvrpOaNbQdD4wvPe3G+Dnj17tmh9/fXXe76hWOsJvu52JJWvovF5wQUXRDbZaurkPoehExKA1113nVW2bFmnlESO2MlRrPTs2RNno2zDhg1zSr3Zu3ev3aFDB7tBgwb2pk2bnNLjwF/3BTvYww72KMN3KUuXLrWrVKmS9J26D9OWZMbUqVNFU+gN3YGXzn7ah/U36xo+QH39YiZqZKq1CfRq2LChp41+hn1MmTJFyvDdsQujaB3rlEhZvqJaoB6WLFkiZcOHD5eyHj162LGLq29ZWF+0bx07dpQ6MMu96iafmDZtWly/xYsXS1lY7eEbG9Cn9IX2nTp1En3d+0P8f/vtt1IWRdwa4fhx7CiDRkePHhU7rzI3iNVGjRp52nh9z4gRI1LuMyrg+GODRzn+RYsWJRx/9+7d7SNHjjiWpCiYPn26HRsUiv4LFy4U/UeOHCl1Av0PHz4sdl5lJps3b7abNm0qMev1uUk6tlEH+pcpU8auXLmyvWDBgrj+qJNu3brZhw4dciyP1YFXuQJdmzVrJnXk9bkS1i5qzJgxw44N7EXr+fPnS9s6atQo0R+aHjx4UOy8yoDpP2/ePE9/XDOvvPJKe+LEifG2S23q169vr127Vuo4V8AxlytXzvOYu3btmqDP6NGjRR93uYK4a9GihcSd+3P9rGrVqvYnn3wi36Nl6G9gnwcOHHCso8nMmTPt8uXLi9Zz584VDaAp9Mfx//jjj2I3ZswYKevSpUu8DL4VKlRI8PWy27dvn3311Vfb48ePj7e9alevXj179erVORWf6QKdKlasKDrNmTNHztGxY8eK7p07d7Z/+OEHx9JOKN+/f79TepwtW7bYbdq0kbrx+lwJa0eKnmJP/nklK/xIlfwDmtTDPs0NyQ4TtXOX63fAB7+NFA5az+bml+TzSjaF8Qde9Z8viT8lE62hHzoZbn/dzPPFy5aJv+NAY3TOTH0wqDM7EGrjVx7kC8wEoLnhHNDEYT6iCUBTE7d+auNVjgRLkC/o1atX0ne0b9/e3r17t2MRXfw0QsdaURt3+bJly+xq1aol+JrbkCFD4lqH+Z4og+NHYsk8fgwQmfgrHjQB6NbfTMypjVmOGK9Ro0aCn7kNHjw4XoewrVmzpqcdNtM239AEoKmHV4JP7czPVFd3G63boEGDRFfY1apVK9AuHxKxmsAzj90vyecuB2H8+/Xrl9SetWvXzt6xY4djkVtoAtA8Hq8En9qZny1fvtyuXbu2b9wNHDgwHste34MN+4t64k/RBKD7+DV5BzTRZyb1gJabvm4bMGDAgKT2pm3btvZ3332X1P+LIpoANI/fnfgDsKtUqVJC8m/FihV23bp1feP5sccek1hNZffoo4/mTUxnE6Xwn1gFEEIIIYQQQgghhBBCIgYfYEIIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYQQQgghhBBCCIkoTP4RQgghhBBCCCGEEBJRmPwjhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwgpdpYtW2Y9//zzzl/+hLUjhBBCCCGEEEKIN0z+EUKKnffff9967bXXrL179zol3oS1I4QQQgghhBBCiDfFmvybNm2aVapUqaStYcOG1ubNm8UGM32qVq3qaTd8+HCxIbkL6tCrbhEbYUjXf9++fVbHjh3FBnGF+MoXMtUa4Lxs1KiR+PXq1cspPQ70rFatWtJ3QHN3wk5tp06dajVt2lTKdP/Yt23bUhbWLtsYMWKEdcIJJyRpgeNIRVjfdPQm/rpOmTIlZRyF9UWdVK9ePcmuQ4cO1p49exyraAKNTjzxxKRjD6MvCOO/fPnyvNF35MiRnnpMnjw5pZ5hfaFnjRo1kuyg5+7dux0rYjJq1CirdOnSSZpNmjTJ+umnnxwrf8L4o15q1aqVZNO+fXtr165dYpOvQL8yZcokaTNx4sTQ+ofxRx3Url07qd1HHezcudOxigajR4+2ypYtm3Cc2CZMmGAdPXrUsfInjP+KFSusM844w1PP77//Xmyigp8e48ePT6nnmDFjrHLlyoX2HTBgQFI8V6lSxZo3b16o8yGXGTt2rFW+fPmEY8f2xhtvWEeOHHGs/EnH/4477kiqU+g8d+7cUOdIrvLkk09aFSpUSDhubOPGjbMOHz7sWPmTjj9sK1asGGj76aefWvXq1UtqR9q2bWtt3bo1VF+TuIiJViwMGzYMtWPHThx76dKlTqltxwa3Uo7PAT6Djf4NtAx2sCe5idZjbJBh7927V8o2bdpkN2jQQDb8fxAF8df4uvjii5NiL8qk0mrjxo1SFoSes7r17NnT+eQ4sMF3xAbhTolt9+rVS+zNc1jRz8zN6/eEtcsWoHfVqlUTtIDeDRs2TPm70/EdPny4p96xC6E9dOhQO9bxc0oJdK1WrVqSro0aNRJdv/32WynzwvTdvXu3lPn5ok5QV1qmdojZKNfJsmXLRKPYQC6lRl74+Tdu3Fj8N2zYIGUjRoywO3bsGLcBt99+u8T8kCFD7Fgn3CnNbaBH9erVRY9du3ZJmZceXvj5NmnSRHy/+eYbKQPQE3WkZWoHPQcPHhwZPQsLaFujRg3RdufOnVK2efNmu2nTpqLt+vXrA8/xsP4jR460O3XqFLcBffr0sWMDHqmX2MDUKc0voF/NmjVFv++//17KoF+zZs1Ev3Xr1qXUv1atWqH8tQ7UDvTt29c+8cQT7UGDBtmxwahTmtssX75cNGnXrp29Y8cOKYMmzZs3F03Wrl0bqCn8a9eundJ/1KhR0rbo32qDtuaJJ56IlJ6qx/bt26UMx9qiRQvRY82aNb56pus7evRou2zZsnbXrl3tAwcOOKX5AbSqU6eOaLVt27Z4TLVs2VK0Wr16ta/OwPT/7rvv4v6tWrVK8h8zZoxdrlw5u0uXLvaPP/4oZfnAihUr7Lp169pt27a1t27dGteoTZs2otHKlSsDNTb9t2zZIrb41/TXPgZszzrrrJS2Y8eOta+44oq4DbjzzjvlPHj00Ufz7jwoDIol+aeJCFQmOppBqK07caDlGIxpMoPkFkgeeSXg3AlgP9L1R6wh5uCHz7x8o0qmWsMPCSnYQ0ckN7ySf16oL+y9LhL6uSZH/Ahrlw0gAQe9lyxZ4pQcA/qlSsxl4gtS6Z2vQFfosnjxYqfkGNOmTZMBdao6KagvQJ24k4dRAwk41cjUQjVCYi5IozD+fokoTXb16NEjMsmq3r17ix6LFi1K0gPJhyA9UvmmSuqpnmbykBwDCTicywsXLkzQdvr06Xbp0qVTJuYy8dfEV/fu3SOTKEkXJN+g34IFC5L0K1OmjCTlgvRX//nz5xfIHwkDJMpQB4cOHXJKc5t+/frJ+Q5NzHZhxowZMqBOlZhT/3nz5qXtbya7NHGY6wTpgQTSwIEDfWMnHV9od8YZZ9jdunXLy4THgAED5EbK3LlzE7SaOXOmXaFCBfvxxx+3Dx486JQmE9Zfk4RIsOZT4g/ccccdotGcOXMS2kVoVKlSJfuxxx4LjD0k5XDNcvvPmjVL/M1kndrOnj07pa0bTRwiObt//36nlISlWJb94rldsUbeuuuuu2RZQ0GIBYh16qmnOn+RXGPz5s3Wxx9/bJ1zzjlW48aNndJjYFlAlSpVZGqvHwXxf/XVV+XfWOdO/s0XMtUanHvuuda2bdusq6++2inJnNhAVKZtd+rUybr33nutG2+80Yo18jJ9u5exnDesXbYQRu/PPvvMKUkkE1/iD3TF0oyzzz7batKkiVN6DCzrCjoHTF93naTyzRc0blUjnJuKGbd+52pY/3xB9WjTpk3aeobx/fzzz7Ou3cwFtmzZItq2bt06SVttC4LiHP5oS/z8q1atGuif76TST2P7J5+ljqY/rgNe+gf5RxHVpFWrVqIp+lpKOprCH5q6/fNNU+jxySefBOr5xRdfeJ7jqXyhJXxVy48++kiWm/72t7+VZb/5hMZdixYtks5l5BVU56C4hdbwd7clbv/Zs2eLzshZ5JPOpkZe5zY0+vLLL32XPGMJLvybN2+eFM/QGPGs/qat+7vctqTwOa52EYFnrs2cOVOCpn379k5p+ixZssRas2aNdGZPOukkp5TkCmhUdu/e7Vl/mtjduHGjxIsX6fovW7bMeuKJJzJKOOcqYbUqqmfE4dkn27dvt26++eaEC+z5559v9evXz1q3bp084wG/Ec/cGTZsmHXLLbfEbWHXv39/a+3atYF22UImsZ3peQGgN26uuPXOZ1RXdFj8dN20aZPnOWD6nnzyyU7pMVL5KvgcdeK1jyiAjpufvjVq1Ihr5Be3qfxPO+20QH/EPG5ORCXmVQ+vdkD19GsHUvlCy1RtCD7XeHXvI59J1Y6kilP443l9fv6pzhM8n+q7776zbrrppoTBUb6QSr8w+gfVXyr9gdbBDTfcIM/UzHXQXkBT9Ivdmmh7gRsKfppoe+PnD02D/KE3+odRaWtMPd3XelNPr/5CKl+3lkiqQjPEbr719dxxZx6/qRV09kq0urV2+5v1ZOqcT+0u2jnV2K1R9erVE9qGII2hm5fGqCO0ydBY2+Ywtl7f9fTTT8tvue666/IuEV4YFHlUo+IwiEdFopILAmb7XHPNNVaDBg3ybhZX1MDsBDc48evXr+/8FUxYfzzgGbOp8MDWfCVTrcOCRGs14yUU//jHPyRRh3PWBBeUv/71r/EOH9oFtA8PPfRQwgxD2D377LPyW4GfXbaB2QVuwuqdjq+X3kOGDMlqbUqKTM6BTHzx8Gh0WJCcijLQyOy0gbAaAcS9lz8e7myy3PXSj7///e/W4MGDJebd/rmMnx7QM9VxBmmZyhcPltd4zcckUyq8tMV1LIy2IKw/4hzXP5Rhe+GFF+QmJq6l+Vwv0M99/Onoj5lVYf3xkgokpmCPz/72t79Zjz/+uHXttddGqg4y1bSg/vpCEKzoiEIyVUknxtzA123j9kXCBTdpzjrrLOkLI+GBz3RDO3E4xMsYch0vnfUaGeb89POH1ijfv3+/6Fy3bl3r4YcfTnrhx8CBA61Dhw45ntGkZcuWnhoh9sJq7D63NZ7d/viuMLZYbaNlqIdnnnnG+t///V/r+uuvZ/KvAKSuxUICJyaCJyy/+93v4ifbSy+9JMmEr7/+WjpGJPfQmQVBaJLHi3T8sWwUMXP//fdLI5JvZKp1umBZP+7kmqCh9rpbo6DzgvMZnewgwtqVJJnoXRDfDz74IMkn35ehutHZBUH41Ql8Mzl/pk+fbr388stWu3bt5G1kuIZFDY3boHM8SKOwcb/HeZuvV8xHaVlwGD0wY7qgbQh8VUs3iFdcLxGrUY3XghKmLVBtvc6FdP0//PBDmdFqks/LglW/oONPpX+q64DbX+vA3F+U6qCwNC2IP1aBvRRra375y19KWxOF5F+657hJQeoC8Ynlv3PmzJEkKm4YYNb3f//3f8tb8qO6TBKzvFJptX79etHKi3T9VWf8e+TIEbkpcOaZZ1r/8z//I2/QR1nUCHNuQyPM2PMiHY3DfpfGPpZiY2aiaY9l2lwWXDCKLfkXNBDwAsk+VDJ8OnToIMlAJHVIdoM60qStbpi5iYsTln4HEZQgDuuPu2P33Xef1bNnz8jPhCoqrdMFCTqcq7rh3H0p1sHDM/vSOedzlUz0Lojvgw8+KM8lUb2HDx9uvfLKK3mjtwkSF3onUDec+7hJhGeGBOFXJ0g0F7Q+0fnBTQfcocQ5cMoppzif5CbQFwM0L32hEf72I6iNCRv3qt8DDzwgnTyN+REjRlj//Oc/Jeb9Ovu5RBg9EFMFbUPg6xWLiFe0J7ijj9mUWKGRj8yYMSNpJk2PHj1ktmlYbb3OhTBtiemPtgODSo3zkSNHWv/617+syy67TJZTRRXo755h071797j+XtoqqfRPdR1w+6P/iBlUWgdYRTJu3Djr8ssvt3bu3Ck2uYzGZKaapuuPJXzoK9apU0dmtJ5++unOJ9kPkpbly5eX49GtW7duMgMs3XPcpCB1gaTpypUrrV/84hfS98Fzc3Gdxr7weJxcT0rh+d4VKlSI64wNWleuXDmlVriOQSsvwvRZTH/o/J///Me6+OKLpQ+EVQ4YcyF+J02alNM6Q+NKlSolaNy1a1dZ1pvq3IZGfv2EdDQO046oLWzuvvtu64cffoi3y3gcA5KwV111lSw3RhkJT5En/9BZRScemWI0/umCmVuYRYElv7goo7NKshc8rw11ZWIun/OaoYSEBZLDYUjlj5d84NmQGHijwdANyWPckTjvvPMkQRYFilrrgoKl1h07drTee+89uWuWL3jNRAqrdya+AwYMkBsk+aY3wPncsGFD569jFNY5kK4vrk2Y0YAB4uuvvy5JmVwH+rrbGCz3UqCRu9OVThvjNaMG/pjtEASeCYqYx4xAxHxUOn5+ekDPVMcYpKWXL+IVAxxcF5HcwKAmX9E4Nwci5lJdL21xo9FPWzcF9cczcnEt1RkoUX2JgrbjQfq7jz0d/b1eQBHWv2/fvvE6QHsTlTrIVNN0/DH2wzPfMaMSN22wpNKs62wHL8Dzik9zWWImMQZft42fL8p0NpTi9XzAXAWPa4LWprbmMlQvnfUaGebc9POHrma51yxC3IxQneGTql6zFT+NdSau14tTcLzQJKzG7hl5Gs9uf6/Ze362Jr1795abv3gJjM7OJOEp8uQfkndXXnmldDCxPLAgIJuMFzcgqYMXf5DsBXWFZZpoFHXD3T487xGNJpYouS9O+uBPDJb9lulm6m+Ct/dFIYmcqdZ+s3IyBXUQhcRHWDKJzcKIa9U7lzrThQXOgVWrViWcA0j0oxy6YmmBn6648+h1DmidwBcdHhM/X3wHbiog8ffWW29JYj4KeOmL5+AE6asP5oZGfnGrgxU/f8xyCvLXmI8KqodXO6B6+rUDqXyhpdsXdrfffrv1/fffyywAxGs+th8KzvmvvvpKBhsa54888ojo5henaAtSxSn2i9kUqdqhfIlzP6DTv//97wT9f//738uxB+kXRv+g+kulP9A6iMr5gfbCfHC/ibYXaN/9NAlKNGlbZfrDpk+fPrLEb+rUqdaFF16YkHTIBRBHmhDR+PzDH/5glS5dOkFPd3/B1NOrr5HK19QyanHoB7TW5JFq/ac//UluTplxh3LF1Ao6e2nk1trtr/WE74+6zjhG3Lg1NcaycSxrVo3dGmHJrdk2BGmMttVLY9QRvht1hH/xXWFsvb4LMxfRdudaW5ItFItquOODqaB4ICkeVu8GgYaZEkHoPjAF333BIdkPGoxLL71Unk+BwaQJksJIDuNNrn6E9XcvQdUNS1ERP0uXLo38syPDaFWULyLA+YmBKPTOh4FLkN76rDK/t5Jm4quo3lgWkQ96hwG6XnLJJfKcFiyRMYGuGIj4nQOmr1eduH2hPx5e/u6778pyJsxiiToat6oR2ljFbGP84jbIP0zcm20MOoC5juqBDrmXHog5vze+pvKFlqYvtMPf77zzjvX888/nfeIvCAw+oC1mObm1xWyDoHoB8Edb4uePmVBB/mbbjjjPt3pKpR/0D3pxhOmP64CX/qlePKF1gGWqUbi+qiZIsEBTc3ZNOprCH5q6/U1Nod2tt94qN8TwgP4LLrggcoN16IGloV56YrYo9PR7U3QqX2gJXyQZAV6k8M0338g4xrTFuBrjGsxQ9Vv2muto3H355ZdJ5zKeBwet8PIH1cqNag1/d1vi9jd1NmeloZ+uOiNxFbX22NTIfW7rM/fw4iO/F2wg+Qd/3Mhxx7P669t5TVu/7wp6ky9ezIKbOkg2MglYAGInQLEwbNgwnGmydejQwd67d68dqzi7QYMGUtazZ0+xi51sdqxDL/ZuYIPPYENyj6lTp0pdm3WocaH1r3iVp+PvBnb5FDuZam2C87Rhw4ZJn2s5vmPJkiUJZbq/WIMu5VEHesc6AglaDB8+XMp69OgR18GrLKxvKr1NW2Lb06ZNi+u6ePFiKQtbJ/CNdSZS+oJevXpJOerAveH69u233zqW0cKtETSBRiiDRrFOs2N5TDt3eRh/xHfjxo0TbLQM+rq/J5eBHrEBohzrokWL5FhHjBghenTv3t0+cuSI2HmV+fmizLQDvXv3Fn93rGKrX7++HRv0OJYETJ8+3Y4NCEXbhQsXirYjR46Ma3v48GGx8yoDYfw3b95sN23aVGwWLFggNlqGtsW9z3wC+sUGgHblypXj2kA/aNqtWzf70KFDjuWxOnCXm/7z58/39YfezZo1kzqAHdoVLUMduL8rl5kxY4ZdtmzZuCY41lGjRolOOM6DBw+KnVcZMP3nzZvn69+vXz+Jc7+2Zu3atVIfuQ70KFeuXIIeo0ePFo26du0a18OrLJXvgQMHxA4gHlu0aCHx+Oabb0q7rv7Qc82aNZHQ04+ZM2faFSpUEK3mzp0rWo0ZM0aOv0uXLvaPP/4odl5lIKw/dG7VqpVcJ19//XVpe9W3Xr169urVqyOrM46zYsWKotGcOXMkxsaOHWuXL1/e7ty5s71//37H0vYsnzVrll2pUqUkf2jn9jdtZ8+e7Wm7ZcsWu02bNnbVqlXjNlqG+nHvk4Sj2JJ/AEkIXFjdFwEkHxS1McsUTWh4fUZyA61Dc/NKOqmd+7Ow/m4QM4irfEn+gXS0RmfC/Aw6obF1++um56D6uj/HvqLcCfHCSwt3okht/MqDfIGf3l625FhSJJWumoTyKw/yxU2sTp06edaJbkOHDo1s3fhphE61iamx+VkYfy8bL7sogGN1D5bdyTu18SsP8kW8XnbZZYHxOnjw4MjpmimawDN1cifk1MYrUZeOv2njZZePaALP1MUrGad27s/S8UfSxbTzs811NIHnPk6vJJ+7HKTyR1tz5ZVXerbduj3xxBORiW1NwpnHZyb5gNr4lbt9zcSfsnz5cvuMM85IaMPzIfGnaBLO1MovyecuB2H8AXQ+88wzE3SOeuJP0QSgqZFXkk2Td35JvVT+IIytl42XHQlPKfwnJiIhhBBCCCGEEEIIISRicJE0IYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hpEhYtmyZ9fzzzzt/BZOOLSG5gsa1bdtOiT/p2JLjLF++3Prb3/6WUrewdoQQ4mbFihXWCy+8YB09etQpISR70Pg8cuSIU+JNWDtCSpJPP/3UevHFF61Dhw45Jd6EtSOJMPlHCCkS3n//feu1116z9u7d65T4k44tIbnCBx98YI0bNy5UXKdjS44D3cK0HWq3Z88ep4QQQsLx4YcfSvuxe/dup4SQ7OGjjz6S/kOq+DTteCOMZCuzZ8+2Xn/9dWvnzp2BcRrWjiRSrMm/adOmWaVKlUraGjZsaG3evFls9u3bZ3Xs2NHTZtWqVZ6fuTdzfyDM95LCZfjw4Z6aoy7CkK6/GTdVq1aVWTT5QqZaA5wHjRo1Er9evXo5pYmg3P0d2PD9CnSvVq2aNXXqVKtp06ZSpvuGv9k4p2ObC4wYMcI64YQTkvTB8aUiHd/bb7/d03bYsGF5e/EL0i+MJoi7xo0bi0/Pnj1T+qC9ueyyy+Q70d4sWbLE+eRYXFevXl2+u0mTJlK2ZcsW2b9732o7ZcoUT9uffvpJykoa6HviiScmaIsNvztszLk1dh8bZuZBC/d3dOjQISlhB9saNWrI9+s+sX9oaO7byw76uu2yhZEjR3rqPHny5JQ6h/WdPn26Vbp06SQ7bD169MjrmU2jRo3y1GbSpEkpYyWML2KvWbNmnm2VbqiDfJ2VAw3LlCmTpMnEiRNDn6vQuHnz5qJx9+7drcOHDzufHANtQu3atZPqoH379jKANMEsKdji+zFegJ3uH/Xk3ncuMXr0aKts2bIJGmCbMGFCqDYgrH///v09z4tBgwblXJz7HfP48eNDt5uIn5YtW0r8devWzXPG0syZM63y5csnfQ82+Bw8eFDsEJ916tSR72/QoIHsU/eP+Exl16pVKzlH1C6bGDNmjKcGb7zxRsq4GTt2bFq+d9xxR1K9VqlSxZo7d26kr4dPPvmkVaFChYTjxoZkWthzc+vWrdbZZ58tfY8uXbpYP/zwg/PJMTAz76yzzkpqb9u2bSu+Zt8EtvXq1ZPvx78ap+ecc47Eve47rB0JICZ8sRAbmKKG7dgJZS9dutQpte3YAEnK8TmIdcgT/gabNm2yL7jgggQ/sHfvXjs2MLBjjZnYeBH2e0nhAZ2hN+oGdQRQP6inoLpSCuKv9XnxxRcn1XWUyVRroOeIbjgH3UDfWIOddF7GOsTy/UuWLHFKbbtXr14J+8OG37Jx40bH4jjp2GYzqIeqVatKPezZs0fKVJ9Ux5OOr9bD0KFD7dhgSMr86iFfgH7VqlVL0q9Ro0ai37fffitlfgwfPlw01fiLdZrj2voxbdo0O9bhsH/xi1+I7osXL3Y+OQbi2tynxrXXb7n99ttD25YEy5YtE31jg2N79+7dUpaOvgAaQy89Pmgc61Q7nx4DNojjDRs2yN/4jsaNG4v9kCFDkuz9dFN/JaxdSQOdq1evLjrv2rVLylSDVL/Xz7dJkybi+80330gZQOzGOur2pEmTUsZ5PgENa9SoIRru3LlTyjZv3pygoZ9efr5NmzYV3/Xr16fUevr06Xbp0qXtwYMH27GBl1OaP0DDmjVriobff/+9lEHDZs2aiYbr1q1LqeHIkSNFQz3PYwNB+9ChQ86nx4ANzindn34H2ohBgwbZhw8fdiyP0bdvXzlfzPajfv36oX5PtrJ8+XK7Vq1adrt27ewdO3ZIGXRo3ry5aL127drAY4N/7dq1U/rPmDHDLlu2rP3EE0/EdVU79HnmzZuX1K5nK+Yxb9++XcpwLC1atJBjXrNmTcp4GD16tOihcdS1a1f74MGDzqfHgW7lypWz33zzzZRtQf/+/RNiXuPT/XvC2mUD0LpOnTqi9bZt2+T3QeuWLVuK1l9//bXvbzZ9v/vuu7hvq1atxHf16tUJvmPGjBGtu3TpYv/4449OafRZsWKFXbduXbtt27b21q1b4zq1bt1adFq1apWvxsrYsWPt8uXLx+Opc+fO9v79+51PjwGbyy+/3N6yZUt8f3feeaecB48++qh94MABKVP0MzNO69WrZ69cuTKhrfCz++qrr3KmTSlJiiX5pwkKBBQ6pH5oMs9MZASh9n77Dfu9pHBB8gi6Q3+TsAnXdP1Rt6hj+OEzL9+okqnW8EMnDPbQEYNvr+QfyqCxO4mF/eN7pkyZ4pQcQ/ebzm+ALZJauQiSPagHd/LNK1nnJh1f2HrVgyaw3PWQD0ATxI87AYckRyrtEXtIbEE3xD8SWqmSf6YdYtvru4HuW+M6aJ/p2BY3SJ7pMZq/SxOgSMwF/V4M6nFskydPlrhV7cJ00NQXCQFNPJrgcyS9oJtXglAJa1eS9O7dW3RetGhRks5IPgT97lS+SCipL5N/3vTp00dibeHChQm6hEnKZeIL0JfFAAnX3zCJwiiCJBs0XLBgQZKGZcqUkcRckIaaPJwwYYLckEBCr3v37knJPy/gi2SYmXg00WSZX4Iw1+jXr5+0h/Pnz09oU7ySdV6ovzt55/aHHdp7dzJx1KhRUqfjx4/PmUR30DEjeZRKM00e4pgRn0gaIj4zTf4B7PuMM86Q+Bw4cKBvzIe1K2kGDBggN1Pmzp2boPXMmTPtChUq2I8//rinbiAdX00UIgmbT4k/cMcdd4hOc+bMSYgx6FSxYkX7scceS0rMmWjycNy4cXJjsk2bNqKjO/nnBXzPOussSbh62evniFOvBKES1o4kUyzLfvE8rx07dlh33XWXFbuAOqX+xC4UhfLco3S/l2TO5s2brY8//lim32KZlUnsoiNTqTFl14+C+L/66qvyL5YR5BOZag3OPfdca9u2bdbVV1/tlPiDZ4RgarUbfA++D8QGljIFu1OnTta9995r3XjjjbKEIdY4Jy3l9bKdNWuWp202E6YePvvsM6ckkYL4hqmHfAH6YWkGlh3oslkFy7WqVq0aeA4g/r/77jvrmmuucUpS869//UtiM9bZl1h1g2WVJ554osT13XffHY9rlPV0LftNZRsbMDmWJYPGJ/RFfJrHa8Zn0LmK2IbG1157radeBUF1w6MecH2/6aabrLfeekuWl5m6wQ5lqexKGtU51oFOW+cwvp9//nnOtKclAdpTaNi6deskDdGOBOkPX7RBBfFVVq9eLUvzfvGLX4hPYZ0nuUIYDRHDQecr2hmcCzfccIO0DYXBjBkzrHLlysmS4AEDBkj7/M4770iZ15LiXEC1xpJPaI0+mBJGa9Mf11y3P665pj8e2QAfd/xXrlw5Z2Idv/+TTz4psGYA19CNGzdKDBVWfOryYMRnnz595PqGcS+WcprLg8PaZQMaXy1atJD4MuMD43ho/cUXX3hqrfUEX3c74uWL58UdPXrU+u1vfyvLfvMFUye/c/jLL78MXPKM/sb69eutW2+9VR7VUBigb3bSSSdZ7dq1k/b15ptvlmdUosxcUhzWjvhT5Mk/PBsJDQ9OOjQ8QaDi0Flds2aNPK8AvgUlne8lhQcaFSQnUI+oT5OaNWtap556qlwA/eo2Xf9ly5bJIDwfE7yZap0O999/v1xIb7nlFmvTpk1ShuTdww8/bP3617+WJAo4//zzrX79+lnr1q2zKlasKL8Pz8sZNmyY+JoXY9jieTBI9qeyzWYyqYd0fe+77z7Pevjd735nXXnllfF6yBdUP3RY/PSDToVxDgC0N7jJcOedd8p3enHeeefJOYC4xm/C4AfPQUJco6Nkksq2pM8BPJPFT98aNWoUur5uEPu4gec+P6Ab2g70FU4++WT5jaqb2XaovqYdnnuE55RmUxujOnu1A6qzXxuSyve0004rtOtAVMmkHYHvrl27fH2hf6pzBM+owkDrnnvuKbTEQC5RGBpmAva9fft26UOa34/2o2/fvtbXX38tvwHtM54zhfbjtttuy8m6QnsBrd3HCrS9QBLVT2ttb/z8ca6oP5IquNHStWtX65tvvpEEIMZljzzyiNyQgb5m4iFbMTXDdcTE1KwwJq2kA/p7iE88Dx9jXcQnXkqj8Qnt07HLBtzxZV6j3fHlTii768nta9YTfJGwxXfgs2zpCxQHuBmrGrt1ql69eqDGhcHTTz8t+7/uuusSEoe4gYPk9H/+8x+pE9TTK6+8Is+cRlJPbU07XB/UDs897ty5c6ElI6NMkbe6qBQMbBBMqKRU/OUvf5EHfL/33nsSlJgBVBDS/V5SuOCugBvUZ/369Z2/ggnrjwdEoyHAA1vzlUy1DgM6D3idOs4pDDJxscBsKSTp//73v8cvHriY/PWvf413CmGPc/Ghhx5Kml0I22effVZ+KwiyzQUwa8FN2HoI6+tXD7j79Y9//COvOjAmfucAHgZcmOCB3/guzALx09ovrh988EGJa9MvHduSBMfs/i1hYzsT3nzzTel84s6uW7dnnnnGOuWUU6QcumFAA91wPqit2w43JaDvAw88kGCXLaAdcP8m1TnVb/XzxTng5Xv99dfLwBufYRsyZEjgzJV8wEtDXMsKqj98/fRXli9fLjPM4O+e6ZJvQAN3MiiMhpmCGweIfcyIMhN6GDs89dRTkjTA92v7gZtwaD9yIXHlR6Zah/FH3/z555+Xmw84h2B/1VVXyY2XF154IedmW2HmX3HGJ657SMxh39gw0cGcbYr4xJgZsyjxOeIT10GspMFMe43lsHbZBLR2/y69nqU677zqye27f/9+SfrXrVtXJjEgFlVnbAMHDvR8GUuU0BfPmITVOB2w+sZ86Qf6ZP/7v/8rfRAzUYeEH170Uq1aNbHDzELEKW4iIE7V1rQDsEMyE5OA3AlF4k3h1W4K0PAjqFKBhvTdd9+VO/jgpZdekiDAHYqCEPZ7SeGgMzWC0AGuF+n4Y8YT4gOz0hA3+UamWqcLkhFI9oUFSTzcMfebIWWSjm22kUk9FMQX9YAli2gX8x2dsREE9EMHIlOwhPTll1+WDnPYawqSUVjSh0RtKtKxLS40PoPu/hZmG2MCvdG+Y2kH3gznF+9I5EE3vM0wCNhh5kMqu5IgTDugiQc3YX31HMBM7SNHjkidYsN1FIOs3//+97L8HJ3ofAPtSFj93edCWF/o73Ueffjhh/LoDcz6Q5I6H1ENg9qZIA0zAYlXtDO//OUvpZ3xG/Qi4bdy5UoZxObytTdTrfWaG9YfKxLQX8nGBFNYMj3H0wWaHThwQPaFTZef/+lPf7Iuu+wyz9+CfslXX32V8kZFWLuSAjPCUsWXJoXcwDdVbKuv2qD9xZJRbJh9jZsx6CP8z//8j7wpH9fKqBHmHNaEWmGA5dW4xpnfh+XXQcuK8RgcLD12L7N3o3bu5cskmGJTKt0BApIBCJSpU6fK31jWVpAEYFENTIg3GLhiWnkQQQnZsP6YjozOGDoVuThLrDDIVOt0wHJH3GXBgHzJkiVybmJW7kuxTjMGjPl8jmVSD+n6aj1gwL548eJ4PWDKez7WA5LFeD5JENAv00E1OpW4yYDn42TjjLGiQuMz6HgLq40xgd5I1uEONGa0Rj0pEqYdgBYFbUPg66chkoFYKoVBJe7QI8ERNCiIImhHwurvPhfC+ursUxMsd8UsiF/96leBiaeooxoGtTN+GmYC9MdY48wzz5QZ9ZjhF3Uy1VqvuWH88RxLtE94nAueqYnBPh7DgCWnV1xxhfX99987HtlNJud4YYBkIJI1mDWJpAna6KjO0sZs/VTxhQQ8tHYD31Sxrb5qg3YXy0fxvFW0v3g2I/rXiNtJkyZFMvkX5hyGTlg5WRggQYfn8KFfgQ2PuUBiFfGMpdr51t/IBoq8p4HOEgYHyCDjQpsuSOwsXbpUTmg8K8LvORRuMv1ekhleD9lHYgLJ2DCk8sdLPvAcJySf0IDphiQx7vzgWSIFXTKea2SqdSpwzuEZLbhg4rugLcByX8zQxRJ9LPXNd9wv5gBh6yGMb6p6wAOcsYQ0Hy+kfucA7sYXBnjJB2amYuYfOoja3mDgiE75z372M7kREVXtoa/72AqzjTFB4g/JEAwMX3/9demE5wteL4ZQnVPFlp8vzoFUvpg5j8H4zp07ZVZAvuKlIdrdguoP3yD9kQTBrNXLL7+80BPouQg0dCc1UmlYUDAuwKxizEhBfxLL/9Cm5wuZap3KH/+PmWp4qQRuVP785z+Xa+dzzz0nEzmQDES/MZeSK14v9Siq+HSDNhrtBMa0aKOL+vtKGmjtnhmm17NUiU+vevLz9ZpF6PV8wCji9eKUsBpnQu/evWWyAl7sgpmXUUywZjtFnvxDg4W7FkjIYHBaEPC8gnQz0IXxvSR9tK6wFAkXRRN0tnDhwmDOb5lupv4m6Fyg8Y4qhalVEFgqh6nwl156qdwxMsGDnBs2bCiJeVw08pFM6iEdX7MecIfTBA/DbdCggbwp1r2fKKP6oTPspx9iNtNzIAzoyEQtcYJOsJ+++mDuwtQX34GbNkhC4Y1uSHDnw4BcdfZqB1RnvzYklS9m9RXGdSDKZNKOwBcDRT9f6O/lC1u015gxhIeU5/OSpYJqWFDwHRiA4sYNVjNceOGFedHOADOx4dbafGGCn9ba3vj541yBP/4fM/8uuugiqTtTX7xkolGjRvLmZK/lm9mGqZm7n2tqxgR+5rjjy0y8mfGF+HSfs+56cvua9QR/d1zmC+ZLPdw6mS8D8dK4MKhUqZJon8/XvJKmWJTH23Yxcw8PK8WyNTcIQNzh98M9CA5Lpt9L0gcNBpITSFIgWWGCJCySsXjYrx9h/XVZuHvDDCjUOWaLYqYO9hdVMtW6MCjouRklgurhgw8+kHpwv7BAycTXJF/rAfpdcsklMsjAUhgT6IfBXWGcA3geH+6EutsbzGDA8gnMbEB7A/2jhMYn9EV84pgVbWPCxGcY0NG/8cYb5Zm/f/vb3/Im8QdUZ8ywdOuscYyXEXh1llP5oo78fBVoj0TU6aefLp3yfAPJJ2iI2UxuDTEzIUh/+KINStcXz0HCrHksN8vXQagSRkO0DYXx3DjEOq4Jb7/9tsw8u+CCC/JKe9Uas6OgtTnDJ4zWpr97+Sn8MZMyVV25kzjZDo754osv9tUMx3zDDTcU6XMNEbe4IYakTZTbC40vPMfN/QgKfXYcXhTh9YZirSf4utsRL1+8GARvocZ40ZxliP44+nN4IzX0jprWpk7ucxg6IQGIF2cU1Qt59GUrSNQyCVhCxE6OYmHYsGE4C2Xr0KGDvXfvXjtW+XaDBg2krGfPnvbUqVPl/6tUqWLHTkbx8ypTsA/sC/vAvrwI872kcPGqM60HU2+vMhDW3wvYecVKVMlUaxOcFw0bNkyywTkTuwgm+as9yqdMmeKU5ieoh1gHQephyZIlUjZ8+HAp69Gjhx27uPqWhfU168Esz/d6mDZtWly/xYsXS1lY7U2gY6NGjXw/9wL7rFq1avx7owj0jXXO4vpCGxw3yqBVrNMsdl5lbkyN3Ta333671A/i2L3her1hwwbHMppA59jgUXRetGiR6DxixAjRtHv37vaRI0fEzqvMzxdlph30b9Kkid2+fXt7165dUrZs2TK7evXqovPgwYN96y7qTJ8+3Y4NCkXDhQsXioYjR46Ma3j48GGx8yoL66ugLb/88sul7ViwYIHY5zvQsEyZMnblypXjmkBD6NqtWzf70KFDjuWxOvAqVzZv3mw3a9ZMtHd/3rdvX6kXdxuDrX79+va6desiXx8zZsywYwN70Xr+/Plyzo8aNUr0h6YHDx4UO68yYPrPmzfP0x8xfuWVV0pbZfqjbpo3by5t/fjx4+NtU7aDYy5XrpznMXft2jVBn9GjR4s+7nIFGrRo0ULi0/25foY2evv27VK2fPly+4wzzhDNBg4c6BnzUWLmzJl2+fLlReu5c+eK1tAU+kPTH3/8UezGjBkjZV26dImXwbdChQoJvl52AFq3atVKYvT111+Xdlr969WrZ69evTqybQGOs2LFiqLTnDlz5DwcO3as6N65c2f7hx9+cCzthPL9+/c7pcfZsmWL3aZNG6kb83Mtx3VOv0PLoLnf/kjRU2zJP4DkBDpH7gsuEhOKJinMDT5eyRxcXFIl/0CY7yWFiyalzM2dVFIbr4RUGH8vUKd+8RJVMtEaOqFhdvvrpueImXgyN2itCat8Bxq7kxfuRJLa+JUH+QLWgzeaADQ1ceunNmY54r9atWoJfuY2dOjQpDowyYfkH9AEoKkNdETHWlEbdzmSS0EaDxkyxN6zZ4/dqVOnpDo0N9iZ+40imsQzjxsDRHOArDZ+5UG+oHfv3kl1iW3SpEmBsZ4PaBLP1AUamsk7tfErD/JVcE7UrFnT9/N8RROApoZeCT61Mz9TTf3akEGDBknC+4orrvCMf91glw91ogk889j9knzuchDG30wAmnZmAi2X0ASgeSxeCT61Mz9DAq927dq+8Wkm9fr375/UlmB78803k9rzqKIJQPP4zcQf0ESdO6mn5aav20ZBvdSpUyehXqKe+FM0AWjq5E78AdhVqlQpIVm3YsUKu27dur7x/Nhjj9kHDhywZ82aJb7uz5n4K1lK4T+xiiCEEEIIIYQQQgghhEQMLrQmhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QQQgghhBBCCCEkojD5RwghhBBCCCGEEEJIRGHyjxBCCCGEEEIIIYSQiMLkHyGEEEIIIYQQQgghEYXJP0IIIYQQQgghhBBCIgqTf4QQQgghhBBCCCGERBQm/wghhBBCCCGEEEIIiShM/hFCCCGEEEIIIYQQElGY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYQQQgghhBBCCIkoTP4RQgghhBBCCCGEEBJRmPwjhBBCCCGEEEIIISSiMPlHCCGEEEIIIYQQQkhEYfKPEEIIIYQQQgghhJCIwuQfIYQQQgghhBBCCCERhck/QgghhBBCCCGEEEIiCpN/hBBCCCGEEEIIIYREFCb/CCGEEEIIIYQQQgiJKEz+EUIIIYQQQgghhBASUZj8I4QUCcuWLbOef/55569g0rElhBBCCCGEEEJIeJj8I4QUCe+//7712muvWXv37nVK/EnHlhBCCCGEEEIIIeEp1uTf8OHDrVKlSnluvXr1cqySmTZtmqdP1apVraZNm3p+Zm4NGza0Nm/e7OztGH779LIl6eNX19A9DGH9ETdum3yrw0y1BtCrUaNG4ud1LmJmXrVq1ZK+o2PHjgkJO7WbOnWqnJtA94392rYtZSAd21xgxIgR1gknnJCkEY4vFWF9Uadedth69uyZc5oVFkH6pdLEz3fKlClJ8Vq9evUkuw4dOlh79uxxrKIJNDrxxBOTjt2tkR9h/JcvX563+qZi5MiRnvpNnjw5pf7wLV26dCjfdGwB2mu03Th/evToYR09etT5JDcZNWqU5/FPmjTJ+umnnxwrb9L17du3b1Kdok+7cOHCUOdUFIGGZcqUSdAE28SJE1PqD9Lx79evX1J9ValSxVqwYEGo78p1Ro8ebZUtWzbh+LFNmDAh1Hkc1r9///6e58WgQYOsI0eOOFa5gd8xjx8/PpRmY8aMscqVK5fSf8WKFVadOnWS+iXt2rWzduzY4VhFG2hVvnz5hOPH9sYbb6SMm7Fjx6b03bJli9W6dWvP66puXbt2tQ4cOCD2UeTJJ5+0KlSokHTcr7/+eqhz089/3Lhx1uHDhx2rY/zmN79Jin20t3PmzMn5fkNOEutkFAvDhg1Db8Zu0KCBvWnTJqfUlv9HGT6LDV6d0uOoXyxI7KVLlzqlth0b1Ek5Plf27t1rxwYKSd/hJp19kvSBptAWdYE6AVrPqeoGhPXXejTrS+vQ9I0ymWoNVEfd/M5DfEdsEO6U2HavXr2S9Adabm74LRs3bnQsjpOObTaDeogN3BI0gvYNGzZMeTzp+CK+YxdNe8qUKU4JgX7VqlVL0q9Ro0ai37fffitlXpi+u3fvljI/3+HDh0udaJnaIWaHDh1qxwaMUh41li1bJhq1b98+pUZehPWHvh07dozbgNtvv13ifciQIXasg+iU5hfQr3r16qLfrl27pAz6NW7cWPTbsGGDlHnh59ukSRPx/eabb6QMpGMLRowYYccGTvF2u3v37nZswOB8mnvg+GvUqCHHv3PnTinbvHlzwvH7neN+vk2bNhXf9evXJ/iOHDlStINmsUGSU5rfQMOaNWuKht9//72UQcNmzZqJhuvWrQtsY9Pxh/6lS5e2u3XrZh86dEjK8only5fbtWrVstu1a2fv2LFDyqBV8+bNRau1a9cGag3/2rVrp/SfMWOGXbZsWfuJJ56Ix7naoc8zb968nGnXzWPevn27lOFYWrRoIce8Zs2a0Jql8h89erR92WWXxe1A//79JWYHDhwY+ZiFVnXq1BGttm3bJrpAq5YtW4pWX3/9ta/Wpu93330X923VqpX4rl69OrCewMyZM+0KFSrYjz/+uH3w4EGnNFqsWLHCrlu3rt22bVt769atcZ1at24tOq1atSpQJ9N/y5YtYot/27RpI/4rV66Mn9tjx44VPTt37mzv379fykjJUizJP68EhQnK8Jk7Gad+CCR0QlOh+wmyT3efJH2QPHLXJQibXA3jj7pDHXrFlJ9/FMlUa/ihEwZ7aIrkhlfyzwv1hb37IqGfpfMbYIskSi6CJCbqYcmSJU7JMTRZF5QcSsdXy5j8Ow70Q/wsXrzYKTnGtGnTQmnv53vCCSekTOohdt3Jw6iBBJxqZGqhGiExF6RRJv4Y0EPfHj165G3yr3fv3qLfokWLkvRDAikoMZrKd/DgwXFftV24cGFKW012TZo0SW5OIEGGOsrl5F+fPn0k1tzHP336dBl04/j9ji8dX01SMfGXSN++fUXDBQsWJGlYpkwZe9CgQYHxpf7z588P9If+SHxB/3xM/IF+/fpJoh9amW2HV7LOC/V3J+/c/rDDTR53MnHUqFFSJ+PHj8+ZNiPomMuVK5eRZvBPldRDUuuMM86QhPWBAwec0mgyYMAAub7MnTs3QaswSblMfMG+ffvsq6++WuI2TKIwV7njjjtEpzlz5iScg9CpYsWK9mOPPRYYZ3feeadcx9z+s2bNsitVqhT31yRhly5dmPjLIopl2S+e54Wpyvfff7910kknOaXHQRk+gw1sFfW76667rNjF2inNjKLYJznO5s2brY8//tg655xzrMaNGzulx4hduGSa76effuqUJBPWH1O2Y4NtKXPH1C233CJ1HBuUOCXRJFOtwbnnnmtt27bNil3snJLMiA0UZalCp06drHvvvde68cYbrdjFRKZ493It5fWyjV04PG2zmTD18NlnnzkliWTiS47pF+vkWWeffbbVpEkTp/QYtWvXlmV0fueA6evWHr5hzp+oo/GpGuHcVMz49DtXM/XPd1S/Nm3apK2fxneQ7+effy6+pi3OI7ctziO1BWivcA2+7rrrEmxzFRwLdMYyMLdW2hb46QxfaBfW98MPP7RiA0rrnnvukSVnJJyGiD/o5oXp745fvQ6ov+p/9913y3LUfEO1atWqlWiNPpiSjtbwh9Zuf1NrgEc2wMd97lSuXFnsc6H9wO//5JNPMtIslf8XX3zh2b7kGxpfLVq0SDqXMWZXrby0Vp3h625HUvkqq1evlkeQXHjhhXLty4X4TBdTJ79z+Msvv/Rdjqv+zZs3T4pnU2f4z549W5YQI+eCZb8kOzheY0XEvn37ZPDfoEED6/zzz3dKk9HOKGzho34oa9++vWOVGUWxT5IIGgW/pFzNmjWtU089VZJyqAsvMvU3+eqrr5z/iyaFqVVBwPNPtm/fbt18883xCyTO8X79+lnr1q2zKlasKL8Pz9sZNmyYJGXNCyls8TyYtWvXprTNZjKph5Kuw1xH9UOHxU+/TZs2BWoP35NPPtkpPYbpuzfgJTT4HDcavPYRBbZu3eqrb40aNQL1BZn6e7Ux+YTq59U+qH5+7QN8d+3a5et72mmnxX1T2QZ9TxTItB2Bdn6+0Nn0RSIQbQU+I8dIV0M3qfzN+kOSJp/113Mdg3Svcx1a42aAn9baJvn5Q2v1/+1vfysJVjw77ZtvvpHkFsZgjzzyiDwv+rzzzktIHGQrpmbu67ypmV9fIVN/8Je//EX2c8MNN0Q6ae2OL/O6744vd7LUrbPb19TZL9H61FNPyfPqELt4fmgU+e677+Iau3WqXr16oMYA/tAZbaifzmiToTPaW9QjyvOxD5etFHmri8rH4L5+/fpJjZ6JXqAV9UNZYV2ki2KfxBvMIHCD+kcchCGVv8YL7tajkTLBAAYJ3nwhU63Dssz10o9//OMfkqi75pprHItjd33++te/xjuFON9w3j300ENJswth++yzz8bbhSDbXACzDtyErYd0fa+99tp4PWBDPeTzXWO/c6BevXrOX/5kcv7gAdLQHcmpKAONEGcmYTUCYf1xxx2dT43rv//979bgwYOlPXD75xNoH/z0S6WLny/ODXd5OrZRxOv4cS0rqM7wNbXDYApJVJQ98MADSS9CGDJkSF4//BwaupNBbg2DwMyqIH/V/6yzzrIefPDBJP3R1mCWSj6QqdZh/DFD+PnnnxfNcQ7B/qqrrpKbuy+88IK8PCOXSBVfqYC/287P3/3Sj+eee87685//LH2/fJgxDK3cx6nXIncduPGqpzC+0HzGjBnxmYOpvifXadmyZYF0UrzqSOMZ/vv375ebLmeeeab1+9//PuklLI899ph18OBBx5MUJ1kf2bhgIBgLk6LYJzkGLvKYCROEJnm8COuPBgbTiNesWSN3e80GBXcTU+0jCmSqdbpgyTxm4ZhgWaRf0glJvK+//lrqJxXp2GYbmdRDur5IgmDJAjTHNnXqVIn5hx9+WJZPF1Zd5wroWLhj0g30w9IjN/DN5PyZPn269fLLL8sb+Nq2bSv1EDU0PoMSy0Eapeuvj+UwwUypfCVM+4BZ1l76h9Eevjg30rGNImHaAtXZrVFYX1O7Dz74wProo4+sefPmSXuOG2u4oYkBEtr0oGVpUUQ1DBN/Xjbp1B+A/lj+i6Vrqj9uRv7xj3+UN5BHWf/C0BrX3LD+V155pdWzZ8+cTlilc44HxWc6mqN9wCN5TJ+gpcVRAZM5UsXX+vXrRSs38E2ls58vwBJVaI43055++umR7NOBMOcwdMLsQC/S0Rk2iGVs7733ntxcQZIVN2D+v//v/5O34WOmJSleii35FzRACKKgfkEUxT7JMcLMugtKvqbjj4TR0qVLE+w7dOggDXg+zPzLVOt0gd5oyHXDbLOXXnopL5NOJpnUQ6Z1iGQgLrBYQoNZU6tWrXI+yQ+QLMbzSYKAfqeccorz13HgW1Dt0fnBc2pxhxPngNf+o4DGZ1AnOCg+0/XHbBzMfNI2ZsSIEdY///lPaWP8OuxRAIlk9yykHj16SEIoVYwiBoPaliDt4YvYTcc2ioRpC1Rnt0ZhfU3tcMMAz5bCc6WwP8yQwnJI1Pf48ePzLvmnGoaJPy+bdOoPqP4///nP4/pjxg/0x6NHojz7sjC0xjU3jD8G+WhboClW6UBXPBbmtddes6644grr+++/dzyym3TO8aD4TEdzPAcbs6L0WohHYLz55puiW6pEZC6DJHyq+ELiCFq5gW8qnf18sUwVq5YuvvhiuZkb5dmVYc5h6GSuxjRJR2fY/OpXv5JnCF566aWiK1aC4CZL3bp1rcmTJzP5VwIUefIPF1t07lOBEw9ZZlwoMKtL/VCGzwqDotgn8cbrQflIECHxGoaw/nhhhd7BwPbuu+9K/eLi2LRpU8cq2mSqdUG54447JOmEuzm4i57veM1QClsPmfiivcTddXSkMYMnH/E7B3A3PRXpnj9I/P3yl7+0du7cab3++utyzYo60Ajtq0k6bUxB/fFMUNzQ0Zk67n1EBcxWx3ORzc60uVTafGGEovql0sTPF+eGuzwd2yjidfxYKlpQneHrpZ17lg/QR5lgVgb88hFo6E58+mnohdfMKC9/6p+51qn88f9/+tOfrAoVKliLFy+WRCuWAmL56vDhwyUZiGRLLi2zDhtffsDfbRfWv0+fPtLfnjNnjlwLo/54AGjlPka9FrnrwI1XPaXyxSNccPMcGqMdCEpsRQWvl5+E1Rh41ZHGs+lvzgJU9PmN+mzAMOcPKTyKPPmnA1Msz1yyZIlTmowu98GzIID6oQyfFQZFsU+SiHagkIRAI2DiTvB6kak/QCOe6gUzUaAwtMoE7DcfEh+pyKQeSroOcx3Vz2vApvrhLmeQ9vBF58PE9NXZIgDfgTdRI/H31ltvRb6N0Q6al776YG4/fUGm/ijPhzYGd9JXrlwpHWZ0grFhKT/K/doH1c+vfdAHb/v54oHd6pvKNuh7okCm7Qi08/OFzuqLLR/iOV3S0dCLVP5af7CD/vkwsPdDz3XcxPI61/WFCX5aa5vu5w+t4Y//x8y/iy66SLQ3Nb/tttusRo0aWe+8805OzOg2NXP3FUzNzL6CSab+QNuOqMeuO77MpJAZX9DDrYVbZ7evqbPpi2fTvf322/JsOsRmVF/0oZgv9XDrZL4MxEtjAH/ojLbVT2e0tdreRv3ZiblIsdQI3qyLKaL33XefBJsbPG/jiSeeSErYqB8+g40b7AszL9KhKPZJjoMGA1N7vZYguhO8XmTqjzrFEirsA/uKMplqlSm4MGOwiPMpnwc0QfWAGUuoB7+3lWbiq6AesGSscuXKeVcP0O+SSy6RQQaSJybQD7OC/c4B09dLe/iaL/KAzjfeeKPMLsbDyjFbK+pofKpGZidP25ig+MzUP9/bGNUPMyfd+mmM3nTTTZ6da41vP19or76mLc6jdL4nCmCQAp0xm8mtFWbZBB0/fKFdWF+8KAEzI/DIEtMWf+O5t5dffnlgEiCKhNEQba/fUjzT3x2/8MdzvNQfD6kP0v+yyy6LtP6qFWbtQGtzhk46WsNfb1gobq39cCdxsh0cM5aD+mmGY8ZbeIM08/PHs9CgeZA/0GshnkXnTqZGCY0vLBN1n8v6TL7rr7/e843HqjN83e1IkC9mU2IF0wUXXJAXCVZTJ/c5DJ2QALzuuut8X8ij/v/+97+T4tn0RxIVLxXZsGGDtK/mLEGMedDeIieDRGLUNc86YidHsTBs2DCchbLh/8HevXvtDh06SFmsc2/HgkPKTUw/2MJn06ZNdoMGDaSsZ8+ejuXx/eEz2PiRzj5J+kydOlV0NOtUNTe19SoDYfy1rmGrqE2q+o8SmWptAs0aNmyYZKPl+I4lS5YklOk+Y42/lOcrqIfYxStBo+HDh0tZjx494vp4lYX1Vc0R93v27JEy1HnVqlWlHoYOHZqX9TBt2rS4fosXL5aysNrDNzYoT+kLevXqJeXQ2r2hzfn2228dy2jh1giaQCOUQaNYh07svMpAGH/EdqNGjRJsUNa4cWPR173PfAL6xQaFos2iRYtEmxEjRoh+3bt3t48cOSJ2XmV+vigz7YBpu3DhwkBbE9RTkyZNpI78bHKB6dOn27FBYcLxjxw5Mn78hw8fFjuvsrC+YPPmzXbTpk2lLZk4caLEtfrXr1/fXr9+vfjnG9AgNli0K1eubC9YsCCuIXTp1q2bfejQIcfyWB24y03/+fPn+/pD/2bNmon+EyZMiOsPX+i/bt26yOs/Y8YMOzawj2sFDUaNGiUaQKuDBw+KnVcZMP3nzZvn6Y8++pVXXiltkukP/Zs3by76jx8/PmfaDBxzuXLlPI+5a9euCfqMHj1a9DHLvfy97KBPixYtpF/3ySefiJ2WQTPYHjhwQGyjysyZM+3y5cuLVnPnzo1rBf1w/D/++KPYjRkzRsq6dOkSL4NvhQoVEny97JR9+/bZV199tV2tWrW4fT4AnSpWrCg6zZkzR87DsWPHiu6dO3e2f/jhB8fSTijfv3+/lM2aNcuuVKmSr7/abdmyxW7Tpo20A6+99pq0w+pbr149e+XKlXmjeTZRbMk/oIkK96YJOD8wwEWnyu2HhIZJ2OQfCLtPUjC86tqdVFIbr4RUGH/87bZJFUtRJBOtzeSR16bnA/y9Eh/YXz4OVLzw0ggDYlMftfErD/IFfgmoKVOmOBb5CRIXqfRTG69ydEyCfNGmdOrUyVN73aKcfPXTyOy0qY27HKTjb9p42eUj0AaJJFMXv+SdX3mQrxLWdtmyZXaNGjUS7Mxt8ODBOVlnmoQzj8WdvFMbv/IgXwX61axZM8E2nxN/iibhTF3MxJ2idu7PwvpD/1q1aiW05/mS+FM0gefWykxiqY27HITxNxOApp2ZAMslNIFnHos78QfUzv1Zuv6mndpGPfGnaALQffxm8k4Tfe6knpabvl6JP7B8+XK7Tp06SfvOBzQBaOrkTvwB2CFZZyb1gCbx3P6mDVixYoVdt27dhPaWib+SpRT+E6sIQgghhBBCCCGEEEJIxIjmA1wIIYQQQgghhBBCCCFM/hFCCCGEEEIIIYQQElWY/COEEEIIIYQQQgghJKIw+UcIIYQQQgghhBBCSERh8o8QQgghhBBCCCGEkIjC5B8hhBBCCCGEEEIIIRGFyT9CCCGEEEIIIYQQQiIKk3+EEEIIIYQQQgghhEQUJv8IIYSQ/5+99wC7ojj7/1d6sYXeewexxcSWvFSx90LvoDH2EpO81/v7J5covRuNRiWWKEiTjjE2EOnNFukg0gSkiXT3f77D3oc5e7Y+5zzPc86e7+e6Vnlm79k9+517Z2funZklhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfySlWrlxpvPzyy9Zf3oSxJclQ68xAtDVN00pxJ4wt8Yd65j+rVq0yXnnlFV+Ng9oRkmmI7/78889Wijtie+rUKSuFpIPVq1cbr776qq+uQe2IM6LfyZMnrRQShKC6Ud/U+Pzzz41x48YZJ06csFLcCWNLEhHtjh8/bqU4E9SOJMLgH8kpPvzwQ2P8+PHGjz/+aKW4E8aWJCP6HTp0yEpxJ4wtCcdHH30U2I/D2BJ/oOeECRPo1/mI+KyfxmJ38OBBK4WQ7ODjjz9W9UgQ3w1jS4IDXVF/HDhwwEpxJqgdcYb+mzc++eQTpZuf3+l2fBEWHtFv//79vvqFsSWJzJs3z3jnnXeMffv2eWoX1I4kUiDBP4x+qFChgnHWWWclbfXr1zfWrVtntGvXznG/vsF2x44d1lENY+bMmYHsQBhbkjrDhw931BvlEBSUC8oH+Xr06GGlnsGtTLHp9uJ/sG/cuLFKk2PbjxvGNlNIRWtcb8WKFZPy4n7UO9Nh7WbMmJGgX4MGDZR+euUcxjYbGDFihFGkSJEkjXB9QZBrR57u3bs7Xn9eyqFRo0bKJkg5+NlmKl7aB/n9uN6GDRuqPG7aC3620LNSpUpxPcHOnTtVHr9jZyrQt2jRognaYps+fXrg67Hr5jaKqVevXklliTp5+fLl8XNhdFPlypXV+eWYOD701o/tZIeysNtlCiNHjnTUedq0ab46B807a9Yso1ixYkl22Lp165bTI5ZGjRrlqM27774byFfgW02aNFH+Cy3dRtf06dPHsayGDBkS1x++W7VqVXVueS7Ax3F8+7GdbOW3eP2OTAP6Fy9ePEETbFOnTvXVXzSw1x1t2rRRHUMBdtWqVfO1AxglBVucX9qi0LVp06ZKVxnRY7fDsZ3sMonRo0cbJUqUSNAA25QpUwLXAbjGZs2aqevt2rVr0uibOXPmGCVLlkw6BzbdHvpVr15dnVt0hq/j2NAvU0b1uGk2efLkUJo1b95cadalSxfXa+vfv7/jvTBw4MAEv6tRo4Y6f7169eJ+h+NDt2PHjnnatWjRQpWD2GUSY8aMMUqVKpV0/RMnTgxUn+H6LrjgAlXPdu7c2Th69Ki1x5nDhw8bN910k6r/y5cvb3z22WfxMsXoslq1ahmTJk0y6tatG9evZcuWSj/92H62R44csSwLn+eee84oXbp0ksYIpvlpjOusXbu2uj49b6tWrYxdu3YltDlwnjJlyiTYYUNgVK8bccw6deqo8+P/ot1FF12k7pWffvoplB3xIFZA+c6KFSvM2M1kDhs2zErxJtaJNdu2bWvGKilz+/btVmoiOBZ+Po6L4wuxDpdK188VxpakjpQ3yhBlCVCOKE+vMtWRMpMt1lGz9pxByg//9wP59eNhc/stYWwLm1S1hs6w27Ztm/ob9rHGl7pm+z2Ecxw8eNBKMc0ePXok2QFJ1zf9HDphbDMZlEOFChUSNBItg1zP8OHDzdjDMK5BrOFmxjo71t4zwM6pHJB36NChCXkkPYi2YWwzDWhfsWLFJO1jnWB1Dd99951KcyOo9iCorZuefr8lE1m5cqXSN9Y5Ng8cOKDSwugLoFusgZagW6xhbe09g9i57dfp2bOno8Zbt261LE4T1K6wgc6VKlVSOu/fv1+lQeeGDRv6/l63vI0aNVJ5v/32W5UGZs6cacY6ROa7777r6ue5CDSsXLmy0nDfvn0qbceOHQkaeuk1cuRIpav4WKyjZ8Y6NtbeM8yaNcuMdTDNwYMHm7EOlkrDeRo3bqye5YsXL46fp3fv3gn3DbZYh9LcsmVL0m8JY5uJQP8qVaoo/X/44QeVBl2aNGmi9N+8ebOv/rhXxE7y4t4fNGhQXGs/O3uZ9enTJ6FcRVf77wlqlwmsWrXKrFq1qtm6dWtz7969Kg06NG3aVGm9adMm3988atQos3jx4vFrjXW6zWPHjll7TzN79myzRIkS5uTJk+P6u9G3b19H/YL8loIAmlWrVk1ptmfPHpUGzZo1a6Y027hxo+/vHD16tNJDrq9z585JmgHoVrJkSfPZZ581jx8/rtLkXGhnfvbZZ/HnY79+/VR9YtfN/nuC2mUC0LpGjRpK6927d6vfh+tv3ry50nrDhg2ev3nMmDFKP7nOTp06mUeOHLH2OjNnzhyzdOnS5q9//WvV3lmwYEGCz/bv3z/B37HVqVPHXL9+fdJvcbNdt25dxmi9evVqs1atWmarVq3MXbt2xTW+4IILlMZ+v3Xs2LGq3ly7dq3yxZ07d5otW7ZUz6ABAwaYR48eVXb6eWCDY4otziP5hfvuuy/hHhHtgtqtWbPGt+1ITDMrg39yPLf9OmFsSXpA8AyaQ3udoMFWKTPYo8xQdqkG/4AcN8xvCGJbmKSqtRM4lj2Q5YTY4TfYHxKyL6jWYosAVjaCYA/KYfny5VbKaVAO6FTYA3M6cv3Tp09X/o6AoZOmbgQtB6/fAMLYZhLQHr972bJlVsppEOQIoj0aeqI9AlpuAb0wtkDss01POwieib76NUBfNPSGDBnieW0SPJw2bZoKJotu9gaa2AUJ/AkS9ILG+B1u+YLaFSa9evVSOi9dujRJZ3SKvX63X14EmiQvg3/OIHgG/1uyZEmCLk7BOjvwLwQOp06dqnwcgTz4sVPwD+dBHW8PyknwEMfQyxnHRlAMvuv1G4Buqwe8sgEEz6C/HvwE0B8d6bxcD/RAkEsPKDrhZyfBMrcAoRDUrrBBoA314aJFixJ8TYJ1AwcO9PztEghDUA8vfxA0RLA7leAfkONCP7/fUNCIZgsXLkzSDIGmsJohkOekGUCgDs9Je2BOgoeTJk1K0BPHrl69utJNDxjaCWpX2CB4hvoUAThdawnQPfPMM466AVwjAocTJ05UL8xatGihAtNewT8EvcQOz1ncw/bgH0Agq2bNmko/r98AwtgWBvfee6/SeP78+QnXCY3LlCmTEMALilOgD0E6PJPs55k7d65ZtmxZ8+mnn046D45Tu3ZtpZ3TfiGoHUkmK9f8w/pge/fuNe6//341zN+LMLYkdWKVqPHpp5+q4beYZqWDYf3ly5dXQ3a9uPjii409e/YYN954o5WSGrHOjhpi3L59e+Phhx82br/9djUdAWk9bFN5w9gWNunQOt1AvyJFiij9HnrooST9YnWOZelsG3sgONpmMkHK4YsvvrBSkoG/7969W005SBe6tg8++GBcW6R1t009xTTAoLaZBrSPNdKMCy+8MD7FVsA0rAoVKnjeA9D++++/D6R9UFvoGevEKz0feOCBuJ5Iy3Q97YhvQ1/4Nu5NQfdtr2vCfQHdbr755oT8dvCsBqh3veyAaIzp7ni233HHHcZ7772npuxA41ijM26HND+7wkZ0xtSgsDoHyfvll19mld8VNJgyBA0xTcyuIeoRPz+Hj+MYt956q6o3/Th48KCyt4Pz4Hw4/+zZs9W0P/hurKOmfPff//63mnbYzTaVF7ZI123ff/99R9tMBFqgHvfSHz5c0PcrdMW01TZt2qhpmKjLoSvSMIXvhDVlTbfr169fXH+7XSYgWmPKJ7TW/TWo1ngebNu2TemBejhV0EYU/fr27av0++CDD+L6Ffa0X2iGaaAFqZnUEfY6p1y5cvE6Arphaix06927t9INz1FM5cT0x2PWdN6gdpmA+CemfKNNp9cF6MND66+++spVa+i8detW484771TP+SBgKjHu0b/+9a/K5+yg/YZpq61bt1Z9E+iHNYTLli2bNKXYbovfodtmwrRf8WfR2O7PaDd//fXXKS8Bgum/OA+WP7DfNyhL+3nQNjv77LOVdrjvoR3WTURap06d4tN5g9oRd/xbKRkGFqJHRYYKABWZF2FsSXpApYKFZNHpwI2oU6VKFeO8885TD8CC/KDApZdeqhpkmzdvVpUyfh/Wxhk2bJhx1113WVanCWNb2OSX1siDgDmOe84551ipyWD9EwRpUfHKAxr6ofGm64d1cEQ//UEuWm/atMnXNpMpbJ9HOaC87OUg2uI3ibbDhw837r77bmUjXHLJJYFtMw3RHg0WN+23b99eoPUN9MQ9IHqiEY+1jODXma6nHTTe3PTFWnrp1BfBlXPPPVcd1+/eF5/duHGjqqPwG0Vjve6QstDtsO4RfDuT6hjR2akOEZ3d6hC/vOeff36BP3OzjYKsR/CCBZ1/dFLQSUXnHsGjJ5980rjmmmuUz8IvxXfXr1+vyhD1CNaRknpZ70jBFusI6rbo0DrZZiLQH4viu+mPa8qL/siDNgo6mvbj6rjZia4bNmyI64p1pqDrPffcEw/i6Ha/+MUvlC852WUCqC+gtZMmUl/ghUJB1hd4sSa+juAWdMZ6YFhrNhP00zWzt4l1zfR1l1Ph97//vQr8IzC3ZcsWVUegL/uHP/xB9WXhb7inoRv8Duvmo58L3fCxGfE7CX4FtcsE5Hkm/qk/o+VZKP6Zjhdaq1evVmutIlBXs2ZNxzYBXu5Av7Vr16r1sVHOb731ltKvY8eOCfrZbaG1botyLWzwMlY0hj/r11ypUqU8a4w86IugzsZxcR7cN/K3U1mi7oeeOA+0Q3D6m2++UfuR/uabb6p6AM9L0U63w7HFDuseZ4rGmU6BtgieeOIJVfiyIeq7cuVKa28wUMjoVMFpUOhehLEl6QWjEOzg5q9bt671V/rASBzdr1DJ6qCCe+mll+INHfgEfOPxxx9PGl0YxjZTSLfW6DSgIkYwSQf3Kh5movNrr72mOtv6SKiwWr/44ovqt4Js0NoLjFqwkx8+71QOaLzomtm1RTAW2j722GPKDvmEMLaZits9gMWACxo3v84mPe1AX/vvTqdvo5GJABXKCyP/0LHB+WQbOnRowpt+aPz3v/9dBQuxHxqjkQ2N5XngZCe+/eijjybYZQqoQ+y/SXT2+61ueaGpU14ZpYZ92FCHFPTIqkzDSUM8y4LoHxR0XF555RXj22+/jS+YfsMNN6hOy7hx4+IdSbRZX3jhBRVYAPBd+DjuD/iuHtBzsoWfO9lmMtDf/luhv5sP+4EXAvBpjNTxCiC52UHX559/XumK87vpGtQuk0i31l5AV/g1jott0KBBCaNRod/f/vY3FTgF4uuYEQL9MiV4ipF/BaEZRq/94x//UEHpetYHOq6//nql46uvvhofnSa6IWAqfie6YaS96BbULpOA1vbfJc+zdN5PuG/xYSQEn92CRtBv7NixKnCq64cXOdBPD/7ZbRG8dbMtbOTDMzqpaIyBMhhBibaFrqVTWcp9o58HAT986EX6N6IdguHQTo6p2wHYIZiJ2R233HILg38BSN8dlAcQIUaDPy+gMQYnDUIYW5IaKE+UqxfSGU4VdKQRpJJthvVVVQSZMf3F6c0lAkt4O4tOoR9hbAuD/NAa00XfeOMNo23btuqrTTqYJoC34zqYUgntnRD98DbfjzC2mUZB+jzAFAL7+bymtiIggjfqQbQNY5sJyIgNLyQwVBiInhiVlY2Ib7vd4yCdvo06BtM3li5dqjrjEujGiAfUTU6/A4E8aIyvGXoBO4x88LMrDILUIRJQsBM0r9wDCDSh4y3PTeiKhvlTTz2lpqqjEZ1roB4Jqr/XvRAUdOQx7TxoB+uRRx5RI0nwFUl0irwIY5spiP5e2ooPB9Ufoylff/1147e//a1qy7hpHdQOgTzoioCtl65B7QqL/NDajeuuu05NKcVxsEFrTEX/05/+pEa5/vDDD5blGaDfmjVr8iUImVeC1g/p0EyAdqgjggaLEMiDbn4vKoLaFRYYPYY2nZeOEhRKFUzRRX8HU/oReA6iB4J4GHEmX6X2Arb//e9/A9kWJNJu9tM4TFsAU3Gh5RVXXKHqUfitjAT0eqkoZWn/LVgyB1OC7dOF7Yidffoy8aZAlcIoIRSwvumjVcIQpsORzs4J8QadXLzx8CK/grHwJZQzAlerVq1SHb0ok26tUVGj44A8aAzb8yFAp9+7uJ9hhw5jLt9fBe3zCCjhYSrlgJGuGPKei+WAICVGkHsB7THyi4RHfNur4ZpO38aUJkzRxbR1nBOjpLDOGQKAmPIIf48iQeoQdIaddA6a1+0eQDAQU3PQGcdLBAQuoqqzG6hHguqfaicObRO8UJw2bZqxcOFCVZdjChOmhqEMUBa5hujvpa34cBD9MZUM7RVM48NoShkRaSeoXZRIt9ZhQEALwQD8H2vkoa7xCgxkCkHrh3RphqmoeEmFEanz5s1Ta6JhmYt33nnHuPbaa30DkdkM6ka06bx0RGA91TYd7n0stYA1GDG6NJNG5OU30m720xizJoOAqdp4QYsReRixKiP3UJa4b7yCclKW6a5riDdZFyZF4wudDUSkcfN6EcaWpBenkUgITCAQm59gKLE0MDAiIhdIh9YI/P3mN79RHQ9M+8XDwQ8sLI4RlliY+eOPP7ZScxenj3oUhM/jrSUC3rlcDm73AN7Gk9SBvvaAUH74No5nf6OPBiU65XhbXZDrUBUGTh+VEJ39AnJueXEP+OXFcxOdyn379imdcxUnDeFzQfQPAo71xz/+US3+vmLFCuOyyy5TnR5MA8ZLHHT0sWxGqgutZyvQ3x4MgmZBfFhAWx8LweMjWgiouo2ADGoXVdKhdV5AXdOhQwfV1kRdk5/nSjdOH/VIt2Y43p///Gf1gQ6MgL/88stV8AT1AuoIfEAB/86kj8jkB9DaXg/K8ywdAWP0czBA5F//+pf68AnufWwYGYn+0FVXXaU+lqR/zCNqOH04JazGCPzhpRXuZSxBJNPUdZzKUu6bdJQlCU/WBf/04I58HdCNMLYkPWC9A7wtQOANN7cOGlsIxGKkAsqGpEa6tEZeTC9AYwyjbLCYcBBwXBw/1ylsn5dyyKWOiyDaOwWGRHsEslnf5A0E3tz0lYW506FvLvswEJ2d6hDR2a0O8cuLej0/658oUFD1CKanY1QPpkbheLq/Y82/Bg0aqOlT6IDlEtDfLcAP/eHDQfRH3l69eqkpbfjS969+9SvHOiWoXRSRlykIcLjVFxixw/riDLpm9ntT1ywdI+Cx/A3qCAT97HUEPt6DOuI///lPWqa9ZiLyPBP/1IOq8iwU/8zvexYjs/FczaYAdRD0j3rAn/Xr0z8G4qfx4cOH1eAD1NH4SCCea/rafnLfYL/9PFKWqPvTMaKehCPrgn8AU4MwlHTgwIGOHwyBQ2N4NAhjS1IHFcbVV1/tOO0WAVgEYvPzq7l4WMgXntHhiTLp0Bp63XbbbaoxgWkvQQN/AHnxYMwFrb3wKgdZn0//Em+6kXLAYs65Vg7QHm9o0VjGFCIdaI/OXX7WN1FHfBv6wrf1xpvUMenybSxAjxFWGBGlnwd/o0OE0SJR7ZCKzhhhaddZ/BiLvTtNn/HLizJyyyugDsH6R1j3CB3OXAMdEGiI0VB2DTGa2kv/dJHLLyugP+pxL/0xPc/rwwTwYdT1eIGJkVEyqtJOULuoIlpjNA601kfeBNU6FaA/AtwICtiDW5kKNLvyyitdNcPoUbSj80szwR78iiLin1jHzb4EBUZGQ2t8UCLVabpYjw+j+nB8fcOHJKDvggUL1MuaTFuvLx2IP4vGuj9DYwQA8eEMrM/pBgJ/nTt3Vut4QrNf//rXSf6P4B/Og3UP7feNfh5+oKMQiDl7vhNrvJvly5c3hw0bZqV4c+jQIbNt27ZmvXr1zO3bt1upieBY+PnYYIs8sEUepHXv3t2yDGdLUmfGjBlKV5Q5yh5IGTiVi5f+Uk52G0mX8gTiZzhmUF/LdlLVGn8j3WmDvtu2bVNaxx6A6hzLly9X+SQNdjhGrFJX6bkKyiHWQEjQaPjw4SqtW7ducX2c0nREVydN/crB7ZhRZ+bMmXHtly1bptLyqn2DBg0C6RjGNtuBvkWKFInri+uFlkjD9Z86dUrZOaXZ0XWz28g++PK0adPUeeTcqIu2bt1qWUYTXGus8ax0Xrp0qbr+ESNGqOvv2rWrefLkSWXnlOaWF2m6HTRu1KiR2aZNG3P//v0qbeXKlWalSpWU7oMHD3Ytu6gza9YsM9ahVBouWbJEaThy5Mi4hidOnFB2Tmk6O3bsMBs3bqx83L4fbZUOHTrEy0/2Sx7UT1OnTs3JMoD+sU6gWa5cOXPx4sVx/VEmXbp0MY8fP25Zni4De3qfPn1UucCP7VvdunXNzZs3q2MGtYsysQ67GevYK60XLVqk/G3UqFFKf2h67NgxZeeUZge+27RpU+XPuo2ko67Zu3evSlu1apVZrVo15ecDBw50vH8yFWhWsmRJpdnChQsTNOvcuXPCtY8ePVrpa08XoE2zZs2SNAOoI66//nrlo8h/9OhRlS55oN2kSZPidXoUmTNnjlmqVCml9YIFC5TW0BT6Q5MjR44ouzFjxqi0Tp06xdN0oFmLFi2U/zrtdwLHrFq1qjpv1DUuU6aM0nj+/PnqWseOHat079ixo/nTTz9ZlmZC+uHDh1Xafffdp3zcqR6tU6eOuXbtWlVuc+fONcuWLavOM2/evPh5SpcunXA8UrAUaPDPyUmQLkELAZWfX/APuB3XKfATxpakjgSl9M0eeBIbe7qXv2CTMnMLXOG4uURetcZ91q5du6S8+iZaIz8aHfb9OF7UG8pBcdLIHhwSGz0d/l6hQoWEfPo2dOjQuK1bOdjPk2tIANBLE7Gxa1+xYsWEfPqmax/GNmpIEE6/XuioBynExp6O4JKXbkOGDInr5mSbC4E/QYJ4+vWjg6h3QsTGLd0rL+jVq1dSWWJ79913I+u/QZEAoK4LNNSDFGKjp8NvK1eunJBP3xBUlXLQA4C6Ddo8EvTKVSQAqOtiD/wBsZN90PTaa6919GvZBg0apALeQeyyKSiVVyQAqF+7PcgnNvZ0PYin55dNAnt9+/Z1DLROnjw5qV7KBiQAqF+LU4BP7PR9fpo9++yzcT/XA4C6DQIon332WcLzNapIAFC/fj3wB2CDIJIe/IPONWrUcNX5mWeeSSovnVwJ/gEJAOr62AN/AHYI4Emw7scffzRvuummpGelvg0YMCAeuJYAoL6fgb/C5Sz8J1YQhBBCCCGEEEIIIYSQiJGVa/4RQgghhBBCCCGEEEL8YfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCGEEEJIRGHwjxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghOcTq1auNV1991Th16pSVQgghJMow+EcIIYQQQgghOcTHH39sjB8/3jhw4ICVQgghJMow+EcIIYQQQgghEQej/apVq2ZMnTrVqF+/vlGkSBFj586dRtOmTY1u3boZx48ftywJIYREjbPMGNa/CSGEEEIIIYRElH79+hnjxo1LmO5bt25d48MPPzRq165tnHXWWVYqIYSQKMGRf4QQQgghhBCSA/zjH/8wli9fblStWlUF+gYOHGisXbvWqFOnDgN/hBASYRj8I4QQQgghhJCIM2fOHKNkyZJGmzZt1AjAO+64w/jggw9UWteuXTntlxBCIgyDf4QQQgghhBAScS6++GKjT58+xvr1641y5cqpj31MmDDBGDFihHHPPfcYRYsWtSwJIYREDa75RwghhBBCCCE5xOjRo43nn3/eeO+997jWHyGE5AAM/hFCCCGEEEIIIYQQElE47ZcQQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCGEEEJIRGHwjxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EdyipUrVxovv/yy9RfJT8JozXLJP0Rb0zStFHfC2BJ/qH3+s2rVKuOVV17x1S2oHSGZhvjuzz//bKW4I7anTp2yUkg6WL16tfHqq6/66hrUjjgj+p08edJKIUEIqhv1TY3PP//cGDdunHHixAkrxZ0wtiQR0e748eNWijNB7UgiDP6RnOLDDz80xo8fb/z4449WCskvROtDhw5ZKe6EsSXh+OijjwL7fBhb4g/0nDBhQiC/DmNLziA+66eb2B08eNBKISQ7+Pjjj1XdEMR3w9iS4EBX1B8HDhywUpwJakecof/mjU8++UTp5ud3uh1fhIVH9Nu/f7+vfmFsSSLz5s0z3nnnHWPfvn2e2gW1I4kUSPAPIxoqVKhgnHXWWUnbHXfcYbRr185xn77Vr1/f2LFjh3VEw5g5c2YgOxDGlqSH4cOHO2qOsggKygZlhHw9evSwUs/g5lfwJz14IXY4d+PGjVWaHNvpuNlGKlpDm4oVKyblhYZunWlo2759e2UHXVesWGHtOXO8GTNmJGjdoEEDpbVeOYexzQZGjBhhFClSJEFHbLi+IMi1I0/37t0drz9oeenaNmrUSNkEKQc/20zFS/sgvx/X27BhQ5XHTXuhZ8+eSefCfbB8+XK1H3pWqlQprifYuXOnOr792GI7ffp0R9sgI30KAuhbtGjRhGvGht8d1D/sGuvXpu9z2/Q8GN1UuXJldX7Jh2NAQz876Gu3yxRGjhzpqPO0adN8dQ6aVzSx27Vt2zbnAxajRo0yihUrlqTNu+++G8hX4FtNmjRR9UO3bt08R9f06dMnqbxQjyxZskSVF8qpatWq6tzyXICP4/j2YzvZym/x+x2ZBPQvXrx4gibYpk6dGvhexXU3bdpUlUHXrl0TRt3o++znkE3Pg1FS1apVU+eXtqgcA7q62eH4TnaZxOjRo40SJUokXf+UKVMCj1rENTZr1iyutX30zZw5c4ySJUsmnQObbg/9qlevrs4tOsPXcWzolymjetw0mzx5cqARobhGu++1bt3a2Lt3r2V1GuhWqlSpBDvZunTpYhw7dkzZ4Zg1atRQ569Xr17c75o3b65087Nr0aKFKgexyyTGjBnjqMHEiRMD1We4vgsuuEDVsZ07dzaOHj1q7TmNvt9+DtkkH0aX1apVy5g0aZJRt27duH4tW7ZU+unH9rM9cuSIZVn4PPfcc0bp0qWTrhvBtKDPjF27dhkXXnih0rFTp07GTz/9ZO05zXvvvWecffbZSefAZreHdnXq1FHnx/9Fu4suukj5vdgGtSMexBoZ+c6KFSvM8uXLm8OGDbNS3Il1YM1YI9SMVVDm9u3brdREcBz8dBwTxxZinS2Vrp8njC1JD1LeKEeUJ0BZoky9ylVHyk22WEfN2nMG2OjnALBzKldJ17egvyWTSVVr6AS7bdu2qb9hH2t8OWoo4N6JVdzmlVdeqc69fPlya89pevTo4ai1nEMnjG0mg3KIddxUORw8eFCliZZBrmf48OFKU9Eg1nAzY50da+8ZYKefA0BD5B06dGhCHkkPom0Y20wD2lesWDFJ+1gnWF3Dd999p9LcCKo9EFsvG+Cmp9Nv6dmzZ2DbwmDlypVK3zZt2pgHDhxQaWH0BdAt1kCLXx/0i3WWrL3ezJw5U+UdMmRIQh433bZu3WpZnCaoXWEDnStVqqR03r9/v0qDzg0bNvT9vW55GzVqpPJ+++23Kg2MGDFClZ2kiR00Gjx4cOByiRrQsHLlykrDffv2qbQdO3YkaOh1z48cOdKMdYDiPhbr6JknTpyw9iYitl42oHfv3gn3DbZYh9LcsmVL0m8JY5uJQP8qVaoo/X/44QeVBv2bNGmi9N+8ebPvdUDXYsWKxa8/1hE0jx8/bu31ZtasWWbx4sXNQYMGJZRJnz59EspVdLX/nqB2mcCqVavMqlWrmq1btzb37t2r0qB106ZNldabNm3y/c2jRo1Sesm1Qutjx45Ze08ze/Zss0SJEubkyZPNkydPWqnO9O3b11G/IL+lIIBm1apVU5rt2bNHpUGzZs2aKc02btzo+TtHjx6t6hKxk7yod5999tkEP4VuJUuWNCdNmuSrW79+/RJ8XnSz/56gdpkAtK5Ro4bSevfu3XG9mjdvrrTesGGD528eM2aM0k+us1OnTuaRI0esvf7MmTPHLF26tPnMM8/Efbp///4J/o6tTp065vr165N+i5vtunXrMkbr1atXm7Vq1TJbtWpl7tq1K67xBRdcoDQO8lvHjh1rlipVKn6NHTt2NA8fPmztPc3cuXPNsmXLmuPHjw9UF993332qzrBrt3bt2oS2iZvdmjVrcrYNE4asC/7Jsdz264SxJekDgTboDv11ggZcpdxgj3JD+TkF/5yQvE72si/Ib8gWUtXaCRzLHsgSUB4IaOG8ODbObQ/+ATlG0PIWWwSwshEEe5y0kECpPTCnI9c/ffr0BH2DNhIkv1Meu7Zexwxjm0lAe/zuZcuWWSmnQdAoiPYIbIn2CIq4BfbE1i/wJ4h9UO2D2hY0CJ6Jvvrv0oNyXr9XgofTpk1TwWTROEgDDe2B9u3bq2eAU/BLgl7QzR4c1AlqV5j06tVL6bx06dIkndEp9vrdfnn9gnqijx48zDUQPIOfLlmyJEFDBIXQaYaGbh1x6IfA4dSpU5WPN27cWPm4U2APtghy+QX+BLGH73r9BqDbIojlFzjIJBA8g/6LFy9O0l+CckGufcqUKeqFBIKG0DhIhxP1zLXXXquevU7BOgmW4XliDw7qBLUrbBBow/2+aNGihHpBgnUDBw70/O0SCENQD1ojaAitUwn+ATku9PP7DQWNaLZw4cIkzRBoysvvlevVA4ogTPAP4DjVq1dXutkDiTpB7QobBM9Qny5YsCBBa6egnB1cIwKHEydOVG2GFi1aqMB00ODfjz/+aN54442qnWIP7CFgVrNmTaWf128AYWwLg3vvvVdpPH/+/AQfg8ZlypQxBwwYYB49etRKTUaChxMmTFA6t2zZ0uzcuXPKwT+AY9euXVtp9/TTT7v+jqB2JJmsW/MPa4NhiPT999+vpjl4EcaWpIcdO3YYn376qRp+i2lWOhjyXr58eTVk14uLL77YiD0IjVgFbKWkRqwDpIYYY6rqww8/bNx+++1qWD3SemTxtN90aB2Wt956S01JijV0rJREoHWRIkWU1g899FCS1sgrONnGHhSOtplMkHL44osvrJRk4O+7d+82brrpJisldXRtH3zwwbi2SOvePXHqaaxzFdg204D2sQaimnaAqZw6mIZVoUIFz3sA2n///feBtMeacdACdQh81A3oWbRoUaXnAw88ENcTaU7ae9nGGp6WZeEgvg19ZdqsoPu2l4/gvoDGN998s6duTsQa32pK41VXXaXKUxDdMN0dz3csH4LpJZiyqesGO6T52RU2ojOmBoXVOUjeL7/8MqPv48IGU4agIaaB2TWE3/n5OXwcx7j11ltVvekF1jSD36GuhQ+7MXv2bDUFFr4b66gp3/33v/+tph12s03lhS3Sddv333/f0TYTgXaox730hw973a8oA9wLt912m6euTqCeiXUkjSuuuEKdT84PXTFttU2bNkb//v1V/Qxdkda165npwbpdv3794vrb7TIB0RpTPqG17q9BtcbzYNu2bUqPsFo7gTai6Ne3b1+l3wcffBDX73ghT/uFZp999llKmuUH0A1TY6Fb7969lW7o92IqJ6Y/HrOm8wa1ywTEPzHlG206vS5APx5af/XVV65awze3bt1q3Hnnneo5HxZpc/zqV79Sz0+cH22yMmXKqCna6JtAP7QHy5YtmzSl2G6L36HbZsK0X/Fn0djuz2g3f/31155T2dHe2LJli3H33Xer51Q6kCnC0A73PbTDuolI06cIB7Uj7mRV8A9rjaESw82PSsyLMLYkfaBSwbpBqDRxI+pUqVLFOO+881SjQV+TL51gzRgEfO+66y4rxTAuvfRS1SDbvHmzqpTx+7A2zrBhwxLsso380hp5oCGOe84551ipp9cnGzRokOpE4wHhBLRG403XGuvgiNb6g1zKZdOmTb62mUxh+zzWoUF54QEomuna4jeJtsOHD1cPa51LLrkksG2mIdrDH9203759e1q0RxARx8NxvYCeuAdETyxcjrWM4NdO2nvZFvY9gPVc3PTFunHp1NcJ+DYCLvaAq/jsxo0bVR2F3yi66XWH6KvbYd0j+HYm1TGis1MdIjq71SF+ec8//3zf+kfqfKdyzgUKsh5BEBG+GLQeQWcUZYi6AetISb2sd9hgizUEdVusjeVkm4lAfyyK76Y/rik/6xmsfYUAKV7A6MEs0XXDhg1xXd955x2l6z333BO31e1+8YtfKF9ysssEUF9AawRS3OoLBFHzS2sn8BJOfL1cuXJKZ3woAWvNZoJ+umZ6mxjomh0K+bEu+DTqXafjBgG6we/WrVun+rrQDR+bEb+T4FdQu0xAnmfin/ozWp6F4p/58ULr+eefV8H63//+9/GgFl4sQL+1a9eq9bFRzhgIAf06duyYoJ/dFlrrtukKlKUCXsaKxvA7XeNKlSrlu8ZuQDsEp7/55htV1tD5zTffVPUAgnp6eYgdng9ih3WPM0XjTCergn8oYHSS4Jh+DacwtiT94K2AHVQydevWtf5KDwhI4S0FKi9sr7/+uuoA6qMGUcG99NJL8YYO/AL+8fjjj6dtdGFhkm6t0WlAhY9gkg4Cq3irhjfgboTRGrYvvvhivNGT7eWCUQt28svn0agQn3/ttdeMIUOGJPm8ri2CsdD2scceU3b6wz6Mbabidg9gMeB0gEYQGuo4HkapojMt+mNDnSONJDe/DqK9l21hAn3tvwW/Od2+rYO37xi5h3PbRwNBt7///e/Gueeeq9KhGxrZ0A2jOMXWbie+/eijjybYZQqoQ+y/SXT2+61ueeGzfnkREJU6P9MDRfmJk4Z4lgXRPwioRxBoRZnAB9FpxHFlQz0uoy3Qbn3hhRdUYAHAd+HjCITDd/VycrKFnzvZZjLQ3/5boX8QH84rqGcwcg/nto+Cga4IBkBXnN9N16B2mURBao2RUrqv4yWyPhoV+v3tb39TgVMgvo5nLfTLlOApRv6lUzO8sML97jaCEvWxrhtm3OijSEU3BEyxX9cNI+3lmEHtMglobf9d8jzLr/sJo39RF2BEnD7CE/qNHTtWBU51/TB6G/rpwT+7LUbHudkWNvgwjF3L/NIYQTmMRIcm2AYMGJA04hQBP3zoRfo3oh0CsdBOgnq6HYAdgpkYmHLLLbcw+BeA/LmDXHjiiSfiBS8bouFhQUMMDhqEMLYkdWQEgRfSwU0HMrVbx2uaHwJLeDuLTmG2kx9aY7roG2+8ob782KpVKyv1TDoas0HvJ9Eab/P9CGObaRS0z2MKQRifR0AEb9SDaBvGNhNAQA5LBHghgaF0gPoG0wuWLl2qgiUrVqxQDZAnn3zS8cvCoidGZfkRxragEN+2X5dOOn1bR/zcr85BEAW64WuGXsAOIx/87AqDIHWIBBTsBM3rdg8gwPr666+r+h4b2mW5hozA8UL097oXggLfRj2ycOFCNX0NL3TQaXzqqadUPWKf0vbII4+okST4iqRf+YSxzRREfy9txYfTob8OpmFj2Q2M+sNgATdQD0HX2rVre+oa1K6wKEitr7vuOtXBx3GwyfT0P/3pT8Y111xj/PDDD5blGaDfmjVr8jXgG5ag9UMYzTAzDW3qq6++WtW7eqALumEqqa4bpkD/+c9/Vro5/RYE8qCb34uKoHaFBUacoU3npaMEhdLNvHnzVF3wu9/9TgWinfRBEA8jzupbX6X2Arb//e9/A9kWJNJu9tMYAbVU6dChQ3wEITZMi8YU6P/7v/9T+zDS0+l3oD7G1GP7NHs7Ymd/cUO8KVClZHSEvqHTH5YwnY386pgQZ9BxxRsPL9IZkIX/6P4EH0NHBmvfoMKJMunWGg9ddByQBxpKPknH2kF4C0sSKWifR5AInUPxebxAwZB3rBuXa3UdgpQY+esFtMfIr3SAJSQwhRTTqgGm02D9EQQAMSUvaohvezVc0+nbAuocjGTCmi65EJAKUoegM+ykc9C8TvcAdEZ9gkDFP//5T8/gR5RBPRJU/3T4IvwaAWusK4XjYRoTggEIAGIUZkGvHVbYiP5e2ooPp7MuwHRjjLz+7W9/q+qZXOg8FpbWAEEtBK7wf6yRhyBpNvh60PohqGbwOwyGQd396quvqhF5XkAvBGuuv/56td5dtuiWFzAwQ2ZzuYHnVbradALKBLOWrrzyyqRgbNSQdrOfxvnRHpCAH0byITAaZV/OZLLqSYeGFzoaiEbjRvUijC1JP04jkRCYQDA2P8Fi1xi1hsWC8UY3F0iH1ugE/uY3v1HrmmDaLx4OAtarwKg8BATxsJANjRc05BAIyaYPdOQXTh/1KAifxzTsXPN5O273AN7GpxOnl0nosKORhLep9n1RAfra7+/89G2sR4Q6Bw1FWUIgF3D6qITo7Fe/uuXFPeCUF3U+Ojmow7G+ViaOiCxonDTES8Qg+ofBaZSQXo9E/cWlG9Df3hGEFm4+nCqoZxCExWiqdAcTMp2C1lpAfY56HW1N+Hp+nivdOH3UI6xm6I+ivYZ11/71r38FHiEquqFPm2265QVobf/ghDzP8iNYhH4PZgZg4Ajq4SBlku04fTglPzUWMPJPBivAl/PzXMSZrAr+ofKTN0eYfuVFGFuSPqQBi6lI9gYsHnp4cOFtV3516HBcHD8XSJfWyIsvX6Ixhq8JYvHqsOBLiehM5iKZ4vO50Fix49VhFu0RyE5Ve+THcXJNY1lg20lfWZg7Hfrq4DwYBYWRFFjkORdG44jOTnWI6OxWh/jlRb1uzwu7nj17qml3mIaDFzi5WH8IBVmPoCxIItAf6+W56Q8fzo96BqO2EXzBelS5MmUM9QW0RnvNrb7A6Kt0ap3t6JohYKGja+Y3Ah5642MQmFqK6f0Y+cupionI80z8Uw9yyrNQ/DNdz6zDhw+rvk/NmjXVB1Civmac/lEP+LOusf4xkHRqTDKLrKt1MO0Kw6+x8CnWSbEDZ37nnXfUv8PYkvSACgNrWGARZbxF0ZH1+fLzC7t4WKAThHKPeiM7HVpDr9tuu834z3/+Y4wbN84x8GefWi0bplhD5+XLl2ften3pwKscZN0y/Uu86UZ8HlNHcq1jCe2vuuoqtVAzpg/oQHtMlUlXfYMPT2DKL/wd/i9g3T+kX3vttb6N/2xDfBv6wrf165Y6Jt2+jbXQMIoV5ZordYrojBGWdp3Fj7FovlNH0S8vykjPi/oCf7///vvGyy+/nPOBP4DgEzTEaCi7hhhN7aV/WPChBYysQL1hr0dktGvU6hE/oD/udy/93T6KkFewvhfqmcsvv1zVM7lyD4jWGFkFrfVRN/mltQ7qHwRdEUzLFt2hGaaDummGYB7a0V6a4boRWMK1Y0mLyy67LFR9IrohaBNlfxX/xDpuaNPpdYGsyXfrrbem9cMZ8+fPV3UBygRt6KjXBeLPorHuz9AYAUB8OAPrc+YHCLai/YHnHHyZAfBCIHZj5TuxRo1Zvnx5c9iwYVaKO4cOHTLbtm1r1qtXz9y+fbuVmgiOg5+ODbbIA1vkQVr37t0ty3C2JD3MmDFDaYsyR9kDKQensvEqAykru42k6+fIxXJNVWv8jXSnDVpu27bNskwGx8R5ly9fbqXkLiiHWIMhQY/hw4ertG7dupmxh6trmg58uH79+qpc7Ptln34OSUN5uR0z6sycOTOu/bJly1RaXrVv0KCB735oPW3aNGWDc8caLupe+e677yzLaCHXKPriuqEl0qDVqVOnlJ1Tmh1dYycbPJ/bt29vVqhQIX6uXAE6xzqPSuelS5eqax8xYoTStGvXrubJkyeVnVOaW16k6XagV69eKr9e18tWt25d89tvv7Usc4tZs2aZsQ6l0nDJkiVKw5EjR8Y1PHHihLJzStPZsWOH2bhxY+XjXvtRF02dOlXdB3Ju6L9ly5ac8nsBGhQvXtwsV66cuXjx4rj+0KVLly7m8ePHLcvTZeCULkDjJk2aqDJy2o965tprr1X1zKJFi3JO79mzZ5uxjr3SGtcPHxw1apTSH5oeO3ZM2Tml2YHWTZs2VVrrNpLepk0bc+/evSpt1apVZqyzr3x/4MCBjvdHpgLNSpYsqTRbuHBhgmadO3dOuPbRo0crffX0vn37Kp91q3c3btyo/BC6NWvWTOm2Z88elRe6Va9eXen27LPPOvp0lJgzZ45ZqlQppfWCBQuU1tAU+kPTI0eOKLsxY8aotE6dOsXTdKBlixYtlP867Qc//vijeeONN5oVK1aMnysXgMZlypRRGs+fP1+1EcaOHat079ixo/nTTz9ZlmZC+uHDh63UM+zcudNs2bKlKht9v6S3bt1a/Rv+vXr1arN27drKl59++mnz6NGjljUpSLIy+AfkmPZK1OkcYWxJepCglL7ZA09iY093Ky/ZpNyczoHNfryok1etca+1a9cuKa++ed0j2IdyYvDvNNAYDzRdP3sgSWz0dPg7OiF6Pn0bOnRo3NbpHNjs58k1JADopYnY2LVHo0/Pp2+69sDJPsqBP0ECgPp1Q0e9oSw29vSVK1d6ajxkyJC4xmJrP0auIEE8XR978E5s3NK98qLOv+aaaxzrENkGDx6ck9oDCcLpekBDPUghNno6/LZy5coJ+fQNmurlAPsqVaok2ORy4E+QAKCui1OAT+z0faKpm28PGjQoXgawrVq1qirDqAdS3JAAoK6RPcgnNvZ0PYin55dNAnsIeNnrJGyTJ09OuB+yBQkA6tdiD/wBsZN9qHevv/56Ry1k04N6/fr1cwwUTpo0KSt1ywsSANSvXw/8AdiULl06IfgH36xRo4arbz7zzDNJvgx7+7FzAQkA6vrYA38AdmXLlk0I/iGIV6tWLVedBwwYoAJ79913X1I9g238+PE5W/dmAmfhP7GCIIQQQgghhBBCCCGERAxOtCaEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSERh8I8QQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCE5xOrVq41XX33VOHXqlJVCCCEkyjD4RwghhBBCCCE5xMcff2yMHz/eOHDggJVCCCEkyjD4RwghhBBCCCERB6P9qlWrZkydOtWoX7++UaRIEWPnzp1G03T7nPoAAMpsSURBVKZNjW7duhnHjx+3LAkhhESNs8wY1r8JIYQQQgghhESUfv36GePGjUuY7lu3bl3jww8/NGrXrm2cddZZViohhJAowZF/hBBCCCGEEJID/OMf/zCWL19uVK1aVQX6Bg4caKxdu9aoU6cOA3+EEBJhGPwjhBBCCCGEkIgzZ84co2TJkkabNm3UCMA77rjD+OCDD1Ra165dOe2XEEIiDIN/hBBCCCGEEBJxLr74YqNPnz7G+vXrjXLlyqmPfUyYMMEYMWKEcc899xhFixa1LAkhhEQNrvlHCCGEEEIIITnE6NGjjeeff9547733uNYfIYTkAAz+EUIIIYQQQgghhBASUTjtlxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSERh8I8QQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwgpcFauXGm8/PLL1l/uBLUjeUP0NU3TSiGEEJItrFq1ynjllVeMU6dOWSmEEEIKms8//9wYN26cceLECSvFmaB2JBnR7vjx41YKyQtnxTp9BdLrQwdz6dKl1l+GUaNGDaNVq1bGxRdfbJx99tlW6hns9jpNmjQxHn30UU8bnWrVqhmPP/54wnl+/PFHY968eca0adOML7/80mjRooVxyy23GL/97W8df09Ye2H27Nkqj/xmQohhDB8+3JgzZ44xdepU45xzzrFSkwlqR/LGiBEjVB1FfQkhJPsYNWqUqsPfeecd4/zzz7dSCSGEFCRjx441Zs2aZbzxxhtGhQoVjLPOOsvak4jYvf7660bFihVd7Ugyzz33nNLun//8p1GpUiVql1cQ/Mtvtm/fbtarVw9BxqStfPny5j/+8Q/L8jRe9tjatm1r7tixQ/3fab99w7FwTOHtt99W53WyRfqKFSssy9OEtRcOHToU/41edrnEsGHDkjTENmPGDMvCm6D5u3fvnmRj94Ook6rWAHrVr19f5YOmTvTo0SPpHNhwfh34f+yBaE6fPl39Btwba9asUcfHsX/++edQdtnC8OHDzdgDKkkfXF8Q9DLo1q2b5/UHsbXr265du6zW1ws37adNm+Z7nXnJizq/ffv2Kh/q/GXLlll7ogk0KlKkSCiNdPzyw58bNmyYtF/f4OenTp2yjhhNRowY4ajTu+++66sz8hYtWjRwXmjeqFEj5cNdu3Y1T548ae3JXUaOHOmo4dSpUwP7HtqsjRs3jut64sQJa88Zgp5n5cqVZpUqVVQ66vBrrrnG/Prrr9Xx3Y6dzUCXYsWKJekyZcqUQPoHzR/rVJolSpRIssPWpUsX8/jx45ZldBk1apRZvHjxpOufPHlyoLrALz/ug6ZNmzo+W2WD1seOHbOOmB24XfekSZN8dRs9erSj3+l5oVuzZs08devcubN59OhRZR9VxowZY5YsWTLp2t95553A9R60bNGihXqmdurUyTxy5Ii15zSrVq0ya9SokaR1q1atzO+//z7hubl69WqzZs2a5sSJE1VdfN1115mff/65Oj78+Keffkqww+/0sssExo4da5YqVSrh2rGNHz8+cB24c+dOs2XLlkrjjh07mocPH7b2JIJzlS5d2vNc0K527drmhAkTlHbXX3+9KiMcHz7vdmziToEG/9CJR+cI4P96UA0FKjjZO4F969ati284Ho71l7/8JSFdPwbOAxucF41ifR8e/JdddllC0CKsvQ462ch35ZVXqmO42eUKooderlLWQQJzQfNL0MupHP18Kir4abVt2zaV5oXoKJtT8A+64gGpa43zIJCE8y9fvtxKPY1ToNDp9wS1y3Qk0IZyOHjwoEoTfYJcjz0A5RX8C2MLfe0Nm2zU1wtoX7FixSTtGzRooK71u+++U2lO6HkPHDig0oLknTlzpmrsXHHFFcr/oxz8QwACGrVp0yaURoJbfgT7kH/r1q0qzQ3ResiQIZEO/kGnSpUqKZ3279+v0oLq5JYXwT3k/fbbb1WaYA8UMvh3WsPKlSsrDfft26fSJJAHDbds2eIbgLUH9ZwCdDgPAnpBz9O7d++kgHDdunUD/Z5sQtflhx9+UGnQpUmTJkqXzZs3e14v8letWjVQfgn+IVAV5TrFDXSooVXr1q3NvXv3qjRohWAdtNq0aZOn1shfrVq1POefPXu2CuwMHDgwqwLY+nXv2bNHpeG6EazDdW/cuNH1ulPJK4huzz77bKQD1NAKQTlotXv3bqULtGrevLnSav369b5a2YOHTsE/2KDelePhHBIsfOaZZ5IC0/37908K/NapUyfp99x7772OdohT+P3uggKBtlq1aqlA565du+LXj0AbNF67dq3vb7UHD92CfxLUw7kQLMRxJWgo55J6+L777ksKkEM7DFzIxbo6VQot+CdIgEEPLHjZeyEBHj0QoSPHhQ1sncD54OggrL0dXBM6gGhQ5OV6oobogY61jl+5CUHye/mOW/4okqrWyIegFeyhqYwKs4MgEvS2B43kvnYa3SbHxv6hQ4daqckEtctkoA/KwR4Eha4IvuG63B6kcv3QUC8DJ/swtoJdX78HerYB7XF99gCcBI28rjkveaE7Al8IusL/nfJHiZ49e8avUddCD8p5+VSQ/G6NOtTtGGGJuscvSJjt9OrVS+m0dOnSJJ0QUPLSyS/v4MGD43klUIgRgajPESCEL+d68A9BNgSplyxZkqAh2nUYTQYNvTSS4CFG6UFXdCqhqz24IedZvHhx4PNIYAx1+KBBgyJZVn369HHVBR1pv+uW/IsWLfLNj7RcDv717dtX1QHQSr9+BJegi19QTvIvXLgwdH7U6RgNhbaLX5Aw0/C6br+gXCp5AXTDSCjoFiRQmM0gyIa6dMGCBQlazZkzR40ecwrM6UjwEKP00G6QUXf24J8TMnIPgUf76D8g+9Gu9/odut2AAQMyboQrApTQeP78+Qn1KjQuW7as+s1eo0sleIhRetDYa3QeAnp4fs2bNy/hXHPnzlXnevrppxPOJcFCaGffR8JR6B/8aNOmjRHrHBuxRpFaVy8/iXXAjVjlaLRt21atN+gE1u+LOaP6d1h7nR07dhiffvqpcdFFF6l1Aa+++mrjgw8+MD7++GPLIrfQ9WjYsKGVeprq1asrH8BCnm4Ezb9z507jwIEDKs2+FuNdd91l7N27V/lalElVa4C1OHfv3m3ceOONVoo70Bu628F5cD4h1uE0Yp16I9ZpNx566CHj9ttvN2KVvFqzoUePHvGPTgS1y3SClMMXX3xhpSQjZXDTTTdZKe6EsdX1ffDBB+P6Iq179+5Zo68X0D7WQDQuvPBCo1GjRlbqabAGrNc9oOe1l5tX3rfffltpF+vgRH4dEvFt0Ui/Xt233XwpaH431q9fb8QagsZVV12lyiSqiE6xBnRoncWPvfJi/WLJi3pq165dai3jqPtvUPBcg/4XXHBBkoZSF3j5OYCuOM6tt96q6lgnsB9lhfOgvrKfp0KFCgnnmT17tlGiRAmjXbt2RqyzZtxxxx3G+++/r9K6detmxDpSyi7b0XVx0x8+HOuIW6mJBNHVK38uIVq1aNFCaa37ahitkR9a2/P7ab1hwwZVp19++eXKPlvqIFz3Z5995qnbV1995VhH+OWFZsjr5Z/ZqltYxL+aNWuWdC9XrVo1rrOXVmhvbN261bjzzjuNYsWKWampgbZzmTJljNatW6v+CY790UcfGWXLljU6d+5sHDlyJG6HNN0O8QC7XWEi/igaO/ny119/7flxKbQ3tmzZYtx9991G8eLFrdRk0NbAuZo2bZp0LpQnfF/O9d5776n+PLTr2rWr0u6TTz5RaZ06dTJ++uknKycJyhm1c4CJEyeq/1933XVJgSEnwtrrSOBQ8iLwBOSYuQYqFbegHIKn5513nmcAONX8OmvWrLH+FU2CanXo0CErNe88/PDD6iEM/96+fbtKQ3DpySefNG644QYVlBIuvfRSo2/fvsbmzZvVwxK/ER+aGDZsmMovD3PY9evXz9i0aZOnXaaTTp9NJ7q++F2i7/Dhw9UDOwqI9miwuGkPf3W6B/S89o+guOVduXKlMWjQIOO+++5T+aIOGm5u+lauXDmukZtv++XHhwu88o8ePVo18vFyIKqdHSA6OdUhorNbHYK8+/fvd80LjQuj/skm/OoRPz8NStD6Ss5zySWXGH369FFBcPyGgwcPGpMmTYrX4XpHKpuBLvDhvOofVtdcRuoLdLzd6gu8UHDTSuoqt/zQ2is/FvJH0PqBBx5IW2CmINB1s7cXdN2c2hp+ef00A3/729/UV2N///vfewZbsh27f+nPfV0r6Oz1MiavoJ7Ys2ePqjdQVnJ+vNxBXbx27Vr18Q7UxW+99Zaqizt27BgvE9j17t1b9T8rVaqk7P71r3+pj+7pdoXJ999/H9dYv0aA36zXAalqLOVp1xNIeaL+RnkiaAvtvvnmG2WPtDfffNMYOXKkCv5F2e/zi0JvIXz44YdqNJZTgA03B95w4mufss2fP9/aGw44Kxq6iFxjtKEfYe3tIMin50WHu169euotMm6eXAVvBezgxq9bt671lzd++aVB56QzOkEok1whVa2DgOAePruOQBL0RQWO0WcYfYCvMekVOh4oL730Uvw+Rx5U4vgStz7CEHYvvvii+q3AzS5bwKgDO+kuhzDY9UUwFvo+9thjSl+9zLKdVO6BMHkRjIJ9//79I6WfH7hm+/WG8W3cG07569SpY/2VzKpVq1S7AOe2jwCIKm46QWe/6/fSOBe0SwdOGuI5lm4Ng54H7ZwXXnhBdcYA6nC0l/EyDs/fqAT/BOhiv6Yw+mNkVZj8GElZtGhRtQ/b4MGDIzOa0o9Utc5LfoxcQ53evHnzpFFA2UJYH9NBXrtNkLxR0C0sTjrLszA/rx8vyFEH3HbbbQnBadTF+Hov+pYoK4x6Q12MWTU333xz3FbsMKINiB2C3bpdJgB/ctK4du3aadcY50JdqyO+L+dCMHDMmDEquApEu/vvv19px+BfePLvTnFh3bp16m0lNnTmn3jiCRUUw7BXO0uXLjXuuece4/rrr49vuPEwyiKTQdAJwSd9uh863Jj6i9GAGBWYayCQiiCvFxLkcSJoflQaqBCgM972ojKWDW/L/Y4RBVLVOiwIGGG6aBhw72O6AsrIi6B2mUhBl0NeQMAPdXE26uuFvKX1wk175A1TbrNmzTLeeOMNNQoNDaRcQHzb6+2vl28HvTfQwLODKTUoWwQ6oq53EJ0keG8nSBlJ0Ig4E6QuEA1TGQkRpL5yO88jjzyiRp3UqlXLM1CQjYj+QXzYySasruhjHDt2TP0bG+p2TKX+4x//aFxzzTXGvn37rFzRI11a5yU/pj9i2RIEQvDyPpsQ3bxwu+5UNcfUR+iGUX/yIiCqoF/tp5UEhdINpuyijYdlRrAEmD1YJSDg99///teoX7++Z10sdg0aNMioOjvIPQyNMWIvVVCeQc5l933UEZgObJ8mT8JRoMphzTsEYFBo2DDc9bLLLlPTFRAcs4O19lasWKEChrJhzQh9KmEmYp/yK+TC1F9M+ZRgm2xY3yDIqDu8uXHrzIXJj4AR/Ea3hy/NmzcvUiP/8kvrMCAQj7cx+C3we1TS+A2vv/66WlOuMANbBYWsoaeXA4KhCKgVVDnkKuicOWmP54m8YXXDTfsw5YYGDDrfXbp0USNucP4oAX31ETC6vtDI63q9fDtoHXXuuedaf50GemPEE9Z+QSM8KnpDZ7z513XG6GmMFvDTCW/InXQWjb00Ql67xrkIRs9g9IBdf0x1CqI/NPTS2Q/UOX71VTrOk6lAfwTZdP2xtpPo73XNXrqkqiuCgQg4XHvttWrNRQRZvdYUywYwg6pkyZJxnbFBa+iUDq3D5sfUPsxE+M1vfuMZWClMoFmpUqXU75YNz/zjx48Hai+46SZ57ek6bnlFNwwqyVTd8gICbaVLl47rjA1alytXzlcrjEyDVukEOmMZI7R5Xn75ZV8fzwZk/UFdYwzAQgDZ7/qgcToC9NJG9zuXW31DUqNAg38I9E2YMEE96LGhIb9kyRLPYB6ChIiOy4bGcCrgQY434kEJa4/pwqNGjVKVFDql+pRlVCJIj/LUX5nerKNPn3NaKB8BIozyCELQ/PApeauA7T//+Y96W4HybNy4sWWV3eS31n7A1//whz+oyhnnQmAfYLov1udDsB/TfKOOWznIA8vpwwXpLIdcBj6Ht6w66boHguTFRz4wMhVvhfUgJF5AoP755S9/mdUfUYG+dt/GtC4BGtmvLYxvO30sAfkx2sGJ8ePHK707dOiQ8GIt2xGd9UauvQ5x09nPt7w09subKzjpr0/BddIQz790a1hQ58k0pB730t8edAuji9OHJoLmRz2D4B/WZgvTF8hU0Da2a61PpUxV67D50SfE7AO8LE534CZdOGlmn96cio8hr93GL+8777yjdMNHfzJVt7yAGXPQWtdWn4bqpLM8C+3pqYI+O/wS/8eABgRidR/IVtw0lgCy04dToDFG4qVbY5zL/gER8f10n4uc4UzJFwCooPAmDSPisKUayAsDHuB4Ew6CfPAhrL2A0YlYkwhBJkypk+nK2LDIPtIxKhALgkYRRPPROcMDSzZ0hFHWeFuAxhNubB1UrAjMQW+3Dl2q+QFGXKKBj2BNFEhV61RHnImv480jfosO3iLh4YKgNx4aUQbXjkaYXg5YziAdPku8gfbwQ7v2SIf2mMbgpj3eujvdA1JuyGv3Xb+8TuALdThWNuKkr7wFd9NXFnKGRm6+LQs6u+V3WuQfdqhP0ADHIs96wzXbgZ4yqshJZ6c6RHR2q0OgMd7ku+WFxqx/ToN7Hu08XX+82II+XvWIk5/mBb3OcTqP3/2U7eD6MQ1O1/+pp55S+sOH86p/ruvqBDTBtDlda0xrFq0xMMGtvkB95KaV/tEFp/zQ2p4fdviSJ6as46MHmTp6DZpJQETXDKO1pZ7FddvbC7puTu0Fv7xOmgHRrWbNmkq3TFovLlWgNQJ8CAiJ1n/+85+NGjVqJPgX0gVdK+icjgDd4cOHVZ8dx3733XfV15SjMroSGuPFra7x//7v/yp/Eo3hj7rG+BiIXgekqrHUF6iH7eeS8sTvTFd5kkSi03oOgEy7ff7555Vz+xHWHsgHTDDyCZ0m+4aRIgCdGPsDMsqgwkCQCMEi6KAjmoneTqSaH9NTMbXKKVAVNYJohU+l5yfSsM7lzqVXOWDdMikHPtjSD7TH+ixYEBtBFR1ZM87tHtDzOpWbnhcvePQOgWz40humNCxbtkwF6HEfRAnxbdFIb7jpdYybb3vld7s3sL4RRhOjbNBhzwVEJzTUnXSCL+LjBE6BUPFjt7zQ2C0vOQ06H9Afo5nsGmKdMi/9w4DzoKxwHtRX9vNgXa9cLCtdFzf9b7/9dtdOeRBdvfIDtNMxTQ5BmqjV4zqiFQIv0BrPNSGM1shvnx7tpjU+4Ig6HYEV1OnZ2BbCdV955ZWOuuGZBd2wVr2Tbn55oZn9AxNAdPv1r3+dtbqFRfwLgWv7vYwlnaDVrbfempZAKAJ/CKqin46vKUNnrzoiKog/isa6P0JjBADT9YENBP9wLrz0cTvXLbfcwo955BexGyjf2b59u1mvXj2zbdu25qFDh6xUd8LaCzNmzEBtYA4bNsxKSQTHwjFh43bst99+2/zLX/6i/p1X+/Lly5srVqxQaXbk2rxsooqUj37tKCukde/eXf0tOKUHyS9lAFtBbKA79M8FUtVaB5rVr18/aT+0bteuXTxvrPJW6WKP9OnTp6u0XAXlEGuYqXJYvny5Shs+fLhK69atW1wzpzQdvQyc9uuEsY0yM2fOjGu/bNkylRZUe+SNdbR987oB2woVKsTzRhG7RtAE1400aHTq1CnL8rQe9vQw+VHXtG/fXmm6dOlSX/2jBHSKdTyUTnLtI0aMUDp17drVPHnypLJzSnPLizTdzg7qkEaNGqlycLPJFWbNmmXGOpRKwyVLligNR44cGdfwxIkTys4pzc6OHTvMxo0bK13tNvp5Fi9e7HqeXAO6xDqAZrly5RJ0gVZdunQxjx8/blmeLgN7up5/0aJFrvlRNk2aNDHbtGlj/vDDDypt1apVZtWqVVW9P2jQoMiXwezZs80SJUrEtUIdPGrUKKUftDp27JhlaTqm6/kXLlzomR91+nXXXWdWrFgxbput4LpLliyZcN2jR49WWnTu3Dl+3U5pfnmPHj2q7ATodv311yvdPvvss6zWLSxz5swxS5curbRasGCBuvYxY8Yo/Tp16mQeOXJE2Tml2cH93qJFC+WXdpv+/fsrn0Ufxr7VqVPHXL9+vapHogg0LlOmjNJ4/vz56vk/duxYs1SpUmbHjh3Nw4cPW5ama7qwc+dOs2XLlsqPnfbPnTvXLFu2rDrXvHnz4udCGbsdk6SHjA7+oRGEm9C+IdjmdBwJeCCY4cbatWvVsWGH499zzz3qmPg//ka6HuQIY48gC9L8rlOCLV6/M6pIGembrrcgdvZ9QfLjb7tNUN+LEmG0RuNW3wdfRkfbnl828V1oKgFAfcN9IMGuXEf01fVB509vPIiNnu5XBkOHDs2TbS6B4Ief9hKEckv3yutGLgT/gJtG9g6JrrG+L2j+lStXqs6O075cADohCKTrZA/eiY1buldeAI0rVaqUYKdvgwcPzkntgQTmdD3sATmxsadD18qVKyfk1TfoKmUR5Dy5iATwdF30wJ0gdvZ9QfP36dMn6V7BNnny5JzxfQng6ddvD9wBsbPvC5ofgdVq1ao57stGJIinX7ce5ANi45Zuz2sP/AHoVr16daWb0/6oIwFAXSt7kE9s7OnQrkaNGkltQtmeeeYZFfi/8cYbHesB2WAXBZ91QwKA+jU7BeMkeKfvW716tVmrVi1XjZ9++ukEv5Vj6DYM/OU/Z+E/MbHzFUyZxdQJfL0Pc+f9pgGKPdbGc6JevXrqoxmY1qITa+SqLy4OGzZMrX3mBobx/3//3/+nvjas06hRI+Ovf/2rGu6rE9Q+1uFT6035nR9TULGIKBbdDKIHIYQQQgghhBBCCCF5oUCCf5kM1iZDcA9fEg5CWHtCCCGEEEIIIYQQQgqLnA/+EUIIIYQQQgghhBASVfiZN0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSERh8I8QQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEJIvrFy50nj55Zetv7wJY0vCIdqapmmlkIKC2hNCUmXVqlXGK6+8Yvz8889Wijtie+rUKSuFpIPVq1cbr776KnUlGYn458mTJ60UZ4LaEWc+//xzY9y4ccaJEyesFJIfiM7Hjx+3UpwJakcSYfCPEJIvfPjhh8b48eONQ4cOWSnuhLEl4fjoo4+Utj/++KOVQgoKaD9hwgT6NSEkz3z88ceqHjl48KCV4k4YWxIc6Irn6IEDB6wUQjKHTz75RN33fv6p2/GlZHhEv/3791O/fGTevHnGO++8Y+zbt89T56B2JJECCf5h9EOFChWMs846y+jRo4eVegZ0Stu1a6c26aDqeexb/fr1jXXr1il7p/36BtsdO3aoY4KZM2cGsgNhbIFuj3/nMsOHD0/QLKwuQfK7lQ82Jz+LKqlqDeDPDRo0UPmctMP9WLFixaRz4B7UAxtiN2PGDKNx48YqTY6N4+qVcxjbbGDEiBFGkSJFkjTC9QVBL4Pu3bs7Xn9eyqFRo0bKJpu19cNL+yDXCm0aNmyo8rhpD9zOM3369HgeaF+pUqW49mDnzp3q+F7HzmRw3UWLFvW8bi/C5kc74JprrlFaox2wfPnyrNQtLCNHjnTUadq0ab7XHyQv/Bx1rZMPy9atW7ecHd00atQoo1ixYkmavPvuu4FG3eE+b9KkidIXOjqNrsHIvKpVqyado02bNqpDKYgdzi3PBZQfjm8/tpOt/Ba335GJQP/ixYsn6IJt6tSpgfQHuO6mTZuqMujatavjCJ2g58EoqWrVqql0tPthI8eHrlEc/TN69GijRIkSSdpMmTIlUL0QJj+0bNasWbysMn30jtu1TZ48OXCdiWtu3ry5uuYuXbo4XjP8rkaNGkn1dOvWrY29e/daVmfscP569eopezk+/PPYsWOedi1atFC6i10mMWbMGKNUqVIJ149t4sSJgeozXN8FF1ygnomdO3c2jh49au1JZOzYsb7nweiyWrVqGZMmTTLq1q0b169ly5ZKP7djZzrPPfecUbp06aRrRzAt6DNj165dxoUXXqh07tSpk/HTTz9ZexL53e9+Z5QsWTLhPOXLlzfmz58fv3egc506ddT58X/R+aKLLlL3ihw7qB3xINYozHdWrFhhxgoZrU/1f/ytE+u0mm3btlUb/g0kz7Bhw9TffsgxYhWbuX37dis1ERzL6TfEOmkqXT9XGFsh1rFT+7Dp15JrSNnpGqBMUDZe5SMEzS9lgf/nKqlqDcTXZYMf24ENznHw4EErxTR79Oih7O33gqTrG37Ltm3bLIszhLHNZFAOFSpUSNAI2sc6DIGuZ/jw4WbsYRjXINZwM2OdEGvvGWCHY8rx5BzIM3To0IQ80FY/JrZs1NYPaF+xYsUk7WOdYHW93333nUpzI6j2+nkOHDig0tzO46a932/JRFauXKmuu02bNr7X7URe8s+cOdOMNejMK664Qt1Xy5YtcyyTKAGdKlWqpHTav3+/SoNODRs2VDpt3bpVpTnhlrdRo0Yq77fffqvSvIDmsQa8OXjwYDPWGLdScwdoWLlyZaXhvn37VNqOHTsSNPTywZEjRyr95H6PdQrNEydOWHvPALv27dvHzwF69+6t/B3axzpdVuqZdL0eiXU+zS1btiT9ljC2mQj0r1KlitL/hx9+UGnQv0mTJkr/zZs3+14HtC1WrFj8+mMdQfP48ePW3tPgPFWrVg18nj59+iSUq+ga5PdkG6tWrVLatG7d2ty7d69KgzZNmzZV2mzatMnzmpG/WrVqgfKPGjXKLF68eEJZHTt2TO3LRPRr27Nnj0rDtTVr1kxd28aNG339YfTo0WaJEiXi19y5c2fHa4Yd6h05ppwHbYpnn302waf79euX4PPY4J/23xPULhOA1jVq1FBa7969O65B8+bNldYbNmzw/M1jxowxS5YsGb/OTp06mUeOHLH2nkE/z/fffx8/T4sWLdR51q9fHz9P//79E/wVW506dRJssonVq1ebtWrVMlu1amXu2rUrfu0XXHCBuvZ169b5XtfYsWPNUqVKxfXo2LGjefjwYWvvGWBXunRp1/069913X8I9IjqvXbs2oV3iZrdmzZqcbL+EpUCDf/fcc4/6vz24IIE7bBLAkDxOQTYn5BhwWjR67cjx3PbrhLEVYAd7XBs25MdxchG36/cKnOoEzc/gX+paIx8617CHDyOQhGMGQfLC3v6QkH1hfgNsEcDKRhDsQTksX77cSjkNdEWDzR6Y05Hrnz59ekIZBG1QSH49+CXYtQ16zGwC2uMaESDSQTAjiPYITIn2CEi5Bf+8zoNOt/08cuxs175nz57x69avQa57yJAhntcWNj/KAQEvlAN0g4a5EPzr1auX0mnp0qVJOiH4AJ3cGrV+ef0Cemg/XXPNNaruCRIojCIInsHXlixZkqDhrFmzVKfZHpjTkcDh1KlT1cuVxo0bK/91Cv45IYEvp4Ch7EM94vUbgG47aNAgT9tMA0E26L948eIk/dHp9rseufYpU6aoFwoI5kFPe/BPzrNo0SLX89jLQIJieJ447Y8Kffv2VS8RoI1eX8yePVt1tAcOHOh57ZJ/4cKFnvklkDZ58mRVVggOoqwyOfjndW0INPlpY79mBPPCXDPyV69ePSH4KMg+p+CgTlC7wgaBNtSnCxYsSNB6zpw5Koj0zDPPuOqGa0RAb+LEieqFGQJ5CCw7Bf/CngcBs5o1ayr9vH5DNnDvvfeqa58/f35CvYprL1OmjDlgwADz6NGjVmoyEjycMGGC0rlly5YqmG0P7okdArB+gT8BeWrXrq10fvrpp11/R1A7kkyBrvl32WWXGTfccIPx+uuvF/i0WKwphuHS999/v5oe4UUYWwHTkjZu3GjcddddakN+HCfX2LFjh/Hpp5+q4beY5qYTe+ioYb4YsutGqvlziXRodfHFFxu7d+82brzxRislNXBfxzr0Rvv27Y2HHnrIuP32243Yw0QN8e5hm27qZDt37lxH20wmSDl88cUXVkoyUgY33XSTlZI6urYPPvhgXFukdc/SqadOQPtYw01NO5AptgKma1WoUMHzHoD233//va/2+nnsZYzz6PdarBOppkBA+wceeCCuPdKyTXvxbblu3JuC7ttu15SX/FhXK9YpN2KdE+WvuYDohGlEYXUOkvfLL7/09Lv169erqaNXXnml8udcA1OGoCGmidk1lPvby89R9+MYt956a9p8dvbs2WpqKpZ0iHXUjDvuuMP497//raYddrNN5YUt0nXb999/39E2E4F2qF+99IcPo15wA2WAe+G2225Tda0T+nnwvLCfB88L/V6Brpiq1qZNG6N///6qLoeuSOvqMqU4WxFtMBUUZaD7cZAy0PNDW3t+0Rb58TzYtm2b0tOtrDIJXNtnn32WZ21Aflwz2taYsgr/7N27t7rv0e/EVE5MfzxmTecNapcJiB9hOrj9HkV/HFp/9dVXrlpD561btxp33nmnWsLBDSlTnMde59jPg/ZbmTJl1LRr9E2gH9ZzLlu2rOeU4kxFv3a3e/Xrr7/2nMqO9saWLVuMu+++Wz2n3MCafHj+IJ6CetOL9957zzj77LOVzqhfUYZYYxFp+pTioHbEnfS0UkLwyCOPqJsKa24U1AL0OA8qP5wXlZ8XYWx1sD5AvXr1jEsvvVRt+DeOU1DXmCmgUsFCsuh04EbUqVKlinHeeeepB6CbLqnmzyUKWyusf7Jnzx5V8cqDE77ft29fY/Pmzephid+H9XKGDRumguL6Axa2/fr1MzZt2uRrm8kUdjng2HjZgIe2nF/XFmmiLdaHxMM6Koj2+rULov327dtT1l4/zznnnGOlnkY/z6FDh4xLLrlE3QOiPRbex3pH8Ots0x7rubjpW7lyZV99w+ZHAGrgwIEqgIE82VIHpIro5FSHiE5udYhf3vPPP9+3/sH6Sujk4CVMuoJX2URB1SNuYN0pvIRAp1L0l3oEgVmUIeoRrDkldbheTrDt06dPgi3apE62mQj0x3qHbvrjmtJdjwcpZ9F1w4YNcV2xzhR0veeee7IicBUU1CMoAwQ+3OoRBFfdykDqIbf80NYrfyaja2N//uva4PmfX8Av0d7W9cXLS/gn1sBHnxX+iZdn4p8S/ApqlwnY/UhvA9j9yOuFlh/2MrWfRy9TvFiAfmvXrlVraSPtrbfeUvp17Ngxo/QLAp41orH92itVqpQ2jQECqChHaOrXnoPOCE5/8803yh46v/nmm2rNaAT1JMio26HeFjuse4zy8ApGktMUeIsAldCf/vQn44MPPlBfz/LjiSeeUA4jGyLSK1eutPYGA46BjhgcGo7iRRhbATcJ3hpfffXV6mbChn+jI4PKNhfBWwE7qGTq1q1r/eVNmPwYtaP7CCrkXCJVrYOC+w4PPtH5tddeUwENfdQUfP+ll16KN05wL+Geevzxx5NGF8L2xRdfVL8VeNlmAxhNYCc/ysEOOoRAD5jatUUwFto+9thjSluxiwpu9wAWA04nQe41N7/OZu1x3fbfHca3g+bHCwXYIviXi0Eo1CFuOvn5jVte3ANeedFOwWhV6G4fAZFrOGmIZ1kQ/cMAzVFP4JjYXn31VRX0xrNU/B7tzxdeeEF1QgHqcHTaH3744QQ74GSLOsfJNpOB/vbfCv39fDgsGMEV5DzQ9fnnn1e6Ij1bdQ1DqmVQUGVYGAT1m/wAL28xEgsjByXYBP/829/+ZpQrVy7un6gj8BLn5ptvjgeng9plEtDa/rvkeZbO+86pTO3nQSAKL2gQONX1w6wa6JdtwT9BPjyjk06NDx8+rILWNWvWNJ566qmkD6sMGDAgYdQpdMaLSOlnYmQhdP7973+vdJagnm4HYIdgJkYX3nLLLQz+BSB9d1AIMEwWI+PwAEXgLAwY4YK32HkBDTg4dhDC2OINABwPoxqFXJ36K6OQvJDOsBNh8qMjjbcSss2wvqqKgDGmv2TjG8YwpKp1WODLePOog6mObm+GEMTDG3O8ZfcjjG2mUdDloIPpva+//roapdyqVSsrNREEnTAiJBu19UPehnsB7dGASAWcJy9lLNpjVFY2Ir7t9fbXy7fD5EcACr6MDknQZ29UCFKHSODBTtC8bvcApi8hP3Q/99xzrdTcIsj9Lfp7+XJQ8OIbSz3oeE0rRtsSo07wxUl0irwIY5spiP5e2ooPp6J/kOeF23nQX4GutWvXzhpdw5BqGYi2+V2GhUHQ+iG/rg2zyF6PPRsxqATtPKdgHervNWvW+L6oCGpXWCAm4OdHEhRKBZzHz9+dzoOAH0ac1be+/p2NBLlXJaCWDjAlFxsGfWEK8OrVq1U9+v/+3/9TX6h3Wj4BS+Zg6rF9mr0dsbNPXybeFIpSeOOJCC3WyEPgzAuMLIKD6lteRwWF6YAHtUWACRUzhqHCSQVU0G3btlVvDcMGOLMZdHLxdsQLr8BqKvnhFygz6J4Loy5T1TosCNDp9yHuTTRIsLZZ0PsqihR0OQioV9DRw7FRDrkWMAEIaGI0uBfQJ9WgBs5TGGVc2IhvezVyva47aH48R+HLWH8oiiNT/QhSh+BtvJPOQfM63QOoQ/7+978b//M//6PaLLmmuxDk/hb906ERfB2dIHmWYrrS22+/bVxzzTVqKlquIfp7aSs+nIr+QZ4X6ThPJoP+CtbewvXJhnWzoEsqZSDa5jV/JhO0fsiPa8NUdQxoQD2PEcIYvRdlEB/w8yMEjqB1KuA8fv6ejvNkIkHuVVw7ZkCmA7QvEKBD8BqBa8wymD59unpBNW3atEitnZotFFqYFNN6Cio4hgYbOhiIYqMi9SKMLUCACYEmRLSlYYgN/0YaApz4GEiu4bTIPgJECKoGIa/5MQT/uuuuU290MCIiF0hV67yCexgjLINO4Y86GLlhJ7/KAXXmb37zG9VRxNpOeJjnMm73AN7Gp5PCutcKG1w3ghQ6Ya7bLz8CH3hWvvHGG6pxKM9RjJzECKlf/vKXaqFtrwXVo4DT6C/RyZ5uxy0v7gG3vFj3CSOuO3TooNosuY6ThghMB9E/FbC2H56lGB2BZ2nU/dwN6G+/dujv5cN5wenjDPlxnkwESy/ZRy3pUx9TLYOCKsPCoKD9Bn1Q9JOxRhvWNIvqqFMnoLX9gxPyPLOXQSo4lWl+nCcTcfpwSn5cu4yg1O8RTN1FcBE+jnNGvd7NNAot+IcgDd5+Bhn9lyp6QMhvGm4YWwAbv+Hg6JznClhbAjc0Am94KOrgJkdQFW+woLMTqebPJQpbKxwXx891CroccA58NRaBP3z9EYuS5yqiPaYxuGmPwGiq2uvnQUNFRz9P1AIo0kBz0lcW5vbSN9X8OvgCII4TRUQnpzpEdHKrQ/zyop5wygtbfMUQI1awmHYuT5kpqHrEDRw3l5+l0B/r6rnpDx9Odz1eGOWcCUADjMJB5x4dbmx//OMflf/JRw7c6hGMlnLTRuoht/zQ1it/JoNrE23sz39dm3Q+/6EhPjKBl18YJfXrX/86J+poux/pQSG7H6USCLWXqf08eplGLeCqf9TDfu36x0BS1RhfQ0Z9yum4mUehlohMjf3LX/6iRg/lJ1gTC0N8saiy0wdDcBO888476t9BbVExYQg9rkFuIH1DGvbhYyDIkwugwnD72IkESrEeohup5pcyQflFvTGdqlapAq3R4cwFrb3wKgdZT0v/InIqQPPbbrvN+M9//mOMGzcupwN/ANpfddVVag0RrMekA+2xrkk67gH9PE5ljPOgjKOG+LZct95IlDrGy7eD5seSAnjLrz8/seErb1jUedmyZWrtxBo1ali5o4XohBGSdp3Ev/Qvwer45YXGTnllDZ4rrrhCNdBzGQREoCFGLdk1xEg8L/3TgTxLMaUPZRG1zqYf0B/1q5f++NBBqh8m0M+D54X9PAi04Pma6nmyEdEGI6FQBvrInyBloOeHtvb80DYdZVgY4NquvPJKV23S7TeoD/AV3vfee099yOdXv/pVzgRQxI8QoLbfo/PmzVNa33rrrSl/ZEPKFOex1znpPE8mol+7/V7FtSMAiA9nlChRwkrNO/ioyNatW40VK1YkjOREfwmzDhBvkQ8qkQIk5vD5TqzQzfLly5vDhg2zUs4g+/BT2rZtax46dCgh3SmPE8iH/PXq1TO3b99upSaCY+E8+rlgizxI6969u2UZzDbIb5TjzJgxw0qJPrhWXDO0gUZAdHDSWE8DQfJLWTj5DOy8yiRKpKq1DjStX79+ko2k4xzLly9PSJNjxh4eKj1XQTnEHl4JGg0fPlyldevWLa6PU5qOXgZO+3v06KHyQ3f7hvsh1oG0LHOHmTNnxrVftmyZSsur9g0aNHDdj/PEGuC+54ka9uvGdeK6kYbrjjXolJ1TGgia34kRI0aYFStWjOeLMtAp1nlUOi1dulRdL64fOnXt2tU8efKksnNKc8uLNN1OwDPzmmuuMStUqBC3z3VmzZplxjp6SsMlS5YoTUaOHBnX8MSJE8rOKU1nx44dZuPGjZVv2/fLPpxj8eLF6hyShnrE7Zi5APQvXry4Wa5cubg20Bpl0qVLF/P48eOW5ekycEoXoGmTJk2Unvb9+nkWLVrkeZ5cY/bs2Waswx/XBnXzqFGjlF7Q5tixY5al6Ziu51+4cKFnfgFl1bRpU1VWTvszBVxbyZIlHa+tc+fOCb999OjRSgd7uoBrbtasmes19+vXT/mjUzuvbt265saNGyNdZ8+ZM8csVaqU0nrBggVKa2gK/aHpkSNHlN2YMWNUWqdOneJpOtC5RYsWyvec9uM8pUuXTjiP3zGjAq69TJky6trnz5+v2ghjx45Vunfs2NH86aefLEszIf3w4cNW6hl27txptmzZUpWNfb/sQ5tl/Pjxqn6dO3euWbZsWbNOnTrm2rVrle6kYCn04B9ARxeVmlsgx74hXQIdAvL5Bf+A23GdfpufLX6302/RkWPYAypRR4JS+mbXQGyctAmSH3/bbbAhby6RitbwT3QA7fllE19HfnRO7PtxvCg3QsLgpJE9KCQ2erpfGQwdOlTZoo5r166do41sYptrIPjhp73Y2LVHcEnPp292PSWQpdvYzxNF3K5bb7SJjT0dBMnvRC4F/wB0QmBJ1wkdRD14JzZu6V55hZUrV5qVKlVSZeC0P1eRAKBdQz0gJzZ6OvSsXLlyQj59Gzx4cFxnp3Ngs58nF5HAnK6LU0BO7PR9KIMqVao4tlOwDRo0KKEMgpwnF5EAnl0be5BK7Oz7guRftWqVWa1aNdeyGjhwYEbeCxIA1H+rU4BP7PR9ftf87LPPKv9DO+/6669Pqsv1TWyjjAQA9evWA39Agnd6oA4616hRw1XnZ555JqG85Bi6TdQDf4IEAPVrtwf+AOwQrNODf6tXrzZr1arlqvOAAQPMo0ePutoy8Fe4nIX/xAqCEEIIIYQQQgghhBASMXJjEQFCCCGEEEIIIYQQQnIQBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCGEEEJIRGHwjxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wixWLlypfHyyy9bf5H8JKjWLJP8RfQ1TdNKcSaoHSGZwqpVq4xXXnnF12eD2hGSiYj/njp1ykohBcnq1auNV199lfoXAKL1yZMnrRTiRxjNqG9qfP7558a4ceOMEydOWCnOBLUjJL9g8I8Qiw8//NAYP3688eOPP1opJL8QrQ8dOmSlOBPUjuSNjz76KJDPB7UjJFMQn/WrO8Tu4MGDVgoh2cPHH39sTJgwgc/IQgL6o/44cOCAlULyC/F1ah2cTz75JK6Z3wsusd2/fz9fhuWBoPqJ3b59+6gzKRTyNfiHjmK7du2Ms846y3OrX7++sWPHDiuXYcycOdPXDiNRKlSoYAwfPlz9LUi6/ZggyHFJ/oLycioDlE1QUFYoM+Tr0aOHlXoG8QH7OeCL9uCF2OL8jRs3VmlyfKdjZxPp0rpBgwYqn10PfZ/bhjzycIPWFStWNGbMmJGgNY6RF7tsYcSIEUaRIkWStMH1BUHXuXv37r7XDx9v3769sodvr1ixwtpzGl3fRo0aKTu/cvCyy2TctJ8+fbrv7w+Tt2fPno62w4YNywqd8go0Klq0aNJ1B9FXgE81bNhQ5YN///zzz9aeZODb11xzjdIavr1s2bKE82AUVOXKldX55Zg4PvxXP7aT3c6dO5PsCpqRI0c66jlt2jRfPYPmlWu327Vt25adahdGjRplFCtWLEmzd999N7CvwL+aNGmifLdbt25Jo2tQLlWrVk06R5s2bVRnUkdscX55NsDPcXynY2c70L948eJJ2kydOjWU/k2bNlX6d+3a1XPUjZ8tRkhVq1ZNnV/aopIH+mfziJ7Ro0cbJUqUSNJ6ypQpgUc3QotmzZrF9Tt+/Li15wxu55k8eXLCeaB19erV1fl1rXF8aO107MIg6PW4gWtq3ry50qxLly7GsWPHrD1nmDNnjlGqVKmkc2DT80CzGjVqqHPXq1dPHRPHb9GihSoP/dhOtrt27XK0zQTGjh3rqMHEiRMD13vQ4oILLlDPy86dOxtHjx619pwGmtSsWVNpoZ+jdevWxu7duxOepxjFV6tWLWPSpElG3bp141q3bNlS6XfkyJEEO/xOsYPOdrtM4LnnnjNKly6dcO3YELAMUreFyf+73/3OKFmyZJLtgAEDMs73IkXMiQuMQ4cOmbEGphmrYMzt27dbqYnEOku4q8zy5cubsU6rlWqasQ6oSsd+gH2wkb8Bjolj2/OCoMcl+YeUGXwAvgCkzLx8QkfKUbZYR83acwbY6MeTc7iVM46hHxNb0N+TqfhpvW3bNpXmRRCt3cB9FavAk/Tu0aNHwjGxOf2eoHaZDsqhQoUKqhwOHjyo0lAOsUZsoOsZPny40lE0iDV2zVhnx9rrjGh/5ZVXKh9Yvny5tecM0Fc/rpu+Qe0yEWhfsWLFJO1jnWV1Dd99951Kc0LPe+DAAZXmlnfmzJlmrCFnDh06NF42Ygv9ly1bptKixsqVK5VGbdq08dXIDfg3tBPfgn/HOkrW3mRE6yuuuELdV0uXLk26H3r27Onos1u3brUsThPUrqCAnpUqVVJ67t+/X6VBz4YNG/r+Lre8jRo1Unm//fZblQZGjBihykjSxA5aDB482FP/XATaVq5cWWm7b98+lbZjxw6zcePGStstW7b41skjR440Yx3NuJ/FOntmrBNk7T0NbFDWcjw5h5RLrGNrWZ6md+/eCfcOtlinMtDvySagf5UqVZT+P/zwg0qDNk2aNFH6b968OZD+xYoVi+vUpUsX8/jx49beREaNGhXItk+fPgllig36B/k9mcqqVavMqlWrmq1btzb37t2r0qB106ZNldabNm3yvTboV7x48QT9Yp14a+9pcJ5q1aoFPk/fvn0dtQ7yewoC/Xr27Nmj0nA9zZo1U9ezceNGz985evRos0SJEvFr69y5s3n06FFr7xlmz55tlixZ0pw0aVJSfWCnX79+CX4smjn9FjfbDRs2ZIS+AnSuUaOG0nn37t3qt0Hn5s2bK53Xr1/v+3vHjBmjNJTr7NSpk3nkyBFr72lg06FDB/P777+PH69///7Kr5955pkkf5Z9un516tRJ+j333nuvo926desyRufVq1ebtWrVMlu1amXu2rUrrnHLli2VxmvXrvX8rXr+nTt3Klv8X88vbYy5c+eaZcuWNZ9++um4v4st2nfz5s3z9XOSNzIq+CcBC7f9OmIrwQU5Nm4mdH51whyX5B8IHqEcUB46QQOwUo6wRzmiPIMGpCQvfESCYTqyP8jvyAbSoTUqX9EawaqgWkPfdu3aqfJxChLJsfE7EDBxI6hdJoPgGcrBHoCDrujU6QEjO3L906dPTygDrwevbocyRn6n4B+w6+v3O/zsMg1oj99tD745BevshMkLW2huD3ZJ4HbatGlZo1kYEDwTjfTrE42GDBnied0SPIQ+qCcQkPIK/sG3ERyBDfRHXqfgH5BgGHwWv8PtmEHtCoJevXopPe3XBD3R8fX6fX55/YJ6ooMePCSnQZANvrZkyZIEbWfNmqU6zE6BOR1oi+Dh1KlTlZ8joAcftgf/nEBeCXxJ4FFH9sN/Bw0aFMmOEoJs0H/x4sVJ+qMj7Xfd0AgBrSlTpqg6GkFDBF+dAnphbIEEy1DP43cEKdNMBkE21AOLFi1KqC8QdEJwauDAgZ7XKEGwyZMnK/0QzIN+9mCJnGfhwoVJ50Fgxuk8cmxo7fc7Chq/63n22Wc9fUjXDAFDaJZq8A/g2NWrV1eaef0GEMa2sECQDXXpggULEnSeM2eOWbp0acfAnA6uEcHDiRMnqpdpLVq0UMFpe/DPCQS1atasqQKzTvayH/p5/Q7dbsCAAZ6/tzBAgBIaz58/P8HHoDECdfjNTr4p3HfffeqZZM/vFOiDLV486gFBMHbsWFWe48ePz0g/jAIZteYf1vfau3evcf/996spDWF48cUXjQ8++EBNs7rxxhut1NOkclySHnbs2GF8+umnxkUXXaSmWelgSH/58uXVsGgvLr74YmPPnj1J5ZsKsc6RGmKMaZIPP/ywcfvtt6uh9UiLdeotq+wiXVpjeHtetF63bp2alnT11Vcn3G/QukiRIkrrhx56SGkdeyDEtY7VR6HsMp0g5fDFF19YKclIGdx0001Wij9vv/22+n+scaz0ckLX98EHH4zri7Tu2rTiWOcqkF0mAu1jDUTjwgsvVFM5dWINbc97QM9rLze3vJguiakedmCLsnYri2xFfFs00q9P920vH8F98f333xs333xzIH2wrlas82/EOibKB52AzxYrVkwt8YDn/R133GG89957Kg0+i/xh7AoK0RNTgMLqGSTvl19+mTX1ZiaBexraYoqYXVupC4L4OY5z6623uvptWGbPnq2mGMJ/Y5015b/vv/++SusWoWm/0A11sZf+8G2v+xX6b9++3bjtttvUND8vgtpC/5IlS6op2f3791fPRuiPtK5dvacUZyqiNaZ7QmvdV4NqjefBtm3blB5u+unnwbPZ7zwy1RVa9+3bV/k6+nqi9fFCnvaL6/nss888dfvqq69c64ggmoVF16x3795KM/SDMRVTnx4MYIv0ILaFifgNpnvDb/S6AP0M0dnPP7du3Wrceeed6lmfDtAmLlOmjJoSjP4Jjo11hMuWLaumFMt0XtghTbfDGpZ2u8JEfFk0dvLlr7/+2nUaO6YxIz+WP7DfCyijChUqJOXHWss4r/3+KFeunDqnfgySPjJGVazlg0oIzoVKKAzozD7xxBOq0f74449bqadJ5bgkfeDmRgcZnZGzzz7bSj1NlSpVjPPOO089AO1r8qULHBsBYPv5L730UqNfv37G5s2bVQWO34h1dBBEvuuuuyyr7CKo1ofyaYFwrH2CihzBVP0BDa3ReNO1xpo5orXYSpls2rTJ0y7TKWifX7lypQr63XfffZ4vOXR98btEX6wReffdd1tWhnHJJZcEsstERHs0Hty0RyfP6R7Q855zzjlW6mmc8oqfQxOUJ0Bw6cknnzSuu+46pWPUQCPPTV+sJycapcu38TIBvo1AB87pVgdAa9QxGzduVGWH34i1oux1h2537rnnKjuseQTfLow6RvR0qitET7e6wi/v+eef71vPYD+ej07lmcv41SPQNp1+bgfHxgtP+/nhv3369DHWr1+vfgM6UFhzSurmqHSYoD/WOyws/d0Q/Tds2BDX/5133lH633PPPWkL4hQkqEegNdoObvUIXjSkqrXUV27nQV2nnwcvQcXXERCA1ngRhPVmM0FrXTd7e0HXLb/a206IZngRj76vaCb+qQe+YIugn26Ll8hOtoWJ3W/0Z7TuN9A5P150/e1vf1P1EV7i6JrghQG0Xrt2rVojG/q99dZbSr+OHTuqtUrFDjqvWbPGqFSpkrL717/+pfxYtytM8DJWNIYv6xrjN+t1gJPGci+gbrbnlzKChlJGst4fgqFoiyFwi5ewf/zjH43f/OY3qq+SjXVpNpAxLQQ4AzqZcA44TlCWLl2qFltv27atujnt5PW4JH/A6AQ7qCTq1q1r/ZU/YJFVYA/ooZJ76aWX4o0Q+Ap8BkHkdI4wLAwKQ2sEoBD4wIMOb350gmoNO4zklYZUtpcJRi3YyY9yQNAVbzYRIPEKXtj1RTAW+j722GNKX8kb1C6TSeUeCJoXjedx48YpfbBwNnSBPnhr/tprr2WFTnkFGtmvL798G+eCb3sFNuCzf//731VAD78LZYJGNnwWI2jlt+p2QHz70UcfTbAraFBXuOnp95vc8tapU8c3LwKfaIxjNALftCfjpC2eY0G0TQWUCzpEGI2jlwvasi+88ILqjAHxc7yIgP9GrQyhv/2aCkJ/N6D/888/r/TH+aX+iIL+BaV10PNAa/TtfvGLX6i/RWvMCoHWmRIcwMi/gvJRGbmG42LDizF9tKlohmAp9kv9AM0w0l7XzG67ZcuWuL5220zASWd5Rqbzvlu9erX6QAeOCV3Qd/nLX/5i3HLLLQnBP+iHj5AgcCr6QWvMloF+Yit2GP0GxO6BBx5IsMsE5MMzOtC4du3agTRGGdn9Ru4FPT/adOhjIOiIkYbIc+2116r7+pVXXlGDP0j+kL47JU3gBoaTBQVfj8Ebaz/CHpekFxlZ4IUEedINRoa+/vrrKkDcqlUrKzUZBJfwJhcdw2ymMLXGdAGMVEAj2Ot+E63xRt+LoHaZSEGWg/i4n+52EBTBG3U/fYPaZQoyYsYLN+2RN2y53XDDDWq6HRp/uYD4ttcb9nT5Nl4mwLfRGQnj2wjkYTQDArJeBLXLT4LUFdLptRM0LzoaToi+eDZiyxUfDkKQukC0TfdoE0wtRbn8z//8jyoXt07XI488okadoKMatbIT/b20zS/9g4JnLvRHxzib9S8oreXZnJfzQGuMnCqsoK8TBVlHYCbB0aNH1XGwyfTzP//5z+or+E6/A89NaBbkBRJsv/nmm0C2BQ1GnPn5pwTU0sG8efNUUEo/n9+0dwT8/vvf/8a/Su2G2DWwvtSeKQS5N6ExRgc6EaaMxKZDhw6q7YwlK0jBkXHBv7AdBkznwYY1IH7/+99bqcmkqyNCvEEQApWZvmFIL6Yk4c2IF/kRoEVlhAZDvXr1jDfeeEO9fYgKmag1RiP4BVmjBspB3g7KhiUIECgriHKA7ugA4gGajSMjUwGBCyftEcCXN6xuuGkfttww2hVTIuAHGImORg3uwzfffFOtyZWuxmhhAH3xNtZJX3nT7Ua6fBvBOYyizJbRpnkhSJ2NDq+TnkHzyihHHeiLwD4CF//85z/VDIlcBJ1oTLvS/Rz1Ke7roNqm0zcxNQrlgoBeLpSLrGGo64/13ER/L23zQ/8og2WQEDCya43nZUFojecrzpXf50knsoYefo9seCZhvcEg7YX8uh4EAxGsuf7669V6dwhCewWnsgGsjYf1Bu1aY2Sin3/iOQad0wECdHqgdcyYMWoJEWiOtbi9AlyZjqw/qGuMdQcxktnv3oTGbs+jIO1CKSPYYO1s3BuYmfef//xHrVWLZYugM3wa04izWedMJmOCf2jUorOAiDIaPmHA6CB0SF5//XXVAdNJ5bgkPJijj0Cbjj59zmmRfQRlEZxNN+jY4KMTKHush5PtI/rsZJLWAOtcYJQeHo6pdvqzCbdykAeg00c90lkOWJ8F62Wg/tMDYagX0TDE70P9GMWHKNZewltWnXTdA0HyYu2Tp556Svk7polAa4AOO15KYeFnTBfJVu2hr923MV1LgEb2a0unb2OdItQpeHGjByERGEED/LLLLlOB1mzv8AhOH48QPf18yC0vRp045cXzES9p8KYeMygKc+RjYSN+LnU20Kf6OmmLe99N21RAOxXlgrobdXvNmjUTflcUkXrcS3/7PZ5f+kcdLFNh11qfSllQWmdTmTppZp+27DQqrCCuBwMaMHoK/RyM3Mr2+wFLBkFrXVt9GqqTzvKMtKenE6zXh4/fzZ8/X32ow+2jF9mAm8YyVdfpwynQGKP2gmiMMrLrI/eC5D98+LDxf//3f+ql28KFC42rrrpKnR8DSLBe4pIlS4x//OMfhf5Bn6hypuQLGVRgCBqgIYqpg2EZNGiQarxh/T+MxBBSPS4JBwJs6KzhASQbghBY7wBvCzBFCZWADhq7eHA5LVieV3AOvLnHcfEVNjy8o0aqWqczQIfz4G0S7sFOnTpZqbkBygFTYvVywAeICtrnvcBX0tDZjxrQHlM27dojHdqjMeymPd7YO90DUm7IiwaPjj0vzo2PUaDhgjQd3AdoYOG+sB8nW3DSFx8y8dJXFuaGHgXl2/gd2Ywshu1UV4iebnWFX14swG3PCzu0lX744QflnwhaRz3A5AXueUyNQ8dE/PwPf/iD0s2rHoG26fRzKRe0VzEaDsHtXCgX6I9pcLr+eKkC/TEapaD0zwWgNb64qWuNBfZFa7QT3OoR1Pupaq1/nMHpPKjr0nGedALNJCCia4Z12nA9opv9Oa/rlksvxFMBWkvwSLTGtGa8nNL9BumC7jfQOT/qTIyUQ12jB8yyFWiMF7e6xv/7v/+rXjSJxvBlXWNMgdbrACeN5V5A3WzPL2WEc6OMMGABL8zxjEPdo+uKtfmxZjxiNjinfhySHjLKi/E1XgwZxeKlegBPgEO+88471l+JwCExugugc6I/VFI5LkkPKB+MwkNHGZ1JHdzgaOzaP8aRV1D2+CITpoJjBE4UA39eBNEaCwanE7wJg944L85PvMsBI8KkHFJtqGAUlN4olQ1vzzCEf/ny5Vm7bmJegfYIyKFxgakwOtAeo2rc7gE9r1O5eeXV8QsyZjPi26KR3jjT65hUfRtTfvUGqmz4Qh6+rIdp1gi8Z/uoNdETDXK7nuJz9o8+CH55URZ6Xjwf8Tdeir388ss5H/jzAh0VaItRSnZt8czzKpewoFxwz6BcMOLhl7/8Zc6XC/RHXeyl/+233x4fsULyjmiNwAu0RptCSKfW+nns01RxHozovu2227KmTHE9V155paNun3zyidItP68H9Qa+kIqgDdoaUa0zxG8QuIbf6HUB1ueD39i/xJtOMFINLyEQ3IqqzuLLorHuy7IGIj5O4vZlYgT/kB8vcuz3guTHB1P8vmxsDxSyfZIPxG6gAuPQoUNm27ZtzXr16pmxm8hKTWTYsGG4o9UGW+SBLfIgrXv37spuxYoVZvny5ZW9juQXOyHocUn+MWPGDKU1yg3lB/zKy61cpOyc9iMNeZ02L9+LEunWun79+q77cS+1a9dOnWv58uVWKgEoh9iDK0Gb4cOHq7Ru3bqZsYeja5qOXgZO+53AMStUqJCzZTJz5sy49suWLVNpQbVH3liH3jcvfL99+/ZJ6SivBg0aqPtq2rRpgcssm7BrhGuERkiDFqdOnbIsT2vnlC6IXm777YwYMcKsWLGiuXTp0shoCz1jHUSlp1wXrhO6de3a1Tx58qSyc0pzy4s03Q706tVL5Ydv2re6deua3377rWVJwKxZs8xYh1Jpu2TJEqXtyJEj49qeOHFC2Tml2dmxY4fZuHFj5ed2m969e3uWy5YtWyLj62GA/rHOolmuXDlz8eLFcf1RJl26dDGPHz9uWZ4uA6d0Afo3adJElZHTfp0wtlFh9uzZZokSJZTWixYtUnXxqFGjlP7Q9NixY5al6ZouQL+mTZsq/ez79fMsXLjQ8zzZAK6nZMmSCdczevRodY2dO3eOX49Tmg40a9asmdLs6NGjVuppZF+bNm3MPXv2qLRVq1aZ1atXV+2PZ599NvJ+OmfOHLN06dJK5wULFiidx4wZo7Tv1KmTeeTIEWXnlGYHerZo0UL5m24j6Wg7f/rpp+rZKWmon72OGQWgcZkyZZTG8+fPV9c/duxYs1SpUmbHjh3Nw4cPW5amY/rcuXPNsmXLJuVHuel2P/74o3nzzTer+lpP37lzp9myZUul9fjx43Om7i1oMi74BySwZ28AIUghuAX/5BywR8dbJ8hxSf4iQSl9cwoqiZ2+z638ZEM56uXvtuVKeYfRGo0Hu9Z4+Nnzy2a/F2EbJjCVS4i+un56oAiIjZ7uVwZDhw711BsBl1wO/gEJAOq62bWXIJZbuldeoAcAdVvUVRI4jCpuGtkDeLrGsm/lypUqgKfn1bchQ4YkHUeIYvAPQCcEkHQd0BHUg3di45bulRe+es011yT5qr4NHjzYVfdcRQKAuk7QVg/giY09HX5euXLlhLz6Br33799vdujQIele0jfY6WWZS0gAUNfDKcAndvo+6F+1alVXnx80aFBc1yC2boHdqCCBOf26nQJyYqfvQzCqWrVqrvoNHDgwrl/Q82QLEgDUr8ce5BMbPd1PMz2o169fv6R6CNukSZNypm6QAKB+/faAnNjY06F1jRo1XLV+5plnVLk4nQNb1AN/ggQA9Wu3B/6ABPrs+yTdL78eANRtETicN29ezj7vCoKz8J+Y2IQQQgghhBBCCCGEkIiRUWv+EUIIIYQQQgghhBBC0geDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSERh8I8QQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoDP4RQgghhBBCCCGEEBJRGPwjhBBCCCGEEEIIISSiMPhHCCGEEEIIIYQQQkhEYfCPEEIIIYQQQgghhJCIwuAfIYQQQgghhBBCCCERhcE/QixWrlxpvPzyy9Zf7gS1I+5Qa0JIfrJq1SrjlVdeMUzTtFKcCWpHCCGEEEJINsPgHyEWH374oTF+/Hjjxx9/tFKcCWpH3BENDx06ZKU4E9SOEEJ0Pvroo0B1h9gdPHjQSiGEEEIIISR6FEjwD6N3KlSoYJx11llJW/369Y0dO3ZYliTqDB8+3NEPZs6caVn4A3+B3yBfjx49rNRksM9+Hvgh/FEQ38T5GzdurNLk+Pqxg9plEunSukGDBiqf03VCl4oVKyado127dkmdbrGdMWNGgoY4Po4tI2+C2mULI0aMMIoUKZKkEa7PjzB5e/bs6Wg7bNiwnB3V5Kbf9OnTfTUJkzdXtYdGRYsWTbruIPoKuLcbNmyo8nXv3t34+eefrT2nwci8SpUqJZ2jbdu2SQE72FauXFmdX46J4zdq1Cjh2E52O3fuTLLLFEaOHOmo87Rp03x1Rt5ixYqFyosXWx06dFA+jefe0qVLI+3HfowaNcpRw3fffTeQr/jlh+81adLEsQ6RrVu3bsbJkyetI+YW0K948eJJmkydOjWw/mHz4x647rrr1H1Xvnx5Y/HixRlXL6TC6NGjjRIlSiRpMmXKFOPUqVOWlTth8sO/mzVrpvy7a9euxvHjx6090cFNj8mTJ/vqOWbMGKNkyZKB8vbv3z/Jl+vVq2ds2rQpJ+rosWPHGqVKlUq4fmwTJ04MVD+GzX/48GHjpptuUvU36oEFCxYEuj+ymeeee84oXbp0kkYTJkwwTpw4YVm5EzT/559/btSpUyfpudeqVStj165dOd3myHdi4uY7K1asMGM3jRnrCFkpp4k1slGyaot1Zq1UElXED2KdNvPQoUMqbfv27WbswaU2/NsP+JD4DDb4kBNi57ZfR/dD2Zx+T1C7TMBP623btqk0L4JoDRucI9YJt1JMs0ePHsrefr8D2advTr8nqF2mg3KIdZ4TNEI51K9f3/d6wuRF/Rl7aJpDhw41Yx0UlSa28IPly5ertFwC+lWsWDFJvwYNGij9vvvuO5XmhJ73wIEDKs0t78yZM81Y4yVJe9hC+2XLlqm0qLFy5UqlUZs2bXw1cmP48OFKO7nHu3XrZsYa1tbe04wYMcJs165d/BygZ8+eyt+HDBmSZC/77HXH1q1bLYvTBLUrbKBzpUqVlM779+9XadC5YcOGvr/XLW+jRo1U3m+//Val2YFPFy1a1LziiitUHbRkyZK4b+ca0LBy5cpKw3379qm0HTt2mI0bN1YabtmyxVObVPPPmjXLjHU8zcGDB5uxzqmVmjtAvypVqij9fvjhB5UG/Zo0aaL027x5s6/+VatWDZ0fupcoUcK8/PLL1T2waNGipLomW1m1apXSpHXr1ubevXtVGjRp2rSp0mTTpk2emiJ/tWrVAuUfNWqUWbx48Xgd26VLF/PYsWNqX1TQ9dizZ49Kgx7NmjVTemzcuNFVzzB5R48erXzy2WefNY8fP67SZs+ebZYsWdJs1apVPH9UgVY1atRQWu3evVvpAq2aN2+utFq/fr2v30r+77//Pp6/RYsWrvnnzJljli5d2vz1r3+t2juffvpppOvh1atXm7Vq1VL+tGvXrrhGLVu2VBqtXbvWU2M9/86dO5Ut/q/nl3p07Nix5rXXXhu3A/fdd5/y8aeffto8evSoSiPpp1CDf0D2YcO/SXRB8MipnBG4QKPAyT90xFdgjw4MKhKngJTYOe1zQ/L4/Y6gdoVNOrRGg1e0RhApqJ6SF/ZODwnZj9+BgIkbQe0yGQQxUQ724JtTsM5OmLywxf1gDyYiuALb6dOnWym5AzSB/9iDb07BOjth8sIW94c92CXaT5s2zfU82QyCZ6KRfn2iEQJzXteNTjka09AHfougoVPwzwnkRVDLzV72o+5wChAKQe0Kk169eimdly5dmqQzAnRev9svLwJK9rwSHIS28HOUUS4H/3r37u2oQdCgXCr58eKuQ4cOqn7xCxJGlT59+ij9Fi9enKQfgkqDBg3y1F/yI3gXND86uwgOdu3aVd0DCN5GKfjXt29fVe/ZrwmBJHS8Bw4caJ44ccJKTUbyL1y40DO/BLYmT56sno8IDkLTqAX/vPRAYE4P1tkJmlcCgghi24N8/fr1U8f47LPPIuOjTvTv31/diwsWLEi4TgnQPfPMM56+FTa/BAYRsMZzFgHzqAf/7r33XqXR/PnzE64TGpUtW9YcMGCAZ1AOwTu8rLHnnzt3rsrvF9RD8LB27dpmp06dzMOHD1upJN0U+pp/F198sfGnP/3J2Lt3r1rfi0STWCVqxCpN46KLLlLTrHSqV6+uhlNjCLAX8JXYQ8+48cYbrRRnxI8eeeQR9X8vYp0gNcy4ffv2xsMPP2zcfvvtRqySU2mxTr1lFdwuE0iX1rt37/bVOgzQsEiRIkrDhx56SGkYeyDENYzVR6HsMp0g5fDFF19YKYnkJe+BAwfU9Bo7sEWeXAL6YXrGhRdeqKZy6sQ6I573gJ7Xrr1bXj/t4btRQvxTNNKvT/dPr3sVvv39998bN998c9r0iXXo1fQcLDtw//33G3fccYfx3nvvqbTu2nTeoHaFjejcsmXL0DqLH3vl/fLLL5PyYv1DXH+sI6SmPOYyuKeh/wUXXJCkodQFXn6O/CgDt/wVKlTwzL9+/Xoj1hkyrrjiCmWfrvskW/DTT3zY7X7V8+M54KS/U35MTzt16pQR6+iqOiFKiCYtWrRQmqKtJYTRFPmhqT2/rimeD9u2bVNtuKjWJdDjs88+89Tzq6++crzH/fJCS+SFlpgGiXZG1apVjbPPPtuyOs1tt92m9m3fvt21Lsl2xO8wfdx+L0MT0dnLb6E18tvrErf8mAqMaap//etf1bTsqKNr5HRvQ6Ovv/7addozfBT5mzZtmuTP0Bj+7JWfFBxnSqYQadOmjXIqBFP4EYVogkoFDyd0OuwPripVqhjnnXeeaiSko/zRMcfxcFw/Lr30UqNfv37G5s2bjTJlyqjfiHV4hg0bZtx1112WVXC7TCCo1n4L4ecVrH2CIO2dd96Z8ICFhn379k3QEGvuiIZiK1pjDRMvu0wnFZ8PmxcBaegCfdAABAiiPvHEE2rdIgRzcwnRDw0WN/2gk9M9oOc955xzrNTTOOUV7e+++25VJgDBpSeffFJpf8kll6i0KCEdESd9K1euHNcov57nqGPwcsJex0Br1DEbN25UZYffiDWo7HWHbnfuuecqO6yvhHVSM6mOEZ2d6gHR2a0OQd79+/e75j3//POT8q5atcoYPHiwWlcK+XIdv3oEGnr5OfKjDPzqIbf8WJ8KHaUHH3wwJwOxfvoF0d+r/Jz0R7AV90CfPn3UPZApdUG6kHrBKYgk9QJeHLhpKnWSW35o6pU/auh62tsLup5ObQ2/vLqWQYJ6a9eudQ1+ZTt2v9PvS10r6OyklV1re369nJAf9cDQoUPVgIOaNWtGrh5wAi9jRWO7RpUqVUqoG7w0Rt3qpDHKCHWyWxmBF154QZ3jlltuUWtbkvwhI4J/8hBGZ9+pgiTRAaMQ7KCSqFu3rvVXaqBSQocGx3vggQdU5aNv6NzpoJJ76aWX4o0Y8cHHH388YdRbULtMIr+1FlbaPvrx2muvqc42FsnVCaP1iy++qH4ryAatvcCoAztByyFoXgT3xo0bp7SSDgv0x+LaKA/8nYukcg8EzSvaI6hdo0YNpTX8tEuXLpHXHhrZry+ovmFAUAqNT5wL2z//+U/VQYfO+vlRd/z9739XAT2ko0zwUZDHHntM3Q9iq9sB2KGOefTRRxPsMgXUA/bfJDr7/Va3vFho256Ohedhj+Cf/tY+13HSEM8xJw2dyEt++Pzs2bNVXvtIl1wDGtj9MYz+GFkVND8Crs2bN1f3QNRG/emkqmmq+aNGGB+zg7x2G3te6ScvXLhQBaz14AmC2xhVlQu6O+ksz0J7uhNu+aG1nv7888+rDw7iJWGuBaFQ/zlpVLt27cAa219WiT/b82OwjqTDf9Eu+7//+z/j1ltvZfAvH/EvxQJAblwSXRCQw9RuLyTIkw4++OAD45NPPjFWrFihHpL4P0aXYiQURkQ5geDShg0bVMfQi6B2hUVBa41p1hjpp4MK3e3NDhAN0WjxIqhdJpJKOeQlLwIhmLKYCw1AP9A4tvukHTftkTes9jfccIP6GmeuaC/+6XWPp7OO+eijj5LKxD7t3Q4CeevWrVMBWS+C2hUGQeoBCVzaCVJGEhwFGK36+uuvq5dmEhTNdYLUBaKhk86p5P/444/V6FaM+svV8hD9gviwm/5+zwE9P4Ktb7zxhvG73/1OBVqiSLo0zWv+qJHKPR6mLDBy6t577zW+++479XVfCZZgwxIaqO+jrDdGg/lptWXLFqWVE2HyY5kh1AN4AfCLX/wiZ9p1Qe5taITRgU6E0Vhs5s2bp0Yc6nkw/ZpTg/OXjAj+oeGKjgICgAgEkuxF1sbTNwybxmgkBN+8SGf5t23bVj00Zboj/v/++++r34B1HKJApmiNAB0qbtkw6u/1WCcSa/alq/OfycgahXo5IAiHgGVeyyFsGcroS/yWZcuWqXKAL7z55puRLgcELJy0R2Aeb8K9cNM+bLlBe4xKg/ZLly5N0B5ryrk1RrMB6Is3uE76QiP87UY66xgE6NAYlDpmxIgRxr/+9S/l29msryBrEOo6I5iM0R5+voi35l51iFcZIS8CS2i0Y3Rk586dk0ZT5gII+mCUgV1/3NdB9JeRpnaC1CVO+TE1CiMg/ud//sdo1apV0miJqAH9S5QokaA/Rq2L/k7aCn76+z0HJD80R1sGyzdg9G9UNRefTFXTvObPRrAkValSpdT1yIaR/cePH8/zPQ7ClgXWwF6yZEl8dgdA/YDBDjiW13GyBQTeSpcura5FNmhdrlw5X60wMg1aORGkzYL8P/30k1qyBetUoh6I4uhfaFy2bNkEjfHsx7Rev3sbGrm9GAmqsX4v4GUjNJe2HUZeT5s2zbj++uvVNGKkkfSTEU83WZcDFRqGhpLsBeu14a2Ujj59zmmRfQn+phOnUScybB5vyKKwHkmmaG0HbycR9ECDBKMXoo5bOcjDzWmEUtByCJIXvvyHP/xBPVBR5rLGHKZGIhCLkZmYRh3FhyiutX79+tZfp0nXPRAkL7R/6qmnVPAFa8TAF4BojxFrmOqerdpDX7tvY7qXAI3s11YQdQzWBMULHuiLOibbfVt01hvN9jrETWe/a3fLi5djko6PfGCENUY76EFIBAQx+uxXv/qVCvpG9W28k/7wcy/9ce/rGnoRNj/KAx/76NChQ9oC6JmM1ONe+tvXMgujv9MHLOz58ZEPaI6XNnogEh+OQyf08ssvV/cAPgAQBVLVNNX82QQGDzj5px4gDuJjbiCv3cYtLz6igtF/OBf24Rl47NgxNeLK/pGFbASjGKG1fh36NFQnneVZaE93wi0/tEY6BodgJgBeLupBSARe8ZLs6quvVi+Gjh49auXOPtw0lqm6Th9OgUYYtRdUY3tbQfzZL3+vXr3US1183AVtu5MnT1p7SDrJiFoCnVNUXFhom2Q3iPyjE4GHkmx4m+oVeEtn8Bf5cZxcIFWt86tTkUtlAFAO6DTo5YDp5an4fJi8aKhgfSg0SvBbdDp16qQ6tXjTZz9OFMD14vrt2iMd+mEag5t+eFPudA+I9siLBo+OPa9of9VVV6k0HWiPBha0tx8nW3DSF2/FvfSVhbmhR6r1uRtRq2OgpyzW7qSzUz0gOrvVIbKIuVteLMztltcJNMZR3lEE9/yaNWsS9McLFejjVY9AQy8/x3FRBn71kJ4fdqgzMOKnY8eOWd+ZDwJ0+u9//5ugP16qQH8v/YLoH+Q5EPQewJcscSz8vmxF/7iBXROpF1DvuGkiC/e75YemXvmzEfiRBETEP//4xz+qFyW6nvbnvK6nU1vDL29QLfFBPHyUAkH0bK8voLUEj0TrP//5z2pZDt3v9HtQ1wo660Fawa61Pb9eTk75dbDuIp6r+jGyCWiMF7e6xv/7v/+rfEg0tmuEqbl63eClMepWJ41RRji3l8YYkYg6OReee4VJoauLqVLorOEtPoYvk2iCCgPBCXSU0ZnUSXfwFyMm8BXH5cuXWymnwd9Iv+666yLVMLETRGt8JTO/wIMZD0YM/45SBz0sXuUga5jZv1YqpJJXRzo4YTr5UQD6ISCH0XgIquhAP6xr4nYP6HmdtPfKq6N3Lp0a/tmM+KdopDfy9DrGzz/zil7HQN+oIjqjoW7XWXzxjjvucGwoix+75UUZSV5Mq8YbdtjoG6ZXYzkBTDXDiyZ0DnIJdFSgP0Y52TXEqAQv/QHyowzc8mNUpT0/1kDCqPkrrrhC+XZ+3UPZgJ9+0B/T89y+hKznx3PASX/JjxF+GNUHG30bNWqU6tQuWrRIveTDtLVsLhPRBAEWaKqPxAmjKfLbvy5r1zQXgB5XXnmlo55Ydxx63nbbbY56+OWFlsjrNfUUz2BMm//1r38d6fpC/O7rr79OupdRZ0IrfCTCTSvRGvntdYmeH89CjOrT6wBs+BgWnqmffvqpqgfsI0GjgK6R/d6Wtfluvvlm1w9xoJ5EfrzIsfuz5Pf7iu/hw4fVCxYEERkEzEdiTp3vrFixwow10s1hw4Yl/I3TY6tXr54ZK2y1j0SXGTNmqPJG2cMHAHwCad27d1d/C27pAvwFfuO0X/YhP84J5Ny54mvp1jr2oEvaL+k4x/LlyxPS5Hixyl+l5yooh1gDIUGj4cOHq7Ru3brF9XFKC5r30KFDZrt27ZTmerpeFtOnT1dpucTMmTPj+i1btkylBdUeeWONDt+80L59+/ZJ6dC+QYMGSvtp06bF06OEXSNcIzRCGrQ4deqUZXlaO6d0QfSy70d6w4YNE84haeLvTseLEtA51nFUGixdulRpMGLECKVn165dzZMnTyo7pzS3vEjT7dyAbcWKFc0lS5ZE0oeDMGvWLDPWoVQaig4jR46Ma3jixAll55QGguYHqE86dOhgVqhQwVy8eHHOaq4D/WKdRbNcuXJxTaAfNO3SpYt5/Phxy/J0GdjT9fyLFi3yzO/EqFGjzFinVuWNSl0ze/Zss0SJEnFNcF24TugETY4dO6bsnNKAnn/hwoWu+XV27NhhNm3aVPm80/5sBnqULFkyQY/Ro0crjTp37hy/Xqc0v7xHjx5Vdqgbrr/+enPKlCnxelvs6tata27cuDHy9cWcOXPM0qVLK60WLFigtBozZozSr1OnTuaRI0eUnVMaCJrfCdhVrVrV/PTTT32fm9kMNCpTpozSaP78+epax44da5YqVcrs2LGjefjwYcvSdEyfO3euWbZs2aT80F2327lzp9myZUv1rJs3b56ykzS0Y+znIumlQIN/aKzbNwnOkNxAglL65hR0Ejt9n5cfYZPgMnCyzbUgcxitEbywa41K2Z5fNtFa8tr3M/B3BieN9EAREBu3dK+8QA8A6hvuAQkc5iISANQ1sesnQSy3dK+8QA8A6rbQXgKHUcVNIzSqdXSNZd/KlStVYEnPq29DhgxRtk7nwOZ0nqgCDRAs0q/fHrwTG7d0r7xuMPh3Ggng2TV0CvLZ00GQ/AD3RJUqVRz35TISwNP1cwrciZ19X9D8TkQx+AckgGfXxCnI5xTQC5J/1apVZrVq1ZKejbINHDgwMn4uQTz9+vQgHxAbt3R7Xgn8Cf369UuqR1q1amXu2bPHsog+EsDTNXAL8jkF9ILkdyJXgn9AAoC6Rk7BOAn02fdJetD8up2bLUkvZ+E/MbEJIYQQQgghhBBCCCERg5OpCSGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCGEEEJIRGHwjxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSERh8I8QQgghhBBCCCGEkIjC4B8hhBBCCCGEEEIIIRGFwT9CCCGEEEIIIYQQQiIKg3+EEEIIIYQQQgghhEQUBv8IIYQQQgghhBBCCIkoBR78+/HHH43Zs2cb9957r3HVVVep/+NvpDsR1p4QkhmsXLnSePnll62/SGEh5WCappVCCCEkW1i1apXxyiuvGD///LOVQgqa1atXG6+++qpx6tQpK8WZoHaEpBPxu5MnT1opzgS1I858/vnnxrhx44wTJ05YKSQ/EJ2PHz9upTgT1I4kUqDBv/Hjxxt16tQxbrjhBuOll14yPvvsM/V//I10dFJ1wtoTQjKHDz/8UN3Dhw4dslJIYfDRRx+pcuALE0IIyT4+/vhjY8KECcbBgwetFFLQoAzwHD1w4ICV4kxQO0LSySeffKLqCD+/0+34Qjg8ot/+/fupXz4yb94845133jH27dvnqXNQO5JIgQX/Zs6caXTq1En9e8SIESoggILCNmvWLKNevXoqWCCEtSeZxfDhw42zzjoraUO5BiFo/h49ejjaIX+ukKrWYMeOHUaDBg1UPmhqB4H2ihUrJp2jXbt2CcE9sZsxY4bRuHFjlSbHxnGjXDmjnipSpEiSRtAiCHoZdO/e3VWrIOfRy6FRo0Zqf5TLwUsTv2t1yzt9+nTXvAikXnPNNSpfhQoVjOXLl1t7ogk0Klq0aCiNdILm79Wrl2NZDB06NCdGPY0cOdJRp2nTpvnqHDQvRpFVrlw5ya5t27Y5H7AYNWqUUaxYsSRt3n333UD+t3PnTqNJkybKh7t16+Y5usbPFuVUtWpVdW55LqAORx6/Y2cr0L948eJJ+k+dOjXw/Q9dmzZtqnTt2rWr5wgd1OPXXXedum/Kly9vLF68OOE8GCVVrVo1df769eur3yLHRxnIse12OLeTXSYxevRoo0SJEgk6Y5syZUqgUYth8vfr1y/pvoLeixYtyqp63e2aJ0+eHHikJ/yiefPmyke6dOniOGJpzpw5RqlSpZLOgw15jh07puzgdzVq1FDnR59Y/A7Hh9/52bVo0ULdI2KXSYwZM8ZRg4kTJwaq+3B9F1xwgbq3O3fubBw9etTak4yfLUaX1apVy5g0aZJRt27duH4tW7ZU+nkdO5N57rnnjNKlSydpjGBa0OfLrl27jAsvvFBph5jNTz/9ZO1J3Gc/h2x6HuiMgV04P/4vOl900UXK78PaEQ9ijcJ8Z/v27WaswkHr04x1xqzURA4dOmTGGjbq32HtSWaxYsUKM/ZgN2OdCVVOQMoUG/7tRdD88A34yLBhw9TfQOyQH8eJOqlqDaAfdJSte/fu1p4zwAbH27Ztm/obx401cpP0Bz169Eg4HjY9bxRBOVSoUEGVw8GDB1WaaBTk2ocPH27GHoRxvWINNzPWKLb2niHMeVAO+jGjWg7QpGLFikmaxDrM6nq/++47leaEnvfAgQMqLUjemTNnmrEGh3nFFVeo+2/ZsmXWnuixcuVKpVGbNm1CaSQEzS+aDhkyxIx1pFQa7Bo2bBjX2OmeiArQqVKlSkqn/fv3qzS5fui0detWleaEW95GjRqpvN9++61KAyNGjDDbtWsXtwO9evVS2g8ePDiufa4BDStXrqw03Ldvn0pDG1PX0Mv/Ro4cacY6OfG6NtYpNE+cOGHtTSSobe/evVW5iB22WOfT3LJlS+TuBehfpUoVpf8PP/yg0qB/kyZNlP6bN2/2vWboWqxYsbhWsY6gefz4cWtvMrNmzTKLFy9uXn755eq5umjRoiT/79OnT0JZSRnYf09Qu0xg1apVZtWqVc3WrVube/fuVWnQumnTpkrrTZs2ef5m5K9WrVqg/KNGjVIaoyyOHTum0rIR/Zr37Nmj0nDNzZo1U9e8ceNG33IePXq0WaJEibh/dO7c2VGT2bNnmyVLljQnTZpknjx50kp1pl+/fgk+L35n/z1B7TIBaF2jRg2l9e7du9Xvg9bNmzdXWm/YsMHzN48ZM0bpJ9fZqVMn88iRI9beRILa9u/fX/mx2GGrU6eOuX79+ozTLwirV682a9WqZbZq1crctWtXXOMLLrhAabxu3Trf6xo7dqxZqlSpuB4dO3Y0Dx8+bO31Zu7cuWbZsmXNp59+2jx69KiVapr33Xdfwj0iOq9duzahbnazW7NmTc62YcJQIME/CdLoAQovwtqTzALBI6fgm1Owzomg+WGHSgqdHB0JZsE+6qSqNfKh0Qt76IggklPwzwnJqwddBNkX5DdEAQTaUA7Lly+3Uk4DXRGAGzp0qOuDVLSaPn16Qhk42Yc9j14OXr8hm4EmuEZ7AA7BJD/tvfKi0+2UF2WEwBUCtPBtp/xRomfPnvFr1LXQg3VefhU0P+zg+/YgF4JVsJs2bZrnebIdBOCg09KlS5N0QlBBD4ra8cvrF9ST4CF82q+zGVUQaEOQesmSJQkaIkCETjM0dNNGAodTp05VL1caN26stHQK6EmQK4gtEHvU4V6/IdtB8Az6L168OEl/dLoHDRrkee2i05QpU9QLBQQNEVR1C/6hoys2qOdRfk7BPyDBMjxP8DvcyiqoXWHTt29fdb/brxdBJ3SoBw4c6PnbJf/ChQs980vALNsDf8DrmhE88tNMtJg8ebLyTwQN4XupBv8Ajl29enXld88++6yrzwe1K2wQaMP9uGDBggSt58yZY5YuXdp85plnXP0J14jA4cSJE1VbokWLFsr/nAJ6YWwBAmY1a9ZU+nn9hmzg3nvvVRrPnz8/wcegcZkyZcwBAwYkBOXsSPBwwoQJSruWLVuqYHaQ4N+PP/5o3nzzzaodbQ/qARy7du3aSmd7cFAnqB1JpkCm/WKYLsDw+rPPPlv924uw9iRziDWojE8//VQNv23YsKGVeprYQ0cN9ceQXTfC5sc0JQz3tQM72EeZVLUGF198sbF7927jxhtvtFJSI9bZVEOw27dvbzz00EPG7bffrqYwxCrnyE77DVIOX3zxhZWSjJTBTTfdZKU4E+Y8ejk8+OCDqhzmzp2r0rp7TCnONqBJrIGophZgerMOpmFVqFDB9R7Q89r1RF63++ftt99W+sUa+8qvo4z4nGikX6/uc27+FDY/6nNMFbEfD3awjyqiE6YRhdU5SN4vv/zStYzI6Wlf0BBTv+waSl3g5eeok3GMW2+9VdWxXsAWZeZnO3v2bDUFFktr4EN3d9xxh/Hvf/9bTTvsFrFpv9AOdbGX/vDhnz2miIqut912m5pm5gfW5Yt1Oo1YJ1dNSXUCZVCyZEmjTZs2Rv/+/dVz9P3331dpXbUpxbodpriirJzsMgHRGlM+obXug0G01vPjmWvPj2eu5Mf6h9D4gQcecNU4G8A1Y835vGoG8Azctm2b8qEg/hkEmR4Mv+vdu7fyOyyHhamcXbTpwUHtMgHxr2bNmsWXrBGwDAK0/uqrr1y1hs5bt2417rzzTl+fC2qLtnOZMmWM1q1bq34M9MNa2mXLlvWdUpyJiD+Lxk738Ndff+05lR3tjS1bthh33323ek6FYcOGDWoq+mWXXabaKHL+9957T8V8oDPqTZQL1lhEmj49OKgdcedMiecTWFMDFR5uWFQ8foS1J5kFKhV04HBD2wO3VapUMc477zxVvihnJ8Lkf+SRR1Q6bnw0+gCCHk888YT6KAyCKlEmVa1TBcfeu3dvwvkvvfRSo2/fvsbmzZvVwxK/D+vgDBs2zLjrrrsSHuRRoaDKIcx5UA7ohGzatEnZSjlgfUg8rKOCaIIGi5sm27dvd9Rez3vOOedYqafR8x6yrWk5aNAg47777lP5og4CcW76Vq5c2VNfECY/XhagfoB/wo8B1vdFfX7ttdeq+jyK9QcQnZzubdHJrQ7xy3v++ef71j9YX2nPnj2qU6N3BHKFVOqR/OKSSy5Rz9L169erMsTHPrDmlNThUSon6I8F9N30x/WnU/9Vq1YZQ4YMMfr06aPWQnMDZQAbdFalDLDOFMrgnnvuiQdxdLtf/OIXypec7DIB1BfQGoEUt/oC7Wk3raW+ccuPe0XyI2COZyvKMJvrbl0ze1tB10xvKxQEeCbC79atW6f6zPBPBLXF7ySgFdQuE7D7l+43dv8qqBdaeLEA/dauXavW0kY5v/XWW0q/jh07Zl1g+/vvv49rDH/WNa5UqVK+a/zCCy+ogPPvfvc79YJEgM4ITn/zzTeqrKHzm2++qdaMRlBPgoy6HeoWscO6xyiPsMHIXCT3WnmkQMBbATuoZOrWrWv95U2Q/Hig/fOf/zQ2btyoGo2owDB6CiObXnvtNcsq+qSqdV5BRwQPBgRf5eGBhwm+yC2NQgSfUDE//vjjaRtdmKlg1IKd/CiHIOdBObz44osqHSAYi3J47LHHVDlkc0PcCbd7AIsB+xHm/sGC37DHKJCoaegFrtl+vWF8O0h+1Ofjxo1TvlqzZk1lD1/FyATU87kQlMK97aaTn7+55cU9YE9H8AONa6Rjg+4YyYrnp995ooyThniWBdE/3aBTg04SAgsA9wU67Q8//LAqpyjeD9Dffl3Q38mHUwEL3eOjCKjHvQJzKIPnn39elQHOL89RexkEtcskUtXaLz8CBwjY1q5dW7U70CFHumx4iZZto1cx8q8g/FOQEWmiGepofRQp/O5vf/ubUa5cObVf6gi8SLv55pvjvh3ULpOA1vbfJc+zgr6foN/YsWNV4FTXD7NqoF+2Bf8E+fCMTn5rjNk0GImKD1fZRx2iTYIXkQiwQmeMLITOv//975XOEtTT7QDsEMy8//77jVtuuYXBvwAU7B1EIg9GGGA0mBcSEHIibH50DhHsy0VS1ToVMMLy9ddfV1+IbNWqlZWaCAJ+eBOOwGyUKahyyOt50PDG6JEolgM6Fxix5AU0QQPCDvKG0ROj0N544w3VYEYDKRcQn/N6++vl22HzY8Q26nM0/HKJIPe2BBTsBM2r3wOYsmTP4zWtNeoEqQtE/8LQCLMcMOoEX5yM4r0h+ntpKz6cqv6Yoou2CzqKGOESFATyUAYIZnmVQVC7wiJVreWZGzQ/6hpMycO0ekwjxIsHtEX+/Oc/q6+9e00tzBSC1g/p8E+AJa8wlRTHwibTyqHZNddc4/hb0C5Zs2aN74uKoHaFBUac+fmXBIUKAwT8MOKsvvX172wkyD0sAbV0M2/ePDXyELNnJBjtBJYKwNRj+zR7O2JnDyQSbwpMKVRWaKQGJaw9yQww9QhvR7zAQ8et8xwmP6bgYW0CdMpXrFihKjJ0HNGwwzo5btMWokKqWucVPJzRGcGxoXWuBELcKKhyKKzyzmTQiUAd4AU0Offcc62/zoC8QfUUn8cotFwaHSU+53W9Xj4XJj/qc0w5mTFjhrF06VK1pk/Pnj3VdA6sXVlYjf2CIMi9jbfxTjoHzavfA48++qgadSOdS0yrwVqW6FjmR4M/0wlSF4j+uXLvFySiv5e24sOp6I/pxXgpiamOeHGci53FVLWWZ27Q/FiXC9NNL7/8cqU31llDMAuzE6ZMmZIVwb+g9UOq/ukGgoEI1lx//fVqvTsEl73WF8xm4Bd+/oXAuv48I+EIcg9D4zAvR4KAKd3/+Mc/VF2AQSPZOmIyCuT7kw9DotE4BXjb4EdYe5KZOC2Uj7fmGOURBL/8COw9+eSTqnLCiAVMGQOY7ov15T744AM17TEXSFXrMCAI8pvf/Eatf4IP8+AhQk4DP7STH+VQUOfJJtzuAbyN9yPI/YPACEaxYuQfOjBoNGFDRxKN8l/+8peR+pCKHWhkv7YwPueXH/X5U089pYIrGBmCNSuhL6ajYl0dLByP+jyqHR7BafSd6OTnW255cQ/45cX6oBjFjVE60NrPPqo4aQjfDKI/SR3ob7/HoX8QHw4C1jnDKHi8UMCHU6QeRzAcHVN0SlGPZ9IHOvKLVLUOmh9/20fE2dduyxacPuqRTv/0An3jDh06qJczGLmV3+crbKC1PTAsz7OotwMKCqcPp+Snxugz4kUAvucgSySQwqFAXnthoX+ANTFQ2fsR1p5kDlgbAQ91jNq0P9RlUW0Ed/EgcyJofvgFOolXX321elOkg68v1atXT60rkE0Ni7CkqnVYcA40jBH4w1cHscg1KbhyKOjyzgZEEzSG3TRBgNpJEz0vGjw6el63UW128IU6HCtKSCfNSV9ZmNtNXxA0P/RGfX7VVVclvVDAAs6YYoMvvNmPERVEJ6d7W3Ryu7f98qK+9qsXsA82udoYT6UeIakD/dEZdNMfPlxQ+uMrmPgdUQ2uoL6A1k6BN6kv0KZ201rqG7f8uFeQH2UalTpF18zeVtA1C9pWIO7Y/Uu/D3X/gn8yeJQ39I96wJ91jfWPgaRT48OHD6svoKNOwMhrrstXuBRI8A/DO/FWGR9m6NatW9IDA+CN3F//+lf177D2JHNAhYGAHDpyiPDr4NPymM4twV0nUs0PpLHu1+HJdtKhVVBwD952223Gf/7zHzUah4G/M3iVg6ytpX8UJa8U1HmyCWiCgNHq1avVVBgdaIJReW73gJ7XSU/khZ4A6ybiTSgaSfqGUWmYPrFs2TI1MhB1TpQQnxON9Eai1DFePpdqfiCdqygHX0QnjJC06yS+6PYlXr+80NjvK76o3xE8xBo89uBrLoBABTTEaCa7hhgJ6aU/SR3oj7rYS//bb7895Q8TYOkGjOrD8fUNX4lE0GHRokVqZGCmrteXDkRrjKyC1voInyBa6/nt00+Rf/fu3fH8+GgD1g7Dsjy6HZZ4wPMSyzlkw/RNXPOVV17pqhmuGe3j/PxwBupovABD0AZ1dNT9E+u4wb/0ugDrxUHrW2+9lVNGU0D8WTTW/VnW5MOHMzA6Ol1gzU/MyMMsGbST+SwtZGI3VoEQczCzXr16uIvN8uXLm/fcc4/Zv39/9X/8jfTu3btb1uHtSeYwY8aMeLnFHvoqbdiwYUll5pQGguQ/dOiQ2bZt26T827dvj/sNjhN1UtVaB9rVr1/f0QZpyO+0Qe9Yx9GyzE1QDrHGmCqH5cuXq7Thw4ertG7dupmxh6trmo5eBk77g54nl5g5c2Zck2XLlqm0oNojb6wR4pvXDdhWqFAhnjeK2DWCJrhupEGjU6dOKTunNBAkP+rzWEcwrrvkx/3QsGFDVc9MmzbNtzyyGegU6zwqnZYuXaqudcSIEUqnrl27midPnlR2TmlueZGm20HPRo0aJdhJGrTXbXONWbNmmbEOpdJmyZIlSpuRI0fGNTxx4oSyc0rT2bFjh9m4cWPlx077dcLYRh3oX7x4cbNcuXLm4sWL4/qjTLp06WIeP37csjxdBk7pAnRt0qSJKiOn/XZwvMqVK5uLFi1KqLuiyuzZs81Yx15pLdc8atQopT80PXbsmLJzSgN6/oULF7rmRzk0bdpU1S2TJ09WdYvkrVu3rrlp0yZVztkAfnfJkiUdr7lz584J+owePVpdoz1dgC7NmjVT/mnfL/vatGlj7tmzR6WtWrXKrF69utLx2WefDeTT2cycOXPMUqVKKa0XLFigtIam0B+aHjlyRNmNGTNGpXXq1CmepgMtW7RooXzSab9OGNsoAI3LlCmjNJ4/f766N8eOHat079ixo/nTTz9ZlmZC+uHDh63UM+zcudNs2bKlKhun/T/++KN58803m5UqVTLnzZuXs22MTKLAgn8ADfzHHnssKXiAhufbb79tWZ0hrD3JHCQopW/2oJLYOAWbguTXA4D6hsa7BMJygVS0hk4IXtjzy4agIXRu166d437ZYJfrQGM0znRd0KnTG7dio6f7lcHQoUMdj6Hb2M+TayD44aeJ2DilI5jildeNXAj+ATeN9I6y2NjTQZD8egBQt0N9LkHDqAOdEFjSr98ekBMbt3SvvMDJzs0215AAoF0XPTAnNnr6ypUrVfBIz6dvgwcPjmsL2ypVqjjaYdNtcw0JAOp6oDNuD3aInb5PdLXXH7INGjTIVddcC/4BCcLpGumBOyA29nQQJD9A4KpatWoJ5ZJtgT9BAoD6NTsF+MRO3+ekg77pQb1+/fol1UPYJk2alDN1gwQA9evXA38ANqVLl04I/kHnGjVquOr8zDPPJJRJUNsoIgFA/ZrtgT8Au7JlyyYE/1avXm3WqlXLVbsBAwaYR48eTbBFOTkFB0nBcxb+EyuoAgdTMzGMuUGDBlaKN2HtCSGEEEIIIYQQQgjJdQot+EcIIYQQQgghhBBCCMlfuOIiIYQQQgghhBBCCCERhcE/QgghhBBCCCGEEEIiCoN/hBBCCCGEEEIIIYREFAb/CCGEEEIIIYQQQgiJKAz+EUIIIYQQQgghhBASURj8I4QQQgghhBBCCCEkojD4RwghhBBCCCGEEEJIRGHwjxBCCCGEEEIIIYSQiMLgHyGEEEIIIYQQQgghEYXBP0IIIYQQQgghhBBCIgqDf4QQQgghhBBCCCGERBQG/wghhBBCCCGEEEIIiSgM/hFCCCGEEEIIIYQQElEY/COEEEIIIYQQQgghJKIw+EcIIYQQQgghhBBCSEQ5y4xh/Tvf+PHHH42//vWvRrVq1YxHH33USk0ENsOHDzfOPffcJJuXX37ZWLp0qfVXIl26dDF++9vfWn+dBseaN2+eMW3aNOPLL780WrRoYdxyyy3K7uyzz7asCCH5ycqVK43ly5cbffv2tVJIYSDl0KdPH+Oss86yUp0JY0vSC7UnhJDMZPXq1ap+7tGjh1G0aFErlRCSS3z++eeqHujatatRvHhxK5WkG9EZMZ4SJUpYqckEtSOJFMjIv3Xr1hnjxo0zZs2apQJzThw6dMh4/fXXk2x27NhhDBw40HjppZccN3tQcPz48UadOnWMG264Qe3/7LPP1P/xN9LRwSKE5D8ffvihuh9xb5PC46OPPlLl4Fb36oSxJekF2k+YMIH3CyGEZBgff/yxejYeOHDASiGE5BqffPKJaqft37/fKICxUzkLBnC98847xr59+zx1DmpHEsmaab9t27Y1VqxYoQKJ+vb4449bFoYxc+ZMo1OnTurfI0aMUJ0oOAM2BBXr1aunAhIk/8EoToxesW8ooyAEyY9/O9lgw9vZXCFVrQGC7A0aNFD5vLSz29krWwTXK1asaMyYMcNo3LixSpM8TvZRAnVOkSJFEsoAG7QIgq5t9+7dHbUSfe3naNeuXULQSC+HRo0aKRu3cghjm6l4aR/k9+N6GzZsqPJ4aV+pUqWkc+DZdPDgQcvqND179nT8PcOGDUvSHsecPn260h7s3LlT/Rb8jp9//lmlFTbQF6Nd7NeD3x1E36D5e/XqlaRb/fr1je+++86yiDYjR4501AmzGPx0zkteBPk7dOigNK9QoYKxbNmyQOUZVUaNGmUUK1YsScN3333X914MmxcjfO3lhTJYsmRJzpYBNMRoGl0TbFOnTg1cF6L+bNq0qfJpjM45ceKEtec0q1atUrOQ7PVMmzZtVAdSB6P9YIvzox6CnRy/W7duScfOJkaPHq1GyugaYJsyZYpx6tQpy8odv/zQqVmzZo7PQdlQPsePH7eOmPm4XfPkyZMDaTZmzBijZMmSvvnnzJljlCpVKskOG0Y4HTt2zLKMLtDKSYOJEycaJ0+etKzcgf9dcMEFqo7t3LmzcfToUWtPImPHjvU9D0aX1apVy5g0aZJRt25d5dM4fsuWLZUPux0703nuueeM0qVLJ107gmlBNAa7du0yLrzwQqUz4i8//fSTtec00K527dpJ9UCrVq1UXv1ZB1sM0sL58X/R+aKLLlJ+L8cOakc8iAmf76xYscIsX768GeskmbEOqpWayPbt28169eol2bil2xE7XFKsw2elJoL8sU6e9RfJL5zKW8oHG/7tRdD8KGev8s4FUtUaDBs2TOkoW/fu3a09iTjZxRrk1t4z9OjRI8EOG37Ltm3bLIvogXKIddxUORw8eFClQftYhyHQtQ8fPtyMPRDjesU6Fo7awk4/B4DeyDt06NCEPJIepBzC2GYa0L5ixYpJ2jdo0EBdw3fffafS3AijPcpTjifnQB5d+5kzZ5qxxkhCmtjiXl22bJlKE3r27Omovd/vLihWrlyp9I11js0DBw6otDD6Bs0PfaHbkCFDzFhHSKWJlnreqAKdKlWqpK51//79Kg06NWzYUOm0detWleaEW95GjRqpvN9++61KswN9Y41284orrlD119KlSx19PxeAhpUrV1Ya7tu3T6Whvahr6KaNW97GjRurvFu2bEnIO3LkSKV7rONonjhxwkrNbaBhlSpVlIY//PCDSoOGTZo0URpu3rzZ1zeha7FixeL1aKwjaB4/ftzaexrYtG/fPn4O0KdPH1UegwYNSioP2afXz3Xr1g30ezKVVatWmVWrVjVbt25t7t27V6VB66ZNmyqtN23a5HltyF+tWrU85589e7ZZokQJc+DAgVnj//o179mzR6Xhmps1a6aueePGjYE188sPfUqWLGlOmjTJPHnypErLJaBVjRo1lFa7d+9WukCr5s2bK602bNjgqfWYMWOUfnK/durUyTxy5Ii19wz6eb7//vv4eVq0aKHOs379+vh5+vfvbxYvXjyhHqhTp06CTTaxevVqs1atWmarVq3MXbt2xa/9ggsuUNe+bt063+saO3asWapUqbgeHTt2NA8fPmztPQ1sOnToYO7cuTN+vPvuu0/d/08//bR59OhRlSbIPrvOa9eujbcLgZvdmjVrEuyIM5EJ/kkgyM+O5D8ICqG8Ue46UkYIInkRND+Df6lrjXzo9MEe9xqCG07BPzc7t4eD2Af5DVEAwTOUw/Lly62U00Avp8Ccjmg1ffr0QNrakfxOefRy8PoNIIxtJgHt8bvtQTUENoJoj8CUaI+AlFvwzwnJj+eOBKfwe/QgoSBBxmnTpjmWE46TidojOCn66r9LAnMI1nn93iD5EWSG9rqOglv+qNGrVy91nfYAnATo9KCoHb+8gwcPTsoLf0dgC/4On4P/5XLwr3fv3kqDJUuWJGgwa9YsFVCChm4d8TB5JcjFwF8iCLJBw8WLFydpiE43AnNegRDRdcqUKaruRdAQGtuDf04gL4JhbvYIEmA/6m+nAGG20bdvX/WyYNGiRQn1QtCgnORfuHBh6Pzon1133XXqGekXJMwkvK4ZgaZUNEP+Z599Nu57uR78Q6ANL1MWLFiQoNWcOXPM0qVLm88884x57NgxKzURCehNnDhRvTBDIA8vAZyCf2HPg4BZzZo1VT3g9RuygXvvvVdd+/z58xN8DNdepkwZc8CAAUmBOR0JHk6YMEHp3LJlS7Nz585JwT8nkLd27doqKOtkL/uhs1OAUAhqR5KJzNd+MUQXxB4q/KhHIbJjxw7j008/VcNvMXVNp3r16kb58uXVkF03Us2fS6RDq4svvtjYvXu3ceONN1opzgS1i3U21RDs9u3bGw899JBx++23qykMsco5stN+g5TDF198YaUkI9redNNNVkrq6OXw4IMPqnKYO3euSutum9aKJRGC2mYa0D7WcFPTDmTarIDpWhUqVPC8B6D9999/n1btwYEDB9Q0BDvwBfgE7gcA7YsWLaq0f+CBB+LaIw3axzpGyq6wEN+GvvBt+d1A9203HwmaH1pBM5SZ/fl95513Gj/88IOxbds2KyV6iE6YRhRW5yB58eEze16sXwb/inVilL/lMvA/aIhpYnYN4ZNe+iMv6qCgebF2HHRHXZvrugtBNIQPe9WHeP7iXrjtttvSpuvs2bPVNM02bdoY/fv3V/Xz+++/r9Iw3e9EFk77Fa3xIURojee8EERrPT+eufb8eOZ65d+wYYOaTn355Zcre72sMxVcM9aPT0Uzv/xfffWV63M0lxD/wpRx+JfuH1WrVo1r5aY12hpbt25V7QYsw+CGlAnOY69z7OdBm6xMmTJG69atVT/mjjvuUGs0ly1b1nNKcaaiX7vbPfz11197TmVHe2PLli3G3XffnbYPn7z33nuq/QedUb+iDLHGItL0KcVB7Yg7Z0o8i8G6NegY4GbFQ5oUHqhU0IlDp8PeiatSpYpx3nnnqbJy+6BAqvlziUzU6tJLL1Vf9928ebN6WOL3Yb2cYcOGGXfddVdWNPTCUtjlgHVo9u7dqx6Aoi/KoV+/fsamTZvUb5JyGD58uHpY61xyySWBbTMN0R4NFjftt2/fnm/a49jQHuc/55xzVNrDDz+sygHaodwBgnxPPvmkejkFvQX8G/eLaI+1A7FmEu4X5C/s+wVrsrjpW7lyZV99g+Y/FOAjJ2vWrIls50h0cqpDRCe3OsQv7/nnn5+Ud9WqVcagQYNUQAP5cp1U6hHkxeLvbnmhv54XgUDUFdhHThNWw3SDta/wEgjBPT1wiPoZazMiYIXfgPoZ60zh2XjPPfdkZfAW9QW0RoDDrb5AENVNa6lv3PLjXvHKD61PnjypXnZ5BWcyCV0zec4LumZuz7FU8+cSdv/S20B2/0qlPWAvE/t59DLBiwXUA2vXrlXrYyPtrbfeUvVAx44ds8aPBdR1orH92itVqpQ2jd144YUX1PFvueWWhMAhdO7du7fxzTffqDKAzm+++aZaMxpBPbHV7fB8EDuse4zySFcwMspkTfDvgw8+iDupvmGEC8k88FbADsoPi6UGIUx+jNrRfQIVci6RqtbpBA8TfF1bGoUIaqBixod5/EYNZjsYtWAnP8phpe2jH6+99poxZMiQBH1RDi+++KI6P0AwFuXw2GOPKTvkE8LYZipu9wAWA85PMOIcjSMEXgWMJsTX7aFjjRo1lH7QEQsRo6y8tJf7JdO0h7723xLGt/3yS4AFb/zRyddBcAov9nIB1CFuOvn5glte3AP2dCymjjJB8E9/65/rOGmIZ1le9UdeXX90phCIRdqjjz6a9IEQ1ONeoy2iDjS0+6Ndw3SA4DcCjTgXjvvKK6+oEbA333xzwvlRLz3//PMqEAA7eTbiBQ/anf9/e2cCbUVx5vEmkT0xCbuIyCa7ZBsdt5nD4hKXuCaRfVFBR7M4xiTneCZnxhFZZIfscdRgzhhRkMdqJsYFRJbHmu1EQBZBQGURkB3Sc//f6+9at253377c+9673ff/O6fFW11f9+t/fV1d9XVVdZzvnUK1Pht7jPjDaMoePXpkjTiKAxi5V4hmsLfzhdnr6DXswzZ27NhYf2QmH6CVHVzX51kx/cavTO3zIBCFD4OgHYJyQD2AFwEYvY06I27BPwX3Ya5rLwaYfWN+9OMXv/iF8+Mf/9i59dZbMwJ10BltE+3fYGQhdH7ggQdEZ81r5gPIh2Dm/fffnxVQJP4Ur3SrGdx0aKia28MPP5z+oigpDdCwxUiYMLSD60c+9ugco+Ot23zvq6rwC3z9NOjNY1IoVOvqBgE/vDFHIzvJ1HQ5YLqBfb6wqa0IJG3evDlSOeSTtxRAoGjv3r3eL3+gPRoQxQaj+Z599lmZeoAvl6Gxotx4443yNUgzLReqfSmNxFLfDnv7G6U+z2WPDtC//du/SaP6ggsuEN1002nxSSZKHaKBB5uotnoPwG9nzpwpI2/OPfdcSSt3UI9E1d/25ai2Zh2EOhzTlJYvXy7TyvBCB4GmH/3oR9KOCZrSllRUw7B6QjUMyxMVTL1GnWIeCyMyw3RHwA8jf9CJzadeLzUK1VqfuWdjr7qj7sHLnriQzz0epFk+mmOGAKaS4v+x6fTzRx55xLn22mtz/i1xBiPCcvmXBoUKAefJVSZ+50HADyPOOnpf/44jUe5hDagVgyVLlmTVt5hSHfaiC3UEph7b0+RtNF8cXybUJrFRCsM8MaILoyR0mzBhgjiGghsZDWFSe0QZpYG36Hi74Ech9ggGonHer18/ebO7adMmb08yKVRrUhxquhwQJEInBQ9SbKgXMeQd68YVK8AYFxCkxPokYUD7Ygc50HB88MEH5Q3pzJkzM46PjjymTmBUemVlpZQR1olBGeGlRKGN1ppEfTuskRulPo9iD79es2ZN+m0uwDIe6DCaaUkkSh0CX/PTOaotfBR+C52xTlFcRvXWBKhHoupvaxbV1qwj8MIAgf5LL71Ujof2LdbGRQBw9uzZZRf8Uw3D/FE1LIbPou7GCCp9hmK62PPPP+9cd911zoEDB7xcyaRQrfWZm689pnaj3/Yv//Iv8rIsTlOm87nHgzQrRHMEAxGsueGGGyRogiB0UusIzIbI5V8IwEOrQsB5cpVJMc5TikS5h3HtxQrQI0CHdfi0vsUoyoqKCvFnTL9GGqlZaiT4p1N6wtA1V84GjBpAAxhgXSBS+/iNREJgAqM8onC29vAFPCjLKRBcqNakOGDkgE1NlANGQSPgjaURECgpR4LuAbxNLzYIoPzrv/6rdBJnzZqVfvYAjDbG6B0ECTDFCWsvgmeeeUbW8cOIH0yLj1tjB/raf3O+9XkUewRBsB4N8mKDT0NT1OcY5R/WWE0Cfh+VUJ3sdJsgW9wDmo6PfGA0NkasmtPJEBDEm/lLLrlEPjRTrlNP/TSE/52t/rA19Vf8RglpOxmjMpI+ayEIaGgHNYI0LCZYdxUvZjAaE3V0OQRfC9U6X3sEVxHwxkvKuAZU/D7qkY9msLfzRbVH3wbBafSTUUdEOV+cgVb2c0ifZ8W8P/3KtDrOU4r4fTilJq59xIgRUg9gmRf0WbAGKKlZaiT4h44Q3u6HjcbSqSvoSKGSyxd8TABgfQ50zkjtoA1YlCceaiYa4A0r40LtywlqVRrUdjnguDh+0gMjfoR1mFV7vOUslvY4B0bxIfCHL45pcE/B8w3PuSuvvFLOa4IFizFVBF+OQwMrDmBtlSB9dWHuMH0LtQcvvviitB+w+H5SfVx18qtDVKegOiSXLRY1z6f+8Vt3MekUUo/AFmvCBdlCf7XFhrIgmeSjYXWg5VIOz1DUF/oxg6D6AqOigrTW+ibIHveKbY98eF62bdtWFuSP24dSTM3sZ7epmd/IbFCofTlh+5cZ5LT9q5D71S4T+zxmmSStXjA/6mFfu/kxkEI1DgJfSUZ9zmm6tUeNKA8H0tFYU6dOzXpgwAGxngaG4GI4/tmAYeQY/bJlyxZZa8k+B8Bb70cffdT7RaoDVBhXXXWVb6D31VdfFR/QQK0fhdqj3DF9Br6U9EZ2oVqR4hBWDro+n/kl3mIDn0fHv0mTJmXXsYT2CLRhlB2mwphAe0yVKdY9AJ3xNchXXnnFeeqppzK+2huF6ghGVjfq29AXvm02ErWOCfPtQu1xT2GNuiuuuEJ0SyqqE0ZI2jqpH99xxx2+jeVcttBYbfGRCbxlRx5zw9f0MLUa09QxMhDrLpYTCD5BQ4xmsjXEyIQw/WGLOiiqLT6UgJEVa9euzciL39Aeo3vKLQgQRUP7S7zFRJ+hX/jCFxL/DFWtMeIJWpsjfKJobdrb009hjxHEtv3SpUtlFPdll10m9Xjcgim4ZjyDgjTDNd92222hmgXZY7QpNA+zB/BRBFARtImjhlFR/8I6bvAvsy7QtePwoYhCP7KhZYLz2HVOMc9TipjXbt/DuHYEAPHhjHr16nmpxeXIkSPyogfBVwYBa4mUw9cIqYJ2L7nkEtxdbufOnd3//u//dhctWuQ+/PDDbtOmTSX9oYce8nJ/Auw6dOjg9uvXzz18+LCX6k/KiSUvjoVj3nnnne6oUaPkXz3H0KFDvdykupg/f366DFINWkmbOHFilv5+aSCKvZ9fIK+WM/KXA4VqbQJNO3bsGJoHmPlSDw0vtbxBOaQaY1IOa9askbRJkyZJ2pAhQ9I6+aWZhGmr+8xzaBrKNuiYSWfBggVp7VevXi1pZ6t9p06dAvcPGzZM7KG1vaEu2rlzp9RF11xzTdZ59NjIW1FREatygr6pxllaX/zt0BJpuMYzZ85IPr80EMVedZs3b15am8mTJ0seaLtjxw5JSzLQKdX5E50qKytFB9Vg8ODB7unTpyWfX1qQLdLMfEEgb/PmzdO25cjChQvdVEdPNFy1apXoMGXKlLSGp06dknx+aVFtwe7du90uXbpIHfHSSy+J/6t9+/bt3e3bt5dlGUCDunXruk2aNHFXrlyZ1hC6DBo0yD158qSXs6oM/NIVaNy1a1fR3tyv6SinFStWyDk0DeURdLykgb5XqmMvWkMH+ODUqVNFf2hw4sQJyeeXBkz75cuXB9oD1O3XX3+91C+aN47gmuvXr+97zQMHDsy45mnTpok+ZrqfvV8++GP37t3dvn37unv37pW09evXu+eff7746JgxYxLvo4sXL3YbNGggWi1btiytFfSDVseOHZN806dPl7QBAwak00ygZc+ePcUn/fbjPA0bNsw4T65jJgVce6NGjeTaly5dKm2EGTNmiO79+/d3jx496uV0M9KPHDnipX7Cnj173F69eknZmPs1vVmzZulzaBraMEHHI9VPjQX/AB4CCPDZHSc8iJ977jkvVyboNEUN/oGgcyDgGHQOUnw0KGVudlBJ8/gFm6LY47edBxtsy4lCtEbAEBWzba+bBlGj5itnoLEdHLIDSZrHTM+l7YQJE9J5/c6BzT5PuaEBwDBNNI+tPTolpp25qfYanPLTXrdcefGc0+Bk3NAAnnk90NHsyGkeOx1EsR8+fHiWZugAHTx40MuRfKATAkamBnbwTvMEpYfZBsHgXxUahLM1NIN3micoPcxWWbdunduqVauMvOUc+FM0AGjq4heQ03zmPtU0qI4eN26c3At+58Dmd54kowE8WwO/IJ+dDqLYAwSuWrdu7bsvbmgAz7xmO/AHNJ+9L6r9yJEjs+oSbC+++GKk+jwJaADQvH4z8Ac0eGcG6uBvbdq0CawHHn/88Qy99RhmnqQH/hQNAJrXbgf+API1btw4I1i3YcMGt23btoE6jx492j1+/Lj78ssvi629n4G/2qUO/pMqiBoHU6AwjBnDT6trCpSeo1OnTl4KIYQQQgghhBBCCCHlQ60F/wghhBBCCCGEEEIIIdULV1kkhBBCCCGEEEIIISShMPhHCCGEEEIIIYQQQkhCYfCPEEIIIYQQQgghhJCEwuAfIYQQQgghhBBCCCEJhcE/QgghhBBCCCGEEEISCoN/hBBCCCGEEEIIIYQkFAb/CCGEEEIIIYQQQghJKAz+EUIIIYQQQgghhBCSUBj8I4QQQgghhBBCCCEkoTD4RwghhBBCCCGEEEJIQmHwjxBCCCGEEEIIIYSQhMLgHyGEEEIIIYQQQgghCYXBP0IIIYQQQgghhBBCEgqDf4QQQgghhBBCCCGEJBQG/wghhBBCCCGEEEIISSgM/hFCqoV169Y5Tz75pPeL1BZaDq7reinB5JOXEEIIIYQQQorFn/70J+fpp592Tp486aX4EzUfyaRGgn8ff/yx8+ijjzpTpkzxUj4BHc17773Xd1uyZImX6xNwrEWLFsn+K6+8Uv7Fb6QTQkqHV1991fnd737nHD582EshtcFrr70m5RCljswnLyGEEEIIIYQUC8R/Zs2a5Rw4cCB0MELUfCSTGgn+ofM/c+ZMZ+HChRmdyt27dztjx451fvWrX/lulZWVXs4q0Clt166dc+ONN8r+t956S/7Fb6Rj1AopDSZNmuTUqVMna1uwYIGXI5wo9ijvZs2aZeW5+uqryyp4UajWAPdip06dxG7YsGFeaiZB55k/f76Xo6pMmjdvLmldunSRND02jpvkynny5MnOpz71qVB9wjDLYOjQob5aoUz9zmHbmOXQuXNn2R9UDvnkLVXCtM/19wfZzps3L8t2+PDhvnknTpwYC53OFmj06U9/Ouu6/TTyI4o92gd+ebDBt//xj39IviSDF6R+GlRUVOTUOaotdD7nnHOy8mEbMmSIc+bMGS9n+TF16lRfbebOnZvT/87GFu2Ur33ta1JuaMusWrUq0fVILqBh3bp1szR86aWXIt3/Ue3vueeerLLq0KGDs3379rLRf9q0aU69evUyNMA2Z86cSHVAVPuRI0f63hfjxo1zTp8+7eWKB0HXPHv27EiaTZ8+3alfv34k+1GjRmX5Mnx069atZeGj0KpBgwYZ14/thRdeyOk3M2bMiGyLAUR+ZTpmzJjEjyb7yU9+4jRs2DDr2hFMi3pvvv/++84Xv/hFeYYNGDDAOXr0qLenCozMu/DCC7Pazb179xZb05eRF7EcnB//wmbPnj3Ol770JWfQoEHpY0fNR0JICV/t7Nq1y01VWm6/fv3cw4cPe6mZ6WvXrnU3bdqUsZmkOnHwELdp06ZuqiORcZxUY9a95JJL3FQHzEshtQnKEuVklreWNTb8fxhR7VHetk+lOoniJ+XiC4VqDaAVNNMNGtrgPKnOiZzn0KFDkoZjd+zYUc7z3nvvSRoYNmxYxvGw2XmSRj76+DFp0iQ39UBM65XqhLupzoq39xNQDyLfvHnzvJRgUA7mMcPKIZ+8pQa0b968eZb2nTp1kmvYuXOnpPlh2h48eFDSgmwXLFjgphoZ7oQJE9Jlo3lxD65evVrSksa6detEo759++bUyI+o9qpvRUWFr+8nHejUokUL0emjjz6SNOh00UUXiU47duyQND+CbDt37iy27777rqQB6JxqqLtz584tS52DgIYtW7YUDQ8cOCBpu3fvztAwSK8g2y5duojt9u3bfW3Rdj3nnHPcyy+/XJ4fK1euLNsygYatWrUSDffv3y9p0LBr166i4bZt20K1iWo/ZcoU0XzcuHFuqoMr+VAOdevWdfv06ZO2TTLr1693zzvvPLneffv2SRq06tatm2i1devWUK1h37p165z2ixYtcuvVq+eOHTvWPXXqVEY++Pvy5cvdM2fOSHqpY17z3r17JQ3X0r17d7nmLVu2RNYsl/20adNEtzFjxrgnT56UNGhZv359t3fv3mn7pAKt2rRpI1p9+OGHogu06tGjh2j1zjvvBGpt2n7wwQdp2549e4rt5s2b07aLFy92GzZs6D7++OPuiRMnJE3zwj/ffPPNdB2RNDZs2OC2bdtW/On9999P63TxxReLTojBBGmszJgxw23QoEG6z9C/f3/3yJEj3t4qkOe6665z9+zZkz7efffdJ/792GOPucePH5c0RfeZfZF27dq5GzduzKgrgvK9/fbbsalTapOSCf6Z6TaaD4WLzq8fsIfjktoHwSN0htGxNtEAbq7AXCH2sIGtXwAriRSqNezwkEN+3GcIVvlpp+dZs2aNl1IF7BA0ss+jx43yNyQBBM/C9DEDRjaqFQJ6Zhn45dfjRQn+AbMcwv4GkE/eUgLa4++2g28IcuTSPszWDvQhL8rGDnZp4DapQavhw4enNTKvTzV64oknQq87qr3+Ltfg34gRI0SnysrKLJ0QrINOQY3aXLbjx49P22oag3+Z3HXXXRKkXrVqVYYuGqCDhkEdwbOxRXsVwUG86EE9g+BtOQf/7r77btHQ1kADc2awzg+1X7FiRaA9AugIBpoBQsW0T3rn8Z577hF/s6/VL1jnh9rbwTvbHvnwkscOJk6dOlXKZPbs2bEJroRdM4JyhWgGew30oV5AQBA+agf5Ro4cKcd46623Eu2jo0aNkpcpy5Yty7hOv2CdTT62yIuXa2ZAEEyfPl3KZNasWaFlGmfuvfde0Wnp0qUZ9yB0atSokTt69OiswJyJBg+ff/55qVd79erlDhw4MCv45wdsL7zwQnfAgAG++XU/2tV+AUIlaj6STSw++JHqUDtbtmxx+vXrJ0NF/fjMZz7jtGrVyvtFaovUg8t58803ZfhtqlL1Uqs4//zznaZNm8qQ3SAKtS8niqHVl7/8ZefDDz90brrpJi8lG5wn9SDNeZ5UfZKelnrNNdc43/3ud53bb7/dST1MZJj3sIRO+41SDn/+85+9lGy0DL7+9a97KYVjlsN3vvMdKYeXX35Z0oZaU4pTnaPIeUsN9U1MO8CUZZPWrVvLVLqge8C0tcsNtn73z8GDB2V6gQ3yoqzh50lCfVs1Mq/P9O0gHynUvlxQnVIN6Lx1imL7l7/8pew1DgP3NDS8+OKLszTUuiBIf9iiHsnXFsvYpDqcTqqTJVOmypkoGsKHoZcfpr0uXaHocwD2yIc6HGnoM5jguffRRx857733npeSTFSrnj17itZ4ziv5aA17aG3bq9Zqf+jQIbGx/b9JkyaS3yyrUgV/P5aZKkSzXPZ//etfRSNMhYSPnnfeeVk+etttt8m+Xbt2JbY+V//q3r171r0MTVQrP61VZ9ja9UiQLfzTnn4K4uSf+WLqFHQP/+1vfwudyo72BpZJ+Na3viXT04vB73//e/H5Pn36OIMHD3a+8Y1vOG+88YakmVOKo+YjwXxS4iUM5umD66+/PqsyJKUFKhU8nNDpsMsKwdnPfe5z0rgKWpOvUHus+bJv3z7nm9/8ppeSXArVKirmeT772c96qVXY5/nqV78q6+ls27bNadSokdhhvZ2JEydKmST1QVoT5ZAPKAestYP1YfA3aTlg3UY8rE2+8pWvRM5baqj2aLAEaY+Gsp/2pm2QX8P2sPfBmu9973viv9AE5QkQOP3BD34gzybomDS0I+Knb8uWLUP1BYXalwuqk18dojoF1SG5bD//+c/XeP0TNwqtRxA0CrKF/rbt+vXrnfHjx8uzEuWWxOdiPpyNhia57M26PFfQZNOmTYFBnCSA+gJa+QWXtL7AC4UgrbW+CbKH1mr/wAMPyHp/AwcOdN59913RHi+Df/jDH8ra3HhmmoGHUsXUzG4rmJppW8EmH/soQb2NGzcm1kdt/zLrRtu/bK1snW1bW+f7779fAlcIIKH9izS8+P7Rj34kA43Qjk7ii5kPPvggrbGtU4sWLUI1LgY///nP5fi33HJLRuAQAyjuuusu5+9//7uUF8rpt7/9rawZjaCe5jXzoX7XfFj3uH///kULRiaZkq914XxouCJi37dvXy+VlDp4K2CDSqZ9+/ber3Ci2q+zPvqBD8sg0BQ2ki1pFKp1VKKcBw8TfIRHG4V4oKJi/v73v5/4MsGoA5vqKAdw8803p30eG3zefEijHH75y1/K+QGCsSiHhx56SMoBNko+eUuVIN/EYsC5iHr/YITm008/Lfq0adNGdIE+WGD4N7/5TSx0OlugkX19+fh2PvZoEKJDiPzYJkyYkOjOuAnqkCCd7HSbIFvcA362t956a4bOTzzxRNnoHISfhniWna3+sPXTHwvSYxQQFvUv91F/JtDQDgYFaegHNA2z10AiRr0gGGg+MxE4RFuyXChU6yj26KQ/+eST0ofDPYT8N9xwg7wIfuqpp+RDC3Eil3/lAvZ2Ptteg9XLly8P9NEo54o70MquG/V5ZpeBjV85+dliRsKvf/1reXnQqVMn2YcXuXg2wj/x0ZAk06NHj0g6FQpm0Jgf/fjFL37h/PjHPxadzUAdAn740Evz5s0lH0YWYmQmXiKgz6N5zXwA+RDMRDDXDigSf4pXugXwxz/+URwOhW1umLpG4gUe8hh5F4YGhPzI1/7VV1/Nyp9rqmtSKFTrqJzteRDwe+edd6TBkmRqqhwAgk3ooKNBiG3+/PlSV2L0Gabt+p0DQbzNmzdHKod88pYCaBzv3bvX++UPtEcDwga2+ZYbviyPL6JC83JAfdvsgNiE+XY+9tAW00zUt3XqOkaJwLf9yjApRKlDNChvE9VW9YPOp0+fztAZnSyMdoDOaESXG1HqAtXf9uWottAftosWLZKXlOjQnHvuuV6O8kY1tLU1MTW0iVoGmI2Ar3tiFJp2cLW/gZc7GI2SdIqhNZ65Ue0RTMHyIXEOcud7j9vkozkCG/DRnTt3ytd9TR9FMBX1fdhx4g7uwVz+pUEhG9jm0tm2xdfW0aYrp4BRlHtYA2rFYMmSJbK0kXk+TL8Om1b87W9/W6Ye29PkbTSfPX2ZhFMSSmFUH96AmtvDDz/sdOnSxctB4gKmsKA8w8AbQAR7/cjXHgEmVCi6YQTUzFTDGlMKgqYtJIVCtY5KTZ0nrtSmPggGoiEDf8dUMkxZKieijNaA9n6dbNjmU24YZYwpEQiWVFZWSn2DdSwx3QD6+zVG4476dliwM8y3C7FHkAqNTwSk8EIHvm02HpNElDoEwQo/naLaBgWaoDOmSl177bWiM6aUJVXnIKLUBaq/7ctRbaE/RpjgBQumMKHuZmelCtUwrJ5QDf3y5FMGDz74oNTfGPGux8LaUXiRjFFXSacYWucafab2GzZskPoJy4hgTU109jHVHetdIuiyf/9+z6K0yce/wvwzquZYL3vVqlWindpgGioGyuBYYceJO7gvc/kXRpFBKxvY5tLZtIV/XnDBBc7s2bOd119/XfwT8YcXX3xRgtZ2wCopRLmHoRNGoBYDBOiwDh+0xIaR7xUVFTIKGFO1y629UQqURMsDbzOwvhSmnumGqT6I+CqI5uONB4kHfqPv8NYcozyicLb2eGOGD8PgIYnKvBwoVOuo1NR54goWdbepCX0wbQQNFTSky7WODPJNvE3PRRS/xosEjIxC5x8NRqwFA5555hl54fDaa6/JdPekNmKgkX1t+fj22dqXm2/7fRhCdcrlW0G2uAdy2UJndMYPHDggowLKFT8Nce+frf6wNfVH0AMjq5999lkZaYLOF7Z///d/l3WY/vmf/1lGSWFkZjkCDe2p57aGYfh9dMHPHn0O+LmOokfg79ixY9LPyDXSJCkUqnUue/z/I4884jRs2NBZvXq1+DZ0xTRL9PcQDMQzM06+HtW/goC9nS/IHlNSMfpPfRRtjBMnTpSNj0Ire2SYPs/sMrDxKyfb9siRI85//Md/yNTelStXOpdffrloivgD/BPTruGrp06dkvxJxO/DKVE1LoQRI0bIS1182AX99HJ93tUmJV97oFGKtx/g7bffln9J6aLrVaCjhoeaCd56YyQHyhPl6keh9qa/JJ1CtYqKeR48GEyKeZ64UlPlQLJR7dGRC9Iebzn9tDdtg/watgj4YdQZRlZeeeWVkmaCUTwdO3aUhaLt48QdTEEK0lcX5g7SFxRqXy6oTn51iOoUVIfkssWoPtY/4RRaj2AduSBb6K+2YSMtFHSIcKwowYSkkI+GfuSyj1LPzJkzR0a74MVOlHKKK6gv9MMHQfUFRlAFaaX1TZA9tIY9/h8vyi677DLR3tT0zjvvlDXW/vCHP8RixLypmf2MNzXzG5kNCrVXMIISI9Xi8qGUs8H2L7MeNP3Lrz61dbZtTZ2xJBHadJdeeqk8H81jYU1KBFhfeeUVOV/S6mLzox62TubHQKI+s/KlcePGUieUw0uWUiUWyuuXW3/2s5+Js5LSBRXGVVdd5TsFUdfnC/sSb6H2eFigE4Sh36jQk0yhWkUF50HQI+g8WDsCn1pPcoM5jLBywNtalEN16gOfxxf0mjRpknift1HfRCcD0xVNoD18M+geMG39yk39Ohd2oDBJqG+rRmYjUeuYMN8u1L5cfFt1wghJWyf1xTvuuMO3sZzLFhoH2SrQGcHrL3zhC+LH5QaCR9AQo5lsDTEyIUx/2KIeiWKLKafmeou64SuF6JBhBAo6pW3btg28J5JIFA1vv/32wHXjTHt72jrsMX0vzB7PbqzF6BeoShqqFUZHQWtzhE8+WsPe/upsFK2BHcQpdXDNV1xxRaBmuObbbrstVLMg+zfeeEM0D7MHeIbCRzGCMsk+qv6Fddzse1nXjsOHIvAVaRvVGbZ2PZLL1sQOFCZNa1Mn+x6GTggA4sMZ1fVBHoy6xIsaBGoZBKwlUjdHtZMqZLdDhw5uv3793MOHD3upwek22Ic8+HOD8j733HPuf/3Xf3m/SG0yf/58KaumTZu6a9eulbSJEydK2tChQ+U38EsDUezVd8w8muZ3zKRSqNYm0K9jx46+eXCe1ANQzrNmzRpJM4+ZenhIWrnip8+kSZMkbciQIWl9/NJMzDKw9+s+1IGHDh2SNJR5s2bNpBwmTJhQluWwYMGCtParV6+WtKjawzbV8Mhpi2fONddck5WOMunUqZPoX1FRkUj9bY1wjdAIadDizJkzks8vDUSxVx3h26lOoditW7fObd68uWj7xBNPZBwziUCnVOdPdKqsrBSdJk+eLDoNHjzYPX36tOTzSwuyRZqZDzp37tzZ7du3r5vq3EgadG7RooXoPH78+MTrHMTChQvdVKdQNFy1apVoOGXKlLSGp06dknx+aVFtg0BelMHKlSvFthyBhnXr1nWbNGmS1gG6QNdBgwa5J0+e9HJW6WWnm/YrVqzwtUc9/rWvfc2dO3du2s81T/v27d1t27aVhf6LFi1yUx37tFbQYurUqaIftDpx4oTk80sDpv3y5ct97aH19ddfL3WVab979263W7du8iydPXt2um4qdXDN9evX973mgQMHZugzbdo00cdM97P3ywfdbrjhBnfOnDlpbTQffHTLli2J99HFixe7DRo0EK2WLVuW1gr6Qatjx45JvunTp0vagAED0mmwbdiwYYatX76PP/7Yvemmm6SONtPhnz179hS/nTVrVs66O65Ap0aNGolOS5cuFV+bMWOG6N6/f3/36NGjXk43I/3IkSNe6ifs2bPH7dWrl5SNuV/T0UfRc2ga9A06Hql+YhH8Axs3bkwHdtDAuvPOO91Ro0bJv/iN9LDABqlZNChlbnb5aJ6gYFNU+1z5kk4hWpvBI78NAT4Fx0CDzdyP45VrZ8XGTx8zUAQ0j5meqwzMoN6wYcOyzoFt3rx5sr9cQfAjl/aaxy8dDZEwW4BnlAYAzbx4/mjgMKkEaYSGtaJ57HQQxX748OG+vp3UoKof0AmdEfP6zeAd0DxB6WG2YMSIEVllgQ0BkXLROQgN4pm62ME7zROUHmYbBIN/VWgAz9RQA3cmms/eF8X+7rvvzrpP+vTp4+7fv9/LUR5oAM/UwQzSAc1jp4Mo9mYA0MxnBsDihAbwzGuxA39A89n7otqPHDkyqy7p3bu3u3fvXi9H8tEAoKmBGfgDGugzg3dA001bOw8wA4BmXg0c2s/OpKEBQPPa7cAfQL7GjRtnBOs2bNjgtm3b1rfNhm306NHu8ePH3Zdfflls7f0M/NUudfCfVEFUK5iqiykV+KpfqoGZHuYdlB4Epqb853/+pzN58mQvpQp84vnRRx91Us7kpRBCCCGEEEIIIYQQQmok+FcdYJ0lBAOxaCwhhBBCCCGEEEIIISSb2Ab/CCGEEEIIIYQQQggh4fATK4QQQgghhBBCCCGEJBQG/wghhBBCCCGEEEIISSgM/hFCCCGEEEIIIYQQklAY/COEEEIIIYQQQgghJKEw+EcIIYQQQgghhBBCSEJh8I8QQgghhBBCCCGEkITC4B8hhBBCCCGEEEIIIQmFwT9CCCGEEEIIIYQQQhIKg3+EEEIIIYQQQgghhCQUBv8IIYQQQgghhBBCCEkoDP4RQgghhBBCCCGEEJJQGPwjhBBCCCGEEEIIISShMPhHCCGEEEIIIYQQQkhCYfCPEEIIIYQQQgghhJCEwuAfIYQQQgghhBBCCCEJhcE/Qki1sG7dOufJJ5/0fhFCCCEkX9avX+/8z//8j/OPf/zDSyE1zYYNG5ynnnrKOXPmjJdCSOmg/nn69GkvhVQHf/rTn5ynn37aOXXqlJdCqgPV+eTJk14KKSYM/hFCqoVXX33V+d3vfuccPnzYSyGEEEJIPrz++uvO888/7xw6dMhLITUNygDtmYMHD3ophJQOb7zxhtQR9M/qRXX+6KOPHNd1vVRSbJYsWeLMmjXLOXDgAHWuBmok+IcRQM2aNXPq1KmTtU2aNMnLlcmCBQt883fs2NHZvXu3l4uUKihXv/JDuUYhqv2wYcN88wX5VRIpVGuAe6pTp05iB039CDrP/PnzvRxV93rz5s0lrUuXLpKmx8Zxk1yJT5482fnUpz4Vqk8Q+dgOHz48Ky/qxV27dnk5yo8w/XL5XJDtvHnzAm0//vhj59prrxU7PNvWrFnj7Ukm0OjTn/50XhqZ5GM/YsSIrPJQjZNcf4ApU6b46lRRUZHz2vO1Rb2MOhpaDxkyhCOaUkydOtU555xzsjScO3dupFF3e/bscbp27ZrWNGwUTq68GO133nnnybn12Ywyg02uY8cV6F+3bt0s/V966aXIox6ha7du3UTXwYMH+47QiXoejKZq3bq1pOMZizx6fJRBnEf/TJs2zalXr16WBnPmzIlUF+RjP3LkyKz7qmnTps6KFStiNZo16Jpnz54duf6E//To0UP8c9CgQaEjm+y8J06c8PZUAf9s06aNnL9Dhw6ST23gn3b+ODF9+nSnQYMGWVq/8MILkeo+6HDxxRfLM3HgwIHO8ePHvT2fAP0uuOAC0c08R58+fZwPP/ww/dzEKLS2bds6L774otO+ffu0zr169ZI6xu/YceAnP/mJ07Bhw4xrx4agW9Tny/vvv+988YtfFJ0HDBjgHD161NtTBbS78MILszTu3bu32JptE+Rt166dnB//qs5f+tKXxP/tY5MCSAlf7axdu9ZNVfTuxIkTvRTXTXVU3VRlhVJ3Ux00L7UK5EM6bGCrIB/SzeOQ0kPLu1+/fu7hw4clTcsbG/4/jKj2fv6g+WzfSSqFag30ftNt6NCh3p5PwHlSHXA5z6FDhyQNx041iOU87733nqSBYcOGZRwPm50naeSjj00+tpMmTXJTD053woQJbqrRLGm4D5Bm2pcT0K958+ZZ+qU6zKLfzp07Jc0P0/bgwYOSFsV2wYIFbqph4l5++eVy/61evdrbkzzWrVsnGvXt2zcvjZR87OHf0DXVcXFTnSkvtTyATi1atBCdPvroI0mDThdddJHotGPHDknzI8i2c+fOYvvuu+9KmjJ58mQ31VhP18+pDoybaux7e8sTaNiyZUvR8MCBA5K2e/fuDA21zvVjypQpWZqeOnXK25tJ1Lx33XWX3A+aD1uq8+lu37499G+JI9C/VatWov/+/fslDfp37dpV9N+2bVvOa4au55xzTlqrVIfRPXnypLe3CpznvPPOi3yeu+++O6OstAyi/D2lyvr160WDPn36uPv27ZM0aNCtWzfRYOvWraHXBvvWrVtHsp86dapbt25dKYsTJ05IWhwxr3nv3r2Shmvu3r27XPOWLVty+sO0adPcevXqpf1o4MCBgZr45T1+/Li39xNGjhyZ4fPY4J9R/p5SBVq3adNGtP7www/lOqB1jx49ROt33nkn9NqmT5/u1q9fP63HgAED3GPHjnl7PwH5unTp4m7evDl9jp49e0qd+/jjj2eUzahRo8SPTZ3btWuXto0bGzZscNu2bev27t3bff/999PXf/HFF4vGmzZtynldM2bMcBs0aJDWo3///u6RI0e8vVUgD+rWjRs3Sptuz549bq9evUTjxx57LMun77vvvgy/V53VnhSHWgv+AU03gw2aBudD45XED5QnyhBlaRI1eBvVHvn8/ESDWcifdArVGnYIPCE/dETAybwfFT3PmjVrvJQqYIfAk9+9jeNG+RuSAAKeYfqYwTqbqLZaPn5BvqBjlAO4dviaHYBDgC6K9kG2aJz42aIcELhCgAq+7WefJIYPH56+RlML1eiJJ54I1BdEtUenHEHCcgz8gREjRohOlZWVWToh+ACdgnTJZTt+/Pi0rQYK586dKy8WENyC5uUe/EOgDf63atWqDA0XLlwonWtoGKSRBg5feukl0RQdSmjqF9DTIFeUvEDz41ka9jfEHQTZoP/KlSuz9Eene9y4caHXrjrNmTNHXiigw4mgqh380/OsWLEi8Dx2WWiwDM8Tv/1x45577pE6ABqYdcqiRYuk4z127NjQa1T75cuXh9prwCzugT8Qds0INOXSTLWYPXu2+CeChvBPP12Q9/zzz8/K6xf8A5of/jlmzJgsn48bCLShPl22bFmG1osXL3YbNmyYFZgzgRYIHL7wwgvywgzBPPifX/DPD7VH4PGDDz7IqCMQMLvgggtE57C/IQ7ce++9ovHSpUsz6lVo3KhRI3f06NGB/gY0ePj888+LzgjoIUBtB//8gO2FF14ogUcEA02Nge6Hzn4BQlI4JbfmH9YJ27dvn3P//ffLlAcSL3bv3u28+eabMkz3oosu8lKrSD2cZKg/hvYGka891rfAsGAb5EP+JFOo1uDLX/6yDG+/6aabvJRscJ7UQzjneVL1iUw1TnXonWuuucb57ne/69x+++1O6mEiw7yHJXTab5Ry+POf/+ylZJKPLfwc/o70z3zmM5KmfOMb33D279/vpDqTXkp5oL6JaQedO3f2UqvAdK1mzZoF3gOmra09bIPun+eee078ONXYF79OMuqfqpF5vaZ/Bt3X+djj2Q++973vJV5XG9UJ04jy1TmK7V/+8pe0LeoaTLe55ZZbyk7nIFC3QkNME7M11LogzM+hKY5x6623yvMvDORFmeXKu2jRIpmaevXVVzupjppzxx13OP/3f/8n0w6HJGzaL7RDXRymP3w41Un0UrNRXW+77TaZguaHeR48L+zz4Hlh3isog/r16zt9+/Z1Ro0aJe2ZP/zhD5I2OGBKcamjGvTs2VO0Nn0witamPTS07VVD2GOdxDNnzjjf/va3ZdpvXME1v/XWW2etGcAzEO0z+FCQfyrIu3Pnzpx50bbG1Fj451133SV1BJ6jmMqJaZInYjjtV/2re/fuWfcoYgLQ+q9//Wug1tBux44d0iYuls+9/PLLTqNGjWQ6MPox0Pm1115zGjduHDiluJRRf1aN/e7hv/3tb6FT2dHe2L59u/Otb31LnlPF4Pe//730baAz6leUIdZYRJrflGJy9gS3PGoADfR985vflN9YRwmVGW5uVGYkfqBSCQpQtGrVyvnc5z4nD0CUtR/52D/44IOSjgoCjT6A4NPDDz/s3HjjjRLYSjKFah0V8zyf/exnvdQq7PN89atfde655x5n27Zt8rCEHdbLmThxotznSexsFlIOxS7Dt99+O7CDmkRUPzRYgvTbtWtXqPawDfJr2JofrFm3bp0zbtw457777hO7pIMgUZC+LVu2DNUX5GOP4Mq5554r6UmsJ8JQnfzqAdUpqB7IZfv5z3++KM+BJFNIPVJdfOUrX5Fn6ebNm6UMDx06JGtOYe1ddLjCAodxA/pjAf0g/XH9xdA/33JGGdx9993OO++8ky4DrEeFMrjzzjtzBnFKEdQX0BqBlKD6Au3pIK21vgmyh4Zqjzodz1ZoG+c63dTMbiuYmtX0x+3Qx4F/btq0SfrN8E98lEb9M44BV9u/TL+x/as62ro4NuIS8FmUNc6PFwvQeePGjbKmOcr5f//3f0Xn/v37x07nDz74IK2xXqPSokWLGtF47969GRoD6Iwg9t///ncpa+j829/+VtaMRvCvWEFGUsPBPwRlUMi64TeCAjrqCAW9detWcTw4BYkveCtgg5sci6VGIYo9HnzPPPOMs2XLFmnMwae+/vWvO0OHDnV+85vfeLmST6FaRyXKefAw+dWvfpVuFOJ+xn39/e9/P3R0YRLAaAKbqOUQxVY7JxihgoenCTr+aPyVK0G+iUWDc5HP/YMFv5Efo0C0wVIO4Jrt643q2yCXPRqZCFChvDDyD4EN5NdtwoQJoaMqkgLqgSCd7HSbIFtomsuWVOGnIZ5lUfQvNqjvf/7zn0tgAeCFGjr3uD/QzklS8E+B/vZ1Qf9i+zBGcEU5D8rgZz/7mZQB0lEGaM8koQwK1TqXPep0BFKx2P9DDz2U9YEVvESL2+jVqH5TU8A/f/rTnzpNmjSR82sdgVk3N998cyyD0wq0tv9+fZ5V532HwQrwS4wg1qAedJ4xY4a0sU2dv/Od74jOcR3Vqh+TMakJjfERK4yaxuh3M6CHgB8+9IIAK3TGyELo/MADD4jODP4Vj+or3YggAIjRWiZoaMEBSfxABw5vTcLQgJAf+dojoIRgXzlSqNZROdvzIOCHN+YIzCaZQsohH1sEVrEcAn4j2IeHo24YoYA3aeUGOhe5rht6oQFhA9t8ym3hwoXOs88+Kw3rcnk+qX+Gvf0N8m2Qrz1mA2CaR2VlpQT7MNISDcEf/vCH0k5I6qjWKPWABh5sotr63QOkiih1gepfGz6IWQ4YdYIvTqK+Txqqf5i26sOF6B/leRF0HgT8UAYIZsW5DArVWjWMao/pkajT8dIS0wjXr18vbcJHHnlEvvYeNrWwVIhaPxTqn4WAdglmftTGi4pioqPCwnTUoFCxwfRetPGuvPJK+RqtX/AUAT+MTOvoff07jkS5h6ExRgcWG0zthcaXX365aBwUOMVSAZh6bE+zJ8WhRhXFKD84m25wwA4dOjjDhw+XRr4S1pkgpU2UEUhhwd187OEzWJsAnfK1a9eKTyEQOHPmTFknB28ek0yhWkelps4TVwrRJ19bvEFfs2aN+L3Sr18/aVybaeUCOhG5rhv6YTqpDWyjao8GKTrgWEcHIz6S2AH3Q/0z7HrD7v187bHcB0ZyY/kA2GAaCNY5QwAQUx7DGqtxJko9gLfxZ1uHwNbvHiBVRKkLVP9yufdrEtU/TFv14UL0j/K8KMZ5SplCtVYNo9pj/S5MS73sssukE4812bCWIl5mzpkzJxbBv6j1Q5L9pqaAX+TyLwTgoXUxwZIAP/jBD+T8Tz75ZM6/Ic5EuYehMWYaFRNM6caLXIzw+/Wvf50e4UdqnloNp+pIFrxRwRt/NKzQEUC0GTciiS9+C+UjoIvAbhRy2SOwh4oalRPWFdH1/TDdF0HmP/7xj84vf/lLSUs6hWodlZo6T1yBH9pE1ScfW/1Ii75EeeWVV+QtKOrRLl26lOXDNMg38TY+F1H8Gh/5wChWvLFEBwYaY8PoVrxB/ad/+id58ZDU4BQ0sq8tn3s/qj1+22/0dU0lvCxM+gsd1ANBOuXyrSBb3AO5bEkVfhrC56LoTwoH+tvT+6F/sX3Y7+MM1XGeUqZQraPa47c9Is5euy0u0G9qDmhtB4b1eWaXQaEg3oCPFOJftPEQhyiHdrTfh1OqS2ME/q699lppx2G5Lgz84oi+2qPWlUdnVcHaCddff306GEjih65LhqlI9kNdF1vGSAWUtR9R7dFowPSBq666SoLIJvj6EioWfDwmTg2LfClU66iY58GDwaSY54krhZRDscoQo6LQYMGIqXJC9fMLDKl+eMsZpj1sg/watkGj2mzwhTocK0loJ81PX12YO0hfENUeZQE/L9e3wKqTXz2gOgXVA7lssVB9OdfPUSikHiGFA/2DAvzQP+hjIPnCcq6qL/QDFUH1BdrUQRpofRNkDw1hn6Q63dTMbiuYmkVtK5BgbP8yg6qmf8E/i+FbR44ccUaOHCnHrqioSI9QTTLmRz3gz6bG5sdAiqkx1slGHYvRvldccUWs16NMArXu4S+88IL8q0FATPvB8OqxY8dmTAVW4KyzZs3yfpFSAxUGAnIIzGGov4n9dWc/CrUH2ohLeoenGFpFAefBGhhB58HIJ3xxuVw77mHlgPVuUA5B+hRiq6CexNR3HAfHKyfUNzds2CDrMZlAP/hm0D1g2vppr34NMN0ab0LRSDI3fO0N0ydWr14tIwNR5yQJ9U/VyGwkah0T5p/52GMBeYyw0iUcFPyGttddd11i63PVCSMkbZ3UF++44w7fTkkuW2gcZEuqQKACGmI0k63h66+/Hqo/KRzoj7o4TP/bb7+94A6jeR48L+zzYEQ9FvpPcsdUNcDIKmhtjvCJorVpDw1te2io9vhoA9YOQx1u5kObBXU6RlsVe/pmdYBrRsAiSLNy8JuaQv0L673Z9+iSJUtEa3woohgf2UBQCl/rxUARfDjl0ksvLYs6Xv1ZNTb9GRojAHjLLbc49erV81LPHmiMATmY6o+PeSC4yvukBEjdWNVOquJ3mzZt6k6cONFLcd358+fjjpatX79+7uHDh709ruSz9+3atcvt0KGDpA0dOtTLSUoRLVuUOcoeaJmaZeeXBqLYwyfgG7a96Sc4TtIpVGsTaNexY0ffPDhPqoMu51mzZo2kmcdMPTwkrVzx02fSpEmSNmTIkLQ+fmlRbeHzV199tTtv3jz5DTQffP69997zUsuLBQsWpPVbvXq1pEXVHrapxl5O2yCQt1mzZmnbJGJrBE1w3UiDRmfOnJF8fmkgqj3qn06dOkmdUlFRIfnUFv69Y8cOyZdUcK2pRrHoVFlZKdc/efJkuf7Bgwe7p0+flnx+aUG2SDPz2UDzzp07SzkE5SkXFi5c6KY6lKLhqlWrRMMpU6akNTx16pTk80sz2b17t9ulSxfR1G+/ST55kw70r1u3rtukSRN35cqVaf1RJoMGDXJPnjzp5awqA790Bbp27dpVysjeb55nxYoVoedJKqmOuJvq2Kc1QB08depU0QUanDhxQvL5pQHTfvny5YH2KIdu3brJ83T27NlSx6ht+/bt3a1bt4r+cQB/d/369X2veeDAgRn6TJs2Ta7RTlegS/fu3cU//fabmHmPHz/upSabxYsXuw0aNBCtly1bJlpDU+gPTY8dOyb5pk+fLmkDBgxIp5lAu549e4pP+u0fNWqUlB/aHPbWrl07d/PmzbHxz3yBxo0aNRKNly5dKvfmjBkzRPf+/fu7R48e9XK6GelHjhzxUj9hz549bq9evaRs7P333Xef3AtBGm/cuDHdBiQ1R40G//wKHwEEP4JsgvKT0kKDUuZmB5U0T1CwKZe9GQA0N/iNBsLKgUK0hk4IXtj2upn3G46BRpy5H8dL6sMxX/z0QafO1EfzBKWH2YJhw4Zl5cM9cOjQIS9HeYLgRy79NI9fOoIpYbZBlEPwDwRpZDbaNI+dDqLYg3Xr1rnNmzfPyFcOgT8FOiGwZF4/On1mYE7zBKWH2QJo3KJFi4x85jZ+/PiybYxrANDUAxqagTnNY6ZD05YtW2bYmRs01XJA3latWvnmw2bmLTc0MGfq4ReQ03zmPtXVfg7oNm7cuLSuUc+TZDQIZ2vgF+Sz00EUe7B+/Xq3devWGeUSt8CfogFA85r9Anyaz9znp4O5jRkzJu1/yHv++edHyptUNABoXrcZ+API07Bhw4zgH7Rr06ZNoHaPP/64lMnHH3/s3nTTTVnPTHPTvElFA4DmNduBP4B8jRs3zgj+bdiwwW3btm2gzqNHj3b37dvn3nzzzVnPVHN77LHHyiaoXUrUwX9SBUAIIYQQQgghhBBCCEkYXMCEEEIIIYQQQgghhJCEwuAfIYQQQgghhBBCCCEJhcE/QgghhBBCCCGEEEISCoN/hBBCCCGEEEIIIYQkFAb/CCGEEEIIIYQQQghJKAz+EUIIIYQQQgghhBCSUBj8I4QQQgghhBBCCCEkoTD4RwghhBBCCCGEEEJIQqnjpvD+Pyd16tTx/o8QQgghhBBCCCGEEFLqcOQfIYQQQgghhBBCCCEJJa+Rf4QQQgghhBBCCCGEkPjAkX+EEEIIIYQQQgghhCQUBv8IIYQQQgghhBBCCEkoDP4RQgghhBBCCCGEEJJIHOf/ASanmZcdjhm0AAAAAElFTkSuQmCC\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003eNote: *: p\u0026lt;0.05, **: p\u0026lt;0.001\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe association between traditional culture and mental health status of students\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAjusted \u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95.0% CI of \u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.003, 0.214)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.394, -0.016)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.175, -0.028)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.475, -0.099)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.346, -0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.629,-0.413)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.007, 0.315)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.015, 0.354)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePRTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.358, -0.046)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNRTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.067, 0.575)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNRTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.091, 0.655)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.016, 0.275)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.340, -0.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNRTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.057, 0.556)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.125, -0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.01, 0.259)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNRTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(0.035, 0.533)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(-0.301, -0.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Only significant results were shown here. *: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we conducted an in-depth analysis of the current state of traditional culture education among college students and its association with mental health conditions. The survey findings underscore the complex relationship between traditional culture exposure and mental well-being among students. The survey revealed that although most students hold positive attitudes towards traditional culture, recognizing it as broad and profound, their understanding of its deeper connotations is relatively limited, and there is a marked insufficiency in the reading of traditional classics, with over half of the students showing extremely low annual reading volumes. This observation highlights a gap between appreciation and engagement, suggesting that while students may value traditional culture, they lack opportunities or motivation to delve deeply into its study.\u003c/p\u003e \u003cp\u003eMoreover, there are numerous issues with the methods and content of traditional culture education, such as monotonous teaching content, overemphasis on theory, and boring classes, which require urgent resolution. These pedagogical issues not only detract from the learning experience but may also hinder the potential therapeutic benefits that traditional culture could offer to mental health. Despite these shortcomings, students still have a strong demand for traditional culture education, preferring to engage with it through elective courses and campus activities, particularly knowledge competitions, drama performances, and exhibitions of etiquette, dance, and costumes. This indicates a clear preference for interactive and experiential learning formats over traditional lecture-based instruction\u003csup\u003e[ 8]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSimultaneously, the student population faces widespread mental health challenges, with depression, pessimism, and dissatisfaction with life prevalent, affecting a considerable portion of students. Feelings of failure, guilt, and self-disappointment are common, indicating low self-efficacy. Social withdrawal and indecisiveness are also frequent, reflecting impaired interpersonal skills and decision-making abilities. These symptoms collectively suggest a pervasive sense of disempowerment and a struggle with personal agency among young adults navigating the academic environment. High incidences of work difficulties and fatigue, along with decreased appetite and distorted body image, further highlight the potential impacts of mental health issues on daily functioning and physical health of college students. Such manifestations not only disrupt academic performance but also pose serious risks to overall well-being, including potential long-term health consequences \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese findings emphasize the multidimensionality and complexity of mental health issues among college students, suggesting that educational institutions and society at large need to adopt comprehensive measures to provide targeted psychological support and services. Given the intricate interplay between academic pressures, social dynamics, and personal development, a holistic approach that integrates mental health education, counseling services, and community support networks is imperative. This approach should aim to foster resilience and coping strategies among students while addressing systemic factors that contribute to mental distress.\u003c/p\u003e \u003cp\u003eTraditional culture plays a significant role in this process, with its positive influence not to be overlooked. Under the influence of globalization, foreign cultures have strongly impacted the values of college students, leading to confusion about cultural identity. In a materialistic society, students often pursue comfort at the expense of spiritual pursuits. What appear to be cognitive and behavioral problems are rooted in differences in cultural backgrounds \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Cultural dissonance can lead to a sense of alienation and disconnection from one's heritage, which may exacerbate feelings of uncertainty and identity crises among students. Research has shown that culture can successfully alter individuals' psychological processes and behavior patterns \u003csup\u003e【11\u0026ndash;14】\u003c/sup\u003e. Therefore, the construction of healthy psychology among college students should be based on the context of Chinese culture. To truly enhance the effectiveness of mental health education among college students and play its important role, the essence of traditional culture must be utilized\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThese research results indicate that traditional culture is not only a bridge between the past and the present but also a valuable resource for shaping modern mental health. The preliminary analysis of this study also reveals the correlation between different dimensions of traditional culture education and mental health indicators among college students. For example, positive cognition of traditional culture shows a significant negative correlation with depression, pessimism, and low satisfaction, while negative cognition shows a significant positive correlation. This suggests that fostering a positive attitude towards traditional culture may serve as a protective factor against mental health issues, whereas a negative perception might increase the risk of experiencing such problems \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe impact of traditional culture education on mental health is multifaceted and can achieve its effects through multiple mechanisms. Cultural confidence manifests as a nation's deep understanding and high recognition of its own culture, representing full acknowledgment of the value of its culture and firm belief in its future development\u003csup\u003e【7】\u003c/sup\u003e. By instilling a strong sense of cultural pride and identity, traditional culture education can bolster students' self-esteem and confidence, equipping them with a robust foundation for personal growth. Enhancing students' literacy in traditional culture can strengthen this cultural confidence, further enhancing individual self-esteem and confidence, improving psychological resilience, and enabling them to more effectively cope with challenges and pressures in life, thus promoting mental health and reducing the occurrence of psychological issues such as anxiety and depression.\u003c/p\u003e \u003cp\u003eChinese culture, with its long history, carries unique national spirits \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, providing rich guiding principles for daily life and helping individuals understand themselves, reflect upon themselves, and pursue the essence of life, enriching their inner world and resisting the influence of negative thoughts and values. The wisdom embedded in Chinese traditional culture, such as the Confucian emphasis on social harmony and the Daoist philosophy of living in accordance with nature, can foster a sense of balance and harmony within individuals, contributing to their emotional stability and well-being. The excellent thoughts contained in Chinese traditional culture continue to influence each generation \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. With the continuous accumulation of cultural knowledge, personal inner qualities are elevated, better showcasing the unique charm of Chinese traditional culture. As students immerse themselves in the study of traditional texts and practices, they not only gain historical insight but also develop a deeper appreciation for the timeless values that underpin their cultural heritage. This process helps in building a stronger sense of personal identity and belonging, which can be a protective factor against mental health issues.\u003c/p\u003e \u003cp\u003eThe virtuous qualities embodied in traditional cultural literature can cultivate the emotions of college students and shape positive attitudes toward life, holding significant value for their holistic growth. Excellent literary works transcend the limitations of modern life, serving as a microcosm of traditional culture \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. These works not only enrich students' intellectual lives but also serve as a source of moral guidance and inspiration, offering timeless wisdom that can be applied to contemporary challenges. These works can inspire and guide learners, optimize their moral qualities, and help them establish lofty life goals. Influenced by exemplary figures, college students become more demanding of themselves, forming positive attitudes, thereby gradually cultivating healthy mental states.\u003c/p\u003e \u003cp\u003eStudies have shown that integrating traditional culture into the teaching of Chinese language and literature can improve students' thinking patterns and behavior, enhance their humanistic literacy, and enrich their spiritual world \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. By incorporating elements of traditional culture into the curriculum, educators can create a learning environment that promotes critical thinking, ethical reasoning, and a deeper appreciation of one's cultural heritage. This holistic approach can contribute to a more balanced and resilient student population. Our research also shows that classic reading has a significant negative correlation with negative psychological states among college students. This indicates that engaging with classical texts can serve as a buffer against psychological distress, fostering a sense of calm and perspective that is beneficial for mental health. These findings further confirm the importance of traditional culture education in promoting mental health, suggesting that a curriculum that includes traditional culture can play a pivotal role in supporting the psychological well-being of students.\u003c/p\u003e \u003cp\u003eMultivariate regression analysis eliminated the effects of confounding factors, providing a more precise assessment of the relationship between traditional culture and mental health. The results show that the relationship between dull classroom environments and depression, work difficulties, and fatigue is more pronounced, indicating that the dullness of teaching methods may directly affect students' mental health status. This suggests that uninspiring classroom dynamics can exacerbate feelings of isolation and disengagement, contributing to a decline in mental well-being. Furthermore, drama activities have a positive effect on reducing depression, pessimism, and fatigue, while classic reading has a positive impact on reducing feelings of failure, guilt, and work difficulties. These findings indicate that active engagement with cultural practices can mitigate negative psychological states, underscoring the therapeutic potential of participatory cultural activities. These results also reflect the existing problems in our current traditional culture education. Traditional culture learning is considered the task of humanities departments alone, with students from other disciplines often showing indifference. There is a misconception that traditional culture is only relevant to those studying the humanities, leading to a lack of interest and engagement from students in other fields. Traditional culture education is only set up as optional public courses within schools, often being phased out because literature courses are perceived as useless for employment. This neglect stems from the perception that such courses do not contribute directly to career readiness, despite their intrinsic value in personal development.\u003c/p\u003e \u003cp\u003eHowever, classroom teaching often simplifies cultural education into rigid knowledge transmission, lacking vitality and appeal, marginalizing the rich humanistic spirit and intrinsic values of traditional culture, making it difficult to evoke a deep resonance within students and their perception of the meaning of life. Teaching methods that focus solely on rote memorization fail to capture the essence of traditional culture, which is meant to inspire reflection and foster a deeper connection with one's heritage. Thus, there is a significant positive correlation between dull classroom teaching and students' negative psychological states.\u003c/p\u003e \u003cp\u003eAlthough this study has revealed a significant correlation between traditional culture education and the mental health status of college students, the specific mechanisms of action still require further exploration. Traditional culture education may positively impact mental health by enhancing cultural confidence, improving social skills, and increasing self-efficacy. Understanding how these mechanisms work together can provide insights into the holistic benefits of traditional culture education, such as fostering a sense of belonging and identity, which are crucial for mental well-being.\u003c/p\u003e \u003cp\u003eFuture research should focus on these potential mechanisms to gain a more comprehensive understanding of the vital role of traditional culture education in promoting the mental health of college students. Investigating the pathways through which traditional culture education influences mental health can inform the development of more effective intervention programs tailored to the needs of today's students. Therefore, strengthening traditional culture education, improving students' positive cognition and understanding of traditional culture, has significant practical implications for improving the mental health status of college students. By emphasizing the importance of cultural literacy and engagement, educational institutions can create supportive environments that enhance mental resilience and foster a healthier student community.\u003c/p\u003e \u003cp\u003eThis study uses Chinese traditional culture as the main entry point, extracting its excellent qualities to understand the impact of integrating traditional culture into literature teaching on the mental health of college students, analyzing the relationship between the integration of excellent traditional culture into quality education and the mental health of college students. By focusing on the positive attributes of traditional culture and their incorporation into modern educational settings, this study aims to bridge the gap between cultural heritage and contemporary mental health needs.\u003c/p\u003e \u003cp\u003eThe innovation of this study lies in two aspects. First, from the perspective of the mental health of college students, this study examines the impact of the excellent qualities of traditional culture on the mental health of college students, going beyond theoretical research to gain new insights. This approach seeks to translate abstract cultural values into tangible mental health benefits, offering a practical framework for educators and policymakers. Second, focusing on the combination of college students' mental health and traditional culture, primarily based on the positive elements of traditional culture, this study provides a new perspective on the research of healthy psychological qualities from the viewpoint of traditional culture. By highlighting the synergistic relationship between traditional culture and mental health, this study contributes to the growing body of evidence that supports the integration of cultural elements into holistic education models.\u003c/p\u003e \u003cp\u003eUsing quantitative analysis methods, this study obtained the significance of factors affecting the mental health of college students, tailoring education to individual needs to foster mental health among college students. The application of statistical techniques allowed us to identify key variables that correlate with mental health outcomes, enabling personalized educational strategies that address the diverse needs of students.\u003c/p\u003e \u003cp\u003eHowever, this study also has certain limitations. Firstly, the design of this study was cross-sectional, making it difficult to draw specific causal relationships. A cross-sectional design limits our ability to infer causality, and future longitudinal studies are needed to explore the temporal dynamics of these relationships. Thirdly, this study only explored several representative dimensions preliminary and selected several topics as representatives for measurement, which is quite limiting. To fully understand the breadth and depth of the impact of traditional culture on mental health, future research should employ a more comprehensive framework that encompasses a wider range of cultural dimensions and thematic areas. We should deepen our understanding of traditional culture, create more dimensions, and construct more rigorous themes and detailed and in-depth research. Enhancing the depth and breadth of research will provide a richer tapestry of insights that can inform more effective interventions and educational policies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, despite certain limitations, our research results demonstrate that traditional culture education may benefit the mental health of students in vocational colleges. Our findings suggest that integrating traditional culture into the educational curriculum can have a positive impact on the psychological well-being of vocational college students, fostering a greater sense of cultural identity and self-worth. Further large-scale randomized controlled studies are needed to explore the relationship between traditional culture education and the mental health of students in vocational colleges. Such studies would provide a more definitive understanding of the causal links and help refine educational strategies that leverage traditional culture to support mental health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDE \u0026nbsp;Depression\u003c/p\u003e\n\u003cp\u003ePE \u0026nbsp;Pessimism\u003c/p\u003e\n\u003cp\u003eSF \u0026nbsp; Sense of Failure\u003c/p\u003e\n\u003cp\u003eDL \u0026nbsp; Dissatisfied with Life\u003c/p\u003e\n\u003cp\u003eFG \u0026nbsp; Feeling of Guilt\u003c/p\u003e\n\u003cp\u003eSD \u0026nbsp;Self Disappointments,\u003c/p\u003e\n\u003cp\u003eNT \u0026nbsp;Negative Tendency\u003c/p\u003e\n\u003cp\u003eSW \u0026nbsp;Social Withdrawal\u003c/p\u003e\n\u003cp\u003eHE \u0026nbsp;Hesitancy\u003c/p\u003e\n\u003cp\u003eBID \u0026nbsp;Body Image Distortion\u003c/p\u003e\n\u003cp\u003eFDW \u0026nbsp;Feeling Difficulties at Work\u003c/p\u003e\n\u003cp\u003eFA \u0026nbsp;Fatigue\u003c/p\u003e\n\u003cp\u003eDA \u0026nbsp; Decreased Appetite\u003c/p\u003e\n\u003cp\u003ePRTC \u0026nbsp;Positive Recognition of Traditional Culture\u003c/p\u003e\n\u003cp\u003eNRTC \u0026nbsp;Negative Recognition of Traditional Culture\u003c/p\u003e\n\u003cp\u003ePTC \u0026nbsp;Prospects for Traditional Culture,\u003c/p\u003e\n\u003cp\u003eVTCK \u0026nbsp;Volume of Traditional Cultural Knowledge\u003c/p\u003e\n\u003cp\u003eCR \u0026nbsp;Classic Reading,\u003c/p\u003e\n\u003cp\u003eCSTC \u0026nbsp;Contemporary Significance of Traditional Culture\u003c/p\u003e\n\u003cp\u003eOCTC \u0026nbsp;Offering Courses on Traditional Culture\u003c/p\u003e\n\u003cp\u003eETCC \u0026nbsp;Effectiveness of Traditional Culture Course\u003c/p\u003e\n\u003cp\u003eFTCC \u0026nbsp;Feeling of Traditional Culture Course\u003c/p\u003e\n\u003cp\u003ePETCCA \u0026nbsp;Positive Evaluations of Traditional Culture Campus Activities\u003c/p\u003e\n\u003cp\u003eNETCCA \u0026nbsp;Negative Evaluations of Traditional Culture Campus Activities\u003c/p\u003e\n\u003cp\u003eTCKC \u0026nbsp;Traditional Culture Knowledge Competition\u003c/p\u003e\n\u003cp\u003eDrama \u0026nbsp;DR\u003c/p\u003e\n\u003cp\u003eCC \u0026nbsp;Cultural Confidence\u003c/p\u003e\n\u003cp\u003eUFC \u0026nbsp;Understanding of Foreign Cultures\u003c/p\u003e\n\u003cp\u003eIFC \u0026nbsp;Impact of Foreign Cultures\u003c/p\u003e\n\u003cp\u003eBoring Class \u0026nbsp;BC\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSu Xiufang is the co-first author. This study was supported by the Guangdong Education Science Planning Project (2024GXJK758).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been approved by the Ethics Committee of Shunde Polytechnic. There is no conflict of interest among all the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen, X., Huang, X. \u0026amp; Chang, L. Neural correlates of Confucian relational processing: An fMRI study of social dilemma resolution. \u003cem\u003eCult. 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Improving 21st-century teaching skills: the key to effective 21st-century learners. \u003cem\u003eRes. Comp. Int. Educ.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (1), 99\u0026ndash;117 (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Traditional Chinese Culture, Mental Health, Students, Higher Vocational Colleges","lastPublishedDoi":"10.21203/rs.3.rs-6500034/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6500034/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims: \u003c/strong\u003eThe mental health of students in higher vocational institutions has become a critical concern, with traditional Chinese culture potentially offering solutions through its positive psychological influences. This study investigates the relationship between traditional Chinese culture and the mental health of vocational students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA random sampling approach was employed to select 432 participants from eight classes of the 2022 and 2023 cohorts at Shunde Polytechnic, representing diverse disciplines such as literature, engineering, and science. Data were collected via an online survey using the platform Questionnaire Star, complemented by interviews for quality assurance. The Beck Depression Inventory (BDI-13) was used to assess mental health status. Results revealed that most students had only a superficial understanding of traditional culture, partly due to monotonous teaching content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Mental health assessments revealed a high prevalence of psychological distress among students, including symptoms of depression and pessimism. Further analysis demonstrated an inverse relationship between positive cultural identity and lower levels of psychological distress, while active engagement with culture was linked to better mental health. A multivariate linear regression analysis indicated that participation in cultural activities, such as drama, was associated negatively with depressive symptoms, and that engagement with classical literature was linked to a mitigation of pessimistic attitudes and other psychological concern.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eIt is evident that strengthening traditional culture education and enhancing teaching methods through innovative approaches significantly may help promoting the mental health of students.\u003c/p\u003e","manuscriptTitle":"Multidimensional Cultural Engagement and Mental Health in Chinese Higher Vocational Students: A Cross-Sectional Study with Implications for Education and Public Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-23 10:51:38","doi":"10.21203/rs.3.rs-6500034/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-19T17:14:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-18T13:02:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15337994194457751061558274247136167128","date":"2025-08-14T06:46:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T07:31:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179096754483509853762284252636801992154","date":"2025-08-12T06:50:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51664663522943122860022534893949784217","date":"2025-08-12T06:48:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-12T06:19:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-11T07:37:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-23T04:26:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-21T10:06:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-22T03:52:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7204ef20-1a40-426f-a42b-704eb1b061cf","owner":[],"postedDate":"April 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47476415,"name":"Biological sciences/Psychology"},{"id":47476416,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-12T16:06:29+00:00","versionOfRecord":{"articleIdentity":"rs-6500034","link":"https://doi.org/10.1038/s41598-025-32007-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-06 15:59:15","publishedOnDateReadable":"January 6th, 2026"},"versionCreatedAt":"2025-04-23 10:51:38","video":"","vorDoi":"10.1038/s41598-025-32007-9","vorDoiUrl":"https://doi.org/10.1038/s41598-025-32007-9","workflowStages":[]},"version":"v1","identity":"rs-6500034","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6500034","identity":"rs-6500034","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}