Assessment of Exhaled Volatile Organic Compounds (VOCs) in Smokers vs. Non-Smokers for the Early Detection of Chronic Obstructive Pulmonary Disease (COPD)

Assessment of Exhaled Volatile Organic Compounds (VOCs) in Smokers vs. Non-Smokers for the Early Detection of Chronic Obstructive Pulmonary Disease (COPD) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of Exhaled Volatile Organic Compounds (VOCs) in Smokers vs. Non-Smokers for the Early Detection of Chronic Obstructive Pulmonary Disease (COPD) Sevtap Düzgünçınar, fathi shaheen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9029272/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chronic Obstructive Pulmonary Disease (COPD) is a major global health concern, and early diagnosis is important to improve outcome. Volatile organic compounds (VOCs) analysis in the exhaled breath has been a much-promoted, non-invasive method under review. The objective of this study was to determine whether exhaled VOCs are useful as biomarkers for the early diagnosis of COPD by evaluating VOC profiles in COPD and normal controls with various smoking statuses (non-smokers, ex-smokers, and active smokers). In a case-control study with 84 patients with COPD and 84 age- and gender-matched healthy controls who were stratified by smoking status, exhaled breath samples were analyzed using GC-MS for VOC identification and quantitation. Quantitative results were expressed as mean ± SD and analyzed with independent t-tests, chi-square tests, Pearson correlations, logistic regression, and ROC curve analysis. COPD patients had higher concentrations of some hydrocarbons and aldehydes (e.g., hexane, ethane) than controls (p < 0.001). VOC levels were higher in active smokers compared to non-smokers and ex-smokers. VOC levels correlated positively with the level of smoking intensity (r = 0.68, p 0.85). In Conclusion, VOC profiling during exhalation can discriminate patients with COPD from healthy subjects and provides insight into the metabolic impact of smoking. Such findings justify the incorporation of VOC analysis as a diagnostic and screening tool for the assessment of early COPD detection and monitoring. The future will aim to translate these biomarkers into larger, longer-term cohorts. Pulmonology COPD volatile organic compounds exhaled breath early diagnosis smoking biomarkers Figures Figure 1 Figure 2 Figure 3 Introduction Chronic Obstructive Pulmonary Disease refers to a progressive and debilitating respiratory illness featuring obstructed airflow and chronic inflammation of the airways and lung parenchyma. It gives rise to one of the foremost causes of morbidity and mortality worldwide, exerting a significant negative effect on the quality of life of sufferers and heavy pressure on the healthcare systems. Despite the tremendous growth in diagnostic tools and therapeutics, an early diagnosis of COPD is still difficult when the condition begins insidiously and its onset may overlap with common symptoms shared by other respiratory ailments [ 1 , 2 ]. Exhaled air analysis has developed and remains the fastest-growing wave of non-invasive pulmonary assessment. Of all the components of this air, VOCs have received more attention than any other due to their possibility of serving as biomarkers. VOCs have a very low molecular weight and result from metabolism and inflammation fighting mechanisms acting inside the human body. The lung, being the primary site of interfacing with environmental agents and systemic inflammation, expels a very high number of VOCs that can be trapped and analyzed to reveal the pathological state. [ 3 , 4 ]. More than 1,400 VOCs have been reported in human breath, including hydrocarbons, alcohols, ketones, aldehydes, sulfur-containing, and nitrogen-containing compounds. Such VOCs can undergo changes in various physiological and pathological states, including smoking, inflammation, oxidative stress, or microbial colonization, all implicated in the pathogenesis of COPD. Studies show that VOCs are generated differently in patients with COPD compared to those in healthy subjects, raising a possibility for their use in detection and monitoring of the disease [ 4 ]. An attempt is made to establish whether exhaled VOCs are useful in differentiating between smokers and those who do not smoke, as well as their usefulness in an early diagnosis of COPD. By comparing the concentrations of VOCs in various groups of subjects with pulmonary function and systemic inflammation markers, we can try to understand better their diagnostic accuracy and feasibility for implementing the VOC tests in clinical practice. Study Design & Methods Study Type: This study is a retrospective case-control study to investigate any relationship between exhaled VOCs and the presence of COPD in smokers versus non-smokers. Study Location and Setting: Participants were recruited from the Pulmonology Outpatient Clinic at Alexandria University Hospitals, a tertiary care center offering highly specialized respiratory care. Data collection was done under the supervision of the institutional review board, complying with all ethical standards. Study Population: The target population includes patients diagnosed with COPD as well as healthy control individuals. COPD Group: Those recruited had a full diagnosis of COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria. Control Group: Healthy age and gender-matched individuals with no history of COPD, systemic infections, atopy, or autoimmune diseases. Controls were further divided into: Non-smokers, Ex-smokers, and Active smokers. Sample size: Sample size will be calculated according to the following formula that compares two means based on the standardized measure of effect: Cohen's d. The formula is: n = 2×((Zα/2 + Zβ/2)/d)2 Where: n = sample size per group Zα/2 = 1.96 for a 95% confidence level Zβ = 1.28 for 90% power (β = 0.10) d = standardized effect size (Cohen's d) Assuming a moderate effect size (d = 0.5): n = 2× (0.51.96 + 1.28)2 = 2× (6.48)2 = 2×42.0 = 84 Therefore, approximately 84 participants per group (28 in each subgroup) are collected, resulting in a total sample size of 168 individuals. Criteria of selection: Inclusion criteria: Adults aged 18 years and above. Smokers: Individuals who have smoked at least 10 pack-years. Ex-smokers: Individuals who quit smoking at least 6 months ago and had a history of at least 10 pack-years. Non-smokers: Individuals who have never smoked or have smoked less than 100 cigarettes in their lifetime. Participants capable of providing informed consent. Participants able to perform spirometry and exhaled breath sampling procedures. Both males and females. No history of acute respiratory infection in the past 4 weeks. Exclusion criteria: Current or recent use (within the last 4 weeks) of inhaled or systemic corticosteroids or bronchodilators. Presence of other chronic respiratory diseases (e.g., asthma, pulmonary fibrosis, bronchiectasis). Acute illness or infection within the past 4 weeks. Recent history of major surgery or hospitalization (within the past 4 weeks). Occupational exposure to known respiratory toxins or VOCs (e.g., industrial solvents). Pregnant or breastfeeding women. Inability to comply with study procedures (e.g., cognitive impairment, poor cooperation). Data Analysis: Data Collection: The subjects were exposed to clinical evaluation, spirometry, and blood tests. Exhaled breath was obtained using a standardized breath collection system, and VOCs were quantified using gas chromatography-mass spectrometry (GC-MS). Demographic data, smoking status, and history, as well as pertinent comorbid conditions, were also captured. Statistical Analysis: All the statistical tests of this study were conducted on SPSS 24.0 with the level of significance at p < 0.05. The quantitative data were expressed in terms of mean and standard deviation, while the qualitative data were expressed in terms of frequencies and percentages. Independent samples t-tests were used to test the difference between quantitative variables in two groups. Chi-square tests were used to test the difference in qualitative variables. To examine correlations between continuous variables—e.g., VOC levels, smoking intensity (in pack-years), pulmonary function test results, and inflammatory biomarkers (C-reactive protein [CRP] and interleukin-6 [IL-6])—Pearson correlation coefficients were calculated. For consideration of diagnostic utility of individual VOCs for COPD detection, multivariate logistic regression models were constructed. Finally, Receiver Operating Characteristic (ROC) curve analysis was used to assess diagnostic accuracy of VOC biomarkers and to provide values of sensitivity, specificity, and area under the curve (AUC). Results Demographic Characteristics Table 1 presents the baseline demographic and clinical characteristics of participants across all four groups. COPD patients were predominantly male and older on average compared to healthy controls. Smoking intensity, as measured by pack-years, was significantly higher in COPD patients and active smokers. Table 1. Demographic and Clinical Characteristics of Study Participants Pulmonary Function Parameters Inflammatory Markers Systemic inflammation markers were significantly elevated in COPD patients compared to controls. See Table 2 Table 2. Comparison of Inflammatory Markers (CRP and IL-6) among Study Groups C-Reactive Protein (CRP) was significantly higher in the COPD group. Interleukin-6 (IL-6), a cytokine associated with systemic inflammation, was also significantly higher in COPD subjects. Elevated inflammatory markers correlated positively with disease severity and smoking history, emphasizing their potential as indirect markers of lung pathology. See Fig. 2 Exhaled VOCs Concentrations The analysis of exhaled breath revealed distinct profiles of Volatile Organic Compounds (VOCs) among COPD patients versus control subjects. Notably elevated compounds in COPD patients included: Alkanes: Ethane and pentane Aldehydes: Hexanal and nonanal Ketones: Acetone and 2-butanone These VOCs were present at concentrations significantly higher than those observed in non-smokers, ex-smokers, and active smokers without COPD. The presence of these markers correlated with FEV1 decline and inflammatory marker elevation, suggesting oxidative stress and inflammation as key contributors to altered VOC profiles. Smoking Intensity and VOC Patterns Among the control groups, active smokers exhibited significantly higher levels of hydrocarbon and aldehyde VOCs compared to non-smokers and ex-smokers. A strong positive correlation (r = 0.68, p < 0.001) was observed between cumulative smoking exposure (pack-years) and exhaled concentrations of specific VOCs such as ethane and hexanal. Ex-smokers exhibited intermediate VOC levels, further supporting a dose-response relationship. See Fig. 3 Multivariate Analysis A logistic regression model including the VOCs hexanal and ethane, along with IL-6 levels, demonstrated strong diagnostic performance for distinguishing COPD patients from controls, achieving an overall accuracy of 88%. Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.91, with high sensitivity (86%) and specificity (90%). These findings suggest a robust predictive value of specific VOCs in conjunction with inflammatory markers. Discussion This study was aimed at examining the potential usefulness of exhaled volatile organic compounds (VOCs) as non-invasive markers of the early detection of Chronic Obstructive Pulmonary Disease (COPD) in both smokers and non-smokers. Gas chromatography-mass spectrometry (GC-MS) was used to distinguish and compare VOCs between COPD patients and age- and gender-matched healthy controls that included non-smokers, ex-smokers, and smokers. Here, we interpret the implications of our findings, compare them to other literature, discuss potential mechanisms, and talk about limitations and future directions. Significance of VOCs in COPD Pathophysiology COPD is characterized by chronic inflammation, oxidative stress, and structural remodeling of lung tissue, all of which may be followed by the generation of characteristic VOCs. Some of the VOCs characterized in our research—like alkanes, aldehydes, ketones, and alcohols—are considered to be metabolic products of lipid peroxidation, cellular apoptosis, and inflammation. The elevated levels of VOCs like isoprene, 2-pentanone, and hexanal in COPD patients confirm the hypothesis that these are biomarkers for airway oxidative damage as well as inflammation. These findings are consistent with previous studies, which revealed that oxidative stress in COPD triggers lipid peroxidation, which results in VOC emission [ 1 – 3 ]. Interestingly, our study found that COPD smokers had higher levels of certain VOCs compared to non-smokers and ex-smokers. This concurs with the known fact that tobacco smoke contains over 4,000 chemicals, and the majority have the potential to alter endogenous metabolic pathways as well as cause airway inflammation. The persistence of dysregulated VOC profiles in ex-smokers also supports the fact that smoking history permanently affects pulmonary and systemic metabolism. Diagnostic Potential and Statistical Significance The variations observed in the concentrations of VOCs between groups were statistically significant. 2-methylpentane and nonanal VOCs were greater in COPD, particularly in active smokers. ROC curve analysis also showed that a combination of some VOCs could differentiate COPD patients from control subjects with a high sensitivity and specificity. This confirms the potential of VOCs as reliable biomarkers for COPD early detection, particularly in settings where refined imaging or invasive examination is not easily available because of restricted resources [ 4 – 7 ]. Furthermore, correlation analysis established pack-years of smoking directly correlated with the occurrence of various VOCs, including isoprene and ethane. This supports a dose-response relationship between VOC production and smoke exposure, and the growing evidence that cumulative smoke exposure enhances biochemical alterations in the respiratory airway [ 8 , 9 ]. Comparison with Earlier Research Several earlier research works have established the promise of breath analysis using exhaled breath in respiratory disease. Dragonieri et al. detected VOC-based breath prints in patients with COPD using electronic nose technology [ 10 ]. Researchers in another study used GC-MS to prove high concentrations of alkanes and methylated hydrocarbons in patients with lung diseases. Our findings complement those of Fens et al., with particular VOC profiles being found to distinguish COPD from asthma and healthy controls [ 11 ]. Although our study also permits a subtler comparison between varying smoking status within the healthy control group, through dividing out the examination of non-smokers, ex-smokers, and current smokers, we were in a better position to disentangle the exact influence of active and past smoking on VOC profiles. This approach increases the clinical relevance and generalizability of the results. Inflammatory Markers and VOCs Higher inflammatory markers (IL-6 and CRP) in COPD patients were linked to higher levels of some VOCs. CRP and IL-6 are well-established systemic inflammation markers, and their link with VOC levels further validates the premise that VOC levels reflect ongoing inflammatory processes [ 12 , 13 ]. This has clinical importance insofar as it suggests that analysis of VOC can complement traditional markers of inflammation in providing a better overall picture of disease activity. One interesting finding was the elevated levels of IL-6 in ex-smokers compared with non-smokers with no current smoking. This is indicative of residual inflammation in ex-smokers, consistent with the hypothesis of a "legacy effect" in the pathogenesis of COPD, in which harm is perpetuated despite cessation of smoking [ 14 ]. Clinical Implications The addition of exhaled VOC analysis to clinical practice can potentially revolutionize COPD diagnosis and monitoring. It offers a non-invasive, cost-effective, and reproducible test for early disease detection, especially in high-risk populations such as chronic smokers. Also, VOC profiling may allow clinicians to phenotype COPD patients and monitor therapeutic response and thus potentially guide personalized treatment [ 15 – 17 ]. At the public health level, early COPD detection in asymptomatic smokers or those with minor symptoms will allow timely cessation therapy, vaccination, and bronchodilator therapy and thus reduce disease progression and healthcare costs. Shortcomings Despite the promising results, several shortcomings must be acknowledged. First, the single-center and retrospective study design could make generalizability of the findings questionable. Second, VOC analysis is confounded by diet, environmental exposures, and underlying diseases that can act as confounders. Although efforts to adjust for these variables were made, it was not possible to rule out residual confounding completely [ 18 ]. Third, while still the gold standard for VOC analysis by GC-MS, it takes time and trained staff and therefore its direct application to real-time practice is less than optimal. Work on portable and simple-to-use breath-analysis equipment (i.e., electronic noses) is ongoing and promises to bridge the gap one day [ 19 ]. In addition, longitudinal data would be needed to define whether VOC profiles change with disease progression or therapy. Our study was cross-sectional, and longitudinal follow-up might prove helpful in defining the prognostic value of VOCs and for therapeutic monitoring. Future Directions Future studies must replicate these findings in multi-center, larger populations. Standardization of VOC collection, storage, and analysis protocols must be achieved to enhance reproducibility as well as comparability across studies. Machine learning techniques can also be used in VOC data for predictive model derivation and enhanced diagnostic sensitivity [ 20 – 22 ]. Furthermore, clarification of the mechanistic pathways connecting chosen VOCs with cellular processes in the lungs would be informative. Combination of breathomics with other -omics platforms (e.g., proteomics, transcriptomics) can potentially provide disease-specific molecular signatures and decipher new drug targets. Conclusion This study demonstrates robust evidence that VOC analysis in breath is potentially a very useful non-invasive diagnostic and monitoring test for COPD. In comparing VOCs in COPD patients with healthy control subjects stratified by smoking history, we identified distinct molecular signatures both for the presence of disease and for smoking status. The elevated levels of some hydrocarbons and aldehydes such as ethane and hexane were strongly correlated with disease severity and with total smoking exposure and therefore potentially have their usefulness as early markers of lung pathology. As a notable point, our findings further solidify the dose-response relationship between intensity of smoking and VOC levels, with active smokers having the highest, ex-smokers intermediate, and lifetime non-smokers lowest levels. This result not only further supports biological relevance of VOCs but also suggests residual effects of smoking on pulmonary metabolic activity after cessation. The inclusion of non-smoker controls provided required comparative baselines, highlighting pathological deviation of VOC emissions by tobacco exposure and inflammation associated with COPD. Moreover, diagnostic performance was established robust by multivariate regression analysis and ROC, with several VOCs having high sensitivity and specificity for distinguishing COPD patients from controls. The results suggest that VOC profiling could be a useful and low-cost screening method, particularly useful where facilities are limited and access to elaborate pulmonary function testing is restricted. In conclusion, VOC analysis in breath is a new and fascinating field of respiratory medicine. It is an insight into pulmonary pathophysiology between biochemical processes and clinical presentation. Large longitudinal studies in the future are required to validate these observations and assess whether VOC monitoring can predict for treatment response and disease progression. Deploying this technology in everyday clinical practice may transform early detection and individualized management of COPD, eventually benefiting patient outcomes and decreasing healthcare costs. Recommendations Add VOC breath analysis to clinical screening programs for early COPD detection, especially in high-risk groups. Conduct multicenter longitudinal studies to determine the diagnostic and prognostic value of a single VOC. Investigate the use of VOC profiles in combination with traditional markers to track response to treatment and disease progression. Trigger the creation and clinical testing of portable VOC analyzers for use in outpatient and point-of-care settings. Promote the training of clinicians on breathomics and its application in respiratory diagnostics. Ethical Considerations: Both participants will be provided with an informed written consent before collection of any data or physical examination. All the data will be kept confidential (purpose of the research). All the patients are at liberty to withdraw from study at any time without giving any reason and without any negative impact on their plan of management. The researcher's contact number and all channels of communication at hand will be made available to the subjects in order to return at any time for clarification. No conflict of interest in the study. Administrative approval on research. Clearance by Faculty of Medicine, Alexandria University ethical committee will be obtained. Declarations Funding This research was entirely self-funded by the author, with no external financial support. Acknowledgments The authors would like to extend their heartfelt appreciation for all the patients and healthy volunteers who participated in this study. We express gratitude to the staff of the Pulmonology Outpatient Clinic, Alexandria University Hospitals, for their valuable assistance in the recruitment of patients, spirometry evaluation, and sample collection. The laboratory staff are particularly thanked for their expertise in running gas chromatography–mass spectrometry analysis, and also the Department of Biostatistics for assistance in data analysis. We also acknowledge the institutional review board of Alexandria University Hospitals for their guidance and ethical approval. Finally, we thank the university administration for the provision of the necessary resources and facilities for this research. 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Chem Soc Rev 43(5):1423–1449 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9029272","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600559190,"identity":"3d4ddbb4-07eb-4dac-ada6-52776c66a4a5","order_by":0,"name":"Sevtap Düzgünçınar","email":"","orcid":"","institution":"A Life Park Hospital, Chest Diseases Clinic, Ankara/TURKEY","correspondingAuthor":false,"prefix":"","firstName":"Sevtap","middleName":"","lastName":"Düzgünçınar","suffix":""},{"id":600559202,"identity":"0ea8a98b-a04d-49e6-85f5-39989c39aec3","order_by":1,"name":"fathi shaheen","email":"data:image/png;base64,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","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"fathi","middleName":"","lastName":"shaheen","suffix":""}],"badges":[],"createdAt":"2026-03-04 10:50:29","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9029272/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9029272/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104180267,"identity":"14f4fe16-0e92-4b19-b10a-ba7d6fb117b7","added_by":"auto","created_at":"2026-03-08 17:12:28","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eComparison of Pulmonary Function Test Results across Study Groups\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9029272/v1/a5e07f80711310b1b473a5d1.jpg"},{"id":104180268,"identity":"6f6a3218-6fab-40c9-9f04-57c318851aab","added_by":"auto","created_at":"2026-03-08 17:12:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15121,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCRP and IL-6 Levels among Study Groups\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9029272/v1/856079282a84188228cacbc7.jpg"},{"id":104180270,"identity":"cb4d82fc-1b4e-43c2-9544-7678dde8ffcf","added_by":"auto","created_at":"2026-03-08 17:12:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":695533,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSmoking Intensity and Exhaled VOC Levels\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9029272/v1/943b68cfde41d20d29c4c19e.png"},{"id":104403932,"identity":"25d232b4-b1e3-4d9c-8d46-4caa55c7a78e","added_by":"auto","created_at":"2026-03-11 12:19:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1482233,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9029272/v1/3f5b7e3d-e8dc-4498-9b21-c0000b5a5379.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAssessment of Exhaled Volatile Organic Compounds (VOCs) in Smokers vs. Non-Smokers for the Early Detection of Chronic Obstructive Pulmonary Disease (COPD)\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic Obstructive Pulmonary Disease refers to a progressive and debilitating respiratory illness featuring obstructed airflow and chronic inflammation of the airways and lung parenchyma. It gives rise to one of the foremost causes of morbidity and mortality worldwide, exerting a significant negative effect on the quality of life of sufferers and heavy pressure on the healthcare systems. Despite the tremendous growth in diagnostic tools and therapeutics, an early diagnosis of COPD is still difficult when the condition begins insidiously and its onset may overlap with common symptoms shared by other respiratory ailments [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExhaled air analysis has developed and remains the fastest-growing wave of non-invasive pulmonary assessment. Of all the components of this air, VOCs have received more attention than any other due to their possibility of serving as biomarkers. VOCs have a very low molecular weight and result from metabolism and inflammation fighting mechanisms acting inside the human body. The lung, being the primary site of interfacing with environmental agents and systemic inflammation, expels a very high number of VOCs that can be trapped and analyzed to reveal the pathological state. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMore than 1,400 VOCs have been reported in human breath, including hydrocarbons, alcohols, ketones, aldehydes, sulfur-containing, and nitrogen-containing compounds. Such VOCs can undergo changes in various physiological and pathological states, including smoking, inflammation, oxidative stress, or microbial colonization, all implicated in the pathogenesis of COPD. Studies show that VOCs are generated differently in patients with COPD compared to those in healthy subjects, raising a possibility for their use in detection and monitoring of the disease [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn attempt is made to establish whether exhaled VOCs are useful in differentiating between smokers and those who do not smoke, as well as their usefulness in an early diagnosis of COPD. By comparing the concentrations of VOCs in various groups of subjects with pulmonary function and systemic inflammation markers, we can try to understand better their diagnostic accuracy and feasibility for implementing the VOC tests in clinical practice.\u003c/p\u003e"},{"header":"Study Design \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eStudy Type:\u003c/h2\u003e\n\u003cp\u003eThis study is a retrospective case-control study to investigate any relationship between exhaled VOCs and the presence of COPD in smokers versus non-smokers.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eStudy Location and Setting:\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited from the Pulmonology Outpatient Clinic at Alexandria University Hospitals, a tertiary care center offering highly specialized respiratory care. Data collection was done under the supervision of the institutional review board, complying with all ethical standards.\u003c/p\u003e\n\u003ch3\u003eStudy Population:\u003c/h3\u003e\n\u003cp\u003eThe target population includes patients diagnosed with COPD as well as healthy control individuals.\u003c/p\u003e\n\u003cp\u003eCOPD Group: Those recruited had a full diagnosis of COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria.\u003c/p\u003e\n\u003cp\u003eControl Group: Healthy age and gender-matched individuals with no history of COPD, systemic infections, atopy, or autoimmune diseases. Controls were further divided into: Non-smokers, Ex-smokers, and Active smokers.\u003c/p\u003e\n\u003ch3\u003eSample size:\u003c/h3\u003e\n\u003cp\u003eSample size will be calculated according to the following formula that compares two means based on the standardized measure of effect: Cohen's d. The formula is: n\u0026thinsp;=\u0026thinsp;2\u0026times;((Z\u0026alpha;/2\u0026thinsp;+\u0026thinsp;Z\u0026beta;/2)/d)2\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;sample size per group\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eZ\u0026alpha;/2\u0026thinsp;=\u0026thinsp;1.96 for a 95% confidence level\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eZ\u0026beta;\u0026thinsp;=\u0026thinsp;1.28 for 90% power (\u0026beta;\u0026thinsp;=\u0026thinsp;0.10)\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ed\u0026thinsp;=\u0026thinsp;standardized effect size (Cohen's d)\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAssuming a moderate effect size (d\u0026thinsp;=\u0026thinsp;0.5): n\u0026thinsp;=\u0026thinsp;2\u0026times; (0.51.96\u0026thinsp;+\u0026thinsp;1.28)2\u0026thinsp;=\u0026thinsp;2\u0026times; (6.48)2\u0026thinsp;=\u0026thinsp;2\u0026times;42.0\u0026thinsp;=\u0026thinsp;84\u003c/p\u003e\n\u003cp\u003eTherefore, approximately 84 participants per group (28 in each subgroup) are collected, resulting in a total sample size of 168 individuals.\u003c/p\u003e\n\u003ch3\u003eCriteria of selection:\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eInclusion criteria:\u003c/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eAdults aged 18 years and above.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eSmokers: Individuals who have smoked at least 10 pack-years.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eEx-smokers: Individuals who quit smoking at least 6 months ago and had a history of at least 10 pack-years.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNon-smokers: Individuals who have never smoked or have smoked less than 100 cigarettes in their lifetime.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eParticipants capable of providing informed consent.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eParticipants able to perform spirometry and exhaled breath sampling procedures.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eBoth males and females.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNo history of acute respiratory infection in the past 4 weeks.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e\n\u003ch3\u003eExclusion criteria:\u003c/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eCurrent or recent use (within the last 4 weeks) of inhaled or systemic corticosteroids or bronchodilators.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePresence of other chronic respiratory diseases (e.g., asthma, pulmonary fibrosis, bronchiectasis).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eAcute illness or infection within the past 4 weeks.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eRecent history of major surgery or hospitalization (within the past 4 weeks).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eOccupational exposure to known respiratory toxins or VOCs (e.g., industrial solvents).\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003ePregnant or breastfeeding women.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eInability to comply with study procedures (e.g., cognitive impairment, poor cooperation).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eData Analysis:\u003c/h2\u003e\n\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n\u003ch2\u003eData Collection:\u003c/h2\u003e\n\u003cp\u003eThe subjects were exposed to clinical evaluation, spirometry, and blood tests. Exhaled breath was obtained using a standardized breath collection system, and VOCs were quantified using gas chromatography-mass spectrometry (GC-MS). Demographic data, smoking status, and history, as well as pertinent comorbid conditions, were also captured.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical Analysis:\u003c/h2\u003e\n\u003cp\u003eAll the statistical tests of this study were conducted on SPSS 24.0 with the level of significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The quantitative data were expressed in terms of mean and standard deviation, while the qualitative data were expressed in terms of frequencies and percentages. Independent samples t-tests were used to test the difference between quantitative variables in two groups. Chi-square tests were used to test the difference in qualitative variables.\u003c/p\u003e\n\u003cp\u003eTo examine correlations between continuous variables\u0026mdash;e.g., VOC levels, smoking intensity (in pack-years), pulmonary function test results, and inflammatory biomarkers (C-reactive protein [CRP] and interleukin-6 [IL-6])\u0026mdash;Pearson correlation coefficients were calculated. For consideration of diagnostic utility of individual VOCs for COPD detection, multivariate logistic regression models were constructed. Finally, Receiver Operating Characteristic (ROC) curve analysis was used to assess diagnostic accuracy of VOC biomarkers and to provide values of sensitivity, specificity, and area under the curve (AUC).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic Characteristics\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e presents the baseline demographic and clinical characteristics of participants across all four groups. COPD patients were predominantly male and older on average compared to healthy controls. Smoking intensity, as measured by pack-years, was significantly higher in COPD patients and active smokers.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1. Demographic and Clinical Characteristics of Study Participants\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cimg 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6H0C1qEgF1koIpTqws42WjDawn2gDYqgghz+llPK0BMwJKmQ0v39XUipD71lyLtkI1dCV4YXDqX2eEvIXg7wDqCkXgkuoEuHKsr62ifjB7ZJZZyeByC1IJhH0EokCXgW5OlJYIkVyM36GMg+PMHMuxrezZfy1wFV0wlVoHvB4VcpLWiLRo9K4jARAAsVxG4qeJXwSTzLUpV+gY0MBsSUpzed4CFXPRGhyDL4lgpoC9ANv4jdVunWQ4peICsaVRVcCpRKaNuO6J8SLS+IXM/4KgeCvqFyMr5A390GWAV2YSTcYNGg/0jKlczbA6WFcJ64IO90CS+lzpTQ4wfAJ17G048S/s4r1aGc2PlSyBZIwwzkw6G6LMBRvxR5DgUmLUv6kHiAM73LS7gZ5zbAJX6kS8DpFry1JBCB0jHn1rk0MtJCD4QOGFeiIw2gQA8L4hI9KFAex4m+36uqWsosA5srKIN79cYowjYg9LDsRREVON+CtkjyoIdUMO/SbdEO2qjSbZJ32rxhwYriHFXmPaXKxKdUBG304qnqeJo8RgAAEABJREFUoSSQYC6Hkhf0FJp3BfAzmpI3w5N5LPRf7vzADi8Ib7o+YGoQaIEnLGEUWQ2BBoBQYGY6O9o8r6mIXLhlNSw7wAeFtmATAF0g8FwF/g+VQGnKMoTsAfLgC/INKhJBDR0TyvrNJ2Ja9WYsRP9FffLwopgnFFaUDHyEX1JWKgNXNhrQl3AOJrSUQ0TQXoBXwrkPZmVwedW2Eo0IHhsZJaA1akkpJmo9S7QEPOOGvk5GlXSEYqEKCqGb6IrTSiGS7kRYR1zbsURWkKXYOuF8WOcAwa/EPmRAN8pUGIleBOui9auEXVCpBAoW1Yy4lxQdD+U0kGdYSFEKltQPYjeQqVGWcJYyaAIUEXWadJkiQrwV/CdSZdHsNzH87DQhSaoLK5nMeYOwraBOwDgi6IfJQkUZkhxjnyUpynhUwqCwbRWlItXJXUj/CioWQrSKCIWkZj9Jwk8A4wgpMnobJEwFDzAqiUOZBK6UVGK5fpNIuSpPEpqA1qmgj5kCWfCGX0mf6KAiAlBvKGFhjr1ZR+E8UNACIPiUPigAVFX6qYuoR1kpjy+nN+SDjZPlRVVapHIAGRwtpzKNT6DMA6S7omba+XmADFPhPEQrMVACoZAlyzSoL5SIDb+ekCUUpYSASwwsghroRaB0EQFekiOY2LactnIy1fAolEMT6EvJQUEcPDLmtRS8iYM6qTLEAb9UD90wOoxTDjugFPMPwMuH19IxfbON0HTqf0AJijZLUUxcqKA94826gGmhUElfRJyZCG1r0F5RmraEnrqUQQVdAVmmLKhIeWleJSgJCkmuDyQVU1R50c0yFFEBCZ4MAE/nsoAgYELa62cgg6qkhIZCmBW0U9JekdIlxaFQJr/JSTI/ehgk3TegpD3bdUHMI8tRhERvOtIRoYgg1XreShIo0RMeBcqVoDnFQSLhhJYzYvKhsPZIxKUBnOuLUAJCL4M4Ax+RSWQieIkSCIwyfcEBoUJXZUGB84X9Q+++MM8yRRbKAprIFem/TAogCyX9zwqVSdcrW2PrSz4gyRNdA4TtgKqKAAUoBScMmoePiJTWmyggCfcWyTYjJ5lNHmMWChZaaSeK84oyVO8ulLGpLxBu/9vGAsF3dzfU09NQdymVCKmEeR5SzdyZMJBpkjKrCTShwBHWVRbdVChUr5MOyX6TiFIqmi4pQalgwo0vVfKFo66eeg8E8AiwmcBSEtBR05NZZ669FohPoaK/7o+pIkwPOIYD5HIZ5M7J6FCYNOVbr7eKBJhToSi9w4lwXkrOJCXRHXCBLtd7+IrW3a25c+eqc+4c1bu6WOtKKdEJfQl195bPnTNHXV3dqtsg0ELrXkpKMp9OeHR3wafT0Clvtu2XYKIGhF1dPamdOfCZM7dTXd20TftJJ7EhcYgIA42XdmJs1sOLN3F3Z526nXLdufTTfcrYgQSHekEfqct0moeuMQbReSA9oczOE7qyhCCQDRXq2FXR274oi6BMBMc2zhKmHgD0ZSrHolO/sCAeQZcZXKWUIONFQjQdoQa+oIA+IhS0736VEZSGSvhXqTAbcKXAprigrBv/0sCoA0zAOESf3aakJp27V0qKSFSS+sfqDa5kKrLwEVAUNeaxRJZ14oaC9vKAK6RFQQwbbwojC76ylurs6VaBbyppsKenVL1eKtAd97PBggJnUT0BJPI4e18uasFiSACR96MqSTMZSZDErEnCDpKM0SPLvKuzC3vt1Nw5la2VzI/1rW59Y948d2IyUHPVYNFGA5l4sSYF61xwICxIFzCNiFRSuj3woly0mdGLsN5RGlHRiNh1FCLQT9rLacTZgnZEQZUu4FYqKLPedHUV+ABw5CuaDPto8NWuIe4UZLsIhQTQhCJCDIMhlEI9oc1Ub4h0mXDmGQG9QYJe0AdlIcmxpMhED4hLOdgWC8asgMZAKRWkKJOPs2/pxicxpIQuLD9BS1y6E46Bbvyh12RzbYDv7iJVcolYBuOR6AgvKSISUCXxUyu8JSUQjMpQJgNAF8hbP1O+qUzogjh8K+UxlICo+aAgprc6GlWahnLrnyHVodCcDVIosQOXEunQi3GQt9+2f+hmnbaelqyRBXopoFRQFaumcmoDOw/bgygBJ0LgXyLnsABtUZTGiO4RSyYxiFA2kaSrB95VItH1JpfkKPUNaaQ4vUqEUSIMD1vygJqgAaGg1CD8cqFbbr5Zvzrh17rx1jsUEYCAUlHL9ehDD+u4E36lC6+4Ul09dbnBDMH796XpBofFFGpZytSkdeHsSjl0d83SrbfcqDPPPU9PPfM8JK4d0AqfRU9ZmNmxKVwL9KQJE3Tu6afq3LPO1MRJk2XCAmXq6ukSEQ64oQnPPqWzTztZ519wniZNmUJ/Mnmi3aJ/TlVn0wFn+oCrLApBAB9BYzCV5Mmv5t/5JpjMacctePNJIOgy840NWJ0MxlRzjUYw4ZMnT9IFF1ygI488UoceepgOPvgwnfznk/Xsc0+rZANS4GSeeeZpnXb6mTrs8CP0k4MO0S9+/lNde9lFmj51CvwzdFWa9sJUnX3mqTro4IP1Y3j85OBDdfSxx+raG27SjJmzJWzo6Sce1Um//40OO+xn+vFBh+snPzlIRx35c5111hl6+qmn2QwU8m+tGwXaT98K6yp9b6DoD9x3h4475ggdTPsHHXSwfvrTQ3TiSb/VPY88xMG9UNrsllKBrgf17KgNHi+Ny6HBIb27q64C3qVCM6dP01VXXKbzLrhQTz83XiVjzaiAvxQsZDqpAWWR+lZHlJx5YAVRWcr8IVJRNNMQ0Ibx3fiFbjb8YKCXmjLvobwOkxKsoaChAjlDAMb2WRcN6rnnntGFF52v22+/k00hlwwYbamcKcwSaVWnkDdjAVYEesXb85ERVzkhvxL+ZWm+oWBws2bP1dVXX6mjjzlMhx/2Pf32t8fpzrvvRY51IWqFa1sWXD70dM/R+eecpl/87Cg9cPcjYti66uqrmLPT9cyz6AiDKBh/3Tu53n5QnRQFvJ1uwWJKoFdkjjxvYs6KBEWSe5oY5m/27Dm67vqbddzxv8SWDtdB2O0vjjle9z34MNXQReReoLelJ5P5F/pWoLzsiVXjy3iGkhdFj0oOIAXlDegbBX0ESud9YMga6HWdpahbDesxc1waUIBGgoBtKetf6qf50R5FKmBWoOdB3m1FhJ75xyM6GXu98NK/atL06dRDj+mT4Nmgr3XsoOTUUCqjLOBBT8DRSQX/zZ41U9dd8zdddMF5en78eIFSCd9SUkmjBW0V0JMEE0CJzcLDBM4R17HJkr6Jyg1oTS/jG9168IH79dsT/6BDDjtMRx5xmK65+nLNmDHNvVGNQ0cG0JxKWN/y91t05M9/oYsvvkzdrNeP/eNRnX7mSbrnvrs4XDfk0KCdBr5ItOUxFZ6DZptqhbeaBCJCEZGGVeJv61xEOZN0k3Rp/UR5GpSV6AFKy9NI+pJwEDewB+tNWZTwAlFat4M0IDLYK5Zhk0mFTrst21kJz556N9ZbyLo6ceIk/fnPp+qsM87R1KlTqR0cZItkswrBo1RqF57Cx2Q4B9AqaFsmUEVje7ING0DBx2/R9zKB6UsTJXSZ3m+2V+YTFnOjKmZgCMP5aiAWiwdMzuNDQBa8QYjbDtAC+Mejj+tPfzwJp3CJps2YpRxlCE5x9Z5u/f3mW/SHP/5Z9973UBJwwU1M0EbiwcQJ51LCt+RW1K2RlZsKEnNmTtMll1ysk089XU88M04NOlYCdRbc0nWhLJj40opFZW/ozj3zNJ15xukcGCbSaUHhMYXqpblm6po7W+edeYbOOescTZrsTVyJsyxkpygFcckXiroK08NTESndoI+FwXhVoUSxhRyqXOv9ZpOANcIgpYmWQ8l8lmhNcCMc6fa+ZEFu6MEHH2Tj/TMdcsghOvfc8/TAgw/p7rvvRj//yob1OQX6evvtf0/lxx33SzaK11B+jy6+6AId+bPDdfppf9bUaS8oIjRl8mSdcvKfdOKJf9Rdd9+nRx97Queed4EOOugwXXjhpZrL14Qnn3hcvznhBJ38p1P08COP6R9PPq1LLruUg8AxbFwP09XXXa/Z3JpiDmwhpMjYPORsLBjEYw/frxN/9xudd+6FevSRx3Xbrbfq97/7nY457njd+9Cj6HepNGJeQW3boxER6Hqj5Ba9Uw8+cJdOOeUkPfjQI9hHgwPDdJ3NQfxPJ5/M5ndcZRPYXoEdUk0ZGyuaF6KTkJ2hlNhYN1RyqBEN2MaF/USEqjYzPXTf3cjzbN330EPJRkvK6mweGrbxkv5Qt6u7rgLb8wamB5/SwIfIwGZt5sxpuvJvV+riv/xVnXztUSj1wVGWIRP4qRdZb/TIi1NJH3gSXV/MPJeFhDxK4gKos/m75urrdRxyu+66a/XMc1w2nH22fvebE3XfvQ8ylAY8Ci4vqMVCd/ddt+nYY4/Sr3/zez32yFOChWbOmpXm7bIrrkDu3Qr6lMaCcIrUOE22npchAQSH3EoULQHZIC8W8pK5K+BkvLDj58c9oz+dfIp++rMjONizBt17vx544AF5Lh5G30p0KENvUbPELVCaGvkcfSm5yOrmZtzzlQV6BEUBNJjUBjZCUhGRWixZ6575xz90/tnn6Lbb7lJXZ7fcn+7uuWrQN/MviHt6etDjOnpRJ25QX0l3qE46kxTJ1zz71BM69ZSTddElf9WUmTO56CoT0D3BGJ4Fm6eC2NkK23w3sMlbbvm7Tjn1FI0b95xsAwW6mdZMZFXSD9mWGEAXNtYNGGU5mEfQh1QOMsL9oR3W5gZ2XlLn4Qfu1vHHH6vzzr9Iz40br+uvv1YnHHcch+pr1Ik/oooQvSIyTeQC77RTT9PhPz1cf7vqWjU4GHUig1tvvUV//NNJGjdhkiCTQlLwwm8U2HuSGe2rX3C/Df1QreSbXAIFtoRmS0w9qpli2QzA28ejphJ6EEAB9LDP62FtKCm33jhuoJtyoDwiFBESj0yjKphOKKUPCXP5om9djiyT7TIi2CtO0kknnaqzsd9pL7ygDD0sKayji5hHYgI5eGwWn1GALAo40mnIKA+VbhReBb6hLEvWmYa6WLfq1SCgefFjOkjVhBdTLHkYpqekVxUEg64ANIOPIAdAICRCZDqi3qdEeLW2TOut/3Ytv9wyuuPOO/T440+IqYBTqRcmTdR99z2gMcssp2222EIj2tvUwWRkapOiTVFrl2o1HF8uZTUgV84mrZaHInINGTxY22y9lT74oQ9qlVXHqsxCGZpSq+XKgOgYpmzQCPA19aA4JZ1s4/NQe1tNHYM6oA0OL7kGtXWk26LIMw0Z0qGi3lXdBDVCUiinTg7fNsoH05+OWpvaiNEJWSHN1xucondmI1xPyAR5GEeyegJuZYIq33ovqRIoB3TM01jhSkXgADD0gpsvRa4JEyew4f49m/7TtdGGG+kb39hb3//+97Xft/fTRz7yES237HLo/WNsLI9NB4jtt3thc98AABAASURBVNtO+1P24x8dqL2+9lUtNXSwfvdbNvAXXaRO39zhbTIc2NprraUvfvF/9eMf/VCf+tRn9Oyz43UGtxzPPf2sgs1tey2jvY319b2+oe8fcKC++Y1vabdddtUVl1+ho35xTDpEtGdZ6m/aeWCPAd/2WmjEUsO088676MADD9C3v/1tbbPN1mysr9GFf7lMU6bNEOqOjrdhF9gGtpej+/ZcGekGm/Jrr7lKv/7VCTjTydBkGjFiKe35znfqP/7jP7X8SivSSkMOOfQ0x80iuh81ZXmbzJxeaVCEhrTVVGsbpKgNBjoopwS8IpPymu658xYORX/U4089pZxJyEKgc+VtudqAjrbQoBp56HMK86wNmyxU55Y28nY9+vCDuuaaazV21dW08UYbalBHO/KgC6EUIjJltBPYeOAfPEYDTYk1JYHtukwIz73omiuHZs2aw9eBszRu/AR94pOf0g8PPETbb78DN9Y36EZuressXiLkmTTx+XE66U9/0Lhx4zRo0GA1WGzMcrdddk99u+ba6/QEh748D+RRc0/SOEwDixc/XokMcl9eXPyviymroQcxokkRE5khSEQrzEHBhMycOYNLoTN0xFFHqY115HNf+IK+8539dcABP9BXv/IVrbvOWio5ZBTcGmasRXm0q6ZcNerm7aHA9lj7VWcOojZMkQ1V0PJg/MFQdLKtJubYfcgURaY7uSw4/tjjdA8XALWsJt9CdrS3q4MOdVBvEPFg1qE21pUcfTSAUtaWK2vvUEH/S7TCbbS3ZeroyFVEsK6BzTLlbW3KavDLB2tw3qFansMVahapDDoyiizXnLmzODxfiG41tNvuu2u5ZZdWnmdqg950tSxTRy1XO/kc6GkUbGy6oS+EW5IDrk8RmTJoSxWKkPIsFMjrtr/fpFv+frN22HlHHXjAAfri5z/HV4xxye9NmvqCGIJZqIvD+18u+otuvPFGtdPvNtZ+pKV11lpbO+ywPXuFO3XTzbdpLpsq9ynPMykkRcZjCEWEmiEi5ss38a34zSmBEmUzKKTMuuUEyhMRyrCR9izXIPQzz9slIMOmyiyTdbPg4Fmy3xN1IEfnSgX0sAFTYpgNYkojlHxCiHyp9vbBrA+D1V4bpDbWo1w1OZTYeFFm8DGUyqjXXsuwEVABO/qqZAdD4Dc42YLgGJGldAZNjVeN6jkNYlLyoVeEgsNF3Qh4BjQREIOXmjH9ZdwC0hqkJTswxGaHmx31QILhRBOx8Li0cMVmfhWtu946euLxf8g/QRL44Nrkkcce0x333afVVl9N66+zph589FGdduYpOunEX+r0P/5Gt//9Rs3p6hbzpaefeEKXnn+urrn2Wl1x9XXctJ6tcXzGX2XsymmDknfUxAFTTz71nP76l0t00u9P1Km//7Wu+9uleuGFqZa3/EWD6UUx2vQMtx9n//UvOvGUP3BT8xc9N+F5HF7JF4Y5THpo8JDBKiKX56+nu0u33nGnTjzpT/r9n07WlWxAJvFpyhJgKAr+y5hsNEkDpTU/olnqeOFia5UsiRLwnBnoW4qChNTV2anr0Mlrr75W733Pe3XIwQfrwx/+sDbYYH1tscUW+sB//peWXnoZXXbZX1lIb9F/feADbND30Z577qFNN9tU//7fH9XXvv5lLTV8iM4+62w9P2mScnSpva2mjvYOrbTiCmxe1tAH/+sD2mHHnTQFvXvumadR47qGDRuqMWNGa+wqK2vNNVfX+973Pu3/3e/qw//93/rHP57UHWxOOllwfWOSnE1ybHWJzTRNaPTo0VpzjTW1HZtc93n48BF64h9Pa+qUF9io36sz+HL3pz/8Tqef8ifdc8cd8k+AZsyYpmuuulqX//UKTcOu/nbV3/SXiy/VzBkzNXbsWHljPnjIEGU46Ig2PfbYozqbryO//f3vdfqpf9Ljjz2CUy/17ISJuvDSy3X1DTfpnnvv1YXnnqXTTvqD7rj5es2aMYOb9zm6+drLdPmll2L7T2HTf9XZfCV4ftJkzZw5S1dfdY1O+uPJ+j1fJ6/jK+UM6qgMTDBTRC5liKhnpm6/5UaNHz9B2227PYvBIE2cOIUD1TXcfN6mW26+U6effjqfm//ERu6u1K8aG6+wcFSo5H4YLrK/sujKIlejaJOUK8uDN/M/t0vLLrO81llnAy23/Ooau/oaautoh66e6tkvTJs6WVddeRnjeDId8IYPHVF9/aEFz+HGm2zKmGZyy3q1Cla8PJNCkn0PTLTwYKqFl/5rljRlghBF2g66LFAHAIFmUeHvv/9+nXPOuWnt+Na+39KXv/h5bYY9brzBBvqP979Xm2y0vtogpYqeGv+szvvrBfrNib9LX/5uvvoabGSSOjramMceXZvs/yrddfudOvO8s/TnU07RDdf9XS9MnyFfVN349+t04fnnadwzz+r6627Q+eefr6eeeEz333+HzmbTfPmNd+msv1yqS9CRGXwxmDOnU7ffdov+zNePE3/7O13AF/HH+OJRsLEI63ajm7WqoUBRekqp6O7Rg3c/gL3+Wb/64/E655Lz9dSzzzL9hTLGgCqjaWgyXxKeffJJbPBRbbrJJujrCuru6tSdtHXFlVfqjvsfTmvbH//4B138179qArbWhj1YJ5GkAkYFG7EgEzAuikxZtAM5bfmhgEV42LBhGrva6vi9pbXWmmvi24aqi3ZcFybcrvbo5htv5iB/jZZbZhkOCevIm6a59UKDOERtuNFGWoN611x/o56fOF3Bqc+bxwa2UdJMluW0mZESplkmSJnW660hAU+yfTk6hkapRKcKDu5OT58ySX+74hLdcteduu72O3T2mWfo/LPO0EOPPiwfqmscdgP/7bTXvDwyzeCrwNVXXcmXwys1bcYsBfpTR4/9dfzCv16mx9lbTmQ9uvzyS9jjnaQT/3Si/nrJhXzheha7KaHPlLd1qMD23JcpUyfp0iuu01XX3amZs+cg80KTJo7TFZeeoeuuuUQ9fHlsy0P+Wn3rrXfx9fI0/f4Pf8K2rtM07DtHdfN0KeD1pFBRlPB48RPhEb8YvyRjGNqCu1cORHts/QeIkWPpYrY1fPhgbbnVpupoz/TA/fdp5qwZbN7n6u777tG4SVO01jpvw3F16erLLmHjcLYuOPcc/fK4Y9PN6lXX3qAZnXP1dz5T/oDN0EE//BGHhQt0O8ryGEry55NP1hE//7mefOJpzZ4zh0X3Kp1z7nm64Lzz9JvjjtePv/u9tOmww8qyUJ2b2aeeepIbj0vY6PxFf/7zyTrgRwfwCfSPmjh5knLG1c6Cn6FoOZmunh5dd911OuaYo/XHk/6oU087VUceeaT8eWr2rNmygqY1qQxlWaZGiQIASiFQOAFlys3/WhBufopW7vWXQP9Z6Z/u3xPjg7nOMPqpbAZvveVWtfPF6n3ve7+WXX45WR9MX2uvEZWaPXumHn/0cY0aOUo77bSzll12GW7sSvX0NFCOulZdfTUOGBuwQE/Ss9xAUwl8yaZA6ujIZec3kYPEJGDo0KEaNnwY9XvUhV30sAloy6VaHtAV6mjv0HZ8wRgzZmk9RpuT/TcPaGAEBpqZM3QFOsrNRib+y/L0U4Fnnn0Gfl1aZbXV1Dm3ocsuvlznnH2W/nLhRfrFkb/Qz376M913zz2aM2eWHuVg/9wz4zQT53vzzTfp9jtv11NPPqVjjz5Whxx6sP7BIaEWuR7E1o855hj9+je/0blszo497jgdi10//vhjGvfcczrokMO1777f1qmnnqbzzztfPz/8UP3kgB/otttu0wxu7++952499vBDmo7Dv/eue3QLG7InOCyde845OurnR+u0087SeRxGfNCyTZdiXGwqgjHlWaZZ08fpmWef0siRo7Xq2FX5qtiu8c+P12GH/RQ4XBdceKEuuOBC+e9NjjjiCN137z0IKBjjXN1zz30688yz+IJwrs4//wKdecZpOv20P7HxO52LjwdV756rYSOG6j3vea/a2ofo1FPO1Il//K2uvOpabciXjM233Ew+fMydMxtZcpOKD/k3aLfYYkvltXbVam24xyBdS3O/1FIj5INTg01TyRgKIMcBpc0SCsWDXpVKwXPJdKZ06zVAAgjG8gHrCJcvBJegWpIy9HyOHnrgfk2aMkXv2PNdWn311bEQMR/CJks16sgZH474ueB6SL/+9e/kL3ZnnXEma8Dv0ZefpIPD5Bema9rsTh19zK/0ve8coIvQpb9dfqmOO/poHXbIQfr7zTdyQ96px//xuJ588gl1c/H0wAMP6pZb/q6nnnpMZ5x+qvbea1+dcMLv9Lcrr+HQeo+eefppXXLxX5K9/fGPJ6J/p+uYo4/Sr0/4te6++16GUsj6Xa/71r+BHtV000236agjjtbvfvdb/eUvF+rMM8/UrbferpJNkTfZBRuuiEyNni49gj1Zr1YZu5qWWmqUGkXobDZce+/9Tf3yN7/XpZdephN/+2v9iHX2j38+XTNmz1U7Dsb9upDDzWmnnQn/c+j76cSn6cyzT9edbN7m4ouU1bThpptojTVW15WXXa4/n3q6zuOSr8aN8E477aRluNxo4HfuwI5PP/0MrbrqqvrAf32Qi4sx8gTU+WTTaBRahkPEmnxdffTRx5ijFyiq5tR+0OUgFBHIokygVnhrSaBUml8RSuwwIuS5L1jrHn3kYWzjpzqIi7lTTj2F/duf9f3vfFfHH3Osnn32ObWjg9a3NnSOalYVzZg1Czs6S9//3g90B/tG65n/FvBU6h922OG69557dR970TPOOIM94cX6HZdb3z/wBzrr7DM0ffYMCSeSt7Ur4N1o9Gj8c0/qGNr708ln6oVpc5RT/uQ/HtNPDzlUxx/3S02bPl3Tpk3HFi9OfT2FC4RTgYMOOoi96fl6gcutCKmOr5dCtkfcPWMsFqjPpZ2/3hwhbTGaXcU8mYDq3cTNFzMwD86APFJRwS1de0fGbepGWm3VldNN5ZNs9KdMGKdbb79NbWyAvIi2w/ltq43V9zkU/OSgQ/Xf/+9DevKZp3T+Xy/Ts1NmqAtHMnfuXBbzOWy6dtIXvvgVvlqsr6l85pzljTsbJjykRo8aqU9+8pM6+PDD9PW9v6ZunOSll10Gr2c1bKlhGsqXgwkTJqSJ+dTH/kdf//rXtNLKK6cblXvvvzfdCDWSo20oy9j0PPy4Tjn1VLW11fSjA3+og370IxaYNeRbojvvvls93O7kKIwn3OOGsUpnPHqEEBGohOQyg9EGRJVwTrdgyZMAPotOlWhlqbLKkH/xM4cN4azZs7Q0G/SVVlqJr1wNiKjHBBfemMOhs7MzOZDlllteK6ywAvMOCU+JMyzqXepoG6Qxo5dWD4fTadOmqYau+ZbeB4S//vXS9Dvr444/Xg89/KA233wzrfW2tVXjUFugp7BXg4VW6JkCc6Xd4cOHJyc0kRvCnp5u/F1AU1fSS3ZNtbY2nFVdD7JpOo/D+R/5iuDNxsiRI7XtNltpxdnwAAAQAElEQVSzwR6uTTbdNH2t+OGPD9K/vfe9bFbu0UVsRsYsvbT2fNe7tPU2W6aF/fNf+Lw+/7nPptvEubNnayqb+7ncJk6ZMlmn/vnPuosvc//93x/SYYceqg998IO6+eabdcmll3BI6eSSoFsTn5+oMUsvq89/6Uv6+Mc+oifwDb7trCOf9/3nB/Vv79qdLygr6L8+8hF99Quf1aDBg/SHP/yBQ9hs7bPPvvrJjw7QDjvsAL4DT9NADJYBQP0pUydwiTBTq45dQ0OHDqcskHG3pk+fpn/843GtutqqHFj207sZz6233qorrrhC3Wzq7Gfuvfc+Dkzn6Cy++pzPYebcc8/VhRddmBaBp7iRarBhUzS0FhubtrbBuvqaG7jIuExPPPmsll1uBY0du7I8t3fferOuu/pqbbrxxvr3D/y3RnJ48ZeaDsYR+I2I0IiRo7hUWUqzuH3ypUdh/8E8MYTUZ0hIlinNvYSYYvI81AdJovUMlECJkCw3++ZMIc6SQJnIuju7WOixs442rbzqWLUPGaRu6L25FjYZQKO7k5vJKRwST2MTfYW222FnHXTIwfrGN/ZClwbpnPPP0zW33K65PYW6esS8j9OwIcP1pc9/QR/58Ac0btyT+itfsP214B27v1Pvfve7NJz15z/+43364he/qLGsdbPnzFQXldvRn49/9KP6zCc+pUceeUy//d2Jwmi1195fTwfwXXbbVVejQ7//3R+wmy7VBg1RiSIMHjRYEZnOPvci3fL3v+s//uP9OuTHh+sj2Mryy6+giJBtvhp1sHbO5aD+rEYuNVwrrLSy8lot0RSNusaNH68p2O6793ynvvqVLzGWQbro4ks47DyNzdT1zNPPoN8X60zs4eyzz8UusI0zz9ZZwAMPPphohDNaYcWVtMrYVfTQAw9gP2fr7/RrMLq+Jl/eBnOp8tRTz8h/Hzicr6Mf+5//0UZ8TehkXa9xOhvSnovzi4YMGapl+Co7g43X7NlzsGumLeNyQ4yHwXhuS2KwiogEThtc5rgFb2IJBH1P4EkumV8pzzI1ODA8ycHbOuQLp/XWW0+f/NRn9LZ11+UQfisXPvcpo6r8xi6sU1mea+lll2Xd3Jw1eBoXzbdrNhfWEyc8r9tuvU3LL7ecVlt1Nflnov/+n/+hQw86mD3o97T88svrPC6KHnv8UVnX/LcGXjfbOmqoeUNzOIT4wi/LchWs8zP5wt7VOUftXIr7735uu/Mu/epXv+aw3aZ9vvUt/eCAH7DOLS0fSu695wEF/azVMrW11RQRKjjUm48GhAhT0qQ7QZn120ByiXyQvzts6N+/sn+mSvdDeWwVlAi7ABpsylfSRhtuqAnPPauH77tXjz/8cLqpXGPtNblhW09rrLSitt1sM9WY7BemvaB2nMuwESM0dcZ0zZgzlw3SYOXcym2x+ZbaaaddmNBluGkdqqVGDJcnbdacLo3g8LH7bjtraW4opkydrhJlGT58pKZx2pvOqW5QxyD5Vtg/nXgPN0vbwmsXeL0LJ9k1t0vPPfOcergB8VDauKnNoo3PptehZHfgxIawwenU7Nmz1d7RpmeeeUZ33HEHG5LZ8rrNlCY5tOW1pNwpM+8ViqhACtyqWmEJlUD09qsZ92bni0ocRNO4Ozo6ZEDT0c9c9Z46+i4cABg28j58Wm/904QuNqNZpSzc7JWy3tba2hWRoxOYGkYzCL0vvWHhgPzsuOdwOr/RkUcdrbvvukt77LGH/uPf35f+XqAUepRlKq1XxO5vBDj65ouLANdWy5VnGW0VHBAaKuiPVLXbjfO97vrr9KMfHaQ/nniiBncM1mc//UltuuHbNXalpbXpphurluWazC3s0GHDZOf7LPbhwS29zHJaik1HCa8x2Jodsjfyea2mjvY2BXZ39z136frrr2dzNUzDsUvzsU15c/LAfffp+eefV9moa2Nsfo893qEtt96Gsb1fq3Kp8Mijj7B5maZlll9JI5Zaii6XGjFyhFbgy8yopUZqOb7izMRhP/zQw+rmkLXzzjtozTVXV8GY6thvTr8tjxf4+vPCC9PUgd3n9MmT2M1GsAMZb7bpZtppxx3xPW/Xe//t37TCCstr3LjnkVOPRowYqf/8z/fr+F8ez43RMTr0sEPTv6Jz7HG/1mE/PVLb7bgT/qldk8aP06mnnKopU6brf/9vL/2SW+D3vf8/0+J1zTVX6eH779bxxx6t+++7Xx3tg3Tf3ffofr66TOGT9p1335X+mH0un6/d35G0GRGaxCHPt2l5nqFDhbusiEiQMmV68wqg9SxUAsjMZWUSk18GYyQXFRzKfEAI2yMI5zE/ZeT99wX1ubP10N136sabbtIaa66t//nIx7T5xptp113foY/9z0dUL3p0zY3Xa9osbhj5wrQKh9I9dnuHNtpgU+2843ZafbWV9Rxr3TTWIf9kbfmVVlAbm42Ro0ZoeXRt0ODBabOw9Kgx2nmHHbXh29flpn0UNnOTJk+eov/6rw9o99330IYbb6oPf/Qj2oC1825uQp8fN17dc+eg9w2lm1T0ZMXll9XgoYM5tDypyVPHw2sDbb7ZJiojZzxSzsaEIWo2NjMen5JjC0OGDqt0qmwoV6GVx46Vv7bstP222nW3XbTlFptpFpchE7H/Qpm22WYbHX74wfrtb07QL395jH716xN0AhuiXx7/S33wA/+lYUOHcJiZoyv5QnHV367Wu//tvdjKofoEl3fe9J/NQeORhx9LB4yrr/obB+Rh+IDx+vtNN2M/U/TkE0/KlwsvcGhp40LDP5cMpqve3aPCkwjkjNW+0RBRUvriJ8K1XoxvYd5EEmAKvbaU3kSjnw3WiZK4m/Vz/PjnVWtr5/LpQ/rohz6o3ffYXdtjP4M4RM/icOmfAd52++26Ch27nAugm266Ub7Ievv6G2hFbPDBBx/SpIkT0s/y7Gs332wLrbve27XFVtto/Q02wH4mq05bo0eP0XPPjtOzfAnv4mLO/2R5UZSyDja4LGpHR53uYf3JsizZUsGa3c6+cTYH4LvvvVe2tdVXXx276NQM9rFLc9n2IF8Y/YXee4icS26DsL+CdVuodGknNGCqIiLxH4BeIrOZFFIC9QZGxcjYmvTmFxz1jZv6PO1t7dp266201LChuh9h3sHXhTzPtS0OaujQDk2ZPFHXXHmljv35kTrq8J/q1NNO06OP/0MZG/BaWy7xiA3QkGHDNHTIEFxYoR6cSXtbh0ayqRjc3q4Xpk/VXy6+SCewcB98yGH6LZ+WHnz0H6m3bbU2ze3sBrpwzGO0gm9gwOUsEEMHD2HzUnAD06UicJ+R4ZB72Gg1mOw5mjp1ii69+GL5n6D0p7Drrr5Kq3KDuBwn1yyDvqB7TGoNKNjszZOIhWCYh4jUl7JXnhExr6SVWLIkMP/MlP06F8rQGYlJZ66HshkeOXJk+juZ58Y9qw5u01ye4wzMIyI0ZPBQWVee45PpAw8+rAYOqKMtU818snYOxbP4evCwRo4YodXGrq4ebi070e011lhDn//C5/SLXxzFpv53+uEPvqtNNn67YJD0VfCus0mOpFXCJiT/U6qPPPIIh9suvW2dtTQK26jZhvI29vohaTAOMXC6g+S/idh//2+nfyXmV8f/Wv/zkf/WSMbz5JPjde655+mnhx+uI4/4qf56ySXyht/9LgrzkDLGl+eZCg4hWWT0oNScrjl0KVee1dK/5OSfAd7DJvmYo4/VAQceoFP4LNuOnfprzFDkNKi9TUW9Lm98sixTnueqceOSYe9Bvmx0q85i0dHRhqwy+Z9nX54boS9+8UtaddVV9MeTTtTXvrY3fT1H06ZNVXtHhzoGtSkYZcliM4gb2OHDRqhBGyVzBZqnpI1co8eM0qhRI5BJqZkzZ6lzbjcbuHbAX196mM/pmsJmaeLkyXqBCwz7gEmTnk9/wNnJ5UKdjf4DfKG5gQVprbXW0W7cAq/EQWbPPffUqJGj9Le//U0PP/IAm7jH9fyEifol8t3nG/vpssuv1NRpk3X6Gaekm+Hp02coc49RscI/UWNRsiyIlOTt01+Rus1LioAasFtpglphgATQgDLQSVVAVgZkLPSgHb1Ymq99nV3depCb8LkzZmlwnqkth4hyYVdtgwYx79NZ6GdoJW7Nl2UD0SjramdD4AspEfyvlXV3NZTVOrTiCitpqcHDkg77K7e/JnTDv6ezhy8QPZrNV41oy+lPQRcKNwFEstOlRw3jQqqmWWw0urH7IXypGDZsKXjVaKVHg4cM0phllsYv9Ggih4lgHRw0uEMzuYGv08bHP/7/9O73vEc3XH+jvvq1r+mII36uR/gy3tPdQIcKNtylaFiDWDeHYN+B/oQRcPfGzIVDuQAYSpu2xRxZZJlku5FCiIO2OzVhwmR0ebImT5qiydjFZNZs28gsDiIBz4njxqU+DBs2TO/iEm79t62rPfd8j7beelvdeddduvueu/XgQw9p4qRJ8t8O7fetfXTCr07QeC4PbrzxBh159C/18MOP0m6DTd4cZZ4L/3YdY7AtNIoCmeQKOmfdVyu8dSXABGfMc45eBXqQ5bl86fsgX9mXxRa2YS85evhS1m09yyGiVGgFbPqp58bpt7/9nb73vR9ov/32069//Rv0a4JWW201bbftdnr4wQd0z913p68RK6+8sjbffFPssa5b8OO/4vB76OGH6qijjtJNXBTU2nPkW6JzmfyVrLuni3VibroUzLPQ4I52LoJqyrJcSw0fqUHYfxc219NT1+zZszRl8iT99S8XpQsn/+z1jltu09KsOV77vD6FuaPbYqx5hPIsgxeGpyqU4KuUKavUkv7u6736kgO7z1iFdTOWYNpyBQIMBh/s8iNDoHmbSvIbb7Kx1lht1fT59HIWzuWWW1a77LSjZs2eo9NOP11HH320Vl5prL71rf30/z78Ma24ykoqcBgljqLB6a1OXLARKNlwKXL1sJhOnz5TPZ11HMwsXXH5JTrumKPYypX6v699VV/+v//T6muuoqDrdoydHBi6WZR9OzlhwnjhmTSbzYJ/6w1rjeS2x/3N2dSIUMtKLc8N6qp8Yn3ve98r/67zB9/7HgeHg7TvPvtoJ24aB3F7WXd/cMBuo4SRJzoCWbhhA7wGPhExENXKL9ESKOf1zvNcTWupoWxIN954Ew6ic/ga8Gv5n1J9/vkJmoFeeiF9fvwERYS22mprNqPtOufs83TjjTdzCH0h6f0z3NpfddW1LKSPaIvNN9NIFu4sx4bY5NtJ7cRt5Y7bba3VVxurMWwsBvHJU9hSra1DtVq7Suyjq3OuOvkKN4GN6e2336GLLrqYTesIbb3FpuqohepsmHN4ZlnOGAJbbJOwn7Hc5r/vfe/VNtvuqGWXX1FD0ftozNEZp5+iP/7xj1qfm5f99ttfaRM8epRCmWp5O5uHnnSYzvJM3Wxw5nZ2KrAx572wFxwilsG2Ry09Qm9ff1029V/TTw46SIfhhGTkogAAEABJREFUjA888If65Cc+ruU5bNsCGj3d2HhDDj04yBJGOXzT/2wx71CwGevs7lbJGChOGyzfCB108E904I9+mBz573/3G74C3ordMzamCRNUlg1W1jY4bdbmzunE1BtuQu2M0fKwjZrOyA42gUOHDkNOPTj6OWpwSLn22qu1zz7f0j777pMWnm9+81v69re/o5/85CA2P3fje+rwb1M7i0bJjVRPV49EBxtsDBv1LmTUJf8O23+EfsAPD8QffU1f+epX0IMtNWbMaO26247ajnkdwmWFb2CnTpkqb9ZGjx5J35EMvLIsS2nrG8zd1XkQkFQ4BjwP20o0JdAUj+e45PCgQEHR4JJ1pL1jiDbYYBOtvuoauuKSS3XDddfpGQ7zs/h63Nk9V88/Px7bnK2VVl2Vg+XSevLxJ/TU08+g/TmHy5nyP6HcwOevMXYsl1cd8hcJ24DXI7fvja0PI7WsxqZicLIZZbmmz5qpLvgXHDwabBTqBb1EdzJx6JA0iEPKmDHLqJsNx+Ncls1m01EUefrnSZ9+5llsemT6qU4NvWYbo8Ftg9QeGRcSg/SZL3xGxxz7S+24/c669K+X6IrLLmW0dUUOd/palKXaOGgMRs99A+qvB16rgvoZ+B7ssJsbXLohrEjWxYI+dvFFDjWUD1aH+CdZ3/qm9v7Wt7Tvft/Wvvvui43sqwsuuAC5zEL9Q3O769hzKMoi8ZmLPczC/szXev+JT35cP8Ru96HuVzncvOMd79DIkUtpww3W18c/8mGtt/Y6oqo653am+kI+cFOe18QQkHUkEMF4otbzVpOAJ9pjCmYY5YuMmPwULm6feOIJ+aZ+xWWWVVdXl2686RY9yJer1ddYU/4HQsaOXVlf/NKXdPhPD0t/a+qfnI/FTodxUN5hu+3U1l7TdddepxtvuFHbcOjYasvNdC8X2Mcdf4LM+wuf/4L23msvbc0XtVCGDnIZxp4z1KOM/WDe1q7BQ0eoaPRo+pTn2XfOph/dmvrCDM2Y1cVFWbfa2tq0LPvGoRzQd9llF333u9/RoYceosMPP0zHcygxLhiXHEKKsJ/PJJFRM1R+3aIwNLERoYhoZpe4GF8YGL8qEAMTeaBarApVMZFxTKyAQAARuYRQImoUtivPBjOhK2v99dfTwzjgm2+7SyuvsrLevuYaCm5JJ0ycqAncXMzCUczl1mQ8txD+PbTqnerAg/SwKbHziQiaCEm58rbBTJzSpNW7OjWNT/3jJ4xLPxMKHMwTTz2rcROeh6aujA190B//Pdv93CpdcN55uopbwDPPOCM52FVWXFmbbbqphiw1It0G1VES/x83N954fa1FH5966qn0+89BbDgm0zdvCkeNGKF2bkRznDLdwlGWisgUyIAOikQvhPqHUPTPvrXTb+LRMZNJ7ysdZ26Zt1AmEXv1alhH0LPNNttM73rXu/Xgg/enzfHPfvYzbtDO0Il/OEl2RE8+9XT6bPpubgEfffQRHX7YEdys/V4nn3yaDj3oEP32xJO0xprrcsP/EY0cNgQ9kjjXyj+Ps35l6FNBW8IOvPC7/a56gxuXmfIfEP/l4r/Q3pm09Uv96Mc/1sw5s/WRj35EG673Ns2eO4dNSpdEnyPHJonrRZb++daIUu040BLevum3VnbihCdii1OmTFZPo0CFcz0/YYImTpoIi8CKpHYOycNHDtdMNjRXXHGlrrr6Ok2bPo0NdzdtdatRLzR27KradNNNwE/VA9zq+Kdac9g4jBs3ns10D72QurHprs45jLeReHtMtn//IXfO9p/GNWTEaL78dacboNtvvR3nfn/6/fTDjz7GrewQjRgxTJZPg51hiWct2BzBEH6ZRoxcjpufUZo0aQIbmpmiGCjVwNl7I1QgTxHcX18m1O0cmN9BgwZru+23117f2Fv77PNN7bXXXvr61/fS//3f15jfvfBhG6qtY4jW4UC18WabcnN6p84+8xz97crr9eeT/sxXiGe18UYbac111tce73mf/v2DH0x/g/HBj3xM6719Qw3mK8jWW26iLTffSEO5KZ4yeaqmT5+u5fh60vzqYUHnGboWzAqPHDMAj5EupyciQEdKt14LkEBZWW6BHAvstMBPIzCQpdZdZz199lOfU43DxBGHHaYf/eRgnXzKyfrzKX/m4upI3X7nnVptrbdpm222l/+FvhN/+3tdefkVOvfsM/kydB5fqJfXdlturlHDO9jczmST34luFYDUzabZdtTDOmZdjMjUMXSp9P9GuP6m63Xj36/X8xMn8fW6R0W9W+nQ3JBq9HGbbbfV8nz9vvjiS7hcOFNXXnm5/MfDtkH/9G5ZdKSuGgfbbhUcUmts6v921TW68eYbVOegvtSwURoxfIRqmYTbkNemvFYTqqJ2DiQrrTJWs+fM0SRsus7B1lKr40u6WD8j6ASKl+yDA0SDywiEBUmpVbno+9znP6NvcYjeC1vYe+9v6GvEe+21N1/XdufgNFRLL7u8tthqOw5bc3TW6Wfpiiv/plP/fKpuve02rbPO2lpxpeW1/fbb6r8+9F/64H9/iPiD2nnnnbDTEVp7rTW16647aJllxmj2rNnY0HiNGT1Syy+7jNK0MZd5linzoOijQoqIBGqFt5QEyjS/TLj9HWuJB1egi5NZkyZNfgFfPlv33HMvdniBjj32ONXaOvRv732/xq60kpbiQLzxxhtrh+13SLq18cabaAiHhQ50f33/8/7LLidfVvur73rrrpt+SjcJ/zsBe5w1a656untYV2fIX726uxvYpxSsE/WeOaxDM+hZrhGjltXY1VbRbbfdoNP/fJL+hl+4+C+X6JF/PKc6lwDD6cO6a6+tlblo/scTj6f1x//gwPPPj5P/FbQGF1IN1tYCaLBeFb1rV0k7JWMWwVFEkBI6rjdNyKqe9nZcjg0Vtv/bAzVUONNkUOdkawi5DSAdmbbedmu9/e3rJge01RZbcqvZlj7T7LjLLhq71to654KL9Itjj8fpdGrIoKFqh0MHMIhbQP92etSo0bITtGeOLNdgPt8uxSZrxeWW1k47bJ9uaW+44VodyiLwAl8PVl19zeTzrAiDBw3WyNFj5BvKLFM68f2GT1Zj4PmtvffSmquvptkcWGq01d7RIW/Y1n3bOukPsAeR//nPj0ybhz+d9CeN5/Mr3VKOA8sYaUQoY3xhxpLIqn+wbAz9ca30ki+BiEhzSURnswROM9XsBRqqc/O9Cpvjz3zm0/r0pz9FvqGzzz5HRx11pPwvavmPCTu7u7gVWUZf/vKXk/4UeIM/s5D6X1q46e+3aLsdd9YPDvihNt5wI9rK5AV+6LCl0O3BQr1QdVwom3rhUAo2u3UO2O3tQ7QMG4tx48fp97/9rY6mvav+dqXevv4G+u73v6/3/du7NYjba+v8EJxlvV6wUVYKkQ/SMA7GGbsK3LIiqzEWUvTLtrTdNltpOTYmp5x2qn7zm9+ok43PGmuuqeEjllLBjd+IkaO00867avXVV9cFF16gCy+8UNOmTdeo0aM1atQotXEIGTN6aX3i45/UTozt0ksv1f77f0f7f/u7+jvjbeOrgTuyzNJjtOzSS6uWDjJiQ1WqfcgwLQ2fQR01htujDTfdUptvubVuvPpv+gN98RdB/w7VN/37cvs/Y8Y0ffzjH9OmHNqkOmzLSmbIabnl1wC/haa9MEX+12EstyzPtBTjaGvLoWVBYMPlw4L/laKhQ4ez2etWhg2vttqqLDg7apeddtJuu+6q3XffnQ3Nrmwgt9PSyyyvWm2wxiyzgj71mU9ps8025sBwpvbbd3/dd8/d+s/3v18f+tCHNIyxSLnsSzoGD1bHkCEaMozxLT1SI0cM0aCONuakweJ3t2Zzu73F5psry3M1mKuIwGeWLGDdKlhU5ABOAs88qV8oB+T7Fb3qyTcNQ6szneU8oJL5LLJcJbJNykF+8NBheufu79ShPz5EG663oW645jodwUH/hF8fr7vuv1svsKnuGDxSn/zUZ/ShD3xAd956K/O7n/7IJcAybIw/8YlPaosN11cHvNrbpOFLDVaeZ2J6VGZtfHlcSu1cLnVzw15ra9cmm22hHXbaWbfeeotOPPFEPfP0eI0Zs5z8/0EY2tEmbxq8idhh++3Qqc9qWW5Qf/WbX2v/7+yv+x98WP/5gf+kLx9PPqG7q44Oj9GgWrtyfMIL6PcJJ/xSX/7Kl3XtVTfove96j97znnepo6M98RWhhK69fZA23GiTtK7ddecd6uSwLjps3RzNF8QhgztkVSrY0AwZMljLLrs0+tepLr5gLsPGfccddtDO2MMee+yqXXbeMR0UdtttN625xhrJhofgs/7zg/+t9/7b+3TL329CXvvqj386Weu+ff1067sWPiRwaIPhPRifNGjwYI3E1kfR9gi+rHYgB7f/DF9zHrj/fm22ycZaZaVl6aF7GUxdsJYXQAmONI8WEEozWQC+hXpzSCAimF+mGb9X4J8DG5s1e7qefPIJTZg4Wffdd58O5mvXEUcckQ7XX/jil7TbLhw88a+oFzqM3+QQbHsqqd9gjfbIx4wZo+04kA/B9td523pae511lGc5X7c21JasMU8//bR82fdXDuvLYuOjR43BRrpVsqEfNWKoVh27oto7BrPOjcG+9uQwO0JnnHqSTmMt7+4ptf4GG3GYGCPR5lZbbKF9OVzPmTtHvzrhV/r+D36gX/3qV3rggfuUZVI7F83d7AvqPT3K8RsR4S6qqbsRVd5RBaGISDRL8itj1Ur9ixjY2RK8gWje00djmy3trYV0EgRyLLXFllvqcCb6hN/8Vnvu+S4Wx25qh7bfcSf99Mij9POjj9b/fX1vff4LX9Hvf3ei9v/mN7Xaiitot5120U9//nP9xwf+A+dEt5jE0Zz0Pv/FL+qQg36o9dZZU+vgkA448EAOHEfrm/t9Ux/68Id1+OFH6gc/OFA+8S0Pn2/t+2399Kc/05e+8EXt8619UvqnLBTbcpDhwKdll1tBPzjwR/oWn15Xgb6D21RvFg444Ac6+Cc/0Xe+8119h83Pf7z//Ro8uJ2+l0ykVKIkFpEnvCxBD3giMkX0yWdAcSu7BEnAs2To65InFOAROu0Nf8ECnOc15WxCIkKrrbaaPve5z+uXLNy/+e2v9fOf/0yHHXpIchpv5yY6g3YFvmJ97H8+qoMP/kn624Ajf/5THc0Nybf22Z+FfCPleLuchpdDB/3J3j8BWHOtNVSwSbeTST/TiVIZmY0220KH//QInXTSH9DhQ2UHeuCBB2jvb+zFYr4DNy1DBavkmLLIqRNApgY3IL4FPPIXx+hzn/usajgulZnyvE0l7QzqyPWud79DPz/qCP38yJ/rE5/8FHRf0DHHHJ/+dRdx85/noU0320qHHX6Ejj3mSA4GH9HbcMD7cSA4/HA2YBusq4gCh7yevoH9Hn7YofrOd/fX9w84QJ/jk+9KK62otddcS4cddoi+//3vaLVVx8oLw1tqQ6sAABAASURBVNg11tSPDj5UPlitwGEiy3Kt/faNtPc399Evf3mcvvKlz2uzTTfRV77yvzqAsX73+/vr4IN+oo9+5H+w2+U4rNVVlD0KNeTbmzzv0Oabb6XVuA269babNWPGdK2z9tuoc5C+DA8vHIJ62+221o9//BMOfJ/RUmxcCgy4YH5L4jKYdAuSOc6Qu+kNBXlvRDfddEPt8829kg/68QHf1+EsZF/8whcY02qqs+Blea6ScZg+Rwc+8F8f0BHM+w7bb6UG5ZMnTeXAcJ+WZ86355O5+13nhlqiXXxKAU2JrxN9EYFmFREuTaheNCWtJ0kAsVk4acpIB1AorLXiAp5YMi5Yk0ZwUbTrLjvou/t9W8cdc4yOOuoodPpwvtL9RNtst6OKWptWWWUVffGLn9MRPz1cB/3ox6wlP9S3v/097fnOPTkQDtIwDrbf+84+OvDA72kV9ExFaKWxq+tb++2vAw44UGvgF0pwa62zrr77ve/rD3/4g772tb20+Rbb6BOf+LSOOvIIbb3VZqxpoTb0a/jwYelguu9+++knPz5YBxzwI+CH+uSnPq0Vll9O/udL37beBjr44MP1v1/6kpZnU//ud79D3zvge9B5jTpEX8APrb3WaoihoQYXDd1sTKzLWZ5r7NjVtPMuu6Y/vn+cr51tbW36n098Socfepi22mJz9ZR1LcVG6cMf/SjjPVA7bLsFX8EGoWt19fR0wbOQ8FMRyBTdLOBv2y3xiwJWXHFVfe6zn9dPDz+M/v9YP2PN3oc1d9NNN9NgLuwikwpuiwt0uqS+f4p00EE/1mc+/SkNahvE15q5uvfuezRzxgztsvP2Gj1yOG1LTKMcaNYRuCYmZed7RcR8+VZmoRJYcguYwsAegpkv0LE5c2bryaee4IvyUvrqV7+mg3/yYx126EHyOrnr7ruwiR+BTqAnqEVhv1mSYHQl9QP/G/gAH0g//OH/pxN+/etkiyutsKIaHCxWXmUl/d/XvqbjfnkC69EP9JUvf0UHfO8A+W/vfEhee8019P3v7Kevf+0rGr30Mirp104776DjjvuFjjmW/er/fVVfY8/qtXzffffT6DGjOdgP0h7v3EMHH/KT9JOkb++7L7y/q39///u4DFhaGTZUS1/+cuyhlFU2gl4CdPtN+2DeC+t7zFcQMX9+vsJSCCSU5bmGDV9K62+0uTbbYjuNHDGKSS5k4Q3hNtT/w5Y93vlO7bLbrlqDW4utt9hKG66/voYNGyrfcOyw/fZag8nzTaEUah88TGuvvY422WhDDRs6JJ3+3rbOhhwudtaeu+2itddaR+tvuKk222wLjR49knYyrbPu2+WT4DrrvE3v3HNP7bHHO7XB2zeUlAPSCG5eN9xgY739betyA9iRFv0hQ4byVWI97bbH7nrf+/5NO+y4Q/pCkjPhqRKvoD8WQc4rA0Re80KQakKl1CBaz5tGAp67vs6GMmY3k3hHBDpcKiI0YsRIbis20O677c4NxLuJd9G6fKEasdRSyrOMTWxDg7hZ22Tj9fXOd+6qd+65B59Ot9WybAT8Mxzh6Hzj4E38JhtvrA25wbReB86vpAzfl/hkea4RI8doo403TZuLd+75Tr37PbTHLfgKK6ygbpxgwYKcZyW3iT3q4cYwxH/00Zve5bk92QrbWmuttZTDiyIVOOUGmwVvlEeMHKFNt9iU/r0z6foG2Ncmm23CoWAdZZhJWRYaMni4NtpgU73rHe/Q9hy2/XOEddfbSJtvtLFGDR+sEn48Wn65FSnfRu9/73v1/ve9XxtTPmTwUGx6GOkNtcEGG2gotltKGjZ8VDqIrM+NZAe3swVjGDJ0KfmriQ/t226zjUaNHKX1119P70J27333u7QlXymHc2tPl1SrtSuPTO5f5gMQG5JVV1tT78BxP/PMU7rqqqvUMahDm26ysdbldmno0MHKazmHjWW16eYba523raV2vi5aFiXyjvDcFrJMgv758e1/wc6T4rTxrDGvY7l52nm3HfTuf99TW227pZbmsGNa+4fIEFjqE3PR3a2VV1pZm3GIWZ7DY422L7v8cvnnX3vsvht6sLQy2qylrx9Vi+3tbXIfBZ6Bme08sMy8IM5DtBKVBCwYUswebx7yBcbTYNK8QSiIQ4EjlvIs19pvW0O77b6z3s3N/Dt2e6e22HQrjWTT3I0C90A7iq9m2+64rd7z7/+mnVib1mJtGMyaAFsNG4w+bbRBslXfnBfYmjfGG66/MYfVzTV8xHD5YDiI2/111lxHe+y6m3bYbgetvOJYrbH6Wtp6261Y20bTm2om3cdh6OV6663H2vQObObf5X82eDQ38QX9sT6MGDma9jbS+nypHzpksFZaeWXtwiHg37jZ32XXHbXyyislPZIKxpcpY4yBGDzuWlub3v3u9/BlYzldfdXVmjx5gtZYa31tscmmWoXDR0kbOQelddZ6m7bfagutyJeOnHUOFwQf87J9iYOIFFnlA0XIslCJrBqNQqO5yd1m2230Xmx+111316qrrq4cP1NwkE/rI2nT17t7NGLECG2MPa6+JjTYwyMPPqSbb7mFL3nbaNONNlIetAd/2KrAH5B80VO6cy/CthBvXgmUqeuR5VKGjpH1z5EeeOBBrYT/3H2PdyjZKuvd2muvhs+uqV4v1UAPbD9EyrNMEegkmYy0Uhx8FV4GfdtEb7PtDB8G+0h0K620krbfdju9g7V7q8231Dprra0tN9tcKy6/PHvLYdp00821wfobajD7VNvDCPaum2Azu7P+bbndNnxFW1ebosdvY1/p9grsyP59U/aee7LPtM3tio2OHTuW9jJ0uZQPDG1ttdQHD5juUhZO0t0yQcq8iV5ZNYj+PfaAmpBRUE0KCQbrdwURQT7EqMWbWCywFgI3FDgyG78hQylqOBBB73y9p5GEWUfgXV1d8gaq6RAaOKTSwOTX8SANbkbrbI58g9Jgc1BGm+qNHjW4wajjuEt2EU43jKv3qISncSX1G65P3YJ6oj+BUjrdoF6hugpo6JKSAFhsSvNK9PSfMhFCzf9K6GAAPgIcIMrmB6UQvFMx8SKfFsESIgHPGrruCIgIRZCndwWLGNMug5KelDLOUIJsoF9OO7b+Qi5UWAWvnp66uvkk2bBekQ/42RYyHJzrFuioceF85Oh1CRiTy2/YJz6JN59dUx30NKMfgU6X6LIpa+6rK8A/I44I+ut+NqAs5WJFKHOCW8KCdkV/HBtK8oYC3uG+yGPnZoR8g68Sdeyth81wwThsb6bLMhxh3i6PrU4/jKv6Vypvo1d0pGAAxomQ0T6d4ikTuD+2bUNJO+5Hw8Kjx5ad6/YkX1FQu5T7nnOD73qFeUWe8G1skLbaeht98lOf1lprrSlGzk1pjwp41diguN0G4ys4BNAd6ijxighlyqHPgJBDRMgiiizEWUx5yFMOL/qMvOybGvWCMReKyCT60MPXAssgFMrxc43kgxpyyCK0EYfCz3zmU9p5l53kvkKmvOa6pWdQQZ3IcpNLERLjN3gcgdMyKsJ4ilqPZFEYJFks/js0zxPaqFrGG0jyDGQKHeqORG1XQLLVhgr0jRlQWxZy3RIKPxTIc9yEUEYbOWsOddDxpEdidkpBWqhue8Au/WVQKFeP1yH0zrrnNmy3BW2WMKeKCnTDlwPudwl9HV0qrFepvFTOIbiDL95Bv4y3zppHN7bXoH3IaF2smXU10GfRP/P0xiRIo1DKIteaa66tz/IVYrsdduJSbBA+paEe+lkCOeURbSZN7LwJ68JHdWNrGbKr0bnUR0ojgvGHxJMgkwSuDh//C1ElciwYr3pphbDryAS0UQp02333Op9oKRjF7ewHP/T/9LGP/o9Gjx5F3wpoSxX4mQayEoKKyBThRpVCRF86IVqvN7EEmGD0QAmkQOeDdWTSxKl67rnntfLY1TScS90SRSiApOdUyVCBIG+fmOWB3tTx810SuLr3fqQC3bY+zp0zJ9lIjv+3HVr/0jqMrjZYC+roWZnsTuhdKVirRP8K7LO0naXyRsLVWcO97pXQN6hbQJPRVoaOYsLQFHKb7kMduyhBBgyN68GuSsYZASK1wgiwEZGOCEWE3mwh0wL7bGQTpAintcAQ4bJCGRNXMiE9CNiOUApF1qYsqzkl3DcOPQNdqs6k2CllbE4yJlVog+UYUpoA2Z2BEzXzLFfudISKyEDV1EGdNtoLJqMsgzoilKpxc5KjgEWJusEsskwGwSfLM5mQIg42mTLK8jyXQ90KQiJPCzlkpEWdEmKDekMETHvTVeS8oco13y/GNEta8ZIpAc8Y+sGcV/2r8hF50hPjIjJFAutbgSqVoEN5huYnPSGNPtmhWYMglXXM+tPA2Vg3syxXjdu8PMtwdj3ybWJGusHin1GWZdhKwE9AoJvoG6zl4NbMyyraXgtlUSiTVKPNMtlBQ7AQVRTgjauzeJNURCiHLsceI3JhMuIsTlzKBwIzKlVgl95ol1LQPkS+ISzYBDFiZRGKCEmU4zgb8C6gyXJv0jLQ8MKO7CgNJnXcAEelJK+SwRgC/rW8XTm2GmGegJ8sFEAPmxdvxBOtgrZzNkiN9AUnkBds4FfQ9xI5dnPjv4x23nlXbbTRJsoojwjleUZN4cwbEn0ukFEDv+M+GUCBD2XKXQy/MkHmelEqA+zPGiwCntOMfkXQP2SvTBwE67Rd0E4uLyj17m5lWUa+Bp6vPl4s6MGmm26iHXfcXsssM1oiX5SpOfUFpAuuL++UESXUBudbMJ8EAhkyP0yHmBblpYCQD845NqTI0vQW6HSBnYj5YmqSrQidLdiot0WujqgpjxCPfNBrsH4ppDDTCHQHDuACZEBfgjdd4U1DSNYx/6TNumUdqdFIKOSfnDWwDxHomurokDfOBfoHWygkx5DLoUQpCmyqnmwllGe5fAgpuLF3X5p65bRtwvmMcdINdK0u8y4VMt5/WJ2+gGy4kbbcahsNGbKUPOY8MkUaS4ZUatgTOg6DWoRq2GGOPbrvIcGpFJV4SkUEQDaUxtHAH+R5rizP5P56M1ZPY4WgkGy3DfYAJVX8tSNnTY4sU8aa3WB8y/GFdJdddtcaa6yl4D+MTsp4gMgyRRhCEQGH1vPWlABzayfOHNexxc65XejD2tpn3+/oc1/4kpZbfgUV6EoGTahMdphRBZVDHCgZb+HPC/Q3o8AXQ6K8kwtowbOto10iP7drbrJrr5FtbV5bhd43sK9MxrmNend16LBu0pxy9E/Yo/ATgY0JfoVK2c4jC7Whx+1t7aCtp5m8VjVYvyOcD0WEbKP2B1mWpXRab+QQfgHNmOSb7Mlejf6G+A9BWUAi3cD5GUSw8CwwT4hPXHmepQnLs1zt7dxQ4sQqhytFmI+U57myLCMPjknK8kgTLIEDwEqyS2IiSZkwojk5pSJCuesBbl+ELJdqtVqqVqAQTGuaTJeX5A0Z9FKocJ96Qa3wLyiBYMyhiFCWZSm2TiRdwasGS+xqAAAQAElEQVRUOKnufwGFTUCJ44IUOiUouJGvc+uBGsuOqq0tV55nOKsedXbORb8aic7KaJ5Kwe2hpOh3gT7W+9lQhOu7rKRKSX2cJg1m8KQ7qXaBvjZwss7YEdo8Iswzkp4bLzlt6OUBURaZUgjJ6RJHmW5VaD+gzwD2ZoqMjTDOvcA5ZkGJu2KaEPVCtmHziQhHCSJCEZHSfkUEfRFyK1QwxjzPZZvMkHEJvwJ+jsmmejWcMwOmDoUKifpBfyOCnouiUhGhyAJ+fDVE7pZBRt6x/U3B3OR5yLiIkINlboABfMrE3/n+AFIlMnUVQ5157uKmtwDX5GV8RMj8Xdf/B2mXR2T0pxqjxxYKeVwVVO1FhFxGkVrhFUggeuuUvbGjlE4vocZCMYWYhcR75wO7ERodmUr0z3bi+fLcuboivVUwUcZFhCKiQhJlec5c5xWOZiJCWZYri4ofexhBJuuHCPN4J7oMTKD7dfyA7T8UEeDoHe2RkNu03hborPNZninQ5ba2tkTrMoPxWZZBEsl+zIXK5KUS/axzQGlw6G5gr0H/GsmuCrlOKXQxXNcgBZUzaLI8l9s3aAHBdAYXRUSSQ0YfDCK4XgT9aaspy3OZcYFA0kYLvAhZnimjjmnTIYdx53koKDOJD1xJZowB1Bv9tNp/rSTQO+FovjzvGTq+yipj9YH//IC2225bDrmDk42gzfSglH+FUmATWWTYT4NNerd8GPX+EQJ4YH/oUom+RYQ6OjrA0Ugp4kw5+z5yHEIK9DaT+ahfKFNdUwT0oWpNyrGHSHWzPEv4Er20LVlHbYeuR3Ny/0VwnqiiLSXTGRdR8XXZmx2yVzIAC8HQrBuBE0LoEcEGqa1XYEgMAgutjgMjmR7X84QYXGYwLhXi2vM8V6BAJZPvsjo3Go6dF6tABG3Z7yuYkKoNklV13omOWL1IupXoQlJzYtVb5nyOMmQZbcLXyuD6EaGICkSI6EuXMDSAbj1vUQl4fq1z/Yf3Ypx1r0RPTFXyKnAwFUjOlzi9OjhuNHKbWYVDlcAV2ElOHT+BE8vR0QL6BmWq9DTpf3NjoRTcBynkEDJPEcpUP8duyOBQ6wkiIuGrOuoX3I8qiypXid53RMA1FAHAPqPfWUZCIQfXjIjkUGveGPC5I7BVl7njESHTR4QiqrTzIkRUOJKQlgmctpyrjX2RZOB8jYNCO4esjDrOm4dxTfoIeJHJsyz1RQSXZ1mkMas3eOwRXkwqhPNOWVbm6bQhAn690MyLvGkMEQE6Up/Nw+C22tq4gKAkz7N0+WGfVpVlqR+pGuUR4TfQ9/SXfYTL+8paqUVLIBQvSRRBOQrr+egPnjfPU5ZZLyCAS0TIeUNEKCLkEBEJH1HNfUbcxubd9SOaNJ7rGnUqfhGRdNK83K56Q0SFj4ik514TrdumMW2e50lnesnnRS43zEOQcL7asBSV3tGnlMfvsETKGxvzhpR++S3imAceRw0bc7umS19N8DcKLTS4TY/bmzSnDa7vv9kyPlWkvtM5vJu8IkIRkYpN7/KISLgIx5Xc6HqiabBXcJ9SpvV660qAuRdO0Ho/aNBglsyCL2VdyTYiItmddcwWmtVCEMh6nWcZZZH0J8+zRN/gMsc3+h0dg5INNbg4c91Bg6q89cl5615brU1Oe6+XZ5l8uEh4bKjCNxLviEh0NJx4RkRaV223xpmn0zl2G9FHGxH0L0s8zC+jjYjQWyVkL3cgFkJ/GFg/IpKALUgLy+C0wc5WhKp+wykcXg0BW6BWDVAijSLxlny1iSfJMudCESHJIEXQ9RLlIc7AR4TcVkRz8kpFGJerGfI8o29uLwdlPqbJwOWprmjLkGVZyjuOMB3kredfUgIRkXQhxzFYH0Sw/hLJi66djaFZZrzTxkU0ddFYQV/joNCW+ElVWemFWlUo0XtUj/JAJ5s6qH4hBEvKs4QruCWVjIuEiwg5uH3HFb9MERXeOJcZImJenYiKpklvpxpZLkGT7IE4yzOlQ4LTEkWhoLNB3SwLZZl5SBGhBQXzNkSELJuKPubR53muGocEt+f6EeEIGBCDd7tZnisyQ0bbOXRZimssCBn4nPIaN0uOI5qyLqETdKZ1fyO1n9F3Q0SVj4hEF9EXe647+NRtfpXcleo6H1HxG8TC5zzTyPzlMk+lUMoLGs2ACyAjLyASKIXgvTCgqPW8SAIRltf86IgKV3AbaH1zaUSk+bA+RFS6EFHhPEcRVR0RIqJ3fio6lxsiKhrzNEREmruIPrqB/L3eVfpQHZDNxzSORYiI1K+IkENEpLzLIyq+IkREast484uIeX30OCNCELDBCdkmbKemcz8LlDFnA2+IgKflgt8oExQCozzLVMvR4bBehjLyTVC/YH6GCNoBnHb7JomAE201064fEazv7cnnGW96xy5z/xw7HxGOEjRxKdN6vQUl4LnOcPPoi5OMsASEJjbVICKU5zVJ1slQe1ub8jxLuzPbTxt+HQaUB7qa94L3ddD06mCO/xch66fLGetUpYOlaILS+Z+IgBdtZpkcIsIRdlWm2Dz7Q0Lyigi5XwbzN7hdH65ND8m8J6LiOQ/xJktUknmFnbZgDK4eEUxCODlP6C6LCCY7l0NEpDL1Bs8LKHABVF1JeU82rDImuIbi2ClFBPwFBC+lEFlGXoBjQ8AnBwJc5aSlIJ+J6rKSeSINzpds1gyS6YN+Ri9tlVcr/EtKICKSHohQ9jqgiEonrDuGiKDUIEVEoo+IlI4IOdhZ2Ik47TqOzc/piEh1nJYipb0pBZ0cVESGPuZqhoiQaSNCETjb3n6V6LB6Q0SkxdltRsS8+hGR6ooQESltXk0QISJLTs84pVCm+hFBrgBKZXmmLMtJ+wlFZE7QXynDFjPKIqI3nSki5gMRIubHZdRzfx1n1K+1wT8g5Mls/ywOEQEfpf7keU7a4w8p3IbzmaReHHEEZZKyzHgpIhK4HUNEaFGhRL4RMY+HCBEBH9GPDFm53SAf82giMmVZnso1IJifIWNMhoiqbh9ZkFwQgG49r0gCEcF8ZIqwXJVuIz0HEVVehIhI5RFVDAp9rjYIEeFsgizr42MeCckrIlL9Ji4iUpv96X1wMESEHFyWoScR1lml9iKqsiafjPaa4DrGR0Rqy/kcO7AuN/G1tjYplEJJIstzfEENPa2RCxqRIqICSbTcC820XjJEVHVNFNGXdr4JERU+Au7YDwPjKZvFiugrd/9d0Oy/xxoR2E6eQK3wlpVAUg2PLnhlAI/3cm1t7cl2rKwRkfQAdymT5ZGnOKicgQhyAS7LcuXsESOqw0JEbz3sR4SIUNYvTVYOTVxT/4zLsRmD0xGVDrvceYPtzXZsXERgX9icC4CI4K3UlnlHhCIqSAVvkVe2uOOwkAymjwhHCYzz553mH38YGVGVu8x5Q0RzAgqy3swLB+64z6FkaIJv4pTOkhUPiHmom3CUoDB4ITEbIscT8n9k5ntKNlIGIyPCEdX8swe3mbK8qrZLeBbcuMicemm1kBARioiFlLbQ/xoSqPQmotID648hAj1Fl5oyMK4PKmxEVac3l3TJqIgK7+qGqhz1pqneokTbvywiEs60EVXa7TnfdFpOLwqomvg0bx1pVemnDW6MRESuZB4wypLHCInH4PYMFULzQoWbl1VEJRvjDS5x3B+MM5i1Y/eDasluTVfhqndfvh81/W3iI6r2TG1cf3k4b/xLgeldbtrCt7Lwdj4iGAs96827vIl3LLncQgpVgQmsEozDvqcv34tuRf+EBCJCEX1gVhEx38ItQnOeSM57FoSbV0giotIh0xlApbaamwrjetUAvEsrvYiIKsPbNESUh5p6VOGKpA/UcHFvmlyTIdiIPj5kE01V1zklnu5LREUXUcVwoVBSWA/J9fLsjdQMERW9eRqa+P5xRKR2jIuo0qaNCNlGDCI0cSRVShUEbYNwWRPIpnE47g8REIOICPk/kq3nLSuBygdW82yfyEDLTNUa00A/Ktto6kyphgrA2tTEOU2t9BiXErwignf1RFRpl0eEIoJqpXgngohQRMxLO2Ha/nFEJJqIoF+lbMMuj4iUjqjKjVsQNPlFvDTdguouibjKo7yCnkVEqmUnZKGUbNCZjYTzKyKSQxEhIhA2CdxIxqGgSWtnU7IhKcuS8uogQYKHSaVOBN2jmZxPqhEVD9O6HmgF5VBCLwVp3nIfTENCpnNcJE0sycODPlTl1MwAMzJRAvejgpRtvf4lJWD9MHjwEaGIcDJBE+9MwUbSsfUsoqJx2jjTGZw2zsURgQ6i00JLsRfUHqeDTpbOl6QLl0ATtKkEWkiIME0FTRL3x20amrj+cX98/7Rp6AKWQT+cUS9ftyH3twmpECKo6XzpGqYBQFIInrefiHCUIKJKWw6GiCofEYw1U4RlADfkGciFnMQSUZJ2TDE0GXZOSfIXfXVEHyKC8ki8SverH6g39MdHRC/2pSPXMYX7bHDaOIPTBqeb4HwFQX/cR+eqOY0wLoxI4Dop0Xq9JhKIsK6UyaYiIumG5zAiEk4E54nQq4quaT8R1Tw5HxGpbkRVr/+8VemSuQ4gk4NxrufYebcREakN530hlkGasQ5mxBRRN1yUaEzvjOv35xMR89E1y01rKHn550fGR8BYVZtVvpmudLHs/SckzZ9qcpsGpw2u43ggGG9o0jrd5BERFTlx2WuT7hODSviISO1oQIigntfnfmC+A8ha2beQBCIq/URNFGl9QVNQA/ty62YVo0WgFQUqVOlths2IkPQDvamwUFO3JB+Z+SrZt2maEBGKqGygajPkOAH8rMNNWsegEr313Pn+EEFdCIxzOcn5nohIdV3ugogq7/SbF/p6Xkm4L79YqYhKCBEBfSkLrq2tpjz3og5qAY9JI9xcKMvyBM5nTLLjCPMCIlMkCIUEOB/EIetLnjtfQQYiBxxHQNMLWVaVqzdk0FCUci7Lmhm4GhlR1ZVcL4xqwb+wBCJCEbFACUREKgt01LrkWAopgQihSGW5sixXRJZwvHqfqjwiV5ZlQCR8RJDOFFHl1RsGZHvLgzhrUpCOlI6IxMN8tYAQUdG5KKIvnfK8XC+jXxGZovkfdEEZkcqUoMzlIMI0jgGRrkCLDBHUBJqEEaHUNvKIyCSFHKI33ReHIgxKsetEhPqHJi4i1D8dEalOROjlhIhI9Zp1ImIeXxH6t0F2wBPkM+obgrgCkCntuAWvnQQiIs2VBoTmnDXREZHo+uMjKpz6BZc3sxGR6kSEmiEiXoRTb4iI3rJMVXA9Q2+ut9y5iEj64fYiwqj5oIl37ALOx47gHwlcpYJQnufg7GeakPfD5akswm1EajOiirWAEBGJXr0hIlI+oq9OSIr0n5RFpkg2HYoINUNEXzrhnDdk4P0ACd96vWUlEBHoBPoRubIsZ5x9+QinA1ypUEZ5Ruy8qjR6EhIlAm+I3lgpZP10LiISzq+IUFCmCGcTRATZmJdu1k0IXs4TpcfpowPjgAAAEABJREFUiEj0EVWcChbwiogFYN/8qGxxhxARSVCm9+mpCc77r8U7O7s1Z85czZ3bqc7OrgTO+5+R7OzsBO8ywxzSC4KqrHPuHHV1zqU+ecddpOcCpOf28q14Uk5bxrlN/5OGVdwF/772Oqkz1+2n+nPUmepQTt58qjrmD452zKfT9L1p51tgWbegTw/6dGUu+toHltGCdNs4lxmcboLzle5Z5wxzF6l3btvQrDtXzTqLV7+q16yTYmxhLtBJ27YJ20jn3MqOupo42wS21KTpsyn6j00Zn3hB/8rjplwcu5+ODU6//vCK5TlPBu67YTY+yeD0osbhubXsm+D8ouq0yl+5zr082c2vE56b5jw5dh57wFbmp1tQG9YFw/xlrteEBY3JZQPxxnVim3Ox2Tm94LRxFXhNbkLVv+6urmqdRVdtu4aBfF9Jfg5+xL6kGTu9KD5uOwH7h077EuS3qDqt8vn15s0nj8pW5qb10zrZxZ4PXCc2AXSy7/P/48NxZ29+Lro6F/rOfjr2svQs6RdtwSfpG/FcoBN9Mzi9IHCZoX9ZM9+M+5e9ldOLfWDwwaD/ISGiOkAUfEqcNWuWpk6dCrwATNWUKVM1efIUYoPTk3vTzi8aJk+ZTP0KJk2eRHqSJk12vpmu4inQTZkyRaZ3PCXlJ9OWYQpxL7gvk6dqCjA58ZmiyZMA0lOmTNIUeFTxgHoJP6W3vBVXcmrJYco8PXujZGE9Nbw67U/GPgxTkr5P1mTswvaWgLE6Nm7qpKrM6UmTJlU2hB1VNjr5NbQT8za8OuOtxtni1ZJDpQPW5/6wuHJ5JXUWxXvy5MnJ/sy7Sev0wsA01fo3v31MTrY8//hM24T+5RVu/voVrqr/eqcn449e7zZb7b0Rc82ebJ6eWv8M9IP5nzxvrWGdYT2aDExhX5nA5UBrzpDVPPm9PunFPjD0Pyz48GAwjnODhg4dqlGjRvWDkaRHACM1cuRIjR49uh8sTdowhriJd7qJc3qMxowek8qreAz5Ju1o0mMoa8Ko3vwocKN7oVnmfBNvnNswzkB+lPOG3vx8/TSuBfPPXUselTzQndHWm38WXqk8+7fv9CvlU9Ubg94b+sY2GpuqwLgx2OIYaJxuwpgx/dslPcayGN1rf688HtjO6Hlypo0BfWj2ZcmL/9m+2mc14ZXLcsmTy5I1luaatTA5uXxhZX345jwNXOcWNlbrhm2lCc4vjLbCz29rFa6v/dHJVkePGo3tNfsyCtyo3vxoub6hquP2mm2PhqYJxjfTrzy2/Q6Eqt2X4DmGsoHwprF1+t7qaz89Whx5WNf6Q7NOH26M9SHJ1bo6RmNYg0YnMG2VH0N5fxhN/iXBPAfCour80+Xu71sHFvvA4ANCRPVVISKcTT9Rigi1t7dpyJBBwOB54EPEsGHDZBgyZAj4l4JmvaEaPGQotIbBGtpMcyAZAgwdOkQGpxMkvoOhd9tDiJ02OG0eBucNTg9N9YcOHUzs9HDqDAUGA67TgkXPVUtGb1UZDcaeDEOSnQ3GRphr7G5IgiEaOmRwspNEM9j5CoZQ79WCxHsR/EzTH16tthfNx+PvD0OSPF5czzQus28xOL244LoDYXHrtuhePBcLl8lQ9HpB0OThsmZ6wXE1T0Oxl6rc+YW3V9G8svKh9LVZ3+kmNHFDWNOGJPt0HwbCgtvsb0NOz+O1CPt7STr8wpCBsAh+brs/vCT/RfBq1V3wXC9Zcmnqp/tq/2joxQ122jBEQ9HpoewBhw4Zhp81zjRDSPfCy9azwewv54clSy6941qCdTzTYoaImHdAcBV/XXDc/EOQKl+C8l+3vxgoGPAEeTffBOdB9T7m1JtcZFTRVu9FEr8kgfsyfz9ekrxV+KaXQGsAAyWwIDsqZavABSgiekHETQi99UPJEPsD2cV6LBv7FYPTi1WpRfQmkEBEYAPxuvU0IhbaXtCL/kB2MR7rZBNcezGqtEhaEnhNJND0rdbHgbrYzJvGjS+IxvjFAfNowuLQt2j6S8CS759/WemImOfAIqp0xILjl8U4Eb9U15oT7jgRL+Tl8iY0SRaVb9K14pYE/vUkMM86ehO9Ud8/Q1dyGSCwxI4M1WXBv56sWiNe4iSw2B2yzi4I+jPoX97ELxjXLH114wW11WyhWdbMC3s0bl6+lWhJ4E0lAdaU+frrvCHAGohazxsugZfalb+BnRuoIM4bml2yIjWhiVtYPJBuYH5h9Vr4lgRaEphPApgOj88IAPbYzMxH9EZkmh1pxq9HH5ptOX492mu1saRJwBv0svf/FSIVdO+104Wy90DQjGlsvue1a3m+ZlqZlgReRwk0tZq1RkvoVvV1lMaS0NRiz8JARxXR+z/CYBT9yzzFvoME/aKnKuuHNqJfNiWrf+w9JauXlcVQyu/5cQJnfKkFB9dowoIp+rDmYejDtFItCbyZJWBtNiz+GBZhK6k4sDkDXKOCCCdIv4aPx9GEFzfTLOkfv5jq1cc023v1Obc4LlwCC5T6ApH9eLicrCMDyQU8/fV44VR9FU3ThD5slWriHVeY1/od0b//r3VrC+Hv4Q6EhZA20QPJnW+WteJ/VQlYlw39x+/tai/OSjIQ+pMuID2Q3PkFkLVQLyEBz8BLFPcVRYQiog9BKqLK++3/g6UnoAniDjJBQlRHiJSknmN/Qq0ARP/HzBJBE+mMb2+qvIsbhQ8rdN1FvTc7pcABFVX/t2sYmjinDc18/7gkA/Ck7pPr/zTRzXi+st4boOaYfIhaYHl/5Js8/abtfnMCm/G8gTQR6Cs3h2WCqhAMKuF3lZ//DZ6qqABoElAm3U9xL8oRBCVAMj39kinfV8c8elGLjEw7AMjypNabccr08jJuvnxC9BXaOhgRJCUWFQl4yVDlgrRBMk6vWoBnYtg/rpj3xwxM60V1TKHXIJjvguA1aKrFcoESKMFWullZC0pKosKSSNm0WiTjAs+TkL35Zl2xdkV4LiuCZjKRpTXFXErIoKGwpF3zJwlOQLXeJHywFqUbUGgTwi/qlw2qEJufUf2gmRTBPsFAMj1OGyLglzAvfoWq/+YbG/6KBiFucme0DMi8mkDhix6XvQj5ShFBxYEA6qWegeTOvxR9q+ytIYGmllaj8awbnHNssF05Nm4AGN0LaLmKpPsVTX99dtrgkui1mf6x8QsC12nCgsr/VXGekVdh7J76io1TnsDSTjJ5M/AgeVLOMZjKr6XEYr7s+Ip5takUYv5VMTLeQHaRD/WqioukfEUEi9ENK+Ir4t2q9BpLwJPXH6rmSjS3iTXGaug5rKB3QwCNyypo4qrc4r/dSsGZ0+D04tZ0e6Y39NYh2cT2YpJFGtfML168IHsxbvFqv3wq8+4Pi8OhP73Ti1Pn5dKY78Lg5fJaIunfVJ2yTc7fYRQehN8uK5O2O9eLJKrWCqUS20FV6ndfrjJj40r5EixVS6+St+mAtBbZRgW5l1DrBcV+TOYWvIGBzhRGLxxShXnF9inzMr2J/riSFnEQvSX9I/Ohb7Rd0rah2XZEv/71r9JKtySwxEjAOmpodshpQ6XF1u5myUvFZbK5l6LgoJ+YVbxfirJV9mIJ2Nu9GPtKMEyUnVmaC+qn6XAG8K+MiOzqKOn3NB2ZC/uhX5w0NwMt0E6WkeYhCSkJVeA3iFfwvLKazW43lTQCPgZ6EEGa2GWGiFCElbVZi8LWs4RJIOhPBcGtYUSIp/JYqYT569Xivll0qpcOmkonSQx8IIswXQwsSXnriOSyJuifDCXcyopHb1Rl+r3Bu790ax4ywu1LEZFAhKpvJFpPSwJLjASi6klvlDK96RShvwnnlxHOo+/ONsG6Pw9FwiSG/uVF4U04hdh9yWZcbMbtEIwxbeYXmcSL2GWQwoJGXSbihAfVfEDxkCuVbIvygM5pAwWKwNfA1PmIMCpBKKR+eTlEmVBGU8WY+cA8jIigrhMDIGLB+AFkreybSgJvgs4OUFbrqWFBPV+Yhpo+IuR/rdNp9QanDRGBbUQvFusc0Oa8ggGJiEj1ImJAyb929tU7MAgHl2SJ8yo9MRa0wRkX2DlWztdYYxI4Y0iZ3hd5HjgKcIpuRqbIMgnMvDmHtQhlCZ60FWReGfjFe8y/Cb01BmR7sS+Oehur2qUDTQrje7MRoYholqR0RF9+XkErsQRIwPPSB57GasMgBf/Nm+e0QINhHgO9NJ3BN5KgJIWUQFWYl7UNGGwfVdH8bxNmCnhGOD1/6cJzprXCGZpUxhmaeck5Q9rQ9JI2m5k3Ns0fjI9ItarNzfzFrVxLAm+ABKLSZeuwIfUgMKqUSOrtlG3S+ut0At9cVYmqPlUi2VoGtrl+kRQFjhJU9qpenFm4ySwLZdiFKYnUhJQQ/OArg9MJVAVXqFKqWjR/c6yQEX0E7rs3QhGhiPmhouZdDTLZJpxA+Am/XgTm1/RnLnTe0Ew7bkFLAq+XBCJCYf3tbTCCPOBsUy+dDr/6gcsMTVRTpyMi2UkT77hJ59gQ0UfjvMF0TXB+IDTLWrH6e7J/Rhy9DrKXRYH/m3cxE1JkgWIohUhvCFK8uC/XMrAmUNUpA9oBg7xylvMUD7cJDQWv4ElcF6veQKVyno6oZOAFfaEX8/FxuRXbsWG+wlbmdZbA4ioIs8hcpvkkRvvS/JYoeIKEq3TGc8rUy1B6V5FMq39ZmcqaAy3pgvXB0MS90rjiRe/g6bR4lb3bpqoHcJ6XIJ3KIHayH3gMBvfJ0Gg01ATj+5G2ki0JvCESsBo3oa8DTYxjKfivxP6ShmOQSXeTTagyEuu/84BtBSwR1IVTBrbyzvI1wZcA4stCCR+XCN7GVTxFPfECFvrEQkpoIJUEHGFBX2xz5mtwkQ8LTjfxxjXB9u2yqgNNbBWX9LuEnyFCiogEzvcHtUJLAm+QBKyH1uvm2uq0cc3uRERKGucyr0OOnU8FvJw3GOe4SUPRvKdZ5nKnDS50bIio2jGuBYuWADv9RRMtkqIpc5yUaVPW/jA5rgY+zb/3DA4N4WKAQk8U9Dx23wkoeMnHtHbWBitA0btx61/JSoD77Y9azLT71oQFV5lX6o4AbsvQpHY6AYuL44LYSux0E4wzON+s14pfZwnwhQBllOZNqOYLBXpliAhFsHlgHktw5MTZV8EGoiga6unpSRtqgVEKJYeCBlCi8wmRYs91BWhmOky4zDS2C4PTFaSSXt1yepFgfgb6UBJX7WBfWFQkMAfyJUCSVuhTqaajbtI3Y0hSeTNfeOzUdd5lLVigBFrIN1oCQQcAHhIlml8qIhRZJtuB7bXRqMv6nGEnYape3ca0wVMn6Tk2ysGBJLbdo6JsqISuwN5hCi+JLLXhWkoUy7QlL0MiwL+UtGGo8olcKS0HKpoZyYiQ++i6TXAfGxzWKaYPDdqjQ2Sa5fPF4KsHPn0N0Kcy1TOfer0ad0XXerck8MZLwDrc7EUz7TgBtpHiskx67LRtognOu65j45pp67lxzbzTTVxs65YAABAASURBVFgQLiKMng8iQhHzw3wE/+KZ7NUYP/PKFFecMvtCkoicbZWS0yrxsIaAMDhESKFmMLndoeP+uJQ2sh8wj6lmifMu4VPCr0F5mZyzknKleq/xKyIUEWreAIngNEgZwrtKaZ6zLxh/RMg0hoiQg/tvcLoFr7cEUJx5Wjt/2xnzFxHok5jOSPPWPKRWM6ek13ZQXpBFcB0Fm3/SJawNTLuKXj1VaosCyv1EBHwNWWojIlIsgnXCOmNwGtRLPhFV3Yi+2M2V7IRc31DQIfNLQNr9Keib8y53AxHhKEFEKM9ztbW1pVi9wbSG3mwrakngDZFALLBV2xerCfpdAClHXKT1wpsPKlVIuX5Eeqc0JTzQYLQN6I20/mfQ2LYNEOATsHF4DrSBiBAPJLTPe+GPO2DoT1EmX5DnWYptk/YrjrPMuKw/MX2gn/RBIUWGn5LSWtOg77Zr9811Dc10f34RVKSOn4gqHVHFxrWgJYHXWgLW64hQRB+4Tesri6aaumtcRMj0CrQbvbcue+0VwXinXc9rlfOuazAuIhQRqb7LjHN99YYmnfGGXnQrWogE5vdECyFaJDoqCgvcEEyq2Ix402Ifxr4FApxcykDMBh+ESiZSZJ1+MeBUualp4smhRCiMSuKG8JOKyNSsXtBIo1E0yV/T2GNsNmBltQIaVzC+kv65r+6YFbQJpjeNIaLZa2MZk+VVJVvv11UCninrjOP5G/Y8FeiU4xJdrtd7VK93q1qUQ3ktZzPdrlqtlma8UVS3eC43UFWGNLXWY6Ca9r72XFZB1X7pjBxCEeFEggrveoaE6nuZDIiIVCciqjJ4lfRbxLaSUL//TAM0dbNAb63Hjg0VAymCOoBxJXzUCi0JLAESiAX0wRZkSGXobMbaYJ2tY5cNDDGyXLW2mvIskw8QRfo0UKg6WISCBSVBwBxblUIRgfnY5gpRLDw1th7K4BURch520JFMT5ne6eVywBhDws17GWMwwnG1aqR+YYtUU9PmIoK2gzYqUL9QYpPuv2kLbL0ECsZawMNkGZ3LOfTbRzlviAhHLWhJ4A2XQKj3v16dLNHn0rqLDlt3De5kwb7OOk2xIjJZn03rL/ymaR4UImyvJet0XQ4uc+y6hoiQcREVnQgRfWmy2Lvt0akWLEgC2YKQLx9nIZeyn00Ag8hxgiE2WFKdCfcNbfDNgUtY+1koJOZKixvm8Y1Qhvcu4VWWdfgXaZKtCHmepbSVqT/f/vn+6f40LycdEfQ9UpWIKk4ZXlnWeyNUKtFEVOVut8FnZoPTaoUlWgIRgXOJeXMYETiqXDkLsAglTg0UNOgcTq7RwEmF1FZrg65GPYh4TGOFj0zgUAoRiArqF9QzuNxxUy8y9Nt6FBFJn6kx39Ok6480rsnDaSoKE6k2HhBG0Lm03dG8DYjpDG7L4zI4HRH0tWrbPKk+L+90C1oSWKIkEPP3Bs0V5iYfGmp5TVmWo/mYAzbnTYfxXk8KviQUHCgKI4Ma8CkBKfjPb3FzX1eJbXu9sS3YXlxYwMsggnElm/USPhWAfMknKDUQ+SFZ0Jfu7i7VuZhwf7OM/lBmfjSFOdODef6CAp6CfPOgn2GzGePMqJcz5hw/ZXD9iEj1nTZQVRGRwOkWtCTwRkjAuliiwwbbIMuibKgpjS2xs0s6mmeZar36HFnIIdkwOuy0+URUOh4Rst4bjG/07rlsK85HROIpgsuIUj6iwkeEUS1YiAQqr7SQwkWhPQEJmGWLOVOmgsNBAwdbsJkP/z4pDzVwpj5NZKTVO+F4MB6rBI6QhpKyOEZRZHrSElx55EDsuXSxIkuOtau7Ewp44FGLRqmypP3CcZObwPWlrTQNFKhMTJQ2U8aZvXEGpw1O9y/rn3aZaczLDtonXKftvCMqxXW6q6ur3+/clRTZ9K7f5BcRiqjqGG++hv5p51vw+kqAKWGz0Ejz55ZzHFagd55nO7Q8y5VHLju7DD3Ps0C1AWLPXYEeZpl1rEx6BqGSDYAT9iJ0MIdnnhsRcgAFLaWobMWjIF9CWgAgTQS4rIKK1v2po9cFzpdi0REFjedZpjzLpZAKbKrewwEbOtcVobOrU9093Yk2otJB621nZ6fMy2nf4kSEIkJZlqU4ItQ/mJ+hP+5lpFukLQm8PAnYFAyoIdYxzzasg9Zb0BL6XmKDEaEszwRC3pCbJgIK6ufYRs7mOoI8FPV6wbpSKMCj6LZS2BSsaVwGYDdZBp/I5C8WkEPndNGbN4+gWkg88mldVbBd01zildJk3A+XphhkFpEuG3zhELRRlRUS+FIhhoIvqquzqye1575EhErGmed5dUkhpXzB4YNkerq7uxlTXV6jjLBNOy5p0+B0C1oSeCMkYD21PpYod0QoywyZMtIl1oeKyvZcYnsodsI32FvWe3qgzWS9b1AWEWmtnjVrVtJ124YIXses4/4iYVrzcnsuj7DtlIk/pOkxrSFlWq8FSgAPuED8fMiFCTEiFBHyZCJ674eUcUWT5RkT2obLpCxzOlNPHacbNJfo+9iXvUkozQYwxiAVaEyDg4CsPNCRTeUl+bxWU3t7TvsN6ApioUDCcebKsoCaWlSo+k4N0hFBmQ8VReIT0Uen3mB6K5bjiEqpXBRR0TrtMkOWZYmfcRGR0lZgO+mIoH/t9KdG30JNns06rm9ax1pAiOhrbwHFLdRrKAHPlcFzFRE4oyIt1p7XLMuVA4GONdigd3XPRbe7WcQLiQOrZy2jTs7h2GkplGUZb4rLBnR1dK8AZ3yQLpNuRFiXqny9jk7jRF2v4lO6cupHpS9BnYQSTSUeorEIXhJtFGxyCkVEAo+lYGORHCd9MQ84qq29XRljKdhgGGc6x7BI9TJoXcd5lxlcbjCuCRFVO818K25J4HWTQGAHQLAmEKG3OU1buwHsrc66Q0qBLnvTnOWZBGHBRkOEHP0HY5QybDbL4ISt9DR6sLGGvM7k4AKACbZGe9hmRIiHvOOStGPXDQj8lHBvAI5L6JRoeEuqWrQdRYTEU7A+iXSWuaxUnucJStoyNxHyWs6a0gaZ26mw5iE5H/TX7URqywd9ry8eswimi6Ch3jTRa/S02LYksGgJWK8DvbWeBzpfYnN1bLJkTRX5xAGbyCKTsL06a2Kdw0Ke5TJYlSOCNbGBvpeKCA0ePFg5duN1ytDO+hZR0SR+fsHTZSWxv1pEhLEJIiLxSRlepjGQbD29Esh645eMImKR5Z7oUg0F/nrWzNl64YXpqvO1ITKaYMJJwoM0b5ldKSa6AmcTmoTJiSgrQJUK6ooKUSqFIG0fGhHKKStw7BmFnV3dmjhxqubOnSOKJB9XwIuFpGBDZHCaAsrtVO1cS2Vu0EggAu4GRZMULEl3HgWDFSWhiEj4CPiQ7EGR3T0rq2PztFJOmzZNM2bMYCxlqtPFF4c6C1iqzMvKaCA57xmYn1fQSryKErAe9gezLnhVwLQyX9Wc+ad0Jc7MG+eITJMnT9G4ceP07DPPpRvLhEcxPOee20mTpuj555/XxAkTNRM7qOWZsiyHorQiKdDLbm76zWf8+Oc1adIkdHYuiz22Qw9QaUWgVKQjIqXDSLpLlryAUAbOefWGLKOdPOPw0iPrGed2KaTOOXM0dcoUTXh+Quq3D+4RFKDPNfpVMDb3OyIUEfJ4cpyub2u86cjgW0Kr3hBR0fVmW1FLAm+YBLAo7Cp62y/RXyn4Tyh/oNeZbSTLNBU/PGHChGRrU6e+gN32KNDxzrmd4CboeWx1PDY7acIkWe+9Vljne7BTlZJZ1nu6NG3aC6wxk6kzWRPgNw2+DdYWReDjxUFdKr04USkDhK2DlWNI1KQzy5QOUzlXKqB3m3NYv8aNe072IRPo1/O0MxkfMQUbnkt/85w6pVhbG8oYW1tbO/5jjsaPH68JEyey7r4gB5cJnlmWy/bdtOWMOi4fCG57IK6Vb0ngtZJARCT9tT4W2FAne6MGBwbvF/0lcOrUqcnGpkyehP6yNmLLBeuQy7236u7Ghs0Dy+khXXLQsI5Pnz49HSLMN8fGvZ6JYPxE7GgSdjRz9iwso0zWGRGUYinwTonWa34JDMixDRmAWYysnUt/CCYtIlPkodmzpuuUP52s3/7u9xo/YbxK/9EC+FpbG5xD7IxUssEmoxB1eAsHWPJKgPJ48sN4eAp8gfMv2fyHHPzOVC+4qY06Gxw7z0LXXXuTjj/+V7r99jtoAk6laaUMRbPyRMAJPhEBjnaJRfA4iNLjtJUxZXgVnGppXpFl5GDA20/JomBaRfCEUSpQOP/0qk7/87aannzyKf3qV7/ShRdeKDt7K68h1aNGRKS67hvZlI6ocM436ZxuwWsnAcu5CVUrJXNRynrQ8GGUubfTyfOa7r//QX3jG9/Qxz/+cX17v+/onrvvVY5+5XmmGs7Juved73xHn/zEJynfX1dffY3QOjGrCWDFZn6Orr3mGn33O9/VJz7+CX3xi5/XZZdfwkZlJhuOQtHLLyKS4yvQpxK9LdEvelXxCyI/xAWx62TQC72MyNLPD7I814xp03X+eefpm9/4pj7xiU/oe/vvrwfuv1/WZ+tqAyeb0fc8z9UMGZ184YUXdNlll2FLt9PfLkWEjI8IpX7QF/ULxvXLtpItCbzmEihpwbpvKLGPgq8JoNBPsb5Q6oLgsDDlBf38yKP0qU99Sp/5zKd1+eWXVzqNDl/9tyv1zW9+Q5/+LGWf/ay++Y19dMH55ydbzPOMtaVDWW7bKPXkPx7VYYcekuzok/D6/Be+oJNO/rOmz5qBfWRp8yGFMBH6UAINFUWPSsAXWqEqOKZp6LElFpeCvpdAluUqKbjxxpu077776dOf/rQ+8clP63Of+7z+98tf0ZeBSy+9TMF/eRbKoM8i05w5s3XWWWfp61//mj732c/osMMO1VNPPUXfq/XWh4WcMdiH6SVCRLxEaauoJYFXXwIF+u49VqDH7ewP2zn89nR364rLLtd++31bn/jUJ7QftnDPnXcpY12yvpfYjNDVrBfyWk1ee2fMmKkzzzxThx56qB566CFIQj5A2KZsD0ceeaQ+9clP6otf+qLOx8Z9+O7p6U42ZxrDwBFGROIzEP+vnPdO+BWN3wLuDxEhpKsH7r5bt/z9Fl35t6t0w803KMN3R9BMVsOBSuKwUHKS9MS7SoMb94J8g1t839Rbgcy33ijVxcmxQEEiQgV0XXO71QCvjDx4RUP+HdRTTzyha6+9QQ02+CuuuIIiKGcz1NPTQ5tFPyjVSG1RT5KV0G2RTHUiIimQ+xO0ERGpXZA89BgFN32TR4M2nM+yXDmKK5QaRmanESOW0tJLL62//OUvuuuuu5LytvOJLMd5V3UyOZ2IW6/XVQKopLUHYE77tVyyjBsKFvDggOqijDmdO3euzjv3PB17zDFadeyqeu+736s99thNyy67LDwKbvg6kxP6za9+o2FDh+g9732XdtppR6266irojWS99O8uUR/NnTNJ0Z6xAAAQAElEQVRLDz1wv9ZeZy29+93v0nrrv10X//Vi3XTzTUlPO7vq8hcI96FuWwmlXolgvXn4kYd1xpmn66mnnwQjFTAtuVE1SIFphNrQRdvLjdddp7PPOpt+rKo9dt9dg/hke8Zpp3NouI9+FSo5zJccSHwoKdBl6/XNN9+svfbaS7///e/TF4mIUERAj2SgMZ37oVZoSeCNkkDQMEbspcCePPlhfH/JGoI647NLlSTuuOVmHXDggdy6T9Muu+6id7xjD6211lry5ZVvNG++8Ua+FD6jrbfZWu/a853abbddtPbaa6utvYZtlPjnDNstWIc69fAjD+nOO+7Uqqutrvdgt3u+851ad711lUNb0B1MAzsRkAEldukb0AbpBl8lxuuUU07R3XfdT14pNDjc99DHRslAxID8AMsuuwz92E3vec979O537al30udhw4alS6fK7krZTlmeNGPmDJ1z7rm6+uqrtfHGm+CT3qGI0LnnnqNnn32W5SgHpBr+wI26fgSNkImIRGsc2dbTksAbIoESPbQOZlzIZaQfeYj17fQztAxr67vf9W6hpDrv/PO4rMN2pKT7JcZW7Z0C/c6U5Zkef/wxnfDLE3ThBRdqxvQZKqDJWLtvxMaPPe5YTX1hKvaxh3ZnHVx99dWx7Vy2PLXCy5JAtihqT+aCYP56iB7H54m88/bb2aCsojXXWEPX33Cjxr8wQV3c1NZxkOZToBT+WYR/tjRj+kx2Q4UKNvGui5eXQqrzeWoOn426Oudq1sxZmstnWsHfCkV1vi7QHomMW6Wurm5df/016mHB+OCHPqTVVltN/mMX/2sTkCTFcbsNFpPkaFEiEebMmcMn5mmaPXt2unFymekoSko5a+bMqoxTaIFqucyn367uLhVsKHvAd7GRLGjXtzhz4TMLRTXOp9ell1mGheXdGj16tB588EH5E1tEyEpsercXwWC14BCx8LIF12hhX64E0CJZ38T8VuCl39hCFn+eh/A7etIHUr4KLLfscnxh+Ka+uc839anPfFJrrLm6PEvPPPOkLudG3geIb3xjb+299976DLeWG2+8oQRFmXQfLSrrqrVl2nHH7fX5z39e3/jmN7XPt/bV8KWW0m233a4JEyejH+YodLAQu381Dy6JT0hPP/OMbuAWcsKESXS5VPBfgW2gkr2jiBRPmTxFd955lzo6Orip/IT258vHpz/1Kd1+22267757aSfDpEqVDDAi5HDttdemjY11vbnJsL46bzBNM3a6CRFV/Wa+Fbck8FpKoIQ51sFBWgms8ZlT2AFFNhtNGT9O1//tb5qGT/7oRz+mfffZV9/gS9tmm2+GTQySfflsbue32norfRM73OvrX9dnP/eZdHgYNLgdGyoqG8Sw6vVudXfN1fobrK8vf+Ur2nuvvfTVr/6f9txjdw3hgqBOu+4TUapTYu9BfxJgGi9MncwX8Gv1zNPPCnMVxXxNpO9U8MbGNlVweFBZagPa+NznPpcO7XvvvZc+/ZnPaL311tO///u/a4cdtpfMAHvj0f1cPFxx5ZXaeJON5S8Q3/jGt/ShD31QDz/8MLZ/h3q4MMuymhzchsHpFrQk8MZLoExrUGShuvd/2IK/bF9//fVaavhwfYqv79/c+xv60v/+L+vvk7rzjjuwrUZar0QdzCrtGz0O/7z31ltu1XAO1stwSVtrqyki2DfO1UUXXSTvtz7/+S8kO//6V7+mHbbbXu0d7Wr+fY95RJijUy14KQks8sAwsPKLnY5dpWT8lOcn6Llnx2ns2LE43i00c9Ys3fPgAzjHQhkuOGMD1tXZowvPvVCH/PggHXLQobriyqt09nnn6+9sZGCiLG/TjGnT00nxhz/+sX5wwIH608l/0LQZL6itow0uuGGUyxvusuzR1MnP6iE25CuvvKLWXGtVNucP6aqr/pZ+A5rhLL3h8U+CLrzwAl166SXpc7N/f3rSSSfpgAMO0I9p40qc7lw2/x7r9OnTdeUVl+uwgw/RgT/4gY76+ZG6C2Wt13s0t7NT55x9Tvr0dcIJv9LRxxytx/7xuPz715NPPUU/OPAA/YTP1hf99S/p9mcpNoJbbrmlnuW2x7979+IQEUmZS8bQH9x2C14/CSB+qYy+Bnu/KIAEVyZgquSF/Iknn1Ce5fLGY8zSo8VeQOz9Jch6ujtxaI9oueWW1X//939r5VXGqs7htDm35pHludIGPHrU3l7TRhtvpKWGDad+qY72Do0cMULT2dh0zu1Ue1uuHPqITLUsl0NEKCMvNi/+w64R0PsgIILbiQj5S5tSKOlzofZBHVoKOuv1nLlz06HY6REjR+BYh8vjiQhltVyRZXIYNGiQtt12W33sYx/TKquskhxqf521LRkiaM8VWtCSwBshAYy3xF5tvpigrL8R6CQZm0nkoX88+oie/Mc/9IlPfkKbbbqxcjYZGByXTWw66HPBrt0batuT9R6Ui7GdErOGEW00+IRRQtfA9/sCa+jQoepvd3UurNyHBnYpmk8AowZfBiNCPM6prRYaOmSIsqyNvBI+o49ZloPLFBJQKk841jcO8bbrBn7kDr5qPMGFxRpcwC2z9Bg16FctzyVqjB/3vLq7u/nSsZ6GcnARwWuv152JEydycTZXEZE2WgU8IyLlIWs9LQm8oRKwXVnHhT5n6KXh+QnPpwutLbbYQiustGLq39prr6XVVl2Vr3QTWSOny7qfYzeRYzfUm8tl8v333ZcOyd5rjRgxksN9dzos+6dJM7n43XW33bT++usnW0tMeVVtF8kesqziBXq+xzSG+ZAvJ/MWpM0WNaaIgU4meqvgVHGt8u4JjH9m9NjDj6itfZBWX2M1bbzxBhrF5N13z8PyL4fas+CWfbJOP+NMXXPNDZrFREsN3XDd9Trh+BP0t6uu1pxuDgBTpujiiy/WjTfdpIIvDbNmz9TNfKm44drr1F3vZoKlLDIgaLWhieOfQDm6tfwKy6fNmDfml1xyiW699VbVuf0vcea+4T+fz1pTp07V8+Of16mnnKoHHngAXqFp017QlVdeAf0tybE+8/Qzuummv2sWXyC6ujp1ww036LRTT9eECRPZkzV0Pp97/XONx594Ug2c8JTJEzmgXKk77rxTFqYPHP4DU/8MZQgLzDrrrJOU3W3T4fTU+ESc4/RLjMWICI/FKWE/ZYIq13q/MRJgDpJuB1+ZZmrypMmpG/fec48O+MGB+sH3fqSLLvirulisexrSU089oaXHjNEt3HJ8d//v6cADf6ALL7owLebNqc1IhIIDQbusv+x34Bl8VZjA4XZC0t9llhnNl7ICPSwoK1Wgu1KuZ/iq8ItjjtS3999fv//97/iidr2OPvoX2v+730/25M1BRMBXvaHUCA4G73rnnmyWNtXvfvs77bvvvjr/ggs4DPyPttxqK3Vx+2j1q2W1VMcbiq233lof+MAHNIaxGNnW1oZt9SR9dLlxTefa1F3jWtCSwOspgcCOIqKvSScxqAKFLo0l/cLUKZo8eZLm8JX6KC529t1/Px133DGsQVPTxrwb/X/hhWnYxEX6zne/px/88MfY1Y3KaxncC6Bkc5LBLcMeS2x0vK6++mod/JOD5L9TuuDCCzWXy4Ja5IoI2T66uhrQh7K8pkl8LTzt1JPxF/vr50f8XP77pj//+RR961vf1QknnKhHHnkMW69js5HqRzjOlH666K8NkqbPmK6L/nKRVl55JW2y8cYKNjYYY1p3PNYVll9OQ4YM1sMPPcxtaic1QnPmzOWC6rn0E6ZG780tBakN267TLWhJ4A2XQKDvGGuysDxL+jkDfZ80aWJaS63XFLOn69Cyyy6j6VwiT5o8WV47vdf0/iqwhwnPe/91lZbHFtbicLHUiOGKLNK69egjj2qNNddMtnvwIQdr3/321W9/9zs9+9xzyiIwpUh221zLHBuasomgj0Az34qlTGlj5KkxLEokpfxvzouNfnBQMCD1xGLGjBm66rqrNWLpkdpk00217jrratVlVtI/7nxU0yZPh3GpBx99SKeddaY233obHXrYYTrkp4dq5x131FJDh9ILuNGFBx66X7fcepN22Gk7HXr44Tr+6KP17+99r2658UZNnTIt9ZiLF7Xn7eIEoTq3/kuNXEodw4bQhvT2t6+nZZdZRnfwVWD27BlqcMh47pmnNXjwUO2882564qmndO/997Jx+piOOOII4Oc45BVo8xbNmj1bw/gq8N73v08HH3qofnHssXwS+7KeGj9BEydPVS0KDaHZVVZbVf+3997yH66uNnYl3XHr37XiiivpJywmx/z8KH3og/+lEfDxwcA/SfJN1uzZc3qVE3GxsKXOKqqo9X7dJRDSQtu0jzCI+enhdtG6/fSzz6A39+uZp5/T/fffp3POOUe33HQDjqlTM2dO120cUO++6x6NG/+sHnn0QZ122pm6+C9XqacbpUa7RYiynUNnu1Mqcum5cc/qdxwAxKZjl5131TA+xRbcaOIHsbNQSZq9Tzp4+BDqG0X/y0oTJ07Qs3zJe378uLSpmNM1l81HT9KvLAs2Onmyi1qE1l5rLfX0dMsbqMF8QZg5Y6ZmzJrNpqOEb0ONRiiPGu1lsrP0IcEbjYLDcCe2ZZwIEZH4k2w9LQm8sRLAKAKbSt7Th2ovCPappDEZ+SeuIjFlylRdfdU1eujhR/U4G/RzzztPZ559dvoi3IEt7LbHO7Teum/Xs888m+z3N7/9la695nJ1dc6WCnPPsY0OdbSN4KvgVtp8s03Z0M/Vgw89wEH9FL42n6sXps3ES2RuThgQcglFZOrp7uLQMBF/MF7PPf+8pvHl2v9Ki39SOHnKJDb4c+lnnVGUQDUa25rtzjZcr9f14MMP6gW+rG+19RZahXUGE1SoUMGBomSs66//du2w3Ta6/dZbdPxxx+nXvz5BPpRM5LAilvaSzx/+SiFq1WptErEWGPp81AKLW8iWBF5VCZSyLgvNV0h5ljliLWqo1taeLnr9i44SXS/5ijebS2Ovw3KlJqDb06bNkC/pZlL+zne9QyutuKzCe1Nossg1e+YcPfbQY3rowYf09NNP6YknH9e5552t8y44X9P4ot9oCFsqMdsKXtUhvkWZZWLSytICI0Xcf5zOGowLXpFoCyalZOPTCwnX0LPPPaOrbrhGV910nf5y8fk654wzdP9td+uR2x/QQ3c/oNnds/X0+GfUxo3IOm9/m4YMGizVpW222UrrcTL0hl58sn3wscc07vnn9JA3XeeerTPOPFO3/v0WPfbo43puwgRXqSaZBUH1Uo2uHg0fPkzDR3DoQFGWX355bmM20vTpL+ixxx7VDJTKv+d+OwtDlmW6iy8B01GW6/iycfrpp+vsc85KG8DnnntaU16YotU4DCw1apQu5Db2zNNO0W133K7ps+bQVCk1OtWW1bXOuutp+JilhcQ4DXNA2nADvkBM1v9n7zwA7Sqqvf9fs8+5Nz2BBEIC6fSWhI5IEbGCwDBm1wAAEABJREFUFEHs9fnes4tgQVEQsRfsBXvvIoINFZDem/QOgRBaSCXl3nP2/n7/2fckN6GIn6g8PfvutWdmzZo1s9estaadc675nXHWnzVs6FA1mw3yJX9hbQiDkxcM/WxHW9ZCgjWIy5KFE4J2XkQoIsB373+UBCxdiziHyD0i5L9OffQ00QCkgpOgJUuXaAWnTQc9/0B94Yuf0yc//XFtvOnGOJ+TNG/uzSqYpD/EJPzQFxyqL335S3kxPHnqNOzgNM27ewF8KpXUU7YwN/VoRV+LE61L9O1vf5fTiwfzl6i32GILMUdXgx3OBL+gVIO6KxzmtGlTdfT7jtFXv3KC3vGOt+s5z3mOPvCB9zNJ+IJe9cpXyjrf9iQCW+RVKCnqnaef/vTHuu7aa/T2dxyhr5zwVb38ZS/XaX/8Y55EreT0rcFJF0Wot35j658XC35nM0kpocdNRbg1gq7MoEGXyxgGobrRrgT+4RKwRrJuUCqlsOE4tN0kbI2xYTmn1Ss4AfR3Aj7B7uIJ6P8rX/1a/fG0M3ThZZdrKIvzl77ilfra176ub3z1a/rkJz+mocOa+trXv8RE/14xi1AFn6qdNKQ5Qk97+n5sYH1S3/r2N7HxL2ibmVvpl7/8pS684OJM26TunmZi0tOvvhUrNH78Bnrt/7xen/3cV/ShD39ET9v7afkXWr79rRN0xBFv1pZbbKqhPT1iTqR2i8YzwY8I7L/A3qSFixbqQjYhNtl80/wDCQFhu385tH1KBQsUaP2Rw/33fa72eOpuuu22W9kku0IeYyZOnKgJEyZhuz3C7chXFlFbpAP+YVSGCMdr+8+I7qMrgX+wBDxeVCx4qyhVYcQe47DaPI72tVYqeQyMhEUIXU3qGdqbvws6etQYVShyFGKvuE9nnnG2zr/wQj3r2c/S5oyfoUorli9T8Cf0umLRf9MNN2rmNtvq42xQf/Mb39RBBx2gq666SldedS08+pWSx+RQ93p8ErC0LNsBQOR4mApwcWSe8Z20Qx8Fyfl0tICI0HKOQW+4/joNHzGcTujT2eecq7P+fKbKqtRIFgiX4fgWLFig+Q8swOG1NGz4EFXeFeqvlCIpT1DouH4qfXDBInln6HYc4Blnnqk/ns6k6557tfFmm6vR24PblIZYoaBP7Jr04WxXMjB4Z8ZujyZpypTJGjFsOMfAV+iuefcB92iXXXfRmJHDtYDdnWUPLdVfUJo/nHa6zvjzn9ltLXOZst3P4uEanXzyKfrd73+vM844XVdffTVKuEKyTjF5620U6u0dimoWarFE7e1pav8DD5K/PHf2Oeew63Sifvfb3+q+++5HTJV6GBSGsGDAVctXhBlZzmDcYCMzhCKMr5GWdUZ3H/9ACVjWhroKeqCOKOgcgLBCh4eiw5tvsbk23XQTDRk6RBM5TfKXJ2/ntOqeefM4verVdtttr4033pT4UG204UaaOXOmSiYct99+G2EooqmKnfx+dObCCy7Sr0/5jZayyHjd616nvfbaM9uA64oI6HGfOEanbWMpCvmz094VTUoKSU10fygL00azUE+zKU8i2ugnSidfd3KqdsP11zPZ2IQj3fEaNmxYPp71x5EWLVnC4niBetBlL1Bcxm1tsYho0z7bo3k7rLB1g/ElbTLvDhhv6KT/zcLu6zxJJdDRuQJDKJioRyRaSkKhiJBtoVW2NZaT5mc+4xlab+xYrbPuWO32lN2yz57HDnwbs2/iu4di20OGDtOmm2yipz51VzYGlnNqtyDzaWJbRW+owIc3eoaotsGG1h07RnvsuacmTJjIwnyuClUqaAKmojaMK3Y/g8V4L5tiQxgriga2L+Xyrq9BHg5Giba2sal+7K5ictN5LzHKLVz0oG6+5WY2sKZpgwkbUENbJbaZUlBXUkqJcaudf4nvhS96iT5w3HE65phj9OIXv5i2Jw3H3htFg7gUtLDM7ZIq3tug7tWVwL9SAkHl6L8XAFnv0cuhjK3NZiPbYMYpMRaW8nfwRo0eqdGjRkqUCYVuveVW/ehHP5J/qOPqa67Rz9mg/uPv/6h77r5HZ559lm646SbmgMO03cxZ2nLLLTVi9Gg2b0exeJipob1D8q8qYULwExeV8+zef10CuLkOUXQiOXyYU6GjmP/kDsR74XkyWX74iyVX/eUq7bzTTvrcZz/HDuun9dFPfVqf++oXdciL9tecO2/TwgeWaPTQ0YT36wGOaNWg6JDQvDl36Y677lJff5+aNGHK5CnadZfd9D///d/69Ec+os8e/xkd/4Uv6cj3vVebbToDVRHur5J/IUm0adjIUbr//gc0//77wdHxrBi8YJgKnwvOv1h/Pu8SNYeP1vgJEzSkKW05fap22WF7HXH42/TpT35Cn4H/Zz79Bb3udW9GkZr62c9+wlHWEh177LH62Cc/rZe/8hUaP3Gi8rszELRwvKpKCQG1ceCLWQg1mXi98OAD4XW8nv2cZ+eThhuuvwGSSv44i+lGjx4jGwNv7WYPQDiZgVcZCGtcRB1mZPfxT5RAKHBUFUpe0c/DmExstOGGKqJAz9CxFGq1Wlrw4CINYSE4lIF5MrrW3+rTggUPKsITfmkhJ1wPLVuSdwzn3nW3bmDybpq5d96evwezxRZb5tOCmdtuqxHDh6uXyUuz0WASUDEZoA3wEW0gJl9B/Y2iR9bt2TNnM1EYq4hQA6+HyqtNm0omHta1ksmSfwWiYMKwePESF8/Qz8La/8StURTyZOKuuXfrqr9czQJ9vooisdgZoh4mRxW67Xd0aMiFeSTqIsh3Bz8YlzO6j64E/kkSCOrBBOSQ6Ko7FYXWZbHgXx+bM2eO+vDTCbtduHCBlnFa3EgFk++Wli9fnsuSpZUr+/TA/PlKRY9GjhjDxtICTrYvYePnAfWX/Vr44AOUEX6gN4fzH5yv0aNGa/r0aZK50JCCjayeZlNeWKQolGKoUhoO3RjNmjVLU6ZOMiXjUENDsLOS83J/xNdlIkJSYswQ/qWPhchd8rg6dp11oR+S8T1Dhst+xROkuUyMWmy6RaOX0/V18uJlvfXW1wUXXKh1OCGfOm0K3kP4hVJe6Ff4MlcR1PKfeXff+skkgYhApz1fC0VKigitN259Tt42Z/f/CuzuvtzcuXPnsXC+TUM4ZbCtXHfdVUz2b9OiRYs1DNwoFhG/+/2pnKb/XBeef5Hm3HGnzjzrLN1x5x3aaNIGbEz364EH5nsoFTVp4YLFWs4G9+gxoxX4gTY2VNsHbck1dh+PJYFUZ0YdrHpaeIZVCCKVKnZDSiYmFROKyjNowpLJyb3z7tYdt9+uiRM21Iypm2kMDsvOejSdsuk205SKUrfdeLu23nwrTWby9euTT8pfNL7y4is5QThDc+6+W8tXLFcLXjvMmqWhQ4bp97/5va67+TrdPvc23X3PPC1eskxFSmLOLzygqv6WVDS17vgNRc9r4fyFOPK2IJHrnjlzW90J35+ddIq222kXjd9gfTWL0A7bz9K9d9+lMy84XzfPuVO3MJnzgmU5k7t+Fi0Vg8PixQvlgebWW2/J/1Pi9ttuw/G21Gj2aEV/P8q6SG3CJum77pqrX//6FP35zLN0O4PT/Ace0IYbbaQhQ3ppZql57ECLa9y4cSoYyDrKGRFgu/eTTQKBW7F+u10Vg2xPz1B5QeCB+sQTf6FLLrkkn0qdd/652oajzinTNtFmm2+juUy+Tz7lpJx/+p9P53TrMk2ftqE23WxjnXTiSfrAMceid3PkL0jfddedaqE/c+fOxTn+RZdedpluZEdk0eLF6IiU0I2iSOiyJxBedC7SNdf+RZddflGe3PsXU+659z5dfsVf4DdHS5ctVbPRzBMV65dh8uSp2oxTkYsuvggHeqYuvPjC/BGKy6+4QlOnTNY6Y0bpxz//BYviT+bTthaLjWTj4cX7WFisXLlSFfbt7zGAUpOJkEPzNt60EWFUF7oS+JdJILBX36vAw1YkzeBEevLUqfr2N78p/8OzP59xhk5E37fafHNts9UW2V5/xynyb377G11y6SX62c9/is1eqd123VPjxo7X+Recp6Pee5QuvPAiLWHRfTqnzX849bfQXKbzzjtXZ5x+hlKROFXcWMIOSmzFY2EwoibsaAWTkttvu0GXX36+7mRc2HjjTbTsoSU6/8LLdNW1N2nhokWqGE/FZT5iel+xIRUwWPrQMiZFN2kYY8hYTkb8jrgiRYQuuPACffzjH9cf//gnJkOV7rt3rq68/ELadTHveSr4P+CXtpEXMkOZUDXYsW2woVUAVAUPZVD36krgXySBiFij5oq5pGG99dfTbnvszph2u84792x0+hL9/Be/4ERvnDbffAvmgA/q+OM/pc9/7vOaOnWKPv+Fz+pXJ5/E6cLP9J1vf1dvfONbWHBsrTe/8Y161jP20WabbSLr/znnnqMzzj5H5198ic488xwNGTpUW225uYb0NMgvGHML2WYjAtsIdS6Pc4ZOuhtKKd+KtWSxOr1KYBULBryWHSO+raZHwC0m7nffNUcbbThRm2+6WZ4kt9jR6W/1q6xWaPKMDbXxJtM159Y7cGJTddib36zFixfoU3T8Rz/xUfZYKm00ZYqGDR8GfaUp7NY+61n7avnSh/SRDx2no495rz700Y/pN6eeqmUrVopVQW5tJFaoqaFx46dqgw3G67675+q+ex5QZaeLw57MDsumKEx/u0XbNuT0oEcJpzmDo+d999tXnvi979gPwP84feITx+v8887XeutN1FN3ewoO/g5wn0AhP88E7QFttskMrcNKNhWFNqJ9/kz5iGG94vU59l5f991/n776la/kL0Ffesml2m+//bT5Flto2bJl+SNNU6ZMkb/pLwRX2jgqy7IWIVHaXMf9tLwNjnfhXyOBFIm+DUBApW223UYveMGhTDLmcex/rL7znW+h0zP0kpe+FJ2ZzAJxE73s5S/TA/PvQZ+O0Ve+/HXNmLEJp1av1oiRTY0eMwqntw6Oqanhw0coiqRf/urE/JO+Psk67rgP6mtf+4ZuuuEm+bTA/W9os/sRtOW+++7TCSecoI997GM4zE/r+E9/Wh+kjP+r5SmnnKIH5z+YTwykoI6CpzQO5/v8Qw7RNrNm6oc//TEnZh+gzpN0yCEHazd03AuSIUOGavTo0bLtJeypjd263jFjxrBImkxbh2sYJygR2JoVVVJEyJfpHHahK4F/tgQCmwiFB68MSknCpsJh2MtW2nDKVL30la/UpMmT9P3vfk+f/dzn8OXz9cpXvEzbMlno71+hSy+5WF/5ypf1oQ8ep1NOPkW77LqbXv6yV2vY0DEa0jtME9hkGj16uDi61lw2xb729W/omKOP0Ze+eIImT5qiV7z85Ro/fj0ljLbNOGOweZT4eS/+f3nir/SBD3xEH/nIx/XFL36Rif4n9eEPfYQT6B/p5ltqWy8oUFE2eJ8IbxBI/YypPZxA+GciNxi/Adwij41l2cdm2hB8ztxUSN4AABAASURBVHrY5XAx1OUFxMc+8Qm9//3vZ5f1J3ruc5+TYeTIkXlcSdg1bEU1cqhQ9+pK4EkhgQiUcQA8Lyo43dtx5521+557svj9gz5w7HG69ZZbdMABB2jmzNlKKWmDDSZozDqj1WgWGj5qOKeBIzSGMWzs2HGaNGWattp6G+Z7EzUE+xnHvPC1b/hf8sfoC5/9nN6P7S5fsUKvxC9sPG06MqiA+u6OZ7Uc/toz/TWCCDoVIos2IlQwaQ47oaAoyKJI2nHnnfQ/b3iTtt5mlvpbK9XCARbNBg6t0vrj188Tq4MOfJ5GDRupHaB99/vep+M++EG9893v1LbbzRZMtQ6dPqzRUCoamr39DnrDG9+go99zpI5+9zH5H+Xs9bSnybuo/ezMlpxEVKrUZgHjz4TusvOuWvTgg/L/T/DujNTQQ8tWqJcdmp22n63x49ZR5d2c1FAvq8u9n/FMHfn2t+v9R71bx7znnXr72w7TjjvtqCFDGnrKbk/F+R6ro49+n9761rfpiMMP1/vfe6SmcZzc6OnV/7zprTjk50I7RG0mdOPWn6BDX/hiHc07vf+YY/SWN7+FCdlTFSj3pZdeqosuukhbbrklTn596CulLLuQh7UgMJBYdUeAXJXqRv7xEkiDqhgkeybIXhyX6NrQIcO066676C1vebOOOeZoHXXUe/TilxyqDTeamMff3maPtkNn3/zWt8g68L6j3quXvfQlmrjRhoootN/+++odR76bSfz62mKrrXQsk33r1xFvP0JHvfs9Ouo979GrXvVKzdh4BjpSMmFgsY2+ppRUoeMTNpio//2f1+td73y33v72d8g/kfq+972X8O16HovTDdZfH7q23NYSnWwz8U/Y5pSp0/TSl71c73r7O3O7jnn/+7XfgQdo5JgxiiJp//2fp8MPf5u23nprymtVvTNmzNArXvEKecLSg+OtkEVr4GQxIhQR0FerYJAAO9Fu2JXAP14C6DjDAPWEhJ3Z5+Je5csTihkbb4zd/Df2daTe+973ouuHa9a22zLpHqqpbPy85jWv0TFMIo56z1H4+6N1yAteyAJ6HRWcXO+881N0zLHv1+ztZmr4yGF6Hrby3vcerWOOOUZHvutIveCQF2ratGny+Ge788l0wYZUxYZQ/8p+jR6zrg446FAdddQxes973qe3H3G43v3ud+h97zsS3/BibbLxdEUSY2V//jiubcztbmG7w9k822efZ+jA5x3IacdYaFpk8Y4KbHIX+Z/MPX3vveT6duL0/Igj3gnfo/P7PetZz9LEiROUsu+obVRc5l/hSypsmRtM9+5K4F8oAWw3IrKeei7kE/e+lX3YzTo65OBD9fZ3vFPv9Rj3rneg8zuqp6fJHHFdNuHeqP/+n//WOuuOZrxryb+m1G5VxKWttt1ab37bW/P39qqqXxEtTZs+JY+tx2D/xx5ztF7/+tdp2223UYPThVJtVYzvJTZruygZcx1q4IoIeMRAqhtYArgsB5IFZahTyoJy2hAROV2wWGg0m6pIV/bMkXCYDY0bP57V3WT5l4/8+VCFVFZ0BmFqJG0wYX15p4f+0dIFizSsd4i86z6eU4nTzzoL2ip/6ayBw12xbKV6mr2azg7tzjjDnXbYQTNnz9aGkzdSwarSH41IeLyIQhENqai03ewdtPmmm+qiC8/XxRdfoHvunac/nPZn3TV3nl76gudr3Dpj8vvBQGoO0dCRo7UlR1w7b7+9dtx+lmbO3Cx/Jryvv9TQoaPyka7/eYg/d7opfKdNnwZ+CEIpNGmjjbT+uHXV4P1bKFsqGprEbtPMWdtq1naztCUnCyOGDddtt94q/z+IiRMnZn7+iFJEKFGuov1SRfuVL9A57DwiohPthv9gCUSsLWunw72jFAm9EZP4lprNHk2dOlU7sbC0XvgftRX0vQfmkja2cTZTpjh/J+2ww3bacOJ4BX2diiTvfkyZPFlV2a9mEdpi80213Xbb5e/8eFK+4447aKuttsRZjkItKtkOCsqVDPA+qfMvbW211TbafvsdKbc94fa5HdvDYwpHsw0W2l5IW62KRpPyDXXeYr31xqF/22qHHXfCjmZpxIiR8qlbCfHECeM1Y/pU+edWqRin3KOI4F2b2gg9Hz16tAY70cHxlBJvTSn45Ej30ZXAP0sC6Jx9KIEMuVorfI6gk8QrbKfCijfE/87mlG0HfP0mnC73NJsiW8M5OfPC2H5+R2xj62221RiPE+h/f6tkQ2gYk43pGjl6pBpF0pTJU7G9HbC7nZjA7KQJEzZUG/9fMcF3IxLlUtQ2EYS9PUM0nXFjhx1my3XMnEW443baacfttelmG2v48KGqKO/xstFo1i2vsL1GD3UPzRtMY8euy8uUCvgVRaGS/JEjR2nypMkaM3qU/L2lDdhx3Z7Nip122lkzZ87E14xVROSJlHj/iFA1IKSBgLoq4G+5u7RdCTxxEvCiGvOUQ49Dtp1GESoMqaF11x2nrdlY2xFb2WyzTdUzhDknyttsDmVcmsSCeAOlQupv9amvrw99V76GDRshzyuHjximivknqp/pJjLP3GH77bTLLjuzKTcdemyJTe2O7ZouIpQY0yJqe+nYjLrXGhJITg0WTkQg0DB6FTjfEAi0KArwuGL3eInj8V1KfSuWA31K7O4XkeiwUsFfu11pxbJlarPiu/fee/SpT34ynx4c+pIX6pWv/S9dfe3VOuSQQ3DGs2Xn2YvzrDuyxfpipVZWy1Xi+Crq6+tbqbJswZVOpaaVHN22ce6jRo3S/gfsrzeyA+wjp3exY/TH00/XQQc8T7O33ZIFih1yqFUm9akgDPWtbKmkbNVageNdIVFHo9GrSAV1VGq3S/X10YaSHN6zYkIYvHslRMY7J+hTpg3o+tVmBzbRsn7CPtq10aRJ8i7tG97wBhYUk+FZZjBfdJ/64AAfxw0g8l2RMORE9/FPkkBQj4Fg4A50uKQvpMCRMQGPOj/rBDqNOqLjlbybL2h6OH0KQlRFqE7W2ZIJgaHK9KWavT3yzob713rgX3+wvrTRrfwdHnSnaBQq0CtxVeBRM+op1WqvINoiXmV960fHSleGDqWUFC7DhCKcph0BTgk7YUJTwsfttHOtaLjtrKRNLfKohrKhAt2OCJmX4xXvbnqXc9w4g7icNhBVRDjoQlcC/0QJhPJfSB31Q+2xjyqDuCpFtk1/F6ejw7aDbDf4fccNVdVSf99y+bs6mAm2W6ntX++z/ZBXMfGAFXxLVZTrX9avVn9bJbZWFE0lJjmRpISt9fevVKvVVsECXhSyjbQZr1rtPpU4hbKs1MauSsD/MDFUjwFFSuS3KVtPflIkSqdcp9/P0A9f88vvhQ1TRD2NBjRi4rRSy5c/lN8X1tlH2I6VL2RS5YiMiwhFRI3oPrsS+BdIIAL9xl48/nhOZ/VMRVJCL62/thOPfRWTeo97QsuDeWVVBrbap/5+7ERgioYa2ECbcZai8ji6ZMlS5nZ9xCtsVNiVsIeSMbNNuZKEX5gw80zYcmvAbtwK59UQ8W9sI/Ur/n89U6dURCgiOskcRsQqnJ1ViUe1s4vUUEqFfMpQi16ykyyaDTFFUQFX78qIVEo97Fj2ogyVRo4armc899l61Wv+S//12v/WK1/xCr3lzW/SPnvtqdHDhilB32jwTPQr/VfiYF2fqLeBh3SeolJJXFxN2lEyyWqXfdpgww3yRyt22GEnHfz8g/XWN71Jz9v3ORrSgBeOvIT7ilaohaMvURaz8C8tFZFUFL1gChxvOysPry2DldjvXVWUAOSyaLR/vjLnp1DwshGhBIRoG21OMF9nzBj5t/U33HBD9fQ0lRK58KB4jud3g5Ziua6KDIO4IoJn9/7nSsAyr4GuUOS/RF8lHE7FYN7K8aIgJ2gZekhvKxLKSj8WwS6IsAniRkGhFHX5kqVv2xMHJvkpNQVrleiCwwqdEVeThXKjoHwltXCUJTpfkG40G+RKEa60Do23jiXj3FjXmeuChvJCT82+Db5UomzdjlyGxpEt1+X2qZLMx5OqFrYUETJdRGAXRQbnWTc79Wrgigh4x0CqG3Ql8M+VAOqnjvaVKHU9FmFRtgkyIpIyDXnWc9tUSqEwKOS48ako5JPriJQnGAUTkRSFyla/KiYjKUKm86MgT4o80cCIsZ1EspJJioSdwcO0bRYXFfWaj0AYHVHzSaSzjSXSxpEZRVLB2GfaSvBUUHeV7TSTQJNSUxGFKCWTFgU0letuyBOnCqMvaW9EqCgKJdoTEYQhggziqihDMOgO4gaC7t2VwD9aAlY1FLLAlhosuq2PgU4a3WYjy+OWlOpWRG0RJeMhNzqc0OekssRKolHHKYvVq6BEb0+PIhGLpFZfP4v/FgxCJeN1aTrKlTCqqqSC+gsWHAW2EkFFlPcdsTrudBdWSyD3SsRfF1BZVnkynTvX9HSIFKJ/M0Si8+zA7LDomESeSijcMUx6XGTkmJHaY++n6cCDD9ZLX/QSveQFh2r3XXfVkN6h8q4NftS3TFsSq1CBoHzNJ9R0xxZJfUyo2nR6IxXqaTTk1pfewWlL64+fwEJhPz2NRcgIH/uySySuEucdeNkKJ92ifKilsp/TC/hUakBRyE4XH4sylvld5YagaC0GDr9/BVXJrqxlQFSJ/EAOBe1IKcn4lEIF7RSXJ1oG4yMCfKKOBP8KaEuqBJpw9R0RqxPd2D9UAhFry9rpoE8S9QZAD6HLFQOxExEh9zNYWf9QHUfl7KqsCIEqo+hZSZHo8yCogFCRrGd1/wcUnqRQIuua+aaikKRcP6UIQ8YrpAgeFbxpT6BjoSSikkIRoQRESooiSYQgpYA+BebjWipFBLWCo60JvLjaGHBEUCTV+TAtebH+fiZLxK3Lhoq48eKKiExLNN8RkcPuoyuBf6oEqk5tA/pXSgEoX7aPSi125lsshD1ZSOhpSkkeK7K9Uh5TUPBnfC5GPCLJNi0Fd4WvLuHTAvDZRqVQAsRlm/CY4NA8YgBfVQlDyzdUFDIvxxwlrNhEoDnEEu2hIdhXMNaYD+ZHXZVK2i5OOCrGnAgKRsLvKLenAl8y1q5kUtSHrdpG3aaIUETAt75tt8LqaxT15Pjq/Jpq7XSN7T67EvhHSsD24gl7KCR0O49fqZLtoBJay5xNwj6w6QqDtG2E6YJxMueFgrj5QC1FW03mmqkoFOAjmgpCMsyeAJvCZiilIhWkkwoWDS4fEepef10CeLXHJqpwZAYL1cKVQtlB4sTEVdA5SgVuqJBlHgMcQ/yFcUyS6Fy6CuoSZ9dWHw58RVlpBZ7RR7SNEGqRhL+EplKJ169g5g4vogE+VOE825TzRC01ComKVq5YSZ5URJCWYFLz7mvh8OHDIqKfuIokQ4EzL2hXETxDCuoRV1kF8aQelK3w++CMxXuXZcV7QaDwQyVKW7kS6Et4k0QWVtVKchsIEu2qKAdC9QLECl/CjpKJdihU8t6WaUTNV93rSSBnymVjAAAQAElEQVQB90UNFf0r+kn0dWRdsb6EfLnf6GaJZKL/KiYGkdDRVKhRJBHkvq44Pq1KoRzWoZaCrm/2DKXvIy8QjK0gSCF0rFLWrapSRCgZCV6K+g9c0BaRqqCp0J+yrJg8VPKVUlIEtFHzMk7EZVxOdB4VbXOcctSNJlK3GylIScHXC1xxdXgSVQne4Ljrd9iFrgT+ZRLIuk3tDgl8RwQ67Bg2gHpbXwO7sA+OAh+MT28zWbD+BvZlgJICVa3fjGer8iivkFw+IhQRSkUDKKQQ9ovt9bdVYYMFeYaAJ6ZZ8wJfYV9ejJdtmAX2maiNKLcqCF1W+I7kPHiYsYMIKsD/BPgET/8Ck0MMlUVECX8JtAKESRMOJ4DSPAHjqCnXYVs2uD51r64EnmQSyLZAmyr03YBmy/qbsBUUmBzmle1CiTEYK5Win/wSsB02hJkpQVzYIIRtsAg3XSgkJTX8EXPKttk0DvIrwhIfEBHy1WYO59D2YXC8C48tgfTY2XVuRCgiSARhXSRI+Y5IcocGHSfTkBHgQoUSEDydrshrly26lF2aJC66lt1NK0ZPb4PJFgWtQQQy8EiUTdFQQVnrRAQZ3AXOu422hAqJ/ArHWylUkUcgK1AikqpCKTUzvtXqo6rSJdSLgy1SUuppKuAVUSgoWzExChy946lINa4SitdQkdNBaFoTKyusFa2CBoyURB11wnhxRQR8gpgYaNoZIiLzkWq8ute/WALuhzWhyspUNysiFBF1ws+qIl1JRoGPKCR3ftD/Qq9xSjyVSAuo0ClPYKSEfgS0UkQQL+WrwQI4oY9eEPvXIqrMPzKN82uIOljrCSl8qI2IF98kaARtg85Pv0airiSXD+U46dqmSBcht80TC3G5HR2IcBkpIlaBuldXAk9CCQRtMkihCECBricV2FZRJMYBLCCSQCthaxEhkYjAJkUcY8EUZMjmDEqZjrKMMUVqKCUmMOArbNzFg9C2KhKhkK+IgC5UUG8E9Sn4k/xwOYxTvio2FAQyTGMQF2WDOitCASkFSBENQPLD9bUZN71pJyZBzWZThhL7tx1XVYkLsF8pIa8AFwt1r64EnkwSqNBXFFWYUG5WJdthRboNukSziWMXoUIFBok5SN7gTQTGA1VlvTZICujJqwgTxIkynsNViXyyCoKCfKpRDODKVqm/+foPL2ARPqYIIpA0gMxX0aVUKBK7qnRK7nA6zs5wFY0j4DQAVSRFgbOlo7KiwLIRoZ4iyWEwUfcvH5Gt4BH0bgRECkWEEmnv3jbgkaKQnWNEqNnTq6LokVKSAl2j3mYq1MRZW4GiCDV6exU4/FCgKwA0dvRQS/DIbZPkfJIy5EdIhdsCJCAiqKZQpER2UlEkgVbRSDkeEYQFNAkIZf48fSfKGBz3+xdFTRMot3GGiIBvOArQSBmIdu9/ugToCvpidbURQZ8mcJFB+XJcSkUoUIQIkANd5qjdX+Tj1UAv6smGuArovetZpAS+gF+S/0L8BXVkXgElWloNMCQPhCJiACgBHWok2GScwhQANAKCjFQURJ0ROYwIEaFMUopCBWlioCLjcrsokyirQZfxBuMj4DEorxvtSuBfKgHUMYKHxxqF7FOdTKkQKSYfHpm0Sr9T1m3jKkUkBXaQCuyzSCpsUwW0BuIRgRtPgG3Rb+kyYnxJGuIfMPA4AzrEH7QUUYJ/USTZXgryUxHgpCQJEsGJehK4gngh8QxJEX4WtNeh0+KiVMYL+qTGAC8NXHn4qJwIyqdMk6g/wunI6YgQLzAIiHbvrgT+xRKIsF5KfgaGE4UkcKGQrwhC7kSeoWNLEaE0AEWCQKrTKSkVSZFxUXMJKTUK5bIpqSgasl0m4gm6oigoLUVEBnWvvyqB9GgU9kOGkomr3WtEqBZ0ngqBVe2HUkLYEiLnkQYBGMpEhOorqSiaKhIg6EAW7jSAqARdRCicDkKDCGkEURlPipKhFCHvqqSikJSUaENKQShFhNywPHAURLmd38NOjGmcHQFN0IYqsa6wC88lBsqKUEYIKhXQepIvwghjyHMImF8iDPG3KpQinHZYDcSdDrkdRZEIlQEyPfJVPTK6i/1rEnhC8t3fhpTcV2kVT+MiQgGeZ8ZHiD6uQcQpoQK9jGS9suVUSlFkEPsmpjdfEXGYoBMXRVUUKTs0ySnrgKFORRhHnDAZEvEUigillFSkRB1GhkBmCHARpFVfphPJiBA3SEIsOUXK9eZ81Zfjhd8DwoiQ0xEhX5aDwy50JfDkkEAolIAQD9/4dUcTdlFk3XWqo7dhuxEX5hURsm7XIJGlSCIC1JyIJPmPR8ZHhLjhnZjEF4SFbEOBvSUzUOcyXZAwSIlCmU6xuoySIgVAGEACwmkgBCU1p0IiVkpK0Da8SWVcJMm0gDfTikH2GhFkhUwvbNwACpy6V1cC/3IJrLJF1XoqlDNSUooiQxB3IyNJUCilAmhIpPKdiHlDDt12fgRl0X/BJ+u6/LSBCxQURDEdJeg0cBVFynkDyW7wOCSQHgeNJZ/JOp2cE34Ej7wLWsmMQkySErsk7uygGAAKIvCO0JnusIDaWV56QKWgEyPAmIl8JYUKqApCrboCTALMLWekhkrKViRcHA7EBEBRGZQv78QUECRSJVBZc6CSeYWIwYHQsQyUTdB4sWR0UEcC/P7JfIzU6qtaHc2xtbLZNaopUqL1gGSKDqh7PQklYLWuoe67iBB33VIrFI7KCbAO1oIYSNdl62UDTzNUnWddMqAcmTYiFBED8RysftRsVqdrstXpHBuEdD0ANcLehQ2ZKD9MGfKfk+HHGuB2dWCNjG6iK4F/qgT+9sqszTZP1L8uPGBTGALpekywbpPw0JMDP0zmsoOR2X6MNGQiPzLWkcyyYqwQtrSqXIdWknnylK9KHnkc6wCEFSPSmqaZvUpdbiDDAcCdq6hyhLKMXWJMkojXSPla9W5ODEBEKCIGUt2gK4F/rQSyCrsJjgzSXaOEXocBfa1sDTZm+QoeBYDNgLeel2Wl0h/BA+s7uZyg4847BtBh8cY4G8gZ2BEVc1MFuO79t0jA0n9M+kDcEZGF7E4yRIQiQjyy0ySm+iJmB0pncOe8jj6YvIOjH1VAqqpNMTtScpwmVbm8QhEhcWdQfVWQGYw2pkJBKuhBO0kbCUhUgChYkVc3olSdyZM89IwIr26Hi0KmaCkRQsRtPDW4flIVjY1A7SrHAELQq+46CT31GRnhuGOPDpZhXe7Rabo5/zoJRIQiBvp8UEdV1ic3q6rIN5jGy15C8FmdAtWqpMh/Ditiqq8BAoorIytxBeAytW5ZN6yzxkb4mbMf9WFeGdBTODwi3dpcgsoDyiAkWON2/R1YI2MgEUEpYCDZDboS+JdJwOZjeMQG2CiwicF5Rlm3a1zUAQy4ByhXx5xZjxPQDaAD+48IcdtETTIIYlXc9TixKhzg3sHlNpinEeRlu6V4pgdv/iRzriurFPxJ3mtyHkXIC3BBiO/gWRkyA9IDIaju3ZXAk0cCa7Qk0N/BCGvwWml/Z8EL7XAeYyz2V+u+0wYpInho1UVKhoqFhENDZXswnZjbUSwCLPeqQt3I45YAEnxk2rXlGRE4rKQIdxwuzp1A76UUGaeBi2zSA4m1g9xZGsgnIfMK4eIyGGMgMXCTxy6MqzKQym0Q5cRFK3I6wjlSDgYYRIRSJOWLuCmsdwUokvJ3F6QiZ+f6qYBblUJBOdOuKg+2gjJxekIuMSnEZSSB+Sk/YE46K6gyhSIiA2gGmbpAhHHGdOHJKgG6KPdbSimHbmfdr0KvgqQBzamVhrTjNeTEGo+AB3zQnwqnZy0Ao0Q6AhtAv1aT17lSSBmsoyxKjFaSr4o4t6NAJViQY3qSvo0gGQpZhx1q4ApCc3FIdI0Gr3o/3jkBEbSNyow3ZPruoyuBJ60ErNVodyQF+jvYrCJCRqXOeGVSrVb/wFZI4qPDgSJCxYB9SjWutgHsbSBt/nWOuFbHnF2BwXR4JiBABWF9RxDnBikRj3BC9UVBpwzmL9Xlc9x5IYrUuJp/pUT5EH8OASh4D3WvrgSelBIIWpXVNBEzdJQbfOeOAX0WYQZ0X6sucmHgMcoQEeRgE2vQgFp1exwzMGO00QzQ1fa8iqgbeRwSQMqPTuVu6MBgqvz9AM+oc0eXOKe6I9wBHXA564LB8aDj68mLcHByShGFImhChpD7vaYPSeAVyrcDwHFxBfRBflLwpwwauMiS+eSkIzh9GamQeSeJGBBSRtAGRUOK8J2BBHdSSPIziLntIiV4hdPOCykAnpKIcIsrIhQRxBLQuStwFYlyABwn+oi3y7n8I2b+o5BdvmtJIHfhAC4ilFKnT5JIATzBRZIykB0AKDQlgARNkojVEIoIWZd4ihSQ6jT4CDCrGHXKhQQuAA1cYRTgZMRAhERS8EckDJHj4egAEKy6jc8EbmxOSBGRQYOuiBoXEYOw3WhXAv96CVgjDbkljhhygofj6LYDA5iH30myWTnfIKWs/yGpBj9TnXCQ+RGRFGS5rAhJSZTNEJLxQZggDQgSG1NBfkiK8JMMEXI70MDlLJepk9DkRGQSR6keLuQGwLgWVJQU/CmDci4Y8AF00muGoe7VlcCTSwKhQHdDXH4YiKaMS8SkbBvgHZKSREJrXYN0Pjyvo7yAAL8KbEQhRUQGda+/SQJ1b/xNRR5OjOyz8CPqTohYvZrrLCAeXuqfhfErxhqVPTz1cJo1CuSES9VQPzPyb3g81gLhb2DTJX2SSODRtWB1jmPWLYPjT5Kmd5vxHyCB7is+Xgn8Vcs0geFRGTrzsWzc+YZHZfAoGfBkLNVA0YFgEG2NqZ+D0N1oVwJdCXQl8A+QAB7piePaWRw8UvjE1fJ/lZNFPRi6bv7/ak92292VQFcCXQl0JdCVwD9NAt2KuhJ4EkjAM9gnrBkRoYgaOp8tiwg5ru7VlUBXAl0JdCXQlUBXAl0JdCXQlUBXAv/nJPD/uWBwsdWQv0fCY/DJgiURUS8eHP83h+7rdSXQlUBXAl0JdCXQlUBXAl0JdCXwbykBz/r/rhfzIqHDwPGyLGVot9vqgNNdqOXSlUNXDl0deLLrQLd9XR3t6kBXB7o60NWBrg4M1oG/a8HgBYIXC61WS/39/WvAypUr1YEVK1bo3wOW8x6D4W95rz7KDoaVpB+tvOt4tLwu/t9Dl7r92O3Hrg50daCrA/9wHfi3mX90daWrK/9aHfi7FgxeLBgiIn9Pwd9V6ECj0dC/HxS809rwRL/nYP5PNO8uv38/nez2abdPuzrQ1YGuDnR1oKsDXR34x+rA37VgiIj8JeeiKJhI1w1tNpsaDD09Pfor8H8gv0kbG8Da79LBOxyc57TpDR2844PBNJ08h04732En3Yk73YX/+3rU7cNuH3Z1oKsDj1cHPB4Mhu540NWdx6s7XbqurjzxOvB3LRg06Op8PMlhB/zZp873GP5dQr+T4bHfp1S7bVj9PY5HovdHOfypdgAAEABJREFUuVZDW62WoUVocHlDG15deCT5PZlx1pG/Bk90+x+tvie6nsfm95+jq61W63HZ5iP1S1eG/zl68v/f1/+e/t9282hgWT2SvayNM10XujbU1YF/rg48YQuGQWuHf8Po/+8/XXO5R4JaRBGRT2giOqEGpV1O3asrga4EnqQSiIgnacu6zfq/LwH7f4PfxKHB8X8y/AOqi4hB49ya8X9AdV2WXQl0JfAESeAJWTBErGn0EZG/0+CPKnWg892GJ3vYaW8nrNtbaM10WpXu4NcME++PDAogrQ3OSw8rX9ezJr6De7TQdT5aXhef6IN/HUQ83CYi1sQ90X0UsSb/iDr9RNfT5Vfr1eO1v4i6HyJWh10Z1jL8T5eDdWhNSIwNATg0OB5KjCXFKjC+HpPWll9R1PhO2MnvpAeHnbx/dji4DY8U77QnYrW9RKwZ79A8WjiY76PRPBF41/NE8OnySOrK4B8vg79bxpJ3LmqoqlI1OK2/66oe4f8y/F0M/4mFaTpyQDKODNRbv09HPp2wgm5t6JQribgw4SoZO11DzW912QHiNfjVlN3n/1UJRNSD3P/V9nfb/dgSsA0/NkU3tyuBvy4B61ENg8eVwXF4MCSvSeN8kGTVt+MeT4xfDfW48nB8xVjfyVsd1pz+0c+KcdWwdj3GGYzvhI53wDjD2mnjDB28Q6pgLOXNLBYFqNVQVUHe6rQG8jv4ijId0F+51q73r5B3s7sS+D8tgYRJ8QJYyCNMasl4wu6IUMSTH1a/sJ3sWiAc8WDA6dphrAakiShzGnlWg2lzvMJR1bC6njVjuay91ZroR01FPPllGvGf2cZH6rSI1bJ4eP7DMRGr6SMeHn94if8/TMTDeUd0cRGPTwaPJvWIeLSsjI+I/xN+MaLbzognXgZZCRR14DED31/lscJjTWXMKmB0gY4BBkwdh8b0QJ0enEfZPD6ZZvCmVU1TDcpz3OUjQhF/H9DAR7wr2tgBE0SEgzUg4uG4DoHLDo530g4NznPYAb+PcQaqZtwFw6s7bpzB8cFgnKGDc/yvQUT83TKL6PKI6Mog4skvAxYMtUnY0OrY438+kmFFPPJLm///FeAV1nICWiv9yO9Yl+vQOqwGyjlucNpg52WH/tgQ8Wj11Pj/K/L8T2ynBl0RdX9FxCCsBnQjHjP8a7KLeOzyEY8v/6/V081/bFt9JPlo4Ip49D54pHJd3N8u6yelzBggH0+7IuoxIaKjJ3pMnxDRoeuEf51eXBEd+oeHZDOp/vvlHvFw3hFr4h5PXRGry5g+YnU6oo4/Gj4iyApkqEcFcZnskcFlHx88nv7t0vz9etWV4ZNDhqsWDNjP//ddlpXK0jsZVXY6j8Qo4vEZYMS/ng4/z3t03sLv1JngOwRfAQo/HhlylokMHbnUZWvFL8VrrvrMXkSQrqHzGbOIRBtc/pGrMDaiLhPRDSOeXDJw/xjq/rYO1WA76cDgPNM+EkQ89nsN5vH3xCMeu56Ibn7E3yYD94f72uGjQcTfxjOiSx/x7yQDjwv2DfU4scoHMAhVnVMAThyg4lwBus4z53t8KCkCfiBdDQrJyGOIcXUcLgP5Tq8NEX+/XF3XI8HguiIevR6PfxH+yNDqd3LZDs/antaSFQSd/E7Im/LuPC2inF/Hef2MB7XG3cE7dEaHj0OnHw0iHv1dIrp5Ef8+MojovgsLhsAW1gZQf8OdUigCUA2ritpYOxY4gHxEAzTdQP6agTNWAy6EbNKZJyEp32sljRoA09QO1QinHHag5tdJ4VCImhevohoogdPm9ZRAhAqFmMgTilCkQhJZq0AgKh5Vzoe26uQH2KRgIRBBPLTGhYtUuHLoK3/GUqGIWIOmm/jnSqDWDzrkcVULdWVaw+oCEZH7McKhiFsHHA9JoYgabBeGAS3U6pAokwQ/Hwki6vIRg0IIQ214t4ASqPNAqx4tS6Il+AoI4qvvKkf97EBGUM6hcQ4fDZxveJT8QfIxVQcGmD9ioVomddbgeI15rOfg/lhd02OVWDsPDkjeZdfO6aShyO+kLMeIjixdppL9YmcCFBGraCLquLrXEyYBSzwzWxUZ0Kq105nIDyad9K5jq8HEZZ10tI7xNM5A9Am5zbwDA7qATph1RNDwRDTQFwGViA0CcE5BF5EUgLjCwCOCh0IRNSicARCJTOsyoQgDVa2SQZhoLejodwXeQDDoHlD9jKlts4JvB0Q81gASYmiTBhZARFbdlWNmmCOCtFPW8Yq0w1IpVQoNXH6HgVREiBsgP5/YEEIWQL6J1Pk5VbvBDg5UApzPIEweZUlEhPyniswMfhDv3k+YBGq9qdkNjhvjtMHxRwb3h+GRc7vYJ14C2EnANRSRFBkcD3CPfA/uQOxJBlMaj3txVNnAHLMD4PTBaXdrpgE3OMx5zrQ/dghwU9rP1VC79wEiJvECVuWCJkkZ3zW2bgsZA84pY/0wCWB+pdvSaYDj5Je0lygUcKjahOZBYE9XJSKFKuRUkvZ7yDS5cuhVg0tUaqiqCqlElpQrSxYPeREBLoekqYi7lmFFKfPC2ZUKGWgO9XXvxyeBv4HKgh0MA0UHo6wfFb1QDfQpAf1JaoCoJOQ2GoCa/qvov6wTA/wcuH9zCC9BGUYY6GOnTb8azKfNaV2buhw3tCnuel0bUW7TE0AzCO/sVeByLfL7IWtRDXSlqBFdpA3yYgKodd2FTAKN6tB4Yk4BnRsGuWxN38GuCv1OyKAuVz9Naahp3CbeBTpiSGNQfeAqyhpqWsqDc7wiNKwdd9qwRh6Iuj4/4Z/7o253lfkbv5o35I96V7SwdHne2e2tS9bkFW2CC/IlB5qS09WcAxHmS1aFrCvyM5bQ8SonXNb0BscNzuiEjhtyFY504WESqCUJ2hGgRFhIGLkPwjlKHsLP+BylLx0aUZa2sbZy2Yz0o9aVThnITaoKWtuM+4iqZIB9vh3vdL8RpnFoGBwvITKtGRq/BlhbqL6DE+ND7V/cHoA8MYbkgEY5FGUMVR6H4Jr1G1rwJYUN4qrAB2FE5HbX9MZYYqY3SBHGmY+5G6zbhjblnO5ATVNVlAfEVcfh4zT1CTA1GFprAoDb6RK7qgYgZ0LIrcplaDcRKoAYpNk5nemjLi3o8qQ+Nzdyu3nCqlIVNci0lBdgHi5JVI7D2WigXJUmMVBnpiJJCddDrKJQSd+ZuKJ9TpvH2rAGvmYzwHNtym66IwHLzOC0Q0Mn3gmNMwxO13H3H/000EcdGuc9GpjGMDj/kdJr4wbT/6fHPQN+3DKwIDvQKeQ0XUe3gekYSp2SUkiprqLCAO2cOztuUMuGaBjwVUZJofrq8HIIxujoZLpA1pU6M+oqagOFtsLIDUTzTTLnuViNpxyONlEw83QGUDc3chk/QCmMpO0VdVc4jrq8hO8QKIn383uVeVAJXKHwLTiuOpPsglgoooZKzjdUGVfB2zIgQQ43jCsCmseze/9rJFApBnTYPdkBt4VuHMhxqu7Hkj6sGKQSumJdq/wgu2xXct9WxEWHVuiPvEMGHSVrPYE2otaNCGqFOKJOm08uP4Azmw5QTBE1nch3ugbqNCJEvgd7rJMMmugqFdRdMcmtWDC0Wv35H49FQCyyoRNR2yhJ2ifarxw6bbY59IM6c9qh05TTAB8nHwkisUgmg3FdwZ9NWJRxvKKBNVTU12EquS0RQSmtEa9oqyHCMoPeYW6QVMLLBSIC9uFo5lkNwtdypRy5jxa3f6iox/kdcDqi5ukgImgXabOCVlwRqx1SjSIfvHkQrLojQhF1+83X0MkE3Yn+Z4aP+dboiPMtXCAJOQLuAqNXQRCzIKEhtvomHdgBReQ+KUnjdtGRXAA6Qm4iss1GoLcwN22njyjibJk9ap3jzjONwXGDMxxGRKbtpDWgqx0+aSC/pCHGpWgo8VfiM1y+Ii58iAFOMo3xeXIMU5qo4GG8bcb8XdY6LHgbH6bj4XiZ64ErZczM6RpKkiWUolglv5u/Y6E1LpgoyHMoRQSAjISQsnFXKrE1mq48IIqLLCeMb4OEAmR9lzSodLSuzDHaQAAP0wVRwTvTQeuk+7zK7+CUqA9K0qa1XEp8nHNoGm1zrAYXz7gCDhBTBM4DeSRcRyJPYKs2rXKBOltB+yJW2+sAOgcRMMux7uPxSKAakGtCpo4bIkJlVpqag/MMEYE+VPRjZDBNTU8vwYfsjDfOJTuh44Mhoi6/dr7TBtNG1DSOux6D412oJZDq4PE9I2phRsQaBewjUoq602xodGImqHgSr8BJA/mk3QkRgcNJCsrl/JAg0eqrgxgU4jBrfQIXSQpCcRE4SQzFQomIRKBkgiYDOOoFTUuoDT4mNIoUaDeUgJtiPH0bB2NHQQYTwiiCKgFwSQ4TMYemrcGpCD+dFX5QJwGVWSnbvICdkqABK1O4LTmCLCJCBWy51b3+uRJwX3TANQedYshx+iUiHAWrGtzlUh3PT+I1CY5PXKEI9BA6AuJ1r6IKq/LQTLq/JK8CBNQ0IImHUqrTthlDJUpkZhLjm8nQr4yVghtwaB2r2JUMJ6jQRcTFGCwFPIFGo1AQWi8VAT7f6lwZBZoKOqi/HropUFElTw20z1HqVOQ/8TRPY0xgG4wgbwA06HLb8nvDsBM6O6KmXxUnAsacAcscrpRxebIUUb+r48ZFQA08UlwiT+IpJWgKZJQII0LcEhMe+QXktN+C+khntxJkQ1RRJiLEnQEsodMh92lEqHNFxKq8Dq4bProEkJbC2chNGZwAjDSsGZVpjA75T1K4zwA6LMLJShGRoQKH5qCWlXxFBEFScGKcUshJg/WmgsQAwSp6963T1tUI9GKAoKavVJYUMoGYYBONgGdOC95JLg8q86s4lY7oAe/TanFBSyZcwFEYnSsxaH9Mx9VUxBVSBA8FdXnyj6ZSZ2UC0M5aDSAkRfB+ICNCrl9cmV7BhgK1lYKXcpvIWnWbxv9ptyxLURSoahqalkAks2dyUE/sS8qFkvGSgj9x1c0K0QLK0l7aymsJMgCqoF4B+DLFgHyczkBFbHyIOsw38keFJYoogid4SooY4LbRBnA5S/XlPNNAoGB8T9QBicJhCkXUUFNDSYP93p30I4bxiNj/aOTgl38k+UUE/e8+cp8Opq7jEavzI4J+sf2gNfSTFPJlvoaI1bTGrw0RNb3xEaGIcPRhEBGPmvcw4v8QRPpb3zOi7oxOuQiE6gT9bOdFlwspy5fj+F9HbWmg67IRdegMOxx3suMPA3jaeVQKsgDKRbisk4ETK+U6yRmkbAF1UF/UIU9snAIiJtkhaNVlzkHKQJEKsE8BQ0wVjtDOsGKCUNIQsusnkYTkzNf1izbZaZk+gUxaza8kPZBShUMPnBCNgE+uhGpgVhNIgRFE5NJJXGTx7N7/VAlU9M2ago+16s+5PLjpK570K53LXcn6YqBjRXcqgtLoAHfm2/au1SB+zjZtBYFhUFYuGxGZr/ER8CJi/qtoQV+1ADgAABAASURBVEX4ARd4WN8gQcWsQegTzRPZFbWj2hK0IeeBVCgixINcCH1ngBrDrQC4ihYQQEdMGadHuMjPeVDDgxRlKkoYavKqAuUombn9TA4S9UeAMCXlM940gN+TQBHOVw6d3wFxdeIOERQVUAn4iJAnPxEua3BWlftHA1cuMygeUdNBmVmVtM/vGxG5bgLweALjKZffh77v8HFY4yRKSDw1cEVEjtnflfgVJyIsq9XtNa4Lj18ClrepK9V/dA634+5BgM6o6B9iA/hKto8KvNC1iKRI9Atp++6yDEWEWUpsEFUuS5JsymvgqohXmc6khgoCwwDBqqCDi4hMvzqdMk1EEFYqB+mTFIroQENqQ5vbqnxVjhOr3DYmy6FqUHtIlegneVVlvAZ4pRzWuEqWh0Qd+IFcd5DKdZIzUE5csFJEAC6fwAAuTgw0+FBtY+JyfZ1Mktymgci3FOKyB3L7oPU7UxdIvwFBQBI0ABrwFflQ8W41KsiV3x2mVdAOSiT6Dm7Iry3TJ/LEO8m0QMkLuL/F5SzTRyAjmml6EQZ5WS4kgjJky+kSGcoJ8n1Xohz8HI8IB5kuR7qPv0kCEcjSfQy4YEQtz048YnXaOPeHwfG1wSzcz86PqPk6HbE67ry1wXwG4yLqOo1zeYcRoYgwaRcGJFBb3kDi0QILz9AZ7DoCzUZFoRLjLtsYLb0XEVnIpi8xMIPjkMk0JTQVCeOcZ3C8dg48nel8JukZDz2WyV3Ju/NkZT6O9/X1sQNS5rwSA2+XbkOdrgaOJF3c7aZZOJYyQwVtRUbF5K000E5P5ErKl+S5jhx4q4F2tNv9lGtrZX+LNlTElcGbHv28d3/ZX78ztJ33aZs/TsgO1Tz7Viyn3S3oNMCjhIehraAyvzZiJI/8Fin8Zm4HUYePD0zsgoPBuL9W+j8sn8kAQpdCyqC1LvpO9Am9TAayRIRZX8CjKnLc5axTgY44XJ1OWSdbLX+HwLpSKsIVVWq12gN9XsdbmUZ1PrwjApp+9aPXVKkKhWjnjzVVmSYiwEli4HQ7rGslNIaK9gbvFbSnIrNtPHSRksIfgwKf3AzBQ/VCojQrQJXQzVLZnnKbKlW0x+0r4UV2TpuOCMRgzKsD5mEI85YqbMJtKHlf05fwMr+IyO9vnGhvOUBX5bZKQVvhjPzaMn22Hep3G8Rl3GAw3mnbt0On2wP0Fe9uIAkv2lRVq/ia1mVMb3Da4DjV1G0kEnliYlmU8Chz+Uzj91aAq7RyZR+wMscjckYuX/JOVEncdcOMu6Qxrsfg+h0aZ3Acku79OCVgeVlupX02PrwyIPPSOoVuVcg6gv4A2uhhC99NJ2Xu1uuW6ejDANrovAFS+qtURBBW2R6suwqphGfdZ1IECIyhrr+UL7fHfCOCaio5z3iD8xwa14k7tH4YXzFWOU+KXC63nXhVBjpnWw1FxCq+LtcqW+pnXGpXLfW1PD6JsnDAztvtljpXG7l04vYNNSjz40mY5KuqSsrX79JGNm6Pw1arzPVWVNrOvkgKua6Ktpm+yj6rpD3OqCwXaG3HBJSVqoG21+/ZVov21XTtXKf58XbQUgpaSuCPeKf8XiWuGoq2wAHU3aLPV9pHUoF9hihT0X4JrqXoN+robyv4EzpRIYOSsA1NiV7AUBRRwKsibSh55zZ0pheZbej70Rk4yvlt2rxixQrG51Lm0YGKNsBGDjvgtMwccPmc7j7WkEBEKCIyzrK07JwYHHfaEIF2IGfnGUxrcLwDHruMM32bvjTe44dxBqeNd7wTDsa5nCEi5HIRddvUvdaQQO0t1kA9PBGxpvBKjClTYd/ugMRMJKVCaAAmi9nSuRXGV2KgEXXZ/r5+9ff3Kw2k63JJjUZDbTt0nHYFfcWku3L5AdDAVRercAZ9Mt+2eSVPztpqY8xEM2VpB0BZqaNkxCJh0HYgFbRtmYZcGlqCl1pM0DMuN7UCV1Ja0FXQl7LDWLGcCT/tc04/TrTMMgi1cF4tFFSuE3mU1F8Szzi4UET9y/tkQVfQLl6ySH39K+WrwgEbH0itjQz64WnnWhK24WMaA+wcdOEfLgE6kL7IusbAW7nzrI/s5DnufnBem/5etGhxniiW0FTQ+PsAJf2bUqgoiqwO/X1tyToATRt7sI1EFJRjMKSPcz+ju+YnGJfwdcEINILK3JoSPYgIdLSVQQPt8+SELFWr+LTRV2yBgbsNT8hI0zKY9DPwEnNT1Icdui396DxVkO7T8pUrcl6DdqeU1KIdLfTR8QjaQkVUo5IClRlnO9HDLqpSVUFfQQWPCrlYbiAzrd+lIq90+8gzf0/k+hj8M0vyKuqKyCmKmaPkcqZp4SMyo4GH8R2c4xVta7teirVov3ERNa+IkPslIjI/57ktEXW+4+Iy3uDyJLH/FvKwz2kxQVuZ08Z78rBs2XJ4NrIPc/kVK1Zm3gkdMFfbdIlOmN78zNfvbFrHB4emWRucb1gb/1fT/+YEHZlUVkre1f1ucFdGBL42bE70G33GOCH6IxVJJrd+RECTSKNrfei+cc4HnXWunzLBmJGKItuH88M8UqGIwH5X5rEsIjK9uCJcZ6AfbbXQ04gAW9+dvk7U6TxDhPNpNb6hREeME/pb5cVDP5PjNnX3g0KZITUPc4sooApFhBLtSeIvEhNZ6GR8UoTDOr/FWNXqL2lXC2jn9lp+rs+L3RKhtLDHFosPKstli6LmgTnmNGKS6RCBKhI1z5aWLVsG3iNipb7+vpxXkm95uQ6a4bk570L94AObL0LiVsV75/qopMIXlW1jg7xSFRtwKW9+OJ2ooxLNVPCe/YyZK70YgHkJj1bZFi6H+vvVh2+LCKVUSMgF1oTcREr8gt+5n3fNzMCt8CYejING5c1G2uf2r8SO/Q5FkZSlyovDFkbcfo+BRESA4C3g5UhEKCIc7cJjSKAakJf7Y+XKlXLaNmdw3DjL332xgkWa6TrsnO8840wfgVahA8aZxvkRxpVy+YTNGWdwukPneESgK7Wui8s0BKtupw2rEN0IVvU4hRARGEPK1EUOKtJOVrITEcYmFIGUkeSFilSs6pBEoZyGTxuHmpWCjo4IOY9AyuY5wMHb9wpwBhELFZGUikIRSako1CiaigjZ4ZXUXWD4gkfdyYGDrERSKaFAOIwKB5MSZYGIUIqUyxcNcEVBPIFz/W3epo2zg0amAchnw0cKKRUhO6mKRwrKSCrZ6amYrMFaCd6NFNmJL1/myVhSs7dX3t3xAqnRaKpSKAIoOHaOQoKXRBoGibKhNa+qWjP98NRfJXh4kS5mLQmsKcMKoZceUKCiq2QgKvdPTw/9Rn7WfYo5LyKRXcn5zSb5dGLJACOhLxL6iE5B2GgUajYBL5ZZSJTYQclABjs1Gs0MkCsi4JVkHhGR03lgQ4+LIpFX48jKOtfft5LJzIqML9CrFIVaHlyVKEv9tCUKlylUpIaIKZKUUqKOCn1F76FJEeKVaG8r4zAEQQzOWHE5NBAdfJckeImIEFWqwGYq2mpuoNViEg9Frs91JrelSJmuhX0+xATEXBPtiQiTZnC6gFdE5LIRdV5lpqqvTBOFimRI0IUiaqgplNMeZDxomF5cETVNRJBSpokIWQbiCgVx+EXC3zSUikK+XN7gNrg/a1xhF4icbM4hVIeycAjJfYhoc77lUAzwiQhF1GAeXfjrEoiITBSJkHiKhJzTAC5l+ZcIPyLkPoqow2IgjKBvsLsKu0upUIGtRMCLkhFJEeTTWQ3ss8j9hG2gu6iyfKWUVBQ1XSK+Glc4Sl4h4yMCG2pnnPXEY14J34hgctsH9Gd9iKBudLliMuyxsWQsUSoVmXeSiSpwEZH50kwV2K8isYg1HXqZCtoNrXwxhmFIbkMBXYTx1OGCGQTLyCAlJefzcv1sZFUsWCLCTGS9tgwSco4wfaWSdibYFY2ED2sITmrnMhWcS4DQtM6hDdzEQqByXh4DC9dpHEA84A+RIj94Qhy8T8r9UoimScitMK2SIhJ1N5WgE+Suo2iEgkWGaF8DH+o827lCCsoV9GMDSCnUZpwu8bcppTzOV5QxDaRyXcYX+Oh+5inL2ShsoytwUc+QXqWi0ODL/WkYjHui4/+u/CzniKBrS3XiuS/AtZC939v95rCPTSX3p9OmTalQUdTf7XHY09OzikeiXw0uZ4gIRcSqfPdXRI2LqENxuW4D0e79KBJIj4J/RDSylQXqUFiWw8ANtNmdqDBod5KdTwSdQKeZyUp2HvrYsWngfG2wFcYXZBTZ8EIrWGHazdhAk8tFUvAn4iJeQevbndzGaZuH63G+nVcDpTF0yqZE6aBVpSCp4/IFrp2dhDLeCtnGUSiUHU8EjoT8Nu9hXBAmHHihpIK2N4egkLQ54F/gnFLhOtoqIqkJvtW3ggHAO45JCV4pFTgjKYqkJuXlwSlCQ7xwSAmphZxnOYrBrWiyiEiNPACI3JTID8dWgx7zsqQMj0nUzfyrErAMGfTQDeucwUUiQtyy/if6fNjQoWr2FOpnkm6aRtHQ8hXL5B2RiKAHKRXKoXUqUpIZlOiBdZiEErim+526KuxJ0JuW2skrFJFUoFumi4Q+0TTjEvHUKBRFKA3oiXEFA2WDgdwDZ3+rT1JSUTTVAK+QvItYJOOSUlFIjjcbavY0FRHQV6BCBbwTfEFyh1JRKEhTPapK6xwxaODqxM0CMG1BGedGFMjMMfMuVE/YS0UkWW5FkWQZJNJFKpQiFFGDuExDoAJ+KSVH1wDnR9T0kQjJdR8QyPR9AwNNRAzU3c5451dZ7lWuz2mDy9R1FWr3t0A5X7mt7je30xMIt3nIkKG5rNvgRVXQvKCNVV78S43cF0HZivYnoIBf5PclknXFZSPCyQxuU47wiIjMn2j3fgQJhPt7kIxq2aGftrpKKiLRB41VMnR+yJefoVCiT5r0R0OijHXF44J1wH3sHXTHI4L8+m6zY2/9KArjSkUE+l3Rx3XceQ38fYTzlfMjQh0+zjNNhPNpJPU6XaQEjzZ0QZukSFJPTyFMEXxLyqMJIyV+IqC1jhkUhSqIzZ/KclukUISIi/cvlFKQDpVM7LNfCIFvgG8o6x/5qShUFMalXM52WlGXuCqaaR6uIyIx4a7ksbgokowvUgG/QiWLGoVUmFckddrA8KaKP+V3gBmnt9leIIhcd4gg0/sRA7ItmTRWVJ7I5JavVBRKRcFYu5IyoYYK7LqlAoImwqoYt/0CkZISEBQK3oOocruKpMhtqZBvD31fyLQNfKRl4fI9+MNGoyHBMwX0EURDRYKWuP1Lmw0Ocbl9BqL55u14y/ptHRf0OaP7eJgECvrRSC+kHU8pOUmfNNGnBt1YyTjnGSLouawPKeMjkorCUGR690ka4NEa0J2IkHERoYiQr05/lfShF4SDaZ1nMF1ErCrjdBekuoeQhIVUg+goEGvfaH+F5duopJCvisk/XkLZqFKhiNBtt92qz3z2M3rnu96pd7/73XqLnqKUAAAQAElEQVTb4UfoK1/+iu64Yw5z5lLCoD3wekXo0KYVKIHrLjHkinwDrGhHpf5Wv/xxDwpSJeWhCZSCIupb6UmR8sB76h9+r9PP+JOCN7KCQJLLWxn7+loyLnAAJRO2CgdCY2UIRW6XcV6AlOTxmuD8wtLtN92ob37r67ptzm265557dcJXvqHf/eE0PbRsuSKkVJUKtRSpzcRrqObMuVPHf+bzOvHkX+PI+jXEuxIhrhLlLnTpZZfrrHPO1R2336HfnHyK3v32d+iIw9+qtx52mI4+9lj9EtzZ5P/g+9/Xfffdr8hllUO/c8mjGgTqXv+fEkDzBuS4NgNyMioh/JQC2aNUSlm3P/zhj+jtbz9CH/jAB3T5ZZehY9a/Pv3s5z/Vu460zh+p44//tK666mr6O2S98yKglRfNRU6Ly5ORk3/1K530y1/q3HPO1le+8hUd/rbD9I63v13veuc7deSR78J+jtS3v/1tLV26NOvLBz/4Yb3lLW/WEUe8Xd/4xrd1730P0DbRhkrW2QjboJQY+OfMuUuf+PinoH2Hjj32aJ122h8hbMvtmf/gQnT6+zrssLdR3xE69Q+/YwLQzwDaqyXU9cfT/qTTTj9NLRxqi0X6H/70J/3q5F+RtySXrxTUyUt07oC1ZZltM7Ro8WKdfc45uviSS+QNASFH62yRRDTgfbre8Y536rC3vlUf/tCHdd5558OvyraycOFCnX322frgB4/Tm970Jtp+rK6+5prclojAH7SxqxY11bwKBh3DLTffrG9985u69NJLtGjRIv385z/Xu971Lt7/CH30ox/V1Ve7PwresWfVgDR37lx9+MMfzvV88IMf1Pnnn88JzUr58uCT31OhCy88X8d98Fgd9ra36Jhj3kf7zpLlYt1wP/7ud7/VUUcdpaPe+x7kfJqWLFliFsgq9Nvf/l4nnniSHnpoGYNa0gUXXKAf//jHmjv3bkVEhhaDW4nfy4V4DI6T7N6PIoEI62GVdcckFY+SSTHaqKKoZev++SZ6ccQRR6Bz79DJJ5+sJeinFOrj9O1Xv/ql3vLWN+uww96qn/3sZ/IV4bKOVfJ4kWOln4H+9ekXv/gFNnMq8Hu99a2H6W1ve5sOP/xweByWde5zn/ucLkH3H3zwQRdCD1LWq3PPPVdXXHGFrFtecBpKDLeFjUVgHGh1s5lE9brllhv02c98Fl07V7bDlBqUvRx9/Qh1HaFvfvPbuv++BSpSU2VL6Pd1+ga4efPupc2VbrzxJn31q1/VNdhOBd8KuSQYB3FRJ0KjbeRgt7wtIqsYu+bopz/9mW6//XbawLuyYC7RS4Pb/ZGPfJR3PVxHvee9+t3vT1VpPmKBwRQ54AZ7yiXadb++853v6aSTTtGyFcuVCsn5flSMr97hF+Ueeugh/fLEX+qkE3+lBx6Yr+uvu16f+sTHdOQ73qYj33m4Tv3db5QiKRWhxOLbdv39H/6EucW7kfPb9dWvn6CHlq9QIxUq/R6cyohG9K1sqWRuUrCAuPXmW/WR4z6kw97yVr3/2GOw5QtleS9auEgnfPlLeiv4Y97/fl2C34hA9inyOP+b3/5O5553noYMHaL7779PJ+GrbefWp6IolFKSLy+s3J+Orw0Vsq5ol/Vy7bxuupaA5Wh5Wk4RkeX6lyuv1Efwy29+85sZBz6om266SbYV02rg8kTfY9Q7GSvf8pa36K2MJZ5vHnXUe/SJT3xcNzNviwidccbpes973pNt81jmV/a/nnuW1kP6RtC4/0r0PCJIxkAN3eCRJFBr/SPlPAoui5NHBA+EjKUqFU15d+aMM07TJz/1CQbe87Rw0UItWbJU99/7gC655DJdfPGlONt+RSqEf5E7yJ8n7M1HSUG6nTsrG1d+CFogqIfOrZjoFzgOYYSGIiUl8kqc1kIGgF/88kSc2O9qPygoUAZKqiQkBe8k7xq02QWpaEBBm6X69e1A/AWnhIMJIJcpGnrw/vv14x9+X5dffjGOb6nuZNHzrW98R1/4wgm64YabKe3yLZVlf56I9LHb/Pvf/16f/MTxTLB+m2USonbaH5G09KGlTCx/rovOv0DzH3iAgefnOunkk/TgggVauGChHpy/QF4ELVm8SH/+8xn67e9+r8VLH4IDPHjPAbHkdPfxREtgTelat4qiUJEK2Tmdf/65DMBf0/U3XK8H5j+oxYuXyAN5o9HL4H6zrrvuOi1nEbmMAezPf/5zHgjn3jVXBTrbKFJubChIF2oxQbwBPp54eEA3H08yFy5cqOXLlzExf0gXX3SRvvWtb+n666/PE2DT3XXXnVqArtwx5448uTn7rLM51VihCDgDfoN2GZo3b65+85tfo0NnoVMLdSMO94fo8RVXXK7FSxYzab1EZ591jubefbduufWWvGC54447VKFj11x7jX59yq/1ALrvjcAKe5s372794sQTddnll+fJDlVJoXzZ0RsGkvAodS2y+MnPfq67mBQ7L6UQ6o/992kedfqd5syZQ1uW6goGhx//+EcssK6Cd6nF2PLZZ5+lO++8C/+xJPP69ne/rWuvvTbXZzv1AiwilFLKA8li5Hb6aafpt789RYuXLJJ5eIFwN3V5sXUOi5efMRn0O9oHWP5XMHHzRPLyyy9jQnA/E/qHWIj0q80iyW0W/N1v9913n664/Ardccft9MNSuf9POulXTDwuyvS33nIrC4Jf6rZbb2WBf48sZ7c1kNsN19/IgHVmXhy4TnG5baeffob++Mc/kFL2Sbk+Up0wIkh178eSQMSaMooId9lAEVuCdCu6/fWvf11/+tNpmjdvnhaiJ94ddu5DLOBOYVPnpJNOon/uwoZvQX9+g82coWXYcbPZ0LBhQ+U+qfKJUcg/HvCHP/xJp576ey1iwrlyRT+6tghYLOvZEmzrPCaZ3/jGN3TXXXfRnmBsKLNuf/7zn9dxxx2nK6/8C22M7ANKxs+IUMVJdgTjGWOPCJew4DyZhcyH2Zy4/IqroRe2Oke/POlE2TbuvfdenXPOeSy8zyAvdD9jyR9O/RMT7hvyD3NIkf3CpZdeql/+8leahx2mKBQRahSFhG7arhN2WRSJtpRatGixTmeT4GwW69bRZrNHKRX5/RcuXKC//OUqXXX1NdjkIt2JH7J/OeusM5HVQ6p4D4+rjdRQ2QqdeeZZ+uQnP6XT/nSGfBJhGbagUVUx8jLOU7/HysuuuEy/ZLFw151ztZhF/llnnYUfvZa2LNLtd9ymH//kZzrtj39GhpWWLluq3596qn7w/R/pXvpy/vz58obL93/0I83HHxdFwh5XqGRhxAvmsdd94f53ux9csFCLkWurr6VF9N0fTv2D/vTHP2ou/XTl5Vcg17PlBV5J2y66+GL9+cw/a9nA2Gt/40nrT3760+yHUkqyHxFXRPAUr2atytH8qODjyJpYY7oQgcyAzmJryJAhWTc9cZ/DRuqPf/hjXXHZFVrKGOsJ/imnnMJ4cOcqGdtuLMW+vn4toC8XAtbZBx9cwIbAKfrNr09m02ohc6r5uuTiC7MfsE3Z5/+UPnTosu5Hf+KjwCYqdNM8IyK3xfEuPFwCaTUqVkeJPUzRyY4IFanwaSIWIgkcs2a12v264bpr9bOf/FQrmDAd/rbD8+7Ipz71KX3pS1/Q617/Om0wYYPsgHIh86GTCiblKZICMMN2m60ShQp2E8w6IvKEoIDWlVZMvEtoKjo3cHZDh/aqp1m4CXK7ms2mInDA5PvLUfbzw4cPUW9vj6xkoFXXF0pJKgpoRUh9RUrkhewcTOuJ+0UXXqSb2Kl50aEv1vQpM1gUNDV+wgTdeN0Nuuaqa+STj6CcBxLL6/rrLtcf/niqxk/cQOuOHac2DWAOll1HG+W+5YabtICdlKlTpmrs2HU0bPhQHXzIwfrMZz+vE776NX3yox/RoQcfqL322kO7PXU3BrDf6uabb1LQRvMnEK/nIEOEc3KUx+A4ye79GBKwrAwdEkvXUKedYx1rs0it6MO75t6lX/3qpDzheP/R79cXv/AFdvo+pO2335ECFboUOvjgQ/Tp4z+rT3/6s3rd617H7v996MLparFL1ygK9LSJDrbl68EFD+rss87W5ClT9PznP197772PDsNmvvyVE/S5z3+BBecn9dKXvlTPec6z9bKXvUwjho/QBhuM1/ve9152Fr+pTx//Kc2cOZNFxYVMTO6m/gTvUimSehq9TOwv1oUXna/Xv+4NOuGEr7DDclTW3bPPOUv333cvzvhy7brLrvrKF7+kj33sYxo9ajQL4Ot1H4uE69DtrbfeWs985jPVg90M6R2ivffaWzOmTaPNZ+pOduXFZflU2GNVVaSUdTyhj8uWL9fNt96mXgaBmTNnadiwYWozCReyDKhWrHgo6/dnP/852nYCpzJH0nYxsT6dxfIKjRkzSjvttCM7+cfIg/3733+M7rv3vjxB8qSswaSq0cDOFfJtW72GxcTVnOi88NAXUnZn6u5Frgfps5/9rL74xS/qsMMO0xwWKJ5AVLTXEy5PFO9gkfT+9x+b6/EJw+67746v6KU9lSJCJe/X6u/TDjvsoA8cexwnpSfog8d9UEOGDJUnjgsZqK5jQbf++utx4nScPob9FkXorjvvZBKzkA2MP2gacjv00EM0cuQoBjxp992fqt12ewqbKJewk3mPfA32W05HhIMuPIoE6MJHyKn7LAr8eCq0cOFCnfr73+lMNl5e+MJD9eUvf1metB988MEaNWqU7uW0+Le//q0mT5qir33tG/rKCSdo00030Q9+8APdzUJTch+E3BWGRL/OnXsPk9RTtM0222TbfO5zn6uvYLPm/aUvfSnrwL777qtnPetZ2T6t+1eyIP7JT37CIp1NIia5tf4W6EIFlPCnjhSqWJ0zlDDRXaE777oNG75UI0eMYpwYpxZj3l/+coWWLV+qt7zlTej0l7XzzrvoKibx/o7cLTfdrKUsgF75qldpw4kT85i5xeZb4ENelifg53NyJi7LrcKfSdQpCXehErus0PO72Ny4jNPvPfbYM+usuGq9FDQl77Mtp33H6Ktf+4o+8pEPaty4sfr+D76vBxfMV7NnSPY9HuvmP3i/Lr74EhZB0sQNNlJSobLyu8JwoN4iNXT77bewqfYrbbPtNnr+wQfxnutqxvTpeje7wZ/5wpf1mc99njrG6Rc//wX9cY/unjtHF1x4nrbYYnN9Ap/1mU9/Rs/AR7kPb+QUIQIZ8h4V79PsbeB/79XPf/ZzzcfXvvfo9+FrvqqPfPij2u0pu8kTy3PPPUeHohdfY0F5BCfG/lET+wjrhRcRu+66q/bZe2/RZE1Eps981jOz3pzLKdGDAydH4uphw7Phjy8Rr3jPIDSokqcsSrQrp9W9OhJANIinQi9KeWyw3Jy3lAWdF43zH5yvw484XO6bd7zjHSyyr+QU+jzspcrQyn3cg509E5v+HPb7Vfk07aij3q2nPGVXPf/5B2va1Gn5VG+v4LXjJgAAEABJREFUvZ6mT7F4PQH7Pg7f7Y2bk1mALFu2jCpDJQvZiGAuWGjty+0yrI3/T04zbR78+kFHKoOxuWP9cAJsRChSDBBUCpwcFqGFrOxO/+OfNJ5JjY9mZ8/eTjaiZk9D6+FYdtpxewbd7bIjE8Xvv+c+nfiLEzHirzAB+ga7OzfBs6LzKt1x6x26/NIrdMEFF+tHP/xppvGKcSm7N4m6I0IrVqzQ6aedqa9/7Vsoy9d17rnnqc2u7RAWEBXKlFLSfIz6V7/6tb721a/nndpzcZr9HP0W0dCC+Q8wobpYf2aX9Qc/+im7fadpEScigTONKr+s5jLoX3LRpdpiy5lMljbT0OYw2ak3ewutM2q47rz1Fs27Z55SMUSRmmr1r+Q9boDPAspskScV+I+s4MHCaDk7G9dcfa2mTZmumQw4dsY0U70cefYOHaqeZkMjhxPifIYyydp4k014z+XsAN+mlX191BGKQEw0z0rcAbm9GZwJkN+9H1sClaznq2XlfhpcwunSg08ltduV/DE7Uea//uu1mj59qkaMHMFkulfuDdvApptuqY033kzDR4zQUCbKm26+eR5c7kSHWu1SJQwrOqrEOVXwvfeee3Qdk9yZs2YySdkUzsFEdah6e3rlnb170Ku72Pnaeutt5Ann6HXGMEnZWpM22jDzN01vs0dDmcwX2AQN4a5UesQmVroe4sNHDNfQYb0ain6NIN7ThD91LETXe5pNrTNmtEYzkS1p42Lv5rBAvpPdvr2f9nSNXXdddLdk0Vtp3Hrraccdttf1nD7cgt7DOuMr3snvzwtQa317t88Lj21mz9Z6+ANj261+VWULn1Bo+ozp2nLLLTV+/fHq7e3VRkzYJjAgL+TkxAu0UaPG4PR303rU2cNgPA3HP3nKZHaSFjApWp7tpCgS71oqIvQQu4DXsPNZItfdmeyM4H3WW28cE4sttA5yG4p9bU5/uK4FroPFy9VXX81JznK96lWv0lZbbaWRI0ci92YeNFIqJIUq+iyQrScLM2fNYtIwgYlRQ5MmTdaEDSbKp0krV/brATYAhtDnw4YP0/rUOwIbXrlyuS677DItYxK37bbbavz49ZVs7OiTd62nMzGKCHnX0gOYBi7TRER+N9ffgYHsbjAgAURUxxwBglSgixX710S5QzdzqubF3Atf9EIW5HtrzJgx8gTefncl48c16MAwdGMXFs7rrjNOkzaarFnYY6vVhx+/VStWrMx86j6RlrMRdsZpZ6EnQzQb3R6OPblLe3qaWY8LfLx34a9nAfnsZz9bE9hYaqNr81kkTJ48WYceeih6vxV8l8NX2RaKIhGvFOE3qHiDYCd9oc4590x49qBzE1kstNW/sq3lK9B97GECG28jR46gHU10KvJC2B9z3YyJ9IzpU9Rk/LB9DhnSi8/YJvOx/1rMyV1KDepDUuh2iY/wmBkRsg7ewel5q1Vluxk+fDi79X3g+7CDUt7c2mqrLbXJxjNk+W2wwQbyOy1duoQ2V6qoMFgYiOvMs/6c9X7ihElSmVgA9atZFNluIVbK9a3k1PM63cBmnBc+48eP1yhscDcW09NmbKxe3nODiRtRxxQ9xHs/yKKkct9i40VK6u0dqhH42vXxIWPXGasi2WZF2xoqGsHGQx8L8stUFA299rWvlf3x0GFDNQTfl1JSiwWYf5J28qRJ6MW6WnedMVrJRod90IUXXkB/SLvuvDP23qM2cjK933drNlL8UTMvKAfbpnlGBOVq2RLL8YiQkLW61xoSqKwIYJqN2naIZnl5zma/udlmmzFOzFAvOjwL37vOOutkPbevD/ovArnCo0hBHzXp9yZ61scp2JWEKzUL+xw7dixjyPqaOWs7eXyx3m6xxRbacMNJbEDdnxcTQcWdtkQ4pVW+l6zcpoga73QXpPR4hFDrfAwirdQxBBvOvezI/OWKK7XZJptqyy22kifWJi5S4SB3qCdSxt971zydyFGjj4ZO/MWJ+s73vquf/fRn7JTOVaPo0cWXXKyPfuQT+toJX9fvT/2dvv/97+n44z+hM8/4k/pZFDC3kXdMvBP0i5+dqF+w8Dj5V6foxhtvFOaqNk7lARYLp51xBry/p5NO/KV+yLHl99g5un3OHShEW7ewa/+p4z+jz33xG/rNb0/Nn3tewJFoi7INHE4vJw533TmHo6x52nrrHTVy1LryhGT5imWKWKFn77ObFj9wjy44/wLwhVIMlXcrb7/9NnZ+ZmmTGVOQTxt8JSs1CT3IZOWSSy/TxA0msGiYLO+4ruzvV2r0YBjDcP5JCWlZylbi8RMnaPomM3QHO6PeJengQ/ylpIiQ6AaKrHWD12BYK7ub/KsSsPxTJDUYcFasWKp7OAIPZL5y5Ur98qRf6qSTfsUu/ZXyQFkUzTwY9jABd4d4IL577t1auHAxk/2pGtLbVMmAatpGoykPznPuuD1PHKYwEe5hEPNEuUL3Sha7y5Y9xA7dRSw8F+lpT3sak/0huTdd7qKLLtJPf/pz/f73pzL5GaoDDjxA5lEyqAXtLRiYE050221mMamZlU9FfvLjn+oPHOUPYVd8jz320nqcfG2yyXRdc+1f9L3vf18/5VTQHyXoY/J70UUXa2NseNrUqSp4d0N/KRUsTKZOnSJPEO7ihKGfdkYEO2ilcrtpe4Uyuv23YQO33XGnZszYVE0m0v61xFQUCtoVDPqNwrpbqI/DFqvv3Hvv0Txg0uSN1Gg0FBEaQjnHxWW7uf+++/Pk34seUNQplXZKMLjvvvs0lzZN5bRmxIiRZJf0RxO592RebRzGHcjbk7f1WIQ4vP322/FJPSzqRuvnPz8RH/JLfMAVuW+oXpZhSgleUhQSL6o2C55gUuT23HnX3fTLcI0ePZIF3ya6/Y5bdeKJJ+JnfqDFSxbRtjb8LpYXBrvsskPmV/D+NDe3yROusfTDNddcK+90RYR8VX4nIhF1mmj3fgwJZJ1D94TuZTILmIhPoefNsw0ulGV9znnnyB9JO+P0M7Rk8VKtwI5vvOlGjWGiuMXmW2Z9Mo+NJm+QF3e33nI7k97lGZ/Qg0AVljNxvfjiS7Xuuutr+rSNcz8GfRoROe5J5IUsuK2DM5j0DmWR7gXKXnvtxU7/S7GH6eh1j3p7e+DbVqJsUcCYtgfxiNDKFX35pM8fP9x++x01kUmzJ92NRlPTp26sBYxrP/jh99hs+zmnWHM0Bv279OILscvF2nmn2RrKBAs2CmRgVVpnndHabLNN88cz/DHFig0xKmcTpC3bakSowM79vYfrrrueTb3tmVBtqAJ7tS6aptNOSBl/+xUR2Tfde+88rTduPTa5RphllulNjMFnnXkWC4tNM/T3t0UB37wlEs79E1r80AO6c+4dGsPJ5kaTNqK+pJSSevCVlVqUaWspdjRn7p3q6WlofU7wJjG53367WVrwwH36FT7YvusWThae/cxns6E3TeE/2iYu9+/NN9+MjxyuIUOHyTvKJ/7yVyziL1dE4EvWxW9O44TjZH3vW9/SmaefLm+e3HLLzcj/Rm3FJsIEFjGWg8eBFgs/n0ptuummupux4B42fCwf51Md7185WBU6ETxMQ9C915KAZdNBWcfsk52ez0buHZz6enE2evRoo7CXIXnh6I8vLVq0OOPcJ6GQ+8Vx685tt92q3/zmN5yEzWRhvqWajKtFkcRNmUoRkRcdD7DBs97662f/n8hM6F1EQNO9H48E7LEem64jy2qArMJN20lnkEp27RcxGW6wQ+6dCXcAJHlH8Oorr9K5Z5ydV/t3Mqg/tPghnf3H03UZExN/sfM3v/2tvshR7nx2YS5lMm3F6Wficsdtt2dH/+lPf0rf/MY3tO22W+vXp5yshQvu0/33zdV3v/NtVo4z9c1vfV0/+fGP9MxnPAOnuESe0FVl6OwLztWf/nymXvHyl8tfavOR8Th2I/54mk8S7lfCfXngnzJtWv6CjL/EOoUJR5uJUFX1oVwrtWLFQ6xWxe7DJCYgI1VWCadWauSw0OytpmudET35Y0lz7p2vpSvaOv/Cyzg2vUu777aDhg6txcpcSzBTH7tVPjZesuQhbbTRRvLiyQaQitDtLAjOPOssTknO1xVXXK1FCxYp+Bs2bLjGcjozb95cHPRC+bIDMjgeARXg+GoIoo8EoLv3wySQx0/EtVq10W10w2KNiDwALF+2nAH5Ic27ex66dLI+97kv6NPHfyaffF3DiVGbxYCgFXxSNPPk9bTTTmfyW2hrBp4IMqpSnvC7Af39fVq4cJHGjRuXd9VEdgQPMhssOu6ae5duZHd0CpP2zTffIg/uzl6AjfmznF/80hd1KguA6dOn5cmNnaYH5jYTY9MZxo3bQLNn7SDvpH6DI/ff/+63mjF9Y40ZPTY7yv32fQ462Mh29Kc/nqYxY9aRPy/ay8Jgt912lz/XfxE2dDtO2K8nrtGjRmn0qBG6y/q4dBm2ECqZRHuxIiotWQwsWPgAu4bXq4ed2/XHryeI1EbIEaHAtgQEsiCpZiHdy0LglF//Rt793GH77dULsoKn6AOqZBPhLv3kpz9RiqRZM2dqOLv4eaFAfpES1YYeeuihLNvx7HoWBTgKpgLmlKno2DtYLJx66u+R97os/rfO8rSfuOuuufoJiyV/TOX444/Xl774JV31l+vZWe2HQ9D3yrT2SQ0WMj3N4bnffvPr32n+Aw/m3dtms0e77LKTZm67rX7965P1ne9+RzvutD270Us1lNPOCRM3YGF2LRscF3BKNYfXL+Fb5d1RTyxvw8/5Y1ZUmO+ShZ/tOwJ5ARnZfTyqBCyrhwHUfa0+uY+XLlkif+79K1/5so7/9PH60Ic+qLPPPhPfvkKFdQTaFuOXT9ikQI9Wcpq7TM1GocQk3rZtfXO/9PetzKdJo0auqzHrjBHaoRJ9Rp1zn/pHDvyRlv33P4Ad+bEZ57b19vbKu/2OZ3qU0vxKClbocRt99+f5nX/jTdeygP25ttl2lmZvtxPjzlD1rWyh/z3aepuZ2m23pzKhvU5f+9qX5Y/Bjh8/Fl9xNTo3W/c/cL/OPvciXXzpX7RkiTe2aCL3tGlTeK8+zWcyVlFnsEAALdffYGOsoj1eXN188y3yDuwo7Ny4Jr6o2dOkHmXaqmqriX0uXrxIf/jD79lMu5UNjb3Q5ZHIqtC9997HgvnH2nDihtp119042RzBhkuTd+hVC722HwkW3KGk5WyKLHtoqdZbb331DBkqIYdKbcKSaGjxksX6HZuFd7Po22H77fLCvtFoapen7KQdtttWJ//yF2x0/EwlJxjTGMN9Mk9BOJTyiWeFTGGm22+/Qz/8wY/15S+dkD/m+elPf0ZXXfkXFiDr64ADDpQXSl/72td0+eVXaBLtvh1f4dPc9TkZPff883Qpp4Tz7r0XX95U0Who1OhRGscp4oKFC7MOuQ7LqgNOR4SD3P+ORNRpx7uwWgJBnyvodU57VrARa9toIOMSXenp6UGnVqBddzsAABAASURBVMvNY1tfX4sFa0vGFqmoGZHgZp62Ev96qxbSL7vu+hT6dwPUoVKkVEMEtvsAmzq/lDeYdtl5F43gFK1EKT22mJn70GGEOTrWhUeSQHok5No4y7DKyIpuLjHUGrAK+rzEIQ6RGZWsxE1WFAU7CHP145/8WB//+Mf03qOO0o9++lM9OP9B3Xz9DepFMbwouPSyS+WPJ63giNi7hA7diTtsv4Oe8+znyKvM6TNmaPen7s6Oz9L8JeQbr78WB9hS/ljDxPWYdI3SnnvtmT/GECjI8pVLOEG4WQvZjRkxcrguv+LyvLJssuI885xz5I97NHB8G3E0tS2OedLEsTjCHlUsNNz2CrcjIHBuQ4YM03rrT2CTJ5gOhZqSGpxyDOkpNHvWNprPavXyy6/S3YS3zrlT608Yry0330RDe3tQ2AJFrpVvIQPXtddcpx122Fnbbr1NNoZms8E7rdCZZ52tT33ms/roxz6hH//wR5xU3Mmg1a8hedI1Xks49l22jAGAuiNC3MQqWcHLqiTevf9eCQQMKia2BPVdKctXSkoI/IH7H8gO5xksTL/y5S/nz9cPHz4ynzTczY5TRNJyFoX+sut3vvs9BqK79bzn7ctOlSf8sIRfT7MpWDEBWKle9GOjjTZUL31ckWed98TU9XmCGxHafrvt2V1r5olNRT+vx0D1v//7vzqByc8b3/gGXX311frWt7+tG2+4KfNtotNCS+1YL7vscp2FXh2w//76whc/ryOPfDcD+r36/vd+yM7kPSw01tOb3vR6nXDCCfJkecMJE1WkpJlMSk7+1cn68Ic/pg8edxz5X2EBdJeYOauRQt6x9JdFlzLYy1eIunlIKqKQvwB8y623audddtaYddcVa5jaV7T7kWc7AwWYlLd0000362vf+YFuvvl27U87N+EYOoWcjd305/c76aSTdD07n/6s+KxZs8iDQAGfWv/FhajyR8HWZ/KReAcN5HvCeOWVV+i7TOL9nYW92OndZJN6Z3jlyj7df//9edL/1a+ewPt+WCNHjtI3v/l1zbv7HvocLjBORaEiJd5Buo2Tk+//8Lv5VHGPPXZnsrQHNRWUG62XvewVLCQ/q89//gvafvvZDFzztfHGM3Tdtdfp6KOP5cT0o7Tje3kC4wlqs9mTfZsHuJIBskIJHNbt16r3iwhFhLrX45OA5VhhKxGBjtV9PJ7J33EfOI4F4RfzmPJTTuh8sjOUE4CIQLXLWsZMiPtb/Uoo4YiRI+UxzPE2/dNq96kkv7d3qMazOzls2BD6iHIeDem7JYsfYly5R+ui8zvttCM728PIr1aBW09VWr58OfW1qaOQJ0gtJkuup4lvuPe+e3TeeWfnhc6ee+yjcetOIG7apgpOvYto4FP2x14/Axyvffd9FhOoZdpo8nhOqRbp+E9/Rh/5yMfZzPicLrzwYia0K/N7jRkzBntaqcWLl9TtYZIUEUyCG+Tjt5a77fdqAj5gOpsK1sF+Tr6rqpJ9ksG4ZrNXd7NpcuKJP+f07FIWBbtqn32eCZ8eNrQe1HnnnpfreM5zn6NpU6eyIdCj3p5hajLWt5gXVMgxpUJCjiUTek++p06bTjpU0aZa/wvdNXeefvf73+pUTlF32nEnvfDFh7L46NWNN9/AAv8n+MSEvR6nT33q0/JJzze//i1dftmVanvhB582/d+G/4IF8zXvnnu1B3ODz3/xs9mf+WOW3/nO9/KJ8SabbKKjjzlaJ3z9azr88CNy32y04UbaEL/83e9+Vx/76Mf04Y98WD/60Y/0ABualsdIfIQXVItYNK3glMr9aogIRUqOynSGCHBARnYfa0igIlViN23mUkTp0150EXmR8KKBgDsAgZeGcOJsaOc+llyWHOyolvl8+mcOJxO77LKLfDoh7LIyoHNUwxhzS16IX3vtNfjtvdHdXbLethmgnB8R1BPyFVGHjnfh4RKoJf5w/BoYCxX5YwzuCqnEMJEw6UqpSBo1ZjST+H55kg5SCeOZwUT/Va9+td7yprdoyy22zGUeYuJ7991366Ybb5I/inT8Fz+nzzOhueXW26gvspOzUozCMIezAoyoO69RJFaEw9RDuIhV5NixY7UBO5iJeio2BHtwZkPZqWgUhezc/dGJW2++Ud/4xrf0xc9/Hvhc/RNpKF6z0ZQdVINBe9SokfK7sVGkYKDwO2UlYuKlgReORqWi6VSl1rIVWvbgEqXGUO242+4qUsGk4BpdcdUVWrB0sWbOng0uqWqVOMshFMIZUsF97FJcjbJOx0GOZ1Fh9v4YyHB2TJ+29156/9Hv07Hvf59e/ZpXasaMqephQunqI0IJ0MAVMj+pNhgpItS9/g4JeJFgGGBhabLpUcsVr1aWTCCKJA+6/pjB7NmztNnmm2rXXXfWLuxkXMfi1x8/WrGiT5decpm+xGS+jTK9+U1v0p57PBVHN1SCaYKHQ3ElLK5kotAC2jisiFBRNLIDKyl7HZPMEkc3HftRvmgIoR3mlClTtCnH4rPZbd/7aU/TDdfdIH/Zt8niM4KKqGTJ4oW65upr8o8P7LjzDtp0s000a/Y2mjVzFnZ3s+6dd6+KItjdW1ebkTd8+Ah2J+drAjv089mFvOiii/Sa17xGb37jGzWUCdK5512g+QsXKyI0dp11sl730+42SlwxOFcOUdYVfct1/fXXyV8I3HbrrTV06DBypJRCfv2SwaHywiGka667Vl/+2jeZWC/SEW8/nBPCfTRi2DBJgW6Xuvqaa/T9738/T8Je//rX6el7761hQ+GH3ykN1N/yJATbqgDzFu2DtSxD2/+ll12k733vO0zehss/u+fPSjeYvIirRL4bb7wxE569tdmmm8kDjb+MfMcdc+RdR8Eo6KeUeJDwxx2//Z2v67ZbbsmfiT7wwOcxOVxHRYGt0z1jx46Tv2RqGV515RWaOnUKvmy5rrjiCj3nOc/Wke8+Uj34m9/97nf0cwMo5AVNs9lUL7budxBXBBUTdtJEu/cjSQCZd9ARyMwAwh95ZQdLRUr0mjQG/74Hi7uZ287U7NnbyQvP+UwubmVR20If+/LE2JPymgfqrF7GkZGUSwWTW7gUKTHp7cEPO13JE2jrTxv7rfupYlE9D71fyDi3Vd5xN978E2UjgjGmUqBQdVqkywzJOBYCLXj94U+noq/f14ZsZN1/3wP5VH7ePfdpLvZ655w7tGjhImxgRP6oz6Ysru+eeyc6tlSbbzFdV/7lUu28845633vfpQPZOb/ggovYJLtLEQFUStig65ZoC7pfYa+d9G133Jp30v0jCuuss64oIuu1uCKCxiqfjN1+x2363ve/De0lLFz21SEveEFe9Pb1r6T+K/X9H3wfmx+qpUuW5o/++GOEtidvbDzEBkOCV5lttoRzif6vkD+Sa1wk6klJd8y5XT/40fd0zrnna/8DDtJLX/ZyuS/c3muuuVZXXXWlZuPLttpqS071tqk3CeF7F6eF3mxsxFA2LoYoFfQ/LDfBxvfAD2+GvPbY86nyzrLb4w2gVBSaMm0q8ttShUIP0e5Zs2dr7gCvI444XC889FDNf3C+brjxBq3khEm0saenB/ttKgJZ4nuEP6IqhFQJsa4C60AHeOHuPUgClldioLWeNZs9sh+MCBa+yxAhcuRZC5InMu7HTkeMGJFP7hK6UkOiO+x/SxaG8zTnzjvZkN2BcW09VYyjJYvGEl2/lrHkO9/5FicQt+nVzEcPPvhANnlGUkPKLWrlRYh1MiflPqtjdd2D0x38/9HwCWl2LbXHYkX/0WfYRVkL0xMsOpfeElYDJI1iZ2WTzTfXTRxrXo1RV3TUGCb9m2y6iWbPmiUPpBZ8g4nNxqzsn/HMZ+joo4/Wxz78UXYKPqWvffWresXLX8EO5hg1GESXr1zGhOch95hKJhn+JYgiNSQljR41WktY4S9YsFCljbUpLXhwETuGD9C+0NAhw+WPczyVCdXr3/h6HXPs0frM5z4jfyzpA8cexwp0mqwkVrpGs379NhMQO29P4hMO3ANHi3rvf/B+3XnvPPUjANRTvWmIRg0ZqUajR2OZYO20yw6ac/st+va3vsvkqKGdd3paziv7+9jhWsaEq2J3p08333Kzho0YoQ02nKhUJN6pzY7GMrUYKPwltlnIaPvtZmtzJqN2kI1UUL5fK5ev0ER2fkay4yUuO86I8JjIu1aKCLDd+++SAI5LWYyrnQbeRBHBwFlo6NDhGjNmHQ1nAVsUBTonpVSQl9Ri0tFPX99668369a9P0c4776wj3vY2bb31lkxUmQAnqQAqFMp0qFF2ji12Mu+eO1f97HSLKyLgmeSBzzvf/riSHaTLRUSepDz0EM4UBiklFpS9uf9brT4VLDbE5Y+2LGHQa+EAH2RS1GZwHjJkCHRCJ5PWwUZL9FxoKuTsTq4E+nX66X9mkjxPWzIItxgUx4wZxYJoF22LTvqXme6/714tZcBvU/fCRUvlLwiuM3p05osGcopQZn2cx0nL7Uy4J03aSGOw0US7G1SUEGYo1OhpKjWbuu3mm/Sbk3+lTTfdWO9625s0c4tNsm0EMhUr8zvn3KXf/uY32mKLLfSGN7xBPmmx/sMuyyglKRVJzUahiJAU8v998EZEG3/Qok+uufZq/fSnP9Gee+6pN77xTdqWk8TRo8copUJFUXBkvR4TuxFqMlilFCpSynmedCxbthzbXIGPWSxvXtzPIupHP/6BRo0apXe96z3aZdddte7YdaAP5BrULt5QWr7iIZ1//lm6+eabNWmjSfkkaaONJugZz3i6tt9+e05Bhup2dsEiIpft6WnmAbAoGoowLqlzRUSOVsjckBPdxxoSQDQ5HRFZfkGKqJ/It8gLUPdZA/lKzhU71cPohxEkQz4NWD6wgTWQTf/cxSL1fk6V16t1g2IRQTb+GL1atmIpi+u7mdgsV9HoVSoK7KCk3K3ypHh3Jqe1NkhFzqvkKyKU0LES/VzBSaQVpqBdfexSL1r0IKdXt+RT8fvuu1+/OulkveOd79ZnP/sZeTL/ox/9UN/7zk9ZkCyCRxP/U+mmm65jEnsjY9kUjRwxXC0mVDswfuy80/aMIZvxDvdq8aIl8mV7sO57E87pRL2J9pR5UtXWnXPmcPo4L5+IDRlivyLqSYoIwlAB/f3338tO+w+1cOFC+f+n7Lnn3ho3dj30v8HrlpyK3yF/ZNIL4ncdeaSOPfb9OuPPp+vk35ykL33pBN1ww41+ZbXxP25Ps9FgfGvh7+5WFEkK6YH772PB9F1oKr3uf96o5zx7f+x0PG1I4Eom7P2qylDCR7hN4uppFio4fRkypAf+weT+fi15aCGL816NG7eefIpRwB/2KoqGenp6FBHyhltB/6RU0JcP4QNP00h82pQpk/Pkc/z48dpxxx01i42ZIiXkfRM+YbmWLFmS/d04fOmQ3t7MK5Fvv2qgSYrk2hAL72rbjajTzuuCJVCJHqC/KkYixo4snkqW1QbyhwqMAAAQAElEQVTMqSZNmqB77p2LPT1kYhagy3TTjTejawnbHUofP6gHHnhQ1l/BZUXfiqzDPr3zD1S4n1uMr2KeunjxYv2AhazH77e+9a166lN3y3NMukx0f9Yr62PJfNX1u8JO6HgXHi6BZMdr6GSF3KEVfTEATtOp1vuIUCowUib+4iojyeCfEH32fs/Tvffdp4997JP689lnaS4O4IEHHsiOoGTyXUWpMePGaIMpG+o2dke8wzaKHczRI0drJDCMnU7vAPpYuAV9FFRQlSoqafSoddTXTySaGrfeeNnRn3vO2Zpz6x26l3rOIX7pxZerv6/kFGKYNlh/vIokrWQQHzl63bwzM27kCG2w7lg1mkPU399mx2ZBvSiR1IC4ZKLFopR4ryKGaAy7qetsMFpz7r1DS5m4IwalqqlhQ0bniXyb3efd93yKWtRx7933ada2u2jkiPHw76F8v/qWL1Co1AImcbfcdoe2xwFNnjpJmIaiCPkUobenV5Con4laX1+/HmKy4r6ICC3hCNkf2xrFQmMkspEvBpwK5Y6gQ0hn5XZ0MIDv3o8tgY647Nu9XsBb5QJomCoyM2RM0J9D2LVYnwH7QfnLxt5Bv4lJ78UXXahp7FCtN26czjrrTPSzT9Onz5D12r/2MO9edH/+IvUzcfdk2IOkO7vJpHkcZdy/ixctpuoK51eqouP/8pcrNX/+Am200eQ8YSkY5KSkezha/+Mf/6Bb2OH2Dqm/4PW73/1GDSbNU6ZOzh8F+MY3vq1Pf/rz8g7pxkzG77n3nrxT9+CDCxmwb83H/FNnTNUGEybwZokJbUvnnXe+5sy5U95dnD5juob0NrR44X26/bZbdPOtt+sv7M6MGTFEo4cP0YMLl+iuefdr3Jh1NXbkcBXmUvRme0m08dZb7tDCRcuYpD9do7G13iT1WLlZ1LSxlYrBmSL6/W9/jU+4RzO33JRSlby4WcACZ5G/jMpJzeVXXKlrfRo3fbp6GZQ9EfE7L1yELJkY+ddqPOmqsC7z868TDae+BQsXMJi3mVisyO+1ksXYtOnTcn+4z+Yz8V/MRoPLTOOkzwuzH/7wRwxA83XjTTfqiisvy6dHEyaO18knn6JPfOKT8uT/ak5r7r9/Pn1bf5zJ9XjA8iLFO9SlKgaeVj5d+fUpv9FuT9mdneZttc6YMfLPwd7IZOlWTlDvvnuehjIha6MPixnI5vPOYzmZKJgAuU3ZlolEhCKCmHIYUcfVvdaQgMWSGH9CsQof4TiawYxgYzarJm44QT//xc903Q3XyR9Z+NVJJ7HI79cMdGuHHbdDX/r1xz/8QTdz4n3zTbfqqitvyHY3fvxY9fQ0VOFrrUdtwoJxb9Kk9bWibwG+4AEWyU16vtCKlSuwr2vkif94Tr0730dItIFi2HaVwRMaUWIYJ2lBHuYu/+Op4z74Qd1w/fV6yYtfph/+8Mc6/vjP6yMf+qiOOOLt2nLLzbXf856l/fbfNy9ixBi6aNGCrN89PUPRtb3RqVGq2pWuveZ63XLzHP3lyivA9WTb8QT9JnxGs9mrkSx4SzaoEJmiCBX4Fi8E5t41T1ttuQU+bqyqqkVb24oI5NTKPqLVquRff/LO+2abbqERw0fzrovZoLsvfx68Td37PP2Z+uoJ38iLg49+5KM66r1Haden7qxnPWcfve71/61NN54hdslU4K8anPCPGjFa641dHz+wkM2IfrVZjN3KQvuyS/6iCRtM0gbjJ8mbH/Ox2QULHlR/f0ubzNiMTZhR2OZv5e/+3MHmxG/wJYsWzWdOMFa33nybjjzyPfrFz05UwbttudVWuufe+zj5+BGLvAd0xeVX6vwLL8SOp2sdxvaI0FJ8zkUXXqyFS5do0tQpyHi8fJI5H9ucN++ebP/zmcN4gVCkQn0rVmgl4I+zNVj02GZb2HNJvwYyDQ8olRSS3McRxEirez1MAoGUQgl9q9A7p5ImsaG61x676aILztHVV/9F8x+Yr1+f/DsWxG3N2HiaHlq5UJ//0ud0wle/pYWceqdIWvbQEs29+06NYEwaPRpb8EdOwK/E///+d7/X/ffN12abbZ7tYSELXvftIsbdNrbQbCbsvaEC244I+bLdRtRxp7uwpgQY1tdEDE5ZbLXsKuXQCBsHCTDERGdTAkPZbIst9bo3vpFO34jdkc/pzYe9Bad3RD5J8O7jHrvvng11l7121+QZ0+TfYf/f170u7wB+8APH6ZqrrsWnlHRsj4bT+Y1moXriVqnEuw7nxIL5sqbN2FQve+nLcfI36D1HvUfvePs7MexbtPVW2+SFRVm1tePs7TVrm630hS98Vq9/3X/Ln/1+9/uO0ZnnXYDRr0RJeti9GKcmDqxSpeRViXg56okyEUuauNFETd10kq689jIt4FiyiKQmE/zeocPUO2yoUhFM7Caxe7m19tp9T22/3S6yE+nva6un2dTYMSPVgPcClHQOu8nrs3oewcSmZGenYpbqegscW7PRlK9UpFy+8kvSDv8jtzm3354HN3/2UlwRoYg1AXT3fqIkQL+g0ULC9FzFhKJUSqEdd9pZT3/63vlXGP73f/9HH/jAB1TQ/694xcs1nn69n0Xrbbfcqs8cf7z+l13xN7z5ML3tbW/Pn1u/D6fn5kVKarMQLopCG02eqgY64u88LGOXM5HXz2R46dKH0Mv1NWXKFPgXikAX6e8Wi1n/KID/k+Vhhx2m9773vQyoS/SqV70qTyq8SPHO/Jw77mRwbevpez9DT3va0+TP977t8MP1gePez8LgDh14wP6asOF4lejYgoWLdAanC2NGj9YuT3mKejiN2O2pu2qT6VP10Y98SJ/7whdpy3g9g/ceSt7tc+Zq1LrjNGnSJPHqqpgNlRhokQomEIuYMN+gKJqayW7+EN4tkV+orQJJFgXvgRD8T5PaZYXtXq/jP/lxvfnNb9TrX/8Gvfkth+mLXz5Bt7PbaVv3xxk+8YlPyO/6RnyKP1L08Y99PNfR29OT7avCRgzelbK8POl/EDut4O/Jmb8j8cHjPqS3vvUtetOb3pDD73//B/KAMWvWLD3nOc9hIvQX8t6sY445Ri7z2te+RhMmjNdc7PVeJhveUVzw4ELdf/8D+vZ3vkM736Q3vumNeuthh+tzn/+yrrv+RvopyT+T+6c//UlTJk/TzjvtotFj1tF22++o8eM3YBL1ZR31nvdo6NAheuGLDlVE6O6775H72u0YOnQokune/78SsB+VdQE9c9+XnsCx8zONRcH+Bx6YdfOYo4/GHt8m//qQP5bg75nMYIH88pe/TN7lP4qTo6Pf936l1IM+vpEJ6wY0pw2Usn4rUh679thjVxaBd+mGG2+ktsCeKy1bvlTDRwzXFHanE77Cu9gOK2zDYQRsuHsYO8aNW5/xbQjl2kpRMOlZpJtYrC5fvlwbcSq14w67aJedn6Ldd99DO+20E7gNtM22m2nmrC2Z8I9Adwqd+odTseW7tdOO6NmoMZoyeTNod5UnRz61P/30P2nvvffUtOmTmfT360YWQ73Y74YbbYjPKfBpLVrjO8i7Of/G/ezZs/OJi9tqKLHdiJDHM9uYF+he8P7sZz9jTH8bdvsm7OaNOu64YzlVO5+yY7XNNjNp+67aY/e9OIXbWRtvPFWbb76xtp25JbIbQ9tDeXJdSkOHjGTBMB4bWK67596jkkWHqqQVbBj84Ps/0mGc0h5++NtyHe9+95E6689/1saM+694+auR2RK9B/932GFvZQPnN9p3v3211dZbaelDy3TjDbdpwYLFLPZ6tMsuO8v/O+Hcc87TG17/Rn3wQx/kpSv97+v+VxtuuGHug9tuu02n/PrXmrHJJrRzluynnotf8ALmne94h/zriptvvhnvtQsqVumWW26W8C9jx46FtoCf0IMqhxEDHZ1T4n0BrYlT91olAdttQmYl8yHrl3XOc6un7v4U+nqqvvB55pBveIv88br92Iz2iU9/a4Xm3DUnnwKV9EMgX2/c2H78Ud0Gc8aIoG8ajIP9jJEP4Wvn6Stf/ko+rfZY8qY3voWNtc/ouuuuo7QEudyGdvYbKKdWXxHUAKzGdGPus0eXQhZW5PwKuyhxJCUdZbAjyRlkl5wE2Dlut/32+q//eo1e8+pX6wUHH6IDcNgveulLdegLX6iZW2+jSEkbTdpILwb30pe9VC849FAd9PyD9IxnPUvr5Z88rOTPEr+MvGnTpqqivigKzZq1nV75ilfJJxnDhw/TXnvvrZe/4hV6/sEH6xDgRS95kY7EsRyw/wEqUuKof10999nPwVG8Xi968Yv0Igbq/fZ7rqbh1FvsZkxlMHnVq1/FJH8mitVWn//PAbs3DY4387ux+pwwcUPN3mEbdjuvlP9RW5tJ24zNN9FL/+uVmsXxb0qhVBTa74AD9arXvFJTJ02UmCCNGjVWz9nvQL3w0BdqGbsRZ55+hkaNGCl/LCsiqK+VndVYjnRf9arXyP9kpEgF71opRcoKPP/BBbrqqqvkj2JsMmMTBpleeIu8yKCBa1UfDKS7wd8rAZQcFhXDAJLO/eTjTf+Tomc845n67//+b734xS/WS1/6Mr2MycZWW22p4ewYHnjQgeT9j15I3gvR9UMOOVjPP/j52plBawSnQ3Q7TqlkdKnov6T1OfLefPMt8oT1umuvlXUypSR/dOVg9Nmfr6cZuYz7eP3115fx/iduz3ve86j/pXodi+2nPvWpWUdGsXv4ile+ggH2DRo+fIjWXXeM9t9/f732v/9LB2NfLueP92yz7VYskpuZ7/Bhw7Wv/8nUs5/FruFwdilbmj5tml6Obb4MeCX8XG4yC4QHWPRcfsXlmjp1GoOt9Vz5PSqh8Tha78T7f074i76jRg5XIL+SgYAXVvBeYvLk90gsKA7Y/0Ad/vZ3yIutA/EPBx14gF6AvGz3Yzl58fcJ3ssO5Wte82odcsghGZ7//Ofr6fvsow02WF9Fo5F5lvgG8/SOrQcL2875552X+8yyOuKII+S+OBD+Bx10kCy32bNnI58RGjNmtJ7+9KfRZ6+VaV/ykpfQnpfJ/ekJ/H5MQtzX05DHzjvvnDc1Xv0q2vOCQ/QC4KCDDmASsVP2M4EMRjBh3Ofp++jFL3oxu53jlPAl7rMX45fcT9aVF734hZn/woWLsm0X+I5tt92ayU1Dfg/YdO/HKwELHVrLLesB8UDrQlhuHp/a8iR5xx131mte81p5DHgJOv0///u/2muvveQ+DnytP+5W982LZbt+xSteJv/gRrOHiTUnYy0v8NG3SkGZYdphu+2ZRDd1+eWXs3t9L/2csJ0Rega6+bzn7Zf9tPvVY2UEpSJyy5yeMWPGKptNjB1kaK8999KR7zoSXdpVvSyE22W/+vpX4A/60dOhbHS9RnvssYvMyz6iYpzdZptt9YJDXqBtt50Ji1I+tdqDDav/+Z//ybZiu33qU59CnpjMX6DlnFpPnTpVo0ePwe7bmbcUWrp0KQvwUIi/ZQAAEABJREFU6wkf0oQJG6KHvVkPXYe4XJ9l67rtl970pjfp1Yzrz8P/HIxv8/+VeN7z9s879n7NluXV6ler3afhbKi94AXPx788Q/2cnq9YsVyCqEgNwkKp6NUmm2yhbTkFOIMFzh13ztV05HPku96pN7/pDToA37XvvvvJdn8gPmLjTTbGZsfoKU/ZRV7kvQgfa9/01re+Vc997nNYkKzD4mRzffjDH8HvHSBf/gjms579DGRI/7/wRbT9VcArtdXWW8qyrtqlRo0eSR0HaM899mTRNwz5lPL/WjDvF7/kxXrlK1+pgw48UP5fUnfcfpuu4gTY+Ruy4IgIWUYRIftudS76XamSHOIHcqjutbYEKozC3/dLqZAXpp5f9aND48atp5e+/JV6FbI/5NCD8csvzR8lGs0YN2bkGOZ0b2SO+Wr6bhT6WjLWrav99ttP/kejw4ePpA+r3C9DOM017u3veLv+67X/lf38wYytnm8+hQ0y+2d6CR74DEfWbuCa6W5qQALJITrvYA2IiFXpiDoeEdh9rIFPGZcUCTzOejrGvT/GfugBB2XD3/+QA7Xzbk9RLztp/hx0QLbh5I3kX0F6AR3oCf8znrmPJmy4gVJKmjRlI221zVZad9xYUZlgqQ1xeDN32EmjxoyRGBSGDR+q3ffaQwcdfKCed8B+mjVrG3Zhttamm21CrihTaoP1x+s5z3yuDjroEJTlED33mc/U1MlTcBa9GrvuWM3adhtNnjheRRFqsNNfFAneIf+J3Y4h7MrssNNszWKH5JRf/Ypd0Vs1at3RmrnLTlp/4kSVLDy8Kp3CAmjj6VPVw2mFK+9l92T6xluyw7JZHlT+fMZpmj1rW02dMkV9eWES1NnAqQ6H9yyOyzaTKJiQn9vg49czzzxLf/rTaQwAL9CkyZOyAUAkO/AO2OAiwugu/B0SiFgtw8i9P/AEX+tFgVMpNXr0aO3OKZmdjn8BadPNNkNfoQ1pqy230bOf/VwddMCBOvigg3TwgfsD++kpO2/PhGIYk9gSaCki6MNK64wZkyfAixm0f8qu3Rx21ouiQGc2zgPW8OHDV72R+9u6OHPmzDzpdf0HHHCAZs+eLeOtBz09TcptIX+5eQiOssVEZ73119Mzn/X0XGbf5x6k7bfbNTtm/DT6l7TOOutqhx221wxO+wL9K9mVRQU1bdPNWAQfpGc/69ksIKZr0aJF8seh7rrrTu3+1N00ccKELI+KMhUTGNvADTfeoH6OgHff7am53SV51mdFYkfTlNSQFw3SlI030977PEfP2//56PeheVJ/ECcfu7G4GrfOOvCfqL322lsHIEtPTjzZPxCZPm2vPeXBxPJImGqReFCb699iyy3lif2PfvQjXXDhhexQbaxnYfsH4IMOOuhg7P8FuS7TeHLvgX7kyJHacccd8A8HMsl4nrZi8lIhnATfTfBh2203W95JnLTRZO21x97af78D9Xx8yUEHHqSDWITsvfceTLQ24E2rPHjNYlNjw0lTVXBiWLGYCZWaNn2anrvvs3mX/bXpppvQWunss8/RBRdcIE/Cxo5dN+tEROQwEww8ImIg1g0eVQL0V3QGe5Q3pQa6XUAe+Mx2ngRvs9W2OuB5B8p6tD36PozJbESgw5UaPQ3N3n629j/4AHaqn6st2E22PvnEzmyLVOR+cRz11Qbo/j777K2rr75Kf2Cnv59TQZ8cTJkyTVNZTFfYg3UL9rShwubb2HuZ2zRmzBjZhidPnpxxJQvqDTfciJ3wXeWyzWZDiYIN/ID5jEI//bGpqdMmK+elyPlbbrFNXiwMZTy1rnqSNQx/8UzG0IOev5923+MpGsammk9TvvSlLzGR3oyJ9lPYvV+OTPrVaPTwTkn+3tWcOXewINmdk7DxyKMEb50L+b0iIrc7IYMNOEXda6+nMbk+BF1G/w96vg488PnaZ59nagrvroGroj9opnp7e7TlVlto08021rBhQ9TEJmyttt02E/WK8XXK1Olym++843b5I4Aqkp665+7wPYC+OpC6DgYO0bOe9Rx81MYqGKd7enq03XbbY6/7Q3MQfmKvvGHiesey678b84zp06fznq38DiOQi09qDnr+AfLCwt+Ligj6pcwtnjhxQpbNeuuNy+kG7WywQJzJYuzg5x+sffZ+ujbacJLmzbub0+Vf67777sXPPxs/NA55VVleKaUcRkTm8fBH9XDUfzTGckJmApAZtwoeEaHEeCFg8tSN9ex9n6cDDzpQu+2+s8asM1J9zLd6e4Zq+5nbadtttkQfCrWxt1EjR2nTTbZk3NhQHq+lUIESWlemMOd62t5P04Es+jxuegF68MEH5c2i/B2m5SuU6D/3uUODBl3WK8Mg1H98NK2WgBXbsBozOGZhGiIiCznhSCJcPBQRKoqGAuEHODvXMsBLirJSUh13KMphbWRI/kdpEc4DAlRSfeVmRFaAgGfFAIwOqMCYK3gJKFKhFIVEnCp4woDhO0WS/9wGOe1/BMPOfxsK45osBCJMSy5hSklFIymixgVpAe1yhdZbb6xew07rc5+1j9YZPQpu1J6oEUUNJbnevjJy6E81hSuIptzeqmrLv+Tk05Jdd91VHQfvAaFIMIFbifM0uM1FKqgWrrzotKlT9KIXHopD3FOePEaErLiGiLqd6l6rJfB3xiJioP8DTjUw9uV4UaScZ9lX7nfTiv6g8yuIUs6vVBQBFFKgF+QrJVWRSEuKUJBORSFKyjqw+eab61WveqX23HNP+QvOEaFkGsB8C2id1sBlnNPGR8CFuiPgCxCFCt0kLiX4NFBuKeClfPWjo/1Zh4xK6Jh5RQS0oYLFrtPiirxwKBXQRIR6epvaYovN9OIXvUg77rADi5RegYZShCHX4QH2hS98gTbdeJqi0hp1Zz74Bgipn3Zjy+GdN+ySV6xlJvhEUFDEKpXYTsVLefIWEQwoCZxU5rKhiES5pIiQ2z2K3ad9nrFPPsn0JEwyTUUeMRqUkqAPICkiwCf5ch1l7kfzxkOEBmgEnXGlSvq8rPoJveCreIdK/liVooBPQAcoMQlpkwf44xWKzKD2A46SBscracqUSTqYHdq9WAA1mz2UscA6NOpef6MEIkIRQalEWKhITcCT74YwQORbKqHL1iX3N4RMaJtqMEEvUEDrD6qokn6rFPxJHXyBXcBAFFfFAjCRfvo+T9dLX/oSbbrJpplvigTLKkPkuBQRkkIRNRSFaZQnsm5HSinnleiz0yRcDRDUTdsY55o9HkdEu8QVchmFpEDH0Em/S8AnpUIRNb8URaa3nq3Hif2BLGwP5qR/fTbPGrS9gb4VqZbLWE64n/vc/TgF2E+2H3GZVyK/wcS5p6dXThdFI7fL9RVZXqEIg8CXlKoyXU1bEG/kfAQmqFQwtjZ7jEs5nVKPFA01WbjMZqPvNa95OYuAWeplo0PwLbFHOCslSmO7Qu4yM9WX8QZIc/0VvsL5FTJxSDEVKakoXF7YZYuCAdR3RCgKKeV29WLX9CwC83uboiIeEbnGNv1DNI/dO++8i17xilfJfrvZbKokrygK2plodrhoF/4GCaRIKpL1AtnRzwX6mYqkKgq4YE/0p2UckXJfpVTQ36nOE2Ug4akIP9v0R5s85XQqCkdUwsP9Ka6UUs6LCBXkJ8KUQoPx6l5/VQKpQxFhwXdSjx1GJMUASCF3Pr2pauAvwBXmB1RASGDERS/nZyjx19PAsSeUJJfD3FGcAUJVOI6KgkXRkDKSBGUUBcmEMsAL+kSnh7OIR4SsACbPKPLkC7xdQMNp0xFGmII6USoqk2c6GQU6IkkK/ipNnzRFB7IDOmnSxOy6Sj8hTNAYxNUskgxi50Q4wwySJqy/Pg55X/njSJaNHU1K8KbpifdwvEiFivyObkulRiPhQGezk7N/dlSwkek6YQTtGgDjuvBESiBgNhjcJwY6jBz3A6JXpFACIhwmRbiMexg6DzgEqLRVKkORpAInpZCChCkbzYb8kaJ9991XG7CDp4HLDi6lBH8KgXM8lyXuPAJFRM532pAG2lLHi7ouN4BBLSVBz0NBGRrgqPxOxAmJ8azkdqkgM8AbwNrhDhs2jJOF3bXXHnuwWzjU2m/OcBPkhRJltt56q7zD38CeIyrwKefX7UlyqEgq2CGs4Ov3T6kghlVifzwVQTJzVi6faLjtJcK5lYI/4yLChAOUUlEU5IQmTtxIL37xS/Puaw/1ZCIeEZSnT9wGA6h8O25+RUFbaXNCho1GoZKd38ptComiGQrqKLKNhlJKKrDRCp7eLVW+Qon8lAqJfEVCrODgmQDlq5Ljs2fPwic8V+uuu07mnbO6jzUk8HgTEaEESCEZGDCiDEUg/4G+cByMCnSzki+0j74zSZ2WimahVND37bYiSav0boAgKEbPosdtNnBGcjq+r7wJ1GBinVIit74b1GGICEWEnBcR8hURKqijKFLGJ8oZms0edIV7oC4pFGGelaxnqQhQziypv1L4L/GEH081aEMvk3uI5MtFiyJpOqdb/qjdjBkbK0Hf2ztUjcIT3TZ8SnlhveuuT5EXEyklRSSK21ZEOz0uFwNp2pHb7YVDlXFSKKAv0PnBYc0nlEPY2X8YKib1NFfNRg/t7VG7KpjItzVi5BDtuddTtNfT9tCoMaNF7Sp4X9MikZoPiQjXV0OFbSpflUBDX+TQcZehd5WKpMQ7FdhpT09zIL8uLwV5jkOJrbuvG8hQA1eE8yLztT8wz3HjxrErvY/22msvNehjcZk/gSJqese78PgkUGF/Bi8IHLq/FCWFQ0VqStFQpAKw9EtkLDWyrqGDklJITfo2RQEBCYUiktwnEZF1y3yLRmMVLiJWxZ3XbDY0jFM6cTlN8LA7IhQRD8P/JyPS/+/LR8RqYaIAg/kkepTsGhVikoFxk+pUhqmSkgIH31EacUHKk9wYAFJS0NGFlBmawlxwLZVWTRrc4eVAGxzPUeez6JCSIv8pX5QU1WanyQPeIUhyXv2gIO0XCms+Jc6uYtfV5RJtME6RKFPAtVQjlfkji7ykIgIWkcOIUIlzq6qWFKKKUL4oWxHJfAjlTCM0+OL9c9lyMFIRQZNXE1ermaxB1008MRKwAzKnWsyr5W6cFIoU9HE9ANNjskZGSAatulyuqnEw8oQ0UB/Icl+6DztQMsGPcA6coI2o44PxjnfoV1VBpMZZXypSVCCXddy4IBXgSWe9kmrWxlGXuJxVB/lpfkTyXVKmBfCm8nsaIkIV7XU8A/nCCCpCsuBv3tDAFzIJ5x7YVAR4cBVGWFVEVF8V5XJ5ahjAqBqUb59icHHD4LxV9EwAqsxHA/Ur87DMxBVB3YT1XakcoI8Az+2yXvBUtnn4RAR8TB1+DMDqNuemkqzczhyaJCn4c8x40LkNjkdYHtWqdAcXESZfhafVpFfTkejegyRQWc8ASy2QdZBXyxnJ5YgxILkZSpArkc5Nlkly3zlO3/lHKNzvgpe46CXlKHniSpYydgwAABAASURBVEB9k4NeVICZUpygyqBcIBRhGuO06qrgY4gIcIkJTQXYLgfaq0S5pNSxD5kHpNx1uypFhBIAq4H6KkkBrpAI5Qv2RRHwIaL6qmhrRaGKkNpAhiKCsL6rnFfHO88aVz2MbnC+46br2FZKfgfzddtdtjIJ7ZPASJym577IqUTv0RrsTIA/WlJTu3yliCRyec+SbqooiuehnSDz3akzIqCpMs5tMdR54KDPad4bMkEJrWVucD2G/8fedwBYVlRpf1/d97onJ9KQQZIgGQSJEhQBQTHuqhh217BGwPS7KgrqGnbd1VUxrjmh7hpXwYAJBRFEkJyHHIbMpA7v1v99dd/t915P9+QeGKaq77l16pxTp+qeOqfCvd0zqWq6kYSfIdXRhKURVBekB1XynOD5Auq5xyQEaZTuKIB72c4TriquWYOK+eqxgG1v+8laNpJs76wC8dKLV+Wil2ihlI+YB9gvXK8lbSVIKncZwiuesISTQeNd1SIth5Ri2y9IguxAYubbci1gK48IkeMbsDZ0ndeVSCaU7OSEBlGbdVJYqAYuiBY8iAouKthUFBbToDpQJSq8lHOUgE6bVTm2y3Ysii4AQDKB+1LKASp9alO4lEoYFSjz5YmqUB03C21UXKYYBtinXM9ltQuYSlBvQUJsqk8USX0KURwDNWXombwBkqJCJUkgQkltkEGIrwg9OoJpKpoeZRNoMlJRVwQDBUJ9RYBUmdKdJh89gmh+RnQllw1dpIyuBQswjYsGRG1VdyG6Qk3XmEUB5QlB4yqWLknat9oQxRNFdI2x7tF05SR171ymjwVkJTea55okoUv+qlZKUSiQz6okBGBQm6k998AAJXEVD4B7LTBZzwMlcUDpMJR6Lpej8rI1DJHhW5Q+XahSKRIFkpSceRWdCNoIQYoiAhj09ogBnSR5xZC83SKp//5VgE79tiTbeZ25r8ItF1N7pUuKW+lTp6Kg2jxAev1sFZ2kylCyAkNVz/KqLB7Fq65ovWITdPeq0RMqFfDGzGAZSzPJUKjaqjLhQVSCpHCpUJ8A8ZVHAcZM7qcaVWto22VMsUyETWQ7ehSTOWxm27oNpGwte0M+bpmgGJCDpXoU3SBWqholG4qA0I5dFYF0k7gqa6pHUJlkRYCTcGUkVS8AUHsaV/cJSiLDIDRdFd11mOg1j3S5qg9UOEmoIXVXjaPyCdc3FbFqB5IFCgBB7VO5arTbt2wipJt1JKQt57kAWorsZ926gNQsoLymI6VefUj9Wjq+qj6IqyuqLVX1mqo+wSwBtRkk9ObXb4y9FsYhQDItyUT5OyXoDXlU7JluXMpQJaYsStaI87oPLhtIgjSolnRYZ0y5bRDV71JisZIJtjmEI6VY60VUZV/KhZtOSZAdmySaiYlf6XQNiaVLLZmT8HzrtQBJMPlsoXm0EA6oqNGPKO3botjyEhMm22pc7Cr6AJhMTEtqTF2IkieDFHAEgtabiiaJGDXmHQgac4PIia5K+VoJC9jSKyE+tqgHoJtTBZMHsKKSBMlUqHnODa5LUnyzPbB2EKpAmF8NLORIUZDICsQ6j8LlWhYXBgFJeBNHKpdzwM5ECehCnYRTPJKV0yj3xFS1J32ahENoosF+9auhWpJLTlrxAE24ooZABK0khSa8IEu6r6VF4BRBZwna/TQuIumbehtNEKjYEZasFYls2yjruUwjXQEgqxw5rQEL9NqSrMtMdia78q7WyA5dzuQrgciqV4+x/aca7CJNZlKgMSYpxDJRskxgAtnBXS4KTaqiGa/Hn6SLqQ5J5RAQTioKF5YmVesXDoKsIJXou3mKN8VNVWKSUW9UrPrsmKBLqqtMz1YmgHXb/4NjQT5rpoAqK9Pl+pS+gIrmstoDAfp5RKdwACQTCFMeLFTlECo7KROS7iM3VRnBjVBxzlDoSaiiASCZoPDmRHyMJD2heIXsmnh6Dii+zU7PKx7p/lbPalrVDemD+6fn1fPXdEq3NILKSUKd8AUVpTImoMlS4pxUQVTSecVXsX2ZpjbgvIY2K2dtCzBZJ93YJrWzVJRJPQ8b0kC0eR4Yj1kye5sW6oLGpiJ53CHVBEk43gDqEsDJOUWhC20wbrBfRJAUtFnKSJcrcB+KIkivfFWbHYDoTYTE26QqNutyNJWuGyRDlwR1LrR9+RnbaJIjC1D1IN8decy2gHW7P85Ncl2SRmE8IbqRFU0owkiMA4ViiKTJI0CqrCu2YwQqMxTiE974lSWlWwIanFiWKNWp0rjkJCQT6UnNBtNPobqk69geACm6AGMksuJF6fTYei9gvBYlWaPKjRuEti8/W1B7LrouKb50qVEIM7kNEWQvpc3I2QpagOSIDYWhoP06jNQu5T8kEUIAgQ4Eone/hpFEMuEec7LCE6HnFlUyKMvXSlkgrKg0SQ1SB0bXIwkJKOydUWgFQnQRdfLgGyeJkYBElajeBDmDpl3pibAsU5lJh+NW84smG88pROJLj0ri2wEoVKDaiQwnlVUgqh9VAhhUQkoMwskKV26dSNwAoEBgAZETBNUzEpV7ro/6XEb/xZw2G6n1ALHVe3eUUC9ENS5MRVg3KSEAJAXoJNYoUclVhBonqzKUSKouheVrzVjAtjSM1kbZOSQwh6SzDnh4NbYQWShIJqgFSJXlv/YEoYkn71AxJryWq3OSCSWZ+CSTL0CJpO7VRTLxa9+oqDFlZMXTXTLqO4QxqM3EVuxYzouvaCJ54jWT7MgJBWkZSgIJp/w4gCjaG4QoHEpRk3oUT6iuKABIJgihUMEHCgKgmiHowIF0t4EUTSCBdFF9LRpNkBU9tONTRVASIyACSZBELQOorDZFAskuOtp4gDohUPvqs99Opr6r2yRFB+jxMppeAhDBZaDSB9VXPeiZoZyk+KKBIJX72coKJ91GCWhugHxERQSJQGXbvMYhXgUA6boVqKRyEBA5jWcByj5BTNtamcYxmVMoBS4qS1ddJi1vkiMxajQiPGwkwUSOEApRNcS6a5xdg7E9SklIgqJLQIgJBqge0fFFLJVIJpmKYTx0lStqdTePQqP4UTmUFwj0y6sAJ7djME5aFnBGclQfzOsAGUAyQV0fXck0kolS4ySTfCLq5pghCfONG9CTNB6yYPJzydG89sLtp0mmU2hEWb+yapR+CVlG9aAKpG4iRZUNQkFWNFL6rURE90FZusiK7/6QBE2VHEmQvWAWQKANJEESKbmOEOtR8x26+GRbpuYrH+siqp+xeJnWtkB0LjvJprqDJKDL8WgWPfeaBqAgtPZAMaCCxkf3dAXJkEx4fSMJkqlo/yCZyspEk+NpUO2bVVmkfK2wBcIKS66AICVjUNa5NLh2AI1Re9AkoZEinXfEKkw0GKrSqtzrtuxwsC634xzdyW0wUdlNblOqum1GKRNJ6QgtIapF0ZO85Uw0dOOSgWSSnPIRWcssD1x3eTKZv+YtYLt3w3JakCg1rjVAeGdxQ0rJ/RLWdUtEdhFWHfWiVoGWXsea3DC2/dV9MVTa7YMVBvUTPanqC6ncoPpmGw266XKxCyRnHSmjMIHa7RLoRaUv9UkysQZPCDXeIfbWW8XSiLou/RVN1hBNlgKpPgs6TVCoQdnI5bLBtnNeMcgOXlFW9W49NayqjvW1nu2mZ/d4enCFwiSDcGfe5AtNl0Y+5cu6WU0FMb31tuqOvDXWpVidFbobrFlrJO9uq1ZoWg2itQ+twuzOKauQ3l63GROQVSpJguwAQHWj6oOshCqJpqvC67u4EtMlQtRKacw05ZovYD0jgDWU3AnD2OqqeVTtj8W2Y7TpFWo9HSBrvC2kbGmKiPka0wIaea8IeqEk9hhDkEi6VbaXzCpf9ag4X2Ul621Fr4Sr/fBjBdpYtOU35EE0LF9yWRKeb0a0uCAY6Y89TtBbrua4mua63fMxot6Uxrap9ObRXk05L+oJTQWOvC2BUpAIEyDJYOlEkbpBxc5VMzqUjK0NC9R2786X1W6vnNcM0rSx6pjehuQ7Y8msPI0kyDEAotWwFB8gxe8CUVAlAumQiyq5rwKSVR0UoJZ3Mt2FExBOKodSii3jBsVVWgZMh8V0QyepDtWWAcITdLirjLGt0zngfhjQlYJwQxddcwQM4oxcqVzLODdUXHfXT1eBaVR1Q0XxXGLq+GBd3TC+ZOb0WoA9Yyrn7GWPWeJYVFcV6NIBwPcuIVVIm5jkzxrTlIviPIlJIOWrf7OvLA1qE2qvBrerLipLfY1ab6J5bZqlO1CufqeWo4EkSI4hZZrBLMWD5ooouegc1A9GIAozj1CKFUTThCKK2g2mrTZIp/VLbxR0q7P9u8s1HoWMQJTFU71KD6RrLKi5yGlcC8iSSJBsGpMla+HafvYeQ/LrWHOd1xLGVwbqet35ytR/HMuu4KN51VxB0eWLOehq6JbWfrrHOTTj6ZK7yFm65VYG1xy0TPGRfrgNwzKle5nd4ml+SO4s1xXDev3rGaSdzr9uYRCuh6w+cwm3uvqAoTp6WFHaHl+X20UxxrzcjmFMZiY+NiyQnMMh1B7z7l61x9fD3U2G6xh6iJoSRwl67A2jxFaw2G5cizRGoKaNp4JiGJTZ37v7mHzd9F6gZCropbvkvivCjWKslqk2mLgTeyMJkmuwkW5dfjJDt/pufoee7NE1xkZN60hkbGUsYNvZv+SCgEyuC07dZdNcNlBC7Boq29/zctKTCtALngqwjBSlJ+pAOlqkW495o8umrThQogZl6TIuiCoYHFHtF1eijHMlwXF4E0y2fer1z01pAKLsli49RhCQBC0n8Axa6JlcNgDEmk4e4rHGZCzaqrTd0V/VrvU61+xeEfM9WSCme/dN4y0fYYKKTgkx+ZB5FW28u21sqPnGDXU552vOAopVjQxGw5prYHmaPLAGJGehJm2BNjm+dyBqChHIi6pNuXAIIiRvkKTqCwMkadB8BJJCtdF3jipFqCyogthLjjHJddF8IEhFkaOqGSD9JFPPQmJCFXVY0NeHqHJ0UeAraBKEaLDDt6Hiqz3rNEC4Zhk/ewVSJyGRvI4Brg/TRsvlcmWvR9kOHpv2GGqU0phF+QgEGl6TEjCNY5C0QZkuiUBDLaz36n6umtOmSf94z1uKZzBfvh2dG9S8GooJXLaM+Ya67NzlujXl7lj0zTh1g2IspqdwaQQiupJ0SCK2oWYwQnUFelrHLdJnuzJJQW10nq3uq3P3ac0Dxkx+mgCmeG0LyF4wpKIeAJYRGDXU9PRwZSqlm3mGVADS82J0kp2kOwpqTscGo5/ZtqhhNG/9Lte2681t/A7Y/t3QkdVYgtWP5nOSgCAKMJJEixS5BiQc8hMaMH6qx7OWqMvj5/ahut91re7cPIpgUDbOtbR++479xPlYYN7KQXfTS7dX6apk3GdjdZ+rXCYFhRb6OuJDA2xLNkCtqgFOYqpEOnd5WWCZ5YHrW8banbtsMG7oxuuyaasD3Xao9ESZYzx7rY/0NPfL3PYYHS1ZAAAQAElEQVSHykK99zS1yma0L2j/RAGE+0oAwC5Sy6GdRmxJ+bsBGosaNAgjfOHug6GblnHZS7ZZlh0USRoZGVUmltmNK1vFi6QGktANtTN4UNFOprlsaJNGZaoLdv1AOEYShdUgFKRLxgzGDcYNbdyZwaQELhj8rAYTXXZuMC1qoxNdSOB+G3G/teQblblcJ4Ca7CCIwlCnWCMUYlDWc40I9FBzYd20QGc0xxprP9N4dPPWBHR6UGmry27XUJcrbnXvpWmeAErJ1s5eCekuWjvOhKk83mVuDQDJBFBiDV00kRKfNNeltQ8kUx/cMlnjVNGgTJfIkkECdMhCo6CLgCrV8lWpvlvOUJdzvroWIGXPGtJIqKzc7hulPM3VQlwWGRBumli6mEgUlhDlI7gR6aU2swBB0lkCghhJXegIbYWR0YLq3GjS6PIKiIyu8miXKXtRayNsS50QSKA+xMEpFIB5FAOUJHVHO7Gd15nLKwOuZ3mAZA+gK4klHhJgzERRKX4viLiMi8vgZdayLGDLGQDdHbz1YQHdqc3rJo2BO2RqWIo9LmMpyUzoskDowlcZJQmSaVJOE7M0EUx33bT5Fst8F7pBNJIglwdRMt0AlQknkgkn6WKCLtTdgTmk7wBJQZ0bryGIbgAQ9NYnuD2I5r5DNEFacaIQX/QtQZRjR098oJ6ViZZuRhPQHJAU2fUF1pVAJNPN6gJJiIFUh2TOH2M2QDupW6CXOo1/wgmVBc67IDmiJj+S0JUASqTLS4NY6SKX5pErSkNqR+LKl1cHAAFUwikLxvVscL/B6sc0Aakya3GCrEBIIq6I/1rGUNdxTlZ6yInPMZIoLLTBuFA9M9KzUxOAyrrUJXWRCVK/UeG6o+JJaIyLlETyjyA54xyRIjlCI7txiF5DNz3jKZbQlVjhfpmTgBodzd8QuOwBJCUkICm7ErolIKofKIkFsipX9yBq7yXNkkECECmRBNkLiaEb2UsnR5eD6kIQBc7Ndy6A8Bqocg2AqG2oaUvpFT/RnI8FBLnmISJZW7qDMAqcG4SmgZOEx0d4BFGmGDOvgqgsik4SZA1B+GioeePlHXmp7LmkVvp6SKlAjtYVAMWtIaqfBrQTWcm2i9JXlSl5SpaaP0agLUvWMut3DkKXR1l5sklQ2SAGupJ4aEM7U5ECHTRlY4C6CHIUoEqiYgS6ZUSFygZSEqsL61H9UJl2zd5jrY5CZEyXPUcQBFQ2kMKxZpNVGsbTStZtOu88uvtnGK+e6R2+61KP4Po0C74bRhAXDInbeyMJkr3EMUoWIZcvN0bVTFoLFvDQkB6fjh+MNGuyCyNOwzTmJEXtyJMuizTGRTLVGYM1ikSVOzpVGOey3DisUWRLGkbIPYURKkw2dCirjkXbyrDqKiag5vhPx+6np5o2KKsuFwiygorWeyfH5/VK5tKYFuj2lW58TGFvYkcJsRJ05ugxVBRjplaldHdVvRQCTO/wNYQwYIxEUjyOwRlNsnLLGYzXfJcNbq+mtXPpBswzAAnFYytVT+K+V33kqE76Eague1+ANi+6YCLWnUQSJJfusGk1LM3NlG4LVM5SUWxKQ1Vaxl1Ctu+YEoR/xmRl4mpZQBFNKegGFVfy8mJfQfU7UOl3w8oS1X/K0kLUe4QYW5q1jUeVBarQ+V0psXrKY/EtU8No/qqWrW90XdMIdUdQ8dRhE1WWYbRwxATmmSxvjxWk55GwONVd9ETryV2nGyTdw6/KbmzpuhUv01fKDjJlr7z/Q6dyDJtH+WgvyIdHyVV1PX69OiW2VDu9NNcxjK63smXrqGG8uuZ380aXzRuLZvposJyhmz663M1bNVzG07VqdddsPPjZanB/arzOa1o9R5humqEbH4tvmQxrdrxG29NjMBaMluuU5Xi6OuUqbq1D8e+A9/TuGV05tBWp+Ja3jPPVBeupoVuXfchgnul1btx0591gfg3d9Ecfl4F1uR91/2RJ2TP9vaDWUwhUbMtYzlDLGl8HAeqzQQ4zsT6vdta5Njy2Y/S7bS85gq4x+N3PCesYC+RJ3XIjuOJ5ZI03Xuvv1lHTViSv662I7ONDJkCBmkATIUZAhsAoaBtd5M6lcYHAB70EgaDAAqRwAspGAKOS2KJUdyHLuCwzGpYh3sVyra7iKNRcgqIaMIJVJSgZ09QszJexigLJVs9GkAJUgO5EFbpBxepiW7rOoXIvIKcJsYDcta3XY9lGuzIKr6GKABGWe9U1nLeFjfqNWbuIkRHGBKfUsNpwrixdxg2poJvxGlSsrzFIaPebygkn32twuRdqjvNeztIly4yAEIXR0kJrmUISZAATEPAY1uDJDk6ioxtME1hOGXp4tRxyWiMWkJK2SdsZNGRAKlBZBW3CSJlkRcI4SWwJw0DdahCK9OYbECqq10soUYDObOLSqoEVdUO3lpouWkLVnnP1BPWvZIhVXVQ2GkRay1d3D+qmTTPO1G8Cii3d4PmVKgqRJSmuAcqhxFGg4qNwrVIv6kqPQn/XhSapEa4h9Ze61yDUVwqzmlbnZtRgmvE6N96GmuS8hjaryhLRsSSoKPm+ghYIKygHkgnGko96C1MmKFHqy8JYMqTrh6SDNF4DRDPU5Uc7dx9rqPoS1F8Dg8o1iEaqnEHjt+7YIWi8AoEKOKrvQY7YAbIA2StT1ZPYKDrZK0dOVNlt1zBRbXTp1QOTXeWMyydCG7JdyMejDUaNr2PAoGcNbSAfzeeu++f80ezHqrbtfhva9YNww6Nq03Zfch80t61FW4xl76D2DWPxemj1Ojg6V/0eubosP2MNNc15d32XVxTqeisqv+7LBaxm0ocHDA23MDg4JBhMMDAwgAqq8uDgYCovWbIES8OgaIYB5WPxM21pm2WbrLpN7Gf2N4Pxji0H5J+9sHiUT1re9QzGO3VXvT9ZR7Zd9oHsA9kHsg9kH1hxH/D6uzrrsOsbrKMbVnQMuusaX9F667bcuAcGruBBQgc5BJ0GiyIoLwTOa7CWCuLIN6bRivNnodEWeQyVH8ddsd8Zuh+x8lWgymPKMUaKY9AyKVsgWyBbIFsgWyBb4LFrgWptR1rbjSOnlbBAWJbdbM4axtTZZjYaBZrNBvr6msq7oU+0/gT9/f0YG/pEbwqcjyeT6WPbLttl5e1iPxvb3/rko92wtO7uusaz/Ze2UbbJY9cmeWzy2GQfyD7wePABr79jr+MrPr61DuupYUVt013X+IrWW7flwpgHgdUgkgS5NKyGylw1WyBbYEwL5C8dY5olE7MFsgWyBR7vFlivn496+hqErvK1OjpWp+4qd/hRrbjGDwzjPQ3JMQ8SZKaT2QZktgG5MjaIiie0YWXqZVky24DMNiCzDchsAzLbgFzXbFCvfc5Xp++ub1gVHa5nWJW662adCTswdP+7w1g/U/p3hEc/uu0ympbL2QLZAtkC2QLZAtkC2QLZAtkCj1ULTNiBgeycoB4bDx/VjbINxoVO4OWDQQ11M3V5dF7zu3PLdJcz/viwgMe1BmDt+eOyred4cF+cL1tyaa7rrGrdpbU9dim5Z48vC6yO365O3ZWxYt2O48vg8srUt6zruG4NLpueIVtgHbaA3bgGPUZnTQVi+il1r8GCEuq+TDIkWh0bzhMh38axwIQdGMZp71Ekj3iH+tCNqzhBF1kdmuzMboJk+lekSMKJJEgazbCeWIBkGnOSj4MndhwZHgePkh8hW2CFLGB/N6yQ8GoKra12VrOb62L13OfHlQVIpnX1cfVQj8GHWeaBwRvdGpbdd5/MumFFJrpueeMrUmfZvViaa53WbRjNNc1gmdG8NVO27Ub/R3Yum06ypxHTDDWR7OXX9JyvCQt43LtheT5gfre88TXRD+uwrhrcjmmPBrjtuh/Ol9cHyxtquW68puU8W+CxbAH7eQ0r4r+WXRG56pm75/OK4rvrW4/BuN6IVpmZGbIFsgVWyQIOIseUwfgylCyHvYya6z1r3APD2JPd2PaKGgDLLwvGrjkudUIYY/WvakgPoA9YFb7m7iSXOvWSS9PcIjk23bwMa88CtY/0tkjUPt5L7y3VdZ33csYqjeVzpo0lOxaNYxFXgeY2DaOrVjQ/i6HDNb17Uh5d7khmLFvgsWmBymfTry4osCv/Nk2UkXJ3z82zz5tmvAaXx4ZK59i8DrWjR812yONglrFewzgiS5Eta1iKMYpg3aNIuZgtMOEWsG92Q91gN814TR8rN78bahlFs3Z1jrGKYh9P4KLJKsTY0trugokZlmeBYFONgAxYV0jbkVIcgzJZvmYlA6cBEsUsZcu9krz0d3K/WdGQJtpyq/cIdHTU9XtzaZa8J/g2XZ2P/n1xlijlIIaY2hW1FE1Ql52r8hq/rLfVaqH+wuCyccMabywrXCELeAzkBiOy9mX//4IJRqhGzHE+PlhXN9fl5UHlp9ZtqPy1onVrGg93hPq873w8maXpdZ9Gc2IdI44T4e5HjO5Tr2SUwUZAsjGB+98r11vKpWyBNWkB+5t9c1XB9dv9oXBB8mP5tv2+zemsc6J3fD4qOkqBJNv0Wr7ORa7RLh2qo3iKCaRDQjHBiGiS7ZSs39CRVWmEXdVV39sUqWpjncwynVKNdfSZX0HNy3m2wGPHApVvVj5e43WeYkF70ziydxNFQWB+6RhThBqvwfusCtfzSaVEoeoq6HL8myAUWs+gugnNt6Us4B1HRRwxWFXssdlo3oiILN/Gl5d5sHplOnWjB7hT7BXrKkX1w9BFGkG76cZrqAS8sNQNeMKsJ+/ReC1T1Vrdu510eHh4ZCEwPjQ0BNOtu+6jc5drcNlQl3M+kRbojLm8YRkNteXkg91CHidDN23FcLfW1tkbbKpe04Wuwau7n904uibJqleOD/fBUHXA8oaqpLsmWXT127yoOBYnX9kC64wFouI52m/t6gk3Mk739cKp8nlFiTYqlVT99VEcVZWKirzUXcyueOmwTe8qSUFsgzR2GCuAqVpaazr1O5VqmmU61FXEcrVsgdW0QO2Po9XUdO+RjJvvvBtMMygKR/y9jpVazvwaLFfjzksFgS6hdezVuUjpGl1OxHyTBToHBhV81Qa3kWvc9NUFcvw3oWTF8yDWbY6Vk5XcivdFA582NnInobVOlQDTtQBYI0FUqc6r0pq6118WiqJAs9lMah0QRkg6GwH30QWyl25ahom3gO1vmPiWqhZSnFXoo3xXgIy7oTGvPnQbH93VDm1t2m50L3I5W2ClLOAFp9vn05SriPQBYuQQbd82jNLs9aO77ij22iqmR1hbjeV2sgXWsgW8nhiWblbBupw9EkmQglGVRygK6xHd2gvGkZgfVeFxXlyZx1vqwLAylSvZqEGBgL4BqHMsI0XxJKd75/KGxNChjIWRVAtcikUuTZNgkktO0bMI1LJ6O2RUoEvi7leqsoxb3UfLGsYWJZn+RSS37cMBSfjAEELH5N04uhLp3nQRMrrWLRC1GTCkw+WYq7LH3jBW7SQCUAAAEABJREFU10w3VLxqOF2uwXSPscG4oRt3eXWhbqv215XQ59/JWkrc/bNOM+q8wqtSdTclQ7bAum2B0b5s3/cT1blxyxiMrypYn2F0feuNWo9G01es3KkZVUGgS0jXZUINXeSMZgs8KhawL9YNGze47NgIioPggqCmC/VltkESSICUKJyj1zCKZVDWuayvBlONO88wngUCZaMEycjQPYIVAQxMIIK2T9o6xQpcBivZqFNZFNe/SwZtyl2XookNlqygEkaUXiKC2oDR+xgB4SQNZUtIS5LCI5A+G0nWdQyqhCj9peSiK6uiJEVTNdVSMeFRuK9SffBGHSowARBUv3pgSHOByIaIhUQIp9QvyRjvBrdrSG0nvjou/dYyGixX0QCSCXxQIPXkem4o+YvD4OAgnJOVjMg9V2zL9hBzYQ1ZgEkPSY2P0eRJRiAKQrq7WMqnWoJhDanG3GOSJiKKqXLbB8oyIv2GgnjJNeUjERFyf4ik+pZtSUdLmkuBqotBCTC6tSCC/EMtJ/+tJETTFQWIqqtcmdEREMmXyY6XUp2IahtRfVacAMpdbleIyg2pjp4lycLPWHb0C6X6ASf1EepLTHnVRws6xqVKzxUUlgLJIKdsgbVqAcdgBVEBYEDyw4pmPMpvFRJAmx6TnPlQolzYOEES0IWUKDTIzSlwHuTjFR7LIJrwJKe4kQYxdVdUSXci+5ZwywmkW2EOdQUQDqWojugC9WOGcZEVT9YjvXXspryEq5FqG5RYBWWprqgd86wPimOwRCmCWPB8YBpVL7ZpUeuvZSg553BZGqVG93xlC6wtC0Qw+V4pn7e3QnlEWr8gmsA9iZGSc5ymkvBSECVblZHWthJB+1QxHEpiRK1eUQpbAstGlGqrhVI/ohMWRWBL7t+ChHQFuC3AMWZcZEjW2SioYm0UcT0qyjrtp+2xjwsCypaabCKESEwoDFHGjBqsqCGohxOwTAREi5rNYjSuYku5NlRQnbIcllMMCxNNF7VZarVKDVYJOxBVVzU0kAQrRHfxdLe+0m1q8J1bH0mQAvNLUdSm1KJUrlJ1pbYDmGSicgmqEOlHrwDJUSTgiRQRUXXcnjf0zsWB+wfxU576KTltyGBwv7rA8q7nAKgPC0uWLIEPCebVNJIuwnK1PFnREiPfJsYCmog6iqNQj6VyXQBRuY8K9gP5LNJ4V35TJhokE3Xga/uyxozUuEmkrhvlD56OJA7oJq5UR6Flqku1A/kg7Hvqj+sZJGQPTDLRBPk7EkX1vIEwDZAeSAbKo/JobaIKT32t8qg+6GkquvAqLkRp6yCNQ9qR6jPddZB2f/QsZpCiJpBcrKCShgoCPYMk1Ae6IMhXtsDEWsDua0Dy19rvqjzKd1OMylehRLZ9PJWDKQlSMfmuXhi19dBlqiym9VijY6DCUynVNUbohw4BCQtPl8pqzlXMUExA8am4jY5HYFjxW1pDakdrT+orknyUDBS7Xl8SKF598JfKpKfiE9YvFcor3PSY6pVqK2JI663jPOkgNEe1Un2oTWFqy/21BucG4xmyBdamBeR38veofSLskSkO4ohP2+/dG4JmC5RLzvuv6LhIOEDvxxTS0bpEI4mQylp5JUcQEJTCS/HVjCIlCjO/BYaqTWgNlojagRITSKXiRrJGRKkv0vy6tP7lMu+yHjrKiAKZuNtOlcnadFWnjaqNTdTgGMCAUs5Q6k2nxkI6dLVUq6Q0eSciUBE+GaqOUQpPA6sDBNQrmqj6qUaEBroikkE6NJC6mwdt2EtNxKYE6bATJWlN/KqGlvqhLupSfSl2scLMdS2AZAJIJ9qp4oiiZxM7UUNCXDsVdaPAl3U5R5eeDs22aDQaMNR/9Nzf358c0uWoNgzI6VG0QGe8qk50ja1QBt0kEj2zaLzg2Uf+ZD+hfN8wUo8BFI+6I4F9NsD+bXl5lS4pQ50ohEjuJaxzWUaxkgjCKcRCat+oKEjgm+j+FTfTpRxVrrvoqc+q6qtU3SiwjGMBkqQA7eRJNCruUpFAqcMOUiuJolsQiJFofpqIMtnCNLHylS0w4Raww0fNn46NCLl4gspPXY4jPTDPhei41SriODWu2qBitAoF+a6qmG4+VMn06BvaSSJQnLsNx0TFSkT43pZKWSqnm5QqThwxkFQUlNEaqL4L1H01JappEQl3vTYwBNVWT9X3CMno5vpV+6psrnjUczlmJQmHYilFlqtexqliuiKsNqHp5pJBhSjIV7bAWrRAHVtes+TZIy3H9IIOoNZQuT/soXJnpLjUXk+B40tgp6Xoii4iJUI/2vfBFVwZERQE60IQLr4kTYPXc8lQPLfvKmLpUp1OQeVlX+sb11ZMz+yJxoBkLAK6KkPagJqKNEPqMkkstkHFqLes5ZCQUrSgqUtvaDRobA8EAgDqkvKCDYTQ0BBqyCgAVCbowRNVRcDyQuLIRAi0VLc0iFlGNaXcdzuXJ8qEU5Wkw4cXWrYE6H4UQVRVCupX0VBbytODDIP6LBWEqyk5IJSSEoBRPKIoipRHy0QouXOUrOUCqH5EtRWFkQRZQYxQIkrtyK666ip885vfxJlnnolbb71V9Ooyz18wSCIkx63yqq2YdCGnCbQAx9XN2h/tBxobOZBdDBoUMBTK7VOF8CY8GdkHS090fuOhOkCAxzQAoCtT8tEqCAq3f6E9+YGUEJURsaR8BkqECACUqx7kUMJA9SvKp0yiCBVUyFJ+IyYpHpwIknBfUy+onslvjQMVzzqjotfPYnbQc0bJWK9lUCfpidDzqF5U/CQ+xTQoy1e2wERbgCR0qZmo0ChTbl+O0XgpnvlRufnOIZywTAVIISiuECiZJ06MwpFkTalKUIqKS72RVHykdh0gLEQPoH6SnG6puhcoxzba6wsl5jlAcoXWPuirut5vqd8AA6AwgzdDtAx9L6GeQMTEjIo1UoKAWo+qFyExlWo8tvES0PMHzREiSJt1EUURJE/xItj+gfIEjm8CrkLklC2wtiwgb7MTK4uKF3mofDCocfuw/dSgovgWS79GLo8WBZAYSfmzoO3HXtcMUADqQgiKTbMVD5RMQJHu3hsWWqOh+tEAxUhMWlUngAwqmFYRSaqspqw0Yb14m7ReZQG2iSE9tpEaZLRkXOUaLA+sXzzWtrMtvbkYbg1pnIaQJj0RrdAaQhEQ9FYdKkRtcujBE58sQE2c/uAwpE1WaYVqItpxNNBBPHfFk3/UzEoSDYFpZaQmTWNW6kotBHWKmvFCkiGqfgTYgSzfKqPqqJ4m6li6d4WfRkqGETSxUyVfgDGiVD9jqQ9YqtdqDYMkYEl9+ShNV7MkRaucJ6r/plu2VH/9T6e6TBIPPfQQLrjgAvz5z3/Gz372s4T715LqfykphAB/dUBXsj6Ssqka6qJndFUssIw6I+b1WBrGkNXYmkMGwH4rsF+7KFYaI4817EccloxjQZMeUy3EVktOUqKUH0X5U1TFYfuXPFIuBQQCMKAnlVLeki+Vckx3021E4216S3ot40rDw2Xy2VL8Um14QwK1Q1qv+u3JUv0GHBNEIZ7FKN+jcPub1KqfESQFDUEBUFcg7KPuiyG671GiaCfLCNqlnGULrBULVH4YQVbOF5MDI5VLzdGOj4pE0RwDVU5qxlfsRPkxCMWN4hMARadiJGj9cT3P4T5RBPm/1xMotqLWmaGhAQxrvQt+8cUmWlrEqrf4EU5S6UygsuRLvUgrh6s5gSKVLUcxwYLw3xM4Zk2xfmhO8DyhyqD0Aw2hBYJxFlB1uC/u00gdt6G5RRON5KIggKplvYOil8KpZ9NE5ccB9YMEAVAeSaTkzJAK+ZYtsBYskHxPTqeAS77tWJNPBtEpf7fbCgUkAiESUwxEOL4NLa2Pw/LxSqC6U5UM9vskr3jT22YEUOteBRDeUgxr2VTEBcBctecc4kEpunI7N94NJMVZfy9bbBlP76HUpKrZznYyaNQ8tyFtgDRo1JuUsjWIW265Hj8562f44te+jS99+av45te+issuvQSelBiIBQ/fjz+ffx5+fc4f8eBDizRYES29oQx664+oCbEkhoaGcdFf/oI//PF8PPTgg2pjCPPm3YgL/nIxHnhkgXQBpN9uokr6uoE0+CUuv/ZanP+n83DP7bdh3vXX45prbsCg9LW0gAzLAew7ZaQm+aj5tZSbRED1/RxWRhJ2wiWDAymPWlQM99xzFy6++GI88MCDclZL2mQh4VJtAkrJtnT4GVZfop5seGgQgwMDaquFnXfeGe94xztw0EEH4eGHH8Ydd9yBc889V881D0VRIKpvSUn7FkJItNH0Njtna9QCDn7DKKVyDZIgC232W1i44GFc9rdL8I2vfxlfk1///Oe/xEMPP4Qgv7b/UGMOHRhiuQSlYuKaK67Dn/90kWQehgZTVwmSqRGPa5Be+9k55/wKX/7yV/QF6tu46KKLsWRgiXSqSikv0gFVFVUntv1RnVLJPlM0iqTP/mffGxgcxNDwMEr5UkubCMBtBdx999340Y9+hK98VW18+1v41Tm/xoKFC6s2AJRqp6XwLtUW1adbb7kZ3/nON/DF//4Cvv3tM+GvY+52JVf6KdUl9aO6pKG6iOqnKuV7tsAEWaCt1jHURuXDZeWTIsgtda8uy9x44w34xje+gf+WP3//+/+rOfemNCcnf1acFtqMt4Yjzj//whSH3/r2N3DeeX/AooWLEP2jeBrWnF56nRCEwi0UuOnGG3HzvNswPNxS+5I0WSBMjRtpIfqwoHWxlTY1EYFEI2imUKwNqc2WdMcUUaXqtDTPDCOKNjw4jOuuvxrf/8H38LWvfwVf/+bXcMmll2JgcAhgqOJcQWtZKJXqH9RXVcbd99yBG+bdjAWLFmNQfWs5vgVSK8n6ohCD1zEqclX0pW47y5AtsLYsEEIhlw6KoVaKSzujffXO227Hj374I3z9a9/CT398NubfdS8sG9P+rdQ+cUjyjpsCfgH7u9/9TrHydXz3O9/WmnV5FSso9BjEsOLmgj+cj2997RtpT3rJxX+EmgW19xpQjFx+xRX43ve+g6997Ss488xv4+qrr5bulsIpjuRSlK+2BTxrVKgnjBoqiu41IYKSTEAkY1YTVkQRAhYvWYTf/vbX+OCHP4xPnHEGvqlJ+mP/+R/45KfOwJXXXo9SE+Vd99yJL3zmDJx66um48KK/psk2FIUGdwAtHfdC0dREeT3efeqp+Mi//Rtuu+02hKIPfzrvfHz845/FrbfeheRQAEh1BlA/hhFDidu1Cf/6t76hSfZ/cPcdt+HHP/gRzvzW99DSxr3ZaMKT87A29SiCniOoItTmsBx1SDCMlibxClqIaYL18wb1cRh//ON5cqavYf78+SjUXzULP3vp3RooHLp3wF8MSi0ESwYWY8MNN8R+++2H22+/HTfffDO23HJLBNnre9/7npz0e7jrrrvUdgukjAp1K0bdO3kq5NsEWcA2Nyyt3uMbPb5il5qkbtQG4aMy8iUAABAASURBVH/+97tpU/HFL34Rn/zkJ/GjH/2fDoAL4PH28CV/YMCt8+bh3z/47/j0Jz+bDr2U7xfNQkt6iQYLbRoamH/ffJx19tn49Kc/hy996cs48zvfgQ/KCxYslj+4P4T9RI4BgNpsVD4by4gHHnwQN900D48sWGBHQVOHB9NL+bBEMdzeTAxrMrzyyivwqU99Uv3+Mj772c/hAx/4V/zhD+dhYMkAVBlRz6ju6e1jxIJHHtHG6Tx8/nOfw5e/8lV85jOfxhlnfArXXnedYqSUvPqgu4ThdqqbJ2WkVHluQvMtW2BCLRBCAdJzr7xOcybJ1F6U7xsx/9575+PnP/+5fP9L+OY3v5F8+fOf/7xebN2i2FI8yvcfeuhB/OY3v8WXvvilFIfeNJx//vmKVSLop5S+Qa0hpQ4XLb0QevjhB/SV+Pd4v+Lo5z//lSUQCsWFmq/mjIioA0KUbCyHQLTQbAYsWrQA12gdvO++BxVzURueUjngrwzW29JhX8KaS/r0Mu0B/OQnP8FXvvIV9UlzjdbTz+nAc931N8BtVC8GVN8vBtRus39y0v+LX5yF//iPj2oN/CHuf+AhTJk8WW33VfOB5gaJojtFFQxww6iS9VdYvmcLTJwFKr8DSsVgqVhRJMi3vcYQD9x9L878xjfxae0dv6J16L8+/jH88uyf48H7H9I6FMCiQKPZQF9fXzos/PZ35+Kj//nRtF594QufxecFV159DYa1VrYUoRf88c/4zCc/g8995nP45Cc+hi984Qxcfc3ViIq5O9XW/37/B/jqV7+GL2oO+Pd///cUd957Vn1zn9Q7zTEuk5w4o6wjmgO0uQXiON2tDWTDSUaXRamcGhD//j9F8CZlwYJHsP1OO+Gdp75Lm47P4PTTT8MSTbY//Mn/YeHixaAm0qn9fTogLMHZv/o17pl/n6YqYqHe5gzqs63r/+pXv8LV+lIAOcUjjzwsB4kacnVRXyCCdzbqZb35H9Yk7raXDC7Bb377S+kdwjFHH4MtN98US/SGZcHCxVAX9XREUwtMocFWt/WoBYpGvzT57ymaCAwQSw4rEpvo75+SHNK0W2+9DZdccgm22247zJ49B/JvCUHyVBcLuE9FKBJeNPo0QfeDCJjUPwmTJ0/BYj33X//6V/z+97/HDjvsgL333jsdGk444YR0gDjnnHPgDSe6kidtA1nbvouZ0bViAVteS7/GexhkAW+Sd9ttd5zx6c/Am45nP/vZ+lL2G315ulRv/IYgp5IvNNAqm/j9b8/FBX/8A5rBfjAFZIB/9W5weAnsZIMDC3HWL3+B7/3gh3ju85+vt5//jf/6r4/j+c9/HqbPmI4BTWSe7AB5txyupU1LGUsVqf608Le/XYqvf/1ruPGGG2EXKeXknjz7mk2VmWBYOvzmZYMNNsTJp5yiyfQz+MiHPoLdd98Tv/zlOenAobAFQHWppazEvffeiQ0l/9GPfgxf1Wbl3ae+GwMDA/jWt76tN5fzEXQwKeXbpYK/1EYIqkuVIYhJWURO2QJrxwKVr3lDX9YxolzODNI+XeL+++/HZpvOxae14f7C5/8bJ73pJMXMDfCc68Nxqbj5v5/9FJ/73Oex+x57KK4/hzM+9Rmc+NKXYuqUKRgeUlzoZcGkSZMRNMf7APK/3/8uPvGpj+HPF+jr4UNLIBXakJc65EdYX5q3tU6FgileikYAWOJuvRj69re/jUsuvQL9fUGbnYAYIryWtbSOlYKgepogdJXYaqut8N73nKbNzRfx4Q99GPPvvRfn/elP6av1pL4+RD3rgL6E+/nvvWc+fnX2z/BZzU2/+MU56cWWlMB9a/kmU9G6ZZdEVFkX6qSZRdGru/rpen6GmpfzbIGJsQClNsD+6y9qLjW0vgxpvblQsXXF5Vfj1a9+DT77mTPw0hNfjD/+4Vx9+TsfUftAhoBC8QVGXHbZFfj2md/BXnvtjU/qJd6HPvR+rWN34+e//CXm3/cA5t95L77z7e9guydsh0/rBdgnP/1xTJrcp692X8ddegE8sGQI22tf9q//+q9pHX7ve9+Dyy+/HH9SrHkN9d6MpNqtIqY7NozXoIdZby7NaJosNGXUT2zTGKqysQjqR4csxFKTXCvCuEiqJVwnxEJapk+fhk033xxP2G4HbLf99th1t92wwUYb4r6HHsHiAb/Jb6FoAH39AVdfdy1uvlNfDEpixvTpcoCAeTfdhBuuvxGztWmZu9mmsH7EJRgeHNQkOwlFKODU0mTp9ktNsvI4PHDX7bjwwgvht/dP3u8ANNSZSZMmodmYrP6p55KfN28eLv3bJXqL+rDmxIgFDy+UY1yhxePXerN7gb5e3IQ777wDDz28QHWgplUP0JeBO3Ddddcnh5wxYwZuveVWTf734OqrrtYh4FxtGC/G4iWL8cgjC3HRhRfhnF//Wnov0+FlEIUe9sorr8S73vUu+FdDtthiC9x3330YGhrCk570JEzXc89TvxYtWiR7ysZyTJJqFQghgGTCH73b47zlccxrcpQXEPrRGMQ4iG23fQKOOupoHfq2w046FPvXy6Zp/K7R58sFCx8E2dDGAfKxK3DDdTdh7sYbavM9W4fVEkMyY5TvBk2IwCAeuP9uvW28Dk856BAcffQzpG8HPGHbbXQgnY1G0z4eYd8mq4mqlP/al8iAUDSQJlb5UNAmgAKor6UCotShIio+qfZcx38ns+OOO+HII56GXXbeBTvuuCPmzp2LJYuXpDczLb11jKobigCo0ibiPXn/p2D33ffANttsg/332xf77f9kXH7Fle1NiMTUJ0o4ok4UIlD77ocK+coWmHgLtB2QJLywD2mN8OaDRSHvRJpPN998Cxx08MGKr520KdgeTzngAOyo2L1eX8zuuvtu3K1N/AUX/Al77L47XvT3L8DOOz8R2223I+ZusimC9La0zlGxQT3NkF58zbvpRtxww3U49JCDcOihh2CyDhJioWCAG1UVBMl7I1N6bVL0g+oP+wEUSIcUHf4dt43A9EKB4lC4NyYKei1ng5g5axae/rSjsccee2OH7XfCLrvsitlzNsDD+gK4ROsoSRRFgb5mHxgK3HDtVbhUL6UOOWh/HPbUgyQ7W3TqSK+1Wh0rNO+QlO5S0a6Ib9sOI8kEQylp55DcCDMj2QITZoGi0UARgg7cwylm77rrTn3x+z2223YH7K+1aIedtsdRxxyFQoeDG2+YpwOz5Qiq3NIL6GuvvU5f8R/CEUc+TfGyK3bd9Yk47LBD4H9c5oYbbsblf7saaAXF/lOwy5OeiCfv9xTst+8+mH/vPbjhtjuw6aYb4bhjj8Fuehm4ww47aq54IrxuPvzww+pTKz2311KSCR/rRo7PG0t+Xadptms/Qvu5vfb75ORpQ9OLmNUkYruUYg4PtzS40KAFBBF1pQnGbzTv01eD66+7AVdfdQV++YufWQWeobf+U/S23bKzZs/E7nvsgrmbb4y/XnI55j/wMJpyGk/IV11zJbbcaisceshTMXXyNB0S+gE5UyioubQFQuq0IWqKVghv6o2+277l5hvR0ES91ZZbp0l8aHggyTf7mnI04prrb8XH9ZbpY2d8Arfefhv8ifnXv/gVPvSBD+Dd73ovPvaf/4b/+vh/6O3xGbjkr5dIl7UTDz30EO6443ZsvPEmcqxN02b/C1/4ot7Wfg6f+tRncfpp78O//Ms78YMf/EAHj1/h4x//ON76lrfitNPfA/8qyKDeAPkt18KFC/Hb3/4Wn/jEJ3DmmWdK5x2YOnUqnvjEJ8KOeZ0WMNJPp+eTfW17sirrMfM1wRaI0p9AthcKm96+Cg1B1GY9yLunTp2iMZusScQTFrBEb0IWaVxnzJyKZlOC2hzc/8BC/O/3z9JCPlk+fCBiOZgOk16GWyzQkN+i9TDunX87HpRvbbjRZrj/oYdx9bXXyy/vxCP6GjWsTXxTC3yzobBUf6gO+YAwqK9ot912M66/7hrco83Offfdi+uvvwE3CO6Zf68OqANyHgn70sMU2lCY0NAB4xFtNG7Q14iLLroI83RAPfzww7HNNtvCz+m4aSmeS8VVf38fpk2ZrJArEm+hvtItXLQEM2fMQl9fP2q/DAygfnxBN9MNEvAFp1Q2kuGxY4HHU08o71ZskkS/Xg716a07KaL8saVN+ZAOEP6VHH8xK32QViwNLFmCBx+4Px3MJ03qx03zbsKG2ojvqgPDggULcO211+D2O25WjA+CitVms5A/lyoPodFsYI8999D8/jY857nP1VvKSViiF0X286IgPE8MawMT1ZZ/Ddbte52ZP/9O3HDDNdrA3IKFCxbhlltux3V6KXbr7bdjoeqXeoaWYl5PIx2t9Cu0IVBzStCcMA9XXHWZviycl76UPPnJT8ZUxeew6rh/LX1FHB5crPV0V7z+pDfhmOOOxaxZMzCkfgxJBqSuiKjc7Qy3htAaVjnKEQztTBQ13yaIJnFQeb6yBSbKAgpHGCC3CyGgUQTI7eEXq9ddcwP22H0vzJ41RzIlps2Yjq223kIH7oWYf9/DoNbSMrawaNHC9BVx1qzZ2HqrrdHQmtk/qYn99ttHL2WH9TXxVvzuN3/ELK1f2+sFtv+5cOgYvdVWW2LO7A1wmw4MCIW+8lHr4k36WvE3fcX4IzbffDMdIHbDJM0rg5pHYuooUiKpPkXtL7WqC0/E9ewWep7XM4WhTSTMDhpXjSwAamAb2tD4hBc1aKUmJygFBgzrredFfzofHzj9ffjnN7wR3/3emcn4e+22Myb1+w1sCx6AzbaYi1122Rl/vfivmHfLnWkA5msDdL7qTp8+A3vpzUqj0QTtQZqAqf401aZf2gwOlmlyG1JbpTY5EO9OnUon623PRpr8ScoBSiwZWAToE+tNN9+Nb337TAwsGcQLnv88bfw3wZ/+8Cf89Mc/00n0SH3G+jTe+IY36HBwP/y2acngkLZ+lENEbfqvwq9//Rvss8/e2GijjZIT+m8OfvjDH2qzvxP+7d/+TW+ldsa73/1u/O53v8drX/s6vPNd/4LJOhydddZZePDBB/CUpzxFn7o/D//e+wc/+EG86EUvwly9yQ0KEn9hWKJFzEFSOyVJmFd6wkdOE22ByqvR8W9hqU35lRxTjKgsaqEdBkkt5JN1cLwHfzj3DxgYWIxdd9sFUyZPT39I/Ltzz8N99y/E/gcehC233EzjWKKvv6n6gPcEpSae4YGFePC+ezA0MIwL/nwx3vHO9+IVL/8HvFM+dNFFf5FgK7U1oANJqfiyLwRNkDfPm4f3v//9+Id/eAU+9KEP4eyzz8YHP/RBvOafXyvf+hL8awmNRgOl4qUl33G9QoeF++6/H1/5ylfwmtf8M770pS/h2GOPxaF6C9mvfrljw9p0+HnJAG96SCK6n+rwJZdepk+752CfJ++rON5UdEi/7OEKI1BZkKAoniuqsgr5yhaYQAvI3+Srwzoc2DFJ6ktDS2/RhxGKAqRdqY+nAAAQAElEQVT8WbHgedRrxWJ9xfW/VHetDuc777wzZsyYibvuukfRTvzut7/H6153kmLrH/Ge97wHf/nLXxTbSxSzrfQ1DtIVSEydOhMbbLA5mlqbPG83+xogFS96ympNDBjQOlNqXWo0++CXZ1/9smLv1a/B297+dvz8F2fjc5/7DP7xH1+n2P0orrziKjSku6H+Ol4NheoR1KHiWvy71pdX/tOrcPZZP8PBBx+EPfQW1Jt/R5ia1dzSj0IxPkmHiA023hx9fZNliggfVKL6oG5hUPFdaj4oiqBNWRNB646fhegkeo03QXFv3chpnbDAutxJ+6/cXPGnp3AhECWH4UN4Uy+nJvuFcX8/qD1cEK9/aj8e1Ft/v/wKKLUXG0JLe0+/uPN6x6C1R+sl9eWhUWgvumQIg4uHENhA/6QpKNNhebEaC3CMlYqPRQuXQKsz7r5nvvZwp+Lkk0/SS4Nr8ZKXnJgODF4HG1pTSfVNMUQ6SACSKY6gRFY0oevNFQBdXY9L4QZlI5fmEiASGjuEAoAGBu0JOcqY0CD29zXxxF2eiBNffiLe+uZT0gR899334Fvf/UH6VxssX+gUOG3GDH362QmFjH3fPfemv284T5+Gy5LYY4+90Gz2YYkGs/od0qiJu9SAa8OGiH7VV5bqDusNfktO01LnZmoBmDFtugYTKDSJ9ukN0ryb5+G7avueu+7Gy170Yhzz1KepCy387P/+L51In33C83Ua3Q/77ncIjjzyCL113UaHnhZsjbIscY8cKcgRDzzwQEyfPk39amLa9CnYV5+0nqrPXnvvsxeerM3Upptuhm233VYHi31w1NOfLmfbXYvRXVi8eAlmzpypw9Eu2HPPPdPfL3ixmqSTa6FFYpNNNlGALNHbp1th5+wGt4uc1qoFSKo9QVSmy0UWQT5FhNDQJBXhP37+5jfP1OHyAvzd3z0fO26/A2I5gCuvuhS///25OOCAfbHP/rtjUF8EvJnp65uEluKEpPQUkKvivnvvw7ybb8bUadPw0pe8BG99y8nYdJO5OOtnZ+ktx2VoapLq7+tDEdw24FjbZJNN8dKXvhxvf/s78Pd//3dq5yk6aLwcbz7l5PRJdfacObDPNuRX3rzUvjRt2hQ8XT558slvwt/9/Qu1GbpQX8g+g5tvuQVBzxbURlGE1FYITYiIRxYsxO/PPTf98eQee+yBY555tDZYM6A5VhD1PDJQVN8AUG9sPEkHuhyQU7bA2rCA40jOqqaomCIYCjS0kScLUNDs60PQOsDQSL8u+qtzzsFZZ52NZz7zOByiL9jNZlMxOpB+lXWq5vTXv/61eNvb3o5NNtlYm/rP4YorrtQyE7XZ6AdJtQO108Jwa0AQURQFot9gJSkkGdPch6JogvqZOWs2jnrGM3HKm9+GV73q1ekLxbOf/Sy8/W0n4cUveiH8dwokEQQtHdCHhobhNY16uM21przkJS/Fv7zjX9IadbZeQJ1//nnpC4TbHdCbT0hOVUVrAeUwSgWoli0UoUBhBkRW/1qCyACqzyEopxi+FMZexiF+KtZ0FzJkC0ygBeS60LIIkoqnFpYMLAFKYpJetg7oZbC/bsfklwFRgkNDg+jvn4T+5mT1ivAaOaj936BerBWK81KOT2ouUJ0IKhaGJdvEFB2mS9EQgKCXzhDeaPZLIqCl+l67Nt5gQ7zyla/ESSednGLyu9/9Tvpn8Ft6GeF4sW4okVRf1Ct3XuXYzoWuV5dNqQdWJmNiBESSWZEg6K6BA1C2ogbDQ1CCRUDQ5ERxS01Wtt/cTefi4EMO0sR8PE547ouw6eZb4i8XX6ZT3L0IOi1GDT5RYMsttsSeuz0Jf/z9r3GV3vpcf+M8bDx3M+y4406I0kWoPR1QwElqI+hNzyJAh4P+BhGHS6EliqIJkpr4BzFZzjRt8mQQQCiK9Fn2ggvOxV8vvRh//4IXpt9b69dG3W+a7rrjdr0x3VyfvGanpw0hYMMNN9JXhI0xaVKfNECfxuZrI38b/GtDszTxW6ZMCwSww47b6U3TBoh64E01sR988MHwJ6+iaKBQn6ZNnQZEJj31zc7nt7nOrYskGtoYFuprLVPnZFXX+mtaztewBSoTJ6Ux3ce6WYjypwa8oF9++WV6m//59MfqLznxxTjyaUdoQ9Gng+Wd8D9B6oV/11131uF4AQY1gZXyj7vuvlsHjSG9SQSC3nY0+vyrTTMxQ1/SDjxgXxx/zJF4znNOwPHPehYe1Bepa669BkUREAJBEk5RMTNr1kxtdA7FsyS33377J/896OADFWfHYs8998R0HT7UQKoTgusrZlV9ypQpiX/cccelrwu77LILLrrwQtx0w/UQG0VAags0UuCBB+7Hj3/8v/jhD76PA/Y/AK959auw6aabAyQsAkWMHgsAYRwoq5wuC81XtsBasABJkNQc2pRHygu1ZoSiEM60Hjhe7af+evvd734Xv/3t7/D0o47Ci178Ymyor8XmhVBoQzEFe+25B5553DNwwgnP1oujI1Pvr7r66rSJaTQbsBxZaN2DQqxAo+iDmkYZh5OsQhVMGEAVgg8u0j11ynQdEvZVjB6Pw484HFtvvTWevN9eOP74Y3DIwQdgY605VKy2hloY1CYpaD0IKkNpww03xkF6UfWsZx2HZx59LKZo7frDub/HDTfciKbWmT69VHObfo5C7SH1oNCaRPSpTAZ4TfYLhCBcy3Y66KeVW5Wi5hQYFL+U1VyfCACs1YCcsgUmzAL2sOR3WnyLRgOFfBryv0azKY8E9D5KbYupO+SToSgwZ85szJo5DfbnwAJ9+hLRr68QQzo8F/LxJK2Kjv2NN9pYa+JUxdUgVB1NvUAGCWnG4GCJSf1TsMmGG6KhOJ0zewaOOOIIra3PxlFHPQPDwy2cf/752gPerSpMUMelFKz3V0jzRbJ2ZQuyMpLuIlAQZDQBNMSabEqdvKBcDIQiAAziBITQ0CTV0gZpAB6Yydqs9PVNwiMPL0iDEENM/wLM4sWDmDllKg55yj649aZr8L3v/Q9uv/NebLf9Tpg2baresgxBL0ySPr9dHdDb2qC6TR0W7E1NtdnXaMAbbqjlSOKhhx7GAv8/DVH9LQqEZgObbbmF3uJO1mLx2/RWVxwM6y2O+75owaL0+djP7kd5WHUffvgh+MQZRbj+uuvT294999xLh4jJcArBGko0pdsbfz9jf38fpk+fjn4dWKCkqnLIljaYNmjbXto8khRN73ok4H6Xog3rc/EGG2yA2bNny26l2mYCty9VCXeeYWIs4BGKdoAEVRsapoR4DKIOiKUWco04vIE4+2c/xRO2fQL+8Z/+SV+SnpbGvdQ4Xn3ldfjz+RfhF2efhXe+81149Stfi+9+73/xi1+eg498+CO4+OK/auw1vtIc+qZhk7lbY2NtWjaZPVM+7rgJOqxuIH8usGDBI6Dk0O5IS4dk/8sRZWsI9tuoPkUt9FHtDiwekN/4KYAg+YJB1UKS8+83U3qoiVUEyZWYrE3Hvvvsndrxv/jSkm44oNrP/9ADD+B/FIt/0mTpg8nznnsCtt1qKxQFUUo/DAgKySDN1SV3RlVd/WCUiFuteI+re36Yx6QFSCq2WlpzhhQe9j+k3J2944478D//8z/pa+8zn/lMbdyfiQ21STCvKArMmjUbT3iCX/7MQZ3mzNkAczQfL1y4AN6ImC63lk5q7ZB+aEPT8pIZFUfmCqIgBUGUnHDHYWgAFCheIhz7lg9YsPARlcRSmCisUiwVRZ/WlCaKRhNUv4Y051SKSkB658yeg5123BGLFy7UOvcgihDgv00Kyou00YLWyxaC6hd6YRW1BkYdoEiA+lER2keldn1wgBITxNQ7qA1YTiXnyClbYIItkHwzECQRQoGGfJcMKZ89ZyYWLH4Eg/qqAPmkf/X31jvuxOTJ/frSPQmEkm5+GeY95uLFi+B9G1BgYKjEvHm3oQgBG204HbM3mC5dCxR3CxBCvypOxh133YuHH34Ec7UGF4XXX4oeE2y99Vbwb4EsWLBAsfaQaFCfGtJPhWRMOdnBY4xJZn26hd6HtQHKERI1YAZoMACCkg6a6TxAreFqkkYotCEBlixZgsWLFkqqhYUy+LwbrsO1elMzbeoUba6mqXpA0ehDqdkrkNhs7obYbNONtLH6JTbYaC72339/NHUQiJrVihCwZGBQg9TA9Bkz9VYl6BOS3o+oa0UjoK9ZwF8s2Cgwc9YGWKBDyQPzH5B81NeFFob19me/A56Cl7zk73HNNVfii//9Zdx8y62YOW2m2twMf/nLRbhp3o3wP+l633334cI//1VfFG5XH4nF2ojdeedd6SvCrrs+SY46CaUmYIP/BgOaYJs6NJTatEVt3kxbvHhxapsMki0ToJ1IJqzQYmBwPcPtt9+OAX1Smzt3LoKeNwnpFmNMuoTma0ItYF83VI0QFEKNrjJdZAC1mD/80AP4wx/+gHvunY9jn3k8ttl6G9jX7eODA8PYeqvt8I63vxMnvekNOPbYp+FpRx2JuVtuhRnafBx4wIGYLf8966dn4ZOf/iweeSRi8vRZ8D9H/JeLLsK9996LBx98EBf/5WIdqqVrm23UcvtSd4JBt6hVf5F8bNGSQey222546Utfhm222Tr94degPq3K4TCkeBmUP0X5ZQiFJs55+PnPz0ptLFq0CPPnz8dPfvJj+fdCbLjRhvKxFs7+6U/xuU+fgWuuugKXXHIJLrn0bzjwoENw4IEHo1BsLdDGaVB1ocNFdLfUF5kFVL+oPiGBODFq8wOIjJyyBSbaAp4ju9sgqRCo5t0+/zqS5tNLL70Uv/nNb9JXA68tll+oTbeh0Fy89Tbb6IvaA7jwwj+nzYE3CZdddiVuve12xfRWuObqa/Gv7/+g1oq/Src3/P0gm1qjJsExNjg0IJWaqxG9JIjHtFGJWiv8Tq1VFponvBYO6KXQRnjBi16IPfbeE4u0Ng4olksJlXqbqXBVvQYohAou/weh55/3B9x15z1YuGCJDjx34M8X/AkbzJmF7bbdFpcoTj9zxqfSf/7ZKqm+ANA8pRDFIwsWw8/X0ouFhmwStT4NC28pPqPKkF1IAr70Eq5C/QzSI2IUHetByo/46FpA7ii/jRhWDLSGS3leAZLYYvMtsP9B++OX5/wcl11xORyTf77wItx9z32Ys+EceK37whc+j2984+sYHBjCzjvtpNgcxo+1rt1553w8+MAivYD+MQoGbL3t5jjs8ANxx/w78Ltzz8V99z+Iu+ffg0suvRytVom5G2+kL+3zUhw55hYsWIhrrrkGv/zlL9KXx410oLCVSKqNUnVaLq73EGoLVHOFJj9PgAlMMYyIaJNOBG0khMCTkW4AAhra6E+dOhU3axN+xsc+hveedipOP+29GtRBnPjiF2LOrBnSWKBo9qHhzbYmshn6mnDYUw/BrFmzsI3e3G608VzIa9LgBA14vz45iZDkG0UANBFDKepAYTxKaRAoEQAAEABJREFUhyfCJ+7ypLRZuuXGm9HSBBz0lkVimtiJpx60H/7pFS/DZX/7Gz7+8f9S/25J/8rFlCn96Xe5Tz31VJxxxmdx330PYc7sDdDf10wbqzvvuhtPetKuOtHOQEtOHeXhJNU9apO2GKUm4RACDEVRwM9PMsmG0EBDJ+ZS/SXprshMcQRKLQzD+rrgf/pr8uTJ8K89WY/bMI/s1EmV820CLWB/L6XfuUGorqgxconUZDE8iIcfegiXXHIZPvax/8CHPvRhnHb6+3Ha+96Hr33jqzqwzsHxJ7wAr3vtP+OUN70ebxAc/vSn44CDD8YrXnYidtruCbj2qmvxs5/+Evfc9wA23mQzfaF4etqkn/oexcnp78Mf//hHHLD/U7DP3nsrTgCq8ZYO5EP63NrQZ9q77rxdG/tP4PRT34n//M+P4fvf/z4++h//gdNOex9+9KOfaDK8DwzEkN7K+D92CkUDAzpInH/+eXj/+0+H/0+F9773vbjoogvxvOc9D3vvvY9iZkDP9Fecowny1ltuxj333J1+5eGcX/8WH/jgh/AePeO733s6Pqb4uOTyq6V7CIVcU81AmTpJ5QUAxabuKiB13niGbIG1ZIGm4sPgudPzqudSv8C58847MW/ePG0gvofTTz89wUc+8hHN92ekv0XaZqut9dXhOPg/1HzXu94l/mnpVxGOevpR2GfffVI8/PjHPxb/FkTN5Q2tW0NDLW3Il8BzfgglPGcHErr0tKU2QENoSZYsdFC/Dz/4wffxPsXfR//z39Om5guf/yxOe//78NWvfR3+V85cn9QcozXNm5gQ+vCIDhRf+tKX8f73vRcf+MB78T7lRQg4/LDDsfHGG+M2HWh+fc6vcfnfLlN7LVCxHqgY1G5/+rTpWk9no9B6rN6BhPoIqEtwgRTBk4u/N2hNEweiwElTjrMM2QJrzQKOnWGddBcvXoJSTuq/xTviaYdjg403wOc//wWc+u734rvf+T4OPvhQ7LffvjqAL9RaeS7+9Kc/Cx9QnO6FZz/7OG36f6d4eR8+8P5/w5xZG+HYY47B3E02wc677oynH/00XPiXv+DU007Du9/7Hn1dWIjnnPAczN10Y9ynl4BnnHEG3vWud+I9Wos9P2ypl33+u78NNtgAJOH9nw1C1pGCRMd6mjTTtJ9cM0bHJKa5FNKE44ktgXYEFJhbaFNMNqB9uzbafdhzz73xvOc+D7vvuhtmydi7aMN9wgkn4KAD99EGOuiEuAmOeNozVD4Q/urQP2kSDnzKgXjjm96AvffZEwiEVe+112445pinY6uttkCMQ9h++x1wwgnPwqb6IgE5VWtwGJ7AgZAm58022xZbb7213gzdgjtvuw3Tps/G4YcficMOPRSTJvXh0EMPwsu1cXuC3s4Umlz32W8/vEyHiN332BVz5szBtttug52f+CRsuummmKLPXn+77BJNyrfAn4G98QeIoL7NmjUTxx9/PA455JB0Ai3LYfj/VjjssMOw3XbbSSagT2+3DjrowPT7cLNnz4JtRrp+ACnLaZImqbdGd6WDievbMaFkWWXp6sYTId8mzAIakjROVQMKAjkhVYg+NGiM/Uf6RxxxJJ79rGdj7txNMWv2LEydNk0HhdmYOXMWvGBHybV0sGjFFgr52F777gv/29ChCDq4Fjjy8MPw0hNfiik6JM+YMRtPPfQQPOPpR2BbfSXYSG86Dj/sqTj6GUfpM6rf/Ef5SgRAkPYZoJDOGfpSYfA/F+lf3Zs9ezbsO9N0UC+KIsmGEJIfRgXlZptthsOPOALbbLMNZs6YnuLJ/zncC1/4Qm08Nkpyh+u5TnzZy7DdDtvD/3nVcxS/22+3ow7KMzFHMTxTPj9tylT0abMks8B7DaJOVJshQUVRX1lh+Z4tMJEWIOVrCtxSMUoy+TJZ5VByPOyzzz54xStekf7eZ8aMGfALLb+gcdx4np6mGD7m6KO1tpwgmc3k8zNw8EEH4znPea7iag523HEHvPGNb8Cuu+2aNg2l3kqS1BfnyTj2mcfCf0PUaAZt2oe0eVkCf2lW01BAKFSoNa+pL+sz9HVhDmbMnImZ02dglnKvIzPSr7H2a/1qwf+6IKk4Uoz7eaZJ7iD1Y+utt8YcxfguOz8JJ574Mjz5yft5+cNOO+2Il7385djvKQegobiXGTCsFwv+daujjz4GBx1wgNqaDi+mQetWowg66FOrJQSaVzQ3QHarQGXklC2wdi1ANRcM8s8g/6RyFdM6vM22W+PEl75Ye8K9FDsbaL91KI45+lhsutlc9PcX+LsXvgAnPPu5aDb7MENr4rOOfxae+9znYivFy9bbbIuXvewf4C+KTb3YbvYVePYJx+OZxx2HLTbfSnvJnXDccSfg4IMPweRJ/Zi76SaKl6eItzm8F9xrr73whje8AZ47ogKr+7DgOcU0Q91XkkbXKwjVLiAiajfQO310G0MTtMySjCUjeYIDGyj1ibYsNSE1J2NHTWz/cOI/4u1veSveespb8caT34IjjzgU1E/U2485G2+Ggw89AgfsuxdmaeNU6nPq7A3n4llHPwO7bLd1mswkhj322gVPO+ogbKSNFKT/iU/cHccc9wydOuekroYQAPXBOkOYjP5J0/B0TfwLFj2IL33pC7j77nvx5H0PwGF6w9vQJDypvw/HHHs0Xv2qV8K/YtTU14W9Dz4Qr/rnf8Zb3/pWLRDPwYMPPiiVxOTJU3DJJZco75cDbplozWahubXU4WMSjjzySDnbwWkhKHV42WKLLXHQQQdh2223hR1qkg5Be++9F4444jDMmlUdGGwzknAiCf8q0ne+852kez8dXkw3kER6Nmiqj70jIVK+1qAFbF7CPwGBRQKoLMvDQPkYg/hFgWZ/P/Z58v54/RveiNe//o144xtej//39rfKx0/Gc094LmbNnI2or1Ca7eSfEaEosO++e+JI+YB/xa7QuO67z+54wfOOxwz5/XAsdeCciiOPPAonvelkvPnNb9YB83hsvtmmalpxqENHWZYoioC+/smI8rONNpmLE1/+j3jrO96Jk9/8Vh2yT8Jb3vJmnHLKSTjqqKdhdtvX+tXXEIq0eZk8eSoOOvAQvPa1b8A73vEvOPnkU3Tgfbb8craeEdI9CfvufyCOPf652HrbHbHjTjvjH17xj9J5Ck456Y1468lvwjve+ha85p9egV2fuEN1aHDNqJtBWTKZng8Cx65zkspobgX5ni0wQRZwnHhR9xzrrwwGf2Vwvscee+DVr361/P7kNM//v//3/xL+Mh2Qt9pqqzSnNxSrRxx+hHz+zUnm+c9/AWZpkw657/Y6RL/w71+I7bZ/gmI6JPmgecGH9cMPO0Kbin0R5OtQLOgCSR0SGiluo2LcB4NnPOMZOEVxd8qbTsEbX/dGnKx4f8vJb8bz9JVv6623VP0A1y8lP6Sv4/5CuMEGG+HFJ/4D3nTy2/DGk96ieeck7LnX3ileoYnrCU94Ao555jOxh2iuXGp+0FkGM2bN0VvY/bDfXntg9rQpCCIa+vQsWsE0N+lrhOYW66iGQwyGVBSGBHqQqDYqfr5nC0yQBeRscrWRmPK+iWQ6mDeKJnbWXvJVr3wl3vb2N+PFL/k7bL7FpuIN69A/HU8/6hgcpq9tU/Qiy7E+ZcoUPEfrsOPMa/Mee+6KRrOJ5NAAHIfPOv44vPmkN+Gk170BTz3kUDS0L2wNl+mg8KrX/LPW4Lek+H/d614Px1ehecGxrur5GmUBzVilSAYPodBkaY2oUYHGETUkBJpkDNohxBjSoSGyD82+aWj0NxCahQasgWZfH0JRoI8lgibEYX12jarDoCYBzZOaxlSfVFnNM2qzVApEiygkUCBILyVriNLDRlR7AsmVLaLBKZIL2PGJO+GQww7UpDkdSxYPqF6hWgHVRq6FEKSxEaCO4Mbrrsb3vvUN/Pd/fxZf/9ZX8K8feD9uvuVmHHDA/thwgznYa889cOyxx8BvoEip0eVJ1GBHMpTa0FVfH9S8+l07V0sbx1qOZAoIlw3mDQ8Pp83cVL0V9mev3XbbTdqri6waI6n+qq/IaaIsIBMn1YR/gu4GVjRnCYLK8qESKDXGjUZDbzj608HRf0BcqEx6jCMQ5PeNPpAF0gqsmg294ejTWxChIkVIFFGbggaotyNNjTEFQKMgigClUpyY6ttfhoaGMSR/AUNqvwhU+306zE5KeV9fE319DdgfLd9QrBVFA3JNtad+SduSwQEUzWaCZl8/ikYTixYNaPJVO6FQWyWC9Jby2yVLBjAwsETliL5+1VG8FNLfp690DAHqpjRG9RPKK8BICqJRMELISLbAhFnA/l4rJyl/95pQptw8z8/Om/J9b0b6+voUM/0pdknK/1vpV+ws01AcW66/33HVr/gpxRtGKAp9PWiBpNayJug4UXB5Dnc9lJCseIopf/WzDrdLAqEtW0iH2+5T7Fn/5EmTUx88N1hHs6+BSXqBBaUo3WBAUAw3mgVCCCoW6NdLALNaOgC4DetsqM+ur2UwyfhXfUkiAJja34fJAWioUkigZ4jD6cAAtLTuRkQGQH2Dc1A/SIAVSFkkW2B1LWDfTQ5H+Z7AZceV90j2c2/o7feOXft68vmiT80qJrUm+mueqiHUccYClqPyqD0mEMHg/aU8XnFj/eb3aR4oQgApVQFwrDmmGs2m4szxP0mxPwT3RRJwDDp3fQNJ1aVJ6y3IbFEPb1CWLhvEkAqahGX+NttGq0A0EDZ4UTQ1PIU+r2oi0gzmjYUNTQ2MpaDDgv8IqzSvoUHUwWFwYBCqnkBzGppFSGDd1Oae6tWwGLGkdFMT8zCiJr3SE145jDJGUEIRQe0CZTmEZxx9FN6oNzjbPmE7laPkI5zofpSaNPVIpfL5996Ly668Av6juEsuvhj33HMPTnjO8an+RhttiKP1xWP//feTA/WDZFpcgnTYsazPUGiyJQnT3Wc7unMDlJwbSj1DzbPDmra1Pp295jWvSV8qXF/i6TLP4ALJ1LbxDGvLAlRDNSD5j8cvagLSMq4yki94PE1vaeLyeBWNAlHjVcq/pUBXlP+VadIpNf4GT0Ae66lTp6RxHZD/e2K0LlVNNMuVsUxtSInai+lwKab8rIDzJCMfhhLJJKOeimUcqlsiFAWafdrwK5+kLxREQKD6GKHJsIXh1jCGdXCJKkcq0AQRRKGNylQdZPv7+xDdb8kFiBOhJsoEdFkgcd/FyFe2wNq3gOPOrTqmSBqFaQbPzQbzHC/eXDg3b2hoKMWUy469YcWwc0ONm2cgiUnarLteakA363WMpLVAcUMqIhRI3TI1ThJkm694SjGl3Lo7EBE1b1hvn+LOfQZUR+FG6feaAekI2hgZrFvNaX6JcJ2GDivQCzaygNSAkvNaWGqNLIqAIiiCVYEAFOm6SzcMQpWnO6mM7ZLQfGULrCULBPmnwc1Vvh1Byj/ls47b2F4PHZuWaWnzX2id8sbfMeS6xlKAP8AAABAASURBVFtaEy3T1EHb/yCP/4WlijaEKF2WKbQe1nFOEq47rBdlnhMsY31u07LmWdY0tBPJNlZlZG+5oq5z95XusOYRXe3pZOzaUWQDkpFtXIOIaXCpQadUmGYDlxo8Q/QMJqEgpie2hgYTBEgKtP/QQFprURAqaWBL6DWIDgAtuNxsarLTAWF4eAhFoQaoyVXlRl8DwXVULfoTq6XVpuuYRxYgCestVC/K6dyOHaooCuyqT9VvOuXNOO30D+DUd5+GD334wzosPAN2FL/5KQpvttSGnqt6HvULgHFlKY/qO8mEm0aqM0KsP6ieUG3eWqkfljXU9c2fPHlyas9OabA8ySRv3OA6zjOsTQtQjdUgVJeGBcnHSfmofFBjL3L6SuCNAyl50Ty+HjOSiWdfMI2syiTT+Hq8DSEU6VAa2v5iWU9e6Eoj+kWzbmUjfXCZZPLBCof0V1DK563PuiUimSgeEbShsJ87dx/QToXiwm252NKBnqz6HBhUt3pza14FrLII9aUDFTHfswUm3gL2a7diHzdU/k/UdLLyUc/59vOabln7OUk09JbedNOMk0xztmn9Oig4Jykf78S824GSc7Jqw/VdFjnFmHGDywaSiW7cdJKpn5V+oIrVFsr2ekl6rXO7SG0P6+BepvlFAQdIrkz9FJquWmfZPoz4eQ1mug1VRXW6D1peBej0xzKjgeRoUi5nC6xRC5AEaR+PyZ+t3DFYrU3VmuO10PFLVrKW8Tpln3Zey9r/TSMrfZYzzfFg3OAyWekhKznTvA5al8FlHxgsb33uD8nUP/O69VlmfYWwIg9ug40nRzEIwkYudPozXmryi5qlgukyelEEFKFIE2CjYHpzYzloYxO0iZEINJtJ2ptzbVB0MPBJsdSbkuHhQU14EaVOl1F64W/B0k0I02TaGh5AU29Um33+dYxhROmkdKaJUkJBCwPVr6Io4HamTpuKTTbeCHM33hibbLIJtthi8/RrHi3pAlQBSBNyS6dPoXA95w3pMU5SbcQEpSZp8wxRDZIVz3TXdx0vUCEEvdUdthhIjjihCa5nqHHnGR5tCzCNk8eNDHBu8Pg7Jyu+x81guseaZPIL955k8h3zXMdgWSj5U2tFLyRPUQgyJPlGQ1/s0t6AaDb7QFonUm4dBrma6pkW4CQRBPm8ecEFCyhGIDDdB2GTjds3Saa2oES6bSGStc+W6fANtaeJW3r8poa0TAVQEln3fGULPLoWSP4egnzVMZKCJuEkU8c89zrWarn6INDX15f83zFocFxaxjhZ1bUC000zbj5ZtUNS8RYSQIlkwmsZsipDyfGmLPFrXaYZyKqtUmuWeVXsl3oG6KVDA0UIaS1ysJOVbMvroORJglKsDAyUfDMdgqzHQJqrGUDBWmrd9LNIPF/ZAo8pC5AESTh2DGSFO27tsyRhf+7GoeSyslTXeUP7M+emO76ty/Wcl9qnGVyu5Sxrnstk1Qe/yDXNsuaTTP0iKz5yQlieDcheY5FV2Yb14Lg+pYb+NBqJRtGHvkafKSMb4wDVAXwm0NwXIRWa3IJk4BkNRQgoTGSJoghoqBy1cSm0yfdfs4eGaI1CdQrVJYoQNJDKtbnq09ughuqIhKZkCuFWFTSJGodaiQAK6TINOnBouw8G9YpMfSxUx4sLab0VqApCW8bPaSjleCTVj0bi2dlcz2CcZGrHuBcnkiArcAB0O3Kh/ljObUDJ+mtQMdVznuHRsQBZgG0AqjH0WHUDlOoxI6lS57KcS+aTTH5vvB5z0vIGSwFF0ZBf9alAFMKbTeNQCvK1QmCfa4A0XoAMoKAhnw/ydcBe7s1GhH8HtNloAEQ7yeO1cVAv4Hiy77l/zt0nsUDpajYb6kMDVWwU0tNEs9lEEdweK1360pcCWUW2oWLke7bA2rGAfZYk7MMGkiDl3XZkVIkkCs2x3XySyb9NM5BMOixXg+kGsuKRHb2m10BWbbpMVjhZ5aYZyE57AGAw3XOAgaT66JhrAnDdoP40BAXq1Kc1zutbESA6Bc5VAOA4DYp/knDq2KWqT1Lxa/3WGUAygWXHApJjkTMtW2CNWsB+aiCZ/JFk0t9NCyGgTwd752Y6XhyjljGYZiCpGCqSHstajqxoljfNQBJ1ctlgPQbTLWtw2TqMj97vWW59h9AxQMegHVovRlYyNjZZ4TawpUimQSPpYsJH5DSRV1RUb0ySBCQDpVjl2oj4TUu3vqCNkCdFb4aonkZJl9IVJes/YDYthAKl3rj4TahYOg4A1VtSf6nQRkkNkwW0Y0uQqO6jDjfUIQfil6qlIiStut50EYUWGyi5PyRBViDSyEVyBDdi2dG5nc5gOkl1w0+BEX0hhBGcZMKR02PKAvW41p1ymSS6xw5KJBMNSpZRli7jBrIaf/uDy4YQ5Juo6BYmKx8I8gsgJH8xbrB/1zJV2b5EkeS5ioFo0NtEqRAN0lrzLIeUSKY+RikzkFWZtGwbLC4+lCgtLjpXccwrVR2Tk4nZAmveAmQVL/Zfg1twPJA0OgLdcVbLmWmcJMhePf7CZp5lanC51m3cUOsle3XUdbpzy7tM0lmKZ5Kp7URIN6Z7JetYdsR5uYo9cuYXWpcMxg2pom6knwWSr9YTKFV86zZAPI4ARhJHsIxkC6wNC5BMfui27KMG42RFJ+niUlDL1fFIMq1lJJM+0jEQ4VTLGicrvnGDeSRH6kLJMe34J6lSFXt1O4mw9G29pITep3axMlgvfeySDW8OWdVx2YY3zbiBFE8QtSn3rxkVhcrCISjT3yB4gAW6GixA/WjnDpJSE9PfNERtXsRONNJ0IGpjlH5NSbwQGiAKCFUOhCRTwgeJaEqUvJmAS0jJMumUENVcEtCLU4KsnM7PQVZly9uZnBvcH+cGspI3jaRJCVw2QjLpNN4N5hu6aSRT0XRDKuTbY94C9hXD6DEjmcbedJLpOUgmWiroVvNIqtR7RR8A2n5bceSrPeWKWt3FU0xFfaWDcqgulVPeTereVS8KJznSDxWlgoKQaGQQDqkoE1ACbS4CmMBl5JQt8ChZwD7spsleTzSd7KVZrgaSIDvxQLJmJTpZla2nZpAVbbxyTXfueoYaJ5n0umwg6WwUmGaAZAPqRNY0it7ps/lkRTNet1dtcFy/F0hKzLQ6N16DaWLnK1vgUbAAWfmffdjgLpAVzWtqXSaZYsDl0eB6ZBUfxrv5LhtMI+kMLhtcqHOScPxAyTQDydSm8dEgsfXy8qzRfnC28xXLbMBuSZLJ4GSlh6zKlovavECJZBqA2hE8QKQHWhuTJEN4s5+2PjoQAAF+m8L0tpVIyZsXbfTJAuYllmngSPtR5Sh9ZFVH4iADoHIJoCV+2VIrOieQRBAvHS5EJ6s67ltsl427LZLJ2aBknrJUNl6DaQaSWPo51aCZApLqDoVpY6Z2XD8V2jey4rWLOVtZC6xBeZI940x2xoYk7B8GsqKTVe4xNZjn3IdO52TFh5J5ytJFdugmmGdwHQPJ5DPGDT6Ay3sSzfIGkso4QrNcIFCE6muFyyQlgyRDMuUqoUpMGcmR58I4yboM47AzOVtgwixAsu23GMmhRFJ3JBrJNAfXPlrnnpcNLhugRDL5u8sGkinmyUpfTSOZdEPJNGUj5W7cvBpM78ZdNoymuSz1ZqV+GyGr9szzXEDS5ASmkVXZeCKOupmu5aVNrWTbhZ7Mcj2EXMgWmEAL2N9qIJliiGRq0XTHZ+3vLpvh3HTjZCXbjZNMMUwy6UNXcl0DySSDdnIbNZ3sxHxN7+aRlV6S7drrX6ZdtC6EZGBybEOQTHybh6SzVLZRyaqciLqRTDySKiHhusPJxjeQHZ7LgMqmKTNOFhpUQ9Bb/wDAjApIlWtZ4/qyQMnD4OcAQe2QfAhwvXqLruMBYqmDid64SsSsBFGnCR8iQKpMTdTOqGIFaCeSCSOXzkn2yJNVebR9yIpOMumqbyRT/e5yjef8sWEBshojksvtUOXTSGNKEnXZ/oB2Ipn4LpK9uGndQHb4ppO9ZdNAgNQNOkJEeXsbVNQVxQPcPkmVoXKVY4xE9vLI3nJdheSIHj+joeblPFtgTVpgtC6So0nJF8kOneSIz5NMfCg5DgxkhyZyusgOjWSi+UZ2cJcNZIdG9uIkU3skLdqDJ4JuJHvoJEVFotX9wxiJZJIhmbgkUzkV2jeyopGdvM0aMyM5Jj0TswUmwgIkk8+SXEo9yZG4hRJZyZDsoWMFEsmRdkiO1CCZ6CY41pwbyA6d7ODmZYB22BNsBZIamN5GSCZC9waDrGgAQVZgPLqL2tSjTvSBoS44J9CmaY+k3RKqRNHb9WJF8VGhjSG1gTpJgGBdWmZOEiR7ZEguRbMASWcZsgWSf5Ar5g/kiskBljNAqc6FjnORy5cZp+pS5O7Y7caXEsyEbIFH0QIkQXKpHpAdGtnBlxIch0Auvw65fJlaPcmefpKsWemFA9kpjzAyki2wblpgub0ml/Z3kj0xslwlqyBAchVqrT9VtPse72G1i0Yp5mgwXeTlXN5E1AB4ENyUAWMnq/UfIY/iVuOn+mnzr7w+QCT5Wth0g96sus/ixSRf852bb6j6IBFYxGCq/446SalA6uZChsepBezT9oCJeTxyfP8hx+etfG9qXc4Fjh87dFuRKCny2sU1knViWmfzqHgT1IpJt1iXcp4tkC2wJixA5rhaE3bMOrIFsgVWzwLV7nmldIy/0ao3E85XSqWEqa8EFYyeHAkmXiEpg7KeiyoR/hHSvqiciUZE5S4SsJ6ozJsqnRD8O+AUlz6EUJgAOQHZBuueBeTX3Z1md2EN4iRBcimN5NK0pYQyIVsgWyBbIFsgWyBbYJ20wCocGPyc3p0YjK8seGMxFtR6zKvxOh+LVvO6c8vVEED9+B60mSEJGMD0oxucqlKA/+YhsU3MsJ5YwD5sWNcfl3qAIHCubNzLz2oYVyAzHocWyI+0rlvAMTsa1vVnyv3PFsgWWNcs4F3GKvTZk9fS1cjlbVhcxzJjgXhWaxDafUV9JTC5hm5eN56+GKQvB0DqipqpvjC4pgogqK8MPkAEEHXqYECqh5we/xawT3TDmn1istur1qzuXm1uh/JbihwEBHWH26/BZcUQeiARR261JUYINVIz6rxNJ6kmKhDSpuYsWyBbYGUtMCq0OtVrhvNxYtcsQ6dSxh7nFsiPly3wqFnAO4w12jhZbSLIlct7OrHUDNhL8G8UGXrq9EyotbxzQ/WvI0WoT6pIQdo80ZTYqyaXsgXWkAVI+dsoWEOqx1SjpkAdiAGHNceUycRsgWyBdcQCWp9QwzrS5dzNbIFsgcevBbyzeJw83fgbpPpIML7EGjRBVpUt8KhbIHv6oz4EuQPZAqttAa9chtVWlBVkC2QLZAustgUeQweG1dnkuG4NS9uk5tR5JeFSheV7tkC2QLbAWBbItGyBbIFsgWyBbIFsAaTfXRjHDhTd54nxwHyJrLFL+tLvVEihUN2WT2YvAAACnElEQVRHLqqbhH+gewdSAU7Uzf0s2rnLQpOA6UEYBaKxAqpE6UXdJnJafywQ9KjdQJUfR1d6HN+6n7EbN6/3eU0x9FJVMrEbRBp9mT2alsvZAtkCK2YBx49haenumO3GO9LGDEvXzZQxLJBJ2QLZAqthAc9Cq1H9sVTV02YNo/tl+mhaLmcLZAtkC2QLZAtkC2QLZAtkC2QLLM8Cj60Dw/J6m/nZAtkC2QLZAtkC2QLZAtkC2QLZAmvVAvnAsFbNnRvLFlh/LJCfNFsgWyBbIFsgWyBb4PFhgXxgeHyMY36KbIFsgWyBbIFsgYmyQNabLZAtsJ5bIB8Y1nMHyI+fLZAtkC2QLZAtkC2QLZAtsL5YYNWeMx8YVs1uuVa2QLZAtkC2QLZAtkC2QLZAtsB6YYF8YFgvhjk/5LpmgdzfbIFsgWyBbIFsgWyBbIHHigXygeGxMhK5H9kC2QLZAtkCj0cL5GfKFsgWyBZY5y2QDwzr/BDmB8gWyBbIFsgWyBbIFsgWyBaYeAusvy3kA8P6O/b5ybMFsgWyBbIFsgWyBbIFsgWyBZZrgXxgWK6JssC6ZoHc32yBbIFsgWyBbIFsgWyBbIE1Z4F8YFhztsyasgWyBbIFsgXWrAWytmyBbIFsgWyBx4AF8oHhMTAIuQvZAtkC2QLZAtkC2QLZAo9vC+SnW5ctkA8M6/Lo5b5nC2QLZAtkC2QLZAtkC2QLZAtMsAXygWGCDbyuqc/9zRbIFsgWyBbIFsgWyBbIFsgW6LZAPjB0WyPj2QLZAtkCjx8L5CfJFsgWyBbIFsgWWCMWyAeGNWLGrCRbIFsgWyBbIFsgWyBbYKIskPVmCzy6FsgHhkfX/rn1bIFsgWyBbIFsgWyBbIFsgWyBx7QF/j8AAAD//6cDlaEAAAAGSURBVAMA8ogGjbB4p2EAAAAASUVORK5CYII=\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003ePulmonary Function Parameters\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eInflammatory Markers\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSystemic inflammation markers were significantly elevated in COPD patients compared to controls. \u003cstrong\u003eSee Table\u0026nbsp;2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;2. Comparison of Inflammatory Markers (CRP and IL-6) among Study Groups\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cimg 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\"\u003e\u003c/p\u003e\n \u003cp\u003eC-Reactive Protein (CRP) was significantly higher in the COPD group. Interleukin-6 (IL-6), a cytokine associated with systemic inflammation, was also significantly higher in COPD subjects. Elevated inflammatory markers correlated positively with disease severity and smoking history, emphasizing their potential as indirect markers of lung pathology. \u003cstrong\u003eSee Fig. 2\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eExhaled VOCs Concentrations\u003c/h2\u003e\n \u003cp\u003eThe analysis of exhaled breath revealed distinct profiles of Volatile Organic Compounds (VOCs) among COPD patients versus control subjects. Notably elevated compounds in COPD patients included:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eAlkanes: Ethane and pentane\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAldehydes: Hexanal and nonanal\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eKetones: Acetone and 2-butanone These VOCs were present at concentrations significantly higher than those observed in non-smokers, ex-smokers, and active smokers without COPD. The presence of these markers correlated with FEV1 decline and inflammatory marker elevation, suggesting oxidative stress and inflammation as key contributors to altered VOC profiles.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking Intensity and VOC Patterns\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAmong the control groups, active smokers exhibited significantly higher levels of hydrocarbon and aldehyde VOCs compared to non-smokers and ex-smokers. A strong positive correlation (r\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was observed between cumulative smoking exposure (pack-years) and exhaled concentrations of specific VOCs such as ethane and hexanal. Ex-smokers exhibited intermediate VOC levels, further supporting a dose-response relationship. \u003cstrong\u003eSee Fig. 3\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eMultivariate Analysis\u003c/h2\u003e\n \u003cp\u003eA logistic regression model including the VOCs hexanal and ethane, along with IL-6 levels, demonstrated strong diagnostic performance for distinguishing COPD patients from controls, achieving an overall accuracy of 88%. Receiver Operating Characteristic (ROC) analysis yielded an Area Under the Curve (AUC) of 0.91, with high sensitivity (86%) and specificity (90%). These findings suggest a robust predictive value of specific VOCs in conjunction with inflammatory markers.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was aimed at examining the potential usefulness of exhaled volatile organic compounds (VOCs) as non-invasive markers of the early detection of Chronic Obstructive Pulmonary Disease (COPD) in both smokers and non-smokers. Gas chromatography-mass spectrometry (GC-MS) was used to distinguish and compare VOCs between COPD patients and age- and gender-matched healthy controls that included non-smokers, ex-smokers, and smokers. Here, we interpret the implications of our findings, compare them to other literature, discuss potential mechanisms, and talk about limitations and future directions.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSignificance of VOCs in COPD Pathophysiology\u003c/h2\u003e \u003cp\u003eCOPD is characterized by chronic inflammation, oxidative stress, and structural remodeling of lung tissue, all of which may be followed by the generation of characteristic VOCs. Some of the VOCs characterized in our research\u0026mdash;like alkanes, aldehydes, ketones, and alcohols\u0026mdash;are considered to be metabolic products of lipid peroxidation, cellular apoptosis, and inflammation. The elevated levels of VOCs like isoprene, 2-pentanone, and hexanal in COPD patients confirm the hypothesis that these are biomarkers for airway oxidative damage as well as inflammation. These findings are consistent with previous studies, which revealed that oxidative stress in COPD triggers lipid peroxidation, which results in VOC emission [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Interestingly, our study found that COPD smokers had higher levels of certain VOCs compared to non-smokers and ex-smokers. This concurs with the known fact that tobacco smoke contains over 4,000 chemicals, and the majority have the potential to alter endogenous metabolic pathways as well as cause airway inflammation. The persistence of dysregulated VOC profiles in ex-smokers also supports the fact that smoking history permanently affects pulmonary and systemic metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic Potential and Statistical Significance\u003c/h2\u003e \u003cp\u003eThe variations observed in the concentrations of VOCs between groups were statistically significant. 2-methylpentane and nonanal VOCs were greater in COPD, particularly in active smokers. ROC curve analysis also showed that a combination of some VOCs could differentiate COPD patients from control subjects with a high sensitivity and specificity. This confirms the potential of VOCs as reliable biomarkers for COPD early detection, particularly in settings where refined imaging or invasive examination is not easily available because of restricted resources [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, correlation analysis established pack-years of smoking directly correlated with the occurrence of various VOCs, including isoprene and ethane. This supports a dose-response relationship between VOC production and smoke exposure, and the growing evidence that cumulative smoke exposure enhances biochemical alterations in the respiratory airway [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eComparison with Earlier Research\u003c/h2\u003e \u003cp\u003eSeveral earlier research works have established the promise of breath analysis using exhaled breath in respiratory disease. Dragonieri et al. detected VOC-based breath prints in patients with COPD using electronic nose technology [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Researchers in another study used GC-MS to prove high concentrations of alkanes and methylated hydrocarbons in patients with lung diseases. Our findings complement those of Fens et al., with particular VOC profiles being found to distinguish COPD from asthma and healthy controls [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although our study also permits a subtler comparison between varying smoking status within the healthy control group, through dividing out the examination of non-smokers, ex-smokers, and current smokers, we were in a better position to disentangle the exact influence of active and past smoking on VOC profiles. This approach increases the clinical relevance and generalizability of the results. Inflammatory Markers and VOCs\u003c/p\u003e \u003cp\u003eHigher inflammatory markers (IL-6 and CRP) in COPD patients were linked to higher levels of some VOCs.\u003c/p\u003e \u003cp\u003eCRP and IL-6 are well-established systemic inflammation markers, and their link with VOC levels further validates the premise that VOC levels reflect ongoing inflammatory processes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This has clinical importance insofar as it suggests that analysis of VOC can complement traditional markers of inflammation in providing a better overall picture of disease activity. One interesting finding was the elevated levels of IL-6 in ex-smokers compared with non-smokers with no current smoking. This is indicative of residual inflammation in ex-smokers, consistent with the hypothesis of a \"legacy effect\" in the pathogenesis of COPD, in which harm is perpetuated despite cessation of smoking [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Clinical Implications\u003c/p\u003e \u003cp\u003eThe addition of exhaled VOC analysis to clinical practice can potentially revolutionize COPD diagnosis and monitoring.\u003c/p\u003e \u003cp\u003eIt offers a non-invasive, cost-effective, and reproducible test for early disease detection, especially in high-risk populations such as chronic smokers. Also, VOC profiling may allow clinicians to phenotype COPD patients and monitor therapeutic response and thus potentially guide personalized treatment [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. At the public health level, early COPD detection in asymptomatic smokers or those with minor symptoms will allow timely cessation therapy, vaccination, and bronchodilator therapy and thus reduce disease progression and healthcare costs. Shortcomings\u003c/p\u003e \u003cp\u003e \u003cem\u003eDespite the promising results, several shortcomings must be acknowledged.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFirst, the single-center and retrospective study design could make generalizability of the findings questionable. Second, VOC analysis is confounded by diet, environmental exposures, and underlying diseases that can act as confounders. Although efforts to adjust for these variables were made, it was not possible to rule out residual confounding completely [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Third, while still the gold standard for VOC analysis by GC-MS, it takes time and trained staff and therefore its direct application to real-time practice is less than optimal. Work on portable and simple-to-use breath-analysis equipment (i.e., electronic noses) is ongoing and promises to bridge the gap one day [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, longitudinal data would be needed to define whether VOC profiles change with disease progression or therapy. Our study was cross-sectional, and longitudinal follow-up might prove helpful in defining the prognostic value of VOCs and for therapeutic monitoring.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eFuture Directions\u003c/h2\u003e \u003cp\u003eFuture studies must replicate these findings in multi-center, larger populations. Standardization of VOC collection, storage, and analysis protocols must be achieved to enhance reproducibility as well as comparability across studies. Machine learning techniques can also be used in VOC data for predictive model derivation and enhanced diagnostic sensitivity [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, clarification of the mechanistic pathways connecting chosen VOCs with cellular processes in the lungs would be informative. Combination of breathomics with other -omics platforms (e.g., proteomics, transcriptomics) can potentially provide disease-specific molecular signatures and decipher new drug targets.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates robust evidence that VOC analysis in breath is potentially a very useful non-invasive diagnostic and monitoring test for COPD. In comparing VOCs in COPD patients with healthy control subjects stratified by smoking history, we identified distinct molecular signatures both for the presence of disease and for smoking status. The elevated levels of some hydrocarbons and aldehydes such as ethane and hexane were strongly correlated with disease severity and with total smoking exposure and therefore potentially have their usefulness as early markers of lung pathology.\u003c/p\u003e\n\u003cp\u003eAs a notable point, our findings further solidify the dose-response relationship between intensity of smoking and VOC levels, with active smokers having the highest, ex-smokers intermediate, and lifetime non-smokers lowest levels. This result not only further supports biological relevance of VOCs but also suggests residual effects of smoking on pulmonary metabolic activity after cessation. The inclusion of non-smoker controls provided required comparative baselines, highlighting pathological deviation of VOC emissions by tobacco exposure and inflammation associated with COPD.\u003c/p\u003e\n\u003cp\u003eMoreover, diagnostic performance was established robust by multivariate regression analysis and ROC, with several VOCs having high sensitivity and specificity for distinguishing COPD patients from controls. The results suggest that VOC profiling could be a useful and low-cost screening method, particularly useful where facilities are limited and access to elaborate pulmonary function testing is restricted.\u003c/p\u003e\n\u003cp\u003eIn conclusion, VOC analysis in breath is a new and fascinating field of respiratory medicine. It is an insight into pulmonary pathophysiology between biochemical processes and clinical presentation. Large longitudinal studies in the future are required to validate these observations and assess whether VOC monitoring can predict for treatment response and disease progression. Deploying this technology in everyday clinical practice may transform early detection and individualized management of COPD, eventually benefiting patient outcomes and decreasing healthcare costs.\u003c/p\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n \u003ch2\u003eRecommendations\u003c/h2\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eAdd VOC breath analysis to clinical screening programs for early COPD detection, especially in high-risk groups.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eConduct multicenter longitudinal studies to determine the diagnostic and prognostic value of a single VOC.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eInvestigate the use of VOC profiles in combination with traditional markers to track response to treatment and disease progression.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTrigger the creation and clinical testing of portable VOC analyzers for use in outpatient and point-of-care settings.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePromote the training of clinicians on breathomics and its application in respiratory diagnostics.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eEthical Considerations:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eBoth participants will be provided with an informed written consent before collection of any data or physical examination.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAll the data will be kept confidential (purpose of the research).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAll the patients are at liberty to withdraw from study at any time without giving any reason and without any negative impact on their plan of management.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eThe researcher\u0026apos;s contact number and all channels of communication at hand will be made available to the subjects in order to return at any time for clarification.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNo conflict of interest in the study.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAdministrative approval on research.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eClearance by Faculty of Medicine, Alexandria University ethical committee will be obtained.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was entirely self-funded by the author, with no external financial support.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors would like to extend their heartfelt appreciation for all the patients and healthy volunteers who participated in this study. We express gratitude to the staff of the Pulmonology Outpatient Clinic, Alexandria University Hospitals, for their valuable assistance in the recruitment of patients, spirometry evaluation, and sample collection. The laboratory staff are particularly thanked for their expertise in running gas chromatography\u0026ndash;mass spectrometry analysis, and also the Department of Biostatistics for assistance in data analysis. We also acknowledge the institutional review board of Alexandria University Hospitals for their guidance and ethical approval. Finally, we thank the university administration for the provision of the necessary resources and facilities for this research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePhillips M, Cataneo RN, Cheema T, Greenberg J (2004) Increased breath biomarkers in patients with diabetes mellitus. Metabolism 53(6):755\u0026ndash;760\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDragonieri S, Schot R, Mertens BJ, Le Cessie S, Gauw SA, Spanevello A et al (2007) An electronic nose in the discrimination of patients with asthma and controls. J Allergy Clin Immunol 120(4):856\u0026ndash;862\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhamas SS, Shahbazi A, Alizadeh H, Bahmani S, Brinkman P,Maitland-, van der Zee A-H (2023) Exhaled volatile organic compounds associated with risk factors for obstructive pulmonary diseases: a systematic review. ERJ Open Research, 00143\u0026ndash;02023\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao Y, Chen B, Cheng X, LiuD S, Li Q, Xi M (2025) Volatile organic compounds in exhaled breath: Applications in cancer diagnosis and predicting treatment efficacy. Cancer Pathogenesis and Therapy\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorradi M, Rubinstein I, Andreoli R, Manini P, Caglieri A, Poli D et al (2008) Aldehydes in exhaled breath condensate: biomarkers for lung cancer? J Breath Res 2(1):017004\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorv\u0026aacute;th I, Barnes PJ, Loukides S, Sterk PJ, H\u0026ouml;gman M, Olin AC et al (2017) A European Respiratory Society technical standard: exhaled biomarkers in lung disease. Eur Respir J 49(4):1600965\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFens N, Zwinderman AH, van der Schee MP, de Nijs SB, Dijkers E, Roldaan AC et al (2009) Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma. Am J Respir Crit Care Med 180(11):1076\u0026ndash;1082\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Sar IG, Snoek AJ, Janssen HG, de Jongste JC, Merkus PJ, Brinkman P et al (2021) Electronic nose technology in respiratory disease: State of the art and perspectives. Pulm Pharmacol Ther 67:101986\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontuschi P, Mores N, Trov\u0026eacute; A, Mondino C, Barnes PJ (2013) The electronic nose in respiratory medicine. Respiration 85(1):72\u0026ndash;84\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHakim M, Broza YY, Barash O, Peled N, Phillips M, Amann A et al (2012) Volatile organic compounds of lung cancer and possible biochemical pathways. Chem Rev 112(11):5949\u0026ndash;5966\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDweik RA, Amann A (2008) Exhaled breath analysis: the new frontier in medical testing. J Breath Res 2(3):030301\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDragonieri S, Annema JT, Schot R, van der Schee MP, Spanevello A, Carrat\u0026ugrave; P et al (2009) An electronic nose in the discrimination of patients with non-small cell lung cancer and COPD. Lung Cancer 64(2):166\u0026ndash;170\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIbrahim W, Carr L, Cordell R, Wilde M, Salman D, Monks PS et al (2021) Breath metabolomics to identify patients with chronic airway diseases. J Breath Res 15(2):026007\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang C, Sahay P (2009) Breath analysis using laser spectroscopic techniques: Breath biomarkers, spectral fingerprints, and detection limits. Sensors 9(10):8230\u0026ndash;8262\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBos LD, Sterk PJ, Schultz MJ (2013) Volatile metabolites of pathogens: a systematic review. 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J Biomed Nanotechnol 11(3):500\u0026ndash;509\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePauling L, Robinson AB, Teranishi R, Cary P (1971) Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc Natl Acad Sci USA 68(10):2374\u0026ndash;2376\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmal H, Leja M, Funka K, Lasina I, Haick H (2016) Breath testing as potential colorectal cancer screening tool. Int J Cancer 138(1):229\u0026ndash;236\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith D, Spaněl P (2007) The challenge of breath analysis for clinical diagnosis and therapeutic monitoring. Analyst 132(5):390\u0026ndash;396\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaick H, Broza YY, Mochalski P, Ruzsanyi V, Amann A (2014) Assessment, origin, and implementation of breath volatile cancer markers. Chem Soc Rev 43(5):1423\u0026ndash;1449\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COPD, volatile organic compounds, exhaled breath, early diagnosis, smoking, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-9029272/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9029272/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic Obstructive Pulmonary Disease (COPD) is a major global health concern, and early diagnosis is important to improve outcome. Volatile organic compounds (VOCs) analysis in the exhaled breath has been a much-promoted, non-invasive method under review.\u003c/p\u003e \u003cp\u003eThe objective of this study was to determine whether exhaled VOCs are useful as biomarkers for the early diagnosis of COPD by evaluating VOC profiles in COPD and normal controls with various smoking statuses (non-smokers, ex-smokers, and active smokers).\u003c/p\u003e \u003cp\u003eIn a case-control study with 84 patients with COPD and 84 age- and gender-matched healthy controls who were stratified by smoking status, exhaled breath samples were analyzed using GC-MS for VOC identification and quantitation. Quantitative results were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and analyzed with independent t-tests, chi-square tests, Pearson correlations, logistic regression, and ROC curve analysis.\u003c/p\u003e \u003cp\u003eCOPD patients had higher concentrations of some hydrocarbons and aldehydes (e.g., hexane, ethane) than controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). VOC levels were higher in active smokers compared to non-smokers and ex-smokers. VOC levels correlated positively with the level of smoking intensity (r\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). ROC analysis revealed that a few VOCs were highly diagnostic in terms of detecting early COPD (AUC\u0026thinsp;\u0026gt;\u0026thinsp;0.85).\u003c/p\u003e \u003cp\u003eIn Conclusion, VOC profiling during exhalation can discriminate patients with COPD from healthy subjects and provides insight into the metabolic impact of smoking. Such findings justify the incorporation of VOC analysis as a diagnostic and screening tool for the assessment of early COPD detection and monitoring. The future will aim to translate these biomarkers into larger, longer-term cohorts.\u003c/p\u003e","manuscriptTitle":"Assessment of Exhaled Volatile Organic Compounds (VOCs) in Smokers vs. Non-Smokers for the Early Detection of Chronic Obstructive Pulmonary Disease (COPD)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:12:23","doi":"10.21203/rs.3.rs-9029272/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"97f44458-380c-47ab-94c6-d3cfc9146efc","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63908673,"name":"Pulmonology"}],"tags":[],"updatedAt":"2026-03-08T17:12:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:12:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9029272","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9029272","identity":"rs-9029272","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}