Association between dietary fiber intake and epilepsy risk: A cross- sectional analysis using weighted data from the National Health and Nutrition Examination Survey

Association between dietary fiber intake and epilepsy risk: A cross- sectional analysis using weighted data from the National Health and Nutrition Examination Survey | 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 Association between dietary fiber intake and epilepsy risk: A cross- sectional analysis using weighted data from the National Health and Nutrition Examination Survey Ling Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9256805/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 Epilepsy is a chronic neurological disorder resulting from abnormal neuronal discharges in the brain.The pathogenesis is intricate and remains partially understood.Dietary fiber reduces postprandial blood glucose and lipid levels, enhancing metabolism and lowering the risk of cardiovascular disease, type 2 diabetes, and certain cancers, with metabolic factors also linked to epilepsy.This research investigated the link between dietary fiber intake and epilepsy risk among U.S. adults. Methods: Logistic regression models were developed using data from the National Health and Nutrition Examination Survey (NHANES) in the United States, covering the period from 2013 to March 2020.The relationship between dietary fiber intake and epilepsy risk was examined.Restricted cubic spline regression (RCS) was used for linear testing to explore whether there was a quantitative relationship between score values and risk.Subgroup and interaction analyses were performed to evaluate the stability of the relationship between dietary fibre and risk for epilepsy in different subgroups. Results: Data from 11,828 respondents, of whom 93 were diagnosed with epilepsy, were included in this study.In a fully adjusted multiple logistic regression model, dietary fiber, treated as a continuous variable, was inversely related to epilepsy risk (OR 0.45, 95% CI 0.27–0.76; P = 0.004).In a fully adjusted model, individuals with high dietary fiber intake had a reduced risk of epilepsy compared to those with low intake (OR 0.27, 95% CI 0.12–0.61; P = 0.003).In the RCS linear test, an inverse association was found between dietary fiber intake and epilepsy risk (nonlinearity, P = 0.97).The stratified analyses showed consistent relationships with no significant interactions across subgroups. Conclusions: In a sample of U.S. adults, dietary fiber intake showed an inverse relationship with epilepsy risk, with each unit increase in the natural log-transformed dietary fiber intake correlating to a 55% reduction in epilepsy risk. Epilepsy Dietary fiber National Health and Nutrition Survey NHANES weighted data Figures Figure 1 Figure 2 Figure 3 1 Introduction Epilepsy (EP) is a chronic neurological disease caused by abnormal discharge of brain neurones, and affects nearly 70 million individuals worldwide ( 1 ).Although existing drug therapies can effectively control seizures in most patients, 30%–40% of patients with refractory EP continue to exhibit a poor response to drug treatment ( 2 ).Therefore, exploring the pathogenesis and factors influencing EP, and identifying new prevention and intervention strategies are important research directions in neuroscience.Recent studies have suggested that nutrient intake is associated with the pathogenesis of EP and that a ketogenic diet plays an anti-epileptic role by regulating metabolism and neuroinflammation ( 3 – 6 ).Supplementation with B vitamins can reduce the frequency of seizures and risk for drug teratogenesis ( 7 – 12 ).As one of the four nutrients, dietary fibre has been shown to reduce the risk for a variety of chronic diseases and all-cause mortality by reducing postprandial blood glucose and cholesterol levels ( 13 – 16 ).These factors are also closely associated the occurrence of EP ( 17 , 18 ).There is a lack of extensive research utilizing data from the general adult population in the United States to investigate the link between dietary fiber intake and EP risk.This study assessed the link between dietary fiber and EP among U.S. adults using weighted data from the National Health and Nutrition Examination Survey (NHANES).We hypothesized that increased dietary fiber intake might correlate with a reduced risk of EP and sought to investigate the impact of specific nutrients on EP. 2 Methods 2.1 Data source This study is a cross-sectional study, and the data used were sourced from the National Health and NHANES websites in the United States. NHANES employs a stratified, multi-stage probability sampling method, and obtains comprehensive data through its research design, interviews, and demographic analysis (19-21).Public archives of four consecutive NHANES data cycles, from 2013 to March 2020, were used in this study.A multistage probability sampling design was employed to ensure a nationally representative survey sample for both data collection and research methodology.The study utilized data obtained on March 20, 2024, from the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm), encompassing respondent information from 2013 to 2020.Participants ≤ 20 years of age, pregnant women, those with missing data regarding intake of dietary fibre, and those with missing covariate data were excluded. 2.2 Diagnosis of EP EP-related information was collected through in-person interviews.Participants reported all medications prescribed in the previous 30 days and their indications.EP was identified by the use of one or more medications classified under 'unknown epilepsy or recurrent seizures' according to ICD-10 code G40 (22). 2.3 Dietary fibre Dietary fiber intake data were sourced from the NHANES database, where participants provided 24-hour dietary recalls. The first recall occurred at the NHANES Mobile Testing Center, and the second was conducted via telephone between days 3 and 10 (23, 24).The final dietary fiber intake for analysis was determined by averaging the two recorded intakes to ensure data rigor.In this study, fibre referred to dietary fibre and did not include fibre supplements. 2.4 Assessment of covariates Covariates in this study were selected based on previous studies and statistical differences at baseline.The study considered various covariates such as age, sex, race, marital status, poverty income ratio (PIR), education level, body mass index (BMI), smoking and alcohol consumption status, physical activity, dietary supplementation, and chronic comorbidities.Patients were categorized into three age groups: under 40, 40 to 65, and over 65 years.Educational level was divided into three groups according to boundaries between 9 and 12 years.Marital status was categorized as either living alone or cohabiting with a partner.Race was classified into non-Hispanic white, Mexican American, non-Hispanic black, and other categories.According to a report by the U.S. government (25), PIR divides household income into three levels of low, medium and high with a cut-off value of 1.3 and 3.5.Based on the smoking questionnaire, individuals were classified as non-smokers if they smoked fewer than 100 cigarettes and as smokers if they smoked 100 or more cigarettes.Alcohol consumption was obtained from the alcohol content reported in the two dietary intake questionnaires.If the two sets of data were zero, participants were considered to be non-drinkers and, if they were > 0, they were considered to be drinkers.Physical activity was classified as basic, moderate, or vigorous.Dietary supplement use was assessed using a questionnaire that asked participants whether they had taken a dietary supplement in the previous month.BMI was determined by dividing weight in kilograms by the square of height in meters and categorized into two groups using a 25 kg/m² threshold.Chronic comorbidities (comorbidities) were also obtained from the questionnaire, which asked whether a physician had told participants about their disease.Five common chronic diseases were selected from among the participants, with hypertension, diabetes, stroke, coronary heart disease, or chronic arthritis considered to be chronic comorbidities. 2.5 Statistical analyses In this study, weighted logistic regression analysis was conducted using the NHANES sampling weights (WTINT2YR) to address the complex survey design, which included stratification (SDMVSTRA), clustering (SDMVPSU), and handling of specific subgroups.Data from the first 24 h and second 24 h samples were weighted so that they were representative of the entire U.S. population.The Kolmogorov–Smirnov test was employed in this study to assess the normality of continuous variables.Given the skewed distribution of dietary fibre intake, natural logarithmic transformation (ln) was used to generate a normal distribution.Variables with a normal distribution are presented as mean ± standard deviation (SD), skewed variables as median (interquartile range [IQR]), and categorical variables as percentages.For normally distributed data, one-way ANOVA was applied, while the Kruskal–Wallis test was utilized for skewed distributions.The chi-squared test was used to compare categorical variables. Participants were categorized into four groups according to ln-transformed quartiles of dietary fiber intake: lowest (-1.61 to <2.30, n=2943), low (2.30 to <2.69, n=2970), high (2.69 to <3.04, n=2949), and highest (3.04 to 4.64, n=2966), with the lowest quartile serving as the reference.Logistic regression was employed to calculate the odds ratio (OR) and 95% confidence interval (CI) to evaluate the link between dietary fiber intake and EP risk.Logistic regression analyses were performed using dietary fibre intake as continuous and categorical variables.Model 1 was controlled for sociodemographic variables such as age, sex, race, education, marital status, and household income.Model 2 was adjusted for sociodemographic factors, BMI, smoking, alcohol use, physical activity, and dietary supplements.Model 3 was refined from Model 2 by incorporating adjustments for chronic comorbidities, including hypertension, coronary heart disease, stroke, diabetes, and arthritis. Restricted cubic spline (RCS) testing was used to determine whether there was a quantitative relationship between dietary fibre and the risk for EP.To ensure accuracy, the RCS tests were performed using raw data without ln transformation.Model 3 incorporated all covariates to create a smooth curve-fitting plot using dietary fiber intake distribution nodes at the 5th, 35th, 65th, and 95th percentiles.Interaction and subgroup analyses based on age, sex, race, education, marital status, household income, smoking, alcohol use, physical activity, BMI, dietary supplementation, and chronic comorbidities were conducted using a logistic regression model.Sensitivity analyses were conducted to evaluate the robustness of the findings by excluding participants with extreme daily energy intake ( 5000 kcal). This study's sample size was solely based on the NHANES database, so no prior statistical performance estimates were conducted.The statistical analysis in this study was conducted using R software version 4.3.3 and Free Statistics software(26) version 2.1.1.A descriptive study was performed on all participants.All statistical tests were two-tailed, with significance set at P<0.05. 2.6 Human ethics and consent to participate The NHANES study protocol was approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board. All participants provided written informed consent (27). The present study is a secondary analysis of de‑identified publicly available data; therefore, no additional ethical approval was required. 3 Results 3.1 Study population This study used data collected between 2013 and March 2020.In the preliminary data, 35,706 individuals participated in the survey, of whom 14,986 who were < 20 years of age and were excluded.Of 20,720 adults, 222 who were pregnant, 2934 with missing dietary fibre intake data, and 5736 with other missing covariates were excluded.Of the 11,828 participants with complete data, 93 had confirmed EP.The exclusion and inclusion processes are illustrated in Fig. 1 . 3.2 Demographic characteristics The study included 11,828 patients with complete data regarding dietary fibre intake and EP, weighted to represent 164,203,933 U.S. adults, of whom 93 had definite EP (weighted percentage, 0.06%), weighted to represent 1,060,853 U.S. adults.The mean median age of the participants was 48 years (IQR 33 to 61 years), 5883 were women (weighted percentage, 49.5%), 4425 were non-Hispanic white (weighted percentage, 65.22%), and those with > 12 years of education had a weighted percentage 64.64%.At baseline, individuals with EP had fewer years of education, more often lived alone, and had lower dietary fibre intake (Table 1 ). Table 1 Baseline population characteristics according to presence or absence of epilepsy Characteristic Overall, N = 164,203,933 n = 11828 NO EP, N = 163,143,080 n = 11735 EP, N = 1,060,853 n = 93 p-value 1 Sex, n (unweighted) (%) 0.74 Male 5,945 (50.50%) 5,902 (50.48%) 43 (52.97%) Female 5,883 (49.50%) 5,833 (49.52%) 50 (47.03%) Age,year 0.32 Mean (mean.std.error) 48.04 (0.45) 48.06 (0.45) 44.04 (4.27) Median (IQR) 48.00 (33.00, 61.00) 48.00 (33.00, 61.00) 41.28 (25.49, 59.00) Age, year(unweighted) (%) 0.33 20-<40 3,848 (36.32%) 3,823 (36.24%) 25 (48.34%) 40-=65 2,713 (20.34%) 2,690 (20.37%) 23 (15.98%) Race/ethnicity, n (unweighted) (%) 0.78 Non-Hispanic white 4,425 (65.22%) 4,388 (65.24%) 37 (62.09%) Non-Hispanic black 2,778 (10.62%) 2,757 (10.61%) 21 (12.79%) Mexican American 1,621 (8.45%) 1,608 (8.43%) 13 (11.58%) Others 3,004 (15.70%) 2,982 (15.71%) 22 (13.54%) Education level(year), n (unweighted) (%) 0.008 < 9 912 (3.22%) 906 (3.19%) 6 (8.10%) 9-=12 6,805 (64.64%) 6,765 (64.82%) 40 (37.25%) Marital status, n (unweighted) (%) < 0.001 Married or living with a partner 7,044 (63.63%) 7,004 (63.81%) 40 (34.79%) Living alone 4,784 (36.37%) 4,731 (36.19%) 53 (65.21%) Family income, n (unweighted) (%) 0.25 Low 3,533 (19.63%) 3,491 (19.53%) 42 (34.50%) Medium 4,654 (35.70%) 4,618 (35.72%) 36 (33.25%) High 3,641 (44.67%) 3,626 (44.75%) 15 (32.26%) Dietary supplements taken, n (unweighted) (%) 0.62 No 5,436 (41.99%) 5,398 (42.03%) 38 (35.96%) Yes 6,392 (58.01%) 6,337 (57.97%) 55 (64.04%) Physical activity n (unweighted) (%) 0.35 Basic inactivity 3,291 (20.85%) 3,255 (20.77%) 36 (32.50%) moderate activity 3,113 (27.30%) 3,085 (27.32%) 28 (24.13%) vigorous activity 5,424 (51.85%) 5,395 (51.91%) 29 (43.36%) Smoking status, n (unweighted) (%) 0.73 Never 6,667 (56.66%) 6,622 (56.63%) 45 (62.19%) Current 2,874 (25.83%) 2,847 (25.84%) 27 (23.48%) Former 2,287 (17.51%) 2,266 (17.53%) 21 (14.33%) Alcohol intake, n (unweighted) (%) 0.79 No 8,552 (67.41%) 8,472 (67.43%) 80 (64.38%) Yes 3,276 (32.59%) 3,263 (32.57%) 13 (35.62%) Body mass index(kg/m2) (unweighted) (%) 0.51 =25 8,779 (73.86%) 8,708 (73.83%) 71 (78.29%) Chronic comorbidities, n (unweighted) (%) 0.75 No 6,067 (55.44%) 6,036 (55.46%) 31 (52.67%) Yes 5,761 (44.56%) 5,699 (44.54%) 62 (47.33%) Fiber,mg/d < 0.001 Mean (mean.std.error) 16.84 (0.24) 16.86 (0.25) 12.93 (1.07) Median (IQR) 15.15 (10.55, 21.20) 15.15 (10.60, 21.20) 9.00 (8.33, 17.16) 1 chi-squared test with Rao & Scott's second-order correction; Wilcoxon rank-sum test for complex survey samples;N is the data of the weighted representative US population, and n is the unweighted data. 3.3 Dietary fibre intake and risk for EP Table 2 presents the multivariate logistic regression analysis results on the association between dietary fiber intake and EP risk.In the unadjusted model, analyzing dietary fiber intake as a continuous variable revealed a significant inverse association with EP risk (OR 0.44, 95% CI 0.29–0.67; P < 0.001).Stratification by dietary fiber intake quartiles revealed a reduced risk of EP in the high-intake group compared to the low-intake group (OR 0.24, 95% CI 0.12–0.49; P < 0.001).In model 1, after accounting for demographic factors such as sex, age, race, education, marital status, and household income, the inverse relationship between dietary fiber intake and EP risk persisted as a continuous variable (OR 0.52 [95% CI 0.33–0.80]; P = 0.004), maintaining statistical significance.Stratifying by dietary fiber intake quartiles revealed a reduced EP risk in the high-intake group compared to the low-intake group (OR 0.30, 95% CI 0.14–0.62; P = 0.002).In model 2, after adjusting for demographic factors, smoking, alcohol consumption, BMI, physical activity, and dietary supplements, dietary fiber intake as a continuous variable was still inversely related to EP risk (OR 0.45 [95% CI 0.27–0.75]; P = 0.003).Stratification by dietary fiber intake quartiles revealed a significantly lower risk of EP in the high-intake group compared to the low-intake group (OR 0.27, 95% CI 0.12–0.60; P = 0.002).Model 3 builds on model 2 by incorporating chronic comorbidities, including diabetes, hypertension, arthritis, coronary heart disease, and stroke, to thoroughly adjust the covariates.The adjusted analysis confirmed a consistent inverse association between dietary fiber intake and EP risk (OR 0.45, 95% CI 0.27–0.76, P = 0.004).Stratification by dietary fiber intake quartiles revealed a reduced risk of EP in the high-intake group compared to the low-intake group (OR 0.27, 95% CI 0.12–0.61, P = 0.003).The relationship between dietary fibre intake and risk for developing EP according to RCS analysis is reported in Fig. 2.After accounting for all confounding variables, an inverse relationship was observed between dietary fiber intake and EP risk, with no evidence of nonlinearity (P = 0.97). Table 2 logistic regression analysis of the association between dietary fiber intake and the risk of epilepsy Modle 1:adjusted for sex, age, race, EDU, marital and PIR Modle 2:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake,PA and BMI Modle 3:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake, PA,BMI and Chronic comorbidities Abbreviations:CI,confidence interwval;OR,odds ratios;BMI,body mass index;PIR,Family income;SUPP,Dietary supplements taken;EDU,Education level；PA,Physical activity 3.4 Subgroup analyses Stratified analyses with P-interaction tests were employed to evaluate the consistency of the association between dietary fiber intake and EP risk across different populations, determining the statistical significance of subgroup differences. Figure 3 illustrates that dietary fiber intake is significantly inversely associated with EP risk across various subgroups, including sex, age, race, marital status, education, household income, smoking status, alcohol consumption, physical activity, BMI, dietary supplement use, and chronic comorbidities.Demographic characteristics include female sex (OR 0.53, 95% CI 0.31–0.92), age groups 20 to < 40 years (OR 0.41, 95% CI 0.20–0.83) and 40 to ≤ 65 years (OR 0.42, 95% CI 0.20–0.87), and non-Hispanic white race (OR 0.33, 95% CI 0.14–0.78).Socioeconomic factors: Nine to < 12 years of education (OR 0.34 [95% CI 0.14–0.81]), living alone (OR 0.35 [95% CI 0.17–0.70]); and high family income (OR 0.38 [95% CI 0.20–0.72]).Behavior and health factors such as taking dietary supplements (OR 0.54, 95% CI 0.31–0.94), alcohol consumption (OR 0.26, 95% CI 0.14–0.48), engaging in vigorous physical activity (OR 0.34, 95% CI 0.22–0.53), being overweight or obese (BMI ≥ 25 kg/m2, OR 0.46, 95% CI 0.25–0.85; P < 0.05), and absence of chronic complications (OR 0.29, 95% CI 0.11–0.81) were analyzed.After adjusting for confounding factors, the protective effect of dietary fibre remained significant (OR 0.45 [95% CI 0.27–0.76]).However, among individuals > 65 years of age, the OR was > 1 (1.74, 95% CI 0.75–4.03), suggesting that there may be heterogeneity in this group, which may be explained by differences in physiological metabolism in the elderly population, the interference of comorbidities, or the small sample size.However, further studies are required to confirm these findings.The data appeared abnormal for education levels below 9 years, likely due to the small sample size in this group (n = 6).Likelihood ratio tests revealed no statistically significant interactions among subgroups, indicating a consistent protective effect of dietary fiber across populations. 3.5 Sensitivity analyses After excluding 152 individuals with extreme energy expenditure, the inverse association between dietary fibre and risk for EP remained stable.In the unadjusted model, the odds ratio (OR) for dietary fiber intake associated with the risk of EP was 0.41 (95% confidence interval [CI]: 0.27–0.64; P < 0.001).In adjusted model 1, the OR was 0.49 (95% CI 0.31–0.79; P = 0.004); in model 2, it was 0.42 (95% CI 0.24–0.73; P = 0.003); and in the fully adjusted model, it remained 0.42 (95% CI 0.24–0.74; P = 0.004) (Table 3 ). Table 3 Association between Dietary Fiber intake and EP risk in participants with extreme energy consumption was not included. Variable n.total n.event_% ln fiber OR(95%CI) p-value Unadjusted 11676 91(0.8) 0.41(0.27–0.64) < 0.001 Modle 1 11676 91(0.8) 0.49 (0.31 ~ 0.79) 0.004 Modle 2 11676 91(0.8) 0.42(0.24 ~ 0.73) 0.003 Modle 3 11676 91(0.8) 0.42 (0.24 ~ 0.74) 0.004 Modle 1:adjusted for sex, age, race, EDU, marital and PIR Modle 2:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake,PA and BMI Modle 3:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake, PA,BMI and Chronic comorbidities Abbreviations:CI,confidence interwval;OR,odds ratios;BMI,body mass index;PIR,Family income;SUPP,Dietary supplements taken;EDU,Education level;PA,Physical activity 4 Discussion The study identified a low dietary fiber intake among EP patients and an inverse relationship between fiber consumption and EP risk.Subgroup analysis identified dietary fiber as a significant protective factor for women, particularly those who are young to middle-aged, non-Hispanic white, possess a medium educational level, live alone, have a high family income, use dietary supplements, consume alcohol, engage in vigorous physical activity, are overweight or obese, and do not have chronic comorbidities.It was also a protective factor in other subgroups; however, there may have been heterogeneity in the subgroups of individuals > 65 years of age.In addition, RCS analysis revealed an inverse relationship between dietary fibre intake and risk for EP, without a nonlinear association. In 2009, the Codex Alimentarius Commission defined dietary fiber as a carbohydrate polymer with ten or more monomer units that is not digested or absorbed in the human small intestine.Some oligosaccharides (such as fructo-oligosaccharide [FOS] and galacto-oligosaccharide [GOS], usually containing 3–9 monomers) recognised to have physiological functions as dietary fibre are also included in the category of dietary fibre.Dietary fibre is not a single substance but a large group of compounds with diverse structures.The main components include the following: non-starch polysaccharides (cellulose, hemicellulose, pectin, gum, mucus, seaweed polysaccharides); resistant starches (oligosaccharides such as FOS, GOS, inulin, etc.); lignin, a non-carbohydrate; and some specific modified or synthetic substances (resistant dextrin, polyglucose, etc.).Dietary fibre can prolong food transport time, delay nutrient absorption, increase faecal volume, and slow the absorption of glucose, lipids, and cholesterol ( 17 ).Dietary fiber undergoes fermentation by intestinal bacteria to produce short-chain fatty acids (SCFA), which are vital for human metabolic processes ( 28 ). As early as 1953, Hipsley ( 29 ) proposed that higher dietary fibre intake may reduce the risk for pregnancy toxaemia, also known as pre-eclampsia.A case-control study by Szałwińska et al.( 30 ) revealed that plant products were consumed much less frequently by patients with EP than by healthy individuals, and were the main source of dietary fibre.Zhang et al. conducted a cross-sectional study.Similar to the findings of this study, ( 17 ) observed that individuals with high dietary fiber intake had a lower risk of seizure events.However, the sample data obtained for this study was weighted to represent the entire U.S. population, which was more rigorous and broader than previous studies.A meta-analysis in The Lancet( 31 ), encompassing 185 prospective studies and 58 clinical trials with 135 million participants, found that high dietary fiber intake significantly reduced all-cause and cardiovascular mortality, coronary heart disease, stroke incidence and mortality, type 2 diabetes, and colorectal cancer incidence by 15 to 30%, along with notable decreases in body weight, systolic blood pressure, and total cholesterol.Prior research indicates a correlation between EP and both metabolic syndrome and overweight conditions ( 18 ). Nevertheless, the mechanisms underlying the inverse association between dietary fibre and EP remain unclear, although neuroinflammation may be an underlying mechanism.Recent studies have suggested that inflammatory processes in the brain are key mechanisms in epileptogenesis ( 32 , 33 ).The relationship between neuroinflammation and EP is bidirectional—it is not only the cause of EP but also the result of an abnormal immune status caused by seizures.Chronic inflammation involving tumour necrosis factor (TNF)-α or interleukin (IL)-6 can induce seizures( 34 ), with TNF-α-driven astrocyte signaling enhancing hippocampal excitability in temporal lobe epilepsy( 35 ).External factors that promote inflammation can initiate, sustain, or worsen neuroinflammation due to its regulation through multiple pathways ( 36 ).Short-chain fatty acids (SCFA), produced from dietary fiber fermentation by bacteria, play a crucial role in regulating immunity and inflammation ( 37 ).SCFA include acetate, propionate and butyrate ( 38 ).Butyrate can physically enhance intestinal barrier function and combine with G protein-coupled receptors to play an anti-inflammatory role ( 39 ).In one study, butyrate administration reduced IL-17 levels in test rats ( 40 ).Butyrate inhibits histone deacetylase (HDAC) to reduce the production of proinflammatory cytokines IL-6 and IL-12 in colonic macrophages within the lamina propria, and modulates nitric oxide production to regulate the antimicrobial activity of lipopolysaccharide-stimulated macrophages ( 41 , 42 ).In primary microglia and astrocyte cultures, acetate diminishes inflammatory signaling, leading to decreased IL-6 and TNF-α expression and interference with MAPK and NF-κB pathways ( 43 ).Therefore, we suggest that neuroinflammation may serve as a bridge between EP and dietary fibre. In contrast, oxidative stress may also be one of the mechanisms involved in EP.Oxidative stress is the imbalance between the production and elimination of reactive oxygen species (ROS) in the body ( 44 ).Excessive ROS can lead to neuronal damage, changes in synaptic plasticity, dysfunction of neural conduction, and increase the risk for seizures ( 9 ).Studies have shown that the excessive production of ROS in EP exceeds the capacity of endogenous antioxidants, leading to the accumulation of hydrogen peroxide (H2O2) and superoxide anions ( 45 ), which can damage cell function and alter the structure and activity of key enzymes such as Na+-K+-ATPase ( 46 ).ROS can also oxidise membrane lipids, destroy cell membrane permeability, and promote the generation of malondialdehyde and other harmful products ( 47 ).Myeloperoxidase (MPO) is a key inflammatory enzyme that catalyses the transformation of H2O2 and Cl– and releases cytotoxic substances ( 48 ).These changes can result in excessive neuronal excitation and EP.Recent research indicates that SCFA can activate the Keap1-Nrf signaling pathway, a key regulator of REDOX homeostasis, to mitigate oxidative stress ( 49 ).Propionate reduces MPO levels in the colon and serum of mice induced by dextran sulphate sodium, while increasing catalase and superoxide dismutase levels ( 50 ).Butyrate promotes epigenetic regulation by inhibiting HDAC and facilitating Nrf2 nuclear translocation, exhibiting antioxidant properties with therapeutic benefits in animal models of neurological diseases( 51 ). The study faced certain limitations.The cross-sectional survey's inherent limitations prevent causal inference( 52 ), necessitating further longitudinal studies.Second, as the database in this study focused solely on U.S. adults, further research with larger, more diverse global samples is necessary to validate our findings.Future studies should consider other potential confounding factors between dietary fiber and EP to validate the current findings. 5 Conclusions A comprehensive cross-sectional study of U.S. adults aged 20 and above found that higher dietary fiber intake was linked to a 55% decrease in EP risk per unit increase in ln-transformed fiber intake. However, this association varied among individuals older than 65.This may be explained differences in physiological metabolism in the elderly population, interference of comorbidities, or the small sample size and, as such, requires further research for verification. Declarations Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest . Funding Author Contribution Conceptualization, L.Z.; methodology,L.Z.; software, L.Z.; validation, L.Z. ; formal analysis, L.Z. ; investigation, L.Z..; resources, L.Z.; data curation,L.Z..;writing—original draft preparation,L.Z. ; writing—review and editing, L.Z.; visualization, L.Z..; supervision, L.Z.; project administration, L.Z.; author have read and agreed to the published version of the manuscript. Acknowledgments We are grateful to Yang Shaojie, Director of the Department of Neurology, Chengdu Eighth People's Hospital, for his contributions in statistical support and consultation on study design. Data Availability Publicly available datasets are available online for this study. 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El-Sayed YY. Obstetric and gynecologic care of women with epilepsy. Epilepsia. 1998;39(Suppl 8):S17–25. 10.1111/j.1528-1157.1998.tb02603.x . Lumley J, Watson L, Watson M, Bower C. Periconceptional supplementation with folate and/or multivitamins for preventing neural tube defects. Cochrane Database Syst Rev. 2000;CD001056. 10.1002/14651858.CD001056 . Ramezani F, Pourghazi F, Eslami M, Gholami M, Mohammadian Khonsari N, Ejtahed HS, et al. Dietary fiber intake and all-cause and cause-specific mortality: An updated systematic review and meta-analysis of prospective cohort studies. Clin Nutr. 2024;43:65–83. 10.1016/j.clnu.2023.11.005 . Kim Y, Je Y. Dietary fiber intake and total mortality: a meta-analysis of prospective cohort studies. Am J Epidemiol. 2014;180:565–73. 10.1093/aje/kwu174 . Threapleton DE, Greenwood DC, Evans CE, Cleghorn CL, Nykjaer C, Woodhead C, et al. Dietary fibre intake and risk of cardiovascular disease: systematic review and meta-analysis. BMJ. 2013;347:f6879. 10.1136/bmj.f6879 . Threapleton DE, Greenwood DC, Evans CE, Cleghorn CL, Nykjaer C, Woodhead C, et al. Dietary fiber intake and risk of first stroke: a systematic review and meta-analysis. Stroke. 2013;44:1360–8. 10.1161/STROKEAHA.111.000151 . Zhang YB, Xu Y, Zheng SF, Lin YX, Kang DZ, Yao PS. Association of dietary fiber intake with epileptic seizures in U.S. adults: A Population-base study of 13,277 participants. Seizure. 2024;122:1–9. 10.1016/j.seizure.2024.09.005 . Verrotti A, Manco R, Agostinelli S, Coppola G, Chiarelli F. The metabolic syndrome in overweight epileptic patients treated with valproic acid. Epilepsia. (2010) 51:268 – 73. 10.1111/j.1528-1167.2009.02206.x Gong R, Pu X, Cheng Z, Ding J, Chen Z, Wang Y. The association between serum cadmium and diabetes in the general population: A cross-sectional study from NHANES (1999–2020). Front Nutr. 2022;9:966500. 10.3389/fnut.2022.966500 . Liu H, Tan X, Liu Z, Ma X, Zheng Y, Zhu B et al. Association Between Diet-Related Inflammation and COPD: Findings From NHANES III. Front Nutr. (2021) 8:732099. 10.3389/fnut.2021.732099 Zeng Z, Cen Y, Wang L, Luo X. Association between dietary inflammatory index and Parkinson's disease from National Health and Nutrition Examination Survey (2003–2018): a cross-sectional study. Front Neurosci. 2023;17:1203979. 10.3389/fnins.2023.1203979 . Ding R, Han Z, Gui J, Xie L, Yang J, Yang X, et al. Inflammatory properties of diet mediate the effect of epilepsy on moderate to severe depression: Results from NHANES 2013–2018. J Affect Disord. 2023;331:175–83. 10.1016/j.jad.2023.03.054 . Zeng Z, Cen Y, Xiong L, Hong G, Luo Y, Luo X. Dietary Copper Intake and Risk of Parkinson's Disease: a Cross-sectional Study. Biol Trace Elem Res. 2024;202:955–64. 10.1007/s12011-023-03750-9 . Yang Z, Zhang J, Zheng Y. Higher vitamin B(6) dietary consumption is associated with a lower risk of glaucoma among United States adults. Front Nutr. 2024;11:1363539. 10.3389/fnut.2024.1363539 . Liu H, Wang L, Chen C, Dong Z, Yu S. Association between Dietary Niacin Intake and Migraine among American Adults: National Health and Nutrition Examination Survey. Nutrients. (2022) 14:3052. 10.3390/nu14153052 Ruan Z, Lu T, Chen Y, Yuan M, Yu H, Liu R, et al. Association Between Psoriasis and Nonalcoholic Fatty Liver Disease Among Outpatient US Adults. JAMA Dermatol. 2022;158:745–53. 10.1001/jamadermatol.2022.1609 . Fan Y, Zhao L, Deng Z, Li M, Huang Z, Zhu M, et al. Non-linear association between Mediterranean diet and depressive symptom in U.S. adults: A cross-sectional study. Front Psychiatry. 2022;13:936283. 10.3389/fpsyt.2022.936283 . Kalkan AE, BinMowyna MN, Raposo A, Ahmad MF, Ahmed F, Otayf AY et al. Beyond the Gut: Unveiling Butyrate's Global Health Impact Through Gut Health and Dysbiosis-Related Conditions: A Narrative Review. Nutrients. (2025) 17:1305. 10.3390/nu17081305 HIPSLEY EH. Dietary fibre and pregnancy toxaemia. Br Med J. 1953;2:420–2. 10.1136/bmj.2.4833.420 . Szałwińska K, Cyuńczyk M, Kochanowicz J, Witkowska AM. Dietary and lifestyle behavior in adults with epilepsy needs improvement: a case-control study from northeastern Poland. Nutr J. 2021;20:62. 10.1186/s12937-021-00704-6 . Reynolds A, Mann J, Cummings J, Winter N, Mete E, Te Morenga L. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. Lancet. 2019;393:434–45. 10.1016/S0140-6736(18)31809-9 . Vezzani A, Granata T. Brain inflammation in epilepsy: experimental and clinical evidence. Epilepsia. 2005;46:1724–43. 10.1111/j.1528-1167.2005.00298.x . Vezzani A, Baram TZ. New roles for interleukin-1 Beta in the mechanisms of epilepsy. Epilepsy Curr. (2007) 7:45–50. 10.1111/j.1535-7511.2007.00165.x Vezzani A. Epilepsy and inflammation in the brain: overview and pathophysiology. Epilepsy Curr. (2014) 14:3–7. 10.5698/1535-7511-14.s2.3 Parsons A, Bucknor E, Castroflorio E, Soares TR, Oliver PL, Rial D. The Interconnected Mechanisms of Oxidative Stress and Neuroinflammation in Epilepsy. Antioxidants (Basel). (2022) 11:157. 10.3390/antiox11010157 Pracucci E, Pillai V, Lamers D, Parra R, Landi S. Neuroinflammation: A Signature or a Cause of Epilepsy. Int J Mol Sci. 2021;22:6981. 10.3390/ijms22136981 . Gasaly N, de Vos P, Hermoso MA. Impact of Bacterial Metabolites on Gut Barrier Function and Host Immunity: A Focus on Bacterial Metabolism and Its Relevance for Intestinal Inflammation. Front Immunol. 2021;12:658354. 10.3389/fimmu.2021.658354 . Ríos-Covián D, Ruas-Madiedo P, Margolles A, Gueimonde M, de Los Reyes-Gavilán CG, Salazar N. Intestinal Short Chain Fatty Acids and their Link with Diet and Human Health. Front Microbiol. 2016;7:185. 10.3389/fmicb.2016.00185 . Siddiqui MT, Han Y, Shapiro D, West G, Fiocchi C, Cresci G. The Postbiotic Butyrate Mitigates Gut Mucosal Disruption Caused by Acute Ethanol Exposure. Int J Mol Sci. 2024;25:1665. 10.3390/ijms25031665 . Zhang M, Zhou Q, Dorfman RG, Huang X, Fan T, Zhang H, et al. Butyrate inhibits interleukin-17 and generates Tregs to ameliorate colorectal colitis in rats. BMC Gastroenterol. 2016;16:84. 10.1186/s12876-016-0500-x . Chang PV, Hao L, Offermanns S, Medzhitov R. The microbial metabolite butyrate regulates intestinal macrophage function via histone deacetylase inhibition. Proc Natl Acad Sci U S A. 2014;111:2247–52. 10.1073/pnas.1322269111 . Kibbie JJ, Dillon SM, Thompson TA, Purba CM, McCarter MD, Wilson CC. Butyrate directly decreases human gut lamina propria CD4 T cell function through histone deacetylase (HDAC) inhibition and GPR43 signaling. Immunobiology. 2021;226:152126. 10.1016/j.imbio.2021.152126 . Silva YP, Bernardi A, Frozza RL. The Role of Short-Chain Fatty Acids From Gut Microbiota in Gut-Brain Communication. Front Endocrinol (Lausanne). 2020;11:25. 10.3389/fendo.2020.00025 . Zorov DB, Juhaszova M, Sollott SJ. Mitochondrial reactive oxygen species (ROS) and ROS-induced ROS release. Physiol Rev. 2014;94:909–50. 10.1152/physrev.00026.2013 . Shin EJ, Jeong JH, Chung YH, Kim WK, Ko KH, Bach JH, et al. Role of oxidative stress in epileptic seizures. Neurochem Int. 2011;59:122–37. 10.1016/j.neuint.2011.03.025 . Stadtman ER. Protein oxidation in aging and age-related diseases. Ann N Y Acad Sci. 2001;928:22–38. 10.1111/j.1749-6632.2001.tb05632.x . Batty M, Bennett MR, Yu E. The Role of Oxidative Stress in Atherosclerosis. Cells. (2022) 11:3843. 10.3390/cells11233843 Shao C, Yuan J, Liu Y, Qin Y, Wang X, Gu J, et al. Epileptic brain fluorescent imaging reveals apigenin can relieve the myeloperoxidase-mediated oxidative stress and inhibit ferroptosis. Proc Natl Acad Sci U S A. 2020;117:10155–64. 10.1073/pnas.1917946117 . González-Bosch C, Boorman E, Zunszain PA, Mann GE. Short-chain fatty acids as modulators of redox signaling in health and disease. Redox Biol. 2021;47:102165. 10.1016/j.redox.2021.102165 . Tong LC, Wang Y, Wang ZB, Liu WY, Sun S, Li L, et al. Propionate Ameliorates Dextran Sodium Sulfate-Induced Colitis by Improving Intestinal Barrier Function and Reducing Inflammation and Oxidative Stress. Front Pharmacol. 2016;7:253. 10.3389/fphar.2016.00253 . Dong Y, Cui C. The role of short-chain fatty acids in central nervous system diseases. Mol Cell Biochem. (2022) 477:2595 – 607. 10.1007/s11010-022-04471-8 Wang X, Cheng Z, Cross-Sectional Studies. Strengths, Weaknesses, and Recommendations. Chest. (2020) 158:S65-65S71. 10.1016/j.chest.2020.03.012 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9256805","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":620038084,"identity":"eac6cf8a-7a47-4f07-871d-edbabbf88bb0","order_by":0,"name":"Ling Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYBAC++MNiQ8SKv7JkaDnzIHHBh/OHDAmQcsNx2eSM9sOJDYQrYNxBnOCNA/bnfS+4wmMHz7mEKGFWbotwZiH51nuzDMPmCVnbiNCC5vMmYRkHgnm3A03EtiYeYnRwiOR/+EwjwFzugHRWiQkEhIbZyQcTiBeiwHPgWSGDwfSDGeeedhMnF8M2BvSfyT+s5HnO5588MNHYrQgAClRA9OSQKqOUTAKRsEoGCkAAPTTPnVkRLDmAAAAAElFTkSuQmCC","orcid":"","institution":"Chengdu Eighth People's Hospital (Geriatric Hospital of Chengdu Medical College)","correspondingAuthor":true,"prefix":"","firstName":"Ling","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-03-29 06:24:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9256805/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9256805/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106750073,"identity":"73b1b3ba-0507-4ba3-868c-8e4caed6e57d","added_by":"auto","created_at":"2026-04-13 06:42:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121766,"visible":true,"origin":"","legend":"\u003cp\u003eThe study’s flow diagram.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9256805/v1/42482c3eb3b62d044c7f1e3c.png"},{"id":106750137,"identity":"617df2d1-5d70-40ea-9bf2-b8486f17afea","added_by":"auto","created_at":"2026-04-13 06:42:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60671,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation of dietary fiber intake \u0026nbsp;\u0026nbsp;with odds ratios for epilepsy：Solid and dashed lines indicate predicted \u0026nbsp;\u0026nbsp;values and 95% confidence intervals\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9256805/v1/a17e93ac41c81dddb8bd4d05.png"},{"id":106749860,"identity":"c5b8cce8-18a2-4213-8e3e-6fe68405d10c","added_by":"auto","created_at":"2026-04-13 06:41:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":201436,"visible":true,"origin":"","legend":"\u003cp\u003eStratified analysis of forest plots：Each stratification factor was adjusted for all other variables in the full model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9256805/v1/9908d700e15fd5259b5fc100.png"},{"id":106750215,"identity":"eac0f716-5d3e-4dba-b8bb-5dda1e61d182","added_by":"auto","created_at":"2026-04-13 06:43:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1367565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9256805/v1/1851b474-ea41-4ae4-8538-6fcad5527f78.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between dietary fiber intake and epilepsy risk: A cross- sectional analysis using weighted data from the National Health and Nutrition Examination Survey","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eEpilepsy (EP) is a chronic neurological disease caused by abnormal discharge of brain neurones, and affects nearly 70\u0026nbsp;million individuals worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).Although existing drug therapies can effectively control seizures in most patients, 30%\u0026ndash;40% of patients with refractory EP continue to exhibit a poor response to drug treatment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).Therefore, exploring the pathogenesis and factors influencing EP, and identifying new prevention and intervention strategies are important research directions in neuroscience.Recent studies have suggested that nutrient intake is associated with the pathogenesis of EP and that a ketogenic diet plays an anti-epileptic role by regulating metabolism and neuroinflammation (\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).Supplementation with B vitamins can reduce the frequency of seizures and risk for drug teratogenesis (\u003cspan additionalcitationids=\"CR8 CR9 CR10 CR11\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).As one of the four nutrients, dietary fibre has been shown to reduce the risk for a variety of chronic diseases and all-cause mortality by reducing postprandial blood glucose and cholesterol levels (\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).These factors are also closely associated the occurrence of EP (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).There is a lack of extensive research utilizing data from the general adult population in the United States to investigate the link between dietary fiber intake and EP risk.This study assessed the link between dietary fiber and EP among U.S. adults using weighted data from the National Health and Nutrition Examination Survey (NHANES).We hypothesized that increased dietary fiber intake might correlate with a reduced risk of EP and sought to investigate the impact of specific nutrients on EP.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003ch2\u003e2.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Data\u0026nbsp;source\u003c/h2\u003e\n\u003cp\u003eThis study is a cross-sectional study, and the data used were sourced from the National Health and NHANES websites in the United States. NHANES employs a stratified, multi-stage probability sampling method, and obtains comprehensive data through its research design, interviews, and demographic analysis (19-21).Public archives of four consecutive NHANES data cycles, from 2013 to March 2020, were used in this study.A multistage probability sampling design was employed to ensure a nationally representative survey sample for both data collection and research methodology.The study utilized data \u0026nbsp;obtained on March 20, 2024, from the NHANES website (https://www.cdc.gov/nchs/nhanes/index.htm), encompassing \u0026nbsp;respondent information from 2013 to 2020.Participants \u0026nbsp;\u0026le; 20 years of age, pregnant women, those with missing data regarding intake of dietary fibre, and those with missing covariate data were excluded.\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Diagnosis of EP\u003c/h2\u003e\n\u003cp\u003eEP-related information was collected through in-person interviews.Participants reported all medications prescribed in the previous 30 days and their indications.EP was identified by the use of one or \u0026nbsp;more medications classified under \u0026apos;unknown epilepsy or recurrent seizures\u0026apos; \u0026nbsp; according \u0026nbsp;to \u0026nbsp;ICD-10 code G40 (22).\u003c/p\u003e\n\u003ch2\u003e2.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Dietary fibre\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eDietary fiber intake data were sourced from the NHANES database, where participants provided 24-hour dietary recalls. \u0026nbsp;The first recall occurred at the NHANES Mobile Testing Center, and the second was conducted via telephone between days 3 and 10 (23, 24).The final dietary \u0026nbsp; fiber \u0026nbsp;intake for analysis was \u0026nbsp;determined by averaging the two recorded intakes to \u0026nbsp;ensure data \u0026nbsp;rigor.In this study, fibre referred to dietary fibre and did not include fibre supplements.\u003c/p\u003e\n\u003ch2\u003e2.4\u0026nbsp; \u0026nbsp; \u0026nbsp;Assessment of covariates\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eCovariates in this study were selected based on previous studies and statistical differences at baseline.The \u0026nbsp;study considered various covariates such \u0026nbsp;as age, sex, race, marital status, poverty income ratio (PIR), education level, body mass index (BMI), smoking and alcohol consumption status, physical activity, dietary supplementation, and chronic comorbidities.Patients were categorized into three age groups: under 40, 40 to 65, and over 65 years.Educational level was divided into three groups according to boundaries between 9 and 12 years.Marital status was categorized as either living alone or cohabiting with a partner.Race was classified into non-Hispanic white, Mexican American, non-Hispanic black, and other categories.According to a report by the U.S. government (25), PIR divides household income into three levels of low, medium and high with a cut-off value of 1.3 and 3.5.Based \u0026nbsp;on the smoking questionnaire, individuals were classified as non-smokers if they smoked fewer than 100 cigarettes and as smokers if they smoked 100 or more cigarettes.Alcohol consumption was obtained from the alcohol content reported in the two dietary intake questionnaires.If the two sets of data were zero, participants were considered to be non-drinkers and, if they were \u0026gt; 0, they were considered to be drinkers.Physical activity was classified as basic, moderate, or vigorous.Dietary supplement use was assessed using a questionnaire that asked participants whether they had taken a dietary supplement in the previous month.BMI was determined by dividing weight in kilograms by the square of height in meters and categorized into two groups using a 25 kg/m\u0026sup2; threshold.Chronic comorbidities (comorbidities) were also obtained from the questionnaire, which asked whether a physician had told participants about their disease.Five common chronic diseases were selected from among the participants, with hypertension, diabetes, stroke, coronary heart disease, or chronic arthritis considered to be chronic comorbidities.\u003c/p\u003e\n\u003ch2\u003e2.5\u0026nbsp; \u0026nbsp; \u0026nbsp;Statistical analyses\u003c/h2\u003e\n\u003cp\u003eIn this study, weighted logistic regression analysis was conducted using the NHANES sampling weights (WTINT2YR) to address the complex survey design, which included stratification (SDMVSTRA), clustering (SDMVPSU), and handling of specific subgroups.Data from the first 24 h and second 24 h samples were weighted so that they were representative of the entire U.S. population.The Kolmogorov\u0026ndash;Smirnov test was employed in this study to assess the normality \u0026nbsp;of continuous variables.Given the skewed distribution of dietary fibre intake, natural logarithmic transformation (ln) was used to generate a normal distribution.Variables with a normal distribution are presented as mean \u0026plusmn; standard deviation (SD), skewed variables as median (interquartile range [IQR]), and categorical variables as percentages.For \u0026nbsp;normally distributed \u0026nbsp;data, one-way \u0026nbsp;ANOVA was applied, while the Kruskal\u0026ndash;Wallis test was utilized for skewed distributions.The chi-squared test was used to compare categorical variables.\u003c/p\u003e\n\u003cp\u003eParticipants were categorized into four groups according \u0026nbsp;to ln-transformed quartiles of dietary fiber intake: lowest (-1.61 to \u0026lt;2.30, \u0026nbsp;n=2943), low (2.30 to \u0026lt;2.69, \u0026nbsp;n=2970), high (2.69 to \u0026lt;3.04, \u0026nbsp;n=2949), and highest (3.04 to 4.64, \u0026nbsp;n=2966), with the lowest quartile serving as the reference.Logistic regression was employed to calculate the odds ratio (OR) and 95% confidence interval (CI) to evaluate the link between dietary fiber intake and EP risk.Logistic regression analyses were performed using dietary fibre intake as continuous and categorical variables.Model 1 was controlled for sociodemographic variables such \u0026nbsp;as age, sex, race, education, marital status, and household income.Model 2 was adjusted for sociodemographic factors, BMI, smoking, alcohol use, physical activity, and dietary supplements.Model 3 was refined from Model 2 by incorporating adjustments for chronic comorbidities, \u0026nbsp; including hypertension, coronary heart disease, stroke, diabetes, and arthritis.\u003c/p\u003e\n\u003cp\u003eRestricted cubic spline (RCS) testing was used to determine whether there was a quantitative relationship between dietary fibre and the risk for EP.To ensure accuracy, the RCS tests were performed using raw data without ln transformation.Model 3 incorporated all covariates to create \u0026nbsp;a \u0026nbsp; smooth curve-fitting \u0026nbsp;plot \u0026nbsp;using dietary \u0026nbsp; fiber \u0026nbsp;intake distribution nodes at \u0026nbsp;the 5th, 35th, 65th, and 95th percentiles.Interaction and subgroup analyses based \u0026nbsp;on age, sex, race, education, marital status, household income, smoking, alcohol use, physical activity, BMI, dietary supplementation, and chronic comorbidities were conducted using a logistic regression model.Sensitivity analyses were conducted to evaluate the robustness of the findings by excluding participants with extreme daily energy intake (\u0026lt; 500 kcal or \u0026gt; 5000 kcal).\u003c/p\u003e\n\u003cp\u003eThis study\u0026apos;s sample size was solely \u0026nbsp;based on the NHANES database, \u0026nbsp;so \u0026nbsp;no prior statistical performance estimates were conducted.The statistical analysis in this study was \u0026nbsp;conducted using R software version 4.3.3 and Free Statistics software(26) version 2.1.1.A descriptive study was performed on all participants.All statistical tests were two-tailed, with significance set at P\u0026lt;0.05.\u003c/p\u003e\n\u003ch2\u003e2.6\u0026nbsp; \u0026nbsp; \u0026nbsp;Human ethics and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe NHANES study protocol was approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board. All participants provided written informed consent (27). The present study is a secondary analysis of de‑identified publicly available data; therefore, no additional ethical approval was required.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e3.1 Study population\u003c/p\u003e\n\u003cp\u003eThis study used data collected between 2013 and March 2020.In the preliminary data, 35,706 individuals participated in the survey, of whom 14,986 who were \u0026lt;\u0026thinsp;20 years of age and were excluded.Of 20,720 adults, 222 who were pregnant, 2934 with missing dietary fibre intake data, and 5736 with other missing covariates were excluded.Of the 11,828 participants with complete data, 93 had confirmed EP.The exclusion and inclusion processes are illustrated in Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e3.2 Demographic characteristics\u003c/p\u003e\n\u003cp\u003eThe study included 11,828 patients with complete data regarding dietary fibre intake and EP, weighted to represent 164,203,933 U.S. adults, of whom 93 had definite EP (weighted percentage, 0.06%), weighted to represent 1,060,853 U.S. adults.The mean median age of the participants was 48 years (IQR 33 to 61 years), 5883 were women (weighted percentage, 49.5%), 4425 were non-Hispanic white (weighted percentage, 65.22%), and those with \u0026gt;\u0026thinsp;12 years of education had a weighted percentage 64.64%.At baseline, individuals with EP had fewer years of education, more often lived alone, and had lower dietary fibre intake (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline population characteristics according to presence or absence of epilepsy\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eOverall,\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164,203,933\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;11828\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eNO EP,\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;163,143,080\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;11735\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eEP,\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,060,853\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;93\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ep-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,945 (50.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,902 (50.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e43 (52.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,883 (49.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,833 (49.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e50 (47.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge,year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMean (mean.std.error)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e48.04 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e48.06 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e44.04 (4.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e48.00 (33.00, 61.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e48.00 (33.00, 61.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e41.28 (25.49, 59.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, year(unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e20-\u0026lt;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,848 (36.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,823 (36.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e25 (48.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e40-\u0026lt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,267 (43.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,222 (43.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e45 (35.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;=65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2,713 (20.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2,690 (20.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e23 (15.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/ethnicity, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNon-Hispanic white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4,425 (65.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e4,388 (65.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e37 (62.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNon-Hispanic black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2,778 (10.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2,757 (10.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e21 (12.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e1,621 (8.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e1,608 (8.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e13 (11.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,004 (15.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2,982 (15.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e22 (13.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level(year), n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e912 (3.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e906 (3.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e6 (8.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e9-\u0026lt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4,111 (32.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e4,064 (31.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e47 (54.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;=12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6,805 (64.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e6,765 (64.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e40 (37.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMarried or living with a partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e7,044 (63.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e7,004 (63.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e40 (34.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4,784 (36.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e4,731 (36.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e53 (65.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily income, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,533 (19.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,491 (19.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e42 (34.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e4,654 (35.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e4,618 (35.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e36 (33.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,641 (44.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,626 (44.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e15 (32.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary supplements taken, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,436 (41.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,398 (42.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e38 (35.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6,392 (58.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e6,337 (57.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e55 (64.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activity n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBasic inactivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,291 (20.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,255 (20.77%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e36 (32.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003emoderate activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,113 (27.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,085 (27.32%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e28 (24.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003evigorous activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,424 (51.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,395 (51.91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e29 (43.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6,667 (56.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e6,622 (56.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e45 (62.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2,874 (25.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2,847 (25.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e27 (23.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2,287 (17.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e2,266 (17.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e21 (14.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol intake, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8,552 (67.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e8,472 (67.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e80 (64.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,276 (32.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,263 (32.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e13 (35.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index(kg/m2) (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3,049 (26.14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e3,027 (26.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e22 (21.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026gt;=25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8,779 (73.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e8,708 (73.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e71 (78.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic comorbidities, n (unweighted) (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e6,067 (55.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e6,036 (55.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e31 (52.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e5,761 (44.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5,699 (44.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e62 (47.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eFiber,mg/d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMean (mean.std.error)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e16.84 (0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e16.86 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e12.93 (1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e15.15 (10.55, 21.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e15.15 (10.60, 21.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e9.00 (8.33, 17.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003echi-squared test with Rao \u0026amp; Scott\u0026apos;s second-order correction; Wilcoxon rank-sum test for complex survey samples;N is the data of the weighted representative US population, and n is the unweighted data.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e3.3 Dietary fibre intake and risk for EP\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the multivariate logistic regression analysis results on the association between dietary fiber intake and EP risk.In the unadjusted model, analyzing dietary fiber intake as a continuous variable revealed a significant inverse association with EP risk (OR 0.44, 95% CI 0.29\u0026ndash;0.67; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).Stratification by dietary fiber intake quartiles revealed a reduced risk of EP in the high-intake group compared to the low-intake group (OR 0.24, 95% CI 0.12\u0026ndash;0.49; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).In model 1, after accounting for demographic factors such as sex, age, race, education, marital status, and household income, the inverse relationship between dietary fiber intake and EP risk persisted as a continuous variable (OR 0.52 [95% CI 0.33\u0026ndash;0.80]; P\u0026thinsp;=\u0026thinsp;0.004), maintaining statistical significance.Stratifying by dietary fiber intake quartiles revealed a reduced EP risk in the high-intake group compared to the low-intake group (OR 0.30, 95% CI 0.14\u0026ndash;0.62; P\u0026thinsp;=\u0026thinsp;0.002).In model 2, after adjusting for demographic factors, smoking, alcohol consumption, BMI, physical activity, and dietary supplements, dietary fiber intake as a continuous variable was still inversely related to EP risk (OR 0.45 [95% CI 0.27\u0026ndash;0.75]; P\u0026thinsp;=\u0026thinsp;0.003).Stratification by dietary fiber intake quartiles revealed a significantly lower risk of EP in the high-intake group compared to the low-intake group (OR 0.27, 95% CI 0.12\u0026ndash;0.60; P\u0026thinsp;=\u0026thinsp;0.002).Model 3 builds on model 2 by incorporating chronic comorbidities, including diabetes, hypertension, arthritis, coronary heart disease, and stroke, to thoroughly adjust the covariates.The adjusted analysis confirmed a consistent inverse association between dietary fiber intake and EP risk (OR 0.45, 95% CI 0.27\u0026ndash;0.76, P\u0026thinsp;=\u0026thinsp;0.004).Stratification by dietary fiber intake quartiles revealed a reduced risk of EP in the high-intake group compared to the low-intake group (OR 0.27, 95% CI 0.12\u0026ndash;0.61, P\u0026thinsp;=\u0026thinsp;0.003).The relationship between dietary fibre intake and risk for developing EP according to RCS analysis is reported in Fig. 2.After accounting for all confounding variables, an inverse relationship was observed between dietary fiber intake and EP risk, with no evidence of nonlinearity (P\u0026thinsp;=\u0026thinsp;0.97).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003eTable 2 \u0026nbsp;logistic regression analysis of the association between dietary fiber intake and the risk of epilepsy\u003c/div\u003e\n \u003cp\u003e\u003cimg 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xHYQhJQyFEVbIj9b72j/5lm/cKUtIPTkxZnfkTpIwSr5ICy7euWVriiKhETJ8VzN6axdtFvkhG1UiEbWk9qCPixeuEAgEAgEAoG+hUCQEH3rezZXbVpKyzTZntOW2zb/rSZafWrjGQ+BQCAQCIwEAhRuCpdV+2oyShUTfCvCVf+evGe14KcxrTJTtpynUPv+oijSRhttVJq8M1NnNZbj1J6ZwL8oiiQeSwvPVWebQvV5ZO9ZKlDYjctIYgroKqus0m429cb1epHrlYs1hBXzoihSvXrWy6e7/apbSPK74IG0QSxkv86ulG0EWI6HOEDIsw4pirakQI4zOlffSN6sL1h1HHbYYYmlDuvCouj8fZ9++mm5DSSXQXlZ78izKDpPn9N1dEWIyM9WK8Qcwot1iPNXbBdCtHWUPsICgUAgEAgEmg+BICGa75uNkRL3diZMkq3gWLFcYIEFyn2fhKXBgwenwRXX2+WM9wcCgUDzIWDl+jvf+U6yVYJZOJNwVgzVscX9wIEDe6VyLDNsN0G2GvcoXO0pWhRdk2th1wAAEABJREFUJvNWpp1TQElTaAQLSwlKrbpUnTMExKk6GIhvG13V34p29bm9e5YFQ4YMSQ6htFWiPfP/nJ6lgHur6a7ZscioKvR+VYO1gW0l1Tq4l2bOOecszwBhru+Zsy3H9gj33e1Yptg6YctAraUC6wVbcTqzesllhJnvzNIj+yHIWMVoCywJWTywXsjhroiaKnHBr6vOd7fNRP4IKttHbEvpimWJbTtwri2v9ut72eah7tpGtTwjU17EGgxZc8jD1iLfntPObI/iHy4QCAQCgUCgbyEQJETPf8+mf6MVMKayhEkCsL3VhBIHZg0fPjzZYmEfqf3NKktIsX/UYVzCCaUESoJQURSJEIqIIHwI55jm2i/KTFN+DhcjrBFICDjyDRcIBAJ9EwGr3/q6PevOjTEmUIZcncNg/BBmfKC4IR2MMcKdMWD7gq0VVqiZ8rMMsN/d/nVxONu7oEcBpNQyU+dvHONf62zdoHQah1gCiMsphzBXYdIZI5VfODN4iiWFTXrjonvkwvXXX5/E8Ws/FC5pjaX8mPkjDdTNmOfgSyvYfk1B3cSVhhLnWRqOn+0mwqvOFjiryrZ3IDLEdZaD7XBWu71X2WABEziLk+skr+233z5RhtV/jjnm4FU62xGU14PySl8URWI1YZ+/8zLkxeLDWQ3M9cXxPlsRHFzIBN+8Id6wYcMSSxH1R9Io35AWAkS4czx8a98eLrYafPDBB15dOmmQGhRn9+YneXLOflAfZdTGJPCtzC++nzZmpT+3BWnUF/lD6Wb1wI9zloRtCbZByCc77/R+7+Ln/bamKC9STBp1sc1EPg71lMa2nKIoyp8eRXbATX2dicEiAF7mXPV177tJpy8gNqTxvlqnXjBDRhRFkWApjXdL79uZY2EpH+2A9ZB8nFeBrPB+bVca87ctFQiVoviqvHDzzZT3b3/7W3LmEz+LDd5VLRsM5MOZ81nYsPYpiiL51vyzs0VJm7NlRXnCBQKBQCAQCPQdBAb0nap0pSYRZ0wgQOAjiNjv62wGAk7eH+xn3ZxoTZAleBK2CRiEXwIoYZlQwvSYIKo8hCN7izfccMMknHNKuZPgxSV8W80kDDEldfildOECgUCgbyJgtV1fZ5ZtnDAmODkfMcl0nVJirKHc2ZePdKCYiWeln+KSlWQEgNVfJ/BbzRaHs/+dcnTaaaeVv+ZjnOJP8amHql8iEIbQoFyJK1/5O9RP/g6PlNYzBUscShmi1eGM8vBeJK7xkSWGOJRWY6TDexES/JAJVoMpwfbHi+PMB6vZlDQkh18VopB7loYznnq3ctS6Qw89NFEojd3iws57xTemw1T5kDes1MSp3ZMvvcMtnROR86eA5vJSYGGqvH6pQz0RAvJCGMmfsumgT+8ztosPH3iKR/GmrBZFkVhUqL8zBYQjMcT1S0lIAfkhqnJZEOMUeDhqP4gOeXLmI2SCMGSVNLYWIEH8Uon2gaxx8DIiXBpkgrbkEEZl4sexLqhH9ng/cumCCy5IiAVKvUMktVXvswVHucx58kFgOTzSFiHh3sUf2aC+2o/vhrRHQhx55JFJe/fNtRffTZvXTqSvdawUHEYJE/lyCDlkCGJBW/AtHCLqO5lvq0QcHJBf2q60SBrfA4nmXSxVkFnavvLK88QTT0wOopRWv0DqiMshPuTDwcIvZfDnbM/kn536aUPCwgUCgUAgEAj0LQR6joToW7j169pQCmylsJqWHYXBKen52dUp2gR0P+lGkODHEYAoElUQHX5FUBPOWWWyR9Rp6J6zI6wSlqpp4z4QCAT6FgIrrbRS+YsSud+7Uuhcq44CZOuBVXS/eCDM1gWKeC0iSE7h2VH2KMVWe7Ofq19hqE3r2eGRwjty+YwJq8Q5HqKWUo884Edptvr/ve99L3nmKJjGSff1nLRWn4uiKH/SUBzKuXI5P8Fzdn42kX97jgKc4zKD/+53v9taDspkDstXhwVW85J+zTXXrHolzzm+K0yVVyRKJj+OUomgcd6DZ+8TBz7IDX6c9M4JEMbBC27CWEj47jk+kmO++eYTrXSICYSSuB05eEvgm+V46mZucnZC9vMLJOJxfsEi+/vlhqIY8UwE769ta5Ry7U0e5k8kWc4HCcS/6ljp5HDEm2+gXfPTzllfuM8OKYNMqeaR75EALFdy+pzGT+DKC0GR/VzFs3Upp59ssskSUkYY52yJHOaqvqwZhHEIBOU1/+dn31dcjl92VSJLGDkih7nCgX+4QCAQCAQCgSZFoINiBwnRATgRFAgEAoFAIBAIBAKBQLMi4Oc9/bIHUj/XAbHAsrCrh4fmdHENBAKBQCAQaB4EGr2kQUI0+heK8gUCgUAgEAgEAoFAIDAKCDhY08+g5u0atiDZdmHLJIuTUchylJLYdmIrhu0po5RBJAoEAoFAoHkQiJJ2AYEgIboAUkQJBAKBQCAQCAQCgUCg2RBwSKRDQ23rcC6T85uc+2DLSXWrSXfVi7WFczwQH0gIZ2/ce++93fW6yDcQCAT6PQIBQLMgECREs3ypKGcgEAgEAoFAIBAIBAIjgYBDR6tnUjh/yZkUDtl0JspIZDVaUZ2T4nBLW0FGK6NIHAgEAo2LQJQsEBgJBIKEGAmwImogEAgEAoFAIBAIBALNgoBfBPFLHoMHD06Dv3Z+GaOnyo/08Osa+d2ufpK7p94f7wkE+gsCUc9AoNkQCBKi2b5YlDcQCAQCgUAgEAgEAoFAIBAIBBoBgShDIBAIjAICQUKMAmiRJBAIBAKBQCAQCAQCgUAgEAgEehOBeHcgEAg0KwJBQjTrl4tyBwKBQCAQCAQCgUAgEAgEAr2BQLwzEAgEAoHRQCBIiNEAL5IGAoFAIBAIBAKBQCAQCAQCPYlAvCsQCAQCgWZHIEiIXviC77//fnr++efTZ5991q1vf+WVV9JDDz2UllpqqXT66aeP9rvuueeetNZaa7XJ5913300333xzWmWVVdIss8xSuu985ztpwgknTNtss02buN3x4Ce/3njjjfTqq6+mL774ojteEXkGAoFAIBAIBAKBQCAAgXCBQCAQCAQCYwCBICHGAIgjkwWl+aKLLkpzzz13evbZZ0cmaRn3zjvvLAmM8qGTP2effXb69a9/nR577LHkhOpOoncY/Oijj6bf/OY36bLLLmuN9+CDD6Y999wzXXrppemYY45JzzzzTOkeeeSRdPjhh6errrqqNe6Yuvnoo4/S3/72t/Tpp5+WWX788cdp//33L0/9fv3110u/+BMIBAKBQCAQCAQCfQ2BqE8gEAgEAoFAX0EgSIhe+JKLLrpoOu6449LUU089Um8fPnx42nHHHdOTTz7ZpXR77bVXOuGEE9JMM83UpfjtRfrf//6XTjnllLTrrru2RkGGKMukk06afvvb36Y555yzNWziiSdOO++8c1p66aVb/cbUzRlnnJFOPPHE1uy+9a1vpY033rh8n/e2BsRNIBAIBAKBQCAQCIwZBCKXQCAQCAQCgUBgDCIQJMQYBLMrWRVFkb73ve+VK/eTTDJJV5K0xkEGPPXUU2m88cZr9evspiiKkYpfL7977703vf322+m73/1uGWz7w/HHH19acgwZMqTd/MUpE4zBP7aEjD322ImTLRJiySWXTCuvvHIaf/zxeYULBAKBQCAQCAT6DAJRkUAgEAgEAoFAoK8hECRED3/RF154IV1xxRWlQv/EE08k2wlYOBx77LFp0003TVdffXV5rsL000+fnK3w2muvlSV866230n//+9/y3ANXaWxJ+PDDD9Pvf//7Mo0zGb797W+X2yDaO2/CGQ4sF2aeeeZyq4bMnVFx8cUXpx/+8Idp4MCB5fWvf/1r+vzzz9Mnn3ySbrnlljTddNOlbGngrAnWGEsssUSaYIIJZFHXTTnllKW/fJzZsPrqq5fl9G51c5aEOqij+rCmsFVl2223LeMhaQ499NASI/WB3XvvvZeUV3zPrieddFIaNGhQiQ+c+G222Wbp6KOPTgcffHCZl7I4o+KDDz5ItnRI+9Of/jQttNBCZRnVk98f//jHtNhii7Vam9g+YzvLRhttVGIDnwUWWCBdd9115ZkeL7/8crrkkkvSfPPNl/7zn/8k8ZE0MFNP39oL5C8Nq5RZZpmltE752c9+JihcIBAIBAKBQGMiEKUKBAKBQCAQCAQCgW5AIEiIbgC1oyydnWArBjLAKj7F95e//GVCQtx+++3pvvvuK89VuO222xJCYcMNNyyzu/HGG8utFUiLc889t1SuWUZQghEE+TwGRMaBBx6YnOFQJqz8QXpQsscdd9zynIj99tuvJBmcG4H8GDZsWKl877TTTumwww5L4lOeEQ5zzDFHq8UDRR4ZUMm6w9t///vfiRK/5pprlnV7/PHH089//vO02mqrlQq8MyUQDw7r/NOf/pS22267pD7OoECY/P3vf08U+4yRMOQCkuGggw5Kf/jDH9Lkk09eWkfcdNNNaffdd0/XXntteX7F4osvXuZ1zjnnpMsvvzzB7rnnnisJCiRILvhLL71U+vk2LE0crCns4YcfTjvssEN58CYclH299dYr3/GPf/wjOXfjtNNOS4gU8REuyAb48Ztmmml4J9927733Tvfff39ZHt8ZUVIGxp9AIBAIBAKBGgTiMRAIBAKBQCAQCAT6KgJBQvTwlz3yyCMTZXSKKaYo3zzbbLOV5y0sssgiiUNICLBabnXfKrzntddeuzz3wAGTlPMzzzwzTTvttOUq/4orrpiOOOKItPnmm5fkAqKCk45z70wHZIMVe2c75K0LtllccMEF5XYG5zsgRhZeeOFylR95wALBgY85vvyQGOONN15JDHjuyLF0yNYASAdxpWeV8P3vf7+0xkBQOOCS5cMvfvGL0hJDvMGDB5fWGAgCyrw62sqy3HLLJfVnAeKMiE022UT00vn1DvjMPvvsaeutt04//vGPS39ppppqqpJkYXEh7TzzzFOG+TNw4MDSogSGnrNDfBRFkVZYYYUEm3HGGac8g2KGGWZIp556alLePfbYo3UriDjqM2TIkJS/sbxYgvgOSJN33nmnPA9EmYSFCwQCgUCgoRCIwgQCgUAgEAgEAoFAINCNCAzoxrwj63YQoKjmMw3aiVJ659X48qGdP1bWEQsIA8rwlltuWVoEVPOnOHtm7fDnP/+5TU6sArhddtmlJDSQH85XYAFg2wISgoVCNZEDNW0XYUnwwAMPVINGuGcZQAHPBEeOYGvHXHPNVW6hsKUk+1evXal/URQJqVFNV+9enAEDBtQLauNXu73k6aefLvOvkjDIBQRQLS7VjGBefd+qq66abEdBBiFf4MzipJom7gOBQCAQCAQCgUAgEAgEAoFAIBDo6wh0rpX1dQSavH7Ig/XXX7+0DKDcshiorVJRFAk5YavBhRdemPbZZ5/yXAXxiqJIFOqTTz45UbhtdbBFBAHhVyfGGmuscluIuNnZJrLOOuuU2zOWX3751q0IObx6LeQZz24AABAASURBVIqvDsZ88cUXy7MdqmEICuSE/Kr+PXWPDKp9F9Kl6sfyxNYZZ01kf+c+fPHFF8kWFX5FUaQq4ZBa/glvubT+R6j87ne/Ky07kD5+PYQ1x913390aJ24CgUCgVxGIlwcCgUAgEAgEAoFAIBAI9AACA3rgHfGKGgQouhTbrKhSxvk5a6EmaqLwIgSyv2dm/fmZxUJWppEHrB1ymKv43mVbxAYbbFCeK2F7hO0PtjlQpOeff/7yrATppVGWu+66K0knbySBsyGEZedQRWclKJttFs5gqFo08HfWgzxWWmmlJO+zzjorJ0+2mVDAbZ3gqU7KWs2DPz95uec8V+N4lpbLeCq/+lbTScs51NKVY81ha4QtKZ7/+c9/Jmdx+B7S80MWONtBXXwf74P5m2++mfI2ENYTLB/Ek4blhzM8nJuRy6q+noVzDsR0ECiLCM/hAoH+jUDUPhAIBAKBQCAQCAQCgUCgvyAQJEQPf+nDDz88OWzx2WefTXvttVd5jsN2222X7rzzznTHHXckBzTeeuutZakcxkjZdTbCsGHD0rzzzltaH+y7776JBQSll1WDX7ZwlgFTfwmttDuckh+TfwcqCrNdw9kSDk306w3C/dLFIYccUp4B4d38lEdZ5GUbh1+yUN5aIsIZE1bz/VqEMkqbnfJRxuXhjAnxTjjhhLK+4jjL4YADDkgOq3S2grMykAHKwmKA5YH6e6e0yArhLC8cVCkP1hssPBw26aBHhAF/+KizAyN33HHHcssHAgA5gaRxjgNSAJHilzSk4RAQyitst912Kw+THDRoUGk5cuWVV7aW/fzzz0+wdOil+M6YcAaF98rHN1Z+Yb/61a+SZwTMVltt1ZqHczic/+GcCvHCBQK9hkC8OBAIBAKBQCAQCAQCgUAgEOhBBIKE6EGwvYqy7tcc/MrCUUcdlRxUSMFGClD8/WKFFXJxEQl+5YISS9GfccYZS7LixBNPLAkMvwix6667Jqvu8vGLE/vvv3+69957y1/b4Cdv50VQnCnWLBucTSAN5d9PRs4333yJkkypl8Z7KffObXCWAmUbCUGRV66qW3fddctDMZVdOaXnEAyUbkq2rQgOdmRdIYxzOCfLDCQHYmTo0KHlT1z69Q6/GuHdDqp86qmnknMsKPe2RiAa/AKGPLzbr2SwUvB+5A5/206clYGc8R5lYK2AvJAWQTJw4MDypzj9rGb+DsgXRIly5oMrlY/Fw3nnnVeSR0OGDEnqtuyyy5aEECxsgVFuv8Dh/UgO3+HBBx9M/H1zlie5fOLIB6Eifbj+i0DUPBAIBAKBQCAQCAQCgUAgEOhvCAQJ0cNf3PkLFOD23Mwzz5wo24pFec7xKOX8EBH8kAcIBSSBZ86BkZRt9/WctPKQzhYLcaTnN9lkkyXv5sfyAXHAvyiKtOiiiya/kOHMCH61Tlzpqi6XrxrXL0rkOOrmHIWiKMpfisj+rjByFoVyeuayX7V+6iusI6cuiATvyu+Hw3jjjVcWrZoW7nDIfp5FUo6MlzCkA/+qc1ilME5ZpYVBfp5yyilb8eUnD3Ws5hH3PYpAvCwQCAQCgUAgEAgEAoFAIBAIBHoBgSAhegH0ZnulsxNYIBx//PGpnjVEs9UnytvbCMT7A4FAIBAIBAKBQCAQCAQCgUCgvyIQJER//fIjWe8f//jHaemll07OOBjJpBG9kRCIsgQCgUAgEAgEAoFAIBAIBAKBQCDQiwgECdGL4Dfbq53V4AyKZit3o5Q3yhEIBAKBQCAQCAQCgUAgEAgEAoFAf0cgSIj+3gJGov7ORphuuulGIkXDRI2CBAKBQCAQCAQCgUAgEAgEAoFAIBAINAACQUI0wEfo20WI2gUCgUAgEAgEAoFAIBAIBAKBQCAQCAQCXyEQJMRXOPTNv1GrQCAQCAQCgUAgEAgEAoFAIBAIBAKBQKCBEAgSops+RmQbCAQCgUAgEAgEAoFAIBAIBAKBQCAQCAQCbRHoiyRE2xrGUyAQCAQCgUAgEAgEAoFAIBAIBAKBQCAQCDQEAmOYhGiIOkUhmgiBTz75JF1xxRXpscce67DUd9xxR7r55ps7jNOVwIcffjg999xzXYkacQKBQCAQCAQCgUAgEAgEAoFAIBAIBNpFYNQCgoQYNdwiVTsIPPDAA2nvvfdOjz/+eDsxvvH+/e9/nzbffPO03XbbpX/+85/fBFTu5CcOd+GFF1ZCRu32o48+ShdddFF69tlnRy2DSBUIBAKBQCAQCAQCgUAgEAgEAoFAbyPQxO8PEqKJP14jFv2ee+5J5557bnryySc7Ld4mm2ySdt999/Tuu++mccYZp278OeecM+28885p5plnThNOOGHdOCPjOf/886fpp5++JCI+/fTTkUkacQOBQCAQCAQCgUAgEAgEAoFAIBBIAcHoIRAkxOjhF6lrENhqq63Siy++mFZZZZWakBEfv/3tb6eBAwcm1xFDv/KZYIIJ0v/93/+lqaee+iuP0fw7YMCAtOiii6b//Oc/6emnnx7N3CJ5IBAIBAKBQCAQCAQCgUAgEAj0IALxqj6AQJAQfeAjjkwVhg4dmoZ+7a655pr05ZdfpkcffbTVL5+7wDrhkksuafVn4fDZZ5+1viqHsya4/vrr07XXXps+/PDD9PHHH5dnPLzwwgutcf/3v/+lv/zlL2VeZ511Vrrzzjtbw/JNzi+X7cYbbyzzyuH1ru+//36ZZ07z1ltvtUbzzosvvrg1vJrfjDPOmCabbLKynK0J4iYQCAQCgUAgEAgEAoFAIBAIBDpAIIICgTGDQJAQYwbHpsnlgw8+SAceeGC5HcGhkLngf/vb39Lll19ePmZC4I033iifH3zwwbT99tuX5zbk9IMHDy7Pcxg2bFh5PfLII8ttE4Nb/J0JwdJAYmcwXHbZZemVV17xmOS1Xc0ZEIiL888/P7366qtlnH/9619phx12SIiN0qPOH0TGTjvt1Bqi7KwweLz88svp0EMPLS0yPKuH+Mruedxxx03zzjtv8k7P4QKBQCAQCAQCgUAgEAgEAoGGRiAKFwj0IQSChOhDH7MrVdlyyy3TRhttlD7//PO02GKLpaIoyvMWnMlwwAEHpKWXXjrZArHmmmumLbbYIg1uIRX22GOPNOWUUyaWE+ONN155kOQ888yTvvjii/IXK1gcrLTSSmmXXXZJG264YWIxMfbYY5fFke+6665bEhXy2nfffdMkk0ySkBesKEQSZ7311ktbb711+b7DDjssLbLIIunEE08UPIJ76aWX0u9+97vEokGe3MEHH5zuuuuuxNLCNov//ve/SZ7ClIubdNJJW/OyBUQcW0daPeMmEAgEAoFAIBAIBAKBQCAQqEEgHgOBQGDMIhAkxJjFs+FzYwWwxhprlOchsA5QYJYH3/nOd9Jss83msXQIAr9e4RDHH/3oR+nWW28tiQhnKvCbYoopSgKDxYHwPffcMyEmnLdQZlD5w9LhF7/4RZplllnSggsumO6+++6EEMhERVEUSX75efzxx08LLbRQSSpUsmm9RR74Sc855pgjDR8+vHQIkbHGGis98sgjST6uM800Uxlma4itG60ZtNxMNdVU5WGYwloe438gEAgEAoFAIBAIBAKBQOMhECUKBAKBPohAkBB98KN2VqUf/OAHackll0ynnHJKabVAYefnnARp/bzmZpttlu699970j3/8o7wuv/zygkbaPfXUU6XlxZtvvlmeBfHwww+X7+5KRvPNN1/daLZVvPfee+WvcLCA4I477rg0aNCgkuRAYBxzzDFpm222ScL8vOfKK6+cnnjiibr5hWcgEAgEAoFAIBAIBAKBQC0C8RwIBAKBQPcgECRE9+Da0LlOPPHEafXVV0933HFHuZ0CUbDMMsuUZWZRwJ/lwLHHHptmnXXW5OwI1gxlhJH8c/XVV5fbNn71q1+laaaZprx/5513OszFu5SpeuZDNQErhummmy6tuOKK6cwzz2zj1l9//TLqcsstV5Iswll0qEP1vepn2wiLjDJB/AkEAoFAIBAIBAKBQKBREIhyBAKBQCDQhxEIEqIPf9yOqrbqqquW2yecEcHiwHYI8W23sGXDuQoOlWR1gIxgFSE8O4c92rKRn/PVGQvSsFTgZ2sE5f+tt97yWJIfzz33XHmf/4jvvAnWEvJkoWF7iG0j4uRyOHDSs20YSJPf/OY35RkQ/Lj99tsvPfDAA+V2j7///e+8SqesDqKUZ+nR8schmM65mH322Vue4n8gEAgEAoFAIBAIBAJfIRB/A4FAIBAIBLoXgSAhuhffhs0d0bDddtuV1gnZeiAX1iGTSIpll102Lbzwwun73/9+WmGFFdIJJ5yQ5pxzzmRrxtChQ5OzIZzzsPPOO5dJ+a+zzjrlWQs77rhjeVClbR3S/+QnPynPhDj11FPLX6Y44ogjyoMjkRS2SxRFkeaff/4099xzp29961tpt912K892cF6FcyTuu+++dNttt5XhN910U0JAnHTSSWnIkCFlvsphGwZC5bXXXkt+KYMf54BLZ1c4jFJB/SwpssJZFt7FL1wgEAgEAoFAIBAI9DoCUYBAIBAIBAKBfoBAkBD94CO3V8UNNtig7uGPrCJOO+209MwzzyRnOCASzj333PLZeRE33HBDeS+cO/7448tX1Po7p2GiiSZKZ599dmv8ueaaK9miIZ1f1fBLGX4N45xzzinjyB+BUWbY8sdhl+Jm5/wKZEdLUEKeZH/XtdZai3daZZVVyrz4cX4idODAgWWYP6+//npyICXCxHO4QCAQCAQCgUAgEAgEAoFAIBAIBAKBnkEgSIiewTne0kAIsK5wLgYLiwYqVhQlEAgEAoFAoL8iEPUOBAKBQCAQCAT6EQJBQvSjjx1VTcmBlDfeeGNpRTH55JMHJIFAIBAIBAL9HIGofiAQCAQCgUAgEAj0LAJBQvQs3vG2XkbgrLPOSn6O1E+UFkXRy6WJ1wcCgUAg0K8RiMoHAoFAIBAIBAKBQD9EIEiIUfzot99+e3I4Y7ihTYXDBBNMkPzaxtChQ5uq3EOjvPG9og1EGxijbWBo4Bl4RhuINhBtINpAtIFoA73SBoKEGEUSYmhLg918881TuMAg2kC0gWgD0QZGqg3E3BFzZ7SBaAPRBqINRBuINtCP20CQEKNIQviJSL+8EO6ZNr9EEXgEHtEGog00chuIskX7jDYQbSDaQLSBaAPRBqIN9G4bCBJiFEmIKaecMvnZx3ADA4eBgcHAwCD6QedtIDAKjKINRBuINhBtINpAtIFoA9EGUpAQo0hCRLJAIBAIBJoHgShpIBAIBAKBQCAQCAQCgUAg0BgIBAnRGN8hShEIBAJ9FYGoVyAQCAQCgUAgEAgEAoFAIBAItCIQJEQrFHETCAQCfQ2BqE8gEAgEAoFAIBAIBAKBQCAQCDQWAkFC9OD3ePHFF9Pw4cM7dB988EG3luj1119Pr7322gjv+Pzzz9PLL788gv+Y8PCTmG8cjMkiAAAQAElEQVS88Ub64osv6mbXWXjdRL3g+d5773X47erh2gvFrPvKzz77LNVrf3Ujf+359ttvJ9/t68cRLsI7aK8jxO+KxyuvvNKKcb13v/XWW63h//3vf7uSZZ+P4zsMrxlX+NWreDXeu+++Wy9K+vTTT5P07fXXuok68dROnn/++fLbvfDCC+nDDz9sk+KTTz5pbZ/PPvtsqpato36nTeeMtIdcP23nyy+/LIPkVfu+MiD+9BkEtNXq98/twLhXW8n333+/bIc5zjvvvFMbpXwWTz8oH8bQH+0yv/fVV18dIVfvzOH6S27DtRHVS3311WpYe+nFe/PNN1N7+VXziPv6CFTnpuFfj7edjSvGPd+pXo5Z7qkXNqp+2nIu20svvTTC9/7444/btH39pr13/e9//yvjGn/rxamGkx+17Whf9ZAKv0AgEGgPgSAh2kOmG/xXX331dPDBB5dujz32SN///vfTT37yk/KZ/1prrZX+8Y9/dMObU7r//vvT2WefndZee+30i1/8YoR33Hjjjem4444bwX90PYYOHVrWzzsJQbX5CT/kkEPKMtULr43fm88w3G+//dL3vve95FsdeOCBZd122GGH8luuttpqvVm8yru/uSUU/Oc//0lHH310GjJkSFlebW3fffdNP/zhD8s28eCDD36ToOWO8HL++eenLbfcMh122GEtPiP+J1idfPLJ6d///veIgaPoow0uu+yyaZZZZindhhtumO6+++7W3O6444605557ttZhzTXXTFdccUVreH+7IeCeeeaZSf/xTbkhLd94k002SVtvvXW66qqrWiEhfMIqY+u6yy67lEJma6SWG+3Fd/jLX/6S5N/iNdr/Cau//vWv0w9+8IPyu84777zpiCOOKIkOmb/11lvpD3/4Q8r96ec//3nafffdEyVNeS699NIynTLXuoMOOigRgLUN6WCgXtttt1168sknk/TDhg1LF110URtiw3vD9Q0EKIennHJK2n///VvHBu3gRz/6UTrqqKPSzTff3Kaiv/3tb5Nx/OCWuXi99dZLu+66a6LwVyNpk+bL2267reo9Wvf33Xdf2mCDDVrb8oorrpiuu+661jwfffTRch5ULs4co3+3RqjcKNfiiy+enn766VZf6ffee+9WDMz1f/zjH8twBLn7f/7zn+Vz/Ok6AuSSCy64oGwzQ1rGV9+G8/2MP1deeWXdzBAU2hkZrzaCsfXiiy9Of/3rX2uDRvnZPL/jjju2ti/tX7lzhshdv+pGFlN+7ev0008fYZxHjvz9738v+454DzzwQM6ivNYLR/SeddZZ6ZprrinjxJ9AIBAIBLqCwICuRIo4YwaBOeecMxEqOILQFFNMkVZdddVWP8LQZJNN1uWXURRMFl1O0BLx8ccfT5NOOmnL3Tf/H3vssSQfwvs3vqN3N3z48LTbbruVq6r33ntvogSNNdZYrZkKp2hY0bnnnnuSia0a3hqxgW6WXHLJdOKJJ5b4rbHGGqXi5FsOHTq0JCUImU899VQDlTil5557Lu21116JIqjNKS+nzK6/+93vku+u7Ar+0EMPpSOPPLJMhxDzKzD8q87KCAEdibHgggtWg0b5noCknJxyEX6QPpRJq5E5nGAlnNtss81KZVv7GuUXN2lCK56UdkLmyiuvnODB+a7cxBNPnJBjxx57bFlD3xfJKA638847J8o9xa2M8PUfisy1116b5DnRRBN97TvqFyQARcu4o11RhFZYYYX0+9//Pt10000lSSAc8UGgV7YTTjghsZZwTS3/jJNIW2HZCUNYITeMJZTQbbbZpsTh1FNPTSwr+BVFkZZZZpmEWLv11ltbcov/fQ0BihdF6Ze//GX5/XMbcdW2tIvrr7++rDYlSbsWlt1dd92VLrvssjLcH1YD+pU+pB/wG11nldiY9uMf/7gso/ZvXNtiiy1KAiSHTzLJJGW4sg1pUXiVXX+svh+h8Kc//amNRaP0yEhllpaT3vipztNPP31aZ511EoxqCZdq3nE/IgKU9quvvrqUZ+BadSyxBg8eXJKctSm1qZtvbkuA5Ti+KSJ/4403zl6jdUV4IHanm266sv2cdNJJacIJJ0zbbrttevjhh0vLM+HGQfNDroNx9Zxzzmnz7sMPP7wkR372s58l4/USSyzRaTi5VV2QGmSINgniIRAIBAKBdhAIEqIdYLrDm+DcUb7rr79+skrYUZwc9uyzz5bM/FtvvZW9OrxSGCltc801V5t4yAGMvNX9aaaZpk3Y6DwQepAMm266afLOcccdNw0Y8E1zy+FWbb27NnxU3t1baeC2yCKLpPHGG6+NYNhb5am+V5tickkgpczlMHizJKCIWlUjPDDlnH322ZPVtHXXXTcRiAkyOU2+UvoJXwsssED2Gu0rRVJ+BDpun332KQVmBBnFmJJhtUUbzi+z2q98FI3s11+uVp0o2xdeeGGi2FTr7RsiH6aaaqpEsb/zzjuTVTIrd7DlCJraBusISk1OD1P5TT311NlrtK5ICMI2KzCWNZtvvnn61a9+lfQXArq2OWzYsDTffPOlGWecsXzXDDPMkLTNvEqo3VrVVe7s1HGrrbZKykmJNI7NM888Zfppp502rbLKKok1Dw9KpzohJTyH6zsIaA+sAbTzWWedtU3FtHfKunHt+OOPL7f7IDGRrsY/kVkjmp8QD545+f3rX/9Kiy22WCqKgtdoO9YaCALWOsqsDEg5/qx4nmohr41xVVIQAbL00kun8847r837tfcJJpggffvb3271lx5pa+U9e6600kpJ+twPBg4cmFiXIStynLh2jACskPHmI22lKIrWBNoSa8CZZ545HXPMMeUYmwN9D5ZcCy+8cPZqvZo7jXlI1LHHHrvVf3RuyIEsNszd2hfywfzASgwB553aDVJL2/Gu+eabLyEOhg4d6rF0hx56aGLZcfDBByeLZkXxTX1F6Chce0R6aePihgsEAoFAoDMEvtEKO4sZ4aONAKWgo0zGH3/8lIUj8Uwcw4cPT8NbnHtWA/w5QpMV6W9961seWx1hXPzsmP21Brbc1MangJhkkRRVksDKudVWk1vOyyTXkkW9/yP4jTPOOGmmmWYawT97CM9KR/Zr1ivMkUKEzEUXXbRhqkHBtNWCQocgqVcwAhSh5YYbbijN37VBwkS1LVTTWWH+85//XAoo1fasnWkzwnN7sZpdTdvRPWH5tNNOa42ifXz3u98tlYDJJ5+8JHdYy7RGaLlhOUOJhX3LY7/5D1eCIkWbgl6v4hRvK3iIG9/LN2ZlkuMSROeYY44SX4o8f+0F4cM6y3N2+r2xAJmQv61V3Bze0VU7stqGjCyKrwRa1jXamPdmkqKaR1EUJWFJGSyKIhH2ufT1P8I9y4rsZ2ycbLLJkrYrSlEUCclZFEV65plneCXKgPZjZa/0iD9NjwDrHhZZLGsQV/UqpK3ttNNOiRUMxZAVYHUsNGZp20sttVRrctuYxKnmaYw3V4qU+4Cr5644RMe5555bEtXim4ezkmcc1ceMocKyM765z23YPYsHpCKrBn2LHye91XD32eX0+lH2o4RKX93mlsPi2hYBFiPIWuTD3HPP3Tbw6ydEPaUbkZS3JpLNWHea04yzX0dtvZC3fC9EavaUBiFlPDS+a1uc+TTH6ejKAsI4r72Lp23IXxuwSGK8rm1f4iFBkHT6gTKrry1M+onwqussXFzEH+KD5YjncIFAIBAIdIRAkBAdodNLYcgFq7vbb799ub/T/n0r01ZzFMnkaJWQ8HTjjTcmTDah3DNFDovNEc6sEBHapavnsOQmou985ztlsNUU+dkrS3lg1icvKyhWoZn3e4904tVztnaYVMsM+/Afq2XqzyT8iSeeSCxKGqm6hE3CSBZM6pWNMMwShYCu3dWLU/UjjGsjBGj+hGIYUHitrLOo0F6s9NmzzORePEKvePXc5ZdfnhyYKl7Vaef/93//l6xsE+IJUdpjjmOFUJz83F+uBEb9kHDZUZ3na1npQtIwx60XD3nDQiGHOTfBOJOfKWOUdtZKCAwC6pAhQ5LvTLHz7QmcVpvrfVd+2mDOL18pS8ql3WmftvQYM4xh4hDGmSsTjj1XHSFdnkgqRINnJsZIF+NYjkuIrhK6/JFxxlDv9xyuuREw/qpBZ/3AWSSUMH1GfGTUsGHDynnTGQ3aYZ7/hNsaRPEcb7zxPJbxrADrK8zYjW/GO+02j/kstpAM2nyt0z/qjVMOgqY8UhZnm222hIzwHuOcF1NWWQu55ywImM9ZK3muupzeGT7tpc/xEeXqX13UyGFx/QYBhKxxyjf6xnfEO+3LWEMGMB6yOPAN2iMubI8xfyJO5aYN2Z5DgSe/aQMsYpCstkuKY6xm9VbbtjyzdMljp7jZkftYCpoHEGocazDjtjgsb4zx7jmEHsLfuCpfDrEhjOssXBwO+WI8Jyt4DhcIBAKBQHsIBAnRHjJd8e+GOCY9q9IEfqaVhB6O6THTQBOW15rkTHh5IuPHEUbE50xsTPKsAgmr5yiUJidCew634pkFNmbQ8rKf3MpTfn+OG9dUWgXAmtLdSHhYbemsPEVRlHtHO4uXwymISChtJvtZraEQWHVn/aK9EGAIP84lyPFG5krosuWA0KRtEvgJ/w6mZNLPiVMURartAyPznmaMC2/9v7OyU8zbi6MvE5opLeL4prZsEHw9Z2eMueWWW8pH+8l9W2kI2lbGyoCR+IM0MB75pvYaIyF8S8Iy0tW9w9PUj0BcmzXF6ZJLLknZlFl+2l1tvHrPFE2EjJXGeuHh11wIIBa6UuKOxgcEG5LAfnnknvwQsgMHDnTb6qxyU+p46APcT3/602ReRg7wHxlHEXQYq75kzDRvm/Nt0dAHONvk5Jn7gXZvW5H4/KsupzcPScvVps/xkR0UbH0s+8V1RASMK8aXEUPa+iDyq2Ot9mQrDaK0bcyvnhAGiKevnr76aywmd3liiaB9IXrNeVkWE9ZVh2hFaDgvBaGGyB/SQiCTLbUNDgFB3lR+i0bauPE+nxGhnCxnbO0jS9QLt+3DVpRquZA2DgWWpuof94FAIBAI1CLQtCREbUX6yrPJg1k0IcgKjXpZkSEsMV/GkBNCWDkwP2Y6PXjw4FIRJsgTzk02TpHPCiCTPPnUcyY/+eQw2zKsGHoXE1Um8cLs12d6SBDzHu/33npuueWWS9VVSen7orMHXf0Jo4TARqsjwYPSRrlsr2yEEEI0Qbc9oamalmmw9kRw4W87gLbJtF+bzSeB80ccZMFqoYUWSrCq57Q3grH8OH2AYEPAl46flSaWOAQjq4GcMO1MexOnvzjjga0/nR0ARtEpiiLVrhTrw2eccUb5awIDBw4sYaOAWSHWt0uPlj/GFtsovG/QoEHl+QtFUSRtXdtiOaMtsIyo9135OfuhJavW/4RdxCgBO1voILQIvgRv3xUZocwOf21N+PUNIta4pAxfe3X54j2Uitwmu5wwIjYkAnnMQIB25KWZrQAAEABJREFUVEDtXbg25Zrbs/bJ2cfOigH5wGLBCq7xRlxOHPOi9moM4qefaNv6AGXePGkcFLfW6R/mbOmy094phywxsp85VRkcIKwfLL/88uV2KWOqeZpS7JyHHL/2Kj7lrzZ9bT+yDdKYb5ytzSOev0HAHFYURfnLYt/4jniHFKZwI7uMYcYn4+OIMb/yGT58eJttt6xOkb/GdG3IFg5zMT/zrHHctknWqLVty7NzHVhWfJX7V38dWo4Y2XXXXb/yaPnrjBO/joJU0L60Pe2XhY+2xfLM4dusGOXr4GPbfpAZSOt64RapWD9WiRLjrPYl75bXxv9AIBAIBNpFYFRIiHYzi4DRR4CQTAiyQljNjVBEYaAoVP2r95QSE6HVvmHDhqXbb7+9DKYolDd1/pgQ63iP4CWPovhqTzfzZ8oJoqOecwBdTEAjQNjjHswiKX1WxAhK9Qpg5QOxYIXNPv16cap+vn31uaN7AlQOdxhhvbbCj/CcFQmkiMMyraZstNFGOXl51Qb1AY6QR5gSj/BeRugnf3wnK2lMtQmG7VWb4uIbUIJyHAoT811WCNpH9req3F4byXHytSiK8syG1PJPGsqY71jPDWlZfWuJVv63px5JyroFwVoUX40nApFgvitHabTlgoArLDsWGQRe40seH4uiSNoCQd24meNq9wgqZcp+2o97bcw1XHMjgOT0jc17HRFLFHsKXXvElTBtwtzrfJGuopLbk/hIBVvGtLda5zySv/3tb6KVjqm69krZo2yWnl//oWzqAxQ55u+IfySE7Y+sEZEd8kfcGrcRsIiJXO5qemWi2Er/dfblRblzfUuP+FMXASQRson1H8uRupFaPJH8SHjYs2JgrecbcRR4c5t7290o6xYGWpJ1+j+PcSLanqa9y6fW2Q7i11zE41iosVrw62S+P7/sbLXQvpBitkEWRVEeTomwGG+88ZLtj8g28T3bIoKsMp56rhduTtGepeGifUEhXCDQJxEY45UKEmKMQzp6GRrArfCY2Az+OTfkA4UDy579aq+2bwhntmlClKY2Tu0zoabWr7NnExkBhxBUz1llNal1lk+Edy8ClEwCti03BI56wo8w5zZYTcnCR0elIsB0FN5e2AEHHFAeElivvTARZVUirTMIKA1+QrJWQBfOWXVCQOgPTF/59SdnRRdxQ8Bk7WTVqbb+9pvDiDWDAyyFExT5UWxqCR6rfoRM8UbG+UYIg3rflV8mIRCjzk6xTad21a76PgepnnjiiUm5ESU5jCIgr9pfGCqKorQC8y7tIsd/5JFHkr3v+dk1j4cIXc/hmhsBCpFxy8GLFLzqfJlrpl0Is4pM8aqSATkO6yrjpO067REVOW57V6Q8RdX7ap2tS0heaf1so/EWAaEf8qt1lDpEoXT6C9KRWX01X1vVELAIDQoq0iLnk9Prlzl9DnOFE/KmquTyD9cWAdagzsWyfQshxFqgbYxUHpiMaNC+jFeU/+p3QpCb2/ixPNDGEBu1+XT2jGhCLsin1iHh8niubbGkRdRqN/XyRRzbiuG8B1vfEMIWr8idLB6qaRDC5AJx6oUjloVX259xVvtCgFfzivtAIBAYHQT6ZtogIXrpu9qDbRW69vUUASsXBGrmcDnc6rCVGvuys59rVQFhUp0P+DNREebFqTrCvFXP7GdFtfrM3yRlIqn1F+Ydrl11VlxYRXD16qtOJnd41FOSu/qeiFcfAfuOrehQ4KqHOoqNSNp9990TE3fCEr/sCLK+B8U1+7kS0nP78MzlZ23Wc9X5vvXaUTVOvldGSjVBztW+Vc5+bYKzeM4TYCrqZ0IJUFaH+Pc3x7rBipvDylwp+RkDfd/BecxvbX3gb1ywlctBZzCEa3aIHwKmsaf2exMyfV/9Uz5Vp99Wn9u7p+RRogjR9sDn97oyH5dO+YxtDt1zoJt2yTpCmPdTAowfhHF+2RVFUf7cJ6HXYb38WesQzCkGnrOjTFC8rFhnv7g2NwK2Hqy22mrJ9i3jmPEm14j1gDbGMXNHmDkUUJ/JcVgLUeL1IUo9xROBXm3vVoGNh9W5Nqd3Nbe5duaMxcqibXqfew5Bm+dV5TG+URDFUbd6+SqfflFbJunl2VF6/cBCAsWzXt7h9w0CyCJjkm0Wu+66a4J5DjWe2TKI7Lelpx65QInXfqptxAJR9Vl+2pe41fbLn0O2u3bmLDQgH/xSh7lUO+AcKuz8JOmNs9oXazRxt9hiC97lLwvZVoq48stLPI3bLM/87CfypF44AsbPl+o30nDaFwIk2hc0wvUJBKIS3YZAkBDdBm37GWOqHVyEEDj55JOTVRTCvhRFUSSTmhVeQlQ2vXOSsRWdbLmAXbeiKC0lkwCOdMimf4R4ZtKEFRNlzsdqjcMlnfHANFAcQnt+P3NCZbOSSCmwF9ZKE+XEZEqAsz/cKo3yduT8qgcGXbmVz0GFDt/KaYRTCNoLz/Ea5eqbqAOsrCjn1YdGKV+9cmgvVtUIEBTA3A5cCT6+p19EsA9VeuQTIYUZpv3RhHuKvrYonGBB4NB2PCMM5p133mQPKuVWm/SrFcKsxhO2mItSdPm155wIjlTQxrQHK3jZ+aUYwh9hkGKpfRKi7F9tL7++7s9ygXAJf4SMlVbflHPeAuEZiclqAglEKGWhRGnJuLpaUbVdh3WAMcHKasbOdghEBrLBu9Zaa60ySBvhZ5XQarT+UAbU+eN72vPspH/OO6uO4E0pQ7wau4xN3lVdWTP2MUVngk5BrH0NYsy4gqhQf3vgkWqsRapx/UKLNqMNV/3jvnkR0L6Rq9q3cW7WWWdN2gCnXWtrDs/LhJY+4Vk4Z44zb7KEyCho05T5/MzUXhzknrZmHBVGoXNdZpllkj32+oXneg7ha77TF83/ypWdsdM4iSA0t3ofwkI7LopvtizlfJWb0qvf6ROIOdsxkLXSW1joKL1f8kD0IWVynnGtj4DxxryEzDV+md/gzyEmHARKCbclLOdgrvItxEFUkLngbV5DMpB5+OX4xljt15gqnsMghZG5xEc4G8+N3fzruUykaaMsC3PbckVIycu8bGsQwtZ8bJ6vWisYg5EOzj1RdnKBs1LyuF8vXLvO4blcrNn0oRhnMyJxHR0EIm3fRiBIiF74vgZzir+VZhOLgZxil4tikjAZmVCyI6BUTeEpDc59QGRYBXW4EMJAntIw+6QkWz0Uhx9HKSDwUFyw2/Zoex+iwfuRF8pmIrU6w1yfYEfpIZhJ670mM/E7ciZvZ05IgwzBxpuwc5racIptNTzHa5QrYUAdYGzV3+TeKGVrrxxFUSTfzio4ZY+ZO0GY4EwhswJuC1BObzWc4EKo1VbEJUhR6sTR7ghNhChtC8kEE9+YEG71BOEhLqJGHN81r7jwr+coA/b0E7pqHRNqv6ZAQFIuArg6FcWIAnq9vPuqnwNlCcUOGzv66KPLXznRd63YWW3zLdUddrYx6NO12LJUQk6I57tZKdZXPbO+sqolDoXLmMKfEK1N8LNtrDp2Ca86YwuhVDuofbdnyh+Syvk1lLNquXM+xhqEmD3O2a961X6NfUgGY5wrAdq7czx1p0S0l0eOF9fmQ8C2JAoVsooFlfaLfDUnIh+qyra+YEzTTjiKIQsIFjK55pR65B6lkJ85TBrjvntjKX/WPdq1McmvGOT+JqzWWSxAGmjztQ75pt2zXpIXkgO5ol3X5uNZuZF33u0sDAoo0g5511l62KiDsV9e4TpHAEGPEDLmIcvNU74PeUD7Mg5Xc9HefAvfSVzOHGk7RlEUifznmVwmnfGbrKVd8GddwB/BZE5F5iNhO1LqtVlWZfKodWQ746Px3T3iGWlSJSC8z3jpnQgLZdcuze+5HdYLJ6fmcHmoK3mUvFAU/Xt+hkeTuyh+INDtCAQJ0e0QN/YL7EulkCIWTCCNXdoo3eggYKXQKocVY4IKQZSpJdKBI3x0lj9BxMoHxZJi2Fn8CO9+BCgVFCRWBPbIIywJuqysfFckTldKYU+z09CRR12J30xx7JVG4rZn3t5MdYmy1kdAO6cUsbqjZFH6WE/pAxwFrH7Ktr4saCh/lLC2Ic3/hOCgUCMSm782PVsD5CZCloUN5fznP/95QnZqWxzl27zaWamQqs5RsG2iK/E7y6+Rwi2oseRBLjdSuZqvLFHiQKB/IBAkRP/4zu3WklKJIbdabQtGuxEjoOkRsEJOAKKIMSXlCO0EU5YNXa2gNBTWvHe0q+kiXvcgYNXXSivFwjclEDM5d494Gpm3agusKQjUI5OukeOy2CDwb7755o1czCjbaCJg249DWG0x1Pb1A89M5lnadDV7VgVIPIf3UTq7mq7R49lCyXKJBUejl7URy8dqFIlvq4L2xRlTWC5oK10tMwICQcbqrC8t/LCCJBOwCuoqFg0ZLwoVCAQCPYZAkBA9BnXjvsiqEQXVwV6NW8oo2ZhGgKBt/6mfPiQ42OLQlXfYkkH4spWIKXBX0kScnkOAEsU8/eqrr07O/HBeRFffLu3Pfvaz5GwIW466mq5R41Ei/VoQxcEvBzVqOaNcYx4Bll76AQsJZx3ZVtiVtzAvt23NVicKZlfSNHocWymZ4Ts/w6GUjV7eZiifLQ5ICWd6OIPD2VxFUXSp6LY02i7kF4O6lKDBI9lawgJPP3MmyagWN9IFAoFA/0IgSIj+9b3brS0TOqcrtxshAvokAvZC2xPd0X7mehUX3zkO9qLWCw+/3kfAvuWuEkvV0i600EKJqbH9zlX/ZrzXvp0hQlmo3QPdjPWJMo88Ak7qd8DgyKRkIYjA0HZGJl2jxjW/O1wTFo1axmYtlzNxnDUyMuXPRFcDLfyMTPFHiKtdIWK6SvSNkEF4BAKBQL9EYEC/rHVUOhAIBAKBQCAQCAQCgUAgEOhVBOLlgUAgEAj0TwSChOif3z1qHQgEAoFAIBAIBAKBQP9FIGoeCAQCgUAg0GsIBAnRa9DHiwOBQCAQCAQCgUAgEOh/CESNA4FAIBAIBPo3AkFC9O/vH7UPBAKBQCAQCAQCgf6DQNQ0EAgEAoFAIBDodQSChOj1TxAFCAQCgUAgEAgEAoG+j0DUMBAIBAKBQCAQCAQgECQEFPqQ89OJ2V100UVtavavf/0r5bBddtklvfbaa23CPeRw15z+448/Tueff3569dVXRQkXCKSbbrop/fGPf2yDxMMPP9zavrSfq666qjX8r3/9axLe6hE3gUAgEAj0JALxrkAgEAgEAoFAIBBoGASChGiYTzF6BXnjjTfSUkstlfxE0kEHHZT8vNjBBx+czjnnnDLjW265JW244YZp6NChpTvppJPS/PPPX4b5I/3SSy89Qvqzzz47jTPOOGmuueZKfeXnytQ33KgjMHz48PTb3/42XX/99a2ZPP/88+mAAw5I2h7nJ+G23377dO2115ZxtE0/+/jCCy+Uz/EnEAgE+g8CUdNAIBAIBAKBQCAQCASqCAQJUUWjie+vvvrq9NZbb5WK4ND0xwMAABAASURBVMCBAxNCYYMNNkjXXHNN+vLLL9O5556bdt555/Le81577ZVefvnldNRRR5W1lv7NN9+sm74oivTDH/4wLbHEEumwww5Ln3/+eZkm/vQ/BHz7O+64IyEivvjii1YAbr311rTPPvskbY/bb7/9kt8OP/PMM8s4k046aUlQ7LDDDumjjz4q/eJPIBAIdDsC8YJAIBAIBAKBQCAQCAQaDoEgIRruk4xagVgyICGee+651gxsn/je976XPvnkk9LqYc0112wNoyTOMsss6dFHHy39EBBvv/12qpe+jNDyZ/DgwSWZ8cADD7Q8xf/+iMATTzyRXn/99ZLkqtZ/4403Tossskirly08E000UUlcZU/WEAiwvM0n+8c1EOibCEStAoFAIBAIBAKBQCAQCATqIRAkRD1UmtBvnnnmKckGe/FPOeWUdOmll6bpp5++3EIx7rjjltfpppuutWYTTzxxGmussRKzeZ7SUxylP/nkk1vTM6kXzk0xxRRpnXXWSeedd57HcP0MAUTV6aefntZbb700wQQTdFh7Z0AgJTbccMM28bbddtt0ySWXJHm1CYiHQGBMIhB5BQKBQCAQCAQCgUAgEAg0LAJBQjTspxm5gtkqcc8996Qbb7wx7bnnnmmLLbZICy20UJpqqqnqZuSQyvfeey9lkmHxxRdPOb2tGltuuWVacMEFR0i/wAILpLvvvrs0x6+bcXj2WQSOOOKItMkmm5TbLNqr5N57751Y2GyzzTblwZW1Z0Astthi6bHHHotDKtsDsA/4RxUCgUAgEAgEAoFAIBAIBAKBjhAIEqIjdJoojBXDaaedlhwk+Ze//CXNMMMMadVVV0077bRT+vTTT9vUxJ581g4OEmQRIVB6q9xnnXVWuuKKK0oritVWWy3tuOOObdLPPPPMybYN2z+kC9c/EHjooYeS7RXOBumoxg6sfOaZZ9JTTz2VZp999rTkkkum+++/vzWJQ07lY6tQq2fcjCkEIp9AIBAIBAKBQCAQCAQCgUCg4REIEqLhP1HnBfzss8/SiSeeWG6v2HTTTdNyyy2XHB7IbP6CCy5oPfdBTggJ5vBzzz13so+fX05fFEXabLPN0rLLLttueuTGhx9+mFhRSBuu7yPwzjvvJKRVURRp6Ne/rvLvf/+7tIZBetU7I2TyyScvD6rU3u68885WkAYMGFCSGfJs9ewTN1GJQCAQCAQCgUAgEAgEAoFAIBDoCgJBQnQFpQaP8+677yaKnq0SuagsHPwSQX7OV7+SgURAQFiR5i/9XXfdlWrTs4IQHi4QWH311VM+U8RBpx988EGnoPhFDKQD4qrTyKMTIdIGAoFAIBAIBAKBQCAQCAQCgUDTIBAkRNN8qvYL+q1vfSsxc/ezidVYTz/9dJp11lnTXHPNVXofe+yx5VaKn/70p8khk6Vnyx/pxx577PTss8+2PH3zvza9kBdffDGNP/745Wq253B9H4FJJpkkrbzyymnw4MGl034caDpw4MDEcsb1sssuK381o4qGM0aWWWaZtPzyy7d6f/HFF6UVjTxbPeMmEAgEAoFAIBAIBAKBQCAQCAT6DQJBQvSBT83qYaONNkpHHXVUch4EMuKqq65KSIfLL788UfyY0x944IFpt912SxNOOGEqiqJ0lMFhw4Yl6Y8++ug26Y855pjyGUGRYUJMTDvttGnGGWfMXnHtHQR65a1vvfVWeuKJJ5IzHZz7kIkr1jS//vWvyy0aw4cPT9rdzTffnK6++uo03njjtZaVFc7nn39ekmOtnnETCAQCgUAgEAgEAoFAIBAIBAL9BoEgIfrIp/7JT36SzjzzzFL5O/jgg9N1112Xrr322vKAypdeein5lYK11147Df56NTtfrWrPNNNMqaP0VYhuuumm9P3vfz9NM800Ve9+dt9/q4tYQG5NPfXUaZ555kmHHHJIQmKxlGCNo+1xiAhbf2qRuuGGG5LDTQcOHFgbFM+BQCAQCAQCgUAgEAgEAoFAINAPEBjQD+rYb6q49NJLl0QEMuK4445LFEWV95OJhx12WGuY8OxYSMw333yipaWWWqo1TjV9Gdjyxy9i+AlQxEXLY+/8j7f2KgJrrLFGym3H9Ywzzkhrrrlm2dYOP/zw1rBdd901sbJJNf8uvPDCtO666yYHV9YExWMgEAgEAoFAIBAIBAKBQCAQCPQDBIKE6AcfeUxVcejQoeUvZ8w333xjKsvIpx8hcMstt6Tnn38+bbDBBv2o1lHVQCAQCAQCgUAgEAgEAoFAIBCoIhAkRBWNxr3v1ZJ9+eWXySGDt956azrxxBPTWGON1avliZc3HwJvv/12cibJlVde2eaMiOarSZQ4EAgEAoFAIBAIBAKBQCAQCARGB4EgITpFLyJ88skn6d577y0JiEAjEBgVBFhB/OY3v4kDTUcFvEgTCAQCgUAgEAgEAoFAIBAI9CEEGpuE6ENAN3NVxh133LTtttum6aefvpmrEWXvRQRWX331tNhii/ViCeLVgUAgEAgEAoFAIBAIBAKBQCDQCAi0S0I0QuGiDIFAIBAIBAKBQCAQCAQCgUAgEAgEAoFAINC9CPRk7kFC9CTa8a5AIBAIBAKBQCAQCAQCgUAgEAgEAoFA4BsE+t1dkBD97pNHhQOBQCAQCAQCgUAgEAgEAoFAIBAIBFIKDHoDgSAhegP1eGcgEAgEAoFAIBAIBAKBQCAQCAQC/RmBqHu/RSBIiH776aPigUAgEAgEAoFAIBAIBAKBQCDQHxGIOgcCvYlAkBA9hP6HH36Ynn/++bTlllumWWaZpdX5xYkjjjgi/e9//0tffPFF+vTTT9MxxxyTpplmmjTWWGOlqaaaqjXutNNOm6aYYop0++23p88//7xNyeV/yCGHpBtuuCF99tln6dFHH00LLLBAmdY79ttvv/TWW2+VaV5//fW09tprp6Io2rgll1yyDJdePvPOO2+aeeaZ04orrpieeOKJ9OWXX5bhL774YjrwwAPTSy+9VD7X/nnnnXfSP/7xj7TooouW78/1HWeccdIaa6yR3n777bTbbrulqaeeOg0YMCB9+9vfTscdd1xZ9n333Te99957tVnG82ggoK288sor6fjjj2/zPbSnlVdeOfmefobVK/7973+XP6M53njjpYkmmqg1/kwzzZR8v1NPPTV99NFHorY6+V9zzTWtP+Hq+/785z8v287AgQPTMssskx555JGyfWvjZ5xxRpt2VxRF2c7FSS3/nn322fTTn/60TO+9V1xxRWt7964//vGP6YILLmiJ2XP/33zzzXTHHXck5cnt2XWCCSZI99xzT2ub/fjjj9Nqq62WJplkkrKO4mQ34YQTphVWWKG1H+bS61cPPfRQ2nXXXUsv+A4dOjTpf9K6XnjhheXYIIL3zT777GX+RfFNHz799NMFl9/HWDDbbLOlWWedtexrxocysOXPbbfdlo455pj0/vvvtzy1/a8sr776ajrppJPS97///dbvP91006Wxxx47+c7KusQSSyS/mqNNLLfccumBBx4o+7Zv1zbH5nzSRmFXFEWabLLJWnGYccYZS9wHDx6ctInUz/8ZV6666qo099xzt2I0wwwzpJ/85CflzzqbS0DkJ56XXnrpsg1pN9V+pF/suuuuZbsVt+rkv/nmm5dzhnnlhBNOaH2P9v3MM8+0Rr/44ovL+aQovukTRVG0jhXS5/nX/Cp+TmxcMq6ccsop2avN1bxsvvMzw/pkdvqFulx//fXpn//8Z1ImY+fEE0+cFlpooXLcOvTQQ8swY1ebTPvBA5nnO9/5TjJOwsR8ADv9SDsoiiJVx6a+DAkZb/jw4Un/gEF2c845Z7r11lvTBx98UFZfO1tnnXWSflEURZs5hx95zBxbRq78kf93v/vd0kde2rO8vWeeeeZJ5lHtXISbbrqpnBuKom1fkUa49GRG7Vn6/fffP5nbhJkjrr322mS+0S/4VZ12bg4h0+X3y0NfIe/pd+YQc6E2YA7xy1nGiB122CH9/e9/L2XYap6Ncn///fcn7Xn88cdPk046acrt2TdVF2NBlqW6UOaIEgj0ewQG9HsEegAAyv+xxx6btt9++0TpIzhlZ6C+5JJLkknngRZBnqBPIDv55JPLQe7II49MOe51111XTkh77LFHeuqpp1pLTmk555xzkglo+eWXLxUCcY466qgyLaVD3ocddliZhpBkQlhvvfUSYTo7ZROBMvj73/8+EcT/85//pLnmmispD2HBBGPCNLkgD8SvOuTHQQcdlP7whz+Uk14uu+uee+6ZnnzyyfTGG2+ko48+Oh1++OHlRGsy22WXXZKyL7jggmWYd1XzjftRQ4DQYVLX9pBPvkN2iCak1iKLLJK0H+3oe9/7XikQ/ehHP0rrrrtu2X7Ev++++9IGG2xQKsp//etfWwtDIKEU/+tf/0obbbRRKaggkqaccsqE0PC9CRu77757SXYQQqZtIdMWX3zxNm1PWsqeCVzbUI7HH388nXXWWWnIkCFJO0wt/1544YWSYFtppZVannrmv3fCD1lICIFHdjCCy1577VUqpQSRSy+9NG222Wal4J3juWrvvsXee++d1DOXnqCOVNEHfK/zzjuvVPb196effjr97ne/S/oywVEaAhAFB1GT+66rPul7eD+8kJW+gXR/+ctfJC2JDArTUkstVfa90rPyx1hEEPSdkC7KzQ0bNixtuummZTv5wQ9+UPZt32iOOeYohcb55psvIU423HDD8vtUsmzKW8rq5ZdfXhIOvj0MOG194YUXTnfddVd6+eWXm7JuY6rQsPjxj39ckuLaKnw47UYfF6YvU2gQ4jfffHPSdpBb8BOX+8UvfpEoP5dddlmbognbaaed0q9+9av0rW99K/3yl79MV199deuYtPPOO5dKv/lKQoS99wwePDgNrjgKkP5mXkJEyPfss89OiLr//ve/kpbzkjlym222KZ+rf95999105plnJvMXQl/67G655Zak7d95553lTxCbl5GGSH7jq4UEY4E+aTyr5tsf7ill2sOgQYPS+uuvX+IMO99/w5axwjhDOe7rWFjE0SYt3iCrYJAdEnfjjTdOlH5KvTb25z//uSSzi6JI5tYc1xyirSG2MikAO+1YPzG2a+unnXZa0idz2oMPPrhsv3fffbfo5QIDWUvbVK7sjOeIQ2M5MkTf+tvf/lbKBOYu8wuyQ18xh5NXywwrf5AMFpnMU9Lnsuv/5nl1Mw4oK/ISoX7llVeWi2bI7z/96U/JfFPJshtuRy3LH/7wh+ViBOzMEeZZ9TPXrrnmmsl3MCaMWu6RKhDofwgM6H9V7tkaG9AJV1aLkACUlmoJkA+Ihtdeey1tt912rUFWoQkwk08+easf4eZnP/tZaTWBac4BJgTM8jItK87ehyRgwUAgE2eWWWYpFUSKjgmE3//93/8lxAjhKjuToDCKI7KBAEGpImQNb2HwEQOEOAMuwkD5xM/OhEdglwa5YrUph7kcjdVWAAAQAElEQVT++te/LldXESCe6zksP2XZRF0vPPxGDoFnn302DWlR4gcNGpSsZlRTEwQQTVYhCCkPPvhgGUywQFRNNtlk5bM/rFYop9oXxZYfRxAiNFAsEBqsKignq6++eqnkUh60cdYtiAxpWAlQIHK7c2WlYTWBEEZoRXxpR5RtirnJXVqCFkuDar/g311OeSgv2jqyjKJTfZeyE7guuuiidO6555ZBVnas/MGj9Pj6jzojZwikFDPe+tnll1+e9Ff9Db7GCiQLRa4oisRCifCDIJCGW2WVVcqVKO/Pzkqz/JCOVhp9P+VGFmgH0lnBgr/v5bnqTjzxxLTtttsmK8/GImNQDjdesG5BdGa/2qtvIg/fCNFYG94XnhGvW2+9dbJCX8+SpC/UsSt10IaRByxizGvaW06nHf/2t78t5xxxjA85DH7GBONL9kPimaMQ2NkPthQtxJe8zUmUIWRFjqOtGsOq1gvabe4P+coiz7xn3lprrbXK5Ag75VAP8xqizphFKS4jVP6Yy5AIiEbzbyUoUdrUX72q/tV745rxDBFoLKuG9dd7ijbF2/iUx6a+ioW2py1rIxZnrKRX64pgRrZp29psDrPSXhRFMq5mP3OIuQIxro/wNwebe8hp+or3UYQp/OZQcchV5hCWRJ45i1Dmf+/MzlwjX3O1sV4fMY/4Xt6JhDA/m8dYScin6uSvP/i2xkmyRA7X54TNPvvs2avudYsttkhICWNs3QgN6OmbIB7h/dxzzzVgCaNIgUBjIhAkRDd/F0o7VhohgPGtfV1RFOUKCqUCmWD1pDZO9Vl+hBqDHn+r10gOE4aJgRJjUmf6aIIXh0MIYMiHt5AJng2W9QQuYZQo4e4JTSYlE5EJCZFBaTWhCq86BMTDDz9ckikUnWpYvjdJVQXQ7J+vzA0pnthyK1DZP66jhgABWhux2uK71ubiWyAXfGfKcG149RmRIA9WEtkfWWS1gzUFPyv3BBVKuGfON9V+8kqgdiQfYbWuKIqk7WZ/eVGs+RGspKP45PDuvqqfLQirrrpqG2Ewv1cfo7zo39p29m/vqv9aRcn9gwCJwNCnCGy+gz5aJQBgCb8q+QOHev23KIqS/Km+X54EWn4UN4qa9J6zs7qGlLSagwDJ/tUrRWrXXXeteo1wTyksiiL5ViME9hEPSuvAgQNLS7U+UqWRrgalHNmNQK+XmOLE+kkYBaee+bgwzpxljNIHPHMUHcR8ts5DQpoPzGPCOSutlCPjj2fOWONa68xn+mr21++MK/IzXyK+KWk5PF8RqqwCEXxM2rN/9apfULqqftV775WeYqVvV8P68z25Qv2thrv2VcfqwxxiAap23FVn7RghoB2xYOXXkdNXyHvmBPFYLLDQ0z7NCQhuVlrmzKIoRCmt8sTPlhA89QnXWqe9kguyv37inQh4+SNLyKu16eVtwYP8hvTI6atXJAkyr+pXe4/YYz2s79WGNfKz9kxeQfo3cjmjbIFAIyEQJEQ3fw2CE4GKsFNvAvJ6ShklhgB144038mp1JgDm2oQXCpFVJcq+1SaRDHxYawSHCcIEYgWVwkKIE4fAZUAXV36EaCZkWG8rUAQ5e3itColvEBVPWaxOMaOjnJjsrOZg2MWrOmmtgisHAb0aVr23ol59rr0viqLcX2wSrVp71MaL564hgMwhjFAK2kuhLVnVqKc4+g7aHseShfkmK5icFwXDCgcBhZ+2ROHQbrQhkzJiQnvzTCHWjlgXaHvaCuGLCSdlRB+xVQAZpw0zmbaSScBijs1cUxv3rp5w+oAy6b9F8ZVAV/teYc4PQLKoZzUccQM7Dn7qTAjTV8WzgqXfw8FzURSlqSyrFKQhP/2K2Sf8PBMybdkwZshPn9pnn33KPcWwISASfAmF+q5xYNllly3Nz63EeZ98qo4Vk/5G6ZNHNSzfwyGTJ9mv9iotIZQ5rXLWhjfrM6HYN4SnbTnIGMJys9ZndMoNi8cee6w8t6heW8p5mwtY0Gh/5rDs78pSBp6cOU371G6EGSPgjGhHzPHTxr2LNVDuB4gDJt352cqpfqFPcIg8eVOgWCU5j4iVjnfaAoBMNXaxDrLFJo9h3pedcYhCxnJI287+1asyelfVr/be+AoLClxtWH96JovAn1ULCwBKN4K3L2NA9ppwwgnrkti53uYPc6f5wmJU9nflBzPO2EORZy2Q5xDynzjZwhSpwZkDct8whyDr8pyCDD///PMTMkNfsYDlvBMyoraMNNO3yHUIDn1y/vnnTywmbQO0EKZsVWe+Ie+av8m01bB8zz8T4tmv9qqvmtsQN9pLbXgjPZvjfBcEI6sSlh7klUYqY5QlEGhkBIKE6OavQ+HqyisoiQbo2rgG9U022aQ8jMsERDGztzLHczgaodDExI9AhDAw+VDa7O0zOFIKTEAEKo5AxGyb0sRM1btNbCYzApN3IT3s6ZWfrR7yMVEZdOXLOUzIeymelEj3o+sozQRXk+bo5tXf09cK//Xw0B4I+PXCHGBISNEGrAg6G6QajxkzgSH7UcyYV7PAYJqvjVjpR2YQjIqiSAQeK6jaHjNr7c4KitV47ZBpKuVAGyQUeSflwwq+7RHyk6/94fm93XUlvHWWt3q1p5wTEFk+IPwoUsgZ15wnZYsgmNNT9AnmlCQm7eqp39luxSJCOsoSs3DkJoKHdRISB07CBw0alFi3SOdAS8QNYYmZLisH/V6+nP4ujXFkTAh8RVEkwrTyep+8+4JDRhHAnSWgLdom0BfqNSp1MI+Yl7qSNpNr1bjmCWQBYpFVk5VwbVe7Fs9cYo5hVeOZM8YYJ5wjYOuWtmsMQXLmfmGcsqJsXOEoueKLKw9nsTAR9x0RE4hQ86l32epIkRCXZaH+IE1X+r94XXGwQAJ2JW5fjWM+gr/vTz5BzHZ/XXv3DWSZrpTAvJCJhWp8FkcsDc0h5ERnM1g4yHEQ1kgB8yo/pLh2rp/YQqhNO1DaXEG2EgdhoW8gE/UVZy+x5Mtbm/Qjc4w5GElnLjI/kAlZ/imTfDmEojzVE1nhfnSduiBvjDWjm1d3poef9myxx4KJLYvd+b7IOxDoawgECdHNX9Rg6hVWbShQ7us5ygDiAAtcDaecHHDAAYl1AsWsGubexEJxoUh65ig1BDAHAnom/FAOpce4m4g233zz8tcpcvhWW22VDKjy42flhyJJkWFqakXIxGd1yz5fq77iUQwx5QRBK0XqyX90HCYeW05gGZ18Im0qf3VC20JUtYeHdkkoJ+DUxnEYGzNS34RwUw0nqFM0tafsjwRjhm2lWNtFKlhxlNae1aIoEiU5t03hhCH7ZK2kyEc5nLPAyoJyYi8qRcHqjBV/1jji2T5AAXffXU7/pXB11K4JSpR8ZSBIumbn8C7Kj/6h/2T/fEVKMJPNz0VRpJVWWikRCMUviqJcrUIaEkLFo2w5Z8M3KYqvzoxATOqjwjlCJPwoPQhKK49wpmg53Ex5kY/5ID55+XZZoJTHqLiiKMpxBXnE4mpU8mjENPb7wtNKtlXzRixjT5VJn0W8GVMoHh29l3WC+NX5yTOiMlvUsXio5qHdaIfaZNXfvOMb5P7C4qcoivLXd8SjqLHUcs9p2yws8njBz9gkDwQERczhchQ2FhMUCXEQTvqNPoIYMT5qz8JGxxnj4AW30cmnqdLWFJb8AH/OOFcU9a3LapI19SNZxvxhHumoIsg3pFp1PhWfZcGOO+5YblMkx/GrOtuJzC/kQP76l/EKQZD7HZKNHMjiVRzypIUFcT2bj1kKsczzzCEhjHcWoqS1rZhc6cwi87I+YRHKWWJkDPVEooyJ9m3eJV+QiZWlUR3rEG2Zs+VV/Ru1rFGuQKARERjQiIXqS2VCKiAFrAwatNurmz2vlBksczWOQY3ShmE10DkpvxpuAqo+53sm7iwoBg8enJAPzmog9NUKdjk+JdEkRhnNfvlKIEQ0MJsk0JksCXPyJlRYbfUOEyEhi8KT047K1cRIIapXllHJrz+nIVxoW5lcqocF4ciET6ivDSeEW7Gyeml1vRreHkmERCDsaB8UX4o2IUYbqabP96wwCDCUj+yXr1ZWkBPTTjtt+esTlIPc9ghRrAZy3O64WqmFjRVT/bPeO/RrgpetDLX9CzGH4GMNoT8iVKp5yLf67N5eW4In/AiC8Mz9T3itE1+c9voLk1rCnDGBxQkyA3mIHKF4sUDxbXwDqzq1+Y/ss/5LmPbOkU0b8RsfASSA/kxJ91PMHZXYvINAE78az3xjlVVb0Z9tN8rh8qW05efqVX/QLzhWRNoZkrQap3rv3fKr+uV7hBySwrzF9Fv/lK8xCxHBilE/NP+xJGTCntOOyhVxUxRFuW1qVNKPbJqI3xgIIAAo6WRA81m9UpmDtTOEfW1fMT9aDEBKa+u1cwZLhto8yXLmfu2ZMzeYh5EZtXE9i++cL3OZ51qHbGBtQd5jNYHwsy2YhQRSwhYSlk36s20e5szaPEbmWXmQf/r3yKSLuIFAINBcCAQJ0c3fi1JCISPEEGzqvY5i4mcPreIgLGrjGNjzqo49ZwSmPJlZzamNX302uTF9pBBY9TGo86NUVuMxtSNc1q7yie+sAKupVqwoNJQV5Ir0mHblV0YKDkXNKhOhUlpxRtZJp34UuJFNG/HbIkABpiA7SA551DY0Je3C3k9kF5KpNtwzIcqp3Mz4KamEA/4UCdf2nLxZ11g10fa0VUJOrVKgLWo/TK5r81Jm70XOMY3WLpj7i0d5oBggvjx3h7O6QUEnaNk6UvsObZU5LNNRGNWGe0YQ+GUSfcjPFup//DmWSa7tOX3LNhjKl9Ur76tV0GAC60GDBo2QDWxtmVl00UWT/k0p1I99b31XfnBVLt/ZyjXC03caIbMueshT1KLo+6uc6tnfnLazzDLLlL/owmJJH6zFQJu0copMFkf/ro3DUsrcQjlCruvr4miX2qr7ek6bZg6OQLPVSB/SXuuRmPqatl2bj+1htnWZT6U1puU5DalHieKPpKDMMWc3R9fm085zXW99VEDMa1DoP85quUNPWRXUm6uMl+RDC0q2p9RrH+Y61nHapsUk7TojiBzI9/Wu+hdiQD+0qKCt576W4+uviAoWdtkvX/Vv2zAQcsgB5TSXGweUSzrnCekrCG7zoW279fpjzrOzq/LIv7N4ER4IBALNjUCQEN38/QhUmGiCEOGe1UB1AjApMSsviiIdeOCBraVBCpicqgqbPfYDBw5MlHzKncieCWUmFs9VZ28rYoDAxozOxIEkIHxdd911STrxCWQmQXE8V53JDgtO6CRQIkmU2eo6Ic1quFVeaZjYUraYzjPHN/HxrzqWFNJU/WrvrRrAyCpWbVg8jxwCtgNYafTLF7bXECCqObAs8E18tyzMEJa1p6oQ4TAqP2/HlF/7kQfrBKs0hBDPVeegQ+0VeaBd2x4g3BkJhCnf17N3WdGkJHP8qo7wb9XFKo3yWU1EcIlDuEJc1G6BmjbxhAAAEABJREFUEDamHKFPnSkl6lFLJFoJtmWJYGgVy3v1K/1M//DMIRAImIgM26ty/flX+7i4nD7pnAfEkBUmYwes5av/62PiGSMQIARFRA+/qrP6hljIh/4hGqxaicM6BqFoT75nZBHClLDs8EzCJP/srAyfc845+bHdqxU9CiYCtt1IEdDUCFA4WNMYT1xzm1Ip4wGi3FYpB0HmfiFMO6VgGF8826KAZHO+iy0R/PRxhIA50HPVUXbsddcn9Tm/9iKcksRs/Msvv/RYOnOc7WK15KB321fPkqoovvo1GQpPnpdcrTozCZeR+dnYhAjUN2rPKtIXjQP6pvjtOT/dZw42lrUXJ/z7HgLaOEsGbZE1Ye0cQj4jF5pjq78QY/41vuf5wVYM7Q9pjDwjm0ELqaztmXc8Z2fct71C+zfu66fIQMS281TIcOLqj/oPctvcxK/qzCFZ9uOvb1iM8j5zsLGelZ0w77PNxtxvvqydQ8iOZJF6fVv67GClryhv9otrIBAI9D0EgoTogW9qgCZoGfgREs5jyO7QQw9N9spTACh1BnaDtPgmGYojIciERDCjwBmgmcJRBgk0iA5KS64KZYHwx1QdAy9vipxwShXFxypVLgOzWEpKvZVU78CeWw2W3r5BB4Z5v/TKbvIUxjHxtm1Eml122SWJU3UmOkKq94vnXv0cxEchlYeJilCY38kv3KghYOUCCQFrK4fVb+Fee2DdYA+pCZ+gLD4SgYUEwUV78nbxWMogLCjUlE0KhtV14ZxvqM3Im8LhvdqBME47o4gL51j4aNtWYAgz4mTHAoIQQ1ng55wSB2V6v7QUIG1bWHc57dA2C/tr9T/vrTqkivMYrDJR6Ck4iD9KGOICMZCFTttdYEuRlwczWv2SQJcFTfWAvXArr8gAuBPIhBEGkX7COYf1Ubb0QcKhONl5P/Nb39CKFX/9LudvjHBwWSb7pFdPJraUSvlXnbFHHpQuZdJWtI199903PfXUU4ISgRZBqu9ONtlkpV8z/oEpfCgBrGCsuBuPm7Eu3VVm57Po3/pI2U4237wc7/UFfZxCYw7yfm3cmQ4UGuSX+9xmkJusDeBtfkTQsRrSjqTNDinnPU79p9QZV4riK2sbypv4wrOjIFHaatuhfodI0PeKokjepZ9q+96vf5rfcp/TltVTuPMjcv75mscg79cf1c/YZZzSH3L59SnjXH7uD1dzufZgzKFsw9m41B/qnutoXrWNQhvSpnK7yVcksq1A5gbjO/kOyYCcN/5oi+7lp5+YM7VFbRVhhkRGKFRxhTWCzgKDOcC5DdlyEZlvrhKuDKwlkXLmGgSg91Qd+cwvYmVSmYynLUurDMg/Mq405D71JOuaA4WLlx2LJ/HMIfqHOdwcYs40ZggjA/Mnp5Jf+DWKM2Zpz8Yzc4TxoFHKFuUIBJoRgSAheuirGVBNNAQVFgdWMzmCHAXCYXOKwhQPGWDfnRVfq0lWfCiLwq1sm2CEm5Csjsrb4CicszJsYmHq6p0YdP7ZUQSdgkzoUwaTD7Pz/I4cz5XQVB1ovQ9xghwxoTgROE9u4ptElQsTbh+7/KvOapJ9hZRerLnB3EoyUz/CrDxMrATDvBLFL9yoI0B5Rh4hFQjl1e9BSLCqmXNHhCHAnBPAjJ/woj0JJ7wgMghEhG2kge9JIMkKmm/o+4tH0VhmmWUkbXXaGCU39wGrJZR4wllrpK9vrN5oR1XByH5tFjbqIEzb/zp6t12UWftUZnX37uz0DdYehDoFIHBa7SKgUHbUT38TxlHeWRbJy7YS+FvZ4oRz+ivFxoqv/lutP3xhQNDLZbDShaCRtup8H+MHa6nsjzTMabWFTPDkcPVAWiAFbeHJ73Bl3eRXIZTbmKEe+rhfM9Ff5UHpIkxaOTZW8GtGR6klSPuGsGDJk4mcRqxPb5VJ+0XQsLrTRjhjBkWpOq5YDUYaUEa1G/NGbjO2K1F0zFeUEf7w144oYblurAn1edZRxpVqv9DW5CG9MnDaMZI+p89XK8dIDO2YnzlLP0CySe8d5mBzsXCOBaC+iGBgsSH/7OTl7Bhkhf7uDBvnIpnb9VfpKYnakvHSc39xvq3xnqWI+cf4Z1zqL/XP9aRMr7jiionMVDuH6CuI7nwgpTHY/Ko/aDPkNFs6cl7OaPLLSOZp7RsprZ2xEspxLD7pD0hmJF8mEIQri75hfsltmKWd9lsUX5F64mVXJRn4Gdv1EeWy4MB6jn925A0EB2KjOi54F1JSXyPvmieNBeQHxAYSXB4sCMnJ+riy8msUZ2zSnuGPnDaONUrZohyBQDMiMKAZC93MZaYQVF2t8lUURbl3uxqHkm+SUW9XwpNwEzzB2CRjwrLqIA6hSr4GTM+1LofLg6N4VgWuanwTindU/QgR0nG1YTmeOARPcaqOklYURfmrDVV/q1VFUSSr4hRgih2/nF9cRx8B7aiKufvaXE36/LPzDbWXHM9KhzBtxrdkeqkdIsYoDEVRlL+HLo68crp8LYpvwsWhELDkyeHVK8FJ+6v6af/ScbVh1Xjdca883lt1te2/KL76icocR/2ycKlMFKcchtyAHQKQgE6Br8YhjHquddU85NVeP9Gnvb+aviiKlNtBe+MDjPN3ln920snLd5U2+yOn1EUY6xjKI4WxKEYUaMVpBmf8gl2uIyIOnnXK3u+9YJVxcqVMaKNVYLSPapsxrvDLcbRhaTntC4FhWx5BP8fRV4R7X/arXnO4OFx744r3Gju085zeGJfnVXNnNSzHca22Ce/gtA1h3uc5OzjwNy5SWhArtlbx6y/OHJHxyNf+3I/MFxmHfDWvVNsDzLTBHK6vVOeQah76ijZJqbelliWivOTJX7/yXOtyuHeI195cI53xvdoffD9zgbScOLVOfASJ8KojN4ir3PLNYcYG/VIYQt47sqUSv0ZxypjLnK+NUrYoRyDQjAgECdGMX62mzIQbg7uf3KsJarpHrDgiwgFHTVf4flhgygZLHiSEAzD7IQSjVWUCJ+sC5uG2N4xWZr2c2JYSq90sMwjR3V+ceENfRYBSZJWRdQIrgmaupy2ItmesttpqiXLVzHWJsjceAkgJFja2RTrvofFKOHIlYr3nrCfEysiljNiBQCDQbAgECdFsX6xOebHkzOlYENijXidKU3gx1bUflyKDRW+KQvfzQhZFkZgu2xNqNb+fwzFK1WfqzaKEaesoZdAbieq80zYtq1e2cNUJDq9AYKQQ0JaYbzMbZ6I9UokbKPIll1ySmNM7P6eBihVF6UMI2Jbo19XIgc1cLds8EJAbb7xxM1cjyh4IBAJdRCBIiC4C1ejRmJLag0+hafSytlc+e+HtGXVtL074Nx4CVmKc60CRbrzSNX6JWEM4tNKhbV0pbaPGYQHBNWr5olzNh4AD8ZxFwuKq+Ur/VYn9apQzkJq5Dl/VJP42MgIsYp3V1chl7Kxs5AgHaVpY6yxuhAcCgUDzIxAkRPN/w9Ya2P9HIWz1aLIbQlreX9tkRe/3xbUf2gpGHwei26qHiHAOQ7e9oAcytgVDPXrgVfGKfoSA/ef2mDdrlZ0/YXxs1vJHuZsHAedHNE9pRywp+Y8cOGJI+AQCgUBfRCBIiL74VaNOgUCfQyAqFAgEAoFAIBAIBAKBQCAQCAQCfQGBICH6wleMOgQC3YlA5B0IBAKBQCAQCAQCgUAgEAgEAoHAGEIgSIgxBGRkEwh0BwKRZyAQCAQCgUAgEAgEAoFAIBAIBAJ9CYEgIfrS14y6jEkEIq9AIBAIBAKBQCAQCAQCgUAgEAgEAoExjECQEGMY0MhuTCAQeTQyAp999lm67bbb0tChQ9u4iy++OH355Zfp8ccfb+N//fXXp5dffjndc889jVytKFsgEAgEAoFAIBAIBAKBQCAQCPQAAkFC9ADITfWKKGwg0AECH3zwQdp8880TYqEa7corr0xbb711K9Hw6KOPpt122y3dcMMNrdEQFxdeeGHrc9wEAoFAIBAIBAKBQCAQCAQCgUD/QyBIiAb65lGUQKCREXjkkUfSfPPNl5ZYYom0xx57pMGDB7e6M844I2277bbp448/TnPOOWdaccUV0wQTTJAWXnjhtMIKK6Rpp502bbnllumoo45KTz75ZCNXM8oWCAQCgUAgEAgEAoFAIBAIBALdiECQEF+BG38DgUCgAwQeeuihtPrqq5cEBLJhkkkmaRN70kknTTPPPHMaOHBgau/fRBNNlPbcc8902GGHpU8//bS9aOEfCAQCgUAgEAgEAoFAIBAIBAJ9GIEGICH6MLpRtUCgDyDgDIhzzz03Pf/882n//fdvt0Y77LBDmnHGGdsNF7DyyiunF154Id13330ewwUCgUAgEAgEAoFAIBAIBAKBQL9CIKUgIfrZB4/qBgIji8B7771XEgfIiNlmm21kk7eJP/bYY6cZZpgh3X777Ul+bQLjIRAIBAKBQCAQCAQCgUAgEAgEug+BBsk5SIgG+RBRjECgURH4/PPPx9j2ibHGGitNMcUU6dlnny3Pj2jUOke5AoFAIBAIBAKBQCAQCAQCgTGJQOT1DQJBQnyDRdwFAoFAHQQcMDnZZJOloiiSsyHqROmyV1EUaZpppklvvPFG+uSTT7qcLiIGAoFAIBAIBAKBQCAQCAQCo4hAJGswBIKEaLAPEsUJBBoNgfHHHz/96Ec/Sg6f3HfffdMrr7zSaEWM8gQCgUAgEAgEAoFAIBAINCQCUahAYEQEgoQYEZPwCQQCgRoE/DLGGmuska677rp0yCGHpJdffrkmRtcev/zyy+SMCdYVtmZ0LVXECgQCgUAgEAgEAoFAIBAYaQQiQSDQoAgECdGgHyaKFQg0EgJTTjllOvbYY9NOO+2UzjjjjLTgggumRx55pE0RDzzwwHTooYe28at9+OKLL9JLL72UHHA58cQT1wbHcyAQCAQCgUAgEAgEAn0CgahEIBAItI9AkBDtYxMhgUAgUEHAdoyjjz463X///ekHP/hBWm211dIss8zS6vjtt99+6YILLkhbbrllGmeccdIxxxyTNt100/Tuu++WOflFDD/ROddcc5VnTJSe8ScQCAQCgUAgEAgEAoExh0DkFAgEAg2OQJAQDf6BoniBQKMhgEC45ppr0jPPPNPGrbfeemnAgAFpo402auN/zjnnpGz18PTTT5dxWFI0Wr2iPIFAIBAIBAKBQCAwughE+kAgEAgEOkcgSIjOMYoYgUAgMIYQsF0DSTHttNOOoRwjm0AgEAgEAoFAIBAoEYg/gUAgEAg0CQJBQjTJh4piBgLNjsCf//zn5GyJDTbYoNmrEuUPBAKBQCAQCATaIBAPgUAgEAgEAl1HIEiIrmMVMQOBQGAUEXCI5S233JJOOumkNN54441iLpEsEAgEAoFAIBAYAYHwCAQCgUAgEGgyBIKEaLIPFsUNBJoRgbnnnrv8dY1mLHuUORAIBAKBQKA9BMI/EAgEAoFAIBAYeQSChBh5zCJFIBAIBIWduKAAABAASURBVAKBQCAQCAQCvYtAvD0QCAQCgUAgEGhSBIKEaNIPF8UOBAKBQCAQCAQCgd5BIN4aCAQCgUAgEAgEAqOOQJdJiC222CIVRREuMIg2EG0g2kC0gWgD0QZ6qw3Ee6PtRRuINhBtINpAtIEmbwNdJiEWX3zxNHjw4HCBQbSBaAPRBqINRBvol20gZIDB8d2j70cbiDYQbSDaQLSB0W4DXSYhttxyy3TmmWeGCwyiDUQbiDYQbSDaQE+3gXhftLloA9EGog1EG4g2EG2gj7SBLpMQo77jI1IGAoFAIBAIBALNi0CUPBAIBAKBQCAQCAQCgUBgzCEQJMSYwzJyCgQCgUAgEBizCERugUAgEAgEAoFAIBAIBAJ9DIEgIfrYB43qBAKBQCAwZhCIXAKBQCAQCAQCgUAgEAgEAoExj0CQEGMe08gxEAgEAoHRQyBSBwKBQCAQCAQCgUAgEAgEAn0UgW4lIZZaaqk0yyyztLqhQ4e2gXGjjTZqDdtxxx3TO++80yZ8TD/89Kc/TbvtttuYzna08vv888/TH//4x1YcFl100S7nd9NNN6VFFlmk3fgdhf/rX/9Khx12WGtaz97tey288MJJ2tbAOje//OUvW8sM11dffbVNrLPOOivNPffcZZxVVlkl/fvf/24T3iwPRx99dFkHuOy8886dFvuYY47pMH41fKedduo0v56MsNVWW6Vrr7223VcKf+aZZ8p2A4967vvf/3567bXX2s2jvYALLrgg/eAHP0g/+9nP0pAhQ9Irr7zSXtRu96++4Pjjj2/9njvssEM1aIT7W2+9tTUubE488cQ2cdZYY4024eJ873vfaxOn3sODDz6YTj311PT++++XwZ7z2Pp///d/6c477yz9O/uz1lprpXvvvbdNNOPPb3/729ZyrbDCCm3CO3u47LLL0i9+8YvWaPJT1vvvv7/Vr1Fv9D/fgNtvv/3Se++9lzr6p/+Ly+27776t8V9//fW03XbbtWIonNt22207yq5hwz766KN08MEHt9bHPN1RYR977LE0aNCg1vh//etf20SvDb/iiivahOeHf/7zn+mAAw7Ij0k+cOR+8pOfpKeffro1rN6N+LPOOmtZjnrxd9999zJMfr6X71Yvn1q/PC9K11FfU/7ZZput9R3ic3/4wx9qsyyf99hjjzLuX/7yl/Tf//43mVP1nzKwgf+YI9Qru86K2ln86667rsShvfzWXnvt1vDaMbWzd/dEuDLlsm+yySadvjLHdTVntJfg3HPPTZtvvnnd4Ntuuy2dffbZ6bPPPivDb7/99rTkkkuWOGmv2mIZ0MmfVVddNd1yyy1tYn3wwQfJHKx83GqrrdYmvKOHeeedtyyDdOeff3764osvOopehnnfIYccks4777w28e++++5WGXKeeeZJGSt6wumnn97QMqV5Mcu/5urnnnuurGt7f2rjP/vss22iXn755a1YyK82XGTj2Q9/+MNyLPEcLhBoBgQGdGchDW577713OVCedtpp5U95VN9H8TjhhBPSBhtskAzkk0wySTV4jN3rwN/5znfSn/70pzYK0hZbbJGmm2669PLLL4+xd41sRuecc0666qqr0l133ZUoeJ988klab731kmtHeQ0fPrwUfJ9//vm60ToKlwYWeYKjMOyyyy7JpPfkk0+mrbfeOnl2X5u5Se/II49MJgFhJhkD6K677prefPPNchJBqlx88cVp2LBh6fHHH0/LLrtsWdbhLWWWphmceu6zzz7pb3/7W/ldbr755nKy3n777VM9QTHHv/766+vGrxf+j3/8o8SlXn49hZFvRtHWD4YOHZo+/vjjEV796aefJv10zTXXLAWM/fffP1Ha3njjjXTMMceU9dV2tQuTo/5sQhwho3Y8EFTjjDMOZTrNMcccabnllkvHHXdceuutt9pJ0f3evhelgIKgbsYyQhEipt73evTRR9Oxxx7bisXhhx+eDjrooDS0BdNc2rHGGivfdvnq++hLP/7xj9OEE05YkjOUYQSiclGkKbv6cL1MEUK/+93v0re//e1SqVOvajxt3DfMfjfccENafvnl67aDHOfDDz8sBcYFFlggrbPOOmW/z2Hq6PtdcsklJRbZv5Gu2rN5aaKJJirLqI/7vieffHLdYooPpwkmmKA1vr570kknlfG/9a1vleOeeKVHk//RHrQ7xLQ2hvRCutS2HdVEjK200krp2a+FZs/mD9//yy+/LImz2vBtttkm5XB5cMaACy+8MFFGzCnavP6EeFCOgQMHJgsV9TAWX37im7Nq47/77rtJnymKoiQyEHHmVwsSrt5fz1F2Jp544qTucNCff/SjHyUKX7344hoT64VV/R544IGEEFx88cXL8iAnjb+UvdVXXz0hgarxG+kegfSrX/2qVAhhMtNMMyWLFu2VuV78hRZaqLWOiKODWwgvCqb8yGk5XJ5I1jy2efYdDzzwwLK/9TYu5gFtQh2UnQw3rEXm0f7r9RVtecopp2wttna59NJLl32h1fPrG33u97//fXrhhRe+9vnmMrxFjkJCSGvsEfc3v/lNOWcqx8Ybb5z23HPPZE76JtU3dwh+ZJ854ZprrhlB1jR3IZJzCiQRcuXtt9/OXiNc5bnyyiuXcoEyGEuNsco5QuQaj/vuuy8deuihCR6CjBtkYnOtviY/5V1zzTXL/kJPQLScccYZqSv9TZ496ZRZ/XO7mGuuucqxC9FYrxy18S1MGOtyfISSuSbnVxv+1FNPlfnPOeecSVuo947wCwQaFYFuJSFUeuqppy6FZwKf51pnIJxqqqlqvcfos8HrkUceSSbMasaEAAp/1a8n7//3v/+Vq8o///nPE5y8m7Jn8rjjjjs81nUEvSuvvDLNN998Ix1OiLv00kvTwBahDvaEMM+IAgIAJWLFFVdM0047bfrzn/88Qv7eTWAk9Jkc/vOf/yQrxCwnCKIEN2EmYnUae+yxS5JpvPHGSwSSETJsUA8T4+Ut7PNZZ51VlhA2hFbEme9Telb+5PhWJ3jn+FYDxO8oHJ7S9IYj/JnUzzvvvFJR1Saq5SAQmARfeumlZOLPYZNPPnlCHFTjU0gRewQSglKO29EV6XHRRRelySabLFHyKP7zzz9/GjBgQKLodZS2O8NM5r4/xch7jB2IOd/TWMKv6lgCEc6zHyKGVQgFN/upnz5TdZ19e4SP1V0rrPKhEPkOVr08U+iQEwRFfZtf1V199dVp9tlnLy0pjLPTTDNNa7AVKAQUwTmXyVhJkesIe+EExptvvjkVRVG2m9ZMW268b/rpp687frQE9/p/SuoTTzyRttxyy7IssF133XWTvq5epWflz0MPPVSSqYRi3jm+vp7jU8RglnF0rQry0jWD03eN04MHD06UamWmAGgjhF3PVad/WJlTX46grC9rj7ARrq0K42rD5WXOQMazmCuKolwoMCeZF4uiKMvBGkO7QxZJU3WINnOV/mncUO5qfES4ecr3LooiTTHFFCXRbo5FSFTzqt4jRIxpSAL+MKFQUAiMW/xqnf6onlWX2424LCmUkyWGFf6iKHiXTr+2kkwGKD0a7A9SmHKEgJ5xxhnL0llwgD+lsfSo/GkvPoKa/FIvnGKZw40v5IeMpTYII9/6xRdfrLypd27NA0cccUSywKYE5B3k+d///ve6yqD5ZMMNN0y5PhaCyGEU1mp7ImNpm+peFN+0D+/gYE4+m3nmmT2mM888My244ILJKjgPBFdRFOX8iaDjV3VwZUHrveOOO26qEiPi+ZbIiVxOlq7Kow8Jr3Xe4XuSeXJfQZBwxo7a+NVnbcfiVy67MOOB/o9c15f5IeiMD/qOZ1aTMFAHz43kjBubbbZZMm8rF0LI2GkRgzzFr+rqxUdY5fgHt5B0m266aZv8quGw9z6WVdoMQrOaf9wHAo2MQLeTEI1SeYMZBbtaHkKJScNgVvXvqXuKDnY5D1bei800UBlkPNdzzFspE4ThkQ2Xr0mI4AgPk5/8TGiUSvlRIEwoiAXPVTf++OOXAhxhiT9yAZFDkcX+IzVYWlBShXPulVd9PTeyozwfddRRpWUKBZvilsu7xBJLlKsGeWUm+7s+/PDDpTJWG59iKH69cCRYGd6LpuvMlm2BUId6zvekOGhrhPd6cWr9KCGwq/Wv9yx/q57VMEq19mlFturfk/cETN+Sy++1CqqN11NcCFwUlByXab+4BKfs11X8cnwrJARCykr2I8gyTc3P+rCVQ32Y8Jr989W3rabP/vnKVNxqY35m4eSbsHbIfrVXAiAlqj1iWXyr34QjiqPnRnKEa+UxZrlyCCPCb73yim9M7ig+gsmqpLya2VGSrfCaA3I9vvvd75bEAIUh++UrZYaVSPXZmGLVWvsXjjhrL5y/d1I885yCnGeJMcMMMwguXR5/mPaXHpU/VkM7ik9hpSgZV3IySvSkk046wvakHI6gs7JtjM5+rsgqY4Myeq511fGiNkw5yBzwQfTXhntGdOvjiBPPjeSMMcjW6jiHcDTeI+pqy9pZfEot0svKbk5bzc+4ZHzKYZ6RPNpnR+NTjt/dV/MA2YaslN9lOxtyRRvJfvm6zDLLJFuC8rOFHxZu2m/2c4UlQqOKM3/unnvuSawtKeWeOe2UBaF7Tru2FUD59EF+Vbf++uunavpqmHvEQfXdlFvzDFlReK3jb6GF8pvHQHIiYsQChr5ZmyY/I9z0qaoMru+Rw+SHVBRXfupoTvTMUbyREPDy3JvOApy5k+xL1jNe5fL4HuRr7V3bzf6uxr3a+OYZ5JT+o3+oXzW/arj8kLXGWfmFCwSaDYGGIyFM7phDwgbWe5ZZZinPPahdATFRE4aFEyCt+NWCf+ONN5bm4+Jg72uFdJ3bCpZ31qbtiWcDl0HbYJvf55kCRxHIftWrCQ42JjQsdjXMfWfhGGbvyIOaSYrCVFWQhJsU6pUBUbHYYoslA6H3ceIrM2HEpEFAyKZkwpXJYGty8dxILpeFwoSNJ0QQdggGBNUc7mpioIwQsD1XHUuBjuLXC9cu28uvmndv3qurlR19zLftqCxW9e3rJChWFQgCClNN9aXQWCXN+ai/9pKf85VSr19akcl+PXm1RavaL73b93eFiWtHzqq6VS8rqTmePoFcgQPXETkgjRVXyrx+5ZlAYgyrYuubKKe+SiARr6uO4szMthofsUBZq10dq8bpyr36EWStbHYlfk/F0d70ReMdAjW/l/JI0K0do3J8eLQXH/bavm+l3pxtMsaQnH+zXFmIaBfwyGX2TJA2V2S/fDUuVJVI/nCinMGzXjh/bdpVfESb+QNR7Vkbh7t26JlTHs/mKs9V11l8CxDM2hH+OZ2+yFKjXn7i+HbGpTxP8uMsEiA0kMeeq04aSpfvn53tXDmOrVnGQm0j+9VeYcDCkaJZG9bbz0gUdadQVcvimSJa9XOvn3UUX36+s/TiZ+dZfsZbMmD2d9UGyD36r+fedBROY1y1DMZP31D5q/5n1p4ZAAAQAElEQVTuyRe17Ul847k6icPZmoy8rvrx52w5QkJX669te6dwTjrjVVfmKfFr3Zprrpnkkf0REEhJ/Sj7Va/qaq7Wh81HOYw85Fn/zH7VK6tCVo/qU/X3PmMDQrg6pxljyZI5rvchU8y12a83rvq6BQqYGVfIyMarXBbPvg+ctPfs74psEV6NL58cHwEuHCklPlcNr81PeLhAoJkQaBgSQmc04RBomAjbx2wFFlFAkGGmjYUHrj2VJvxsIsZczAqDVX7hBEnnHSAqdGLOZJhXcqzI2/dMITCRVAc66XvKISGKokgG3fT1v6Io2jynmn/MW+FUHZSqUToLp1BiqPM7CZYGTpNFNZ/a52pY9R6uvhHBCXFhorIn0Z51rLWJBEOMREJWVNL26i3FweStLZnM7DW1LcAKlMOatJXadtFR+bXNjuLXC8/foFeB6OTlTMx90+pqTzUJwZ6Coi5WJpBNVt9z+3HGAEXX4Yf6IdNCKyvypWQjEn0HcUzmtq3I38TLQshKh+eedr6/vlF9rzpWn+vdW/VVD+OXeiJHs8KizRG84EDx0v8JsfWERTjqVxTb/B7ESFEU5VaVVPnXlXJVond4C2+CIaKxw4idBPr+FDYHu9b2i06SdmswoQ2Zo3xF8Y2ps+f2Xtxe/KL4Kr20lAkEr2+L0LQX2gpVe3k2qj+z4aIo2rSxomj7nDr4R+Ewv1JkKBK1UYWzDGMynsMpF/oBHMU3f5vfi+IrfPkJK4pvnvll11l8xCcrC3vUfR/lo8yRF9ob041r+mVteEd9jSk0ct47OOcHWXW2LcdYwrKQZQXzfWME8pDCbazJdXE1j7IO6WgFWbyeduQE/acWg9rnXC4kREfxRzY/34MsAdeq0pbf19NXsqN2Wfve9vCojYcEsw0pH+xrnCSHmEMQebXxhSO1EPQ5jNxMBqt9Z71y5TQje7Wl0DxtcaZeWvMaEqL2ncpUFPX7rP6BhKpnEUQBR94PGTIkWbBQR32ILCHPahmUy1xa24eqccb0vXarLzv7SD82z6sL+ce1KIoRxs/acqev/2lDRVG0iZ9a/mUsOwtviRr/A4GmRqBhSAisN1KBYoJ0ICRQtAl3VgwNMiYhaFN47T2nyBDqrVgURZEMhAZq+/YNzPZaic85bMc73BNIDGh5fxm/ZnAUZEqawa9eeTsLl8ZK11RTjbkzOJiSEbiRQL4VlpbwbQ8bgYHySUml2HDK0NuOIIw9Z3FD6bLablKkNPV22Rrt/QR139RqaL2yWZlyIKXJuGpqKi7lwMRM0MirHQ5e0x70XSb9FG0rJvaF+gbVNmLViIIir2ZxDghTD+a4BCl70527ofwESHV1j2w1JomLoONXdZQwKycIsqp/d94z67VPmfA3Jt6DuKKEEKTGRH6NmgeFyJaEPH4whWZWTzimaDRqucd0ufR3Y6r5mal5bf7C99prr1QbTnA3JtTGH1PPlH2kuDGITGAPPRmAP1JgTL0HccfaIedHuWRZZ64x7yIVkNGULP2eIoPgRcBWLTKsjIsLr5xXf79SdCmi2ol5o9nxQHIZ//UHi2HqY04k85obPNc6ZD25VpzasO56di6B+Qvxk0nD0X2Xb4lks42QbFEvP4uI8LFV08KFNCxJBg0a1CY6GUEY2b9NQDc9OJfEeWfOA3JeE9K2I8umbipGZBsI9BkEGoaE6AhRrHB1AKQY2V6BgaymY6JmQKIAMB+TrhreEPeVQjBZNanYi1zxTspdra8wwiyhxqBngOZYejBPc88CAh7thbMqQeRYYZVfdhhXEwEiJ/vlKzzzfb0rhtrBTAZlQl2OwxTQ5ErYIzhkoYr1iboqb3YECitjOW2jXBEqylpbHngRHGv924tfFF8drNZeuPysntXm1yjPLFk6KouVQocwUrgdzIjcy/Gt9BO6Tdz5eztsij+hO1sI5Pi1V/1Dm63174ln30ufq31XURRttiLVhudn6fUL/dvezuxfvRI2Ken13qOfZtI1p5Fne/GRRL5FjjuyV+SmAwntwbZyLL1xNH+3fB2Z70FhUF6kn/wawRXFV/3ReGd1urZMk002Wa1XgvvIxJcBUk5eI4OXdL3tECrm0NpvhmxkndRR+RDOrJdYHNSLxzoILgibHA4fc1h+dvWeoihSvfFB+cSpOvE9dxTfWQPKZ05CFOpzZAR7qZFvuX27WonW//QnZKC8q46/Obrq1969VWvlynja/26blvj6mfEQSUfB5Mfl9iad50Zx5qmiKNr8Go6ysQDRPtxXnf5fFO3Hl5/4CBfX7Orlx6LMXGJhI8fr7av+rZ3UlkP5fcNa//xsXHe4JouXTNxbXWc1RhbSBjlndxmDzSOsq1hkmU9yPq76g3HMfOq56sgpRVHfEqEar717Z0qw1PBrJCyVxKvKl8rIIRF9f23ceC9e1dXKkX6ukrUzZzHRopV6U+w9kw+kZxWiv3IICOn4CcvON7Dw2CiEXUflgRF5L5fdtbP4sGuvfvIrilH/vt4fLhDobQR6hIQwONUbJFXe6r2O5r4rjoDEbJ6pn4F88ODB5SE7OrP0BkEriO5rXaM9E8jUx4E1uWyeKb9WEbOfKyXDIT72WPtZKI55nInGvRUXq/rthWPbKXXyqjoTJmHA5JKFHgO6Ad+2jWrc6r2JYtddd00ES+dqVMOq94Q9k40VcIKggVN5s0MmqUc1TXffK4MtA1bwMfz5vAJtMb+bgEo4zc+uBAJ4Wen0XHWdxW8vnEBLGa3m1Uj3BMnOyqP92C6lLoSITFwQtpgh2t6SvzeiwoqPFdOsPHSWf2+EExAp5tV3s8pQH5ZaVf/27gmMhI68Ql4vnnCrObVhSEjvqvqz5CKQENiyv3fA21hiLMj+I3O1SkvIZbVSbdsUyvzd8rXeGDIy72qEuL6tlWirkbk8lECKQ72xyIo54rs2vnGkXvycJyuW2nE8hzXqVVtVT4pxLqNnRHVH87RDZJHNLEDMVTltvrJshGNteL32BFfvrK5umu/Ni+axnGe+ep+wrsY337JYQJbof9p8bt+uVjZ9V30QgZrf42plWD8cmdVobUAa+dUSLtqIfg5f+TeyY8VVFEXy6zLVclqMQKhU/dxrD0XRfnzh8Lc9RvzsavOzZdKWAPJGlvNy3N682kqDYLZNLpfDOELedYhi9qu9IlSkQS6YM4UjE1gBIyK0Qc4vMhnXza1+YUY7L4q2Sqcxi79yyIdDmCIGEAfaFr+Rdb6x7WUIQ1secnptQNmqDg7Kb35EiOS4ykQ2VL7s56o/ODvKT5DKBwmhH5ATEB7GCfGy07dZPLOgchZa9u+N66BBgxIizFzJusrcTS7PZYEFXcecmv18D2OTNlH7PTqL7/trT1XZtJpfbj/5XXENBJoNgW4nIZxf8PbbbycTCaWkCpCB2KCL5cz+hGxEAuE6+7lmfwSDLQAGPYMZf5MWoUU8kzmlzso/xZof5ZowYTDz3CjOKdnK6zCrPHhjnwl76qCcMMKAuzcBEGaysxpjEjdZSdNROGXSgGXQhJn8OIKRE5pNOllAMoFZdbC6LY5BEMZw9G0I5CYnAqXvIYwzAYvPSYPIYCFhoMX4K69BOJff1TesnaSk725HAYaXiQ2+GH9nixDCmVFbwYKZ1WFl0R4dFqY9m5Q9w8kKhnCTEwGpGp9VQI7fUTgzYXn0ptMmfNvcDnNZtBf+XPZzrY1PAUYOakNWKxBZ+jUB34qO9ul7c/ou/IuiSN4nb3jKt+oQXQSpql9P3RP6WPSwNvJO5XOeipVTbdozxYgz9mg/VUHBWGebBWGF2SlBxbglL044xd+qqzbIr+rgpb/AOfvrOwRxeOpf/I1p2i/lzFhAANIPCSrCs5MPnF2zn6vxBZGoDfom+jEnT8++V9UZQ6Tjcl75yq/q9A+k3cgobNX03XFfFEVaYIEFku+HiPAObZAiRAhWP89wITgWRZHyFiHjXo5vPnN4HMx//etfJwQlfIUbE43phGv58WsWZwzUNs0H+bvCxrhIaVQPY54VYBh6ZoUnvjFT29N+uNxGjQvwMgbWhsPH/JXzkp/3UF5sV/AMV/gaN2xF9MxCIRMl4uuX5nhhXDW+PDgr7srlV46Qpchn/kiPahuXH6LK99X/9THx1IdcoU/77p7l5+oQbD+daBFBXA5GzMkpK8quHenzOT84U0iVh7IhDafvIWd6Y170/vacLTbqYRzM9SSviG+ecyU36Pf6UHvxfR9bV4QbY2FXzS+Hy88coE36mVM4w5vTN8UTp7ecbYbkJ+0ut1/fV1vKCzhkIP1FGclPl112Wflzyc7NMsaoizqaLy1USMuRi4z/+gf5iSxCUS+KIuV+KU/Olj+Eufbt2TfwLt9EO81zgnFJeHY5n1z27G8eo2ibA30XZeS0y3pzgrnKwYxIB99FPtq2RRyWrvlZ31eW2jzIYeYJbV7dhUujDvBjVStv2wTJGcKyEy6+dpn9uvuKJEGG6AfmEASJMYMlh/LDwtZy2CkLGUEZs0xv7NIm1A/RXxtfmPhkJ/KXcNtXcn7VcPlnl7+nvpf94hoINAACHRah20kIAqjTfg1q9nZZgcjOSoTzHigrJmb7kU3yOpnJO09wOqsBW7gJywBPMGKmZeVfXAMs5tZhiIQLgqYVDe8Sx+pHURSJICkfE2WHyPRQoBUkLP9RRx2VlNUkRWGHmyKwIHC+ArNVzyZejLO4fq7JxIxBJwSaTDoLp2xUWVqD/xprrJFMglar5EuodOqwyUF+8CUkWXE1Ydr2IQ6hkn92BkvxnQBupZupqbyx3vbBKn+jOoKgVS5Eg7aCtd5xxx2TesAExiZ6bVkdTMgmIt/Hs9Vx8WFTjS9dR+GsV4T3ltO3KAnOK2C14p7gnYUJ9dI3CdTKqI3ByTka2p74+qQwk6zVDSv1SCrnPRx33HGl0EQYgQun32oj+jp8CE/IG2Hy4fRnwpAD7jz3tFMXVjL6onL5TvqbcUxZCHqsjxwcSUAkiLHyEJezrYEw4BA64foIc3BhnHB4W/mRX60jVMlTv66GIf5YntiaJR/7ZhEQBEbxkCH2udvH65lgIh5lhwDoHtaIE6QI03BlcVCgMmbHzFYbl0etQ3D45iyc9Hdnwsg3j1E5vnGKstFofZ9gR7HJ3+OUU04pzxOimCq7Mc6Bgn6qzrP4lAZkjXrm+M7BIeSbvxARcBRuCxqBGqkhfTO5oiiSMcyYr2+qD4WeEpgVANvqtD/tVzglSJ+2Gp7bj6t2Jlwbc60NN+bAxjxDQXHPUUxZquX0cEUMI3Xgba7SbyhZxiPxEQPtxTfGkQucvaButhCSRSh53teeGzx4cEIgmseUX3sxn3HSXHLJJUnbUA9l0SfM5+JyLO3MqeotPnkHge3Xg4RrT0VRJNtDhGdHsWE1ONlkk2Wvhrn6zsZ/WKiDNmI12zdUSFvzKOf5e3YWv6NwchHyyziij2lT2bGgNA55Z285MoK6I5jND/AwzlpYgil11QAAEABJREFUUyblM49YbNJmnQ2iL5Axcj1cWd3AURrOvGkM0Q7U3ZjOj0xI2TV3iped9mS+1q6VQX9B8Ji7xfFe84N52bOFAvIbwsQc5Qw187l53vvIzepEjla+7MwJyAV51DqyEOIQSa4M2r1vZl4RF3FOPiR7e86OAu/9SA79R1pKOnJBGcihxh3tBJY5Xb7SAyj+SJvs19NXYwtHZuGQJr6RuVl9nHdl7EE4KJuzJGzLoot4zvGNA+L73uanHN9YK7/2wuky0pnzfU/zMgK3vW/lneH6CwKNX89uJyEwepRog4jBtgoJRcVKYNXPSofOZhLO/gYfSrpBOOdH4bNSYKI2mZsEhEuj8xIKDc6eDdyESgN99uPfCI61gUEpC+qUDBNGLhvBhSJMkcl++cqfkmeQzn7Va71wk4KJhhKS4xKS4It55WdViUCO5c/Pvh+m3mosIcxzraOAis/Jg8JuMvLcLM6ERvFUd1cDurIzezSpEDrzs3aKnffM+XYmTvfiC8/x+dWGa6PVcHF6yyH21BV5Vy2DPqtf5Qkzhw0aNCjpc7XxCSq+uVU/cbVl7YTC7pkSwS+nI7yKn5/F4SiCBFkKjufecA6upXB6t9VSJEMel3xfz5xwq8D6sntOn2JG656rF24ME1bPeR+Cg4JTDTeW6fOUI/4IB+3KPedZP8wCKD8O5vpjLj8/jqLl+9Q6bd/YKk57TrjVX2NFbRwEldUg7aE2rLefzRuUasK2siB8fAt9Pz8TDCm2nnN8Fj6eKb3V+IRrygVCVziMKdHtjcviNLLTJnbYYYeUy68fsP7JZUYAIGCMkfxq205+pph3JRwBTMimqInPsc5D4LmHq3EA+eGZDIAUouwVxVfm6Tm+8aU2vjTceuutl5QNuei5M2ds0r4p1eJSsijf7jnPwtVTGzGPW60WxjG3F+ae03ctiOjXno0RnvUjz9khB82f6pn9GuUKC/Mg6xVlQgxRVt1zng899NCkT3muF5+FiTBOOEyr+VXDKeO+Wa3TRhsBH31DfY3X6mO+qI69nhEVwshP9eqD2KZsi5OdvmUMIttmP1f9joWl++xYShjbycn8jPXG5IwPkhpBUStrIA68u1pe6fWtWrw9mxNynuJVHcsh9SQb8mfBaHxl6ZuflUHZPFcd+YIsBAP9N4fBi4yBzFPH7F+9WjDRr6t+vXGvfPq772YOJhdkYkT5Mi7KZq4wVsDMc44vD8/iVxdfzC/aWHvh0nCIC+MJAtxzuF5GIF7fJQS6nYTIpdDRTBxVZ6DK4Vb3EAXV8KyY6Mw6mDATnglOJ/UsDaZWx/WcBzkTPsGFn9VqHZPVhWdphHs3pZpQ6b43nPcTOJSLI5hUy4ExpcAZ3PgXRZFMNuJWHQsHA3hRdBxOeURoWM2QX3YwzHjVvs938i7pCAvu6znfoCiKlOMjg3L+zXolJOW65jajLgR0SqeJ03N27cWvF07Izf69dSWwW73KdXTVt3Kf0O60B6aHlARtjAIsXnZWXXL5q/lZ9eOv/+a4FLu8/UC/zP75Kj7HnB22eeLl1xtO3XPZ1COXAQmB0MvChWe45biUIthV43cUnuNVrwR6KyxMMav+2k1+T35/DjcOGDMIcPyMLzluvlqZ05cJn9mv9qr8FCt51Dr18s1r0xAmc1wWHNqQsmS/RroSjnP7IxQa/3L5YCOsqkCKrz2qs3GyXnxhHCWqPWE9v6ORrywEKCjqwlXrqtzmT/O5Ogpvz0nXXhj/PD8gF6zkWvmVf3bmf/E4c6S2LMwYQzBXjqL4ioTgLz7yp734/MkZ4nbVGeel43z/ovjmfeY578v1yM/icrVKn3dabBDGKb/xlH92rD8ReOSc7NdoV4SU8nPGm2r5jHGc8TD7dxRfHHnIi3PPjzMG8avnWFjZqiBebzsyVS5jHneVyThpBVy7MZYaF3K86tUiXZ4rpXPfXjjFnuWg+VHc7FhleJd0xq7s7yo/43Aen5Fexjxxs9Pe9I16smWO43vkPijfWmfczHK6OYYlX45j7iRnKGf2c0V45PzzVboc3zgjXj1HhmUJpd71wnvLT58m4+T6aKvVsliQ0Bbgxb+z+MKrfag2P3Jpfle+Gr+N4/Lvjy7q3DwI9BgJ0YiQMF2i9Hc0sDZiuUenTBQDwg/zO+a0o5NXpO37COgbBAqm/LVKQnfV3tYrqz2NuIreXXWuly9B3j5TqxvMPOvFaUQ/5u+22lBGKO+NWMYoU+MgwAKPJZYtF41Tqp4vCfNpViZWwEOB6Hn8m+GNyAzktK3H+YyAZij3mC6jutuCYFsVsmdM5x/5jTICkTAQGCkE+i0JYf+bVQcs9Egh1gciW8V0uI49ZH2gOlGFbkaAmbqVFPs3kRHd+TrEoL2qtmXZD9yd72qGvBFAVgevu+66uj9Z2Gh1cEYEAompqbI3WvmiPI2JAIsC1hC1K7yNWdoxXyrWD8hGc3OtddOYf1vk2MwIWEVnIeicBZYAzVyXUSk7AgJhaQER0T0qefTNNFGrQKD5EOiXJIT9p/a3MemkXDXfZxu9EmcT02yeN3q5Rer+gADzPgJyT9SVSaitU7GKnhKTY6az2eS7J/Af3XcwSbZVidnv6OYV6fsHAiz0HGpXFN9sd+gfNf+mlrZzVM93+SYk7gKBbxBgxm98tTX2G9/+dWdhxPYOW8IaouZRiEAgEBglBAaMUqomT2SvqgMFnTqbDxRq8iqNdPGdq2Fv/0gnjAT9FgHWCbYIdCcAlG7kIEGrO9/TTHnrq85vsBe+0ctdFEWyH9Y+1UYva5SvsRBgnVc9h6OxSte9pSGHIHnt/+7eN0XufQEBfYUlQH9sL4gHv7zhfBXfMlwgEAg0LwL9koSw39Lhbq7N++mi5IFAIBAIBAKBQCAQCAQCgUCPIxAvDAQCgUBgtBDolyTEaCEWiQOBQCAQCAQCgUAgEAgEAoFeQSBeGggEAoFA8yMQJETzf8OoQSAQCAQCgUAgEAgEAoFAdyMQ+QcCgUAgEAiMEQSChBgjMEYmgUAgEAgEAoFAIBAIBALdhUDkGwgEAoFAINB3EOh3JMTnn3+eXnrppfThhx/2ma+oTq+++moaPnx4evbZZ9Mbb7zR5bp98MEHZbq33347+Xm9d999t3we3pJXrXvttdfKvD/++OMu59+XI/qpqOeee64vVzHqFggEAoFAIBAIBAKBQCAQCAQCgcAYRaBfkRCXXnppOuGEE5JT/m+++eYxCmRvZYaAuOmmm9J+++2XDjrooLTPPvukTTfdND3zzDOdFun6669Pp59+ejr44IPTLbfckr744ot03nnnJb8eUs+dccYZ6Yorrkh/+tOf0jvvvNNp/n01grpfffXV6Te/+U2af/75+2o1o16BQCAQCAQCvY5AFCAQCAQCgUAgEOh7CDQVCUEJvv/++0frK1jNp0SOViYNlPitt95Kxx13XNpwww3TmWeemU455ZTEosH9Rx99VLekLBlOPfXUdNFFF5U/pyfu6quvnsYaa6w0wQQTpP3337/Miz935JFHlsQGcsN7WEggPupm3sc933///XTEEUeUFidILT+f2MerHNULBAKBQKB/IhC1DgQCgUAgEAgEAoFuQaBpSIgHH3wwHXrooYkCPapIrL322mmrrbYa1eQNme6qq65KrCEWXHDBNGDAgDTJJJOk9ddf///ZuxN43abyD+BrCxHlpox/wzWGEhXKfElRMmVISFdUklBJgxSV0iwRleEKSYaUookQKWUo83yNmV1TSPjf72Yd6+77vuc9dzjnvO85z/3c5+y913rW2mv99lrPep5nDW8S3m5bxu9+97t6NcOnP/3ptO66605RrznmmCNtt912afz48X204oorpg033DAttNBCSbyVJJwQHDpTJB4FD3POOWfafffd084775wWWWSRNPfcc4+CWkcVA4FAIBAIBAKBQCAQCAQCgUAgEJg5CAyZE+L+++9PqCy28wduv/322ojO4Q899NAUZxI4s0Ac54NzHMzWe87EAHfGg9l5lPlzvFUBDzzwQF+e9vHnuMG5Dm2u11xzTZp33nnTmDFj6hdXVZXmm2++BNtWKyFgcfDBB6ftt98+LbvssnWa8g8HxgorrNAXZKXF1VdfndZaa63aySFiueWWS//+97/TRRdd5HFUEUfPAgsskGafffZRVe+obCAQCAQCgUAgEAgEAoFAIBAIBAIzA4FBd0JYvj5hwoRkFcJee+1Vl9kM+i9+8Yv0sY99LK2++uopOw5stdh7773rMwqcU2BG/sILL0w33XRTPbPPCfHrX/+6Prdg4sSJiUFti8aXvvSlOs12k2fwpZN//aLJf7zbdgXhyGqKycEj5r+zH171qldNUZ+55pqr7Qz9xRdfnODz8pe/PJ144okJPs55aLdqwrkRMl988cVdauL0WGmllerVFHVA/AkEAoFAIBAIBAKBQCAQCAQCgUAgEAgEBoDATHNC9PcuqxhazcpzLljZwCCW/utf/3piUDuHADGQ3/CGN4hKjz32WH1w4jzzzFM/+7PPPvvUhvSXv/zl+gwD/Azrn/3sZ6KT/M4444z6PAP5oZxfzTAC/jRXl3Sq0jnnnJP8kgbnDqcOB9AXvvCF9P3vf7/GuEzP0XPcccfV2zPKcPcLL7xwsiXDfVAgEAgEAoFAIBAIBAKBQCAQCAQCgcDoQWBGajroTgiz8pb+jx07tq+ctgtsscUWae211+4Lc3PPPfekY489Nn31q1/1WG8XcPDfUkstld72trell770pWmrrbaqtxJgMEu/2Wab1dsPPNtesNhii6VLLrkkMaAPP/zwtOeee6all15adE1bb711fR2tfy6//PK0zDLLpA9/+MNp/Pjxadddd00f+chH0pFHHjnVdhlnRuy2225p/vnnnwquBRdcMD399NPpzjvvnCouAgKBQCAQCAQCgUAgEAgEAoFAIBAIBAYFgZ7PdNCdEP0hNOuss04RbWadgfzjH/84cSbMNttsyeqFKZheeDCbzwi2vWKJJZZImRjFtguIt/rCrz28kGREXmyTcD6DszFyBd07t4DTJoflK37nR1jJ4HwD5IwHK1KsWMHnHA2//ODcg3e84x2CpiLpqqpK//vf/6aKi4BAIBAIBAKBQCAQCAQCgUAgEAgERh4CUaOZgcCQOCE4G1CzwM6LaIZdcMEFyTkHV111Vdpoo43qn0Ns8ni2QkKeO+20U80vTabvfOc79ZkIDGsHN+LP5CDMfD8SrquttlpyMOdtt91WV+fZZ59NN954Y1p00UXrX8qoA4s/funi4YcfTuUZELZlcE5YtYJVXkcffXTacccdPbYkDgvvil+HaAlPBAYCgUAgEAgEAoFAIBAIBAKBwMxEIPIaMQgMiRPCzzr6acPy1xQYuc4lMGvvlxwgakuAK3JOhNn2HXbYwWMfMaA9LLnkkvVhlyeccELKZ0AIlydHhvhx48bV50J4FnfeeeelU045xe2IIe4p7uUAABAASURBVCsVqqpKfnbTL3888sgjSX033XTTxKkAW1tSnI0B68z/29/+NuHnCHLYp+0xtslYXQIjqyBWXnnltjjdfffdiePCGR5tmUZ4BEfOtJ7JMcIhieoFAoFAIBAIBAKBQCAQCIxABKJKgcDMRGBInBAK7NwBBm/eNmEmfezYsYkx+9rXvjYdccQR9aqHHO/6zne+M+Vf1Fh33XXrmf0NN9wwvfnNb07nn39+OvDAA+sDFZ1vgB/94Q9/SIxnjo/DDjssrb/++omBLc4ZEs5BcPaEq5+jVLZepkUWWSR97Wtfqx0xzsTwU5p+VeTtb397/ZOaMIfDv/71r/pgT+djOIiSEwj/qquuWv9CCQxt37jyyiuTXxvhwOnPwYBvzTXX7GXopqvstp8ceuih9fafSy+9NFlZo2352VMOnOnKNBIFAoFAIBAIBAKBQCAQCAQCrRGI0EBgxCEwZE6IVVZZpXY45C0TnBJWMDDqLP93QOJ11103xdYKhnE+08FKiptvvrneevC3v/0trbPOOslqiS233DJZHZHz3X///eutGL7UmDFjaieFn6QUz2lhO4J3cn78/Oc/x9bTZLUIZ8C5555bH8bJOWC1g5UMKuYASfXdd999kzM28G+wwQbp73//e81/9dVX1wd9whe/Xw+B5x577FE7MYQ1CXbO3uDcacaN9GdbgHbfffe6nXKkWV2ibXGWwXek1z/qFwgEAoFAIBAIBAKBwOhBIGoaCAQCg4HAkDkhBqPwkefQI+DQyssuuyxZxbLSSisNfQHijYFAIBAIBAKBQCAQCAQCIx+BqGEgEAiMWATCCTFiP+3gVOw///lPcraGbTHzzDPP4Lwkcg0EAoFAIBAIBAKBQCAQGDYE4sWBQCAQCAwmAuGEGEx0R2DeBx10ULJlw5kRtnaMwCpGlQKBQCAQCAQCgUAgEBguBOK9gUAgEAiMeATCCTHiP/HMreCXv/zl9J73vKc+X2Lm5hy5BQKBQCAQCAQCgUAgMJwIxLsDgUAgEAgEhgKBcEIMBcrxjkAgEAgEAoFAIBAIBAKB9ghETCAQCAQCgcCoQSCcEKPmU0dFA4FAIBAIBAKBQCAQmBqBCAkEAoFAIBAIBIYSgXBCDCXa8a5AIBAIBAKBQCAQCAReRCDuAoFAIBAIBAKBUYdAOCFG3SePCgcCgUAgEAgEAoFASoFBIBAIBAKBQCAQCAwHAoPihJg0aVL69a9/nSZMmJBOOumk9Mgjj7St29NPP13/5CNe9Pjjj7flHUjECSeckG688cY+Vvn94he/SPfee29fWDfdPPfcc+nqq6+usVL/n//85/0W74ILLujjxY/OPPPM9Oijj9bpnnrqqfSrX/2qj+faa6+tw5t/7r///vT3v/+9L9izd8vP9Y477uiLa948+eST6Zxzzul7h/c9+OCDfWyd4vsYu+Dm8ssv76uHnx7tVKRO/J3ic/7XXXdduvDCC/NjV1zPPvvsdOutt7Yti3h9WbvRTlqR/vfEE0+0zaNdxPXXX59++tOfpj/84Q/pb3/7W/JTsO14uyFcP/vlL3/Z13auuuqqfov1j3/8o4/3Zz/7WZo4ceIU/HfffXc6+eSTa55W8VMwFw8333xzKvv4v/71rzoP3+ZPf/pTwdn+Vt//61//OhXmd911V19e8vvnP//ZPpMejNHf1Qv95S9/Scai/qrRH/9jjz02hdz1HfrLq5vjnnnmmboPwgX99re/7be4Dz30UDrttNP62sott9zSlt84JU+y77///e8UfP/+97+TdpgD5XPsscfW+dInHn744RzV7/W8885rOd5Pb37GQ2VG+mm/Ly8i//znP6djjz026aNFcN+tsTzH01PUnT7Qx9ClN8YIWGTqVMxO/J3ic/7GleOOOy6dfvrpSX/L4cN91dczFr///e/7Lc59991Xt+fM30qmXnHFFX087fLTV8j9Z599tn6f51NOOaVOp716riM6/KG73Xnnnf1y/eY3v0kDzc8YnutGxxloe77mmmvqst9www19ZaET+N7yM9ZmHfO/k+WG8TY/9yUYwpubbrop0XWU7dRTT+3Tv9sVoRN/f/F0jVLfvuiii9q9JsIDgZ5DYFCcEBmFr3/96+lDH/pQOuuss3LQVFeCZqeddko/+MEPkkFmKoYBBDB6pZfPrrvumgzu99xzT/r4xz+ehH3xi19Mt99++wByGnqWSy+9NH3rW99KWcHae++90w9/+MO2BaHsqVNJBx54YJ/S9alPfSqNHz++rjeeD3/4w4kyVGZIESQ4sxA3wHzlK1+pBxqDGkNw3333TTm+TCv+j3/8Y8oGDuyV//vf/36tGHSKL/Ma7nsD8AEHHFAXg3Kwzz77JAN4HdDiTyt+TrbMesYZZ6RmfmV85qPI+maHH354Dhq2KyXh3HPP7WsvjOVWhfG9yzhpPvKRj6RLLrmkj51hoc1985vfnKa+zEF48cUXJ23pxBNPrJ1y2rnBty/zLrphMBxxxBHp/PPPr0tFGdxtt90SI6cOaPwRr7+pj/7B2fDZz342aQdYGSnaTZZRlNqPfexjHWXWbbfdlg455BBZ1MQZqd964FhwTyn03I58L/Td7363Twbhlf7b3/6225rIkI9+9KNTOC7riB7943v85Cc/qUtP/sGfolcHtPijPZb8+++/f+2IxQqrb3zjG0kb9uy7kCX5WVi3UX/lIf+POeaYvj5sHGX4tUsjfnwx5nhuZVyRrZ/+9KdbZvPAAw/UBjt5hEH6L33pS8kzveDoo4+u27pn8a3IN9CWjYH0ipJHn5Kf/ic/9fve975X51/yNe8/8IEP9DlGjHuecz9t8uZnThl9h2OrVXlzPHlZxjPEvvOd7+RsuvJqgodc0eYV0L1fzHLfijrxN+M///nPp1b5cXzvt99+HR2FaYj/cRKQHV5Lh6NvHX/88R6nohyfI4ypu+yyyxSTEfIjW/Bw+LfKTz5kPR0Xn/FTe2PIeuY0+NrXvtanEwor6X//+18i//QVdOWVV5bRU9xziOvP2uYUEY0HfYoeaJwQRa/dc889E1nouT+iuzPoSx7p99hjjz69RDnp8XQEfJz4dCsOCc9DSSbo6G95/KbHHXbYYbX+26ocnDz4jTPi8R966KF9/K3isz6d+dU/kzbTnzyWJigQ6BUEBsUJMWbMmPSud70rLbDAArWHkCDLg1YTmKOOOirNPvvsaeWVV07ve9/70lxzzdVk6fgs/dZbb53e/e539/HOO++86ROf+ERaf/3106yzztq1PympjBtssEHafffdE0XOAASTdkJ/oYUWqgcQBk8mHvDFF1+8dgwYXAhwcRQ3g0JTQFK2DVzrrrtuMutllsmVgoUYVAwng2QfoC/cmKG2ckNZEScTY9SAwJDvFP9CNsN+MThSaj73uc/VuBto11tvvUSBbdVWO/GLp0B1yo8STKGigHaaeR0KkAyGVgq97W1vS4xkfbb5XgO+VRBbbbVVesUrXpFWXXXV9I53vKPuq36uVTtADNktttiibp9NI6CZZ37W7mDhvTvttFPtkJO31RDem/m66Xr55ZfXBmfus9rOK1/5yvSjH/1oqmKqn++94YYbpg9+8INJ/9LG9G8OHPFme1760pfWDls4Ur5mm222RFmZKsMigMOVzFxuueUSxYjs0AblsddeeyVyxVW/LJLVt94/bty4hH+RRRZJVVVNISMpw2uuuWbdN+THYKMAdruRVFeuwx/KOiXO91A3jt/Xve51ifOsVVL8+gjlL/OvuOKKidGLn5yEJ4NB/Gc+85m0/PLLJwaa+AZ19SOj+OCDD076ca7P9ttvn4xJVsY0C8/xypBk5BtzOMWMJ5yJ5Enm1344IbJ81LaM2zneioD5558/rb766rXO4H1vfvOb6/anHNttt13iOCBnc5p85cDgIFtmmWXSm970pjr9y1/+8hxdP8uP3PJ9cn7eeWs/K7+8j4OQUSwdY4mD5sgjj+zLu9WNdqXuyiTdkksuOQWbeH2pjKf3vPe9760dW+ThFAm66IH88o3IFXUjo+BEXrcqZif+nXfeOb3lLW9J/eV3+WR5y6lHpzRGbL755mnuuedOw/2PXFU/+tL48eNrHW7HHXdMHAKtHFVkTjleGns5tOln6iI/eNCn5Kd9vP/976/HxDI/zjD6mz40yyyzJPq19pYxpFMar+mB8m0SuUW/07+8/9WvfnWTpX7Wr+mWeOqAfv6cd955yXfi6FN2sk8bJ0v6SVbbCRyOyiydPkyHJCvGjRuX6BFWPfjmxlerAMgN+grnief+8h+MOGMg+W6cVmbjLl1bOVu9T3swRnPK4D9g8sRXyd+Mh6E+pX4cFCYl6QjkqwlWY430reRxq/dHWCDQzQgMihOirDBFmYJiiRkFp4yzXIvXlnFDmJZx03Iv7XzzzZc4MnI6Svyiiy6aKIs5rNuuZsoY9JSjl7zkJXXxDLRmSgj0OqDxR71e+9rXprFjx/YRxwRHC884QTf2hTgD9he+8IXaQDFoyYrCRkkkxOeYY4569pkSDaesuL3mNa9Jyy67bL2VRpqSDP4UgqWWWqoOhj0DcokllqiNmE7xdaIu+EPRgxnsFcc9JZADIs9wC8/Ujh+e+DvF53woGpdddlniAMphw3k1485AWHDBBWtnHRzK8jCSrQDRVvSnHKe9VlVVp8lhvr22k58HcjWDYtZGO6qqKnEeKssqq6zS74qggeQ9GDzw4NhTTjLHO7T/NdZYo1YGPZcEJ44CCpU6invVq16VkH5rVooSpk/DT7z6UxC9x3OTyFErHPRRRpd4RoBw6Tz7jhyzkyZNqg0bYSVRoqxmISvmmWeepGxVVfWxMPpKp+7LXvayxFmhn/cx9dzN8wW25Fe/XWyxxeoAMnW9yQ5IslhcHVj8oYw3+Tm3KfKUZMq+vHJ7oCSLp5T6vkVWXX/LmCCjtEdtQoHf/va3J4pvKwcARZghph0h8oSRz3g3kys9pzdjhnKtDQkrCU5wzzLRjCHd4A1veEPNphwMVX2u1SyzvsSQ4zjJ30CaOvHkP2Ys5ffGN76xdraJ00/a5Tc5SeIs9i7jMQeBMA5YhiGdRXsQVpJZWUYjg5CzJffnzMPpzAhhnDHSmvFkLIysFsGT03XLlR5HzvhO5ItybbrppvW4T5Z4Lqk/fjoHnbCZ3yabbFLnJ15e2tAOO+yQtCkytKpelFHih5OUka721re+tS4GWc/BxCGsXnVg8Ufb4ITIQfQtk0e5T8BQfpzHeOTH8ckQtVVHGAOdYb/ZZpv1jb0cgSuttFLiyMZDFtFrOMy0OWElaZvaH6dfVVW17E+Nf9qwPsXAbkRN9YjXWLXwwgunMWPG1PHGRPWQhzGzDiz+KBdnLX2Lka0v5mgyU3o6KgfeCiuskKwcpN/Ts/CRsfoS+4IOIWwoSNk4fYy7xg3vVEZ1p88364qfQ5Y+U/L/3//9Xz2RAbtm/BKTdekcT3aRVeuss04iXzlaRe9pAAAQAElEQVSeyCXO06zTK0NQINCrCAy6E4KgoBzzAjeFBU/wV7/61bbYmdWfMGFCmjCZ7AlrppeQAige6ZjCOhEBSNmSBhGgndIMRrzyGswJ3Jw/QUUg2zKRw8oro+Lcc8+tMVF2AjErLNtuu23iICj5GTSUHQqUcGkpeYwQz4Sk/ZXe6RkxOCh2nBqe+yOKF2WCoipNk7dTfJN/qJ5hUBrV3uuZ8tlKwezEb7CQXj6ZPJf5mVHwzTg7KCCZr5uv+pxZ8dVWW61esdRfWW3f4ak3YDKQMy/FiiND3Xn0tfscBx9GT37OVwqnJaclb44bzqvyagtmjxgNuSz6mWWy+bndVXozHGuttVaigOKTTn/PCow+6ZkyK75JcIbn2muv3Relr1KE+gIm31BuyV6K3uTHGfpvNQdjjME5XRl1SSJ4mFUkq8rvx3idc845p1rCXPKLz9Xw/T3DXb9mHBhXcjzjiexrZbhnnm68criol5U9uXy+OwMnjzM53JVx2GwTsJU+42vmlUFhllOaJjGWjIOccuLgWVXVFLPdxiflatcnpGtH8vMd1SPz5PwYeDmsvBoDpFt66aXL4MTJ6jsbM6eImPzg7AwGgm2okx+n+m9bqnh4TBX5QgDjRtvC+0JQ11w4nODIQCoL5ZleUoa5Jydb8ZNL+OVHHnrGn8mzeM+cPp45Jzx3E2mLWY/K5VJWOpwxL4e1u5poIvOtnsBDLpkxd58p55fxoDPT5xjmmUc5Sh1SX9UHtWH4Z76BXo0/9GOY0wU7pSPnjEnGQA6+zE//8awd5LB85aTRxq0uymH5Sle1ulBfyGH6LnmSJ7+Ec7Tg1ac8DwVxlnKAGC/y++DNoWMc155zuCt5Kr7J73vh58TuL/71r399revLK5Nvy9nTKzpkLndcA4FWCAy6E0KH4c21vEoHzoXgJacAmIHKYflKaTaQU06EUcgt9R4/frzHmoRZRssbLcBzfw4NPIiyaNktIeuZILCsymy256Eky6sIaYI0v7f5nMPzlcFG8c3PVjuoj3rksPJqoDOLZLZTuGXFBrD8bMCRJwVPfCYCjic+PzevDCm4+SaWZE5rfJN/qJ8pQM0BlmLarhyd+DvFy9eecoNoO2UcT7eRGUTtg7e/Vdn0J20QWVLpql/m9kSxMuuirUvP4Zefrcix9FR/14altfQdHwOdAmZvpOduIUodpY9SxHDK5aIYUj7zc/Oqjmag1NFsp2c88jC7wUGTMSIbnRuhb+JpErlJwWQQ5TgygZKWn10Zgq4zQsqlzLae9JpB3arevh+HofYJ+8zTfM7hrpToZjzZIX1VVYlDSbtG+DnOzG5lw0FYrxClmJKtfecya9fqm587XfUPM3/SyM9KB21Rv9eWGBhW/+R8OC4Zc/iFMf4Z+d7rGYlTLvfTSjm/Mn2n/BiRHLDNMaH5XJbF6iRjq/alnqicFNAm1LNdfM7L1iD6Cdmaw7rh6rvqP75lWZ7mc45rx8+AwtMpnpyzgob+YrYcnohzWvrhJv2cftssRzs8Mp/zD9SD7lQ69sjXTvnZVsShl/MyjtB9jT85jN5GXuXnab3CnX5nJRJ9tFN6s/l0BDKjql5cqUKvbZXeuOa8FGVWdlig8syH5jv1GfwmQ8q4zTffPOlX5EUZPlj3vjl81TW/wzhQPudw18xP3nhGZfpO8fibZAUeGcHp04yL50Cg1xAYdCcERWKjjTZKPIUOc8sAOejLUqpm5+UZpoD/7ne/q5dgjR8/PtlzR4G3rNPhN/KgyBPgziTIPPvvv7+ofkneZiy23HLLJJ3048aNSz/+8Y+nOJit30xmUuT0KBn2pzLylB1RfOxRNVPZLBYHjbri9x3EM3BKI5jnlrIlblqIMW1vO8cPA8XecrPcOY9O8ZlvuK4GTnUf6Ps78XeKp2AYcAyaA31nN/BRRigTZudalceAqm1ZqWS5qa0HHAiZ1/JT7Vxf114dgMoo0S7N5FtmSSk1G0QJ4XjIac1CWrmTn7vhSgkndwZYlj42dTSrZz8oOWV1ibrDzxJ2SoUVJJZikm1mgdopGYxbmJeyU/sjO/teOJNuzIb5LuSj2S5LjxmWMyn7YclmWr8fbNsVtKqqZGm08cRSbN/P6gDtmHJqaXS7tN0YPqPKvKXh5Jwl9Nq22U4GhAkF2y61JUq0MSk73Rij8Mp4aMf9YZ75BnqdnvysdpiW8YGjSn04UfVt9XQOjDMy9O8ynm5Txhs/y7ro95y3DLQyfLjv9Rvyb6DloFf0xy+//vJyELJvxxFhLIAZfltOYeh+OMm41l/92pXNmUfqYnWwlbwMcFvBOuXH0Ocg4MjKec9of835lFdbP7yjkzMlp9FPrIbIz52unIImN2xLpY/DwtY/NgEsmunhgs/2jlK3wEfP1Fc4YzwPNmnT0/IOZe+Pv1N8M63vT99nt5Tjf5MvngOBXkFg0J0QgLAXk4LtYBkGiBURZiXMlogviYAyC2A5d/YKU2bycn+DusGe0U2pMWMvPZ68nNNzO6IgmDE0eEycODGZweZhpQhNiyBtl/+0hFNSlcNAW6bjPUZlWL43E1N6Ve3PpMAZoDKPK4ztLbWHTv2E8UBTkmDlGVVVVe8JNJCkxj/lawT1PfK0W243duzYxLA2m1s6IdrFqyvcMzHOp1UQ9xViBm7gqyzNLKqqSiU+6YV/7fhFi0Ot8hMPW6tFtGHtTN0t19bWKeyMSnzdSNpLVVX1XupW5bOUkIPQvkUHNqlX5vNtKZKcXpRw9WbIMsgNpvohI007szxRW5JfTk/h0I7z87RdB49b+/BN9d3yLcLL5/JeHS1bVkftwGwWZQKPpZqciWQR2UbGUapsrxLfJKuetJmqqvqi+mt//ZWrL4M2N2SwMq+88srJ+TK+GwPASgzfMxP5A5M22XRVMDyUtfn9FFKca0mw7Y9fm+Vcgo3vR2EmCyjWvnuZV7ffKy9c1LcsK1yq6sX2Vsblew5uEwZmJsl/4eSHsdy5L2Yxx04eLzjS8YozJjEiYIwfVdXz71EOzyUpX/k8kPuq6j8/cji3Y1ffUbmqqkqurd5Rlle8/shAsTXloIMOqvdv678cDPQZBleOt8oTDuI5KMRrN/JBZGHOz3O3UK6ztl2WqaqqWodIjX/ajKB2/J3ijRnaAHno7AmYObBPmMMZXeU/XKT8rdpHVVUtdYj0wj86nLogfYVTl57WX36wt9pNnfG9kFV9LoSwJsbiSz7PAyHjM4czJ4S+QF+RN0ei93McCS+J3qx8TZmR39fss/iNH9q/QxnhwNntAFxbsOkNOa2rrRvKZRKjmRf9gcNQPN7Bpoxpq7rCoKqelzW5HPh9n3b86tNffM7H1bhvssbqUGeACAsKBHodgSFxQgDJLJHVEGYBLcV08FXeEiC+SWZCdM4y3J5nBjWjFZVxA72nYPDCUhQojmZmCVqrNRhFA81nZvCZNSNACfScH4FPcFFEclinK6dE6RWl0Fh14gRdhk9OXxqIOYwQ5Mgx4GdBaWA1C+MbZb7+rtIzLNvNlpfxFD64Z7KSwvfoL//BiNOWmu81MMLed2m+sx0//GxV4ABrlZ94Kwm0W04a9bZqxBJkDjkK+XBsBWrWr92zga9dXA6nRHB4UbQp1ZMmTaqj4Kk9O8hNvVFWwDkmYV0z9tAfioY+RY6UMkjfau7nbVctBpr+rc00efRBs8b64zvf+c5mdP2Tgq1mv+THqCsTUMyU12xRGT69975zVT2/V99WGt8zE+WxxGN63zHY6aqqSnCnVJNF+X0wtbqkFVb4fY+B8jugzDa4bbbZJmffM1dbfMh+9c2FZjQYq1EOa17V1yF0ZnaN8zlefvo5R00Okw8Ho/fY9pDD89VY5p36VA6DvTByI4cN9Co/42wpy3J+lpyTw7kdu9p37136KV2lfA9DjGOOIVmGmzXGbxwsw+1bJwON0f3F03fKdN14b9KBPGmOcwxTxmCzzCZH+uMXX1VVsjKmTJvzy/G+XxnPIYrHNy3Dh/qePFT2Uu6RI8oBK9dORN6QO3QkfaK//LynqRPDyDtKw53+phzKB3/xAyWTdMquHyDOQ/3UVlLbSOiWwkvShznSTaho6/ldwo1LVvbkMFcTkPj1iap60WgnK+hL+iY+ZGWV1VT0dH1M2HCSb8SZyGbI5dAOtUffoom3byCOvpD5fR9h+OmO7tvFk53ScdSSryYCrNwWFhQIjAQEhswJ4YAVKxcIFUuxGbi5g5VAElCMQD9fVwojgtBpsBtvvHEisBl2ZhDKtGZXyudW92ZjCBJLnnnVMzGi5NsqzWCFWcVA+SgVHbOhhFIrg8a++WZZKEUUIjPR4sygOD2ZAmx/qrBM+JqOAsqhpeCWAxKueBmPDBpYey6J8G0azYwdaZ390Sned8uYu3KWUATLdwzFPU+y9qSe+X32dHM2tFJ0W/FzJGR+ilEzvxzPmLQfWn2R/a1WjmiLZsPN8uQyzOh1Zqe3DHYgeRoYnXZtRt/MlTT6GWXD91XvkgYyS0yJkV5e3UJklhVclMVs1DBYyB6/iNAsJwXFOSxlOLlGqXAeRhnufsKECclPB37yk59MFBRhJVVVVW9to8CV4X7dBl4Owsrh9t1SAhlCOWwgV+Xz02dkSclvaw45bjmxrTfl97TdhqOt5O/G+6qq6sMF9VVyLpeRIaqPN9tbVVWJLLbSo8kPiyY/3A488MC00UYbJVtXcv69cvVtyfOyHXGSMwA4Y1rVQ1/Q750J08RD2zN2GxdyWu1L+zXO428a7sYoJN+cRnkYOMqXwwZ6lZf3lMZzmR85XLZlhpe2YPxs9l3PVjI1DWNjq7GgOTaa5WbUaSvimzpLjmeQ5PowIDksGKc5rBuuviUjSxvP5dEvyDJxOSxfhbXiZzDDnBwlT5v55Xgr6KR38HXO09U7yTu6oufhInUgc8nFXAYrdJXZdroc5sqBQO9lgHrOxHFv1YHxs1V+VhJWVZVgRZbLO6fN17e85S3J+GMcEsZ5ZyWdNPAVNlCyOqHsC/vtt1/SP51ton8raxnvXhgZqQzGu/wuqztsy8rP+arv0A384k6JBxnBESEOL8cHbOkV+q+wJhmj1JE8acYNxjOnESdrqbPDm0xj0zS/jzEcPydtLg9+fRw//aq/ePkZd8hXOqPzh3I+cQ0ERgICQ+aEAJZZb1dChgLinmJBmSdM3FuNYH8tj6hl/niQ2QkzEDyBZiIpeMLyybj215lBxFsSYWwAICSEU5YZnsrivcIo6xR/DgHPQ0UUD0vMbFPhRfZeChADjfDy7JcU7LM38OIXJxyZreJs4JU2QAmj7DBshROYcEawMkAY2GGCF8GbEczbzPEjjFIA6zyQchzJg+JmALF3z2wfXpg5LIlDxR7YTvHSdAMxGDlf1F15KBPahANQzdR5xmO/t3j3/fGvt956iWJkWSF+6cv8hGWCmTZpNjaHDfdV/6PEcGqVZdEOc3nLcPVr8tunqH1qySvLdQAAEABJREFUf5bsU8w59yZMNqytypFeH3dIrXjPFA8OLIaK55L0Uwp/GTbc95QCyoAy26usPBx4jFpOVs8UFOdd+OWaqqpqBdG9ODNZftmCgeHsAGFIHhRRyh4HqX7PQSiuSZyl5CP8cxzlhCPMNg9hvienpdkTSqRnzrAmnsrD6KQY5fwYQAxAzjJ5IUtiLR0mJxZccEFBPUtkJOXP9iGV0AYZh/l7eLY0mAIuXr8u+c1a4dfexSNjCVlizNp6660Txdl3EtdLRM5rS/os5VfZfXdjcjYEyETtNPdZh0trK+S/9Jm0cw5dWzHll8cdW9M4aSjh8jeew889Ms6Jh6H2Sf7Y4kK2Guc8W0HG+LJySJpMnPjacS6bcPlzXjiDhfyRXt/185vt2jIDV3vQ7skz+Vj949tb7ZWfjbHOw8HvnAvjYuY3jmpjzrEiC8UzKi13l97ee8vRUenA8w4YjBkzBlvXEKycA0WmMCAVzLM2r095NhFBxuhDnfhzvF9IyPlpVzk/fU7+ZTxdx/jcyrj1/qEkMp7eo4zkq3fbjmPCwff2rI2TC/Qs45mVwMKRtiKtVWSwkJ8xQFiZn5WT8tMmjD90QekzOSND/5CfsHPPPbf+JavVV1+93kZpvJU3h4f4TPqj/pP7eQ4vr3QUemMuTxmX741Fxh350WWFa/t0hNxXPJMDyoJf3zPmZH6OJrr8SSedlDgUYKItfO9730v00CxTXDmMvQPBlM6prXgebNJPyX0yMZeDg8AYkfuAVRvkpZ8pzvzG/1b8ZTyHi/LLj67JEepZn6JLavPqCQNETyDr8AQFAr2KwKA4IXj3Cd5bb701GZCyoKGUMYYJIN5LoBHSBneDPSWaEsGDa88fHp0NubdUTB7uKRT2olMUxRPA9l+a9TBQMYZ05L322itROrbbbrtkCwajipAmML1PWrPxFPR2Sr9yDhb5uS7KlMFHWShf6qGO3mmWwRUxTAxA+BCjh/BebrnlRNczb9LxrBqs6sDGH84bihBlTFRVVYnyyGAxYMiXgubZ7Be+cpCyksHMtgMH8a688sq18c1LbnDpFO+dM5+mPUdKozZG0KsHZVmdtQO5UWJLL30rflsLMr94TjB45PzKeHkiq1QMqmZMzPhwCtnjJ244iEfeDIyZdwOi/qLPalfKwyCBhbJ6ppCY6TUoUozwG5TFwYCzgULF2cfYcBI+ByGjAS7aKueZNkcOWG3D6MUnXj6IM4QhzPDw3E2kDmQGRUmZGRcUR+HKyUFBwXKvT6gr5yJeRgsnBWyyUccY0bcptOQSWdCfLGKI6ZccH96BYM9Z6Ht5jz5KPmb8fOeyPUtDidH+tFsK0hprrJHITrKDUnn22WcneSH1tRyXbJG2l8kYAX9Yq5uxijyjJKuX8SJ/P8+ZnxzEr91yNPhe4inCFES4abdWuFCMxfUaVVWVGM6MJuOw+podVV/1Ux91dEXi8ZIFVfXi0mpxSPs37mqvZsbxkzef+cxnEkccHisOGKEMIs/GMP3JeGS81q/kQ0ZUVZUo3nlSAT/iCNDmrcKSDyeSLaCcGPIj3/yak/YuP3XJ+UnfiozLHO/knXLTY5Qzf1vtR/45Leek1W+Zn2zEQw/Bo3+JJzvlx3g0nud4PMiMsrD8HmHdQuS4wwONe+rgm5IZvo8y5nHCPWrFT+5kfvcM95yfNidMvO8mPRmW4/VNzi2GqvyHk7RfqxvosNoePMzekyXK5dvm9qG9mRgygYMPkUG2N2SZKj9O3jI/k2M5P3hwAHKAyj8TuWXyxDgsX3LaOJydWNpg5nWln9N3jElW5+gnymbFk3hkYo7jQh/RDvUfE2ZW6YpvEgOc8cwBpwy+oX6Q60aHMPGS09GTOJf0Kfxkpmfnx5Cn0tILUE7T6gov+or20ip+MMLgRSYaB5TdeK+8vp/3lfLRM37je+aHQ8mf47Vz+ZFtZIT82AJWUZCvQ1lH5Q4KBIYCgUFxQhAkBgoCliFBOObK8OoR2PkZT0mEojidznKuHMcr2lTMCcgcr9PyEuZnwp5nMT+7UnzkTRFhGAlDBo5sEIgfSqLA7b///kk5kFUP5fspLc4SyOWzZQAfgk/Jy2gQ3ooIM0KNc8ZA4ruUaSnijCNpeaTz+wx8Bh/h8PVsKbZndM0116Q8SMqvUzyebiIDp3qgbFQonz2ultZSbj1nKvkZizk8XzvFU0y9K5ODFynbOf1QXzkeOPByeVw5+3j2lUX75Liy15sRqw2Z6cGXiSKBF1FYcn4UC2EM2syrvpRv4ZyPOTxfhSOKuOXfZjA9dxsxnCiDyp2dWbmMjBd9iaIiLD/jNTvCKBOeKcdT5nNYf1e4UBB9pyYfWeE9iPMjx5tFw49ymFVl+EpyUrn4zJ/jLLvl/BA3EshsKqeN+mnbFMBcL44icQygHIY/j2lmFMnLHJf5jSk5rJev2ekCG1Rio16cZpznJgTEt6OMkfZatsudd95ZNn3EEcnZzjnZFzj5xnid8zZGkkWTg+vtmPqQcjDuhDHOfJfM72rFQVW96BixKkv/E6ev5fykb0e2UuBHvr/xLfMaF+Xn3TmMEY0XmVgp+fFwQItD4puGBceiiRiGFf5uJOOV8iO/+FOWkXxB5EcO748fD91EXqiZn3jfShyi5wnrJmI8Kxsil3PZ6FBWuGk3wvIzPkSmNnVafO3yE2fs1M6tUPCciRPBu+RrXM3hrg6LpTdmvZt+TubhzWSFwtixY7HXxGEmTY53tZqpvz5DP8w6N+eAbRp1ZpP/aM8mv5Rz8mP9nwMrl5meq2+IIE+b5fP+TJw0+Bj7DHT6qOehIjpQqcdxKJTvNqlkgoIDVTh+3y2Xv8nfjC/buEnbnK55NX6bfPCOoECgVxEYFCdEr4LRa+WenvISjIxtHnwzStOTR6QZPQgY5BghnAIU5KGouZmAM888M1FOh+J9vfYO34QBxElmprbXyh/lDQRKBJxnZPtf06le8oyWezPatv4xFEdLnaOeA0eAk0v7sLx/4KlGJqfJQ47+PGEyMmsZtQoERjYC4YSYvu/bs6l4XXmjLclrzjz1bKWi4IOGQFVVyd5Ssxr5HIdBe9kLGZsFMUPUaqXJCyyj/mKljq1oVpaNejACgJ5GwBY+7di+9rx8vacrNJ2Ft7LDCiorNqYzi0g2ChCw1dFWj+Zq1lFQ9b4q2i5qNUj0lT5I4iYQ6EkEetAJ0ZM4d1WhLTG17NG2i64qWBSmKxHguLKf2kylA8cGs5D2V1oFYQtX3tM6mO/r5bxtk7ElzVL3Xq5HlD0QsL3JuUKWGI9GNEwIOODZ0n1b2kYjBlHngSHg3ABnZNj2aIvkwFKNHC7n9dgC6Zw3W1xGTs2iJoHA6ENg2pwQow+fEVtjBwnZ2z9iKxgVm+kIOHSq3Os7018wOUMHUTkwy7ahyY/xvwMC9qM3z5HpkCSiA4GuRMCKq/Icjq4s5CAVyrkZzrBonhExSK+LbHscAYeg7rjjjmk0thcrpzjf8xkSPf4po/iBQG8gMEilDCfEIAEb2QYCgUAgEAgEAoFAIBAIBAKBQCAQCAQC04PASE4TToiR/HWjboFAIBAIBAKBQCAQCAQCgUAgEAgEAtOCQPAOMgLhhBhkgCP7QCAQCAQCgUAgEAgEAoFAIBAIBAKBgSAQPKMBgXBCjIavHHUMBAKBQCAQCAQCgUAgEAgEAoFAoD8EIi4QGCIEwgkxREDHawKBQCAQCAQCgUAgEAgEAoFAIBBohUCEBQKjCYGec0Lst99+6ZRTThlN36hjXR988MHkJw39dNPSSy+dvvSlL/Wb5qabbkrvfve7E37k5xfLBP3lJ+9LLrmkZI/7QCAQmE4E/MTaQQcdlPws6UCyGAj/ww8/nPbaa6+6f99+++1TZXvDDTekH/3oR+mhhx6aKi4CAoFAIBAIBAKBUYhAVDkQCASGGIGud0I899xzadKkScnPSS622GLp4IMPTk888cQQw9S9r3v88cfT5z73ubTCCiuk66+/Pl144YXp8MMPT8ccc0x69tlnpyr4Aw88kD784Q8nP+13yy23pMsvvzxdeuml6dBDD02w/s9//lPnt/zyy9f5/eUvf6nzO/roo+v89txzz3TsscemK664Yqq8IyAQCAQ6I6Cf6Yd77713WnzxxdN3v/vd9OSTT7ZNWPKPHTu25m8lA5955pm6z26yySbpbW97W9K/F1100anyXWaZZZKfOTviiCOmiouAQCAQCAQCgUBgaBGItwUCgcBoRKDrnRAU63POOSetscYa6eSTT06zzjprmnfeeUfjt2pZ5yuvvLI2PLbeeus022yz1djstttu6fTTT28508l5wNGw5ppr1vnNPffcaZtttkm33nprbQjJ77rrrks5v1e+8pXpox/9aPrlL3+ZrJB4+ctfnqQ944wzwhlUIxh/AoFpQ+Dpp59O+g9nwe9+97s055xzJv2qXS5N/jnmmKN2IjT5TzzxxLTlllumb3/722njjTduRk/x7N1///vf08UXXzxFeDwEAoFAIBAIjCIEoqqBQCAQCAwTAl3vhOB0sHWAUv2Sl7xkmGDq3tdy0LzqVa9K888/f11IjojXve516dprr02PPfZYHVb+eeSRR9Idd9xRz5IK5+R56qmn0nLLLVc7Mc4+++wkvwUWWEB0HZbze/TRR9Mss8yS3vzmNyfOiquuuqrmiT+BQCAwcARmn332NH78+LTuuusOKNFA+K1m+uIXv5iOOuqotOqqq3bMd6655kq77LJL+uAHP5hs3+iYIBgCgUAgEAgEZioCkVkgEAgEAqMZga53QozmjzOQultyvdBCC9XOgsw/zzzzpJe97GWJgyGH5SsDxazr9ttvn7761a/WKybsM99uu+3qVSYTJ05M7fLL2zss8baMfKD72PO74xoIBAIzHwFbM4477rhkC9Vqq6024BdssMEGyXau888/f8BpgjEQCAQCgRGAQFQhEAgEAoFAYJgRCCfEMH+AGX39zTffXK9OKPOxWqGqqjKo756D4fjjj08rrbRSOuSQQ+oZWStM/vvf/yZ7z+XnuS/B5Bv5ocm39X/xHBEnnHBC/Rx/AoFAYPgQcL6E82CsZnJmi8Nm55tvvrTTTjslK5/alcwKi9e85jXp1FNPbccS4YFAIBAIzGQEIrtAIBAIBAKBQCClcEKMslZwzz33pJNOOil96lOfSr///e/TFltskb73ve+lT3ziE8l2i4HCwZnB+Gm15WOgeQRfIBAIzDgC+uGtt96aLrroorTDDjvUW604FmzV+vSnP93vCzgh7rrrrsQJ2S9jRAYCgUDvIxA1CAQCgUAgEAgEugSBcEJ0yYeY3mI4pLPVbKfT752n0czXsm1nQKy33nrp9a9/fZowYUL9c34XXHBBffCkgyhb7RG3hcMKiJyfPeWeGUA5LK6BQCAwfAh87GMf6zsPYp111klrrbVWOu200/otkPNfOCAcVtsvY0QGAoHADCEQibAgX4MAABAASURBVAOBQCAQCAQCgUDgRQTCCfEiFj15t9RSS6U777wz3XfffX3lv/fee+tfyeAo6At84ebPf/5z/XOeDrAU5LrKKqukRRZZJHEqLL300snMaDM/zgm/pCFNUCAQCHQPAvolZ4LzHcpS2ZKh35ZhcR8IjEIEosqBQCAQCAQCgUAg0GUI9JQTwkGLzi1w7TIch604fkrz/vvvr3+mEzZPPvlkuuyyy9Laa69d/4wfrG6//fb6BHzx9ov7WT6H2Sm0+BtvvDGtuOKKicGy1VZbpXb5OfBSGsRJ4ZwIB1R6DgoEAoFpR0D/0y/zoa85B6uRbLFwaGwOc23F/+pXvzrZVnHhhRcmq5zw2Saln++9994e25IzYMaMGZPGTKa2TBERCEw3ApEwEAgEAoFAIBAIBAKBqRHoCScEo/j0009PP/vZzxIj+4wzzki//OUvUzakp67W6AlxIv473vGO9KMf/SgdeeSR6dhjj00Mmi233LL+xQzY+YnNQw89NDFo9thjj2SlxL777ltvxZDGT23utttuyYxqzu+HP/xhX34MH84JqyYysn6VY9y4cfkxroFAIDANCNx9993p5JNPTg53feihhxKZ5jln4ZyWZZZZJnEgCsv8DpWdNGlS+tWvflWnF8c5uOuuu6aJEyemL3/5y3W//sY3vpHIBT/Diacd/eMf/0i2brSLj/AeRiCKHggEAoFAIBAIBAKBQJci0BNOiIydX3Q44ogj0pprrpmDRv11zjnnrA+Z3GabbWqng7MbPvnJT6bFFlusxsbZEAyaTTbZpN5useSSS6aDDz64Pg8CA/7Pfe5zadlll/WYcn7vec97WuaHyQGWV199ddpwww09BgUCgcB0IrDCCivUv1JjS1SZxTvf+c7asWhLRRme+f3Ubhn+xje+sc7HdirhHAvkgPt2xMFx3XXXpbe+9a3tWCJ8OhGIZIFAIBAIBAKBQCAQCAQC7RHoCSeE5cabb755/XOS48ePr6+bbbZZbTC3r9roiTETuvHGG9e4bLfddmn++efvqzynwvjJmDmE0vYJEbZkCENNfvH95SfeEm7Oi/XXX99jUCAQCEwjAgsuuGCylUofzOQ5Z8MpIdzqJGGd+PFY8SQN2mCDDdLLXvYywW3J6jL9X7q2TL0XESUOBAKBQCAQCAQCgUAgEOhyBHrCCdHlGI6q4j399NPp7LPPrveg+5nOUVX5qGwgMEIQuOOOO9LPf/7zdMABB9QrpGZOtSKXQCAQCAQCgUAgEAgEAoFAoDMC4YTojFFwFAj4dQ0/57f99tvX2zWKqLgNBAKB4UJgGt7rTIlTTz017bPPPmnRRRedhpTBGggEAoFAIBAIBAKBQCAQCMw4AuGEmHEMR1UOfvbz/e9/f1pggQVGVb2jsoFAOwR6Mdyv58RZEL345aLMgUAgEAgEAoFAIBAI9D4C4YTo/W84pDV485vfHLOnQ4p4vKwfBCJqOhAYM2ZMcpBlpzMjpiPrSBIIBAKBQCAQCAQCgUAgEAh0RCCcEB0hCoZAIBCYGoEICQQCgUAgEAgEAoFAIBAIBAKBQGDaEQgnxLRjFikCgeFFIN4eCAQCgUAgEAgEAoFAIBAIBAKBQI8iEE6IHv1wUezhQSDeGggEAoFAIBAIBAKBQCAQCAQCgUAgMP0IhBNi+rGLlEOLQLwtEAgEAoFAIBAIBAKBQCAQCAQCgUCgxxEYFCfE008/nf7973+niRMnpttvvz15bofTs88+m+67776aF////ve/dqwDCr/tttvSY4891scrvzvvvDM99dRTfWHddvPII4/01R9eAy3fE088UeNb8t9///19ecET+RZwKPng8eCDD/YFefZu/K7y7otMU9898MADfe+5++670zPPPFMzPffcc1N8T/mV9Oijj9Z83fJn0qRJffXQDjuVqxN/f/EwLbF4+OGHO71uSOPvvffe9J///KftO8Xry9pNWY/yXv/LbaFtRi0itAtp77nnniT/6cmjRbaDHqS9K3PGQF/u76W+eeZ11e/a8WdebarJI057yuEPPfRQXzvWH8nVHNfu+t///jfdeuutU0X7xnfddVedn3jfZiqmHgzQv2GOyK9OGA2U3zfUduUJFm1XX/GekoSJ73bSpvXBXHbtqb8ya0fG2Mz/+OOPT8H+5JNP1m0px2urUzC88IAvYyhIPjmNMUy7FN6OOvGXY6Nv4Tu1y6sMNx7mcihjGdfffX6fcmU+8iHnpU453Phc1j2Hd+PVGJHr4NqpjJ34+4sv26F3IW1Nm+v03qGKJ4uVCxkLOr0XX6ZShsOBvM1x5VUf1EZy3tohuayvCvN8xx131P1Me/UsvBOR82UZ8MuzxB2P8IEQOZjLrXwDSYMn94tSdxfeKj9yG/9wtgHlzGWDe/ltlLtJnfj7i1df8irj2ityoolBPAcCrRAYFCeEDvOjH/0orb766mmllVZK559/fqt312EE5rve9a603nrrpX333TcR6HXENPyhnJx77rlpwoQJ6bWvfW065ZRTEiH185//PB1yyCHp7W9/e/rnP/85DTkOHevEyY6aL33pS+kzn/lMOuCAA9Iaa6wxJV5timKQ+drXvpb8WkXJ8sUvfjEtscQSU9BWW201hbEh7a9//et0+umn10lhfuSRRyZp0S677JK+8Y1vpFJ5qhkn/zFAXXPNNWnrrbfue8f666+ffve739XOJgPpXnvt1RdXluV1r3tduvjiiyfn0h3/tYm99967xt31ve99b/rHP/7RtnCd+P/1r38l+fiOrmV+BuRDDz20fpd4cbvtttsU36Xtiwcxwve87rrr6r6z4YYbprPOOqvl2/Bob5ST3//+92m77bZLyy67bPrABz7QV6f3ve996TWveU067bTT0rQoCLA59dRT05e//OW05557pqOOOiqdd955qdPA3rKgQxz429/+Nn3qU5+qMfjQhz6U+vumlLn999+/5j1gcl9fd911E0wnTZo0RakZtWTm4YcfnsiGc845Z4p4xs0Pf/jDdPXVV9fhN9xwQ/rCF76QPve5z9XXLbfcMl144YV9jsGaqfgDb+X++te/npZffvkiJiUKz9FHH13LIX13ySWXTB//+McTOTUFY489XHrppemTn/xkjb36+Fb6a7tqXHbZZX38n/jEJ1I7/iuuuCL5Ftrub37zmzo7feRjH/vYVDLwwx/+cB3f7X/U6fOf/3w9HmunG2+8cbr88svbFvv73/9+/Wsr2gvSFinmOYH+nPvI+PHj00477ZRuuummHF1fjTU//elPU8ZQ+oMOOqj+XvSC97///cl4XjO3+INfe1beJj9nw9///ve6n+4/uf999rOfrfvpH/7wh0T+tciuL+jYY49NvqV83/Oe99T9sZ0TJScyBsr7W9/6Vl1+eIozbmoDMELG+pNPPllUra/AyThaB3TpH7odmZW/5xve8Ia+b9aqyJ34O8V/+9vfnqofkZuwbPW+oQ4jgz/96U/X35kOR9f829/+1rIYjP3jjz9+ivroK8YFCYy9xs8lGvrb0ksvncggcgWffH71q1+ls88+u5bX5DkZpM9qp/rXD37wgyQcf5PIePJwwmR9mY5urCl5LrnkkqSt53Jop8aT/sZj4z29gO6oDPQCbWQgBvN5552XyJADJo+JyqUs8tOHcn4777xz3X+NffTXM844I9Fh+yuTfAaD9H+yKX934y2dx7jd6n2TJk1K/fE349/97ncn+lDOT7t4xzve0dduttlmm37lcasyRFgg0K0IDIoT4v/+7/8SY5ZA5Qw44YQT6kG2FQg/+9nPEiE8bty4dMQRR6RXvepVrdgGFNZKUb7lllvSS1/60jTHHHMMKI+SaSju4TT//POnY445piaGnDDOmf7e/8c//jGhJs8iiyxSK485P1dKmXdkXoPklVdemTgnDEiEvTBK3ITJA9M+++yTCPm//vWvOUnf1QD44x//uHYuyZuhNMsss6T99tsvUSgwrrDCCunggw+u64MHMco/+MEPpre+9a1Yhp2UVT3XWmutvnJqt7vvvnvLttqKH9Yf/ehHa/5O8QxJ7RAWCM4XXXRROuyww4YVC8rMT37yk0SpmzjZIfbKV75yqvKY3aEs77jjjmmBBRZI2267ba3Ezz333Inioz6ZVltttdqBJa+pMmoRoP1pe9qntsRQ3HzzzWsFw4xXiyRdE6QPaS+MWvX3TRm23/3ud1uWkaK1ySab9LU3fBR6bSMnYDBxAsD7bW97W3JPKSnjf/nLX6bFF188vf71r68df/LlTFAGpE1T3ilsOV2+ctjq5zfffHOSz3zzzZej6qt2oD3oG/LSbynOjDHKX83UY3/MOBtbNttss6ROvtPLX/7y9M1vfjO1+odfW8z80rziFa+Yit/YxaBlJOjH+of8ZptttkQGwlnaTIxZ8d1MjHLGM+d2Lveb3vSmJCwbQWX59V3Og1zXXXfdtR7HhWlr4inZMM/5kSd0AvE5L20RHwyNMdq9skgj7RZbbFHLFWlzmnzFjy/3nSY/B4X+wMmKDzFkOSTI7ZxP82pc/M53vpOQNPLlnPfdm7zlsz7NmWC8k+4tb3lLvcLsq1/9aho7dmzdBrUX7YRxxZCdd955k7qbNPFc5tdN93QJBqJ6Ic9kBCd1q3KKb/KT8Znf+MHYkhfCX8bTB+UvLpNvsOiii7Z63ZCGmbzhVCKHc9lMupEJVlE1C0PO57aE3/c2Bnzve9/rY23WFZ8JC05/YyRGegP5TZd6yUteUo+Vxh3yDP9nJk9okeEcqfibdNJJJ9VpOBvIOrKt5IGvn3CWF+LM4CzpTyflPDCRpT7SkJ8mdNyXeTfv6brKaqzDu84669Qsyk7PzPlxqiivPuinpTfaaKN07rnnJmNwnWAI/yinsZDjx/0ee+yRyL/rr7++ZSnIMvzGIPwmWkr+Zvxee+1V56ePGMM5Z+hc0pLD6u3aSh63LEAEBgJdjMAsg122TTfdtJ791qGa7+J80JF59hhoVVVllmm6GszHTXZijB8/vi8dwSpfM/Z9gV12Y4aEsvLOd74zzTnnnHXpKHGMr/5WDIi3FGzllVeu05R/OFu23377BItM8qd047Psi8LHuy2McDzzzDMT4/HVr351qqoqrbLKKmmppZZKFElpSqJQmLUyMyh/V8oVZS4L4bGTFS1xJTFuKWVlXsN5/5e//KXeMrTDDjvUxYCFulx11VVJXB1Y/BFmwC751Qe/WYJO8VaLyD9nyUFnJUGpiOe4obxSxs2yUNAN7qh8PyeBWXOK4nLLLdcXpZ1RgEp+xpj8zARyPvYx93ODl/Kk/88666xp1VVXrdueGfgTTzyxn5TDH3XcccelZZZZJpkNVJqFF144UUq1h+ZMr3jOCu3APWLkupazOaeffnpSbysqKILiS5KvlV7rrbdeIvc4WSmla6+9du1s9U3kq122UhphzHHC+OHI0O7L/Mkks2PkkP5L+TSrRQFkJJa8vXIIe4AsAAAQAElEQVR/7bXXJoYoGafM88wzTzK7bwawFUaZX1tsx88BzPFq/CJfZ599dqx9RH4yHmCYqfz2fYxddsNwYAQzBnKdyDzhDJ9mcbV1M4G5jpRjTkRGCSPN6jdK9VxzzVUnNbsqjNzTFgVyWGrDDBHP5CznBUPDs3ZuhrmqqparIfBzmOOvqqruFyW/b0yZ51ipqqqekPDNyLQLLrjAK1oShwDnB1mEgaPP2GpcVDdhTWJUMRL0G20gx5s91X8Y2bDSvxhZ5J8ZbXwLLrhg4tTmAPTcbWR8J5tMXnBAKx/HGp2AHuO5pHb8vr0xRTws6Whlfjk+59XsR5yynDY5friuf/7zn5MVNmbrlYEOxwHAkav9CiuJDKUD+P7IysgNNtggWUGgbeDVvsSVBA/tWTziUNM/s+zmVDBWZIfyyiuvXK9I5EQrxxZpkX7CEDaGGC+M5cIzKb8+m8vgG1kFqp9mnvLq+5OHJnGMh+JclfnAAw/02JI4X5Sd0yPLZozqq+z95cc5RYZzAEgzlJS/GxvDe30L+gsZRF8SVhJ+DiPjjvAmfzOeDuWbyM947z10B9/DdyNjOV/INfkFBQK9jEALJ8TMrQ7PLuFlmSVhVeZuNoTQJrzL8HxPcZQWcViY6chx+WpwF48Y1Dk8XwnZfJ+vBAVPtTSIgpLjhvLKgPC+hRZayKUmgzFqt4xN2RkKDEKz0nWi4o9BR1r1QgRViRtlkoFioKqqql7yDsPsgJAVYenZMm/PJY0ZM6ZefkwhE24VhMGCUqAelE0DqTzEm82iYFo1kJU54cNNcDGbkhVh5VE++InzXJKwVvyw1U6ROjbzy/EUBgNLztO3p8iaDclhw3H1PQ3o7d6tT1EYKQnt+mlOq39TLDlYUBmu/2qPt956az0rmOPgI01+dtWmKEhmVijpwrqRGGsrrrjiFEUzA87Rpw9OETH5Ic9kTb6t/zNWFltssXormgDpKNyWnutfVTW1U9b2DA7EnJd2xEgrv6Fvqv9ps/ItqaqqxNihNJXh+d6MCyXHNxDmmzOmKELZKBXeK0T+aHMwKR1mHEb6KmduWZfMD7+Sn2yDM37jhbbJ+CD7yvTu5UGOMI61eWS80dbFdzOZLPCdyfNcTg5kddI+c1i+cmDaBpSfyX/txRgmH88ox5N5Zlb176p6vn3rB+TM2MnOa3zeAyttzjMyHslHn/NcUub3zXJ4yd/cT49H+66qKrUa48SbZdSH9UPPmTgcOViz0ZjDXRmejC5Lr8uyi9NOrC6Ei2fv54Suqipl41E45wiZx6jz3E1kjCPjyaxcLnJE39DWc1i+duIXz+DsLz/9CNb6UCZtI79jOK/Ko61r57kc5D+MWuHBMcX5lHnpBPilJ58488r2BhtOHunwSGdFGjyMAZ6RMYA8c4/IbDKe/KcvCitJfy77Shnnnn7pm7pH9B66USkPhWdSXyuUvFO7Fu4qjVVKvrOwkqzcsALCioly7MLDOdgqPw7MMj8TJ76BrRDSDQVxxGp/pe6d8VZmcWU58GvDsMnhc8wxR/KMn/xpFQ9/8ZxLZIGxSnpXbYYc8V5hQYHAzENg6HMadCcEAUPw2s9JgctVNJtvT5fzIHJYvlIqGD7SWYrEUcH7zWOYeSgtZgQt08JjCZylbjm+3ZXA9F6z99LJ2/43wqBdmsEKN3hwksAov6P5nMPzlQOBomi2MoeVV0LP3lJ1Q87I+MUvfpEIb3w8zwbOrPgY6ChcBkTxmSihBF5+7u9KqWw1qyqN95ptonDNMVn4CusGYhQbjMuyEPzlc3nfiV88RaJM0yo/M4eWFFpyyhHEcVGm6bZ7/ZSTQJtpVTb9SX2QbQGUb7N9uT1pW2aLv/KVr9T7ZnnzLVdmyFF2zLLo72aD5MFY8x7tFn6WLXvuNqIowYZxUZYt96syrLynpDBG1NVKGjOfFAo8Zkb1f44N8chWCH1IPCxt0yj7vv7OECgVRP0s4y/djBDjk5PSzFb5jhnJc6jTMkJhzImQ3w2frNjnsHzF34zXrjP/jTfeWJ8do//6RsgMMaNVHvoEY9lMHxls9opzJ8944+lW0te1n9JI0b7Uf6Bl1l7I+6wkwyPLPTPBnAnic36UbE51mAuz0s74rhyekfKUz8IyMdrxK2cOK/nJLs4Pzg7tGa9vof9m/uaVoaffkUFlXPO5jOOYYlwYz7UJZG93yVPeMzLU2XL+MpzDV1nhVoYP9z1jEn6lAaZMzWdhCL798YtnJDfTl894rDjTj5DVdoxXY4Z3DCdxbrYav7WBgZZLfxs3blxLdqsB9BVGZ2ZgtOcVQ8LgQO6Uuge9TbsSPzPImKzdZ8d3M09jofFcGTgfcrx+UD7ncN/cORDahjz1E2RcpI9q9/LTh8v0rfLbaaedkjFSGXL+g3n1zeGrbPk9xpXyOYe74hdfyk/PsGoX38wfX0nGJw5bjtYyPO57HIFRWvxBd0JQRGzJMPAzODLOlGkKCcGSw1wJKA4Ie6Z4gO2DIqAsH/acB3X7qDg2LA3Eg+xdlUd/RPngrMjpKP46MwcHZaa/tDM7jrI2rXnaI8chA9dWaRl5ZkvhgSyrgxvPM35LAhl47hG8KWjup4d8V4OlJX4GlGYeVkEYKO2VbMYN57My8UAPtAyd+MUzMAean6XZtsV85CMfqbeFDDTdUPNZOWPALBXDsgww5NgyY2PwdCBt2Q8d3mQvbG6T+hllg9OhzKfVPYXTmRWt4oY7zPdW9xkpBwXK4V1kHdlDNskTnvJlCOnPZlbFc0BSyjgExCOOCdfBIlsTHEpoyXQ7I3Cw3j0z8qXocpIONK9O/OI5gSnm+WwAM+MccJbMeg+F01ZADjQyGGnLHI/iu5ko/zNSPqsBGFb2sFO2m3k5YA0Pg5IyLd5spllO94gRwhHhfiDUiZ/Dg67he+hzxkRtWt5N/UMY4oDQF90PhPRDjiftI7cLfYfewnBs5qE/m0CxUrQ0MvGRtTCckXFZPjObtHP1G2i+yt8fv/w65WVVpXMj9CFk6x4nt61UndIOdjz53F/9Or3fuGjFBCdlk1e4LS70gxwHT2OA1Tg5bEb7a86nv6tJLWcZWRHRio/eMy39Fa8tH7bwct7KkwzwXW3N0O/0D+GdiFyFibw68c6MeN98WvLpxN8pvvku39tqGCtoTRQ24+N5+hCIVMOHwKA7IVTNzN2aa65ZHyxlxphHnUBliIkviYBieFjKlZemUX51OgqDfbjS2ztNocjLvvFYyljm1ere0i1KYjbEGfP2/tpj5d2t0nRLGOWG17zdYKCc9r2W8WZaecUJefEUaHV2PzPIKgvKhG/RSuk0iPp2M/OdM6Pcw5WHfsCwtOff3l/blDhxhqs8nd5rpt3sPAdDK17f1aoi/YkyUPIwMjge11tvvcTRJ06/pmRrh/ouY8Ustf2jcClXEpjBpNhLN1IIlhQ6deWg4Qy1oothZtYPPtqFeI4dDgqOVwaN5bVVVdVnPwwVHoxG5TFTPVTv7Pb32KfLaHb+h+9ExvpWZvQ57fQJ5+pw3qkLZZFTgpz0DYWNRGIIaNsMxXKG2AqSLPfgBSuz23n1oRWSeAYLE7PJzjXh9N1///3rg5uN+QxIqyBnxnutauDsMj7bp66e3uV8Fkacvl2+xyQMWZcdV2WcpfUmKAZqiJVpR9q9VSHGgVwvbccscK+PC2QI5xTZ73vn+uUr/ZbzrOxHHBMmjciXzDfYVysYrXJ1Lkw7HWBay2Diih1AV6UH6Su2dBlrONzpDQPN03hpFYTVIANN08t8tmqSZa1spx6tVxR7lCMwy1DUn3FqRoDwpFRbhk2pNQg3308xMLNBWa+q5/eM4rHU0uBDgHFg8CDKT9y0EMXHjKOZeYqkWUUzJGbxvXNa8ppRXsKd15dAznmpv2XPFNcc5mqmxcyJg6+UG9m7TfFzb4bZUja8JcGeg8YMqkHM+8p4AwsnBSHu3eJc8ZWDv/CSxFO6rUYxC9j8FuIZL4RmmY/3KG8mxutwGOG+d9MgyO2uucRevfvjp0R0ipdHSb6HXzEQZibBtRuJgdBfuaqqqg9mpHgzlineuR1qb2YUrYLI39usn1k+jsD+8hWnP2pH7ruNOET1U86UsmzaEKOnudWn5Mn3DC8Hk+lv8NCHzOxw0uBRfyuMOEcZJfAUXhKZyFghE3M4RbWqqlQqsDluoFf5cR5yMjpIS3uVlrKYv6Ur55HwbqWqqupfdCE/jR25nNqVOpX70cVV1fP85FQ7fuOW/p7lhO/ksEXf0PJb+TTJ+OV7N8O77Zms1t7MuOWyaU/GI+06hzWvxmNjPCdMc3tBk9c2FmOOdk++NOWffiVOOXJa30s5OC5zWL4OhB/+vpf+gt9KLG2XA9T2TG05kz7JEDJu2nqT3+PK4JE+O5iEId8ev4kTWAnzbGJEPfRfYcjqQO3Eigx9XlhJ2qW6wqAMH+57S/Krqkp5QiOXR/vPMiuHuRoXq6o9/7TmJ0/6Clxh5Hk4yWSP9lG2X+2UztUKj1xWOpvVvRxQ2lwOz1djipWrDE3Y5nAyqdkmtGfjLSdY5sOjHPCfXpy0c6sUXP38MMzl71crlLkkOrXxUBm0W3zIWKjfNcch+Bgfyd48OUE2+hUZWJIlrfJTT+Uo88v4lO/17sEi71YvK+HyO7xbuY0JuTw5ThuBYSlPfZ/MzwZoFS/PMj9jvPNmOGxmnkMolzKugcDwITAkTgjVM0PgMB3bKP70pz/VP2FmQBFXkjCCycwfAybHUQjNNDgFniBCjJkc72qFhGt/RGgrB0XAmQyZCNysPPSXfmbGOXSGADLg5HwNNAwAXvAc5qpsliDm8rqaxSGo3DvxHq54SzL7ZkDkdDHoU7rKeMKfIDSzoCziKOywLfceCs/kW1DcOHMYKTm8vIo766yzknM9ynCDi/JmMnve7j1lupl9T5nVxsrBBL5wLpc75ve24nc6tsHUdxRPeSjzy/EMbzMfcMv5ueKHfXZGCOs24qQbSJmsaEBmMvJ2At/aXkmrYfL3zldL07W9/vI28Dbba3/8Qx1nJsfWsVJOWWLLkcDgKcujT6l7GebeqePajxkdZ0FYkVXmRx5oY/LTVqQpicFna4j2lcMZUIw8xnIOm5YrZZJj0YxLubVGHla9qEcmxpzwbqWqqhKFmcMRlrmc5B2Dm5KYw1yr6nl+Y0mT3zeiOEvDkIC7NMg95do39E0ZnsIzUUL1c2lzWDderVjQVsv2BAuGd7u97tqbZdTOV4JPWa9WDmbONM5nvEjeZRrtnTKvjeVwxh55YLY0h+UrhwD+0jjuj1/bNr5ZicRIcy6Vd2XiXLd607eyeiK/x9Wz70iuec6kzOSdX0vIYa76kn5o7PUsb33GykHhwppkHNaW1KkZN5zPvhm8rNrK5dDuYUmG5bB8Ne614ydX+stPvHNEGGs5P1fvoyP6BQHPw0kcjyaQ6BG5HLb5MFI52nJYeaUf2LLI4KaHlnH5i+N83wAAEABJREFU3hlK2jT5lMNc9b+qenFiThji+CJzOB480/msvPFNpqcN0VOs0OQMsJVXnpnoRrmf5KtVX/RqdecoyLx+MYyOmp/zleONg4SMKb8vRx1dle4rP3Vq5mdFWc7HlUzQxjrpEnhnBhlL2B6lzg5vZc/tvXyPeqivuuRw/A8++GBtA/nGreKNPbl/aPPOvaCL+eWhnE9cA4GRgMCQOSGAZZmmAZawpKgL4/GjsOlo7nVIZ0hQ2koBaNlaVVXJTByFnBB3PkI2vAk8glOeJenw3kmwCmcQUVA4QwgwYfanUQ5KgSd8sIljgLeb0Uap9T5LNzlaCBzPjDq4cUx4Lomggpk6CifoLJ9zjyiTDuw0o0mwC3PN/J7hbQmtg7DyYCofSpAZUDyUDkqTAdegQRGjwFE+hGdiWOKnZBponfZMMRPWbeQnk2BheaeyaX9HHHFEUgcKo2dKtb3L4lvxW05pTy9+37GZX4434DJOS4cNI8izd+Zv7T3DReqrXxpMyzIwvPQLfagMb8UPK4a5NuvsEQaGlTAOEqN4S6+9cs6I96yfU9pKw1s4oqTkNui528jqD8qevcrKZlZXXTneGFaezQ77zuIZP6WR4qdxKXL2wjJitEV9jGzC71tY+QRD38EsjFkU2ItHVpRRDC3fpTTqnxyAZIh26fnggw9O2lmZTlr5U4rdZ9IGzNBa4eSgvdy3XcmIzNdLVwYBBZ6cVW5tzngB1/zMiLZFwDN+2LXjb8aTzb6xn3PUl+Vt65x+Iz/jjTDf13M3k/5LjmlPeZwwrnIUMxCU3combTT3WW0DvzbmPpOfmDN2CJcOaW+2aBk/GPnCtOs8Fudn7zO+a+9wtD+eg0TZPJs0MJMsXnqrGtrxyxPZAqFsHIdWDjIahLci/Vf7cICed+Pxs9lWcdIh8jNHnXqW/PIXbzxlUBpTjIN0GPzaAt1GWZAxmpNMGkQGaH9WV3juFiJrnA2jn+Tyki3aDINXOR3GSp7pY+34bbHAz3EvPzIz5yd9juekh418kX7mMF/6DCeFsOEkYz4nsJ/MzLLVdmHlM/Ypm7HAuOjed3U2iXPItAXfHqmTSR08xkmTNxxjTcOaHsHghgPeTLaDSUOnEObncTkf6MhVVSXjLT3FeCo+k/6t/7jmMFe/WqfM2rHyKiNylpq+h6ckqx3oR+pnTBNHp/ZNTY7lZ+cfmehpxT9x4sREhurDZDVs5Uf25PTGU3X1nMl2UX2vlYM+8zSvM/JsgtQvWNkyrjzyYjsYnzmgPZP9Vi1wzmZ+52BZ/SSeY5YzA3+rePlxXojHz/GvX2gz5fcgR1t9D2mCAoFeQWBQnBCMU44ECghhwiAFCAWC8mGfJONXGC8uw5sSo9MxYO0hpwQTQDorMmNOiTBw8UQ6rMhP9BjExFMYGdMcGoSdwxt5qi1fslyMB5FxxGvrfYSld0tL0SdEeNiVaSjJFguDjUFZWSgrMMr4MAQIrazwMSoYPXgpRwZ79aRU2aNsmZ84ZNaIcu2a68T7bpDKzwY138PAyWstHWMJJlZZeJ8ltvI1+DGmDay+sfM1hGfyfQhFg5iVJk2vdX5nN1zhrM0xItWZQqrNqJvyUZbVJysHrfgZHZlfvEG0zC/HG3Thrv15F/ILEbYujBs3zuuGjShPlD4/N6gt6S8Uesq2QlH8ObsoBJ59XwMspYbygt/AKM4qEgolfsuQOWE4xfRVA7d6kwEUe32PosXJYLaQsS5ePoiBTJHB47kbySwGhx0lVNnNnlI2OACUl9xxiJQlrLCB5cYbb1zPzOM3c0QWUdbx68dw5/wSz0lpKax+nWUEJw5ZiB9xFsJYe6UQw9cqCIaSdqf/MtgofxxJ0lOC5c8Yks69tskZRF5r98qhH+e+7coo8M5eI05r34hSra7qyIgh99RFe1VnMstzk994RD5nfgYGvHxr+TlfgIFObldVlXxnMppDQjynDjnhe8q/m6mqqsTY0Ha1R+V3ZYRog8quzfrFI+1FPFz1VbN12kkmDjaOAk50fMg4zHDlZGAoyU8/Mp64R8Z3W/m817gMRwYUg7SqqvqXnkw+0BEYUfiN+fSHVvxWUOpTjD2OBd+N4Zzf752tyLiJ1wovZTcBwkDwDvwcivo3Q8iz8QM2DlPEbzxlrJBhrsrIMGNoZoxcjaPknTyQ/k0mdJsTQtnoK74LA1cdjQd0jLxijXPKJIVxpR2/9pD5bYX13XJ+ZFSOh3upAzJ0GcfGEnkPN1mtQD8w2WPWGh6WyueDJslWfQIPg5QMgA3j1XfPxKlD3upznFTal/bZrB+d0CocTq8yjlzyXn1LGcgmW3XJMXzkmq2SyuNZXyPPjOH6sHZKV+MIILf87K6Zfm02l9FV2+eklkeTlNd3U3dlcNaDe7jg9c7jjz8+cch6NkZyxHHM4qfH0yPYDeJzfmSn+GZ+eBDHOF5jnuehIDKN/mK8VzYTKtplXh1FZrAv6MvKk/npgJmfIzfzN+PJFeO+eE4c8piDyRjlO2TCZzz3jqBAoFcRGBQnBEWYAGM4EzqESwZI5yqX0hF8jBmDFk8hby/F2kBHWFNkEKOt9HYaoCkzDCfxPIWEkU5J2BrYLW1m4BC0jCiKCMWDEkoB9z5pKTMEf1VNvdQtl3uwrry+ZksseVUWsyZ5gPZO+FFa8HlWfgohXrNHBgU4EVYwwS8OcQKZbZJGWmTAgYm6e0aUOEKekSEdY5qQ5aCQlveZsieM8khh8twk5fDtDG7wZtjLv1uJ4WCWQJ2VndLDcFNegwXFl6D3jJr8lM3M3yneYMxg9S5E8dDGpRtO0tbM8FmJw2DVNrQ3iqFyGQgNtowM39v3zTNdmT87GfHroxyJ8mEIy5/yz9BTb+2TU8LsBeWM00Ybxi9eHojSIhzGnruV9AntRNnVRf31GeWlNKsDhcOzlUFwxosYNRx94jIxPhhN4rVJSqf+KZ4RSLFjAMJeGDJrwtGAX1kokXn/vjTkgFkTjjJ92veQv9Vh5KV7shEvZ4Uy+9ZN4gzxvl4jdbbyjvKurhRsTi/1VReObf2cgeUZP8M48zMQSn7xHAqUT/lpq+R2xpwzyDcytonXzo0vuV14RzcTPMy6aU/Kr+4MoFxmYwdjk2wQ32wn+ZmxCBNtEh+yxN4YXzr8OSzxkBH5HcYyTkxp4HjIIYekvH1BHJmjv/kW0gjz/VrxM1AYZlYKcfrmfKTrj7QPxpJyyZcRxgGV0xgX9UPjhjD8+njmJ++1I9+dcSWPjE15Ne5qM/JghMOC46uqhl4fUYb+CM6whL36lMaXdOpM7yKTPHfib8aTldqVtOQeh4z3IJMhdEt4iu8GIr9NZugTymi8yn1FO6PXki30NzoxeVt+e/fkMAcbZxs9kOOl7B9lPa2+48SXJodrd3QuzjBlYJibYa+q59sPh94tt9ySOHqkgaGJKLqz8nCQ0IF9M7ol41m5msSwznWTT0n0An1F+ZWBk5CeX1XPl4GjhF7AySIdfn2CnogfRiYRc38W3yq/HC8PGJiIM4HmeajIqkWOt9wHyB0Oqfx+zntyjhwV1om/GU/u5fxMLqpn81t4tmqk1D+9KygQ6DUEBsUJ0WsgjKbyMprMAlKoGBujqe5R12lHwCBn9p5RRbme9hymPQVF3Owqg3vaU4/sFJRQM2YM6ZFd06jdaEHAyhFyhlNntNS5XT3NRDNerE5rxxPhPYbATCyu1Tkmd8yKz8RsezIrjhOOfs6OnqxAFDoQCARSOCFGWSPgyd52220TT7gVI6Os+lHdaUSgqqpk9tDsJe/+NCafLnZLDy1xNUM6XRmM4ES+g9k2M01m2UZwVaNqowQBK8wsB7dk3AzfKKn2VNV0hoSl3FaaTRUZAdOFwEhMxBFtjLS1ZyTWbyB1sjqKDusMjoHwB08gEAh0JwLhhOjO7zKopbI1YKuttkqWtA7qiyLzEYGAJbMUH8sMLbcczErZwmWftSWWDmcbzHf1Yt6Wo1rGaouZbTS9WIcocyDQRMDZMGZ57RNvxo2GZ0vVnbVjTLZ1ZwTUOaowSAg4iNjqIdsmR+NqVtu3Hf7orBWrQgYJ5sg2EAgEhgCBcEIMAcjd9gp7Ku05dfhkt5UtytOdCNhXbfmjk+gHs4RW6jjrxZahqnp+P+lgvq8X87Z03RkOzrbpxfJHmQOBJgL2wDtYz5lRzbjR8Mzh6pygfJjgjNU5Uo9kBOhvDHBnteg3I7murepmUsT4t8EGG6SqCh2hFUYRFgj0CgLhhOiVLxXlDAQCgUAgEAgEAoHuRSBKFggEAoFAIBAIBAIDQiCcEAOCKZgCgUAgEAgEAoFAoFsRiHIFAoFAIBAIBAKBQO8gEE6I3vlWUdJAIBAIBAKBQKDbEIjyBAKBQCAQCAQCgUAgME0IhBNimuAK5kAgEAgEAoFAoFsQiHIEAoFAIBAIBAKBQCDQewiEE6L3vlmUOBAIBAKBQGC4EYj3BwKBQCAQCAQCgUAgEAhMFwI944Q4+uij00477VTTt7/97fTwww9PV4VHYqJHH300HXLIITU2Tkz+6U9/2raaf/rTn2q+jGV5PeKII9Ljjz+e/ExaGe7+pJNOSn4WUN433nhj2/wjIhAIBAaOwDPPPJP86sjf//73joluu+22vr67++67p/w78ZMmTUrf+973+uL010zkwdlnnz1F3nfeeWc666yz0mOPPTZFeC89RFkDgUAgEAgEAoFAIBAIBHoXga53QlDSjzzyyLTnnnumCRMm1LTffvulr33ta7XB3LvQz5ySP/nkk+mb3/xmuv/++9O+++6bdt1117T33nunM844o+ULrrvuuhrDCS9gWV5XXnnlBO8LL7xwKp5//OMfyW9Sr7766omzYuLEiS3zj8BAIBAYGAL7779/WmqppZKfG7v11lv7TXT11VenbbfdNnEq+GndZ599NvlJQ4meeOKJdM4550zVZ/VtTsPVVlsNWx/NP//86Y477kgnn3xyX9g03ARrIBAIBAKBQCAQCAQCgUAgMEMIdL0T4pFHHkl//vOf0+mnn56ee+65ZNbvHe94RzrmmGPSPffcM0OVHwmJzWrm1Q1LL710WnHFFdP2229fGxitVouMGTMm/fWvf62xhCe64YYb0uGHH56WW2655N+GG26Y7r777il4ODpe9rKXpcUWWywtu+yy6Ve/+lXtsMAfFAgEAgNHgNPgs5/9bN3ffv3rXycOhXnmmadtBhyDP/7xj9Pmm2+e1lprrTR27NhkJYSVDBwNEurzDzzwwBR99tRTT03f//7308tf/nIsfTTbbLOlrbfeOh111FHpwQcf7AuPm0AgEAgEAoFAIBAIBAKBQGAoEOh6J8Sss86aNthgg/T617++xoOyblUEg5jSXQeO4j+//OUv03zzzZcWXHDBGoU55pgjvfnNb06Wd7dyQph55UiomSf/sbrBKgfhY8aMmRySkjzmnHPO+r755yUveUlaZ5110mWXXZauv10o8LEAABAASURBVP76ZnQ8BwIjE4GZWCt9y0qubbfddkC53nXXXenaa69NK620Uh//CiuskBZeeOH0k5/8JMmPA5FMzAyciJy3u+yySw6a4qqvf+QjH6kdlpwiU0TGQyAQCAQCgUAgEAgEAoFAIDCICHS9E8Is3vve977a0M44MJItKWZ857DRer3lllsSLBgiGQOOGs4bDoYclq+rrrpqWmihhfJjmjhxYrrqqqvSW97yljrMrOy//vWvemtH3ldulUQd+cIfM7Fzzz13+sMf/vBCSFwCgcFDYLTn7JwW57Ho5yUWHIf33Xdf4lDgpCUXxeO1CmLTTTf12JasKLviiitqh2VbpogIBAKBQCAQCAQCgUAgEAgEZjICXe+EaFXfm2++Ob32ta9N8847b6voURVmK0U2PnLFLbdG+bm/q20tVjZw9uCzPaOqqvSe97wn2Xu+2WabpU996lPp0EMPTU8//TSWeqWErR9mYeuA+DNSEYh6dQECtl0gq5DK4sw111zlY989xyR+MrIvsMUN+fma17ymPhizRXQEBQKBQCAQCAQCgUAgEAgEAoOCQM85IRyo9tvf/jaNHz8+veIVrxgUUHop01arHQZa/j/+8Y/p8ssvT29729v6krzyla9M9p/nvecbb7xxvSrCIXYOv8yMVlNwBs3I+3NecW2FQIQFAs8jwDFohdLzT/3/dX7Eb37zm3qrRnPlRKuUnBA33XRTfS5Fq/gICwQCgUAgEAgEAoFAIBAIBGY2Aj3lhHAGhJ+i3GijjepzCWY2GL2Yn9lQv5DRLLvtGc2Z05LHPvPvfve79cF1ZXjz3ooKh11a4l06HCwBF+dgzGaann+OCgQCXYSAfswJwcHQLFZewZTD//nPf6Yrr7wyvetd78pB/V7/7//+LzkTwgHA/TJGZCAQCAQCgUAgEAgEAoFAIDCTEOgZJ4RfwvjKV76S1ltvvfqn6mZS/Xs+G/vCOQLKQyjdv/rVr64PrGtVwaeeeqr+mc0111wzLbnkkq1Ypgqz8mH22WefKnxmB0R+gUAgMCUCzl+x5crKozLGCoa11167L+ihhx5Ku+22W3r3u9+drGjqi4ibQCAQCAQCgUAgEAgEAoFAoIsQ6AknhBUQBx10UNphhx2Sw9S6CL9hL8omm2ySrGq47bbb6rI4t8FM6Morr5wcUFkHNv5ceuml6fe//33aYostypj6ngFT37zwR36MHzOr5UGgkyZNqs+IMJP6AmtcAoFAYBAQ4AC0beIvf/lLX+62pTlUdscdd+wLs7KJI2LDDTfsC+t0w4Fp1VRsbeuEVMQHAoFAIBAIBAKBQCAQCMwsBLreCcHYPeCAA9LBBx+cVllllVRVVR8tvvjiMwuHYc5n+l8Pk2WWWaY+x8HP+HFA+HULB0u+9KUvTffee2/9yyIHHnhg7TSw7PpHP/pRetOb3pQWXXTRqV7skMp99tmn/tWMiRMnplNOOSXdeOON6QMf+ECaZZYXmwsjyLkRfoVjqkwiIBAIBPpFwBYqfejyyy9Pjz76aN3HPOdEfsJT/3XIpC0X+vOZZ56ZTjvttLpvTpgwoV4R5vBJZ0ZccMEF9c91ckTYJpXz6XS9+uqr0+qrrz5F3+6UJuIDgUAgEAgEAoFAIBAIBAKBGUHgRatyRnIZxLSWHFPSHUTZpK233nrG39zjOTBQvvOd79SOhq9//evpyCOPTBwOK6ywQl0zWyisYvATfpwI+XDJrbbaKlnmXTMVf3baaafkZ/84fpCtHc7hKFgSA4qjY7311iuD4z4QCAQGiAAHn3579tlnJz+lefHFFyfPObltVtttt13Sv4VZ3XDUUUelM844I+mXViXttddeomrnIjmpP77zne+swwby58EHH0wXXXRRGjdu3EDYgycQCAQCgUAgEAgEAoFAIBCYKQgMqxNiIDUwY3/MMcekVvStb31rIFmMeJ6FF1447bfffjVGhx12WFp66aX76uwASdjZtuGAO2dAeGaw9DEVN7ZwiM+06667FrHP3zKgqqpKDgh9PiT+BgKBwLQgsNxyy9VOh9zPXEsnxDbbbFP3Z2e75HzXWGONOgzvhz/84T4nIkfj+9///jou8w7ketZZZ6X1118/rbrqqgNhD55AIBAIBAKBQCAQCAQCgUBghhDIibveCZELGtfuQMAJ/eeff36yFWaJJZbojkJFKQKBQGCaELDN7fDDD0/O2nEmxDQlDuZAIBAIBAKBQCAQCAQCgV5DoKvKG06Irvoc3V8YB2A6e8LWGCf2d3+Jo4SBQCBQIuCw2ZNOOqk+52WllVYqo+I+EAgEAoFAIBAIBAKBQGCmIxAZNhEIJ0QTkXjuF4ELL7wwve9970tjx47tly8iA4FAoDsRcFitbR7NX8LpztJGqQKBQCAQCAQCgUAgEJgBBCJpVyIQToiu/CzdW6gddtghveENb+jeAkbJAoFAoF8E/KzulltumZwX0y9jRAYCgUAgEAgEAoFAIDADCETSQKAdAuGEaIdMhAcCgUAgEAgEAoFAIBAIBAKBQCDQewhEiQOBrkYgnBBd/XmicIFAIBAIBAKBQCAQCAQCgUAg0DsIREkDgUCgEwLhhOiEUMQHAoFAIBAIBAKBQCAQCAQCgUD3IxAlDAQCgZ5AIJwQPfGZopCBQCAQCAQCgUAgEAgEAoFA9yIQJQsEAoFAYKAIhBNioEgFXyAQCAQCgUAgEAgEAoFAINB9CESJAoFAIBDoKQQGxQlx/fXXp0033TTNOeecaf7550+XX355W1Duv//+tMkmm6S55547Lb744umuu+5qy9su4tlnn0333XdfmjhxYnr5y1+eJkyYkJ5++ul0++23p4suuigtt9xy9bVd+uEMf/TRR9PXvva1tNhii6UlllgiLbLIInVdOpXpmWeeSccdd1xaeOGFp2DdeeedU1VVU9Caa66Zbrrppj4+ac8///z0pS99qQ6D1e9+97v0pje9qf7pTXgdf/zx6X//+18d3/zzyCOP1D/TWVXPv0f+11xzTfIdHn/88bT99ttP8f6qep5vttlmSz/5yU+a2Q3b86RJk9I+++xT477oooumLbbYIj300ENty9OJ/+GHHx5QfvD+5je/mT7wgQ+0fddQRmiD+s4GG2yQTj311JavxvPe97433XLLLenAAw9MfuLxJS95SVpggQVq/LTd+eabr+7HV155Zd0WWmbUIlA7O/LII9PrXve6WhZ85jOfSddee2167rnnWnB3VxAZ46cu1X/BBRdMX/jCF9J//vOfloV84okn6ni8aK655kq/+MUvallVJtCPyLOvf/3raamllkrf+c53yuj01FNPpW984xvpnHPOqcMfe+yxtPfee9fy00/nrrPOOunWW29tix+877777nTWWWell73sZXUe+Q/MyQbfoqqqNOuss6avfOUrSb/OPL141a+1X7iTsePHj0///ve/21ZFX99uu+3qto3//e9/f8uxSZ//9a9/nV7/+ten/fbbb6r8xP/mN7+p4z//+c9PFd+NAdrexz72sbo9wWuttdZK8GhX1j/84Q9Ju6uq5+X8D37wg6StN/mNO4ceemgaN25cM6oea84444w+DKX/0Y9+VONPLzDG/PWvf50qXQ7I/EsuuWRd7pJfm37wwQeTb6g+xlq/DnPdddfl5G2v5OKKK65Yl+NVr3pVOumkk9J///vftvwi1POee+5JH/7wh+t0v/zlLwUn46b3KoM6zTHHHOnGG2+s47RFfXh69J86gyH6Q/YcddRRyXipHrPPPnu//agTv/ijjz66bX6f/OQnp9Illl566fTPf/5ziGrc/2t8U/16iSWWqHU4sldba5VKuyCXq+r5flJVVa3Dabv4jb3aRFW9GF9VVZplllnSRhttVMv0NPmffM4888wEN7IcGUdWW221ur0tv/zy6bTTTqv71GT2qf7rD+ThxMn68mtf+9pE9yuZtMXx48f34W4soKdLV/KV98Ysbd54pV3QC4xfTz75ZMnW8p68+fa3v12XXf/KTMZReH3rW99Ke+21Vw6u+9Fhhx2WLrzwwrZjXB/zINzo/96/7LLL1mVeYYUV0j/+8Y+2Og99j0zM/L5Pyd8p/oorrkhkMFz1O/k88MADg1CzyDIQGHoEZhmMV+okv/rVr9Kb3/zmWnlheGZB23wfBY0w2XzzzZPO1jSqm/ytngmFk08+OVGccryBgPK+77771oo2hT/HddOV8GUQqDsDb4011kjjx49Pyt9fOS+55JKpjBP8Y8eOTe985zuTPDJ55pwRj6666qr0xz/+Me222261EGd0EJKUpZtvvrk2Ogj+Vs4jSoMy54GKw8FgtueeeyYDlfwXWmihtM0220xRhre//e1p4403TjvuuCOWYSdGtTIbWOEOT4PeTjvt1FKBbsWvTWf+TvG5wt536aWXpp/+9KddYdj5xgyDXXfdtXbUNY1S5aZo/fCHP0x4DIT6lPbxile8Ik2YMCHBD1GE9F/K95133ilpR4IH7DkwXBl+73nPe2oF69577+2YfjgZGAybbbZZ7ZBTf30KHoccckjLYnG0cN7gRRwWDOM///nPffyUOfnA+DWveU3tPPzEJz4xRTwFlEFEVlBAyTnfTb9m1DCyvvjFL6ZWhiMF9sQTT0y+30c+8pHaaduX+eQb341jbqWVVqr7L8cUZVLZKUuTWXruP0cAPOAF97///e+1fIVBq8pk/re85S1128YPS3Kv5BfOSGIQMZC//OUvl9Epx+tj4jlzpmDo0oeDDjoo+RlXjkB4mSD43Oc+11Jeid9jjz3SeuutV7eXddddN2m7nNjaWir+nXvuuUneRVDfrTGIYs4xbjzXj/7yl78k45FyMMIY6WRRX6IXbrTLzM/Z3uRn5EirTctPP+Fo16986xeymepy9dVXJ0blj3/847od/OxnP6sd7JxOUzEXAT//+c/TZz/72cTpAR8yQp3IWY5nYZz2H/rQhxJdyVhqzNxll13SBz/4wX6N+uI1w3L7/e9/v9YdLrvsshoTdfRt6DCtCtSKf8MNN0yZX/zvf//7lPMbP1n3KeO1Q7qD8EwcOa985StffN0w3Rn/d99992Ts903pcMYz35VjuFks49v6669f9xN1IV9cta/M+7a3va0vXhxaffXVk3GR4wrfv/71r1pXfte73lU7ic+d3K8Y7+S6chhX9DNyB3+T/va3v6WDDz64ngThiOP4KHnIMd/Hu9HEyc4Kk1ucDCVfeX/DDTfUTjfjhDLQJfVJOkHJ17zneCRDtX/pjP14jGPHHHNMPVFGJrz0pS8VXBO9gy5J51e2OnAI/6gTeU5mKfMOO+xQTwK4b1UM/CZDMz8dmDzK/K3iYSJeO6J7Ic/6yTzzzJM+/vGPt5THrd4fYYFANyMwy2AXbtVVV006H6HSfBdD28CcV0Lw+DZ5BvJMiDKoSyWRJ/a73/1uojwNJI/h4CFAebMJMYJFGQwgFKWLL77YY0viBaXgUqr+UksDAAAQAElEQVSaDBRGKysI8EyUQitS8Bo4CT2zO/POO289q2og4Gk1k+sbrL322rVXnzIlTUk824wvhknO/zOTZ64pdhRAvMp1+OGHpxzvamXMpz/9adFdQfCl9DJOFAg+H/3oR+vZZYJeWEmd+MX7Jp3ygx+j0/vK/IfrvqqqNG7cuHoFx5gxY1JTuaNUUXLMnKy88sp9xdTOzJKX/NqQ1SQMtv4Ulr5MJt/Aw4yn/CgajHIzC9omB+Vklq79z9CyukedFdKMEaWNkcKwEFaSeAZbDuM05XTQn3IYhyy5xYlHLubwfMWrXzL2yD3vMROtf8HQN2EYaItWaeR05ZXDR1+08sl9Gacdkw36LDLr6V0XXHBBS6dGmbZb78kmspbSrowU3s033zxxlDNQhZWEn8KX8cfPkCz5Kfh77bVX7VglXzmByjzEUxQ5gFvFl7zddG8Vo2+tvlYyKpt2Sok2LnkuiUPsHe94xxSynpyQR+kw4NzSJjkryvTuyQp9nfFZVVXyrE1zcFdVVa+oVB4yyPukKSnzM9Sqamp+31Jf8D2rqqodb4wdbYJBVuZV3lutZpUTY1E4A5ERacxutzKITDD2MSI4vaTLxKGnPXjWXhgjVpMpmzCOEWW00sxzt5FvaNznZOZMVT5lZYRbVeW5pHb8DCv8OZ5zO+fHUZfjc16MULIokzJwtOb44brSHxjCecynw8FDmxLXLJeVa2Rzrgcj/Y1vfGPi3FJn/BwAOT5fyeMsu/CYhbeCIesQ2hxZbhWCeH0MnsbtpiNQvDGCI4cDxfjFqBeeifOPcyi/f//9908cKK10eGk4wn1PK8Zym1cvfcW3w9OKOCrojnR3fbfJo050A/U0tpXxY8eOTd7RX/4l/8y857w25tOX5UtnIeuMncZzYSWRI8abzL/tttvWqzkyfzNefvqUdkT/Igd9b3n6rpxcdKzcZoQHBQK9isCgOyEsVeO5JYAJqxIoiodB1xKjMnx677PSVKZvFVbGD+e9GRsrC8r6U3gNDHfccUfboplFkSZ7xkvGqqoSY64MK++l5cWlWHE4mKGhBJnBNjjhJfSVg5D0XJIVFbzslh8LV1aeegOwOMoVxW3MZINWPDJDYNkmI8xzNxDPvTqXgxvniTbquzTL2IofBmbhYGqAbuZXxuf8zPp4zzLLLJODhvWqLL5fu0Jon/qpujSVlVZpzCxyAFISWsU3w7S/8847b4pg7ZcixRifIqLLHvQPS2DLYlHCOFcp2GW4e3VyzcQI0uc4/XIY5wM+xEDJ4flqlYW+b9m5MI4/bVCf9Yz0Xf1S/p5LkqeZy6bzIfMwBG310F+FyYsTQrqqqgT1FFHi4MBhU/Z1Cjvc4FdWKPNrg+XquZKfwkk51m8oo2V69zneSkCyUFivkFUdVVXV26xymRkXlGLtOoflKwc6IyU/WymlDxhbqurF9sKw0aZbyRCON0o1I1w+ZIhVaWUbVQZp8eIpSdr++I1vvmtu09JyntIN6Caem6QMZD5Dp4xjWMmvFRZmlTlsrLDLRkNO691kRVW9iIl89GVOm8xnZR0HFtmSw9pchzyYEwou+kJ+ObnDMDL+5bB87Y8ftpxD+kqr/MTnfPTdfN9NVytljPkc5rlc2r6+ou45LF85W6y+yc9WupEhxlh6E2des91wSjBa8zsY+/qo1SE5H9sfS12QnNMP6SWtnBCrrLJKvT0sp29ejfflN1EuK+/06SavZ+W3bcJYYZwQpr2rCxysqhBWknAr+Dho6aJlnHtbboTn/IQ1yVjJ4d/UH5p8M/OZXs7pqd/mfOFtxY723HRC0APUv3Sa4SfP8N92222pv3htXxvJ73IlN+jSpXwUHhQI9CICswx2oQlHnjzLxcpZJzPyPNrve9/7pioCQ1DHfMMb3lDvudKB3ZcDM+FKIFg5sMQSz+/H41meKrNGACFBAI4fP74v76222ioNh1eRcswIyR5SRfXMiFNOz00i1P70pz8lylCrQcHAY6YCJoiCYGYPXvLyHQivLERhTREonQZVVdVnebTKX5gBiZEjPyRvQpjSXlVVcsUnzgBlJQyjlJNCWDeQGeUSd2XSVimr6uO5pHb8eHyrTvH4fAczeWbUMj7Cu5konWZBKUxV9aICncus7toxsrfU7ItZdu0ODyfD2Wefnd761rfW/c3gayZRu5C3Qdi9gV0e7qVjwDESjj32WI9dR7nepbKmkOqnDYn33CRx2oq6mvEw4ysNPktZGVQcARQNPJS73B5h+b3vfS/Z757bD1kGJwaaPBCFlpGV0wkbKOm70pb88qFgek8Z3iv3VouQbxwLuczq6Fndcli+4hdPAcxhjADP+BlInIkc6L4R0o59H/zt4nPbxtOtZCWE9qO+uYy+Ozy03RyWr5zPZdsTru0bw6TzbFaY0c7h6blJZKKxKr/TKgM4K0fmFefZeJXD8pUDQrj4HFbyMxTpCpR+8fImi20flE5Yk/RDOopxq4xTzpRSy/3flkxrAwxEbQJ5b5nevXAy1RZIYzmDTTjSJhlfJm3gKKxbiO6hDWTdIZfLc6uyduLvFC//W2+9NX3qU5+qxw7Yk3u2M7b7btIMFenzzckE+htdSBtrloMMYoCW4dqYlX/qpf2WepWVQxxb48aN60vCCW2LUG4zcKAr0+kykzz011ZlyDz9XZVfeTKPNk1XUv4cVl7F60vG/DKdMYMTQRlLfm2ITmC7JT1Wf0DGxVbtqExb3pPHtonQEaYlXZnHtN5rj/ClA+e0voW6K4O65XBX9RJPHnlGnjO//DyX8fLP8fgRx5a8Tj/99GQlrS2TJdZ4ggKBXkRg0J0QhC4jn2LGa5lBYgwTIBSEHOaqE5vtoKDzAlMceHrtASOMDUD4KO9mYcyu4KFUEGLi+iOzDPZebr311vWeRs+Eoa0chGl/aWd2nMFjWvM84ogj6sP74NoqrVnVgw8+uK4bXCg0HC55dt+MVDm7Y6AqnUOt8uwvzGyipbfea6Bq8novZcMsUDNuOJ8t7VX2gZahE3+neIOI2VPLNQf6zm7g0xcNuM1+msvGALBU1CymbQK+NyM6x1O01ZmBrT06TFX7dO6BwdSqGgq/c2MOOOCAVCrtZkMsNc15ddPV954eeUEh0w7UlYFDCXMgmbyy4UFBE8+ZQ8k95ZRT6sPwyD6KhxmmjAWDOd8PxpVMZURavstBMRjvGMw8jScM4IG+YyD82jGntTbsO1lSbLZQu/aeHJ+/Y47nQBLfzURWz0j51N3qAuM3g1peHDbaOaPBc5OsRnE2Qg63RYtMyM9TXFs84OfQbBFVB5FNtnNYNm+JuckKfUq7aDeO+r76ZJ3BAP5wnFiyboUSmaddmPk263zeeVOu9DpgspwjA4w/xsVmvNUFMCRjBvDqIWNhaOofA31hJ/5O8d7DGW2ljXaFtt1222R1EQNd/HASvZHhOb1l4GDghCLnm3loz8bTMo7Dgq5Fp8v85XiZw2b2la7O8dF0uOf3aMfKm587XdXDZBlj2/iuP1hBZKtSaSN0ykc8HYFOaxLD82CTbz4t7+jEP9Bym4CFky0s5JYtGTMqq6elHsEbCAwWAoPuhFBwM3eMVAaH8wwMPmbwKAbiSyKg7LPjRZVGnJkW+295e+21lN5A7xAnTgg8ZtkHcv7DCSecUG9XMPjndISfmQmGorBuJcoKxa5cvtksK8dMGe/MDcoU4xCvmS54up8ZZJWDpZgO3MozX2W+FHD4mjErw0fbvcGDcc7D3Ut1108pC9pdq3KbvbGiiRHRVFIo0fZs2gttFkt6SiWnhnM3bAvQj2FitouBUObh3pJX6UYKwZJSra7IUkty0ZYlfZSMs/VFHLKHGL6+A4Wzqqr6F0iGCg+GFAM7y8uhem+3vocRRoHmkGFw+kaIQ50TgnzN8dq8OMTxzQnBGd+tdetUrk7xHAe2E1jdmFc9WOVglo8zrV167ZocaRc/o+HeT2+wTaKqqvpMCCsrOSDIoBnNX3oGAUNM/+Vw8c05O+zn96sp9B58SBwSb+bcltUynsOXocHBi380k7MCbHHIGHDe0F8YZTmsF6+cx7YbkgmW1jfrYFWhdsuBluM4hDk9hlKXcl6Fdk2/a6cD5PIN9KpdW0XiOzozLvcFk2PO5aI3DDQvMph+W/afgabtJT4rSeGETOpwcDujyCRiL9UjyhoINBEYEieEZVy2ZBhYnQRs1QLhkZchl4UyU8jJQEBZypXjGCqWy5s14V3kQbRsLMcP9Go/HcPZDAUlkXLkYBhLZQn4geYzM/isHCBEmgKUgsupUr4Ddg46c2CQciNKLyzcczbwSJdp3MORskVQG/jM8AjPBGMKYCsHDEdQ5mt1tULFIZiEYqtvaemg78zQyul9W+XNZFbXqpYcP1RXyxWbuHu3mWZGsvuSOvGLV7cyjXv5GcQpnLzXud6WENp7qf35pni7kToZTepn+bHVNr63QTLXw5YChom9n7nelp46cMnspbafeVtdtctme23FNxxhvrdllIyP5vvN+OpzzfDmMyXTjDHHq77LIGG8cdrgVX+HdlHKvMfSTeEl6aNkF8WuDHdvSbzr9JJ3Uz4doKeu8uHozd/S1bcX3q1UVVWCs3YE42Y5zTqXYVX1PD95SGaWce7xk88cZPk7cb5yhvvmZrBzvG1X0oi3ik+88UfYNNKQsRtT9U0yq3ypMVy7LsOa9yYFOB2tMhRnbOIUN4OnrSArofR/9xyzjJFm2/WeqqqScsinpFbjTObXD0pe95nfdzODTk5xqnH4cRAYn8y+Kk8m31V/0+aNmfIpiSPRtyzDGGj6LwcEw0qc8Z1DxkrDVvlYCaUssNY+pUHy0lY7yUe8Q0l0sKp6/uDQ8r3Kq32UYe478XeKl0eT4K4/t2obTd7BftamONCa79FujA/N8Pxs1Qx9gAPMBE0Oz1fOBiseyA9tLYdbOcsJmp9dtW9yyjjruSR6TFVNvYWy5OnvniPESkhOcuMMXpMHuZ/kK8crx4gytNKhc1rpEZ2TTNRPsm6orPCgk9Eb8A2EjJHeCYOB8M8oj2/ORtFnm3nBgD5UhuPXl215LsPd44dNf/HN/KTjQDXpQ99Ud2FBgUCvIjAkTgjgWM5LaDn0zKoDxidhLa6kqqqScIJY58xxeUBmxOiYiKKY410p8679kQGTomAbhuV9EydOTASfZXFmMfpLO7PjCBKKE6dMzpsywuFAOcphrgZey7E5X5QbwZSQc++kY+nwlgRDMyuWrRF4FKUy3iBnAKCUZUFOYDI+/dpByZvvfQtlcR6HJcnKluPylbLNKGW0GHRyOMVDeTOpu8E2xw/VlUPLbAr88zsd2GlQYwjmsHxtxU+ZNpjid26JZetlfjne4XVworCoN+eN05JtMYKzpYj5Pd12Va9OZdKGHLhlBl87tDxSGm0NPg6fUm+kvzE6nIKuL+JrR9qZPNrFD2c4+eOcDI4k5cxlUXfGB+Uwh7nqW5RP9yVp+SX1UgAAEABJREFUE/ZUM0gYtpysZX54GbWUWv3Xc0lkCCcFbHM4owfu0yvPKPhWXzCsGW6+b877q1/9at9WL++01D7HdeuVYQ3XUj5avQUfTsBmufFbeQLXlJ6P1U/JLniTp+Lg9Hzs83+1Vd8xxzfHI3JQ/PPc3fmXYa5uvm0uofakDcArh5VXOBgLOBws21ZP8cYmmDPA5YesirQayr2VkORL5pcGccDrK4wuzwi/canVWMEwxe89eFF//MZ6DhArFPRj28nwZyKrlZFh7SBA+WXiMIeRMTOHueqfyqFdeS5J/+UogVMZ7t47YWB88YwYFspVVdNvQMpnZpO2q1zGuZw3g4zuAJMclq/0vXb8xgr5VVWVWuUnnpHVNLq9D87las/8vqG+kte+tzEtv9sWCzocPTWHlVf6gS0I2hYdoKqm/sa2PxgD6MhlWm2uqqbkJ3M4m62ky1h5P4e1b9LsW2V+7e6920QdPd0EHWM58zKAtdmSrGAw5nHA+j6Z13flZGuWwbhPNtBltfXM76qfiHM/EFJWfNqZ62CTfmosL1doskO01eWXXz4166qN08Hpublsvg+Zip+e3188mVdiKg/85B29k1wWFhQI9CoCswxlwc2I6lQ8pxR47yY4dWrC2b0Bm3eYoWZPHB5k/zjlyB45Sp4lbBwahL54SuNpp53mdgqiCOrEOq4Is3sUSrMf3iuM8mIJbRZowoaCOEMowb/97W/r35r2TuUinPIyPHEUffUQXxJBBLOs3DAQLH/NPOL9xB7Fj9dZONzLvBgrlDAGOYMIj+/jezCSPRtweO55fw0aBidGp72JwjPZRoMfn9l9S8go9MK6jZTNgOLnlpRNfbU3P91GufDsp0x9D/Gt+CkL9qji7xQvj0zamTbJGM9hw31VX+VqlskgKVx5yzJqc8JLfuc++N5+A9sMJ0XMTLnZzzxoa6/6n3j5GZDlnfunsEwMx27eBkCWkDv6pzIzuPQBs59WIHl21oXZIwaVPlEqrBRHcbYsUeKk09fMQMkPtg67Y3iRB5wV8POtxCP9mrJvq5Z+rX9yEFLiOS08W7pJqSzTSSt/CpT7TL4pxZO85ZzNfduVXMh8Q3KdCS+pqir5qTffw+yiLLU58s4qlPwMc07IqnqRHwY53h50fd0z5Z7yl+PhzrBluFphl+Pz+8Q7sFVbFi+PbiWHbTI6tCd9XDndq5tx1zOZaIY0j59WOsDOygftJJO2jL8k4782ltOKY4SXzxx4HGC2Tmrv+I05xkXt3bPvR16L1y+MpT/96U+TZ/Elv3cgZzZYgWZrp7HS9xDeimBgLDD+ZgNC3/XNHfwsjWf5kQHaF72l5NfnyT7tzCyxrWfGRmmR9qEt0mM8ZzIBwxDjjMlh3XA13mu/Dscj25TJeTbwz1iSNeLVS5vpj1+872mcbZWfrRfkqfcg/YgMpfvZ2ihsOMnMPR1CO82y9fDDD68PDTf2KZs4/cW9NmDlqHrRu3I/0UaMBXiMk1YLM97xCMtEnjO24ZDDXK2wJN85HjxzjFRVlawywG+8dQYKw1d8Jv1bf3HNYa5kGb2IQW07Ri4n55y+hackEzdWeunvJp/E0anVxfaK/KytKAt+ZaO7Z35jjb5jW6axUJpMxqiMbw7LV30PTvSOHDaYV7KJjNTOc5tVBw5a7dK7jRX0cH1dufrjL+NhIL38OLyNI/oGGVPW31hltVa7SUJ5BAUCvYLAoDghLGWkmBAyn/3sZ1OeTSCoKHI8wAZtIFnCecYZZyRKmv3HHA2EuyX+FAV7TJGOR4BTTqS1NcFAbXmleILSLBWByvA20yo/eRDOZmooLZQVQtuy8ZzWoZSUI+UZajKoKl8ui3uCmBKkLO4NCASaZ0aF2Rh1NvAY2KSFIccAA1Acsg+WEQkHaRGFPCtVnnnSzUgZNPFL59cLfBeDXvk+A4sVJGbuKaYcQvgzSW+QMstkIBPuHd1IPNScYgZn5YThmDFjksPLlJdCDXvt2HMrft8o84vXjsr8ynh5IAoaJZYST5G2V9zePnHDQRQaSjlFWFvSb6xcoGArDyVSuFkLz74vxYRCTdHEb8WLOMYEJYxiAE+rBOTrbBfPcLZ3XvvADzuGvFkEfOKFI3mbYdt00009diVx7um/6qHsyBkOVr4osH5mOwNFAjYcrHgyUU71WTIJPyPGtirfI/OQaZwUFDczY/ojRQ4/smpMPGcGjOGr7erzZgw5eJxB4UBbmFI6KXvyZ5SR1e4p+xxBTt0mZ327j3zkI0lcJn3aO3uNGApkkzFCXcgvM9fGInUh12DEYeQZPznqOfPry4xJ8RzHcCInxevPFFLtoF08BdM7xHczVVWVyDzGtrqhqqqSdkXZV3ZjrzGW7BBvubYxybjqORPHBH7tioNAOGNLv9ZWc/zYsWPr1TV4kfGd8UIXkAZZVeYbVlWVvNf4rRzaM2OdHOnELx9yTFqrNvQd72tHtpVoB9IhuNBLGOPSqLP+nethzER4kX7sTAP9iFOQkx+O4pAxgOPW2Cu/TJx9+r02l8O65cqA9j2VH6k7TBhNymjscMYFme65Ez8nKxklL1TmB1uYC0fwhAldTt7DTZxyyk8XUj5ETmc5QGcjG9RB24ST8ZKTGG8mbcZYwPmE38qGcePGTVU9dTcGkPVlpDZGJu2xxx61vDYey8fkCD6ynC7Dqe+ZzCcDjTW+pfLSk/UNbdrZKfRJOOcyutKXSmehvDLlMd43wiutcdDKKDzqrHzkimeTE7Zoexd+/Uw/0MfF0zmMQ+KMZyYY3efJCzxIe4EJJ4DnoSBlJHfIMGVim6hHdp7QgXxrTkjlwe+a+Y2/sMj8OV5eSHzOz8+QmuzKacWTw/BqtQLZe4ICgV5CYFCcEJwDFBKzEYRbebAQ46X0YvsFDE4KCq6OS9AyBnU+gzQBiSh9eWYewAQWRejEE0+sDUedlseRgs6zbLC3FYCiyLN42GGHJTOKOjABzEOtbPImoBlbPL/yHkoyg8CQYcAqC6eNrRO5DLBRnyxkebbNIOCFjxUclEDCnqFjVlYcogxQtC1xy/mZ3TEYlV5xwtBA6ZAk6QwgvpHZPu+TBy+3Qc2MLKPKc5MsRcfPcORUgml+bzdeeZPhq84GPO0g48wBow6lg6DJr01mfvXrFI+HcuFd8qZYWxLs24kbDrI00iBIMWcc6C8UegqW8vDUU4i1Gc++LwWCUUFZxq99iEOchGYChPPUU47UlwMQzojjRVulKGlz2jB+cfJA2hblg1HvuVtJXczwKLu6MG7IGOXV/uHG0eAZL5zxIjhnB4R4tMsuu6Tch22JoKxQSsVROhhG5KpnVFVVgjO5ip+h630MO/H6MCVG2RjeVVUl8tj7OcHMmrnXdjkkGXZmsODfJMquPHuNGJvabB4rnFtg25DlzeoCK9/QWOQZv7Ei85ONxozML97qsdympeOQlU9O3188nm4mbUF70m+1DW3QDGAus19x4TRk/ItvtpP8bByQRrsysYDXkm3ywdhrpk+895E9Zjw9I6sezABqz76XtAx5cQw9mDNAyCNh/fGTccpClmvf6667riQdSX9hVOXvrMx+6SsnzGMpJ74w/MbczG9FEaNBebUZdTGhoC6IoyVjIH0m/Y+Dczj0kVyGdlcGn7OoyBN1UKc8AyyNfsQoy+2lE794eaFmfvSSLAvFwTbj6V3dQOR3qUsaz/PYyQnMEa3dcayRy+Rt7h/5arLOWECXsFWDvJa2Vf04tDgKyjhySVujR8LJvfaj3+GDGePfVgrP9HO6izHc+MRRxOFjfKFbclrkspVXY1epS8ork/p5j7IrA5lJL8hloBfor/R6afCrc+bXn8lY/UQ82SI/eSmDlQXutQnxmeiiQz0u0YccKsrZo0zI1ohcJuOwySgTgMJa8a+88sqiauovXjvQvrIs9i71zW2sziD+BAI9jMCgOCEovoy4sZNnOMwqcSxkjAgfSkF+xlNSFloGYANZjjPAV9WU++E4K3I8Qey9+dn7GTr52VUe3otPvDBEyfc+cUNNVfX8QWjKgQjfsgwwaJYPhnhLgnFVVQl/Dndf5uWeYWT5tlUUvLnCkFnajBdBX+KR3wc3ClXOv3n1vqqqku9iiWb+lvLvVlLXXI9sPCqrsquPduI5Uzv+gcbDJr/PVf8QltMP9ZUS71spSyaOh6wMUDoYEJRBq4WqqqoP+su8rpSaXO4yP21SeNlmyvoaSKUvCb/Zfk5JRru0woaGpv0tVVWlEr8yB+2prK/nsq4ZnzJNVVWp5NEOy3gOQkYg5TGHw5wCK533lTKkqqoEZ/H4pMn9GX8msrGqqinkR47L1zJf+fQSqTsc1MX3Iu9y+ck1ccaQHIZf38dPLpb8eHwXacQ3MR9IPJ5uJbJfn1Y31Kw7/Mx8w0h8O8rpqmpqmSFNjueYtdyY8V1iok3iQwykqnp+/Pde71eOgfL7tvLxrcs0ne59Z+mQ9lDy536U6yGOboMXNcuX+cUhBoY0JTG2yDyOmTK8m+6NV8qPmjLM2IHglsvcHz8eecgLuReWSV7CETyr6vk2kOO74Uq2Kh8i43OZ9COyQbtx74qnSXjUW9t0r+/lPJpXTnntQzsp47QlaeVNLpVx8qbLaJvCvQeWeDPRa4Q322iOd6WHVlV7/KUnK/EqQ9YhvFOZvVM5PSO6RS5zWT5x8FImeZVU5snZRZd1bpE0Q0VV9byOm8tFtpTv1h58a3gIr6r++auq/3j55Xe5ln1L/kGBQC8jMChOiF4GZKSX3SBgWTEnhCXEI72+Ub8ZQ4DCzwlB0baiaMZy6yd1EcXAdiaMWf8iOG4nI2A1Elzsz2W4TQ6K/4FATyNAsSZjzGr2dEVmsPCWb1uxydE4g1lF8hGMgKX4toDY4jGCq9lv1Wxvs2LD6ul+GSMyEAgEuhqBcEJ09ecZnMJZcmcbiH12g/OGyLWXEOhUVjMglkZavpn3+nZKM73x9pw6n8C5MYyT6c1npKYzQ2RJq+1UlraP1HpGvUYXArY0mA11DsfoqvnztTUhYEuCrS8O7Xs+NP4GAlMjYPumbTwOR3RG09QcIzvEgcoclvqJrYgju7ZRu0BgZCMQToiR/X1b1s4yOHtb/cRnS4YIHCoEeuY9flXFPk9Lawez0JYwOivCnvxYdtgaaUvR7Z8t92K35ozQQKA3ELDSyvar8tyn3ij5zCmlZfDOq3B2yczJMXIZqQjY8kF/c26XlYojtZ7t6pX1V9swQkdoh1KEBwK9gUA4IXrjO830UtofaJ/tTM+4ZzKMgk4rAvaqDvagX1VVsseSM2Jayzea+O3zpYyOpjpHXUc2AowLfX9k17J17chV8rWq2u+5b50yQkcjAvqKM3qqavS1F44XkyF02NH47aPOgcBIQiCcECPpa/ZKXaKcgUAgEAgEAoFAIBAIBAKBQCAQCAQCoxKBcEKMss8e1Q0EAoFAIBAIBAKBQCAQCAQCgUAgEAgEhguBcN66SJoAAAr+SURBVEIMHfLxpkAgEAgEAoFAIBAIBAKBQCAQCAQCgUBgVCMwSpwQo/obR+UDgUAgEAgEAoFAIBAIBAKBQCAQCAQCga5AYPCdEDOhmk8++WTyc0QTJkxIEybTGWeckR566KGZkPPIyAI+55xzTo2Nnzi7+OKL21bsuuuuq/ng2KTzzz9/qnS33357ze/nAJ999tkk73vvvXcqvggIBAKBaUdAn/rHP/6RJk6c2DGxn/HLffbEE0/sk4F+sqyUj5nHlTy49tprp8h70qRJ6corr0xPPfXUFOHxEAgEAoFAIBAIBAKBQCAQCMwwAgPIoOudEJT03/72tykbyBTub3zjG+mwww5L7gdQxxHN8vTTT6cTTjghccw888wziYGx6667pr/97W8t6/2nP/0p7bTTTi3p3//+9xRpvvWtb6XDDz98ijCYM2zuueeeKcLjIRAIBKYNAf1WX9xjjz0SR0R/qW+77bb06U9/Ot1///0128knn5z8pJ+Hhx9+OB1yyCEt+/SHPvQhLFPRn//85/THP/5xqvAICAQCgUAgEAgEAoFAIBDoXQR6peRd74R49NFH0w033JDGjx9fEwObYv3Tn/40mRnsFaAHq5wwOP7442sD5AMf+EDaeeed08orr5yEPfbYY1O99hWveEU69dRT0y233NJHF154Yfryl7+c1l9//Zqfo2HPPfdMVkEwdMZPxv71r3998tNIa665Zn0966yzat74EwgEAtOGwBNPPJE++9nPJs6D7bffPt15553Jz631l8uECRPSq1/96rTXXnsl/fGTn/xk4kg488wz62Sbbrppuuyyy1LZr4877ri0zz77pOWWW67myX/GjBmTNtlkk3TQQQfloLgGAoFAIBAIBAKBQCAQCMwYApF6GhDoeifEPPPMkz71qU+lJZZYoq4WQ3iBBRZISy65ZJp11lnrsNH8x4woxwI8qqpKc801V9pwww2T7RmttqzAc+WVV05jx46tafHFF0+2Vyy//PJpvvnmS1aecPBw/Hz+85+vw0p8Z5tttvTWt741XXTRRcnsbBkX94FAINAZgTnnnDN97WtfS7vttltaeOGFU1VVtWMvtfnHSWEb1BprrNEn8zgDyUErwl7ykpekpZZaKi2zzDJ1nx47dmxacMEF0+9+97v0pS99qWWuiyyySNpmm20Sx6UVVC2ZIjAQCAQCgUAgEAgEAoGeQCAK2WsIdL0Togmo8w/sZ95oo43SmDFjmtGj7tnM56te9ao099xz99Wdo4EzwVaNvsAXbjbeeOPagfPCY7IF45prrklrr712HcTgOfroo9OOO+44lQOiZpj8h8ND3ueee+7kp/gfCAQCg4nA448/Xm8947Ao38PxwBE4//zzp3HjxtUOSPH/+9//0mmnnVY7GTy3o8033zz96le/qs+HaMcT4YFAIBAIBAKBQCAQCPSLQEQGAtOBQM84Ia644oq0++6719sOfvzjH09HVUdmkptuuilZCVHWbo455khmW8uwdve2ZlgNwZDB89e//jVx9NgG89GPfrTG+wtf+MIUqx4sHV9hhRWSFRPSBAUCgcDgIWBblT5pFVL5lnnnnbd87Lu/66676m0ZK620Ul9Yq5tFF100veY1r6m3Z7WKj7BAIBAIBAKBQCAQ6G4EonSBQK8i0DNOiKWXXrre32wZszMhPve5z4URPLnVMVAmX6brvxUlnBBbbrllX3qH1V199dXpkksuSZwQ9qCbLd1///3TpEmT+vgWWmihmqcvIG4CgUBgUBCwXcLKo4FkbgWUPmx1lC0XndJwQjhLohNfxAcCgUAgEAgEAoHAFAjEQyAQCMwAAj3jhDCzv9hiiyX7nRnNq622WpowYcIMVH1kJHUuBsOjWRv7xKuqagb3PTscb++9904HH3xweulLX9oXfvPNN9dbMw444IBktYPZ1H333Tf95je/SQ888EAfn/MjnM9x66239oXFTSAQCMx8BKqqSs8991xNzdz1/zLMr2c4C2LzzTfv95yJnMaWDqueSgdjjotrIBAIBAKBQCDQnQhEqQKBQKDXEegZJ0QJtO0Hzj3IWwjKuNF2z4i44447EqdCrrt7h9Zx3OSw8mrP+DHHHFM7GRxSWcYtu+yyybJvlMPhDG8zsjksroFAIDA0CDjvhVPR+S3lG++7777EGZvD/KqNn/t0MK2DKXN4XAOBQCAQCAQCgZmGQGQUCAQCgcBMQKDrnRAOXrvgggumqKoZ+aeeeirZljFFxCh8WG+99ZI94HBSfQ6Ga6+9NnEmcNYIa5L4U045Jb3nPe9pRqU3velN9U+fMnBypFlSK1DK/ByWxylh2Xfmi2sgEAjMfASsOvLrQH/5y1/6Mrfi4aqrrkrbbbddX9gJJ5yQ8Lz73e/uC+t0Q5bOPvvs6WUve1kn1ogPBAKBQCAQGGYE4vWBQCAQCIwUBLreCWE237kFzigAuln+I488sv4ZyvXXX1/QqKZ8Kv7Pfvaz+kBJDoNzzz03bb311vXhlIyMVVddNR166KHJvnLOG8aK/eL2gzfBe9e73lWfsn/iiSfW+T388MPpuOOOSzvvvHOyIiLzm5VdccUVp/hVjhwX10AgEBgYApx9ZJotEWWKI444oj408vbbb08OoNx0003T8ccfny699NKaTX9fa621kp/qFOAXbr7//e+n/fbbb5p+Nej6669PVkNxRMgnKBAIBAKBQKAlAhEYCAQCgUAgMBMR6HonBAX8ta99bdpqq62S2cBVVlmlnq3/2Mc+lpr7oWciLj2T1atf/er0wx/+MF1++eVp+eWXT29961vTF7/4xbT66qunqqqS1QpmTXOFGCsMGEu2x4wZk4P7rhwNzokwoyo/Rs6uu+5ar5pwBgRGef7zn/9MjCDPQYFAIDBtCPgVmjXWWCN94AMfqFchfPKTn6z7bM6FM/G///1v/VhVVb3i4dvf/nZyHg45eOONN6YDDzywloGcGBwUHBkf/OAH6zQD+SP/3//+9/UZMAPhD55AIBAIBIYHgXhrIBAIBAKBwEhDoOudEPZC77LLLvVPzt1yyy3JEmQOiZH2IWakPn455Be/+EWNEefAG9/4xr7sOBXg5udNnfNg1tPz9ttv38fTvLHCgXGCzy9obLDBBlOwmJ1l8Gy22WZThMdDIBAIDAyBt7zlLfXWCX0s00UXXdSX+DOf+Uzdn/2MZg7cYost6jD8HIXZiWi1GIeE8Mw7kKtf0eBoXGeddQbCHjyBQCAwGhGIOgcCgUAgEAgEAoOAQNc7IQahzpHlDCDglzj+9re/JWdELLfccjOQUyQNBAKB4ULAmS62tX31q19NDp0drnLEewOBQKA9AhETCAQCgUAgEAiMVATCCTFSv+wg1csKiAsvvLDenjHXXHMN0lsi20AgEBhMBM4444zkrBjbsgbzPZF3INCjCESxA4FAIBAIBAKBQGAQEQgnxCCCOxKz/s53vpMckrfSSivVZ06MxDpGnQKBkYzADTfckPysr8Nm41ydkfyle7VuUe5AIBAIBAKBQCAQGOkIDNgJYfZ7woQJaULQqMbAoXgMmGgHE0Z1O5gQcqBnvz9Z7kDbM888s2frEO1vwuB8u+jXgWu0gWgD0QaiDUQbiDYwBG1gwE6Io446Ku20005BgUG0gWgD0QaiDUQbmMltIMbX0C+iDUQbiDYQbSDaQLSB0dIGBuyE+MY3vtF3MrtT2INuCTxuCQyiH0QbiDbQ820gZHnI8mgD0QaiDUQbiDYQbSDawBC2gf8HAAD//3rugCIAAAAGSURBVAMAjjMcCptrRewAAAAASUVORK5CYII=\"\u003e\u003c/p\u003e\u0026nbsp;\n\u003c/div\u003e\n\u003cp\u003eModle 1:adjusted for sex, age, race, EDU, marital and PIR\u003c/p\u003e\n\u003cp\u003eModle 2:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake,PA and BMI\u003c/p\u003e\n\u003cp\u003eModle 3:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake, PA,BMI and Chronic comorbidities\u003c/p\u003e\n\u003cp\u003eAbbreviations:CI,confidence interwval;OR,odds ratios;BMI,body mass index;PIR,Family income;SUPP,Dietary supplements taken;EDU,Education level；PA,Physical activity\u003c/p\u003e\n\u003ch2\u003e3.4 \u0026nbsp; \u0026nbsp; Subgroup analyses\u003c/h2\u003e\n\u003cp\u003eStratified analyses with P-interaction tests were employed to evaluate the consistency of the association between dietary fiber intake and EP risk across different populations, determining the statistical significance of subgroup differences. Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates that dietary fiber intake is significantly inversely associated with EP risk across various subgroups, including sex, age, race, marital status, education, household income, smoking status, alcohol consumption, physical activity, BMI, dietary supplement use, and chronic comorbidities.Demographic characteristics include female sex (OR 0.53, 95% CI 0.31\u0026ndash;0.92), age groups 20 to \u0026lt;\u0026thinsp;40 years (OR 0.41, 95% CI 0.20\u0026ndash;0.83) and 40 to \u0026le;\u0026thinsp;65 years (OR 0.42, 95% CI 0.20\u0026ndash;0.87), and non-Hispanic white race (OR 0.33, 95% CI 0.14\u0026ndash;0.78).Socioeconomic factors: Nine to \u0026lt;\u0026thinsp;12 years of education (OR 0.34 [95% CI 0.14\u0026ndash;0.81]), living alone (OR 0.35 [95% CI 0.17\u0026ndash;0.70]); and high family income (OR 0.38 [95% CI 0.20\u0026ndash;0.72]).Behavior and health factors such as taking dietary supplements (OR 0.54, 95% CI 0.31\u0026ndash;0.94), alcohol consumption (OR 0.26, 95% CI 0.14\u0026ndash;0.48), engaging in vigorous physical activity (OR 0.34, 95% CI 0.22\u0026ndash;0.53), being overweight or obese (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m2, OR 0.46, 95% CI 0.25\u0026ndash;0.85; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and absence of chronic complications (OR 0.29, 95% CI 0.11\u0026ndash;0.81) were analyzed.After adjusting for confounding factors, the protective effect of dietary fibre remained significant (OR 0.45 [95% CI 0.27\u0026ndash;0.76]).However, among individuals\u0026thinsp;\u0026gt;\u0026thinsp;65 years of age, the OR was \u0026gt;\u0026thinsp;1 (1.74, 95% CI 0.75\u0026ndash;4.03), suggesting that there may be heterogeneity in this group, which may be explained by differences in physiological metabolism in the elderly population, the interference of comorbidities, or the small sample size.However, further studies are required to confirm these findings.The data appeared abnormal for education levels below 9 years, likely due to the small sample size in this group (n\u0026thinsp;=\u0026thinsp;6).Likelihood ratio tests revealed no statistically significant interactions among subgroups, indicating a consistent protective effect of dietary fiber across populations.\u003c/p\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Sensitivity analyses\u003c/h2\u003e\n \u003cp\u003eAfter excluding 152 individuals with extreme energy expenditure, the inverse association between dietary fibre and risk for EP remained stable.In the unadjusted model, the odds ratio (OR) for dietary fiber intake associated with the risk of EP was 0.41 (95% confidence interval [CI]: 0.27\u0026ndash;0.64; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).In adjusted model 1, the OR was 0.49 (95% CI 0.31\u0026ndash;0.79; P\u0026thinsp;=\u0026thinsp;0.004); in model 2, it was 0.42 (95% CI 0.24\u0026ndash;0.73; P\u0026thinsp;=\u0026thinsp;0.003); and in the fully adjusted model, it remained 0.42 (95% CI 0.24\u0026ndash;0.74; P\u0026thinsp;=\u0026thinsp;0.004) (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociation between Dietary Fiber intake and EP risk in participants with extreme energy consumption was not included.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003en.total\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003en.event_%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\n \u003cp\u003eln fiber\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eOR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e91(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.41(0.27\u0026ndash;0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eModle 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e91(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.49 (0.31\u0026thinsp;~\u0026thinsp;0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eModle 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e91(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.42(0.24\u0026thinsp;~\u0026thinsp;0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eModle 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e11676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e91(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.42 (0.24\u0026thinsp;~\u0026thinsp;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\n \u003cp\u003eModle 1:adjusted for sex, age, race, EDU, marital and PIR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\n \u003cp\u003eModle 2:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake,PA and BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\n \u003cp\u003eModle 3:adjusted for sex, age, race, EDU, marital, PIR, SUPP, smoke, alcohol intake, PA,BMI and Chronic comorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations:CI,confidence interwval;OR,odds ratios;BMI,body mass index;PIR,Family income;SUPP,Dietary supplements taken;EDU,Education level;PA,Physical activity\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe study identified a low dietary fiber intake among EP patients and an inverse relationship between fiber consumption and EP risk.Subgroup analysis identified dietary fiber as a significant protective factor for women, particularly those who are young to middle-aged, non-Hispanic white, possess a medium educational level, live alone, have a high family income, use dietary supplements, consume alcohol, engage in vigorous physical activity, are overweight or obese, and do not have chronic comorbidities.It was also a protective factor in other subgroups; however, there may have been heterogeneity in the subgroups of individuals\u0026thinsp;\u0026gt;\u0026thinsp;65 years of age.In addition, RCS analysis revealed an inverse relationship between dietary fibre intake and risk for EP, without a nonlinear association.\u003c/p\u003e \u003cp\u003eIn 2009, the Codex Alimentarius Commission defined dietary fiber as a carbohydrate polymer with ten or more monomer units that is not digested or absorbed in the human small intestine.Some oligosaccharides (such as fructo-oligosaccharide [FOS] and galacto-oligosaccharide [GOS], usually containing 3\u0026ndash;9 monomers) recognised to have physiological functions as dietary fibre are also included in the category of dietary fibre.Dietary fibre is not a single substance but a large group of compounds with diverse structures.The main components include the following: non-starch polysaccharides (cellulose, hemicellulose, pectin, gum, mucus, seaweed polysaccharides); resistant starches (oligosaccharides such as FOS, GOS, inulin, etc.); lignin, a non-carbohydrate; and some specific modified or synthetic substances (resistant dextrin, polyglucose, etc.).Dietary fibre can prolong food transport time, delay nutrient absorption, increase faecal volume, and slow the absorption of glucose, lipids, and cholesterol (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).Dietary fiber undergoes fermentation by intestinal bacteria to produce short-chain fatty acids (SCFA), which are vital for human metabolic processes (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs early as 1953, Hipsley (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) proposed that higher dietary fibre intake may reduce the risk for pregnancy toxaemia, also known as pre-eclampsia.A case-control study by Szałwińska et al.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) revealed that plant products were consumed much less frequently by patients with EP than by healthy individuals, and were the main source of dietary fibre.Zhang et al. conducted a cross-sectional study.Similar to the findings of this study, (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) observed that individuals with high dietary fiber intake had a lower risk of seizure events.However, the sample data obtained for this study was weighted to represent the entire U.S. population, which was more rigorous and broader than previous studies.A meta-analysis in The Lancet(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), encompassing 185 prospective studies and 58 clinical trials with 135\u0026nbsp;million participants, found that high dietary fiber intake significantly reduced all-cause and cardiovascular mortality, coronary heart disease, stroke incidence and mortality, type 2 diabetes, and colorectal cancer incidence by 15 to 30%, along with notable decreases in body weight, systolic blood pressure, and total cholesterol.Prior research indicates a correlation between EP and both metabolic syndrome and overweight conditions (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNevertheless, the mechanisms underlying the inverse association between dietary fibre and EP remain unclear, although neuroinflammation may be an underlying mechanism.Recent studies have suggested that inflammatory processes in the brain are key mechanisms in epileptogenesis (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).The relationship between neuroinflammation and EP is bidirectional\u0026mdash;it is not only the cause of EP but also the result of an abnormal immune status caused by seizures.Chronic inflammation involving tumour necrosis factor (TNF)-α or interleukin (IL)-6 can induce seizures(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), with TNF-α-driven astrocyte signaling enhancing hippocampal excitability in temporal lobe epilepsy(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).External factors that promote inflammation can initiate, sustain, or worsen neuroinflammation due to its regulation through multiple pathways (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).Short-chain fatty acids (SCFA), produced from dietary fiber fermentation by bacteria, play a crucial role in regulating immunity and inflammation (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).SCFA include acetate, propionate and butyrate (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).Butyrate can physically enhance intestinal barrier function and combine with G protein-coupled receptors to play an anti-inflammatory role (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).In one study, butyrate administration reduced IL-17 levels in test rats (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).Butyrate inhibits histone deacetylase (HDAC) to reduce the production of proinflammatory cytokines IL-6 and IL-12 in colonic macrophages within the lamina propria, and modulates nitric oxide production to regulate the antimicrobial activity of lipopolysaccharide-stimulated macrophages (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).In primary microglia and astrocyte cultures, acetate diminishes inflammatory signaling, leading to decreased IL-6 and TNF-α expression and interference with MAPK and NF-κB pathways (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).Therefore, we suggest that neuroinflammation may serve as a bridge between EP and dietary fibre.\u003c/p\u003e \u003cp\u003eIn contrast, oxidative stress may also be one of the mechanisms involved in EP.Oxidative stress is the imbalance between the production and elimination of reactive oxygen species (ROS) in the body (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).Excessive ROS can lead to neuronal damage, changes in synaptic plasticity, dysfunction of neural conduction, and increase the risk for seizures (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).Studies have shown that the excessive production of ROS in EP exceeds the capacity of endogenous antioxidants, leading to the accumulation of hydrogen peroxide (H2O2) and superoxide anions (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), which can damage cell function and alter the structure and activity of key enzymes such as Na+-K+-ATPase (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).ROS can also oxidise membrane lipids, destroy cell membrane permeability, and promote the generation of malondialdehyde and other harmful products (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).Myeloperoxidase (MPO) is a key inflammatory enzyme that catalyses the transformation of H2O2 and Cl\u0026ndash; and releases cytotoxic substances (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).These changes can result in excessive neuronal excitation and EP.Recent research indicates that SCFA can activate the Keap1-Nrf signaling pathway, a key regulator of REDOX homeostasis, to mitigate oxidative stress (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e).Propionate reduces MPO levels in the colon and serum of mice induced by dextran sulphate sodium, while increasing catalase and superoxide dismutase levels (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).Butyrate promotes epigenetic regulation by inhibiting HDAC and facilitating Nrf2 nuclear translocation, exhibiting antioxidant properties with therapeutic benefits in animal models of neurological diseases(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study faced certain limitations.The cross-sectional survey's inherent limitations prevent causal inference(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), necessitating further longitudinal studies.Second, as the database in this study focused solely on U.S. adults, further research with larger, more diverse global samples is necessary to validate our findings.Future studies should consider other potential confounding factors between dietary fiber and EP to validate the current findings.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eA comprehensive cross-sectional study of U.S. adults aged 20 and above found that higher dietary fiber intake was linked to a 55% decrease in EP risk per unit increase in ln-transformed fiber intake. However, this association varied among individuals older than 65.This may be explained differences in physiological metabolism in the elderly population, interference of comorbidities, or the small sample size and, as such, requires further research for verification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003e \u003cem\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest\u003c/em\u003e.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, L.Z.; methodology,L.Z.; software, L.Z.; validation, L.Z. ; formal analysis, L.Z. ; investigation, L.Z..; resources, L.Z.; data curation,L.Z..;writing\u0026mdash;original draft preparation,L.Z. ; writing\u0026mdash;review and editing, L.Z.; visualization, L.Z..; supervision, L.Z.; project administration, L.Z.; author have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe are grateful to Yang Shaojie, Director of the Department of Neurology, Chengdu Eighth People's Hospital, for his contributions in statistical support and consultation on study design.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003ePublicly available datasets are available online for this study. The repository/repositories name and accession numbers are available online at http://www.cdc.gov/ nchs/nhanes.htm (accessed on 20 March 2024).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThijs RD, Surges R, O'Brien TJ, Sander JW. Epilepsy in adults. Lancet. 2019;393:689\u0026ndash;701. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(18)32596-0\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(18)32596-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeard JL. Iron biology in immune function, muscle metabolism and neuronal functioning. J Nutr. 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(2020) 158:S65-65S71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.chest.2020.03.012\u003c/span\u003e\u003cspan address=\"10.1016/j.chest.2020.03.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Epilepsy, Dietary fiber, National Health and Nutrition Survey, NHANES, weighted data","lastPublishedDoi":"10.21203/rs.3.rs-9256805/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9256805/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEpilepsy is a chronic neurological disorder resulting from abnormal neuronal discharges in the brain.The pathogenesis is intricate and remains partially understood.Dietary fiber reduces postprandial blood glucose and lipid levels, enhancing metabolism and lowering the risk of cardiovascular disease, type 2 diabetes, and certain cancers, with metabolic factors also linked to epilepsy.This research investigated the link between dietary fiber intake and epilepsy risk among U.S. adults.\u003c/p\u003e \u003cp\u003eMethods: Logistic regression models were developed using data from the National Health and Nutrition Examination Survey (NHANES) in the United States, covering the period from 2013 to March 2020.The relationship between dietary fiber intake and epilepsy risk was examined.Restricted cubic spline regression (RCS) was used for linear testing to explore whether there was a quantitative relationship between score values and risk.Subgroup and interaction analyses were performed to evaluate the stability of the relationship between dietary fibre and risk for epilepsy in different subgroups.\u003c/p\u003e \u003cp\u003eResults: Data from 11,828 respondents, of whom 93 were diagnosed with epilepsy, were included in this study.In a fully adjusted multiple logistic regression model, dietary fiber, treated as a continuous variable, was inversely related to epilepsy risk (OR 0.45, 95% CI 0.27\u0026ndash;0.76; P\u0026thinsp;=\u0026thinsp;0.004).In a fully adjusted model, individuals with high dietary fiber intake had a reduced risk of epilepsy compared to those with low intake (OR 0.27, 95% CI 0.12\u0026ndash;0.61; P\u0026thinsp;=\u0026thinsp;0.003).In the RCS linear test, an inverse association was found between dietary fiber intake and epilepsy risk (nonlinearity, P\u0026thinsp;=\u0026thinsp;0.97).The stratified analyses showed consistent relationships with no significant interactions across subgroups.\u003c/p\u003e \u003cp\u003eConclusions: In a sample of U.S. adults, dietary fiber intake showed an inverse relationship with epilepsy risk, with each unit increase in the natural log-transformed dietary fiber intake correlating to a 55% reduction in epilepsy risk.\u003c/p\u003e","manuscriptTitle":"Association between dietary fiber intake and epilepsy risk: A cross- sectional analysis using weighted data from the National Health and Nutrition Examination Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-13 06:39:12","doi":"10.21203/rs.3.rs-9256805/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":"ba863804-fc5a-456d-b8b9-3bac10870da3","owner":[],"postedDate":"April 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T14:23:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-13 06:39:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9256805","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9256805","identity":"rs-9256805","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}