5 resultados para Determinants of quits and dismissals and bivariate probit model

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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There is worldwide recognition that the burden of noncommunicable diseases (NCDs) and obesity-related health problems is rapidly increasing in low- and middle-income countries. Environmental determinants of obesity are likely to differ between countries, particularly in those undergoing rapid socioeconomic and nutrition transitions such as Brazil. This study aims to describe some built environment and local food environment variables and to explore their association with the overweight rate and diet and physical activity area-level aggregated indicators of adults living in the city of Sao Paulo, the largest city in Brazil. This formative study includes an ecological analysis of environmental factors associated with overweight across 31 submunicipalities of the city of Sao Paulo using statistical and spatial analyses. Average prevalence of overweight was 41.69% (95% confidence interval 38.74, 44.64), ranging from 27.14% to 60.75% across the submunicipalities. There was a wide geographical variation of both individual diet and physical activity, and indicators of food and built environments, favoring wealthier areas. After controlling for area socioeconomic status, there was a positive correlation between regular fruits and vegetables (FV) intake and density of FV specialized food markets (r = 0.497; p < 0.001), but no relationship between fast-food restaurant density and overweight prevalence was found. A negative association between overweight prevalence and density of parks and public sport facilities was seen (r = -0.527; p < 0.05). Understanding the relationship between local neighborhood environments and increasing rates of poor diet, physical activity, and obesity is essential in countries undergoing rapid economic and urban development, such as Brazil, in order to provide insights for policies to reduce increasing rates of NCDs and food access and health inequalities.

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Deforestation in Brazilian Amazonia accounts for a disproportionate global scale fraction of both carbon emissions from biomass burning and biodiversity erosion through habitat loss. Here we use field- and remote-sensing data to examine the effects of private landholding size on the amount and type of forest cover retained within economically active rural properties in an aging southern Amazonian deforestation frontier. Data on both upland and riparian forest cover from a survey of 300 rural properties indicated that 49.4% (SD = 29.0%) of the total forest cover was maintained as of 2007. and that property size is a key regional-scale determinant of patterns of deforestation and land-use change. Small properties (<= 150 ha) retained a lower proportion of forest (20.7%, SD = 17.6) than did large properties (>150 ha; 55.6%, SD = 27.2). Generalized linear models showed that property size had a positive effect on remaining areas of both upland and total forest cover. Using a Landsat time-series, the age of first clear-cutting that could be mapped within the boundaries of each property had a negative effect on the proportion of upland, riparian, and total forest cover retained. Based on these data, we show contrasts in land-use strategies between smallholders and largeholders, as well as differences in compliance with legal requirements in relation to minimum forest cover set-asides within private landholdings. This suggests that property size structure must be explicitly considered in landscape-scale conservation planning initiatives guiding agro-pastoral frontier expansion into remaining areas of tropical forest. (C) 2010 Elsevier Ltd. All rights reserved.

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The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

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We have examined the effect of the uncharged species of lidocaine (LDC) and etidocaine (EDC) on the acyl chain moiety of egg phosphatidylcholine liposomes. Changes in membrane organization caused by both anesthetics were detected through the use of EPR spin labels (5, 7 and 12 doxyl stearic acid methyl ester) or fluorescence probes (4, 6, 10, 16 pyrene-fatty acids). The disturbance caused by the LA was greater when the probes were inserted in more external positions of the acyl chain and decreased towards the hydrophobic core of the membrane. The results indicate a preferential insertion of LDC at the polar interface of the bilayer and in the first half of the acyl chain, for EDC. Additionally, 2 H NMR spectra of multilamellar liposomes composed by acyl chain-perdeutero DMPC and EPC (1:4 mol%) allowed the determination of the segmental order (S-mol) and dynamics (T-1) of the acyl chain region. In accordance to the fluorescence and EPR results, changes in molecular orientation and dynamics are more prominent if the LA preferential location is more superficial, as for LDC while EDC seems to organize the acyl chain region between carbons 2-8, which is indicative of its positioning. We propose that the preferential location of LDC and EDC inside the bilayers creates a ""transient site"", which is related to the anesthetic potency since it could modulate the access of these molecules to their binding site(s) in the voltage-gated sodium channel. (C) 2007 Elsevier B.V. All rights reserved.

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A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.