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In this study, the probability of occurrence of fumonisins in corn in the states of greatest production in Brazil was determined. The data were analyzed through quantitative risk analysis using the Monte Carlo simulation. The results indicated that there is a strong correlation between fumonisins contamination levels and the geographical region due to the influence of climatic characteristics, with temperature having the main influence. The Southern states presented higher risks of occurrence and concentration levels of fumonisins in corn due to the temperate climate with lower average temperature and higher relative humidity and precipitation indices. Cultivation in the best season indicates a significant reduction in the production of fumonisins when this period was evaluated, with average concentration levels up to 42% lower. The generated data are important for regulatory agencies and the agricultural sector, which needs to be aware that the chance of success in grain production depends on efficient planning of the growing season, mainly concerning the climatic conditions to which it is subject to minimize the risks. • Risk of fumonisins in corn was assessed using quantitative risk assessment; • Temperature plays a critical role in fumonisin incidence and level in corn; • Reduction in fumonisin of up to 42% when cultivation at the best time was assessed; • Strong correlation between fumonisins levels and the geographical region was found; • Low temperatures and high humidity increased the probability of fumonisin in corn. [ABSTRACT FROM AUTHOR]

Background. The authors assessed whether dentists' diagnostic inferences differ when test accuracy information is communicated using natural frequencies versus conditional probabilities. Methods. A parallel, randomized controlled trial with dentists was carried out in Rio de Janeiro, Brazil. The dentists received a question on the probability of a patient having interproximal caries, given a positive bite-wing radiograph. This question was asked using information that was formulated into either natural frequencies or conditional probabilities. Results. Only 14 (13.9%) of the dentists gave the correct answer; 13 in the natural frequencies group, and 1 in the conditional probabilities group (P < .001). There were 7 nearly correct answers in the natural frequencies group and none in the conditional probabilities group (P ¼ .005). Conclusions. Representing diagnostic test accuracy in natural frequencies substantially helped dentists make diagnostic inferences. Nearly twice as many dentists overestimated the presence of interproximal caries when given information in conditional probabilities. Practical Implications. Our study findings show information shared using natural frequencies may be more accurately interpreted by dentists than that based on conditional probabilities. Patients will probably receive different standards of care depending on the format in which dentists receive diagnostic test accuracy information. [ABSTRACT FROM AUTHOR]

The recorded historical series of precipitation are usually available for short periods of time and with many failures. The use of mathematical modeling to simulate rainfall is a tool used to circumvent this problem and to simulate the operation of water systems in different scenarios. The present study applies mathematical modeling to the hourly pluviometric precipitation data simulation. A pluviographical data set from October 1980 to December 2007 was used in the study. Precipitation data sets were obtained through daily pluviometric digitalization from the Meteorologic Station of Epagri at Urussanga, in southern Santa Catarina, Brazil (latitude 28° 31' S and longitude 48° 19' W). To simulate the hourly rain series, the stochastic model was modified based on the Bartlett-Lewis rectangular pulses model with six parameters. Those parameters were fitted by minimizing a function related to the analytical expressions that define the average, variance, and autocorrelation coefficient at lag 1 and the probability of a dry period related to the estimated values from the observed data. Ten series were simulated for 100 years of data. Data analyses and results showed that fitting Bartlett-Lewis model parameters makes it possible to simulate hourly rainfall while preserving precipitation statistical properties at several temporal aggregation levels. In general, the probability of dry periods tended to be overestimated. [ABSTRACT FROM AUTHOR]

Objective: To estimate the prevalence of depression and correlate clinical and demographic characteristics in pregnant women assisted by the public health system in the city of Pelotas, RS, Brazil. Method: We performed a cross-sectional study focused on pregnant women assisted by the public health service. The Edinburgh Postnatal Depression Scale (EPDS) was used to screen for depression. Results: In a sample of 1,264 pregnant women aged 12-46 years, 21.1% (n = 255) presented a depressive episode during pregnancy. The presence of depression was associated with older age, lower education, lack of a cohabiting partner, not being primiparous, planned pregnancy, abortion thoughts, psychological or psychiatric treatment, smoking and alcohol consumption during pregnancy, and stressful events. Conclusion: Pregnant women assisted by the Brazilian public health system presented a high prevalence of depression. Psychiatric history, lack of support, and stressful events increase the probability of antenatal depression. [ABSTRACT FROM AUTHOR]

Contingent valuation has become one of the dominant methods for valuing nonmarketed environmental goods, as well as for damage assessment due to natural hazards. In this study, the method is applied for evaluating the household willingness to pay for a flood control project in an impoverished periphery of Rio de Janeiro, Brazil. Theoretical validity is analyzed via a binary logistic regression, which describes the impact of sociodemographic, dwelling characteristics, and flood related variables on the willingness to pay for the project. Analysis of content validity indicates a series of characteristics—uncertainty, novelty, lack of well-differentiated values, institutional setting, and entitlement structure—which appear to drastically limit the use of contingent valuation for flood control projects in low income areas of developing countries. The study concludes that the method, in it’s current formulation, is not appropriate for use in policy decisions about flood control investments in areas described by a concentration of low income households in developing countries. [ABSTRACT FROM AUTHOR]