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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]

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]

It is of great importance to know the rain distribution in the region of Tangará da Serra (latitude 14°37′55″S, longitude 57°28′05″W and altitude 488 m), as it is an agricultural region, which makes such information essential for an adequate planning, maximization of agricultural potential and optimization of hydric resources. Thus, this work was aimed at evaluating the annual, monthly and ten-day pluviometric variability, and also quantifying the number of dry and rainy days and different levels of rain probability for the region. Pluviometric data provided by ′Agência Nacional de Águas′ (ANA) were used to analyze a period of 38 years (from January 1970 to December 2007). Precipitation behavior in Tangará da Serra has annual and monthly variations, constituting two well defined seasons - a dry one from May to September, and a rainy one from October to April. Annual variability during the analyzed period corresponds to the maximum value of 2,861, minimum of 1,404 and average of 1,830 mm, respectively. The incomplete gamma function adequately expresses precipitation probability in Tangará da Serra. Precipitation averages range from 40 to 50% probability for rainy months and from 30 to 40% for dry ones. According to the results, this type of research might help the elaboration and development of irrigation projects in this region. [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]