Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

Evapotranspiration and crop coefficients of melon plants measured by lysimeter and estimated according to FAO 56 methodology

Aiming at contributing to an adequate management of water resources, this study aimed to analyze and compare evapotranspiration (ETc) and crop coefficients (Kc) of melon plants measured by a lysimeter and estimated according to the FAO 56 methodology, in the city of Mossoró, state of Rio Grande do Norte (RN), Brazil. In order to measure ETc, weighing lysimeters with an area of 2.25m² were used, with two repetitions. The Penman-Monteith equation parameterized by FAO was used to estimate the reference evapotranspiration, and crop coefficients were those recommended in FAO-56 Bulletin adjusted to local climatic conditions. The required climatic data and lysimeter measurements were collected by an automatic weather station installed at the site. The results were compared by means of statistical indicators: of precision (r), of accuracy (d), and performance (c), in daily and weekly intervals. The data estimated by the FAO 56 methodology were adjusted optimally to the values measured by the lysimeters in accordance with index "c" in the two time scales assessed, indicating the potential of the method proposed by FAO to irrigation management in the climatic conditions of Agripole Assú-Mossoró.

Insights into the role of hydration in protein structure and stability obtained through hydrostatic pressure studies

A thorough understanding of protein structure and stability requires that we elucidate the molecular basis for the effects of both temperature and pressure on protein conformational transitions. While temperature effects are relatively well understood and the change in heat capacity upon unfolding has been reasonably well parameterized, the state of understanding of pressure effects is much less advanced. Ultimately, a quantitative parameterization of the volume changes (at the basis of pressure effects) accompanying protein conformational transitions will be required. The present report introduces a qualitative hypothesis based on available model compound data for the molecular basis of volume change upon protein unfolding and its dependence on temperature.