HIV/AIDS knowledge among men who have sex with men: applying the item response theory

OBJECTIVE To evaluate the level of HIV/AIDS knowledge among men who have sex with men in Brazil using the latent trait model estimated by Item Response Theory. METHODS Multicenter, cross-sectional study, carried out in ten Brazilian cities between 2008 and 2009. Adult men who have sex with men were recruited (n = 3,746) through Respondent Driven Sampling. HIV/AIDS knowledge was ascertained through ten statements by face-to-face interview and latent scores were obtained through two-parameter logistic modeling (difficulty and discrimination) using Item Response Theory. Differential item functioning was used to examine each item characteristic curve by age and schooling. RESULTS Overall, the HIV/AIDS knowledge scores using Item Response Theory did not exceed 6.0 (scale 0-10), with mean and median values of 5.0 (SD = 0.9) and 5.3, respectively, with 40.7% of the sample with knowledge levels below the average. Some beliefs still exist in this population regarding the transmission of the virus by insect bites, by using public restrooms, and by sharing utensils during meals. With regard to the difficulty and discrimination parameters, eight items were located below the mean of the scale and were considered very easy, and four items presented very low discrimination parameter (< 0.34). The absence of difficult items contributed to the inaccuracy of the measurement of knowledge among those with median level and above. CONCLUSIONS Item Response Theory analysis, which focuses on the individual properties of each item, allows measures to be obtained that do not vary or depend on the questionnaire, which provides better ascertainment and accuracy of knowledge scores. Valid and reliable scales are essential for monitoring HIV/AIDS knowledge among the men who have sex with men population over time and in different geographic regions, and this psychometric model brings this advantage.

Cálculo ab initio de intensidades Raman dinâmicas utilizando a teoria da resposta linear

In this paper a methodology for the computation of Raman scattering cross-sections and depolarization ratios within the Placzek Polarizability Theory is described. The polarizability gradients are derived from the values of the dynamic polarizabilities computed at the excitation frequencies using ab initio Linear Response Theory. A sample application of the computational program, at the HF, MP2 and CCSD levels of theory, is presented for H2O and NH3. The results show that high correlated levels of theory are needed to achieve good agreement with experimental data.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Synecological comparisons sustained by ecophysiological fingerprinting of intrinsic photosynthetic capacity of plants as assessed by measurements of light response curves

In some literature variations in photosynthetic rates are considered to be of little relevance for individual fitness. This depends among other things on how one defines fitness, i.e. if one takes strictly Darwinian fitness as seed production or if one needs to evaluate particular traits and consider plant establishment. It also matters if one takes the Darwinian "organism individual" as the central entity in evolution ("individual fitness") or the "species individual" in a modified "Structure of Evolutionary Theory" sensu Stephen Jay Gould. A phenotypically expressed trait like photosynthetic rate, even if intra- and interspecific differences may be small, can matter in habitat performance and niche acquisition. Light dependence curves (LCs) of photosynthetic rates are now readily measured under field conditions using miniaturized equipment of pulse amplitude modulated fluorometers. In contrast to actual momentary measurements of quantum yield of photosynthesis under actually prevailing ambient conditions, LC measurements reflect the expressed intrinsic capacity of photosynthesis. In this review we explore the power of LC measurements yielding cardinal points such as maximum apparent electron transport rate of photosystem II (ETRmax) and saturating photosynthetically active radiation (PARsat) in making intra- and interspecific comparisons of plant performance and synecological fingerprinting in ecophysiological studies across species, sites, habitats and ecosystems.