Geographic range, habitats, and host plants of bromeliad-living jumping spiders (Salticidae)

Although spiders are a very diverse group on vegetation, their associations with plants are poorly known. Some salticid species specifically use Bromeliaceae as host plants in some regions of South America. In this study, I report the geographic range of these spider-bromeliad associations, and whether the spiders inhabit particular bromeliad species and vegetation types, as well as open areas or interior of forests. Nine salticid species were found to be associated with up to 23 bromeliad species in cerrados (savanna-like vegetation), semideciduous and seasonal forests, coastal sand dune vegetation, restingas, inselbergs, highland forests, chacos, and rain forests at 47 localities in Brazil, Paraguay, Bolivia, and Argentina. Some species were typically specialists, inhabiting almost exclusively one bromeliad species over a large geographic range (e.g., Psecas chapoda on Bromelia balansae), whereas others were generalists, occurring on up to 7-8 bromeliad species (e.g., Psecas sp., Eustiromastix nativo, and Coryphasia sp. 1). The regional availability of bromeliad species among habitats may explain this pattern of host plant use. More jumping spiders were found on bromeliads in open areas than on bromeliads in the interior of forests. These results show that several jumping spider species may be strictly associated with the Bromeliaceae in the Neotropics. This is one of the few studies to show host-specific associations for spiders on a particular plant type over a wide geographic range.

A partial least squares regression study with antioxidant flavonoid compounds

The quantitative structure-activity relationship of a set of 19 flavonoid compounds presenting antioxidant activity was studied by means of PLS (Partial Least Squares) regression. The optimization of the structures and calculation of electronic properties were done by using the semiempirical method AMI. A reliable model (r(2) = 0.806 and q(2) = 0.730) was obtained and from this model it was possible to consider some aspects of the structure of the flavonoid compounds studied that are related with their free radical scavenging ability. The quality of the PLS model obtained in this work indicates that it can be used in order to design new flavonoid compounds that present ability to scavenge free radicals.

GEOGRAPHIC-VARIATION IN APIS-CERANA-INDICA F - A SPATIAL AUTOCORRELATION ANALYSIS OF MORPHOMETRIC PATTERNS

Spatial patterns of morphometric variation in Apis cerana indica were analysed. Factor and spatial autocorrelation analyses were applied to 29 characters, measured in 17 populations in India. Correlograms showed that 15 characters are patterned geographically, and 13 of them are related to overall size. These characters are distributed as a north-south cline, probably reflecting adaptations to environmental conditions. However, the great number of characteristics without geographical pattern suggests that part of the morphometric variability is due to local stochastic divergences.

Embedded crack elements with non-uniform discontinuity modes

The consequences of the use of embedded crack finite elements with uniform discontinuity modes (opening and sliding) to simulate crack propagation in concrete are investigated. It is shown the circumstances in which the consideration of uniform discontinuity modes is not suitable to accurately model the kinematics induced by the crack and must be avoided. It is also proposed a technique to embed cracks with non-uniform discontinuity modes into standard displacement-based finite elements to overcome the shortcomings of the uniform discontinuity modes approach.

The Geometric Birnbaum-Saunders regression model with cure rate

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

Geographic distribution and morphological variation in Mimon bennettii (Chiroptera, Phyllostomidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)