Validity of the running anaerobic sprint test for assessing anaerobic power and predicting short-distance performances

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil

The non-native invasive anuran Lithobates catesbeianus is presently distributed in Brazil, especially in the Atlantic Rainforest biodiversity hotspot. Here, we use a maximum entropy ecological niche modeling algorithm (i) to model the North American native geographic distribution of this species and (ii) to project that model onto the whole of Brazil. After applying a threshold value that balances commission and omission errors, the projection results suggested high probabilities of occurrence mostly in southern and southeastern Brazil. We also present the first report on the species known distribution in Brazil, showing good agreement with model predictions. If the predictive map is interpreted as depicting invasiveness potential of L. catesbeianus, strategies to prevent further invasion in Brazil should be focused especially in the Atlantic Rainforest biodiversity hotspot.

Predicting peptides structure with solvation potential and rotamer library dependent of the backbone

In this work, genetic algorithms concepts along with a rotamer library dependent of backbone and implicit solvation potential are used to study the tertiary structure of peptides. We starting from known primary sequence and optimize the structure of the backbone while the side chains allowed adopting the conformations present in a rotamer library. The GA, implemented with two force fields with a growing complexity, was used predict the structure of a polyalanine and a poly-isolueucine. This paper presents good and interesting results about the study of peptides structures and about the development of computational tools to study peptides structures. (C) 2007 Elsevier B.V. All rights reserved.

Expression pattern of claudins 1 and 3-an auxiliary tool in predicting behavior of mucoepidermoid carcinoma of salivary gland origin

Claudins (CLDNs) are a family of membrane proteins important for permeability of tight junctions. They have also been implicated in carcinogenesis and tumor progression. We analyzed patterns of distribution and intensity of expression of CLDNs 1, 3, 4, and 7 in mucoepidermoid carcinoma (MEC) of salivary gland in 39 patients. Correlations between the expression of CLDNs, tumor grade, and survival were explored. In immunohistochemical analysis, high expression of CLDN 1 was seen in low-grade MEC, and it appeared to be a suitable auxiliary marker of good prognosis. It classified MEC similarly to histological grading in 89.7% of cases (p=0.001). High CLDN 3 expression was seen in intermediate-and high-grade MEC, while it was low in low-grade MEC. CLDN 3 intensity correctly categorized tumors into grades in 71.8% of cases (p=0.017). However, in multivariate analysis CLDN 1 and CLDN 3 did not achieve significance over tumor grade in predicting patient behavior. We conclude that analysis of staining intensities of CLDN 1 and 3 is useful as an auxiliary diagnostic and prognostic tool in patients with salivary gland MEC.

Molecular physicochemical parameters predicting antioxidant activity of Brazilian natural products

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

Environmental factors predicting fish community structure in two neotropical rivers in Brazil

Com o objetivo de identificar os padrões de organização das comunidades de peixes dos rios Jogui e Iguatemi nós amostramos peixes através de redes de espera trimestralmente entre Novembro/1999 e Agosto/2000. Hypostomus ancistroides e Parauchenipterus galeatus foram as espécies de peixes mais abundantes nos rios Jogui e Iguatemi, respectivamente. A variação longitudinal foi mais importante que a sazonal na determinação da composição de espécies em ambos os rios e a diferença entre estações não foi significativa. A altitude foi o fator mais importante na determinação da distribuição das espécies.

Salting kinetics and salt diffusivities in farmed Pantanal caiman muscle

A criação de jacaré do Pantanal (Caiman crocodilus yacare) em cativeiro tem sido estimulada, e entre as técnicas de processamento de sua carne, a salga é um processo de conservação relativamente simples e de baixo custo. O objetivo deste trabalho foi estudar a cinética de difusão de cloreto de sódio em carne de jacaré do Pantanal criado em cativeiro, durante a salga úmida. Foram utilizados volumes limitados de salmoura e os experimentos foram realizados com relações salmoura/músculo de 3, 4 e 5, com concentrações de salmoura de 15%, 20% e 25% em peso e temperaturas de 10, 15 e 20ºC. A solução analítica da segunda lei de Fick, considerando difusão unidimensional em uma placa infinita em contato com uma solução bem agitada de volume limitado, foi utilizada para calcular os coeficientes de difusão efetivos de sal e estimar o conteúdo de cloreto de sódio nos filés. Obteve-se boa concordância entre o modelo analítico considerado e os dados experimentais. As difusividades do sal nos filés ocorreram na faixa de 0,47x10-10 a 9,62x10-10 m²/s.

Predicting the occurrence of alate aphids in Brassicaceae

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

EFFECT OF CR2O3 ON THE ELECTRICAL-PROPERTIES OF MULTICOMPONENT ZNO VARISTORS AT THE PREBREAKDOWN REGION

The effect of Cr2O3 on the electrical properties of the multicomponent ZnO varistors was investigated using voltage-current curves and impedance spectroscopy. The structure and morphological modifications were analysed by X-ray diffraction and scanning electron microscopy, respectively. It was observed in samples with addition 0.1 mol% Cr2O3 that there was an improvement in the electrical properties of the varistors, but the increase in concentration had a deleterious effect on the potential barrier at the grain boundary. The excess Cr2O3 segregates at the grain-boundary region and increases the donor concentration, leading to a higher leakage current.

Predicting structural models for silicon clusters

This article introduces an efficient method to generate structural models for medium-sized silicon clusters. Geometrical information obtained from previous investigations of small clusters is initially sorted and then introduced into our predictor algorithm in order to generate structural models for large clusters. The method predicts geometries whose binding energies are close (95%) to the corresponding value for the ground-state with very low computational cost. These predictions can be used as a very good initial guess for any global optimization algorithm. As a test case, information from clusters up to 14 atoms was used to predict good models for silicon clusters up to 20 atoms. We believe that the new algorithm may enhance the performance of most optimization methods whenever some previous information is available. (C) 2003 Wiley Periodicals, Inc.

Preliminary study of a methodology based on the degree-days concept for predicting the phenological phases of crops

This work develops a methodology (using the degree-days concept and linear regression), to forecast the duration of phenological phases in crops. An experiment was conducted in the greenhouse with three cultivars of cowpea (Vigna unguiculata (C.) Walp.), cv. California-781, Tvx 5058-09C and IT 81D-1032. The methodology was based on the relative thermal efficiency rate, determined for each species or cv. The results show that the proposed methodology may be a good alternative in works involving crops, especially because it does not require the repetition of the experiments.

Influence of La2O3, Pr2O3 and CeO2 on the nonlinear properties of SnO2 multicomponent varistors

The influence of La2O3, Pr2O3 and CeO2 on a new class of polycrystalline ceramics with nonlinear properties based on SnO2, was investigated. La2O3 and Pr2O3 were found to precipitate at the grain boundary region, causing a considerable increase in the nonlinear behavior. It was found that CeO2 forms a solid solution in the bulk but. unlike La2O3 and Pr2O3, it does not increase the nonlinear behavior. A higher nonlinear coefficient of similar to80 was obtained for La2O3-doped SnO2-based systems. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Predicting beef carcass retail products of Mediterranean buffaloes by real-time ultrasound measures

Twenty eight Mediterranean buffaloes bulls were scanned with real-time ultrasound (RTU), slaughtered, and fabricated into retail cuts to determine the potential for ultrasound measures to predict carcass retail yield. Ultrasound measures of fat thickness, ribeye area and rump fat thickness were recorded three to five days prior to slaughter. Carcass measurements were taken, and one side of each carcass was fabricated into retail cuts. Stepwise regression analysis was used to compare possible models for prediction of either kilograms or percent retail product from carcass mesaurements and ultrasound measures. Results indicate that possible prediction models for percent or kilograms of retail products using RTU measures were similar in their predictive power and accuracy when compared to models derived from carcass measurements. Both fat thickness and ribeye area were over-predicted when measured ultrasonically compared to measurements taken on the carcass in the cooler. The mean absolute differences for both traits are larger than the mean differences, indicating that some images were interpreted to be larger and some smaller than actual carcass measurements. Ultrasound measurements of REA and FT had positive correlations with carcass measures of the same traits (r=.96 for REA and r=.99 for FT). Standard errors of prediction currently are being used as the standard to certify ultrasound technicians for accuracy. Regression equations using live weight (LW), rib eye area (REAU) and subcutaneous fat thickness (FTU) between 12(th) and 13 (th) ribs and also over the biceps femoris muscle (FTP8) by ultrasound explained 95% of the variation in the hot carcass weight when measure immediately before slaughter.

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.