Chemometrics in fuel science: demonstration of the feasibility of chemometrics analyses applied to physicochemical parameters to screen solvent tracers in Brazilian commercial gasoline

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

(1)H NMR Fingerprinting of Brazilian Commercial Gasoline: Pattern-Recognition Analyses for Origin Authentication Purposes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle

Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Predicción de ecuaciones para el porcentaje de grasa a partir de circunferencias corporales en niños pre-púberes

Introduction: The analysis of body composition through direct and indirect methods allows the study of the various components of the human body, becoming the central hub for assessing nutritional status. Objective: The objective of the study was to develop equations for predicting body fat% from circumferential body arm, waist and calf and propose percentiles to diagnose the nutritional status of school children of both sexes aged 4-10 years. Methods: We selected intentionally (non-probabilistic) 515 children, 261 children and 254 being girls belonging to Program interaction and development of children and adolescents from the State University of Campinas (Sao Paulo, Brazil). Anthropometric variables were evaluated for weight, height, triceps and subscapular skinfolds and body circumferences of arm, waist and calf, and the% fat determined by the equation proposed by Boileau, Lohman and Slaughter (1985). Through regression method 2 were generated equations to predict the percentage of fat from the body circumferences, the equations 1 and 2 were validated by cross validation method. Results: The equations showed high predictive values ranging with a R2 = 64-69%. In cross validation between the criterion and the regression equation proposed no significant difference (p > 0.05) and there was a high level of agreement to a 95% CI. Conclusion: It is concluded that the proposals are validated and shown as an alternative to assess the percentage of fat in school children of both sexes aged 4-10 years in the region of Campinas, SP (Brazil).

Development and application of an electronic tongue for detection and monitoring of nitrate, nitrite and ammonium levels in waters

This work presents the first study and development of an electronic tongue analysis system for the monitoring of nitrogen stable species: nitrate, nitrite and ammonium in water. The electronic tongue was composed of an array of 15 potentiometric poly(vinyl chloride) membrane sensors sensitive to cations and anions plus an artificial neural network (ANN) response model. The building of the ANN model was performed in a medium containing sodium, potassium, and chloride as interfering ions, thus simulating real environmental samples. The correlation coefficient in the cross-validation of nitrate, nitrite and ammonium was satisfactory in the three cases with values higher than 0.92. Finally, the utility of the proposed system is shown in the monitoring of the photoelectrocatalytic treatment of nitrate. © 2013 Elsevier B.V.

Método dos mínimos quadrados com penalidades: aplicação no posicionamento relativo GPS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribuição espacial da produtividade média anual das culturas de arroz, feijão, milho e café no Estado de São Paulo e sua correlação com índices climáticos

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Investigando a influência das crenças de alunos do Curso de Letras da Universidade Federal do Pará sobre sua prontidão para a aprendizagem autônoma do inglês: um estudo de caso

Objetiva investigar como as crenças sobre o ensino e aprendizagem de inglês de quatro alunas do curso de Letras da UFPA influenciam, positiva ou negativamente, sua prontidão para a aprendizagem autônoma. Os princípios desta pesquisa são qualitativos com a utilização de narrativas, questionário e entrevista para coleta e posterior triangulação de dados. Ao analisar as crenças e sua relação com a aprendizagem autônoma, constatamos que professores e alunos podem construir um novo entendimento do processo de ensino e aprendizagem, assim como podem compreender melhor o papel que desempenham nele. Essa conscientização é um dos importantes fundamentos da autonomia.

Agricultura de precisão por metodologia geoestatística: aplicação em solo do Estado de Rondônia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise genética de resistência ao Rhipicephalus (Boophilus) microplus em bovinos cruzados Hereford x Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Erodibilidade de latossolos predita pela suscetibilidade magnética e espectroscopia de reflectância difusa

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.