Implementação de um método robusto para o controle fiscal de umidade em queijo minas artesanal. Abordagem metrológica multivariada

This study developed and validated a method for moisture determination in artisanal Minas cheese, using near-infrared spectroscopy and partial-least-squares. The model robustness was assured by broad sample diversity, real conditions of routine analysis, variable selection, outlier detection and analytical validation. The model was built from 28.5-55.5% w/w, with a root-mean-square-error-of-prediction of 1.6%. After its adoption, the method stability was confirmed over a period of two years through the development of a control chart. Besides this specific method, the present study sought to provide an example multivariate metrological methodology with potential for application in several areas, including new aspects, such as more stringent evaluation of the linearity of multivariate methods.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Pedotransfer functions related to spatial variability of water retention attributes for lowland soils

The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.

Analysis of experiments in square lattice with emphasis on variance components. i. Individual analysis

This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

CO2-response function of radiation use efficiency in rice for climate change scenarios

The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

Comparação entre métodos compostos no cálculo de afinidades por próton e elétron em sistemas moleculares

The CBS-4M, CBS-QB3, G2, G2(MP2), G3 and G3(MP2) model chemistry methods have been used to calculate proton and electron affinities for a set of molecular and atomic systems. Agreement with the experimental value for these electronic properties is quite good considering the uncertainty in the experimental data. A comparison among the six theories using statistical analysis (average value, standard deviation and root-mean-square) showed a better performance of CBS-QB3 to obtain these properties.

Aplicação de técnicas multivariadas e inteligência artificial na análise de espectros de infravermelho para determinação de matéria orgânica em amostras de solos

In this paper studies based on Multilayer Perception Artificial Neural Network and Least Square Support Vector Machine (LS-SVM) techniques are applied to determine of the concentration of Soil Organic Matter (SOM). Performances of the techniques are compared. SOM concentrations and spectral data from Mid-Infrared are used as input parameters for both techniques. Multivariate regressions were performed for a set of 1117 spectra of soil samples, with concentrations ranging from 2 to 400 g kg-1. The LS-SVM resulted in a Root Mean Square Error of Prediction of 3.26 g kg-1 that is comparable to the deviation of the Walkley-Black method (2.80 g kg-1).

REDUÇÃO DE VARIÁVEIS DE ENTRADA DE REDES NEURAIS ARTIFICIAIS A PARTIR DE DADOS DE ANÁLISE DE COMPONENTES PRINCIPAIS NA MODELAGEM DE OXIGÊNIO DISSOLVIDO

The objective of this work is to demonstrate the efficient utilization of the Principal Components Analysis (PCA) as a method to pre-process the original multivariate data, that is rewrite in a new matrix with principal components sorted by it's accumulated variance. The Artificial Neural Network (ANN) with backpropagation algorithm is trained, using this pre-processed data set derived from the PCA method, representing 90.02% of accumulated variance of the original data, as input. The training goal is modeling Dissolved Oxygen using information of other physical and chemical parameters. The water samples used in the experiments are gathered from the Paraíba do Sul River in São Paulo State, Brazil. The smallest Mean Square Errors (MSE) is used to compare the results of the different architectures and choose the best. The utilization of this method allowed the reduction of more than 20% of the input data, which contributed directly for the shorting time and computational effort in the ANN training.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional least-square method (LS). Among these the most important are: there are no restrictions on linearity or in the form which the parameters appears in the mathematical model describing the system, and it is not required that these parameters be time invariant. The EKF uses the statistical properties of the process and the observation noise, to produce estimates based on the mean square error of the estimates themselves. Differently, the LS minimizes a cost function based on the plant output behavior. Results for the estimation of some longitudinal aerodynamic derivatives from simulated data are presented.

Heart rate variability under resting conditions in postmenopausal and young women

The aim of the present study was to compare the modulation of heart rate in a group of postmenopausal women to that of a group of young women under resting conditions on the basis of R-R interval variability. Ten healthy postmenopausal women (mean ± SD, 58.3 ± 6.8 years) and 10 healthy young women (mean ± SD, 21.6 ± 0.82 years) were submitted to a control resting electrocardiogram (ECG) in the supine and sitting positions over a period of 6 min. The ECG was obtained from a one-channel heart monitor at the CM5 lead and processed and stored using an analog to digital converter connected to a microcomputer. R-R intervals were calculated on a beat-to-beat basis from the ECG recording in real time using a signal-processing software. Heart rate variability (HRV) was expressed as standard deviation (RMSM) and mean square root (RMSSD). In the supine position, the postmenopausal group showed significantly lower (P<0.05) median values of RMSM (34.9) and RMSSD (22.32) than the young group (RMSM: 62.11 and RMSSD: 49.1). The same occurred in the sitting position (RMSM: 33.0 and RMSSD: 18.9 compared to RMSM: 57.6 and RMSSD: 42.8 for the young group). These results indicate a decrease in parasympathetic modulation in postmenopausal women compared to young women which was possibly due both to the influence of age and hormonal factors. Thus, time domain HRV proved to be a noninvasive and sensitive method for the identification of changes in autonomic modulation of the sinus node in postmenopausal women.

Drying kinetics of potato pulp waste

Potato pulp waste (PPW) drying was investigated under different experimental conditions (temperatures from 50 to 70 °C and air flow from 0.06 to 0.092 m³ m- 2 s- 1) as a possible way to recover the waste generated by potato chip industries and to select the best-fit model to the experimental results of PPW drying. As a criterion to evaluate the fitting of mathematical models, a method based on the sum of the scores assigned to the four evaluated statistical parameters was used: regression coefficient (R²), relative mean error P (%), root mean square error (RMSE), and reduced chi-square (χ²). The results revealed that temperature and air velocity are important parameters to reduce PPW drying time. The models Midilli and Diffusion had the lowest sum values, i.e., with the best fit to the drying data, satisfactorily representing the drying kinetics of PPW.

Validação da versão brasileira do "Cuestionario para la Evaluación del Síndrome de Quemarse por el Trabajo" em professores

OBJETIVO: Avaliar a validade fatorial e de construto da versão brasileira do "Cuestionario para la Evaluación del Síndrome de Quemarse por el Trabajo" (CESQT). MÉTODOS: O processo de versão do questionário original do espanhol para o português incluiu as etapas de tradução, retrotradução e equivalência semântica. Foi realizada análise fatorial confirmatória e utilizados modelos de equações estruturais de quatro fatores, similar ao da estrutura original do CESQT. A amostra foi constituida de 714 professores que trabalhavam em instituições de ensino da cidade de Porto Alegre, RS, e região metropolitana 2008. O questionário possui 20 itens distribuídos em quatro subescalas: Ilusão pelo trabalho (5 itens), Desgaste psíquico (4 itens), Indolência (6 itens) e Culpa (5 itens). O modelo foi analisado com base no programa LISREL 8. RESULTADOS: As medidas de ajuste indicaram adequação do modelo hipotetizado: χ2(164) = 605,86 (p < 0,000), Goodness Fit Index = 0,92, Adjusted Goodness Fit Index = 0,90, Root Mean Square Error of Approximation = 0,062, Non-Normed Fit Index = 0,91, Comparative Fit Index = 0,92, Parsimony Normed Fit Index = 0,77. O valor de alfa de Cronbach para todas as subescalas foi maior que 0,70. CONCLUSÕES: Os resultados indicam que o CESQT possui validade fatorial e consistência interna adequada para avaliar burnout em professores brasileiros.

Adaptação transcultural Portugal-Brasil do Inventário de Burnout de Maslach para estudantes

OBJETIVO: Realizar a adaptação transcultural da versão em português do Inventário de Burnout de Maslach para estudantes e investigar sua confiabilidade, validade e invariância transcultural. MÉTODOS: A validação de face envolveu participação de equipe multidisciplinar. Foi realizada validação de conteúdo. A versão em português foi preenchida em 2009, pela internet, por 958 estudantes universitários brasileiros e 556 portugueses da zona urbana. Realizou-se análise fatorial confirmatória utilizando-se como índices de ajustamento o χ²/df, o comparative fit index (CFI), goodness of fit index (GFI) e o root mean square error of approximation (RMSEA). Para verificação da estabilidade da solução fatorial conforme a versão original em inglês, realizou-se validação cruzada em 2/3 da amostra total e replicada no 1/3 restante. A validade convergente foi estimada pela variância extraída média e confiabilidade composta. Avaliou-se a validade discriminante e a consistência interna foi estimada pelo coeficiente alfa de Cronbach. A validade concorrente foi estimada por análise correlacional da versão em português e dos escores médios do Inventário de Burnout de Copenhague; a divergente foi comparada à Escala de Depressão de Beck. Foi avaliada a invariância do modelo entre a amostra brasileira e a portuguesa. RESULTADOS: O modelo trifatorial de Exaustão, Descrença e Eficácia apresentou ajustamento adequado (χ²/df = 8,498; CFI = 0,916; GFI = 0,902; RMSEA = 0,086). A estrutura fatorial foi estável (λ: χ²dif = 11,383, p = 0,50; Cov: χ²dif = 6,479, p = 0,372; Resíduos: χ²dif = 21,514, p = 0,121). Observou-se adequada validade convergente (VEM = 0,45;0,64, CC = 0,82;0,88), discriminante (ρ² = 0,06;0,33) e consistência interna (α = 0,83;0,88). A validade concorrente da versão em português com o Inventário de Copenhague foi adequada (r = 0,21;0,74). A avaliação da validade divergente do instrumento foi prejudicada pela aproximação do conceito teórico das dimensões Exaustão e Descrença da versão em português com a Escala de Beck. Não se observou invariância do instrumento entre as amostras brasileiras e portuguesas (λ:χ²dif = 84,768, p < 0,001; Cov: χ²dif = 129,206, p < 0,001; Resíduos: χ²dif = 518,760, p < 0,001). CONCLUSÕES: A versão em português do Inventário de Burnout de Maslach para estudantes apresentou adequada confiabilidade e validade, mas sua estrutura fatorial não foi invariante entre os países, apontando ausência de estabilidade transcultural.

Preocupação com a forma do corpo de graduandos de Farmácia-Bioquímica

Objetivo Identificar a preocupação com a forma do corpo de estudantes de Farmácia-Bioquímica e sua relação com variáveis sociais e laborais e com o estado nutricional. Métodos Participaram 346 discentes com média de idade de 20,2 (DP = 2,4) anos, sendo 278 (80,3%) do sexo feminino. Utilizou-se o Body Shape Questionnaire (BSQ). As validades fatorial e convergente e a consistência interna (α) do BSQ foram estimadas. Utilizaram-se como índices de ajustamento o qui-quadrado pelos graus de liberdade (χ2/gl), o Comparative Fit Index (CFI), o Normed Fit Index (NFI) e o Root Mean Square Error of Approximation (RMSEA). O escore médio de preocupação com a forma do corpo foi obtido por meio de algoritmo gerado na análise fatorial confirmatória. Para comparar os escores médios segundo as variáveis de interesse, utilizou-se Análise de Variância (ANOVA). Resultados O BSQ apresentou, para a amostra de estudo, adequada validade (χ2/gl = 3,29; CFI = 0,87, NFI = 0,82, RMSEA = 0,08) e confiabilidade (α = 0,97) após ajustamento. Verificou-se que as mulheres (p < 0,001) apresentaram maior preocupação com a forma do corpo que os homens. Além disso, os estudantes que avaliaram o curso como pior que as expectativas iniciais (p = 0,048), que consomem medicamentos por causa dos estudos (p < 0,001), que já pensaram em desistir do curso (p = 0,002) e foram classificados com sobrepeso/obesidade (p < 0,001) também apresentaram alta preocupação com a forma do corpo. Conclusão As varáveis sexo, avaliação em relação ao curso, ingestão de medicamentos por causa dos estudos, pensamento em desistir do curso e o estado nutricional apresentaram relação significativa com a preocupação com a forma do corpo entre os estudantes.