978 resultados para NIRS. Plum. Multivariate calibration. Variables selection


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The degradation of herbicides in aqueous solution by photo-Fenton process using ferrioxalate complex (FeOx) as source of Fe2+ was evaluated under blacklight irradiation. The commercial products of the herbicides tebuthiuron, diuron and 2,4-D were used. The multivariate analysis, more precisely, the response surface methodology was applied to evaluate the role of FeOx and hydrogen peroxide concentrations as variables in the degradation process, and in particular, to define the concentration ranges that result in the most efficient degradation of the herbicides. The degradation process was evaluated by the determination of the remaining total organic carbon content (TOC), by monitoring the decrease of the concentrations of the original compounds using HPLC and by the chloride ion release in the case of diuron and 2,4-D. Under optimized conditions, 20min were sufficient to mineralize 93% of TOC from 2,4-D and 90% of diuron, including oxalate. Complete dechlorination of these compounds was achieved after 10 min reaction. It was found that the most recalcitrant herbicide is tebuthiuron, while diuron shows the highest degradability. However, under optimized conditions the initial concentration of tebuthiuron was reduced to less than 15%, while diuron and 2,4-D were reduced to around 2% after only 1 min reaction. Furthermore, it was observed that the ferrioxalate complex plays a more important role than H2O2 in the photodegradation of these herbicides in the ranges of concentrations investigated. (C) 2004 Elsevier Ltd. All rights reserved.

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In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods of eliciting prior distributions for one unknown parameter have been proposed. However, there are relatively few methods for specifying a multivariate prior distribution and most are just applicable to specific classes of problems and/or based on restrictive conditions, such as independence of variables. Besides, many of these procedures require the elicitation of variances and correlations, and sometimes elicitation of hyperparameters which are difficult for experts to specify in practice. Garthwaite et al. (2005) discuss the different methods proposed in the literature and the difficulties of eliciting multivariate prior distributions. We describe a flexible method of eliciting multivariate prior distributions applicable to a wide class of practical problems. Our approach does not assume a parametric form for the unknown prior density f(.), instead we use nonparametric Bayesian inference, modelling f(.) by a Gaussian process prior distribution. The expert is then asked to specify certain summaries of his/her distribution, such as the mean, mode, marginal quantiles and a small number of joint probabilities. The analyst receives that information, treating it as a data set D with which to update his/her prior beliefs to obtain the posterior distribution for f(.). Theoretical properties of joint and marginal priors are derived and numerical illustrations to demonstrate our approach are given. (C) 2010 Elsevier B.V. All rights reserved.

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Thirty-two Polwarth sheep of ages up to 1 year were observed under temperatures varying from 10.5 to 46.5°C. The following blood cell counts were made: erythrocyte (RBC), leucocyte (WBC), eosinophil (EOS), neutrophil (NEU), lymphocyte (LYM) and monocyte (MON). Other traits measured were: haemoglobin (HB), haematocrit (HT), blood glucose (GLU) and serum protein (PROT). Multivariate analysis of variance was used and the results showed a significant (P<0.001) effect for the interaction of shearing and temperature treatment. Under temperatures >25°C, sheep presented a decrease of RBC, WBC, HB and HT, these differences being greater in the shorn than in the unshorn animals. Unshorn animals presented higher variations in EOS, NEU, LYM, MON and GLU. Blood glucose increased under high temperatures in the shorn animals (from 56.36±0.65 mg/100 ml to 60.52±0.69 mg/100 ml) as in the unshorn animals (from 54.72±0.74 mg/100 ml to 57.56±0.77 mg/100 ml). © 1992 International Society of Biometeorology.

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The original brachytic population 'Dent Single Cross Composite' (DSCC-br2br2) and a selection-derived sub-population with modified plant architecture (DSCC-br2br2-Lg3Lg3, selected for erect leaves), were evaluated for the following characteristics number of vascular bundles of greater and smaller size, total vascular tissue area (phloem and xylem), sustaining tissue area (vascular tissue plus sclerenchyma), phloem and sclerenchyma areas in apical, medial and basal portions from midclub and in apical and basal sheath regions (from second leaf above and first below ear insertion). These variables had different values for the five different sections studied in each leaf and these differences did not have the same pattern in the two DSCC populations (brachytic and with modified architecture). Selection for architectural modification caused some indirect foliar anatomical modifications. With the exception of the phloem and the vascular tissue areas in apical leaf and sheath base regions, the modified plant architecture population showed smaller values of sustaining tissue area, sclerenchyma area, vascular tissue area and number of smaller vascular bundles than the original one. In the ligule region the modified maize leaves had smaller vascular and sustaining tissue areas, reducing transportation area, which could reduce gram yield.

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A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

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The effect of combining the photocatalytic processes using TiO 2 and the photo-Fenton reaction with Fe3+ or ferrioxalate as a source of Fe2+ was investigated in the degradation of 4-chlorophenol (4CP) and dichloroacetic acid (DCA) using solar irradiation. Multivariate analysis was used to evaluate the role of three variables: iron, H2O2 and TiO2 concentrations. The results show that TiO2 plays a minor role when compared to iron and H2O2 in the solar degradation of 4CP and DCA in the studied conditions. However, its presence can improve TOC removal when H2O2 is totally consumed. Iron and peroxide play major roles, especially when Fe(NO3)3 used in the degradation of 4CP. No significant synergistic effect was observed by the addition of TiO 2 in this process. On the other hand, synergistic effects were observed between FeOx and TiO2 and between H 2O2 and TiO2 in the degradation of DCA. © IWA Publishing 2004.

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A calibration method was developed using flow injection analysis (FI) with a Gradient Calibration Method (GCM). The method allows the rapid determination of zinc In foods (approximately 30 min) after treatment with concentrated sulphuric acid and 30% hydrogen peroxide, and analysis with flame atomic absorption spectrometry (FAAS). The method provides analytical results with a relative standard deviation of about 2% and requires less time than by conventional FI calibration. The electronic selection of different segments along the gradient and monitoring of the technique covers wide concentration ranges while maintaining the inherent high precision of flow injection analysis. Concentrations, flow rates, and flow times of the reagents were optimized in order to obtain best accuracy and precision. Flow rates of 10 mL/min were selected for zinc. In addition, the system enables electronic dilution and calibration where a multipoint curve can be constructed using a single sample injection.

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The application of multi-wavelength holography for surface shape measurement is presented. In our holographic setup a Bi12TiO 20 (BTO) photorefractive crystal was the holographic recording medium and a multimode diode laser emitting in the red region was the light source in a two-wave mixing scheme. The holographic imaging with multimode lasers results in multiple holograms in the BTO. By employing such lasers the resulting holographic image appears covered of interference fringes corresponding to the object relief and the interferogram spatial frequency is proportional to the diode laser free spectral range (FSR). We used a Fabry-Perot étalon at the laser output for laser mode selection. Thus, larger effective values of the laser FSR were achieved, leading to higher-spatial frequency interferograms and therefore to more sensitive and accurate measurements. The quantitative evaluation of the interferograms was performed through the phase stepping technique (PST) and the phase map unwrapping was carried out through the Cellular-Automata method. For a given surface, shape measurements with different interferogram spatial frequencies were performed and compared, concerning measurement noise and visual inspection.

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In this article, we evaluate the performance of the T2 chart based on the principal components (PC chart) and the simultaneous univariate control charts based on the original variables (SU X̄ charts) or based on the principal components (SUPC charts). The main reason to consider the PC chart lies on the dimensionality reduction. However, depending on the disturbance and on the way the original variables are related, the chart is very slow in signaling, except when all variables are negatively correlated and the principal component is wisely selected. Comparing the SU X̄, the SUPC and the T 2 charts we conclude that the SU X̄ charts (SUPC charts) have a better overall performance when the variables are positively (negatively) correlated. We also develop the expression to obtain the power of two S 2 charts designed for monitoring the covariance matrix. These joint S2 charts are, in the majority of the cases, more efficient than the generalized variance |S| chart.

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Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

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Multivariate orthogonal polynomials associated with a Sobolev-type inner product, that is, an inner product defined by adding to a measure the evaluation of the gradients in a fixed point, are studied. Orthogonal polynomials and kernel functions associated with this new inner product can be explicitly expressed in terms of those corresponding with the original measure. We apply our results to the particular case of the classical orthogonal polynomials on the unit ball, and we obtain the asymptotics of the kernel functions. © 2011 Universidad de Jaén.

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Utilizando-se dados do campo de Camorim (Bacia de Sergipe-Alagoas), foi testado e aplicado um conjunto de técnicas estatísticas multivariantes (análises de agrupamentos, de componentes principais e discriminante) no intuito de identificar as fácies, previamente definidas em poços testemunhados, por meio dos perfis, viabilizando o reconhecimento das mesmas nos demais poços não testemunhados da área. A segunda etapa do processo de determinação das fácies consistiu no emprego de métodos auxiliares (análises composicional e de seqüência de fácies), que, combinados com as técnicas multivariantes, propiciaram melhores resultados na calibração rocha-perfil. A determinação das fácies, uma vez estabelecida, possibilitou o refinamento do processo de avaliação de formações ao viabilizar o exame de cada fácies-reservatório, isoladamente. Assim, esse procedimento tornou possível a escolha, para cada litologia, dos parâmetros utilizados na interpretação dos perfis ao mesmo tempo em que permitiu a totalização em separado dos valores de espessura, porosidade e saturação dos fluidos, bem como a adoção de diferentes valores de corte (cut-offs) para cada grupo considerado. Outras aplicações incluíram a melhoria na estimativa da porosidade e da permeabilidade, a adaptação de algoritmos para o cálculo preliminar de porosidade, a confecção de mapas de fácies e a geração automática de seções estratigráficas. Finalmente, foram destacadas a perspectiva de integração desse estudo com sistemas estatísticos de descrição de reservatórios, outras técnicas de determinação de fácies em desenvolvimento e a retomada da utilização de métodos estatísticos multivariantes em dados de perfis, como ferramenta de exploração.

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Physiological potential characterization of seed lots is usually performed by germination and vigor tests; however, the choice of a single test does not reflect such potential, once each test assesses seeds of differentiated mode. Multivariate techniques allow understanding structural dependence contained in each variable, as well as characterize groups of seed lots according to specific standards. The study aimed at evaluating variability among soybean seed lots and discriminate these lots by multivariate exploratory techniques as function of seed vigor. Experiment was performed with 20 soybean seed lots (10 lots cv. BRS Valiosa RR and 10 lots cv. M-SOY 7908 RR). Seed physiological potential was assessed by testing for: germination (standard, and under different water availability); vigor (accelerated aging and electrical conductivity); and field seedling emergence. Cluster analysis of seed lots, as well as Principal Component Analysis was performed using data obtained on all tests. Multivariate techniques allowed stratifying seed lots into two distinct groups. Principal Component Analysis showed that values obtained for variables: field seedling emergence, accelerated aging, and germination under different water availability were linked to BRS Valiosa RR; while to variables germination and electrical conductivity, were linked to M-SOY 7908 RR.

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)