Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Assemblage of immature Odonata (Insecta, Anisoptera) in streams of the Mato Grosso do Sul State: spatial implications

ABSTRACT This study investigated the assemblages attributes (composition, abundance, richness, diversity and evenness) and the most representative genera of Odonata, Anisoptera at Água Boa and Perobão Streams, Iguatemi River basin, Brazil. Both are first order streams with similar length that are impacted by riparian forest removal and silting. Quarterly samplings were conducted from March to December 2008 in the upper, intermediate and lower stretch of each stream. The Mantel test was used to check the influence of spatial autocorrelation on the Odonata composition. Spatial variations in the composition were summarized by the Principal Coordinates Analysis (PCoA) using Mantel test residuals. The effects of spatial correlation on richness and abundance were investigated by the spatial correlogram of Moranʼs I coefficients. The most representative genera in each stream were identified by the Indicator Value Method. The spatial variations in the attributes of the assemblages were assessed using analysis of variance of null models. We collected 500 immature individuals of 23 genera and three families. Among the attributes analyzed only the composition and abundance showed significant spatial differences, with the highest mean abundance found in the Perobão Stream. Miathyria and Zenithoptera were the indicator genera of the Água Boa Stream and Erythrodiplax, Libellula, Macrothemis, Progomphus and Tramea were the indicator genera of the Perobão Stream.

Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Quimiometria I: calibração multivariada, um tutorial

The aim of this work is to present a tutorial on Multivariate Calibration, a tool which is nowadays necessary in basically most laboratories but very often misused. The basic concepts of preprocessing, principal component analysis (PCA), principal component regression (PCR) and partial least squares (PLS) are given. The two basic steps on any calibration procedure: model building and validation are fully discussed. The concepts of cross validation (to determine the number of factors to be used in the model), leverage and studentized residuals (to detect outliers) for the validation step are given. The whole calibration procedure is illustrated using spectra recorded for ternary mixtures of 2,4,6 trinitrophenolate, 2,4 dinitrophenolate and 2,5 dinitrophenolate followed by the concentration prediction of these three chemical species during a diffusion experiment through a hydrophobic liquid membrane. MATLAB software is used for numerical calculations. Most of the commands for the analysis are provided in order to allow a non-specialist to follow step by step the analysis.

Uma abordagem robusta de cálculo aplicada a um sistema potenciométrico de medida de concentrações hidrogeniônicas em soluções aquosas

The data analyzed in this work were generated following the methodology developed by Molina et al.(J. Electroanal. Chem., 1979) for the calibration of a potentiometric system of measurement of hydrogen-ion concentrations resulting from neutralizations, at 25 ºC, of acidic or alkaline solutions at constant ionic strength (0.1 mol.l-1) held with NaClO4. The observed data present a serious deviation in relation to the mathematical model derived from the Nernst equation, for pH values ranging from 3 to 11, where pH=-log[H+]. We show that the minimization of the sum of the absolute values of the residuals gives estimates that are not influenced by outlying values.

Comparação de duas metodologias de amostragem atmosférica com ferramenta estatística não paramétrica

In atmospheric aerosol sampling, it is inevitable that the air that carries particles is in motion, as a result of both externally driven wind and the sucking action of the sampler itself. High or low air flow sampling speeds may lead to significant particle size bias. The objective of this work is the validation of measurements enabling the comparison of species concentration from both air flow sampling techniques. The presence of several outliers and increase of residuals with concentration becomes obvious, requiring non-parametric methods, recommended for the handling of data which may not be normally distributed. This way, conversion factors are obtained for each of the various species under study using Kendall regression.

QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.

Progress of Asian soybean rust and airborne urediniospores of Phakopsora pachyrhizi in southern Brazil

Asian soybean rust, caused by the fungus Phakopsora pachyrhizi, was reported at epidemic levels in 2003/2004 and is the main soybean disease in Brazil. The aim of this study was to investigate the spread of Asian soybean rust and to quantify airborne urediniospores in the region of Campo Mourão, Paraná State, Brazil. Three experiments were conducted under field conditions during the 2007/08 and 2008/09 crop seasons. Using the disease gradient method, provided by the application of increasing levels of the fungicide tebuconazole, four Asian soybean rust epidemics at different intensities were obtained in each experiment. To quantify the urediniospores, weathercock-type spore collectors were installed during and between the two crop seasons. Disease progress curves were plotted for each epidemic, and maximum severity was estimated. The curves were fit to the logistic model, which provided higher coefficients of determination and more randomly distributed residuals plotted over time. Analyses of the area under the disease progress curve showed that the largest epidemics occurred in the 2007/2008 crop season and that the progress rates were higher for severity, even among plants protected with the fungicide. The number of urediniospores collected in the air was related to the presence of soybean plants in the cultivated crops. The quantity of urediniospores was also positively correlated to the disease severity and incidence, as well as to cumulative rainfall and favorable days for P. Pachyrhizi infection.

Mathematical models to describe the volumetric shrinkage rate of red beans during drying

The present study aimed to determine the volumetric shrinkage rate of bean (Phaseolus vulgaris L.) seeds during air-drying under different conditions of air, temperature and relative humidity, and to adjust several mathematical models to the empiric values observed, and select the one that best represents the phenomenon. Six mathematical models were adjusted to the experimental values to represent the phenomenon. It was determined the degree of adjustment of each model from the value of the coefficient of determination, the behavior of the distribution of the residuals, and the magnitude of the average relative and estimated errors. The rate of volumetric shrinkage that occurred in bean seeds during drying is between 25 and 37%. It basically depends on the final moisture content, regardless of the air conditions during drying. The Modified Bala & Woods' model best represented the process.

Application of cutting fluids in machining processes

In the last decade a lot has been discussed about the suitability of using cutting fluid in abundance to cool and lubricate machining processes. The use of cutting fluid generally causes economy of tools and it becomes easier to keep tight tolerances and to maintain workpiece surface properties without damages. In the other hand, it brings also some problems, like fluid residuals and human diseases. Because of them some alternatives has been sought to minimise or even avoid the use of cutting fluid in machining operations. Some of these alternatives are dry cutting and cutting with minimum quantity of fluid (MQF). The main goal of this work is to discuss these tendencies. Therefore, topics like kinds and methods of applications of modern cutting fluids and what are new in this area will unavoidably be considered. MQF and dry cutting techniques, their applications and where it is not possible to apply them will also be focused. To exemplify the topics, this work will describe some of the researches been developed in two important Brazilian Universities: State University of Campinas (UNICAMP) and Federal University of Uberlândia (UFU).

Potential of plant species for bioremediation of soils applied with imidazolinone herbicides

Imidazolinone herbicides present physicochemical characteristics that allow them to persist longer in environment, with increased chances of soil and water contamination, as well as carryover effects on subsequent crops. Phytoremediation is shown as a promising technique to decontaminate soils polluted by herbicides. The aim of this study was to assess the potential of some winter grown species in removing residuals from soils contaminated with imazethapyr + imazapic and imazapic + imazapyr, using pre-emergence to control weeds in summer grown rice fields. The experiment was conducted in a completely randomized design, with four replications. All species were subjected to herbicide application at different doses. Imazethapyr + imazapic and imazapyr + imazapic were applied at doses of 0.0, 1.0 and 2.0 L ha-1, and 0.0, 140 and 280 g ha-1, respectively, in pre-emergence of the species. Brassica napus and Festuca arundinaceae are not tolerant to herbicides, with 100% of phytotoxicity (plant death) for all doses assessed. The herbicide imazapyr + imazapic proved to be less selective, causing the highest phytotoxicity in the species tested. The most tolerant species to the herbicides was Vicia sativa, which may be the most suitable one for phytoremediation programs in areas contaminated with imazethapyr + imazapic and imazapyr + imazapic.