Changes in soil organic carbon storage under different agricultural management systems in the Southwest Amazon Region of Brazil

The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.

The association between air pollution and blood pressure in traffic controllers in Santo Andre, Sao Paulo, Brazil

Background: Urban air pollutants are associated with cardiovascular events. Traffic controllers are at high risk for pollution exposure during outdoor work shifts. Objective: The purpose of this study was to evaluate the relationship between air pollution and systemic blood pressure in traffic controllers during their work shifts. Methods: This cross-sectional study enrolled 19 male traffic controllers from Santo Andre city (Sao Paulo, Brazil) who were 30-60 years old and exposed to ambient air during outdoor work shifts. Systolic and diastolic blood pressure readings were measured every 15 min by an Ambulatory Arterial Blood Pressure Monitoring device. Hourly measurements (lags of 0-5 h) and the moving averages (2-5 h) of particulate matter (PM(10)), ozone (O(3)) ambient concentrations and the acquired daily minimum temperature and humidity means from the Sao Paulo State Environmental Agency were correlated with both systolic and diastolic blood pressures. Statistical methods included descriptive analysis and linear mixed effect models adjusted for temperature, humidity, work periods and time of day. Results: Interquartile increases of PM(10) (33 mu g/m(3)) and O(3) (49 mu g/m(3)) levels were associated with increases in all arterial pressure parameters, ranging from 1.06 to 2.53 mmHg. PM(10) concentration was associated with early effects (lag 0), mainly on systolic blood pressure. However, O(3) was weakly associated most consistently with diastolic blood pressure and with late cumulative effects. Conclusions: Santo Andre traffic controllers presented higher blood pressure readings while working their outdoor shifts during periods of exposure to ambient pollutant fluctuations. However, PM(10) and O(3) induced cardiovascular effects demonstrated different time courses and end-point behaviors and probably acted through different mechanisms. (C) 2011 Elsevier Inc. All rights reserved.

Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.

Local Influence Analysis for Skew-Normal Linear Mixed Models

In this article, we consider local influence analysis for the skew-normal linear mixed model (SN-LMM). As the observed data log-likelihood associated with the SN-LMM is intractable, Cook`s well-known approach cannot be applied to obtain measures of local influence. Instead, we develop local influence measures following the approach of Zhu and Lee (2001). This approach is based on the use of an EM-type algorithm and is measurement invariant under reparametrizations. Four specific perturbation schemes are discussed. Results obtained for a simulated data set and a real data set are reported, illustrating the usefulness of the proposed methodology.

ELECTROMYOGRAPHIC AMPLITUDE RATIO OF SERRATUS ANTERIOR AND UPPER TRAPEZIUS MUSCLES DURING MODIFIED PUSH-UPS AND BENCH PRESS EXERCISES

Imbalance and weakness of the serratus anterior and upper trapezius force couple have been described in patients with shoulder dysfunction. There is interest in identifying exercises that selectively activate these muscles and including it in rehabilitation protocols. This study aims to verify the UT/SA electromyographic (EMG) amplitude ratio, performed in different upper limb exercises and on two bases of support. Twelve healthy men were tested (average age = 22.8 +/- 3.1 years), and surface EMG was recorded from the upper trapezius and serratus anterior using single differential surface electrodes. Volunteers performed isometric contractions over a stable base of support and on a Swiss ball during the wall push-up (WP), bench press (BP), and push-up (PU) exercises. All SEMG data are reported as a percentage of root mean square or integral of linear envelope from the maximal value obtained in one of three maximal voluntary contractions for each muscle studied. A linear mixed-effect model was performed to compare UT/SA ratio values. The WP, BP, and PU exercises showed UT/SA ratio mean +/- SD values of 0.69 +/- 0.72, 0.14 +/- 0.12, and 0.39 +/- 0.37 for stable surfaces, respectively, whereas for unstable surfaces, the values were 0.73 +/- 0.67, 0.43 +/- 0.39, and 0.32 +/- 0.30. The results demonstrate that UT/SA ratio was influenced by the exercises and by the upper limb base of support. The practical application is to show that BP on a stable surface is the exercise preferred over WP and PU on either surfaces for serratus anterior muscle training in patients with imbalance between the UT/SA force couple or serratus anterior weakness.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Relationship between median nerve somatosensory evoked potentials and spinal cord injury levels in patients with quadriplegia

Study design: Cross-sectional study. Objectives: To observe if there is a relationship between the level of injury by the American Spinal Cord Injury Association (ASIA) and cortical somatosensory evoked potential (SSEP) recordings of the median nerve in patients with quadriplegia. Setting: Rehabilitation Outpatient Clinic at the university hospital in Brazil. Methods: Fourteen individuals with quadriplegia and 8 healthy individuals were evaluated. Electrophysiological assessment of the median nerve was performed by evoked potential equipment. The injury level was obtained by ASIA. N(9), N(13) and N(20) were analyzed based on the presence or absence of responses. The parameters used for analyzing these responses were the latency and the amplitude. Data were analyzed using mixed-effect models. Results: N(9) responses were found in all patients with quadriplegia with a similar latency and amplitude observed in healthy individuals; N(13) responses were not found in any patients with quadriplegia. N(20) responses were not found in C5 patients with quadriplegia but it was present in C6 and C7 patients. Their latencies were similar to healthy individuals (P > 0.05) but the amplitudes were decreased (P < 0.05). Conclusion: This study suggests that the SSEP responses depend on the injury level, considering that the individuals with C6 and C7 injury levels, both complete and incomplete, presented SSEP recordings in the cortical area. It also showed a relationship between the level of spinal cord injury assessed by ASIA and the median nerve SSEP responses, through the latency and amplitude recordings. Spinal Cord (2009) 47, 372-378; doi:10.1038/sc.2008.147; published online 20 January 2009

Sampling, WLS, and Mixed Models

Mixed models may be defined with or without reference to sampling, and can be used to predict realized random effects, as when estimating the latent values of study subjects measured with response error. When the model is specified without reference to sampling, a simple mixed model includes two random variables, one stemming from an exchangeable distribution of latent values of study subjects and the other, from the study subjects` response error distributions. Positive probabilities are assigned to both potentially realizable responses and artificial responses that are not potentially realizable, resulting in artificial latent values. In contrast, finite population mixed models represent the two-stage process of sampling subjects and measuring their responses, where positive probabilities are only assigned to potentially realizable responses. A comparison of the estimators over the same potentially realizable responses indicates that the optimal linear mixed model estimator (the usual best linear unbiased predictor, BLUP) is often (but not always) more accurate than the comparable finite population mixed model estimator (the FPMM BLUP). We examine a simple example and provide the basis for a broader discussion of the role of conditioning, sampling, and model assumptions in developing inference.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

Urban air pollution and chronic obstructive pulmonary disease-related emergency department visits

Background: Patients with chronic obstructive pulmonary disease (COPD) can have recurrent disease exacerbations triggered by several factors, including air pollution. Visits to the emergency respiratory department can be a direct result of short-term exposure to air pollution. The aim of this study was to investigate the relationship between the daily number of COPD emergency department visits and the daily environmental air concentrations of PM(10), SO(2), NO(2), CO and O(3) in the City of Sao Paulo, Brazil. Methods: The sample data were collected between 2001 and 2003 and are categorised by gender and age. Generalised linear Poisson regression models were adopted to control for both short-and long-term seasonal changes as well as for temperature and relative humidity. The non-linear dependencies were controlled using a natural cubic spline function. Third-degree polynomial distributed lag models were adopted to estimate both lag structures and the cumulative effects of air pollutants. Results: PM(10) and SO(2) readings showed both acute and lagged effects on COPD emergency department visits. Interquartile range increases in their concentration (28.3 mg/m(3) and 7.8 mg/m(3), respectively) were associated with a cumulative 6-day increase of 19% and 16% in COPD admissions, respectively. An effect on women was observed at lag 0, and among the elderly the lag period was noted to be longer. Increases in CO concentration showed impacts in the female and elderly groups. NO(2) and O(3) presented mild effects on the elderly and in women, respectively. Conclusion: These results indicate that air pollution affects health in a gender-and age-specific manner and should be considered a relevant risk factor that exacerbates COPD in urban environments.

Impact of outdoor biomass air pollution on hypertension hospital admissions

Background This study aimed to evaluate the association between the total suspended particles (TSP) generated from burning sugar cane plantations and the incidence of hospital admissions from hypertension in the city of Araraquara. Methods The study was an ecological time-series study. Total daily records of hypertension (ICD 10th I10-15) were obtained from admitted patients of all ages in a hospital in Araraquara, Sao Paulo State, Brazil, from 23 March 2003 to 27 July 2004. The daily concentration of TSP (mu g/m(3)) was obtained using a Handi-Vol sampler placed in downtown Araraquara. The local airport provided daily measures of temperature and humidity. In generalised linear Poisson regression models, the daily number of hospital admissions for hypertension was considered to be the dependent variable and the daily TSP concentration the independent variable. Results TSP presented a lagged effect on hypertension admissions, which was first observed 1 day after a TSP increase and remained almost unchanged for the following 2 days. A 10 mu g/m(3) increase in the TSP 3 day moving average lagged in 1 day led to an increase in hypertension-related hospital admissions during the harvest period (12.5%, 95% CI 5.6% to 19.9%) that was almost 30% higher than during non-harvest periods (9.0%, 95% CI 4.0% to 14.3%). Conclusions Increases in TSP concentrations were associated with hypertension-related hospital admissions. Despite the benefits of reduced air pollution in urban cities achieved by using ethanol produced from sugar cane to power automobiles, areas where the sugar cane is produced and harvested were found to have increased public health risk.

Cardiac arrhythmia emergency room visits and environmental air pollution in Sao Paulo, Brazil

Objectives: Air-pollution exposure has been associated with increased cardiovascular hospital admissions and mortality in time-series studies. We evaluated the relation between air pollutants and emergency room (ER) visits because of cardiac arrhythmia in a cardiology hospital. Methods: In a time-series study, we evaluated the association between the emergency room visits as a result of cardiac arrhythmia and daily variations in SO2, CO, NO2, O-3 and PM10, from January 1998 to August 1999. The cases of arrhythmia were modelled using generalised linear Poisson regression models, controlling for seasonality (short-term and long-term trend), and weather. Results: Interquartile range increases in CO (1.5 ppm), NO2 (49,5 mu g/m(3)) and PM10 (22.2 mu g/m(3)) on the concurrent day were associated with increases of 12.3% (95% CI: 7.6% to 17.2%), 10.4% (95% CI: 5.2% to 15.9%) and 6.7% (95% CI: 1.2% to 12.4%) in arrhythmia ER visits, respectively. PM10, CO and NO2 effects were dose-dependent and gaseous pollutants had thresholds. Only CO effect resisted estimates in models with more than one pollutant. Conclusions: Our results showed that air pollutant effects on arrhythmia are predominantly acute starting at concentrations below air quality standards, and the association with CO and NO2 suggests a relevant role for pollution caused by cars.