Discharge-calcium concentration relationships in streams of the Amazon and Cerrado of Brazil: soil or land use controlled

Stream discharge-concentration relationships are indicators of terrestrial ecosystem function. Throughout the Amazon and Cerrado regions of Brazil rapid changes in land use and land cover may be altering these hydrochemical relationships. The current analysis focuses on factors controlling the discharge-calcium (Ca) concentration relationship since previous research in these regions has demonstrated both positive and negative slopes in linear log(10)discharge-log(10)Ca concentration regressions. The objective of the current study was to evaluate factors controlling stream discharge-Ca concentration relationships including year, season, stream order, vegetation cover, land use, and soil classification. It was hypothesized that land use and soil class are the most critical attributes controlling discharge-Ca concentration relationships. A multilevel, linear regression approach was utilized with data from 28 streams throughout Brazil. These streams come from three distinct regions and varied broadly in watershed size (< 1 to > 10(6) ha) and discharge (10(-5.7)-10(3.2) m(3) s(-1)). Linear regressions of log(10)Ca versus log(10)discharge in 13 streams have a preponderance of negative slopes with only two streams having significant positive slopes. An ANOVA decomposition suggests the effect of discharge on Ca concentration is large but variable. Vegetation cover, which incorporates aspects of land use, explains the largest proportion of the variance in the effect of discharge on Ca followed by season and year. In contrast, stream order, land use, and soil class explain most of the variation in stream Ca concentration. In the current data set, soil class, which is related to lithology, has an important effect on Ca concentration but land use, likely through its effect on runoff concentration and hydrology, has a greater effect on discharge-concentration relationships.

Paleoamerican Morphology in the Context of European and East Asian Late Pleistocene Variation: Implications for Human Dispersion Into the New World

Early American crania show a different morphological pattern from the one shared by late Native Americans. Although the origin of the diachronic morphological diversity seen on the continents is still debated, the distinct morphology of early Americans is well documented and widely dispersed. This morphology has been described extensively for South America, where larger samples are available. Here we test the hypotheses that the morphology of Early Americans results from retention of the morphological pattern of Late Pleistocene modern humans and that the occupation of the New World precedes the morphological differentiation that gave rise to recent Eurasian and American morphology. We compare Early American samples with European Upper Paleolithic skulls, the East Asian Zhoukoudian Upper Cave specimens and a series of 20 modern human reference crania. Canonical Analysis and Minimum Spanning Tree were used to assess the morphological affinities among the series, while Mantel and Dow-Cheverud tests based on Mahalanobis Squared Distances were used to test different evolutionary scenarios. Our results show strong morphological affinities among the early series irrespective of geographical origin, which together with the matrix analyses results favor the scenario of a late morphological differentiation of modern humans. We conclude that the geographic differentiation of modern human morphology is a late phenomenon that occurred after the initial settlement of the Americas. Am J Phys Anthropol 144:442-453, 2011. (c) 2010 Wiley-Liss, Inc.

Exploratory Approach to the use of Techniques of Regression Analysis and Pooled Analysis in Studies of Consumer Behavior

This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Chemometric Studies on Natural Products as Potential Inhibitors of the NADH Oxidase from Trypanosoma cruzi Using the VolSurf Approach

Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

An oracle approach for interaction neighborhood estimation in random fields

We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Liquid-liquid extraction by mixed micellar systems: A new approach for clavulanic acid recovery from fermented broth

This work is the first attempt to apply aqueous two-phase mixed micellar systems (ATPMS) of the nonionic surfactant Triton X-114 and the anionic one AOT to extract clavulanic acid (CA) from broth fermented by Streptomyces clavuligerus. Cloud points were determined in McIlvane buffer pH 6.5 with or without NaCl, and diagram phases/coexistence curves were constructed. CA partition was investigated following a 2(4)-full factorial design in which AOT (0.022, 0.033 and 0.044% w/w), Triton X-114 (1.0, 3.0 and 5.0% w/w) and NaCl (0, 2.85 and 5.70% w/w) concentrations and temperature (24,26 and 28 degrees C) were selected as independent variables, and CA partition coefficient (K(CA)) and yield in the top phase (eta(CA)) as responses. CA partitioned always to the top, micelle-poor phase. The regression analysis pointed out that NaCl concentration and interaction between temperature and Triton X-114 concentration had statistically significant effects on K(CA), while eta(CA) was mainly influenced by temperature, Triton X-114 concentration and their interaction. Different ATPMS compositions were then needed to maximize these responses, specifically 0.022% (w/w) AOT, 5% (w/w) Triton X-114 for K(CA) (2.08), and 0.044% (w/w) AOT, 1% (w/w) Triton X-114 for eta(CA) (98.7%), both at 24 degrees C without NaCl. Since at 0.022% (w/w) AOT, 1% (w/w) Triton X-114 and 28 degrees C without NaCl the system was able to ensure satisfactory intermediate results (K(CA) = 1.48; eta(CA) = 86.3%), these conditions were selected as the best ones. These preliminary results are of concern for possible industrial application, because CA partition to the dilute phase can simplify the subsequent purification protocol. (C) 2011 Elsevier B.V. All rights reserved.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

A practical approach to assess depression risk and to guide risk reduction strategies in later life

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.

Risk stratification in neonates and infants submitted to cardiac surgery with cardiopulmonary bypass: A multimarker approach combining inflammatory mediators, N-terminal pro-B-type natriuretic peptide and troponin I

Low cardiac output syndrome (LCOS) is a common problem following cardiac surgery with cardiopulmonary bypass (CPB) in neonates and infants, and its early recognition remains a challenging task. We aimed to test whether a multimarker approach combining inflammatory and cardiac markers provides complementary information for prediction of LCOS and death in children submitted to cardiac surgery with CPB. Forty-six children younger than 18 months with congenital heart defects were prospectively enrolled. No intervention was made. Blood samples were collected pre-operatively, during CPB and post-operatively (PO) for measurement of interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor (TNF)-alpha, cardiac troponin I (cTnI) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Clinical data and outcome variables were recorded. Logistic regression was used to identify predictors of LCOS and death. Multivariate logistic regression identified pre-operative NT-proBNP and IL-8 4 h PO as independent predictors of LCOS, while cTnI 4 h PO and CPB length were independent predictors of death. The use of inflammatory and cardiac markers in combination improved sensitivity, negative predictive value and accuracy of the models. In conclusion, the combined assessment of inflammatory and cardiac biochemical markers can be useful for identifying young children at increased risk for LCOS and death after heart surgery with CPB. (C) 2008 Elsevier Ltd. All rights reserved.

A Novel Approach to Intraoral Mandibular Nerve Anesthesia: Changing Reference Planes in the Gow-Gates Block Technique

Purpose: The Gow-Gates technique is said to have several advantages over traditional techniques to achieve mandibular nerve anesthesia; however, its routine use is quite limited, mainly due to complications during visual alignment of reference landmarks. The purpose of this study was to verify the validity and accuracy of a new method to reach the injection site. Material and Methods: Fifteen magnetic resonance images were captured. Distances from the ideal injection point in the condylar neck (puncture ideal) to the injection points located in the a and 0 plane intersection (Puncture Gow-Gates and puncture modified) were measured and compared. Results: Positive and significant (P <= .003) Pearson correlations between landmarks and injection points confirmed the validity of the modified technique. Paired t test showed that the segment line puncture ideal-puncture modified, 5.17 mm, was 3 times shorter (P < .001) than the segment line puncture ideal-puncture Gow-Gates, 17.91 mm. As calculated by linear regression, establishing the injection point of the modified technique depended only on the anteroposterior and lateromedial condyle positions. Conclusions: The modified technique proved to be valid and precise and has a determined and an effective injection site. (C) 2009 American Association of Oral and Maxillofacial Surgeons J Oral Maxillofac Surg 67:2609-2616, 2009

A gender approach to work ability and its relationship to professional and domestic work hours among nursing personnel

The association between working hours and work ability was examined in a cross-sectional study of male (N = 156) and female (N = 1092) nurses in three public hospitals. Working hours were considered in terms of their professional and domestic hours per week and their combined impact; total work load. Logistic regression analysis showed a significant association between total work load and inadequate work ability index (WAI) for females only. Females reported a higher proportion of inadequate WAI, fewer professional work hours but longer domestic work hours. There were no significant differences in total work load by gender. The combination of professional and domestic work hours in females seemed to best explain their lower work ability. The findings suggest that investigations into female well-being need to consider their total work load. Our male sample may have lacked sufficient power to detect a relationship between working hours and work ability. (c) 2008 Elsevier Ltd. All rights reserved.

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.