Ground-based detection of sprites and their parent lightning flashes over Africa during the 2006 AMMA campaign

Sprites have been detected in video camera observations from Niger over mesoscale convective systems in Nigeria during the 2006 AMMA (African Monsoon Multidisciplinary Analysis) campaign The parent lightning flashes have been detected by multiple Extremely Low Frequency (ELF) receiving stations worldwide The recorded charge moments of the patent lightning flashes are often in excellent agreement between different receiving sites, and are furthermore consistent with conventional dielectric breakdown in the mesosphere as the origin of the sprites Analysis of the polarization of the horizontal magnetic field at the distant receivers provides evidence that the departure from linear magnetic polarization at ELF is caused primarily by the clay night asymmetry of the Earth-ionosphere cavity Copyright (C) 2009 Royal Meteorological Society

Factors associated with health-related quality of life after successful kidney transplantation: a population-based study

Kidney transplantation improves the quality of life of end-stage renal disease patients. The quality of life benefits, however, pertain to patients on average, not to all transplant recipients. The aim of this study was to identify factors associated with health-related quality of life after kidney transplantation. Population-based study with a cross-sectional design was carried out and quality of life was assessed by SF-36 Health Survey Version 1. A multivariate linear regression model was constructed with sociodemographic, clinical and laboratory data as independent variables. Two hundred and seventy-two kidney recipients with a functioning graft were analyzed. Hypertension, diabetes, higher serum creatinine and lower hematocrit were independently and significantly associated with lower scores for the SF-36 oblique physical component summary (PCSc). The final regression model explained 11% of the PCSc variance. The scores of oblique mental component summary (MCSc) were worse for females, patients with a lower income, unemployed and patients with a higher serum creatinine. The regression model explained 9% of the MCSc variance. Among the studied variables, comorbidity and graft function were the main factors associated with the PCSc, and sociodemographic variables and graft function were the main determinants of MCSc. Despite comprehensive, the final regression models explained only a little part of the heath-related quality of life variance. Additional factors, such as personal, environmental and clinical ones might influence quality of life perceived by the patients after kidney transplantation.

Phylogeny of South American Pogonieae (Orchidaceae, Vanilloideae) based on sequences of nuclear ribosomal (ITS) and chloroplast (psaB, rbcL, rps16, and trnL-F) DNA, with emphasis on Cleistes and discussion of biogeographic implications

Tribe Pogonieae (Orchidaceae), as Currently known, comprises live genera distributed from South to North America and Eastern Asia. Phylogenetic inferences within Cleistes and among genera of tribe Pogonieae were made based oil nrDNA (ITS) and cpDNA (trnL-F, rps16, rbcL, and psaB) Sequence data and maximum parsimony. Eighteen species of Cleistes, members of all other genera of Pogonieae, and outgroups were sampled. Analyses based oil individual DNA regions provided similar topologies. All evidence indicates that Cleistes is paraphyletic. The North American C. divaricata and C bifaria are more closely related to the temperate genera Isotria and Pogonia than to their Central and South American congeners, the latter Constituting a monophyletic group characterized by the production of nectar as reward, tuberous roots, and their distribution in Central and South America. The Amazonian Duckeella is sister to the remainder of Pogonieae. Taxonomic and biogeographic implications are discussed, and morphological synapomorphies are given For clades obtained in the inferred molecular phylogeny. (C) 2008 Gesellschaft fur Biologische Systematik. Published by Elsevier GmbH. All rights reserved.

Methods of Estimation in Multiple Linear Regression: Application to Clinical Data

Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features. Published by Elsevier Ltd.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

A discontinuous-Galerkin-based immersed boundary method with non-homogeneous boundary conditions and its application to elasticity

We propose a discontinuous-Galerkin-based immersed boundary method for elasticity problems. The resulting numerical scheme does not require boundary fitting meshes and avoids boundary locking by switching the elements intersected by the boundary to a discontinuous Galerkin approximation. Special emphasis is placed on the construction of a method that retains an optimal convergence rate in the presence of non-homogeneous essential and natural boundary conditions. The role of each one of the approximations introduced is illustrated by analyzing an analog problem in one spatial dimension. Finally, extensive two- and three-dimensional numerical experiments on linear and nonlinear elasticity problems verify that the proposed method leads to optimal convergence rates under combinations of essential and natural boundary conditions. (C) 2009 Elsevier B.V. All rights reserved.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Large Changes of Static Electric Properties Induced by Hydrogen Bonding: An ab Initio Study of Linear HCN Oligomers

We report the partitioning of the interaction-induced static electronic dipole (hyper)polarizabilities for linear hydrogen cyanide complexes into contributions arising from various interaction energy terms. We analyzed the nonadditivities of the studied properties and used these data to predict the electric properties of an infinite chain. The interaction-induced static electric dipole properties and their nonadditivities were analyzed using an approach based on numerical differentiation of the interaction energy components estimated in an external electric field. These were obtained using the hybrid variational-perturbational interaction energy decomposition scheme, augmented with coupled-cluster calculations, with singles, doubles, and noniterative triples. Our results indicate that the interaction-induced dipole moments and polarizabilities are primarily electrostatic in nature; however, the composition of the interaction hyperpolarizabilities is much more complex. The overlap effects substantially quench the contributions due to electrostatic interactions, and therefore, the major components are due to the induction and exchange induction terms, as well as the intramolecular electron-correlation corrections. A particularly intriguing observation is that the interaction first hyperpolarizability in the studied systems not only is much larger than the corresponding sum of monomer properties, but also has the opposite sign. We show that this effect can be viewed as a direct consequence of hydrogen-bonding interactions that lead to a decrease of the hyperpolarizability of the proton acceptor and an increase of the hyperpolarizability of the proton donor. In the case of the first hyperpolarizability, we also observed the largest nonadditivity of interaction properties (nearly 17%) which further enhances the effects of pairwise interactions.

Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

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.

Urea amperometric biosensors based on a multifunctional bipolymeric layer: Comparing enzyme immobilization methods

This paper outlines the results obtained with biosensors designed for urea amperometric detection. The incorporation of urease into a bipolymeric substrate consisting of poly(pyrrole) and poly(5-amino-1-naphthol) was performed through four different approaches: direct adsorption, entrapment in cellulose acetate layer. cross-linking with glutaraldehyde, and also covalent attachment to the polymeric matrix. Poly(pyrrole) acts as amperometric transducer in these biosensors, while poly(5-amino-1-naphthol) drastically reduces the interference signal of agents such as ascorbic and uric acids. The biosensors containing urease covalently attached to the substrate provided interesting results in terms of sensitivity towards urea (0.50 mu A cm(-2) mmol(-1) L), lifetime (20 days) and short response times, due to the enzyme immobilization method used. All biosensors analyzed showed also a wide linear concentration range (up to 100 mmol L(-1)) and low detection limits (0.22-0.58 mmol L(-1)). (C) 2009 Elsevier B.V. All rights reserved.

A green flow-based procedure for fluorimetric determination of acid-dissociable cyanide in natural waters exploiting multicommutation

A flow system designed with solenoid valves is proposed for determination of weak acid dissociable cyanide, based on the reaction with o-phthalaldehyde (OPA) and glycine yielding a highly fluorescent isoindole derivative. The proposed procedure minimizes the main drawbacks related to the reference batch procedure, based on reaction with barbituric acid and pyridine followed by spectrophotometric detection, i.e., use of toxic reagents, high reagent consumption and waste generation, low sampling rate, and poor sensitivity. Retention of the sample zone was exploited to increase the conversion rate of the analyte with minimized sample dispersion. Linear response (r=0.999) was observed for cyanide concentrations in the range 1-200 mu g L(-1), with a detection limit (99.7% confidence level) of 0.5 mu g L(-1)(19 nmol L(-1)). The sampling rate and coefficient of variation (n=10) were estimated as 22 measurements per hour and 1.4%, respectively. The results of determination of weak acid dissociable cyanide in natural water samples were in agreement with those achieved by the batch reference procedure at the 95% confidence level. Additionally to the improvement in the analytical features in comparison with those of the flow system with continuous reagent addition (sensitivity and sampling rate 90 and 83% higher, respectively), the consumption of OPA was 230-fold lower.

New hydrazine sensors based on electropolymerized meso-tetra (4-sulphonatephenyl)porphyrinate manganese (III)/silver nanomaterial

A new electrocatalytic active porphyrin nanocomposite material was obtained by electropolymerization of meso-tetra(4-sulphonatephenyl) porphyrinate manganese(III) complex (MnTPPS) in alkaline solutions containing sub-micromolar concentrations of silver chloride. The modified glassy carbon electrodes efficiently oxidize hydrazine at 10 mV versus Ag/AgCl, dramatically decreasing the overpotential of conventional carbon electrodes. The analytical characteristics of this amperometric sensor coupled with batch injection analysis (BIA) technique were explored. Wide linear dynamic range (2.5 x 10(-7) to 2.5 x 10(-4) mol L-1), good repeatability (R.S.D. = 0.84%, n = 30) and low detection (3.1 x 10(-8) mol L-1) and quantification (1.0 x 10(-7) mol L-1) limits, as well as very fast sampling frequency (60 determinations per hour) were achieved. (c) 2007 Elsevier B.V. All rights reserved.