Computer simulation study of collective dynamics in the glass former Ca(NO3)(2)center dot 4H(2)O

Time correlation functions of current fluctuations were calculated by molecular dynamics (MD) simulations in order to investigate sound waves of high wavevectors in the glass-forming liquid Ca(NO3)(2)center dot 4H(2)O. Dispersion curves, omega(k), were obtained for longitudinal (LA) and transverse acoustic (TA) modes, and also for longitudinal optic (LO) modes. Spectra of LA modes calculated by MD simulations were modeled by a viscoelastic model within the memory function framework. The viscoelastic model is used to rationalize the change of slope taking place at k similar to 0.3 angstrom(-1) in the omega(k) curve of acoustic modes. For still larger wavevectors, mixing of acoustic and optic modes is observed. Partial time correlation functions of longitudinal mass currents were calculated separately for the ions and the water molecules. The wavevector dependence of excitation energies of the corresponding partial LA modes indicates the coexistence of a relatively stiff subsystem made of cations and anions, and a softer subsystem made of water molecules. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4751548]

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Risk factors for computer visual syndrome (CVS) among operators of two call centers in Sao Paulo, Brazil

The aims of this study were to investigate work conditions, to estimate the prevalence and to describe risk factors associated with Computer Vision Syndrome among two call centers' operators in Sao Paulo (n = 476). The methods include a quantitative cross-sectional observational study and an ergonomic work analysis, using work observation, interviews and questionnaires. The case definition was the presence of one or more specific ocular symptoms answered as always, often or sometimes. The multiple logistic regression model, were created using the stepwise forward likelihood method and remained the variables with levels below 5% (p < 0.05). The operators were mainly female and young (from 15 to 24 years old). The call center was opened 24 hours and the operators weekly hours were 36 hours with break time from 21 to 35 minutes per day. The symptoms reported were eye fatigue (73.9%), "weight" in the eyes (68.2%), "burning" eyes (54.6%), tearing (43.9%) and weakening of vision (43.5%). The prevalence of Computer Vision Syndrome was 54.6%. Associations verified were: being female (OR 2.6, 95% CI 1.6 to 4.1), lack of recognition at work (OR 1.4, 95% CI 1.1 to 1.8), organization of work in call center (OR 1.4, 95% CI 1.1 to 1.7) and high demand at work (OR 1.1, 95% CI 1.0 to 1.3). The organization and psychosocial factors at work should be included in prevention programs of visual syndrome among call centers' operators.

NURSES' PERCEPTION REGARDING THE IMPLEMENTATION OF COMPUTER-BASED CLINICAL NURSING DOCUMENTATION

This qualitative, exploratory, descriptive study was performed with the objective of understanding the perception of the nurses working in medical-surgical units of a university hospital, regarding the strategies developed to perform a pilot test of the PROCEnf-USP electronic system, with the purpose of computerizing clinical nursing documentation. Eleven nurses of a theoretical-practical training program were interviewed and the obtained data were analyzed using the Content Analysis Technique. The following categories were discussed based on the references of participative management and planned changes: favorable aspects for the implementation; unfavorable aspects for the implementation; and expectations regarding the implementation. According to the nurses' perceptions, the preliminary use of the electronic system allowed them to show their potential and to propose improvements, encouraging them to become partners of the group manager in the dissemination to other nurses of the institution.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

A log-linear regression model for the beta-Birnbaum-Saunders distribution with censored data

The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.

Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

A Comparative Analysis between Ultrasonometry and Computer-Aided Tomography to Evaluate Bone Healing

An ultrasonometric and computed-tomographic study of bone healing was undertaken using a model of a transverse mid-shaft osteotomy of sheep tibiae fixed with a semi-flexible external fixator. Fourteen sheep were operated and divided into two groups of seven according to osteotomy type, either regular or by segmental resection. The animals were killed on the 90th postoperative day and the tibiae resected for the in vitro direct contact transverse and axial measurement of ultrasound propagation velocity (UV) followed by quantitative computer-aided tomography (callus density and volume) through the osteotomy site. The intact left tibiae were used for control, being examined in a symmetrical diaphyseal segment. Regular osteotomies healed with a smaller and more mature callus than resection osteotomies. Axial UV was consistently and significantly higher (p?=?0.01) than transverse UV and both transverse and axial UV were significantly higher for the regular than for the segmental resection osteotomy. Transverse UV did not differ significantly between the intact and operated tibiae (p?=?0.20 for regular osteotomy; p?=?0.02 for resection osteotomy), but axial UV was significantly higher for the intact tibiae. Tomographic callus density was significantly higher for the regular than for the resection osteotomy and higher than both for the intact tibiae, presenting a strong positive correlation with UV. Callus volume presented an opposite behavior, with a negative correlation with UV. We conclude that UV is at least as precise as quantitative tomography for providing information about the healing state of both regular and resection osteotomy. (C) 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:10761082, 2012

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

Comparison of fast-track diagnostics respiratory pathogens multiplex real-time RT-PCR assay with in-house singleplex assays for comprehensive detection of human respiratory viruses

Fast-track Diagnostics respiratory pathogens (FTDRP) multiplex real-time RT-PCR assay was compared with in-house singleplex real-time RT-PCR assays for detection of 16 common respiratory viruses. The FTDRP assay correctly identified 26 diverse respiratory virus strains, 35 of 41 (85%) external quality assessment samples spiked with cultured virus and 232 of 263 (88%) archived respiratory specimens that tested positive for respiratory viruses by in-house assays. Of 308 prospectively tested respiratory specimens selected from children hospitalized with acute respiratory illness, 270 (87.7%) and 265 (86%) were positive by FTDRP and in-house assays for one or more viruses, respectively, with combined test results showing good concordance (K=0.812, 95% CI = 0.786-0.838). Individual FTDRP assays for adenovirus, respiratory syncytial virus and rhinovirus showed the lowest comparative sensitivities with in-house assays, with most discrepancies occurring with specimens containing low virus loads and failed to detect some rhinovirus strains, even when abundant. The FTDRP enterovirus and human bocavirus assays appeared to be more sensitive than the in-house assays with some specimens. With the exceptions noted above, most FTDRP assays performed comparably with in-house assays for most viruses while offering enhanced throughput and easy integration by laboratories using conventional real-time PCR instrumentation. Published by Elsevier B.V.

A general class of zero-or-one inflated beta regression models

This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe the continuous component of the model, since its density has a wide range of different shapes depending on the values of the two parameters that index the distribution. We use a suitable parameterization of the beta law in terms of its mean and a precision parameter. The parameters of the mixture distribution are modeled as functions of regression parameters. We provide inference, diagnostic, and model selection tools for this class of models. A practical application that employs real data is presented. (C) 2011 Elsevier B.V. All rights reserved.

Effects of discontinuous Percoll gradient centrifugation on the quality of bovine spermatozoa evaluated with computer-assisted semen analysis and fluorescent probes association

The objective of this study was to evaluate the quality of bovine frozen-thawed sperm cells after Percoll gradient centrifugation. Frozen semen doses were obtained from six bulls of different breeds, including three taurine and three Zebu animals. Four ejaculates per bull were evaluated before and after discontinuous Percoll gradient centrifugation. Sperm motility was assessed by computer-assisted semen analysis and the integrity of the plasma and acrosomal membranes, as well as mitochondrial function, were evaluated using a combination of fluorescent probes propidium iodide, fluorescein isothiocyanate-conjugated Pisum sativum agglutinin and 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethylbenzimidazolcarbocyanine iodide. The procedure of Percoll gradient centrifugation increased the percentage of total and progressive sperm motility, beat frequency, rectilinear motility, linearity and rapidly moving cells. In addition, the percentage of cells with intact plasma membrane and mitochondrial membrane potential was increased in post-centrifugation samples. However, the percentage of sperm cells with intact acrosomal membrane was markedly reduced. The method used selected the motile cells with intact plasma membrane and higher mitochondrial functionality in frozen-thawed bull semen, but processing, centrifugation and/or the Percoll medium caused damage to the acrosomal membrane.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Head & neck optical diagnostics: vision of the future of surgery

Review paper and Proceedings of the Inaugural Meeting of the Head and Neck Optical Diagnostics Society (HNODS) on March 14th 2009 at University College London.