Comparing lock-in ranges and transient responses of second- and third-order phase-locked loops in master-slave clock distribution networks

The distribution of clock signals throughout the nodes of a network is essential for several applications. in control and communication with the phase-locked loop (PLL) being the component for electronic synchronization process. In systems with master-slave (MS) strategies, the PLLs are the slave nodes responsible for providing reliable clocks in all nodes of the network. As PLLs have nonlinear phase detection, double-frequency terms appear and filtering becomes necessary. Imperfections in filtering process cause oscillations around the synchronous state worsening the performance of the clock distribution process. The behavior of one-way master-slave (OWMS) clock distribution networks is studied and performances of first- and second-order filter processes are compared, concerning lock-in ranges and responses to perturbations of the synchronous state. (c) 2007 Elsevier GmbH. All rights reserved.

Comparative physical-chemical characterization of encapsulated lipid-based isotretinoin products assessed by particle size distribution and thermal behavior analyses

Isotretinoin is the drug of choice for the management of severe recalcitrant nodular acne. Nevertheless, some of its physical-chemical properties are still poorly known. Hence, the aim of our study consisted to comparatively evaluate the particle size distribution (PSD) and characterize the thermal behavior of the three encapsulated isotretinoin products in oil suspension (one reference and two generics) commercialized in Brazil. Here, we show that the PSD, estimated by laser diffraction and by polarized light microscopy, differed between the generics and the reference product. However, the thermal behavior of the three products, determined by thermogravimetry (TGA), differential thermal (DTA) analyses and differential scanning calorimetry (DSC), displayed no significant changes and were more thermostable than the isotretinoin standard used as internal control. Thus, our study suggests that PSD analyses in isotretinoin lipid-based formulations should be routinely performed in order to improve their quality and bioavailability. (C) 2010 Elsevier B.V. All rights reserved.

Three-Dimensional Stress Distribution in the Human Periodontal Ligament in Masticatory, Parafunctional, and Trauma Loads: Finite Element Analysis

Background: The presence of the periodontal ligament (PDL) makes it possible to absorb and distribute loads produced during masticatory function and other tooth contacts into the alveolar process via the alveolar bone proper. However, several factors affect the integrity of periodontal structures causing the destruction of the connective matrix and cells, the loss of fibrous attachment, and the resorption of alveolar bone. Methods: The purpose of this study was to evaluate the stress distribution by finite element analysis in a PDL in three-dimensional models of the upper central incisor under three different load conditions: 100 N occlusal loading at 45 degrees (model 1: masticatory load); 500 N at the incisal edge at 45 degrees (model 2: parafunctional habit); and 800 N at the buccal surface at 90 degrees (model 3: trauma case). The models were built from computed tomography scans. Results: The stress distribution was quite different among the models. The most significant values (harmful) of tensile and compressive stresses were observed in models 2 and 3, with similarly distinct patterns of stress distributions along the PDL. Tensile stresses were observed along the internal and external aspects of the PDL, mostly at the cervical and middle thirds. Conclusions: The stress generation in these models may affect the integrity of periodontal structures. A better understanding of the biomechanical behavior of the PDL under physiologic and traumatic loading conditions might enhance the understanding of the biologic reaction of the PDL in health and disease. J Periodontol 2009;80:1859-1867.

Predicting the columnar-to-equiaxed transition for a distribution of nucleation undercoolings

A deterministic mathematical model for steady-state unidirectional solidification is proposed to predict the columnar-to-equiaxed transition. In the model, which is an extension to the classic model proposed by Hunt [Hunt JD. Mater Sci Eng 1984;65:75], equiaxed grains nucleate according to either a normal or a log-normal distribution of nucleation undercoolings. Growth maps are constructed, indicating either columnar or equiaxed solidification as a function of the velocity of isotherms and temperature gradient. The fields A columnar and equiaxed growth change significantly with the spread of the nucleation undercooling distribution. Increasing the spread Favors columnar solidification if the dimensionless velocity of the isotherms is larger than 1. For a velocity less than 1, however, equiaxed solidification is initially favored, but columnar solidification is enhanced for a larger increase in the spread. This behavior was confirmed by a stochastic model, which showed that an increase in the distribution spread Could change the grain structure from completely columnar to 50% columnar grains. (c) 2008 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The genus Rhagomys (Thomas 1917) (Rodentia, Cricetidae, Sigmodontinae) in South America: morphological considerations, geographic distribution and zoogeographic comments

American Museum of Natural History

Herbicide distribution in soils of a riparian forest and neighboring sugar cane field

Riparian forests are protected by Brazilian law to preserve rivers and their margins. A sugar cane field adjacent to a strip of young riparian forest bordering an older riparian forest along a stream was used to study the riparian forest as a buffer zone to prevent pesticides pollution. Concentrations of the herbicides diuron, hexazinone and tebuthiuron were determined in different soil layers of a Red Yellow Oxisol during 2003 and 2004. The determination was done by High Performance Liquid Chromatography with reverse phase C-18 column, through two mobile phases. Diuron and hexazinone concentration diminished between the sugar cane and riparian forest as buffer strip demonstrating a protective effect. However, tebuthiuron had about four times higher concentrations in the old riparian forest compared to the other areas. Concentrations were higher in the surface and decreased in deeper soil layers in the old riparian forest suggesting that this herbicide probably was introduced by air pollution. This pesticide concentrated in the canopy could be washed by rain to the soil adjacent to the stream. Our data suggest that climate conditions were responsible for enhanced volatilization exposing the old riparian forest to more air pollution that was captured by the higher canopy. (C) 2010 Elsevier B.V. All rights reserved.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

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