The Poisson-exponential lifetime distribution

In this paper we proposed a new two-parameters lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk problem base. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulae for its reliability and failure rate functions, quantiles and moments, including the mean and variance. A simple EM-type algorithm for iteratively computing maximum likelihood estimates is presented. The Fisher information matrix is derived analytically in order to obtaining the asymptotic covariance matrix. The methodology is illustrated on a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Numerical study of tensile tests conducted on systems with elastic-plastic films deposited onto elastic-plastic substrates

In this work, a series of two-dimensional plane-strain finite element analyses was conducted to further understand the stress distribution during tensile tests on coated systems. Besides the film and the substrate, the finite element model also considered a number of cracks perpendicular to the film/substrate interface. Different from analyses commonly found in the literature, the mechanical behavior of both film and substrate was considered elastic-perfectly plastic in part of the analyses. Together with the film yield stress and the number of film cracks, other variables that were considered were crack tip geometry, the distance between two consecutive cracks and the presence of an interlayer. The analysis was based on the normal stresses parallel to the loading axis (sigma(xx)), which are responsible for cohesive failures that are observed in the film during this type of test. Results indicated that some configurations studied in this work have significantly reduced the value of sigma(xx) at the film/substrate interface and close to the pre-defined crack tips. Furthermore, in all the cases studied the values of sigma(xx) were systematically larger at the film/substrate interface than at the film surface. (C) 2010 Elsevier B.V. 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.

Variability on red blood cell transfusion practices among Brazilian neonatal intensive care units

BACKGROUND: Guidelines for red blood cell (RBC) transfusions exist; however, transfusion practices vary among centers. This study aimed to analyze transfusion practices and the impact of patients and institutional characteristics on the indications of RBC transfusions in preterm infants. STUDY DESIGN AND METHODS: RBC transfusion practices were investigated in a multicenter prospective cohort of preterm infants with a birth weight of less than 1500 g born at eight public university neonatal intensive care units of the Brazilian Network on Neonatal Research. Variables associated with any RBC transfusions were analyzed by logistic regression analysis. RESULTS: Of 952 very-low-birth-weight infants, 532 (55.9%) received at least one RBC transfusion. The percentages of transfused neonates were 48.9, 54.5, 56.0, 61.2, 56.3, 47.8, 75.4, and 44.7%, respectively, for Centers 1 through 8. The number of transfusions during the first 28 days of life was higher in Center 4 and 7 than in other centers. After 28 days, the number of transfusions decreased, except for Center 7. Multivariate logistic regression analysis showed higher likelihood of transfusion in infants with late onset sepsis (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.8-4.4), intraventricular hemorrhage (OR, 9.4; 95% CI, 3.3-26.8), intubation at birth (OR, 1.7; 95% CI, 1.0-2.8), need for umbilical catheter (OR, 2.4; 95% CI, 1.3-4.4), days on mechanical ventilation (OR, 1.1; 95% CI, 1.0-1.2), oxygen therapy (OR, 1.1; 95% CI, 1.0-1.1), parenteral nutrition (OR, 1.1; 95% CI, 1.0-1.1), and birth center (p < 0.001). CONCLUSIONS: The need of RBC transfusions in very-low-birth-weight preterm infants was associated with clinical conditions and birth center. The distribution of the number of transfusions during hospital stay may be used as a measure of neonatal care quality.

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.

MULTIVARIATE STATISTICAL METHOD IN OPTIMIZATION OF PROTEIN EXTRACTION FROM SOYBEAN FLOUR WITH DAIRY WHEY

The aim objective of this project was to evaluate the protein extraction of soybean flour in dairy whey, by the multivariate statistical method with 2(3) experiments. Influence of three variables were considered: temperature, pH and percentage of sodium chloride against the process specific variable ( percentage of protein extraction). It was observed that, during the protein extraction against time and temperature, the treatments at 80 degrees C for 2h presented great values of total protein (5.99%). The increasing for the percentage of protein extraction was major according to the heating time. Therefore, the maximum point from the function that represents the protein extraction was analysed by factorial experiment 2(3). By the results, it was noted that all the variables were important to extraction. After the statistical analyses, was observed that the parameters as pH, temperature, and percentage of sodium chloride, did not sufficient for the extraction process, since did not possible to obtain the inflection point from mathematical function, however, by the other hand, the mathematical model was significant, as well as, predictive.

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.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

Multivariate analysis of sensory characteristics of coffee grains (Coffea arabica L.) in the region of upper Paranaiba

This study aimed to examine the sensory characteristics of the grains of 21 cultivars of Coffea arabica L. and Coffea canephora Pierre from the essays of genetic improvement of EPAMIG, located in Patrocinio Municipality, Minas Gerais State, where they were collected through cloths stripping method and washed. Subsequently to dry (11 to 12% moisture b.u.), we obtained the coffee designated as natural. The evaluated varieties were: Acaia Cerrado MG 1474; Bourbon Vermelho DATERRA; Catigua MG 1; Catigua MG 2; Catual Amarelo IAC 62; Catuai Vermelho IAC 15; H 419-3-1-4-2; H 419-6-2 -5-2; H 419-6-2-5-3; H 419-6-2-7-3 Vermelho; H 493-1-2-10; H 514-7-10-1 Vermelho; H 514-7-10-6; H 515-4-2-2; H 518-3-6-1; Icatu Amarelo IAC 3282; Mundo Novo 379-19; Mundo Novo TAO 376-4; Rubi MG 1192; Sacramento MG 1 and Topazio MG 1190, from 2005/2006 and 2006/2007 seasons. The cultivars according to the first principal component with notes above 80 points, regarded as superior drink according to attributes with the highest scores (flavor, sweetness, balance, acidity, clean drink, and aspect) were: Catigua MG2, Rubi MG 1192, 514-7-10-6 H, H 419-3-1-4-2, H 419-6-2-5-2, 493-1-2-10 H, H 514-7-10-1 Vermelho, Catigua MG1, Sacramento MG1, 419-6-2-5-3 H, H 515-9-2-2 and Catuai Amarelo IAC 62.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 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.

General results for the beta-modified Weibull distribution

We study in detail the so-called beta-modified Weibull distribution, motivated by the wide use of the Weibull distribution in practice, and also for the fact that the generalization provides a continuous crossover towards cases with different shapes. The new distribution is important since it contains as special sub-models some widely-known distributions, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among several others. It also provides more flexibility to analyse complex real data. Various mathematical properties of this distribution are derived, including its moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are also derived for the chf, mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The estimation of parameters is approached by two methods: moments and maximum likelihood. We compare by simulation the performances of the estimates from these methods. We obtain the expected information matrix. Two applications are presented to illustrate the proposed distribution.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.