139 resultados para Taylor, Elizabeth , 1932-2011
Resumo:
Although the Hertz theory is not applicable in the analysis of the indentation of elastic-plastic materials, it is common practice to incorporate the concept of indenter/specimen combined modulus to consider indenter deformation. The appropriateness was assessed of the use of reduced modulus to incorporate the effect of indenter deformation in the analysis of the indentation with spherical indenters. The analysis based on finite element simulations considered four values of the ratio of the indented material elastic modulus to that of the diamond indenter, E/E(i) (0, 0.04, 0.19, 0.39), four values of the ratio of the elastic reduced modulus to the initial yield strength, E(r)/Y (0, 10, 20, 100), and two values of the ratio of the indenter radius to maximum total displacement, R/delta(max) (3, 10). Indenter deformation effects are better accounted for by the reduced modulus if the indented material behaves entirely elastically. In this case, identical load-displacement (P - delta) curves are obtained with rigid and elastic spherical indenters for the same elastic reduced modulus. Changes in the ratio E/E(i), from 0 to 0.39, resulted in variations lower than 5% for the load dimensionless functions, lower than 3% in the contact area, A(c), and lower than 5% in the ratio H/E(r). However, deformations of the elastic indenter made the actual radius of contact change, even in the indentation of elastic materials. Even though the load dimensionless functions showed only a little increase with the ratio E/E(i), the hardening coefficient and the yield strength could be slightly overestimated when algorithms based on rigid indenters are used. For the unloading curves, the ratio delta(e)/delta(max), where delta(e) is the point corresponding to zero load of a straight line with slope S from the point (P(max), delta(max)), varied less than 5% with the ratio E/E(i). Similarly, the relationship between reduced modulus and the unloading indentation curve, expressed by Sneddon`s equation, did not reveal the necessity of correction with the ratio E/E(i). The most affected parameter in the indentation curve, as a consequence of the indentation deformation, was the ratio between the residual indentation depth after complete unloading and the maximum indenter displacement, delta(r)/delta(max) (up to 26%), but this variation did not significantly decrease the capability to estimate hardness and elastic modulus based on the ratio of the residual indentation depth to maximum indentation depth, h(r)/h(max). In general, the results confirm the convenience of the use of the reduced modulus in the spherical instrumented indentation tests.
Resumo:
This work examines the extraction of mechanical properties from instrumented indentation P-h(s) curves via extensive three-dimensional finite element analyses for pyramidal tips in a wide range of solids under frictional and frictionless contact conditions. Since the topography of the imprint changes with the level of pile-up or sink-in, a relationship is identified between correction factor beta in the elastic equation for the unloading indentation stage and the amount of surface deformation effects. It is shown that the presumption of a constant beta significantly affects mechanical property extractions. Consequently, a new best-fit function is found for the correlation between penetration depth ratios h(e)/h(max), h(r)/h(max) and n, circumventing the need for the assumption of a constant value for beta, made in our prior investigation [Acta Mater. 53 (2005) pp. 3545-3561]. Simulations under frictional contact conditions provide sensible boundaries for the influence of friction on both h(e)/h(max) and h(r)/h(max). Friction is essentially found to induce an overestimation in the inferred n. Instrumented indentation experiments are also performed in three archetypal metallic materials exhibiting distinctly different contact responses. Mechanical property extractions are finally demonstrated in each of these materials.
Resumo:
A gap has been identified in the literature on the diagnosis and monitoring of the degree of strategic alignment. The main objective of this article is to diagnose and analyze the strategic alignment profile using the alignment diagnostic profile (ADP) tool, which enables organizations to show visually their degree of strategic alignment. The methodological approach adopted is multiple-case studies, which were conducted at five organizations in the medical diagnostics sector. The results indicate that the ADP enables organizations to understand the steps required to improve their level of alignment and to identify and locate gaps and conflicts.
Resumo:
The `biomimetic` approach to tissue engineering usually involves the use of a bioreactor mimicking physiological parameters whilst supplying nutrients to the developing tissue. Here we present a new heart valve bioreactor, having as its centrepiece a ventricular assist device (VAD), which exposes the cell-scaffold constructs to a wider array of mechanical forces. The pump of the VAD has two chambers: a blood and a pneumatic chamber, separated by an elastic membrane. Pulsatile air-pressure is generated by a piston-type actuator and delivered to the pneumatic chamber, ejecting the fluid in the blood chamber. Subsequently, applied vacuum to the pneumatic chamber causes the blood chamber to fill. A mechanical heart valve was placed in the VAD`s inflow position. The tissue engineered (TE) valve was placed in the outflow position. The VAD was coupled in series with a Windkessel compliance chamber, variable throttle and reservoir, connected by silicone tubings. The reservoir sat on an elevated platform, allowing adjustment of ventricular preload between 0 and 11 mmHg. To allow for sterile gaseous exchange between the circuit interior and exterior, a 0.2 mu m filter was placed at the reservoir. Pressure and flow were registered downstream of the TE valve. The circuit was filled with culture medium and fitted in a standard 5% CO(2) incubator set at 37 degrees C. Pressure and flow waveforms were similar to those obtained under physiological conditions for the pulmonary circulation. The `cardiomimetic` approach presented here represents a new perspective to conventional biomimetic approaches in TE, with potential advantages. Copyright (C) 2010 John Wiley & Sons, Ltd.
Resumo:
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.
Resumo:
The aim of this study was to investigate the behavior of the association between atrazine and glyphosate in the soil through mineralization and degradation tests. Soil treatments consisted of the combination of a field dose of glyphosate (2.88 kg ha-1) with 0, 1/2, 1 and 2 times a field dose of atrazine (3.00 kg ha-1) and a field dose of atrazine with 0, 1/2, 1 and 2 times a field dose of glyphosate. The herbicide mineralization rates were measured after 0, 3, 7, 14, 21, 28, 35, 42, 49, 56 and 63 days of soil application, and degradation rates after 0, 7, 28 and 63 days. Although glyphosate mineralization rate was higher in the presence of 1 (one) dose of atrazine when compared with glyphosate alone, no significant differences were found when half or twice the atrazine dose was applied, meaning that differences in glyphosate mineralization rates cannot be attributed to the presence of atrazine. On the other hand, the influence of glyphosate on atrazine mineralization was evident, since increasing doses of glyphosate increased the atrazine mineralization rate and the lowest dose of glyphosate accelerated atrazine degradation.
Resumo:
Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.
Resumo:
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
Resumo:
In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
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.
Resumo:
A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.
Resumo:
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.
Resumo:
Maize breeding programmes in Brazil and elsewhere seek reliable methods to identify genotypes resistant to Phaeosphaeria leaf spot. The area under the disease progress curve (AUDPC) is an accurate method to evaluate the severity of foliar diseases. However, at least three data points are required to calculate the AUDPC, which is unfeasible when there are thousands of genotypes to be assessed. The aim of this work was to estimate the heritability of disease resistance, evaluate disease severity at different times using a nine-point scale in comparison to the AUDPC, and establish the most suitable phenological period for disease assessment. A repeated experiment was conducted in a 11 x 11 lattice experimental design with three replications. Disease assessments were carried out at flowering, 15 and 30 days post-anthesis for the parental lines DS95, DAS21, the F1 generation and 118 F2:3 progenies. Then, the AUDPC was obtained and results compared with the single-point evaluations used to calculate it. Individual and joint analyses of variance were conducted to obtain heritabiliy estimates. The assessments performed after the flowering stage gave higher estimates of heritability and correlation with AUDPC. We concluded that one assessment between the 15th and 30th day after flowering could provide enough information to distinguish maize genotypes for their resistance to Phaeosphaeria leaf spot under tropical conditions.
Resumo:
This paper provides the description of Phaenocarpa neosilbae sp. n. (Braconidae: Alysiinae) reared from larvae of Neosilba perezi (Romero Ruppel, 1973) (Diptera: Lonchaeidae) in Brazil. Diagnostic characters are figured and the key to the Neotropical species of Phaenocarpa (Arouca Penteado-Dias, 2006) is modified to include the new species.
Resumo:
Chromoblastomycosis is a chronic skin infection caused by the fungus Fonsecaea pedrosoi. Exploring the reasons underlying the chronic nature of F. pedrosoi infection in a murine model of chromoblastomycosis, we find that chronicity develops due to a lack of pattern recognition receptor (PRR) costimulation. F. pedrosoi was recognized primarily by C-type lectin receptors (CLRs), but not by Toll-like receptors (TLRs), which resulted in the defective induction of proinflammatory cytokines. Inflammatory responses to F. pedrosoi could be reinstated by TLR costimulation, but also required the CLR Mincle and signaling via the Syk/CARD9 pathway. Importantly, exogenously administering TLR ligands helped clear F. pedrosoi infection in vivo. These results demonstrate how a failure in innate recognition can result in chronic infection, highlight the importance of coordinated PRR signaling, and provide proof of the principle that exogenously applied PRR agonists can be used therapeutically.