Characterization of crack nucleation in TA6V under fretting-fatigue loading using the potential drop technique

Crack initiation in a Ti-6Al-4V alloy was investigated experimentally in fretting fatigue conditions. A cylinder-plane geometry was used for the contact, and partial slip conditions were considered. The experiments were conducted on a new bi-actuator fretting fatigue machine and an original interrupted test expertise methodology was proposed. The potential drop technique is used to monitor crack nucleation. The careful calibration procedure used in this study and presented in this paper allowed the detection of cracks as small as 50 [mu]m. Three experimental campaigns were conducted: fretting tests (optical expertise), fretting fatigue tests up to a lifetime of 100,000 cycles (optical expertise) and fretting fatigue interrupted tests (potential drop technique). The experiments have shown that the addition of a fretting-fatigue to conventional fretting conditions can induce a drop off of 45% of the tangential threshold for crack nucleation. Two mechanisms were shown to promote this drop off: increasing the fatigue load leads to a decrease of the tangential force nucleation threshold whereas raising the fretting load leads to a decrease of the nucleation and fracture fatigue lifetime

Evaluating Risk Measures and Capital Allocations Based on Multi-Losses Driven by a Heavy-Tailed Background Risk: The Multivariate Pareto-II Model

Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult task. In this paper, we demonstrate how this can be successfully accomplished when losses follow the multivariate Pareto distribution of the second kind, which is an attractive model for multi-losses whose dependence and tail heaviness are influenced by a heavy-tailed background risk. A particular attention is given to the distortion and weighted risk measures and allocations, as well as their special cases such as the conditional layer expectation, tail value at risk, and the truncated tail value at risk. We derive formulas that are either of closed form or follow well-defined recursive procedures. In either case, their computational use is straightforward

Development and characterization of stable cell lines constitutively expressing the porcine reproductive and respiratory syndrome virus nucleocapsid protein

Despite global efforts to control porcine reproductive and respiratory syndrome virus (PRRSV) infection, the virus continues to cause economic problems in the swine industry worldwide. In this study, we attempted to generate and characterize a panel of stable BHK cell lines that constitutively express the nucleocapsid (N) protein of type 1 or type 2 PRRSV. The established BHK cell lines were found to react well with N-specific antibodies as well as the hyperimmune serum of pigs raised against each genotype of PRRSV. Taken together, the data implicate a potential usefulness for the newly generated stable cell lines as a diagnostic reagent for PRRSV serology

Estimation of a regression spline sample selection model

It is often the case that an outcome of interest is observed for a restricted non-randomly selected sample of the population. In such a situation, standard statistical analysis yields biased results. This issue can be addressed using sample selection models which are based on the estimation of two regressions: a binary selection equation determining whether a particular statistical unit will be available in the outcome equation. Classic sample selection models assume a priori that continuous regressors have a pre-specified linear or non-linear relationship to the outcome, which can lead to erroneous conclusions. In the case of continuous response, methods in which covariate effects are modeled flexibly have been previously proposed, the most recent being based on a Bayesian Markov chain Monte Carlo approach. A frequentist counterpart which has the advantage of being computationally fast is introduced. The proposed algorithm is based on the penalized likelihood estimation framework. The construction of confidence intervals is also discussed. The empirical properties of the existing and proposed methods are studied through a simulation study. The approaches are finally illustrated by analyzing data from the RAND Health Insurance Experiment on annual health expenditures

Statistical Communication Theory

Contains reports on eleven completed research projects and four on-going research projects.Joint Services Electronics Program (Contract DA36-039-AMC-03200(E))National Science Foundation (Grant GP-2495)National Aeronautics and Space Administration (Grant NsG-334)National Aeronautics and Space Administration (Grant NsG-496

Statistical Communication Theory

Contains reports on five research projects.National Science Foundation (Grant GP- 2495)National Institutes of Health (Grant MH-04737-05)National Aeronautics and Space Administration (Grant NsG-496

Statistical Communication Theory

Contains reports on eleven research projects.National Institutes of Health (Grant MH-04737-03)National Science Foundation (Grant G-16526)National Aeronautics and Space Administration (Grant NsG-496

A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution

Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invoke higher sensitivities and lower specificities. A generalized linear mixed model (GLMM) is currently recommended to synthesize diagnostic test accuracy studies. We propose a copula mixed model for bivariate meta-analysis of diagnostic test accuracy studies. Our general model includes the GLMM as a special case and can also operate on the original scale of sensitivity and specificity. Summary receiver operating characteristic curves are deduced for the proposed model through quantile regression techniques and different characterizations of the bivariate random effects distribution. Our general methodology is demonstrated with an extensive simulation study and illustrated by re-analysing the data of two published meta-analyses. Our study suggests that there can be an improvement on GLMM in fit to data and makes the argument for moving to copula random effects models. Our modelling framework is implemented in the package CopulaREMADA within the open source statistical environment R

A 2-D π–π dimer model system to investigate structure-charge transfer relationships in rubrene

© The Royal Society of Chemistry 2019Rubrene (5,6,11,12-tetraphenyltetracene) is undoubtedly one of the best performing organic charge transfer mediating materials, with experimentally determined mobilities up to 40 cm2 V−1 s−1. Consequently, there has been increasing interest by means of crystal engineering in trying to generate rubrene-based materials with analogous or even superior conducting properties. Often, experimental measurements are carried out in thin film architectures of these materials, where measured properties can be detrimentally impacted by device manufacture rather than intrinsic charge transfer properties of the material. The latter results in discarding potential good performers. To address these concerns, we report a two-dimensional model system that will allow researchers to predict charge transfer properties of their materials solely requiring the coordinates of the π–π stacking motifs. We envisaged this study to be of significant interest to the increasingly large community of materials scientists devoted to the realisation of improved organic charge mediating materials and particularly to those engaged in exploiting rubrene-based architectures.Peer reviewedFinal Accepted Versio