Lightweight, high-strength, reinforced plastic tube-franging die

Dies of a phenolic molding compound with chopped glass fibers as fill material possess a flexural strength of 20,000 psi and a compressive strength of 28,500 psi

Semiparametric inference in mixture models with predictive recursion marginal likelihood

Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm fails to account for any uncertainty in the additional unknown structural parameter. As an alternative to existing profile likelihood methods, we treat predictive recursion as a filter approximation to fitting a fully Bayes model, whereby an approximate marginal likelihood of the structural parameter emerges and can be used for inference. We call this the predictive recursion marginal likelihood. Convergence properties of predictive recursion under model mis-specification also lead to an attractive construction of this new procedure. We show pointwise convergence of a normalized version of this marginal likelihood function. Simulations compare the performance of this new marginal likelihood approach that of existing profile likelihood methods as well as Dirichlet process mixtures in density estimation. Mixed-effects models and an empirical Bayes multiple testing application in time series analysis are also considered

Risk based bridge data collection and asset management and the role of structural health monitoring

Peer reviewedPostprin

Optimal designs for stated choice experiments generated from fractional factorial designs

This article gives optimal designs obtained by developing a fractional factorial design for the estimation of main effects in stated choice experiments under the assumption of equal selection probabilities. This construction approach follows that of Burgess and Street (2005), who develop complete factorial designs to construct optimal designs for choice experiments, but we obtain choice experiments with fewer choice sets. We construct the fractional factorial designs using the Rao-Hamming method, which assumes all attributes have the same number of levels, which must be a prime or a prime power. We also find optimal designs for stated choice experiments that are generated from asymmetric fractional factorial designs constructed using expansive replacement under the same assumption. We use the multinomial logit model to analyze the results, and we make the assumption of equal selection probabilities when calculating optimality properties. The methods that we use to implement these constructions are given in the last section. Copyright © Grace Scientific Publishing, LLC

Sample size determination for logistic regression: A simulation study

This article considers the different methods for determining sample sizes for Wald, likelihood ratio, and score tests for logistic regression. We review some recent methods, report the results of a simulation study comparing each of the methods for each of the three types of test, and provide Mathematica code for calculating sample size. We consider a variety of covariate distributions, and find that a calculation method based on a first order expansion of the likelihood ratio test statistic performs consistently well in achieving a target level of power for each of the three types of test. © 2015 Taylor & Francis Group, LLC

Reconstruction subgrid models for nonpremixed combustion

Large-eddy simulation of combustion problems involves highly nonlinear terms that, when filtered, result in a contribution from subgrid fluctuations of scalars, Z, to the dynamics of the filtered value. This subgrid contribution requires modeling. Reconstruction models try to recover as much information as possible from the resolved field Z, based on a deconvolution procedure to obtain an intermediate field ZM. The approximate reconstruction using moments (ARM) method combines approximate reconstruction, a purely mathematical procedure, with additional physics-based information required to match specific scalar moments, in the simplest case, the Reynolds-averaged value of the subgrid variance. Here, results from the analysis of the ARM model in the case of a spatially evolving turbulent plane jet are presented. A priori and a posteriori evaluations using data from direct numerical simulation are carried out. The nonlinearities considered are representative of reacting flows: power functions, the dependence of the density on the mixture fraction (relevant for conserved scalar approaches) and the Arrhenius nonlinearity (very localized in Z space). Comparisons are made against the more popular beta probability density function (PDF) approach in the a priori analysis, trying to define ranges of validity for each approach. The results show that the ARM model is able to capture the subgrid part of the variance accurately over a wide range of filter sizes and performs well for the different nonlinearities, giving uniformly better predictions than the beta PDF for the polynomial case. In the case of the density and Arrhenius nonlinearities, the relative performance of the ARM and traditional PDF approaches depends on the size of the subgrid variance with respect to a characteristic scale of each function. Furthermore, the sources of error associated with the ARM method are considered and analytical bounds on that error are obtained

Distribution and Diversity of Archaeal and Bacterial Ammonia Oxidizers in Salt Marsh Sediments

Diversity and abundance of ammonia-oxidizing Betaproteobacteria (β-AOB) and archaea (AOA) were investigated in a New England salt marsh at sites dominated by short or tall Spartina alterniflora (SAS and SAT sites, respectively) or Spartina patens (SP site). AOA amoA gene richness was higher than β-AOB amoA richness at SAT and SP, but AOA and β-AOB richness were similar at SAS. β-AOB amoA clone libraries were composed exclusively of Nitrosospira-like amoA genes. AOA amoA genes at SAT and SP were equally distributed between the water column/sediment and soil/sediment clades, while AOA amoA sequences at SAS were primarily affiliated with the water column/sediment clade. At all three site types, AOA were always more abundant than β-AOB based on quantitative PCR of amoA genes. At some sites, we detected 109 AOA amoA gene copies g of sediment−1. Ratios of AOA to β-AOB varied over 2 orders of magnitude among sites and sampling dates. Nevertheless, abundances of AOA and β-AOB amoA genes were highly correlated. Abundance of 16S rRNA genes affiliated with Nitrosopumilus maritimus, Crenarchaeota group I.1b, and pSL12 were positively correlated with AOA amoA abundance, but ratios of amoA to 16S rRNA genes varied among sites. We also observed a significant effect of pH on AOA abundance and a significant salinity effect on both AOA and β-ΑΟΒ abundance. Our results expand the distribution of AOA to salt marshes, and the high numbers of AOA at some sites suggest that salt marsh sediments serve as an important habitat for AOA