[1] Bayesian analysis has become vital to uncertainty quantification in groundwater modeling, but its application has been hindered by the computational cost associated with numerous model executions required by exploring the posterior probability density function (PPDF) of model parameters. This is particularly the case when the PPDF is estimated using Markov Chain Monte Carlo (MCMC) sampling....

Insulin resistance is highly prevalent in Asian Indians and contributes to worldwide public health problems, including diabetes and related disorders. Surrogate measurements of insulin sensitivity/resistance are used frequently to study Asian Indians, but these are not formally validated in this population. In this study, we compared the ability of simple surrogate indices to accurately predict...

This article defines the term surrogate as an organism, particle, or substance used to study the fate of a pathogen in a specific environment. Pathogenic organisms, nonpathogenic organisms, and innocuous particles have been used as surrogates for a variety of purposes, including studies on survival and transport as well as for method development and as "indicators" of certain conditions. This a...

The evaluation of aerospace designs is synonymous with the use of long running and computationally intensive simulations. This fuels the desire to harness the efficiency of surrogate-based methods in aerospace design optimization. Recent advances in surrogate-based design methodology bring the promise of efficient global optimization closer to reality. We review the present state of the art of ...

Our understanding of cell-cell interactions has been significantly improved in the past years with the help of Total Internal Reflection Fluorescence Microscope (TIRFM) in combination with an antigen presenting system supported by planar lipid bilayer (PLB) membranes, which are used to mimic the extensive receptor and ligand interactions within cell-cell contact interface. In TIRFM experiments,...

We implement and assess a Markov chain Monte Carlo method with a surrogate forward computational model for determining the flight conditions of the HyShot II supersonic re-entry vehicle given pressure measurements. The surrogate models we examine are non-intrusive, i.e., sampling-based, and include (1) a dimension-reduced global polynomial surrogate, (2) ordinary Kriging, and (3) a low-rank sep...

It has been shown that cooperative coevolution (CC) can effectively deal with large scale optimization problems (LSOPs) through a divide-and-conquer strategy. However, its performance is severely restricted by the current context-vectorbased sub-solution evaluation method since this method needs to access the original high dimensional simulation model when evaluating each sub-solution and thus ...

Most statistical signal nonlinearity analyses adopt the Monte-Carlo approach proposed by Theiler and co-workers, namely the ‘surrogate data’ method. A surrogate time series, or ‘surrogate’ for short, is generated as a realisation of the null hypothesis of linearity. A measure (‘test statistic’) is computed for the original time series and it is compared to those computed for an ensemble of surr...