Computational applications in stochastic operations research

Several computational applications in stochastic operations research are presented, where, for each application, a computational engine is used to achieve results that are otherwise overly tedious by hand calculations, or in some cases mathematically intractable. Algorithms and code are developed and implemented with specific emphasis placed on achieving exact results and substantiated via Monte Carlo simulation. The code for each application is provided in the software language utilized and algorithms are available for coding in another environment. The topics include univariate and bivariate nonparametric random variate generation using a piecewise-linear cumulative distribution, deriving exact statistical process control chart constants for non-normal sampling, testing probability distribution conformance to Benford\u27s law, and transient analysis of M/M/s queueing systems. The nonparametric random variate generation chapters provide the modeler with a method of generating univariate and bivariate samples when only observed data is available. The method is completely nonparametric and is capable of mimicking multimodal joint distributions. The algorithm is black-box, where no decisions are required from the modeler in generating variates for simulation. The statistical process control chart constant chapter develops constants for select non-normal distributions, and provides tabulated results for researchers who have identified a given process as non-normal The constants derived are bias correction factors for the sample range and sample standard deviation. The Benford conformance testing chapter offers the Kolmogorov-Smirnov test as an alternative to the standard chi-square goodness-of-fit test when testing whether leading digits of a data set are distributed according to Benford\u27s law. The alternative test has the advantage of being an exact test for all sample sizes, removing the usual sample size restriction involved with the chi-square goodness-of-fit test. The transient queueing analysis chapter develops and automates the construction of the sojourn time distribution for the nth customer in an M/M/s queue with k customers initially present at time 0 (k ≥ 0) without the usual limit on traffic intensity, rho \u3c 1, providing an avenue to conduct transient analysis on various measures of performance for a given initial number of customers in the system. It also develops and automates the construction of the sojourn time joint probability distribution function for pairs of customers, allowing the calculation of the exact covariance between customer sojourn times

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Reproducibility of Transcranial Doppler ultrasound in the middle cerebral artery

Abstract Background Transcranial Doppler ultrasound remains the only imaging modality that is capable of real-time measurements of blood flow velocity and microembolic signals in the cerebral circulation. We here assessed the repeatability and reproducibility of transcranial Doppler ultrasound in healthy volunteers and patients with symptomatic carotid artery stenosis. Methods Between March and August 2017, we recruited 20 healthy volunteers and 20 patients with symptomatic carotid artery stenosis. In a quiet temperature-controlled room, two 1-h transcranial Doppler measurements of blood flow velocities and microembolic signals were performed sequentially on the same day (within-day repeatability) and a third 7–14 days later (between-day reproducibility). Levels of agreement were assessed by interclass correlation co-efficient. Results In healthy volunteers (31±9 years, 11 male), within-day repeatability of Doppler measurements were 0.880 (95% CI 0.726–0.950) for peak velocity, 0.867 (95% CI 0.700–0.945) for mean velocity, and 0.887 (95% CI 0.741–0.953) for end-diastolic velocity. Between-day reproducibility was similar but lower: 0.777 (95% CI 0.526–0.905), 0.795 (95% CI 0.558–0.913), and 0.674 (95% CI 0.349–0.856) respectively. In patients (72±11 years, 11 male), within-day repeatability of Doppler measurements were higher: 0.926 (95% CI 0.826–0.970) for peak velocity, 0.922 (95% CI 0.817–0.968) for mean velocity, and 0.868 (95% CI 0.701–0.945) for end-diastolic velocity. Similarly, between-day reproducibility revealed lower values: 0.800 (95% CI 0.567–0.915), 0.786 (95% CI 0.542–0.909), and 0.778 (95% CI 0.527–0.905) respectively. In both cohorts, the intra-observer Bland Altman analysis demonstrated acceptable mean measurement differences and limits of agreement between series of middle cerebral artery velocity measurements with very few outliers. In patients, the carotid stenoses were 30–40% (n = 9), 40–50% (n = 6), 50–70% (n = 3) and > 70% (n = 2). No spontaneous embolisation was detected in either of the groups. Conclusions Transcranial Doppler generates reproducible data regarding the middle cerebral artery velocities. However, larger studies are needed to validate its clinical applicability. Trial registration ClinicalTrial.gov (ID NCT 03050567), retrospectively registered on 15/05/2017