Sample Size and Number of Failure Requirements for Demonstration Tests with Log-Location-Scale Distributions and Type II Censoring

Reliability demonstration tests require demonstrating, with some level of confidence, that reliability exceeds a given standard. Demonstration tests can be expensive and time-consuming. Careful planning of sample size and test length are essential. This paper develops exact theoretical methods, based on pivotal quantities and confidence intervals, to aid in proper sample size selection and determining how long the test should be run (in terms of how many units must fail before the test’s end) for demonstration tests with Type II censored data from log-location-scale (and the corresponding location-scale) distributions. The methods have been implemented in S-PLUS for the lognormal, Weibull, and loglogistic distributions to allow users to develop graphs depicting probability of successful demonstration as a function of actual reliability, a target reliability, sample size, and number of units failing for an assumed distribution

Opportunities, Barriers and Actions for Industrial Demand Response in California

In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term

Markovian Dynamics on Complex Reaction Networks

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.Comment: 52 pages, 11 figures, for freely available MATLAB software, see http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.htm

Effects of bursty protein production on the noisy oscillatory properties of downstream pathways

Experiments show that proteins are translated in sharp bursts; similar bursty phenomena have been observed for protein import into compartments. Here we investigate the effect of burstiness in protein expression and import on the stochastic properties of downstream pathways. We consider two identical pathways with equal mean input rates, except in one pathway proteins are input one at a time and in the other proteins are input in bursts. Deterministically the dynamics of these two pathways are indistinguishable. However the stochastic behavior falls in three categories: (i) both pathways display or do not display noise-induced oscillations; (ii) the non-bursty input pathway displays noise-induced oscillations whereas the bursty one does not; (iii) the reverse of (ii). We derive necessary conditions for these three cases to classify systems involving autocatalysis, trimerization and genetic feedback loops. Our results suggest that single cell rhythms can be controlled by regulation of burstiness in protein production

Roadmap on biology in time varying environments

Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research

Nitrogen uptake strategies of edaphically specialized Bornean tree species

The association of tree species with particular soil types contributes to high b diversity in forests, but the mechanisms producing such distributions are still debated. Soil nitrogen (N) often limits growth and occurs in differentially available chemical forms. In a Bornean forest where tree species composition changes dramatically along a soil gradient varying in supplies of different N-forms, we investigated whether tree species’ N-uptake and soil specialization strategies covaried. We analyzed foliar 15N natural abundance for a total of 216 tree species on clay or sandy loam (the soils at the gradient’s extremes) and conducted a 15N-tracer experiment with nine specialist and generalist species to test whether species displayed flexible or differential uptake of ammonium and nitrate. Despite variation in ammonium and nitrate supplies and nearly 4 % difference in foliar δ15N between most soil specialists and populations of generalists on these soils, our 15N tracer experiment showed little support for the hypothesis that soil specialists vary in N-form use or the ratios in which they use these forms. Instead, our results indicate that these species possess flexible capacities to take up different inorganic N forms. Variation between soil specialists in uptake of different N forms is thus unlikely to cause the soil associations of tree species and high b diversity characteristic of this Bornean rain forest. Flexible uptake strategies would facilitate N-acquisition when supply rates of N-forms exhibit spatiotemporal variation and suggest that these species may be functionally redundant in their responses to N gradients and influences on ecosystem N-cycles

Transvenous phrenic nerve stimulation is associated with normalization of nocturnal heart rate perturbations in patients with central sleep apnea

STUDY OBJECTIVES: To determine the effect of transvenous phrenic nerve stimulation (TPNS) on nocturnal heart rate perturbations in patients with CSA. METHODS: In this ancillary study of the remede System Pivotal Trial, we analyzed electrocardiograms from baseline and follow-up overnight polysomnograms (PSG) in 48 CSA patients in sinus rhythm with implanted TPNS randomized to stimulation (treatment group; TPNS on) or no stimulation (control group; TPNS off). We quantified heart rate variability in the time and frequency domain. Mean change from baseline and standard error is provided. RESULTS: TPNS titrated to reduce respiratory events is associated with reduced cyclical heart rate variations in the very low-frequency domain across REM (VLFI: 4.12 ±0.79 % vs. 6.87 ± 0.82 %, p = 0.02) and NREM sleep (VLFI: 5.05 ± 0.68 % vs. 6.74 ± 0.70 %, p = 0.08) compared to the control group. Further, low-frequency oscillations were reduced in the treatment arm in REM (LFn: 0.67 ± 0.03 n.u. vs. 0.77 ± 0.03 n.u., p=0.02) and NREM sleep (LFn: 0.70 ± 0.02 n.u. vs. 0.76 ± 0.02 n.u., p=0.03). CONCLUSION: In adult patients with moderate to severe central sleep apnea, transvenous phrenic nerve stimulation reduces respiratory events and is associated with the normalization of nocturnal heart rate perturbations. Long-term follow-up studies could establish whether the reduction in heart rate perturbation by TPNS also translates into cardiovascular mortality reduction

Sample Size and Number of Failure Requirements for Demonstration Tests with Log-Location-Scale Distributions and Type II Censoring

Reliability demonstration tests require demonstrating, with some level of confidence, that reliability exceeds a given standard. Demonstration tests can be expensive and time-consuming. Careful planning of sample size and test length are essential. This paper develops exact theoretical methods, based on pivotal quantities and confidence intervals, to aid in proper sample size selection and determining how long the test should be run (in terms of how many units must fail before the test’s end) for demonstration tests with Type II censored data from log-location-scale (and the corresponding location-scale) distributions. The methods have been implemented in S-PLUS for the lognormal, Weibull, and loglogistic distributions to allow users to develop graphs depicting probability of successful demonstration as a function of actual reliability, a target reliability, sample size, and number of units failing for an assumed distribution.This preprint was published as, "Sample Size and Number of Failure Requirements for Demonstration Tests with Log-Location-Scale Distributions and Failure Censoring," Technometrics 47 (2005): 182–190, doi:10.1198/004017005000000030. </p