Optimization Applied to Transportation Systems

This volume summarizes the results of the first Workshop initiated by the Working Group on Transportation, which was established by the Systems Engineering Committee (SECOM) of the International Federation of Automatic Control (IFAC). Three levels of transportation systems analysis are utilized as a framework: -- Transportation systems planning from a socio-economic point of view; -- Operational planning, mainly focusing on routing and scheduling problems; and, -- Control and guidance of transportation systems. Formal presentations dealing with the state-of-the-art of transportation systems and selected specific topics are included in the proceedings, as well as summaries of panel discussions which followed the individual sessions

Novel statistical approaches for non-normal censored immunological data: analysis of cytokine and gene expression data

Background: For several immune-mediated diseases, immunological analysis will become more complex in the future with datasets in which cytokine and gene expression data play a major role. These data have certain characteristics that require sophisticated statistical analysis such as strategies for non-normal distribution and censoring. Additionally, complex and multiple immunological relationships need to be adjusted for potential confounding and interaction effects. Objective: We aimed to introduce and apply different methods for statistical analysis of non-normal censored cytokine and gene expression data. Furthermore, we assessed the performance and accuracy of a novel regression approach in order to allow adjusting for covariates and potential confounding. Methods: For non-normally distributed censored data traditional means such as the Kaplan-Meier method or the generalized Wilcoxon test are described. In order to adjust for covariates the novel approach named Tobit regression on ranks was introduced. Its performance and accuracy for analysis of non-normal censored cytokine/gene expression data was evaluated by a simulation study and a statistical experiment applying permutation and bootstrapping. Results: If adjustment for covariates is not necessary traditional statistical methods are adequate for non-normal censored data. Comparable with these and appropriate if additional adjustment is required, Tobit regression on ranks is a valid method. Its power, type-I error rate and accuracy were comparable to the classical Tobit regression. Conclusion: Non-normally distributed censored immunological data require appropriate statistical methods. Tobit regression on ranks meets these requirements and can be used for adjustment for covariates and potential confounding in large and complex immunological datasets

Data production models for the CDF experiment

The data production for the CDF experiment is conducted on a large Linux PC farm designed to meet the needs of data collection at a maximum rate of 40 MByte/sec. We present two data production models that exploits advances in computing and communication technology. The first production farm is a centralized system that has achieved a stable data processing rate of approximately 2 TByte per day. The recently upgraded farm is migrated to the SAM (Sequential Access to data via Metadata) data handling system. The software and hardware of the CDF production farms has been successful in providing large computing and data throughput capacity to the experiment.Comment: 8 pages, 9 figures; presented at HPC Asia2005, Beijing, China, Nov 30 - Dec 3, 200

Plant sterols and cardiovascular disease: a systematic review and meta-analysis†

The impact of increased serum concentrations of plant sterols on cardiovascular risk is unclear. We conducted a systematic review and meta-analysis aimed to investigate whether there is an association between serum concentrations of two common plant sterols (sitosterol, campesterol) and cardiovascular disease (CVD). We systematically searched the databases MEDLINE, EMBASE, and COCHRANE for studies published between January 1950 and April 2010 that reported either risk ratios (RR) of CVD in relation to serum sterol concentrations (either absolute or expressed as ratios relative to total cholesterol) or serum sterol concentrations in CVD cases and controls separately. We conducted two meta-analyses, one based on RR of CVD contrasting the upper vs. the lower third of the sterol distribution, and another based on standardized mean differences between CVD cases and controls. Summary estimates were derived by fixed and random effects meta-analysis techniques. We identified 17 studies using different designs (four case–control, five nested case–control, three cohort, five cross-sectional) involving 11 182 participants. Eight studies reported RR of CVD and 15 studies reported serum concentrations in CVD cases and controls. Funnel plots showed evidence for publication bias indicating small unpublished studies with non-significant findings. Neither of our meta-analyses suggested any relationship between serum concentrations of sitosterol and campesterol (both absolute concentrations and ratios to cholesterol) and risk of CVD. Our systematic review and meta-analysis did not reveal any evidence of an association between serum concentrations of plant sterols and risk of CVD

Data processing model for the CDF experiment

The data processing model for the CDF experiment is described. Data processing reconstructs events from parallel data streams taken with different combinations of physics event triggers and further splits the events into datasets of specialized physics datasets. The design of the processing control system faces strict requirements on bookkeeping records, which trace the status of data files and event contents during processing and storage. The computing architecture was updated to meet the mass data flow of the Run II data collection, recently upgraded to a maximum rate of 40 MByte/sec. The data processing facility consists of a large cluster of Linux computers with data movement managed by the CDF data handling system to a multi-petaByte Enstore tape library. The latest processing cycle has achieved a stable speed of 35 MByte/sec (3 TByte/day). It can be readily scaled by increasing CPU and data-handling capacity as required.Comment: 12 pages, 10 figures, submitted to IEEE-TN

Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies

<p>Abstract</p> <p>Background</p> <p>Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling.</p> <p>Methods</p> <p>We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error.</p> <p>Results</p> <p>The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates.</p> <p>Conclusion</p> <p>Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.</p

Search for bottom squarks in pbarp collisions at sqrt(s)=1.8 TeV

We report on a search for bottom squarks produced in pbarp collisions at sqrt(s) = 1.8 TeV using the D0 detector at Fermilab. Bottom squarks are assumed to be produced in pairs and to decay to the lightest supersymmetric particle (LSP) and a b quark with branching fraction of 100%. The LSP is assumed to be the lightest neutralino and stable. We set limits on the production cross section as a function of bottom squark mass and LSP mass.Comment: 5 pages, Latex. submitted 3-12-1999 to PRD - Rapid Communicatio

A Quasi-Model-Independent Search for New Physics at Large Transverse Momentum

We apply a quasi-model-independent strategy ("Sleuth") to search for new high p_T physics in approximately 100 pb^-1 of ppbar collisions at sqrt(s) = 1.8 TeV collected by the DZero experiment during 1992-1996 at the Fermilab Tevatron. Over thirty-two e mu X, W+jets-like, Z+jets-like, and 3(lepton/photon)X exclusive final states are systematically analyzed for hints of physics beyond the standard model. Simultaneous sensitivity to a variety of models predicting new phenomena at the electroweak scale is demonstrated by testing the method on a particular signature in each set of final states. No evidence of new high p_T physics is observed in the course of this search, and we find that 89% of an ensemble of hypothetical similar experimental runs would have produced a final state with a candidate signal more interesting than the most interesting observed in these data.Comment: 28 pages, 17 figures. Submitted to Physical Review