Mission safety evaluation report for STS-37, postflight edition

STS-37/Atlantis was launched on April 5, 1991 from Kennedy Space Center launch complex 39B at 9:23 a.m. Eastern Standard Time (EST). Launch was delayed 4 minutes 45 seconds because of safety concerns about the low cloud ceiling and the wind direction in the potential blast area. Based on the limited number and type of inflight anomalies encountered, the Space Shuttle operated satisfactorily throughout the STS-37 mission. A contingency EVA was performed by the crew on Flight Day (FD) 3 to free a sticky Gamma Ray Observatory (GRO) high gain antenna, after which the GRO primary payload was successfully deployed by the Orbiter's Remote Manipulator System. The GRO, which weighed just over 35,000 lbs, was the heaviest NASA science satellite ever deployed by the Space Shuttle into low Earth orbit. The scheduled entry/landing on FD 6 was waved off for one day due to high wind conditions at Edwards Air Force Base. Atlantis landed on FD 7, 11 April 1991 on Edwards AFB lakebed runway 33 at 9:55 a.m. Eastern Daylight Time

Mission safety evaluation report for STS-31, postflight edition

Mission safety factors relative to Space Transportation System (STS) Mission 31 are discussed. In addition to a mission summary, safety risk factors and inflight anomalies are discussed

Mission safety evaluation report for STS-33: Postflight edition

Space Transportation System 33 (STS-33) safety risk factors that represent a change from previous flights, factors from previous flights that have an impact on this flight, and the factors that are not unique to this flight are discussed. While some changes to the safety risk baseline are included to highlight their significance in risk level change, the primary purpose is to insure that changes which were too late to include in formal changes through the Failure Modes and Effects Analysis/Critical Items List and Hazard Analysis process are documented along with the safety position, which includes the acceptance rationale

Mission safety evaluation report for STS-34, postflight edition

Mission safety factors relative to Space Transportation System (STS) Mission 34 are discussed. In addition to a mission summary, safety risk factors and inflight anomalies are discussed

General methods for flash chromatography using disposable columns

As technology has evolved available guidelines for normal-phase flash chromatography have become less relevant. Years of experience performing chromatography with disposable columns have been condensed into simple guidelines useful for translating TLC results into either isocratic- or gradient-flash chromatography. The described studies should provide researchers with a means of selecting adequate columns and guidelines to reduce the waste of solvents, silica, time, and money. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11030-008-9104-x) contains supplementary material, which is available to authorized users

NEURAL NETWORKS IN FORECASTING AND DECISION MAKING

Neural networks (NN) have been widely touted as solving many forecasting and decision modeling problems. For example, they are argued to be able to model easily any type of parametric or non-parametric process and also automatically and optimally transform the input data. Also, they are easy to embed in information systems and they can learn how to perform simple forecasting and decision making tasks without human input. Our research-in-progress evaluates these claims. We will spend the first half of the session reviewing our work comparing neural networks to classical techniques in time series forecasting, regression-based causal forecasting, and regression-based decision models. In tile second half of the session, we will discuss the art and science of building these models. In Hill, O\u27Connor and Remus (1992), time series forecasts based on neural networks were compared with forecasts from six statistical time series methods (including exponential smoothing and Box-Jenkins) and two judgment-based methods; we did this for 111 real financial time series. The classical methods were all estimated by experts. Across all series, the neural networks did better than or as good as statistical and judgment methods. In Marquez et al. (forthcoming), data representing three common bivariate functional forms used in causal forecasting (linear, log-linear, and reciprocal) were generated and the performance of the neural network models was compared against the true regression model across differing functional forms, sample sizes, and noise levels. The results showed that neural network models perform within 2% of the mean absolute percentage error (MAPE); this is very good performance in the real world. This work is continuing as Marquez studies issues such as the vulnerability of neural networks and regression to multicolinearity, outliers, and other data problems. In Remus and Hill (forthcoming), tile production scheduling decisions as modeled by neural networks and regression-based decision rules for sixty-two decision makers were compared. Neural network models performed as well as but not better than those using the linear regression models. In Hill and Remus (forthcoming), the above research was continued and composite neural network models were estimated. The neural networks performed better than both the classical models and neural networks from the earlier study. The coinposite neural network also performed at least as well as classical composite models

The Dynamics of Abell 2125

We present 371 galaxy velocities in the field of the very rich cluster Abell 2125 (z~0.25). These were determined using optical spectroscopy collected over several years from both the WIYN 3.5m telescope and NOAO Mayall 4m telescope. Prior studies at a variety of wavelengths (radio, optical, and X-ray) have indicated that A2125 is a likely cluster-cluster merger, a scenario which we are able to test using our large velocity database. We identified 224 cluster galaxies, which were subjected to a broad range of statistical tests using both positional and velocity information to evaluate the cluster dynamics and substructure. The tests confirmed the presence of substructures within the Abell 2125 system at high significance, demonstrating that A2125 is a complex dynamical system. Comparison of the test results with existing simulations strengthens the merger hypothesis, and provides clues about the merger geometry and stage. The merger model for the system can reconcile A2125's low X-ray temperature and luminosity with its apparently high richness, and might also explain A2125's high fraction of active galaxies identified in prior radio and optical studies.Comment: 34 pages, including tables and 3 color figures; to appear in Ap

On G-invariant norms

AbstractA result of R. Mathias and Horn [cf. Linear Algebra Appl. 142 (1990) 63] on the representation of the unitarily invariant norm is extended in the context of Eaton triples and of real semisimple Lie algebras. The representation is related to a function ∥·∥α. Criteria for ∥·∥α being a norm is given in terms of α and the longest element of the underlying finite reflection group. In particular, for the real simple Lie algebras, ∥·∥α is a norm on its Cartan subspace for a given nonzero α if and only if ω0α=−α, where ω0 is the longest element of the Weyl group (this is the case if the Weyl group contains −id). Some related results are obtained