Operator, organizational, direct and general support, and depot maintenance manual : generator set, self-powered, diesel engine driven, 30 KW, AC, 3 phase, 120/208V, 240/416V, 60 hertz, convertible to 25 KW, 50 hertz, skid mounted (military design model SF-30-MD/CIED), FSN 6115-935-5111.

"January 1969."

Conveyor drag type piler self-propelled crawler mounted gasoline driven 35 ft long, 75 ton per hr capacity : Barber-Greene model 689 (less engine) /

Includes index.

Operator's, organizational, direct support, and general support maintenance manual for roller, vibratory, self-propelled, high impact, single smooth drum (CCE) Tampo model RS-28 (NSN 3895-01-012-8875).

Includes index.

Operator, organizational, direct support, and general support maintenance manual : shelter, multipurpose, medical unit, self-contained, transportable (MUST) (Brunswick model CW1), NSN 5410-00-809-6634.

"June 1976."

Unit, direct support, and general support maintenance repair parts and special tools lists : drill, pneumatic, drifter, boom-type, crawler-mounted, self-propelled (NSN 3820-00-854-4149), Ingersoll-Rand model CM150A/D475A.

"May 1992."

A cognitive model of binge drinking: The influence of alcohol expectancies and drinking refusal self-efficacy

While binge drinking-episodic or irregular consumption of excessive amounts of alcohol-is recognised as a serious problem affecting our youth, to date there has been a lack of psychological theory and thus theoretically driven research into this problem. The current paper develops a cognitive model using the key constructs of alcohol expectancies (AEs) and drinking refusal self-efficacy (DRSE) to explain the acquisition and maintenance of binge drinking. It is suggested that the four combinations of the AE and DRSE can explain the four drinking styles. These are normal/social drinkers, binge drinkers, regular heavy drinkers, and problem drinkers or alcoholics. Since AE and DRSE are cognitive constructs and therefore modifiable, the cognitive model can thus facilitate the design of intervention and-prevention strategies for binge drinking. (C) 2003 Elsevier Ltd. All rights reserved.

A self-similar array model of single-walled carbon nanotubes

To describe single-walled carbon nanotube (SWNT) arrays, we propose a self-similar array model. For isolated SWNT bundles, the self-similar array model is consistent with the classical triangular array model; for SWNT bundle arrays, it can present hierarchy structures and specify different array configurations. Based on this self-similar array model, we calculated the energetics of SWNT arrays, investigated the driving force for the formation of macroscopic SWNT arrays, and briefly discussed the hierarchy structures in real macroscopic SWNT arrays. (c) 2005 American Institute of Physics.

Methodology for the model-driven development of self-managing systems

Based on recent advances in autonomic computing, we propose a methodology for the cost-effective development of self-managing systems starting from a model of the resources to be managed and using a general-purpose autonomic architecture.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

Run-time model evaluation for requirements model-driven self-adaptation

A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results. © 2012 IEEE.