Attributions and relapse in opiate addicts.

Investigated whether attributions of opiate addicts would predict both their ability to abstain from future use and their reactions to abstinence violations. Measures of generalized beliefs about responsibility for positive and negative outcomes and specific attributions about relapse episodes were elicited from 80 addicts at the time of admission for inpatient detoxification and treatment. Addicts who at admission attributed to themselves greater responsibility for negative outcomes and who attributed relapse episodes to more personally controllable factors were subsequently (at 6-mo follow-up) more likely either to be completely abstinent or to contain the effects of temporary lapses into opiate use. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Statistical modeling of device mismatch for analog MOS integratedcircuits

A generalized parameter-level statistical model, called statistical MOS (SMOS), capable of generating statistically significant model decks from intra- and inter-die parameter statistics is described. Calculated model decks preserve the inherent correlations between model parameters while accounting for the dependence of parameter variance on device separation distance and device area. Using a Monte Carlo approach to parameter sampling, circuit output means and standard deviations can be simulated. Incorporated in a CAD environment, these modeling algorithms will provide the analog circuit designer with a method to determine the effect of both circuit layout and device sizing on circuit output variance. Test chips have been fabricated from two different fabrication processes to extract statistical information required by the model. Experimental and simulation results for two analog subcircuits are compared to verify the statistical modeling algorithms     

The analysis of solvation in ionic liquids and organic solvents using the Abraham linear free energy relationship

The contentions made in an earlier paper [J Chem Technol Biotechnol 80 : 133–137 (2005)] that the coefficients of the Abraham solvation equation do not provide meaningful information on the molecular properties of ionic liquid solvents is refuted. The objections noted in the earlier paper disappear when the solvation equation model is correctly applied to the experimental data. It is further shown that the coefficients of the Abraham solvation equations can be used to characterize ionic liquids and can be used to select solvents for the solubility of gaseous solutes. Copyright © 2006 Society of Chemical Industry     

Assessing the relative priority of projects

Where there are a large number of projects competing for a limited pool of resources, projects have to be assigned priorities to determine which should proceed and which should be curtailed. The traditional economic procedures for assessing the relative priority of projects are reviewed, and alternative methods of ranking projects are suggested, with particular emphasis on methods that are inexpensive and easy to use.     

Cardiovascular responses to occupational stress in male medical students: A paradigm for ambulatory monitoring studies.

Examined hemodynamic responses to systematic variations in occupational stress using ambulatory blood pressure monitors. Heart rate, systolic blood pressure, diastolic blood pressure, rate–pressure product, and mood states were measured before, during, and after low-stress (lecture) and high-stress (examination) work in 44 healthy White male medical students. The lecture day was characterized by stable patterns of cardiovascular activity across all 3 periods. Hemodynamic activity and reports of activation and distress were greater on the examination day than on the lecture day. Cardiovascular activity during the pre-examination period was as high as that seen during the examination period itself, indicating an anticipatory stress effect. Pressor activity decreased after the examination, although some residual chronotropic activity was seen. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using rainbow net simulation to measure fault tolerance in a multiprocessor

The Rainbow net simulation technique is applied to modelling the impact of system load and fault handling on the availability of a fault-tolerant multiprocessor architecture. Rainbow nets are described along with the motivation for creating this modelling technique. A Rainbow net fault-handling model is created for the fault-tolerant multiprocessor architecture and the topology is shown to remain constant in size, independent of the number of processor, memory and I/O elements configured in the system. Simulation is performed with a varying load in terms of the number of active jobs the system must support. Results are given showing how the fault-tolerant capability varies with load. Two new metrics for evaluating fault tolerance are introduced; namely full fault-tolerability and partial fault-tolerability. They are based on simple observations in the model.     

Self-image resilience and dissonance: The role of affirmational resources.

Predicted that high self-esteem Ss (HSEs) would rationalize an esteem-threatening decision less than low self-esteem Ss (LSEs), because HSEs presumably had more favorable self-concepts with which to affirm, and thus repair, their overall sense of self-integrity. This prediction was supported in 2 experiments within the "free-choice" dissonance paradigm: one that manipulated self-esteem through personality feedback and the other that varied it through selection of HSEs and LSEs, but only when Ss were made to focus on their self-concepts. A 3rd experiment countered an alternative explanation of the results in terms of mood effects that may have accompanied the experimental manipulations. Results were discussed in terms of the following: (1) their support for a resources theory of individual differences in resilience to self-image threats—an extension of self-affirmation theory, (2) their implications for self-esteem functioning, and (3) their implications for the continuing debate over self-enhancement vs self-consistency motivation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Targets and methods for the detection of processed animal proteins in animal feedstuffs

Bovine spongiform encephalopathy (BSE), or ‘mad cow disease’, is one of several transmissable spongiform encephalopathies (TSEs) known to affect certain mammals and is spread through the ingestion of infected animal tissue. It is believed that the inadvertent contamination of meat and bone meal (MBM) with infected animal tissue and the subsequent use of this material as a feed supplement contributed to the spread of the disease in cattle. As a result, the use of processed animal proteins (PAPs) in animal feeds is regulated in many parts of the world. Although feed testing is the only definitive means to certify compliance, regulatory compliance often relies solely on paper certification. Recently, rapid methods have become available that can be used by regulators to determine compliance during routine inspections. We describe a rapid, immunochromatographic strip test that can detect 0.1% MBM in animal feed. The test takes 15 min to perform and large numbers of samples can be screened for PAPs simultaneously.     

Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

Sheet molding compound characterization using spiral flow

Sheet molding compound (SMC) is a fiber‐reinforced polymeric composite. It is often used in automotive, marine, and industrial applications over other materials because of its high strength to density ratio, resistance to corrosion, and low cost. There is a demand in the SMC industry to be able to characterize SMC processability. This is particularly true for heavy truck body panels, one of the fastest growing applications of SMC. Because of their large size and high strength requirement, the molding forces have a major influence in the molding cycle. Also because of the long flow paths involved, the ability of the paste to carry glass needs to be properly characterized when developing new SMC materials. In this article, we demonstrate the benefits of using spiral flow as a processability tester. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008