The influence of motorcyclist behavior in crash involvement

Introduction: In Singapore, motorcycle crashes account for 50% of traffic fatalities and 53% of injuries. While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood. The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. Methods: To explore the rider behavior, a 61-item questionnaire examining sensation seeking (Zuckerman et al., 1978), impulsiveness (Eysenck et al., 1985), aggressiveness (Buss & Perry, 1992), and risk-taking behavior (Weber et al., 2002) was developed. A total of 240 respondents with at least one year riding experience form the sample that relate behavior to their crash history, traffic penalty awareness, and demographic characteristics. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk was developed. Results and Discussions: Crash-involved motorcyclists scored higher in impulsive sensation seeking, aggression and risk-taking behavior. Aggressive and high risk-taking motorcyclists were respectively 1.30 and 2.21 times more likely to fall under the high crash involvement group while impulsive sensation seeking was not found to be significant. Based on the scores on risk-taking and aggression, the motorcyclists were clustered into four distinct personality combinations namely, extrovert (aggressive, impulsive risk-takers), leader (cautious, aggressive risk-takers), follower (agreeable, ignorant risk-takers), and introvert (self-consciousness, fainthearted risk-takers). “Extrovert” motorcyclists were most prone to crashes, being 3.34 times more likely to involve in crash and 8.29 times more vulnerable than the “introvert”. Mediating factors like demographic characteristics, riding experience, and traffic penalty awareness were found not to be significant in reducing crash risk. Conclusion: The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business.

Problems in the assessment of magnesium depletion in the rat by in vivo 31P NMR

Prior in vitro studies, utilizing 31Pn uclear magnetic resonance (31PN MR) to measure the chemical shift (CT) of 0-ATP and lengthening of the phosphocreatine spin-spin (7"') relaxation time, suggested an assessment of their efficacy in measuring magnesium depletion in vivo. Dietary magnesium depletion (Me$) produced markedly lower magnesium in plasma (0.44 vs 1. I3 mmol/liter) and bone (1 30 vs 190 pmol/g) but much smaller changes in muscle (41 vs 45 pmol/g, P < 0.01), heart (42.5 vs 44.6 prnol/g), and brain (30 vs 32 pmollg). NMR experiments in anesthetized rats in a Bruker 7-T vertical bore magnet showed that in M e $ rats there was a significant change in brain j3-ATP shift (16.15 vs 16.03 ppm, P < 0.05). These chemical shifts gave a calculated free [Mg"] of 0.71 mM (control) and 0.48 mM (MgZ+$). In muscle the change in j3-ATP shift was not significant (Me$ 15.99 ppm, controls 15.96 ppm), corresponding to a calculated free M P of 0.83 and 0.95 mM, respectively. Phosphccreatine Tz (Carr-Purcell, spin-echo pulse sequence) was no different with M e $ in muscle in vivo (surface coil) (M$+$ 136, control 142 ms) or in isolated perfused hearts (Helmholtz coil) (control 83, M e $ 92 ms). 3'P NMR is severely limited in its ability to detect dietary magnesium depletion in vivo. Measurement of j3-ATP shift in brain may allow studies of the effects of interaction in group studies but does not allow prediction of an individual magnesium status.

A mass spectrometric assay for the quantification of neuropeptide PYY in plasma

A multiple reaction monitoring mass spectrometric assay for the quantification of PYY in human plasma has been developed. A two stage sample preparation protocol was employed in which plasma containing the full length neuropeptide was first digested using trypsin, followed by solid-phase extraction to extract the digested peptide from the complex plasma matrix. The peptide extracts were analysed by LC-MS using multiple reaction monitoring to detect and quantify PYY. The method has been validated for plasma samples, yielding linear responses over the range 5–1,000 ng mL−1. The method is rapid, robust and specific for plasma PYY detection.

Determining the optimal proportion of design in design-build request for proposals (RFPs)

The design-build (DB) system is a popular and effective delivery method of construction projects worldwide. After owners decide to procure their projects through the DB system, they may wish to determine the optimal proportion of design to be provided in the DB request for proposals (RFPs), which serve as solicitations for design-builders and describe the scope of work. However, this presents difficulties to DB owners and there is little, if any, systematic research in this area. This paper reports on an empirical study in the USA entailing both an online questionnaire survey and Delphi survey to identify and evaluate the factors influencing owners’ decisions in determining the proportion of design to include in DB RFPs. Eleven factors are identified, i.e. (1) clarity of project scope; (2) applicability of performance specifications; (3) desire for design innovation; (4) site constraints; (5) availability of competent design-builders; (6) project control requirements; (7) user group involvement level; (8) third party requirements; (9) owner experience with DB; (10) project complexity; and (11) schedule constraints. A statistically significant agreement on the eleven factors was also obtained from the (mainly non-owner) Delphi experts. Although some of the experts hold different opinions on how these factors affect the proportion of design, these findings furnish various stakeholders with a better understanding of the delivery process of DB projects and the appropriate provision of project information in DB RFPs. As the result is mainly industry opinion concerning the optimal proportion of design, in addition and for completeness, future studies should be conducted to obtain a big picture of the optimal proportion of design by means of seeking owners’ inputs.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.