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Methods: Seven hundred and sixty drivers aged from 19 to 60 years old were asked to complete the MDSI and a personality scale (trait anger, sensation seeking, altruism, and normlessness). Exploratory factory analysis (EFA) and confirmatory factor analysis (CFA) were used to obtain the factorial structure of the MDSI. The external validity of the MDSI was then evaluated by examining the associations between driving styles and personality traits, demographic variables, and traffic violations and crashes.
Results: EFA revealed a 6-factor structure of the MDSI (i.e., risky, anxious, angry, distress reduction, careful, and dissociative driving styles). CFA confirmed that the model fit of the MDSI was acceptable. The MDSI factors were moderately or weakly correlated with trait anger, sensation seeking, altruism, and normlessness. Significant gender and age differences in driving styles were found. Moreover, drivers who had traffic violations or crashes in the past year scored higher on risky and angry driving styles and lower on careful driving style than those who had not have traffic violations or crashes.
Conclusions: The Chinese version of the MDSI proved to be a reliable, valid, and highly useful instrument. It could be used to assess Chinese drivers who are at risk due to their maladaptive driving styles. 相似文献
The optimal allocation of sediment resources needs to balance three objectives including ecological, economic, and social benefits so as to realize sustainable development of sediment resources. This study aims to apply fuzzy programming and bargaining approaches to solve the problem of optimal allocation of sediment resources. Firstly, Pareto-optimal solutions of multi-objective optimization were introduced, and the multi-objective optimal allocation model of sediment resources and fuzzy programming model was constructed. Then, from the perspective of multiplayer cooperation, the optimal allocation model of sediment resources was transformed into a game model by using Nash bargaining, and Nash bargaining solution was obtained as the optimal equilibrium strategy. Finally, the influence of different disagreement utility points and bargaining weights on the results was discussed, and the results of Nash bargaining and fuzzy programming methods were compared and analyzed. Results corroborate that Nash bargaining can achieve the cooperative optimization of multiple objectives with competitive relationship and obtain satisfactory scheme. Disagreement utility points and bargaining weights have a certain impact on the optimization results. The solution of fuzzy programming is close to that of Nash bargaining, which provides different ideas for multi-objective optimization problem.
相似文献Characterization of the typical petroleum pollutants, polycyclic aromatic hydrocarbons (PAHs) and n-alkanes, and indigenous microbial community structure and function in historically contaminated soil at petrol stations is critical. Five soil samples were collected from a petrol station in Beijing, China. The concentrations of 16 PAHs and 31 n-alkanes were measured by gas chromatography-mass spectrometry. The total concentrations of PAHs and n-alkanes ranged from 973 ± 55 to 2667 ± 183 μg/kg and 6.40 ± 0.38 to 8.65 ± 0.59 mg/kg (dry weight), respectively, which increased with depth. According to the observed molecular indices, PAHs and n-alkanes originated mostly from petroleum-related sources. The levels of ΣPAHs and the total toxic benzo[a]pyrene equivalent (ranging from 6.41 to 72.54 μg/kg) might exert adverse biological effects. Shotgun metagenomic sequencing was employed to investigate the indigenous microbial community structure and function. The results revealed that Proteobacteria and Actinobacteria were the most abundant phyla, and Nocardioides and Microbacterium were the important genera. Based on COG and KEGG annotations, the highly abundant functional classes were identified, and these functions were involved in allowing microorganisms to adapt to the pressure from contaminants. Five petroleum hydrocarbon degradation-related genes were annotated, revealing the distribution of degrading microorganisms. This work facilitates the understanding of the composition, source, and potential ecological impacts of residual PAHs and n-alkanes in historically contaminated soil.
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