Search

Drivers' fault emergency response behavior can easily lead to crashes, resulting in significant economic and property losses. Exploring the causes of improper emergency response behavior is crucial for regulating driver behavior and preventing crash. Therefore, based on crashes data between commercial motor vehicles (CMVs) and noncommercial motor vehicles (NCMVs) that occurred in China from 2014 to 2018, this study established a binary logistic regression model. It systematically analyzed the key factors influencing drivers' fault emergency response behaviors in terms of individuals, vehicles, road conditions, environment, and corporate management. Additionally, it compared the differences in the influencing factors of fault emergency response behaviors between drivers of CMV and NCMV. The results indicate that the model fits well. The presence of faulty emergency response behavior in drivers is significantly correlated with five factors: age, gender, fatigue driving, speeding, and weather conditions. Moreover, these factors have different impacts on CMV drivers and NCMV drivers. Fatigue driving and speeding have a more significant impact on CMV drivers, while other factors are more pronounced for NCMV drivers. This study can provide valuable insights for the development of measures aimed at reducing the severity of CMV-NCMV crashes., Author(s): Panyi Wei [1,2,3,4]; Jianling Huang [5]; Yanyan Chen (corresponding author) [1,2]; Jianming Ma [6]; Yunchao Zhang [1,2]; Shaohua Wang [7]; Ning Chen [1,2] 1. Introduction In recent years, crashes [...]

This paper investigates the internal mechanism of the trucker's willingness to use familiar roads by constructing a structural equation model of road loyalty, in which the influence of the trucker's “emotional value” is additionally considered. The proposed method can be used to understand the trucker's psychological needs to improve the level of road service. Based on questionnaire data, AMOS software was used to analyze the correlations and corresponding parameters among 10 latent variables and 30 explicit variables. The model results show that, in addition to the value of roads as a commodity, the emotional dependence of truckers in the process of using them also has an impact on the perceived value of road services. The results of model index scores show that truck drivers' loyalty to the road does not represent their satisfaction, and familiarity with the road is still “forced” to be the first choice of most truckers due to the cost and trust in the reliability of unfamiliar roads when the road service quality and experience do not meet truckers' expectations. The latent variable scores indicate that improvements in “road safety” and “costs” are the key points to improve truckers' overall satisfaction with road freight access., Author(s): Panyi Wei [1,2,3,4]; Jianling Huang [5]; Yanyan Chen (corresponding author) [1,2]; Ronggui Zhou [3,4]; Ning Chen [1,2]; Yunchao Zhang [1,2] 1. Introduction As the main mode of cargo transportation [...]

The current approach to selecting sites for abandoned spoil areas primarily relies on qualitative methods, often overlooking the impact of policy factors on decision-making. Traditional single-site selection strategies may not be flexible enough to accommodate evolving external policy demands. Addressing this challenge is crucial for ensuring the site selection for abandoned spoil areas is both scientifically sound and policy-compliant. This research integrates various analytical methods, including principal component analysis, complex network theory, the CRITIC method, and the ordered weighted averaging method, to thoroughly evaluate the factors influencing site selection. Utilizing geographic information system (GIS) technology, the study simulates different policy scenarios, such as construction cost, social and ecological concerns, natural security, spatial accessibility, and a comprehensive balance approach. It specifically analyzes the suitability of the spoil site of a segment of the Chongqing ZW Railway under these policy conditions. Based on the actual policy situation in the local area, six potential suitable sites were screened with the help of field investigation. This study can offer a methodological framework and theoretical guidance for optimally locating mountain railway engineering waste disposal sites. In addition, the methodology presented in this study can be adapted to the development and change in policy scenarios. [ABSTRACT FROM AUTHOR]

Objective To explore the association between DLL3 expression and chemosensitivity of advanced SCLC patients to cis-platinum/etoposide therapy, and to evaluate the prognostic value of DLL3. Methods We selected 64 patients diagnosed as stage Ⅲ/Ⅳ SCLC. Protein levels of DLL3 were examined by immunohistochemistry. χ2 test was used to analyze the relation between DLL3 expression and chemotherapy efficacy. Kaplan-Meier and Cox multivariate analysis were used to investigate the impacts of DLL3 and other factors on PFS and OS of advanced SCLC patients. Results DLL3 was detected in 84.1% (54/64) of the samples and not associated with gender, age, smoking history or stage (P > 0.05). The response rate(RR) and disease control rate in DLL3-high group were lower than those in DLL3-low group (P < 0.05); PFS of patients with low DLL3 expression were better than those with high DLL3 expression (P < 0.05). DLL3 expression, tumor stage and tumor diameter were independent prognostic factors for PFS, and tumor stage was an independent prognostic factor for OS of advanced SCLC patients. Conclusion DLL3 is related to the response rate of EP chemotherapy and PFS. It may become a biomarker for predicting chemosensitivity. DLL3 has no predictive value for long-term prognosis of patients with advanced SCLC.

With the rise of the transportation mode of shared electric bikes (shared e-bikes) in China, shared e-bike related accidents have gradually increased. To facilitate the design of safety policies, it is important to understand the factors that influence shared e-bike riders' traffic accidents to facilitate intervention strategies. For this purpose, the structural equation model (SEM) with mediation analysis was applied by incorporating seven latent factors: traffic accidents, traffic violation behaviors, attitude toward safety responsibility, and attitude toward rule violations, risk perception, perceptive-motor skills, and safety skills. A questionnaire survey of a sample of 406 shared e-bike riders in China was conducted to obtain self-reported survey data. The results reveal that traffic violation behaviors and attitude toward safety responsibility had a statistically significant consequence on traffic accidents. Attitude toward rule violations, perceptive-motor skills, and safety skills can predict shared e-bike riders' traffic accidents when the traffic violation behaviors are used as a mediator. Moreover, risk perception could also be used to predict shared e-bike riders' traffic accidents when using attitudes toward safety responsibility or rule violations and traffic violation behaviors as a mediator. This paper lays a foundation for policymakers and traffic managers to develop effective intervention strategies and improve shared e-bike safety. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)