Job stress,burnout and substance use among urban transit operators: The potential mediating role of coping behaviour

Abstract

Urban transit operators, compared to other occupational groups, have higher rates of mortality and morbidity. A major risk factor is the highly stressful objective environment. This study used structural equation modelling to test a model hypothesizing that transit operators’ coping behaviours in responding to daily job hassles mediate the associations of work stress with burnout and substance use. The study sample consisted of 1231 transit operators who participated in the San Francisco MUNI Health and Safety Study. The results showed a direct and strong association between transit operators’ daily job stress and symptoms of occupational burnout even when a series of controls and coping behaviours were considered. In addition, use of “disengage-deny” and escapist strategies to cope with job stress was positively associated with burnout; the job stress–burnout association was partially mediated through such coping practices. Daily job stress was related to substance use only indirectly and mediated through burnout and use of “disengage-deny” and escapist coping strategies. “Disengage-deny” coping strategies might help reduce substance use whereas escapist coping strategies might increase such use. Overall, our findings suggest that coping behaviour may be an important correlate of transit operators’ ill health. Interventions enabling healthy coping behaviours may help reduce health risks for this occupational group.     

Spatial hidden Markov models and species distributions

A spatial hidden Markov model (SHMM) is introduced to analyse the distribution of a species on an atlas, taking into account that false observations and false non-detections of the species can occur during the survey, blurring the true map of presence and absence of the species. The reconstruction of the true map is tackled as the restoration of a degraded pixel image, where the true map is an autologistic model, hidden behind the observed map, whose normalizing constant is efficiently computed by simulating an auxiliary map. The distribution of the species is explained under the Bayesian paradigm and Markov chain Monte Carlo (MCMC) algorithms are developed. We are interested in the spatial distribution of the bird species Greywing Francolin in the south of Africa. Many climatic and land-use explanatory variables are also available: they are included in the SHMM and a subset of them is selected by the mutation operators within the MCMC algorithm.     

一类多元Bernstein算子的加权逼近

主要讨论了一类二元的Bernstein算子的加权逼近问题。首先，我们举例说明在通常的加权范数下它是无界的。然后我们给出了一类新的加权范数，在此范数下它是有界的。最后我们利用一类新的加权K一泛函给出了二元Bernstein算子加Jacobi权逼近的特征刻划。     

A genetic algorithm for assembly line balancing

Assembly line balancing is a very important aspect in any mass production setup. However, finding the optimal balance is a very difficult proposition because of the computational complexity involved. Hence sub-optimal solutions are preferred over optimal solutions. In this work, a genetic algorithm (GA) is presented for obtaining good quality solutions for assembly line balancing problems. A major feature of GA is the ability to take care of a variety of objective functions. A modified GA working with two populations, one of which allows infeasible solutions, and exchange of specimens at regular intervals is proposed for handling irregular search spaces. The experimental results obtained with a single population, as well as two populations are encouraging.     

Morrey空间上极大算子的有界性和Carleson测度

本文研究Morrey空间上的极大算子的有界性和Carleson测度     

多元Kantorovich算子在Orlicz空间中的逼近逆定理

研究了多元Kantorovich算子在Orlicz空间中的逼近问题,得到弱型逆定理.     

多元post-widder算子逼近阶的特征刻划

首先给出了一类多元post-widder算子,然后利用A.Grundmann的方法给出了多元post-widder算子逼近阶在Lp逼近和一致逼近时的特征刻划.     

角形域上一类二维Bernstein-Durrmeyer算子的Lp—逼近

本文给出了角形域上一维Bernstein－Durrmeyer算子在p方可积函数空间上的一些逼近性质，并建立了逼近等价定理．     

Bernstein算子线性组合加Jacobi权的收敛阶

通过引入一种新的范数给出了Ｂｅｒｎｓｔｅｉｎ算子线性组合加Ｊａｃｏｂｉ权的特征刻划。     

遗传算法在WMS货位优化分配中的应用

从一汽轿车股份有限公司仓储中心WMS的实际业务出发,考虑物料的进出库频率和货架的受力情况,为货位分配问题建立多目标优化模型.利用遗传算法中的并列选择法,设计遗传算子并进行求解.优化后结果表明:可以减少堆垛机的运行距离,合理安排货物的分配,减少人工作业,提高仓储的利用效率,降低企业成本.