There is an assumption that with the disintegration of the Soviet Union, the Second World ceased to exist. Yet the demise of the Communist bloc as a geopolitical reality did not mean that it stopped exerting a defining influence over how people think and behave. This article examines how the postsocialist state in Kazakhstan deals with potential crises such as earthquakes and the extent to which the Soviet legacy still shapes intellectual debates, state structures, and civil society organisations in in that country. Drawing on fieldwork and interviews, this paper re-examines the Second World in its historical context and re-establishes it as a conceptual framework for considering disaster risk reduction in the former Soviet bloc. It argues that it is essential to pay attention to this legacy in Kazakhstan both in policy and practice if earthquake risk reduction is to be made more effective. 相似文献
RAMP I is a screening tool developed to support practitioners in screening for work-related musculoskeletal disorder risk factors related to manual handling. RAMP I, which is part of the RAMP tool, is based on research-based studies combined with expert group judgments. More than 80 practitioners participated in the development of RAMP I. The tool consists of dichotomous assessment items grouped into seven categories. Acceptable reliability was found for a majority of the assessment items for 15 practitioners who were given 1?h of training. The usability evaluation points to RAMP I being usable for screening for musculoskeletal disorder risk factors, i.e., usable for assessing risks, being usable as a decision base, having clear results and that the time needed for an assessment is acceptable. It is concluded that RAMP I is a usable tool for practitioners. 相似文献
Complex systems often experience a long period of incubation before accidents occur. Therefore, a proactive risk assessment is essential for process safety. The conventional job hazard analysis (JHA) method has been an effective tool to conduct a process risk assessment in the high-risk industrial field. However, the conventional JHA is inadequate for the proactive risk assessment since it is usually conducted during and before one specific operation process. Operations such as startup and maintenance are performed repeatedly on the lifecycle of a plant. Therefore, the risk reduction measures for the industrial process should include not only preventive actions obtained from the conventional JHA but also recovery ones. Resilience engineering (RE) has proven to be helpful for the recovery analysis of a complex system. The objective of this paper is to propose a proactive and comprehensive process risk assessment approach based on JHA and RE. The mechanism of applying RE to address operation process risk is illustrated. The integrated approach can provide guidelines to establish proactive risk reduction measures as well as maintain a low-risk level. Finally, a gas transmission startup process risk assessment case is presented to demonstrate its applicability. 相似文献
Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献