居住区地下车库噪声在建筑群间的传播和影响模拟计算

针对城市居住区2种典型的建筑布局,结合随机点声源模型,对居住区内地下车库噪声影响进行了分析计算.通过实测值和预测值的比较,该预测模型精度较好.运用该模型预测规划与新建的居住区地下车库的噪声的影响,可为城市小区建设规划中有效控制噪声污染提供科学依据.     

两类藻毒素聚酮合成酶遗传相似性及其二级结构预测分析

研究微囊藻毒素聚酮合成酶、节球藻毒素聚酮合成酶之间的遗传关联性,并对其二级结构进行预测分析.应用聚合酶链反应得到2株蓝绿藻的毒素聚酮合成酶(PKS)基因,并进行基因序列分析.从GenBank中提取产微囊藻毒素、产节球藻毒素藻株的相应基因序列,利用DNAStar和phylip软件分析目的基因一致性及2类藻毒素PKS的进化情况.采用Garnier-Robson法、Karplus-Schulz法预测项圈藻株202A1/35、节球藻株NSOR10PKS蛋白片段的二级结构,Kyte-doolittle法分析蛋白的亲水性,Emini法预测蛋白质的表面可能性.结果表明,2类藻毒素PKS目的基因的相似性非常高;项圈藻属、念珠藻属的微囊藻毒素PKS与节球藻毒素PKS的进化关系较近;2种藻毒素PKS分析片段二级结构具有较大的相似性,其亲水性与表面可能性区域等特征也极为相似.     

城市环境地球化学调查研究方法综述

总结了城市环境地球化学调查的技术路线,论述了城市环境地球化学解释的思路和方法,提出了城市环境地球化学调查研究的重点问题及研究方向,为开展城市环境调查和评价工作提供了有参考价值的研究线索。     

模糊评价法在沧州市区地下水脆弱性评价中的应用

以DRASTIC模型为基础,建立了评价含水层污染性难易程度的模糊分析理论与方法,并将其应用于沧州市区地下水系统脆弱性评价。评价结果从趋势上反映了沧州市区地下水受污染的难易程度,与市区地下水污染现状吻合较好。     

煤矿岗前人员不安全状态智能检测系统研究——以红柳林煤矿为例

为从根本上降低煤矿从业人员实施不安全行为的概率,在充分考虑煤矿从业人员不安全个体状态是诱发其不安全行为的主要原因的基础上,设计开发一套矿工不安全状态智能检测系统。首先,对2007—2022年期间各高危行业安全事故调查报告和专家研究进行归纳,总结得出煤矿从业人员不安全状态的影响因素,构建包括生理状态、心理状态以及个体能力状态在内的3个一级指标和15个二级指标体系;其次,通过相应的表征模型对不安全状态影响因素进行深入剖析;最后,基于构建的从业人员不安全状态倾向数据库,建立煤矿岗前不安全状态智能检测系统。研究结果表明：在下井工作前对从业人员个体状态进行智能检测,能够实现矿工不安全状态“早发现、早干预”,能够有效地降低人因事故发生率,研究结果对煤炭行业安全管理具有重要的参考价值。     

考虑后悔与失望心理的应急救援任务匹配方法

为研究区间犹豫模糊信息下的应急救援任务匹配问题,提出考虑救援人员与受灾群众后悔与失望心理的决策方法以及确定双边主体效用值的方法,基于后悔理论与失望理论获得双边主体的后悔值与失望值,确定双边主体的综合感知效用值,并构建最大化综合感知效用值的多目标匹配优化模型,以得到最优匹配结果。研究结果表明：后悔与失望心理对双边主体的心理感知具有重要影响,但不影响最优匹配结果。研究结果可为应急救援任务匹配提供理论支持。     

智能手机应用程序使用与操作的驾驶分心风险影响研究

为研究智能手机应用程序操作方式与使用行为对驾驶分心影响的问题,探讨智能手机程序操作方式对驾驶分心影响的优劣关系,基于结构方程模型提出4个因果关系假设,构建涵盖程序使用、驾驶分心、驾驶绩效等潜变量的智能手机使用行为影响的结构方程模型。通过收集线下问卷的方式进行调查,搭建模拟场景,设计6项实验方案,通过驾驶模拟实验方式收集相关数据,建立相对偏差矩阵。研究结果表明：手机通话功能的使用(路径系数0.472)对驾驶分心影响显著,手机导航功能使用(路径系数0.256)、手机音乐功能使用(路径系数0.249)对驾驶分心影响不显著。语音交互方式均优于手动操作方式,其中语音交互启动导航方式(F₃=0.019)的影响最小。研究结果可对道路驾驶情况下智能手机应用使用与操作方式的研究起推动作用。     

弹用聚酰胺材料老化试验研究

以聚酰胺材料老化试验为例,讨论了储存寿命预测的分析技术、试验设计技术;提出了影响试验准确性的因素和解决问题的方法,因素包括试验样品选择、考核性能选择、试验方法选择、产品环境剖面分析、热老化温度确定等。     

Perceptions of safety on a shared road: Driving,cycling, or walking near an autonomous vehicle

Introduction: While improved safety is a highly cited potential benefit of autonomous vehicles (AVs), at the same time a frequently cited concern is the new safety challenges that AVs introduce. The literature lacks a rigorous exploration of the safety perceptions of road users who will interact with AVs, including vulnerable road users. Addressing this gap is essential because the successful integration of AVs into transportation systems hinges on an understanding of how all road users will react to their presence. Methods: A stated preference survey of the Phoenix, Arizona, metropolitan statistical area (Phoenix MSA) was conducted in July 2018. A series of ordered probit models was estimated to analyze the survey responses and identify differences between various population groups with respect to the perceived safety of driving, cycling, and walking near AVs. Results: Greater exposure to and awareness of AVs are not uniformly associated with increases in perceived safety. Various attitudinal factors, level of AV automation, and other intrinsic and extrinsic factors are related to safety perceptions of driving, walking, and cycling near AVs. Socioeconomic and demographic characteristics, such as gender, age, income, employment, and automobile usage and ownership, have various relationships with perceived safety. Conclusions: Cycling near an AV was perceived as the least safe activity, followed by walking and then driving near an AV. Both similarities and differences were observed among the factors associated with the perceived safety of different travel alternatives. Practical Applications: Public perception will guide the development and adoption of AVs directly and indirectly. To help maintain control of public perception, transportation planners, decision makers, and other stakeholders should consider more deliberate and targeted messaging to address the concerns of different road users. In addition, more careful pilot testing and more direct attention to vulnerable road users may help avoid a backlash that could delay the rollout of this technology.     

An application of a modified theory of planned behavior model to investigate adolescents’ job safety knowledge,norms, attitude and intention to enact workplace safety and health skills

Introduction: For many reasons, including a lack of adequate safety training and education, U.S. adolescents experience a higher rate of job-related injury compared to adult workers. Widely used social-psychological theories in public health research and practice, such as the theory of planned behavior, may provide guidance for developing and evaluating school-based interventions to prepare adolescents for workplace hazards and risks. Method: Using a structural equation modeling approach, the current study explores whether a modified theory of planned behavior model provides insight on 1,748 eighth graders’ occupational safety and health (OSH) attitude, subjective norm, self-efficacy and behavioral intention, before and after receiving instruction on a free, national young worker safety and health curriculum. Reliability estimates for the measures were produced and direct and indirect associations between knowledge and other model constructs assessed. Results: Overall, the findings align with the theory of planned behavior. The structural equation model adequately fit the data; most path coefficients are statistically significant and knowledge has indirect effects on behavioral intention. Confirmatory factor analyses suggest that the knowledge, attitude, self-efficacy, and behavioral intention measures each reflect a unique dimension (reliability estimates ≥0.86), while the subjective norm measure did not perform adequately. Conclusion: The findings presented provide support for using behavioral theory (specifically a modified theory of planned behavior) to investigate adolescents’ knowledge, perceptions, and behavioral intention to engage in safe and healthful activities at work, an understanding of which may contribute to reducing the downstream burden of injury on this vulnerable population—the future workforce. Practical application: Health behavior theories, commonly used in the social and behavioral sciences, have utility and provide guidance for developing and evaluating OSH interventions, including those aimed at preventing injuries and promoting the health and safety of adolescent workers in the U.S., who are injured at higher rates than are adults.