有机氯农药在南京市郊蔬菜中的生物富集与质量安全

用气相色谱．电子捕获检测器(GC-ECD)测定南京市郊蔬菜中的有机氯农药残留．结果表明，12种有机氯农药在所有的供试蔬菜中均有检出，DDT和HCH在各蔬菜中的含量较高，分别占有机氯农药总残留量的49．5％～75．0％和13．9％～28．2％．Wα-HCH／Wγ-HCH和WDDE／WDDT的比值在各蔬菜体内均小于或等于1，说明这些蔬菜生长的环境中可能有新的有机氯污染物的输入．各种蔬菜对有机氯农药总量的富集因子为0．41～0．78．富集能力最大的为胡萝卜，蒜苗和菠菜．HCH类农药在各种蔬菜体内的生物富集因子(0．70～1．10)要高于DDT类(0．28～0．80)．胡萝卜对HCH和DDT等有机氯农药的富集能力较强，而莴苣、蒜苗和菠菜对六氯苯、狄氏剂，异狄氏剂和硫丹有较高的生物富集能力．虽然各种蔬菜体内有机氯农药的残留量低于国家最大残留限量，但其检出率仍为100％，仍然对农产品质量安全和人类健康造成潜在的威胁．关键词：有机氯农药；蔬菜；残留量；生物富集；人类健康     

The sound of cooperation: Musical influences on cooperative behavior

Music as an environmental aspect of professional workplaces has been closely studied with respect to consumer behavior while sparse attention has been given to its relevance for employee behavior. In this article, we focus on the influence of music upon cooperative behavior within decision‐making groups. Based on results from two extended 20‐round public goods experiments, we find that happy music significantly and positively influences cooperative behavior. We also find a significant positive association between mood and cooperative behavior. Consequently, while our studies provide partial support for the relevance of affect in relation to cooperation within groups, we also show an independently important function of happy music that fits with a theory of synchronous and rhythmic activity as a social lubricant. More generally, our findings indicate that music and perhaps other atmospheric variables that are designed to prime consumer behavior might have comparably important effects for employees and consequently warrant closer investigation. Copyright © 2016 The Authors Journal of Organizational Behavior Published by John Wiley & Sons Ltd.     

公共场所人群加速度异常检测系统

针对目前基于速度检测公共场所密集人群异常行为存在的检测准确率低、使用范围局限的问题,从人群的加速度角度对可能导致公共安全事故的人群异常行为进行研究,提出了一种基于加速度检测人群异常行为的算法,并基于该算法实现了针对人群逃散、人群聚集、人群拥挤和人群逆行4种异常行为检测的系统。首先,利用金字塔Lucas-Kanade光流法进行特征点跟踪;然后,在获取到特征点的速度矩阵基础上进一步计算其加速度矩阵,反映速度的整体变化;最后,从加速度大小和方向两方面检测人群异常行为。结果表明,所提算法检测用时较少,相比基于速度检测的对比算法,检测的正确率提高到80%,误报率降低为5%。     

基于MAIB事故报告的人为失误灰色关联分析

人为失误作为海上交通事故的主要原因,受到多种因素的影响。为了识别这些影响因素,避免或减少因人为失误导致的海上交通事故,基于96件英国海事调查委员会(MAIB)事故报告,应用熵加权灰色关联分析,分别按船旗国、船舶类型、事故类型计算人为失误与影响因素之间的关联度。结果表明,能力/技能/知识、团队协作、程序和现行规程、设备、交流(内部和外部)和管理/检验/检查是影响人为失误的主要因素。     

基于SEM的双车道公路超车行为安全评价

为提高驾驶人在双车道公路上超车的安全性,基于tau理论适应性分析,提出超车过程中驾驶人不仅根据tau线索估计避碰时间,也利用距离、速度、加速度等判断超车是否安全的试验假设。招募12名受试者,应用驾驶模拟系统试验平台,依据试验假设采集12个与超车行为有关的驾驶行为数据,对其进行无量纲化处理,并利用Bootstrap法对数据进行扩增。结合驾驶行为问卷得分,利用AMOS软件,建立超车行为安全评价的结构方程模型。通过对初始假设模型进行多次修正与评价,得到影响超车行为安全的3个驾驶行为参数。结果表明,超车车辆在超车并道后的速度、与前导车之间的避碰时间及与对向车辆之间的避碰时间这3个驾驶行为参数可作为超车行为安全评价的有效指标。     

机场安检人员心理授权与违章行为关系研究

为减少民航机场安检人员的违章行为、提升民航机场安全水平,研究民航机场安检员的心理授权与违章行为之间的关系。在心理授权与违章行为关系中加入安全意识、安全动机和安全服从3个中介变量,构建机场安检人员心理授权与违章行为关系的理论假设模型;通过实证研究收集国内机场的安检员相关数据,对已构建的理论假设模型采取结构方程模型(SEM)进行检验。结果表明:机场安检员心理授权与违章行为存在一定相关性,即通过安全意识、安全动机与安全服从对违章行为产生间接影响;心理授权通过违章行为产生间接影响,通过安全意识、安全动机和安全服从的中介作用对心理授权与安全意识、安全动机和安全服从均呈现显著正相关。其中,对于安全动机的影响最大,其次是安全意识,影响最小的是安全服从;安全意识、安全动机和安全服从对于机场安检员的无意识违章、失控违章和故意违章3个维度均呈现显著负相关;安全动机对于违章行为的3个维度产生影响的差异性最小,即安全意识动机越高,机场安检员的违章行为的出现概率就会越低;安全服从与机场安检员的故意违章行为显著正相关。     

High-risk behaviors while driving: A population-based study from Iran

Objective: Traffic injuries are becoming one of the most important challenges of public health systems. Because these injuries are mostly preventable, the aim of this study is to evaluate the four main high-risk behaviors while driving.

Methods: This cross-sectional study was conducted on a random sample from the population of Mashhad, Iran, in 2014. A checklist and a previously validated questionnaire for the transtheoretical stages of change model (TTM) were used for data collection. Statistical analyses were performed using SPSS 11.5 software with P <.05 statistically significant.

Results: Totally 431 individuals were included with a mean age of 30 ± 11.3 years. Forty-three percent (183) were male. The TTM model revealed that participants were mostly in pre-actional phases regarding not using a cell phone while driving (80%), fastening the driver's seat belt (66%), front seat belt (68%), and rear seat belt (85%) The penalty was a protective factor only for using cellphone (odd ratio [OR] = 0.82, 95% confidence interval [CI], 0.68–0.98). Lower education (OR = 0.12, 95% CI, 0.01–0.94) and male gender (OR = 0.35, 95% CI, 0.14–0.83) were indicative of lower rates of fastening the front and rear seat belts.

Conclusion: The stages of change model among study participants is a proper reflection of the effectiveness of the current policies. More serious actions regarding these high-risk behaviors should be considered in legislation.     

海底管道泄漏油气扩散规律数值仿真与对比分析

为研究海底原油与天然气单相泄漏扩散规律的差异性,合理制定应急响应策略,减小事故损失,针对海底管道失效所致的原油与天然气泄漏问题,基于计算流体动力学CFD方法,建立海底油气管道泄漏事故后果预测与评估模型,对特定事故场景下的海底原油与天然气泄漏扩散过程进行模拟与分析,从泄漏扩散过程、工况因素影响、泄漏后果及应对策略4个方面对比原油与天然气的泄漏扩散特性。结果表明:相同工况下,海底原油与天然气在泄漏速率、扩散时间、扩散形态及水平最大扩散距离方面存在显著差别;与天然气相比,原油泄漏扩散行为对工况因素具有更高的敏感性;原油泄漏会引发严重的环境灾害,天然气泄漏则会影响海上结构物的稳定性及引发火灾爆炸事故,据此需合理制定具有针对性的应对策略。     

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction

Objective: This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving.

Method: Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual–manual task) and distracted (poststarting of visual–manual task) driving periods. Average relative spectral power in a low frequency range (0–0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses.

Results: Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual–manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving.

Conclusions: This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.