Risk perception and trust in the context of urban brownfields

Data are reported from a postal questionnaire completed by 747 residents of two urban local authority areas within which there were sites of brownfield land with significant levels of contamination. Respondents rated their perceptions of the extent to which their neighbourhood and own home were relatively vulnerable to contamination, their concern about possible effects of contamination, their satisfaction with their council in terms of consultation with residents on housing and development issues, and their trust in their council with respect to contaminated land risks. Satisfaction with, and trust in, the council was generally low in both areas, and especially so among those who perceived themselves to be more vulnerable to contamination. Nonetheless, dissatisfaction was less marked in the area where the local authority, according to background information, had pursued a more open and proactive style of risk communication and consultation with residents. The main predictors of trust, across both areas, were perceptions that the council was openly prepared to tell residents what they knew, and that the council had residents’ interests at heart. Implications are discussed for the impact of different modes of risk communication on trust.     

火灾模拟结果误差分析的函数分析法

火灾试验结果和模拟预测结果常能表达成关于时间变化的曲线,为定量描述两种随时间变化曲线间相符合的程度,引入误差分析的函数分析法。采用适合于低Mach数流修正的N-S方程描述烟气的输运过程,使用大涡模拟和Smagorinsky亚格子模型,对封闭空间内的火灾过程进行数值模拟;对其计算结果的分析表明,函数分析法能定量对模拟预测曲线与试验曲线间的差别进行描述,模是两曲线值大小的相对误差的度量,余弦是两曲线形状相似程度的度量。     

水质自动监测中的质量保证与质量控制

质量保证与质量拉制是水质自动监测中十分重要的技术工作和管理工作，包括人员素质、运行与管理机制、试剂与标准溶液的配制及文件记录等。在实际工作中，监测人员可根据仪器的运行状况，定期对仪器进行校准、标准溶液的棱查、比对实验验证及试剂有效性检查，用以检查仪器的基线飘移情况。如果分析中出现一个异常值，它的前后均为正常值，这种数值大多是由仪器的进样、仪器内部试剂传输等原因所致，如果发生原因不明的数据异常，就要及时检查系统的各个环节并采集实际水样进行人工分析，直至查清原因，剔除异常值，并在周报中加以说明，以确保上报数据的准确性、精密性和可比性。     

Entrainment mortality of Ichthyoplankton: Detectability and precision of estimates

The ability to detect and to develop a precise and accurate estimate of the entrainment mortality fraction is an important step in projecting power plant impacts on future fish population levels. Recent work indicates that these mortailities may be considerably less than 100% for some fish species in the early life stages. Point estimates of the entrainment mortality fraction have been developed based on probabilistic arguments, but the precision of these estimates has not been studied beyond the simple statistical test of the null hypothesis that no entrainment mortaility exists.The ability to detect entrainment mortality is explored as a function of the sample sizes (numbers of organisms collected) at the intake and discharge sampling stations of a power plant and of the proportion of organisms found alive in the intake samples (intake survival). Minimum detectable entrainment mortality, confidence interval width, and type II error (probability of accepting the null hypothesis of no entrainment mortality when there is mortality) are considered. Increasing sample size and/or decreasing sampling mortality will decrease the minimum detectable entrainment mortality, confidence interval width, and type II error for a given level of type I error.The results of this study are considered in the context of designing useful monitoring programs for determining the entrainment mortality fraction. Preliminary estimates of intake survival and the entrainment mortality fraction can be used to obtain estimates of the sample size needed for a specified level of confidence interval width or type II error. Final estimates of the intake survival and the entrainment mortality fraction can be used to determine the minimum detectable entrainment mortality and the type II error.     

Rethinking receiver operating characteristic analysis applications in ecological niche modeling

The area under the curve (AUC) of the receiver operating characteristic (ROC) has become a dominant tool in evaluating the accuracy of models predicting distributions of species. ROC has the advantage of being threshold-independent, and as such does not require decisions regarding thresholds of what constitutes a prediction of presence versus a prediction of absence. However, we show that, comparing two ROCs, using the AUC systematically undervalues models that do not provide predictions across the entire spectrum of proportional areas in the study area. Current ROC approaches in ecological niche modeling applications are also inappropriate because the two error components are weighted equally. We recommend a modification of ROC that remedies these problems, using partial-area ROC approaches to provide a firmer foundation for evaluation of predictions from ecological niche models. A worked example demonstrates that models that are evaluated favorably by traditional ROC AUCs are not necessarily the best when niche modeling considerations are incorporated into the design of the test.     

The impact of team familiarity and team leader experience on team coordination errors: A panel analysis of professional basketball teams

To explore the dynamics involved in team coordination, we examine the impact of team familiarity and team leader experience on team coordination errors (TCEs). We argue that team familiarity has a U‐shaped effect on TCEs. We study the moderating effects of team leader prior experience and team leader team‐specific experience on the association between team familiarity and TCEs. We use panel data on teams from the National Basketball Association to test the hypotheses. Our findings support the U‐shaped relationship between team familiarity and TCEs and the moderating effect of team leader team‐specific experience on this relationship. The paper advances research on errors in organizations by analyzing the antecedents of TCEs, so far an underexplored empirical phenomenon. Moreover, it contributes to research on coordination in teams by empirically examining the interplay between formal and informal coordination mechanisms. Copyright © 2015 John Wiley & Sons, Ltd.     

基于改进的HFACS和SPA的矿山安全人因分析

为了更好地服务于矿山安全管理,同时解决矿山人为因素调查、分析和评价方面存在的缺失,对部分矿山事故进行了统计分析,研究了诱发事故发生的人因因素,并分析了各因素发生的原因。在此基础上,结合对部分矿山安全管理现状的研究,建立了矿山HFACS分析模型。该模型包括5类事故致因、24个人因因素。应用该模型,结合集对分析方法,可实现矿山人因因素定量与定性分析。以陕西省某矿山为例,建立了该矿山的HFACS模型。采用专家评分法、层次分析法确定各因素的权重,计算出系统的联系度表达式。利用该表达式对该矿山的集对势、联系度、不确定性和悲观势进行了分析。结果表明,该矿山人因安全状况良好,个别人因因素指标需要改善和提高。矿山HFACS模型可以很好地涵盖矿山事故中的人因因素,通过对矿山人因现状的集对分析,可以有效提高矿山安全性。     

高寒条件下振弦式传感器在线测量尾矿坝浸润线的误差分析及对策

为减少和消除高寒条件下振弦式传感器在线测量浸润线的误差,通过理论分析和现场试验,对造成误差的因素及其影响情况进行了深入研究。结果表明,振弦式传感器产生测量误差的主要来源为设备安装深度的测量误差与尾矿水密度及重力加速度的取值误差,并提出了减少或消除误差的方法和工程技术措施,为高寒地区的浸润线在线精确测量提供了重要指导意义。     

页岩气压裂作业人因失误结构化辨识方法研究

为提高页岩气压裂作业人因失误辨识结果的全面性和针对性,建立一种结构化的人因失误辨识方法。通过概括辨识阶段的作业流程,建立作业人员行为模型,概述作业人员的行为阶段。利用筛选出的引导词辨识行为阶段人因失误。将该方法应用于页岩气压裂过程的替液阶段。结果表明,用引导词能明确辨识方向,减少头脑风暴时间以及对专家知识的依赖;辨识过程的动态调整能改善认知可靠性,使更多人因失误模式(与传统CREAM方法相比)被辨识出来。     

Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

This paper describes the utility of QUAL2E as a modelling package in the evaluation of a water quality improvement programme. In this study, QUAL2E was applied to determine the pollution loads in the river Yamuna during its course through the national capital territory of Delhi, India. The study aimed at examining the influence of different scenarios on river water quality. Four different pollution scenarios were analysed besides the 'business as usual' situation. The study revealed that it was necessary to treat the discharge from drains to the river Yamuna and diversion of a substantial load to the Agra canal for further treatment was also essential. It was also established through this study that maintaining a flow rate of more than 10 m(3)/s in the river could also help preserve the river's water quality. To clearly display the model outcomes and demarcate polluted zones in the river stretch, model results were interfaced with a Geographical Information System (GIS) to produce cartographic outputs. In addition, uncertainty analysis in the form of first-order error analysis and Monte Carlo analysis was performed, to realise the effect of each model parameter on DO and BOD predictions. The uncertainty analysis gave satisfactory results on simulated data.