Effects of daily events on mood states in major depressive disorder.

Major depressive disorder (MDD) is characterized by high negative affect (NA) and low positive affect (PA), but little is known about emotional reactivity in daily life. The authors used experience sampling methodology to investigate changes in NA and PA following minor daily events in MDD compared with healthy participants. Contrary to expectation, MDD participants did not report more frequent negative events, although they did report fewer positive events. Multilevel regression showed that both NA and PA responses to negative events were blunted in the MDD group, whereas responses to positive events were enhanced. NA responses to negative events persisted longer in MDD participants. Depressed participants with a positive family history or longer current episodes showed relatively greater NA responses to negative events. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Clarifying and Extending the Construct of Adult Resilience.

In this article the author responds to comments made in this issue (see records 2005-03019-010; 2005-03019-011; 2005-03019-012; 2005-03019-013; and 2005-03019-014) responding to his original article entitled Loss, trauma, and human resilience: Have we underestimated the human capacity to thrive after extremely aversive events? (see record 2004-10043-003). The author notes that in his original article he focused on three crucial points: Resilience among adults represents a distinct and empirically separable outcome trajectory from that normally associated with recovery from trauma; resilience is more prevalent than generally accepted in either the lay or professional literature; and there are multiple and sometimes unexpected factors that inform adult resilience. Owing to the brevity of the article, the author could only touch briefly on many of the more nuanced and complex issues suggested by the resilience construct; this left plenty of room for critique. Fortunately, the comments are generous and insightful and for the most part compatible with the driving goal of the article. As might be expected, of course, there were statements peppered throughout the comments that the author deemed worthy of rebuttal or correction. He considers four points that seemed to beg most urgently for response. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling heterogeneity in social interaction processes using multilevel survival analysis.

More than 15 years ago, survival or hazard regression analyses were introduced to psychology (W. Gardner & W. A. Griffin, 1989; W. A. Griffin & W. Gardner, 1989) as powerful methodological tools for studying real time social interaction processes among dyads. Almost no additional published applications have appeared, although such data are commonly collected and the applicable questions are central to many important theoretical perspectives. To revisit the basic methods, the authors use an example from emotion regulation theory in which the level of child antisocial behavior is hypothesized to be positively associated with the hazard rate of angry emotions and negatively associated with sad, fearful emotions in the face of parental negative behavior (scolding). The authors discuss the limitations of traditional approaches to the analysis of social interaction and demonstrate improvements in the ability to model individual differences now available in existing software. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Risk of extreme events in the configuration of priority systems

This paper presents a reliability-based framework for the configuration of priority systems that control the risks of extreme transaction latencies. Modeling of priority systems can be computationally complex and lack robustness with respect to the feasible variations of such systems. The analyses tend to be ad hoc and overly particular to the application at hand. Furthermore, modeling of priority systems has focused on assessment of the average latencies, rather than on the potential for extremes of latency. The developed framework includes (i) a compact notation useful for modeling of priority systems, (ii) assessment of the risk of extreme latencies, and (iii) multiobjective analysis for the tuning of system parameters. An acceptable balance is sought among multiple risks of extreme transaction latencies. The framework is demonstrated in the configuration of an e-business server to minimize the lost transactions, e.g. ‘purchase’ requests for which a customer needs to wait longer than 8 s.     

国外系统模拟技术及其在矿业中应用的新进展

概述系统模拟技术的主要作用，分析模拟技术的新进展及在矿业中应用的现状，并讨论模拟技术在矿业中应用的前景。     

风电爬坡事件对系统运行充裕性的影响评估

风电爬坡事件具有大波动性和强不确定性的特点,可造成系统中发用电的严重不平衡,从而导致负荷损失。在分析风电爬坡事件特征和爬坡预测研究现状的基础上,建立了风电爬坡事件模型,定量表示爬坡事件表征量与风电功率曲线之间的关系;同时考虑负荷预测的不确定性,采用场景削减方法生成风电爬坡过程对应的典型净负荷场景集。构建了评估系统运行充裕性的指标体系,推导了缓冲失负荷概率指标的计算公式;将系统状态分为充裕、失负荷和临界3种,分别计算各状态对应概率及失负荷严重程度。以甘肃电网为例,典型事件的评估结果验证了所述方法和指标体系的有效性和合理性,分析了常规机组爬坡速率及系统备用比例在防范风电爬坡事件不利影响方面的作用。     

项目经理在重大赛事项目中的作用分析

随着国家之间或城市之间竞争的逐渐加剧,一些国家或一些地方政府都对申办大型体育赛事显示出空前的热情。但是,并不是所有赛事都会给举办地的城市发展带来积极影响。本研究结合项目经理基本能力和重大赛事项目的特点,分析提出了项目经理在重大赛事项目中的5种作用:包括项目经理应参与场馆选址决策、应参与场馆建设规模与标准论证决策、在项目初期组建赛后经营团队参与规划设计、应与协调经营团队拓展场馆功能、核算全周期成本收益,并指出项目经理应努力发挥好这5个方面的作用,从而保障重大赛事项目取得全项目周期的成功。     

基于贝叶斯网络的群体性事件智能视频分析与判定技术

为提高群体性事件智能视频监控的可靠性,提出在传统图像处理算法实现目标检测和特征提取的基础上,采用贝叶斯网络进一步对事件特征进行分析,重点介绍人群聚集事件判定贝叶斯网络建模、参数设置和推理等关键过程,并以具体的实例进行验证。结果表明:该方法具有建模简单、对智能视频分析算法依赖性低、鲁棒性和移植性强等特点,对建立可靠的智能视频监控系统具有参考价值。     

基于物联网的危机事件应急物资保障建设思考

为在危机处理环节能精确、快速实现应急物资保障,将物联网技术运用于军队危机事件应急救援物资保障网链建设。在分析物联网技术特点、功能优势的基础上,结合危机事件应急救援物资保障需求实际,提出基于物联网技术的军队应急救援物资保障网链建设对策建议。该研究可为建设军事物联网提供一定的参考。     

Using naturalistic driving data to explore the association between traffic safety-related events and crash risk at driver level

There has been considerable research conducted over the last 40 years using traffic safety-related events to support road safety analyses. Dating back to traffic conflict studies from the 1960s these observational studies of driver behavior have been criticized due to: poor quality data; lack of available and useful exposure measures linked to the observations; the incomparability of self-reported safety-related events; and, the difficulty in assessing culpability for safety-related events. This study seeks to explore the relationships between driver characteristics and traffic safety-related events, and between traffic safety-related events and crash involvement while mitigating some of those limitations. The Virginia Tech Transportation Institute 100-Car Naturalistic Driving Study dataset, in which the participants’ vehicles were instrumented with various cameras and sensors during the study period, was used for this study. The study data set includes 90 drivers observed for 12–13 months driving. This study focuses on single vehicle run-off-road safety-related events only, including 14 crashes and 182 safety-related events (30 near crashes, and 152 crash-relevant incidents). Among the findings are: (1) drivers under age 25 are significantly more likely to be involved in safety-related events and crashes; and (2) significantly positive correlations exist between crashes, near crashes, and crash-relevant incidents. Although there is still much to learn about the factors affecting the positive correlation between safety-related events and crashes, a Bayesian multivariate Poisson log-normal model is shown to be useful to quantify the associations between safety-related events and crash risk while controlling for driver characteristics.