Spatial Risk Analysis of Power Systems Resilience During Extreme Events

The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real‐time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience‐based decisions for risk mitigation. The IEEE 24‐bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.     

Human Agency in Disaster Planning: A Systems Approach

Current approaches to risk management place insufficient emphasis on the system knowledge available to the assessor, particularly in respect of the dynamic behavior of the system under threat, the role of human agents (HAs), and the knowledge available to those agents. In this article, we address the second of these issues. We are concerned with a class of systems containing HAs playing a variety of roles as significant system elements—as decisionmakers, cognitive agents, or implementers—that is, human activity systems. Within this family of HAS, we focus on safety and mission‐critical systems, referring to this subclass as critical human activity systems (CHASs). Identification of the role and contribution of these human elements to a system is a nontrivial problem whether in an engineering context, or, as is the case here, in a wider social and public context. Frequently, they are treated as standing apart from the system in design or policy terms. Regardless of the process of policy definition followed, analysis of the risk and threats to such a CHAS requires a holistic approach, since the effect of undesirable, uninformed, or erroneous actions on the part of the human elements is both potentially significant to the system output and inextricably bound together with the nonhuman elements of the system. We present a procedure for identifying the potential threats and risks emerging from the roles and activity of those HAs, using the 2014 flooding in southwestern England and the Thames Valley as a contemporary example.     

A Framework to Understand Extreme Space Weather Event Probability

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well‐being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst ) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments.     

企业组织中人力资本道德风险因素分析

基于市场里的企业是“一个人力资本与非人力资本的特别合约”的观点,就人力资本的道德风险问题进行了研究。认为影响人力资本道德风险的因素主要有诚实履行合约后的正常收益、道德风险行为被发现的概率、贴现因子、道德风险行为的额外收益以及道德风险行为被发现后的次优收益。并且以预期收益为目标建立了数学模型,分析人力资本道德风险行为动机与影响因素之间的关系,提出了相关的激励、约束及协作策略。最后,讨论了随机因素的影响。     

Behavioral pathways to private well risk mitigation: A structural equation modeling approach

Complex, multihazard risks such as private groundwater contamination necessitate multiannual risk reduction actions including seasonal, weather-based hazard evaluations. In the Republic of Ireland (ROI), high rural reliance on unregulated private wells renders behavior promotion a vital instrument toward safeguarding household health from waterborne infection. However, to date, pathways between behavioral predictors remain unknown while latent constructs such as extreme weather event (EWE) risk perception and self-efficacy (perceived behavioral competency) have yet to be sufficiently explored. Accordingly, a nationwide survey of 560 Irish private well owners was conducted, with structural equation modeling (SEM) employed to identify underlying relationships determining key supply management behaviors. The pathway analysis (SEM) approach was used to model three binary outcomes: information seeking, post-EWE action, and well testing behavior. Upon development of optimal models, perceived self-efficacy emerged as a significant direct and/or indirect driver of all three behavior types—demonstrating the greatest indirect effect (β = −0.057) on adoption of post-EWE actions and greatest direct (β = 0.222) and total effect (β = 0.245) on supply testing. Perceived self-efficacy inversely influenced EWE risk perception in all three models but positively influenced supply awareness (where present). Notably, the presence of a vulnerable (infant and/or elderly) household member negatively influenced adoption of post-EWE actions (β = −0.131, p = 0.016). Results suggest that residential and age-related factors constitute key demographic variables influencing risk mitigation and are strongly mediated by cognitive variables—particularly self-efficacy. Study findings may help contextualize predictors of private water supply management, providing a basis for future risk-based water interventions.     

外商直接投资影响因素的偏最小二乘回归建模分析

改革开放的20多年来,我国的外商直接投资逐年增加,对我国经济的快速发展发挥了重要的作用。而影响外商直接投资的因素有很多,不同的因素变量之间往往存在多重共线性或近似多重共线性关系,使得分析问题的难度加大。本文运用新型的多元统计数据分析方法——偏最小二乘(PLS)回归方法(既克服了传统方法的不足,又有效地消除了因素变量之间的多重共线性),分析了影响我国外商直接投资的因素,以及其影响程度,为我国进一步引进外商直接投资提供了有益的定量依据。     

Challenges to the Acceptance of Probabilistic Risk Analysis

This paper discusses a number of the key challenges to the acceptance and application of probabilistic risk analysis (PRA). Those challenges include: (a) the extensive reliance on subjective judgment in PRA, requiring the development of guidance for the use of PRA in risk-informed regulation, and possibly the development of robust or reference prior distributions to minimize the reliance on judgment; and (b) the treatment of human performance in PRA, including not only human error per se but also management and organizational factors more broadly. All of these areas are seen as presenting interesting research challenges at the interface between engineering and other disciplines.     

移动短视频用户体验影响因素及作用机理研究——基于抖音APP用户的调查

随着短视频行业发展进入下半场,如何提升和完善用户体验成为各短视频平台可持续发展的关键。以用户体验五要素模型为基础,构建移动短视频用户体验模型,运用结构方程方法对模型的适用性进行检验,深入挖掘移动短视频用户体验的主要影响因素,为企业和相关平台方优化用户体验、提高用户留存率提供参考。研究发现：视觉吸引力、界面设计、交互、内容、需求满足对用户体验具有显著的直接影响,且这五个变量通过中介变量情感感知间接影响用户体验。基于此,短视频平台在秉持内容制胜的同时还需丰富互动形式,以优秀的界面设计和深厚的情感,抓住用户眼球、引发用户共鸣、满足用户多元需求,以此构建健康的平台生态圈。     

农村居民消费不平等的微观结构分析

提出了个体微观数据基尼系数的组群、要素统一分解式,并利用该分解式考察消费结构、区域结构和收入不平等对农村居民消费不平等的影响.采用了2009年福建省农村居民生活状况调查数据进行分析,得出结论:食品、衣着类消费的增长可以降低农村居民的消费不平等,其中谷物、薯类、食用油、蔬菜及制品、肉禽蛋奶及制品的消费增长对消费公平性的提高产生积极的作用;组内不平等在总体消费不平等中占80％以上,消费差异主要表现为内部的差异;农村居民的消费不平等受收入不平等影响显著.     

陕西省苹果汁出口影响因素分析

结合陕西最新苹果产业发展状况,分析了其苹果汁出口在全国的相对优势地位。利用多年数据分析影响陕西苹果汁出口额的主要因子:国际环境、国际苹果汁出口均价、成本、苹果汁出口量等,同时利用SPSS数据处理软件,拟合了陕西苹果汁出口额与众多影响因素的回归模型,通过各种检查,拟合效果良好。