Twitter,incivility, and presidential communication: A theoretical incursion into spectacle and power

ABSTRACT

By approaching civility as an operational logic for democracy, we ask how incivility is a strategy related to power and domination, particularly from the president of the United States. We propose that Twitter is part of an infrastructure of incivility, through which structures and discursive mechanisms contribute to a devaluation of normative democratic discourses. Spectacle provides a theoretical framework to contextualize the forces at play in mediating our relations. Using President Trump’s Twitter use as a case study, we offer four propositions that together formulate a framework for theorizing the strategic use and deployment of incivility as an increasingly legitimate, yet problematic tool for democratic governance.     

A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods

Scour (localized erosion by water) is an important risk to bridges, and hence many infrastructure networks, around the world. In Britain, scour has caused the failure of railway bridges crossing rivers in more than 50 flood events. These events have been investigated in detail, providing a data set with which we develop and test a model to quantify scour risk. The risk analysis is formulated in terms of a generic, transferrable infrastructure network risk model. For some bridge failures, the severity of the causative flood was recorded or can be reconstructed. These data are combined with the background failure rate, and records of bridges that have not failed, to construct fragility curves that quantify the failure probability conditional on the severity of a flood event. The fragility curves generated are to some extent sensitive to the way in which these data are incorporated into the statistical analysis. The new fragility analysis is tested using flood events simulated from a spatial joint probability model for extreme river flows for all river gauging sites in Britain. The combined models appear robust in comparison with historical observations of the expected number of bridge failures in a flood event. The analysis is used to estimate the probability of single or multiple bridge failures in Britain's rail network. Combined with a model for passenger journey disruption in the event of bridge failure, we calculate a system‐wide estimate for the risk of scour failures in terms of passenger journey disruptions and associated economic costs.     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.     

A Decision Framework for Managing Risk to Airports from Terrorist Attack

This article presents an asset‐level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast‐resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life‐cycle cost considering a 10‐year service period.     

基于元网络分析的重大基础设施建设项目风险评估框架与实证

重大基础设施项目具有战略性、集成性、复杂性等特征，项目容易受到多种风险因素的综合影响，导致项目目标的偏离。现有风险评估与风险决策的方法缺乏对于风险因素、风险事件之间关联的分析。为了实现重大基础设施建设项目综合系统的风险评估，本文采用元网络分析方法，构建项目目标、风险事件和风险因素的交互模型，揭示重大基础设施风险事件发生机制的黑箱过程。风险评估过程中，通过多个网络叠加运算分析每个风险因素对于各种风险事件以及项目各目标的影响情况，改进了以往仅对风险因素单一影响程度的风险评估方法。同时，本研究选择我国某河流水电站过坝运输项目方案比选的风险评估过程验证方法的适用性。     

Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically‐oriented models to advanced physical‐flow‐based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations of models to use when analyzing large‐scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed.     

Impact of socio-economic infrastructure investments on income inequality in Iran

One of the main subjects, governments have been facing is fair distribution of income, and making effort to improve it. In this study, we evaluated the effects of economic (energy, water, ICT) and social (health, education) infrastructure expenses on income inequality in the Iranian provinces for the period of 2007–2016 by the panel corrected standard errors (PCSE) model. The results show that social and economic infrastructures improvements reduce income inequality. However, the magnitude of these effects varies. Investment on education, healthcare, communication technology, energy, and water infrastructures has the greatest impact on income inequality reduction, respectively. Therefore, in order to reduce inequality in deprived areas, combination and optimal allocation of economic and social infrastructures should be considered.     

The Multiscale Importance of Road Segments in a Network Disruption Scenario: A Risk‐Based Approach

This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real‐world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.     

Impact of Water Level Rise on Urban Infrastructures: Washington,DC, and Shanghai as Case Studies

The observed global sea level rise owing to climate change, coupled with the potential increase in extreme storms, requires a reexamination of existing infrastructural planning, construction, and management practices. Storm surge shows the effects of rising sea levels. The recent super storms that hit the United States (e.g., Hurricane Katrina in 2005, Sandy in 2012, Harvey and Maria in 2017) and China (e.g., Typhoon Haiyan in 2010) inflicted serious loss of life and property. Water level rise (WLR) of local coastal areas is a combination of sea level rise, storm surge, precipitation, and local land subsidence. Quantitative assessments of the impact of WLR include scenario identification, consequence assessment, vulnerability and flooding assessment, and risk management using inventory of assets from coastal areas, particularly population centers, to manage flooding risk and to enhance infrastructure resilience of coastal cities. This article discusses the impact of WLR on urban infrastructures with case studies of Washington, DC, and Shanghai. Based on the flooding risk analysis under possible scenarios, the property loss for Washington, DC, was evaluated, and the impact on the metro system of Shanghai was examined.     

农村水利设施整体性供给与社会资本的关联效应测度

农村水利设施的有效供给是实现农村治理能力现代化的现实载体。通过梳理公共品整体性供给与社会资本的既有文献,进而以博弈论诠释农村水利设施整体性供给的行为选择。同时建构出社会资本对农村水利设施整体性供给的Logit回归模型,借助于CFPS中关于“农村水利基础设施”的数据证据进行分析。研究发现,社会资本的存量对农村水利基础设施整体性供给起到积极作用,其中社会网络、社会参与以及农户个体特征对整体性供给产生显著影响。为此,通过营造农民整合参与的有利环境,增强农村社会资本的建设,有效培育和发展农村精英,以此来实现农村水利设施整体性供给的有效性。