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The role of information processing in understanding people's responses to risk information has recently received substantial attention. One limitation of this research concerns the unavailability of a validated questionnaire of information processing. This article presents two studies in which we describe the development and validation of the Information‐Processing Questionnaire to meet that need. Study 1 describes the development and initial validation of the questionnaire. Participants were randomized to either a systematic processing or a heuristic processing condition after which they completed a manipulation check and the initial 15‐item questionnaire and again two weeks later. The questionnaire was subjected to factor reliability and validity analyses on both measurement times for purposes of cross‐validation of the results. A two‐factor solution was observed representing a systematic processing and a heuristic processing subscale. The resulting scale showed good reliability and validity, with the systematic condition scoring significantly higher on the systematic subscale and the heuristic processing condition significantly higher on the heuristic subscale. Study 2 sought to further validate the questionnaire in a field study. Results of the second study corresponded with those of Study 1 and provided further evidence of the validity of the Information‐Processing Questionnaire. The availability of this information‐processing scale will be a valuable asset for future research and may provide researchers with new research opportunities.

The heat wave this summer, at the latest, has made the absence of water a socially acceptable issue of debate in European regions where otherwise little concern has been in place about the availability of water. Against the background of this topicality, this text will pursue the questions of "How is water actually known?" and "In what form can water be made the subject of quotidian as well as cultural anthropological knowledge?" Making Kirsten Hastrups "Waterworlds" project a starting point and based on current empirical findings, the text elaborates on the manifold heuristic potentials of existing work and discusses new perspectives for an anthropology of the present and the future that makes water its explicit subject.

AbstractThis paper describes a comprehensive simulation modeling approach to the problem of locating warehousing facilities in a fashion that minimizes the cost associated with operating a multi‐product, multi‐source, multi‐destination distribution system. The digital simulation model presented in the study is derived within an "industrial dynamics" framework, utilizes input from an existing management information system, and employs a number of relatively simple heuristic procedures to analyze various alternative warehousing networks. Simulation results, in terms of the distribution costs associated with various warehouse locations, are presented for cases involving the effect of provision of a 100% service level, the effect of constraining product availability and/or inventory capacities at various warehouses, and the effect of deleting various warehouses from the existing warehouse network.

The pedagogical value of experiential learning, or "learning-by-doing," has led to the widespread use of simulations and games in the social sciences and other disciplines. Despite some questions concerning the effective transmission of factual information through simulations and games, their value as heuristic devices in teaching is based on the experience gained by students in adopting strategies and making decisions in a group context, experiences so varied that they would be impossible to relate through conventional classroom techniques. The pressures and constraints of a simulated political environment challenge participants to (1) confront the limited availability of options and approaches for resolving problems; (2) develop a deeper understanding of the concepts, principles, and procedures involved; and (3) formulate and propose novel solutions that may not have otherwise occurred to them.

Scholarship on security communities often invokes a common goal: for war to become unthinkable. Unthinkable here means impossible, and states are considered to be most secure when war is unthinkable between them. Interestingly, the term unthinkable appears in policy discourse with nearly the opposite meaning, referring to wars that are eminently possible but horrifying to contemplate, such as war with a nuclear Iran. Taking this discrepancy as my starting point, I propose that the social phenomenon of unthinkability is not well understood and that a deeper understanding of it can point toward new directions for research on security communities. I conceptualize unthinkability along two dimensions, empirical availability and normative acceptability, combining these to create four distinct types of unthinkability. I then use this typology as a heuristic device to identify research directions on security communities and on the phenomenon of unthinkable war.

"We investigate whether the theory of strategic voting can explain voting behavior in a fairly common type of political system, multi-party systems with proportional representation, minimum vote thresholds, and coalition governments. In this paper, we develop a formal (computational) strategic voting game and show in a simulation that the model produces election scenarios and outcomes with desirable characteristics as well as different opportunities for strategic voting. We then test the decision-theoretic model in a laboratory experiment, taking into account both sophisticated and heuristic decision strategies. Participants with a purely instrumental (financial) motivation voted in a series of 25 independent elections. The availability of polls and coalition signals by parties was manipulated. The results show that voters are frequently able to make optimal or strategic vote decisions, but that voters also rely on simple decision heuristics and are highly susceptible to coalition signals by parties." (author's abstract)

Despite relatively low crime rates, the Irish public believes itself to be experiencing a law and order crisis. In this article, it is argued that a plausible explanation for the public misperception is the distorted image of crime in the media. A sample of over 2000 Irish newspaper articles dealing with crime is analysed and it is argued that there are four ways in which the press skews the representation of crime. These are the bias towards extreme and atypical offences in terms of frequency, the bias towards those extreme offences in terms of newspaper space, the bias towards stories involving vulnerable victims and invulnerable offenders and the bias towards pessimistic accounts of the criminal justice system generally. By incorporating the cognitive heuristic of `availability', an elegant explanation of the relationship between biased media accounts and distorted public opinion can be offered.

What is the role of arms in insurgency? Despite growing attention to the study of conflict and non-state belligerents, the linkages between weapons and armed conflict have remained under-researched. This paper explores practices and processes of firearms availability and control in insurgencies and argues that these should be understood in mutual relation with the constitution and distribution of authority. The contributions of the article are twofold. By conceptually systematizing recent shifts in the literature on civil wars and elaborating on small arms and light weapons research, it offers a novel heuristic framework to understand weapons-insurgency relations that revolves around the concept of firearms as "meta-resources" and gestures towards non-deterministic approaches. Second, based on empirical analysis conducted through two embedded case studies, it argues that patterns of authority in the insurgencies taken into consideration in Myanmar and Ukraine dialectically emerged with processes of arms acquisition by armed non-state actors.

Using policy cycle model as a heuristic, this article studies Indian, Brazilian, and South African engagement with Nationally Appropriate Mitigation Actions (NAMAs) by (a) comparing NAMA policy process and (b) identifying factors driving or limiting the framework's domestic application. India largely remained uninterested in NAMAs, Brazil aligned its domestic climate policy and NAMAs, while South Africa had a more nuanced engagement when formulating NAMAs. Four factors influenced these countries' NAMA engagements: the level and necessity of international support, the availability of domestic policy provisions to tackle climate change, the domestic institutional capacity to coordinate interministerial functioning, and the role of individuals in the institutional apparatus. As an international climate policy framework, studying NAMA engagement provides learnings for nationally determined contributions under the Paris Agreement for designing the instrument, ensuring clarity on support provisions for ratcheting up ambitions, and enhancing institutional capacity, to expedite transition from policy formulation to implementation and beyond.

This article examines information-search heuristics and communication patterns in an online forum of investors during a period of market uncertainty. Global connections, real-time communication, and technological sophistication have created an unpredictable market environment. As such, investors try to deal with semantic, strategic, and operational uncertainty by following heuristics that reduce information redundancy. In this study, we have tried to find traces of cognitive communication heuristics in a large-scale data set including 8 years of online posts (2004–2012) for a forum of Italian investors. We identified various market volatility conditions on a daily basis to understand the influence of market uncertainty on cognitive and communication processes. We found that investors communicated more dynamically when the market was unstable, while they were more prone to anchor heuristic when market uncertainty was invariant. Furthermore, abnormal market trends triggered more availability-based communication patterns. We also found that expertise matters. This would suggest that online communities need intelligent, context-specific tools to support partner selection and stimulate nonredundant communication.

Availability: Free download from the isoFinder project site: http://isofinder.sourceforge.net/ Web server: http://bioinfo2.ugr.es/IsoFinder ; Isochores are long genome segments relatively homogeneous in G+C. A heuristic algorithm based on entropic segmentation has been developed by our group, and a web server implementing all the required components is available. However, a researcher may want to perform batch processing of many sequences simultaneously in its local machine, instead of analyzing them on one by one basis through the web. To this end, standalone versions are required. We report here the implementation of two standalone programs, able to predict isochores at the sequence level: 1) a command-line version (IsoFinder) for Windows and Linux systems; and 2) a user-friendly version (IsoFinderWin) running under Windows. ; The IsoFinder project was supported by the Spanish Government (Grant No. BIO2005-09116-C03-01) and the Spanish Junta de Andalucía (Grants No. P06-FQM-01858, P07-FQM3163 and CVI-162).

We consider modeling and operational analysis of a generic asymmetric service-system situation in which (a) Red agents, potentially threatening, but possibly requiring assistance, arrive according to some partially known and possibly changing pattern in time and space; and (b) Reds are impatient: have effectively limited unknown deadlines or times of availability for Blue service, i.e., detection, classification, and attack in a military setting, or emergency assistance in other settings, such as medical care. We discuss various service options by Blue service agents and devise several approximations allowing one to compute efficiently proportions of tasks of different types that are successfully served or, more generally, if different rewards are associated with different types of tasks, the percentage of the possible reward gained. We suggest a heuristic policy for a Blue server to select the next task to perform and to decide how much time to allocate to that service. We discuss this and related policies for a number of specific examples.

An emerging prognostic and health management (PHM) technology has recently attracted a great deal of attention from academies, industries, and governments. The need for higher equipment availability and lower maintenance cost is driving the development and integration of prognostic and health management systems. PHM models depend on the smart sensors and data generated from sensors. This paper proposed a machine learning-based methods for developing PHM models from sensor data to perform fault diagnostic for transformer systems in a smart grid. In particular, we apply the Cuckoo Search (CS) algorithm to optimize the Back-propagation (BP) neural network in order to build high performance fault diagnostics models. The models were developed using sensor data called dissolved gas data in oil of the power transformer. We validated the models using real sensor data collected from power transformers in China. The results demonstrate that the developed meta heuristic algorithm for optimizing the parameters of the neural network is effective and useful ; and machine learning-based models significantly improved the performance and accuracy of fault diagnosis/detection for power transformer PHM.

Wireless communication is used in many different situations such as mobile telephony, radio and TV broadcasting, satellite communication, wireless LANs, and military operations. In each of these situations a frequency assignment problem arises with application specific characteristics. Researchers have developed different modeling ideas for each of the features of the problem, such as the handling of interference among radio signals, the availability of frequencies, and the optimization criterion. This survey gives an overview of the models and methods that the literature provides on the topic. We present a broad description of the practical settings in which frequency assignment is applied. We also present a classification of the different models and formulations described in the literature, such that the common features of the models are emphasized. The solution methods are divided in two parts. Optimization and lower bounding techniques on the one hand, and heuristic search techniques on the other hand. The literature is classified according to the used methods. Again, we emphasize the common features, used in the different papers. The quality of the solution methods is compared, whenever possible, on publicly available benchmark instances.