A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation‐based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source‐to‐source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.     

NONLINEAR TUBE-FITTING FOR THE ANALYSIS OF ANATOMICAL AND FUNCTIONAL STRUCTURES

We are concerned with the estimation of the exterior surface and interior summaries of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT) and to a white-matter tract image produced using diffusion tensor imaging (DTI).     

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1—Decision Support System

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human–natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.     

Measuring the Effect of Sexual Health Education Training in Professionals: Structure of the Sexual Health Education for Professionals Scale (SHEPS) Among Marriage and Family Therapy Graduate Students

Marriage and family therapists and sexual health therapists are likely to receive training in graduate school that prepares them to encounter sexual concerns among clients, but there are few standard ways to assess the efficacy of this training. The Sexual Health Education for Professionals Scale (SHEPS) was developed to address this deficit. In this preliminary study, 163 marriage and family therapy graduate students completed the SHEPS prior to starting a graduate course in assessing and treating sexual concerns. Exploratory factor analyses indicate that the SHEPS subscales have good psychometric properties. The Skills and Knowledge subscales have factors labeled Typical Clients, Special Clients, Conservative Clients, and Ethically Complicated Clients. The Attitudes subscale had factors called General Sexual Attitudes, Valuing Sexual Health Training, Open to Providing Sexual Help, and Conservatism. This new instrument may be used to assess education and training of sexual health and marriage and family therapists. Larger sample sizes and longitudinal studies are needed in future.     

In the right place at the right time: electronic tagging and problems of social order/disorder

This paper explores the relationship between technology and problems of social order/disorder in the context of discussions of surveillance and ‘virtuality’. The emphasis is on understanding the connections between technology and social relations in areas where issues of social order/disorder are a prominent feature of concern and where one can identify the emergence of new regimes of virtual control which are directed at solving the (supposed) deficits in order or the threats posed to it. Rather than constituting a ‘technical fix’ for the problems of social order/disorder, it is argued that forms of virtual control both presuppose a reconstruction of social order and at the same time aim to effect a suppression of disorder. Focusing in particular on various manifestations of electronic tagging from prisoners to babies, from retail goods to works of art, from television programmes to Personal Identification Numbers—the paper argues that these share a problematic which interrelates technology, order/disorder, subjects/objects, time, and space. It thus seeks to generalize the concept of electronic tagging, to regard it as a practice rather than a specific set of artefacts. Moreover, in contrast to the negative, panoptic reading of tagging technologies, the paper considers the active public participation in systems of surveillance and thereby the more positive or productive exercises of power which they may be taken to constitute.     

Religion and subjective well-being among the elderly in China

Evidence from developed and developing countries alike demonstrates a strongly positive relationship between religiosity and happiness, particularly for women and particularly among the elderly. Using survey data from the oldest old in China, we find a strong negative relationship between religious participation and subjective well-being in a rich multivariate logistic framework that controls for demographics, health and disabilities, living arrangements, wealth and income, lifestyle and social networks, and location. In contrast to other studies, we also find that religion has a larger effect on subjective well-being on men than women.     

Cooperation and Knowledge Transfer within Buyer–Supplier Relationships: The Moderating Properties of Trust,Relationship Duration and Supplier Performance*

This paper examines the effect of relational factors on knowledge transfer within strategic buyer–supplier exchange. Prior research examining inter‐firm knowledge transfer has focused almost exclusively on horizontal forms of governance such as strategic alliances and joint ventures, whilst research on vertical forms, such as buyer–supplier relationships, is limited. We test the effect of four important relational properties: cooperation, trust, relationship duration and supplier performance. Quantitative data, gathered from 104 UK manufacturing firms in eight industry sectors, are used to analyse the hypothesized relationships through a moderated hierarchical regression model. Our study provides support for the importance of considering relational factors in the transfer of knowledge at the inter‐organizational level. In particular, the results indicate that knowledge transfer is positively influenced by the extent of cooperation, but that this relationship is moderated by the level of trust and the performance of the supplier firm. Managerial implications for these findings and future directions for research are then offered.     

Predicting treatment efficacy via quantitative magnetic resonance imaging: a Bayesian joint model

The prognosis for patients with high grade gliomas is poor, with a median survival of 1 year. Treatment efficacy assessment is typically unavailable until 5-6 months post diagnosis. Investigators hypothesize that quantitative magnetic resonance imaging can assess treatment efficacy 3 weeks after therapy starts, thereby allowing salvage treatments to begin earlier. The purpose of this work is to build a predictive model of treatment efficacy by using quantitative magnetic resonance imaging data and to assess its performance. The outcome is 1-year survival status. We propose a joint, two-stage Bayesian model. In stage I, we smooth the image data with a multivariate spatiotemporal pairwise difference prior. We propose four summary statistics that are functionals of posterior parameters from the first-stage model. In stage II, these statistics enter a generalized non-linear model as predictors of survival status. We use the probit link and a multivariate adaptive regression spline basis. Gibbs sampling and reversible jump Markov chain Monte Carlo methods are applied iteratively between the two stages to estimate the posterior distribution. Through both simulation studies and model performance comparisons we find that we can achieve higher overall correct classification rates by accounting for the spatiotemporal correlation in the images and by allowing for a more complex and flexible decision boundary provided by the generalized non-linear model.     

Children's Anger Attribution Bias: Relations to Family Environment and Social Adjustment

We examined the relations of caregiver depression and family instability to preschool children's anger attribution bias and emotion attribution accuracy on a test of emotion situation knowledge. After controlling for age, gender, and verbal ability, caregiver depression and family instability predicted children's anger attribution bias but not the overall accuracy of their emotion attributions. We also divided children into groups low and high on teacher reports of aggression and groups low and high on teacher reports of peer rejection and examined the anger attribution bias of these groups. For boys but not girls, greater anger attribution bias predicted higher levels of aggression. For all children, greater anger attribution bias predicted higher levels of peer rejection. Results suggest that the misattribution of anger to others may be an important component of some children's early emotional and social difficulties.     

BBC Radio 4 and the experiential dimension of disability

In April 1998, BBC Radio 4’s programmes were rescheduled and a commitment was given that disability would become a mainstream issue for the network. Does He Take Sugar?, the network’s weekly programme which presented in‐depth treatment of disability issues was dropped. You and Yours, Radio 4’s weekday consumerist programme, was given the remit to include disability‐related coverage in its content. While mainstreaming yielded the possibility of increased coverage, the accompanying risk was that insightful treatment of disability would be lost. However, findings from an analysis of the series No Triumph, No Tragedy demonstrate that, post mainstreaming, meaningful exploration of disability continued on Radio 4. Crucial to this, it is argued, is the fact that the series was conducted by a disabled presenter.