Performance measurement and classification data in DEA: Input-oriented model

This paper presents an improved efficiency measurement tool by modifying the existing data envelopment analysis methodology to permit the incorporation of expert knowledge. A previous paper examined the inclusion of such knowledge within the additive model. This information appeared in the form of a binary classification of a subset of the decision making units under study (e.g. good versus poor performers). In the current paper, we extend this logic to the input-oriented radial projection model. We demonstrate that the inclusion of this and other forms of expert judgment can improve the performance of the DEA tool in the sense that the efficiency scores are more in line with expert/management beliefs.     

Predictive Bayesian Microbial Dose-Response Assessment Based on Suggested Self-Organization in Primary Illness Response: Cryptosporidium parvum

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.     

A spatiotemporal auto-regressive moving average model for solar radiation

Summary.  To investigate the variability in energy output from a network of photovoltaic cells, solar radiation was recorded at 10 sites every 10 min in the Pentland Hills to the south of Edinburgh. We identify spatiotemporal auto-regressive moving average models as the most appropriate to address this problem. Although previously considered computationally prohibitive to work with, we show that by approximating using toroidal space and fitting by matching auto-correlations, calculations can be substantially reduced. We find that a first-order spatiotemporal auto-regressive (STAR(1)) process with a first-order neighbourhood structure and a Matern noise process provide an adequate fit to the data, and we demonstrate its use in simulating realizations of energy output.     

Bayesian inference for a discretely observed stochastic kinetic model

The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observed by means of discrete-time sampling systems, which are often limited in their completeness. In this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes behaviour typical of many biochemical networks which exhibit auto-regulatory behaviour. Various MCMC algorithms are described and their performance evaluated in several data-poor scenarios. An algorithm based on an approximating process is shown to be particularly efficient.     

Project Jump: Young People's Perspectives on a Sexual Health Drama Project for Hard to Reach Young People

This article explores the qualitative process findings from an evaluation of Project Jump — a sexual health drama project for hard to reach young people. Project Jump aimed to enable young people to consider their sexual behaviour and its impact and consequence on other people and themselves. The research aimed to capture the experiences and perceptions of young people's involvement in the project, particularly in relation to the use of drama as a medium for learning. Findings from young people demonstrate that drama can offer an important alternative to traditional health promotion in that young people articulated positive aspects of their involvement. These included enthusiastic participation, empowerment and sexual health skills acquisition. In addition, critical areas for consideration for policy‐makers and practitioners in employing a drama‐based approach particularly in relation to effective identification, engagement and ongoing follow‐up activity with vulnerable groups are highlighted. © 2006 University of the West of England. Journal compilation © 2006 National Children's Bureau.     

Communication of risk: health hazards from mobile phones

Summary. Possible health hazards from mobile phones arise from the use of the phones themselves and via the base stations that relay signals. Except for an increase in traffic accidents induced by the use of mobile phones in cars the evidence for a health hazard is at most indirect, but it cannot be entirely dismissed; the phones have not been widely used for sufficiently long for direct epidemiological studies to have high sensitivity for detecting any induced incidence of cancer, for example. The background and evidence are briefly reviewed and the steps taken in the UK to make information widely available described.     

On the Third Law of Demand

The Alchian and Allen theorem predicts that it will be harder to find "good" apples in the State of Washington, a prime apple-growing region, than in, say, New York City, where the addition of shipping charges makes "bad" apples comparatively more expensive. We recast the theorem as a testable proposition by explicitly taking the supply side into account and identifying plausible scenarios in which a fixed cost either has no effect on the relative prices of high and low quality grades of the same good in distant markets or, indeed, causes more of the bad apples to be shipped out.     

Complex belief-desire reasoning in children

Previous research concerned with children's belief-desire psychology has examined the capacity to predict or interpret action on the basis of the implicit proposition that ‘when an actor desires a particular end and believes that a particular action will achieve that end, he or she will undertake that action’. The limitations of this formulation for understanding acts of omission are outlined and an elaborated version of belief-desire psychology introduced. This version holds that ‘when an actor desires a particular end and believes that a particular action will achieve that end, and when it is believed that there are no co-occurring outcomes of that action whose avoidance is desired more highly than is the originally conceived end, then the actor will undertake the action which will satisfy the original desire’. An experiment is reported which examines 4-, 5, and 7-year-olds' ability to predict story characters' actions on the basis of either their true or false beliefs concerning undesirable outcomes associated with the pursuit of a desired end. Children of all age-groups provided evidence of understanding the elaborated version of belief-desire psychology. However, a significant improvement was noted between the ages of 4 and 7 years in the ability to understand circumstances involving false beliefs.     

Pulling together: building a community debriefing team.

1. Research shows that many emergency workers are affected physically and emotionally by critical incident stress. 2. Debriefings conducted by trained team members are an effective method to mitigate the impact of critical incident stress. A debriefing is a structured, time-limited group intervention. 3. Cooperation among community agencies is essential for the development and effective functioning of a critical incident stress debriefing team. 4. Several teams in Illinois have organized to form a Critical Incident Stress Debriefing Network. The Illinois network is part of an international organization composed of critical incident stress debriefing providers.