Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Perceived Risks from Radiation and Nuclear Testing Near Semipalatinsk, Kazakhstan: A Comparison Between Physicians, Scientists, and the Public

Determining the difference in perception of risk between experts, or more educated professionals, and laypeople is important so that a potential hazard can be effectively communicated to the public. Many surveys have been conducted to better understand the difference between expert and public opinions, and often laypeople exhibit higher perceptions of risk to hazards in comparison to experts. This is especially true when health risk is due to radiation, nuclear power, and nuclear waste. This article focuses on one section of a risk perception survey given to two groups of individuals with a more specialized education (scientists and physicians) and laypeople (villagers) in the Semipalatinsk region of Kazakhstan. All of these groups live near the former Soviet nuclear test site. Originally, it was expected that the scientists and physicians would have similar perceptions of radiation risk, while the public perceptions would be higher, but this was not always the case. For example, when perceptions of risk pertain to the health impacts of nuclear testing or the dose-response nature of radiation exposure, the physicians tend to agree with the laypeople, not the scientists. The villagers are always the most risk-averse group, followed by the physicians and then the scientists. These differences are likely due to different frames of reference for each of the populations.     

The Incremental Group Testing Model for Gap Closing in Sequencing Long Molecules

In this paper, we propose the incremental group testing model for the gap closing problem, which assumes that we can tell the difference between the outcome of testing a subset S, and the outcome of testing S {x}. We also give improvements over currently best results in literature for some other models.     

Influence of Safety Measures on the Risks of Transporting Dangerous Goods Through Road Tunnels

Quantitative risk assessment (QRA) models are used to estimate the risks of transporting dangerous goods and to assess the merits of introducing alternative risk reduction measures for different transportation scenarios and assumptions. A comprehensive QRA model recently was developed in Europe for application to road tunnels. This model can assess the merits of a limited number of "native safety measures." In this article, we introduce a procedure for extending its scope to include the treatment of a number of important "nonnative safety measures" of interest to tunnel operators and decisionmakers. Nonnative safety measures were not included in the original model specification. The suggested procedure makes use of expert judgment and Monte Carlo simulation methods to model uncertainty in the revised risk estimates. The results of a case study application are presented that involve the risks of transporting a given volume of flammable liquid through a 10-km road tunnel.     

Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression

We propose a novel statistic for conducting joint tests on all the structural parameters in instrumental variables regression. The statistic is straightforward to compute and equals a quadratic form of the score of the concentrated log–likelihood. It therefore attains its minimal value equal to zero at the maximum likelihood estimator. The statistic has a χ² limiting distribution with a degrees of freedom parameter equal to the number of structural parameters. The limiting distribution does not depend on nuisance parameters. The statistic overcomes the deficiencies of the Anderson–Rubin statistic, whose limiting distribution has a degrees of freedom parameter equal to the number of instruments, and the likelihood based, Wald, likelihood ratio, and Lagrange multiplier statistics, whose limiting distributions depend on nuisance parameters. Size and power comparisons reveal that the statistic is a (asymptotic) size–corrected likelihood ratio statistic. We apply the statistic to the Angrist–Krueger (1991) data and find similar results as in Staiger and Stock (1997).     

Reliability Analysis for Hazardous Waste Treatment Processes

The reliability of a treatment process is addressed in terms of achieving a regulatory effluent concentration standard and the design safety factors associated with the treatment process. This methodology was then applied to two aqueous hazardous waste treatment processes: packed tower aeration and activated sludge (aerobic) biological treatment. The designs achieving 95 percent reliability were compared with those designs based on conventional practice to determine their patterns of conservatism. Scoping-level treatment costs were also related to reliability levels for these treatment processes. The results indicate that the reliability levels for the physical/chemical treatment process (packed tower aeration) based on the deterministic safety factors range from 80 percent to over 99 percent, whereas those for the biological treatment process range from near 0 percent to over 99 percent, depending on the compound evaluated. Increases in reliability per unit increase in treatment costs are most pronounced at lower reliability levels (less than about 80 percent) than at the higher reliability levels (greater than 90 percent, indicating a point of diminishing returns. Additional research focused on process parameters that presently contain large uncertainties may reduce those uncertainties, with attending increases in the reliability levels of the treatment processes.     

A fair result in foul weather

The Duckworth–Lewis method for adjusting targets in rain-interrupted one-day cricket matches is used throughout the world, but, as Frank Duckworth explains, he originally came to statistics from physics via metallurgy, and only thought of applying statistical methods to sport when their power became apparent to him during his career in the nuclear energy industry     

The Sociology of Mental Health: A Brief Review of Major Approaches

The article emphasises the importance of making sense of the theoretical debate in the sociology of mental health in order to 'position' the wide range of studies that have contributed to this field within three main approaches. The article indicates ways in which various studies have proved highly influential and continue to form the basis for research, policy and practice. Sociological concepts such as stigma continue to resonate as they highlight the sense in which negative social attitudes often make life harder for those who are already experiencing distress. The politics of risk in mental health, which has become a particularly powerful force in recent years, has made the prevailing climate more and not less stigmatising for those identified with 'mental illness'. The article concludes by arguing that the sociology of mental health continues to offer the conceptual and theoretical foundation from which negative associations can be challenged and overturned.