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The increase of exposure to toxic materials and hazardous chemicals is a major concern due to the adverse effect on human health. Among the major concerns of toxicologists is to determine acceptable levels of exposure to hazardous substances. Current approaches often evaluate each endpoint and stressor individually. We propose a novel method to simultaneously determine the Benchmark Dose Tolerable Region (BMDTR) for multiple endpoint and multiple stressor studies by adopting a Bayesian approach. A main concern while assessing the combined toxicological effect of a chemical mixture is the anticipated type of the combined action (i.e. synergistic or antagonistic); thus it was essential to account for interaction effects to handle this situation, imposing more challenges due to the non-linearity of the tolerable region. The proposed method will be evaluated using two approaches, the first one using the estimated value of the posterior median and the second approach using all MCMC samples from the posterior distribution. Furthermore, we propose a new method to determine the endpoint probabilities for each endpoint, which reflects the importance of each endpoint in helping determining the boundaries of the benchmark dose tolerable region (BMDTR). [ABSTRACT FROM AUTHOR]

Bayesian inclusion probabilities have become a popular tool for variable assessment. From a frequentist perspective, it is often difficult to evaluate these probabilities as typically no Type I error rates are considered, neither are any explorations of power of the methods given. This paper considers how a frequentist may evaluate Bayesian inclusion probabilities for screening predictors. This evaluation looks at both unrestricted and restricted model spaces and develops a framework which a frequentist can utilize inclusion probabilities that preserve Type I error rates. Furthermore, this framework is applied to an analysis of the Arabidopsis thaliana with respect to determining quantitative trait loci associated with cotelydon opening angle. [ABSTRACT FROM AUTHOR]

This paper introduces a framework for incorporating uncertainty in water supply system models that uses Bayesian statistics and mixed-integer programming. The output of the framework includes the most probable least cost solution, the probability of feasibility for a given solution, component probabilities for each decision, and a distribution of the optimal objective function value. The method is applied to the problem of developing a water supply system design for Israel, Jordan, and the Palestinian territories. The method allows decision makers to evaluate various alternatives for a water supply plan that incorporates uncertainties in future demand and costs. The design of a water supply plan is a concern with properties that are distinct from traditional approaches to the design of water distribution systems; namely, local engineering decisions concerning pipe diameters and water pressure are not explicitly modeled, but large-scale decisions concerning the construction of water conveyances (pipes, canals, and tunnels) and sources (desalination plants) are the focus in the model. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Individuals with disabilities often face stigma and negative social interactions. Human-animal interaction literature suggests that an individual paired with an animal will be perceived differently than an individual alone. Although people with disabilities report increases in social interactions when with assistance dogs, the reasons for this remain unclear. One possibility is that attitudes toward people with disabilities are altered by the presence of assistance dogs, thus affecting the social behaviors of the perceiver. This study examines whether implicit attitudes toward individuals with disabilities differ in the presence of an assistance dog. METHOD: College students (N = 244) completed the Attitudes of Adults to Dogs scale, an item assessing dog ownership, and the Disabilities and Assistance Dog Implicit Association Test (IAT). RESULTS: A 1-sample t test demonstrated a significant IAT effect, t(240) = 3.62, p < .001, with a positive implicit bias observed toward an individual with a disability when paired with an assistance dog over the individual alone. White individuals were more likely than Black individuals to hold positive implicit attitudes toward an individual with a disability paired with a dog, F(2, 238) = 3.18, p = .04. There were no significant differences in IAT D scores based on gender or dog ownership. IMPLICATIONS: This study extends previous research regarding social interactions for individuals with disabilities who are paired with assistance dogs. Increases in positive implicit attitudes toward an individual with a disability paired with a dog may explain these changes in social interactions. Dogs may serve as a social lubricant, increasing positive social interactions for individuals with disabilities. [ABSTRACT FROM AUTHOR]