Estimating Consumer Exposure to PFOS and PFOA

Perfluorinated compounds have been used for more than 50 years as process aids, surfactants, and for surface protection. This study is a comprehensive assessment of consumer exposure to perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) from a variety of environmental and product-related sources. To identify relevant pathways leading to consumer exposure to PFOS and PFOA a scenario-based approach has been applied. Scenarios represent realistic situations where age- and gender-specific exposure occurs in the everyday life of consumers. We find that North American and European consumers are likely to experience ubiquitous and long-term uptake doses of PFOS and PFOA in the range of 3 to 220 ng per kg body weight per day (ng/kg_bw/day) and 1 to 130 ng/kg_bw/day, respectively. The greatest portion of the chronic exposure to PFOS and PFOA is likely to result from the intake of contaminated foods, including drinking water. Consumer products cause a minor portion of the consumer exposure to PFOS and PFOA. Of these, it is mainly impregnation sprays, treated carpets in homes, and coated food contact materials that may lead to consumer exposure to PFOS and PFOA. Children tend to experience higher total uptake doses (on a body weight basis) than teenagers and adults because of higher relative uptake via food consumption and hand-to-mouth transfer of chemical from treated carpets and ingestion of dust. The uptake estimates based on scenarios are within the range of values derived from blood serum data by applying a one-compartment pharmacokinetic model.     

Perceptions of Ecological Risk Associated with Mountain Pine Beetle (Dendroctonus ponderosae) Infestations in Banff and Kootenay National Parks of Canada

Western Canada is experiencing an unprecedented outbreak of the mountain pine beetle (MPB). The MPB has the potential to impact some of Canada's national parks by affecting park ecosystems and the visitor experience. Controls have been initiated in some parks to lessen the impacts and to prevent the beetle from spreading beyond park boundaries. We examine the perception of ecological risk associated with MPB in two of Canada's national parks, the factors affecting perceptions of risk, and the influence of risk judgments on support for controlling MPB outbreaks in national parks. Data were collected using two studies of park visitors: a mail survey in 2003 and an onsite survey in 2005. The MPB was rated as posing a greater risk to the health and productivity of park ecosystems than anthropogenic hazards and other natural disturbance agents. Visitors who were familiar with MPB rated the ecological and visitor experience impacts as negative, unacceptable, and eliciting negative emotion. Knowledge and residency were the most consistent predictors of risk judgments. Of knowledge, risk, and demographic variables, only sex and risk to ecosystem domains influenced support for controlling the MPB in national parks. Implications for managing MPB in national parks, visitor education, and ecological integrity are discussed.     

Analysis of postponement strategy by EPQ-based models with planned backorders

This paper develops economic production quantity (EPQ)-based models with planned backorders to evaluate the impact of the postponement strategy on a manufacturer in a supply chain. We derive the optimal total average costs per unit time for producing and keeping n end-products in a postponement system and a non-postponement system, respectively. By comparing the optimal total average costs of the two systems, we evaluate the impact of postponement on the manufacturer under four circumstances. Our results show that postponement strategy can give a lower total average cost under certain circumstances. We also find that the key factors in postponement decisions are the variance of the machine utilization rates and the variance of the backorder costs.     

Characterizing performance in socio-technical systems: A modeling framework in the domain of nuclear power

In modeling complex socio-technical systems, the critical nature of many interactions between human and automation are often unrecognized until the system experiences catastrophic consequences. One reason for this is that the systems are generally very robust and serious problems are rare. Another reason is the difficulty in modeling the variety of interactions in a manner compatible with analytical and/or computational models of the technological components of the system. Organizational issues and extraneous influences add to these modeling difficulties. We have developed a modeling framework that integrates certain ideas from social networks, graph theory, and simulation, all tied together using heuristics that reflect deep domain knowledge. This framework forms the basis for a computational implementation, portions of which have been implemented. Details of the model and the rationale for the model structure are described in this paper.     

The Price Chameleons Pay: Self‐monitoring,Boundary Spanning and Role Conflict in the Workplace*

The vast majority of research on self‐monitoring in the workplace focuses on the benefits that accrue to chameleon‐like high self‐monitors (relative to true‐to‐themselves low self‐monitors). In this study, we depart from the mainstream by focusing on a potential liability of being a high self‐monitor: high levels of experienced role conflict. We hypothesize that high self‐monitors tend to choose work situations that, although consistent with the expression of their characteristic personality, inherently involve greater role conflict (i.e. competing role expectations from different role senders). Data collected from a 116‐member high‐tech firm showed support for this mediation hypothesis: relative to low self‐monitors, high self‐monitors tended to experience greater role conflict in work organizations because high self‐monitors were more likely to occupy boundary spanning positions. To help draw a more realistic and balanced portrait of self‐monitoring in the workplace, we call for more theoretically grounded research on the price chameleons pay.     

Leadership efficacy: Review and future directions

The concept of leader efficacy has received relatively little attention in the leadership literature. This is somewhat surprising given that effective leadership requires high levels of agency (i.e., deliberately or intentionally exerting positive influence) and confidence. This review uses existing theory and research on leader efficacy as a point of departure for proposing an expanded and multi-level framework for understanding the domain of leadership efficacy that includes leader, follower, and collective efficacies. The primary goals are to provide a conceptual framework to stimulate future theory and research on building efficacious leadership and to understand how such leadership develops and has implications for effective performance.     

Improved adaptive group testing algorithms with applications to multiple access channels and dead sensor diagnosis

We study group-testing algorithms for resolving broadcast conflicts on a multiple access channel (MAC) and for identifying the dead sensors in a mobile ad hoc wireless network. In group-testing algorithms, we are asked to identify all the defective items in a set of items when we can test arbitrary subsets of items. In the standard group-testing problem, the result of a test is binary—the tested subset either contains defective items or not. In the more generalized versions we study in this paper, the result of each test is non-binary. For example, it may indicate whether the number of defective items contained in the tested subset is zero, one, or at least two. We give adaptive algorithms that are provably more efficient than previous group testing algorithms. We also show how our algorithms can be applied to solve conflict resolution on a MAC and dead sensor diagnosis. Dead sensor diagnosis poses an interesting challenge compared to MAC resolution, because dead sensors are not locally detectable, nor are they themselves active participants. A preliminary version of this paper was presented at SPAA 2006.     

Rising food security concerns among New Zealand adolescents and association with health and wellbeing

The current paper explores recent changes in food insecurity among adolescents and determine if food security concerns are associated with poorer wellbeing. Data were collected as part of two nationally representative surveys of the health and wellbeing of high-school students in New Zealand in 2007 and 2012. In 2012, 11% of young people reported food security concerns often or always, with 33% reporting food security concerns occasionally/sometimes. The prevalence of food security concerns at both frequencies increased significantly from 2007 (8% and 28%, respectively). Young people with food security concerns were more likely to report poor indicators of health and wellbeing, including truancy, poor general health, mental health concerns and obesity. Our findings highlight the growing concerns of food insecurity reported by adolescents in New Zealand. Interventions that address food security for families may provide a tangible means of promoting the healthy development of children and young people.     

Modern variable selection for longitudinal semi-parametric models with missing data

Penalized methods for variable selection such as the Smoothly Clipped Absolute Deviation penalty have been increasingly applied to aid variable section in regression analysis. Much of the literature has focused on parametric models, while a few recent studies have shifted the focus and developed their applications for the popular semi-parametric, or distribution-free, generalized estimating equations (GEEs) and weighted GEE (WGEE). However, although the WGEE is composed of one main and one missing-data module, available methods only focus on the main module, with no variable selection for the missing-data module. In this paper, we develop a new approach to further extend the existing methods to enable variable selection for both modules. The approach is illustrated by both real and simulated study data.