Development and piloting of an exposure database and surveillance system for DOE cleanup operations

An industrial hygiene exposure database and surveillance system was developed in partnership between National Institute for Occupational Safety and Health (NIOSH)-funded independent investigators and practicing industrial hygienists at the Rocky Flats Environmental Technology Site (RFETS) in Golden, Colo. RFETS is a former U.S. Department of Energy nuclear weapons plant that is now in cleanup phase. This project is presented as a case study in the development of an exposure database and surveillance system in terms that are generalizable to most other industries and work contexts. Steps include gaining organizational support; defining system purpose and scope; defining database elements and coding; planning practical and efficient analysis strategies; incorporating reporting capabilities; and anticipating communication strategies that maximize the probability that surveillance findings will feed back to preventive applications. For each of these topics, the authors describe both general considerations as well as the specific choices made for this system. An important feature of the system is a two-tier task-coding scheme comprising 33 categories of task groups. Examples of grouped analyses of exposure data captured during the system pilot period demonstrate applications to exposure control, medical surveillance, and other preventive measures. Reprinted by permission of the publisher.

Predicting avian distributions to evaluate spatiotemporal overlap with locust control operations in eastern Australia.

Locusts and grasshoppers cause considerable economic damage to agriculture worldwide. The Australian Plague Locust Commission uses multiple pesticides to control locusts in eastern Australia. Avian exposure to agricultural pesticides is of conservation concern, especially in the case of rare and threatened species. The aim of this study was to evaluate the probability of pesticide exposure of native avian species during operational locust control based on knowledge of species occurrence in areas and times of application. Using presence-absence data provided by the Birds Australia Atlas for 1998 to 2002, we developed a series of generalized linear models to predict avian occurrences on a monthly basis in 0.5 degrees grid cells for 280 species over 2 million km2 in eastern Australia. We constructed species-specific models relating occupancy patterns to survey date and location, rainfall, and derived habitat preference. Model complexity depended on the number of observations available. Model output was the probability of occurrence for each species at times and locations of past locust control operations within the 5-year study period. Given the high spatiotemporal variability of locust control events, the variability in predicted bird species presence was high, with 108 of the total 280 species being included at least once in the top 20 predicted species for individual space-time events. The models were evaluated using field surveys collected between 2000 and 2005, at sites with and without locust outbreaks. Model strength varied among species. Some species were under- or over-predicted as times and locations of interest typically did not correspond to those in the prediction data set and certain species were likely attracted to locusts as a food source. Field surveys demonstrated the utility of the spatially explicit species lists derived from the models but also identified the presence of a number of previously unanticipated species. These results also emphasize the need for special consideration of rare and threatened species that are poorly predicted by presence-absence models. This modeling exercise was a useful a priori approach in species risk assessments to identify species present at times and locations of locust control applications, and to discover gaps in our knowledge and need for further focused data collection.

How do SMEs with single and multiple owners finance their operations differently? Empirical evidence from China

We study the impact of firm-level characteristics on the capital structures of private small and medium-sized enterprises (SMEs) as well as the differences between the capital structures adopted by SMEs with single and multiple owners in China. Our findings highlight the limited use of asset-based financing by Chinese SMEs. We also find that the propensity of SMEs with single-owners to use external debt was significantly less than those with multiple owners. Furthermore, our findings suggest that single-owned firms are subject to a more constrained pecking order than those with multiple owners.

Complex simulation of stockyard mining operations

Conflicts between resources in stockyards cause mining companies millions of dollars a year. An effective planning strategy needs to be established in order to reduce these operational conflicts. In this research a stockyard simulation model of a mining operation is proposed. The simulation uses discrete event and continuous strategies to create a high detail level of visualization and animation that closely resemble actual stockyard operation. The proposed simulation model is tightly integrated with a stockpile planner and it is used to evaluate the feasibility of a given production plan. The high detail visualization of the simulation model allows planner to determine the source of conflict, which can be used to guide the elimination of these conflicts.