Modeling for Risk Assessment of Neurotoxic Effects

The regulation of noncancer toxicants, including neurotoxicants, has usually been based upon a reference dose (allowable daily intake). A reference dose is obtained by dividing a no-observed-effect level by uncertainty (safety) factors to account for intraspecies and interspecies sensitivities to a chemical. It is assumed that the risk at the reference dose is negligible, but no attempt generally is made to estimate the risk at the reference dose. A procedure is outlined that provides estimates of risk as a function of dose. The first step is to establish a mathematical relationship between a biological effect and the dose of a chemical. Knowledge of biological mechanisms and/or pharmacokinetics can assist in the choice of plausible mathematical models. The mathematical model provides estimates of average responses as a function of dose. Secondly, estimates of risk require selection of a distribution of individual responses about the average response given by the mathematical model. In the case of a normal or lognormal distribution, only an estimate of the standard deviation is needed. The third step is to define an adverse level for a response so that the probability (risk) of exceeding that level can be estimated as a function of dose. Because a firm response level often cannot be established at which adverse biological effects occur, it may be necessary to at least establish an abnormal response level that only a small proportion of individuals would exceed in an unexposed group. That is, if a normal range of responses can be established, then the probability (risk) of abnormal responses can be estimated. In order to illustrate this process, measures of the neurotransmitter serotonin and its metabolite 5-hydroxyindoleacetic acid in specific areas of the brain of rats and monkeys are analyzed after exposure to the neurotoxicant methylene-dioxymethamphetamine. These risk estimates are compared with risk estimates from the quantal approach in which animals are classified as either abnormal or not depending upon abnormal serotonin levels.     

Female Labor Force Participation in Urban and Rural China1

Abstract The objective of this study is to examine female labor force participation and its determinants in rural and urban China. The sociological literature has demonstrated that participation tends to increase in urban and industrialized places where women have higher levels of education and fewer children, where more workers are engaged in service pursuits, and where family structure is less traditional. With the use of data on counties and cities (N = 2,377) from the I-percent sample of the 1982 census of the People's Republic of China, it was found that female labor force participation is likely to rise in areas with increased agricultural employment, educational levels, proportion of female-headed households, and higher male-to-female sex ratios. Both the size of the service sector and the fertility rate had negligible effects on female labor force participation. Although, on average, rural places have slightly higher levels of female labor force participation, when other variables are controlled, urban places have a higher rate of female participation. In addition, the findings suggest that market factors (i.e., education) are more likely to determine the rate of female labor force participation in urban areas; whereas demographic and social factors (i.e., sex ratio and household structure) play a more important role in explaining the female labor force participation in rural counties.     

Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

Opposition to Solid Waste Incineration: Pre- Implementation Anxieties Surrounding a New Environmental Controversy*

Despite sociopolitical controversy surrounding the solid waste crisis, little sociological attention has focused on this crucial environmental issue. Drawing on research from the technological controversies, environmental concern, and solid waste literatures, this study examines the pre-implementation anxieties of a Louisiana community faced with a proposal to build an incinerator in its backyard. Utilizing survey data, a causal path model is developed in which the perceived advantages of the technology, general environmental concern, and support for recycling initiatives are identified as explanatory variables of incinerator opposition. Implications of these findings for the study of technical controversies and the larger solid waste crisis also are suggested.     

Ninth-Grade Students' Attitudes Toward Nontraditional Occupations

This study explored how students choose careers, their attitudes toward vocational education, and whether or not they would consider enrolling in a nontraditional vocational education program.     

Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.     

SUNK COSTS, PROFIT VARIABILITY, AND TURNOVER

Dynamic competitive models of industry evolution suggest that firm profit will be more volatile, and turnover lower, in industries with higher sunk costs. These implications are consistent with empirical observation. (JEL L00 )