Significance of the Dermal Route of Exposure to Risk Assessment

The skin is a route of exposure that needs to be considered when conducting a risk assessment. It is necessary to identify the potential for dermal penetration by a chemical as well as to determine the overall importance of the dermal route of exposure as compared with inhalation or oral routes of exposure. The physical state of the chemical, vapor or liquid, the concentration, neat or dilute, and the vehicle, lipid or aqueous, is also important. Dermal risk is related to the product of the amounts of penetration and toxicity. Toxicity involves local effects on the skin itself and the potential for systemic effects. Dermal penetration is described in large part by the permeability constant. When permeability constants are not known, partition coefficients can be used to estimate a chemical's potential to permeate the skin. With these concepts in mind, a tiered approach is proposed for dermal risk assessment. A key first step is the determination of a skin-to-air or skin-to-medium partition coefficient to estimate a potential for dermal absorption. Building a physiologically-based pharmacokinetic (PBPK) model is another step in the tiered approach and is useful prior to classical in vivo toxicity tests. A PBPK model can be used to determine a permeability constant for a chemical as well as to show the distribution of the chemical systemically. A detailed understanding of species differences in the structure and function of the skin and how they relate to differences in penetration rates is necessary in order to extrapolate animal data from PBPK models to the human. A study is in progress to examine anatomical differences for four species.     

Reducing U.S. carbon dioxide emissions: an assessment of different instruments

The possibility that carbon dioxide emissions from fossil fuel use might lead to global warming has become a leading environmental concern. Many scientific and environmental organizations have called for immediate action to limit carbon dioxide production. For the most part, however, public debate has focused on a single policy instrument: a carbon tax applied to fossil fuels in proportion to their carbon content. We present a detailed model of the U.S. economy and use it to compare carbon taxes with two other instruments that could achieve the same reduction in carbon dioxide emissions: a tax on the energy content of fossil fuels (a BTU tax) and an ad valorem tax on fuel use. We find that carbon taxes can achieve a given reduction with the least overall effect on the economy, but with a large effect on coal mining. Energy taxes are fairly similar to carbon taxes but have slightly less impact on coal mining and slightly greater overall cost. In contrast, ad valorem taxes fall much more lightly on coal mining but have a much greater effect on the economy as a whole.     

A measure of slope-rotatability for second order response surface experimental designs

In the design of experiments for estimating the slope of a response surface, slope-rotatability is a desirable property. In this paper, a measure is introduced that enables us to assess the degree of slope-rotatability for a given response surface design. The measure takes the value zero if and only if the design is slope-rotatable, and becomes larger as the design deviates from a slope-rotatable design. Examples of applying this measure to some response surface designs are also given.     

TEACHING TOOLS: ON JOURNALISTS' USE OF MACROECONOMIC CONCEPTS

Five macroeconomic concepts are presented which are prominent in the business sections of newspapers, but which are not given equivalent prominence in macroeconomic textbooks. These are the discouraged worker phenomenon, the use of inventories in forecasting, the effect of changes in the money supply on the bond market, and the effects of inflation and nominal interest rates in the foreign exchange market. These concepts are presented via news clips illustrating the way they typically appear in the press. Instructors are urged to place extra emphasis on these concepts.     

Pseudo–Modelling of Outliers for Estimation of Regression And Time Series Models

This paper documents situations where the variance inflation model for outliers has undesirable properties. The model is commonly used to accommodate outliers in a Bayesian analysis of regression and time series models. The alternative approach provided here does not suffer from these undesirable properties but gives inferences similar to those of the variance inflation model when this is appropriate. It can be used with regression, time series, and regression with correlated errors in a unified way, and adheres to the scientific principle that inference should be based on the data after obvious outliers have been discarded. Only one parameter is required for outliers; it is interpretable as the a priori willingness to remove observations from the analysis.     

Joint Attention,Self‐Recognition,and Neurocognitive Function in Toddlers

Recent studies have attempted to understand the processes involved in joint attention because of its relevance to both atypical and normal development. Data from a recent study of young children with autism suggests that performance on a delay nonmatch to sample (DNMS) task associated with ventromedial prefrontal functions, but not an A‐not‐B/delayed response task associated with dorsolateral prefrontal cortex, was related to joint attention skills (Dawson et al., 2002). Recent research also suggests that joint attention is associated with dorsalmedial brain systems linked to self‐monitoring (Mundy, 2003). This study investigated the relations among joint attention, DNMS, and self‐recognition performance in a longitudinal study of 39 normally developing toddlers from 14 to 18 months. The results indicated that development on the DNMS and self‐recognition tasks, but not a means end task, predicted joint attention at 18 months. Further analysis showed that the model was only significant for initiating joint attention (IJA). The implications of these results for the neuro‐development of IJA are discussed.     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

Improving on truncated linear estimates of exponential and gamma scale parameters

We consider the problem of estimating the scale parameter of an exponential or a gamma distribution under squared error loss when the scale parameter θ is known to be greater than some fixed value θ₀. Natural estimators in this setting include truncated linear functions of the sufficient statistic. Such estimators are typically inadmissible, but explicit improvements seem difficult to find. Some are presented here. A particularly interesting finding is that estimators which are admissible in the untruncated problem which take values only in the interior of the truncated parameter space are found to be inadmissible for the truncated problem.