Interrupted stories, interrupted lives

In attempting to manage their practices efficiently, doctors may not allow seriously ill patients enough time to sort out their feelings and raise important questions. What is at stake here is not information about prognosis and treatments but the very survival of the soul.     

Basic aspects of evolution strategies

Evolution strategies (ESs) are a special class of probabilistic, direct, global optimization methods. They are similar to genetic algorithms but work in continuous spaces and have the additional capability of self-adapting their major strategy parameters. This paper presents the most important features of ESs, namely their self-adaptation, as well as their robustness and potential for parallelization which they share with other evolutionary algorithms.Besides the early (1 + 1)-ES and its underlying theoretical results, the modern ( + )-ES and (, )-ES are presented with special emphasis on the self-adaptation of strategy parameters, a mechanism which enables the algorithm to evolve not only the object variables but also the characteristics of the probability distributions of normally distributed mutations. The self-adaptation property of the algorithm is also illustrated by an experimental example.The robustness of ESs is demonstrated for noisy fitness evaluations and by its application to discrete optimization problems, namely the travelling salesman problem (TSP).Finally, the paper concludes by summarizing existing work and general possibilities regarding the parallelization of evolution strategies and evolutionary algorithms in general.     

What lies ahead for medical management?

The consensus is that, in spite of a reluctance in Washington to undertake any drastic reform of the health care financing and delivery system, the changes that are already in place in individual organizations and that are in place or being contemplated at the state level are certain to make the health care system of tomorrow very different from that of today. Physician executives can play an important role in the transition that will be required, but they will have to use a flexible, especially nondogmatic approach if they wish to cope successfully in this increasingly whirling environment. For such physicians, the author says, the opportunities, though unknown, are enormous.     

Recent migrations from Morocco to Spain

"This study addressed the problem of the Moroccan immigration into Spain within the context of South-North movements, focusing on analyzing provisional data from the last immigrant regularization in the country completed during the end months of 1991."     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

Finite mixture models with concomitant information: assessing diagnostic criteria for diabetes

The World Health Organization (WHO) diagnostic criteria for diabetes mellitus were determined in part by evidence that in some populations the plasma glucose level 2 h after an oral glucose load is a mixture of two distinct distributions. We present a finite mixture model that allows the two component densities to be generalized linear models and the mixture probability to be a logistic regression model. The model allows us to estimate the prevalence of diabetes and sensitivity and specificity of the diagnostic criteria as a function of covariates and to estimate them in the absence of an external standard. Sensitivity is the probability that a test indicates disease conditionally on disease being present. Specificity is the probability that a test indicates no disease conditionally on no disease being present. We obtained maximum likelihood estimates via the EM algorithm and derived the standard errors from the information matrix and by the bootstrap. In the application to data from the diabetes in Egypt project a two-component mixture model fits well and the two components are interpreted as normal and diabetes. The means and variances are similar to results found in other populations. The minimum misclassification cutpoints decrease with age, are lower in urban areas and are higher in rural areas than the 200 mg dl^-1 cutpoint recommended by the WHO. These differences are modest and our results generally support the WHO criterion. Our methods allow the direct inclusion of concomitant data whereas past analyses were based on partitioning the data.     

GENDER, EARNINGS, AND THE ENGLISH SKILL ACQUISITION OF HISPANIC WORKERS IN THE UNITED STATES

Using the 1980 and 1990 Public Use Microdata Samples, we find that labor market outcomes associated with English proficiency vary with respect to gender. For example, a synthetic cohort analysis provides evidence of gender-related differences in Hispanic workers' English skill acquisition. Moreover, we observe that Hispanic women face a lower English deficiency earnings penalty that rises more sharply with education than the penalty obtained by their otherwise similar male peers. Finally, English fluency appears to serve as a stronger occupational sorting mechanism for women than men. ( JEL J3, J1)