Category-theoretic fibration as an abstraction mechanism in information systems

This paper examines the problem of establishing a formal relationship of abstraction and refinement between abstract enterprise models and the concrete information systems which implement them. It introduces and justifies a number of reasonableness requirements, which turn out to justify the use of category theoretic concepts, particularly fibrations, to precisely specify a semantics for enterprise models which enables them to be considered as abstractions of the conceptual models from which the implementing information systems are built. The category-theoretic concepts are developed towards the problem of testing whether a system satisfies the fibration axioms, and are applied to case studies to demonstrate their practicability.

Development and implementation of the population Fisher information matrix for the evaluation of population pharmacokinetic designs.

In population pharmacokinetic studies, the precision of parameter estimates is dependent on the population design. Methods based on the Fisher information matrix have been developed and extended to population studies to evaluate and optimize designs. In this paper we propose simple programming tools to evaluate population pharmacokinetic designs. This involved the development of an expression for the Fisher information matrix for nonlinear mixed-effects models, including estimation of the variance of the residual error. We implemented this expression as a generic function for two software applications: S-PLUS and MATLAB. The evaluation of population designs based on two pharmacokinetic examples from the literature is shown to illustrate the efficiency and the simplicity of this theoretic approach. Although no optimization method of the design is provided, these functions can be used to select and compare population designs among a large set of possible designs, avoiding a lot of simulations.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Long-term outcomes of genetic counseling in women at increased risk of developing hereditary breast cancer Information,

This multicenter study evaluated the impact of genetic counseling in 218 women at risk of developing hereditary breast cancer. Women were assessed prior to counseling and 12-month post-counseling using self-administered, mailed questionnaires. Compared to baseline, breast cancer genetics knowledge was increased significantly at follow-up. and greater increases in knowledge were associated with educational level. Breast cancer anxiety decreased significantly from baseline to follow-up, and these decreases were associated with improvements in perceived risk. A significant decrease in clinical breast examination was observed at the 12-month follow-up. Findings suggest that women with a family history of breast cancer benefit from attending familial cancer clinics as it leads to increases in breast cancer genetics knowledge and decreases in breast cancer anxiety. The lowered rates of clinical breast examination indicate that the content of genetic counseling may need to be reviewed to ensure that women receive and take away the right message. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

Semantic priming in Parkinson's disease: Evidence for delayed spreading activation

Nineteen persons with Parkinson's disease (PD) and 19 matched control participants completed a battery of online lexical decision tasks designed to isolate the automatic and attentional aspects of semantic activation within the semantic priming paradigm. Results highlighted key processing abnormalities in PD. Specifically, persons with PD exhibited a delayed time course of semantic activation. In addition, results suggest that experimental participants were unable to implicitly process prime information and, therefore, failed to engage strategic processing mechanisms in response to manipulations of the relatedness proportion. Results are discussed in terms of the 'Gain/Decay' hypothesis (Milberg, McGlinchey-Berroth, Duncan, & Higgins, 1999) and the dopaminergic modulation of signal to noise ratios in semantic networks.