Jocelyne Fayn

An Automatic Approach to Generate XML Schemas from Relational Models

Data storage in enterprise information systems is usually performed in relational databases, and XML is a common standard for exchanging data within and among organizations. Automating databases update from data in XML format remains a challenge. In this paper, we propose a methodology to efficiently generate, from a relational model, an XML schema which can then be used by an XML middleware platform that performs the mediation management between the source and target XML representations. Our method is composed of two main steps, with the objective of both avoiding any data redundancy by performing a high level of nesting, and preserving the integrity constraints. The first step consists in an algorithm that stratifies all the relations of the database model in different levels depending on the existing functional dependencies and on the foreign keys degrees. The second step consists in an algorithm based on a set of generic XML Schema fragments templates that automatically creates an XML schema according to the classification performed by the previous step. Our methodology has been successfully tested in the eHealth domain between an XML representation of an open format ISO standard communications protocol embedding biosignals and related metadata and a European relational reference model including these data.

The T wave: is it the Traffic light of cardiac disorders or the Troublemaker of rhythmology?

It was a great pleasure to read the paper of Odenstedt et al published in this issue of the journal that shows the relevance of considering the T wave in its own preferential space. Odenstedt et al studied 8 spatial T-loop measurements in a porcine ischemia-reperfusion model. Among the 33 pigs included in their study, 16 (48%) pigs developed ventricular fibrillation (VF) during coronary artery occlusion or reperfusion. Significant changes in T-wave planarity were observed before VF (P = .028). These original findings are of utmost importance for sudden cardiac death prevention. I remember the bad reputation of the Twave when I began research in quantitative electrocardiology in the early 1980s. At that time, the T wave was qualified as the fickle wave of the orthogonal electrocardiogram (ECG) wave in classical vectorcardiography. Unlike the QRS wave, the projections of the spatial T wave into the 3 planes of the Frank system presented a great variety of heterogeneous and changing patterns that were difficult to categorize according to the cardiac diseases. We then demonstrated in our group that provided that it is explored in its own preferential space, thanks to the CAVIAR (Comparative Analysis of electroVectocardiograms and their Interpretation with Auto-Reference to the patient) method, the T wave seemed to be extraordinarily plane and very stable along time in a healthy population, whereas standard electrocardiography attempted to exploit its alternance in populations with cardiac disease. These planarity and stability of the Twave in space were even observed in a large population of 720 healthy men and occurred to be significantly modified under quinidine, showing in that case a figure of a Concordetype aircraft nose. I was very pleased to read that the group of Bergfeldt reused the same concept and thus increased its value. The study reported in this issue by Odenstedt et al led to the important finding that there was no relation between the amount of ischemic myocardium or the area of risk and the occurrence of VF. These results thus corroborate the relevance of exploring the repolarization wave in its preferential space, all the more as the authors found in their study that there was no significant difference in occurrences of VF or in infarct size between the pigs who received clevidipine vs those that received placebo. Among the 8 spatial T-wave measurements that the authors included in their analysis, only the T-loop distortion was significantly