Abstract
Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences that might be useful in the explanation of the function or activity of the newly discovered ones. In current web sites and data bases of sequences there are, usually, a set of paper references linked to each sequence. Those links are very useful because the papers describe useful information concerning the sequences. They are, therefore, a good starting point to look for relevant information related to a set of sequences. One way is to implement such approach is to do a blast with the new decoded sequences, and collect similar sequences. Then one looks at the papers linked with the similar sequences. Most often the number of retrieved papers is small and one has to search large data bases for relevant papers. In this paper we propose a process of generating a classifier based on the initially set of relevant papers that are directly linked to the similar sequences retrieved and use that classifier to automatically enlarge the set of relevant papers by searching the MEDLINE using the automatically constructed classifier. We have empirically evaluated our proposal and report very promising results. © 2011 IEEE.

Abstract
Although IT governance practices (like ITIL, which recommends on the use of audit logs for proper service level management) are being introduced in many Hospitals to cope with increasing levels of information quality and safety requirements, the standard maturity levels of hospital IT departments is still not enough to reach the level of frequent use of audit logs. This paper aims to address the issues related to the existence of AT in patient records, describe the Hospitals scenario and to produce recommendations. Representatives from four hospitals were interviewed regarding the use of AT in their Hospital IS. Very few AT are known to exist in these hospitals (average of 1 per hospital in an estimate of 21 existing IS). CIOs should to be much more concerned with the existence and maintenance of AT. Recommendations include server clock synchronization and using advanced log visualization tools.

Abstract
In this study, we focus on the interaction between microtiming patterns and several musical properties: intensity, meter and spectral characteristics. The data-set of 106 musical audio excerpts is processed by means of an auditory model and then divided into several spectral regions and metric levels. The resulting segments are described in terms of their musical properties, over which patterns of peak positions and their intensities are sought. A clustering algorithm is used to systematize the process of pattern detection. The results confirm previously reported anticipations of the third and fourth semiquavers in a beat. We also argue that these patterns of microtiming deviations interact with different profiles of intensities that change according to the metrical structure and spectral characteristics. In particular, we suggest two new findings: (i) a small delay of microtiming positions at the lower end of the spectrum on the first semiquaver of each beat and (ii) systematic forms of accelerando and ritardando at a microtiming level covering two-beat and four-beat phrases. The results demonstrate the importance of multidimensional interactions with timing aspects of music. However, more research is needed in order to find proper representations for rhythm and microtiming aspects in such contexts.

Abstract
A Fabry-Perot (FP) cavity of simple design and based on a pure silica diaphragm-free hollow tube is proposed. Its operation is based on a first reflection of light at the end of the single-mode fiber that illuminates the silica rod and in a second reflection that takes place at the end of the rod. The FP cavity is characterized for high temperature, pressure and refractive index sensing, showing useful characteristics for the measurement of these three parameters. The diaphragm-free configuration simplifies the measurement of the refractive index of fluids. (C) 2011 Optical Society of America

Abstract
We propose a constructive procedure for building a distribut-ed cognition model of a system out of contextual / ethnographic data. We then show how such a model can be conveniently used for studying, in a repeatable and justifiable way, if a system correctly implements selected user-centred design principles. Our approach thus complements user studies in that it enables reasoning about the situated use of a teamwork system even before direct user involvement. We have applied our procedure to a healthcare case study. In particular, we have re-analysed a well-known adverse incident that led to a fatality and for which a comprehensive investigation report is in the public domain. By reasoning about the distributed cognition model, we identified several issues that were not addressed in the incident report nor in other subsequent analyses. © 2011 Springer-Verlag Berlin.

Abstract
In this work, we introduce in the first part new developments in Principal Component Analysis (PCA) and in the second part a new method to select variables (genes in our application). Our focus is on problems where the values taken by each variable do not all have the same importance and where the data may be contaminated with noise and contain outliers, as is the case with microarray data. The usual PCA is not appropriate to deal with this kind of problems. In this context, we propose the use of a new correlation coefficient as an alternative to Pearson's. This leads to a so-called weighted PCA (WPCA). In order to illustrate the features of our WPCA and compare it with the usual PCA, we consider the problem of analyzing gene expression data sets. In the second part of this work, we propose a new PCA-based algorithm to iteratively select the most important genes in a microarray data set. We show that this algorithm produces better results when our WPCA is used instead of the usual PCA. Furthermore, by using Support Vector Machines, we show that it can compete with the Significance Analysis of Microarrays algorithm.