Results from the ULTRA experiment in the framework of the EUSO project

The detection of Cerenkov light from EAS in a delayed coincidence with fluorescence light gives a strong signature to discriminate protons and neutrinos in cosmic rays. For this purpose, the ULTRA experiment has been designed with 2 detectors: a small EAS array (ETscope) and an UV optical device including wide field (Belenos) and narrow field (UVscope) Cerenkov light detectors. The array measures the shower size and the arrival direction of the incoming EAS, while the UV devices, pointing both to zenith and nadir, are used to determine the amount of direct and diffused coincident Cerenkov light. This information, provided for different diffusing surfaces, will be used to verify the possibility of detecting from Space the Cerenkov light produced by UHECRs with the EUSO experiment, on board the ISS

Advances in indoor location

This paper presents the research activities carried out within the scope of the Liaison project. Most of the work has been performed on WiFi location. WiFi is nowadays widely deployed in buildings such as hotels, hospitals, airports, train stations, public buildings, etc. Using this infrastructure to locate terminals connected to the wireless LAN is expected to have a low cost. Methods presented in this paper include fingerprinting and tracking through particle filter constrained on a Voronoi diagram and TOA based on data frames and acknowledgments at the link level. Other technologies have also been researched: A-GNSS to handle the transition between outdoors and indoors, UWB in ad-hoc mode to cope with possible lacks of infrastructure and inertial MEMS to increase the availability and robustness of the overall system

Proprietes vibrationnelles et conformationnelles de phosphazenes lineaires

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : T 77779 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

A computing system for discovering causal relationships among human genes to improve drug repositioning

The automatic discovery of causal relationships among human genes can shed light on gene regulatory processes and guide drug repositioning. To this end, a computationally-heavy method for causal discovery is distributed on a volunteer computing grid and, taking advantage of variable subsetting and stratification, proves to be useful for expanding local gene regulatory networks. The input data are purely observational measures of transcripts expression in human tissues and cell lines collected within the FANTOM project. The system relies on the BOINC platform and on optimized client code. The functional relevance of results, measured by analyzing the annotations of the identified interactions, increases significantly over the simple Pearson correlation between the transcripts. Additionally, in 82% of cases networks significantly overlap with known protein-protein interactions annotated in biological databases. In the two case studies presented, this approach has been used to expand the networks of genes associated with two severe human pathologies: prostate cancer and coronary artery disease. The method identified respectively 22 and 36 genes to be evaluated as novel targets for already approved drugs, demonstrating the effective applicability of the approach in pipelines aimed to drug repositionin