Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
The CoPanFlu-France cohort of households was set up in 2009 to study the risk factors for infection by the pandemic influenza virus (H1N1pdm) in the French general population. The authors developed an integrative data-driven approach to identify individual, collective and environmental factors associated with the post-seasonal serological H1N1pdm geometric mean titer, and derived a nested case-control analysis to identify risk factors for infection during the first season. This analysis included 1377 subjects (601 households). The GMT for the general population was 47.1 (95% confidence interval (CI): 45.1, 49.2). According to a multivariable analysis, pandemic vaccination, seasonal vaccination in 2009, recent history of influenza-like illness, asthma, chronic obstructive pulmonary disease, social contacts at school and use of public transports by the local population were associated with a higher GMT, whereas history of smoking was associated with a lower GMT. Additionally, young age at inclusion and risk perception of exposure to the virus at work were identified as possible risk factors, whereas presence of an air humidifier in the living room was a possible protective factor. These findings will be interpreted in light of the longitudinal analyses of this ongoing cohort.
ISSN: 1932-6203

Droits : http://creativecommons.org/licenses/by-sa/
hal-01122215
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01122215
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01122215/document
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01122215/file/journal.pone.0060127.pdf
PUBMED : 23613718

Éditeur(s) : HAL CCSD
Résumé : We show how to translate the Calculus of Inductive Constructions (CIC) as implemented by Coq into the ??-calculus modulo, a proposed common backend proof format for heterogeneous proof assistants.
Second International Workshop on Proof Exchange for Theorem Proving (PXTP 2012)
Manchester, United Kingdom

hal-01126128
https://hal.archives-ouvertes.fr/hal-01126128

Éditeur(s) : HAL CCSD
Résumé : National audience
We propose a method to solve the problem of clustering individuals described by mixed variables structured in blocks. It is a hierarchical method with two levels similar to Hierarchical Principal Component Analysis presented by Wold, based on the mixed topology maps (MTM). The first step consists in establishing, for each block of mixed variables, a clustering representing a synthesis of local individuals at the block level. The second step is to re-apply MTM on the weighted results of the first level. We obtain a global clustering of individuals, consensus among the partitions from level 1. The proposed method is illustrated on data from the national survey in the French housing stock carried out in 2003-2005 by the Observatory for Indoor Air Quality (OQAI).
Fouille de Données Complexes, complexité liée aux données multiples et massives (FDC)
bordeaux, France

hal-00748841
https://hal.archives-ouvertes.fr/hal-00748841
https://hal.archives-ouvertes.fr/hal-00748841/document