Pulse Rate Analysis in Case of Central Sleep Apnea: A New Algorithm for Cardiac Rate Estimation

Annual International Conference of the IEEEInternational audienceThis paper first describes the AM-FM demodulation of an arterial pressure signal. Although it is known to be efficient on signals modulated by breathing, we demonstrate that in case of lack of respiratory modulation (central sleep apnea), the AM-FM algorithm doesn't perform well in heart rate extraction. We introduce then a new algorithm based on Singular Spectrum Analysis eigen values which performs better cardiac frequency estimation in this context. The error for cardiac frequency estimation is around 0.2 BPM (Beats Per Minute) versus 5.5 BPM for the AM-FM demodulation. Further experimentations will be performed (with this time both cardiac and respiratory assessments) and will deal with real sleep apnea cases

Évaluation du stress : application à la détection des chutes

National audienceThis paper deals with the association of several physiological parameters in order to estimate a stress level that can be use in the detection of falls or the evaluation of fear of falling among elderly people

Electronic excited state of protonated aromatic molecules: protonated Fluorene

The photo-fragmentation spectrum of protonated fluorene has been recorded in the visible spectral region, largely red shifted as compared to the first excited state absorption of neutral fluorene. The spectrum shows two different vibrational progressions, separated by 0.19 eV that are assigned to the absorption of two isomers. As in protonated linear PAHs, comparison with ab-initio calculations indicates that the red shift is due to the charge transfer character of the excited state

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools

Background: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. Results: We present the Systems Biology Markup Language (SBML) Qualitative Models Package (“qual”), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. Conclusions: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks

Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2

Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel­2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel­2 for Agriculture” system.Instituto de Clima y AguaFil: Bontemps, Sophie. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Arias, Marcela. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Cara, Cosmin. CS Romania S.A.; RumaniaFil: Dedieu, Gérard. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Guzzonato, Eric. CS Systèmes d’Information; FranciaFil: Hagolle, Olivier. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Inglada, Jordi. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Matton, Nicolas. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Morin, David. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Popescu, Ramona. CS Romania S.A.; RumaniaFil: Rabaute, Thierry. CS Systèmes d’Information; FranciaFil: Savinaud, Mickael. CS Systèmes d’Information; FranciaFil: Sepulcre, Guadalupe. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Valero, Silvia. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Wu, Bingfang. Chinese Academy of Sciences. Institute of Remote Sensing and Digital Earth; República de ChinaFil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Diarra, Alhousseine. Université Cadi Ayyad. Faculté des Sciences Semlalia; MarruecosFil: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: French, Andrew. United States Department of Agriculture. Agricultural Research Service. Arid Land Agricultural Research Center; ArgentinaFil: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Kussul, Nataliia. National Academy of Sciences of Ukraine. Space Research Institute and State Space Agency of Ukraine; UcraniaFil: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Le Page, Michel. Université Cadi Ayyad. Faculté des Sciences Semlalia. Laboratoire Mixte International TREMA; Marruecos. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Newby, Terrence. Agricultural Research Council; SudáfricaFil: Savin, Igor. V.V. Dokuchaev Soil Science Institute; RusiaFil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Koetz, Benjamin. European Space Agency. European Space Research Institute; ItaliaFil: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute; Bélgic