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106. SCILAB to SCILAB//: The OURAGAN project.

Author

Eddy Caron, Serge Chaumette, Sylvain Contassot-Vivier, Frederic Desprez, Eric Fleury, Claude Gomez, Maurice Goursat, Martin Quinson, Emmanuel Jeannot, Dominique Lazure, Frédéric Lombard, Jean-Marc Nicod, Laurent Philippe 0001, Pierre Ramet, Jean Roman, Frank Rubi, Serge Steer, Frédéric Suter, and Gil Utard

Published
2001
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111. Author Correction: Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics

Author

Audrey Duval, Thomas Obadia, Lucie Martinet, Pierre-Yves Boëlle, Eric Fleury, Didier Guillemot, Lulla Opatowski, Laura Temime, I-Bird study group, Biostatistique, Biomathématique, Pharmacoépidémiologie et Maladies Infectieuses (B2PHI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Malaria : parasites et hôtes - Malaria : parasites and hosts, Institut Pasteur [Paris], Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), and Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM)

Subjects
Rehabilitation hospital, Cross Infection, Multidisciplinary, business.industry, [SDV]Life Sciences [q-bio], lcsh:R, lcsh:Medicine, medicine.disease, Long-Term Care, Hospitals, Disease Transmission, Infectious, Humans, Medicine, Interpersonal Relations, lcsh:Q, Health Facilities, Medical emergency, Author Correction, business, lcsh:Science
Abstract

Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.

Published
2020
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112. The role of Fe particle size and oxide distribution on the hydrogenation properties of ball-milled nano-crystalline powder mixtures of Fe and Mg

Author

Jin-Yoo Suh, Jae-Hyeok Shim, Young Whan Cho, Eric Fleury, Jee Yun Jung, Young-Su Lee, and Julien O. Fadonougbo

Subjects
Materials science, Mechanical Engineering, Kinetics, Composite number, Doping, Metals and Alloys, Oxide, 02 engineering and technology, 010402 general chemistry, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, chemistry.chemical_compound, Hydrogen storage, chemistry, Chemical engineering, Mechanics of Materials, Particle-size distribution, Materials Chemistry, Particle size, 0210 nano-technology, Powder mixture
Abstract

In the aim of evidencing the relationship between Mg2FeH6 synthesis and the size of Fe particles, several specimens have been prepared by applying various milling energies (milling time) on a 2.1 Mg and 1Fe powder mixture doped with a small fraction of Unsaturated Fatty Amine (UFA). The resulting nano-crystalline composite structures display a broad Fe particle size distribution as a function of milling time. The hydrogenation of those complex powders has been conducted at temperatures lower than 400 °C under 60 bar of hydrogen pressure. As expected, the Fe particle size significantly influenced the hydrogenation kinetics. Also, the inevitable distribution of a minor fraction of oxides occurring during the milling process affected greatly the hydrogen storage capacity. Under the low pressure and temperature conditions selected in the frame of this study, lower than 100 bar and 500 °C conventionally used for synthesis of high purity Mg2FeH6, the hydrogenation reaction was demonstrated to be almost completed within 6 h, confirming the fast hydrogen absorption capability of the prepared materials. Plus, nearly 84 wt% of Mg2FeH6 was achieved under the afore mentioned moderate conditions and a minor fraction of unreacted Fe still remained due to diffusion constraints existing at low temperatures.

Published
2019
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124. Determination of orientation relationships between FCC-hydride and HCP-titanium and their correlation with hydrides distribution

Author

Jing Wen, Nathalie Allain, Eric Fleury, Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux (LEM3), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)

Subjects
Materials science, Stereographic projection, Titanium hydride, Thermodynamics, 02 engineering and technology, 010402 general chemistry, 01 natural sciences, Texture (geology), chemistry.chemical_compound, [SPI]Engineering Sciences [physics], Materials Chemistry, interface planes, Precipitation (chemistry), Plane (geometry), Hydride, Mechanical Engineering, Orientation relationships, Metals and Alloys, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Electron backscatter diffraction, Grain orientation, chemistry, Mechanics of Materials, Deformation (engineering), 0210 nano-technology
Abstract

International audience; Since the crystallographic orientation relationships (ORs) play an important role in the hydrides precipitation as well as in the deformation behavior of α-titanium alloys containing hydrides, the present work aimed at exploring thoroughly the ORs and their interface planes between the fcc-hydride and the α-titanium using the stereographic projections of the corresponding OR plane and OR direction and a trace analysis. In addition to the general reported two ORs in the α-titanium, a new OR closely related to the texture component of the rolled Ti-sheet is also determined in the present work. The overall identified ORs and their interface planes are accounted for by edge-to-edge matching model. Furthermore, a quantitative analysis using the high-angular resolution SEM-EBSD highlighted the dependency of hydride distribution on the ORs and the parent grain orientation.

Published
2020
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125. Mechanisms of oxide dependent tribological behavior in Ti / Steel sliding and influence of nanostructured surfaces

Author

Thierry Grosdidier, Eric Fleury, Laurent Weiss, Philippe Bocher, and Pierre Maurel

Subjects
chemistry.chemical_compound, 020303 mechanical engineering & transports, Materials science, 0203 mechanical engineering, chemistry, 021105 building & construction, 0211 other engineering and technologies, Oxide, 02 engineering and technology, Tribology, Composite material, TA1-2040, Engineering (General). Civil engineering (General)
Abstract

The tribological behavior of pure titanium having coarse-grained or nanostructured surfaces has been investigated against a steel ball moved with an alternative motion. The nanostructures were obtained by Surface Mechanical Attrition Treatment (SMAT) both at room and at cryogenic temperatures. An unexpected wear behavior was revealed: the hard steel ball was abraded for all cases even if it was several times harder compared to the Ti surface. This was due to the formation of a third body consisting of hard Ti oxides. Interestingly, important variations of the coefficient of friction were also revealed during the rubbing process. These variations could be separated into three successive stages, each with its specific wear mechanisms. The wear regimes were related to changes in the third body layer formed between the Ti and steel surfaces. SMAT changed the formation kinetics of the third body. The temperature at which the SMAT was conducted also introduced different third body formation kinetics. Important variations in the wear resistance were consequently observed between each surface condition.

Published
2020

130. Nanometer-scale phase separation and formation of delta ZrH2 in Cu-Zr binary amorphous alloys

Author

Gyeung-Ho Kim, Julien O. Fadonougbo, Jin-Yoo Suh, Young Whan Cho, Eric Fleury, and Cheol-Hwee Shim

Subjects
Materials science, Amorphous metal, Hydride, Mechanical Engineering, Alloy, Metals and Alloys, 02 engineering and technology, engineering.material, Zirconium hydride, 010402 general chemistry, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, Crystallography, Differential scanning calorimetry, Mechanics of Materials, Phase (matter), Materials Chemistry, engineering, Physical chemistry, Dehydrogenation, Crystallite, 0210 nano-technology
Abstract

Different Cu-Zr alloys were hydrogenated under 100 bars of hydrogen pressure at different temperatures. The hydrogenation induced transformation of the initially amorphous phase into a polycrystalline structure characterized by its nanoscale ( 2 . Calorimetry measurements after hydrogenation showed a low temperature exothermic transformation occurring in the alloys hydrogenated at temperatures below 473 K, followed by multiple endothermic peaks at higher temperature attributed to dehydrogenation of different hydride phases. Activation barrier energies of the phase transformation were derived from Kissinger's method, and further characterization involving transmission electron microscopy revealed the existence of delta ZrH 2 with cubic structure contrasting with the typical epsilon ZrH 2 with tetragonal structure. This study evidences the effect of hydrogen pressure, temperature, and the alloy chemistry on the nature of the hydride formation in Cu-Zr binary amorphous alloys during the hydrogenation procedure.

Published
2017
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133. Interaction reconstruction methods for large-scale RFID social experiments

Author

Sicheng Dai, Màrton Karsai, Hélène Bouchet, Eric Fleury, JP Chevrot, Aurélie Nardy, Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM ), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), ANR-16-CE28-0013,DyLNet,Dynamiques langagières, apprentissages linguistiques et sociabilité à l'école maternelle : apport des capteurs de proximité pour le recueil de données massives(2016), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM), Université Grenoble Alpes (UGA), Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Lumière - Lyon 2 (UL2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Joseph Fourier - Grenoble 1 (UJF)-École normale supérieure - Lyon (ENS Lyon)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Joseph Fourier - Grenoble 1 (UJF), Université Stendhal - Grenoble 3-Université Grenoble Alpes (UGA), and ANR-16-CE28-0013,DyLNet,Dynamiques langagières, apprentissages linguistiques et sociabilité à l’école maternelle : apport des capteurs de proximité pour le recueil de données massives(2016)

Subjects
RFID sensors, Sociolinguistic experiment, Temporal networks, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, Supervised learning, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], Signal reconstruction
Abstract

International audience; The emerging technology of radio-frequency identification (RFID) opens entirely new ways to record various aspects of human social interactions in a broad set of settings. First of all, this technology allows to log the temporal dynamics of face-to-face interactions by detecting the physical proximity of participants. The power of this method has been demonstrated earlier in several studies addressing the temporal and spatial evolution of social interactions with high resolution [1, 2]. As examples, such experiments brought us understanding about the structure and evolution of networks formed by face-to-face interactions [3, 4] or how epidemics are spreading in specific environments like in schools or hospitals [2, 5, 6]. Building on these advancements we have taken an uncharted direction by designing RFID tags, which capture not only proximity but also the verbal communication of participants [7]. We use our technology for a large-scale longitudinal sociolinguistic experiment, where we record the oral and face-to-face interactions of children between age 3 to 6 in a preschool setting for one week per month over three years. Our primary goal is to understand how the acquisition of linguistic patterns of children, coming from families of various socioeconomic, cultural, and linguistic background, co-evolve with their social network in time towards a consensus matching the linguistic standards. There are several challenges in such an experiment starting with the reliable reconstruction of social interactions from the recorded RFID signals. Although this problematic has appeared earlier in other RFID studies, no systematic methods have been proposed so far, despite its importance to determine the outcome of any proximity study based on this technology. Packages exchanged between RFID sensors are sometimes lost due to noise or environmental conditions, which easily cause falsely interrupted or missed interactions or lead to the identification of fake ones. These can considerably bias the observations of the temporal social network and any dy-namical process, like language or epidemics, evolving on the top of it. In this contribution our aim is to close this gap by exploring several signal reconstruction strategies using supervised learning methods trained on recorded and annotated data obtained from controlled RFID experiments. Our aim is to find the best method, which provides the highest reconstruction score of temporal interactions for the best approximation of the original social network. More precisely, we consider the communication between pairs of RFID badges, which may receive a package from each other every five seconds with signal strength depending on the distance and orientation of the hosting people. First, using regression methods, we determine a baseline threshold of signal strength corresponding to a distance-range of 1 − 2 meters of realistic verbal face-to-face interactions. Using this threshold we convert our raw sequence to a sequence of pairs of binary signals indicating mutual simultaneous packages observed between sensors (see pairs of green arrows in Fig. 1b) if they capture a meaningful social interaction, or missing packages otherwise (red arrows in Fig. 1b). Reconstruction from a perfect signal would give us periods of interactions built from consecutive mutually observed packages, separated by 1

Published
2019

134. Location, Occupation, and Semantics based Socioeconomic Status Inference on Twitter

Author

Eric Fleury, Jacob Levy Abitbol, Márton Karsai, Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), ANR-15-CE38-0011,SoSweet,Une sociolinguistique de Twitter : liens sociaux et variations linguistiques(2015), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), and Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
FOS: Computer and information sciences, Physics - Physics and Society, Inference, FOS: Physical sciences, 02 engineering and technology, Physics and Society (physics.soc-ph), Semantics, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], Task (project management), 03 medical and health sciences, Computer Science - Computers and Society, 0302 clinical medicine, Computers and Society (cs.CY), 0202 electrical engineering, electronic engineering, information engineering, Feature (machine learning), Socioeconomic status, Social and Information Networks (cs.SI), Data collection, Computer Science - Computation and Language, Social network, business.industry, Computer Science - Social and Information Networks, Data science, Social stratification, Physics - Data Analysis, Statistics and Probability, 020201 artificial intelligence & image processing, business, Computation and Language (cs.CL), 030217 neurology & neurosurgery, Data Analysis, Statistics and Probability (physics.data-an)
Abstract

The socioeconomic status of people depends on a combination of individual characteristics and environmental variables, thus its inference from online behavioral data is a difficult task. Attributes like user semantics in communication, habitat, occupation, or social network are all known to be determinant predictors of this feature. In this paper we propose three different data collection and combination methods to first estimate and, in turn, infer the socioeconomic status of French Twitter users from their online semantics. Our methods are based on open census data, crawled professional profiles, and remotely sensed, expert annotated information on living environment. Our inference models reach similar performance of earlier results with the advantage of relying on broadly available datasets and of providing a generalizable framework to estimate socioeconomic status of large numbers of Twitter users. These results may contribute to the scientific discussion on social stratification and inequalities, and may fuel several applications., Accepted as a full paper in the 2018 IEEE 18th International Conference on Data Mining - IWSC'18 2nd International Workshop on Social Computing

Published
2019
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135. Close proximity interactions support transmission of ESBL-K. pneumoniae but not ESBL-E. coli in healthcare settings

Author

Jean-Louis Herrmann, Thomas Obadia, Laura Temime, Audrey Duval, Pierre-Yves Boëlle, Lulla Opatowski, Eric Fleury, Didier Guillemot, Bodescot, Myriam, Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID, Biostatistique, Biomathématique, Pharmacoépidémiologie et Maladies Infectieuses (B2PHI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Malaria : parasites et hôtes - Malaria : parasites and hosts, Institut Pasteur [Paris] (IP), Bioinformatique évolutive - Evolutionary Bioinformatics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Service de Microbiologie [Garches], Hôpital Raymond Poincaré [AP-HP], Infection et inflammation (2I), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), This study was supported by the European Commission under the Life Science Health Priority of the 6th Framework Program (MOSAR network contract LSHP-CT-2007-037941), funding was also received from the French Government through the National Clinical Research Program and the Investissement d’Avenir program, Laboratoire d’Excellence 'Integrative Biology of Emerging Infectious Diseases' (grant no. ANR-10-LABX-62-IBEID, http://www.agencenationale-recherche.fr/ProjetIA-10-LABX-0062) to DG and from the Ecole des Hautes Etudes en Santé Publique (EHESP, https://www.ehesp.fr/) to AD., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris], Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI)

Subjects
0301 basic medicine, Male, Species Delimitation, Klebsiella pneumoniae, Nosocomial Infections, Speciation, Health Care Providers, Nurses, Pathology and Laboratory Medicine, law.invention, Klebsiella Pneumoniae, 0302 clinical medicine, law, Antibiotics, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Klebsiella, Epidemiology, Medicine and Health Sciences, polycyclic compounds, Infection control, Public and Occupational Health, 030212 general & internal medicine, Medical Personnel, Biology (General), Escherichia coli Infections, 0303 health sciences, Cross Infection, Ecology, biology, Antimicrobials, K pneumoniae, Drugs, Drug Resistance, Microbial, Hygiene, Middle Aged, Hospitals, 3. Good health, Care facility, Anti-Bacterial Agents, Bacterial Pathogens, Professions, Transmission (mechanics), Infectious Diseases, Computational Theory and Mathematics, Medical Microbiology, Modeling and Simulation, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Female, Pathogens, Wireless Technology, Research Article, Adult, medicine.medical_specialty, Evolutionary Processes, QH301-705.5, Microbiology, beta-Lactamases, Cellular and Molecular Neuroscience, 03 medical and health sciences, Antibiotic resistance, Enterobacteriaceae, Environmental health, Microbial Control, Drug Resistance, Bacterial, Genetics, medicine, Disease Transmission, Infectious, Escherichia coli, Humans, Molecular Biology, Microbial Pathogens, Ecology, Evolution, Behavior and Systematics, Aged, Pharmacology, Infection Control, Evolutionary Biology, Bacteria, 030306 microbiology, Organisms, Biology and Life Sciences, biochemical phenomena, metabolism, and nutrition, biology.organism_classification, bacterial infections and mycoses, Health Care, 030104 developmental biology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Antibiotic Resistance, Healthcare settings, People and Places, bacteria, Population Groupings, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Antimicrobial Resistance, 030217 neurology & neurosurgery
Abstract

Antibiotic-resistance of hospital-acquired infections is a major public health issue. The worldwide emergence and diffusion of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, including Escherichia coli (ESBL-EC) and Klebsiella pneumoniae (ESBL-KP), is of particular concern. Preventing their nosocomial spread requires understanding their transmission. Using Close Proximity Interactions (CPIs), measured by wearable sensors, and weekly ESBL-EC–and ESBL-KP–carriage data, we traced their possible transmission paths among 329 patients in a 200-bed long-term care facility over 4 months. Based on phenotypically defined resistance profiles to 12 antibiotics only, new bacterial acquisitions were tracked. Extending a previously proposed statistical method, the CPI network’s ability to support observed incident-colonization episodes of ESBL-EC and ESBL-KP was tested. Finally, mathematical modeling based on our findings assessed the effect of several infection-control measures. A potential infector was identified in the CPI network for 80% (16/20) of ESBL-KP acquisition episodes. The lengths of CPI paths between ESBL-KP incident cases and their potential infectors were shorter than predicted by chance (P = 0.02), indicating that CPI-network relationships were consistent with dissemination. Potential ESBL-EC infectors were identified for 54% (19/35) of the acquisitions, with longer-than-expected lengths of CPI paths. These contrasting results yielded differing impacts of infection control scenarios, with contact reduction interventions proving less effective for ESBL-EC than for ESBL-KP. These results highlight the widely variable transmission patterns among ESBL-producing Enterobacteriaceae species. CPI networks supported ESBL-KP, but not ESBL-EC spread. These outcomes could help design more specific surveillance and control strategies to prevent in-hospital Enterobacteriaceae dissemination., Author summary Tracing extended-spectrum β-lactamase (ESBL) dissemination in hospitals is an important step in the fight against the spread of multi-drug resistant bacteria. Indeed, understanding ESBL spreading dynamics will help identify efficient control interventions. In the i-Bird study, patients and hospital staff from a French long-term care facility carried a wearable sensor to capture their interactions at less than 1.5 meters, every 30 seconds over a 4-month period. Every week, patients were also swabbed to detect carriage of ESBL-producing Enterobacteriaceae. Based on the analysis of these longitudinal data, this study shows that ESBL-producing Klebsiella pneumoniae (ESBL-KP) mostly spreads during close-proximity interactions between individuals, while this is not the case for ESBL-producing Escherichia coli (ESBL-EC), suggesting that ESBL-KP but not ESBL-EC may be controlled by contact reduction interventions.

Published
2019
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136. Mechanical properties and microstructural study of homogeneous and heterogeneous laser welds in α, β,and α + β titanium alloys

Author

Julien Zollinger, Laurent Weiss, Alexandre Mathieu, Eric Fleury, Pierre Sallamand, Eugen Cicala, Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux (LEM3), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM), Institut Jean Lamour (IJL), Université de Lorraine (UL)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interdisciplinaire Carnot de Bourgogne [Dijon] (LICB), and Université de Bourgogne (UB)-Université de Technologie de Belfort-Montbeliard (UTBM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Equiaxed crystals, 0209 industrial biotechnology, Thin layers, Materials science, Mechanical Engineering, Alloy, Metals and Alloys, Titanium alloy, 02 engineering and technology, Welding, [CHIM.MATE]Chemical Sciences/Material chemistry, engineering.material, Microstructure, 020501 mining & metallurgy, law.invention, 020901 industrial engineering & automation, 0205 materials engineering, Mechanics of Materials, law, Ultimate tensile strength, engineering, Composite material, Electron backscatter diffraction
Abstract

International audience; Heterogeneous welding has been investigated for three different couples of titanium alloys: α/α + β, α/β,andα + β/β. Plates of 100 × 60 mm and 1.6 or 1.8 mm thick were welded with a Yb:YAG laser. Tensile tests show that the resistance of the heterogeneous welded specimens was generally controlled by those of the weakest material except for the α + β/β where the ultimate tensile strength was approximately equal to the average value of both materials. In every case, the elongation of the welded sample was found to be smaller than that of the base metals. The rupture generally took place outside the weld metal and was found to be most of the time located in the alloy having the lowest mechanical properties. Nevertheless, a few large-size porosities detected by tomography in the α + β/β couple could explain why rupture for these samples occurred in the weld bead. For each couple, the porosities were situated at the board between the heat-affected zone and the molten zone. EBSD maps and EDX enabled the observation of different microstructures, which could be correlated to the heterogeneous composition and diffusion into the melted bath. When the stable microstructure of one of the couple alloys is the β phase, the molten zone of the bead consists of an alternative disposition of thin layers made of large equiaxed β grains and nano-martensite α′. That is explained by the weak diffusion of the alloying elements.

Published
2019
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137. Oxide dependent wear mechanisms of titanium against a steel counterface: Influence of SMAT nanostructured surface

Author

Laurent Weiss, Philippe Bocher, Eric Fleury, Pierre Maurel, Thierry Grosdidier, Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux (LEM3), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM), and Ecole de Technologie Supérieure [Montréal] (ETS)

Subjects
Third body, Nanostructure, Materials science, Kinetics, Oxide, chemistry.chemical_element, 02 engineering and technology, Surfaces and Interfaces, [CHIM.MATE]Chemical Sciences/Material chemistry, Tribology, 021001 nanoscience & nanotechnology, Condensed Matter Physics, Steel ball, Surfaces, Coatings and Films, chemistry.chemical_compound, 020303 mechanical engineering & transports, 0203 mechanical engineering, chemistry, Mechanics of Materials, Materials Chemistry, Composite material, 0210 nano-technology, Layer (electronics), Titanium
Abstract

International audience; The analysis of the tribological behavior of a steel ball on pure titanium has been carried out under alternative motion on both, a coarse grained Ti surface and its nanostructured derivative obtained by surface mechanical attrition treatment (SMAT). Along the duration of the tribology test, variations in friction behavior were interpreted as a three stages sequence of different wear mechanisms that were controlled by the successive formation of Ti-rich and Fe-rich oxides. Surface nanostructures appeared to change the oxide formation kinetics and delay the formation of a protective Fe-rich third body oxide layer on Ti. The results indicate that apparently contradicting literature results can be explained by taking into account the contamination induced during the SMAT process.

Published
2019
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138. On Absolute War : Terrorism and the Logic of Armed Conflict

Author

Eric Fleury and Eric Fleury

Subjects
Terrorism--History, War--History
Abstract

Nearly two decades after the declaration of a ‘War on Terror,'the precise relationship between warfare and terrorism remains unclear. The United States and its allies have long sought to inflict a decisive defeat upon groups such as Al Qaeda and ISIS, while regarding their individual members as malevolent criminals undeserving of combatant status. A clearer understanding of how terrorists define victory, and how their method of fighting relates to conventional military forces, is necessary in order to devise more realistic and effective strategies of counterterrorism. On Absolute War constructs a theoretical framework for the study of terrorism based on Carl von Clausewitz's On War, widely regarded as the greatest analysis of war ever written. Through a review of Clausewitz's work and a set of historical case studies ranging from the Fenian Dynamite Campaign of the 1880s to the wars in Iraq and Afghanistan, Prof. Fleury reveals just how closely terrorism mimics the logic of war. Terrorism attempts to restore war to its theoretical baseline, a condition that Clausewitz called ‘absolute war'featuring relentless escalation toward a climactic result. While never achieving this ideal in practice, terrorists succeed to the extent that they compel their enemies and their prospective followers to engage mutual escalation, which will ultimately favor whichever side is better able to jettison logistical and normative limits. Consequently, states must engage terrorists on the basis of Clausewitz's two most important injunctions, namely that war is temporary and subordinate to political controls. Given the very real prospect of a war without any temporal and spatial limits, On Absolute War provides the theoretical basis for a strategy of limiting the effects of terrorism, rather than repeatedly trying and failing to destroy it.

Published
2019

139. Sensor Networks : 6th International Conference, SENSORNETS 2017, Porto, Portugal, February 19-21, 2017, and 7th International Conference, SENSORNETS 2018, Funchal, Madeira, Portugal, January 22-24, 2018, Revised Selected Papers

Author

César Benavente-Peces, Nancy Cam-Winget, Eric Fleury, Andreas Ahrens, César Benavente-Peces, Nancy Cam-Winget, Eric Fleury, and Andreas Ahrens

Subjects
Computer networks
Abstract

This book constitutes the refereed proceedings of the 6th International Conference, SENSORNETS 2017, Porto, Portugal, held in February 2017, and the 7th International Conference, SENSORNETS 2018, Funchal, Madeira, Portugal, held in January 2018. The 18 full papers presented were carefully reviewed and selected from 67 submissions. The papers cover the following topics: sensor networks, including hardware of sensor networks, wireless communication protocols, sensor networks software and architectures, wireless information networks, data manipulation, signal processing, localization and object tracking through sensor networks, obstacles, applications and uses.

Published
2019

140. Hydrogen-induced decomposition of Cu–Zr binary amorphous metallic alloys

Author

Cheol-Hwee Shim, Soogyeong Han, Julien O. Fadonougbo, Jin-Yoo Suh, Gyeung-Ho Kim, Man-Ho Kim, Eric Fleury, Young Whan Cho, Korea Advanced Institute of Science and Technology (KAIST), Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux (LEM3), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Arts et Métiers Sciences et Technologies

Subjects
Diffraction, Materials science, Hydrogen, Analytical chemistry, chemistry.chemical_element, 02 engineering and technology, 010402 general chemistry, 01 natural sciences, 7. Clean energy, Condensed Matter::Materials Science, Materials Chemistry, Physics::Atomic Physics, Amorphous metal, Mechanical Engineering, Metals and Alloys, [CHIM.MATE]Chemical Sciences/Material chemistry, 021001 nanoscience & nanotechnology, Small-angle neutron scattering, Decomposition, 0104 chemical sciences, Amorphous solid, Crystallography, chemistry, Mechanics of Materials, Transmission electron microscopy, Nanometre, 0210 nano-technology
Abstract

International audience; The hydrogen-induced phase separation of Cu–Zr binary amorphous alloys during hydrogen gas charging at elevated temperature was demonstrated; the homogeneous binary alloy was decomposed into pure Cu and Zr-hydride by absorbing hydrogen into the structure. The decomposition, which is attributed to the opposed affinity to hydrogen of Cu and Zr, took place in nanometer scale. The hydrogen absorption kinetics was compared for the alloys with different compositions. The structure after hydrogen absorption was analyzed using x-ray diffraction, ultra-small and small angle neutron scattering, and electron microscopy.

Published
2016
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141. Erratum: 'Oxide dependent wear mechanisms of titanium against a steel counterface: Influence of SMAT nanostructured surface', [Wear, (2019) 430–431, 245–255]

Author

Philippe Bocher, Pierre Maurel, Thierry Grosdidier, Eric Fleury, and Laurent Weiss

Subjects
chemistry.chemical_compound, Materials science, chemistry, Mechanics of Materials, Metallurgy, Materials Chemistry, Oxide, chemistry.chemical_element, Surfaces and Interfaces, Condensed Matter Physics, Surfaces, Coatings and Films, Titanium
Published
2020
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142. Thermally-activated hardening recovery of thermo-elasto-plastic metals during annealing: Constitutive modeling for the simulation of welding process

Author

Georges Chatzigeorgiou, Eric Fleury, Fodil Meraghni, Francis Praud, J. Serri, L. Mouelle, Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux (LEM3), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), and This research was supported by Fives Cryo (Golbey, France) and Région Lorraine.

Subjects
Materials science, Plasticity, Annealing (metallurgy), Constitutive equation, 02 engineering and technology, Welding, [SPI.MECA.SOLID]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Solid mechanics [physics.class-ph], engineering.material, Annealing, law.invention, 0203 mechanical engineering, law, [SPI.MECA.MEMA]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanics of materials [physics.class-ph], General Materials Science, Mécanique: Mécanique des matériaux [Sciences de l'ingénieur], Austenitic stainless steel, Composite material, Instrumentation, Hardening recovery, Thermomechanical behavior, Mécanique: Mécanique des solides [Sciences de l'ingénieur], Elasto plastic, Constitutive model, 021001 nanoscience & nanotechnology, 020303 mechanical engineering & transports, Welding process, Mechanics of Materials, engineering, Hardening (metallurgy), 0210 nano-technology
Abstract

In this paper, a new thermodynamically-consistent modeling approach, dedicated to welding applications, is presented to describe the phenomenon of hardening recovery in metals during annealing. The constitutive equations are based on a classical thermo-elasto-plastic formulation, which is enhanced by a new recovery variable counterbalancing the effect of the hardening through a temperature-dependent evolution law. The identification of the model parameters is achieved through experimental compressive tests and heat treatments on 316L austenitic stainless steel. Finally, numerical simulations considering various thermomechanical loading configurations are carried out to evaluate the capabilities and limits of the model, which are furthermore illustrated in the context of welding applications through a FE example. This research was supported by Fives Cryo (Golbey, France) and Région Lorraine.

Published
2020
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143. Host contact dynamics shapes richness and dominance of pathogen strains

Author

Francesco Pinotti, Chiara Poletto, Didier Guillemot, Pierre-Yves Boëlle, Eric Fleury, Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Biostatistique, Biomathématique, Pharmacoépidémiologie et Maladies Infectieuses (B2PHI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), FP received funding from 'Pierre Louis' School of Public Health of UPMC (www.ed393.upmc.fr)., École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bodescot, Myriam, École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), and École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML)

Subjects
0301 basic medicine, Staphylococcus, Network structure, Pathogenesis, Pathology and Laboratory Medicine, 0302 clinical medicine, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Medicine and Health Sciences, Relative Abundance Distribution, Biology (General), Pathogen, 0303 health sciences, education.field_of_study, Contact behavior, Virulence, Ecology, Community structure, Population ecology, Bacterial Pathogens, 3. Good health, Computational Theory and Mathematics, Community Ecology, Medical Microbiology, Modeling and Simulation, Host-Pathogen Interactions, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Disease Susceptibility, Pathogens, Algorithms, Network Analysis, Research Article, Staphylococcus aureus, Computer and Information Sciences, Ecological Metrics, QH301-705.5, Population, Biology, Communicable Diseases, Microbiology, Host-Parasite Interactions, Cellular and Molecular Neuroscience, 03 medical and health sciences, Genetics, Disease Transmission, Infectious, Humans, Computer Simulation, Dynamical network, education, Molecular Biology, Microbial Pathogens, Community Structure, Ecology, Evolution, Behavior and Systematics, Relative abundance distribution, 030304 developmental biology, Bacteria, Population Biology, 030306 microbiology, Ecology and Environmental Sciences, Organisms, Biology and Life Sciences, Ecological indicator, 030104 developmental biology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Evolutionary biology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Population Ecology, Species richness, 030217 neurology & neurosurgery
Abstract

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains., Author summary Pathogens are structured in multiple strains that interact and co-circulate on the same host population. This ecological diversity affects, in many cases, the spread dynamics and the efficacy of vaccination and antibiotic treatment. Thus understanding its biological and host-behavioral drivers is crucial for outbreak assessment and for explaining trends of new-strain emergence. We used stochastic modeling and network theory to quantify the role of host contact behavior on strain richness and dominance. We systematically compared multi-strain spread on different network models displaying properties observed in real-world contact patterns. We then analyzed the real-case example of Staphylococcus aureus spread in a hospital, leveraging on a combined dataset of carriage and close proximity interactions. We found that contact dynamics has a profound impact on a strain population. Contact heterogeneity, for instance, reduces strain diversity by reducing the number of circulating strains and leading few strains to dominate over the others. These results have important implications in disease ecology and in the epidemiological interpretation of biological data.

Published
2018
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144. Structural homogeneity and mass density of bulk metallic glasses revealed by their rough surfaces and ultra-small angle neutron scattering (USANS)

Author

Eric Fleury, Man-Ho Kim, Kyung Tae Hong, Jin-Yoo Suh, and Su Gyeong Han

Subjects
Scattering from rough surfaces, Multidisciplinary, Amorphous metal, Materials science, Condensed matter physics, Scattering, lcsh:R, lcsh:Medicine, 02 engineering and technology, Neutron scattering, 021001 nanoscience & nanotechnology, 01 natural sciences, Small-angle neutron scattering, Article, Amorphous solid, 0103 physical sciences, Surface roughness, lcsh:Q, Small-angle scattering, lcsh:Science, 010306 general physics, 0210 nano-technology
Abstract

The ultra-small angle neutron scattering (USANS) measures the microscale structure of heterogeneity and the scattering from rough surfaces with small scattering volumes can be neglected. But this is not true in amorphous alloys. The small angle scattering from such surfaces is not negligible, regardless of scattering volume. However, we demonstrate that the unwanted rough surfaces can be utilized to determine the homogeneity and mass density of amorphous metallic glasses using the USANS and surface neutron contrast matching technique. The power law scattering of the homogeneous Cu50Zr50 amorphous alloy disappeared under the surface contrast-matched environment, a mixture of hydrogenated/deuterated ethanol having low surface tension against the metallic alloys, indicating that the scattering originated not from its internal structure but from the rough surface. This confirms the structural homogeneity not only at the atomic level but also on a larger scale of micrometer. On the other hand, the crystallized Cu50Zr50 alloy showed strong power-law scattering under the matching environment due to the structural heterogeneity inside the alloy. This technique can apply to the bulk samples when the transmission is high enough not causing multiple scattering that is easily detected with USANS and when the surface roughness is dominant source of scattering.

Published
2018
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145. Socioeconomic and network dependencies of linguistic patterns in Twitter

Author

Jacobo Levy Abitbol, Márton Karsai, JP Chevrot, Jean-Philippe Magué, Eric Fleury, Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM ), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut Rhône-Alpin des systèmes complexes (IXXI), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Interactions, Corpus, Apprentissages, Représentations (ICAR), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-INRP-Ecole Normale Supérieure Lettres et Sciences Humaines (ENS LSH)-Centre National de la Recherche Scientifique (CNRS), ANR-15-CE38-0011,SoSweet,Une sociolinguistique de Twitter : liens sociaux et variations linguistiques(2015), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-INRP-Ecole Normale Supérieure Lettres et Sciences Humaines (ENS LSH)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Grenoble Alpes (UGA)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-École normale supérieure - Lyon (ENS Lyon)

Subjects
[INFO.INFO-WB]Computer Science [cs]/Web, [INFO]Computer Science [cs], [SCCO.LING]Cognitive science/Linguistics, [SHS.LANGUE]Humanities and Social Sciences/Linguistics, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]
Abstract

International audience

Published
2018

146. Recueil de données massives de contacts sociaux en école maternelle : validation éthologique de l’utilisation des capteurs de proximité

Author

Hélène Bouchet, Màrton Karsai, Stéphanie Barbu, JP Chevrot, Eric Fleury, Aurélie Nardy, LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM ), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Ethologie animale et humaine (EthoS), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1, Société Française pour l'Etude du Comportement Animal, ANR-16-CE28-0013,DyLNet,Dynamiques langagières, apprentissages linguistiques et sociabilité à l'école maternelle : apport des capteurs de proximité pour le recueil de données massives(2016), LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM), Université Stendhal - Grenoble 3-Université Grenoble Alpes (UGA), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Lumière - Lyon 2 (UL2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Joseph Fourier - Grenoble 1 (UJF)-École normale supérieure - Lyon (ENS Lyon)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Joseph Fourier - Grenoble 1 (UJF), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS), ANR-16-CE28-0013,DyLNet,Dynamiques langagières, apprentissages linguistiques et sociabilité à l’école maternelle : apport des capteurs de proximité pour le recueil de données massives(2016), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), and École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML)

Subjects
[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior, [SCCO.NEUR]Cognitive science/Neuroscience, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2018

147. Prepaid or Postpaid? That Is the Question: Novel Methods of Subscription Type Prediction in Mobile Phone Services

Author

Martin Minnoni, Carlos Sarraute, Márton Karsai, Wei Du, Eric Fleury, Yongjun Liao, École normale supérieure de Lyon (ENS de Lyon), Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA), Laboratoire de l'Informatique du Parallélisme (LIP), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Grandata [Buenos Aires], ANR-15-CE38-0011,SoSweet,Une sociolinguistique de Twitter : liens sociaux et variations linguistiques(2015), ANR-13-CORD-0017,CODDDE,Communautés dynamiques, diffusion et détection d'événements(2013), École normale supérieure - Lyon (ENS Lyon), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
Behavioural prediction, Information retrieval, Computer science, Node (networking), Supervised learning, Subscription types, 02 engineering and technology, Indirect Inference, Type (model theory), [INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI], Terms of service, Mobile phone, Mobile phone services, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Key (cryptography), 020201 artificial intelligence & image processing, Graph labelling
Abstract

International audience; In this paper, we investigate the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. Our study reveals that (a) postpaid customers are more active in terms of service usage and (b) there are strong structural correlations in the mobile phone call network as connections between customers of the same subscription type are much more frequent than those between customers of different subscription types. Based on these observations, we provide methods to detect the subscription type of customers by using information about their personal call statistics, and also their egocentric networks simultaneously. The key of our first approach is to cast this classification problem as a problem of graph labelling, which can be solved by max-flow min-cut algorithms. Our experiments show that, by using both user attributes and relationships, the proposed graph labelling approach is able to achieve a classification accuracy of ∼87%, which outperforms by ∼7% supervised learning methods using only user attributes. In our second problem, we aim to infer the subscription type of customers of external operators. We propose via approximate methods to solve this problem by using node attributes, and a two-way indirect inference method based on observed homophilic structural correlations. Our results have straightforward applications in behavioural prediction and personal marketing.

Published
2018
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148. Socioeconomic Dependencies of Linguistic Patterns in Twitter: A Multivariate Analysis

Author

Jean-Pierre Chevrot, Eric Fleury, Jacob Levy Abitbol, Márton Karsai, Jean-Philippe Magué, Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Interactions, Corpus, Apprentissages, Représentations (ICAR), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-INRP-Ecole Normale Supérieure Lettres et Sciences Humaines (ENS LSH)-Centre National de la Recherche Scientifique (CNRS), Institut Rhône-Alpin des systèmes complexes (IXXI), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), LInguistique et DIdactique des Langues Étrangères et Maternelles (LIDILEM ), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), ANR-15-CE38-0011,SoSweet,Une sociolinguistique de Twitter : liens sociaux et variations linguistiques(2015), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-INRP-Ecole Normale Supérieure Lettres et Sciences Humaines (ENS LSH)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI)

Subjects
FOS: Computer and information sciences, Physics - Physics and Society, Computer science, Inference, FOS: Physical sciences, Machine Learning (stat.ML), 02 engineering and technology, Physics and Society (physics.soc-ph), Homophily, Computer Science - Computers and Society, Statistics - Machine Learning, Computers and Society (cs.CY), 0202 electrical engineering, electronic engineering, information engineering, Social network analysis, Socioeconomic status, 060201 languages & linguistics, Social and Information Networks (cs.SI), Computer Science - Computation and Language, Social network, business.industry, [INFO.INFO-WB]Computer Science [cs]/Web, Computer Science - Social and Information Networks, 06 humanities and the arts, [SCCO.LING]Cognitive science/Linguistics, Variety (linguistics), Linguistics, 0602 languages and literature, 020201 artificial intelligence & image processing, business, Computation and Language (cs.CL), Sociolinguistics
Abstract

Our usage of language is not solely reliant on cognition but is arguably determined by myriad external factors leading to a global variability of linguistic patterns. This issue, which lies at the core of sociolinguistics and is backed by many small-scale studies on face-to-face communication, is addressed here by constructing a dataset combining the largest French Twitter corpus to date with detailed socioeconomic maps obtained from national census in France. We show how key linguistic variables measured in individual Twitter streams depend on factors like socioeconomic status, location, time, and the social network of individuals. We found that (i) people of higher socioeconomic status, active to a greater degree during the daytime, use a more standard language; (ii) the southern part of the country is more prone to use more standard language than the northern one, while locally the used variety or dialect is determined by the spatial distribution of socioeconomic status; and (iii) individuals connected in the social network are closer linguistically than disconnected ones, even after the effects of status homophily have been removed. Our results inform sociolinguistic theory and may inspire novel learning methods for the inference of socioeconomic status of people from the way they tweet., In WWW 2018: The Web Conference, 10 pages, 6 figures

Published
2018
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149. Correlations and dynamics of consumption patterns in social-economic networks

Author

Eric Fleury, Márton Karsai, Yannick Léo, Carlos Sarraute, Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Grandata [Buenos Aires], ANR-15-CE38-0011,SoSweet,Une sociolinguistique de Twitter : liens sociaux et variations linguistiques(2015), ANR-13-CORD-0017,CODDDE,Communautés dynamiques, diffusion et détection d'événements(2013), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), and École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML)

Subjects
FOS: Computer and information sciences, Multivariate statistics, Physics - Physics and Society, FOS: Physical sciences, 02 engineering and technology, Physics and Society (physics.soc-ph), Recommender system, [INFO.INFO-MC]Computer Science [cs]/Mobile Computing, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Media Technology, Econometrics, Socioeconomic status, Consumption (economics), Social and Information Networks (cs.SI), Social network, business.industry, Communication, 05 social sciences, Computer Science - Social and Information Networks, Purchasing, Computer Science Applications, Human-Computer Interaction, Geography, Mobile phone, Resource allocation, 050211 marketing, 020201 artificial intelligence & image processing, business, Information Systems
Abstract

We analyse a coupled dataset collecting the mobile phone communications and bank transactions history of a large number of individuals living in a Latin American country. After mapping the social structure and introducing indicators of socioeconomic status, demographic features, and purchasing habits of individuals we show that typical consumption patterns are strongly correlated with identified socioeconomic classes leading to patterns of stratification in the social structure. In addition we measure correlations between merchant categories and introduce a correlation network, which emerges with a meaningful community structure. We detect multivariate relations between merchant categories and show correlations in purchasing habits of individuals. Finally, by analysing individual consumption histories, we detect dynamical patterns in purchase behaviour and their correlations with the socioeconomic status, demographic characters and the egocentric social network of individuals. Our work provides novel and detailed insight into the relations between social and consuming behaviour with potential applications in resource allocation, marketing, and recommendation system design., Comment: 20 pages, 8 figures, 1 table. Accepted in Social Analysis Network and Mining (Springer). arXiv admin note: substantial text overlap with arXiv:1609.03756

Published
2018
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150. Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics

Author

Audrey Duval, Thomas Obadia, Lucie Martinet, Pierre-Yves Boëlle, Eric Fleury, Didier Guillemot, Lulla Opatowski, Laura Temime, I-Bird study group, Biostatistique, Biomathématique, Pharmacoépidémiologie et Maladies Infectieuses (B2PHI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Bioinformatique évolutive - Evolutionary Bioinformatics, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris], Dynamic Networks : Temporal and Structural Capture Approach (DANTE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure - Lyon (ENS Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Epidémiologie, Systèmes d'Information, Modélisation, Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), This study was supported by the European Commission under the Life Science Health Priority of the 6th Framework Program (MOSAR network contract LSHP-CT-2007-037941). Funding was also received from the French Government through the National Clinical Research Program and the Investissement d’Avenir program, Laboratoire d’Excellence 'Integrative Biology of Emerging Infectious Diseases' (grant no. ANR-10-LABX-62-IBEID)., We thank Thomas Sorel for his work on the database and Judith Legrand for statistical advice, Consortia: I-Bird study group, Anne Sophie Alvarez, Audrey Baraffe, Mariano Beiró, Inga Bertucci, Camille Cyncynatus, Florence Dannet, Marie Laure Delaby, Pierre Denys, Matthieu Domenech de Cellès, Antoine Fraboulet, Jean-Louis Gaillard, Jean-Louis Herrmann, Boris Labrador, Jennifer Lasley, Christine Lawrence, Judith Legrand, Odile Le Minor, Caroline Ligier, Karine Mignon, Catherine Sacleux, Jérôme Salomon, Marie Perard, Laure Petit, Laeticia Remy, Anne Thiebaut, Damien Thomas, Philippe Tronchet & Isabelle Villain, ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut Rhône-Alpin des systèmes complexes (IXXI), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Jean Moulin - Lyon 3 (UJML), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Fleury, Eric, and Integrative Biology of Emerging Infectious Diseases - - IBEID2010 - ANR-10-LABX-0062 - LABX - VALID

Subjects
0301 basic medicine, Rehabilitation hospital, medicine.medical_specialty, Statistical methods, Epidemiology, lcsh:Medicine, Context (language use), Article, Care setting, 03 medical and health sciences, [INFO.INFO-MC]Computer Science [cs]/Mobile Computing, 0302 clinical medicine, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, medicine, 030212 general & internal medicine, Contact duration, Duration (project management), lcsh:Science, Health policy, Multidisciplinary, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Network topology, business.industry, lcsh:R, medicine.disease, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 3. Good health, Care facility, Experimental models of disease, 030104 developmental biology, lcsh:Q, Medical emergency, business
Abstract

Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.

Published
2018
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