Éditeur(s) : HAL CCSD VertigO
Résumé : International audience
Les submersions marines sont le plus souvent associées à des conditions météorologiques locales de tempête et aux phénomènes bien connus de surcote résultant du cumul de l’effet barométrique inverse et des vents d'afflux. Le déferlement des vagues joue également un rôle prépondérant dans la surélévation totale. Il provoque des variations du niveau d’eau de deux types : une surélévation statique du niveau moyen (surcote de vague) et des variations instantanées provoquées par le jet de rive. Ces deux phénomènes sont responsables dans certains cas de plus de 2/3 de la surélévation totale. Lors de la circulation des cyclones Lenny et Omar, le littoral ouest de l’île de la Martinique a été considérablement affecté. Les surélévations du niveau marin lors du passage au large de ces deux cyclones ont été reconstituées pour le nord-ouest de l'ile et particulièrement sur les plages de la commune de St Pierre. Les facteurs de variations du niveau marin ont été décomposés et modélisés en emboîtement d'échelles à partir des modèles ADCIRC pour les composantes de marée et de surcotes météorologiques, SWAN pour la propagation des vagues en zone côtière et les surcotes de vague et enfin pCOULWAVE pour le jet de rive. Ce travail de décomposition des facteurs de variations du niveau marin, associé à la reconstitution par enquêtes de terrain et témoignages, des limites des inondations, met en avant la vulnérabilité de la commune face aux houles cycloniques et la nécessité de prendre en compte l’ensemble des facteurs de variation du niveau marin dans l’étude de l’aléa de submersion et les documents de prévention des risques.
ISSN: 1492-8442

hal-01119372
https://hal-brgm.archives-ouvertes.fr/hal-01119372
https://hal-brgm.archives-ouvertes.fr/hal-01119372/document
https://hal-brgm.archives-ouvertes.fr/hal-01119372/file/Nicolae%20et%20al%202014%20Vertigo-15326-modelisation-lenny-1999-et-omar-2008.pdf
DOI : 10.4000/vertigo.15326

Éditeur(s) : HAL CCSD
Résumé : International audience
The 20th Caribbean Academy of Sciences Biennal Meeting was held in Guadeloupe, FWI, on November 24 th to 26 th, 2016. It has gathered over 130 participants from more than 14 countries within or outside the Caribbean. In this booklet, you may find all abstracts form the scientific sessions, and the desciption of two round tables and three symposiums. Sessions were as followed :- Poster session- Mathematics and Informatics- Science Education- Physics of the Athmosphere- Medical Sciences (1)- Interface and Material Physics- Radiochemistry and Nuclear Medicine and Biomolecules- Interdisciplinary Oral Session- Biology- Hydrology and Hydrodynamics- Material and Environmental Chemistry- Medical Sciences (2)
https://hal.univ-antilles.fr/hal-01413318
Dehaies, Guadeloupe

hal-01413318
https://hal.univ-antilles.fr/hal-01413318
https://hal.univ-antilles.fr/hal-01413318v2/document
https://hal.univ-antilles.fr/hal-01413318/file/CAS_2016_Booklet.pdf

Éditeur(s) : HAL CCSD Public Library of Science
Résumé : International audience
Understanding how communities respond to natural disturbances is fundamental to assess the mechanisms of ecosystem resistance and resilience. However, ecosystem responses to natural disturbances are rarely monitored both through space and time, while the factors promoting ecosystem stability act at various temporal and spatial scales. Hence, assessing both the spatial and temporal variations in species composition is important to comprehensively explore the effects of natural disturbances. Here, we suggest a framework to better scrutinize the mechanisms underlying community responses to disturbances through both time and space. Our analytical approach is based on beta diversity decomposition into two components, replacement and biomass difference. We illustrate this approach using a 9-year monitoring of coral reef fish communities off Moorea Island (French Polynesia), which encompassed two severe natural disturbances: a crown-of-thorns starfish outbreak and a hurricane. These disturbances triggered a fast logistic decline in coral cover, which suffered a 90% decrease on all reefs. However, we found that the coral reef fish composition remained largely stable through time and space whereas compensatory changes in bio-mass among species were responsible for most of the temporal fluctuations, as outlined by the overall high contribution of the replacement component to total beta diversity. This suggests that, despite the severity of the two disturbances, fish communities exhibited high resistance and the ability to reorganize their compositions to maintain the same level of total community biomass as before the disturbances. We further investigated the spatial congruence of this pattern and showed that temporal dynamics involved different species across sites; yet, herbivores controlling the proliferation of algae that compete with coral communities were consistently favored. These results suggest that compensatory changes in bio-mass among species and spatial heterogeneity in species responses can provide further
ISSN: 1932-6203

hal-01212344
https://hal-univ-perp.archives-ouvertes.fr/hal-01212344
https://hal-univ-perp.archives-ouvertes.fr/hal-01212344/document
https://hal-univ-perp.archives-ouvertes.fr/hal-01212344/file/journal.pone.0138696.pdf
DOI : 10.1371/journal.pone.0138696

Éditeur(s) : HAL CCSD
Résumé : International audience
“Affective Computing is computing that relates to, arises from, or deliberately influences emotions” (R.W. Picard, MIT Press, 1997). Specifically, psychosocial equilibrium is now considered as a major issue for both individual and public health. Predicting human emotions via non-intrusive methods is a great challenge triggered by the rise of intelligent assisting systems. In order to determine the emotional state of a subject having a potential psychosocial disorder, it is required to process both neutral and expressive emotions. A computer-engineered method aiming to provide emotional information from videos is proposed. An original approach for affect classification and its interpretation is presented.The database is part of the HUMAINE database, and consists of a large volume of video clips, each displaying individuals, depressed or not, talking with a conversational agent. Both the high-dimensionality of data and its temporal aspect require a pre-training that consists of cleaning, sorting and feature selection, in order to make relevant information usable for further processing by MachineLearning methods. Next step consists in classifying the affective state of subjects according to their positivity or negativity (Russell's model, 1980). By means of six independent classifiers, each running a Support Vector Machine algorithm, separate performances are obtained for each class of emotions. The results reveal an interesting “neutral area phenomenon”, where emotions tend to be harder to be detected.Though more frequent, neutral emotions seem to carry less discriminant information than expressive ones. This issue will be a key for designing a tuning step in further research.
Caribbean Academy Of Science
Deshaies, France

hal-01408029
https://hal.univ-antilles.fr/hal-01408029