Éditeur(s) : HAL CCSD
Résumé : International audience
To study social health inequalities, contextual data may constitute an appropriate alternative to individual socioeconomic characteristics, often hard to retrieve. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. The main objectives of this work are to develop a statistical procedure to create a neighborhood socioeconomic index and to investigate the influence of the clustering method of the deprivation index on the measure of health inequalities. Our study setting is composed of three major French metropolitan areas: Lille, Lyon and Marseille. The statistical unit is the French census block. The methodology uses several successive principal components analyses to select variables and create the index. Deprivation categories are drawn with hierarchical clustering on principal components. Twenty socioeconomic variables are selected in the neighborhood deprivation index. An optimal clustering obtained by HC is in three classes and the clusters are ordered along the first axis of the PCA.
SFDS - 44èmes journées de Statistique - 2012
Bruxelles, Belgium

hal-00734769
https://hal.archives-ouvertes.fr/hal-00734769
https://hal.archives-ouvertes.fr/hal-00734769/document
https://hal.archives-ouvertes.fr/hal-00734769/file/submission_44.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
Background: Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise...) or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare.Aims: We propose to use data mining techniques to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach on a large French metropolitan area.Methods: The study was carried out in the Great Lyon area (France, 1,260,348 inhabitants in 2007, 527 km²) at the census block group (BG) scale. Indicators on NO2 annual concentrations, noise levels, proximity to green spaces and to industrial plants, and road traffic were synthetized using Multiple Factor Analysis (MFA), which allows to explore the relations between exposures and BGs without a priori knowledge, and to synthetize indicators of different types. Hierarchical clustering was then used to create BG classes. Results: The four first components of the MFA explained respectively 23, 14, 13 and 12% of the total variance. Clustering in 3 classes group: 1) BGs far from industries, greener and with less noise and air pollution than the average; 2) BGs close to industries with less green spaces and air pollution than the average; and 3)BGs far from industries but with higher levels of noise, air pollution and traffic. Greater numbers of classes were tested in order to assess a variety of clustering.Conclusions: We present a data driven approach using data mining techniques, which seem overlooked for cumulative exposure assessment in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.
Environment and Health – Bridging South, North, East and West. Conference of ISEE, ISES and ISIAQ.
Basel, Switzerland

hal-01432884
https://hal.archives-ouvertes.fr/hal-01432884
https://hal.archives-ouvertes.fr/hal-01432884/document
https://hal.archives-ouvertes.fr/hal-01432884/file/Poster_2013_ISEE_20130711.pdf

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
Background: Despite intensive research over several decades, the etiology of multiple sclerosis (MS) remains poorly understood, although environmental factors are supposedly implicated. Our goal was to identify spatial clusters of MS incident cases at the small-area level to provide clues to local environmental risk factors that might cause or trigger the disease. Methods: A population-based and multi-stage study was performed in the French Brittany region to accurately ascertain the clinical onset of disease during the 2000-2004 period. The municipality of residence at the time of clinical onset was geocoded. To test for the presence of MS incidence clusters and to identify their approximate locations, we used a spatial scan statistic. We adjusted for socioeconomic deprivation, known to be strongly associated with increased MS incident rates, and scanned simultaneously for areas with either high or low rates. Sensitivity analyses (focusing on relapsing-remitting forms and/or places of residence available within the year following clinical onset) were performed. Results: A total of 848 incident cases of MS were registered in Brittany, corresponding to a crude annual incidence rate of 5.8 per 100,000 inhabitants. The spatial scan statistic did not find a significant cluster of MS incidence in either the primary analysis (p value >= 0.56) or in the sensitivity analyses (p value >= 0.16). Conclusion: The findings of this study indicate that MS incidence is not markedly affected across space, suggesting that in the years preceding the first clinical expression of the disease, no environmental trigger is operative at the small-area population level in the French Brittany region.
ISSN: 1476-072X

hal-01616063
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01616063
DOI : 10.1186/s12942-017-0108-6
PUBMED : 28934989

Éditeur(s) : HAL CCSD
Résumé :  Diffusion du document : INRA Antilles-Guyane, UMR ECOFOG, F97387 Kourou, Guyane (France)Diplôme : Master Recherche
il s'agit d'un type de produit dont les métadonnées ne correspondent pas aux métadonnées attendues dans les autres types de produit : DISSERTATION
Origin and maintenance of species diversity is one of the main questions in evolutive biology. Species complexes, ie sister species still exchanging genes, are common in tropical forests and contribute to this diversity. This poster describes the organization of the genetic diversity in two closely related tree species, Carapa guianensis and C. procera, which are in sympatry in French Guiana. By using a clustering method based on nuclear markers (Pritchard et al. 2000), 506 trees sampled in French Guiana have been assigned to a species. Interestingly, many individuals harbored intermediate genome and we assigned to an hybrid group. The geographic distribution of these individuals revealed the presence of a contact zone between the two carapa species in the Eastern part of French Guiana. We then analysed genetic diversity at cholroplast genome and revealed a symmetrical gene flow between the two sister species. In addition, hybridization between hybrids and parental species ar likely possible but still need validations thanks to control crosses. Within species, we finally revealed the presence of a departure from the neutral equilibrium in thedirection of a population expansion likely related to Holocene perturbations. This expansion may have contributed to the hybrid zone formation in French Guiana.
L'origine et le maintien de la diversité spécifique des forêts tropicales humides est une question clé en biologie évolutive. Ce travail contribue à améliorer la compréhension de ces mécanismes à travers l'étude de la distribution de la diversité génétique de deux espèces sœurs interfertiles, le Carapa procera et C. guianensis en Guyane. L'assignation botanique des arbres échantillonnés (506) a été effectuée en adoptant une approche moléculaire qui repose sur l'analyse de la répartition des fréquences alléliques de six microsatellites nucléaires (Pritchard et al. 2000). Chaque locus présente des allèles dont les différences de fréquences entre espèces sont importantes, permettant ainsi d'envisager des outils simples de reconnaissances pour ces espèces difficilement identifiables sur la seule base de leurs caractères phénotypiques. Une zone de contact des deux espèces où les phénomènes d'hybridations sont fréquents a par ailleurs été localisée. En associant une analyse de la diversité au niveau du génome chloroplastique sur un sous ensemble d'individus (244), j'ai pu montrer que l'introgression est bidirectionnelle et que les backcross sont possibles. Les flux de gènes entre les deux espèces sont fréquents, et à l'intérieur des espèces, les populations sont peu structurées bien que la différenciation soit significative entre les sites les plus éloignés. Enfin, ce travail met en évidence que les populations de chacune des deux espèces présentent un signal d'expansion de population, avec un signal plus fort pour le C. procera, qui laisse présager une expansion récente, vraisemblablement à l'origine de la zone de contact. L'impact des évènements climatiques et/ou des activités amérindiennes des 10 000 dernières années pourrait expliquer la restriction puis l'expansion de ce genre post pionnier.
https://hal.archives-ouvertes.fr/hal-01189488

hal-01189488
https://hal.archives-ouvertes.fr/hal-01189488
PRODINRA : 42333

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In French Guiana, severe cases of toxoplasmosis in immunocompetent patients are associated with atypical strains of Toxoplasma gondii linked to a wild neotropical rainforest cycle and a higher genetic diversity than usually observed for T. gondii isolates from anthropized environment. This raises the question of the impact of anthropization of the natural environment, on genetic diversity and on the population structure of T. gondii. However, few data are available on strains circulating in the anthropized areas from French Guiana. Seropositive animals originating mainly from anthropized sub-urban areas and punctually from wild environment in French Guiana were analyzed for T. gondii isolation and genotyping. Thirty-three strains were obtained by bioassay in mice and compared with 18 previously reported isolates chiefly originating from the Amazon rainforest. The genotyping analysis performed with 15 microsatellite markers located on 12 different chromosomes revealed a lower genetic diversity in the anthropized environment. Results were analyzed in terms of population structure by clustering methods, Neighbor-joining trees reconstruction based on genetic distances, F(ST,) Mantel's tests and linkage disequilibrium. They clearly showed a genetic differentiation between strains associated to the anthropized environment and those associated to the wild, but with some inbreeding between them. The majority of strains from the anthropized environment were clustered into additional lineages of T. gondii that are common in the Caribbean. In conclusion the two environmental populations "wild" and "anthropized" were genetically well differentiated. The anthropization of the environment seems to be accompanied with a decreased diversity of T. gondii associated with a greater structure of the populations. We detected potential interpenetration and genetic exchanges between these two environmental populations. As a higher pathogenicity in human of "wild" genotypes has been described, the interpenetration of both environments leads to hybridization between strains that may be at risk for human health.
ISSN: 1567-1348

pasteur-00654105
https://hal-riip.archives-ouvertes.fr/pasteur-00654105
https://hal-riip.archives-ouvertes.fr/pasteur-00654105/document
https://hal-riip.archives-ouvertes.fr/pasteur-00654105/file/Mercier_et_al_IGE2011.pdf
DOI : 10.1016/j.meegid.2011.05.003

Éditeur(s) : HAL CCSD Seismological Society of America
Résumé : International audience
We present an improvement of the maximum intersection (MAXI) method in which absolute earthquake location is defined by the maximum intersection number of hyperbolic equal differential time (EDT) volumes (one EDT volume being described as all grid nodes satisfying the arrival‐time differences between two stations, ± a tolerance value known as TERR). This 3D technique is well adapted to a strongly heterogeneous environment, avoids the depth versus origin‐time trade‐off (even using P arrivals alone), and objectively filters possible erroneous arrival times. Improvements consist of introducing an iterative multiscale approach on the TERR parameter and conducting a hierarchy of grid discretization to refine the preliminary solution (multigrid algorithm). The outlier cleaning process is strengthened by conducting statistical analyses based on the number of EDT volume intersections per station, rather than on travel‐time residues. Processing two series of synthetic arrival times computed in the 3D seismological configuration of the southernmost Ryukyu subduction zone, offshore Taiwan, allows us to (1) confirm MAXI robustness, even when arrival times are highly disturbed or azimuthal coverage largely reduced, and (2) show that MAXI, by limiting trade‐offs between origin time and depth and between epicentral position and depth, is less affected by a wrong velocity model than a technique that minimizes travel‐time residues. To conclude, we apply the MAXI method to locate earthquakes recorded by the combined Central Weather Bureau of Taiwan (CWB) and the Japanese Meteorological Agency (JMA) networks (1991-2008) within a georealistic a priori 3D P‐velocity model. Hypocenter determinations are selected based on MAXI confidence factors, and earthquake clustering along well‐known tectonic features witnesses hypocenter determination accuracy.
ISSN: 0037-1106

hal-00725227
https://hal.archives-ouvertes.fr/hal-00725227
DOI : 10.1785/0120100311

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Numerous methods have been proposed in order to perform clustering from social networks. While significant works have been carried out on the design of new approaches, able to search for various kinds of clusters, a major challenge concerns the scalability of these approaches. Indeed, given the mass of data that can now be collected from online social networks, particularly from social platforms, it is important to have efficient methods for exploring and analyzing these very large amount of data. One of the recent social network clustering approaches is the extraction of conceptual links, a new approach that performs link clustering by exploiting both the structure of the network and attributes of nodes to identify strong links between groups of nodes in which nodes share common attributes. In this paper, we focus on the optimization of the search for conceptual links. In particular, we propose PALM, a parallel algorithm that aims to improve the efficiency of the extraction by simultaneously exploring several areas of the search space. For this purpose, we begin by demonstrating that the solution space forms a concept lattice. Then, we propose an approach that explores in parallel the branches of the lattice while reducing the search space based on various properties of conceptual links. We demonstrate the efficiency of the algorithm by comparing the performances with the original extraction approach. The results obtained show a significant gain on the computation time.
28th International Conference on Database and Expert Systems Applications (DEXA)
Lyon, France

hal-01637554
https://hal.archives-ouvertes.fr/hal-01637554
DOI : 10.1007/978-3-319-64471-4_21

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

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

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Recently, a large amount of work has been devoted to the study of spectral clustering — a powerful unsupervised classification method. This paper brings contributions to both its foundations, and its applications to text classification. Departing from the mainstream, concerned with hard membership, we study the extension of spectral clustering to soft membership (probabilistic, EM style) assignments. One of its key features is to avoid the complexity gap of hard membership. We apply this theory to a challenging problem, text clustering for languages having permeable borders, via a novel construction of Markov chains from corpora. Experiments with a readily available code clearly display the potential of the method, which brings a visually appealing soft distinction of languages that may define altogether a whole corpus.
ISSN: 0031-3203

hal-00329991
https://hal.archives-ouvertes.fr/hal-00329991
DOI : 10.1016/j.patcog.2008.06.024

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
ABSTRACT: BACKGROUND: Climate change poses unprecedented challenges, ranging from global and local policy challenges to personal and social action. Heat-related deaths are largely preventable, but interventions for the most vulnerable populations need improvement. Therefore, the prior identification of high risk areas at the community level is required to better inform planning and prevention. We aimed to demonstrate a simple and flexible conceptual framework relying upon satellite thermal data and other digital data with the goal of easily reproducing this framework in a variety of urban configurations. RESULTS: The study area encompasses Rennes, a medium-sized French city. A Landsat ETM + image (60 m resolution) acquired during a localized heatwave (June 2001) was used to estimate land surface temperature (LST) and derive a hazard index. A land-use regression model was performed to predict the LST. Vulnerability was assessed through census data describing four dimensions (socio-economic status, extreme age, population density and building obsolescence). Then, hazard and vulnerability indices were combined to deliver a heatwave health risk index. The LST patterns were quite heterogeneous, reflecting the land cover mosaic inside the city boundary, with hotspots of elevated temperature mainly observed in the city center. A spatial error regression model was highly predictive of the spatial variation in the LST (R2 = 0.87) and was parsimonious. Three land cover descriptors (NDVI, vegetation and water fractions) were negatively linked with the LST. A sensitivity analysis (based on an image acquired on July 2000) yielded similar results. Southern areas exhibited the most vulnerability, although some pockets of higher vulnerability were observed northeast and west of the city. The heatwave health risk map showed evidence of infra-city spatial clustering, with the highest risks observed in a north--south central band. Another sensitivity analysis gave a very high correlation between 2000 and 2001 risk indices (r = 0.98, p < 10-12). CONCLUSIONS: Building on previous work, we developed a reproducible method that can provide guidance for local planners in developing more efficient climate impact adaptations. We recommend, however, using the health risk index together with hazard and vulnerability indices to implement tailored programs because exposure to heat and vulnerability do not require the same prevention strategies.
ISSN: 1476-072X

inserm-00762303
http://www.hal.inserm.fr/inserm-00762303
http://www.hal.inserm.fr/inserm-00762303/document
http://www.hal.inserm.fr/inserm-00762303/file/1476-072X-11-38.pdf
DOI : 10.1186/1476-072X-11-38

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
BACKGROUND: Few studies have explored how noise might contribute to social health inequalities, and even fewer have considered infant mortality or its risk factors as the health event of interest.In this paper, we investigate the impact of neighbourhood characteristics - both socio-economic status and ambient noise levels - on the spatial distribution of infant mortality in the Lyon metropolitan area, in France. METHODS: All infant deaths (n = 715) occurring between 2000 and 2009 were geocoded at census block level. Each census block was assigned multi-component socio-economic characteristics and Lden levels, which measure exposure to noise. Using a spatial-scan statistic, we examined whether there were significant clusters of high risk of infant mortality according to neighbourhood characteristics. RESULTS: Our results highlight the fact that infant mortality is non-randomly distributed spatially, with clusters of high risk in the south-east of the Lyon metropolitan area (RR = 1.44; p = 0.09). After adjustments for socio-economic characteristics and noise levels, this cluster disappears or shifts according to in line with different scenarios, suggesting that noise and socio-economic characteristics can partially explain the spatial distribution of infant mortality. CONCLUSION: Our findings show that noise does have an impact on the spatial distribution of mortality after adjustments for socio-economic characteristics. A link between noise and infant mortality seems plausible in view of the three hypothetical, non-exclusive, pathways we propose in our conceptual framework: (i) a psychological pathway, (ii) a physiological disruption process and (iii) an unhealthy behaviours pathway. The lack of studies makes it is difficult to compare our findings with others. They require further research for confirmation and interpretation.
ISSN: 1476-069X

Droits : info:eu-repo/semantics/OpenAccess
inserm-00924503
http://www.hal.inserm.fr/inserm-00924503
http://www.hal.inserm.fr/inserm-00924503/document
http://www.hal.inserm.fr/inserm-00924503/file/1476-069X-12-109.pdf
PUBMED : 24341620

Éditeur(s) : Centre français du littoral
Résumé : This study presents the first results of an ongoing research program that aims to derive thematic maps of the intertidal lagoon of Arcachon (SW Atlantic coast of France) from space imagery. At this stage, we present the results of the tests performed on Formosat-2 imagery. Several classification strategies have been tried with the aim to discriminate the sedimentary facies and the main species of the lagoon. The classes calculated by an optimized unsupervised clustering method, based on simulated annealing global minimization technique, were used to train a supervised classification algorithm. This approach allowed us to derive a bio-sedimentary map which overall accuracy is about 84%. Also, this method has the advantage of describing the fraction of vegetation cover of the seagrass.
Cette étude présente les premiers résultats d’un vaste programme de recherche qui ambitionne de définir une méthode de cartographie des platiers intertidaux du Bassin d’Arcachon (France) par télédétection. Les résultats présentés ici concernent les tests effectués sur l’imagerie Formosat-2 dans le but de discriminer les sédiments et les principales espèces végétales de la lagune. Le résultat d'une classification non supervisée optimisée par la méthode du recuit simulé est ensuite utilisé pour entraîner une classification par minimum de distance. Cette approche permet d’obtenir une carte des faciès bio-sédimentaires dont la précision est estimée à plus de 84 %. Cette méthode présente, en outre, un excellent potentiel pour la détermination du pourcentage de couvert végétal des herbiers à zostères.
Paralia (1760-8716) (Centre français du littoral), 2008 , N. 10 , P. 563-572

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/00254/36572/35110.pdf
DOI:10.5150/jngcgc.2008.054-L
http://archimer.ifremer.fr/doc/00254/36572/

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
A comprehensive inventory of global biodiversity would be greatly improved by automating methods for species delimitation. The Automatic Barcode Gap Discovery method, the Poisson tree processes algorithm and the Generalized mixed Yule coalescent model have been proposed as means of increasing the rate of biodiversity description using single locus data. We applied these methods to explore the diversity within the Aglaopheniidae, a hydrozoan family with many species widely distributed across tropical and tem perate oceans. Our analyses revealed widespread cryptic diversity in this family, almost half of the morpho species presenting several independent evolutionary lineages, as well as support for cases of synonymy. For two common species of this family, Lytocarpia brevirostris and Macrorhynchia phoenicea, we compared the outputs to clustering analyses based on microsatellite data and to nuclear gene phylo genies. For L. brevirostris, microsatellite data were congruent with results of the species delimitation methods, revealing the existence of two cryptic species with Indo Pacific distribution. For M. phoenicea, all analyses confirmed the presence of two cryptic species within the South Western Indian Ocean. Our study suggests that the diversity of Aglaopheniidae might be much higher than assumed, likely related to low dispersal capacities. Sequence based species delimitation methods seem highly valuable to reveal cryptic diversity in hydrozoans; their application in an integrative framework will be very useful in describing the phyletic diversity of these organisms.
ISSN: 1055-7903

hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407
https://hal.archives-ouvertes.fr/hal-01359407/document
https://hal.archives-ouvertes.fr/hal-01359407/file/Postaire-etal2016MolPhylEvol_sp_delim_hydraires_HAL.pdf
DOI : 10.1016/j.ympev.2016.08.013

Éditeur(s) : HAL CCSD Geological Society of America
Résumé : International audience
In this study, a novel application of a statistical approach is utilized for analysis of downhole logging data from Miocene-aged siliciclastic shelf sediments on the New Jersey Margin (eastern USA). A multivariate iterative nonhierarchical cluster analysis (INCA) of spectral gamma-ray logs from Integrated Ocean Drilling Program (IODP) Expedition 313 enables lithology within this siliciclastic succession to be inferred and, through comparison with the 1311 m of recovered core, a continuous assessment of depositional sequences is constructed. Signifi cant changes in INCA clusters corroborate most key stratigraphic surfaces interpreted from the core, and this result has particular value for surface recognition in intervals of poor core recovery. This analysis contributes to the evaluation of sequence stratigraphic models of large-scale clinoform complexes that predict depositional environments, sediment composition, and stratal geometries in response to sea-level changes. The novel approach of combining statistical analysis with detailed lithostratigraphic and seismic refl ection data sets will be of interest to any scientists working with downhole logs, especially spectral gamma-ray data, and also provides a reference for the strengths and weaknesses of multi component analysis applied to continental margin lithofacies. The method presented here is appropriate for evaluating successions elsewhere and also has value for hydrocarbon exploration where sequence stratigraphy is a fundamental tool.
EISSN: 1553-040X

insu-00858238
https://hal-insu.archives-ouvertes.fr/insu-00858238
DOI : 10.1130/GES00913.1

Éditeur(s) : HAL CCSD
Résumé : National audience
Designing systems able to interact with students in a natural manner is a complex and far from solved problem. A key aspect of natural interaction is the ability to understand and appropriately respond to human emotions. This paper details our response to the continuous Audio/Visual Emotion Challenge (AVEC'12) whose goal is to predict four affective signals describing human emotions. The proposed method uses Fourier spectra to extract multi-scale dynamic descriptions of signals characterizing face appearance, head movements and voice. We perform a kernel regression with very few representative samples selected via a supervised weighted-distance-based clustering, that leads to a high generalization power. We also propose a particularly fast regressor-level fusion framework to merge systems based on different modalities. Experiments have proven the efficiency of each key point of the proposed method and our results on challenge data were the highest among 10 international research teams.
IHM'14, 26e conférence francophone sur l'Interaction Homme-Machine
Lille, France

hal-01089628
https://hal.archives-ouvertes.fr/hal-01089628
https://hal.archives-ouvertes.fr/hal-01089628/document
https://hal.archives-ouvertes.fr/hal-01089628/file/p44-nicole.pdf

Éditeur(s) : HAL CCSD IRD
Résumé : International audience
Malaria remains a major health problem in French Guiana despite the decrease in the number of cases since 2010. A previous study in Camopi, an Amerindian village on the Oyapock River, revealed that Plasmodium falciparum malaria incidence was significantly related to landscape features and that its spatial distribution exhibited some obvious patterns. In the present study, we first identified the spatial patterns that exhibit a significant Moran's index of spatial auto-correlation and that significantly explain P. falciparum malaria incidence within the multiple linear regression framework. Secondly, we linked these patterns with remotely sensed environmental features. The selected model is composed of five spatial components: three patterns, representing 50.7% of the total variance, are associated with large scale variations of the incidence, and the remaining patterns are associated with local scale variations and represent 28.7% of the total variance. Different hamlet clusters that have specificities in terms of P. falciparum malaria incidence rate, environmental characteristics and mosquito control strategies have been identified. The methodology proposed in the present study can provide useful knowledge on the spatial distribution of the P. falciparum malaria incidence in Camopi at different scales and on possible explanation of such distribution, as a function of the scale.
Symposium of the Latin American Society for Remote Sensing and Spatial Information Systems (SELPER)
Cayenne, French Guiana

ird-00797353
http://hal.ird.fr/ird-00797353
http://hal.ird.fr/ird-00797353/document
http://hal.ird.fr/ird-00797353/file/Roux_et_al_SELPER_2012.pdf
IRD : fdi:010058342

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
These last years, many analysis methods have been proposed to extract knowledge from social networks. As for the traditional data mining domain, these network-based approaches can be classified according to two main families. The approaches based on predictive modelling, which encompass the techniques that analyse current and historical facts to make predictive assumptions about future or unknown events. The approaches based on descriptive modelling, which cover the set of techniques that aim to summarize the data by identifying some relevant features in order to describe how things organize and actually work. In this paper, we review the main descriptive modelling methods of social networks and show for each of them the resulting useful knowledge on a running example. We particularly emphasize on the most recent methods that combine information available on both the network structure and the node attributes in order to provide original description models taking into account the context.
EISSN: 1877-0509

hal-01312383
https://hal.univ-antilles.fr/hal-01312383
DOI : 10.1016/j.procs.2015.05.505

Éditeur(s) : HAL CCSD Oxford Journals
Résumé : International audience
Background - Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France.Methods - All adult patients living in Bretagne and beginning renal replacement therapy during the 2004–09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence.Results - The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted.Conclusions - Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.
Clinical Kidney Journal

hal-01118626
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01118626
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01118626/document
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01118626/file/Spatial%20distribution%20of%20end-stage%20renal%20disease.pdf
DOI : 10.1093/ckj/sfu131

Éditeur(s) : Colloque IMBC - International Marine Biotechnology Conference
Résumé : Since 1997, a new pathology seasonally occurs in new caledonian shrimp farms during the warm season. Diseased Litopenaeus stylirostris shrimp suffer from a systemic vibriosis which was attributed to highly pathogenic Vibrio nigripulchritudo. At the present time, only two farms among 17 are affected by the so called "summer syndrome". In such a context it appears urgent to develop reliable diagnostic tools to detect V. nigripulchritudo strains and to differentiate highly virulent strains from non virulent ones in order to understand the mechanisms of infection and overcome disease spreading. Multilocus Sequencing Typing (MLST) analysis on 24 bacterial strains isolated in geographically distinct shrimp farms highlighted the existence of a cluster A containing only strains displaying moderate to high virulence. Since experimental infection procedure for virulence status determination is material intensive and time consuming, and MLST method not accurate enough to inform on the virulence status of strains, it appeared of great interest to develop other diagnostic tools. Two phylogenetically closed strains, one highly virulent SFn1 and the other non-virulent SFn118 were selected in order to characterize genes specific of the virulent strain by Substractive Suppression Hybridization (SSH). Firstly, a total of 622 DNA fragments specific of SFn1 were sequenced, characterized and further used as probes in a DNA macroarray. Testing 24 strains, hybridization profiles were found to be strongly correlated with both MLST genotypes and bacterial virulence status. A total of 96 representative probes were secondly selected to validate macroarray results on 34 more additionnal strains, allowing identification of genetic markers of virulence. Most of DNA fragments specific of highly virulent strains associated to summer syndrome were found to be bore by a plasmid successfully isolated in the laboratory. In next future, these results would permit the development of relevant diagnostic tools useful for accurate epidemiological survey of the summer syndrome.

Droits : info:eu-repo/semantics/openAccess
http://archimer.ifremer.fr/doc/2007/acte-3398.pdf
http://archimer.ifremer.fr/doc/00000/3398/

Éditeur(s) : HAL CCSD
Résumé : International audience
We propose in this article a color image segmentation technique based on an optimization of the Mean Shift method. It consists in classifying clusters of data points of a digital image, it does not require any preliminary designation of the number of classes and of their centers. The Mean Shift method applied to a digital color image creates a new image made up of aggregates of points belonging to a finished number of color classes. The complexity of this method based on a global approach of the image is in O(NxN), N being the number of pixels of the image. Our idea consists in applying a change of scale to the image to be segmented, to reduce the quantity of information and, in using a median filter to decrease the number of colors to minimize the complexity of the latter. The comparative study which we present shows that the optimization which we proposed gives better, reliable results than the classic use of the Mean Shift method.
Complex, Intelligent and Software Intensive Systems, International Conference
Cracovie, Poland

hal-00508427
https://hal.archives-ouvertes.fr/hal-00508427
DOI : 10.1109/CISIS.2010.62