A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population.

BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Using environmental niche modeling to understand biological invasions in a changing world

L'activité humaine affecte particulièrement la biodiversité, qui décline à une vitesse préoccupante. Parmi les facteurs réduisant la biodiversité, on trouve les espèces envahissantes. Symptomatiques d'un monde globalisé où l'échange se fait à l'échelle de la planète, certaines espèces, animales ou végétales, sont introduites, volontairement ou accidentellement par l'activité humaine (par exemple lors des échanges commerciaux ou par les voyageurs). Ainsi, ces espèces atteignent des régions qu'elles n'auraient jamais pu coloniser naturellement. Une fois introduites, l'absence de compétiteur peut les rendre particulièrement nuisibles. Ces nuisances sont plus ou moins directes, allant de problèmes sanitaires (p. ex. les piqûres très aigües des fourmis de feu, originaires d'Amérique du Sud et colonisant à une vitesse fulgurante les USA, l'Australie ou la Chine) à des nuisances sur la biodiversité (p. ex. les ravages de la perche du Nil sur la diversité unique des poissons Cichlidés du Lac Victoria). Il est donc important de pouvoir prévenir de telles introductions. De plus, pour le biologiste, ces espèces représentent une rare occasion de pouvoir comprendre les mécanismes évolutifs et écologiques qui expliquent le succès des envahissantes dans un monde où les équilibres sont bouleversés. Les modèles de niche environnementale sont un outil particulièrement utile dans le cadre de cette problématique. En reliant des observations d'espèces aux conditions environnementales où elles se trouvent, ils peuvent prédire la distribution potentielle des envahissantes, permettant d'anticiper et de mieux limiter leur impact. Toutefois, ils reposent sur des hypothèses pas évidentes à démontrer. L'une d'entre elle étant que la niche d'une espèce reste constante dans le temps, et dans l'espace. Le premier objectif de mon travail est de comparer si la niche d'une espèce envahissante diffère entre sa distribution d'origine native et celle d'origine introduite. En étudiant 50 espèces de plantes et 168 espèces de Mammifères, je démontre que c'est le cas et que par corolaire, il est possible de prédire leurs distributions. La deuxième partie de mon travail consiste à comprendre quelles seront les interactions entre le changement climatiques et les envahissantes, afin d'estimer leur impact sous un climat réchauffé. En étudiant la distribution de 49 espèces de plantes envahissantes, je démontre que les montagnes, régions relativement préservée par ce problème, deviendront bien plus exposées aux risques d'invasions biologiques. J'expose aussi comment les interactions entre l'activité humaine, le réchauffement climatique et les espèces envahissantes menacent la vigne sauvage en Europe et propose des zones géographiques particulièrement adaptée pour sa conservation. Enfin, à une échelle beaucoup plus locale, je montre qu'il est possible d'utiliser ces modèles de niches le long d'une rivière à une échelle extrêmement fine (1 mètre), potentiellement utile pour rationnaliser des mesures de conservations sur le terrain. - Biodiversity is significantly negatively affected by human activity. Invasive species are one of the most important factors causing biodiversity's decline. Intimately linked to the era of global trade, some plant or animal species can be accidentally or casually introduced with human activity (e.g. trade or travel). In this way, these species reach areas they could never reach through natural dispersal. Once naturalized, the lack of competitors can make these species highly noxious. Their effect is more or less direct, from sanitary problems (e.g. the harmful sting of Fire Ants, originating from South America and now spreading throughout USA, China and Australia) or can affect biodiversity (e.g. the Nile perch, devastating the one of the richest hotspot of Cichlid fishes diversity in Lake Victoria). It is thus important to prevent such harmful introductions. Moreover, invasive species represent for biologists one of the rare occasions to understand the evolutionary and ecological mechanisms behind the success of invaders in a world where natural equilibrium is already disturbed. Environmental niche models are particularly useful to tackle this problematic. By relating species observation to the environmental conditions where they occur, they can predict the potential distribution of invasive species, allowing a better anticipation and thus limiting their impact. However, they rely on strong assumption, one of the most important being that the modeled niche remains constant through space and time. The first aim of my thesis is to quantify the difference between the native and the invaded niche. By investigating 50 plant and 168 mammal species, I show that the niche is at least partially conserved, supporting for reliable predictions of invasive' s potential distributions. The second aim of my thesis is to understand the possible interactions between climate change and invasive species, such as to assess their impact under a warmer climate. By studying 49 invasive plant species, I show that mountain areas, which were relatively preserved, will become more suitable for biological invasions. Additionally, I show how interactions between human activity, global warming and invasive species are threatening the wild grapevine in Europe and propose geographical areas particularly adapted for conservation measures. Finally, at a much finer scale where conservation plannings ultimately take place, I show that it is possible to model the niche at very high resolution (1 meter) in an alluvial area allowing better prioritizations for conservation.

Debris flow susceptibility mapping at a regional scale along the National Road N7, Argentina

A first assessment of debris flow susceptibility at a large scale was performed along the National Road N7, Argentina. Numerous catchments are prone to debris flows and likely to endanger the road-users. A 1:50,000 susceptibility map was created. The use of a DEM (grid 30 m) associated to three complementary criteria (slope, contributing area, curvature) allowed the identification of potential source areas. The debris flow spreading was estimated using a process- and GISbased model (Flow-R) based on basic probabilistic and energy calculations. The best-fit values for the coefficient of friction and the mass-to-drag ratio of the PCM model were found to be ? = 0.02 and M/D = 180 and the resulting propagation on one of the calibration site was validated using the Coulomb friction model. The results are realistic and will be useful to determine which areas need to be prioritized for detailed studies.

Fine-scale genetic structure and marginal processes in an expanding population of Biscutella laevigata L. (Brassicaceae).

Evolutionary processes acting at the expanding margins of a species' range are still poorly understood. Genetic drift is considered prevalent in marginal populations, and the maintenance of genetic diversity during recolonization might seem puzzling. To investigate such processes, a fine-scale investigation of 219 individuals was performed within a population of Biscutella laevigata (Brassicaceae), located at the leading edge of its range. The survey used amplified fragment length polymorphisms (AFLPs). As commonly reported across the whole species distribution range, individual density and genetic diversity decreased along the local axis of recolonization of this expanding population, highlighting the enduring effect of the historical colonization on present-day diversity. The self-incompatibility system of the plant may have prevented local inbreeding in newly found patches and sustained genetic diversity by ensuring gene flow from established populations. Within the more continuously populated region, spatial analysis of genetic structure revealed restricted gene flow among individuals. The distribution of genotypes formed a mosaic of relatively homogenous patches within the continuous population. This pattern could be explained by a history of expansion by long-distance dispersal followed by fine-scale diffusion (that is, a stratified dispersal combination). The secondary contact among expanding patches apparently led to admixture among differentiated genotypes where they met (that is, a reshuffling effect). This type of dynamics could explain the maintenance of genetic diversity during recolonization.

Experimental plant communities develop phylogenetically overdispersed abundance distributions during assembly

The importance of competition between similar species in driving community assembly is much debated. Recently, phylogenetic patterns in species composition have been investigated to help resolve this question: phylogenetic clustering is taken to imply environmental filtering, and phylogenetic overdispersion to indicate limiting similarity between species. We used experimental plant communities with random species compositions and initially even abundance distributions to examine the development of phylogenetic pattern in species abundance distributions. Where composition was held constant by weeding, abundance distributions became overdispersed through time, but only in communities that contained distantly related clades, some with several species (i.e., a mix of closely and distantly related species). Phylogenetic pattern in composition therefore constrained the development of overdispersed abundance distributions, and this might indicate limiting similarity between close relatives and facilitation/complementarity between distant relatives. Comparing the phylogenetic patterns in these communities with those expected from the monoculture abundances of the constituent species revealed that interspecific competition caused the phylogenetic patterns. Opening experimental communities to colonization by all species in the species pool led to convergence in phylogenetic diversity. At convergence, communities were composed of several distantly related but species-rich clades and had overdispersed abundance distributions. This suggests that limiting similarity processes determine which species dominate a community but not which species occur in a community. Crucially, as our study was carried out in experimental communities, we could rule out local evolutionary or dispersal explanations for the patterns and identify ecological processes as the driving force, underlining the advantages of studying these processes in experimental communities. Our results show that phylogenetic relations between species provide a good guide to understanding community structure and add a new perspective to the evidence that niche complementarity is critical in driving community assembly.

Genetic and phenotypic population divergence on a microgeographic scale in brown trout.

Salmonid populations of many rivers are rapidly declining. One possible explanation is that habitat fragmentation increases genetic drift and reduces the populations' potential to adapt to changing environmental conditions. We measured the genetic and eco-morphological diversity of brown trout (Salmo trutta) in a Swiss stream system, using multivariate statistics and Bayesian clustering. We found large genetic and phenotypic variation within only 40 km of stream length. Eighty-eight percent of all pairwise F(ST) comparisons and 50% of the population comparisons in body shape were significant. High success rates of population assignment tests confirmed the distinctiveness of populations in both genotype and phenotype. Spatial analysis revealed that divergence increased with waterway distance, the number of weirs, and stretches of poor habitat between sampling locations, but effects of isolation-by-distance and habitat fragmentation could not be fully disentangled. Stocking intensity varied between streams but did not appear to erode genetic diversity within populations. A lack of association between phenotypic and genetic divergence points to a role of local adaptation or phenotypically plastic responses to habitat heterogeneity. Indeed, body shape could be largely explained by topographic stream slope, and variation in overall phenotype matched the flow regimes of the respective habitats.

Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

The mapping of the local contributions of Fermi and Coulomb correlation into intracule and extracule density distributions

The contributions of the correlated and uncorrelated components of the electron-pair density to atomic and molecular intracule I(r) and extracule E(R) densities and its Laplacian functions ∇2I(r) and ∇2E(R) are analyzed at the Hartree-Fock (HF) and configuration interaction (CI) levels of theory. The topologies of the uncorrelated components of these functions can be rationalized in terms of the corresponding one-electron densities. In contrast, by analyzing the correlated components of I(r) and E(R), namely, IC(r) and EC(R), the effect of electron Fermi and Coulomb correlation can be assessed at the HF and CI levels of theory. Moreover, the contribution of Coulomb correlation can be isolated by means of difference maps between IC(r) and EC(R) distributions calculated at the two levels of theory. As application examples, the He, Ne, and Ar atomic series, the C2-2, N2, O2+2 molecular series, and the C2H4 molecule have been investigated. For these atoms and molecules, it is found that Fermi correlation accounts for the main characteristics of IC(r) and EC(R), with Coulomb correlation increasing slightly the locality of these functions at the CI level of theory. Furthermore, IC(r), EC(R), and the associated Laplacian functions, reveal the short-ranged nature and high isotropy of Fermi and Coulomb correlation in atoms and molecules

The relevance of the Laplacian of intracule and extracule density distributions for analyzing electron-electron interactions in molecules

A topological analysis of intracule and extracule densities and their Laplacians computed within the Hartree-Fock approximation is presented. The analysis of the density distributions reveals that among all possible electron-electron interactions in atoms and between atoms in molecules only very few are located rigorously as local maxima. In contrast, they are clearly identified as local minima in the topology of Laplacian maps. The conceptually different interpretation of intracule and extracule maps is also discussed in detail. An application example to the C2H2, C2H4, and C2H6 series of molecules is presented

A comparative analysis by means of quantum molecular similarity measures of density distributions derived from conventional ab initio and density functional methods

A procedure based on quantum molecular similarity measures (QMSM) has been used to compare electron densities obtained from conventional ab initio and density functional methodologies at their respective optimized geometries. This method has been applied to a series of small molecules which have experimentally known properties and molecular bonds of diverse degrees of ionicity and covalency. Results show that in most cases the electron densities obtained from density functional methodologies are of a similar quality than post-Hartree-Fock generalized densities. For molecules where Hartree-Fock methodology yields erroneous results, the density functional methodology is shown to yield usually more accurate densities than those provided by the second order Møller-Plesset perturbation theory

Assessing dystrophies and other muscle diseases at the nanometer scale by atomic force microscopy.

AIM: Atomic force microscopy nanoindentation of myofibers was used to assess and quantitatively diagnose muscular dystrophies from human patients. MATERIALS & METHODS: Myofibers were probed from fresh or frozen muscle biopsies from human dystrophic patients and healthy volunteers, as well as mice models, and Young's modulus stiffness values were determined. RESULTS: Fibers displaying abnormally low mechanical stability were detected in biopsies from patients affected by 11 distinct muscle diseases, and Young's modulus values were commensurate to the severity of the disease. Abnormal myofiber resistance was also observed from consulting patients whose muscle condition could not be detected or unambiguously diagnosed otherwise. DISCUSSION & CONCLUSION: This study provides a proof-of-concept that atomic force microscopy yields a quantitative read-out of human muscle function from clinical biopsies, and that it may thereby complement current muscular dystrophy diagnosis.

Seismic attenuation and velocity dispersion in heterogeneous partially saturated porous rocks

Using a numerical approach, we explore wave-induced fluid flow effects in partially saturated porous rocks in which the gas-water saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighbouring regions can exhibit different levels of saturation. To determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. The multiscale nature of the fluid saturation is taken into account by locally computing the physical properties of an effective fluid, which are then used for the larger-scale simulations. We consider two sets of numerical experiments to analyse such effects in heterogeneous partially saturated porous media, where the saturation field is determined by variations in porosity and clay content, respectively. In both cases we also evaluate the seismic responses of corresponding binary, patchy-type saturation patterns. Our results indicate that significant attenuation and modest velocity dispersion effects take place in this kind of media for both binary patchy-type and spatially continuous gas saturation patterns and in particular in the presence of relatively small amounts of gas. The numerical experiments also show that the nature of the gas distribution patterns is a critical parameter controlling the seismic responses of these environments, since attenuation and velocity dispersion effects are much more significant and occur over a broader saturation range for binary patchy-type gas-water distributions. This analysis therefore suggests that the physical mechanisms governing partial saturation should be accounted for when analysing seismic data in a poroelastic framework. In this context, heterogeneities associated with the dry frame properties, which do not play important roles in wave-induced fluid flow processes per se, should be taken into account since they may determine the kind of gas distribution pattern taking place in the porous rock.

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.