150 resultados para Regional heterogeneity

em Université de Lausanne, Switzerland


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Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

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Language is typically a function of the left hemisphere but the right hemisphere is also essential in some healthy individuals and patients. This inter-subject variability necessitates the localization of language function, at the individual level, prior to neurosurgical intervention. Such assessments are typically made by comparing left and right hemisphere language function to determine "language lateralization" using clinical tests or fMRI. Here, we show that language function needs to be assessed at the region and hemisphere specific level, because laterality measures can be misleading. Using fMRI data from 82 healthy participants, we investigated the degree to which activation for a semantic word matching task was lateralized in 50 different brain regions and across the entire cortex. This revealed two novel findings. First, the degree to which language is lateralized across brain regions and between subjects was primarily driven by differences in right hemisphere activation rather than differences in left hemisphere activation. Second, we found that healthy subjects who have relatively high left lateralization in the angular gyrus also have relatively low left lateralization in the ventral precentral gyrus. These findings illustrate spatial heterogeneity in language lateralization that is lost when global laterality measures are considered. It is likely that the complex spatial variability we observed in healthy controls is more exaggerated in patients with brain damage. We therefore highlight the importance of investigating within hemisphere regional variations in fMRI activation, prior to neuro-surgical intervention, to determine how each hemisphere and each region contributes to language processing. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.

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PURPOSE: To determine the relationship between carotid intima-media thickness (IMT), coronary artery calcification (CAC), and myocardial blood flow (MBF) at rest and during vasomotor stress in type 2 diabetes mellitus (DM). METHODS: In 68 individuals, carotid IMT was measured using high-resolution vascular ultrasound, while the presence of CAC was determined with electron beam tomography (EBT). Global and regional MBF was determined in milliliters per gram per minute with (13)N-ammonia and positron emission tomography (PET) at rest, during cold pressor testing (CPT), and during adenosine (ADO) stimulation. RESULTS: There was neither a relationship between carotid IMT and CAC (r = 0.10, p = 0.32) nor between carotid IMT and coronary circulatory function in response to CPT and during ADO (r = -0.18, p = 0.25 and r = 0.10, p = 0.54, respectively). In 33 individuals, EBT detected CAC with a mean Agatston-derived calcium score of 44 +/- 18. There was a significant difference in regional MBFs between territories with and without CAC at rest and during ADO-stimulated hyperemia (0.69 +/- 0.24 vs. 0.74 +/- 0.23 and 1.82 +/- 0.50 vs. 1.95 +/- 0.51 ml/g/min; p < or = 0.05, respectively) and also during CPT in DM but less pronounced (0.81 +/- 0.24 vs. 0.83 +/- 0.23 ml/g/min; p = ns). The increase in CAC was paralleled with a progressive regional decrease in resting as well as in CPT- and ADO-related MBFs (r = -0.36, p < or = 0.014; r = -0.46, p < or = 0.007; and r = -0.33, p < or = 0.041, respectively). CONCLUSIONS: The absence of any correlation between carotid IMT and coronary circulatory function in type 2 DM suggests different features and stages of early atherosclerosis in the peripheral and coronary circulation. PET-measured MBF heterogeneity at rest and during vasomotor stress may reflect downstream fluid dynamic effects of coronary artery disease (CAD)-related early structural alterations of the arterial wall.

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The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

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RESUME Nous n'avons pas de connaissance précise des facteurs à l'origine de l'hétérogénéité phénotypique des cellules T CD4 mémoires. Une troisième population phénotypique des cellules T CD4 mémoires, caractérisée par les marqueurs CD45RA+CCR7- a été identifiée dans cette étude. Cette population présente un état de différentiation avancée, comme en témoigne son histoire de réplication, ainsi que sa capacité de prolifération homéostatique. Les réponses des cellules T CD4 mémoires à différentes conditions de persistance et charge antigénique ont trois patterns phénotypiques différents, caractérisés par les marqueurs CD45RA et CCR7. La réponse CD4 mono -phénotypique CD45RA-CCR7+ ou CD45RA- CCR7- est associée à des conditions d'élimination de l'antigène (telle la réponse CD4 tétanos spécifique) ou à des conditions de persistance antigénique et de virémie élevée (telle la réponse HIV chronique ou la primo-infection CMV) respectivement. D'autre part, les réponses T CD4 multi -phénotypiques CD45RA-CCR7+ sont associées à des conditions d'exposition antigénique prolongée et de faible virémie (telles les infections CMV, EBV et HSV ou les infections HIV chez les long term non progressons). La réponse mono -phénotypique CD45RA- CCR7+ est propre aux cellules T CD4 secrétant de IL2, définies également comme centrales mémoires, la réponse CD45RA- CCR7- aux cellules T CD4 secrétant de l'IFNγ et finalement la réponse mufti-phénotypique aux cellules T CD4 secrétant à la fois de l'IL2 et de l' IFNγ. En conclusion, ces résultats témoignent d'une régulation de l'hétérogénéité phénotypique par l'exposition et la charge antigénique. ABSTRACT The factors responsible for the phenotypic heterogeneity of memory CD4 T cells are unclear. In the present study, we have identified a third population of memory CD4 T cells characterized as CD45RA+CCRT that, based on its replication history and the homeostatic proliferative capacity, was at an advanced stage of differentiation. Three different phenotypic patterns of memory CD4 T cell responses were delineated under different conditions of antigen (Ag) persistence and load using CD45RA and CCR7 as markers of memory T cells. Mono-phenotypic CD45RA'CCR7+ or CD45RA'CCR7' CD4 T cell responses were associated with conditions of Ag clearance (tetanus toxoid-specific CD4 T cell response) or Ag persistence and high load (chronic HIV-1 and primary CMV infections), respectively. Multi-phenotypic CD45RA CCR7+, CD45RA'CCRT and CD45RA+CCRT CD4 T cell responses were associated with protracted Ag exposure and low load (chronic CMV, EBV and HSV infections and HIV-1 infection in long-term nonprogressors). The mono-phenotypic CD45RA'CCR7+ response was typical of central memory (TCM) IL-2-secreting CD4 T cells, the mono-phenotypic CD45RA CCRT response of effector memory (TEM) IFN-γ -secreting CD4 T cells and the multi-phenotypic response of both IL-2- and IFN-γ -secreting cells. The present results indicate that the heterogeneity of different Ag-specific CD4 T cell responses is regulated by Ag exposure and Ag load.

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Purpose: The purpose of this study was to compare the plaque morphology between coronary and peripheral arteries using intravascular ultrasound (IVUS). Methods: IVUS was performed in 68 patients with coronary and 93 with peripheral artery lesions (29 carotid, 50 renal, and 14 iliac). Plaques were classified as fibroatheroma (VH-FA) (further subclassified as thin-capped [VH-TCFA] and thick-capped [VH-ThCFA]), fibrocalcific plaque (VH-FC) and pathological intimal thickening (VH-PIT). Results: Plaque rupture (13% of coronary, 7% of carotid, 6% of renal, and 7% of iliac arteries; P=NS) and VH-TCFA (37% of coronary, 24% of carotid, 16% of renal, and 7% of iliac arteries; P=0.02) was observed in all arteries. Compared to coronary arteries, VH-FA was less frequently observed in renal (P<0.001) and iliac arteries (P<0.006), while VH-PIT and VH-FC were prevalent in both of these peripheral arteries. Lesions with positive remodeling demonstrated more characteristics of VH-FA in coronary, carotid, and renal arteries compared to those with intermediate/negative remodeling (all P<0.01). There was positive relationship between RI and percent necrotic core area in all four arteries. Conclusions: Atherosclerotic plaque phenotypes were heterogeneous among four different arteries. In contrast, the associations of remodeling mode with plaque phenotype and composition were similar among the various arterial beds.

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We have identified C7orf11, which localizes to the nucleus and is expressed in fetal hair follicles, as the first disease gene for nonphotosensitive trichothiodystrophy (TTD). C7orf11 maps to chromosome 7p14, and the disease locus has been designated "TTDN1" (TTD nonphotosensitive 1). Mutations were found in patients with Amish brittle-hair syndrome and in other nonphotosensititive TTD cases with mental retardation and decreased fertility but not in patients with Sabinas syndrome or Pollitt syndrome. Therefore, genetic heterogeneity in nonphotosensitive TTD is a feature similar to that observed in photosensitive TTD, which is caused by mutations in transcription factor II H (TFIIH) subunit genes. Comparative immunofluorescence analysis, however, suggests that C7orf11 does not influence TFIIH directly. Given the absence of cutaneous photosensitivity in the patients with C7orf11 mutations, together with the protein's nuclear localization, C7orf11 may be involved in transcription but not DNA repair.

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The prevalence of clonal complex (CC) 398 methicillin-susceptible Staphylococcus aureus (MSSA) was unexpectedly high among bone and joint infections (BJIs) and nasal-colonizing isolates in France, with surprising geographical heterogeneity. With none of the major, most-known staphylococcal virulence genes, MSSA CC398 BJI was associated with lower biological inflammatory syndrome and lower treatment failure rates.

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Debris flow susceptibility mapping at a regional scale has been the subject of various studies. The complexity of the phenomenon and the variability of local controlling factors limit the use of process-based models for a first assessment. GISbased approaches associating an automatic detection of the source areas and a simple assessment of the debris flow spreading may provide a substantial basis for a preliminary susceptibility assessment at the regional scale. The use of a digital elevation model, with a 10 m resolution, for the Canton de Vaud territory (Switzerland), a lithological map and a land use map, has allowed automatic identification of the potential source areas. The spreading estimates are based on basic probabilistic and energy calculations that allow to define the maximal runout distance of a debris flow.

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The expression of Ia-like antigen (Ia) has been studied in 55 cases of acute myeloid leukaemia (AML) in correlation with the expression of both Sudan Black (SB) and naphthol AS-D chloroacetate esterase (NCAE) stains. Operationally the AML cases were divided into three groups using only NCAE expression on the leukaemic cells: the first group with early maturation stage (MS1) consisted of 30 cases with less than 10% NCAE positive cells (SB: 15-100%): the MS2 group of 14 cases with 10-70% NCAE positive cells (SB: 65-100%) and the MS3 group of 11 cases with 70-100% NCAE positive cells (SB: 89-100%). Ia expression was determined by complement-dependent cytotoxicity, immunofluorescence and immunoperoxidase methods. A similar high percentage (80%) of patients from both group MS1 and MS2 expressed Ia on the surface of 32-100% of the cells. Furthermore, individual comparison of all cases from these two groups showed no correlation between Ia, NCAE and SB expression. Only in the 11 cases from the MS3 group, which included nine cases of promyelocytic leukaemias, was there a correlation between very low expression of Ia antigen with the high NCAE expression. Thus, for AML with a low degree of differentiation the expression of Ia seems to be independent of conventional cytochemical markers of cell maturation.

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Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.