Control of landslide retrogression by discontinuities: Evidence by the integration of airbone- and ground-based geophysical information

The objective of this work is to present a multitechnique approach to define the geometry, the kinematics, and the failure mechanism of a retrogressive large landslide (upper part of the La Valette landslide, South French Alps) by the combination of airborne and terrestrial laser scanning data and ground-based seismic tomography data. The advantage of combining different methods is to constrain the geometrical and failure mechanism models by integrating different sources of information. Because of an important point density at the ground surface (4. 1 points m?2), a small laser footprint (0.09 m) and an accurate three-dimensional positioning (0.07 m), airborne laser scanning data are adapted as a source of information to analyze morphological structures at the surface. Seismic tomography surveys (P-wave and S-wave velocities) may highlight the presence of low-seismic-velocity zones that characterize the presence of dense fracture networks at the subsurface. The surface displacements measured from the terrestrial laser scanning data over a period of 2 years (May 2008?May 2010) allow one to quantify the landslide activity at the direct vicinity of the identified discontinuities. An important subsidence of the crown area with an average subsidence rate of 3.07 m?year?1 is determined. The displacement directions indicate that the retrogression is controlled structurally by the preexisting discontinuities. A conceptual structural model is proposed to explain the failure mechanism and the retrogressive evolution of the main scarp. Uphill, the crown area is affected by planar sliding included in a deeper wedge failure system constrained by two preexisting fractures. Downhill, the landslide body acts as a buttress for the upper part. Consequently, the progression of the landslide body downhill allows the development of dip-slope failures, and coherent blocks start sliding along planar discontinuities. The volume of the failed mass in the crown area is estimated at 500,000 m3 with the sloping local base level method.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

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.

Toward an integration of spirituality and religiousness into the psychosocial dimension of schizophrenia.

OBJECTIVE: Spirituality and religiousness have been shown to be highly prevalent among patients with schizophrenia. However, clinicians are rarely aware of the importance of religion and understand little of the value or difficulties it presents to treatment. This study aimed to assess the role of religion as a mediating variable in the process of coping with psychotic illness. METHOD: Semistructured interviews about religious coping were conducted with a sample of 115 outpatients with psychotic illness. RESULTS: For some patients, religion instilled hope, purpose, and meaning in their lives (71%), whereas for others, it induced spiritual despair (14%). Patients also reported that religion lessened (54%) or increased (10%) psychotic and general symptoms. Religion was also reported to increase social integration (28%) or social isolation (3%). It may reduce (33%) or increase (10%) the risk of suicide attempts, reduce (14%) or increase (3%) substance use, and foster adherence to (16%) or be in opposition to (15%) psychiatric treatment. CONCLUSIONS: Our results highlight the clinical significance of religion in the care of patients with schizophrenia. Religion is neither a strictly personal matter nor a strictly cultural one. Spirituality should be integrated into the psychosocial dimension of care. Our results suggest that the complexity of the relationship between religion and illness requires a highly sensitive approach to each unique story.

Activation of a HIF1alpha-PPARgamma axis underlies the integration of glycolytic and lipid anabolic pathways in pathologic cardiac hypertrophy.

Development of cardiac hypertrophy and progression to heart failure entails profound changes in myocardial metabolism, characterized by a switch from fatty acid utilization to glycolysis and lipid accumulation. We report that hypoxia-inducible factor (HIF)1alpha and PPARgamma, key mediators of glycolysis and lipid anabolism, respectively, are jointly upregulated in hypertrophic cardiomyopathy and cooperate to mediate key changes in cardiac metabolism. In response to pathologic stress, HIF1alpha activates glycolytic genes and PPARgamma, whose product, in turn, activates fatty acid uptake and glycerolipid biosynthesis genes. These changes result in increased glycolytic flux and glucose-to-lipid conversion via the glycerol-3-phosphate pathway, apoptosis, and contractile dysfunction. Ventricular deletion of Hif1alpha in mice prevents hypertrophy-induced PPARgamma activation, the consequent metabolic reprogramming, and contractile dysfunction. We propose a model in which activation of the HIF1alpha-PPARgamma axis by pathologic stress underlies key changes in cell metabolism that are characteristic of and contribute to common forms of heart disease.

Stage-specific integration of maternal and embryonic peroxisome proliferator-activated receptor delta signaling is critical to pregnancy success.

Successful pregnancy depends on well coordinated developmental events involving both maternal and embryonic components. Although a host of signaling pathways participate in implantation, decidualization, and placentation, whether there is a common molecular link that coordinates these processes remains unknown. By exploiting genetic, molecular, pharmacological, and physiological approaches, we show here that the nuclear transcription factor peroxisome proliferator-activated receptor (PPAR) delta plays a central role at various stages of pregnancy, whereas maternal PPARdelta is critical to implantation and decidualization, and embryonic PPARdelta is vital for placentation. Using trophoblast stem cells, we further elucidate that a reciprocal relationship between PPARdelta-AKT and leukemia inhibitory factor-STAT3 signaling pathways serves as a cell lineage sensor to direct trophoblast cell fates during placentation. This novel finding of stage-specific integration of maternal and embryonic PPARdelta signaling provides evidence that PPARdelta is a molecular link that coordinates implantation, decidualization, and placentation crucial to pregnancy success. This study is clinically relevant because deferral of on time implantation leads to spontaneous pregnancy loss, and defective trophoblast invasion is one cause of preeclampsia in humans.

Effets des supplémentations en calcium et vitamine D sur la maladie cardiovasculaire. [Effects of calcium and vitamin D supplementations on cardiovascular disease: review article].

Studies exploring the effect of calcium supplementation on cardiovascular risk suggest that systolic blood pressure decreases with supplementation. A lower calcium intake has been associated with an increased risk of stroke. By contrast, calcium supplementation may increase the risk of myocardial infarction. The effect of vitamin D supplementation on blood pressure is still unclear and no effect of vitamin D supplementation on coronary heart disease or stroke has been clearly demonstrated. There is a lack of randomized clinical trials primarily addressing the effect of these parameters on CVD. Currently, the use of calcium and vitamin D supplementations for the prevention of cardiovascular disease is not justified.

Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

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.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Selective integration of auditory-visual looming cues by humans.

An object's motion relative to an observer can confer ethologically meaningful information. Approaching or looming stimuli can signal threats/collisions to be avoided or prey to be confronted, whereas receding stimuli can signal successful escape or failed pursuit. Using movement detection and subjective ratings, we investigated the multisensory integration of looming and receding auditory and visual information by humans. While prior research has demonstrated a perceptual bias for unisensory and more recently multisensory looming stimuli, none has investigated whether there is integration of looming signals between modalities. Our findings reveal selective integration of multisensory looming stimuli. Performance was significantly enhanced for looming stimuli over all other multisensory conditions. Contrasts with static multisensory conditions indicate that only multisensory looming stimuli resulted in facilitation beyond that induced by the sheer presence of auditory-visual stimuli. Controlling for variation in physical energy replicated the advantage for multisensory looming stimuli. Finally, only looming stimuli exhibited a negative linear relationship between enhancement indices for detection speed and for subjective ratings. Maximal detection speed was attained when motion perception was already robust under unisensory conditions. The preferential integration of multisensory looming stimuli highlights that complex ethologically salient stimuli likely require synergistic cooperation between existing principles of multisensory integration. A new conceptualization of the neurophysiologic mechanisms mediating real-world multisensory perceptions and action is therefore supported.

TORC1 is a calcium- and cAMP-sensitive coincidence detector involved in hippocampal long-term synaptic plasticity.

A key feature of memory processes is to link different input signals by association and to preserve this coupling at the level of synaptic connections. Late-phase long-term potentiation (L-LTP), a form of synaptic plasticity thought to encode long-term memory, requires gene transcription and protein synthesis. In this study, we report that a recently cloned coactivator of cAMP-response element-binding protein (CREB), called transducer of regulated CREB activity 1 (TORC1), contributes to this process by sensing the coincidence of calcium and cAMP signals in neurons and by converting it into a transcriptional response that leads to the synthesis of factors required for enhanced synaptic transmission. We provide evidence that TORC1 is involved in L-LTP maintenance at the Schaffer collateral-CA1 synapses in the hippocampus.

Colloid cysts of the third ventricle: correlation of MR and CT findings with histology and chemical analysis.

Eight patients with colloid cysts of the third ventricle were examined with CT and MR. In six, surgical resection was performed and the material was subjected to histologic evaluation; the concentrations of trace elements were determined by particle-induced X-ray emission. Stereotaxic aspiration was performed in two. The investigation showed that colloid cysts are often iso- or hypodense relative to brain on CT (5/8), but sometimes have a center of increased density. Increased density did not correlate with increased concentration of calcium or other metals but did not correlate with high cholesterol content. Colloid cysts appear more heterogeneous on MR (6/8) than on CT (3/8), despite a homogeneous appearance at histology. High signal on short TR/TE sequences is correlated with a high cholesterol content. A marked shortening of the T2 relaxation time is often noticed in the central part of the cyst. Analysis of trace elements showed that this phenomenon is not related to the presence of metals with paramagnetic effects. Our analysis of the contents of colloid cysts does not support the theory that differing metallic concentrations are responsible for differences in MR signal intensity or CT density. We did find that increased CT density and high MR signal correlated with high cholesterol content.