Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Changes in leg-spring behavior during a 5000 m self-paced run in differently trained athletes

Summary Aims.-To explore whether fatigue-induced changes in spring-mass behavior during a 5000m self-paced run varied according to the runner's training status. Methods and results.-Six highly- and six well-trained triathletes completed a 5000m time trial. Running velocity and vertical stiffness decreased significantly (P < 0.05) with fatigue, whereas leg stiffness remained constant. None of these parameters displayed a significant interaction between fatigue and training status, despite vertical stiffness being higher (P < 0.05) in highly-trained triathletes. Conclusions.-During a 5000m self-paced run, impairments in leg-spring behavior that occur with fatigue are not affected by athletes' training status. © 2009 Elsevier Masson SAS. All rights reserved. Objectifs.-Étudier, chez des athlètes de niveaux différents, les modifications de raideur mécanique liées à l'apparition de la fatigue lors d'une course de 5000 m. Synthèse des faits.-Six triathlètes très entraînés et six autres bien entraînés ont réalisé une course de 5000 m. La vitesse de course et la raideur verticale diminuaient significativement (p < 0,05) avec la fatigue, alors que la raideur de la jambe demeurait inchangée. Aucune interaction entre la fatigue et le niveau d'entraînement n'a été détectée, malgré des niveaux de raideur verticale plus élevés (p < 0,05) chez les sujets les mieux entraînés.

Time-scale and other invariants of integrative mechanical behavior in living cells.

In dealing with systems as complex as the cytoskeleton, we need organizing principles or, short of that, an empirical framework into which these systems fit. We report here unexpected invariants of cytoskeletal behavior that comprise such an empirical framework. We measured elastic and frictional moduli of a variety of cell types over a wide range of time scales and using a variety of biological interventions. In all instances elastic stresses dominated at frequencies below 300 Hz, increased only weakly with frequency, and followed a power law; no characteristic time scale was evident. Frictional stresses paralleled the elastic behavior at frequencies below 10 Hz but approached a Newtonian viscous behavior at higher frequencies. Surprisingly, all data could be collapsed onto master curves, the existence of which implies that elastic and frictional stresses share a common underlying mechanism. Taken together, these findings define an unanticipated integrative framework for studying protein interactions within the complex microenvironment of the cell body, and appear to set limits on what can be predicted about integrated mechanical behavior of the matrix based solely on cytoskeletal constituents considered in isolation. Moreover, these observations are consistent with the hypothesis that the cytoskeleton of the living cell behaves as a soft glassy material, wherein cytoskeletal proteins modulate cell mechanical properties mainly by changing an effective temperature of the cytoskeletal matrix. If so, then the effective temperature becomes an easily quantified determinant of the ability of the cytoskeleton to deform, flow, and reorganize.

Ispol'zovanie metodov teorii vosstanovleniia v modeliakh optimal'nogo dobyvaniia pishchi [Restoration theory in models of optimal feeding behavior]

The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.

Mirror me : the effect of the voting advice application smartvote on voting preferences and behavior of Swiss voters

Voting Advice Applications (VAAs) have become a central component of election campaigns worldwide. Through matching political preferences of voters to parties and candidates, the web application grants voters a look into their political mirror and reveals the most suitable political choices to them in terms of policy congruence. Both the dense and concise information on the electoral offer and the comparative nature of the application make VAAs an unprecedented information source for electoral decision making. In times where electoral choices are found to be highly individualized and driven by political issue positions, an ever increasing number of voters turn to VAAs before casting their ballots. With VAAs in high demand, the question of their effects on voters has become a pressing research topic. In various countries, survey research has been used to proclaim an impact of VAAs on electoral behavior, yet practically all studies fail to provide the scientific evidence that would allow for making such claims. In this thesis, I set out to systematically establish the causal link between VAA use and electoral behavior, using various data sources and appropriate statistical techniques in doing so. The focus lies on the Swiss VAA smartvote, introduced in the forefront of the 2003 Swiss federal elections and meanwhile an integral part of the national election campaign, smartvote has produced over a million voting recommendations in the last Swiss federal elections to an active electorate of two million, potentially guiding a vast amount of voters in their choices on the ballot. In order to determine the effect of the VAA on electoral behavior, I analyze both voting preferences and choice among Swiss voters during two consecutive election periods. First, I introduce statistical techniques to adequately examine VAA effects in observational studies and use them to demonstrate that voters who used smartvote prior to the 2007 Swiss federal elections were significantly more likely to swing vote in the elections than non- users. Second, I analyze preference voting during the same election and show that the smartvote voting recommendation inclines politically knowledgeable voters to modify their ballots and cast candidate specific preference votes. Third, to further tackle the indication that smartvote use affects the preference structure of voters, I employ an experimental research design to demonstrate that voters who use the application tend to strengthen their vote propensities for their most preferred party and adapt their overall party preferences in a way that they consider more than one party as eligible vote options after engaging with the application. Finally, vote choice is examined for the 2011 Swiss federal election, showing once more that the VAA initiated a change of party choice among voters. In sum, this thesis presents empirical evidence for the transformative effect of the Swiss VAA smartvote on the electoral behavior.

Startegy selection during exploratory behavior: sex differences, uncertainty and risk managment

This study deals with the psychological processes underlying the selection of appropriate strategy during exploratory behavior. A new device was used to assess sexual dimorphisms in spatial abilities that do not depend on spatial rotation, map reading or directional vector extraction capacities. Moreover, it makes it possible to investigate exploratory behavior as a specific response to novelty that trades off risk and reward. Risk management under uncertainty was assessed through both spontaneous searching strategies and signal detection capacities. The results of exploratory behavior, detection capacities, and decision-making strategies seem to indicate that women's exploratory behavior is based on risk-reducing behavior while men behavior does not appear to be influenced by this variable. This difference was interpreted as a difference in information processing modifying beliefs concerning the likelihood of uncertain events, and therefore influencing risk evaluation.

Numerical analysis of the impact of charcoal production on soil hydrological behavior, runoff response and erosion susceptibility

The impact of charcoal production on soil hydraulic properties, runoff response and erosion susceptibility were studied in both field and simulation experiments. Core and composite samples, from 12 randomly selected sites within the catchment of Kotokosu were taken from the 0-10 cm layer of a charcoal site soil (CSS) and adjacent field soils (AFS). These samples were used to determine saturated hydraulic conductivity (Ksat), bulk density, total porosity, soil texture and color. Infiltration, surface albedo and soil surface temperature were also measured in both CSS and AFS. Measured properties were used as entries in a rainfall runoff simulation experiment on a smooth (5 % slope) plot of 25 x 25 m grids with 10 cm resolutions. Typical rainfall intensities of the study watershed (high, moderate and low) were applied to five different combinations of Ks distributions that could be expected in this landscape. The results showed significantly (p < 0.01) higher flow characteristics of the soil under charcoal kilns (increase of 88 %). Infiltration was enhanced and runoff volume reduced significantly. The results showed runoff reduction of about 37 and 18 %, and runoff coefficient ranging from 0.47-0.75 and 0.04-0.39 or simulation based on high (200 mm h-1) and moderate (100 mm h-1) rainfall events over the CSS and AFS areas, respectively. Other potential impacts of charcoal production on watershed hydrology were described. The results presented, together with watershed measurements, when available, are expected to enhance understanding of the hydrological responses of ecosystems to indiscriminate charcoal production and related activities in this region.

Bilateral olfactory sensory input enhances chemotaxis behavior.

Neural comparisons of bilateral sensory inputs are essential for visual depth perception and accurate localization of sounds in space. All animals, from single-cell prokaryotes to humans, orient themselves in response to environmental chemical stimuli, but the contribution of spatial integration of neural activity in olfaction remains unclear. We investigated this problem in Drosophila melanogaster larvae. Using high-resolution behavioral analysis, we studied the chemotaxis behavior of larvae with a single functional olfactory neuron on either the left or right side of the head, allowing us to examine unilateral or bilateral olfactory input. We developed new spectroscopic methods to create stable odorant gradients in which odor concentrations were experimentally measured. In these controlled environments, we observed that a single functional neuron provided sufficient information to permit larval chemotaxis. We found additional evidence that the overall accuracy of navigation is enhanced by the increase in the signal-to-noise ratio conferred by bilateral sensory input.