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.

Olfactory cues potentiate learning of distant visuospatial information

The influence of proximal olfactory cues on place learning and memory was tested in two different spatial tasks. Rats were trained to find a hole leading to their home cage or a single food source in an array of petri dishes. The two apparatuses differed both by the type of reinforcement (return to the home cage or food reward) and the local characteristics of the goal (masked holes or salient dishes). In both cases, the goal was in a fixed location relative to distant visual landmarks and could be marked by a local olfactory cue. Thus, the position of the goal was defined by two sets of redundant cues, each of which was sufficient to allow the discrimination of the goal location. These experiments were conducted with two strains of hooded rats (Long-Evans and PVG), which show different speeds of acquisition in place learning tasks. They revealed that the presence of an olfactory cue marking the goal facilitated learning of its location and that the facilitation persisted after the removal of the cue. Thus, the proximal olfactory cue appeared to potentiate learning and memory of the goal location relative to distant environmental cues. This facilitating effect was only detected when the expression of spatial memory was not already optimal, i.e., during the early phase of acquisition. It was not limited to a particular strain.

Accurate memory for object location by individuals with intellectual disability: Absolute spatial tagging instead of configural processing?

Using head-mounted eye tracker material, we assessed spatial recognition abilities (e.g., reaction to object permutation, removal or replacement with a new object) in participants with intellectual disabilities. The "Intellectual Disabilities (ID)" group (n=40) obtained a score totalling a 93.7% success rate, whereas the "Normal Control" group (n=40) scored 55.6% and took longer to fix their attention on the displaced object. The participants with an intellectual disability thus had a more accurate perception of spatial changes than controls. Interestingly, the ID participants were more reactive to object displacement than to removal of the object. In the specific test of novelty detection, however, the scores were similar, the two groups approaching 100% detection. Analysis of the strategies expressed by the ID group revealed that they engaged in more systematic object checking and were more sensitive than the control group to changes in the structure of the environment. Indeed, during the familiarisation phase, the "ID" group explored the collection of objects more slowly, and fixed their gaze for a longer time upon a significantly lower number of fixation points during visual sweeping.

Population density and optimal body size.

The population density of an organism is one of the main aspects of its environment, and shoud therefore strongly influence its adaptive strategy. The r/K theory, based on the logistic model, was developed to formalize this influence. K-selectioon is classically thought to favour large body sizes. This prediction, however, cannot be directly derived from the logistic model: some auxiliary hypotheses are therefor implicit. These are to be made explicit if the theory is to be tested. An alternative approach, based on the Euler-Lotka equation, shows that density itself is irrelevant, but that the relative effect of density on adult and juvenile features is crucial. For instance, increasing population will select for a smaller body size if the density affects mainly juvenile growth and/or survival. In this case, density shoud indeed favour large body sizes. The theory appears nevertheless inconsistent, since a probable consequence of increasing body size will be a decrease in the carrying capacity

Erste Resultate der HOT-Studie in der Schweiz. [Initial results of the HOT-study in Switzerland (hypertension optimal treatment)]

The HOT study (hypertension-optimal treatment) is an international clinical study on primary prevention of cardiovascular events in 19,193 hypertensive patients worldwide. It aims at the recognition of the optimal diastolic blood pressure value (< 90, < 85 or < 80 mmHg?) in order to maximize the possible benefit of an antihypertensive therapy. In addition, the HOT study investigates whether low doses of aspirin (75 mg/day) are able to reduce the occurrence of severe cardiovascular events. In Switzerland a total of 797 patients have been enrolled in the study. Antihypertensive therapy was initiated with felodipine = Plendil (5 mg/day). This vasoelective calcium antagonist could reduce diastolic blood pressure values to < 90 or < 80 mg/Hg, respectively, in one of two or one of three patients within the first three months. In nine or six patients, respectively out of ten a reduction of diastolic blood pressure values to < 90 or < 80 mmHg was reached within one year by combination of felodipine with other antihypertensive drugs (ACE inhibitors, beta blockers and diuretics).

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.

Optimal activation of tumor-reactive T cells by selected antigenic peptide analogues.

Many mechanisms have been proposed to explain why immune responses against human tumor antigens are generally ineffective. For example, tumor cells have been shown to develop active immune evasion mechanisms. Another possibility is that tumor antigens are unable to optimally stimulate tumor-specific T cells. In this study we have used HLA-A2/Melan-A peptide tetramers to directly isolate antigen-specific CD8(+) T cells from tumor-infiltrated lymph nodes. This allowed us to quantify the activation requirements of a representative polyclonal yet monospecific tumor-reactive T cell population. The results obtained from quantitative assays of intracellular Ca(2+) mobilization, TCR down-regulation, cytokine production and induction of effector cell differentiation indicate that the naturally produced Melan-A peptides are weak agonists and are clearly suboptimal for T cell activation. In contrast, optimal T cell activation was obtained by stimulation with recently defined peptide analogues. These findings provide a molecular basis for the low immunogenicity of tumor cells and suggest that patient immunization with full agonist peptide analogues may be essential for stimulation and maintenance of anti-tumor T cell responses in vivo.

The mechanisms of agglomeration: Evidence from the effect of inter-industry relations on the location of new firms

The objective of this paper is to explore the relative importance of each of Marshall's agglomeration mechanisms by examining the location of new manufacturing firms in Spain. In particular, we estimate the count of new firms by industry and location as a function of (pre-determined) local employment levels in industries that: 1) use similar workers (labor market pooling); 2) have a customer- supplier relationship (input sharing); and 3) use similar technologies (knowledge spillovers). We examine the variation in the creation of new firms across cities and across municipalities within large cities to shed light on the geographical scope of each of the three agglomeration mechanisms. We find evidence of all three agglomeration mechanisms, although their incidence differs depending on the geographical scale of the analysis.

Timing, location and crop species influence the magnitude of amelioration of aluminum toxicity by magnesium

The protective effect of cations, especially Ca and Mg, against aluminum (Al) rhizotoxicity has been extensively investigated in the last decades. The mechanisms by which the process occurs are however only beginning to be elucidated. Six experiments were carried out here to characterize the protective effect of Mg application in relation to timing, location and crop specificity: Experiment 1 - Protective effect of Mg compared to Ca; Experiment 2 - Protective effect of Mg on distinct root classes of 15 soybean genotypes; Experiment 3 - Effect of timing of Mg supply on the response of soybean cvs. to Al; Experiment 4 - Investigating whether the Mg protective effect is apoplastic or simplastic using a split-root system; Experiment 5 - Protective effect of Mg supplied in solution or foliar spraying, and Experiment 6 - Protective effect of Mg on Al rhizotoxicity in other crops. It was found that the addition of 50 mmol L-1 Mg to solutions containing toxic Al increased Al tolerance in 15 soybean cultivars. This caused soybean cultivars known as Al-sensitive to behave as if they were tolerant. The protective action of Mg seems to require constant Mg supply in the external medium. Supplying Mg up to 6 h after root exposition to Al was sufficient to maintain normal soybean root growth, but root growth was not recovered by Mg addition 12 h after Al treatments. Mg application to half of the root system not exposed to Al was not sufficient to prevent Al toxicity on the other half exposed to Al without Mg in rooting medium, indicating the existence of an external protection mechanism of Mg. Foliar spraying with Mg also failed to decrease Al toxicity, indicating a possible apoplastic role of Mg. The protective effect of Mg appeared to be soybean-specific since Mg supply did not substantially improve root elongation in sorghum, wheat, corn, cotton, rice, or snap bean when grown in the presence of toxic Al concentrations.

Tax differentials and agglomeration economies in intraregional firm location

This paper analyses empirically how differences in local taxes affect the intraregional location of new manufacturing plants. These effects are examined within the random profit maximization framework while accounting for the presence of different types of agglomeration economies (localization/ urbanization/ Jacobs¿ economies) at the municipal level. We look at the location decision of more than 10,000 establishments locating between 1996 and 2003 across more than 400 municipalities in Catalonia, a Spanish region. It is necessary to restrict the choice set to the local labor market and, above all, to control for agglomeration economies so as to identify the effects of taxes on the location of new establishments.

Tax differentials and agglomeration economies in intraregional firm location

This paper analyses empirically how differences in local taxes affect the intraregional location of new manufacturing plants. These effects are examined within the random profit maximization framework while accounting for the presence of different types of agglomeration economies (localization/ urbanization/ Jacobs¿ economies) at the municipal level. We look at the location decision of more than 10,000 establishments locating between 1996 and 2003 across more than 400 municipalities in Catalonia, a Spanish region. It is necessary to restrict the choice set to the local labor market and, above all, to control for agglomeration economies so as to identify the effects of taxes on the location of new establishments.

The mechanisms of agglomeration: Evidence from the effect of inter-industry relations on the location of new firms

The objective of this paper is to explore the relative importance of each of Marshall's agglomeration mechanisms by examining the location of new manufacturing firms in Spain. In particular, we estimate the count of new firms by industry and location as a function of (pre-determined) local employment levels in industries that: 1) use similar workers (labor market pooling); 2) have a customer- supplier relationship (input sharing); and 3) use similar technologies (knowledge spillovers). We examine the variation in the creation of new firms across cities and across municipalities within large cities to shed light on the geographical scope of each of the three agglomeration mechanisms. We find evidence of all three agglomeration mechanisms, although their incidence differs depending on the geographical scale of the analysis.

The determinants of industrial location in Spain, 1856-1929

Durant el segle XIX, l'economia espanyola va transitar per les primeres etapes de la industrialització. Aquest procés es va donar en paral·lel a la integració del mercat domèstic de béns i factors, en un moment en què les reformes liberals i la construcció de la xarxa ferroviària, entre d'altres, van generar una important caiguda en els costos detransport. Al mateix temps que es donava aquesta progressiva integració del mercat domèstic espanyol, es van produir canvis significatius en la pauta de localització industrial. D'una banda, hi hagué un augment considerable de la concentració espacial de la indústria des de mitjans de segle XIX i fins a la Guerra Civil, i d¿altra, un increment de l'especialització regional. Ara bé, quines van ser les forces que van generar aquests canvis? Des d¿un punt de vista teòric, el model de Heckscher-Ohlin suggereix que la distribució a l'espai de l¿activitat econòmica ve determinada per l'avantatge comparativa dels territoris en funció de la dotació relativa de factors. Al seu torn, els models de Nova Geografia Econòmica (NEG) mostren l'existència d'una relació en forma de campana entre el procés d'integració econòmica i el grau de concentració geogràfica de l'activitat industrial. Aquest article examina empíricament els determinants de la localització industrial a Espanya entre 1856 i 1929, mitjançant l'estimació d¿un model que combina els elements de tipus Heckscher-Ohlin i els factors apuntats des de la NEG, amb l'objectiu de contrastar la força relativa dels arguments vinculats a aquestes dues interpretacions a l'hora de modular la localització de la indústria a Espanya. L'anàlisi dels resultats obtinguts mostra que tant la dotació de factors com els mecanismes de tipus NEG van ser elements determinants que expliquen la distribució geogràfica de la indústria des del segle XIX, tot i que la seva força relativa va anar variant amb el temps.