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.

Regional structure of wages and external economies in Spain

Regional data on wages for the Spanish economy show that workers who live in developed regions earn more than workers in other regions.Literature on external economies provides a possible explanation of why firms do not move from these regions to others where wages are lower. Previous studies for the Spanish case use aggregated sectoral data to explain in terms of external economies why average wages are different across regions. The originalcontribution of this paper consists of using individual data to detect the existenceand nature of external economies as an explanatory cause of territorial wagedifferences. With this aim, we have used individual data from the EPF 1990-91(INE). This information permits us to control the influence of individual and jobcharacteristics on wages to, first, detect the existence of external economies and,second, to test alternative explanations of their presence. The empirical evidenceobtained confirms the relevance of territorial external economies and their influence on wages, as a result of improvements in the productive efficiency of the firm. In concrete terms, the more relevant external economies are associatedwith the regional human capital stock and geographical productive specialisation

Consequences of modified lipid and glucose metabolism on peripheral nervous system structure and function

284 million people worldwide suffered from type 2 diabetes mellitus (T2DM) in 2010, which will, in approximately half of them, lead to the development of diabetic peripheral neuropathy (DPN). Although DPN is the most common complication of diabetes mellitus and the leading cause of non-traumatic amputations its pathophysiology is still poorly understood. To get more insight into the molecular mechanism underlying DPN in T2DM, I used a rodent model of T2DM, the db/db mice.¦ln vivo electrophysiological recordings of diabetic animals indicated that in addition to reduced nerve conduction velocity db/db mice also present increased nerve excitability. Further ex vivo evaluation of the electrophysiological properties of db/db nerves clearly established a presence of the peripheral nerve hyperexcitability (PNH) phenotype in diabetic animals. Using pharmacological inhibitors we demonstrated that PNH is mostly mediated by the decreased activity of Kv1 channels. ln agreement with these data 1 observed that the diabetic condition led to a reduced presence of the Kv1.2 subunits in juxtaparanodal regions of db/db peripheral nerves whereas its mANA and protein expression levels were not affected. Lmportantly, I confirmed a loss of juxtaparanodal Kv1.2 subunits in nerve biopsies from type 2 diabetic patients. Together these observations indicate that the type 2 diabetic condition leads to potassium-channel mediated changes of nerve excitability thus identifying them as potential drug targets to treat sorne of the DPN related symptoms.¦Schwann cells ensheath and isolate peripheral axons by the production of myelin, which consists of lipids and proteins in a ratio of 2:1. Peripheral myelin protein 2 (= P2, Pmp2 or FABP8) was originally described as one of the most abundant myelin proteins in the peripheral nervous system. P2, which is a member of the fatty acid binding protein (FABP) family, is a 14.8 kDa cytosolic protein expressed on the cytoplasmic side of compact myelin membranes. As indicated by their name, the principal role of FABPs is thought to be the binding and transport of fatty acids.¦To study its role in myelinating glial cells I have recently generated a complete P2 knockout mouse model (P2-/-). I confirmed the loss of P2 in the sciatic nerve of P2-/- mice at the mRNA and protein level. Electrophysiological analysis of the adult (P56) mutant mice revealed a mild but significant reduction in the motor nerve conduction velocity. lnterestingly, this functional change was not accompanied by any detectable alterations in general myelin structure. However, I have observed significant alterations in the mRNA expression level of other FABPs, predominantly FABP9, in the PNS of P2-/- mice as compared to age-matched P2+/+ mice indicating a role of P2 in the glial myelin lipid metabolism.¦Le diabète de type 2 touche 284 million de personnes dans le monde en 2010 et son évolution conduit dans la moitié des cas à une neuropathie périphérique diabétique. Bien que la neuropathie périphérique soit la complication la plus courante du diabète pouvant conduire jusqu'à l'amputation, sa physiopathologie est aujourd'hui encore mal comprise. Dans le but d'améliorer les connaissances moléculaires expliquant les mécanismes de la neuropathie liée au diabète de type 2, j'ai utilisé un modèle murin du diabète de type 2, les souris db/db.¦ln vivo, les enregistrements éléctrophysiologiques des animaux diabétiques montrent qu'en plus d'une diminution de la vitesse de conduction nerveuse, les souris db/db présentent également une augmentation de l'excitabilité nerveuse. Des mesures menées Ex­ vivo ont montré l'existence d'un phénotype d'hyperexcitabilité sur les nerfs périphériques isolés d'animaux diabétiques. Grâce à l'utilisation d'inhibiteurs pharmacologiques, nous avons pu démontrer que l'hyperexcitabilité démontrée était due à une réduction d'activité des canaux Kv1. En accord avec ces données, j'ai observé qu'une situation de diabète conduisait à une diminution des canaux Kv1.2 aux régions juxta-paranodales des nerfs périphériques db/db, alors que l'expression du transcrit et de la protéine restait stable. J'ai également confirmé l'absence de canaux Kv1.2 aux juxta-paranoeuds de biopsies de nerfs de patients diabétiques. L'ensemble de ces observations montrent que les nerfs périphériques chez les patients atteints de diabète de type 2 est due à une diminution des canaux potassiques rapides juxtaparanodaux les identifiant ainsi comme des cibles thérapeutiques potentielles.¦Les cellules de Schwann enveloppent et isolent les axones périphériques d'une membrane spécialisée, la myéline, composée de deux fois plus de lipides que de protéines. La protéine P2 (Pmp2 "peripheral myelin protein 2" ou FABP8 "fatty acid binding protein") est l'une des protéines les plus abondantes au système nerveux périphérique. P2 appartient à la famille de protéines FABP liant et transportant les acides gras et est une protéine cytosolique de 14,8 kDa exprimée du côté cytoplasmique de la myéline compacte.¦Afin d'étudier le rôle de P2 dans les cellules de Schwann myélinisantes, j'ai généré une souris knockout (P2-/-). Après avoir validé l'absence de transcrit et de protéine P2 dans les nerfs sciatiques P2-/-, des mesures électrophysiologiques ont montré une réduction modérée mais significative de la vitesse de conduction du nerf moteur périphérique. Il est important de noter que ces changements fonctionnels n'ont pas pu être associés à quelconque changement dans la structure de la myéline. Cependant, j'ai observé dans les nerfs périphériques P2-/-, une altération significative du niveau d'expression d'ARNm d'autres FABPs et en particulier FABP9. Ce dernier résultat démontre l'importance du rôle de la protéine P2 dans le métabolisme lipidique de la myéline.

Effects of prior hydrogenation on the structure and properties of thermally nanocrystallized silicon layers

Nanocrystalline silicon layers have been obtained by thermal annealing of films sputtered in various hydrogen partial pressures. The as-deposited and crystallized films were investigated by infrared, Raman, x-ray diffraction, electron microscopy, and optical absorption techniques. The obtained data show evidence of a close correlation between the microstructure and properties of the processed material, and the hydrogen content in the as-grown deposit. The minimum stress deduced from Raman was found to correspond to the widest band gap and to a maximum hydrogen content in the basic unannealed sample. Such a structure relaxation seems to originate from the so-called "chemical annealing" thought to be due to Si-H2 species, as identified by infrared spectroscopy. The variation of the band gap has been interpreted in terms of the changes in the band tails associated with the disorder which would be induced by stress. Finally, the layers originally deposited with the highest hydrogen pressure show a lowest stress-which does not correlate with the hydrogen content and the optical band gap¿and some texturing. These features are likely related to the presence in these layers of a significant crystalline fraction already before annealing.

Diagnostic techniques applied in geostatistics for agricultural data analysis

The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Regional structure of wages and external economies in Spain

Regional data on wages for the Spanish economy show that workers who live in developed regions earn more than workers in other regions.Literature on external economies provides a possible explanation of why firms do not move from these regions to others where wages are lower. Previous studies for the Spanish case use aggregated sectoral data to explain in terms of external economies why average wages are different across regions. The originalcontribution of this paper consists of using individual data to detect the existenceand nature of external economies as an explanatory cause of territorial wagedifferences. With this aim, we have used individual data from the EPF 1990-91(INE). This information permits us to control the influence of individual and jobcharacteristics on wages to, first, detect the existence of external economies and,second, to test alternative explanations of their presence. The empirical evidenceobtained confirms the relevance of territorial external economies and their influence on wages, as a result of improvements in the productive efficiency of the firm. In concrete terms, the more relevant external economies are associatedwith the regional human capital stock and geographical productive specialisation

Hypernuclear structure with the new Nijmegen potentials

Information on level density for nuclei with mass numbers A?20250 is deduced from discrete low-lying levels and neutron resonance data. The odd-mass nuclei exhibit in general 47 times the level density found for their neighboring even-even nuclei at the same excitation energy. This excess corresponds to an entropy of ?1.7kB for the odd particle. The value is approximately constant for all midshell nuclei and for all ground state spins. For these nuclei it is argued that the entropy scales with the number of particles not coupled in Cooper pairs. A simple model based on the canonical ensemble theory accounts qualitatively for the observed properties.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Empirical determination of the very high energy heavy quark cross section from nonaccelerator data

To cosmic rays incident near the horizon the Earth's atmosphere represents a beam dump with a slant depth reaching 36 000 g cm-2 at 90. The prompt decay of a heavy quark produced by very high energy cosmic ray showers will leave an unmistakable signature in this dump. We translate the failure of experiments to detect such a signal into an upper limit on the heavy quark hadroproduction cross section in the energy region beyond existing accelerators. Our results disfavor any rapid growth of the cross section or the gluon structure function beyond conservative estimates based on perturbative QCD.

Exporting Contours to DICOM-RT Structure Set

This paper presents an ITK implementation for exportingthe contours of the automated segmentation results toDICOM-RT Structure Set format. The âeurooeradiotherapystructure setâeuro (RTSTRUCT) object of the DICOM standard isused for the transfer of patient structures and relateddata, between the devices found within and outside theradiotherapy department. It mainly contains theinformation of regions of interest (ROIs) and points ofinterest (E.g. dose reference points). In many cases,rather than manually drawing these ROIs on the CT images,one can indeed benefit from the automated segmentationalgorithms already implemented in ITK. But at present, itis not possible to export the ROIs obtained from ITK toRTSTRUCT format. In order to bridge this gap, we havedeveloped a framework for exporting contour data toRTSTRUCT. We provide here the complete implementation ofRTSTRUCT exporter and present the details of the pipelineused. Results on a 3-D CT image of the Head and Neck(H&N) region are presented.

Genetic and karyotypic structure in the shrews of the Sorex araneus group: are they independent?

The species of the common shrew (Sorex araneus) group are morphologically very similar but exhibit high levels of karyotypic variation. Here we used genetic variation at 10 microsatellite markers in a data set of 212 individuals mostly sampled in the western Alps and composed of five karyotypic taxa (Sorex coronatus, Sorex antinorii and the S. araneus chromosome races Cordon, Bretolet and Vaud) to investigate the concordance between genetic and karyotypic structure. Bayesian analysis confirmed the taxonomic status of the three sampled species since individuals consistently grouped according to their taxonomical status. However, introgression can still be detected between S. antinorii and the race Cordon of S. araneus. This observation is consistent with the expected low karyotypic complexity of hybrids between these two taxa. Geographically based cryptic substructure was discovered within S. antinorii, a pattern consistent with the different postglaciation recolonization routes of this species. Additionally, we detected two genetic groups within S. araneus notwithstanding the presence of three chromosome races. This pattern can be explained by the probable hybrid status of the Bretolet race but also suggests a relatively low impact of chromosomal differences on genetic structure compared to historical factors. Finally, we propose that the current data set (available at http://www.unil.ch/dee/page7010_en.html#1) could be used as a reference by those wanting to identify Sorex individuals sampled in the western Alps.

Coarsening of solid-liquid mixtures in a random acceleration field

The effects of flow induced by a random acceleration field (g-jitter) are considered in two related situations that are of interest for microgravity fluid experiments: the random motion of isolated buoyant particles, and diffusion driven coarsening of a solid-liquid mixture. We start by analyzing in detail actual accelerometer data gathered during a recent microgravity mission, and obtain the values of the parameters defining a previously introduced stochastic model of this acceleration field. The diffusive motion of a single solid particle suspended in an incompressible fluid that is subjected to such random accelerations is considered, and mean squared velocities and effective diffusion coefficients are explicitly given. We next study the flow induced by an ensemble of such particles, and show the existence of a hydrodynamically induced attraction between pairs of particles at distances large compared with their radii, and repulsion at short distances. Finally, a mean field analysis is used to estimate the effect of g-jitter on diffusion controlled coarsening of a solid-liquid mixture. Corrections to classical coarsening rates due to the induced fluid motion are calculated, and estimates are given for coarsening of Sn-rich particles in a Sn-Pb eutectic fluid, an experiment to be conducted in microgravity in the near future.

Electronic structure and properties of Cu2O

The structural and electronic properties of Cu2O have been investigated using the periodic Hartree-Fock method and a posteriori density-functional corrections. The lattice parameter, bulk modulus, and elastic constants have been calculated. The electronic structure of and bonding in Cu2O are analyzed and compared with x-ray photoelectron spectroscopy spectra, showing a good agreement for the valence-band states. To check the quality of the calculated electron density, static structure factors and Compton profiles have been calculated, showing a good agreement with the available experimental data. The effective electron and hole masses have been evaluated for Cu2O at the center of the Brillouin zone. The calculated interaction energy between the two interpenetrated frameworks in the cuprite structure is estimated to be around -6.0 kcal/mol per Cu2O formula. The bonding between the two independent frameworks has been analyzed using a bimolecular model and the results indicate an important role of d10-d10 type interactions between copper atoms.

Complex regional pain syndrome type I affects brain structure in prefrontal and motor cortex.

The complex regional pain syndrome (CRPS) is a rare but debilitating pain disorder that mostly occurs after injuries to the upper limb. A number of studies indicated altered brain function in CRPS, whereas possible influences on brain structure remain poorly investigated. We acquired structural magnetic resonance imaging data from CRPS type I patients and applied voxel-by-voxel statistics to compare white and gray matter brain segments of CRPS patients with matched controls. Patients and controls were statistically compared in two different ways: First, we applied a 2-sample ttest to compare whole brain white and gray matter structure between patients and controls. Second, we aimed to assess structural alterations specifically of the primary somatosensory (S1) and motor cortex (M1) contralateral to the CRPS affected side. To this end, MRI scans of patients with left-sided CRPS (and matched controls) were horizontally flipped before preprocessing and region-of-interest-based group comparison. The unpaired ttest of the "non-flipped" data revealed that CRPS patients presented increased gray matter density in the dorsomedial prefrontal cortex. The same test applied to the "flipped" data showed further increases in gray matter density, not in the S1, but in the M1 contralateral to the CRPS-affected limb which were inversely related to decreased white matter density of the internal capsule within the ipsilateral brain hemisphere. The gray-white matter interaction between motor cortex and internal capsule suggests compensatory mechanisms within the central motor system possibly due to motor dysfunction. Altered gray matter structure in dorsomedial prefrontal cortex may occur in response to emotional processes such as pain-related suffering or elevated analgesic top-down control.