Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Character Networks and Centrality

A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.

Arbuscular mycorrhizal fungi: genetics of multigenomic, clonal networks and its ecological consequences

Arbuscular mycorrhizal fungi are thought to have remained asexual for 400 million years although recent studies have suggested that considerable genetic and phenotypic variation could potentially exist in populations. A brief discussion of these multigenomic organisms is presented. (C) 2003 The Linnean Society of London.

Neural differentiation and therapeutic potential of adipose tissue derived stem cells.

Neural tissue has historically been regarded as having poor regenerative capacity but recent advances in the growing fields of tissue engineering and regenerative medicine have opened new hopes for the treatment of nerve injuries and neurodegenerative disorders. Adipose tissue has been shown to contain a large quantity of adult stem cells (ASC). These cells can be easily harvested with low associated morbidity and because of their potential to differentiate into multiple cell types, their use has been suggested for a wide variety of therapeutic applications. In this review we examine the evidence indicating that ASC can stimulate nerve regeneration by both undergoing neural differentiation and through the release of a range of growth factors. We also discuss some of the issues that need to be addressed before ASC can be developed as an effective cellular therapy for the treatment of neural tissue disorders.

Association of T-zone reticular networks and conduits with ectopic lymphoid tissues in mice and humans.

Ectopic or tertiary lymphoid tissues (TLTs) are often induced at sites of chronic inflammation. They typically contain various hematopoietic cell types, high endothelial venules, and follicular dendritic cells; and are organized in lymph node-like structures. Although fibroblastic stromal cells may play a role in TLT induction and persistence, they have remained poorly defined. Herein, we report that TLTs arising during inflammation in mice and humans in a variety of tissues (eg, pancreas, kidney, liver, and salivary gland) contain stromal cell networks consisting of podoplanin(+) T-zone fibroblastic reticular cells (TRCs), distinct from follicular dendritic cells. Similar to lymph nodes, TRCs were present throughout T-cell-rich areas and had dendritic cells associated with them. They expressed lymphotoxin (LT) β receptor (LTβR), produced CCL21, and formed a functional conduit system. In rat insulin promoter-CXCL13-transgenic pancreas, the maintenance of TRC networks and conduits was partially dependent on LTβR and on lymphoid tissue inducer cells expressing LTβR ligands. In conclusion, TRCs and conduits are hallmarks of secondary lymphoid organs and of well-developed TLTs, in both mice and humans, and are likely to act as important scaffold and organizer cells of the T-cell-rich zone.

Regional deterministic characterization of fracture networks and its application to GIS-based rock fall risk assessment

The study investigates the possibility to incorporate fracture intensity and block geometry as spatially continuous parameters in GIS-based systems. For this purpose, a deterministic method has been implemented to estimate block size (Bloc3D) and joint frequency (COLTOP). In addition to measuring the block size, the Bloc3D Method provides a 3D representation of the shape of individual blocks. These two methods were applied using field measurements (joint set orientation and spacing) performed over a large field area, in the Swiss Alps. This area is characterized by a complex geology, a number of different rock masses and varying degrees of metamorphism. The spatial variability of the parameters was evaluated with regard to lithology and major faults. A model incorporating these measurements and observations into a GIS system to assess the risk associated with rock falls is proposed. The analysis concludes with a discussion on the feasibility of such an application in regularly and irregularly jointed rock masses, with persistent and impersistent discontinuities.

The α1-adrenergic receptors: diversity of signaling networks and regulation.

The α(1)-adrenergic receptor (AR) subtypes (α(1a), α(1b), and α(1d)) mediate several physiological effects of epinephrine and norepinephrine. Despite several studies in recombinant systems and insight from genetically modified mice, our understanding of the physiological relevance and specificity of the α(1)-AR subtypes is still limited. Constitutive activity and receptor oligomerization have emerged as potential features regulating receptor function. Another recent paradigm is that β arrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effects. The aim of this review is to summarize our current knowledge on some recently identified functional paradigms and signaling networks that might help to elucidate the functional diversity of the α(1)-AR subtypes in various organs.

Bayesian networks and the evaluation of scientific evidence in forensic science

Résumé Ce travail de thèse étudie des moyens de formalisation permettant d'assister l'expert forensique dans la gestion des facteurs influençant l'évaluation des indices scientifiques, tout en respectant des procédures d'inférence établies et acceptables. Selon une vue préconisée par une partie majoritaire de la littérature forensique et juridique - adoptée ici sans réserve comme point de départ - la conceptualisation d'une procédure évaluative est dite 'cohérente' lors qu'elle repose sur une implémentation systématique de la théorie des probabilités. Souvent, par contre, la mise en oeuvre du raisonnement probabiliste ne découle pas de manière automatique et peut se heurter à des problèmes de complexité, dus, par exemple, à des connaissances limitées du domaine en question ou encore au nombre important de facteurs pouvant entrer en ligne de compte. En vue de gérer ce genre de complications, le présent travail propose d'investiguer une formalisation de la théorie des probabilités au moyen d'un environment graphique, connu sous le nom de Réseaux bayesiens (Bayesian networks). L'hypothèse principale que cette recherche envisage d'examiner considère que les Réseaux bayesiens, en concert avec certains concepts accessoires (tels que des analyses qualitatives et de sensitivité), constituent une ressource clé dont dispose l'expert forensique pour approcher des problèmes d'inférence de manière cohérente, tant sur un plan conceptuel que pratique. De cette hypothèse de travail, des problèmes individuels ont été extraits, articulés et abordés dans une série de recherches distinctes, mais interconnectées, et dont les résultats - publiés dans des revues à comité de lecture - sont présentés sous forme d'annexes. D'un point de vue général, ce travail apporte trois catégories de résultats. Un premier groupe de résultats met en évidence, sur la base de nombreux exemples touchant à des domaines forensiques divers, l'adéquation en termes de compatibilité et complémentarité entre des modèles de Réseaux bayesiens et des procédures d'évaluation probabilistes existantes. Sur la base de ces indications, les deux autres catégories de résultats montrent, respectivement, que les Réseaux bayesiens permettent également d'aborder des domaines auparavant largement inexplorés d'un point de vue probabiliste et que la disponibilité de données numériques dites 'dures' n'est pas une condition indispensable pour permettre l'implémentation des approches proposées dans ce travail. Le présent ouvrage discute ces résultats par rapport à la littérature actuelle et conclut en proposant les Réseaux bayesiens comme moyen d'explorer des nouvelles voies de recherche, telles que l'étude de diverses formes de combinaison d'indices ainsi que l'analyse de la prise de décision. Pour ce dernier aspect, l'évaluation des probabilités constitue, dans la façon dont elle est préconisée dans ce travail, une étape préliminaire fondamentale de même qu'un moyen opérationnel.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.