105 resultados para Graphical representation, Textual discourse
em Université de Lausanne, Switzerland
Resumo:
The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.
Resumo:
In 1851 the French Social economist Auguste Ott discussed the problem of gluts and commercial crises, together with the issue of distributive justice between workers in co-operative societies. He did so by means of a 'simple reproduction scheme' sharing some features with modern intersectoral transactions tables, in particular in terms of their graphical representation. This paper presents Ott's theory of crises (which was based on the disappointment of expectations) and the context of his model, and discusses its peculiarities, supplying a new piece for the reconstruction of the prehistory of input-output analysis.
Resumo:
The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.
Resumo:
Abstract: To cluster textual sequence types (discourse types/modes) in French texts, K-means algorithm with high-dimensional embeddings and fuzzy clustering algorithm were applied on clauses whose POS (part-ofspeech) n-gram profiles were previously extracted. Uni-, bi- and trigrams were used on four 19th century French short stories by Maupassant. For high-dimensional embeddings, power transformations on the chi-squared distances between clauses were explored. Preliminary results show that highdimensional embeddings improve the quality of clustering, contrasting the use of bi and trigrams whose performance is disappointing, possibly because of feature space sparsity.
Resumo:
Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.
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Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.
Resumo:
In the context of an autologous cell transplantation study, a unilateral biopsy of cortical tissue was surgically performed from the right dorsolateral prefrontal cortex (dlPFC) in two intact adult macaque monkeys (dlPFC lesioned group), together with the implantation of a chronic chamber providing access to the left motor cortex. Three other monkeys were subjected to the same chronic chamber implantation, but without dlPFC biopsy (control group). All monkeys were initially trained to perform sequential manual dexterity tasks, requiring precision grip. The motor performance and the prehension's sequence (temporal order to grasp pellets from different spatial locations) were analysed for each hand. Following the surgery, transient and moderate deficits of manual dexterity per se occurred in both groups, indicating that they were not due to the dlPFC lesion (most likely related to the recording chamber implantation and/or general anaesthesia/medication). In contrast, changes of motor habit were observed for the sequential order of grasping in the two monkeys with dlPFC lesion only. The changes were more prominent in the monkey subjected to the largest lesion, supporting the notion of a specific effect of the dlPFC lesion on the motor habit of the monkeys. These observations are reminiscent of previous studies using conditional tasks with delay that have proposed a specialization of the dlPFC for visuo-spatial working memory, except that this is in a different context of "free-will", non-conditional manual dexterity task, without a component of working memory.
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Sound localization relies on the analysis of interaural time and intensity differences, as well as attenuation patterns by the outer ear. We investigated the relative contributions of interaural time and intensity difference cues to sound localization by testing 60 healthy subjects: 25 with focal left and 25 with focal right hemispheric brain damage. Group and single-case behavioural analyses, as well as anatomo-clinical correlations, confirmed that deficits were more frequent and much more severe after right than left hemispheric lesions and for the processing of interaural time than intensity difference cues. For spatial processing based on interaural time difference cues, different error types were evident in the individual data. Deficits in discriminating between neighbouring positions occurred in both hemispaces after focal right hemispheric brain damage, but were restricted to the contralesional hemispace after focal left hemispheric brain damage. Alloacusis (perceptual shifts across the midline) occurred only after focal right hemispheric brain damage and was associated with minor or severe deficits in position discrimination. During spatial processing based on interaural intensity cues, deficits were less severe in the right hemispheric brain damage than left hemispheric brain damage group and no alloacusis occurred. These results, matched to anatomical data, suggest the existence of a binaural sound localization system predominantly based on interaural time difference cues and primarily supported by the right hemisphere. More generally, our data suggest that two distinct mechanisms contribute to: (i) the precise computation of spatial coordinates allowing spatial comparison within the contralateral hemispace for the left hemisphere and the whole space for the right hemisphere; and (ii) the building up of global auditory spatial representations in right temporo-parietal cortices.
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Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.
Resumo:
Recent technological advances in remote sensing have enabled investigation of the morphodynamics and hydrodynamics of large rivers. However, measuring topography and flow in these very large rivers is time consuming and thus often constrains the spatial resolution and reach-length scales that can be monitored. Similar constraints exist for computational fluid dynamics (CFD) studies of large rivers, requiring maximization of mesh-or grid-cell dimensions and implying a reduction in the representation of bedform-roughness elements that are of the order of a model grid cell or less, even if they are represented in available topographic data. These ``subgrid'' elements must be parameterized, and this paper applies and considers the impact of roughness-length treatments that include the effect of bed roughness due to ``unmeasured'' topography. CFD predictions were found to be sensitive to the roughness-length specification. Model optimization was based on acoustic Doppler current profiler measurements and estimates of the water surface slope for a variety of roughness lengths. This proved difficult as the metrics used to assess optimal model performance diverged due to the effects of large bedforms that are not well parameterized in roughness-length treatments. However, the general spatial flow patterns are effectively predicted by the model. Changes in roughness length were shown to have a major impact upon flow routing at the channel scale. The results also indicate an absence of secondary flow circulation cells in the reached studied, and suggest simpler two-dimensional models may have great utility in the investigation of flow within large rivers. Citation: Sandbach, S. D. et al. (2012), Application of a roughness-length representation to parameterize energy loss in 3-D numerical simulations of large rivers, Water Resour. Res., 48, W12501, doi: 10.1029/2011WR011284.
Resumo:
The thesis at hand is concerned with the spatio-temporal brain mechanisms of visual food perception as investigated by electrical neuroimaging. Due to the increasing prevalence of obesity and its associated challenges for public health care, there is a need to better understand behavioral and brain processes underlying food perception and food-based decision-making. The first study (Study A) of this thesis was concerned with the role of repeated exposure to visual food cues. In our everyday lives we constantly and repeatedly encounter food and these exposures influence our food choices and preferences. In Study A, we therefore applied electrical neuroimaging analyses of visual evoked potentials to investigate the spatio-temporal brain dynamics linked to the repeated viewing of high- and low-energy food cues (published manuscript: "The role of energetic value in dynamic brain response adaptation during repeated food image viewing" (Lietti et al., 2012)). In this study, we found that repetitions differentially affect behavioral and brain mechanisms when high-energy, as opposed to low-energy foods and non-food control objects, were viewed. The representation of high-energy food remained invariant between initial and repeated exposures indicating that the sight of high-energy dense food induces less behavioral and neural adaptation than the sight of low-energy food and non-food control objects. We discuss this finding in the context of the higher salience (due to greater motivation and higher reward or hedonic valuation) of energy- dense food that likely generates a more mnemonically stable representation. In turn, this more invariant representation of energy-dense food is supposed to (partially) explain why these foods are over-consumed despite of detrimental health consequences. In Study Β we investigated food responsiveness in patients who had undergone Roux-en-Y gastric bypass surgery to overcome excessive obesity. This type of gastric bypass surgery is not only known to alter food appreciation, but also the secretion patterns of adipokines and gut peptides. Study Β aimed at a comprehensive and interdisciplinary investigation of differences along the gut-brain axis in bypass-operated patients as opposed to weight-matched non-operated controls. On the one hand, the spatio-temporal brain dynamics to the visual perception of high- vs. low-energy foods under differing states of motivation towards food intake (i.e. pre- and post-prandial) were assessed and compared between groups. On the other hand, peripheral gut hormone measures were taken in pre- and post-prandial nutrition state and compared between groups. In order to evaluate alterations in the responsiveness along the gut-brain-axis related to gastric bypass surgery, correlations between both measures were compared between both participant groups. The results revealed that Roux-en- Y gastric bypass surgery alters the spatio-temporal brain dynamics to the perception of high- and low-energy food cues, as well as the responsiveness along the gut-brain-axis. The potential role of these response alterations is discussed in relation to previously observed changes in physiological factors and food intake behavior post-Roux-en-Y gastric bypass surgery. By doing so, we highlight potential behavioral, neural and endocrine (i.e. gut hormone) targets for the future development of intervention strategies for deviant eating behavior and obesity. Together, the studies showed that the visual representation of foods in the brain is plastic and that modulations in neural activity are already noted at early stages of visual processing. Different factors of influence such as a repeated exposure, Roux-en-Y gastric bypass surgery, motivation (nutrition state), as well as the energy density of the visually perceived food were identified. En raison de la prévalence croissante de l'obésité et du défi que cela représente en matière de santé publique, une meilleure compréhension des processus comportementaux et cérébraux liés à la nourriture sont nécessaires. En particulier, cette thèse se concentre sur l'investigation des mécanismes cérébraux spatio-temporels liés à la perception visuelle de la nourriture. Nous sommes quotidiennement et répétitivement exposés à des images de nourriture. Ces expositions répétées influencent nos choix, ainsi que nos préférences alimentaires. La première étude (Study A) de cette thèse investigue donc l'impact de ces exposition répétée à des stimuli visuels de nourriture. En particulier, nous avons comparé la dynamique spatio-temporelle de l'activité cérébrale induite par une exposition répétée à des images de nourriture de haute densité et de basse densité énergétique. (Manuscrit publié: "The role of energetic value in dynamic brain response adaptation during repeated food image viewing" (Lietti et al., 2012)). Dans cette étude, nous avons pu constater qu'une exposition répétée à des images représentant de la nourriture de haute densité énergétique, par opposition à de la nourriture de basse densité énergétique, affecte les mécanismes comportementaux et cérébraux de manière différente. En particulier, la représentation neurale des images de nourriture de haute densité énergétique est similaire lors de l'exposition initiale que lors de l'exposition répétée. Ceci indique que la perception d'images de nourriture de haute densité énergétique induit des adaptations comportementales et neurales de moindre ampleur par rapport à la perception d'images de nourriture de basse densité énergétique ou à la perception d'une « catégorie contrôle » d'objets qui ne sont pas de la nourriture. Notre discussion est orientée sur les notions prépondérantes de récompense et de motivation qui sont associées à la nourriture de haute densité énergétique. Nous suggérons que la nourriture de haute densité énergétique génère une représentation mémorielle plus stable et que ce mécanisme pourrait (partiellement) être sous-jacent au fait que la nourriture de haute densité énergétique soit préférentiellement consommée. Dans la deuxième étude (Study Β) menée au cours de cette thèse, nous nous sommes intéressés aux mécanismes de perception de la nourriture chez des patients ayant subi un bypass gastrique Roux- en-Y, afin de réussir à perdre du poids et améliorer leur santé. Ce type de chirurgie est connu pour altérer la perception de la nourriture et le comportement alimentaire, mais également la sécrétion d'adipokines et de peptides gastriques. Dans une approche interdisciplinaire et globale, cette deuxième étude investigue donc les différences entre les patients opérés et des individus « contrôles » de poids similaire au niveau des interactions entre leur activité cérébrale et les mesures de leurs hormones gastriques. D'un côté, nous avons investigué la dynamique spatio-temporelle cérébrale de la perception visuelle de nourriture de haute et de basse densité énergétique dans deux états physiologiques différent (pre- et post-prandial). Et de l'autre, nous avons également investigué les mesures physiologiques des hormones gastriques. Ensuite, afin d'évaluer les altérations liées à l'intervention chirurgicale au niveau des interactions entre la réponse cérébrale et la sécrétion d'hormone, des corrélations entre ces deux mesures ont été comparées entre les deux groupes. Les résultats révèlent que l'intervention chirurgicale du bypass gastrique Roux-en-Y altère la dynamique spatio-temporelle de la perception visuelle de la nourriture de haute et de basse densité énergétique, ainsi que les interactions entre cette dernière et les mesures périphériques des hormones gastriques. Nous discutons le rôle potentiel de ces altérations en relation avec les modulations des facteurs physiologiques et les changements du comportement alimentaire préalablement déjà démontrés. De cette manière, nous identifions des cibles potentielles pour le développement de stratégies d'intervention future, au niveau comportemental, cérébral et endocrinien (hormones gastriques) en ce qui concerne les déviances du comportement alimentaire, dont l'obésité. Nos deux études réunies démontrent que la représentation visuelle de la nourriture dans le cerveau est plastique et que des modulations de l'activité neurale apparaissent déjà à un stade très précoce des mécanismes de perception visuelle. Différents facteurs d'influence comme une exposition repetee, le bypass gastrique Roux-en-Y, la motivation (état nutritionnel), ainsi que la densité énergétique de la nourriture qui est perçue ont pu être identifiés.
Resumo:
This study aims at better understanding how the form of childhood violence experienced and the type of offense subsequently committed affect how sex offenders recall punishments and difficult events. Fifty-four male perpetrators convicted of sexual offenses against children (SOCs) or against adults (SOAs) were interviewed in France, Belgium, and Switzerland using the Lausanne Clinical Interview (Entretien Clinique de Lausanne or LCI). Almost three-quarters of the sex offenders reported having been victimized during childhood. The correspondence analysis identified several factors that differentiated them. Their appraisal of the distressing event, method of coping with and distancing themselves from it, and how they dealt with emotions varied markedly depending on whether they recognized having experienced various forms of violence during childhood and on what type of offense they subsequently committed. Victimization can be identified as much by the events experienced as by their effect on the sex offender's discourse. Identification of these discursive indicators may lead to an improved therapeutic approach for potentially traumatic childhood experiences.