908 resultados para INVARIANT-MANIFOLDS
Resumo:
En aquest treball realitzem un estudi sobre la detecció y la descripció de punts característics, una tecnologia que permet extreure informació continguda en les imatges. Primerament presentem l'estat de l'art juntament amb una avaluació dels mètodes més rellevants. A continuació proposem els nous mètodes que hem creat de detecció i descripció, juntament amb l'algorisme òptim anomenat DART, el qual supera l'estat de l'art. Finalment mostrem algunes aplicacions on s'utilitzen els punts DART. Basant-se en l'aproximació de l'espai d'escales Gaussià, el detector proposat pot extreure punts de distint tamany invariants davant canvis en el punt de vista, la rotació i la iluminació. La reutilització de l'espai d'escales durant el procés de descripció, així com l'ús d'estructures simplificades i optimitzades, permeten realitzar tot el procediment en un temps computacional menor a l'obtingut fins al moment. Així s'aconsegueixen punts invariants i distingibles de forma ràpida, el qual permet la seva utilització en aplicacions com el seguiment d'objectes, la reconstrucció d'escenaris 3D i en motors de cerca visual.
Resumo:
Donada una aplicació racional en una varietat complexa, Bellon i Viallet van definit l’entropia algebraica d’aquesta aplicació i van provar que aquest valor és un invariant biracional. Un invariant biracional equivalent és el grau asimptòtic, grau dinàmic o complexitat, definit per Boukraa i Maillard. Aquesta noció és propera a la complexitat definida per Arnold. Conjecturalment, el grau asimptòtic satisfà una recurrència lineal amb coeficients enters. Aquesta conjectura ha estat provada en el cas polinòmic en el pla afí complex per Favre i Jonsson i resta oberta en per al cas projectiu global i per al cas local. L’estudi de l’arbre valoratiu de Favre i Jonsson ha resultat clau per resoldre la conjectura en el cas polinòmic en el pla afí complex. El beneficiari ha estudiat l’arbre valoratiu global de Favre i Jonsson i ha reinterpretat algunes nocions i resultats des d’un punt de vista més geomètric. Així mateix, ha estudiat la demostració de la conjectura de Bellon – Viallet en el cas polinòmic en el pla afí complex com a primer pas per trobar una demostració en el cas local i projectiu global en estudis futurs. El projecte inclou un estudi detallat de l'arbre valoratiu global des d'un punt de vista geomètric i els primers passos de la demostració de la conjectura de Bellon - Viallet en el cas polinòmic en el pla afí complex que van efectuar Favre i Jonsson.
Resumo:
Donada una aplicació racional en una varietat complexa, Bellon i Viallet van definit l’entropia algebraica d’aquesta aplicació i van provar que aquest valor és un invariant biracional. Un invariant biracional equivalent és el grau asimptòtic, grau dinàmic o complexitat, definit per Boukraa i Maillard. Aquesta noció és propera a la complexitat definida per Arnold. Conjecturalment, el grau asimptòtic satisfà una recurrència lineal amb coeficients enters. Aquesta conjectura ha estat provada en el cas polinòmic en el pla afí complex per Favre i Jonsson i resta oberta en per al cas projectiu global i per al cas local. L’estudi de l’arbre valoratiu de Favre i Jonsson ha resultat clau per resoldre la conjectura en el cas polinòmic en el pla afí complex. El beneficiari ha estudiat l’arbre valoratiu global de Favre i Jonsson i ha reinterpretat algunes nocions i resultats des d’un punt de vista més geomètric. Així mateix, ha estudiat la demostració de la conjectura de Bellon – Viallet en el cas polinòmic en el pla afí complex com a primer pas per trobar una demostració en el cas local i projectiu global en estudis futurs. El projecte inclou un estudi detallat de l'arbre valoratiu global des d'un punt de vista geomètric i els primers passos de la demostració de la conjectura de Bellon - Viallet en el cas polinòmic en el pla afí complex que van efectuar Favre i Jonsson.
Biased V beta usage in immature thymocytes is independent of DJ beta proximity and pT alpha pairing.
Resumo:
During thymus development, the TCR beta locus rearranges before the TCR alpha locus. Pairing of productively rearranged TCR beta-chains with an invariant pT alpha chain leads to the formation of a pre-TCR and subsequent expansion of immature pre-T cells. Essentially nothing is known about the TCR V beta repertoire in pre-T cells before or after the expression of a pre-TCR. Using intracellular staining, we show here that the TCR V beta repertoire is significantly biased at the earliest developmental stage in which VDJ beta rearrangement has occurred. Moreover (and in contrast to the V(H) repertoire in immature B cells), V beta repertoire biases in immature T cells do not reflect proximity of V beta gene segments to the DJ beta cluster, nor do they depend upon preferential V beta pairing with the pT alpha chain. We conclude that V gene repertoires in developing T and B cells are controlled by partially distinct mechanisms.
Resumo:
En aquest projecte es proposa un algorisme de detecció de pell que introdueix el veïnatge a l’hora de classificar píxels. Partim d’un espai de color invariant après a partir de múltiples vistes i introduïm la influència del veïnatge mitjançant camps aleatoris de Markov. A partir dels experiments realitzats podem concloure que la inclusió del veïnatge en el procés de classificació de píxels millora significativament els resultats de detecció.
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In this paper we consider a representative a priori unstable Hamiltonian system with 2+1/2 degrees of freedom, to which we apply the geometric mechanism for diffusion introduced in the paper Delshams et al., Mem.Amer.Math. Soc. 2006, and generalized in Delshams and Huguet, Nonlinearity 2009, and provide explicit, concrete and easily verifiable conditions for the existence of diffusing orbits. The simplification of the hypotheses allows us to perform explicitly the computations along the proof, which contribute to present in an easily understandable way the geometric mechanism of diffusion. In particular, we fully describe the construction of the scattering map and the combination of two types of dynamics on a normally hyperbolic invariant manifold.
Resumo:
We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom) applying moment- based estimator at time-varying parameter model with endogenous regressors. Using this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually pointing to the importance of applying time-varying estimation framework. Second, the interest rate smoothing parameter is much lower that what previous time-invariant estimates of policy rules typically report. External factors matter for all countries, albeit the importance of exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates on inflation is particularly strong during the periods, when central bankers want to break the record of high inflation such as in the U.K. or in Australia at the beginning of 1980s. Contrary to common wisdom, the response becomes less aggressive after the adoption of inflation targeting suggesting the positive effect of this regime on anchoring inflation expectations. This result is supported by our finding that inflation persistence as well as policy neutral rate typically decreased after the adoption of inflation targeting.
Resumo:
This paper computes and compares alternative quality-adjusted price indexes for new cars in Spain in the period 1990-2000. The proposed hedonic approach simultaneously controls for time-invariant unobserved product e¤ects and time-variant unobserved quality changes, that are assumed to be captured by model age effects. The results show that the non-adjusted price index largely overstates the increase in the cost of living induced by changes in car prices and that previous evidence for this market have not measured the real extent of that bias, probably due to the omission of controls for unobservables. It is also shown that omitting age effects can also lead to misleading conclusions. The estimated price indexes give also some insights on what could have been the determinants of price evolution in the Spanish car market.
Resumo:
This paper computes and compares alternative quality-adjusted price indexes for new cars in Spain in the period 1990-2000. The proposed hedonic approach simultaneously controls for time-invariant unobserved product effects and time-variant unobserved quality changes, that are assumed to be captured by model age effects. The results show that the non-adjusted price index largely overstates the increase in the cost of living induced by changes in car prices and that previous evidence for this market have not measured the real extent of that bias, probably due to the omission of controls for unobservables. It is also shown that omitting age effects can also lead to misleading conclusions. The estimated price indexes give also some insights on what could have been the determinants of price evolution in the Spanish car market. JEL classi…fication numbers: C43, E31, L11, L13, Keywords: Hedonic price indexes, Spanish car market, car prices, CPI, Cost of living
Resumo:
Trypanosomosis is the most economically important disease constraint to livestock productivity in sub-Saharan Africa and has significant negative impact in other parts of the world. Livestock are an integral component of farming systems and thus contribute significantly to food and economic security in developing countries. Current methods of control for trypanosomosis are inadequate to prevent the enormous socioeconomic losses resulting from this disease. A vaccine has been viewed as the most desirable control option. However, the complexity of the parasite's antigenic repertoire made development of a vaccine based on the variable surface glycoprotein coat unlikely. As a result, research is now focused on identifying invariant trypanosome components as potential targets for interrupting infection or infection-mediated disease. Immunosuppression appears to be a nearly universal feature of infection with African trypanosomes and thus may represent an essential element of the host-parasite relationship, possibly by reducing the host's ability to mount a protective immune response. Antibody, T cell and macrophage/monocyte responses of infected cattle are depressed in both trypanosusceptible and trypanotolerant breeds of cattle. This review describes the specific T cell and monocyte/macrophage functions that are altered in trypanosome-infected cattle and compares these disorders with those that have been described in the murine model of trypanosomosis. The identification of parasite factors that induce immunosuppression and the mechanisms that mediate depressed immune responses might suggest novel disease intervention strategies.
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:
La meva recerca en els tres anys de gaudiment de beca s'ha centrat en l'estudi de teories semitopològiques definides a través d'espais de cicles algebraics, introduïts per Friedlander i Lawson. Hem estudiat propietats de descens d'aquestes teories i hem construït una successió espectral que calcula explícitament la cohomologia mòrfica d'una varietat tòrica. D'altra banda, estem treballant en l'estudi de propietats d'invariància homotòpica per la cohomologia mòrfica, així com en l'estructura algebraica dels grups d'homologia de Lawson.
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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
Resumo:
Although NK cells use invariant receptors to identify diseased cells, they nevertheless adapt to their environment, including the presence of certain MHC class I (MHC-I) molecules. This NK cell education, which is mediated by inhibitory receptors specific for MHC-I molecules, changes the responsiveness of activating NK cell receptors (licensing) and modifies the repertoire of MHC-I receptors used by NK cells. The fact that certain MHC-I receptors have the unusual capacity to recognize MHC-I molecules expressed by other cells (trans) and by the NK cell itself (cis) has raised the question regarding possible contributions of the two types of interactions to NK cell education. Although the analysis of an MHC-I receptor variant suggested a role for cis interaction for NK cell licensing, adoptive NK cell transfer experiments supported a key role for trans recognition. To reconcile some of these findings, we have analyzed the impact of cell type-specific deletion of an MHC-I molecule and of a novel MHC-I receptor variant on the education of murine NK cells when these mature under steady-state conditions in vivo. We find that MHC-I expression by NK cells (cis) and by T cells (trans), and MHC-I recognition in cis and in trans, are both needed for NK cell licensing. Unexpectedly, modifications of the MHC-I receptor repertoire are chiefly dependent on cis binding, which provides additional support for an essential role for this unconventional type of interaction for NK cell education. These data suggest that two separate functions of MHC-I receptors are needed to adapt NK cells to self-MHC-I.
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Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.