952 resultados para Curves of double curvature.


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The Hybrid Monte Carlo algorithm is adapted to the simulation of a system of classical degrees of freedom coupled to non self-interacting lattices fermions. The diagonalization of the Hamiltonian matrix is avoided by introducing a path-integral formulation of the problem, in d + 1 Euclidean space–time. A perfect action formulation allows to work on the continuum Euclidean time, without need for a Trotter–Suzuki extrapolation. To demonstrate the feasibility of the method we study the Double Exchange Model in three dimensions. The complexity of the algorithm grows only as the system volume, allowing to simulate in lattices as large as 163 on a personal computer. We conclude that the second order paramagnetic–ferromagnetic phase transition of Double Exchange Materials close to half-filling belongs to the Universality Class of the three-dimensional classical Heisenberg model.

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Near-infrared polarimetry observation is a powerful tool to study the central sources at the center of the Milky Way. My aim of this thesis is to analyze the polarized emission present in the central few light years of the Galactic Center region, in particular the non-thermal polarized emission of Sagittarius~A* (Sgr~A*), the electromagnetic manifestation of the super-massive black hole, and the polarized emission of an infrared-excess source in the literature referred to as DSO/G2. This source is in orbit about Sgr~A*. In this thesis I focus onto the Galactic Center observations at $\lambda=2.2~\mu m$ ($K_\mathrm{s}$-band) in polarimetry mode during several epochs from 2004 to 2012. The near-infrared polarized observations have been carried out using the adaptive optics instrument NAOS/CONICA and Wollaston prism at the Very Large Telescope of ESO (European Southern Observatory). Linear polarization at 2.2 $\mu m$, its flux statistics and time variation, can be used to constrain the physical conditions of the accretion process onto the central super-massive black hole. I present a statistical analysis of polarized $K_\mathrm{s}$-band emission from Sgr~A* and investigate the most comprehensive sample of near-infrared polarimetric light curves of this source up to now. I find several polarized flux excursions during the years and obtain an exponent of about 4 for the power-law fitted to polarized flux density distribution of fluxes above 5~mJy. Therefore, this distribution is closely linked to the single state power-law distribution of the total $K_\mathrm{s}$-band flux densities reported earlier by us. I find polarization degrees of the order of 20\%$\pm$10\% and a preferred polarization angle of $13^o\pm15^o$. Based on simulations of polarimetric measurements given the observed flux density and its uncertainty in orthogonal polarimetry channels, I find that the uncertainties of polarization parameters under a total flux density of $\sim 2\,{\mathrm{mJy}}$ are probably dominated by observational uncertainties. At higher flux densities there are intrinsic variations of polarization degree and angle within rather well constrained ranges. Since the emission is most likely due to optically thin synchrotron radiation, the obtained preferred polarization angle is very likely reflecting the intrinsic orientation of the Sgr~A* system i.e. an accretion disk or jet/wind scenario coupled to the super-massive black hole. Our polarization statistics show that Sgr~A* must be a stable system, both in terms of geometry, and the accretion process. I also investigate an infrared-excess source called G2 or Dusty S-cluster Object (DSO) moving on a highly eccentric orbit around the Galaxy's central black hole, Sgr~A*. I use for the first time the near-infrared polarimetric imaging data to determine the nature and the properties of DSO and obtain an improved $K_\mathrm{s}$-band identification of this source in median polarimetry images of different observing years. The source starts to deviate from the stellar confusion in 2008 data and it does not show a flux density variability based on our data set. Furthermore, I measure the polarization degree and angle of this source and conclude based on the simulations on polarization parameters that it is an intrinsically polarized source with a varying polarization angle as it approaches Sgr~A* position. I use the interpretation of the DSO polarimetry measurements to assess its possible properties.

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Das Gesundheitsmanagement von Milchkühen hat in den vergangenen Jahren auf den landwirtschaftlichen Betrieben an Bedeutung gewonnen. Neben Präventionsmaßnahmen zur Gesunderhaltung der Tiere ist die frühzeitige und systematische Erkennung von Erkrankungen hierbei der Hauptbestandteil. Es zeigt sich vermehrt, dass vor allem Transitkühe verstärkt an Stoffwechselerkrankungen in sowohl klinischer als auch subklinischer Form erkranken. Letztere stellen ein hohes Risiko dar, zum einen weil subklinische Erkrankungen oftmals nur schwer oder gar nicht erkannt werden und zum anderen, weil sie in vielen Fällen die Grundlage für meist schwerwiegendere Folgeerkrankungen sind. In der vorliegenden Studie wird das Thema der Früherkennung von subklinischen Ketosen und der subakuten Pansenazidose behandelt. Verschiedene Methoden wurden unter praktischen Versuchsbedingungen auf ihre Tauglichkeit zur Krankheitserkennung hin geprüft. In einer ersten Studie wurde auf einem konventionellen Milchviehbetrieb ein Ketose-Monitoring bei frischlaktierenden Kühen ab Tag 3 postpartum durchgeführt. Insgesamt 15 Tiere waren an einer subklinischen Ketose erkrankt, was eine Aufkommensrate von 26% in den untersuchten Tieren bedeutete. Die Blutproben von insgesamt 24 Tieren wurden auf ihren IL-6-Gehalt untersucht. Von den untersuchten Tieren waren 14 Tiere erkrankt, 10 Tiere bildeten die gesunde Kontrollgruppe. Interleukin-6 wurde bestimmt, da dem Zytokin IL-6 in anderen Studien in Bezug auf Ketosen eine Rolle zugesprochen wurde. Die erwartete Erhöhung von IL-6 bei erkrankten Tieren konnte nicht festgestellt werden; die erkrankten Kühe zeigten vielmehr die niedrigsten IL-6 Werte der Studiengruppe. Insgesamt waren die IL-6 Konzentrationen auf einem niedrigen Niveau mit 27.2 pg/m l± 10.2. Es zeigte sich, dass die IL-6 Bestimmung im Blut hinsichtlich der Erkennung von subklinischen Ketosen nur eingeschränkt nutzbar ist. Es konnte ausschließlich eine schwache negative Korrelation zwischen Beta- Hydroxybutyrat (BHBA, Goldstandard für den Nachweis einer Ketose) und IL-6 detektiert werden. Zusätzlich zu den Blutanalysen wurde ebenfalls die tägliche Wiederkauaktivität mit dem „DairyCheck“ System bestimmt, welches kontinuierlich die charakteristischen Kaumuskelkontraktionen aufzeichnet und somit die Dauer des Wiederkäuens bestimmt werden kann. Es wurde geprüft, ob sich ketotische Tiere von nicht ketotischen Tieren hinsichtlich der täglichen Wiederkäuzeit unterscheiden. Milchkühe mit einer Ketose kauten im Schnitt 475 min/d ± 56 wieder, nach Genesung 497 min/d ± 48. Sie befanden sich somit im Durchschnitt immer unterhalb der gesunden Kontrollgruppe, welche 521 min/d ± 76 wiederkaute. Eine Korrelation zwischen der Wiederkauzeit und dem BHBA- Gehalt im Blut war nur sehr schwach ausgeprägt, nicht zuletzt da die Tiere generell eine hohe Variabilität in der Wiederkauaktivität zeigten. Bei einer weiteren Studie, ebenfalls auf einem Praxisbetrieb durchgeführt, wurde auf die Erkennung der subakuten Pansensazidose (SARA) fokussiert. Hierbei kam ein drahtloses, kommerziell verfügbares Bolussystem zum Einsatz, welches den pH Wert kontinuierlich im Retikulorumen misst. Es macht die Erkennung einer SARA auch unter Praxisbedingungen ohne invasive Methoden wie der Punktion möglich. Das Bolussystem wurde 24 Milchkühen kurz vor der Abkalbung oral eingegeben, um den pH-Wert während der gesamten Transitphase messen und überwachen zu können. Während in der Trockenstehphase nur vereinzelte SARA Fälle auftraten, erlitt ein Großteil der untersuchten Tiere in der Frühlaktation eine SARA. Auf Grundlage von pH-Werten von laktierenden Milchkühen, wurde zusätzlich eine Sensitivitätsanalyse von verschieden, bereits eingesetzten Nachweismethoden durchgeführt, um die Tauglichkeit für die SARA-Diagnostik zu untersuchen. Es handelte sich hierbei zum einen um einen SARA-Nachweis unter Heranziehung von Einzelwerten, Fress- und Wiederkäuzeiten, sowie ausgewählten Milchinhaltsstoffen und der Milchmenge. Die Analyse ergab, dass nahezu alle Nachweismethoden im Vergleich zur Langzeitmessung nur eingeschränkt zur SARA-Diagnostik nutzbar sind. In einem weiteren Teil der Studie wurde eine Kotfraktionierung bei den gleichen Tieren durchgeführt, um damit SARA-Tiere auch mittels der Kotanalyse erkennen kann. Es konnte gezeigt werden, dass zum einen die Ration einen Einfluss auf die Kotzusammensetzung hat (Trockensteherration versus Ration für Laktierende) zum anderen aber auch, dass eine SARA die Zusammensetzung des Kotes verändert. Hierfür wurden Kotproben ausschließlich von laktierenden Kühen untersucht, sodass der Einfluss der Ration ausgeschlossen werden konnte. Erhöhte Faseranteile im Kot von SARA - Kühen gaben Hinweis auf eine verminderte Verdaulichkeit. Dabei erwies sich vor allem die Hemizellulose als guter Parameter, um auf eine SARA schließen zu können. Die Versuchsbedingungen ließen es ebenfalls zu, die pH-Verläufe der Tiere in der Frühlaktation zu untersuchen. Eine Clusteranalyse von pH-Werten der ersten 12 Tage postpartum zeigte, dass die untersuchten Tiere trotz gleicher Haltungs- und Fütterungsbedingungen unterschiedliche pH-Wert Verläufe entwickelten. So gab es eine Gruppe von Milchkühen, die den pH-Wert stabil halten konnte, während die restlichen pH-Abfälle in verschiedenen Verläufen und Intensitäten aufzeigten. Es konnte ebenfalls aufgezeigt werden, dass Tiere innerhalb der Testherde unterschiedliche Schweregrade der SARA entwickelten. Auch in dieser Studie wurde deutlich, dass Tiere scheinbar unterschiedliche Möglichkeiten haben, auf ihre Umwelt zu reagieren, bzw. suboptimalen Bedingungen entgegenwirken zu können. Zusammengefasst wurden verschiedene Methoden zur Ketose- und SARA- Erkennung geprüft, von denen nur einzelne für die Praxis zu empfehlen sind. Die Variabilität der Tiere, sowohl bei der Ausprägung der Erkrankungen als auch bei den gemessenen Parametern verdeutlicht die Notwendigkeit, diese im Herden- und Gesundheitsmanagement in Zukunft stärker zu berücksichtigen.

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Abstract: The objectives of this study were to evaluate the combined effects of soil bioticand abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two typesofsewagesludge intosoil ina 5-years field assay under tropical conditions and topredict the effectsof these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. Amultiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil.

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The topic of seismic loss assessment not only incorporates many aspects of the earthquake engineering, but also entails social factors, public policies and business interests. Because of its multidisciplinary character, this process may be complex to challenge, and sound discouraging to neophytes. In this context, there is an increasing need of deriving simplified methodologies to streamline the process and provide tools for decision-makers and practitioners. This dissertation investigates different possible applications both in the area of modelling of seismic losses, both in the analysis of observational seismic data. Regarding the first topic, the PRESSAFE-disp method is proposed for the fast evaluation of the fragility curves of precast reinforced-concrete (RC) structures. Hence, a direct application of the method to the productive area of San Felice is studied to assess the number of collapses under a specific seismic scenario. In particular, with reference to the 2012 events, two large-scale stochastic models are outlined. The outcomes of the framework are promising, in good agreement with the observed damage scenario. Furthermore, a simplified displacement-based methodology is outlined to estimate different loss performance metrics for the decision-making phase of the seismic retrofit of a single RC building. The aim is to evaluate the seismic performance of different retrofit options, for a comparative analysis of their effectiveness and the convenience. Finally, a contribution to the analysis of the observational data is presented in the last part of the dissertation. A specific database of losses of precast RC buildings damaged by the 2012 Earthquake is created. A statistical analysis is performed, allowing deriving several consequence functions. The outcomes presented may be implemented in probabilistic seismic risk assessments to forecast the losses at the large scale. Furthermore, these may be adopted to establish retrofit policies to prevent and reduce the consequences of future earthquakes in industrial areas.

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The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

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This work aims to develop a neurogeometric model of stereo vision, based on cortical architectures involved in the problem of 3D perception and neural mechanisms generated by retinal disparities. First, we provide a sub-Riemannian geometry for stereo vision, inspired by the work on the stereo problem by Zucker (2006), and using sub-Riemannian tools introduced by Citti-Sarti (2006) for monocular vision. We present a mathematical interpretation of the neural mechanisms underlying the behavior of binocular cells, that integrate monocular inputs. The natural compatibility between stereo geometry and neurophysiological models shows that these binocular cells are sensitive to position and orientation. Therefore, we model their action in the space R3xS2 equipped with a sub-Riemannian metric. Integral curves of the sub-Riemannian structure model neural connectivity and can be related to the 3D analog of the psychophysical association fields for the 3D process of regular contour formation. Then, we identify 3D perceptual units in the visual scene: they emerge as a consequence of the random cortico-cortical connection of binocular cells. Considering an opportune stochastic version of the integral curves, we generate a family of kernels. These kernels represent the probability of interaction between binocular cells, and they are implemented as facilitation patterns to define the evolution in time of neural population activity at a point. This activity is usually modeled through a mean field equation: steady stable solutions lead to consider the associated eigenvalue problem. We show that three-dimensional perceptual units naturally arise from the discrete version of the eigenvalue problem associated to the integro-differential equation of the population activity.

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The purpose of the thesis is to develop a model for the functional behaviour of neurons in the primary motor cortex (M1) responsible for arm reaching movements. From Georgopoulos neurophysiological data, we provide a first bundle structure compatible with the hypercolumnar organization and with the position-direction selectivity of motor cortical cells. We then extend this model to encode the direction of arm movement which varies in time, as experimentally measured by Hatsopoulos by introducing the notion of movement fragments. We provide a sub-Riemannian model which describes the time-dependent directional selectivity of cells though integral curves of the geometric structure we set up. The sub-Riemannian distance we define allows to implement a grouping algorithm able to detect a set of hand motor trajectories. These paths, identified by using a kernel defined in terms of kinematic variables, are compatible with the motor primitives obtained from neurophysiological results by spectral analysis applied directly on cortical variables. In a second part of the work, we propose geodesics in this space as an alternative model of models for arm movement trajectories. We define a special class of curves, called admissible, on which to study the geodesics problem: we provide a connectivity property in terms of admissible paths and the existence of normal length minimizers. Admissible geodesics are used as a model of reaching paths, finding a first validation through Flash and Hogan minimizing trajectories.

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We study automorphisms and the mapping class group of irreducible holomorphic symplectic (IHS) manifolds. We produce two examples of manifolds of K3[2] type with a symplectic action of the alternating group A7. Our examples are realized as double EPW-sextics, the large cardinality of the group allows us to prove the irrationality of the associated families of Gushel-Mukai threefolds. We describe the group of automorphisms of double EPW-cubes. We give an answer to the Nielsen realization problem for IHS manifolds in analogy to the case of K3 surfaces, determining when a finite group of mapping classes fixes an Einstein (or Kähler-Einstein) metric. We describe, for some deformation classes, the mapping class group and its representation in second cohomology. We classify non-symplectic involutions of manifolds of OG10 type determining the possible invariant and coinvariant lattices. We study non-symplectic involutions on LSV manifolds that are geometrically induced from non-symplectic involutions on cubic fourfolds.

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Inflation is the primordial stage of accelerated expansion of the Universe which solves the issues of the initial conditions of a decelerating Universe (horizon, flatness and entropy problems). Moreover, it is supposed that quantum fluctuations originated during the first moments after the Big Bang gave rise to the formation of galaxies and other structures of the Universe when inflation ends. Among these structures also primordial black holes (PBHs) may have been generated. The interest in PBHs relies on their possible connection with dark matter: they could constitute a portion or even the whole dark matter content of our Universe.\\ In this work we consider inflation in the Induced Gravity (IR) context and study possible mechanisms of amplification of the curvature perturbations generated during the cosmic acceleration. In particular we consider the possibility of a period of Constant Roll (CR). Starting from the previous work of Starobinsky et al. Our final purpose is to analyse the power spectrum of the scalar perturbations and to find in which conditions there is an enhancement of the power spectrum possibly leading to PBHs formation.

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This paper presents two techniques to evaluate soil mechanical resistance to penetration as an auxiliary method to help in a decision-making in subsoiling operations. The decision is based on the volume of soil mobilized as a function of the considered critical soil resistance to penetration in each case. The first method, probabilistic, uses statistical techniques to define the volume of soil to be mobilized. The other method, deterministic, determines the percentage of soil to be mobilized and its spatial distribution. Both cases plot the percentage curves of experimental data related to the soil mechanical resistance to penetration equal or larger to the established critical level and the volume of soil to be mobilized as a function of critical level. The deterministic method plots showed the spatial distribution of the data with resistance to penetration equal or large than the critical level. The comparison between mobilized soil curves as a function of critical level using both methods showed that they can be considered equivalent. The deterministic method has the advantage of showing the spatial distribution of the critical points.

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The present work aimed the development of a low cost servo-valve that answers to an electronic control signal, for variable rates liquid inputs application. A literature research to define which valve type should be used was made. A mechanically activated proportional valve with an electronically controlled servo-engine was designed and evaluated. Since developed the servo-valve, the system was submited to a number of tests .The evaluation of its behavior was obtained in terms of repeatability, hystheresis and linearity. The test was accomplished in a bench, specially developed for this aim. As a result, were obtained three curves of opening percentage as function of flow rate, describing three opening and closing increments in two different work pressures. The servo-valve presented a good repeatability, reasonable hysteresis and a typically quadratic curve. This one maintained the low cost target. These results were very satisfied because the non-linearity and the hysteresis could be easily corrected by software.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física