999 resultados para Multimodal timbre characterization
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A flexible and multipurpose bio-inspired hierarchical model for analyzing musical timbre is presented in this paper. Inspired by findings in the fields of neuroscience, computational neuroscience, and psychoacoustics, not only does the model extract spectral and temporal characteristics of a signal, but it also analyzes amplitude modulations on different timescales. It uses a cochlear filter bank to resolve the spectral components of a sound, lateral inhibition to enhance spectral resolution, and a modulation filter bank to extract the global temporal envelope and roughness of the sound from amplitude modulations. The model was evaluated in three applications. First, it was used to simulate subjective data from two roughness experiments. Second, it was used for musical instrument classification using the k-NN algorithm and a Bayesian network. Third, it was applied to find the features that characterize sounds whose timbres were labeled in an audiovisual experiment. The successful application of the proposed model in these diverse tasks revealed its potential in capturing timbral information.
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La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.
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A discriminação de fases que são praticamente indistinguíveis ao microscópio ótico de luz refletida ou ao microscópio eletrônico de varredura (MEV) é um dos problemas clássicos da microscopia de minérios. Com o objetivo de resolver este problema vem sendo recentemente empregada a técnica de microscopia colocalizada, que consiste na junção de duas modalidades de microscopia, microscopia ótica e microscopia eletrônica de varredura. O objetivo da técnica é fornecer uma imagem de microscopia multimodal, tornando possível a identificação, em amostras de minerais, de fases que não seriam distinguíveis com o uso de uma única modalidade, superando assim as limitações individuais dos dois sistemas. O método de registro até então disponível na literatura para a fusão das imagens de microscopia ótica e de microscopia eletrônica de varredura é um procedimento trabalhoso e extremamente dependente da interação do operador, uma vez que envolve a calibração do sistema com uma malha padrão a cada rotina de aquisição de imagens. Por esse motivo a técnica existente não é prática. Este trabalho propõe uma metodologia para automatizar o processo de registro de imagens de microscopia ótica e de microscopia eletrônica de varredura de maneira a aperfeiçoar e simplificar o uso da técnica de microscopia colocalizada. O método proposto pode ser subdividido em dois procedimentos: obtenção da transformação e registro das imagens com uso desta transformação. A obtenção da transformação envolve, primeiramente, o pré-processamento dos pares de forma a executar um registro grosseiro entre as imagens de cada par. Em seguida, são obtidos pontos homólogos, nas imagens óticas e de MEV. Para tal, foram utilizados dois métodos, o primeiro desenvolvido com base no algoritmo SIFT e o segundo definido a partir da varredura pelo máximo valor do coeficiente de correlação. Na etapa seguinte é calculada a transformação. Foram empregadas duas abordagens distintas: a média ponderada local (LWM) e os mínimos quadrados ponderados com polinômios ortogonais (MQPPO). O LWM recebe como entradas os chamados pseudo-homólogos, pontos que são forçadamente distribuídos de forma regular na imagem de referência, e que revelam, na imagem a ser registrada, os deslocamentos locais relativos entre as imagens. Tais pseudo-homólogos podem ser obtidos tanto pelo SIFT como pelo método do coeficiente de correlação. Por outro lado, o MQPPO recebe um conjunto de pontos com a distribuição natural. A análise dos registro de imagens obtidos empregou como métrica o valor da correlação entre as imagens obtidas. Observou-se que com o uso das variantes propostas SIFT-LWM e SIFT-Correlação foram obtidos resultados ligeiramente superiores aos do método com a malha padrão e LWM. Assim, a proposta, além de reduzir drasticamente a intervenção do operador, ainda possibilitou resultados mais precisos. Por outro lado, o método baseado na transformação fornecida pelos mínimos quadrados ponderados com polinômios ortogonais mostrou resultados inferiores aos produzidos pelo método que faz uso da malha padrão.
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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A multimodal MR study including relaxometry, diffusion tensor imaging (DTI), and MR spectroscopy was performed on patients with classical phenylketonuria (PKU) and matched controls, to improve our understanding of white matter (WM) lesions. Relaxometry yields information on myelin loss or malformation and may substantiate results from DTI attributed to myelin changes. Relaxometry was used to determine four brain compartments in normal-appearing brain tissue (NABT) and in lesions: water in myelin bilayers (myelin water, MW), water in gray matter (GM), water in WM, and water with long relaxation times (cerebrospinal fluid [CSF]-like signals). DTI yielded apparent diffusion coefficients (ADCs) and fractional anisotropies. MW and WM content were reduced in NABT and in lesions of PKU patients, while CSF-like signals were significantly increased. ADC values were reduced in PKU lesions, but also in the corpus callosum. Diffusion anisotropy was reduced in lesions because of a stronger decrease in the longitudinal than in the transverse diffusion. WM content and CSF-like components in lesions correlated with anisotropy and ADC. ADC values in lesions and in the corpus callosum correlated negatively with blood and brain phenylalanine (Phe) concentrations. Intramyelinic edema combined with vacuolization is a likely cause of the WM alterations. Correlations between diffusivity and Phe concentrations confirm vulnerability of WM to high Phe concentrations.
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When components of a propulsion system are exposed to elevated flow temperatures there is a risk for catastrophic failure if the components are not properly protected from the thermal loads. Among several strategies, slot film cooling is one of the most commonly used, yet poorly understood active cooling techniques. Tangential injection of a relatively cool fluid layer protects the surface(s) in question, but the turbulent mixing between the hot mainstream and cooler film along with the presence of the wall presents an inherently complex problem where kinematics, thermal transport and multimodal heat transfer are coupled. Furthermore, new propulsion designs rely heavily on CFD analysis to verify their viability. These CFD models require validation of their results, and the current literature does not provide a comprehensive data set for film cooling that meets all the demands for proper validation, namely a comprehensive (kinematic, thermal and boundary condition data) data set obtained over a wide range of conditions. This body of work aims at solving the fundamental issue of validation by providing high quality comprehensive film cooling data (kinematics, thermal mixing, heat transfer). 3 distinct velocity ratios (VR=uc/u∞) are examined corresponding to wall-wake (VR~0.5), min-shear (VR ~ 1.0), and wall-jet (VR~2.0) type flows at injection, while the temperature ratio TR= T∞/Tc is approximately 1.5 for all cases. Turbulence intensities at injection are 2-4% for the mainstream (urms/u∞, vrms/u∞,), and on the order of 8-10% for the coolant (urms/uc, vrms/uc,). A special emphasis is placed on inlet characterization, since inlet data in the literature is often incomplete or is of relatively low quality for CFD development. The data reveals that min-shear injection provides the best performance, followed by the wall-jet. The wall-wake case is comparably poor in performance. The comprehensive data suggests that this relative performance is due to the mixing strength of each case, as well as the location of regions of strong mixing with respect to the wall. Kinematic and thermal data show that strong mixing occurs in the wall-jet away from the wall (y/s>1), while strong mixing in the wall-wake occurs much closer to the wall (y/s<1). Min-shear cases exhibit noticeably weaker mixing confined to about y/s=1. Additionally to these general observations, the experimental data obtained in this work is analyzed to reveal scaling laws for the inlets, near-wall scaling, detecting and characterizing coherent structures in the flow as well as to provide data reduction strategies for comparison to CFD models (RANS and LES).
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Görgeyite, K2Ca5(SO4)6··H2O, is a very rare monoclinic double salt found in evaporites related to the slightly more common mineral syngenite. At 1 atmosphere with increasing external temperature from 25 to 150 °C, the following succession of minerals was formed: first gypsum and K2O, followed at 100 °C by görgeyite. Changes in concentration at 150 °C due to evaporation resulted in the formation of syngenite and finally arcanite. Under hydrothermal conditions, the succession is syngenite at 50 °C, followed by görgyeite at 100 and 150 °C. Increasing the synthesis time at 100 °C and 1 atmosphere showed that initially gypsum was formed, later being replaced by görgeyite. Finally görgeyite was replaced by syngenite, indicating that görgeyite is a metastable phase under these conditions. Under hydrothermal conditions, syngenite plus a small amount of gypsum was formed, after two days being replaced by görgeyite. No further changes were observed with increasing time. Pure görgeyite showed elongated crystals approximately 500 to 1000 µ m in length. The infrared and Raman spectra are mainly showing the vibrational modes of the sulfate groups and the crystal water (structural water). Water is characterized by OH-stretching modes at 3526 and 3577 cm–1 , OH-bending modes at 1615 and 1647 cm–1 , and an OH-libration mode at 876 cm–1 . The sulfate 1 mode is weak in the infrared but showed strong bands at 1005 and 1013 cm–1 in the Raman spectrum. The 2 mode also showed strong bands in the Raman spectrum at 433, 440, 457, and 480 cm–1 . The 3 mode is characterized by a complex set of bands in both infrared and Raman spectra around 1150 cm–1 , whereas 4 is found at 650 cm–1.
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Single walled carbon nanotubes (SWNTs) were incorporated in polymer nanocomposites based on poly(3-octylthiophene) (P3OT), thermoplastic polyurethane (TPU) or a blend of them. Thermogravimetry demonstrated the success of the purification procedure employed in the chemical treatment of SWNTs prior to composite preparation. Stable dispersions of SWNTs in chloroform were obtained by non-covalent interactions with the dissolved polymers. Composites exhibited glass transitions, melting temperatures and heat of fusion which changed in relation to pure polymers. This behavior is discussed as associated to interactions between nanotubes and polymers. The conductivity at room temperature of the blend (TPU-P3OT) with SWNT is higher than the P3OT/SWNT composite.