14 research outputs found

    High-Speed LIF Imaging for Cycle-Resolved Formaldehyde Visualization in HCCI Combustion

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    High-speed laser diagnostics was utilized for singlecycle resolved studies of the formaldehyde distribution in the combustion chamber of an HCCI engine. A multi- YAG laser system consisting of four individual Qswitched, flash lamp-pumped Nd:YAG lasers has previously been developed in order to obtain laser pulses at 355 nm suitable for performing LIF measurements of the formaldehyde molecule. Bursts of up to eight pulses with very short time separation can be produced, allowing capturing of LIF image series with high temporal resolution. The system was used together with a high-speed framing camera employing eight intensified CCD modules, with a frame-rate matching the laser pulse repetition rate. The diagnostic system was used to study the combustion in a truck-size HCCI engine, running at 1200 rpm using n-heptane as fuel. By using laser pulses with time separations as short as 7

    Isoflurane does not cause neuroapoptosis but reduces astroglial processes in young adult mice

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    <p>Abstract</p> <p>Background</p> <p>Isoflurane, a volatile anesthetic widely used clinically, has been implicated to be both neuroprotective and neurotoxic. The claim about isoflurane causing neural apoptosis remains controversial. In this study, we investigated the effects of isoflurane exposures on apoptotic and anti-apoptotic signals, cell proliferation and neurogenesis, and astroglial processes in young adult mouse brains.</p> <p>Methods</p> <p>Sixty 6-week-old mice were randomly assigned to four anesthetic concentration groups (0 as control and 0.6%, 1.3%, and 2%) with four recovery times (2 h and 1, 6, and 14 d) after 2-h isoflurane exposure. Immunohistochemistry measurements of activated caspase-3 and Bcl-xl for apoptotic and anti-apoptotic signals, respectively, glial fibrillary acidic protein (GFAP) and vimentin for reactive astrocytosis, doublecortin (Dcx) for neurogenesis, and BrdU for cell proliferation were performed.</p> <p>Results</p> <p>Contrary to the previous conclusion derived from studies with neonatal rodents, we found no evidence of isoflurane-induced apoptosis in the adult mouse brain. Neurogenesis in the subgranule zone of the dentate gyrus was not affected by isoflurane. However, there is a tendency of reduced cell proliferation after 2% isoflurane exposure. VIM and GFAP staining showed that isoflurane exposure caused a delayed reduction of astroglial processes in the hippocampus and dentate gyrus.</p> <p>Conclusion</p> <p>Two-hour exposure to isoflurane did not cause neuroapoptosis in adult brains. The delayed reduction in astroglial processes after isoflurane exposure may explain why some volatile anesthetics can confer neuroprotection after experimental stroke because reduced glial scarring facilitates better long-term neuronal recoveries.</p

    Low-rank matrix completion : theory, algorithms and applications

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    Orientadores: Cristiano Torezzan, Carlile Campos LavorTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação CientíficaResumo: O problema de estimar dados faltantes em matrizes aparece em diversas aplicações e tem despertado interesses de pesquisadores das mais variadas áreas. Em termos gerais, o Problema de Completamento de Matrizes (PCM) consiste em determinar as entradas desconhecidas ou imprecisas de uma matriz. Em diversas situações o PCM está associado a matrizes que possuem postos reduzidos. Nestes casos, o PCM pode ser modelado como um problema de otimização, que admite uma relaxação nuclear na forma Lagrangiana por meio de um parâmetro regularizador. Neste trabalho, desenvolvemos um estudo teórico e computacional sobre o PCM com posto reduzido. Propomos uma maneira de computar a sequência associada ao parâmetro regularizador, quando o posto da matriz é conhecido visando acelerar a convergência do algoritmo conhecido na literatura como Soft-Impute. Esta modificação tem apresentado resultados computacionais relevantes permitindo, por exemplo, resolver problemas com até 99% de dados faltantes com alta precisão. Como aplicação, exploramos o completamento de Matriz de Distâncias Euclidianas (EDM) e propomos um protocolo de recuperação que explora a matriz de Gram associada à EDM. Finalmente, comparamos os resultados obtidos, usando a nossa proposta, com os resultados obtidos a partir de outros métodos e propomos aplicações relacionadas ao processamento de imagens, tanto para eliminação de ruído quanto para a construção de compressores de imagens usando o PCM. Diversos resultados numéricos atestam a eficiência das nossas propostasAbstract: The problem of estimating missing data in matrices appears in several applications and it has aroused the attention of researchers from different areas. In general, the Matrix Completion Problem (PCM) consists in determining the values of a subset of the entries in a matrix that are unknown or imprecise. In several situations the PCM is associated with matrices that have low-rank. In these cases, the PCM can be modeled as an optimization problem that admits a nuclear relaxation in the Lagrangian form, and uses a regularization parameter. In this work, we develop a theoretical and computational study on the PCM with low-rank. We propose a new way to compute the sequence associated with the regularization parameter for the case where the rank of the matrix is known a priori in order to accelerate the convergence of an algorithm known in the literature as Soft- Impute. This modification has presented relevant computational results allowing, for example, solving problems with up to 99% of missing data with high precision. As an application, we explore the Euclidean Distances Matrix (EDM) completion and propose a retrieval protocol that explores the Gram matrix associated to the EDM. Finally, we compare the results obtained, using our proposal, with the results obtained from other methods and propose applications related to image processing, both for noise elimination and for the construction of image compressors using PCM. Several numerical results attest the efficiency of our proposalsDoutoradoMatematica AplicadaDoutor em Matemática AplicadaCAPE

    Reconocimiento óptico de caracteres en placas vehiculares haciendo uso de redes neuronales convolucionales

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    La visión por computador es una rama de la inteligencia artificial, que tiene como objetivo comprender los elementos o características de una escena o imagen del mundo real, todo esto basado en poder automatizar algunos procesos o simplemente permitir que un computador pueda realizar tareas que normalmente ejecuta un ser humano. Por tal motivo surge la posibilidad de automatizar algunos procesos que para las personas son repetitivos o requieren una concentración extrema, principalmente en temas asociados a vigilancia. Por consiguiente nace la necesidad de construir herramientas que faciliten las labores operativas y poder suplir la presencia de un ser humano en algunos procesos. Continuando el hilo de la información y haciendo uso de un enfoque a problemas de control de tráfico aparece una herramienta bastante versátil debido a sus diferentes formas de realizarse como lo son los sistemas ALPR (Automatic License Plate Recognition) que permiten satisfacer las razones anteriormente mencionadas y además poder atacar esta problemática con herramientas de visión artificial como lo son las redes neuronales convolucionales

    Resultados teóricos y prácticos sobre procesamiento de señales

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    Tesis doctoral inédita, leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Matemáticas. Fecha de lectura: 19-12-201

    Discrete maximum principle for a space-time least squares formulation of the transport equation with finite element.

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    Finite element methods are known to produce spurious oscillations when the transport equation is solved. In this paper, a variational formulation for the transport equation is proposed, and by introducing a positivity constraint combined with a penalization of the total variation of the solution, a discrete maximum principle is verified for lagrange first order finite element methods. Moreover, the oscillations are cancelled
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