854 resultados para Steel and synthetic fibres
Resumo:
Data of the strength of Earth’s magnetic field (paleointensity) in the geological past are crucial for understanding the geodynamo. Conventional paleointensity determination methods require heating a sample to a high temperature in one or more steps. Consequently, many rocks are unsuitable for these methods due to a heating-induced experimental alteration. Alternative non-heating paleointensity methods are investigated to assess their effectiveness and reliability using both natural samples from Lemptégy Volcano, France, and synthetic samples. Paleointensity was measured from the natural and synthetic samples using the Pseudo-Thellier, ARM, REM, REMc, REM’, and Preisach methods. For the natural samples, only the Pseudo-Thellier method was able to produce a reasonable paleointensity estimate consistent with previous paleointensity data. The synthetic samples yielded more successful estimates using all the methods, with the Pseudo-Thellier and ARM methods producing the most accurate results. The Pseudo-Thellier method appears to be the best alternative to the heating-based paleointensity methods.
Resumo:
Matrix metalloproteinases (MMPs, including the membrane-type MMPs (MT-MMPs)), a disintegrin and metalloproteinase (ADAM), and ADAM with thrombospondin motifs belong to the metzincins, a subclass of metalloproteinases that contain a Met residue and a Zn(2+) ion at the catalytic site necessary for enzymatic reaction. MMP proteolytic activity is mainly controlled by their natural tissue inhibitors of metalloproteinase (TIMP). A number of synthetic inhibitors have been developed to control deleterious MMP activity. The roles of MMPs and some of their ECM substrates in CNS physiology and pathology are covered by other chapters of the present volume and will thus not be addressed in depth. This chapter will focus (i) on the endogenous MMP inhibitors in the CNS, (ii) on MMP and TIMP regulations in three large classes of neuropathologic processes (inflammatory, neurodegenerative, and infectious), and (iii) on synthetic inhibitors of MMPs and the perspective of their use in different brain diseases.
Resumo:
Synthetic mass accumulation rates have been calculated for ODP Site 707 using depth-density and depth-porosity functions to estimate values for these parameters with increasing sediment thickness, at 1 Ma time intervals determined on the basis of published microfossil datums. These datums were the basis of the age model used by Peterson and Backman (1990, doi:10.2973/odp.proc.sr.115.163.1990) to calculate actual mass accumulation rate data using density and porosity measurements. A comparison is made between the synthetic and actual mass accumulation rate values for the time interval 37 Ma to the Recent for 1 Myr time intervals. There is a correlation coefficient of 0.993 between the two data sets, with an absolute difference generally less than 0.1 g/cm**2/kyr. We have used the method to extend the mass accumulation rate analysis back to the Late Paleocene (60 Ma) for Site 707. Providing age datums (e.g. fossil or magnetic anomaly data) are available the generation of synthetic mass accumulation rates can be calculated for any sediment sequence.
Resumo:
Zinc chelates have been widely used to correct deficiencies in this micronutrient in different soil types and under different moisture conditions. The aging of the metal in soil could cause a change in its availability. Over time the most labile forms of Zn could decrease in activity and extractability and change to more stable forms. Various soil parameters, such as redox conditions, time, soil type and moisture conditions, affect the aging process and modify the solubility of the metal. In general, redox conditions influence pH and also the chemical forms dissolved in the soil solution. Soil pH also affects Zn solubility; at high pH values, most of the Zn is present in forms that are not bioavailable to plants. The objective of this study was to determine the changes in Zn over time in a soil solution in a waterlogged acidic soil to which synthetic and natural chelates were applied
Resumo:
La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.
Resumo:
This research sets out to build upon excited state o-azaxylylene cycloaddition. The mechanism behind the excitation and cycloaddition process of photogenerated o-azaxylylenes was determined experimentally. Time-correlated single-photon counting, steady-state spectroscopy, triplet quenching experiments, and quantum yield studies provided evidence suggesting that excited state intramolecular proton transfer is followed by intersystem crossing and stepwise addition to the tethered unsaturated pendant. In keeping with the principles of diversity oriented synthesis, a modular approach was taken to gain access to a diverse array of N,O,S-Polyheterocycles which were modified postphotochemically via Suzuki coupling to yield fused biaryls. Cycloaddition products, outfitted with halogens in the aromatic ring of the o-azaxylylene, proved to be reactive with a variety of boronic acids resulting in a rapid growth in structural complexity. A novel procedure was developed that utilized multiple o-azaxylylene cores in a photochemical cascade transformation yielding complex scaffolds of unprecedented topology. The photoprecursors were produced in a one-pot two-step sequence from commercially available starting materials, and upon irradiation yield structures containing up to five fused hetrocyclic rings, and showed complete diastereoselectivity.