940 resultados para An eddy-resolving ocean model simulation


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Atualmente, sensores remotos e computadores de alto desempenho estão sendo utilizados como instrumentos principais na coleta e produção de dados oceanográficos. De posse destes dados, é possível realizar estudos que permitem simular e prever o comportamento do oceano por meio de modelos numéricos regionais. Dentre os fatores importantes no estudo da oceanografia, podem ser destacados àqueles referentes aos impactos ambientais, de contaminação antrópica, utilização de energias renováveis, operações portuárias e etc. Contudo, devido ao grande volume de dados gerados por instituições ambientais, na forma de resultados de modelos globais como o HYCOM (Hybrid Coordinate Ocean Model) e dos programas de Reanalysis da NOAA (National Oceanic and Atmospheric Administration), torna-se necessária a criação de rotinas computacionais para realizar o tratamento de condições iniciais e de contorno, de modo que possam ser aplicadas a modelos regionais como o TELEMAC3D (www.opentelemac.org). Problemas relacionados a baixa resolução, ausência de dados e a necessidade de interpolação para diferentes malhas ou sistemas de coordenadas verticais, tornam necessária a criação de um mecanismo computacional que realize este tratamento adequadamente. Com isto, foram desenvolvidas rotinas na linguagem de programação Python, empregando interpoladores de vizinho mais próximo, de modo que, a partir de dados brutos dos modelos HYCOM e do programa de Reanalysis da NOAA, foram preparadas condições iniciais e de contorno para a realização de uma simulação numérica teste. Estes resultados foram confrontados com outro resultado numérico onde, as condições foram construídas a partir de um método de interpolação mais sofisticado, escrita em outra linguagem, e que já vem sendo utilizada no laboratório. A análise dos resultados permitiu concluir que, a rotina desenvolvida no âmbito deste trabalho, funciona adequadamente para a geração de condições iniciais e de contorno do modelo TELEMAC3D. Entretanto, um interpolador mais sofisticado deve ser desenvolvido de forma a aumentar a qualidade nas interpolações, otimizar o custo computacional, e produzir condições que sejam mais realísticas para a utilização do modelo TELEMAC3D.

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Recent realistic high resolution modeling studies show a net increase of submesoscale activity in fall and winter when the mixed layer depth is at its maximum. This submesoscale activity increase is associated with a reduced deepening of the mixed layer. Both phenomena can be related to the development of mixed layer instabilities, which convert available potential energy into submesoscale eddy kinetic energy and contribute to a fast restratification by slumping the horizontal density gradient in the mixed layer. In the present work, the mixed layer formation and restratification was studied by uniformly cooling a fully turbulent zonal jet in a periodic channel at different resolutions, from eddy resolving (10 km) to submesoscale permitting (2 km). The effect of the submesoscale activity, highlighted by these different horizontal resolutions, was quantified in terms of mixed layer depth, restratification rate and buoyancy fluxes. Contrary to many idealized studies focusing on the restratification phase only, this study addresses a continuous event of mixed layer formation followed by its complete restratification. The robustness of the present results was established by ensemble simulations. The results show that, at higher resolution, when submesoscale starts to be resolved, the mixed layer formed during the surface cooling is significantly shallower and the total restratification almost three times faster. Such differences between coarse and fine resolution models are consistent with the submesoscale upward buoyancy flux, which balances the convection during the formation phase and accelerates the restratification once the surface cooling is stopped. This submesoscale buoyancy flux is active even below the mixed layer. Our simulations show that mesoscale dynamics also cause restratification, but on longer time scales. Finally, the spatial distribution of the mixed layer depth is highly heterogeneous in the presence of submesoscale activity, prompting the question of whether it is possible to parameterize submesoscale effects and their effects on the marine biology as a function of a spatially-averaged mixed layer depth.

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Due to the growth of design size and complexity, design verification is an important aspect of the Logic Circuit development process. The purpose of verification is to validate that the design meets the system requirements and specification. This is done by either functional or formal verification. The most popular approach to functional verification is the use of simulation based techniques. Using models to replicate the behaviour of an actual system is called simulation. In this thesis, a software/data structure architecture without explicit locks is proposed to accelerate logic gate circuit simulation. We call thus system ZSIM. The ZSIM software architecture simulator targets low cost SIMD multi-core machines. Its performance is evaluated on the Intel Xeon Phi and 2 other machines (Intel Xeon and AMD Opteron). The aim of these experiments is to: • Verify that the data structure used allows SIMD acceleration, particularly on machines with gather instructions ( section 5.3.1). • Verify that, on sufficiently large circuits, substantial gains could be made from multicore parallelism ( section 5.3.2 ). • Show that a simulator using this approach out-performs an existing commercial simulator on a standard workstation ( section 5.3.3 ). • Show that the performance on a cheap Xeon Phi card is competitive with results reported elsewhere on much more expensive super-computers ( section 5.3.5 ). To evaluate the ZSIM, two types of test circuits were used: 1. Circuits from the IWLS benchmark suit [1] which allow direct comparison with other published studies of parallel simulators.2. Circuits generated by a parametrised circuit synthesizer. The synthesizer used an algorithm that has been shown to generate circuits that are statistically representative of real logic circuits. The synthesizer allowed testing of a range of very large circuits, larger than the ones for which it was possible to obtain open source files. The experimental results show that with SIMD acceleration and multicore, ZSIM gained a peak parallelisation factor of 300 on Intel Xeon Phi and 11 on Intel Xeon. With only SIMD enabled, ZSIM achieved a maximum parallelistion gain of 10 on Intel Xeon Phi and 4 on Intel Xeon. Furthermore, it was shown that this software architecture simulator running on a SIMD machine is much faster than, and can handle much bigger circuits than a widely used commercial simulator (Xilinx) running on a workstation. The performance achieved by ZSIM was also compared with similar pre-existing work on logic simulation targeting GPUs and supercomputers. It was shown that ZSIM simulator running on a Xeon Phi machine gives comparable simulation performance to the IBM Blue Gene supercomputer at very much lower cost. The experimental results have shown that the Xeon Phi is competitive with simulation on GPUs and allows the handling of much larger circuits than have been reported for GPU simulation. When targeting Xeon Phi architecture, the automatic cache management of the Xeon Phi, handles and manages the on-chip local store without any explicit mention of the local store being made in the architecture of the simulator itself. However, targeting GPUs, explicit cache management in program increases the complexity of the software architecture. Furthermore, one of the strongest points of the ZSIM simulator is its portability. Note that the same code was tested on both AMD and Xeon Phi machines. The same architecture that efficiently performs on Xeon Phi, was ported into a 64 core NUMA AMD Opteron. To conclude, the two main achievements are restated as following: The primary achievement of this work was proving that the ZSIM architecture was faster than previously published logic simulators on low cost platforms. The secondary achievement was the development of a synthetic testing suite that went beyond the scale range that was previously publicly available, based on prior work that showed the synthesis technique is valid.

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In the Tropics, continental shelves governed by western boundary currents are considered to be among the least productive ocean margins in the world, unless eddy-induced shelf-edge upwelling becomes significant. The eastern Brazilian shelf in the Southwest Atlantic is one of these, and since the slight nutrient input from continental sources is extremely oligotrophic. It is characterized by complex bathymetry with the presence of shallow banks and seamounts. In this work, a full three-dimensional nonlinear primitive equation ocean model is used to demonstrate that the interaction of tidal currents and the bottom topography of the east Brazil continental shelf is capable of producing local upwelling of South Atlantic Central Water, bringing nutrients up from deep waters to the surface layer. Such upper layer enrichment is found to be of significance in increasing local primary productivity. (c) 2005 Elsevier Ltd. All rights reserved.

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Macro and micro-economic perspectives are combined in an eco- nomic growth model. An agent-based modeling approach is used to develop an overlapping generation framework where endogenous growth is supported by work- ers that decide to study depending on their relative (skilled and unskilled) indi- vidual satisfaction. The micro perspective is based on individual satisfaction: an utility function computed from the variation of the relative income in both space and time. The macro perspective emerges from micro decisions, and, as in other growth models of this type, concerns an important allocative social decision the share of the working population that is engaged in producing ideas (skilled work- ers). Simulations show that production and satisfaction levels are higher when the evolution of income measured in both space and time are equally weighted.

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In the Southern Hemisphere (SH) polar region, satellite observations reveal a significant upper-mesosphere cooling and a lower-thermosphere warming during warm ENSO events in December. An opposite pattern is observed in the tropical mesopause region. The observed upper-mesosphere cooling agrees with a climate model simulation. Analysis of the simulation suggests that enhanced planetary wave (PW) dissipation in the Northern Hemisphere (NH) high-latitude stratosphere during El Nino strengthens the Brewer-Dobson circulation and cools the equatorial stratosphere. This increases the magnitude of the SH stratosphere meridional temperature gradient and thus causes the anomalous stratospheric easterly zonal wind and early breakdown of the SH stratospheric polar vortex. The resulting perturbation to gravity wave (GW) filtering causes anomalous SH mesospheric eastward GW forcing and polar upwelling and cooling. In addition, constructive inference of ENSO and quasi-biennial oscillation (QBO) could lead to stronger stratospheric easterly zonal wind anomalies at the SH high latitudes in November and December and early breakdown of the SH stratospheric polar vortex during warm ENSO events in the easterly QBO phase (defined by the equatorial zonal wind at similar to 25 hPa). This would in turn cause much more SH mesospheric eastward GW forcing and much colder polar temperatures, and hence it would induce an early onset time of SH summer polar mesospheric clouds (PMCs). The opposite mechanism occurs during cold ENSO events in the westerly QBO phase. This implies that ENSO together with QBO could significantly modulate the breakdown time of SH stratospheric polar vortex and the onset time of SH PMC.

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For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.

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Previous work has shown that high-temperature short-term spike thermal annealing of hydrogenated amorphous silicon (a-Si:H) photovoltaic thermal (PVT) systems results in higher electrical energy output. The relationship between temperature and performance of a-Si:H PVT is not simple as high temperatures during thermal annealing improves the immediate electrical performance following an anneal, but during the anneal it creates a marked drop in electrical performance. In addition, the power generation of a-Si:H PVT depends on both the environmental conditions and the Staebler-Wronski Effect kinetics. In order to improve the performance of a-Si:H PVT systems further, this paper reports on the effect of various dispatch strategies on system electrical performance. Utilizing experimental results from thermal annealing, an annealing model simulation for a-Si:Hbased PVT was developed and applied to different cities in the U.S. to investigate potential geographic effects on the dispatch optimization of the overall electrical PVT systems performance and annual electrical yield. The results showed that spike thermal annealing once per day maximized the improved electrical energy generation. In the outdoor operating condition this ideal behavior deteriorates and optimization rules are required to be implemented.

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Abstract Where photosynthetic eukaryotic organisms survived during the Snowball Earth events of the Neoproterozoic remains unclear. Our previous research tested whether a narrow arm of the ocean, similar to the modern Red Sea, could have been a refugium for photosynthetic eukaryotes during the Snowball Earth. Using an analytical ice-flow model, we demonstrated that a limited range of climate conditions could restrict sea-glacier flow sufficiently to allow an arm of the sea to remain partially free from sea-glacier penetration, a necessary condition for it to act as a refugium. Here we expand on the previous study, using a numerical ice-flow model, with the ability to capture additional physics, to calculate sea-glacier penetration, and to explore the effect of a channel with a narrow entrance. The climatic conditions are made selfconsistent by linking sublimation rate to surface temperature. As expected, the narrow entrance allows parts of the nearly enclosed sea to remain safe from sea-glacier penetration for a wider range of climate conditions.

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Primary glioblastoma (GB), the most common and aggressive adult brain tumour, is refractory to conventional therapies and characterised by poor prognosis. GB displays striking cellular heterogeneity, with a sub-population, called Glioblastoma Stem Cells (GSCs), intrinsically resistant to therapy, hence the high rate of recurrence. Alterations of the tumour suppressor gene PTEN are prevalent in primary GBM, resulting in the inhibition of the polarity protein Lgl1 due to aPKC hyperactivation. Dysregulation of this molecular axis is one of the mechanisms involved in GSC maintenance. After demonstrating that the PTEN/aPKC/Lgl axis is conserved in Drosophila, I deregulated it in different cells populations of the nervous system in order to individuate the cells at the root of neurogenic brain cancers. This analysis identified the type II neuroblasts (NBs) as the most sensitive to alterations of this molecular axis. Type II NBs are a sub-population of Drosophila stem cells displaying a lineage similar to that of the mammalian neural stem cells. Following aPKC activation in these stem cells, I obtained an adult brain cancer model in Drosophila that summarises many phenotypic traits of human brain tumours. Fly tumours are indeed characterised by accumulation of highly proliferative immature cells and keep growing in the adult leading the affected animals to premature death. With the aim to understand the role of cell polarity disruption in this tumorigenic process I carried out a molecular characterisation and transcriptome analysis of brain cancers from our fly model. In summary, the model I built and partially characterised in this thesis work may help deepen our knowledge on human brain cancers by investigating many different aspects of this complicate disease.

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Gliomas are one of the most frequent primary malignant brain tumors. Acquisition of stem-like features likely contributes to the malignant nature of high-grade gliomas and may be responsible for the initiation, growth, and recurrence of these tumors. In this regard, although the traditional 2D cell culture system has been widely used in cancer research, it shows limitations in maintaining the stemness properties of cancer and in mimicking the in vivo microenvironment. In order to overcome these limitations, different three-dimensional (3D) culture systems have been developed to mimic better the tumor microenvironment. Cancer cells cultured in 3D structures may represent a more reliable in vitro model due to increased cell-cell and cell-extracellular matrix (ECM) interaction. Several attempts to recreate brain cancer tissue in vitro are described in literature. However, to date, it is still unclear which main characteristics the ideal model should reproduce. The overall goal of this project was the development of a 3D in vitro model able to reproduce the brain ECM microenvironment and to recapitulate pathological condition for the study of tumor stroma interactions, tumor invasion ability, and molecular phenotype of glioma cells. We performed an in silico bioinformatic analysis using GEPIA2 Software to compare the expression level of seven matrix protein in the LGG tumors with healthy tissues. Then, we carried out a FFPE retrospective study in order to evaluate the percentage of expression of selected proteins. Thus, we developed a 3D scaffold composed by Hyaluronic Acid and Collagen IV in a ratio of 50:50. We used two astrocytoma cell lines, HTB-12 and HTB-13. In conclusion, we developed an in vitro 3D model able to reproduce the composition of brain tumor ECM, demonstrating that it is a feasible platform to investigate the interaction between tumor cells and the matrix.

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Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.

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The inflation pressure of the endotracheal tube cuff can cause ischemia of the tracheal mucosa at high pressures; thus, it can cause important tracheal morbidity and tracheal microaspiration of the oropharyngeal secretion, or it can even cause pneumonia associated with mechanical ventilation if the pressure of the cuff is insufficient. In order to investigate the effectiveness of the RUSCH® 7.5 mm endotracheal tube cuff, this study was designed to investigate the physical and mechanical aspects of the cuff in contact with the trachea. For this end, we developed an in vitro experimental model to assess the flow of dye (methylene blue) by the inflated cuff on the wall of the artificial material. We also designed an in vivo study with 12 Large White pigs under endotracheal intubation. We instilled the same dye in the oral cavity of the animals, and we analyzed the presence or not of leakage in the trachea after the region of the cuff after their deaths (animal sacrifice). All cuffs were inflated at the pressure of 30 cmH2O. We observed the passage of fluids through the cuff in all in vitro and in vivo experimental models. We conclude that, as well as several other cuff models in the literature, the RUSCH® 7.5 mm tube cuffs are also not able to completely seal the trachea and thus prevent aspiration of oropharyngeal secretions. Other prevention measures should be taken.

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The human mitochondrial Hsp70, also called mortalin, is of considerable importance for mitochondria biogenesis and the correct functioning of the cell machinery. In the mitochondrial matrix, mortalin acts in the importing and folding process of nucleus-encoded proteins. The in vivo deregulation of mortalin expression and/or function has been correlated with age-related diseases and certain cancers due to its interaction with the p53 protein. In spite of its critical biological roles, structural and functional studies on mortalin are limited by its insoluble recombinant production. This study provides the first report of the production of folded and soluble recombinant mortalin when co-expressed with the human Hsp70-escort protein 1, but it is still likely prone to self-association. The monomeric fraction of mortalin presented a slightly elongated shape and basal ATPase activity that is higher than that of its cytoplasmic counterpart Hsp70-1A, suggesting that it was obtained in the functional state. Through small angle X-ray scattering, we assessed the low-resolution structural model of monomeric mortalin that is characterized by an elongated shape. This model adequately accommodated high resolution structures of Hsp70 domains indicating its quality. We also observed that mortalin interacts with adenosine nucleotides with high affinity. Thermally induced unfolding experiments indicated that mortalin is formed by at least two domains and that the transition is sensitive to the presence of adenosine nucleotides and that this process is dependent on the presence of Mg2+ ions. Interestingly, the thermal-induced unfolding assays of mortalin suggested the presence of an aggregation/association event, which was not observed for human Hsp70-1A, and this finding may explain its natural tendency for in vivo aggregation. Our study may contribute to the structural understanding of mortalin as well as to contribute for its recombinant production for antitumor compound screenings.

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Universidade Estadual de Campinas . Faculdade de Educação Física