336 research outputs found

    Src Family Kinases in Intracerebral Hemorrhage

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    Vertical compact torus injection into the STOR-M Tokamak

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    Central fuelling is a fundamental issue in the neat generation tokamak – ITER (International Thermonuclear Experimental Reactor). It is essential for optimization of the bootstrap current which is proportional to the pressure gradient of trapped particles. The conventional tokamak fuelling techniques, such as gas puffing and cryogenic pellet injection, are considered to be inadequate to fulfill this goal due to premature ionization caused by high plasma temperature and density. Fuelling by injecting a compact torus (CT) may be the only viable method suitable for a reactor-grade tokamak. CTs can be injected at different angles with respect to the tokamak toroidal magnetic field, either horizontally or vertically. In vertical injection, deeper CT penetration is expected due to the absence of the gradient of tokamak toroidal magnetic field in that direction. This thesis contributes to experimental investigation of vertical compact torus injection into the STOR-M tokamak. To perform vertical injection, the original injector- USCTI (University of Saskatchewan Compact Torus Injector) was modified by attaching a segment of 90˚ curved drift tube to bend the CT trajectory from horizontal to vertical. Bench tests have shown that a CT injected horizontally can be deflected effectively to the vertical direction. The velocity of 130 km•s^{-1}has been achieved while the CT passes through the 90˚ curved drift tube. It was found that the CT magnetic field structure kept intact as a typical structure of compact torus plasma. By further optimization of the USCTI configuration, the velocity has been increased to 270 km•s^{-1}. Based on the encouraging bench test results, actual vertical CT injection experiments have been performed in the STOR-M tokamak. Experimental results demonstrated, for the first time, vertical CT injection into a tokamak. Prompt increases both in line averaged electron density and in soft X-ray emission (central cord) are observed following vertical injection. Some H-mode phenomena, characterized by suppression of the m =2 Mirnov oscillation level and drop in Hα radiation level, have also been observed following the vertical injection. Fuelling effects caused by vertical injection and by tangential injection are discussed. The experimental results suggest that vertical CT injection is a feasible tokamak fuelling technique

    Analyzing big time series data in solar engineering using features and PCA

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    In solar engineering, we encounter big time series data such as the satellite-derived irradiance data and string-level measurements from a utility-scale photovoltaic (PV) system. While storing and hosting big data are certainly possible using today’s data storage technology, it is challenging to effectively and efficiently visualize and analyze the data. We consider a data analytics algorithm to mitigate some of these challenges in this work. The algorithm computes a set of generic and/or application-specific features to characterize the time series, and subsequently uses principal component analysis to project these features onto a two-dimensional space. As each time series can be represented by features, it can be treated as a single data point in the feature space, allowing many operations to become more amenable. Three applications are discussed within the overall framework, namely (1) the PV system type identification, (2) monitoring network design, and (3) anomalous string detection. The proposed framework can be easily translated to many other solar engineer applications

    microRNA expression in peripheral blood cells following acute ischemic stroke and their predicted gene targets.

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    BackgroundmicroRNA (miRNA) are important regulators of gene expression. In patients with ischemic stroke we have previously shown that differences in immune cell gene expression are present. In this study we sought to determine the miRNA that are differentially expressed in peripheral blood cells of patients with acute ischemic stroke and thus may regulate immune cell gene expression.MethodsmiRNA from peripheral blood cells of forty-eight patients with ischemic stroke and vascular risk factor controls were compared. Differentially expressed miRNA in patients with ischemic stroke were determined by microarray with qRT-PCR confirmation. The gene targets and pathways associated with ischemic stroke that may be regulated by the identified miRNA were characterized.ResultsIn patients with acute ischemic stroke, miR-122, miR-148a, let-7i, miR-19a, miR-320d, miR-4429 were decreased and miR-363, miR-487b were increased compared to vascular risk factor controls. These miRNA are predicted to regulate several genes in pathways previously identified by gene expression analyses, including toll-like receptor signaling, NF-κβ signaling, leukocyte extravasation signaling, and the prothrombin activation pathway.ConclusionsSeveral miRNA are differentially expressed in blood cells of patients with acute ischemic stroke. These miRNA may regulate leukocyte gene expression in ischemic stroke including pathways involved in immune activation, leukocyte extravasation and thrombosis

    Statistical modeling, parameter estimation and measurement planning for PV degradation

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    Photovoltaics (PV) degradation is a key consideration during PV performance evaluation. Accurately predicting power delivery over the course of lifetime of PV is vital to manufacturers and system owners. With many systems exceeding 20 years of operation worldwide, degradation rates have been reported abundantly in the recent years. PV degradation is a complex function of a variety of factors, including but not limited to climate, manufacturer, technology and installation skill. As a result, it is difficult to determine degradation rate by analytical modeling; it has to be measured. As one set of degradation measurements based on a single sample cannot represent the population nor be used to estimate the true degradation of a particular PV technology, repeated measures through multiple samples are essential. In this chapter, linear mixed effects model (LMM) is introduced to analyze longitudinal degradation data. The framework herein introduced aims to address three issues: 1) how to model the difference in degradation observed in PV modules/systems of a same technology that are installed at a shared location; 2) how to estimate the degradation rate and quantiles based on the data; and 3) how to effectively and efficiently plan degradation measurements
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