625 research outputs found

    Finite element electromagnetic analysis of generator transient performance

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    Coolant side heat transfer with rotation. Task 3 report: Application of computational fluid dynamics

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    An experimental and analytical program was conducted to investigate heat transfer and pressure losses in rotating multipass passages with configurations and dimensions typical of modern turbine blades. The objective of this program is the development and verification of improved analysis methods that will form the basis for a design system that will produce turbine components with improved durability. As part of this overall program, a technique is developed for computational fluid dynamics. The specific objectives were to: select a baseline CFD computer code, assess the limitations of the baseline code, modify the baseline code for rotational effects, verify the modified code against benchmark experiments in the literature, and to identify shortcomings in the code as revealed by the verification. The Pratt and Whitney 3D-TEACH CFD code was selected as the vehicle for this program. The code was modified to account for rotating internal flows, and these modifications were evaluated for flow characteristics of those expected in the application. Results can make a useful contribution to blade internal cooling

    Efficient discriminative learning of parametric nearest neighbor classifiers

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    Linear SVMs are efficient in both training and testing, however the data in real applications is rarely linearly separable. Non-linear kernel SVMs are too computationally intensive for applications with large-scale data sets. Recently locally linear classifiers have gained popularity due to their efficiency whilst remaining competitive with kernel methods. The vanilla nearest neighbor algorithm is one of the simplest locally linear classifiers, but it lacks robustness due to the noise often present in real-world data. In this paper, we introduce a novel local classifier, Parametric Nearest Neighbor (P-NN) and its extension Ensemble of P-NN (EP-NN). We parameterize the nearest neighbor algorithm based on the minimum weighted squared Euclidean distances between the data points and the prototypes, where a prototype is represented by a locally linear combination of some data points. Meanwhile, our method attempts to jointly learn both the prototypes and the classifier parameters discriminatively via max-margin. This makes our classifiers suitable to approximate the classification decision boundaries locally based on nonlinear functions. During testing, the computational complexity of both classifiers is linear in the product of the dimension of data and the number of prototypes. Our classification results on MNIST, USPS, LETTER, and Chars 74K are comparable and in some cases are better than many other methods such as the state-of-the-art locally linear classifiers

    The effects of changes in the order of verbal labels and numerical values on children's scores on attitude and rating scales

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    Research with adults has shown that variations in verbal labels and numerical scale values on rating scales can affect the responses given. However, few studies have been conducted with children. The study aimed to examine potential differences in children’s responses to Likert-type rating scales according to their anchor points and scale direction, and to see whether or not such differences were stable over time. 130 British children, aged 9 to 11, completed six sets of Likert-type rating scales, presented in four different ways varying the position of positive labels and numerical values. The results showed, both initially and 8-12 weeks later, that presenting a positive label or a high score on the left of a scale led to significantly higher mean scores than did the other variations. These findings indicate that different arrangements of rating scales can produce different results which has clear implications for the administration of scales with children

    The selective phosphodiesterase 4 inhibitor roflumilast and phosphodiesterase 3/4 inhibitor pumafentrine reduce clinical score and TNF expression in experimental colitis in mice.

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    The specific inhibition of phosphodiesterase (PDE)4 and dual inhibition of PDE3 and PDE4 has been shown to decrease inflammation by suppression of pro-inflammatory cytokine synthesis. We examined the effect of roflumilast, a selective PDE4 inhibitor marketed for severe COPD, and the investigational compound pumafentrine, a dual PDE3/PDE4 inhibitor, in the preventive dextran sodium sulfate (DSS)-induced colitis model. The clinical score, colon length, histologic score and colon cytokine production from mice with DSS-induced colitis (3.5% DSS in drinking water for 11 days) receiving either roflumilast (1 or 5 mg/kg body weight/d p.o.) or pumafentrine (1.5 or 5 mg/kg/d p.o.) were determined and compared to vehicle treated control mice. In the pumafentrine-treated animals, splenocytes were analyzed for interferon-γ (IFNγ) production and CD69 expression. Roflumilast treatment resulted in dose-dependent improvements of clinical score (weight loss, stool consistency and bleeding), colon length, and local tumor necrosis factor-α (TNFα) production in the colonic tissue. These findings, however, were not associated with an improvement of the histologic score. Administration of pumafentrine at 5 mg/kg/d alleviated the clinical score, the colon length shortening, and local TNFα production. In vitro stimulated splenocytes after in vivo treatment with pumafentrine showed a significantly lower state of activation and production of IFNγ compared to no treatment in vivo. These series of experiments document the ameliorating effect of roflumilast and pumafentrine on the clinical score and TNF expression of experimental colitis in mice
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