64,998 research outputs found

    Effect of solute atoms on dislocation motion in Mg: an electronic structure perspective.

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    Solution strengthening is a well-known approach to tailoring the mechanical properties of structural alloys. Ultimately, the properties of the dislocation/solute interaction are rooted in the electronic structure of the alloy. Accordingly, we compute the electronic structure associated with, and the energy barriers to dislocation cross-slip. The energy barriers so obtained can be used in the development of multiscale models for dislocation mediated plasticity. The computed electronic structure can be used to identify substitutional solutes likely to interact strongly with the dislocation. Using the example of a-type screw dislocations in Mg, we compute accurately the Peierls barrier to prismatic plane slip and argue that Y, Ca, Ti, and Zr should interact strongly with the studied dislocation, and thereby decrease the dislocation slip anisotropy in the alloy

    Methodology for tidal turbine representation in ocean circulation model

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    The present method proposes the use and adaptation of ocean circulation models as an assessment tool framework for tidal current turbine (TCT) array layout optimization. By adapting both momentum and turbulence transport equations of an existing model, the present TCT representation method is proposed to extend the actuator disc concept to 3-D large-scale ocean circulation models. Through the reproduction of experimental flume tests and grid dependency tests, this method has shown its numerical coherence as well as its ability to simulate accurately both momentum and turbulent turbine-induced perturbations in both near and far wakes in a relatively short period of computation time. Consequently the present TCT representation method is a very promising basis for the development of a TCT array layout optimization tool

    The noise policy statement for England : significance, application and implications

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    The Noise Policy Statement for England, published by Defra in March 2010, describes a ‘policy vision to facilitate decisions regarding what is an acceptable noise burden to place on society’. The publication of the NPSE coincided with the formal adoption and publication of the Noise Action Plans as required by the Environmental Noise (England) Regulations 2006 (as amended) and the Environmental Noise Directive . However, the potential implications of the NPSE go much wider, and as this article shows, it may well turn out to have a considerable impact on the work of many members of the Institute of Acoustics

    Radio Band Observations of Blazar Variability

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    The properties of blazar variability in the radio band are studied using the unique combination of temporal resolution from single dish monitoring and spatial resolution from VLBA imaging; such measurements, now available in all four Stokes parameters, together with theoretical simulations, identify the origin of radio band variability and probe the characteristics of the radio jet where the broadband blazar emission originates. Outbursts in total flux density and linear polarization in the optical-to-radio bands are attributed to shocks propagating within the jet spine, in part based on limited modeling invoking transverse shocks; new radiative transfer simulations allowing for shocks at arbitrary angle to the flow direction confirm this picture by reproducing the observed centimeter-band variations observed more generally, and are of current interest since these shocks may play a role in the gamma-ray flaring detected by Fermi. Recent UMRAO multifrequency Stokes V studies of bright blazars identify the spectral variability properties of circular polarization for the first time and demonstrate that polarity flips are relatively common. All-Stokes data are consistent with the production of circular polarization by linear-to-circular mode conversion in a region that is at least partially self-absorbed. Detailed analysis of single-epoch, multifrequency, all-Stokes VLBA observations of 3C 279 support this physical picture and are best explained by emission from an electron-proton plasma.Comment: 6 pages, 5 figures, uses, jaa.sty. Invited talk presented at the conference Multifrequency Variability of Blazars, Guangzhou, China, September 22-24, 2010. To appear in J. Astrophys. Ast

    Versican splice variant messenger RNA expression in normal human Achilles tendon and tendinopathies

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    Versican is the principal large proteoglycan expressed in mid-tendon, but its role in tendon pathology is unknown. Our objective was to define the expression of versican isoform splice variant messenger ribonucleic acid (mRNA) in normal Achilles tendons, in chronic painful tendinopathy and in ruptured tendons. Total RNA isolated from frozen tendon samples (normal n = 14; chronic painful tendinopathy n = 10; ruptured n = 8) was assayed by relative quantitative reverse transcriptase polymerase chain reaction (RT-PCR) for total versican, versican variants V0, V1, V2, V3 and type I collagen a1 mRNA, normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Differences between sample groups were tested by Wilcoxon statistics. Painful and ruptured tendons showed a significant decrease (median 2-fold) in the expression of versican mRNA, in contrast to an increased expression (median 8-fold) of type I collagen a1 mRNA in painful tendons. Versican splice variants V0 and V1 mRNA were readily detected in normal samples, V3 levels were substantially lower, and V2 levels were more variable. Each of V1, V2 and V3 mRNA showed significant decreases in expression in painful and ruptured tendons, but V0 was not significantly changed. Changes in versican expression relative to that of collagen, and alterations in the balance of versican splice variants, may contribute to changes in matrix structure and function in tendinopathies

    Preoperative systemic inflammation predicts postoperative infectious complications in patients undergoing curative resection for colorectal cancer

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    The presence of systemic inflammation before surgery, as evidenced by the glasgow prognostic score (mGPS), predicts poor long-term survival in colorectal cancer. The aim was to examine the relationship between the preoperative mGPS and the development of postoperative complications in patients undergoing potentially curative resection for colorectal cancer. Patients (n=455) who underwent potentially curative resections between 2003 and 2007 were assessed consecutively, and details were recorded in a database. The majority of patients presented for elective surgery (85%) were over the age of 65 years (70%), were male (58%), were deprived (53%), and had TNM stage I/II disease (61%), had preoperative haemoglobin (56%), white cell count (87%) and mGPS 0 (58%) in the normal range. After surgery, 86 (19%) patients developed a postoperative complication; 70 (81%) of which were infectious complications. On multivariate analysis, peritoneal soiling (P<0.01), elevated preoperative white cell count (P<0.05) and mGPS (P<0.01) were independently associated with increased risk of developing a postoperative infection. In elective patients, only the mGPS (OR=1.75, 95% CI=1.17-2.63, P=0.007) was significantly associated with increased risk of developing a postoperative infection. Preoperative elevated mGPS predicts increased postoperative infectious complications in patients undergoing potentially curative resection for colorectal cancer

    Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification

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    This paper explores the problem of breast tissue classification of microscopy images. Based on the predominant cancer type the goal is to classify images into four categories of normal, benign, in situ carcinoma, and invasive carcinoma. Given a suitable training dataset, we utilize deep learning techniques to address the classification problem. Due to the large size of each image in the training dataset, we propose a patch-based technique which consists of two consecutive convolutional neural networks. The first "patch-wise" network acts as an auto-encoder that extracts the most salient features of image patches while the second "image-wise" network performs classification of the whole image. The first network is pre-trained and aimed at extracting local information while the second network obtains global information of an input image. We trained the networks using the ICIAR 2018 grand challenge on BreAst Cancer Histology (BACH) dataset. The proposed method yields 95 % accuracy on the validation set compared to previously reported 77 % accuracy rates in the literature. Our code is publicly available at https://github.com/ImagingLab/ICIAR2018Comment: 10 pages, 5 figures, ICIAR 2018 conferenc
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