3 research outputs found

    FPGA-based Degradation Evaluation for Traction Power Module with Deep Recurrent Autoencoder

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    The timely and quantitative evaluation of the degradation is crucial for traction inverter systems in railway applications. The implementation in the industry is impeded by two major challenges including the varying operational profiles and the scalability for system-level applications. This paper proposes a deep recurrent autoencoder-based degradation evaluation method, to assess the degradation level of the traction power module online. The recurrent structure is embedded for processing multivariate time series condition monitoring data stream, in order to exploit the inherent time dependence to improve the accuracy and robustness. The autoencoder-based framework enables the scalability of the proposed method to system-level applications and can be applied under varying operating conditions. The method is experimentally demonstrated on an FPGA-based hardware platform.</p

    An atlas of DNA methylomes in porcine adipose and muscle tissues

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    It is evident that epigenetic factors, especially DNA methylation, have essential roles in obesity development. Here, using pig as a model, we investigate the systematic association between DNA methylation and obesity. We sample eight variant adipose and two distinct skeletal muscle tissues from three pig breeds living within comparable environments but displaying distinct fat level. We generate 1,381 Gb of sequence data from 180 methylated DNA immunoprecipitation libraries, and provide a genome-wide DNA methylation map as well as a gene expression map for adipose and muscle studies. The analysis shows global similarity and difference among breeds, sexes and anatomic locations, and identifies the differentially methylated regions. The differentially methylated regions in promoters are highly associated with obesity development via expression repression of both known obesity-related genes and novel genes. This comprehensive map provides a solid basis for exploring epigenetic mechanisms of adipose deposition and muscle growth
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