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  • Open Access

    ARTICLE

    Expression Changes, Prognostic Analysis and Risk Factors of miR-625-3p and miR-449a in Osteosarcoma Patients after Surgery

    Hui Zhang, Zhan Wang, Lin Liu, Fuqiang Zhang, Yuxin Song, Yaowen Qian*

    Oncologie, Vol.22, No.1, pp. 23-33, 2020, DOI:10.32604/oncologie.2020.012493

    Abstract The expression changes of miR-625-3p and miR-449a in osteosarcoma patients after surgery is the critical study in this paper. Analysis of their prognosis and risk factors can be helpful in understanding the prognostic value for clinical purposes. Fifty-eight patients with osteosarcoma diagnosed in our hospital were considered as the research group (RG), and 52 health subjects at the same time were collected as the control group (CG). Fluorescence quantitative PCR (RTPCR) was employed to test the expression levels of miR-625-3p and miR-449a in the serum of subjects in both groups before surgery and patients in the RG after surgery. The… More >

  • Open Access

    ARTICLE

    Ensemble Recurrent Neural Network-Based Residual Useful Life Prognostics of Aircraft Engines

    Jun Wu1,*, Kui Hu1, Yiwei Cheng2, Ji Wang1, Chao Deng2,*, Yuanhan Wang3

    Structural Durability & Health Monitoring, Vol.13, No.3, pp. 317-329, 2019, DOI:10.32604/sdhm.2019.05571

    Abstract Residual useful life (RUL) prediction is a key issue for improving efficiency of aircraft engines and reducing their maintenance cost. Owing to various failure mechanism and operating environment, the application of classical models in RUL prediction of aircraft engines is fairly difficult. In this study, a novel RUL prognostics method based on using ensemble recurrent neural network to process massive sensor data is proposed. First of all, sensor data obtained from the aircraft engines are preprocessed to eliminate singular values, reduce random fluctuation and preserve degradation trend of the raw sensor data. Secondly, three kinds of recurrent neural networks (RNN),… More >

  • Open Access

    ARTICLE

    The Use of High-Performance Fatigue Mechanics and the Extended Kalman / Particle Filters, for Diagnostics and Prognostics of Aircraft Structures

    Hai-Kun Wang1,2, Robert Haynes3, Hong-Zhong Huang1, Leiting Dong2,4, Satya N. Atluri2

    CMES-Computer Modeling in Engineering & Sciences, Vol.105, No.1, pp. 1-24, 2015, DOI:10.3970/cmes.2015.105.001

    Abstract In this paper, we propose an approach for diagnostics and prognostics of damaged aircraft structures, by combing high-performance fatigue mechanics with filtering theories. Fast & accurate deterministic analyses of fatigue crack propagations are carried out, by using the Finite Element Alternating Method (FEAM) for computing SIFs, and by using the newly developed Moving Least Squares (MLS) law for computing fatigue crack growth rates. Such algorithms for simulating fatigue crack propagations are embedded in the computer program Safe- Flaw, which is called upon as a subroutine within the probabilistic framework of filter theories. Both the extended Kalman as well as particle… More >

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