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246 results on '"Wei, Minghui"'

24. Feature extraction method for ultrasonic pipeline defects based on fractional-order VMD.

Author

Wei, MingHui, Miao, Qi, and Jiang, LiXia

Abstract

Ensuring the safety of pipeline transportation is vital for societal well-being. Traditional methods for identifying defects in steel pipelines through ultrasonic echo signal pattern recognition often fail to extract comprehensive and effective features crucial for accurate defect detection. This study introduces an innovative feature extraction method employing a fractional Fourier transform variational modal decomposition (FRFT-VMD), hereafter referred to as the fractional-order VMD algorithm. This method utilises the fourth-order central moment and envelope entropy to optimise several key parameters: the fractional order in the Fourier transform, the number of decomposition layers, and the penalty factor in variational modal decomposition. To evaluate the effectiveness of the proposed method, ultrasonic echo signals from both finite element simulations and experimental platforms were analysed using the FRFT-VMD technique. The features extracted were then classified using a Least Squares Support Vector Machine (LSSVM) to determine defect depths. The results show a recognition accuracy of 95.2% in simulated signals and 89.1% in experimentally measured signals across various defect depths, indicating a significant improvement over existing feature extraction methodologies. The fractional-order VMD algorithm proves to be superior in extracting features that enhance the accuracy of defect identification in steel pipelines. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Autophagy regulates anti-angiogenic property of lenvatinib in thyroid cancer

Author

Xue, Lingbin, Gong, Zhongqin, Vlantis, Alexander C, Chan, Jason YK, Meehan, Katie, van Hasselt, Charles Andrew, Li, Dongcai, Zeng, Xianhai, Wei, Minghui, Tong, Michael CF, and Chen, George G

Subjects
Original Article
Abstract

We aimed to explore the role of lenvatinib-mediated autophagy in papillary thyroid cancer (PTC). K1 and BCPAP, were tested for cell viability, proliferation, and apoptosis after treatment with lenvatinib or chloroquine (CQ) or both. The levels of angiogenesis vascular endothelial growth factor A (VEGFA) were measured by ELISA. Transwell and wound-healing assays were performed using endothelial HUVECs cells. The dynamics of microvessels were detected by tubular formation assay. Western blotting was used to determine the expression of LC3-I/II and Atg-7 and alterations in the PI3K/Akt/mTOR and MEK/ERK pathways. In vivo tumor growth assay and immunohistochemical staining (IHC) was also performed. The results showed that lenvatinib inhibited the viability of K1 and BCPAP cells and caused apoptosis. We further showed that lenvatinib also upregulated autophagy levels in thyroid cancer cells in a dose-dependent manner through the PI3K/Akt/mTOR and MEK/ERK pathways. Co-administration of lenvatinib with CQ resulted in a greater decrease of VEGFA in the tumor supernatant than with either lenvatinib or CQ alone. Autophagy inhibition enhanced the cytotoxicity and anti-angiogenic ability of lenvatinib, which was supported by the HUVECs migration, wound healing, and tube formation assays. Inhibiting autophagy chemically or genetically enhanced lenvatinib’s cytotoxic effects and anti-angiogenic efficacy in thyroid cancer cells in vitro and in vivo. In conclusion, lenvatinib inhibited cell viability and induced apoptosis and autophagy in human PTC cells. Significantly, the combination of lenvatinib and autophagy inhibition may represent a novel and effective treatment option for PTC, which may be able to overcome drug resistance.

Published
2023

43. Research on Rolling Bearing Fault Diagnosis Method Based on Harmonic Noise Kurtosis-Time Characteristic Blind Deconvolution

Author

Yang, Jianwei, Sun, Runtao, Yao, Dechen, Wang, Jinhai, and Wei, Minghui

Abstract

Blind deconvolution filtering methods are a widely employed technique in the domain of mechanical fault diagnosis. However, they are frequently susceptible to interference signals, which have a considerable impact on their accuracy and stability. In light of the aforementioned limitations, this article introduces a novel blind deconvolution method, designated as harmonic noise kurtosis-time characteristic blind deconvolution (HTBD). This method comprises two principal components: The harmonic noise kurtosis (HNK) and time characteristic energy ratio (TCER) are two key components. HNK serves as an objective function in blind deconvolution, addressing both the joint periodicity and sparsity of the signal. The objective function is enhanced in terms of precision and stability through the incorporation of TCER, which facilitates the identification of fault periods and improves the effectiveness of the blind deconvolution process. Subsequently, we propose a blind deconvolution filtering method utilizing an iterative algorithm. Simulation and comparative experiments demonstrate that HTBD exhibits superior robustness against various interference signals and offers distinct advantages in terms of convergence speed and stability.

Published
2024
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