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251 results on '"TANG, Mingming"'

11. Induction of local immunosuppression in allogeneic cell transplantation by cell-type-specific expression of PD-L1 and CTLA4Ig

Author

Zhu, Wenliang, primary, Li, Mengqi, additional, Zou, Jun, additional, Zhang, Da, additional, Fang, Minghui, additional, Sun, Yun, additional, Li, Can, additional, Tang, Mingming, additional, Wang, Yukai, additional, Zhou, Qi, additional, Zhao, Tongbiao, additional, Li, Wei, additional, Hu, Zheng, additional, and Hu, Baoyang, additional

Published
2023
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15. A Seismic Inversion Method Based on Multi-Scale Super-Asymmetric Cycle-JNet Network.

Author

Tang, Mingming, Huang, Boyang, Xie, Rong, and Chen, Zhenzhen

Subjects
CONVOLUTIONAL neural networks, RECURRENT neural networks, WAVELETS (Mathematics), MACHINE learning, DEEP learning, WAVELET transforms
Abstract

In order to improve the resolution and accuracy of seismic inversion, this study constructs a multi-scale super-asymmetric network (Cycle-JNet). In this model, wavelet analysis is used to capture the multi-scale data characteristics of well-seismic data, thereby improving the machine's ability to learn details. Using the UNet neural network from Convolutional Neural Network (CNN), we modified the network structure by adding several convolution kernel layers at the output end to expand generated data, solving the problem of mismatched resolutions in well-seismic data, thus improving the resolution of seismic inversion and achieving the purpose of accurately identifying thin sandstone layers. Meanwhile, a cycle structure of Recurrent Neural Network (RNN) was designed for the secondary learning of the seismic data generated by JNet. By comparing the data transformed through inverse wavelet transform with the original data again, the accuracy of machine learning can be improved. After optimization, the Cycle-JNet model significantly outperforms traditional seismic inversion methods in terms of resolution and accuracy. This indicates that this method can provide more precise inversion results in more complex data environments, providing stronger support for seismic analysis. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Twin-Twin Transfusion Syndrome After Radiofrequency Ablation in Dizygotic Monochorionic Triamniotic Triplet Pregnancy With Sex Discordance: A Case Report

Author

Tang, Mingming, Tian, Xingbo, Luo, Jianglai, Zhang, Xiaohang, Ran, Suzhen, Xiong, Jiaojiao, Chen, Yanlin, and Chen, Gongli

Subjects
General Medicine
Abstract

BackgroundWe report a case of dizygotic monochorionic triamniotic triplet pregnancy. Twin-twin transfusion syndrome was subsequently diagnosed combined with sex discordance in the two surviving fetuses after one fetus was reduced, which is extremely rare and has not been previously reported.Case PresentationAfter reducing one fetus by radiofrequency ablation of a monochorionic triamniotic triplet pregnancy, twin-twin transfusion syndrome was subsequently diagnosed combined with sex discordance in the two surviving fetuses. Amniotic fluid for chromosome analysis showed normal karyotype 46, XY/46, XX of the donor and recipient fetus, and short tandem repeat (STR) analysis revealed dizygotic twins.ConclusionsThrough this is an unusual case, we aim to emphasize the importance of accurate diagnosis of chorionicity and zygosity in sex discordant triplet pregnancy, which is the key to appropriate clinical management.

Published
2022

36. A method of dynamic union control for intelligent mould bed system in ship block building.

Author

Wang, Zhen, Jing, Xuwen, Cai, Youhui, Liu, Jinfeng, Zhu, Tianhu, Zhou, Honggen, Tang, Mingming, Li, Lei, Li, Chunjin, and Dong, Lei

Subjects
INTELLIGENT buildings, INTELLIGENT control systems, PROCESS control equipment, ADAPTIVE control systems, FUZZY neural networks
Abstract

Mould bed is the most important equipment to control the deformation in the process of block construction. However, its height needs to be controlled separately based on the known height, and it affects the construction precision of block severely. Therefore, a dynamic union control method is proposed in this paper. Firstly, in order to realize the union control of mould bed system, the distribution types of mould bed system are defined, and a dynamic relationship is established, the determination algorithm number, position and height compensation layer number is proposed. Secondly, the fuzzy PID control based on neural network is used to realize the adaptive control of height according to the changes of pressure, so as to control the construction quality better of block. Thirdly, the MATLAB/Simulink module is used to verify the proposed method and shows that the response time is significantly shortened by 41% and 37.5% respectively. [ABSTRACT FROM AUTHOR]

Published
2022
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