M
Mingwei Chen
Researcher at Johns Hopkins University
Publications - 1108
Citations - 63568
Mingwei Chen is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 108, co-authored 536 publications receiving 51351 citations. Previous affiliations of Mingwei Chen include National Taiwan University & Chiba University.
Papers
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Experimental Constraints on the Fate of Subducted Sedimentary Nitrogen in the Reduced Mantle
Sheng Nan Huang,Xiangwei Wu,Stella Chariton,Vitali B. Prakapenka,Lin Liang,Dongzhou Zhang,Yan Yang,Mingwei Chen,Shan Qin +8 more
TL;DR: In this article , the stability of subducted sedimentary nitrogen in the reduced mantle was investigated to 35 GPa and 1600 K by laser-heated diamond anvil cell experiments and first-principles calculations.
Modeling Irradiation-Induced Degradation for 4H-SiC Power MOSFETs
Shiwei Liang,Yu Yang,Lei Shu,Ziyuan Wu,Mingwei Chen,Hengyu Yu,Han Guang Liu,Liang Wang,Tongde Li,Gaoqiang Deng,Jun Wang +10 more
TL;DR: In this article , a comprehensive model for predicting the degradation of SiC MOSFETs after gamma-ray irradiation was proposed, and the maximum prediction error is lower than 0.08 V, which proves the rationale and accuracy of the proposed degradation model.
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Flying Trot Control Method for Quadruped Robot Based on Trajectory Planning
TL;DR: In this paper , an intuitive control method for the walking trot of a quadruped robot, which combines trajectory planning with real-time balance control, is presented, and a posture control method based on a foot acceleration adjustment is proposed to improve the robustness of running.
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A Meroterpenoid from Tibetan Medicine Induces Lung Cancer Cells Apoptosis through ROS-Mediated Inactivation of the AKT Pathway
TL;DR: Wang et al. as mentioned in this paper isolated a meroterpenoid named D1399 from Meconopsis grandis prain endophytic fungi with strong antitumor activity, which can induce the apoptosis of lung cancer cells on the extrinsic and intrinsic pathways.
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Study on Artificial Neural Network for Predicting Gas-Liquid Two-Phase Pressure Drop in Pipeline-Riser System
TL;DR: In this paper , an ANN network with a hidden layer containing 14 neurons was developed based on a trial-and-error method to predict the pressure drop for air-water two-phase flow in pipeline systems with S-shaped and vertical risers at various inclinations.