In this paper,the small-signal modeling of the Indium Phosphide High Electron Mobility Transistor(InP HEMT)based on the Transformer neural network model is investigated.The AC S-parameters of the HEMT device are train...In this paper,the small-signal modeling of the Indium Phosphide High Electron Mobility Transistor(InP HEMT)based on the Transformer neural network model is investigated.The AC S-parameters of the HEMT device are trained and validated using the Transformer model.In the proposed model,the eight-layer transformer encoders are connected in series and the encoder layer of each Transformer consists of the multi-head attention layer and the feed-forward neural network layer.The experimental results show that the measured and modeled S-parameters of the HEMT device match well in the frequency range of 0.5-40 GHz,with the errors versus frequency less than 1%.Compared with other models,good accuracy can be achieved to verify the effectiveness of the proposed model.展开更多
Dichloromethane(DCM)dehalogenase stands as a crucial enzyme implicated in the degradation of methylene chloride across diverse environmental and biological contexts.However,the unbinding pathways of ligands from DCM d...Dichloromethane(DCM)dehalogenase stands as a crucial enzyme implicated in the degradation of methylene chloride across diverse environmental and biological contexts.However,the unbinding pathways of ligands from DCM dehalogenase remain unexplored.In order to gain a deeper understanding of the binding sites and dissociation pathways of dichloromethane(DCM)and glutathione(GSH)from the DCM dehalogenase,random accelerated molecular dynamics(RAMD)simulations were performed,in which DCM and GSH were forced to leave the active site.The protein structure was predicted using Alphafold2,and the conformations of GSH and DCM in the binding pocket were predicted by docking.A long equilibrium simulation was conducted to validate the structure of the complex.The results show that GSH is most commonly observed in three main pathways,one of which is more important than the other two.In addition,DCM was observed to escape along a unique pathway.The key residues and protein helices of each pathway were identified.The results can provide a theoretical foundation for the subsequent dissociation mechanism of DCM dehalogenase.展开更多
基金Supported by the National Natural Science Foundation of China(62201293,62034003)the Open-Foundation of State Key Laboratory of Millimeter-Waves(K202313)the Jiangsu Province Youth Science and Technology Talent Support Project(JSTJ-2024-040)。
文摘In this paper,the small-signal modeling of the Indium Phosphide High Electron Mobility Transistor(InP HEMT)based on the Transformer neural network model is investigated.The AC S-parameters of the HEMT device are trained and validated using the Transformer model.In the proposed model,the eight-layer transformer encoders are connected in series and the encoder layer of each Transformer consists of the multi-head attention layer and the feed-forward neural network layer.The experimental results show that the measured and modeled S-parameters of the HEMT device match well in the frequency range of 0.5-40 GHz,with the errors versus frequency less than 1%.Compared with other models,good accuracy can be achieved to verify the effectiveness of the proposed model.
基金National Natural Science Foundation of China(22073030)the Oriental Scholars of Shanghai Universities。
文摘Dichloromethane(DCM)dehalogenase stands as a crucial enzyme implicated in the degradation of methylene chloride across diverse environmental and biological contexts.However,the unbinding pathways of ligands from DCM dehalogenase remain unexplored.In order to gain a deeper understanding of the binding sites and dissociation pathways of dichloromethane(DCM)and glutathione(GSH)from the DCM dehalogenase,random accelerated molecular dynamics(RAMD)simulations were performed,in which DCM and GSH were forced to leave the active site.The protein structure was predicted using Alphafold2,and the conformations of GSH and DCM in the binding pocket were predicted by docking.A long equilibrium simulation was conducted to validate the structure of the complex.The results show that GSH is most commonly observed in three main pathways,one of which is more important than the other two.In addition,DCM was observed to escape along a unique pathway.The key residues and protein helices of each pathway were identified.The results can provide a theoretical foundation for the subsequent dissociation mechanism of DCM dehalogenase.
