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您的检索式：作者名="CUI ChunLiang"
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| 1 | Amplification of terahertz/infrared field at the nodes of Ranvier for myelinated nerve显示文摘The myelination of axons was the last major evolution in the vertebrate nervous system.Myelin promotes the speed of action potential by two orders,and modulates the conduction of neurons,important for learning new skills.However,the intrinsic mechanism for high-speed information propagation in myelin in the nervous systems is still unclear.We propose that myelinated nerve fibres serve as dielectric waveguides for the high-frequency electromagnetic information in a certain mid-infrared to terahertz spectral range.Based on the structure characteristics of myelinated nerve composed of periodic nodes of Ranvier and myelin sheath,the energy for the signal propagation is supplied and amplified when crossing the nodes of Ranvier via a periodic relay.In this work,we exploit the quasi-quantum model of amplification for neural terahertz/infrared information at the nodes of Ranvier,and prove the existence of biomolecular ensemble for three-energy-level amplification,revealing the essential mechanism of high-speed electromagnetic information transmitting in myelinated nerves. | YanSheng Liu KaiJie Wu ChunLiang Liu GangQiang Cui Chao Chang GuoZhi Liu | 2020 | Science China(Physics,Mechanics & Astronomy)2020，63，7： | 3 |
| 2 | Modeling of daily pan evaporation using partial least squares regression显示文摘This study presented the application of partial least squares regression (PLSR) in estimating daily pan evaporation by utilizing the unique feature of PLSR in eliminating collinearity issues in predictor variables. The climate variables and daily pan evaporation data measured at two weather stations located near Elephant Butte Reservoir,New Mexico,USA and a weather station located in Shanshan County,Xinjiang,China were used in the study. The nonlinear relationship between climate variables and daily pan evaporation was successfully modeled using PLSR approach by solving collinearity that exists in the climate variables. The modeling results were compared to artificial neural networks (ANN) models with the same input variables. The results showed that the nonlinear equations developed using PLSR has similar performance with complex ANN approach for the study sites. The modeling process was straightforward and the equations were simpler and more explicit than the ANN black-box models. | ABUDU Shalamu CUI ChunLiang J. Phillip KING Jimmy MORENO A. Salim BAWAZIR | 2011 | Science China(Technological Sciences)2011，54，1： | 0 |
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