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| 1 | Computer simulation studies on the interactions between nanoparticles and cell membrane显示文摘In recent times,nanoparticles(NPs)have received intense attention not only due to their potential applications as a candidate for drug delivery,but also because of their undesirable effects on human health.Although extensive experimental studies have been carried out in literature in order to understand the interaction between NPs and a plasma membrane,much less is known about the molecular details of the interaction mechanisms and pathways.As complimentary tools,coarse grained molecular dynamics(CGMD)and dissipative particle dynamics(DPD)simulations have been extensively used on the interaction mechanism and evolution pathway.In the present review we summarize computer simulation studies on the NP-membrane interaction,which developed over the last few years,and particularly evaluate the results from the DPD technique.Those studies undoubtedly deepen our understanding of the NP-membrane interaction mechanisms and provide a design guideline for new NPs. | TIAN Fa Lin YUE Tong Tao LI Ye ZHANG Xian Ren | 2014 | Science China Chemistry2014，57，12： | 2 |
| 2 | 带延迟调整的脉冲神经元梯度下降学习算法显示文摘脉冲神经元有监督学习算法通过梯度下降法调整神经元的突触权值,但目标学习序列长度的增加会降低其精度并延长学习周期。为此,提出一种带延迟调整的梯度下降学习算法。将每个突触的延迟作为学习参数,在学习过程中调整权值,同时对突触的延迟时间进行梯度下降调整,从而使神经元激发出目标脉冲序列。实验结果表明,该算法在不增加算法复杂度的情况下,能够提高神经元学习复杂脉冲序列的能力,且收敛速度较快。 | 杨静 徐彦 赵欣 | 2019 | 计算机工程2019，45，9： | 1 |
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