光动力作用促人肝癌细胞HepG2凋亡及对bax，bcl-2蛋白表达的影响

应用流式细胞仪分析光动力作用后细胞凋亡及免疫组化染色检测凋亡相关蛋白bcl-2蛋白，bax蛋白表达水平．发现血卟啉光动力实验组人肝癌细胞HepG2凋亡率达24．23±1．86％，与对照组相比，差异非常显著（P〈0．01）；光动力作用后凋亡相关蛋白bcl-2表达显著高于对照组（P〈0．05）；实验结果显示血卟啉光动力作用具有诱导人肝癌细胞HepG2凋亡的生物学效应，而凋亡调控蛋白bcl-2表达水平的降低可能是血叶林光动力作用诱导人肝癌细胞HepG2凋亡的一个重要机制．     

生物细胞X射线成像

许多生物细胞非常小，无法用光学显微镜进行研究．而X射线衍射和电子显微镜技术不适于对活细胞的研究．2000年生物物理学家Janos Hajdu提出了一种新的活细胞及微小生物粒子成像方法，这种方法使用极强的超短X射线激光脉冲产生的衍射图案来成像．     

Chalcogenide Random Access Memory Cell with Structure of W Sub-Microtube Heater Electrode

In order to reduce the reset current of cllalcogenide random access memory; a W sub-microtube heater electrode with outer/inner diameter of 260/100nm, which was fabricated with standard 0.184-μm technology, is proposed for the first time to achieve a reset current of about 0.5 mA. The reasons may be that sub-microtube increases the number of electrode edge and thermal efficiency is improved greatly because the thermal density on the edge of sub-microtube electrode is generally the highest.     

量子细胞神经网络超混沌系统同步及在保密通信中的应用

研究了六阶量子细胞神经网络超混沌系统的同步方法,提出了一种基于量子细胞神经网络超混沌同步系统的保密通信系统,应用MATLAB对六阶量子细胞神经网络超混沌系统进行了数值模拟,结果证明利用线性反馈法可实现该高维系统的混沌同步,利用混沌掩盖可实现保密通信.     

基于多种敏感膜的多参数细胞微生理计研究

基于对多种离子敏感膜的研究，结合微透镜阵列，设计了一种基于光寻址电位传感器（LAPS）的新型多参数微生理计，实现同时并行检测H^＋，Na^＋，K^＋，Ca^2＋等多种不同离子。已经测得H^＋，K^＋，Ca^2＋ -敏LAPS的灵敏度分别达到50mV/pH，43mV/pK以及25mV/pCa，线性度良好。     

单电子晶体管及其在细胞神经网络中的应用

研究了单电子晶体管的特性及主方程法,建立了基于主方程法的单电子晶体管SPICE模型,实现了对细胞神经网络单元的仿真。仿真结果表明,采用主方程法建立的单电子晶体管模型具有合理的精确度,对细胞神经网络单元的实现具有速度快、低功耗的优点,适合复杂细胞神经网络的进一步构建。     

One-way hash function based on hyper-chaotic cellular neural network

The design of an efficient one-way hash function with good performance is a hot spot in modern cryptography researches. In this paper, a hash function construction method based on cell neural network with hyper-chaos characteristics is proposed. First, the chaos sequence is gotten by iterating cellular neural network with Runge Kutta algorithm, and then the chaos sequence is iterated with the message. The hash code is obtained through the corre- sponding transform of the latter chaos sequence. Simulation and analysis demonstrate that the new method has the merit of convenience, high sensitivity to initial values, good hash performance, especially the strong stability.     

Exponential stability of cellular neural networks with multiple time delays and impulsive effects

In this work, the stability issues of the equilibrium points of the cellular neural networks with multiple time delays and impulsive effects are investigated. Based on the stability theory of Lyapunov-Krasovskii, the method of linear matrix inequality （LMI） and parametrized first-order model transformation, several novel conditions guaranteeing the delaydependent and the delay-independent exponential stabilities are obtained. A numerical example is given to illustrate the effectiveness of our results.