基于元胞自动机的无线传感网络整体行为研究

探讨自组织通信网络中局部行为与系统整体行为的关联, 对于相关系统的设计和控制具有重要应用价值. 利用二维元胞自动机模型对无线传感网络的拓扑控制过程进行模拟, 可以分析节点间局部交互作用规则对网络整体行为的影响. 研究表明, 在不同的局部演化规则作用下, 该系统呈现出复杂的时空演化现象, 发现系统整体行为空间中存在振荡、衰减、稳定等基本模式, 并且该模型可以反映系统内不同全局目标之间的折中关系, 为进一步研究无线传感网络整体行为的控制问题提供一种新的途径. 关键词： 自组织 元胞自动机 通信网络 无线传感网络     

一维元胞自动机随机交通流模型的宏观方程分析

在一维局部作用元胞自动机交通流模型中引入刹车噪声与产生、消失概率,得到一完全随机的元胞自动机交通流模型.利用玻耳兹曼近似,建立了该模型的宏观动力学方程,并对宏观方程在特殊条件下的解进行了理论分析和计算机模拟. 关键词： 元胞自动机 交通流 Burgers方程 激波     

纯物质枝晶凝固的元胞自动机模型

采用元胞自动机模型模拟了纯物质凝固微观组织演化行为. 与以往采用KGT模型简化考虑不同,采用界面能量守恒方程来自洽地确定液固界面的生长动力学,考察了模型的网格尺寸相关性和时间相关性,并对模型的稳定性进行了验证. 采用这个模型模拟了纯丁二腈在过冷熔体中的自由枝晶生长,并与Glicksman的等温枝晶生长实验(isothermal dendritic growth experiment,IDGE)和LM-K临界稳定性原理进行了对比. 模拟的形貌再现了实验形貌的特征,并且特征参数与理论结果及实验结果符合得很好. 关键词： 元胞自动机 界面 凝固 临界稳定性原理     

一个新的用于元胞自动机模拟微观组织的溶质分配模型及其计算验证

在已有的几种溶质再分配计算模型的基础上, 建立了一个新的更为合理的溶质再分配模型.该模型充分考虑了枝晶生长过程中可能出现的固/液界面元胞的各种状态及其邻居元胞的各种状态, 根据这两者的不同状态, 分别建立不同的计算公式展开计算. 利用所建立的模型消除了原有的扩散控制的元胞自动机(CA)生长模型存在的在晶界处元胞不凝固的缺陷. 接着, 为了进一步验证模型的可靠性, 在Kurz-Giovanola-Trivedi方法控制的CA生长模型中引入新的溶质再分配计算模型, 对Al-4.7 wt%Cu 合金铸锭进行了模拟计算, 并与实验结果进行了金相组织和成分分布两方面的对比, 表明新模型具有较好的精确性. 关键词： 元胞自动机方法 微观组织模拟 溶质再分配     

基于一维元胞自动机的复杂网络恶意软件传播研究

基于一维元胞自动机,研究复杂网络恶意软件传播行为.利用信息网络节点全局交互的特点,建立元胞自动机邻域和状态转换函数,提出恶意软件传播模型,研究在多种网络拓扑下恶意软件传播的概率行为.研究表明,该模型能够准确描述在最近邻耦合网络（nearest-neighbor coupled network, NC）,Erdos-Renyi（ER）随机网络,Watts-Strogatz（WS） 小世界网络和Barabasi-Albert（BA）幂率网络等拓扑下的传播动力学行为,不仅能反映恶意软件传播的平均趋势,而且可以描述病毒消亡和渗透等稀有概率事件,有效克服基于平均场方法建立的微分方程模型只能反映传播的平均趋势,只适合对传播作整体预测的局限性.同时,研究指出网络中度分布的异质化程度和网络的局域空间交互特征是影响传播及免疫行为的关键要素. 关键词： 复杂网络 恶意软件传播 元胞自动机 状态转换函数     

一种改进的多速双向行人流元胞自动机模型

考虑行人的位置交换、侧向前进和后退行为,建立了一种改进的元胞自动机模型,用于研究地下通道中具有多种运动速度的双向行人流.将改进的元胞自动机模型与Weng的模型进行了比较.计算机模拟表明,改进的模型具有提高系统中行人的平均速度并降低行人占据密度的倾向. 关键词： 双向行人流 元胞自动机 计算机模拟     

一种考虑速度随机慢化概率动态演化的交通流元胞自动机模型

在NS模型的基础上,利用司机的记忆效应和当前交通环境动态地调整随机慢化概率,从而得到一个改进的交通流元胞自动机模型.数值实验表明,该模型可以很好地刻画司机记忆效应对交通流的影响,记忆效应的引入可以提高平均速度和流量. 关键词： 交通流 元胞自动机模型 记忆效应 随机慢化概率     

复合元胞自动机系统反向迭代加密技术研究

提出了元胞自动机的交叉复合在序列R下随机复合的思想,分析了复合元胞自动机系统的密码学特性,利用元胞自动机反向迭代加密技术,构造了两个基于复合元胞自动机的密码系统.新的复合元胞自动机密码系统很好地解决了单一元胞自动机密码系统中存在的误差单向扩散的问题,并且能够以较小的规则半径获得大密钥空间.计算机仿真结果表明,复合元胞自动机密码系统具有良好的扰乱和扩散性能,能够有效地抵抗蛮力攻击和差分分析. 关键词： 离散动力系统 复合元胞自动机 反向迭代 分组密码     

一种基于元胞自动机的自适应网络病毒传播模型

自适应网络是节点动力学和网络动力学相互作用和反馈的演化网络. 基于元胞自动机建立自适应网络中易感-感染-易感(susceptible-infected-susceptible)的病毒传播模型,研究节点为了规避病毒传播所采取的多种网络重连规则对病毒传播及网络统计特征的影响. 结果表明:自适应网络中的重连规则可以有效减缓病毒传播速度,降低病毒传播规模;随机重连规则使得网络统计特征趋于随机网络;基于元胞自动机建立的传播模型清晰地表达了病毒在传播过程中的双稳态现象. 关键词： 自适应网络 传播动力学 网络动力学 元胞自动机     

双出口房间内疏散行人流的仿真和实验研究

为研究行人疏散过程中的路径选择行为, 提出了一个基于元胞自动机的行人微观模型, 并组织了三组双出口教室内的学生疏散实验. 模型中, 行人路径选择行为受其到出口距离、前方路径通行能力和行人间排斥力影响. 通过观察实验结果, 得到一些相关现象. 利用实验结果对模型参数进行校正. 利用校正模型对该教室内疏散学生流进行仿真, 结果表明 模型能有效地刻画教室内学生流的疏散特征, 疏散时间随学生人数线性增加. 该研究有助于类似场景中行人疏散策略和方案的制定. 关键词： 元胞自动机 行人疏散 仿真 实验     

Biophysical model for high-throughput tumor and epithelial cell co-culture in complex biochemical microenvironments

The in vivo tumor microenvironment is a complex niche that includes heterogeneous physical structures,unique biochemical gradients and multiple cell interactions.Its high-fidelity in vitro reconstruction is of fundamental importance to improve current understandings of cell behavior,efficacy predictions and drug safety.In this study,we have developed a high-throughput biochip with hundreds of composite extracellular matrix(ECM)microchambers to co-culture invasive breast cancer cells(MDA-MB-231-RFP)and normal breast epithelial cells(MCF-10 A-GFP).The composite ECM is composed of type I collagen and Matrigel which provides a heterogeneous microenvironment that is similar to that of in vivo cell growth.Additionally,the growth factors and drug gradients that involve human epidermal growth factor(EGF),discoidin domain receptor 1(DDR1)inhibitor 7 rh and matrix metalloproteinase inhibitor batimastat allow for the mimicking of the complex in vivo biochemical microenvironment to investigate their effect on the spatial-temporal dynamics of cell growth.Our results demonstrate that the MDA-MB-231-RFP cells and MCF-10 A-GFP cells exhibit different spatial proliferation behaviors under the combination of growth factors and drugs.Basing on the experimental data,we have also developed a cellular automata(CA)model that incorporated drug diffusion to describe the experimental phenomenon,as well as employed Shannon entropy(SE)to explore the effect of the drug diffusion coefficient on the spatial-temporal dynamics of cell growth.The results indicate that the uniform cell growth is related to the drug diffusion coefficient,which reveals that the pore size of the ECM plays a key role in the formation of complex biochemical gradients.Therefore,our integrated,biomimetic and high-throughput co-culture platforms,as well as the computational model can be used as an effective tool for investigating cancer pathogenesis and drug development.     

Dynamics and pattern formation in invasive tumor growth

We study the in vitro dynamics of the malignant brain tumor glioblastoma multiforme. The growing tumor consists of a dense proliferating zone and an outer less dense invasive region. Experiments with different types of cells show qualitatively different behavior: one cell line invades in a spherically symmetric manner, but another gives rise to branches. We formulate a model for this sort of growth using two coupled reaction-diffusion equations for the cell and nutrient concentrations. When the ratio of the nutrient and cell diffusion coefficients exceeds some critical value, the plane propagating front becomes unstable with respect to transversal perturbations. The instability threshold and the full phase-plane diagram in the parameter space are determined. The results are in a qualitative agreement with experimental findings for the two types of cells.     

In vitro three-dimensional cancer metastasis modeling:Past,present, and future

Metastasis is the leading cause of most cancer deaths, as opposed to dysregulated cell growth of the primary tumor.Molecular mechanisms of metastasis have been studied for decades and the findings have evolved our understanding of the progression of malignancy. However, most of the molecular mechanisms fail to address the causes of cancer and its evolutionary origin, demonstrating an inability to find a solution for complete cure of cancer. After being a neglected area of tumor biology for quite some time, recently several studies have focused on the impact of the tumor microenvironment on cancer growth. The importance of the tumor microenvironment is gradually gaining attention, particularly from the perspective of biophysics. In vitro three-dimensional(3-D) metastatic models are an indispensable platform for investigating the tumor microenvironment, as they mimic the in vivo tumor tissue. In 3-D metastatic in vitro models, static factors such as the mechanical properties, biochemical factors, as well as dynamic factors such as cell–cell, cell–ECM interactions, and fluid shear stress can be studied quantitatively. With increasing focus on basic cancer research and drug development, the in vitro 3-D models offer unique advantages in fundamental and clinical biomedical studies.     

Finite-temperature collective dynamics of a Fermi gas in the BEC-BCS crossover

We report on experimental studies on the collective behavior of a strongly interacting Fermi gas with tunable interactions and variable temperature. A scissors mode excitation in an elliptical trap is used to characterize the dynamics of the quantum gas in terms of hydrodynamic or near-collisionless behavior. We obtain a crossover phase diagram for collisional properties, showing a large region where a nonsuperfluid strongly interacting gas shows hydrodynamic behavior. In a narrow interaction regime on the BCS side of the crossover, we find a novel temperature-dependent damping peak, suggesting a relation to the superfluid phase transition.     

胶原纤维网络和癌细胞的力学微环境

文章以第一类胶原纤维网络为例, 着重分析了癌细胞三维微环境的多尺度结构及力学特征. 对于细胞与细胞外介质结合的蛋白集团、单个细胞以及细胞群体, 分别由单个纤维(或亚纤维)、纤维集束以及纤维网络整体来决定相应的力学环境. 文章同时也讨论了胶原纤维(及其类似材料) 的局限性.     

Adsorption phenomena in amphiphilic systems

The wetting behavior of a ternary mixture of oil, water, and amphiphile in the presence of a surface is studied. An interface model carefully derived from an underlying Ginzburg-Landau theory is introduced, which contains position dependent rigidity and stiffness coefficients. Using this model we predict a rich surface phase diagram containing thin-thick, first-order, and continuous wetting transitions. Application of the model to other interface behavior in these mixtures is also addressed.     

Traffic Modelling for Moving-Block Train Control System

This paper presents a new cellular automaton （CA） model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.     

Influence of Cell-Cell Interactions on the Population Growth Rate in a Tumor

The understanding of the macroscopic phenomenological models of the population growth at a microscopic level is important to predict the population behaviors emerged from the interactions between the individuals. In this work, we consider the influence of the population growth rate R on the cell-cell interaction in a tumor system and show that, in most cases especially small proliferative probabilities, the regulative role of the interaction will be strengthened with the decline of the intrinsic proliferative probabilities. For the high replication rates of an individual and the cooperative interactions, the proliferative probability almost has no effect. We compute the dependences of R on the interactions between the cells under the approximation of the nearest neighbor in the rim of an avascular tumor. Our results are helpful to qualitatively understand the influence of the interactions between the individuals on the growth rate in population systems.     

Continuous macroscopic limit of a discrete stochastic model for interaction of living cells

We derive a continuous limit of a two-dimensional stochastic cellular Potts model (CPM) describing cells moving in a medium and reacting to each other through direct contact, cell-cell adhesion, and long-range chemotaxis. All coefficients of the general macroscopic model in the form of a Fokker-Planck equation describing evolution of the cell probability density function are derived from parameters of the CPM. A very good agreement is demonstrated between CPM Monte Carlo simulations and a numerical solution of the macroscopic model. It is also shown that, in the absence of contact cell-cell interactions, the obtained model reduces to the classical macroscopic Keller-Segel model. A general multiscale approach is demonstrated by simulating spongy bone formation, suggesting that self-organizing physical mechanisms can account for this developmental process.