关联白噪声对抗肿瘤体系免疫效果的影响

在免疫监视的Logistic肿瘤生长动力学模型中引入关联的乘性白噪声,并考虑抗肿瘤体系的免疫系统激活阈值存在差异,对上述动力学生长方程进行数值仿真计算.发现噪声关联强度能够调节抗肿瘤体系个体的免疫效果,但调节的结果存在差异;噪声关联强度λ的取值存在一个最佳区间,在该区间内更多的抗肿瘤体系个体能实现最大免疫效果. 关键词： Logistic生长模型 随机涨落 肿瘤 免疫     

双稳系统演化的时间尺度与随机共振的加强

噪声作用下的双稳系统存在着单一势阱内的随机波动和两势阱之间的概率跃迁,这两种不同层级的运动具有不同的时间尺度,且低层级的势阱内的波动影响着高层级的势阱间的跃迁．当外作用周期信号的时间尺度与噪声诱导的势阱间概率跃迁达到随机同步时,则能产生随机共振;给系统再加第二驱动周期信号,使其时间尺度与低层级的势阱内的波动相匹配,则存在着频率吸收现象,并能增强双稳系统的随机共振效应． 关键词： 随机共振 双稳系统 层级 时间尺度     

Scaling behavior of earthquakes’ inter-events time series

In this paper, we investigate the statistical and scaling properties of the California earthquakes’ inter-events over a period of the recent 40 years. To detect long-term correlations behavior, we apply detrended fluctuation analysis (DFA), which can systematically detect and overcome nonstationarities in the data set at all time scales. We calculate for various earthquakes with magnitudes larger than a given M. The results indicate that the Hurst exponent decreases with increasing M; characterized by a Hurst exponent, which is given by, H = 0:34 + 1:53/M, indicating that for events with very large magnitudes M, the Hurst exponent decreases to 0:50, which is for independent events.      

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.      

Stochastic resonance induced by a multiplicative periodic signal in a logistic growth model with correlated noises

The stochastic resonance (SR) phenomenon induced by a multiplicative periodic signal in a logistic growth model with correlated noises is studied by using the theory of signal-to-noise ratio (SNR) in the adiabatic limit. The expressions of the SNR are obtained. The effects of multiplicative noise intensity α and additive noise intensity D, and correlated intensity λ on the SNR are discussed respectively. It is found that the existence of a maximum in the SNR is the identifying characteristic of the SR phenomena. In comparison with the SR induced by additive periodic signal, some new features are found: (1) When SNR as a function of λ for fixed ratio of α and D, the varying of α can induce a stochastic multi-resonance, and can induce a re-entrant transition of the peaks in SNR vs λ; (2) There exhibits a doubly critical phenomenon for SNR vs D and λ, i.e., the increasing of D (or λ) can induce the critical phenomenon for SNR with respect to λ (or D); (3) The doubly stochastic resonance effect appears when α and D are simultaneously varying in SNR, i.e., the increment of one noise intensity can help the SR on another noise intensity come forth.      

二维映射神经元模型中频率依赖的随机共振

通过数值模拟方法, 研究了在具有稳定次阈值振荡特性的二维映射神经元体系中, 噪声对体系非线性动力学的调控作用. 通过计算发现了噪声诱导的动作电位和随机共振现象. 另外,还研究了体系的控制参数及输入信号的频率对体系动力学的影响, 发现了该体系中频率依赖的随机共振现象. 关键词： 二维映射神经元模型 次阈值振荡 高斯白噪声 随机共振     

基于Zernike模式的自适应光学系统随机并行梯度下降算法

 控制算法的收敛速度一定程度上限制了无波前探测自适应光学技术在实时波前畸变校正中的应用。从理论分析角度提出将模式法和区域法结合起来以提高算法收敛速度,并以61单元变形镜为校正器,建立基于随机并行梯度下降算法自适应光学系统仿真模型。结果表明：达到同样的校正效果时,采用组合优化的算法收敛速度要明显优于基于区域法的收敛速度,从而验证了理论分析的合理性。     

阵发型神经元网络的联想记忆与分割

以Hindmarsh-Rose(HR)神经元组成网络,研究这些网络的记忆(或模式)存储与时间分割问题．给定一个输入模式,它是几种模式的叠加,网络能够以一部分神经元同步发放的形式一个接一个地分割出每一种模式．如果输入的模式是缺损的,系统能够恢复为原型,即网络具有联想记忆功能．模拟也得到据作者所知至今还未报道的一些现象．     

基于随机搜索的一个约束优化问题的全局收敛算法

讨论了具有一般约束的全局优化问题,给出该问题的一个随机搜索算法,证明了该算法依概率1收敛到问题的全局最优解．数值结果显示该方法是有效的．     

旋流燃烧室内颗粒运动的数值模拟

本文应用流体相湍流脉动速度大小和方向均具有随机性的颗粒相随机轨道模型,对有直流一次风和旋流二次风的旋流燃烧室内的颗粒运动进行了数值模拟。得到的颗粒相轴向总质量流通量、轴向与切向速度分布与实验测量数据相符合,并比 Gosman 颗粒随机轨道模型的模拟结果有一定的改进。