A compound spike model for formation of nuclear tracks in solids

Formation of nuclear tracks in solids has been described as a thermal spike as well as a Coulomb explo- sion spike.Here,formation of nuclear tracks is described as a compound spike including partial roles of both thermal and Coulomb explosion spikes in track formation.Fractional roles of both spikes depend on atomic and electronic structure of a track detector and deposited energy density in the track detector by the incident charged particle.Be- havior of the cylindrical zone along the path of the incident particle is described mathematically in terms of bulk and individual atomic flow or movement.Defect structure of the latent nuclear tracks is described and conditions of con- tinuity and discontinuity of latent tracks are evaluated and discussed.This paper includes mathematical description, analysis and evaluation of the nuclear track formation issue in the light of published experimental and theoretical re- sults,which are useful for users of nuclear track detection technique and researchers involved in ion beam induced materials modification and ions implantation in semiconductors.

Numerical simulation of neuronal spike patterns in a retinal network model

This study utilized a neuronal compartment model and NEURON software to study the effects of external light stimulation on retinal photoreceptors and spike patterns of neurons in a retinal network Following light stimulation of different shapes and sizes, changes in the spike features of ganglion cells indicated that different shapes of light stimulation elicited different retinal responses. By manipulating the shape of light stimulation, we investigated the effects of the large number of electrical synapses existing between retinal neurons. Model simulation and analysis suggested that interplexiform cells play an important role in visual signal information processing in the retina, and the findings indicated that our constructed retinal network model was reliable and feasible. In addition, the simulation results demonstrated that ganglion cells exhibited a variety of spike patterns under different light stimulation sizes and different stimulation shapes, which reflect the functions of the retina in signal transmission and processing.

基于贝叶斯原理的多维Spike Train分类预测模型

神经元集群编码和spike train分析是神经信息处理的关键问题。该文介绍了一种利用高阶多维泊松模型对spike train进行分类预测的方法,并从spike的强度分布、匹配准确性和集成策略上进行了数学论证。最后利用该方法在大鼠U迷宫实验中选取20组作为训练集进行分类测试,实验结果表明,利用该方法得到的分类准确率在97%左右。

Modeling of Track Formation in Semiconductors Irradiated with Swift Heavy Ions

The interaction of the heavy charged particles, of energy higher than a few MeV/amu with semiconductor single crystals can lead to the structural modification of their physical properties and participate at the creation of the defects which are called latent tracks. Several models were tested for explaining the track formation in semiconductors irradiated with swift heavy ions, one of them is the thermal spike model. This work shows that the experimental data obtained in semiconductors, in our case in InP irradiated with swift heavy ions can be described on the basis of the thermal spike model. The experimental results obtained on InP have allowed the parameters of this model to be understood. The only free parameter is the electron-phonon coupling constant g which is unknown in InP This model allows the evolution of track radii to be found as a function of electronic stopping power （dE/dx）e for different beam energies. For InP a good agreement is observed between calculated track radii and experimental ones on one hand, and on the other hand between calculated and experimental threshold value of electronic stopping power. This allows determining the electron-phonon coupling value for InP to be equal 0.9 × 10%11 Wcm-3K-land the （dE/dx）e threshold for latent track formation in InP equal 27 ＋ 3 keV/nm for ion energies ranging from 0.4-10 MeV/amu.

采用Spiked协方差模型与“相变”现象的电网不平衡扰动评估

为了提升随机矩阵理论在电网不平衡扰动场景中的适用性,提出了一种基于Spiked协方差模型与"相变"现象的电网扰动识别与定位方法。首先,通过含噪声三相数据源的采集,构造Spiked协方差模型与样本协方差矩阵。然后,利用特征值"相变"现象构建样本最大特征值评价指标及对应的动态阈值。当该指标越过其阈值,即判定电网中有扰动事件发生时,根据Spiked与样本最小特征向量元素改变量的网络位置,结合特征向量"相变"现象以实现电网不平衡扰动的快速定位。最后,借助DIgSILENT和MATLAB R2014a软件,案例分析在一个IEEE 118母线177支路系统和一个德国872母线1 840支路实际配电系统中展开,涉及负荷突变和线路故障等不平衡扰动事件,与传统随机矩阵理论方法的比较结果表明了所提方法的有效性和高效性。

基于Spiked模型的低信噪比环境电网异常状态检测

为发展基于大数据技术的电网态势感知理论与方法,提出了一种基于Spiked模型电网异常状态动态辨识方法,该方法源于随机矩阵理论。首先,通过数据源矩阵的构造,窗口数据矩阵及其标准矩阵的构建,进而形成其样本协方差矩阵,并计算该矩阵的最大特征值;然后,利用由Kaiser窗函数校正的经典谱估计法进行全局信噪比估计,进而得出对应的动态阈值,并与最大特征值比较来进行异常状态判别;最后,借助MATLAB软件,案例分析在一个IEEE50机标准系统展开,涉及负荷异常跃变及三相短路接地故障,与传统的平均谱半径分析法的计算结果比较表明该方法具有抗噪性能高、适应性强的优点,同时对于非完整性信息有一定的鲁棒性。

基于随机矩阵理论与Spiked模型的电力系统态势感知方法研究

从数据驱动角度,结合随机矩阵理论(RMT)和Spiked模型,研究了电力系统异常状态感知方法和关键节点辨识方法.提出了基于样本协方差矩阵最大特征值(MESCM)的电力系统异常状态感知方法;在此基础上引入Spiked模型对其进行改进,实现了电力系统异常状态的动态感知;以系统电压数据为原始数据,结合熵理论提取了数据有效信息,对电力系统网络的关键节点进行辨识.通过模拟分析和实际检测验证了该方法具有抗噪性能高、计算耗时少的优点,提高了电力系统异常状态感知模型的准确度和鲁棒性.该方法有效反映了电力系统异常状态的演化方向及其分布,可用于支持电力系统预防、检修和运维,辅助电力系统决策.

基于RISC-V架构的Spike缓存模型的设计和实现

使用基于精简指令集原则的指令架构(RISC-V)的指令集,针对现有Spike验证模型中的缓存写回功能的缺失问题,设计一种基于RISC-V指令集的现代超标量处理器缓存模型。基于现代高速缓存的基本原理,结合Spike验证模型,实现现代高速缓存的基本读写操作,并进行系统级芯片(SoC)环境下的仿真和验证,可作为微型电子芯片(IC)前端逻辑设计中的验证模型使用。该方案能够以较快的时间完成基于RISC-V指令集的大型SoC的设计与验证。

Three-dimensional numerical simulation of crown spike due to coupling effect between bubbles and free surface

The motion of gas bubbles beneath a free surface will lead to a spike of fluid on the free surface. The distance of the bubbles to the free surface is the key factor to different phenomena. When the inception distance varies in some range, crown phenomenon would happen after the impact of weak buoyancy bubbles, so this kind of spike is defined as crown spike in the present paper. Based on potential flow theory, a three-dimensional numerical model is established to simulate the motion of the free-surface spike generated by one bubble or a horizontal line of two in-phase bubbles. After the downward jet formed near the end of the collapse phase, the simulation of the free surface is performed to study the crown spike without regard to the toroidal bubble＇s effect. Calculations about the interaction between one bubble and free surface agree well with the experimental results conducted with a high-speed camera, and relative error is within 15%. Crown spike in both single- and two-bubble cases are simulated numerically. Different features and laws of the motion of crown spike, depending on the bubble-boundary distances and the inter-bubble distances, have been investigated.

Modelling Epidemiological Data Using Box-Jenkins Procedure

In this paper, the Box-Jenkins modelling procedure is used to determine an ARIMA model and go further to forecasting. We consider data of Malaria cases from Ministry of Health (Kabwe District)-Zambia for the period, 2009 to 2013 for age 1 to under 5 years. The model-building process involves three steps: tentative identification of a model from the ARIMA class, estimation of parameters in the identified model, and diagnostic checks. Results show that an appropriate model is simply an ARIMA (1, 0, 0) due to the fact that, the ACF has an exponential decay and the PACF has a spike at lag 1 which is an indication of the said model. The forecasted Malaria cases for January and February, 2014 are 220 and 265, respectively.

Numerical Simulation Analysis of a Mathematical Model of Circadian Pacemaker Neurons

Sim and Forger have proposed a mathematical model of circadian pacemaker neurons in the suprachiasmatic nucleus (SCN). This model, which has been formulated on the Hodgkin-Huxley mo-del, is described by a system of nonlinear ordinary differential equations. An important feature of the SCN neurons observed in electrophysiological recording is spontaneous repetitive spiking, which is reproduced using this model. In the present study, numerical simulation analysis of this model was performed to evaluate variations in two system parameters of this model: the maximal conductance of calcium current (gCa) and the maximal conductance of sodium current (gNa). Simulation results revealed the spontaneous repetitive spiking states of the model in the (gCa, gNa)-pa-rameter space.

A Coordination Model of Gene Sequences for SARS-CoV and its Receptor

A Z curve-based coordination model of genome sequences for the interaction of the SARS coronavirus (SARS-CoV) with its receptor, angiotensin-converting enzyme 2 (ACE2) is proposed. The model provides a novel, intuitive tool for visualizing and analyzing DNA sequences of SARS. It will be useful to the analysis of SARS-CoV in lab detection. Also, it can be used as a solution to other studies in bioinformatics field.

The Phenomenon of Neural Bursting and Spiking in Neurons: Morris-Lecar Model

In this study, we explore the interesting phenomenon of firing spikes and complex dynamics of Morris-Lecar model. We consider a set of parameters such that the model exhibits a wide range of phenomenons. We investigate the influences of injected current and temperature on the spiking dynamics of Morris-Lecar model. Moreover, we study bifurcations, and computational properties of this neuron model. Also, we define a bound (Max and Min voltage) for membrane potential and a certain voltage value or threshold for firing the spikes. Studying the two co-dimension bifurcations demonstrates much more complicated behaviors for this single neuron model. We also describe the phenomenon of neural bursting, and investigate the dynamics of Morris-Lecar model as a square-wave burster, elliptic burster and parabolic burster.

The spike timing precision of FitzHugh-Nagumo neuron network coupled by gap junctions

It has been proved recently that the spike timing can play an important role in information transmission, so in this paper we develop a network with N-unlt FitzHugh-Nagumo neurons coupled by gap junctions and discuss the dependence of the spike timing precision on synaptic coupling strength, the noise intensity and the size of the neuron ensemble. The calculated results show that the spike timing precision decreases as the noise intensity increases; and the ensemble spike timing precision increases with coupling strength increasing. The electric synapse coupling has a more important effect on the spike timing precision than the chemical synapse coupling.

Modeling Neuromorphic Persistent Firing Networks

Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.

基于近红外光谱分析的土壤污染柴油含量预测方法研究

为了快速定量测量柴油污染土壤中的柴油含量,扩大近红外光谱技术在污染土壤监测中的应用,制备了含柴油的高岭土样本集F1和含柴油的实际土壤样本集F2,对近红外光谱检测数据建立了BP神经网络、随机森林和支持向量机回归3种预测模型。结果表明,预测模型对样本集F1的预测精度良好,但无法准确预测样本集F2中的柴油含量。通过加标和重复加标处理,改善了实际土壤中柴油含量的预测效果。与直接建模相比,由柴油高岭土样本加入少量实际土壤样本后建立的近红外光谱模型,能更准确地预测柴油含量。

基于不同神经网络模型预测体测成绩

为更加准确地反应当前学生的身体素质情况,基于多个不同的神经网络模型构建体测成绩预测模型,为降低体测成绩中各项目数据之间的相关性,使用主成分分析法对数据集进行处理。使用BP神经网络结合脉冲神经网络构建一个预测模型,加强模型处理分析数据集的能力,提高预测的准确性。在长短期记忆神经网络中加入注意力机制构建另一个预测模型,使模型更加关注数据集中的关键信息。通过实验,预测模型输出的预测值与实际值的重合率高达90%以上,预测准确率整体在95%以上。

热工水力系统分析软件数值水锤抑制方法研究

中广核集团正在研发一款新的热工水力系统分析软件LOCUST 2.0,它采用两流体双压力七方程模型。由于LOCUST 2.0采用欧拉体系描述流体方程,在数值离散的控制体边界会因数值处理方式引入像管道末端水锤现象类似的虚假的压力剧烈波动,这种现象一般被称为水塞或数值水锤现象。单压力模型的水塞现象抑制方法不再适用双压力,因此设计了一种针对双压力模型的系统分析软件水塞现象抑制的方法。该方法包括识别发生水塞现象的控制体,并修正发生水塞现象的控制体压力方程中的特定项,进而重新求解压力方程。修正压力方程过程中,设计了具备压力波动幅度自适应能力的抑制因子。将上述方法用于LOCUST 2.0数值求解中,对不同压力下饱和与过冷液相入口条件进行了测试,结果表明:本方法达到了消除压力剧烈波动的目的,且所设计的抑制因子的效果优于采用两流体单压力系统分析软件传统采用抑制因子的效果。

糖尿病合并新型冠状病毒S蛋白感染小鼠病理生理特征

目的建立糖尿病(DM)合并新型冠状病毒(SARS-CoV-2)感染小鼠模型,研究DM合并SARS-CoV-2感染病程发展中的重要病理生理变化。方法将野生型(WT)小鼠和由细胞角蛋白18基因启动子驱动的人血管紧张素转化酶2受体(K18-hACE2,简称hACE2)的转基因小鼠分别随机分为溶剂对照组、DM组、SARS-CoV-2病毒刺突蛋白感染(S)组以及DM合并S蛋白感染(DM+S)组,每组10~12只。除溶剂对照组及S组外,其余组通过10周高脂饮食后连续3 d ip给予链脲佐菌素(STZ)40 mg·kg^(-1)诱导DM症状,溶剂对照组及S组给予等体积0.1 mol·L^(-1)柠檬酸钠缓冲液。在此基础上,S组及DM+S组小鼠经鼻腔滴入15μg SARS-CoV-2 S蛋白与1 g·L^(-1)聚肌胞苷酸(Poly[I:C])的混合溶液50μL,溶剂对照组滴鼻给予等体积无菌水。在高脂喂养第6周和ip给予STZ 1周后,以口服葡萄糖耐量实验评价小鼠糖耐量水平及胰岛β细胞功能。高脂喂养第6周至ip给予STZ 2周后,每周用血糖仪检测小鼠随机血糖及空腹血糖。DM小鼠S蛋白感染前及感染24,48和120 h后,每组取3只小鼠颌下静脉取血后处死并取肺组织,采用苏木精-伊红染色法观察合并S蛋白感染前后的肺组织病理改变。S组小鼠在感染S蛋白前及感染6,24,48,72和120 h后采血,Luminex液相芯片技术检测小鼠血浆细胞因子白细胞介素1β(IL-1β)、IL-2、IL-6、IL-10、IL-17、干扰素诱导蛋白10(IP-10)、干扰素γ(IFN-γ)、肿瘤坏死因子α(TNF-α)、单核细胞趋化蛋白1(MCP-1)和粒细胞集落刺激因子(G-CSF)水平,ELISA检测血浆硫酸乙酰肝素(HS)水平;将细胞因子水平、HS水平与小鼠感染S蛋白后的肺部病理损伤程度进行Spearman相关性分析。结果STZ合并高脂饮食可诱导小鼠DM样表现,hACE2-DM组随机血糖(P<0.01)和1周后的空腹血糖(P<0.05)均显著高于WT-DM组,且hACE2-DM小鼠胰岛功能损伤程度显著高于WT-DM小鼠(P<0.05)。与DM组相比,DM+S组小鼠均表现出更严重的肺部病理变化,并伴有大量炎症浸润和肺间质增厚。与溶剂对照组相比,S蛋白感染6 h,WT-S组小鼠血浆中促炎细胞因子G-CSF,IL-6和IP-10均显著升高(P<0.01),S蛋白感染24 h,促炎细胞因子IL-17和抗炎细胞因子IL-10均显著升高(P<0.05);S蛋白感染6 h,hACE2-S组血浆中促炎细胞因子IL-1β,IL-6,TNF-α,MCP-1,G-CSF和IP-10均显著升高(P<0.05,P<0.01);WT-DM+S组和hACE2-DM+S组IL-17分别在S蛋白感染24和6 h显著升高(P<0.01,P<0.05),hACE2-DM+S组IFN-γ和IL-1β延迟至48 h显著升高(P<0.05,P<0.01),MCP-1延迟至72 h显著升高(P<0.05)。与溶剂对照组相比,S蛋白感染6和24 h后,WT-S组血浆中HS水平显著升高(P<0.05,P<0.01),48 h开始降低;同时,与WT-S组相比,感染6 h后,WT-DM+S组HS水平略升高,24 h出现降低;hACE2-S组HS水平于24 h显著升高(P<0.01),且在S蛋白感染24,48和120 h后与WT-S组基本持平;S蛋白感染6,24和48 h后,hACE2-DM+S组血浆HS水平均显著升高(P<0.01,P<0.05),升高持续时间较其S组长。小鼠血浆中IL-1β,IL-10,MCP-1,IP-10,G-CSF以及HS水平与DM+S小鼠肺损伤程度呈正相关(P<0.05,P<0.01)。结论本研究建立的DM合并SARS-CoV-2 S蛋白感染小鼠模型能成功模拟临床患者的部分病理生理特征,主要表现为较单纯感染免疫反应钝化,HS水平升高且持续时间较长。IL-1β,IL-10,MCP-1,IP-10,G-CSF以及HS可能有助于及时了解DM合并SARS-CoV-2感染患者的病程。

小麦地上部器官几何造型与可视化研究

为了精确重构小麦三维空间形态,增强几何模型与品种特性及作物模型间的衔接,通过对小麦植株拓扑结构和形态结构的观测分析,对叶片、穗、茎秆等地上部器官几何造型算法进行了研究。结果表明,小麦叶脉曲线可用比叶重、叶倾角和叶长3个参数确定,进一步与叶形和叶片边缘几何造型模型整合,能够对小麦叶片生长、卷曲以及扭曲等进行精确描述。在麦穗几何造型中,使用偏圆柱体重构穗轴节片,以二次曲面代表颖片、稃片,可以实现麦穗的参数化建模。通过定量化小麦植株拓扑结构和器官的形态特征参数,采用结构化建模途径,在VC++6.0集成开发环境和OpenGL图形平台上驱动器官几何模型,可以快速精确重构出不同生育时期的小麦三维形态,并实现可视化显示,重构出的小麦植株具有较强的真实感。因此,基于形态特征参数的小麦地上部器官几何造型算法能够较好地实现器官及植株的精确重构,且易于交互、可控性强。