Computation of the rms state variables and control forces in a half-car model with preview active suspension using spectral decomposition methods

Spectral decomposition methods are applied to compute accurately the rms values for the control forces, suspension strokes and tyre deflection at front and rear in a half-car model with preview. The vehicle model is assumed to be fitted with active suspension and travelling at constant speed on a random road and the control is assumed to be optimal.     

ALD of ZnO using diethylzinc as metal-precursor and oxygen as oxidizing agent

We report on ZnO atomic layer deposition (ALD) with a precursor combination of diethylzinc as metal-precursor and pure oxygen (O₂) as oxidant as an alternative to H₂O as oxygen precursor. The temperature region of self-limiting ALD growth (ALD window) is determined and shows an increase in growth rate of about 60% compared to water as oxygen-precursor. Finally, in situ X-ray photoelectron spectroscopy (XPS) and synchrotron-radiation photoelectron spectroscopy (SR-PES) have been used to analyze the initial growth and film properties of ALD-ZnO deposited in monolayer steps using both precursor combinations.     

TMOS based water repellent silica thin films by co-precursor method using TMES as a hydrophobic agent

The present paper describes the room temperature synthesis of dip coated water repellent silica coatings on glass substrates using trimethylethoxysilane (TMES) as a co-precursor. Silica sol was prepared by keeping the molar ratio of tetramethoxysilane (TMOS) precursor, methanol (MeOH) solvent, water (H₂O) constant at 1:29.27:2.09 respectively, with 0.5 M NH₄OH throughout the experiments and the TMES/TMOS molar ratio (M) was varied from 0 to 3.8. It was found that with an increase in M value, the roughness and hydrophobicity of the films increased, however the optical transmission decreased from 93% to 57% in the visible range. The hydrophobic silica films retained their hydrophobicity up to a temperature of 250 °C and above this temperature the films became hydrophilic. The hydrophobic silica thin films were characterized by taking into consideration the surface roughness studies, Fourier transform infrared (FT-IR) spectroscopy, percentage of optical transmission, scanning electron microscopy (SEM) and contact angle measurements.     

Application of a fusion model using collective variables and microscopically related mass parameters

A calculation of nucleus-nucleus collisions is presented, using a model which starts from a TDHF equation and leads to classical equations of motion for a set of four collective variables. Restricting to axial symmetry and assuming the liquid drop mass formula to hold, a differential equation is derived, which describes nuclear deformations and energies and is used to construct a potential energy surface for the collective variables. The nuclear deformations are obtained without the need of shape parameters. The equations of motion for the collective variables are solved numerically.     

基于大脑情感学习模型和自适应遗传算法的混沌时间序列预测

针对传统神经网络预测精度不高、收敛速度慢的问题,提出一种基于大脑情感学习模型和自适应遗传算法的混沌时间序列预测方法.大脑情感学习模型模拟了哺乳动物大脑中杏仁体和眶额皮质之间的情感学习机制,具有计算复杂度低、运算速度快的特点,因此可以大大提高混沌预测的快速性.为了进一步提高大脑情感学习模型的预测精度,采用自适应遗传算法优化其参数,将待优化的权值与阈值分布在染色体基因序列上,用适应度函数选出最佳参数,从而增强了模型的逼近能力.基于Lorenz混沌时间序列和实际地磁Dst指数序列的预测结果表明,本文方法较其他传统方法在预测精度、运算速度和稳定性上均具有明显优势.     

一种基于用户相对权重的在线社交网络信息传播模型

根据在线社交网络信息传播特点和目前社交网络传播模型研究中存在的问题, 本文定义了网络用户之间的相互影响力函数, 在此基础上提出了一种基于用户相对权重的社交网络信息传播模型, 并对网络中的传播路径及传播过程进行了分析, 讨论了不同路径的信息传播影响力.为验证模型的有效性, 将传统的SIR模型和本文模型在六类不同网络拓扑下进行了仿真实验.仿真结果表明, 两类模型在均匀网络中没有明显差异, 但在非均匀网络中本文模型更能体现真实网络特点, 实验同时验证了节点的地位影响着信息的传播, 并且发现英文社交平台Twitter和中文社交平台新浪微博在拓扑结构上具备一定相似性.     

Magnetic resonance venography in liver bipartition procedures using preservation solution as contrast agent

To evaluate whether the hepatic veins can be visualized with a rapid noninvasive technique, and if so, whether the obtained images could be helpful in the preparation of split liver grafts for transplantation, six cold stored human donor livers were investigated with magnetic resonance imaging (MRI). The hepatic vein branches and their confluence were clearly visualized. Anatomic variations of the middle hepatic vein with consequences for the choice of the transection plane could be demonstrated. Furthermore, unexpected vascular abnormalities were detected. From these preliminary results it is concluded that visualization of the hepatic veins can be helpful in determining the feasibility of the bipartition procedure and the choice of the transection plane. A potential wide application of this fast and noninvasive technique is possible.     

DMH镀金体系在ICF空腔靶中的应用

将 5,5-二甲基乙内酰脲(DMH)新型无氰电镀体系应用于惯性约束聚变金空腔靶制备中。利用扫描电镜和库仑计法研究了以DMH为配位剂的镀液组成和工艺条件对电镀金层质量等的影响。结果表明:该镀液体系具有良好的稳定性,控制镀液中金盐质量浓度为8 g/L,DMH质量浓度为80 g/L时,在阴极电流密度1.5 A/dm2、pH值9~10、温度45 ℃的条件下,可制得结晶致密、厚度均一的金镀层。     

Stochastic persistence and stationary distribution in a Holling-Tanner type prey-predator model

In this paper, we study a stochastic predator-prey model with Beddington-DeAngelis type functional response and logistic growth for predators. The deterministic model is already well-studied and we recall some important results here. We construct the stochastic model from the deterministic model by introducing multiplicative noise terms into the growth equations of prey and predator populations. For the stochastic model, we show that the system admits unique positive global solution starting from the positive initial value. Then we prove that the system is strongly persistent in mean when the intensity of environmental forcing is less than some threshold magnitudes. Finally, we show that the system has a stationary distribution under certain parametric restrictions. Numerical simulations are carried out to substantiate the analytical results.     

Synthesis and characterization of a nano-scaled barium cerate perovskite powder using starch as polymerization agent

The preparation of nano-sized BaCeO₃ powder using starch as a polymerization agent is described herein. Phase evolution during the decomposition process of a (BaCe)-gel was monitored by XRD. A phase-pure nano-sized BaCeO₃ powder was obtained after calcining of the (BaCe)-gel at 920 °C. The resulting powder has a specific surface area of 15.4 m²/g. TEM investigations reveal particles mainly in the size range of 30 to 65 nm. The shrinkage and sintering behavior of resulting powder compacts were studied in comparison to a coarse-grained mixed-oxide BaCeO₃ powder (S_BET = 2.1 m²/g). Dilatometric measurements show that the beginning of shrinkage of compacts from the nano-sized powder is downshifted by 300 °C compared to mixed-oxide powder. Compacts from the nano-sized powder reach a relative density of 91% after sintering at 1450 °C for 10 h.     

基于局部和全局信息的自适应水平集图像分割

针对仅采用局部或全局信息无法快速准确分割灰度不均匀图像的问题,提出了一种基于局部和全局信息的自适应水平集图像分割模型。首先,利用图像局部信息和全局信息建立局部能量项和全局能量项,并且利用演化曲线轮廓内外小邻域的灰度均值差作为自变量,建立了权重函数模型,实现了局部能量项和全局能量项之间权重的自适应调整,提高了模型分割灰度不均匀图像的效率和准确性。其次,提出了一种新的能量惩罚项,避免了水平集函数的重新初始化,增强了数值计算的稳定性。最后,为验证模型的优越性,将模型与CV模型、LBF模型和LGIF模型进行了对比,并通过分割时间、迭代次数以及相似度等指标对分割结果进行了客观、定量分析。最终结果表明:该模型不但对初始轮廓具有较高鲁棒性,而且对灰度不均匀图像具有较高的分割准确性与分割效率。     

基于局部和全局信息的自适应水平集图像分割

针对仅采用局部或全局信息无法快速准确分割灰度不均匀图像的问题,提出了一种基于局部和全局信息的自适应水平集图像分割模型。首先,利用图像局部信息和全局信息建立局部能量项和全局能量项,并且利用演化曲线轮廓内外小邻域的灰度均值差作为自变量,建立了权重函数模型,实现了局部能量项和全局能量项之间权重的自适应调整,提高了模型分割灰度不均匀图像的效率和准确性。其次,提出了一种新的能量惩罚项,避免了水平集函数的重新初始化,增强了数值计算的稳定性。最后,为验证模型的优越性,将模型与CV模型、LBF模型和LGIF模型进行了对比,并通过分割时间、迭代次数以及相似度等指标对分割结果进行了客观、定量分析。最终结果表明:该模型不但对初始轮廓具有较高鲁棒性,而且对灰度不均匀图像具有较高的分割准确性与分割效率。     

Reduction of systematic uncertainty in the transmission measurement of iron using entropy based mutual information

Neutron cross-section determination by transmission measurement is essentially a data reduction process of obtaining the cross-section from the raw data of the neutron detector counts. The data reduction parameters are dominated by systematic uncertainty with a large coefficient of correlation. All the efforts have so far been devoted only to minimize the statistical uncertainty in neutron detector counts by repeated measurements but the dominant systematic uncertainty in the data reduction parameters has either been neglected or randomized. As the conventional central limit theorem cannot be applied to reduce the highly correlated systematic uncertainty, we propose a new approach called entropy based mutual information to set theoretical limits and minimize the systematic uncertainty using an algorithm we have developed. In our algorithm one can determine the upper and lower bounds of the non-diagonal elements of the correlation matrix for maximization of mutual information. We demonstrate the utility of our approach in reducing the systematic and hence the total uncertainty of neutron cross-section of iron in the transmission measurement.     

Temporal correlations and persistence in the kinetic Ising model: the role of temperature

We study the statistical properties of the sum S _t = dt'σ _t', that is the difference of time spent positive or negative by the spin σ _t, located at a given site of a D-dimensional Ising model evolving under Glauber dynamics from a random initial configuration. We investigate the distribution of S_t and the first-passage statistics (persistence) of this quantity. We discuss successively the three regimes of high temperature ( T > T _c), criticality ( T = T _c), and low temperature ( T < T _c). We discuss in particular the question of the temperature dependence of the persistence exponent , as well as that of the spectrum of exponents (x), in the low temperature phase. The probability that the temporal mean S _t/t was always larger than the equilibrium magnetization is found to decay as t ^{- - ?}. This yields a numerical determination of the persistence exponent in the whole low temperature phase, in two dimensions, and above the roughening transition, in the low-temperature phase of the three-dimensional Ising model. Received 4 December 2000     

Clustering and information in correlation based financial networks

Networks of companies can be constructed by using return correlations. A crucial issue in this approach is to select the relevant correlations from the correlation matrix. In order to study this problem, we start from an empty graph with no edges where the vertices correspond to stocks. Then, one by one, we insert edges between the vertices according to the rank of their correlation strength, resulting in a network called asset graph. We study its properties, such as topologically different growth types, number and size of clusters and clustering coefficient. These properties, calculated from empirical data, are compared against those of a random graph. The growth of the graph can be classified according to the topological role of the newly inserted edge. We find that the type of growth which is responsible for creating cycles in the graph sets in much earlier for the empirical asset graph than for the random graph, and thus reflects the high degree of networking present in the market. We also find the number of clusters in the random graph to be one order of magnitude higher than for the asset graph. At a critical threshold, the random graph undergoes a radical change in topology related to percolation transition and forms a single giant cluster, a phenomenon which is not observed for the asset graph. Differences in mean clustering coefficient lead us to conclude that most information is contained roughly within 10% of the edges.Received: 11 December 2003, Published online: 14 May 2004PACS: 89.65.-s Social and economic systems - 89.75.-k Complex systems - 89.90. + n Other topics in areas of applied and interdisciplinary physics (restricted to new topics in section 89)     

Bubbles,crashes and intermittency in agent based market models

We define and study a rather complex market model, inspired from the Santa Fe artificial market and the Minority Game. Agents have different strategies among which they can choose, according to their relative profitability, with the possibility of not participating to the market. The price is updated according to the excess demand, and the wealth of the agents is properly accounted for. Only two parameters play a significant role: one describes the impact of trading on the price, and the other describes the propensity of agents to be trend following or contrarian. We observe three different regimes, depending on the value of these two parameters: an oscillating phase with bubbles and crashes, an intermittent phase and a stable `rational' market phase. The statistics of price changes in the intermittent phase resembles that of real price changes, with small linear correlations, fat tails and long range volatility clustering. We discuss how the time dependence of these two parameters spontaneously drives the system in the intermittent region. We analyze quantitatively the temporal correlation of activity in the intermittent phase, and show that the `random time strategy shift' mechanism that we proposed earlier allows one to understand the observed long ranged correlations. Other mechanisms leading to long ranged correlations are also reviewed. We discuss several other issues, such as the formation of bubbles and crashes, the influence of transaction costs and the distribution of agents wealth. Received 5 July 2002 / Received in final form 9 December 2002 Published online 14 February 2003 RID="a" ID="a"e-mail: irene.giardina@roma1.infn.it     

Quantum Fisher information and chaos in the Dicke model

We introduce a method of quantum tomography for a continuous variable system in position and momentum space. We consider a single two-level probe interacting with a quantum harmonic oscillator by means of a class of Hamiltonians, linear in position and momentum variables, during a tunable time span. We study two cases: the reconstruction of the wavefunctions of pure states and the direct measurement of the density matrix of mixed states. We show that our method can be applied to several physical systems where high quantum control can be experimentally achieved.