The Exact Hausdorff Measure Function of the Level Sets of Multi-parameter Symmetric Stable Process

In this paper, we investigate the Hausdorff measure for level sets of N-parameter Rd-valued stable processes, and develop a means of seeking the exact Hausdorff measure function for level sets of N-parameter Rd-valued stable processes. We show that the exact Hausdorff measure function of level sets of N-parameter Rd-valued symmetric stable processes of index α is Ф（r） = r^N-d/α （log log l/r）d/α when Nα 〉 d. In addition, we obtain a sharp lower bound for the Hausdorff measure of level sets of general （N, d, α） strictly stable processes.     

A risk model driven by Lévy processes

We present a general risk model where the aggregate claims, as well as the premium function, evolve by jumps. This is achieved by incorporating a Lévy process into the model. This seeks to account for the discrete nature of claims and asset prices. We give several explicit examples of Lévy processes that can be used to drive a risk model. This allows us to incorporate aggregate claims and premium fluctuations in the same process. We discuss important features of such processes and their relevance to risk modeling. We also extend classical results on ruin probabilities to this model. Copyright © 2003 John Wiley & Sons, Ltd.     

The Asymmetric Avalanche Process

An asymmetric stochastic process describing the avalanche dynamics on a ring is proposed. A general kinetic equation which incorporates the exclusion and avalanche processes is considered. The Bethe ansatz method is used to calculate the generating function for the total distance covered by all particles. It gives the average velocity of particles which exhibits a phase transition from an intermittent to continuous flow. We calculated also higher cumulants and the large deviation function for the particle flow. The latter has the universal form obtained earlier for the asymmetric exclusion process and conjectured to be common for all models of the Kardar–Parisi–Zhang universality class.     

酵母蛋白质网络的动力学性质

蛋白质-蛋白质、蛋白质-DNA相互作用网络决定了细胞中各种关键功能的执行．基于芽殖酵母(budding yeast saccharomyces cerevisiae)的蛋白质-蛋白质相互作用网络数据和相关的实验文献，我们建立了调控细胞周期和生命周期(cell cycle and life cycle)的蛋白质网络，并利用离散模型研究了该网络的动力学性质，研究表明：细胞周期网络的动力学性质具有很强的稳定性，约94％的蛋白质初态将演化到对应于生物学G1基态的稳定态，使其成为惟一的全局吸引点；同时，绝大多数的初态的演化路径都通过由G1激发态到G1基态的细胞周期演化路径，使细胞周期路径成为全局性的“吸引”路径。     

Liminf results on the increments of an (N,d)-Gaussian process

We establish some liminf theorems on the increments of a (N,d)-Gaussian process with the usual Euclidean norm, via estimating upper bounds of large deviation probabilities on the suprema of the (N,d)-Gaussian process. This revised version was published online in June 2006 with corrections to the Cover Date.     

A theoretical analysis of the TiO2/Sn doped (1 1 0) surface properties

We have used the periodic quantum-mechanical method with density functional theory at the B3LYP level in order to study TiO₂/Sn doped (1 1 0) surfaces and have investigated the structural, electronic and energy band properties of these oxides. Our calculated relaxation directions for TiO₂ is the experimental one and is also in agreement with other theoretical results. We also observe for the doped systems relaxation of lattice positions of the atoms. Modification of Sn, O and Ti charges depend on the planes and positions of the substituted atoms. Doping can modify the Fermi levels, energy gaps as well as the localization and composition of both valence and conduction band main components. Doping can also modify the chemical, electronic and optical properties of these oxides surfaces increasing their suitability for use as gas sensors and optoelectronic devices.     

僧帽牡蛎碱性磷酸酶功能基团的研究

采用化学修饰法研究僧帽牡蛎碱性磷酸酶活性功能基团性质.酶经0.4mmol·L-1PCMB修饰30min后活力仍然保持不变,提示巯基与酶的活力无关;用二巯基苏糖醇(DTT)对酶进行修饰,当DTT浓度达到2.5mmol·L-1时,酶活力丧失98%,表明硫 硫键与酶活力有密切的关系;以N 溴代琥珀酰亚胺(NBS)修饰酶的色氨酸残基,酶的修饰失活呈一级反应,当NBS浓度达到0.65mmol·L-1时,酶活力丧失100%,并辅以紫外吸收光谱的变化分析,表明色氨酸残基是酶催化活力所必需的;醋酸酐、马来酸酐、甲醛等氨基试剂对酶的修饰作用显示氨基是酶的必需基团.     

一类随机过程的多尺度建模

基于多尺度随机模型具有有效性和高度并行算法这一优势，提出如何用三阶树多尺度模型来表示1-D Reciprocal过程；并如何获得多尺度模型的参数。这就为具有Markov统计特性的信号或过程建立起一般的三阶树多尺度随机模型，为更有效的解决实际问题提供了理沦基础，同时，给出了一类定义在单位区间上的随机过程三阶树多尺度表示的仿真示例。     

热连轧精轧机组温度模型的改进

从实际生产数据入手,研究了温度模型设定精度的现状及设定精度与各影响因素之间的关系,同时还消化了原来的温度模型程序并将其移植到微机上.经大量的离线统计回归分析,提出了一个行之有效的温度模型改进方案.该改进方案的思路同样适合其他热轧生产线.     

解释学习在机器人过程控制中的应用

机器人过程控制是智能机器人系统的一个特别重要而又十分复杂的研究课题。本文将解释学习应用于机器人过程控制，为之开发了一种新的方法。仿真结果表明，该方法可行、有效。同时，还尝试了将Ｐｒｏｌｏｇ语言作为机器人过程控制的运行机制的形式化表达工具的可能性。