受圆形表面单面约束的点锚固圆环热屈曲分析

应用Ｗ．Ｔ．Ｋｏｉｔｅｒ的初始后屈曲理论，研究了受圆形混凝土表面单面约束的点锚固圆环的热屈曲问题，根据混凝土容器壁的几何约束条件，假设了圆环的合理屈曲模状，得出了圆环在两锚固点之间发生屈曲的临界温度，并研究了其后屈曲性态和缺陷敏感性。结果表明，临界点和后屈曲路径的平衡均为稳定的，圆环对于与屈曲模态形状相同的缺陷是不敏感的。     

Quantum fluctuations of vacuum stress tensors and spacetime curvatures

We analyze the quantum fluctuations of vacuum stress tensors and spacetime curvatures, using the framework of linear response theory which connects these fluctuations to dissipation mechanisms arising when stress tensors and spacetime metric are coupled. Vacuum fluctuations of spacetime curvatures are shown to be a sum of two contributions at lowest orders; the first one corresponds to vacuum gravitational waves and is restricted to light-like wavevectors and vanishing Einstein curvature, while the second one arises from gravity of vacuum stress tensors. From these fluctuations, we deduce noise spectra for geodesic deviations registered by probe fields which determine ultimate limits in length or time measurements. In particular, a relation between noise spectra characterizing spacetime fluctuations and the number of massless neutrino fields is obtained.     

On a Multiparameter Version of Tukey's Linear Sensitivity Measure and its Properties

A multiparameter version of Tukey's (1965, Proc. Nat. Acad. Sci. U.S.A., 53, 127–134) linear sensitivity measure, as a measure of informativeness in the joint distribution of a given set of random variables, is proposed. The proposed sensitivity measure, under some conditions, is a matrix which is non-negative definite, weakly additive, monotone and convex. Its relation to Fisher information matrix and the best linear unbiased estimator (BLUE) are investigated. The results are applied to the location-scale model and it is observed that the dispersion matrix of the BLUE of the vector location-scale parameter is the inverse of the sensitivity measure. A similar property was established by Nagaraja (1994, Ann. Inst. Statist. Math., 46, 757–768) for the single parameter case when applied to the location and scale models. Two illustrative examples are included.     

Application of refractive medium in optical micromechanics

The refractive medium is used in moire interferometry and holographic grating fabrication technique. The sensitivity of traditional interferometry and the frequency of grating are enhanced effectively. These two novel techniques extend the application scope of the moire interferometry and facilitate the realization of superlattice method in micromechanics study. The project supported by the National Natural Science Foundation of China     

Statistical inference with partial prior information based on a Gauss-type inequality

Potter and Anderson [1] have developed a Bayesian decision procedure requiring the specification of a class of prior distributions restricted to have a minimal probability content for a given subset of the parameter space. They do not, however, provide a method for the selection of that subset. We show how a generalization of Gauss' inequality can be used to determine the relevant parameter subset.     

微机械生化传感器

自从Clark和Lyons在1962年研制出第一个生物传感器以来，探测各种生物和化学分子的生化传感器相继问世。这类传感器的基本原理是通过生化敏感层，被分析分子在敏感层上的物理或化学吸附被换能器转化为电信号。在众多的设计中，将活泼的生化敏感材料涂镀在硅器件表面是一个最有新意的设想。以往的硅生化传感器多设计为膜片式，器件的灵敏度受到限制。硅微机械悬臂梁是一种灵敏度极高的器件，近年来在传感器领域受到关注。文章总结了目前世界上硅基微悬梁生化传感器的最新发展动态。对几种硅悬臂梁的设计方法和工作原理进行了讨论，并给出了几种新型微生化气体和液体传感器检测不同有机分子和生物分子的结果。     

最优值函数的方向导数

本文详细介绍了参数非线性规划问题最优值函数的方向导数的存在性、表示形式和有关的发展历史,本文不仅讨论了这一问题的经典结论,还叙述了最近二十年来的新结果。本文最后指出进一步研究的方向。     

Distribution sensitivity for certain classes of chance-constrained models with application to power dispatch

Using results from parametric optimization, we derive for chance-constrained stochastic programs quantitative stability properties for locally optimal values and sets of local minimizers when the underlying probability distribution is subjected to perturbations in a metric space of probability measures. Emphasis is placed on verifiable sufficient conditions for the constraint-set mapping to fulfill a Lipschitz property which is essential for the stability results. Both convex and nonconvex problems are investigated. For a chance-constrained model of power dispatch, where the power demand enters as a random vector with incompletely known probability distribution, we discuss consequences of our general results for the stability of optimal generation costs and optimal generation policies.The authors thank P. Kleinmann (formerly with the Humboldt-Universität, Berlin, Germany) for his active cooperation in designing the power dispatch model and J. Mayer (MTA SZTAKI, Budapest, Hungary) for his insight into energy optimization. Further thanks are due to the referees for their constructive criticism.This research was developed in the course of a contract study between the International Institute for Applied Systems Analysis, Laxenburg, Austria and the Humboldt-Universität, Berlin, Germany.     

On regular minimax optimization

We consider functions of maximum type (max functions for short), subject to (in)equality constraints. The space dimension is finite, and the maximum is taken over a compact manifold with boundary. Effective local minimization algorithms based on Newton's method can be derived in the case where a local minimum is nondegenerate (in a two-level sense). In fact, nondegeneracy refers on the one hand to a local (implicit) reduction of the original max function to another one, where the maximum is taken over a finite set. On the other hand, it refers to strict complementarity and nondegeneracy of the underlying quadratic form with respect to the reduced stationary situation. As the main goal, we show that the set ofn-parameter families of functions, for which the stationary points of the corresponding max function are nondegenerate, constitutes an open and dense subset in the space of alln-parameter families (the topology used takes derivatives up to second order into account). An application to approximation problems of Chebyshev type is presented.     

Differential sensitivity of solutions of convex constrained optimal control problems for discrete systems

A family of optimal control problems for discrete systems that depend on a real parameter is considered. The problems are strongly convex and subject to state and control constraints. Some regularity conditions are imposed on the constraints.The control problems are reformulated as mathematical programming problems. It is shown that both the primal and dual optimal variables for these problems are right-differentiable functions of a parameter. The right-derivatives are characterized as solutions to auxiliary quadratic control problems. Conditions of continuous differentiability are discussed, and some estimates of the rate of convergence of the difference quotients to the respective derivatives are given.