关于图的直径和平均距离

图的直径和平均距离是度量网络有效性的两个重要参数．Ore通过图的顶点数和直径给出无向图的最大边数．Entringer，Jakson，Slater和Ng，Teh通过图的顶点数和边数分别给出无向图和有向图平均距离的下界．该文提供这两个结果的简单证明，给出有向图类似Ore的结果，并通过图的直径改进Entringer等人的结果到更一般的情形．结合本文和Ore的结果，可以得到一个无向图和有向图平均距离的下界，它比Plesnik得到的下界更好．     

Decomposition algorithms for the tree edit distance problem

We study the behavior of dynamic programming methods for the tree edit distance problem, such as [P. Klein, Computing the edit-distance between unrooted ordered trees, in: Proceedings of 6th European Symposium on Algorithms, 1998, p. 91–102; K. Zhang, D. Shasha, SIAM J. Comput. 18 (6) (1989) 1245–1262]. We show that those two algorithms may be described as decomposition strategies. We introduce the general framework of cover strategies, and we provide an exact characterization of the complexity of cover strategies. This analysis allows us to define a new tree edit distance algorithm, that is optimal for cover strategies.     

Tomography of Binomial States of the Radiation Field

The symplectic, optical, and photon-number tomographic symbols of binomial states of the radiation field are studied. Explicit relations for all tomograms of the binomial states are obtained. Two measures for nonclassical properties of these states are discussed.     

Construction of best Bregman approximations in reflexive Banach spaces

An iterative method is proposed to construct the Bregman projection of a point onto a countable intersection of closed convex sets in a reflexive Banach space.

     

Structural properties and tractability results for linear synteny

The syntenic distance between two species is the minimum number of fusions, fissions, and translocations required to transform one genome into the other. The linear syntenic distance, a restricted form of this model, has been shown to be close to the syntenic distance. Both models are computationally difficult to compute and have resisted efficient approximation algorithms with non-trivial performance guarantees. In this paper, we prove that many useful properties of syntenic distance carry over to linear syntenic distance. We also give a reduction from the general linear synteny problem to the question of whether a given instance can be solved using the maximum possible number of translocations. Our main contribution is an algorithm exactly computing linear syntenic distance in nested instances of the problem. This is the first polynomial time algorithm exactly solving linear synteny for a non-trivial class of instances. It is based on a novel connection between the syntenic distance and a scheduling problem that has been studied in the operations research literature.     

同步辐射小角x射线散射方法研究由城市固体垃圾制备的活性炭

应用同步辐射小角x射线散射方法研究了由不同城市固体垃圾制备而成的活性炭的孔结构-结果发现利用木类、纸张、塑料这三类典型垃圾组分的热解残余物为原料制备中孔发达的活性炭是可行的-活性炭的形态和结构取决于垃圾热解残余物的组分和热解程度等因素- 关键词： 小角x射线散射 活性炭 分形维数 平均孔径     

10瓦级双包层光纤激光器

考虑到所用大功率激光二极管的光谱特性，对光纤激光器的基本法布里-珀罗腔型稍加改变，研制出激光二极管抽运的10w级双包层光纤激光器，获得最高功率为11．8w、波长1100mm的单模激光输出。     

A strong law of large numbers for generalized random sets from the viewpoint of empirical processes

In this article we prove a strong law of large numbers for Borel measurable nonseparably valued random elements in the case of generalized random sets.

     

Classical Limit of Expectation Values in a Wave Packet Involving Few Stationary States

Expectation values of physical quantities in a wave packet involving few stationary states in an infinite square well are calculated. Explicit results show that the expectation values in the classical limit go over to the corresponding classical quantity in the form of the arithmetic mean (in mathematical term, the Fejér's average) of the partial Fourier series converging to the classical quantity. The number of the stationary states is that of the partial Fourer series in the Fejér's average. The quantum uncertainty is then demonstrated to have a classical counterpart.     

Minimum Disparity Estimation in Linear Regression Models: Distribution and Efficiency

This paper deals with the minimum disparity estimation in linear regression models. The estimators are defined as statistical quantities which minimize the blended weight Hellinger distance between a weighted kernel density estimator of errors and a smoothed model density of errors. It is shown that the estimators of the regression parameters are asymptotic normally distributed and efficient at the model if the weights of the density estimators are appropriately chosen.