到三定点相对距离的和等于定数的点的轨迹

本文研究了相对测度空间中的距离问题. 利用质点几何的理论方法获得如下结果:对任意给定的实数, 满足条件dT (P,A) + dT (P,B) + dT (P,C) =τ的点P的轨迹是凸十二边形或九边形(其中T:=ABC 是由给定的不同三点A, B, C构成的三角形), 所得结果丰富了相对距离研究领域的内容.     

Steiner centers and Steiner medians of graphs

Let G be a connected graph and S a set of vertices of G. The Steiner distance of S is the smallest number of edges in a connected subgraph of G that contains S and is denoted by d_G(S) or d(S). The Steiner n-eccentricity e_n(v) and Steiner n-distance d_n(v) of a vertex v in G are defined as e_n(v)=max{d(S)| SV(G), |S|=n and vS} and d_n(v)=∑{d(S)| SV(G), |S|=n and vS}, respectively. The Steiner n-center C_n(G) of G is the subgraph induced by the vertices of minimum n-eccentricity. The Steiner n-median M_n(G) of G is the subgraph induced by those vertices with minimum Steiner n-distance. Let T be a tree. Oellermann and Tian [O.R. Oellermann, S. Tian, Steiner centers in graphs, J. Graph Theory 14 (1990) 585–597] showed that C_n(T) is contained in C_n+1(T) for all n2. Beineke et al. [L.W. Beineke, O.R. Oellermann, R.E. Pippert, On the Steiner median of a tree, Discrete Appl. Math. 68 (1996) 249–258] showed that M_n(T) is contained in M_n+1(T) for all n2. Then, Oellermann [O.R. Oellermann, On Steiner centers and Steiner medians of graphs, Networks 34 (1999) 258–263] asked whether these containment relationships hold for general graphs. In this note we show that for every n2 there is an infinite family of block graphs G for which C_n(G)C_n+1(G). We also show that for each n2 there is a distance–hereditary graph G such that M_n(G)M_n+1(G). Despite these negative examples, we prove that if G is a block graph then M_n(G) is contained in M_n+1(G) for all n2. Further, a linear time algorithm for finding the Steiner n-median of a block graph is presented and an efficient algorithm for finding the Steiner n-distances of all vertices in a block graph is described.     

A central limit theorem for normalized products of random matrices

This note concerns the asymptotic behavior of a Markov process obtained from normalized products of independent and identically distributed random matrices. The weak convergence of this process is proved, as well as the law of large numbers and the central limit theorem. This work was supported by the PSF Organization under Grant No. 2005-7-02, and by the Consejo Nacional de Ciencia y Tecnología under Grants 25357 and 61423.     

Accuracy of approximation in the Poisson theorem in terms of the χ<Superscript>2</Superscript>-distance

We study the limit behavior of the χ²-distance between the distributions of the nth partial sum of independent not necessarily identically distributed Bernoulli random variables and the accompanying Poisson law. As a consequence in the i.i.d. case we make the multiplicative constant preciser in the available upper bound for the rate of convergence in the Poisson limit theorem.     

The Intrinsic Diameter of the Surface of a Parallelepiped

In the paper we obtain an explicit formula for the intrinsic diameter of the surface of a rectangular parallelepiped in 3-dimensional Euclidean space. As a consequence, we prove that an parallelepiped with relation for its edge lengths has maximal surface area among all rectangular parallelepipeds with given intrinsic diameter.     

Characterization of crystal structure in binary mixtures of latex globules

Colloidal crystals formed by two types of polystyrene particles of different sizes (94 and 141 nm) at various number ratios (94:141 nm) are studied. Experiments showed that the formation time of crystals lengthens as the number ratio of the two components approaches 1:1. The dependence of the mean interparticle distance (D₀), crystal structure and alloy structure on the number ratio of the two types of particles was studied by means of Kossel diffraction technique and reflection spectra. The results showed that as the number ratio decreased, the mean interparticle distance (D₀) became larger. And the colloidal crystal in binary mixtures is more preferably to form the bcc structure. This study found that binary systems form the substitutional solid solution (sss)-type alloy structure in all cases except when the number ratio of two types of particles is 5:1, which results instead in the superlattice structure.     

Planar Location Problems with Block Distance and Barriers

This paper considers one facility planar location problems using block distance and assuming barriers to travel. Barriers are defined as generalized convex sets relative to the block distance. The objective function is any convex, nondecreasing function of distance. Such problems have a non-convex feasible region and a non-convex objective function. The problem is solved by modifying the barriers to obtain an equivalent problem and by decomposing the feasible region into a polynomial number of convex subsets on which the objective function is convex. It is shown that solving a planar location problem with block distance and barriers requires at most a polynomial amount of additional time over solving the same problem without barriers.     

On the Mean Distance in Scale Free Graphs

We consider a graph, where the nodes have a pre-described degree distribution F, and where nodes are randomly connected in accordance to their degree. Based on a recent result (R. van der Hofstad, G. Hooghiemstra and P. Van Mieghem, “Random graphs with finite variance degrees,” Random Structures and Algorithms, vol. 17(5) pp. 76–105, 2005), we improve the approximation of the mean distance between two randomly chosen nodes given by M. E. J. Newman, S. H. Strogatz, and D. J. Watts, “Random graphs with arbitrary degree distribution and their application,” Physical Review. E vol. 64, 026118, pp. 1–17, 2001. Our new expression for the mean distance involves the expectation of the logarithm of the limit of a super-critical branching process. We compare simulations of the mean distance with the results of Newman et al. and with our new approach. AMS 2000 Subject Classification: 05C80, 60F05     

Codes from Affine Permutation Groups

It is shown that A(22,10) 50, A(23,10) 76, A(25,10) 166, A(26,10) 270, A(29,10) 1460, and A(28,12) 178, where A(n,d) denotes the maximum cardinality of a binary code of length n and minimum Hamming distance d. The constructed codes are invariant under permutations of some affine (or closely related) permutation group and have been found using computer search.