Geometry-Experiment Algorithm for Steiner Minimal Tree Problem

It is well known that the Steiner minimal tree problem is one of the classical nonlinear combinatorial optimization problems. A visualization experiment approach succeeds in generating Steiner points automatically and showing the system shortest path, named Steiner minimum tree, physically and intuitively. However, it is difficult to form stabilized system shortest path when the number of given points is increased and irregularly distributed. Two algorithms, geometry algorithm and geometry-experiment algorithm (GEA), are constructed to solve system shortest path using the property of Delaunay diagram and basic philosophy of Geo-Steiner algorithm and matching up with the visualization experiment approach (VEA) when the given points increase. The approximate optimizing results are received by GEA and VEA for two examples. The validity of GEA was proved by solving practical problems in engineering, experiment, and comparative analysis. And the global shortest path can be obtained by GEA successfully with several actual calculations

Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal's conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations

Sobre o problema Euclidiano de Steiner no Rn

The Euclidean Steiner Problem (ESP) asks for a network of minimum length interconnecting a finite set of given points in Rn. The distances considered are Euclidean and it’s allowed to add additional points to decrease the overall length of the network. Problems of this nature are often found in several areas of mathematics, engineering, etc. In this work, we study the origins of ESP, their properties, complexity, and resolution methods. We conclude by analyzing a conjecture proposed in 1992 by Warren Smith on the application of this problem to the vertices of an n-dimensional hypercube, which has remained open since its publication.O Problema Euclidiano de Steiner (PES) tem como objetivo determinar uma rede de comprimento mínimo que conecte um conjunto finito de pontos do Rn previamente escolhidos. A norma utilizada é a euclidiana e é permitido o uso de pontos extras que possam contribuir para a redução do comprimento final da rede. Problemas desta natureza são frequentemente encontrados em diversas áreas da matemática, engenharia, etc. Neste trabalho, estudamos as origens do PES, suas propriedades, complexidade e métodos de resolução. Encerramos analisando uma conjectura proposta em 1992 por Warren Smith sobre a aplicação desse problema aos vértices de um hipercubo n-dimensional, a qual está em aberto desde sua publicação