Showing papers by "Cornel Sultan published in 2006"
TL;DR: In this article, a set of waypoints through which these trajectories pass and assuming that the trajectories are piecewise cubic polynomials are assumed to have a quasi-quadratic structure in the waypointsparameters are introduced.
Abstract: ThisNotepresentsamethodforthegenerationofenergysuboptimal,collision-free, reconfiguration trajectories for formations flying in deep space(gravity-free environment). The main idea is to introduce a set ofwaypoints through which these trajectories pass and to assume thatthe trajectories are piecewise cubic polynomials. The resulting op-timization problem has a quasi-quadratic structure in the waypointsparameters.Gradient-basedalgorithms,whichexploitthisstructure,are developed for the solution. Examples show that this methodol-ogy is very efficient and fast.
10 citations
01 Dec 2006
TL;DR: The paper traces down the roots of the first man-made objects which resemble what are nowadays known as tensegrity structures and then shows how the tenseGrity concept evolved, finding increasingly large audiences in engineering, mathematics, and biology.
Abstract: The paper traces down the roots of the first man made objects which resemble what are nowadays known as tensegrity structures and then shows how the tensegrity concept evolved, finding increasingly large audiences in engineering, mathematics, and biology.
8 citations
01 Jan 2006
TL;DR: This chapter describes how structural networks built using the principles of tensegrity architecture and computational models that incorporate these features can predict many of the complex mechanical behaviors that are exhibited by living mammalian cells and discusses how genome-wide biochemical signaling networks produce “attractor” states that may represent the stable cell phenotypes.
Abstract: The genomic revolution has led to the systematic characterization of all the genes of the genome and the proteins they encode. But we still do not fully understand how many cell behaviors are controlled, because many important biological properties of cells emerge at the whole-system level from the collective action of thousands of molecular components, which is orchestrated through specific regulatory interactions. In this chapter we present two distinct approaches based on the concept of molecular networks to understand two fundamental system properties of living cells: their ability to maintain their shape and mechanical stability, and their ability to express stable, discrete cell phenotypes and switch between them. We first describe how structural networks built using the principles of tensegrity architecture and computational models that incorporate these features can predict many of the complex mechanical behaviors that are exhibited by living mammalian cells. We then discuss how genome-wide biochemical signaling networks produce “attractor” states that may represent the stable cell phenotypes, such as growth, differentiation, and apoptosis, and which explain how cells can make discrete cell fate decisions in the presence of multiple conflicting signals. These network-based concepts help to bridge the apparent gap between emergent system features characteristic of living cells and the underlying molecular processes.
8 citations