A combinatorial approach to discrete geometry

We present a paralell approach to discrete geometry: the first one introduces Voronoi cell complexes from statistical tessellations in order to know the mean scalar curvature in term of the mean number of edges of a cell. The second one gives the restriction of a graph from a regular tessellation in order to calculate the curvature from pure combinatorial properties of the graph. Our proposal is based in some epistemological pressupositions: the macroscopic continuous geometry is only a fiction, very usefull for describing phenomena at certain sacales, but it is only an approximation to the true geometry. In the discrete geometry one starts from a set of elements and the relation among them without presuposing space and time as a background.Comment: LaTeX, 5 pages with 3 figures. To appear in the Proceedings of the XXVIII Spanish Relativity Meeting (ERE2005), 6-10 September 2005, Oviedo, Spai

Representations of the discrete inhomogeneous Lorentz group and Dirac wave equation on the lattice

We propose the fundamental and two dimensional representation of the Lorentz groups on a (3+1)-dimensional hypercubic lattice, from which representations of higher dimensions can be constructed. For the unitary representation of the discrete translation group we use the kernel of the Fourier transform. From the Dirac representation of the Lorentz group (including reflections) we derive in a natural way the wave equation on the lattice for spin 1/2 particles. Finally the induced representation of the discrete inhomogeneous Lorentz group is constructed by standard methods and its connection with the continuous case is discussed.Comment: LaTeX, 20 pages, 1 eps figure, uses iopconf.sty (late submission

New Prognostic Biomarkers in Patients With Traumatic Brain Injury

Context: Traumatic brain injury (TBI) is a leading cause of death, disability, and resource consumption per year. There are two kinds of brain injury in TBI, primary and secondary injuries. Primary injury refers to the initial physical forces applied to the brain at the moment of impact. Secondary injury occurs over a period of hours or days following the initial trauma and results from the activation of different pathways such as inflammation, coagulation, oxidation, and apoptosis. Evidence Acquisition: This review focuses on new prognostic biomarkers of mortality in TBI patients related to inflammation, coagulation, oxidation, and apoptosis. Results: Recently circulating levels of substance P (SP), soluble CD40 ligand (sCD40L), tissue inhibitor of matrix metalloproteinases (TIMP)-1, malondialdehyde (MDA), and cytokeratin (CK)-18 fragmented have been found to be associated with mortality in TBI patients. Substance P is a neuropeptide of the tachykinin family, mainly synthesized in the central and peripheral nervous system, with proinflammatory effects when binding to their neurokinin-1 receptor (NK1R). Soluble CD40 ligand, a member of the tumor necrosis factor (TNF) family that is released into circulation from activated platelets, exhibit proinflamatory, and procoagulant properties on binding to their cell surface receptor CD40. Matrix metalloproteinases (MMPs) are a family of zinc-containing endoproteinases involved neuroinflammation and TIMP-1 is the inhibitor of some of them. Malondialdehyde is an end-product formed during lipid peroxidation due to degradation of cellular membrane phospholipids, that is released into extracellular space and finally into the blood. Cytokeratin -18 is cleaved by the action of caspases during apoptosis, and CK-18 fragmented is released into the blood. Conclusions: Circulating levels of some biomarkers, such as SP, sCD40L, TIMP-1, MDA, and CK-18 fragmented, related to inflammation, coagulation, oxidation, and apoptosis have been recently associated with mortality in patients with TBI. These biomarkers could help in the prognostic classification of the patients and open new research lines in the treatment of patients with TBI

Model-based robocentric planning and navigation for dynamic environments

This work addresses a new technique of motion planning and navigation for differential-drive robots in dynamic environments. Static and dynamic objects are represented directly on the control space of the robot, where decisions on the best motion are made. A new model representing the dynamism and the prediction of the future behavior of the environment is defined, the dynamic object velocity space (DOVS). A formal definition of this model is provided, establishing the properties for its characterization. An analysis of its complexity, compared with other methods, is performed. The model contains information about the future behavior of obstacles, mapped on the robot control space. It allows planning of near-time-optimal safe motions within the visibility space horizon, not only for the current sampling period. Navigation strategies are developed based on the identification of situations in the model. The planned strategy is applied and updated for each sampling time, adapting to changes occurring in the scenario. The technique is evaluated in randomly generated simulated scenarios, based on metrics defined using safety and time-to-goal criteria. An evaluation in real-world experiments is also presented

A hierarchical scheduling model for component-based real-time systems

In this paper, we propose a methodology for developing component-based real-time systems based on the concept of hierarchical scheduling. Recently, much work has been devoted to the schedulability analysis of hierarchical scheduling systems, in which real-time tasks are grouped into components, and it is possible to specify a different scheduling policy for each component. Until now, only independent components have been considered. In this paper, we extend this model to tasks that interact through remote procedure calls. We introduce the concept of abstract computing platform on which each component is executed. Then, we transform the system specification into a set of real-time transactions and present a schedulability analysis algorithm. Our analysis is a generalization of the holistic analysis to the case of abstract computing platforms. We demonstrate the use of our methodology on a simple example