A process of rumor scotching on finite populations

Rumor spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumor is propagated by pairwise interactions between spreaders and ignorants. Spreaders can become stiflers only after contacting spreaders or stiflers. Here we propose a model that considers the traditional assumptions, but stiflers are active and try to scotch the rumor to the spreaders. An analytical treatment based on the theory of convergence of density dependent Markov chains is developed to analyze how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can be applied to study systems in which informed agents try to stop the rumor propagation. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumor propagation.Comment: 13 pages, 11 figure

Theoretical and Experimental Analysis of Stability Limits of Non-Axisymmetric Liquid Bridges under Microgravity Conditions

The stability of nonaxisymmetric liquid bridges under microgravity conditions is investigated. The influence on the stability of an almost cylindrical liquid bridge of axisymmetric effects like its volume, a small axial acceleration acting on it, and unequal-diameter supporting disks, as well as that of nonaxisymmetric perturbations like small lateral acceleration and noncoaxial supporting disks, has been analyzed by using standard bifurcation techniques. An expression for the maximum length of a liquid bridge, including all the above-mentioned effects, has been obtained. In addition, the effect on the stability of liquid bridges having noncoaxial supporting disks has been experimentally studied within the constraints of an Earth laboratory by using millimetric liquid bridges. Analytical and experimental results show that each one of the nonaxisymmetric perturbations like the ones here considered (lateral acceleration and eccentricity) can be, from the point of view of stability, as critical as axisymmetric perturbations. In addition, it is demonstrated that when both nonaxisymmetric perturbations are not negligible, the coupling of both perturbations can be a stabilizing effect on the liquid bridg

Origin and role of neural signatures in bursting neurons

Copyright 2007 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.A traditional view in neuroscience is that information arriving through one channel, i.e. a synapse, is encoded through a single code in the signal, e.g., the rate or the precise timing of the incoming events. However, not all the neural readers have to be interested in the same aspect of a common input signal, especially in multifunctional networks that can take advantage of several simultaneous codes. Multiple codes can be used to discriminate or contextualize certain inputs, even in single neurons. Dynamical mechanisms can add to the existing hard-wired connectivity for this task. Recent experiments have revealed the existence of neural signatures in the activity of bursting cells of invertebrate central pattern generators. These signatures consist of cell-specific spike timings in the bursting activity of the neurons. The signatures coexist with the information encoded in the frequency and/or phase relationships of the slow waves. The functional role of these neural fingerprints is still unclear. Based on experiments and using conductance-based models, we discuss the origin and the role of neural signatures as a part of a multicoding strategy for single cells in different types of neural circuits.This work was supported by Fundacion BBVA, MEC BFU2006-07902/BFI and MEC TIN2004-04363-C03-03

Effect of individual spiking activity on rhythm generation of central pattern generators

This is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neurocomputing 58-60 (2004):10.1016/j.neucom.2004.01.091Central Pattern Generators (CPGs) are highly specialized neural networks often with redundant elements that allow the system to act properly in case of error. CPGs are multifunctional circuits, i.e. the same CPG can produce many di®erent rhythms in response to modulatory or sensory inputs. All these rhythms have to be optimal for motor control and coordination. In this paper, we use a model of the well-known pyloric CPG of crustacean to analyze the importance of redundant connections and individual spiking activity in the generation of the CPG rhythm. In particular, we study the e®ect of di®erent spike distributions of a neuron on the collective behavior of the CPG.This work was supported by the Spanish MCyT (BFI-2000- 0157 and TIC 2002-572-C02-02

Design and Manufacturing of an APTF to Test Fluid Behaviour in Microgravity Environment

The present paper deals with the design and manufacturing of an APTF (Advanced Plateau Tank Facility) in order to carrying out earth experiments, previous to space experiments, of fluid behaviour in microgravity environment. This work has been done in collaboration between Manufacturing and Microgravity Laboratories in the Polytechnic University of Madrid, and analyses the requirements and restrictions that must be considered for an APTF design and manufacture. Mechanism employed in each part of the prototype are described in detail, emphasising those that suppose new solutions rather previous designs

On the use of liquid bridges as accelerometers

The shape of the interface of a drop of liquid held by surface tension forces between two solid disks,a liquid bridge, depends on the geometry of the supporting disks, the volume of liquid and the external forces acting on the drop. Therefore, once the geometry of the supporting disks and the volume of liquid are fixed, and assuming that the value of the surface tension is known, a way to measure such external forces could be by measuring the deformation of the liquid bridge interface

Dynamical invariants for CPG control in autonomous robots

This is an electronic version of the paper presented at the 7th International Conference on Informatics in Control, Automation and Robotics, held in Madeira on 2010Several studies have shown the usefulness of central pattern generator circuits to control autonomous rhythmic motion in robots. The traditional approach is building CPGs from nonlinear oscillators, adjusting a connectivity matrix and its weights to achieve the desired function. Compared to existing living CPGs, this approach seems still somewhat limited in resources. Living CPGs have a large number of available mechanisms to accomplish their task. The main function of a CPG is ensuring that some constraints regarding rhythmic activity are always kept, surmounting any disturbances from the external environment. We call this constraints the “dynamical invariant” of a CPG. Understanding the underlying biological mechanisms would take the design of robotic CPGs a step further. It would allow us to begin the design with a set of invariants to be preserved. The presence of these invariants will guarantee that, in response to unexpected conditions, an effective motor program will emerge that will perform the expected function, without the need of anticipating every possible scenario. In this paper we discuss how some bio-inspired elements contribute to building up these invariants.Work supported by MICINN BFU2009-08473, CAM S-SEM-0255-2006 and TIN 2007-65989. Fernando Herrero-Carrón with an FPU-UAM gran

Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Real-time activity-dependent drug microinjection

From Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18–23 July 2009This work was supported by MEC PHB2007-0013TA, BFU2006-07902/BFI, TIN 2007-65989, CAM S-SEM-0255-2006. RDP was supported by the Brazilian agencies: CAPES, CNPq and FAPESP

On-line characterization of transient neuronal activity

Paper presented firstly in a poster at the IV International Conference Net-Works 2011 Complex Networks: Structure, Applications and Related Topics, held in El Escorial (Spain) on October 26th-28th, 2011Characterization and control of nonlinear and non-stationary pro- cesses is an active topic in the field of the applied theory of dynamical systems. In this context classical control techniques cannot be applied straightforward, and thus observation and actuation should be properly incorporated into a real-time feedback (or closed-loop) methodology. One of the possible application scenarios of this methodology is depicted by neural activity. In this work we analyze the problem related to the first component of the real-time closed-loop technology for the case of neural activity. This being the case, be discuss different methods to classify dynamics and to detect events in a automatic and fast way.This work was supported by MICINN BFU2009-08473 and TIN-2010-19607