1000 resultados para Communication Robustness


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Aquest document se centra en els casos dels dos principals partits espanyols (PP i PSOE) i catalans (PSC i CDC) en el període immediatament després de les eleccions generals espanyoles de maig de 2008, quan aquests celebraren els seus congressos. En general, es poden distingir tres tipus d'actors: en primer lloc, els ciberactivistes que tracten d'obtenir el reconeixement formal de la seva activitat en els seus partits. Així com, els líders del partit que poden intentar promoure la presència del partit en el ciberespai, però que també poden romandre indecisos perquè no és clar l'impacte electoral a la xarxa del ciberactivisme. Finalment, alguns militants tradicionals (off-line) solen ser reticents al reconeixement del ciberactivisme perquè amenaça les recompenses previstes dins del partit. Aquest article mostra com els nostres partits varen respondre al desafiament del ciberactivisme i arriba a la conclusió que la seva situació electoral, mediada per la seva ideologia, estructura organitzativa i el tipus de militància, poden ajudar-nos a comprendre el grau diferent d'institucionalització en l'organització del partit.

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MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

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Conflicts among siblings are widespread and their resolution involves complex physical and communication tools. Observations in the barn owl Tyto alba showed that siblings vocally communicate in the absence of parents to negotiate priority of access to the impending food resources that parents will bring. In the present paper, we hypothesize and provide correlative evidence that after a parent brought a food item to their progeny, sibling competition involves vocal sib-sib communication. A food item takes a long time to be entirely consumed, and hence siblings continue to compete over prey monopolization even after parents gave a food item to a single offspring. When physical competition is pronounced and thereby the risk of prey theft is high, the individual that received a prey item consumes it in a concealed place. Concomitantly, nestlings vocalize intensely probably to indicate their motivation to siblings to not share their food item, since this vocal behaviour was particularly frequent in younger individuals for which the risk of being robbed is higher than in their older siblings. Furthermore, nestlings consumed more rapidly a food item when their siblings vocalized intensely presumably because the intensity of siblings' vocalizations is associated with a risk of prey theft. Our correlative study suggests that sibling competition favoured the evolution of sib-sib communication under a wide range of situations.