Graph Transformations and Game Theory: A Generative Mechanism for Network Formation

Many systems can be described in terms of networks with characteristic structural properties. To better understand the formation and the dynamics of complex networks one can develop generative models. We propose here a generative model (named dynamic spatial game) that combines graph transformations and game theory. The idea is that a complex network is obtained by a sequence of node-based transformations determined by the interactions of nodes present in the network. We model the node-based transformations by using graph grammars and the interactions between the nodes by using game theory. We illustrate dynamic spatial games on a couple of examples: the role of cooperation in tissue formation and tumor development and the emergence of patterns during the formation of ecological networks

Evolution-Communication P Systems: Time-Freeness

Membrane computing is a (biologically motivated) theoretical framework of distributed parallel computing. If symbol-objects are considered, then membrane sys- tems (also called P systems) are distributed multiset processing systems. In evolution- communication (EC) P systems the computation is carried out with the use of non- cooperative rewriting rules and with (usually the minimally cooperative) transport rules. The goal of this article is to improve the existing results on evolution-communication P systems. It is known that EC P systems with 2 membranes are universal, and so are time-free EC P systems with targets with 3 membranes. We prove that any recursively enumerable set of vectors of nonnegative integers can be generated by time-free EC P systems (without targets) with 2 membranes, thus improving both results

P Systems with Symport/Antiport of Rules

Moving \instructions" instead of \data", using transport mecha- nisms inspired by biology { this could represent, shortly, the basic idea of the computing device presented in this paper. Speci¯cally, we propose a new class of P systems that use, at the same time, evolution rules and symport/antiport rules. The idea of this kind of systems is simple: during a computation symbol- objects (the \data") evolve using evolution rules but they cannot be moved; on the other hand, the evolution rules (the \instructions") can be moved across the membranes using classical symport/antiport rules. We present di®erent results using di®erent combinations between the power of the evolution rules (catalytic, non-cooperative rules) and the weight of the symport/antiport rules. In particular, we show that, using non-cooperative rules and antiports of un- bounded weight is possible to obtain at least the Parikh set of ET0L languages. On the other hand, using catalytic rules (one catalyst) and antiports of weight 2, the system becomes universal. Several open problems are also presented

Guidelines for Reprocessing Non-Lumened, Heat-Sensitive ENT Endoscopes

Endoscopes have become an indispensable instrument in the ENT department, but their use has introduced potential health risks such as the infection transmission

Coulomb blockade microscopy of spin density oscillations and fractional charge in quantum spin Hall dots

We evaluate the spin density oscillations arising in quantum spin Hall quantum dots created via two localized magnetic barriers. The combined presence of magnetic barriers and spin-momentum locking, the hallmark of topological insulators, leads to peculiar phenomena: a half-integer charge is trapped in the dot for antiparallel magnetization of the barriers, and oscillations appear in the in-plane spin density, which are enhanced in the presence of electron interactions. Furthermore, we show that the number of these oscillations is determined by the number of particles inside the dot, so that the presence or the absence of the fractional charge can be deduced from the in-plane spin density. We show that when the dot is coupled with a magnetized tip, the spatial shift induced in the chemical potential allows to probe these peculiar features.Comment: 6 pages, 6 figure

Non-equilibrium effects on charge and energy partitioning after an interaction quench

Charge and energy fractionalization are among the most intriguing features of interacting onedimensional fermion systems. In this work we determine how these phenomena are modified in the presence of an interaction quench. Charge and energy are injected into the system suddenly after the quench, by means of tunneling processes with a non-interacting one-dimensional probe. Here, we demonstrate that the system settles to a steady state in which the charge fractionalization ratio is unaffected by the pre-quenched parameters. On the contrary, due to the post-quench nonequilibrium spectral function, the energy partitioning ratio is strongly modified, reaching values larger than one. This is a peculiar feature of the non-equilibrium dynamics of the quench process and it is in sharp contrast with the non-quenched case, where the ratio is bounded by one.Comment: 12 pages, 4 figure

Factor Network Autoregressions

We propose a factor network autoregressive (FNAR) model for time series with complex network structures. The coefficients of the model reflect many different types of connections between economic agents ("multilayer network"), which are summarized into a smaller number of network matrices ("network factors") through a novel tensor-based principal component approach. We provide consistency results for the estimation of the factors and the coefficients of the FNAR. Our approach combines two different dimension-reduction techniques and can be applied to ultra-high dimensional datasets. In an empirical application, we use the FNAR to investigate the cross-country interdependence of GDP growth rates based on a variety of international trade and financial linkages. The model provides a rich characterization of macroeconomic network effects and exhibits good forecast performance compared to popular dimension-reduction methods

Computing Using Signals: From Cells to P Systems

In cell biology one of the fundamental topic is the study of how biological signals are managed by cells. Signals can arise from inside the cell or from the external environment and the correct answer to certain signals is essential for bacteria to survive in a certain environment. Starting from these biological motivations we consider a model of P systems where the computa- tion is controlled by signals which move across the regions. In particular, we consider Signals-Based P systems where the symbol-objects cannot be moved and the rules can be activated/inactivated using a ¯nite number of signals (signal-promoters) moved across the membranes; di®erently from standard P systems using promoters, in our case promoters cannot be created during the computation. After discussing the biological motivations we show how this model becomes universal when it uses one catalyst, and a bounded number of signal-promoters

Partial Knowledge in Membrane Systems: A Logical Approach

Abstract. We propose a logic for specifying and proving properties of membrane systems. The main idea is to approach a membrane system by using the “point of view ” of an external observer. Observers (as epis-temic agents) accumulate their knowledge from the partial information they collect by observing subparts of the system and by applying logical reasoning to this information. We provide a formal framework to com-bine and interpret distributed knowledge in order to recover the complete knowledge about a membrane system. The proposed logic can be used to model biological situations where information concerning parts of the biological system is missing or incomplete.