414 research outputs found
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.
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