1,721,049 research outputs found
EFFECTS OF ACUTE AND CHRONIC STRESS AND OF GENOTYPE ON OXOTREMORINE-INDUCED LOCOMOTOR DEPRESSION OF MICE
The locomotor behavior of unstressed and stressed mice of two inbred strains, DBA/2 and C57/BL6, was investigated. Animals were tested in a toggle-floor box apparatus, 30 min after saline or oxotremorine treatment (ip). A dose of oxotremorine that did not depress the activity of naive mice (0.01 mg/kg) was chosen. Stressed mice were injected 24 h after either a single 2-h stress session (acute stress) or the last of 14 daily stress sessions of tube restraining (chronic stress). Acute stress did not modify the depressant effect of oxotremorine on locomotor behavior in either strain. On the contrary, chronic stress induced a clear sensitization of DBA but not C57 mice to the depressant effect of oxotremorine. These findings show that chronic stress may result in modifications of the cholinergic function, and its behavioral correlates, and that these changes are modulated by the genetic makeup
Universality of the off-equilibrium response function in the kinetic Ising chain
The off-equilibrium response function X(t,tw) and autocorrelation function C(t,tw) of an Ising chain with spin-exchange dynamics are studied numerically and compared with the same quantities in the case of spin-flip dynamics. It is found that, even though these quantities are different in the two cases, the parametric plot of X(t,tw) versus C(t,tw) is the same. While this result could be expected in higher dimensionality, where X(C) is related to the equilibrium state, it is far from trivial in the one-dimensional case where this relation does not hold. The origin of the universality of X(C) is traced back to the optimization of domains position with respect to the perturbing external field. This mechanism is investigated resorting to models with a single domain moving in a random environment. ©2002 The American Physical Society
Optimal quantum key distribution networks: capacitance versus security
The rate and security of quantum communications between users placed at arbitrary points of a quantum communication network depend on the structure of the network, on its extension and on the nature of the communication channels. In this work we propose a strategy for the optimization of trusted-relays based networks that intertwines classical network approaches and quantum information theory. Specifically, by suitably defining a quantum communication efficiency functional, we identify the optimal quantum communication connections through the network by balancing security and the quantum communication rate. The optimized network is then constructed as the network of the maximal quantum communication efficiency connections and its performance is evaluated by studying the scaling of average properties as functions of the number of nodes and of the network spatial extension
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Scaling and universality for percolation in random networks: a unified view
Percolation processes on random networks have been the subject of intense research activity over the last decades: the overall phenomenology of standard percolation on uncorrelated and unclustered topologies is well known. Still some critical properties of the transition, in particular for heterogeneous substrates, have not been fully elucidated and contradictory results appear in the literature. In this paper we present, by means of a generating functions approach, a thorough and complete investigation of percolation critical properties in uncorrelated locally treelike random networks. We determine all critical exponents, the associated critical amplitude ratios, and the form of the cluster size distribution for networks of any level of heterogeneity. We uncover, in particular for highly heterogeneous networks, subtle crossover phenomena, nontrivial scaling forms, and violations of hyperscaling. In this way we clarify the origin of inconsistencies in the previous literature
General theory for extended-range percolation on simple and multiplex networks
Extended-range percolation is a robust percolation process that has relevance for quantum communication problems. In extended-range percolation nodes can be trusted or untrusted. Untrusted facilitator nodes are untrusted nodes that can still allow communication between trusted nodes if they lie on a path of distance at most between two trusted nodes. In extended-range percolation the extended-range giant component (ERGC) includes trusted nodes connected by paths of trusted and untrusted facilitator nodes. Here, based on a message-passing algorithm, we develop a general theory of extended-range percolation, valid for arbitrary values of as long as the networks are locally treelike. This general framework allows us to investigate the properties of extended-range percolation on interdependent multiplex networks. While the extended-range nature makes multiplex networks more robust, interdependency makes them more fragile. From the interplay between these two effects a rich phase diagram emerges including discontinuous phase transitions and reentrant phases. The theoretical predictions are in excellent agreement with extensive Monte Carlo simulations. The proposed exactly solvable model constitutes a fundamental reference for the study of models defined through properties of extended-range paths
Emergence of polarization in a voter model with personalized information
The flourishing of fake news is supported by recommendation algorithms of online social networks, which, based on previous user activity, provide content adapted to their preferences and so create filter bubbles. We introduce an analytically tractable voter model with personalized information, in which an external field tends to align the agent's opinion with the one she held more frequently in the past. Our model shows a surprisingly rich dynamics despite its simplicity. An analytical mean-field approach, confirmed by numerical simulations, allows us to build a phase diagram and to predict if and how consensus is reached. Remarkably, polarization can be avoided only for weak interaction with personalized information and if the number of agents is below a threshold. We compute analytically this critical size, which depends on the interaction probability in a strongly nonlinear way
Extended-range percolation in complex networks
Classical percolation theory underlies many processes of information transfer
along the links of a network. In these standard situations, the requirement for
two nodes to be able to communicate is the presence of at least one
uninterrupted path of nodes between them. In a variety of more recent data
transmission protocols, such as the communication of noisy data via
error-correcting repeaters, both in classical and quantum networks, the
requirement of an uninterrupted path is too strict: two nodes may be able to
communicate even if all paths between them have interruptions/gaps consisting
of nodes that may corrupt the message. In such a case a different approach is
needed. We develop the theoretical framework for extended-range percolation in
networks, describing the fundamental connectivity properties relevant to such
models of information transfer. We obtain exact results, for any range , for
infinite random uncorrelated networks and we provide a message-passing
formulation that works well in sparse real-world networks. The interplay of the
extended range and heterogeneity leads to novel critical behavior in scale-free
networks.Comment: 5 pages, 3 figures + appendice
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