2,705 research outputs found
The influence of persuasion in opinion formation and polarization
We present a model that explores the influence of persuasion in a population
of agents with positive and negative opinion orientations. The opinion of each
agent is represented by an integer number that expresses its level of
agreement on a given issue, from totally against to totally in favor
. Same-orientation agents persuade each other with probability ,
becoming more extreme, while opposite-orientation agents become more moderate
as they reach a compromise with probability . The population initially
evolves to (a) a polarized state for , where opinions' distribution is
peaked at the extreme values , or (b) a centralized state for ,
with most opinions around . When , polarization lasts for a
time that diverges as , where is the population's size. Finally,
an extremist consensus ( or ) is reached in a time that scales as
for
Interacting social processes on interconnected networks
We propose and study a model for the interplay between two different
dynamical processes --one for opinion formation and the other for decision
making-- on two interconnected networks and . The opinion dynamics on
network corresponds to that of the M-model, where the state of each agent
can take one of four possible values (), describing its level of
agreement on a given issue. The likelihood to become an extremist ()
or a moderate () is controlled by a reinforcement parameter .
The decision making dynamics on network is akin to that of the
Abrams-Strogatz model, where agents can be either in favor () or against
() the issue. The probability that an agent changes its state is
proportional to the fraction of neighbors that hold the opposite state raised
to a power . Starting from a polarized case scenario in which all agents
of network hold positive orientations while all agents of network have
a negative orientation, we explore the conditions under which one of the
dynamics prevails over the other, imposing its initial orientation. We find
that, for a given value of , the two-network system reaches a consensus
in the positive state (initial state of network ) when the reinforcement
overcomes a crossover value , while a negative consensus happens
for . In the phase space, the system displays a
transition at a critical threshold , from a coexistence of both
orientations for to a dominance of one orientation for
. We develop an analytical mean-field approach that gives an
insight into these regimes and shows that both dynamics are equivalent along
the crossover line .Comment: 25 pages, 6 figure
Synchronization in interacting Scale Free Networks
We study the fluctuations of the interface, in the steady state, of the
Surface Relaxation Model (SRM) in two scale free interacting networks where a
fraction of nodes in both networks interact one to one through external
connections. We find that as increases the fluctuations on both networks
decrease and thus the synchronization reaches an improvement of nearly
when . The decrease of the fluctuations on both networks is due mainly to
the diffusion through external connections which allows to reducing the load in
nodes by sending their excess mostly to low-degree nodes, which we report have
the lowest heights. This effect enhances the matching of the heights of low-and
high-degree nodes as increases reducing the fluctuations. This effect is
almost independent of the degree distribution of the networks which means that
the interconnection governs the behavior of the process over its topology.Comment: 13 pages, 7 figures. Added a relevant reference.Typos fixe
Recovery of Interdependent Networks
Recent network research has focused on the cascading failures in a system of
interdependent networks and the necessary preconditions for system collapse. An
important question that has not been addressed is how to repair a failing
system before it suffers total breakdown. Here we introduce a recovery strategy
of nodes and develop an analytic and numerical framework for studying the
concurrent failure and recovery of a system of interdependent networks based on
an efficient and practically reasonable strategy. Our strategy consists of
repairing a fraction of failed nodes, with probability of recovery ,
that are neighbors of the largest connected component of each constituent
network. We find that, for a given initial failure of a fraction of
nodes, there is a critical probability of recovery above which the cascade is
halted and the system fully restores to its initial state and below which the
system abruptly collapses. As a consequence we find in the plane of
the phase diagram three distinct phases. A phase in which the system never
collapses without being restored, another phase in which the recovery strategy
avoids the breakdown, and a phase in which even the repairing process cannot
avoid the system collapse
Evolution equation for a model of surface relaxation in complex networks
In this paper we derive analytically the evolution equation of the interface
for a model of surface growth with relaxation to the minimum (SRM) in complex
networks. We were inspired by the disagreement between the scaling results of
the steady state of the fluctuations between the discrete SRM model and the
Edward-Wilkinson process found in scale-free networks with degree distribution
for [Pastore y Piontti {\it et al.},
Phys. Rev. E {\bf 76}, 046117 (2007)]. Even though for Euclidean lattices the
evolution equation is linear, we find that in complex heterogeneous networks
non-linear terms appear due to the heterogeneity and the lack of symmetry of
the network; they produce a logarithmic divergency of the saturation roughness
with the system size as found by Pastore y Piontti {\it et al.} for .Comment: 9 pages, 2 figure
Spin-dependent resonant tunneling in semiconductor nanostructures
The spin-dependent quantum transport of electrons in non magnetic III-V semiconductor nanos-tructures is studied theoretically within the envelope function approximation and the Kane model for the bulk. It is shown that an unpolarized beam of conducting electrons can be strongly polarized in zero magnetic field by resonant tunneling across asymmetric double-barrier structures, as an effect of the spin-orbit interaction. The electron transmission probability is calculated as a function of energy and angle of incidence. Specific results for tunneling across lattice matched politype Ga0.47In0.53As / InP/Ga0.47In0.53As / GaAs0.5Sb0.5 / Ga0.47In0.53 As double barrier heterostructures show sharp spin split resonances, corresponding to resonant tunneling through spin-orbit split quasi-bound electron states. The polarization of the transmitted beam is also calculated and is shown to be over 50%
Topological Dirac states in asymmetric Pb1-xSnxTe quantum wells
The electronic structure of lead-salt (IV-VI semiconductor) topological
quantum wells (T-QWs) is investigated with analytical solutions of the
effective 4x4 Dimmock k & BULL; p model, which gives an accurate
description of the bands around the fundamental energy gap. Specific
results for three-layer Pb1-xSnxTe nanostructures with varying Sn
composition are presented and the main differences between topological
and normal (N) QWs highlighted. A series of new features are found in
the spectrum of T-QWs, in particular in asymmetric QWs where large
(Rashba spin-orbit) splittings are obtained for the topological Dirac
states inside the gap
Synchronization in Scale Free networks: The role of finite size effects
Synchronization problems in complex networks are very often studied by
researchers due to its many applications to various fields such as
neurobiology, e-commerce and completion of tasks. In particular, Scale Free
networks with degree distribution , are widely used in
research since they are ubiquitous in nature and other real systems. In this
paper we focus on the surface relaxation growth model in Scale Free networks
with , and study the scaling behavior of the fluctuations, in
the steady state, with the system size . We find a novel behavior of the
fluctuations characterized by a crossover between two regimes at a value of
that depends on : a logarithmic regime, found in previous
research, and a constant regime. We propose a function that describes this
crossover, which is in very good agreement with the simulations. We also find
that, for a system size above , the fluctuations decrease with
, which means that the synchronization of the system improves as
increases. We explain this crossover analyzing the role of the
network's heterogeneity produced by the system size and the exponent of the
degree distribution.Comment: 9 pages and 5 figures. Accepted in Europhysics Letter
Umbilical Cord Mesenchymal Stromal Cells for Cartilage Regeneration Applications
Chondropathies are increasing worldwide, but effective treatments are currently lacking. Mesenchymal stromal cell (MSCs) transplantation represents a promising approach to counteract the degenerative and inflammatory environment characterizing those pathologies, such as osteoarthritis (OA) and rheumatoid arthritis (RA). Umbilical cord-(UC-) MSCs gained increasing interest due to their multilineage differentiation potential, immunomodulatory, and anti-inflammatory properties as well as higher proliferation rates, abundant supply along with no risks for the donor compared to adult MSCs. In addition, UC-MSCs are physiologically adapted to survive in an ischemic and nutrient-poor environment as well as to produce an extracellular matrix (ECM) similar to that of the cartilage. All these characteristics make UC-MSCs a pivotal source for a stem cell-based treatment of chondropathies. In this review, the regenerative potential of UC-MSCs for the treatment of cartilage diseases will be discussed focusing on in vitro, in vivo, and clinical studies
Using relaxational dynamics to reduce network congestion
We study the effects of relaxational dynamics on congestion pressure in scale
free networks by analyzing the properties of the corresponding gradient
networks (Z. Toroczkai, K. E. Bassler, Nature {\bf 428}, 716 (2004)). Using the
Family model (F. Family, J. Phys. A, {\bf 19}, L441 (1986)) from surface-growth
physics as single-step load-balancing dynamics, we show that the congestion
pressure considerably drops on scale-free networks when compared with the same
dynamics on random graphs. This is due to a structural transition of the
corresponding gradient network clusters, which self-organize such as to reduce
the congestion pressure. This reduction is enhanced when lowering the value of
the connectivity exponent towards 2.Comment: 10 pages, 6 figure
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