2,478 research outputs found
Detecting degree symmetries in networks
The surrounding of a vertex in a network can be more or less symmetric. We
derive measures of a specific kind of symmetry of a vertex which we call degree
symmetry -- the property that many paths going out from a vertex have
overlapping degree sequences. These measures are evaluated on artificial and
real networks. Specifically we consider vertices in the human metabolic
network. We also measure the average degree-symmetry coefficient for different
classes of real-world network. We find that most studied examples are weakly
positively degree-symmetric. The exceptions are an airport network (having a
negative degree-symmetry coefficient) and one-mode projections of social
affiliation networks that are rather strongly degree-symmetric
Psychosocial and educational outcomes of weight faltering in infancy in ALSPAC
OBJECTIVES: To investigate whether infants with weight faltering have impaired psychosocial and educational outcomes in later childhood. DESIGN: Follow-up of infants with weight faltering in a large UK cohort study. SETTING: The Avon Longitudinal Study of Parents and Children (ALSPAC). PARTICIPANTS: 11 534 term infants from ALSPAC with complete weight records. Weight gain (conditional on initial weight) was calculated for three periods: from birth to 8 weeks, 8 weeks to 9 months, and birth to 9 months. Cases of weight faltering were defined as those infants with a conditional weight gain below the 5th centile, and these were compared with the rest of the cohort as the control group. OUTCOMES: Between 6 and 11 years, social, emotional and behavioural development was measured by direct assessment of the children and parental and teacher report. Educational outcomes included Standardised Assessment Test results at 7 and 11 years and Special Educational Needs status at age 11. RESULTS: Differences seen on univariate analysis in attention, non-verbal accuracy, educational attainment and special educational needs became non-significant after adjustment for confounding. Children with weight faltering in infancy did not differ from controls on any measures of self-esteem, peer relationships, experience of bullying, social cognition, antisocial activities, anxiety, depression or behavioural problems. CONCLUSIONS: Weight faltering in early infancy was associated with poorer educational outcomes in later childhood, but these associations were explained by confounding. The subsequent psychosocial development of infants with slow weight gain was not different from that of their peers
Network reachability of real-world contact sequences
We use real-world contact sequences, time-ordered lists of contacts from one
person to another, to study how fast information or disease can spread across
network of contacts. Specifically we measure the reachability time -- the
average shortest time for a series of contacts to spread information between a
reachable pair of vertices (a pair where a chain of contacts exists leading
from one person to the other) -- and the reachability ratio -- the fraction of
reachable vertex pairs. These measures are studied using conditional uniform
graph tests. We conclude, among other things, that the network reachability
depends much on a core where the path lengths are short and communication
frequent, that clustering of the contacts of an edge in time tend to decrease
the reachability, and that the order of the contacts really do make sense for
dynamical spreading processes.Comment: (v2: fig. 1 fixed
A network-based threshold model for the spreading of fads in society and markets
We investigate the behavior of a threshold model for the spreading of fads
and similar phenomena in society. The model is giving the fad dynamics and is
intended to be confined to an underlying network structure. We investigate the
whole parameter space of the fad dynamics on three types of network models. The
dynamics we discover is rich and highly dependent on the underlying network
structure. For some range of the parameter space, for all types of substrate
networks, there are a great variety of sizes and life-lengths of the fads --
what one see in real-world social and economical systems
Majority-vote model on hyperbolic lattices
We study the critical properties of a non-equilibrium statistical model, the
majority-vote model, on heptagonal and dual heptagonal lattices. Such lattices
have the special feature that they only can be embedded in negatively curved
surfaces. We find, by using Monte Carlo simulations and finite-size analysis,
that the critical exponents , and are different
from those of the majority-vote model on regular lattices with periodic
boundary condition, which belongs to the same universality class as the
equilibrium Ising model. The exponents are also from those of the Ising model
on a hyperbolic lattice. We argue that the disagreement is caused by the
effective dimensionality of the hyperbolic lattices. By comparative studies, we
find that the critical exponents of the majority-vote model on hyperbolic
lattices satisfy the hyperscaling relation
, where is an
effective dimension of the lattice. We also investigate the effect of boundary
nodes on the ordering process of the model.Comment: 8 pages, 9 figure
Core-periphery organization of complex networks
Networks may, or may not, be wired to have a core that is both itself densely
connected and central in terms of graph distance. In this study we propose a
coefficient to measure if the network has such a clear-cut core-periphery
dichotomy. We measure this coefficient for a number of real-world and model
networks and find that different classes of networks have their characteristic
values. For example do geographical networks have a strong core-periphery
structure, while the core-periphery structure of social networks (despite their
positive degree-degree correlations) is rather weak. We proceed to study radial
statistics of the core, i.e. properties of the n-neighborhoods of the core
vertices for increasing n. We find that almost all networks have unexpectedly
many edges within n-neighborhoods at a certain distance from the core
suggesting an effective radius for non-trivial network processes
Tax evasion dynamics and Zaklan model on Opinion-dependent Network
Within the context of agent-based Monte-Carlo simulations, we study the
well-known majority-vote model (MVM) with noise applied to tax evasion on
Stauffer-Hohnisch-Pittnauer (SHP) networks. To control the fluctuations for tax
evasion in the economics model proposed by Zaklan, MVM is applied in the
neighborhood of the critical noise to evolve the Zaklan model. The
Zaklan model had been studied recently using the equilibrium Ising model. Here
we show that the Zaklan model is robust because this can be studied besides
using equilibrium dynamics of Ising model also through the nonequilibrium MVM
and on various topologies giving the same behavior regardless of dynamic or
topology used here.Comment: 14 page, 4 figure
Exploring the assortativity-clustering space of a network's degree sequence
Nowadays there is a multitude of measures designed to capture different
aspects of network structure. To be able to say if the structure of certain
network is expected or not, one needs a reference model (null model). One
frequently used null model is the ensemble of graphs with the same set of
degrees as the original network. In this paper we argue that this ensemble can
be more than just a null model -- it also carries information about the
original network and factors that affect its evolution. By mapping out this
ensemble in the space of some low-level network structure -- in our case those
measured by the assortativity and clustering coefficients -- one can for
example study how close to the valid region of the parameter space the observed
networks are. Such analysis suggests which quantities are actively optimized
during the evolution of the network. We use four very different biological
networks to exemplify our method. Among other things, we find that high
clustering might be a force in the evolution of protein interaction networks.
We also find that all four networks are conspicuously robust to both random
errors and targeted attacks
Network dynamics of ongoing social relationships
Many recent large-scale studies of interaction networks have focused on
networks of accumulated contacts. In this paper we explore social networks of
ongoing relationships with an emphasis on dynamical aspects. We find a
distribution of response times (times between consecutive contacts of different
direction between two actors) that has a power-law shape over a large range. We
also argue that the distribution of relationship duration (the time between the
first and last contacts between actors) is exponentially decaying. Methods to
reanalyze the data to compensate for the finite sampling time are proposed. We
find that the degree distribution for networks of ongoing contacts fits better
to a power-law than the degree distribution of the network of accumulated
contacts do. We see that the clustering and assortative mixing coefficients are
of the same order for networks of ongoing and accumulated contacts, and that
the structural fluctuations of the former are rather large.Comment: to appear in Europhys. Let
The dependence of strange hadron multiplicities on the speed of hadronization
Hadron multiplicities are calculated in the ALCOR model for the Pb+Pb
collisions at CERN SPS energy. Considering the newest experimental results, we
display our prediction obtained from the ALCOR model for stable hadrons
including strange baryons and anti-baryons.Comment: 8 pages, LaTeX in IOP style, appeared in the Proceedings of
Strangeness'97 Conference, Santorini, April 14-18 1997, J. of Physics G23
(1997) 194
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