1,470 research outputs found
Visual Mining of Epidemic Networks
We show how an interactive graph visualization method based on maximal
modularity clustering can be used to explore a large epidemic network. The
visual representation is used to display statistical tests results that expose
the relations between the propagation of HIV in a sexual contact network and
the sexual orientation of the patients.Comment: 8 page
Short-range spin glasses and Random Overlap Structures
Properties of Random Overlap Structures (ROSt)'s constructed from the
Edwards-Anderson (EA) Spin Glass model on with periodic boundary
conditions are studied. ROSt's are random matrices whose entries
are the overlaps of spin configurations sampled from the Gibbs measure. Since
the ROSt construction is the same for mean-field models (like the
Sherrington-Kirkpatrick model) as for short-range ones (like the EA model), the
setup is a good common ground to study the effect of dimensionality on the
properties of the Gibbs measure. In this spirit, it is shown, using translation
invariance, that the ROSt of the EA model possesses a local stability that is
stronger than stochastic stability, a property known to hold at almost all
temperatures in many spin glass models with Gaussian couplings. This fact is
used to prove stochastic stability for the EA spin glass at all temperatures
and for a wide range of coupling distributions. On the way, a theorem of Newman
and Stein about the pure state decomposition of the EA model is recovered and
extended.Comment: 27 page
The Irreducible Spine(s) of Undirected Networks
Using closure concepts, we show that within every undirected network, or
graph, there is a unique irreducible subgraph which we call its "spine". The
chordless cycles which comprise this irreducible core effectively characterize
the connectivity structure of the network as a whole. In particular, it is
shown that the center of the network, whether defined by distance or
betweenness centrality, is effectively contained in this spine. By counting the
number of cycles of length 3 <= k <= max_length, we can also create a kind of
signature that can be used to identify the network. Performance is analyzed,
and the concepts we develop are illurstrated by means of a relatively small
running sample network of about 400 nodes.Comment: Submitted to WISE 201
Universality of the Crossing Probability for the Potts Model for q=1,2,3,4
The universality of the crossing probability of a system to
percolate only in the horizontal direction, was investigated numerically by
using a cluster Monte-Carlo algorithm for the -state Potts model for
and for percolation . We check the percolation through
Fortuin-Kasteleyn clusters near the critical point on the square lattice by
using representation of the Potts model as the correlated site-bond percolation
model. It was shown that probability of a system to percolate only in the
horizontal direction has universal form for
as a function of the scaling variable . Here,
is the probability of a bond to be closed, is the
nonuniversal crossing amplitude, is the nonuniversal metric factor,
is the nonuniversal scaling index, is the correlation
length index.
The universal function . Nonuniversal scaling factors
were found numerically.Comment: 15 pages, 3 figures, revtex4b, (minor errors in text fixed,
journal-ref added
Emergence of communities on a coevolutive model of wealth interchange
We present a model in which we investigate the structure and evolution of a
random network that connects agents capable of exchanging wealth. Economic
interactions between neighbors can occur only if the difference between their
wealth is less than a threshold value that defines the width of the economic
classes. If the interchange of wealth cannot be done, agents are reconnected
with another randomly selected agent, allowing the network to evolve in time.
On each interaction there is a probability of favoring the poorer agent,
simulating the action of the government. We measure the Gini index, having real
world values attached to reality. Besides the network structure showed a very
close connection with the economic dynamic of the system.Comment: 5 pages, 7 figure
The three-dimensional random field Ising magnet: interfaces, scaling, and the nature of states
The nature of the zero temperature ordering transition in the 3D Gaussian
random field Ising magnet is studied numerically, aided by scaling analyses. In
the ferromagnetic phase the scaling of the roughness of the domain walls,
, is consistent with the theoretical prediction .
As the randomness is increased through the transition, the probability
distribution of the interfacial tension of domain walls scales as for a single
second order transition. At the critical point, the fractal dimensions of
domain walls and the fractal dimension of the outer surface of spin clusters
are investigated: there are at least two distinct physically important fractal
dimensions. These dimensions are argued to be related to combinations of the
energy scaling exponent, , which determines the violation of
hyperscaling, the correlation length exponent , and the magnetization
exponent . The value is derived from the
magnetization: this estimate is supported by the study of the spin cluster size
distribution at criticality. The variation of configurations in the interior of
a sample with boundary conditions is consistent with the hypothesis that there
is a single transition separating the disordered phase with one ground state
from the ordered phase with two ground states. The array of results are shown
to be consistent with a scaling picture and a geometric description of the
influence of boundary conditions on the spins. The details of the algorithm
used and its implementation are also described.Comment: 32 pp., 2 columns, 32 figure
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What do coronary artery disease patients think about their treatments? An assessment of patients' treatment representations
This article investigates patients' beliefs about the intervention offered to manage their illness. Coronary artery disease (CAD) patients, 70 of whom were undergoing medication, 71 to undergo angioplasty and 73 to undergo surgery, completed a 58-item questionnaire regarding their treatment beliefs. Responses were subject to principal components analysis, which indicated four factors accounting for 36.7 per cent of the variance. After excluding extraneous items, the final questionnaire consisted of 27 items, clustered around four components: treatment-value, treatment-concerns, decision-satisfaction and cure. A coherent set of subscale inter-correlations and ANCOVAs examining treatment group differences on these sub-scales showed a logical, explicable pattern of group differences reflecting the distinctive natures of each treatment and demonstrated discriminant validity. Correlations with other scales provided evidence of construct validity
Spin glass models with Kac interactions
In this paper I will review my work on disordered systems -spin glass model
with two body and body interactions- with long but finite interaction
range . I will describe the relation of these model with Mean Field Theory
in the Kac limit and some attempts to go beyond mean field.Comment: Proceedings of the Stat-phys23 conferenc
Clusters in weighted macroeconomic networks : the EU case. Introducing the overlapping index of GDP/capita fluctuation correlations
GDP/capita correlations are investigated in various time windows (TW), for
the time interval 1990-2005. The target group of countries is the set of 25 EU
members, 15 till 2004 plus the 10 countries which joined EU later on. The
TW-means of the statistical correlation coefficients are taken as the weights
(links) of a fully connected network having the countries as nodes. Thereafter
we define and introduce the overlapping index of weighted network nodes. A
cluster structure of EU countries is derived from the statistically relevant
eigenvalues and eigenvectors of the adjacency matrix. This may be considered to
yield some information about the structure, stability and evolution of the EU
country clusters in a macroeconomic sense.Comment: 6 pages, 8 figures, 1 table, 17 references, submitted to Physica A;
proceedings of APFA
Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution
We compare and contrast the long-time dynamical properties of two
individual-based models of biological coevolution. Selection occurs via
multispecies, stochastic population dynamics with reproduction probabilities
that depend nonlinearly on the population densities of all species resident in
the community. New species are introduced through mutation. Both models are
amenable to exact linear stability analysis, and we compare the analytic
results with large-scale kinetic Monte Carlo simulations, obtaining the
population size as a function of an average interspecies interaction strength.
Over time, the models self-optimize through mutation and selection to
approximately maximize a community fitness function, subject only to
constraints internal to the particular model. If the interspecies interactions
are randomly distributed on an interval including positive values, the system
evolves toward self-sustaining, mutualistic communities. In contrast, for the
predator-prey case the matrix of interactions is antisymmetric, and a nonzero
population size must be sustained by an external resource. Time series of the
diversity and population size for both models show approximate 1/f noise and
power-law distributions for the lifetimes of communities and species. For the
mutualistic model, these two lifetime distributions have the same exponent,
while their exponents are different for the predator-prey model. The difference
is probably due to greater resilience toward mass extinctions in the food-web
like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J.
Math. Biol., in pres
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