149 research outputs found
Hardcore classification: identifying play styles in social games using network analysis
In the social network of a web-based online game, all players are not equal. Through network analysis, we show that the community of players in a online social game is an example of a scale free small world network and that the growth of the player-base obeys a power law.
The community is centred around a minority group of ``hardcore" players who define the social environment for the game, and without whom the social network would collapse. Methods are discussed for identifying this critically important subset of players automatically through analysing social behaviours within the game
Coupled non-equilibrium growth equations: Self-consistent mode coupling using vertex renormalization
We find that studying the simplest of the coupled non-equilibrium growth
equations of Barabasi by self-consistent mode coupling requires the use of
dressed vertices. Using the vertex renormalization, we find a roughness
exponent which already in the leading order is quite close to the numerical
value.Comment: 7 pages, 3 figure
A machine learning pipeline for discriminant pathways identification
Motivation: Identifying the molecular pathways more prone to disruption
during a pathological process is a key task in network medicine and, more in
general, in systems biology.
Results: In this work we propose a pipeline that couples a machine learning
solution for molecular profiling with a recent network comparison method. The
pipeline can identify changes occurring between specific sub-modules of
networks built in a case-control biomarker study, discriminating key groups of
genes whose interactions are modified by an underlying condition. The proposal
is independent from the classification algorithm used. Three applications on
genomewide data are presented regarding children susceptibility to air
pollution and two neurodegenerative diseases: Parkinson's and Alzheimer's.
Availability: Details about the software used for the experiments discussed
in this paper are provided in the Appendix
Novel universality classes of coupled driven diffusive systems
Motivated by the phenomenologies of dynamic roughening of strings in random
media and magnetohydrodynamics, we examine the universal properties of driven
diffusive system with coupled fields. We demonstrate that cross-correlations
between the fields lead to amplitude-ratios and scaling exponents varying
continuosly with the strength of these cross-correlations. The implications of
these results for experimentally relevant systems are discussed.Comment: To appear in Phys. Rev. E (Rapid Comm.) (2003
Universal features of network topology
Recent studies have revealed characteristic general features in the topology of real-world networks. We investigate the universality of mechanisms that result in the power-law behaviour of many real-world networks, paying particular attention to the Barabasi-Albert process of preferential attachment as the most successful. We introduce a variation on this theme where at each time step either a new vertex and edge is added to the network or a new edge is created between two existing vertices. This process retains a power-law degree distribution, while other variations destroy it. We also introduce alternative models which favour connections to vertices with high degree but by a different mechanism and find that one of the models displays behaviour that is compatible with a power-law degree distribution
Exclusive Queueing Process with Discrete Time
In a recent study [C Arita, Phys. Rev. E 80, 051119 (2009)], an extension of
the M/M/1 queueing process with the excluded-volume effect as in the totally
asymmetric simple exclusion process (TASEP) was introduced. In this paper, we
consider its discrete-time version. The update scheme we take is the parallel
one. A stationary-state solution is obtained in a slightly arranged matrix
product form of the discrete-time open TASEP with the parallel update. We find
the phase diagram for the existence of the stationary state. The critical line
which separates the parameter space into the regions with and without the
stationary state can be written in terms of the stationary current of the open
TASEP. We calculate the average length of the system and the average number of
particles
Neurological Disorders and Publication Abstracts Follow Elements of Social Network Patterns when Indexed Using Ontology Tree-Based Key Term Search
Disorders of the Central Nervous System (CNS) are worldwide causes of morbidity and mortality. In order to further investigate the nature of the CNS research, we generate from an initial reference a controlled vocabulary of CNS disorder-related terms and ontological tree structure for this vocabulary, and then apply the vocabulary in an analysis of the past ten years of abstracts (N = 10,488) from a major neuroscience journal. Using literal search methodology with our terminology tree, we find over 5,200 relationships between abstracts and clinical diagnostic topics. After generating a network graph of these document-topic relationships, we find that this network graph contains characteristics of document-author and other human social networks, including evidence of scale-free and power law-like node distributions. However, we also found qualitative evidence for Z-normal-type (albeit logarithmically skewed) distributions within disorder popularity. Lastly, we discuss potential consumer-centered as well as clinic-centered uses for our ontology and search methodology
Theoretical approach and impact of correlations on the critical packet generation rate in traffic dynamics on complex networks
Using the formalism of the biased random walk in random uncorrelated networks
with arbitrary degree distributions, we develop theoretical approach to the
critical packet generation rate in traffic based on routing strategy with local
information. We explain microscopic origins of the transition from the flow to
the jammed phase and discuss how the node neighbourhood topology affects the
transport capacity in uncorrelated and correlated networks.Comment: 6 pages, 5 figure
Bulk dynamics for interfacial growth models
We study the influence of the bulk dynamics of a growing cluster of particles
on the properties of its interface. First, we define a {\it general bulk growth
model} by means of a continuum Master equation for the evolution of the bulk
density field. This general model just considers arbitrary addition of
particles (though it can be easily generalized to consider substraction) with
no other physical restriction. The corresponding Langevin equation for this
bulk density field is derived where the influence of the bulk dynamics is
explicitly shown. Finally, when it is assumed a well-defined interface for the
growing cluster, the Langevin equation for the height field of this interface
for some particular bulk dynamics is written. In particular, we obtain the
celebrated Kardar-Parisi-Zhang (KPZ) equation. A Monte Carlo simulation
illustrates the theoretical results.Comment: 6 pages, 2 figure
Aging in humid granular media
Aging behavior is an important effect in the friction properties of solid
surfaces. In this paper we investigate the temporal evolution of the static
properties of a granular medium by studying the aging over time of the maximum
stability angle of submillimetric glass beads. We report the effect of several
parameters on these aging properties, such as the wear on the beads, the stress
during the resting period, and the humidity content of the atmosphere. Aging
effects in an ethanol atmosphere are also studied. These experimental results
are discussed at the end of the paper.Comment: 7 pages, 9 figure
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