3,279 research outputs found
Evaluation of microbial activity in soil profiles by carbon dioxide evolution and thermal procedures
Comparison and validation of community structures in complex networks
The issue of partitioning a network into communities has attracted a great
deal of attention recently. Most authors seem to equate this issue with the one
of finding the maximum value of the modularity, as defined by Newman. Since the
problem formulated this way is NP-hard, most effort has gone into the
construction of search algorithms, and less to the question of other measures
of community structures, similarities between various partitionings and the
validation with respect to external information. Here we concentrate on a class
of computer generated networks and on three well-studied real networks which
constitute a bench-mark for network studies; the karate club, the US college
football teams and a gene network of yeast. We utilize some standard ways of
clustering data (originally not designed for finding community structures in
networks) and show that these classical methods sometimes outperform the newer
ones. We discuss various measures of the strength of the modular structure, and
show by examples features and drawbacks. Further, we compare different
partitions by applying some graph-theoretic concepts of distance, which
indicate that one of the quality measures of the degree of modularity
corresponds quite well with the distance from the true partition. Finally, we
introduce a way to validate the partitionings with respect to external data
when the nodes are classified but the network structure is unknown. This is
here possible since we know everything of the computer generated networks, as
well as the historical answer to how the karate club and the football teams are
partitioned in reality. The partitioning of the gene network is validated by
use of the Gene Ontology database, where we show that a community in general
corresponds to a biological process.Comment: To appear in Physica A; 25 page
Lexical and syntactic causatives in Oromo
In the syntactic process of causative formation in Oromo, the affixation of the causative morpheme is sensitive to initial grammatical relations: the number of causative morphemes corresponds to the number of logical subjects in the clause. Thus, transitive and unergative verbs can be distinguished from unaccusatives in causative constructions. A causative-intensive construction may also be formed via reduplication of this causative morpheme. However, not all predicates that appear to be causatives can be intensified in this way. We propose that these predicates (a restricted number of unaccusative verb stems) combine derivationally with the causative morpheme, and that the output of this derivation may not be intensified. Oromo, then, shows the distinct effects of similar morphological processes arising either in the lexicon or in the syntax
Periodicity of mass extinctions without an extraterrestrial cause
We study a lattice model of a multi-species prey-predator system. Numerical
results show that for a small mutation rate the model develops irregular
long-period oscillatory behavior with sizeable changes in a number of species.
The periodicity of extinctions on Earth was suggested by Raup and Sepkoski but
so far is lacking a satisfactory explanation. Our model indicates that this is
a natural consequence of the ecosystem dynamics, not the result of any
extraterrestrial cause.Comment: 4 pages, accepted in Phys.Rev.
An experimental and theoretical study of transient negative ions in Mg, Zn, Cd and Hg
A range of experimental and theoretical techniques have been applied to the study of transient negative ions (resonances) formed in electron scattering from the Group II metals Mg, Zn, Cd, and Hg at incident electron energies below the first ionization potential. A wealth of resonance structures have been observed and from the experimental observations and theoretical information, classifications are proposed for some of these negative ion states
Stochastic Renormalization Group in Percolation: I. Fluctuations and Crossover
A generalization of the Renormalization Group, which describes
order-parameter fluctuations in finite systems, is developed in the specific
context of percolation. This ``Stochastic Renormalization Group'' (SRG)
expresses statistical self-similarity through a non-stationary branching
process. The SRG provides a theoretical basis for analytical or numerical
approximations, both at and away from criticality, whenever the correlation
length is much larger than the lattice spacing (regardless of the system size).
For example, the SRG predicts order-parameter distributions and finite-size
scaling functions for the complete crossover between phases. For percolation,
the simplest SRG describes structural quantities conditional on spanning, such
as the total cluster mass or the minimum chemical distance between two
boundaries. In these cases, the Central Limit Theorem (for independent random
variables) holds at the stable, off-critical fixed points, while a ``Fractal
Central Limit Theorem'' (describing long-range correlations) holds at the
unstable, critical fixed point. This first part of a series of articles
explains these basic concepts and a general theory of crossover. Subsequent
parts will focus on limit theorems and comparisons of small-cell SRG
approximations with simulation results.Comment: 33 pages, 6 figures, to appear in Physica A; v2: some typos corrected
and Eqs. (26)-(27) cast in a simpler (but equivalent) for
Network Topology of an Experimental Futures Exchange
Many systems of different nature exhibit scale free behaviors. Economic
systems with power law distribution in the wealth is one of the examples. To
better understand the working behind the complexity, we undertook an empirical
study measuring the interactions between market participants. A Web server was
setup to administer the exchange of futures contracts whose liquidation prices
were coupled to event outcomes. After free registration, participants started
trading to compete for the money prizes upon maturity of the futures contracts
at the end of the experiment. The evolving `cash' flow network was
reconstructed from the transactions between players. We show that the network
topology is hierarchical, disassortative and scale-free with a power law
exponent of 1.02+-0.09 in the degree distribution. The small-world property
emerged early in the experiment while the number of participants was still
small. We also show power law distributions of the net incomes and
inter-transaction time intervals. Big winners and losers are associated with
high degree, high betweenness centrality, low clustering coefficient and low
degree-correlation. We identify communities in the network as groups of the
like-minded. The distribution of the community sizes is shown to be power-law
distributed with an exponent of 1.19+-0.16.Comment: 6 pages, 12 figure
Damage Spreading and Opinion Dynamics on Scale Free Networks
We study damage spreading among the opinions of a system of agents, subjected
to the dynamics of the Krause-Hegselmann consensus model. The damage consists
in a sharp change of the opinion of one or more agents in the initial random
opinion configuration, supposedly due to some external factors and/or events.
This may help to understand for instance under which conditions special
shocking events or targeted propaganda are able to influence the results of
elections. For agents lying on the nodes of a Barabasi-Albert network, there is
a damage spreading transition at a low value epsilon_d of the confidence bound
parameter. Interestingly, we find as well that there is some critical value
epsilon_s above which the initial perturbation manages to propagate to all
other agents.Comment: 5 pages, 5 figure
Robustness of a Network of Networks
Almost all network research has been focused on the properties of a single
network that does not interact and depends on other networks. In reality, many
real-world networks interact with other networks. Here we develop an analytical
framework for studying interacting networks and present an exact percolation
law for a network of interdependent networks. In particular, we find that
for Erd\H{o}s-R\'{e}nyi networks each of average degree , the giant
component, , is given by
where is the initial fraction of removed nodes. Our general result
coincides for with the known Erd\H{o}s-R\'{e}nyi second-order phase
transition for a single network. For any cascading failures occur
and the transition becomes a first-order percolation transition. The new law
for shows that percolation theory that is extensively studied in
physics and mathematics is a limiting case () of a more general general
and different percolation law for interdependent networks.Comment: 7 pages, 3 figure
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