2,091 research outputs found
A Group-Based Yule Model for Bipartite Author-Paper Networks
This paper presents a novel model for author-paper networks, which is based
on the assumption that authors are organized into groups and that, for each
research topic, the number of papers published by a group is based on a
success-breeds-success model. Collaboration between groups is modeled as random
invitations from a group to an outside member. To analyze the model, a number
of different metrics that can be obtained in author-paper networks were
extracted. A simulation example shows that this model can effectively mimic the
behavior of a real-world author-paper network, extracted from a collection of
900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure
Portraits of Complex Networks
We propose a method for characterizing large complex networks by introducing
a new matrix structure, unique for a given network, which encodes structural
information; provides useful visualization, even for very large networks; and
allows for rigorous statistical comparison between networks. Dynamic processes
such as percolation can be visualized using animations. Applications to graph
theory are discussed, as are generalizations to weighted networks, real-world
network similarity testing, and applicability to the graph isomorphism problem.Comment: 6 pages, 9 figure
Geometric and dynamic perspectives on phase-coherent and noncoherent chaos
Statistically distinguishing between phase-coherent and noncoherent chaotic
dynamics from time series is a contemporary problem in nonlinear sciences. In
this work, we propose different measures based on recurrence properties of
recorded trajectories, which characterize the underlying systems from both
geometric and dynamic viewpoints. The potentials of the individual measures for
discriminating phase-coherent and noncoherent chaotic oscillations are
discussed. A detailed numerical analysis is performed for the chaotic R\"ossler
system, which displays both types of chaos as one control parameter is varied,
and the Mackey-Glass system as an example of a time-delay system with
noncoherent chaos. Our results demonstrate that especially geometric measures
from recurrence network analysis are well suited for tracing transitions
between spiral- and screw-type chaos, a common route from phase-coherent to
noncoherent chaos also found in other nonlinear oscillators. A detailed
explanation of the observed behavior in terms of attractor geometry is given.Comment: 12 pages, 13 figure
Twitter-based analysis of the dynamics of collective attention to political parties
Large-scale data from social media have a significant potential to describe
complex phenomena in real world and to anticipate collective behaviors such as
information spreading and social trends. One specific case of study is
represented by the collective attention to the action of political parties. Not
surprisingly, researchers and stakeholders tried to correlate parties' presence
on social media with their performances in elections. Despite the many efforts,
results are still inconclusive since this kind of data is often very noisy and
significant signals could be covered by (largely unknown) statistical
fluctuations. In this paper we consider the number of tweets (tweet volume) of
a party as a proxy of collective attention to the party, identify the dynamics
of the volume, and show that this quantity has some information on the
elections outcome. We find that the distribution of the tweet volume for each
party follows a log-normal distribution with a positive autocorrelation of the
volume over short terms, which indicates the volume has large fluctuations of
the log-normal distribution yet with a short-term tendency. Furthermore, by
measuring the ratio of two consecutive daily tweet volumes, we find that the
evolution of the daily volume of a party can be described by means of a
geometric Brownian motion (i.e., the logarithm of the volume moves randomly
with a trend). Finally, we determine the optimal period of averaging tweet
volume for reducing fluctuations and extracting short-term tendencies. We
conclude that the tweet volume is a good indicator of parties' success in the
elections when considered over an optimal time window. Our study identifies the
statistical nature of collective attention to political issues and sheds light
on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON
Spin measurements for 147Sm+n resonances: Further evidence for non-statistical effects
We have determined the spins J of resonances in the 147Sm(n,gamma) reaction
by measuring multiplicities of gamma-ray cascades following neutron capture.
Using this technique, we were able to determine J values for all but 14 of the
140 known resonances below En = 1 keV, including 41 firm J assignments for
resonances whose spins previously were either unknown or tentative. These new
spin assignments, together with previously determined resonance parameters,
allowed us to extract separate level spacings and neutron strength functions
for J = 3 and 4 resonances. Furthermore, several statistical test of the data
indicate that very few resonances of either spin have been missed below En =
700eV. Because a non-statistical effect recently was reported near En = 350 eV
from an analysis of 147Sm(n,alpha) data, we divided the data into two regions;
0 < En < 350 eV and 350 < En < 700 eV. Using neutron widths from a previous
measurement and published techniques for correcting for missed resonances and
for testing whether data are consistent with a Porter-Thomas distribution, we
found that the reduced-neutron-width distribution for resonances below 350 eV
is consistent with the expected Porter-Thomas distribution. On the other hand,
we found that reduced-neutron-width data in the 350 < En < 700 eV region are
inconsistent with a Porter-Thomas distribution, but in good agreement with a
chi-squared distribution having two or more degrees of freedom. We discuss
possible explanations for these observed non-statistical effects and their
possible relation to similar effects previously observed in other nuclides.Comment: 40 pages, 13 figures, accepted by Phys. Rev.
Effect of suppressive DNA on CpG-induced immune activation.
Bacterial DNA and synthetic oligodeoxynucleotides (ODN) containing unmethylated CpG motifs stimulate a strong innate immune response. This stimulation can be abrogated by either removing the CpG DNA or adding inhibitory/suppressive motifs. Suppression is dominant over stimulation and is specific for CpG-induced immune responses (having no effect on LPS- or Con A-induced activation). Individual cells noncompetitively internalize both stimulatory and suppressive ODN. Studies using ODN composed of both stimulatory and suppressive motifs indicate that sequence recognition proceeds in a 5'-->3' direction, and that a 5' motif can block recognition of immediately 3' sequences. These findings contribute to our understanding of the immunomodulatory activity of DNA-based products and the rules that govern immune recognition of stimulatory and suppressive motifs
Partisan Asymmetries in Online Political Activity
We examine partisan differences in the behavior, communication patterns and
social interactions of more than 18,000 politically-active Twitter users to
produce evidence that points to changing levels of partisan engagement with the
American online political landscape. Analysis of a network defined by the
communication activity of these users in proximity to the 2010 midterm
congressional elections reveals a highly segregated, well clustered partisan
community structure. Using cluster membership as a high-fidelity (87% accuracy)
proxy for political affiliation, we characterize a wide range of differences in
the behavior, communication and social connectivity of left- and right-leaning
Twitter users. We find that in contrast to the online political dynamics of the
2008 campaign, right-leaning Twitter users exhibit greater levels of political
activity, a more tightly interconnected social structure, and a communication
network topology that facilitates the rapid and broad dissemination of
political information.Comment: 17 pages, 10 figures, 6 table
Regional differentiation and post-glacial expansion of the Atlantic silverside, Menidia menidia, an annual fish with high dispersal potential
The coastal marine environment of the Northwest Atlantic contains strong environmental gradients that create distinct marine biogeographic provinces by limiting dispersal, recruitment, and survival. This region has also been subjected to numerous Pleistocene glacial cycles, resulting in repeated extirpations and recolonizations in northern populations of marine organisms. In this study, we examined patterns of genetic structure and historical demography in the Atlantic silverside, Menidia menidia, an annual marine fish with high dispersal potential but with well-documented patterns of clinal phenotypic adaptation along the environmental gradients of the Northwest Atlantic. Contrary to previous studies indicating genetic homogeneity that should preclude regional adaptation, results demonstrate subtle but significant (F(ST) = 0.07; P < 0.0001) genetic structure among three phylogeographic regions that partially correspond with biogeographic provinces, suggesting regional limits to gene flow. Tests for non-equilibrium population dynamics and latitudinal patterns in genetic diversity indicate northward population expansion from a single southern refugium following the last glacial maximum, suggesting that phylogeographic and phenotypic patterns have relatively recent origins. The recovery of phylogeographic structure and the partial correspondence of these regions to recognized biogeographic provinces suggest that the environmental gradients that shape biogeographic patterns in the Northwest Atlantic may also limit gene flow in M. menidia, creating phylogeographic structure and contributing to the creation of latitudinal phenotypic clines in this species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00227-010-1577-3) contains supplementary material, which is available to authorized users
Using Multiple Signatures to Improve Accuracy of Substorm Identification
We have developed a new procedure for combining lists of substorm onset times from multiple sources. We apply this procedure to observational data and to magnetohydrodynamic (MHD) model output from 1–31 January 2005. We show that this procedure is capable of rejecting false positive identifications and filling data gaps that appear in individual lists. The resulting combined onset lists produce a waiting time distribution that is comparable to previously published results, and superposed epoch analyses of the solar wind driving conditions and magnetospheric response during the resulting onset times are also comparable to previous results. Comparison of the substorm onset list from the MHD model to that obtained from observational data reveals that the MHD model reproduces many of the characteristic features of the observed substorms, in terms of solar wind driving, magnetospheric response, and waiting time distribution. Heidke skill scores show that the MHD model has statistically significant skill in predicting substorm onset times.Plain Language SummaryMagnetospheric substorms are a process of explosive energy release from the plasma environment on the nightside of the Earth. We have developed a procedure to identify substorms that uses multiple forms of observational data in combination. Our procedure produces a list of onset times for substorms, where each onset time has been independently confirmed by two or more observational data sets. We also apply our procedure to output from a physical model of the plasma environment surrounding the Earth and show that this model can predict a significant fraction of the substorm onset times.Key PointsCombining substorm onsets from multiple types of observations can produce a more accurate list of onset times than any single listThe resulting onset list exhibits expected behavior for substorms in terms of magnetospheric driving and responseSWMF has a weak but consistent and statistically significant skill in predicting substormsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/1/jgra55605_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/2/jgra55605-sup-0002-2019JA027559-Text_SI-S01.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/3/jgra55605.pd
Structural and Electronic Properties of Small Neutral (MgO)n Clusters
Ab initio Perturbed Ion (PI) calculations are reported for neutral
stoichiometric (MgO)n clusters (n<14). An extensive number of isomer structures
was identified and studied. For the isomers of (MgO)n (n<8) clusters, a full
geometrical relaxation was considered. Correlation corrections were included
for all cluster sizes using the Coulomb-Hartree-Fock (CHF) model proposed by
Clementi. The results obtained compare favorably to the experimental data and
other previous theoretical studies. Inclusion of correlaiotn is crucial in
order to achieve a good description of these systems. We find an important
number of new isomers which allows us to interpret the experimental magic
numbers without the assumption of structures based on (MgO)3 subunits. Finally,
as an electronic property, the variations in the cluster ionization potential
with the cluster size were studied and related to the structural isomer
properties.Comment: 24 pages, LaTeX, 7 figures in GIF format. Accepted for publication in
Phys. Rev.
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