8,987 research outputs found
Kepler observations of A-F pre-main sequence stars in Upper Scorpius: Discovery of six new ~Scuti and one ~Doradus stars
We present light curves and periodograms for 27 stars in the young Upper
Scorpius association (age=\,Myr) obtained with the Kepler spacecraft.
This association is only the second stellar grouping to host several pulsating
pre-main sequence (PMS) stars which have been observed from space. From an
analysis of the periodograms, we identify six ~Scuti variables and one
~Doradus star. These are most likely PMS stars or else very close to
the zero-age main sequence. Four of the ~Scuti variables were observed
in short-cadence mode, which allows us to resolve the entire frequency
spectrum. For these four stars, we are able to infer some qualitative
information concerning their ages. For the remaining two ~Scuti stars,
only long-cadence data are available, which means that some of the frequencies
are likely to be aliases. One of the stars appears to be a rotational variable
in a hierarchical triple system. This is a particularly important object, as it
allows the possibility of an accurate mass determination when radial velocity
observations become available. We also report on new high-resolution echelle
spectra obtained for some of the stars of our sample.Comment: 19 pages, 9 figures. Accepted for publication on MNRA
Some semi-classical issues in boundary sine-Gordon model
The semi-classical quantisation of the two lowest energy static solutions of boundary sine-Gordon model is considered. A relation between the Lagrangian and bootstrap parameters is established by comparing their quantum corrected energy difference and the exact one. This relation is also confirmed by studying the semi-classical limit of soliton reflections on the boundary
Maps of random walks on complex networks reveal community structure
To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach that reveals
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.Comment: 7 pages and 4 figures plus supporting material. For associated source
code, see http://www.tp.umu.se/~rosvall
Detection of delta Scuti-like pulsation in H254, a pre-main sequence F-type star in IC 348
We present time series observations of intermediate mass PMS stars belonging
to the young star cluster IC 348. The new data reveal that a young member of
the cluster, H254, undergoes periodic light variations with delta Scuti-like
characteristics. This occurrence provides an unambiguous evidence confirming
the prediction that intermediate-mass pre-main sequence (PMS) stars should
experience this transient instability during their approach to the
main-sequence. On the basis of the measured frequency f=7.406 c/d, we are able
to constrain the intrinsic stellar parameters of H254 by means of linear, non
adiabatic, radial pulsation models. The range of the resulting luminosity and
effective temperature permitted by the models is narrower than the
observational values. In particular, the pulsation analysis allows to derive an
independent estimate of the distance to IC 348 of about 320 pc. Further
observations could either confirm the monoperiodic nature of H254 or reveal the
presence of other frequencies.Comment: 7 pages, including 7 postscript figures, accepted for publication on
A&
Some semi-classical issues in the boundary sine-Gordon model
The semi-classical quantisation of the two lowest energy static solutions of
boundary sine-Gordon model is considered. A relation between the Lagrangian and
bootstrap parameters is established by comparing their quantum corrected energy
difference and the exact one. This relation is also confirmed by studying the
semi-classical limit of soliton reflections on the boundary.Comment: 22 pages, references update
Local modularity measure for network clusterizations
Many complex networks have an underlying modular structure, i.e., structural
subunits (communities or clusters) characterized by highly interconnected
nodes. The modularity has been introduced as a measure to assess the
quality of clusterizations. has a global view, while in many real-world
networks clusters are linked mainly \emph{locally} among each other
(\emph{local cluster-connectivity}). Here, we introduce a new measure,
localized modularity , which reflects local cluster structure. Optimization
of and on the clusterization of two biological networks shows that the
localized modularity identifies more cohesive clusters, yielding a
complementary view of higher granularity.Comment: 5 pages, 4 figures, RevTex4; Changed conten
Time-frequency analysis of rhythmic masticatory muscle activity
The aim of this study was to develop and validate under laboratory conditions an algorithm for a time-frequency analysis of rhythmic masticatory muscle activity (RMMA). The algorithm baseband demodulated the electromyographic (EMG) signal to provide a frequency versus time representation. Using appropriate thresholds for frequency and power parameters, it was possible to automatically assess the features of RMMA without examiner interaction. The algorithm was first tested using synthetic EMG signals and then using real EMG signals obtained from the masticatory muscles of 11 human subjects who underwent well-defined rhythmic, static, and possible confounding oral tasks. The accuracy of detection was quantified by receiver operating characteristics (ROC) curves. Sensitivity and specificity values were >/=90% and >/=96%, respectively. The areas under the ROC curves were >/=95% (standard error +/-0.1%). The proposed approach represents a promising tool to effectively investigate rhythmical contractions of the masticatory muscles. Muscle Nerve, 2009
Mixture models and exploratory analysis in networks
Networks are widely used in the biological, physical, and social sciences as
a concise mathematical representation of the topology of systems of interacting
components. Understanding the structure of these networks is one of the
outstanding challenges in the study of complex systems. Here we describe a
general technique for detecting structural features in large-scale network data
which works by dividing the nodes of a network into classes such that the
members of each class have similar patterns of connection to other nodes. Using
the machinery of probabilistic mixture models and the expectation-maximization
algorithm, we show that it is possible to detect, without prior knowledge of
what we are looking for, a very broad range of types of structure in networks.
We give a number of examples demonstrating how the method can be used to shed
light on the properties of real-world networks, including social and
information networks.Comment: 8 pages, 4 figures, two new examples in this version plus minor
correction
Resolution limit in community detection
Detecting community structure is fundamental to clarify the link between
structure and function in complex networks and is used for practical
applications in many disciplines. A successful method relies on the
optimization of a quantity called modularity [Newman and Girvan, Phys. Rev. E
69, 026113 (2004)], which is a quality index of a partition of a network into
communities. We find that modularity optimization may fail to identify modules
smaller than a scale which depends on the total number L of links of the
network and on the degree of interconnectedness of the modules, even in cases
where modules are unambiguously defined. The probability that a module conceals
well-defined substructures is the highest if the number of links internal to
the module is of the order of \sqrt{2L} or smaller. We discuss the practical
consequences of this result by analyzing partitions obtained through modularity
optimization in artificial and real networks.Comment: 8 pages, 3 figures. Clarification of definition of community in
Section II + minor revision
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