Kepler observations of A-F pre-main sequence stars in Upper Scorpius: Discovery of six new δ\delta~Scuti and one γ\gamma~Doradus stars

We present light curves and periodograms for 27 stars in the young Upper Scorpius association (age=$11 \pm 1$\,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 $\delta$~Scuti variables and one $\gamma$~Doradus star. These are most likely PMS stars or else very close to the zero-age main sequence. Four of the $\delta$~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 $\delta$~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 $Q$ has been introduced as a measure to assess the quality of clusterizations. $Q$ 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 $LQ$, which reflects local cluster structure. Optimization of $Q$ and $LQ$ 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