The number of graphs and a random graph with a given degree sequence

We consider the set of all graphs on n labeled vertices with prescribed degrees D = ( d 1 ,…, d n ). For a wide class of tame degree sequences D we obtain a computationally efficient asymptotic formula approximating the number of graphs within a relative error which approaches 0 as n grows. As a corollary, we prove that the structure of a random graph with a given tame degree sequence D is well described by a certain maximum entropy matrix computed from D . We also establish an asymptotic formula for the number of bipartite graphs with prescribed degrees of vertices, or, equivalently, for the number of 0‐1 matrices with prescribed row and column sums. © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 2013Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97179/1/20409_ftp.pd

MAP: Microblogging Assisted Profiling of TV Shows

Online microblogging services that have been increasingly used by people to share and exchange information, have emerged as a promising way to profiling multimedia contents, in a sense to provide users a socialized abstraction and understanding of these contents. In this paper, we propose a microblogging profiling framework, to provide a social demonstration of TV shows. Challenges for this study lie in two folds: First, TV shows are generally offline, i.e., most of them are not originally from the Internet, and we need to create a connection between these TV shows with online microblogging services; Second, contents in a microblogging service are extremely noisy for video profiling, and we need to strategically retrieve the most related information for the TV show profiling.To address these challenges, we propose a MAP, a microblogging-assisted profiling framework, with contributions as follows: i) We propose a joint user and content retrieval scheme, which uses information about both actors and topics of a TV show to retrieve related microblogs; ii) We propose a social-aware profiling strategy, which profiles a video according to not only its content, but also the social relationship of its microblogging users and its propagation in the social network; iii) We present some interesting analysis, based on our framework to profile real-world TV shows

Spectrophotometric evidence for velocity variability in the HH 34 and HH 111 stellar jets

We present Fabry-Perot observations and long-slit spectrophotometry of the collimated jet regions of the HH 34 and HH 111 outflows. There is a close correlation between the observed [S II] flux and the electron density in the bright low-excitation knots in both the HH 34 jet and the HH 111 jet. The electron densities in some of the low-excitation HH 111 jet knots exceed 2500 cm-3, from which we infer that the true gas densities may be significantly higher than ∼104 cm-3 because the peak ionization is only a few percent for such weak shocks. We detect weak [O III]λ5007 emission from the HH 111 jet knot L, which implies that the shock velocity for this knot is ∼100 km s-1. This knot also has a large velocity dispersion (∼200 km s-1) and bow-shaped morphology {Reipurth et al. [ApJ, 392, 145 (1992)]}. We argue that such a feature cannot be explained by models in which knots correspond to internal shock waves excited by boundary layer instabilities, but is consistent with an internal working surface in a velocity-variable outflow. We review evidence for multiple ejections in each of these stellar jets

Observations of entrainment and time variability in the HH 47 jet

We present new Fabry-Perot images of the HH 47 jet that show the first clear evidence for entrainment in a jet from a young star. The material in the jet moves faster down the axis of the flow and slower at the edges, similar to viscous flow in a pipe. The higher excitation lines occur along the edges of the jet, as expected if entrainment accelerates and heats the ambient material. We confirm previous observations of multiple bow shocks in this system. Together, time variability and entrainment produce much of the observed shock-excited gas in this object. Our data show that the "wiggles" along the jet are not caused by jet material tied to a spiraling magnetic field, but instead result from time variability, variable ejection angles, or inhomogeneities in the flow. The gas entrained in the HH 47 jet may be atomic; our results do not provide direct evidence that stellar jets drive molecular outflows

Unravelling the Yeast Cell Cycle Using the TriGen Algorithm

Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior under the conditions tested. Biclustering emerges as an improvement of classical clustering since it relaxes the constraints for grouping allowing genes to be evaluated only under a subset of the conditions and not under all of them. However, this technique is not appropriate for the analysis of temporal microarray data in which the genes are evaluated under certain conditions at several time points. In this paper, we present the results of applying the TriGen algorithm, a genetic algorithm that finds triclusters that take into account the experimental conditions and the time points, to the yeast cell cycle problem, where the goal is to identify all genes whose expression levels are regulated by the cell cycle

Fabry-Perot observations and new models of the HH 47A and HH 47D bow shocks

We present new models for the HH 47 A and HH 47D bow shocks based on line flux and velocity maps obtained with an imaging Fabry-Perot spectrometer. We confirm that HH 47A and HH 47D each show a bow shock/Mach disk morphology, and that velocity variability in the outflow can account for the observed structures. While it was suggested a decade ago that the inner working surface HH 47A appears to be traveling into the wake of HH 47D, we find kinematic evidence that the outer bow shock HH 47D is also not the primary ejection event in the outflow but follows in the wake of previously ejected material. By comparing the observed line ratios and line profiles to those predicted by our bow shock models, we find that both bow shocks have substantially lower shock velocities than their space motions would imply, and that the emission from each bow shock is systematically blueshifted from the rest-frame velocity of the ambient emission, indicating a comoving preshock medium. We derive kinematic ages of ∼1150 yr for HH 47D and ∼550 yr for HH 47A, which implies that the stellar driving source may undergo repetitive eruptions similar to FU Orionis-type outbursts every several hundred years. This timescale is similar to estimates made by Reipurth and collaborators for the separation between major outbursts in the HH 34 and HH 111 stellar jets

The bow shock and mach disk of HH 111V

We present spatially resolved line profiles in Hα and [S II] λλ16716, 6731 across the working surface region in the Herbig-Haro object HH 111V. Data were acquired with the Rutgers/CTIO imaging Fabry-Perot interferometer on the CTIO 4 m telescope at ∼1″.3 FWHM spatial and ∼35 km s-1 FWHM kinetic resolution. We separate Mach disk emission spatially and kinematically from the bow shock emission. We have used the Hα flux measured at the apex of the bow shock to estimate the preshock density of ∼200 cm-3. Our detailed measurements of the electron density as a function of position and velocity across the bow shock, combined with new models of the bow shock emission, show that an ambient magnetic field of ∼30 μG inhibits the compression of the postshock gas. Our models indicate that the magnetic field also contributes to extending the cooling distance behind the shock to resolvable scales, as observed in the spatial separation of [S II] and Hα in the emission-line images of Reipurth et al. However, the ram pressure at the bow shock HH 111V exceeds the magnetic energy density by a factor of ∼103, so the magnetic field is not large enough to change the direction of the flow. The preshock medium must flow away from the stellar energy source at ∼300 km s-1 to account for the observed kinematics of the line emission in HH 111V. Hence, this working surface is a secondary ejection moving into the wake of an earlier ejection. HH 111 is the third case (HH 34 and HH 47 are other examples) of a stellar jet where the brightest bow shock moves into the wake of a previous high-velocity ejection. Balancing the ram pressures in the bow shock and Mach disk yields an estimated jet-to-ambient density ratio ∼10, similar to our previous estimate for the HH 34 jet (Morse et al.)

Extracting collective trends from Twitter using social-based data mining

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40495-5_62Proceedings 5th International Conference, ICCCI 2013, Craiova, Romania, September 11-13, 2013,Social Networks have become an important environment for Collective Trends extraction. The interactions amongst users provide information of their preferences and relationships. This information can be used to measure the influence of ideas, or opinions, and how they are spread within the Network. Currently, one of the most relevant and popular Social Network is Twitter. This Social Network was created to share comments and opinions. The information provided by users is specially useful in different fields and research areas such as marketing. This data is presented as short text strings containing different ideas expressed by real people. With this representation, different Data Mining and Text Mining techniques (such as classification and clustering) might be used for knowledge extraction trying to distinguish the meaning of the opinions. This work is focused on the analysis about how these techniques can interpret these opinions within the Social Network using information related to IKEA® company.The preparation of this manuscript has been supported by the Spanish Ministry of Science and Innovation under the following projects: TIN2010-19872, ECO2011-30105 (National Plan for Research, Development and Innovation) and the Multidisciplinary Project of Universidad Aut´onoma de Madrid (CEMU-2012-034