Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology.Comment: 20 pages, 5 figures. In Press in Sci Rep 201

Vertical structure models of the 1990 equatorial disturbance on Saturn

In September 1990, an atmospheric disturbance in the form of an abnormally high albedo area developed in the equatorial region of Saturn. Events of this nature are exceedingly rare for this planet as they have been detected in the equatorial region on only two other occasions in over a century. In ongoing monitoring of the atmospheres of the outer planets, CCD imaging observations of Saturn by New Mexico State University's Tortugas Mountain Station were made before, during, and after the disturbance's formation through both broad-band filters and narrow-band visible/near-IR filters centered in methane absorption bands. Also, multispectral Hubble Space Telescope observations were made within weeks of the event and later in 1991. These observations were calibrated and scans of reflectivity at constant latitude are being modeled with a vertically inhomogeneous, multiple scattering model previously used to model Jupiter's South Equatorial Belt brightening event in 1989. In addition, the reflectivity of the disturbance as a function of the scattering angles is being obtained so as to model this feature's vertical structure in particular. A preliminary report of the modeling results will be presented

The Discovery of lambda Bootis Stars -- The Southern Survey II

The $\lambda$ Boo stars are chemically peculiar A-type stars whose abundance anomalies are associated with the accretion of metal-poor material. We searched for $\lambda$ Boo stars in the southern hemisphere in a targeted spectroscopic survey of metal-weak and emission-line stars. Obtaining spectra for 308 stars and classifying them on the MK system, we found or co-discovered 24 new $\lambda$ Boo stars. We also revised the classifications of 11 known $\lambda$ Boo stars, one of which turned out to be a chemically normal rapid rotator. We show that stars previously classified in the literature as blue horizontal branch stars or emission-line A stars have a high probability of being $\lambda$ Boo stars, although this conclusion is based on small-number statistics. Using WISE infrared fluxes, we searched our targets for infrared excesses that might be attributable to protoplanetary or debris discs as the source of the accreted material. Of the 34 $\lambda$ Boo stars in our sample, 21 at various main-sequence ages have infrared excesses, confirming that not all $\lambda$ Boo stars are young.Comment: Accepted for publication in MNRAS. Figures do not have heavy reliance on colour. Online data will be hosted with the journal / Vizier@CD

NGC 5548 in a Low-Luminosity State: Implications for the Broad-Line Region

We describe results from a new ground-based monitoring campaign on NGC 5548, the best studied reverberation-mapped AGN. We find that it was in the lowest luminosity state yet recorded during a monitoring program, namely L(5100) = 4.7 x 10^42 ergs s^-1. We determine a rest-frame time lag between flux variations in the continuum and the Hbeta line of 6.3 (+2.6/-2.3) days. Combining our measurements with those of previous campaigns, we determine a weighted black hole mass of M_BH = 6.54 (+0.26/-0.25) x 10^7 M_sun based on all broad emission lines with suitable variability data. We confirm the previously-discovered virial relationship between the time lag of emission lines relative to the continuum and the width of the emission lines in NGC 5548, which is the expected signature of a gravity-dominated broad-line region. Using this lowest luminosity state, we extend the range of the relationship between the luminosity and the time lag in NGC 5548 and measure a slope that is consistent with alpha = 0.5, the naive expectation for the broad line region for an assumed form of r ~ L^alpha. This value is also consistent with the slope recently determined by Bentz et al. for the population of reverberation-mapped AGNs as a whole.Comment: 24 pages, 3 tables, 7 figures, accepted for publication in Ap

The Mass of the Black Hole in the Seyfert 1 Galaxy NGC 4593 from Reverberation Mapping

We present new observations leading to an improved black hole mass estimate for the Seyfert 1 galaxy NGC 4593 as part of a reverberation-mapping campaign conducted at the MDM Observatory. Cross-correlation analysis of the H_beta emission-line light curve with the optical continuum light curve reveals an emission-line time delay of 3.73 (+-0.75) days. By combining this time delay with the H_beta line width, we derive a central black hole mass of M_BH = 9.8(+-2.1)x10^6 M_sun, an improvement in precision of a factor of several over past results.Comment: 22 pages, 3 tables, 5 figures, accepted for publication in Ap

Local v.s. AWS provisioning: Experience fusing a month’s data on AWS and local provisioning

The Terra ACCESS project provides enhanced access via fused data from all instruments on the NASA TERRA Earth science satellite. The fused data set is 2.4 PB in size and covers the period 2000 - 2015. This document is a technical report from early 2019, comparing the benefits and costs of performing the data fusion on Amazon Web Services and the Illinois campus cluster.NASA Award NNX16AM07AOpe

The Malta cistern mapping project : expedition II

This paper documents the second of two archeological expeditions that employed several underwater robot mapping and localization techniques. The goal of this project is to explore and map ancient cisterns located on the islands of Malta and Gozo. Dating back to 300 B.C., the cisterns of interest acted as water storage systems for fortresses, private homes, and churches. They often consisted of several connected chambers, still containing water. A Remotely Operated Vehicle (ROV), was deployed into cisterns to obtain video and sonar images. Using a variety of sonar based mapping techniques, two-dimensional maps of 18 different cisterns were created.peer-reviewe

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a investigation for maximising their effectiveness.We carry out a comparison between several common machine learning methods for galaxy classification (Convolutional Neural Network (CNN), K-nearest neighbour, LogisticRegression, Support Vector Machine, Random Forest, and Neural Networks) by using DarkEnergy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project(GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of _2,800 galaxies with visual classification from GZ1, we reach an accuracy of _0.99 for the morphological classification of Ellipticals and Spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals an the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually Lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both Es and Spirals.We confirm that _2.5% galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result)