1,919 research outputs found

    The host galaxies and explosion sites of long-duration gamma-ray bursts: Hubble Space Telescope near-infrared imaging

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    We present the results of a Hubble Space Telescope WFC3/F160WSnapshot survey of the host galaxies of 39 long-duration gamma-ray bursts (LGRBs) at z < 3. We have non-detections of hosts at the locations of four bursts. Sufficient accuracy to astrometrically align optical afterglowimages and determine the location of the LGRB within its hostwas possible for 31/35 detected hosts. In agreement with other work, we find the luminosity distribution of LGRB hosts is significantly fainter than that of a star formation rate-weighted field galaxy sample over the same redshift range, indicating LGRBs are not unbiasedly tracing the star formation rate. Morphologically, the sample of LGRB hosts is dominated by spiral-like or irregular galaxies. We find evidence for evolution of the population of LGRB hosts towards lower luminosity, higher concentrated hosts at lower redshifts. Their half-light radii are consistent with other LGRB host samples where measurements were made on rest-frame UV observations. In agreement with recent work, we find their 80 per cent enclosed flux radii distribution to be more extended than previously thought, making them intermediate between core-collapse supernova (CCSN) and superluminous supernova (SLSN) hosts. The galactocentric projectedoffset distribution confirms LGRBs as centrally concentrated, much more so than CCSNe and similar to SLSNe. LGRBs are strongly biased towards the brighter regions in their host light distributions, regardless of their offset. We find a correlation between the luminosity of the LGRB explosion site and the intrinsic column density, NH, towards the burst. © 2017 The Authors

    Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

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    One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

    Duckietown: An Innovative Way to Teach Autonomy

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    Teaching robotics is challenging because it is a multidisciplinary, rapidly evolving and experimental discipline that integrates cutting-edge hardware and software. This paper describes the course design and first implementation of Duckietown, a vehicle autonomy class that experiments with teaching innovations in addition to leveraging modern educational theory for improving student learning. We provide a robot to every student, thanks to a minimalist platform design, to maximize active learning; and introduce a role-play aspect to increase team spirit, by modeling the entire class as a fictional start-up (Duckietown Engineering Co.). The course formulation leverages backward design by formalizing intended learning outcomes (ILOs) enabling students to appreciate the challenges of: (a) heterogeneous disciplines converging in the design of a minimal self-driving car, (b) integrating subsystems to create complex system behaviors, and (c) allocating constrained computational resources. Students learn how to assemble, program, test and operate a self-driving car (Duckiebot) in a model urban environment (Duckietown), as well as how to implement and document new features in the system. Traditional course assessment tools are complemented by a full scale demonstration to the general public. The “duckie” theme was chosen to give a gender-neutral, friendly identity to the robots so as to improve student involvement and outreach possibilities. All of the teaching materials and code is released online in the hope that other institutions will adopt the platform and continue to evolve and improve it, so to keep pace with the fast evolution of the field.National Science Foundation (U.S.) (Award IIS #1318392)National Science Foundation (U.S.) (Award #1405259

    Differential expression analysis for sequence count data

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    *Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.&#xd;&#xa;&#xd;&#xa;*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. &#xd;&#xa;&#xd;&#xa;*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from &#x22;http://www-huber.embl.de/users/anders/DESeq&#x22;:http://www-huber.embl.de/users/anders/DESeq

    Long gamma-ray bursts and core-collapse supernovae have different environments

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    When massive stars exhaust their fuel they collapse and often produce the extraordinarily bright explosions known as core-collapse supernovae. On occasion, this stellar collapse also powers an even more brilliant relativistic explosion known as a long-duration gamma-ray burst. One would then expect that long gamma-ray bursts and core-collapse supernovae should be found in similar galactic environments. Here we show that this expectation is wrong. We find that the long gamma-ray bursts are far more concentrated on the very brightest regions of their host galaxies than are the core-collapse supernovae. Furthermore, the host galaxies of the long gamma-ray bursts are significantly fainter and more irregular than the hosts of the core-collapse supernovae. Together these results suggest that long-duration gamma-ray bursts are associated with the most massive stars and may be restricted to galaxies of limited chemical evolution. Our results directly imply that long gamma-ray bursts are relatively rare in galaxies such as our own Milky Way.Comment: 27 pages, 4 figures, submitted to Nature on 22 August 2005, revised 9 February 2006, online publication 10 May 2006. Supplementary material referred to in the text can be found at http://www.stsci.edu/~fruchter/GRB/locations/supplement.pdf . This new version contains minor changes to match the final published versio

    Fermi Gamma-ray Imaging of a Radio Galaxy

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    The Fermi Gamma-ray Space Telescope has detected the gamma-ray glow emanating from the giant radio lobes of the radio galaxy Centaurus A. The resolved gamma-ray image shows the lobes clearly separated from the central active source. In contrast to all other active galaxies detected so far in high-energy gamma-rays, the lobe flux constitutes a considerable portion (>1/2) of the total source emission. The gamma-ray emission from the lobes is interpreted as inverse Compton scattered relic radiation from the cosmic microwave background (CMB), with additional contribution at higher energies from the infrared-to-optical extragalactic background light (EBL). These measurements provide gamma-ray constraints on the magnetic field and particle energy content in radio galaxy lobes, and a promising method to probe the cosmic relic photon fields.Comment: 27 pages, includes Supplementary Online Material; corresponding authors: C.C. Cheung, Y. Fukazawa, J. Knodlseder, L. Stawar

    Detection of Gamma-Ray Emission from the Starburst Galaxies M82 and NGC 253 with the Large Area Telescope on Fermi

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    We report the detection of high-energy gamma-ray emission from two starburst galaxies using data obtained with the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. Steady point-like emission above 200 MeV has been detected at significance levels of 6.8 sigma and 4.8 sigma respectively, from sources positionally coincident with locations of the starburst galaxies M82 and NGC 253. The total fluxes of the sources are consistent with gamma-ray emission originating from the interaction of cosmic rays with local interstellar gas and radiation fields and constitute evidence for a link between massive star formation and gamma-ray emission in star-forming galaxies.Comment: Submitted to ApJ Letter

    Search For Heavy Pointlike Dirac Monopoles

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    We have searched for central production of a pair of photons with high transverse energies in ppˉp\bar p collisions at s=1.8\sqrt{s} = 1.8 TeV using 70pb170 pb^{-1} of data collected with the D\O detector at the Fermilab Tevatron in 1994--1996. If they exist, virtual heavy pointlike Dirac monopoles could rescatter pairs of nearly real photons into this final state via a box diagram. We observe no excess of events above background, and set lower 95% C.L. limits of 610,870,or1580GeV/c2610, 870, or 1580 GeV/c^2 on the mass of a spin 0, 1/2, or 1 Dirac monopole.Comment: 12 pages, 4 figure
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