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Sökning: WFRF:(Simmons Audrey)

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1.
  • Dilday, Benjamin, et al. (författare)
  • A Measurement of the Rate of Type Ia Supernovae in Galaxy Clusters from the SDSS-II Supernova Survey
  • 2010
  • Ingår i: Astrophysical Journal. - 0004-637X .- 1538-4357. ; 715, s. 1021-1035
  • Tidskriftsartikel (refereegranskat)abstract
    • We present measurements of the Type Ia supernova (SN) rate in galaxy clusters based on data from the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. The cluster SN Ia rate is determined from 9 SN events in a set of 71 C4 clusters at z <= 0.17 and 27 SN events in 492 maxBCG clusters at 0.1 <= z <= 0.3. We find values for the cluster SN Ia rate of (0.37+0.17+0.01 -0.12-0.01) SNur h 2 and (0.55+0.13+0.02 -0.11-0.01) SNur h 2 (SNux = 10-12 L -1 xsun yr-1) in C4 and maxBCG clusters, respectively, where the quoted errors are statistical and systematic, respectively. The SN rate for early-type galaxies is found to be (0.31+0.18+0.01 -0.12-0.01) SNur h 2 and (0.49+0.15+0.02 -0.11-0.01) SNur h 2 in C4 and maxBCG clusters, respectively. The SN rate for the brightest cluster galaxies (BCG) is found to be (2.04+1.99+0.07 -1.11-0.04) SNur h 2 and (0.36+0.84+0.01 -0.30-0.01) SNur h 2 in C4 and maxBCG clusters, respectively. The ratio of the SN Ia rate in cluster early-type galaxies to that of the SN Ia rate in field early-type galaxies is 1.94+1.31+0.043 -0.91-0.015 and 3.02+1.31+0.062 -1.03-0.048, for C4 and maxBCG clusters, respectively. The SN rate in galaxy clusters as a function of redshift, which probes the late time SN Ia delay distribution, shows only weak dependence on redshift. Combining our current measurements with previous measurements, we fit the cluster SN Ia rate data to a linear function of redshift, and find rL = [(0.49+0.15 -0.14)+(0.91+0.85 -0.81) × z] SNuB h 2. A comparison of the radial distribution of SNe in cluster to field early-type galaxies shows possible evidence for an enhancement of the SN rate in the cores of cluster early-type galaxies. With an observation of at most three hostless, intra-cluster SNe Ia, we estimate the fraction of cluster SNe that are hostless to be (9.4+8.3 -5.1)%.
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2.
  • Dilday, Benjamin, et al. (författare)
  • Measurements of the Rate of Type Ia Supernovae at Redshift lsim0.3 from the Sloan Digital Sky Survey II Supernova Survey
  • 2010
  • Ingår i: Astrophysical Journal. - 0004-637X .- 1538-4357. ; 713, s. 1026-1036
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a measurement of the volumetric Type Ia supernova (SN Ia) rate based on data from the Sloan Digital Sky Survey II (SDSS-II) Supernova Survey. The adopted sample of supernovae (SNe) includes 516 SNe Ia at redshift z <~ 0.3, of which 270(52%) are spectroscopically identified as SNe Ia. The remaining 246 SNe Ia were identified through their light curves; 113 of these objects have spectroscopic redshifts from spectra of their host galaxy, and 133 have photometric redshifts estimated from the SN light curves. Based on consideration of 87 spectroscopically confirmed non-Ia SNe discovered by the SDSS-II SN Survey, we estimate that 2.04+1.61 -0.95% of the photometric SNe Ia may be misidentified. The sample of SNe Ia used in this measurement represents an order of magnitude increase in the statistics for SN Ia rate measurements in the redshift range covered by the SDSS-II Supernova Survey. If we assume an SN Ia rate that is constant at low redshift (z < 0.15), then the SN observations can be used to infer a value of the SN rate of rV = (2.69+0.34+0.21 -0.30-0.01)×10-5 SNe yr-1 Mpc-3 (H 0/(70 km s-1 Mpc-1))3 at a mean redshift of ~0.12, based on 79 SNe Ia of which 72 are spectroscopically confirmed. However, the large sample of SNe Ia included in this study allows us to place constraints on the redshift dependence of the SN Ia rate based on the SDSS-II Supernova Survey data alone. Fitting a power-law model of the SN rate evolution, rV (z) = Ap × ((1 + z)/(1 + z 0))ν, over the redshift range 0.0 < z < 0.3 with z 0 = 0.21, results in Ap = (3.43+0.15 -0.15) × 10-5 SNe yr-1 Mpc-3 (H 0/(70 km s-1 Mpc-1))3 and ν = 2.04+0.90 -0.89.
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3.
  • Galbany, Lluis, et al. (författare)
  • TYPE Ia SUPERNOVA PROPERTIES AS A FUNCTION OF THE DISTANCE TO THE HOST GALAXY IN THE SDSS-II SN SURVEY
  • 2012
  • Ingår i: Astrophysical Journal. - 0004-637X .- 1538-4357. ; 755:2, s. 125-
  • Tidskriftsartikel (refereegranskat)abstract
    • We use Type Ia supernovae (SNe Ia) discovered by the Sloan Digital Sky Survey-II SN Survey to search for dependencies between SN Ia properties and the projected distance to the host-galaxy center, using the distance as a proxy for local galaxy properties (local star formation rate, local metallicity, etc.). The sample consists of almost 200 spectroscopically or photometrically confirmed SNe Ia at redshifts below 0.25. The sample is split into two groups depending on the morphology of the host galaxy. We fit light curves using both MLCS2k2 and SALT2, and determine color (A(V), c) and light-curve shape (Delta, x(1)) parameters for each SN Ia, as well as its residual in the Hubble diagram. We then correlate these parameters with both the physical and the normalized distances to the center of the host galaxy and look for trends in the mean values and scatters of these parameters with increasing distance. The most significant (at the 4 sigma level) finding is that the average fitted A(V) from MLCS2k2 and c from SALT2 decrease with the projected distance for SNe Ia in spiral galaxies. We also find indications that supernovae (SNe) in elliptical galaxies tend to have narrower light curves if they explode at larger distances, although this may be due to selection effects in our sample. We do not find strong correlations between the residuals of the distance moduli with respect to the Hubble flow and the galactocentric distances, which indicates a limited correlation between SN magnitudes after standardization and local host metallicity.
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4.
  • Hudson, Lawrence N, et al. (författare)
  • The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
  • 2017
  • Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 7:1, s. 145-188
  • Tidskriftsartikel (refereegranskat)abstract
    • The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
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5.
  • Klionsky, Daniel J., et al. (författare)
  • Guidelines for the use and interpretation of assays for monitoring autophagy
  • 2012
  • Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
  • Forskningsöversikt (refereegranskat)abstract
    • In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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6.
  • Parreiras, Lucas S., et al. (författare)
  • Engineering and two-stage evolution of a lignocellulosic hydrolysate-tolerant Saccharomyces cerevisiae strain for anaerobic fermentation of xylose from AFEX pretreated corn stover
  • 2014
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:9
  • Tidskriftsartikel (refereegranskat)abstract
    • The inability of the yeast Saccharomyces cerevisiae to ferment xylose effectively under anaerobic conditions is a major barrier to economical production of lignocellulosic biofuels. Although genetic approaches have enabled engineering of S. cerevisiae to convert xylose efficiently into ethanol in defined lab medium, few strains are able to ferment xylose from lignocellulosic hydrolysates in the absence of oxygen. This limited xylose conversion is believed to result from small molecules generated during biomass pretreatment and hydrolysis, which induce cellular stress and impair metabolism. Here, we describe the development of a xylose-fermenting S. cerevisiae strain with tolerance to a range of pretreated and hydrolyzed lignocellulose, including Ammonia Fiber Expansion (AFEX)-pretreated corn stover hydrolysate (ACSH). We genetically engineered a hydrolysate-resistant yeast strain with bacterial xylose isomerase and then applied two separate stages of aerobic and anaerobic directed evolution. The emergent S. cerevisiae strain rapidly converted xylose from lab medium and ACSH to ethanol under strict anaerobic conditions. Metabolomic, genetic and biochemical analyses suggested that a missense mutation in GRE3, which was acquired during the anaerobic evolution, contributed toward improved xylose conversion by reducing intracellular production of xylitol, an inhibitor of xylose isomerase. These results validate our combinatorial approach, which utilized phenotypic strain selection, rational engineering and directed evolution for the generation of a robust S. cerevisiae strain with the ability to ferment xylose anaerobically from ACSH.
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