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Träfflista för sökning "WFRF:(Masters A.) srt2:(2015-2019)"

Sökning: WFRF:(Masters A.) > (2015-2019)

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1.
  • Blanton, Michael R., et al. (författare)
  • Sloan Digital Sky Survey IV : Mapping the Milky Way, Nearby Galaxies, and the Distant Universe
  • 2017
  • Ingår i: Astronomical Journal. - : IOP Publishing Ltd. - 0004-6256 .- 1538-3881. ; 154:1
  • Tidskriftsartikel (refereegranskat)abstract
    • We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and. high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z similar to 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z similar to 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs. and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the. Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July.
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2.
  • Abolfathi, Bela, et al. (författare)
  • The Fourteenth Data Release of the Sloan Digital Sky Survey : First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment
  • 2018
  • Ingår i: Astrophysical Journal Supplement Series. - : IOP Publishing Ltd. - 0067-0049 .- 1538-4365. ; 235:2
  • Tidskriftsartikel (refereegranskat)abstract
    • The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V.
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3.
  • Aguado, D. S., et al. (författare)
  • The Fifteenth Data Release of the Sloan Digital Sky Surveys : First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library
  • 2019
  • Ingår i: Astrophysical Journal Supplement Series. - : Institute of Physics Publishing (IOPP). - 0067-0049 .- 1538-4365. ; 240:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July-2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA-we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data.
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4.
  • Mehrtens, N., et al. (författare)
  • The XMM Cluster Survey : the halo occupation number of BOSS galaxies in X-ray clusters
  • 2016
  • Ingår i: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 463:2, s. 1929-1943
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a direct measurement of the mean halo occupation distribution (HOD) of galaxies taken from the eleventh data release (DR11) of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS). The HOD of BOSS low-redshift (LOWZ: 0.2 < z < 0.4) and Constant-Mass (CMASS: 0.43 < z < 0.7) galaxies is inferred via their association with the dark matter haloes of 174 X-ray-selected galaxy clusters drawn from the XMM Cluster Survey (XCS). Halo masses are determined for each galaxy cluster based on X-ray temperature measurements, and range between log10(M180/M⊙) = 13 and 15. Our directly measured HODs are consistent with the HOD-model fits inferred via the galaxy-clustering analyses of Parejko et al. for the BOSS LOWZ sample and White et al. for the BOSS CMASS sample. Under the simplifying assumption that the other parameters that describe the HOD hold the values measured by these authors, we have determined a best-fitting alpha-index of 0.91 ± 0.08 and 1.27−0.04+0.03" role="presentation">1.27+0.03−0.04 for the CMASS and LOWZ HOD, respectively. These alpha-index values are consistent with those measured by White et al. and Parejko et al. In summary, our study provides independent support for the HOD models assumed during the development of the BOSS mock-galaxy catalogues that have subsequently been used to derive BOSS cosmological constraints.
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7.
  • Ashton, Nicholas J., et al. (författare)
  • A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease.
  • 2019
  • Ingår i: Science advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 5:2
  • Tidskriftsartikel (refereegranskat)abstract
    • A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer's disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.
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8.
  • Masters, C. L., et al. (författare)
  • Alzheimer's disease
  • 2015
  • Ingår i: Nature Reviews Disease Primers. - : Springer Science and Business Media LLC. - 2056-676X. ; 1
  • Tidskriftsartikel (refereegranskat)abstract
    • Alzheimer's disease is a chronic illness with long preclinical and prodromal phases (20 years) and an average clinical duration of 8-10 years. The disease has an estimated prevalence of 10-30% in the population >65 years of age with an incidence of 1-3%. Most patients with Alzheimer's disease (>95%) have the sporadic form, which is characterized by a late onset (80-90 years of age), and is the consequence of the failure to clear the amyloid-beta (A beta) peptide from the interstices of the brain. A large number of genetic risk factors for sporadic disease have been identified. A small proportion of patients (<1%) have inherited mutations in genes that affect processing of A beta and develop the disease at a much younger age (mean age of similar to 45 years). Detection of the accumulation of A beta is now possible in preclinical and prodromal phases using cerebrospinal fluid biomarkers and PET. Several approved drugs ameliorate some of the symptoms of Alzheimer's disease, but no current interventions can modify the underlying disease mechanisms. Management is focused on the support of the social networks surrounding the patient and the treatment of any co-morbid illnesses, such as cerebrovascular disease.
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9.
  • Shaw, L. M., et al. (författare)
  • Method comparison study of the Elecsys® β-Amyloid (1–42) CSF assay versus comparator assays and LC-MS/MS
  • 2019
  • Ingår i: Clinical Biochemistry. - : Elsevier BV. - 0009-9120. ; 72:October, s. 7-14
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Alzheimer's disease (AD) biomarkers, such as cerebrospinal fluid (CSF) amyloid-β (1–42; Aβ42), can provide high diagnostic accuracy. Several immunoassays are available for Aβ42 quantitation, but standardisation across assays remains an issue. We compared the Elecsys® β-Amyloid (1–42) CSF assay with three assays and two liquid chromatography tandem mass spectrometry (LC-MS/MS) methods. Methods: Three method comparison studies evaluated the correlation between the Elecsys® β-Amyloid (1–42) CSF assay versus: INNOTEST® β-AMYLOID(1–42) (860 samples) and the Roche Diagnostics-developed LC-MS/MS method (250 samples); INNO-BIA AlzBio3 and the University of Pennsylvania (UPenn)-developed LC-MS/MS method (250 samples); and ADx-EUROIMMUN Beta-Amyloid (1–42) enzyme-linked immunosorbent assay (ELISA) (49 samples). Results: High correlation was demonstrated between Elecsys® β-Amyloid (1–42) CSF and comparator assays: INNOTEST® β-AMYLOID(1–42) (Spearman's ρ, 0.954); INNO-BIA AlzBio3 (Spearman's ρ, 0.864); ADx-EUROIMMUN Beta-Amyloid (1–42) ELISA (Pearson's r, 0.925). Elecsys® assay and LC-MS/MS measurements were highly correlated: Pearson's r, 0.949 (Roche Diagnostics-developed method) and 0.943 (UPenn-developed method). Conclusion: Findings from this multicentre evaluation further support use of the Elecsys® β-Amyloid (1–42) CSF assay to aid AD diagnosis. CSF-based certified reference materials should improve agreement across assays and mass spectrometry-based methods, which is essential to establish a global uniform CSF Aβ42 cut-off to detect amyloid pathology. © 2019
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