ORCID Profile
0000-0003-3574-2963
Current Organisation
Washington State University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: American Chemical Society (ACS)
Date: 11-03-2022
Publisher: American Astronomical Society
Date: 22-10-2020
Publisher: American Chemical Society (ACS)
Date: 11-2019
Abstract: α-Dicarbonyl compounds (α-DCs) are a major class of intermediates generated during Maillard reactions. They can serve as chemical markers of thermal processing and storage of sugar-rich foods. To distinguish between naturally matured acacia honey (NMAH) and artificially heated acacia honey (AHAH), we purified 12 major α-DCs quinoxaline derivatives to investigate the effects of temperature during heat treatment and storage on their accumulation in acacia honey. Nine of the 12 α-dicarbonyl compounds were found in acacia honey s les, and their contents varied depending on processing and storage conditions. Among them, the contents of 3-deoxyglucosulose (3-DG), 1,4-dideoxyglucosone (1,4-DDG), and 1-deoxyglucosone (1-DG) increased commensurately with heat. 3-DG content ranged from 103.7 to 146.6 mg/kg in NMAH and 572.4-1371.2 mg/kg in AHAH. Given the abundance and stability of 3-DG following heat treatment and storage, this compound can potentially serve as a reliable marker for distinguishing between NMAH and AHAH.
Publisher: Wiley
Date: 03-2019
DOI: 10.1111/IJFS.14124
Publisher: American Astronomical Society
Date: 05-2023
Abstract: We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high ( %) in idual completeness and purity, which will help build an anchor photometric SNe Ia s le for cosmology. We then use our photometric classifier to characterize our photometric s le of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.
Location: United States of America
No related grants have been discovered for Christopher Carroll.