The Hunt for Red Quasars : Luminous Obscured Black Hole Growth Unveiled in the Stripe 82 X-Ray Survey

We present results of a ground-based near-infrared campaign with Palomar TripleSpec, Keck NIRSPEC, and Gemini GNIRS to target two samples of reddened active galactic nucleus (AGN) candidates from the 31 deg(2) Stripe 82 X-ray survey. One sample, which is similar to 89% complete to K 4, Vega). The fainter sample (K > 17, Vega) represents a pilot program to follow-up four sources from a parent sample of 34 that are not detected in the single-epoch SDSS catalog and have WISE quasar colors. All 12 sources are broad-line AGNs (at least one permitted emission line has an FWHM exceeding 1300 km s(-1)) and span a redshift range 0.59 0.5), and a greater percentage have high X-ray luminosities (L-X,L- full > 10(44) erg s(-1)). Such outflows and high luminosities may be consistent with the paradigm that reddened broad-line AGNs represent a transitory phase in AGN evolution as described by the major merger model for black hole growth. Results from our pilot program demonstrate proof of concept that our selection technique is successful in discovering reddened quasars at z > 1 missed by optical surveys.Peer reviewe

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

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). 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 (eBOSS); 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 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 website (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.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Dying of the Light: An X-ray Fading Cold Quasar at z ~ 0.405

Cold quasars are a rare subpopulation observed to host unobscured, X-ray luminous active galactic nuclei (AGN) while also retaining a cold gas supply fueling high star formation rates. These objects are interpreted as AGN early in their evolution. We present new SOFIA HAWC+ far-infrared observations, FUV-FIR photometry, and optical spectroscopy to characterize the accretion and star formation behavior in a cold quasar at z ~ 0.405 (CQ 4479). CQ 4479 is a starburst galaxy with a predominantly young stellar population and a high gas mass fraction of ~50-70%. The AGN component has yet to become the dominant component of the FIR emission. We also find AGN bolometric luminosity that varies as a function of observation method and AGN region probed. Finally, we identify a candidate outflow feature corroborating the hypothesis that cold quasars have energetic feedback. This object presents an intriguing look into the early stages of AGN feedback and probes the rare phase where an AGN and cold gaseous component co-exist.Comment: 10 pages, 8 figures, Published in ApJ 6-November-202

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

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

Using Machine Learning to Determine Morphologies of z < 1 AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey

We present a machine-learning framework to accurately characterize the morphologies of active galactic nucleus (AGN) host galaxies within z < 1. We first use PSFGAN to decouple host galaxy light from the central point source, then we invoke the Galaxy Morphology Network (G a M or N et ) to estimate whether the host galaxy is disk-dominated, bulge-dominated, or indeterminate. Using optical images from five bands of the HSC Wide Survey, we build models independently in three redshift bins: low (0 < z < 0.25), mid (0.25 < z < 0.5), and high (0.5 < z < 1.0). By first training on a large number of simulated galaxies, then fine-tuning using far fewer classified real galaxies, our framework predicts the actual morphology for ∼60%–70% of the host galaxies from test sets, with a classification precision of ∼80%–95%, depending on the redshift bin. Specifically, our models achieve a disk precision of 96%/82%/79% and bulge precision of 90%/90%/80% (for the three redshift bins) at thresholds corresponding to indeterminate fractions of 30%/43%/42%. The classification precision of our models has a noticeable dependency on host galaxy radius and magnitude. No strong dependency is observed on contrast ratio. Comparing classifications of real AGNs, our models agree well with traditional 2D fitting with GALFIT. The PSFGAN+G a M or N et framework does not depend on the choice of fitting functions or galaxy-related input parameters, runs orders of magnitude faster than GALFIT, and is easily generalizable via transfer learning, making it an ideal tool for studying AGN host galaxy morphology in forthcoming large imaging surveys

Perlecan-Containing Pericellular Matrix Regulates Solute Transport and Mechanosensing Within the Osteocyte Lacunar-Canalicular System

The pericellular matrix (PCM), a thin coating surrounding nearly all mammalian cells, plays a critical role in many cell-surface phenomena. In osteocytes, the PCM is believed to control both “outside-in” (mechanosensing) and “inside-out” (signaling molecule transport) processes. However, the osteocytic PCM is challenging to study in situ because it is thin (∼100 nm) and enclosed in mineralized matrix. To this end, we recently developed a novel tracer velocimetry approach that combined fluorescence recovery after photobleaching (FRAP) imaging with hydrodynamic modeling to quantify the osteocytic PCM in young murine bone. In this study, we applied the technique to older mice expressing or deficient for perlecan/HSPG2, a large heparan-sulfate proteoglycan normally secreted in osteocytic PCM. The objectives were (1) to characterize transport within an altered PCM; (2) to test the sensitivity of our approach in detecting the PCM alterations; and (3) to dissect the roles of the PCM in osteocyte mechanosensing. We found that: (1) solute transport increases in the perlecan-deficient (hypomorphic [Hypo]) mice compared with control mice; (2) PCM fiber density decreases with aging and perlecan deficiency; (3) osteocytes in the Hypo bones are predicted to experience higher shear stress (+34%), but decreased fluid drag force (−35%) under 3-N peak tibial loading; and (4) when subjected to tibial loading in a preliminary in vivo experiment, the Hypo mice did not respond to the anabolic stimuli as the CTL mice did. These findings support the hypothesis that the PCM fibers act as osteocyte's sensing antennae, regulating load-induced cellular stimulations and thus bone's sensitivity and in vivo bone adaptation. If this hypothesis is further confirmed, osteocytic PCM could be new targets to develop osteoporosis treatments by modulating bone's intrinsic sensitivity to mechanical loading and be used to design patient-specific exercise regimens to promote bone formation

Real-time sewage surveillance for SARS-CoV-2 in Dhaka, Bangladesh versus clinical COVID-19 surveillance: a longitudinal environmental surveillance study (Dec 2019 – Dec 2021)

Background: Clinical surveillance for COVID-19 has typically been challenging in low-middle income settings. From December 2019 to December 2021, we implemented environmental surveillance (ES) in a converging informal sewage network in Dhaka, Bangladesh, to investigate SARS-CoV-2 transmission across different income levels of the city compared to clinical surveillance. Methods: All sewage lines were mapped, and sites were selected with estimated catchment population of >1,000 individuals. We analysed 2,073 sewage samples, collected weekly from 37 sites and 648 days of case data from 8 wards with varying socio-economic statuses. We assessed the correlations between the viral load in sewage samples and clinical cases. Findings: SARS-CoV-2 was consistently detected across all wards (low to high income) despite large differences in reported clinical cases and periods of no cases. Most COVID-19 cases (60.3%, n=28,766/47,683) were reported from high-income areas with high levels of clinical testing (261-1603 monthly tests per 100,000 vs. 0-189 in lower-income areas), despite containing 25% (184,117/734,755) of the study population. Conversely, a similar quantity of SARS-CoV-2 was detected in sewage across different income levels (mean difference in high vs. low-income areas: 0.35 log10 viral copies + 1). The correlation between the mean sewage viral load (log10 viral copies + 1) and the log10 clinical cases increased with time (R=0.90 July 2021-December 2021 and R=0.59 July 2020-December 2020). Before major waves of infection, viral load quantity in sewage samples increased one to two weeks before the clinical cases. Interpretation: This study demonstrates the utility and importance of environmental surveillance for SARS-CoV-2 in a low-middle income country. We show ES provides an early warning of increases in transmission and shows evidence of persistent circulation in poorer areas where access to clinical testing is limited. Funding: Bill and Melinda Gates Foundation (INV-022699 and OPP1193124 to M Taniuchi). IM Blake acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 programme supported by the European Union