VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift $\textit{zs}$ = 2.74 and image separation of 2.9 arcsec lensed by a foreground $\textit{zl}$ = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and $\textit{gi}$ multicolour photometric observations from the Dark Energy Survey (DES), near-IR $\textit{JK}$ photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with $\textit{iAB}$ = 18.61 and $\textit{iAB}$ = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of $\textit{z}$ = 2.739 ± 0.003 and a foreground early-type galaxy with $\textit{z}$ = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass $\textit{M}$enc ∼ 4 × 10$^{11}$$\textit{M}$⊙ and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.FO is supported jointly by CAPES (the Science without Borders programme) and the Cambridge Commonwealth Trust. RGM, CAL, MWA, MB, SLR acknowledge the support of UK Science and Technology Research Council (STFC). AJC acknowledges the support of a Raymond and Beverly Sackler visiting fellowship at the Institute of Astronomy. For further information regarding funding please visit the publisher's website

HOST GALAXY IDENTIFICATION FOR SUPERNOVA SURVEYS

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope, which will discover SNe by the thousands. Spectroscopic resources are limited, and so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey

Weight outcomes audit in 1.3 million adults during their first 3 months' attendance in a commercial weight management programme

Background: Over sixty percent of adults in the UK are now overweight/obese. Weight management on a national scale requires behavioural and lifestyle solutions that are accessible to large numbers of people. Evidence suggests commercial weight management programmes help people manage their weight but there is little research examining those that pay to attend such programmes rather than being referred by primary care. The objective of this analysis was to evaluate the effectiveness of a UK commercial weight management programme in self-referred, fee-paying participants. Methods: Electronic weekly weight records were collated for self-referred, fee-paying participants of Slimming World groups joining between January 2010 and April 2012. This analysis reports weight outcomes in 1,356,105 adult, non-pregnant participants during their first 3 months’ attendance. Data were analysed by regression, ANOVA and for binomial outcomes, chi-squared tests using the R statistical program. Results: Mean (SD) age was 42.3 (13.6) years, height 1.65 m (0.08) and start weight was 88.4 kg (18.8). Mean start BMI was 32.6 kg/m² (6.3 kg/m²) and 5 % of participants were men. Mean weight change of all participants was −3.9 kg (3.6), percent weight change −4.4 (3.8), and BMI change was −1.4 kg/m² (1.3). Mean attendance was 7.8 (4.3) sessions in their first 3 months. For participants attending at least 75 % of possible weekly sessions (n = 478,772), mean BMI change was −2.5 kg/m² (1.3), weight change −6.8 kg (3.7) and percent weight change −7.5 % (3.5). Weight loss was greater in men than women absolutely (−6.5 (5.3) kg vs −3.8 (3.4) kg) and as a percentage (5.7 % (4.4) vs 4.3 % (3.7)), respectively. All comparisons were significant (p < 0.001). Level of attendance and percent weight loss in the first week of attendance together accounted for 55 % of the variability in weight lost during the study period. Conclusions: A large-scale commercial lifestyle-based weight management programme had a significant impact on weight loss outcomes over 3 months. Higher levels of attendance led to levels of weight loss known to be associated with significant clinical benefits, which on this scale may have an impact on public health

Clustering of Unhealthy Behaviors in the Aerobics Center Longitudinal Study

Background Clustering of unhealthy behaviors has been reported in previous studies; however the link with all-cause mortality and differences between those with and without chronic disease requires further investigation. Objectives To observe the clustering effects of unhealthy diet, fitness, smoking, and excessive alcohol consumption in adults with and without chronic disease and to assess all-cause mortality risk according to the clustering of unhealthy behaviors. Methods Participants were 13,621 adults (aged 20–84) from the Aerobics Center Longitudinal Study. Four health behaviors were observed (diet, fitness, smoking, and drinking). Baseline characteristics of the study population and bivariate relations between pairs of the health behaviors were evaluated separately for those with and without chronic disease using cross-tabulation and a chi-square test. The odds of partaking in unhealthy behaviors were also calculated. Latent class analysis (LCA) was used to assess clustering. Cox regression was used to assess the relationship between the behaviors and mortality. Results The four health behaviors were related to each other. LCA results suggested that two classes existed. Participants in class 1 had a higher probability of partaking in each of the four unhealthy behaviors than participants in class 2. No differences in health behavior clustering were found between participants with and without chronic disease. Mortality risk increased relative to the number of unhealthy behaviors participants engaged in. Conclusion Unhealthy behaviors cluster together irrespective of chronic disease status. Such findings suggest that multi-behavioral intervention strategies can be similar in those with and without chronic disease

Combining dark energy survey science verification data with near-infrared data from the ESO VISTA hemisphere survey

We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near infrared data from the ESO VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint 7-band ($grizYJK$) photometric catalogues are produced in a single 3 sq-deg DECam field centred at 02h26m$-$04d36m where the availability of ancillary multi-wavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of $\sim$4.5 relative to a simple catalogue level matching and results in a $\sim$1.5 mag increase in the 80\% completeness limit of the NIR data. Almost 70\% of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both $z1$. We present example DES+VHS colour selection criteria for high redshift Luminous Red Galaxies (LRGs) at $z\sim0.7$ as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with $<$10\% contamination from galactic stars in the case of spectroscopically confirmed quasars and $<0.5\%$ contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS dataset, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.We thank the referee, Nicholas Cross, for a very useful report on this manuscript. MB acknowledges a postdoctoral fellowship via OL’s Advanced European Research Council Grant (TESTDE). Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana- Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, Financiadora de Estudos e Projetos, Fundac¸ ˜ao Carlos Chagas Filho de Amparo `a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cient´ıfico e Tecnol ´ogico and the Minist´erio da Ciˆencia e Tecnologia, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratories, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the Eidgen¨ossische Technische Hochschule (ETH) Z¨urich, Fermi National Accelerator Laboratory, the University of Edinburgh, the University of Illinois at Urbana-Champaign, the Institut de Ciencies de l’Espai (IEEC/CSIC), the Institut de Fisica d’Altes Energies, the Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universit ¨at and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Laboratory, Stanford University, the University of Sussex, and Texas A&M University. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2009-13936, AYA2012- 39559, AYA2012-39620, and FPA2012-39684, which include FEDER funds from the European Union. We are grateful for the extraordinary contributions of our CTIO colleagues and the DES Camera, Commissioning and Science Verification teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DES Data Management organisation. The analysis presented here is based on observations obtained as part of the VISTA Hemisphere Survey, ESO Progam, 179.A- 2010 (PI: McMahon) and data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 179.A-2006 (PI: Jarvis). Data for the OzDES spectroscopic survey were obtained with the Anglo-Australian Telescope (program numbers 12B/11 and 13B/12). Parts of this research were conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO), through project number CE110001020. TMD acknowledges the support of the Australian Research Council through Future Fellowship, FT100100595.This is the final published version. It first appeared at http://mnras.oxfordjournals.org/content/446/3/2523.abstract

Associations of iron metabolism genes with blood manganese levels: a population-based study with validation data from animal models

<p>Abstract</p> <p>Background</p> <p>Given mounting evidence for adverse effects from excess manganese exposure, it is critical to understand host factors, such as genetics, that affect manganese metabolism.</p> <p>Methods</p> <p>Archived blood samples, collected from 332 Mexican women at delivery, were analyzed for manganese. We evaluated associations of manganese with functional variants in three candidate iron metabolism genes: <it>HFE </it>[hemochromatosis], <it>TF </it>[transferrin], and <it>ALAD </it>[δ-aminolevulinic acid dehydratase]. We used a knockout mouse model to parallel our significant results as a novel method of validating the observed associations between genotype and blood manganese in our epidemiologic data.</p> <p>Results</p> <p>Percentage of participants carrying at least one copy of <it>HFE C282Y</it>, <it>HFE H63D</it>, <it>TF P570S</it>, and <it>ALAD K59N </it>variant alleles was 2.4%, 17.7%, 20.1%, and 6.4%, respectively. Percentage carrying at least one copy of either <it>C282Y </it>or <it>H63D </it>allele in <it>HFE </it>gene was 19.6%. Geometric mean (geometric standard deviation) manganese concentrations were 17.0 (1.5) μg/l. Women with any <it>HFE </it>variant allele had 12% lower blood manganese concentrations than women with no variant alleles (β = -0.12 [95% CI = -0.23 to -0.01]). <it>TF </it>and <it>ALAD </it>variants were not significant predictors of blood manganese. In animal models, <it>Hfe</it>^-/-mice displayed a significant reduction in blood manganese compared with <it>Hfe</it>^+/+mice, replicating the altered manganese metabolism found in our human research.</p> <p>Conclusions</p> <p>Our study suggests that genetic variants in iron metabolism genes may contribute to variability in manganese exposure by affecting manganese absorption, distribution, or excretion. Genetic background may be critical to consider in studies that rely on environmental manganese measurements.</p

Discovery of the lensed quasar system DES J0408-5354

We report the discovery and spectroscopic confirmation of the quad-like lensed quasar system DES J0408-5354 found in the Dark Energy Survey (DES) Year 1 (Y1) data. This system was discovered during a search for DES Y1 strong lensing systems using a method that identified candidates as red galaxies with multiple blue neighbors. DES J0408-5354 consists of a central red galaxy surrounded by three bright (i<20) blue objects and a fourth red object. Subsequent spectroscopic observations using the Gemini South telescope confirmed that the three blue objects are indeed the lensed images of a quasar with redshift z = 2.375, and that the central red object is an early-type lensing galaxy with redshift z = 0.597. DES J0408-5354 is the first quad lensed quasar system to be found in DES and begins to demonstrate the potential of DES to discover and dramatically increase the sample size of these very rare objects

Imprint of DES super-structures on the Cosmic Microwave Background

Small temperature anisotropies in the Cosmic Microwave Background can be sourced by density perturbations via the late-time integrated Sachs-Wolfe effect. Large voids and superclusters are excellent environments to make a localized measurement of this tiny imprint. In some cases excess signals have been reported. We probed these claims with an independent data set, using the first year data of the Dark Energy Survey in a different footprint, and using a different super-structure finding strategy. We identified 52 large voids and 102 superclusters at redshifts $0.2 < z < 0.65$. We used the Jubilee simulation to a priori evaluate the optimal ISW measurement configuration for our compensated top-hat filtering technique, and then performed a stacking measurement of the CMB temperature field based on the DES data. For optimal configurations, we detected a cumulative cold imprint of voids with $\Delta T_{f} \approx -5.0\pm3.7~\mu K$ and a hot imprint of superclusters $\Delta T_{f} \approx 5.1\pm3.2~\mu K$ ; this is $\sim1.2\sigma$ higher than the expected $|\Delta T_{f}| \approx 0.6~\mu K$ imprint of such super-structures in $\Lambda$CDM. If we instead use an a posteriori selected filter size ($R/R_{v}=0.6$), we can find a temperature decrement as large as $\Delta T_{f} \approx -9.8\pm4.7~\mu K$ for voids, which is $\sim2\sigma$ above $\Lambda$CDM expectations and is comparable to previous measurements made using SDSS super-structure data