511 research outputs found

    Antecedents and outcomes of consumer environmentally friendly attitudes and behaviour

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    With the intensification of problems relating to the environment, a growing number of consumers are becoming more ecologically conscious in their preferences and purchases of goods. This paper presents the results of a study conducted among 500 Cypriot consumers, focusing on the factors that shape consumer environmental attitudes and behaviour, as well as on the resulting outcomes. The findings confirmed that both the inward and outward environmental attitudes of a consumer are positively influenced by his/her degree of collectivism, long-term orientation, political involvement, deontology, and law obedience, but have no connection with liberalism. The adoption of an inward environmental attitude was also found to be conducive to green purchasing behaviour that ultimately leads to high product satisfaction. On the other hand, an outward environmental attitude facilitates the adoption of a general environmental behaviour, which is responsible for greater satisfaction with life. The findings of the study have important implications for shaping effective company offerings to consumers in target markets, as well as formulating appropriate policies at the governmental level to enhance environmental sensitivity among citizens

    Quasar accretion disk sizes from continuum reverberation mapping in the DES standard-star fields

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    Measurements of the physical properties of accretion disks in active galactic nuclei are important for better understanding the growth and evolution of supermassive black holes. We present the accretion disk sizes of 22 quasars from continuum reverberation mapping with data from the Dark Energy Survey (DES) standard star fields and the supernova C fields. We construct continuum lightcurves with the \textit{griz} photometry that span five seasons of DES observations. These data sample the time variability of the quasars with a cadence as short as one day, which corresponds to a rest frame cadence that is a factor of a few higher than most previous work. We derive time lags between bands with both JAVELIN and the interpolated cross-correlation function method, and fit for accretion disk sizes using the JAVELIN Thin Disk model. These new measurements include disks around black holes with masses as small as 107\sim10^7 MM_{\odot}, which have equivalent sizes at 2500\AA \, as small as 0.1\sim 0.1 light days in the rest frame. We find that most objects have accretion disk sizes consistent with the prediction of the standard thin disk model when we take disk variability into account. We have also simulated the expected yield of accretion disk measurements under various observational scenarios for the Large Synoptic Survey Telescope Deep Drilling Fields. We find that the number of disk measurements would increase significantly if the default cadence is changed from three days to two days or one day.Comment: 33 pages, 24 figure

    Astrometric calibration and performance of the Dark Energy Camera

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    We characterize the ability of the Dark Energy Camera (DECam) to perform relative astrometry across its 500~Mpix, 3 deg^2 science field of view, and across 4 years of operation. This is done using internal comparisons of ~4x10^7 measurements of high-S/N stellar images obtained in repeat visits to fields of moderate stellar density, with the telescope dithered to move the sources around the array. An empirical astrometric model includes terms for: optical distortions; stray electric fields in the CCD detectors; chromatic terms in the instrumental and atmospheric optics; shifts in CCD relative positions of up to ~10 um when the DECam temperature cycles; and low-order distortions to each exposure from changes in atmospheric refraction and telescope alignment. Errors in this astrometric model are dominated by stochastic variations with typical amplitudes of 10-30 mas (in a 30 s exposure) and 5-10 arcmin coherence length, plausibly attributed to Kolmogorov-spectrum atmospheric turbulence. The size of these atmospheric distortions is not closely related to the seeing. Given an astrometric reference catalog at density ~0.7 arcmin^{-2}, e.g. from Gaia, the typical atmospheric distortions can be interpolated to 7 mas RMS accuracy (for 30 s exposures) with 1 arcmin coherence length for residual errors. Remaining detectable error contributors are 2-4 mas RMS from unmodelled stray electric fields in the devices, and another 2-4 mas RMS from focal plane shifts between camera thermal cycles. Thus the astrometric solution for a single DECam exposure is accurate to 3-6 mas (0.02 pixels, or 300 nm) on the focal plane, plus the stochastic atmospheric distortion.Comment: Submitted to PAS

    Forward Global Photometric Calibration of the Dark Energy Survey

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    Many scientific goals for the Dark Energy Survey (DES) require calibration of optical/NIR broadband b=grizYb = grizY photometry that is stable in time and uniform over the celestial sky to one percent or better. It is also necessary to limit to similar accuracy systematic uncertainty in the calibrated broadband magnitudes due to uncertainty in the spectrum of the source. Here we present a "Forward Global Calibration Method (FGCM)" for photometric calibration of the DES, and we present results of its application to the first three years of the survey (Y3A1). The FGCM combines data taken with auxiliary instrumentation at the observatory with data from the broad-band survey imaging itself and models of the instrument and atmosphere to estimate the spatial- and time-dependence of the passbands of individual DES survey exposures. "Standard" passbands are chosen that are typical of the passbands encountered during the survey. The passband of any individual observation is combined with an estimate of the source spectral shape to yield a magnitude mbstdm_b^{\mathrm{std}} in the standard system. This "chromatic correction" to the standard system is necessary to achieve sub-percent calibrations. The FGCM achieves reproducible and stable photometric calibration of standard magnitudes mbstdm_b^{\mathrm{std}} of stellar sources over the multi-year Y3A1 data sample with residual random calibration errors of σ=56mmag\sigma=5-6\,\mathrm{mmag} per exposure. The accuracy of the calibration is uniform across the 5000deg25000\,\mathrm{deg}^2 DES footprint to within σ=7mmag\sigma=7\,\mathrm{mmag}. The systematic uncertainties of magnitudes in the standard system due to the spectra of sources are less than 5mmag5\,\mathrm{mmag} for main sequence stars with 0.5<gi<3.00.5<g-i<3.0.Comment: 25 pages, submitted to A

    Transfer learning for galaxy morphology from one survey to another

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    © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of \sim5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy (\sim 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies (\sim500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio
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