7,897 research outputs found

    Canadian ERTS program progress report

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    Progress of the Canadian ERTS program is provided along with statistics on the production and role of ERTS images both from the CCRS in Ottawa and from the Prince Albert Saskatchewan satellite station. The types of products, difficulties of production and some of the main applications in Canada are discussed

    Near-infrared Detection of WD 0806-661 B with the Hubble Space Telescope

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    WD 0806-661 B is one of the coldest known brown dwarfs (T=300-345 K) based on previous mid-infrared photometry from the Spitzer Space Telescope. In addition, it is a benchmark for testing theoretical models of brown dwarfs because its age and distance are well-constrained via its primary star (2+/-0.5 Gyr, 19.2+/-0.6 pc). We present the first near-infrared detection of this object, which has been achieved through F110W imaging (~Y+J) with the Wide Field Camera 3 on board the Hubble Space Telescope. We measure a Vega magnitude of m110=25.70+/-0.08, which implies J~25.0. When combined with the Spitzer photometry, our estimate of J helps to better define the empirical sequence of the coldest brown dwarfs in M4.5 versus J-[4.5]. The positions of WD 0806-661 B and other Y dwarfs in that diagram are best matched by the cloudy models of Burrows et al. and the cloudless models of Saumon et al., both of which employ chemical equilibrium. The calculations by Morley et al. for 50% cloud coverage differ only modestly from the data. Spectroscopy would enable a more stringent test of the models, but based on our F110W measurement, such observations are currently possible only with Hubble, and would require at least ~10 orbits to reach a signal-to-noise ratio of ~5

    Gene loss and lineage specific restriction-modification systems associated with niche differentiation in the Campylobacter jejuni Sequence Type 403 clonal complex

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    Campylobacter jejuni is a highly diverse species of bacteria commonly associated with infectious intestinal disease of humans and zoonotic carriage in poultry, cattle, pigs, and other animals. The species contains a large number of distinct clonal complexes that vary from host generalist lineages commonly found in poultry, livestock, and human disease cases to host-adapted specialized lineages primarily associated with livestock or poultry. Here, we present novel data on the ST403 clonal complex of C. jejuni, a lineage that has not been reported in avian hosts. Our data show that the lineage exhibits a distinctive pattern of intralineage recombination that is accompanied by the presence of lineage-specific restriction-modification systems. Furthermore, we show that the ST403 complex has undergone gene decay at a number of loci. Our data provide a putative link between the lack of association with avian hosts of C. jejuni ST403 and both gene gain and gene loss through nonsense mutations in coding sequences of genes, resulting in pseudogene formation

    Using Multiple Signatures to Improve Accuracy of Substorm Identification

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    We have developed a new procedure for combining lists of substorm onset times from multiple sources. We apply this procedure to observational data and to magnetohydrodynamic (MHD) model output from 1–31 January 2005. We show that this procedure is capable of rejecting false positive identifications and filling data gaps that appear in individual lists. The resulting combined onset lists produce a waiting time distribution that is comparable to previously published results, and superposed epoch analyses of the solar wind driving conditions and magnetospheric response during the resulting onset times are also comparable to previous results. Comparison of the substorm onset list from the MHD model to that obtained from observational data reveals that the MHD model reproduces many of the characteristic features of the observed substorms, in terms of solar wind driving, magnetospheric response, and waiting time distribution. Heidke skill scores show that the MHD model has statistically significant skill in predicting substorm onset times.Plain Language SummaryMagnetospheric substorms are a process of explosive energy release from the plasma environment on the nightside of the Earth. We have developed a procedure to identify substorms that uses multiple forms of observational data in combination. Our procedure produces a list of onset times for substorms, where each onset time has been independently confirmed by two or more observational data sets. We also apply our procedure to output from a physical model of the plasma environment surrounding the Earth and show that this model can predict a significant fraction of the substorm onset times.Key PointsCombining substorm onsets from multiple types of observations can produce a more accurate list of onset times than any single listThe resulting onset list exhibits expected behavior for substorms in terms of magnetospheric driving and responseSWMF has a weak but consistent and statistically significant skill in predicting substormsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/1/jgra55605_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/2/jgra55605-sup-0002-2019JA027559-Text_SI-S01.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154913/3/jgra55605.pd

    The Brown-dwarf Atmosphere Monitoring (BAM) Project II: Multi-epoch monitoring of extremely cool brown dwarfs

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    With the discovery of Y dwarfs by the WISE mission, the population of field brown dwarfs now extends to objects with temperatures comparable to those of Solar System planets. To investigate the atmospheres of these newly identified brown dwarfs, we have conducted a pilot study monitoring an initial sample of three late T-dwarfs (T6.5, T8 and T8.5) and one Y-dwarf (Y0) for infrared photometric variability at multiple epochs. With J-band imaging, each target was observed for a period of 1.0h to 4.5h per epoch, which covers a significant fraction of the expected rotational period. These measurements represent the first photometric monitoring for these targets. For three of the four targets (2M1047, Ross 458C and WISE0458), multi-epoch monitoring was performed, with the time span between epochs ranging from a few hours to ~2 years. During the first epoch, the T8.5 target WISE0458 exhibited variations with a remarkable min-to-max amplitude of 13%, while the second epoch light curve taken ~2 years later did not note any variability to a 3% upper limit. With an effective temperature of ~600 K, WISE0458 is the coldest variable brown dwarf published to-date, and combined with its high and variable amplitude makes it a fascinating target for detailed follow-up. The three remaining targets showed no significant variations, with a photometric precision between 0.8% and 20.0%, depending on the target brightness. Combining the new results with previous multi-epoch observations of brown dwarfs with spectral types of T5 or later, the currently identified variables have locations on the colour-colour diagram better matched by theoretical models incorporating cloud opacities rather than cloud-free atmospheres. This preliminary result requires further study to determine if there is a definitive link between variability among late-T dwarfs and their location on the colour-colour diagram.Comment: 9 pages, 6 figures, 3 tables, accepted for publication in MNRA

    An L Band Spectrum of the Coldest Brown Dwarf

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    The coldest brown dwarf, WISE 0855, is the closest known planetary-mass, free-floating object and has a temperature nearly as cold as the solar system gas giants. Like Jupiter, it is predicted to have an atmosphere rich in methane, water, and ammonia, with clouds of volatile ices. WISE 0855 is faint at near-infrared wavelengths and emits almost all its energy in the mid-infrared. Skemer et al. 2016 presented a spectrum of WISE 0855 from 4.5-5.1 micron (M band), revealing water vapor features. Here, we present a spectrum of WISE 0855 in L band, from 3.4-4.14 micron. We present a set of atmosphere models that include a range of compositions (metallicities and C/O ratios) and water ice clouds. Methane absorption is clearly present in the spectrum. The mid-infrared color can be better matched with a methane abundance that is depleted relative to solar abundance. We find that there is evidence for water ice clouds in the M band spectrum, and we find a lack of phosphine spectral features in both the L and M band spectra. We suggest that a deep continuum opacity source may be obscuring the near-infrared flux, possibly a deep phosphorous-bearing cloud, ammonium dihyrogen phosphate. Observations of WISE 0855 provide critical constraints for cold planetary atmospheres, bridging the temperature range between the long-studied solar system planets and accessible exoplanets. JWST will soon revolutionize our understanding of cold brown dwarfs with high-precision spectroscopy across the infrared, allowing us to study their compositions and cloud properties, and to infer their atmospheric dynamics and formation processes.Comment: 19 pages, 21 figures. Accepted for publication in Ap

    Cannabis and depression: A twin model approach to co-morbidity

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    Cannabis use disorder (CUD) co-occurs with major depressive disorder (MDD) more frequently than would be expected by chance. However, studies to date have not produced a clear understanding of the mechanisms underlying this co-morbidity. Genetically informative studies can add valuable insight to this problem, as they allow the evaluation of competing models of co-morbidity. This study uses data from the Australian Twin Registry to compare 13 co-morbidity twin models initially proposed by Neale and Kendler (Am J Hum Genet 57:935–953, 1995). The analysis sample comprised 2410 male and female monozygotic and dizygotic twins (average age 32) who were assessed on CUD and MDD using the SSAGA-OZ interview. Data were analyzed in OpenMx. Of the 13 different co-morbidity models, two fit equally well: CUD causes MDD and Random Multiformity of CUD. Both fit substantially better than the Correlated Liabilities model. Although the current study cannot differentiate between them statistically, these models, in combination, suggest that CUD risk factors may causally influence the risk to develop MDD, but only when risk for CUD is high
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