| 1. |
- de Jong, R. S., et al.
(författare)
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4MOST : Project overview and information for the First Call for Proposals
- 2019
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Ingår i: The Messenger. - : European Southern Observatory. - 0722-6691. ; 175, s. 3-11
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We introduce the 4-metre Multi-Object Spectroscopic Telescope (4MOST), a new high-multiplex, wide-field spectroscopic survey facility under development for the four-metre-class Visible and Infrared Survey Telescope for Astronomy (VISTA) at Paranal. Its key specifications are: a large field of view (FoV) of 4.2 square degrees and a high multiplex capability, with 1624 fibres feeding two low-resolution spectrographs (R = λ/Δλ ~ 6500), and 812 fibres transferring light to the high-resolution spectrograph (R ~ 20 000). After a description of the instrument and its expected performance, a short overview is given of its operational scheme and planned 4MOST Consortium science; these aspects are covered in more detail in other articles in this edition of The Messenger. Finally, the processes, schedules, and policies concerning the selection of ESO Community Surveys are presented, commencing with a singular opportunity to submit Letters of Intent for Public Surveys during the first five years of 4MOST operations.
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| 2. |
- Kirby, Andrew, et al.
(författare)
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Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:3, s. 299-303
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Tidskriftsartikel (refereegranskat)abstract
- Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (similar to 1.5-5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.
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| 3. |
- Stanley, Flora, 1990, et al.
(författare)
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The mean star formation rates of unobscured QSOs: searching for evidence of suppressed or enhanced star formation
- 2017
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Ingår i: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 472:2, s. 2221-2240
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Tidskriftsartikel (refereegranskat)abstract
- We investigate the mean star formation rates (SFRs) in the host galaxies of similar to 3000 optically selected quasi-stellar objects (QSOs) from the Sloan Digital Sky Survey within the Herschel-ATLAS fields, and a radio-luminous subsample covering the redshift range of z = 0.2-2.5. Using Wide-field Infrared Survey Explorer (WISE) and Herschel photometry (12-500 mu m) we construct composite spectral energy distributions (SEDs) in bins of redshift and active galactic nucleus (AGN) luminosity. We perform SED fitting to measure the mean infrared luminosity due to star formation, removing the contamination from AGN emission. We find that the mean SFRs show a weak positive trend with increasing AGN luminosity. However, we demonstrate that the observed trend could be due to an increase in black hole (BH) mass (and a consequent increase of inferred stellar mass) with increasing AGN luminosity. We compare to a sample of X-ray selected AGN and find that the two populations have consistent mean SFRs when matched in AGN luminosity and redshift. On the basis of the available virial BH masses, and the evolving BH mass to stellar mass relationship, we find that the mean SFRs of our QSO sample are consistent with those of main sequence star-forming galaxies. Similarly the radio-luminous QSOs have mean SFRs that are consistent with both the overall QSO sample and with star-forming galaxies on the main sequence. In conclusion, on average QSOs reside on the main sequence of star-forming galaxies, and the observed positive trend between the mean SFRs and AGN luminosity can be attributed to BH mass and redshift dependencies.
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| 4. |
- Bernhard, E., et al.
(författare)
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Evidence for a mass-dependent AGN Eddington ratio distribution via the flat relationship between SFR and AGN luminosity
- 2018
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Ingår i: Monthly Notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 476:1, s. 436-450
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Tidskriftsartikel (refereegranskat)abstract
- The lack of a strong correlation between AGN X-ray luminosity (L-X; a proxy for AGN power) and the star formation rate (SFR) of their host galaxies has recently been attributed to stochastic AGN variability. Studies using population synthesis models have incorporated this by assuming a broad, universal (i.e. does not depend on the host galaxy properties) probability distribution for AGN specific X-ray luminosities (i.e. the ratio of L-X to host stellar mass; a common proxy for Eddington ratio). However, recent studies have demonstrated that this universal Eddington ratio distribution fails to reproduce the observed X-ray luminosity functions beyond z similar to 1.2. Furthermore, empirical studies have recently shown that the Eddington ratio distribution may instead depend upon host galaxy properties, such as SFR and/or stellar mass. To investigate this further, we develop a population synthesis model in which the Eddington ratio distribution is different for star-forming and quiescent host galaxies. We show that, although this model is able to reproduce the observed X-ray luminosity functions out to z similar to 2, it fails to simultaneously reproduce the observed flat relationship between SFR and X-ray luminosity. We can solve this, however, by incorporating a mass dependency in the AGN Eddington ratio distribution for star-forming host galaxies. Overall, our models indicate that a relative suppression of low Eddington ratios (lambda(Edd) less than or similar to 0.1) in lower mass galaxies (M-* less than or similar to 10(10-11)M(circle dot)) is required to reproduce both the observed X-ray luminosity functions and the observed flat SFR/X-ray relationship.
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| 5. |
- Hallgren, Christoffer, et al.
(författare)
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Brief communication : On the definition of the low-level jet
- 2023
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 8:11, s. 1651-1658
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Tidskriftsartikel (refereegranskat)abstract
- Low-level jets (LLJs) are examples of non-logarithmic wind speed profiles affecting wind turbine power production, wake recovery, and structural/aerodynamic loading. However, there is no consensus regarding which definition should be applied for jet identification. In this study we argue that a shear definition is more relevant to wind energy than a falloff definition. The shear definition is demonstrated and validated through the development of a European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis (ERA5) LLJ climatology for six sites. Identification of LLJs and their morphology, frequency, and intensity is critically dependent on the (i) vertical window of data from which LLJs are extracted and (ii) the definition employed.
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| 6. |
- Hallgren, Christoffer, et al.
(författare)
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Machine learning methods to improve spatial predictions of coastal wind speed profiles and low-level jets using single-level ERA5 data
- 2024
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 9:4, s. 821-840
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Tidskriftsartikel (refereegranskat)abstract
- Observations of the wind speed at heights relevant for wind power are sparse, especially offshore, but with emerging aid from advanced statistical methods, it may be possible to derive information regarding wind profiles using surface observations. In this study, two machine learning (ML) methods are developed for predictions of (1) coastal wind speed profiles and (2) low-level jets (LLJs) at three locations of high relevance to offshore wind energy deployment: the US Northeastern Atlantic Coastal Zone, the North Sea, and the Baltic Sea. The ML models are trained on multiple years of lidar profiles and utilize single-level ERA5 variables as input. The models output spatial predictions of coastal wind speed profiles and LLJ occurrence. A suite of nine ERA5 variables are considered for use in the study due to their physics-based relevance in coastal wind speed profile genesis and the possibility to observe these variables in real-time via measurements. The wind speed at 10 ma.s.l. and the surface sensible heat flux are shown to have the highest importance for both wind speed profile and LLJ predictions. Wind speed profile predictions output by the ML models exhibit similar root mean squared error (RMSE) with respect to observations as is found for ERA5 output. At typical hub heights, the ML models show lower RMSE than ERA5 indicating approximately 5 % RMSE reduction. LLJ identification scores are evaluated using the symmetric extremal dependence index (SEDI). LLJ predictions from the ML models outperform predictions from ERA5, demonstrating markedly higher SEDIs. However, optimization utilizing the SEDI results in a higher number of false alarms when compared to ERA5.
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