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Your search keyword '"Dai, Y. -S."' showing total 33 results

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33 results on '"Dai, Y. -S."'

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1. Emission-line galaxies at $z\sim1$ from near-IR HST Slitless Spectroscopy: metallicities, star formation rates and redshift confirmations from VLT/FORS2 spectroscopy

2. WFC3 Infrared Spectroscopic Parallel (WISP) Survey: Photometric and Emission Line Data Release

3. The true number density of massive galaxies in the early Universe revealed by JWST/MIRI

4. Deep HI Mapping of Stephan's Quintet and Its Neighborhood

5. A Diverse Population of z ~ 2 ULIRGs Revealed by JWST Imaging

6. The SCUBA-2 Large eXtragalactic Survey: 850um map, catalogue and the bright-end number counts of the XMM-LSS field

7. A 0.6 Mpc HI Structure Associated with Stephan's Quintet

8. The average dust attenuation curve at z~1.3 based on HST grism surveys

9. Identification of single spectral lines in large spectroscopic surveys using UMLAUT: an Unsupervised Machine Learning Algorithm based on Unbiased Topology

10. A Complete 16 micron-Selected Galaxy Sample at $z\sim1$: Mid-infrared Spectral Energy Distributions

11. Identification of single spectral lines through supervised machine learning in a large HST survey (WISP): a pilot study for Euclid and WFIRST

14. The role of quenching time in the evolution of the mass-size relation of passive galaxies from the WISP survey

15. WFC3 Infrared Spectroscopic Parallel (WISP) survey: photometric and emission-line data release.

16. Deep H i Mapping of Stephan’s Quintet and Its Neighborhood

17. The SCUBA-2 Large eXtragalactic Survey: 850μm map, catalogue and the bright-end number counts of theXMM-LSS field

18. Erratum: “Identification of Single Spectral Lines in Large Spectroscopic Surveys Using UMLAUT: an Unsupervised Machine-learning Algorithm Based on Unbiased Topology” (2021, ApJS, 257, 67)

19. The SCUBA-2 Large eXtragalactic Survey: 850μm map, catalogue and the bright-end number counts of the XMM-LSS field.

20. The average dust attenuation curve at z ∼ 1.3 based on HST grism surveys

21. Erratum: Identification of single spectral lines in large spectroscopic surveys using UMLAUT: An unsupervised machine-learning algorithm based on unbiased topology (Astrophysical Journal, Supplement Series (2021) 257 (67) DOI: 10.3847/1538-4365/ac250c)

22. Identification of Single Spectral Lines in Large Spectroscopic Surveys Using UMLAUT: an Unsupervised Machine-learning Algorithm Based on Unbiased Topology

23. average dust attenuation curve at z ∼ 1.3 based on HST grism surveys.

24. Predicting the Redshift 2 H-Alpha Luminosity Function Using [OIII] Emission Line Galaxies

25. A Complete 16 μm Selected Galaxy Sample at z ∼ 1: Mid-infrared Spectral Energy Distributions

26. A 0.6 Mpc H istructure associated with Stephan’s Quintet

27. Identification of Single Spectral Lines through Supervised Machine Learning in a Large HST Survey (WISP): A Pilot Study for Euclid and WFIRST

29. THE ROLE OF QUENCHING TIME IN THE EVOLUTION OF THE MASS–SIZE RELATION OF PASSIVE GALAXIES FROM THE WISP SURVEY

30. PREDICTING THE REDSHIFT 2 HαLUMINOSITY FUNCTION USING [O iii] EMISSION LINE GALAXIES

32. A Complete 16 micron-Selected Galaxy Sample at $z\sim1$: Mid-infrared Spectral Energy Distributions

33. [Analysis of hemoglobin variants in Tianjin City and neighboring areas].

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