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An updated classification scheme for transition O2-3.5If*/WN5-7 stars is presented, following recent revisions to the spectral classifications for O and WN stars. We propose that O2-3.5If*, O2-3.5If*/WN5-7 and WN5-7 stars may be discriminated using the morphology of Hbeta to trace increasing wind density as follows: purely in absorption for O2-3.5If* stars in addition to the usual diagnostics from Walborn et al.; P Cygni for O2-3.5If*/WN5-7 stars; purely in emission for WN stars in addition to the usual diagnostics from Smith et al. We also discuss approximate criteria to discriminate between these subtypes from near-IR spectroscopy. The physical and wind properties of such stars are qualitatively discussed together with their evolutionary significance. We suggest that the majority of O2-3.5If*/WN5-7 stars are young, very massive hydrogen-burning stars, genuinely intermediate between O2-3.5If* and WN5-7 subtypes, although a minority are apparently core helium-burning stars evolving blueward towards the classical WN sequence. Finally, we reassess classifications for stars exhibiting lower ionization spectral features plus Hbeta emission.
Mechanisms involved in the star formation process and in particular the duration of the different phases of the cloud contraction are not yet fully understood. Photometric data alone suggest that objects coexist in the young cluster NGC6530 with ages
We report the detection of 7 new Wolf-Rayet (WR) star locations in M81 using the Multi-Object Spectrograph of the OSIRIS instrument at Gran Telescopio Canarias. These detections are the result of a follow-up of an earlier study using the same instrum
We present a semi-empirical spectral classification scheme for normal B-type stars using near-infrared spectra (1.5-1.7 $mu$m) from the SDSS APOGEE2-N DR14 database. The main motivation for working with B-type stars is their importance in the evoluti
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification and regressi
Context. At least 492 central stars of Galactic planetary nebulae (CSPNs) have been assigned spectral types. Since many CSPNs are faint, these classification efforts are frequently made at low spectral resolution. However, the stellar Balmer absorpti