Catching a star before explosion: the luminous blue variable progenitor of SN 2015bh

In this paper we analyse the pre-explosion spectrum of SN2015bh by performing radiative transfer simulations using the CMFGEN code. This object has attracted significant attention due to its remarkable similarity to SN2009ip in both its pre- and post-explosion behaviour. They seem to belong to a class of events for which the fate as a genuine core-collapse supernova or a non-terminal explosion is still under debate. Our CMFGEN models suggest that the progenitor of SN2015bh had an effective temperature between 8700 and 10000 K, luminosity in the range ~ 1.8-4.74e6 Lsun, contained at least 25% H in mass at the surface, and half-solar Fe abundances. The results also show that the progenitor of SN 2015bh generated an extended wind with a mass-loss rate of ~ 6e-4 to 1.5e-3 Msun/yr and a velocity of 1000 km/s. We determined that the wind extended to at least 2.57e14 cm and lasted for at least 30 days prior to the observations, releasing 5e-5 Msun into the circumstellar medium. In analogy to 2009ip, we propose that this is the material that the explosive ejecta could interact at late epochs, perhaps producing observable signatures that can be probed with future observations. We conclude that the progenitor of SN 2015bh was most likely a warm luminous blue variable of at least 35 Msun before the explosion. Considering the high wind velocity, we cannot exclude the possibility that the progenitor was a Wolf-Rayet star that inflated just before the 2013 eruption, similar to HD5980 during its 1994 episode. If the star survived, late-time spectroscopy may reveal either a similar LBV or a Wolf-Rayet star, depending on the mass of the H envelope before the explosion. If the star exploded as a genuine SN, 2015bh would be a remarkable case of a successful explosion after black-hole formation in a star with a possible minimum mass 35 Msun at the pre-SN stage.Comment: 13 pages, 10 figures, accepted for publication in A&

The possible disappearance of a massive star in the low metallicity galaxy PHL 293B

We investigate a suspected very massive star in one of the most metal-poor dwarf galaxies, PHL~293B. Excitingly, we find the sudden disappearance of the stellar signatures from our 2019 spectra, in particular the broad H lines with P~Cygni profiles that have been associated with a massive luminous blue variable (LBV) star. Such features are absent from our spectra obtained in 2019 with the ESPRESSO and X-shooter instruments of the ESO's VLT. We compute radiative transfer models using CMFGEN that fit the observed spectrum of the LBV and are consistent with ground-based and archival Hubble Space Telescope photometry. Our models show that during 2001--2011 the LBV had a luminosity $L_* = 2.5-3.5 \times 10^6 ~L_{\odot}$, a mass-loss rate $\dot{M} = 0.005-0.020 ~M_{\odot}$~yr$^{-1}$, a wind velocity of 1000~km~s$^{-1}$, and effective and stellar temperatures of $T_\mathrm{eff} = 6000-6800$~K and $T_\mathrm{*}=9500-15000$~K. These stellar properties indicate an eruptive state. We consider two main hypotheses for the absence of the broad emission components from the spectra obtained since 2011. One possibility is that we are seeing the end of an LBV eruption of a surviving star, with a mild drop in luminosity, a shift to hotter effective temperatures, and some dust obscuration. Alternatively, the LBV could have collapsed to a massive black hole without the production of a bright supernova.Comment: 8, pages, 7 figures, MNRAS accepted ; see also the ESO press release at: https://www.eso.org/public/news/eso2010

Mental health at different stages of cancer survival: a natural language processing study of Reddit posts

IntroductionThe purpose of this study was to use text-based social media content analysis from cancer-specific subreddits to evaluate depression and anxiety-loaded content. Natural language processing, automatic, and lexicon-based methods were employed to perform sentiment analysis and identify depression and anxiety-loaded content.MethodsData was collected from 187 Reddit users who had received a cancer diagnosis, were currently undergoing treatment, or had completed treatment. Participants were split according to survivorship status into short-term, transition, and long-term cancer survivors. A total of 72524 posts were analyzed across the three cancer survivor groups.ResultsThe results showed that short-term cancer survivors had significantly more depression-loaded posts and more anxiety-loaded words than long-term survivors, with no significant differences relative to the transition period. The topic analysis showed that long-term survivors, more than other stages of survivorship, have resources to share their experiences with suicidal ideation and mental health issues while providing support to their survivor community.DiscussionThe results indicate that Reddit texts seem to be an indicator of when the stressor is active and mental health issues are triggered. This sets the stage for Reddit to become a platform for screening and first-hand intervention delivery. Special attention should be dedicated to short-term survivors

Connecting evolved massive stars to interacting supernovae

Massive stars and supernovae are not only remarkable objects on their own but they are closely related to many other topics in Astrophysics, such as nucleosynthesis, star formation, and gravitational waves. However the properties of massive stars at late stages and their links to supernovae are not well understood.In our work we aim to improve the knowledge on these topics, by studying the spectra of evolved massive stars and the early spectra of supernovae that interact with the winds/atmospheres of massive stars, as they provide valuable information about supernova progenitors, such as mass-loss rates, wind velocities, and surface abundances.We use the radiative transfer code for expanding atmospheres in non-local thermodynamic equilibrium, CMFGEN. The code makes no assumptions for the source of radiative energy at the inner boundary and hence can be employed in modelling both stars with dense atmospheres/winds and eject a from explosive events interacting with the circumstellar material. Supernova progenitors are usually constrained from post-explosion data, but in exceptional cases they have been directly observed, mainly photometrically, and on even rarer occasions spectroscopically. Such is the case of SN 2015bh,a transient whose post-explosion fate is unknown, with a spectrum taken 1.5 yrs pre-explosion. In the first part of this thesis we aim to determine the progenitor properties of SN 2015bh using CMFGEN. Modelling the pre-explosion spectrum of SN 2015bh shows that the star had an effective temperature between8 700 and 10 000 K, luminosity of 1.8?4.74?106L, mass-loss rate of 0.6?1.5?10?3Myr?1, a wind terminal velocity of 1000 km s?1, and contained at least 25% H in mass at the surface, and half-solar Fe abundances. Therefore we conclude that the progenitor of SN 2015bh was a warm luminous blue variable star with an extended wind. Given the high wind velocity there is also the possibility the star was an inflated Wolf-Rayet star. If SN 2015bh was an impostor, we expect late-time spectroscopy to reveal either a similar luminous blue variable star or a Wolf-Rayet star, depending on how much H it retained in its envelope. If it was a genuine supernova, its minimum mass of 35M at the pre-supernova stage makes it a remarkable case of a successful explosion with black-hole formation.In the second part of this thesis, we investigate the post-explosion proper-ties of massive stars. We built an extensive library of spectra simulating the interaction of supernovae with their progenitor?s circumstellar medium at early times. We considered a range of progenitor mass-loss rates ( ?M=5?10?4to10?2Myr?1), abundances (solar-like, CNO-processed, and He-rich), and explosion luminosities (L=1.9?108to 2.5?1010L). The diversity of massive star properties at the pre-supernova stage causes a variety of early-time interacting supernovae. We recognise three main classes of early-time spectra based on the ionisation stages of the species present, i.e. high (e.g. HeIIand OVI), medium(e.g. CIIIand NIII), and low-ionisation (e.g. HeIand FeII/III). Additionally, our modelled spectra respond strongly to changes in surface abundances, allowing well constrained measurements of H, He, and CNO. These can be used to obtain the progenitor type and mass, if it followed single star evolution. We also show that if ?M.5?10?4(??/150km s?1)Myr?1no interaction signatures will be observable in the spectra.Using our library of models described above, we then constrain the proper-ties of a sample of 17 observed early-time interacting supernovae. We show that these events cover a wide range of explosion and progenitor properties. They exhibit supernova luminosities from 108to 1012L, and temperatures from 10to 60 kK. The progenitor mass-loss rates are all higher than a few 10?4Myr?1,even up to 1Myr?1, with wind velocities spanning 100 to 800 km s?1. These values suggest that many progenitors of supernovae interacting with circumstellar material have significantly increased mass loss before explosion compared to what massive stars show during the rest of their lifetimes. While the surface abundances range from solar-like to H-depleted, we find that the majority of the events in our sample have CNO-processed surface abundances. In the single star scenario, this result points to a preference towards high-mass red supergiants as progenitors of interacting supernovae.Supernovae showing interaction with dense circumstellar material are extremely diverse and our grid of models can be extended to include all types of events, from the dimmest to the brightest supernovae observed to date

Additional file 1: of An evidence-based gamified mHealth intervention for overweight young adults with maladaptive eating habits: study protocol for a randomized controlled trial

SPIRIT 2013 Checklist: recommended items to address in a clinical trial protocol and related documents. (DOC 123 kb

Mental health at different stages of cancer survival: A natural language processing study of Reddit posts

The purpose of this study was to use text-based social media content analysis from cancer-specific subreddits to evaluate depression and anxiety-loaded content. Natural language processing, automatic, and lexicon-based methods were employed to perform sentiment analysis and to identify depression and anxiety-loaded content. Data were collected from 187 Reddit users who had received a cancer diagnosis, were currently undergoing treatment or had completed treatment. Participants were split according to survivorship status into short-term, transition, and long-term cancer survivors. A number of 72524 posts were analysed across the three cancer survivor groups. The results showed that short-term cancer survivors had significantly more depression-loaded posts and more anxiety-loaded words than long-term survivors, with no significant differences relative to the transition period. The topic analysis showed that long-term survivors, more than other stages of survivorship, have resources to share their experiences with suicidal ideation and mental health issues while providing support to their survivor community. The results indicate that Reddit texts seem to be an indicator of when the stressor is active and mental health issues are triggered. This sets the stage for Reddit to become a platform for screening and first-hand intervention delivery. Special attention should be dedicated to short-term survivors