dataesr/scientific-paragraphs-categorization huggingface dataset:
Randomisation and allocation concealment A member of the research staff not involved in conducting the TASK trial generates a permuted block randomisation sequence with random block sizes using STATA14  [26]. The sequence is uploaded to the in-built randomisation module within REDCap, which is inaccessible to the TASK researcher enrolling participants. Once baseline data collection is complete, the TASK researcher randomises the participant and emails him/her the allocated treatment website address and login details. Participants receive telephone instructions on commencing the allocated treatment. Participants allocated to TASK-CBT also receive an appointment for their first telephone session.
Feasibility outcomes The current trial assesses the feasibility of the TASK-CBT intervention and the technology-enabled trial procedures. Feasibility data collected: recruitment (number per month), percentage of completed consent (online or by post), time taken to complete remote eligibility confirmation via electronic health records (date of randomisation-date of 'Sign Up and Consent Form' received), percentage drop out after fewer than three telephone TASK-CBT sessions and self-completion of electronic follow-up surveys at T1 and T2 (percentage of completed surveys). We define a lack of feasibility of TASK-CBT and the current trial design as (1) recruitment number of < 2 per month, (2) > 50% of TASK-CBT patients dropping out after fewer than three telephone sessions, (3) > 10% non-completion of follow up surveys at T2 and (4) participants reporting harm from the intervention.
Assessing intervention fidelity and quality monitoring of therapist The therapist for this feasibility trial is a stroke physician (HYC) who has received training on delivering CBT from and has ongoing supervision by a consultant neuropsychiatrist (AJC) at weekly meetings during the TASK trial. For intervention fidelity, we will assess (i) percentage agreement between the therapist's record and transcripts of audio-recording of telephone sessions, assessed by a clinician independent of the study; (ii) automated data capture of online task completion; (iii) summary web usage data from Google Analytics.
Data management All study data are collected and managed using REDCap electronic data capture tools hosted at University of Edinburgh. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies  [20]. Identifiable data are only accessible by the TASK trial investigators and managing team of the REDCap database. Anonymised data from all smartwatch devices will be downloaded as binary files and sent to our collaborating data scientist at the Centre for Medical Informatics, Usher Institute, University of Edinburgh for analysis.
Statistical analyses and power calculation As this is a feasibility study, we did not perform power calculation. Feasibility outcomes will be summarised descriptively. All electronic items on the follow-up surveys must be scored to permit submission, preventing any missing values. Only the trial investigators have access to the final trial dataset. Actigraphy data from the smartwatch device will be sent anonymously for time-series analysis at the Centre for Medical Informatics, Usher Institute, University of Edinburgh.
Choice of primary outcome In TASK II, we will determine an appropriate primary outcome measure to be used in the definitive trial. We will consider a range of candidate outcome measures of anxiety, functional independence, quality of life and participation. We will select the primary outcome based on the measure's sensitivity to change/difference between groups, its practicality for use in large-scale RCT (to minimise attrition) and its clinical meaningfulness. Our observational data suggested that stroke/TIA patients with anxiety disorder reported a statistically significantly higher level of functional dependence on the modified Rankin Scale, a poorer quality of life on EurolQol-5D-5L and worse participation on a the Work and Social Adjustment Scale, compared to those without anxiety  [3].
Such work has been attempted with Hubble Space Telescope (HST) photometry, e. g. in the ANGST survey  (Dalcanton et al. 2009) , for the galaxy NGC 300 studied in this paper see specifically  Gogarten et al. (2010). However limitations of photometry, e. g. the age-metallicity degeneracy, sensitivity to extinction, or the lacking ability to distinguish objects such as Wolf-Rayet (WR) stars from normal O stars, carbon stars from M stars, etc. would rather call for spatially resolved spectroscopy. Except for conventional slit spectroscopy of individual bright giants or supergiants in local volume galaxies, e. g. Bresolin et al. (2001) ,  Smartt et al. (2001)  in the optical, or  Urbaneja et al. (2005) ,  Gazak et al. (2015)  in the NIR, there exists to date no comprehensive spectroscopic dataset for stars in heavily crowded fields of nearby galaxies beyond the Magellanic Clouds.
2014). These first experiments were taken to another level with commissioning data from MUSE, where the globular cluster NGC6397 was observed as a 5 × 5 mosaic of ≈ 60s snapshot exposures, resulting in a spectacular dataset of spectra for more than 12000 stars. By fitting to a library of PHOENIX spectra  (Husser et al. 2013 ) and with photometry, good results for the atmospheric parameters T eff and log g, as well as metallicities were obtained, such that a spectroscopic Hertzsprung-Russell diagram (HRD) could be presented for a globular cluster for the first time  (Husser et al. 2016). In a kinematic analysis of the same dataset,  Kamann et al. (2016)  study again the radial velocities and velocity dispersion of individual stars, however with a sample size of more than 12000 objects. Despite the low spectral resolution of MUSE, it is shown that for spectra with sufficient signal-to-noise ratio (S/N), the radial velocities are measured to an accuracy of 1 km s -1.
Fitting stellar spectra Two major goals of the project were to demonstrate, as a proof of principle for crowded fields in NGC 300, that PSF-fitting IFS is capable of extracting spectra of individual stars with sufficient quality to derive trustworthy spectral type classifications, and to measure radial velocities, even with moderate to low signalto-noise ratios (S/N). To this end, we have fitted the extracted spectra both to an empirical library of stellar spectra, in what follows MIUSCAT, and to a grid of models computed with the Phoenix code  (Husser et al. 2013) , henceforth GLIB (Göttingen Library). MIUSCAT is an (unpublished) extension of the MILES library  (Sánchez-Blázquez et al. 2006; Cenarro et al. 2007; Falcón-Barroso et al. 2011 ) that was kindly provided to us by Alexandre Vazdekis.
Especially for our application, where we are confronted with spectra of low S/N, the output of several (up to 10) library spectra with their respective weights supports a proper judgement of the quality of the fit and the identification of potential problems. As a practical disadvantage, the ULySS output requires a significant level of human interaction, i. e. a decision for each individual input spectrum in how far the linear combination of library spectra with different weights allows to make a good guess for the spectral type of the observed star. However, any less than plausible spectra can be ruled out immediately, e. g. foreground stars, or main sequence stars, the latter of which, at a distance of 1. 9 Mpc, would be far below the detection limit of MUSE. In order to assist with this criterion, we searched the Simbad database for photometry of the MIUSCAT library stars and shifted their magnitudes to the most recent, cepheid-based NGC 300 distance modulus of (m-M) 0 =26.
From successful ULySS fits to the MIUSCAT library we obtained a total of 345 and 392 results for the HST and FIND input catalogues, respectively. For the same number of spectra, the fitting procedure was repeated using GLIB and the code from  Husser et al. (2013). All of the spectra and corresponding fits were inspected visually, along with VRI images of the stars extracted from the datacube, as well as from HST, where available, for comparison and assessment of blending. Following the determination of spectral type, radial velocity v rad , and quality parameters as described in §3. 2, we created the final catalogues for the two sets of spectra. An excerpt of the catalogue for field (i) with HST input is presented in Table  6. The complete catalogue for field (i) will be made publicly available through CDS.
Artificial star tests as commonly used for CCD photometry were not found to be useful because PampelMuse works already with a catalogue of stars obtained at high angular resolution (HST) with the benefit of accurately pin-pointing stellar centroids, regardless of magnitude. We therefore used the information from that catalogue as a reference. To this end, we convolved our flux-calibrated MUSE spectra with the ACS F606W filter curve as provided at the Spanish Virtual Observatory website 4. In ors (F606W-F814W)≥0. 4, blue symbols hot stars with (F606W-F814W)<0. 4. Both datasets show a very similar distribution, with a tight correlation at bright magnitudes, and a rapid degradation towards large errors at faint magnitudes. Residuals against the 1:1 relation in magnitude bins of 0. 2 mag are shown in the lower right part of the graph (with an offset of 20.
These spectra were modulated with random noise resulting in S/N = 30, 20, 10, 7. 5, 5, 4, 3, 2, 1, with 10 random realizations per S/N value, and a sample of in total 630 simulated spectra. The ULySS code was applied to each spectrum to recover the input spectral type from the noisy simulation. Fig. 9  shows the outcome of the exercise as the recovered T eff for each simulation versus the corresponding S/N value as provided as an output parameter by the ULySS code, color-coded for the different spectral types. One can immediately see that at S/N ≥7. 5 all of the spectra are perfectly well recovered (with the exception of two G3III outliers at S/N=7. 5). Below that noise level, the reliability of the fit is strongly depending on the spectral type. For example, K0 and K4 subgiants show still agreement down to S/N=3, however with some outliers involving offsets of a few 100 K in T eff.
In this particular case, the situation is somewhat more complicated as it turns out that in the HST image star A is resolved into two distinct stars. From the ULySS fit, we conclude that there is a weak blend from an M6III star, which explains the less than perfect fit of the spectrum. Nevertheless, the facts remain that for the main sequence K spectrum component, such a star is not visible at the distance of NGC 300, and that the well-constrained radial A&A proofs: manuscript no. NGC300_MUSE_2column_arXiv velocity is incompatible with stars within this galaxy. Using the new Besancon Galaxy model  (Czekaj et al. 2014)  we have estimated the number of stars that one would expect in the direction towards NGC 300 down to V = 20 to 0. 5 stars per 1×1 arcmin 2. Extrapolation to V=24. 25 predicts approximately 4500 star per square degree, i.
As we have shown with a proof-of-principle in field (i), such a two-step procedure is no longer necessary with IFS. MUSE allows, for the first time over a reasonable FoV, to combine the different survey strategies into one: imaging and spectroscopy combined in a single datacube under identical observing conditions. Concerning the imaging capabilities, it is worthwhile noting that the discovery of evolved massive stars with heavy mass loss and fast stellar winds such as A&A proofs: manuscript no. NGC300_MUSE_2column_arXiv LBVs or WR stars is much facilitated by narrowband images that are readily extracted from a datacube at the wavelengths of interest, e. g. Hα, or He ii λ4686, see for comparison  Massey et al. (2015). Although this capability was already demonstrated with PMAS by  Relaño et al.
(2016)  include 14143 stellar spectra taken with DEIMOS at the Keck-II 10m telescope. The spectra were obtained from 151 individual DEIMOS masks for 60 separate fields, with a typical exposure time of 3600 s per mask. The observations were targeting the environment of M31, i. e. dwarf spheroidals, dwarf ellipticals, the smooth virialized halo, halo substructure, and M32. From this entire dataset, 41 unambiguous carbon stars were identified. It is interesting to note that spectroscopy is apparently essential for obtaining a reliable identification. We take as an example the dwarf elliptical galaxy NGC 147: based on NIR photometry,  Davidge (2005)  found 65 carbon stars,  Sohn et al. (2006)  reported 91 carbon stars using the same technique, while  Hamren et al. (2016)  confirmed merely 12 stars on the basis of photometry and spectroscopy in the visual.
A higher quality spectrum is presented for the A1 supergiant ID151 of field (i) in Fig. 12  that exhibits a S/N of 22 -despite the fact that this star is about a magnitude fainter than B11, illustrating the importance of high image quality for this kind of observation. In contrast to the blue supergiants with rel-atively few identifiable lines, our example of the late K to early M supergiant ID301 in field (i) with m F606W =21. 56 and S/N=14 shows a multitude of absorption lines, including TiO bands, that are reproduced by the MIUSCAT fit (Fig. 13 ). It is clear that with longer exposure times, the quality of such spectra will be improved. We stress again, however, that excellent seeing is a prerequisite. Insofar the installation of the adaptive optics (AO) facility at VLT-UT4 and the GALACSI module in front of MUSE  (Stuik et al.
(  2012 )). The latter authors estimate the distance to R Aqr as 250 pc. Schmid et al. (2017)  used observations with HST and SPHERE ZIMPOL at the VLT to measure an Hα flux of 4. 6 × 10 -11 erg/cm 2 /s. Pushing this object to the distance of NGC 300, this would translate to a flux of roughly 10 -18 erg/cm 2 /s, i. e. just detectable with MUSE. We therefore flagged red giant emission line stars as symbiotic star candidates. A special case is the Wolf-Rayet star (WR) that was readily detected from the He ii narrowband image created for field (c). Inspection of the PampelMUSE-extracted spectrum confirmed that this object is indeed a hot star with the characteristic blue WR bump (see Fig. 17 ). A&A proofs: manuscript no. NGC300_MUSE_2column_arXiv  For example, the H ii region labelled De100 in Fig.
Supernova remnants Results: We inspected the [O iii] maps for extended emission to find SNR candidates and subsequently used the spectra to select only those objects that show evidence for shock excitation on the basis of the canonical line ratio criterion [S ii]/Hα > 0. 4  (Mathewson & Clarke 1973). We found prominent, high surface brightness examples, e. g. Fig. 21 , as well as low surface brightness objects that barely stand out from the noise. In our dataset, we have reached limiting surface brightness levels of 2×10 -17 erg cm -2 s -1 arcsec -2 in [O III]. In total, we detected 38 SNR and measured their fluxes, sizes, and radial velocities. Nebulae that have a similar appearance as SNR and spectra pointing to shock excitation rather than photoionization, however formally failing the [S II]/Hα line ratio criterion, were classified as shells to distinguish them from H ii regions.
Diffuse ionized gas Results: Diffuse ionized gas, that has been thought for some time to be due to photoionization from field stars and Lyman continuum radiation leaking from H ii regions  (Oey & Kennicutt 1997) , is ubiquitously found in our dataset. Fig. 19  illustrates the distribution of DIG emission, whose visibility is enhanced by choosing the [S II] emission line map as opposed to Hα, as well as a suitable color table. Apart from bright H ii regions, SNR, and shells that appear in pink and white hues, the greenish structure can mostly be attributed to the ISM. Typical [S II] surface brightness values corresponding to this color coding are from a few up to 50×10 -18 erg cm -2 s -1 arcsec -2. The presence of DIG is very prominent along the NW spiral arm, and even near the nucleus of the galaxy, with a particularly enhanced level over a roughly A&A proofs: manuscript no.
For the scope of this paper, we have not attempted to remove the disturbing emission, e. g. following the discussion of Falcón-Barroso et al. (  2004 ) for the measurement of emissionfree stellar kinematics. We reserve this step to the future analysis of the complete dataset with the pPXF tool  (Cappellari & Emsellem 2004) , that would also address a stellar population analysis of the background component. The present results are plotted in panel (b) of Fig. 25  with the same colour-code as the Hα velocity map, where black areas indicate that no ULySS fit was obtained due to bright nebular emission lines. Despite the fact that significant areas are not covered with LOSV information, for the tiles that do carry information the velocities are almost indistinguishable from the Hα map. The predominance of G type main sequence star spectra of the ULySS fits for the background in field (a), changing to predominantly B type spectra for the fields associated with the spiral arm is suggestive of a population age ≥ 10 Gyr near the nucleus  (Bertelli et al.
It is going to be interesting to see after the final analysis of our full dataset whether a similar behavior can be found for AGB stars as the progenitors of PNe. We also speculate that we may be able to find evidence for the existence of migration along the leading and trailing edges of spiral arms as suggested by the predictions from numerical simulations by  Grand et al. (2016) , although it would be premature at this stage to draw any conclusions from our as yet provisional dataset.
(2017). A possible alternative is that star B has moved closer to the position of star A. In that case B would be the actual foreground star with a rather high proper motion. Unlike an ongoing MUSE GTO program on globular clusters  (Giesers et al. 2018) , we have as yet not attempted to obtain multi-epoch observations in NGC 300 with the purpose of detecting radial velocity or spectrophotometric variability. However, such an observing strategy of future MUSE surveys in nearby galaxies would open unique opportunities, e. g. , to discover O star binaries.
Summary and conclusions This paper is presenting the first results obtained from MUSE observations of the nearby galaxy NGC 300 in the wide field mode, utilizing the novel technique of crowded field 3D spectroscopy. The dataset used at this stage comprises five complete pointings at the nucleus of the galaxy and adjacent regions to the west with a total exposure time of 1. 5 h per field, two of which are compromised by poor seeing. Two more pointings were as yet incomplete with exposure times of 0. 5 and 1 h, respectively. The major purpose of this first paper is to demonstrate the feasibility of crowded field 3D spectroscopy in nearby galaxies, and to inform the astronomical community about the legacy value of MUSE datacubes, in particular concerning the multitude of scientific results over a variety of different objects one can expect from such data.
The significant level of human interaction at this stage is timeconsuming and cumbersome. We are actively working on the improvement of the currently available tools and expect that future developments will enable fully automatic procedures, which is a prerequisite for the analysis of surveys larger than the present study. As the major outcome of this pilot study, that can be considered a proof-of-principle for MUSE crowded-field 3D spectroscopy in nearby galaxies, we summarize the following results: 1. It is possible to decompose nearby galaxies into individual giant stars and an unresolved component of faint background stars. From the analysis of field (i), which is the best one in our dataset in terms of seeing, we present spectra for a total of 517 stars whose S/N was sufficient for spectral type classification and the determination of radial velocities ( S/N ≥ 3).
We registered a total of 38 SNR candidates, with sizes ranging between a few and more than 100 pc. Some of the SNR candidates exhibit very low surface brightness, and therefore a possible confusion with the DIG. 10. We measured DIG emission lines in the nuclear region of NGC 300 down to surface brightness levels as low as a few 10 -18 erg cm -2 s -1 arcsec -2 and identified filamentary structures that show diagnostic emission line ratios that are characteristic for shock excitation, whereas only a few areas with very low surface brightness were found whose spectra are characteristic for photoionization. 11. Two young clusters within a projected distance of less than 75 pc from the nucleus of NGC 300 were discovered. 12. Of serendipitous discoveries made in the process of data analysis, we mention that 28 background galaxies with redshifts z=0.
For an instrument like MUSE that has a factor of ∼350 times more spaxels than PMAS, such an approach is computationally very expensive. The further development of PampelMUSE will specifically address this issue. Another limitation was imposed by the incomplete coverage of the HRD by the MIUSCAT and GLIB libraries, especially for hot stars, emission line stars, and also for carbon stars. We are planning to resolve this problem by complementing the libraries with simulations and new observational data. The MaStar library currently being planned as part of the SDSS-IV collaboration  (Yan et al. 2017 ) may become a promising solution to this end. Future work shall address the completed dataset of stellar spectra of all fields with secured quality checks, including two new pointings at larger galactocentric distance that are not shown in this paper.
Furthermore, from a detailed kinematic study we expect insight into phenomena like migration, mergers, and runaway stars. Another challenging goal will be the determination of chemical abundances for individual stars, with interesting prospects concerning young and old stellar populations, e. g. blue and red supergiants vs. RGB and AGB stars. Again on the basis of the complete dataset, we shall study the origin of the PNLF and influences on its shape owing to the underlying stellar population, in particular M and C stars as their progenitors. This goal has become more accute with the revised picture of post-AGB evolution from the latest models of Miller Bertolami  (2016) , that are three to ten times faster and ∼0. 1-0. 3 dex brighter than the previous models by  Vassiliadis & Wood (1994)  and  Bloecker (1995) , that were being used in many studies.
With the hypothesis that DIG emission may be dominated by shock excitation, we are planning a follow-up paper to systematically investigate all of our pointings in more detail in order to obtain a more global view of the characteristics and origin of DIG in different parts of the galaxy. For the modest investment in observing time (9 h) the yield as summarized in Table  14  is impressive. It has been a fundamental goal of the development of the MUSE instrument to break the conventional sequence of photometry -follow-up spectroscopy, and replace it with a single-step observation, that provides spectra and images from a single homogenous dataset. Beyond this already fundamental achievement, it is worthwhile to stress that not just quantitatively, but also qualitatively it has been only the format and performance of MUSE that has enabled the efficient use of crowded field spectroscopy, both in terms of multiplex advantage, as well as in utilizing the PSF fitting technique to deblend overlapping stellar images.