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The Birmingham Solar Oscillations Network (BiSON) observes acoustic oscillations of the Sun. The dominant noise source is caused by fluctuations of Earth’s atmosphere, and BiSON seeks to mitigate this effect by combining multiple rapid observations in alternating polarization states. Current instrumentation uses bespoke Pockels-effect cells to select the polarization state. Here, we investigate an alternative off-the-shelf solution, a liquid crystal (LC) retarder, and discuss the potential impact of differences in performance. We show through electrical simulation of the photodiode-based detectors, and assessment of both types of polarization device, that although the switching rate is slower the off-the-shelf LC retarder is a viable replacement for a bespoke Pockels-effect cell. The simplifications arising from the use of off-the-shelf components allow easier and quicker instrumentation deployment.

We describe a new spectrophotometer for the Birmingham Solar Oscillations Network (BiSON), based on a next generation observation platform, BiSON:NG, a significantly miniaturised system making use of inexpensive consumer-grade hardware and off-the-shelf components, where possible. We show through system modelling and simulation, along with a summer observing campaign, that the prototype instrument produces data on the Sun's low-degree acoustic (p-mode) oscillations that are of equal quality and can be seamlessly integrated into the existing network. Refreshing the existing ageing hardware, and the extended observational network potential of BiSON:NG, will secure our ongoing programme of high-quality synoptic observations of the Sun's low-degree oscillations (e.g., for seismic monitoring of the solar cycle at a "whole Sun" level)., 8 pages, 8 figures, 1 table. Accepted by RAS Techniques and Instruments: 2022 September 26

Introduction Chronic pain is associated with frailty. We hypothesised that painful comorbidities would be more strongly associated with frailty than non-painful comorbidities. Method Data were from Investigating Musculoskeletal Health and Wellbeing, a UK-based cohort of people with or at risk of musculoskeletal problems or frailty. Average pain over the previous month was assessed using an 11-point numerical rating scale (NRS). The original FRAIL questionnaire comprises five self-report items: Fatigue, Resistance, Ambulation, Illnesses and Loss of weight. In this study risk of frailty was operationalised using a modified FRAIL questionnaire, omitting the “illnesses” item which related to comorbidities. Comorbidities were classified as either ‘painful’ or ‘non-painful’ based on the International Association for the Study of Pain chronic pain classification criteria. Ordinal logistic regression models explored associations of comorbidity counts with frailty. Results Cross-sectional data were from 2473 participants, 57% female, median age 72 (range 40 to 96) years. 518 (21%) participants were classified as frail. Mean (SD) pain score was 5.5 (2.5). Median (IQR) painful comorbidities was 2 (1 to 3) and non-painful 1 (0 to 2). Highest comorbidity frequency: arthritis (66%) and hypertension (38%). Pain was associated with frailty (OR 1.58 (1.52 to 1.64)). Painful comorbidities (aOR 1.64 (1.54 to 1.75) and non-painful comorbidities (aOR 1.31 (1.21 to 1.41)) were both associated with frailty when included in the same multivariable model adjusted for age, sex and BMI. Conclusions Painful comorbidities were most strongly associated with frailty, although non-painful comorbidities also contributed. Pain and frailty are interconnected, and this might in part be due to comorbidities or their treatments. These findings provide justification for further research to identify the mechanisms through which pain is involved in frailty and to include pain management in interventions to ameliorate frailty.

We examine the solar-cycle variation of the power in the low-degree helioseismic modes by looking at binned power spectra from 45 years of observations with the Birmingham Solar Oscillations Network, which provides a more robust estimate of the mode power than that obtained by peak fitting. The solar-cycle variation of acoustic mode power in the five-minute band is clearly seen. Unusually, even though Cycle 24 was substantially weaker in terms of surface magnetic activity than Cycle 23, the reduction in mode power at solar maximum is very similar for the two cycles, suggesting that the relationship between mode power and magnetic activity is more complex than has previously been thought. This is in contrast to the mode frequencies, which show a strong correlation with activity with only subtle differences between in the response across different solar cycles., Comment: 8 pages, 6 figures, accepted by MNRAS 27-5-22

We present an up-to-date latitude–time map of the solar zonal flows at 0.99 R ⊙ from global helioseismology using data from the Global Oscillation Network Group, the Michelson Doppler Imager, and the Helioseismic and Magnetic Imager.

Context. Current and future space-based observatories such as the Transiting Exoplanet Survey Satellite (TESS) and PLATO are set to provide an enormous amount of new data on oscillating stars, and in particular stars that oscillate similar to the Sun. Solar-like oscillators constitute the majority of known oscillating stars and so automated analysis methods are becoming an ever increasing necessity to make as much use of these data as possible. Aims. Here we aim to construct an algorithm that can automatically determine if a given time series of photometric measurements shows evidence of solar-like oscillations. The algorithm is aimed at analyzing data from the TESS mission and the future PLATO mission, and in particular stars in the main-sequence and subgiant evolutionary stages. Methods. The algorithm first tests the range of observable frequencies in the power spectrum of a TESS light curve for an excess that is consistent with that expected from solar-like oscillations. In addition, the algorithm tests if a repeating pattern of oscillation frequencies is present in the time series, and whether it is consistent with the large separation seen in solar-like oscillators. Both methods use scaling relations and observations which were established and obtained during the CoRoT, Kepler, and K2 missions. Results. Using a set of test data consisting of visually confirmed solar-like oscillators and nonoscillators observed by TESS, we find that the proposed algorithm can attain a 94.7% true positive (TP) rate and a 8.2% false positive (FP) rate at peak accuracy. However, by applying stricter selection criteria, the FP rate can be reduced to ≈ 2%, while retaining an 80% TP rate.

BackgroundCentral mechanisms of knee pain occur in the central nervous system and may intensify and prolong pain. Central pain mechanisms might be facilitated by ongoing nociceptive input. A link between multimorbidity and central mechanisms of knee pain is proposed; ongoing sensory inputs due to comorbidities may trigger changes in pain processing by the CNS. This might be particularly expected with painful comorbidities.ObjectivesTo investigate potential relationships of painful and non-painful multimorbidity with central mechanisms of knee pain.MethodsCross-sectional analysis of self-report data from participants of the Investigating Musculoskeletal Health and Wellbeing cohort, who reported knee as their most bothersome site of joint pain over the previous month, with pain rated ≥1/10, and who had completed FRAIL and CAP-Knee (1) questionnaires. Two indirect measures suggesting central mechanisms involvement in knee pain were used as dependent variables; pain intensity (0-10 numerical rating scale) and CAP-Knee score (0-16 scale). Comorbidities were assigned either “painful comorbidity” or “non-painful comorbidity” status based on IASP classification of chronic pain criteria (2). Multivariable linear regression models, adjusted for age and sex, were employed to explore associations of comorbidity counts with pain intensity and CAP-Knee score.Results736 participants satisfied inclusion criteria. 55% were female, mean age 71 (range 40 to 95). Painful comorbidity count and non-painful comorbidity count each had positive associations with pain intensity (β=0.42, 95% CI=0.29 to 0.54, pConclusionBoth painful and non-painful comorbidities were positively associated with central mechanisms of knee pain, providing further insight into the interconnectedness of pain processing systems and the rest of the body. The explanation behind these relationships may depend on more than just ongoing nociceptive input. Future work should address possible contributions from genetic, pathophysiological, psychological, and pharmacological factors associated with comorbid diagnosis.References[1]Akin-Akinyosoye K, Frowd N, Marshall L, Stocks J, Fernandes GS, Valdes A, et al. Traits associated with central pain augmentation in the Knee Pain In the Community (KPIC) cohort. Pain [Internet]. 2018 Jun PMC5959005]; 159(6):[1035-44 pp.]. Available from: https://dx.doi.org/10.1097%2Fj.pain.0000000000001183.[2]IASP-Task-Force-on-Taxonomy. Classification of Chronic Pain (Second Edition) [E-Book]. Seattle: IASP Task Force on Taxonomy. IASP Press; 1994 [Part I: Topics and Codes]. Available from: https://www.iasp-pain.org/publications/free-ebooks/classification-of-chronic-pain-second-edition-revised/ [date accessed: October 22, 2021].Disclosure of InterestsHarrison R. Lewis: None declared, Wendy J. Chaplin: None declared, Daniel F. McWilliams Grant/research support from: Receives grants and research support from Pfizer and Eli Lilly., Bonnie S. Millar: None declared, Seyed Shahtaheri: None declared, John F.R. Gladman: None declared, David Walsh Grant/research support from: Grants and research support were received from Pfizer and Eli Lilly.

Dating stars is a major challenge with a deep impact on many astrophysical fields. One of the most promising techniques for this is using chemical abundances. Recent space- and ground-based facilities have improved the quantity of stars with accurate observations. This has opened the door for using Bayesian inference tools to maximise the information we can extract from them. Our aim is to present accurate and reliable stellar age estimates of FGK stars using chemical abundances and stellar parameters. We used one of the most flexible Bayesian inference techniques (hierarchical Bayesian models) to exceed current possibilities in the use of chemical abundances for stellar dating. Our model is a data-driven model. We used a training set that has been presented in the literature with ages estimated with isochrones and accurate stellar abundances and general characteristics. The core of the model is a prescription of certain abundance ratios as linear combinations of stellar properties including age. We gathered four different testing sets to assess the accuracy, precision, and limits of our model. We also trained a model using chemical abundances alone. We found that our age estimates and those coming from asteroseismology, other accurate sources, and also with ten Gaia benchmark stars agree well. The mean absolute difference of our estimates compared with those used as reference is 0.9 Ga, with a mean difference of 0.01 Ga. When using open clusters, we reached a very good agreement for Hyades, NGC 2632, Ruprecht 147, and IC4651. We also found outliers that are a reflection of chemical peculiarities and/or stars at the limit of the validity ranges of the training set. The model that only uses chemical abundances shows slightly worse mean absolute difference (1.18 Ga) and mean difference (-0.12 Ga)., Comment: 15 pages, 15 figures. Accepted for publication in Astronomy & Astrophysics

We present a set of 87 RAVE stars with detected solar like oscillations, observed during Campaign 1 of the K2 mission (RAVE K2-C1 sample). This dataset provides a useful benchmark for testing the gravities provided in RAVE Data Release 4 (DR4), and is key for the calibration of the RAVE Data Release 5 (DR5). In the present work, we use two different pipelines, GAUFRE (Valentini et al. 2013) and Sp_Ace (Boeche & Grebel 2016), to determine atmospheric parameters and abundances by fixing log(g) to the seismic one. Our strategy ensures highly consistent values among all stellar parameters, leading to more accurate chemical abundances. A comparison of the chemical abundances obtained here with and without the use of seismic log(g) information has shown that an underestimated (overestimated) gravity leads to an underestimated (overestimated) elemental abundance (e.g. [Mg/H] is underestimated by ~0.25 dex when the gravity is underestimated by 0.5 dex). We then perform a comparison between the seismic gravities and the spectroscopic gravities presented in the RAVE DR4 catalogue, extracting a calibration for log(g) of RAVE giants in the colour interval 0.50, Comment: 20 pages, 27 figures, accepted

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We present preliminary asteroseismic results from Kepler on three G-type stars. The observations, made at one-minute cadence during the first 33.5d of science operations, reveal high signal-to-noise solar-like oscillation spectra in all three stars: About 20 modes of oscillation may be clearly distinguished in each star. We discuss the appearance of the oscillation spectra, use the frequencies and frequency separations to provide first results on the radii, masses and ages of the stars, and comment in the light of these results on prospects for inference on other solar-type stars that Kepler will observe., Comment: 16 pages, 3 figures, 1 table; now accepted for publication in ApJ Letters

Kepler mission will provide a huge amount of asteroseismic data during the next few years, among which hundreds of solar-like stars will be targeted. The amount of stars and their observation length represent a step forward in the comprehension of the stellar evolution that has already been initiated by CoRoT and MOST missions. Up to now, the slow cadence of observed targets allowed an individual and personalized analysis of each star. During the survey phase of Kepler, this will be impossible. This is the reason why, within the AsteroFLAG team, we have been developing automatic pipelines for the Kepler solar-like oscillation stars. Our code starts by finding the frequency-range where p-mode power is present and, after fitting the background, it looks for the mode amplitudes as well as the central frequency of the p-mode hump. A good estimation of the large separation can thus be inferred in this region. If the signal to noise is high enough, the code obtains the characteristics of the p modes by doing a global fitting on the power spectrum. Here, we will first describe a few features of this pipeline and its application to AsteroFLAG synthetic data to check the validity of the code., Comment: 4 pages, 7 figures, Stellar Pulsation Conference (Santa Fe, NM, USA) proceedings