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Einstein's article on the EPR paradox is the most cited of his works, but not many know that it was not fully representative of the way he thought about the incompleteness of the quantum formalism. Indeed, his main worry was not Heisenberg's uncertainty principle, which he accepted, but the experimental non-separability of spatially separate systems. The same problem was also recognized, years later, by one of us, as part of an axiomatic analysis of the quantum formalism, which revealed an unexpected structural limitation of the quantum formalism in Hilbert space, preventing the description of separate systems. As we will explain, this limitation does not manifest at the level of the states, but of the projectors describing the properties, in the sense that there are not enough properties in the formalism to describe separate systems. The question remains whether separability is a possibility at the fundamental level and if a formalism should integrate it into its mathematical structure, as a possibility. To aid our intuition, we offer a reflection based on a powerful analogy between physical systems and human conceptual entities, as the question of separability also arises for the latter., Comment: 33 pages, no figures

Multimodal/vision language models (VLMs) are increasingly being deployed in healthcare settings worldwide, necessitating robust benchmarks to ensure their safety, efficacy, and fairness. Multiple-choice question and answer (QA) datasets derived from national medical examinations have long served as valuable evaluation tools, but existing datasets are largely text-only and available in a limited subset of languages and countries. To address these challenges, we present WorldMedQA-V, an updated multilingual, multimodal benchmarking dataset designed to evaluate VLMs in healthcare. WorldMedQA-V includes 568 labeled multiple-choice QAs paired with 568 medical images from four countries (Brazil, Israel, Japan, and Spain), covering original languages and validated English translations by native clinicians, respectively. Baseline performance for common open- and closed-source models are provided in the local language and English translations, and with and without images provided to the model. The WorldMedQA-V benchmark aims to better match AI systems to the diverse healthcare environments in which they are deployed, fostering more equitable, effective, and representative applications., Comment: submitted for review, total of 14 pages

Gravito-inertial asteroseismology saw its birth from the 4-years long light curves of rotating main-sequence stars assembled by the Kepler space telescope. High-precision measurements of internal rotation and mixing are available for about 600 stars of intermediate mass so far that are used to challenge the state-of-the-art stellar structure and evolution models. Our aim is to prepare for future large ensemble modelling of gravity (g)-mode pulsators by relying on a new sample of such stars recently discovered from the third Data Release of the Gaia space mission and confirmed by space photometry from the TESS mission. This sample of potential asteroseismic targets is about 23 times larger than the Kepler sample. We use the effective temperature and luminosity inferred from Gaia to deduce evolutionary masses, convective core masses, radii, and ages for ~14,000 g-mode pulsators classified as such from their nominal TESS light curves. We do so by constructing two dedicated grids of evolutionary models for rotating stars with input physics from the asteroseismic calibrations of Kepler $\gamma$ Dor pulsators. We find the new g-mode pulsators to cover an extended observational instability region covering masses from about 1.3 to 9Msun. We provide their mass-luminosity and mass-radius relations, as well as convective core masses. Our results suggest that oscillations excited by the opacity mechanism occur uninterruptedly for the mass range above about 2Msun, where stars have a radiative envelope aside from thin convection zones in their excitation layers. Our evolutionary parameters for the sample of Gaia-discovered g-mode pulsators with confirmed modes by TESS offer a fruitful starting point for future TESS ensemble asteroseismology once a sufficient number of modes is identified in terms of the geometrical wave numbers and overtone for each of the pulsators., Comment: Accepted for publication in Astronomy & Astrophysics. 13 pages, 16 figures. Full abstract in PDF

Eclipsing binaries are crucial for understanding stellar physics, allowing detailed studies of stellar masses, radii, and orbital dynamics. Recent space missions like the Transiting Exoplanet Survey Satellite (TESS) have significantly expanded the catalogue of observed eclipsing binaries with uninterrupted time series photometry, providing an opportunity for large-scale ensemble studies. This study aims to analyse the statistical properties of circularisation in a large sample of intermediate-to-high mass eclipsing binaries observed by TESS. We explore the dependence of orbital circularisation on stellar properties and orbital parameters to improve our understanding of the physical processes affecting these systems. We further aim to assess the role of stellar pulsations in circularisation. We compiled a catalogue of O- to F-type stars to search for eclipsing binary signals in the TESS data. Using automated classification and data analysis methodologies, we arrive at a well-characterised sample of 14,573 eclipsing binaries. We investigate the statistical characteristics of the sample as a function of temperature, orbital period, and scaled orbital separation. The orbital circularisation was measured with statistical methods to obtain three distinct measurements of the critical period and separation in four temperature ranges. Pulsations were identified in the g- and p-mode regimes and a reduced fraction of eccentric systems was found among them. Our analysis confirmed and expanded upon previous findings that additional dissipation is needed as compared to the predictions of turbulent viscosity and non-resonant radiative damping. We speculate that pulsations may play a role in the circularisation of close binaries. Our study highlights the need for dissipative mechanisms that can produce a wide range of critical periods from a range of initial conditions., Comment: 15 pages, 10 figures, 4 appendices (15 pages, 26 figures). Accepted for publication in A&A

Background: Large language models (LLMs) are trained to follow directions, but this introduces a vulnerability to blindly comply with user requests even if they generate wrong information. In medicine, this could accelerate the generation of misinformation that impacts human well-being. Objectives/Methods: We analyzed compliance to requests to generate misleading content about medications in settings where models know the request is illogical. We investigated whether in-context directions and instruction-tuning of LLMs to prioritize logical reasoning over compliance reduced misinformation risk. Results: While all frontier LLMs complied with misinformation requests, both prompt-based and parameter-based approaches can improve the detection of logic flaws in requests and prevent the dissemination of medical misinformation. Conclusion: Shifting LLMs to prioritize logic over compliance could reduce risks of exploitation for medical misinformation., Comment: Submitted for Review

We study a daily urban waste collection problem arising in the municipality of Groningen, The Netherlands, where residents bring their waste to local underground waste containers organised in clusters. The municipality plans routes for waste collection vehicles to empty the container clusters. These routes should be as short as possible to limit operational costs, but also long enough to visit sufficiently many clusters and ensure that containers do not overflow. A complicating factor is that the actual fill levels of the clusters' containers are not known, and only the number of deposits is observed. Additionally, it is unclear whether the containers should be upgraded with expensive fill level sensors so that the service level can be improved or routing costs can be reduced. We propose an efficient integrated selection and routing (ISR) policy that jointly optimises the daily cluster selection and routing decisions. The integration is achieved by first estimating prizes that express the urgency of selecting a cluster to empty, and then solving a prize-collecting vehicle routing problem with time windows and driver breaks to collect these prizes while minimising routing costs. We use a metaheuristic to solve the prize-collecting vehicle routing problem inside a realistic simulation environment that models the waste collection problem faced by the municipality. We show that solving the daily waste collection problem in this way is very effective, and can lead to substantial cost savings for the municipality in practice, with no reduction in service level. In particular, by integrating the container selection and routing problems using our ISR policy, routing costs can be reduced by more than 40% and the fleet size by 25%. We also show that more advanced measuring techniques do not significantly reduce routing costs, and the service level not at all.

Coronary artery calcium (CAC) is highly predictive of cardiovascular events. While millions of chest CT scans are performed annually in the United States, CAC is not routinely quantified from scans done for non-cardiac purposes. A deep learning algorithm was developed using 446 expert segmentations to automatically quantify CAC on non-contrast, non-gated CT scans (AI-CAC). Our study differs from prior works as we leverage imaging data across the Veterans Affairs national healthcare system, from 98 medical centers, capturing extensive heterogeneity in imaging protocols, scanners, and patients. AI-CAC performance on non-gated scans was compared against clinical standard ECG-gated CAC scoring. Non-gated AI-CAC differentiated zero vs. non-zero and less than 100 vs. 100 or greater Agatston scores with accuracies of 89.4% (F1 0.93) and 87.3% (F1 0.89), respectively, in 795 patients with paired gated scans within a year of a non-gated CT scan. Non-gated AI-CAC was predictive of 10-year all-cause mortality (CAC 0 vs. >400 group: 25.4% vs. 60.2%, Cox HR 3.49, p < 0.005), and composite first-time stroke, MI, or death (CAC 0 vs. >400 group: 33.5% vs. 63.8%, Cox HR 3.00, p < 0.005). In a screening dataset of 8,052 patients with low-dose lung cancer-screening CTs (LDCT), 3,091/8,052 (38.4%) individuals had AI-CAC >400. Four cardiologists qualitatively reviewed LDCT images from a random sample of >400 AI-CAC patients and verified that 527/531 (99.2%) would benefit from lipid-lowering therapy. To the best of our knowledge, this is the first non-gated CT CAC algorithm developed across a national healthcare system, on multiple imaging protocols, without filtering intra-cardiac hardware, and compared against a strong gated CT reference. We report superior performance relative to previous CAC algorithms evaluated against paired gated scans that included patients with intra-cardiac hardware.

This paper considers learning online (implicit) nonlinear model predictive control (MPC) laws using neural networks and Laguerre functions. Firstly, we parameterize the control sequence of nonlinear MPC using Laguerre functions, which typically yields a smoother control law compared to the original nonlinear MPC law. Secondly, we employ neural networks to learn the coefficients of the Laguerre nonlinear MPC solution, which comes with several benefits, namely the dimension of the learning space is dictated by the number of Laguerre functions and the complete predicted input sequence can be used to learn the coefficients. To mitigate constraints violation for neural approximations of nonlinear MPC, we develop a constraints-informed loss function that penalizes the violation of polytopic state constraints during learning. Box input constraints are handled by using a clamp function in the output layer of the neural network. We demonstrate the effectiveness of the developed framework on a nonlinear buck-boost converter model with sampling rates in the sub-millisecond range, where online nonlinear MPC would not be able to run in real time. The developed constraints-informed neural-Laguerre approximation yields similar performance with long-horizon online nonlinear MPC, but with execution times of a few microseconds, as validated on a field-programmable gate array (FPGA) platform.

We have proved in both human-based and computer-based tests that natural concepts generally `entangle' when they combine to form complex sentences, violating the rules of classical compositional semantics. In this article, we present the results of an innovative video-based cognitive test on a specific conceptual combination, which significantly violates the Clauser--Horne--Shimony--Holt version of Bell's inequalities (`CHSH inequality'). We also show that collected data can be faithfully modelled within a quantum-theoretic framework elaborated by ourselves and a `strong form of entanglement' occurs between the component concepts. While the video-based test confirms previous empirical results on entanglement in human cognition, our ground-breaking empirical approach surpasses language barriers and eliminates the need for prior knowledge, enabling universal accessibility. Finally, this transformative methodology allows one to unravel the underlying connections that drive our perception of reality. As a matter of fact, we provide a novel explanation for the appearance of entanglement in both physics and cognitive realms., Comment: 23 pages, 2 figures, standard LaTeX. arXiv admin note: text overlap with arXiv:2102.03847

Gaia/DR3 has provided a large sample of new g-mode pulsators, among which~11,600 are Gam Dor stars. This work present the spectroscopic parameters of these Gam Dor pulsators estimated by the GSP-spec module that analysed millions of Gaia spectra. The Galactic positions, kinematics, and orbital properties of these new Gaia pulsators were examined in order to define a sub-sample belonging to the Milky Way thin disc, in which these young stars should preferentially be found. The stellar luminosities, radii, and astrometric surface gravities were estimated without adopting any priors from uncertain stellar evolution models. These parameters, combined with the GSP-spec effective temperatures, spectroscopic gravities, and metallicities were then validated by comparison with recent literature studies. Most stars are found to belong to the Galactic thin disc, as expected. It is also found that the derived luminosities, radii, and astrometric surface gravities are of high quality and have values typical of genuine Gam Dor pulsators. Moreover, we have shown that Teff and [M/H] of pulsators with high enough SNR spectra or slow to moderate rotation rates are robust. This allowed to define a sub-sample of genuine slow-rotating Gaia Gam Dor pulsators. Their Teff are found between ~6500 and ~7800K, log(g) around 4.2 and luminosities and stellar radii peak at ~5Lsun and ~1.7Rsun. [M/H] is close to the Solar value, although 0.5dex more metal-poor and metal-rich Gam Dor are identified. The [alpha/Fe] content is fully consistent with the chemical properties of the Galactic disc. Gaia/DR3 spectroscopic properties of Gam Dor stars therefore confirm the nature of these pulsators and allow to chemo-physically parametrise a new large sample of such stars. Moreover, future Gaia DR should drastically increase the number of Gam Dor stars with good-precision spectroscopically derived parameters., Comment: A&A, revised version

Identical systems, or entities, are indistinguishable in quantum mechanics (QM), and the symmetrization postulate rules the possible statistical distributions of a large number of identical quantum entities. However, a thorough analysis on the historical development of QM attributes the origin of quantum statistics, in particular, Bose-Einstein statistics, to a lack of statistical independence of the micro-states of identical quantum entities. We have recently identified Bose-Einstein statistics in the combination of words in large texts, as a consequence of the entanglement created by the meaning carried by words when they combine in human language. Relying on this investigation, we put forward the hypothesis that entanglement, hence the lack of statistical independence, is due to a mechanism of contextual updating, which provides deeper reasons for the appearance of Bose-Einstein statistics in human language. However, this investigation also contributes to a better understanding of the origin of quantum mechanical statistics in physics. Finally, we provide new insights into the intrinsically random behaviour of microscopic entities that is generally assumed within classical statistical mechanics., Comment: 30 pages, 5 figures

Spectral lines of hot massive stars are known to exhibit large excess broadening in addition to rotational broadening. This excess broadening is often attributed to macroturbulence whose physical origin is a matter of active debate in the stellar astrophysics community. By looking into the statistical properties of a large sample of O- and B-type stars, both in the Galaxy and LMC, we aim to shed light on the physical origin of macroturbulent line broadening. We deliver newly measured macroturbulent velocities for 86 stars from the Galaxy in a consistent manner with 126 stars from the LMC. A total sample of 594 O- and B-type stars with measured macroturbulent velocities was composed by complementing our sample with archival data. Furthermore, we compute an extensive grid of MESA models to compare, in a statistical manner, the predicted interior properties of stars (such as convection and wave propagation) with the inference of macroturbulent velocities from high-resolution spectroscopic observations. We find the presence of two principally different regimes where, depending on the initial stellar mass, different mechanisms may be responsible for the observed excess line broadening. Stars with initial masses above some 30$M_{\odot}$ are found to have macroturbulent velocities fully determined by subsurface convective zones formed in the iron opacity bump (FeCZ), while some other mechanism is required to explain observations for masses below 12$M_{\odot}$. The latter finding leaves the potential for waves generated at the interface of the convective core and radiative envelope of the star to be responsible for the observed macroturbulent broadening. Both mechanisms may co-exist in the intermediate regime of stellar masses, between some 12 and 30$M_{\odot}$., Comment: Accepted for publication in A&A on 17 Oct 2024

The Gaia mission discovered many new candidate \beta Cephei (\beta Cep) pulsators, which are meanwhile confirmed from TESS space photometry. We aim to analyse all currently available TESS data for these \beta Cep pulsators, of which 145 were new discoveries, in order to exploit their asteroseismic potential. \beta Cep stars belong to an under-represented class of pulsators in the current space photometry revolution while being of critical importance to improve evolution models of massive stars. We extracted light curves for 216 star from the TESS full-frame images and performed pre-whitening. Based on Gaia DR3, we deduced stellar properties and compared them to those of known \beta Cep stars. We developed a methodology to identify the dominant pulsation modes of the \beta Cep stars from Gaia and TESS amplitude ratios and from the detection of rotationally-split multiplets. We used grid modelling to gain insights into the population of \beta Cep stars. With the combination of TESS and Gaia, we successfully identified the mode degrees for 176 stars. of which the majority are dipole non-radial modes. Many non-radial modes show splittings in their TESS frequency spectra allowing us to assemble a large set of split multiplets in \beta Cep stars and to calculate their envelope rotation, spin parameter, and the level of differential envelope-to-surface rotation. For the latter, we find an upper limit of 4, with most stars rotating almost rigidly. We also provide the asymmetries of the multiplets. Based on grid modelling, we provide mass, convective core mass, and ages for 164 stars. By combining Gaia and TESS, we enable asteroseismology of \beta Cep stars as a population. Our study prepares for future detailed modelling based on individual frequencies of identified modes leading towards a better understanding of these massive pulsators, as crucial probes of stellar evolution theory. (abridged), Comment: Submitted to A&A on 30 July 2024

We find that the observed pressure-mode rotational splittings of slowly/moderately rotating Delta Scuti stars and Beta Cephei stars mostly have a positive asymmetry. That is, the left frequency spacing is larger than the right spacing in the dipole mode splitting triplets and the $l=2$ mode splitting multiplets (considering $m=1, 0, -1$ modes only). This is in agreement with the second-order perturbative effect of the rotational non-spherical distortion: both the prograde and retrograde modes have their frequencies shifted towards lower values relative to the $m=0$ modes. We thus study the rotational perturbation both in the first and second order, as well as the near-degeneracy mode coupling effect in MESA models representing Delta Scuti stars. For faster rotators, the near-degeneracy mode coupling between the nearest radial and quadrupole modes can significantly shift the $m=0$ modes, reduce the splitting asymmetry, and even change its sign. We find the theoretical splitting asymmetry from the second-order non-spherical distortion is larger than observed asymmetry. To facilitate future detections, we predict correlations between splitting asymmetry, splitting amplitude, and pulsation frequency. We also discuss additional factors that can influence splitting asymmetry, including embedded magnetic fields, resonant mode coupling, and binarity., Comment: MNRAS, submitted

Products of stellar mergers are predicted to be common in stellar populations and can potentially explain stars with peculiar properties. When the merger occurs after the initially more massive star has evolved into the Hertzsprung gap (HG), the merger product may remain in the blue part of the Hertzsprung-Russell diagram (HRD) for millions of years. Such objects could, therefore, explain the overabundance of observed blue stars, such as blue supergiants. However, it is currently not straightforward to distinguish merger products from genuine single stars. We make detailed asteroseismic comparisons between models of massive post-main-sequence merger products and genuine single stars to identify which asteroseismic diagnostics can be used to distinguish them. In doing so, we develop tools for the relatively young field of merger seismology. Genuine single stars in the HG are fully radiative, while merger products have a convective He-burning core and convective H-burning shell while occupying similar locations in the HRD. These structural differences are reflected in lower asymptotic period spacing values for merger products and the appearance of deep dips in their period spacing patterns. Our genuine single-star models with masses above roughly 11.4 solar masses develop short-lived intermediate convective zones during their HG evolution. This also leads to deep dips in their period spacing patterns. Because of the lack of a convective core, merger products and genuine single stars can be distinguished based on their asymptotic period spacing value in this mass range. We perform the comparisons with and without the effects of slow rotation included in the pulsation equations and conclude that the two types of stars are seismically distinguishable in both cases. The observability of the distinguishing asteroseismic features of merger products can now be assessed and exploited in practice., Comment: 26 pages (incl. appendix), 21 figures; accepted for publication in A&A

Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases. This is particularly crucial for drug names, where patients often use brand names like Advil or Tylenol instead of their generic equivalents. To study this, we create a new robustness dataset, RABBITS, to evaluate performance differences on medical benchmarks after swapping brand and generic drug names using physician expert annotations. We assess both open-source and API-based LLMs on MedQA and MedMCQA, revealing a consistent performance drop ranging from 1-10\%. Furthermore, we identify a potential source of this fragility as the contamination of test data in widely used pre-training datasets. All code is accessible at https://github.com/BittermanLab/RABBITS, and a HuggingFace leaderboard is available at https://huggingface.co/spaces/AIM-Harvard/rabbits-leaderboard., Comment: submitted for review, total 15 pages

This paper introduces a novel method for predicting tool wear in CNC turning operations, combining ultrasonic microphone arrays and convolutional neural networks (CNNs). High-frequency acoustic emissions between 0 kHz and 60 kHz are enhanced using beamforming techniques to improve the signal- to-noise ratio. The processed acoustic data is then analyzed by a CNN, which predicts the Remaining Useful Life (RUL) of cutting tools. Trained on data from 350 workpieces machined with a single carbide insert, the model can accurately predict the RUL of the carbide insert. Our results demonstrate the potential gained by integrating advanced ultrasonic sensors with deep learning for accurate predictive maintenance tasks in CNC machining.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

KIC 4150611 is a high-order multiple composed of a triple system composed of the F1V primary (Aa), which is eclipsed on a 94.2d period by a tight 1.52d binary composed of two dim K/M dwarfs (Ab1, Ab2), which also eclipse each other; an 8.65d eccentric, eclipsing binary composed of two G stars (Ba, Bb); and another faint eclipsing binary composed of two stars of unknown spectral type (Ca and Cb). In addition to its many eclipses, the system is an SB3 spectroscopic multiple (Aa, Ba, and Bb) and the primary (Aa) is a hybrid pulsator. We employ a novel photometric analysis of the complicated eclipse geometry of Aa to obtain orbital and stellar properties of the triple. We acquired 51 TRES spectra at the Fred L. Whipple Observatory, calculating radial velocities and orbital elements of Aa (SB1) and the B binary (SB2). These spectra and radial velocities are used to perform spectral disentangling for Aa, Ba, and Bb. Spectral modelling is applied to the disentangled spectrum of Aa to obtain atmospheric properties. We obtain precise stellar properties of the triple, including the mass ratios (MAa/(MAb1 + MAb2) = 3.61 +/- 0.01, MAb1/MAb2 = 1.113 +/- 0.001), separation ratio (aAab/aAb1Ab2 = 21.81 +/- 0.01), orbital periods (PAab = 94.29486 +/- 0.00008d, PAb1Ab2 = 1.522248 +/- 0.000001d), and stellar radii (RAa = 1.64 +/- 0.06 Rsun, RAb1 = 0.42 +/- 0.01 Rsun, RAb2 = 0.38 +/- 0.01 Rsun). Radial velocity fitting and spectral disentangling arrive at orbital elements for Aa, Ba, and Bb in excellent agreement with each other and with previous results in the literature. Spectral modelling on the disentangled spectrum of Aa provides constraints on the effective temperature (Teff = 7280 +/- 70 K), surface gravity (log(g) = 4.14 +/- 0.18 dex), micro-turbulent velocity (vmicro = 3.61 +/- 0.19 km s-1), rotation velocity (v sin i = 127 +/- 4 km s-1), and metallicity ([M/H] = -0.23 +/- 0.06).

Asteroseismology gives us the opportunity to look inside stars and determine their internal properties. Based on these observations, estimations can be made for the amount of the convective boundary mixing and envelope mixing of such stars, and the shape of the mixing profile in the envelope. However, these results are not typically included in stellar evolution models. We aim to investigate the impact of varying convective boundary mixing and envelope mixing in a range based on asteroseismic modelling in stellar models, both for the stellar structure and for the nucleosynthetic yields. In this first study, we focus on the pre-explosive evolution of a 20Msun star and evolve the models to the final phases of carbon burning. We vary the convective boundary mixing, implemented as step-overshoot, with the overshoot parameter in the range 0.05-0.4 and the amount of envelope mixing in the range 1-10$^{6}$ with a mixing profile based on internal gravity waves. We use a large nuclear network of 212 isotopes to study the nucleosynthesis. We find that enhanced mixing according to asteroseismology of main-sequence stars, both at the convective core boundary and in the envelope, has significant effects on the nucleosynthetic wind yields. Our evolutionary models beyond the main sequence diverge in yields from models based on rotational mixing, having longer helium burning lifetimes and lighter helium-depleted cores. We find that the asteroseismic ranges of internal mixing calibrated from core hydrogen burning stars lead to similar wind yields as those resulting from the theory of rotational mixing. Adopting the seismic mixing levels beyond the main sequence, we find earlier transitions to radiative carbon burning compared to models based on rotational mixing. This influences the compactness and the occurrence of shell-mergers, which may affect the supernova properties and explosive nucleosynthesis., Comment: 18 pages, 14 figures, 2 tables

The main science aim of the BlackGEM array is to detect optical counterparts to gravitational wave mergers. Additionally, the array will perform a set of synoptic surveys to detect Local Universe transients and short time-scale variability in stars and binaries, as well as a six-filter all-sky survey down to ~22nd mag. The BlackGEM Phase-I array consists of three optical wide-field unit telescopes. Each unit uses an f/5.5 modified Dall-Kirkham (Harmer-Wynne) design with a triplet corrector lens, and a 65cm primary mirror, coupled with a 110Mpix CCD detector, that provides an instantaneous field-of-view of 2.7~square degrees, sampled at 0.564\arcsec/pixel. The total field-of-view for the array is 8.2 square degrees. Each telescope is equipped with a six-slot filter wheel containing an optimised Sloan set (BG-u, BG-g, BG-r, BG-i, BG-z) and a wider-band 440-720 nm (BG-q) filter. Each unit telescope is independent from the others. Cloud-based data processing is done in real time, and includes a transient-detection routine as well as a full-source optimal-photometry module. BlackGEM has been installed at the ESO La Silla observatory as of October 2019. After a prolonged COVID-19 hiatus, science operations started on April 1, 2023 and will run for five years. Aside from its core scientific program, BlackGEM will give rise to a multitude of additional science cases in multi-colour time-domain astronomy, to the benefit of a variety of topics in astrophysics, such as infant supernovae, luminous red novae, asteroseismology of post-main-sequence objects, (ultracompact) binary stars, and the relation between gravitational wave counterparts and other classes of transients, Comment: Submitted to PASP

Dimensionality reduction algorithms are often used to visualise high-dimensional data. Previously, studies have used prior information to enhance or suppress expected patterns in projections. In this paper, we adapt such techniques for domain knowledge guided interactive exploration. Inspired by Mapper and STAD, we present three types of lens functions for UMAP, a state-of-the-art dimensionality reduction algorithm. Lens functions enable analysts to adapt projections to their questions, revealing otherwise hidden patterns. They filter the modelled connectivity to explore the interaction between manually selected features and the data's structure, creating configurable perspectives each potentially revealing new insights. The effectiveness of the lens functions is demonstrated in two use cases and their computational cost is analysed in a synthetic benchmark. Our implementation is available in an open-source Python package: https://github.com/vda-lab/lensed_umap., Comment: 11 pages, 5 figures, submitted to IEEE Transactions on Visualization and Computer Graphics

Numerical computations of stellar oscillations for models representative of B-type stars predict fewer modes to be excited than observations reveal from modern space-based photometric data. One shortcoming of state-of-the-art evolution models of B-type stars that may cause a lack of excited modes is the absence of microscopic diffusion in most such models. We investigate whether the inclusion of microscopic diffusion in stellar models of B-type stars, notably radiative levitation experienced by isotopes, leads to extra mode driving by the opacity mechanism compared to the case of models that do not include microscopic diffusion. We consider the case of slowly to moderately rotating stars and use non-rotating equilibrium models, while we account for (uniform) rotation in the computations of the pulsation frequencies. We calculate 1D stellar models with and without microscopic diffusion and examine the effect of radiative levitation on mode excitation, for both low-radial order pressure and gravity modes and for high-radial order gravity modes. We find systematically more modes to be excited for the stellar models including microscopic diffusion compared to those without it, in agreement with observational findings of pulsating B-type dwarfs. Furthermore, the models with microscopic diffusion predict that excited modes occur earlier on in the evolution compared to modes without it. In order to maintain realistic surface abundances during the main sequence, we include macroscopic envelope mixing by internal gravity waves. While radiative levitation has so far largely been neglected in stellar evolution computations of B-type stars for computational convenience, it impacts mode excitation predictions for stellar models of such stars. We conclude that the process of radiative levitation is able to reduce the discrepancy between predicted and observed excited pulsation modes in B-type stars., Comment: Paper accepted for publication in Astronomy & Astrophysics (10 pages, 11 figures). Full abstract in PDF

Purpose: To examine whether incorporating anatomical awareness into a deep learning model can improve generalizability and enable prediction of disease progression. Methods: This retrospective multicenter study included conventional pelvic radiographs of 4 different patient cohorts focusing on axial spondyloarthritis (axSpA) collected at university and community hospitals. The first cohort, which consisted of 1483 radiographs, was split into training (n=1261) and validation (n=222) sets. The other cohorts comprising 436, 340, and 163 patients, respectively, were used as independent test datasets. For the second cohort, follow-up data of 311 patients was used to examine progression prediction capabilities. Two neural networks were trained, one on images cropped to the bounding box of the sacroiliac joints (anatomy-aware) and the other one on full radiographs. The performance of the models was compared using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Results: On the three test datasets, the standard model achieved AUC scores of 0.853, 0.817, 0.947, with an accuracy of 0.770, 0.724, 0.850. Whereas the anatomy-aware model achieved AUC scores of 0.899, 0.846, 0.957, with an accuracy of 0.821, 0.744, 0.906, respectively. The patients who were identified as high risk by the anatomy aware model had an odds ratio of 2.16 (95% CI: 1.19, 3.86) for having progression of radiographic sacroiliitis within 2 years. Conclusion: Anatomical awareness can improve the generalizability of a deep learning model in detecting radiographic sacroiliitis. The model is published as fully open source alongside this study.

Purpose: To introduce a deep learning model capable of multi-organ segmentation in MRI scans, offering a solution to the current limitations in MRI analysis due to challenges in resolution, standardized intensity values, and variability in sequences. Materials and Methods: he model was trained on 1,200 manually annotated MRI scans from the UK Biobank, 221 in-house MRI scans and 1228 CT scans, leveraging cross-modality transfer learning from CT segmentation models. A human-in-the-loop annotation workflow was employed to efficiently create high-quality segmentations. The model's performance was evaluated on NAKO and the AMOS22 dataset containing 600 and 60 MRI examinations. Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD) was used to assess segmentation accuracy. The model will be open sourced. Results: The model showcased high accuracy in segmenting well-defined organs, achieving Dice Similarity Coefficient (DSC) scores of 0.97 for the right and left lungs, and 0.95 for the heart. It also demonstrated robustness in organs like the liver (DSC: 0.96) and kidneys (DSC: 0.95 left, 0.95 right), which present more variability. However, segmentation of smaller and complex structures such as the portal and splenic veins (DSC: 0.54) and adrenal glands (DSC: 0.65 left, 0.61 right) revealed the need for further model optimization. Conclusion: The proposed model is a robust, tool for accurate segmentation of 40 anatomical structures in MRI and CT images. By leveraging cross-modality learning and interactive annotation, the model achieves strong performance and generalizability across diverse datasets, making it a valuable resource for researchers and clinicians. It is open source and can be downloaded from https://github.com/hhaentze/MRSegmentator., Comment: 13 pages, 6 figures; corrected co-author info

Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data. In this study, we introduce Cross-Care, the first benchmark framework dedicated to assessing biases and real world knowledge in LLMs, specifically focusing on the representation of disease prevalence across diverse demographic groups. We systematically evaluate how demographic biases embedded in pre-training corpora like $ThePile$ influence the outputs of LLMs. We expose and quantify discrepancies by juxtaposing these biases against actual disease prevalences in various U.S. demographic groups. Our results highlight substantial misalignment between LLM representation of disease prevalence and real disease prevalence rates across demographic subgroups, indicating a pronounced risk of bias propagation and a lack of real-world grounding for medical applications of LLMs. Furthermore, we observe that various alignment methods minimally resolve inconsistencies in the models' representation of disease prevalence across different languages. For further exploration and analysis, we make all data and a data visualization tool available at: www.crosscare.net., Comment: Submitted for review, data visualization tool available at: www.crosscare.net

The Gaia mission has delivered hundreds of thousands of variable star light curves in multiple wavelengths. Recent work demonstrates that these light curves can be used to identify (non-)radial pulsations in the OBAF-type stars, despite the irregular cadence and low light curve precision of order a few mmag. With the considerably more precise TESS photometry, we revisit these candidate pulsators to conclusively ascertain the nature of their variability. We seek to re-classify the Gaia light curves with the first two years of TESS photometry for a sample of 58,970 p- and g- mode pulsators, encompassing gamma Dor, delta Scuti, SPB, and beta Cep variables. We also supply four new catalogues containing the confirmed pulsators, along with their dominant and secondary pulsation frequencies, the number of independent mode frequencies, and a ranking according to their usefulness for future asteroseismic ensemble analysis. We find that the Gaia photometry is exceptionally accurate for detecting the dominant and secondary frequencies, reaching approximately 80% accuracy in frequency for p- and g-mode pulsators. The majority of Gaia classifications are consistent with the classifications from the TESS data, illustrating the power of the low-cadence Gaia photometry for pulsation studies. We find that the sample of g-mode pulsators forms a continuous group of variable stars along the main sequence across B, A, and F spectral types, implying that the mode excitation mechanisms for all these pulsators need to be updated with improved physics. Finally, we provide a rank-ordered table of pulsators according to their asteroseismic potential for follow-up studies. Our catalogue offers a major increase in the number of confirmed gravity-mode pulsators with an identified dominant mode suitable for follow-up TESS ensemble asteroseismology of such stars., Comment: 14 pages, 8 figures, accepted to A&A

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 \pm 0.82 M\odot BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way., Comment: 23 pages, accepted fro publication in A&A Letters. New version with small fixes

We study the phenomenon of categorical perception within the quantum measurement process. The mechanism underlying this phenomenon consists in dilating stimuli being perceived to belong to different categories and contracting stimuli being perceived to belong to the same category. We show that, due to the naturally different way in determining the distance between pure states compared to the distance between density states, the phenomenon of categorical perception is rooted in the structure of the quantum measurement process itself. We apply our findings to the situation of visual perception of colors and argue that it is possible to consider colors as light quanta for human visual perception in a similar way as photons are light quanta for physical measurements of light frequencies. In our approach we see perception as a complex encounter between the existing physical reality, the stimuli, and the reality expected by the perciever, resulting in the experience of the percepts. We investigate what that means for the situation of two colors, which we call Light and Dark, given our findings on categorical perception within the quantum measurement process., Comment: 28 pages, 4 figures. arXiv admin note: text overlap with arXiv:2208.03726

We have detected solar-like oscillations in the mid K-dwarf $\varepsilon$ Indi A, making it the coolest dwarf to have measured oscillations. The star is noteworthy for harboring a pair of brown dwarf companions and a Jupiter-type planet. We observed $\varepsilon$ Indi A during two radial velocity campaigns, using the high-resolution spectrographs HARPS (2011) and UVES (2021). Weighting the time series, we computed the power spectra and established the detection of solar-like oscillations with a power excess located at $5265 \pm 110 \ \mu$Hz -- the highest frequency solar-like oscillations so far measured in any star. The measurement of the center of the power excess allows us to compute a stellar mass of $0.782 \pm 0.023 \ M_\odot$ based on scaling relations and a known radius from interferometry. We also determine the amplitude of the peak power and note that there is a slight difference between the two observing campaigns, indicating a varying activity level. Overall, this work confirms that low-amplitude solar-like oscillations can be detected in mid-K type stars in radial velocity measurements obtained with high-precision spectrographs., Comment: 10 pages, 3 figures, accepted for publication in ApJ

Introduction: Lung cancer is a leading cause of cancer-related mortality, and stereotactic body radiotherapy (SBRT) has become a standard treatment for early-stage lung cancer. However, the heterogeneous response to radiation at the tumor level poses challenges. Currently, standardized dosage regimens lack adaptation based on individual patient or tumor characteristics. Thus, we explore the potential of delta radiomics from on-treatment magnetic resonance (MR) imaging to track radiation dose response, inform personalized radiotherapy dosing, and predict outcomes. Methods: A retrospective study of 47 MR-guided lung SBRT treatments for 39 patients was conducted. Radiomic features were extracted using Pyradiomics, and stability was evaluated temporally and spatially. Delta radiomics were correlated with radiation dose delivery and assessed for associations with tumor control and survival with Cox regressions. Results: Among 107 features, 49 demonstrated temporal stability, and 57 showed spatial stability. Fifteen stable and non-collinear features were analyzed. Median Skewness and surface to volume ratio decreased with radiation dose fraction delivery, while coarseness and 90th percentile values increased. Skewness had the largest relative median absolute changes (22%-45%) per fraction from baseline and was associated with locoregional failure (p=0.012) by analysis of covariance. Skewness, Elongation, and Flatness were significantly associated with local recurrence-free survival, while tumor diameter and volume were not. Conclusions: Our study establishes the feasibility and stability of delta radiomics analysis for MR-guided lung SBRT. Findings suggest that MR delta radiomics can capture short-term radiographic manifestations of intra-tumoral radiation effect.

Synthetic longitudinal brain MRI simulates brain aging and would enable more efficient research on neurodevelopmental and neurodegenerative conditions. Synthetically generated, age-adjusted brain images could serve as valuable alternatives to costly longitudinal imaging acquisitions, serve as internal controls for studies looking at the effects of environmental or therapeutic modifiers on brain development, and allow data augmentation for diverse populations. In this paper, we present a diffusion-based approach called SynthBrainGrow for synthetic brain aging with a two-year step. To validate the feasibility of using synthetically-generated data on downstream tasks, we compared structural volumetrics of two-year-aged brains against synthetically-aged brain MRI. Results show that SynthBrainGrow can accurately capture substructure volumetrics and simulate structural changes such as ventricle enlargement and cortical thinning. Our approach provides a novel way to generate longitudinal brain datasets from cross-sectional data to enable augmented training and benchmarking of computational tools for analyzing lifespan trajectories. This work signifies an important advance in generative modeling to synthesize realistic longitudinal data with limited lifelong MRI scans. The code is available at XXX., Comment: 8 pages, 4 figures

Abstract abridged. Eclipsing binary systems provide the opportunity to measure the fundamental parameters of their component stars in a stellar-model-independent way. This makes them ideal candidates for testing and calibrating theories of stellar structure and (tidal) evolution. Even without spectroscopic follow-up there is often enough information in their photometric time series to warrant analysis, especially if there is an added value present in the form of intrinsic variability, such as pulsations. Our goal is to implement and validate a framework for the homogeneous analysis of large numbers of eclipsing binary light curves, such as the numerous high-duty-cycle observations from space missions like TESS. The aim of this framework is to be quick and simple to run and to limit the user's time investment when obtaining, amongst other parameters, orbital eccentricities. We developed a new and fully automated methodology for the analysis of eclipsing binary light curves with or without additional intrinsic variability. Our method includes a fast iterative pre-whitening procedure. Orbital and stellar parameters are measured under the assumption of spherical stars of uniform brightness. We tested our methodology in two settings: a set of synthetic light curves with known input and the catalogue of Kepler eclipsing binaries. The synthetic tests show that we can reliably recover the frequencies and amplitudes of the sinusoids included in the signal as well as the input binary parameters. Recovery of the tangential component of eccentricity is the most accurate and precise. Kepler results confirm a robust determination of orbital periods, with 80.5% of periods matching the catalogued ones. We present the eccentricities for this analysis and show that they broadly follow the theoretically expected pattern as a function of the orbital period., Comment: 17 pages, 17 figures, 1 table, 5 appendices (43 additional figures, 1 additional table). Accepted for publication in A&A

The theory the rotational and chemical evolution is incomplete, thereby limiting the accuracy of model-dependent stellar mass and age determinations. The $\gamma$ Doradus pulsators are excellent points of calibration for the current state-of-the-art stellar evolution models, as their gravity modes probe the physical conditions in the deep stellar interior. Yet, individual asteroseismic modelling of these stars is not always possible because of insufficient observed oscillation modes. This paper presents a novel method to derive distributions of the stellar mass, age, core-boundary mixing efficiency and initial rotation rates for $\gamma$ Dor stars. We compute a grid of rotating stellar evolution models covering the entire $\gamma$ Dor instability strip. We then use the observed distributions of the luminosity, effective temperature, buoyancy travel time and near-core rotation frequency of a sample of 539 stars to assign a statistical weight to each of our models. This weight is a measure of how likely the combination of a specific model is. We then compute weighted histograms to derive the most likely distributions of the fundamental stellar properties. We find that the rotation frequency at zero-age main sequence follows a normal distribution, peaking around 25% of the critical Keplerian rotation frequency. The probability-density function for extent of the core-boundary mixing zone, given by a factor $f_{\rm CBM}$ times the local pressure scale height (assuming an exponentially decaying parameterisation) decreases linearly with increasing $f_{\rm CBM}$. Converting the distribution of fractions of critical rotation at the zero-age main sequence to units of d$^{-1}$, we find most F-type stars start the main sequence with a rotation frequency between 0.5 and 2 d$^{-1}$. Regarding the core-boundary mixing efficiency, we find that it is generally weak in this mass regime., Comment: Accepted for publication in Astronomy & Astrophysics. 7 pages

Galactic archaeology largely relies on precise ages of distant evolved stars in the Milky Way. Nowadays, asteroseismology can deliver ages for many red giants observed with high-cadence, high-precision photometric space missions. Our aim is to quantify age uncertainties of slowly-rotating red giants due to the cumulative effect of their fast rotation during core-hydrogen burning. Their rotation in earlier evolutionary phases caused mixing resulting in heavier helium cores and the prolongation of their main sequence. These rotational effects are usually ignored when age-dating red giants, despite our knowledge of fast rotation for stars with $M\ge1.3\,$M$_\odot$. We use a sample of 490 $\gamma$ Doradus pulsators with precise asteroseismic estimates of their internal rotation rate and with luminosity estimates from Gaia. For this sample, which includes stars rotating from nearly 0 to about 60% of the critical rate, we compute the cumulative effect on the age in their post-main sequence evolution caused by rotational mixing on the main sequence. We use stellar model grids with different physical prescriptions mimicking rotational mixing to assess systematic uncertainties on the age. With respect to non-rotating models, the sample of 490 stars, as red giant progenitors, reveals age differences up to 5% by the time they start hydrogen-shell burning when relying on the theory of rotationally induced diffusive mixing as included in the MIST isochrones. Using rotational mixing based on an advective-diffusive approach including meridional circulation leads to an age shift of 20% by the time of the TRGB. Age-dating of red giants is affected by the cumulative effect of rotational mixing during the main sequence. Such rotationally-induced age shifts should be taken into account in addition to other effects if the aim is to perform Galactic archaeological studies at the highest precision. (abridged), Comment: Accepted for publication in A&A, 10+3 pages, 8+2 figures

Background: Recent advancements in large language models (LLMs) offer potential benefits in healthcare, particularly in processing extensive patient records. However, existing benchmarks do not fully assess LLMs' capability in handling real-world, lengthy clinical data. Methods: We present the LongHealth benchmark, comprising 20 detailed fictional patient cases across various diseases, with each case containing 5,090 to 6,754 words. The benchmark challenges LLMs with 400 multiple-choice questions in three categories: information extraction, negation, and sorting, challenging LLMs to extract and interpret information from large clinical documents. Results: We evaluated nine open-source LLMs with a minimum of 16,000 tokens and also included OpenAI's proprietary and cost-efficient GPT-3.5 Turbo for comparison. The highest accuracy was observed for Mixtral-8x7B-Instruct-v0.1, particularly in tasks focused on information retrieval from single and multiple patient documents. However, all models struggled significantly in tasks requiring the identification of missing information, highlighting a critical area for improvement in clinical data interpretation. Conclusion: While LLMs show considerable potential for processing long clinical documents, their current accuracy levels are insufficient for reliable clinical use, especially in scenarios requiring the identification of missing information. The LongHealth benchmark provides a more realistic assessment of LLMs in a healthcare setting and highlights the need for further model refinement for safe and effective clinical application. We make the benchmark and evaluation code publicly available., Comment: 11 pages, 3 figures, 5 tables

Creativity is a critical skill that professional software engineers leverage to tackle difficult problems. In higher education, multiple efforts have been made to spark creative skills of engineering students. However, creativity is a vague concept that is open to interpretation. Furthermore, studies have shown that there is a gap in perception and implementation of creativity between industry and academia. To better understand the role of creativity in software engineering (SE), we interviewed 33 professionals via four focus groups and 10 SE students. Our results reveal 45 underlying topics related to creativity. When comparing the perception of students versus professionals, we discovered fundamental differences, grouped into five themes: the creative environment, application of techniques, creative collaboration, nature vs nurture, and the perceived value of creativity. As our aim is to use these findings to install and further encourage creative problem solving in higher education, we have included a list of implications for educational practice.

Asteroseismic modelling of isolated star presents significant challenges due to the difficulty in accurately determining stellar parameters, particularly the stellar age. These challenges can be overcomed by observing stars in open clusters, whose coeval members share an initial chemical composition. The light curves by TESS allow us to investigate and analyse stellar variations in clusters with an unprecedented level. We aim to detect gravity-mode oscillations in the early-type main-sequence members of the young open cluster NGC 2516. We selected the 301 member stars as our sample and analysed the TESS FFI light curves. We also collected high-resolution spectra using the FEROS for the g-mode pulsators. By fitting the theoretical isochrones to the colour-magnitude diagram (CMD) of a cluster, we determined an age of 102 $\pm$ 15 Myr and inferred the extinction at 550 nm ($A_0$) is 0.53 $\pm$ 0.04 mag. We identified 147 stars with surface brightness modulations, 24 with g-mode pulsations ($\gamma$ Doradus or Slowly Pulsating B stars), and 35 with p-mode pulsations ($\delta$ Sct stars). When sorted by colour index, the amplitude spectra of the $\delta$ Sct stars show a distinct ordering and reveal a discernible frequency-temperature relationship. The near-core rotation rates, measured from period spacing patterns in two SPB and nine $\gamma$ Dor stars, reach up to 3/d . This is at the high end of the values found from Kepler data of field stars of similar variability type. The $\gamma$ Dor stars have internal rotation rates as high as 50% of their critical value, whereas the SPB stars exhibit rotation rates close to their critical rate. We did not find long-term brightness and colour variations in the mid-infrared, which suggests that there are no disk or shell formation events in our sample. We also discussed the results of our spectroscopic observations for the g-mode pulsators., Comment: Accepted to be published by A&A. 15 figures and 3 tables in the main paper, 51 figures and 1 table in the appendix

Clustering algorithms are often used to find subpopulations in exploratory data analysis workflows. Not only the clusters themselves, but also their shape can represent meaningful subpopulations. In this paper, we present FLASC, an algorithm that detects branches within clusters to identify such subpopulations. FLASC builds upon HDBSCAN*, a state-of-the-art density-based clustering algorithm, and detects branches in a post-processing step that describes within-cluster connectivity. Two variants of the algorithm are presented, which trade computational cost for noise robustness. We show that both variants scale similarly to HDBSCAN* in terms of computational cost and provide stable outputs using synthetic data sets, resulting in an efficient flare-sensitive clustering algorithm. In addition, we demonstrate the benefit of branch-detection on two real-world data sets., Comment: Previously, 20 pages, 11 figures, submitted to ACM TKDD. Now, 15 pages, 8 figures, submitted to PeerJ Computer Science (simplified method and rewritten for clarity)

Rotation matters for the life of a star. It causes a multitude of dynamical phenomena in the stellar interior during a star's evolution and its effects accumulate until the star dies. All stars rotate at some level but those born with a mass above about 1.3 times the mass of the Sun rotate rapidly during more than 90% of their nuclear lifetime. Internal rotation guides the angular momentum and chemical element transport throughout the stellar interior. These transport processes change over time as the star evolves. The cumulative effects of stellar rotation and its induced transport processes determine the helium content of the core by the time it exhausts its hydrogen isotopes. The amount of helium at that stage also guides the heavy element yields by the end of the star's life. A proper theory of stellar evolution and any realistic models for the chemical enrichment of galaxies, must be based on observational calibrations of stellar rotation and of the induced transport processes. Since a few years, asteroseismology offers such calibrations, for single and binary stars. We review the current status of asteroseismic modelling of rotating stars for different stellar mass regimes, in an accessible way for the non-expert. While doing so, we describe exciting opportunities sparked by asteroseismology for various domains in astrophysics, touching upon topics from exoplanetary science to galactic structure and evolution towards gravitational wave physics. Along the way, we provide ample sneak-previews for future 'industrialised' applications of asteroseismology to slow and rapid rotators, from exploitation of combined Kepler, TESS, PLATO, Gaia, and spectroscopy surveys. We end the review with a list of take away messages and achievements of asteroseismology, which are of relevance for many fields of astrophysics., Comment: Invited review paper to appear in Astronomy \& Astrophysics (37 pages, 11 figures). This is the accepted and language edited version