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AU Mic is a very active M dwarf with an edge-on debris disk and two transiting sub-Neptunes with a possible third planetary companion. The two transiting planets exhibit significant transit-timing variations (TTVs) that are caused by the gravitational interaction between the bodies in the system. Using photometrical observations taken with the CHaracterizing ExOPlanet Satellite (CHEOPS), our goal is to constrain the planetary radii, the orbital distances and periods of AU Mic b and c. We aim to determine the superperiod of the TTVs for AU Mic b and to update the transit ephemeris for both planets. Based on the observed TTVs, we study the possible presence of a third planet in the system. We conducted high precision photometric observations with CHEOPS in 2022 and 2023. We used Allesfitter to fit the planetary transits and to constrain the planetary and orbital parameters. We combined our new measurements with results from previous years to determine the periods and amplitudes of the TTVs. We applied dynamical modelling based on TTV measurements from the 2018-2023 period to reconstruct the perceived variations. The orbital distances and periods for AU Mic b and c agree with the results from previous works. However, the values for the planetary radii deviate slightly from previous values, which we attribute to the effect of stellar spots. AU Mic c showed very strong TTVs, with transits that occurred ~80 minutes later in 2023 than in 2021. Through dynamical analysis of the system, we found that the observed TTVs can be explained by a third planet with an orbital period of ~12.6 days and a mass of 0.203+0.022-0.024 M_E. We explored the orbital geometry of the system and found that AU Mic c has a misaligned retrograde orbit. Due limited number of observations the exact configuration and planetary parameters could not be determined. Further monitoring with CHEOPS may improve these results., Comment: 15 pages, 10 figures

The CHaracterising ExOPlanet Satellite (CHEOPS) is a partnership between the European Space Agency and Switzerland with important contributions by 10 additional ESA member States. It is the first S-class mission in the ESA Science Programme. CHEOPS has been flying on a Sun-synchronous low Earth orbit since December 2019, collecting millions of short-exposure images in the visible domain to study exoplanet properties. A small yet increasing fraction of CHEOPS images show linear trails caused by resident space objects crossing the instrument field of view. To characterize the population of satellites and orbital debris observed by CHEOPS, all and every science images acquired over the past 3 years have been scanned with a Hough transform algorithm to identify the characteristic linear features that these objects cause on the images. Thousands of trails have been detected. This statistically significant sample shows interesting trends and features such as an increased occurrence rate over the past years as well as the fingerprint of the Starlink constellation. The cross-matching of individual trails with catalogued objects is underway as we aim to measure their distance at the time of observation and deduce the apparent magnitude of the detected objects. As space agencies and private companies are developing new space-based surveillance and tracking activities to catalogue and characterize the distribution of small debris, the CHEOPS experience is timely and relevant. With the first CHEOPS mission extension currently running until the end of 2026, and a possible second extension until the end of 2029, the longer time coverage will make our dataset even more valuable to the community, especially for characterizing objects with recurrent crossings., Comment: 9 pages, 8 figures, Special Issue of the Journal of Space Safety Engineering

Li-ion battery performance is strongly influenced by their cathodes' properties and consequently by the 3D microstructure of the particles the cathodes are comprised of. During calendaring and cycling, cracks develop within cathode particles, which may affect performance in multiple ways. On the one hand, cracks reduce internal connectivity such that electron transport within cathode particles is hindered. On the other hand, intra-particle cracks can increase the cathode reactive surface. Due to these contradictory effects, it is necessary to quantitatively investigate how battery cycling effects cracking and how cracking in-turn influences battery performance. Thus, it is necessary to characterize the 3D particle morphology with structural descriptors and quantitatively correlate them with effective battery properties. Typically, 3D structural characterization is performed using image data. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles that exhibit crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, more easily available 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. In future research, the virtually generated 3D particles will be used as geometry input for spatially resolved electro-chemo-mechanical simulations, to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.

The rapid development of automated vehicles (AVs) promises to revolutionize transportation by enhancing safety and efficiency. However, ensuring their reliability in diverse real-world conditions remains a significant challenge, particularly due to rare and unexpected situations known as edge cases. Although numerous approaches exist for detecting edge cases, there is a notable lack of a comprehensive survey that systematically reviews these techniques. This paper fills this gap by presenting a practical, hierarchical review and systematic classification of edge case detection and assessment methodologies. Our classification is structured on two levels: first, categorizing detection approaches according to AV modules, including perception-related and trajectory-related edge cases; and second, based on underlying methodologies and theories guiding these techniques. We extend this taxonomy by introducing a new class called "knowledge-driven" approaches, which is largely overlooked in the literature. Additionally, we review the techniques and metrics for the evaluation of edge case detection methods and identified edge cases. To our knowledge, this is the first survey to comprehensively cover edge case detection methods across all AV subsystems, discuss knowledge-driven edge cases, and explore evaluation techniques for detection methods. This structured and multi-faceted analysis aims to facilitate targeted research and modular testing of AVs. Moreover, by identifying the strengths and weaknesses of various approaches and discussing the challenges and future directions, this survey intends to assist AV developers, researchers, and policymakers in enhancing the safety and reliability of automated driving (AD) systems through effective edge case detection., Comment: Preprint submitted to IEEE Transactions on Intelligent Transportation Systems

We study the evolution of populations of binary stars within massive cluster-forming regions. We simulate the formation of young massive star clusters within giant molecular clouds with masses ranging from 2 x 10$^{4}$ to 3.2 x 10$^{5}$ M$_{\odot}$. We use Torch, which couples stellar dynamics, magnetohydrodynamics, star and binary formation, stellar evolution, and stellar feedback through the AMUSE framework. We find that the binary fraction decreases during cluster formation at all molecular cloud masses. The binaries' orbital properties also change, with stronger and quicker changes in denser, more massive clouds. Most of the changes we see can be attributed to the disruption of binaries wider than 100 au, although the close binary fraction also decreases in the densest cluster-forming region. The binary fraction for O stars remains above 90%, but exchanges and dynamical hardening are ubiquitous, indicating that O stars undergo frequent few-body interactions early during the cluster formation process. Changes to the populations of binaries are a by-product of hierarchical cluster assembly: most changes to the binary population take place when the star formation rate is high and there are frequent mergers between sub-clusters in the cluster-forming region. A universal primordial binary distribution based on observed inner companions in the Galactic field is consistent with the binary populations of young clusters with resolved stellar populations, and the scatter between clusters of similar masses could be explained by differences in their formation history., Comment: 16 pages, 7+1 figures, 3 tables. Accepted for publication in ApJ

Massive stars are predominantly born in stellar associations or clusters. Their radiation fields, stellar winds, and supernovae strongly impact their local environment. In the first few million years of a cluster's life, massive stars are dynamically ejected running away from the cluster at high speed. However, the production rate of dynamically ejected runaways is poorly constrained. Here we report on a sample of 55 massive runaway stars ejected from the young cluster R136 in the Large Magellanic Cloud. Astrometric analysis with Gaia reveals two channels of dynamically ejected runaways. The first channel ejects massive stars in all directions and is consistent with dynamical interactions during and after the birth of R136. The second channel launches stars in a preferred direction and may be related to a cluster interaction. We find that 23-33% of the most luminous stars initially born in R136 are runaways. Model predictions have significantly underestimated the dynamical escape fraction of massive stars. Consequently, their role in shaping and heating the interstellar and galactic medium, along with their role in driving galactic outflows, is far more important than previously thought., Comment: Published in Nature on 2024 October 09. 39 pages, 17 figures

Since neural networks can make wrong predictions even with high confidence, monitoring their behavior at runtime is important, especially in safety-critical domains like autonomous driving. In this paper, we combine ideas from previous monitoring approaches based on observing the activation values of hidden neurons. In particular, we combine the Gaussian-based approach, which observes whether the current value of each monitored neuron is similar to typical values observed during training, and the Outside-the-Box monitor, which creates clusters of the acceptable activation values, and, thus, considers the correlations of the neurons' values. Our experiments evaluate the achieved improvement.

The Programmable Liquid-crystal Active Coronagraphic Imager for the DAG telescope (PLACID) instrument is a novel high-contrast direct imaging facility that was recently delivered to the Turkish 4-m DAG telescope, with first light anticipated by the end of 2024. In a nutshell, PLACID consists in a fore-optics coronagraphic intermediate stage platform, installed in-between the TROIA XAO system and the DIRAC HAWAII-1RG focal-plane array. The PLACID project, led by a consortium of Swiss Universities contracted by the Atat\"urk University Astrophysics Research and Application Center (ATASAM), has passed the Delivery Readiness Review (DRR) milestone in September 2023, and was delivered to ATASAM campus facilities in March 2024. The PLACID commissioning activities with the calibration light source at the summit, on the DAG telescope Nasmyth platform, are foreseen to take place this fall, with first light scheduled to take place before the end of the year. When on-sky, PLACID will be the world's first ''active coronagraph'' facility, fielding a customized spatial light modulator (SLM) acting as a dynamically programmable focal-plane phase mask (FPM) coronagraph from H- to Ks-band. This will provide a wealth of novel options to observers, among which software-only abilities to change or re-align the FPM pattern in function of conditions or science requirements, free of any actuator motion. Future features will include non-common path aberrations (NCPA) self-calibration, optimized coronagraphy for binary stars, as well as coherent differential imaging (CDI). We hereby present the delivered PLACID instrument, its current capabilities, and Factory Acceptance commissioning results with relevant performance metrics., Comment: 10 pages, 9 figures, SPIE Astronomical Telescopes + Instrumentation: Ground-based and Airborne Instrumentation for Astronomy X (Yokohama 2024), Paper 130961M

We report the spectroscopic confirmation and fundamental properties of TOI-757 b, a mini-Neptune on a 17.5-day orbit transiting a bright star ($V = 9.7$ mag) discovered by the TESS mission. We acquired high-precision radial velocity measurements with the HARPS, ESPRESSO, and PFS spectrographs to confirm the planet detection and determine its mass. We also acquired space-borne transit photometry with the CHEOPS space telescope to place stronger constraints on the planet radius, supported with ground-based LCOGT photometry. WASP and KELT photometry were used to help constrain the stellar rotation period. We also determined the fundamental parameters of the host star. We find that TOI-757 b has a radius of $R_{\mathrm{p}} = 2.5 \pm 0.1 R_{\oplus}$ and a mass of $M_{\mathrm{p}} = 10.5^{+2.2}_{-2.1} M_{\oplus}$, implying a bulk density of $\rho_{\text{p}} = 3.6 \pm 0.8$ g cm$^{-3}$. Our internal composition modeling was unable to constrain the composition of TOI-757 b, highlighting the importance of atmospheric observations for the system. We also find the planet to be highly eccentric with $e$ = 0.39$^{+0.08}_{-0.07}$, making it one of the very few highly eccentric planets among precisely characterized mini-Neptunes. Based on comparisons to other similar eccentric systems, we find a likely scenario for TOI-757 b's formation to be high eccentricity migration due to a distant outer companion. We additionally propose the possibility of a more intrinsic explanation for the high eccentricity due to star-star interactions during the earlier epoch of the Galactic disk formation, given the low metallicity and older age of TOI-757., Comment: Accepted for publication in MNRAS; 26 pages, 14 figures, 6 tables

We present a wavenumber-explicit analysis of FEM-BEM coupling methods for time-harmonic Helmholtz problems proposed in arXiv:2004.03523 for conforming discretizations and in arXiv:2105.06173 for discontinuous Galerkin (DG) volume discretizations. We show that the conditions that $kh/p$ be sufficiently small and that $\log(k) / p$ be bounded imply quasi-optimality of both conforming and DG-method, where $k$ is the wavenumber, $h$ the mesh size, and $p$ the approximation order. The analysis relies on a $k$-explicit regularity theory for a three-field coupling formulation.

We propose a hierarchical training algorithm for standard feed-forward neural networks that adaptively extends the network architecture as soon as the optimization reaches a stationary point. By solving small (low-dimensional) optimization problems, the extended network provably escapes any local minimum or stationary point. Under some assumptions on the approximability of the data with stable neural networks, we show that the algorithm achieves an optimal convergence rate s in the sense that loss is bounded by the number of parameters to the -s. As a byproduct, we obtain computable indicators which judge the optimality of the training state of a given network and derive a new notion of generalization error.

Mobile Health (mHealth) applications have become a crucial part of health monitoring and management. However, the proliferation of these applications has also raised concerns over the privacy and security of Personally Identifiable Information and Protected Health Information. Addressing these concerns, this paper introduces a novel framework for the qualitative evaluation of privacy practices in mHealth apps, particularly focusing on the handling and transmission of sensitive user data. Our investigation encompasses an analysis of 152 leading mHealth apps on the Android platform, leveraging the proposed framework to provide a multifaceted view of their data processing activities. Despite stringent regulations like the General Data Protection Regulation in the European Union and the Health Insurance Portability and Accountability Act in the United States, our findings indicate persistent issues with negligence and misuse of sensitive user information. We uncover significant instances of health information leakage to third-party trackers and a widespread neglect of privacy-by-design and transparency principles. Our research underscores the critical need for stricter enforcement of data protection laws and sets a foundation for future efforts aimed at enhancing user privacy within the mHealth ecosystem., Comment: 8 pages, 6 figures, accepted at the 2024 International Workshop on Privacy Engineering (IWPE'24)

The behavior of neural networks (NNs) on previously unseen types of data (out-of-distribution or OOD) is typically unpredictable. This can be dangerous if the network's output is used for decision-making in a safety-critical system. Hence, detecting that an input is OOD is crucial for the safe application of the NN. Verification approaches do not scale to practical NNs, making runtime monitoring more appealing for practical use. While various monitors have been suggested recently, their optimization for a given problem, as well as comparison with each other and reproduction of results, remain challenging. We present a tool for users and developers of NN monitors. It allows for (i) application of various types of monitors from the literature to a given input NN, (ii) optimization of the monitor's hyperparameters, and (iii) experimental evaluation and comparison to other approaches. Besides, it facilitates the development of new monitoring approaches. We demonstrate the tool's usability on several use cases of different types of users as well as on a case study comparing different approaches from recent literature., Comment: accepted at CAV 2024

The TOI-421 planetary system contains two sub-Neptune-type planets and is a prime target to study the formation and evolution of planets and their atmospheres. The inner planet is especially interesting as the existence of a hydrogen-dominated atmosphere at its orbital separation cannot be explained by current formation models without previous orbital migration. We jointly analysed photometric data of three TESS sectors and six CHEOPS visits as well as 156 radial velocity data points to retrieve improved planetary parameters. We also searched for TTVs and modelled the interior structure of the planets. Finally, we simulated the evolution of the primordial H-He atmospheres of the planets using two different modelling frameworks. We determine the planetary radii and masses of TOI-421 b and c to be $R_{\rm b} = 2.64 \pm 0.08 \, R_{\oplus}$, $M_{\rm b} = 6.7 \pm 0.6 \, M_{\oplus}$, $R_{\rm c} = 5.09 \pm 0.07 \, R_{\oplus}$, and $M_{\rm c} = 14.1 \pm 1.4 \, M_{\oplus}$. We do not detect any statistically significant TTV signals. Assuming the presence of a hydrogen-dominated atmosphere, the interior structure modelling results in both planets having extensive envelopes. While the modelling of the atmospheric evolution predicts for TOI-421 b to have lost any primordial atmosphere that it could have accreted at its current orbital position, TOI-421 c could have started out with an initial atmospheric mass fraction somewhere between 10 and 35%. We conclude that the low observed mean density of TOI-421 b can only be explained by either a bias in the measured planetary parameters (e.g. driven by high-altitude clouds) and/or in the context of orbital migration. We also find that the results of atmospheric evolution models are strongly dependent on the employed planetary structure model., Comment: 21 pages, 12 figures, accepted for publication in A&A

We consider a novel way of discretizing wave scattering problems using the general formalism of convolution quadrature, but instead of reducing the timestep size ($h$-method), we achieve accuracy by increasing the order of the method ($p$-method). We base this method on discontinuous Galerkin timestepping and use the Z-transform. We show that for a certain class of incident waves, the resulting schemes observes(root)-exponential convergence rate with respect to the number of boundary integral operators that need to be applied. Numerical experiments confirm the findings.

We investigate the influence of crystallographic twins on the elastoplastic response of $\gamma$-TiAl intermetallics via full-field FFT-based computations. We first introduce a hierarchical stochastic model, which is used to simulate synthetic polycrystalline microstructures containing twin grains with certain morphologies, and apply it to generate representative volume elements. Second, we develop a Fourier-based method with regularization for solving the effective and local mechanical response of polycrystalline media using the M\'eric-Cailletaud crystal plasticity constitutive law. Numerical results show that, across configurations of twinning, the corresponding average effective response is similar. Although differences were quantified, the effect of twins on the yield stress is negligible in practice (less than $1\%$).

The World Wide Web's connectivity is greatly attributed to the HTTP protocol, with HTTP messages offering informative header fields that appeal to disciplines like web security and privacy, especially concerning web tracking. Despite existing research employing HTTP request messages to identify web trackers, HTTP response headers are often overlooked. This study endeavors to design effective machine learning classifiers for web tracker detection using binarized HTTP response headers. Data from the Chrome, Firefox, and Brave browsers, obtained through the traffic monitoring browser extension T.EX, serves as our dataset. Ten supervised models were trained on Chrome data and tested across all browsers, including a Chrome dataset from a year later. The results demonstrated high accuracy, F1-score, precision, recall, and minimal log-loss error for Chrome and Firefox, but subpar performance on Brave, potentially due to its distinct data distribution and feature set. The research suggests that these classifiers are viable for web tracker detection. However, real-world application testing remains pending, and the distinction between tracker types and broader label sources could be explored in future studies.

A stochastic 3D microstructure model for polycrystals is introduced which incorporates two types of twin grains, namely neighboring and inclusion twins. They mimic the presence of crystal twins in $\gamma$-TiAl polycrystalline microstructures as observed by 3D imaging techniques. The polycrystal grain morphology is modeled by means of Voronoi and -- more generally -- Laguerre tessellations. The crystallographic orientation of each grain is either sampled uniformly on the space of orientations or chosen to be in a twinning relation with another grain. The model is used to quantitatively study relationships between morphology and mechanical properties of polycrystalline materials. For this purpose, full-field Fourier-based computations are performed to investigate the combined effect of grain morphology and twinning on the overall elastic response. For $\gamma$-TiAl polycrystallines, the presence of twins is associated with a softer response compared to polycrystalline aggregates without twins. However, when comparing the influence on the elastic response, a statistically different polycrystalline morphology has a much smaller effect than the presence of twin grains. Notably, the bulk modulus is almost insensitive to the grain morphology and exhibits much less sensitivity to the presence of twins compared to the shear modulus. The numerical results are consistent with a two-scale homogenization estimate that utilizes laminate materials to model the interactions of twins.

Observations of clusters suffer from issues such as completeness, projection effects, resolving individual stars and extinction. As such, how accurate are measurements and conclusions are likely to be? Here, we take cluster simulations (Westerlund2- and Orion- type), synthetically observe them to obtain luminosities, accounting for extinction and the inherent limits of Gaia, then place them within the real Gaia DR3 catalogue. We then attempt to rediscover the clusters at distances of between 500pc and 4300pc. We show the spatial and kinematic criteria which are best able to pick out the simulated clusters, maximising completeness and minimising contamination. We then compare the properties of the 'observed' clusters with the original simulations. We looked at the degree of clustering, the identification of clusters and subclusters within the datasets, and whether the clusters are expanding or contracting. Even with a high level of incompleteness (e.g. $<2\%$ stellar members identified), similar qualitative conclusions tend to be reached compared to the original dataset, but most quantitative conclusions are likely to be inaccurate. Accurate determination of the number, stellar membership and kinematic properties of subclusters, are the most problematic to correctly determine, particularly at larger distances due to the disappearance of cluster substructure as the data become more incomplete, but also at smaller distances where the misidentification of asterisms as true structure can be problematic. Unsurprisingly, we tend to obtain better quantitative agreement of properties for our more massive Westerlund2-type cluster. We also make optical style images of the clusters over our range of distances., Comment: 19 pages, 10 figures, 6 tables. Accepted for publication in MNRAS

Multiwavelength photometry of the secondary eclipses of extrasolar planets is able to disentangle the reflected and thermally emitted light radiated from the planetary dayside. This leads to the measurement of the planetary geometric albedo $A_g$, which is an indicator of the presence of clouds in the atmosphere, and the recirculation efficiency $\epsilon$, which quantifies the energy transport within the atmosphere. In this work we aim to measure $A_g$ and $\epsilon$ for the planet WASP-178 b, a highly irradiated giant planet with an estimated equilibrium temperature of 2450 K.} We analyzed archival spectra and the light curves collected by Cheops and Tess to characterize the host WASP-178, refine the ephemeris of the system and measure the eclipse depth in the passbands of the two respective telescopes. We measured a marginally significant eclipse depth of 70$\pm$40 ppm in the Tess passband and statistically significant depth of 70$\pm$20 ppm in the Cheops passband. Combining the eclipse depth measurement in the Cheops (lambda_eff=6300 AA) and Tess (lambda_eff=8000 AA) passbands we constrained the dayside brightness temperature of WASP-178 b in the 2250-2800 K interval. The geometric albedo 0.1<$\rm A_g$<0.35 is in general agreement with the picture of poorly reflective giant planets, while the recirculation efficiency $\epsilon>$0.7 makes WASP-178 b an interesting laboratory to test the current heat recirculation models., Comment: Accepted by Astronomy and Astrophysics on 31/08/2023