Search

Sulphur-bearing species play crucial roles in interstellar chemistry, yet their precise characterisation remains challenging. Here, we present laboratory experiments aimed at extending the high-resolution spectroscopy of protonated carbonyl sulphide (HOCS$^+$), a recently detected molecular ion in space. Using a frequency-modulated free-space absorption spectrometer, we detected rotational transitions of HOCS$^+$ in an extended negative glow discharge with a mixture of H$_2$ and OCS, extending the high-resolution rotational characterisation of the cation well into the millimetre wave region (200-370 GHz). Comparisons with prior measurements and quantum chemical calculations revealed an overall agreement in the spectroscopic parameters. With the new spectroscopic dataset in hand, we re-investigated the observations of HOCS$^+$ towards G+0.693-0.027, which were initially based solely on K$_a$ = 0 lines contaminated by HNC$^{34}$S. This re-investigation enabled the detection of weak K$_a$ = 0 transitions, free from HNC$^{34}$S contamination. Our high-resolution spectroscopic characterisation also provides valuable insights for future millimetre and submillimetre astronomical observations of these species in different interstellar environments. In particular, the new high-resolution catalogue will facilitate the search for this cation in cold dark clouds, where very narrow line widths are typically observed., Comment: 9 pages, 3 figures, and 3 tables. Accepted for publication in Astronomy & Astrophysics

In this work, we determine the dissociation line of the nitrogen (N$_{2}$) hydrate by computer simulation using the TIP4P/Ice model for water and the TraPPE force field for N$_{2}$. This work is the natural extension of our previous paper in which the dissociation temperature of the N$_2$ hydrate has been obtained at $500$, $1000$, and $1500\,\text{bar}$ [\emph{J. Chem. Phys.} \textbf{159}, 224707 (2023)] using the solubility method and assuming single occupancy. We extend our previous study and determine the dissociation temperature of the N$_2$ hydrate at different pressures, from $500$ to $4500\,\text{bar}$, taking into account single and double occupancy of the N$_{2}$ molecules in the hydrate structure. We calculate the solubility of N$_2$ in the aqueous solution, as a function of temperature, when it is in contact with a N$_{2}$-rich liquid phase and when in contact with the hydrate phase with single and double occupancy via planar interfaces. Both curves intersect at a certain temperature that determines the dissociation temperature at a given pressure. We observe a negligible effect of the occupancy on the dissociation temperature. Our findings are in very good agreement with the experimental data taken from the literature. We have also obtained the driving force for nucleation of the hydrate as a function of the temperature and occupancy at several pressures. As in the case of the dissociation line, the effect of the occupancy on the driving force for nucleation is negligible. To the best of our knowledge, this is the first time that the effect of the occupancy on the driving force for nucleation of a hydrate that exhibits sII crystallographic structure is studied from computer simulation., Comment: 15 pages, 13 figures

The advances of machine-learned force fields have opened up molecular dynamics (MD) simulations for compounds for which ab-initio MD is too resource-intensive and phenomena for which classical force fields are insufficient. Here we describe a neural-network force field parametrized to reproduce the r2SCAN potential energy landscape of HfO$_2$. Based on an automatic differentiable implementation of the isothermal-isobaric (NPT) ensemble with flexible cell fluctuations, we study the phase space of HfO$_2$. We find excellent predictive capabilities regarding the lattice constants and experimental X-ray diffraction data. The phase transition away from monoclinic is clearly visible at a temperature around 2000 K, in agreement with available experimental data and previous calculations. Another abrupt change in lattice constants occurs around 3000 K. While the resulting lattice constants are closer to cubic, they exhibit a small tetragonal distortion, and there is no associated change in volume. We show that this high-temperature structure is in agreement with the available high-temperature diffraction data.

Python, one of the most prevalent programming languages today, is widely utilized in various domains, including web development, data science, machine learning, and DevOps. Recent scholarly efforts have proposed a methodology to assess Python competence levels, similar to how proficiency in natural languages is evaluated. This method involves assigning levels of competence to Python constructs, for instance, placing simple 'print' statements at the most basic level and abstract base classes at the most advanced. The aim is to gauge the level of proficiency a developer must have to understand a piece of source code. This is particularly crucial for software maintenance and evolution tasks, such as debugging or adding new features. For example, in a code review process, this method could determine the competence level required for reviewers. However, categorizing Python constructs by proficiency levels poses significant challenges. Prior attempts, which relied heavily on expert opinions and developer surveys, have led to considerable discrepancies. In response, this paper presents a new approach to identifying Python competency levels through the systematic analysis of introductory Python programming textbooks. By comparing the sequence in which Python constructs are introduced in these textbooks with the current state of the art, we have uncovered notable discrepancies in the order of introduction of Python constructs. Our study underscores a misalignment in the sequences, demonstrating that pinpointing proficiency levels is not trivial. Insights from the study serve as pivotal steps toward reinforcing the idea that textbooks serve as a valuable source for evaluating developers' proficiency, and particularly in terms of their ability to undertake maintenance and evolution tasks., Comment: 12 pages, 7 figures, 6 tables, ICSME2024

We present a catalog of stellar parameters (effective temperature $T_{\rm eff}$, surface gravity $\log g$, age, and metallicity [Fe/H]) and elemental-abundance ratios ([C/Fe], [Mg/Fe], and [$\alpha$/Fe]) for some five million stars (4.5 million dwarfs and 0.5 million giants stars) in the Milky Way, based on stellar colors from the Javalambre Photometric Local Universe Survey (J-PLUS) DR3 and \textit{Gaia} EDR3. These estimates are obtained through the construction of a large spectroscopic training set with parameters and abundances adjusted to uniform scales, and trained with a Kernel Principal Component Analysis. Owing to the seven narrow/medium-band filters employed by J-PLUS, we obtain precisions in the abundance estimates that are as good or better than derived from medium-resolution spectroscopy for stars covering a wide range of the parameter space: 0.10-0.20 dex for [Fe/H] and [C/Fe], and 0.05 dex for [Mg/Fe] and [$\alpha$/Fe]. Moreover, systematic errors due to the influence of molecular carbon bands on previous photometric-metallicity estimates (which only included two narrow/medium-band blue filters) have now been removed, resulting in photometric-metallicity estimates down to [Fe/H] $\sim -4.0$, with typical uncertainties of 0.25 dex and 0.40 dex for dwarfs and giants, respectively. This large photometric sample should prove useful for the exploration of the assembly and chemical-evolution history of our Galaxy., Comment: 31 pages, 20 figures, 3 tables, accepeted by ApJ

A tethered marsupial robotics system comprises three components: an Unmanned Ground Vehicle (UGV), an Unmanned Aerial Vehicle (UAV), and a tether connecting both robots. Marsupial systems are highly beneficial in industry as they extend the UAV's battery life during flight. This paper introduces a novel strategy for a specific path planning problem in marsupial systems, where each of the three components must avoid collisions with ground and aerial obstacles modeled as 3D cuboids. Given an initial configuration in which the UAV is positioned atop the UGV, the goal is to reach an aerial target with the UAV. We assume that the UGV first moves to a position from which the UAV can take off and fly through a vertical plane to reach an aerial target. We propose an approach that discretizes the space to approximate an optimal solution, minimizing the sum of the lengths of the ground and air paths. First, we assume a taut tether and use a novel algorithm that leverages the convexity of the tether and the geometry of obstacles to efficiently determine the locus of feasible take-off points for the UAV. We then apply this result to scenarios that involve loose tethers. The simulation test results show that our approach can solve complex situations in seconds, outperforming a baseline planning algorithm based on RRT* (Rapidly exploring Random Trees)., Comment: 26 pages, 9 figures, 3 tables

A strong increase of the reflection loss (from 25 up to 35 dBs) and an extension of the absorption bandwidth up to 20% under far-field real radar conditions are experimentally reported in this work by creating a functional bilayer system. Each layer consists of a composite material, typically a dielectric matrix filled with magnetic entities (powder or wires). Combining the two types of materials into a bilayer structure has shown unprecedented improvements in microwave absorption capacities compared to the former absorption of each layer. The potential of random magnets to create thin broadband absorbers is also demonstrated. The capacity to improve the shielding behavior is strongly related to each layer's permittivity, permeability, and thickness. This provides strong control over the design of novel materials for stealth applications.

This work shows a procedural method for extracting object heights from LiDAR and aerial imagery. We discuss how to get heights and the future of LiDAR and imagery processing. SOTA object segmentation allows us to take get object heights with no deep learning background. Engineers will be keeping track of world data across generations and reprocessing them. They will be using older procedural methods like this paper and newer ones discussed here. SOTA methods are going beyond analysis and into generative AI. We cover both a procedural methodology and the newer ones performed with language models. These include point cloud, imagery and text encoding allowing for spatially aware AI.

We developed SaludConectaMX as a comprehensive system to track and understand the determinants of complications throughout chemotherapy treatment for children with cancer in Mexico. SaludConectaMX is unique in that it integrates patient clinical indicators with social determinants and caregiver mental health, forming a social-clinical perspective of the patient's evolving health trajectory. The system is composed of a web application (for hospital staff) and a mobile application (for family caregivers), providing the opportunity for cooperative patient monitoring in both hospital and home settings. This paper presents the system's preliminary design and usability evaluation results from a 1.5-year pilot study. Our findings indicate that while the hospital web app demonstrates high completion rates and user satisfaction, the family mobile app requires additional improvements for optimal accessibility; statistical and qualitative data analysis illuminate pathways for system improvement. Based on this evidence, we formalize suggestions for health system development in LMICs, which HCI researchers may leverage in future work.

The Universe is shaped as a web-like structure, formed by clusters, filaments, and walls that leave large volumes in between named voids. Galaxies in voids have been found to be of a later type, bluer, less massive, and to have a slower evolution than galaxies in denser environments (filaments and walls). However, the effect of the void environment on their stellar population properties is still unclear. We aim to address this question using 118 optical integral field unit datacubes from the Calar Alto Void Integral-field Treasury surveY (CAVITY), observed with the PMAS/PPaK spectrograph at the 3.5m telescope at the Calar Alto Observatory (Almer\'ia, Spain). We used the non-parametric full spectral fitting code STARLIGHT to estimate their stellar population properties: stellar mass, stellar mass surface density, age, star formation rate (SFR), and specific star formation rate (sSFR). We analysed the results through the global and spatially resolved properties. Then, we compared them with a control sample of galaxies in filaments and walls from the CALIFA survey, matched in stellar mass and morphological type. Key findings include void galaxies having a slightly higher half-light radius (HLR), lower stellar mass surface density, and younger ages across all morphological types, and slightly elevated SFR and sSFR (only significant enough for Sas). Many of these differences appear in the outer parts of spiral galaxies in voids (HLR > 1), which are younger and exhibit a higher sSFR, indicative of less evolved discs. This trend is also found for early-type spirals, suggesting a slower transition from star-forming to quiescent states in voids. Our analysis indicates that void galaxies, influenced by their surroundings, undergo a more gradual evolution, especially in their outer regions, with a more pronounced effect for low-mass galaxies., Comment: 24 pages, 22 figures, 5 tables. Accepted for publication in A&A. Updated references list

Ultraviolet (UV) processing in the insterstellar medium (ISM) induces the dehydrogenation of hydrocarbons. Aliphatics, including alkanes, are present in different interstellar environments, being prevalently formed in evolved stars; thus, the dehydrogenation by UV photoprocessing of alkanes plays an important role in the chemistry of the ISM, leading to the formation of unsaturated hydrocarbons and eventually to aromatics, the latter ubiquitously detected in the ISM. Here, through combined experimental results and \textit{ab-initio} calculations, we show that UV absorption (mainly at the Ly-$\alpha$ emission line of hydrogen at 121.6 nm) promotes an alkane to an excited Rydberg state from where it evolves towards fragmentation inducing the formation of olefinic C=C bonds, which are necessary precursors of aromatic hydrocarbons. We show that photochemistry of aliphatics in the ISM does not primarily produce direct hydrogen elimination but preferential C-C photocleavage. Our results provide an efficient synthetic route for the formation of unsaturated aliphatics, including propene and dienes, and suggest that aromatics could be formed in dark clouds by a bottom-up mechanism involving molecular fragments produced by UV photoprocessing of aliphatics.

Acoustic local positioning systems (ALPSs) are an interesting alternative for indoor positioning due to certain advantages over other approaches, including their relatively high accuracy, low cost, and room-level signal propagation. Centimeter-level or fine-grained indoor positioning can be an asset for robot navigation, guiding a person to, for instance, a particular piece in a museum or to a specific product in a shop, targeted advertising, or augmented reality. In airborne system applications, acoustic positioning can be based on using opportunistic signals or sounds produced by the person or object to be located (e.g., noise from appliances or the speech from a speaker) or from encoded emission beacons (or anchors) specifically designed for this purpose. This work presents a review of the different challenges that designers of systems based on encoded emission beacons must address in order to achieve suitable performance. At low-level processing, the waveform design (coding and modulation) and the processing of the received signal are key factors to address such drawbacks as multipath propagation, multiple-access interference, nearfar effect, or Doppler shifting. With regards to high-level system design, the issues to be addressed are related to the distribution of beacons, ease of deployment, and calibration and positioning algorithms, including the possible fusion of information. Apart from theoretical discussions, this work also includes the description of an ALPS that was implemented, installed in a large area and tested for mobile robot navigation. In addition to practical interest for real applications, airborne ALPSs can also be used as an excellent platform to test complex algorithms, which can be subsequently adapted for other positioning systems, such as underwater acoustic systems or ultrawideband radiofrequency (UWB RF) systems.

The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to anticipate the net load - the difference between consumer electrical demand and renewable power generation. This paper proposes a deep learning (DL) model based on long short-term memory (LSTM) networks for net load forecasting in renewable-based microgrids, considering both solar and wind power. The model's architecture is detailed, and its performance is evaluated using a residential microgrid test case based on a typical meteorological year (TMY) dataset. The results demonstrate the effectiveness of the proposed LSTM-based DL model in predicting the net load, showcasing its potential for enhancing energy management in renewable-based microgrids., Comment: Submitted to 2024 IEEE North American Power Symposium

In this study, we investigated Rydberg atom-based microwave electrometry using polarization spectroscopy in a room-temperature vapor cell. By measuring Autler-Townes splitting in the electromagnetically induced transparency (EIT) spectrum, we determined that the minimum measurable microwave electric field is approximately five times lower than conventional EIT techniques. The results are well reproduced by a full optical Bloch equation model, which takes into account all the hyperfine levels involved. Subsequently, the EIT setup was used to characterize a custom microwave cylindrical lens, which increases the field at the focus by a factor of three, decreasing the minimum measurable microwave electric field by the same amount. Our results indicate that the combination of polarization spectroscopy and a microwave lens may enhance microwave electrometry.

Myxococcus xanthus is a unicellular organism whose cells possess the ability to move and communicate, leading to the emergence of complex collective properties and behaviours. This has made it an ideal model system to study the emergence of collective behaviours in interdisciplinary research efforts lying at the intersection of biology and physics, especially in the growing field of active matter research. Often, challenges arise when setting up reliable and reproducible culturing protocols. This tutorial provides a clear and comprehensive guide on the culture, growth, development, and experimental sample preparation of \textit{M. xanthus}. Additionally, it includes some representative examples of experiments that can be conducted using these samples, namely motility assays, fruiting body formation, predation, and elasticotaxis.

Mathematical modelling is a cornerstone of computational biology. While mechanistic models might describe the interactions of interest of a system, they are often difficult to study. On the other hand, abstract models might capture key features but remain disconnected from experimental manipulation. Geometric methods have been useful in connecting both approaches, although they have only been established for specific type of systems. Phenomena of biological relevance, such as limit cycles, are still difficult to study using conventional methods. In this paper, I explore an alternative description of planar dynamical systems and I present an algorithm to compute numerically the geometric structure of planar systems with a limit cycle.

The very late thermal pulse (VLTP) affects the evolution of $\sim$20\% of 1--8\,$\mathrm M_\odot$ stars, repeating the last phases of the red giant within a few years and leading to the formation of a new, but hydrogen-poor nebula within the old planetary nebula (PN). The strong dust formation in the latter obscures the optical and near-infrared radiation of the star. We aimed to determine the reheating timescale of the central star in Sakurai's object, which is an important constraint for the poorly understood VLTP evolution. We observed the radio continuum emission of Sakurai's object for almost 20 years from 2004 to 2023. Continuous, multi-frequency observations proved to be essential to distinguish between phases dominated by photoionization and shock ionization. The flux density fluctuates by more than a factor 40 within months to years. The spectral index remained negative between 2006 and 2017 and is close to zero since 2019. The emission region is barely resolved since 2021. Non-thermal radio emission observed from 2004 to 2017 traces shocks induced by wind interactions due to discrete mass-loss events. Thermal emission dominates during the period 2019--2023 and may indicate photoionization of the nebula by the central star., Comment: 6 pages, 3 figures, 2 tables, Astronomy & Astrophysics, accepted after minor revision

Deep architectures are the current state-of-the-art in predicting subjective image quality. Usually, these models are evaluated according to their ability to correlate with human opinion in databases with a range of distortions that may appear in digital media. However, these oversee affine transformations which may represent better the changes in the images actually happening in natural conditions. Humans can be particularly invariant to these natural transformations, as opposed to the digital ones. In this work, we evaluate state-of-the-art deep image quality metrics by assessing their invariance to affine transformations, specifically: rotation, translation, scaling, and changes in spectral illumination. Here invariance of a metric refers to the fact that certain distances should be neglected (considered to be zero) if their values are below a threshold. This is what we call invisibility threshold of a metric. We propose a methodology to assign such invisibility thresholds for any perceptual metric. This methodology involves transformations to a distance space common to any metric, and psychophysical measurements of thresholds in this common space. By doing so, we allow the analyzed metrics to be directly comparable with actual human thresholds. We find that none of the state-of-the-art metrics shows human-like results under this strong test based on invisibility thresholds. This means that tuning the models exclusively to predict the visibility of generic distortions may disregard other properties of human vision as for instance invariances or invisibility thresholds., Comment: 24 pages 40 figures

Autonomous driving is a challenging scenario for image segmentation due to the presence of uncontrolled environmental conditions and the eventually catastrophic consequences of failures. Previous work suggested that a biologically motivated computation, the so-called Divisive Normalization, could be useful to deal with image variability, but its effects have not been systematically studied over different data sources and environmental factors. Here we put segmentation U-nets augmented with Divisive Normalization to work far from training conditions to find where this adaptation is more critical. We categorize the scenes according to their radiance level and dynamic range (day/night), and according to their achromatic/chromatic contrasts. We also consider video game (synthetic) images to broaden the range of environments. We check the performance in the extreme percentiles of such categorization. Then, we push the limits further by artificially modifying the images in perceptually/environmentally relevant dimensions: luminance, contrasts and spectral radiance. Results show that neural networks with Divisive Normalization get better results in all the scenarios and their performance remains more stable with regard to the considered environmental factors and nature of the source. Finally, we explain the improvements in segmentation performance in two ways: (1) by quantifying the invariance of the responses that incorporate Divisive Normalization, and (2) by illustrating the adaptive nonlinearity of the different layers that depends on the local activity.

To date, we have access to enormous inventories of stellar spectra that allow the extraction of atmospheric parameters and chemical abundances essential in stellar studies. However, characterizing such a large amount of data is complex and requires a good understanding of the studied object to ensure reliable and homogeneous results. In this study, we present a methodology to measure homogenously the basic atmospheric parameters and detailed chemical abundances of over 1600 thin disk main-sequence stars in the 100 pc solar neighborhood, using APOGEE-2 infrared spectra. We employed the code tonalli to determine the atmospheric parameters using a prior on log g. The log g prior in tonalli implies an understanding of the treated population and helps to find physically coherent answers. Our atmospheric parameters agree within the typical uncertainties (100 K in Teff, 0.15 dex in log g and $[M/H]$) with previous estimations of ASPCAP and Gaia DR3. We use our temperatures to determine a new infrared color-temperature sequence, in good agreement with previous works, that can be used for any main-sequence star. Additionally, we used the BACCHUS code to determine the abundances of Mg, Al, Si, Ca, and Fe in our sample. The five elements (Mg, Al, Si, Ca, Fe) studied have an abundance distribution centered around slightly sub-solar values, in agreement with previous results for the solar neighborhood. The over 1600 main-sequence stars atmospheric parameters and chemical abundances presented here are useful in follow-up studies of the solar neighborhood or as a training set for data-driven methods., Comment: 20 pages, 15 figures, 6 tables, Accepted in MNRAS for publication

We study the fundamental properties of pointwise semi-Lipschitz functions between asymmetric spaces, which are the natural asymmetric counterpart of pointwise Lipschitz functions. We also study the influence that partial symmetries of a given space may have on the behavior of pointwise semi-Lipschitz functions defined on it. Furthermore, we are interested in characterizing the pointwise semi-Lipschitz structure of an asymmetric space in terms of real-valued pointwise semi-Lipschitz functions defined on it. By using two algebras of functions naturally associated to our spaces of pointwise real-valued semi-Lipschitz functions, we are able to provide two Banach-Stone type results in this context. In fact, these results are obtained as consequences of a general Banach-Stone type theorem of topological nature, stated for abstract functional spaces, which is quite flexible and can be applied to many spaces of continuous functions over metric and asymmetric spaces., Comment: No additional comments

We present a dynamical study of the intermediate polar cataclysmic variable YY Dra based on time-series observations in the $K$ band, where the donor star is known to be the major flux contributor. We covered the $3.97$-h orbital cycle with 44 spectra taken between $2020$ and $2022$ and two epochs of photometry observed in 2021 March and May. One of the light curves was simultaneously obtained with spectroscopy to better account for the effects of irradiation of the donor star and the presence of accretion light. From the spectroscopy, we derived the radial velocity curve of the donor star metallic absorption lines, constrained its spectral type to M0.5$-$M3.5 with no measurable changes in the effective temperature between the irradiated and non-irradiated hemispheres of the star, and measured its projected rotational velocity $v_\mathrm{rot} \sin i = 103 \pm 2 \, \mathrm{km}\,\mathrm{s}^{-1}$. Through simultaneous modelling of the radial velocity and light curves, we derived values for the radial velocity semi-amplitude of the donor star, $K_2 = 188^{+1}_{-2} \, \mathrm{km} \, \mathrm{s}^{-1}$, the donor to white dwarf mass ratio, $q=M_2/M_1 = 0.62 \pm 0.02$, and the orbital inclination, $i={42^{\circ}}^{+2^{\circ}}_{-1^{\circ}}$. These binary parameters yield dynamical masses of $M_{1} = 0.99^{+0.10}_{-0.09} \, \mathrm{M}_{\odot}$ and $M_2 = 0.62^{+0.07}_{-0.06} \, \mathrm{M}_{\odot}$ ($68$ per cent confidence level). As found for the intermediate polars GK Per and XY Ari, the white dwarf dynamical mass in YY Dra significantly differs from several estimates obtained by modelling the X-ray spectral continuum., Comment: 12 pages, 7 figures, 6 tables, accepted for publication in A&A

The Koopman operator enables the analysis of nonlinear dynamical systems through a linear perspective by describing time evolution in the infinite-dimensional space of observables. Here this formalism is applied to shear flows, specifically the minimal flow unit plane Couette flow and a nine-dimensional model of turbulent shear flow between infinite parallel free-slip walls under a sinusoidal body force (Moehlis et al., New J. Phys. 6, 56 (2004)). We identify a finite set of observables and approximate the Koopman operator using neural networks, following the method developed by Constante-Amores et al., Chaos, 34(4), 043119 (2024). Then the time evolution is determined with a method here denoted as "Projected Koopman Dynamics". Using a high-dimensional approximate Koopman operator directly for the plane Couette system is computationally infeasible due to the high state space dimension of direct numerical simulations (DNS). However, the long-term dynamics of the dissipative Navier-Stokes equations are expected to live on a lower-dimensional invariant manifold. Motivated by this fact, we perform dimension reduction on the DNS data with a variant of the IRMAE-WD (implicit rank-minimizing autoencoder-weight decay) autoencoder (Zeng et al., MLST 5(2), 025053 (2024)) before applying the Koopman approach. We compare the performance of data-driven state space (neural ordinary differential equation) and Projected Koopman Dynamics approaches in manifold coordinates for plane Couette flow. Projected Koopman Dynamics effectively captures the chaotic behavior of Couette flow and the nine-dimensional model, excelling in both short-term tracking and long-term statistical analysis, outperforming other frameworks applied to these shear flows.

Concave in measure and d-concave in measure nonautonomous scalar ordinary differential equations given by coercive and time-compactible maps have similar properties to equations satisfying considerably more restrictive hypotheses. This paper describes the generalized simple or double saddle-node bifurcation diagrams for one-parametric families of equations of these types, from which the dynamical possibilities for each of the equations follow. This new framework allows the analysis of ``almost stochastic" equations, whose coefficients vary in very large chaotic sets. The results also apply to the analysis of the occurrence of critical transitions for a range of models much larger than in previous approaches., Comment: 39 pages, 10 figures

We consider a Bubble Expansion mechanism for the production of scalar dark matter during a first-order phase transition in the very early Universe. Seeking for a dark matter energy density in agreement with observations, we study different renormalizable and non-renormalizable interactions between the dark matter species and the field undergoing the transition, considering all possible regimes for the Lorentz boost factor associated with the motion of the bubble wall. By employing a combination of analytical and numerical techniques, we demonstrate that sufficient dark matter production is achievable even in the previously unexplored low-velocity bubble expansion regime, enlarging the parameter space and possibilities of the scenario. Notably, for the non-renormalizable interactions it is found that the produced dark matter abundances exhibit a similar qualitative behavior to the renormalizable case, even for low Lorentz boost factors. Furthermore, for a transition around the electroweak scale, the associated gravitational wave spectrum is within the reach of future detectors., Comment: 15 pages, 6 figures. Extended numerical analysis, changes in the limiting expression for the abundance modifying the parameter space and scope of the results, title adapted accordingly

Jets and disk winds arise from materials with excess angular momentum ejected from the accretion disks in forming stars. How these structures are launched and how they impact the gas within the innermost regions of these objects remains poorly understood. MWC349A is a massive star that has a circumstellar disk which rotates in accord with Kepler's Law, with an ionized wind and a high-velocity jet launched from the disk surface. The strongly maser-amplified emission of hydrogen radio recombination lines (RRLs) observed toward this system provides a comprehensive picture of its ionized environment with exquisite detail. In this Letter, we present ALMA observations of the H26$\alpha$ RRL and continuum emission obtained with the highest angular resolution ever used toward this source (beam of $\sim$0.02"). The maser RRL emission is resolved for the first time and clearly delineates the ionized disk, wind and jet. We analyzed the RRL data cubes with the 3D non-LTE radiative transfer model MORELI, confirming that the jet is poorly collimated. We found that the jet orientation is closer to the rotation axis of the system than derived from spatially unresolved data. This study confirms that hydrogen RRL masers are powerful probes of the physical structure and kinematics of the innermost ionized material around massive stars., Comment: Accepted for publication in The Astrophysical Journal Letters

AGB stars are not expected to be X-ray-emitters, yet a small fraction of them, the so-called X-AGBs, show X-ray emission that can be attributed to coronal activity of a companion or accretion onto it. By searching the recently released eROSITA-DE eRASS1 source catalog, we aim to increase the sample of known X-AGBs. So far, 36 X-AGBs have been reported, including 21 previous ROSAT RASS, Chandra and XMM detections and 15 more eROSITA eRASS1 recent detections. We cross-correlated the position of sources in the eROSITA-DE eRASS1 catalog with those of AGB stars to find possible X-ray counterparts. We carefully checked these by comparing X-ray and near-IR $K$ images, disregarding those affected by optical loading, diffuse sources, or unreliable positional associations. Seven high-confidence X-AGBs and another seven possible ones are found. Accounting for previous X-ray detections, the sample of X-AGBs is increased from 36 up to 47, of which eROSITA-DE has so far discovered 26 new X-AGBs, more than doubling the number of known X-AGBs. This demonstrates eROSITA's capability to detect X-AGBs despite the challenge posed by the optical loading caused by their near-IR brightness. The eRASS1 X-AGBs tend to have higher X-ray luminosity than previously detected X-AGBs, suggesting a bias toward brighter sources. A comparison of the X-ray and far-UV luminosity of X-AGBs with those of X-ray-emitter symbiotic stars (X-SySts) revealed an overlap in the X-ray luminosity range $10^{29.5}

The existence of breather type solutions, i.e., periodic in time, exponentially localized in space solutions, is a very unusual feature for continuum, nonlinear wave type equations. Following an earlier work [Comm. Math. Phys. {\bf 302}, 815-841 (2011)], establishing a theorem for the existence of such structures, we bring to bear a combination of analysis-inspired numerical tools that permit the construction of such wave forms to a desired numerical accuracy. In addition, this enables us to explore their numerical stability. Our computations show that for the spatially heterogeneous form of the $\phi^4$ model considered herein, the breather solutions are generically found to be unstable. Their instability seems to generically favor the motion of the relevant structures. We expect that these results may inspire further studies towards the identification of stable continuous breathers in spatially-heterogeneous, continuum nonlinear wave equation models.

The onset of Industry 4.0 is rapidly transforming the manufacturing world through the integration of cloud computing, machine learning (ML), artificial intelligence (AI), and universal network connectivity, resulting in performance optimization and increase productivity. Digital Twins (DT) are one such transformational technology that leverages software systems to replicate physical process behavior, representing the physical process in a digital environment. This paper aims to explore the use of photogrammetry (which is the process of reconstructing physical objects into virtual 3D models using photographs) and 3D Scanning techniques to create accurate visual representation of the 'Physical Process', to interact with the ML/AI based behavior models. To achieve this, we have used a readily available consumer device, the iPhone 15 Pro, which features stereo vision capabilities, to capture the depth of an Industry 4.0 system. By processing these images using 3D scanning tools, we created a raw 3D model for 3D modeling and rendering software for the creation of a DT model. The paper highlights the reliability of this method by measuring the error rate in between the ground truth (measurements done manually using a tape measure) and the final 3D model created using this method. The overall mean error is 4.97\% and the overall standard deviation error is 5.54\% between the ground truth measurements and their photogrammetry counterparts. The results from this work indicate that photogrammetry using consumer-grade devices can be an efficient and cost-efficient approach to creating DTs for smart manufacturing, while the approaches flexibility allows for iterative improvements of the models over time.

For a graph $G$, let Conf$(G,n)$ denote the classical configuration space of $n$ labelled points in $G$. Abrams introduced a cubical complex, denoted here by DConf$(G,n)$, sitting inside Conf$(G,n)$ as a strong deformation retract provided $G$ is suitably subdivided. Using discrete Morse Theory techniques, we extend Abrams' result to the realm of configurations having no $k$-fold collisions., Comment: 23 pages, 4 figures