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Fundamental questions about the physics responsible for fragmenting molecular parsec-scale clumps into cores of ~1000 au are still open, that only a statistically significant investigation with ALMA is able to address: what are the dominant agents that determine the core demographics, mass, and spatial distribution as a function of the physical properties of the hosting clumps, their evolutionary stage and the different Galactic environments in which they reside? To what extent extent is fragmentation driven by clumps dynamics or mass transport in filaments? With ALMAGAL we observed the 1.38 mm continuum and lines toward more than 1000 dense clumps in our Galaxy, with M>500M_sun, surface density > 0.1 g/cm2 and d<7.5 kpc. The ACA and two 12-m array setups were used to deliver a minimum resolution of ~1000 au over the entire sample distance range. The sample covers all evolutionary stages from infrared dark clouds (IRDCs) to HII regions from the tip of the Galactic bar to the outskirts of the Galaxy. The spectral setup includes several molecular lines to trace the multiscale physics and dynamics of gas, notably CH3CN, H2CO, SiO, CH3OH, DCN, HC3N, SO etc. We present an initial overview of the observations and the early science product and results, with a first characterization of the morphological properties of the continuum emission. We use "perimeter-versus-area" and convex hull-versus-area metrics to classify the different morphologies. More extended and morphologically complex shapes are found toward clumps that are relatively more evolved and have higher surface densities., Comment: 21 pages, 18 figures plus appendices. Astronomy & Astrophysics, accepted

Trivalent lanthanide ion-doped nanoparticles are widely employed as nanoscale thermometers, driving rapid advancements in real-world applications. When the Luminescence Intensity Ratio (LIR) technique is used, these thermometric systems typically require a calibration process to obtain macroscopic calibration parameters. However, despite extensive studies from various research groups, significant discrepancies are observed among the reported values, even for identical Ln$^{3+}$-host systems under similar experimental conditions. Also, in many cases, the obtained calibration parameters substantially differ from their microscopic counterparts, which is commonly ignored in the literature. This study addresses some sources for these inconsistencies by providing fundamental theoretical insights into the measurement process. We demonstrate that the thermalization of the electronic population within the Stark sublevels of a given manifold plays a crucial role in the LIR's temperature dependence and consequently in measuring the macroscopic parameters. As a result, attempts to construct primary thermometers without prior calibration can result in temperature measurement errors exceeding 20 K. Additionally, we show that pathways disrupting Boltzmann thermalization, influenced by experimental conditions, also affect the evaluation of the macroscopic quantities. These findings contribute to a more robust theoretical framework for interpreting and understanding ratiometric Boltzmann luminescence thermometry experiments, also paving the way for developing more accurate and reliable primary thermometers., Comment: 13 pages, 3 figures, supporting information available

Ontological models (as used in the generalized contextuality literature) play a central role in current research on quantum foundations, serving as a framework for defining classicality, constructing classical analogues of key quantum phenomena, and even examining the ontology of quantum states. In this work, we analyse the quantum state update rule in these models and argue that incompatibility -- or, equivalently, order-dependent theoretical predictions of sequential measurements -- is sufficient to stop them from being able to adequately represent a scenario. This is because, as we argue, the quantum state update rule requires ontological models to update their states according to conditional probability, which in turn renders predictions of sequential measurements order-independent. This implies that ontological models, even contextual ones, must either act differently to what we would expect given the quantum state update rule, or cannot model quantum behaviour. Building on this, we argue that classical wave theory is equally incompatible with ontological models, challenging the notion that generalized contextuality serves as a signature of classicality., Comment: 30+7 pages, 0 figures

Lipid membranes and membrane deformations are a long-standing area of research in soft matter and biophysics. Computer simulations have complemented analytical and experimental approaches as one of the pillars in the field. However, setting up and using membrane simulations can come with barriers due to the multidisciplinary effort involved and the vast choice of existing simulations models. In this review, we introduce the non-expert reader to coarse-grained membrane simulations (CGMS) at the mesoscale. Firstly, we give a concise overview of the modelling approaches to study fluid membranes, together with guidance to more specialized references. Secondly, we provide a conceptual guide on how to develop CGMS. Lastly, we construct a hands-on tutorial on how to apply CGMS, by providing a pedagogical examination of tether pulling, tubulation and fluctuations with three different membrane models, and discussing them in terms of their scope and how resource-intensive they are. To ease the reader's venture into the field, we provide a repository with ready-to-run tutorials.

This paper establishes an equivalence between the pairwise compatibility of all observables in a scenario, and our ability to create a deterministic underlying-state model for that scenario (a type of hidden-variable model, typically used in the contextuality and nonlocality literature, where quantum states are treated as probability measures over ``better-defined states''). We first argue that the quantum state update rule implies that underlying-state models must update their states in agreement with the rules of conditional probability. We then demonstrate that deterministic underlying-state models meeting this criterion exist if and only if the system's observables are pairwise compatible, which is equivalent to the theoretical predictions of sequential measurements being independent of measurement order., Comment: 5+3 pages, no figures

PyMOLfold is a flexible and open-source plugin designed to seamlessly integrate AI-based protein structure prediction and visualization within the widely used PyMOL molecular graphics system. By leveraging state-of-the-art protein folding models such as ESM3, Boltz-1, and Chai-1, PyMOLfold allows researchers to directly predict protein tertiary structures from amino acid sequences without requiring external tools or complex workflows. Furthermore, with certain models, users can provide a SMILES string of a ligand and have the small molecule placed in the protein structure. This unique capability bridges the gap between computational folding and structural visualization, enabling users to input a primary sequence, perform a folding prediction, and immediately explore the resulting 3D structure within the same intuitive platform., Comment: GitHub Repository: https://github.com/colbyford/PyMolfold

In recent years, approximately 150 low-mass white dwarfs (WDs), typically with masses below 0.4 solar masses, have been discovered. Observational evidence indicates that most of these low-mass WDs are found in binary systems, supporting binary evolution scenarios as the primary formation pathway. A few extremely low-mass (ELM) WDs in this population have also been found to be pulsationally variable. In this work, we present a comprehensive analysis aimed at identifying new variable low-mass WDs. From our candidate selection, we observed 16 objects identified within the ZZ Ceti instability strip. These objects were observed over multiple nights using high-speed photometry from the SOAR/Goodman and SMARTS-1m telescopes. Our analysis led to the discovery of three new pulsating WDs: one pulsating ELM, one low-mass WD, and one ZZ Ceti star. Additionally, we identified three objects in binary systems: two with ellipsoidal variations in their light curves, one of which is likely a pre-ELM star, and a third showing a reflection effect.

We present the experimental production and characterization of a dense cold atomic cloud of \(^{88}\text{Sr}\) atoms, optimized for the future studies of light transport in highly dense regimes. Using narrow-line molasses on the 689 nm transition, combined with a far off-resonant optical dipole trap, we achieve spatial densities as high as \(7.9 \times 10^{13} \, \text{atoms/cm}^3\) and optical depths up to 64. This approach stands out from previous methods by integrating narrow-line molasses with an optical dipole trap, enabling high-density samples without relying on evaporative cooling. Unlike traditional absorption imaging, which becomes inaccurate in such dense regimes, we demonstrate that phase-contrast imaging (PCI) can reliably reconstruct the in-situ density profile even for highly spatially and optically dense samples. The use of a spatial light modulator instead of a fixed phase plate in the PCI setup provides enhanced flexibility and control of imaging parameters, making this imaging technique robust against imaging artifacts and adaptable to varying experimental conditions. Moreover, we derive theoretical conditions for reliable PCI operation in dense regimes and validate these experimentally, showing excellent agreement with time-of-flight measurements even at the highest densities. Our results establish a robust method for producing and characterizing dense atomic clouds., Comment: 11 pages, 7 figures

We present numerous aspects of the evolution of the LP 890-9 (SPECULOOS-2/TOI-4306) planetary system, focusing on the likelihood that planet c can support life. We find that the host star reaches the main sequence in 1 Gyr and that planet c lies close to the inner boundary of the habitable zone. We find the magma ocean stage can last up to 50 Myr, remove 8 Earth-oceans of water, and leave up to 2000 bars of oxygen in the atmosphere. However, if the planet forms with a hydrogen envelope as small as 0.1 Earth-masses, no water will be lost during the star's pre-main sequence phase from thermal escape processes. We find that the planets are unlikely to be in a 3:1 mean motion resonance and that both planets tidally circularize within 0.5 Gyr when tidal dissipation is held constant. However, if tidal dissipation is a function of mantle temperature and rheology, then we find that planet c's orbit may require more than 7 Gyr to circularize, during which time tidal heating may reach hundreds of terawatts. We thus conclude that the habitability of planet c depends most strongly on the initial volatile content and internal properties, but no data yet preclude the viability of an active biosphere on the planet., Comment: 16 pages, 9 figures, accepted to PSJ

Antarctic krill (Euphausia superba) are among the most abundant species on our planet and serve as a vital food source for many marine predators in the Southern Ocean. In this paper, we utilise statistical spatio-temporal methods to combine data from various sources and resolutions, aiming to accurately model krill abundance. Our focus lies in fitting the model to a dataset comprising acoustic measurements of krill biomass. To achieve this, we integrate climate covariates obtained from satellite imagery and from drifting surface buoys (also known as drifters). Additionally, we use sparsely collected krill biomass data obtained from net fishing efforts (KRILLBASE) for validation. However, integrating these multiple heterogeneous data sources presents significant modelling challenges, including spatio-temporal misalignment and inflated zeros in the observed data. To address these challenges, we fit a Hurdle-Gamma model to jointly describe the occurrence of zeros and the krill biomass for the non-zero observations, while also accounting for misaligned and heterogeneous data sources, including drifters. Therefore, our work presents a comprehensive framework for analysing and predicting krill abundance in the Southern Ocean, leveraging information from various sources and formats. This is crucial due to the impact of krill fishing, as understanding their distribution is essential for informed management decisions and fishing regulations aimed at protecting the species.

The General Data Protection Regulation (GDPR) is the benchmark in the European Union (EU) for privacy and data protection standards. Substantial research has been conducted in the requirements engineering (RE) literature investigating the elicitation, representation, and verification of privacy requirements in GDPR. Software systems including mobile apps must comply with the GDPR. With the growing pervasiveness of mobile apps and their increasing demand for personal data, privacy concerns have acquired further interest within the software engineering (SE) community at large. Despite the extensive literature on GDPR-relevant privacy concerns in mobile apps, there is no secondary study that describes, analyzes, and categorizes the current focus. Research gaps and persistent challenges are thus left unnoticed. In this article, we aim to systematically review existing primary studies highlighting various GDPR concepts and how these concepts are addressed in mobile apps research. The objective is to reconcile the existing work on GDPR in the RE literature with the research on GDPR-related privacy concepts in mobile apps in the SE literature. Our findings show that the current research landscape reflects a rather shallow understanding of GDPR requirements. Some GDPR concepts such as data subject rights (i.e., the rights of individuals over their personal data) are fundamental to GDPR, yet under-explored in the literature. In this article, we highlight future directions to be pursued by the SE community for supporting the development of GDPR-compliant mobile apps.

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

Two-dimensional (2D) $\beta$-TeO$_2$ has gained attention as a promising material for optoelectronic and power device applications, thanks to its transparency and high hole mobility. However, the underlying mechanism behind its $p$-type conductivity and dopability remains unclear. In this study, we investigate the intrinsic and extrinsic point defects in monolayer and bilayer $\beta$-TeO$_2$, the latter of which has been experimentally synthesized, using the HSE+D3 hybrid functional. Our results reveal that most intrinsic defects are unlikely to contribute to $p$-type doping in 2D $\beta$-TeO$_2$. Moreover, Si contamination could further impair $p$-type conductivity. Since the point defects do not contribute to $p$-type conductivity, we propose two possible mechanisms for hole conduction: hopping conduction via localized impurity states, and substrate effects. We also explored substitutional $p$-type doping in 2D $\beta$-TeO$_2$ with 10 trivalent elements. Among these, the Bi dopant is found to exhibit a relatively shallow acceptor transition level. However, most dopants tend to introduce deep localized states, where hole polarons become trapped at Te's lone pairs. Interestingly, monolayer $\beta$-TeO$_2$ shows potential advantages over bilayers due to reduced self-compensation effects for $p$-type dopants. These findings provide valuable insights into defect engineering strategies for future electronic applications involving 2D $\beta$-TeO$_2$.

Laminar separation bubbles around airfoils lead to the growth of instability waves, which enhances to acoustic scattering at the trailing-edge, forming a feedback loop that produces to tonal noise. To reduce the trailing-edge tonal noise, an array of roughness elements was used over a NACA0012 airfoil, at low angles of attack and moderate Reynolds number. Aeroacoustics and flow visualization experiments were performed for four configurations: a baseline smooth airfoil, two configurations with roughness elements on either airfoil surface (pressure side or suction side), and a fourth configuration with roughness elements at both airfoil surfaces. The roughness elements are made up of a row of spanwise periodically spaced cylinders, which were placed close to the mid-chord position. It is expected the proposed array of roughness elements stabilizes the Kelvin-Helmholtz instability mechanism that is present on the separated shear layer through the induction of streak structures. The separation bubble is assessed using oil flow visualizations, and the cases with roughness elements show the generation of streaks downstream of the array cylinders, disrupting the separation bubble. Acoustic measurements results show a decrease, and in some cases the total suppression, of the tonal noise at Reynolds numbers ranging from 0.6$\times$10$^5$ to 2.5$\times$10$^5$, and angles of attack ranging from 0 to 4 degrees., Comment: 20 pages, 17 figures

We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment, DARWIN. We train an anomaly detector comprising a variational autoencoder and a classifier on extensive, high-dimensional simulated detector response data and construct a one-dimensional anomaly score optimised to reject the background only hypothesis in the presence of an excess of non-background-like events. We benchmark the procedure with a sensitivity study that determines its power to reject the background-only hypothesis in the presence of an injected WIMP dark matter signal, outperforming the classical, likelihood-based background rejection test. We show that our neural networks learn relevant energy features of the events from low-level, high-dimensional detector outputs, without the need to compress this data into lower-dimensional observables, thus reducing computational effort and information loss. For the future, our approach lays the foundation for an efficient end-to-end pipeline that eliminates the need for many of the corrections and cuts that are traditionally part of the analysis chain, with the potential of achieving higher accuracy and significant reduction of analysis time., Comment: 10 Figures, 3 Tables, 23 Pages (incl. references)

Navigating higher education requires more than attending classes and completing assignments; it requires "college fluency," a set of skills that enables students, faculty, and staff to effectively locate and utilize institutional resources. College fluency can empower students, faculty, and staff to navigate the complex culture and bureaucracy of higher education, supporting students to advocate for themselves as they move through these systems. Libraries play a crucial role in fostering this college fluency by equipping students with the tools and resources for both their curricular and non-curricular needs. Both curricular and non-curricular support are crucial, as student success encompasses not only academic performance, but also overall well-being and the ability to navigate the complexities of life while at college. To better understand the current landscape of college fluency, and the challenges faced by institutions, Ithaka S+R and the Borough of Manhattan Community College, with support from IMLS, fielded a national survey to gather insights from administrators, librarians, and faculty and staff from academic and student affairs departments across community colleges in the US. This survey aimed to explore the perceptions of college fluency, evaluate the effectiveness of existing support and resource referrals, and identify gaps in non-curricular information and resources available to faculty, staff, and students.

Navigating the landscape of higher education takes more than just attending classes, passing, and graduating. It requires a set of skills known as "college fluency." Libraries play a pivotal role in helping fluency flourish, training their employees and other faculty and staff members across their institution to adapt to the needs of students in an ever-changing world. As students and staff grapple with challenges beyond the syllabus, with issues such as employee turnover rates, food insecurity, and the challenges of hybrid work and study, the need for college fluency becomes even more evident. To further examine and develop impactful strategies for unmet needs related to college fluency, the Borough of Manhattan Community College Library (BMCC) and Ithaka S+R have partnered on the College Fluency Capacity Building initiative with support from the Institute of Museum and Library Services (IMLS). Looking specifically at the development of college fluency services in community colleges across the US, this initiative takes a deep dive into the nuances of this programming toward increasing librarians' own college fluency and that of their students. To do this, BMCC and Ithaka S+R are publishing a series of case studies to further understand how institutions are currently addressing college fluency needs and to learn how to enhance the abilities of academic librarians and library workers to help their students successfully navigate institutional resources and services. The second case study in this series looks at a small northeastern community college that has been developing college fluency programs with both their library and non-library faculty and staff. The college fluency initiatives are still in their early stages, with a primary focus on the library. Other more traditional programs at this college that also contribute to college fluency are primarily non-library related, highlighting just how much of a campus-wide effort it takes to promote greater college fluency.

Three-dimensional (3D) simulations of the structure of liquid crystal (LC) torons, topologically protected distortions of the LC director field, under material flows are rare but essential in microfluidic applications. Here, we show that torons adopt a steady-state configuration at low flow velocity before disintegrating at higher velocities, in line with experimental results. Furthermore, we show that under partial slip conditions at the boundaries, the flow induces a reversible elongation of the torons, also consistent with the experimental observations. These results are in contrast with previous simulation results for 2D skyrmions under similar flow conditions, highlighting the need for a 3D description of this LC soliton in relation to its coupling to the material flow. These findings pave the way for future studies of other topological solitons, like hopfions and heliknotons, in flowing soft matter systems.

We perform the first search for ultralight dark matter using a magnetically levitated particle. A sub-millimeter permanent magnet is levitated in a superconducting trap with a measured force sensitivity of $0.2\,\mathrm{fN/\sqrt{Hz}}$. We find no evidence of a signal and derive limits on dark matter coupled to the difference between baryon and lepton number, $B - L$, in the mass range $(1.10360 \text{ - } 1.10485) \times 10^{-13}\,\mathrm{eV} / c^2$. Our most stringent limit on the coupling strength is $g_{B - L} \lesssim 2.98 \times 10^{-21}$. We propose the POLONAISE (Probing Oscillations using Levitated Objects for Novel Accelerometry in Searches of Exotic physics) experiment, featuring short-, medium-, and long-term upgrades that will give us leading sensitivity in a wide mass range and demonstrating the promise of this novel quantum sensing technology in the hunt for dark matter., Comment: 5 pages, 7 figures, 1 table, 4 appendices

Removed per arXiv policy. Please see version at https://doi.org/10.31219/osf.io/4wqcr, Comment: arXiv admin note: Removed per arXiv policy. Please see version at https://doi.org/10.31219/osf.io/4wqcr

The adoption of microservice architecture has seen a considerable upswing in recent years, mainly driven by the need to modernize legacy systems and address their limitations. Legacy systems, typically designed as monolithic applications, often struggle with maintenance, scalability, and deployment inefficiencies. This study investigates the motivations, activities, and challenges associated with migrating from monolithic legacy systems to microservices, aiming to shed light on common practices and challenges from a practitioner's point of view. We conducted a comprehensive study with 53 software practitioners who use microservices, expanding upon previous research by incorporating diverse international perspectives. Our mixed-methods approach includes quantitative and qualitative analyses, focusing on four main aspects: (i) the driving forces behind migration, (ii) the activities to conduct the migration, (iii) strategies for managing data consistency, and (iv) the prevalent challenges. Thus, our results reveal diverse practices and challenges practitioners face when migrating to microservices. Companies are interested in technical benefits, enhancing maintenance, scalability, and deployment processes. Testing in microservice environments remains complex, and extensive monitoring is crucial to managing the dynamic nature of microservices. Database management remains challenging. While most participants prefer decentralized databases for autonomy and scalability, challenges persist in ensuring data consistency. Additionally, many companies leverage modern cloud technologies to mitigate network overhead, showcasing the importance of cloud infrastructure in facilitating efficient microservice communication.

This work presents Retail-GPT, an open-source RAG-based chatbot designed to enhance user engagement in retail e-commerce by guiding users through product recommendations and assisting with cart operations. The system is cross-platform and adaptable to various e-commerce domains, avoiding reliance on specific chat applications or commercial activities. Retail-GPT engages in human-like conversations, interprets user demands, checks product availability, and manages cart operations, aiming to serve as a virtual sales agent and test the viability of such assistants across different retail businesses., Comment: 5 pages, 4 figures

This note proposes a new type of Parallel Distributed Controller (PDC) for Takagi-Sugeno (TS) fuzzy models. Our idea consists of using two control terms based on state feedback, one composed of a convex combination of linear gains weighted by the normalized membership grade, as in traditional PDC, and the other composed of linear gains weighted by the time-derivatives of the membership functions. We present the design conditions as Linear Matrix Inequalities, solvable through numerical optimization tools. Numerical examples are given to illustrate the advantages of the proposed approach, which contains the the traditional PDC as a special case., Comment: 20 pages, 4 figures

We study a percolation model with restrictions on the opening of sites on the square lattice. In this model, each site $s \in \mathbb{Z}^{2}$ starts closed and an attempt to open it occurs at time $t=t_s$, where $(t_s)_{s \in \mathbb{Z}^2}$ is a sequence of independent random variables uniformly distributed on the interval $[0,1]$. The site will open if the volume difference between the two largest clusters adjacent to it is greater than or equal to a constant $r$ or if it has at most one adjacent cluster. Through numerical analysis, we determine the critical threshold $t_c(r)$ for various values of $r$, verifying that $t_c(r)$ is non-decreasing in $r$ and that there exists a critical value $r_c=5$ beyond which percolation does not occur. Additionally, we find that the correlation length exponent of this model is equal to that of the ordinary percolation model. For $t = 1$ and $1 \leq r \leq 9$, we estimate the averages of the density of open sites, the number of distinct cluster volumes, and the volume of the largest cluster.

Although $\beta$-TeO$_2$ is a promising $p$-type transparent conducting oxide (TCO) due to the large optical gap ($\sim$ 3.7 eV) and a light effective hole mass, its hole dopability still remains unexplored. In this work, electronic structure of $\beta$-TeO$_2$ and its point defects are investigated using the HSEsol functional with the band-gap-tuned mixing parameter. Our calculations reveal that $\beta$-TeO$_2$ exhibits a significant difference between the fundamental and optical band gaps because lower energy optical transitions are dipole forbidden. Additionally, it has a low hole effective mass, especially in-plane. The point defect calculations show that $\beta$-TeO$_2$ is intrinsically an insulator. From systematic calculations of the trivalent dopants as well as hydrogen, Bi doping is suggested as the best candidate as an acceptor dopant. This work paves the way for the material design of the $p$-type $\beta$-TeO$_2$.

This article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/$c^2$, as well as upper limits on dark photon kinetic mixing and axion-like particle axioelectric coupling for masses between 1.2 and 23.3 eV/$c^2$. Compared to an earlier HVeV search, sensitivity was improved as a result of an increased overburden of 225 meters of water equivalent, an anticoincidence event selection, and better pile-up rejection. In the case of dark-matter-electron scattering via a heavy mediator, an improvement by up to a factor of 25 in cross-section sensitivity was achieved., Comment: 7 pages + title and references, 4 figures, and 1 table

We propose a heuristic model of the universe as a growing quasicrystal projected from a higher-dimensional lattice. This quasicrystalline framework offers a novel perspective on cosmic expansion, where the intrinsic growth dynamics naturally give rise to the observed large-scale expansion of the universe. Motivated by this model, we explore the Schr\"odinger equation for a particle in a box with time-dependent boundaries, representing the expanding underlying space. By introducing a constraint that links microscale quantum phenomena with macroscale cosmological quantities, we derive an equation resembling the Friedmann equation, providing potential insights into the Hubble tension. Our model incorporates phonons and phasons-quasiparticles inherent in quasicrystalline structures-that play critical roles in cosmic-scale dynamics and the universe's expansion. This framework suggests that the necessity for an inflationary period may be obviated. Furthermore, phonons arising from the quasicrystalline structure may serve as dark matter candidates, influencing the dynamics of ordinary matter while remaining largely undetectable through electromagnetic interactions. Drawing parallels with crystalline matter at atomic scales, which is fundamentally quantum in nature, we explore how the notion of tiling space can support continuous symmetry atop a discrete structure. This provides a novel framework for understanding the universe's expansion and underlying structure. Consequently, our approach suggests that further development could enhance our understanding of cosmic expansion and the universe's structure, bridging concepts from quantum mechanics, condensed matter physics, and cosmology.

The resource theory of contextuality considers resourceful objects to be probabilistic data-tables, known as correlations or behaviors, that fail to have an explanation in terms of Kochen-Specker noncontextual models. In this work, we advance this resource theory, considering free operations to be noncontextual wirings (NCW). We show that all such wirings form a convex set. When restricted to Bell scenarios, we show that such wirings are not equivalent to local operations assisted by a common source of classical shared randomness (LOSR). The set of all NCW operations contains LOSR, but is strictly larger. We also prove several elementary facts about how different resources can be converted via NCW. As a concrete example, we show that there are pairs of behaviors that cannot be converted one into the other using NCW. Since resource conversion mathematically induces a pre-order over the set of all behaviors, our results reveal the intricate ordering induced by NCW in scenarios beyond Bell scenarios., Comment: 23 pages, 7 figures; supersedes arXiv:2210.03268. Comments are welcome

Modeling is often associated with complex and heavy tooling, leading to a negative perception among practitioners. However, alternative paradigms, such as everything-as-code or low-code, are gaining acceptance due to their perceived ease of use. This paper explores the dichotomy between these perceptions through the lens of ``modeler experience'' (MX). MX includes factors such as user experience, motivation, integration, collaboration \& versioning and language complexity. We examine the relationships between these factors and their impact on different modeling usage scenarios. Our findings highlight the importance of considering MX when understanding how developers interact with modeling tools and the complexities of modeling and associated tooling.

Quantum thermodynamics aims to explore quantum features to enhance energy conversion beyond classical limits. While significant progress has been made, the understanding of caloric potentials in quantum systems remains incomplete. In this context, this study focuses on deriving general expressions for these caloric potentials, by developing a quantum Maxwell relationship obtained from a thermal average form of the Ehrenfest theorem. Our results recover the classical cases and also reveal that the isothermal entropy change can be related to genuine quantum correlations in the system. Thus, this work aims to contribute to the understanding of the caloric behavior of quantum systems and their potential implication in caloric devices.

In classical thermodynamics, heat must spontaneously flow from hot to cold systems. In quantum thermodynamics, the same law applies when considering multipartite product thermal states evolving unitarily. If initial correlations are present, anomalous heat flow can happen, temporarily making cold thermal states colder and hot thermal states hotter. Such effect can happen due to entanglement, but also because of classical randomness, hence lacking a direct connection with nonclassicality. In this work, we introduce scenarios where anomalous heat flow \emph{does} have a direct link to nonclassicality, defined to be the failure of noncontextual models to explain experimental data. We start by extending known noncontextuality inequalities to a setup where sequential transformations are considered. We then show a class of quantum prepare-transform-measure protocols, characterized by time intervals $(0,\tau_c)$ for a given critical time $\tau_c$, where anomalous heat flow happens only if a noncontextuality inequality is violated. We also analyze a recent experiment from Micadei et. al. [Nat. Commun. 10, 2456 (2019)] and find the critical time $\tau_c$ based on their experimental parameters. We conclude by investigating heat flow in the evolution of two qutrit systems, showing that our findings are not an artifact of using two-qubit systems., Comment: 14+10 pages, 2 figures. Comments are welcome!

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: Published in PASP

Multi-dimensional parameter spaces are commonly encountered in physics theories that go beyond the Standard Model. However, they often possess complicated posterior geometries that are expensive to traverse using techniques traditional to astroparticle physics. Several recent innovations, which are only beginning to make their way into this field, have made navigating such complex posteriors possible. These include GPU acceleration, automatic differentiation, and neural-network-guided reparameterization. We apply these advancements to dark matter direct detection experiments in the context of non-standard neutrino interactions and benchmark their performances against traditional nested sampling techniques when conducting Bayesian inference. Compared to nested sampling alone, we find that these techniques increase performance for both nested sampling and Hamiltonian Monte Carlo, accelerating inference by factors of $\sim 100$ and $\sim 60$, respectively. As nested sampling also evaluates the Bayesian evidence, these advancements can be exploited to improve model comparison performance while retaining compatibility with existing implementations that are widely used in the natural sciences. Using these techniques, we perform the first scan in the neutrino non-standard interactions parameter space for direct detection experiments whereby all parameters are allowed to vary simultaneously. We expect that these advancements are broadly applicable to other areas of astroparticle physics featuring multi-dimensional parameter spaces., Comment: 26 pages, 6 figures, 5 tables, 5 appendices. Compared to v1: Added Bayesian to title, included more physical background, and added a table with 1D marginalised credible intervals for NSI parameters. Matches journal version

Topology establishes a unifying framework for a diverse range of scientific areas including particle physics, cosmology, and condensed matter physics. One of the most fascinating manifestations of topology in the context of condensed matter is the topological Hall effect, and its relative: the Skyrmion Hall effect. Skyrmions are stable vortex-like spin configurations in certain chiral magnets, and when subject to external electric currents can drift in the transverse direction to the current. These quasi-particles are characterised by a conserved topological charge which in the Skyrmion Hall effect plays the role of electric charges in the ordinary Hall effect. Recently, it has been shown that liquid crystals endowed with chiral properties serve as an ideal testbed for the fundamental investigation of topological solitons, including their two- and three-dimensional realisations. Here, we show experimentally and numerically that three-dimensional solitons aka "torons" exhibit a Hall-like effect when driven by shear flows: the torons are deflected in the direction perpendicular to the shear plane. The experimental results are rationalised in terms of the dynamic Ericksen-Leslie equations, which predict the emergence of the transverse component of the net mass flow, the magnitude of which scales as the 3rd power of the shear rate. The perturbation analysis highlights an interplay of the viscous and chiral elastic torques as the mechanism for the emergence of net transverse currents. Numerical simulations demonstrate, however, that torons are not merely dragged by the flow but move with their own transverse speed, much larger than the average flow velocity in the transverse direction. Our findings may enable responsive microfluidic applications relying on soft topological solitons., Comment: 10 pages, 9 figures, supplementary material and 3 supplementary videos

One of the limitations of conventional VCO-ADCs is the restriction to first-order noise shaping. True-VCO architectures have been proposed to increase the noise-shaping order by cascading several VCO integrators, but without requiring analog feedback loops. A high noise shaping order allows to reduce the input VCO frequency compared to a conventional VCO-ADC with similar dynamic range, which improves power consumption. Prior-art True-VCO architectures represent state variables either with a thermometer code or with a single-bit. Thermometer encoding is a natural choice when ring oscillators are selected as loop filter integrators. However, chip area restrictions force thermometer-encoded state variables to have few levels. A reduced number of levels in the state variables limits the dynamic range of True VCO-ADCs. In this paper, we show experimentally a second-order audio VCO-based ADC which uses ring oscillators as integrators but employs Gray and binary encoding for state variables. As a consequence, the complexity and area of the True-VCO architecture is reduced, breaking the barrier that limits the dynamic range of prior designs. The implemented chip shows a dynamic range of 103~dB achieving a peak SNDR of 76.5 dB-A with a power of 250 $\mu$W occupying 0.095 $\text{mm}^2$ in 130 nm CMOS., Comment: 11 pages, 15 figures

As the significance of Software Engineering (SE) professionals continues to grow in the industry, the adoption of gamification techniques for training purposes has gained traction due to its potential to enhance class appeal through game-derived elements. This paper presents a tertiary study investigating the application of gamification in Software Engineering (SE) education. The study was conducted in response to recent systematic literature reviews and mappings on the topic. The findings reveal that the areas of SE most frequently gamified are Software Testing and Software Quality, with competition and cooperation being the most commonly utilized gamification elements. Additionally, the majority of studies focus on structural gamification, where game elements are employed to modify the learning environment without altering the content. The results demonstrate the potential of gamification to improve students' engagement and motivation throughout the SE learning process, while also impacting other aspects such as performance improvement, skill development, and fostering good SE practices. However, caution is advised as unplanned and incorrectly applied gamification measures may lead to significant declines in performance and motivation. (English Version of the paper in Portuguese available here: HTTP://doi.org/10.1145/3613372.3614193

Purpose: Software modelling and Model-Driven Engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations behind the use of software models is inherently human-centred. Models aim to enable practitioners to communicate about software designs, make software understandable, or make software easier to write through domain-specific modelling languages. Several recent studies challenge the idea that these aims can always be reached and indicate that human factors play a role in the success of MDE. However, there is an under-representation of research focusing on human factors in modelling. Methods: During a GI-Dagstuhl seminar, topics related to human factors in modelling were discussed by 26 expert participants from research and industry. Results: In breakout groups, five topics were covered in depth, namely modelling human aspects, factors of modeller experience, diversity and inclusion in MDE, collaboration and MDE, and teaching human-aware MDE. Conclusion: We summarise our insights gained during the discussions on the five topics. We formulate research goals, questions, and propositions that support directing future initiatives towards an MDE community that is aware of and supportive of human factors and values.

The nearby elliptical galaxy M87 contains one of the only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (EHT). In 2018, more than two dozen multi-wavelength (MWL) facilities (from radio to gamma-ray energies) took part in the second M87 EHT campaign. The goal of this extensive MWL campaign was to better understand the physics of the accreting black hole M87*, the relationship between the inflow and inner jets, and the high-energy particle acceleration. Understanding the complex astrophysics is also a necessary first step towards performing further tests of general relativity. The MWL campaign took place in April 2018, overlapping with the EHT M87* observations. We present a new, contemporaneous spectral energy distribution (SED) ranging from radio to very high energy (VHE) gamma-rays, as well as details of the individual observations and light curves. We also conduct phenomenological modelling to investigate the basic source properties. We present the first VHE gamma-ray flare from M87 detected since 2010. The flux above 350 GeV has more than doubled within a period of about 36 hours. We find that the X-ray flux is enhanced by about a factor of two compared to 2017, while the radio and millimetre core fluxes are consistent between 2017 and 2018. We detect evidence for a monotonically increasing jet position angle that corresponds to variations in the bright spot of the EHT image. Our results show the value of continued MWL monitoring together with precision imaging for addressing the origins of high-energy particle acceleration. While we cannot currently pinpoint the precise location where such acceleration takes place, the new VHE gamma-ray flare already presents a challenge to simple one-zone leptonic emission model approaches, and emphasises the need for combined image and spectral modelling., Comment: 46 pages, 23 figures, accepted by Astronomy & Astrophysics on August. 29, 2024

The ability to measure differences in collected data is of fundamental importance for quantitative science and machine learning, motivating the establishment of metrics grounded in physical principles. In this study, we focus on the development of such metrics for viscoelastic fluid flows governed by a large class of linear and nonlinear stress models. To do this, we introduce a kernel function corresponding to a given viscoelastic stress model that implicitly embeds flowfield snapshots into a Reproducing Kernel Hilbert Space (RKHS) whose squared norm equals the total mechanical energy. Working implicitly with lifted representations in the RKHS via the kernel function provides natural and unambiguous metrics for distances and angles between flowfields without the need for hyperparameter tuning. Additionally, we present a solution to the preimage problem for our kernels, enabling accurate reconstruction of flowfields from their RKHS representations. Through numerical experiments on an unsteady viscoelastic lid-driven cavity flow, we demonstrate the utility of our kernels for extracting energetically-dominant coherent structures in viscoelastic flows across a range of Reynolds and Weissenberg numbers. Specifically, the features extracted by Kernel Principal Component Analysis (KPCA) of flowfield snapshots using our kernel functions yield reconstructions with superior accuracy in terms of mechanical energy compared to conventional methods such as ordinary Principal Component Analysis (PCA) with na\"ively-defined state vectors or KPCA with ad-hoc choices of kernel functions. Our findings underscore the importance of principled choices of metrics in both scientific and machine learning investigations of complex fluid systems., Comment: 33 pages, 10 figures, Revised version of the publication

Sharp structural variations induce specific signatures on stellar pulsations that can be studied to infer localised information on the stratification of the star. This information is key to improve our understanding of the physical processes that lead to the structural variations and how to model them. Here we revisit and extend the analysis of the signature of different types of buoyancy glitches in gravity-mode and mixed-mode pulsators presented in earlier works, including glitches with step-like, Gaussian-like, and Dirac-$\delta$-like shapes. In particular, we provide analytical expressions for the perturbations to the periods and show that these can be reliably used in place of the expressions provided for the period spacings, with the advantage that the use of the new expressions does not require modes with consecutive radial orders to be observed. Based on a comparison with two limit cases and on simulated data, we further tested the accuracy of the expression for the Gaussian-like glitch signature whose derivation in an earlier work involved a significant approximation. We find that the least reliable glitch parameter inferred from fitting that expression is the amplitude, which can be up to a factor of two larger than the true amplitude, reaching this limit when the glitch is small. We further discuss the impact on the glitch signature of considering a glitch in the inner and outer half of the g-mode cavity, emphasising the break of symmetry that takes place in the case of mixed-mode pulsators., Comment: 16 pages, accepted for publication in Astronomy & Astrophysics

Estimating power consumption in modern Cloud environments is essential for carbon quantification toward green computing. Specifically, it is important to properly account for the power consumed by each of the running applications, which are packaged as containers. This paper examines multiple challenges associated with this goal. The first challenge is that multiple customers are sharing the same hardware platform (multi-tenancy), where information on the physical servers is mostly obscured. The second challenge is the overhead in power consumption that the Cloud platform control plane induces. This paper addresses these challenges and introduces a novel pipeline framework for power model training. This allows versatile power consumption approximation of individual containers on the basis of available performance counters and other metrics. The proposed model utilizes machine learning techniques to predict the power consumed by the control plane and associated processes, and uses it for isolating the power consumed by the user containers, from the server power consumption. To determine how well the prediction results in an isolation, we introduce a metric termed isolation goodness. Applying the proposed power model does not require online power measurements, nor does it need information on the physical servers, configuration, or information on other tenants sharing the same machine. The results of cross-workload, cross-platform experiments demonstrated the higher accuracy of the proposed model when predicting power consumption of unseen containers on unknown platforms, including on virtual machines., Comment: This is a full-version (8-page) paper of our previous publication in IEEE MASCOTS 2023, which has been accepted as a 4-page short paper (https://ieeexplore.ieee.org/document/10387542)

We report on a quantum interface linking a diamond NV center quantum network node and 795nm photonic time-bin qubits compatible with Thulium and Rubidium quantum memories. The interface makes use of two-stage low-noise quantum frequency conversion and waveform shaping to match temporal and spectral photon profiles. Two-photon quantum interference shows high indistinguishability of (89.5 $\pm$ 1.9)% between converted 795nm photons and the native NV center photons. We use the interface to demonstrate quantum teleportation including real-time feedforward from an unbiased set of 795nm photonic qubit input states to the NV center spin qubit, achieving a teleportation fidelity of (75.5 $\pm$ 1.0)%. This proof-of-concept experiment shows the feasibility of interconnecting different quantum network hardware.

We present the first volume-limited sample of spectroscopically confirmed hot subluminous stars out to 500 pc, defined using the accurate parallax measurements from the {\em Gaia} space mission data release 3 (DR3). The sample comprises a total of 397 members, with 305 ($\sim 77\%$) identified as hot subdwarf stars, including 83 newly discovered systems. Of these, we observe that 178 ($\sim58\%$) are hydrogen-rich sdBs, 65 are sdOBs ($\sim 21\%$), 32 are sdOs ($\sim 11\%$), and 30 are He-sdO/Bs ($\sim 10\%$). Among them, 48 ($\sim 16\%$) exhibit an infrared excess in their spectral energy distribution fits, suggesting a composite binary system. The hot subdwarf population is estimated to be 90\% complete, assuming that most missing systems are these composite binaries located within the main sequence (MS) in the \emph{Gaia} colour-magnitude diagram (CMD). The remaining sources in the sample include cataclysmic variables (CVs), blue horizontal branch stars (BHBs), hot white dwarfs (WDs), and MS stars. We derived the mid-plane density $\rho_{0}$ and scale height $\mathrm{h}_{z}$ for the non-composite hot subdwarf star population using a hyperbolic sechant profile (sech$^2$). The best-fit values are $\rho_{0}\,=\,5.17\pm 0.33 \times10^{-7}$ stars/pc$^{3}$ and $\mathrm{h}_{z} = 281 \pm 62$ pc. When accounting for the composite-colour hot subdwarfs and their estimated completeness, the mid-plane density increases to $\rho_{0}\,=\,6.15^ {+1.16}_{-0.53} \times10^{-7}$ stars/pc$^{3}$. This corrected space density is an order of magnitude lower than predicted by population synthesis studies, supporting previous observational estimates., Comment: Accepted for publication with A&A (permission has been granted by A&A to share this article on arXiv), 30 pages, 16 figures, 7 tables (4 + 3 appendices). The full table will be available in electronic form at the CDS

Classic automobiles are an important part of the automotive industry and represent the historical and technological achievements of certain eras. However, to be considered masterpieces, they must be maintained in pristine condition or restored according to strict guidelines applied by expert services. Therefore, all data about restoration processes and other relevant information about these vehicles must be rigorously documented to ensure their verifiability and immutability. Here, we report on our ongoing research to adequately provide such capabilities to the classic car ecosystem. Using a design science research approach, we have developed a blockchain-based solution using Hyperledger Fabric that facilitates the proper recording of classic car information, restoration procedures applied, and all related documentation by ensuring that this data is immutable and trustworthy while promoting collaboration between interested parties. This solution was validated and received positive feedback from various entities in the classic car sector. The enhanced and secured documentation is expected to contribute to the digital transformation of the classic car sector, promote authenticity and trustworthiness, and ultimately increase the market value of classic cars.

(Ultra)light spin-$1$ particles -- dark photons -- can constitute all of dark matter (DM) and have beyond Standard Model couplings. This can lead to a coherent, oscillatory signature in terrestrial detectors that depends on the coupling strength. We provide a signal analysis and statistical framework for inferring the properties of such DM by taking into account (i) the stochastic and (ii) the vector nature of the underlying field, along with (iii) the effects due to the Earth's rotation. Owing to equipartition, on time scales shorter than the coherence time the DM field vector typically traces out a fixed ellipse. Taking this ellipse and the rotation of the Earth into account, we highlight a distinctive three-peak signal in Fourier space that can be used to constrain DM coupling strengths. Accounting for all three peaks, we derive latitude-independent constraints on such DM couplings, unlike those stemming from single-peak studies. We apply our framework to the search for ultralight $B - L$ DM using optomechanical sensors, demonstrating the ability to delve into previously unprobed regions of this DM candidate's parameter space., Comment: 23 pages, 9 figures, and 5 appendices. Compared to v2, added 1 figure. Also, for a movie of the vector field behavior based on simulations, visit https://www.youtube.com/watch?v=bbw6yFRLS7s

Tissue organization plays a crucial role in morphogenesis, wound healing and cancer metastasis. Hydra, known for its regenerative capabilities, serves as an excellent model for studying cellular structures, particularly in pattern formation and the diffusion of cell clusters. Established experimental protocols enable the examination of regeneration and tissue segregation through optical microscopy. Recent experiments challenge previous theories by suggesting that cell collective behavior is a key factor in hydra cell aggregate organization. Utilizing image treatment techniques on fluorescent images from Hydra's segregation experiment, we track endoderm cell clusters and investigate the relationship between their diffusion constant and cluster size. In contrast to results observed in non-active matter, we discover a nearly constant dependence of diffusion on cluster mass. This finding contributes to understanding the rapid segregation observed in recent experiments and holds implications for general cellular tissue processes.

Approximately 150 low-mass white dwarfs, with masses below 0.4Msun, have been discovered. The majority of these low-mass WDs are observed in binary systems as they cannot be formed through single-star evolution within the Hubble time. In this study, we present a comprehensive analysis of the double low-mass WD eclipsing binary system J2102-4145. Our investigation involved an extensive observational campaign, resulting in the acquisition of approximately 28 hours of high-speed photometric data across multiple nights using NTT/ULTRACAM, SOAR/Goodman, and SMARTS-1m telescopes. These observations have provided critical insights into the orbital characteristics of this system, including parameters such as inclination and orbital period. To disentangle the binary components of J2102-4145, we employed the XT GRID spectral fitting method with GMOS/Gemini-South and X-Shooter data. Additionally, we used the PHOEBE package for light curve analysis on NTT/ULTRACAM high-speed time-series photometry data to constrain the binary star properties. Our analysis reveals remarkable similarities between the two components of this binary system. For the primary star, we determined Teff1 = 13688 +- 65 K, log g1 = 7.36 +- 0.01, R1 = 0.0211 +- 0.0002 Rsun, and M1 = 0.375 +- 0.003 Msun, while the secondary star is characterized by Teff2 = 12952 +- 53 K, log g2 = 7.32 +- 0.01, R2 = 0.0203 +- 0.0002 Rsun, and M2 = 0.31 +- 0.003 Msun. Furthermore, we observe a notable discrepancy between Teff and R of the less massive WD compared to evolutionary sequences for WDs from the literature, which has significant implications for our understanding of WD evolution. We discuss a potential formation scenario for this system that might explain this discrepancy and explore its future evolution. We predict that this system will merge in about 800 Myr, evolving into a helium-rich hot subdwarf star and later into a hybrid He/CO WD.

We show that gauge fields after a spontaneous symmetry breaking (SSB) mechanism do not have a Gribov problem along the broken directions. In order to make this proof, we describe a gauge fixing procedure inspired on Morse theory leading to the concept of a gauge fixing generating functional. This approach is specially suited in order to understand the unitary gauges of t Hooft. The conclusion is that after a SSB process, the generalized Faddeev-Popov operator acquires a positive definite value along the broken directions. We show how this works in the eletroweak $SU(2)XU(1)$ theory, where such a result is in fact expected as in this case the gauge fields acquire masses after the SSB. Then we apply this development to the $SL(3,c)$ confining model of [1]. The final result explains why such confining mechanism is actually a solution to Gribov problem for the confined gauge fields. These cases show that although confinement is not a general effect of the solution of the Gribov problem, as we can infer from the eletroweak example, its solution indeed seems to be necessary in order to achieve confinement. In the end, these conclusions allow us to speculate that the strong interaction confinement may be the result of some hidden SSB mechanism yet to be described., Comment: No figure , 17 pages, accepted final version Physical Review D

The adiabatic temperature change ($\Delta T_{ad}$) of a magnetic refrigerant can be indirectly estimated through field ($H$) and temperature ($T$) dependent magnetization ($M$) and specific heat ($C_p$) measurements. A direct integration approach for this estimation is frequently reported, which is an approximation to a rigorous mathematical approach. In this work, we propose an iterative method in small $H$ steps, to estimate $\Delta T_{ad}$ from indirect measurements. We show that this approach is able to reproduce the reversibility of the magnetocaloric effect, and provides a more accurate estimation of $\Delta T_{ad}$, up to 10\% when considering a detailed $M(H,T)$ and $Cp(H,T)$ dataset that reproduces the magnetothermal properties of gadolinium, a benchmark room-temperature magnetic refrigerant.