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We report the first detection in interstellar medium of the 1-cyano propargyl radical, HC$_3$HCN. This species is an isomer of the 3-cyano propargyl radical (CH$_2$C$_3$N), which was recently discovered in TMC-1. The 1-cyano propargyl radical was observed in the cold dark cloud TMC-1 using data from the ongoing QUIJOTE line survey, which is being carried out with the Yebes 40m telescope. A total of seven rotational transitions with multiple hyperfine components were detected in the 31.0-50.4 GHz range. We derived a column density of (2.2$\pm$0.2)$\times$10$^{11}$ cm$^{-2}$ and a rotational temperature of 7$\pm$1\,K. The abundance ratio between HC$_3$HCN and CH$_2$C$_3$N is 1.4. The almost equal abundance of these isomers indicates that the two species may be produced in the same reaction with a similar efficiency, probably in the reaction C + CH$_2$CHCN and perhaps also in the reaction C$_2$ + CH$_3$CN and the dissociative recombination with electrons of CH$_2$C$_3$NH$^+$, Comment: Accepted as a Letter to the Editor in Astronomy & Astrophysics on December 29th 2024

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes $5.5 < H_r < 8.2$ detected in the Dark Energy Survey (DES), we characterize the relationships between their dynamical state and physical properties -- namely $H_r$, indicating size; colors, indicating surface composition; and flux variation semi-amplitude $A$, indicating asphericity and surface inhomogeneity. We seek ``birth'' physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with 2 Gaussian distributions in $griz$ space, ``near-IR bright'' (NIRB) and ``near-IR faint'' (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF $H_r$ and $A$ distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling $p(H_r)$, but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with $\approx70\%$ NIRB, and resonances' NIRB fractions show significant variation. The NIRB component of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our $H_r$ range. These results will strongly constrain models of the outer solar system., Comment: 52 pages, 13 figures, 4 appendices. Abstract abridged. Associated repository: https://github.com/bernardinelli/des_tno_likelihood

Using the Event Horizon Telescope (EHT), the gravitationally lensed rings around the supermassive black holes (SMBHs) in Messier 87 (M87) and Sagittarius A* (Sgr A*) have now been successfully imaged at a resolution under 10 gravitational radii (R$_{\rm g}$ $ = \rm{GM/c^2}$). To expand studies beyond M87 and Sgr A*, we have constructed the Event Horizon and Environs (ETHER) sample, a comprehensive database encompassing approximately 3.15 million SMBH mass estimates, $\sim$ 20,000 Very-Long Baseline Interferometry (VLBI) radio flux densities, and $\sim$ 36,000 hard X-ray flux densities. This database is designed to identify and optimize target selection for the EHT and its upgrades on the ground and in space. We have identified a Gold Sample (GS) of nearby low-luminosity Active Galactic Nuclei (AGNs) within it that are ideal for studying jet bases and potentially imaging black hole shadows. We observed 27 of these AGNs using the EHT from 2022 to 2024, providing an opportunity to resolve and image accretion flows and jets at resolutions of $\leq$ 100 R$_{\rm g}$. Only a few SMBHs have sufficiently high enough flux density to be imaged at scales of $\leq$ 50 R$_{\rm g}$ with the present EHT. Among these are M87, Sgr A*, NGC4594 (Sombrero/M104), NGC4261, and NGC4374 (Messier 84/M84). Of these, NGC4261, Sombrero, and M84 have been observed and/or are scheduled for deep imaging with EHT+ALMA from 2023 to 2025. Sombrero, NGC4261, M84, NGC4278, and NGC5232 are clearly detected in our EHT+ALMA observations in 2022, indicating that the 230 GHz flux density from the accretion flows is significantly high. Ongoing imaging of the ETHER GS will enable measurements of black hole mass and spin, help constrain General Relativity, and enrich our understanding of jet launching and accretion inflows across a broad multi-parameter space, including black hole mass, spin, accretion rate, and orientation., Comment: 9 pages, 6 figures, 1 table, published in Proceedings of the 16th EVN Symposium, Ed. E. Ros, P. Benke, S.A. Dzib, I. Rottmann, & J.A. Zensus, Bonn: Max-Planck-Institut f\"ur Radioastronomie, 2024, pages 75-84, https://cloud.mpifr-bonn.mpg.de/index.php/s/BkX2CC2Xjn2aKR4

Turbulence cascade has been modeled using various methods; the one we have used applies to a more exact representation of turbulence where people use the multifractal representation. The nature of the energy dissipation is usually governed by partial differential equations that have been described, such as Navier-Stokes Equations, although usually in climate modeling, the Kolmogorov turbulence cascading approximation leads towards an isotropic representation. In recent years, Meneveau et al. have proposed to go away from Kolmogorov assumptions and propose multifractal models where we can account for a new anisotropic representation. Our research aims to use Direct Numerical Simulations (DNS) from the JHU Turbulence Database and Large Eddy Simulations (LES) we simulated using OpenFOAM to predict how accurate these simulations are in replicating Meneveau experimental procedures with numerical simulations using the same rigorous mathematical approaches. Modeling turbulence cascading using higher fidelity data will advance the field and produce faster and better remote sensing metrics. We have written computer code to analyze DNS and LES data and study the multifractal nature of energy dissipation. The box-counting method is used to identify the multifractal dimension spectrum of the DNS and LES data in every direction to follow Meneveau work to represent turbulence-cascading effects in the atmosphere better., Comment: 12 pages

Building trust between humans and robots has long interested the robotics community. Various studies have aimed to clarify the factors that influence the development of user trust. In Human-Robot Interaction (HRI) environments, a critical aspect of trust development is the robot's ability to make its behavior understandable. The concept of an eXplainable Autonomous Robot (XAR) addresses this requirement. However, giving a robot self-explanatory abilities is a complex task. Robot behavior includes multiple skills and diverse subsystems. This complexity led to research into a wide range of methods for generating explanations about robot behavior. This paper presents a systematic literature review that analyzes existing strategies for generating explanations in robots and studies the current XAR trends. Results indicate promising advancements in explainability systems. However, these systems are still unable to fully cover the complex behavior of autonomous robots. Furthermore, we also identify a lack of consensus on the theoretical concept of explainability, and the need for a robust methodology to assess explainability methods and tools has been identified., Comment: 14 pages, 12 figures, 10 tables. This paper is a preprint of an article submitted to IEEE Access

Combining gaseous detectors with a high-granularity pixelated charge readout enables experimental applications which otherwise could not be achieved. This includes high-resolution tracking of low-energetic particles, requiring ultra-low material budget, X-ray polarimetry at low energies ($\lessapprox$ 2 keV) or rare-event searches which profit from event selection based on geometrical parameters. In this article, the idea of embedding a pixel ASIC - specifically the Timepix4 - into a micro-pattern gaseous amplification stage is illustrated. Furthermore, the first results of reading out a triple-GEM detector with the Timepix4 (GEMPix4) are shown, including the first X-ray images taken with a Timepix4 utilising Through Silicon Vias (TSVs). Lastly, a new readout concept is presented, called the 'Silicon Readout Board', extending the use of pixel ASICs to read out gaseous detectors to a wider range of HEP applications.

Three-orifice baffles equally spaced along a circular tube are investigated as a means for heat transfer enhancement under net, oscillatory and compound flows. An unprecedented, systematic analysis of the relative orientation of consecutive baffles -- aligned or opposed -- is accomplished to assess the changes induced on the flow structure and their impact on the thermal-hydraulic performance. The results cover the Nusselt number, the net and oscillatory friction factors and the instantaneous velocity fields using PIV in an experimental campaign with a 32 mm tube diameter. The study is conducted in the range of net Reynolds numbers $50 < Re_n < 1000$ and oscillatory Reynolds numbers $0 < Re_{osc}< 750$, for a dimensionless amplitude $x_0/D = 0.5$ and $Pr=65$. In absence of oscillatory flow, opposed baffles advance the transition to turbulence from $Re_n = 100$ to $50$, increasing the net friction factor (40 %) for $Re_n > 50$ and the Nusselt number (maximum of 27 %) for $Re_n < 150$. When an oscillatory flow is applied, augmentations caused by opposed baffles are only observed for $Re_n < 150$ and $Re_{osc} < 150$. Above $Re_n$, $Re_{osc}>150$, opposed baffles are not recommended for the promotion of heat transfer, owing to friction penalties. However, the chaotic mixing and lack of short-circuiting between baffles observed with flow velocimetry over a wide range of operational conditions point out the interest of this configuration to achieve plug flow., Comment: 20 pages, 16 figures

We propose AV-Link, a unified framework for Video-to-Audio and Audio-to-Video generation that leverages the activations of frozen video and audio diffusion models for temporally-aligned cross-modal conditioning. The key to our framework is a Fusion Block that enables bidirectional information exchange between our backbone video and audio diffusion models through a temporally-aligned self attention operation. Unlike prior work that uses feature extractors pretrained for other tasks for the conditioning signal, AV-Link can directly leverage features obtained by the complementary modality in a single framework i.e. video features to generate audio, or audio features to generate video. We extensively evaluate our design choices and demonstrate the ability of our method to achieve synchronized and high-quality audiovisual content, showcasing its potential for applications in immersive media generation. Project Page: snap-research.github.io/AVLink/, Comment: Project Page: snap-research.github.io/AVLink/

Although a good portion of elementary linear algebra concerns itself with matrices over a field such as $\mathbb{R}$ or $\mathbb{C}$, many combinatorial problems naturally surface when we instead work with matrices over a finite field. As some recent work has been done in these areas, we turn our attention to the problem of enumerating the square matrices with entries in $\mathbb{Z}_{p^k}$ that are diagonalizable over $\mathbb{Z}_{p^k}$. This turns out to be significantly more nontrivial than its finite field counterpart due to the presence of zero divisors in $\mathbb{Z}_{p^k}$., Comment: 17 pages, 4 figures, 3 tables, published in Involve, a Journal of Mathematics

A monolithic silicon pixel ASIC prototype, produced in 2024 as part of the Horizon 2020 MONOLITH ERC Advanced project, was tested with a 120 GeV/c pion beam. The ASIC features a matrix of hexagonal pixels with a 100 \mu m pitch, read by low-noise, high-speed front-end electronics built using 130 nm SiGe BiCMOS technology. It includes the PicoAD sensor, which employs a continuous, deep PN junction to generate avalanche gain. Data were taken across power densities from 0.05 to 2.6 W/cm2 and sensor bias voltages from 90 to 180 V. At the highest bias voltage, corresponding to an electron gain of 50, and maximum power density, an efficiency of (99.99 \pm 0.01)% was achieved. The time resolution at this working point was (24.3 \pm 0.2) ps before time-walk correction, improving to (12.1 \pm 0.3) ps after correction.

The James Webb Space Telescope (JWST) has recently discovered a new population of objects at high redshift referred to as `Little Red Dots' (LRDs). Their nature currently remains elusive, despite their surprisingly high inferred number densities. This emerging population of red point-like sources is reshaping our view of the early Universe and may shed light on the formation of high-redshift supermassive black holes. Here we present a spectroscopically confirmed LRD CANUCS-LRD-z8.6 at $z_{\rm spec}=8.6319\pm 0.0005$ hosting an Active Galactic Nucleus (AGN), using JWST data. This source shows the typical spectral shape of an LRD (blue UV and red optical continuum, unresolved in JWST imaging), along with broad H$\beta$ line emission, detection of high-ionization emission lines (CIV, NIV]) and very high electron temperature indicative of the presence of AGN. This is also combined with a very low metallicity ($Z<0.1 Z_\odot$). The presence of all these diverse features in one source makes CANUCS-LRD-z8.6 unique. We show that the inferred black hole mass of CANUCS-LRD-z8.6 ($M_{\rm BH}=1.0^{+0.6}_{-0.4}\times 10^{8}\rm ~M_\odot$) strongly challenges current standard theoretical models and simulations of black hole formation, and forces us to adopt `ad hoc' prescriptions. Indeed if massive seeds, or light seeds with super-Eddington accretion, are considered, the observed BH mass of CANUCS-LRD-z8.6 at $z=8.6$ can be reproduced. Moreover, the black hole is over-massive compared to its host, relative to the local $M_{\rm BH}-M_*$ relations, pointing towards an earlier and faster evolution of the black hole compared to its host galaxy., Comment: 4 main figures; 8 supplementary figures; 5 supplementary tables

This study examines the impact of lifelong learning on the professional lives of employed and unemployed individuals. Lifelong learning is a crucial factor in securing employment or enhancing one's existing career prospects. To achieve this objective, this study proposes the implementation of a multi-criteria decision support system for the evaluation of training courses in accordance with their capacity to enhance the employability of the students. The methodology is delineated in four stages. Firstly, a `working life curve' was defined to provide a quantitative description of an individual's working life. Secondly, an analysis based on K-medoids clustering defined a control group for each individual for comparison. Thirdly, the performance of a course according to each of the four predefined criteria was calculated using a t-test to determine the mean performance value of those who took the course. Ultimately, the unweighted TOPSIS method was used to evaluate the efficacy of the various training courses in relation to the four criteria. This approach effectively addresses the challenge of using extensive datasets within a system while facilitating the application of a multi-criteria unweighted TOPSIS method. The results of the multi-criteria TOPSIS method indicated that training courses related to the professional fields of administration and management, hostel and tourism and community and sociocultural services have positive impact on employability and improving the working conditions of citizens. However, courses that demonstrate the greatest effectiveness in ranking are the least demanded by citizens. The results will help policymakers evaluate the effectiveness of each training course offered by the regional government., Comment: 24 pages, 12 figures

In this study, we investigate the Klein-Gordon-Zakharov system with a focus on identifying multi-soliton solutions. Specifically, for a given number $N$ of solitons, we demonstrate the existence of a multi-soliton solution that asymptotically converges, in the energy space, to the sum of these solitons. Our proof extends and builds upon the previous results in \cite{cote, cotem, IA} concerning the nonlinear Schr\"{o}dinger equation and the generalized Klein-Gordon equation. In contrast to the method used in \cite{cotem} to establish the existence of multi-solitons for the Klein-Gordon equation, where the difficulty arises from the directions imposed by the coercivity property, requiring the identification of eigenfunctions of the coercivity operator to derive new control estimates, the structure of the present system allows for a more refined result. Specifically, the directional constraints can be eliminated by employing orthogonality arguments derived from localization and modulation techniques., Comment: arXiv admin note: text overlap with arXiv:2406.17498

A kinetic model for granular mixtures is considered to study three different non-equilibrium situations. The model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle velocity and a gas of inelastic hard spheres. As a first problem, the relaxation of the velocity moments to their forms in the homogeneous cooling state (HCS) is studied. Then, taking the HCS as the reference state, the kinetic model is solved by the Chapman-Enskog method, which is conveniently adapted to inelastic collisions. For small spatial gradients, the mass, momentum and heat fluxes of the mixture are determined and exact expressions for the Navier-Stokes transport coefficients are obtained. As a third nonequilibrium problem, the kinetic model is solved exactly in the uniform shear flow (USF) state, where the rheological properties of the mixture are computed in terms of the parameter space of the mixture. In addition to the transport properties, the velocity distribution functions of each species are also explicitly obtained. To assess the reliability of the model, its theoretical predictions are compared with both (approximate) analytical results and computer simulations of the original Boltzmann equation. In general, the comparison shows a reasonable agreement between the two kinetic equations. While the diffusion transport coefficients show excellent agreement with the Boltzmann results, more quantitative differences appear in the case of the shear viscosity coefficient and the heat flux transport coefficients. In the case of the USF, although the model qualitatively captures the shear rate dependence of the rheological properties well, the discrepancies increase with increasing inelasticity in collisions., Comment: 24 pages; 11 figures; Fig. 11 has been changed

The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without convexity or concavity of the quadratic form, the StQP is NP-hard. This problem has many relevant real-life applications ranging portfolio optimization to pairwise clustering and replicator dynamics. Sometimes, the data matrix is uncertain. We investigate models where the distribution of the data matrix is known but where both the StQP after realization of the data matrix and the here-and-now problem are indefinite. We test the performance of a chance-constrained epigraphic StQP to the uncertain StQP.

Quantum networks are promising venues for quantum information processing. This motivates the study of the entanglement properties of the particular multipartite quantum states that underpin these structures. In particular, it has been recently shown that when the links are noisy two drastically different behaviors can occur regarding the global entanglement properties of the network. While in certain configurations the network displays genuine multipartite entanglement (GME) for any system size provided the noise level is below a certain threshold, in others GME is washed out if the system size is big enough for any fixed non-zero level of noise. However, this difference has only been established considering the two extreme cases of maximally and minimally connected networks (i.e. complete graphs versus trees, respectively). In this article we investigate this question much more in depth and relate this behavior to the growth of several graph theoretic parameters that measure the connectivity of the graph sequence that codifies the structure of the network as the number of parties increases. The strongest conditions are obtained when considering the degree growth. Our main results are that a sufficiently fast degree growth (i.e. $\Omega(N)$, where $N$ is the size of the network) is sufficient for asymptotic robustness of GME, while if it is sufficiently slow (i.e. $o(\log N)$) then the network becomes asymptotically biseparable. We also present several explicit constructions related to the optimality of these results., Comment: 45 pages

The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large Language Models (LLMs), powered by advanced generative AI, have emerged as transformative tools capable of automating and enhancing qualitative analysis. This study systematically maps the literature on the use of LLMs for qualitative research, exploring their application contexts, configurations, methodologies, and evaluation metrics. Findings reveal that LLMs are utilized across diverse fields, demonstrating the potential to automate processes traditionally requiring extensive human input. However, challenges such as reliance on prompt engineering, occasional inaccuracies, and contextual limitations remain significant barriers. This research highlights opportunities for integrating LLMs with human expertise, improving model robustness, and refining evaluation methodologies. By synthesizing trends and identifying research gaps, this study aims to guide future innovations in the application of LLMs for qualitative analysis., Comment: 8 pages, includes 1 figures and 3 tables. Submitted to the WSESE 2025 ICSE Workshop

The electron-phonon interaction is one of the most fundamental mechanisms in condensed matter physics. Phonons can induce memory effects in solid-state platforms when localized electronic states interact with lattice vibrations in non-unitary dynamical maps. In this work, we demonstrate how single-mode and structured phonon environments can give rise to non-Markovian dynamics of an individual negatively charged silicon-vacancy center in diamond. Using trace distance as a quantifier via numerical simulations and theoretical calculations, we identify the physical conditions for emerging and understanding non-Markovian behavior in diverse scenarios. Most importantly, we investigate the influence of magnetic fields (longitudinal and transverse), phonon couplings, Fock states, and temperature to understand how these factors influence memory effects in this solid-state device., Comment: 14 pages, 7 figures, 1 table

Software bots, extensively adopted by Open Source Software (OSS) projects, support developers across several activities, from automating predefined tasks to generating code that aids software engineers. However, with the growing prominence of bots, questions have emerged regarding the extension to which they truly assist or hinder software engineers in their routine tasks. To address this, an exploratory survey was conducted with 37 software engineers to gather insights into their views on the use of bots within the software development process. The findings suggest that bots are present across multiple phases of the software development lifecycle, providing daily support to professionals by enhancing productivity and facilitating task automation. Respondents stated that current bots are not sufficiently intelligent and raised new challenges and enhancements to aid bot designers in developing additional functionalities and integrations., Comment: 6 pages, 6 figures, 3 tables

In this paper, we introduce a new technique to study the distribution in residue classes of sets of integers with digit and sum-of-digits restrictions. From our main theorem, we derive a necessary and sufficient condition for integers with missing digits to be uniformly distributed in arithmetic progressions, extending previous results going back to work of Erd\H{o}s, Mauduit and S\'ark\"ozy. Our approach utilizes Markov chains and does not rely on Fourier analysis as many results of this nature do. Our results apply more generally to the class of multiplicatively invariant sets of integers. This class, defined by Glasscock, Moreira and Richter using symbolic dynamics, is an integer analogue to fractal sets and includes all missing digits sets. We address uniform distribution in this setting, partially answering an open question posed by the same authors., Comment: 40 pages

The recent discovery of superconductivity in infinite-layer (IL, ABO$_2$) nickelates has opened a new avenue to deepen the understanding of high-temperature superconductivity. However, progress in this field is slowed by significant challenges in material synthesis and the scarcity of research groups capable of producing high quality superconducting samples. IL nickelates are obtained from a reduction of the perovskite ABO$_3$ phase, typically achieved by annealing using CaH$_2$ as a reducing agent. Here, we present a new method to synthesize superconducting infinite-layer nickelate Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ thin films using an aluminum overlayer deposited by sputtering as a reducing agent. We systematically optimized the aluminum deposition parameters and obtained superconducting samples reduced either in situ or ex situ (after air exposure of the precursor ABO$_3$ films). A comparison of their crystalline quality and transport properties shows that in situ Al reduction enhances the quality of the superconducting Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ thin films, achieving a maximum superconducting transition temperature $T_{c}^{onset}$ of 17 K, in agreement with the optimum value reported for this compound. This simple synthesis route, much more accessible than existing methods, offers better control and reproducibility over the topotactic transformation, opening new opportunities to gain insights into the physics of superconductivity in nickelates.

Examples of algebraic surfaces of general type with maximal Picard number are not abundant in the literature. Moreover, most known examples either possess low invariants, lie near the Noether line $K^2=2\chi-6$ or are somewhat scattered. A notable exception is Persson's sequence of double covers of the projective plane with maximal Picard number, whose invariants converge to the Severi line $K^2=4\chi$. This note is devoted to the construction of infinitely many new sequences of surfaces of general type with maximal Picard number whose invariants converge to the Severi line., Comment: 12 pages, comments are welcome. arXiv admin note: text overlap with arXiv:2306.15241

Methods of Machine and Deep Learning are gradually being integrated into industrial operations, albeit at different speeds for different types of industries. The aerospace and aeronautical industries have recently developed a roadmap for concepts of design assurance and integration of neural network-related technologies in the aeronautical sector. This paper aims to contribute to this paradigm of AI-based certification in the context of supervised learning, by outlining a complete validation pipeline that integrates deep learning, optimization and statistical methods. This pipeline is composed by a directed graphical model of ten steps. Each of these steps is addressed by a merging key concepts from different contributing disciplines (from machine learning or optimization to statistics) and adapting them to an industrial scenario, as well as by developing computationally efficient algorithmic solutions. We illustrate the application of this pipeline in a realistic supervised problem arising in aerostructural design: predicting the likelikood of different stress-related failure modes during different airflight maneuvers based on a (large) set of features characterising the aircraft internal loads and geometric parameters., Comment: 38 pages, 17 figures

We present and analyze two stabilized finite element methods for solving numerically the Poisson--Nernst--Planck equations. The stabilization we consider is carried out by using a shock detector and a discrete graph Laplacian operator for the ion equations, whereas the discrete equation for the electric potential need not be stabilized. Discrete solutions stemmed from the first algorithm preserve both maximum and minimum discrete principles. For the second algorithm, its discrete solutions are conceived so that they hold discrete principles and obey an entropy law provided that an acuteness condition is imposed for meshes. Remarkably the latter is found to be unconditionally stable. We validate our methodology through numerical experiments., Comment: 29 pages, 25 figures

Large scientific institutions, such as the Space Telescope Science Institute, track the usage of their facilities to understand the needs of the research community. Astrophysicists incorporate facility usage data into their scientific publications, embedding this information in plain-text. Traditional automatic search queries prove unreliable for accurate tracking due to the misidentification of facility names in plain-text. As automatic search queries fail, researchers are required to manually classify publications for facility usage, which consumes valuable research time. In this work, we introduce a machine learning classification framework for the automatic identification of facility usage of observation sections in astrophysics publications. Our framework identifies sentences containing telescope mission keywords (e.g., Kepler and TESS) in each publication. Subsequently, the identified sentences are transformed using Term Frequency-Inverse Document Frequency and classified with a Support Vector Machine. The classification framework leverages the context surrounding the identified telescope mission keywords to provide relevant information to the classifier. The framework successfully classifies usage of MAST hosted missions with a 92.9% accuracy. Furthermore, our framework demonstrates robustness when compared to other approaches, considering common metrics and computational complexity. The framework's interpretability makes it adaptable for use across observatories and other scientific facilities worldwide., Comment: 11 pages, 6 figures, 1 table

In the framework of data envelopment analysis (DEA), Tone (2001) introduced the slacks-based measure (SBM) of efficiency, which is a nonradial model that incorporates all the slacks of the evaluated decision-making units (DMUs) into their efficiency scores, unlike classical radial efficiency models. Next, Tone (2002) developed the SBM super-efficiency model in order to differentiate and rank efficient DMUs, whose SBM efficiency scores are always $1$. However, as pointed out by Chen (2013), some interpretation problems arise when the so-called super-efficiency projections are weakly efficient, leading to an overestimation of the SBM super-efficiency score. Moreover, this overestimation is closely related to discontinuity issues when implementing SBM super-efficiency in conjunction with SBM efficiency. Chen (2013) and Chen et al. (2019) treated these problems, but they did not arrive to a fully satisfactory solution. In this paper, we review these papers and propose a new complementary score, called composite SBM, that actually fixes the discontinuity problems by counteracting the overestimation of the SBM super-efficiency score. Moreover, we extend the composite SBM model to different orientations and variable returns to scale, and propose additive versions. Finally, we give examples and state some open problems., Comment: 25 pages, 3 figures

We construct a new family of chance constrained directional models in stochastic data envelopment analysis, generalizing the deterministic directional models and the chance constrained radial models. We prove that chance constrained directional models define the same concept of stochastic efficiency as the one given by chance constrained radial models and, as a particular case, we obtain a stochastic version of the generalized Farrell measure. Finally, we give some examples of application of chance constrained directional models with stochastic and deterministic directions, showing that inefficiency scores obtained with stochastic directions are less or equal than those obtained considering deterministic directions whose values are the means of the stochastic ones., Comment: 15 pages

Quantum Communications is a field that promises advances in cryptography, quantum computing and clock synchronisation, among other potential applications. However, communication based on quantum phenomena requires an extreme level of isolation from external disturbances, making the transmission of quantum signals together with classical ones difficult. A range of techniques has been tested to introduce quantum communications in already deployed optical networks which also carry legacy traffic. This comes with challenges, not only at the physical layer but also at the operations and management layer. To achieve a broad acceptance among network operators, the joint management and operation of quantum and classical resources, compliance with standards, and quality and legal assurance need to be addressed. This article presents a detailed account of solutions to the above issues, deployed and evaluated in the MadQCI (Madrid Quantum Communication Infrastructure) testbed. This network is designed to integrate quantum communications in the telecommunications ecosystem by installing quantum-key-distribution modules from multiple providers in production nodes of two different operators. The modules were connected through an optical-switched network with more than 130 km of deployed optical fibre. The tests were done in compliance with strict service level agreements that protected the legacy traffic of the pre-existing classical network. The goal was to achieve full quantum-classical compatibility at all levels, while limiting the modifications of optical transport and encryption and complying with as many standards as possible. This effort was intended to serve as a blueprint, which can be used as the foundation of large-scale quantum network deployments. To demonstrate the capabilities of MadQCI, end-to-end encryption services were deployed and a variety of use-cases were showcased., Comment: 18 pages

This study presents a comparative analysis between two scientific document classification systems. The first system employs the Scopus journal-based assignment method, adapted to a fractional model, while the second system uses an item-by-item system based on reclassified references according to the origin of the citers. The study's results are divided into three different sections: the first involves comparisons at the Scopus area level, the second examines comparisons at the category level, and the third tests various bibliometric indicators to identify the variations between the two systems. Highlighting the characteristics of the paper level system, it offers a reduction in the number of categories to which each document is assigned, achieving higher values of single-category assignment compared to the All Science Journal Classification (ASJC). When reclassifying areas and categories, the paper level system tends to accentuate differences at the extreme values, increasing the size of the largest categories and reducing that of the smallest ones. Moreover, the paper-by-paper system provides more homogeneous distributions in normalised impacts and adjusts values related to excellence more uniformly.

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $\Omega_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5., Comment: Data access available at https://jamiemccullough.github.io/data/blueshear/

As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques. Counterfactual explanations, with roots in human reasoning, identify the minimal input changes needed to obtain a given output and, hence, are crucial for supporting decision-making. Despite their importance, the evaluation of these explanations often lacks grounding in user studies and remains fragmented, with existing metrics not fully capturing human perspectives. To address this challenge, we developed a diverse set of 30 counterfactual scenarios and collected ratings across 8 evaluation metrics from 206 respondents. Subsequently, we fine-tuned different Large Language Models (LLMs) to predict average or individual human judgment across these metrics. Our methodology allowed LLMs to achieve an accuracy of up to 63% in zero-shot evaluations and 85% (over a 3-classes prediction) with fine-tuning across all metrics. The fine-tuned models predicting human ratings offer better comparability and scalability in evaluating different counterfactual explanation frameworks., Comment: This paper extends the AAAI-2025 version by including the Appendix

The evolution of protoplanetary disks in regions with massive OB stars is influenced by externally driven winds that deplete the outer parts of disks. These winds have previously been studied via forbidden oxygen emission lines, which also arise in isolated disks in low-mass star forming-regions (SFRs) with weak external UV fields in photoevaporative or magnetic (internal) disk winds. It is crucial to determine how to disentangle external winds from internal ones. Here, we report a proxy for unambiguously identifying externally driven winds with a forbidden line of neutral atomic carbon, [C i] 8727 A. We compare for the first time the spatial location of the emission in the [O i] 5577 A, [O i] 6300 A, and [C i] 8727 A lines traced by VLT/MUSE-NFM, with the ALMA Band 7 continuum disk emission in a sample of 12 proplyds in the Orion Nebula Cluster (ONC). We confirm that the [O i] 5577 A emission is co-spatial with the disk emission, whereas the [O i] 6300 A is emitted both on the disk surface and on the ionization front of the proplyds. We show for the first time that the [C i] 8727 A line is also co-spatial with the disk surface in proplyds, as seen in the MUSE and ALMA data comparison. To verify whether the [C i] 8727 A line is detected in regions where external photoevaporation is not expected, we examine VLT/X-Shooter spectra for young stars in low-mass SFRs. Although the [O i] lines are well detected in all these targets, there is <<10% detection rate in the case of the [C i] 8727 A line. This number increases substantially to a ~40% detection rate in sigma-Orionis, a region with intermediate UV radiation. The spatial location of the [C i] 8727 A line emission and the lack of its detection in isolated disks in low-mass SFRs strongly suggest that this line is a tell-tale tracer of externally driven photoevaporative winds, which agrees with recent excitation models., Comment: Accepted to A&A on October 25, 2024

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, $S_8$. However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. In this work, we evaluate an alternative cluster proxy, outskirt stellar mass, $M_{\textrm{out}}$, defined as the total stellar mass within a $[50,100]$ kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, $\lambda$, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a $M_{\textrm{out}}$ selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of $M_{\textrm{out}}$ and $\lambda$ with halo mass. Our results show $M_{\textrm{out}}$ has a scatter consistent with $\lambda$, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find $\lambda$-selected samples introduce features into the measured $\Delta \Sigma$ signal that are not well fit by a log-normal scatter only model, absent in $M_{\textrm{out}}$ selected samples. Our findings suggest that $M_{\textrm{out}}$ offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the $\lambda-M_{\textrm{out}}$ scaling relation to be $0.49 \pm 0.02$ and $0.38 \pm 0.09$., Comment: 22 pages, 8 figures, 4 tables, submitted to PRD

A reference-based classification system for individual Scopus publications is presented which takes into account the categories of the papers citing those references instead of the journals in which those cited papers are published. It supports multiple assignments of up to 5 categories within the Scopus ASJC structure, but eliminates the Multidisciplinary Area and the miscellaneous categories, and it allows for the reclassification of a greater number of publications (potentially 100%) than traditional reference-based systems. Twelve variants of the system were obtained by adjusting different parameters, which were applied to the more than 3.2 million citable papers from the active Scientific Journals in 2020 indexed in Scopus. The results were analyzed and compared with other classification systems such as the original journal-based Scopus ASJC, the 2-generation-reference based M3-AWC-0.8 (\'Alvarez-Llorente et al., 2024), and the corresponding authors' assignment based AAC (\'Alvarez-Llorente et al., 2023). The different variants obtained of the classification give results that improve those used as referents in multiple scientometric fields. The variation called U1-F-0.8 seems especially promising due to its restraint in assigning multiple categories, consistency with reference classifications and the fact of applying normalization processes to avoid the overinfluence of articles that have a greater number of references.

We investigate entanglement entropy in $3d$ $\mathcal{N}=2$ superconformal field theories from two different perspectives. We first confirm that the dependence of supersymmetric entanglement entropy (as defined in arXiv:1306.2958) on the entangling region is purely topological. We then compute entanglement entropy of $3d$ $\mathcal{N}=2$ superconformal gauge theories at arbitrary Yang-Mills coupling using the heat kernel method. This reveals a particular divergence originating in charge fluctuations in the vacuum, hence carrying information about internal symmetries of the theory. This computation leads to universal contributions to entanglement entropy from chiral and vector multiplets for unitary gauge groups of arbitrary rank, and has the advantage that the integral over the gauge moduli is simple to compute., Comment: 14 pages + appendix, 2 figures

Mass transport of impurities immersed in a confined quasi-two-dimensional moderately dense granular gas of inelastic hard spheres is studied. The effect of the confinement on granular particles is modeled through a collisional model (the so-called $\Delta$-model) that includes an effective mechanism to transfer the kinetic energy injected by vibration in the vertical direction to the horizontal degrees of freedom of grains. The impurity can differ in mass, diameter, inelasticity, or the energy injection at collisions, compared to the gas particles. The Enskog--Lorentz kinetic equation for the impurities is solved via the Chapman--Enskog method to first order in spatial gradients for states close to the homogeneous steady state. As usual, the three diffusion transport coefficients for tracer particles in a mixture are given in terms of the solutions of a set of coupled linear integral equations which are solved by considering the lowest Sonine approximation. The theoretical predictions for the tracer diffusion coefficient (relating the mass flux with the gradient of the number density of tracer particles) are compared with both direct simulation Monte Carlo and molecular dynamics simulations. The agreement is in general good, except for strong inelasticity and/or large contrast of energy injection at tracer-gas collisions compared to gas-gas collisions. Finally, as an application of our results, the segregation problem induced by both a thermal gradient and gravity is exhaustively analyzed., Comment: 26 pages, 12 figures, to be published in Physics of Fluids

The gravitational-wave events observed by the LIGO-Virgo-KAGRA collaboration are attributed to compact binary coalescences happening in vacuum. However, the large merger rates observed suggest that matter environments likely play a significant role in the formation and evolution of compact binaries. Why have we not seen environmental effects in LVK signals? While matched-filtering remains the most effective technique for gravitational-wave searches, it comes with a burden: we might only observe signals that align with our (vacuum) expectations, potentially missing unexpected or unknown phenomena. Even more concerning is the possibility that environmental effects could mimic vacuum waveforms, introducing biases in parameter estimation and impacting population studies. Here, we use numerical relativity simulations of binary black hole mergers inside stellar envelopes to show that: (i) a \texttt{GW150914}-like event would be detected (with a false alarm rate smaller than $10^{-4}\, \mathrm{yr^{-1}}$) using a template bank of vacuum waveforms, even when immersed in stellar material of density larger than $10^{7}\,\mathrm{g/cm^3}$; (ii) environmental effects can pass routinely performed tests of vacuum General Relativity, while leading to considerable biases in parameter estimation; but (iii) phenomenological environment waveforms are effectual in detecting environmental effects and can resolve systematic biases., Comment: 10 pages, 7 figures, Comments are welcomed

This paper examines the interdependence between green financial instruments, represented by green bonds and green stocks, and a set of major conventional assets, such as Treasury, investment-grade and high-yield corporate bonds, general stocks, crude oil, and gold. To that end, a novel wavelet-based network approach that allows for assessing the degree of interconnection between green financial products and traditional asset classes across different investment horizons is applied. The~empirical results show that green bonds are tightly linked to Treasury and investment-grade corporate bonds, while green stocks are strongly tied to general stocks, regardless of the specific time period and investment horizon considered. However, despite their common climate-friendly nature, there is no a remarkable association between green bonds and green stocks. This means that these green investments constitute basically two independent asset classes, with a distinct risk-return profile and aimed at a different type of investor. Furthermore, green financial products have a weak connection with high-yield corporate bonds and crude oil. These findings can have important implications for investors and policy makers in terms of investment decision, hedging strategies, and sustainability and energy policies., Comment: 24 pages, 4 figures

We present deep ($\sim$ 20 hr), high-angular resolution Atacama Large Millimeter/submillimeter Array (ALMA) observations of the $\rm CO ~ (4-3)$ and $\rm [CI] ~ (1-0)$ transitions, along with the rest-frame 630 $\mu$m dust continuum, in BX610 --a massive, main-sequence galaxy at the peak epoch of cosmic star formation $(z = 2.21)$. Combined with deep Very Large Telescope (VLT) SINFONI observations of the H$\alpha$ line, we characterize the molecular gas and star formation activity on kiloparsec scales. Our analysis reveals that the excitation of the molecular gas, as traced by the $L'_{\rm CO ~ (4-3)} / L'_{\rm [CI] ~ (1-0)}$ line luminosity ratio, decreases with increasing galactocentric radius. While the line luminosity ratios in the outskirts are similar to those typically found in main-sequence galaxies at $z \sim 1$, the ratios in the central regions of BX610 are comparable to those observed in local starbursts. There is also a giant extra-nuclear star-forming clump in the southwest of BX610 that exhibits high star formation activity, molecular gas abundance, and molecular gas excitation. Furthermore, the central region of BX610 is rich in molecular gas $(M_{\rm mol} / M_{\rm \star} \approx 1)$; however, at the current level of star formation activity, such molecular gas is expected to be depleted in $\sim$ 450 Myr. This, along with recent evidence for rapid inflow toward the center, suggests that BX610 may be experiencing an evolutionary phase often referred to as wet compaction, which is expected to lead to central gas depletion and subsequent inside-out quenching of star formation activity., Comment: Submitted to Astronomy & Astrophysics. 09 pages, 05 figures

In this work we present the wavScalogram R package, which contains methods based on wavelet scalograms for time series analysis. These methods are related to two main wavelet tools: the windowed scalogram difference and the scale index. The windowed scalogram difference compares two time series, identifying if their scalograms follow similar patterns at different scales and times, and it is thus a useful complement to other comparison tools such as the squared wavelet coherence. On the other hand, the scale index provides a numerical estimation of the degree of non-periodicity of a time series and it is widely used in many scientific areas., Comment: 27 pages, 17 figures

The relation between the Husain-Kucha\v{r} model and some extensions thereof that incorporate a dynamical time variable is explored. To this end, we rely on the geometric approach to the Hamiltonian dynamics of singular (constrained) systems provided by the Gotay-Nester-Hinds method (GNH). We also use recent results regarding the derivation of the Ashtekar formulation for Euclidean general relativity without using the time gauge. The insights provided by the geometric approach followed in the paper shed light on several issues related to the dynamics of general relativity and the role of time., Comment: 30 pages

Artificial Intelligence (AI), particularly large language models (LLMs), holds the potential to bridge language and information gaps, which can benefit the economies of developing nations. However, our analysis of FLORES-200, FLORES+, Ethnologue, and World Development Indicators data reveals that these benefits largely favor English speakers. Speakers of languages in low-income and lower-middle-income countries face higher costs when using OpenAI's GPT models via APIs because of how the system processes the input -- tokenization. Around 1.5 billion people, speaking languages primarily from lower-middle-income countries, could incur costs that are 4 to 6 times higher than those faced by English speakers. Disparities in LLM performance are significant, and tokenization in models priced per token amplifies inequalities in access, cost, and utility. Moreover, using the quality of translation tasks as a proxy measure, we show that LLMs perform poorly in low-resource languages, presenting a ``double jeopardy" of higher costs and poor performance for these users. We also discuss the direct impact of fragmentation in tokenizing low-resource languages on climate. This underscores the need for fairer algorithm development to benefit all linguistic groups., Comment: Project GitHub repository at https://github.com/worldbank/double-jeopardy-in-llms

Context. The gravitational lens system SDSS J1004+4112 was the first known example of a quasar lensed by a galaxy cluster. The interest in this system has been renewed following the publication of r-band light curves spanning 14.5 years and the determination of the time delays between the four brightest quasar images. Aims. We constrained the quasar accretion disk size and the fraction of the lens mass in stars using the signature of microlensing in the quasar image light curves. Methods. We built the six possible histograms of microlensing magnitude differences between the four quasar images and compared them with simulated model histograms, using a $\chi^2$ test to infer the model parameters. Results. We infer a quasar disk half-light radius of $R_{1/2}=(0.70\pm0.04)\, R_E=(6.4\pm0.4) \sqrt{M/0.3M_{\odot}}$ light-days at 2407\r{A} in the rest frame and stellar mass fractions at the quasar image positions of $\alpha_A>0.059$, $\alpha_B=0.056^{+0.021}_{-0.027}$, $\alpha_C=0.030^{+0.031}_{-0.021}$, and $\alpha_D=0.072^{+0.034}_{-0.016}$. Conclusions. The inferred disk size is broadly compatible with most previous estimates, and the stellar mass fractions are within the expected ranges for galaxy clusters. In the region where image C lies, the stellar mass fraction is compatible with a stellar contribution from the brightest cluster galaxy, galaxy cluster members, and intracluster light, but the values at images B, D, and especially A are slightly larger, possibly suggesting the presence of extra stellar components., Comment: 7 pages, 6 figures, 2 tables, A&A in press

Through automation, deep learning (DL) can enhance the analysis of transesophageal echocardiography (TEE) images. However, DL methods require large amounts of high-quality data to produce accurate results, which is difficult to satisfy. Data augmentation is commonly used to tackle this issue. In this work, we develop a pipeline to generate synthetic TEE images and corresponding semantic labels. The proposed data generation pipeline expands on an existing pipeline that generates synthetic transthoracic echocardiography images by transforming slices from anatomical models into synthetic images. We also demonstrate that such images can improve DL network performance through a left-ventricle semantic segmentation task. For the pipeline's unpaired image-to-image (I2I) translation section, we explore two generative methods: CycleGAN and contrastive unpaired translation. Next, we evaluate the synthetic images quantitatively using the Fr\'echet Inception Distance (FID) Score and qualitatively through a human perception quiz involving expert cardiologists and the average researcher. In this study, we achieve a dice score improvement of up to 10% when we augment datasets with our synthetic images. Furthermore, we compare established methods of assessing unpaired I2I translation and observe a disagreement when evaluating the synthetic images. Finally, we see which metric better predicts the generated data's efficacy when used for data augmentation., Comment: MICCAI2023; DALI Workshop