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The EdResearch for Action "Overview Series" summarizes the research on key topics to provide K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students. This research brief breaks down what is known about multilingual students classified as English Learners (ML-ELs), how ML-ELs perform in K-12 education, and what challenges they face. Key insights provided include: (1) research-based practices--such as bilingual program models--district and school leaders can use to support the academic success and linguistic development of ML-ELs; and (2) one-size-fits-all practices to avoid that can limit many students' opportunities to engage with rigorous content. [This brief was produced in collaboration with the University of Texas at Austin, College of Education.]

Large Language Models (LLMs) have facilitated the definition of autonomous intelligent agents. Such agents have already demonstrated their potential in solving complex tasks in different domains. And they can further increase their performance when collaborating with other agents in a multi-agent system. However, the orchestration and coordination of these agents is still challenging, especially when they need to interact with humans as part of human-agentic collaborative workflows. These kinds of workflows need to be precisely specified so that it is clear whose responsible for each task, what strategies agents can follow to complete individual tasks or how decisions will be taken when different alternatives are proposed, among others. Current business process modeling languages fall short when it comes to specifying these new mixed collaborative scenarios. In this exploratory paper, we extend a well-known process modeling language (i.e., BPMN) to enable the definition of this new type of workflow. Our extension covers both the formalization of the new metamodeling concepts required and the proposal of a BPMN-like graphical notation to facilitate the definition of these workflows. Our extension has been implemented and is available as an open-source human-agentic workflow modeling editor on GitHub.

Time-resolved X-ray absorption spectroscopy (tr-XAS) has been shown to be a versatile measurement technique for investigating non-equilibrium dynamics. Novel X-ray free electron laser (XFEL) facilities like the European XFEL offer increased repetition rates for stroboscopic XAS experiments through a burst operation mode, which enables measurements with up to 4.5 MHz. These higher repetition rates lead to higher data acquisition rates but can also introduce long-lived excitations that persist and thus build up during each burst. Here, we report on such long-lived effects in Ni and NiO thin film samples that were measured at the European XFEL. We disentangle the long-lived excitations from the initial pump-induced change and perform a detailed modelling-based analysis of how they modify transient X-ray spectra. As a result, we link the long-lived effects in Ni to a local temperature increase, as well as the effects in NiO to excited charge carrier trapping through polaron formation. In addition, we present possible correction methods, as well as discuss ways in which the effects of these long-lived excitations could be minimized for future time-resolved X-ray absorption spectroscopy measurements.

Metric depth estimation from visual sensors is crucial for robots to perceive, navigate, and interact with their environment. Traditional range imaging setups, such as stereo or structured light cameras, face hassles including calibration, occlusions, and hardware demands, with accuracy limited by the baseline between cameras. Single- and multi-view monocular depth offers a more compact alternative, but is constrained by the unobservability of the metric scale. Light field imaging provides a promising solution for estimating metric depth by using a unique lens configuration through a single device. However, its application to single-view dense metric depth is under-addressed mainly due to the technology's high cost, the lack of public benchmarks, and proprietary geometrical models and software. Our work explores the potential of focused plenoptic cameras for dense metric depth. We propose a novel pipeline that predicts metric depth from a single plenoptic camera shot by first generating a sparse metric point cloud using machine learning, which is then used to scale and align a dense relative depth map regressed by a foundation depth model, resulting in dense metric depth. To validate it, we curated the Light Field & Stereo Image Dataset (LFS) of real-world light field images with stereo depth labels, filling a current gap in existing resources. Experimental results show that our pipeline produces accurate metric depth predictions, laying a solid groundwork for future research in this field., Comment: 8 pages (6 for text + 2 for references), 6 figures, 2 tables. Submitted to IEEE ICRA 2025

Ultra-light axion-like particles (ALPs) can be a viable solution to the dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$ Hz and $2\times10^{-8}$ Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, have been obtained in the mass range between $6\times10^{-24}$ eV and $5\times10^{-21}$ eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them., Comment: 24 pages, 15 figures

Let $\A$ be a finite dimensional vector space and $\Phi$ be a finite root system in $\A$. To this data is associated an affine poly-simplicial complex. Motivated by a forthcoming construction of connectified higher buildings, we study "affine weight polytopes" associated to these data. We prove that these polytopes tesselate $\A$. We also prove a kind of "mixed" tessellation, involving the affine weight polytopes and the poly-simplical structure on $\A$.

The current neutrino experiments provide an opportunity for testing the inverse see-saw mechanism through charged lepton flavor violating processes and neutrinoless double beta decay. Motivated by this, in this paper we study the $\mathbf{S}_{3}\otimes \mathbf{Z}_{2}$ discrete symmetry in the $B-L$ gauge model where the active light neutrino mass matrix comes from the aforementioned mechanism. In this framework, the effect of complex vacuum expectation values of the Higgs doublets on the fermion masses is explored and, under certain assumptions on the Yukawa couplings, we find that the neutrino mixing is controlled by the Cobimaximal pattern, but a sizeable deviation from the charged lepton sector breaks the well known predictions on the atmospheric angle ($45^{\circ}$) and the Dirac CP-violating phase ($-90^{\circ}$). In addition, due to the presence of heavy neutrinos at the $TeV$ scale, charged lepton flavor violation (CLFV) and neutrinoless double beta decay get notable contributions. Analytical formulae for these observables are obtained, and then a numerical calculation allows to fit quite well the lepton mixing for the normal and inverted hierarchies, however, the branching ratios decay values for CLFV disfavors the latter one. Along with this, the region of parameter space for the $m_{ee}$ effective neutrino mass lies below the GERDA bounds for both the normal and inverted hierarchies. On the other hand, with a particular benchmark, the quark mass matrices are found to have textures that allow to fit with great accuracy the CKM mixing matrix., Comment: 37 pages, 10 figures, 3 tables

Massive star-forming regions exhibit a rich chemistry with complex gas distributions, especially on small scales. While surveys have yielded constraints on typical gas conditions, they often have coarse spatial resolution and limited bandwidths. Thus, to establish an interpretative framework for these efforts, detailed observations that simultaneously provide high sensitivity, spatial resolution, and large bandwidths for a subset of diverse sources are needed. Here, we present wideband (32 GHz) Submillimeter Array observations of four high-mass star-forming regions (G28.20-0.05, G20.08-0.14 N, G35.58-0.03, W33 Main) at subarcsecond resolution, where we detect and spatially-resolve 100s of lines from over 60 molecules, including many complex organic molecules (COMs). The chemical richness of our sample is consistent with an evolutionary sequence from the line-rich hot cores and HC HII regions of G28.20-0.05 and G20.08-0.14 N to the more chemically-modest UC HII regions in G35.58-0.03, followed by the molecule-poor HII region W33 Main. We detect lines across a range of excitation conditions (Eu=20 to >800 K) and from numerous isotopologues, which enables robust estimates of gas properties. We derive nearly constant COM column density ratios that agree with literature values in other low- and high-mass protostellar cores, supporting the idea that COM abundances are set during the pre-stellar phase. In all regions, we identify spatial offsets among different molecular families, due to a combination of source physical structure and chemistry. In particular, we find potential evidence of carbon grain sublimation in G28.20-0.05 and identify an elemental oxygen gradient and rich sulfur-chemistry in G35.58-0.03. Overall, these results demonstrate that the SMA's wide bandwidth is a powerful tool to untangle the complex molecular gas structures associated with massive star formation., Comment: 47 pages, 36 figures, accepted for publication in ApJS. Data and image cubes available at https://zenodo.org/records/13342640

We develop a parametrised model to describe the formation and evolution of massive black holes, designed for comparisons with both electromagnetic and gravitational wave observations. Using an extended Press-Schechter formalism, we generate dark matter halo merger trees. We then seed and evolve massive black holes through parameterised prescriptions. This approach, which avoids solving differential equations, is computationally efficient, enabling us to analyse observational data and infer the parameters of our model in a fully Bayesian framework. We find that observations of the black hole luminosity function are compatible with the nHz gravitational wave signal (likely) measured by PTAs, provided we allow for an increased luminosity function at high redshift ($4-7$), as recently suggested by JWST observations. Our model can simultaneously reproduce the bulk of the $M_*-M_{\rm BH}$ relation at $z-0$, as well as its outliers, something cosmological simulations struggle to do. The inferred model parameters are consistent with expectations from observations and more complex simulations: They favour heavier black hole seeds and short delays between halo and black hole mergers, while requiring supper-Edington accretion episodes lasting a few tens of million years, which in our model are linked to galaxy mergers. We find accretion to be suppressed in the most massive black holes below $z\simeq 2.5$, consistently with the anti-hierarchical growth hypothesis. Finally, our predictions for LISA, although fairly broad, are in agreement with previous models. Our model offers a new perspective on the apparent tensions between the black hole luminosity function and the latest JWST and PTA results. Its flexibility makes it ideal to fully exploit the potential of future gravitational wave observations of massive black hole binaries with LISA., Comment: Update figures

The structure of the normal modes of vibration of rotationally invariant $n$-vortices in the Ginzburg-Landau/Abelian Higgs model is completely unveiled for any value of the coupling constant., Comment: 5 pages, 4 figures

Gamma rays consist of high-energy photons that selectively interact with nuclei, induce and mediate nuclear reactions and elementary particle interactions, and exceed x-rays in penetrating power and thus are indispensable for analysis and modification of dense or compressed object interior. Yet, the available gamma sources lack power and brightness which, if available, would revolutionize science and technology. The predicted laser-driven Gamma Flash (GF) would be the highest-power and the brightest terrestrial gamma source with a 30-40% laser-to-gamma energy conversion. It is based on inverse Compton scattering in a laser-solid interaction at irradiance typically above $10^{23}W/cm^2$. GF is one of the motivating goals for the most advanced laser facilities. However, till now GF remains overshadowed by simultaneously generated low-brightness Bremsstrahlung. Here we experimentally differentiate these two mechanisms and demonstrate a GF dominant regime producing several times the number of Bremsstrahlung photons. We found steep GF yield growth with the laser power and irradiance. Simulations revealed a Terawatt GF with nanometre source and an attosecond pulse train with a record brightness of $~10^{22}photons/mm^2mrad^2s0.1\%BW$ at up to tens of MeV. The small source size and high brightness paves the way towards spatially coherent gamma rays. At high photon energies, our regime is comparable in brightness to astrophysical Gamma Ray Bursts. We anticipate that the gamma ray source based on our findings will facilitate a breakthrough in research on future inertial fusion energy by enabling high-spatial-resolution time-resolved radiography of fuel mixing instabilities in extremely compressed targets. Such a new compact bright ultrafast gamma source could facilitate significant advances in time-resolved nuclear physics, homeland security, and nuclear waste management and non-proliferation., Comment: 36 pages, 11 figures

There have been several attempts in recent years to extend the notions of symplectic and Poisson structures in order to create a suitable geometrical framework for classical field theories, trying to achieve a success similar to the use of these concepts in Hamiltonian mechanics. These notions always have a graded character, since the multisymplectic forms are of a higher degree than two. Another line of work has been to extend the concept of Dirac structures to these new scenarios. In the present paper we review all these notions, relate them and propose and study a generalization that (under some mild regularity conditions) includes them and is of graded nature. We expect this generalization to allow us to advance in the study of classical field theories, their integrability, reduction, numerical approximations and even their quantization.

In this paper methods for deforming scalar field theories on Euclidean target spaces, in which new field theories are constructed so that solutions are known, are generalized to the context of Sigma models. In particular, deformations between Sigma models on the plane and on the sphere are considered. Three different examples are presented, where the change in the structure of the kink variety and the energy of the deformed kinks during this procedure are studied., Comment: 23 pages, 20 figures

Particle-producing targets in high-energy research facilities are often made from refractory metals, and they typically require dedicated cooling systems due to the challenging thermomechanical conditions they experience. However, direct contact of water with target blocks can induce erosion, corrosion, and embrittlement, especially of tungsten (W). One approach to overcoming this problem is cladding the blocks with tantalum (Ta). Unfortunately, Ta generates high decay heat when irradiated, raising safety concerns in the event of a loss-of-cooling accident. This study explored the capacity of niobium (Nb) and its alloys to form diffusion bonds with W and TZM (a molybdenum alloy with titanium and zirconium). This is because the Beam Dump Facility (BDF), a planned new fixed-target installation in CERN's North Area, uses these target materials. The bonding quality of pure Nb, Nb1Zr, and C103 (a Nb alloy with 10% hafnium and 1% titanium) with TZM and W obtained using hot isostatic pressing (HIP) was evaluated. The effects of different HIP temperatures and the introduction of a Ta interlayer were examined. Optical microscopy indicated promising bonding interfaces, which were further characterized using tensile tests and thermal-diffusivity measurements. Their performance under high-energy beam impact was validated using thermomechanical simulations. C103 exhibited higher interface strengths and safety factors than Ta2.5W, positioning it as a potential alternative cladding material for the BDF production target. The findings highlight the viability of Nb-based materials, particularly C103, for improving operational safety and efficiency in fixed-target physics experiments; however, considerations regarding the long half-life of 94Nb require further attention.

The Beam Dump Facility (BDF) is a planned fixed-target installation in CERN's North Area, set to start operating in 2031. A proton beam of 400 GeV/c will be delivered in 1 s pulses of 4e13 protons every 7.2 s, amounting to 4e19 protons on target (PoT) per year, with an average thermal power deposition of 305 kW. The experiment requires high-Z and high-density materials and involves challenging thermomechanical conditions; hence, a water-cooled refractory metal core is proposed. To prevent corrosion and erosion, the target materials - tungsten and a molybdenum-based alloy, TZM-, are clad with a tantalum alloy using hot isostatic pressing. To verify the reliability of the target design and manufacturing process, a reduced-scale prototype target was manufactured and irradiated with 2.4e16 PoT in 2018. This paper presents the findings of the post-irradiation examination (PIE) conducted 2.5 years later. The PIE consisted of non-destructive and destructive activities, including film imaging, microscopy, metrology, ultrasonic testing, microstructural analysis, and mechanical and thermal characterization. No irradiation effects resulting from thermal stresses, such as geometrical changes or cracks in the cladding, were observed, and it was determined that the bonding between the core and cladding materials was robust. Moreover, no changes were detected in the microstructures or mechanical properties of the bulk materials. In conclusion, the robustness of the target baseline design and manufacturing process was confirmed, validating its suitability for operating under the desired conditions. Nonetheless, the observed brittleness of sintered tungsten indicates a potential area for improvement to enhance the lifetime of the BDF target. Overall, the examinations provided valuable insights into the performance of the prototype and indicated potential refinements for the future BDF target complex.

Software repositories is one of the sources of data in Empirical Software Engineering, primarily in the Mining Software Repositories field, aimed at extracting knowledge from the dynamics and practice of software projects. With the emergence of social coding platforms such as GitHub, researchers have now access to millions of software repositories to use as source data for their studies. With this massive amount of data, sampling techniques are needed to create more manageable datasets. The creation of these datasets is a crucial step, and researchers have to carefully select the repositories to create representative samples according to a set of variables of interest. However, current sampling methods are often based on random selection or rely on variables which may not be related to the research study (e.g., popularity or activity). In this paper, we present a methodology for creating representative samples of software repositories, where such representativeness is properly aligned with both the characteristics of the population of repositories and the requirements of the empirical study. We illustrate our approach with use cases based on Hugging Face repositories., Comment: The paper has been accepted for publication in the Proceedings of the 18th International Symposium on Empirical Software Engineering and Measurement (ESEM 2024)

Label-free single-molecule detection is essential for studying biomolecules in their native state, yet having materials with intrinsic molecular specificity to identify a broad range of molecules without complex functionalization remains challenging. We present a method that utilizes emissions from selectively activated defects at the aqueous hexagonal boron nitride (hBN) interface to detect and identify biomolecules, including lipids, nucleotides, and amino acids. Using spectrally-resolved single-molecule localization microscopy combined with machine learning, we harvest spatial, spectral and temporal data of individual events to uncover optical fingerprints of biomolecules. This approach allows us to probe fine chemical differences, as small as the single deprotonation of an amino acid's side chain and detect dynamics of biomolecules at the interface with exceptional detail. As a proof-of-concept, we identified five different amino acids at the single-molecule level with high accuracy. Our findings shed light on hBN-biomolecule interactions and highlight the potential of hBN for label-free single-molecule identification.

Superconductors exhibit remarkable properties such as zero resistivity and diamagnetism at the boiling temperature of liquid hydrogen (20 K) and even aboven the boiling temperature of liquid nitrogen (77 K), making them promising candidates for various applications including electrical engines, energy generation, storage, and high-tech devices like single photon detectors. In this overview, we explore the correlation between ceramic superconductors and the United Nations (UN) Development Goals, emphasizing their potential impact on sustainable development. Through bibliometric analysis, we underscore the significance of ceramic superconductors in addressing global challenges outlined by the UN. Additionally, we discuss the application of supermagnets and second-generation tapes in healthcare systems, particularly in magnetic resonance imaging (MRI) devices for diagnostic imaging. Electric superconducting motors offer a clean alternative to highly polluting diesel engines in maritime transportation and superconducting wires/cables enable effective transport of energy on large scale as well as in industrial structures. Magnetic levitation technology holds promise for developing zero-emission public transportation systems, and magnetic separation with strong magnets will contribute to solve the microplastic pollution. The combination of superconductivity with the planned hydrogen economy further offers new possibilities to bring superconductivity to common applications. At the nanoscale, superconducting nanowire single photon detectors (SNSPDs) enable real-time monitoring of environmental health, exemplified by applications in plant physiology, and superconducting qubits provide the best-engineered structures for quantum computers. However it is still crordwork to works with superconductors UN develepoment goals., Comment: 51 pages, 17 figures, 7 tables, Review paper based on bibliometry

We present a surrogate numerical-relativity model for close hyperbolic black-hole encounters with equal masses and spins aligned with the orbital momentum. Our model, generated in terms of the Newman-Penrose scalar $\psi_4$, spans impact parameters $b/M\in [11, 15]$ and spin components $\chi_{i} \in [-0.5,0.5]$, modeling the $(\ell,m)=(2,0)$, $(2, \pm 2)$, $(3,\pm 2)$ and $(4,\pm 4)$ emission multipoles. The model is faithful to numerical relativity simulations, yielding mismatches lower than $10^{-3}$. We test the ability of our model to recover the parameters of numerically simulated signals. We find that, despite the high accuracy of the model, parameter inference struggles to correctly capture the parameters of the source even for SNRs as large as 50 due to the strong degeneracies present in the parameter space. This indicates that correctly identifying these systems will require of extremely large signal loudness, only typical of third generation detectors. Nevertheless, we also find that, if one attempts to infer certain combinations of such degenerated parameters, there might be a chance to prove the existence of this type of events, even with the current ground-based detectors, as long as these combinations make sense astrophysically and cosmologically., Comment: 18 pages, 15 figures

We present the Planetary Enriched White Dwarf Database (PEWDD), a collection of published photospheric abundances of white dwarfs accreting planetary debris alongside additional information relevant to metal-enrichment and the presence of infrared excesses, emission lines, and binary companions. PEWDD contains at the time of publishing information on 1739 white dwarfs and will be kept up-to-date with information from new publications. A total of 24 photospheric metals are recorded and are linked to accretion of exo-planetary material. The overall properties of metal-enriched white dwarfs are severely affected by observational selection effects; in particular we find that what metals are detectable strongly correlates with the effective temperature. By considering metal-enriched white dwarfs which have abundances measured by different methods, we find a spread that is comparable with the often quoted ad-hoc estimated abundance uncertainties, i.e. ~0.1-0.2dex. We draw attention to a dichotomy in the median accretion rates for metal-enriched H- and He-dominated white dwarfs, with M_{acc, H} = 7.7e7g/s and M_{acc, He} = 8.7e8g/s when extrapolating bulk compositions from bulk Earth Ca abundance. We identify 40 metal-enriched white dwarfs in binary systems and find evidence that enrichment is suppressed by binary companions within 200au., Comment: 19 pages, 13 figures, 2 tables + appendix. Accepted for publication in A&A

Massive black-hole binaries will be the loudest sources detectable by LISA. These systems are predicted to form during the hierarchical assembly of cosmic structures and coalesce by interacting with the surrounding environment. The hardening phase of their orbit is driven by either stars or gas and encodes distinctive features into the binary black holes that can potentially be reconstructed with gravitational-wave observations. We present a Bayesian framework to assess the likelihood of massive mergers being hardened by either gaseous or stellar interactions. We use state-of-the-art astrophysical models tracking the cosmological evolution of massive black-hole binaries and construct a large number of simulated catalogs of sources detectable by LISA. From these, we select a representative catalog and run both parameter estimation assuming a realistic LISA response as well model comparison capturing selection effects. Our results suggest that, at least within the context of the adopted models, future LISA observations can confidently constrain whether stars or gas are responsible for the binary hardening. We stress that accurate astrophysical modeling of the black-hole spins and the inclusion of subdominant emission modes in the adopted signal might be crucial to avoid systematic biases., Comment: 10 pages, 6 figures (submitted to Physical Review D)

Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective management. This paper pioneers the development of a Marine Digital Twin Platform aimed at modeling the Mar Menor Coastal Lagoon Ecosystem in the Region of Murcia. The platform leverages Artificial Intelligence to emulate complex hydrological and ecological models, facilitating the simulation of what-if scenarios to predict ecosystem responses to various stressors. We integrate diverse datasets from public sources to construct a comprehensive digital representation of the lagoon's dynamics. The platform's modular design enables real-time stakeholder engagement and informed decision-making in marine management. Our work contributes to the ongoing discourse on advancing marine science through innovative digital twin technologies.

A new determination of the molar gas constant was performed from measurements of the speed of sound in argon at the triple point of water and extrapolation to zero pressure. A new resonant cavity was used. This is a triaxial ellipsoid whose walls are gold-coated steel and which is divided into two identical halves that are bolted and sealed with an O-ring. Microwave and electroacoustic traducers are located in the northern and southern parts of the cavity, respectively, so that measurements of microwave and acoustic frequencies are carried out in the same experiment. Measurements were taken at pressures from 600 kPa to 60 kPa and at 273.16 K. The internal equivalent radius of the cavity was accurately determined by microwave measurements and the first four radial symmetric acoustic modes were simultaneously measured and used to calculate the speed of sound. The improvements made using the new cavity have reduced by half the main contributions to the uncertainty due to the radius determination using microwave measurements which amounts to 4.7 parts in $10^{6}$ and the acoustic measurements, 4.4 parts in $10^{6}$, where the main contribution (3.7 parts in $10^{6}$) is the relative excess half-widths associated with the limit of our acoustic model, compared with our previous measurements. As a result of all the improvements with the new cavity and the measurements performed, we determined the molar gas constant $R$ = (8.314 449 $\pm$ 0.000 056) J/(K mol) which corresponds to a relative standard uncertainty of 6.7 parts in $10^{6}$. The value reported in this paper lies -1.3 parts in $10^{6}$ below the recommended value of CODATA 2014, although still within the range consistent with it.

In the last years, model-related publications have been exploring the application of modeling techniques in different domains. Initially focused on UML and the Model-Driven Architecture approach, the literature has been evolving towards the usage of more general concepts such as Model-Driven Development or Model-Driven Engineering. With the emergence of Low-Code software development platforms, the modeling community has been studying how these two fields may combine and benefit from each other, thus leading to the publication of a number of works in recent years. In this paper, we present a metascience study of Low-Code. Our study has a two-fold approach: (1) to examine the composition (size and diversity) of the emerging Low-Code community; and (2) to investigate how this community differs from the "classical" model-driven community in terms of people, venues, and types of publications. Through this study, we aim to benefit the low-code community by helping them better understand its relationship with the broader modeling community. Ultimately, we hope to trigger a discussion about the current and possible future evolution of the low-code community as part of its consolidation as a new research field.

This paper presents a novel joint neural networks approach to address the challenging one-shot object recognition and detection tasks. Inspired by Siamese neural networks and state-of-art multi-box detection approaches, the joint neural networks are able to perform object recognition and detection for categories that remain unseen during the training process. Following the one-shot object recognition/detection constraints, the training and testing datasets do not contain overlapped classes, in other words, all the test classes remain unseen during training. The joint networks architecture is able to effectively compare pairs of images via stacked convolutional layers of the query and target inputs, recognising patterns of the same input query category without relying on previous training around this category. The proposed approach achieves 61.41% accuracy for one-shot object recognition on the MiniImageNet dataset and 47.1% mAP for one-shot object detection when trained on the COCO dataset and tested using the Pascal VOC dataset. Code available at https://github.com/cjvargasc/JNN recog and https://github.com/cjvargasc/JNN detection/, Comment: published as part of the PhD thesis: https://qmro.qmul.ac.uk/xmlui/handle/123456789/72758

We analyze the entanglement generation in a pair of qubits that experience the vacuum fluctuations of a scalar field in the Cosmic String spacetime. The qubits are modeled as Unruh-DeWitt detectors coupled to a massless scalar field. We introduce a Heisenberg $XY$-interaction between the qubits that enhances the generation of quantum correlations. It is supposed that the qubits begin at a general mixed state described by a density operator with no entanglement while the field stays at its vacuum state. In this way, we find the general properties and conditions to create entanglement between the qubits by exploiting the field vacuum fluctuations. We quantify the qubits entanglement using the Negativity measure based on the Peres-Horodecki positive partial transpose criterion. We find that the Cosmic String would increase the entanglement harvesting when both qubits are near the Cosmic String. When the qubits locations are far from the Cosmic String we recover the usual results for Minkowski space. The Heisenberg $XY$-interaction enhance the entanglement harvesting irrespective of the coupling nature (ferromagnetic or anti-ferromagnetic). When the qubits are far apart from each other we find a maximum entanglement harvesting at the resonance points between the Heisenberg coupling constant and the qubits energy gap., Comment: 54 pages, 29 figures

The defect-type solutions of a deformed $O(2N+1)$ linear sigma model with a real and $N$ complex fields in $(1+1)$-dimensional Minkowski spacetime are studied. All the solutions are analytically found for the $N=2$ case. Two types of solitons have been determined: (a) Simple solutions formed by a topological kink with or without the presence of a $Q$-ball. (b) Composite solutions. They are constituted by some one-parameter families of solutions which can be understood as a non-linear combination of simple solutions. The properties of all of those solutions and the analysis of their linear stability, as well as decay channels, are discussed., Comment: 24 pages, 42 figures

Pulsar Timing Array (PTA) collaborations reported evidence of a nano-Hz stochastic gravitational wave background (sGWB) compatible with an adiabatically inspiraling population of massive black hole binaries (MBHBs). Despite the large uncertainties, the relatively flat spectral slope of the recovered signal suggests a possible prominent role of MBHB dynamical coupling with the environment or/and the presence of an eccentric MBHB population. This work aims at studying the capabilities of future PTA experiments to detect single MBHBs under the realistic assumption that the sGWB is originated from an eccentric binary population coupled with its environment. To this end, we generalize the standard signal-to-noise ratio (SNR) and Fisher Information Matrix calculations used in PTA for circular MBHBs to the case of eccentric systems. We consider an ideal 10-year MeerKAT and 30-year SKA PTAs and apply our method over a wide number of simulated eccentric MBHB populations. We find that the number of resolvable MBHBs for the SKA (MeerKAT) PTA is ${\sim}\,30$ ($4$) at $\rm SNR\,{>}\,5$ (${>}\,3$), featuring an increasing trend for larger eccentricity values of the MBHB population. This is the result of eccentric MBHBs at ${\lesssim}\,10^{-9}\, \rm Hz$ emitting part of their power at high harmonics, thus reaching the PTA sensitivity band. Our results also indicate that resolved MBHBs do not follow the eccentricity distribution of the underlying MBHB population, but prefer low eccentricity values (${<}\,0.6$). Finally, the recovery of binary intrinsic properties and sky-localization do not depend on the system eccentricity, while orbital parameters such as eccentricity and initial orbital phase show clear trends. Although simplified, our results show that SKA will enable the detection of tens of MBHBs, projecting us into the era of precision gravitational wave astronomy at nano-Hz frequencies., Comment: 17 pages, 11 figures, submitted to A&A

The resonant energy transfer mechanism, responsible for the presence of fractal patterns in the velocity diagrams of kink-antikink scattering, is analyzed for a family of two-component scalar field theory models, in which the kink solutions have two shape modes (one longitudinal and one orthogonal to the kink orbit), in addition to the zero mode, and in which energy redistribution can occur among these three discrete modes. We investigate the scattering between wobbling kinks whose orthogonal shape mode is initially excited, examining how the final velocities, amplitudes, and frequencies depend on the initial excitation amplitude. The differences that this model presents with respect to the $\phi^4$ model and its novel properties are highlighted. This analysis sheds light on the intricate dynamics that arise from the interplay between multiple degrees of freedom in kink scattering processes, offering insights distinct from those observed in simpler models., Comment: 20 pages, 11 figures

In the field of autonomous driving research, the use of immersive virtual reality (VR) techniques is widespread to enable a variety of studies under safe and controlled conditions. However, this methodology is only valid and consistent if the conduct of participants in the simulated setting mirrors their actions in an actual environment. In this paper, we present a first and innovative approach to evaluating what we term the behavioural gap, a concept that captures the disparity in a participant's conduct when engaging in a VR experiment compared to an equivalent real-world situation. To this end, we developed a digital twin of a pre-existed crosswalk and carried out a field experiment (N=18) to investigate pedestrian-autonomous vehicle interaction in both real and simulated driving conditions. In the experiment, the pedestrian attempts to cross the road in the presence of different driving styles and an external Human-Machine Interface (eHMI). By combining survey-based and behavioural analysis methodologies, we develop a quantitative approach to empirically assess the behavioural gap, as a mechanism to validate data obtained from real subjects interacting in a simulated VR-based environment. Results show that participants are more cautious and curious in VR, affecting their speed and decisions, and that VR interfaces significantly influence their actions., Comment: Paper submitted to International Journal of Human Computer Interaction

Visual Place Recognition (VPR) plays a critical role in many localization and mapping pipelines. It consists of retrieving the closest sample to a query image, in a certain embedding space, from a database of geotagged references. The image embedding is learned to effectively describe a place despite variations in visual appearance, viewpoint, and geometric changes. In this work, we formulate how limitations in the Geographic Distance Sensitivity of current VPR embeddings result in a high probability of incorrectly sorting the top-k retrievals, negatively impacting the recall. In order to address this issue in single-stage VPR, we propose a novel mining strategy, CliqueMining, that selects positive and negative examples by sampling cliques from a graph of visually similar images. Our approach boosts the sensitivity of VPR embeddings at small distance ranges, significantly improving the state of the art on relevant benchmarks. In particular, we raise recall@1 from 75% to 82% in MSLS Challenge, and from 76% to 90% in Nordland. Models and code are available at https://github.com/serizba/cliquemining.

Model-Driven Engineering (MDE) is a software engineering methodology focusing on models as primary artifacts. In the last years, the emergence of Web technologies has led to the development of Web-based modeling tools and model-based approaches for the Web that offer a web-based environment to create and edit models or model-based low-code solutions. A common requirement when developing Web-based modeling tools is to provide a fast and efficient way for model management, and this is particularly a hot topic in model-based system engineering. However, the number of approaches offering RESTful services for model management is still limited. Among the alternatives for developing distributed services, there is a growing interest in the use of RESTful services. In this paper, we present an approach to provide RESTful services for model management that can be used to interact with any kind of model and can be used to build a modeling platform providing modeling-as-a-service. The approach follows the REST principles to provide a stateless and scalable service., Comment: 3 pages, 1 figure, 1 table

Filaments connecting halos are a long-standing prediction of cold dark matter theories. We present a detection of the cosmic web emission connecting two quasar-host galaxies at redshift z ~3.22 in the MUSE Ultra Deep Field (MUDF). The very deep observations unlock a high-definition view of the filament morphology, a measure of the transition radius between the intergalactic and circumgalactic medium, and the characterization of the surface brightness profiles along the filament and in the transverse direction. Through systematic comparisons with simulations, we validate the filaments' typical density predicted in the current cold dark-matter model. Our analysis of the MUDF field, an excellent laboratory for quantitatively studying filaments in emission, opens a new avenue to constrain the physical properties of the cosmic web and to trace the distribution of dark matter on large scales., Comment: 4 main figures and 1 table; 7 extended data figures; 1 extended data table

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA's work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes., Comment: 27 pages, 0 figures

Surface Acoustic Waves (SAW) have been used frequently in spintronic applications, mostly to decrease the magnetic field or the electric current required to move magnetic domain walls (DW). Because the SAW cannot achieve magnetic switching without the assistance of a magnetic field or a current, for a marginal improvement in the energy required for the magnetic switching, the device gains in complexity, making it impractical. In this work, we report a mechanism that allows a transfer of linear momentum from the acoustic wave to the magnetic domain wall. Experimentally we show that, using the appropriate dimensions of the magnetic strip, the SAW can move the DW in the same direction as the traveling SAW. With the help of micromagnetic simulations, we reveal a complex yet direct mechanism that allows the SAW to push the DW in the same direction of its travel, even without any external field or currents. The DW can reach velocities in the range of 100 m/s and at a very small energetic cost, equivalent to using a current density of $\sim 5 \cdot 10^4 A/cm^2$ if the movement was triggered by spin transfer. This new mechanism opens the door to designing innovative spintronic devices where the magnetization can be controlled exclusively by an acoustic wave., Comment: 11 pages, 5 figures. Submitted to Nature Communications

Surface operators are nonlocal probes of gauge theories capable of distinguishing phases that are not discernible by the classic Wilson-'t Hooft criterion. We prove that the correlation function of a surface operator with a chiral primary operator in ${\cal N}=4$ super Yang-Mills is a finite polynomial in the Yang-Mills coupling constant. Surprisingly, in spite of these observables receiving nontrivial quantum corrections, we find that these correlation functions are exactly captured in the 't Hooft limit by supergravity in asymptotically $AdS_5\times S^5$ [1]! We also calculate exactly the surface operator vacuum expectation value and the correlator of a surface operator with 1/8-BPS Wilson loops using supersymmetric localization. We demonstrate that these correlation functions in ${\cal N}=4$ SYM realize in a nontrivial fashion the conjectured action of $S$-duality. Finally, we perturbatively quantize ${\cal N}=4$ SYM around the surface operator singularity and identify the Feynman diagrams that when summed over reproduce the exact result obtained by localization., Comment: 83 pages, 8 figures

We find a spectral wall in collisions of two vortices in the Abelian Higgs model at the critical coupling. It occurs if the out-of-phase mode of initially separated vortices is excited., Comment: 6 pages, 4 figures and ancillary files (5 videos)

Predicting the risk of death for chronic patients is highly valuable for informed medical decision-making. This paper proposes a general framework for dynamic prediction of the risk of death of a patient given her hospitalization history, which is generally available to physicians. Predictions are based on a joint model for the death and hospitalization processes, thereby avoiding the potential bias arising from selection of survivors. The framework accommodates various submodels for the hospitalization process. In particular, we study prediction of the risk of death in a renewal model for hospitalizations, a common approach to recurrent event modelling. In the renewal model, the distribution of hospitalizations throughout the follow-up period impacts the risk of death. This result differs from prediction in the Poisson model, previously studied, where only the number of hospitalizations matters. We apply our methodology to a prospective, observational cohort study of 512 patients treated for COPD in one of six outpatient respiratory clinics run by the Respiratory Service of Galdakao University Hospital, with a median follow-up of 4.7 years. We find that more concentrated hospitalizations increase the risk of death., Comment: 29 pages, 5 tables, 3 figures

Models are developed for the motion of charge-2 Abelian Higgs vortices through the 2-vortex moduli space $M$, with the vortices excited by their shape mode oscillations. The models simplify to the well-known geodesic flow on $M$, modified by a potential, when the mode oscillations are fast relative to the moduli space motion and their amplitudes are small. When the lowest-frequency mode is excited with a large amplitude, the geodesic flow is not a correct description. Instead, a chaotic, or even fractal, multi-bounce structure in vortex-vortex collisions is predicted., Comment: 24 pages, 6 figures

Detecting protoplanets during their formation stage is an important but elusive goal of modern astronomy. Kinematic detections via the spiral wakes in the gaseous disc are a promising avenue to achieve this goal. We aim to test the applicability to observations in the low and intermediate planet mass regimes of a commonly used semi-analytical model for planet induced spiral waves. In contrast with previous works which proposed to use the semi-analytical model to interpret observations, in this study we analyse for the first time both the structure of the velocity and density perturbations. We run a set of FARGO3D hydrodynamic simulations and compare them with the output of the semi-analytic model in the code wakeflow, which is obtained by solving Burgers' equation using the simulations as an initial condition. We find that the velocity field derived from the analytic theory is discontinuous at the interface between the linear and nonlinear regions. After 0.2 r$_p$ from the planet, the behaviour of the velocity field closely follows that of the density perturbations. In the low mass limit, the analytical model is in qualitative agreement with the simulations, although it underestimates the azimuthal width and the amplitude of the perturbations, predicting a stronger decay but a slower azimuthal advance of the shock fronts. In the intermediate regime, the discrepancy increases, resulting in a different pitch angle between the spirals of the simulations and the analytic model. The implementation of a fitting procedure based on the minimisation of intensity residuals is bound to fail due to the deviation in pitch angle between the analytic model and the simulations. In order to apply this model to observations, it needs to be revisited accounting also for higher planet masses., Comment: 10 pages, 7 figures. Accepted for publication in A&A May 27, 2024

In this paper we study coisotropic reduction in multisymplectic geometry. On the one hand, we give an interpretation of Hamiltonian multivector fields as Lagrangian submanifolds and prove that $k$-coisotropic submanifolds induce a Lie subalgebra in the algebra of Hamiltonian $(k-1)$-forms, similar to how coisotropic submanifolds in symplectic geometry induce a Lie subalgebra under the Poisson bracket. On the other hand, we extend the classical result of symplectic geometry of projection of Lagrangian submanifolds in coisotropic reduction to bundles of forms, which naturally carry a multisymplectic structure.

V892 Tau is a young binary star surrounded by a circumbinary disc which show hints of interaction with the low-mass nearby star V892 Tau NE. The goal of this paper is to constrain the orbit of V892 Tau NE and to determine the resulting circumbinary disc dynamics. We present new ALMA observations of the V892 Tau circumbinary disc at a twice higher angular and spectral resolution. We model the data with V892 Tau as a triple system and perform a grid of hydrodynamical simulations testing several orbits of the companion. The simulation outputs are then post-processed to build synthetic maps that we compare to the observations. The 12CO emission of the disc shows clear non-Keplerian features such as spiral arms. When comparing the data with our synthetic observations, we interpret these features as ongoing interactions with the companion. Our simulations indicate that an eccentricity of 0.5 of the companion is needed to reproduce the observed disc extent and that a mutual inclination of approximately 60{\deg} with the inner binary reproduces the measured disc tilt. In order to explain most of the features of the circumbinary disc, we propose that V892 Tau NE follows a misaligned eccentric orbit, with an eccentricity between 0.2 and 0.5 and a mutual inclination between 30{\deg} and 60{\deg}. Such a misaligned companion suggests the disc is oscillating and precessing with time, stabilising in an intermediate plane with a non-zero mutual inclination with the inner binary. Given that orbital configuration, we show that the stability of future planets is compromised in the second half of the disc once the gas has dissipated., Comment: Published in A&A, 29 pages, 15 figures

The evolution of 1-vortices when their massive bound mode is excited is investigated in detail (both analytically and numerically) in the Abelian-Higgs model for different ranges of the self-coupling constant. The dependence of the spectrum of the 1-vortex fluctuation operator on the model parameter is discussed initially. A perturbative approach is employed to study the radiation emission in both the scalar and the vector channels. Our findings reveal that the oscillating initial configuration of the 1-vortex radiates at a frequency twice that of the internal mode. Through energy conservation considerations, we derive the decay law of the massive mode. Finally, these analytical results are compared with numerical simulations in field theory., Comment: 16 pages, 10 figures

Prediction of road users' behaviors in the context of autonomous driving has gained considerable attention by the scientific community in the last years. Most works focus on predicting behaviors based on kinematic information alone, a simplification of the reality since road users are humans, and as such they are highly influenced by their surrounding context. In addition, a large plethora of research works rely on powerful Deep Learning techniques, which exhibit high performance metrics in prediction tasks but may lack the ability to fully understand and exploit the contextual semantic information contained in the road scene, not to mention their inability to provide explainable predictions that can be understood by humans. In this work, we propose an explainable road users' behavior prediction system that integrates the reasoning abilities of Knowledge Graphs (KG) and the expressiveness capabilities of Large Language Models (LLM) by using Retrieval Augmented Generation (RAG) techniques. For that purpose, Knowledge Graph Embeddings (KGE) and Bayesian inference are combined to allow the deployment of a fully inductive reasoning system that enables the issuing of predictions that rely on legacy information contained in the graph as well as on current evidence gathered in real time by onboard sensors. Two use cases have been implemented following the proposed approach: 1) Prediction of pedestrians' crossing actions; 2) Prediction of lane change maneuvers. In both cases, the performance attained surpasses the current state of the art in terms of anticipation and F1-score, showing a promising avenue for future research in this field.

In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicle-to-Vehicle (V2V) enabled track management system that leverages the synergy between V2V signals and detections from radar and camera sensors. The core innovation lies in the creation of independent priority track lists, consisting of fused detections validated through V2V communication. This approach enables more flexible and resilient thresholds for track management, particularly in scenarios with numerous occlusions where the tracked objects move outside the field of view of the perception sensors. The proposed system considers the implications of falsification of V2X signals which is combated through an initial vehicle identification process using detection from perception sensors. Presented are the fusion algorithm, simulated environments, and validation mechanisms. Experimental results demonstrate the improved accuracy and robustness of the proposed system in common driving scenarios, highlighting its potential to advance the reliability and efficiency of autonomous vehicles., Comment: 6 pages, 5 figures

Methods for clustering people into construals--social affinity groups of individuals who share similarities in how they organize their outlooks on a collection of issues--have recently gained traction. Relational Class Analysis (RCA) is currently the most commonly used method for construal clustering. RCA has been applied to identify affinity groups in social spheres as varied as politics, musical preferences, and attitudes towards science. In this study, we highlight limitations in RCA's ability to accurately identify the number and underlying structure of construals. These limitations stem from RCA's mathematical underpinnings and its insensitivity to the bipolar structure of the survey items, which require respondents to place themselves in a support or rejection space and then express the intensity of their support or rejection. We develop an alternative method, which we call Bipolar Class Analysis (BCA), that aims to address this foundational limitation. BCA conceptualizes people's attitudinal positions as moving along support/rejection semispaces and assesses similarity in opinion organization by taking into account position switches across these semispaces. We conduct extensive simulation analyses, with data organized around different construals, to demonstrate that BCA clusters individuals more accurately than RCA and other available alternatives. We also replicate previous analyses to show that BCA leads to substantively different empirical results than those produced by RCA in its original and later versions, and by Correlational Clustering Analysis (CCA), a method that has been proposed as an alternative to RCA.

A population of non-stellar black holes ($\gtrsim$100 M$_{\odot}$) has been long predicted to wander the Milky Way. We aim to characterize this population by using the L-Galaxies semi-analytical model applied on top of the high resolution Millennium-II merger trees. Our results predict $\sim$10 wandering black holes with masses $\sim$2 $\times$ 10$^{3}$ M$_{\odot}$ in a typical $z$ = 0 Milky Way galaxy, accounting for $\sim$2$\%$ of the total non-stellar black hole mass budget of the galaxy. We find that the locations of these wanderers correlate with their formation scenario. While the ones concentrated at $\lesssim$1 kpc from the galactic nucleus on the disk come from past galactic mergers, the ones formed as a consequence of ejections due to gravitational recoils or the disruption of satellite galaxies are typically located at $\gtrsim$100 kpc. Such small and large distances might explain the absence of strong observational evidence for wandering black holes in the Milky Way. Our results also indicate that $\sim$67$\%$ of the wandering population is conformed by the leftovers of black hole seeds that had little to no growth since their formation. We find that wandering black holes that are leftover seeds become wanderers at an earlier time with respect to grown seeds, and also come from more metal-poor galaxies. Finally, we show that the number of wandering black holes in a Milky Way-type galaxy depends on the seeding efficiency., Comment: Accepted for publication in MNRAS, 14 pages, 9 figures