Search

In the context of the rapid dissemination of multimedia content, identifying disinformation on social media platforms such as TikTok represents a significant challenge. This study introduces a hybrid framework that combines the computational power of deep learning with the interpretability of fuzzy logic to detect suspected disinformation in TikTok videos. The methodology is comprised of two core components: a multimodal feature analyser that extracts and evaluates data from text, audio, and video; and a multimodal disinformation detector based on fuzzy logic. These systems operate in conjunction to evaluate the suspicion of spreading disinformation, drawing on human behavioural cues such as body language, speech patterns, and text coherence. Two experiments were conducted: one focusing on context-specific disinformation and the other on the scalability of the model across broader topics. For each video evaluated, high-quality, comprehensive, well-structured reports are generated, providing a detailed view of the disinformation behaviours.

This article presents a review about the main CERN n\_TOF contributions to the field of neutron-capture experiments of interest for $s$-process nucleosynthesis studies over the last 25 years, with special focus on the measurement of radioactive isotopes. A few recent capture experiments on stable isotopes of astrophysical interest are also discussed. Results on $s$-process branching nuclei are appropriate to illustrate how advances in detection systems and upgrades in the facility have enabled increasingly challenging experiments and, as a consequence, have led to a better understanding and modeling of the $s$-process mechanism of nucleosynthesis. New endeavors combining radioactive-ion beams from ISOLDE for the production of radioisotopically pure samples for activation experiments at the new NEAR facility at n\_TOF are briefly discussed. On the basis of these new exciting results, also current limitations of state-of-the-art TOF and activation techniques will be depicted, thereby showing the pressing need for further upgrades and enhancements on both facilities and detection systems. A brief account of the potential technique based on inverse kinematics for direct neutron-capture measurements is also presented., Comment: submitted to Eur. Phys. Jour. Topical Collection

Current axion detection limits neglect the relevance of the relative velocity between the axion field and the detectors. However, this aspect can lead to a daily modulation of the detected axion signal. In this work, we calculate the cross-correlation of various signals potentially originated in multiple-cavity setups, and we analyze how the signal-to-noise ratio and directional sensitivity depend on the signal cross-correlation among multiple cavities. The signal-to-noise ratio after cross-correlation exhibits a greater rate of increase over time compared to the power-summation technique, making it clear that this method could be potentially employed in a real setup for the reduction of the exposure time. For the study of the daily modulation, three interferometric experiments have been proposed in this manuscript: (i) three rectangular cavities in different Earth locations; (ii) three rectangular cavities located in the same Earth spot but oriented towards different perpendicular directions; (iii) six rectangular cavities in the same Earth location but oriented towards different directions. In each set-up, we have simulated three different cavity lengths. Similar results have been found for the cases (i) and (ii): when the highest length upon the three proposed is considered, a phase difference between the recorded voltages of more than $2^{\circ}$ has been obtained with our numerical calculations. We observe a daily modulation in the imaginary part of the signals cross-correlation for experiment (iii), that could be potentially used for the characterization of the axion velocity distribution. To the knowledge of the authors, this is the first time that the cross-correlation technique has been applied to the directional sensitivity analysis of an array of haloscopes., Comment: 29 pages, 19 figures

One of the instruments aboard the Sunrise III mission, the Tunable Magnetograph (TuMag), is a tunable imaging spectropolarimeter in visible wavelengths. It is designed to probe the vector magnetic field and the line-of-sight velocity of the photosphere and the lower chromosphere. The quasi-simultaneous observation of two spectral lines provides excellent diagnostic measurements of the magnetic and dynamic coupling in these layers. The key technologies employed for TuMag are an LCVR-based polarimeter and a solid, LiNbO3 Fabry-P\'erot etalon as a spectrometer. However, it also incorporates several innovative features, such as home-made high-sensitivity scientific cameras and a double filter wheel. TuMag can sequentially observe any two out of the three spectral lines of Fe I at 525.02 and 525.06 nm and of Mg I at 517.3 nm. Laboratory measurements have demonstrated outstanding performance, including a wavefront root-mean-square error better than {\lambda}/13 for image quality, a full-width-at-half-maximum of 8.7 pm for the filtergraph transmission profile, and polarimetric efficiencies > 0.54. Here we report on the concept, design, calibration, and integration phases of the instrument, as well as on the data reduction pipeline., Comment: Contains 58 pages and 25 figures; to be published in Solar Physics Topical Collection "The Sunrise III Solar Observatory" (https://link.springer.com/collections/jegdciedig)

Procedural representations are desirable, versatile, and popular shape encodings. Authoring them, either manually or using data-driven procedures, remains challenging, as a well-designed procedural representation should be compact, intuitive, and easy to manipulate. A long-standing problem in shape analysis studies how to discover a reusable library of procedural functions, with semantically aligned exposed parameters, that can explain an entire shape family. We present ShapeLib as the first method that leverages the priors of frontier LLMs to design a library of 3D shape abstraction functions. Our system accepts two forms of design intent: text descriptions of functions to include in the library and a seed set of exemplar shapes. We discover procedural abstractions that match this design intent by proposing, and then validating, function applications and implementations. The discovered shape functions in the library are not only expressive but also generalize beyond the seed set to a full family of shapes. We train a recognition network that learns to infer shape programs based on our library from different visual modalities (primitives, voxels, point clouds). Our shape functions have parameters that are semantically interpretable and can be modified to produce plausible shape variations. We show that this allows inferred programs to be successfully manipulated by an LLM given a text prompt. We evaluate ShapeLib on different datasets and show clear advantages over existing methods and alternative formulations.

In July 2024, Sunrise completed its third successful science flight. The Sunrise III observatory had been upgraded significantly after the two previous successful flights in 2009 and 2013. Three completely new instruments focus on the small-scale physical processes and their complex interaction from the deepest observable layers in the photosphere up to chromospheric heights. Previously poorly explored spectral regions and lines are exploited to paint a three-dimensional picture of the solar atmosphere with unprecedented completeness and level of detail. The full polarimetric information is captured by all three instruments to reveal the interaction between the magnetic fields and the hydrodynamic processes. Two slit- based spectropolarimeters, the Sunrise UV Spectropolarimeter and Imager (SUSI) and the Sunrise Chromospheric Infrared spectro-Polarimeter (SCIP), focus on the near-ultraviolet and the near-infrared regions respectively, and the imaging spectropolarimeter Tunable Magnetograph (TuMag) simultaneously obtains maps of the full field-of-view of $46 \times 46$ Mm$^2$ in the photosphere and the chromosphere in the visible. The instruments are operated in an orchestrated mode, benefiting from a new Image Stabilization and Light Distribution unit (ISLiD), with the Correlating Wavefront Sensor (CWS) providing the autofocus control and an image stability with a root-mean-square value smaller than 0.005''. A new gondola was constructed to significantly improve the telescope pointing stability, required to achieve uninterrupted observations over many hours. Sunrise III was launched successfully on July 10, 2024, from the Esrange Space Center near Kiruna (Sweden). It reached the landing site between the Mackenzie River and the Great Bear Lake in Canada after a flight duration of 6.5 days. In this paper, we give an overview of the Sunrise III observatory and its instruments., Comment: 67 pages, 25 figures; to be published in Solar Physics Topical Collection "The Sunrise III Solar Observatory" (https://link.springer.com/collections/jegdciedig)

We give an explicit characterization of the solid rings of 4th type, finishing a work by Bousfield and Kan in the 70s.

Spectral bias, the tendency of neural networks to prioritize learning low-frequency components of functions during the initial training stages, poses a significant challenge when approximating solutions with high-frequency details. This issue is particularly pronounced in physics-informed neural networks (PINNs), widely used to solve differential equations that describe physical phenomena. In the literature, contributions such as Wavelet Kolmogorov Arnold Networks (Wav-KANs) have demonstrated promising results in capturing both low- and high-frequency components. Similarly, Fourier features (FF) are often employed to address this challenge. However, the theoretical foundations of Wav-KANs, particularly the relationship between the frequency of the mother wavelet and spectral bias, remain underexplored. A more in-depth understanding of how Wav-KANs manage high-frequency terms could offer valuable insights for addressing oscillatory phenomena encountered in parabolic, elliptic, and hyperbolic differential equations. In this work, we analyze the eigenvalues of the neural tangent kernel (NTK) of Wav-KANs to enhance their ability to converge on high-frequency components, effectively mitigating spectral bias. Our theoretical findings are validated through numerical experiments, where we also discuss the limitations of traditional approaches, such as standard PINNs and Fourier features, in addressing multi-frequency problems., Comment: 29 pages, 13 figures

Visual prostheses are designed to restore partial functional vision in patients with total vision loss. Retinal visual prostheses provide limited capabilities as a result of low resolution, limited field of view and poor dynamic range. Understanding the influence of these parameters in the perception results can guide prostheses research and design. In this work, we evaluate the influence of field of view with respect to spatial resolution in visual prostheses, measuring the accuracy and response time in a search and recognition task. Twenty-four normally sighted participants were asked to find and recognize usual objects, such as furniture and home appliance in indoor room scenes. For the experiment, we use a new simulated prosthetic vision system that allows simple and effective experimentation. Our system uses a virtual-reality environment based on panoramic scenes. The simulator employs a head-mounted display which allows users to feel immersed in the scene by perceiving the entire scene all around. Our experiments use public image datasets and a commercial head-mounted display. We have also released the virtual-reality software for replicating and extending the experimentation. Results show that the accuracy and response time decrease when the field of view is increased. Furthermore, performance appears to be correlated with the angular resolution, but showing a diminishing return even with a resolution of less than 2.3 phosphenes per degree. Our results seem to indicate that, for the design of retinal prostheses, it is better to concentrate the phosphenes in a small area, to maximize the angular resolution, even if that implies sacrificing field of view.

Legal texts, characterized by complex and specialized terminology, present a significant challenge for Language Models. Adding an underrepresented language, such as Spanish, to the mix makes it even more challenging. While pre-trained models like XLM-RoBERTa have shown capabilities in handling multilingual corpora, their performance on domain specific documents remains underexplored. This paper presents the development and evaluation of MEL, a legal language model based on XLM-RoBERTa-large, fine-tuned on legal documents such as BOE (Bolet\'in Oficial del Estado, the Spanish oficial report of laws) and congress texts. We detail the data collection, processing, training, and evaluation processes. Evaluation benchmarks show a significant improvement over baseline models in understanding the legal Spanish language. We also present case studies demonstrating the model's application to new legal texts, highlighting its potential to perform top results over different NLP tasks., Comment: 8 pages, 6 figures, 3 tables

Legal corpora for Natural Language Processing (NLP) are valuable and scarce resources in languages like Spanish due to two main reasons: data accessibility and legal expert knowledge availability. INESData 2024 is a European Union funded project lead by the Universidad Polit\'ecnica de Madrid (UPM) and developed by Instituto de Ingenier\'ia del Conocimiento (IIC) to create a series of state-of-the-art NLP resources applied to the legal/administrative domain in Spanish. The goal of this paper is to present the Corpus of Legal Spanish Contract Clauses (3CEL), which is a contract information extraction corpus developed within the framework of INESData 2024. 3CEL contains 373 manually annotated tenders using 19 defined categories (4 782 total tags) that identify key information for contract understanding and reviewing., Comment: 12 pages, 13 figures, 6 tables

We present a systematic investigation of the optical response to circularly polarized illumination in twisted stacked plasmonic nanostructures. The system consissts in two identical, parallel gold triskelia centrally aligned and rotated at a central angle relative to each other. Sample fabrication was acomplished through a double electron beam lithograpy process. This stack holds two plasmonic modes of multipolar character in the near-infrared range, showing a strong dependence of their excitation intensities on the handedness of the circularly polarized incident light. This translates in a large circular dicrhoism which can be modulated by adjusting the twist angle of the stack. Fourier-transform infrared spectroscopy and numerical simulations were employed to characterize the spectral features of the modes. Remarkable, in contrast to previous results in other stacked nanostructures, the system's response exhibits a behavious analogous to that of two interacting dipoles only at small angles. As the angle approaches 15 degrees, where the maximum dichroism is observed, more complex modes of the stack emerge. These modes evolve towards two in-phase multipolar excitations of the two triskelia as the angle increases uo to 60 degrees. Finally, simulations for a triangular array of such stacked elements show a sharp mode arising from the hybridization of a surface lattice resonance with the low-energy mode of the stack.

Maintaining railway axles is critical to preventing severe accidents and financial losses. The railway industry is increasingly interested in advanced condition monitoring techniques to enhance safety and efficiency, moving beyond traditional periodic inspections toward Maintenance 4.0. This study introduces a robust Deep Autoregressive solution that integrates seamlessly with existing systems to avert mechanical failures. Our approach simulates and predicts vibration signals under various conditions and fault scenarios, improving dataset robustness for more effective detection systems. These systems can alert maintenance needs, preventing accidents preemptively. We use experimental vibration signals from accelerometers on train axles. Our primary contributions include a transformer model, ShaftFormer, designed for processing time series data, and an alternative model incorporating spectral methods and enhanced observation models. Simulating vibration signals under diverse conditions mitigates the high cost of obtaining experimental signals for all scenarios. Given the non-stationary nature of railway vibration signals, influenced by speed and load changes, our models address these complexities, offering a powerful tool for predictive maintenance in the rail industry.

Dwarf novae are a crucial astrophysical laboratory for probing the nature of accretion, binary mass transfer, and binary evolution -- yet their diverse observational characteristics continue to challenge our theoretical understanding. We here present the discovery of, and subsequent observing campaign on GOTO065054+593624 (hereafter GOTO0650), a dwarf nova of the WZ Sge type, discovered in real-time by citizen scientists via the Kilonova Seekers citizen science project. An extensive dataset charts the photometric and spectroscopic evolution of this object, covering the first two months of its 2024 superoutburst. GOTO0650 shows a complete absence of visible emission lines during the high state, strong H and barely-detected He~II emission, and high-amplitude echo outbursts with a rapidly decreasing timescale that together do not neatly fit in with our current view of cataclysmic variables. The comprehensive dataset presented here not only underscores the uniqueness of this dwarf nova and marks it as a candidate period bouncer, but also highlights the important contribution that citizen scientists can make to the study of Galactic transients., Comment: 14 pages, 14 figures. Submitted to A&A

Orchestrating next gen applications over hterogeneous resources along the Cloud-IoT continuum calls for new strategies and tools to enable scalable and application-specific managements. Inspired by the self-organisation capabilities of bacteria colonies, we propose a declarative, fully decentralised application management solution, targeting pervasive opportunistic Cloud-IoT infrastructures. We present acustomisable declarative implementation of the approach and validate its scalability through simulation over motivating scenarios, also considering end-user's mobility and the possibility to enforce application-specific management policies for different classes of applications.

This study compares three evolutionary algorithms for the problem of fog service placement: weighted sum genetic algorithm (WSGA), non-dominated sorting genetic algorithm II (NSGA-II), and multiobjective evolutionary algorithm based on decomposition (MOEA/D). A model for the problem domain (fog architecture and fog applications) and for the optimization (objective functions and solutions) is presented. Our main concerns are related to optimize the network latency, the service spread and the use of the resources. The algorithms are evaluated with a random Barabasi-Albert network topology with 100 devices and with two experiment sizes of 100 and 200 application services. The results showed that NSGA-II obtained the highest optimizations of the objectives and the highest diversity of the solution space. On the contrary, MOEA/D was better to reduce the execution times. The WSGA algorithm did not show any benefit with regard to the other two algorithms.

Ewing's sarcoma (ES), characterized by a high density of small round blue cells without structural organization, presents a significant health concern, particularly among adolescents aged 10 to 19. Artificial intelligence-based systems for automated analysis of histopathological images are promising to contribute to an accurate diagnosis of ES. In this context, this study explores the feature extraction ability of different pre-training strategies for distinguishing ES from other soft tissue or bone sarcomas with similar morphology in digitized tissue microarrays for the first time, as far as we know. Vision-language supervision (VLS) is compared to fully-supervised ImageNet pre-training within a multiple instance learning paradigm. Our findings indicate a substantial improvement in diagnostic accuracy with the adaption of VLS using an in-domain dataset. Notably, these models not only enhance the accuracy of predicted classes but also drastically reduce the number of trainable parameters and computational costs., Comment: 11 pages, 5 figures, 2 tables. Oral presentation at KES-InMed 2024 held in Madeira, Portugal

Proper characterization of quantum correlations in a multimode optical state is critical for applications in quantum information science; however, the most common entanglement measurements can lead to an incomplete state reconstruction. This is the case for the ubiquitous spectral measurement of field quadratures for which a full characterization of the quantum correlations between optical beams is not possible. We demonstrate this effect in twin beams generated through parametric amplification by four-wave mixing in hot rubidium vapor, showing the role of a frequency dependent gain response. We implement a resonator-based measurement that reveals entanglement between beams that is otherwise hidden by usual spectral measurements. Additionally, this system shows how the phase shifts between the carrier and the sidebands on the involved fields affect the observation of entanglement for different entanglement witnesses, demonstrating the relevance of making a complete state tomography.

FH Ser experienced a slow classical nova outburst in February 1970 that was the first one observed at UV, optical, and IR wavelengths. Its nova remnant is elliptical in shape, with multiple knots, and a peculiar ring-like filament along its minor axis. This work aims at unveiling its true 3D spatio-kinematical structure to investigate the effects of early shaping and to assess its mass and kinetic energy using VLT VIMOS integral field spectroscopic observations. The data cube has been analyzed using 3D visualisations that reveal different structural components. FH Ser consists of a tilted prolate ellisoidal shell, most prominent in H-alpha, and a ring-like structure, most prominent in [N II]. The ellipsoidal shell has equatorial and polar velocities of 505 and 630 km/s, respectively, with its major axis tilted by 52 deg with respect to the line of sight. The inclination angle of the symmetry axis of the ring is similar, i.e., it can be described as an equatorial belt of the main ellipsoidal shell. The ionized mass is 2.6E-4 solar mass, with a kinetic energy of 1.6E45 erg. The presence of two different structural components in FH Ser with similar orientation can be linked to a density enhancement along a plane, most likely the orbital plane at the time of the nova event. The acquisition of integral field spectroscopic observations of nova remnants is most required to disentangle different structural components and to assess their 3D physical structure., Comment: 16 pages, 6 figures, 2 appendixes with 10 additional figures, accepted by A&A

Vacancy-cluster color centers in lithium fluoride have been studied in detail both theoretically and experimentally for over a century, giving rise to various applications in solid-state lasers, broadband photonic devices, and radiation dosimeters. These color centers are also attractive candidate platforms for applications in quantum information science, due to their spin properties and strong coupling to the crystal lattice, which allows their properties to be easily tuned. Here we present hybrid functional calculations of common vacancy defects in lithium fluoride, including their energetic, spin, and optical properties. We show that for a wide range of hybrid functional parameters tuned to match the experimental band gap, certain defects have little variation in their predicted optical properties. We further demonstrate that the parameters needed to satisfy the generalized Koopman's theorem and correctly position defect levels within the gap, can vary dramatically, even for different charge states of the same defect. Our work establishes the accuracy of the computationally lightweight hybrid-functional approach for predicting the optical and energetic properties of color centers in polar materials., Comment: 10 pages, 5 figures

We study the production and possible detection of a single Higgs boson in association with a top quark in proton-proton collisions ($pp \to th + X$) at the High-Luminosity Large Hadron Collider. This process absent in the Standard Model is predicted by other models such as the Two-Higgs Doublet Model of type III, which is the theoretical framework adopted in this work. Promising results are found for specific scenarios of the model parameter space, which consist mainly of the parameters $\tan\beta$, $\cos(\alpha-\beta)$ and the parameter $\chi_{tc}$, responsible for the Flavor-Changing Neutral Scalar Interactions (FCNSI). Using the machine learning \textit{Boosted Decision Trees} algorithm, we predict \textit{signal significances} at level of $5\sigma$ for $\tan\beta=1$, $\cos(\alpha-\beta)=0.1$ and $\chi_{tc}=5$ and integrated luminosities in the range $2500\, {\rm fb}^{-1}\leq \mathcal{L}_{\rm int} \leq 3000 \, {\rm fb}^{-1}$., Comment: 13 pages, 10 figures

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

We train a feed-forward text-to-3D diffusion generator for human characters using only single-view 2D data for supervision. Existing 3D generative models cannot yet match the fidelity of image or video generative models. State-of-the-art 3D generators are either trained with explicit 3D supervision and are thus limited by the volume and diversity of existing 3D data. Meanwhile, generators that can be trained with only 2D data as supervision typically produce coarser results, cannot be text-conditioned, or must revert to test-time optimization. We observe that GAN- and diffusion-based generators have complementary qualities: GANs can be trained efficiently with 2D supervision to produce high-quality 3D objects but are hard to condition on text. In contrast, denoising diffusion models can be conditioned efficiently but tend to be hard to train with only 2D supervision. We introduce GANFusion, which starts by generating unconditional triplane features for 3D data using a GAN architecture trained with only single-view 2D data. We then generate random samples from the GAN, caption them, and train a text-conditioned diffusion model that directly learns to sample from the space of good triplane features that can be decoded into 3D objects., Comment: https://ganfusion.github.io/

The identification of the nebula HaTr 5 with the shell remnant of the historic Nova Sco 1437 around the low-accretion rate cataclysmic variable 2MASS J17022815-4306123 has been used in the framework of the hibernation scenario to set an upper limit of <580 yr to the transition time from a nova-like binary to a dwarf nova. This work aims at clarifying the nature of HaTr 5, which has also previously been proposed to be a possible planetary nebula. Intermediate- and high-dispersion long-slit spectra of HaTr\,5 have been obtained and analyzed in conjunction with archival optical and infrared images to investigate its spectral properties using photoionization models, to derive its H-alpha flux and ionized mass, and to determine its spatio-kinematic by means of 3D models to clarify its true nature. The H-alpha flux of HaTr 5 implies an ionized mass of 0.059 M_Sun at the 0.99 kpc distance of J170228, i.e., about 1000 times the typical ejecta of a nova. If HaTr\,5 were actually an unrelated planetary nebula, its H-alpha flux implies a distance of 2.25 kpc and an ionized mass of 0.47 M_Sun. The expansion velocity of HaTr 5 is found to be of 27 km/s, with a heliocentric radial velocity of -1 km/. The ionized mass of HaTr 5 and its expansion velocity (and associated kinematic age) are clearly inconsistent with those expected for a nova remnant, which all strongly support a planetary nebula nature. The association of J170228 with HaTr 5 is further called into question by their differing radial velocities and almost orthogonal motions on the plane of the sky. It is concluded that HaTr 5 is an old, evolved planetary nebula unrelated to the remnant of Nova Sco 1437 and to the cataclysmic variable J170228, the latter being by chance projected onto HaTr 5., Comment: 11 pages, 3 tables, 7 figures, accepted to A&A

Pattern images are everywhere in the digital and physical worlds, and tools to edit them are valuable. But editing pattern images is tricky: desired edits are often programmatic: structure-aware edits that alter the underlying program which generates the pattern. One could attempt to infer this underlying program, but current methods for doing so struggle with complex images and produce unorganized programs that make editing tedious. In this work, we introduce a novel approach to perform programmatic edits on pattern images. By using a pattern analogy -- a pair of simple patterns to demonstrate the intended edit -- and a learning-based generative model to execute these edits, our method allows users to intuitively edit patterns. To enable this paradigm, we introduce SplitWeave, a domain-specific language that, combined with a framework for sampling synthetic pattern analogies, enables the creation of a large, high-quality synthetic training dataset. We also present TriFuser, a Latent Diffusion Model (LDM) designed to overcome critical issues that arise when naively deploying LDMs to this task. Extensive experiments on real-world, artist-sourced patterns reveals that our method faithfully performs the demonstrated edit while also generalizing to related pattern styles beyond its training distribution., Comment: Website: https://bardofcodes.github.io/patterns/

We use a combination of molecular dynamics and quantum transport simulations to investigate the upper limit of spin transport in suspended graphene. We find that thermally-induced atomic-scale corrugations are the dominant factor, limiting spin lifetimes to ~10 ns by inducing a strongly-varying local spin-orbit coupling. These extremely short-range corrugations appear even when the height profile appears to be smooth, suggesting they may be present in any graphene device. We discuss our results in the context of experiments, and briefly consider approaches to suppress these short-range corrugations and further enhance spin lifetimes in graphene-based spin devices., Comment: 9 pages, 5 figures

Motivated by industrial computed tomography, we propose a memory efficient strategy to estimate the regularization hyperparameter of a non-smooth variational model. The approach is based on a combination of FISTA and Condat-Vu algorithms exploiting the convergence rate of the former and the low per-iteration complexity of the latter. The estimation is cast as a bilevel learning problem where a first-order method is obtained via reduced-memory automatic differentiation to compute the derivatives. The method is validated with experimental industrial tomographic data with the numerical implementation available.

The reliability of Neural Networks has gained significant attention, prompting efforts to develop SW-based hardening techniques for safety-critical scenarios. However, evaluating hardening techniques using application-level fault injection (FI) strategies, which are commonly hardware-agnostic, may yield misleading results. This study for the first time compares two FI approaches (at the application level (APP) and instruction level (ISA)) to evaluate deep neural network SW hardening strategies. Results show that injecting permanent faults at ISA (a more detailed abstraction level than APP) changes completely the ranking of SW hardening techniques, in terms of both reliability and accuracy. These results highlight the relevance of using an adequate analysis abstraction for evaluating such techniques., Comment: 6 pages, 2 figures, 1 table, Asian Test Symposium

A large, faint nebula was unexpectedly discovered near M31 using narrowband [O III] images. Its apparent size and the lack of a clear counterpart at other wavelengths make it unique and challenging to explain. We aim to determine whether the nebula is extragalactic or located within the Milky Way. This will enable us to constrain its physical properties and assess its nature. To do so, we obtained deep narrowband [O II]3727 and H$\alpha$+[NII] observations with the JAST80 telescope at the Observatorio Astrof\'isico de Javalambre, as well as high-spectral-resolution spectroscopy at four locations within the region of interest using MEGARA at the Gran Telescopio Canarias. We found extended [O II] emission along two near-parallel strands to the [O III], offset by six arcmin. The nebular spectra reveals up to 6 emission lines from [O III]4959,5007, H$\beta$, [N II]6583, and [S II]6716,6731. Their receding velocities are above $-$40 km s$^{-1}$, far from the systemic velocity of M31 ($-$300 km s$^{-1}$). The fluxes and velocities are consistent for the same lines across different regions of the nebula. The nebular properties suggest a location within the Milky Way rather than being physically associated with M31. The most likely scenario is a resolved ionization structure in a Galactic nebula with a separation between [O II] and [O III] of a few parsecs. The observed receding velocities would be unprecedented for an object physically linked to M31 but are common for nearby gas filaments. Their consistency across the nebula would also be unusual if it were larger than a kiloparsec. The analysis of the emission-line ratios, line widths, and morphology suggests the possibility of it being an interstellar gas filament with an additional source of ionization to explain the [O III] emission. However, the complex properties of this object call for further observations to confirm its nature., Comment: 13 pages, 6 figures. Submitted to Astronomy & Astrophysics

ZIP loads (the parallel combination of constant impedance loads, constant current loads and constant power loads) exist widely in power system. In order to stabilize buck converter based DC distributed system with ZIP load, an adaptive energy shaping controller (AESC) is devised in this paper. Firstly, based on the assumption that lumped disturbances are known, a full information controller is designed in the framework of the port Hamiltonian system via energy shaping technique. Besides, using mathematical deductive method, an estimation of the domain of attraction is given to ensure the strict stability. Furthermore, to eliminate the influence of parameter perturbations on the system, a disturbance observer is proposed to reconstruct the lumped disturbances and then the estimated terms are introduced to above controller to form an AESC scheme. In addition, the stability analysis of the closed-loop system is given. Lastly, the simulation and experiment results are presented for assessing the designed controller.

The central star of the Helix Nebula, WD 2226$-$210 presents enigmatic hard X-ray emission and mid-IR excess. The latter has been attributed to a dusty disk or a cloud-like structure around WD 2226$-$210 formed from material of Kuiper Belt-like or comet-like objects in highly eccentric orbits. We present here a detailed analysis of multi-epoch Chandra and XMM-Newton X-ray observations of WD 2226$-$210, comparing these to previous Einstein and ROSAT data. The luminosity of the hard X-ray component of WD 2226$-$210 has remained basically constant in the decade from 1992 to 2002, with very subtle evidence for variability in timescales of hours. Under the assumption that the X-ray emission from WD 2226$-$210 is due to accretion of material, an accretion rate of $\dot{M}\approx10^{-10}$ M$_\odot$ yr$^{-1}$ is estimated. The origin of the material accreted by WD 2226$-$210 is uncertain, and can be attributed to the disk-like structure around it or to a sub-stellar donor companion. The accretion rate proposed for the continuous replenishment by bombardment of the mid-IR-emitting structure around WD 2226$-$210 cannot match that required by the X-ray emission., Comment: 8 pages, 3 figures, 3 tables; accepted to MNRAS

Magnetic fields remain one of the least understood aspects of exoplanetary systems. A deeper understanding of planetary dynamos and the evolution of surface magnetic properties throughout a planet's lifetime is a key scientific purpose, with implications for planetary evolution, habitability, and atmospheric dynamics. This study models the evolution of magnetic fields generated by dynamo action in cold giant gaseous planets. We solve the resistive magnetohydrodynamic (MHD) equations under anelastic approximation with a 3D pseudo-spectral spherical shell MHD code. We employ 1D thermodynamical hydrostatic profiles taken from gas giant evolutionary models as the background states of our MHD models. Numerical integration leads to saturated dynamo solutions. Such calculations are performed with radial profiles corresponding to different planetary ages so that we can interpret them as different snapshots of the magnetoconvection evolution during the long-term planetary evolution. We characterize magnetic fields across different evolutionary stages of a cold gaseous planet in terms of topology and strength. We find the occurrence of a transition from multipolar to dipolar-dominated dynamo regime throughout the life of a Jovian planet. During the planetary evolution and the cooling down phase, we observe a decrease in the average magnetic field strength near the dynamo surface as $\sim t^{-0.2}-t^{-0.3}$, a trend compatible with previously proposed scaling laws. We also find that some dimensionless parameters evolve differently for the multipolar to dipolar branch, possibly reflecting a force balance change. This approach can be extended to study hot gaseous planets, offering a versatile tool for interpreting the magnetic properties of giant planets., Comment: 19 pages, submitted for publication, comments are welcome

Gravitational wave approximants are widely used tools in gravitational-wave astronomy. They allow for dense coverage of the parameter space of binary black hole (BBH) mergers for purposes of parameter inference, or, more generally, match filtering tasks, while avoiding the computationally expensive full evolution of numerical relativity simulations. However, this comes at a slight cost in terms of accuracy when compared to numerical relativity waveforms, depending on the approach. One way to minimize this is by constructing so-called~\textit{surrogate models} which, instead of using approximate physics or phenomenological formulae, rather interpolate within the space of numerical relativity waveforms. In this work, we introduce~\texttt{NRSurNN3dq4}, a surrogate model for non-precessing BBH merger waveforms powered by neural networks. By relying on the power of deep learning, this approximant is remarkably fast and competitively accurate, as it can generate millions of waveforms in a tenth of a second, while mismatches with numerical relativity waveforms are restrained below $10^{-3}$. We implement this approximant within the~\textsc{bilby} framework for gravitational-wave parameter inference, and show that it it is suitable for parameter estimation tasks.

The design of fast reactors burning MOX fuels requires accurate capture and fission cross sections. For the particular case of neutron capture on 242Pu, the NEA recommends that an accuracy of 8-12% should be achieved in the fast energy region (2 keV-500 keV) compared to their estimation of 35% for the current uncertainty. Integral irradiation experiments suggest that the evaluated cross section of the JEFF-3.1 library overestimates the 242Pu(n,{\gamma}) cross section by 14% in the range between 1 keV and 1 MeV. In addition, the last measurement at LANSCE reported a systematic reduction of 20-30% in the 1-40 keV range relative to the evaluated libraries and previous data sets. In the present work this cross section has been determined up to 600 keV in order to solve the mentioned discrepancies. A 242Pu target of 95(4) mg enriched to 99.959% was irradiated at the n TOF-EAR1 facility at CERN. The capture cross section of 242Pu has been obtained between 1 and 600 keV with a systematic uncertainty (dominated by background subtraction) between 8 and 12%, reducing the current uncertainties of 35% and achieving the accuracy requested by the NEA in a large energy range. The shape of the cross section has been analyzed in terms of average resonance parameters using the FITACS code as implemented in SAMMY, yielding results compatible with our recent analysis of the resolved resonance region.The results are in good agreement with the data of Wisshak and K\"appeler and on average 10-14% below JEFF-3.2 from 1 to 250 keV, which helps to achieve consistency between integral experiments and cross section data. At higher energies our results show a reasonable agreement within uncertainties with both ENDF/B-VII.1 and JEFF-3.2. Our results indicate that the last experiment from DANCE underestimates the capture cross section of 242Pu by as much as 40% above a few keV., Comment: 20 pages, 19 figures, submitted to Phys. Rev. C

Predicting diverse object motions from a single static image remains challenging, as current video generation models often entangle object movement with camera motion and other scene changes. While recent methods can predict specific motions from motion arrow input, they rely on synthetic data and predefined motions, limiting their application to complex scenes. We introduce Motion Modes, a training-free approach that explores a pre-trained image-to-video generator's latent distribution to discover various distinct and plausible motions focused on selected objects in static images. We achieve this by employing a flow generator guided by energy functions designed to disentangle object and camera motion. Additionally, we use an energy inspired by particle guidance to diversify the generated motions, without requiring explicit training data. Experimental results demonstrate that Motion Modes generates realistic and varied object animations, surpassing previous methods and even human predictions regarding plausibility and diversity. Project Webpage: https://motionmodes.github.io/

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $\gamma$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$\gamma$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $\gamma$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

Let $(G,+)$ be an Abelian group. Given $h\in \mathbb{Z}^+$, a non-empty subset $A$ of $G$ is called an $S_h$-set if all the sums of $h$ distinct elements of $A$ are different. We extend the concept of $S_h$-set to a more general context in the context of finite vectorial spaces over finite fields. More precisely, a $\emptyset \neq A\subseteq \mathbb{F}_q^r$ is called an $S_h$-linear set if all the linear combinations of $h$ elements of $A$ are different. We establish a correspondence between $q$-ary linear codes and $S_h$-linear sets. This connection allow us to find lower bounds for the maximum size of $S_h$-sets in $\mathbb{F}_q^r$., Comment: 17 pages, 2 figures

We present the first analysis of Dark Matter axion detection applying neural networks for the improvement of sensitivity. The main sources of thermal noise from a typical read-out chain are simulated, constituted by resonant and amplifier noises. With this purpose, an advanced modal method employed in electromagnetic modal analysis for the design of complex microwave circuits is applied. A feedforward neural network is used for a boolean decision (there is axion or only noise), and robust results are obtained: the neural network can improve by a factor of $5\cdot 10^{3}$ the integration time needed to reach a given signal to noise ratio. This could either significantly reduce measurement times or achieve better sensitivities with the same exposure durations., Comment: 6 pages, 6 figures, 1 table

BabyIAXO is the intermediate stage of the International Axion Observatory (IAXO) to be hosted at DESY. Its primary goal is the detection of solar axions following the axion helioscope technique. Axions are converted into photons in a large magnet that is pointing to the sun. The resulting X-rays are focused by appropriate X-ray optics and detected by sensitive low-background detectors placed at the focal spot. The aim of this article is to provide an accurate quantitative description of the different components (such as the magnet, optics, and X-ray detectors) involved in the detection of axions. Our efforts have focused on developing robust and integrated software tools to model these helioscope components, enabling future assessments of modifications or upgrades to any part of the IAXO axion helioscope and evaluating the potential impact on the experiment's sensitivity. In this manuscript, we demonstrate the application of these tools by presenting a precise signal calculation and response analysis of BabyIAXO's sensitivity to the axion-photon coupling. Though focusing on the Primakoff solar flux component, our virtual helioscope model can be used to test different production mechanisms, allowing for direct comparisons within a unified framework., Comment: 36 pages, 18 figures, 4 tables, Submitted to JHEP

A considerable number of asymptotic giant branch (AGB) stars exhibit UV excess and/or X-ray emission that indicates a binary companion. AGB stars are so bright that they easily outshine their companions. This almost prevents their identification. Y Gem has been known for some decades to be an AGB star that is bright in the far-UV and X-rays, but it is unclear whether its companion is a main-sequence star or a white dwarf (WD) in a symbiotic system (SySt). Our goal is to uncover the true nature of Y Gem, which will help us to study the possible misidentified population of SySts. Multiwavelength IR, optical, UV, and X-ray observations were analyzed to investigate the properties of the stellar components and the accretion process in Y Gem. In particular, an optical spectrum of Y Gem is presented here for the first time, while X-ray data are interpreted by means of reflection models produced by an accretion disk and material in its vicinity. The optical spectrum exhibits the typical sawtooth-shaped features of molecular absorptions in addition to narrow recombination and forbidden emission lines. The emission lines and the analysis of the extinction-corrected UV spectrum suggest a hot component with $T_\mathrm{eff}\approx$60,000 K, $L$=140 L$_{\odot}$, and $R$=0.11 R$_{\odot}$ that very likely is an accreting WD. The late component is found to be an 1.1 M$_\odot$ AGB star with $T_\mathrm{eff}$=3350 K and $R$=240 R$_\odot$. Using IR, optical, UV, and X-ray data, we found that Y Gem is an S-type SySt whose compact component is accreting at an estimated mass-accretion rate of $\dot{M}_\mathrm{acc}=2.3\times10^{-7}$ M$_\odot$ yr$^{-1}$. At this accretion rate, the accreting WD has reached the stable and steady burning phase in which no recurrent events are expected., Comment: 13 pages, 9 Figures, 4 Tables; To appear in A&A

Understanding the dust content of galaxies, its evolution with redshift and its relationship to stars and star formation is fundamental for our understanding of galaxy evolution. Using the ALMA Lensing Cluster Survey (ALCS) wide-area band-6 continuum dataset ($\sim\,$110 arcmin$^2$ across 33 lensing clusters), we aimed at constraining the dust mass evolution with redshift, stellar mass and star formation rate (SFR). After binning sources according to redshift, SFR and stellar mass -- extracted from an HST-IRAC catalog -- we performed a set of continuum stacking analyses in the image domain using \textsc{LineStacker} on sources between $z=1$ and $z=5$, further improving the depth of our data. The large field of view provided by the ALCS allows us to reach a final sample of $\sim4000$ galaxies with known coordinates and SED-derived physical parameters. We stack sources with SFR between $10^{-3}$ and $10^{3}$ M$_\odot$ per year, and stellar mass between $10^{8}$ and $10^{12}$ M$_\odot$, splitting them in different stellar mass and SFR bins. Through stacking we retrieve the continuum 1.2\,mm flux, a known dust mass tracer, allowing us to derive the dust mass evolution with redshift and its relation with SFR and stellar mass. We observe clear continuum detections in the majority of the subsamples. From the non detections we derive 3-$\sigma$ upper limits. We observe a steady decline in the average dust mass with redshift. Moreover, sources with higher stellar mass or SFR have higher dust mass on average, allowing us to derive scaling relations. Our results are mostly in good agreement with models at $z\sim1$-3, but indicate typically lower dust-mass than predicted at higher redshift.

Tactile perception is essential for human interaction with the environment and is becoming increasingly crucial in robotics. Tactile sensors like the BioTac mimic human fingertips and provide detailed interaction data. Despite its utility in applications like slip detection and object identification, this sensor is now deprecated, making many existing valuable datasets obsolete. However, recreating similar datasets with newer sensor technologies is both tedious and time-consuming. Therefore, it is crucial to adapt these existing datasets for use with new setups and modalities. In response, we introduce ACROSS, a novel framework for translating data between tactile sensors by exploiting sensor deformation information. We demonstrate the approach by translating BioTac signals into the DIGIT sensor. Our framework consists of first converting the input signals into 3D deformation meshes. We then transition from the 3D deformation mesh of one sensor to the mesh of another, and finally convert the generated 3D deformation mesh into the corresponding output space. We demonstrate our approach to the most challenging problem of going from a low-dimensional tactile representation to a high-dimensional one. In particular, we transfer the tactile signals of a BioTac sensor to DIGIT tactile images. Our approach enables the continued use of valuable datasets and the exchange of data between groups with different setups., Comment: Paper Submitted to ICRA2025. arXiv admin note: text overlap with arXiv:2410.14310

In this paper we share the experience of the U.S. National Science Foundation (NSF) National Solar Observatory (NSO) scientists, educators and public outreach officers organizing an eclipse viewing party at a sports complex stadium on the US/Mexico border in Eagle Pass, TX in collaboration with educators from Eagle Pass and Uvalde areas. We describe reasons we chose Eagle Pass, contacts we established with the local community, preparations for and activities set up during the eclipse viewing party, the eclipse day on April 8 2024 and lessons learned from organizing our event., Comment: 17 pages, 9 figures, submitted to Bulletin of the AAS: Celebrating the Wonder of Science in the Shadow II

Multi-epoch Chandra and XMM-Newton observations of the symbiotic system R Aquarii (R Aqr) spanning 22 yr are analysed by means of a reflection model produced by an accretion disc. This methodology helps dissecting the contribution from different components in the X-ray spectra of R Aqr: the soft emission from the jet and extended emission, the heavily-extinguished plasma component of the boundary layer and the reflection contribution, which naturally includes the 6.4 keV Fe fluorescent line. The evolution with time of the different components is studied for epochs between 2000 Sep and 2022 Dec, and it is found that the fluxes of the boundary layer and that of the reflecting component increase as the stellar components in R Aqr approach periastron passage, a similar behaviour is exhibited by the shocked plasma produced by the precessing jet. Using publicly available optical and UV data we are able to study the evolution of the mass-accretion rate $\dot{M}_\mathrm{acc}$ and the wind accretion efficiency $\eta$ during periastron. These exhibit a small degree of variability with median values of $\dot{M}_\mathrm{acc}$=7.3$\times10^{-10}$ M$_\odot$ yr$^{-1}$ and $\eta$=7$\times10^{-3}$. We compare our estimations with predictions from a modified Bondi-Hoyle-Lyttleton accretion scenario., Comment: 17 pages, 15 figures, 4 tables; accepted to MNRAS