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This study explores the hydrogen bond-mediated association between chitosan (CHI) and alkyl polyglucoside (APG), a bio-based surfactant, in acidic conditions with varying ionic strengths. Unlike conventional polyelectrolyte-surfactant interactions that depend on electrostatic forces, the association in this system relies purely on non-ionic interactions. Using UV visible spectroscopy, phase diagrams, and quartz crystal microbalance with dissipation monitoring (QCM-D), the bulk phase behavior and adsorption characteristics of CHI-APG mixtures on negatively charged surfaces was studied. Results demonstrate that APG concentration controls the phase behavior, with moderate levels inducing coacervate formation, while higher ionic strengths promote this coacervation through enhanced hydrogen bonding interactions. This shift leads to the formation of a phase separated morphology, with micronsized coacervate droplets observable in solution. Zeta potential measurements suggest that these droplets adopt a core shell structure, characterized by a hydrophobic core due to the surfactant s alkyl chains and a hydrophilic shell formed by chitosan. Additionally, the coacervation process significantly enhances the adsorption of CHI APG complexes onto solid substrates, a feature with potential applications in targeted delivery and controlled release systems. Overall, this study provides critical insights into the design of bio-based, sustainable formulations and expands the understanding of hydrogen bond-driven, nonelectrostatic coacervation, relevant for applications in cosmetics, biomedical coatings, and environmentally friendly materials., Comment: Published in Journal of Molecular Liquids 425 (2025) 127259

We present a data-driven approach to Reynolds-averaged Navier-Stokes turbulence closure modelling in magnetohydrodynamic (MHD) flows. In these flows the magnetic field interacting with the conductive fluid induces unconventional turbulence states such as quasi two-dimensional (2D) turbulence, and turbulence suppression, which are poorly represented by standard Boussinesq models. Our data-driven approach uses time-averaged Large Eddy Simulation (LES) data of annular pipe flows, at different Hartmann numbers, to derive corrections for the $k$-$\omega$ SST model. Correction fields are obtained by injecting time averaged LES fields into the MHD RANS equations, and examining the remaining residuals. The correction to the Reynolds-stress anisotropy is approximated with a modified Tensor Basis Neural Network (TBNN). We extend the generalised eddy hypothesis with a traceless antisymmetric tensor representation of the Lorentz force to obtain MHD flow features, thus keeping Galilean and frame invariance while including MHD effects in the turbulence model. The resulting data-driven models are shown to reduce errors in the mean flow, and to generalise to annular flow cases with different Hartmann numbers from those of the training cases., Comment: 30 pages, 18 figures (including appendix), for a journal

The increasing complexity of natural disaster incidents demands innovative technological solutions to support first responders in their efforts. This paper introduces the TRIFFID system, a comprehensive technical framework that integrates unmanned ground and aerial vehicles with advanced artificial intelligence functionalities to enhance disaster response capabilities across wildfires, urban floods, and post-earthquake search and rescue missions. By leveraging state-of-the-art autonomous navigation, semantic perception, and human-robot interaction technologies, TRIFFID provides a sophisticated system composed of the following key components: hybrid robotic platform, centralized ground station, custom communication infrastructure, and smartphone application. The defined research and development activities demonstrate how deep neural networks, knowledge graphs, and multimodal information fusion can enable robots to autonomously navigate and analyze disaster environments, reducing personnel risks and accelerating response times. The proposed system enhances emergency response teams by providing advanced mission planning, safety monitoring, and adaptive task execution capabilities. Moreover, it ensures real-time situational awareness and operational support in complex and risky situations, facilitating rapid and precise information collection and coordinated actions.

Flag manifolds encode hierarchical nested sequences of subspaces and serve as powerful structures for various computer vision and machine learning applications. Despite their utility in tasks such as dimensionality reduction, motion averaging, and subspace clustering, current applications are often restricted to extracting flags using common matrix decomposition methods like the singular value decomposition. Here, we address the need for a general algorithm to factorize and work with hierarchical datasets. In particular, we propose a novel, flag-based method that decomposes arbitrary hierarchical real-valued data into a hierarchy-preserving flag representation in Stiefel coordinates. Our work harnesses the potential of flag manifolds in applications including denoising, clustering, and few-shot learning.

Before a binary system enters into a common envelope (CE) phase, accretion from the primary star onto the companion star through Roche Lobe overflow (RLOF) will lead to the formation of an accretion disk, which may generate jets. Accretion before and during the CE may alter the outcome of the interaction. Previous studies have considered different aspects of this physical mechanism. Here we study the properties of an accretion disk formed via 3D hydrodynamic simulations of the RLOF mass transfer between a 7 M$_\odot$, red supergiant star and a 1.4 M$_\odot$, neutron star companion. We simulate only the volume around the companion for improved resolution. We use a 1D implicit MESA simulation of the evolution of the system during 30,000 years between the on-set of the RLOF and the CE to guide the binary parameters and the mass-transfer rate, while we simulate only 21 years of the last part of the RLOF in 3D using an ideal gas isothermal equation of state. We expect that a pre-CE disk under these parameters will have a mass of $\sim 5\times 10^{-3}$ M$_\odot$ and a radius of $\sim$40 R$_\odot$ with a scale height of $\sim$5 R$_\odot$. The temperature profile of the disk is shallower than that predicted by the formalism of Shakura and Sunyaev, but more reasonable cooling physics would need to be included. We stress test these results with respect to a number of physical and numerical parameters, as well as simulation choices, and we expect them to be reasonable within a factor of a few for the mass and 15% for the radius. We also contextualize our results within those presented in the literature, in particular with respect to the dimensionality of simulations and the adiabatic index. We consider what properties of magnetic fields and jets may be supported by our disk and discuss prospects for future work., Comment: 17 pages, 20 figures

In this paper, we establish the global existence of a semi-linear class of hyperbolic equations in 3+1 dimensions, that satisfy the bounded weak null condition. We propose a conformal compactification of the future directed null-cone in Minkowski spacetime, enabling us to establish the solution to the wave equation in a neighbourhood of future null infinity. Using this framework, we formulate a conformal symmetric hyperbolic Fuchsian system of equations. The existence of solutions to this Fuchsian system follows from an application of the existence theory developed in [1], and [2]., Comment: 25 pages, 4 figures

Zinc phosphorus trisulfide (ZnPS$_3$), a promising material for photocatalysis and energy storage, is shown in this study to exhibit remarkable stability under extreme conditions. We explore its optical and structural properties under high pressure and cryogenic temperatures using photoluminescence (PL) spectroscopy, Raman scattering, and density functional theory (DFT). Our results identify a pressure-induced phase transition starting at 6.75 GPa and stabilizing by 12.5 GPa, after which ZnPS$_3$ demonstrates robust stability across a broad pressure range of 15 to 100 GPa. DFT calculations predict a semiconductor-to-semimetal transition at 100 GPa, while PL measurements reveal defect-assisted emissions that quench under pressure due to enhanced non-radiative recombination. At cryogenic temperatures, PL quenching intensifies as non-radiative processes dominate, driven by a rising Gr\"uneisen parameter and reduced phonon population. Cryogenic X-ray diffraction (XRD) also reveals a high mean thermal expansion coefficient (TEC) of (4.369 $\pm$ 0.393) $\times$ 10$^{-5}$ K$^{-1}$, among the highest reported for 2D materials. This unique combination of tunable electronic properties under low pressure and high thermal sensitivity makes ZnPS$_3$ a strong candidate for sensing applications in extreme environments.

In this work we investigate the two-neutron decay of 13Li and of the excited states of 11Li populated via one-proton removal from 14Be and 12Be, respectively. A phenomenological model is used to describe the decay of 11Li and 13Li. While the first one displays important sequential components, the second one appears dominated by the direct two-neutron decay. A microscopic three-body model is used to extract information on the spatial configuration of the emitted neutrons before the decay and shows that the average distance between the neutrons increases going from 11Li to 13Li.

Isoscalar dipole transitions are a distinctive fingerprint of cluster structures. A {1^-} resonance at 7.27(10) MeV, located just below the {\alpha}-emission threshold, has been observed in the deuteron inelastic scattering reactions off 10Be. The deformation lengths of the excited states in 10Be below 9 MeV have been inferred from the differential cross sections using coupled channel calculations. This observed {1^-} resonance has isoscalar characteristics and exhausts approximately 5{\%}-15{\%} of the isoscalar dipole energy-weighted sum rule, providing evidence for pronounced {\alpha} cluster structure in 10Be. The Gamow coupled channel approach supports this interpretation and suggests the near-threshold effect might be playing an important role in this excitation energy domain. The {\alpha}+{\alpha}+n+n four-body calculation reproduces the observed enhanced dipole strength, implying that the four-body cluster structure is essential to describe the {1^-} states in 10Be., Comment: 7 pages, 4 figures

We present 50-fs, single-shot measurements of the x-ray thermal diffuse scattering (TDS) from copper foils that have been shocked via nanosecond laser-ablation up to pressures above 135~GPa. We hence deduce the x-ray Debye-Waller (DW) factor, providing a temperature measurement. The targets were laser-shocked with the DiPOLE 100-X laser at the High Energy Density (HED) endstation of the European X-ray Free-Electron Laser (EuXFEL). Single x-ray pulses, with a photon energy of 18 keV, were scattered from the samples and recorded on Varex detectors. Despite the targets being highly textured (as evinced by large variations in the elastic scattering), and with such texture changing upon compression, the absolute intensity of the azimuthally averaged inelastic TDS between the Bragg peaks is largely insensitive to these changes, and, allowing for both Compton scattering and the low-level scattering from a sacrificial ablator layer, provides a reliable measurement of $T/\Theta_D^2$, where $\Theta_D$ is the Debye temperature. We compare our results with the predictions of the SESAME 3336 and LEOS 290 equations of state for copper, and find good agreement within experimental errors. We thus demonstrate that single-shot temperature measurements of dynamically compressed materials can be made via thermal diffuse scattering of XFEL radation., Comment: 17 pages, 9 figures in main article; 10 pages, 5 figures in supplementary material

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

The design of localization systems for small-scale flapping-wing aerial robots faces relevant challenges caused by the limited payload and onboard computational resources. This paper presents an ultra-wideband localization system particularly designed for small-scale flapping-wing robots. The solution relies on custom 5 grams ultra-wideband sensors and provides robust, very efficient (in terms of both computation and energy consumption), and accurate (mean error of 0.28 meters) 3D position estimation. We validate our system using a Flapper Nimble+ flapping-wing robot.

We define and study $H$-graded coverings for supermanifolds, where $H$ is a finite abelian group.

Obtaining an explicit understanding of communication within a Hybrid Intelligence collaboration is essential to create controllable and transparent agents. In this paper, we describe a number of Natural Language Understanding models that extract explicit symbolic triples from social conversation. Triple extraction has mostly been developed and tested for Knowledge Base Completion using Wikipedia text and data for training and testing. However, social conversation is very different as a genre in which interlocutors exchange information in sequences of utterances that involve statements, questions, and answers. Phenomena such as co-reference, ellipsis, coordination, and implicit and explicit negation or confirmation are more prominent in conversation than in Wikipedia text. We therefore describe an attempt to fill this gap by releasing data sets for training and testing triple extraction from social conversation. We also created five triple extraction models and tested them in our evaluation data. The highest precision is 51.14 for complete triples and 69.32 for triple elements when tested on single utterances. However, scores for conversational triples that span multiple turns are much lower, showing that extracting knowledge from true conversational data is much more challenging.

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

Foundation Models (FMs) have been successful in various computer vision tasks like image classification, object detection and image segmentation. However, these tasks remain challenging when these models are tested on datasets with different distributions from the training dataset, a problem known as domain shift. This is especially problematic for recognizing animal species in camera-trap images where we have variability in factors like lighting, camouflage and occlusions. In this paper, we propose the Camera Trap Language-guided Contrastive Learning (CATALOG) model to address these issues. Our approach combines multiple FMs to extract visual and textual features from camera-trap data and uses a contrastive loss function to train the model. We evaluate CATALOG on two benchmark datasets and show that it outperforms previous state-of-the-art methods in camera-trap image recognition, especially when the training and testing data have different animal species or come from different geographical areas. Our approach demonstrates the potential of using FMs in combination with multi-modal fusion and contrastive learning for addressing domain shifts in camera-trap image recognition. The code of CATALOG is publicly available at https://github.com/Julian075/CATALOG.

This article deals with the boundary null controllability of some degenerate parabolic equations posed on a square domain, presenting the first study of boundary controllability for such equations in multidimensional settings. The proof combines two classical techniques: the method of moments and the Lebeau-Robbiano strategy. A key novelty of this work lies in the analysis of boundary control localized on a subset of the boundary where the degeneracy occurs. Furthermore, we establish the Kalman rank condition as a full characterization of boundary controllability for coupled degenerate systems. The results are extended to $N$-dimensional domains, and potential extensions and open problems are discussed to motivate further research in this area.

The performance of modern wireless communication systems is typically limited by interference. The impact of interference can be even more severe in ultra-reliable and low-latency communication (URLLC) use cases. A powerful tool for managing interference is rate splitting multiple access (RSMA), which encompasses many multiple-access technologies like non-orthogonal multiple access (NOMA), spatial division multiple access (SDMA), and broadcasting. Another effective technology to enhance the performance of URLLC systems and mitigate interference is constituted by reconfigurable intelligent surfaces (RISs). This paper develops RSMA schemes for multi-user multiple-input multiple-output (MIMO) RIS-aided broadcast channels (BCs) based on finite block length (FBL) coding. We show that RSMA and RISs can substantially improve the spectral efficiency (SE) and energy efficiency (EE) of MIMO RIS-aided URLLC systems. Additionally, the gain of employing RSMA and RISs noticeably increases when the reliability and latency constraints are more stringent. Furthermore, RISs impact RSMA differently, depending on the user load. If the system is underloaded, RISs are able to manage the interference sufficiently well, making the gains of RSMA small. However, when the user load is high, RISs and RSMA become synergetic.

Coding camps bring together individuals from diverse backgrounds to tackle given challenges within a limited timeframe. Such camps create a rich learning environment for various skills, some of which are directly associated with the camp, and some of which are a result of working as a team during the camp. Unfortunately, coding camps often remain isolated from the broader educational curriculum or other bigger context, which downplays the opportunities they can offer to students. In this paper, we present the vision of the European initiative Oscar, which aims at connecting coding camps to the educational and professional context faced by the learners. In addition, we sketch a supporting platform and its features for connected coding camps., Comment: Accepted for publication at SIGCSE TS 2025, Proceedings of the 56th ACM Technical Symposium on Computer Science Education

The challenges in dense ultra-reliable low-latency communication networks to deliver the required service to multiple devices are addressed by three main technologies: multiple antennas at the base station (MISO), rate splitting multiple access (RSMA) with private and common message encoding, and simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Careful resource allocation, encompassing beamforming and RIS optimization, is required to exploit the synergy between the three. We propose an alternating optimization-based algorithm, relying on minorization-maximization. Numerical results show that the achievable second-order max-min rates of the proposed scheme outperform the baselines significantly. MISO, RSMA, and STAR-RIS all contribute to enabling ultra-reliable low-latency communication (URLLC)., Comment: Accepted at 2025 International Conference on Mobile and Miniaturized Terahertz Systems (ICMMTS)

In this paper, we address the exponential stabilization of the linearized FitzHugh-Nagumo system using an event-triggered boundary control strategy. Employing the backstepping method, we derive a feedback control law that updates based on specific triggering rules while ensuring the exponential stability of the closed-loop system. We establish the well-posedness of the system and analyze its input-to-state stability in relation to the deviations introduced by the event-triggered control. Numerical simulations demonstrate the effectiveness of this approach, showing that it stabilizes the system with fewer control updates compared to continuous feedback strategies while maintaining similar stabilization performance.

We analyze the finite-block-length rate region of wireless systems aided by reconfigurable intelligent surfaces (RISs), employing treating interference as noise. We consider three nearly passive RIS architectures, including locally passive (LP) diagonal (D), globally passive (GP) D, and GP beyond diagonal (BD) RISs. In a GP RIS, the power constraint is applied globally to the whole surface, while some elements may amplify the incident signal locally. The considered RIS architectures provide substantial performance gains compared with systems operating without RIS. GP BD-RIS outperforms, at the price of increasing the complexity, LP and GP D-RIS as it enlarges the feasible set of allowed solutions. However, the gain provided by BD-RIS decreases with the number of RIS elements. Additionally, deploying RISs provides higher gains as the reliability/latency requirement becomes more stringent.

Characterizing the dimensionality of the superconducting state in the infinite-layer (IL) nickelates is crucial to understand its nature. Most studies have addressed the problem by studying the anisotropy of the upper critical fields. Yet, the dominance of Pauli-paramagnetism effects over orbital ones makes it challenging to interpret the experiments in terms of dimensionality. Here we address the question from a different perspective, by investigating the vortex phase diagram in the mixed-state. We demonstrate that superconducting Pr0.8Sr0.2NiO2 thin films present a vortex liquid-to-glass transition of a purely two-dimensional nature. The obtained results suggest that bidimensionality is an intrinsic property, and that superconductivity resides in fully-decoupled NiO2 planes. In this scenario, the coherence length along the c-axis must be shorter than the distance between those planes, while Josephson and magnetostatic coupling between them must be negligible. We believe that these conclusions are relevant for theories on the origin of superconductivity in the IL-nickelates.

In this work, we present MedImageInsight, an open-source medical imaging embedding model. MedImageInsight is trained on medical images with associated text and labels across a diverse collection of domains, including X-Ray, CT, MRI, dermoscopy, OCT, fundus photography, ultrasound, histopathology, and mammography. Rigorous evaluations demonstrate MedImageInsight's ability to achieve state-of-the-art (SOTA) or human expert level performance across classification, image-image search, and fine-tuning tasks. Specifically, on public datasets, MedImageInsight achieves SOTA in CT 3D medical image retrieval, as well as SOTA in disease classification and search for chest X-ray, dermatology, and OCT imaging. Furthermore, MedImageInsight achieves human expert performance in bone age estimation (on both public and partner data), as well as AUC above 0.9 in most other domains. When paired with a text decoder, MedImageInsight achieves near SOTA level single image report findings generation with less than 10\% the parameters of other models. Compared to fine-tuning GPT-4o with only MIMIC-CXR data for the same task, MedImageInsight outperforms in clinical metrics, but underperforms on lexical metrics where GPT-4o sets a new SOTA. Importantly for regulatory purposes, MedImageInsight can generate ROC curves, adjust sensitivity and specificity based on clinical need, and provide evidence-based decision support through image-image search (which can also enable retrieval augmented generation). In an independent clinical evaluation of image-image search in chest X-ray, MedImageInsight outperformed every other publicly available foundation model evaluated by large margins (over 6 points AUC), and significantly outperformed other models in terms of AI fairness (across age and gender). We hope releasing MedImageInsight will help enhance collective progress in medical imaging AI research and development.

The commissioning and operation of future large-scale scientific experiments will challenge current tuning and control methods. Reinforcement learning (RL) algorithms are a promising solution thanks to their capability of autonomously tackling a control problem based on a task parameterized by a reward function. The conventionally utilized machine learning (ML) libraries are not intended for microsecond latency applications, as they mostly optimize for throughput performance. On the other hand, most of the programmable logic implementations are meant for computation acceleration, not being intended to work in a real-time environment. To overcome these limitations of current implementations, RL needs to be deployed on-the-edge, i.e. on to the device gathering the training data. In this paper we present the design and deployment of an experience accumulator system in a particle accelerator. In this system deep-RL algorithms run using hardware acceleration and act within a few microseconds, enabling the use of RL for control of ultra-fast phenomena. The training is performed offline to reduce the number of operations carried out on the acceleration hardware. The proposed architecture was tested in real experimental conditions at the Karlsruhe research accelerator (KARA), serving also as a synchrotron light source, where the system was used to control induced horizontal betatron oscillations in real-time. The results showed a performance comparable to the commercial feedback system available at the accelerator, proving the viability and potential of this approach. Due to the self-learning and reconfiguration capability of this implementation, its seamless application to other control problems is possible. Applications range from particle accelerators to large-scale research and industrial facilities.

We demonstrate spectroscopy of incoherent light with sub-diffraction resolution. In a proof-of-principle experiment we analyze the spectrum of a pair of incoherent point-like sources whose separation is below the diffraction limit. The two sources mimic a planetary system, with a brighter source for the star and a dimmer one for the planet. Acquiring spectral information about the secondary source is hard because the two images have a substantial overlap. This limitation is solved by leveraging a structured measurement based on spatial-mode demultiplexing, where light is first sorted in its Hermite-Gaussian components in the transverse field, then measured by photon detection. This allows us to effectively decouple the photons coming from the two sources. An application is suggested to enhance exoplanets' atmosphere spectroscopy. A number of experiments of super-resolution imaging based on spatial demultiplexing have been conducted in the past few years, with promising results. Here, for the first time to the best of our knowledge, we extend this concept to the domain of spectroscopy., Comment: 11 pages, 6 figures, comments welcome

Visual analytics is essential for studying large time series due to its ability to reveal trends, anomalies, and insights. DeepVATS is a tool that merges Deep Learning (Deep) with Visual Analytics (VA) for the analysis of large time series data (TS). It has three interconnected modules. The Deep Learning module, developed in R, manages the load of datasets and Deep Learning models from and to the Storage module. This module also supports models training and the acquisition of the embeddings from the latent space of the trained model. The Storage module operates using the Weights and Biases system. Subsequently, these embeddings can be analyzed in the Visual Analytics module. This module, based on an R Shiny application, allows the adjustment of the parameters related to the projection and clustering of the embeddings space. Once these parameters are set, interactive plots representing both the embeddings, and the time series are shown. This paper introduces the tool and examines its scalability through log analytics. The execution time evolution is examined while the length of the time series is varied. This is achieved by resampling a large data series into smaller subsets and logging the main execution and rendering times for later analysis of scalability., Comment: Admitted pending publication in Lecture Notes in Network and Systems (LNNS) series (Springer). Code available at https://github.com/vrodriguezf/deepvats

In this paper, we develop energy-efficient schemes for multi-user multiple-input single-output (MISO) broadcast channels (BCs), assisted by reconfigurable intelligent surfaces (RISs). To this end, we consider three architectures of RIS: locally passive diagonal (LP-D), globally passive diagonal (GP-D), and globally passive beyond diagonal (GP-BD). In a globally passive RIS, the power of the output signal of the RIS is not greater than its input power, but some RIS elements can amplify the signal. In a locally passive RIS, every element cannot amplify the incident signal. We show that these RIS architectures can substantially improve energy efficiency (EE) if the static power of the RIS elements is not too high. Moreover, GP-BD RIS, which has a higher complexity and static power than LP-D RIS and GP-D RIS, provides better spectral efficiency, but its EE performance highly depends on the static power consumption and may be worse than its diagonal counterparts., Comment: Accepted at 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

We demonstrate that a fully metallic and air-filled geodesic waveguide can be employed as an analog electromagnetic model of a static and spherically symmetric gravitational field. By following the Plebanski formalism, a space-time metric of the aforementioned type is firstly encoded into the electromagnetic properties of a flat space-time region in the form of an isotropic and radially varying refractive index distribution. Then, a three-dimensional, air-filled, and axially symmetric waveguide, composed of two equally spaced and curved metallic surfaces, is employed. Its shape is tailored such that the effective paths, followed by transverse electromagnetic beams of microwave radiation within this waveguide, result equivalent to null-geodesics taking place in the aforementioned refractive medium. This strategy avoids the need for a refractive medium, although it only allows to reproduce the space-time metric on the invariant plane. Two analog electromagnetic models of gravity, using the proposed approach, are designed to reproduce the metric of both a Schwarzschild black hole and a Morris-Thorne wormhole. The results from full-wave simulations demonstrate that a one-dimensional Gaussian beam faithfully follows a path completely equivalent to general relativistic null geodesics with a mean relative error within 4%., Comment: 16 pages, 6 figures, accepted for publication in Physical Review D

We present the results of the ALMA Large Program Early Planet Formation in Embedded disks observations of the Class 0 protostar GSS30 IRS3. Our observations included 1.3 mm continuum with a resolution of 0.''05 (7.8 au) and several molecular species including $^{12}$CO, $^{13}$CO, C$^{18}$O, H$_{2}$CO and c-C$_{3}$H$_{2}$. The dust continuum analysis unveiled a disk-shaped structure with a major axis size of $\sim$200 au. We observed an asymmetry in the minor axis of the continuum emission suggesting that the emission is optically thick and the disk is flared. On the other hand, we identified two prominent bumps along the major axis located at distances of 26 and 50 au from the central protostar. The origin of the bumps remains uncertain and might be due to an embedded substructure within the disk or the result of the temperature distribution instead of surface density due to optically thick continuum emission. The $^{12}$CO emission reveals a molecular outflow consisting of three distinct components: a collimated one, an intermediate velocity component exhibiting an hourglass shape, and a wider angle low-velocity component. We associate these components with the coexistence of a jet and a disk-wind. The C$^{18}$O emission traces both a Keplerian rotating circumstellar disk and the infall of the rotating envelope. We measured a stellar dynamical mass of 0.35$\pm$0.09 M$_{\odot}$., Comment: 25 pages, 19 figures. Accepted for publication in A&A

Recent work by Ram\'irez et al. [2] has introduced Multi-Channel Factor Analysis (MFA) as an extension of factor analysis to multi-channel data that allows for latent factors common to all channels as well as factors specific to each channel. This paper validates the MFA covariance model and analyzes the statistical properties of the MFA estimators. In particular, a thorough investigation of model identifiability under varying latent factor structures is conducted, and sufficient conditions for generic global identifiability of MFA are obtained. The development of these identifiability conditions enables asymptotic analysis of estimators obtained by maximizing a Gaussian likelihood, which are shown to be consistent and asymptotically normal even under misspecification of the latent factor distribution.

In this work, we make new developments in generic cotangent bundle geometries, depending on all phase-space variables. In particular, we will focus on the so-called generalized Hamilton spaces, discussing how the main ingredients of this geometrical framework, such as the Hamiltonian and the nonlinear and affine connections, can be derived from a given metric. Several properties of this kind of spaces are demonstrated for autoparallel Hamiltonians. Moreover, we study the spacetime and momentum isometries of the metric. Finally, we discuss the possible applications of cotangent bundle geometries in quantum gravity, such as the construction of deformed relativistic kinematics and non-commutative spacetimes., Comment: 16 pages

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the binary Class 0 protostellar system BHR 71 IRS1 and IRS2 as part of the Early Planet Formation in Embedded Disks (eDisk) ALMA Large Program. We describe the $^{12}$CO ($J$=2--1), $^{13}$CO ($J$=2--1), C$^{18}$O ($J$=2--1), H$_2$CO ($J=3_{2,1}$--$2_{2,0}$), and SiO ($J$=5--4) molecular lines along with the 1.3 mm continuum at high spatial resolution ($\sim$0.08" or $\sim$5 au). Dust continuum emission is detected toward BHR 71 IRS1 and IRS2, with a central compact component and extended continuum emission. The compact components are smooth and show no sign of substructures such as spirals, rings or gaps. However, there is a brightness asymmetry along the minor axis of the presumed disk in IRS1, possibly indicative of an inclined geometrically and optically thick disk-like component. Using a position-velocity diagram analysis of the C$^{18}$O line, clear Keplerian motions were not detected toward either source. If Keplerian rotationally-supported disks are present, they are likely deeply embedded in their envelope. However, we can set upper limits of the central protostellar mass of 0.46 M$_\odot$ and 0.26 M$_\odot$ for BHR 71 IRS1 and BHR 71 IRS2, respectively. Outflows traced by $^{12}$CO and SiO are detected in both sources. The outflows can be divided into two components, a wide-angle outflow and a jet. In IRS1, the jet exhibits a double helical structure, reflecting the removal of angular momentum from the system. In IRS2, the jet is very collimated and shows a chain of knots, suggesting episodic accretion events., Comment: 38 pages, 29 figures, accepted in ApJ

We study the existence and concentration of positive and nodal solutions to a Schr\"odinger equation in the presence of a shrinking self-focusing core of arbitrary shape. Via a suitable rescaling, the concentration gives rise to a limiting profile that solves a nonautonomous elliptic semilinear equation with a sharp sign change in the nonlinearity. We characterize the (radial or foliated Schwarz) symmetries and the (polynomial) decay of the least-energy positive and nodal limiting profiles., Comment: Revised version

Spin polarization in chiral molecules is a magnetic molecular response associated with electron transport and enantioselective bond polarization that occurs even in the absence of an external magnetic field. An unexpected finding by Santos and co-workers reported enantiospecific NMR responses in solid-state cross-polarization (CP) experiments, suggesting a possible additional contribution to the indirect nuclear spin-spin coupling in chiral molecules induced by bond polarization in the presence of spin-orbit coupling. Herein we provide a theoretical treatment for this phenomenon, presenting an effective spin-Hamiltonian for helical molecules like DNA and density functional theory (DFT) results on amino acids that confirm the dependence of J-couplings on the choice of enantiomer. The connection between nuclear spin dynamics and chirality could offer insights for molecular sensing and quantum information sciences. These results establish NMR as a potential tool for chiral discrimination without external agents., Comment: 102 pages, 16 figures, 40 tables

We develop an artificial agent motivated to augment its knowledge base beyond its initial training. The agent actively participates in dialogues with other agents, strategically acquiring new information. The agent models its knowledge as an RDF knowledge graph, integrating new beliefs acquired through conversation. Responses in dialogue are generated by identifying graph patterns around these new integrated beliefs. We show that policies can be learned using reinforcement learning to select effective graph patterns during an interaction, without relying on explicit user feedback. Within this context, our study is a proof of concept for leveraging users as effective sources of information.

In this paper, we study linear backward parabolic SPDEs and present new a priori estimates for their weak solutions. Inspired by the seminal work of Y. Hu, J. Ma and J. Yong from 2002 on strong solutions, we establish $L^p$-estimates requiring minimal assumptions on the regularity of the coefficients, the terminal data, and the external force. To this end, we derive a new It\^{o}'s formula for the $L^p$-norm of the solution, extending the classical result in the $L^2$-setting. This formula is then used to improve further the regularity of the first component of the solution up to $L^\infty$. Additionally, we present applications such as the controllability of backward SPDEs with $L^p$-controls and a local existence result for a semilinear equation without imposing any growth condition on the nonlinear term.

The oxidation of NO molecules on epoxy-functionalized highly oriented pyrolytic graphite, thermalized at 300 K, was studied by means of ab initio molecular dynamics (AIMD) calculations. Four collision energies and two different orientations were analyzed where the reaction, adsorption, and scattering probabilities were computed. Our results reveal that NO$_2$ formation can occur even at the lowest collision energy investigated (0.025 eV), approximately equivalent to room temperature (300 K), which agrees qualitatively with the experimental results. This underscores the influence of dynamics on the NO oxidation process, since this oxidation barrier was previously theoretically estimated to be about 0.1 eV at 0 K, which is four times higher than our lowest collision energy. Additionally, we obtained angular and energy distributions of the products under selected simulation conditions. Scattered NO molecules show low specular reflection, lose half of their initial translational energy, and remain vibrationally cold with minimal rotational excitation. Furthermore, a statistical analysis of all reactive trajectories, focusing on configurations at specific reaction moments, elucidated the structural requirements for the reaction to occur under dynamic conditions. Finally, this study demonstrates the potential of oxygen-doped carbon surfaces for the conversion of NO to NO$_2$.

Context. When low and intermediate-mass stars leave the Asymptotic Giant Branch (AGB) phase, and before they reach the Planetary Nebulae stage, they enter a very brief and rather puzzling stellar evolutionary stage named post-AGB. Aims. To provide a reliable catalogue of galactic post-AGB stars together with their physical and evolutionary properties obtained through Gaia DR3 astrometry and photometry. Methods. We started by identifying post-AGB stars or possible candidates from the bibliography with their Gaia DR3 counterpart sources. Using the available photometry, interstellar extinction, literature spectroscopically derived temperatures or spectral types and parallax-derived distances from Gaia DR3, we fitted their Spectral Energy Distributions and we estimated their luminosities and circumstellar extinctions. When compared to models, luminosity values allowed us to disclose objects that are likely post-AGB stars from other target types. Their position on the HR diagram allows direct comparison with updated post-AGB evolutionary tracks and an estimation of their masses and evolutionary ages. Results. We obtained a sample of 69 reliable post-AGB candidates that meet our classification criteria, providing their coordinates, distances, effective temperature, total extinction, luminosity, mass, and evolutionary age. In addition, similar data for other stellar objects in our initial compilation, such as supergiant stars or young stellar objects, is provided. Conclusions. We have filtered out the data that have the best precision in parallaxes and distances to obtain more accurate luminosities, which allows us to classify with confidence the objects of the sample among different stellar phases. This allows us to provide a small but reliable sample of post-AGB objects. Derived mean evolutionary time and average mass values are in agreement with theoretical expectations.