Search

Environmental monitoring is used to characterize the health and relationship between organisms and their environments. In forest ecosystems, robots can serve as platforms to acquire such data, even in hard-to-reach places where wire-traversing platforms are particularly promising due to their efficient displacement. This paper presents the RaccoonBot, which is a novel autonomous wire-traversing robot for persistent environmental monitoring, featuring a fail-safe mechanical design with a self-locking mechanism in case of electrical shortage. The robot also features energy-aware mobility through a novel Solar tracking algorithm, that allows the robot to find a position on the wire to have direct contact with solar power to increase the energy harvested. Experimental results validate the electro-mechanical features of the RaccoonBot, showing that it is able to handle wire perturbations, different inclinations, and achieving energy autonomy., Comment: Pre-print submitted to the 2025 IEEE International Conference on Robotics & Automation (ICRA 2025)

(Abridged) We reassess the alpha-element abundance ratios (Ne/O, S/O, Ar/O) with respect to metallicity in ~1000 spectra of Galactic and extragalactic HII regions and star-forming galaxies (SFGs) of the local Universe. Using the DEep Spectra of Ionised REgions Database (DESIRED) Extended project (DESIRED-E), which includes spectra with direct electron temperature determinations, we homogeneously derive physical conditions and chemical abundances for all objects. Various ionisation correction factor (ICF) schemes are analyzed for Ne, S, and Ar to identify the most reliable abundance estimates. Our findings indicate that the ICF scheme by Izotov et al. (2006) better reproduces the Ne/O, S/O, and Ar/O trends. Ne/O ratios in HII regions display large dispersion and no clear dependence on O/H, suggesting that current ICF(Ne) schemes fail for these objects. However, SFGs show consistent linear relations with slightly positive slopes for log(Ne/O) vs. 12+log(O/H) or 12+log(Ne/H), likely influenced by metallicity-dependent O dust depletion and ICF effects. The log(S/O) vs. 12+log(O/H) distribution is largely constant, especially for HII regions or combined samples (SFGs + HII regions). Conversely, log(S/O) vs. 12+log(S/H) shows a tight linear fit with a positive slope, flattening at 12+log(S/H) < 6.0, suggesting S contributions from SNe Ia. For log(Ar/O) vs. 12+log(O/H), similar trends emerge for HII regions and SFGs, independent of ionisation degree or ICF(Ar). A slight log(Ar/O) decrease with increasing 12+log(O/H) contrasts with log(Ar/O) vs. 12+log(Ar/H), which shows a small positive slope, indicating a possible minor Ar contribution from SNe Ia., Comment: 20 pages, 13 Figures, 2 Tables in the main text. Appendices include 3 additional figures and tables. Submitted to A&A. Comments welcome

In the era of precision measurements of neutrino oscillation parameters, it is necessary for experiments to disentangle discrepancies that may indicate physics beyond the Standard Model in the neutrino sector. KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study the oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on the initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photosensors. A high-purity neutrino sample was extracted during 2020 and 2021, corresponding to an exposure of 433 kton-years. This sample is analysed following a binned log-likelihood approach to search for invisible neutrino decay, in a three-flavour neutrino oscillation scenario, where the third neutrino mass state $\nu_3$ decays into an invisible state, e.g. a sterile neutrino. The resulting best fit of the invisible neutrino decay parameter is $\alpha_3 = 0.92^{+1.08}_{-0.57}\times 10^{-4}~\mathrm{eV^2}$, corresponding to a scenario with $\theta_{23}$ in the second octant and normal neutrino mass ordering. The results are consistent with the Standard Model, within a $2.1\,\sigma$ interval., Comment: 20 pages, 8 figures

We present the strongest limits to date on the mixing angle, $\theta$, with which a new scalar particle, $S$, mixes with the Higgs field in the mass range $100$ $MeV

Empirical Software Engineering has received much attention in recent years and became a de-facto standard for scientific practice in Software Engineering. However, while extensive guidelines are nowadays available for designing, conducting, reporting, and reviewing empirical studies, similar attention has not yet been paid to teaching empirical software engineering. Closing this gap is the scope of this edited book. In the following editorial introduction, we, the editors, set the foundation by laying out the larger context of the discipline for a positioning of the remainder of this book., Comment: Preprint to a chapter for the edited book "Handbook on Teaching Empirical Software Engineering", Springer, 2024

In this paper we develop a mathematical model combined with machine learning techniques to predict shade-seeking behavior in cows exposed to heat stress. The approach integrates advanced mathematical features, such as time-averaged thermal indices and accumulated heat stress metrics, obtained by mathematical analysis of data from a farm in Titaguas (Valencia, Spain), collected during the summer of 2023. Two predictive models, Random Forests and Neural Networks, are compared for accuracy, robustness, and interpretability. The Random Forest model is highlighted for its balance between precision and explainability, achieving an RMSE of $14.97$. The methodology also employs $5-$fold cross-validation to ensure robustness under real-world conditions. This work not only advances the mathematical modeling of animal behavior but also provides useful insights for mitigating heat stress in livestock through data-driven tools., Comment: 22 pages, 10 figures

Regularized estimation of quantitative ultrasound (QUS) parameters, such as attenuation and backscatter coefficients, has gained research interest. Recently, the alternating direction method of multipliers (ADMM) has been applied successfully to estimate these parameters, by utilizing L2 and L1 norms for attenuation and backscatter coefficient regularization, respectively. While this method improves upon previous approaches, it does not fully leverage the prior knowledge of minimum physically feasible parameter values, sometimes yielding values outside the realistic range. This work addresses this limitation by incorporating minimum QUS parameter values as constraints to enhance ADMM estimation. The proposed method is validated using experimental phantom data., Comment: accepted in ISBI 2025

Context. The supernova remnant (SNR) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (CRs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy CRs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNR and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. Results. The combined spectra of Fermi-LAT and MAGIC, extending from 100MeV to several TeV, were used to derive constraints on the escape of CRs. Using a time-dependent model to describe the particle acceleration and escape from the SNR, we show that the maximum energy of the accelerated particles has to be ' 40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission.

Mrk 421 was in its most active state around early 2010, which led to the highest TeV gamma-ray flux ever recorded from any active galactic nuclei. We aim to characterize the multiwavelength behavior during this exceptional year for Mrk 421, and evaluate whether it is consistent with the picture derived with data from other less exceptional years. We investigated the period from November 5, 2009, (MJD 55140) until July 3, 2010, (MJD 55380) with extensive coverage from very-high-energy (VHE; E$\,>\,$100$\,$GeV) gamma rays to radio with MAGIC, VERITAS, Fermi-LAT, RXTE, Swift, GASP-WEBT, VLBA, and a variety of additional optical and radio telescopes. We investigated the variability and correlation behavior among different energy bands in great detail. We find the strongest variability in X-rays and VHE gamma rays, and PSDs compatible with power-law functions. We observe strong correlations between X-rays and VHE gamma rays. We also report a marginally significant positive correlation between high-energy (HE; E$\,>\,$100$\,$MeV) gamma rays and the ultraviolet band. We detected marginally significant correlations between the HE and VHE gamma rays, and between HE gamma rays and the X-ray, that disappear when the large flare in February 2010 is excluded from the correlation study. The activity of Mrk 421 also yielded the first ejection of features in the VLBA images of the jet of Mrk 421. Yet the large uncertainties in the ejection times of these radio features prevent us from firmly associating them to the specific flares recorded during the campaign. We also show that the collected multi-instrument data are consistent with a scenario where the emission is dominated by two regions, a compact and extended zone, which could be considered as a simplified implementation of an energy-stratified jet as suggested by recent IXPE observations., Comment: Accepted for publication in Astronomy & Astrophysics. Corresponding authors: Felix Schmuckermaier, David Paneque, Axel Arbet Engels

Anxiety and depression are the most common mental health issues worldwide, affecting a non-negligible part of the population. Accordingly, stakeholders, including governments' health systems, are developing new strategies to promote early detection and prevention from a holistic perspective (i.e., addressing several disorders simultaneously). In this work, an entirely novel system for the multi-label classification of anxiety and depression is proposed. The input data consists of dialogues from user interactions with an assistant chatbot. Another relevant contribution lies in using Large Language Models (LLMs) for feature extraction, provided the complexity and variability of language. The combination of LLMs, given their high capability for language understanding, and Machine Learning (ML) models, provided their contextual knowledge about the classification problem thanks to the labeled data, constitute a promising approach towards mental health assessment. To promote the solution's trustworthiness, reliability, and accountability, explainability descriptions of the model's decision are provided in a graphical dashboard. Experimental results on a real dataset attain 90 % accuracy, improving those in the prior literature. The ultimate objective is to contribute in an accessible and scalable way before formal treatment occurs in the healthcare systems.

The BL Lacertae object VER J0521+211 underwent a notable flaring episode in February 2020. A short-term monitoring campaign, led by the MAGIC (Major Atmospheric Gamma Imaging Cherenkov) collaboration, covering a wide energy range from radio to very-high-energy (VHE, 100 GeV < E < 100 TeV) gamma rays was organised to study its evolution. These observations resulted in a consistent detection of the source over six consecutive nights in the VHE gamma-ray domain. Combining these nightly observations with an extensive set of multiwavelength data made modelling of the blazar's spectral energy distribution (SED) possible during the flare. This modelling was performed with a focus on two plausible emission mechanisms: i) a leptonic two-zone synchrotron-self-Compton scenario, and ii) a lepto-hadronic one-zone scenario. Both models effectively replicated the observed SED from radio to the VHE gamma-ray band. Furthermore, by introducing a set of evolving parameters, both models were successful in reproducing the evolution of the fluxes measured in different bands throughout the observing campaign. Notably, the lepto-hadronic model predicts enhanced photon and neutrino fluxes at ultra-high energies (E > 100 TeV). While the photon component, generated via decay of neutral pions, is not directly observable as it is subject to intense pair production (and therefore extinction) through interactions with the cosmic microwave background photons, neutrino detectors (e.g. IceCube) can probe the predicted neutrino component. Finally, the analysis of the gamma-ray spectra, as observed by MAGIC and the Fermi-LAT telescopes, yielded a conservative 95\% confidence upper limit of z \leq 0.244 for the redshift of this blazar., Comment: Accepted for publication in A&A

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of $1.11\times 10^{21}$ protons on target, a $70\%$ increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. MicroBooNE data is compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electron-like interpretation of the MiniBooNE excess based on these models at $> 99\%$ CL$_\mathrm{s}$ in all kinematic variables., Comment: 8 pages, 5 figures, 1 table

Variance theories quantify the variance that one or more independent variables cause in a dependent variable. In software engineering (SE), variance theories are used to quantify -- among others -- the impact of tools, techniques, and other treatments on software development outcomes. To acquire variance theories, evidence from individual empirical studies needs to be synthesized to more generally valid conclusions. However, research synthesis in SE is mostly limited to meta-analysis, which requires homogeneity of the synthesized studies to infer generalizable variance. In this paper, we aim to extend the practice of research synthesis beyond meta-analysis. To this end, we derive a conceptual framework for the evolution of variance theories and demonstrate its use by applying it to an active research field in SE. The resulting framework allows researchers to put new evidence in a clear relation to an existing body of knowledge and systematically expand the scientific frontier of a studied phenomenon.

We report a novel nanoscale device concept based on a highly doped $\delta$-layer tunnel junction embedded in a semiconductor for charge sensing. Recent advances in Atomic Precision Advanced Manufacturing (APAM) processes have enabled the fabrication of devices based on quasi-2D, highly conductive, highly doped regions in semiconductor materials. In this work, we demonstrate that FET-based sensors utilizing APAM $\delta$-layer tunnel junctions are ultrasensitive to the presence of charges near the tunnel junction, allowing the use of these devices for detecting charges by observing changes in the electrical current. We demonstrate that these devices can enhance the sensitivity in the limit, i.e. for small concentrations of charges, exhibiting significantly superior sensitivity compared to traditional FET-based sensors. We also propose that the extreme sensitivity arises from the strong quantization of the conduction band in these highly-confined systems.

We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneous spatial and spectral renderings by encoding material properties from multi-view 3D hyperspectral datasets. HyperGS reconstructs high-fidelity views from arbitrary perspectives with improved accuracy and speed, outperforming currently existing methods. To address the challenges of high-dimensional data, we perform view synthesis in a learned latent space, incorporating a pixel-wise adaptive density function and a pruning technique for increased training stability and efficiency. Additionally, we introduce the first HNVS benchmark, implementing a number of new baselines based on recent SOTA RGB-NVS techniques, alongside the small number of prior works on HNVS. We demonstrate HyperGS's robustness through extensive evaluation of real and simulated hyperspectral scenes with a 14db accuracy improvement upon previously published models.

We propose a fully $ \textit{ab initio} $ approach to predicting thermal attenuation in elastic helium atom scattering amplitudes, validated through strong agreement with experiments on Nb(100) and (3$\times$1)-O/Nb(100) surfaces. Our results reveal the relative contributions from bulk, resonant, and surface phonon modes, as well as from different surface mode polarizations, providing insights into differences between smooth and corrugated surfaces. These findings advance understanding of surface dynamics and electron-phonon coupling, laying groundwork for future studies on surface superconductivity.

Even after decades of usage as an extragalactic standard candle, the universal bright end of the planetary nebula luminosity function (PNLF) still lacks a solid theoretical explanation. Until now, models have modeled planetary nebulae (PNe) from artificial stellar populations, without an underlying cosmological star formation history. We present PICS (PNe In Cosmological Simulations), a novel method of modeling PNe in cosmological simulations, through which PN populations for the first time naturally occur within galaxies of diverse evolutionary pathways. We find that only by using realistic stellar populations and their metallicities is it possible to reproduce the bright end of the PNLF for all galaxy types. In particular, the dependence of stellar lifetimes on metallicity has to be accounted for to produce bright PNe in metal-rich populations. Finally, PICS reproduces the statistically complete part of the PNLF observed around the Sun, down to six orders of magnitude below the bright end., Comment: 6 pages, 3 figures, accepted for publication in the proceedings of IAU Symposium 384 (Planetary Nebulae: a Universal Toolbox in the Era of Precision Astrophysics)

This paper presents the development and implementation of a versatile ad-hoc metropolitan-range Quantum Key Distribution (QKD) network. The approach presented integrates various types of physical channels and QKD protocols, and a mix of trusted and untrusted nodes. Unlike conventional QKD networks that predominantly depend on either fiber-based or free-space optical (FSO) links, the testbed presented amalgamates FSO and fiber-based links, thereby overcoming some inherent limitations. Various network deployment strategies have been considered, including permanent infrastructure and provisional ad-hoc links to eradicate coverage gaps. Furthermore, the ability to rapidly establish a network using portable FSO terminals and to investigate diverse link topologies is demonstrated. The study also showcases the successful establishment of a quantum-secured link to a cloud server.

We study the occupation time statistics for non-Markovian random walkers based on the formalism of the generalized master equation for the Continuous-Time Random Walk. We also explore the case when the random walker additionally undergoes a stochastic resetting dynamics. We derive and solve the backward Feynman-Kac equation to find the characteristic function for the occupation time in an interval and for the half occupation time in the semi-infinite domain. We analyze the behaviour of the PDFs, the moments, the limiting distributions and the ergodic properties for both occupation times when the underlying random walk is normal or anomalous. For the half occupation time, we revisit the famous arcsine law and examine its validity pertaining to various regimes of the rest period of the walker. Our results have been verified with numerical simulations exhibiting an excellent agreement.

We report on an educational pilot program for low-cost physics experimentation run in Ecuador, South Africa, and the United States. The program was developed after having needs-based discussions with African educators, researchers, and leaders. It was determined that the need and desire for low-cost, skills-building, and active-learning tools is very high. From this, we developed a 3D-printable, Raspberry Pi-based multispectral camera (15 to 25 spectral channels in the visible and near-IR) for as little as $100. The program allows students to learn 3D modeling, 3D printing, feedback, control, image analysis, Python programming, systems integration and artificial intelligence as well as spectroscopy. After completing their cameras, the students in the program studied plant health, plant stress, post-harvest fruit ripeness, and polarization and spectral analysis of nanostructured insect wings, the latter of which won the ``best-applied research" award at a conference poster session and will be highlighted in this paper. Importantly, these cameras can be an integral part of any developing country's agricultural, recycling, medical, and pharmaceutical infrastructure. Thus, we believe this experiment can play an important role at the intersection of student training and developing countries' capacity building.

Recent observations reveal a rapid dust build-up in high-redshift galaxies (z > 4), challenging current models of galaxy formation. While our understanding of dust production and destruction in the interstellar medium (ISM) is advancing, probing baryonic processes in the early Universe remains a complex task. We characterize the evolution of 98 z~5 star-forming galaxies observed as part of the ALPINE survey by constraining the physical processes underpinning the gas and dust production, consumption, and destruction in their ISM. We make use of chemical evolution models to simultaneously reproduce the observed dust and gas content. For each galaxy, we estimate initial gas mass, inflows and outflows, and efficiencies of dust growth and destruction. We test the models with the canonical Chabrier and top-heavy initial mass functions (IMFs), with the latter enabling rapid dust production on shorter timescales. Our models successfully reproduce gas and dust content in older galaxies (> 600 Myr) regardless of the IMF, with Type II SNe as the primary dust source and no dust growth in ISM with moderate inflow of primordial gas. In case of intermediate-age galaxies (300 - 600 Myr), we reproduce the gas and dust content through Type II SNe and dust growth in ISM, though we observe an over-prediction of dust mass in older galaxies, potentially indicating an unaccounted dust destruction mechanism and/or an overestimation of the observed dust masses. The number of young galaxies (< 300 Myr) reproduced, increases for models assuming top-heavy IMF but with maximal prescriptions of dust production. Galactic outflows are necessary to reproduce observed gas and dust masses. The Chabrier IMF models reproduce 65% of galaxies, while top-heavy IMF models improve this to 93%, easing tensions with observations. Upcoming JWST data will refine these models by resolving degeneracies in intrinsic galaxy properties., Comment: Accepted for publication in A&A

Semiconductor-superconductor hybrid devices have been proposed as promising platforms for detecting and analyzing Majorana zero modes, which find applications in topological quantum computing. In this work, we solve the Kohn-Sham Density Functional Theory and Bogoliubov-de Gennes equations to describe the normal and superconducting properties of a PbTe/Pb heterostructure. We resolve a proximity-induced superconducting gap on the PbTe side. The hybridization between PbTe and Pb causes the emergence of a soft Bardeen-Cooper-Schrieffer-like superconducting gap. We compute the anomalous charge density in real space, estimating its decay length and showing that the pairing potential is anisotropic, which is a necessary condition for unconventional superconductivity. Contrary to the models that predict Majorana zero modes in these interfaces, we find a significantly large Schottky barrier in the normal state preventing the emergence of zero modes. Our findings strengthen the understanding of the physics governing PbTe/Pb hybrid devices and their viability for Majorana zero modes applications.

Quantum resistance is vital for emerging cryptographic systems as quantum technologies continue to advance towards large-scale, fault-tolerant quantum computers. Resistance may be offered by quantum key distribution (QKD), which provides information-theoretic security using quantum states of photons, but may be limited by transmission loss at long distances. An alternative approach uses classical means and is conjectured to be resistant to quantum attacks, so-called post-quantum cryptography (PQC), but it is yet to be rigorously proven, and its current implementations are computationally expensive. To overcome the security and performance challenges present in each, here we develop hybrid protocols by which QKD and PQC inter-operate within a joint quantum-classical network. In particular, we consider different hybrid designs that may offer enhanced speed and/or security over the individual performance of either approach. Furthermore, we present a method for analyzing the security of hybrid protocols in key distribution networks. Our hybrid approach paves the way for joint quantum-classical communication networks, which leverage the advantages of both QKD and PQC and can be tailored to the requirements of various practical networks., Comment: 6 pages, 3 figures, including extra supplementary materials

The rapid advancement of quantum technologies calls for the design and deployment of quantum-safe cryptographic protocols and communication networks. There are two primary approaches to achieving quantum-resistant security: quantum key distribution (QKD) and post-quantum cryptography (PQC). While each offers unique advantages, both have drawbacks in practical implementation. In this work, we introduce the pros and cons of these protocols and explore how they can be combined to achieve a higher level of security and/or improved performance in key distribution. We hope our discussion inspires further research into the design of hybrid cryptographic protocols for quantum-classical communication networks., Comment: 4 pages, a blue print paper, Submission for IEEE 2024 IEEE Workshop on Quantum IntelLigence, Learning & Security (QUILLS), https://sites.google.com/pitt.edu/quills/home

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

In this paper we propose a novel traffic flow model based on understanding the city as a porous media, this is, streets and building-blocks characterizing the urban landscape are seen now as the fluid-phase and the solid-phase of a porous media, respectively. Moreover, based in the interchange of mass in the porous media models, we can model the interchange of cars between streets and off-street parking-spaces. Therefore, our model is not a standard conservation law, being formulated as the coupling of a non-stationary convection-diffusion-reaction PDE with a Darcy-Brinkman-Forchheimer PDE system. To solve this model, the classical Galerkin P1 finite element method combined with an explicit time marching scheme of strong stability-preserving type was enough to stabilize our numerical solutions. Numerical experiences on an urban-porous domain inspired by the city of Guadalajara (Mexico) allow us to simulate the influence of the porosity terms on the traffic speed, the traffic flow at rush-valley hours, and the streets congestions due to the lack of parking spaces.

In this work we present a novel methodology to deal with the optimal performance of raceways (open-channel ponds where the circulating wastewater, during its purification process, is used to grow algae that will be used as a source for the production of bioenergy). The maximization of algal productivity is addressed here within an optimal control framework for partial differential equations. Thus, after introducing a rigorously detailed mathematical formulation of the real-world control problem, we prove the existence of optimal solutions, we propose a numerical algorithm for its computational resolution and, finally, we show some results for the numerical optimization of a realistic case.

KM3NeT/ORCA is an underwater neutrino telescope under construction in the Mediterranean Sea. Its primary scientific goal is to measure the atmospheric neutrino oscillation parameters and to determine the neutrino mass ordering. ORCA can constrain the oscillation parameters $\Delta m^{2}_{31}$ and $\theta_{23}$ by reconstructing the arrival direction and energy of multi-GeV neutrinos crossing the Earth. Searches for deviations from the Standard Model of particle physics in the forward scattering of neutrinos inside Earth matter, produced by Non-Standard Interactions, can be conducted by investigating distortions of the standard oscillation pattern of neutrinos of all flavours. This work reports on the results of the search for non-standard neutrino interactions using the first six detection units of ORCA and 433 kton-years of exposure. No significant deviation from standard interactions was found in a sample of 5828 events reconstructed in the 1 GeV$-$1 TeV energy range. The flavour structure of the non-standard coupling was constrained at 90\% confidence level to be $|\varepsilon_{\mu\tau} | \leq 5.4 \times 10^{-3}$, $|\varepsilon_{e\tau} | \leq 7.4 \times 10^{-2}$, $|\varepsilon_{e\mu} | \leq 5.6 \times 10^{-2}$ and $-0.015 \leq \varepsilon_{\tau\tau} - \varepsilon_{\mu\mu} \leq 0.017$. The results are comparable to the current most stringent limits placed on the parameters by other experiments.

As robots increasingly coexist with humans, they must navigate complex, dynamic environments rich in visual information and implicit social dynamics, like when to yield or move through crowds. Addressing these challenges requires significant advances in vision-based sensing and a deeper understanding of socio-dynamic factors, particularly in tasks like navigation. To facilitate this, robotics researchers need advanced simulation platforms offering dynamic, photorealistic environments with realistic actors. Unfortunately, most existing simulators fall short, prioritizing geometric accuracy over visual fidelity, and employing unrealistic agents with fixed trajectories and low-quality visuals. To overcome these limitations, we developed a simulator that incorporates three essential elements: (1) photorealistic neural rendering of environments, (2) neurally animated human entities with behavior management, and (3) an ego-centric robotic agent providing multi-sensor output. By utilizing advanced neural rendering techniques in a dual-NeRF simulator, our system produces high-fidelity, photorealistic renderings of both environments and human entities. Additionally, it integrates a state-of-the-art Social Force Model to model dynamic human-human and human-robot interactions, creating the first photorealistic and accessible human-robot simulation system powered by neural rendering., Comment: 8 pages, 5 figures

Cross-view Geo-localisation is typically performed at a coarse granularity, because densely sampled satellite image patches overlap heavily. This heavy overlap would make disambiguating patches very challenging. However, by opting for sparsely sampled patches, prior work has placed an artificial upper bound on the localisation accuracy that is possible. Even a perfect oracle system cannot achieve accuracy greater than the average separation of the tiles. To solve this limitation, we propose combining cross-view geo-localisation and relative pose estimation to increase precision to a level practical for real-world application. We develop PEnG, a 2-stage system which first predicts the most likely edges from a city-scale graph representation upon which a query image lies. It then performs relative pose estimation within these edges to determine a precise position. PEnG presents the first technique to utilise both viewpoints available within cross-view geo-localisation datasets to enhance precision to a sub-metre level, with some examples achieving centimetre level accuracy. Our proposed ensemble achieves state-of-the-art precision - with relative Top-5m retrieval improvements on previous works of 213%. Decreasing the median euclidean distance error by 96.90% from the previous best of 734m down to 22.77m, when evaluating with 90 degree horizontal FOV images. Code will be made available: tavisshore.co.uk/PEnG, Comment: 8 pages, 6 figures

A kinetic model for granular mixtures is considered to study three different non-equilibrium situations. The model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle velocity and a gas of inelastic hard spheres. As a first problem, the relaxation of the velocity moments to their forms in the homogeneous cooling state (HCS) is studied. Then, taking the HCS as the reference state, the kinetic model is solved by the Chapman-Enskog method, which is conveniently adapted to inelastic collisions. For small spatial gradients, the mass, momentum and heat fluxes of the mixture are determined and exact expressions for the Navier-Stokes transport coefficients are obtained. As a third nonequilibrium problem, the kinetic model is solved exactly in the uniform shear flow (USF) state, where the rheological properties of the mixture are computed in terms of the parameter space of the mixture. In addition to the transport properties, the velocity distribution functions of each species are also explicitly obtained. To assess the reliability of the model, its theoretical predictions are compared with both (approximate) analytical results and computer simulations of the original Boltzmann equation. In general, the comparison shows a reasonable agreement between the two kinetic equations. While the diffusion transport coefficients show excellent agreement with the Boltzmann results, more quantitative differences appear in the case of the shear viscosity coefficient and the heat flux transport coefficients. In the case of the USF, although the model qualitatively captures the shear rate dependence of the rheological properties well, the discrepancies increase with increasing inelasticity in collisions., Comment: 25 pages; 11 figures; to be published in Phys. Fluids

CHANCES, the CHileAN Cluster galaxy Evolution Survey, will study the evolution of galaxies in and around ${\sim}$150 massive galaxy clusters, from the local universe out to z=0.45. CHANCES will use the new 4MOST Spectroscopic Survey Facility on the VISTA 4m telescope to obtain spectra for ${\sim}$500,000 galaxies with magnitudes $r_\mathrm{AB} < 20.5$, providing comprehensive spectroscopic coverage of each cluster out to $5r_{200}$. Its wide and deep scope will trace massive and dwarf galaxies from the surrounding filaments and groups to the cores of galaxy clusters, enabling the study of galaxy pre-processing and the role of the evolving environment on galaxy evolution. In this paper we present and characterize the sample of clusters and superclusters to be targeted by CHANCES. We used literature catalogues based on X-ray emission and Sunyaev-Zel'dovich effect to define the cluster sample in a homogeneous way, with attention to cluster mass and redshift, as well as the availability of ancillary data. We calibrated literature mass estimates from various surveys against each other and provide an initial mass estimate for each cluster, which we used to define the radial extent of the 4MOST coverage. We also present an initial assessment of the structure surrounding these clusters based on the redMaPPer red-sequence algorithm as a preview of some of the science CHANCES will enable., Comment: 11 pages, 9 figures, plus references and appendix containing catalog tables, submitted to A&A

We present a detailed study of the large-scale shock front in Stephan's Quintet, a byproduct of past and ongoing interactions. Using integral-field spectroscopy from the new William Herschel Telescope Enhanced Area Velocity Explorer (WEAVE), recent 144 MHz observations from the LOFAR Two-metre Sky Survey (LoTSS), and archival data from the Very Large Array and James Webb Space Telescope (JWST), we obtain new measurements of key shock properties and determine its impact on the system. Harnessing the WEAVE large integral field unit's (LIFU) field of view (90 $\times$ 78 arcsec$^{2}$), spectral resolution ($R\sim2500$) and continuous wavelength coverage across the optical band, we perform robust emission line modeling and dynamically locate the shock within the multi-phase intergalactic medium (IGM) with higher precision than previously possible. The shocking of the cold gas phase is hypersonic, and comparisons with shock models show that it can readily account for the observed emission line ratios. In contrast, we demonstrate that the shock is relatively weak in the hot plasma visible in X-rays (with Mach number of $\mathcal{M} \sim 2 - 4$), making it inefficient at producing the relativistic particles needed to explain the observed synchrotron emission. Instead, we propose that it has led to an adiabatic compression of the medium, which has increased the radio luminosity ten-fold. Comparison of the Balmer line-derived extinction map with the molecular gas and hot dust observed with JWST suggests that pre-existing dust may have survived the collision, allowing the condensation of H$_{2}$ - a key channel for dissipating the shock energy., Comment: 23 pages, 15 figures, accepted for publication in MNRAS

The delay experienced by a probe due to interactions with a scattering media is highly related to the internal dynamics inside that media. This property is well captured by the Wigner delay time and the resonance widths. By the use of the equivalence between the adjacency matrix of a random graph and the tight-binding Hamiltonian of the corresponding electronic media, the scattering matrix approach to electronic transport is used to compute Wigner delay times and resonance widths of Erd\"os-R\'enyi graphs and random geometric graphs, including bipartite random geometric graphs. In particular, the situation when a single-channel lead attached to the graphs is considered. Our results show a smooth crossover towards universality as the graphs become complete. We also introduce a parameter $\xi$, depending on the graph average degree $\langle k \rangle$ and graph size $N$, that scales the distributions of both Wigner delay times and resonance widths; highlighting the universal character of both distributions. Specifically, $\xi = \langle k \rangle N^{-\alpha}$ where $\alpha$ is graph-model dependent., Comment: 9 pages, 8 figures

We present a new non-perturbative model to describe the stopping power by ionization of the $d$-electrons of transition metals. These metals are characterized by the filling of the d-subshell and the promotion of part of the electrons to the conduction band. The contribution of d-electrons at low-impact energies has been noted experimentally in the past as a break of the linear dependence of the stopping power with the ion velocity. In this contribution, we describe the response of these electrons considering the atomic "inhomogeneous" momentum distribution. We focus on the transition metals of Groups 10 and 11 in the periodic table: Ni, Pd, Pt, Cu, Ag, and Au. Results describe the low energy-stopping power, with good agreement with the experimental data and available TDDFT results. By combining the present non-perturbative model for the $d$-subshell contribution with other approaches for the valence electrons and for the inner shells, we provide a coherent theoretical method capable of describing the stopping power of these transition metals from the very low to the high energy region., Comment: 13 figures. Manuscript submitted to Physical Review A, under evaluation

The dynamics and processes involved in particle-molecule scattering, including nuclear dynamics, is described and analyzed by different quantum information quantities along the different stages of the scattering. The main process studied and characterized with the information quantities is the interatomic coulombic electronic capture (ICEC), an inelastic process that can lead to dissociation of the target molecule. The analysis is focused in a one-dimensional transversely confined $\text{NeHe}$ molecule model used to simulate the scattering between an electron $\text{e}^-$(particle) and a $\text{NeHe}^+$ ion (molecule). The time-independent Schr\"odinger equation (TISE) is solved using the Finite Element Method (FEM) with a self-developed Julia package FEMTISE to compute potential energy curves (PECs) and the parameters of the interactions between particles. The time-dependent Schr\"odinger equation (TDSE) is solved using the Multi-configuration time-dependent Hartree (MCTDH) algorithm. The time dependent electronic and nuclear probability densities are calculated for different electron incoming energies, evidencing elastic and inelastic processes that can be correlated to changes in von Neumann entropy, conditional mutual information and Shannon entropies. The expectation value of the position of the particles, as well as their standard deviations, are analyzed along the whole dynamics and related to the entanglement during the collision and after the process is over, hence evidencing the dynamics of entanglement generation. It is shown that the correlations generated in the collision is partially retained only when the inelastic process is active.

Indirect dark matter detection methods are used to observe the products of dark matter annihilations or decays originating from astrophysical objects where large amounts of dark matter are thought to accumulate. With neutrino telescopes, an excess of neutrinos is searched for in nearby dark matter reservoirs, such as the Sun and the Galactic Centre, which could potentially produce a sizeable flux of Standard Model particles. The KM3NeT infrastructure, currently under construction, comprises the ARCA and ORCA undersea \v{C}erenkov neutrino detectors located at two different sites in the Mediterranean Sea, offshore of Italy and France, respectively. The two detector configurations are optimised for the detection of neutrinos of different energies, enabling the search for dark matter particles with masses ranging from a few GeV/c$^2$ to hundreds of TeV/c$^2$. In this work, searches for dark matter annihilations in the Galactic Centre and the Sun with data samples taken with the first configurations of both detectors are presented. No significant excess over the expected background was found in either of the two analyses. Limits on the velocity-averaged self-annihilation cross section of dark matter particles are computed for five different primary annihilation channels in the Galactic Centre. For the Sun, limits on the spin-dependent and spin-independent scattering cross sections of dark matter with nucleons are given for three annihilation channels.

The Arecibo Message was a brief binary-encoded communication transmitted into space from the Arecibo Observatory on November 16, 1974, intended to demonstrate human technological prowess. In late 2018, to commemorate the 45th anniversary of this message, the Arecibo Observatory initiated the New Arecibo Message competition. Following a series of challenges, our Boriken Voyagers team was recognized as the winner of the competition in August 2020. Although the primary objective of the competition was to conceptualize rather than transmit a message, the collapse of the Arecibo Telescope in December 2020 precluded any subsequent transmission efforts. Therefore, to commemorate the 50th anniversary of the Arecibo Message, this paper presents the Last Arecibo Message, as originally developed for the Arecibo Telescope. If the original message says "we are a form of life reaching out to connect", our message says "we are ready to explore the universe together." The prospect of transmitting this or a similar message remains an open question., Comment: 12 pages, 4 figures. Additional content is available at https://phl.upr.edu/message/

We introduce the Data Analysis Pipeline (DAP) for the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM) project, referred to as the LVM-DAP. We outline our methods for recovering both stellar and emission line components from the optical integral field spectroscopy, highlighting the developments and changes implemented to address specific challenges of the data set. The observations from the LVM project are unique because they cover a wide range of physical resolutions, from approximately 0.05 pc to 100 pc, depending on the distance to the targets. This, along with the varying number of stars sampled in each aperture (ranging from zero, just one of a few, to thousands), presents challenges in using previous spectral synthesis methods and interpreting the spectral fits. We provide a detailed explanation of how we model the stellar content and separate it from the ionized gas emission lines. To assess the accuracy of our results, we compare them with both idealized and more realistic simulations, highlighting the limitations of our methods. We find that the DAP robustly correct for stellar continuum features and recover emission line parameters (e.g. flux, equivalent width, systemtic velocity and velocity dispersion) with a precision and accuracy that fulfill the requirements of the primary goal of the analysis. In addition, the recovered stellar parameters are reliable for single stars, the recovery of integrated populations is less precise. We conclude with a description of the data products we provide, instructions for downloading and using our software, and a showcase illustrating the quality of the data and the analysis on a deep exposure taken on the Huygens region at the center of the Orion Nebula., Comment: 35 pages, 17 figures, 8 tables, accepted for publication in AJ

Hexagonal antiferromagnetic D019-Mn3X (X = Sn, Ge, Ga) compounds, with a non-collinear Kagome spin structure, are Weyl semimetals exhibiting novel topological transport properties. The longitudinal magnetoresistance of c-oriented epitaxial Ru/Mn3Ga thin films exhibits a positive quadratic dependence on magnetic field over a wide range of temperatures. Here we describe the transverse magnetoresistance, with the field in the out-of-plane direction, for c-oriented epitaxial GaN (0001)/Mn3Ga films. There is a transition from a negative linear to a positive quadratic dependence on magnetic field in the temperature range from 200 K to 300 K. The electrical resistivity shows a metallic to semiconductor transition at 230 K. By applying the electric field along two perpendicular in-plane directions we find asymmetry in the magnetoresistance curves due to self-spin polarized currents created through magnetic octupole clusters. First principles calculations confirmed the metallic to semiconductor transition corresponds to reordering the spin structure to a higher symmetry configuration., Comment: 16 pages, 4 figures, to be submitted to Nano Letters

We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy. Edify Image utilizes cascaded pixel-space diffusion models trained using a novel Laplacian diffusion process, in which image signals at different frequency bands are attenuated at varying rates. Edify Image supports a wide range of applications, including text-to-image synthesis, 4K upsampling, ControlNets, 360 HDR panorama generation, and finetuning for image customization.

Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges associated with combining machine learning technology with robotics, robot learning remains one of the most promising directions for enhancing the capabilities of robots. When deploying learning-based approaches on real robots, extra effort is required to address the challenges posed by various real-world factors. To investigate the key factors influencing real-world deployment and to encourage original solutions from different researchers, we organized the Robot Air Hockey Challenge at the NeurIPS 2023 conference. We selected the air hockey task as a benchmark, encompassing low-level robotics problems and high-level tactics. Different from other machine learning-centric benchmarks, participants need to tackle practical challenges in robotics, such as the sim-to-real gap, low-level control issues, safety problems, real-time requirements, and the limited availability of real-world data. Furthermore, we focus on a dynamic environment, removing the typical assumption of quasi-static motions of other real-world benchmarks. The competition's results show that solutions combining learning-based approaches with prior knowledge outperform those relying solely on data when real-world deployment is challenging. Our ablation study reveals which real-world factors may be overlooked when building a learning-based solution. The successful real-world air hockey deployment of best-performing agents sets the foundation for future competitions and follow-up research directions., Comment: Accept at NeurIPS 2024 Dataset and Benchmark Track

New metal-organic frameworks (MOFs) are periodically synthesized all over the world due to the wide range of societally and environmentally relevant applications they possess. However, the mechanisms and thermodynamics associated to MOF self-assembly are poorly understood because of the difficulties in studying such a multi-scale process with molecular-level resolution. In this work, we performed well-tempered metadynamics simulations of the early nucleation and late growth steps of the self-assembly of ZIF-4 using a reactive force field. We found that the formation of building blocks is a complex, multi-step process that involves changes in the coordination of the metal ion. Saturating the ligand coordination of a metal ion is more energetically favorable during growth than during early nucleation. The addition of a fourth ligand is less exergonic than it is for the first three and the associated free energy is highly dependent on the local environment of the undercoordinated metal ion. The stability of this bond depends on the strength of the solvent--metal ion interaction. Incorporating a ligand to a ZIF-1 crystal is less favorable compared to the more stable ZIF-4 polymorph. Milder differences were found when comparing the growth of (100), (010) and (001) ZIF-4 surfaces., Comment: 37 pages, 10 figures, 4 tables

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mis-modeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

Cognitive and neurological impairments are very common, but only a small proportion of affected individuals are diagnosed and treated, partly because of the high costs associated with frequent screening. Detecting pre-illness stages and analyzing the progression of neurological disorders through effective and efficient intelligent systems can be beneficial for timely diagnosis and early intervention. We propose using Large Language Models to extract features from free dialogues to detect cognitive decline. These features comprise high-level reasoning content-independent features (such as comprehension, decreased awareness, increased distraction, and memory problems). Our solution comprises (i) preprocessing, (ii) feature engineering via Natural Language Processing techniques and prompt engineering, (iii) feature analysis and selection to optimize performance, and (iv) classification, supported by automatic explainability. We also explore how to improve Chatgpt's direct cognitive impairment prediction capabilities using the best features in our models. Evaluation metrics obtained endorse the effectiveness of a mixed approach combining feature extraction with Chatgpt and a specialized Machine Learning model to detect cognitive decline within free-form conversational dialogues with older adults. Ultimately, our work may facilitate the development of an inexpensive, non-invasive, and rapid means of detecting and explaining cognitive decline.

Context: As the diversity and complexity of regulations affecting Software-Intensive Products and Services (SIPS) is increasing, software engineers need to address the growing regulatory scrutiny. As with any other non-negotiable requirements, SIPS compliance should be addressed early in SIPS engineering - i.e., during requirements engineering (RE). Objectives: In the conditions of the expanding regulatory landscape, existing research offers scattered insights into regulatory compliance of SIPS. This study addresses the pressing need for a structured overview of the state of the art in software RE and its contribution to regulatory compliance of SIPS. Method: We conducted a systematic mapping study to provide an overview of the current state of research regarding challenges, principles and practices for regulatory compliance of SIPS related to RE. We focused on the role of RE and its contribution to other SIPS lifecycle phases. We retrieved 6914 studies published from 2017 until 2023 from four academic databases, which we filtered down to 280 relevant primary studies. Results: We identified and categorized the RE-related challenges in regulatory compliance of SIPS and their potential connection to six types of principles and practices. We found that about 13.6% of the primary studies considered the involvement of both software engineers and legal experts. About 20.7% of primary studies considered RE in connection to other process areas. Most primary studies focused on a few popular regulation fields and application domains. Our results suggest that there can be differences in terms of challenges and involvement of stakeholders across different fields of regulation. Conclusion: Our findings highlight the need for an in-depth investigation of stakeholders' roles, relationships between process areas, and specific challenges for distinct regulatory fields to guide research and practice., Comment: Accepted to "Information and Software Technology" Journal