Search

We have developed a neutrino detector with threshold energies from ~0.115 to 105 MeV in a clean detection mode almost completely void of accidental backgrounds. It was initially developed for the NASA $\nu$SOL project to put a solar neutrino detector very close to the Sun with 1,000 to 10,000 times higher solar neutrino flux than on Earth. Similar interactions have been found for anti-neutrinos, which were initially intended for Beta decay neutrinos from reactors, geological sources, or for nuclear security applications. These techniques work at the 1 to 100 MeV region for neutrinos from the ORNL Spallation Neutron Source or low energy accelerator neutrino and anti-neutrino production targets less than $\sim$100 MeV. The identification process is clean, with a double pulse detection signature within a time window between the first interaction producing the conversion electron or positron and the secondary gamma emission 100 ns to ~1 $\mu$s, which removes most accidental backgrounds. These new modes for neutrino and anti-neutrino detection of low energy neutrinos and anti-neutrinos could allow improvements to neutrino interaction measurements from an accelerator beam on a target., Comment: Contribution to the 25th International Workshop on Neutrinos from Accelerators

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.

We study a flaring activity of the HSP Mrk421 that was characterized from radio to very-high-energy (VHE; E $>0.1$TeV) gamma rays with MAGIC, Fermi-LAT, Swift, XMM-Newton and several optical and radio telescopes. These observations included, for the first time for a gamma-ray flare of a blazar, simultaneous X-ray polarization measurements with IXPE. We find substantial variability in both X-rays and VHE gamma rays throughout the campaign, with the highest VHE flux above 0.2 TeV occurring during the IXPE observing window, and exceeding twice the flux of the Crab Nebula. However, the VHE and X-ray spectra are on average softer, and the correlation between these two bands weaker that those reported in previous flares of Mrk421. IXPE reveals an X-ray polarization degree significantly higher than that at radio and optical frequencies. The X-ray polarization angle varies by $\sim$100$^\circ$ on timescales of days, and the polarization degree changes by more than a factor 4. The highest X-ray polarization degree reaches 26%, around which a X-ray counter-clockwise hysteresis loop is measured with XMM-Newton. It suggests that the X-ray emission comes from particles close to the high-energy cutoff, hence possibly probing an extreme case of the Turbulent Extreme Multi-Zone model. We model the broadband emission with a simplified stratified jet model throughout the flare. The polarization measurements imply an electron distribution in the X-ray emitting region with a very high minimum Lorentz factor, which is expected in electron-ion plasma, as well as a variation of the emitting region size up to a factor of three during the flaring activity. We find no correlation between the fluxes and the evolution of the model parameters, which indicates a stochastic nature of the underlying physical mechanism. Such behaviour would be expected in a highly turbulent electron-ion plasma crossing a shock front., Comment: Submitted to Astronomy and Astrophysics. Corresponding authors: Axel Arbet-Engels, Lea Heckmann, David Paneque

OT 081 is a well-known, luminous blazar that is remarkably variable in many energy bands. We present the first broadband study of the source which includes very-high-energy (VHE, $E>$100\,GeV) $\gamma$-ray data taken by the MAGIC and H.E.S.S. imaging Cherenkov telescopes. The discovery of VHE $\gamma$-ray emission happened during a high state of $\gamma$-ray activity in July 2016, observed by many instruments from radio to VHE $\gamma$-rays. We identify four states of activity of the source, one of which includes VHE $\gamma$-ray emission. Variability in the VHE domain is found on daily timescales. The intrinsic VHE spectrum can be described by a power-law with index $3.27\pm0.44_{\rm stat}\pm0.15_{\rm sys}$ (MAGIC) and $3.39\pm0.58_{\rm stat}\pm0.64_{\rm sys}$ (H.E.S.S.) in the energy range of 55--300\,GeV and 120--500\,GeV, respectively. The broadband emission cannot be sucessfully reproduced by a simple one-zone synchrotron self-Compton model. Instead, an additional external Compton component is required. We test a lepto-hadronic model that reproduces the dataset well and a proton-synchrotron dominated model that requires an extreme proton luminosity. Emission models that are able to successfully represent the data place the emitting region well outside of the Broad Line Region (BLR) to a location at which the radiative environment is dominated by the infrared thermal radiation field of the dusty torus. In the scenario described by this flaring activity, the source appears to be an FSRQ, in contrast with past categorizations. This suggests that the source can be considered to be a transitional blazar, intermediate between BL~Lac and FSRQ objects., Comment: Accepted on MNRAS Corresponding authors: M. Manganaro, J. Becerra Gonz\'alez, M. Seglar-Arroyo, D. A. Sanchez

X-ray polarization is a unique new probe of the particle acceleration in astrophysical jets made possible through the Imaging X-ray Polarimetry Explorer. Here we report on the first dense X-ray polarization monitoring campaign on the blazar Mrk 421. Our observations were accompanied by an even denser radio and optical polarization campaign. We find significant short-timescale variability in both X-ray polarization degree and angle, including a $\sim90^\circ$ angle rotation about the jet axis. We attribute this to random variations of the magnetic field, consistent with the presence of turbulence but also unlikely to be explained by turbulence alone. At the same time, the degree of lower-energy polarization is significantly lower and shows no more than mild variability. Our campaign provides further evidence for a scenario in which energy-stratified shock-acceleration of relativistic electrons, combined with a turbulent magnetic field, is responsible for optical to X-ray synchrotron emission in blazar jets., Comment: 23 pages, including 8 pages of appendices. 12 figures, 3 tables. Submitted to ApJ

Security and RAS are two non-functional requirements under focus for current systems developed for the computing continuum. Due to the increased number of interconnected computer systems across the continuum, security becomes especially pervasive at all levels, from the smallest edge device to the high-performance cloud at the other end. Similarly, RAS (Reliability, Availability, and Serviceability) ensures the robustness of a system towards hardware defects. Namely, making them reliable, with high availability and design for easy service. In this paper and as a result of the Vitamin-V EU project, the authors detail the comprehensive approach to malware and hardware attack detection; as well as, the RAS features envisioned for future systems across the computing continuum.

Renewable energy is becoming an increasingly important component of energy systems. However, renewable energy production is heavily dependent on the prevailing weather conditions, which are changing as a result of climate change. It is therefore necessary to build energy systems that are robust to energy shortages caused by weather-dependent changes to energy demand and renewable energy production. To design such systems, we must monitor how changes in the climate are expected to influence future energy production and demand; this is important for policymakers to decide when, where, and by how much renewable energy installed capacities should be increased, for example. In this paper, we study the behaviour of standardised energy indices in future European climate projections, and use this to monitor how characteristics of energy production droughts in Europe are expected to change in the future. We use these results to make suggestions regarding how the energy mix should be adapted in the future to decrease the risk of energy production droughts., Comment: Main body: 14 pages, 7 Figures. Under review at Environmental Research Letters

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gamma-ray sources and precise measurements of the already discovered ones. To achieve these goals, both hardware and data analysis must employ cutting-edge techniques. This also applies to the LST-1, the first IACT built for the CTAO, which is currently taking data on the Canary island of La Palma. This paper introduces a new event reconstruction technique for IACT data, aiming to improve the image reconstruction quality and the discrimination between the signal and the background from misidentified hadrons and electrons. The technique models the development of the extensive air shower signal, recorded as a waveform per pixel, seen by CTAO telescopes' cameras. Model parameters are subsequently passed to random forest regressors and classifiers to extract information on the primary particle. The new reconstruction was applied to simulated data and to data from observations of the Crab Nebula performed by the LST-1. The event reconstruction method presented here shows promising performance improvements. The angular and energy resolution, and the sensitivity, are improved by 10 to 20% over most of the energy range. At low energy, improvements reach up to 22%, 47%, and 50%, respectively. A future extension of the method to stereoscopic analysis for telescope arrays will be the next important step., Comment: Accepted in A&A

Current star formation models are based on the local structure of the interstellar medium (ISM), yet the details on how the small-scale physics propagates up to global galactic-scale properties are still under debate. To investigate this we use {\small VINTERGATAN}, a high-resolution (20 pc) cosmological zoom-in simulation of a Milky Way-like galaxy. We study how the velocity dispersion and density structure of the ISM on 50-100 pc scales evolve with redshift, and quantify their impact on the star formation efficiency per free-fall timescale, $\epsilon_{\rm ff}$. During starbursts the ISM can reach velocity dispersions as high as $\sim 50$ km s$^{-1}$ for the densest and coldest gas, most noticeable during the last major merger event ($1.3 < z < 1.5$). After a merger-dominated phase ($11$ to 0.3\% at $z<1$. The mass-weighted average shows a universal $\langle \epsilon_{\rm ff} \rangle \approx 1\%$, caused by an almost invariant virial parameter distribution in star forming clouds. Changes in their density and turbulence levels are coupled so the kinetic-to-gravitational energy ratio remains close to constant. Finally, we show that a \textit{theoretically} motivated instantaneous $\epsilon_{\rm ff}$ is intrinsically different to its \textit{observational} estimates adopting tracers of star formation e.g. H$\alpha$. Since the physics underlying star formation can be lost on short ($\sim$ 10 Myr) timescales, caution must be taken when constraining star formation models from observational estimates of $\epsilon_{\rm ff}$., Comment: 14 pages, 6 figures, comments welcome

Accurate anomaly detection is critical in vision-based infrastructure inspection, where it helps prevent costly failures and enhances safety. Self-Supervised Learning (SSL) offers a promising approach by learning robust representations from unlabeled data. However, its application in anomaly detection remains underexplored. This paper addresses this gap by providing a comprehensive evaluation of SSL methods for real-world anomaly detection, focusing on sewer infrastructure. Using the Sewer-ML dataset, we evaluate lightweight models such as ViT-Tiny and ResNet-18 across SSL frameworks, including BYOL, Barlow Twins, SimCLR, DINO, and MAE, under varying class imbalance levels. Through 250 experiments, we rigorously assess the performance of these SSL methods to ensure a robust and comprehensive evaluation. Our findings highlight the superiority of joint-embedding methods like SimCLR and Barlow Twins over reconstruction-based approaches such as MAE, which struggle to maintain performance under class imbalance. Furthermore, we find that the SSL model choice is more critical than the backbone architecture. Additionally, we emphasize the need for better label-free assessments of SSL representations, as current methods like RankMe fail to adequately evaluate representation quality, making cross-validation without labels infeasible. Despite the remaining performance gap between SSL and supervised models, these findings highlight the potential of SSL to enhance anomaly detection, paving the way for further research in this underexplored area of SSL applications.

The Flat Spectrum Radio Quasar OP~313 entered an enhanced activity phase in November 2023 and has undergone multiple flares since then which have motivated the organisation of several large multi-wavelength campaigns, including two deep observations from the hard X-ray telescope NuSTAR. The broadband emission from OP~313 during these two observations is investigated under a new unified analysis framework, with data spanning from optical to gamma rays. Traditional methods for analyzing blazar emissions often rely on proprietary software tailored to specific instruments, making it challenging to integrate and interpret data from multi-wavelength campaigns comprehensively. This study demonstrates the feasibility of utilizing gammapy, an open-source Python package, and common data formats originally developed for gamma-ray instrumentation, to perform a consistent multi-instrument analysis. This enables a forward folding approach that fully incorporates source observations, detector responses, and various instrumental and astrophysical backgrounds. The methodology is applied as an example to recent data collected from the distant quasar OP~313. We present a comprehensive data reconstruction and analysis for instruments including the Liverpool Telescope's IO:O detector, Swift-UVOT, Swift-XRT, NuSTAR, and Fermi-LAT. The resulting spectral analysis is validated against the native tools for each instrument. Additionally, a multi-wavelength phenomenological model of the source emission, encompassing optical to gamma-ray bands, is developed, incorporating absorption components across different energy regimes. We introduce and validate a new unified framework for multi-wavelength forward folding data analysis based on gammapy and open data formats, demonstrating its application to spectral data from the quasar OP~313., Comment: 20 pages, 10 figures github: https://github.com/mireianievas/gammapy_mwl_workflow zenodo: https://zenodo.org/records/13837637

In this article, we describe the components and procedures for building a drone ready for networking experimentation. In particular, our drone design includes multiple technologies and elements such as 4G/5G connectivity for real-time data transmission, a 360-degree camera for immersive vision and AR/VR, precise GPS for navigation, and a powerful Linux-based system with GPU for computer vision experiments and applications. Component selection and assembly techniques are included, along with software integration for a smooth, seamless operation of advanced edge applications.

Instruments for gamma-ray astronomy at Very High Energies ($E>100\,{\rm GeV}$) have traditionally derived their scientific results through proprietary data and software. Data standardisation has become a prominent issue in this field both as a requirement for the dissemination of data from the next generation of gamma-ray observatories and as an effective solution to realise public data legacies of current-generation instruments. Specifications for a standardised gamma-ray data format have been proposed as a community effort and have already been successfully adopted by several instruments. We present the first production of standardised data from the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) telescopes. We converted $166\,{\rm h}$ of observations from different sources and validated their analysis with the open-source software Gammapy. We consider six data sets representing different scientific and technical analysis cases and compare the results obtained analysing the standardised data with open-source software against those produced with the MAGIC proprietary data and software. Aiming at a systematic production of MAGIC data in this standardised format, we also present the implementation of a database-driven pipeline automatically performing the MAGIC data reduction from the calibrated down to the standardised data level. In all the cases selected for the validation, we obtain results compatible with the MAGIC proprietary software, both for the manual and for the automatic data productions. Part of the validation data set is also made publicly available, thus representing the first large public release of MAGIC data. This effort and this first data release represent a technical milestone toward the realisation of a public MAGIC data legacy., Comment: Accepted for publication in the Journal of High Energy Astrophysics

The recent emergence of quantum confined nanomaterials in the field of radiation detection, in particular lead halide perovskite nanocrystals, offers potentially revolutionary scalability and performance advantages over conventional materials. This development raises fundamental questions about the mechanism of scintillation itself at the nanoscale and the role of particle size, arguably the most defining parameter of quantum dots. Understanding this is crucial for the design and optimisation of future nanotechnology scintillators. In this work, we address these open questions by theoretically and experimentally studying the size-dependent scintillation of CsPbBr3 nanocrystals using a combination of Monte Carlo simulations, spectroscopic, and radiometric techniques. The results reveal and unravel a complex parametric space where the fine balance between the simultaneous effects of size-dependent energy deposition, (multi-)exciton population, and light emission under ionizing excitation, typical of confined particles, combine to maximize the scintillation efficiency and time performance of larger nanocrystals due to greater stopping power and reduced Auger decay. The remarkable agreement between theory and experiment produces a fully validated descriptive model that unprecedentedly predicts the scintillation yield and kinetics of nanocrystals without free parameters, providing the first fundamental guide for the rational design of nanoscale scintillators.

Engineering biology requires precise control of biomolecular circuits, and Cybergenetics is the field dedicated to achieving this goal. A significant challenge in developing controllers for cellular functions is designing systems that can effectively manage molecular noise. To address this, there has been increasing effort to develop model-based controllers for stochastic biomolecular systems, where a major difficulty lies in accurately solving the chemical master equation. In this work we develop a framework for optimal and Model Predictive Control of stochastic gene regulatory networks with three key advantageous features: high computational efficiency, the capacity to control the overall probability density function enabling the fine-tuning of the cell population to obtain complex shapes and behaviors (including bimodality and other emergent properties), and the capacity to handle high levels of intrinsic molecular noise. Our method exploits an efficient approximation of the Chemical Master Equation using Partial Integro-Differential Equations, which additionally enables the development of an effective adjoint-based optimization. We illustrate the performance of the methods presented through two relevant studies in Synthetic Biology: shaping bimodal cell populations and tracking moving target distributions via inducible gene regulatory circuits.

Aviation's non-CO$_2$ effects, especially the impact of aviation-induced contrails, drive atmospheric changes and can influence climate dynamics. Although contrails are believed to contribute to global warming through their net warming effect, uncertainties persist due to the challenges in accurately measuring their radiative impacts. This study aims to address this knowledge gap by investigating the relationship between aviation-induced contrails, as observed in Meteosat Second Generation (MSG) satellite imagery, and their impact on radiative forcing (RF) over a two-week study. Results show that while daytime contrails generally have a cooling effect, the higher number of nighttime contrails results in a net warming effect over the entire day. Net RF values for detected contrails range approximately from -8 TW to 2.5 TW during the day and from 0 to 6 TW at night. Our findings also show a 41.03% increase in contrail coverage from January 24-30, 2023, to the same week in 2024, accompanied by a 128.7% rise in contrail radiative forcing (CRF), indicating greater warming from the added contrails. These findings highlight the necessity of considering temporal factors, such as the timing and duration of contrail formation, when assessing their overall warming impact. They also indicate a potential increase in contrail-induced warming from 2023 to 2024, attributable to the rise in contrail coverage. Further investigation into these trends is crucial for the development of effective mitigation strategies., Comment: SESAR Innovation Days 2024

Sewerage infrastructure is among the most expensive modern investments requiring time-intensive manual inspections by qualified personnel. Our study addresses the need for automated solutions without relying on large amounts of labeled data. We propose a novel application of Self-Supervised Learning (SSL) for sewer inspection that offers a scalable and cost-effective solution for defect detection. We achieve competitive results with a model that is at least 5 times smaller than other approaches found in the literature and obtain competitive performance with 10\% of the available data when training with a larger architecture. Our findings highlight the potential of SSL to revolutionize sewer maintenance in resource-limited settings., Comment: Poster at the LatinX in AI Workshop @ ICML 2024

Direct redshift determination of BL Lac objects is highly challenging as the emission in the optical and near-infrared (NIR) bands is largely dominated by the non-thermal emission from the relativistic jet that points very close to our line of sight. Therefore, their optical spectra often show no emission lines from the host galaxy. In this work, we aim to overcome this difficulty by attempting to detect the host galaxy and derive redshift constraints based on assumptions on the galaxy magnitude ("imaging redshifts"). Imaging redshifts are derived by obtaining deep optical images under good seeing conditions, so that it is possible to detect the host galaxy as weak extension of the point-like source. We then derive the imaging redshift by using the host galaxy as a standard candle using two different methods. We determine imaging redshift for 9 out of 17 blazars that we observed as part of this program. The redshift range of these targets is 0.28-0.60 and the two methods used to derive the redshift give very consistent results within the uncertainties. We also performed a detailed comparison of the imaging redshifts with those obtained by other methods, like direct spectroscopic constraints or looking for groups of galaxies close to the blazar. We show that the constraints from different methods are consistent and that for example in the case of J2156.0+1818, which is the most distant source for which we detect the host galaxy, combining the three constraints narrows down the redshift to $0.63

We present multiwavelength polarization measurements of the luminous blazar Mrk~501 over a 14-month period. The 2--8 keV X-ray polarization was measured with the Imaging X-ray Polarimetry Explorer (IXPE) with six 100-ks observations spanning from 2022 March to 2023 April. Each IXPE observation was accompanied by simultaneous X-ray data from NuSTAR, Swift/XRT, and/or XMM-Newton. Complementary optical-infrared polarization measurements were also available in the B, V, R, I, and J bands, as were radio polarization measurements from 4.85 GHz to 225.5 GHz. Among the first five IXPE observations, we did not find significant variability in the X-ray polarization degree and angle with IXPE. However, the most recent sixth observation found an elevated polarization degree at $>3\sigma$ above the average of the other five observations. The optical and radio measurements show no apparent correlations with the X-ray polarization properties. Throughout the six IXPE observations, the X-ray polarization degree remained higher than, or similar to, the R-band optical polarization degree, which remained higher than the radio value. This is consistent with the energy-stratified shock scenario proposed to explain the first two IXPE observations, in which the polarized X-ray, optical, and radio emission arises from different regions., Comment: Accepted for publication in ApJ

With the advent of next-generation AR/VR headsets, many of them with affordable prices, telecom operators have forecasted an explosive growth of traffic in their networks. Penetration of AR/VR services and applications is estimated to grow exponentially in the next few years. This work attempts to shed light on the bandwidth capacity requirements and latency of popular AR/VR applications with four different real experimental settings on the Meta Quest 3 headsets, and their potential impact on the network.

Long-term adherence to medication is a critical factor in preventing chronic diseases, such as cardiovascular disease. To address poor adherence, physicians may recommend adherence-improving interventions; however, such interventions are costly and limited in their availability. Knowing which patients will stop adhering helps distribute the available resources more effectively. We developed a binary integer program (BIP) model to select patients for adherence-improving intervention under budget constraints. We further studied a long-term adherence prediction model using dynamic logistic regression (DLR) model that uses patients' claim data, medical health factors, demographics, and monitoring frequencies to predict the risk of future non-adherence. We trained and tested our predictive model to longitudinal data for cardiovascular disease in a large cohort of patients taking medication for cholesterol control seen in the national Veterans Affairs health system. Our study shows the importance of including past adherence to increase prediction accuracy. Finally, we assess the potential benefits of using the prediction model by proposing an algorithm that combines the DLR and BIP models to decrease the number of CVD events in a population.

Experimentally obtained X-ray diffraction (XRD) patterns can be difficult to solve, precluding the full characterization of materials, pharmaceuticals, and geological compounds. Herein, we propose a method based upon a multi-objective evolutionary search that uses both a structure's enthalpy and similarity to a reference XRD pattern (constituted by a list of peak positions and their intensities) to facilitate structure solution of inorganic systems. Because the similarity index is computed for locally optimized cells that are subsequently distorted to find the best match with the reference, this process transcends both computational (e.g. choice of theoretical method, and 0 K approximation) and experimental (e.g. external stimuli, and metastability) limitations. We illustrate how the proposed methodology can be employed to successfully uncover complex crystal structures by applying it to a range of test cases, including inorganic minerals, pure elements ramp-compressed to extreme conditions, and molecular crystals. The results demonstrate that our approach not only improves the accuracy of structure prediction but also significantly reduces the time required to achieve reliable solutions, thus providing a powerful tool for the advancement of materials science and related fields.

Context: There are currently three pulsars firmly detected by imaging atmospheric Cherenkov telescopes (IACTs), two of them reaching TeV energies, challenging models of very-high-energy (VHE) emission in pulsars. More precise observations are needed to better characterize pulsar emission at these energies. The LST-1 is the prototype of the Large-Sized Telescope, that will be part of the Cherenkov Telescope Array Observatory (CTAO). Its improved performance over previous IACTs makes it well suited for studying pulsars. Aims: To study the Crab pulsar emission with the LST-1, improving and complementing the results from other telescopes. These observations can also be used to characterize the potential of the LST-1 to study other pulsars and detect new ones. Methods: We analyzed a total of $\sim$103 hours of gamma-ray observations of the Crab pulsar conducted with the LST-1 in the period from September 2020 to January 2023. The observations were carried out at zenith angles less than 50 degrees. A new analysis of the Fermi-LAT data was also performed, including $\sim$14 years of observations. Results: The Crab pulsar phaseogram, long-term light-curve, and phase-resolved spectra are reconstructed with the LST-1 from 20 GeV to 450 GeV for P1 and up to 700 GeV for P2. The pulsed emission is detected with a significance of 15.2$\sigma$. The two characteristic emission peaks of the Crab pulsar are clearly detected (>10$\sigma$), as well as the so-called bridge emission (5.7$\sigma$). We find that both peaks are well described by power laws, with spectral indices of $\sim$3.44 and $\sim$3.03 respectively. The joint analysis of Fermi-LAT and LST-1 data shows a good agreement between both instruments in the overlapping energy range. The detailed results obtained in the first observations of the Crab pulsar with LST-1 show the potential that CTAO will have to study this type of sources., Comment: Accepted by A&A

New technologies such as Machine Learning (ML) gave great potential for evaluating industry workflows and automatically generating key performance indicators (KPIs). However, despite established standards for measuring the efficiency of industrial machinery, there is no precise equivalent for workers' productivity, which would be highly desirable given the lack of a skilled workforce for the next generation of industry workflows. Therefore, an ML solution combining data from manufacturing processes and workers' performance for that goal is required. Additionally, in recent times intense effort has been devoted to explainable ML approaches that can automatically explain their decisions to a human operator, thus increasing their trustworthiness. We propose to apply explainable ML solutions to differentiate between expert and inexpert workers in industrial workflows, which we validate at a quality assessment industrial workstation. Regarding the methodology used, input data are captured by a manufacturing machine and stored in a NoSQL database. Data are processed to engineer features used in automatic classification and to compute workers' KPIs to predict their level of expertise (with all classification metrics exceeding 90 %). These KPIs, and the relevant features in the decisions are textually explained by natural language expansion on an explainability dashboard. These automatic explanations made it possible to infer knowledge from expert workers for inexpert workers. The latter illustrates the interest of research in self-explainable ML for automatically generating insights to improve productivity in industrial workflows., Comment: IEEE Industrial Electronics Magazine (2023)

We report a colloidal synthesis of blue emissive, stable cube-shaped CsPbBr3 quantum dots (QDs) in the strong quantum confinement regime via a dissolution-recrystallization starting from pre-synthesized (KxCs1-x)4PbBr6 nanocrystals which are then reacted with PbBr2. This is markedly different from the known case of Cs4PbBr6 nanocrystals that react within seconds with PbBr2 and get transformed into much larger, green emitting CsPbBr3 nanocrystals. Here, instead, the conversion of (KxCs1-x)4PbBr6 nanocrystals to CsPbBr3 QDs occurs in a time span of hours, and tuning of the QDs size is achieved by adjusting the concentration of precursors. The QDs exhibit excitonic features in optical absorption that are tunable in the 420 - 452 nm range, accompanied by blue photoluminescence with quantum yield around 60%. Detailed spectroscopic investigations in both the single and multi-exciton regime reveal the exciton fine structure and the effect of Auger recombination of these CsPbBr3 QDs, confirming theoretical predictions for this system.

This paper describes our experience implementing a Hypervisor extension for a 64-bit RISC-V processor. We describe the design process and the main required parts with a brief explanation of each one., Comment: RISC-V Summit Europe 2023, June 5-9, 2023

The Lorentz Invariance Violation (LIV), a proposed consequence of certain quantum gravity (QG) scenarios, could instigate an energy-dependent group velocity for ultra-relativistic particles. This energy dependence, although suppressed by the massive QG energy scale $E_\mathrm{QG}$, expected to be on the level of the Planck energy $1.22 \times 10^{19}$ GeV, is potentially detectable in astrophysical observations. In this scenario, the cosmological distances traversed by photons act as an amplifier for this effect. By leveraging the observation of a remarkable flare from the blazar Mrk\,421, recorded at energies above 100 GeV by the MAGIC telescopes on the night of April 25 to 26, 2014, we look for time delays scaling linearly and quadratically with the photon energies. Using for the first time in LIV studies a binned-likelihood approach we set constraints on the QG energy scale. For the linear scenario, we set $95\%$ lower limits $E_\mathrm{QG}>2.7\times10^{17}$ GeV for the subluminal case and $E_\mathrm{QG}> 3.6 \times10^{17}$ GeV for the superluminal case. For the quadratic scenario, the $95\%$ lower limits for the subluminal and superluminal cases are $E_\mathrm{QG}>2.6 \times10^{10}$ GeV and $E_\mathrm{QG}>2.5\times10^{10}$ GeV, respectively.

We report the X-ray polarization properties of the high-synchrotron-peaked (HSP) blazar PKS 2155$-$304 based on observations with the Imaging X-ray Polarimetry Explorer (IXPE). We observed the source between Oct 27 and Nov 7, 2023. We also conducted an extensive contemporaneous multiwavelength (MW) campaign. We find that during the first half ($T_1$) of the IXPE pointing, the source exhibited the highest X-ray polarization degree detected for an HSP blazar thus far, (30.7$\pm$2.0)%, which dropped to (15.3$\pm$2.1)% during the second half ($T_2$). The X-ray polarization angle remained stable during the IXPE pointing at 129.4$^\circ$$\pm$1.8$^\circ$ and 125.4$^\circ$$\pm$3.9$^\circ$ during $T_1$ and $T_2$, respectively. Meanwhile, the optical polarization degree remained stable during the IXPE pointing, with average host-galaxy-corrected values of (4.3$\pm$0.7)% and (3.8$\pm$0.9)% during the $T_1$ and $T_2$, respectively. During the IXPE pointing, the optical polarization angle changed achromatically from $\sim$140$^\circ$ to $\sim$90$^\circ$ and back to $\sim$130$^\circ$. Despite several attempts, we only detected (99.7% conf.) the radio polarization once (during $T_2$, at 225.5 GHz): with degree (1.7$\pm$0.4)% and angle 112.5$^\circ$$\pm$5.5$^\circ$. The direction of the broad pc-scale jet is rather ambiguous and has been found to point to the east and south at different epochs; however, on larger scales (> 1.5 pc) the jet points toward the southeast ($\sim$135$^\circ$), similar to all of the MW polarization angles. Moreover, the X-ray to optical polarization degree ratios of $\sim$7 and $\sim$4 during $T_1$ and $T_2$, respectively, are similar to previous IXPE results for several HSP blazars. These findings, combined with the lack of correlation of temporal variability between the MW polarization properties, agree with an energy-stratified shock-acceleration scenario in HSP blazars., Comment: 17 pages, 10 figures, 4 tables, Accepted for publication in A&A

IOP4 is a pipeline to perform photometry and polarimetry analysis of optical data from Calar Alto (CAHA) and Sierra Nevada (OSN) observatories. IOP4 implements Object Relational Mapping (ORM) to seamlessly integrate all information about the reduction and results in a database which can be used to query and plot results, flag data and inspect the reduction process in an integrated fashion with the whole pipeline. It also ships with an already built-in web interface which can be used out of the box to browse the database and supervise all pipeline processes. It is built to ease debugging and inspection of data. Reduction from five different instruments are already implemented: RoperT90, AndorT90 and DIPOL (at OSN 0.9m telescope), AndorT150 (OSN 1.5m telescope) and CAFOS (CAHA 2.2m telescope). IOP4's modular design allows for easy integration of new observatories and instruments, and its results have already featured in several high-impact refereed publications. In this paper we describe the implementation and characteristics of IOP4., Comment: Submitted April 23, 2024

Surface-adsorbed rare-earth nanostructures are ideal platforms to investigate the interplay between intra-atomic interactions and multi-orbital spin configurations. However, addressing these properties has posed severe experimental and theoretical challenges. Here, we use the orbital selectivity offered by X-ray absorption spectroscopy to quantify the Coulomb integrals of Nd atoms on conductive surfaces, as well as the variation of individual orbital occupation upon cluster nucleation. Using X-ray magnetic circular dichroism we identify magnetic moments of the order of \MK{few tens of}~$\mu_{\rm{B}}$ at the $5d$ orbitals and their magnetic coupling with the $4f$ spins. Our results validate orbital-resolved X-ray spectroscopy as a reliable method for quantifying complex multi-orbital interactions in surface-adsorbed lanthanides.

In this paper we study networks of nodes characterised by binary traits that change both endogenously and through nearest-neighbour interaction. Our analytical results show that those traits can be ranked according to the noisiness of their transmission using only measures of order in the stationary state. Crucially, this ranking is independent of network topology. As an example, we explain why, in line with a long-standing hypothesis, the relative stability of the structural traits of languages can be estimated from their geospatial distribution. We conjecture that similar inferences may be possible in a more general class of Markovian systems. Consequently, in many empirical domains where longitudinal information is not easily available the propensities of traits to change could be estimated from spatial data alone., Comment: 6+78 pages, 4+23 figures

Context. The blazar AO 0235+164, located at redshift $z=0.94$, has displayed interesting and repeating flaring activity in the past, the latest episodes occurring in 2008 and 2015. In 2020, the source brightened again, starting a new flaring episode that peaked in 2021. Aims. We study the origin and properties of the 2021 flare in relation to previous studies and the historical behavior of the source, in particular to the 2008 and 2015 flaring episodes. Methods. We analyze the multi-wavelength photo-polarimetric evolution of the source. From Very Long Baseline Array images, we derive the kinematic parameters of new components associated with the 2021 flare. We use this information to constrain a model for the spectral energy distribution of the emission during the flaring period. We propose an analytical geometric model to test whether the observed wobbling of the jet is consistent with precession. Results. We report the appearance of two new components that are ejected in a different direction than previously, confirming the wobbling of the jet. We find that the direction of ejection is consistent with that of a precessing jet.The derived period independently agrees with the values commonly found in the literature. Modeling of the spectral energy distribution further confirm that the differences between flares can be attributed to geometrical effects., Comment: Accepted 15 May 2024

A CubeSat with a prototype scintillating detector with a sensitive volume of GAGG crystal is being developed with a possible launch date of 2025. Its purpose is to characterize the background signals that mimic the neutrino interaction that the nuSOL team is looking for. An important part of the characterization of the backgrounds and the expected real signal is understanding the gamma ray detection efficiency of the prototype detector. To this end we have used and developed three techniques to do an absolute measurement of gamma ray efficiency. The first is using EC sources that emit an X-ray before prompt emission of a de-excitation gamma ray, specifically Zn-65 and Mn-54. The second is using a beta + decay source wherein a positron annihilates on an atomic shell electron producing two back-to-back 511 keV gammas followed promptly by a de-excitation gamma, specifically Na-22. The third is using a gamma cascade of two near-simultaneous de-excitation gammas from the same nucleus, specifically from Co-60 decay., Comment: 27 pages. 29 Figures. This is soon to be a Nuclear Instruments and Methods Article

Methods.We applied distinct selection criteria to attain an SFG sample with minimal AGN contamination. Multiple approaches were used to estimate the intrinsic extinction, SFR and gas-phase metallicity for the SFGs. In conjunction with findings in the literature, we examined the correlation between SFRs and stellar masses ($M_*$), as well as the metallicity evolution depending on $M_*$. Finally, the 3D relationship between $M_*$, SFR and metallicity, is also studied.} Results. From the initial spectroscopic sample of 409 FIR-selected objects from the Lockman--SpReSO catalogue, 69 (17\%) AGNs have been identified and excluded, which is nearly double the percentage found in local studies, leaving a sample of 340 SFGs. The analysis of the $M_*$--SFR relationship revealed that Lockman--SpReSO IR-selected SFGs show signs of evolution at redshifts $z>0.4$, shifting above the main sequence, with a mean value of $\sim0.4$ dex. They are located within the starburst galaxy region since 78\% of the galaxies fall into this category. In addition, no evident flattening was found in the relation to specific SFR with redshift for $\log M_* (M_\odot) \gtrsim 10.5$. In line with the $M_*$--metallicity relation (MZR) outcomes published in previous studies for optically selected SFGs, however, during the analysis of the MZR, it was found that IR-selected SFGs exhibit lower metallicities than those anticipated on the basis of their $M_*$ and redshift. During the investigation of the 3D $M_*$--SFR--metallicity relation (FP), it was established that the research sample is consistent with relations in the existing literature, with an average scatter of $\sim0.2$ dex. However, a re-calibration of the FP when using the SFR obtained from the IR luminosity is required and, in this case, no attenuation in the correlation for $\log M_* (M_\odot) \gtrsim 10.5$ is observed., Comment: 21 pages, 17 figures, accepted in A&A

Reconfigurable computing offers a good balance between flexibility and energy efficiency. When combined with software-programmable devices such as CPUs, it is possible to obtain higher performance by spatially distributing the parallelizable sections of an application throughout the reconfigurable device while the CPU is in charge of control-intensive sections. This work introduces an elastic Coarse-Grained Reconfigurable Architecture (CGRA) integrated into an energy-efficient RISC-V-based SoC designed for the embedded domain. The microarchitecture of CGRA supports conditionals and irregular loops, making it adaptable to domain-specific applications. Additionally, we propose specific mapping strategies that enable the efficient utilization of the CGRA for both simple applications, where the fabric is only reconfigured once (one-shot kernel), and more complex ones, where it is necessary to reconfigure the CGRA multiple times to complete them (multi-shot kernels). Large kernels also benefit from the independent memory nodes incorporated to streamline data accesses. Due to the integration of CGRA as an accelerator of the RISC-V processor enables a versatile and efficient framework, providing adaptability, processing capacity, and overall performance across various applications. The design has been implemented in TSMC 65 nm, achieving a maximum frequency of 250 MHz. It achieves a peak performance of 1.22 GOPs computing one-shot kernels and 1.17 GOPs computing multi-shot kernels. The best energy efficiency is 72.68 MOPs/mW for one-shot kernels and 115.96 MOPs/mW for multi-shot kernels. The design integrates power and clock-gating techniques to tailor the architecture to the embedded domain while maintaining performance. The best speed-ups are 17.63x and 18.61x for one-shot and multi-shot kernels. The best energy savings in the SoC are 9.05x and 11.10x for one-shot and multi-shot kernels., Comment: 14 pages, 11 figures

Defect tolerance is a critical enabling factor for efficient lead-halide perovskite materials, but the current understanding is primarily on band-edge (cold) carriers, with significant debate over whether hot carriers (HCs) can also exhibit defect tolerance. Here, this important gap in the field is addressed by investigating how internationally-introduced traps affect HC relaxation in CsPbX3 nanocrystals (X = Br, I, or mixture). Using femtosecond interband and intraband spectroscopy, along with energy-dependent photoluminescence measurements and kinetic modelling, it is found that HCs are not universally defect tolerant in CsPbX3, but are strongly correlated to the defect tolerance of cold carriers, requiring shallow traps to be present (as in CsPbI3). It is found that HCs are directly captured by traps, instead of going through an intermediate cold carrier, and deeper traps cause faster HC cooling, reducing the effects of the hot phonon bottleneck and Auger reheating. This work provides important insights into how defects influence HCs, which will be important for designing materials for hot carrier solar cells, multiexciton generation, and optical gain media., Comment: 18 pages, 5 figures

The aim of this article is to solve the system $XA=Y$ where $A=(a_{ij})\in M_{m\times n}(S)$, $Y\in S^{m}$ and $X$ is an unknown vector of size $n$, being $S$ an additively idempotent semiring. If the system has solutions then we completely characterize its maximal one, and in the particular case where $S$ is a generalized tropical semiring a complete characterization of its solutions is provided as well as an explicit bound of the computational cost associated to its computation. Finally, when $S$ is finite, we give a cryptographic application by presenting an attack to the key exchange protocol proposed by Maze, Monico and Rosenthal., Comment: 24 pages

Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common errors or misconceptions among real students. To date, the task of crafting high-quality distractors largely remains a labor and time-intensive process for teachers and learning content designers, which has limited scalability. In this work, we study the task of automated distractor generation in the domain of math MCQs and explore a wide variety of large language model (LLM)-based approaches, from in-context learning to fine-tuning. We conduct extensive experiments using a real-world math MCQ dataset and find that although LLMs can generate some mathematically valid distractors, they are less adept at anticipating common errors or misconceptions among real students., Comment: NAACL 2024 findings

In this work, we investigate methods to reduce the noise in deep saliency maps coming from convolutional downsampling. Those methods make the investigated models more interpretable for gradient-based saliency maps, computed in hidden layers. We evaluate the faithfulness of those methods using insertion and deletion metrics, finding that saliency maps computed in hidden layers perform better compared to both the input layer and GradCAM. We test our approach on different models trained for image classification on ImageNet1K, and models trained for tumor detection on Camelyon16 and in-house real-world digital pathology scans of stained tissue samples. Our results show that the checkerboard noise in the gradient gets reduced, resulting in smoother and therefore easier to interpret saliency maps.

This paper explores the application of Human-in-the-Loop (HITL) strategies in training machine learning models in the medical domain. In this case a doctor-in-the-loop approach is proposed to leverage human expertise in dealing with large and complex data. Specifically, the paper deals with the integration of genomic data and Whole Slide Imaging (WSI) analysis of breast cancer. Three different tasks were developed: segmentation of histopathological images, classification of this images regarding the genomic subtype of the cancer and, finally, interpretation of the machine learning results. The involvement of a pathologist helped us to develop a better segmentation model and to enhance the explainatory capabilities of the models, but the classification results were suboptimal, highlighting the limitations of this approach: despite involving human experts, complex domains can still pose challenges, and a HITL approach may not always be effective.

The BL Lac object 3C 371 has been observed by the Transiting Exoplanet Survey Satellite (\textit{TESS}) for approximately a year, between July 2019 and July 2020, with an unmatched 2-minute observing cadence. In parallel, the Whole Earth Blazar Telescope (WEBT) Collaboration organized an extensive observing campaign, providing three years of continuous optical monitoring between 2018 and 2020. These datasets allow for a thorough investigation of the variability of the source. The goal of this study is evaluating the optical variability of 3C 371. Taking advantage of the remarkable cadence of \textit{TESS} data, we aim to characterize the intra-day variability (IDV) displayed by the source and identify its shortest variability timescale. With this estimate, constraints on the size of the emitting region and black hole mass can be calculated. Moreover, WEBT data is used to investigate long-term variability (LTV), including understanding spectral behaviour of the source and the polarization variability. Based on the derived characteristics, information on the origin of the variability on different timescales is extracted. We evaluated the variability applying the variability amplitude tool that quantifies how variable the emission is. Moreover, we employed common tools like ANOVA (ANalysis Of VAariance) tests, wavelet and power spectral density (PSD) analyses to characterize the shortest variability timescales present in the emission and the underlying noise affecting the data. Short- and long-term colour behaviours have been evaluated to understand the spectral behaviour of the source. The polarized emission was analyzed, studying its variability and possible rotation patterns of the electric vector position angle (EVPA). Flux distributions of IDV and LTV were also studied with the aim of linking the flux variations to turbulent and/or accretion disc related processes., Comment: Accepted in A&A, 20 pages, 19 figures

In this paper, we revisit the data for the galaxy cluster ZwCl 0024.0+1652 provided by the GLACE survey and study the mass--metallicity function and its relationship with the environment. Here we describe an alternative way to reduce the data from OSIRIS tunable filters. This method gives us better uncertainties in the fluxes of the emission lines and the derived quantities. We present an updated catalogue of cluster galaxies with emission in H$\alpha$ and [N\,{\sc{ii}}] $\lambda\lambda$6548,6583. We also discuss the biases of these new fluxes and describe the way in which we calculated the mass--metallicity relationship and its uncertainties. We generated a new catalogue of 84 emission-line galaxies with reliable fluxes in [N\,{\sc{ii}}] and H$\alpha$ lines from a list of 174 galaxies. We find a relationship between the clustercentric radius and the density of galaxies. We derived the mass--metallicity relationship for ZwCl 0024.0+1652 and compared it with clusters and field galaxies from the literature. We find a difference in the mass--metallicity relationship when compared to more massive clusters, with the latter showing on average higher values of abundance. This could be an effect of the quenching of the star formation, which seems to be more prevalent in low-mass galaxies in more massive clusters. We find little to no difference between ZwCl 0024.0+1652 galaxies and field galaxies located at the same redshift., Comment: 13 pages, 17 figures, accepted for publication in Astronomy and Astrophysics

We build on the concept of eigenvector continuation to develop an efficient multi-state method for the rigorous and smooth interpolation of a small training set of many-body wavefunctions through chemical space at mean-field cost. The inferred states are represented as variationally optimal linear combinations of the training states transferred between the many-body basis of different nuclear geometries. We show that analytic multi-state forces and nonadiabatic couplings from the model enable application to nonadiabatic molecular dynamics, developing an active learning scheme to ensure a compact and systematically improvable training set. This culminates in application to the nonadiabatic molecular dynamics of a photoexcited 28-atom hydrogen chain, with surprising complexity in the resulting nuclear motion. With just 22 DMRG calculations of training states from the low-energy correlated electronic structure at different geometries, we infer the multi-state energies, forces and nonadiabatic coupling vectors at 12,000 geometries with provable convergence to high accuracy along an ensemble of molecular trajectories, which would not be feasible with a brute force approach. This opens up a route to bridge the timescales between accurate single-point correlated electronic structure methods and timescales of relevance for photo-induced molecular dynamics.

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

PG 1553+113 is one of the few blazars with a convincing quasi-periodic emission in the gamma-ray band. The source is also a very high-energy (VHE; >100 GeV) gamma-ray emitter. To better understand its properties and identify the underlying physical processes driving its variability, the MAGIC Collaboration initiated a multiyear, multiwavelength monitoring campaign in 2015 involving the OVRO 40-m and Medicina radio telescopes, REM, KVA, and the MAGIC telescopes, Swift and Fermi satellites, and the WEBT network. The analysis presented in this paper uses data until 2017 and focuses on the characterization of the variability. The gamma-ray data show a (hint of a) periodic signal compatible with literature, but the X-ray and VHE gamma-ray data do not show statistical evidence for a periodic signal. In other bands, the data are compatible with the gamma-ray period, but with a relatively high p-value. The complex connection between the low and high-energy emission and the non-monochromatic modulation and changes in flux suggests that a simple one-zone model is unable to explain all the variability. Instead, a model including a periodic component along with multiple emission zones is required., Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Society. 19 pages, 9 figures. Corresponding authors: Elisa Prandini, Antonio Stamerra, Talvikki Hovatta

Blazars present highly variable $\gamma$-ray emission. This variability, which can range from a few minutes to several years, is also observed at other wavelengths across the entire electromagnetic spectrum. We make use of the first 12 years of data from the Fermi Large Area Telescope (LAT), complemented with multiwavelength (MWL) archival data from different observatories and facilities in radio, infrared and optical bands, to study the possible periodic emission from 19 blazars previously claimed as periodic candidates. A periodicity analysis is performed with a pipeline for periodicity searches. Moreover, we study the cross-correlations between the $\gamma$-ray and MWL light curves. Additionally, we use the fractional variability and the structure function to evaluate the variability timescales. We find five blazars showing hints of periodic modulation with $\geq$3.0$\sigma$ ($\approx$0$\sigma$ post-trials), with periods ranging from 1.2 to 4 years, both in their $\gamma$-ray and MWL emission. The results provide clues for understanding the physical mechanisms generating the observed periodicity., Comment: 21 pages, 5 figures

We show that a previously introduced key exchange based on a congruence-simple semiring action is not secure by providing an attack that reveals the shared key from the distributed public information for any of such semirings