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A key step in Adaptive Radiation Therapy (ART) workflows is the evaluation of the patient's anatomy at treatment time to ensure the accuracy of the delivery. To this end, Cone Beam Computerized Tomography (CBCT) is widely used being cost-effective and easy to integrate into the treatment process. Nonetheless, CBCT images have lower resolution and more artifacts than CT scans, making them less reliable for precise treatment validation. Moreover, in complex treatments such as Total Marrow and Lymph Node Irradiation (TMLI), where full-body visualization of the patient is critical for accurate dose delivery, the CBCT images are often discontinuous, leaving gaps that could contain relevant anatomical information. To address these limitations, we propose ARTInp (Adaptive Radiation Therapy Inpainting), a novel deep-learning framework combining image inpainting and CBCT-to-CT translation. ARTInp employs a dual-network approach: a completion network that fills anatomical gaps in CBCT volumes and a custom Generative Adversarial Network (GAN) to generate high-quality synthetic CT (sCT) images. We trained ARTInp on a dataset of paired CBCT and CT images from the SynthRad 2023 challenge, and the performance achieved on a test set of 18 patients demonstrates its potential for enhancing CBCT-based workflows in radiotherapy.

This paper presents BOUQuET, a multicentric and multi-register/domain dataset and benchmark, and its broader collaborative extension initiative. This dataset is handcrafted in non-English languages first, each of these source languages being represented among the 23 languages commonly used by half of the world's population and therefore having the potential to serve as pivot languages that will enable more accurate translations. The dataset is specially designed to avoid contamination and be multicentric, so as to enforce representation of multilingual language features. In addition, the dataset goes beyond the sentence level, as it is organized in paragraphs of various lengths. Compared with related machine translation (MT) datasets, we show that BOUQuET has a broader representation of domains while simplifying the translation task for non-experts. Therefore, BOUQuET is specially suitable for the open initiative and call for translation participation that we are launching to extend it to a multi-way parallel corpus to any written language.

In this work, we present a novel approach to multi-label chest X-ray (CXR) image classification that enhances clinical interpretability while maintaining a streamlined, single-model, single-run training pipeline. Leveraging the CheXpert dataset and VisualCheXbert-derived labels, we incorporate hierarchical label groupings to capture clinically meaningful relationships between diagnoses. To achieve this, we designed a custom hierarchical binary cross-entropy (HBCE) loss function that enforces label dependencies using either fixed or data-driven penalty types. Our model achieved a mean area under the receiver operating characteristic curve (AUROC) of 0.903 on the test set. Additionally, we provide visual explanations and uncertainty estimations to further enhance model interpretability. All code, model configurations, and experiment details are made available., Comment: 9 pages with 3 figures, for associated implementation see https://github.com/the-mercury/CIHMLC

We confirm the conjecture posed by Gu{\'e}don, Hinrichs, Litvak, and Prochno in 2017 that $\mathbb{E}\|(a_{ij}g_{ij})_{i\le m, j\le n}\colon \ell_p^n \to \ell_q^m\|$ is comparable, up to constants depending only on $p$ and $q$, to \[ \max_i \|(a_{ij})_j\|_{p^*} +\max_j \|(a_{ij})_i\|_{q} +\mathbb{E} \max_{i,j} |a_{ij}g_{ij}| \] provided that $1\le p<2

Recent research has explored methods for updating and modifying factual knowledge in large language models, often focusing on specific multi-layer perceptron blocks. This study expands on this work by examining the effectiveness of existing knowledge editing methods across languages and delving into the role of attention mechanisms in this process. Drawing from the insights gained, we propose Mass-Editing Memory with Attention in Transformers (MEMAT), a method that achieves significant improvements in all metrics while requiring minimal parameter modifications. MEMAT delivers a remarkable 10% increase in magnitude metrics, benefits languages not included in the training data and also demonstrates a high degree of portability. Our code and data are at https://github.com/dtamayo-nlp/MEMAT.

In 2022, fuel combustion in road transport accounted for approximately 21% (760 million tonnes) of CO2 emissions in the European Union (EU). Road transport is the only sector with rising emissions, with an increase of 24% compared to 1990. The EU initially aimed to ban new CO2-emitting cars by 2030 but has since delayed this target to 2035, underscoring the ongoing challenges in the push for rapid decarbonisation. The pace of decarbonisation in this sector will either ease or intensify the pressure on other sectors to stay within the EU's carbon budget. This paper explores the effects of speeding up or slowing down the transition in road transport. We reveal that a slower decarbonisation path not only drives up system costs by 126 billion Euro/a (6%) but also demands more than a doubling of the CO2 price from 137 to 290 Euro/tCO2 in 2030 to trigger decarbonisation in other sectors. On the flip side, accelerating the shift to cleaner transport proves to be the most cost-effective strategy, giving room for more gradual changes in the heating and industrial sectors, while reducing the reliance on carbon removal in later years. Earlier mandates than currently envisaged by the EU can avoid stranded assets and save up to 43 billion Euro/a compared to current policies.

The observed correlation between inner super-Earths and outer gas giants places strong constraints on formation theories. Building on previous work, Bryan $\&$ Lee 2024 showed that there is a statistically significant positive correlation between super-Earths and outer gas giants around metal-rich FGK stars, and that this correlation disappears for metal-poor hosts. Here we consider how this connection evolves across stellar mass. Starting with our sample of 85 M-dwarfs ($<$0.6 M$_{\odot}$) hosting inner super-Earths, we calculate P(GG|SE, [Fe/H]$>$0) = 9.4 (+10.2 -3.1)$\%$ and P(GG|SE, [Fe/H]$\leq$0)$<$3.1$\%$. Compared to the field gas giant frequency calculated from the Rosenthal et al 2021 sample, we find P(GG|[Fe/H]$>$0) = 10.3 (+6.9 -3.1)$\%$, and P(GG|[Fe/H]$\leq$0)$<$2.6$\%$ for M-dwarfs. While we see a higher gas giant frequency around metal-rich M-dwarfs for both samples, we find no significant correlations between super-Earths and gas giants. Combining our 85 M-dwarf sample with our FGK sample from Bryan $\&$ Lee 2024, we resolve the SE/GG correlation in stellar mass (0.3--1.5 M$_{\odot}$) and metallicity. We show the positive correlation emerges in metal-rich K-dwarfs and strengthens with increasing stellar mass. Gas giant properties also impact the correlation -- for metal rich stars, the positive correlation is strengthened by: 1) dynamically hot gas giants for all stellar masses; 2) distant gas giants only for higher mass stars; and 3) single gas giants for K-dwarfs and multiple gas giants around more massive stars. We discuss how the stellar mass dependence of the inner-outer planet correlation can be understood from the increasing disk mass budget for higher mass stars., Comment: accepted to ApJL

Computational Fluid Dynamics (CFD) plays a pivotal role in fluid mechanics, enabling precise simulations of fluid behavior through partial differential equations (PDEs). However, traditional CFD methods are resource-intensive, particularly for high-fidelity simulations of complex flows, which are further complicated by high dimensionality, inherent stochasticity, and limited data availability. This paper addresses these challenges by proposing a data-driven approach that leverages a Gaussian Mixture Variational Autoencoder (GMVAE) to encode high-dimensional scientific data into low-dimensional, physically meaningful representations. The GMVAE learns a structured latent space where data can be categorized based on physical properties such as the Reynolds number while maintaining global physical consistency. To assess the interpretability of the learned representations, we introduce a novel metric based on graph spectral theory, quantifying the smoothness of physical quantities along the latent manifold. We validate our approach using 2D Navier-Stokes simulations of flow past a cylinder over a range of Reynolds numbers. Our results demonstrate that the GMVAE provides improved clustering, meaningful latent structure, and robust generative capabilities compared to baseline dimensionality reduction methods. This framework offers a promising direction for data-driven turbulence modeling and broader applications in computational fluid dynamics and engineering systems.

Purpose: We present a virtual model to optimize point of entry (POE) in lung biopsy planning systems. Our model allows to compute the quality of a biopsy sample taken from potential POE, taking into account the margin of error that arises from discrepancies between the orientation in the planning simulation and the actual orientation during the operation. Additionally, the study examines the impact of the characteristics of the lesion. Methods: The quality of the biopsy is given by a heatmap projected onto the skeleton of a patient-specific model of airways. The skeleton provides a 3D representation of airways structure, while the heatmap intensity represents the potential amount of tissue that it could be extracted from each POE. This amount of tissue is determined by the intersection of the lesion with a cone that represents the uncertainty area in the introduction of biopsy instruments. The cone, lesion, and skeleton are modelled as graphical objects that define a 3D scene of the intervention. Results: We have simulated different settings of the intervention scene from a single anatomy extracted from a CT scan and two lesions with regular and irregular shapes. The different scenarios are simulated by systematic rotation of each lesion placed at different distances from airways. Analysis of the heatmaps for the different settings show a strong impact of lesion orientation for irregular shape and the distance for both shapes. Conclusion: The proposed heatmaps help to visually assess the optimal POE and identify whether multiple optimal POEs exist in different zones of the bronchi. They also allow us to model the maximum allowable error in navigation systems and study which variables have the greatest influence on the success of the operation. Additionally, they help determine at what point this influence could potentially jeopardize the operation.

Mechanical quantum systems, such as resonators and levitated particles, offer unique opportunities for quantum metrology. Particularly, their significant mass and quantum-level control enable applications in measuring gravitational effects. This article highlights key challenges, alongside potential solutions to advance precision sensing and quantum-gravitational research., Comment: 4 pages, 1 figure

Liquid metal (LM)-based composites hold promise for soft electronics due to their high conductivity and fluidic nature. However, the presence of {\alpha}_Ga2O3 and GaOOH layers around LM droplets impairs conductivity and performance. We tackle this issue by replacing the oxide layer with conductive silver (Ag) using an ultrasonic_assisted galvanic replacement reaction. The Ag_coated nanoparticles form aggregated, porous microparticles that are mixed with styrene_isoprene_styrene (SIS) polymers, resulting in a digitally printable composite with superior electrical conductivity and electromechanical properties compared to conventional fillers. Adding more LM enhances these properties further. The composite achieves EMI shielding effectiveness (SE) exceeding 75 dB in the X_band frequency range, even at 200 per cent strain, meeting stringent military and medical standards. It is applicable in wireless communications and Bluetooth signal blocking and as a thermal interface material (TIM). Additionally, we highlight its recyclability using a biodegradable solvent, underscoring its eco_friendly potential. This composite represents a significant advancement in stretchable electronics and EMI shielding, with implications for wearable and bioelectronic applications.

Non-thermal photo-ionized plasmas are now established in the laboratory, and require models that treat the atomic processes and electron distribution self-consistently. We investigate the effects of inelastic thermalization in iron under intense X-ray irradiation using the atomic model BigBarT, suited for the self-consistent evolution of the electron continuum, including degeneracy effects. Our study focuses particularly on collisional $M$-shell ionization, which we identify as the dominant relaxation process of the non-thermal electrons. We show that $M$-shell satellite intensities are sensitive to non-thermal ionization, providing a potential method to refine collisional cross sections that are otherwise difficult to compute due to their proximity to the continuum and the associated plasma screening effects.

Here we present results from our spectroscopic follow-up of SDSS J2320+0024, a candidate binary supermassive black hole (SMBH) with a suspected sub-pc separation, identified by a 278-day periodicity observed in its multi-band optical light curves. We investigate the dramatic variability of the complex Mg II emission line profile aiming to test the alignments of the observed photometric light curves and the spectroscopic signatures in the context of the binary SMBH system. We extract the pure broad Mg II line from the newly obtained Gemini and Magellan spectra and measure the emission line parameters to reveal fundamental dynamical parameters of the SMBHs binary system. We adopt the PoSKI sub-pc binary SMBH model, which includes broad-line region (BLR) around less massive component and a circumbinary BLR, to interpret the observed variability in the spectral profile. We find that the Mg II line profile has a distinctive complex shape with the asymmetry and two peaks present which is varying across recent and archival observations. The temporal variability of the Mg II line profile may be associated with the emission from the binary SMBH system consisting of components with masses $M_1 = 2 \times 10^7 \, M_{\odot}$ and $M_2 = 2 \times 10^8 \, M_{\odot}$, and eccentricity e = 0.1. With an total estimated mass of $\sim 10^9 M_{\odot}$ and a subannual orbital period, this system may be a rare example of high-mass compact candidate of SMBH binary, thus important for further investigations of the evolution of the binary system. This study is a prototype of synergies of spectroscopic follow-up and future massive time-domain photometric surveys like Vera C. Rubin Observatory Legacy Survey of Space and Time., Comment: Accepted for publication in A&A

Road transport is responsible for about a quarter of Europe's greenhouse gas emissions, making its transformation a crucial part of Europe's overall decarbonization goals. Current European policies promote decarbonizing the transport sector and passenger car sales show an increased adoption of electric vehicles. Full electrification of land transport will significantly increase the average electricity demand but the use of smart charging and vehicle-to-grid could provide additional flexibility to balance wind and solar generation. In this study, we find cost-optimal transition pathways of the European land transport sector embedded in the sector-coupled open energy model PyPSA-Eur. We consider fossil-fueled, hydrogen-fueled, and electric cars using a 3-hour time resolution for a full year and covering 33 interconnected European countries. We analyze a transition path from 2025 to 2050 under different carbon budgets corresponding to a 1.7{\deg}C and 2{\deg}C temperature increase. Our results show that rapid electrification of road transport reduces the total system cost, even in the absence of climate targets. We see a clear preference for rapidly decommissioning internal combustion engine vehicles and using electric vehicles in all countries and under all carbon budgets. Allowing smart charging of electric vehicles decreases the total system cost by 1.6% because it reduces the need to install stationary batteries by almost 40%.

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

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

The syntactic structure of a sentence can be described as a tree that indicates the syntactic relationships between words. In spite of significant progress in unsupervised methods that retrieve the syntactic structure of sentences, guessing the right direction of edges is still a challenge. As in a syntactic dependency structure edges are oriented away from the root, the challenge of guessing the right direction can be reduced to finding an undirected tree and the root. The limited performance of current unsupervised methods demonstrates the lack of a proper understanding of what a root vertex is from first principles. We consider an ensemble of centrality scores, some that only take into account the free tree (non-spatial scores) and others that take into account the position of vertices (spatial scores). We test the hypothesis that the root vertex is an important or central vertex of the syntactic dependency structure. We confirm that hypothesis and find that the best performance in guessing the root is achieved by novel scores that only take into account the position of a vertex and that of its neighbours. We provide theoretical and empirical foundations towards a universal notion of rootness from a network science perspective.

In semiconductor hole spin qubits, low magnetic field ($B$) operation extends the coherence time ($T_\mathrm{2}^*$) but proportionally reduces the gate speed. In contrast, singlet-triplet (ST) qubits are primarily controlled by the exchange interaction ($J$) and can thus maintain high gate speeds even at low $B$. However, a large $J$ introduces a significant charge component to the qubit, rendering ST qubits more vulnerable to charge noise when driven. Here, we demonstrate a highly coherent ST hole spin qubit in germanium, operating at both low $B$ and low $J$. By modulating $J$, we achieve resonant driving of the ST qubit, obtaining an average gate fidelity of $99.68\%$ and a coherence time of $T_\mathrm{2}^*=1.9\,\mu$s. Moreover, by applying the resonant drive continuously, we realize a dressed ST qubit with a tenfold increase in coherence time ($T_\mathrm{2\rho}^*=20.3\,\mu$s). Frequency modulation of the driving signal enables universal control, with an average gate fidelity of $99.64\%$. Our results demonstrate the potential for extending coherence times while preserving high-fidelity control of germanium-based ST qubits, paving the way for more efficient operations in semiconductor-based quantum processors.

This article describes a procedure for measuring and evaluating radio impulsive noise (IN) from a specific source. A good knowledge of the noise caused by different sources is essential to plan radio services and to ensure good quality of service. Moreover, it is necessary to harmonize noise measurement methods to achieve results that can be mutually compared. This article not only provides steps that should be followed to make proper measurements, but also specifies appropriate parameters to characterize the IN when it is generated by a principal source. A detailed description of parameter calculation is presented, based on the recommendations of the International Telecommunication Union (ITU). This answers the request made in an ITU-R 214-4/3 question, which suggests determining the appropriate parameters to describe the noise when it has an impulsive characteristic.

The interaction of body worn antennas with the human body causes a significant decrease in the antenna efficiency and a shift in the resonant frequency. A resonant slot in a small conductive box placed on the body has been shown to reduce these effects. The specific absorption rate (SAR) is less than international health standards for most wearable antennas due to the small transmitter power. This paper reports the linear relationship between the power absorbed by biological tissues at different locations on the body, and the radiation efficiency based on numerical modeling (r = 0.99). While the -10 dB bandwidth of the antenna remains constant and equal to 12.5%, the maximum frequency shift occurs when the antenna is close to the elbow (6.61%) and on the thigh (5.86%). The smallest change was found on the torso (4.21%). Participants with body-mass index (BMI) between 17 and 29 kg/m2 took part in experimental measurements, where the maximum frequency shift was 2.51%. Measurements show better agreement with simulations on the upper arm. These experimental results demonstrate that the BMI for each individual has little effect on the performance of the antenna.

This paper investigates deteriorations in knee and ankle dynamics during running. Changes in lower limb accelerations are analyzed by a wearable musculo-skeletal monitoring system. The system employs a machine learning technique to classify joint stiffness. A maximum-entropyrate method is developed to select the most relevant features. Experimental results demonstrate that distance travelled and energy expended can be estimated from observed changes in knee and ankle motions during 5 km runs.

Recent observations from JWST have revealed an abundant population of active galactic nuclei (AGN) and so-called ``Little Red Dots'' (LRDs) at $2\lesssim z \lesssim 11$, many of which are characterized by V-shaped UV-to-optical continua with turnovers around the Balmer limit. The physical nature of these LRDs is unclear, and it remains debated whether the peculiar spectral shape originates from AGN, compact galaxies, or both. We present the analysis of new NIRSpec-IFU data from the BlackTHUNDER JWST Large Programme and archival NIRSpec-MSA data of a lensed LRD at $z=7.04$. The spectra confirm the presence of a smooth Balmer break and a broad H$\beta$ tracing the Broad Line Region (BLR) of an AGN. The small velocity dispersion of the H$\beta$ narrow component indicates a small dynamical mass of the host galaxy of $M_{\rm dyn}<4 \times 10^8~M_{\odot}$, which implies that the stellar population cannot contribute more than 10% to the optical continuum. We show that the Balmer break can be well described by an AGN continuum absorbed by very dense ($n_{\rm H}\sim 10^{10}~{\rm cm^{-3}}$) and nearly dust-free gas along our line-of-sight (possibly gas in the BLR or its surrounding). The same gas is expected to produce H$\beta$ absorption, at a level consistent with a tentative detection ($3\sigma$) in the high-resolution spectrum. Such a non-stellar origin of the Balmer break may apply to other LRDs, and would alleviate the issue of extremely high stellar mass surface densities inferred in the case of a stellar interpretation of the Balmer break. We note that this is a rare case of a black hole that is overmassive relative to both the host galaxy stellar and dynamical masses. We finally report indications of variability and the first attempt of AGN reverberation mapping at such an early epoch., Comment: 34 pages, 24 figures, submitted to MNRAS

We revisit the convex integration constructions for the Monge-Amp\`ere system and prove its flexibility in dimension $d=2$ and codimension $k=3$, up to $\mathcal{C}^{1,1-1/\sqrt{5}}$. To our knowledge, it is the first result in which the obtained H\"older exponent $1-\frac{1}{\sqrt{5}}$ is larger than $1/2$ but it is not contained in the full flexibility up to $\mathcal{C}^{1,1}$ result. Previous various approaches, based on Kuiper's corrugations, always led to the H\"older regularity not exceeding $\mathcal{C}^{1,1/2}$, while constructions based on the Nash spirals (when applicable) led to the regularity $\mathcal{C}^{1,1}$. Combining the two approaches towards an interpolation between their corresponding exponent ranges has been so far an open problem.

Molecular dynamics (MD)-based path sampling algorithms are a very important class of methods used to study the energetics and kinetics of rare (bio)molecular events. They sample the highly informative but highly unlikely reactive trajectories connecting different metastable states of complex (bio)molecular systems. The metadynamics of paths (MoP) method proposed by Mandelli, Hirshberg, and Parrinello [Pys. Rev. Lett. 125 2, 026001 (2020)] is based on the Onsager-Machlup path integral formalism. This provides an analytical expression for the probability of sampling stochastic trajectories of given duration. In practice, the method samples reactive paths via metadynamics simulations performed directly in the phase space of all possible trajectories. Its parallel implementation is in principle infinitely scalable, allowing arbitrarily long trajectories to be simulated. Paving the way for future applications to study the thermodynamics and kinetics of protein-ligand (un)binding, a problem of great pharmaceutical interest, we present here the efficient implementation of MoP in the HPC-oriented biomolecular simulation software GROMACS. Our benchmarks on a membrane protein (150,000 atoms) show an unprecedented weak scaling parallel efficiency of over 70% up to 3200 GPUs on the pre-exascale JUWELS Booster machine at the J\"ulich Supercomputing Center., Comment: 13 pages, 6 figures, 1 table, short technical report

Detecting the first generation of stars, Population III (PopIII), has been a long-standing goal in astrophysics, yet they remain elusive even in the JWST era. Here we present a novel NIRCam-based selection method for PopIII galaxies, and carefully validate it through completeness and contamination simulations. We systematically search ~500 arcmin$^{2}$ across JWST legacy fields for PopIII candidates, including GLIMPSE which, assisted by gravitational lensing, has produced JWST's deepest NIRCam imaging thus far. We discover one promising PopIII galaxy candidate (GLIMPSE-16043) at $z=6.50^{+0.03}_{-0.24}$, a moderately lensed galaxy (mu=2.9) with an intrinsic UV magnitude of $M_{UV}$=-15.89. It exhibits key PopIII features: strong H$\alpha$ emission (rest-frame EW $2810\pm550$\AA); a Balmer jump; no dust (UV slope $\beta=-2.34\pm0.36$); and undetectable metal lines (e.g., [OIII]; [OIII]/H$\beta$<0.44) implying a gas-phase metallicity of Zgas/Zsun<0.5%. These properties indicate the presence of a nascent, metal-deficient young stellar population (<5Myr) with a stellar mass of $\simeq10^{5}M_{\odot}$. Intriguingly, this source deviates significantly from the extrapolated UV-metallicity relation derived from recent JWST observations at $z=4-10$, consistent with UV enhancement by a top-heavy PopIII initial mass function or the presence of an extremely metal-poor AGN. We also derive the first observational constraints on the PopIII UV luminosity function at z~6-7. The volume density of GLIMPSE-16043 ($\approx10^{-4}$ cMpc$^{-3}$) is in excellent agreement with theoretical predictions, independently reinforcing its plausibility. This study demonstrates the power of our novel NIRCam method to finally reveal distant galaxies even more pristine than the Milky Way's most metal-poor satellites, thereby promising to bring us closer to the first generation of stars than we have ever been before., Comment: 41 pages, 20 figures, and 10 Tables. Submitted to ApJ. Comments are welcome!

Underwater noise pollution from human activities, particularly shipping, has been recognised as a serious threat to marine life. The sound generated by vessels can have various adverse effects on fish and aquatic ecosystems in general. In this setting, the estimation and analysis of the underwater noise produced by vessels is an important challenge for the preservation of the marine environment. In this paper we propose a model for the spatio-temporal characterisation of the underwater noise generated by vessels. The approach is based on the reconstruction of the vessels' trajectories from Automatic Identification System (AIS) data and on their deployment in a spatio-temporal database. Trajectories are enriched with semantic information like the acoustic characteristics of the vessels' engines or the activity performed by the vessels. We define a model for underwater noise propagation and use the trajectories' information to infer how noise propagates in the area of interest. We develop our approach for the case study of the fishery activities in the Northern Adriatic sea, an area of the Mediterranean sea which is well known to be highly exploited. We implement our approach using MobilityDB, an open source geospatial trajectory data management and analysis platform, which offers spatio-temporal operators and indexes improving the efficiency of our system. We use this platform to conduct various analyses of the underwater noise generated in the Northern Adriatic Sea, aiming at estimating the impact of fishing activities on underwater noise pollution and at demonstrating the flexibility and expressiveness of our approach.

In this work, we consider the so-called correlated random walk system (also known as correlated motion or persistent motion system), used in biological modelling, among other fields, such as chromatography. This is a linear system which can also be seen as a weakly damped wave equation with certain boundary conditions. We are interested in the long-time behaviour of its solutions. To be precise, we will prove that the decay of the solutions to this problem is of exponential form, where the optimal decay rate exponent is given by the dominant eigenvalue of the corresponding operator. This eigenvalue can be obtained as a particular solution of a system of transcendental equations. A complete description of the spectrum of the operator is provided, together with a comprehensive analysis of the corresponding eigenfunctions and their geometry., Comment: 24 pages, 6 figures

In this paper, we study the trajectory of a classic SIR epidemic on a family of dynamic random graphs of fixed size, whose set of edges continuously evolves over time. We set general infection and recovery times, and start the epidemic from a positive, yet small, proportion of vertices. We show that in such a case, the spread of an infectious disease around a typical individual can be approximated by the spread of the disease in a local neighbourhood of a uniformly chosen vertex. We formalize this by studying general dynamic random graphs that converge dynamically locally in probability and demonstrate that the epidemic on these graphs converges to the epidemic on their dynamic local limit graphs. We provide a detailed treatment of the theory of dynamic local convergence, which remains a relatively new topic in the study of random graphs. One main conclusion of our paper is that a specific form of dynamic local convergence is required for our results to hold.

Background: Evidence maps have been used in healthcare to understand existing evidence and to support decision-making. In oncology they have been used to summarise evidence within a disease area but have not been used to compare evidence across different diseases. As an increasing number of oncology drugs are licensed for multiple indications, visualising the accumulation of evidence across all indications can help inform policy-makers, support evidence synthesis approaches, or to guide expert elicitation on appropriate cross-indication assumptions. Methods: The multi-indication oncology therapy bevacizumab was selected as a case-study. We used visualisation methods including timeline, ridgeline and split-violin plots to display evidence across seven licensed cancer types, focusing on the evolution of evidence on overall and progression-free survival over time as well as the quality of the evidence available. Results: Evidence maps for bevacizumab allow for visualisation of patterns in study-level evidence, which can be updated as evidence accumulates over time. The developed tools display the observed data and synthesised evidence across- and within-indications. Limitations: The effectiveness of the plots produced are limited by the lack of complete and consistent reporting of evidence in trial reports. Trade-offs were necessary when deciding the level of detail that could be shown while keeping the plots coherent. Conclusions: Clear graphical representations of the evolution and accumulation of evidence can provide a better understanding of the entire evidence base which can inform judgements regarding the appropriate use of data within and across indications. Implications: Improved visualisations of evidence can help the development of multi-indication evidence synthesis. The proposed evidence displays can lead to the efficient use of information for health technology assessment., Comment: 22 pages, 6 figures

Phonon polaritons (PhPs) -- light coupled to lattice vibrations -- in polar van der Waals (vdW) crystals are promising candidates for controlling the flow of energy at the nanoscale due to their strong field confinement, anisotropic propagation, and ultra-long lifetime in the picosecond range \cite{ref1,ref2,ref3,ref4,ref5}. However, the lack of tunability in their narrow and material-specific spectral range -- the Reststrahlen Band (RB) -- severely limits their technological implementation. Here, we demonstrate that the intercalation of Na atoms in the vdW semiconductor $\alpha$-V$_2$O$_5$ enables a broad spectral shift of RBs, and that the PhPs excited exhibit ultra-low losses (lifetime of $4 \pm 1$~ps), similar to PhPs in the non-intercalated crystal (lifetime of $6 \pm 1$ ps). We expect our intercalation method to be applicable to other vdW crystals, opening the door for the use of PhPs in broad spectral bands in the mid-infrared domain., Comment: 15 pages, 5 figures

Standard deep neural network inference involves the computation of interleaved linear maps and nonlinear activation functions. Prior work for ultra-low latency implementations has hardcoded these operations inside FPGA lookup tables (LUTs). However, FPGA LUTs can implement a much greater variety of functions. In this paper, we propose a novel approach to training DNNs for FPGA deployment using multivariate polynomials as the basic building block. Our method takes advantage of the flexibility offered by the soft logic, hiding the polynomial evaluation inside the LUTs with minimal overhead. By using polynomial building blocks, we achieve the same accuracy using considerably fewer layers of soft logic than by using linear functions, leading to significant latency and area improvements. LUT-based implementations also face a significant challenge: the LUT size grows exponentially with the number of inputs. Prior work relies on a priori fixed sparsity, with results heavily dependent on seed selection. To address this, we propose a structured pruning strategy using a bespoke hardware-aware group regularizer that encourages a particular sparsity pattern that leads to a small number of inputs per neuron. We demonstrate the effectiveness of PolyLUT on three tasks: network intrusion detection, jet identification at the CERN Large Hadron Collider, and MNIST., Comment: arXiv admin note: text overlap with arXiv:2309.02334

We provide the first reference framework for extremely metal-poor (XMP) OB-type stars. We parsed a grid of 0.10 $Z_{\odot}$ FASTWIND models, covering the parameter space of O stars and early-B supergiants, through contemporary spectral classification criteria to deliver a calibration of key stellar properties as a function of spectral type, and tabulated colours for the most common photometric systems. By using an extensive grid of models, we account for the different combinations of stellar parameters that result in the same spectral morphology and provide a range of parameters and colours compatible with each spectral subtype and luminosity class. We supply updated photometric criteria to optimize candidate selection of OB stars in XMP environments. We find 0.10 $Z_{\odot}$ OB stars are 1-6 kK hotter and produce higher ionizing fluxes than their Galactic analogues. In addition, we find a bimodal distribution of the HeII-ionizing flux with spectral type; because of its known dependence on effective temperature and the wind, $\log~q_{HeII}$ for individual XMP late-O type stars could be underestimated by up to 4 orders of magnitude by other calibrations, some of them used by population synthesis codes. Finally, we used our calibrated colours to map the extinction of the 0.10 $Z_{\odot}$ galaxy Sextans A finding that reddening is non-negligible and uneven., Comment: Accepted in MNRAS

Objective: Speech tests aim to estimate discrimination loss or speech recognition threshold (SRT). This paper investigates the potential to estimate SRTs from clinical data that target at characterizing the discrimination loss. Knowledge about the relationship between the speech test outcome variables--conceptually linked via the psychometric function--is important towards integration of data from different databases. Design: Depending on the available data, different SRT estimation procedures were compared and evaluated. A novel, model-based SRT estimation procedure was proposed that deals with incomplete patient data. Interpretations of supra-threshold deficits were assessed for the two interpretation modes. Study sample: Data for 27009 patients with Freiburg monosyllabic speech test (FMST) and audiogram (AG) results from the same day were included in the retrospective analysis. Results: The model-based SRT estimation procedure provided accurate SRTs, but with large deviations in the estimated slope. Supra-threshold hearing loss components differed between the two interpretation modes. Conclusions: The model-based procedure can be used for SRT estimation, and its properties relate to data availability for individual patients. All SRT procedures are influenced by the uncertainty of the word recognition scores. In the future, the proposed approach can be used to assess additional differences between speech tests.

The main objective of this work is to derive the distribution of the the metal content of HII galaxies using sulphur as an abundance tracer. This increases the metallicity range that can safely be reached. We selected a sample of emission-line galaxies that we extracted from the SDSS-DR16. These objects have a redshift of z less than 0.04 so that the [SIII] 9069 A emission line and H beta equivalent widths that are higher than 10 A in emission were included, and they are compact in appearance. We used the so-called direct method for objects with the electron-temperature-sensitive [SIII] 6312 A emission line, and an empirical method based on the S23 parameter. The last provided an abundance calibration that monotonically increased up to at least the solar value, and can be applied based on the spectral range from 6000 to 9500 A alone. We show that the bias that is introduced when the [OIII] 4363 A line is required restricts the sample to objects with an [OIII] electron temperature higher than 10,000K, and their temperature distribution is then rather narrow. For objects with determinations of te [SIII], the distribution is flatter and wider, which fits a more realistic scenario better. For the objects in the sample that required the detection of the [OIII] 4363 A line and [SIII] 6312 A, the distribution abundances as traced directly by oxygen and sulphur appear to be very similar to each other. However, when the restriction for weak temperature-sensitive lines is relaxed, the abundance distribution is wider . In summary, the abundance distributions traced by sulphur can reach reliable abundances up to the solar value at least and provide a more complete picture of the metallicity distribution of HII galaxies., Comment: 11 pages, 13 figures

We give a general proof of the strong consistency of the Maximum Likelihood Estimator for the case of independent non-identically distributed (i.n.i.d) data, assuming that the density functions of the random variables follow a particular set of assumptions. Our proof is based on the works of Wald~\cite{wald1949note}, Goel~\cite{goel1974note}, and Ferguson~\cite{ferguson2017course}. We use this result to prove the strong consistency of a Maximum Likelihood Estimator for Orbit Determination.

Predicting individual mobility patterns is crucial across various applications. While current methods mainly focus on predicting the next location for personalized services like recommendations, they often fall short in supporting broader applications such as traffic management and epidemic control, which require longer period forecasts of human mobility. This study addresses mid-term mobility prediction, aiming to capture daily travel patterns and forecast trajectories for the upcoming day or week. We propose a novel Multi-scale Spatial-Temporal Decoupled Predictor (MSTDP) designed to efficiently extract spatial and temporal information by decoupling daily trajectories into distinct location-duration chains. Our approach employs a hierarchical encoder to model multi-scale temporal patterns, including daily recurrence and weekly periodicity, and utilizes a transformer-based decoder to globally attend to predicted information in the location or duration chain. Additionally, we introduce a spatial heterogeneous graph learner to capture multi-scale spatial relationships, enhancing semantic-rich representations. Extensive experiments, including statistical physics analysis, are conducted on large-scale mobile phone records in five cities (Boston, Los Angeles, SF Bay Area, Shanghai, and Tokyo), to demonstrate MSTDP's advantages. Applied to epidemic modeling in Boston, MSTDP significantly outperforms the best-performing baseline, achieving a remarkable 62.8% reduction in MAE for cumulative new cases.

In this work, we evaluate the performance of SeisSol, a simulator of seismic wave phenomena and earthquake dynamics, on a RISC-V-based system utilizing a vector processing unit. We focus on GEMM libraries and address their limited ability to leverage long vector architectures by developing a batched DGEMM library in plain C. This library achieves speedups ranging from approximately 3.5x to 32.6x compared to the reference implementation. We then integrate the batched approach into the SeisSol application, ensuring portability across different CPU architectures. Lastly, we demonstrate that our implementation is portable to an Intel CPU, resulting in improved execution times in most cases., Comment: Accepted at the First PPAM Workshop on RISC-V (PPAM24)

Incoherent Diffraction Imaging - IDI - is a diffraction-based imaging technique that has been recently proposed to exploit the partial coherence of incoherently scattered light to retrieve structural information from the scattering centers. Similar to the stellar intensity interferometry of Hanbury Brown and Twiss, the signal builds up on the second-order spatial correlations of the emitted light. The complex spatial distribution of the target is thereby encoded in the spatial intensity fluctuations of the scattered light. The first experimental realisations of this imaging technique have been realised using the fluorescence excited by an ultra-short X-ray pulse at Free Electron Laser (FEL) facilities. Here, we propose an alternative set-up based on a table-top Pseudo-Thermal Light Source. This set-up allows us to explore IDI under a wide range of physically relevant conditions as well as to benchmark numerical and analytical models currently used to determine the imaging capabilities of this technique.

The dynamics of cosmic reheating, that is, on how the energy stored in the inflaton is transferred to the standard model (SM) thermal bath, is largely unknown. In this work, we show that the phenomenology of the nonbaryonic dark matter (DM) ultraviolet freeze-in production strongly depends on the dynamics of the cosmic-reheating era. Using a general parametrization for the Hubble expansion rate and SM temperature, we thoroughly investigate DM production during reheating, not only recovering earlier findings that focused on specific cases, but also exploring alternative scenarios. Additionally, we derive a generalized framework for DM production via inflaton decays and identify the viable parameter space, while simultaneously addressing constraints from CMB observations. As illustrative examples, we explore gravitational DM production through scatterings of SM particles or inflatons, deriving well-defined parameter regions for these scenarios., Comment: 21 pages, 6 figures

Context. Recent developments in exoplanetary research highlight the importance of Love numbers in understanding their internal dynamics, formation, migration history and their potential habitability. Love numbers represent crucial parameters that gauge how exoplanets respond to external forces such as tidal interactions and rotational effects. By measuring these responses, we can gain insights into the internal structure, composition, and density distribution of exoplanets. The rate of apsidal precession of a planetary orbit is directly linked to the second-order fluid Love number, thus we can gain valuable insights into the mass distribution of the planet. Aims. In this context, we aim to re-determine the orbital parameters of WASP-43b-in particular, orbital period, eccentricity, and argument of the periastron-and its orbital evolution. We study the outcomes of the tidal interaction with the host star:whether tidal decay and periastron precession are occurring in the system. Method. We observed the system with HARPS, whose data we present for the first time, and we also analyse the newly acquired JWST full-phase light curve. We fit jointly archival and new radial velocity and transit and occultation mid-times, including tidal decay, periastron precession and long-term acceleration in the system. Results. We detected a tidal decay rate of \dotP_a=(-1.99pm0.50) and a periastron precession rate of \dotomega=(0.1851+0.0070-0.0077)=(0.1727+0.0083-0.0089)deg/d=(621.72+29.88-32.04)arcsec/d. This is the first time that both periastron precession and tidal decay are simultaneously detected in an exoplanetary system. The observed tidal interactions can neither be explained by the tidal contribution to apsidal motion of a non-aligned stellar or planetary rotation axis nor by assuming non-synchronous rotation for the planet, and a value for the planetary Love number cannot be derived. [...], Comment: 17 pages, 16 figures, 11 tables

Score-based Generative Models (SGMs) aim to sample from a target distribution by learning score functions using samples perturbed by Gaussian noise. Existing convergence bounds for SGMs in the $\mathcal{W}_2$-distance rely on stringent assumptions about the data distribution. In this work, we present a novel framework for analyzing $\mathcal{W}_2$-convergence in SGMs, significantly relaxing traditional assumptions such as log-concavity and score regularity. Leveraging the regularization properties of the Ornstein-Uhlenbeck (OU) process, we show that weak log-concavity of the data distribution evolves into log-concavity over time. This transition is rigorously quantified through a PDE-based analysis of the Hamilton-Jacobi-Bellman equation governing the log-density of the forward process. Moreover, we establish that the drift of the time-reversed OU process alternates between contractive and non-contractive regimes, reflecting the dynamics of concavity. Our approach circumvents the need for stringent regularity conditions on the score function and its estimators, relying instead on milder, more practical assumptions. We demonstrate the wide applicability of this framework through explicit computations on Gaussian mixture models, illustrating its versatility and potential for broader classes of data distributions.

Filamentary molecular clouds are an essential intermediate stage in the star formation process. To test whether these structures are universal throughout cosmic star formation history, it is crucial to study low-metallicity environments within the Local Group. We present an ALMA analysis of the ALMA archival data at the spatial resolution of $\sim$0.1 pc for 17 massive young stellar objects (YSOs) in the Small Magellanic Cloud (SMC; Z $\sim$0.2 $Z_{\odot}$). This sample represents approximately 30% of the YSOs confirmed by Spitzer spectroscopy. Early ALMA studies of the SMC have shown that the CO emission line traces an H$_2$ number density of $\gtrsim$10$^4$ cm$^{-3}$, an order of magnitude higher than in the typical Galactic environments. Using the CO($J$ = 3-2) data, we investigated the spatial and velocity distribution of molecular clouds. Our analysis shows that about 60% of the clouds have steep radial profiles from the spine of the elongated structures, while the remaining clouds have a smooth distribution and are characterized by lower brightness temperatures. We categorized the former as filaments and the latter as non-filaments. Some of the filamentary clouds are associated with YSOs with outflows and exhibit higher temperatures, likely reflecting their formation conditions, suggesting that these clouds are younger than non-filamentary ones. This indicates that even if filaments form during star formation, their steep structures may become less prominent and transit to a lower-temperature state. Such transitions in structure and temperature have not been reported in metal-rich regions, highlighting a key behavior for characterizing the evolution of the interstellar medium and star formation in low-metallicity environments., Comment: 22 pages, 10 figures, 2tables, Accepted for publication in ApJ

Given a group G and positive integers k,n, we let B_n=B_n(G) denote the set of all elements x in G such that |x^G|\leq n, and we say that G satisfies the (k,n)-covering condition for commutators if there is a subset S in G such that |S|\leq k and all commutators of G are contained in the product SB_n. The importance of groups satisfying this condition was revealed in the recent study of probabilistically nilpotent finite groups of class two. The main result obtained in this paper is the following theorem. Let G be a group satisfying the (k,n)-covering condition for commutators. Then G' contains a characteristic subgroup B such that [G':B] and |B'| are both (k,n)-bounded. This extends several earlier results of similar flavour.

Nonlinear quantum dynamics is often invoked in models trying to bridge the gap between the quantum micro-world and the classical macro-world. Such endeavors, however, encounter challenges at the nexus with relativity. In 1989 Nicolas Gisin proved a powerful no-go theorem, according to which nonlinear quantum dynamics would lead to superluminal signalling, violating Einstein's causality. Here we analyse the theorem from the perspective of recent developments. First, we observe that it harmonises with the no-restriction hypothesis from General Probabilistic Theories. Second, we note that it requires a suitable synchronisation of Alice's and Bob's clocks and actions. Next, we argue that it does not automatically exclude the possibility of global nonlinear quantum dynamics on a tensor product Hilbert space. Consequently, we investigate a class of such dynamics inspired by discrete analogues of nonlinear Schr\"odinger equations. We show that, in general, they exhibit a chaotic character. In this context we inspect whether superluminal signalling can be avoided by relaxing the no-restriction hypothesis. We study three possible communication protocols involving either local measurements or modifications of a local Hamiltonian. We conclude that, in general, in all three cases, two spacelike separated parties can effectuate statistical superluminal information transfer. Nevertheless, we show an example of a nonlocal nonlinear quantum dynamics, which does not allow for it, provided that we relax the no-restriction hypothesis., Comment: 31 pages, 13 figures. Comments are welcome

Enhancing reproducibility and data accessibility is essential to scientific research. However, ensuring data privacy while achieving these goals is challenging, especially in the medical field, where sensitive data are often commonplace. One possible solution is to use synthetic data that mimic real-world datasets. This approach may help to streamline therapy evaluation and enable quicker access to innovative treatments. We propose using a method based on sequential conditional regressions, such as in a fully conditional specification (FCS) approach, along with flexible parametric survival models to accurately replicate covariate patterns and survival times. To make our approach available to a wide audience of users, we have developed user-friendly functions in R and Python to implement it. We also provide an example application to registry data on patients affected by Creutzfeld-Jacob disease. The results show the potentialities of the proposed method in mirroring observed multivariate distributions and survival outcomes., Comment: 18 pages, 3 figures

Scaling by training on large datasets has been shown to enhance the quality and fidelity of image generation and manipulation with diffusion models; however, such large datasets are not always accessible in medical imaging due to cost and privacy issues, which contradicts one of the main applications of such models to produce synthetic samples where real data is scarce. Also, finetuning on pre-trained general models has been a challenge due to the distribution shift between the medical domain and the pre-trained models. Here, we propose Latent Drift (LD) for diffusion models that can be adopted for any fine-tuning method to mitigate the issues faced by the distribution shift or employed in inference time as a condition. Latent Drifting enables diffusion models to be conditioned for medical images fitted for the complex task of counterfactual image generation, which is crucial to investigate how parameters such as gender, age, and adding or removing diseases in a patient would alter the medical images. We evaluate our method on three public longitudinal benchmark datasets of brain MRI and chest X-rays for counterfactual image generation. Our results demonstrate significant performance gains in various scenarios when combined with different fine-tuning schemes. The source code of this work will be publicly released upon its acceptance.