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

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

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

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

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

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

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

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

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

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

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

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

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

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

The KM3NeT Collaboration has tackled a common challenge faced by the astroparticle physics community, namely adapting the experiment-specific simulation software to work with the CORSIKA air shower simulation output. The proposed solution is an extension of the open-source code gSeaGen, allowing for the transport of muons generated by CORSIKA to a detector of any size at an arbitrary depth. The gSeaGen code was not only extended in terms of functionalities but also underwent a thorough redesign of the muon propagation routine, resulting in a more accurate and efficient simulation. This paper presents the capabilities of the new gSeaGen code as well as prospects for further developments., Comment: 27 pages, 13 figures

Electrochemical biosensors ("E-AB" or "E-DNA" type sensors) that utilize square-wave voltammetry originated in academic labs with a few standard experimental configurations for the electrochemical cell and data analysis. We report here on adaptations of these approaches that are friendly to novice scientists such as those in undergraduate laboratories. These approaches utilize commercially available components, low volumes, work over extended periods and enable facile analysis using a custom excel sheet.

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

Historical ciphered manuscripts are documents that were typically used in sensitive communications within military and diplomatic contexts or among members of secret societies. These secret messages were concealed by inventing a method of writing employing symbols from diverse sources such as digits, alchemy signs and Latin or Greek characters. When studying a new, unseen cipher, the automatic search and grouping of ciphers with a similar alphabet can aid the scholar in its transcription and cryptanalysis because it indicates a probability that the underlying cipher is similar. In this study, we address this need by proposing the CSI metric, a novel way of comparing pairs of ciphered documents. We assess their effectiveness in an unsupervised clustering scenario utilising visual features, including SIFT, pre-trained learnt embeddings, and OCR descriptors., Comment: Acccepted at ECCV24 Workshop AI4DH

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

Understanding the complex ionization structure and chemical composition of \hii\ regions poses a significant challenge in astrophysics. The abundance discrepancy problem, characterized by inconsistencies between abundances derived from recombination lines (RLs) and collisionally excited lines (CELs), has long been a puzzle in the field. In this theoretical study, we present novel photoionization models that incorporate temperature, density, and chemical inhomogeneities within a single cloud to comprehensively address this discrepancy. By accounting for the intricate interplay between ionization, excitation, and chemistry, our models successfully reproduce both observed RLs and CELs with with an average difference between our models and the observations of 25% -- within uncertainties inherent in Galactic archival long-slit and new SDSS-V Local Volume Mapper observations. Through comparisons between generic inhomogeneous model predictions and observations, demonstrating the ability of our theoretical framework to analyze the abundance discrepancy problem within \hii\ regions. Our results highlight the importance of incorporating spatially resolved temperature, density, and chemical structures when interpreting the physical processes governing emission line spectra in these astrophysical environments.

Chlorine (Cl) is a chemical element of the group of the halogens and is between the 17th and the 20th most abundant elements in the Solar System. It is thought to be produced from the capture of a proton or neutron by specific alpha-element isotopes during both hydrostatic and explosive oxygen burning, though some contribution may come from Type Ia supernovae. Cl lines are quite rare in stellar spectra, so most of the information available about its abundance comes from analyzing the emission lines of ionized nebulae, especially the collisionally excited lines of Cl2+ ([Cl III] {\lambda}{\lambda}5518,5538). Our goal is to accurately determine the Cl abundance in H II regions, and gather more information about its nucleosynthetic origin. For this work we used a sample of observations that encompasses the deepest spectra of H II regions available in the literature, from both the Milky Way and other galaxies in the local Universe, covering a range of oxygen (O) abundances, 12+log(O/H), from 7.18 to 8.70. As a first step, we determine the most representative electron temperature of the zone of the nebulae where the Cl2+ ion lies. To this aim we used a grid of photoionization models and diagnostics valid for other ions, as that parameter cannot be determined directly through [Cl III] lines. We then computed the total Cl abundance using different sets of ionization correction factors to account for the contribution from unseen ionization stages., Comment: Proceedings of the XVI Scientific Meeting of the Spanish Astronomical Society

We study the asymptotic behaviour of stationary densities of one-dimensional random diffeomorphisms, at the boundaries of their support, which correspond to deterministic fixed points of extremal diffeomorphisms. In particular, we show how this stationary density at a boundary depends on the underlying noise distribution, as well as the linearisation of the extremal diffeomorphism at the boundary point (in case the corresponding fixed point is hyperbolic), or the leading nonlinear term of the extremal diffeomorphism (in case the corresponding fixed point is not hyperbolic).

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy ($<$3 MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV $^{208}$Tl decay $\gamma$ rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of $^{208}$Tl in the fiberglass composing these struts, $(11.7 \pm 0.2 ~\text{(stat)} \pm 2.8~\text{(syst)})~\text{Bq/kg}$. Cosmogenically-produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4., Comment: 19 pages, 15 figures total including the supplementary material section, 1 table. CC BY license

Developing industry-wide standards and making sure producers of mission-critical systems comply with them is crucial to foster consumer acceptance. Producers of such systems can rely on assurance cases to demonstrate to regulatory authorities how they have complied with such standards to help prevent system failure, which could result in fatalities and environmental damage. In this paper, we introduce SmartGSN, an innovative online tool that relies on Large Language Models to (semi-)automate the management of assurance cases complying with GSN -a very popular notation to graphically represent assurance cases. The evaluation of SmartGSN demonstrates its strong capability to detect assurance case patterns within the assurance cases manually created for five systems spanning several application domains. SmartGSN is accessible online at [https://smartgsn.vercel.app], and a demonstration video can be viewed at [https://youtu.be/qLrTHf-SZbM].

We investigate the different transport mechanisms that can occur in atomically precise advanced-manufacturing (APAM) pn junction devices at cryogenic and room temperatures. We first elucidate the potential cause of the anomalous behaviors observed in the forward-bias response of these devices in recent cryogenic temperature measurements, which deviates from the theoretical response of a silicon Esaki diode. Specifically, the suppression of the tunneling current at low bias and the appearance of regular diode current at lower biases than theoretically expected for silicon. We find that the latter can be attributed to modifications in the electronic band structure within the $\delta$-layer regions, leading to band-gap narrowing induced by the high density of dopants. We also find that a combination of two sets of band-to-band tunneling (BTBT) parameters can qualitatively approximate the shape of the tunneling current at low bias. This can arise from band quantization and realignment due to the strong potential confinement in APAM-doped layers. Finally, we extend our analyses to room temperature operation, and we predict that trap-assisted tunneling (TAT) may become significant, leading to a complex superposition of BTBT and TAT transport mechanisms in the electrical measurements.

The physics of recombination lines (RLs) in the HeI singlet system is expected to be relatively simple, supported by accurate atomic models. We examine the intensities of HeI singlets $\lambda \lambda$3614, 3965, 5016, 6678, 7281 and the triplet HeI $\lambda$5876 in various types of ionized nebulae and compare them with theoretical predictions to test the validity of the ``Case B'' recombination scenario and the assumption of thermal homogeneity. Our analysis includes 85 spectra from Galactic and extragalactic HII regions, 90 from star-forming galaxies, and 218 planetary nebulae, all compiled by the DEep Spectra of Ionized REgions Database Extended (DESIRED-E) project. By evaluating the ratios HeI $\lambda$7281/$\lambda$6678 and HeI $\lambda$7281/$\lambda$5876, we determine $T_e$(HeI) and compare it with direct measurements of $T_e$([OIII] $\lambda$4363/$\lambda$5007). We find that $T_e$(HeI) is systematically lower than $T_e$([OIII]) across most objects and nebula types. Additionally, we identify a correlation between the abundance discrepancy factor (ADF(O$^{2+}$)) and the difference $T_e$([OIII]) - $T_e$(HeI) for planetary nebulae. We explore two potential explanations: photon loss from $n^1P \rightarrow 1^1S$ transitions and temperature inhomogeneities. Deviations from ``Case B'' may indicate photon absorption by HI rather than HeI and/or generalized ionizing photon escape, highlighting the need for detailed consideration of radiative transfer effects. If temperature inhomogeneities are widespread, identifying a common physical phenomenon affecting all ionized nebulae is crucial. Our results suggest that both scenarios can contribute to the observed discrepancies., Comment: Submitted to the AAS, comments and feedback from the community are welcome

This paper presents a model for a vehicle routing problem in which customer demands are stochastic and vehicles are divided into compartments. The problem is motivated by the needs of certain agricultural cooperatives that produce various types of livestock food. The vehicles and their compartments have different capacities, and each compartment can only contain one type of feed. Additionally, certain farms can only be accessed by specific vehicles, and there may be urgency constraints. To solve the problem, a two-step heuristic algorithm is proposed. First, a constructive heuristic is applied, followed by an improvement phase based on iterated tabu search. The designed algorithm is tested on several instances, including an analysis of real-world datasets where the results are compared with those provided by the model. Furthermore, multiple benchmark instances are created for this problem and an extensive simulation study is conducted. Results are presented for different model parameters, and it is shown that, despite the problems' complexity, the algorithm performs efficiently. Finally, the proposed heuristic is compared to existing solution algorithms for similar problems using benchmark instances from the literature, achieving competitive results., Comment: 25 pages, 8 figures

Classifying ionised nebulae in nearby galaxies is crucial to studying stellar feedback mechanisms and understanding the physical conditions of the interstellar medium. This classification task is generally performed by comparing observed line ratios with photoionisation simulations of different types of nebulae (HII regions, planetary nebulae, and supernova remnants). However, due to simplifying assumptions, such simulations are generally unable to fully reproduce the line ratios in observed nebulae. This discrepancy limits the performance of the classical machine-learning approach, where a model is trained on the simulated data and then used to classify real nebulae. In this study, we use a domain-adversarial neural network (DANN) to bridge the gap between photoionisation models (source domain) and observed ionised nebulae from the PHANGS-MUSE survey (target domain). The DANN is an example of a domain-adaptation algorithm, whose goal is to maximise the performance of a model trained on labelled data in the source domain on an unlabelled target domain by extracting domain-invariant features. Our results indicate a significant improvement in classification performance in the target domain when employing the DANN framework compared to a classical neural network (NN) classifier. Additionally, we investigate the impact of adding noise to the source dataset, finding that noise injection acts as a form of regularisation, further enhancing the performances of both the NN and DANN models on the observational data. The combined use of domain adaptation and noise injection improves the classification accuracy in the target domain by 24%. This study highlights the potential of domain adaptation methods in tackling the domain-shift challenge when using theoretical models to train machine-learning pipelines in astronomy., Comment: submitted for publication, comments welcome

Inspired by the discovery of a variety of correlated insulators in the moir\'e universe, controlled by interactions projected to a set of isolated bands with a narrow bandwidth, we examine here a partial sum-rule associated with the inverse frequency-weighted optical conductivity restricted to low-energies. Unlike standard sum-rules that extend out to $infinite$ frequencies, which include contributions from $all$ inter-band transitions, we focus here on transitions associated $only$ with the $projected$ degrees of freedom. We analyze the partial sum-rule in a non-perturbative but "solvable" limit for a variety of correlation-induced insulators. This includes (i) magic-angle twisted bilayer graphene at integer-filling with projected Coulomb interactions, starting from the chiral flat-band limit and including realistic perturbations, (ii) fractional fillings of Chern-bands which support generalized Laughlin-like states, starting from a Landau-level and including a periodic potential and magnetic-field, respectively, drawing connections to twisted MoTe$_2$, and (iii) integer filling in toy-models of non-topological flat-bands with a tunable quantum geometry in the presence of repulsive interactions. The partial sum-rule in all of these examples is implicitly constrained by the form of the band quantum geometry via the low-lying excitation spectrum, but is not related to it explicitly. For interacting Slater-determinant insulators, the partial sum-rule is related to a new quantity -- "many-body projected quantum geometry" -- obtained from the interaction-renormalized electronic bands. We also point out an intriguing connection between the partial sum-rule and the quantum Fisher information associated with the projected many-body position operator., Comment: Main text: 14 pages, 5 figures, Supplementary information: 5 pages

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

The decomposition of high-density surface electromyography (HD-sEMG) signals into motor unit discharge patterns has become a powerful tool for investigating the neural control of movement, providing insights into motor neuron recruitment and discharge behavior. However, current algorithms, while very effective under certain conditions, face significant challenges in complex scenarios, as their accuracy and motor unit yield are highly dependent on anatomical differences among individuals. This can limit the number of decomposed motor units, particularly in challenging conditions. To address this issue, we recently introduced Swarm-Contrastive Decomposition (SCD), which dynamically adjusts the separation function based on the distribution of the data and prevents convergence to the same source. Initially applied to intramuscular EMG signals, SCD is here adapted for HD-sEMG signals. We demonstrated its ability to address key challenges faced by existing methods, particularly in identifying low-amplitude motor unit action potentials and effectively handling complex decomposition scenarios, like high-interference signals. We extensively validated SCD using simulated and experimental HD-sEMG recordings and compared it with current state-of-the-art decomposition methods under varying conditions, including different excitation levels, noise intensities, force profiles, sexes, and muscle groups. The proposed method consistently outperformed existing techniques in both the quantity of decoded motor units and the precision of their firing time identification. For instance, under certain experimental conditions, SCD detected more than three times as many motor units compared to previous methods, while also significantly improving accuracy. These advancements represent a major step forward in non-invasive EMG technology for studying motor unit activity in complex scenarios.

This paper reports on a novel method for LiDAR odometry estimation, which completely parameterizes the system with dual quaternions. To accomplish this, the features derived from the point cloud, including edges, surfaces, and Stable Triangle Descriptor (STD), along with the optimization problem, are expressed in the dual quaternion set. This approach enables the direct combination of translation and orientation errors via dual quaternion operations, greatly enhancing pose estimation, as demonstrated in comparative experiments against other state-of-the-art methods. Our approach reduced drift error compared to other LiDAR-only-odometry methods, especially in scenarios with sharp curves and aggressive movements with large angular displacement. DualQuat-LOAM is benchmarked against several public datasets. In the KITTI dataset it has a translation and rotation error of 0.79% and 0.0039{\deg}/m, with an average run time of 53 ms.

Flatback airfoils, characterized by a blunt trailing edge, are used at the root of large wind turbine blades. A low-drag pocket has recently been identified in the flow past these airfoils at high angles of attack, potentially offering opportunities for enhanced energy extraction. This study uses three-dimensional Detached Eddy Simulations (DES) combined with statistical and data-driven modal analysis techniques to explore the aerodynamics and coherent structures of a flatback airfoil in these conditions. Two angles of attack - one inside $\left(12^{\circ}\right)$ and one outside $\left(0^{\circ}\right)$ of the low-drag pocket - are examined more thoroughly. The spanwise correlation length of secondary instability is analyzed in terms of autocorrelation of the $\Gamma_{1}$ vortex identification criterion, while coherent structures were extracted via the multiscale Proper Orthogonal Decomposition (mPOD). The results show increased base pressure, BL thickness, vortex formation length, and more organized wake structures inside the low-drag regime. While the primary instability (B\'enard-von K\'arm\'an vortex street) dominates in both cases, the secondary instability is distinguishable only for the $12^{\circ}$ case and is identified as a Mode S$^{\prime}$ instability., Comment: 27 pages, 25 figures, submitted to Physical Review Fluids

Sloshing of cryogenic liquid propellants can significantly impact a spacecraft's mission safety and performance by unpredictably altering the center of mass and producing large pressure fluctuations due to the increased heat and mass transfer within the tanks. This study, conducted as part of the NT-SPARGE (Non-isoThermal Sloshing PARabolic FliGht Experiment) project, provides a detailed experimental investigation of the thermodynamic evolution of a partially filled upright cylindrical tank undergoing non-isothermal sloshing in microgravity. Sloshing was induced by a step reduction in gravity during the 83rd European Space Agency (ESA) parabolic flight, resulting in a chaotic reorientation of the free surface under inertia-dominated conditions. To investigate the impact of heat and mass transfer on the sloshing dynamics, two identical test cells operating with a representative fluid, HFE-7000, in single-species were considered simultaneously. One cell was maintained in isothermal conditions, while the other started with initially thermally stratified conditions. Flow visualization, pressure, and temperature measurements were acquired for both cells. The results highlight the impact of thermal mixing on liquid dynamics coupled with the significant pressure and temperature fluctuations produced by the destratification. The comprehensive experimental data gathered provide a unique opportunity to validate numerical simulations and simplified models for non-isothermal sloshing in microgravity, thus contributing to improved cryogenic fluid management technologies.

In this article, we present results of our recent work of epitaxially-grown aluminum (epi-Al) on antimonide heterostructures, where the epi-Al thin film is grown at either room temperature or below zero $^o$C. A sharp superconducting transition at $T \sim 1.3$ K is observed in these epi-Al films, and the critical magnetic field follows the BCS (Bardeen-Cooper-Schrieffer) model. We further show that supercurrent states are achieved in Josephson junctions fabricated in the epi-Al/antimonide heterostructures with mobility $\mu \sim 1.0 \times 10^6$ cm$^2$/Vs, making these heterostructures a promising platform for the exploration of Josephson junction effects for quantum microelectronics applications, and the realization of robust topological superconducting states that potentially allow the realization of intrinsically fault-tolerant qubits and quantum gates.

This paper explores a unique cave art found in southern Puerto Rico that depicts a comet over a tomb. Through interdisciplinary methods, including art interpretation, historical documentation, and demographic analysis, this study uncovered the artist's identity, the societal context of the period, and the potential motivations behind the creation of this art. The investigation revealed a connection to the passage of Halley's Comet in 1910 and the widespread panic it induced., Comment: 7 pages, 6 figures. Submitted to the Journal of Astronomical History and Heritage

The structure and chemistry of the dusty interstellar medium (ISM) are shaped by complex processes that depend on the local radiation field, gas composition, and dust grain properties. Of particular importance are Polycyclic Aromatic Hydrocarbons (PAHs), which emit strong vibrational bands in the mid-infrared, and play a key role in the ISM energy balance. We recently identified global correlations between PAH band and optical line ratios across three nearby galaxies, suggesting a connection between PAH heating and gas ionization throughout the ISM. In this work, we perform a census of the PAH heating -- gas ionization connection using $\sim$700,000 independent pixels that probe scales of 40--150 pc in nineteen nearby star-forming galaxies from the PHANGS survey. We find a universal relation between $\log$PAH(11.3 \mic/7.7 \mic) and $\log$([SII]/H$\alpha$) with a slope of $\sim$0.2 and a scatter of $\sim$0.025 dex. The only exception is a group of anomalous pixels that show unusually high (11.3 \mic/7.7 \mic) PAH ratios in regions with old stellar populations and high starlight-to-dust emission ratios. Their mid-infrared spectra resemble those of elliptical galaxies. AGN hosts show modestly steeper slopes, with a $\sim$10\% increase in PAH(11.3 \mic/7.7 \mic) in the diffuse gas on kpc scales. This universal relation implies an emerging simplicity in the complex ISM, with a sequence that is driven by a single varying property: the spectral shape of the interstellar radiation field. This suggests that other properties, such as gas-phase abundances, gas ionization parameter, and grain charge distribution, are relatively uniform in all but specific cases., Comment: resubmitted to ApJ after addressing referee report; Figure 12 summarizes the results

Neutrinos described as an open quantum system may interact with the environment which introduces stochastic perturbations to their quantum phase. This mechanism leads to a loss of coherence along the propagation of the neutrino $-$ a phenomenon commonly referred to as decoherence $-$ and ultimately, to a modification of the oscillation probabilities. Fluctuations in space-time, as envisaged by various theories of quantum gravity, are a potential candidate for a decoherence-inducing environment. Consequently, the search for decoherence provides a rare opportunity to investigate quantum gravitational effects which are usually beyond the reach of current experiments. In this work, quantum decoherence effects are searched for in neutrino data collected by the KM3NeT/ORCA detector from January 2020 to November 2021. The analysis focuses on atmospheric neutrinos within the energy range of a few GeV to $100\,\mathrm{GeV}$. Adopting the open quantum system framework, decoherence is described in a phenomenological manner with the strength of the effect given by the parameters $\Gamma_{21}$ and $\Gamma_{31}$. Following previous studies, a dependence of the type $\Gamma_{ij} \propto (E/E_0)^n$ on the neutrino energy is assumed and the cases $n = -2,-1$ are explored. No significant deviation with respect to the standard oscillation hypothesis is observed. Therefore, $90\,\%$ CL upper limits are estimated as $\Gamma_{21} < 4.6\cdot 10^{-21}\,$GeV and $\Gamma_{31} < 8.4\cdot 10^{-21}\,$GeV for $n = -2$, and $\Gamma_{21} < 1.9\cdot 10^{-22}\,$GeV and $\Gamma_{31} < 2.7\cdot 10^{-22}\,$GeV for $n = -1$, respectively., Comment: 17 pages, 5 figures

In the pursuit of alternative and less invasive medical treatments, magnetic nanoparticles (NPs) have gained significant relevance. Iron carbides NPs stand out for their higher saturation magnetizations compared to iron oxides, while maintaining a suitable biocompatibility. In this work, high control is achieved over the composition and morphology of Fe3C/C encapsulated core/shell nanoparticles through fine-tuning of the sol-gel synthesis parameters. Specifically, the impact of decreasing each surfactant concentration added, nt, the same both for oleylamine (ON) and oleic acid (OA), has been explored. A minimum value for such parameter denoted by nt,min. was required to produce pure Fe3C@C NP-composites. For nt < 4 mmol, some minor {\alpha}-Fe impurities arise, and the effective carburization becomes unstable due to insufficient carbon. The magnetic properties of the materials prepared were optimized by reducing the excess carbon from surfactants, resulting in saturation magnetization values of 86 emu/g. (for pure Fe3C at nt = 5 mmol) and 102 emu/g (for Fe3C and <2 % w.t. of {\alpha}-Fe impurity at nt = 4 mmol). In view of this, several cytotoxicity studies for different Fe3C@C samples were conducted, exhibiting excellent biocompatibility in cell-based assays, which could lead to potential application at the forefront of biomedical fields.

Deep learning developments have improved medical imaging diagnoses dramatically, increasing accuracy in several domains. Nonetheless, obstacles continue to exist because of the requirement for huge datasets and legal limitations on data exchange. A solution is provided by Federated Learning (FL), which permits decentralized model training while maintaining data privacy. However, FL models are susceptible to data corruption, which may result in performance degradation. Using pre-trained models, this research suggests a strong FL framework to improve kidney stone diagnosis. Two different kidney stone datasets, each with six different categories of images, are used in our experimental setting. Our method involves two stages: Learning Parameter Optimization (LPO) and Federated Robustness Validation (FRV). We achieved a peak accuracy of 84.1% with seven epochs and 10 rounds during LPO stage, and 77.2% during FRV stage, showing enhanced diagnostic accuracy and robustness against image corruption. This highlights the potential of merging pre-trained models with FL to address privacy and performance concerns in medical diagnostics, and guarantees improved patient care and enhanced trust in FL-based medical systems.

Accurate depth estimation in endoscopy is vital for successfully implementing computer vision pipelines for various medical procedures and CAD tools. In this paper, we present the EndoDepth benchmark, an evaluation framework designed to assess the robustness of monocular depth prediction models in endoscopic scenarios. Unlike traditional datasets, the EndoDepth benchmark incorporates common challenges encountered during endoscopic procedures. We present an evaluation approach that is consistent and specifically designed to evaluate the robustness performance of the model in endoscopic scenarios. Among these is a novel composite metric called the mean Depth Estimation Robustness Score (mDERS), which offers an in-depth evaluation of a model's accuracy against errors brought on by endoscopic image corruptions. Moreover, we present SCARED-C, a new dataset designed specifically to assess endoscopy robustness. Through extensive experimentation, we evaluate state-of-the-art depth prediction architectures on the EndoDepth benchmark, revealing their strengths and weaknesses in handling endoscopic challenging imaging artifacts. Our results demonstrate the importance of specialized techniques for accurate depth estimation in endoscopy and provide valuable insights for future research directions.

We present a chemical analysis of selected HII regions from the PHANGS-MUSE nebular catalogue. Our intent is to empirically re-calibrate strong-line diagnostics of gas-phase metallicity, applicable across a wide range of metallicities within nearby star-forming galaxies. To ensure reliable measurements of auroral line fluxes, we carried out a new spectral fitting procedure whereby only restricted wavelength regions around the emission lines of interest are taken into account: this assures a better fit for the stellar continuum. No prior cuts to nebulae luminosity were applied to limit biases in auroral line detections. Ionic abundances of O+, O++, N+, S+, and S++ were estimated by applying the direct method. We integrated the selected PHANGS-MUSE sample with other existing auroral line catalogues, appropriately re-analysed to obtain a homogeneous dataset. This was used to derive strong-line diagnostic calibrations that span from 12+log(O/H) = 7.5 to 8.8. We investigate their dependence on the ionisation parameter and conclude that it is likely the primary cause of the significant scatter observed in these diagnostics. We apply our newly calibrated strong-line diagnostics to the total sample of HII regions from the PHANGS-MUSE nebular catalogue, and we exploit these indirect metallicity estimates to study the radial metallicity gradient within each of the 19 galaxies of the sample. We compare our results with the literature and find good agreement, validating our procedure and findings. With this paper, we release the full catalogue of auroral and nebular line fluxes for the selected HII regions from the PHANGS-MUSE nebular catalogue. This is the first catalogue of direct chemical abundance measurements carried out with PHANGS-MUSE data., Comment: 20 pages, 14 figures, 6 tables; accepted for publication in Astronomy & Astrophysics

Josephson junction field-effect transistors (JJFETs) have recently re-emerged as promising candidates for superconducting computing. For JJFETs to perform Boolean logic operations, the so-called gain factor $\alpha_{R}$ must be larger than 1. In a conventional JJFET made with a classical channel material, due to a gradual dependence of superconducting critical current on the gate bias, $\alpha_{R}$ is much smaller than 1. In this Letter, we propose a new device structure of quantum enhanced JJFETs in a zero-energy-gap InAs/GaSb heterostructure. We demonstrate that, due to an excitonic insulator quantum phase transition in this zero-gap heterostructure, the superconducting critical current displays a sharp transition as a function of gate bias, and the deduced gain factor $\alpha_{R}$ ~ 0.06 is more than 50 times that (~ 0.001) reported in a classical JJFET. Further optimization may allow achieving a gain factor larger than 1 for logic applications.

This paper analyses the set of scientific publications in open access, other than journals (monographs, conferences proceedings, teaching materials and grey literature), published by Spanish public universities, studying their volume, documentary typology, level of description and open access policies with the aim of measuring their degree of incorporation and compliance with the principles of Open Science. An exhaustive review of the disposed material in open access by these publishers has been carried out, which has allowed to make a diagnosis of their level of open access publishing. Grey literature is the most common documentary type followed by the monograph, in the open publication of these publishers that does not reach even 5% of the average editorial production. The results allow us to conclude that the academic publishing, and more specifically the academic books in open access, still has a very reduced presence within the editorial production of these institutions., Comment: 10 pages, in Spanish language, 3 figures, 4 tables

Motivated by the wide presence of multilayer networks in both natural and human-made systems, within a random matrix theory (RMT) approach, in this study we compute eigenfunction and spectral properties of multilayer directed random networks (MDRNs) in two setups composed by $M$ layers of size $N$: A line and a complete graph (node-aligned multiplex network). First, we numerically demonstrate that the normalized localization length $\beta$ of the eigenfunctions of MDRNs follows a simple scaling law given by $\beta=x^*/(1+x^*)$, with $x^*\propto (b_{\rm eff}^2/L)^\delta$, $\delta\sim 1$ and $b_{\rm eff}$ being the effective bandwidth of the adjacency matrix of the network of size $L=M\times N$. Here, $b_{\rm eff}$ incorporates both intra- and inter-layer edges. Then, we show that other eigenfunction and spectral RMT measures (the inverse participation ratio of eigenfunctions, the ratio between nearest- and next-to-nearest-neighbor eigenvalue distances, and the ratio between consecutive singular-value spacings) of MDRNs also scale with $x^*$., Comment: 11 pages, 8 figures. arXiv admin note: substantial text overlap with arXiv:2406.15426, arXiv:1611.06695

With the rapid growth of the Natural Language Processing (NLP) field, a vast variety of Large Language Models (LLMs) continue to emerge for diverse NLP tasks. As an increasing number of papers are presented, researchers and developers face the challenge of information overload. Thus, it is particularly important to develop a system that can automatically extract and organise key information about LLMs from academic papers (\textbf{LLM model card}). This work is to develop such a pioneer system by using Named Entity Recognition (\textbf{NER}) and Relation Extraction (\textbf{RE}) methods that automatically extract key information about large language models from the papers, helping researchers to efficiently access information about LLMs. These features include model \textit{licence}, model \textit{name}, and model \textit{application}. With these features, we can form a model card for each paper. \textbf{Data-contribution} wise, 106 academic papers were processed by defining three dictionaries - LLMs name, licence, and application. 11,051 sentences were extracted through dictionary lookup, and the dataset was constructed through manual review of the final selection of 129 sentences that have a link between the name and the licence, and 106 sentences that have a link between the model name and the application. Data and code in \textsc{LLM-Card} is openly hosted at \url{https://github.com/shengwei-tian/dependency-parser-visualization}, Comment: ongoing work, 16 pages

We have generated an updated version of the $p\Omega$ potential for low-energy interactions based on an effective field theory approach at leading order. This potential, together with other potentials based either on different parametrizations or lattice QCD calculations, have been used to solve the Schr\"odinger equation numerically, obtaining the scattering wave functions for different values of the relative momentum. Using these wave functions, we have computed the $p \Omega$ femtoscopic correlation functions, comparing the results with those published by the ALICE collaboration., Comment: 1+4 pages, 4 figures. Contribution to the proceedings of the 10th International Conference on Quarks and Nuclear Physics (QNP2024)

Objective: To propose a mathematical model for applying Ionization Detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP). Approach: Our model provides for selection of preferred ID parameters (I_p) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopic I_p and macroscopic RTP. Selection of I_p is demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen Ip: N_k; k = 2,3,...,10, the number of ionizations in clusters of k or more per particle, and F_k; k = 1,2,...,10, the number of clusters of k or more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation. Main results: The preferred I_p were N_4 and F_5 for aerobic cells, N_5 and F_7 for hypoxic cells. Signifcant differences were found in cell survival for beams having the same LET or the preferred N_k. Conversely, there was no signi?cant difference for F_5 for aerobic cells and F_7 for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for these I_p had the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert that I_p exist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation. Signifcance: Our model provides a practical means to select preferred I_p from radiobiological data, and to convert I_p to the macroscopic cluster dose for particle RTP., Comment: 31 pages, 12 figures

Cross-View Geo-Localisation within urban regions is challenging in part due to the lack of geo-spatial structuring within current datasets and techniques. We propose utilising graph representations to model sequences of local observations and the connectivity of the target location. Modelling as a graph enables generating previously unseen sequences by sampling with new parameter configurations. To leverage this newly available information, we propose a GNN-based architecture, producing spatially strong embeddings and improving discriminability over isolated image embeddings. We outline SpaGBOL, introducing three novel contributions. 1) The first graph-structured dataset for Cross-View Geo-Localisation, containing multiple streetview images per node to improve generalisation. 2) Introducing GNNs to the problem, we develop the first system that exploits the correlation between node proximity and feature similarity. 3) Leveraging the unique properties of the graph representation - we demonstrate a novel retrieval filtering approach based on neighbourhood bearings. SpaGBOL achieves state-of-the-art accuracies on the unseen test graph - with relative Top-1 retrieval improvements on previous techniques of 11%, and 50% when filtering with Bearing Vector Matching on the SpaGBOL dataset.

Motivated by the study of the electrodynamics of particles, we propose in this work an arbitrary-order discrete de Rham scheme for the treatment of elliptic problems with potential and flux jumps across a fixed interface. The scheme seamlessly supports general elements resulting from the cutting of a background mesh along the interface. Interface conditions are enforced weakly \`a la Nitsche. We provide a rigorous convergence of analysis of the scheme for a steady model problem and showcase an application to a physical problem inspired by the Leaky Dielectric Model.