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Proximity-based cities have attracted much attention in recent years. The 15-minute city, in particular, heralded a new vision for cities where essential services must be easily accessible. Despite its undoubted merit in stimulating discussion on new organisations of cities, the 15-minute city cannot be applicable everywhere, and its very definition raises a few concerns. Here, we tackle the feasibility and practicability of the '15-minute city' model in many cities worldwide. We provide a worldwide quantification of how close cities are to the ideal of the 15-minute city. To this end, we measure the accessibility times to resources and services, and we reveal strong heterogeneity of accessibility within and across cities, with a significant role played by local population densities. We provide an online platform (\href{whatif.sonycsl.it/15mincity}{whatif.sonycsl.it/15mincity}) to access and visualise accessibility scores for virtually all cities worldwide. The heterogeneity of accessibility within cities is one of the sources of inequality. We thus simulate how much a better redistribution of resources and services could heal inequity by keeping the same resources and services or by allowing for virtually infinite resources. We highlight pronounced discrepancies among cities in the minimum number of additional services needed to comply with the 15-minute city concept. We conclude that the proximity-based paradigm must be generalised to work on a wide range of local population densities. Finally, socio-economic and cultural factors should be included to shift from time-based to value-based cities.

This paper addresses the channel estimation problem for beyond diagonal reconfigurable intelligent surface (BD-RIS) from a tensor decomposition perspective. We first show that the received pilot signals can be arranged as a three-way tensor, allowing us to recast the cascaded channel estimation problem as a block Tucker decomposition problem that yields decoupled estimates for the involved channel matrices while offering a substantial performance gain over the conventional (matrix-based) least squares (LS) estimation method. More specifically, we develop two solutions to solve the problem. The first one is a closed-form solution that extracts the channel estimates via a block Tucker Kronecker factorization (BTKF), which boils down to solving a set of parallel rank-one matrix approximation problems. Exploiting such a low-rank property yields a noise rejection gain compared to the standard LS estimation scheme while allowing the two involved channels to be estimated separately. The second solution is based on a block Tucker alternating least squares (BTALS) algorithm that directly estimates the involved channel matrices using an iterative estimation procedure. We discuss the uniqueness and identifiability issues and their implications for training design. We also propose a tensor-based design of the BD-RIS training tensor for each algorithm that ensures unique decoupled channel estimates under trivial scaling ambiguities. Our numerical results shed light on the tradeoffs offered by BTKF and BTALS methods. Specifically, while the first enjoys fast and parallel extraction of the channel estimates in closed form, the second has a more flexible training design, allowing for a significantly reduced training overhead compared to the state-of-the-art LS method.

The IEA's International Civic and Citizenship Education Study (ICCS) investigates the ways in which young people around the world are prepared to undertake their roles as citizens. This report presents the European results from the third cycle of the study (ICCS 2022). Eighteen countries and two benchmarking participants (the German states of North Rhine-Westphalia and Schleswig-Holstein) administered the European student questionnaire to target grade students in this study cycle. ICCS 2022 studied contexts for and learning outcomes of civic and citizenship education in a wide range of national contexts at the beginning of the third decade of the 21st Century. The general purpose of the European student questionnaire is to explore specific European-related civic and citizenship issues derived from the overarching ICCS 2022 assessment framework, supplementing the data obtained from the international survey with a specific European perspective. The ICCS 2022 European student questionnaire included 12 questions aimed at examining students' interest and their opinions regarding European-related civic and citizenship issues such as students' sense of European identity; students' opportunities for learning about Europe provided by schools; and students' attitudes toward free movement of European citizens within Europe, toward the European Union, and toward cooperation among European countries. It also encompasses questions on students' perceptions of discrimination in their country, of the future of Europe, and of their life in the future, as well as on students' sustainable behaviors and those related to political and ethical consumerism. Over the past 50 years, the IEA has conducted comparative research studies in a range of domains focusing on educational policies, practices, and outcomes in many countries around the world. Prior to ICCS 2022, the IEA had conducted four international comparative studies of civic and citizenship education, with a first survey implemented in 1971, a second in 1999, a third in 2009 and a fourth in 2016. ICCS 2022 data will allow education systems to evaluate the strengths of educational policies, both internationally and in the European regional context, and to measure progress in achieving critical social objectives of their educational policy. [This report was jointly prepared by Libera Università Maria Santissima Assunta (LUMSA Università -- Rome, Italy).]

Orbiting space objects have become in the last decade a major nuisance impacting ground astronomy and orbiting space assets, from observatories to satellites and space stations. In particular with the rise of the satellite population in Low Earth Orbits (LEOs), space objects are becoming an even bigger threat and a strong problem to astronomical observations. To tackle these threats several coordinated surveillance networks composed of dedicated sensors (telescopes, radars and laser ranging facilities) track and survey space objects, from debris to active satellites. As part of the European Space Surveillance \& Tracking (EU-SST) network, Portugal is developing the PAmpilhosa da Serra Space Observatory (PASO), with both radio and optical telescopes dedicated to the Space Situational Awareness (SSA) domain, deployed at a Dark Sky destination. To optimize telescope survey time, we developed {\tt{CLOWN}} (CLOud Watcher at Night), an application interface that automatically monitors clouds in real time. This software can correctly trace clouds positions in the sky, provides accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas. {\tt{CLOWN}} only requires the use of an all-sky camera, which is already a norm in observatories with optical telescopes and can be used with any camera, including those for which no information about its model specification do exist. {\tt{CLOWN}} does not require great computing power and it does not require the installation of additional equipment. {\tt{CLOWN}} results are very promising and confirm that the app can correctly identify clouds in a variety of different conditions and cloud types., Comment: 15 pages, 22 figures. This is the Accepted Manuscript version of an article accepted for publication in Astromomical Journal. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record will be available online at https://iopscience.iop.org/journal/1538-3881

The Listening in Spatialized Noise Sentences (LiSN-S) is a test to evaluate auditory spatial processing currently only available in the English language. It produces a three-dimensional auditory environment under headphones and uses a simple repetition response protocol to determine speech reception thresholds (SRTs) for sentences presented in competing speech under various conditions. In order to develop the LiSN-S test in Brazilian Portuguese, it was necessary to prepare a speech database recorded by professional voice actresses and to devise presentation software. These sentences were presented to 35 adults (aged between 19 and 40 years) and 24 children (aged between 8 and 10 years), all with normal hearing-verified through tone and speech audiometry and tympanometry-and good performance at school. We used a logistic curve describing word error rate versus presentation level, fitted for each sentence, to select a set of 120 sentences for the test. Furthermore, all selected sentences were adjusted in amplitude for equal intelligibility. The framework of LiSN-S in Brazilian Portuguese is ready for normative data analysis. After its conclusion, we believe it will contribute to diagnosing and rehabilitating Brazilian children with complaints related to hearing difficulties in noisy environments

Intelligent assistants powered by Large Language Models (LLMs) can generate program and test code with high accuracy, boosting developers' and testers' productivity. However, there is a lack of studies exploring LLMs for testing Web APIs, which constitute fundamental building blocks of modern software systems and pose significant test challenges. Hence, in this article, we introduce APITestGenie, an approach and tool that leverages LLMs to generate executable API test scripts from business requirements and API specifications. In experiments with 10 real-world APIs, the tool generated valid test scripts 57% of the time. With three generation attempts per task, this success rate increased to 80%. Human intervention is recommended to validate or refine generated scripts before integration into CI/CD pipelines, positioning our tool as a productivity assistant rather than a replacement for testers. Feedback from industry specialists indicated a strong interest in adopting our tool for improving the API test process., Comment: 6 pages, 4 figures, submitted to IEEE Software Special Issue on Next-generation Software Testing: AI-powered Test Automation

We suggest a method for simultaneously generating high order quadrature weights for integrals over Lipschitz domains and their boundaries that requires neither meshing nor moment computation. The weights are determined on pre-defined scattered nodes as a minimum norm solution of a sparse underdetermined linear system arising from a discretization of a suitable boundary value problem by either collocation or meshless finite differences. The method is easy to implement independently of the domain's representation, since it only requires as inputs the position of all quadrature nodes and the direction of outward-pointing normals at each node belonging to the boundary. Numerical experiments demonstrate the robustness and high accuracy of the method on a number of smooth and piecewise smooth domains in 2D and 3D, including some with reentrant corners and edges.

Context. Tailed radio galaxies are shaped by ram pressure owing to the high-velocity motion of their host through the intracluster medium (ICM). Recent works have reported on the increasing complexity of the phenomenology of tailed galaxies, with departures from theoretical ageing models and evidence of re-energising mechanisms, which are yet unclear. Aims. The nearby (z = 0.0894) galaxy cluster Abell 2142 hosts two tailed galaxies, namely T1 and T2, which exhibit peculiar morphological features. We aim to investigate the properties of T1 and T2 and constrain their spectral evolution, dynamics, and interactions with the ICM. Methods. We combined LOw Frequency Array (LOFAR), upgraded Giant Metrewave Radio Telescope (uGMRT), Very Large Array (VLA), and MeerKAT data (from 30 MHz to 6.5 GHz) to carry out a detailed spectral analysis of T1 and T2. We analysed surface brightness profiles, measured integrated and spatially-resolved spectral indices, and performed a comparison with single injection ageing models. Chandra X-ray data were used to search for discontinuities in the ICM properties in the direction of the targets. Results. The spectral properties of T1 at low frequencies are predicted by ageing models, and provide constraints on the 3D dynamics of the host by assuming a constant velocity. However, sharp transitions along sub-regions of the tail, local surface brightness enhancements, and a spectral shape at high frequencies that is not predicted by models suggest a more complex scenario, possibly involving hydrodynamical instabilities and particle mixing. T2 exhibits unusual morphological and surface brightness features, and its spectral behaviour is not predicted by standard models. Two AGN outburst events during the infall of T2 towards the cluster centre could explain its properties., Comment: 23 pages (including Appendices). 15 figures. Accepted for publication in A&A

This is an index of the contributions by the Giant Radio Array for Neutrino Detection (GRAND) Collaboration to the 10th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities (ARENA 2024, University of Chicago, June 11-14, 2024). The contributions include an overview of GRAND in its present and future incarnations, methods of radio-detection that are being developed for them, and ongoing joint work between the GRAND and BEACON experiments., Comment: Note: To access the list of contributions, please follow the "HTML" link that can be found on the arXiv page

RISTRETTO is a visible high-resolution spectrograph fed by an extreme adaptive optics (AO) system, to be proposed as a visitor instrument on ESO VLT. The main science goal of RISTRETTO is to pioneer the detection and atmospheric characterisation of exoplanets in reflected light, in particular the temperate rocky planet Proxima b. RISTRETTO will be able to measure albedos and detect atmospheric features in a number of exoplanets orbiting nearby stars for the first time. It will do so by combining a high-contrast AO system working at the diffraction limit of the telescope to a high-resolution spectrograph, via a 7-spaxel integral-field unit (IFU) feeding single-mode fibers. Further science cases for RISTRETTO include the study of accreting protoplanets such as PDS70b/c through spectrally-resolved H-alpha emission, and spatially-resolved studies of Solar System objects such as icy moons and the ice giants Uranus and Neptune. The project is in the manufacturing phase for the spectrograph sub-system, and the preliminary design phase for the AO front-end. Specific developments for RISTRETTO include a novel coronagraphic IFU combining a phase-induced amplitude apodizer (PIAA) to a 3D-printed microlens array feeding a bundle of single-mode fibers. It also features an XAO system with a dual wavefront sensor aiming at high robustness and sensitivity, including to pupil fragmentation. RISTRETTO is a pathfinder instrument in view of similar developments at the ELT, in particular the SCAO-IFU mode of ELT-ANDES and the future ELT-PCS instrument., Comment: 6 pages, 1 figure, SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

Cellular automata (CAs) and convolutional neural networks (CNNs) are closely related due to the local nature of information processing. The connection between these topics is beneficial to both related fields, for conceptual as well as practical reasons. Our contribution solidifies this connection in the case of non-uniform CAs (nuCAs), simulating a global update in the architecture of the Python package TensorFlow. Additionally, we demonstrate how the highly optimised out-of-the-box multiprocessing in TensorFlow offers interesting computational benefits, especially when simulating large numbers of nuCAs with many cells., Comment: 10 pages, 5 figures, Conference Proceedings Article

The 15-minute city concept, advocating for cities where essential services are accessible within 15 minutes on foot and by bike, has gained significant attention in recent years. However, despite being celebrated for promoting sustainability, there is an ongoing debate regarding its effectiveness in reducing car usage and, subsequently, emissions in cities. In particular, large-scale evaluations of the effectiveness of the 15-minute concept in reducing emissions are lacking. To address this gap, we investigate whether cities with better walking accessibility, like 15-minute cities, are associated with lower transportation emissions. Comparing 700 cities worldwide, we find that cities with better walking accessibility to services emit less CO$_2$ per capita for transport. Moreover, we observe that among cities with similar average accessibility, cities spreading over larger areas tend to emit more. Our findings highlight the effectiveness of decentralised urban planning, especially the proximity-based 15-minute city, in promoting sustainable mobility. However, they also emphasise the need to integrate local accessibility with urban compactness and efficient public transit, which are vital in large cities.

Symmetry protected states (SPT's) of quantum spin systems were studied by several authors. For one-dimensional systems (spin chains), there is an essentially complete and rigorous understanding: SPT's corresponding to finite on-site symmetry groups $G$ are classified by the second cohomology group $H^2(G,U(1))$, as established by Kapustin et al. [J. Math. Phys. (2021)]. We extend this result to the case of compact topological symmetry groups $G$. We also strengthen the existing results in the sense that our classification results holds within the class of spin chains with locally bounded on-site dimensions., Comment: 37 pages, 7 figures

The leading Fock state light-front wave functions of heavy quarkonia and $D$ and $B$ mesons are obtained from the projections of their Bethe-Salpeter wave functions on the light front. We compute therefrom their leading-twist time-reversal even transverse momentum distributions and parton distribution functions. Mirroring the behavior of parton distribution amplitudes, the support of both distributions is increasingly narrower and shifted towards larger $x$ as a function of the meson mass. The dependence of $x$ and $\k_\perp^2$ of the transverse distributions does not factorize into separate functions, and their fall-off with $\k_\perp^2$ is much slower than that of light mesons.

The bond distance is the simplest and most obvious indicator of the nature of a given chemical bond. However, for rare chemistry, it may happen that it is not yet firmly established. In this communication, we will show that the formally-triple protactinium(V) mono-oxo bond is predicted longer than what was previously reported in the solid state and in solution, based on robust quantum mechanical calculations, supported by an extensive methodological study. Furthermore, additional calculations are used to demonstrate that the Pa-Ooxo bond of interest is more sensitive to complexation than the supposedly analogous U-Oyl ones, not only in terms of bond distance but also of finer bond descriptors associated with the effective bond multiplicity.

Averaged local bond order parameters based on spherical harmonics, also known as Lechner and Dellago order parameters, are routinely used to determine crystal structures in molecular simulations. Among different options, the combination of the $\overline{q}_{4}$ and $\overline{q}_{6}$ parameters is one of the best choices in the literature since allows one to distinguish, not only between solid- and liquid-like particles but also between different crystallographic phases, including cubic and hexagonal phases. Recently, Algaba et al. [J. Colloid Interface Sci. 623, 354, (2022)] have used the Lechner and Dellago order parameters to distinguish hydrate- and liquid-like water molecules in the context of determining the carbon dioxide hydrate-water interfacial free energy. According to the results, the preferred combination previously mentioned is not the best option to differentiate between hydrate- and liquid-like water molecules. In this work, we revisit and extend the use of these parameters to deal with systems in which clathrate hydrates phases coexist with liquid phases of water. We consider carbon dioxide, methane, tetrahydrofuran, nitrogen, and hydrogen hydrates that exhibit sI and sII crystallographic structures. We find that the $\overline{q}_{3}$ and $\overline{q}_{12}$ combination is the best option possible between a large number of possible different pairs to distinguish between hydrate- and liquid-like water molecules in all cases., Comment: 18 pages, 8 figures

The tracking-by-detection paradigm is the mainstream in multi-object tracking, associating tracks to the predictions of an object detector. Although exhibiting uncertainty through a confidence score, these predictions do not capture the entire variability of the inference process. For safety and security critical applications like autonomous driving, surveillance, etc., knowing this predictive uncertainty is essential though. Therefore, we introduce, for the first time, a fast way to obtain the empirical predictive distribution during object detection and incorporate that knowledge in multi-object tracking. Our mechanism can easily be integrated into state-of-the-art trackers, enabling them to fully exploit the uncertainty in the detections. Additionally, novel association methods are introduced that leverage the proposed mechanism. We demonstrate the effectiveness of our contribution on a variety of benchmarks, such as MOT17, MOT20, DanceTrack, and KITTI., Comment: Accepted for the ECCV 2024 Workshop on Uncertainty Quantification for Computer Vision

Multi-fidelity surrogate models combining dimensionality reduction and an intermediate surrogate in the reduced space allow a cost-effective emulation of simulators with functional outputs. The surrogate is an input-output mapping learned from a limited number of simulator evaluations. This computational efficiency makes surrogates commonly used for many-query tasks. Diverse methods for building them have been proposed in the literature, but they have only been partially compared. This paper introduces a unified framework encompassing the different surrogate families, followed by a methodological comparison and the exposition of practical considerations. More than a dozen of existing multi-fidelity surrogates have been implemented under the unified framework and evaluated on a set of benchmark problems. Based on the results, guidelines and recommendations are proposed regarding multi-fidelity surrogates with functional outputs. Our study shows that most multi-fidelity surrogates outperform their tested single-fidelity counterparts under the considered settings. But no particular surrogate is performing better on every test case. Therefore, the selection of a surrogate should consider the specific properties of the emulated functions, in particular the correlation between the low- and high-fidelity simulators, the size of the training set, the local nonlinear variations in the residual fields, and the size of the training datasets.

Music streaming services often leverage sequential recommender systems to predict the best music to showcase to users based on past sequences of listening sessions. Nonetheless, most sequential recommendation methods ignore or insufficiently account for repetitive behaviors. This is a crucial limitation for music recommendation, as repeatedly listening to the same song over time is a common phenomenon that can even change the way users perceive this song. In this paper, we introduce PISA (Psychology-Informed Session embedding using ACT-R), a session-level sequential recommender system that overcomes this limitation. PISA employs a Transformer architecture learning embedding representations of listening sessions and users using attention mechanisms inspired by Anderson's ACT-R (Adaptive Control of Thought-Rational), a cognitive architecture modeling human information access and memory dynamics. This approach enables us to capture dynamic and repetitive patterns from user behaviors, allowing us to effectively predict the songs they will listen to in subsequent sessions, whether they are repeated or new ones. We demonstrate the empirical relevance of PISA using both publicly available listening data from Last.fm and proprietary data from Deezer, a global music streaming service, confirming the critical importance of repetition modeling for sequential listening session recommendation. Along with this paper, we publicly release our proprietary dataset to foster future research in this field, as well as the source code of PISA to facilitate its future use., Comment: 11 pages. Accepted by RecSys'2024, full paper

The growth of the entanglement between a disjoint subsystem and its complement after a quantum quench is regarded as a dynamical chaos indicator. Namely, it is expected to show qualitatively different behaviours depending on whether the underlying microscopic dynamics is chaotic or integrable. So far, however, this could only be verified in the context of conformal field theories. Here we present an exact confirmation of this expectation in a class of interacting microscopic Floquet systems on the lattice, i.e., dual-unitary circuits. These systems can either have zero or a super extensive number of conserved charges: the latter case is achieved via fine-tuning. We show that, for almost all dual unitary circuits the asymptotic entanglement dynamics agrees with what is expected for chaotic systems. On the other hand, if we require the systems to have conserved charges, we find that the entanglement displays the qualitatively different behaviour expected for integrable systems. Interestingly, despite having many conserved charges, charge-conserving dual-unitary circuits are in general not Yang-Baxter integrable., Comment: 6+5 pages, 4 figures

We propose and analyze the use of an explicit time-context window for neural network-based spectral masking speech enhancement to leverage signal context dependencies between neighboring frames. In particular, we concentrate on soft masking and loss computed on the time-frequency representation of the reconstructed speech. We show that the application of a time-context windowing function at both input and output of the neural network model improves the soft mask estimation process by combining multiple estimates taken from different contexts. The proposed approach is only applied as post-optimization in inference mode, not requiring additional layers or special training for the neural network model. Our results show that the method consistently increases both intelligibility and signal quality of the denoised speech, as demonstrated for two classes of convolutional-based speech enhancement models. Importantly, the proposed method requires only a negligible ($\leq1\%$) increase in the number of model parameters, making it suitable for hardware-constrained applications., Comment: This work has been submitted to the IEEE for possible publication

What data or environments to use for training to improve downstream performance is a longstanding and very topical question in reinforcement learning. In particular, Unsupervised Environment Design (UED) methods have gained recent attention as their adaptive curricula enable agents to be robust to in- and out-of-distribution tasks. We ask to what extent these methods are themselves robust when applied to a novel setting, closely inspired by a real-world robotics problem. Surprisingly, we find that the state-of-the-art UED methods either do not improve upon the na\"{i}ve baseline of Domain Randomisation (DR), or require substantial hyperparameter tuning to do so. Our analysis shows that this is due to their underlying scoring functions failing to predict intuitive measures of ``learnability'', i.e., in finding the settings that the agent sometimes solves, but not always. Based on this, we instead directly train on levels with high learnability and find that this simple and intuitive approach outperforms UED methods and DR in several binary-outcome environments, including on our domain and the standard UED domain of Minigrid. We further introduce a new adversarial evaluation procedure for directly measuring robustness, closely mirroring the conditional value at risk (CVaR). We open-source all our code and present visualisations of final policies here: https://github.com/amacrutherford/sampling-for-learnability.

We generalize the potential reconstruction method to set up a dynamical Einstein-Born-Infeld-dilaton model, which we then use to study holographic quarkonium melting in an external magnetic field. The non-linear nature of the model allows to couple the magnetic field to the quarkonium inner structure without having to introduce back-reacting charged flavour degrees of freedom. The magnetic field dependent melting temperature is computed from the spectral functions and suggests a switch from magnetic to inverse magnetic catalysis when the magnetic field increases. We also discuss the differences due to the anisotropy brought in by the external field., Comment: 34 pages, 16 figures

This study investigates vulnerabilities in dependencies of sampled open-source software (OSS) projects, the relationship between these and overall project security, and how developers' behaviors and practices influence their mitigation. Through analysis of OSS projects, we have identified common issues in outdated or unmaintained dependencies, including pointer dereferences and array bounds violations, that pose significant security risks. We have also examined developer responses to formal verifier reports, noting a tendency to dismiss potential issues as false positives, which can lead to overlooked vulnerabilities. Our results suggest that reducing the number of direct dependencies and prioritizing well-established libraries with strong security records are effective strategies for enhancing the software security landscape. Notably, four vulnerabilities were fixed as a result of this study, demonstrating the effectiveness of our mitigation strategies., Comment: 16 pages

We study quasinormal modes of massive scalar perturbations in Kerr black holes using the isomonodromic method. For arbitrary scalar masses $M \mu$ and black hole spins $a/M$, we numerically determine the quasinormal frequencies for various orbital $\ell$, azimuthal $m$, and overtone $n$ numbers. In particular, we derive an analytic expression for frequencies of the zero-damping modes near the extremal limit $a/M \rightarrow 1$. For $\ell=m=1$, we reveal that the fundamental mode becomes a damped mode (rather than a zero-damping mode) if the scalar field is sufficiently heavy. By exploring the parameter space, we find numerical evidence for level-crossing between the longest-living mode and the first overtone at an exceptional point $(M\mu)_c \simeq 0.3704981$ and $(a/M)_c\simeq 0.9994660$., Comment: 20 pages, 13 graphics, 2 figures, 2 tables

Materials with chiral electronic structures are of great interest. We report a triazatruxene, TAT, molecular semiconductor with chiral alkyl side chains that crystallises from solution to form chirally-stacked columns with a helical pitch of 6 TATs (2.3 nm). These crystals show strong circularly polarised, CP, green photoluminescence, with dissymmetry of 24%. Electronic structure calculations using the full crystal structure, show that this chiral stacking associates angular momentum to the valence and conduction states and thus gives rise to the observed CP luminescence. Free-standing crystals are not useful for active semiconductor devices, but we have discovered that co-sublimation of TAT as the guest in a structurally mismatched host enables the fabrication of thin films where the chiral crystallization is achieved in-situ by thermally-triggered nano-phase segregation of dopant and host whilst preserving the integrity of the film. This enables fabrication of bright (green) organic light-emitting diodes with unexpectedly high external quantum efficiencies of up to 16% and electroluminescence dissymmetries above 10%. These materials and this process method offer significant application potential in spintronics, optical displays and multidimensional optoelectronics.

We characterize the critical parameter of oriented percolation on $\mathbb{Z}^2$ through the value of a zero-sum game. Specifically, we define a zero-sum game on a percolation configuration of $\mathbb{Z}^2$, where two players move a token along the non-oriented edges of $\mathbb{Z}^2$, collecting a cost of 1 for each edge that is open, and 0 otherwise. The total cost is given by the limit superior of the average cost. We demonstrate that the value of this game is deterministic and equals 1 if and only if the percolation parameter exceeds $p_c$, the critical exponent of oriented percolation. Additionally, we establish that the value of the game is continuous at $p_c$. Finally, we show that for $p$ close to 0, the value of the game is equal to 0.

We consider how to target evolution conditioned on atypical measurement outcomes in monitored quantum circuits, i.e., the post-selection problem. We show that for a simple class of measurement schemes, post-selected light-cone dynamical correlation functions can be obtained efficiently from the averaged correlations of a different unitary circuit. This connects rare measurement outcomes in one circuit to typical outcomes in another one. We derive conditions for the existence of this rare-to-typical mapping in brickwork quantum circuits made of XYZ gates. We illustrate these general results with a model system that exhibits a dynamical crossover (a smoothed dynamical transition) in event statistics, and discuss extensions to more general dynamical correlations.

MIMO (multiple input, multiple output) approaches are a recent trend in neural network architectures for video restoration problems, where each network evaluation produces multiple output frames. The video is split into non-overlapping stacks of frames that are processed independently, resulting in a very appealing trade-off between output quality and computational cost. In this work we focus on the low-latency setting by limiting the number of available future frames. We find that MIMO architectures suffer from problems that have received little attention so far, namely (1) the performance drops significantly due to the reduced temporal receptive field, particularly for frames at the borders of the stack, (2) there are strong temporal discontinuities at stack transitions which induce a step-wise motion artifact. We propose two simple solutions to alleviate these problems: recurrence across MIMO stacks to boost the output quality by implicitly increasing the temporal receptive field, and overlapping of the output stacks to smooth the temporal discontinuity at stack transitions. These modifications can be applied to any MIMO architecture. We test them on three state-of-the-art video denoising networks with different computational cost. The proposed contributions result in a new state-of-the-art for low-latency networks, both in terms of reconstruction error and temporal consistency. As an additional contribution, we introduce a new benchmark consisting of drone footage that highlights temporal consistency issues that are not apparent in the standard benchmarks., Comment: See the project web page to download the associated videos

We generalize the retractions to standard parabolic subgroups for even Artin groups to FC-type Artin groups and other more general families. We prove that these retractions uniquely extend to any parabolic subgroup. We use retractions to generalize the results of Antol\'in and Foniqi that reduce the problem of intersection of parabolic subgroups to weaker conditions. As a corollary, we characterize coherence for the FC case., Comment: 21 pages. Comments are welcome

In recent years, there have been significant advancements in computer vision which have led to the widespread deployment of image recognition and generation systems in socially relevant applications, from hiring to security screening. However, the prevalence of biases within these systems has raised significant ethical and social concerns. The most extensively studied biases in this context are related to gender, race and age. Yet, other biases are equally pervasive and harmful, such as lookism, i.e., the preferential treatment of individuals based on their physical appearance. Lookism remains under-explored in computer vision but can have profound implications not only by perpetuating harmful societal stereotypes but also by undermining the fairness and inclusivity of AI technologies. Thus, this paper advocates for the systematic study of lookism as a critical bias in computer vision models. Through a comprehensive review of existing literature, we identify three areas of intersection between lookism and computer vision. We illustrate them by means of examples and a user study. We call for an interdisciplinary approach to address lookism, urging researchers, developers, and policymakers to prioritize the development of equitable computer vision systems that respect and reflect the diversity of human appearances., Comment: Paper accepted at the ECCV 2024 workshop named "Fairness and ethics towards transparent AI: facing the chalLEnge through model Debiasing (FAILED)", https://failed-workshop-eccv-2024.github.io/

X-shaped radio galaxies (XRGs) are characterised by two pairs of misaligned lobes, namely the active lobes hosting radio jets and the wings. None of the formation mechanisms proposed so far can exhaustively reproduce the diverse features observed among XRGs. The emerging evidence is the existence of sub-populations of XRGs forming via different processes. The brightest cluster galaxy in Abell 3670 (A3670) is a dumbbell system hosting the XRG MRC 2011-298. The morphological and spectral properties of this interesting XRG have been first characterised through Karl G. Jansky Very Large Array (JVLA) data at 1-10 GHz. In the present work, we followed-up MRC 2011-298 with the upgraded Giant Metrewave Radio Telescope (uGMRT) at 120-800 MHz to further constrain its properties and origin. We carried out a detailed spectral analysis sampling different spatial scales. Integrated radio spectra, spectral index maps, radio colour-colour diagrams, and radiative age maps of both the active lobes and prominent wings have been employed to test the origin of the source. We confirm a progressive spectral steepening from the lobes to the wings. The maximum radiative age of the source is $\sim 80$ Myr, with the wings being older than the lobes by $\gtrsim 30$ Myr in their outermost regions. The observed properties are in line with an abrupt reorientation of the jets by $\sim 90$ deg from the direction of the wings to their present position. This formation mechanism is further supported by the comparison with numerical simulations in the literature, which additionally highlight the role of hydrodynamic processes in the evolution of large wings such as those of MRC 2011-298. Potentially, the coalescence of supermassive black holes could have triggered the spin-flip of the jets. Moreover, we show that the S-shape of the radio jets is likely driven by precession with a period $P \sim 10$ Myr., Comment: 23 pages (including Appendices), 14 figures. Accepted for publication in A&A

Experimental searches for axions or dark photons that couple to the standard model photon require photosensors with low noise, broadband sensitivity, and near zero backgrounds. Here, we introduce a Transition Edge Sensor (TES) based photon sensor with a high sensitivity athermal phonon sensor coupled to the substrate on which the TES is deposited. We show that single photons absorbed locally in the TES have $\sim$35% energy deposition in the electronic system of the TES, with $\sim$26% of the photon energy absorbed by the athermal photon sensor (due to athermal phonons leaking out of the TES during the downconversion process). Backgrounds are observed to be largely coupled to either the TES or phonon system. At high energies, these backgrounds can be efficiently discriminated from TES photon absorption events, while at low energies, their leakage into the passage band is well modeled. With significant sensitivity improvements to both the photon and phonon channel, this coincidence technique could be used to suppress backgrounds in bosonic dark matter searches down to energies near the superconducting bandgap of the sensor., Comment: 5 pages, 5 figures

In nontwist systems, primary shearless curves act as barriers to chaotic transport. Surprisingly, the onset of secondary shearless curves has been reported in a few twist systems. Meanwhile, we found that, in twist systems, the onset of these secondary shearless curves is a standard process that may appear as control parameters are varied in situations where there is resonant mode coupling. Namely, we analyze these shearless bifurcations in two-harmonic systems for the standard map, the Ullmann map, and for the Walker-Ford Hamiltonian flow. The onset of shearless curves is related to bifurcations of periodic points. Furthermore, depending on the bifurcation, these shearless curves can emerge alone or in pairs, and in some cases, deform into separatrices.

The operation of upcoming ultra-high-energy cosmic-ray, gamma-ray, and neutrino radio-detection experiments, like the Giant Radio Array for Neutrino Detection (GRAND), poses significant computational challenges involving the production of numerous simulations of particle showers and their detection, and a high data throughput. GRANDlib is an open-source software tool designed to meet these challenges. Its primary goal is to perform end-to-end simulations of the detector operation, from the interaction of ultra-high-energy particles, through -- by interfacing with external air-shower simulations -- the ensuing particle shower development and its radio emission, to its detection by antenna arrays and its processing by data-acquisition systems. Additionally, GRANDlib manages the visualization, storage, and retrieval of experimental and simulated data. We present an overview of GRANDlib to serve as the basis of future GRAND analyses., Comment: 11 pages, 9 figures, plus appendices

The challenge of Multimodal Deformable Image Registration (MDIR) lies in the conversion and alignment of features between images of different modalities. Generative models (GMs) cannot retain the necessary information enough from the source modality to the target one, while non-GMs struggle to align features across these two modalities. In this paper, we propose a novel coarse-to-fine MDIR framework,LLM-Morph, which is applicable to various pre-trained Large Language Models (LLMs) to solve these concerns by aligning the deep features from different modal medical images. Specifically, we first utilize a CNN encoder to extract deep visual features from cross-modal image pairs, then we use the first adapter to adjust these tokens, and use LoRA in pre-trained LLMs to fine-tune their weights, both aimed at eliminating the domain gap between the pre-trained LLMs and the MDIR task. Third, for the alignment of tokens, we utilize other four adapters to transform the LLM-encoded tokens into multi-scale visual features, generating multi-scale deformation fields and facilitating the coarse-to-fine MDIR task. Extensive experiments in MR-CT Abdomen and SR-Reg Brain datasets demonstrate the effectiveness of our framework and the potential of pre-trained LLMs for MDIR task. Our code is availabel at: https://github.com/ninjannn/LLM-Morph.

In this article, we study a two-parameter family of rotating rank-one maps defined on $\textbf{S}^1\times [1, 1+b]\times \textbf{S}^1$, with $b\gtrsim 0$, whose dynamics is characterised by a coupling of a family of planar maps exhibiting rank-one strange attractors and an Arnold family of circle maps. The main result is about the dynamics on the skew-product, which is governed by the existence and prevalence of strange attractors in the corresponding resonance tongues of the Arnold family. The strange attractors carry the unique physical measure of the system, which determines the behaviour of Lebesgue-almost all initial conditions. This phenomenon can be considered as the transition dynamics from a strange attractor with one positive Lyapunov exponent to hyperchaos. Besides an analytical rigorous proof, we illustrate the main results with numerical simulations. We also conjecture how persistent hyperchaos can be obtained., Comment: 28 pages

Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) generalizes and goes beyond conventional diagonal reconfigurable intelligent surfaces (D-RIS) by interconnecting elements to generate beyond diagonal scattering matrices, which significantly strengthen the wireless channels. In this work, we use BD-RIS for passive multiuser beamforming in multiuser multiple-input-single-output (MU-MISO) systems. Specifically, we design the scattering matrix of BD-RIS to either maximize the sum received signal power at the users following maximum ratio transmission (MRT), or to nullify the interference at the users following zero forcing (ZF). Furthermore, we investigate uniform/optimized power allocation and ZF precoding at the base station (BS). Numerical results show that BD-RIS improves the interference nulling capability and sum rate with fewer reflecting elements (REs) compared to D-RIS. In addition, at moderate to high signal to noise ratios (SNRs), passive interference nulling reduces the complexity at the BS by relaxing the need for precoding or water-filling power allocation design. Furthermore, the passive MRT with ZF precoding achieves a tight sum rate performance to the joint design considering MU-MISO scenarios with many REs while maintaining low computational complexity and simplifying the channel estimation.

In this paper we study holomorphic actions of the complex multiplicative group on complex manifolds around a singular (fixed) point. We prove linearization results for the germ of action and also for the whole action under some conditions on the manifold. This can be seen as a follow-up to previous works of M. Suzuki and other authors.

This work presents Retail-GPT, an open-source RAG-based chatbot designed to enhance user engagement in retail e-commerce by guiding users through product recommendations and assisting with cart operations. The system is cross-platform and adaptable to various e-commerce domains, avoiding reliance on specific chat applications or commercial activities. Retail-GPT engages in human-like conversations, interprets user demands, checks product availability, and manages cart operations, aiming to serve as a virtual sales agent and test the viability of such assistants across different retail businesses., Comment: 5 pages, 4 figures

Finding the eigenvalues connected to the covariance operator of a centred Hilbert-space valued Gaussian process is genuinely considered a hard problem in several mathematical disciplines. In statistics this problem arises for instance in the asymptotic null distribution of goodness-of-fit test statistics of weighted $L^2$-type. For this problem we present the Rayleigh-Ritz method to approximate the eigenvalues. The usefulness of these approximations is shown by high lightening implications such as critical value approximation and theoretical comparison of test statistics by means of Bahadur efficiencies., Comment: 18 pages, 16 tables

We consider the problem of minimizing the second conformal eigenvalue of the conformal Laplacian in a conformal class of metrics with renormalized volume. We prove, in dimensions $n\in\left\{3,\dotsc,10\right\}$, that a minimizer for this problem does not exist for metrics sufficiently close to the round metric on the sphere. This is in striking contrast with the situation in dimensions $n \ge 11$, where Ammann and Humbert obtained the existence of minimizers for the second conformal eigenvalue on any smooth closed non-locally conformally flat manifold. As a byproduct of our techniques, we also obtain a lower bound on the energy of sign-changing solutions of the \nobreak Yamabe equation in dimensions 3, 4 and 5, which extends a result obtained by Weth in the case of the round sphere., Comment: Comments welcome

KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on an initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photo-sensors. A high-purity neutrino sample was extracted, corresponding to an exposure of 433 kton-years. The sample of 5828 neutrino candidates is analysed following a binned log-likelihood method in the reconstructed energy and cosine of the zenith angle. The atmospheric oscillation parameters are measured to be $\sin^2\theta_{23}= 0.51^{+0.04}_{-0.05}$, and $ \Delta m^2_{31} = 2.14^{+0.25}_{-0.35}\times 10^{-3}~\mathrm{eV^2} \cup \{-2.25,-1.76\}\times 10^{-3}~\mathrm{eV^2}$ at 68\% CL. The inverted neutrino mass ordering hypothesis is disfavoured with a p-value of 0.25., Comment: 25 pages, 10 figures

A complex variety $X$ admits a \emph{cellular resolution of singularities} if there exists a resolution of singularities $\widetilde X\to X$ such that its exceptional locus as well as $\widetilde X$ and the singular locus of $X$ admit a cellular decomposition. We give a concrete description of the motive with compact support of $X$ in terms of its Borel--Moore homology, under some mild conditions. We give many examples, including rational projective curves and toric varieties of dimension two and three., Comment: 13 pages

Porous media are ubiquitous in the fields of energy storage and conversion, catalysis, biomechanics, hydrogeology, and other chemical engineering processes. These media possess high surface-to-volume ratios and their complex channels can restrict and direct the flow. This makes them key components of multiple equipment despite the challenges in selecting design parameters for specific applications. Pore-resolved CFD reveals the effects of their structure at the microscopic scale, but is currently limited by high computing costs and the performance of mesh generation algorithms. This work introduces a RBF-based representation of solids in a massively parallel immersed-boundary framework, enabling both the usage of non-conformal grids and dynamic mesh adaptation. We verify it using the method of manufactured solutions. We validate it using pressure drop measurements through porous silicone monoliths digitized by X-ray computed microtomography for Reynolds numbers up to 30, using grids of 200 M cells distributed over 8 k cores. The reliable model is then used to highlight that pore network structure is the main factor describing pressure evolution and that preferential channels are present at this scale of the porous media. This work opens the door to design and optimize processes by linking microscopic flow to macroscopic properties through the usage of physics-based digital twins of complex porous media., Comment: 26 pages, 18 figures

The predictions of hadronic interaction models for cosmic-ray induced air showers contain inherent uncertainties due to limitations of available accelerator data. This leads to differences in shower simulations using each of those models. Many studies have been carried out to track those differences by investigating the shower development or the particle content. In this work, we propose a new approach to search for discrepancies and similarities between the models, via the IACT images resulting from the observations of hadronic air showers. We use simulations of H.E.S.S. as a show-case scenario and, by investigating variables of the camera images, we find potential indicators to highlight differences between models. Number of pixels, Hillas image size, and density showed the largest difference between the models. We then further explore the (in)compatibility of the models by combining all the variables and using Boosted Decision Trees. For protons, a significant difference in the classifier output is found for EPOS-LHC when compared to both QGSJET-II04 and Sybill 2.3d. For helium and nitrogen, QGSJET-II04 is shown to be the outlier case. No significant differences are found for silicon and iron. The distribution of (in)compatibility between the models in the phase space of shower parameters shows that a targeted search can be fruitful, with showers with energies of a few TeV and core closer to the large telescope presenting the largest power of separation.

AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes. We conceptualize these challenges through the lens of vulnerability, the potential for university assessments and learning outcomes to be impacted by student use of generative AI. We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses. Specifically, we compile a novel dataset of textual assessment questions from 50 courses at EPFL and evaluate whether two AI assistants, GPT-3.5 and GPT-4 can adequately answer these questions. We use eight prompting strategies to produce responses and find that GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. When grouping courses in our dataset by degree program, these systems already pass non-project assessments of large numbers of core courses in various degree programs, posing risks to higher education accreditation that will be amplified as these models improve. Our results call for revising program-level assessment design in higher education in light of advances in generative AI., Comment: 20 pages, 8 figures