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Node regression consists in predicting the value of a graph label at a node, given observations at the other nodes. To gain some insight into the performance of various estimators for this task, we perform a theoretical study in a context where the graph is random. Specifically, we assume that the graph is generated by a Latent Position Model, where each node of the graph has a latent position, and the probability that two nodes are connected depend on the distance between the latent positions of the two nodes. In this context, we begin by studying the simplest possible estimator for graph regression, which consists in averaging the value of the label at all neighboring nodes. We show that in Latent Position Models this estimator tends to a Nadaraya Watson estimator in the latent space, and that its rate of convergence is in fact the same. One issue with this standard estimator is that it averages over a region consisting of all neighbors of a node, and that depending on the graph model this may be too much or too little. An alternative consists in first estimating the true distances between the latent positions, then injecting these estimated distances into a classical Nadaraya Watson estimator. This enables averaging in regions either smaller or larger than the typical graph neighborhood. We show that this method can achieve standard nonparametric rates in certain instances even when the graph neighborhood is too large or too small.

GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50\% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.

In the Jaynes-Cummings (JC) model, the time dependence in the coupling parameter allows changes in the forms of the Rabi oscillations. In the inverse problem approach (IPA), the time-dependent coupling parameter is obtained from the resulting population inversion. In this work, we employ the IPA to obtain a time-dependent coupling that reproduces the effects of $\kappa$-deformation in an undeformed JC. This is relevant because it may pave the way for interpreting quantum deformation in the $\kappa$-JC and possibly enables an experimental verification in a setting where the coupling can be precisely controlled. We also propose a generalized IPA, which includes the cavity with a distribution of photons., Comment: 7 pages, 8 figures, comments are welcome

We present a systematic study of the energy levels of twisted bilayer graphene (tBLG) quantum dots (QD) and rings (QR) under an external perpendicular magnetic field. The confinement structures are modeled by a circular dot-like- and ring-like-shaped site-dependent staggered potential, which prevents edge effects and leads to an energy gap between the electron and hole states. Results are obtained within the tight-binding model with interlayer hopping parameters defined by the Slater-Koster form for different interlayer twist angles $\theta$. Our findings show that, for $\theta$ around 0$^\circ$ or $60^\circ$, the energy spectra exhibit features resulting from the interplay between characteristics of the AA and AB/BA stacking orders that compose the moir\'e pattern of such tBLG, while the low-energy levels are shown to be nearly independent on the rotation angle for $10^\circ\lesssim \theta\lesssim 50^\circ$. In the absence of a magnetic field, the energy levels of the QR scale with its width $W$ according to a power law $W^{-\alpha}$, whose exponent $1 \lessapprox\alpha\lessapprox 2$ depends on the twist angle. Most interestingly, the lowest energy states of tBLG QRs oscillate as a function of its average radius, with the oscillation period matching half of the moir\'e period. In the presence of an intense magnetic field, the lowest energy levels for the tBLG QDs and QRs match almost perfectly, regardless of whether the external radius of the quantum confinement structure is smaller or on the order of the moir\'e period, which is due to the interplay of the trigonal warping effect and the preferential localization of the eigenstates. Our results reveal relevant information about the moir\'e pattern in tBLG and its role in charge particle confinement., Comment: 16 pages, 12 figures

(Abridged) We explore the chemistry of the most abundant C, O, S, and N bearing species in molecular clouds, in the context of the IRAM 30 m Large Programme Gas phase Elemental abundances in Molecular Clouds (GEMS). In this work, we aim to assess the limitations introduced in the observational works when a uniform density is assumed along the line of sight for fitting the observations, developing a very simple numerical model of a turbulent box. We perform a MHD simulation in order to reproduce the turbulent steady-state of a turbulent box with properties typical of a molecular filament before collapse. We post-process the results of the MHD simulation with a chemical code to predict molecular abundances, and then post-process this cube with a radiative transfer code to create synthetic emission maps for a series of rotational transitions observed during the GEMS project. From the chemical point of view, we find that turbulence produces variations on the predicted abundances, but they are more or less critical depending on the chosen transition and the chemical age. When compared to real observations, the results from the turbulent simulation provides a better fit than when assuming a uniform gas distribution along the line of sight. In the view of our results, we conclude that taking into account turbulence when fitting observations might significantly improve the agreement with model predictions. This is especially important for sulfur bearing species that are very sensitive to the variations of density produced by turbulence at early times (0.1 Myr). The abundance of CO is also quite sensitive to turbulence when considering the evolution beyond a few 0.1 Myr., Comment: Published in Astronomy and Astrophysics

In Reinforcement Learning (RL), multi-armed Bandit (MAB) problems have found applications across diverse domains such as recommender systems, healthcare, and finance. Traditional MAB algorithms typically assume stationary reward distributions, which limits their effectiveness in real-world scenarios characterized by non-stationary dynamics. This paper addresses this limitation by introducing and evaluating novel Bandit algorithms designed for non-stationary environments. First, we present the Adaptive Discounted Thompson Sampling (ADTS) algorithm, which enhances adaptability through relaxed discounting and sliding window mechanisms to better respond to changes in reward distributions. We then extend this approach to the Portfolio Optimization problem by introducing the Combinatorial Adaptive Discounted Thompson Sampling (CADTS) algorithm, which addresses computational challenges within Combinatorial Bandits and improves dynamic asset allocation. Additionally, we propose a novel architecture called Bandit Networks, which integrates the outputs of ADTS and CADTS, thereby mitigating computational limitations in stock selection. Through extensive experiments using real financial market data, we demonstrate the potential of these algorithms and architectures in adapting to dynamic environments and optimizing decision-making processes. For instance, the proposed bandit network instances present superior performance when compared to classic portfolio optimization approaches, such as capital asset pricing model, equal weights, risk parity, and Markovitz, with the best network presenting an out-of-sample Sharpe Ratio 20% higher than the best performing classical model.

This work presents the development of a lane detection system aimed at assisting the driving of conventional and autonomous vehicles. The system was implemented using traditional computer vision techniques, focusing on robustness and efficiency to operate in real-time, even under adverse conditions such as worn-out lanes and weather variations. The methodology employs an image processing pipeline that includes camera calibration, distortion correction, perspective transformation, and binary image generation. Lane detection is performed using sliding window techniques and segmentation based on gradients and color channels, enabling the precise identification of lanes in various road scenarios. The results indicate that the system can effectively detect and track lanes, performing well under different lighting conditions and road surfaces. However, challenges were identified in extreme situations, such as intense shadows and sharp curves. It is concluded that, despite its limitations, the traditional computer vision approach shows significant potential for application in driver assistance systems and autonomous navigation, with room for future improvements.

The planar dynamics of spin-1/2 quantum relativistic particles is important for several physical systems. In this paper we derive, by a simple method, the generators for the continuous symmetries of the 3+1 Dirac equation for planar motion, when there is circular symmetry, i.e., the interactions depend only on the radial coordinate. We consider a general set of potentials with different Lorentz structures. These generators allow for several minimal complete sets of commuting observables and their corresponding quantum numbers. We show how they can be used to label the general eigenspinors for this problem. We also derive the generators of the spin and pseudospin symmetries for this planar Dirac problem, which arise when the vector and scalar potentials have the same magnitude and tensor potential and the space components of the four-vector potential are absent. We investigate the associated energy degeneracies and compare them to the known degeneracies in the spherically symmetric 3+1 Dirac equation.

Ionic liquids have been suggested as new engineering fluids, namely in the area of heat transfer, as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and pose some environmental problems. Recently, we have proposed 1-ethyl-3-methylimidazolium methanesulfonate, [$C_{2}mim$][$CH_{3}SO_{3}$], as a new heat transfer fluid, because of its thermophysical and toxicological properties. However, there are some interesting points raised in this work, namely the possibility of the existence of liquid metastability below the melting point (303 K) or second order-disorder transitions ($\lambda$-type) before reaching the calorimetric freezing point. This paper analyses in more detail this zone of the phase diagram of the pure fluid, by reporting accurate thermal-conductivity measurements between 278 and 355 K with an estimated uncertainty of 2% at a 95% confidence level. A new value of the melting temperature is also reported, $T_{melt}$ = 307.8 $\pm$ 1 K. Results obtained support liquid metastability behaviour in the solid-phase region and permit the use of this ionic liquid at a heat transfer fluid at temperatures below its melting point. Thermal conductivity models based on Bridgman theory and estimation formulas were also used in this work, failing to predict the experimental data within its uncertainty.

Ionic liquids have proved to be excellent heat transfer fluids and alternatives to common HTFs used in industries for heat exchangers and other heat transfer equipment. However, its industrial utilization depends on the cost per kg of its production, to be competitive for industrial applications with biphenyl and diphenyl oxide, alkylated aromatics, and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and possess some environmental problems. The efficiency of a heat transfer fluid depends on the fundamental thermophysical properties influencing convective heat transfer (density, heat capacity, thermal conductivity, and viscosity), as these properties are necessary to calculate the heat transfer coefficients for different heat exchanger geometries. In Part 1, the thermophysical properties of pure 1-ethyl-3-methylimidazolium methanesulfonate $[C_{2}mim][CH_{3}SO_{3}]$ (CAS no. 145022-45-3), (ECOENG 110), produced by BASF, under the trade name of Basionics ST35, with an assay $\geq$97% with $\leq$0.5% water and $\leq$2% chloride ($Cl^{-}$), were presented, for temperatures slightly below room temperature and up to 355 K. In this paper, we report the thermophysical properties of mixtures of [C2mim][CH3SO3] with water, in the whole concentration range, at $P$ = 0.1 MPa. The properties measured were density and speed of sound (293.15 < $T$/K < 343.15), viscosity, electrical and thermal conductivities, refractive index (293.15 < $T$/K < 353.15), and infinite dilution diffusion coefficient of the ionic liquid in water (298.15 K).

As the interest in FPGA-based accelerators for HPC applications increases, new challenges also arise, especially concerning different programming and portability issues. This paper aims to provide a snapshot of the current state of the FPGA tooling and its problems. To do so, we evaluate the performance portability of two frameworks for developing FPGA solutions for HPC (SYCL and OpenCL) when using them to port a highly-parallel application to FPGAs, using both ND-range and single-task type of kernels. The developer's general recommendation when using FPGAs is to develop single-task kernels for them, as they are commonly regarded as more suited for such hardware. However, we discovered that, when using high-level approaches such as OpenCL and SYCL to program a highly-parallel application with no FPGA-tailored optimizations, ND-range kernels significantly outperform single-task codes. Specifically, while SYCL struggles to produce efficient FPGA implementations of applications described as single-task codes, its performance excels with ND-range kernels, a result that was unexpectedly favorable.

The non-Hermitian skin effect (NHSE) is a distinctive topological phenomenon observed in nonHermitian systems. Recently, there has been considerable interest in exploring higher-order NHSE occurrences in two and three dimensions. In such systems, topological edge states collapse into a corner while bulk states remain delocalized. Through a Hermitian-non-Hermitian correspondence, this study predicts and experimentally observes the higher-order NHSE in an acoustic Kagome lattice possessing nonreciprocal hoppings. By rotating the frequency spectrum and employing complexfrequency excitation techniques, we observe the localization of acoustic energy towards a corner of the lattice in the topologically nontrivial phase, even when the source is located far from that corner. In contrast, the acoustic energy spreads out when excited at the frequencies hosting the bulk states. These observations are unequivocal evidence of the higher-order NHSE.

To describe the spatial trajectory of an overdamped Brownian particle, inertial effects can be neglected. Yet, at the energetic level of stochastic thermodynamics, changes in kinetic energy must be considered to accurately predict the heat exchanged with the thermal bath. On the other hand, in the presence of external driving forces, one would expect the effects of kinetic energy fluctuations to be reduced, as thermal noise becomes comparatively less relevant. Here, we investigate the competition between the kinetic energy and the external work contributions to the heat statistics of passive and active overdamped Brownian particles subject to external driving forces. We find that kinetic energy effects cause fluctuations in the exchanged heat to become non-Gaussian. To evaluate the relevance of these effects, we compute the excess kurtosis and the Pearson correlation. For fixed parameter values adapted from experiments, we identify a crossover transition from a regime in which the stochastic heat of overdamped particles is dominated by external work, where kinetic energy changes can be safely ignored, to a regime dominated by kinetic energy effects. Our results also provide a quantitative analytical way to assess how deep into a particular regime the system is., Comment: 13 pages, 4 figures

The inner alignment problem, which asserts whether an arbitrary artificial intelligence (AI) model satisfices a non-trivial alignment function of its outputs given its inputs, is undecidable. This is rigorously proved by Rice's theorem, which is also equivalent to a reduction to Turing's Halting Problem, whose proof sketch is presented in this work. Nevertheless, there is an enumerable set of provenly aligned AIs that are constructed from a finite set of provenly aligned operations. Therefore, we argue that the alignment should be a guaranteed property from the AI architecture rather than a characteristic imposed post-hoc on an arbitrary AI model. Furthermore, while the outer alignment problem is the definition of a judge function that captures human values and preferences, we propose that such a function must also impose a halting constraint that guarantees that the AI model always reaches a terminal state in finite execution steps. Our work presents examples and models that illustrate this constraint and the intricate challenges involved, advancing a compelling case for adopting an intrinsically hard-aligned approach to AI systems architectures that ensures halting., Comment: Submitted for the Scientific Reports AI Alignment Collection

As Field Programmable Gate Arrays (FPGAs) computing capabilities continue to grow, also does the interest on building scientific accelerators around them. Tools like Xilinx's High-Level Synthesis (HLS) help to bridge the gap between traditional high-level languages such as C and C++, and low-level hardware description languages such as VHDL and Verilog. In this report, we study the implementation of a fluid dynamics application, the Finite-Time Lyapunov Exponent (FTLE) calculation, on FPGA using HLS. We provide speed and resource-consumption results for 2- and 3-dimensional cases., Comment: 8 pages, 2 tables

Carbon abundances in first-ascent giant stars are usually lower than those of their main-sequence counterparts. At moderate metallicities, stellar evolution of single stars cannot account for the existence of red-giant branch stars with enhanced carbon abundances. The phenomenon is usually interpreted as resulting from past mass transfer from an evolved binary companion now in the white dwarf evolutionary stage. Aims: We aim to confirm the links between [C/O] enhancement, s-process element enhancement and binary fraction using large-scale catalogues of stellar abundances and probable binary stars. Methods: We use a large data set from the 17 data release of the SDSS-IV/APOGEE~2 survey to identify carbon-enhanced stars in the Galactic disk. We identify a continuum of carbon enrichment throughout three different sub-populations of disk stars and explore links between the degree of carbon enrichment and binary frequency, metallicity and chemical compositions. Results: We verify a clear correlation between binary frequency and enhancement in the abundances of both carbon and cerium, lending support to the scenario whereby carbon-enhanced stars are the result of mass transfer by an evolved binary companion. In addition, we identify clustering in the carbon abundances of high-$\alpha$ disk stars, suggesting that those on the high metallicity end are likely younger, in agreement with theoretical predictions for the presence of a starburst population following the gas-rich merger of the Gaia-Enceladus/Sausage system., Comment: 20 pages

We present our numerical simulation approach for the End-to-End (E2E) model applied to various astronomical spectrographs, such as SOXS (ESO-NTT), CUBES (ESO-VLT), and ANDES (ESO-ELT), covering multiple wavelength regions. The E2E model aim at simulating the expected astronomical observations starting from the radiation of the scientific sources (or calibration sources) up to the raw-frame data produced by the detectors. The comprehensive description includes E2E architecture, computational models, and tools for rendering the simulated frames. Collaboration with Data Reduction Software (DRS) teams is discussed, along with efforts to meet instrument requirements. The contribution to the cross-correlation algorithm for the Active Flexure Compensation (AFC) system of CUBES is detailed., Comment: 19 pages, 17 figures, SPIE Astronomical Telescopes + Instrumentation, Yokohama 2024. arXiv admin note: text overlap with arXiv:2209.07185, arXiv:2012.12684

A recent stream of structured learning approaches has improved the practical state of the art for a range of combinatorial optimization problems with complex objectives encountered in operations research. Such approaches train policies that chain a statistical model with a surrogate combinatorial optimization oracle to map any instance of the problem to a feasible solution. The key idea is to exploit the statistical distribution over instances instead of dealing with instances separately. However learning such policies by risk minimization is challenging because the empirical risk is piecewise constant in the parameters, and few theoretical guarantees have been provided so far. In this article, we investigate methods that smooth the risk by perturbing the policy, which eases optimization and improves generalization. Our main contribution is a generalization bound that controls the perturbation bias, the statistical learning error, and the optimization error. Our analysis relies on the introduction of a uniform weak property, which captures and quantifies the interplay of the statistical model and the surrogate combinatorial optimization oracle. This property holds under mild assumptions on the statistical model, the surrogate optimization, and the instance data distribution. We illustrate the result on a range of applications such as stochastic vehicle scheduling. In particular, such policies are relevant for contextual stochastic optimization and our results cover this case., Comment: 10 pages main document, 3 pages supplement

The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of $\sim$100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 $\mu$m with the goal of extending it to 0.35-2.4 $\mu$m with the addition of a U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allow ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coud\'e room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases, there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states., Comment: SPIE astronomical telescope and instrumentation 2024, in press

In this article, we introduce the novel concept of the second maximum of a Gaussian random field on a Riemannian submanifold. This second maximum serves as a powerful tool for characterizing the distribution of the maximum. By utilizing an ad-hoc Kac Rice formula, we derive the explicit form of the maximum's distribution, conditioned on the second maximum and some regressed component of the Riemannian Hessian. This approach results in an exact test, based on the evaluation of spacing between these maxima, which we refer to as the spacing test. We investigate the applicability of this test in detecting sparse alternatives within Gaussian symmetric tensors, continuous sparse deconvolution, and two-layered neural networks with smooth rectifiers. Our theoretical results are supported by numerical experiments, which illustrate the calibration and power of the proposed tests. More generally, this test can be applied to any Gaussian random field on a Riemannian manifold, and we provide a general framework for the application of the spacing test in continuous sparse kernel regression. Furthermore, when the variance-covariance function of the Gaussian random field is known up to a scaling factor, we derive an exact Studentized version of our test, coined the $t$-spacing test. This test is perfectly calibrated under the null hypothesis and has high power for detecting sparse alternatives., Comment: 5 figures, 22 pages main document, 2 pages supplements

This works reports evidence for the topological signatures of ambiguity in sentence embeddings that could be leveraged for ranking and/or explanation purposes in the context of vector search and Retrieval Augmented Generation (RAG) systems. We proposed a working definition of ambiguity and designed an experiment where we have broken down a proprietary dataset into collections of chunks of varying size - 3, 5, and 10 lines and used the different collections successively as queries and answers sets. It allowed us to test the signatures of ambiguity with removal of confounding factors. Our results show that proxy ambiguous queries (size 10 queries against size 3 documents) display different distributions of homologies 0 and 1 based features than proxy clear queries (size 5 queries against size 10 documents). We then discuss those results in terms increased manifold complexity and/or approximately discontinuous embedding submanifolds. Finally we propose a strategy to leverage those findings as a new scoring strategy of semantic similarities.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Unlike traditional statistical methods, Conformal Prediction (CP) allows for the determination of valid and accurate confidence levels associated with individual predictions based only on exchangeability of the data. We here introduce a new feature selection method that takes advantage of the CP framework. Our proposal, named Conformal Recursive Feature Elimination (CRFE), identifies and recursively removes features that increase the non-conformity of a dataset. We also present an automatic stopping criterion for CRFE, as well as a new index to measure consistency between subsets of features. CRFE selections are compared to the classical Recursive Feature Elimination (RFE) method on several multiclass datasets by using multiple partitions of the data. The results show that CRFE clearly outperforms RFE in half of the datasets, while achieving similar performance in the rest. The automatic stopping criterion provides subsets of effective and non-redundant features without computing any classification performance.

The nonlinear Schrodinger equation supports solitons -- self-interacting, localized states that behave as nearly independent objects. We exhibit solitons with self-induced nonreciprocal dynamics in a discrete nonlinear Schrodinger equation. This nonreciprocal behavior, dependent on soliton power, arises from the interplay between linear and nonlinear terms in the equations of motion. Initially stable at high power, solitons exhibit nonreciprocal instabilities as power decreases, leading to unidirectional acceleration and amplification. This behavior is topologically protected by winding numbers on the solitons' mean-field Hamiltonian and their stability matrix, linking nonlinear dynamics and point gap topology in non-Hermitian Hamiltonians., Comment: 6 pages, 3 figures

Stellar rotation at early ages plays a crucial role in the survival of primordial atmospheres around Earth-mass exoplanets. Earth-like planets orbiting fast-rotating stars may undergo complete photoevaporation within the first few hundred Myr driven by the enhanced stellar XUV radiation, while planets orbiting slow-rotating stars are expected to experience difficulty to lose their primordial envelopes. Besides the action of stellar radiation, stellar winds induce additional erosion on these primordial atmospheres, altering their morphology, extent, and causing supplementary atmospheric losses. In this paper, we study the impact of activity-dependent stellar winds on primordial atmospheres to evaluate the extent at which the action of these winds can be significant in the whole planetary evolution at early evolutionary stages. We performed 3D magnetohydrodynamical (MHD) simulations of the interaction of photoevaporating atmospheres around unmagnetized Earth-mass planets in the time-span between 50 and 500 Myr, analyzing the joint evolution of stellar winds and atmospheres for both fast- and slow-rotating stars. Our results reveal substantial changes in the evolution of primordial atmospheres when influenced by fast-rotating stars, with a significant reduction in extent at early ages. In contrast, atmospheres embedded in the stellar winds from slow-rotating stars remain largely unaltered. The interaction of the magnetized stellar winds with the ionized upper atmospheres of these planets allows to evaluate the formation and evolution of different MHD structures, such as double-bow shocks and induced magnetospheres. This work will shed light to the first evolutionary stages of Earth-like exoplanets, that are of crucial relevance in terms of planet habitability.

T Tauri Stars (TTSs) are magnetically active stars that accrete matter from the inner border of the surrounding accretion disc; plasma gets trapped into the large scale magnetic structures and falls onto the star, heating the surface through the so-called accretion shocks. The X-ray spectra of the TTSs show prominent Fe II Kalpha fluorescence emission at 6.4keV that cannot be explained in a pure accretion scenario. Neither, it can be produced by the hot coronal plasma. TTSs display all signs of magnetic activity and magnetic reconnection events are expected to occur frequently. In these events, electrons may get accelerated to relativistic speeds and their interaction with the environmental matter may result in Fe Kalpha emission. It is the aim of this work to evaluate the expected Fe Kalpha emission in the context of the TTS research and compare it with the actual Fe Kalpha measurements obtained during the flare detected while monitoring RY Tau with the XMM-Newton satellite. The propagation of high-energy electrons in dense gas generates a cascade of secondary particles that results in an electron shower of random nature whose evolution and radiative throughput is simulated in this work using the Monte Carlo code PENELOPE. A set of conditions representing the environment of the TTSs where these showers may impinge has been taken into account to generate a grid of models that can aid to the interpretation of the data. The simulations show that the electron beams produce a hot spot at the point of impact; strong Fe Kalpha emission and X-ray continuum radiation are produced by the spot. This emission is compatible with RY Tau observations. The Fe Kalpha emission observed in TTSs could be produced by beams of relativistic electrons accelerated in magnetic reconnection events during flares., Comment: 9 pages, 12 figures

We propose a notion of conditioned stochastic stability of invariant measures on repellers: we consider whether quasi-ergodic measures of absorbing Markov processes, generated by random perturbations of the deterministic dynamics and conditioned upon survival in a neighbourhood of a repeller, converge to an invariant measure in the zero-noise limit. Under suitable choices of the random perturbation, we find that equilibrium states on uniformly expanding repellers are conditioned stochastically stable. In the process, we establish a rigorous foundation for the existence of ``natural measures'', which were proposed by Kantz and Grassberger in 1984 to aid the understanding of chaotic transients., Comment: 40 pages

Linguistic ambiguity continues to represent a significant challenge for natural language processing (NLP) systems, notwithstanding the advancements in architectures such as Transformers and BERT. Inspired by the recent success of instructional models like ChatGPT and Gemini (In 2023, the artificial intelligence was called Bard.), this study aims to analyze and discuss linguistic ambiguity within these models, focusing on three types prevalent in Brazilian Portuguese: semantic, syntactic, and lexical ambiguity. We create a corpus comprising 120 sentences, both ambiguous and unambiguous, for classification, explanation, and disambiguation. The models capability to generate ambiguous sentences was also explored by soliciting sets of sentences for each type of ambiguity. The results underwent qualitative analysis, drawing on recognized linguistic references, and quantitative assessment based on the accuracy of the responses obtained. It was evidenced that even the most sophisticated models, such as ChatGPT and Gemini, exhibit errors and deficiencies in their responses, with explanations often providing inconsistent. Furthermore, the accuracy peaked at 49.58 percent, indicating the need for descriptive studies for supervised learning., Comment: in Portuguese language, 16 p\'aginas, 5 p\'aginas de ap\^endice e 4 imagens

We prove the Effros-Hahn conjecture for groupoid algebras with coefficients in a sheaf, obtaining as a consequence a description of the ideals in skew inverse semigroup rings. We also use the description of the ideals to characterize when the groupoid algebras with coefficients in a sheaf are von Neumann regular, primitive, semiprimitive, or simple. We apply our results to the topological dynamics of actions of inverse semigroups, describing the existence of dense orbits and minimality in terms of primitivity and simplicity, respectively, of the associated algebra. Moreover, we apply our results to the usual complex groupoid algebra of continuous functions with compact support, used to build the C*-algebra associated with a groupoid, and describe criteria for its simplicity.

Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzyme Chemistry Relation Extraction Dataset, a new training and benchmarking dataset to support the development of Natural Language Processing (NLP) methods such as (large) language models that can assist enzyme curation. EnzChemRED consists of 1,210 expert curated PubMed abstracts in which enzymes and the chemical reactions they catalyze are annotated using identifiers from the UniProt Knowledgebase (UniProtKB) and the ontology of Chemical Entities of Biological Interest (ChEBI). We show that fine-tuning pre-trained language models with EnzChemRED can significantly boost their ability to identify mentions of proteins and chemicals in text (Named Entity Recognition, or NER) and to extract the chemical conversions in which they participate (Relation Extraction, or RE), with average F1 score of 86.30% for NER, 86.66% for RE for chemical conversion pairs, and 83.79% for RE for chemical conversion pairs and linked enzymes. We combine the best performing methods after fine-tuning using EnzChemRED to create an end-to-end pipeline for knowledge extraction from text and apply this to abstracts at PubMed scale to create a draft map of enzyme functions in literature to guide curation efforts in UniProtKB and the reaction knowledgebase Rhea. The EnzChemRED corpus is freely available at https://ftp.expasy.org/databases/rhea/nlp/.

The problem of vectorial mesons embedded in an electromagnetic field via Duffin-Kemmer-Petiau (DKP) formalism is reinvestigated. Considering the electromagnetic interaction as a minimal coupling, an incorrect value $(g=1)$ is identified for the gyromagnetic factor ($g$-factor). Furthermore, it is shown that is cumbersome to find analytical solutions due to the presence of the so-called anomalous term for the spin-1 sector of the DKP theory. Suspecting that the anomalous term results from an incomplete version of the DKP equation to describe the electromagnetic interaction, we consider the addition of a non-minimal coupling. This leads to the correct $g$-factor $(g=2)$, and as a consequence, the anomalous term becomes proportional to an external four current. As an application, the DKP equation with a static uniform magnetic field is considered, yielding the corresponding Landau levels., Comment: 06 pages

As an organic semiconductor and a prototypical acceptor molecule in organic photovoltaics, C$_{60}$ has broad relevance to the world of organic thin film electronics. Although highly uniform C$_{60}$ thin films are necessary to conduct spectroscopic analysis of the electronic structure of these C$_{60}$-based materials, reported C$_{60}$ films show a relatively low degree of order beyond a monolayer. Here, we develop a generalizable two-stage growth technique that consistently produces single-domain C$_{60}$ films of controllable thicknesses, using Au(111) as an epitaxially well-matched substrate. We characterize the films using low-energy electron diffraction, low-energy electron microscopy, scanning tunneling microscopy, and angle-resolved photoemission spectroscopy (ARPES). We report highly oriented epitaxial film growth of C$_{60}$/Au(111) from 1 monolayer (ML) up to 20 ML films. The high-quality of the C$_{60}$ thin films enables the direct observation of the electronic dispersion of the HOMO and HOMO-1 bands via ARPES without need for small spot sizes. Our results indicate a path for the growth of organic films on metallic substrates with long-range ordering., Comment: 16 pages, 7 figures

To address the global issue of online hate, hate speech detection (HSD) systems are typically developed on datasets from the United States, thereby failing to generalize to English dialects from the Majority World. Furthermore, HSD models are often evaluated on non-representative samples, raising concerns about overestimating model performance in real-world settings. In this work, we introduce NaijaHate, the first dataset annotated for HSD which contains a representative sample of Nigerian tweets. We demonstrate that HSD evaluated on biased datasets traditionally used in the literature consistently overestimates real-world performance by at least two-fold. We then propose NaijaXLM-T, a pretrained model tailored to the Nigerian Twitter context, and establish the key role played by domain-adaptive pretraining and finetuning in maximizing HSD performance. Finally, owing to the modest performance of HSD systems in real-world conditions, we find that content moderators would need to review about ten thousand Nigerian tweets flagged as hateful daily to moderate 60% of all hateful content, highlighting the challenges of moderating hate speech at scale as social media usage continues to grow globally. Taken together, these results pave the way towards robust HSD systems and a better protection of social media users from hateful content in low-resource settings., Comment: ACL 2024 main conference. Data and models available at https://github.com/worldbank/NaijaHate

Context and motivation: Software Product Lines (SPL) enable the creation of software product families with shared core components using feature models to model variability. Choosing features from a feature model to generate a product may not be sufficient in certain situations because the application engineer may need to be able to decide on configuration time the system's elements to which a certain feature will be applied. Therefore, there is a need to select which features have to be included in the product but also to which of its elements they have to be applied. Objective: We introduce local features that are selectively applied to specific parts of the system during product configuration. Results: We formalize local features using multimodels to establish relationships between local features and other elements of the system models. The paper includes examples illustrating the motivation for local features, a formal definition, and a domain-specific language for specification and implementation. Finally, we present a case study in a real scenario that shows how the concept of local features allowed us to define the variability of a complex system. The examples and the application case show that the proposal achieves higher customization levels at the application engineering phase.

The pseudopotential and free energy models are two popular extensions of the lattice Boltzmann method for multiphase flows. Until now, they have been developed apart from each other in the literature. However, important questions about whether each method performs better needs to be solved. In this work, we perform a theoretical and numerical comparison between both methods. This comparison is only possible because we developed a novel approach for controlling the interface thickness in the pseudopotential method independently on the equation of state. In this way, it is possible to compare both methods maintaining the same equilibrium densities, interface thickness, surface tension and equation of state parameters. The well-balanced approach was selected to represent the free energy. We found that the free energy one is more practical to use, as it is not necessary to carry out previous simulations to determine simulation parameters (interface thickness, surface tension, etc). In addition, the tests proofed that the free energy model is more accurate than the pseudopotential model. Furthermore, the pseudopotential method suffers from a lack of thermodynamic consistency even when applying the corrections proposed in the literature. On the other hand, for both static and dynamic tests we verified that the pseudopotential method is more stable than the free energy one, allowing simulations with lower reduced temperatures. We hope that these results will guide authors in the use of each method., Comment: 20 pages, 9 figures

Planets orbiting members of open or globular clusters offer a great opportunity to study exoplanet populations systematically as stars within clusters provide a mostly homogeneous sample at least in chemical composition and stellar age. However, even though there have been coordinated efforts to search for exoplanets in stellar clusters, only a small number of planets has been detected. One successful example is the seven-year radial velocity (RV) survey "Search for giant planets in M67" of 88 stars in the open cluster M67 which led to the discovery of five giant planets, including three close-in ($P < 10$ days) hot-Jupiters. In this work, we continue and extend the observation of stars in M67 with the aim to search for additional planets. We conducted spectroscopic observations with the HPF, HARPS, HARPS-North, and SOPHIE spectrographs of 11 stars in M67. Six of our targets showed a variation or long-term trends in their RV during the original survey, while the other five were not observed in the original sample bringing the total number of stars to 93. An analysis of the radial velocities revealed one additional planet around the turn-off point star S1429 and gave solutions for the orbits of stellar companions around S2207 and YBP2018. S1429 b is a warm Jupiter on a likely circular orbit with a period of $77.48_{-0.19}^{+0.18}$ days and a minimum mass $\text{M} \sin i = 1.80 \pm 0.2$ M$_\text{J}$. We update the hot-Jupiter occurrence rate in M67 to include the five new stars, deriving $4.2_{-2.3}^{+4.1} \%$ when considering all stars, and $5.4_{-3.0}^{+5.1} \%$ if binary star systems are removed., Comment: 27 pages, 20 figures. Accepted for publication in A&A

Observations at (sub-)millimeter wavelengths offer a complementary perspective on our Sun and other stars, offering significant insights into both the thermal and magnetic composition of their chromospheres. Despite the fundamental progress in (sub-)millimeter observations of the Sun, some important aspects require diagnostic capabilities that are not offered by existing observatories. In particular, simultaneously observations of the radiation continuum across an extended frequency range would facilitate the mapping of different layers and thus ultimately the 3D structure of the solar atmosphere. Mapping large regions on the Sun or even the whole solar disk at a very high temporal cadence would be crucial for systematically detecting and following the temporal evolution of flares, while synoptic observations, i.e., daily maps, over periods of years would provide an unprecedented view of the solar activity cycle in this wavelength regime. As our Sun is a fundamental reference for studying the atmospheres of active main sequence stars, observing the Sun and other stars with the same instrument would unlock the enormous diagnostic potential for understanding stellar activity and its impact on exoplanets. The Atacama Large Aperture Submillimeter Telescope (AtLAST), a single-dish telescope with 50\,m aperture proposed to be built in the Atacama desert in Chile, would be able to provide these observational capabilities. Equipped with a large number of detector elements for probing the radiation continuum across a wide frequency range, AtLAST would address a wide range of scientific topics including the thermal structure and heating of the solar chromosphere, flares and prominences, and the solar activity cycle. In this white paper, the key science cases and their technical requirements for AtLAST are discussed., Comment: 14 pages, 4 figures, submitted to Open Research Europe as part of a collection on the Atacama Large Aperture Submillimeter Telescope (AtLAST)