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The goal of Smithsonian Science for North and South Carolina Classrooms was to provide teachers with ongoing, differentiated professional development and research-based curricular materials to improve elementary student achievement in science, mathematics, and reading. This work used an inquiry-based science curriculum, Smithsonian Science for the Classroom, which is aligned with the Next Generation Science Standards (NGSS), and was implemented in Grades 3-5 within predominantly rural North and South Carolina school districts serving high-needs students. The Center for Research in Educational Policy (CREP) at the University of Memphis, a State of Tennessee Center of Excellence, was the independent third-party evaluator. CREP implemented a Randomized Controlled Trial (RCT) to collect and analyze data using a rigorous, mixed-methods approach, including quantitative analyses of student achievement data from the Stanford-10 and state assessments, and qualitative analyses of classroom observation data, as well as teacher feedback from professional development surveys, module logs, and focus groups. For this study, 36 schools (including one split cohort being treated as one school) in seven districts within North and South Carolina were randomly assigned to treatment and comparison groups. The study cohort, followed over three academic years (2020-21 through 2022-23), was composed of more than 1,600 third grade (2020-21) students in these schools. In the comparison condition, schools used their business-as-usual science curricula and teacher professional development and did not receive Smithsonian Science curricular materials or professional development. As the pretests for achievement outcomes, students took the Abbreviated Battery of the Stanford Achievement Test Series, Tenth Edition (Stanford-10) in Reading and Math in spring of 2021 (the cohort's third grade year). The main findings and posttests included the combined sample (i.e., both states combined) for (a) the Stanford-10 Science subtest, which was administered in the spring of 2023 (the cohort's fifth grade year), and (b) spring 2023 standardized state assessment scores in Reading and Math. Using a hierarchical linear model (HLM) with school as a random effect, the analysis of the effect of Smithsonian Science for the three main findings after several years of disruptions from the COVID-19 pandemic was (a) positive (g = 0.18) and statistically significant (p = 0.032) on the Stanford-10 science assessment and (b) positive for both Reading (g = 0.10) and Math (g = 0.16), meaning students in the treatment group performed better than the control group, but the effects were not statistically significant. Teachers were generally positive in terms of the professional development provided, and feedback on the module logs largely supported the effectiveness of the professional development and fidelity of implementation. Classroom observations further supported the effectiveness of the professional development and fidelity to inquiry-based practices in treatment classrooms (e.g., use of experiential hands-on learning and level of class time dedicated to inquiry-based science). With instructional time for science lagging other subject areas, and as learning recovery in reading and math after COVID-19 receive national attention, the results demonstrate that ongoing, differentiated, high-quality professional learning and high-quality instructional materials for science instruction can support student achievement in science, math, and reading.

Leveraging rich data on the universe of Texas high school graduates, we estimate how the relationship between geographic access to public two- and four-year postsecondary institutions and postsecondary outcomes varies across race-ethnicity and socioeconomic status. We find that students are sensitive to the distance they must travel to access public colleges and universities, but there are heterogeneous effects across students -- particularly with regard to distance to public two-year colleges (i.e., community colleges). White, Asian, and higher-income students who live in a community college desert (i.e., at least 30 minutes driving time from the nearest public two-year college) substitute towards four-year colleges and are more likely to complete bachelor's degrees. Meanwhile, Black, Hispanic, and lower-income students respond to living in a community college desert by forgoing college enrollment altogether, reducing the likelihood that they earn associate's and reducing the likelihood that they ultimately transfer to four-year colleges and earn bachelor's degrees. These relationships persist up to eight years following high school graduation, resulting in substantial long-term gaps in overall degree attainment by race-ethnicity and income in areas with limited postsecondary access.

K-dwarf stars are promising targets in the exploration of potentially habitable planets. Their properties, falling between G and M dwarfs, provide an optimal trade-off between the prospect of habitability and ease of detection. The KOBE experiment is a blind-search survey exploiting this niche, monitoring the radial velocity of 50 late-type K-dwarf stars. It employs the CARMENES spectrograph, with an observational strategy designed to detect planets in the habitable zone of their system. In this work, we exploit the KOBE data set to characterize planetary signals in the K7V star HIP 5957 (KOBE-1) and to constrain the planetary population within its habitable zone. We used 82 CARMENES spectra over a time span of three years. We employed a GLS periodogram to search for significant periodic signals that would be compatible with Keplerian motion on KOBE-1. We carried out a model comparison within a Bayesian framework to ensure the significance of the planetary model over alternative configurations of lower complexity. We also inspected two available TESS sectors in search of planetary signals. We identified two signals: at 8.5d and 29.7d. We confirmed their planetary nature through ruling out other non-planetary configurations. Their minimum masses are 8.80+/-0.76ME and 12.4+/-1.1ME, corresponding to absolute masses within the planetary regime at a high certainty (>99.7%). By analyzing the sensitivity of the CARMENES time series to additional signals, we discarded planets above 8.5ME within the habitable zone. We identified a single transit-like feature in TESS, whose origin is still uncertain, but still compatible within 1sigma with a transit from planet c. We have explored future prospects for characterizing this system, concluding that nulling interferometry with the LIFE mission could be capable of directly imaging both planets and characterizing their atmospheres in future studies., Comment: 29 pages, 21 figures, 10 tables, published in Astronomy & Astrophysics

Inference of sociodemographic attributes of social media users is an essential step for computational social science (CSS) research to link online and offline behavior. However, there is a lack of a systematic evaluation and clear guidelines for optimal methodologies for this task on Reddit, one of today's largest social media. In this study, we fill this gap by comparing state-of-the-art (SOTA) and probabilistic models. To this end, first we collect a novel data set of more than 850k self-declarations on age, gender, and partisan affiliation from Reddit comments. Then, we systematically compare alternatives to the widely used embedding-based model and labeling techniques for the definition of the ground-truth. We do so on two tasks: ($i$) predicting binary labels (classification); and ($ii$)~predicting the prevalence of a demographic class among a set of users (quantification). Our findings reveal that Naive Bayes models not only offer transparency and interpretability by design but also consistently outperform the SOTA. Specifically, they achieve an improvement in ROC AUC of up to $19\%$ and maintain a mean absolute error (MAE) below $15\%$ in quantification for large-scale data settings. Finally, we discuss best practices for researchers in CSS, emphasizing coverage, interpretability, reliability, and scalability. The code and model weights used for the experiments are publicly available.\footnote{https://anonymous.4open.science/r/SDI-submission-5234}

In this article, we consider an inverse problem involving the simultaneous reconstruction of two real valued potentials for a Schr\"odinger equation with mixed boundary conditions: a dynamic boundary condition of Wentzell type and a Dirichler boundary condition. The main result of this paper is a Lipschitz stability estimate for such potentials from a single measurement of the flux. This result is deduced using the Bukhgeim-Klibanov method and a suitable Carleman estimate where the weight function depends on Minkowski's functional.

Quantum computers create new security risks for today's encryption systems. This paper presents an improved version of the Advanced Encryption Standard (AES) that uses quantum technology to strengthen protection. Our approach offers two modes: a fully quantum-based method for maximum security and a hybrid version that works with existing infrastructure. The system generates encryption keys using quantum randomness instead of predictable computer algorithms, making keys virtually impossible to guess. It regularly refreshes these keys automatically to block long-term attacks, even as technology advances. Testing confirms the system works seamlessly with current security standards, maintaining fast performance for high-volume data transfers. The upgraded AES keeps its original security benefits while adding three key defenses: quantum-powered key creation, adjustable security settings for different threats, and safeguards against attacks that exploit device vulnerabilities. Organizations can implement this solution in stages--starting with hybrid mode for sensitive data while keeping older systems operational. This phased approach allows businesses to protect financial transactions, medical records, and communication networks today while preparing for more powerful quantum computers in the future. The design prioritizes easy adoption, requiring no costly replacements of existing hardware or software in most cases., Comment: 28 pages, 5 figures

Oscillations of atmospheric muon and electron neutrinos produce tau neutrinos with energies in the GeV range, which can be observed by the ORCA detector of the KM3NeT neutrino telescope in the Mediterranean Sea. First measurements with ORCA6, an early subarray corresponding to about 5$\%$ of the final detector, are presented. A sample of 5828 neutrino candidates has been selected from the analysed exposure of 433 kton-years. The $\nu_\tau$ normalisation, defined as the ratio between the number of observed and expected tau neutrino events, is measured to be $S_\tau = 0.48^{+0.5}_{-0.33}$. This translates into a $\nu_\tau$ charged-current cross section measurement of $\sigma_{\tau}^{\text{meas}} = (2.5 ^{+2.6}_{-1.8}) \times 10^{-38}$ cm$^{2}$ nucleon$^{-1}$ at the median $\nu_\tau$ energy of 20.3 GeV. The result is consistent with the measurements of other experiments. In addition, the current limit on the non-unitarity parameter affecting the $\tau$-row of the neutrino mixing matrix was improved, with $\alpha_{33}>$ 0.95 at the 95$\%$ confidence level., Comment: 25 pages, 8 figures

We study in detail the class of even polynomials and their behavior with respect to finite free convolutions. To this end, we use some specific hypergeometric polynomials and a variation of the rectangular finite free convolution to understand even real-rooted polynomials in terms of positive-rooted polynomials. Then, we study some classes of even polynomials that are of interest in finite free probability, such as even hypergeometric polynomials, symmetrizations, and finite free commutators. Specifically, we provide many new examples of these objects, involving classical families of special polynomials (such as Laguerre, Hermite, and Jacobi). Finally, we relate the limiting root distributions of sequences of even polynomials with the corresponding symmetric measures that arise in free probability., Comment: 37 pages

The gravitational waveform emitted by a particle moving in a Schwarzschild geometry can be computed, in perturbation theory, as a double series expansion in the limit where distances are large with respect to the size of the horizon, $z=2M/r\ll 1$ (Post-Minkowskian approximation), but small with respect to the gravitational wavelength, $y=2{\rm i} \omega r\ll 1$ (Post-Newtonian approximation). While in the case of bounded systems the two expansions are linked, for scattering processes they describe complementary regions of spacetime. In this paper, we derive all order formulae for those two expansions of the waveform, where the entire dependence on the $y$ or $z$ variables is resummed under the assumption $\omega M\ll 1$. The results are based on a novel hypergeometric representation of the confluent Heun functions and provide a new derivation of the recently discovered Heun connection formulae. Similar results are found for the non-confluent Heun case. Finally, in the case of circular orbits we compute our formulae at order 30PN and show excellent agreement against solutions obtained via numerical integrations and the MST method., Comment: 21 pages + Appendix + References, 2 Figures, 4 Tables; ancillary files are present, containing two Mathematica codes and relative data that are imported within them

Sub-Neptunes are the most common type of planet in our galaxy. Interior structure models suggest that the coldest sub-Neptunes could host liquid water oceans underneath their hydrogen envelopes - sometimes called 'hycean' planets. JWST transmission spectra of the $\sim$ 250 K sub-Neptune K2-18 b were recently used to report detections of CH$_4$ and CO$_2$, alongside weaker evidence of (CH$_3$)$_2$S (dimethyl sulfide, or DMS). Atmospheric CO$_2$ was interpreted as evidence for a liquid water ocean, while DMS was highlighted as a potential biomarker. However, these notable claims were derived using a single data reduction and retrieval modeling framework, which did not allow for standard robustness tests. Here we present a comprehensive reanalysis of K2-18 b's JWST NIRISS SOSS and NIRSpec G395H transmission spectra, including the first analysis of the second-order NIRISS SOSS data. We incorporate multiple well-tested data reduction pipelines and retrieval codes, spanning 60 different data treatments and over 250 atmospheric retrievals. We confirm the detection of CH$_4$ ($\approx$ 4$\sigma$), with a volume mixing ratio of log CH$_4$ = $-1.15^{+0.40}_{-0.52}$, but we find no statistically significant or reliable evidence for CO$_2$ or DMS. Finally, we quantify the observed atmospheric composition using photochemical-climate and interior models, demonstrating that our revised composition of K2-18 b can be explained by an oxygen-poor mini-Neptune without requiring a liquid water surface or life., Comment: 42 pages, 20 figures. Submitted to AAS Journals

We establish sufficient conditions for the density of shallow neural networks \cite{C89} on the family of continuous real functions defined on a compact metric space, taking into account variations in the function domains. For this we use the Gromov-Hausdorff distance defined in \cite{5G}., Comment: 10 pages

The proliferation of exoplanet discoveries in exotic environments like the Neptune desert challenges our understanding of planetary atmospheres under intense irradiation. The unexpected discovery of LTT9779 b, an ultra-hot Neptune within this desert, offers a prime opportunity for atmospheric studies. We build on prior observations of LTT9779 b from TESS, Spitzer, and CHEOPS, incorporating new VLT/ESPRESSO data to probe its atmospheric dynamics. Preliminary analyses suggest a metal-rich atmosphere and a high day-side geometric albedo, possibly indicating silicate clouds. Minimal atmospheric escape is observed, contrasting existing models of planetary evolution under extreme irradiation. We obtained the transmission spectrum of LTT9779 b between 0.4 and 0.78 microns with ESPRESSO, addressing systematics across three transits. Our analysis focused on the sodium doublet and H-alpha, using cross-correlation with models containing Na, K, FeH, TiO, and VO. No significant atmospheric signal was detected, with metallicity limits set at [Fe/H] $\geq$ 2.25 ($\geq$ 180 times solar). The non-detection aligns with a high-metallicity, cloud-free model, implying a high mean molecular weight and reduced atmospheric scale height. We interpret this as evidence for a metal-rich atmosphere with suppressed spectral features, possibly due to high-altitude clouds or hazes. These findings are consistent with JWST observations, supporting the hypothesis of metal-rich atmospheres obscured by aerosols in extreme environments., Comment: 12 pages, 11 figures, 3 tables, Accepted for publication in Astronomy and Astrophysics

We report on the properties of the two-dimensional electron gas in a dual-gate geometry, using quantum Monte Carlo methods to obtain aspects of the phase diagram as a function of electron density and gate distance. We identify the critical gate distance below which the Wigner crystal phase disappears. For larger gate distances, the system undergoes a re-entrant transition from crystal to liquid at sufficiently low density. We also present preliminary evidence for a fully polarized ferromagnetic liquid state at low electron density and intermediate gate distances. The quantum Monte Carlo results are compared with simpler approximate methods, which are shown to be semi-quantitatively reliable for determining key features of the phase diagram. These methods are then used to obtain the phase boundary between the Wigner crystal and liquid in the single-gate geometry., Comment: 4+4 pages

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

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

We present two transit observations of the $\sim$520K, 1.85R$_\oplus$, 4.0M$_\oplus$ super-Earth TOI-776b with JWST NIRSpec/G395H, resulting in a 2.8-5.2$\mu$m transmission spectrum. Producing reductions using the ExoTiC-JEDI and Eureka! pipelines, we obtain a median transit depth precision of 34ppm for both visits and both reductions in spectroscopic channels 30 pixels wide ($\sim$0.02$\mu$m). We find that our independent reductions produce consistent transmission spectra, however, each visit shows differing overall structure. For both reductions, a flat line is preferred for Visit 1 while a flat line with an offset between the NRS1 and NRS2 detectors is preferred for Visit 2; however, we are able to correct for this offset during our modeling analysis following methods outlined in previous literature. Using picaso forward models, we can rule out metallicities up to at least 100$\times$ solar with an opaque pressure of 10$^{-3}$ bar to $\geq$3$\sigma$ in all cases, however, the exact lower limit varies between the visits, with Visit 1 ruling out $\lesssim$100$\times$ solar while the lower limits for Visit 2 extend beyond $\sim$350$\times$ solar. Our results add to the growing list of super-Earth atmospheric constraints by JWST, which provide critical insight into the diversity and challenges of characterizing terrestrial planets., Comment: 17 pages, 7 figures, 4 tables. Accepted for publication in AJ. arXiv admin note: text overlap with arXiv:2404.00093

Neuromorphic engineering aims to incorporate the computational principles found in animal brains, into modern technological systems. Following this approach, in this work we propose a closed-loop neuromorphic control system for an event-based robotic arm. The proposed system consists of a shifted Winner-Take-All spiking network for interpolating a reference trajectory and a spiking comparator network responsible for controlling the flow continuity of the trajectory, which is fed back to the actual position of the robot. The comparator model is based on a differential position comparison neural network, which governs the execution of the next trajectory points to close the control loop between both components of the system. To evaluate the system, we implemented and deployed the model on a mixed-signal analog-digital neuromorphic platform, the DYNAP-SE2, to facilitate integration and communication with the ED-Scorbot robotic arm platform. Experimental results on one joint of the robot validate the use of this architecture and pave the way for future neuro-inspired control of the entire robot., Comment: 5 pages, 7 figures, conference, ISCAS 2025, accepted for publication, Spiking Neural Network

New observations obtained with JWST of the proto-stellar HH~270 jet and the "deflected" HH 110 system, show that HH 110 has a morphology of a series of distorted working surfaces. These working surfaces appear to be "deflected versions" of the heads of the incident, HH 270 jet. We compute a series of 3D numerical simulations, in which we explore the possible parameters of a shearing environment that could give origin to the deflection of HH 270 into the HH 110 flow. We find that we need a quite high sideways velocity for the streaming environment (of ~30km/s) in order to produce the complex structure observed in HH 110. This high velocity would be possible in an environment which has been strongly perturbed by the passage of other outflows., Comment: Accepted for publication in ApJ

This paper explores the application of tensor networks (TNs) to the simulation of material deformations within the framework of linear elasticity. Material simulations are essential computational tools extensively used in both academic research and industrial applications. TNs, originally developed in quantum mechanics, have recently shown promise in solving partial differential equations (PDEs) due to their potential for exponential speedups over classical algorithms. Our study successfully employs TNs to solve linear elasticity equations with billions of degrees of freedom, achieving exponential reductions in both memory usage and computational time. These results demonstrate the practical viability of TNs as a powerful classical backend for executing quantum-inspired algorithms with significant efficiency gains. This work is based on our research conducted with IKERLAN., Comment: 12 pages, 7 figures

Static analysis is an essential component of many modern software development tools. Unfortunately, the ever-increasing complexity of static analyzers makes their coding error-prone. Even analysis tools based on rigorous mathematical techniques, such as abstract interpretation, are not immune to bugs. Ensuring the correctness and reliability of software analyzers is critical if they are to be inserted in production compilers and development environments. While compiler validation has seen notable success, formal validation of static analysis tools remains relatively unexplored. In this paper, we propose a method for testing abstract interpretation-based static analyzers. Broadly, it consists in checking, over a suite of benchmarks, that the properties inferred statically are satisfied dynamically. The main advantage of our approach lies in its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We demonstrate that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: 1) the static analyzer, which outputs its results as the original program source with assertions interspersed; 2) the assertion run-time checking mechanism, which instruments a program to ensure that no assertion is violated at run time; 3) the random test case generator, which generates random test cases satisfying the properties present in assertion preconditions; and 4) the unit-test framework, which executes those test cases. We have applied our approach to the CiaoPP static analyzer, resulting in the identification of many bugs with reasonable overhead. Most of these bugs have been either fixed or confirmed, helping us detect a range of errors not only related to analysis soundness but also within other aspects of the framework., Comment: Under consideration in Theory and Practice of Logic Programming (TPLP). Extended, revised version of our work published in LOPSTR (Casso et al. 2021)

We present measurements of large-scale cosmic microwave background (CMB) E-mode polarization from the Cosmology Large Angular Scale Surveyor (CLASS) 90 GHz data. Using 115 det-yr of observations collected through 2024 with a variable-delay polarization modulator, we achieved a polarization sensitivity of $78\,\mathrm{\mu K\,arcmin}$, comparable to Planck at similar frequencies (100 and 143 GHz). The analysis demonstrates effective mitigation of systematic errors and addresses challenges to large-angular-scale power recovery posed by time-domain filtering in maximum-likelihood map-making. A novel implementation of the pixel-space transfer matrix is introduced, which enables efficient filtering simulations and bias correction in the power spectrum using the quadratic cross-spectrum estimator. Overall, we achieved an unbiased time-domain filtering correction to recover the largest angular scale polarization, with the only power deficit, arising from map-making non-linearity, being characterized as less than $3\%$. Through cross-correlation with Planck, we detected the cosmic reionization at $99.4\%$ significance and measured the reionization optical depth $\tau=0.053^{+0.018}_{-0.019}$, marking the first ground-based attempt at such a measurement. At intermediate angular scales ($\ell>30$), our results, both independently and in cross-correlation with Planck, remain fully consistent with Planck's measurements., Comment: 24 pages, 19 figures, 3 tables; submitted to ApJ

Context. Supernova remnants are one potential source class considered a PeVatron (i.e. capable of accelerating cosmic rays above PeV energies). The shock fronts produced after the explosion of the supernova are ideal regions for particle acceleration. IC 443 is a supernova remnant that has been studied extensively at different wavelengths. We study this region using very-high-energy gamma-ray data. Aims. We explore the region of IC 443 using 2966 days of gamma-ray data from the HAWC observatory. We study the emission of this supernova remnant and search for signatures that would show acceleration of (hadronic) cosmic rays at the PeV range. Methods. We use the maximum likelihood estimation and a likelihood ratio test to perform a multi-source fitting search. We find the best-fit morphology and spectrum of the IC 443 region above $\sim$300 GeV that best describes the HAWC data. Results. We observe a point source located at ($\alpha$=94.42$^{\circ}$, $\delta$=22.35$^{\circ}$) that we associate with IC 443. The measured spectrum is a simple power law with an index of -3.14$\pm$0.18, which is consistent with previous TeV observations. We also find a new extended component in the region whose emission is described by a simple power law with an index of -2.49$\pm$0.08 and which we call HAWC J0615+2213. Conclusions. Although we cannot confirm that IC 443 is a hadronic PeVatron, we do not find any sign that the spectrum has a cut off at tens of TeV energies, with the spectrum extending to $\sim$30 TeV. Furthermore, we find a new extended source in the region. While we show evidence that this new source might be a new TeV halo, we defer a detailed analysis of this new source to another publication.

In the era of precision measurements of neutrino oscillation parameters, it is necessary for experiments to disentangle discrepancies that may indicate physics beyond the Standard Model in the neutrino sector. 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 the oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on the initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photosensors. A high-purity neutrino sample was extracted during 2020 and 2021, corresponding to an exposure of 433 kton-years. This sample is analysed following a binned log-likelihood approach to search for invisible neutrino decay, in a three-flavour neutrino oscillation scenario, where the third neutrino mass state $\nu_3$ decays into an invisible state, e.g. a sterile neutrino. The resulting best fit of the invisible neutrino decay parameter is $\alpha_3 = 0.92^{+1.08}_{-0.57}\times 10^{-4}~\mathrm{eV^2}$, corresponding to a scenario with $\theta_{23}$ in the second octant and normal neutrino mass ordering. The results are consistent with the Standard Model, within a $2.1\,\sigma$ interval., Comment: 20 pages, 8 figures

This work introduces SMARTe-VR, a platform for student monitoring in an immersive virtual reality environment designed for online education. SMARTe-VR is aimed to gather data for adaptive learning, focusing on facial biometrics and learning metadata. The platform allows instructors to create tailored learning sessions with video lectures, featuring an interface with an Auto QA system to evaluate understanding, interaction tools (e.g., textbook highlighting and lecture tagging), and real-time feedback. Additionally, we release a dataset containing 5 research challenges with data from 10 users in VR-based TOEIC sessions. This dataset, spanning over 25 hours, includes facial features, learning metadata, 450 responses, question difficulty levels, concept tags, and understanding labels. Alongside the database, we present preliminary experiments using Item Response Theory models, adapted for understanding detection using facial features. Two architectures were explored: a Temporal Convolutional Network for local features and a Multilayer Perceptron for global features., Comment: Published in the Workshop on Artificial Intelligence for Education (AI4EDU) at AAAI 2025

An important effort is currently underway to extend optical cycling and laser cooling to more molecular species. Significant challenges arise in particular when multiple nuclear spins give rise to complex, resolved hyperfine spectra, as is the case for several molecular species relevant to precision tests of fundamental symmetries. We provide a detailed introduction to the use of optical spectra generated via serrodyne waveforms to address this complexity. We discuss our experimental implementation of these serrodynes, characterize their properties, and outline procedures to find optimized sideband configurations that generate strong laser cooling forces. We demonstrate the application of these techniques to barium monofluoride molecules and explore their prospects for the cooling of other species relevant to the study of fundamental physics., Comment: 9 pages + appendix, 9 figures

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

The physical and orbital parameters of Trans-Neptunian Objects (TNOs) provide valuable information about the Solar System's formation and evolution. In particular, the characterization of binaries provides insights into the formation mechanisms that may be playing a role at such large distances from the Sun. Studies show two distinct populations, and (38628) Huya occupies an intermediate position between the unequal-size binaries and those with components of roughly equal sizes. In this work, we predicted and observed three stellar occultation events by Huya. Huya and its satellite - S/2012 (38628) 1 - were detected during occultations in March 2021 and again in June 2023. Additionally, an attempt to detect Huya in February 2023 resulted in an additional single-chord detection of the secondary. A spherical body with a minimum diameter of D = 165 km can explain the three single-chord observations and provide a lower limit for the satellite size. The astrometry of Huya's system, as derived from the occultations and supplemented by observations from the Hubble Space Telescope and Keck Observatory, provided constraints on the satellite orbit and the mass of the system. Therefore, assuming the secondary is in an equatorial orbit around the primary, the limb fitting was constrained by the satellite orbit position angle. The system density, calculated by summing the most precise measurement of Huya's volume to the spherical satellite average volume, is $\rho_{1}$ = 1073 $\pm$ 66 kg m$^{-3}$. The density that the object would have assuming a Maclaurin equilibrium shape with a rotational period of 6.725 $\pm$ 0.01 hours is $\rho_{2}$ = 768 $\pm$ 42 kg m$^{-3}$. This difference rules out the Maclaurin equilibrium assumption for the main body shape., Comment: Manuscript accepted by Planetary Science Journal (PSJ)

Peer-to-peer energy trading platforms enable direct electricity exchanges between peers who belong to the same energy community. In a semi-decentralized system, a community manager adheres to grid restrictions while optimizing social welfare. However, with no further supervision, some peers can be discriminated against from participating in the electricity trades. To solve this issue, this paper proposes an optimization-based mechanism to enable distributionally fair peer-to-peer electricity trading. For the implementation of our mechanism, peers are grouped by energy poverty level. The proposed model aims to redistribute the electricity trades to minimize the maximum Wasserstein distance among the transaction distributions linked to the groups while limiting the sacrifice level with a predefined parameter. We demonstrate the effectiveness of our proposal using the IEEE 33-bus distribution grid, simulating an energy community with 1600 peers. Results indicate that up to 70.1% of unfairness can be eliminated by using our proposed model, even achieving a full elimination when including a non-profit community photovoltaic plant.

In this work, we study the $\Xi_c$ baryon electromagnetic decay widths within the constituent quark model formalism through an analysis of the transitions from $P-$wave states to ground states. We use the non-relativistic limit of the Hamiltonian of the electromagnetic interaction on keeping all the terms up to the order $m_j^{-1}$. We calculate the electromagnetic decay widths analytically, for the first time, without any further approximation. Specifically, our theoretical results for the $\Xi_c(2790)^{+/0}$ and $\Xi_c(2815)^{+/0}$ radiative decay widths, without the introduction of any additional parameters, display a significant agreement with the recent experimental values obtained by the Belle experiment. The agreement is due to the fact that we have not introduced further approximation to simplify the calculation of the difficult convective term, unlike what was done in previous studies. Our predictions may be useful for future experiments at the Belle, BABAR, and LHC experiments., Comment: 5 pages

When dealing with shallow water simulations, the velocity profile is often assumed to be constant along the vertical axis. However, since in many applications this is not the case, modeling errors can be significant. Hence, in this work, we deal with the Shallow Water Linearized Moment Equations (SWLME), in which the velocity is no longer constant in the vertical direction, where a polynomial expansion around the mean value is considered. The linearized version implies neglecting the non-linear terms of the basis coefficients in the higher order equations. As a result, the model is always hyperbolic and the stationary solutions can be more easily computed. Then, our objective is to propose an efficient, accurate and robust numerical scheme for the SWLME model, specially adapted for low Froude number situations. Hence, we describe a semi-implicit second order exactly fully well-balanced method. More specifically, a splitting is performed to separate acoustic and material phenomena. The acoustic waves are treated in an implicit manner to gain in efficiency when dealing with subsonic flow regimes, whereas the second order of accuracy is achieved thanks to a polynomial reconstruction and Strang-splitting method. We also exploit a reconstruction operator to achieve the fully well-balanced character of the method. Extensive numerical tests demonstrate the well-balanced properties and large speed-up compared to traditional methods.

Synthetic control (SC) methods are widely used to evaluate the impact of policy interventions, particularly those targeting specific geographic areas or regions, commonly referred to as units. These methods construct an artificial (synthetic) unit from untreated (control) units, intended to mirror the characteristics of the treated region had the intervention not occurred. While neighboring areas are often chosen as controls due to their assumed similarities with the treated, their proximity can introduce spillovers, where the intervention indirectly affects these controls, biasing the estimates. To address this challenge, we propose a Bayesian SC method with distance-based shrinkage priors, designed to estimate causal effects while accounting for spillovers. Modifying traditional penalization techniques, our approach incorporates a weighted distance function that considers both covariate information and spatial proximity to the treated. Rather than simply excluding nearby controls, this framework data-adaptively selects those less likely to be impacted by spillovers, providing a balance between bias and variance reduction. Through simulation studies, we demonstrate the finite-sample properties of our method under varying levels of spillover. We then apply this approach to evaluate the impact of Philadelphia's beverage tax on the sales of sugar-sweetened and artificially sweetened beverages in mass merchandise stores.

The discovery of high-temperature superconductivity in bulk La$_3$Ni$_2$O$_7$ under high hydrostatic pressure and, more recently, biaxial compression in epitaxial thin films has ignited significant interest in understanding the interplay between atomic and electronic structure in these compounds. Subtle changes in the nickel-oxygen bonding environment are thought to be key drivers for stabilizing superconductivity, but specific details of which bonds and which modifications are most relevant remains so far unresolved. While direct, atomic-scale structural characterization under hydrostatic pressure is beyond current experimental capabilities, static stabilization of strained La$_3$Ni$_2$O$_7$ films provides a platform well-suited to investigation with new picometer-resolution electron microscopy methods. Here, we use multislice electron ptychography to directly measure the atomic-scale structural evolution of La$_3$Ni$_2$O$_7$ thin films across a wide range of biaxial strains tuned via substrate. By resolving both the cation and oxygen sublattices, we study strain-dependent evolution of atomic bonds, providing the opportunity to isolate and disentangle the effects of specific structural motifs for stabilizing superconductivity. We identify the lifting of crystalline symmetry through modification of the nickel-oxygen octahedral distortions under compressive strain as a key structural ingredient for superconductivity. Rather than previously supposed $c$-axis compression, our results highlight the importance of in-plane biaxial compression in superconducting thin films, which suggests an alternative -- possibly cuprate-like -- understanding of the electronic structure. Identifying local regions of inhomogeneous oxygen stoichiometry and high internal strain near crystalline defects, we suggest potential pathways for improving the sharpness and temperature of the superconducting transition., Comment: 4 figures, 3 tables, 15 supplemental figures

Introduced with the advent of statistical wireless channel models for high mobility communications and having a profound role in communication-centric (CC) integrated sensing and communications (ISAC), the doubly-dispersive (DD) channel structure has long been heralded as a useful tool enabling the capture of the most important fading effects undergone by an arbitrary time-domain transmit signal propagating through some medium. However, the incorporation of this model into multiple-input multiple-output (MIMO) system setups, relying on the recent paradigm-shifting transceiver architecture based on stacked intelligent metasurfaces (SIM), in an environment with reconfigurable intelligent surfaces (RISs) remains an open problem due to the many intricate details that have to be accounted for. In this paper, we fill this gap by introducing a novel DD MIMO channel model that incorporates an arbitrary number of RISs in the ambient, as well as SIMs equipping both the transmitter and receiver. We then discuss how the proposed metasurfaces-parametrized DD (MPDD) channel model can be seamlessly applied to waveforms that are known to perform well in DD environments, namely, orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), and affine frequency division multiplexing (AFDM), with each having their own inherent advantages and disadvantages. An illustrative application of the programmable functionality of the proposed model is finally presented to showcase its potential for boosting the performance of the aforementioned waveforms. Our numerical results indicate that the design of waveforms suitable to mitigating the effects of DD channels is significantly impacted by the emerging SIM technology., Comment: Submitted to an IEEE journal for possible publication

Predicting dynamic behaviors is one of the goals of science in general as well as essential to many specific applications of human knowledge to real world systems. Here we introduce an analytic approach using the sigmoid growth curve to model the dynamics of individual entities within complex systems. Despite the challenges posed by nonlinearity and unpredictability in system behaviors, we demonstrate the applicability of the sigmoid curve to capture the acceleration and deceleration of growth, predicting an entitys ultimate state well in advance of reaching it. We show that our analysis can be applied to diverse systems where entities exhibit nonlinear growth using case studies of (1) customer purchasing and (2) U.S. legislation adoption. This showcases the ability to forecast months to years ahead of time, providing valuable insights for business leaders and policymakers. Moreover, our characterization of individual component dynamics offers a framework to reveal the aggregate behavior of the entire system. We introduce a classification of entities based upon similar lifepaths. This study contributes to the understanding of complex system behaviors, offering a practical tool for prediction and system behavior insight that can inform strategic decision making in multiple domains.

We examine how social media users from eight European Union (EU) member states express their socio-political identities, focusing on users' online self-presentation and group identity cues conveyed through bios. Our goal is to explore commonalities and differences in topics discussed in social media profiles, across Left-and Right-wing user groups, within and across EU countries. Through a novel approach we map how identity-related discourse varies by country and political orientation, revealing how group identity is expressed within the EU. We find that topics related to democracy, national way of life, and decentralization emerge as particularly divisive, showing considerable variation both within and between EU countries. A subset of topics, which includes education, environmentalism, sustainability, equality, freedom & human rights, and traditional morality, among others, clearly differentiate Left-from Right-leaning user groups. These partisan topics are relevant as they could be leveraged for mobilizing ideological groups and highlight Left-Right identitarian differences at the EU level. Finally, we show that our Left-Right identity similarity metrics reflect aspects of real-world political fragmentation, which are closely aligned to the perceptions of political conflict intensity by country, as measured by the 2022 PEW survey.

This R\&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines., Comment: proceedings for 42nd International Conference on High Energy Physics (ICHEP2024), 18-24 July 2024, Prague, Czech Republic

We present the Cosmic Evolution Early Release Science (CEERS) Survey, a 77.2 hour Director's Discretionary Early Release Science Program. CEERS demonstrates, tests, and validates efficient extragalactic surveys using coordinated, overlapping parallel observations with the JWST instrument suite, including NIRCam and MIRI imaging, NIRSpec low (R~100) and medium (R~1000) resolution spectroscopy, and NIRCam slitless grism (R~1500) spectroscopy. CEERS targets the Hubble Space Telescope-observed region of the Extended Groth Strip (EGS) field, supported by a rich set of multiwavelength data. CEERS facilitated immediate community science in both of the extragalactic core JWST science drivers ``First Light" and ``Galaxy Assembly," including: 1) The discovery and characterization of large samples of galaxies at z >~ 10 from ~90 arcmin^2 of NIRCam imaging, constraining their abundance and physical nature; 2) Deep spectra of >1000 galaxies, including dozens of galaxies at 63; and 4) Characterizing galaxy mid-IR emission with MIRI to study dust-obscured star-formation and supermassive black hole growth at z~1-3. As a legacy product for the community, the CEERS team has provided several data releases, accompanied by detailed notes on the data reduction procedures and notebooks to aid in reproducibility. In addition to an overview of the survey and quality of the data, we provide science highlights from the first two years with CEERS data., Comment: 38 pages, 13 figures, 6 tables

The metallic delafossites host ultra-high mobility carriers in the bulk, while at their polar surfaces, intrinsic electronic reconstructions stabilise markedly distinct electronic phases, from charge-disproportionated insulators, to Rashba-split heavy-hole gases and ferromagnetic metals. The understanding of these phases has been strongly informed by surface spectroscopic measurements, but previous studies have been complicated by the presence of spatially varying terminations of the material surface. Here, we demonstrate the potential of microscopic-area angle-resolved photoemission to overcome these challenges. Our measurements of the model compound PdCoO$_2$ yield extremely high-quality spectra of the electronic structure, which allows us to place new experimental constraints on the weak electron-phonon coupling in the bulk of PdCoO$_2$, while revealing much stronger interactions at its surfaces. While the CoO$_2$-terminated surface exhibits a conventional weak-coupling behavior, our measurements reveal surprising spectroscopic signatures of polaron formation at the Pd-terminated surface, despite its pronounced metallicity. Together, our findings reveal how mode and symmetry-selective couplings can markedly tune the electron-phonon interactions in a single host material, here opening routes to stabilise surprisingly persistent polaronic quasiparticles., Comment: 17 pages including supplementary information

In this work we introduce a criterion for testing general covariance in effective quantum gravity theories. It adapts the criterion based on general spacetime diffeomorphisms of the Einstein-Hilbert action to the case of effective canonical models. While the main purpose is to test models obtained in Loop Quantum Gravity, the criterion is not limited to those physical systems and may be applied to any canonically formulated modified theory of gravity. The approach here is hence not that of finding an effective model, but rather to analyze a given one represented by a quantum corrected Hamiltonian. Specifically, we will apply the criterion to spherically symmetric spacetimes in the vacuum with inverse triad and holonomy modifications that arise as a consequence of the loop quantization procedure. It is found that, in addition to the initial modifications of the Hamiltonian, quantum corrections of the classical metric itself are needed as well in order to obtain generally covariant models. A comparison with a recent alternative criterion is included in the discussion., Comment: 19 pages

This work presents Kinodynamic Adaptive Robot Coordination (K-ARC), a novel algorithm for multi-robot kinodynamic planning. Our experimental results show the capability of K-ARC to plan for up to 32 planar mobile robots, while achieving up to an order of magnitude of speed-up compared to previous methods in various scenarios. K-ARC is able to achieve this due to its two main properties. First, K-ARC constructs its solution iteratively by planning in segments, where initial kinodynamic paths are found through optimization-based approaches and the inter-robot conflicts are resolved through sampling-based approaches. The interleaving use of sampling-based and optimization-based approaches allows K-ARC to leverage the strengths of both approaches in different sections of the planning process where one is more suited than the other, while previous methods tend to emphasize on one over the other. Second, K-ARC builds on a previously proposed multi-robot motion planning framework, Adaptive Robot Coordination (ARC), and inherits its strength of focusing on coordination between robots only when needed, saving computation efforts. We show how the combination of these two properties allows K-ARC to achieve overall better performance in our simulated experiments with increasing numbers of robots, increasing degrees of problem difficulties, and increasing complexities of robot dynamics.

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

This Letter reports the precise measurement of reactor antineutrino spectrum and flux based on the full data set of 4.7 million inverse-beta-decay (IBD) candidates collected at Daya Bay near detectors. Expressed in terms of the IBD yield per fission, the antineutrino spectra from all reactor fissile isotopes and the specific $\mathrm{^{235}U}$ and $\mathrm{^{239}Pu}$ isotopes are measured with 1.3$\%$, 3$\%$ and 8$\%$ uncertainties respectively near the 3 MeV spectrum peak in reconstructed energy, reaching the best precision in the world. The total antineutrino flux and isotopic $\mathrm{^{235}U}$ and $\mathrm{^{239}Pu}$ fluxes are precisely measured to be $5.84\pm0.07$, $6.16\pm0.12$ and $4.16\pm0.21$ in units of $10^{-43} \mathrm{cm^2/fission}$. These measurements are compared with the Huber-Mueller (HM) model, the reevaluated conversion model based on the Kurchatov Institute (KI) measurement and the latest Summation Model (SM2023). The Daya Bay flux shows good consistency with KI and SM2023 models, but disagrees with HM model. The Daya Bay spectrum, however, disagrees with all model predictions.

We provide new connections between multitype $\Lambda$-coalescents and multitype continuous state branching processes via duality and a homeomorphism on their parameter space. The approach is based on a sequential sampling procedure for the frequency process of independent CSBPs, and provides forward and backward processes for multitype population models under $\Lambda$-type reproduction. It provides some insight on different approaches to generalise $\Lambda$-coalescents to the multitype setup.

This article presents the Keystroke Verification Challenge - onGoing (KVC-onGoing), on which researchers can easily benchmark their systems in a common platform using large-scale public databases, the Aalto University Keystroke databases, and a standard experimental protocol. The keystroke data consist of tweet-long sequences of variable transcript text from over 185,000 subjects, acquired through desktop and mobile keyboards simulating real-life conditions. The results on the evaluation set of KVC-onGoing have proved the high discriminative power of keystroke dynamics, reaching values as low as 3.33% of Equal Error Rate (EER) and 11.96% of False Non-Match Rate (FNMR) @1% False Match Rate (FMR) in the desktop scenario, and 3.61% of EER and 17.44% of FNMR @1% at FMR in the mobile scenario, significantly improving previous state-of-the-art results. Concerning demographic fairness, the analyzed scores reflect the subjects' age and gender to various extents, not negligible in a few cases. The framework runs on CodaLab., Comment: arXiv admin note: substantial text overlap with arXiv:2401.16559, arXiv:2311.06000

This work reflects on mechanics as an epistemological framework on the state of a physical system to regard dynamics as the distribution of mechanical properties over spacetime coordinates. The resulting distribution is taken to be the partition function of the relevant physical quantities over a space-time parametrized by coordinates. The partition yields a probabilistic interpretation that, based on Feynman's path integral formulation, leads to a dynamical law that generalizes the Schr\"odinger equation. A variety of systems can be put into the form proposed here, including particles in potentials, as well as matter and interaction fields. The main advantage of the proposed framework is that it presents the space of properties separately from that of the space of coordinates, whereas the dynamical law can be interpreted as the equation of two differential structures, one from each of these spaces. The resulting framework shows possibilities to further study physical quantities that relate directly to the space-time coordinates, whose dynamics is best described in thermodynamical, rather than Hamiltonian, terms. A notable case being the theory of general relativity.

We perform extensive simulations of the two-dimensional cavity-coupled electron gas in a modulating potential as a minimal model for cavity quantum materials. These simulations are enabled by a newly developed quantum-electrodynamical (QED) auxiliary-field quantum Monte Carlo method. We present a procedure to greatly reduce finite-size effects in such calculations. Based on our results, we show that a modified version of weak-coupling perturbation theory is remarkably accurate for a large parameter region. We further provide a simple parameterization of the light-matter correlation energy as a functional of the cavity parameters and the electronic density. These results provide a numerical foundation for the development of the QED density functional theory, which was previously reliant on analytical approximations, to allow quantitative modeling of a wide range of systems with light-matter coupling., Comment: 6 pages, 3 figures

For molecules and solids, we developed efficient MPI-parallel algorithms for evaluating the second-order exchange term with bare, statically screened, and dynamically screened interactions. We employ the resulting term in a fully self-consistent manner together with scGW, resulting in the following vertex-corrected scGW schemes: scGWSOX, scGWSOSEX, scGW2SOSEX, and scG3W2theories. We show that for the vertex evaluation, the reduction of scaling by tensor hypercontraction (THC) has two limiting execution regimes. We used the resulting code to perform the largest (by the number of orbitals) fully self-consistent calculations with the SOX term. We demonstrate that our procedure allows for a reliable evaluation of even small energy differences. Utilizing a broken-symmetry approach, we explore the influence of the SOX term on the effective magnetic exchange couplings. We show that the treatment of SOX has a significant impact on the obtained values of the effective exchange constants, which we explain through a self-energy dependence on an effective dielectric constant. We confirm this explanation by analyzing natural orbitals and local changes in charge transfer quantifying superexchange. Our analysis explains the structure of weak electron correlation responsible for the modulation of superexchange in both molecules and solids. Finally, for solids, we evaluate Neel temperatures utilizing the high-temperature expansion and compare the results obtained with experimental measurements.

Stellar surface heterogeneities, such as spots and faculae, often contaminate exoplanet transit spectra, hindering precise atmospheric characterization. We demonstrate a novel, epoch-based, model-independent method to mitigate stellar contamination, applicable to multi-planet systems with at least one airless planet. We apply this method using quasi-simultaneous transits of TRAPPIST-1 b and TRAPPIST-1 c observed on July 9, 2024, with JWST NIRSpec PRISM. These two planets, with nearly identical radii and impact parameters, are likely either bare rocks or possess thin, low-pressure atmospheres, making them ideal candidates for this technique, as variations in their transit spectra would be primarily attributed to stellar activity. Our observations reveal their transit spectra exhibit consistent features, indicating similar levels of stellar contamination. We use TRAPPIST-1 b to correct the transit spectrum of TRAPPIST-1 c, achieving a 2.5x reduction in stellar contamination at shorter wavelengths. At longer wavelengths, lower SNR prevents clear detection of contamination or full assessment of mitigation. Still, out-of-transit analysis reveals variations across the spectrum, suggesting contamination extends into the longer wavelengths. Based on the success of the correction at shorter wavelengths, we argue that contamination is also reduced at longer wavelengths to a similar extent. This shifts the challenge of detecting atmospheric features to a predominantly white noise issue, which can be addressed by stacking observations. This method enables epoch-specific stellar contamination corrections, allowing co-addition of planetary spectra for reliable searches of secondary atmospheres with signals of 60-250 ppm. Additionally, we identify small-scale cold (2000 K) and warm (2600 K) regions almost uniformly distributed on TRAPPIST-1, with overall covering fractions varying by 0.1% per hour., Comment: Resubmitted to ApJL after addressing reviewer comments

The NAHU$^2$ project is a Franco-Mexican collaboration aimed at building the $\pi$-YALLI corpus adapted to machine learning, which will subsequently be used to develop computer resources for the Nahuatl language. Nahuatl is a language with few computational resources, even though it is a living language spoken by around 2 million people. We have decided to build $\pi$-YALLI, a corpus that will enable to carry out research on Nahuatl in order to develop Language Models (LM), whether dynamic or not, which will make it possible to in turn enable the development of Natural Language Processing (NLP) tools such as: a) a grapheme unifier, b) a word segmenter, c) a POS grammatical analyser, d) a content-based Automatic Text Summarization; and possibly, e) a translator translator (probabilistic or learning-based)., Comment: 9 pages, in French language, 2 figures