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Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human-machine interfacing. However, technologies used to directly measure CNS activity are limited by their resolution, sensitivity to interferences, and invasiveness. Advances in muscle recordings and deep learning allow us to decode the spiking activity of spinal motor neurons (MNs) in real time and with high accuracy. MNs represent the motor output layer of the CNS, receiving and sampling signals originating in different regions in the nervous system, and generating the neural commands that control muscles. The input signals to MNs can be estimated from the MN outputs. Here we argue that peripheral neural interfaces using muscle sensors represent a promising, non-invasive approach to estimate some neural activity from the CNS that reaches the MNs but does not directly modulate force production. We also discuss the evidence supporting this concept, and the necessary advances to consolidate and test MN-based CNS interfaces in controlled and real-world settings.

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

Decoding nervous system activity is a key challenge in neuroscience and neural interfacing. In this study, we propose a novel neural decoding system that enables unprecedented large-scale sampling of muscle activity. Using micro-electrode arrays with more than 100 channels embedded within the forearm muscles, we recorded high-density signals that captured multi-unit motor neuron activity. This extensive sampling was complemented by advanced methods for neural decomposition, analysis, and classification, allowing us to accurately detect and interpret the spiking activity of spinal motor neurons that innervate hand muscles. We evaluated this system in two healthy participants, each implanted with three electromyogram (EMG) micro-electrode arrays (comprising 40 electrodes each) in the forearm. These arrays recorded muscle activity during both single- and multi-digit isometric contractions. For the first time under controlled conditions, we demonstrate that multi-digit tasks elicit unique patterns of motor neuron recruitment specific to each task, rather than employing combinations of recruitment patterns from single-digit tasks. This observation led us to hypothesize that hand tasks could be classified with high precision based on the decoded neural activity. We achieved perfect classification accuracy (100%) across 12 distinct single- and multi-digit tasks, and consistently high accuracy (>96\%) across all conditions and subjects, for up to 16 task classes. These results significantly outperformed conventional EMG classification methods. The exceptional performance of this system paves the way for developing advanced neural interfaces based on invasive high-density EMG technology. This innovation could greatly enhance human-computer interaction and lead to substantial improvements in assistive technologies, offering new possibilities for restoring motor function in clinical applications.

The long-term solar magnetic activity and its cyclical behaviour, which is maintained by a dynamo mechanism, are both still challenging for the astrophysics. In particular, an atypical event occurred between 1645 and 1715 when the solar activity was remarkably decreased and the number of sunspots got extremely reduced. However, it is still unclear what happened to the solar cycle. The discovery of longer activity minima in cool stars may shed light on the nature of the complex mechanisms involved in the long-term behaviour of the solar-stellar dynamo. Our aim is to explore if the G5V solar-like star HD 4915, which showed a striking chromospheric activity pattern in a previous study performed with HIRES data, could be considered a bona fide Maunder Minimum (hereafter MM) candidate. We have analyzed over 380 spectra acquired between 2003 and 2022 using HARPS and HIRES spectrographs. We carried out a detailed search of activity signatures in HD 4915 by using the Mount Wilson and the Balmer H$_{\alpha}$ activity indexes. This task was performed by means of the GLS periodogram. The new HARPS data show that the chromospheric activity of HD 4915 is not decreasing. In fact, the rise of the activity after the broad minimum in three years gets to the level of activity before that phase, suggesting that it is not entering into a MM phase. HD 4915 shows a distinctive activity behaviour initially attributed to a possible and incipient MM phase. The additional HARPS data allow us to discard a MM in the star. Our analysis shows that the complex activity pattern of HD 4915 could be ruled by a multiple activity cycle, being a shorter cycle of 4.8-yr modulated by a potential longer one. More activity surveys with extensive records and suitable cadence are crucial for accurate identification of stars in Magnetic Grand Minima., Comment: (5 pages, 4 figures)

Strategies aimed at reducing the negative effects of long-term uncertainty and risk are common in biology, game theory, and finance, even if they entail a cost in terms of mean benefit. Here, we focus on the single mutant's invasion of a finite resident population subject to fluctuating environmental conditions. Thus, the game-theoretical model we analyze integrates environmental and demographic randomness, i.e., the two leading sources of stochasticity and uncertainty. We use simulations and mathematical analysis to study if and when strategies that either increase or reduce payoff variance across environmental states can enhance the mutant fixation probability. Variance aversion implies that the mutant pays insurance in terms of mean payoff to avoid worst-case scenarios. Variance-prone or gambling strategies, on the other hand, entail specialization, allowing the mutant to capitalize on transient favorable conditions, leading to a series of ``boom-and-bust'' cycles. Our analyses elucidate how the rate of change of environmental conditions and the shape of the probability distribution of possible states affect the possible most convenient strategies. We discuss how our results relate to the bet-hedging theory, which aims to reduce fitness variance rather than payoff variance. We also describe the analogies and differences between these similar yet distinct approaches.

The challenge of imaging low-density objects in an electron microscope without causing beam damage is significant in modern TEM. This is especially true for life science imaging, where the sample, rather than the instrument, still determines the resolution limit. Here, we explore whether we have to accept this or can progress further in this area. To do this, we use numerical simulations to see how much information we can obtain from a weak phase object at different electron doses. Starting from a model with four phase values, we compare Zernike phase contrast with measuring diffracted intensity under multiple random phase illuminations to solve the inverse problem. Our simulations have shown that diffraction-based methods perform better than the Zernike method, as we have found and addressed a normalization issue that, in some other studies, led to an overly optimistic representation of the Zernike setup. We further validated this using more realistic 2D objects and found that random phase illuminated diffraction can be up to five times more efficient than an ideal Zernike implementation. These findings suggest that diffraction-based methods could be a promising approach for imaging beam-sensitive materials and that current low-dose imaging methods are not yet at the quantum limit., Comment: 25 pages, 7 figures

In this paper, we present ASPEN, an answer set programming (ASP) implementation of a recently proposed declarative framework for collective entity resolution (ER). While an ASP encoding had been previously suggested, several practical issues had been neglected, most notably, the question of how to efficiently compute the (externally defined) similarity facts that are used in rule bodies. This leads us to propose new variants of the encodings (including Datalog approximations) and show how to employ different functionalities of ASP solvers to compute (maximal) solutions, and (approximations of) the sets of possible and certain merges. A comprehensive experimental evaluation of ASPEN on real-world datasets shows that the approach is promising, achieving high accuracy in real-life ER scenarios. Our experiments also yield useful insights into the relative merits of different types of (approximate) ER solutions, the impact of recursion, and factors influencing performance., Comment: Extended version of a paper accepted at KR 2024

Generalized disjunctive programming (GDP) models with bilinear and concave constraints, often seen in water network design, are challenging optimization problems. This work proposes quadratic and piecewise linear approximations for nonlinear terms to reformulate GDP models into quadratic GDP (QGDP) models that suitable solvers may solve more efficiently. We illustrate the benefits of the quadratic reformulation with a water treatment network design problem in which nonconvexities arise from bilinear terms in the mixers' mass balances and concave investment cost functions of treatment units. Given the similarities with water network design problems, we suggest quadratic approximation for the GDP model for the optimal design of a large-scale reverse electrodialysis (RED) process. This power technology can recover energy from salinity differences between by-product streams of the water sector, such as desalination brine mixed with regenerated wastewater effluents. The solver Gurobi excels in handling QGDP problems, but weighing the problem's precision and tractability balance is crucial. The piecewise linear approximation yields more accurate, yet larger QGDP models that may require longer optimization times in large-scale process synthesis problems., Comment: 7 pages, Proceedings of the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering (ESCAPE34/PSE24), June 2-6, 2024, Florence, Italy

The virtualization of cultural events in the metaverse creates opportunities to generate valuable and innovative experiences that replicate and extend in-person events; but the process faces associated challenges. In the absence of relevant empirical studies, the aim of this article is to analyze the positive and negative aspects of the user experience in a cultural event held in the metaverse. A mixed-methods approach is employed to test the proposed hypotheses. The results from three focus groups demonstrated the difficulty that users face in focusing their attention on the main elements of the metaverse, and the inability of this virtual sphere to convey the authenticity of a cultural event. Based on these findings, a metaverse-focused quantitative study was conducted to examine whether perceived gamification mitigate the negative effects of users failing to pay attention in their metaverse experiences. When users increased their attention levels, their ability to imagine the real experience and their perceptions of the authenticity of the cultural event increased, which produced positive behavioral intentions. This is one of the first studies to empirically analyze the tourist experience in the metaverse; managers and policymakers can benefit from the results to hold valuable virtual cultural events., Comment: Published research article

Potentials in cosmological inflation often involve scalars with trans-Planckian ranges. As a result, towers of states become massless and their presence pushes the fundamental scale not to coincide with $M_{\rm P}$ but rather with the $species\, scale$, $\Lambda$. This scale transforms as an automorphic form of the theory's duality symmetries. We propose that the inflaton potential should be 1) an automorphic invariant form, non-singular over all moduli space, 2) depending only on $\Lambda$ and its field derivatives, and 3) approaching constant values in the large moduli to ensure a long period of inflation. These conditions lead to the proposal $V \sim \lambda(\phi, \phi^*)$, with $\lambda = G^{i\bar{j}} (\partial_i \Lambda)(\partial_{\bar{j}} \Lambda) / \Lambda^2$, determining the 'species scale convex hull'. For a single elliptic complex modulus with $SL(2, Z)$ symmetry, this results in an inflaton potential $V \simeq (\text{Im} \tau)^2 |\tilde{G}_2|^2 / N^2$, with $N \simeq -\log(\text{Im} \tau |\eta(\tau)|^4)$, where $\eta$ is the Dedekind function and $\tilde{G}_2$ the Eisenstein modular form of weight 2. Surprisingly, this potential at large modulus resembles that of the Starobinsky model. We compute inflation parameters yielding results similar to Starobinsky's, but extended to modular invariant expressions. Interestingly, the number of e-folds is proportional to the number of species in the tower, $N_e \simeq N$, and $\epsilon \simeq \Lambda^4$ at large moduli, suggesting that the tower of states plays an important role in the inflation process., Comment: 21 pages + appendices, 3 figures. v2: references added, minor changes

A proven methodology to solve multiphase flows is based on the one-fluid formulation of the governing equations, which treats the phase transition across the interface as a single fluid with varying properties and adds additional source terms to satisfy interface jump conditions, e.g., surface tension and mass transfer. Used interchangeably in the limit of non-evaporative flows, recent literature has formalized the inconsistencies that arise in the momentum balance of the non-conservative one-fluid formulation compared to its conservative counterpart when phase change is involved. This translates into an increased sensitivity of the numerical solution to the choice of formulation. Motivated by the fact that many legacy codes using the non-conservative one-fluid formulation have been extended to phase-change simulations, the inclusion of two corrective forces at the interface and a modification of the pressure-velocity solver with an additional predictor-projection step are shown to recover the exact momentum balance in the evaporative non-conservative one-fluid framework for low-viscosity incompressible flows. This has direct implications for obtaining a physically meaningful pressure field and is seen to affect the dynamics of two-phase flows. In the high-viscosity domain, the discretization of the viscous term introduces a momentum imbalance which is highly dependent on the chosen method to model the phase transition. Lastly, the need to develop sub-models for heat and mass transfer and for surface tension becomes evident since typical grid resolutions defined as ``resolved" in the literature may not be enough to capture interfacial phenomena., Comment: 40 pages, 26 figures

We present a novel analysis of the redshift-space power spectrum of galaxies in the SDSS-III BOSS survey. Our methodology improves upon previous analyses by using a theoretical model based on cosmological simulations coupled with a perturbative description of the galaxy-matter connection and a phenomenological prescription of Fingers of God. This enables a very robust analysis down to mildly non-linear scales, $k\sim 0.4\,h\,{\rm Mpc}^{-1}$. We carried out a number of tests on mock data, different subsets of BOSS, and using model variations, all of which support the robustness of our analysis. Our results provide constraints on $\sigma_8$, $\Omega_m$, $h$, and $S_8 \equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$. Specifically, we measure $\Omega_m=0.301\pm 0.011$, $\sigma_8=0.745^{+0.028}_{-0.035}$, $h=0.705\pm 0.015$, and $ S_8 = 0.747^{+0.032}_{-0.039}$ when all the nuisance parameters of our model are left free. By adopting relationships among bias parameters measured in galaxy formation simulations, the value of $S_8$ remains consistent whereas uncertainties are reduced by $\sim20\%$. Our cosmological constraints are some of the strongest obtained with the BOSS power spectrum alone: they exhibit a $2.5-3.5\sigma$ tension with the results of the {\it Planck\/} satellite, agreeing with the lower values of $S_8$ derived from gravitational lensing. However, the cosmological model preferred by {\it Planck\/} is still a good fit to the BOSS data, assuming small departures from physical bias priors and, therefore, cannot be excluded at high significance. We conclude that, at the present, the BOSS data alone does not show strong evidence for a tension between the predictions of $\Lambda$CDM for the high- and low-redshift Universe., Comment: 17 pages, 12 figures

The concept of spin symmetries has gained renewed interest as a valuable tool for classifying novel magnetic phases, including altermagnets and recently identified unconventional p-wave magnets. In this work, we show that in certain cases, the photoresponse is determined by spin group rather than the conventional magnetic group symmetry, a finding with implications for compounds with weak spin-orbit coupling. As a concrete realization we consider the nonlinear shift photocurrent in Mn$_5$Si$_3$, a material that features the two possible classes of unconventional p-wave magnetism in the form of two competing spin structures, a coplanar and non-coplanar one. While both are predicted to generate shift currents based on magnetic symmetry considerations, only the non-coplanar configuration survives the spin symmetry requirements. This is numerically confirmed by our $\textit{ab-initio}$ calculations, providing a protocol to experimentally identify the spin configuration of this promising material via linear photogalvanic measurements.

Hypothetical axions provide a compelling explanation for dark matter and could be emitted from the hot solar interior. The CERN Axion Solar Telescope (CAST) has been searching for solar axions via their back conversion to X-ray photons in a 9-T 10-m long magnet directed towards the Sun. We report on an extended run with the IAXO (International Axion Observatory) pathfinder detector, doubling the previous exposure time. The detector was operated with a xenon-based gas mixture for part of the new run, providing technical insights for future detector configurations in IAXO. No counts are detected in the 95\% signal-encircling region during the new run, while one is expected. The new data improve the axion-photon coupling limit to 5.7$\times 10^{-11}\,$GeV$^{-1}$ at 95\% C.L., the most restrictive experimental limit to date., Comment: 8 pages, 4 figures (plus 6 pages, 10 figures of supplemental material) Corresponding authors: C. Margalejo (cmargalejo@unizar.es) and J. Ruz (Jaime.Ruz@cern.ch)

We study how tiny Dirac neutrino masses consistent with experimental constraints can arise in string theory SM-like vacua. We use as a laboratory 4d ${\cal N}=1$ type IIA Calabi--Yau orientifold compactifications, and in particular recent results on Yukawa couplings at infinite field-space distance. In this regime we find Dirac neutrino masses of the form $m_\nu \simeq g_\nu\langle H\rangle$, with $g_{\nu}$ the gauge coupling of the massive $U(1)$ under which the right-handed neutrinos $\nu_R$ are charged, and which should be in the range $g_{\nu}\simeq 10^{-14}-10^{-12}$ to reproduce neutrino data. The neutrino mass suppression occurs because the right-handed neutrino kinetic term behaves as $K_{\nu\nu} \simeq 1 /g_{\nu}^2 $. At the same time a tower of $\nu_R$-like states appears with characteristic scale $m_0\simeq g_{\nu}^2M_{\rm P}\simeq 0.1-500$ eV, in agreement with Swampland expectations. Two large hidden dimensions only felt by the $\nu_R$ sector arise at the same scale, while the string scale is around $M_s\simeq g_\nu M_{\rm P}\simeq 10-700$ TeV. Some phenomenological implications and model building challenges are described. As a byproduct, independently of the neutrino issue, we argue that a single large dimension in the context of SM-like type IIA Calabi--Yau orientifolds leads to too small Yukawa couplings for quarks and charged leptons., Comment: 31 pages + appendices, 4 figures, 4 tables. v2: references added; Appendix updated

Large language models (LLMs) often lack culture-specific knowledge of daily life, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LLMs' cultural sensitivities are limited to a single language or collected from online sources such as Wikipedia, which do not reflect the mundane everyday lifestyles of diverse regions. That is, information about the food people eat for their birthday celebrations, spices they typically use, musical instruments youngsters play, or the sports they practice in school is common cultural knowledge but uncommon in easily collected online sources, especially for underrepresented cultures. To address this issue, we introduce BLEnD, a hand-crafted benchmark designed to evaluate LLMs' everyday knowledge across diverse cultures and languages. BLEnD comprises 52.6k question-answer pairs from 16 countries/regions, in 13 different languages, including low-resource ones such as Amharic, Assamese, Azerbaijani, Hausa, and Sundanese. We construct the benchmark to include two formats of questions: short-answer and multiple-choice. We show that LLMs perform better for cultures that are highly represented online, with a maximum 57.34% difference in GPT-4, the best-performing model, in the short-answer format. For cultures represented by mid-to-high-resource languages, LLMs perform better in their local languages, but for cultures represented by low-resource languages, LLMs perform better in English than the local languages. We make our dataset publicly available at: https://github.com/nlee0212/BLEnD.

Dielectric breakdown of physical vacuum (Schwinger effect) is the textbook demonstration of compatibility of Relativity and Quantum theory. Although, the observation of this effect in its original static formulation is practically unachievable, it has been shown that the requirements on field strengths can be significantly reduced for dynamical generalizations of Schwinger effect. Here, we report on observation of an analog dynamical Schwinger effect in gapped Dirac semiconductor lead-halide perovskite MAPbBr$_3$. Specifically, we observe strong photoluminescence of a lead-halide perovskite driven by deep sub-gap irradiation, and use the quasi-adiabatic Landau-Dykhne approach to interpret our data in terms of the dynamical Schwinger effect. Further, the exponential sensitivity of the Schwinger effect to driving fields allows us to measure the local frozen-in fields in a nominally cubic single perovskite crystal at room temperature. Finally, we demonstrate an AC analogue of biasing in our system -- the non-perturbative cooperation between two time-dependent fields simultaneously driving the sample. Our results establish lead-halide perovskites as an excellent platform for simulating effects of strong fields on Dirac fields. In addition, they contribute to the on-going discussion about inversion-breaking in MAPbBr$_3$ single crystal and pave the way for a mid-infrared light detection with lead-halide perovskites.

We present an approach to compute the Floquet quasienergy spectrum of time-periodic systems. The method allows to characterize the light-matter interaction in finite and extended structures by carefully addressing the resolution of the position operator. In periodic systems we discuss the role of the quantum-geometric gauge freedom of Bloch states and employ a Wannier-based scheme to compute the required matrix elements. As a consequence, the method is accurate and applicable to a broad range of systems, from atoms and molecules to cold atomic gases and materials described by density functional theory, as well as model systems. We demonstrate the applicability of the approach by studying two cases: a particle trapped in a one-dimensional box and the semiconducting material BC$_2$N. We employ the first example to provide a numerical proof of the invariance of the Floquet quasienergy spectrum with respect to the choice of electromagnetic gauge. The analysis of BC$_2$N then serves to illustrate the physical effects described by the quasienergies, such as multiphoton resonances, and their expected range of occurrence in real materials in terms of external electric field and frequency of the drive pulse., Comment: 16 pages, 6 figures

Defects in crystals can have a transformative effect on the properties and functionalities of solid-state systems. Dopants in semiconductors are core components in electronic and optoelectronic devices. The control of single color centers is at the basis of advanced applications for quantum technologies. Unintentional defects can also be detrimental to the crystalline structure and hinder the development of novel materials. Whatever the research perspective, the identification of defects is a key but complicated, and often long-standing issue. Here, we present a general methodology to identify point defects by combining isotope substitution and polytype control, with a systematic comparison between experiments and first-principles calculations. We apply this methodology to hexagonal boron nitride (hBN) and its ubiquitous color center emitting in the ultraviolet spectral range. From isotopic purification of the host hBN matrix, a local vibrational mode of the defect is uncovered, and isotope-selective carbon doping proves that this mode belongs to a carbon-based center. Then, by varying the stacking sequence of the host hBN matrix, we unveil different optical responses to hydrostatic pressure for the non-equivalent configurations of this ultraviolet color center. We conclude that this defect is a carbon dimer in the honeycomb lattice of hBN. Our results show that tuning the stacking sequence in different polytypes of a given crystal provides unique fingerprints contributing to the identification of defects in 2D materials.

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

We investigate modifications to Bayesian Optimization for a resource-constrained setting of sequential experimental design where changes to certain design variables of the search space incur a switching cost. This models the scenario where there is a trade-off between evaluating more while maintaining the same setup, or switching and restricting the number of possible evaluations due to the incurred cost. We adapt two process-constrained batch algorithms to this sequential problem formulation, and propose two new methods: one cost-aware and one cost-ignorant. We validate and compare the algorithms using a set of 7 scalable test functions in different dimensionalities and switching-cost settings for 30 total configurations. Our proposed cost-aware hyperparameter-free algorithm yields comparable results to tuned process-constrained algorithms in all settings we considered, suggesting some degree of robustness to varying landscape features and cost trade-offs. This method starts to outperform the other algorithms with increasing switching-cost. Our work broadens out from other recent Bayesian Optimization studies in resource-constrained settings that consider a batch setting only. While the contributions of this work are relevant to the general class of resource-constrained problems, they are particularly relevant to problems where adaptability to varying resource availability is of high importance

It has been previously advocated that the presence of the daily and annual modulations of the axion flux on the Earth's surface may dramatically change the strategy of the axion searches. The arguments were based on the so-called Axion Quark Nugget (AQN) dark matter model which was originally put forward to explain the similarity of the dark and visible cosmological matter densities $\Omega_{\rm dark}\sim \Omega_{\rm visible}$. In this framework, the population of galactic axions with mass $ 10^{-6} {\rm eV}\lesssim m_a\lesssim 10^{-3}{\rm eV}$ and velocity $\langle v_a\rangle\sim 10^{-3} c$ will be accompanied by axions with typical velocities $\langle v_a\rangle\sim 0.6 c$ emitted by AQNs. Furthermore, in this framework, it has also been argued that the AQN-induced axion daily modulation (in contrast with the conventional WIMP paradigm) could be as large as $(10-20)\%$, which represents the main motivation for the present investigation. We argue that the daily modulations along with the broadband detection strategy can be very useful tools for the discovery of such relativistic axions. The data from the CAST-CAPP detector have been used following such arguments. Unfortunately, due to the dependence of the amplifier chain on temperature-dependent gain drifts and other factors, we could not conclusively show the presence or absence of a dark sector-originated daily modulation. However, this proof of principle analysis procedure can serve as a reference for future studies., Comment: 18 pages, 8 figures

Selective, accurate, fast, and with minimal usage of instrumentation has become paramount nowadays in areas of environmental monitoring. Here, we chemically modified fluorescent graphene quantum dots (GQDs) and trained a Machine Learning (ML) algorithm for the selective quantification of Hg2+ and Fe3+ ions present within real water samples. The probe is obtained by an electrosynthesis of CVD graphene in the presence of urea, followed by the functionalization with 1-nitroso-2-naphthol (NN). The functionalization with NN moieties dramatically improve selectivity and sensitivity toward Hg2+ and Fe3+, as demonstrated by LODs as low as 0.001 mg L-1 and 0.003 mg L-1; respectively. Time-dependent density-functional theory (TD-DFT) reveals that the NN molecules within the GQDs are responsible of the florescence emission of the probe. The emission spectra profiles exhibited distinct characteristics between Hg2+ and Fe3+ enabling the ML model to precisely quantify and differentiate between both analytes present in natural and drinking waters. The ML results were further validated by measurements via cold vapor-atomic fluorescence spectroscopy and UV-vis spectroscopy. The efficiency of the ML model eliminates the necessity of extensive training values and validations, making it a reliable tool for precisely quantifying the presence of Fe and Hg ions in real water samples.

Understanding $\textit{galaxy bias}$ -- that is the statistical relation between matter and galaxies -- is of key importance for extracting cosmological information from galaxy surveys. While the bias function $f$ -- that is the probability of forming galaxy in a region with a given density field -- is usually approximated through a parametric expansion, we show here, that it can also be measured directly from simulations in a non-parameteric way. Our measurements show that the Lagrangian bias function is very close to a Gaussian for halo selections of any mass. Therefore, we newly introduce a Gaussian bias model with several intriguing properties: (1) It predicts only strictly positive probabilities $f > 0$ (unlike expansion models), (2) It has a simple analytic renormalized form and (3) It behaves gracefully in many scenarios where the classical expansion converges poorly. We show that the Gaussian bias model describes the galaxy environment distribution $p(\delta | \mathrm{g})$, the scale dependent bias function $f$ and the renormalized bias function $F$ of haloes and galaxies generally equally well or significantly better than a second order expansion with the same number of parameters. We suggest that a Gaussian bias approach may enhance the range of validity of bias schemes where the canonical expansion converges poorly and further, that it may make new applications possible, since it guarantees the positivity of predicted galaxy densities., Comment: 21 pages, 12 figures, submitted to A&A

The spatial distribution of galaxies is a highly complex phenomenon currently impossible to predict deterministically. However, by using a statistical $\textit{bias}$ relation, it becomes possible to robustly model the average abundance of galaxies as a function of the underlying matter density field. Understanding the properties and parametric description of the bias relation is key to extract cosmological information from future galaxy surveys. Here, we contribute to this topic primarily in two ways: (1) We develop a new set of probabilistic estimators for bias parameters using the moments of the Lagrangian galaxy environment distribution. These estimators include spatial corrections at different orders to measure bias parameters independently of the damping scale. We report robust measurements of a variety of bias parameters for haloes, including the tidal bias and its dependence with spin at a fixed mass. (2) We propose an alternative formulation of the bias expansion in terms of "cumulant bias parameters" that describe the response of the logarithmic galaxy density to large-scale perturbations. We find that cumulant biases of haloes are consistent with zero at orders $n > 2$. This suggests that: (i) previously reported bias relations at order $n > 2$ are an artefact of the entangled basis of the canonical bias expansion; (ii) the convergence of the bias expansion may be improved by phrasing it in terms of cumulants; (iii) the bias function is very well approximated by a Gaussian -- an avenue which we explore in a companion paper., Comment: 26 pages, 16 figures, submitted to A&A

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $\Lambda$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented., Comment: New submissions welcome! Challenge data available at https://github.com/ANSalcedo/Beyond2ptMock

In this paper, the construction of $C^{1}$ cubic quasi-interpolants on a three-direction mesh of $\RR^{2}$ is addressed. The quasi-interpolating splines are defined by directly setting their Bernstein-B\'{e}zier coefficients relative to each triangle from point and gradient values in order to reproduce the polynomials of the highest possible degree. Moreover, additional global properties are required. Finally, we provide some numerical tests confirming the approximation properties.

Information literacy (IL) involves a group of competences and fundamental skills in the 21st century. Today, society operates around information, which is challenging considering the vast amount of content available online. People must be capable of searching, critically assessing, making sense of, and communicating information. This set of competences must be properly developed since childhood, especially if considering early age access to online resources. To better understand the evolution and current status of IL development and assessment at school (K-12) level, we conducted a systematic literature review based on the guidelines established by the PRISMA statement. Our review led us to an initial set of 1,234 articles, from which 53 passed the inclusion criteria. These articles were used to address six research questions focused on IL definitions, skills, standards, and assessment tools. Our review shows IL evolution over the years and how it has been formalisedthrough definitions and standards. These findings reveal key gaps that must be addressed in order to advance the field further. Keywords: Elementary education, Information literacy, Secondary education, 21st Century abilities.

We study a one-parameter family of time-reversible Hamiltonian vector fields in $\mathbb{R}^4$, which has received great attention in the literature. On the one hand, it is due to the role it plays in the context of certain applications in the field of Physics or Engineering and, on the other hand, we especially highlight its relevance within the framework of generic unfoldings of the four-dimensional nilpotent singularity of codimension four. The system exhibits a bifocal equilibrium point for a range of parameter values. The associated two-dimensional invariant manifolds, stable and unstable, fold into the phase space in such a way that they produce intricate patterns. This entangled geometry has previously been called \textit{tentacular geometry}. We consider a three-dimensional level set containing the bifocal equilibrium point to gain insight into the folding behavior of these invariant manifolds. Our method consists of describing the traces left by invariant manifolds when crossing an invariant cross section by the reversibility map. With this new approach, we provide a better understanding of how tentacular geometry evolves with respect to the parameter. Our techniques enables us to link the tentacular geometry on the cross section with the study of cocooning cascades of homoclinic tangencies. Indeed, we present a general theory to extend to $\mathbb{R}^4$ the phenomena related to cocoon bifurcation that classically develop within families of three-dimensional reversible vector fields. On the basis of these results, we conjecture the existence of heteroclinic cycles consisting of two orbits connecting the bifocus with a saddle node periodic orbit.

Gas time projection chambers (TPCs) with Micromegas pixelated readouts are being used in dark matter searches and other rare event searches, due to their potential in terms of low background levels, energy and spatial resolution, gain, and operational stability. Moreover, these detectors can provide precious features,such as topological information, allowing for event directionality and powerful signal-background discrimination. The Micromegas technology of the microbulk type is particularly suited to low-background applications and is being exploited by detectors for CAST and IAXO (solar axions) and TREX-DM (low-mass WIMPs) experiments. Challenges for the future include reducing intrinsic background levels, reaching lower energy detection levels, and technical issues such as robustness of detector, new design choices, novel gas mixtures and operation points, scaling up to larger detector sizes, handling large readout granularity, etc. We report on the status and prospects of the development ongoing in the context of IAXO and TREX-DM experiments, pointing to promising perspectives for the use of Micromegas detectors in directdark matter searches

Particle tracking in turbulent flows is fundamental to the study of the transport of tracers, inertial particles or even active objects in space and time, i.e. the Lagrangian frame of reference. It provides experimental tests of theoretical predictions (e.g. for the statistics of fluid accelerations and particle dispersion) and helps to understand important natural processes where particle inertia is important (e.g. cloud microphysics). While the spatial (Eulerian) properties of turbulent flows have been studied for high, atmospheric Reynolds numbers ($R_\lambda > 10^4$), the profound difficulties in accurately tracking particles in turbulent flows have limited the Reynolds numbers in the Lagrangian reference frame to the Taylor scale Reynolds numbers $R_\lambda \lesssim 10^3$. Here we describe a setup that allowed Lagrangian particle tracking at $R_\lambda$ between 100 and 6000 in the Max Planck Variable Density Turbulence Tunnel (VDTT). We describe the imaging setup within the pressurised facility, the laser illumination, the particles and the particle dispersion mechanism. We verify that the KOBO Cellulobeads D-10 particles are suitable tracers. They carry negligible charge and their Stokes number is small over the full range of experimental conditions. We present typical data from the experiment and discuss the challenges and constraints of the setup.

A widely accepted way to assess the performance of iterative black-box optimizers is to analyze their empirical cumulative distribution function (ECDF) of pre-defined quality targets achieved not later than a given runtime. In this work, we consider an alternative approach, based on the empirical attainment function (EAF) and we show that the target-based ECDF is an approximation of the EAF. We argue that the EAF has several advantages over the target-based ECDF. In particular, it does not require defining a priori quality targets per function, captures performance differences more precisely, and enables the use of additional summary statistics that enrich the analysis. We also show that the average area over the convergence curves is a simpler-to-calculate, but equivalent, measure of anytime performance. To facilitate the accessibility of the EAF, we integrate a module to compute it into the IOHanalyzer platform. Finally, we illustrate the use of the EAF via synthetic examples and via the data available for the BBOB suite.

This paper deals with Hermite osculatory interpolating splines. For a partition of a real interval endowed with a refinement consisting in dividing each subinterval into two small subintervals, we consider a space of smooth splines with additional smoothness at the vertices of the initial partition, and of the lowest possible degree. A normalized B-spline-like representation for the considered spline space is provided. In addition, several quasi-interpolation operators based on blossoming and control polynomials have also been developed. Some numerical tests are presented and compared with some recent works to illustrate the performance of the proposed approach.

Graph convolutional networks (GCNs) have emerged as a powerful alternative to multiple instance learning with convolutional neural networks in digital pathology, offering superior handling of structural information across various spatial ranges - a crucial aspect of learning from gigapixel H&E-stained whole slide images (WSI). However, graph message-passing algorithms often suffer from oversmoothing when aggregating a large neighborhood. Hence, effective modeling of multi-range interactions relies on the careful construction of the graph. Our proposed multi-scale GCN (MS-GCN) tackles this issue by leveraging information across multiple magnification levels in WSIs. MS-GCN enables the simultaneous modeling of long-range structural dependencies at lower magnifications and high-resolution cellular details at higher magnifications, akin to analysis pipelines usually conducted by pathologists. The architecture's unique configuration allows for the concurrent modeling of structural patterns at lower magnifications and detailed cellular features at higher ones, while also quantifying the contribution of each magnification level to the prediction. Through testing on different datasets, MS-GCN demonstrates superior performance over existing single-magnification GCN methods. The enhancement in performance and interpretability afforded by our method holds promise for advancing computational pathology models, especially in tasks requiring extensive spatial context.

The layer stacking morphology in nanocarbons is paramount for achieving new properties and outperforming applications. Here, we demonstrate that graphene quantum dots (GQDs) retain crystallinity and a stacking structure from CVD graphene grown on Ni foam. Our results reveal that GQD subdomains comprise a few-layer graphene structure in the AB -- AB and ABC -- ABC stacking configuration. HR-TEM images along with a multiple-approach characterization (XRD, XPS, UV-vis, AFM, and ATR-IR) exhibit 3.0 to 8.0 nm crystalline GQDs with 2-6 graphene layers thick indicating a disk-shape structure. The UV-vis profiles show changes in color of the dispersion (from colorless to red) during and after the electrochemistry, suggesting a systematic electrooxidation of graphene into smaller, highly crystalline, and more complex sp2/sp3 structures. Importantly, a control experiment performed under the same conditions but with a graphitic rod exhibited large, polydisperse, and multilayer carbon structures. This work demonstrates a relatively easy electrochemical synthesis to obtain GQDs which retain the pristine and, in turn, distinctive structure of graphene grown on Ni foam., Comment: 33 pages

This document is written as an academic exercise, with the goal of exploring the feasibility of writing a white paper in accordance with Regulation (EU) 2023/1114 (MiCA). It is meant as a Proof of Concept (PoC) illustrating a concrete application of the requirements of MiCA. Like the MiCA white papers PoC shared by ESMA, this document is solely for the purposes of the PoC, to inform the public as to how a crypto-asset white paper could work, inspire public debate and feedback, and enhance the public conversation around the implementation of EU regulations., Comment: 32 pages

We study limits of vanishing Yukawa couplings of 4d chiral matter fields in Quantum Gravity, using as a laboratory type IIA orientifolds with D6-branes. In these theories chiral fermions arise at brane intersections, where an infinite tower of charged particles dubbed gonions are localised. We show that in the limit $Y\rightarrow 0$ some of these towers become asymptotically massless, while at the same time the kinetic term of some chiral fields becomes singular and at least two extra dimensions decompactify. For limits parametrised by a large complex structure saxion $u$, Yukawa couplings have a behaviour of the form $Y \, \sim \, {1}/{u^r}$, with $r$ some positive rational number. Moreover, in this limit some of the gauge couplings associated to the Yukawa vanish. The lightest gonion scales are of order $m_{\rm gon} \sim g^s M_{\rm P}$ with $s>1$, verifying the magnetic WGC with room to spare and with no need of its tower/sublattice versions. We also show how this behaviour can be understood in the context of the emergence of kinetic terms in Quantum Gravity. All these results may be very relevant for phenomenology, given the fact that some of the Yukawa couplings in the Standard Model are very small., Comment: 56 pages + appendices, 9 figures, 7 tables. v4: JHEP version

In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1-10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common techniques we used a multi-layer veto system designed to tag cosmogenic neutron background. Over an effective time of 52 days, a background level of $8.6 \times 10^{-7}\,\text{counts keV}^{-1}\,\text{cm}^{-2} \, \text{s}^{-1}$ was reached in a laboratory at above ground level. This is the lowest background level achieved at surface level. In this paper we present the experimental setup, show simulations of the neutron-induced background, and demonstrate the process to identify background signals in the data. Finally, prospects to reach lower background levels down to $10^{-7} \, \text{counts keV}^{-1} \, \text{cm}^{-2} \, \text{s}^{-1}$ will be discussed.

The use of contrast agents has previously been proposed as a novel method to increase the activation close to the Bragg peak, aiming to improve the quality of proton range monitoring in vivo. In a recent work, we demonstrated the feasibility of $^{127}$I for online verification, thanks to its high cross-section (200 mbarn at 10 MeV) and low energy production threshold for $^{127m}$Xe. The spectroscopy-based method relies on identifying two specific delayed $\gamma$ lines (at 124.6 and 172.5 keV), which can be analyzed via single-photon emission computed tomography (SPECT). In this work, we present a proof-of-principle study to investigate proton activation in a commercial iodinated contrast media (ICM) for radiology. Five measurements were conducted at different proton energies (6-10 MeV), equivalent to the last millimeters of clinical proton range. Activation in the ICM was measured with four LaBr$_3$(Ce) scintillators. The contribution from iodine was separated from the activation of the solvent, yielding excellent agreement with previously reported data. These results demonstrate the potential of this technique and pave the way for further testing in clinically relevant scenarios.