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The widespread adoption of generative artificial intelligence (AI) has fundamentally transformed technological landscapes and societal structures in recent years. Our objective is to identify the primary methodologies that may be used to help predict the economic and social impacts of generative AI adoption. Through a comprehensive literature review, we uncover a range of methodologies poised to assess the multifaceted impacts of this technological revolution. We explore Agent-Based Simulation (ABS), Econometric Models, Input-Output Analysis, Reinforcement Learning (RL) for Decision-Making Agents, Surveys and Interviews, Scenario Analysis, Policy Analysis, and the Delphi Method. Our findings have allowed us to identify these approaches' main strengths and weaknesses and their adequacy in coping with uncertainty, robustness, and resource requirements.

Distributional semantics is the linguistic theory that a word's meaning can be derived from its distribution in natural language (i.e., its use). Language models are commonly viewed as an implementation of distributional semantics, as they are optimized to capture the statistical features of natural language. It is often argued that distributional semantics models should excel at capturing graded/vague meaning based on linguistic conventions, but struggle with truth-conditional reasoning and symbolic processing. We evaluate this claim with a case study on vague (e.g. "many") and exact (e.g. "more than half") quantifiers. Contrary to expectations, we find that, across a broad range of models of various types, LLMs align more closely with human judgements on exact quantifiers versus vague ones. These findings call for a re-evaluation of the assumptions underpinning what distributional semantics models are, as well as what they can capture., Comment: 9 Pages, 3 Figures

Tool-augmented LLMs are a promising approach to create AI agents that can have realistic conversations, follow procedures, and call appropriate functions. However, evaluating them is challenging due to the diversity of possible conversations, and existing datasets focus only on single interactions and function-calling. We present a test generation pipeline to evaluate LLMs as conversational AI agents. Our framework uses LLMs to generate diverse tests grounded on user-defined procedures. For that, we use intermediate graphs to limit the LLM test generator's tendency to hallucinate content that is not grounded on input procedures, and enforces high coverage of the possible conversations. Additionally, we put forward ALMITA, a manually curated dataset for evaluating AI agents in customer support, and use it to evaluate existing LLMs. Our results show that while tool-augmented LLMs perform well in single interactions, they often struggle to handle complete conversations. While our focus is on customer support, our method is general and capable of AI agents for different domains., Comment: 14 pages, 5 figures, Submitted to GenBench@EMNLP2024

Generative artificial intelligence (AI) systems have transformed various industries by autonomously generating content that mimics human creativity. However, concerns about their social and economic consequences arise with widespread adoption. This paper employs agent-based modeling (ABM) to explore these implications, predicting the impact of generative AI on societal frameworks. The ABM integrates individual, business, and governmental agents to simulate dynamics such as education, skills acquisition, AI adoption, and regulatory responses. This study enhances understanding of AI's complex interactions and provides insights for policymaking. The literature review underscores ABM's effectiveness in forecasting AI impacts, revealing AI adoption, employment, and regulation trends with potential policy implications. Future research will refine the model, assess long-term implications and ethical considerations, and deepen understanding of generative AI's societal effects., Comment: 6 pages, 2 figures

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

Phase recognition in surgical videos is crucial for enhancing computer-aided surgical systems as it enables automated understanding of sequential procedural stages. Existing methods often rely on fixed temporal windows for video analysis to identify dynamic surgical phases. Thus, they struggle to simultaneously capture short-, mid-, and long-term information necessary to fully understand complex surgical procedures. To address these issues, we propose Multi-Scale Transformers for Surgical Phase Recognition (MuST), a novel Transformer-based approach that combines a Multi-Term Frame encoder with a Temporal Consistency Module to capture information across multiple temporal scales of a surgical video. Our Multi-Term Frame Encoder computes interdependencies across a hierarchy of temporal scales by sampling sequences at increasing strides around the frame of interest. Furthermore, we employ a long-term Transformer encoder over the frame embeddings to further enhance long-term reasoning. MuST achieves higher performance than previous state-of-the-art methods on three different public benchmarks.

Continuous-time dynamic graphs (CTDGs) are essential for modeling interconnected, evolving systems. Traditional methods for extracting knowledge from these graphs often depend on feature engineering or deep learning. Feature engineering is limited by the manual and time-intensive nature of crafting features, while deep learning approaches suffer from high inference latency, making them impractical for real-time applications. This paper introduces Deep-Graph-Sprints (DGS), a novel deep learning architecture designed for efficient representation learning on CTDGs with low-latency inference requirements. We benchmark DGS against state-of-the-art (SOTA) feature engineering and graph neural network methods using five diverse datasets. The results indicate that DGS achieves competitive performance while inference speed improves between 4x and 12x compared to other deep learning approaches on our benchmark datasets. Our method effectively bridges the gap between deep representation learning and low-latency application requirements for CTDGs.

In the realm of fundamental quantum science and technologies, non-classical states of light, such as single-photon Fock states, are widely studied. However, current standards and metrological procedures are not optimized for low light levels. Progress in this crucial scientific domain depends on innovative metrology approaches, utilizing reliable devices based on quantum effects. We present a new generation of molecule-based single photon sources, combining their integration in a polymeric micro-lens with pulsed excitation schemes, thereby realizing suitable resources in quantum radiometry. Our strategy enhances the efficiency of generated single photon pulses and improves stability, providing a portable source at 784.7 nm that maintains consistent performance even through a cooling and heating cycle. The calibration of a single photon avalanche detector is demonstrated using light sources with different photon statistics, and the advantages of the single-molecule device are discussed. A relative uncertainty on the intrinsic detection efficiency well below 1 % is attained, representing a new benchmark in the field.

We study existence of a weak solution for one-dimensional problems as \begin{equation}\label{intro}\tag{1} \begin{cases} \displaystyle -\frac{d}{dx}\left(a(x) \frac{d u}{dx}\right) = - \frac{d \phi (u) }{dx}- \frac{d g(x) }{dx}& \text{in}\;(0,L),\\ u(0)=u(L)=0\,, & \end{cases} \end{equation} where $a$ is a positive bounded function, $g\in L^2(0,L)$, and $\phi:\mathbb{R}\mapsto \mathbb{R}\cup \{+\infty\}$ is continuous as a function with values in $\mathbb{R}\cup \{+\infty\}$. Some relevant qualitative and quantitative facts concerning such problems and their solutions are described. In particular a precise characterization of the behaviour of suitable approximating solution is provided. Of particular (and independent) interest is the study of an associated ODE for which, we prove existence, uniqueness and comparison results. As a consequence of our arguments, a delicate stability result as well a quite unexpected multiplicity result is shown for problems as in \eqref{intro}.

Visualization techniques have been widely used to analyze various data types, including text. This paper proposes an approach to analyze a controversial text in Portuguese by applying graph visualization techniques. Specifically, we use a story charting technique that transforms the text into a graph. Each node represents a character or main entities, and each edge represents the interactions between characters. We also present several visualization techniques to gain insights into the story's structure, relationships between the characters, the most important events, and how some key terms are used throughout the book. By using this approach, we can effectively reveal complex patterns and relationships that may not be easily discernible from reading the text. Finally, we discuss the potential applications of our technique in Literary Studies and other fields.

Background: Despite the recent advances in computational fluid dynamics (CFD) techniques applied to blood flow within the left atrium (LA), the relationship between atrial geometry, flow patterns, and blood stasis within the left atrial appendage (LAA) remains unclear. A better understanding of this relationship would have important clinical implications, as thrombi originating in the LAA are a common cause of stroke in patients with atrial fibrillation (AF). Aim: To identify the most representative atrial flow patterns on a patient-specific basis and study their influence on LAA blood stasis by varying the flow split ratio and some common atrial modeling assumptions. Methods: Three recent techniques were applied to nine patient-specific computational fluid dynamics (CFD) models of patients with AF: a kinematic atrial model to isolate the influence of wall motion because of AF, projection on a universal LAA coordinate system, and quantification of stagnant blood volume (SBV). Results: We identified three different atrial flow patterns based on the position of the center of the main circulatory flow. The results also illustrate how atrial flow patterns are highly affected by the flow split ratio, increasing the SBV within the LAA. As the flow split ratio is determined by the patient's lying position, the results suggest that the most frequent position adopted while sleeping may have implications for the medium- and long-term risks of stroke., Comment: Accepted manuscript, 21 pages, 10 figures, 5 tables

Solid modules over $\mathbb{Q}$ or $\mathbb{F}_p$, introduced by Clausen and Scholze, are a well-behaved variant of complete topological vector spaces that forms a symmetric monoidal Grothendieck abelian category. For a discrete field $k$, we construct the category of ultrasolid $k$-modules, which specialises to solid modules over $\mathbb{Q}$ or $\mathbb{F}_p$. In this setting, we show some commutative algebra results like an ultrasolid variant of Nakayama's lemma. We also explore higher algebra in the form of animated and $\mathbb{E}_\infty$ ultrasolid $k$-algebras, and their deformation theory. We focus on the subcategory of complete profinite $k$-algebras, which we prove is contravariantly equivalent to equal characteristic formal moduli problems with coconnective tangent complex., Comment: 52 pages

Quantum computing represents a revolutionary computational paradigm with the potential to address challenges beyond classical computers' capabilities. The development of robust quantum software is indispensable to unlock the full potential of quantum computing. Like classical software, quantum software is expected to be complex and extensive, needing the establishment of a specialized field known as Quantum Software Engineering. Recognizing the regional focus on Latin America within this special issue, we have boarded on an in-depth inquiry encompassing a systematic mapping study of existing literature and a comprehensive survey of experts in the field. This rigorous research effort aims to illuminate the current landscape of Quantum Software Engineering initiatives undertaken by universities, research institutes, and companies across Latin America. This exhaustive study aims to provide information on the progress, challenges, and opportunities in Quantum Software Engineering in the Latin American context. By promoting a more in-depth understanding of cutting-edge developments in this burgeoning field, our research aims to serve as a potential stimulus to initiate pioneering initiatives and encourage collaborative efforts among Latin American researchers., Comment: 27 pages, 9 figures

The NEXT-White detector, a high-pressure gaseous xenon time projection chamber, demonstrated the excellence of this technology for future neutrinoless double beta decay searches using photomultiplier tubes (PMTs) to measure energy and silicon photomultipliers (SiPMs) to extract topology information. This analysis uses $^{83m}\text{Kr}$ data from the NEXT-White detector to measure and understand the energy resolution that can be obtained with the SiPMs, rather than with PMTs. The energy resolution obtained of (10.9 $\pm$ 0.6) $\%$, full-width half-maximum, is slightly larger than predicted based on the photon statistics resulting from very low light detection coverage of the SiPM plane in the NEXT-White detector. The difference in the predicted and measured resolution is attributed to poor corrections, which are expected to be improved with larger statistics. Furthermore, the noise of the SiPMs is shown to not be a dominant factor in the energy resolution and may be negligible when noise subtraction is applied appropriately, for high-energy events or larger SiPM coverage detectors. These results, which are extrapolated to estimate the response of large coverage SiPM planes, are promising for the development of future, SiPM-only, readout planes that can offer imaging and achieve similar energy resolution to that previously demonstrated with PMTs.

In this paper we provide a complete characterization of the regularity properties of the solutions associated to the homogeneous Dirichlet problem \begin{equation*} \begin{cases} \displaystyle - \Delta_1 u= h(u)f & \text{in } \Omega, \\ \newline u=0 & \text{on } \partial \Omega, \end{cases} \end{equation*} where $\Omega\subset\mathbb{R}^N$ is a bounded open set with Lipschitz boundary, $f \in L^m(\Omega)$ with $m\geq 1$ is a nonnegative function and $h\colon \mathbb{R}^+ \to \mathbb{R}^+$ is continuous, possibly singular at the origin and bounded at infinity. Without any growth restrictions on $h$ at zero, we prove existence of global finite energy solutions in $BV(\Omega)$ under sharp conditions on the summability of $f$ and on the behaviour of $h$ at infinity. Roughly speaking, the faster $h$ goes to zero at infinity, the less regularity is required on $f$. In contrast to the $p$-Laplacian case ($p>1$), we show that the behaviour of $h$ at the origin plays essentially no role. The main result contains an extension of the celebrated one of Lazer-McKenna (\cite{lm}) to the case of the $1$-Laplacian as principal operator.

In a Josephson junction, the current phase relation relates the phase variation of the superconducting order parameter, $\varphi$, between the two superconducting leads connected through a weak link, to the dissipationless current . This relation is the fingerprint of the junction. It is usually dominated by a $\sin(\varphi)$ harmonic, however its precise knowledge is necessary to design superconducting quantum circuits with tailored properties. Here, we directly measure the current phase relation of a superconducting quantum interference device made with gate-tunable graphene Josephson junctions and we show that it can behave as a $\sin(2\varphi)$ Josephson element, free of the traditionally dominant $\sin(\varphi)$ harmonic. Such element will be instrumental for the development of superconducting quantum bits protected from decoherence., Comment: 15 pages, 3 figures, Supplemental Material in Ancillary files

The imaging of individual Ba$^{2+}$ ions in high pressure xenon gas is one possible way to attain background-free sensitivity to neutrinoless double beta decay and hence establish the Majorana nature of the neutrino. In this paper we demonstrate selective single Ba$^{2+}$ ion imaging inside a high-pressure xenon gas environment. Ba$^{2+}$ ions chelated with molecular chemosensors are resolved at the gas-solid interface using a diffraction-limited imaging system with scan area of 1$\times$1~cm$^2$ located inside 10~bar of xenon gas. This new form of microscopy represents an important enabling step in the development of barium tagging for neutrinoless double beta decay searches in $^{136}$Xe, as well as a new tool for studying the photophysics of fluorescent molecules and chemosensors at the solid-gas interface.

We develop a stochastic two-patch epidemic model with nonlinear recidivism to investigate infectious disease dynamics in heterogeneous populations. Extending a deterministic framework, we introduce stochasticity to account for random transmission, recovery, and inter-patch movement fluctuations. We showcase the interplay between local dynamics and migration effects on disease persistence using Monte Carlo simulations and three stochastic approximations-discrete-time Markov chain (DTMC), Poisson, and stochastic differential equations (SDE). Our analysis shows that stochastic effects can cause extinction events and oscillations near critical thresholds like the basic reproduction number, R0, phenomena absent in deterministic models. Numerical simulations highlight source-sink dynamics, where one patch is a persistent infection source while the other experiences intermittent outbreaks., Comment: 22 pages, 12 figures

We present a specific-purpose globalized and preconditioned Newton-CG solver to minimize a metric-aware curved high-order mesh distortion. The solver is specially devised to optimize curved high-order meshes for high polynomial degrees with a target metric featuring non-uniform sizing, high stretching ratios, and curved alignment -- exactly the features that stiffen the optimization problem. To this end, we consider two ingredients: a specific-purpose globalization and a specific-purpose Jacobi-$\text{iLDL}^{\text{T}}(0)$ preconditioning with varying accuracy and curvature tolerances (dynamic forcing terms) for the CG method. These improvements are critical in stiff problems because, without them, the large number of non-linear and linear iterations makes curved optimization impractical. Finally, to analyze the performance of our method, the results compare the specific-purpose solver with standard optimization methods. For this, we measure the matrix-vector products indicating the solver computational cost and the line-search iterations indicating the total amount of objective function evaluations. When we combine the globalization and the linear solver ingredients, we conclude that the specific-purpose Newton-CG solver reduces the total number of matrix-vector products by one order of magnitude. Moreover, the number of non-linear and line-search iterations is mainly smaller but of similar magnitude., Comment: 64 pages, 9 figures

We define a regularized size-shape distortion (quality) measure for curved high-order elements on a Riemannian space. To this end, we measure the deviation of a given element, straight-sided or curved, from the stretching, alignment, and sizing determined by a target metric. The defined distortion (quality) is suitable to check the validity and the quality of straight-sided and curved elements on Riemannian spaces determined by constant and point-wise varying metrics. The examples illustrate that the distortion can be minimized to curve (deform) the elements of a given high-order (linear) mesh and try to match with curved (linear) elements the point-wise stretching, alignment, and sizing of a discrete target metric tensor. In addition, the resulting meshes simultaneously match the curved features of the target metric and boundary. Finally, to verify if the minimization of the metric-aware size-shape distortion leads to meshes approximating the target metric, we compute the Riemannian measures for the element edges, faces, and cells. The results show that, when compared to anisotropic straight-sided meshes, the Riemannian measures of the curved high-order mesh entities are closer to unit. Furthermore, the optimized meshes illustrate the potential of curved $r$-adaptation to improve the accuracy of a function representation., Comment: 49 pages, 23 figures

We have performed a comprehensive study of the Orion Nebula Cluster (ONC) combining the photometric data obtained by the two \textit{HST} Treasury programs that targeted this region. To consistently analyze the rich dataset obtained in a wide variety of filters, we adopted a Bayesian approach to fit the Spectral Energy Distribution of the sources, deriving mass, age, extinction, distance, and accretion for each source in the region. The three dimensional study of mass distribution for bona-fide cluster members shows that mass segregation in the ONC extends to sub-solar masses, while the age distribution strongly supports the idea that star formation in the ONC is best described by a major episode of star formation that happened $\sim 1$ Myr ago. For masses $\gtrsim 0.1$ \Msun, our derived empirical initial mass function (IMF) is in good agreement with a Chabrier system IMF. Both the accretion luminosity (\Lacc) and mass accretion rates (\dMacc) are best described by broken power-law relations. This suggests that for the majority of young circumstellar disks in this cluster the excess emission may be dominated by X-ray-driven photoevaporation by the central star rather than external photoevaporation. If this is the case, the slopes of the power-law relations may be largely determined by the initial conditions set at the onset of the star formation process, which may be quite similar between regions that eventually form clusters of different sizes.

In this study, we derive the infinite product representation of the $\operatorname{sinc}(\mathrm{z})$ function by expressing it in a trigonometric form, evoking similarities to Morrie's Law and Euler's Product formula, along with their generalizations. The results presented in this investigation are entirely novel and are believed to introduce new insights into the topic., Comment: 4 pages

We derive the infinite product of the tangent function expressed in terms of trigonometric expressions such as Eulers Sinc function and Vietes formula, along with their generalizations. All the results presented in this work are novel., Comment: 4 pages