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The theory of tensor categories has found applications across various fields, including representation theory, quantum field theory (conformal in 2 dimensions, and topological in 3 and 4 dimensions), quantum invariants of low-dimensional objects, topological phases of matter, and topological quantum computation. In essence, it is a categorification of the classical theory of algebras and modules. In this analogy, the Deligne tensor product $\boxtimes$ is to the linear tensor $\otimes_{\mathbb{C}}$ as the balanced tensor product $\boxtimes_C$ is to the tensor over algebra $\otimes_A$, where $\mathbb{C}$ is a field, $A$ is a $\mathbb{C}$-algebra, and $C$ is a tensor category. Before this work, several algebraic constructions for balanced tensor products were known, including categories of modules, internal Hom spaces, and generalized categorical centers. In this paper, we introduce a topological construction based on skein theory that offers a better mix of algebra and topology. This approach not only works for products of multiple module categories, but also provides the missing key to proving that the Turaev-Viro state sum model naturally arises from the 3-functor in the classification of fully extended field theories. Building on this result, we establish this long-anticipated proof in an upcoming work., Comment: 25 pages

In this work, we discuss several results concerning Serrin's problem in convex cones in Riemannian manifolds. First, we present a rigidity result for an overdetermined problem in a class of warped products with Ricci curvature bounded below. As a consequence, we obtain a rigidity result for Einstein warped products. Next, we derive a soap bubble result and a Heintze-Karcher inequality that characterize the intersection of geodesic balls with cones in these spaces. Finally, we analyze the analogous ovedetermined problem for the drift Laplacian, where the ambient space is a cone in the Euclidean space., Comment: Comments are welcome!

Early-type galaxies (ETGs) are reference systems to understand galaxy formation and evolution processes. The physics of their collapse and internal dynamics are codified in well-known scaling relations. Cosmological hydrodynamical simulations play an important role, providing insights into the 3D distribution of matter and galaxy formation mechanisms, as well as validating methods to infer the properties of real objects. In this work, we present the closest-to-reality sample of ETGs from the IllustrisTNG100-1 simulation, dubbed "virtual-ETGs," based on an observational-like algorithm that combines standard projected and three-dimensional galaxy structural parameters. We extract 2D photometric information by projecting the galaxies' light into three planes and modeling them via S\'ersic profiles. Aperture velocity dispersions, corrected for softened central dynamics, are calculated along the line-of-sight orthogonal to the photometric projection plane. Central mass density profiles assume a power-law model, while 3D masses remain unmodified from the IllustrisTNG catalogue. The final catalogue includes $10121$ galaxies at redshifts $z \leq 0.1$. By comparing the virtual properties with observations, we find that the virtual-ETG scaling relations (e.g., size-mass, size-central surface brightness, and Faber-Jackson), central density slopes, and scaling relations among total density slopes and galaxy structural parameters are generally consistent with observations. We make the virtual-ETG publicly available for galaxy formation studies and plan to use this sample as a training set for machine learning tools to infer galaxy properties in future imaging and spectroscopic surveys.

We study obstacle problems governed by two distinct types of diffusion operators involving interacting free boundaries. We obtain a somewhat surprising coupling property, leading to a comprehensive analysis of the free boundary. More precisely, we show that near regular points of a coordinate function, the free boundary is analytic, whereas singular points lie on a smooth manifold. Additionally, we prove that uncoupled free boundary points are singular, indicating that regular points lie exclusively on the coupled free boundary. Furthermore, optimal regularity, non-degeneracy, and lower dimensional Hausdorff measure estimates are obtained. Explicit examples illustrate the sharpness of assumptions., Comment: 19

Calibration, the alignment between model confidence and prediction accuracy, is critical for the reliable deployment of large language models (LLMs). Existing works neglect to measure the generalization of their methods to other prompt styles and different sizes of LLMs. To address this, we define a controlled experimental setting covering 12 LLMs and four prompt styles. We additionally investigate if incorporating the response agreement of multiple LLMs and an appropriate loss function can improve calibration performance. Concretely, we build Calib-n, a novel framework that trains an auxiliary model for confidence estimation that aggregates responses from multiple LLMs to capture inter-model agreement. To optimize calibration, we integrate focal and AUC surrogate losses alongside binary cross-entropy. Experiments across four datasets demonstrate that both response agreement and focal loss improve calibration from baselines. We find that few-shot prompts are the most effective for auxiliary model-based methods, and auxiliary models demonstrate robust calibration performance across accuracy variations, outperforming LLMs' internal probabilities and verbalized confidences. These insights deepen the understanding of influence factors in LLM calibration, supporting their reliable deployment in diverse applications., Comment: 24 pages, 11 figures, 8 tables

Large language models and vision transformers have demonstrated impressive zero-shot capabilities, enabling significant transferability in downstream tasks. The fusion of these models has resulted in multi-modal architectures with enhanced instructional capabilities. Despite incorporating vast image and language pre-training, these multi-modal architectures often generate responses that deviate from the ground truth in the image data. These failure cases are known as hallucinations. Current methods for mitigating hallucinations generally focus on regularizing the language component, improving the fusion module, or ensembling multiple visual encoders to improve visual representation. In this paper, we address the hallucination issue by directly enhancing the capabilities of the visual component. Our approach, named EAGLE, is fully agnostic to the LLM or fusion module and works as a post-pretraining approach that improves the grounding and language alignment of the visual encoder. We show that a straightforward reformulation of the original contrastive pre-training task results in an improved visual encoder that can be incorporated into the instructional multi-modal architecture without additional instructional training. As a result, EAGLE achieves a significant reduction in hallucinations across multiple challenging benchmarks and tasks., Comment: 12 pages, 4 figures, 8 tables

Animal welfare has become a critical issue in contemporary society, emphasizing our ethical responsibilities toward animals, particularly within livestock farming. The advent of Artificial Intelligence (AI) technologies, specifically computer vision, offers an innovative approach to monitoring and enhancing animal welfare. Cows, as essential contributors to sustainable agriculture, are central to this effort. However, existing cow detection algorithms face challenges in real-world farming environments, such as complex lighting, occlusions, pose variations, and background interference, hindering detection. Model generalization is crucial for adaptation across contexts beyond the training dataset. This study addresses these challenges using a diverse cow dataset from six environments, including indoor and outdoor scenarios. We propose a detection model combining YOLOv8 with the CBAM (Convolutional Block Attention Module) and assess its performance against baseline models, including Mask R-CNN, YOLOv5, and YOLOv8. Our findings show baseline models degrade in complex conditions, while our approach improves using CBAM. YOLOv8-CBAM outperformed YOLOv8 by 2.3% in mAP, achieving 95.2% precision and an mAP@0.5:0.95 of 82.6%, demonstrating superior accuracy. Contributions include (1) analyzing detection limitations, (2) proposing a robust model, and (3) benchmarking state-of-the-art algorithms. Applications include health monitoring, behavioral analysis, and tracking in smart farms, enabling precise detection in challenging settings. This study advances AI-driven livestock monitoring, improving animal welfare and smart agriculture.

The property of $*$-cleanness in group rings has been studied for some groups considering the classical involution, given by $g^*=g^{-1}$. A group is called an SLC-group if its quotient by its center is isomorphic to the Klein group; these groups are equipped with its own canonical involution, which usually does not coincide with the classical one. In this paper we study the $*$-cleanness of $RG$ when $G$ is an SLC-group, considering $*$ as its canonical involution. In that context, we prove that if $RG$ is $*$-clean then $G$ is the direct product of $Q_8$ and an abelian group with some extra properties and we find a converse for some specific cases, generalizing a result by Gao, Chen and Li for $Q_8$.

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

In this work, we analyze the impact of non-metricity on particle creation and the evaporation process of black holes within the framework of bumblebee gravity. In general lines, we compare black holes in the metric formalism [1] and the metric-affine approach [2]. Initially, we focus on bosonic particle modes to investigate Hawking radiation. Using the Klein-Gordon equation, we compute the Bogoliubov coefficients and derive the Hawking temperature. Subsequently, we examine Hawking radiation as a tunneling process, resolving divergent integrals through the residue method. The analysis is then extended to fermionic particle modes, also within the tunneling framework. Particle creation densities are calculated for both bosonic and fermionic cases. Additionally, greybody bounds are estimated for bosonic and fermionic particles. Finally, we explore the evaporation process, considering the final state of the black holes. In a general panorama, non-metricity in bumblebee gravity raises particle density for bosons while reducing it for fermions, increases greybody factors (for both bosons and fermions), amplifies the emission rate, and accelerates the evaporation process., Comment: 24 pages (in two columns) and 28 figures

In this paper, we study a Bhabha-like scattering in a massive Rarita-Schwinger model at finite temperature. The analysis is conducted at the tree level and addresses temperature effects through the thermofield dynamics formalism. We consider the usual fermion-antifermion into fermion-antifermion scattering and compute the cross-section in order to investigate the influence of the finite temperature effects., Comment: 21 pages, 7 figures

The dynamic magnetic properties of Full Heusler alloy thin films of Co$_2$FeGe, grown on MgO (001) substrates under different thermal conditions, were investigated. Brillouin light scattering and ferromagnetic resonance measurements revealed that depositing at room temperature followed by annealing at 300 deg C for 1 hour produces the best results for maximizing magnetization, exchange stiffness, and minimizing spin-dynamic dissipation in the films, which are desirable characteristics for high-speed spintronic devices. Additionally, strong hybridization of spin waves in the Damon-Eshbach geometry was observed, which is attractive for applications in magnonic signal processing circuits., Comment: 13 pages, 6 figures

Image processing has always been a topic of significant importance to society. Recently, this field has gained considerable prominence due to the development of intelligent systems. In this work, we present a new method of image processing that utilizes statistical analysis, specifically designed for applications in intelligent systems. We tested our method on a large collection of images to assess its effectiveness.

The radio pulsar PSR J0742-2822 is known to exhibit rapid changes between different pulse profile states that correlate with changes in its spin-down rate. However, the connection between these variations and the glitch activity of the pulsar remains unclear. We aim to study the evolution of the pulse profile and spin-down rate of PSR J0742-2822 in the period MJD 58810-60149 (November 2019 to July 2023), which includes the glitch on MJD 59839 (September 2022). In particular, we look for pulse profile or spin-down changes associated with the 2022 glitch. We observed PSR J0742-2822 with high cadence from the Argentine Institute of Radio astronomy (IAR) between November 2019 and July 2023. We used standard timing tools to characterize the times of arrival of the pulses and study the pulsar rotation, and particularly, the oscillations of $\dot \nu$. We also study the evolution of the pulse profile. For both of them, we compare their behavior before and after the 2022 glitch. With respect to $\dot \nu$, we found oscillations diminished in amplitude after the glitch. We found four different components contributing to the pre-glitch $\dot \nu$ oscillations, and only one component after the glitch. About the emission, we found the pulse profile has two main peaks. We detected an increase in the $W_{50}$ of the total pulse profile of $\sim$12% after the glitch and we found the amplitude of the trailing peak increased with respect to the amplitude of the leading one after the glitch. We found significant changes in the pulse profile and the spin-down rate of PSR J0742-2822 after its 2022 glitch. These results suggest that there is a strong coupling between the internal superfluid of the neutron star and its magnetosphere, and that pulse profile changes may be led by this coupling instead of being led purely by magnetospheric effects., Comment: 8 pages, 8 figures, submitted to A&A. Comments are welcome

We study a general class of elliptic free boundary problems equipped with a Dirichlet boundary condition. Our primary result establishes an optimal $C^{1,1}$-regularity estimate for $L^p$-strong solutions at points where the free and fixed boundaries intersect. A key novelty is that no convexity or concavity assumptions are imposed on the fully nonlinear operator governing the system. Our analysis derives BMO estimates in a universal neighbourhood of the fixed boundary. It relies solely on a differentiability assumption. Once those estimates are available, applying by now standard methods yields the optimal regularity.

This work introduces the Schmidt quantum compressor, an innovative approach to quantum data compression that leverages the principles of Schmidt decomposition to encode quantum information efficiently. In contrast to traditional variational quantum autoencoders, which depend on stochastic optimization and face challenges such as shot noise, barren plateaus, and non-convex optimization landscapes, our deterministic method substantially reduces the complexity and computational overhead of quantum data compression. We evaluate the performance of the compressor through numerical experiments, demonstrating its ability to achieve high fidelity in quantum state reconstruction compared to variational quantum algorithms. Furthermore, we demonstrate the practical utility of the Schmidt quantum compressor in one-class classification tasks.

Boundaries in gauge theory and gravity give rise to symmetries and charges at both finite and asymptotic distance. Due to their structural similarities, it is often held that soft modes are some kind of asymptotic limit of edge modes. Here, we show in Maxwell theory that there is an arguably more interesting relationship between the \emph{asymptotic} symmetries and their charges, on one hand, and their \emph{finite-distance} counterparts, on the other, without the need of a limit. Key to this observation is to embed the finite region in the global spacetime and identify edge modes as dynamical $\rm{U}(1)$-reference frames for dressing subregion variables. Distinguishing \emph{intrinsic} and \emph{extrinsic} frames, according to whether they are built from field content in- or outside the region, we find that non-trivial corner symmetries arise only for extrinsic frames. Further, the asymptotic-to-finite relation requires asymptotically charged ones (like Wilson lines). Such frames, called \emph{soft edges}, extend to asymptotia and realize the corner charge algebra by ``pulling in'' the asymptotic one from infinity. Realizing an infinite-dimensional algebra requires a new set of \emph{soft boundary conditions}, relying on the distinction between extrinsic and intrinsic data. We identify the subregion Goldstone mode as the relational observable between extrinsic and intrinsic frames and clarify the meaning of vacuum degeneracy. We also connect the asymptotic memory effect with a more operational \emph{quasi-local} one. A main conclusion is that the relationship between asymptotia and finite distance is \emph{frame-dependent}; each choice of soft edge mode probes distinct cross-boundary data of the global theory. Our work combines the study of boundary symmetries with the program of dynamical reference frames and we anticipate that core insights extend to Yang-Mills theory and gravity., Comment: 69 pages, 13 figures

This work presents a novel methodology for deriving stationary and axially symmetric solutions to Einstein field equations using the 1+3 tetrad formalism. This approach reformulates the Einstein equations into first order scalar equations, enabling systematic resolution in vacuum scenarios. We derive two distinct solutions in polar and hyperbolic geometries by assuming the separability of a key metric function. Our method reproduces well known solutions such as Schwarzschild and Kerr metrics and extends the case of rotating spacetimes to hyperbolic configurations. Additionally, we explore the role of Killing tensors in enabling separable metric components, simplifying analyses of geodesic motion and physical phenomena. This framework demonstrates robustness and adaptability for addressing the complexities of axially symmetric spacetimes, paving the way for further applications to Kerr like solutions in General Relativity.

This paper explores gravitational phenomena associated with a non-commutative black hole. Geodesic equations are derived, and a thin accretion disk is analyzed to model the black hole shadow image, considering an optically thin, radiating, and infalling gas. Retrolensing effects are examined to trace photon emission configurations, while gravitational lensing is investigated through weak and strong deflection limits, with lensing equations and observables applied to Sagittarius A*. The study also includes calculations of time delay, energy deposition rate from neutrino annihilation, phase and probability of neutrino oscillation, and neutrino gravitational lensing., Comment: 26 pages, 9 figures and 2 tables

The particles of synthetic colloids are usually treated with chemical techniques to prevent the loss of colloidal stability caused by van der Waals and magnetic dipolar attractive interactions. However, understanding the counterbalance between the attractive and repulsive interactions is challenging due to the limitations of the conventional mesoscopic models at short nanoparticle separations. In this study, we examined three models that describe short-range interactions by proposing different corrections to the van der Waals energy for short distances. The three models show only a minimal deviation from energy extensivity, as expected of a system with a comparatively short interaction range. Our analysis shows that a more detailed microscopic model at short-range separations is crucial for proper sampling, which is necessary to estimate physical quantities adequately. The same model predicts that polydispersity can lead to an overall decrease in mean particle distance for a configuration with 5% colloidal volume fraction. The other, simpler models make the opposite prediction, which opens an interesting venue for experimental exploration that could shed light on the validity of this model. The predicted decrease in particle distance could lead to coagulation, suggesting a preference for ferrofluids with more uniform particle sizes, leading to lower attraction, but still responding to applied fields, as needed in most applications., Comment: 17 pages (11 main text + 6 supplementary), 10 figures (5 main text + 5 supplementary)

3D human motion generation has seen substantial advancement in recent years. While state-of-the-art approaches have improved performance significantly, they still struggle with complex and detailed motions unseen in training data, largely due to the scarcity of motion datasets and the prohibitive cost of generating new training examples. To address these challenges, we introduce CoMA, an agent-based solution for complex human motion generation, editing, and comprehension. CoMA leverages multiple collaborative agents powered by large language and vision models, alongside a mask transformer-based motion generator featuring body part-specific encoders and codebooks for fine-grained control. Our framework enables generation of both short and long motion sequences with detailed instructions, text-guided motion editing, and self-correction for improved quality. Evaluations on the HumanML3D dataset demonstrate competitive performance against state-of-the-art methods. Additionally, we create a set of context-rich, compositional, and long text prompts, where user studies show our method significantly outperforms existing approaches., Comment: Project Page: https://gabrie-l.github.io/coma-page/

This work examines the implications of a black hole featuring a de Sitter core. We begin by analyzing the spacetime and event horizon in the presence of de Sitter core. Then the partial wave equation necessary for calculating quasinormal modes is derived and the relation of scalar quasinormal modes with the de Sitter core parameter is explored. Subsequently, we explore the greybody factors and their correspondence with the gravitational quasinormal modes. We also analyze the emission rate. Finally, variations in the thin accretion disks and the influence of de Sitter core spacetime on the optical appearance of the black hole are discussed as well.

We report on a search for millicharged particles (mCPs) produced in cosmic ray proton atmospheric interactions using data collected during the first science run of the LUX-ZEPLIN experiment. The mCPs produced by two processes -- meson decay and proton bremsstrahlung -- are considered in this study. This search utilized a novel signature unique to liquid xenon (LXe) time projection chambers (TPCs), allowing sensitivity to mCPs with masses ranging from 10 to 1000 MeV/c$^2$ and fractional charges between 0.001 and 0.02 of the electron charge e. With an exposure of 60 live days and a 5.5 tonne fiducial mass, we observed no significant excess over background. This represents the first experimental search for atmospheric mCPs and the first search for mCPs using an underground LXe experiment.

The properties of the entire neutron star population can be inferred by modeling their evolution, from birth to the present, through pulsar population synthesis. This involves simulating a mock population, applying observational filters, and comparing the resulting sources to the limited subset of detected pulsars. We specifically focus on the magneto-rotational properties of Galactic isolated neutron stars and provide new insights into the intrinsic radio luminosity law by combining pulsar population synthesis with a simulation-based inference (SBI) technique called truncated sequential neural posterior estimation (TSNPE). We employ TSNPE to train a neural density estimator on simulated pulsar populations to approximate the posterior distribution of the underlying parameters. This technique efficiently explores the parameter space by concentrating on regions that are most likely to match the observed data thus allowing a significant reduction in training dataset size. We demonstrate the efficiency of TSNPE over standard neural posterior estimation (NPE), achieving robust inferences of magneto-rotational parameters consistent with previous studies using only around 4% of the simulations required by NPE approaches. Moreover, for the first time, we incorporate data from the Thousand Pulsar Array (TPA) program on MeerKAT, the largest unified sample of neutron stars with consistent fluxes measurement to date, to help constrain the stars' intrinsic radio luminosity. We find that adding flux information as an input to the neural network largely improves the constraints on the pulsars' radio luminosity, as well as improving the estimates on other input parameters.

The channel estimation problem has been widely discussed in traditional reconfigurable intelligent surface assisted multiple-input multiple-output. However, solutions for channel estimation adapted to beyond diagonal RIS need further study, and few recent works have been proposed to tackle this problem. Moreover, methods that avoid or minimize the use of pilot sequences are of interest. This work formulates a data-driven (semi-blind) joint channel and symbol estimation algorithm for beyond diagonal RIS that avoids a prior pilot-assisted stage while providing decoupled estimates of the involved communication channels. The proposed receiver builds upon a PARATUCK tensor model for the received signal, from which a trilinear alternating estimation scheme is derived. Preliminary numerical results demonstrate the proposed method's performance for selected system setups. The symbol error rate performance is also compared with that of a linear receiver operating with perfect knowledge of the cascaded channel.

The propagation of light that undergoes multiple-scattering by resonant atomic vapor can be described as a L\'evy flight. L\'evy flight is a random walk with heavy tailed step-size (r) distribution, decaying asymptotically as $P(r)\sim r^{-1-\alpha}$, with $\alpha<2$. The large steps, typical of L\'evy flights, have its origins in frequency redistribution of the light scattered by the vapor. We calculate the frequency redistribution function and the step-size distribution for light diffusion in atomic vapor. From the step-size distribution we extract a L\'evy parameter $\alpha$ that depends on the step's size. We investigate how the frequency redistribution function and step-size distribution are influenced by the finite size of the vapor and the many-level structure typical for alkali vapors. Finite size of the vapor introduces cutoff on the light scattered spectrum and thus in the size of steps. Multi-level structure introduces oscillations in $P(r)$ slope. Both effects might have an impact on measurables related to the L\'evy flight random walk., Comment: 37 pages, 12 figures

Liquid argon detectors rely on wavelength shifters for efficient detection of scintillation light. The current standard is tetraphenyl butadiene (TPB), but it is challenging to instrument on a large scale. Poly(ethylene 2,6-naphthalate) (PEN), a polyester easily manufactured as thin sheets, could simplify the coverage of large surfaces with wavelength shifters. Previous measurements have shown that commercial grades of PEN have approximately 50% light conversion efficiency relative to TPB. Encouraged by these results, we conducted a large-scale measurement using $4~m^2$ combined PEN and specular reflector foils in a two-tonne liquid argon dewar to assess its stability over approximately two weeks. This test is crucial for validating PEN as a viable substitute for TPB. The setup used for the measurement of the stability of PEN as a wavelength shifter is described, together with the first results, showing no evidence of performance deterioration over a period of 12 days., Comment: 10 pages, 13 figures

Fog Computing provides computational resources close to the end user, supporting low-latency and high-bandwidth communications. It supports IoT applications, enabling real-time data processing, analytics, and decision-making at the edge of the network. However, the high distribution of its constituent nodes and resource-restricted devices interconnected by heterogeneous and unreliable networks makes it challenging to execute service maintenance and troubleshooting, increasing the time to restore the application after failures and not guaranteeing the service level agreements. In such a scenario, increasing the observability of Fog applications and services may speed up troubleshooting and increase their availability. An observability system is a data-intensive service, and Fog Computing could have its nodes and channels saturated with an additional load. In this work, we detail the three pillars of observability (metrics, log, and traces), discuss the challenges, and clarify the approaches for increasing the observability of services in Fog environments. Furthermore, the system architecture that supports observability in Fog, related tools, and technologies are presented, providing a comprehensive discussion on this subject. An example of a solution shows how a real-world application can benefit from increased observability in this environment. Finally, there is a discussion about the future directions of Fog observability.

We propose a $U(1)_{B-L}$ gauge extension to the SM, in which the dark sector is stabilized through a matter parity symmetry preserved after spontaneous symmetry breaking. The fermion spectrum includes three neutral right-handed fields with $B-L$ charges $(-4,-4, 5)$, that make the model free of gauge anomalies. Two of these neutral fermion fields serve as mediators in a scotogenic mechanism for light-active Majorana neutrino masses. The corresponding neutrino mass matrix has rank 2, predicting a massless state and a lower bound for neutrinoless double beta decay. Regions in the parameter space consistent with dark matter relic abundance are accomplished by the lightest neutral mediator.

In face of climate change and increasing urbanization, the predictive mosquito-borne diseases (MBD) transmission models require constant updates. Thus, is urgent to comprehend the driving forces of this non stationary behavior, observed through spatial and incidence expansion. We observed that temperature is a critical driver in predictive models for MBD transmission, also being consistently used in multiple reviewed papers with considerable incidence predictive capacity. Rainfall, however, have more subtle importance as moderate precipitation creates breeding sites for mosquitoes, but excessive rainfall can reduce larvae populations. We highlight the frequent use of mechanistic models, particularly those that integrate temperature-dependent biological parameters of disease transmission in incidence proxies as the Vectorial Capacity (VC) and temperature-based basic reproduction number $R_0(t)$, for example. These models show the importance of climate variables, but the socio-demographic factors are often not considered. This gap is a significant opportunity for future research to incorporate socio-demographic data into long-term predictive models for more comprehensive and reliable forecasts. With this survey, we outline the most promising paths to be followed by long-term MBD transmission research and highlighting the potential facing challenges. Thus, we offer a valuable foundation for enhancing disease forecasting models and supporting more effective public health interventions, specially in the long term.

This work investigates the application of the Newton's method for the numerical solution of a nonlinear boundary value problem formulated through an ordinary differential equation (ODE). Nonlinear ODEs arise in various mathematical modeling contexts, where an exact solution is often unfeasible due to the intrinsic complexity of these equations. Thus, a numerical approach is employed, using Newton's method to solve the system resulting from the discretization of the original problem. The procedure involves the iterative formulation of the method, which enables the approximation of solutions and the evaluation of convergence with respect to the problem parameters. The results demonstrate that Newton's method provides a robust and efficient solution, highlighting its applicability to complex boundary value problems and reinforcing its relevance for the numerical analysis of nonlinear systems. It is concluded that the methodology discussed is suitable for solving a wide range of boundary value problems, ensuring precision and stability in the results., Comment: 9 pages, 2 figures

In this paper, frequency dynamics in modern power systems with a high penetration of converter-based generation is analysed. A fundamental analysis of the frequency dynamics is performed to identify the limitations and challenges when the converter penetration is increased. The voltage-source behaviour is found as an essential characteristic of converters to improve the initial frequency derivative of Synchronous Generators (SGs). A detailed small-signal analysis, based on the system's eigenvalues, participation factors and mode shapes, is then performed in a reduced system for different converter penetrations, showing that the flexibility of grid-forming (GFOR) converters as well as the system's inertia reduction may lead to have a more controllable system frequency. First-order frequency responses can be programmed for high converter penetrations, when GFOR operation can impose their dominance over SGs. These results have been validated in the IEEE 118-bus system simulated in PSCAD., Comment: 11 pages, 17 figures

In this work, we examine particle creation and the evaporation process in the context of Kalb-Ramond gravity. Specifically, we build upon two existing solutions from the literature \cite{yang2023static} and \cite{Liu:2024oas}, both addressing a static, spherically symmetric configuration. For this study, we focus on the scenario in which the cosmological constant vanishes. To begin, the corrections to Hawking radiation for bosonic modes are examined by studying the Klein-Gordon equation in curved spacetime. Through the calculation of Bogoliubov coefficients, we identify how the parameter $\ell$, which governs Lorentz symmetry breaking, contributes a correction to the amplitude associated with particle production. Within this approach, the power spectrum and Hawking temperature are derived. Additionally, we obtain expressions for the power spectrum and particle number density by analyzing Hawking radiation from a tunneling viewpoint. A parallel approach is applied to fermionic modes. Finally, we examine black hole evaporation, finding that the black hole lifetime in these cases can be determined analytically., Comment: 14 pages, and 11 figures

In this paper, we investigate the influence of the geometry in the electronic states of a quantum ripple surface. We have considered an electron governed by the spinless stationary Schr\"{o}dinger equation constrained to move on the ripple surface due to a confining potential from which the Da Costa potential emerges. We investigate the role played by the geometry and orbital angular momentum on the electronic states of the system., Comment: 8 pages, two column, 7 figures

Yttrium calcium aluminate, with the formula CaYAl3O7, has been extensively researched due to its remarkable luminescent properties when doped or co-doped. Additionally, it exhibits exceptional piezoelectric properties at high temperatures. However, the potential magnetic properties this material can acquire through doping or co-doping have largely gone unexplored until now. In this innovative study, we investigate the quantum magnetic characteristics of yttrium calcium aluminate particles doped with transition metals such as cobalt, iron, and nickel. Our magnetic measurements of hysteresis curves in the macroscopic regime reveal intriguing magnetic characteristics that have not been documented in the literature. Given the high applicability of this material in biological microelectromechanical systems, we conducted a detailed study to demonstrate these findings.

In this work, we start by examining a spherically symmetric black hole within the framework of non-commutative geometry and apply a modified Newman-Janis method to obtain a new rotating solution. We then investigate its consequences, focusing on the horizon structure, ergospheres, and the black hole's angular velocity. Following this, a detailed thermodynamic analysis is performed, covering surface gravity, Hawking temperature, entropy, and heat capacity. We also study geodesic motion, with particular emphasis on null geodesics and their associated radial accelerations. Additionally, the photon sphere and the resulting black hole shadows are explored. Finally, we compute the quasinormal modes for scalar perturbations using the 6th-order WKB approximation., Comment: 37 pages, 16 figures and 2 tables

In this study, we aim to enhance radiology reporting by improving both the conciseness and structured organization of findings (also referred to as templating), specifically by organizing information according to anatomical regions. This structured approach allows physicians to locate relevant information quickly, increasing the report's utility. We utilize Large Language Models (LLMs) such as Mixtral, Mistral, and Llama to generate concise, well-structured reports. Among these, we primarily focus on the Mixtral model due to its superior adherence to specific formatting requirements compared to other models. To maintain data security and privacy, we run these LLMs locally behind our institution's firewall. We leverage the LangChain framework and apply five distinct prompting strategies to enforce a consistent structure in radiology reports, aiming to eliminate extraneous language and achieve a high level of conciseness. We also introduce a novel metric, the Conciseness Percentage (CP) score, to evaluate report brevity. Our dataset comprises 814 radiology reports authored by seven board-certified body radiologists at our cancer center. In evaluating the different prompting methods, we discovered that the most effective approach for generating concise, well-structured reports involves first instructing the LLM to condense the report, followed by a prompt to structure the content according to specific guidelines. We assessed all prompting strategies based on their ability to handle formatting issues, reduce report length, and adhere to formatting instructions. Our findings demonstrate that open-source, locally deployed LLMs can significantly improve radiology report conciseness and structure while conforming to specified formatting standards.

Cages ($r$-regular graphs of girth $g$ and minimum order) and their variants have been studied for over seventy years. Here we propose a new variant, "weighted cages". We characterize their existence; for cases $g=3,4$ we determine their order; we give Moore-like bounds and present some computational results.

We report the enhancement of quantum correlations for biphotons generated via spontaneous four-wave mixing in an ensemble of cold two-level atoms. This enhancement is based on the filtering of the Rayleigh linear component of the spectrum of the two emitted photons, favoring the quantum-correlated sidebands reaching the detectors. We provide direct measurements of the unfiltered spectrum presenting its usual triplet structure, with Rayleigh central components accompanied by two peaks symmetrically located at the detuning of the excitation laser with respect to the atomic resonance. The filtering of the central component results in a violation of the Cauchy-Schwarz inequality to $4.8 \pm 1.0 \leq 1$ for a detuning of 60 times the atomic linewidth, representing an enhancement by a factor of four compared with the unfiltered quantum correlations observed at the same conditions., Comment: 5 pages, 4 figures

We explore the gravitational properties of a nonlinear electromagnetic extension of an AdS Reissner-Nordstr\"om black hole. Our study begins with an analysis of the metric function and horizon structure, followed by calculations of the Ricci and Kretschmann scalars and an evaluation of the non-vanishing Christoffel symbols. These calculations allow us to examine geodesics and their influence on the photon sphere, shadow formation, and bending angle. In the thermodynamic framework, we evaluate essential quantities, including the Hawking temperature, entropy, heat capacity, Gibbs free energy, and Hawking radiation emission. We further investigate black hole evaporation by estimating the evaporation timescale as the black hole approaches its final state. Additionally, quasinormal modes for scalar and vector perturbations are computed using the WKB approximation to characterize oscillatory behavior of the system. Finally, a time-domain analysis is provided in order to examine the evolution of these perturbations., Comment: 45 pages, 20 figures, and 7 tables -- version accepted for publication in Journal of Cosmology and Astroparticle Physics

Very-high-energy (0.1-100 TeV) gamma-ray emission was observed in HAWC data from the lobes of the microquasar SS 433, making them the first set of astrophysical jets that were resolved at TeV energies. In this work, we update the analysis of SS 433 using 2,565 days of data from the High Altitude Water Cherenkov (HAWC) observatory. Our analysis reports the detection of a point-like source in the east lobe at a significance of $6.6\,\sigma$ and in the west lobe at a significance of $8.2\,\sigma$. For each jet lobe, we localize the gamma-ray emission and identify a best-fit position. The locations are close to the X-ray emission sites "e1" and "w1" for the east and west lobes, respectively. We analyze the spectral energy distributions and find that the energy spectra of the lobes are consistent with a simple power-law $\text{d}N/\text{d}E\propto E^{\alpha}$ with $\alpha = -2.44^{+0.13+0.04}_{-0.12-0.04}$ and $\alpha = -2.35^{+0.12+0.03}_{-0.11-0.03}$ for the east and west lobes, respectively. The maximum energy of photons from the east and west lobes reaches 56 TeV and 123 TeV, respectively. We compare our observations to various models and conclude that the very-high-energy gamma-ray emission can be produced by a population of electrons that were efficiently accelerated.

Quantum correlations in four-wave-mixing from ensembles of cold two-level atoms may prevail without filtering over background light with well-known classical interpretations, such as Rayleigh scattering, as recently experimentally demonstrated in Phys. Rev. Lett. {\bf 128}, 083601 (2022). Here we provide an extended investigation of this effect, in which we detail the experimental procedure and the variation of the quantum correlation with various parameters of the system. Particularly, we show that the decay rate of the quantum correlations changes with the number of atoms in the sample, providing another indication of its superradiance-like nature. The nonclassical aspects of the signal occur for short timescales, but the long timescales carry as well a lot of information on the classical correlations of the system. This slow classical regime presents also two clearly distinct timescales, which we explain by two different pathways for the creation of biphotons. From the global analysis of the data in all its timescales, we are able to derive an empirical expression to fit the data, resulting in information on, among other parameters, the sample's temperature and superradiant-like acceleration. In general, the reported quantum correlations present a dependence on critical parameters of the system, such as optical depth and excitation power, that is quite different from other systems used for biphoton generation, and are more robust to changes in these parameters. This opens the possibility of exploring this process for efficient generation of narrow-band biphotons or of other quantum-correlated photonic states of higher order., Comment: 14 pages, 16 figures

A set of n non-collinear points in the Euclidean plane defines at least n different lines. Chen and Chv\'tal in 2008 conjectured that the same results is true in metric spaces for an adequate definition of line. More recently, it was conjectured in 2018 by Aboulker et al. that any large enough bridgeless graph on n vertices defines a metric space that has at least n lines. We study the natural extension of Aboulker et al.'s conjecture into the context of quasi-metric spaces defined by digraphs of low diameter. We prove that it is valid for quasi-metric spaces defined by bipartite digraphs of diameter at most three, oriented graphs of diameter two and, digraphs of diameter three and directed girth four.

The vector notation adopted by GNU Octave plays a significant role as a tool for introspection, aligning itself with the vision of Kenneth E. Iverson. He believed that, just like mathematics, a programming language should be an effective thinking tool for representing and reasoning about problems we wish to address. This work aims to explore the use of vector notation in GNU Octave through the analysis of operators and functions, providing a closer alignment with mathematical notation and enhancing code efficiency. We will delve into fundamental concepts such as indexing, broadcasting, and function handles, and present case studies for a deeper understanding of these concepts. By adopting vector notation, GNU Octave becomes a powerful tool for mathematicians, scientists and engineers, enabling them to express and solve complex problems more effectively and intuitively., Comment: 22 pages, 1 figure (3 subfigures)

Constrained multiobjective optimization problems (CMOPs) are commonly found in real-world applications. CMOP is a complex problem that needs to satisfy a set of equality or inequality constraints. This paper proposes a variant of the bidirectional coevolution algorithm (BiCo) with differential evolution (DE). The novelties in the model include the DE differential mutation and crossover operators as the main search engine and a non-dominated sorting selection scheme. Experimental results on two benchmark test suites and eight real-world CMOPs suggested that the proposed model reached better overall performance than the original model., Comment: 6 pages

This paper introduces the inverse modeling constrained multi-objective evolutionary algorithm based on decomposition (IM-C-MOEA/D) for addressing constrained real-world optimization problems. Our research builds upon the advancements made in evolutionary computing-based inverse modeling, and it strategically bridges the gaps in applying inverse models based on decomposition to problem domains with constraints. The proposed approach is experimentally evaluated on diverse real-world problems (RWMOP1-35), showing superior performance to state-of-the-art constrained multi-objective evolutionary algorithms (CMOEAs). The experimental results highlight the robustness of the algorithm and its applicability in real-world constrained optimization scenarios., Comment: 6 pages, 1 figure, 1 algorithm, and 2 tables

Dengue is a climate-sensitive mosquito-borne disease with a complex transmission dynamic. Data related to climate, environmental and sociodemographic characteristics of the target population are important for project scenarios. Different datasets and methodologies have been applied to build complex models for dengue forecast, stressing the need to evaluate these models and their relative accuracy grounded on a reproducible methodology. The goal of this work is to describe and present Mosqlimate, a web-based platform composed by a dashboard, a data store, model and rediction registries and support for a community of practice in arbovirus forecasting. Multiple API endpoints give access to data for development, open registration of predictive models from different approaches and sharing of predictive models for arboviruses incidence, facilitating interaction between modellers and allowing for proper comparison of the performance of different registered models, by means of probabilistic scores. Epidemiological, entomological, climatic and sociodemographic datasets related to arboviruses in Brazil, are freely available for download, alongside full documentation., Comment: 10 pages, 2 figures, 6 tables