December 2024 arXiv papers — page 116

Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga, Gianandrea Minneci

Knowledge graphs use nodes, relationships, and properties to represent arbitrarily complex data. When stored in a graph database, the Cypher query language enables efficient modeling and querying of knowledge graphs. However, using Cypher requires specialized knowledge, which can present a challenge for non-expert users. Our work Text2Cypher aims to bridge t

Enrique Barba Roque, Luis Cruz, Thomas Durieux

Energy consumption in software systems is becoming increasingly important, especially in large-scale deployments. However, debugging energy-related issues remains challenging due to the lack of specialized tools. This paper presents an energy debugging methodology for identifying and isolating energy consumption hotspots in software systems. We demonstrate t

Futa Tomita, Jun-nosuke Teramae

Large-scale systems with inherent heterogeneity often exhibit complex dynamics that are crucial for their functional properties. However, understanding how such heterogeneity shapes these dynamics remains a significant challenge, particularly in systems with widely varying time scales. To address this, we extend Dynamical Mean Field Theory$\unicode{x2014}$a

Tuur Stuyck, Gene Wei-Chin Lin, Egor Larionov, Hsiao-yu Chen

Realistic hair motion is crucial for high-quality avatars, but it is often limited by the computational resources available for real-time applications. To address this challenge, we propose a novel neural approach to predict physically plausible hair deformations that generalizes to various body poses, shapes, and hairstyles. Our model is trained using a sel

Jacob P. Crossett, Yara L. Jaffé, Sean L. McGee, Rory Smith

Ram pressure stripped galaxies are rare cases of environmental evolution in action. However, our ability to understand these galaxies is limited by the small number of identified galaxies experiencing ram pressure stripping (RPS). Our aim is to explore the efficacy of citizen science classifications in identifying ram pressure stripped galaxies, and use this

Dongyun Kam, Myeongji Yun, Sunwoo Yoo, Seungwoo Hong

Low bit-precisions and their bit-slice sparsity have recently been studied to accelerate general matrix-multiplications (GEMM) during large-scale deep neural network (DNN) inferences. While the conventional symmetric quantization facilitates low-resolution processing with bit-slice sparsity for both weight and activation, its accuracy loss caused by the acti

Avinandan Mondal, Dawood Kothawala

We discuss the structure of microcanonical ensembles in inertial and non-inertial frames attached to a confined system of positive energy particles in curved spacetime. Under certain physically reasonable assumptions that ensure the existence of such ensembles, we obtain, for microcanonical ensembles, exact analytical results in certain stationary spacetimes

Salvatore Muratore, Danilo Triggiani, Vincenzo Tamma

The Rayleigh's criterion infamously imposes a minimum separation between two incoherent sources for them to be distinguishable via classical methods. In this work, we demonstrate the emergence of two-photon beats from the interference of a single reference photon and a photon coming from one of two transversally displaced incoherent sources. We also show tha

Zhikai Lei, Tianyi Liang, Hanglei Hu, Jin Zhang

Large Language Models (LLMs) are commonly evaluated using human-crafted benchmarks, under the premise that higher scores implicitly reflect stronger human-like performance. However, there is growing concern that LLMs may ``game" these benchmarks due to data leakage, achieving high scores while struggling with tasks simple for humans. To substantively address

Gerhard Hiss, Frank Lübeck

Using computational methods, we determine the irreducible Brauer characters of the automorphism group of the Chevalley group F_4(2), up to one parameter and one consistency issue.

Debarghya Datta, Soumajit Pramanik

In the ever-evolving landscape of natural language processing and information retrieval, the need for robust and domain-specific entity linking algorithms has become increasingly apparent. It is crucial in a considerable number of fields such as humanities, technical writing and biomedical sciences to enrich texts with semantics and discover more knowledge.

Daniel Wrench, Tulasi N. Parashar

Structure functions, which represent the moments of the increments of a stochastic process, are essential complementary statistics to power spectra for analysing the self-similar behaviour of a time series. However, many real-world environmental datasets, such as those collected by spacecraft monitoring the solar wind, contain gaps, which inevitably corrupt

Xingyu Xiao, Peng Chen

The Fussell-Vesely Importance (FV) reflects the potential impact of a basic event on system failure, and is crucial for ensuring system reliability. However, traditional methods for calculating FV importance are complex and time-consuming, requiring the construction of fault trees and the calculation of minimal cut set. To address these limitations, this stu

Alexandre Parriaux, Kenichi N. Komagata, Mathieu Bertrand, Mattias Beck

Optical injection locking of the repetition frequency of a quantum cascade laser frequency comb is demonstrated using an intensity modulated near-infrared light at 1.55 $\mu$m illuminating the front facet of the laser. Compared to the traditional electrical modulation approach, the introduced technique presents benefits from several perspectives such as the

Roberto Daza, Alvaro Becerra, Ruth Cobos, Julian Fierrez

This work presents the IMPROVE dataset, a multimodal resource designed to evaluate the effects of mobile phone usage on learners during online education. It includes behavioral, biometric, physiological, and academic performance data collected from 120 learners divided into three groups with different levels of phone interaction, enabling the analysis of the

Liang Zhao, Zehan Bao, Yi Xie, Hong Chen

Recent advances in Gaussian Splatting have significantly advanced the field, achieving both panoptic and interactive segmentation of 3D scenes. However, existing methodologies often overlook the critical need for reconstructing specified targets with complex structures from sparse views. To address this issue, we introduce TSGaussian, a novel framework that

Taewhan Kim, Hojin Bae, Zeming Li, Xiaoqi Li

Visual actionable affordance has emerged as a transformative approach in robotics, focusing on perceiving interaction areas prior to manipulation. Traditional methods rely on pixel sampling to identify successful interaction samples or processing pointclouds for affordance mapping. However, these approaches are computationally intensive and struggle to adapt

Runyi Hu, Jie Zhang, Yiming Li, Jiwei Li

In today's digital landscape, the blending of AI-generated and authentic content has underscored the need for copyright protection and content authentication. Watermarking has become a vital tool to address these challenges, safeguarding both generated and real content. Effective watermarking methods must withstand various distortions and attacks. Current de

Hanna Müller, Victor Kartsch, Michele Magno, Luca Benini

Nano-drones, with their small, lightweight design, are ideal for confined-space rescue missions and inherently safe for human interaction. However, their limited payload restricts the critical sensing needed for ego-velocity estimation and obstacle detection to single-bean laser-based time-of-flight (ToF) and low-resolution optical sensors. Although those se

Lu Wang, Fangkai Yang, Chaoyun Zhang, Junting Lu

As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actions. This evolution requires the transition from traditional Large Language Models (LLMs), which excel at generating textual responses, to Large Action Models (LAMs), designed for a

Juno C. L. Chan, Harry Ho-Yin Ng, Patrick Chi-Kit Cheong

We present the first general relativistic, neutrino-radiation hydrodynamics simulations of accretion-induced collapse (AIC) extending to seconds after core bounce, using realistic hadron-quark hybrid equations of state (EOSs). A first-order QCD phase transition (PT) triggers a second dynamical collapse and the formation of a quasistable protohybrid star (PHS

Xiaoxu Li, Xucheng Meng

In this paper, we study the multi-patch discontinuous Galerkin isogeometric (DG-IGA) approximations for full-potential electronic structure calculations. We decompose the physical domain into several subdomains, represent each part of the wavefunction separately using B-spline basis functions, possibly with different degrees, on varying mesh sizes, and then

Yuanhao Cheng, Hanyu Bai, Yichen Liang, Xiaofan Cui

Battery degradation modes influence the aging behavior of Li-ion batteries, leading to accelerated capacity loss and potential safety issues. Quantifying these aging mechanisms poses challenges for both online and offline diagnostics in charging station applications. Data-driven algorithms have emerged as effective tools for addressing state-of-health issues

Jose A. Vílchez Membrilla, Ignacio Mateos, Ángel Quirós-Olozábal, Mario F. Pantoja

Here a minimum power dissipation coil transducer has been designed to allow in-flight noise characterization of a low-frequency magnetic measurement system. The coil was produced using PCB technology to provide mechanical stability and easy integration close to the magnetic sensors. The transducer design strategy relies on an inverse boundary element method,

Hao Zhang

This paper studies the noncommutative singularity theory of the double $A_n$ quiver $Q_n$ (with a single loop at each vertex), with applications to algebraic geometry and representation theory. We give various intrinsic definitions of a Type A potential on $Q_n$, then via coordinate changes we (1) prove a monomialization result that expresses these potential

Repana Devendra, Pankaj Dey, Santanu Dey

Let $\rho_1$ and $\rho_2$ be two states on $\mathbb{C}^{d_1}$ and $\mathbb{C}^{d_2}$ respectively. The marginal state space, denoted by $\mathcal{C}(\rho_1,\rho_2)$, is the set of all states $\rho$ on $\mathbb{C}^{d_1}\otimes \mathbb{C}^{d_2}$ with partial traces $\rho_1, \rho_2$. K. R. Parthasarathy established that if $\rho$ is an extreme point of $\mathca

Chen Li, Rui Zhao, Zeyu Wang, Huiying Xu

Object detection in Unmanned Aerial Vehicle (UAV) images has emerged as a focal area of research, which presents two significant challenges: i) objects are typically small and dense within vast images; ii) computational resource constraints render most models unsuitable for real-time deployment. Current real-time object detectors are not optimized for UAV im

Anne Helby Petersen

New proposals for causal discovery algorithms are typically evaluated using simulations and a few selected real data examples with known data generating mechanisms. However, there does not exist a general guideline for how such evaluation studies should be designed, and therefore, comparing results across different studies can be difficult. In this article,

Gianmarco Callegher, Thomas Kneib, Johannes Söding, Paul Wiemann

Structured additive distributional regression extends generalized additive models by allowing all parameters of a response distribution to depend on structured additive predictors. Bayesian formulations regularize these models through prior distributions that enforce smoothness or shrinkage, but Markov chain Monte Carlo methods, the standard computational to

Xuerao He, Kengo Deguchi, Runjie Song, Hugh M. Blackburn

Shear-thinning fluids flowing through pipes are crucial in many practical applications, yet many unresolved problems remain regarding their turbulent transition. Using highly robust numerical tools for the Carreau-Yasuda model, we discovered that linear instability can arise when the power-law index falls below 0.35. This inelastic non-axisymmetric instabili

Manoj Kumar Yadav, Chirala Satyanarayana, A. Sreedhar

We generate Gaussian radial function based higher order compact RBF-FD formulas for some differential operators. Analytical expressions for weights associated to first and second derivative formulas (up to order 10) and 2D-Laplacian formulas (up to order 6) are derived. Then these weights are used to obtain analytical expression for local truncation errors.

Antonino Petralia, Jesús Maldonado, Giuseppina Micela

Context. The characterization of exoplanets requires a good description of the host star. Stellar activity acts as a source of noise which can alter planet radii as derived from the transit depth or atmospheric characterization. Aims. Here, we propose PAStar, a model to describe photospheric activity in the form of spots and faculae which could be applied to

Patricio Guerrero, Simon Bellens, Wim Dewulf

Motivated by industrial computed tomography, we propose a memory efficient strategy to estimate the regularization hyperparameter of a non-smooth variational model. The approach is based on a combination of FISTA and Condat-Vu algorithms exploiting the convergence rate of the former and the low per-iteration complexity of the latter. The estimation is cast a

Zhihang Song, Lihui Peng, Jianming Hu, Danya Yao

The multi-modal perception methods are thriving in the autonomous driving field due to their better usage of complementary data from different sensors. Such methods depend on calibration and synchronization between sensors to get accurate environmental information. There have already been studies about space-alignment robustness in autonomous driving object

Niclas Popp, Dan Zhang, Jan Hendrik Metzen, Matthias Hein

While unlabeled image data is often plentiful, the costs of high-quality labels pose an important practical challenge: Which images should one select for labeling to use the annotation budget for a particular target task most effectively? To address this problem, we focus on single-pass data selection, which refers to the process of selecting all data to be

Jizhihui Liu, Qixun Teng, Qing Ma, Junjun Jiang

Fluorescence microscopy image (FMI) denoising faces critical challenges due to the compound mixed Poisson-Gaussian noise with strong spatial correlation and the impracticality of acquiring paired noisy/clean data in dynamic biomedical scenarios. While supervised methods trained on synthetic noise (e.g., Gaussian/Poisson) suffer from out-of-distribution gener

Francesco Benetti, Andrea Lapi, Samuele Silveravalle, Stefano Liberati

In a series of recent papers it was shown that several aspects of Dark Matter (DM) phenomenology, such as the velocity profiles of individual dwarfs and spiral galaxies, the scaling relations observed in the latter, and the pressure and density profiles of galaxy clusters, can be explained by assuming the DM component in virialized halos to feel a non-local

Yeyuan Wang, Dehong Gao, Lei Yi, Linbo Jin

Existing Vision-Language Pretraining (VLP) methods have achieved remarkable improvements across a variety of vision-language tasks, confirming their effectiveness in capturing coarse-grained semantic correlations. However, their capability for fine-grained understanding, which is critical for many nuanced vision-language applications, remains limited. Prevai

Chang-Bin Zhang, Yujie Zhong, Kai Han

Existing methods enhance the training of detection transformers by incorporating an auxiliary one-to-many assignment. In this work, we treat the model as a multi-task framework, simultaneously performing one-to-one and one-to-many predictions. We investigate the roles of each component in the transformer decoder across these two training targets, including s

Giovanni Di Giannatale, Arnas Volčokas, Justin Ball, Alberto Bottino

This work aims at improving our understanding of the conditions enabling the development of an Internal transport barriers (ITB), using a more comprehensive physical model, including low-$\beta$ electromagnetic flux-driven simulations. Our key findings are that electron dynamics is crucial for ITB formation even in an ITG scenario and that having $q_{\text{m

Ruibang Liu, Minyu Chen, Ling-I Wu, Jingyu Ke

Automated program verification has always been an important component of building trustworthy software. While the analysis of real-world programs remains a theoretical challenge, the automation of loop invariant analysis has effectively resolved the problem. However, real-world programs that often mix complex data structures and control flows pose challenges

A. Naeimi, S. -A. Biehs

We reinvestigate the mechanism of near-field heat transfer rectification between two Weyl semimetal nanoparticles and a planar Weyl semimetal substrate via the coupling to non-reciprocal surface modes. We first show that the previously predicted rectification ratio of 2673 is incorrect and should rather be 1502. Furthermore we show that depending on the dist

Panchi Li, Xiao-Ping Wang

The dynamics of magnetization in ferromagnetic materials are modeled by the Landau-Lifshitz equation, which presents significant challenges due to its inherent nonlinearity and non-convex constraint. These complexities necessitate efficient numerical methods for micromagnetics simulations. The Gauss-Seidel Projection Method (GSPM), first introduced in 2001,

Jean-Michel Benkert, Ludmila Matyskova, Egor Starkov

A researcher allocates a budget of informative tests across multiple unknown attributes to influence a decision-maker. We derive the researcher's equilibrium learning strategy by solving an auxiliary single-player problem. The attribute weights in this problem depend on how much the researcher and the decision-maker disagree. If the researcher expects an exc

Eyal Ackerman, Gábor Damásdi, Balázs Keszegh, Rom Pinchasi

In 1972, Branko Gr\"unbaum conjectured that any arrangement of $n>2$ pairwise crossing pseudocircles in the plane can have at most $2n-2$ digons (regions enclosed by exactly two pseudoarcs), with the bound being tight. While this conjecture has been confirmed for cylindrical arrangements of pseudocircles and more recently for geometric circles, we extend the

Jingjing Wang, Hongjie Zhu, Haoran Xie, Fu Lee Wang

\Graph similarity computation is an essential task in many real-world graph-related applications such as retrieving the similar drugs given a query chemical compound or finding the user's potential friends from the social network database. Graph Edit Distance (GED) and Maximum Common Subgraphs (MCS) are the two commonly used domain-agnostic metrics to evalua

Wenhui Chen, Giovanni Girardi

In this paper we consider semilinear wave equation and other second order $\sigma$-evolution equations with different (effective or non-effective) damping mechanisms driven by fractional Laplace operators; in particular, the nonlinear term is the product of a power nonlinearity $|u|^p$ with the critical exponent $p=p_{\mathrm{c}}(n)$ and a modulus of continu

Zhenfeng Zhuang, Min Cen, Yanfeng Li, Fangyu Zhou

Significant disparities between the features of natural images and those inherent to histopathological images make it challenging to directly apply and transfer pre-trained models from natural images to histopathology tasks. Moreover, the frequent lack of annotations in histopathology patch images has driven researchers to explore self-supervised learning me

Zameddin I. Ismailov, Pembe Ipek Al

In this article, firstly, some simple and smoothness properties of the weighted numerical radius and the weighted Crawford number functions are investigated. Then, some generalization formulas for lower and upper bounds of the weighted numerical radius function are obtained. Later on, some evaluations for lower and upper bounds of the weighted numerical inde

Aleksandr Nesterenok

We study the absorption of a gamma-ray burst afterglow in a dense molecular cloud in the X-ray wavelength range. We report the results of numerical simulations of the propagation of the gamma-ray burst radiation in the cloud for various gas densities, metallicities, and distances from the gamma-ray burst progenitor star and the cloud. We consider a sample of

Federico Girotti, Damiano Poletti

Gaussian quantum Markov semigroups (GQMSs) are of fundamental importance in modelling the evolution of several quantum systems. Moreover, they represent the noncommutative generalization of classical Orsntein-Uhlenbeck semigroups; analogously to the classical case, GQMSs are uniquely determined by a "drift" matrix $\mathbf{Z}$ and a "diffusion" matrix $\math

Giulia Polverini, Jakob Melin, Elias Onerud, Bor Gregorcic

Artificial intelligence-based chatbots are increasingly influencing physics education due to their ability to interpret and respond to textual and visual inputs. This study evaluates the performance of two large multimodal model-based chatbots, ChatGPT-4 and ChatGPT-4o on the Brief Electricity and Magnetism Assessment (BEMA), a conceptual physics inventory r

Chen Qing, Jialong Cui, Lishuang Feng, Dengke Zhang

Manipulating vector beams is pivotal in fields such as particle manipulation, image processing, and quantum communication. Flexibly adjusting the intensity distribution of these beams is crucial for effectively realizing these applications. This study introduces a vectorial dual-beam system utilizing thermal atoms as the medium for modulating the intensity p

Petr Girg, Lukáš Kotrla, Anežka Švandová

The aim of this paper is to discuss several aspects of connections between the p-Laplacian and mathematical models in hydrology. At first we present models of groundwater flow in phreatic aquifers and models of irrigation and drainage that lead to quasilinear parabolic equations involving the p-Laplacian. Next, we survey conditions of validity of Strong Maxi

Francesco Coghi, Kristian Stølevik Olsen

We develop a framework for designing density-dependent stochastic resetting protocols to regulate distributions of random walkers on networks. Resetting mechanisms that depend on local densities induce correlations in otherwise non-interacting walkers. Our framework allows for the study of both transient trajectories and stationary properties and identifies

Irina V. Lebedeva, Sergey A. Vyrko, Alexander S. Sinitsa, Sergey V. Ratkevich

It has been proposed recently that 1D hybrid nanoobjects consisting of alternating double carbon chains and polycyclic carbon regions can be obtained from graphene nanoribbons of alternating width by electron irradiation. Here, based on density functional theory calculations, we show that magnetic and electronic properties of such nanoobjects can be changed

Iasson Karafyllis

This paper provides two results for the omega limit sets of a dynamical system. We show that omega limit sets can be estimated by using functions that satisfy different (and in many cases less demanding) assumptions than the usual assumptions in Lyapunov theorems and LaSalle's theorem.

Yao Yuan

Let $X$ be a projective smooth surface over $\mathbb{C}$ with $H^2(\mathcal{O}_X)=0$. Let $M=M(L,\chi)$ be the moduli space of 1-dimensional semistable sheaves with determinant $\mathcal{O}_X(L)$ and Euler characteristic $\chi$. We have the Hilbert-Chow morphism $\pi:M\rightarrow |L|$. We give explicit forms of the higher direct images $R^i\pi_*\mathcal{O}_M

Matteo Fiacchi, Nikolai Nikolov

We provide sharp estimates for the intrinsic distances of Finsler metrics with precise boundary estimates. These metrics include the Kobayashi-Hilbert metric near strongly convex points, the minimal metric near convex and strongly minimally convex points, and the $k$-quasi hyperbolic metric in $k$-strongly convex domains. Finally, we prove a characterization

Niloy Kumar Kundu, Sarah Kobir, Md. Rayhan Ahmed, Tahmina Aktar

Speech emotion recognition (SER) is crucial for enhancing affective computing and enriching the domain of human-computer interaction. However, the main challenge in SER lies in selecting relevant feature representations from speech signals with lower computational costs. In this paper, we propose a lightweight SER architecture that integrates attention-based

Sridevi Kuriyattil, Pablo M. Poggi, Jonathan D. Pritchard, Johannes Kombe

Quantum states featuring extensive multipartite entanglement are a resource for quantum-enhanced metrology, with sensitivity up to the Heisenberg limit. However, robust generation of these states using unitary dynamics typically requires all-to-all interactions among particles. Here, we demonstrate that optimal states for quantum sensing can be generated wit

Reagan J. Lee, Samarth Goel, Kannan Ramchandran

Embedding models are crucial for tasks in Information Retrieval (IR) and semantic similarity measurement, yet their handling of longer texts and associated positional biases remains underexplored. In this study, we investigate the impact of content position and input size on text embeddings. Our experiments reveal that embedding models, irrespective of their

Krzysztof Rudaś, Szymon Jaroszewicz

Uplift modeling and Heterogeneous Treatment Effect (HTE) estimation aim at predicting the causal effect of an action, such as a medical treatment or a marketing campaign on a specific individual. In this paper, we focus on data from Randomized Controlled Experiments which guarantee causal interpretation of the outcomes. Class and treatment imbalance are impo

Anastasia Zhukova, Christian E. Matt, Bela Gipp

Domain-specific languages that use a lot of specific terminology often fall into the category of low-resource languages. Collecting test datasets in a narrow domain is time-consuming and requires skilled human resources with domain knowledge and training for the annotation task. This study addresses the challenge of automated collecting test datasets to eval

Sze-Man Ngai, Wen-Quan Zhao

Let $d\geq1$, $\Omega$ be a bounded domain of a smooth complete Riemannian d-manifold M, and $\mu$ be a positive finite Borel measure with compact support in $\overline{\Omega}$. We prove the Courant nodal domain theorem for the eigenfunctions of Kre\u{i}n-Feller operator $\Delta_{\mu}$ under the assumption that such eigenfunctions are continuous on $\overli

Xiaohui Rao, Haoze Li, Xiaofang Lin, Lijuan Liang

In reading garden-path sentences, people must resolve competing interpretations, though initial misinterpretations can linger despite reanalysis. This study examines the role of inhibitory control (IC) in managing these misinterpretations among Chinese-English bilinguals. Using self-paced reading tasks, we investigated how IC influences recovery from garden-

Ziyuan Chen, Fang Yao

Noisy matrix completion has attracted significant attention due to its applications in recommendation systems, signal processing and image restoration. Most existing works rely on (weighted) least squares methods under various low-rank constraints. However, minimizing the sum of squared residuals is not always efficient, as it may ignore the potential struct

Yi-Hua Huang, Yan-Pei Cao, Yu-Kun Lai, Ying Shan

Texture synthesis is a fundamental problem in computer graphics that would benefit various applications. Existing methods are effective in handling 2D image textures. In contrast, many real-world textures contain meso-structure in the 3D geometry space, such as grass, leaves, and fabrics, which cannot be effectively modeled using only 2D image textures. We p

Cédric Lecouvey

We introduce some (p,q)-deformations of the weight multiplicities for the representations of any simple Lie algebra g over the complex numbers. This is done by associating the indeterminate q to the positive roots of a parabolic subsystem of g and the indeterminate p to the remaining positive roots. When p=q, we just recover the usual Lusztig analogues of we

Seon-Ho Lee, Jue Wang, David Fan, Zhikang Zhang

Audio Description (AD) plays a pivotal role as an application system aimed at guaranteeing accessibility in multimedia content, which provides additional narrations at suitable intervals to describe visual elements, catering specifically to the needs of visually impaired audiences. In this paper, we introduce $\mathrm{CA^3D}$, the pioneering unified Context-

Armand Ley

Given a Gaussian process $(X_t)_{t \in \mathbb{R}}$, we construct a Gaussian \emph{Markov} process with the same one-dimensional marginals using sequences of transformations of $(X_t)_{t \in \mathbb{R}}$ "made Markov" at finitely many times. We prove that there exists at least such a Markov transform of $(X_t)_{t \in \mathbb{R}}$. In the case the instantaneo

Romain Ducasse, Samuel Tréton

We analyze a model designed to describe the spread and accumulation of opinions in a population. Inspired by the social contagion paradigm, our model is built on the classical SIR model of Kermack and McKendrick and consists in a system of reaction-diffusion equations. In the scenario we consider, individuals within the population can adopt new opinions via

Jerzy J. Langer

Here we report a working physical model of a programmable neural nanonetwork based on a nanostructured conductive polymer - polyaniline. The device can be programmed owing to controlled growth of nanowires, a method developed in our laboratory. The response (output signal) of the network depends on the activated input line, but also on the amplitude of the i

Tao Song, Yicheng Wu, Minhao Hu, Xiangde Luo

Accelerated MRI reconstruction plays a vital role in reducing scan time while preserving image quality. While most existing methods rely on complex-valued image-space or k-space data, these formats are often inaccessible in clinical practice due to proprietary reconstruction pipelines, leaving only magnitude images stored in DICOM files. To address this gap,

Xiao Cai, Sitong Su, Jingkuan Song, Pengpeng Zeng

Text-to-3D (T23D) generation has emerged as a crucial visual generation task, aiming at synthesizing 3D content from textual descriptions. Studies of this task are currently shifting from per-scene T23D, which requires optimization of the model for every content generated, to General T23D (GT23D), which requires only one pre-trained model to generate differe

François Dubois, Michel Salaün, Stéphanie Salmon

We consider the bidimensional Stokes problem for incompressible fluids in stream function-vorticity. For this problem, the classical finite elements method of degree one converges only to order one-half for the L2 norm of the vorticity. We propose to use harmonic functions to approach the vorticity along the boundary. Discrete harmonics are functions that ar

Long Wen, Markus Rickert, Fengjunjie Pan, Jianjie Lin

The emergence of Software-Defined Vehicles (SDVs) signifies a shift from a distributed network of electronic control units (ECUs) to a centralized computing architecture within the vehicle's electrical and electronic systems. This transition addresses the growing complexity and demand for enhanced functionality in traditional E/E architectures, with containe

Sara Rezaeimanesh, Faezeh Hosseini, Yadollah Yaghoobzadeh

Large language models (LLMs) have shown superior capabilities in translating figurative language compared to neural machine translation (NMT) systems. However, the impact of different prompting methods and LLM-NMT combinations on idiom translation has yet to be thoroughly investigated. This paper introduces two parallel datasets of sentences containing idiom

Yuming Qin, Hongli Wang

In this paper, we investigate the dynamical behavior of non-autonomous Lame thermoelastic systems within $N$-dimensional materials. With appropriate constraints on nonlinear characteristics and functional parameters, we initially establish the existence of a uniformly absorbing set by constructing a Lyapunov function. Subsequently, we employ the contraction

Canishk Naik, Elaine Chew

Tipping points are moments of change that characterise crucial turning points in a piece of music. This study presents a first step towards quantitatively and systematically describing the musical properties of tipping points. Timing information and computationally-derived tonal tension values which correspond to dissonance, distance from key, and harmonic m

Mayukh Bagchi

Since decades, the modelling of metadata has been core to the functioning of any academic library. Its importance has only enhanced with the increasing pervasiveness of Generative Artificial Intelligence (AI)-driven information activities and services which constitute a library's outreach. However, with the rising importance of metadata, there arose several

Mengmeng Wang, Teli Ma, Shuo Xin, Xiaojun Hou

Visual Object Tracking (VOT) is an attractive and significant research area in computer vision, which aims to recognize and track specific targets in video sequences where the target objects are arbitrary and class-agnostic. The VOT technology could be applied in various scenarios, processing data of diverse modalities such as RGB, thermal infrared and point

Faustine Cantalloube, Camille Noûs

During its annual conference in 2024, the French Society of Astronomy & Astrophysics (SF2A) hosted a special session dedicated to discussing the environmental transition within the scope of our occupation. Since 2021, thinking on this subject has progressed significantly, both quantitatively and qualitatively. This year was an opportunity to take stock of th

Shiwen Ni, Haihong Wu, Di Yang, Qiang Qu

The quality of instruction data directly affects the performance of fine-tuned Large Language Models (LLMs). Previously, \cite{li2023one} proposed \texttt{NUGGETS}, which identifies and selects high-quality quality data from a large dataset by identifying those individual instruction examples that can significantly improve the performance of different tasks

Albert Lin, Shuang Peng, Somil Bansal

As learning-based methods for legged robots rapidly grow in popularity, it is important that we can provide safety assurances efficiently across different controllers and environments. Existing works either rely on a priori knowledge of the environment and safety constraints to ensure system safety or provide assurances for a specific locomotion policy. To a

Pegah Eshraghi, Riccardo Talami, Arman Nikkhah Dehnavi, Maedeh Mirdamadi

In rapidly urbanizing regions, designing climate-responsive urban forms is crucial for sustainable development, especially in dry arid-climates where urban morphology has a significant impact on energy consumption and environmental performance. This study advances urban morphology evaluation by combining Urban Building Energy Modeling (UBEM) with machine lea

Beth Goldberg, Diana Acosta-Navas, Michiel Bakker, Ian Beacock

Two substantial technological advances have reshaped the public square in recent decades: first with the advent of the internet and second with the recent introduction of large language models (LLMs). LLMs offer opportunities for a paradigm shift towards more decentralized, participatory online spaces that can be used to facilitate deliberative dialogues at

Wen Qi Zhang

We extend the $L^1$ Stein-Weiss inequalities studied by De N\'{a}poli and Picon [4] in two ways: First we address an open question posed by the authors about whether the cocanceling condition was necessary for some of their Stein-Weiss inequalities. We replace the cocanceling condition with a weaker vanishing moment assumption, and under this assumption exte

Rathish P. Ratnasingam, Philipp V. F. Edelmann, Dominic M. Bowman, Tamara M. Rogers

It is well-known that the cores of massive stars sustain a stellar dynamo with a complex magnetic field configuration. However, the same cannot be said for the field's strength and geometry at the convective-radiative boundary, which are crucial when performing asteroseismic inference. In this Letter, we present three-dimensional (3D) magnetohydrodynamic (MH

Jian Zheng, Size Wu, Kai Liu, Bosai Lyu

Graphene-based moire superlattices provide a versatile platform for exploring novel correlated and topological electronic states, driven by enhanced Coulomb interactions within flat bands. The intrinsic tunability of graphene s multiple degrees of freedom enables precise control over these complex quantum phases. In this study, we observe a range of competin

Neil Thapen

Subclasses of TFNP (total functional NP) are usually defined by specifying a complete problem, which is necessarily in TFNP, and including all problems many-one reducible to it. We study two notions of how a TFNP problem can be reducible to an object, such as a complexity class, outside TFNP. This gives rise to subclasses of TFNP which capture some propertie

Federico Siciliano, Francesca Pezzuti, Nicola Tonellotto, Fabrizio Silvestri

In the era of dense retrieval, document indexing and retrieval is largely based on encoding models that transform text documents into embeddings. The efficiency of retrieval is directly proportional to the number of documents and the size of the embeddings. Recent studies have shown that it is possible to reduce embedding size without sacrificing - and in so

Jongmin Park, Minh-Quan Viet Bui, Juan Luis Gonzalez Bello, Jaeho Moon

Synthesizing novel views from in-the-wild monocular videos is challenging due to scene dynamics and the lack of multi-view cues. To address this, we propose SplineGS, a COLMAP-free dynamic 3D Gaussian Splatting (3DGS) framework for high-quality reconstruction and fast rendering from monocular videos. At its core is a novel Motion-Adaptive Spline (MAS) method

Ziqi Sheng, Wei Lu, Xiangyang Luo, Jiantao Zhou

Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering technologies, extracting more comprehensive and accurate forgery clues remains an urgent challenge. To address these challenges, we introduce a novel information-theoretic IFL fram

Lingyun Wang, Deqi Su, Aohua Zhang, Yujun Zhu

In recent years, as the population ages, falls have increasingly posed a significant threat to the health of the elderly. We propose a real-time fall detection system that integrates the inertial measurement unit (IMU) of a smartphone with optimized Wi-Fi channel state information (CSI) for secondary validation. Initially, the IMU distinguishes falls from ro

Alexander Yosifov, Aditya Iyer, Vlatko Vedral

Quantum reservoirs have great potential as they utilize the complex real-time dissipative dynamics of quantum systems for information processing and target time-series generation without precise control or fine-tuning of the Hamiltonian parameters. Nonetheless, their realization is challenging as quantum hardware with appropriate dynamics, robustness to nois

Vladimir Semenov

It is shown that nonlocal coupling provides for controlling the collective noise-induced dynamics in the regime of stochastic resonance. This effect is demonstrated by means of numerical simulation on an example of coupled overdamped bistable oscillators. In particular, it has been established that increasing the coupling radius and coupling strength allows

Kinfung Ngan, Shuo Sun

Solid-state quantum emitters, such as quantum dots, color centers, rare-earth dopants, and organic molecules, offer qubit systems that integrate well with chip-scale photonic and electronic devices. To fully harness their potential for quantum applications requires the generation of entanglement between two remote qubits with high fidelity and efficiency. In

Lie Fu

Given a smooth compact complex surface together with a holomorphic line bundle on it, using the theory of Hodge modules, we compute the twisted Hodge groups/numbers of Hilbert schemes (or Douady spaces) of points on the surface with values in the naturally associated line bundle. This proves an amended version of Boissi\`ere's conjecture proposed by the auth

Chao-Ran Cai, Dong-Qian Cai

In discrete-time dynamics, it is frequently assumed that the transition probabilities (e.g., the recovery probability) are independent of the network structure. However, there is a lack of empirical evidence to support this claim in large time intervals. This paper presents the nonlinear relations between the rates (in continuous-time dynamics) and probabili