March 2025 arXiv papers — page 110

Gennadi Malaschonok, Roman Sakh

The article provides a brief description of the MathPartner service. This freely available cloud-based Mathematics is a universal system for symbolic-numeric calculations. Its Mathpar language is a subset of the LaTeX language, but allows you to create mathematical texts that contain "computable" mathematical operators. This opens up completely new opportuni

Omar Cabrera

We prove the existence of ground states and high-energy solutions to the following Schr\"odinger-Poisson system \begin{align*} \begin{cases} - \Delta u + a(x) u + u v = 0,\newline \Delta v = u^2, \end{cases} \quad \text{in } \mathbb{R}^3, \end{align*} where $a \in L^\infty(\mathbb{R}^3)$ is nonnegative and radially symmetric in the first two variables. Diffe

Nóra Takács, Csaba Kiss, Róbert Szakáts, András Pál

Using multidirectional measurements from the Transiting Exoplanet Survey Satellite (TESS), we investigated the viability of determining the approximate shape and spin axis orientations for 44 selected main belt asteroids, using light curve inversion, assuming Lommel-Seeliger ellipsoids. This study aims to investigate the applicability of low-degree-of-freedo

Jin Yan

We investigate the emergence of complex dynamics in a system of coupled dissipative kicked rotors and show that critical transitions can be understood via bifurcations of simple states. We study multistability and bifurcations in the single rotor model, demonstrating how these give rise to a variety of coexisting spatial patterns in a coupled system. A combi

Sijia Gu, Noor Nashid, Ali Mesbah

Automating unit test generation remains a significant challenge, particularly for complex methods in real-world projects. While Large Language Models (LLMs) have made strides in code generation, they struggle to achieve high branch coverage due to their limited ability to reason about intricate control flow structures. To address this limitation, we introduc

Ricardo Bigolin Lanfredi, Yan Zhuang, Mark Finkelstein, Praveen Thoppey Srinivasan Balamuralikrishna

Extracting structured labels from radiology reports has been employed to create vision models to simultaneously detect several types of abnormalities. However, existing works focus mainly on the chest region. Few works have been investigated on abdominal radiology reports due to more complex anatomy and a wider range of pathologies in the abdomen. We propose

Beatriz Costa-Gomes, Joel Greer, Nikolai Juraschko, James Parkhurst

Ease of access to data, tools and models expedites scientific research. In structural biology there are now numerous open repositories of experimental and simulated datasets. Being able to easily access and utilise these is crucial for allowing researchers to make optimal use of their research effort. The tools presented here are useful for collating existin

Lan Chen, Qi Mao, Yuchao Gu, Mike Zheng Shou

We introduce a new setting, Edit Transfer, where a model learns a transformation from just a single source-target example and applies it to a new query image. While text-based methods excel at semantic manipulations through textual prompts, they often struggle with precise geometric details (e.g., poses and viewpoint changes). Reference-based editing, on the

Jakub Koncki, Richard Rimanyi

We provide an explicit description of the maximal-dimensional components of the variety parametrizing sequences of matrices of prescribed sizes whose product is zero.

Max Demirdilek, Christoph Schweigert

Grothendieck-Verdier categories (also known as $\ast$-autonomous categories) generalize rigid monoidal categories, with notable representation-theoretic examples including categories of bimodules, modules over Hopf algebroids, and modules over vertex operator algebras. In this paper, we develop a surface-diagrammatic calculus for Grothendieck-Verdier categor

Karlheinz Gröchenig, Irina Shafkulovska

We develop a method for the transfer of an uncertainty principle for the short-time Fourier transform or a Fourier pair to an uncertainty principle for a sesquilinear or quadratic metaplectic time-frequency representation. In particular, we derive Beurling-type and Hardy-type uncertainty principles for metaplectic time-frequency representations.

Andrew Baker, Brantly Callaway, Scott Cunningham, Andrew Goodman-Bacon

Difference-in-differences (DiD) is arguably the most popular quasi-experimental research design. Its canonical form, with two groups and two periods, is well-understood. However, empirical practices can be ad hoc when researchers go beyond that simple case. This article provides an organizing framework for discussing different types of DiD designs and their

Xin Dong, Rui Miao, Suyan Zhang, Shuaibing Jia

Repositioning drug-disease relationships has always been a hot field of research. However, actual cases of biologically validated drug relocation remain very limited, and existing models have not yet fully utilized the structural information of the drug. Furthermore, most repositioning models are only used to complete the relationship matrix, and their pract

Seokhyeon Hong, Soojin Choi, Chaelin Kim, Sihun Cha

Despite the growing accessibility of skeletal motion data, integrating it for animating character meshes remains challenging due to diverse configurations of both skeletons and meshes. Specifically, the body scale and bone lengths of the skeleton should be adjusted in accordance with the size and proportions of the mesh, ensuring that all joints are accurate

Camille Roy, Simone Frasca, Pasquale Scarlino

Superconducting resonators with high-kinetic inductance play a central role in hybrid quantum circuits, enabling strong coupling with quantum systems with small electric dipole moment and improved parametric amplification. However, optimizing these resonators simultaneously for high internal quality factors ($Q_i$) and resilience to strong magnetic fields re

Shuo Fang, Shi Pu, Di-Lun Yang

We investigate the radiative corrections on spin polarization of relativistic fermions induced by vortical fields in thermal-equilibrium QCD matter at weak coupling. Such corrections stem from the self-energy gradients in quantum kinetic theory, which are further obtained by a more systematic and general approach through the Keldysh equation. By applying the

Shitong Shao, Hongwei Yi, Hanzhong Guo, Tian Ye

Recently, open-source video diffusion models (VDMs), such as WanX, Magic141 and HunyuanVideo, have been scaled to over 10 billion parameters. These large-scale VDMs have demonstrated significant improvements over smaller-scale VDMs across multiple dimensions, including enhanced visual quality and more natural motion dynamics. However, these models face two m

D. Tsitsonis, M. Kircher, N. M. Novikovskiy, F. Trinter

We experimentally demonstrate that individual molecules of formic acid are chiral even when they are in the vibronic ground state, which has a planar equilibrium structure. We ionize the C 1s shell of the molecule and record the photoelectron in coincidence with positively charged fragments. This provides two consecutive measurements of the structure of one

Enrico Foglia, Benjamin Bobbia, Nikita Durasov, Michael Bauerheim

Quantifying model uncertainty is critical for understanding prediction reliability, yet distinguishing between aleatoric and epistemic uncertainty remains challenging. We extend recent work from classification to regression to provide a novel frequentist approach to epistemic and aleatoric uncertainty estimation. We train models to generate conditional predi

Marcello Iotti, Paolo Davini, Jost von Hardenberg, Giuseppe Zappa

To this day, accurately simulating local-scale precipitation and reliably reproducing its distribution remains a challenging task. The limited horizontal resolution of Global Climate Models is among the primary factors undermining their skill in this context. The physical mechanisms driving the onset and development of precipitation, especially in extreme ev

Luis A. Anchordoqui, Karem Peñaló Castillo

Motivated by a recent proposal that points to the Sombrero galaxy as a source of the highest energy cosmic rays, we investigate the feasibility of accelerating light and heavy nuclei in the supermassive black hole located at the center of this dormant galaxy. We show that cosmic ray nuclei concentrated in the immediate vicinity of the supermassive black hole

Temirlan Kurbanov, Linxiao Miao, Jiří Vokřínek

This paper presents a novel multicriteria shortest path search algorithm called Hierarchical MLS. The distinguishing feature of the algorithm is the multilayered structure of compressed k-Path-Cover graphs it operates on. In addition to providing significant improvements in terms of time and memory consumption, the algorithm is notable for several other feat

M. Rybak, D. Sluse, K. K. Gupta, M. Millon

Determining the nature of emission processes at the heart of quasars is critical for understanding environments of supermassive black holes. One of the key open questions is the origin of long-wavelength emission from radio-quiet quasars. The proposed mechanisms span a broad range, from central star formation to dusty torus, low-power jets, or coronal emissi

Katharina Hübner

We consider a proper morphism $X \to S$ and a locally closed immersion $S' \to S$ of discretely ringed adic spaces and prove proper base change for the tame topology in this setting. More precisely, we show that for an abelian $p$-torsion sheaf ($p = char^+(S)$) on the tame site of $X$ that the base change homomorphism for the derived pushforward along $X \t

Simone Cacace, Roberto Ferretti, Giulia Tatafiore

We consider a scheme of Semi-Lagrangian (SL) type for the numerical solution of Hamilton-Jacobi (HJ) equation on unstructured triangular grids. As it is well known, SL schemes are not well suited for unstructured grids, due to the cost of the point location phase; this drawback is augmented by the need for repeated minimization. In this work, we propose a sc

Matteo Esposito, Xiaozhou Li, Sergio Moreschini, Noman Ahmad

Context: Generative Artificial Intelligence (GenAI) is transforming much of software development, yet its application in software architecture is still in its infancy, and no prior study has systematically addressed the topic. Aim: We aim to systematically synthesize the use, rationale, contexts, usability, and future challenges of GenAI in software architec

Farnoush Bayatmakou, Reza Taleei, Milad Amir Toutounchian, Arash Mohammadi

Despite advancements in Computer-Aided Diagnosis (CAD) systems, breast cancer remains one of the leading causes of cancer-related deaths among women worldwide. Recent breakthroughs in Artificial Intelligence (AI) have shown significant promise in development of advanced Deep Learning (DL) architectures for breast cancer diagnosis through mammography. In this

Mariza Cooray, Rolando Gonzales Martinez

This working paper uses a Dynamic Factor Model ('the model') to identify underlying factors contributing to the debt-induced economic crisis in the People's Democratic Republic of Laos ('Laos'). The analysis aims to use the latent macroeconomic insights to propose ways forward for forecasting. We focus on Laos's historic structural weaknesses to identify whe

Simon Shuofeng Xu

The goal of this paper is to first define a Hodge theoretic fundamental group for smooth connected complex algebraic varieties and then prove and study a right exact sequence of Hodge theoretic fundamental groups associated to a smooth projective family of algebraic varieties $f\colon X\to B$. In particular, we study when this right exact sequence is exact,

Catalin-Mihai Halati, Ameneh Sheikhan, Giovanna Morigi, Corinna Kollath

We investigate the dynamical spreading of correlations in many-body quantum systems with competing short- and global-range couplings. We monitor the non-equilibrium dynamics of the correlations following a quench, showing that for strong short-range couplings the propagation of correlations is dominated at short and intermediate distances by a causal, light-

Patrick Callaghan, Reid Simmons, Henny Admoni

Confusing or otherwise unhelpful learner feedback creates or perpetuates erroneous beliefs that the teacher and learner have of each other, thereby increasing the cognitive burden placed upon the human teacher. For example, the robot's feedback might cause the human to misunderstand what the learner knows about the learning objective or how the learner learn

Chi Han, Heng Ji

Most written natural languages are composed of sequences of words and sentences. Similar to humans, large language models (LLMs) exhibit flexibility in handling textual positions - a phenomenon we term position generalization. They can understand texts with position perturbations and generalize to longer texts than those encountered during training with the

Witold Wydmański, Marek Śmieja

Feature selection (FS) is a fundamental challenge in machine learning, particularly for high-dimensional tabular data, where interpretability and computational efficiency are critical. Existing FS methods often cannot automatically detect the number of attributes required to solve a given task and involve user intervention or model retraining with different

Yinqiao Wang, Hao Xu, Pheng-Ann Heng, Chi-Wing Fu

Estimating the 3D pose of hand and potential hand-held object from monocular images is a longstanding challenge. Yet, existing methods are specialized, focusing on either bare-hand or hand interacting with object. No method can flexibly handle both scenarios and their performance degrades when applied to the other scenario. In this paper, we propose UniHOPE,

S. V. Zaitsev-Zotov, P. D. Grigoriev, D. Voropaev, A. A. Morocho

Slow oscillations of the magnetoresistance periodic in the inverse magnetic field with a frequency of 3.4 T have been identified in HoTe3. The temperature dependence of the oscillation amplitude is close to exponential even at low temperatures. This may be attributed to the existence of soft modes in the system and allows the estimation of the electron scatt

Ling-An Zeng, Gaojie Wu, Ancong Wu, Jian-Fang Hu

Although existing text-to-motion (T2M) methods can produce realistic human motion from text description, it is still difficult to align the generated motion with the desired postures since using text alone is insufficient for precisely describing diverse postures. To achieve more controllable generation, an intuitive way is to allow the user to input a few m

Yijun Liu, Jinzheng Yu, Yang Xu, Zhongyang Li

Large language models (LLMs) based on Transformer have been widely applied in the filed of natural language processing (NLP), demonstrating strong performance, particularly in handling short text tasks. However, when it comes to long context scenarios, the performance of LLMs degrades due to some challenges. To alleviate this phenomenon, there is a number of

Roman Chertovskih, Nikolay Pogodaev, Maxim Staritsyn, A. Pedro Aguiar

We present an approach to solving unconstrained nonlinear optimal control problems for a broad class of dynamical systems. This approach involves lifting the nonlinear problem to a linear ``super-problem'' on a dual Banach space, followed by a non-standard ``exact'' variational analysis, -- culminating in a descent method that achieves rapid convergence with

Lara Maleyeff, Shirin Golchi, Erica E. M. Moodie

Precision medicine aims to optimize treatment by identifying patient subgroups most likely to benefit from specific interventions. To support this goal, we introduce fkbma, an R package that implements a Bayesian model averaging approach with free-knot B-splines for identifying tailoring variables. The package employs a reversible jump Markov chain Monte Car

Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen

Bayesian Neural Networks (BNNs) often improve model calibration and predictive uncertainty quantification compared to point estimators such as maximum-a-posteriori (MAP). Similarly, deep ensembles (DEs) are also known to improve calibration, and therefore, it is natural to hypothesize that deep ensembles of BNNs (DE-BNNs) should provide even further improvem

Lingnan Shen, Mao Lin, Cedric Yen-Yu Lin, Di Xiao

Strongly correlated topological phases of matter are central to modern condensed matter physics and quantum information technology but often challenging to probe and control in material systems. The experimental difficulty of accessing these phases has motivated the use of engineered quantum platforms for simulation and manipulation of exotic topological sta

Fabio Nicola

This note is the transcription of an interview with Professor Luigi Rodino, on the occasion of the ISAAC-ICMAM Conference of Analysis in Developing Countries (December 2, 2024 - Bogot\`a), that was dedicated to him. Luigi Rodino is at present Emeritus Professor at the University of Turin, and a member of the Accademia delle Scienze di Torino.

Christopher E. Rura, Vadim M. Uritsky, Shaela I. Jones, Cooper Downs

Coronagraph observations provide key information about the orientation of the Sun's magnetic field. Previous studies used various algorithms to segment quasi-radial features in coronagraph images and approximate their local plane-of-sky geometry and orientation which can be used as input for optimizing and constraining coronal magnetic field models. We prese

Yo Kusafuka, Tomoki Matsuoka, Ryo Sawada

Decades have passed since the first confirmed association between a broad-lined Type Ic supernova (Type IcBL SN) and a long gamma-ray burst (GRB), and the number of known GRB-SN associations has steadily increased. However, it is important to note that the radiation from GRB afterglows and the radio emission from SNe may be both produced by outflows evolving

Raymond G. Carlberg

Measurements of the GD-1 star stream velocity distribution within $\pm$3 degrees of the centerline find a total line of sight velocity spread of 5-6 km/s in the well measured $\phi_1=$ [-30, 0] region (Valluri25). The velocity spread is far above the $\sim$2-3 km/s of a dissolved globular cluster in a smooth galactic potential. The dynamical heating of the G

Thomas Banker, Nathan P. Lawrence, Ali Mesbah

Making optimal decisions under uncertainty is a shared problem among distinct fields. While optimal control is commonly studied in the framework of dynamic programming, it is approached with differing perspectives of the Bellman optimality condition. In one perspective, the Bellman equation is used to derive a global optimality condition useful for iterative

Fangzhi Xu, Hang Yan, Chang Ma, Haiteng Zhao

Inference-time optimization scales computation to derive deliberate reasoning steps for effective performance. While previous search-based strategies address the short-sightedness of auto-regressive generation, the vast search space leads to excessive exploration and insufficient exploitation. To strike an efficient balance to derive the optimal step, we fra

Wataru Yata, Keita Kume, Isao Yamada

We propose a nonconvexly regularized convex model for linear regression problems under non-Gaussian noise. The cost function of the proposed model is designed with a possibly non-quadratic data fidelity term and a nonconvex regularizer via the generalized Moreau enhancement of a seed convex regularizer. We present sufficient conditions (i) for the cost funct

Yanping Huang

Radiative decays of the $J/\psi$ particle are of gluon-rich environment, providing an ideal place for hunting glueballs. The $X(2370)$ particle was first discovered in $J/\psi\to \gamma \pi^+\pi^-\eta^{\prime}$ process in 2011 with the BESIII experiment at BEPCII Collider, and later it was confirmed in $J/\psi\to\gamma K\bar{K}\eta^{\prime}$ decays. In 2024,

Rebecca Rothermel, Thomas Schuster

The article considers the nonlinear inverse problem of identifying the material parameters in viscoelastic structures based on a generalized Maxwell model. The aim is to reconstruct the model parameters from stress data acquired from a relaxation experiment, where the number of Maxwell elements, and thus the number of material parameters themselves, are assu

CTA-LST Project, :, K. Abe, S. Abe

The recurrent nova RS Ophiuchi (RS Oph) underwent a thermonuclear eruption in August 2021. In this event, RS Oph was detected by the High Energy Stereoscopic System (H.E.S.S.), the Major Atmospheric Gamma Imaging Cherenkov (MAGIC), and the first Large-Sized Telescope (LST-1) of the future Cherenkov Telescope Array Observatory (CTAO) at very-high gamma-ray en

Xiaodi Li, Shaika Chowdhury, Chung Il Wi, Maria Vassilaki

Patient matching is the process of linking patients to appropriate clinical trials by accurately identifying and matching their medical records with trial eligibility criteria. We propose LLM-Match, a novel framework for patient matching leveraging fine-tuned open-source large language models. Our approach consists of four key components. First, a retrieval-

Rongrong Liu, Zhengyi Shao, Lu Li

The Pleiades is a young open cluster that has not yet dynamically relaxed, making it an ideal target to observe various internal dynamical effects. By employing a well-defined sample of main-sequence (MS) cluster members, including both MS single stars and unresolved MS+MS binaries, we revisited their individual masses and mass functions and quantified the m

Xinkai Zou, Yan Liu, Xiongbo Shi, Chen Yang

As requirements drift with rapid iterations, agile development becomes the dominant paradigm. Goal-driven Requirements Elicitation (RE) is a pivotal yet challenging task in agile project development due to its heavy tangling with adaptive planning and efficient collaboration. Recently, AI agents have shown promising ability in supporting requirements analysi

Jérôme Lodewyck, Tetsuya Ido

The current definition of the SI second based on the Cs ground state hyperfine transition is expected to be replaced by a new definition based on optical frequency standards in the next decade. Several options are currently under consideration for the new definition, including a definition based on the weighted geometric mean of several transitions. In this

Alfred Simbun, Suresh Kumar

Background: The COVID-19 pandemic has overwhelmed healthcare systems, emphasizing the need for AI-driven tools to assist in rapid and accurate patient prognosis. Chest X-ray imaging is a widely available diagnostic tool, but existing methods for prognosis classification lack scalability and efficiency. Objective: This study presents a high-accuracy deep lear

Manfred Borzechowski, Malvin Gattinger, Helle Hvid Hansen, Revantha Ramanayake

We show that Propositional Dynamic Logic (PDL) has the Craig Interpolation Property. This question has been open for many years. Three proof attempts were published, but later criticized in the literature or retracted. Our proof is based on the main ideas from Borzechowski (1988, master thesis). We define a cyclic tableau system for PDL with a loading mechan

Seyoung Song

We introduce a novel large language model (LLM)-driven agent framework, which iteratively refines queries and filters contextual evidence by leveraging dynamically evolving knowledge. A defining feature of the system is its decoupling of external sources from an internal knowledge cache that is progressively updated to guide both query generation and evidenc

Nicholas Miesch, Edward Shuryak, Ismail Zahed

The standard description of the nucleon in the non-relativistic quark model is an $1S,L=0$ state without orbital motion. Yet, there are several indications from phenomenology that an admixture of states with nonzero orbital motion maybe substantial. In this paper we focus on the ``second shell" of the nucleon excitations (D-shell), for which we give a modern

Katja Schwarz, Norman Mueller, Peter Kontschieder

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated sequences. In addition, directly training generative 3D models is challenging due to a lack of 3D training data at scale. In

Chengen Wang, Murat Kantarcioglu

In recent years, numerous graph generative models (GGMs) have been proposed. However, evaluating these models remains a considerable challenge, primarily due to the difficulty in extracting meaningful graph features that accurately represent real-world graphs. The traditional evaluation techniques, which rely on graph statistical properties like node degree

Alessio Zaccone, Konrad Samwer

Analytical relations for the glass transition temperature, $T_g$, and the crystal melting temperature, $T_m$, are developed on the basis of nonaffine lattice dynamics. The proposed relations explain: (i) the seemingly universal factor of $\approx 2/3$ difference between glass transition temperature and melting temperature of the corresponding crystal, and (i

Wenyi Xu, Yuren Mao, Xiaolu Zhang, Chao Zhang

Relational database-driven data analysis (RDB-DA) report generation, which aims to generate data analysis reports after querying relational databases, has been widely applied in fields such as finance and healthcare. Typically, these tasks are manually completed by data scientists, making the process very labor-intensive and showing a clear need for automati

Jian Xiao, Ji Wang, Yuanwei Liu

Pinching Antennas (PAs) represent a revolutionary flexible antenna technology that leverages dielectric waveguides and electromagnetic coupling to mitigate large-scale path loss. This letter is the first to explore channel estimation for Pinching-Antenna SyStems (PASS), addressing their uniquely ill-conditioned and underdetermined channel characteristics. In

Shoupan Liu, Yunqi Liu, Yan Peng, Cheng-Yong Zhang

In this study, we investigate rotating black hole solutions within a scalar Gauss-Bonnet gravity framework that incorporates a squared Gauss-Bonnet term. By employing a quadratic exponential coupling function between the scalar field and the Gauss-Bonnet invariant, we derive both the standard General Relativity solutions and novel scalarized black hole confi

H. P. de Oliveira

We investigate the interaction between a non-rotating black hole and incoming gravitational waves using the characteristic formulation of the Einstein field equations, framed as a Bondi problem. By adopting retarded time as the null coordinate and recognizing that the final state is invariably a black hole, we demonstrate that an apparent horizon forms once

Amazon AGI, Aaron Langford, Aayush Shah, Abhanshu Gupta

We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highly-capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks. Amazon Nova Lite is a low-cost multimodal model that is lightning fast

Luxi Chen, Zihan Zhou, Min Zhao, Yikai Wang

Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel framework consisting of two key components: (1) a strong video-to-video (V2V) diffusion model to generate high-quality novel view images from incomplete input rendered from a co

Subrata Ghosh, Giacomo Pagani, Andrea Macrelli, Alberto Calloni

Pulsed laser-deposited amorphous carbon nanofoams are potential candidate for electrochemical energy storage applications due to ultra-light weight, large volumetric void fractions, and co-existence of sp, sp2 and sp3 carbon hybridization. It is known that charge storage in carbon nanostructures containing disordered sp2-domains is determined by their wettab

H. T. J. Bevins, T. Gessey-Jones, W. J. Handley

Neural network emulators are widely used in astrophysics and cosmology to approximate complex simulations inside Bayesian inference loops. Ad hoc rules of thumb are often used to justify the emulator accuracy required for reliable posterior recovery. We provide a theoretically motivated limit on the maximum amount of incorrect information inferred by using a

Deyin Yi, Yihao Liu, Lang Cao, Mengyu Zhou

Tabular data analysis is crucial in many scenarios, yet efficiently identifying the most relevant data analysis queries and results for a new table remains a significant challenge. The complexity of tabular data, diverse analytical operations, and the demand for high-quality analysis make the process tedious. To address these challenges, we aim to recommend

Leonard E. C. Romano, Ellis R. Owen, Kentaro Nagamine

Aims. We investigate the role of cosmic ray (CR) halos in shaping the properties of starburst-driven galactic outflows. Methods. We develop a microphysical model for galactic outflows driven by a continuous central feedback source, incorporating a simplified treatment of CRs. The model parameters are linked to the effective properties of a starburst. By anal

Amit Zalcher, Navve Wasserman, Roman Beliy, Oliver Heinimann

Visual perceptual tasks aim to predict human judgment of images (e.g., emotions invoked by images, image quality assessment). Unlike objective tasks such as object/scene recognition, perceptual tasks rely on subjective human assessments, making its data-labeling difficult. The scarcity of such human-annotated data results in small datasets leading to poor ge

Riku Anttila, Sylvester Eriksson-Bique, Ryosuke Shimizu

We construct self-similar $p$-energy forms as normalized limits of discretized $p$-energies on a rich class of Laakso-type fractal spaces. Collectively, we refer to them as IGS-fractals, where IGS stands for (edge-)iterated graph systems. We propose this framework as a rich source of "toy models" that can be consulted for tackling challenging questions that

Menghua Xia, Kuan-Yin Ko, Der-Shiun Wang, Ming-Kai Chen

Positron emission tomography (PET) image denoising, along with lesion and organ segmentation, are critical steps in PET-aided diagnosis. However, existing methods typically treat these tasks independently, overlooking inherent synergies between them as correlated steps in the analysis pipeline. In this work, we present the anatomically and metabolically info

Mark Edelman

The regular logistic map was introduced in 1960s, served as an example of a complex system, and was used as an instrument to demonstrate and investigate the period doubling cascade of bifurcations scenario of transition to chaos. In this paper, we review various fractional generalizations of the logistic map and their applications.

Tianxing Fu, Jia Hu, Geyong Min, Zi Wang

Federated learning (FL) enables multiple participants to collaboratively train machine learning models while ensuring their data remains private and secure. Blockchain technology further enhances FL by providing stronger security, a transparent audit trail, and protection against data tampering and model manipulation. Most blockchain-secured FL systems rely

Yu Liu, Hanbin Jiang, Lei Zhu, Yu Zhang

In the real world, users always have multiple interests while surfing different services to enrich their daily lives, e.g., watching hot short videos/live streamings. To describe user interests precisely for a better user experience, the recent literature proposes cross-domain techniques by transferring the other related services (a.k.a. domain) knowledge to

Islem Saadaoui

This study explores the economic value of Aleppo pine forests, a unique and threatened ecosystem in the border region of central Tunisia. These forests play a vital role in supporting small rural communities, but face increasing pressures and restrictions on their use. This research aims to assign a monetary value to forest conservation, considering the regi

Maxime Louis, Thibault Formal, Hervé Dejean, Stéphane Clinchant

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge, leading to improved accuracy and relevance. However, scaling RAG pipelines remains computationally expensive as retrieval sizes grow. To address this, we introduce OSCAR, a novel query-dependent online soft compression method that reduces computation

Jingqi Jiang, Shida Xu, Kaicheng Zhang, Jiyuan Wei

Radar has become an essential sensor for autonomous navigation, especially in challenging environments where camera and LiDAR sensors fail. 4D single-chip millimeter-wave radar systems, in particular, have drawn increasing attention thanks to their ability to provide spatial and Doppler information with low hardware cost and power consumption. However, most

Paulo Carrillo Rouse, Laurent Guillaume

Let $p$ be a prime number and $\mathcal{S}_p$ the $p$-solenoid. For $\alpha\in \mathbb{R}\times \mathbb{Q}_p$ we consider in this paper a naturally associated action groupoid $S_\alpha:=\mathbb{Z} [1/p]\ltimes_\alpha \mathcal{S}_p \rightrightarrows \mathcal{S}_p$ whose $C^*-$algebra is a model for the noncommutative solenoid $\mathcal{A}_\alpha^\mathscr{S}$

Zejia Zhang, Bo Yang, Xinxing Chen, Weizhuang Shi

A promising effective human-robot interaction in assistive robotic systems is gaze-based control. However, current gaze-based assistive systems mainly help users with basic grasping actions, offering limited support. Moreover, the restricted intent recognition capability constrains the assistive system's ability to provide diverse assistance functions. In th

Benoît Savoini, Jonathan Bertolaccini, Stéphane Montavon, Michel Deriaz

Lameness and gait irregularities are significant concerns in equine health management, affecting performance, welfare, and economic value. Traditional observational methods rely on subjective expert assessments, which can lead to inconsistencies in detecting subtle or early-stage lameness. While AI-based approaches have emerged, many require multiple sensors

Agnieszka Sroka-Oleksiak, Adam Pardyl, Dawid Rymarczyk, Aldona Olechowska-Jarząb

Sepsis is a life-threatening condition which requires rapid diagnosis and treatment. Traditional microbiological methods are time-consuming and expensive. In response to these challenges, deep learning algorithms were developed to identify 14 bacteria species and 3 yeast-like fungi from microscopic images of Gram-stained smears of positive blood samples from

Ziming Li, Zhimin Wang, Jie Yang

The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to pr

Akshay Thakur, Matthew J. Zahr

The Riemann problem is fundamental in the computational modeling of hyperbolic partial differential equations, enabling the development of stable and accurate upwind schemes. While exact solvers provide robust upwinding fluxes, their high computational cost necessitates approximate solvers. Although approximate solvers achieve accuracy in many scenarios, the

Huan Jiang, Yang Ge, Shao-Kai Jian

We study the boundary criticality for the Gross-Neveu-Yukawa (GNY) models. Employing interacting Dirac fermions on a honeycomb lattice with armchair boundaries, we use determinant quantum Monte Carlo simulation to uncover rich boundary criticalities at the quantum phase transition to a charge density wave (CDW) insulator, including the ordinary, special, and

Guoyou Sun, Panagiotis Karras, Qi Zhang

Semantic communication has emerged as a promising paradigm to tackle the challenges of massive growing data traffic and sustainable data communication. It shifts the focus from data fidelity to goal-oriented or task-oriented semantic transmission. While deep learning-based methods are commonly used for semantic encoding and decoding, they struggle with the s

S. M. Thomas, C. S. Kengle, W. Simeth, Chan-young Lim

Materials in the family $R$V$_{6}$Sn$_{6}$ ($R=$ rare earth) provide a unique platform to investigate the interplay between local moments from $R$ layers and nonmagnetic vanadium kagome layers. Yet, the investigation of actinide members remains scarce. Here we report the synthesis of UV$_{6}$Sn$_{6}$ single crystals through the self-flux technique. Magnetic

Weiwei Su, Shigefumi Hata, Hiroshi Kori, Hiroya Nakao

Rhythmic phenomena, which are ubiquitous in biological systems, are typically modelled as systems of coupled limit cycle oscillators. Recently, there has been an increased interest in understanding the impact of higher-order interactions on the population dynamics of coupled oscillators. Meanwhile, the estimation of a mathematical model from experimental dat

Isabel Hubard, Primož Potočnik, Primož Šparl

In this paper, we provide the first known infinite family of simple graphs, each of which is the skeleton of a chiral map, a skeleton of a reflexible map on an orientable surfaces, as well as a skeleton of a reflexible map on a non-orientable surface. This family consists of all lexicographic product $C_n[mK_1]$, where $m\ge 3$, $n = sm$, with $s$ an integer

Anand Pillay, Françoise Point, Silvain Rideau-Kikuchi

We study groups definable in existentially closed geometric fields with commuting derivations. Our main result is that such a group can be definably embedded in a group interpretable in the underlying geometric field. Compared to earlier work of the first two authors toguether with K. Peterzil, the novelty is that we also deal with infinite dimensional group

Zhifu Tian, Tao Hu, Chaoyang Niu, Di Wu

Scene-aware Adaptive Compressive Sensing (ACS) has attracted significant interest due to its promising capability for efficient and high-fidelity acquisition of scene images. ACS typically prescribes adaptive sampling allocation (ASA) based on previous samples in the absence of ground truth. However, when confronting unknown scenes, existing ACS methods ofte

Ryo Takahashi, Changyo Han, Wakako Yukita, John S. Ho

Wireless body networks comprising battery-free on-body sensors and textile-based wireless readers can enable daily health monitoring and activity tracking by continuously monitoring physiological signals across the body. However, previous textile-based wireless networks made of coils or antennas have limited the data and power transmission area because cover

Yan-Guang Yue, Shuai Yang, Zheng-Xin Liu, Yan Chen

It is known that the topological Hopf term in two-dimensional (2D) spin systems can be derived by coupling to massless Dirac fermions. We establish a universal rule governing the generation of Hopf terms in 2D quantum spin systems coupled to Dirac fermions. The key insight identifies the Hopf coefficient as the oriented volume in the $\mathfrak{su}(2)$ Lie a

Yasaman Asgari, Hongyu Zhou, Ozgur Kadir Ozer, Rezvaneh Rezapour

The 2010-2011 Arab Spring reverberated far beyond politics, reshaping how the Middle East and North Africa region (MENA) is studied. Analyzing 3.7 million Scopus-indexed articles published between 2002 and 2019, we find that mentions of ten of these countries in titles or abstracts rose significantly after 2011 relative to the global baseline, with Egypt rec

Islem Saadaoui, Christopher Robin Bryant, Hichem Rejeb, Alexandru-Ionuţ Petrişor

This research examines global issues concerning the development of mountain areas considered as territories difficult to manage. The case study area is part of the sub-region of High Alpine Steppes belonging to the Tunisian Ridge and reaching Tebessa Mountains in Algeria. The central question of this article is based on the analysis of the links between the

Ihab Asaad, Maha Shadaydeh, Joachim Denzler

Machine learning classification models trained with empirical risk minimization (ERM) often inadvertently rely on spurious correlations. When absent in the test data, these unintended associations between non-target attributes and target labels lead to poor generalization. This paper addresses this problem from a model optimization perspective and proposes a

Christopher D. Woodgate, Hubert J. Naguszewski, David Redka, Ján Minár

We study the thermodynamics and phase stability of the AlTiVNb and AlTiCrMo refractory high-entropy superalloys using a combination of \textit{ab initio} electronic structure theory -- namely a concentration wave analysis -- and atomistic Monte Carlo simulations. Our multiscale approach is suitable both for examining atomic short-range order in the solid sol