March 2025 arXiv papers — page 31

J. M. P. Carmelo, J. E. C. Carmelo

Using a general representation that accounts for the effects on finite-temperature spin and charge transport of the global [SU (2) X SU(2) X U(1)]/(Z2 X Z2) symmetry of the one-dimensional (1D) Hubbard model, we show that important finite-temperature transport quantities as the finite-field spin and finite-chemical potential charge stiffnesses and the zero-f

Chun Yin Lam, André Schlichting

The continuous generalized exchange-driven growth model (CGEDG) is a system of integro-differential equations describing the evolution of cluster mass under mass exchange. The rate of exchange depends on the masses of the clusters involved and the mass being exchanged. This can be viewed as both a continuous generalization of the exchange-driven growth model

Alimjan Mattursun, Liejun Wang, Yinfeng Yu, Chunyang Ma

Speech self-supervised learning (SSL) has made great progress in various speech processing tasks, but there is still room for improvement in speech enhancement (SE). This paper presents BSP-MPNet, a dual-path framework that combines self-supervised features with magnitude-phase information for SE. The approach starts by applying the perceptual contrast stret

F. Archilli, Sw. Banerjee, E. Ben-Haim, F. U. Bernlochner

Heavy-flavour physics is an essential component of the particle-physics programme, offering critical tests of the Standard Model and far-reaching sensitivity to physics beyond it. Experiments such as LHCb, Belle II, and BESIII drive progress in the field, along with contributions from ATLAS and CMS. The LHCb Upgrade II and upgraded Belle II experiments will

S. Siddardha Chelluri, Sanchar Sharma, Frank Schmidt, Silvia Viola Kusminskiy

Long-distance quantum communication necessitates the use of quantum repeaters, which typically include highly coherent quantum memories. We provide a theoretical analysis of the secret key rates for a quantum repeater system incorporating bosonic error correction and memory components. Specifically, we focus on the application of Binomial codes for two repea

Pedro-José Cazorla García, Lucas Villagra Torcomian

In his breakthrough article, Darmon presented a program to study Generalized Fermat Equations (GFE) via abelian varieties of $\text{GL}_2$-type over totally real fields. So far, only Jacobians of some Frey hyperelliptic curves have been used with that purpose. In the present article, we show how most of the known Frey hyperelliptic curves are particular inst

Alonso Castillo-Ramirez, Alejandro Vazquez-Aceves, Angel Zaldivar-Corichi

We study two categories of cellular automata. First, for any group $G$, we consider the category $\mathcal{CA}(G)$ whose objects are configuration spaces of the form $A^G$, where $A$ is a set, and whose morphisms are cellular automata of the form $\tau : A_1^G \to A_2^G$. We prove that the categorical product of two configuration spaces $A_1^G$ and $A_2^G$ i

Tongchao Luo, Mingquan Qiu, Zhenyu Wu, Zebo Zhao

To address the challenges of low diagnostic accuracy in traditional bearing fault diagnosis methods, this paper proposes a novel fault diagnosis approach based on multi-scale spectrum feature images and deep learning. Firstly, the vibration signal are preprocessed through mean removal and then converted to multi-length spectrum with fast Fourier transforms (

Vrinda Mehta, Hans De Raedt, Kristel Michielsen, Fengping Jin

Understanding the physical nature of the D-Wave annealers remains a subject of active investigation. In this study, we analyze the sampling behavior of these systems and explore whether their results can be replicated using quantum and Markovian models. Employing the standard and the fast annealing protocols, we observe that the D-Wave annealers sample state

Ryunosuke Takebayashi, Vitor Hideyo Isume, Takuya Kiyokawa, Weiwei Wan

Cooking tasks remain a challenging problem for robotics due to their complexity. Videos of people cooking are a valuable source of information for such task, but introduces a lot of variability in terms of how to translate this data to a robotic environment. This research aims to streamline this process, focusing on the task plan generation step, by using a

Antonis Matakos, Martino Ciaperoni, Heikki Mannila

The Min-Max Fair PCA problem seeks a low-rank representation of multi-group data such that the the approximation error is as balanced as possible across groups. Existing approaches to this problem return a rank-$d$ fair subspace, but lack the fundamental containment property of standard PCA: each rank-$d$ PCA subspace should contain all lower-rank PCA subspa

Jonathan Lee, Bolivar Solarte, Chin-Hsuan Wu, Jin-Cheng Jhang

We present uLayout, a unified model for estimating room layout geometries from both perspective and panoramic images, whereas traditional solutions require different model designs for each image type. The key idea of our solution is to unify both domains into the equirectangular projection, particularly, allocating perspective images into the most suitable l

Yu-Hui Liang, Chun-Hao Lai, Chin-Wei Wang, Shinichiro Yano

Materials with a spiral spin ordering always show a rich phase diagram and can be a playground for studying the exotic physical properties associated with spiral magnetism. Using neutron elastic and resonant x-ray scattering on a high-quality single crystal YBaCuFeO$_{5}$, we demonstrate YBaCuFeO$_{5}$ to be a helimagnet consisting of a double-spiral spin or

Somayeh Hosseinhashemi, Philipp Rieder, Orkun Furat, Benedikt Prifling

The 3D microstructure of porous media, such as electrodes in lithium-ion batteries or fiber-based materials, significantly impacts the resulting macroscopic properties, including effective diffusivity or permeability. Consequently, quantitative structure-property relationships, which link structural descriptors of 3D microstructures such as porosity or geode

Yu Cheng, Harun Šiljak

Recent advancements in unmanned aerial vehicle (UAV) technology have opened new avenues for dynamic data collection in challenging environments, such as sports fields during fast-paced sports action. For the purposes of monitoring sport events for dangerous injuries, we envision a coordinated UAV fleet designed to capture high-quality, multi-view video foota

Gaofeng Zhou, Rui-Feng Wang, Kangning Cui

Community detection, which identifies densely connected node clusters with sparse between-group links, is vital for analyzing network structure and function in real-world systems. Most existing community detection methods based on GCNs primarily focus on node-level information while overlooking community-level features, leading to performance limitations on

Xingdi Yuan, Morgane M Moss, Charbel El Feghali, Chinmay Singh

Large Language Models (LLMs) are increasingly relied upon for coding tasks, yet in most scenarios it is assumed that all relevant information can be either accessed in context or matches their training data. We posit that LLMs can benefit from the ability to interactively explore a codebase to gather the information relevant to their task. To achieve this, w

Nicolas Guès

We prove explicit linear stable ranges for the $\mathsf{FI}$-modules $\mathrm{Hom}(\pi_p \mathrm{Conf} M, \mathbb Z)$ and $\mathrm{Ext}(\pi_p \mathrm{Conf} M, \mathbb Z)$ with $\mathrm{Conf} M$ being the configuration co$\mathsf{FI}$-space of a $d$-dimensional manifold with $d \geq 3$. The proof of this result uses a homotopy-theoretic approach to representa

Hyunjun Lee, Hyunsoo Lee, Sookwan Han

There have been many attempts to leverage multiple diffusion models for collaborative generation, extending beyond the original domain. A prominent approach involves synchronizing multiple diffusion trajectories by mixing the estimated scores to artificially correlate the generation processes. However, existing methods rely on naive heuristics, such as avera

Tomona Kinugawa, Tetsuo Hyodo

The internal structure of the near-threshold exotic hadrons, $T_{cc}$ and $X(3872)$, are studied by respecting the decay and coupled-channel contributions. The effective field theory model is introduced to calculate the compositeness, the probability of finding the hadronic molecular component. Applying the new interpretation scheme for the complex composite

Zheng-He Liu, Yu Liu, Gui-Han Liang, Cheng-Lin Deng

Time-dependent drives hold the promise of realizing non-equilibrium many-body phenomena that are absent in undriven systems. Yet, drive-induced heating normally destabilizes the systems, which can be parametrically suppressed in the high-frequency regime by using periodic (Floquet) drives. It remains largely unknown to what extent highly controllable quantum

Saeid Sadeghi Vilni, Risto Wichman

We consider a pull-based real-time tracking system consisting of multiple partially coupled sources and a sink. The sink monitors the sources in real-time and can request one source for an update at each time instant. The sources send updates over an unreliable wireless channel. The sources are partially coupled, and updates about one source can provide part

Francesco Ferraro, Christian Grilletta, Emanuele Pigani, Samir Suweis

Explaining the wide range of dynamics observed in ecological communities is challenging due to the large number of species involved, the complex network of interactions among them, and the influence of multiple environmental variables. Here, we consider a general framework to model the dynamics of species-rich communities under the effects of external enviro

Pampa Paul

In this article, we have determined the irreducible unitary representations with non-zero relative Lie algebra cohomology and Poincare polynomials of cohomologies of these representations for a connected Lie group G with Lie algebra f4(4). We have also determined a necessary and sufficient condition for these representations to be discrete series representat

Yiming Pan, Danni Chen, Xiaoxi Xu, Zhaopin Chen

We propose a novel amplification mechanism for high harmonic generation (HHG) in solids by leveraging bandgap engineering with momentum k-gaps. By constructing a simple diatomic lattice featuring balanced, alternating gain and loss profiles, facilitated by an array of four-level systems, we explore the physics of k-gap-amplified Bloch oscillations in the int

Viet-Anh Le, Panagiotis Kounatidis, Andreas A. Malikopoulos

In this paper, we develop a fast mixed-integer convex programming (MICP) framework for multi-robot navigation by combining graph attention networks and distributed optimization. We formulate a mixed-integer optimization problem for receding horizon motion planning of a multi-robot system, taking into account the surrounding obstacles. To address the resultin

Peter Danchev, Mina Doostalizadeh, Omid Hasanzadeh, Arash Javan

The target of the present work is to give a new insight in the theory of {\it strongly weakly nil-clean} rings, recently defined by Kosan and Zhou in the Front. Math. China (2016) and further explored in detail by Chen-Sheibani in the J. Algebra Appl. (2017). Indeed, we consider those rings whose non-units are strongly weakly nil-clean and succeed to establi

Juliana Costa-Silva, David Menotti, Fabricio M. Lopes

Motivation: Bulk RNA-Seq is a widely used method for studying gene expression across a variety of contexts. The significance of RNA-Seq studies has grown with the advent of high-throughput sequencing technologies. Computational methods have been developed for each stage of the identification of differentially expressed genes. Nevertheless, there are few stud

Moskov Amaryan

In this paper, I pay tribute to my exceptional colleagues and friends Dmitri Diakonov, Victor Petrov, and Maxim Polyakov by examining the experimental progress and current status of the searches of the $\Theta^+$ pentaquark from its inception to the present.

Yuwei Yin, EunJeong Hwang, Giuseppe Carenini

Intent, typically clearly formulated and planned, functions as a cognitive framework for communication and problem-solving. This paper introduces the concept of Speaking with Intent (SWI) in large language models (LLMs), where the explicitly generated intent encapsulates the model's underlying intention and provides high-level planning to guide subsequent an

Pawel Gajer, Jacques Ravel

We introduce a novel approach to compositional data analysis based on $L^{\infty}$-normalization, addressing challenges posed by zero-rich high-throughput data. Traditional methods like Aitchison's transformations require excluding zeros, conflicting with the reality that omics datasets contain structural zeros that cannot be removed without violating inhere

Jalal Jalali, Mostafa Darabi, Rodrigo C. de Lamare

Reconfigurable Intelligent Surfaces (RIS) have emerged as a key solution to dynamically adjust wireless propagation by tuning the reflection coefficients of large arrays of passive elements. Reconfigurable Holographic Surfaces (RHS) build on the same foundation as RIS but extend it by employing holographic principles for finer-grained wave manipulation | tha

Achint Soni, Meet Soni, Sirisha Rambhatla

Text-guided image editing aims to modify specific regions of an image according to natural language instructions while maintaining the general structure and the background fidelity. Existing methods utilize masks derived from cross-attention maps generated from diffusion models to identify the target regions for modification. However, since cross-attention m

Florian Onur Kuhlmeier, Leon Hanschmann, Melina Rabe, Stefan Luettke

LLMs promise to overcome limitations of rule-based mental health chatbots through improved natural language capabilities, yet their ability to deliver evidence-based psychological interventions remains largely unverified because evaluations rarely apply the validated fidelity measures used to assess psychotherapists. We developed an LLM-based chatbot that de

Shumpei Fujimura, Ibrahim Abd El-Sadek, Rion Morishita, Shuichi Makita

The wavelength and system-resolution dependencies of dynamic optical coherence tomography (DOCT) are investigated experimentally and numerically. Experimental investigations demonstrate significant wavelength dependency for the DOCT values but no resolution dependency. Numerical simulations were performed using diffusion, random-ballistic motion, and mono-di

Haruto Nakashima, Siddhartha Ganguly, Kohei Morimoto, Kenji Kashima

This article introduces a formation shape control algorithm, in the optimal control framework, for steering an initial population of agents to a desired configuration via employing the Gromov-Wasserstein distance. The underlying dynamical system is assumed to be a constrained linear system and the objective function is a sum of quadratic control-dependent st

Ahmed Naeem, Liza Afeef, Huseyin Arslan

A key challenge in dual-polarized multiplexing for joint radar and communication (JRC) systems is cross-polarization (cross-pol) leakage caused by depolarization. In conventional MIMO systems, depolarization arises solely from the channel; however, in XL-MIMO systems, non-stationary properties of the array cause additional polarization shifts at each antenna

J. Quetzalcóatl Toledo-Marin, Anindita Maiti, Geoffrey C. Fox, Roger G. Melko

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. We address two central challenges: clarifying the connections

Udita Goswami, Shuvashree Mondal

The analysis of panel count data has garnered considerable attention in the literature, leading to the development of multiple statistical techniques. In inferential analysis, most works focus on leveraging estimating equation-based techniques or conventional maximum likelihood estimation. However, the robustness of these methods is largely questionable. In

Nihar Ranjan Ghosh, Malay K. Nandy

Classical general relativity predicts a singularity at the center of a black hole, where known laws of physics break down. This suggests the existence of deeper, yet unknown principles of Nature. Among various theoretical possibilities, one of the most promising proposals is a transition to a de Sitter phase at the BH core. This transition, originally propos

Zetao Lin, Benjamin Kadoch, Saddrudin Benkadda, Kai Schneider

We investigate the behavior of heavy impurities in edge plasma turbulence by analyzing their trajectories using the Hasegawa-Wakatani model. Through direct numerical simulations, we track ensembles of charged impurity particles over hundreds of eddy turnover times within statistically steady turbulent flows. Assuming that heavy impurities lag behind the flow

Carlo Flore, Cynthia Hadjidakis, Daniel Kikoła, Aleksander Kusina

We perform an analysis of the potential impact of future $D$- and $B$-meson measurement within the SMOG2 fixed-target program at the LHCb experiment on nuclear parton distribution functions. Following~\cite{Bursche:2018orf}, we assume that SMOG2 will collect data for five nuclear targets: He, Ne, Ar, Kr, Xe and hydrogen which will provide a baseline for cons

Umer Butt, Stalin Veranasi, Günter Neumann

As the Information Retrieval (IR) field increasingly recognizes the importance of inclusivity, addressing the needs of low-resource languages remains a significant challenge. Transliteration between Urdu and its Romanized form, Roman Urdu, remains underexplored despite the widespread use of both scripts in South Asia. Prior work using RNNs on the Roman-Urdu-

Abhay Kumar, Dushyant Sharma, Mayukha Pal

Grid-forming converters (GFCs) are crucial for frequency and voltage stability in modern power systems. However, their performance under overload conditions remains a challenge. This paper highlights the limitations of existing approaches in managing DC source saturation and AC current limits, emphasizing the need for improved control strategies to ensure sy

Q. Rogliardo, A. Kanellakopoulos, H. Corcelle, M. Fedel

Monitoring $^{90}$Sr contamination in milk following a nuclear accident is critical due to its radiotoxicity and calcium-mimicking behaviour, leading to accumulation in bones and teeth. This study presents a high-efficiency protocol for quantifying$^{90}$Sr in cow milk by integrating freeze-drying, high-temperature calcination, ion exchange chromatography an

Robert Chew, Matthew R. Williams, Elan A. Segarra, Alexander J. Preiss

Differential privacy (DP) is becoming increasingly important for deployed machine learning applications because it provides strong guarantees for protecting the privacy of individuals whose data is used to train models. However, DP mechanisms commonly used in machine learning tend to struggle on many real world distributions, including highly imbalanced or s

Kouichi Taira

In this paper, we study time decay estimates for the Schr\"odinger propagator on the product cone $(X,g)$, where $X=C(\rho \mathbb{S}^{n-1})=(0,\infty)\times \rho\mathbb{S}^{n-1}$. We prove that the usual dispersive estimate holds when the radius $\rho$ is greater than or equal to 1 and fails otherwise. A part of the former result was already established in

Christine W. Bang, Vanessa Didelez

In this paper we consider the use of tiered background knowledge within constraint based causal discovery. Our focus is on settings relaxing causal sufficiency, i.e. allowing for latent variables which may arise because relevant information could not be measured at all, or not jointly, as in the case of multiple overlapping datasets. We first present novel i

Yuxi Hu, Jun Zhang, Zhe Zhang, Rafael Weilharter

Multi-view Stereo (MVS) aims to estimate depth and reconstruct 3D point clouds from a series of overlapping images. Recent learning-based MVS frameworks overlook the geometric information embedded in features and correlations, leading to weak cost matching. In this paper, we propose ICG-MVSNet, which explicitly integrates intra-view and cross-view relationsh

Keiichi Ando, Kohki Kawabata, Tatsuma Nishioka

We investigate the gauging of a $\mathbb{Z}_N$ symmetry in lattice conformal field theories (CFTs), also known as Narain CFTs. For prime $N$, we derive a spin selection rule for operators in a $\mathbb{Z}_N$ charge-twisted sector of a general bosonic CFT. Using this result, we formulate the gauging procedures in lattice CFTs as modifications of the momentum

Dorian Martino, Katarzyna Mazowiecka, Rémy Rodiac

In this article, we show that sequences of $(n+\alpha)$-harmonic maps with a free boundary in $\mathbb S^{d-1}$, where $\alpha$ is a parameter tending to zero, converge to a bubble tree. For such sequences, we prove in detail that the limiting energy is equal to the energy of the macroscopic limit plus the sum of the energies of certain ``bubbles'', each mul

Matthéo Lecrivain, Hanifa Barry, Dalila Tamzalit, Houari Sahraoui

The microservices architectural style has become the de facto standard for large-scale cloud applications, offering numerous benefits in scalability, maintainability, and deployment flexibility. Many organizations are pursuing the migration of legacy monolithic systems to a microservices architecture. However, this process is challenging, risky, time-intensi

Karan Bhuwalka, Hari Ramachandran, Swati Narasimhan, Adrian Yao

Surging demand for graphite in energy storage applications has led to concerns about supply chai security for manufacturers and nations globally. Currently, China produces over 92% of graphite for anodes, posing a risk for industries reliant on graphite supply. Here, we systematically assess the costs of producing natural and synthetic battery-grade graphite

Sergio I. Rey, Martin J. Cross, Malte L. Welsch, Frederik Schröder

Coherent acoustic phonons (CAPs)$-$propagating strain waves that can dynamically modify the structure and symmetry of a crystal$-$offer unique opportunities for controlling material properties. We investigate CAP generation in the Janus-like layered alloy tungsten sulfide selenide (WS$_x$Se$_{1-x}$, hereafter WSSe). Employing high-fluence photoexcitation at

Paweł Cieśliński, Tamás Vértesi, Mateusz Kowalczyk, Wiesław Laskowski

Imperfect detection efficiency remains one of the major obstacles in achieving loophole-free Bell tests over long distances. At the same time, the challenge of establishing a common reference frame for measurements becomes more pronounced as the separation between parties increases. In this work, we tackle both of these issues by examining the impact of limi

Christopher T. Hill

The Nambu--Jona-Lasinio (NJL) model involves a pointlike 4-fermion interaction. While it gives a useful description of chiral dynamics (mainly in QCD), it nonetheless omits the crucially important internal wave-function of a two-body bound state, $\phi(r)$. This becomes significant near critical coupling where $\phi(r)$ extends to large distance, leading to

Denis Céolin, Tsveta Miteva, Jean-Pascal Rueff, Rémi Dupuy

Understanding the interaction between metal ions and their aqueous environment is fundamental in many areas of chemistry, biology, and environmental science. In this study, we investigate the electronic structure of hydrated calcium ions, focusing on how water molecules influence the behavior of the metal ion. We employed advanced X-ray techniques, including

Niklas Valentin Lehmann

Can we create binding agreements between nations? Recently, scholars have argued that blockchain technology enables us to do so. Given that this could greatly affect the anarchical world order implied by state sovereignty, this remarkable claim is investigated thoroughly. By focusing on the technical implementation of smart contracts between nations, this ar

Roberto Hernández Palomares

We show that the core inclusion arising from a Cuntz-Pimsner algebra generated by a full, faithful and dualizable correspondence is C*-discrete, and express it as a crossed-product by an action of a unitary tensor category. In particular, we show the inclusion of the UHF subalgebra of the Cuntz algebra arising as the fixed-point subalgebra under the gauge sy

Suzukaze Kamei, Hideaki Kawaguchi, Shin Nishio, Takahiko Satoh

To evaluate the performance of quantum computing systems relative to classical counterparts and explore the potential, we propose a game-solving benchmark based on Elo ratings in the game of tic-tac-toe. We compare classical convolutional neural networks (CCNNs), quantum or quantum convolutional neural networks (QNNs, QCNNs), and hybrid classical-quantum neu

Ana-Maria Bucur, Andreea-Codrina Moldovan, Krutika Parvatikar, Marcos Zampieri

Depression is the most common mental health disorder, and its prevalence increased during the COVID-19 pandemic. As one of the most extensively researched psychological conditions, recent research has increasingly focused on leveraging social media data to enhance traditional methods of depression screening. This paper addresses the growing interest in inter

Reiko Liu, Wen-Jie Ma

Assuming the existence of crossing symmetric celestial OPE, we propose a method to reconstruct four-point massless scattering amplitudes in the framework of celestial holography. This method relies only on CFT techniques and a remarkable property: scattering amplitudes can be derived from a single conformal block coefficient in celestial CFT. Utilizing this

Reinder Meinsma

We disprove a conjecture of Kuznetsov--Shinder, which posits that $D$-equivalent simply connected varieties are $L$-equivalent, by constructing a counterexample using moduli spaces of sheaves on K3 surfaces.

Ji Li, Ke Wang, Qiliang Wu, Qing Yu

A wave front and a wave back that spontaneously connect two hyperbolic equilibria, known as a heteroclinic wave loop, give rise to periodic waves with arbitrarily large spatial periods through the heteroclinic bifurcation. The nonlinear stability of these periodic waves is established in the setting of the FitzHugh-Nagumo equation, which is a well-known reac

Eleanor Gleave, Andrew Jaffe

Gravitational wave (GW) observations probe both a diffuse, stochastic gravitational wave background (SGWB) as well as individual cataclysmic events such as the merger of two compact objects. The detection and description of the gravitational-wave background requires somewhat different techniques than required for individual events. In this paper, we probe th

Sai Karthikeya Vemuri, Tim Büchner, Joachim Denzler

Implicit Neural Representations (INRs) model signals as continuous, differentiable functions. However, monolithic INRs scale poorly with data dimensionality, leading to excessive training costs. We propose F-INR, a framework that addresses this limitation by factorizing a high-dimensional INR into a set of compact, axis-specific sub-networks based on functio

Ruotong Yin, Yuanji Li, Zengyi Du, Dengpeng Yuan

UTe2 is a promising candidate for spin-triplet superconductor, yet its exact superconducting order parameter remains highly debated. Here, via scanning tunneling microscopy/spectroscopy, we observe a novel type of magnetic vortex with distinct dark-bright contrast in local density of states on UTe2 (011) surface under a perpendicular magnetic field, resembli

Dilnoza Muslimova, Niels Rietveld

This perspective posits that gene-environment interplay (GxE) studies should be developed both theoretically and empirically to be of relevance to policy makers. On the theoretical front, this development is essential because the current literature lacks the integration of a clear framework capturing the various goals of public policies. Empirically, GxE mod

Yue Li, Meng Tian, Zhenyu Lin, Jiangtong Zhu

Existing benchmarks for Vision-Language Model (VLM) on autonomous driving (AD) primarily assess interpretability through open-form visual question answering (QA) within coarse-grained tasks, which remain insufficient to assess capabilities in complex driving scenarios. To this end, we introduce $\textbf{VLADBench}$, a challenging and fine-grained dataset fea

Yuxue Hu, Junsong Li, Meixuan Chen, Dongyu Su

Euphemism identification deciphers the true meaning of euphemisms, such as linking "weed" (euphemism) to "marijuana" (target keyword) in illicit texts, aiding content moderation and combating underground markets. While existing methods are primarily text-based, the rise of social media highlights the need for multimodal analysis, incorporating text, images,

Nils Christian Aars Wilhelmsen, Ole Morten Aamo

The problem of leak detection in a pipeline with nonlinear friction is considered. A distributed observer-based method is proposed which applies a linearised, distributed adaptive observer design to the nonlinear model. The methodology is tested in simulations for two different operating points.

Yifei Wang, Shuting Wu, Genke Yang, Jian Chu

Mathematical Programs with Complementarity Constraints (MPCC) are critical in various real-world applications but notoriously challenging due to non-smoothness and degeneracy from complementarity constraints. The $\ell_1$-Exact Penalty-Barrier enhanced \texttt{IPOPT} improves performance and robustness by introducing additional inequality constraints and dec

Brett Levac, Ajil Jalal, Kannan Ramchandran, Jonathan I. Tamir

Blind inverse problems in imaging arise from uncertainties in the system used to collect (noisy) measurements of images. Recovering clean images from these measurements typically requires identifying the imaging system, either implicitly or explicitly. A common solution leverages generative models as priors for both the images and the imaging system paramete

Haote Yang, Xingjian Wei, Jiang Wu, Noémi Ligeti-Nagy

We introduce OpenHuEval, the first benchmark for LLMs focusing on the Hungarian language and specifics. OpenHuEval is constructed from a vast collection of Hungarian-specific materials sourced from multiple origins. In the construction, we incorporated the latest design principles for evaluating LLMs, such as using real user queries from the internet, emphas

Suman Pramanick, Somnath Bharadwaj, Khandakar Md Asif Elahi, Rajesh Mondal

The rapid evolution of the cosmological neutral hydrogen (HI) distribution during the EoR is imprinted along the line of sight (LoS) in the redshifted 21-cm signal due to the light cone (LC) effect. The LC EoR 21-cm signal ceases to be ergodic along the LoS, and the Fourier transform-based three-dimensional power spectrum (PS) fails to capture the full two-p

Giorgia Adorni

The rapid digitalisation of contemporary society has profoundly impacted various facets of our lives, including healthcare, communication, business, and education. The ability to engage with new technologies and solve problems has become crucial, making CT skills, such as pattern recognition, decomposition, and algorithm design, essential competencies. In re

Lipo Mo, Jianjun Li, Min Zuo, Lei Wang

The evaluation of final-iteration tracking performance is a formidable obstacle in distributed online optimization algorithms. To address this issue, this paper proposes a novel evaluation metric named distributed forgetting-factor regret (DFFR). It incorporates a weight into the loss function at each iteration, which progressively reduces the weights of his

Erick Elejalde, Timur Naushirvanov, Kyriaki Kalimeri, Elisa Omodei

This study examines behavioral responses to mobile phone evacuation alerts during the February 2024 wildfires in Valpara\'iso, Chile. Using anonymized mobile network data from 580,000 devices, we analyze population movement following emergency SMS notifications. Results reveal three key patterns: (1) initial alerts trigger immediate evacuation responses with

Huacheng Li, Jingyong Su, Kai Wang

The rapid development of network technologies and industrial intelligence has augmented the connectivity and intelligence within the automotive industry. Notably, in the Internet of Vehicles (IoV), the Controller Area Network (CAN), which is crucial for the communication of electronic control units but lacks inbuilt security measures, has become extremely vu

Timo Budszuhn, Mark Joachim Krallmann, Daniel Horn

The challenge of noisy multi-objective optimization lies in the constant trade-off between exploring new decision points and improving the precision of known points through resampling. This decision should take into account both the variability of the objective functions and the current estimate of a point in relation to the Pareto front. Since the amount an

Natalia Tziotziou

We provide extensions of geometric inequalities about sections and projections of convex bodies to the setting of integrable log-concave functions. Namely, we consider suitable generalizations of the affine and dual affine quermassintegrals of a log-concave function $f$ and obtain upper and lower estimates for them in terms of the integral $\|f\|_1$ of $f$,

Liangrui Wei, Kai-Ming Ho, Renata M. Wentzcovitch, Yang Sun

The Fe-Ni alloy is believed to be the main component of Earth's core. Yet, a comprehensive understanding of phase equilibria near the melting point of this alloy under core conditions is still lacking, leaving the effect of nickel inconclusive. Using ab initio simulations, we computed Gibbs free energy and phase diagram for liquid and solid solutions of the

D. M. A. Meyer, D. F. Torres, Z. Meliani

Pulsars are one of the possible final stages in the evolution of massive stars. If a supernova explosion is anisotropic, it can give the pulsar a powerful kick, propelling it to supersonic speeds. The resulting pulsar wind nebula is significantly reshaped by its interaction with the surrounding medium as the pulsar moves through it. First, the pulsar crosses

Siavash Mahmoudi, Amirreza Davar, Dongyi Wang

Deformable Object Manipulation (DOM) remains a critical challenge in robotics due to the complexities of developing suitable model-based control strategies. Deformable Tool Manipulation (DTM) further complicates this task by introducing additional uncertainties between the robot and its environment. While humans effortlessly manipulate deformable tools using

Tsz Ho Chan

In this paper, we study how short an interval $[x, x + x^\theta]$ contains an integer of the form $n_1 n_2 n_3$ and $m_1 m_2 m_3 m_4$ with $n_1 \approx n_2 \approx n_3$ and $m_1 \approx m_2 \approx m_3 \approx m_4$. The new idea is to adopt a second moment method (usually used for almost all results) to deduce a result for all short intervals.

Edwin Tay, Nazli Tümer, Amir A. Zadpoor

Living biological tissue is a complex system, constantly growing and changing in response to external and internal stimuli. These processes lead to remarkable and intricate changes in shape. Modeling and understanding both natural and pathological (or abnormal) changes in the shape of anatomical structures is highly relevant, with applications in diagnostic,

Conor Murphy, Ross Towe, Philip Jonathan

We assess the value of calibrating forecast models for significant wave height Hs, wind speed W and mean spectral wave period Tm for forecast horizons between zero and 168 hours from a commercial forecast provider, to improve forecast performance for a location in the central North Sea. We consider two straightforward calibration models, linear regression (L

Shaoxuan Cui, Guofeng Zhang, Hildeberto Jardon-Kojakhmetov, Ming Cao

It is known that a linear system with a system matrix A constitutes a Hamiltonian system with a quadratic Hamiltonian if and only if A is a Hamiltonian matrix. This provides a straightforward method to verify whether a linear system is Hamiltonian or whether a given Hamiltonian function corresponds to a linear system. These techniques fundamentally rely on t

Hamadi Chihaoui, Paolo Favaro

Two of the main challenges of image restoration in real-world scenarios are the accurate characterization of an image prior and the precise modeling of the image degradation operator. Pre-trained diffusion models have been very successfully used as image priors in zero-shot image restoration methods. However, how to best handle the degradation operator is st

Tsz Ho Chan

This note concerns the non-existence of three consecutive powerful numbers. We use Pell equations, elliptic curves, and second-order recurrences to show that there are no such triplets with the middle term a perfect cube and each of the other two having only a single prime factor raised to an odd power.

Beatrice Brienza, Anna Fino, Gueo Grantcharov

In the present paper we provide a construction via mapping tori of (non Bismut flat) strong HKT and generalized hyperk\"ahler structures on compact manifolds. The skew-symmetric torsion is parallel, but the manifolds are not a product of a hyperk\"ahler manifold and a compact Lie group.

Shuming Liu, Chen Zhao, Tianqi Xu, Bernard Ghanem

Large video-language models (VLMs) have demonstrated promising progress in various video understanding tasks. However, their effectiveness in long-form video analysis is constrained by limited context windows. Traditional approaches, such as uniform frame sampling, often inevitably allocate resources to irrelevant content, diminishing their effectiveness in

Adam Morawiec

The geometric state of a flat boundary is frequently described using the so-called macroscopic parameters. They are a principal tool for dealing with interfaces at the continuous scale. The paper describes a new method for macroscopic identification of boundaries. The proposed approach is based on Euler angles representing orientations of the crystals. Two p

L Baratchart, D P Hardin, C Villalobos-Guillén

We describe a method to discretize optimization problems arising in the regularization of linear inverse problem having compact forward operator defined on 3-D valed measures, compactly supported on a fixed set. The criterion is a quadratic residual attached to the data, with an additive penalization of the total variation of the measure.

Martin Werres, Dariusz Niedziela, Arnulf Latz, Birger Horstmann

Lithium metal batteries are promising for next-generation high-energy-density batteries, especially when lithium is directly plated on a current collector. However, lithium whiskers can form in the early stages of electroplating. These whiskers lead to low Coulombic efficiency due to isolated lithium formation during stripping. The mechanism of whisker forma

John Murzaku, Owen Rambow

The use of omni-LLMs (large language models that accept any modality as input), particularly for multimodal cognitive state tasks involving speech, is understudied. We present OmniVox, the first systematic evaluation of four omni-LLMs on the zero-shot emotion recognition task. We evaluate on two widely used multimodal emotion benchmarks: IEMOCAP and MELD, an

Filippo Girardi, Aadil Oufkir, Bartosz Regula, Marco Tomamichel

We study the quantum umlaut information, a correlation measure defined for bipartite quantum states $\rho_{AB}$ as a reversed variant of the quantum mutual information: $U(A;B)_\rho = \min_{\sigma_B} D(\rho_A\otimes \sigma_B\|\rho_{AB})$ in terms of the quantum relative entropy $D$. As in the classical case [Girardi et al., arXiv:2503.18910], this definition

Tomasz Kobos, Konrad Swanepoel

We prove that there are arbitrarily large equilateral sets of planar and symmetric convex bodies in the Banach--Mazur distance. The order of the size of these $d$-equilateral sets asymptotically matches the bounds of the size of maximum-size $d$-separated sets (determined by Bronstein in 1978), showing that our construction is essentially optimal.

Zhaojun Nan, Yunchu Han, Sheng Zhou, Zhisheng Niu

In edge intelligence systems, deep neural network (DNN) partitioning and data offloading can provide real-time task inference for resource-constrained mobile devices. However, the inference time of DNNs is typically uncertain and cannot be precisely determined in advance, presenting significant challenges in ensuring timely task processing within deadlines.

Jani Nykänen

We study mean field stochastic differential equations with a diffusion coefficient that depends on the distribution function of the unknown process in a discontinuous manner, which is a type of distribution dependent regime switching. To determine the distribution function we show that under certain conditions these equations can be transformed into SDEs wit