March 2025 arXiv papers — page 33

Satvir Kaur, Jiatong Wu, Siqi Xu, Chandan Mondal

We investigate the color structure of the deuteron by solving the light-front QCD Hamiltonian for its six-quark and six-quark-one-gluon components using basis light-front quantization. In this framework, the deuteron wavefunction consists of a singlet-singlet color state as well as additional hidden color states arising from non-trivial color rearrangements.

Spandan Choudhury, Jongsoo Kim, Paola Caselli, Chang Won Lee

CONTEXT: Dense cores are thought to be isolated from the surrounding cloud. However, observations of streamers and subsonic material outside core boundaries challenges this idea. AIMS: In this study, we aim to probe the extended subsonic region observed around the pre-stellar core H-MM1 in L1688 using multi-component kinematical analysis of very high-sensiti

Adrienn Pataki, Péter Raffai, István Csabai, Gábor Rácz

We constrain AvERA cosmologies in comparison with the flat $\Lambda$CDM model using cosmic chronometer (CC) data and the Pantheon+ sample of type Ia supernovae (SNe Ia). The analysis includes fits to both CC and SN datasets using the \texttt{dynesty} dynamic nested sampling algorithm. For model comparison, we use the Bayesian model evidences and Anderson-Dar

Jiaxin Han, Ming Li, Wenkang Jiang, Zhao Chen

We provide an overview of the Jiutian simulations, a hybrid simulation suite for the China Space Survey Telescope (CSST) extragalactic surveys. It consists of four complementary modules: the primary runs with high resolutions with the fiducial concordance cosmology, the emulator runs exploring the parameter uncertainties around the fiducial cosmology, the re

Bořek Reich, Matej Kunda, Fedor Zolotarev, Tuomas Eerola

We propose a novel, good-quality, and less demanding method for detecting knots on the surface of wooden logs using multimodal data fusion. Knots are a primary factor affecting the quality of sawn timber, making their detection fundamental to any timber grading or cutting optimization system. While X-ray computed tomography provides accurate knot locations a

Antun Balaz, Diego Blas, Oliver Buchmueller, Sergio Calatroni

Long-baseline atom interferometry is a promising technique for probing various aspects of fundamental physics, astrophysics and cosmology, including searches for ultralight dark matter (ULDM) and for gravitational waves (GWs) in the frequency range around 1~Hz that is not covered by present and planned detectors using laser interferometry. The MAGIS detector

Yuanrong Tang, Yu Kang, Yifan Wang, Tianhong Wang

Current AI counseling systems struggle with maintaining effective long-term client engagement. Through formative research with counselors and a systematic literature review, we identified five key design considerations for AI counseling interactions. Based on these insights, we propose CA+, a Cognition Augmented counselor framework enhancing contextual under

Zhenxiang Ma, Zhenyu Yang, Miao Tao, Yuanzhen Zhou

3D reconstruction is vital for applications in autonomous driving, virtual reality, augmented reality, and the metaverse. Recent advancements such as Neural Radiance Fields(NeRF) and 3D Gaussian Splatting (3DGS) have transformed the field, yet traditional deep learning frameworks struggle to meet the increasing demands for scene quality and scale. This paper

A. Sbaffoni, J. Liske, S. P. Driver, A. S. G. Robotham

From a carefully selected sample of $52\,089$ galaxies and $10\,429$ groups, we investigate the variation of the low-redshift galaxy stellar mass function (GSMF) in the equatorial Galaxy And Mass Assembly (GAMA) dataset as a function of four different environmental properties. We find that: (i) The GSMF is not strongly affected by distance to the nearest fil

Christopher J. Lustri, John R. King

We use exponential asymptotic analysis to identify the relevance of Stokes' phenomenon to integrability in discrete systems. We study Stokes' phenomenon in two discrete problems with the same (leading-order) continuous limit, a finite-difference discretisation of the first continuous Painlev\'{e} equation and the first discrete Painlev\'{e} equation, as well

Jonas Bresch, Dirk A. Lorenz, Felix Schneppe, Maximilian Winkler

This paper considers the problem of detecting adjoint mismatch for two linear maps. To clarify, this means that we aim to calculate the operator norm for the difference of two linear maps, where for one we only have a black-box implementation for the evaluation of the map, and for the other we only have a black-box for the evaluation of the adjoint map. We g

Manuela Sanguinetti, Alessandra Perniciano, Luca Zedda, Andrea Loddo

This work explores using Large Language Models (LLMs) to translate user preferences into energy optimization constraints for home appliances. We describe a task where natural language user utterances are converted into formal constraints for smart appliances, within the broader context of a renewable energy community (REC) and in the Italian scenario. We eva

M. Berretti, S. Mestici, L. Giovannelli, D. Del Moro

Solar flares result from the rapid conversion of stored magnetic energy within the Sun's corona. These energy releases are associated with coronal magnetic loops, which are rooted in dense photospheric plasma and are passively transported by surface advection. Their emissions cover a wide range of wavelengths, with soft X-rays being the primary diagnostic fo

Josef Cikhart, Aneta Leskourová, Michal H. Kolář

Ribosomes are critical biomolecular nanomachines responsible for protein synthesis in all known organisms. The function and dynamics of ribosomes can be studied using molecular dynamics computer simulations. Although this task remains challenging at atomic level, several studies have reported all-atom molecular dynamics simulations of the entire ribosome. Ho

Moncef Garouani, Josiane Mothe, Ayah Barhrhouj, Julien Aligon

The rapid evolution of machine learning (ML) has led to the widespread adoption of complex "black box" models, such as deep neural networks and ensemble methods. These models exhibit exceptional predictive performance, making them invaluable for critical decision-making across diverse domains within society. However, their inherently opaque nature raises con

M. S. Swapna, S. Sankararaman, D. Korte

In this work, Ag0 nanoparticles (NPs)were synthesized and detected by flow-injection analysis coupled to collinear dual-beam thermal lens spectrometric (TLS) detection. The estimated limit of detection was 0.8 microgram/L. The use of 2 the IonPac Cryptand G1 column enabled Ag0 NPs detection in the presence of interfering ions normally present in water. Ag0 n

Benjamin Fuks, Jonathan Kriewald, Miha Nemevšek, Fabrizio Nesti

We investigate a novel collider signature within the minimal Left-Right Symmetric Model, featuring a Higgs sector composed of a bi-doublet and two triplets. Our study focuses on a region of the parameter space where the $SU(2)_R$ charged gauge boson $W_R$ lies in the multi-TeV regime (3-100 TeV) and the additional Higgs states play a significant role. In thi

Jiaxi Liu, Fanrui Zeng, Hongyue Duyang, Wanlei Guo

Atmospheric neutrino oscillations are important to the study of neutrino properties, including the neutrino mass ordering problem. A good capability to identify neutrinos' flavor and neutrinos against antineutrinos is crucial in such measurements. In this paper, we present a machine-learning-based approach for identifying atmospheric neutrino events in a lar

Tianhang Zhang, Shengnan Fu, David M. Schultz, Zhonghua Zheng

Large language models afford opportunities for using computers for intensive tasks, realizing research opportunities that have not been considered before. One such opportunity could be a systematic interrogation of the scientific literature. Here, we show how a large language model can be used to construct a literature review of 2699 publications associated

Jean Michel Menjanahary, Rimvydas Krasauskas

Dupin cyclides are surfaces conformally equivalent to a torus, a circular cone, or a cylinder. Their patches admit rational bilinear quaternionic B\'ezier parametrizations and are used in geometric design and architecture. Dupin cyclidic cubes are a natural trivariate generalization of Dupin cyclide patches. In this article, we derive explicit formulas for c

Guy Damari, Itzik Klein

Autonomous underwater vehicles (AUVs) are sophisticated robotic platforms crucial for a wide range of applications. The accuracy of AUV navigation systems is critical to their success. Inertial sensors and Doppler velocity logs (DVL) fusion is a promising solution for long-range underwater navigation. However, the effectiveness of this fusion depends heavily

Noah Losch, Lucas Plagwitz, Antonius Büscher, Julian Varghese

We investigate the effectiveness of fine-tuning large language models (LLMs) on small medical datasets for text classification and named entity recognition tasks. Using a German cardiology report dataset and the i2b2 Smoking Challenge dataset, we demonstrate that fine-tuning small LLMs locally on limited training data can improve performance achieving compar

Moncef Garouani, Franck Ravat, Nathalie Valles-Parlangeau

The rise of artificial intelligence and data science across industries underscores the pressing need for effective management and governance of machine learning (ML) models. Traditional approaches to ML models management often involve disparate storage systems and lack standardized methodologies for versioning, audit, and re-use. Inspired by data lake concep

Maximilian Stegemeyer

We study the space of paths in a closed manifold $M$ with endpoints determined by an involution $f\colon M\to M$. If the involution is fixed point free and if $M$ is $2$-connected then this path space is the universal covering space of the component of non-contractible loops of the free loop space of $M/\mathbb{Z}_2$. On the homology of said path space we st

Ruilin Wang, Xiang Feng, Huiqun Yu, Edmund M-K Lai

In evolutionary multitasking, strategies such as crossover operators and skill factor assignment are critical for effective knowledge transfer. Existing improvements to crossover operators primarily focus on low-dimensional variable combinations, such as arithmetic crossover or partially mapped crossover, which are insufficient for modeling complex high-dime

Jingtao Li, Yingyi Liu, Xinyu Wang, Yunning Peng

Advanced interpretation of hyperspectral remote sensing images benefits many precise Earth observation tasks. Recently, visual foundation models have promoted the remote sensing interpretation but concentrating on RGB and multispectral images. Due to the varied hyperspectral channels,existing foundation models would face image-by-image tuning situation, impo

Lena Zellinger, Nicola Branchini, Víctor Elvira, Antonio Vergari

Many Monte Carlo (MC) and importance sampling (IS) methods use mixture models (MMs) for their simplicity and ability to capture multimodal distributions. Recently, subtractive mixture models (SMMs), i.e. MMs with negative coefficients, have shown greater expressiveness and success in generative modeling. However, their negative parameters complicate sampling

Baibhab Bose, Devvrat Tiwari, Subhashish Banerjee

Out-of-time order correlators (OTOCs) are crucial tools for studying quantum chaos as they show distinct scrambling behavior for chaotic Hamiltonians. We calculate OTOC and analyze the quantum information scrambling in atom-field and spin-spin interaction models, which are open-system models and exhibit non-Markovian behavior. We also examine the Loschmidt e

Tisha Ghosh

The wastage of perishable items has led to significant health and economic crises, increasing business uncertainty and fluctuating customer demand. This issue is worsened by online food delivery services, where frequent and unpredictable orders create inefficiencies in supply chain management, contributing to the bullwhip effect. This effect results in stock

Luigi Pacciani, Dawoon E. Kim, Riccardo Middei, Herman L. Marshall

We report the Imaging X-ray Polarimetry Explorer (IXPE) polarimetric and simultaneous multiwavelength observations of the high-energy-peaked BL Lacertae (HBL) object 1ES 1959+650, performed in 2022 October and 2023 August. In 2022 October IXPE measured an average polarization degree $\Pi_{\rm X}=9.4\;\!\%\pm 1.6\;\!\%$ and an electric-vector position angle $

Robert Pelka, Yuji Miyazaki, Yasuhiro Nakazawa, Dawid Pinkowicz

Magnetocaloric effect in [Nb$^\mathrm{IV}${($\mu$-CN)$_4$Mn$^\mathrm{II}$(H$_2$O)$_2$]}$_2\cdot$4H$_2$O]$_n$ molecular magnet is reported. The compound crystallizes in the tetragonal I4/m space group. It exhibits a phase transition to a long-range ferrimagnetically ordered state at $T_\mathrm{c}$ = 47.0(2) K. In order to calculate magnetocaloric properties r

Giovanni Donati, Dafydd Owen-Newns, Joshua Robertson, Xavier Porte

Neuromorphic computing, inspired by the functionality and efficiency of biological neural systems, holds promise for advancing artificial intelligence and computational paradigms. Resonant tunneling diodes (RTDs), thanks to their ability to generate neuronal dynamical responses, such as excitable spiking and refractoriness, have recently emerged as candidate

Ahana Bhattacharya, Andri Darmawan, Jeong Woo Han, Frederik Steinkamp

A two-dimensional electron gas (2DEG) forms at the interface of complex oxides like $SrTiO_{3}$ (STO) and $LaTiO_{3}$ (LTO), despite each material having a low native conductivity, as a band and a Mott insulator, respectively. The interface 2DEG hosts charge carriers with moderate charge carrier density and mobility that raised interest as a material system

Hidemitsu Takahashi, Atsutoshi Ikeda, Shunsaku Kitagawa, Hirokazu Kadobayashi

We report X-ray diffraction patterns and calculated electronic band structures of the Dirac line-nodal material CaSb$_2$ under pressure. Its superconducting transition temperature ($T_{\mathrm{c}}=1.7$ K) increases under pressure and reaches a maximum at 3.4 K at around 3 GPa. We observed subtle anomalies in lattice parameters accompanied by a jump in bulk m

Jie Jiang, Deog Ki Hong, Dong-han Yeom

The Wheeler-DeWitt (WDW) equation is analyzed using two boundary proposals: the Hartle-Hawking no-boundary condition and tunneling condition. By compactifying the scale factor $a$ into $ x = a/(1+a) $, we reformulate the WDW equation to find stable numerical solutions with clearer boundary conditions. The no-boundary wave function peaks at the horizon scale,

Yehui Shen, Lei Zhang, Qingqiu Li, Xiongwei Zhao

Visual place recognition (VPR) is crucial for robots to identify previously visited locations, playing an important role in autonomous navigation in both indoor and outdoor environments. However, most existing VPR datasets are limited to single-viewpoint scenarios, leading to reduced recognition accuracy, particularly in multi-directional driving or feature-

Chih-Chyau Yang, Tian-Sheuan Chang

This paper introduces a 71.2-$\mu$W speech recognition accelerator designed for edge devices' real-time applications, emphasizing an ultra low power design. Achieved through algorithm and hardware co-optimizations, we propose a compact recurrent spiking neural network with two recurrent layers, one fully connected layer, and a low time step (1 or 2). The 2.7

Hikaru Wakaura, Rahmat Mulyawan, Andriyan B. Suksmono

Kolmogorov-Arnold Network (KAN) is a novel multi-layer neuromorphic network. Many groups worldwide have studied this network, including image processing, time series analysis, solving physical problems, and practical applications such as medical use. Therefore, we propose an Adaptive Variational Quantum Kolmogorov-Arnold Network (VQKAN) that takes advantage

Ci-Hao Wu, Tian-Sheuan Chang

Transformer-based speech enhancement models yield impressive results. However, their heterogeneous and complex structure restricts model compression potential, resulting in greater complexity and reduced hardware efficiency. Additionally, these models are not tailored for streaming and low-power applications. Addressing these challenges, this paper proposes

Mathieu Gerber

Particle filters (PFs) form a class of Monte Carlo algorithms that propagate over time a set of $N\geq 1$ particles which can be used to estimate, in an online fashion, the sequence of filtering distributions $(\hat{\eta}_t)_{t\geq 1}$ defined by a state-space model. Despite the popularity of PFs, the study of the time evolution of their estimates has receiv

Lucas Suire, Anirban Jana, Pierre Nassoy, Amaury Badon

The production of monodisperse particles or droplets is a longstanding issue across various fields, from aerosol science to inkjet printing. In bioengineering, submillimeter cell laden hydrogel capsules have proven valuable for developing in vitro tissue models. A common practical approach for producing such droplets relies on the Plateau Rayleigh instabilit

Taewon Yun, Jihwan Oh, Hyangsuk Min, Yuho Lee

Summarization refinement faces challenges when extending to multi-dimension. In this paper, we introduce ReFeed, a powerful summarization refinement pipeline that enhances multiple dimensions through reflective reasoning on feedback. To achieve this, we release SumFeed-CoT, a large-scale Long-CoT-based dataset optimized for training a lightweight model with

Dai Tateishi, Nobuaki Sasaki, Yukikatsu Terada, Satoru Katsuda

We report the azimuthal distribution of the X-ray energy spectrum of non-thermal dominant supernova remnant RX J0852.0$-$4622. The X-rays from the shock region observed by the X-ray astronomy satellite Suzaku/XIS in the energy range of 2-8 keV are well described by the absorbed power-law model and can be parameterized with flux and photon index. The X-ray fl

Yimo Yan, Yejia Liao, Guanhao Xu, Ruili Yao

The rapid rise of Large Language Models (LLMs) is transforming traffic and transportation research, with significant advancements emerging between the years 2023 and 2025 -- a period marked by the inception and swift growth of adopting and adapting LLMs for various traffic and transportation applications. However, despite these significant advancements, a sy

Sebastian Maneth, Helmut Seidl

We consider two natural subclasses of deterministic top-down tree-to-tree transducers, namely, linear and uniform-copying transducers. For both classes we show that it is decidable whether the translation of a transducer with look-ahead can be realized by a transducer from the same class without look-ahead. The transducers constructed in this way, may still

Suman Raj, Bhavani A Madhabhavi, Kautuk Astu, Arnav A Rajesh

VIP navigation requires multiple DNN models for identification, posture analysis, and depth estimation to ensure safe mobility. Using a hazard vest as a unique identifier enhances visibility while selecting the right DNN model and computing device balances accuracy and real-time performance. We present Ocularone-Bench, which is a benchmark suite designed to

Zsuzsanna Koczor-Benda, Joe Gilkes, Francesco Bartucca, Abdulla Al-Fekaiki

A range of generative machine learning models for the design of novel molecules and materials have been proposed in recent years. Models that can generate three-dimensional structures are particularly suitable for quantum chemistry workflows, enabling direct property prediction. The performance of generative models is typically assessed based on their abilit

O. Copie, J. Varignon, I. C. Infante, M. Martirosyan

In orthorhombic perovskite oxides (RMO$_3$), substituting R$^{3+}$ rare-earth cations tailors the spin, orbital, and charge degrees of freedom of the central M$^{3+}$ transition metal cations through lattice distortions. In turn, these modify also the surrounding environment of R$^{3+}$. When both R$^{3+}$ and M$^{3+}$ exhibit magnetic properties, phenomena

Alex Karrila, Tuomas Virtanen, Christian Webb

In this article, we initiate the study of operator product expansions (OPEs) for the sine-Gordon model. For simplicity, we focus on the model below the first threshold of collapse ($\beta<4\pi$) and on the singular terms in OPEs of derivative-type fields $\partial \varphi$ and $\bar\partial\varphi$. We prove that compared to corresponding free field OPEs, th

Cornelia Drutu, Davide Spriano, Stefanie Zbinden

We relate two notions of non-positive curvature: bounded combings and the Morse local-to-global (MLTG) property (in its weak and strong version). The latter is a property of a space that has been shown to eliminate pathological behavior of Morse geodesics. We showcase its importance in a survey in the appendix. We show that having a bounded combing implies t

Ivan A. Korneev, Vladimir V. Semenov

Using methods of numerical simulation, we analyze the influence of L\'evy noise on synchronization of excitable oscillators in the regime of coherence resonance. Three cases are under consideration: forced synchronization of a single FitzHugh-Nagumo oscillator subject to periodic forcing, mutual synchronization of two coupled FitzHugh-Nagumo oscillators and

Ling Feng, Tianyu Xie, Wei Ma, Ruijie Fu

The modernization of smart farming is a way to improve agricultural production efficiency, and improve the agricultural production environment. Although many large models have achieved high accuracy in the task of object recognition and segmentation, they cannot really be put into use in the farming industry due to their own poor interpretability and limitat

Haoran Luo, Haihong E, Guanting Chen, Yandan Zheng

Standard Retrieval-Augmented Generation (RAG) relies on chunk-based retrieval, whereas GraphRAG advances this approach by graph-based knowledge representation. However, existing graph-based RAG approaches are constrained by binary relations, as each edge in an ordinary graph connects only two entities, limiting their ability to represent the n-ary relations

Vytas Zacharovas

Suppose $n$ independent random variables $X_1, X_2, \dots, X_n$ have zero mean and equal variance. We prove that if the average of $\chi^2$ distances between these variables and the normal distribution is bounded by a sufficiently small constant, then the $\chi^2$ distance between their normalized sum and the normal distribution is $O(1/n)$.

Ben Allanach, Christoph Englert, Wrishik Naskar

TeV-scale $Z^\prime$ bosons with family-dependent couplings can explain some anomalies inferred from $B-$meson measurements of processes involving the $b \rightarrow s \ell^+\ell^-$ transition. A $Z^\prime$ originating from kinetically-mixed spontaneously broken $U(1)_{B_3-L_2}$ gauge symmetry has been shown to greatly ameliorate global fits~\cite{Allanach:2

Pierre Galmiche, Hyewon Seo, Yvan Pin, Philippe Meyer

The treatment of breast cancer using radiotherapy involves uncertainties regarding breast positioning. As the studies progress, more is known about the expected breast positioning errors, which are taken into account in the Planning Target Volume (PTV) in the form of the margin around the clinical target volume. However, little is known about the non-rigid d

Dawei Chen, Gianluca Faraco

We provide a complete description of realizable relative period representations for holomorphic differentials on Riemann surfaces with prescribed orders of zeros and additional invariants given by the hyperelliptic structure and spin parity. This answers a question posed by Simion Filip.

Cheng Wang, Yiwei Wang, Yujun Cai, Bryan Hooi

Retrieval-augmented generation (RAG) systems enhance large language models by incorporating external knowledge, addressing issues like outdated internal knowledge and hallucination. However, their reliance on external knowledge bases makes them vulnerable to corpus poisoning attacks, where adversarial passages can be injected to manipulate retrieval results.

Simrandeep Kaur, Unmesh Ghorai, Abhisek Samanta, Kenji Watanabe

In this Letter, we present a comprehensive study of magnetotransport in high-mobility trilayer graphene (TLG) devices under a transverse displacement field, focusing on symmetry-broken Landau levels (LLs) from monolayer-like and bilayer-like bands. A striking displacement-field-induced enhancement of the Land\'e g-factor is observed in the zeroth Landau leve

Zerui Chen, Rolandos Alexandros Potamias, Shizhe Chen, Cordelia Schmid

Reconstructing hand-held objects in 3D from monocular images remains a significant challenge in computer vision. Most existing approaches rely on implicit 3D representations, which produce overly smooth reconstructions and are time-consuming to generate explicit 3D shapes. While more recent methods directly reconstruct point clouds with diffusion models, the

Charlie Kersuzan, Aymerick Bazin, Amaury Badon

Capturing biological specimens at large scales with sub-micron resolution is crucial for biomedical research, but conventional cameras often can't handle the pixel requirements. While most microscopes use motorized stages to move samples and capture images tile by tile, we propose a method that eliminates the need for sample movement. Our approach integrates

Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi, Nariman Naderi

Introduction: This study provides a comprehensive performance assessment of vision-language models (VLMs) against established convolutional neural networks (CNNs) and classic machine learning models (CMLs) for computer-aided detection (CADe) and computer-aided diagnosis (CADx) of colonoscopy polyp images. Method: We analyzed 2,258 colonoscopy images with cor

Jun Gao, ChongYang Liu, Mengyang Li, XiaoMin Shen

Fragmentation functions (FFs) are crucial non-perturbative components in quantum chromodynamics (QCD), playing a vital role in predictions and understanding of the hadronization process. In this paper, we present the FFs for $K_S^0$, $\eta$, $\pi^0$ mesons, and $\Lambda$ baryons in the context of global QCD analysis. The data included in the fit are from sin

Nicolò Barbieri, Kerstin Hötte, Peter Persoon

Green patents are a key indicator to track technological efforts aimed at fighting climate change. Using an original dataset that merges different Patstat releases, we identify three mechanisms that may bias green patent statistics, potentially leading to contradictory findings. First, patent reclassifications due to updates in (green) classification codes r

Zixu Li, Zhiheng Fu, Yupeng Hu, Zhiwei Chen

Composed Image Retrieval (CIR) facilitates image retrieval through a multimodal query consisting of a reference image and modification text. The reference image defines the retrieval context, while the modification text specifies desired alterations. However, existing CIR datasets predominantly employ coarse-grained modification text (CoarseMT), which inadeq

P. S. Kolesnikov, B. K. Sartayev

In this paper, we consider three types of operads: alternative, assosymmetric, and bicommutative. We prove that the Hadamard product of these operads with the Novikov operad coincides with their white Manin product. As an application, we identify a variety of algebras in which all algebras are special.

Dongchen Lu, Yuyao Sun, Zilu Zhang, Leping Huang

Most multimodal large language models (MLLMs) treat visual tokens as "a sequence of text", integrating them with text tokens into a large language model (LLM). However, a great quantity of visual tokens significantly increases the demand for computational resources and time. In this paper, we propose InternVL-X, which outperforms the InternVL model in both p

Anunay Prasanna, Guillaume T. Bokman, Samuele Fiorini, Armand Sieber

Perfluorohexane is a biocompatible material that serves as a liquid core for acoustically-responsive agents in biomedical applications. Despite its relatively widespread usage, there is a lack of experimental data determining its thermodynamic properties. This challenges numerical simulations to predict the acoustic response of agents developed using this ma

Dorde Popovic, Amin Sadeghi, Ting Yu, Sanjay Chawla

Backdoor attacks are among the most effective, practical, and stealthy attacks in deep learning. In this paper, we consider a practical scenario where a developer obtains a deep model from a third party and uses it as part of a safety-critical system. The developer wants to inspect the model for potential backdoors prior to system deployment. We find that mo

Euclid Collaboration, T. Dusserre, H. Dole, F. Sarron

[ABRIGED ABSTRACT] A large catalogue of candidate galaxy protoclusters with high star-formation rates was produced by the Planck collaboration. We search, in the first data release (Q1) of the Euclid survey, for the visible and infrared counterparts of the Planck galaxy protocluster candidates expected to be above $z > 1.5$. Eight of them are in Euclid Q1. O

Eugenio Cutolo, Carlos Granero-Belinchon, Ptashanna Thiraux, Jinbo Wang

Oceanic processes at fine scales are crucial yet difficult to observe accurately due to limitations in satellite and in-situ measurements. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution Sea Surface Height (SSH) data, though noise patterns often obscure fine scale structures. Current methods struggle with noisy data or require

Chence Niu, Elnaz Irannezhad, Casey Myers, Vinayak Dixit

Quantum computing, leveraging the principles of quantum mechanics, has been found to significantly enhance computational capabilities in principle, in some cases beyond classical computing limits. This paper explores quantum computing's potential to address complex, large-scale problems in transportation systems. It focuses on three principal paradigms: Gate

Gabriel M. Colacion, Lala Rukh, Franco Buck, Tara E. Drake

Stoichiometric silicon nitride has emerged as a widely used integrated photonic material owing to its high index of refraction, nonlinear optical properties, and broad transparency window spanning visible to mid-IR frequencies. However, silicon nitride is generally more resistant to reactive ion etching than are typical etch masks made of polymer-based resis

Mohamed Aziz Aboud, Nawel Zangar, Rami Langar, Marion Berbineau

The actual railway communication system used in Europe for high-speed trains (HST) is called the GSM-R system, which is a communication system based on 2G infrastructure. This system is meant to be replaced by a new system based on 5G NR infrastructure called the Future Railway Mobile Communication System (FRMCS) by 2030. For the next years, both systems wil

Ronald Mickens, Talitha Washington

We show that it is possible to construct microscopic-level discrete equations from macroscopic modeling PDEs for heat conduction in one space dimension. The significance of this result is that, in general, one starts from microscopic theories and then take their continuum limits to obtain the corresponding macroscopic PDEs, whereas here it is demonstrated th

Ali Fahkar, Kévin Polisano, Irène Gannaz, Sophie Achard

This work deals with the generation of theoretical correlation matrices with specific sparsity patterns, associated to graph structures. We present a novel approach based on convex optimization, offering greater flexibility compared to existing techniques, notably by controlling the mean of the entry distribution in the generated correlation matrices. This a

Huanyu Qu, Weihao Zhang, Junfeng Lin, Songchen Ma

To efficiently support large-scale NNs, multi-level hardware, leveraging advanced integration and interconnection technologies, has emerged as a promising solution to counter the slowdown of Moore's law. However, the vast design space of such hardware, coupled with the complexity of their spatial hierarchies and organizations, introduces significant challeng

Liang-Liang Sun, Armin Tavakoli, René Schwonnek, Matthias Kleinmann

Understanding the invasive nature of quantum measurement and its implications in quantum foundations and information science demands a mathematically rigorous and physically well-grounded characterization of intrinsic back-action in general measurement processes. However, such a framework remains elusive, leaving a critical gap in quantum theory. Here, we ad

Shuaijie She, Junxiao Liu, Yifeng Liu, Jiajun Chen

Large language models (LLMs) inevitably make mistakes when performing step-by-step mathematical reasoning. Process Reward Models (PRMs) have emerged as a promising solution by evaluating each reasoning step. However, existing PRMs typically output evaluation scores directly, limiting both learning efficiency and evaluation accuracy, which is further exacerba

Ekta Sharma, Prerana Biswas, Mousumi Das, Benjamin Winkel

Void galaxies are located in the most underdense environments of the Universe, where the number density of galaxies is extremely low. They are, hence, good targets for studying the secular evolution of galaxies and the slow buildup of stellar mass through star formation. To date, very little is known about their cold gas content, both molecular (H$_2$) gas a

Maria Kefalogianni, Leonidas Mouchliadis, Emmanuel Stratakis, Sotiris Psilodimitrakopoulos

Lately the non-linear optical third harmonic generation (THG) microscopy is starting to emerge as a laboratory standard for label-free studies in biological samples. In this study, the THG signals produced from corn starch granules are investigated. In particular, the polarization-dependent THG (P-THG) signals emerging from the outer layer (shell) of the sta

Calin Vaida, Iosif Birlescu, Bogdan Gherman, Daniel Condurache

The paper presents a novel modular hybrid parallel robot for pancreatic surgery and its higher-order kinematics derived based on various formalisms. The classical vector, homogeneous transformation matrices and dual quaternion approaches are studied for the kinematic functions using both classical differentiation and multidual algebra. The algorithms for inv

Birger Moell, Fredrik Sand Aronsson, Sanian Akbar

Integrating large language models (LLMs) like DeepSeek R1 into healthcare requires rigorous evaluation of their reasoning alignment with clinical expertise. This study assesses DeepSeek R1's medical reasoning against expert patterns using 100 MedQA clinical cases. The model achieved 93% diagnostic accuracy, demonstrating systematic clinical judgment through

Lewis Wooltorton, Peter Brown, Roger Colbeck

Conference key agreement aims to establish shared, private randomness among many separated parties in a network. Device-independent conference key agreement (DICKA) is a variant in which the source and the measurement devices used by each party need not be trusted. So far, DICKA protocols largely fall into two categories: those that rely on violating a joint

Jacopo Massa, Stefano Forti, Federica Paganelli, Patrizio Dazzi

Cloud-Edge applications like industrial control systems and connected vehicles demand stringent end-to-end latency guarantees. Among existing data plane candidate solutions for bounded latency networking, the guaranteed Latency-Based Forwarding (gLBF) approach ensures punctual delivery of traffic flows by managing per-hop delays to meet specific latency targ

Lorenzo Pagliara, Vincenzo Petrone, Enrico Ferrentino, Andrea Chiacchio

Free-hand dental procedures are typically repetitive, time-consuming and require high precision and manual dexterity. Robots can play a key role in improving procedural accuracy and safety, enhancing patient comfort, and reducing operator workload. However, robotic solutions for free-hand procedures remain limited or completely lacking. To address this gap,

Subarna Bhattacharjee, Aninda Kumar Nanda, Subhashree Patra

In this paper, we analyze the relative errors in various reliability measures due to the tacit assumption that the components associated with a $n$-component series system or a parallel system are independently working where the components are dependent. We use Copula functions in said error analysis. This technique generalizes the existing work on error ass

Thomas Le Fils

We characterise the elements of $H^1(S, Z, \mathbb C)$, where $S$ is a closed surface and $Z\subset S$ is a finite set, that arise as the relative periods of an abelian differential in a given connected component of a stratum of their moduli space. This generalises a theorem obtained independently by Bainbridge, Johnson, Judge and Park and the author, and an

Hanyue Tu, Siqi Wu, Li Li, Wengang Zhou

Autoencoder-based structures have dominated recent learned image compression methods. However, the inherent information loss associated with autoencoders limits their rate-distortion performance at high bit rates and restricts their flexibility of rate adaptation. In this paper, we present a variable-rate image compression model based on invertible transform

Bernabé Cedrés, Ángel Bongiovanni, Jordi Cepa, Carmen P. Padilla-Torres

We present an analysis of the emitters (\ha, \hb, and \oii) from the OTELO survey, in order to characterize the star formation properties of low-mass galaxies ($<10^9$ M$_{\odot}$ stellar masses). We calculated the specific star formation rate function, the stellar mass function, and, by integrating them, the associated densities for both quantities: the spe

Julien Besset, Hélène Barucq, Rabia Djellouli, Stefano Frambati

This paper presents an efficient strategy for constructing Reduced-Order Model (ROM) bases using Taylor polynomial expansions and Fr{\'e}chet derivatives with respect to model parameters. The proposed approach enables the construction of ROM bases with minimal additional computational cost. By exploiting Fr{\'e}chet derivatives -solution to the same problem

Ngoc Luyen Le, Marie-Hélène Abel

Group decision-making is becoming increasingly common in areas such as education, dining, travel, and finance, where collaborative choices must balance diverse individual preferences. While conventional recommender systems are effective in personalization, they fall short in group settings due to their inability to manage conflicting preferences, contextual

Ulrike Höfler, Daniel Plabst, Norbert Hanik

Low-cost analog phase precoding is used to compensate chromatic dispersion (CD) in fibers with intensity modulation and direct detection (IM/DD). In contrast to conventional precoding with an in-phase and quadrature (IQ) Mach-Zehnder modulator (MZM), only a single additional phase modulator (PM) is required at the transmitter. Depending on the CD, the PM gen

Chengyi Wang, Ji Wang

This work is motivated by the engineering challenge of suppressing vibrations in turbine blades of aero engines, which often operate under extreme thermal conditions and high-Mach aerodynamic environments that give rise to complex vibration phenomena, commonly referred to as thermally-induced and flow-induced vibrations. Using Hamilton's variational principl

Masao Jinzenji

In this paper, we propose a geometric proof of the generalized mirror transformation for multi-point virtual structure constants of degree k hypersurfaces in CP^{N-1}.

Shuo Liu, Minghui Xu, Tianyi Sun, Xiuzhen Cheng

Asynchronous Byzantine fault-tolerant (BFT) consensus protocols, known for their robustness in unpredictable environments without relying on timing assumptions, are becoming increasingly vital for wireless applications. While these protocols have proven effective in wired networks, their adaptation to wireless environments presents significant challenges. As

Angela Borchers, Claire S. Ye, Maya Fishbach

One proposed black hole formation channel involves hierarchical mergers, where black holes form through repeated binary mergers. Previous studies have shown that such black holes follow a near-universal spin distribution centered around 0.7. However, gravitational-wave kicks can eject remnants from their host environments, meaning only retained black holes c

Hiroya Makino, Takahiro Yamaguchi, Hiroyuki Sakai

We propose a novel, zero-shot image generation technique called "Visual Concept Blending" that provides fine-grained control over which features from multiple reference images are transferred to a source image. If only a single reference image is available, it is difficult to isolate which specific elements should be transferred. However, using multiple refe

Naritaka Oshita, Emanuele Berti, Vitor Cardoso

The quasinormal mode spectrum of black holes is unstable against small modifications of the radial potential describing massless perturbations. We study how these small modifications affect the convergence of the quasinormal mode expansion and the mode excitation by computing the mode amplitudes from first principles, without relying on any fitting procedure

Subarna Bhattacharjee, Aninda Kumar Nanda, Subhashree Patra

In this paper, we analyze the relative errors that crop up in the various reliability measures due to the tacit assumption that the components are independently working associated with a $n$-component series system or a parallel system where the components are dependent and follow a well-defined multivariate Weibull or exponential distribution. We also list