March 2025 arXiv papers — page 5

M. F. P. ten Eikelder, E. H. van Brummelen, D. Schillinger

Fluid mixture models are essential for describing a wide range of physical phenomena, including wave dynamics and spinodal decomposition. However, there is a lack of consensus in the modeling of compressible mixtures, with limited connections between different classes of models. On the one hand, existing compressible two-phase flow models accurately describe

Hanlin Gu, Fan Feng

Cofactor conditions (CCs) provide a geometric criterion for achieving highly compatible austenite/twinned martensite interfaces and have served as a guiding principle for the design of highly reversible martensitic materials. However, their standard ten- sorial form obscures the direct connection between crystallographic lattice parameters and compatibility.

Riccardo Borsato, Miguel García Fernández

Using a Drinfeld twist of Jordanian type, we construct a deformation of the non-compact and $\mathfrak{sl}_2$-invariant $XXX_{-1/2}$ spin-chain. Before the deformation, the seed model can be understood as a sector of the $\mathfrak{psu}(2,2|4)$-invariant spin-chain encoding the spectral problem of $\mathcal{N}=4$ super Yang-Mills at one loop in the planar li

Anne-Sophie de Suzzoni, Annalaura Stingo, Arthur Touati

In this article we consider a system of two Klein-Gordon equations, set on the $d$-dimensional box of size $L$, coupled through quadratic semilinear terms of strength $\varepsilon$ and evolving from well-prepared random initial data. We rigorously derive the effective dynamics for the correlations associated to the solution, in the limit where $L\to\infty$ a

James Taylor

For a finite extension $F$ of $\mathbb{Q}_p$ and $n \geq 1$, we show that the category of Lubin-Tate bundles on the $(n-1)$-dimensional Drinfeld symmetric space is equivalent to the category of finite-dimensional smooth representations of the group of units of the division algebra of invariant $1/n$ over $F$.

Abdul Sittar, Dunja Mladenic, Alenka Gucek, Marko Grobelnik

This paper presents BAR-Analytics, a web-based, open-source platform designed to analyze news dissemination across geographical, economic, political, and cultural boundaries. Using the Russian-Ukrainian and Israeli-Palestinian conflicts as case studies, the platform integrates four analytical methods: propagation analysis, trend analysis, sentiment analysis,

Karim Radouane, Hanane Azzag, Mustapha lebbah

We propose a unified framework that integrates object detection (OD) and visual grounding (VG) for remote sensing (RS) imagery. To support conventional OD and establish an intuitive prior for VG task, we fine-tune an open-set object detector using referring expression data, framing it as a partially supervised OD task. In the first stage, we construct a grap

Sesuai Y. Madanha, X. Mbaale, Tendai M. Mudziiri Shumba

Let $ G $ be a finite group and $ \chi \in \mathrm{Irr}(G) $. Define $ \mathrm{cv}(G)=\{\chi(g)\mid \chi \in \mathrm{Irr}(G), g\in G \} $, $ \mathrm{cv}(\chi)=\{\chi(g)\mid g\in G \} $ and denote $ \mathrm{dl}(G) $ by the derived length of $ G $. In the 1990s Berkovich, Chillag and Zhmud described groups $ G $ in which $ |\mathrm{cv}(\chi)|=3 $ for every non

Killian Pujol, Roberta Baggio, Dominique Lambert, Jean-François Muzy

Forecasting Heavy Precipitation Events (HPE) in the Mediterranean is crucial but challenging due to the complexity of the processes involved. In this context, Artificial Intelligence methods have recently proven to be competitive with state-of-the-art Numerical Weather Prediction (NWP). This work focuses on improving the prediction of the occurrence of HPE o

Nitay Alon, Joseph Barnby, Reuth Mirsky, Stefan Sarkadi

Theory of Mind (ToM) is a hallmark of human cognition, allowing individuals to reason about others' beliefs and intentions. Engineers behind recent advances in Artificial Intelligence (AI) have claimed to demonstrate comparable capabilities. This paper presents a model that surpasses traditional ToM tests designed for 3-year-old children, providing strong su

Fangtong Zhou, Ruozhou Yu

We study an edge demand response problem where, based on historical edge workload demands, an edge provider needs to dispatch moving computing units, e.g. truck-carried modular data centers, in response to emerging hotspots within service area. The goal of edge provider is to maximize the expected revenue brought by serving congested users with satisfactory

Tamás Kriváchy, Martin Kerschbaumer

Bell nonlocality without input settings, e.g. in the triangle network, has been perceived to be particularly fragile, with low robustness to noise in physical implementations. Here we show to the contrary that nonlocality based on N00N states already for $N=2$ has an exceptionally high robustness to photon loss. For the dominant noise factor, single photon l

Christian Beron Curti, Rodrigo Vargas Sainz, Yitong Tseo

This research project explores the optimization of the family selection process for participation in Uruguay's Crece Contigo Family Support Program (PAF) through machine learning. An anonymized database of 15,436 previous referral cases was analyzed, focusing on pregnant women and children under four years of age. The main objective was to develop a predicti

Rulin Shen, Deyu Yan

Given a finite group $G$, let $\pi(G)$ denote the set of all primes that divide the order of $G$. For a prime $r \in \pi(G)$, we define $r$-singular elements as those elements of $G$ whose order is divisible by $r$. Denote by $S_r(G)$ the number of $r$-singluar elements of $G$. We denote the proportion $S_r(G)/|G|$ of $r$-singular elements in $G$ by ${\mu_r}

Efstratios Koukoutsis, Kyriakos Hizanidis, George Vahala, Christos Tsironis

Based on the Dirac representation of Maxwell equations we present an explicit, discrete space-time, quantum walk-inspired algorithm suitable for simulating the electromagnetic wave propagation and scattering from inhomogeneities within magnetized plasmas. The quantum walk is implemented on a lattice with an internal space of $n_q=4$--qubits, used to encode t

Seungjun Lee, Gim Hee Lee

Reconstructing sharp 3D representations from blurry multi-view images are long-standing problem in computer vision. Recent works attempt to enhance high-quality novel view synthesis from the motion blur by leveraging event-based cameras, benefiting from high dynamic range and microsecond temporal resolution. However, they often reach sub-optimal visual quali

Yue Zhao, Joshua W. Burby, Andrew Christlieb, Huan Lei

We introduce a data-driven approach to learn a generalized kinetic collision operator directly from molecular dynamics. Unlike the conventional (e.g., Landau) models, the present operator takes an anisotropic form that accounts for a second energy transfer arising from the collective interactions between the pair of collision particles and the environment. N

Jim W. Barrett, Nils Erlanson, Joana Félix China, G. Niklas Norén

Objectives: To advance state-of-the-art for duplicate detection in large-scale pharmacovigilance databases and achieve more consistent performance across adverse event reports from different countries. Background: Unlinked adverse event reports referring to the same case impede statistical analysis and may mislead clinical assessment. Pharmacovigilance relie

Clement Yung

Let $E$ be a vector space over a countable field of dimension $\aleph_0$. Two infinite-dimensional subspaces $V,W \subseteq E$ are almost disjoint if $V \cap W$ is finite-dimensional. This paper provides some improvements on results about the definability of maximal almost disjoint families (mad families) of subspaces in [18]. We construct a full mad family

Abdul Sittar, Luka Golob, Mateja Smiljanic

This study explores the generation and evaluation of synthetic fake news through fact based manipulations using large language models (LLMs). We introduce a novel methodology that extracts key facts from real articles, modifies them, and regenerates content to simulate fake news while maintaining coherence. To assess the quality of the generated content, we

Stefano Riva, Andrea Missaglia, Carolina Introini, In Cheol Bang

In recent years, algorithms aiming at learning models from available data have become quite popular due to two factors: 1) the significant developments in Artificial Intelligence techniques and 2) the availability of large amounts of data. Nevertheless, this topic has already been addressed by methodologies belonging to the Reduced Order Modelling framework,

Weijie Liu, Han Bao, Makoto Yamada, Zenan Huang

Many-to-many matching seeks to match multiple points in one set and multiple points in another set, which is a basis for a wide range of data mining problems. It can be naturally recast in the framework of Optimal Transport (OT). However, existing OT methods either lack the ability to accomplish many-to-many matching or necessitate careful tuning of a regula

Fangtong Zhou, Xiaorui Liu, Ruozhou Yu, Guoliang Xue

Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a critical challenge. Although learning-based approaches have been proposed to address the scalability of traditional TE algorithms, their practical application is often hindered by a lack of generalization, high trainin

Lawrence Hollom, Julien Portier, Victor Souza

Erd\H{o}s conjectured in 1945 that for any unit vectors $v_1, \dotsc, v_n$ in $\mathbb{R}^2$ and signs $\varepsilon_1, \dotsc, \varepsilon_n$ taken independently and uniformly in $\{-1,1\}$, the random Rademacher sum $\sigma = \varepsilon_1 v_1 + \dotsb + \varepsilon_n v_n$ satisfies $\|\sigma\|_2 \leq 1$ with probability $\Omega(1/n)$. While this conjecture

Norbert Hegyvári

Let $A_k=\{r(k-r): 1\leq r \leq k-1\}$. Erd\H os and Graham asked about the cardinality of the set of common elements. We answer this elementary question and apply our result to a sum-product type result.

Xiang-Pan Duan, Lin Chen, Guo-Liang Ma, Carlos A. Salgado

The Koba-Nielsen-Olesen (KNO) scaling of hadron multiplicity distributions, empirically confirmed to hold approximately in $e^+e^-$ collisions and Deep Inelastic Scattering, has been observed to be violated in hadron-hadron collisions. In this work, we show that the universality of KNO scaling can be extended to hadron-hadron collisions when restricted to QC

Abdul Sittar, Simon Münker, Fabio Sartori, Andreas Reitenbach

User engagement on social media platforms is influenced by historical context, time constraints, and reward-driven interactions. This study presents an agent-based simulation approach that models user interactions, considering past conversation history, motivation, and resource constraints. Utilizing German Twitter data on political discourse, we fine-tune A

Jingxian Xu, Mengyu Zhou, Weichang Liu, Hanbing Liu

Large Language Models (LLMs) have made significant strides in problem-solving by incorporating reasoning processes. However, this enhanced reasoning capability results in an increased number of output tokens during inference, leading to higher computational costs. To address this challenge, we propose TwT (Thinking without Tokens), a method that reduces infe

Justin Baars, Sami Umut Can, Roger J. A. Laeven

Consider an observation of a multivariate temporal point process $N$ with law $\mathcal P$ on the time interval $[0,T]$. To test the null hypothesis that $\mathcal P$ belongs to a given parametric family, we construct a convergent compensated counting process to which we apply an innovation martingale transformation. We prove that the resulting process conve

Dave Dykstra, Mine Altunay, Shreyas Bhat, Dmitry Litvintsev

Fermilab is the first High Energy Physics institution to transition from X.509 user certificates to authentication tokens in production systems. All the experiments that Fermilab hosts are now using JSON Web Token (JWT) access tokens in their grid jobs. Many software components have been either updated or created for this transition, and most of the software

Waheed Ahmad, Jing Xiong, Zeyang Xia

In orthodontic treatment, the biological response of the tooth, periodontal ligament, and bone complex to orthodontic force is crucial in influencing treatment outcomes. The challenge lies in accurately measuring, estimating, and predicting these forces during clinical procedures. This review aims to fill the gap in the literature by systematically summarizi

Naresh Dadhich

It is noteworthy that limiting compactness of a static bounded configuration is characterized by a general principle: \textit{one, by equipartition of mass between inside and outside, and the other by vanishing of energy inside.} The former implies gravitational energy being half of mass leading to limiting compactness $M/R = 4/9$ of Buchdahl star while for

J. Gamboa

We study QED$_4$ in the adiabatic approximation, incorporating global topological effects associated with the $U(1)$ Berry connection. The Berry phase accumulated by the fermionic vacuum is given by $\Delta \alpha = \oint_{\mathcal{C}} \gamma_5\, \mathcal{A}^{(n)}$, where $\mathcal{A}^{(n)}$ is a closed but non-exact one-form defined over the space of gauge

Harim Yoo

The Axiom-Based Atlas is a novel framework that structurally represents mathematical theorems as proof vectors over foundational axiom systems. By mapping the logical dependencies of theorems onto vectors indexed by axioms - such as those from Hilbert geometry, Peano arithmetic, or ZFC - we offer a new way to visualize, compare, and analyze mathematical know

Enrico Palumbo, Gustavo Penha, Andreas Damianou, José Luis Redondo García

In recent years, Large Language Models (LLMs) have enabled users to provide highly specific music recommendation requests using natural language prompts (e.g. "Can you recommend some old classics for slow dancing?"). In this setup, the recommended tracks are predicted by the LLM in an autoregressive way, i.e. the LLM generates the track titles one token at a

Valentine Maris

Recent results on causality in noncommutative space-time are reviewed. We study, in particular, quantum causal structures in 1+1 dimensional kappa Minkowski space-time. This later is described by a twisted Lorentzian Spectral Triple build with a twisted set of derivatives. Investigation of causality provides a quantum constraint, which is a quantum analog of

Xiaomeng Ma, Qihui Xu

Humans acquire language through implicit learning, absorbing complex patterns without explicit awareness. While LLMs demonstrate impressive linguistic capabilities, it remains unclear whether they exhibit human-like pattern recognition during in-context learning at inferencing level. We adapted three classic artificial language learning experiments spanning

Ben Brubaker, Daniel Bump, Henrik P. A. Gustafsson

The free-fermion point refers to a $\operatorname{GL}(2)\times\operatorname{GL}(1)$ parametrized Yang-Baxter equation within the six-vertex model. It has been known for a long time that this is connected with the quantum group $U_q(\mathfrak{gl}(1|1))$. We demonstrate that $R$-matrices from the finite quantum superalgebra $U_q(\mathfrak{gl}(1|1))$ produce a

Sophie L. Newman, Ana Sainz de Murieta

Popular culture plays a significant role in shaping public interest in science, and Taylor Swift's discography frequently incorporates astrophysics terminology. This study examines the occurrence of astrophysics-related words in her lyrics and their representation in the Eras tour set list. By analyzing the frequency of words in Swift's total discography, we

James A. D. Gardner, Will Rowan, William A. P. Smith

In this paper, we introduce NeuRaLaTeX, which we believe to be the first deep learning library written entirely in LaTeX. As part of your LaTeX document you can specify the architecture of a neural network and its loss functions, define how to generate or load training data, and specify training hyperparameters and experiments. When the document is compiled,

Lan Wei, Gema Vera Gonzalez, Phatsimo Kgwarae, Alexander Timms

In vivo image-guided multi-pipette patch-clamp is essential for studying cellular interactions and network dynamics in neuroscience. However, current procedures mainly rely on manual expertise, which limits accessibility and scalability. Robotic automation presents a promising solution, but achieving precise real-time detection of multiple pipettes remains a

Miguel A. Cardona, Miroslav Repický, Saharon Shelah

Let $\mathfrak{e}^\mathsf{const}_2$ be the constant evasion number, that is, the size of the least family $F\subseteq{}^{\omega}2$ of reals such that for each predictor $\pi\colon {}^{<\omega}2\to 2$ there is $x\in F$ which is not constantly predicted by $\pi$; and let $\mathfrak{v}_2^\mathsf{const}$ be the constant prediction number, that is, the size of th

Richard Fitzpatrick

A number of improvements to the TJ toroidal tearing mode code [Phys. Plasmas 31, 102507 (2024)] are documented. The TJ code is also successfully benchmarked against the STRIDE toroidal tearing mode code [Phys. Plasmas 25, 082502 (2018)]. Finally, the new capabilities of the TJ code are used to investigate the stability of tearing modes in tokamak plasmas as

Yingrui Ji, Xi Xiao, Gaofei Chen, Hao Xu

Contrastive Language-Image Pretraining (CLIP) has achieved remarkable success in cross-modal tasks such as zero-shot image classification and text-image retrieval by effectively aligning visual and textual representations. However, the theoretical foundations underlying CLIP's strong generalization remain unclear. In this work, we address this gap by proposi

Beatrice Bucciarelli

Major advancements in space science and detector technology brought about a revolution in global astrometry, the science of measuring distances and motions of stars in the Milky Way and in the local universe. From the first ESA astrometric mission HIPPARCOS of the early 80s to the current Gaia mission, the data volume and computational complexity of the full

Ziming Cheng, Zhiyuan Huang, Junting Pan, Zhaohui Hou

Graphical user interfaces (GUI) automation agents are emerging as powerful tools, enabling humans to accomplish increasingly complex tasks on smart devices. However, users often inadvertently omit key information when conveying tasks, which hinders agent performance in the current agent paradigm that does not support immediate user intervention. To address t

Akifumi Kira, Nobuo Terajima

In this study, we focus on a form of joint transportation called mixed transportation and enumerate the combinations with high cooperation effects from among a number of transport lanes registered in a database (logistics big data). As a measure of the efficiency of mixed transportation, we consider the reduction rate that represents how much the total dista

Mengyao Wang, Fan Zhang, Xinyao Guo, Haixing Miao

Current gravitational-wave detectors have achieved remarkable sensitivity around 100 Hz, enabling ground-breaking discoveries. Enhancing sensitivity at higher frequencies in the kilohertz (kHz) range promises access to rich physics, particularly the extreme conditions during the merger stage of binary neutron stars. However, the high-frequency sensitivity of

Zhaohui Wang, Han Li, Shengtai Fan, Jiasen Xu

The strong correlation effect in cuprate superconductors have greatly enriched the phase diagram showing the co-existence of superconductivity with many intertwined orders. One of the prominent issues concerning the superconductivity mechanism is about the pseudogap phase which behaves either as cooperator or competitor for superconductivity and its fundamen

Natalia Podoliak, Lubor Lejcek, Martin Cigl, Vladimira Novotna

Regulation of topological structures and pattern formation is attracting wide interest in the field of condensed matter. Liquid crystals (LCs) represent soft matter with a remarkable combination of fluidity and anisotropic properties. Topological defects may appear in confined LCs under external stimuli. Recently discovered ferroelectric nematics (NF) opened

E. G. Pottebaum

In a preliminary study of numerical humor, we propose the Perceived Specificity Hypothesis (PSH). The PSH states that, for nonnegative integers < 100, the funniness of a number increases with its apparent precision. A survey of 68 individuals supports the veracity of this hypothesis and indicates that oddly specific numbers tend to be funniest. Our results m

Jan Čechal, Pavel Procházka

Low-energy electron microscopy (LEEM) is a surface science method that works primarily in the UHV environment. It provides information complementary to the other established techniques: it extends the limited view of scanning probe microscopies from nanometers to micrometers and measurement time down to tens of milliseconds, enabling to visualize the changes

Si-wen Li, Xiao-tong Zhang

(ArXiv version) We investigate holographically the effective theory of the worldvolume fermion on the flavor branes in the D3/D7 model with homogeneously smeared D(-1)-branes. As a top-down approach in gauge-gravity duality, the D(-1)-branes are instantons and violate the CP symmetry in the dual theory. In the confined geometry, we introduce a baryon vertex

Anas Shrinah, Kerstin Eder

Simulation-based testing provides a safe and cost-effective environment for verifying the safety of Uncrewed Aerial Vehicles (UAVs). However, simulation can be resource-consuming, especially when High-Fidelity Simulators (HFS) are used. To optimise simulation resources, we propose a pseudo-random test generator that uses a Low-Fidelity Simulator (LFS) to est

Yusen Wu, Yukun Zhang, Chuan Wang, Xiao Yuan

Quantum process characterization is a fundamental task in quantum information processing, yet conventional methods, such as quantum process tomography, require prohibitive resources and lack scalability. Here, we introduce an efficient quantum process learning method specifically designed for short-time Hamiltonian dynamics. Our approach reconstructs an equi

Lukas Köhldorfer, Peter Balazs

We introduce a localization concept for operator-valued frames, where the quality of localization is measured by the associated operator-valued Gram matrix belonging to some suitable Banach algebra. We prove that intrinsic localization of an operator-valued frame is preserved by its canonical dual. Moreover, we show that the series associated to the perfect

Jicheng Shi, Colin N. Jones

This paper considers stochastic linear time-invariant systems subject to constraints on the average number of state-constraint violations over time without knowing the disturbance distribution. We present a novel disturbance-adaptive model predictive control (DAD-MPC) framework, which adjusts the disturbance model based on measured constraint violations. Usi

Erik Adli, Gerardo D'Auria, Nuria Catalan Lasheras, Vera Cilento

The Compact Linear Collider (CLIC) is a TeV-scale high-luminosity linear e$^+$e$^-$ collider studied by the international CLIC and CLICdp collaborations. CLIC uses a two-beam acceleration scheme, in which normal-conducting high-gradient 12 GHz accelerating structures are powered via a high-current drive beam. CLIC is foreseen to be built and operated in stag

Changying Ding, Daniel Drimbe

We demonstrate a relative solidity property for the product of a nonamenable biexact group with an arbitrary infinite group in the measure equivalence setting. Among other applications, we obtain the following unique product decomposition for products of nonamenable biexact groups, strengthening \cite{Sa09}: for any nonamenable biexact groups $\Gamma_1,\cdot

Fabian Fuchs, Mario Ruben Fernandez, Norman Ettrich, Janis Keuper

Seismic processing plays a crucial role in transforming raw data into high-quality subsurface images, pivotal for various geoscience applications. Despite its importance, traditional seismic processing techniques face challenges such as noisy and damaged data and the reliance on manual, time-consuming workflows. The emergence of deep learning approaches has

Peiying Hua, Andrea Olofson, Faraz Farhadi, Liesbeth Hondelink

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSCLC patients, approximately 32.3% have mutations in the epidermal growth factor receptor (EGFR) gene. Osimertinib, a third-generation EGFR-tyrosine kinase inhibitor (TKI), has demonstrated remarkable efficacy in t

Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak, Hakim Hacid

Large vision and language models show strong performance in tasks like image captioning, visual question answering, and retrieval. However, challenges remain in integrating speech, text, and vision into a unified model, especially for spoken tasks. Speech generation methods vary (some produce speech directly), others through text (but their impact on quality

Cailian Yu, Zhihua Zheng, Menghao Gao, Zhenjiang Zhao

Quantum information science (QIS), encompassing technologies such as quantum computing, sensing, and communication, relies on the development and manipulation of quantum bits (qubits). Recently, two-dimensional (2D) materials -- characterized by their atomic thinness and external controllability -- have emerged as promising candidates for qubit fabrication a

Thomas Mädler, Radouane Gannouji, Emanuel Gallo

The characteristic initial boundary problem is discussed in spherical symmetry for the Einstein-Maxwell-scalar field equations. It is formulated for an affine-null metric and the resulting field equations are cast into a hierarchical system of partial differential equations. The initial boundary value problem for a family of null hypersurfaces is specified f

Enrico Le Donne, Luca Nalon, Nicola Paddeu, Simone Verzellesi

In this paper we provide an algebraic characterization of those stratified groups in which boundaries with locally constant normal are locally flat. We show that these groups, which we call hypergenerated, are exactly the stratified groups where embeddings of non-characteristic hypersurfaces are locally bi-Lipschitz. Finally, we extend these results to subma

Bashra Mahamed, Francis James Dent, Robert Simpson, Nicola Weston

Identification and characterization of natural dew collecting models is instrumental for the inspiration, design and development of engineered dew harvesting systems. Short low growing grass is one of the most ubiquitous and proficient examples of natural dew harvesting, owing to its large surface area, small thermal capacity, structured rough surface and pr

Angela Lopez-Cardona, Parvin Emami, Sebastian Idesis, Saravanakumar Duraisamy

Information Visualization (InfoVis) systems utilize visual representations to enhance data interpretation. Understanding how visual attention is allocated is essential for optimizing interface design. However, collecting Eye-tracking (ET) data presents challenges related to cost, privacy, and scalability. Computational models provide alternatives for predict

Zlatko Dimcovski, Michael Doser

Following a successful pioneering study of the biological effects of antimatter ( the AD-4/ACE experiment at CERN), the use of antiprotons in clinical radiotherapy became a very serious possibility. A major part of any future radiotherapy using antiprotons will be real-time imaging of antiproton annihilation in biological targets. In principle, real-time ima

Jianhao Li, Xianchao Xiu

Recent advances in large language models (LLMs) have provided new opportunities for decision-making, particularly in the task of automated feature selection. In this paper, we first comprehensively evaluate LLM-based feature selection methods, covering the state-of-the-art DeepSeek-R1, GPT-o3-mini, and GPT-4.5. Then, we propose a new hybrid strategy called L

Slavisa Tomic, Marko Beko, Yakubu Tsado, Bamidele Adebisi

This work proposes a novel approach to reinforce localization security in wireless networks in the presence of malicious nodes that are able to manipulate (spoof) radio measurements. It substitutes the original measurement model by another one containing an auxiliary variance dilation parameter that disguises corrupted radio links into ones with large noise

The Belle II Collaboration

Belle II is an intensity-frontier experiment at the SuperKEKB collider in Tsukuba, Japan. Over the coming decades, it will record the decays of billions of bottom mesons, charm hadrons, and tau leptons produced in 10 GeV electron-positron collisions. The experiment's low-background environment and precisely known kinematics enable high-precision measurements

Alexis Reboul-Salze, Aurélie Astoul, Hao-Jui Kuan, Arthur G. Suvorov

During the last seconds of a binary neutron-star merger, the tidal force can excite stellar oscillation modes to large amplitudes. From the perspective of premerger electromagnetic emissions and next-generation gravitational-wave detectors, gravity ($g-$) modes constitute a propitious class. However, existing estimates for their impact employ linear schemes

Heng Zhang, Abdel Lisser

Chance constraints describe a set of given random inequalities depending on the decision vector satisfied with a large enough probability. They are widely used in decision making under uncertain data in many engineering problems. This paper aims to derive the convexity of chance constraints with row dependent elliptical and skewed random variables via a copu

Winnie Chan, Zhiyu He, Keith Moffat, Saverio Bolognani

Feedback optimization optimizes the steady state of a dynamical system by implementing optimization iterations in closed loop with the plant. It relies on online measurements and limited model information, namely, the input-output sensitivity. In practice, various issues including inaccurate modeling, lack of observation, or changing conditions can lead to s

Kailas Vodrahalli, Wei Wei, James Zou

Recent advances in generative AI have been driven by alignment techniques such as reinforcement learning from human feedback (RLHF). RLHF and related techniques typically involve constructing a dataset of binary or ranked choice human preferences and subsequently fine-tuning models to align with these preferences. This paper shifts the focus to understanding

Florian Zimmer, Janosch Haber, Mayuko Kaneko

As data is increasingly acknowledged as a highly valuable asset, much effort has been put into investigating inter-organisational data sharing, aiming at utilising the value of formerly unused data. Moreover, most researchers agree, that trust between actors is key for successful data sharing activities. However, existing research oftentimes focus on trust f

Yang Zou, Xin Na, Yimiao Sun, Yuan He

Backscatter is a key technology for battery-free sensing in industrial IoT applications. To fully cover numerous tags in the deployment area, one often needs to deploy multiple readers, each of which communicates with tags within its communication range. However, the actual backscattered signals from a tag are likely to reach a reader outside its communicati

Charles St-Arnault, Santiago Bernal, Derek Kita, Ross Dickson

We report the first 3.2 and 4.2 Tbps (8 x 225Gbaud PAM4-8), IM/DD transmission system using FR8 and DR8 configurations with TFLN modulators driven by a 3nm SerDes under the HD-FEC threshold.

Mingyan Yu, Zhenke Wu, Michelle M. Hood, Carrie A. Karvonen-Gutierrez

Longitudinal biomarker data and health outcomes are routinely collected in many studies to assess how biomarker trajectories predict health outcomes. Existing methods primarily focus on mean biomarker profiles, treating variability as a nuisance. However, excess variability may indicate system dysregulations that may be associated with poor outcomes. In this

Wazeer Zulfikar, Treyden Chiaravalloti, Jocelyn Shen, Rosalind Picard

People inherently use experiences of their past while imagining their future, a capability that plays a crucial role in mental health. Resonance is an AI-powered journaling tool designed to augment this ability by offering AI-generated, action-oriented suggestions for future activities based on the user's own past memories. Suggestions are offered when a new

Pablo Concha-Vega

Local complementation of a graph $G$ on vertex $v$ is an operation that results in a new graph $G*v$, where the neighborhood of $v$ is complemented. Two graph are locally equivalent if on can be reached from the other one through local complementation. It was previously established that recognizing locally equivalent graphs can be done in $\mathcal{O}(n^4)$

Kurt Horvath, Dragi Kimovski, Stojan Kitanov, Radu Prodan

The rapid digitalization of urban infrastructure opens the path to smart cities, where IoT-enabled infrastructure enhances public safety and efficiency. This paper presents a 6G and AI-enabled framework for traffic safety enhancement, focusing on real-time detection and classification of emergency vehicles and leveraging 6G as the latest global communication

Chun-Yen Hsu, Zhi-Yun Li, Yisheng Tu, Xiao Hu

We investigate the dynamics of dust concentration in actively accreting, substructured, non-ideal MHD wind-launching disks using 2D and 3D simulations incorporating pressureless dust fluids of various grain sizes and their aerodynamic feedback on gas dynamics. Our results reveal that mm/cm-sized grains are preferentially concentrated within the inner 5-10 au

Emanuele Naldi, Felix Schneppe

The primal-dual Douglas-Rachford method is a well-known algorithm to solve optimization problems written as convex-concave saddle-point problems. Each iteration involves solving a linear system involving a linear operator and its adjoint. However, in practical applications it is often computationally favorable to replace the adjoint operator by a computation

Harry Robertshaw, Benjamin Jackson, Jiaheng Wang, Hadi Sadati

Purpose: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, are not generalizable to other patient vasculatures, and do not consider safety. We propose a safe dual-device

Coraline Letouzé, Pascal Viot, Laura Messio

Quenched disorder can destroy magnetic order, for example when a random field is applied in a 2-dimensional Ising model. Even when an order exists in the presence of quenched disorder, it is usually only the survival of the order of the clean model. We present here a surprising phenomenon where an order emerges, driven by quenched disorder. This order has no

Guodong Weng, Johannes Slotboom

Magnetic resonance spectroscopy (MRS) offers significant diagnostic potential but is inherently constrained by low signal-to-noise ratio (SNR). While increasing the main magnetic field strength B_0 is theoretically linked to increased SNR, practically obtained gains in SNR from B07/4 to B0 depending on the domination of thermal noise at high B0, are not alwa

Uxue Delaquintana-Aramendi, Leire Benito-del-Valle, Aitor Alvarez-Gila, Javier Pascau

In colonoscopy, 80% of the missed polyps could be detected with the help of Deep Learning models. In the search for algorithms capable of addressing this challenge, foundation models emerge as promising candidates. Their zero-shot or few-shot learning capabilities, facilitate generalization to new data or tasks without extensive fine-tuning. A concept that i

D. Q. Adams, C. Alduino, K. Alfonso, F. T. Avignone

We present a new measurement of the 2nbb half-life of 130Te (T1/2) using the first complete model of the CUORE data, based on 1038 kg yr of collected exposure. Thanks to optimized data selection, we achieve a factor of two improvement in precision, obtaining T1/2 = (9.32 +0.05 -0.04 (stat.) +0.07 -0.07 (syst.)) x10^20 yr. The signal-to-background ratio is in

Antoine Ayache, Julien Hamonier, laurent Loosveldt

Hermite processes are paradigmatic examples of stochastic processes which can belong to any Wiener chaos of an arbitrary order; the wellknown fractional Brownian motion belonging to the Gaussian first order Wiener chaos and the Rosenblatt process belonging to the non-Gaussian second order Wiener chaos are two particular cases of them. Except these two partic

Alexis Guichemerre, Soufiane Belharbi, Mohammadhadi Shateri, Luke McCaffrey

Weakly supervised object localization (WSOL) methods allow training models to classify images and localize ROIs. WSOL only requires low-cost image-class annotations yet provides a visually interpretable classifier. Standard WSOL methods rely on class activation mapping (CAM) methods to produce spatial localization maps according to a single- or two-step stra

Jia-Jun Zou, Yun-Long Liu, Qi Kong, A-Man Zhang

Vortex-induced vibration (VIV) remains a fundamental yet computationally challenging problem in computational fluid dynamics (CFD). This study develops a moving mesh Fluid-structure interaction (FSI) algorithm within a Runge-Kutta Discontinuous Galerkin (RKDG) adaptive mesh refinement (AMR) framework. The viscous term in the compressible Navier-Stokes (NS) e

Alexandre R. Nieto, Rubén Capeáns, Miguel A. F. Sanjuán

The introduction of a memristor in a chaotic system can significantly modify its dynamical behavior. In this paper, we couple a discrete memristor model with a chaotic map to investigate the memristor's impact on the stability of chaotic attractors. Our results reveal that introducing the memristor substantially enlarges the basin of attraction of a given ch

Martin Langhammer, George A. Constantinides

Recent advances in soft GPGPU architectures have shown that a small (<10K LUT), high performance (770 MHz) processor is possible in modern FPGAs. In this paper we architect and evaluate soft SIMT processor banked memories, which can support high bandwidth (up to 16 ports) while maintaining high speed (over 770 MHz). We compare 9 different memory architecture

R. Abgrall, M. Dumbser, P. H. Maire

We introduce a new family of discontinuous Galerkin (DG) finite element schemes for the discretization of first order systems of hyperbolic partial differential equations (PDE) on unstructured simplex meshes in two and three space dimensions that respect the two basic vector calculus identities exactly also at the discrete level, namely that the curl of the

Diego Machain Rivera, Selen Ercan Jenny, Ping Hsun Tsai, Ena Lloret-Fritschi

This work proposes a Graph Neural Network (GNN) modeling approach to predict the resulting surface from a particle based fabrication process. The latter consists of spray-based printing of cementitious plaster on a wall and is facilitated with the use of a robotic arm. The predictions are computed using the robotic arm trajectory features, such as position,

Dominik Schnaus, Nikita Araslanov, Daniel Cremers

The platonic representation hypothesis suggests that vision and language embeddings become more homogeneous as model and dataset sizes increase. In particular, pairwise distances within each modality become more similar. This suggests that as foundation models mature, it may become possible to match vision and language embeddings in a fully unsupervised fash

Giovanni Italiano, Matteo Migliorini

We build the first example of a hyperbolic 6-manifold that admits a perfect circle-valued Morse function, which can be considered as the analogue of a fibration over the circle for manifolds with non-vanishing Euler characteristic. As a consequence, we obtain a new example of a subgroup of a hyperbolic group which is of type $\mathcal{F}_2$ but not $\mathcal

Joshua Hatherley

It is commonly accepted that clinicians are ethically obligated to disclose their use of medical machine learning systems to patients, and that failure to do so would amount to a moral fault for which clinicians ought to be held accountable. Call this "the disclosure thesis." Four main arguments have been, or could be, given to support the disclosure thesis

Chengzhi Wang, Peng Yang

Video analytics demand substantial computing resources, posing significant challenges in computing resource-constrained environment. In this paper, to achieve high accuracy with acceptable computational workload, we propose a cost-effective regions of interest (RoIs) extraction and adaptive inference scheme based on the informative encoding metadata. Specifi