November 2024 arXiv papers — page 31

Adrian Friday, Christina Bremer, Oliver Bates, Christian Remy

The growth of semiconductor technology is unprecedented, with profound transformational consequences for society. This includes feeding an over-reliance on digital solutions to systemic problems such as climate change ('techno-solutionism'). Such technologies come at a cost: environmental, social and material. We unpack topics arising from "The True Cost of

Jingtong Yue, Xin Lin, Zijiu Yang, Chao Ren

No-Reference Image Quality Assessment for distorted images has always been a challenging problem due to image content variance and distortion diversity. Previous IQA models mostly encode explicit single-quality features of synthetic images to obtain quality-aware representations for quality score prediction. However, performance decreases when facing real-wo

Xu-Fan Hu, Yosuke Mizuno, Christian M. Fromm

Context. Relativistic jets from Active Galactic Nuclei are observed to be collimated on the parsec scale. When the pressure between the jet and the ambient medium is mismatched, recollimation shocks and rarefaction shocks are formed. Previous numerical simulations have shown that instabilities can destroy the recollimation structure of jets. Aims. In this st

Haoyu Huang, Chong Chen, Zeang Sheng, Yang Li

In real-world scenarios, most of the data obtained from the information retrieval (IR) system is unstructured. Converting natural language sentences into structured Knowledge Graphs (KGs) remains a critical challenge. We identified three limitations with respect to existing KG construction methods: (1) There could be a large amount of noise in real-world doc

Dongwon Kim, Matteo Zecchin, Sangwoo Park, Joonhyuk Kang

Bayesian optimization (BO) is a sequential approach for optimizing black-box objective functions using zeroth-order noisy observations. In BO, Gaussian processes (GPs) are employed as probabilistic surrogate models to estimate the objective function based on past observations, guiding the selection of future queries to maximize utility. However, the performa

Bastian Wittmann, Yannick Wattenberg, Tamaz Amiranashvili, Suprosanna Shit

Segmenting 3D blood vessels is a critical yet challenging task in medical image analysis. This is due to significant imaging modality-specific variations in artifacts, vascular patterns and scales, signal-to-noise ratios, and background tissues. These variations, along with domain gaps arising from varying imaging protocols, limit the generalization of exist

Duolikun Danier, Mehmet Aygün, Changjian Li, Hakan Bilen

Large-scale pre-trained vision models are becoming increasingly prevalent, offering expressive and generalizable visual representations that benefit various downstream tasks. Recent studies on the emergent properties of these models have revealed their high-level geometric understanding, in particular in the context of depth perception. However, it remains u

Ahmed Gailani, Peter Taylor

Decarbonising the industrial sector is vital to reach net zero targets. The deployment of industrial decarbonisation technologies is expected to increase industrial electricity demand in many countries and this may require upgrades to the existing electricity network or new network investment. While the infrastructure requirements to support the introduction

Ziyi Xu, Ziyao Huang, Juan Cao, Yong Zhang

The generation of anchor-style product promotion videos presents promising opportunities in e-commerce, advertising, and consumer engagement. Despite advancements in pose-guided human video generation, creating product promotion videos remains challenging. In addressing this challenge, we identify the integration of human-object interactions (HOI) into pose-

Yangyang Shi, Qianqian Ren, Yong Liu, Jianguo Sun

Time series forecasting is crucial in many fields, yet current deep learning models struggle with noise, data sparsity, and capturing complex multi-scale patterns. This paper presents MFF-FTNet, a novel framework addressing these challenges by combining contrastive learning with multi-scale feature extraction across both frequency and time domains. MFF-FTNet

Adam Skowyrski

This article is devoted to introduce a new notion of periodicity shadow, which appeared naturally in the study of combinatorics of tame symmetric algebras of period four, or more generally, algebras of generalized quaternion type. For any such an algebra $\La$, we consider its shadow $\bS_\La$, which is the (signed) adjacency matrix of the Gabriel quiver of

Aleksei Kulikov, Feng Shao

For a sequence of vectors $\{v_n\}_{n\in\mathbb{N}}$ in the uniformly convex Banach space $X$ which for all $n, m\in \mathbb{N}$ satisfy $\|v_{n+m}\|\le \|v_n + v_m\|$ we show the existence of the limit $\lim_{n\to \infty} \frac{v_n}{n}$. This extends the classical Fekete's subadditivite lemma to Banach space-valued sequences.

Nikita Shulga

In 1971 Cusick proved that every real number $x\in[0,1]$ can be expressed as a sum of two continued fractions with no partial quotients equal to $1$. In other words, if we define a set $$ S(k):= \{ x\in[0,1] : a_n(x) \geq k \text{ for all } n\in\mathbb{N} \}, $$ then $$ S(2)+S(2) = [0,1]. $$ He also conjectured that this result is unique in the sense that if

Dylan G. L. Allegretti, Peng Shan

We consider the quantized $\mathrm{SL}_2$-character variety of a once-punctured torus. We show that this quantized algebra has three $\mathbb{Z}_2$-invariant subalgebras that are isomorphic to quantized $K$-theoretic Coulomb branches in the sense of Braverman, Finkelberg, and Nakajima. These subalgebras are permuted by the $\mathrm{SL}_2(\mathbb{Z})$ mapping

M. Bojer, A. Cidrim, P. P. Abrantes, R. Bachelard

We investigate the photon statistics of an ensemble of coherently driven non-interacting two-level atoms in the weak driving regime. As it turns out, the system displays unique emission characteristics that are strongly in contrast to the emission of classical oscillating dipoles. By deriving the second-order autocorrelation function, we show that extraordin

Ryo Fujii, Hideo Saito, Ryo Hachiuma

This paper jointly addresses three key limitations in conventional pedestrian trajectory forecasting: pedestrian perception errors, real-world data collection costs, and person ID annotation costs. We propose a novel framework, RealTraj, that enhances the real-world applicability of trajectory forecasting. Our approach includes two training phases -- self-su

Theodora Worledge, Tatsunori Hashimoto, Carlos Guestrin

Across all fields of academic study, experts cite their sources when sharing information. While large language models (LLMs) excel at synthesizing information, they do not provide reliable citation to sources, making it difficult to trace and verify the origins of the information they present. In contrast, search engines make sources readily accessible to us

Junhua Liu, Roy Ka-Wei Lee, Kwan Hui Lim

Fairness in both Machine Learning (ML) predictions and human decision-making is essential, yet both are susceptible to different forms of bias, such as algorithmic and data-driven in ML, and cognitive or subjective in humans. In this study, we examine fairness using a real-world university admissions dataset comprising 870 applicant profiles, leveraging thre

Xuzhou Yang

In this paper, a certain type of linear boundary diffusion equation is studied. Such equation is crucial in the research of a non-linear boundary diffusion problem which was originated from the boundary heat control problem and Yamabe flow. Such equation is also analogous to the classical fast diffusion equation and porous medium equation. Under an compatibl

Yufan Zheng, Wei Jiang, Tong Chen, Alexander Zhou

Among various spatio-temporal prediction tasks, epidemic forecasting plays a critical role in public health management. Recent studies have demonstrated the strong potential of spatio-temporal graph neural networks (STGNNs) in extracting heterogeneous spatio-temporal patterns for epidemic forecasting. However, most of these methods bear an over-simplified as

Zejun Huang, Jiahui Liu, Chenxi Yang

Let $G$ be a connected nonregular graphs of order $n$ with maximum degree $\Delta$ that attains the maximum spectral radius. Liu and Li (2008) proposed a conjecture stating that $G$ has a degree sequence $(\Delta,\ldots,\Delta,\delta)$ with $\delta<\Delta$. For $\Delta=3$ and $\Delta=4$, Liu (2024) confirmed this conjecture by characterizing the structure of

Muskan Arora, Jyoti Arya, Pranav Chokkara, Jasleen Lugani

Spontaneous parametric down conversion (SPDC), especially in non-linear waveguides, serves as an important process to generate quantum states of light with desired properties. In this work, we report on a design of a strongly dispersive, singly poled thin film lithium niobate (TFLN) waveguide geometry which acts as a convertible source of photon pairs across

Anis Allagui, Enrique H. Balaguera, Chunlei Wang

In this work we derive and study the analytical solution of the voltage and current diffusion equation for the case of a finite-length resistor-constant phase element (CPE) transmission line (TL) network that can represent a model for porous electrodes in the absence of any Faradic processes. The energy storage component is considered to be an elemental CPE

Chen Li, Elena Ferro, Corey Lammie, Manuel Le Gallo

Analog In-Memory Computing (AIMC) offers a promising solution to the von Neumann bottleneck. However, deploying transformer models on AIMC remains challenging due to their inherent need for flexibility and adaptability across diverse tasks. For the benefits of AIMC to be fully realized, weights of static vector-matrix multiplications must be mapped and progr

Marek Janasz, Izabela Leśniak

In this paper we provide the non-existence criterion for the so-called maximizing curves of odd degrees. Furthermore, in the light of our criterion, we define a new class of plane curves that generalizes the notion of maximizing curves which we call as $M$-curves.

Paul M. Burdekin, Ilse Maillette de Buy Wenniger, Stephen Sagona-Stophel, Jerzy Szuniewicz

Future optical quantum technologies, such as quantum networks, distributed quantum computing and sensing, demand efficient, broadband quantum memories. However, achieving high efficiency without introducing noise, reducing bandwidth, or limiting scalability remains a challenge. Here, we present a new approach to enhance quantum memory protocols by leveraging

Bo Yang, Jianke Yang

Large-time patterns of general higher-order lump solutions in the KP-I equation are investigated. It is shown that when the index vector of the general lump solution is a sequence of consecutive odd integers starting from one, the large-time pattern in the spatial $(x, y)$ plane generically would comprise fundamental lumps uniformly distributed on concentric

Jie Xu, Xiaokang Li, Chengyu Yue, Yuanyuan Wang

Medical image segmentation often faces the challenge of prohibitively expensive annotation costs. While few-shot learning offers a promising solution to alleviate this burden, conventional approaches still rely heavily on pre-training with large volumes of labeled data from known categories. To address this issue, we propose leveraging the Segment Anything M

Richard Ueltzen

For a positive integer $k$ and a graph $H$ on $k$ vertices, we are interested in the inducibility of $H$, denoted $\mathrm{ind}(H)$, which is defined as the maximum possible probability that choosing $k$ vertices uniformly at random from a large graph $G$, they induce a copy of $H$. It follows from the resolved Edge-statistics conjecture that if $H \not \in

Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu

Recent cross-domain recommendation (CDR) studies assume that disentangled domain-shared and domain-specific user representations can mitigate domain gaps and facilitate effective knowledge transfer. However, achieving perfect disentanglement is challenging in practice, because user behaviors in CDR are highly complex, and the true underlying user preferences

Md Redwanul Islam, Niklas Wolff, Georg Schönweger, Tom-Niklas Kreutzer

This article examines systematic oxygen (O)-incorporation to reduce total leakage currents in sputtered wurtzite-type ferroelectric Al0.73Sc0.27N thin films, along with its impact on the material structure and the polarity of the as-grown films. The O in the bulk Al0.73Sc0.27N was introduced through an external gas source during the reactive sputter process.

Hanying Deng, Yaxin Li, Zhihao qu, Jing Deng

We investigate the nonlinear optical response of graphene nanoribbon (GNR) heterojunctions both without and with one or multiple topological interface states. By implementing a distant-neighbor quantum-mechanical (DNQM) method, we demonstrate a pronounced enhancement of the nonlinear optical response of GNR heterojunctions as the number of topological states

Joseph Karmazyn, Emma Lepri, Michael Wemyss

To any periodic module over any algebra, this paper introduces an associated trivial extension DG-algebra T. After first passing to a strictly unital $A_\infty$-minimal model, it then constructs a particular $A_\infty$-algebra N, called the unitally positive $A_\infty$-algebra, which roughly speaking describes the identity in degree zero and all the positive

Angharad Weeks, Vincent Van Eylen, Daniel Huber, Daisuke Kawata

Interior compositions are key for our understanding of Earth-like exoplanets. The composition of the core can influence the presence of a magnetic dynamo and the strength of gravity on the planetary surface, both of which heavily impact thermal and possible biological processes and thus the habitability for life and its evolution on the planet. However, deta

A. Alshemi, E. M. Forgan, A. Hiess, R. Cubitt

Multiband superconductivity arises when multiple electronic bands contribute to the formation of the superconducting state, allowing distinct pairing interactions and gap structures. Here, we present field- and temperature-dependent data on the vortex lattice structure in 2$H$-NbSe$_2$ as a contribution to the ongoing debate on the nature of the superconduct

Endale H. Kirubel, P. Aswin, A. Sameen

In this article, we introduce a new mathematical framework that can describe the budget of turbulence kinetic energy and heat transfer in both physical space and scale space of turbulence. We derived two exact transport equations for inhomogeneous and anisotropic buoyancy-driven incompressible turbulent flow. The two equations are the turbulent kinetic energ

Dhruv Agrawal, W. L. Reenbohn

In this study, we explore an overdamped system of a dimer in a bistable potential immersed in a heat bath. The monomers interact via the combination of the Lennard-Jones potential and the harmonic potential. We have introduced a short-range interaction in our model making it more physical. Such a classical system can be used as a model for stochastic resonan

Hanning Yuan, Zhihui Zhang, Qi Guo, Lianhua Chi

Multi-view contrastive clustering (MVCC) has gained significant attention for generating consistent clustering structures from multiple views through contrastive learning. However, most existing MVCC methods create cross-views by combining any two views, leading to a high volume of unreliable pairs. Furthermore, these approaches often overlook discrepancies

Mahdi Salahshour, Amirahmad Shafiee, Mojtaba Tefagh

The Lightning Network (LN) has emerged as a second-layer solution to Bitcoin's scalability challenges. The rise of Payment Channel Networks (PCNs) and their specific mechanisms incentivize individuals to join the network for profit-making opportunities. According to the latest statistics, the total value locked within the Lightning Network is approximately \

A. A. Kamashev, N. N. Garif'yanov, A. A. Validov, V. Kataev

To increase the efficiency of the superconducting spin valve (SSV), special attention should be paid to the choice of ferromagnetic materials for the F1/F2/S SSV multilayer. Here, we report the preparation and the superconducting properties of the SSV heterostructures where Pb is used as the superconducting S layer. In the magnetic part of the structure, we

Jan Goedgebeur, Jorik Jooken, Tibo Van den Eede

An $(\{r,m\};g)$-graph is a (simple, undirected) graph of girth $g\geq3$ with vertices of degrees $r$ and $m$ where $2 \leq r < m$ . Given $r,m,g$, we seek the $(\{r,m\};g)$-graphs of minimum order, called $(\{r,m\};g)$-cages or bi-regular cages, whose order is denoted by $n(\{r,m\};g)$. In this paper, we use computational methods for finding $(\{r,m\};g)$-g

Yuanchen Bei, Weizhi Chen, Hao Chen, Sheng Zhou

Multi-label node classification is an important yet under-explored domain in graph mining as many real-world nodes belong to multiple categories rather than just a single one. Although a few efforts have been made by utilizing Graph Convolution Networks (GCNs) to learn node representations and model correlations between multiple labels in the embedding space

Ting Xiaoyang, Minfeng Zhang, Shu gonglee, Saimin Chen Zhang

The evolving landscape of edge computing envisions platforms operating as dynamic intermediaries between application providers and edge servers (ESs), where task offloading is coupled with payments for computational services. Ensuring efficient resource utilization and meeting stringent Quality of Service (QoS) requirements necessitates incentivizing ESs whi

Davide Salvi, Amit Kumar Singh Yadav, Kratika Bhagtani, Viola Negroni

Recent techniques for speech deepfake detection often rely on pre-trained self-supervised models. These systems, initially developed for Automatic Speech Recognition (ASR), have proved their ability to offer a meaningful representation of speech signals, which can benefit various tasks, including deepfake detection. In this context, pre-trained models serve

Lars Dammann, Richard Kohns, Patrick Huber, Robert H. Meißner

Molecular Dynamics (MD) simulations are a powerful tool for studying matter at the atomic scale. However, to simulate solids, an initial atomic structure is crucial for the successful execution of MD simulations, but can be difficult to prepare due to insufficient atomistic information. At the same time Wide Angle X-ray Scattering (WAXS) measurements can det

Filippo Ansalone, Flavio Maiorana, Daniele Affinita, Flavio Volpi

Advancing human-robot communication is crucial for autonomous systems operating in dynamic environments, where accurate real-time interpretation of human signals is essential. RoboCup provides a compelling scenario for testing these capabilities, requiring robots to understand referee gestures and whistle with minimal network reliance. Using the NAO robot pl

Kainan Chang, Muhammad Zubair, Jin Luo Cheng, Wang-Kong Tse

We theoretically investigate the second harmonic generation (SHG) of topological insulator surface states in a perpendicular magnetic field. Our theory is based on the microscopic expression of the second-order magneto-optical conductivity developed from the density matrix formalism, taking into account hexagonal warping effects on the surface states' band s

Yingxiang Hu, Haizhong Li, Botong Xu

The $L_p$-Christoffel-Minkowski problem and the prescribed $L_p$-Weingarten curvature problem for convex hypersurfaces in Euclidean space are important problems in geometric analysis. In this paper, we consider their counterparts in hyperbolic space. For the horospherical $p$-Christoffel-Minkowski problem first introduced and studied by the second and third

Kensuke Ogawa, Moeta Tsukamoto, Yusuke Mori, Daigo Takafuji

Imaging spin-wave propagation in magnetic materials in a wide frequency range is crucial for understanding and applying spin-wave dynamics. Recently, nitrogen-vacancy (NV) centers in diamond have attracted attention as sensors capable of quantitatively measuring the amplitude and phase of coherent spin waves. However, the conventional sensing protocol has be

Masoud Jamshidiyan Tehrani

Software built on poor structural patterns often shows higher exposure to security defects. When code differs from established best practices, verification and maintenance become increasingly difficult, thereby raising the risk of unintentional vulnerabilities. In the context of blockchain technology, where immutable smart contracts handle high-value transac

Marek Wodzinski, Mateusz Daniol, Daria Hemmerling

Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting time for reconstruction surgery can extend to several weeks or even months, especially in less developed countries. One factor contributing to the extended waiting period is the intricate process of personalized im

Markus Feldt, Thomas Bertram, Carlos Correia, Olivier Absil

The Mid-infrared ELT Imager and Spectrograph (METIS) is a first-generation instrument for the Extremely Large Telescope (ELT), Europe's next-generation 39 m ground-based telescope for optical and infrared wavelengths. METIS will offer diffraction-limited imaging, low- and medium-resolution slit spectroscopy, and coronagraphy for high-contrast imaging between

Aleksei Luchinsky, Umar Islambekov

Persistent homology is a widely-used tool in topological data analysis (TDA) for understanding the underlying shape of complex data. By constructing a filtration of simplicial complexes from data points, it captures topological features such as connected components, loops, and voids across multiple scales. These features are encoded in persistence diagrams (

Chao Wang, Jiaxuan Zhao, Lingling Li, Licheng Jiao

Graph neural architecture search (GNAS) can customize high-performance graph neural network architectures for specific graph tasks or datasets. However, existing GNAS methods begin searching for architectures from a zero-knowledge state, ignoring the prior knowledge that may improve the search efficiency. The available knowledge base (e.g. NAS-Bench-Graph) c

Changgeon Ko, Jisu Shin, Hoyun Song, Jeongyeon Seo

Large language models (LLMs) often reflect real-world biases, leading to efforts to mitigate these effects and make the models unbiased. Achieving this goal requires defining clear criteria for an unbiased state, with any deviation from these criteria considered biased. Some studies define an unbiased state as equal treatment across diverse demographic group

Jan Boelts, Michael Deistler, Manuel Gloeckler, Álvaro Tejero-Cantero

Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challenge. Simulation-based inference (SBI) addresses this by enabling Bayesian inference for simulators, identifying parameters that match observed data and align with

Md Sayeed Anwar, Dibakar Ghosh, Kevin O'Keeffe

We study the collective dynamics of swarmalators subjected to periodic (sinusoidal) forcing. Although previous research focused on the simplified case of motion in a one-dimensional (1D) periodic domain, we extend this analysis to the more realistic scenario of motion in two and three spatial dimensions with periodic boundary conditions. In doing so, we iden

Zeyu Ling, Bo Han, Shiyang Li, Jikang Cheng

Large language models (LLMs) are, by design, inherently capable of multi-task learning: through a unified next-token prediction paradigm, they can naturally address a wide variety of downstream tasks. Prior work in the motion domain has demonstrated some generality by adapting LLMs via a Motion Tokenizer coupled with an autoregressive Transformer to generate

Guojian Zhan, Qiang Ge, Haoyu Gao, Yuming Yin

Numerical stability is of great significance for discrete-time dynamic vehicle model. Among the unstable factors, low-speed singularity stands out as one of the most challenging issues, which arises from that the denominator of tire side angle term only contains the vehicle longitudinal speed. Consequently, for the common low-speed and stop-start driving sce

Hongwei Ge, Zhanwen Han

The stability criteria of rapid mass transfer and common-envelope evolution are fundamental in binary star evolution. They determine the mass, mass ratio, and orbital distribution of many important systems, such as X-ray binaries, type Ia supernovae, and merging gravitational-wave sources. In the limit of extremely rapid mass transfer, the response of a dono

Carlos Garrido-Munoz, Jorge Calvo-Zaragoza

Recent advances in Handwritten Text Recognition (HTR) have led to significant reductions in transcription errors on standard benchmarks under the i.i.d. assumption, thus focusing on minimizing in-distribution (ID) errors. However, this assumption does not hold in real-world applications, which has motivated HTR research to explore Transfer Learning and Domai

Ruzhi Song, Fengling Li, Jie Wu, Fengchun Lei

Many structures in science, engineering, and art can be viewed as curves in 3-space. The entanglement of these curves plays a crucial role in determining the functionality and physical properties of materials. Many concepts in knot theory provide theoretical tools to explore the complexity and entanglement of curves in 3-space. However, classical knot theory

Pranjal Dutta, Amit Sinhababu, Thomas Thierauf

For a polynomial $f$ from a class $\mathcal{C}$ of polynomials, we show that the problem to compute all the constant degree irreducible factors of $f$ reduces in polynomial time to polynomial identity tests (PIT) for class $\mathcal{C}$ and divisibility tests of $f$ by constant degree polynomials. We apply the result to several classes $\mathcal{C}$ and obta

Ernö Robert Csetnek, Szilárd Csaba László

We introduce and investigate the asymptotic behaviour of the trajectories of a second order dynamical system with Tikhonov regularization for solving a monotone equation with single valued, monotone and continuous operator acting on a real Hilbert space. We consider a vanishing damping which is correlated with the Tikhonov parameter and which is in line with

Tianci Luo, Yong Wei

The horospherical $p$-Christoffel-Minkowski problem was posed by Li and Xu (2022) as a problem prescribing the $k$-th horospherical $p$-surface area measure of $h$-convex domains in hyperbolic space $\mathbb{H}^{n+1}$. It is a natural generalization of the classical $L^p$ Christoffel-Minkowski problem in the Euclidean space $\mathbb{R}^{n+1}$. In this paper,

Aung Phone Maw

We demonstrate the general outlines of a method for obtaining analytic expressions for certain types of general arithmetical sums. In particular, analytical expressions for a general arithmetical sum whose terms are summed over either the positive integer solutions $(a,b)$ of the Diophantine equation $kb^2+da^2 = N$ or the positive integer solutions $(a,b)$

Juan Carlos Saborio, Joachim Hertzberg

Intention recognition, or the ability to anticipate the actions of another agent, plays a vital role in the design and development of automated assistants that can support humans in their daily tasks. In particular, industrial settings pose interesting challenges that include potential distractions for a decision-maker as well as noisy or incomplete observat

José Claudio Sabina de Lis

This work is devoted to prove an optimum version of the trace inequality associated to the embedding $BV(\Omega)\subset L^1(\partial\Omega)$. Special emphasis is placed on the regularity that the domain $\Omega$ should exhibit for this result to be valid.

Yingjing Xu, Jie Kong, Jiazhi Wang, Xiao Pan

In this paper, we focus on the task of instruction-based image editing. Previous works like InstructPix2Pix, InstructDiffusion, and SmartEdit have explored end-to-end editing. However, two limitations still remain: First, existing datasets suffer from low resolution, poor background consistency, and overly simplistic instructions. Second, current approaches

Chunyang Dou, Fu-tao Hu, Xing Peng

For a family of graphs $\cal F$, a graph $G$ is $\cal F$-free if it does not contain a member of $\cal F$ as a subgraph. The Tur\'an number $\textrm{ex}(n,{\cal F})$ is the maximum number of edges in an $n$-vertex graph which is $\cal F$-free. Let ${\cal C}_{\geq k}$ be the set of cycles with length at least $k$. In this paper, we investigate the Tur\'an num

Sam Grierson, William J Buchanan, Craig Thomson, Baraq Galeb

Biometric systems, while offering convenient authentication, often fall short in providing rigorous security assurances. A primary reason is the ad-hoc design of protocols and components, which hinders the establishment of comprehensive security proofs. This paper introduces a formal framework for constructing secure and privacy-preserving biometric systems.

Andrew Cheek, Ui Min

Preferred axion models are minimal realizations of the Peccei-Quinn solution to the strong CP problem while providing a dark matter candidate. These models invoke new heavy quarks that interact strongly with the Standard Model bringing them into thermal equilibrium in the early Universe. We show that for a number of these models, the heavy quarks will decay

Antonio Capolupo, Salvatore Capozziello, Gabriele Pisacane, Aniello Quaranta

We show that, in the framework of quantum field theory in curved spacetime, the semiclassical energy-momentum tensor of the neutrino flavor vacuum fulfills the equation of state of dust and cold dark matter. We consider spherically symmetric spacetimes, and we demonstrate that, within the weak field approximation, the flavor vacuum contributes as a Yukawa co

Yaya Etiabi, Eslam Eldeeb, Mohammad Shehab, Wafa Njima

Accurate indoor localization remains challenging due to variations in wireless signal environments and limited data availability. This paper introduces MetaGraphLoc, a novel system leveraging sensor fusion, graph neural networks (GNNs), and meta-learning to overcome these limitations. MetaGraphLoc integrates received signal strength indicator measurements wi

Shaoqi Hou

In this work, it is shown that based on the linear analysis, as long as a theory of gravity is diffeomorphism invariant and possesses the tensor degrees of freedom propagating at a constant, isotropic speed without dispersion, its asymptotic symmetry group of an isolated system contains the (extended/generalized) Bondi-Metzner-Sachs group. The tensor gravita

Artur Bromboszcz

In this note we focus on combinatorial aspects of plus-one generated line arrangements. We provide combinatorial constraints on such arrangements and we construct a polynomial that decodes the plus-one generated property. We present new examples of plus-one generated arrangements constructed by using classical Klein and Wiman reflection arrangements, and we

Christophe Eloy

Planktonic organisms, despite their passive drift in the ocean, exhibit complex responses to fluid flow, including escape behaviors and larval settlement detection. But what flow signals can they perceive? This paper addresses this question by considering an organism covered with sensitive cilia and immersed in a background flow. The organism is modeled as a

L. Sidoli, V. Sguera, P. Esposito, R. Sathyaprakash

We report on the results of X-ray observations (XMM-Newton, INTEGRAL and Swift) of two hard X-ray sources, IGR J17503-2636 and IGR J17507-2647, whose nature is not fully elucidated in the literature. Three XMM-Newton observations covered the field of IGR J17503-2636, in 2020 and twice in 2023. The analysis of the two XMM-Newton observations performed in Sept

Olesia Pashina, Albert Seredin, Giulia Crotti, Giuseppe Della Valle

Ultrafast excitation of non-equilibrium carriers under intense pulses offer unique opportunities for controlling optical properties of semiconductor materials. In this work, we propose a scheme for ultrafast generation of surface plasmon polaritons (SPPs) via a transient metagrating formed under two interfering optical pump pulses in the semiconductor GaAs t

Ryota Maeda, Yunseong Moon, Seung-Hwan Baek

Light-matter interactions modify both the intensity and polarization state of light. Changes in polarization, represented by a Mueller matrix, encode detailed scene information. Existing optical ellipsometers capture Mueller-matrix images; however, they are often limited to capturing static scenes due to long acquisition times. Here, we introduce Event Ellip

Juan M. Espejo Salcedo, Karl Glazebrook, Deanne B. Fisher, Sarah M. Sweet

We present measurements of the specific angular momentum $j_\star$ of 41 star-forming galaxies at $1.5<z<2.5$. These measurements are based on radial profiles inferred from near-IR \textit{HST} photometry, along with multi-resolution emission-line kinematic modelling using integral field spectroscopy (IFS) data from KMOS, SINFONI, and OSIRIS. We identified 2

Ray P. Norris, Bärbel S. Koribalski, Catherine L. Hale, Matt J. Jarvis

We present the discovery of a new Odd Radio Circle (ORC J0219--0505) in 1.2~GHz radio continuum data from the MIGHTEE survey taken with the MeerKAT telescope. The radio-bright host is a massive elliptical galaxy, which shows extended stellar structure, possibly tidal tails or shells, suggesting recent interactions or mergers. The radio ring has a diameter of

Maorong Wang, Jiafeng Mao, Xueting Wang, Toshihiko Yamasaki

The recent success of denoising diffusion models has significantly advanced text-to-image generation. While these large-scale pretrained models show excellent performance in general image synthesis, downstream objectives often require fine-tuning to meet specific criteria such as aesthetics or human preference. Reward gradient-based strategies are promising

Cristobal Ortega, Yann Falevoz, Renaud Ayrignac

Large Language Models (LLMs) have become essential in a variety of applications due to their advanced language understanding and generation capabilities. However, their computational and memory requirements pose significant challenges to traditional hardware architectures. Processing-in-Memory (PIM), which integrates computational units directly into memory

Anastasia Stavrova

Let $G$ be a simply connected Chevalley--Demazure group scheme without $SL_2$-factors. For any unital commutative ring $R$, we denote by $E(R)$ the standard elementary subgroup of $G(R)$, that is, the subgroup generated by the elementary root unipotent elements. We prove that the map $$ G(R[x_1^{\pm 1},\ldots,x_n^{\pm 1}])/E(R[x_1^{\pm 1},\ldots,x_n^{\pm 1}]

Bernd Fiedler

We agree with the interpretation of W. Schlosser, that the Nebra Sky Disc is a reminder of a method of determining a start date (and possibly also an end date) of the farming year. We extend this interpretation. We think that we found the constellation Taurus on the Disc, which forms by addition of three stars from the constellation Gemini the pattern of a p

Hadewijch De Clercq, Nicolai Reshetikhin, Jasper Stokman

We extend the graphical calculus developed in the first part of this paper to the parametrising spaces of quantum vertex operators. This involves a graphical implementation of the dynamical twist functor, which is a strict monoidal functor that describes how a morphism acting on the spin space of a quantum vertex operator $\Phi$ is transported to a morphism

Vedrana Krivokuca Hahn, Jeremy Maceiras, Alain Komaty, Philip Abbet

We present three biometric datasets (iCarB-Face, iCarB-Fingerprint, iCarB-Voice) containing face videos, fingerprint images, and voice samples, collected inside a car from 200 consenting volunteers. The data was acquired using a near-infrared camera, two fingerprint scanners, and two microphones, while the volunteers were seated in the driver's seat of the c

Milena Chadimová, Eduard Jurášek, Tomáš Kliegr

This paper introduces a novel method, referred to as "hashing", which involves masking potentially bias-inducing words in large language models (LLMs) with hash-like meaningless identifiers to reduce cognitive biases and reliance on external knowledge. The method was tested across three sets of experiments involving a total of 490 prompts. Statistical analys

Dmitry Kobyakov, Xavier Viñas

Within the liquid drop model built up with the nuclear interaction parametrization Sk$\chi$450, which is based on the chiral effective field theory, we calculate numerically the internal energy density for each of nuclear pasta phases and for the uniform nuclear matter. We provide quantitative arguments in favor of coexistence of various nuclear matter phase

N. Bukharskii, Ph. Korneev

The work considers an optical scheme for collimation of high-energy proton beams using $\sim 10^5$~T scale magnetic fields induced in a miniature "snail" target by petawatt or multi-petawatt laser irradiation in ps or fs regime. Such magnetic fields are known to be frozen into hot plasma and exist on at least a hundred of picoseconds time-scale, allowing the

Yunyi Liu, Yingshu Li, Zhanyu Wang, Xinyu Liang

Automated radiology report generation (R2Gen) has advanced significantly, introducing challenges in accurate evaluation due to its complexity. Traditional metrics often fall short by relying on rigid word-matching or focusing only on pathological entities, leading to inconsistencies with human assessments. To bridge this gap, we introduce ReFINE, an automati

Shaofei Du, Wenjuan Luo, Hao Yu

It was shown by Kutnar, Maru\v si\v c and Zhang in 2012 that every connected vertex-transitive graph of order $10p$, where $p$ is a prime and $p\ne 7$, contains a Hamilton path, except for graphs $X$ arising from the action of PSL$(2, s^m)$ on cosets of $\mathbb{Z}_s^m\rtimes \mathbb{Z}_{\frac{s^m-1}{10}}$, where $s$ is a prime. In this paper, Hamilton cycle

Serdar Çite, Oğul Esen

This work presents higher order Lagrangian dynamics possessing locally conformal character. More concretely, locally conformal higher order Euler-Lagrange equations are written with particular focus on the second- and the third-order cases.

Shuai Wang, Shengyao Zhuang, Bevan Koopman, Guido Zuccon

2D Matryoshka Training is an advanced embedding representation training approach designed to train an encoder model simultaneously across various layer-dimension setups. This method has demonstrated higher effectiveness in Semantic Text Similarity (STS) tasks over traditional training approaches when using sub-layers for embeddings. Despite its success, disc

Yifei Gu, Jun Jie Miao

In the paper, we study the generalized $q$-dimensions of measures supported by nonautonomous attractors, which are the generalization of classic Moran sets and attractors of iterated function systems. First, we estimate the generalized $q$-dimensions of measures supported on nonautonomous attractors, and we provide dimension formulas for generalized $q$-dime

Yuxin Tian, Yaxuan Li, Bing Xiong, Junwen Zhang

Current wireless communication systems are increasingly constrained by insufficient bandwidth and limited power output, impeding the achievement of ultra-high-speed data transmission. The terahertz (THz) range offers greater bandwidth, but it also imposes higher requirements on broadband and high-power devices. In this work, we present a modified uni-traveli

L. Sudharani, N. S. Kavya, V. Venkatesha

We study Coupling Extended Proca-Nuevo gravity, a non-linear theory extending from dRGT massive gravity with a spin-1 field. This theory is shown to yield reliable, ghost-free cosmological solutions, modeling both the Universe's thermal history and late-time acceleration. By analyzing data from Dark energy spectroscopic instruments (DESI), Cosmic Chronometer

Guoguo Ai, Guansong Pang, Hezhe Qiao, Yuan Gao

Graph Transformers (GTs) have demonstrated remarkable performance in graph representation learning over popular graph neural networks (GNNs). However, self--attention, the core module of GTs, preserves only low-frequency signals in graph features, leading to ineffectiveness in capturing other important signals like high-frequency ones. Some recent GT models

Yaxian Zhang, Fuliang Lu, Heping Zhang

A connected graph G is matching covered if every edge lies in some perfect matching of G. Lovasz proved that every matching covered graph G can be uniquely decomposed into a list of bricks (nonbipartite) and braces (bipartite) up to multiple edges. Denote by b(G) the number of bricks of G. An edge e of G is removable if G-e is also matching covered, and soli