April 2024 arXiv papers — page 131

Valentina Abramenko, Regina Suleymanova

We used magnetograms acquired with the {\it Helioseismic and Magnetic Imager} (HMI) on board the {\it Solar Dynamics Observatory} (SDO) to calculate and analyze spatial correlation functions and the multi-fractal spectra in solar active regions (ARs). The analysis was performed for two very different types of ARs: i) simple bipolar magnetic structures with r

B. Nisini, M. G. Navarro, T. Giannini, S. Antoniucci

We present the first results of the JWST program PROJECT-J (PROtostellar JEts Cradle Tested with JWST ), designed to study the Class I source HH46 IRS and its outflow through NIRSpec and MIRI spectroscopy (1.66 to 28 micron). The data provide line-images (~ 6.6" in length with NIRSpec, and up to 20" with MIRI) revealing unprecedented details within the jet,

Regina A. Suleymanova, Leonty I. Miroshnichenko, Valentina I. Abramenko

Charged particles, generated in solar flares, sometimes can get extremely high energy, above the 500 MeV level, and produce abrupt ground level enhancements (GLEs) on the ground-based detectors of cosmic rays. The initial flares are strong eruptions and they should be originated from active regions (ARs). A list of GLE events and associated flares was initia

Vikash Sharma, Sudip Pal, Divya Sharma, Dinesh Kumar Shukla

We report exchange bias (EB) in single-phase CoO nanoparticles, where two magnetic phases naturally emerge as the crystallite size decreases from 34.6 to 10.8 nm. The N\'eel temperature (TN) associated with antiferromagnetic ordering decreases monotonically with the reduction in crystallite size, highlighting the significant influence of size effects. The 34

Shifeng Cui, Wenan Guo, G. G. Batrouni, Pinaki Sengupta

Spin-Peierls transition occurs in a one-dimensional $S=1$ Heisenberg antiferromagnetic model with single-ion anisotropy, coupled to finite frequency bond phonons, in a magnetic field. Our results indicate that for the pure Heisenberg model, any Peierls transition is suppressed by quantum fluctuations of the phonon field. However, a novel magnetic field-induc

Tilahun Abebaw, Amanuel Mamo, David Ssevviiri, Zelalem Teshome

Let $R$ be a commutative unital ring, $\mathfrak{ a}$ an ideal of $R$ and $M$ a fixed $R$-module. We introduce and study generalisations of $\mathfrak{a}$-reduced modules, $\mathfrak{R}_{\mathfrak{ a}}$ and $\mathfrak{a}$-coreduced modules, $\mathfrak{C}_{\mathfrak{ a}}$ studied in the literature. They are called modules $\mathfrak{ a}$-reduced with respect

Md. Shariful Islam, Ahmed Zubair

The polarizer-based device industry is expanding quickly, requiring high-quality research on nanoscale wideband polarizers. Here, we investigated the possibility of utilizing Al dimer nanostructures on broad-band polarizers. Metals are always considered promising candidates for reflection-based polarizer development because of their high extinction ratio. Th

Anton Freund

A predilator is a particularly uniform transformation of linear orders. We have a dilator when the transformation preserves well-foundedness. Over the theory $\mathsf{ACA}_0$ from reverse mathematics, any $\Pi^1_2$-formula is equivalent to the statement that some predilator is a dilator. We show how this completeness result breaks down without arithmetical c

Weiming Wang, Kai Wu, Fred van Keulen, Jun Wu

In additive manufacturing, the fabrication sequence has a large influence on the quality of manufactured components. While planning of the fabrication sequence is typically performed after the component has been designed, recent developments have demonstrated the possibility and benefits of simultaneous optimization of both the structural layout and the corr

Jürgen Struckmeier

In the extended Lagrange formalism of classical point dynamics, the system's dynamics is parametrized along a system evolution parameter $s$, and the physical time $t$ is treated as a \emph{dependent} variable $t(s)$ on equal footing with all other configuration space variables $q^{i}(s)$. In the action principle, the conventional classical action $L\,dt$ is

Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto

Deep Learning has advanced significantly in medical applications, aiding disease diagnosis in Chest X-ray images. However, expanding model capabilities with new data remains a challenge, which Continual Learning (CL) aims to address. Previous studies have evaluated CL strategies based on classification performance; however, in sensitive domains such as healt

Pavle Pandžić, Petr Somberg

Motivated by our attempts to construct an analogue of the Dirac operator in the setting of $U_q(\mathfrak{sl}_n)$, we write down explicitly the braided coproduct, antipode, and adjoint action for quantum algebra $U_q(\mathfrak{sl}_2)$. The braided adjoint action is seen to coincide with the ordinary quantum adjoint action, which also follows from the general

Sanjar Shaymatov, Naresh Dadhich, Arman Tursunov

Buchdahl star is the most compact object without an event horizon and is an excellent candidate for a black hole mimicker. Unlike black holes, rotating Buchdahl star can be over-extremal with respect to the black hole, sustaining a larger spin. We show that it can also develop an ergosphere above the threshold spin $\beta > 1/\sqrt{2}$, which allows extracti

Shirel Attia, Revital Shani Hershkovich, Alissa Tabakhov, Angeleene Ang

Background: Sleep staging is a fundamental component in the diagnosis of sleep disorders and the management of sleep health. Traditionally, this analysis is conducted in clinical settings and involves a time-consuming scoring procedure. Recent data-driven algorithms for sleep staging, using the photoplethysmogram (PPG) time series, have shown high performanc

Xiaoxi Wei, Jyotindra Narayan, A. Aldo Faisal

Machine learning has enhanced the performance of decoding signals indicating human behaviour. EEG decoding, as an exemplar indicating neural activity and human thoughts non-invasively, has been helpful in neural activity analysis and aiding patients via brain-computer interfaces. However, training machine learning algorithms on EEG encounters two primary cha

Emma Kun, Imre Bartos, Julia Becker Tjus, Peter L. Biermann

The first high-energy neutrino source identified by IceCube was a blazar -- an active galactic nucleus driving a relativistic jet towards Earth. Jets driven by accreting black holes are commonly assumed to be needed for high-energy neutrino production. Recently, IceCube discovered neutrinos from Seyfert galaxies, which appears unrelated to jet activity. Here

V. N. Berestovskii

The author studies the G\"odel Universe as the Lie group with left-invariant Lorentz metric. The expressions for timelike and isotropic geodesics in elementary functions are found by methods of geometric theory of optimal control for the search of geodesics on Lie groups with left-invariant (sub-)Lorentz metrics. It is proved that the G\"odel Universe has no

Tom Bordin, Thomas Maugey

This study addresses the challenge of, without training or fine-tuning, controlling the global color aspect of images generated with a diffusion model. We rewrite the guidance equations to ensure that the outputs are closer to a known color map, and this without hindering the quality of the generation. Our method leads to new guidance equations. We show in t

Sagiv Shiber, Orsola De Marco, Patrick M. Motl, Bradley Munson

We study the properties of double white dwarf (DWD) mergers by performing hydrodynamic simulations using the new and improved adaptive mesh refinement code Octo-Tiger. We follow the orbital evolution of DWD systems of mass ratio q=0.7 for tens of orbits until and after the merger to investigate them as a possible origin for R Coronae Borealis (RCB) type star

Remco Royen, Adrian Munteanu

While deep learning-based methods have demonstrated outstanding results in numerous domains, some important functionalities are missing. Resolution scalability is one of them. In this work, we introduce a novel architecture, dubbed RESSCAL3D, providing resolution-scalable 3D semantic segmentation of point clouds. In contrast to existing works, the proposed m

Zhuo Pan, Jianbo Liu, Pengjie Wang, Zhusong Mei

Direct laser acceleration of electrons in near-critical-density (NCD) carbon nanotube foams (CNFs) has its advantages in the high-efficiency generation of relativistic electrons and broadband X-rays. Here, we report the first simultaneous measurement on the spectra of laser-driven electrons and X-rays from CNFs at moderately relativistic intensities of aroun

Ana Palacios, Artur Garcia-Saez, Bruno Julia-Diaz, Marta P. Estarellas

Achieving densely connected hardware graphs is a challenge for most quantum computing platforms today, and a particularly crucial one for the case of quantum annealing applications. In this context, we present a scalable architecture for quantum annealers to realize effective Ising Hamiltonians of arbitrary connectivity. Our proposal consists on a resource-e

Fulong Ma, Weiqing Qi, Guoyang Zhao, Linwei Zheng

3D lane detection is essential in autonomous driving as it extracts structural and traffic information from the road in three-dimensional space, aiding self-driving cars in logical, safe, and comfortable path planning and motion control. Given the cost of sensors and the advantages of visual data in color information, 3D lane detection based on monocular vis

Marina Ceccon, Davide Dalle Pezze, Alessandro Fabris, Gian Antonio Susto

Despite the critical importance of the medical domain in Deep Learning, most of the research in this area solely focuses on training models in static environments. It is only in recent years that research has begun to address dynamic environments and tackle the Catastrophic Forgetting problem through Continual Learning (CL) techniques. Previous studies have

Claus Fieker, Tommy Hofmann

We give a brief introduction to computational algebraic number theory in OSCAR. Our main focus is on number fields, rings of integers and their invariants. After recalling some classical results and their constructive counterparts, we showcase the functionality in two examples related to the investigation of the Cohen-Lenstra heuristic for quadratic fields a

Pierre-Cyril Aubin-Frankowski, Stéphane Gaubert

There have been many parallel streams of research studying order isomorphisms of some specific sets $G$ of functions from a set $X$ to $\mathbb{R}\cup\{\pm\infty\}$, such as the sets of convex or Lipschitz functions. We develop in this article a unified approach inspired by $c$-convex functions. Our results are obtained highlighting the role of inf and sup-i

Mohamadreza Rostami, Marco Chilese, Shaza Zeitouni, Rahul Kande

Modern computing systems heavily rely on hardware as the root of trust. However, their increasing complexity has given rise to security-critical vulnerabilities that cross-layer at-tacks can exploit. Traditional hardware vulnerability detection methods, such as random regression and formal verification, have limitations. Random regression, while scalable, is

Cung The Anh, Phan Duc An, Pham Trieu Duong

In this paper, we study the Cauchy problem to the linear damped $\sigma$-evolution equation with time-dependent damping in the effective cases \begin{equation*} u_{t t}+(-\Delta)^\sigma u+b(t)(-\Delta)^\delta u_t=0, \end{equation*} and investigate the decay rates of the solution and its derivatives that are expressed in terms of the decay character of the in

Jinghong Chen, Weizhe Lin, Jingbiao Mei, Bill Byrne

The Directed Acyclic Transformer is a fast non-autoregressive (NAR) model that performs well in Neural Machine Translation. Two issues prevent its application to general Natural Language Generation (NLG) tasks: frequent Out-Of-Vocabulary (OOV) errors and the inability to faithfully generate entity names. We introduce Control-DAG, a constrained decoding algor

Wei Liu, Yuxiao Li, Chunxia Yao, Dongsheng Zhang

Laser metal additive manufacturing technology is capable of producing components with complex geometries and compositions that cannot be realized by conventional manufacturing methods. However, a large number of pores generated during the additive manufacturing process greatly affect the mechanical properties of the additively manufactured parts, and the mec

Mugeng Liu, Xiaolong Huang, Wei He, Yibing Xie

The Software Engineering (SE) community has been embracing the open science policy and encouraging researchers to disclose artifacts in their publications. However, the status and trends of artifact practice and quality remain unclear, lacking insights on further improvement. In this paper, we present an empirical study to characterize the research artifacts

Junsheng Zhou, Weiqi Zhang, Baorui Ma, Kanle Shi

Diffusion models have shown remarkable results for image generation, editing and inpainting. Recent works explore diffusion models for 3D shape generation with neural implicit functions, i.e., signed distance function and occupancy function. However, they are limited to shapes with closed surfaces, which prevents them from generating diverse 3D real-world co

Nico Föge, Markus Pauly, Lena Schmid, Marc Ditzhaus

The last decade has shed some light on theoretical properties such as their consistency for regression tasks. In the current paper, we propose a new class of very simple learners based on so-called naive trees. These naive trees partition the feature space completely at random and independent of the data. Although counter-intuitive, we prove these naive tree

Terry Lyons, Andrew D. McLeod

We investigate the consequence of two Lip$(\gamma)$ functions, in the sense of Stein, being close throughout a subset of their domain. A particular consequence of our results is the following. Given $K_0 > \varepsilon > 0$ and $\gamma > \eta > 0$ there is a constant $\delta = \delta(\gamma,\eta,\varepsilon,K_0) > 0$ for which the following is true. Let $\Sig

J. Karls, M. Björkhage, M. Blom, N. D. Gibson

Radiative lifetimes of three elements of the nitrogen group have been experimentally investigated at the Double ElectroStatic Ion Ring Experiment (DESIREE) facility at Stockholm University. The experiments were performed through selective laser photodetachment of excited states of P$^-$, As$^-$ and Sb$^-$ ions stored in a cryogenic storage ring. The experime

Marcel Nutz

The optimal transport problem with quadratic regularization is useful when sparse couplings are desired. The density of the optimal coupling is described by two functions called potentials; equivalently, potentials can be defined as a solution of the dual problem. We prove the existence of potentials for a general square-integrable cost. Potentials are not n

Daniel Biebert, Christian Hakert, Kuan-Hsun Chen, Jian-Jia Chen

Bringing high-level machine learning models to efficient and well-suited machine implementations often invokes a bunch of tools, e.g.~code generators, compilers, and optimizers. Along such tool chains, abstractions have to be applied. This leads to not optimally used CPU registers. This is a shortcoming, especially in resource constrained embedded setups. In

Zhangliang Chen, Yizhi Chen, Chen Chen, Hongwei Ge

Brown dwarfs (BDs) possessing masses within the range $40-60 M_{\rm Jup}$ are rare around solar-type main-sequence (MS) stars, which gives rise to the brown dwarf desert (BDD). One caveat associated with previous studies of BDD is the relatively limited sample size of MS$-$BD binaries with accurately determined BD masses. We aim to produce a large sample of

Damián Gvirtz-Chen, Giacomo Mezzedimi

We prove that elliptic K3 surfaces over a number field which admit a second elliptic fibration satisfy the potential Hilbert property. Equivalently, the set of their rational points is not thin after a finite extension of the base field. Furthermore, we classify those families of elliptic K3 surfaces over an algebraically closed field which do not admit a se

Yanting Zhang, Ligong Wang

Let $H_7$ denote the $7$-vertex \textit{fan graph} consisting of a $6$-vertex path plus a vertex adjacent to each vertex of the path. Let $K_3 \vee \frac{m-3}{3}K_1$ be the graph obtained by joining each vertex of a triangle $K_3$ to $\frac{m-3}{3}$ isolated vertices. In this paper, we show that if $G$ is an $H_{7}$-free graph with size $m\geq 33$, then the

Ziyang Chen, Wei Long, He Yao, Yongjun Zhang

Learning-based stereo matching techniques have made significant progress. However, existing methods inevitably lose geometrical structure information during the feature channel generation process, resulting in edge detail mismatches. In this paper, the Motif Cha}nnel Attention Stereo Matching Network (MoCha-Stereo) is designed to address this problem. We pro

Kai Jiang, Meng Li, Juan Zhang, Lei Zhang

In this study, we address the challenge of solving elliptic equations with quasiperiodic coefficients. To achieve accurate and efficient computation, we introduce the projection method, which enables the embedding of quasiperiodic systems into higher-dimensional periodic systems. To enhance the computational efficiency, we propose a compressed storage strate

Joachim Cuntz, James Gabe

We develop the approach via quasihomomorphisms and the universal algebra $qA$ to Kasparov's $KK$-theory, so as to cover versions of $KK$ such as $KK^{nuc}$, $KK^G$ and ideal related $KK$-theory.

Hendrik De Bie, Ze Yang

In this paper we consider the kernel of the radially deformed Fourier transform introduced in the context of Clifford analysis in [10]. By adapting the Laplace transform method from [4], we obtain the Laplace domain expressions of the kernel for the cases of $m=2$ and $m > 2$ when $1+c=\frac{1}{n}, n\in \mathbb{N}_0\backslash\{1\}$ with $n$ odd. Moreover, we

Ehsan Sadeghi, Abel van Raalte, Alessandro Chiumento, Paul Havinga

Recognizing animal activities holds a crucial role in monitoring animals' health and well-being. Additionally, a considerable audience is keen on monitoring their pets' well-being and health status. Insight into animals' habitual activities and patterns not only aids veterinarians in accurate diagnoses but also offers pet owners early alerts. Traditional met

Miriam Anschütz, Edoardo Mosca, Georg Groh

Text simplification seeks to improve readability while retaining the original content and meaning. Our study investigates whether pre-trained classifiers also maintain such coherence by comparing their predictions on both original and simplified inputs. We conduct experiments using 11 pre-trained models, including BERT and OpenAI's GPT 3.5, across six datase

Taojun Hu, Yi Zhou, Satoshi Hattori

Meta-analysis is a powerful tool to synthesize findings from multiple studies. The normal-normal random-effects model is widely used to account for between-study heterogeneity. However, meta-analysis of sparse data, which may arise when the event rate is low for binary or count outcomes, poses a challenge to the normal-normal random-effects model in the accu

Muer Tie, Julong Wei, Zhengjun Wang, Ke Wu

Online construction of open-ended language scenes is crucial for robotic applications, where open-vocabulary interactive scene understanding is required. Recently, neural implicit representation has provided a promising direction for online interactive mapping. However, implementing open-vocabulary scene understanding capability into online neural implicit m

Yanqi Ge, Jiaqi Liu, Qingnan Fan, Xi Jiang

In this work, we target the task of text-driven style transfer in the context of text-to-image (T2I) diffusion models. The main challenge is consistent structure preservation while enabling effective style transfer effects. The past approaches in this field directly concatenate the content and style prompts for a prompt-level style injection, leading to unav

Guanhang Lei, Zhen Lei, Lei Shi, Chenyu Zeng

In this paper, we consider approximating the parameter-to-solution maps of parametric partial differential equations (PPDEs) using deep neural networks (DNNs). We propose an efficient approach combining reduced collocation methods (RCMs) and DNNs. In the approximation analysis section, we rigorously derive sharp upper bounds on the complexity of the neural n

Li Zhou, Taelin Karidi, Wanlong Liu, Nicolas Garneau

Recent studies have highlighted the presence of cultural biases in Large Language Models (LLMs), yet often lack a robust methodology to dissect these phenomena comprehensively. Our work aims to bridge this gap by delving into the Food domain, a universally relevant yet culturally diverse aspect of human life. We introduce FmLAMA, a multilingual dataset cente

Mathis Kruse, Marco Rudolph, Dominik Woiwode, Bodo Rosenhahn

Detecting anomalies in images has become a well-explored problem in both academia and industry. State-of-the-art algorithms are able to detect defects in increasingly difficult settings and data modalities. However, most current methods are not suited to address 3D objects captured from differing poses. While solutions using Neural Radiance Fields (NeRFs) ha

Ayush Sawarni, Nirjhar Das, Siddharth Barman, Gaurav Sinha

We study the generalized linear contextual bandit problem within the constraints of limited adaptivity. In this paper, we present two algorithms, $\texttt{B-GLinCB}$ and $\texttt{RS-GLinCB}$, that address, respectively, two prevalent limited adaptivity settings. Given a budget $M$ on the number of policy updates, in the first setting, the algorithm needs to

Silvio Mandelli, Lorenzo Maggi, Bill Zheng, Christophe Grangeat

International standards bodies define Electromagnetic field (EMF) emission requirements that can be translated into control of the base station actual Effective Isotropic Radiated Power (EIRP), i.e., averaged over a sliding time window. In this work we show how to comply with such requirements by designing a water-filling power allocation method operating at

ATLAS Collaboration

A summary of precision measurements sensitive to electroweak, QCD and quark-flavour effects performed by the ATLAS Collaboration at the Large Hadron Collider is reported. The measurements are predominantly performed on proton$-$proton ($pp$) collision data recorded at a centre-of-mass energy of 13 TeV taken from 2015 to 2018, with an integrated luminosity of

Yusuke Miyajima, Masahito Mochizuki

A single-celled amoeba can solve the traveling salesman problem through its shape-changing dynamics. In this paper, we examine roles of several elements in a previously proposed computational model of the solution-search process of amoeba and three modifications towards enhancing the solution-search preformance. We find that appropriate modifications can ind

Bihui Jin, Heng Li, Ying Zou

Web browsers have been used widely by users to conduct various online activities, such as information seeking or online shopping. To improve user experience and extend the functionality of browsers, practitioners provide mechanisms to allow users to install third-party-provided plugins (i.e., extensions) on their browsers. However, little is known about the

Rainer Buckdahn, Juan Li, Yanwei Li, Yi Wang

Our paper is devoted to the study of Peng's stochastic maximum principle (SMP) for a stochastic control problem composed of a controlled forward stochastic differential equation (SDE) as dynamics and a controlled backward SDE which defines the cost functional. Our studies combine the difficulties which come, on one hand, from the fact that the coefficients o

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel, Johanna Barzen

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -key qualities of any industry-grade software-mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differ

Phuong Bich Duong, Ben Van Herbruggen, Arne Broering, Adnan Shahid

Indoor positioning systems based on Ultra-wideband (UWB) technology are gaining recognition for their ability to provide cm-level localization accuracy. However, these systems often encounter challenges caused by dense multi-path fading, leading to positioning errors. To address this issue, in this letter, we propose a novel methodology for unsupervised anch

J. Tong, Y. Fu, D. Domaretskiy, F. Della Pia

The basal plane of graphene can function as a selective barrier that is permeable to protons but impermeable to all ions and gases, stimulating its use in applications such as membranes, catalysis and isotope separation. Protons can chemically adsorb on graphene and hydrogenate it, inducing a conductor-insulator transition that has been explored intensively

Arevik V. Asatryan, Albert S. Benight, Artem V. Badasyan

With the help of one-dimensional random Potts-like model we study the origins of fine structure observed on differential melting profiles of double-stranded DNA. We assess the effects of sequence arrangement on DNA melting curves through the comparison of results for random, correlated, and block sequences. Our results re-confirm the smearing out the fine st

Chun Liu, Guanghui Hu, Jianli Xiang, Jiayi Zhang

This paper is concerned with inverse scattering problems of determining the support of an isotropic and homogeneous penetrable body from knowledge of multi-static far-field patterns in acoustics and in linear elasticity. The normal derivative of the total fields admits no jump on the interface of the scatterer in the trace sense. If the contrast function of

Florian Gnadlinger, Simone Kriglstein

This contribution draws attention to implications connected with meta-architectural design decisions for intelligent tutoring systems in the context of formative assessments. As a first result of addressing this issue, this contribution presents a meta-architectural system design that includes the role of educators.

Hui Li, Jingwen Shi, Qi Tian, Zheng Li

As cloud computing gains traction, data owners are outsourcing their data to cloud service providers (CSPs) for Database Service (DBaaS), bringing in a deviation of data ownership and usage, and intensifying privacy concerns, especially with potential breaches by hackers or CSP insiders. To address that, encrypted database services propose encrypting every t

Nicolas Raoux, Abdelkibir Benelfellah, Nourredine Aït Hocine

Polymers are increasingly used in the transport sector due to their many advantages; lightness, corrosion resistance, ease to process... However, most of them have limited mechanical properties. To improve these latter, one of the solutions is the addition of nano-reinforcements, this type of material is called nanocomposite. The particularity of these nanoc

Taegyun Kwon, Dasaem Jeong, Juhan Nam

In recent years, advancements in neural network designs and the availability of large-scale labeled datasets have led to significant improvements in the accuracy of piano transcription models. However, most previous work focused on high-performance offline transcription, neglecting deliberate consideration of model size. The goal of this work is to implement

Dimitrios Stefas, Konstantinos Giotis, Laurent Invernizzi, Hans Höft

The present study explores combining machine learning (ML) algorithms with standard optical diagnostics (such as time-integrated emission spectroscopy and imaging) to accurately predict operating conditions and assess the emission uniformity of a cylindrical surface Dielectric Barrier Discharge (SDBD). It is demonstrated that ML can be complementary with the

Rémi Carles, Fangyuan Dong

We consider the fractional Schrodinger equation with a logarithmic nonlinearity, when the power of the Laplacian is between zero and one. We prove global existence results in three different functional spaces: the Sobolev space corresponding to the quadratic form domain of the fractional Laplacian, the energy space, and a space contained in the operator doma

Zhenyu Wang, Ju-Jia Zhang, Xinzhong Er, Jinming Bai

The Multi-channel Photometric Survey Telescope (Mephisto) is a real-time, three-color photometric system designed to capture the color evolution of stars and transients accurately. This telescope system can be crucial in cosmological distance measurements of low-redshift (low-$z$, $z$ $\lesssim 0.1$) Type Ia supernovae (SNe Ia). To optimize the capabilities

Étienne Burle, Hervé Talé Kalachi, Freddy Lende Metouke, Ayoub Otmani

The LG cryptosystem is a public-key encryption scheme in the rank metric using the recent family of $\lambdav-$Gabidulin codes and introduced in 2019 by Lau and Tan. In this paper, we present a cryptanalysis showing that the security of several parameters of the scheme have been overestimated. We also show the existence of some weak keys allowing an attacker

Tianxin Huang, Zhiwen Yan, Yuyang Zhao, Gim Hee Lee

3D point clouds directly collected from objects through sensors are often incomplete due to self-occlusion. Conventional methods for completing these partial point clouds rely on manually organized training sets and are usually limited to object categories seen during training. In this work, we propose a test-time framework for completing partial point cloud

Kiet Tuan Hoang, Brage Rugstad Knudsen, Lars Struen Imsland

Controlling gas turbines (GTs) efficiently is vital as GTs are used to balance power in onshore/offshore hybrid power systems with variable renewable energy and energy storage. However, predictive control of GTs is non-trivial when formulated as a dynamic optimisation problem due to the semi-continuous operating regions of GTs, which must be included to ensu

Mingrui Fu, Weijiang Li

The purpose of emotion-cause pair extraction is to extract the pair of emotion clauses and cause clauses. On the one hand, the existing methods do not take fully into account the relationship between the emotion extraction of two auxiliary tasks. On the other hand, the existing two-stage model has the problem of error propagation. In addition, existing model

Pascal Bégout, Jesús Ildefonso Díaz

We consider the damped nonlinear Schr\''{o}dinger equation with saturation: i.e., the complex evolution equation contains in its left hand side, besides the potential term $V(x)u,$ a nonlinear term of the form $\mathrm{i}\mu u(t,x)/|u(t,x)|$ for a given parameter $\mu >0$ (arising in optical applications on non-Kerr-like fibers). In the right hand side we as

Keng Hao Ooi

We develop a theory of capacities associated with local Muckenhoupt weights. Fundamental properties of local Muckenhoupt weights will be revisited. Weak type boundedness of nonlinear potential and capacitary strong type inequalities associated with such weights will be addressed. The boundedness of the local maximal function on the spaces of Choquet integral

Ruotong Pan, Boxi Cao, Hongyu Lin, Xianpei Han

The rapid development of large language models has led to the widespread adoption of Retrieval-Augmented Generation (RAG), which integrates external knowledge to alleviate knowledge bottlenecks and mitigate hallucinations. However, the existing RAG paradigm inevitably suffers from the impact of flawed information introduced during the retrieval phrase, there

Somnath Maity, Premananda Panigrahi

The centrality measure (CM) is one of the most fundamental metrics for evaluating the efficiency and vulnerability analysis of complex power grids (CPGs). Despite an abundance of different CMs for individual nodes, there are only a few metrics available in the literature to measure the centrality of individual lines. We propose here the current-flow (CF) lin

Taeuk Jeong, Yoon Mo Jung, Euntack Lee

Dimensionality reduction represents the process of generating a low dimensional representation of high dimensional data. Motivated by the formation control of mobile agents, we propose a nonlinear dynamical system for dimensionality reduction. The system consists of two parts; the control of neighbor points, addressing local structures, and the control of re

Subham Agrawal, Marlene Wessels, Jorge de Heuvel, Johannes Kraus

Mobile robots are increasingly being used in noisy environments for social purposes, e.g. to provide support in healthcare or public spaces. Since these robots also operate beyond human sight, the question arises as to how different robot types, ambient noise or cognitive engagement impacts the detection of the robots by their sound. To address this research

Mingyao Cui, Zijian Zhang, Linglong Dai, Kaibin Huang

By deploying a large number of antennas with sub-half-wavelength spacing in a compact space, dense array systems (DASs) can fully unleash the multiplexing and diversity gains of limited apertures. To acquire these gains, accurate channel state information acquisition is necessary but challenging due to the large antenna numbers. To overcome this obstacle, th

Brendon Mizener, Mathilde Vandenberghe-Descamps, Hervé Abdi, Sylvie Chollet

French and American participants listened to new music stimuli and evaluated the stimuli using either adjectives or quantitative musical dimensions. Results were analyzed using correspondence analysis (CA), hierarchical cluster analysis (HCA), multiple factor analysis (MFA), and partial least squares correlation (PLSC). French and American listeners differed

Sam Sanders

Continuous functions on the unit interval are relatively tame from the logical and computational point of view. A similar behaviour is exhibited by continuous functions on compact metric spaces equipped with a countable dense subset. It is then a natural question what happens if we omit the latter 'extra data', i.e. work with 'unrepresented' compact metric s

Mounir Hayani

In this paper we produce unconditionally new instances of Galois number field extensions exhibiting strong discrepancies in the distribution of Frobenius elements among conjugacy classes of the Galois group. We first prove an inverse Galois theoretic statement showing a dichotomy between ``extreme Chebyshev biases'' and ``equal prime ideal counting''. We fur

Mickaël Delcey, Yoann Cheny, Jean-Baptiste Keck, Adrien Gans

Physics-Informed Neural Networks (PINNs) have shown great potential in the context of fluid dynamics simulations, particularly in reconstructing flow fields and identifying key parameters. In this study, we explore the application of PINNs to recover the dimensionless settling velocity for sedimentation flow. The flow involves sediment-laden fresh water over

Yuehao Wang, Bingchen Gong, Yonghao Long, Siu Hin Fan

The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are able to conduct surgical planning and surgery training on scenarios close to real-world cases. However, a significant challenge in achieving such a goal is the scarcity of high-qual

Xi Chen, Julien Cumin, Fano Ramparany, Dominique Vaufreydaz

This paper presents two models to address the problem of multi-person activity recognition using ambient sensors in a home. The first model, Seq2Res, uses a sequence generation approach to separate sensor events from different residents. The second model, BiGRU+Q2L, uses a Query2Label multi-label classifier to predict multiple activities simultaneously. Perf

Elie Allouche

This article proposes the construction of a systemic model of digital education as part of research applied to public policy (French Ministry of Education). Considering the digital domain in its pervasiveness, it highlights the importance of a complex approach to understanding the transformation of practices. As an applied research modality, we present digit

Paolo Novati, Fulvio Tagliaferro, Marino Zennaro

Recently Ahmadi et al. (2021) and Tagliaferro (2022) proposed some iterative methods for the numerical solution of linear systems which, under the classical hypothesis of strict diagonal dominance, typically converge faster than the Jacobi method, but slower than the forward/backward Gauss-Seidel one. In this paper we introduce a general class of iterative m

Maurice Pfeiffer, Xinyan Wu, Fatemeh Ebrahimi, Nadiia Mameka

Chemical interface damping is a change in the effective collision frequency of conduction band electrons in metal originating from a chemical change of the metal interface. In this work, we present in-situ ellipsometric measurements that reveal the chemical interface damping effect from electrochemical oxidation of single crystal and polycrystalline gold fil

Ke Zou, Yang Bai, Bo Liu, Yidi Chen

Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current methods rely on manual extraction of key phrases from medical reports, reducing efficiency and increasing the workload for clinicians. Additionally, the lack of model confidence e

Soheil Behnezhad, Moses Charikar, Vincent Cohen-Addad, Alma Ghafari

We study the classic correlation clustering in the dynamic setting. Given $n$ objects and a complete labeling of the object-pairs as either similar or dissimilar, the goal is to partition the objects into arbitrarily many clusters while minimizing disagreements with the labels. In the dynamic setting, an update consists of a flip of a label of an edge. In a

Deng Wang

The DESI year one observations can help probe new physics on cosmological scales. In light of the latest DESI BAO measurements, we constrain five popular cosmological scenarios including inflation, modified gravity, annihilating dark matter and interacting dark energy. Using a data combination of BICEP/Keck array, cosmic microwave background and DESI, we obt

Zhuo Li, He Zhao, Zhen Li, Tongliang Liu

Real-world datasets usually are class-imbalanced and corrupted by label noise. To solve the joint issue of long-tailed distribution and label noise, most previous works usually aim to design a noise detector to distinguish the noisy and clean samples. Despite their effectiveness, they may be limited in handling the joint issue effectively in a unified way. I

Barbara Perri, Adam Finley, Victor Réville, Susanna Parenti

Solar Orbiter provides unique capabilities to understand the heliosphere. In particular, it has made observations of the far-side of the Sun and provides unique information to improve space weather monitoring. We aim to quantify how far-side data will affect simulations of the corona and the interplanetary medium, especially in the context of space weather f

Ayuki Kamada, Takumi Kuwahara, Shigeki Matsumoto, Yu Watanabe

The decay of the mediator particle into standard model (SM) particles plays a significant role in exploring the dark sector scenario. We consider such a decay, taking the dark photon mediator as an example that mixes with the SM photon. We find that it requires a careful analysis of the decay rate in the presence of an SM vector boson (e.g., $Z$ boson, $\rho

Bjørn Leth Møller, Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen

Ulcerative Colitis (UC) is a chronic inflammatory bowel disease decreasing life quality through symptoms such as bloody diarrhoea and abdominal pain. Endoscopy is a cornerstone of diagnosis and monitoring of UC. The Mayo endoscopic subscore (MES) index is the standard for measuring UC severity during endoscopic evaluation. However, the MES is subject to high

Tomasz Rybotycki, Tomasz Białecki, Josep Batle, Jakub Tworzydło

We demonstrate a determinant dimension witness of a qubit space. Our test has a minimal number of independent parameters. We achieve it by mapping the Bloch sphere $\pi/2$-rotation axis angle on the non-planar so-called Viviani curve. We ran our test on different platforms: IBM Quantum, IQM Resonance, and IonQ. Our investigations show that numerous qubits, e

Heming Bai, Zhicheng Wang, Xuesen Chu, Jian Deng

Time-dependent flow fields are typically generated by a computational fluid dynamics (CFD) method, which is an extremely time-consuming process. However, the latent relationship between the flow fields is governed by the Navier-Stokes equations and can be described by an operator. We therefore train a deep operator network, or simply DeepONet, to learn the t

Florian Ludwig, Jakob Holstein, Anastasiya Krysl, Alvydas Lisauskas

We report on the modeling and experimental characterization of Si CMOS detectors of terahertz radiation based on antenna-coupled field-effect transistors (TeraFETs). The detectors are manufactured using TSMC's 65-nm technology. We apply two models -- the TSMC RF foundry model and our own ADS-HDM -- to simulate the Si CMOS TeraFET performance and compare thei