November 2024 arXiv papers — page 30

Muhammad Maikudi Isah, Lorenzo Sorace, Alessandro Lascialfari, Paolo Arosio

We report on the spin dynamics of two Terbium-based molecular nanomagnets, Tb-SQ and Tb-Trp, investigated by means of longitudinal muon spin relaxation ($\mu$SR) measurements as a function of applied field, flanked by AC susceptibility characterization. In the two molecules Tb(III) magnetic ion has an isotructural coordination sphere, but in the former the T

Andreas Groll, Akshat Khanna, Leonid Zeldin

Life insurance, like other forms of insurance, relies heavily on large volumes of data. The business model is based on an exchange where companies receive payments in return for the promise to provide coverage in case of an accident. Thus, trust in the integrity of the data stored in databases is crucial. One method to ensure data reliability is the automati

Jaewoo Jung, Hyunsuk Moon, Euisung Park

In this article, we investigate the rank index of projective curves $\mathscr{C} \subset \mathbb{P}^r$ of degree $r+1$ when $\mathscr{C} = \pi_p (\tilde{\mathscr{C}})$ for the standard rational normal curve $\tilde{\mathscr{C}} \subset \mathbb{P}^{r+1}$ and a point $p \in \mathbb{P}^{r+1} \setminus \tilde{\mathscr{C}}^3$. Here, the rank index of a closed sub

Emanuele Aiello, Umberto Michieli, Diego Valsesia, Mete Ozay

Personalized image generation requires text-to-image generative models that capture the core features of a reference subject to allow for controlled generation across different contexts. Existing methods face challenges due to complex training requirements, high inference costs, limited flexibility, or a combination of these issues. In this paper, we introdu

Yuxuan Sheng, Junwei Liu, Jia Zhang, Menghao Wu

According to the recent studies on sliding/moire ferroelectricity, most 2D van der Waals nonferroelectric monolayers can become ferroelectric via multilayer stacking. In this paper we propose that similar strategy can be used to induce desirable van der Waals altermagnetism with symmetry-compensated collinear magnetic orders and non-relativistic spin splitti

Takayoshi Sano, Shogo Isayama, Kenta Takahashi, Shuichi Matsukiyo

The interaction between a thin foil target and a circularly polarized laser light injected along an external magnetic field is investigated numerically by particle-in-cell simulations. A standing wave appears at the front surface of the target, overlapping the injected and partially reflected waves. Hot electrons are efficiently generated at the standing wav

Omri Kaduri, Shai Bagon, Tali Dekel

Vision-Language Models (VLMs) have recently demonstrated remarkable capabilities in comprehending complex visual content. However, the mechanisms underlying how VLMs process visual information remain largely unexplored. In this paper, we conduct a thorough empirical analysis, focusing on attention modules across layers. We reveal several key insights about h

Ziwei Wang, Sameera Ramasinghe, Chenchen Xu, Julien Monteil

Structuring latent representations in a hierarchical manner enables models to learn patterns at multiple levels of abstraction. However, most prevalent image understanding models focus on visual similarity, and learning visual hierarchies is relatively unexplored. In this work, for the first time, we introduce a learning paradigm that can encode user-defined

Nicolai Hermann, Jorge Condor, Piotr Didyk

Modern reconstruction techniques can effectively model complex 3D scenes from sparse 2D views. However, automatically assessing the quality of novel views and identifying artifacts is challenging due to the lack of ground truth images and the limitations of no-reference image metrics in predicting reliable artifact maps. The absence of such metrics hinders a

Jiaxu Zheng, Zhenrong Shen, Lichi Zhang, Qun Chen

Deep-learning-based MR-to-CT synthesis can estimate the electron density of tissues, thereby facilitating PET attenuation correction in whole-body PET/MR imaging. However, whole-body MR-to-CT synthesis faces several challenges including the issue of spatial misalignment and the complexity of intensity mapping, primarily due to the variety of tissues and orga

Erik Insko, Martha Precup, Alexander Woo

This paper investigates the geometry of regular Hessenberg varieties associated with the minimal indecomposable Hessenberg space in the flag variety of a complex reductive group. These varieties form a flat family of irreducible subvarieties of the flag variety, encompassing notable examples such as the Peterson variety and toric varieties linked to Weyl cha

Yong-Yeon Jo, Byeong Tak Lee, Beom Joon Kim, Jeong-Ho Hong

Online Test-Time Adaptation (OTTA) enhances model robustness by updating pre-trained models with unlabeled data during testing. In healthcare, OTTA is vital for real-time tasks like predicting blood pressure from biosignals, which demand continuous adaptation. We introduce a new test-time scenario with streams of unlabeled samples and occasional labeled samp

Adrien Ragot, Thomas Seiller, Lorenzo Tortora de Falco

We provide a new realisability model based on orthogonality for the multiplicative fragment of linear logic, both in presence of generalised axioms (MLL*) and in the standard case (MLL). The novelty is the definition of cut elimination for generalised axioms. We prove that our model is adequate and complete both for MLL* and MLL.

William F. Podlaski, Christian K. Machens

Associative memory architectures such as the Hopfield network have long been important conceptual and theoretical models for neuroscience and artificial intelligence. However, translating these abstract models into spiking neural networks has been surprisingly difficult. Indeed, much previous work has been restricted to storing a small number of primarily no

Maaike B. Elgersma, Germán Morales-España, Karen I. Aardal, Niina Helistö

Fast and accurate large-scale energy system models are needed to investigate the potential of storage to complement the fluctuating energy production of renewable energy systems. However, standard Mixed-Integer Programming (MIP) models that describe optimal investment and operation of these storage units, including the optional capacity to provide up/down re

Patrick Schäfer, Jakob Brand, Ulf Leser, Botao Peng

Similarity search is a fundamental operation for analyzing data series (DS), which are ordered sequences of real values. To enhance efficiency, summarization techniques are employed that reduce the dimensionality of DS. SAX-based approaches are the state-of-the-art for exact similarity queries, but their performance degrades for high-frequency signals, such

Y. C. Wang, Y. Sun, Z. J. Ding

The multisilce method is an important algorithm for electron diffraction and image simulations in transmission electron microscopy. We have proposed a quantum algorithm of the multislice method based on quantum circuit model previously. In this work we have developed an improved quantum algorithm. We reconstruct the phase-shifting quantum circuit without usi

Mengzhao Wang, Huafeng Li, Yafei Zhang, Jinxing Li

Video Paragraph Grounding (VPG) aims to precisely locate the most appropriate moments within a video that are relevant to a given textual paragraph query. However, existing methods typically rely on large-scale annotated temporal labels and assume that the correspondence between videos and paragraphs is known. This is impractical in real-world applications,

Chenlei Li, Jianghao He, Ming Zhang, Yeyu Tong

Electro-optic modulators for next-generation optical interconnects require low loss-efficiency products, compact footprints, high modulation efficiency, broad bandwidths, and low losses. Here we propose and demonstrate a low-loss high-efficiency thin-film lithium-niobate Mach Zehnder modulator enabled by a novel ultralow-loss slow-light structure based on ap

Joseph R. Guerci, Sandeep Gogineni, Robert W. Schutz, Gavin I. McGee

Modern AI (i.e., Deep Learning and its variants) is here to stay. However, its enigmatic black box nature presents a fundamental challenge to the traditional methods of test and validation (T&E). Or does it? In this paper we introduce a Digital Engineering (DE) approach to T&E (DE-T&E), combined with generative AI, that can achieve requisite mil spec statist

David Van Assche, Thomas Beneyton, Alexandre Baron, Jean-Christophe Baret

The mechanism of coalescence of aqueous droplet pairs under an electric field is quantitatively studied using microfluidics in quiescent conditions. We experimentally trap droplet pairs and apply electric fields with varying frequencies and formulation compositions. We find that the electrical resistance of the oil used as continuous phase controls the onset

Marco Matteini

I present a recap of a fully analytical calculation of the Euclidean action for a self-interacting scalar field with a quartic potential, in the thin-wall approximation. I then apply this result to the coupled fluid-scalar field model, a phenomenologically relevant model for cosmological first order phase transitions, and compare results with numerical simul

Albane Théry, Andres Zambrano, Eric Lauga, Roberto Zenit

Motivated by the aim of understanding the effect of media heterogeneity on the swimming dynamics of flagellated bacteria, we study the rotation and swimming of rigid helices in dilute suspensions experimentally and theoretically. We first measure the torque experienced by, and thrust force generated by, helices rotating without translating in suspensions of

Xiaowen Ma, Zhenliang Ni, Xinghao Chen

Mamba has shown great potential for computer vision due to its linear complexity in modeling the global context with respect to the input length. However, existing lightweight Mamba-based backbones cannot demonstrate performance that matches Convolution or Transformer-based methods. By observing, we find that simply modifying the scanning path in the image d

Rose Berry

For a $p$-adic field $F$ of residual cardinality $q$, we provide a triangulated equivalence between the bounded derived category $D^b(\mathcal{B}_{1}(G)_{fg})$ of finitely generated unipotent representations of $G=\mathrm{GL}_2(F)$ and perfect complexes over a dg enriched Schur algebra, in the non-banal case of odd characteristic $l$ dividing $q+1$. The dg S

Fatemeh Nourilenjan Nokabadi, Jean-Francois Lalonde, Christian Gagné

Adversarial perturbations aim to deceive neural networks into predicting inaccurate results. For visual object trackers, adversarial attacks have been developed to generate perturbations by manipulating the outputs. However, transformer trackers predict a specific bounding box instead of an object candidate list, which limits the applicability of many existi

Xiaodong Shen, Jiajun Cao, Weizheng Liang, Borong Cong

2D magnetic semiconductor CrSBr exhibits unique magneto-optical properties, yet its electronic structure and photophysical mechanisms remain unclear at high magnetic field and low temperature. Through comprehensive spectroscopic investigations, its charge-transfer band edge is identified at 500 nm. Below this band-edge, local excitonic magnetic polaronic sta

Kevin Qinghong Lin, Linjie Li, Difei Gao, Zhengyuan Yang

Building Graphical User Interface (GUI) assistants holds significant promise for enhancing human workflow productivity. While most agents are language-based, relying on closed-source API with text-rich meta-information (e.g., HTML or accessibility tree), they show limitations in perceiving UI visuals as humans do, highlighting the need for GUI visual agents.

Arís Fanjul-Hevia, Juan Carlos Pardo-Fernández, Wenceslao González-Manteiga

The ROC curve is a statistical tool that analyses the accuracy of a diagnostic test in which a variable is used to decide whether an individual is healthy or not. Along with that diagnostic variable it is usual to have information of some other covariates. In some situations it is advisable to incorporate that information into the study, as the performance o

Eléa Prat, Richard M. Lusby, Juan Miguel Morales, Salvador Pineda

Energy storage scheduling problems, where a storage is operated to maximize its profit in response to a price signal, are essentially infinite-horizon optimization problems as storage systems operate continuously, without a foreseen end to their operation. Such problems can be solved to optimality with a rolling-horizon approach, provided that the planning h

Shuang Zhang, Serdar Elhatisari, Ulf-G. Meißner, Shihang Shen

The proton-rich nucleus $^{22}$Si is studied using Nuclear Lattice Effective Field Theory with high-fidelity chiral forces. Our results indicate that $^{22}$Si is more tightly bound than $^{20}$Mg, thereby excluding the possibility of two-proton emission. The $Z = 14$ shell closure in $^{22}$Si is supported by the evolution of the $2^+$ state in the neighbor

Elizabeth Lui, Rui Sun, Vatsal Shah, Xihan Xiong

Centralization enhances the efficiency of Artificial Intelligence (AI) but also introduces critical challenges, including single points of failure, inherent biases, data privacy risks, and scalability limitations. To address these issues, blockchain-based Decentralized Artificial Intelligence (DeAI) has emerged as a promising paradigm that leverages decentra

O. O. Oyadare

The JEFT is the acronym for the Joint-Eigenspace Fourier Transform defined on a noncompact symmetric space. It is a consequence of a general construction of a Fourier transform modelled on the Harish-Chandra Fourier transform (on a semi-simple Lie group with finite centre) which (on the corresponding symmetric space of the noncompact type) serves as the Pois

Pavel Buividovich, Johann Ostmeyer, Alessandro Troisi

We use first-principle Quantum Monte-Carlo (QMC) simulations and numerical exact diagonalization to analyze the low-frequency charge carrier mobility within a simple tight-binding model of molecular organic semiconductors on a two-dimensional triangular lattice. These compounds feature transient localization, an unusual charge transport mechanism driven by d

Zongjian Li, Bin Lin, Yang Ye, Liuhan Chen

Video Variational Autoencoder (VAE) encodes videos into a low-dimensional latent space, becoming a key component of most Latent Video Diffusion Models (LVDMs) to reduce model training costs. However, as the resolution and duration of generated videos increase, the encoding cost of Video VAEs becomes a limiting bottleneck in training LVDMs. Moreover, the bloc

Travis Davies, Jiahuan Yan, Xiang Chen, Yu Tian

Recent advances in imitation learning have shown significant promise for robotic control and embodied intelligence. However, achieving robust generalization across diverse mounted camera observations remains a critical challenge. In this paper, we introduce a video-based spatial perception framework that leverages 3D spatial representations to address enviro

C. G. Feyisa, Cheng-Yu Liu, Muhammad S. Hasan, J. S. You

Non-Hermitian quantum systems have attracted significant interest in recent years due to the presence of unique spectral singularities known as exceptional points (EPs), where eigenvalues and eigenvectors coalesce. The drastic changes in these systems around their EPs have led to unique entanglement dynamics, which remained elusive until quite recently. In t

Ningyuan Yang, Tianyi Tao

In this paper, we present a simplified proof of Rado's Theorem and demonstrate that when an integer matrix $M$ satisfies the column condition and $M\mathbf x=\mathbf 0$ has an element-distinct solution on $\mathbb N$, then under any finite coloring of $\mathbb N$, the equation $M\mathbf x=\mathbf 0$ has a monochromatic element-distinct solution. This gives a

David Venhoek

We prove an explicit formula for the Fourier transform of $f(u(t))$, given the Fourier transform of $f(t)$, assuming $f\in L^2(-\infty,\infty)$ and $u$ sufficiently well behaved. We illustrate its usefulness by calculating the Fourier transform of $(a^2 + \sinh(bt)^2)^{-1}$.

Lucas I. Iñigo Gamiz, Robert Babjak, Bertrand Martinez, Marija Vranić

The next generation of Petawatt-class lasers presents the opportunity to study positron production and acceleration experimentally, in an all-optical setting. Several configurations were proposed to produce and accelerate positrons in a single laser stage. However, these configurations have yielded limited positron beam quality and low particle count. This p

Jingyou Xie, Jiayi Kuang, Zhenzhou Lin, Jiarui Ouyang

Given a query from one modality, few-shot cross-modal retrieval (CMR) retrieves semantically similar instances in another modality with the target domain including classes that are disjoint from the source domain. Compared with classical few-shot CMR methods, vision-language pretraining methods like CLIP have shown great few-shot or zero-shot learning perfor

Zhen Sun, Tianshuo Cong, Yule Liu, Chenhao Lin

Fine-tuning is an essential process to improve the performance of Large Language Models (LLMs) in specific domains, with Parameter-Efficient Fine-Tuning (PEFT) gaining popularity due to its capacity to reduce computational demands through the integration of low-rank adapters. These lightweight adapters, such as LoRA, can be shared and utilized on open-source

Lei Li, Yuancheng Wei, Zhihui Xie, Xuqing Yang

Vision-language generative reward models (VL-GenRMs) play a crucial role in aligning and evaluating multimodal AI systems, yet their own evaluation remains under-explored. Current assessment methods primarily rely on AI-annotated preference labels from traditional VL tasks, which can introduce biases and often fail to effectively challenge state-of-the-art m

Joris Bekkers, Amod Sahasrabudhe

A counterattack in soccer is a high speed, high intensity direct attack that can occur when a team transitions from a defensive state to an attacking state after regaining possession of the ball. The aim is to create a goal-scoring opportunity by convering a lot of ground with minimal passes before the opposing team can recover their defensive shape. The pur

Maryam Zahra, Homa Tajiani, Hadi Alasti

This paper presents a novel efficient method for spatial monitoring of the distribution of correlated field signals, such as temperature, humidity, etc. using unmanned aerial vehicles (UAVs). The spatial signal is compressed to its iso-contour lines at a number of known levels that are introduced by data fusion center (DFC). The UAV traces a contour line of

Ben Green, Mehtaab Sawhney

Suppose that $A \subset \{1,\dots, N\}$ has no two elements differing by a square. Then $|A| \ll N e^{-c\sqrt{\log N}}$.

Kiran Sharma, Aanchal Sharma, Jazlyn Jose, Vansh Saini

Retractions undermine the reliability of scientific literature and the foundation of future research. Analyzing collaboration networks in retracted papers can identify risk factors, such as recurring co-authors or institutions. This study compared the network structures of retracted and non-retracted papers, using data from Retraction Watch and Scopus for 30

Naveenkumar G Venkataswamy, Masudul H Imtiaz

User authentication is a pivotal element in security systems. Conventional methods including passwords, personal identification numbers, and identification tags are increasingly vulnerable to cyber-attacks. This paper suggests a paradigm shift towards biometric identification technology that leverages unique physiological or behavioral characteristics for us

Gabriele Benomio, Alejandro Cárdenas-Avendaño, Frans Pretorius, Andrew Sullivan

Motivated by understanding the nonlinear gravitational dynamics of spacetimes admitting stably trapped null geodesics, such as ultracompact objects and black string solutions to general relativity, we explore the dynamics of nonlinear scalar waves on a simple (fixed) model geometry with stable trapping. More specifically, we consider the time evolution of so

Tejaswi Kasarla, Abhishek Jha, Faye Tervoort, Rita Cucchiara

Active Learning aims to optimize performance while minimizing annotation costs by selecting the most informative samples from an unlabelled pool. Traditional uncertainty sampling often leads to sampling bias by choosing similar uncertain samples. We propose an active learning method that utilizes fixed equiangular hyperspherical points as class prototypes, e

Chuntao Li, Jiale Deng, Xingzhao Huang, Xiaochao Luo

On-chip narrow linewidth microlasers with real-time wavelength tunability are highly desirable for various applications including precision metrology, quantum technology, and coherent information processing. Realizing such laser remains a challenge despite significant advances made by various groups in recent years [Nat. Commun. 13, 5344 (2022); Nature 615,

Sami Boulebnane, Maria Ciudad-Alañón, Lana Mineh, Ashley Montanaro

In this work we develop theoretical techniques for analysing the performance of the quantum approximate optimization algorithm (QAOA) when applied to random boolean constraint satisfaction problems (CSPs), and use these techniques to compare the complexity of a variety of CSPs, such as $k$-SAT, 1-in-$k$ SAT, and NAE-SAT. Our techniques allow us to compute th

Alice Hedenlund, Tasos Moulinos

We construct a lift of the degree filtration on the integer valued polynomials to (even MU-based) synthetic spectra. Namely, we construct a bialgebra in modules over the evenly filtered sphere spectrum which base-changes to the degree filtration on the integer valued polynomials. As a consequence, we may lift the Hilbert additive group scheme to a spectral g

Shenghai Yuan, Jinfa Huang, Xianyi He, Yunyuan Ge

Identity-preserving text-to-video (IPT2V) generation aims to create high-fidelity videos with consistent human identity. It is an important task in video generation but remains an open problem for generative models. This paper pushes the technical frontier of IPT2V in two directions that have not been resolved in literature: (1) A tuning-free pipeline withou

Wangdan Liao, Weidong Wang

Spiking Neural Networks (SNNs) offer a biologically inspired alternative to conventional artificial neural networks, with potential advantages in power efficiency due to their event-driven computation. Despite their promise, SNNs have yet to achieve competitive performance on complex visual tasks, such as image classification. This study introduces a novel S

Ruben van Bergen, Justus Hübotter, Alma Lago, Pablo Lanillos

Autonomous intelligent agents must bridge computational challenges at disparate levels of abstraction, from the low-level spaces of sensory input and motor commands to the high-level domain of abstract reasoning and planning. A key question in designing such agents is how best to instantiate the representational space that will interface between these two le

Mireia Hernandez Caralt, Ivan Sekulić, Filip Carević, Nghia Khau

Detecting user frustration in modern-day task-oriented dialog (TOD) systems is imperative for maintaining overall user satisfaction, engagement, and retention. However, most recent research is focused on sentiment and emotion detection in academic settings, thus failing to fully encapsulate implications of real-world user data. To mitigate this gap, in this

Elisha Modelevsky, Nicholas C. Stone, Re'em Sari

In kinetic theory, the classic $n \Sigma v$ approach calculates the rate of particle interactions from local quantities: the number density of particles $n$, the cross-section $\Sigma$, and the average relative speed $v$. In stellar dynamics, this formula is often applied to problems in collisional (i.e. dense) environments such as globular and nuclear star

Vicent Gimeno i Garcia, Fernán González-Ibáñez

This paper explores the behavior of the torsional rigidity of a precompact domain as the ambient manifold evolves under a geometric flow. Specifically, we derive bounds on torsional rigidity under the Ricci Flow for Heisenberg spaces and homogeneous spheres. Additionally, we establish bounds under the Inverse Mean Curvature Flow for strictly convex, free-bou

Dustin G. Mixon, Brantley Vose

For an unknown finite group $G$ of automorphisms of a finite-dimensional Hilbert space, we find sharp bounds on the number of generic $G$-orbits needed to recover $G$ up to group isomorphism, as well as the number needed to recover $G$ as a concrete set of automorphisms.

Ashton Hetherington, Javier López Leonés, Soledad Le Clainche

This article introduces a novel methodology that integrates singular value decomposition (SVD) with a shallow linear neural network for forecasting high resolution fluid mechanics data. The method, termed LC-SVD-DLinear, combines a low-cost variant of singular value decomposition (LC-SVD) with the DLinear architecture, which decomposes the input features-spe

Susu Fang, Hao Li

The SLAMMOT, i.e. simultaneous localization, mapping, and moving object (detection and) tracking, represents an emerging technology for autonomous vehicles in dynamic environments. Such single-vehicle systems still have inherent limitations, such as occlusion issues. Inspired by SLAMMOT and rapidly evolving cooperative technologies, it is natural to explore

Chen Li, Bipin. Rajendran

We present Noise Adaptor, a novel method for constructing competitive low-latency spiking neural networks (SNNs) by converting noise-injected, low-bit artificial neural networks (ANNs). This approach builds on existing ANN-to-SNN conversion techniques but offers several key improvements: (1) By injecting noise during quantized ANN training, Noise Adaptor bet

Aviad Etzion, Nadav Cohen, Orzion Levy, Zeev Yampolsky

Mobile robots are used in various fields, from deliveries to search and rescue applications. Different types of sensors are mounted on the robot to provide accurate navigation and, thus, allow successful completion of its task. In real-world scenarios, due to environmental constraints, the robot frequently relies only on its inertial sensors. Therefore, due

Hugo Attali, Davide Buscaldi, Nathalie Pernelle, Fragkiskos D. Malliaros

Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challenges: over-squashing, where information from distant nodes is excessively compressed, and over-smoothing, where repeated propagation makes node representations indistinguishable. Both phenomena stem from the intera

Chengyang Liang, Dong Li

Semantic communication (SemCom) has emerged as a promising technique for the next-generation communication systems, in which the generation at the receiver side is allowed with semantic features' recovery. However, the majority of existing research predominantly utilizes a singular type of semantic information, such as text, images, or speech, to supervise a

Leonardo Geiger, Nicolas Fdida, Christophe Dumouchel, Jean-Bernard Blaisot

A method for analyzing liquid ligaments of a textural atomization process is presented in this article for the case of a rocket engine type assisted atomization process under combustion. The operating point positions the atomization process in the fiber type regime carrying an intense textural atomization process. Multiscale in nature, the method based on im

Fanxu Meng, Pingzhi Tang, Fan jiang, Muhan Zhang

Decoder-only models generate tokens autoregressively by caching key/value vectors, but as the cache grows, inference becomes memory-bound. To address this issue, we introduce CLOVER (Cross-Layer Orthogonal Vectors), a novel approach that treats pairs of attention layers as a set of low-rank decompositions. CLOVER applies Singular Value Decomposition (SVD) to

Xue Xia, Randall Balestriero, Tao Zhang, Lorenz Hurni

Tracking geographic entities from historical maps, such as buildings, offers valuable insights into cultural heritage, urbanization patterns, environmental changes, and various historical research endeavors. However, linking these entities across diverse maps remains a persistent challenge for researchers. Traditionally, this has been addressed through a two

Roger Sanchez-Vital, Andrey Belogaev, Carles Gomez, Jeroen Famaey

Wi-Fi facilitates the Internet connectivity of billions of devices worldwide, making it an indispensable technology for modern life. Wi-Fi networks are becoming significantly denser, making energy consumption and its effects on operational costs and environmental sustainability crucial considerations. Wi-Fi has already introduced several mechanisms to enhanc

Mingze Sun, Junhao Chen, Junting Dong, Yurun Chen

Recent advances in generative models have enabled high-quality 3D character reconstruction from multi-modal. However, animating these generated characters remains a challenging task, especially for complex elements like garments and hair, due to the lack of large-scale datasets and effective rigging methods. To address this gap, we curate AnimeRig, a large-s

Jannik Zenner, Karl Ulrich Schreiber, Simon Stellmer

A ring laser is defined by its perimeter, which directly enters the conversion factor between measured Sagnac frequency and the actual rotation rate. Large ring lasers employed in geodesy and fundamental physics require stability of the perimeter at or below the parts-per-billion level. We present two complementary approaches to actively control the perimete

Subrata Paul, Sukanta Das

This work studies Temporally Non-Uniform Cellular Automata (t-NUCAs), a variant of non-uniform cellular automata, which temporally use two rules in a sequence during their evolution. The one-dimensional t-NUCAs, under finite as well as infinite lattices, are considered in this work. Surjectivity and injectivity of the t-NUCAs are studied. The reversibility o

Fuyou Mao, Lixin Lin, Ming Jiang, Dong Dai

The integration of multimodal medical imaging can provide complementary and comprehensive information for the diagnosis of Alzheimer's disease (AD). However, in clinical practice, since positron emission tomography (PET) is often missing, multimodal images might be incomplete. To address this problem, we propose a method that can efficiently utilize structur

Jan Quan, Brecht Evens, Rodolphe Sepulchre, Panagiotis Patrinos

The scaled relative graph (SRG) is a powerful graphical tool for analyzing the properties of operators, by mapping their graph onto the complex plane. In this work, we study the SRG of two classes of nonmonotone operators, namely the general class of semimonotone operators and a class of angle-bounded operators. In particular, we provide an analytical descri

Omnia Alwazzan, Amaya Gallagher-Syed, Thomas O. Millner, Sebastian Brandner

The integration of DNA methylation data with a Whole Slide Image (WSI) offers significant potential for enhancing the diagnostic precision of central nervous system (CNS) tumor classification in neuropathology. While existing approaches typically integrate encoded omic data with histology at either an early or late fusion stage, the potential of reintroducin

Naomi Oei, Juan M. Torres-Rincon, Hendrik van Hees, Carsten Greiner

We present a classical model to study the formation of charmonia, as well as dissociation and regeneration processes of heavy-quark bound states in the quark gluon plasma using Langevin simulations. The charm and anticharm quarks are described as Brownian particles in the background medium of light quarks and gluons and interact among them over a Coulomb-lik

Mohamed Yassine Bouhamidi, Chunhui Dai, Michel Stephan, Joyeeta Nag

Solid-state nanopores, nm-sized holes in thin, freestanding membranes, are powerful single-molecule sensors capable of interrogating a wide range of target analytes, from small molecules to large polymers. Interestingly, due to their high spatial resolution, nanopores can also identify tags on long polymers, making them an attractive option as the reading el

Juan P. Aguilera, Yudai Suzuki, Keita Yokoyama

In this paper, we give characterizations of the set of $\Pi^1_{e}$-consequences, $\Sigma^1_{e}$-consequences and $\mathsf{B}(\Pi^1_{e})$-consequences of the axiomatic system of the strong dependent choice for $\Sigma^1_i$ formulas $\Sigma^1_i$-$\mathsf{SDC}_0$ for $i > 0$ and $e < i+2$. Here, $\mathsf{B}(\Gamma)$ denotes the set generated by $\land,\lor,\lno

Anirban Biswas, Eung Jin Chun, Sanjoy Mandal, Dibyendu Nanda

The gauge-singlet right-handed neutrinos would be essential to explain the tiny masses of active neutrinos. We consider the effective field theory of the Standard Model extended with these fields under the assumption that neutrinos are Dirac particles. In this framework, we provide a comprehensive study for the phenomenological consequences of various dimens

Shinhyung Yang, David Georg Reichelt, Wilhelm Hasselbring

Performance engineering has become crucial for the cloud-native architecture. This architecture deploys multiple services, with each service representing an orchestration of containerized processes. OpenTelemetry is growing popular in the cloud-native industry for observing the software's behaviour, and Kieker provides the necessary tools to monitor and anal

Asghar Daneshvar, Hajar Kiamehr, Maryam Yazdanifar, Malihe Yousofzadeh

Since 2020, finite weight modules have been studied over twisted affine Lie superalgebras. To complete the characterization of modules over affine Lie superalgebras, we need some information regarding modules over untwisted affine Lie superalgebras. There are several known results on representations of twisted affine Lie superalgebras that hold for untwisted

Shiquan Li

Let $S$ be a noetherian normal scheme, and let $X\to S$ be a surjective projective morphism of pure relative dimension $d$. We construct a symmetric multi-additive functor $\mathcal{P}\mathrm{ic}(X)^{d+1} \to \mathcal{P}\mathrm{ic}(S)$, and prove its functorial properties. Our construction uses Elkik's and Garc\'ia's ideas, as well as algebraic Hartogs' theo

Nadia Bihari Padhan, Axel Voigt

The coarsening dynamics at late times in phase-separating systems lead to universally hyperuniform patterns. This is well known for scalar field theories, such as the Cahn-Hilliard equation, but has also been shown for dry scalar active field theories. We demonstrate the role of hydrodynamic interactions in influencing hyperuniformity in a wet active system

Alex J. Cridland, Elena Lega, Myriam Benisty

In an ongoing effort to understand planet formation the link between the chemistry of the protoplanetary disk and the properties of resulting planets have long been a subject of interest. These connections have generally been made between mature planets and young protoplanetary disks through the carbon-to-oxygen (C/O) ratio. In a rare number of systems, youn

N. Susshma, S. Deepa, K. Vijay Sai, R. Gowrishankar

The existence of low-lying long-lived isomers, predominantly in odd-odd nuclei of the light rare-earth mass region, is investigated through an extensive survey of available nuclear data. The characteristics of these isomeric states and their systematics has revealed intriguing and unusual properties, including the identification of isomer triplets, a phenome

Meng Wei, Zhongnian Li, Peng Ying, Xinzheng Xu

Recent advances in vision-language models (VLMs) have demonstrated remarkable capabilities in image classification by leveraging predefined sets of labels to construct text prompts for zero-shot reasoning. However, these approaches face significant limitations in undefined domains, where the label space is vocabulary-unknown and composite. We thus introduce

Trung Hieu Giang

A nonlinear shell model is studied in this paper. This is a nonlinear variant of the Budiansky-Sanders linear shell model. Under some suitable assumptions on the magnitude of the applied force, we will prove the existence of a minimizer for this shell model. In addition, we will also show that our existence result can be applied to all kinds of geometries of

Teng Wang, Wing-Yin Yu, Zhenqi He, Zehua Liu

LLMs exhibit advanced reasoning capabilities, offering the potential to transform natural language questions into mathematical models. However, existing open-source datasets in operations research domain lack detailed annotations of the modeling process, such as variable definitions, focusing solely on objective values, which hinders reinforcement learning a

Qiong-Ao Huang, Wei Jiang, Jerry Zhijian Yang, Cheng Yuan

Two primary scalar auxiliary variable (SAV) approaches are widely applied for simulating gradient flow systems, i.e., the nonlinear energy-based approach and the Lagrange multiplier approach. The former guarantees unconditional energy stability through a modified energy formulation, whereas the latter preserves original energy stability but requires small ti

Dingding Hu, Tao Yu, Pengfei Li

This article considers the receiver operating characteristic (ROC) curve analysis for medical data with non-ignorable missingness in the disease status. In the framework of the logistic regression models for both the disease status and the verification status, we first establish the identifiability of model parameters, and then propose a likelihood method to

Pengfei Cao, Yuheng Chen, Zhuoran Jin, Yubo Chen

Large language models (LLMs) have learned vast amounts of factual knowledge through self-supervised pre-training on large-scale corpora. Meanwhile, LLMs have also demonstrated excellent multilingual capabilities, which can express the learned knowledge in multiple languages. However, the knowledge storage mechanism in LLMs still remains mysterious. Some rese

John K. Aceti

The purpose of this paper is to explore properties of the whisker topology, which is a topology endowed on the fundamental group and whose utility is to detect locally complicated phenomena in pathological topological spaces. We show that the whisker topology preserves products, resolve an open question regarding the existence of a space which makes $\pi_1^{

Kesen Wang, Marc G. Genton

In recent decades, statisticians have been increasingly encountering spatial data that exhibit non-Gaussian behaviors such as asymmetry and heavy-tailedness. As a result, the assumptions of symmetry and fixed tail weight in Gaussian processes have become restrictive and may fail to capture the intrinsic properties of the data. To address the limitations of t

Peter Hirvonen, Ansgar Jüngel

A transient Poisson-Nernst-Planck system with steric effects is analyzed in a bounded domain with no-flux boundary conditions for the ion concentrations and mixed Dirichlet-Neumann boundary conditions for the electric potential. The steric repulsion of ions is modeled by a localized Lennard-Jones force, leading to cross-diffusion terms. The existence of glob

Kun Liu, Jin Zhao

In the field of finance, the prediction of individual credit default is of vital importance. However, existing methods face problems such as insufficient interpretability and transparency as well as limited performance when dealing with high-dimensional and nonlinear data. To address these issues, this paper introduces a method based on Kolmogorov-Arnold Net

Zhuo-Ting Cai, Hai-Dong Li, Wei Chen

Real-to-complex spectral transitions and the associated spontaneous symmetry breaking of eigenstates are central to non-Hermitian physics, yet a comprehensive and universal theory that precisely describes the underlying physical mechanisms for each individual state remains elusive. Here, we resolve the mystery by employing the complex path integral formalism

Fabio Benatti, Giovanni Nichele

We investigate a phenomenon known as Superactivation of Backflow of Information (SBFI); namely, the fact that the tensor product of a non-Markovian dynamics with itself exhibits Backflow of Information (BFI) from environment to system even if the single dynamics does not. Such an effect is witnessed by the non-monotonic behaviour of the Helstrom norm and eme

Kaya Miah, Jelle J. Goeman, Hein Putter, Annette Kopp-Schneider

In multi-state models based on high-dimensional data, effective modeling strategies are required to determine an optimal, ideally parsimonious model. In particular, linking covariate effects across transitions is needed to conduct joint variable selection. A useful technique to reduce model complexity is to address homogeneous covariate effects for distinct

Volodymyr Anisimov, Lucas Oliver

Clinical trials in the modern era are characterized by their complexity and high costs and usually involve hundreds/thousands of patients to be recruited across multiple clinical centres in many countries, as typically a rather large sample size is required in order to prove the efficiency of a particular drug. As the imperative to recruit vast numbers of pa