October 2024 arXiv papers — page 41

Peter Grönquist, Deblina Bhattacharjee, Bahar Aydemir, Baran Ozaydin

In the evolving landscape of deep learning, there is a pressing need for more comprehensive datasets capable of training models across multiple modalities. Concurrently, in digital humanities, there is a growing demand to leverage technology for diverse media adaptation and creation, yet limited by sparse datasets due to copyright and stylistic constraints.

Kouki Yamaguchi

The $n$-loop Kontsevich invariant of knots takes its value in the completion of the space of $n$-loop open Jacobi diagrams, which is an infinite dimensional vector space. Since the 1-loop part is presented by the Alexander polynomial, we are interested in the image of the $\geq 2$-loop Kontsevich invariant of knots having the same Alexander polynomial. In th

Jian Ding, Peng Yang, Zijie Zhuang

In this paper, we study the evolution of the zero-temperature random field Ising model as the mean of the external field $M$ increases from $-\infty$ to $\infty$. We focus on two types of evolutions: the ground state evolution and the Glauber evolution. For the ground state evolution, we investigate the occurrence of global avalanche, a moment where a large

Phyu Phyu Win, Zhigui Lin, Mengyun Zhang

To understand the impact of vaccination, we consider a SIVR (susceptible-infected-vaccinated-recovered) model which combines impulsive vaccination into the classical SIR model. The final size is firstly defined and estimated, and then the peak value and peak time are considered. Finally, the critical times for a given infected number is studied, and it can b

Bing Li, D. M. Pajerowski, J. -Q. Yan, R. J. McQueeney

MnBi$_{4}$Te$_{7}$ belongs to a family of antiferromagnetic topological insulators. It forms a natural heterostructure of magnetic (septuple) and non-magnetic (quintuple) topological blocks. Here, we explore the magnetism and magnetic interactions in this compound using inelastic neutron scattering. We find that the interlayer magnetic coupling is much weake

Karoline M. Gilbert, Yumi Choi, Martha L. Boyer, Benjamin F. Williams

The Local Ultraviolet to Infrared Treasury (LUVIT) is a Hubble Space Telescope program that combines newly acquired data in the near ultraviolet (NUV), optical, and near infrared (NIR) with archival optical and NIR imaging to produce multiband panchromatic resolved stellar catalogs for 23 pointings in 22 low-mass, star-forming galaxies ranging in distance fr

Kateryna Pozharska, Anatolii Romanyuk

Exact order estimates are obtained of the best $m$-term trigonometric approximations of the Nikol'skii-Besov classes $B^r_{p, \theta}$ of periodic functions of one and many variables in the space $B_{q,1}$. In the univariate case ($d=1$), we get the orders of the respective approximation characteristics on the classes $B^r_{p, \theta}$ as well as on the Sobo

Spencer Locke, Dmitry E. Pelinovsky

Babenko's equation describes traveling water waves in holomorphic coordinates. It has been used in the past to obtain properties of Stokes waves with smooth profiles analytically and numerically. We show in the deep-water limit that properties of Stokes waves with peaked profiles can also be recovered from the same Babenko's equation. In order to develop the

Yijin Li, Yichen Shen, Zhaoyang Huang, Shuo Chen

Recent advances in event-based vision suggest that these systems complement traditional cameras by providing continuous observation without frame rate limitations and a high dynamic range, making them well-suited for correspondence tasks such as optical flow and point tracking. However, there is still a lack of comprehensive benchmarks for correspondence tas

Jawad Allam, Alex Matzkin

The evolution of the quantum state of a system upon measurement results in state update. In this work, we investigate the characterization of updated states of multi-partite entangled qubit states with non-destructive weak measurements, involving weakly coupling a pointer to each qubit in a relativistic context. As is well-known, the updated state at interme

Mi Zhou, Evgeniy Petrov

In the present paper, a new type of mappings called perimetric contractions on $k$-polygons is introduced. These contractions can be viewed as a generalization of mappings that contracts perimeters of triangles. A fixed point theorem for this type of mappings in a complete metric space is established. Achieving a fixed point necessitates the avoidance of per

Yair Censor, Daniel Reem, Maroun Zaknoon

Given a Hilbert space and a finite family of operators defined on the space, the common fixed point problem (CFPP) is to find a point in the intersection of the fixed point sets of these operators. Instances of the problem have numerous applications in science and engineering. We consider an extrapolated block-iterative method with dynamic weights for solvin

Wentao Yang, Yucong Liao, Zhaoru Sun

Ice recrystallization inhibition (IRI) activity of polymers generally increases with chain length. However, for polyproline (PPro), a highly potent cryoprotectant, the IRI activity varies nonmonotonically with the degree of polymerization (DP), i.e., DP=8 (P8) > DP=15 (P15) > DP=3 (P3). Herein, we employ molecular dynamics simulations to reveal the microscop

Marco Rampazzo, Ying Xie

We prove that every simple flop of type $D_5$, i.e., resolved by blowups with exceptional divisor isomorphic to a generalized Grassmann bundle with fiber $OG(4, 10)$, induces a derived equivalence. This provides new evidence for the DK conjecture of Bondal--Orlov and Kawamata. The proof is based on a sequence of mutations of exceptional objects: we use the s

Yuwei Du, Jie Feng, Jie Zhao, Yong Li

Trajectory modeling, which includes research on trajectory data pattern mining and future prediction, has widespread applications in areas such as life services, urban transportation, and public administration. Numerous methods have been proposed to address specific problems within trajectory modeling. However, the heterogeneity of data and the diversity of

Li Jiao, Qiuxia Lai, Yu Li, Qiang Xu

Continual learning requires to overcome catastrophic forgetting when training a single model on a sequence of tasks. Recent top-performing approaches are prompt-based methods that utilize a set of learnable parameters (i.e., prompts) to encode task knowledge, from which appropriate ones are selected to guide the fixed pre-trained model in generating features

Anass B. El-Yaagoubi, Jean-Marc Freyermuth, Hernando Ombao

We present a general and flexible framework for detecting regime changes in complex, non-stationary data across multi-trial experiments. Traditional change point detection methods focus on identifying abrupt changes within a single time series (single trial), targeting shifts in statistical properties such as the mean, variance, and spectrum over time within

Ayushi Nema, Ankush Bhaskar, Kamlesh N. Pathak, Smitha V. Thampi

This study investigates the impact of High-intensity Long-Duration Continuous Auroral Electrojet Activity (HILDCAA) on the relativistic electrons in radiation belt of Earth. Utilizing data from Van Allen Probe mission of NASA, we conducted a comprehensive statistical analysis to understand the impact of HILDCAA events on the radiation belt fluxes. The super

Yury Alkhimenkov

An application based on graphical processing units (GPUs) applied to 3-D digital images is described for computing the linear anisotropic elastic properties of heterogeneous materials. The application can also retrieve the property contribution tensors of individual inclusions of any shape. The code can be executed on professional GPUs as well as on a basic

Agata Smoktunowicz

Let $p>3$ be a prime number and let $A$ be a brace whose additive group is a direct sum of cyclic groups of cardinalities larger than $p^{\alpha }$ for some $\alpha $. Suppose that either (i) $A^{\lfloor{\frac {p-1}4}\rfloor}\subseteq pA$ or that (ii) the additive group of brace $A$ has rank smaller than ${\lfloor{\frac {p-1}4}\rfloor}$. It is shown that for

Linghang Kong, Elynn Chen, Yuzhou Chen, Yuefeng Han

Multi-dimensional time series data, such as matrix and tensor-variate time series, are increasingly prevalent in fields such as economics, finance, and climate science. Traditional Transformer models, though adept with sequential data, do not effectively preserve these multi-dimensional structures, as their internal operations in effect flatten multi-dimensi

Ram Manohar, S. M. Mallikarjunaiah

We propose an $hp$-adaptive discontinuous Galerkin finite element method (DGFEM) to approximate the solution of a static crack boundary value problem. The mathematical model describes the behavior of a geometrically linear strain-limiting elastic body. The compatibility condition for the physical variables, along with a specific algebraically nonlinear const

Xiaorui Zhao, Rui Ming Zhang, Xuefei Xu, Haitao Xu

Unimolecular gas phase chemical reactions could be activated by both infrared (IR) radiation and inter-molecular collision in the interstellar environment. Understanding the interplay and competition between the radiation and collision activation mechanisms is crucial for assessing accurate reaction rate constants with an appropriate model. In this work, gui

H. Falomir, M. Loewe, E. Muñoz, J. C. Rojas

We explore the meromorphic structure of the $\zeta$-function associated to the boundary eigenvalue problem of a modified Sturm-Liouville operator subject to spectral dependent boundary conditions at one end of a segment of length $l$. We find that it presents isolated simple poles which follow the general rule valid for second order differential operators su

Yuk-Kwan Wong, Ziqiang Zheng, Mingzhe Zhang, David Suggett

Coral reef imagery offers critical data for monitoring ecosystem health, in particular as the ease of image datasets continues to rapidly expand. Whilst semi-automated analytical platforms for reef imagery are becoming more available, the dominant approaches face fundamental limitations. To address these challenges, we propose CoralSCOP-LAT, a coral reef ima

Huiling Chen, Shanli Ye

Let $\alpha>0$ and $\mu$ be a positive Borel measure on the interval $[0,1)$. The Hankel matrix $\mathcal{H}_{\mu,\alpha}=(\mu_{n,k,\alpha})_{n,k\ge0}$ with entries $\mu_{n,k,\alpha}=\int_{[0,1)}^{}\frac{\Gamma(n+\alpha)}{\Gamma(n+1)\Gamma(\alpha)}t^{n+k}d\mu(t)$, induces, formally, the generalized-Hilbert operator as $$ \mathcal{H}_{\mu,\alpha}\left ( f \ri

P. Lunkenheimer, K. Samwer, A. Loidl

Recently, a universal relation between the thermal expansion coefficient of glasses $\alpha_g$, their glass-transition temperature Tg, and the so-called fragility index m of the corresponding supercooled liquid state was found to be valid for more than 200 glass formers, namely $\alpha_g/m\propto 1/T_g$ [P. Lunkenheimer et al., Nat. Phys. 19, 694 (2023)]. He

Keiya Murashima, Natsuki Hosono, Takayuki R. Saitoh, Takanori Sasaki

There are some traces of the existence of internal ocean in some icy moons, such as the vapor plumes of Europa and Enceladus. This implies a region of liquid water beneath the surface ice shell. Since liquid water would be essential for the origin of life, it is important to understand the development of these internal oceans, particularly their temperature

Sina Däubener, Kira Maag, David Krueger, Asja Fischer

Deep neural networks have proven to be extremely powerful, however, they are also vulnerable to adversarial attacks which can cause hazardous incorrect predictions in safety-critical applications. Certified robustness via randomized smoothing gives a probabilistic guarantee that the smoothed classifier's predictions will not change within an $\ell_2$-ball ar

Fatjon Seraj

Infrastructure maintenance is inherently complex, especially for widely dispersed transport systems like roads and railroads. Maintaining this infrastructure involves multiple partners working together to ensure safe, efficient upkeep that meets technical and safety standards, with timely materials and budget adherence. Traditionally, these requirements are

Sergei Devadze, Christine Elizabeth Nielsen, Dmitri Mihhailov, Peeter Ellervee

The planned high-luminosity upgrade of the Large Hadron Collider (LHC) at CERN will bring much higher data rates that are far above the capabilities of currently installed software-based data processing systems. Therefore, new methods must be used to facilitate on-the-fly extraction of scientifically significant information from the immense flow of data prod

Joshua Meyer, Alexander Rath, Ömercan Yazici, Philipp Slusallek

Multiple importance sampling (MIS) is an indispensable tool in rendering that constructs robust sampling strategies by combining the respective strengths of individual distributions. Its efficiency can be greatly improved by carefully selecting the number of samples drawn from each distribution, but automating this process remains a challenging problem. Exis

Haitao Zhang, Bo An

Large models are a hot research topic in the field of artificial intelligence. Leveraging their generative capabilities has the potential to enhance the level and quality of medical services. In response to the limitations of current large language models, which often struggle with accuracy and have narrow capabilities in medical applications, this paper pre

Wei-Yi Chen, Yi-Ling Lin, Yu-An Su, Wei-Hsin Yeh

Combining sports and machine learning involves leveraging ML algorithms and techniques to extract insight from sports-related data such as player statistics, game footage, and other relevant information. However, datasets related to figure skating in the literature focus primarily on element classification and are currently unavailable or exhibit only limite

Wentao Gao, Xiaojing Du, Wenjun Yu, Xiongren Chen

Time series forecasting is a critical task in various domains, where accurate predictions can drive informed decision-making. Traditional forecasting methods often rely on current observations of variables to predict future outcomes, typically overlooking the influence of latent confounders, unobserved variables that simultaneously affect both the predictors

Fatemeh Shirmohammadzadeh Maleki

This Paper investigate sequent calculi for certain weak subintuitionistic logics. We establish that weakening and contraction are height-preserving admissible for each of these calculi, and we provide a syntactic proof for the admissibility of the cut rule for most of these sequent calculi. We also demonstrate the equivalence of these calculi to their corres

Ziming Li, Qianbo Zang, David Ma, Jiawei Guo

Data science tasks involving tabular data present complex challenges that require sophisticated problem-solving approaches. We propose AutoKaggle, a powerful and user-centric framework that assists data scientists in completing daily data pipelines through a collaborative multi-agent system. AutoKaggle implements an iterative development process that combine

Wentao Gao, Cheng Zhou

Accurate prediction of human behavior is crucial for effective human-robot interaction (HRI) systems, especially in dynamic environments where real-time decisions are essential. This paper addresses the challenge of forecasting future human behavior using multivariate time series data from wearable sensors, which capture various aspects of human movement. Th

Anna Fino, Gueo Grantcharov

The generalized hypercomplex structures defined within the framework of generalized geometry include hypercomplex and holomorphic symplectic structures as particular cases. They have a $S^2$-family of generalized complex structures, and in this paper we study the types of these structures and the corresponding twistor space. We show that there are generalize

Yu Liu, Arif Mahmood, Muhammad Haris Khan

Many current visual object tracking benchmarks such as OTB100, NfS, UAV123, LaSOT, and GOT-10K, predominantly contain day-time scenarios while the challenges posed by the night-time has been less investigated. It is primarily because of the lack of a large-scale, well-annotated night-time benchmark for rigorously evaluating tracking algorithms. To this end,

Bin Chen, Haowei Sun, Jie Xu

In this work, we study the geodesics in different types of Carrollian RN (Reissner-Nordstr\"om) black holes, considering the motions of both neutral and charged particles. We use the geodesic equations in the weak Carrollian structure and analyze the corresponding trajectories projected onto the absolute space, and find that the geodesics are well-defined. I

Qingtong Wu

In this paper we investigate estimates about the Laplace operator in heat flows of harmonic maps, focusing outside the singularities through spherical coordinates. These estimates can be used in the general Ericksen--Leslie system to obtain higher-order estimates. We consider the problem subject to the $\mathbb{T}^2$ and $\mathbb{T}^3$ boundary conditions.

Zhengmian Hu, Heng Huang

Large language models are probabilistic models, and the process of generating content is essentially sampling from the output distribution of the language model. Existing watermarking techniques inject watermarks into the generated content without altering the output quality. On the other hand, existing acceleration techniques, specifically speculative sampl

Olivier Malenfant-Thuot, Dounia Shaaban Kabakibo, Simon Blackburn, Bruno Rousseau

We introduce a machine learning prediction workflow to study the impact of defects on the Raman response of 2D materials. By combining the use of machine-learned interatomic potentials, the Raman-active $\Gamma$-weighted density of states method and splitting configurations in independant patches, we are able to reach simulation sizes in the tens of thousand

Zhongjian Zhu

In this paper, we develop the new method, initiated by B. Gray (1972), to compute the unstable homotopy groups of the mapping cone, especially for $2$-cell complex $X=S^m\cup_{\alpha} e^{n}$. By Gray's work mentioned above or the traditional method given by I.M.James (1957) which were widely used in previous related work to compute $\pi_{i}(X)$, the dimensio

Zepei Xing, Vicky Kalogera, Tassos Fragos, Jeff J. Andrews

The existence of a mass gap of $3-5\,M_{\odot}$ between the heaviest neutron stars (NSs) and the lightest black holes (BHs), inferred from the BH mass distribution in low mass X-ray binaries (LMXBs), has been suggested for decades. The recently reported gravitational-wave source GW230529 has been confidently identified as a NSBH merger, with the BH mass fall

Zhen Xiong

In this paper, first we introduce the notion of a skew-Hom-Lie algebra and give some examples. Then we study their representations and give the coboundary operator of skew-Hom-Lie algebras. As an application, there have a skew-Hom-Lie algebra $(R^4_2,[\cdot,\cdot]_\theta,P)$ in semi-Euclidean spaces. For the null space of Semi-Euclidean spaces, there have a

Vincent Hue, Thibault Cavalié, James A. Sinclair, Xi Zhang

Observations of the Jovian upper atmosphere at high latitudes in the UV, IR and mm/sub-mm all indicate that the chemical distributions and thermal structure are broadly influenced by auroral particle precipitations. Mid-IR and UV observations have shown that several light hydrocarbons (up to 6 carbon atoms) have altered abundances near Jupiter's main auroral

André Carvalho, Pedro V. Silva

We prove that a subset of a virtually free group is rational if and only if the language of geodesic words representing its elements (in any generating set) is rational and that the language of geodesics representing conjugates of elements in a rational subset of a virtually free group is context-free. As a corollary, the doubly generalized conjugacy problem

Arslan Majal, Aamir Hussain Chughtai

Trajectory Reconstruction (TR) is vital for accurately mapping movement patterns and validating analyses, especially in fields like robotics, biomechanics, and environmental tracking, where data might be missing or affected by outliers. Improving Trajectory estimation by employing Gaussian smoothing techniques in the presence of non-Gaussian noise is the sub

Chandradoy Chatterjee

The ePIC detector is being designed as a general-purpose detector to deliver the full physics program of the Electron-Ion Collider (EIC) in BNL USA. Particle Identification (PID) plays a crucial role in the EIC physics program. Over a wide phase-space the PID systems provide excellent hadron identification required for the EIC physics program. Additionally,

N. A. Khokhlov

I present a new approximation of the $S$-matrix dependence on momentum $q$, formulated as a sum of a rational function and a truncated Sinc series. This approach enables pointwise determination of the $S$ matrix with specified resolution, capturing essential features such as resonance behavior with high accuracy. The resulting approximation provides a separa

Long Chen, Xuehai Huang

This paper introduces a novel tangential-normal ($t$-$n$) decomposition for finite element differential forms, presenting a new framework for constructing bases in finite element exterior calculus. The main contribution is the development of a $t$-$n$ basis where degrees of freedom and shape functions are explicitly dual, a property that streamlines stiffnes

A. Tomasino, A Shams-Ansari, M. Lončar, I. -C. Benea-Chelmus

Deployment of terahertz communication and spectroscopy systems relies on the availability of low-noise and fast detectors, with plug-and-play capabilities. However, most currently available technologies are stand-alone, discrete components, either slow or susceptible to temperature drifts. Moreover, phase-sensitive schemes are mainly based on bulk crystals a

Hongyu Sun, Qiuhong Ke, Yongcai Wang, Wang Chen

This paper investigates the 3D domain generalization (3DDG) ability of large 3D models based on prevalent prompt learning. Recent works demonstrate the performances of 3D point cloud recognition can be boosted remarkably by parameter-efficient prompt tuning. However, we observe that the improvement on downstream tasks comes at the expense of a severe drop in

Martin Rabel, Wiebke Günther, Jakob Runge, Andreas Gerhardus

Causal structure learning with data from multiple contexts carries both opportunities and challenges. Opportunities arise from considering shared and context-specific causal graphs enabling to generalize and transfer causal knowledge across contexts. However, a challenge that is currently understudied in the literature is the impact of differing observationa

Fei Wang, Zeren Zhang

We address a threshold problem of the Couette flow $(y,0)$ in a uniform magnetic field $(\beta,0)$ for the 2D MHD equation on $\mathbb{T}\times\mathbb{R}$ with fluid viscosity $\nu$ and magnetic resistivity $\mu$. The nonlinear enhanced dissipation and inviscid damping are also established. In particularly, when $0<\nu\leq\mu^3\leq1$, we get a threshold $\nu

Miho Aoki

We determine the Galois module structure of the ring of integers for all cubic fields using roots of the generic cyclic cubic polynomial $f_n(X)=X^3-nX^2-(n+3)X-1$. Let $L_n=\mathbb Q(\rho_n)$ be a cyclic cubic field with Galois group $G:={\rm Gal}(L_n/\mathbb Q)$, where $\rho_n$ is a root of $f_n (X)$, and ${\mathcal O}_{L_n}$ the ring of integers of $L_n$.

Lu Wang, Hongchan Chen, Bing Wang, Qian Li

In the field of materials science, exploring the relationship between composition, microstructure, and properties has long been a critical research focus. The mechanical performance of solid-solution Mg-Gd alloys is significantly influenced by Gd content, dendritic structures, and the presence of secondary phases. To better analyze and predict the impact of

Meng Chen, Xue-ping Wang

This article introduces a weak pseudo-inverse of a monotone function, which is applied to characterize the associativity of a two-place function $T: [0,1]^2\rightarrow [0,1]$ defined by $T(x,y)=t^{[-1]}(F(t(x),t(y)))$ where $F:[0,\infty]^2\rightarrow[0,\infty]$ is an associative function with neutral element in $[0,\infty]$, $t: [0,1]\rightarrow [0,\infty]$

Kunal Dahiya, Diego Ortego, David Jiménez

Extreme Multi-label Classification (XMC) methods predict relevant labels for a given query in an extremely large label space. Recent works in XMC address this problem using deep encoders that project text descriptions to an embedding space suitable for recovering the closest labels. However, learning deep models can be computationally expensive in large outp

Fabian Ihle, Michael Menth

In MPLS, packets are encapsulated with labels that add domain-specific forwarding information. Special purpose labels were introduced to trigger special behavior in MPLS nodes but their number is limited. Therefore, the IETF proposed the MPLS Network Actions (MNA) framework. It extends MPLS with new features, some of which have already been defined to suppor

Benjamin F. Spector, Simran Arora, Aaryan Singhal, Daniel Y. Fu

The challenge of mapping AI architectures to GPU hardware is creating a critical bottleneck in AI progress. Despite substantial efforts, hand-written custom kernels fail to meet their theoretical performance thresholds, even on well-established operations like linear attention. The diverse hardware capabilities of GPUs might suggest that we need a wide varie

Matthias Holzenkamp, Dongyu Lyu, Ulrich Kleinekathöfer, Peter Zaspel

Uncertainty estimations for machine learning interatomic potentials (MLIPs) are crucial for quantifying model error and identifying informative training samples in active learning strategies. In this study, we evaluate uncertainty estimations of Gaussian process regression (GPR)-based MLIPs, including the predictive GPR standard deviation and ensemble-based

Ken Hiura

We study nonlinear fluctuating hydrodynamic theories with charge and energy conservation in and above two dimensions that describe the large-scale behavior of the Hamiltonian XY model in the disordered and ordered phases. Using renormalization group analysis at one-loop order, we show that while Fourier's law holds in the ordered phase above two dimensions a

Lorenzo Foscolo, Federico Trinca

We exhibit new minimal 2-spheres in hyperk\"ahler 4-manifolds arising from the Gibbons--Hawking ansatz and in the K3 manifold endowed with a hyperk\"ahler metric. These minimal surfaces are obtained via a gluing construction using the Scherk surface in flat space and the holomorphic cigar in the Taub-NUT space as building blocks. As for the stable minimal 2-

Yu Liu, Arif Mahmood, Muhammad Haris Khan

RGB video object tracking is a fundamental task in computer vision. Its effectiveness can be improved using depth information, particularly for handling motion-blurred target. However, depth information is often missing in commonly used tracking benchmarks. In this work, we propose a new framework that leverages monocular depth estimation to counter the chal

Victor Guillemot, Riccardo Messina, Valentina Krachmalnicoff, Rémi Carminati

We present high precision measurements of the radiative heat transfer of a glass microsphere immersed in a thermal bath in vacuum facing three different planar substrates (SiO2, SiC and Au), which exhibit very different optical behaviors in the infrared region. Using a thermoresistive probe on a cantilever, we show the nonmonotonic behavior of the radiative

Daoyuan Qian, Ila Fiete

Reservoir computing (RC) harnesses the intrinsic dynamics of a chaotic system, called the reservoir, to perform various time-varying functions. An important use-case of RC is the generation of target temporal sequences via a trainable output-to-reservoir feedback loop. Despite the promise of RC in various domains, we lack a theory of performance bounds on RC

Marc Cabanes, Britta Späth

We prove that for any prime $\ell$, any finite group has as many irreducible complex characters of degree prime to $\ell$ as the normalizers of its Sylow $\ell$-subgroups. This equality was conjectured by John McKay. The conjecture was reduced by Isaacs--Malle--Navarro (2007) to a conjecture on representations, linear and projective, of finite simple groups

Lei Wang, Liang Du, Peng Zhou

Multiple kernel learning (MKL) aims to find an optimal, consistent kernel function. In the hierarchical multiple kernel clustering (HMKC) algorithm, sample features are extracted layer by layer from a high-dimensional space to maximize the retention of effective information. However, information interaction between layers is often ignored. In this model, onl

Liena Colarte-Gómez, Francesco Galuppi

In this paper, we study the symmetric rank of products of linear forms and an irreducible quadratic form. The main result presents a new, non-trivial lower bound for the rank, and the arguments rely on the apolarity lemma. In the special case of degree 4, we give a list of normal forms for such quartics, and we apply our general result to compute the rank of

Ronghui Li, Hongwen Zhang, Yachao Zhang, Yuxiang Zhang

We propose Lodge++, a choreography framework to generate high-quality, ultra-long, and vivid dances given the music and desired genre. To handle the challenges in computational efficiency, the learning of complex and vivid global choreography patterns, and the physical quality of local dance movements, Lodge++ adopts a two-stage strategy to produce dances fr

Yunhui Liang, Jianwen Gan, Yan Chen, Peng Zhou

High-dimensional data is commonly encountered in numerous data analysis tasks. Feature selection techniques aim to identify the most representative features from the original high-dimensional data. Due to the absence of class label information, it is significantly more challenging to select appropriate features in unsupervised learning scenarios compared to

Françoise Michel, Claude Weber

In the article we give a self-contained new proof that a normal quasi-ordinary surface germ is analytically isomorphic to a cyclic quotient surface germ.

A. Arhrib, S. Moretti, S. Semlali, C. H. Shepherd-Themistocleous

In this study, we explore the potential to probe the process $gg \to H_{\text{SM-like}} \to hh \to b\bar{b}\tau\tau$ at the Large Hadron Collider (LHC), within the framework of the Two Higgs Doublet Model (2HDM) Type-I. After performing a detailed Monte Carlo (MC) simulation, we focus on isolating the signal from the Standard Model (SM) backgrounds. Our anal

Soumyadip Sahu

The article generalizes an observation of Zagier and Gangl to show that the image of the spectral Eisenstein series on a general congruence subgroup of $\text{SL}_2(\mathbb{Z})$, under the Eichler-Shimura isomorphism, is defined over a cyclotomic number field. We use the same technique to generalize an invariant attached to imaginary quadratic fields in conn

Vagelis Plevris

This study explores the limitations of image-based structural health monitoring (SHM) techniques in detecting structural damage. Leveraging machine learning and computer vision, image-based SHM offers a scalable and efficient alternative to manual inspections. However, its reliability is impacted by challenges such as false positives, false negatives, and en

Fei Li, Liang Du, Chaohong Ren

Non-negative Matrix Factorization(NMF) algorithm can only be used to find low rank approximation of original non-negative data while Concept Factorization(CF) algorithm extends matrix factorization to single non-linear kernel space, improving learning ability and adaptability of matrix factorization. In unsupervised environment, to design or select proper ke

Joan Solà Peracaula

The possibility that the vacuum energy density (VED) could be time dependent in the expanding Universe is intuitively more reasonable than just a rigid cosmological constant for the entire cosmic history. The framework of the running vacuum model (RVM) is a salient example derived from QFT in curved spacetime, wherein the VED appears as a power series of the

Haoyu Zhang, Jun Liu, Zhenhua Zhu, Shulin Zeng

ANNS for embedded vector representations of texts is commonly used in information retrieval, with two important information representations being sparse and dense vectors. While it has been shown that combining these representations improves accuracy, the current method of conducting sparse and dense vector searches separately suffers from low scalability an

Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung

One-shot Federated Learning (OFL) significantly reduces communication costs in FL by aggregating trained models only once. However, the performance of advanced OFL methods is far behind the normal FL. In this work, we provide a causal view to find that this performance drop of OFL methods comes from the isolation problem, which means that local isolatedly tr

Davide Radi, Frank Westerhoff

We propose an evolutionary competition model to investigate the green transition of firms, highlighting the role of adjustment costs, dynamically adjusted transition risk, and green technology progress in this process. Firms base their decisions to adopt either green or brown technologies on relative performance. To incorporate the costs of switching to anot

Hongmou Zhang, Hezhishi Jiang, Yihang Li, Qing Lu

In this article we reframe the classic problem of massive location choice for retail chains, introducing an alternative approach. Traditional methodologies of massive location choice models encounter limitations rooted in assumptions such as power-law distance decay and oversimplified travel patterns. In response, we present a spatial operations research mod

keqiang Lyu, Ying Wu

In this work, we introduce an advanced acoustic leaky-wave antenna employing zero-refractive-index metamaterials (ZIMs) that significantly surpasses traditional designs in terms of radiation ef-ficiency and directivity. Our design features a novel space-coiling structure, which manipulates the Dirac-like dispersion based on accidental degeneracy to achieve d

Xin Lei, Erxi Xiao, Yingge Huang, Yujie Feng

The dynamic mechanisms underlying single charge-exchange reactions have been investigated using a theoretical framework that combines the Isospin-dependent Quantum Molecular Dynamics (IQMD) model with the statistical decay model GEMINI++. Two distinct channels contribute to the single isobaric charge-exchange reaction: quasi-elastic channel, where neutron-pr

Anna Dalklint, Rasmus E. Christiansen, Ole Sigmund

Topology optimization has matured to become a powerful engineering design tool that is capable of designing extraordinary structures and materials taking into account various physical phenomena. Despite the method's great advancements in recent years, several unanswered questions remain. This paper takes a step towards answering one of the larger questions,

Puchen Zhu, Huayu Zhang, Xin Ma, Xiaoyin Zheng

Flexible endoscopes are commonly adopted in narrow and confined anatomical cavities due to their higher reachability and dexterity. However, prolonged and unintuitive manipulation of these endoscopes leads to an increased workload on surgeons and risks of collision. To address these challenges, this paper proposes a CT-guided control framework for the diagno

Anne Bernand-Mantel, Valeriy V. Slastikov, Cyrill B. Muratov

We derive asymptotically exact formulas for the equilibrium magnetic stripe period in ultrathin films with out-of-plane anisotropy that include the full domain wall magnetic dipolar energy. Starting with the reduced two-dimensional micromagnetic model valid for thin films, we obtain the leading order approximation for the energy per unit volume in the vanish

Ang Li, Jiang Long, Jing-Long Yang

We study the three-dimensional Carrollian field theory on the Rindler horizon which is dual to a bulk massless scalar field theory in the four-dimensional Rindler wedge. The Carrollian field theory could be mapped to a two-dimensional Euclidean field theory in the transverse plane by a Fourier transform. After defining the incoming and outgoing states at the

Jiaxing Huang, Jingyi Zhang, Kai Jiang, Shijian Lu

Recent studies on generalizable object detection have attracted increasing attention with additional weak supervision from large-scale datasets with image-level labels. However, weakly-supervised detection learning often suffers from image-to-box label mismatch, i.e., image-level labels do not convey precise object information. We design Language Hierarchica

Bergur Snorrason

We study various regularization operators on plurisubharmonic functions that preserve Lelong classes with growth given by certain compact convex sets. The purpose is to show that the weighted Siciak-Zakharyuta functions associated with these Lelong classes are lower semicontinuous. These operators are given by integral, infimal, and supremal convolutions. Co

Rong Lei, Songzi Li, Xiang-Dong Li

We introduce the Langevin deformation for the R\'enyi entropy on the $L^2$-Wasserstein space over $\mathbb{R}^n$ or a Riemannian manifold, which interpolates between the porous medium equation and the Benamou-Brenier geodesic flow on the $L^2$-Wasserstein space and can be regarded as the compressible Euler equations for isentropic gas with damping. We prove

Yao Wei, Siyu Chen, Bartomeu Monserrat

We report a first principles computational analysis of two phonon-mediated superconductors, In$_{5}$Bi$_{3}$ and In$_{5}$Sb$_{3}$. We show that spin-orbit coupling leads to splitting of electron bands around the Fermi energy, resulting in a suppression of the electronic density of states in both compounds. In In$_{5}$Bi$_{3}$, the spin-orbit coupling is esse

Puja Mukherjee, Ujjal Debnath, Anirudh Pradhan

In the Horava Lifshitz gravity scenario, we have described the mass accretion process of a 4 dimensional Kehagias Sfetsos black hole caused by some candidates of dark energy in detail. Firstly, we have obtained the equation of mass for the black hole with respect to the cosmic scale parameter a in the Horava Lifshitz gravity framework. Then, one by one, we h

Yinghua Qiu, Long Ma, Zhe Liu, Hongwen Zhang

During the dielectric breakdown process of thin solid-state nanopores, the application of high voltages may cause the formation of multi-nanopores on one chip, which number and sizes are important for their applications. Here, simulations were conducted to mimic the investigation of in situ nanopore detection with scanning ion conductance microscopy (SICM).

Sunwoo Kim, Soo Yong Lee, Fanchen Bu, Shinhwan Kang

Graph autoencoders (Graph-AEs) learn representations of given graphs by aiming to accurately reconstruct them. A notable application of Graph-AEs is graph-level anomaly detection (GLAD), whose objective is to identify graphs with anomalous topological structures and/or node features compared to the majority of the graph population. Graph-AEs for GLAD regard

Chao Zhang, Mengnan Guo, Hongwen Zhang, Xiuhua Ren

The ionic selectivity of nanopores is crucial for the energy conversion based on nanoporous membranes. It can be significantly affected by various parameters of nanopores and the applied fields driving ions through porous membranes. Here, with finite element simulations, the selective transport of ions through nanopores is systematically investigated under t

Rotem Zelingher

Ensuring food security is a critical global challenge, particularly for low-income countries where food prices impact the access to nutritious food. The volatility of global agricultural commodity (AC) prices exacerbates food insecurity, with international trade restrictions and market disruptions further complicating the situation. Despite online platforms

Yifang Chen, David Zhu, Simon Du, Kevin Jamieson

Recent advances in large language model (LLM) training have highlighted the need for diverse, high-quality instruction data. Recently, many works are exploring synthetic data generation using LLMs. However, they primarily focus on prompt engineering with standard supervised instruction-finetuned models, which contains a fundamental limitation: these models a