May 2024 arXiv papers — page 122

Renqi Chen, Wenwei Han, Haohao Zhang, Haoyang Su

Genomic selection (GS), as a critical crop breeding strategy, plays a key role in enhancing food production and addressing the global hunger crisis. The predominant approaches in GS currently revolve around employing statistical methods for prediction. However, statistical methods often come with two main limitations: strong statistical priors and linear ass

Zhiheng Ma, Anjia Cao, Funing Yang, Yihong Gong

Most dataset distillation methods struggle to accommodate large-scale datasets due to their substantial computational and memory requirements. Recent research has begun to explore scalable disentanglement methods. However, there are still performance bottlenecks and room for optimization in this direction. In this paper, we present a curriculum-based dataset

Surojit Biswas, Buddhananda Banerjee

Sampling from circular distributions is a fundamental task in directional statistics. A key challenge in acceptance-rejection methods lies in selecting an efficient envelope density, as poor choices can lead to low acceptance rates and increased computational cost, especially in large-scale simulations. To address this, we propose a new sampling framework th

Xiaoyang Du, Feng Hong

Target identification of ship-radiated noise is a crucial area in underwater target recognition. However, there is currently a lack of multi-target ship datasets that accurately represent real-world underwater acoustic conditions. To tackle this issue, we conducted experimental data acquisition, resulting in the release of QiandaoEar22 \textemdash a comprehe

Honghui Chen, Pingping Chen, Huan Mao, Mengxi Jiang

Anomaly detection and localization without any manual annotations and prior knowledge is a challenging task under the setting of unsupervised learning. The existing works achieve excellent performance in the anomaly detection, but with complex networks or cumbersome pipelines. To address this issue, this paper explores a simple but effective architecture in

Aleksandre Japaridze, Victor Struijk, Kushal Swamy, Irek Roslon

Synchronization plays a crucial role in the dynamics of living organisms, from fireflies flashing in unison to pacemaker cells that jointly generate heartbeats. Uncovering the mechanism behind these phenomena requires an understanding of individual biological oscillators and the coupling forces between them. Here, we develop a single-cell assay that studies

Tal Hershko, Maksim Zhukovskii

We study the problem of distinguishing between two independent samples $\mathbf{G}_n^1,\mathbf{G}_n^2$ of a binomial random graph $G(n,p)$ by first order (FO) sentences. Shelah and Spencer proved that, for a constant $\alpha\in(0,1)$, $G(n,n^{-\alpha})$ obeys FO zero-one law if and only if $\alpha$ is irrational. Therefore, for irrational $\alpha\in(0,1)$, a

L. M. Pulgar-Escobar, N. A. Henríquez-Salgado, Pierluigi Cerulo, R. E. Mennickent

The presence of pre-main-sequence and low-mass stars, combined with the new data from Gaia DR3 and with 2MASS, significantly enhances the relevance of studying this cluster. We aim to accurately identify cluster members, determine fundamental parameters, assess mass segregation, and establish precise age and distance using Gaia DR3 and 2MASS data. We employe

Siqi Xie, Jiantao Li

This article explores the evaluation method for the language communication proficiency of AI-driven robots engaging in interactive communication with children. The utilization of AI-driven robots in children's everyday communication is swiftly advancing, underscoring the importance of evaluating these robots'language communication skills. Based on 11 Chinese

Wladimir Sarlin, Rodolphe Grivet, Julien Xu, Axel Huerre

The present study reports experiments of water droplet impacting on ice or on a cold metallic substrate, with the aim of understanding the effect of phase change on the impingement process. Both liquid and substrate temperatures are varied, as well as the height of fall. The dimensionless maximum spreading diameter, $\beta_m$, is found to increase with both

Jenthe Thienpondt, Kris Demuynck

Current speaker diarization systems rely on an external voice activity detection model prior to speaker embedding extraction on the detected speech segments. In this paper, we establish that the attention system of a speaker embedding extractor acts as a weakly supervised internal VAD model and performs equally or better than comparable supervised VAD system

Fumitaka Nakamura, Chau-Ching Chiong, Kotomi Taniguchi, Chen Chien

We report on the development and commissioning of a new Q-band receiver for the Nobeyama 45-m telescope, covering 30--50 GHz with a receiver noise temperature of about 15 K. We name it eQ (extended Q-band) receiver. The system noise temperatures for observations are measured to be $\sim$ 30 K at 33 GHz and $\sim$ 75 K at 45 GHz. The Half-Power-Beam-Width (HP

Kang-Jie Li, Ze-Quan Wang, Zu-Xin Chen, Yusheng Hou

The emergence of multiferroic materials, which possess both ferromagnetic (FM) and ferroelectric (FE) properties, drive advancements in magnetoelectric applications and the next generation of spintronics. Based on first-principles calculations, we investigate an engineered two-dimensional multiferroic van der Waals heterostructures consisting of FM VSiSnN4 m

Chao Fan, Saihui Hou, Junhao Liang, Chuanfu Shen

Gait recognition, a rapidly advancing vision technology for person identification from a distance, has made significant strides in indoor settings. However, evidence suggests that existing methods often yield unsatisfactory results when applied to newly released real-world gait datasets. Furthermore, conclusions drawn from indoor gait datasets may not easily

Kushal Chakrabarti, Nikhil Chopra

This paper considers the observer design problem for discrete-time nonlinear dynamical systems with sampled measurement data. Earlier, the recently proposed Iteratively Preconditioned Gradient-Descent (IPG) observer, a Newton-type observer, has been empirically shown to have improved robustness against measurement noise than the prominent nonlinear observers

Guangpu Zhu, Brandon van Gogh, Lailai Zhu, On Shun Pak

Shear-thinning viscosity is a non-Newtonian behaviour that active particles often encounter in biological fluids such as blood and mucus. The fundamental question of how this ubiquitous non-Newtonian rheology affects the propulsion of active particles has attracted substantial interest. In particular, spherical Janus particles driven by self-diffusiophresis,

Han-Xiao Tao, Re-Bing Wu

Pulse-based quantum machine learning (QML) models possess full expressivity when they are ensemble controllable. However, it has also been shown that barren plateaus emerge in such models, rendering training intractable for systems with large dimension. In this paper, we show that the trade-off is closely related to the controllability of the underlying puls

Ahmed Adel Attia, Dorottya Demszky, Tolulope Ogunremi, Jing Liu

Creating Automatic Speech Recognition (ASR) systems that are robust and resilient to classroom conditions is paramount to the development of AI tools to aid teachers and students. In this work, we study the efficacy of continued pretraining (CPT) in adapting Wav2vec2.0 to the classroom domain. We show that CPT is a powerful tool in that regard and reduces th

Xiaoyang Du, Feng Hong

Target identification of ship-radiated noise is a crucial area in underwater target recognition. However, there is currently a lack of multi-target ship datasets that accurately represent real-world underwater acoustic conditions. To ntackle this issue, we release QiandaoEar22 \textemdash an underwater acoustic multi-target dataset, which can be download on

Žiga Virk

We prove that for each positive integer $n$, the Rips complexes of the $n$-dimensional integer lattice in the $d_1$ metric (i.e., the Manhattan metric, also called the natural word metric in the Cayley graph) are contractible at scales above $n^2(2n-1)$, with the bounds arising from the Jung's constants. We introduce a new concept of locally dominated vertic

Fan Lyu, Daofeng Liu, Linglan Zhao, Zhang Zhang

Online Continual Learning (OCL) empowers machine learning models to acquire new knowledge online across a sequence of tasks. However, OCL faces a significant challenge: catastrophic forgetting, wherein the model learned in previous tasks is substantially overwritten upon encountering new tasks, leading to a biased forgetting of prior knowledge. Moreover, the

Yilei Zhang, Haoyu Liao, Zekun Wang, Bo Huang

Static binary lifting is essential in binary rewriting frameworks. Existing tools overlook the impact of External Function Completion (EXFC) in static binary lifting. EXFC recovers the prototypes of External Functions (EXFs, functions defined in standard shared libraries) using only the function symbols available. Incorrect EXFC can misinterpret the source b

Hongbin Xu, Weitao Chen, Baigui Sun, Xuansong Xie

Despite the impressive performance of Multi-view Stereo (MVS) approaches given plenty of training samples, the performance degradation when generalizing to unseen domains has not been clearly explored yet. In this work, we focus on the domain generalization problem in MVS. To evaluate the generalization results, we build a novel MVS domain generalization ben

Ran Wolff

The contextual integrity model is a widely accepted way of analyzing the plurality of norms that are colloquially called "privacy norms". Contextual integrity systematically describes such norms by distinguishing the type of data concerned, the three social agents involved (subject, sender, and recipient) and the transmission principle governing the transfer

Poonam Rani, Rajveer Jha, V. P. S. Awana, Yoshikazu Mizuguchi

Decomposition of superconductors sometimes becomes crucial when studying essential physical properties of the superconductors. For example, the cuprate superconductor YBa2Cu3O7-d decomposes by long-time air exposure. In this study, we investigate the aging effects on superconducting properties of BiS2-based superconductors Bi4O4S3 and LaO0.5F0.5BiS2, both we

M. Reza Mohammadi Mozaffar

We study various aspects of capacity of entanglement in the squeezed states of a scalar field theory. This quantity is a quantum informational counterpart of heat capacity and characterizes the width of the eigenvalue spectrum of the reduced density matrix. In particular, we carefully examine the dependence of capacity of entanglement and its universal terms

Nicholas Zaunders, Ziqing Wang, Timothy C. Ralph, Ryan Aguinaldo

Classical free-space optical (FSO) communication promises massive data throughput rates relative to traditional wireless technologies - an attractive outcome now being pursued in the context of satellite-ground, inter-satellite and deep-space communications. The question we investigate here is: how can we minimally alter classical FSO systems, both in infras

Alberto Castro

A procedure to find optimal regimes for quantum thermal engines (QTMs) is described and demonstrated. The QTMs are modelled as the periodically-driven non-equilibrium steady states of open quantum systems, whose dynamics is approximated in this work with Markovian master equations. The action of the external agent, and the couplings to the heat reservoirs ca

Honghui Chen, Yuhang Qiu, Jiabao Wang, Pingping Chen

Scene Text Recognition (STR) is challenging in extracting effective character representations from visual data when text is unreadable. Permutation language modeling (PLM) is introduced to refine character predictions by jointly capturing contextual and visual information. However, in PLM, the use of random permutations causes training fit oscillation, and t

S. V. Bolokhov, K. A. Bronnikov, M. V. Skvortsova

The widely discussed ``black-bounce'' mechanism of removing a singularity at $r=0$ in a spherically symmetric space-time, proposed by Simpson and Visser, consists in removing the point $r=0$ and its close neighborhood, resulting in emergence of a regular minimum of the spherical radius that can be a wormhole throat or a regular bounce. Instead, it has been r

Daniele Bartoli, Alessandro Giannoni, Giuseppe Marino

The exploration of linear subspaces, particularly scattered subspaces, has garnered considerable attention across diverse mathematical disciplines in recent years, notably within finite geometries and coding theory. Scattered subspaces play a pivotal role in analyzing various geometric structures such as blocking sets, two-intersection sets, complete arcs, c

Shaobo Zhang, Akib Karim, Harry M. Quiney, Muhammad Usman

Quantum chemistry is a promising application in the era of quantum computing since the unique effects of quantum mechanics that take exponential growing resources to simulate classically are controllable on quantum computers. Fermionic degrees of freedom can be encoded efficiently onto qubits and allow for algorithms such as the Quantum Equation-of-Motion me

Kai-Zhi Bai, Bo Fu, Shun-Qing Shen

We develop a Dirac fermion theory for topological phases in magnetic topological insulator films. The theory is based on exact solutions of the energies and the wave functions for an effective model of the three-dimensional topological insulator (TI) film. It is found that the TI film consists of a pair of massless or massive Dirac fermions for the surface s

Jing Shi, Cunrui Han, Tao Wang, Chao Qi

Seismic anisotropy, arising from the crystallographic or lattice-preferred orientation of anisotropic minerals or the shape-preferred orientation of melts or cracks, can establish a critical link between Mars's past evolution and its current state. So far, although seismic anisotropy in Mars has been proposed due to different velocities of vertically and hor

Ram Prakash Pandeya, Konstantin P. Shchukin, Yannic Falke, Gregor Mussler

We synthesize and spectroscopically investigate monolayer C$_{60}$ on the topological insulator (TI) Bi$_4$Te$_3$. This C$_{60}$/Bi$_4$Te$_3$ heterostructure is characterized by excellent translational order in a novel (4 x 4) C$_{60}$ superstructure on a (9 x 9) unit of Bi$_4$Te$_3$. We measure the full two-dimensional energy band structure of C$_{60}$/Bi$_

Alireza Ahmadi, Michael Halstead, Claus Smitt, Chris McCool

In this article, we focus on the critical tasks of plant protection in arable farms, addressing a modern challenge in agriculture: integrating ecological considerations into the operational strategy of precision weeding robots like \bbot. This article presents the recent advancements in weed management algorithms and the real-world performance of \bbot\ at t

Xing Huang, Yuzhuo Wang, Jian Zhao, Saijun Wu

When a laser-cooled atomic sample is optically excited, the envelope of coherent forward scattering can often be decomposed into a few complex Gaussian profiles. The convenience of Gaussian propagation helps addressing key challenges in digital holography. In this work, we develop a Gaussian-decomposition-assisted approach to inline holography, for single-sh

Peng Peng, Zhengxi Zhang, Yaoyuan Fan, Guoling Yin

We study the dynamical evolution of cold atoms in crossed optical dipole trap theoretically and experimentally. The atomic transport process is accompanied by two competitive kinds of physical mechanics, atomic loading and atomic loss. The loading process normally is negligible in the evaporative cooling experiment on the ground, while it is significant in t

Domenik Eichhorn, Maximilian Schweikart, Nick Poser, Frederik Fiand

The advent of quantum algorithms has initiated a discourse on the potential for quantum speedups for optimization problems. However, several factors still hinder a practical realization of the potential benefits. These include the lack of advanced, error-free quantum hardware, the absence of accessible software stacks for seamless integration and interaction

Yiming Wu, Qihe Pan, Zhen Zhao, Zicheng Wang

In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remarkable success have been achieved by current image inpainting approaches, their application to the SOE task generally results in failure cases such as Object Missing, Text-Image Mism

Kai Hu, Weichen Yu, Yining Li, Kai Chen

Recent research indicates that large language models (LLMs) are susceptible to jailbreaking attacks that can generate harmful content. This paper introduces a novel token-level attack method, Adaptive Dense-to-Sparse Constrained Optimization (ADC), which has been shown to successfully jailbreak multiple open-source LLMs. Drawing inspiration from the difficul

Xiaoling Zhang, Zhengzi Xu, Shouguo Yang, Zhi Li

Reverse engineers would acquire valuable insights from descriptive function names, which are absent in publicly released binaries. Recent advances in binary function name prediction using data-driven machine learning show promise. However, existing approaches encounter difficulties in capturing function semantics in diverse optimized binaries and fail to res

Dechen Gao, Shuangyu Cai, Hanchu Zhou, Hang Wang

To safely navigate intricate real-world scenarios, autonomous vehicles must be able to adapt to diverse road conditions and anticipate future events. World model (WM) based reinforcement learning (RL) has emerged as a promising approach by learning and predicting the complex dynamics of various environments. Nevertheless, to the best of our knowledge, there

Shuwen Chen, Fangyang Zheng

An old conjecture in non-K\"ahler geometry states that, if a compact Hermitian manifold has constant holomorphic sectional curvature, then the metric must be K\"ahler (when the constant is non-zero) or Chern flat (when the constant is zero). It is known to be true in complex dimension $2$ by the work of Balas and Gauduchon in 1985 (when the constant is negat

Stanley Mugisha, Vamsi Krishna Guda, Christine Chevallereau, Damien Chablat

Humans use collaborative robots as tools for accomplishing various tasks. The interaction between humans and robots happens in tight shared workspaces. However, these machines must be safe to operate alongside humans to minimize the risk of accidental collisions. Ensuring safety imposes many constraints, such as reduced torque and velocity limits during oper

Zhi Qin, Zhoubo He, Zhe Cao, Tao Chen

The half-size prototype of the multi wire drift chamber (MWDC) for the cooling storage ring (CSR) external-target experiment (CEE) was assembled and tested in 350 MeV/u Kr+Fe reactions on the heavy ion research facility in Lanzhou (HIRFL). The prototype consists of 6 sense layers, where the sense wires are stretched in three directions X, U and V, meeting $0

Karthik Elamvazhuthi

It is known that if a nonlinear control affine system without drift is bracket generating, then its associated sub-Laplacian is invertible under some conditions on the domain. In this note, we investigate the converse. We show how invertibility of the sub-Laplacian operator implies a weaker form of controllability, where the reachable sets of a neighborhood

G. Y. Thiancourt, S. M. Ngom, N. Bardou, T. Devolder

The dispersion relation of spin waves can vary monotonically about the center of the Brillouin zone, allowing zero-momentum wavepackets to flow unidirectionally, which is of interest for applications. Techniques such as propagating spin wave spectroscopy are inoperative in such cases because of the difficulty to identify the spin wave wavevector at a particu

Amir Ali Farzin, Iman Shames

The application of a zeroth-order scheme for minimising Polyak-\L{}ojasewicz (PL) functions is considered. The framework is based on exploiting a random oracle to estimate the function gradient. The convergence of the algorithm to a global minimum in the unconstrained case and to a neighbourhood of the global minimum in the constrained case along with their

Asahi Ushio, Jose Camacho-Collados

In machine learning, temporal shifts occur when there are differences between training and test splits in terms of time. For streaming data such as news or social media, models are commonly trained on a fixed corpus from a certain period of time, and they can become obsolete due to the dynamism and evolving nature of online content. This paper focuses on tem

Hao Chen, Valery I. Levitas

Virtual melting (VM) as alternative deformation and stress relaxation mechanisms under extreme load is directly validated by molecular dynamics (MD) simulations of the simple shear of single crystal Si I at a temperature 1,383 K below the melting temperature. The shear band consisting of liquid Si is formed immediately after the shear instability while stres

Jonathan Gornet, Bruno Sinopoli

Decision-making under uncertainty is a fundamental problem encountered frequently and can be formulated as a stochastic multi-armed bandit problem. In the problem, the learner interacts with an environment by choosing an action at each round, where a round is an instance of an interaction. In response, the environment reveals a reward, which is sampled from

Jonah S. Gannon, Anna Ferré-Mateu, Duncan A. Forbes, Jean P. Brodie

In order to help facilitate the future study of ultra-diffuse galaxies (UDGs) we compile a catalogue of their spectroscopic properties. Using it, we investigate some of the biases inherent in the current UDG sample that have been targeted for spectroscopy. In comparison to a larger sample of UDGs studied via their spectral energy distributions (SED), current

Wei He, Hanwu Li

In this paper, we study the backward stochastic differential equations driven by G-Brownian motion with double mean reflections, which means that the constraints are made on the law of the solution. Making full use of the backward Skorokhod problem with two nonlinear reflecting boundaries and the fixed-point theory, the existence and uniqueness of solutions

Shuma Kumamoto, Shuji Kijima, Tomoyuki Shirai

It is a celebrated fact that a simple random walk on an infinite $k$-ary tree for $k \geq 2$ returns to the initial vertex at most finitely many times during infinitely many transitions; it is called transient. This work points out the fact that a simple random walk on an infinitely growing $k$-ary tree can return to the initial vertex infinitely many times,

Rajpal Singh, Chandan Kumar Sah, Jishnu Keshavan

The discovery of linear embedding is the key to the synthesis of linear control techniques for nonlinear systems. In recent years, while Koopman operator theory has become a prominent approach for learning these linear embeddings through data-driven methods, these algorithms often exhibit limitations in generalizability beyond the distribution captured by tr

Alastair Darby, Fang Li, Zhi Lu

Inspired by the ideas and techniques used in the study of cluster algebras we construct a new class of algebras, called bistellar cluster algebras, from closed oriented triangulated even-dimensional manifolds by performing middle-dimensional bistellar moves. This class of algebras exhibit the algebraic behaviour of middle-dimensional bistellar moves but do n

Ayman Kachmar, Mikael Sundqvist

Starting from the Ginzburg--Landau model in a planar simply connected domain, with a local compactly supported applied magnetic field, we derive an effective model in the strong field limit, defined on a non-simply connected domain. The effective model features oscillations in the Little-Parks and Aharonov--Bohm spirit. We discuss also a similar question for

Jonah S. Gannon, Duncan A. Forbes, Aaron J. Romanowsky, Jean P. Brodie

We present spatially resolved Keck Cosmic Web Imager stellar spectroscopy of the Virgo cluster dwarf galaxies VCC 9 and VCC 1448. These galaxies have similar stellar masses and large half-light radii but very different globular cluster (GC) system richness ($\sim$25 vs. $\sim$99 GCs). Using the KCWI data, we spectroscopically confirm 10 GCs associated with V

Daniil I. Sarypov, Dmitriy A. Pokhabov, Arthur G. Pogosov, Evgeny Yu. Zhdanov

Electron transport in suspended and non-suspended GaAs point contacts (PCs) of different widths is experimentally studied. The superballistic contribution to the conductance, that demonstrates a distinctive quadratic dependence on the PC width and temperature growth, is extracted from the experiment. The studied PCs are shown to be described in the framework

Lukas Taus, Yen-Hsi Richard Tsai

Sensor placement optimization methods have been studied extensively. They can be applied to a wide range of applications, including surveillance of known environments, optimal locations for 5G towers, and placement of missile defense systems. However, few works explore the robustness and efficiency of the resulting sensor network concerning sensor failure or

Florian Beyer, Elliot Marshall, Todd A. Oliynyk

Using numerical methods, we examine, under a Gowdy symmetry assumption, the dynamics of nonlinearly perturbed FLRW fluid solutions of the Einstein-Euler-scalar field equations in the contracting direction for linear equations of state $p = K\rho$ and sound speeds $0\leq K<1/3$. This article builds upon the numerical work from \cite{BMO:2023} in which perturb

Lei Meng, Miao Miao Zhao, Yi Yang Xu, Chu Xin Peng

The microscopic origin of the remarkable optoelectronic properties of one of the most studied contemporary materials remains unclear. Here, we identify the existence of magnetic interactions between intermolecular proton orbitals in CH$_3$NH$_3$PbI$_3$ and CH$_3$NH$_3$PbBr$_3$. In particular, a unique sharp drop and a pronounced step-up discontinuity in the

Saieed Akbari, Irena M. Jovanović, Johnny Lim

Let $G_S$ be the graph obtained by attaching a self-loop at every vertex in $S \subseteq V(G)$ of a simple graph $G$ of order $n.$ In this paper, we explore several new results related to the line graph $L(G_S)$ of $G_S.$ Particularly, we show that every eigenvalue of $L(G_S)$ must be at least $-2,$ and relate the characteristic polynomial of the line graph

Yang Zhang, Shu-Guang Wu

Starting with the density field equation of a self-gravity fluid in a static Universe, using the Schwinger functional differentiation technique, we derive the field equation of the 4-point correlation function (4PCF) of galaxies in the Gaussian approximation, which contains hierarchically 2PCF and 3PCF. By use of the known solutions of 2PCF and 3PCF, the equ

Hao-Lan Xu

We study the scaling functions associated with the lightest particle mass $M_1$ in 2d Ising field theory in external magnetic field. The scaling functions depend on the scaling parameter $\xi = h/|m|^{\frac{15}{8}}$, or related parameter $\eta = m / h^{\frac{8}{15}}$. Analytic properties of $M_1$ in the high-T domain were discussed in arXiv:2203.11262. In th

Minhao Bai. Jinshuai Yang, Kaiyi Pang, Huili Wang, Yongfeng Huang

Linguistic steganography provides convenient implementation to hide messages, particularly with the emergence of AI generation technology. The potential abuse of this technology raises security concerns within societies, calling for powerful linguistic steganalysis to detect carrier containing steganographic messages. Existing methods are limited to finding

Hideto Nakashima

It is known that degrees of basic relative invariants of homogeneous open convex cones of rank $r$ are less than or equal to $2^{r-1}$. In this article, we show that there exists a homogeneous cone of rank $r$ one of whose basic relative invariants has degree $2^{r-1}$. The main idea for this is to construct such a homogeneous cone inductively to have specif

Samuel Bastida

It is well known that the class of transversal matroids is not closed under contraction or duality. In particular, after contracting a set of elements from a transversal matroid, the resulting matroid may or may not be transversal, and the computational complexity of determining whether it is transversal is not well understood. As a step toward resolving thi

Li Mingqian

The connotation of transaction costs has never been definitively determined, and the independence of the concept has never been rigorously demonstrated. This paper delves into the thought systems of several prominent economists in the development of transaction cost economics, starting from first-hand materials. By combining multiple works of the authors, it

Toshitaka Matsuki, Yusuke Sakemi, Kazuyuki Aihara

Chaos-based reinforcement learning (CBRL) is a method in which the agent's internal chaotic dynamics drives exploration. However, the learning algorithms in CBRL have not been thoroughly developed in previous studies, nor have they incorporated recent advances in reinforcement learning. This study introduced Twin Delayed Deep Deterministic Policy Gradients (

Usuf Rahaman, M. Ikram, Ishfaq A. Rather, Anisul Ain Usmani

The present study focuses on investigating the shape evolution of neutron-rich even-even Osmium (Os) transitional nuclei within the range of neutron number N = 82 to N = 190. The investigation is conducted using density-dependent meson-nucleon and point-coupling models within the framework of the covariant density functional theory (CDFT). Additionally, the

Valerian Callens, Zeeshan Meghji, Jan Gorzny

In this work we explore ways to restrict the ability to call Solidity smart contract functions for a specified duration. We describe methods to restrict functions from being called twice in the same transaction, block, or time period. This is related to the notion of non-reentrant functions, which are functions that can be called within a previous execution.

Jiamei Xiong, Xuefeng Yan, Yongzhen Wang, Wei Zhao

Haze severely degrades the visual quality of remote sensing images and hampers the performance of road extraction, vehicle detection, and traffic flow monitoring. The emerging denoising diffusion probabilistic model (DDPM) exhibits the significant potential for dense haze removal with its strong generation ability. Since remote sensing images contain extensi

Han-Tang Lin, Yen-Chen Pan, Abdurro'uf

Recent studies suggested that the ejecta velocity of Type Ia supernova (SN Ia) is a promising indicator in distinguishing the progenitor systems and explosion mechanisms. By classifying the SNe Ia based on their ejecta velocities, studies found SNe Ia with high Si II $\lambda$6355 velocities (HV SNe Ia; v>12000 km/s) tend to be physically different from thei

Hitoshi Yoshioka, Hirotada Hashimoto

This study developed an explainable AI for ship collision avoidance. Initially, a critic network composed of sub-task critic networks was proposed to individually evaluate each sub-task in collision avoidance to clarify the AI decision-making processes involved. Additionally, an attempt was made to discern behavioral intentions through a Q-value analysis and

Murat Bayraktar, Nuria González-Prelcic, Mikko Valkama, Hao Chen

In this paper, we propose a hybrid precoding/combining framework for communication-centric integrated sensing and full-duplex (FD) communication operating at mmWave bands. The designed precoders and combiners enable multiuser (MU) FD communication while simultaneously supporting monostatic sensing in a frequency-selective setting. The joint design of precode

Qinghao Mao, Yujie Wang, Walter Kob

Granular materials such as sand, powders, and food grains are ubiquitous in civil engineering, geoscience, agriculture, and medicine. While the influence of friction between the grains on the static structure of these systems is well understood, its impact on the dynamics is an open problem. Here we use particle-based simulations of a granular pack under cyc

Saeed Ranjbar Alvar, Ivan V. Bajić

Deep models produce a number of features in each internal layer. A key problem in applications such as feature compression for remote inference is determining how important each feature is for the task(s) performed by the model. The problem is especially challenging in the case of multi-task inference, where the same feature may carry different importance fo

Tejas Mirthipati

This study explores the enhancement of customer satisfaction in the airline industry, a critical factor for retaining customers and building brand reputation, which are vital for revenue growth. Utilizing a combination of machine learning and causal inference methods, we examine the specific impact of service improvements on customer satisfaction, with a foc

Chaiyong Ragkhitwetsagul, Veerakit Prasertpol, Natanon Ritta, Paphon Sae-Wong

At present, code recommendation tools have gained greater importance to many software developers in various areas of expertise. Having code recommendation tools has enabled better productivity and performance in developing the code in software and made it easier for developers to find code examples and learn from them. This paper proposes Typhon, an approach

Chaiyong Ragkhitwetsagul, Vipawan Jarukitpipat, Raula Gaikovina Kula, Morakot Choetkiertikul

Security vulnerabilities introduced by applications using third-party dependencies are on the increase, caused by the emergence of large ecosystems of libraries such as the NPM packages for JavaScript. Nowadays, libraries depend on each other. Relying on these large ecosystems thus means that vulnerable dependencies are not only direct but also indirect (tra

Haodong Yang, Zhe Zhang, Zhongling Huang

Most existing sparse representation-based approaches for attributed scattering center (ASC) extraction adopt traditional iterative optimization algorithms, which suffer from lengthy computation times and limited precision. This paper presents a solution by introducing an interpretable network that can effectively and rapidly extract ASC via deep unfolding. I

Junlei Wang, Shenfang Li, Daniil Yurchenko, Hongjun Zhu

This paper numerically investigates the influence of a fixed downstream control cylinder on the flow-induced vibration of an elastically-supported primary cylinder. These two cylinders are situated in a tandem arrangement with small dimensionless centre-to-centre spacing ($L/D$, $L$ is the intermediate spacing, and $D$ is the cylinder diameter). The present

Heesoo Shin, Seyed Morteza Habibi Khorasani, Zhaoyu Shi, Jiasheng Yang

Understanding the influence of surface roughness on drag forces remains a significant challenge in fluid dynamics. This paper presents a convolutional neural network (CNN) that predicts drag solely by the topography of rough surfaces and is capable of discovering spatial patterns linked to drag-inducing structures. A CNN model was developed to analyze spatia

Inhyeok Choi, Ilya Gekhtman, Wenyuan Yang, Tianyi Zheng

In this paper, we study the growth of confined subgroups through boundary actions of groups with contracting elements. We establish that the growth rate of a confined subgroup is strictly greater than half of the ambient growth rate in groups with purely exponential growth. Along the way, several results are obtained on the Hopf decomposition for boundary ac

Nicholas Milef, John Keyser, Shu Kong

Optical motion capture (mocap) requires accurately reconstructing the human body from retroreflective markers, including pose and shape. In a typical mocap setting, marker labeling is an important but tedious and error-prone step. Previous work has shown that marker labeling can be automated by using a structured template defining specific marker placements,

Satyabrata Patro, Anurag Tripathi

The inertial number-based rheology, popularly known as the JFP model, is well known for describing the rheology of granular materials in the dense flow regime. While most of the recent studies focus on the steady-state rheology of granular materials, the time-dependent rheology of such materials has received less attention. Owing to this fact, we perform thr

Lukas Kölsch

In this article, we present two new constructions for semifields of order $p^{2m}$. Together, the constructions unify and generalize around a dozen distinct semifield constructions, including both the oldest known construction by Dickson and the largest known construction in odd characteristic by Taniguchi. The constructions also provably yield many new semi

Zi-Yan Yang, Qian Wang, Wei Chen

The observation of the $T_{c\bar{s}}(2900)$ indicates the potential existence of strange double charm pentaquarks based on the heavy antidiquark symmetry. We systematically study the mass spectra of strange double charm pentaquarks with strangeness $S=-1$ in both molecular and compact structures for quantum numbers $J^{P}=1/2^{-}$, $3/2^{-}$, $5/2^{-}$. By c

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We present the first search for the leptonic decays $D^{*+}\to e^+\nu_e$ and $D^{*+}\to \mu^+\nu_\mu$ by analyzing a data sample of electron-positron collisions recorded with the BESIII detector at center-of-mass energies between 4.178 and 4.226 GeV, corresponding to an integrated luminosity of 6.32~fb$^{-1}$. No significant signal is observed. The upper lim

A. L. S. Santos Junior, J. C. de Carvalho Junior, M. Gil de Oliveira, E. V. S. Cubas

We develop a novel technique to measure small angular and lateral displacements of structured light beams. The technique relies on using high-order Hermite-Gaussian (HG) and Laguerre-Gaussian (LG) modes, which have well-defined symmetry under inversion. We show that the displacements of such fields lead to a crosstalk with modes with opposite parity under in

Lei Meng, Chen He, Wei Ji, Fei Yen

We observe sharp step-down discontinuities in the magnetic susceptibility of NH$_4$H$_2$PO$_4$ and NH$_4$H$_2$PO$_4$-$d$$_{60}$ (60% deuterated) along the $a$ and $c$-axes occurring exactly at their antiferroelectric transition temperatures. For the case of KH$_2$PO$_4$, less pronounced discontinuities occur at the ferroelectric transition temperature. To ex

Hsi-Wei Yen, Jonathan P. Williams, Jinshi Sai, Patrick M. Koch

The magnetic field of a molecular cloud core may play a role in the formation of circumstellar disks in the core. We present magnetic field morphologies in protostellar cores of 16 targets in the Atacama Large Millimeter/submillimeter Array large program "Early Planet Formation in Embedded Disks (eDisk)", which resolved their disks with 7 au resolutions. The

Emilian Postolache, Natalia Polouliakh, Hiroaki Kitano, Akima Connelly

In this article, we explore the potential of using latent diffusion models, a family of powerful generative models, for the task of reconstructing naturalistic music from electroencephalogram (EEG) recordings. Unlike simpler music with limited timbres, such as MIDI-generated tunes or monophonic pieces, the focus here is on intricate music featuring a diverse

Tsuyoshi Idé, Jokin Labaien, Pin-Yu Chen

We propose a new positional encoding method for a neural network architecture called the Transformer. Unlike the standard sinusoidal positional encoding, our approach is based on solid mathematical grounds and has a guarantee of not losing information about the positional order of the input sequence. We show that the new encoding approach systematically impr

Hans G. Feichtinger, Masaharu Kobayashi, Enji Sato

This paper discusses spectral synthesis for those modulation spaces $M^{p,q}_s({\mathbf R}^n)$ which form Banach algebras under pointwise multiplication. An important argument will be the ``ideal theory for Segal algebras'' by H. Reiter [15]. This paper is a continuation of our paper [5] where the case $q=1$ is treated. As a by-product we obtain a variant of

Bao Nguyen, Arianna Formenti, Remi Lehe, Jean-Luc Vay

As part of the Snowmass'21 planning exercise, the Advanced Accelerator Concepts community proposed developing multi-TeV linear colliders and considered beam-beam effects for these machines. Such colliders operate under a high disruption regime with an enormous number of electron-positron pairs produced from QED effects. Thus, it requires a self-consistent tr

Haomiao Sun, Mingjie He, Shiguang Shan, Hu Han

Although face analysis has achieved remarkable improvements in the past few years, designing a multi-task face analysis model is still challenging. Most face analysis tasks are studied as separate problems and do not benefit from the synergy among related tasks. In this work, we propose a novel task-adaptive multi-task face analysis method named as Q-Face, w

Hans G. Feichtinger, Masaharu Kobayashi, Enji Sato

In this paper, we give some properties of the modulation spaces $M_s^{p,1}({\mathbf R}^n)$ as commutative Banach algebras. In particular, we show the Wiener-L\'evy theorem for $M^{p,1}_s({\mathbf R}^n)$, and clarify the sets of spectral synthesis for $M^{p,1}_s ({\mathbf R}^n)$ by using the ``ideal theory for Segal algebras'' developed in Reiter [30].The inc