May 2023 arXiv papers — page 164

Wenwu Jiang, Ting Liang, Jianbin Xu, Wengen Ouyang

Thermal transport property of homogeneous twisted molybdenum disulfide (MoS$_2$) is investigated using non-equilibrium molecular dynamics simulations with the state-of-art force fields. The simulation results demonstrate that the cross-plane thermal conductivity strongly depends on the interfacial twist angle, while it has only a minor effect on the in-plane

Amrita Ghosh, Mugdha Sarkar

We study a system of hard-core bosons on a two-dimensional periodic honeycomb lattice subjected to an on-site potential with alternating signs along $y$-direction, using machine learning (ML) techniques. The model hosts a rich phase diagram consisting of six different phases including a charge density wave, a superfluid phase and two dimer insulator phases,

Zihao Wang, Weizhi Fei, Hang Yin, Yangqiu Song

Answering complex queries on knowledge graphs is important but particularly challenging because of the data incompleteness. Query embedding methods address this issue by learning-based models and simulating logical reasoning with set operators. Previous works focus on specific forms of embeddings, but scoring functions between embeddings are underexplored. I

David Garofalo

The link between black holes and star formation allows us to draw a connection between black holes and the places and times extraterrestrial intelligences (ETIs) had a greater chance of emerging. Within the context of the gap paradigm for black holes, we show that denser cluster environments that led to gas rich mergers and copious star formation were places

Kechi Zhang, Huangzhao Zhang, Ge Li, Jia Li

Automatically generating source code from natural language descriptions has been a growing field of research in recent years. However, current large-scale code generation models often encounter difficulties when selecting appropriate APIs for specific contexts. These models may generate APIs that do not meet requirements or refer to non-existent APIs in thir

Mahender Kumar

Key escrow refers to storing a copy of a cryptographic key with a trusted third party, typically a government agency or some other organization. Key escrow aims to ensure that law enforcement agencies can access encrypted data when necessary, for example, in criminal investigations or national security matters. However, key escrow also raises concerns about

Zhengyu Hua, Bowen Xu, Li Xing, Fengyu Quan

Aerial manipulators are composed of an aerial multi-rotor that is equipped with a 6-DOF servo robot arm. To achieve precise position and attitude control during the arm's motion, it is critical for the system to have high performance control capabilities. However, the coupling effect between the multi-rotor UAVs' movement poses a challenge to the entire syst

Regina Schuster, Laura Koesten, Kathleen Gregory, Torsten Möller

How do different audiences make sense of climate change data visualizations and what do they take away as a main message? To investigate this question, we are building on the results of a previous study, focusing on expert opinions regarding public climate change communication and the role of data visualizations. Hereby, we conducted semi-structured intervie

Georgy Gordeev, Lucas Lafeta, Benjamin Scott Flavel, Ado Jorio

In this work we investigate the role of exciton resonances in coherent anti-Stokes Raman scattering (er-CARS) in single walled carbon nanotubes (SWCNTs). We drive the nanotube system in simultaneous phonon and excitonic resonances, where we observe a superior enhancement by orders of magnitude exceeding non-resonant cases. We investigated the resonant effect

Dionysios Karagiannis, Roy Maartens, José Fonseca, Stefano Camera

The power spectrum and bispectrum of dark matter tracers are key and complementary probes of the Universe. Next-generation surveys will deliver good measurements of the bispectrum, opening the door to improved cosmological constraints and the breaking of parameter degeneracies, from the combination of the power spectrum and bispectrum. Multi-tracer power spe

Ameya Pore, Zhen Li, Diego Dall'Alba, Albert Hernansanz

Increased demand for less invasive procedures has accelerated the adoption of Intraluminal Procedures (IP) and Endovascular Interventions (EI) performed through body lumens and vessels. As navigation through lumens and vessels is quite complex, interest grows to establish autonomous navigation techniques for IP and EI for reaching the target area. Current re

Siyuan Li, Yongpan Wang, Chaopeng Dong, Shouguo Yang

Third-party libraries (TPLs) are extensively utilized by developers to expedite the software development process and incorporate external functionalities. Nevertheless, insecure TPL reuse can lead to significant security risks. Existing methods are employed to determine the presence of TPL code in the target binary. Existing methods, which involve extracting

Changmin Kim, Young Sun Lee, Timothy C. Beers, Young Kwang Kim

The second generation of stars in the GCs of the MW exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range -3.0 < [Fe/H] < 0.0 from a sa

Qin Li, Li Wang, Yunan Yang

Most inverse problems from physical sciences are formulated as PDE-constrained optimization problems. This involves identifying unknown parameters in equations by optimizing the model to generate PDE solutions that closely match measured data. The formulation is powerful and widely used in many sciences and engineering fields. However, one crucial assumption

Mohamed A. Abed, Anton A. Babaev, Leonid G. Sukhikh

Luminosity is the key quantity characterizing the performance of charged particle colliders. Precise luminosity determination is an important task in collider physics. Part of this task is the proper calibration of detectors dedicated for luminosity measurements. The wide-used experi-mental method of calibration is the van-der-Meer scan, which is the beam se

Han Xiao, Xiaoyan Hu, Pengcheng Mu, Wenjie Wang

This paper investigates the multi-antenna covert communications assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In particular, to shelter the existence of covert communications between a multi-antenna transmitter and a single-antenna receiver from a warden, a friendly full-duplex receiver with two anten

Hao Wu, Jian Yan, Linling Kuang

The emergence of new applications brings multi-class traffic with diverse quality of service (QoS) requirements to wide area networks (WANs), motivating research in traffic engineering (TE). In recent years, novel centralized and hierarchical TE schemes have used heuristic or machine learning techniques to orchestrate resources in closed systems such as data

Xiaoxuan Zhang, Zengfu Wang, Kun Lu, Quan Pan

Deep convolutional neural network has made great achievements in sea-land clutter classification for over-the-horizon-radar (OTHR). The premise is that a large number of labeled training samples must be provided for a sea-land clutter classifier. In practical engineering applications, it is relatively easy to obtain label-free sea-land clutter samples. Howev

S. I. Dimitrov

In this paper we study the distribution of consecutive square-free numbers of the forms $x^2+y^2+z+1$, $x^2+y^2+z+2$ and $x^2+y^2+z^2+z+1$, $x^2+y^2+z^2+z+2$, respectively. We establish asymptotic formulas for each of these two cases.

Alain Bensoussan, Ho Man Tai, Sheung Chi Phillip Yam

In this article, we provide an original systematic global-in-time analysis of mean field type control problems on $\mathbb{R}^n$ with generic cost functionals by the modified approach but not the same, firstly proposed in [7], as the ``lifting'' idea introduced by P. L. Lions. As an alternative to the recent popular analytical method by tackling the master e

Mehrana R. Nejad, Julia M. Yeomans

We use numerical simulations and linear stability analysis to study active nematic droplets, in the regime where the passive phase is isotropic. We show that activity leads to the emergence of nematic order and of spontaneous rotation in both two and three dimensions. In 2D the rotation is caused by the formation of a chiral $+1$ defect at the center of the

Wanli Xing, Shijie Lin, Lei Yang, Jia Pan

Calibrating the extrinsic parameters of sensory devices is crucial for fusing multi-modal data. Recently, event cameras have emerged as a promising type of neuromorphic sensors, with many potential applications in fields such as mobile robotics and autonomous driving. When combined with LiDAR, they can provide more comprehensive information about the surroun

Shangying Feng, Tian Liang

Let $\Omega$ be a bounded domain in $\mathbb{R}^n$ with $n\ge2$ and $s\in(0,1)$. Assume that $\phi : [0, \infty) \to [0, \infty)$ be a Young function obeying the doubling condition with the constant $K_\phi<2^{\frac{n}{s}}$. We demonstrate that $\Omega $ supports a $(\phi_\frac{n}{s}, \phi)$-Poincar\'e inequality if it is is a John domain. Alternately, assum

Gianguido Dall'Agata, Nikolaos Liatsos, Ruggero Noris, Mario Trigiante

We present the full Lagrangian and supersymmetry transformation rules for the gauged D=4, N=4 (half-maximal) supergravity coupled to an arbitrary number of vector multiplets. Using the embedding tensor formulation, the final results are universal and valid in arbitrary symplectic frames. We also analyze the conditions for the critical points of the scalar po

Gabriel J. Man, Aleksandr Kalinko, Dibya Phuyal, Pabitra K. Nayak

Point defect tolerance in materials, which extends operational lifetime, is essential for societal sustainability, and the creation of a framework to design such properties is a grand challenge in the material sciences. Using three prototypical lead bromide perovskites in single crystal form and high-resolution synchrotron-based X-ray spectroscopy, we reveal

T. Martinic-Bilac, S. Meljanac, S. Mignemi

The Yang model is an example of noncommutative geometry on a background spacetime of constant curvature. We discuss the Hermitian realizations of its associated algebra on phase space in a perturbative expansion up to sixth order. We also discuss its realizations on extended phase spaces, that include additional tensorial and/or vectorial degrees or freedom.

Gaolin Li, Chong Shen, Kaiyun Wang, Xiaoyong Xi

A topological space has a domain model if it is homeomorphic to the maximal point space $\mbox{Max}(P)$ of a domain $P$. Lawson proved that every Polish space $X$ has an $\omega$-domain model $P$ and for such a model $P$, $\mbox{Max}(P)$ is a $G_{\delta}$-set of the Scott space of $P$. Martin (2003) then asked whether it is true that for every $\omega$-domai

Spiros Cotsakis, Jose P. Mimoso, John Miritzis

We propose a new formulation of $f(R)$ gravity, dubbed scalarized $f(R)$ gravity, in which the Legendre transform is included as a dynamical term. This leads to a theory with second-order field equations that describes general relativity with a self-interacting scalar field, without requiring the introduction of conformal frames. We demonstrate that the quad

Fu-Lin Li, Yu Liu, Xiao Fan, Mao-Kai Hu

Astrophysical events that occur in active galactic nucleus (AGN) disks are believed to differ significantly from the ordinary in the interstellar medium. We show that stars located in the outer region of the AGN disk would explode near the original migration starting points instead of being accreted by the central supermassive black hole due to the effect of

Khiem Hong Phan, Dzung Tri Tran, Anh Thu Nguyen

We present analytic results for one-loop radiative corrections to off-shell decay $H^* \rightarrow W^+W^-$ in 't Hooft-Veltman gauge within Standard Model framework. In numerical results, we show off-shell decay rate and its corrections with varying off-shell Higgs mass. The results show that the corrections are of $10\%$ contributions to total decay rates.

Geoff Keeling

The technical landscape of clinical machine learning is shifting in ways that destabilize pervasive assumptions about the nature and causes of algorithmic bias. On one hand, the dominant paradigm in clinical machine learning is narrow in the sense that models are trained on biomedical datasets for particular clinical tasks such as diagnosis and treatment rec

Weijia Wang, Xuequan Lu, Di Shao, Xiao Liu

Existing normal estimation methods for point clouds are often less robust to severe noise and complex geometric structures. Also, they usually ignore the contributions of different neighbouring points during normal estimation, which leads to less accurate results. In this paper, we introduce a weighted normal estimation method for 3D point cloud data. We inn

Mekia Shigute Gaso, Selcuk Cankurt, Abdulhamit Subasi

We have implemented a deep learning model with L2 regularization and trained it on Electromyography (EMG) data. The data comprises of EMG signals collected from control group, myopathy and ALS patients. Our proposed deep neural network consists of eight layers; five fully connected, two batch normalization and one dropout layers. The data is divided into tra

A. V. Lipatov, M. A. Malyshev

An earlier developed $k_T$-factorization framework to calculate the associated prompt photon and hadronic jets production cross sections at high energies is extended now to the electron-proton deep inelastic scattering. The proposed method is based on joint usage of the PEGASUS and CASCADE Monte-Carlo event generators, which deal with the transverse momentum

Tsz Yan Leung, Miguel Xochicale

In this paper, we present a simple framework of skill transfer learning for robotic ultrasound-guidance procedures. We briefly review challenges in skill transfer learning for robotic ultrasound-guidance procedures. We then identify the need of appropriate sampling techniques, computationally efficient neural networks models that lead to the proposal of a si

Marco Casadio, Luca Arnaboldi, Matthew L. Daggitt, Omri Isac

Verification of machine learning models used in Natural Language Processing (NLP) is known to be a hard problem. In particular, many known neural network verification methods that work for computer vision and other numeric datasets do not work for NLP. Here, we study technical reasons that underlie this problem. Based on this analysis, we propose practical m

L. T. Hue, Dzung Tri Tran, Thanh Huy Nguyen, Khiem Hong Phan

A systematic study of one-loop contributions to the decay channels $h\rightarrow l\bar{l}\gamma$ with $l=\nu_{e,\mu, \tau}, e, \mu$, performed in Higgs extended versions of the Standard Model, is presented in the 't Hooft-Veltman gauge. Analytic formulas for one-loop form factors are expressed in terms of the logarithm and di-logarithmic functions. As a resu

Seungwoo Lee, Chaerin Kong, Donghyeon Jeon, Nojun Kwak

Recent advances in diffusion models have showcased promising results in the text-to-video (T2V) synthesis task. However, as these T2V models solely employ text as the guidance, they tend to struggle in modeling detailed temporal dynamics. In this paper, we introduce a novel T2V framework that additionally employ audio signals to control the temporal dynamics

Sz. Kálmán, A. Derekas, Sz. Csizmadia, Gy. M. Szabó

Close-in, sub-stellar companions to $\delta$ Scuti type stars present a highly suitable testbed for examining how planetary-mass objects can influence stellar pulsations. We aim to constrain the mass of HD 31221 b, probe its atmosphere, and demonstrate how it affects the pulsational pattern of its host, HD 31221. We made use of the available data from the sh

G. W. Forbes, Miguel A. Alonso

Asymptotic expansions are presented for the moments of bound states in one-dimensional anharmonic potentials. The results are derived by using the SAFE method and include only the first non-zero wave-related correction to the familiar semi-classical approximation. Application to a couple of widely studied potentials that do not permit closed-form solutions i

Wen Chang

We give a geometric model for any algebraic heart in the derived category of a gentle algebra, which is equivalent to the module category of some gentle algebra. To do this, we deform the geometric model for the module category of a gentle algebra given in [BC21], and then embed it into the geometric model of the derived category given in [OPS18], in the sen

Xin Lin, Jingtong Yue, Sixian Ding, Chao Ren

Rain in the dark poses a significant challenge to deploying real-world applications such as autonomous driving, surveillance systems, and night photography. Existing low-light enhancement or deraining methods struggle to brighten low-light conditions and remove rain simultaneously. Additionally, cascade approaches like ``deraining followed by low-light enhan

Jassem Abbasi, Pål Østebø Andersen

The application of Physics-Informed Neural Networks (PINNs) is investigated for the first time in solving the one-dimensional Countercurrent spontaneous imbibition (COUCSI) problem at both early and late time (i.e., before and after the imbibition front meets the no-flow boundary). We introduce utilization of Change-of-Variables as a technique for improving

G. Abbas, R. H. Ali

In this paper, we study thermodynamics, thermal fluctuations, phase transitions and the charged anti-de Sitter black hole surrounded by perfect fluid dark matter. Large black holes are shown to be stable when subject to thermal fluctuations, and we begin by exploring how these fluctuations affect the uncorrected thermodynamic quantities of entropy, Helmholtz

Shiyi Jiang, Jianqiang Cheng, Kai Pan, Zuo-Jun Max Shen

Moment-based distributionally robust optimization (DRO) provides an optimization framework to integrate statistical information with traditional optimization approaches. Under this framework, one assumes that the underlying joint distribution of random parameters runs in a distributional ambiguity set constructed by moment information and makes decisions aga

Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu

Recently, a series of pioneer studies have shown the potency of pre-trained models in sequential recommendation, illuminating the path of building an omniscient unified pre-trained recommendation model for different downstream recommendation tasks. Despite these advancements, the vulnerabilities of classical recommender systems also exist in pre-trained reco

Nozomi Akashi, Yasuo Kuniyoshi, Taketomo Jo, Mitsuhiro Nishida

Harnessing complex body dynamics has been a long-standing challenge in robotics. Soft body dynamics is a typical example of high complexity in interacting with the environment. An increasing number of studies have reported that these dynamics can be used as a computational resource. This includes the McKibben pneumatic artificial muscle, which is a typical s

Takuma Izumi, Keiichi Wada, Masatoshi Imanishi, Kouichiro Nakanishi

Active galaxies contain a supermassive black hole at their center, which grows by accreting matter from the surrounding galaxy. The accretion process in the central ~10 parsecs has not been directly resolved in previous observations, due to the small apparent angular sizes involved. We observed the active nucleus of the Circinus Galaxy using sub-millimeter i

Xu'an Dou, Fanhao Kong, Weijun Xu, Zhennan Zhou

The voltage-conductance kinetic equation for an ensemble of neurons has been studied by many scientists and mathematicians, while its rigorous analysis is still at a premature stage. In this work, we obtain for the first time the exponential convergence to the steady state of this kinetic model in the linear setting. Our proof is based on a probabilistic ref

Han Xiao, Xiaoyan Hu, Pengcheng Mu, Wenjie Wang

This paper investigates the multi-antenna covert communications assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). In particular, to shelter the existence of communications between transmitter and receiver from a warden, a friendly full-duplex receiver with two antennas is leveraged to make contributions t

Daria S. Roshal, Karim Azzag, Kirill K. Fedorenko, Sergei B. Rochal

During embryonic development, structures with complex geometry can emerge from planar epithelial monolayers and to study these shape transitions is of key importance for revealing the biophysical laws involved in the morphogenesis of biological systems. Here, using the example of normal proliferative monkey kidney (COS) cell monolayers, we investigate global

Yaohui Wang, Xin Ma, Xinyuan Chen, Cunjian Chen

Spatio-temporal coherency is a major challenge in synthesizing high quality videos, particularly in synthesizing human videos that contain rich global and local deformations. To resolve this challenge, previous approaches have resorted to different features in the generation process aimed at representing appearance and motion. However, in the absence of stri

Simone Dovetta

We investigate the asymptotic behaviour of nonlinear Schr\"odinger ground states on $d$-dimensional periodic metric grids in the limit for the length of the edges going to zero. We prove that suitable piecewise-affine extensions of such states converge strongly in $H^1(\mathbb{R}^d)$ to the corresponding ground states on $\mathbb{R}^d$. As an application of

Zhoujian Sun, Chenyang Zhao, Zhengxing Huang, Nai Ding

Policy learning (PL) is a module of a task-oriented dialogue system that trains an agent to make actions in each dialogue turn. Imitating human action is a fundamental problem of PL. However, both supervised learning (SL) and reinforcement learning (RL) frameworks cannot imitate humans well. Training RL models require online interactions with user simulators

Md. Shafiul Alam, Bijan Krishna Saha, Chinmayee Podder

For a triangle group $G$, the $G$-automorphic function is the inverse of Schwarz triangle function. In this paper, we compute the first derivative of the $G$-automorphic function for the triangle group $G$ in terms of the Gaussian hypergeometric function.

Sayan Bandyapadhyay, William Lochet, Saket Saurabh, Jie Xue

We revisit a natural variant of geometric set cover, called minimum-membership geometric set cover (MMGSC). In this problem, the input consists of a set $S$ of points and a set $\mathcal{R}$ of geometric objects, and the goal is to find a subset $\mathcal{R}^*\subseteq\mathcal{R}$ to cover all points in $S$ such that the \textit{membership} of $S$ with respe

François Gay-Balmaz, Vakhtang Putkaradze

If a porous media is being damaged by excessive stress, the elastic matrix at every infinitesimal volume separates into a 'solid' and a 'broken' component. The 'solid' part is the one that is capable of transferring stress, whereas the 'broken' part is advecting passively and is not able to transfer the stress. In previous works, damage mechanics was address

Yang Wu, Zhibin Liu, Hefeng Wu, Liang Lin

In this paper, we study video synthesis with emphasis on simplifying the generation conditions. Most existing video synthesis models or datasets are designed to address complex motions of a single object, lacking the ability of comprehensively understanding the spatio-temporal relationships among multiple objects. Besides, current methods are usually conditi

Yu Cheng Hung, Ping Hung Chen, Jian Jiun Ding

Pitch estimation is to estimate the fundamental frequency and the midi number and plays a critical role in music signal analysis and vocal signal processing. In this work, we proposed a new architecture based on a learning-based enhancement preprocessor and a combination of several traditional and deep learning pitch estimation methods to achieve better pitc

Beiduo Chen, Shaohan Huang, Zihan Zhang, Wu Guo

ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing performance, ELECTRA still faces the challenges of monotonous training and deficient interaction. Generator with only masked language modeling (MLM) leads to biased learning and label imb

Ruijia Wu, Yuhang Wang, Huafeng Shi, Zhipeng Yu

Denoising diffusion models have shown remarkable potential in various generation tasks. The open-source large-scale text-to-image model, Stable Diffusion, becomes prevalent as it can generate realistic artistic or facial images with personalization through fine-tuning on a limited number of new samples. However, this has raised privacy concerns as adversarie

Yuxing Zhong, Akio K. Inoue, Yuma Sugahara, Kana Morokuma-Matsui

Radio-loud active galactic nuclei (RLAGNs) are rare among AGN populations. Lacking high-resolution and high-frequency observations, their structure and evolution stages are not well understood at high redshifts. In this work, we report ALMA 237 GHz continuum observation at $0.023''$ resolution and VLA 44 GHz continuum observation at $0.08''$ resolution of th

Sanefumi Moriyama, Tomoki Nosaka

We investigate partition functions of the circular-quiver supersymmetric Chern-Simons theory which corresponds to the q-deformed Painleve VI equation. From the partition functions with the lowest rank vanishing, where the circular quiver reduces to a linear one, we find 40 bilinear relations. The bilinear relations extend naturally to higher ranks if we rega

Da Ren, Yi Cai, Qing Li

Generative Adversarial Networks (GANs) have been studied in text generation to tackle the exposure bias problem. Despite their remarkable development, they adopt autoregressive structures so suffering from high latency in both training and inference stages. Although GANs have potential to support efficient generation by adopting non-autoregressive (NAR) stru

Q. Y. Liu, X. Z. Er, Z. H. Fan, D. Z. Liu

The weak gravitational lensing is a powerful tool in modern cosmology. To accurately measure the weak lensing signal, one has to control the systematic bias to a small level. One of the most difficult problems is how to correct the smearing effect of the Point Spread Function (PSF) on the shape of the galaxies. The chromaticity of PSF for a broad-band observ

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

Quantum-correlated $D\bar{D}$ pairs collected by the BESIII experiment at the $\psi(3770)$ resonance, corresponding to an integrated luminosity of 2.93 fb$^{-1}$, are used to study the $D^0 \rightarrow K^{0}_S\pi^{+} \pi^{-} \pi^{0}$ decay mode. The $C\!P$-even fraction of $D^0 \rightarrow K^{0}_S\pi^{+} \pi^{-} \pi^{0}$ decays is determined to be $0.235\pm

Debajyoti Choudhuri, Dušan D. Repovš, Kamel Saoudi

Using variational methods, we establish the existence of infinitely many solutions to an elliptic problem driven by a Choquard term and a singular nonlinearity. We further show that if the problem has a positive solution, then it is bounded a.e. in the domain $\Omega$ and is H\"{o}lder continuous.

Chunkit Chan, Xin Liu, Jiayang Cheng, Zihan Li

Implicit Discourse Relation Recognition (IDRR) is a sophisticated and challenging task to recognize the discourse relations between the arguments with the absence of discourse connectives. The sense labels for each discourse relation follow a hierarchical classification scheme in the annotation process (Prasad et al., 2008), forming a hierarchy structure. Mo

Zida Cheng, Chen Ju, Shuai Xiao, Xu Chen

The rise of multi-modal search requests from users has highlighted the importance of multi-modal retrieval (i.e. image-to-text or text-to-image retrieval), yet the more complex task of image-to-multi-modal retrieval, crucial for many industry applications, remains under-explored. To address this gap and promote further research, we introduce and define the c

Jie Ma, Pinghui Wang, Zewei Wang, Dechen Kong

Question answering methods are well-known for leveraging data bias, such as the language prior in visual question answering and the position bias in machine reading comprehension (extractive question answering). Current debiasing methods often come at the cost of significant in-distribution performance to achieve favorable out-of-distribution generalizabilit

Yuxiang Zhang, Junjie Wang, Xinyu Zhu, Tetsuya Sakai

Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP). Notably, recent NER research focuses on utilizing massive extra data, including pre-training corpora and incorporating search engines. However, these methods suffer from high costs associated with data collect

Maojun Zhang, Yang Li, Dongzhu Liu, Richeng Jin

Federated edge learning (FEEL) is a popular distributed learning framework for privacy-preserving at the edge, in which densely distributed edge devices periodically exchange model-updates with the server to complete the global model training. Due to limited bandwidth and uncertain wireless environment, FEEL may impose heavy burden to the current communicati

L. Gambera, S. A. Marano, D. Motreanu

In this paper, we consider a quasi-linear Dirichlet system with possible competing $(p,q)$-Laplacians and convections. Due to the lack of ellipticity, monotonicity, and variational structure, the standard approaches to the existence of weak solutions cannot be adopted. Nevertheless, through an approximation procedure and a corollary of Brouwer's fixed point

Kanji Itoh, Yusuke Masaki, Hiroaki Matsueda

We study the quantum energy teleportation in a four-spin one-dimensional Heisenberg model. A local magnetic field is applied at the edge sites to control the degree of the ground-state entanglement. In the teleportation protocol, an energy sender performs a projective measurement at one edge site, while an energy receiver performs a feedback control at the o

Shipeng Ji, Yang Li, Ruizhi Fu, Jiabao Wang

As deep learning applications extensively increase by leaps and bounds, their interpretability has become increasingly prominent. As a universal property, chirality exists widely in nature, and applying it to the explanatory research of deep learning may be helpful to some extent. Inspired by a recent study that used CNN (convolutional neural network), which

Charles Elbar, Alexandre Poulain

We propose a new generalized compressible diphasic Navier-Stokes Cahn-Hilliard model that we name G-NSCH. This new G-NSCH model takes into account important properties of diphasic compressible fluids such as possible non-matching densities and contrast in mechanical properties (viscosity, friction) between the two phases of the fluid. the model also comprise

Zeynab Chitsazian, Saeed Sedighian Kashi, Amin Nikanjam

In the context of Just-In-Time Software Defect Prediction (JIT-SDP), Concept drift (CD) can occur due to changes in the software development process, the complexity of the software, or changes in user behavior that may affect the stability of the JIT-SDP model over time. Additionally, the challenge of class imbalance in JIT-SDP data poses a potential risk to

Zhiqiang Huang

Entropy production and the detailed fluctuation theorem are of fundamental importance for thermodynamic processes. In this paper, we study the multiple entropy production for multitime quantum processes in a unified framework. For closed quantum systems and Markovian open quantum systems, the given entropy productions all satisfy the detailed fluctuation rel

Yueshan Xiong, Haozhi Zeng

The notation of torus manifolds were introduced by A. Hattori and M. Masuda. Toric manifolds, quasitoric manifolds, topological toric manifolds, toric origami manifolds and $b$-symplectic toric manifolds are typical examples of torus manifolds with locally standard action. Recently, L. Yu introduced a nice notion topological face ring $\mathbf{k}[Q]$, a gene

Ye Sang, Yujin Huang, Shuo Huang, Helei Cui

The increasing popularity of deep learning (DL) models and the advantages of computing, including low latency and bandwidth savings on smartphones, have led to the emergence of intelligent mobile applications, also known as DL apps, in recent years. However, this technological development has also given rise to several security concerns, including adversaria

Midas Segers, Aderik Voorspoels, Takahiro Sakaue, Enrico Carlon

Proteins often regulate their activities via allostery - or action at a distance - in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at di

Vaishnavi Kateel, Viola Krizakova, Siddharth Rao, Kaiming Cai

Current-induced spin-orbit torques (SOTs) enable fast and efficient manipulation of the magnetic state of magnetic tunnel junctions (MTJs), making it attractive for memory, in-memory computing, and logic applications. However, the requirement of the external magnetic field to achieve deterministic switching in perpendicular magnetized SOT-MTJs limits its imp

Julian Neuberger, Lars Ackermann, Stefan Jablonski

Process-aware information systems offer extensive advantages to companies, facilitating planning, operations, and optimization of day-to-day business activities. However, the time-consuming but required step of designing formal business process models often hampers the potential of these systems. To overcome this challenge, automated generation of business p

Sipra Mohapatra, Sougata Halder, Sachin R. Chaudhary, Roland R. Netz

We investigate the effect of pectin on the structure and ion transport properties of the room-temperature ionic liquid electrolyte 1-n-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6]) using molecular dynamics simulations. We find that pectin induces intriguing structural changes in the electrolyte that disrupt large ionic aggregates and promote th

Shoji Yamamoto, Jun Ohara

We construct modified spin-wave thermodynamics for frustrated noncollinear antiferromagnets for the first time. The well-known modified spin-wave theory for collinear antiferromagnets diagonalizes a bosonic Hamiltonian subject to the constraint that the total staggered magnetization be zero. Applying this scheme as it is to frustrated noncollinear antiferrom

Yuliang Li, Mingliang Chen, Jinquan Qi, Chenjin Deng

Underwater ghost imaging is an effective means of underwater detection. In this paper, a theoretical and experimental study of underwater ghost imaging is carried out by combining the description of underwater optical field transmission with the inherent optical parameters of the water body. This paper utilizes the Wells model and the approximate S-S scatter

Sanghyun Kim, Jiwon Seo

In urban areas, dense buildings frequently block and reflect global positioning system (GPS) signals, resulting in the reception of a few visible satellites with many multipath signals. This is a significant problem that results in unreliable positioning in urban areas. If a signal reception condition from a certain satellite can be detected, the positioning

Yuan-An Xiao, Chenyang Yang, Bo Wang, Yingfei Xiong

Long patch validation time is a limiting factor for automated program repair (APR). Though the duality between patch validation and mutation testing is recognized, so far there exists no study of systematically adapting mutation testing techniques to general-purpose patch validation. To address this gap, we investigate existing mutation testing techniques an

Matej Cief, Jacek Golebiowski, Philipp Schmidt, Ziawasch Abedjan

Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy. OPE is a viable alternative to running expensive online A/B tests: it can speed up the development of new policies, and reduces the risk of exposing customers to suboptimal treatments. However, when the number of a

Xu Chen, Zida Cheng, Shuai Xiao, Xiaoyi Zeng

Data sparsity is an important issue for click-through rate (CTR) prediction, particularly when user-item interactions is too sparse to learn a reliable model. Recently, many works on cross-domain CTR (CDCTR) prediction have been developed in an effort to leverage meaningful data from a related domain. However, most existing CDCTR works have an impractical li

Longfei Fang, Yanhua Zhao

Let $C_{\ell}$ be the cycle of order ${\ell}$. The square of $C_{\ell}$, denoted by $C_{\ell}^2$, is obtained by joining all pairs of vertices with distance no more than two in $C_{\ell}$. A graph is called $F$-free if it does not contain $F$ as a subgraph. Denote by $ex(n,F)$ and $spex(n,F)$ the maximum size and spectral radius over all $n$-vertex $F$-free

William Craig, Wissam Raji

We consider the period polynomials $r_f(z)$ associated with cusp forms $f$ of weight $k$ on all of $\mathrm{SL}_2\left( \mathbb{Z} \right)$, which are generating functions for the critical $L$-values of the modular $L$-function associated to $f$. In 2014, El-Guindy and Raji proved that if $f$ is an eigenform, then $r_f(z)$ satisfies a ``Riemann hypothesis" i

Shengyao Zhuang, Linjun Shou, Guido Zuccon

Effective cross-lingual dense retrieval methods that rely on multilingual pre-trained language models (PLMs) need to be trained to encompass both the relevance matching task and the cross-language alignment task. However, cross-lingual data for training is often scarcely available. In this paper, rather than using more cross-lingual data for training, we pro

Fan Zhang, Mei Tu, Sangha Kim, Song Liu

Most multi-domain machine translation models rely on domain-annotated data. Unfortunately, domain labels are usually unavailable in both training processes and real translation scenarios. In this work, we propose a label-free multi-domain machine translation model which requires only a few or no domain-annotated data in training and no domain labels in infer

Haoren Xiong

We study Toeplitz operators on the Bargmann space, whose Toeplitz symbols are exponentials of complex inhomogeneous quadratic polynomials. Extending a result by Coburn--Hitrik--Sj\"{o}strand, we show that the boundedness of such Toeplitz operators implies the boundedness of the corresponding Weyl symbols, thus completing the proof of the Berger--Coburn conje

Sourav Dutta, Sunanda, Reetanjali Moharana, Manish Kumar

Gamma-ray bursts (GRBs) can be classified with their linearly dependent parameters alongside the standard $T_{90}$ distribution. The Generalized linear mixture model(GLM) identifies the number of linear dependencies in a two-parameter space. Classically, GRBs are classified into two classes by the presence of bimodality in the histogram of T$_{90}$. However,

Kalpesh Ghag, Anil Raghav, Ankush Bhaskar, Shirish Soni

Interplanetary Coronal Mass Ejections (ICMEs) are prominent drivers of space weather disturbances and mainly lead to intense or extreme geomagnetic storms. The reported studies suggested that the planar ICME sheath and planar magnetic clouds (MCs) cause extreme storms. Here, we investigated the severe two-step geomagnetic storm ($Dst \sim -187$ nT) of 25$^{t

Nonthaphat Wongwattanakij, Nattawut Phetmak, Chaiporn Jaikaeo, Jittat Fakcharoenphol

This paper considers a movement minimization problem for mobile sensors. Given a set of $n$ point targets, the $k$-Sink Minimum Movement Target Coverage Problem is to schedule mobile sensors, initially located at $k$ base stations, to cover all targets minimizing the total moving distance of the sensors. We present a polynomial-time approximation scheme for

Shu Liu, Siting Liu, Stanley Osher, Wuchen Li

We propose an easy-to-implement iterative method for resolving the implicit (or semi-implicit) schemes arising in solving reaction-diffusion (RD) type equations. We formulate the nonlinear time implicit scheme as a min-max saddle point problem and then apply the primal-dual hybrid gradient (PDHG) method. Suitable precondition matrices are applied to the PDHG

Deyi Ji, Haoran Wang, Mingyuan Tao, Jianqiang Huang

Existing knowledge distillation works for semantic segmentation mainly focus on transferring high-level contextual knowledge from teacher to student. However, low-level texture knowledge is also of vital importance for characterizing the local structural pattern and global statistical property, such as boundary, smoothness, regularity and color contrast, whi