April 2023 arXiv papers — page 23

Zhongtuo Fu, Ruokai Xu, Yingqi Chen, Song Bao

The honeycomb-lattice cobaltate Na$_3$Co$_2$SbO$_6$ has recently been proposed to be a proximate Kitaev quantum spin liquid~(QSL) candidate. However, non-Kitaev terms in the Hamiltonian lead to a zigzag-type antiferromagnetic~(AFM) order at low temperatures. Here, we partially substitute magnetic Co$^{2+}$ with nonmagnetic Zn$^{2+}$ and investigate the chemi

Takaaki Nomura, Hiroshi Okada

We propose a quark and lepton model explaining their masses, mixings, and CP violating phases, introducing modular $A_4$ and hidden gauged $U(1)$ symmetries. The hidden $U(1)$ brings us heavier Majorana fermions that are requested by chiral anomaly cancellations, and we work on a canonical seesaw scenario due to their neutral particles.In this framework, we

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Xun Yi

Due to the rising awareness of privacy and security in machine learning applications, federated learning (FL) has received widespread attention and applied to several areas, e.g., intelligence healthcare systems, IoT-based industries, and smart cities. FL enables clients to train a global model collaboratively without accessing their local training data. How

Yufeng Zhang, Weiyao Lin, Wenrui Dai, Huabin Liu

The scene graph is a new data structure describing objects and their pairwise relationship within image scenes. As the size of scene graph in vision applications grows, how to losslessly and efficiently store such data on disks or transmit over the network becomes an inevitable problem. However, the compression of scene graph is seldom studied before because

Hang-Ying Shui, Fu-Guo Xie, Zhen Yan, Ren-Yi Ma

The observation of varying broad iron lines during the state transition of the black hole X-ray binaries (BHXBs) have been accumulating.In this work, the relation between the normalized intensity and the width of iron lines is investigated, in order to understand better the variation of iron lines and possibly its connection to state transition. Considering

Liming Xu, Hanqi Li, Bochuan Zheng, Weisheng Li

Hashing methods have made significant progress in cross-modal retrieval tasks with fast query speed and low storage cost. Among them, deep learning-based hashing achieves better performance on large-scale data due to its excellent extraction and representation ability for nonlinear heterogeneous features. However, there are still two main challenges in catas

Christopher J. Fewster, Rainer Verch

The topic of measurement in relativistic quantum field theory is addressed in this article. Some of the long standing problems of this subject are highlighted, including the incompatibility of an instantaneous ``collapse of the wavefunction'' with relativity of simultaneity, and the difficulty of maintaining causality in the rules for measurement highlighted

Shusong Zhang, Li Fu, Yanbo Xie

The classical continuum theories fail to describe the ionic transport in Angstrom channels, where conduction deviates from Ohm's law, as attributed to dehydration/self-energy barrier and dissociation of Bjerrum ion-pairs in previous work. Here we found that the cations are strongly bound to the surface charge that blockade the ionic transport in a single-fil

Peng-Bi Cui

Polarization issue is generally subject to ideological polarization and affective polarization. In particular, affective polarization usually accelerates the polarization process and transform social interactions into a zero-sum game. Yet, a wide array of existing literature have not provided valid ways to make distinction between them. Therefore, the mechan

D. N. Dinh

Recent experimental results on muon anomalous magnetic dipole moment have shown a $4.2\sigma$ tension with the SM prediction, which has blown a fresh wind into the elementary particle physics community. The problem is believed to be explained only by physics beyond the standard model. Current work considers the anomalous moment in a scenario of models with m

Aditya Pribadi Kalapaaking, Veronika Stephanie, Ibrahim Khalil, Mohammed Atiquzzaman

Rapidly developing intelligent healthcare systems are underpinned by Sixth Generation (6G) connectivity, ubiquitous Internet of Things (IoT), and Deep Learning (DL) techniques. This portends a future where 6G powers the Internet of Medical Things (IoMT) with seamless, large-scale, and real-time connectivity amongst entities. This article proposes a Convoluti

F. Benatti, F. Carollo, R. Floreanini, H. Narnhofer

We consider a specific instance of a superconducting circuit, the so-called charge-qubit, consisting of a capacitor and a Josephson junction. Starting from the microscopic description of the latter in terms of two tunneling BCS models in the strong-coupling quasi-spin formulation, we derive the Hamiltonian governing the quantum behavior of the circuit in the

Krishnam Hasija, Shrishti Pradhan, Manasi Patwardhan, Raveendra Kumar Medicherla

In this paper, we define a neuro-symbolic approach to address the task of finding semantically similar clones for the codes of the legacy programming language COBOL, without training data. We define a meta-model that is instantiated to have an Intermediate Representation (IR) in the form of Abstract Syntax Trees (ASTs) common across codes in C and COBOL. We

Zenan Shi, Haipeng Chen, Long Chen, Dong Zhang

In this paper, we propose a novel image forgery detection paradigm for boosting the model learning capacity on both forgery-sensitive and genuine compact visual patterns. Compared to the existing methods that only focus on the discrepant-specific patterns (\eg, noises, textures, and frequencies), our method has a greater generalization. Specifically, we firs

Jiangjiang Cheng, Wenjun Mei, Wei Su, Ge Chen

The stable cooperation ratio of spatial evolutionary games has been widely studied using simulations or approximate analysis methods. However, sometimes such ``stable'' cooperation ratios obtained via approximate methods might not be actually stable, but correspond to quasi-equilibriums instead. We find that various classic game models, like the evolutionary

William Gao, Noam Aigerman, Thibault Groueix, Vladimir G. Kim

We present a technique for automatically producing a deformation of an input triangle mesh, guided solely by a text prompt. Our framework is capable of deformations that produce both large, low-frequency shape changes, and small high-frequency details. Our framework relies on differentiable rendering to connect geometry to powerful pre-trained image encoders

Minami Yoshida, Toshifumi Shimizu, Shin Toriumi

The solar magnetic structure changes over the solar cycle. It has a dipole structure during solar minimum, where the open flux extends mainly from the polar regions into the interplanetary space. During maximum, a complex structure is formed with low-latitude active regions and weakened polar fields, resulting in spread open field regions. However, the compo

Mohammad Ali Khan, Tuomas Oikarinen, Tsui-Wei Weng

In this work, we propose a general framework called Concept-Monitor to help demystify the black-box DNN training processes automatically using a novel unified embedding space and concept diversity metric. Concept-Monitor enables human-interpretable visualization and indicators of the DNN training processes and facilitates transparency as well as deeper under

Yu Qiao, Bing Kwan So

Boundary groupoids were introduced by the second author, which can be used to model many analysis problems on singular spaces. In order to investigate index theory on boundary groupoids, we introduce the notion of {\em a deformation from the pair groupoid}.Under the assumption that a deformation from the pair groupoid $M \times M$ exists for Lie groupoid $\m

Maximilien Burq, Niranjan Sridhar

Automated and accurate human activity recognition (HAR) using body-worn sensors enables practical and cost efficient remote monitoring of Activity of DailyLiving (ADL), which are shown to provide clinical insights across multiple therapeutic areas. Development of accurate algorithms for human activity recognition(HAR) is hindered by the lack of large real-wo

Haakon Bakka

High stakes classification refers to classification problems where erroneously predicting the wrong class is very bad, but assigning "unknown" is acceptable. We make the argument that these problems require us to give multiple unknown classes, to get the most information out of our analysis. With imperfect data we refer to covariates with a large number of m

Bing Wang, Xinnian Liang, Jian Yang, Hui Huang

Large Language Models (LLMs) are constrained by their inability to process lengthy inputs, resulting in the loss of critical historical information. To address this limitation, in this paper, we propose the Self-Controlled Memory (SCM) framework to enhance the ability of LLMs to maintain long-term memory and recall relevant information. Our SCM framework com

Akira Okazaki, Shuichi Kawano

Multi-task learning (MTL) is a methodology that aims to improve the general performance of estimation and prediction by sharing common information among related tasks. In the MTL, there are several assumptions for the relationships and methods to incorporate them. One of the natural assumptions in the practical situation is that tasks are classified into som

Elisa Gorla, Flavio Salizzoni

The MacWilliams' Extension Theorem is a classical result by Florence Jessie MacWilliams. It shows that every linear isometry between linear block-codes endowed with the Hamming distance can be extended to a linear isometry of the ambient space. Such an extension fails to exist in general for rank-metric codes, that is, one can easily find examples of linear

Sean Harris

We present a generalisation of the theory of iterated function systems and associated fractals to the setting of noncommutative geometry. Along the way, we discuss some ideas surrounding locally compact noncommutative metric spaces.

Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face challenges when applying BBO methods to their problems at hand with existing software packages in terms of applicability, performance, and efficiency. This paper presents OpenBox, an op

T-H. Hubert Chan, Ting Wen, Hao Xie, Quan Xue

We study game-theoretically secure protocols for the classical ordinal assignment problem (aka matching with one-sided preference), in which each player has a total preference order on items. To achieve the fairness notion of equal treatment of equals, conventionally the randomness necessary to resolve conflicts between players is assumed to be generated by

Fabian Birkmann, Stefan Milius, Henning Urbat

We propose a novel topological perspective on data languages recognizable by orbit-finite nominal monoids. For this purpose, we introduce pro-orbit-finite nominal topological spaces. Assuming globally bounded support sizes, they coincide with nominal Stone spaces and are shown to be dually equivalent to a subcategory of nominal boolean algebras. Recognizable

Reza Darvishi Kamachali, Theophilus Wallis, Yuki Ikeda, Ujjal Saikia

A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modelling of segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.\% Zn can segregate to the GB. We found that the amount of segregation abruptly increases with d

Fabrizio Bianchi, Tien-Cuong Dinh

We consider the unique measure of maximal entropy of an automorphism of a compact K{\"a}hler manifold with simple action on cohomology. We show that it is exponentially mixing of all orders with respect to H{\"o}lder observables. It follows that the Central Limit Theorem (CLT) holds for these observables. In particular, our result applies to all automorphism

Tobias Kühn, Rémi Monasson

Continuous attractor neural networks (CANN) form an appealing conceptual model for the storage of information in the brain. However a drawback of CANN is that they require finely tuned interactions. We here study the effect of quenched noise in the interactions on the coding of positional information within CANN. Using the replica method we compute the Fishe

Sibo Wang, Hui Tong, Qiang Zhao, Chencan Wang

Nucleon effective masses in neutron-rich matter are studied with the relativistic Brueckner-Hartree-Fock (RBHF) theory in the full Dirac space. The neutron and proton effective masses for symmetric nuclear matter are 0.80 times rest mass, which agrees well with the empirical values. In neutron-rich matter, the effective mass of the neutron is found larger th

Yuwen Li, Jonathan Siegel

We present convergence estimates of two types of greedy algorithms in terms of the metric entropy of underlying compact sets. In the first part, we measure the error of a standard greedy reduced basis method for parametric PDEs by the metric entropy of the solution manifold in Banach spaces. This contrasts with the classical analysis based on the Kolmogorov

David Maximilian Janas, Andreas Windischbacher, Mira Sophie Arndt, Michael Gutnikov

On-surface metal porphyrins can undergo electronic and conformational changes that play a crucial role in determining the chemical reactivity of the molecular layer. Therefore, understanding those properties is pivotal for the design and implementation of organic-based devices. Here, by means of photoemission orbital tomography supported by density functiona

Kaoru Mizuta, Keisuke Fujii

Quantum eigenvalue transformation (QET) and its generalization, quantum singular value transformation (QSVT), are versatile quantum algorithms that allow us to apply broad matrix functions to quantum states, which cover many of significant quantum algorithms such as Hamiltonian simulation. However, finding a parameter set which realizes preferable matrix fun

Guillaume Lauga, Elisa Riccietti, Nelly Pustelnik, Paulo Gonçalves

This paper presents a multilevel framework for inertial and inexact proximal algorithms, that encompasses multilevel versions of classical algorithms such as forward-backward and FISTA. The methods are supported by strong theoretical guarantees: we prove both the rate of convergence and the convergence of the iterates to a minimum in the convex case, an impo

Tam Le

Motivated by the conspicuous use of momentum-based algorithms in deep learning, we study a nonsmooth nonconvex stochastic heavy ball method and show its convergence. Our approach builds upon semialgebraic (definable) assumptions commonly met in practical situations and combines a nonsmooth calculus with a differential inclusion method. Additionally, we provi

Bonpagna Kann, Sandra Castellanos-Paez, Philippe Lalanda

Pervasive computing allows the provision of services in many important areas, including the relevant and dynamic field of health and well-being. In this domain, Human Activity Recognition (HAR) has gained a lot of attention in recent years. Current solutions rely on Machine Learning (ML) models and achieve impressive results. However, the evolution of these

Pranaya Pratik Das, Biplab Ganguli

Out-of-Time-Order-Correlator (OTOC) and Loschmidt Echo (LE) are commonly regarded as diagnostic tools for chaos, although they may yield misleading results because of various other factors. Previous studies have concluded that OTOC shows exponential growth in the neighbourhood of a local maximum. If this statement holds true, the exponential growth should br

Azam A. Imomov

Consider the critical Galton-Watson branching system with infinite variance of the offspring law. We provide an alternative arguments against what Slack~{\cite{Slack68}} did when it seeked for a local expression in the neighborhood of point $1$ of the generating function for invariant measures of the branching system. So, we obtain the global expression for

Shilpa Jangid, Hiroshi Okada

In this article, we examine the Standard Model extended with a $Y=0$ Higgs triplet and a real singlet. We consider the Higgs triplet to be odd under the $Z_2$ symmetry, and hence the lightest stable particle from the inert triplet becomes the dark matter candidate, whereas the real singlet is considered to be even under the $Z_2$ symmetry. A dimension-5 effe

Yoon Kyung Lee, Yong-Ha Park, Sowon Hahn

We investigated the potential and limitations of generative artificial intelligence (AI) in reflecting the authors' cognitive processes through creative expression. The focus is on the AI-generated artwork's ability to understand human intent (alignment) and visually represent emotions based on criteria such as creativity, aesthetic, novelty, amusement, and

Guoce Xin, Yingrui Zhang, ZiHao Zhang

The Todd polynomials, denoted as $td_k(b_1,b_2,\ldots,b_m)$, are characterised by their generating functions: $$\sum_{k\ge 0} td_k s^k = \prod_{i=1}^m \frac{b_i s}{e^{b_i s}-1}.$$ These polynomials serve as fundamental components in the Todd class of toric varieties, a concept of significant relevance in the study of lattice polytopes and number theory. We i

Bhathiya Rathnayake, Mamadou Diagne

This paper presents an event-triggered boundary control strategy for a class of reaction-diffusion PDEs with time-varying reactivity under Robin actuation. The control approach consists of a backstepping full-state feedback boundary controller and a dynamic event-triggering condition, which determines the time instants when the control input needs to be upda

Gilles Dowek

We give a presentation of Krivine and Parigot's Second-order functional arithmetic in Deduction modulo. Expressing this theory in Deduction modulo sheds light on an original aspect of this theory: the fact that programs are specified, not with propositions, but with congruences.

S. Habib Mazharimousavi, Kanishk Verma

Starting from the most general action in Einstein-Dilaton-Nonlinear Electrodynamics (NED) theory, we obtain the field equations. We apply the field equations for the specific NED known as the Liouville type plus a cosmological constant and solve the field equations. With a pure magnetic field it is shown that the square root model is the strong field limit o

Gilles Dowek

We give a presentation of Simple Type Theory as a clausal rewrite system in Polarized deduction modulo.

Gilles Dowek

The physical Church thesis is a thesis about nature that expresses that all that can be computed by a physical system-a machine-is computable in the sense of computability theory. At a first look, this thesis seems contradictory with the existence, in nature, of chaotic dynamical systems, that is systems whose evolution cannot be ''computed'' because of thei

Agelos Georgakopoulos, Alex Wendland

We prove that every recurrent graph $G$ quasi-isometric to $\mathbb{R}$ admits an essentially unique Lipschitz harmonic function $h$. If $G$ is vertex-transitive, then the action of $Aut(G)$ preserves $\partial h$ up to a sign, a fact that we exploit to prove various combinatorial results about $G$. As a consequence, we prove the 2-ended case of the conjectu

A. Komaki, S. Fukuhara, T. K. Suzuki, N. Yoshida

Recent infrared and submillimeter observations suggest that the protoplanetary disk lifetime depends on the central stellar mass. The disk dispersal is thought to be driven by viscous accretion, magneto-hydrodynamics (MHD) winds, and photoevaporation by the central star. We perform a set of one-dimensional simulations of long-term disk evolution that include

Liya Gaynutdinova, Martin Ladecký, Ivana Pultarová, Miloslav Vlasák

This paper focuses on the design, analysis and implementation of a new preconditioning concept for linear second order partial differential equations, including the convection-diffusion-reaction problems discretized by Galerkin or discontinuous Galerkin methods. We expand on the approach introduced by Gergelits et al. and adapt it to the more general setting

Krishna Mahapatra, Selvakumar R

Alzheimer's Disease is a devastating neurological disorder that is increasingly affecting the elderly population. Early and accurate detection of Alzheimer's is crucial for providing effective treatment and support for patients and their families. In this study, we present a novel approach for detecting four different stages of Alzheimer's disease from MRI s

Aru Beri, Vishal Gaur, Phil Charles, David R. A. Williams

Swift J1357.2$-$0933 is a black-hole candidate X-ray transient, which underwent its third outburst in 2019, during which several multi-wavelength observations were carried out.~Here, we report results from the \emph{Neil Gehrels Swift} and \emph{NICER} observatories and radio data from \emph{AMI}.~For the first time,~millihertz quasi-periodic X-ray oscillati

Mingjie Li, Quanshi Zhang

In this technical note, we aim to explain a deep neural network (DNN) by quantifying the encoded interactions between input variables, which reflects the DNN's inference logic. Specifically, we first rethink the definition of interactions, and then formally define faithfulness and conciseness for interaction-based explanation. To this end, we propose two kin

Taichi Kato, Tonny Vanmunster

We found that SDSS J094002.56+274942.0 underwent a superoutburst in 2019 February based on our observations and Zwicky Transient Facility (ZTF) data. This object showed shallow eclipses during this superoutburst and we established the orbital period to be 0.1635015(1) d in combination with the ZTF and Asteroid Terrestrial-impact Last Alert System (ATLAS) dat

Sabine Thater, Mariya Lyubenova, Katja Fahrion, Ignacio Martín-Navarro

Supermassive black holes (SMBHs) and nuclear star clusters (NSCs) co-exist in many galaxies. While the formation history of the black hole is essentially lost, NSCs preserve their evolutionary history imprinted onto their stellar populations and kinematics. Studying SMBHs and NSCs in tandem might help us to ultimately reveal the build-up of galaxy centres. I

Mijin Lim, Byeonghyeon Choi, Minjae Ghim, Je-Geun Park

Fe3GeTe2 (FGT), a ferromagnetic van der Waals topological nodal line semimetal, has recently been studied. Using first-principles calculations and symmetry analysis, we investigate the effect of a uniaxial tensile strain on the nodal line and the resultant intrinsic anomalous Hall effect (AHE). Our results reveal their robustness to the in-plane strain. More

Wenyao Zhang, Xinxi Liu, Kai Jiao, Qiuwang Wang

Ionic thermoelectricity in nanochannels has received increasing attention because of its advantages such as high Seebeck coefficient and low cost. However, most studies have focused on dilute simple electrolytes that neglect the effects of finite ion sizes and short-range electrostatic correlation. Here, we reveal a new thermoelectric mechanism arising from

Dennis Wei, Dmitry M. Malioutov

Maximum subarray is a classical problem in computer science that given an array of numbers aims to find a contiguous subarray with the largest sum. We focus on its use for a noisy statistical problem of localizing an interval with a mean different from background. While a naive application of maximum subarray fails at this task, both a penalized and a constr

Rupak Bag, Dibyendu Roy

We explore special features of quantum light-matter interactions inside structured waveguides due to their finite bandwidth, band edges, and non-trivial topological properties. We model the waveguides as either a tight-binding (TB) chain or a Su-Schrieffer-Heeger (SSH) chain. For unstructured waveguides with infinite bandwidth, the transmission and reflectio

Song Chen, Hua-Hua Fu

Theoretical studies on spin-dependent transport through helical molecules with straight spiral geometry have received intense research interest in the past decade, however, the physics in circular helical molecules has still less been explored. In this work, we theoretically construct a circular single helix (CSH) possessing the chirality-induced spin-orbit

Takahiko Matsubara

The integrated perturbation theory (iPT) is a set of methods in nonlinear perturbation theory for the structure formation in the Universe. In Papers I and II [arXiv:2210.10435, arXiv:2210.11085], the basic formalism and technical methods of the iPT for cosmological tensor fields are developed, generalizing the corresponding theory for scalar fields. In previ

Papia Panda, Monojit Ghosh, Rukmani Mohanta

In this paper, we study the possibility of determining the neutrino mass ordering from the future supernova neutrino events at the DUNE and T2HK detectors. We estimate the expected number of neutrino event rates from a future supernova explosion assuming Garching flux model corresponding to different processes that are responsible for detecting the supernova

Fuheng Wu, Ivan Davchev, Jun Qian

This paper proposes a non-intrusive, declarative, dynamic and transparent system called `HiQ` to track Python program runtime information without compromising on the run-time system performance and losing insight. HiQ can be used for monolithic and distributed systems, offline and online applications. HiQ is developed when we optimize our large deep neural n

Chunxi Guo, Zhiliang Tian, Jintao Tang, Pancheng Wang

Text-to-SQL is a task that converts a natural language question into a structured query language (SQL) to retrieve information from a database. Large language models (LLMs) work well in natural language generation tasks, but they are not specifically pre-trained to understand the syntax and semantics of SQL commands. In this paper, we propose an LLM-based fr

Sandeep Singh, Vimlesh Kumar, Varun Sharma, Daniele Faccio

Hong-Ou-Mandel (HOM) interference, the bunching of two indistinguishable photons on a balanced beam-splitter, has emerged as a promising tool for quantum sensing. There is a need for wide spectral-bandwidth photon pairs (for high-resolution sensing) with high brightness (for fast sensing). Here we show the generation of photon-pairs with flexible spectral-ba

Adam LaClair

We associate to every graph a linear program for packings of vertex disjoint paths. We show that the optimal primal and dual values of the corresponding integer program are the binomial grade and height of the binomial edge ideal of the graph. We deduce from this a new combinatorial characterization of graphs of K\"onig type and use it to show that all trees

Dehui Zhang, Dong Xu, Yuhang Li, Yi Luo

Nonlinear optical processing of ambient natural light is highly desired in computational imaging and sensing applications. A strong optical nonlinear response that can work under weak broadband incoherent light is essential for this purpose. Here we introduce an optoelectronic nonlinear filter array that can address this emerging need. By merging 2D transpar

Xiaolong Duan, Bin Li, Zhaoxia Yin, Xinpeng Zhang

Transmitting images for communication on social networks has become routine, which is helpful for covert communication. The traditional steganography algorithm is unable to successfully convey secret information since the social network channel will perform lossy operations on images, such as JPEG compression. Previous studies tried to solve this problem by

Adam Hassan Denawi, Fabien Bruneval, Marc Torrent, Mauricio Rodríguez-Mayorga

The $GW$ approximation is a well-established method for calculating ionization potentials and electron affinities in solids and molecules. For numerous years, obtaining self-consistent $GW$ total energies in solids has been a challenging objective that is not accomplished yet. However, it was shown recently that the linearized $GW$ density matrix permits a r

Zhehan Qin, Zhong-Zhi Xianyu

Inflation correlators with one-loop massive exchange encode rich information about the dynamics of the massive loop particles. Their nonanalytic behavior in certain soft limits leads to characteristic oscillatory pattern, which is the leading signal of many particle models of cosmological collider physics. In this work, we investigate systematically such non

Mrityunjay Kumar, Venkatesh Choppella

One of the key challenges for a novice engineer in a product company is to comprehend the product sufficiently and quickly. It can take anywhere from six months to several years for them to attain mastery but they need to start delivering results much before. SaaS (Software-as-a-Service) products have sophisticated system architecture which adds to the time

G. J. Abrahams, E. Ellul, I. O. Robertson, A. Khalid

Optically detected magnetic resonance (ODMR) spectroscopy of defect-rich semiconductors is being increasingly exploited for realising a variety of practical quantum sensing devices. A prime example is the on-going development of compact magnetometers based on the nitrogen-vacancy (NV) defect in diamond for the remote sensing of magnetic signals with high acc

Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoudi, Alcides Alcoba Inciarte

Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems. In this work we describe our participation in the slot and intent detection for low-resource language varieties (SID4LR; Aepli et al. (2023)). We investigate the slot and intent detection (SID) tasks using a wide range of models

Ignatios Antoniadis, Spiros Cotsakis, Dimitrios Trachilis

We construct a generic asymptotic solution for modified gravity near a sudden singularity. This solution contains a fluid source with no equation of state and is function-counting stable, that is it has eleven independent arbitrary functions of the spatial coordinates as dictated by the Cauchy problem of the theory. We further show that near the sudden singu

Jia-Huei Ju, Sheng-Chieh Lin, Ming-Feng Tsai, Chuan-Ju Wang

This paper presents ConvRerank, a conversational passage re-ranker that employs a newly developed pseudo-labeling approach. Our proposed view-ensemble method enhances the quality of pseudo-labeled data, thus improving the fine-tuning of ConvRerank. Our experimental evaluation on benchmark datasets shows that combining ConvRerank with a conversational dense r

Siqi Wang, Tee Hiang Cheng, Meng-Hiot Lim

As an emerging network model, spiking neural networks (SNNs) have aroused significant research attentions in recent years. However, the energy-efficient binary spikes do not augur well with gradient descent-based training approaches. Surrogate gradient (SG) strategy is investigated and applied to circumvent this issue and train SNNs from scratch. Due to the

Z. T. Zhang, H. Yan, Z. Huang, X. Chi

Double-perovskite oxides have attracted recent attention due to their attractive functionalities and application potential. In this paper, we demonstrate the effect of dual controls, i.e., the deposition pressure of oxygen (P$_O2$) and lattice mismatch ($\epsilon$), on tuning magnetic properties in epitaxial double-perovskite Sr$_2$FeReO$_6$ films. In a near

Yi Rong, Xiongbo Lu, Zhaoyang Sun, Yaxiong Chen

Self-supervised learning (SSL) techniques have recently been integrated into the few-shot learning (FSL) framework and have shown promising results in improving the few-shot image classification performance. However, existing SSL approaches used in FSL typically seek the supervision signals from the global embedding of every single image. Therefore, during t

Yan-Chao Zhao, Zhi-Qing Zhang, Zi-Yu Zhang, Zhi-Jie Sun

In this work, we investigate the quasi-two-body decays $B_c\to D^*h\to D\pi h$ with $h = (K^0,\pi^0,\eta,\eta^{\prime})$ using the perturbative QCD(PQCD) approach. The description of final state interactions between the $D\pi$ pair is achieved through the two-meson distribution amplitudes(DAs), which are normalized to the time-like form factor. The PQCD pred

Hanji Wu, Wei Wang, Na Sai, Haifan Zhu

MAXI J1348-630 is a low-mass X-ray black hole binary located in the Galaxy and undergone the X-ray outburst in 2019. We analyzed the observation data in very soft state during the outburst between MJD 58588 and MJD 58596 based on the Insight-HXMT observations from 2 -- 20 keV via the continuum fitting method to measure the spin of the stellar-mass black hole

Tomohiro Harada, Chul-Moon Yoo, Yasutaka Koga

Shibata and Sasaki [arXiv:gr-qc/9905064] introduced the so-called compaction function. Since then, it has been empirically established that the maximum value of this function (or its volume-averaged counterpart) in the long-wavelength solutions gives a very robust threshold of primordial black hole formation. In this paper, we show that in spite of initial i

W. Yang, W. Wang, Q. Liu, X. Chen

We present the results of the neutron star X-ray binary system Cen X-3 performed by $Insight$-HXMT with two observations during 2017 and 2018. During these two observations, the source reached a X-ray luminosity of $\sim 10^{38}$ erg s$^{-1}$ from 2 -- 105 keV. The analysis of the broadband X-ray spectrum reports the presence of two cyclotron resonance scatt

Dawood Ahmed, Ranjan Sapkota, Martin Churuvija, Manoj Karkee

Labor shortages in fruit crop production have prompted the development of mechanized and automated machines as alternatives to labor-intensive orchard operations such as harvesting, pruning, and thinning. Agricultural robots capable of identifying tree canopy parts and estimating geometric and topological parameters, such as branch diameter, length, and angl

Hanji Wu, Wei Wang, Na Sai

We analyzed two observations of the low-mass black hole X-ray binary MAXI J1348-630 from Nuclear Spectroscopic Telescope Array (NuSTAR) during low hard state and hard intermediate state in the 2019 outburst. The reflection components are found in the X-ray spectra, and the spectral fittings give an inclination angle of $\sim 25^\circ-35^\circ$ for the binary

B. Yu. Irgashev

In the article, in a rectangular domain, by the Fourier method, the initial boundary value problem for a high-order equation with two lines of degeneracy with a fractional derivative in the sense of Caputo is investigated for uniqueness and solvability. Sufficient conditions for the well-posedness of the problem posed are obtained.

Qi Liu, Wei Wang

We present a detailed temporal analysis for the eclipsing high-mass X-ray binary system Cen X-3 using the Insight-HXMT data in 2018 and 2020. Three consecutive and high statistic observations among data are used for the precise timing analysis. The pulse profiles are revealed to vary with energy and time. The pulse profiles for the 2018 observations showed a

Mohammed Alkinoon, Abdulrahman Alabduljabbar, Hattan Althebeiti, Rhongho Jang

Using a total of 4,774 hospitals categorized as government, non-profit, and proprietary hospitals, this study provides the first measurement-based analysis of hospitals' websites and connects the findings with data breaches through a correlation analysis. We study the security attributes of three categories, collectively and in contrast, against domain name,

Kunzhe Song, Qingfeng Sun, Can Xu, Kai Zheng

With the increasing development of e-commerce and online services, personalized recommendation systems have become crucial for enhancing user satisfaction and driving business revenue. Traditional sequential recommendation methods that rely on explicit item IDs encounter challenges in handling item cold start and domain transfer problems. Recent approaches h

Shuai Li, Zhao Song, Yu Xia, Tong Yu

Large language models (LLMs) are known for their exceptional performance in natural language processing, making them highly effective in many human life-related or even job-related tasks. The attention mechanism in the Transformer architecture is a critical component of LLMs, as it allows the model to selectively focus on specific input parts. The softmax un

Hao Lu, Adam Thelen, Olga Fink, Chao Hu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning maintenance engineers of impending failure or identifying current system health conditions. However, singl

Souvik Kundu, Yuke Zhang, Dake Chen, Peter A. Beerel

Large number of ReLU and MAC operations of Deep neural networks make them ill-suited for latency and compute-efficient private inference. In this paper, we present a model optimization method that allows a model to learn to be shallow. In particular, we leverage the ReLU sensitivity of a convolutional block to remove a ReLU layer and merge its succeeding and

Abdulrahman Alabduljabbar, Runyu Ma, Ahmed Abusnaina, Rhongho Jang

Free content websites that provide free books, music, games, movies, etc., have existed on the Internet for many years. While it is a common belief that such websites might be different from premium websites providing the same content types, an analysis that supports this belief is lacking in the literature. In particular, it is unclear if those websites are

Junyang Wang, Ming Yan, Yi Zhang, Jitao Sang

With the development of Vision-Language Pre-training Models (VLPMs) represented by CLIP and ALIGN, significant breakthroughs have been achieved for association-based visual tasks such as image classification and image-text retrieval by the zero-shot capability of CLIP without fine-tuning. However, CLIP is hard to apply to generation-based tasks. This is due

Eva-Maria Hekkelman, Edward McDonald

We give an abstract formulation of the Dixmier trace formula for the density of states. This recovers prior versions and allows us to provide a Dixmier trace formula for the density of states of second order elliptic differential operators on manifolds of bounded geometry satisfying a certain geometric condition. This formula gives a new perspective on Roe's

Yoshihiro Kawasaki, Masahiro N. Machida

We investigate the influence of dust particle size evolution on non-ideal magnetohydrodynamic effects during the collapsing phase of star-forming cores, taking both the turbulence intensity in the collapsing cloud core and the fragmentation velocity of dust particles as parameters. When the turbulence intensity is small, the dust particles do not grow signif

Ye-Xin Lu, Yang Ai, Zhen-Hua Ling

This paper proposes a source-filter-based generative adversarial neural vocoder named SF-GAN, which achieves high-fidelity waveform generation from input acoustic features by introducing F0-based source excitation signals to a neural filter framework. The SF-GAN vocoder is composed of a source module and a resolution-wise conditional filter module and is tra

Chengpeng Hu, Yunlong Zhao, Ziqi Wang, Haocheng Du

Games have been the perfect test-beds for artificial intelligence research for the characteristics that widely exist in real-world scenarios. Learning and optimisation, decision making in dynamic and uncertain environments, game theory, planning and scheduling, design and education are common research areas shared between games and real-world problems. Numer

K. L. Nguyen, L. Yin, B. J. Albright, D. H. Edgell

In cross-beam energy transfer (CBET), the interference of two laser beams ponderomotively drives an ion-acoustic wave that coherently scatters light from one beam into the other. This redirection of laser beam energy can severely inhibit the performance of direct-drive inertial confinement fusion (ICF) implosions. To assess the role of nonlinear and kinetic

Longbing Cao, Hui Chen, Xuhui Fan, Joao Gama

Federated learning (FL) demonstrates its advantages in integrating distributed infrastructure, communication, computing and learning in a privacy-preserving manner. However, the robustness and capabilities of existing FL methods are challenged by limited and dynamic data and conditions, complexities including heterogeneities and uncertainties, and analytical