October 2022 arXiv papers — page 10

Jiabao Zhang, Xiang-Nan Jin, Chia-Wei Liu, Chao-Qiang Geng

We study the heavy quark symmetry with the homogeneous bag model (HBM) and light-front quark model (LFQM) based on the decays of $\Lambda_b^0\to\Lambda_c^+\ell^-\overline{\nu}_\ell~(\ell=e,\mu,\tau)$. In particular, we calculate various parameters in the heavy quark expansions, including the Isgur-Wise functions and their first order corrections. The paramet

Nan Li, Zijia Li, Zhi-Hong Yang, Lihong Zhi

In 1936, Krull asked if the integral closure of a primary ideal is still primary. Fifty years later, Huneke partially answered this question by giving a primary polynomial ideal whose integral closure is not primary in a regular local ring of characteristic $p=2$. We provide counterexamples to Krull's question regarding polynomial rings with any characterist

Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang, Jen-Yueh Hsiao

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time and resource-consuming, and it has a low probability of success. Recent advances in machine learning and deep learning technology have reduced the time and cost of the discovery process and therefore, improved

Hanqing Wang, Wei Liang, Luc Van Gool, Wenguan Wang

With the emergence of varied visual navigation tasks (e.g, image-/object-/audio-goal and vision-language navigation) that specify the target in different ways, the community has made appealing advances in training specialized agents capable of handling individual navigation tasks well. Given plenty of embodied navigation tasks and task-specific solutions, we

Zi-Han Wang, Peng-Hui Chen, Xiang-Hua Zeng, Zhao-Qing Feng

We have calculated production cross sections of new superheavy elements with atomic number Z=119,120 in the fusion-evaporation reactions of $^{48}$Ca+$^{252}$Es, $^{48}$Ca+$^{257}$Fm, $^{49}$Sc+$^{252}$Es, $^{49}$Sc+$^{251}$Cf, $^{50}$Ti+$^{247}$Bk, $^{50}$Ti+$^{251}$Cf, $^{51}$V+$^{247}$Cm, $^{51}$V+$^{247}$Cf, $^{54}$Cr+$^{243}$Am, $^{54}$Cr+$^{247}$Cm, $^

Lei Wang, Piotr Koniusz

We propose a Few-shot Learning pipeline for 3D skeleton-based action recognition by Joint tEmporal and cAmera viewpoiNt alIgnmEnt (JEANIE). To factor out misalignment between query and support sequences of 3D body joints, we propose an advanced variant of Dynamic Time Warping which jointly models each smooth path between the query and support frames to achie

Mingming Hu, Kun Zhang, Ruibang You, Bibo Tu

Behavioral biometrics-based continuous authentication is a promising authentication scheme, which uses behavioral biometrics recorded by built-in sensors to authenticate smartphone users throughout the session. However, current continuous authentication methods suffer some limitations: 1) behavioral biometrics from impostors are needed to train continuous au

Bui Trong Kien, Bui Ngoc Muoi, Ching-Feng Wen, Jen-Chih Yao

A class of optimal control problems governed by linear fractional diffusion equation with control constraint is considered. We first establish some results on the existence of strong solution to the state equation and the existence of optimal solutions for the optimal control problem. Then we derive first-and second-order optimality conditions for locally op

Ji-Hoon Ha, Dongsu Ryu, Hyesung Kang

Cosmology models predict that external accretion shocks form in the outer region of galaxy clusters due to supersonic gas infall from filaments and voids in the cosmic web. They are characterized by high sonic and Alfv\'enic Mach numbers, $M_s\sim10-10^2$ and $M_A\sim10^2-10^3$, and propagate into weakly magnetized plasmas of $\beta\equiv P_g/P_B\gtrsim10^2$

Dimitra-Dionysia Stergiopoulou

The stability of the class of projectively coresolved Gorenstein flat modules, under the very Gorenstein process used to define them, is proven in this paper. Moreover, a new characterization of the projectively coresolved Gorenstein flat dimension is given.

L. Mandelli, S. Berretti

In this paper, we introduce a new approach for retrieval and classification of 3D models that directly performs in the Computer-Aided Design (CAD) format without any conversion to other representations like point clouds or meshes, thus avoiding any loss of information. Among the various CAD formats, we consider the widely used STEP extension, which represent

Bachana Beradze, Alexander Nersesyan

Ultracold Fermi gases with synthetic gauge field represent an excellent platform to study the combined effect of lattice frustration and an effective magnetic flux close to one flux quantum per particle. The minimal theoretical model to accomplish this task is a system of spinless noninteracting fermions on a triangular two-chain flux ladder. In this paper w

Yongtong Wu, Kejia Hu, Shenquan Liu

Deep brain stimulation(DBS)has become an effective intervention for advanced Parkinson's disease, but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia(BG), the abnormal pathological changes of the BG in Parkinson's disease, and how computational models can h

Md Asif Hossain Bhuiyan, Shamima Akter Mitu, Sajid Muhaimin Choudhury

In this study, we present an all-optical reflection modulator for 2$\mu$m communication band exploiting a nano-gear-array metasurface and a phase-change-material Ge$_2$Sb$_2$Te$_5$ (GST). The reflectance of the structure can be manipulated by altering the phase of GST by employing optical stimuli. The paper shows details on the optical and opto-thermal model

Mehedi Hasan Himel, Bejoy Sikder, Tanvir Ahmed, Sajid Muhaimin Choudhury

Biomimicry has been utilized in many branches of science and engineering to develop devices for enhanced and better performance. The application of nanotechnology has made life easier in modern times. It has offered a way to manipulate matter and systems at the atomic level. As a result, the miniaturization of numerous devices has been possible. Of late, the

Fernando Julio Cendra, Lan Ma, Jiajun Shen, Xiaojuan Qi

Deep learning has attained remarkable success in many 3D visual recognition tasks, including shape classification, object detection, and semantic segmentation. However, many of these results rely on manually collecting densely annotated real-world 3D data, which is highly time-consuming and expensive to obtain, limiting the scalability of 3D recognition task

Gérard Fleury, Philippe Lacomme

This paper concerns the Grover algorithm that permits to make amplification of quantum states previously tagged by an Oracle. Grover's algorithm allows searches in an unstructure database of n entries finding a marked element with a quadratic speedup. The algorithm requires a predefined number of runs to succeed with probability close to one.This article pro

Stanislav Minsker, Mohamed Ndaoud, Lang Wang

We consider the high-dimensional linear regression model and assume that a fraction of the measurements are altered by an adversary with complete knowledge of the data and the underlying distribution. We are interested in a scenario where dense additive noise is heavy-tailed while the measurement vectors follow a sub-Gaussian distribution. Within this framew

F. Principi, S. Berretti, C. Ferrari, N. Otberdout

Human facial expressions change dynamically, so their recognition / analysis should be conducted by accounting for the temporal evolution of face deformations either in 2D or 3D. While abundant 2D video data do exist, this is not the case in 3D, where few 3D dynamic (4D) datasets were released for public use. The negative consequence of this scarcity of data

Md. Shafiul Alam

We define a set of holomorphic functions in terms of the Hauptmodul of a quotient Riemann surface and prove that these functions are holomorphic on the upper half-plane. It is also shown that these functions are automorphic forms of weight k with respect to a Fuchsian group.

Zhibin Qiu, Mengfan Fu, Yinfeng Yu, LiLi Yin

Diffusion model, as a new generative model which is very popular in image generation and audio synthesis, is rarely used in speech enhancement. In this paper, we use the diffusion model as a module for stochastic refinement. We propose SRTNet, a novel method for speech enhancement via Stochastic Refinement in complete Time domain. Specifically, we design a j

Yanping Cong, Bin Yue, Yidong Xu, Yuan Shi

The free-free absorption of low frequency radio waves by thermal electrons in the warm ionized medium of our Galaxy becomes very significant at $\lesssim 10$ MHz (ultralong-wavelength), and the absorption strength depends on the radio frequency. Upcoming space experiments such as the Discovering Sky at the Longest wavelength (DSL) and Farside Array for Radio

S. D. Brechet

In geometric algebra, the rotation of a vector is described using rotors. Rotors are phasors where the imaginary number has been replaced by a oriented plane element of unit area called a unit bivector. The algebra in three dimensional space relating vectors and bivectors is the Pauli algebra. Multivectors consisting of linear combinations of scalars and biv

Shenglun Yi, Mattia Zorzi

A robust fixed-lag smoothing approach is proposed in the case there is a mismatch between the nominal model and the actual model. The resulting robust smoother is characterized by a dynamic game between two players: one player selects the least favorable model in a prescribed ambiguity set, while the other player selects the fixed-lag smoother minimizing the

Yu Feng, Xiaoqian Xu

The main contribution of this paper is twofold: (1) Recently, Iyer, Xu, and Zlato\v{s} studied the dissipation enhancement by cellular flows based on standard advection-diffusion equations via a stochastic method. We generalize their results to advective hyper-diffusion equations and advective nonlinear diffusion equations. (2) We prove there exist smooth in

David Naccache, Ofer Yifrach-Stav

The Ramanujan Machine project detects new expressions related to constants of interest, such as $\zeta$ function values, $\gamma$ and algebraic numbers (to name a few). In particular the project lists a number of conjectures concerning the Catalan constant $G= 0.91596559\ldots$ We show how to generate infinitely many. We used an ad hoc software toolchain and

Julio C. Carrasquel, Irina A. Lomazova

Trading systems are software platforms that support the exchange of securities (e.g., company shares) between participants. In this paper, we present a method to search for deviations in trading systems by checking conformance between colored Petri nets and event logs. Colored Petri nets (CPNs) are an extension of Petri nets, a formalism for modeling of dist

David Hasler, Markus Lange

We consider Hamiltonians of models describing non-relativistic quantum mechanical matter coupled to a relativistic field of bosons. If the free Hamiltonian has an eigenvalue, we show that this eigenvalue persists also for nonzero coupling. The eigenvalue of the free Hamiltonian may be degenerate provided there exists a symmetry group acting irreducibly on th

Yiming Chen, Yan Zhang, Bin Wang, Zuozhu Liu

Most sentence embedding techniques heavily rely on expensive human-annotated sentence pairs as the supervised signals. Despite the use of large-scale unlabeled data, the performance of unsupervised methods typically lags far behind that of the supervised counterparts in most downstream tasks. In this work, we propose a semi-supervised sentence embedding fram

Chuan-Chi Lai, Bhola, Ang-Hsun Tsai, Li-Chun Wang

Unmanned aerial vehicle-aided communication (UAB-BS) is a promising solution to establish rapid wireless connectivity in sudden/temporary crowded events because of its more flexibility and mobility features than conventional ground base station (GBS). Because of these benefits, UAV-BSs can easily be deployed at high altitudes to provide more line of sight (L

Mao Yoshii, Sota Kitamura, Takahiro Morimoto

Quasiperiodic systems show a universal gap structure due to quasiperiodicity which is analogous to gap openings at the Brillouin zone boundary in periodic systems. The integrated density of states (IDoS) below those energy gaps are characterized by a few integers, which is known as the ``gap labeling theorem'' (GLT) for quasiperiodic systems. In this study,

Çağan Selim Çoban, Oğuzhan Keskin, Jordi Pont-Tuset, Fatma Güney

In Video Instance Segmentation (VIS), current approaches either focus on the quality of the results, by taking the whole video as input and processing it offline; or on speed, by handling it frame by frame at the cost of competitive performance. In this work, we propose an online method that is on par with the performance of the offline counterparts. We intr

Liangang Ma, Mark Pollicott

The first part of this work is devoted to the study of higher differentials of pressure functions of H\"older potentials on shift spaces of finite type. By describing the differentials of pressure functions via the Central Limit Theorem for the associated random processes, we discover some rigid relationships between differentials of various orders. The rigi

Jürgen Prestin, Viktor Savchuk, Andrii Shidlich

Approximative properties of the Taylor-Abel-Poisson linear summation me\-thod of Fourier series are considered for functions of several variables, periodic with respect to the hexagonal domain, in the integral metric. In particular, direct and inverse theorems are proved in terms of approximations of functions by the Taylor-Abel-Poisson means and $K$-functio

Michael Herrmann, Barbara Niethammer

We study a system of non-identical bistable particles that is driven by a dynamical constraint and coupled through a non-local mean-field. Assuming piecewise affine constitutive laws we prove the existence of traveling wave solutions and characterize their dynamical stability. Our findings explain the two dynamical regimes for phase interface that can be obs

Bozhong Liu, Xiaoxi Yu, Hantao Huang

Acoustic echo cancellation (AEC) is designed to remove echoes, reverberation, and unwanted added sounds from the microphone signal while maintaining the quality of the near-end speaker's speech. This paper proposes adaptive speech quality complex neural networks to focus on specific tasks for real-time acoustic echo cancellation. In specific, we propose a co

Tuan-Anh Nguyen, Nguyen Kim Thang, Denis Trystram

Decentralized learning has been studied intensively in recent years motivated by its wide applications in the context of federated learning. The majority of previous research focuses on the offline setting in which the objective function is static. However, the offline setting becomes unrealistic in numerous machine learning applications that witness the cha

Silu He, Qinyao Luo, Ronghua Du, Ling Zhao

The key to traffic prediction is to accurately depict the temporal dynamics of traffic flow traveling in a road network, so it is important to model the spatial dependence of the road network. The essence of spatial dependence is to accurately describe how traffic information transmission is affected by other nodes in the road network, and the GNN-based traf

Seongyeong Lee, Hansoo Park, Dong Uk Kim, Jihyeon Kim

RGB-based 3D hand pose estimation has been successful for decades thanks to large-scale databases and deep learning. However, the hand pose estimation network does not operate well for hand pose images whose characteristics are far different from the training data. This is caused by various factors such as illuminations, camera angles, diverse backgrounds in

Yu Yao, Yong Ni, Ling-hui He

Architected 2D lattice materials are appealing for shape-shifting applications due to the tunable sign of Poisson's ratio. It is commonly believed that the positive and negative Poisson's ratios lead to anticlastic and synclastic curvatures respectively when the material is bent in one direction. Here, taking 2D beam lattices with star-shaped unit cells as e

Gyunam Park, Aaron Küsters, Mara Tews, Cameron Pitsch

Several decision points exist in business processes (e.g., whether a purchase order needs a manager's approval or not), and different decisions are made for different process instances based on their characteristics (e.g., a purchase order higher than $500 needs a manager approval). Decision mining in process mining aims to describe/predict the routing of a

Andrew Huard, Mengyu Chen, Misha Sra

Presence in virtual reality (VR) is meaningful for remotely connecting with others and facilitating social interactions despite great distance while providing a sense of "being there." This work presents CardsVR, a two-person VR experience that allows remote participants to play a game of cards together. An entire deck of tracked cards are used to recreate t

Lê Nguyên Hoang, Romain Beylerian, Bérangère Colbois, Julien Fageot

This paper presents Solidago, an end-to-end modular pipeline to allow any community of users to collaboratively score any number of entities. Solidago proposes a six-module decomposition. First, it uses pretrust and peer-to-peer vouches to assign trust scores to users. Second, based on participation, trust scores are turned into voting rights per user per en

Omran Kouba

Using the expansion in a Fourier-Gegenbauer series, we prove several identities that extend and generalize known results. In particular, it is proved among other results, that \begin{equation*} \sum_{n=0}^\infty\frac{1}{4^n}\binom{2n}{n}\frac{z-2n}{\binom{z-1/2}{n}}\binom{z}{n}^3 =\frac{\tan(\pi z)}{\pi} \end{equation*} for all complex numbers $z$ such that

Muhammad Yameen

We study the limiting behavior of extremal cohomology groups of $k$-points configuration spaces of complex projective spaces of complex dimension $m\geq 4.$ In the previous work, we prove that the extremal cohomology groups of degrees $(2m-2)k+i$ are eventually vanish for each $i\in\{1,2,3\}.$ In this paper, we investigate the extremal cohomology groups for

Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li

This paper proposes an unsupervised method for learning a unified representation that serves both discriminative and generative purposes. While most existing unsupervised learning approaches focus on a representation for only one of these two goals, we show that a unified representation can enjoy the mutual benefits of having both. Such a representation is a

Mohamed Mabrouk, Ali Zamani

Let $a$ be a positive element in a unital $C^*$-algebra $\mathfrak{A}$. We define a semi-norm on $\mathfrak{A}$, which generalizes the $a$-operator semi-norm and the $a$-numerical radius. We investigate basic properties of this semi-norm and prove inequalities involving it. Further, we derive new upper and lower bounds for the $a$-numerical radii of elements

Sriparna Majumdar, Aaron Brick

The forensic attribution of the handwriting in a digitized document to multiple scribes is a challenging problem of high dimensionality. Unique handwriting styles may be dissimilar in a blend of several factors including character size, stroke width, loops, ductus, slant angles, and cursive ligatures. Previous work on labeled data with Hidden Markov models,

Ruilin Liu, Sebastián V. Romero, Izaskun Oregi, Eneko Osaba

Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning,and quantum optics. In this article, two ways to digitally prepare coherent states in quantum circuits are introduced. First, we construct the displacement operator by decomposing it into Pauli matrices via ladder operators, i

Vadim Semenov

We introduce a relaxation of the Aleksandrov condition for the Gauss Image Problem. This weaker condition turns out to be a necessary condition for two measures to be related by a convex body. We provide several properties of the new condition. A solution to the Gauss Image Problem is obtained for the case when one of the measures is assumed to be discrete a

Jiadi Yao, Xing Chen, Xiao-Lei Zhang, Wei-Qiang Zhang

Adversarial attack approaches to speaker identification either need high computational cost or are not very effective, to our knowledge. To address this issue, in this paper, we propose a novel generation-network-based approach, called symmetric saliency-based encoder-decoder (SSED), to generate adversarial voice examples to speaker identification. It contai

Veysel Kocaman, Ofer M. Shir, Thomas Bäck, Ahmed Nabil Belbachir

We propose an augmentation policy for Contrastive Self-Supervised Learning (SSL) in the form of an already established Salient Image Segmentation technique entitled Global Contrast based Salient Region Detection. This detection technique, which had been devised for unrelated Computer Vision tasks, was empirically observed to play the role of an augmentation

Wenqi Shi, Wenkai Xu

Learning causal relationships is a fundamental problem in science. Anchor regression has been developed to address this problem for a large class of causal graphical models, though the relationships between the variables are assumed to be linear. In this work, we tackle the nonlinear setting by proposing kernel anchor regression (KAR). Beyond the natural for

Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye

In this paper, we study \xw{dataset distillation (DD)}, from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline. Unlike conventional DD approaches that aim to produce distilled and representative samples, \emph{HaBa} explores decomposing a datas

Yuxiang Wu, Yu Zhao, Baotian Hu, Pasquale Minervini

Access to external knowledge is essential for many natural language processing tasks, such as question answering and dialogue. Existing methods often rely on a parametric model that stores knowledge in its parameters, or use a retrieval-augmented model that has access to an external knowledge source. Parametric and retrieval-augmented models have complementa

Yogendar Singh, Vivek Kumar, Saurabh Kumar Sharma, Pawan Kumar Kulriya

The thermal conductivity study on the pyrochlore structured ceramics is important for utilization of these materials as an inert matrix fuel, electrolytes for oxide fuel cell and thermal barrier coating. The impact of porosity, structural defects and boundary scattering on thermal properties of the nanocrystalline Gd2Ti2O7 fabricated by spark plasma sinterin

Zhuoyi Yang, Ming Ding, Yanhui Guo, Qingsong Lv

In recent years, pretrained models revolutionized the paradigm of natural language understanding (NLU), where we append a randomly initialized classification head after the pretrained backbone, e.g. BERT, and finetune the whole model. As the pretrained backbone makes a major contribution to the improvement, we naturally expect a good pretrained classificatio

V. Taghiloo, M. H. Vahidinia

We consider the standard Maxwell's theory in 1+3 dimensions in the presence of a timelike boundary. In this context, we show that (generalized) Ampere-Maxwell's charge appears as a Noether charge associated with the Maxwell U(1) gauge symmetry which satisfies a spatial conservation equation. Furthermore, we also introduce the notion of spatial memory field a

Mathieu Stiénon, Luca Vitagliano, Ping Xu

Given an inclusion $A\hookrightarrow L$ of Lie algebroids sharing the same base manifold $M$, i.e. a Lie pair, we prove that the space $\Gamma(\Lambda^\bullet A^\vee)\otimes_{R} \frac{U(L)}{U(L)\cdot\Gamma(A)}$, where $R=C^\infty(M)$, admits an $A_\infty$-algebra structure, unique up to $A_\infty$-isomorphisms. As a consequence, the Chevalley-Eilenberg cohom

Xiaorui Ding, Wenbo Xu, Yue Wang

Direction-of-arrival (DoA) is a critical parameter in wireless channel estimation. With the ever-increasing requirement of high data rate and ubiquitous devices in wireless communication systems, effective wideband DoA estimation is desirable. In this paper, an iterative coherent signal-subspace method including three main steps in each iteration is proposed

S. Operto, P. Amestoy, H. S. Aghamiry, S. Beller

Frequency-domain Full Waveform Inversion (FWI) is potentially amenable to efficient processing of full-azimuth long-offset stationary-recording seabed acquisition carried out with sparse layout of ocean bottom nodes (OBNs) and broadband sources because the inversion can be performed with a few discrete frequencies. However, computing efficiently the solution

Lizhi Xin, Houwen Xin

What is the observer's role in quantum measurement? Obviously, observers prepare the apparatus, observe and interpret the measured results. Although the observer will have a certain influence on the measurement results by setting up the measuring apparatus, we don't believe human consciousness cause reducing of wave packet; also observers are certainly requi

Jiawei Lian, Shaohui Mei, Shun Zhang, Mingyang Ma

DNNs are vulnerable to adversarial examples, which poses great security concerns for security-critical systems. In this paper, a novel adaptive-patch-based physical attack (AP-PA) framework is proposed, which aims to generate adversarial patches that are adaptive in both physical dynamics and varying scales, and by which the particular targets can be hidden

Ailing Wang, Tao An, Xiaopeng Cheng, Luis C. Ho

We observed 20 Palomar-Green (PG) quasars at low redshift ($z<0.5$) with total flux density > 1 mJy, including 4 radio-loud quasars (RLQs) and 16 radio-quiet quasars (RQQs), using the Very Long Baseline Array (VLBA) at 5 GHz. Ten RQQs are clearly detected in the VLBA images, and a compact radio core is identified in eight of them, indicating the prevalence o

Akihiro Higashitani, Hirotake Kurihara

The goal of this paper is to characterization generalized Alexander quandles of finite groups in the language of the underlying groups. Firstly, we prove that if finite groups $G$ are simple, then the quandle isomorphic classes of generalized Alexander quandles of $G$ one-to-one correspond to the conjugacy classes of the automorphism groups of $G$. This corr

Takumi Funato, Mamoru Matsuo

We theoretically investigate a spin-mediated conversion from fluid dynamics to voltage, known as spin hydrodynamic generation (SHDG), in oscillatory and transient unsteady flows. We consider unsteady flows of liquid metal between two parallel infinite planes and then calculate its vorticity fields based on the Navier--Stokes equation for an incompressible vi

Belle Collaboration, G. Gong, L. K. Li, Y. Zhang

The processes $ e^+e^-\rightarrow \Sigma^0\overline{\Sigma}{}^0 $ and $ e^+e^-\rightarrow\Sigma^+\overline{\Sigma}{}^-$ are studied using initial-state-radiation events in a sample of 980 $\,\mbox{fb}^{-1}$ collected with the Belle detector at the KEKB asymmetric-energy $ e^+e^- $ collider. The cross sections from the mass threshold to $ 3{\mathrm{\,Ge\kern

Anna Hasenfratz, Claudio Rebbi, Oliver Witzel

The step-scaling function, the lattice analog of the renormalization group $\beta$ function, is presented for the SU(3) gauge system with eight flavors in the fundamental representation. Our investigation is based on generating dynamical eight flavor gauge field configurations using stout-smeared M\"obius domain wall fermions and Symanzik gauge action. On th

Rachna Aggarwal, Krishnendu Gongopadhyay, Mukund Madhav Mishra

We examine the group of isometries of the open unit ball of a complex Banach space of certain bounded linear operators equipped with the Carath\'eodory metric. Therein we obtain a charactrization of the normal isometries in terms of their special type of fixed points.

Jiepeng Fang, Yixin Lan, Jie Xiao

Given any symmetric Cartan datum, Lusztig has provided a pair of key lemmas to construct the perverse sheaves over the corresponding quiver and the functions of irreducible components over the corresponding preprojective algebra respectively. In the present article, we prove that these two inductive algorithms of Lusztig coincide. Consequently we can define

Futoshi Takahashi

In this note, we prove the nondegenracy of the explicit finite-mass solution to the $N$-Laplace Liouville equation on the whole space, which is recently shown to be unique up to scaling and translation.

Tong Liu

Medium modification of particle spectra and the origin of collectivity in small collision systems are widely debated topics in the heavy-ion community. To address these open questions, we propose the study of particle production and collectivity for varying system sizes,Au+Au $>$ Ru+Ru/Zr+Zr $>$ Cu+Cu $>$ d+Au $>$ $\gamma$+Au, available at RHIC using the STA

Xianghu Yue, Junyi Ao, Xiaoxue Gao, Haizhou Li

Self-supervised pre-training has been successful in both text and speech processing. Speech and text offer different but complementary information. The question is whether we are able to perform a speech-text joint pre-training on unpaired speech and text. In this paper, we take the idea of self-supervised pre-training one step further and propose token2vec,

Qingquan Zhang, Jialin Liu, Zeqi Zhang, Junyi Wen

In the literature of mitigating unfairness in machine learning, many fairness measures are designed to evaluate predictions of learning models and also utilised to guide the training of fair models. It has been theoretically and empirically shown that there exist conflicts and inconsistencies among accuracy and multiple fairness measures. Optimising one or s

Shahane A. Khachatryan

We propose new inhomogeneous local integrability equations - combined equations, for statistical vertex models of general dimensions in the framework of the Algebraic Bethe Ansatz (ABA). For the low dimensional cases the efficiency of the step by step consideration of the transfer matrices' commutation is demonstrated. We construct some simple 3D solutions w

Yujie Lian, Shuo Cao, Tonghua Liu, Marek Biesiada

Observations of galaxy-scale strong gravitational lensing (SGL) systems have enabled unique tests of nonlinear departures from general relativity (GR) on the galactic and supergalactic scales. One of the most important cases of such tests is constraints on the gravitational slip between two scalar gravitational potentials. In this paper, we use a newly compi

Yusuke Kawamoto, Tetsuya Sato, Kohei Suenaga

We propose a formal language for describing and explaining statistical causality. Concretely, we define Statistical Causality Language (StaCL) for expressing causal effects and specifying the requirements for causal inference. StaCL incorporates modal operators for interventions to express causal properties between probability distributions in different poss

Muhammad Usman, Azka Rehman, Abdullah Shahid, Siddique Latif

In this study, we propose a lung nodule detection scheme which fully incorporates the clinic workflow of radiologists. Particularly, we exploit Bi-Directional Maximum intensity projection (MIP) images of various thicknesses (i.e., 3, 5 and 10mm) along with a 3D patch of CT scan, consisting of 10 adjacent slices to feed into self-distillation-based Multi-Enco

Isaac Noel, Hanjue Zhu, Nickolay Gnedin

The low-redshift mass-metallicity relation (MZR) is well studied, but the high-redshift MZR remains difficult to observe. To study the early MZR further, we analyze the Cosmic Reionization on Computers (CROC) simulations with a focus on the MZR from redshifts 5 to 10. We find that, across all redshifts, CROC galaxies exhibit similar stellar-phase and gas-pha

Justin Xie

Paraphrase generation, a.k.a. paraphrasing, is a common and important task in natural language processing. Emotional paraphrasing, which changes the emotion embodied in a piece of text while preserving its meaning, has many potential applications, e.g., moderating online dialogues and preventing cyberbullying. We introduce a new task of fine-grained emotiona

Jie Li, Chunlin Liu, Siming Tu, Tao Yu

Using the idea of local entropy theory, we characterize the sequence entropy tuple via mean forms of the sensitive tuple in both topological and measure-theoretical senses. For the measure-theoretical sense, we show that for an ergodic measure-preserving system, the $\mu$-sequence entropy tuple, the $\mu$-mean sensitive tuple and the $\mu$-sensitive in the m

Bruno Kenichi Saika, Satoshi Hamao, Yuki Majima, Xiang Huang

In intercalated transition metal dichalcogenides (I-TMDC), transition metal intercalation introduces magnetic phases which in some cases induce topological band crossing. However, evidence of the topological properties remains elusive in such materials. Here we employ angle-resolved photoemission spectroscopy to reveal the band structure of epitaxially grown

Huijun Fan, Tian Lan, Zongrui Yang

For a nondegenerate homogeneous polynomial $f\in\mathbb{C}[z_0, \dots, z_{n+1}]$ with degree $n+2$, we can obtain a $tt^*$ structure from the Landau-Ginzburg model $(\C^{n+2}, f)$ and a (new) $tt^*$ structure on the Calabi-Yau hypersurface defined by the zero locus of $f$ in $\C P^{n+1}$. We can prove that the big residue map considered by Steenbrink gives a

Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo

A purposely built deep learning algorithm for the Verification of Earth-System ParametERisation (VESPER) is used to assess recent upgrades of the global physiographic datasets underpinning the quality of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), which is used both in numerical weather predictio

Changlin Wu, Chang Wang, Guanjun You, Juncheng Cao

Drude model successfully quantifies the optical constants for bulk matter, but it is not suitable for subwavelength objects. In this paper, terahertz near-field optical microscopy and finite element simulation are used to study gold patches fabricated by Gallium etching. Electron transport is discovered in determining the optical signal strength. The signal

Shujun Wang, Yongqiang Tian andDengcheng He

Regular expressions (regexes) are widely used in different fields of computer science, such as programming languages, string processing, and databases. However, existing tools for synthesizing or repairing regexes always assume that the input examples are faultless. In real industrial scenarios, this assumption does not entirely hold. Thus, this paper presen

Jie Wang, Menglong Xu, Jingyong Hou, Binbin Zhang

Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an indispensable component of smart devices. Recently, end-to-end (E2E) methods have become the most popular approach for on-device KWS tasks. However, there is still a gap between the research and deployment of E2E KWS methods. In this paper, we introduce WeKws, a production-

Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam Sakla

We present a fully automated framework for building object detectors on satellite imagery without requiring any human annotation or intervention. We achieve this by leveraging the combined power of modern generative models (e.g., StyleGAN) and recent advances in multi-modal learning (e.g., CLIP). While deep generative models effectively encode the key semant

Shengshi Yao, Sixian Wang, Jincheng Dai, Kai Niu

Semantic communications have shown great potential to boost the end-to-end transmission performance. To further improve the system efficiency, in this paper, we propose a class of novel semantic coded transmission (SCT) schemes over multiple-input multiple-output (MIMO) fading channels. In particular, we propose a high-efficiency SCT system supporting concur

Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li

Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs). Recently, graph neural network (GNN) based methods, which can simultaneously explore topological and temporal information, have become the state-of-the-art (SOTA) to complete TKGs. However, these studies are based on hand-designed architectures and fail to explore the divers

Arunkumar A, Mudit Batra, Umesh S

In a multilingual country like India, multilingual Automatic Speech Recognition (ASR) systems have much scope. Multilingual ASR systems exhibit many advantages like scalability, maintainability, and improved performance over the monolingual ASR systems. However, building multilingual systems for Indian languages is challenging since different languages use d

Hiroshi Itoyama, Takeshi Oota, Reiji Yoshioka

A sequence of massive scaling limits of the $\beta$-deformed $A_{n-1}$ quiver matrix model that keeps the size of the matrices finite and that corresponds to the $N_{f} =2n \rightarrow 2n-1, 2n-2$ limits on the number of flavors at 4d $su(n)$ ${\cal N} = 2$ SUSY gauge theory side is carried out to provide us with the integral representation of $su(n)$ irregu

Xiangzhi Cao

In this paper, we will show vanishing theorem of $p$ harmonic $1$ form on submanifold $M$ in $ \bar{M} $ whose BiRic curvature satisfying $ \overline{\mathrm{BiRic}}^a \geq \Phi_a(H,S) $. As an corollary, we can get the corresponding theorem for $ p $ harmonic function and $ p $ harmonic map. We also investigate the finiteness problem of $p$ harmonic $1$ for

James O Sullivan, Mohammad Arif Ul Alam

Person re-identification is a critical privacy breach in publicly shared healthcare data. We investigate the possibility of a new type of privacy threat on publicly shared privacy insensitive large scale wearable sensing data. In this paper, we investigate user specific biometric signatures in terms of two contextual biometric traits, physiological (photople

Wei-Chang Yeh

The binary-state network, a basic network, and its components are either working or failed. It is fundamental to all types of current networks, such as utility networks (gas, water, electricity, and 4G/5G), the Internet of Things (IoT), social networks, and supply chains. Network reliability is an important index in the planning, design, evaluation, and cont

Yue-Yue Tian, Bo-Yuan Ning, X. -D. Xiang, Hui-Fen Zhang

Equation of state (EOS) for bcc tungsten at 300 K (or 3000 K) up to 1000 GPa (or 300 GPa) was predicted for the first time by solving the partition function via a direct integral approach (DIA) with ab initio calculations of the atoms' interactions. Compared with available experiments under static compressions up to 150 GPa (or 35 GPa) for room temperature (

Deepan Muthirayan, Jianjun Yuan, Pramod P. Khargonekar

In this paper, we investigate the framework of Online Convex Optimization (OCO) for online learning. OCO offers a very powerful online learning framework for many applications. In this context, we study a specific framework of OCO called {\it OCO with long term constraints}. Long term constraints are introduced typically as an alternative to reduce the compl

Pravin Khanal, Bowei Zhou, Hamid Almasi, Ali Habiboglu

The interfacial oxidation level and thermodynamic properties of the MgO-based perpendicular magnetic tunneling junctions are investigated. The symmetry-conserved tunneling effect depends sensitively on the MgO adatom energy during the RF sputtering, as well as the thermal stability of the structure during the post-growth thermal annealing. Two different fail

Dejun Luo, Bin Tang

We consider the stochastic inviscid Leray-$\alpha$ model on the torus driven by transport noise. Under a suitable scaling of the noise, we prove that the weak solutions converge, in some negative Sobolev spaces, to the unique solution of the deterministic viscous Leray-$\alpha$ model. This implies that transport noise regularizes the inviscid Leray-$\alpha$

Huan Yee Koh, Jiaxin Ju, He Zhang, Ming Liu

Abstractive summarization has made tremendous progress in recent years. In this work, we perform fine-grained human annotations to evaluate long document abstractive summarization systems (i.e., models and metrics) with the aim of implementing them to generate reliable summaries. For long document abstractive models, we show that the constant strive for stat