January 2022 arXiv papers — page 42

Kenta Nakata, Ken-ichi Maruno

We propose a systematic method for constructing integrable delay-difference and delay-differential analogues of known soliton equations such as the Lotka-Volterra, Toda lattice, and sine-Gordon equations and their multi-soliton solutions. It is carried out by applying a reduction and delay-differential limit to the discrete KP or discrete two-dimensional Tod

Aika Tsunematsu, Kenta Nakata, Yuta Tanaka, Ken-ichi Maruno

Integrable delay analogues of the two-dimensional Toda lattice equation are presented and their muti-soliton solutions are constructed by applying the delay reduction to the Gram determinant solution.

Xiaochun An, Frank K. Soong, Lei Xie

End-to-end neural TTS has shown improved performance in speech style transfer. However, the improvement is still limited by the available training data in both target styles and speakers. Additionally, degenerated performance is observed when the trained TTS tries to transfer the speech to a target style from a new speaker with an unknown, arbitrary style. I

Mobolaji Williams

We introduce a derangement model of ligand-receptor binding that allows us to quantitatively frame the question "How can ligands seek out and bind to their optimal receptor sites in a sea of other competing ligands and suboptimal receptor sites?" To answer the question, we first derive a formula to count the number of partial generalized derangements in a li

Monisankha Pal, Aditya Raikar, Ashish Panda, Sunil Kumar Kopparapu

Recent works on speech spoofing countermeasures still lack generalization ability to unseen spoofing attacks. This is one of the key issues of ASVspoof challenges especially with the rapid development of diverse and high-quality spoofing algorithms. In this work, we address the generalizability of spoofing detection by proposing prototypical loss under the m

Naresh Dadhich

Black hole and Buchdahl star are identified respectively by $\Phi(R)=1/2, 4/9$ where $g_{tt}=1-2\Phi(R)$ for a spherically symmetric static metric. We investigate the maximum force for black hole and Buchdahl star when one of the participating objects is charged and/or rotating while the other is neutral and non-rotating. It turns out that the maximum force

Kai Li, Yong Xu

While non-Hermitian Hamiltonians have been experimentally realized in cold atom systems, it remains an outstanding open question of how to experimentally measure their complex energy spectra in momentum space for a realistic system with boundaries. The existence of non-Hermitian skin effects may make the question even more difficult to address given the fact

Mariia Anosova, Christof Gattringer, Tin Sulejmanpasic

We study U(1) gauge theories with a modified Villain action. Such theories can naturally be coupled to electric and magnetic matter, and display exact electric-magnetic duality. In their simplest formulation without a $\theta$-term, such theories are ultra-local. We extend the discussion to U(1) gauge theories with $\theta$-terms, such that $\theta$ periodic

Keisuke Okumura, Ryo Yonetani, Mai Nishimura, Asako Kanezaki

Multi-agent path planning (MAPP) in continuous spaces is a challenging problem with significant practical importance. One promising approach is to first construct graphs approximating the spaces, called roadmaps, and then apply multi-agent pathfinding (MAPF) algorithms to derive a set of conflict-free paths. While conventional studies have utilized roadmap c

Shota Fukushima

We prove a microlocal smoothing effect of Schr\"odinger equations on manifolds. We employ radially homogeneous wavefront sets introduced by Ito and Nakamura (Amer. J. Math., 2009). In terms of radially homogeneous wavefront sets, we can apply our theory to both of asymptotically conical and hyperbolic manifolds. We relate wavefront sets in initial states to

Xiwu Yang, Ni Lu, Xiaodong Chen, Yuansheng Yang

Let $\textrm{cr}(G)$ denote the crossing number of a graph $G$. The well-known Zarankiewicz's conjecture (ZC) asserted $\textrm{cr}(K_{m,n})$ in 1954. In 1971, Harborth gave a conjecture (HC) on $\textrm{cr}(K_{x_1,...,x_n})$. HC on $K_{1,m,n}$ is verified if ZC is true by Ho et al. in 2021. In this paper, we showed the following results: If both $m$ and $n$

Stephen Pankavich

We consider the repulsive Vlasov-Poisson system in dimension $d \geq 4$. A sufficient condition on the decay rate of the associated electric field is presented that guarantees the scattering and determination of the complete asymptotic behavior of large data solutions as $t \to \infty$. More specifically, we show that under this condition the spatial average

Zhengwei Bai, Guoyuan Wu, Xuewei Qi, Yongkang Liu

Endowed with automation and connectivity, Connected and Automated Vehicles are meant to be a revolutionary promoter for Cooperative Driving Automation. Nevertheless, CAVs need high-fidelity perception information on their surroundings, which is available but costly to collect from various onboard sensors as well as vehicle-to-everything (V2X) communications.

Alessandro Palmieri, Hiroyuki Takamura

In this paper, we consider a weakly coupled system of a wave and damped Klein-Gordon equation with nonlinearities of derivative type. We prove a blow-up result for the Cauchy problem associated with this system for nonnegative and compactly supported data by means of an iteration argument.

Shivanshu Tripathi, Anoop Jain, Abhisek K. Behera

A partially distributed economic dispatch algorithm, which renders optimal value in fixed time with the objective of supplying the load requirement as well as the power transmission losses, is proposed in this paper. The transmission losses are modeled using Kron's $\mathcal{B}-$loss formula, under a standard assumption on the values of $\mathcal{B}-$coeffic

Yuta Nakahara, Shota Saito, Akira Kamatsuka, Toshiyasu Matsushima

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical expressive capability causes a problem in tree selection to avoid overfitting. One unified approach to solve this is a Bayes

Yui Kasagi, Takayuki Kotani, Hajime Kawahara, Tomoyuki Tajiri

Photometric monitoring by the Transiting Exoplanet Survey Satellite (TESS) has discovered not only periodic signals by transiting exoplanets but also episodic or quasi-periodic dimming around young stellar objects. The mechanisms of the dimming of these objects, so-called "dippers", are thought to be related to the property of the accretion or the structure

Renjie Gu, Chaoyue Niu, Yikai Yan, Fan Wu

Data heterogeneity is an intrinsic property of recommender systems, making models trained over the global data on the cloud, which is the mainstream in industry, non-optimal to each individual user's local data distribution. To deal with data heterogeneity, model personalization with on-device learning is a potential solution. However, on-device training usi

Anh Khoa Lanh Luu, Van Tu Duong, Huy Hung Nguyen, Sang Bong Kim

Generally, humanoid robots usually suffer significant impact force when walking or running in a non-predefined environment that could easily damage the actuators due to high stiffness. In recent years, the usages of passive, compliant series elastic actuators (SEA) for driving humanoid's joints have proved the capability in many aspects so far. However, desp

Yan Li, Guanghui Lan, Tuo Zhao

We propose a new policy gradient method, named homotopic policy mirror descent (HPMD), for solving discounted, infinite horizon MDPs with finite state and action spaces. HPMD performs a mirror descent type policy update with an additional diminishing regularization term, and possesses several computational properties that seem to be new in the literature. We

Young-Woo Son, Hosub Jin, Sejoong Kim

We study electronic properties of a new planar carbon crystal formed through networking biphenylene molecules. Novel electronic features among carbon materials such as zone-center saddle point and peculiar type-II Dirac fermionic states are shown to exist in the low energy electronic spectrum. The type-II state here has a nearly flat branch and is close to a

Xu Liu, Shuang Li, Ming Xin

This paper develops a sequential convex programming approach for Mars entry trajectory planning by range discretization. To improve the accuracy of numerical integration, the range of entry trajectory is selected as the independent variable rather than time or energy. A dilation factor is employed to normalize the entry dynamics and integration interval of t

Jithin Jagannath, Anu Jagannath, Justin Henney, Tyler Gwin

The proliferation of wireless devices and their ever increasing influence on our day-to-day life is very evident and seems irreplaceable. This exponential growth in demand, both in terms of the number of devices and Quality of Service (QoS) had spawned the concept of cross-layer optimization several years ago. The primary goal of the cross-layer approach was

Dan Qiao, Zhaoxia Peng, Guoguang Wen, Tingwen Huang

Existing Nussbaum function based methods on the consensus of multi-agent systems require (partial) identical unknown control directions of all agents and cause dangerous dramatic control shocks. This paper develops a novel saturated Nussbaum function to relax such limitations and proposes a Nussbaum function based control scheme for the consensus problem of

Karola Mészáros, Linus Setiabrata, Avery St. Dizier

Grothendieck polynomials $\mathfrak{G}_w$ of permutations $w\in S_n$ were introduced by Lascoux and Sch\"utzenberger in 1982 as a set of distinguished representatives for the K-theoretic classes of Schubert cycles in the K-theory of the flag variety of $\mathbb{C}^n$. We conjecture that the exponents of nonzero terms of the Grothendieck polynomial $\mathfrak

Xiaobo Guo, Yaojia Sun, Soroush Vosoughi

According to the World Health Organization (WHO), one in four people will be affected by mental disorders at some point in their lives. However, in many parts of the world, patients do not actively seek professional diagnosis because of stigma attached to mental illness, ignorance of mental health and its associated symptoms. In this paper, we propose a mode

Kunchang Li, Yali Wang, Junhao Zhang, Peng Gao

It is a challenging task to learn discriminative representation from images and videos, due to large local redundancy and complex global dependency in these visual data. Convolution neural networks (CNNs) and vision transformers (ViTs) have been two dominant frameworks in the past few years. Though CNNs can efficiently decrease local redundancy by convolutio

Gregorio Chinni, Makhlouf Derridj

We prove via FBI-transform a result concerning the microlocal Gevrey regularity of analytic vectors for operators sums of squares of vector fields with real-valued real analytic coefficients of H\"ormander type, thus providing a microlocal version, in the analytic category, of a result due to M. Derridj in "Local estimates for H\"ormander's operators of firs

Ankit Kulshrestha, Vishwas Lele

There has been a steadily growing interest in development of novel methods to learn a representation of a given input data and subsequently using them for several downstream tasks. The field of natural language processing has seen a significant improvement in different tasks by incorporating pre-trained embeddings into their pipelines. Recently, these method

Chunnan Wang, Hongzhi Wang, Xiangyu Shi

Model compression methods can reduce model complexity on the premise of maintaining acceptable performance, and thus promote the application of deep neural networks under resource constrained environments. Despite their great success, the selection of suitable compression methods and design of details of the compression scheme are difficult, requiring lots o

Imoleayo Abel, Drew Steeves, Miroslav Krstic, Mrdjan Jankovic

Safety in dynamical systems is commonly pursued using control barrier functions (CBFs) which enforce safety-constraints over the entire duration of a system's evolution. We propose a prescribed-time safety (PTSf) design which enforces safety only for a finite time of interest to the user. While traditional CBF designs would keep the system away from the barr

Gregorio Chinni

The sharp Gevrey hypoellipticity is provided for the following generalization of the M\'etivier operator, "Non-hypoellipticit\'e analytique pour $D_{x}^{2}+\left( x^{2} + y^{2}\right)D_{y}^{2}$" by G. M\'etivier, \begin{align*} D_{x}^{2}+\left(x^{2n+1}D_{y}\right)^{2}+\left(x^{n}y^{m}D_{y}\right)^{2}, \end{align*} in $\Omega$ open neighborhood of the origin

Eric Larson, Isabel Vogt

In this paper we determine the number of general points through which a Brill--Noether curve of fixed degree and genus in any projective space can be passed.

Gregorio Chinni

The global and semi-global analytic hypoellipticity on the torus is proved for two classes of sums of squares operators, introduced in "Analytic Hypoellipticity for Sums of Squares and the Treves Conjecture" by P. Albano and A. Bove and M. Mughetti, and in "Analytic Hypoellipticity for Sums of Squares and the Treves Conjecture. II" by A. Bove and M. Mughetti

Antonio Bove, Gregorio Chinni

We consider sums of squares operators globally defined on the torus. We show that if some assumptions are satisfied the operators are globally analytic hypoelliptic. The purpose of the assumptions is to rule out the existence of a Hamilton leaf on the characteristic variety lying along the fiber of the cotangent bundle, i.e. the case of the (global) M\'etivi

Chun Wang, Yang Huang, Haibo Yuan, Huawei Zhang

We present a value-added catalog containing stellar parameters estimated from 7.10 million low-resolution spectra for 5.16 million unique stars with spectral signal-to-noise ratios (SNRs) higher than 10 obtained by the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Galactic spectroscopic surveys. The catalog presents values of stellar atm

Chen Wu, Sencun Zhu, Prasenjit Mitra

Federated Learning (FL) is designed to protect the data privacy of each client during the training process by transmitting only models instead of the original data. However, the trained model may memorize certain information about the training data. With the recent legislation on right to be forgotten, it is crucially essential for the FL model to possess th

Mu Chen, Yeping Jiang, Junping Peng, Huimin Zhang

The surface of a three-dimensional topological insulator (TI) hosts two-dimensional massless Dirac fermions (DFs), the gapless and spin-helical nature of which yields many exotic phenomena, such as the immunity of topological surface states (TSS) to back-scattering. This leads to their high transmission through surface defects or potential barriers. Quantum

Guangyue Huang, Bingqing Ma, Mingfang Zhu

In this paper, we achieve a Reilly type integral formula associated with the $\phi$-Laplacian. As its applications, we obtain Heintze-Karcher and Minkowski type inequalities. Furthermore, almost Schur lemmas are also given. They recover the partial results of Li and Xia in [15]. On the other hand, we also study eigenvalue problem for Wentzell boundary condit

Chun Wang, Haibo Yuan, Yang Huang

We have studied the zero-point offset of Gaia early Data Release 3 (EDR3) parallaxes based on a sample of 0.3 million giant stars built from the LAMOST data with distance accuracy better than 8.5\%. The official parallax zero-point corrections largely reduce the global offset in the Gaia EDR3 parallaxes: the global parallax offsets are $-$27.9 $\mu$as and $-

Leslie Ching Ow Tiong, HeeJeong Jasmine Lee, Kai Li Lim

With the recent prevalence of remote education, academic assessments are often conducted online, leading to further concerns surrounding assessment misconducts. This paper investigates the potentials of online assessment misconduct (e-cheating) and proposes practical countermeasures against them. The mechanism for detecting the practices of online cheating i

Naoki Kitazawa

The class of special generic maps is a natural class of smooth maps containing Morse functions on spheres with exactly two singular points and canonical projections of unit spheres. We find new restrictions on such maps on $6$-dimensional or higher dimensional closed and simply-connected manifolds into ${\mathbb{R}}^5$. Spheres which are not diffeomorphic to

Kumar Vijay Mishra, Arpan Chattopadhyay, Siddharth Sankar Acharjee, Athina P. Petropulu

With the use of common signaling methods for dual-function radar-communications (DFRC) systems, the susceptibility of eavesdropping on messages aimed at legitimate users has worsened. For DFRC systems, the radar target may act as an eavesdropper (ED) that receives a high-energy signal thereby leading to additional challenges. Unlike prior works, we consider

Yan-Xing Yang, Yao Wang, Zhao-Feng Ding, Adrian D. Hillier

Magnetic susceptibility, specific heat, and muon spin relaxation ($\mu$SR) measurements have been performed on a newly synthesized three-dimensional sandglass-type lattice Tm$_3$SbO$_7$, where two inequivalent sets of non-Kramers Tm$^{3+}$ ions (Tm$^{3+}_1$ and Tm$^{3+}_2)$ show crystal electrical field effect at different temperature ranges. The existence o

Minheng Xiao

This paper aims to more effectively manage and mitigate stock market risks by accurately characterizing financial market returns and volatility. We enhance the Stochastic Volatility (SV) model by incorporating fat-tailed distributions and leverage effects, estimating model parameters using Markov Chain Monte Carlo (MCMC) methods. By integrating extreme value

Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu

We initiate the study of active learning polynomial threshold functions (PTFs). While traditional lower bounds imply that even univariate quadratics cannot be non-trivially actively learned, we show that allowing the learner basic access to the derivatives of the underlying classifier circumvents this issue and leads to a computationally efficient algorithm

Xurong Xie, Xiang Sui, Xunying Liu, Lan Wang

The Mandarin Chinese language is known to be strongly influenced by a rich set of regional accents, while Mandarin speech with each accent is quite low resource. Hence, an important task in Mandarin speech recognition is to appropriately model the acoustic variabilities imposed by accents. In this paper, an investigation of implicit and explicit use of accen

Alexey A. Kryukov

The Bohigas-Giannoni-Schmit (BGS) conjecture states that the Hamiltonian of a microscopic analogue of a classical chaotic system can be modeled by a random matrix from a Gaussian ensemble. Here, this conjecture is considered in the context of a recently discovered geometric relationship between classical and quantum mechanics. Motivated by BGS, we conjecture

Yusuke Kousaka, Satoshi Iwasaki, Taisei Sayo, Hiroshi Tanida

We performed a crystal growth to obtain chirality-controlled enantiopure crystals using a laser-diode-heated floating zone (LDFZ) method with a composition-gradient feed rod. It has been argued that the crystal handedness of $T$Si ($T$ : transition metal) is fixed depending on $T$ in the case of the ones grown by the conventional methods. We found that right

Rajmohan Muthaiah, Fatema Tarannum, N. Yedukondalu, Jivtesh Garg

Designing and searching for high lattice thermal conductivity materials in both bulk and nanoscale level is highly demanding for electronics cooling. Boron phosphide is a III-V compound semiconductor with superior structural and thermal properties. In this work, we studied the lattice thermal conductivity of hexagonal boron phosphide(h-BP) using first princi

Jiayue Xu

The price of carbon emission rights play a crucial role in carbon trading markets. Therefore, accurate prediction of the price is critical. Taking the Shanghai pilot market as an example, this paper attempted to design a carbon emission purchasing strategy for enterprises, and establish a carbon emission price prediction model to help them reduce the purchas

Xue Jiang, Xiulian Peng, Chengyu Zheng, Huaying Xue

Deep-learning based methods have shown their advantages in audio coding over traditional ones but limited attention has been paid on real-time communications (RTC). This paper proposes the TFNet, an end-to-end neural speech codec with low latency for RTC. It takes an encoder-temporal filtering-decoder paradigm that has seldom been investigated in audio codin

Chang-woo Cho, Cheuk Yin Ng, Mahmoud Abdel-Hafiez, Alexander N. Vasiliev

We compare the upper critical field of bulk single-crystalline samples of the two intrinsic transition metal dichalcogenide (TMD) superconductors, 2H-NbSe2 and 2H-NbS2, in high magnetic fields where their layer structure is aligned strictly parallel and perpendicular to the field, using magnetic torque experiments and a high-precision piezo-rotary positioner

Rem Hida, Masaki Hamada, Chie Kamada, Emiru Tsunoo

Although end-to-end text-to-speech (TTS) models can generate natural speech, challenges still remain when it comes to estimating sentence-level phonetic and prosodic information from raw text in Japanese TTS systems. In this paper, we propose a method for polyphone disambiguation (PD) and accent prediction (AP). The proposed method incorporates explicit feat

Xu Yang, Xin Li

In this article we study the existence of solutions for the Dirac systems \begin{equation}\label{e:0.1} \left\{ \begin{array}{c} Pu=\frac{\partial H}{\partial v}(x,u,v) \quad\hbox{on} \ M, Pv=\frac{\partial H}{\partial u}(x,u,v) \quad\hbox{on} \ M, B_{\text{CHI}}u= B_{\text{CHI}}v=0\quad\hbox{on} \ \partial M \end{array} \right. \end{equation} where $M$ is a

Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck

Post-processing immunity is a fundamental property of differential privacy: it enables arbitrary data-independent transformations to differentially private outputs without affecting their privacy guarantees. Post-processing is routinely applied in data-release applications, including census data, which are then used to make allocations with substantial socie

Jiongzhi Zheng, Yawei Hong, Wenchang Xu, Wentao Li

The multiple Traveling Salesmen Problem (mTSP) is a general extension of the famous NP-hard Traveling Salesmen Problem (TSP), that there are m (m > 1) salesmen to visit the cities. In this paper, we address the mTSP with both the minsum objective and minmax objective, which aims at minimizing the total length of the $m$ tours and the length of the longest to

Sebastian Hensel, Yuning Liu

We investigate the sharp interface limit of a diffuse interface system that couples the Allen--Cahn equation with the instationary Navier--Stokes system in a bounded domain in $\mathbb{R}^d$ with $d \in \{2,3\}$. This model is used to describe a propagating front in a viscous incompressible flow with the width of the transition layer being characterized by a

Xurong Xie, Rukiye Ruzi, Xunying Liu, Lan Wang

Dysarthric speech recognition is a challenging task due to acoustic variability and limited amount of available data. Diverse conditions of dysarthric speakers account for the acoustic variability, which make the variability difficult to be modeled precisely. This paper presents a variational auto-encoder based variability encoder (VAEVE) to explicitly encod

Yin Dai, Yifan Gao, Fayu Liu, Jun Fu

Recent works on Multimodal 3D Computer-aided diagnosis have demonstrated that obtaining a competitive automatic diagnosis model when a 3D convolution neural network (CNN) brings more parameters and medical images are scarce remains nontrivial and challenging. Considering both consistencies of regions of interest in multimodal images and diagnostic accuracy,

A. Gómez, A. Martín-Ruiz, L. F. Urrutia

The CPT odd contribution to the effective electromagnetic action deriving from the vacuum polarization tensor in a large class of fermionic systems exhibiting Lorentz invariance violation (LIV) is calculated using thermal field theory methods, focusing upon corrections depending on the chemical potential. The systems considered exhibit the axial anomaly and

Zhi-Ping Liu, Min-Gang Zhou, Wen-Bo Liu, Chen-Long Li

Continuous-variable quantum key distribution (CV QKD) with discrete modulation has attracted increasing attention due to its experimental simplicity, lower-cost implementation and compatibility with classical optical communication. Correspondingly, some novel numerical methods have been proposed to analyze the security of these protocols against collective a

Yuling Jiao, Yang Wang, Yunfei Yang

This paper studies the approximation capacity of ReLU neural networks with norm constraint on the weights. We prove upper and lower bounds on the approximation error of these networks for smooth function classes. The lower bound is derived through the Rademacher complexity of neural networks, which may be of independent interest. We apply these approximation

Yuki Sughiyama, Atsushi Kamimura, Dimitri Loutchko, Tetsuya J. Kobayashi

We consider growing open chemical reaction systems (CRSs), in which autocatalytic chemical reactions are encapsulated in a finite volume and its size can change in conjunction with the reactions. The thermodynamics of growing CRSs is indispensable for understanding biological cells and designing protocells by clarifying the physical conditions and costs for

Kosuke Namekata, Hiroyuki Maehara, Satoshi Honda, Yuta Notsu

Young solar-type stars are known to show frequent "superflares", which may severely influence the habitable worlds on young planets via intense radiations and coronal mass ejections. Here we report an optical spectroscopic and photometric observation of a long-duration superflare on the young solar-type star EK Draconis (50-120 Myr age) with the Seimei teles

Min Qiu, Jinhong Yuan

We propose a new family of spatially coupled product codes, called sub-block rearranged staircase (SR-staircase) codes. Each code block of SR-staircase codes is obtained by encoding rearranged preceding code blocks and new information block, where the rearrangement involves sub-blocks decomposition and transposition. The proposed codes can be constructed to

Changcun Huang

This paper aims to interpret the mechanism of feedforward ReLU networks by exploring their solutions for piecewise linear functions, through the deduction from basic rules. The constructed solution should be universal enough to explain some network architectures of engineering; in order for that, several ways are provided to enhance the solution universality

Min Qiu, Xiaowei Wu, Jinhong Yuan, Alexandre Graell i Amat

A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes (PCCs) with a fraction of information bits repeated $q$ times. GSC-PCCs can be seen as a generalization of the original

Takashi Goda, Pierre L'Ecuyer

We study quasi-Monte Carlo (QMC) integration of smooth functions defined over the multi-dimensional unit cube. Inspired by a recent work of Pan and Owen, we study a new construction-free median QMC rule which can exploit the smoothness and the weights of function spaces adaptively. For weighted Korobov spaces, we draw a sample of $r$ independent generating v

Oliver Knill

Analytic torsion is a functional on graphs which only needs linear algebra to be defined. In the continuum it corresponds to the Ray-Singer analytic torsion. We have formulas for analytic torsion if the graph is contractible or if it is a discrete sphere. A key insight is that analytic torsion is the super determinant of the Dirac operator of the graph.

Ye Zhang, Chuchu Chen

We introduce Stochastic Asymptotical Regularization (SAR) methods for the uncertainty quantification of the stable approximate solution of ill-posed linear-operator equations, which are deterministic models for numerous inverse problems in science and engineering. We prove the regularizing properties of SAR with regard to mean-square convergence. We also sho

Yi Geng

The inclusion of material identification in wireless communication system is an emerging area that offers many opportunities for 6G systems. By using reflected radio wave to determine the material of reflecting surface, not only the performance of 6G networks can be improved, but also some exciting applications can be developed. In this paper, we recap a few

Essam A. Rashed, Sachiko Kodera, Akimasa Hirata

Background: Recently, a high number of daily positive COVID-19 cases have been reported in regions with relatively high vaccination rates; hence, booster vaccination has become necessary. In addition, infections caused by the different variants and correlated factors have not been discussed in depth. With large variabilities and different co-factors, it is d

Vinay Shukla, A. Swaminathan

In this manuscript, new algebraic and analytic aspects of the orthogonal polynomials satisfying $R_{II}$ type recurrence relation given by \begin{align*} \mathcal{P}_{n+1}(x) = (x-c_n)\mathcal{P}_n(x)-\lambda_n (x-a_n)(x-b_n)\mathcal{P}_{n-1}(x), \quad n \geq 0, \end{align*} where $\lambda_n$ is a positive chain sequence and $a_n$, $b_n$, $c_n$ are sequences

Fanfei Meng, Sheng Wang, Chengbin Xu

In this paper, we study the dynamics behavior of the NLS system with three waves interaction in the energy space $H^1(\mathbb{R}^5) \times H^1(\mathbb{R}^5)\times H^1(\mathbb{R}^5) $. Inspired by B. Dodson and J. Murphy in \cite{Dodson2018}, we establish an interaction Morawetz estimate for the NLS system, together with the criterion which proved by Tao-Dods

Xingjiao Wu, Luwei Xiao, Xiangcheng Du, Yingbin Zheng

The document layout analysis (DLA) aims to decompose document images into high-level semantic areas (i.e., figures, tables, texts, and background). Creating a DLA framework with strong generalization capabilities is a challenge due to document objects are diversity in layout, size, aspect ratio, texture, etc. Many researchers devoted this challenge by synthe

Lijun Bo, Agostino Capponi, Chao Zhou

We study the forward investment performance process (FIPP) in an incomplete semimartingale market model with closed and convex portfolio constraints, when the investor's risk preferences are of the power form. We provide necessary and sufficient conditions for the existence of such FIPP. In a semimartingale factor model, we show that the FIPP can be recovere

Aaron Nicolson, Jason Dowling, Bevan Koopman

Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators -- which are predominantly encoder-to-decoder models -- lack the diagnostic accuracy to be deployed in a clinical setting. To improve CXR report generation, we investig

Andrew R. Wade, Kirk McKenzie

We present an approach to mitigate coating thermal noise in optical cavities by using multiple TEM spatial modes to readout and stabilize laser frequency. With optimal weightings we synthesize a wider sampling of the mirror surface, improving averaging of Brownian thermal fluctuation. We show thermal noise improvement factors of 1.57, comparable to a MESA be

Chin-Ping Hu, Wataru Ishizaki, C. -Y. Ng, Shuta J. Tanaka

We present a systematic study of particle transport by diffusion in young pulsar wind nebulae (PWNe). We selected nine bright sources that are well resolved with the Chandra X-ray Observatory. We analyzed archival data to obtain their radial profiles of photon index ($\Gamma$) and surface brightness ($\Sigma$) in a consistent way. These profiles were then fi

Thomas Browning

The commuting probability of a finite group $G$ is the probability that two randomly chosen elements commute. Let $S\subseteq(0,1]$ denote the set of all possible commuting probabilities of finite groups. We prove that $S\cup\{0\}$ is closed, which was conjectured by Keith Joseph in 1977.

Joshua L. Pulsipher, Benjamin R. Davidson, Victor M. Zavala

We present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces (e.g., space and time) such as stochastic processes (e.g., time series, Gaussian processes, and Markov processes), random m

Ilia Smilga

In this note, we present some results that partially answer the following question. Let $G$ be a simple real Lie group; what is the set of representations $V$ of $G$ in which the longest element $w_0$ of the restricted Weyl group $W$ acts nontrivially on the subspace $V^L$ of $V$ formed by vectors that are invariant by $L$, the centralizer of a maximal split

Magnus Hellstrøm-Finnsen

This paper expands further on a category theoretical formulation of Hochschild cohomology for monoid objects in monoidal categories enriched over abelian groups, which has been studied in arXiv:1605.00842. This topic was also presented at ISCRA, Isfahan, Iran, April 2019. The present paper aims to provide a more intuitive formulation of the Hochschild cochai

Jiahao Huang, Yinzhe Wu, Huanjun Wu, Guang Yang

Magnetic resonance imaging (MRI) is a widely used non-radiative and non-invasive method for clinical interrogation of organ structures and metabolism, with an inherently long scanning time. Methods by k-space undersampling and deep learning based reconstruction have been popularised to accelerate the scanning process. This work focuses on investigating how p

Devin Jean, Suk Seo

Let $G$ be a graph of a network system with vertices, $V(G)$, representing physical locations and edges, $E(G)$, representing informational connectivity. A \emph{locating-dominating (LD)} set $S \subseteq V(G)$ is a subset of vertices representing detectors capable of sensing an "intruder" at precisely their location or somewhere in their open-neighborhood -

Wanyu Lin, Baochun Li, Cong Wang

Many real-world networks are inherently decentralized. For example, in social networks, each user maintains a local view of a social graph, such as a list of friends and her profile. It is typical to collect these local views of social graphs and conduct graph learning tasks. However, learning over graphs can raise privacy concerns as these local views often

Tianxiao Zhang, Bo Luo, Ajay Sharda, Guanghui Wang

Label assignment plays a significant role in modern object detection models. Detection models may yield totally different performances with different label assignment strategies. For anchor-based detection models, the IoU (Intersection over Union) threshold between the anchors and their corresponding ground truth bounding boxes is the key element since the p

Dominik Müller, Dennis Hartmann, Philip Meyer, Florian Auer

Correct performance assessment is crucial for evaluating modern artificial intelligence algorithms in medicine like deep-learning based medical image segmentation models. However, there is no universal metric library in Python for standardized and reproducible evaluation. Thus, we propose our open-source publicly available Python package MISeval: a metric li

Zhijian Li, Jack Xin, Guofa Zhou

We developed an integrated recurrent neural network and nonlinear regression spatio-temporal model for vector-borne disease evolution. We take into account climate data and seasonality as external factors that correlate with disease transmitting insects (e.g. flies), also spill-over infections from neighboring regions surrounding a region of interest. The cl

Sudhansu S. Biswal, Sushree S. Mishra, K. Sridhar

There is serious disagreement between the predictions of Non-Relativistic Quantum Chromodynamics (NRQCD) and the data on $J/\psi$ polarisation which has persisted for almost a quarter of a century. We find that if we account for the effect of perturbative soft gluons on the intermediate charm-anticharm octet states in NRQCD then the polarisation problem can

Houda Lamqaddam, Inez De Prekel, Koenraad Brosens, Katrien Verbert

Network representation is a crucial topic in historical social network analysis. The debate around their value and connotations, led by humanist scholars, is today more relevant than ever, seeing how common these representations are as support for historical analysis. Force-directed networks, in particular, are popular as they can be developed relatively qui

Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei

We study the problem of semi-supervised learning with Graph Neural Networks (GNNs) in an active learning setup. We propose GraphPart, a novel partition-based active learning approach for GNNs. GraphPart first splits the graph into disjoint partitions and then selects representative nodes within each partition to query. The proposed method is motivated by a n

Dmitrijs Kass, Ekta Vats

This work proposes an attention-based sequence-to-sequence model for handwritten word recognition and explores transfer learning for data-efficient training of HTR systems. To overcome training data scarcity, this work leverages models pre-trained on scene text images as a starting point towards tailoring the handwriting recognition models. ResNet feature ex

Arunava Naha, André Teixeira, Anders Ahlén, Subhrakanti Dey

The addition of a physical watermarking signal to the control input increases the detection probability of data deception attacks at the expense of increased control cost. In this paper, we propose a parsimonious policy to reduce the average number of watermarking events when the attack is not present, which in turn reduces the control cost. We model the sys

Hussein K. Alzubaidy, Dhiah Al-Shammary, Mohammed Hamzah Abed

In this survey, thirty models for steganography and visual encryption methods have been discussed to provide patients privacy protection.

Timothy Buttsworth, Maximilien Hallgren, Yongjia Zhang

We construct a rotationally invariant Ricci flow through surgery starting at any closed rotationally invariant Riemannian manifold. We demonstrate that a sequence of such Ricci flows with surgery converges to a Ricci flow spacetime in the sense of [32]. Results of Bamler-Kleiner [8] and Haslhofer [29] then guarantee the uniqueness and stability of these spac

Bhupesh Kumar, Patrick Sebbah

If disorder-induced Anderson localized states have been observed experimentally in optics, their study remains challenging leaving a number of open questions unsolved. Among them, the impact on Anderson localization of non-Hermiticity, optical gain and loss, and more generally, nonlinearities has been the subject of numerous theoretical debates, without yet

Sunhyuk Lim, Facundo Memoli

We generalize the classical Multidimensional Scaling procedure to the setting of general metric measure spaces. We develop a related spectral theory for the generalized cMDS operator, which provides a more natural and rigorous mathematical background for cMDS. Also, we show that the sum of all negative eigenvalues of the cMDS operator is a new invariant meas

Dhurgham Hassan Mahlool, Mohammed Hamzah Abed

This paper provides a comprehensive study of Federated Learning (FL) with an emphasis on components, challenges, applications and FL environment. FL can be applicable in multiple fields and domains in real-life models. in the medical system, the privacy of patients records and their medical condition is critical data, therefore collaborative learning or fede