August 2022 arXiv papers — page 114

Silvia Müllner, Florian Büscher, Angela Möller, Peter Lemmens

We use vortex photon fields with orbital and spin angular momentum to probe chiral fluctuations within liquid crystals. In the regime of iridescence with a well-defined pitch length of chirality, we find low energy Raman scattering that can be decomposed into helical and chiral components depending on the scattering vector and the topological charge of the i

Mengyang Liu, Haozheng Luo, Leonard Thong, Yinghao Li

Weak labeling is a popular weak supervision strategy for Named Entity Recognition (NER) tasks, with the goal of reducing the necessity for hand-crafted annotations. Although there are numerous remarkable annotation tools for NER labeling, the subject of integrating weak labeling sources is still unexplored. We introduce a web-based tool for text annotation c

Qiyu Dai, Jiyao Zhang, Qiwei Li, Tianhao Wu

Commercial depth sensors usually generate noisy and missing depths, especially on specular and transparent objects, which poses critical issues to downstream depth or point cloud-based tasks. To mitigate this problem, we propose a powerful RGBD fusion network, SwinDRNet, for depth restoration. We further propose Domain Randomization-Enhanced Depth Simulation

Dan Jia, Alexander Hermans, Bastian Leibe

We propose a new attention mechanism, called Global Hierarchical Attention (GHA), for 3D point cloud analysis. GHA approximates the regular global dot-product attention via a series of coarsening and interpolation operations over multiple hierarchy levels. The advantage of GHA is two-fold. First, it has linear complexity with respect to the number of points,

Ephraim Fischbach, Dennis E. Krause, Quan Le Thien, Carol Scarlett

Recently announced results from the KATRIN collaboration imply an upper bound on the effective electron anti-neutrino mass $m_{\nu_{e}}$, $m_{\nu_{e}}< 0.8~{\rm eV}/c^{2}$. Here we explore the implications of combining the KATRIN upper bound using a previously inferred lower bound on the smallest neutrino mass state, $m_{i,{\rm min}}\gtrsim 0.4~{\rm eV}/c^{2

Rishabh Agrawal, Nirav Ajmeri, Munindar P. Singh

Norms help regulate a society. Norms may be explicit (represented in structured form) or implicit. We address the emergence of explicit norms by developing agents who provide and reason about explanations for norm violations in deciding sanctions and identifying alternative norms. These agents use a genetic algorithm to produce norms and reinforcement learni

Sela Fried

Suppose that the $n^2$ vertices of the grid graph $P_n^2$ are labeled, such that the set of their labels is $\{1,2,\ldots,n^2\}$. The labeling induces a walk on $P_n^2$, beginning with the vertex whose label is $1$, proceeding to the vertex whose label is $2$, etc., until all vertices are visited. The question of the maximal possible length of such a walk, d

David J. Benson

We answer in the negative a question of Hartley about representations of finite groups, by constructing examples of finite simple groups with arbitrarily large representations whose endomorphism ring consists of just the scalars. We show as a consequence that there are finite simple groups of automorphisms of the locally finite simple group $SL(\infty,\mathb

Udit Halder, Vidya Raju, Matteo Mischiati, Biswadip Dey

Avian flocks display a wide variety of flight behaviors, including steady directed translation of center of mass, rapid change of overall morphology, re-shuffling of positions of individuals within a persistent form, etc. These behaviors may be viewed as flock-scale strategies, emerging from interactions between individuals, accomplishing some collective ada

Aimen Gaba, Vidya Setlur, Arjun Srinivasan, Jane Hoffswell

The language for expressing comparisons is often complex and nuanced, making supporting natural language-based visual comparison a non-trivial task. To better understand how people reason about comparisons in natural language, we explore a design space of utterances for comparing data entities. We identified different parameters of comparison utterances that

Roberta De Viti, Isaac Sheff, Noemi Glaeser, Baltasar Dinis

Analytics on personal data, such as individuals' mobility, financial, and health data can be of significant benefit to society. Such data is already collected by smartphones, apps and services today, but liberal societies have so far refrained from making it available for large-scale analytics. Arguably, this is due at least in part to the lack of an analyti

Tyler J. Evans, Alice Fialowski

Consider the maximal nilpotent subalgebra $n_+(A_1^{(1)})$ of the simplest affine algebra $A_1^{(1)}$ which is one of the $\mathbb{N}$-graded Lie algebras with minimal number of generators. We show truncated versions of this algebra in positive characteristic admit the structure of a family of restricted Lie algebras. We compute the ordinary and restricted 1

Tulio R. Ricciardi, William R. Wolf

Large eddy simulations are performed to study tonal noise generation by a NACA0012 airfoil at an angle of attack ${\alpha = 3}$ deg. and freestream Mach number of ${M_{\infty} = 0.3}$. Different Reynolds numbers are analyzed spanning ${0.5 \times 10^5 \le Re \le 4 \times 10^5}$. Results show that the flow patterns responsible for noise generation appear from

Yohei Watanabe, Naoto Yanai, Junji Shikata

IoT technology has been developing rapidly, while at the same time, notorious IoT malware such as Mirai is a severe and inherent threat. We believe it is essential to consider systems that enable us to remotely control infected devices in order to prevent or limit malicious behaviors of infected devices. In this paper, we design a promising candidate for suc

Tal Rubin, Elijah J. Kolmes, Ian E. Ochs, Mikhail E. Mlodik

Recently, a method to achieve a "natural hot-ion mode" was suggested, by utilizing ion viscous heating in a rotating plasma with a fixed boundary. We explore the steady-state solution to the Braginskii equations and find the parameter regime in which a significant temperature difference between ions and electrons can be sustained in a driven steady state. Th

Shashank Reddy Vadyala, Sai Nethra Betgeri

In this work, the generalized broken soliton-like (gBS-like) equation is derived through the generalized bilinear method. The neural network model, which can fit the explicit solution with zero error, is found. The interference wave solution of the gBS-like equation is obtained by using the bilinear neural network method (BNNM) and physical informed neural n

Minmin Liu, Xuechen Li, Xiangbo Gao, Junliang Chen

Due to the difficulty of cancer samples collection and annotation, cervical cancer datasets usually exhibit a long-tailed data distribution. When training a detector to detect the cancer cells in a WSI (Whole Slice Image) image captured from the TCT (Thinprep Cytology Test) specimen, head categories (e.g. normal cells and inflammatory cells) typically have a

Zohar Finkelstein, Kfir Sulimany, Shachar Resisi, Yaron Bromberg

In the past few years, there is a renewed interest in using multimode fibers for a wide range of technologies such as communication, imaging and spectroscopy. Practical implementations of multimode fiber in such applications, however, are held back, due to the challenges in dealing with modal dispersion, mode coupling and the fiber's sensitivity to mechanica

Mohamed ElKabbash, Nathaniel Hoffman, Andrew R Lininger, Sohail A. Jalil

Structural coloring is a photostable and environmentally friendly coloring approach that harnesses optical interference and nanophotonic resonances to obtain colors with a range of applications including steganography, d\'ecor, data storage, and anticounterfeiting measures. We show that optical coatings exhibiting the photonic Fano Resonance is an ideal plat

Ethan Mills, Alexey Pozdnyakov

Differential equations are used in a wide variety of disciplines, describing the complex behavior of the physical world. Analytic solutions to these equations are often difficult to solve for, limiting our current ability to solve complex differential equations and necessitating sophisticated numerical methods to approximate solutions. Trained neural network

Hieu H. Pham, Louahdi Khoudour, Alain Crouzil, Pablo Zegers

Human action recognition is an important application domain in computer vision. Its primary aim is to accurately describe human actions and their interactions from a previously unseen data sequence acquired by sensors. The ability to recognize, understand, and predict complex human actions enables the construction of many important applications such as intel

Israel Michael Sigal

We review very briefly the main mathematical structures and results in some important areas of Quantum Mechanics involving PDEs and formulate open problems.

Roshan Sah, Raunak Srivastava, Kaushik Das

Today\'s world of space\'s primary concern is the uncontrolled growth of space debris and its probability of collision with spacecraft, particularly in the low earth orbit (LEO) regions. This paper is aimed to design an optimized micro-propulsion system, Cold Gas Thruster, to de-orbit the PSLV debris from 668km to 250 km height after capturing process. The p

Hongtao Hao, Yumian Cui, Zhengxiang Wang, Yea-Seul Kim

The IEEE VIS Conference (VIS) recently rebranded itself as a unified conference and officially positioned itself within the discipline of Data Science. Driven by this movement, we investigated (1) who contributed to VIS, and (2) where VIS stands in the scientific world. We examined the authors and fields of study of 3,240 VIS publications in the past 32 year

Itzhak Goldman, Rabindra N. Mohapatra, Shmuel Nussinov, Yongchao Zhang

It was pointed out in a recent paper that the observed cooling rate of old, cold neutron stars (NS) can provide an upper limit on the transition rate of neutron to mirror neutron ($n-n'$). This limit is so stringent that it would preclude any discovery of $n \to n'$ oscillation in the current round of terrestrial searches for the process. Motivated by this c

Farrukh Mukhamedov, Abdessatar Souissi, Tarek Hamdi, Amen Allah Andolsi

In the present paper, we construct QMC (Quantum Markov Chains) associated with Open Quantum Random Walks such that the transition operator of the chain is defined by OQRW and the restriction of QMC to the commutative subalgebra coincides with the distribution of OQRW. Furthermore, we first propose a new construction of QMC on trees, which is an extension of

Farrukh Mukhamedov, Abdessatar Souissi, Tarek Hamdi

In the present paper, we construct QMC (Quantum Markov Chains) associated with Open Quantum Random Walks such that the transition operator of the chain is defined by OQRW and the restriction of QMC to the commutative subalgebra coincides with the distribution $P_\rho$ of OQRW. However, we are going to look at the probability distribution as a Markov field ov

J. C. Texca García, D. Rosales Herrera, J. E. Ramírez, A. Fernández Téllez

We investigate the finite-size effects on the transition temperature associated with the quark-gluon plasma (QGP) formation. From a percolation perspective, the onset of the QGP in high-energy collisions occurs when the spanning cluster of color strings emerges. The principal result presented here is the finite-size effects on the transition temperature expr

Farrukh Mukhamedov, Abdessatar Souissi

In this paper, we continue the investigation of quantum Markov states (QMS) and define their mean entropies. Such entropies are explicitly computed under certain conditions. The present work takes a huge leap forward at tackling one of the most important open problems in quantum probability which concerns the calculations of mean entropies of quantum Markov

Arjun Ashok, K J Joseph, Vineeth Balasubramanian

In class-incremental learning, the model is expected to learn new classes continually while maintaining knowledge on previous classes. The challenge here lies in preserving the model's ability to effectively represent prior classes in the feature space, while adapting it to represent incoming new classes. We propose two distillation-based objectives for clas

Silvia N. Santalla, Giovanni Ramírez, Sudipto Singha Roy, Germán Sierra

The time evolution of a quantum state with short-range correlations after a quench to a one-dimensional critical Hamiltonian can be understood using the quasi-particle picture, which states that local entanglement spreads as if it was carried by quasi-particles which separate at a fixed speed. We extend the quasi-particle picture using the recently introduce

G. Grätzer, R. Quackenbush

If $A$ is an algebra and \bgt is a tolerance on $A$, then $A/\bgt$ is a multi-algebra in a natural way. We give an example to show that not every multi-algebra arises in this manner. We slightly generalize the construction of $A/\bgt$ and prove that every multi-algebra arises from this modified construction.

Tejan Karmali, Rishubh Parihar, Susmit Agrawal, Harsh Rangwani

Progress in GANs has enabled the generation of high-resolution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such images via mathematical operations on the latent style vectors in the W/W+ space that effectively modulate the rich hierarchical representations of the generator. Such operations have recen

Lin Li, Long Chen, Hanrong Shi, Wenxiao Wang

The Scene Graph Generation (SGG) task aims to detect all the objects and their pairwise visual relationships in a given image. Although SGG has achieved remarkable progress over the last few years, almost all existing SGG models follow the same training paradigm: they treat both object and predicate classification in SGG as a single-label classification prob

Fabian Resare, Johannes Hofmann

Motivated by recent advances in the creation of few-body atomic Fermi gases with attractive interactions, we study theoretically the few-to-many-particle crossover of pair excitations, which for large particle numbers evolve into a mode that describes amplitude fluctuations of the superfluid order parameter (the "Higgs" mode). Our analysis is based on the hy

Ronaldas Paulius Lencevičius

The neural tangent kernel is a kernel function defined over the parameter distribution of an infinite width neural network. Despite the impracticality of this limit, the neural tangent kernel has allowed for a more direct study of neural networks and a gaze through the veil of their black box. More recently, it has been shown theoretically that the Laplace k

Dmitry Rabinovich, Alfred M. Bruckstein

We study a combinatorial problem inspired by the following scenario: fully autonomous vehicles drive on a multi-lane ($m \geq 2$) road. Each vehicle heads to its own destination and is allowed to exit the road only through a single designated off-ramp lane. However, an individual vehicle has a severely limited memory and sensing capabilities, and, moreover,

Ivan Chajda, Helmut Länger

Weakly orthomodular and dually weakly orthomodular lattices were introduced by the authors in a recent paper. Similarly as for orthomodular lattices we try to introduce an implication in these lattices which can be easily axiomatized and which yields a nice lattice structure. As shown in the paper, this can be realized in several different ways. Moreover, we

Jerry Anunrojwong, Krishnamurthy Iyer, David Lingenbrink

We consider a persuasion problem between a sender and a receiver whose utility may be nonlinear in her belief; we call such receivers risk-conscious. Such utility models arise when the receiver exhibits systematic biases away from expected-utility-maximization, such as uncertainty aversion (e.g., from sensitivity to the variance of the waiting time for a ser

Graziella Branduardi-Raymont, Chi Wang

This chapter describes the SMILE (Solar wind Magnetosphere Ionosphere Link Explorer) mission, currently under development as a joint project of the European Space Agency and the Chinese Academy of Sciences. SMILE aims to study the solar wind coupling with the terrestrial magnetosphere in a very novel and global way, by imaging the Earth's magnetosheath and c

Mi Hu

In this paper, we investigate the behavior of orbits inside parabolic basins. Let $f(z)=z+az^{m+1}+(\text{higher terms}), m\geq1, a\neq0.$ We choose an arbitrary constant $C>0$ and a point $q\in{\bf v_j}\cap\mathcal{P}_j$. Then there exists a point $z_0\in \mathcal{P}_j$ so that for any $\tilde{q}\in Q:= \cup_{l=0}^{\infty}f^{-l}(f^k(q)) (l, k$ are non-negat

Kyle R. Helson, Stefan Arseneau, Alyssa Barlis, Charles L. Bennett

Infrared-blocking scattering aerogel filters have a broad range of potential applications in astrophysics and planetary science observations in the far-infrared, sub-millimeter, and microwave regimes. Successful dielectric modeling of aerogel filters allowed the fabrication of samples to meet the mechanical and science instrument requirements for several exp

Huairui Wang, Zhenzhong Chen

Learned video compression methods have gained a variety of interest in the video coding community since they have matched or even exceeded the rate-distortion (RD) performance of traditional video codecs. However, many current learning-based methods are dedicated to utilizing short-range temporal information, thus limiting their performance. In this paper, w

Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian

Out-of-distribution (O.O.D.) generalization remains to be a key challenge for real-world machine learning systems. We describe a method for O.O.D. generalization that, through training, encourages models to only preserve features in the network that are well reused across multiple training domains. Our method combines two complementary neuron-level regulariz

Fubao Zhu, Guojie Wang, Chen Zhao, Saurabh Malhotra

Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can be displayed both in traditional short-axis (SA) cardiac planes and polar maps for interpretation and quantification. It is essential to reorient the reconstructed transaxial SPECT MPI into standard SA slices. This study is aimed to develop a deep-learning-based approach

R. Nikandish, M. Mehrara, M. J. Nikmehr

The essential annihilating-ideal graph $\mathcal{EG}(R)$ of a commutative unital ring $R$ is a simple graph whose vertices are non-zero ideals of $R$ with non-zero annihilator and there exists an edge between two distinct vertices $I,J$ if and only if $Ann(IJ)$ has a non-zero intersection with any non-zero ideal of $R$. In this paper, we show that $\mathcal{

Taichi Murayama, Yasuko Matsubara, Yasushi Sakurai

Large quantifies of online user activity data, such as weekly web search volumes, which co-evolve with the mutual influence of several queries and locations, serve as an important social sensor. It is an important task to accurately forecast the future activity by discovering latent interactions from such data, i.e., the ecosystems between each query and the

Mengting Li, Fengchun Zhang, Xiang Zhang, Yejian Lyu

Omni-directional pathloss, which refers to the pathloss when omni-directional antennas are used at the link ends, are essential for system design and evaluation. In the millimeter-wave (mm-Wave) and beyond bands, high gain directional antennas are widely used for channel measurements due to the significant signal attenuation. Conventional methods for omni-di

Yongqiang Wang, Tamer Basar

By enabling multiple agents to cooperatively solve a global optimization problem in the absence of a central coordinator, decentralized stochastic optimization is gaining increasing attention in areas as diverse as machine learning, control, and sensor networks. Since the associated data usually contain sensitive information, such as user locations and perso

Weiming Sun, Zimao Zhang

Fourier series multiscale method, a concise and efficient analytical approach for multiscale computation, will be developed out of this series of papers. The second paper is concerned with simultaneous approximation to functions and their (partial) derivatives. On the basis of sufficient conditions of 2r (r is a positive integer) times term-by-term different

A. Yu. Ulitskaya

In this paper, we develop a continual analog of decomposition over orthogonal bases in spaces generated by equidistant shifts of a single function. By doing so, we obtain an explicit expression for best approximation by spaces of shifts in $L_2(\mathbb{R})$. The result is formulated in terms of classical Fourier transform and tends to have various applicatio

Junchao Chen, Bo Yang, Bao-Feng Feng

In this paper, general rogue wave solutions in the massive Thirring (MT) model are derived by using the Kadomtsev-Petviashvili (KP) hierarchy reduction method and these rational solutions are presented explicitly in terms of determinants whose matrix elements are elementary Schur polynomials. In the reduction process, three reduction conditions including one

Mingying Zhong

In the present paper, we study the diffusion limit of the classical solution to the Vlasov-Poisson-Fokker-Planck (VPFP) system with initial data near a global Maxwellian. We prove the convergence and establish the optimal convergence rate of the global strong solution to the VPFP system towards the solution to the drift-diffusion-Poisson system based on the

G. Grätzer, G. Klus, A. Nguyen

In 1960, G. Gr\"atzer and E.\,T. Schmidt proved that every finite distributive lattice can be represented as the congruence lattice of a sectionally complemented finite lattice $L$. For $u \leq v$ in $L$, they constructed a sectional complement, which is now called the \emph{1960 sectional complement}. In 1999, G. Gr\"atzer and E.\,T. Schmidt discovered a ve

Sanja Danilovic

The chromosphere is a dynamic and complex layer where all the relevant physical processes happen on very small spatio-temporal scales. A few spectral lines that can be used as chromospheric diagnostics give us convoluted information that is hard to interpret without realistic theoretical models. What are the key ingredients that these models need to contain?

Hsiu-Fu Yeh

We consider the problem of computing 2-center in maximal outerplanar graph. In this problem, we want to find an optimal solution where two centers cover all the vertices with the smallest radius. We provide the following result. We can compute the optimal centers and the optimal radius in $O(n^2)$ time for a given maximal outerplanar graph with $n$ vertices.

Yunpeng Bai, Chao Dong, Cairong Wang

We study how to represent a video with implicit neural representations (INRs). Classical INRs methods generally utilize MLPs to map input coordinates to output pixels. While some recent works have tried to directly reconstruct the whole image with CNNs. However, we argue that both the above pixel-wise and image-wise strategies are not favorable to video data

Gábor Czédli, George Grätzer

We prove that a tolerance relation of a lattice is a homomorphic image of a congruence relation.

Satheesh K. Perepu, Jean P. Martins, Ricardo Souza S, Kaushik Dey

Recently, intent-based management has received good attention in telecom networks owing to stringent performance requirements for many of the use cases. Several approaches in the literature employ traditional closed-loop driven methods to fulfill the intents on the KPIs. However, these methods consider every closed-loop independent of each other which degrad

Gioacchino Antonelli, Enrico Pasqualetto, Marco Pozzetta, Daniele Semola

This paper studies sharp and rigid isoperimetric comparison theorems and asymptotic isoperimetric properties for small and large volumes on $N$-dimensional ${\rm RCD}(K,N)$ spaces $(X,\mathsf{d},\mathscr{H}^N)$. Moreover, we obtain almost regularity theorems formulated in terms of the isoperimetric profile and enhanced consequences at the level of several fu

Jacob Bryon, D. K. Weiss, Xinyuan You, Sara Sussman

Recent theoretical work has highlighted that quantizing a superconducting circuit in the presence of time-dependent flux $\Phi(t)$ generally produces Hamiltonian terms proportional to $d\Phi/dt$ unless a special allocation of the flux across inductive terms is chosen. Here, we present an experiment probing the effects of a fast flux ramp applied to a heavy-f

Charles Gauthier, Raghav Malhotra, Agustin Troccoli Moretti

This paper develops a framework to study the statistical power of revealed-preference tests. With randomly sampled budgets and mild smoothness of demand, statistical learning implies that any model consistent with the data must approximate true choice behaviour. We interpret this result as follows: passing a revealed-preference test is informative only to th

Evgeny Akhmedov, Alexei Y. Smirnov

Spatial separation of the wave packets (WPs) of neutrino mass eigenstates leads to decoherence and damping of neutrino oscillations. Damping can also be caused by finite energy resolution of neutrino detectors or, in the case of experiments with radioactive neutrino sources, by finite width of the emitted neutrino line. We study in detail these two types of

Brian Jiang, Luca Ciotti, Zhaoming Gan, Jeremiah Ostriker

Star formation in disk galaxies is observed to follow the empirical Kennicutt-Schmidt law, a power-law relationship between the surface density of gas ($\Sigma_{gas}$) [$\textrm{M}_{\odot}\; \textrm{kpc}^{-2}$] and the star formation rate ($\Sigma_{SFR}$) [$\textrm{M}_{\odot}\; \textrm{kpc}^{-2} \; \textrm{Gyr}^{-1}$]. In contrast to disk galaxies, early-typ

Hee Cheol Chung, Yang Ni, Irina Gaynanova

Sequencing-based technologies provide an abundance of high-dimensional biological datasets with skewed and zero-inflated measurements. Classification of such data with linear discriminant analysis leads to poor performance due to the violation of the Gaussian distribution assumption. To address this limitation, we propose a new semiparametric discriminant an

Gauhar Abbas, Vartika Singh, Neelam Singh, Ria Sain

We investigate flavour bounds on the $\mathcal{Z}_2 \times \mathcal{Z}_5$ and $\mathcal{Z}_2 \times \mathcal{Z}_9$ flavour symmetries. These flavour symmetries are a minimal and a non-minimal forms of the $\mathcal{Z}_2 \times \mathcal{Z}_N$ flavour symmetry, that can provide a simple set-up for the Froggatt-Nielsen mechanism. The $\mathcal{Z}_2 \times \math

Taekyun Kim, Dae san Kim

The Mersenne primes are primes which can be written as some prime power of 2 minus 1. These primes were studied from antiquity in that their close connection with perfect numbers and even to present day in that their easiness for primality test. In this paper, we introduce the dimorphic Mersenne numbers as a degenerate version of the Mersenne numbers and inv

Naresh Adhikari, Soichiro Morisaki

The detection of gravitational waves from compact binary coalescence (CBC) has allowed us to probe the strong-field dynamics of General Relativity (GR). Among various tests performed by the LIGO-Virgo-KAGRA collaboration are parameterized tests, where parameterized modifications to GR waveforms are introduced and constrained. This analysis typically requires

Ville J. Härkönen

We combine the recently developed many-body Green's function theory for electrons and nuclei with the exact factorization of the wave function. The existing Born-Oppenheimer Green's functions are shown to be special cases of our exact approach. We consider the limitations of the laboratory frame formulation of the Green's function theory and discuss why the

Z. -Y. Xiu, Y. -X. Jiang

In this article, we study new methods for constructing uninorms on bounded lattices. First, we present new methods for constructing uninorms on bounded lattices under the additional constraints and prove that some of these constraints are sufficient and necessary for the uninorms. Second, we show that the additional constraints on $t$-norms ($t$-conorms) and

Sneha Puri, Rochish M. Thaokar

In the present work, we conducted mechanical characterization of the membrane of human serum albumin (HSA) microcapsules using the electrodeformation technique which shows that HSA capsules are strain-softening in nature. The viscoelasto-electrohydrodynamic model was utilized to understand the creep mechanism in the HSA capsules. The effect of different reac

L. Feher

We consider three 'classical doubles' of any semisimple, connected and simply connected compact Lie group $G$: the cotangent bundle, the Heisenberg double and the internally fused quasi-Poisson double. On each double we identify a pair of 'master integrable systems' and investigate their Poisson reductions. In the simplest cotangent bundle case, the reductio

Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenjun Zeng

Multi-object tracking in videos requires to solve a fundamental problem of one-to-one assignment between objects in adjacent frames. Most methods address the problem by first discarding impossible pairs whose feature distances are larger than a threshold, followed by linking objects using Hungarian algorithm to minimize the overall distance. However, we find

Diederik Aerts, Jonito Aerts Arguëlles

For two decades, the formalism of quantum mechanics has been successfully used to describe human decision processes, situations of heuristic reasoning, and the contextuality of concepts and their combinations. The phenomenon of 'categorical perception' has put us on track to find a possible deeper cause of the presence of this quantum structure in human cogn

Daniel Castro, Hillel Aharoni

We consider planar liquid crystal elastomers: two dimensional objects made of anisotropic responsive materials, that upon activation remain flat however change their planar shape. We derive a closed form, analytical solution based on the implicit linearity featured by this subclass of deformations. Our solution provides the nematic director field on an arbit

King Leung Lee, Jacob Sturm, Xiaowei Wang

The moment map $\mu$ is a central concept in the study of Hamiltonian actions of compact Lie groups $K$ on symplectic manifolds. In this short note, we propose a theory of moment maps coupled with an $\mathrm{Ad}_K$-invariant convex function $f$ on $\mathfrak{k}^{\ast}$, the dual of Lie algebra of $K$, and study the properties of the critical point of $f\cir

Tong-Yu He, Ziqiang Cai, Rong-Jia Yang

We consider the accretion process in the thin disk around a supermassive black hole in Einstein-aether-scalar theory. We probe the effects of the model parameter on the physical properties of the disk. The results show that with increasing value of the parameter, the energy flux, the radiation temperature, the spectra cut-off frequency, the spectra luminosit

Yukio Ohsawa, Kaira Sekiguchi, Tomohide Maekawa, Hiroki Yamaguchi

A method for representing the digest information of each dataset is proposed, oriented to the aid of innovative thoughts and the communication of data users who attempt to create valuable products, services, and business models using or combining datasets. Compared with methods for connecting datasets via shared attributes (i.e., variables), this method conn

Adrian Zahariuc

We construct small resolutions of the moduli space $\overline{Q}_n$ of stable scaled $n$-marked lines of Ziltener and Ma'u--Woodward and of the moduli space $\overline{P}_n$ of stable $n$-marked ${\mathbb G}_a$-rational trees introduced in earlier work. The resolution of $\overline{P}_n$ is the augmented wonderful variety corresponding to the graphic matroid

Zhengyang Shen, Tao Hong, Qi She, Jinwen Ma

Steerable models can provide very general and flexible equivariance by formulating equivariance requirements in the language of representation theory and feature fields, which has been recognized to be effective for many vision tasks. However, deriving steerable models for 3D rotations is much more difficult than that in the 2D case, due to more complicated

Longxiang Jiang, Liyuan Wang, Xinkun Chu, Yonghao Xiao

Solving partial differential equations (PDEs) is an important research means in the fields of physics, biology, and chemistry. As an approximate alternative to numerical methods, PINN has received extensive attention and played an important role in many fields. However, PINN uses a fully connected network as its model, which has limited fitting ability and l

Ai Linh Nguyen, Wenyuan Liu, Khiam Aik Khor, Andrea Nanetti

Nowadays, patenting activities are essential in converting applied science to technology in the prevailing innovation model. To gain strategic advantages in the technological competitions between regions, nations need to leverage the investments of public and private funds to diversify over all technologies or specialize in a small number of technologies. In

Rui Cao, Qi-Li Gao, Guoping Qiu

Acceleration of urbanisation is posing great challenges to sustainable development. Growing accessibility to big data and artificial intelligence (AI) technologies have revolutionised many fields and offered great potential for addressing pressing urban problems. However, using these technologies without explicitly considering responsibilities would bring ne

Seongjin Choi, Jinwoo Lee

Parking is a crucial element of the driving experience in urban transportation systems. Especially in the coming era of Shared Autonomous Vehicles (SAVs), parking operations in urban transportation networks will inevitably change. Parking stations will serve as storage places for unused vehicles and depots that control the level-of-service of SAVs. This stud

Laura Tociu, Gregory Rassolov, Étienne Fodor, Suriyanarayanan Vaikuntanathan

Active systems, which are driven out of equilibrium by local non-conservative forces, exhibit unique behaviors and structures with potential utility for the design of novel materials. An important and difficult challenge along the path towards this goal is to precisely predict how the structure of active systems is modified as their driving forces push them

Zhengping Ji, Daizhan Cheng

The modeling and control of networks over finite lattices are studied via the algebraic state space approach. Using the semi-tensor product of matrices, we obtain the algebraic state space representation of the dynamics of (control) networks over finite lattices. Basic properties concerning networks over sublattices and product lattices are investigated, whi

Yufeng Shi, Zhi Yang

In this paper, we study one-dimensional backward stochastic differential equation (BSDE, for short), whose coefficient $f$ is Lipschitz in $y$ but only continuous in $z$. In addition, if the terminal condition $\xi$ has bounded Malliavin derivative, we prove some uniqueness results for the BSDE with quadratic and linear growth in $z$, respectively.

Tsofar Maniv, Vladimir Zhuravlev

The phenomenon of field-induced superconductor-to-insulator transitions observed experimentally in electron-doped SrTiO$_{3}$/LaAlO$_{3}$ interfaces, analyzed recently by means of 2D superconducting fluctuations theory (Phys. Rev. B \textbf{104}, 054503 (2021)), is revisited with new insights associating it with the appearance at low temperatures of field-in

Mandar Kulkarni, Soumya Chennabasavaraj, Nikesh Garera

With the broad reach of the internet and smartphones, e-commerce platforms have an increasingly diversified user base. Since native language users are not conversant in English, their preferred browsing mode is their regional language or a combination of their regional language and English. From our recent study on the query data, we noticed that many of the

Sarmad N. Mohammed, Semra Gündüç

In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The information obtained from random walks is converted to anonymous walks to extract the topological features of nodes. In

Mandar Kulkarni, Nikesh Garera

With the democratization of e-commerce platforms, an increasingly diversified user base is opting to shop online. To provide a comfortable and reliable shopping experience, it's important to enable users to interact with the platform in the language of their choice. An accurate query translation is essential for Cross-Lingual Information Retrieval (CLIR) wit

Heng Zhang, Xiaohong Chen

With the advancement of the data acquisition techniques, multi-view learning has become a hot topic. Some multi-view learning methods assume that the multi-view data is complete, which means that all instances are present, but this too ideal. Certain tensor-based methods for handing incomplete multi-view data have emerged and have achieved better result. How

Jung Hoon Han, Patrick A. Lee

A recent demonstration of the periodic oscillation of resistance in the thin film of CsV$_3$Sb$_5$ superconductor with a hole in the film suggests that charge-$4e$ and charge-$6e$ Cooper pairs may have condensed in this compound. While exciting, such interpretation calls for a precise determination of the effective area for the passage of Cooper pairs from o

Hakan Gokcesu, Suleyman S. Kozat

We study the prediction with expert advice setting, where the aim is to produce a decision by combining the decisions generated by a set of experts, e.g., independently running algorithms. We achieve the min-max optimal dynamic regret under the prediction with expert advice setting, i.e., we can compete against time-varying (not necessarily fixed) combinatio

Ahmed El Kerim, Pierre Gosselet, Frederic Magoules

The Global-Local non-invasive coupling is an improvement of the submodeling technique, which permits to locally enhance structure computations by introducing patches with refined models and to take into accounts all the interactions. In order to circumvent its inherently limited computational performance, we propose and implement an asynchronous version of t

Guanlong Bao, Fangqin Ye

For $0<s<1$, let $\{z_n\}$ be a sequence in the open unit disk such that $\sum_n (1-|z_n|^2)^s \delta_{z_n}$ is an $s$-Carleson measure. In this paper, we consider the connections between this $s$-Carleson measure and the theory of M\"obius invariant $F(p, p-2, s)$ spaces by the Volterra type operator, the reciprocal of a Blaschke product, and second order c

ali Ullah Khan, Zain Ali, Eva Lagunas, Asad Mahmood

This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while res

Sebastian Lutz, Richard Blythman, Koustav Ghosal, Matthew Moynihan

Monocular 3D human pose estimation technologies have the potential to greatly increase the availability of human movement data. The best-performing models for single-image 2D-3D lifting use graph convolutional networks (GCNs) that typically require some manual input to define the relationships between different body joints. We propose a novel transformer-bas

Malik Shahid Sultan, Samuel Horvath, Hernando Ombao

Dependence between nodes in a network is an important concept that pervades many areas including finance, politics, sociology, genomics and the brain sciences. One way to characterize dependence between components of a multivariate time series data is via Granger Causality (GC). Standard traditional approaches to GC estimation / inference commonly assume lin

Pascal Stadler, Mikael Fogelström

Electronic and transport properties of bilayer heterostructure under light irradiation are of fundamental interest to improve functionality of optoelectronic devices. We theoretically study the modification of transport properties of bilayer graphene and bilayer heterostructures under a time-periodic external light field. The bulk electronic and transport pr