March 2023 arXiv papers — page 74

Richárd Grünwald, Zsolt Páles

The purpose of this paper is to investigate the following invariance equation involving two $2$-variable generalized Bajraktarevi\'c means, i.e., we aim to solve the functional equation $$ f^{-1}\bigg(\frac{p_1(x)f(x)+p_2(y)f(y)}{p_1(x)+p_2(y)}\bigg)+g^{-1}\bigg(\frac{q_1(x)g(x)+q_2(y)g(y)}{q_1(x)+q_2(y)}\bigg)=x+y \qquad(x,y\in I), $$ where $I$ is a nonempt

Akram Ashyani, Yu-Heng Wu, Huan-Wei Hsu, Torbjörn E. M. Nordling

Dynamical compensation (DC) provides robustness to parameter fluctuations. As an example, DC enable control of the functional mass of endocrine or neuronal tissue essential for controlling blood glucose by insulin through a nonlinear feedback loop. Researchers have shown that DC is related to structural unidentifiability and $\mathbb{P}$-invariance property,

Alexandr Valyuzhenich

The $n$-dimensional hypercube has $n+1$ distinct eigenvalues $n-2i$, $0\leq i\leq n$, with corresponding eigenspaces $U_i(n)$. In 2021 it was proved by the author that if a function with non-empty support belongs to the direct sum $U_i(n)\oplus U_{i+1}(n)\oplus\ldots\oplus U_j(n)$, where $0\leq i\leq j\leq n$, then it has at least $\max(2^i,2^{n-j})$ non-zer

Aditya Dwarkesh, Amartya Goswami

The aim of this paper is to study the primitive ideals of Novikov algebras. In terms of modular maximal right ideals, a characterization of the primitive ideals of a Novikov algebra has been obtained. We prove a Chevalley-Jacobson density-type theorem for primitive Novikov algebras. We obtain some equivalences between prime, simple, and primitive Novikov alg

T. Konstantin Rusch, Michael M. Bronstein, Siddhartha Mishra

Node features of graph neural networks (GNNs) tend to become more similar with the increase of the network depth. This effect is known as over-smoothing, which we axiomatically define as the exponential convergence of suitable similarity measures on the node features. Our definition unifies previous approaches and gives rise to new quantitative measures of o

Bosco García-Archilla, Julia Novo

In this paper we analyze a pressure-robust method based on divergence-free mixed finite element methods with continuous interior penalty stabilization. The main goal is to prove an $O(h^{k+1/2})$ error estimate for the $L^2$ norm of the velocity in the convection dominated regime. This bound is pressure robust (the error bound of the velocity does not depend

Jinyoung Jun, Jae-Han Lee, Chang-Su Kim

A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a versatile depth estimator (VDE), composed of a common relative depth estimator (CRDE) and multiple relative-to-metric converters (R2MCs). The CRDE extracts relative depth information

Qifeng Lin, Rui Li, Feilong Zhang, Kai Kazuki

By leveraging their high mobility and small size, insects have been combined with microcontrollers to build up cyborg insects for various practical applications. Unfortunately, all current cyborg insects rely on implanted electrodes to control their movement, which causes irreversible damage to their organs and muscles. Here, we develop a non-invasive method

Harald Ruess, Natarajan Shankar

Cyberlogic is an enabling logical foundation for building and analyzing digital transactions that involve the exchange of digital forms of evidence. It is based on an extension of (first-order) intuitionistic predicate logic with an attestation and a knowledge modality. The key ideas underlying Cyberlogic are extremely simple, as (1) public keys correspond t

Giovanni E. Comi, Giorgio Stefani

We continue the study of the fine properties of sets having locally finite distributional fractional perimeter. We refine the characterization of their blow-ups and prove a Leibniz rule for the intersection of sets with locally finite distributional fractional perimeter with sets with finite fractional perimeter. As a byproduct, we provide a description of n

Khaled Kassem, Alia Saad

Socially Assistive Robots (SARs) are robots that are designed to replicate the role of a caregiver, coach, or teacher, providing emotional, cognitive, and social cues to support a specific group. SARs are becoming increasingly prevalent, especially in elderly care. Effective communication, both explicit and implicit, is a critical aspect of human-robot inter

Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp

In this work, we propose a realistic, physics-aware motion simulation procedure for T2*-weighted magnetic resonance imaging (MRI) to improve learning-based motion correction. As T2*-weighted MRI is highly sensitive to motion-related changes in magnetic field inhomogeneities, it is of utmost importance to include physics information in the simulation. Additio

Sara Frimodig, Per Enqvist, Jan Kronqvist

The number of cancer cases per year is rapidly increasing worldwide. In radiation therapy (RT), radiation from linear accelerators is used to kill malignant tumor cells. Scheduling patients for RT is difficult both due to the numerous medical and technical constraints, and because of the stochastic inflow of patients with different urgency levels. In this pa

Rainer Picard, Sascha Trostorff

We consider two operators $A_{0},B_{0}$ between two Hilbert spaces satisfying $A_{0}\subseteq-B_{0}^{\ast}$ and $B_{0}\subseteq-A_{0}^{\ast}$ and inspect extensions $A^{\#}$ and $B^{\#}$ of $A_{0}$ and $B_{0}$, respectively, whose domain consists of those elements satisfying an abstract periodic boundary condition. The motivating example is the derivative on

Weiping Yu, Siqiang Luo

We present FasCo, a simple yet effective learning-based estimator for the cost of executing a database query plan. FasCo uses significantly shorter training time and a lower inference cost than the state-of-the-art approaches, while achieving higher estimation accuracy. The effectiveness of FasCo comes from embedding abundant explicit execution-plan-based fe

Zhibo Jiang, Shaobo Zhang, Zhiwei Chen, Yang Yang

We have started a systematic survey of molecular clumps with infall motions to study the very early phase of star formation. Our first step is to utilize the data products by MWISP to make an unbiased survey for blue asymmetric line profiles of CO isotopical molecules. Within a total area of $\sim$ 2400 square degrees nearby the Galactic plane, we have found

Federico Califano

In this letter we propose a holistic analysis merging the techniques of passivity-based control (PBC) and control barrier functions (CBF). We constructively find conditions under which passivity of the closed-loop system is preserved under CBF-based safety-critical control. The results provide an energetic interpretation of safety-critical control schemes, a

Benjamin Scheidt, Nicole Schweikardt

We introduce the 2-sorted counting logic $GC^k$ that expresses properties of hypergraphs. This logic has available k variables to address hyperedges, an unbounded number of variables to address vertices, and atomic formulas E(e,v) to express that a vertex v is contained in a hyperedge e. We show that two hypergraphs H, H' satisfy the same sentences of the lo

Stephen W. Lovesey

The ferrimagnet Mn3Si2Te6 attracts attention because of a recently discovered colossal magnetoresistance (CMR) with unique magnetic field properties. An improved magnetic structure for the material has emerged from a neutron diffraction study linked to understanding the CMR. A deeper theoretical investigation of the magnetic structure has now revealed anapol

Wenliang Li

In quantum field theory, the Dyson-Schwinger equations are an infinite set of coupled equations relating $n$-point Green's functions in a self-consistent manner. They have found important applications in non-perturbative studies, ranging from quantum chromodynamics and hadron physics to strongly correlated electron systems. However, they are notoriously form

Motokazu Abe, Okuto Morikawa, Soma Onoda, Hiroshi Suzuki

We extend the definition of L\"uscher's lattice topological charge to the case of $4$d $SU(N)$ gauge fields coupled with $\mathbb{Z}_N$ $2$-form gauge fields. This result is achieved while maintaining the locality, the $SU(N)$ gauge invariance, and $\mathbb{Z}_N$ $1$-form gauge invariance, and we find that the manifest $1$-form gauge invariance plays the cen

Jiaer Xia, Lei Tan, Pingyang Dai, Mingbo Zhao

Occluded person re-identification (Re-ID) aims to address the potential occlusion problem when matching occluded or holistic pedestrians from different camera views. Many methods use the background as artificial occlusion and rely on attention networks to exclude noisy interference. However, the significant discrepancy between simple background occlusion and

Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu

In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint. Two major challenges prevail in VIC3D: 1) inherent calibration noise when fusing

Andrei Chertkov, Olga Tsymboi, Mikhail Pautov, Ivan Oseledets

Neural networks are deployed widely in natural language processing tasks on the industrial scale, and perhaps the most often they are used as compounds of automatic machine translation systems. In this work, we present a simple approach to fool state-of-the-art machine translation tools in the task of translation from Russian to English and vice versa. Using

Bilol Banerjee

In this article, we present a nonparametric method for the general two-sample problem involving functional random variables modelled as elements of a separable Hilbert space ${\cal H}$. First, we present a general recipe based on linear projections to construct a measure of dissimilarity between two probability distributions on ${\cal H}$. In particular, we

Jan Sellner, Silvia Seidlitz, Alexander Studier-Fischer, Alessandro Motta

Robust semantic segmentation of intraoperative image data could pave the way for automatic surgical scene understanding and autonomous robotic surgery. Geometric domain shifts, however, although common in real-world open surgeries due to variations in surgical procedures or situs occlusions, remain a topic largely unaddressed in the field. To address this ga

Dongliang Cao, Florian Bernard

The matching of 3D shapes has been extensively studied for shapes represented as surface meshes, as well as for shapes represented as point clouds. While point clouds are a common representation of raw real-world 3D data (e.g. from laser scanners), meshes encode rich and expressive topological information, but their creation typically requires some form of (

Ivan Hejný, Jonas Wallin, Małgorzata Bogdan

The Sorted L-One Estimator (SLOPE) is a popular regularization method in regression, which induces clustering of the estimated coefficients. That is, the estimator can have coefficients of identical magnitude. In this paper, we derive an asymptotic distribution of SLOPE for the ordinary least squares, Huber, and Quantile loss functions, and use it to study t

N. Dresing, L. Rodríguez-García, I. C. Jebaraj, A. Warmuth

Context. A solar eruption on 17 April 2021 produced a widespread Solar Energetic Particle (SEP) event that was observed by five longitudinally well-separated observers in the inner heliosphere at heliocentric distances of 0.42 to 1 au: BepiColombo, Parker Solar Probe, Solar Orbiter, STEREO A, and near-Earth spacecraft. The event produced relativistic electro

Marvin Fritz

In this survey article, a variety of systems modeling tumor growth are discussed. In accordance with the hallmarks of cancer, the described models incorporate the primary characteristics of cancer evolution. Specifically, we focus on diffusive interface models and follow the phase-field approach that describes the tumor as a collection of cells. Such systems

Xiaokang Chen, Yajie Xing, Gang Zeng

Semantic Scene Completion (SSC) aims to simultaneously predict the volumetric occupancy and semantic category of a 3D scene. In this paper, we propose a real-time semantic scene completion method with a feature aggregation strategy and conditioned prediction module. Feature aggregation fuses feature with different receptive fields and gathers context to impr

Rongxiang Weng, Qiang Wang, Wensen Cheng, Changfeng Zhu

Neural machine translation (NMT) has achieved remarkable success in producing high-quality translations. However, current NMT systems suffer from a lack of reliability, as their outputs that are often affected by lexical or syntactic changes in inputs, resulting in large variations in quality. This limitation hinders the practicality and trustworthiness of N

Mingming Cao, Kôzô Yabuta, Dachun Yang

We prove a compact version of the $T1$ theorem for bi-parameter singular integrals. That is, if a bi-parameter singular integral operator $T$ admits the compact full and partial kernel representations, and satisfies the weak compactness property, the diagonal $\mathrm{CMO}$ condition, and the product $\mathrm{CMO}$ condition, then $T$ can be extended to a co

Johno van IJsseldijk, Joeri Brackenhoff, Jan Thorbecke, Kees Wapenaar

The data-driven Marchenko method is able to redatum wavefields to arbitrary locations in the subsurface, and can, therefore, be used to isolate zones of specific interest. This creates a new reflection response of the target zone without interference from over- or underburden reflectors. Consequently, the method is well suited to obtain a clear response of a

Fei Si, Zheng Zhang, Chuyu Zhou

In this note, we prove two results regarding the variation of K-moduli. The first one reveals the relationship between the chamber decomposition for K-semistable domains and the variation of GIT. The second one presents the relationship between the K-moduli generically parametrizing K-semistable smooth Fano complete intersections of the form $S_1\cap...\cap

Kenneth Blomqvist, Francesco Milano, Jen Jen Chung, Lionel Ott

Recently, groundbreaking results have been presented on open-vocabulary semantic image segmentation. Such methods segment each pixel in an image into arbitrary categories provided at run-time in the form of text prompts, as opposed to a fixed set of classes defined at training time. In this work, we present a zero-shot volumetric open-vocabulary semantic sce

Qiang Qu, Xiaoming Chen, Yuk Ying Chung, Weidong Cai

Light field imaging can capture both the intensity information and the direction information of light rays. It naturally enables a six-degrees-of-freedom viewing experience and deep user engagement in virtual reality. Compared to 2D image assessment, light field image quality assessment (LFIQA) needs to consider not only the image quality in the spatial doma

Heather Doig, Oscar Pizarro, Stefan B. Williams

Autonomous Underwater Vehicles (AUVs) conduct regular visual surveys of marine environments to characterise and monitor the composition and diversity of the benthos. The use of machine learning classifiers for this task is limited by the low numbers of annotations available and the many fine-grained classes involved. In addition to these challenges, there ar

Nicky Zimmerman, Matteo Sodano, Elias Marks, Jens Behley

Object-based maps are relevant for scene understanding since they integrate geometric and semantic information of the environment, allowing autonomous robots to robustly localize and interact with on objects. In this paper, we address the task of constructing a metric-semantic map for the purpose of long-term object-based localization. We exploit 3D object d

Dongqi Li, Rong-Xin Miao

It is controversial whether entanglement islands can exist in massless gravity theories. Recently, it is found that the massless entanglement island appears in wedge holography with DGP gravity on the branes. In this paper, we generalize the discussions to the codim-n holography named cone holography. For simplicity, we focus on the case with a codim-2 E bra

Oliver Salazar Celis

The current implementation of Thiele rational interpolation in Maple (the ThieleInterpolation routine) breaks down when the points are not well-ordered. In this article, it is shown how this breakdown can be avoided by ordering the interpolation points in an adaptive way.

Peter Jürgens, Sylvianne D. C. Roscam Abbing, Mark Mero, Graham G. Brown

The generation of high-order harmonics in bulk solids subjected to intense ultrashort laser pulses has opened up new avenues for research in extreme nonlinear optics and light-matter interaction on sub-cycle timescales. Despite significant advancement over the past decade, a complete understanding of the involved phenomena is still lacking. High-harmonic gen

Zhiwei Cui, Baojiang Cui, Li Su, Haitao Du

The security context used in 5G authentication is generated during the Authentication and Key Agreement (AKA) procedure and stored in both the user equipment (UE) and the network sides for the subsequent fast registration procedure. Given its importance, it is imperative to formally analyze the security mechanism of the security context. The security context

Laya Das, Blazhe Gjorgiev, Giovanni Sansavini

Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data regime. These models serve as digital twins to generate large quantities of data to train DNNs which would otherwise be difficult to obtain from the real-life system. However, such

Daqi Fang, Pin-Chieh Tseng

We study the error-correction problem of the communication between two vertices in a social network. By applying the concepts of coding theory into the Social Network Analysis (SNA), we develop the code social network model, which can offer an efficient way to ensure the correctness of the message transmission within the social netwoks. The result of this st

Jean-Marie Malherbe

The spectroheliograph is a spectroscopic instrument designed to produce monochromatic images of the photosphere (the visible layer) and the chromosphere of the Sun. It was invented at the same time (1892), but independently, by Hale in the USA and Deslandres in France and was dedicated to long-term surveys of the solar cycles. For that purpose, systematic ob

Aristotelis Ballas, Christos Diou

Despite their immense success in numerous fields, machine and deep learning systems have not yet been able to firmly establish themselves in mission-critical applications in healthcare. One of the main reasons lies in the fact that when models are presented with previously unseen, Out-of-Distribution samples, their performance deteriorates significantly. Thi

Junjie Ye, Changhong Fu, Ziang Cao, Shan An

Most previous progress in object tracking is realized in daytime scenes with favorable illumination. State-of-the-arts can hardly carry on their superiority at night so far, thereby considerably blocking the broadening of visual tracking-related unmanned aerial vehicle (UAV) applications. To realize reliable UAV tracking at night, a spatial-channel Transform

Joackim Bernier, Sergio Blanes, Fernando Casas, Alejandro Escorihuela-Tomàs

We analyze the preservation properties of a family of reversible splitting methods when they are applied to the numerical time integration of linear differential equations defined in the unitary group. The schemes involve complex coefficients and are conjugated to unitary transformations for sufficiently small values of the time step-size. New and efficient

Haibin Yu, Yuxuan Hu, Yao Qian, Ma Jin

Code-switching speech refers to a means of expression by mixing two or more languages within a single utterance. Automatic Speech Recognition (ASR) with End-to-End (E2E) modeling for such speech can be a challenging task due to the lack of data. In this study, we investigate text generation and injection for improving the performance of an industry commonly-

Diego Chamorro, Claudiu Mîndrilă

We address here the problem of regularity for weak solutions of the 3D Boussinesq equation. By introducing the new notion of partial suitable solutions, which imposes some conditions over the velocity field only, we show a local gain of regularity for the two variables u and $\theta$.

Sudhir Pandurang Rode, Partha Pratim Bhaduri, Amaresh Jaiswal

We investigate the effect of flow fluctuations, incorporated in non boost-invariant blast-wave model, on kinetic freeze-out parameters of identified hadrons in low energy relativistic heavy-ion collisions. For the purpose of this study, we use the transverse momentum spectra of the identified hadrons produced in central Pb--Pb collisions, at SPS energies ran

Victor P. Ruban

A new type of long-lived solitary structures for paraxial optics with two circular polarizations of light in a homogeneous defocusing Kerr medium with an anomalous group velocity dispersion has been revealed numerically in the coupled nonlinear Schr\"odinger equations. A found hybrid three-dimensional soliton is a vortex ring against the background of a plan

Junyang Chen, Xiaoyu Xian, Zhijing Yang, Tianshui Chen

Pose transfer aims to transfer a given person into a specified posture, has recently attracted considerable attention. A typical pose transfer framework usually employs representative datasets to train a discriminative model, which is often violated by out-of-distribution (OOD) instances. Recently, test-time adaption (TTA) offers a feasible solution for OOD

Ege Özsoy, Felix Holm, Mahdi Saleh, Tobias Czempiel

Scene Graph Generation (SGG) is a visual understanding task, aiming to describe a scene as a graph of entities and their relationships with each other. Existing works rely on location labels in form of bounding boxes or segmentation masks, increasing annotation costs and limiting dataset expansion. Recognizing that many applications do not require location d

V. A. Bednyakov

The paper presents a theoretical approach to the description of the relativistic scattering of a massive (neutral) lepton on a nucleus, in which the latter retains its integrity. The measurable cross section of this process includes the elastic (or coherent) contribution, when the nucleus remains in its original quantum state and the inelastic (incoherent) c

Bolaji Yusuf, Aditya Gourav, Ankur Gandhe, Ivan Bulyko

End-to-end speech recognition models are improved by incorporating external text sources, typically by fusion with an external language model. Such language models have to be retrained whenever the corpus of interest changes. Furthermore, since they store the entire corpus in their parameters, rare words can be challenging to recall. In this work, we propose

Haoyu Wang, Shaoli Huang, Fang Zhao, Chun Yuan

We present a simple yet effective method for skeleton-free motion retargeting. Previous methods transfer motion between high-resolution meshes, failing to preserve the inherent local-part motions in the mesh. Addressing this issue, our proposed method learns the correspondence in a coarse-to-fine fashion by integrating the retargeting process with a mesh-coa

Xiwei Zhang, Tao Li, Yan Chen, Qianyuan Long

We propose a decentralized online learning algorithm for distributed random inverse problems over network graphs with online measurements, and unifies the distributed parameter estimation in Hilbert spaces and the least mean square problem in reproducing kernel Hilbert spaces (RKHS-LMS). We transform the convergence of the algorithm into the asymptotic stabi

Tijs Karman, Marcin Gronowski, Michal Tomza, Juliana J. Park

We present a combined experimental and theoretical study of the spectrum of magnetically tunable Feshbach resonances in NaLi $(a^3\Sigma^+)$ $+$ Na collisions. In the accompanying paper, we observe experimentally 8 and 17 resonances occur between $B=0$ and $1400$~G in upper and lower spin-stretched states, respectively. Here, we perform ab initio calculation

Tingting Shi, Wei Zhang, C. A. R. Sá de Melo

We discuss standard and tighter upper bounds on the critical temperature $T_c$ of two-dimensional (2D) superconductors and superfluids versus particle density $n$ or filling factor $\nu$ for continuum and lattice systems from the Bardeen-Cooper-Schrieffer (BCS) to Bose regime. We discuss only one-band Hamiltonians, where the transition from the normal to sup

Shengnan Feng, Rentong Duan, Yu Ju, Shuyi Li

Under continuous light illumination, it is known that localized domains with segregated halide compositions form in semiconducting mixed-halide perovskites, thus severely limiting their optoelectronic applications due to the negative changes in bandgap energies and charge-carrier characteristics. Here we deposit mixed-halide perovskite CsPbBr1.2I1.8 nanocrys

Cagri Gungor, Adriana Kovashka

Despite recent attention and exploration of depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integrating depth information. Our approach can be applied to any WSOD method based on multiple-instance learning, without necessitating

Ya Jing, Tao Kong

We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to unseen embodied tasks is insufficiently studied, which will help various relevant applications (e.g., home robots). Unlike static perception methods trained on pre-collected image

Penghui Yao, Zekun Ye

The query model has generated considerable interest in both classical and quantum computing communities. Typically, quantum advantages are demonstrated by showcasing a quantum algorithm with a better query complexity compared to its classical counterpart. Exact quantum query algorithms play a pivotal role in developing quantum algorithms. For example, the De

Hyun Ryu, Junil Choi

Modulation classification (MC) is the first step performed at the receiver side unless the modulation type is explicitly indicated by the transmitter. Machine learning techniques have been widely used for MC recently. In this paper, we propose a novel MC technique dubbed as Joint Equalization and Modulation Classification based on Constellation Network (EMC2

A. Chiesa, M. Kružík, U. Stefanelli

We analyze the finite-strain Poynting-Thomson viscoelastic model. In its linearized small-deformation limit, this corresponds to the serial connection of an elastic spring and a Kelvin-Voigt viscoelastic element. In the finite-strain case, the total deformation of the body results from the composition of two maps, describing the deformation of the viscoelast

Natarajan Shriethar, Nageswaran Rajendran

This work discusses a few theories including the interaction of dark matter, cosmic strings, and locally coupled dark energy. The paper also examines mathematical models used to describe the pressure and density within a star, including the polytropic relationship and the Lane-Emden equation. Simulation results from the IllustrisTNG datasets are also present

Nicola Mayer, David Ayuso, Piero Decleva, Margarita Khokhlova

The topological response of matter to electromagnetic fields is a property in high demand in materials design and metrology due to its robustness against noise and decoherence, stimulating recent advances in ultrafast photonics. Embedding topological properties into the enantio-sensitive optical response of chiral molecules could therefore enhance the effici

Gašper Beguš, Andrej Leban, Shane Gero

This paper proposes a methodology for discovering meaningful properties in data by exploring the latent space of unsupervised deep generative models. We combine manipulation of individual latent variables to extreme values with methods inspired by causal inference into an approach we call causal disentanglement with extreme values (CDEV) and show that this m

Andreas Wiedholz, Stefanie Wucherer, Simon Dietrich

Adapting robot programmes to changes in the environment is a well-known industry problem, and it is the reason why many tedious tasks are not automated in small and medium-sized enterprises (SMEs). A semantic world model of a robot's previously unknown environment created from point clouds is one way for these companies to automate assembly tasks that are ty

Svitlana Bilun, Bohdana Hladysh, Alexandr Prishlyak, Vladislav Sinitsyn

We describe all possible topological structures of codimension one gradient vector fields on the shpere with at most ten singular points. To describe structures, we use a graph whose edges are one-dimensional stable manifolds. The saddle-node singularity is specified by selecting a pair of vertices-edge or edge-face, and the saddle connection is specified by

Minh-Loc Bui, Le-Anh Nguyen, Panagiota Papakonstantinou, Naftali Auerbach

Recent high-energy heavy ion collision experiments have revealed that some atomic nuclei exhibit unusual softness and significant shape fluctuations. In this work, we use the fully self-consistent mean-field theory to identify all even-even nuclei that are unstable or soft against octupole deformation. All exceptional cases of enhanced octupole transition st

Yulong Zheng, Rahul Venkatesh, Connor P. Callaway, Campbell Viersen

Linear and nonlinear optical lineshapes reveal details of excitonic structure in semiconductor polymers. We implement absorption, photoluminescence, and transient absorption spectroscopies in DPP-DTT, an electron push-pull copolymer, to explore the relationship between their spectral lineshapes and chain conformation, deduced from resonance Raman spectroscop

Leran Ma, Ke Chen, Mingfu Shao

In computational biology, $k$-mers and edit distance are fundamental concepts. However, little is known about the metric space of all $k$-mers equipped with the edit distance. In this work, we explore the structure of the $k$-mer space by studying its maximal independent sets (MISs). An MIS is a sparse sketch of all $k$-mers with nice theoretical properties,

Jinwei Rao, C. Y. Wang, Bimu Yao, Z. J. Chen

We experimentally realize a meter-scale strong coupling effect between magnons and photons at room temperature, with a coherent coupling of 20 m and a dissipative coupling of 7.6 m. To this end, we integrate a saturable gain into a microwave cavity and then couple this active cavity to a magnon mode via a long coaxial cable. The gain compensates for the cavi

Klaus Altmann, Andreas Hochenegger, Frederik Witt

For a vector bundle $\mathcal E \to \mathbb P^\ell$ we investigate exceptional sequences of line bundles on the total space of the projectivisation $X = \mathbb P(\mathcal E)$. In particular, we consider the case of the cotangent bundle of $\mathbb P^\ell$. If $\ell = 2$, we completely classify the (strong) exceptional sequences and show that any maximal exc

Phani Krishna Uppala, Abhishek Bamotra, Raj Kolamuri

This research paper focuses on the problem of dynamic objects and their impact on effective motion planning and localization. The paper proposes a two-step process to address this challenge, which involves finding the dynamic objects in the scene using a Flow-based method and then using a deep Video inpainting algorithm to remove them. The study aims to test

Jungwook Shin, Jaeill Kim, Kyungeun Lee, Hyunghun Cho

In autonomous driving, data augmentation is commonly used for improving 3D object detection. The most basic methods include insertion of copied objects and rotation and scaling of the entire training frame. Numerous variants have been developed as well. The existing methods, however, are considerably limited when compared to the variety of the real world pos

Mayengbam Kishan Singh, S. Robertson Singh, N. Nimai Singh

Motivated by the significance of modular symmetry in generating neutrino masses and flavor mixings, we apply the modular $A_4$ symmetry in a 3+1 scheme of active-sterile neutrino mixings. Neutrino oscillation observables in the 3$\sigma$ range are successfully reproduced through the vacuum expectation value of the modulus $\tau$. We also study phenomenologie

H. S. Ramadhan, M. F. Ishlah, F. P. Pratama, I. Alfredo

We study nonsingular black holes viewed from the point of view of Ayon-Beato-Garcia (ABG) nonlinear electrodynamics (NLED) and present a complete study of their corresponding strong gravitational lensing. The NLED modifies the the photon's geodesic, and our calculations show that such effect increases the corresponding photon sphere radius and image separati

Jianfei Li, Chen Zhou, Jingfeng Yyao, Chengxun Yuan

Plasma photonic crystals designed in this paper are composed of gas discharge tubes to control the flow of electromagnetic waves. The band structures calculated by the finite element method are consistent with the experimental results in that two distinct attenuation peaks appear in the ranges of 1 GHz to 2.5 GHz and 5 GHz to 6 GHz. Electromagnetic parameter

Yuanming Shi, Yong Zhou, Dingzhu Wen, Youlong Wu

Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is envisaged to go beyond data-centric services to provide intelligent and immersive experiences. To efficiently support intelligent tasks with customized service requirements, it becomes critical to develop novel information compression and transmission technologi

Philippe Jaming, Karim Kellay, Chadi Saba

In this paper, we give a direct quantitative estimate of $L^1$norms of non-harmonic trigonometric polynomials over large enough intervals. This extends the result by Konyagin and Mc Gehee, Pigno, Smith to the settingof trigonometric polynomials with non-integer frequencies.The result is a quantitative extension of a result by Nazarov and also covers a result

E Chénier, E Jamelot, C Le Potier, A Peitavy

The resolution of the incompressible Navier-Stokes equations is tricky, and it is well known that one of the major issue is to compute a divergence free velocity. The non-conforming Crouzeix-Raviart finite element are convenient since they induce local mass conservation. Moreover they are such that the stability constant of the Fortin operator is equal to 1.

Xiaoyu Yang, Qiujia Li, Chao Zhang, Philip C. Woodland

Although large foundation models pre-trained by self-supervised learning have achieved state-of-the-art performance in many tasks including automatic speech recognition (ASR), knowledge distillation (KD) is often required in practice to transfer the knowledge learned by large teacher models into much smaller student models with affordable computation and mem

Zhifeng Wang, Jialong Yao, Chunyan Zeng, Wanxuan Wu

Deep learning-based computer vision technology has grown stronger in recent years, and cross-fertilization using computer vision technology has been a popular direction in recent years. The use of computer vision technology to identify students' learning behavior in the classroom can reduce the workload of traditional teachers in supervising students in the

D. Hunter, C. Perrella, A. McWilliam, J. P. McGilligan

Magnetic field imaging is a valuable resource for signal source localization and characterization. This work reports an optically pumped magnetometer (OPM) based on the free-induction-decay (FID) protocol, that implements microfabricated cesium (Cs) vapor cell technology to visualize the magnetic field distributions resulting from various magnetic sources pl

Atanu Nandy

The spectral landscape and the transport property of a translationally invariant network with side-coupled quantum dots are demonstrated within the tight-binding framework. For periodic environment band structure is demonstrated analytically in details. Moreover, if the side-coupling here follows a typical quasiperiodic Aubry-Andre-Harper type of modulation

Lei Ma, Rong xin Li, Fanhai Zeng, Ling Guo

Fractional partial differential equations (FPDEs) can effectively represent anomalous transport and nonlocal interactions. However, inherent uncertainties arise naturally in real applications due to random forcing or unknown material properties. Mathematical models considering nonlocal interactions with uncertainty quantification can be formulated as stochas

Fan Cui, Liyong Guo, Quandong Wang, Peng Gao

In this paper, we investigate representation learning for low-resource keyword spotting (KWS). The main challenges of KWS are limited labeled data and limited available device resources. To address those challenges, we explore representation learning for KWS by self-supervised contrastive learning and self-training with pretrained model. First, local-global

S. M. Rafi-Ul-Islam, Zhuo Bin Siu, Haydar Sahin, Mansoor B. A. Jalil

We propose a 3D topolectrical (TE) network that can be tuned to realize various higher-order topological gapless and chiral phases. We first study a higher-order Dirac semimetal phase that exhibits a hinge-like Fermi arc linking the Dirac points. This circuit can be extended to host highly tunable first- and second-order Weyl semimetal phases by introducing

David Haritone Shikumo, Oluoch Oluoch, Joshua Matanda Wepukhulu

A significant number of the non-financial firms listed at the Nairobi Securities Exchange have been experiencing declining financial performance and financial growth, which deter investors from investing in such firms. Hence, the study aimed at establishing the effect of financial structure on the financial growth of non-financial firms listed at the Nairobi

Jeongwhan Choi, Noseong Park

Traffic forecasting is one of the most popular spatio-temporal tasks in the field of machine learning. A prevalent approach in the field is to combine graph convolutional networks and recurrent neural networks for the spatio-temporal processing. There has been fierce competition and many novel methods have been proposed. In this paper, we present the method

Yang Xu, Loni Philip Tabb

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization, has been linked to adverse health outcomes, including morbidity and mortality; however, statistical methods for measuring the association between racialized economic segregation and health outcomes are not well-developed and are usually stu

A. Banerjee, Gangadhar Das, V. Rajaji, S. Majumdar

We report here a comprehensive study on structural, magnetic, caloric and electronic properties of the monoclinic phase of double perovskite compound Tm2CoMnO6 (TCMO) in its polycrysttaline format. Magnetic measurements confirm the presence of thermal hysteresis in magnetization indicates towards a first order magnetic transition at its critical point (Tc).

Rene Laub, Klaus M. Miller, Bernd Skiera

Regulators and browsers increasingly restrict user tracking to protect users' privacy online. In two large-scale empirical studies, we study the economic implications for publishers relying on selling advertising space to finance their content. In our first study, we draw on 42 million ad impressions from 111 publishers covering EU desktop browsing traffic i

Jonathan Taylor

We define the local multiplier module of a Hilbert module in analogy to the local multiplier algebra for $C^*$-algebras. We use properties of the local multiplier module to lift non-closed actions on $C^*$-algebras by Hilbert bimodules to closed actions on local multiplier algebras, and descend known results on such closed actions down to their unclosed coun

Charuka Herath, Yogachandran Rahulamathavan, Xiaolan Liu

Federated learning has gained popularity as a solution to data availability and privacy challenges in machine learning. However, the aggregation process of local model updates to obtain a global model in federated learning is susceptible to malicious attacks, such as backdoor poisoning, label-flipping, and membership inference. Malicious users aim to sabotag

Lilang Lin, Jiahang Zhang, Jiaying Liu

The self-supervised pretraining paradigm has achieved great success in skeleton-based action recognition. However, these methods treat the motion and static parts equally, and lack an adaptive design for different parts, which has a negative impact on the accuracy of action recognition. To realize the adaptive action modeling of both parts, we propose an Act