May 2023 arXiv papers — page 161

Chengpeng Wang, Peisen Yao, Wensheng Tang, Gang Fan

This paper presents Squid, a new conjunctive query synthesis algorithm for searching code with target patterns. Given positive and negative examples along with a natural language description, Squid analyzes the relations derived from the examples by a Datalog-based program analyzer and synthesizes a conjunctive query expressing the search intent. The synthes

Matthew Molineaux, Dustin Dannenhauer, Eric Kildebeck

To be robust to surprising developments, an intelligent agent must be able to respond to many different types of unexpected change in the world. To date, there are no general frameworks for defining and characterizing the types of environment changes that are possible. We introduce a formal and theoretical framework for defining and categorizing environment

Xingzhen Fan, Andrey V. Tyukhtin

We study an electromagnetic radiation of a small bunch having a variable charge value and crossing a flat interface between two media. Both media are homogeneous, stationary, and isotropic. They may have frequency dispersion but no spatial dispersion. Cherenkov radiation can be generated in the second medium only. It is assumed that the bunch charge value de

Andreas Nicolaides, Constantinos Psomas, Ghassan M. Kraidy, Sheng Yang

In this paper, we investigate the performance of multiple-input multiple-output (MIMO) fading channels assisted by a reconfigurable intelligent surface (RIS), through the employment of partition-based RIS schemes. The proposed schemes are implemented without requiring any channel state information knowledge at the transmitter side; this characteristic makes

David Harel, Assaf Marron

In his seminal paper ``Computing Machinery and Intelligence'', Alan Turing introduced the ``imitation game'' as part of exploring the concept of machine intelligence. The Turing Test has since been the subject of much analysis, debate, refinement and extension. Here we sidestep the question of whether a particular machine can be labeled intelligent, or can b

Saul Shanabrook

E-graphs have emerged as a versatile data structure with applications in synthesis, optimization, and verification through techniques such as equality saturation. This paper introduces Python bindings for the experimental egglog library (previously called egg-smol), which aims to bring the benefits of e-graphs to the Python ecosystem. The bindings offer a hi

Jiasheng Qian, Zhiguang Liao, Rong Yu

Magnetic properties of Hubbard model have been studied extensively. A theoretical description of these states, however, is not straight forward within conventional mean-field approach due to the electron correlation effects. Here we provide a slave spin theory of the magnetic states in the single band Hubbard model. By introducing an additional decomposition

Jinfeng Wen, Zhenpeng Chen, Federica Sarro, Shangguang Wang

Serverless computing is an emerging cloud computing paradigm for developing applications at the function level, known as serverless functions. Due to the highly dynamic execution environment, multiple identical runs of the same serverless function can yield different performance, specifically in terms of end-to-end response latency. However, surprisingly, ou

John Herbert Marr

Galaxy number counts in the $K$-, $H$-, $I$-, $R$-, $B$- and $U$-bands from the Durham Extragalactic Astronomy and Cosmology catalogue could be well-fitted over their whole range using luminosity function (LF) parameters derived from the SDSS at the bright region and required only modest luminosity evolution with the steepening of the LF slope ($\alpha$), ex

Martin Šípka, Michal Pavelka, Oğul Esen, Miroslav Grmela

In this paper, we present neural networks learning mechanical systems that are both symplectic (for instance particle mechanics) and non-symplectic (for instance rotating rigid body). Mechanical systems have Hamiltonian evolution, which consists of two building blocks: a Poisson bracket and an energy functional. We feed a set of snapshots of a Hamiltonian sy

Nathalie Ramos, Christoph Mittermeier, Josef Kiendl

A good understanding of the heat transfer in fused filament fabrication is crucial for an accurate stress prediction and subsequently for repetitive, high quality printing. This work focuses on two challenges that have been presented when it comes to the accuracy and efficiency in simulating the heat transfer in the fused filament fabrication process. With t

Takaaki Fujita

Tangle is a concept in graph theory that has a dual relationship with branch-width which is well-known graph width parameter. Ultrafilter, a fundamental notion in mathematics, is similarly known to have a dual relationship with branch-width when extended to a connectivity system (X, f). We will reconsider these concepts using separation and partition.

Mateusz Litka

In this paper we consider a game played on the edge set of the infinite clique $K_\mathbb{N}$ by two players, Builder and Painter. In each round of the game, Builder chooses an edge and Painter colors it red or blue. Builder wins when Painter creates a red copy of $G$ or a blue copy of $H$, for some fixed graphs $G$ and $H$. Builder wants to win in as few ro

Lei Kang, Lichao Zhang, Dazhi Jiang

Speech Emotion Recognition (SER) is to recognize human emotions in a natural verbal interaction scenario with machines, which is considered as a challenging problem due to the ambiguous human emotions. Despite the recent progress in SER, state-of-the-art models struggle to achieve a satisfactory performance. We propose a self-attention based method with comb

Bence Borda, Marc Munsch, Igor Shparlinski

We obtain new bounds, pointwisely and on average, for Dedekind sums $\mathsf{s}(\lambda,p)$ modulo a prime $p$ with $\lambda$ of small multiplicative order $d$ modulo $p$. Assuming the infinitude of Mersenne primes, the range of our results is optimal. Moreover, we relate high moments of $L(1,\chi)$ over subgroups of characters to some correlations of Dedeki

Yongcheng Ding, Yiming Pan, Xi Chen

Superoscillation is a counterintuitive phenomenon for its mathematical feature of ``faster-than-Fourier", which has allowed novel optical imaging beyond the diffraction limit. In this article, we introduce a superoscillating quantum control protocol realized by sequential selections within the framework of weak measurement, which steers the apparatus (target

Lei Yuan, Lihe Li, Ziqian Zhang, Fuxiang Zhang

Cooperative Multi-agent Reinforcement Learning (MARL) has attracted significant attention and played the potential for many real-world applications. Previous arts mainly focus on facilitating the coordination ability from different aspects (e.g., non-stationarity, credit assignment) in single-task or multi-task scenarios, ignoring the stream of tasks that ap

Taekyun Kim, Dae San Kim, Hye Kyung Kim

It is remarkable that, in recent years, intensive studies have been done for degenerate versions of many special polynomials and numbers and have yielded many interesting results. The aim of this paper is to study the generalized degenerate (r, s)-Stirling numbers of the second and their natural extensions to polynomials, namely the generalized degenerate (r

Yuxiang Zhao, Zhuomin Chai, Yibo Lin, Runsheng Wang

Accurate early congestion prediction can prevent unpleasant surprises at the routing stage, playing a crucial character in assisting designers to iterate faster in VLSI design cycles. In this paper, we introduce a novel strategy to fully incorporate topological and geometrical features of circuits by making several key designs in our network architecture. To

Eduardo Fernandes, Marcos Kalinowski

Several refactorings performed while evolving software features aim to improve internal quality attributes like cohesion and complexity. Indeed, internal attributes can become critical if their measurements assume anomalous values. Yet, current knowledge is scarce on how developers perceive the relevance of critical internal attributes while evolving feature

In-Jee Jeong, Junha Kim, Yao Yao

We investigate the well-posedness of $\alpha$-SQG equations in the half-plane, where $\alpha=0$ and $\alpha=1$ correspond to the 2D Euler and SQG equations respectively. For $0<\alpha \le 1/2$, we prove local well-posedness in certain weighted anisotropic H\"older spaces. We also show that such a well-posedness result is sharp: for any $0<\alpha \le 1$, we p

Pawan Kumar Jha, Sanyam Nitin Totade, Prabeer Barpanda, Gopalakrishnan Sai Gautam

Given increasing energy storage demands and limited natural resources of Li, K-ion batteries (KIBs) could be promising next-generation systems having natural abundance, similar chemistry and energy density. Here, we have investigated the P3-type K$_{0.5}$TMO$_2$ (where TM = Ti, V, Cr, Mn, Co, or Ni) systems using density functional theory calculations, as po

Jinyu Miao, Kun Jiang, Yunlong Wang, Tuopu Wen

High-precision vehicle localization with commercial setups is a crucial technique for high-level autonomous driving tasks. Localization with a monocular camera in LiDAR map is a newly emerged approach that achieves promising balance between cost and accuracy, but estimating pose by finding correspondences between such cross-modal sensor data is challenging,

Yijun Wang, Changzhi Sun, Yuanbin Wu, Lei Li

Entity relation extraction consists of two sub-tasks: entity recognition and relation extraction. Existing methods either tackle these two tasks separately or unify them with word-by-word interactions. In this paper, we propose HIORE, a new method for unified entity relation extraction. The key insight is to leverage the high-order interactions, i.e., the co

Lei Yuan, Tao Jiang, Lihe Li, Feng Chen

Many multi-agent scenarios require message sharing among agents to promote coordination, hastening the robustness of multi-agent communication when policies are deployed in a message perturbation environment. Major relevant works tackle this issue under specific assumptions, like a limited number of message channels would sustain perturbations, limiting the

Jan Olszewski

Neural Radiance Fields has become a prominent method of scene generation via view synthesis. A critical requirement for the original algorithm to learn meaningful scene representation is camera pose information for each image in a data set. Current approaches try to circumnavigate this assumption with moderate success, by learning approximate camera position

Xabier Garcia-Casas, Francisco J. Aparicio, Jorge Budagosky, Ali Ghaffarinejad

Nanogenerators and self-powered nanosensors have shown the potential to power low-consumption electronics and human-machine interfaces, but their practical implementation requires reliable, environmentally friendly and scalable, processes for manufacturing and processing. This article presents a plasma synthesis approach for the fabrication of piezoelectric

Zhen Huang, Han Li, Shitong Shao, Heqin Zhu

The pelvis, the lower part of the trunk, supports and balances the trunk. Landmark detection from a pelvic X-ray (PXR) facilitates downstream analysis and computer-assisted diagnosis and treatment of pelvic diseases. Although PXRs have the advantages of low radiation and reduced cost compared to computed tomography (CT) images, their 2D pelvis-tissue superpo

Yuanbin Chen, Ying Wang, Xufeng Guo, Zhu Han

In this paper, we investigate the employment of reconfigurable intelligent surfaces (RISs) into vehicle platoons, functioning in tandem with a base station (BS) in support of the high-precision location tracking. In particular, the use of a RIS imposes additional structured sparsity that, when paired with the initial sparse line-of-sight (LoS) channels of th

Zhouzhe Wang, Jiayang Yu, Xu Zhang

This paper is the second part of our series of works to establish $L^2$ estimates and existence theorems for the $\overline{\partial}$ operators in infinite dimensions. In this part, we consider the most difficult case, i.e., the underlying space is a general pseudo-convex domain. In order to solve this longstanding open problem, we introduce several new con

M. Donello, G. Palkar, M. H. Naderi, D. C. Del Rey Fernández

Time-dependent basis reduced order models (TDB ROMs) have successfully been used for approximating the solution to nonlinear stochastic partial differential equations (PDEs). For many practical problems of interest, discretizing these PDEs results in massive matrix differential equations (MDEs) that are too expensive to solve using conventional methods. Whil

Andreas Anastasiou, Tobias Kley

The autocovariance and cross-covariance functions naturally appear in many time series procedures (e.g., autoregression or prediction). Under assumptions, empirical versions of the autocovariance and cross-covariance are asymptotically normal with covariance structure depending on the second and fourth order spectra. Under non-restrictive assumptions, we der

J. -C. Sibel, V. Corlay, A. Bechihi

In this paper, we focus on the selection of a pilot pattern to track the phase noise in high frequency bands in a DFT-s-OFDM chain. By considering the Wiener filter at the receiver side to perform the tracking, we use the inner cost function of the said filter as the cost function for the pilot selection. To obtain this cost function, the phase noise autocor

Xiaojin Zhang, Kai Chen, Qiang Yang

Federated learning (FL) enables participating parties to collaboratively build a global model with boosted utility without disclosing private data information. Appropriate protection mechanisms have to be adopted to fulfill the requirements in preserving \textit{privacy} and maintaining high model \textit{utility}. The nature of the widely-adopted protection

Enrico Zardini, Enrico Blanzieri, Davide Pastorello

The k-nearest neighbors (k-NN) is a basic machine learning (ML) algorithm, and several quantum versions of it, employing different distance metrics, have been presented in the last few years. Although the Euclidean distance is one of the most widely used distance metrics in ML, it has not received much consideration in the development of these quantum varian

Elia Bonetto, Chenghao Xu, Aamir Ahmad

Simulation engines are widely adopted in robotics. However, they lack either full simulation control, ROS integration, realistic physics, or photorealism. Recently, synthetic data generation and realistic rendering has advanced tasks like target tracking and human pose estimation. However, when focusing on vision applications, there is usually a lack of info

Stefano Riolo

By gluing some copies of a polytope of Kerckhoff and Storm's, we build the smallest known orientable hyperbolic 4-manifold that is not commensurable with the ideal 24-cell or the ideal rectified simplex. It is cusped and arithemtic, and has twice the minimal volume.

Rohit Chawla, Aasifa Rounak, Chandan Bose, Vikram Pakrashi

The stability and bifurcation behaviour of a wake-induced vibro-impacting oscillator is studied. The effects of a discontinuity on the stability of the structure while it is undergoing phase-locked motions due to the surrounding fluid-structure interactions (FSI) are examined. The primary structure and the near wake dynamics are modelled as a harmonic oscill

Fatemeh Asadi, Zohreh Fathi, Sajjad Lakzian

We discuss topological rigidity of vector bundles with asymptotically conical (AC) total spaces of rank greater than 1 with a sufficiently connected link; our focus will mainly be on ALE (asymptotically locally Euclidean) bundles. Within the smooth category, we topologically classify all ALE tangent bundles by showing only 2-sphere, projective plane and open

Elia Bonetto, Chenghao Xu, Aamir Ahmad

Recently, synthetic data generation and realistic rendering has advanced tasks like target tracking and human pose estimation. Simulations for most robotics applications are obtained in (semi)static environments, with specific sensors and low visual fidelity. To solve this, we present a fully customizable framework for generating realistic animated dynamic e

Juni Schindler, Mauricio Barahona

In data clustering, it is often desirable to find not just a single partition into clusters but a sequence of partitions that describes the data at different scales (or levels of coarseness). A natural problem then is to analyse and compare the (not necessarily hierarchical) sequences of partitions that underpin such multiscale descriptions. Here, we use too

S. Hameed, Z. Wang, D. M. Gautreau, J. Joe

Neutron scattering is used to study spin waves in the three-dimensional Heisenberg ferromagnet YTiO$_3$, with spin-spin exchange disorder introduced $via$ La-substitution at the Y site. No significant changes are observed in the spin-wave dispersion up to a La concentration of 20%. However, a strong broadening of the spectrum is found, indicative of shortene

Zixuan Chen, Lei Shi, Xuandong Liu, Xin Ai

Distributed Machine Learning (DML) systems are utilized to enhance the speed of model training in data centers (DCs) and edge nodes. The Parameter Server (PS) communication architecture is commonly employed, but it faces severe long-tail latency caused by many-to-one "incast" traffic patterns, negatively impacting training throughput. To address this challen

Mokhtar Kirane, Ahmad Fino, Sebti Kerbal, Aymen Laadhari

We consider a semilinear wave equation involving a time-dependent structural damping term of the form $\displaystyle\frac{1}{{(1+t)}^{\beta}}(-\Delta)^{\sigma/2} u_t$. Our results show the influence of the parameters $\beta,\sigma$ on the nonexistence of global weak solutions under assumptions on the given system data.

Christian Bick, Tobias Böhle, Christian Kuehn

Coupled oscillator networks provide mathematical models for interacting periodic processes. If the coupling is weak, phase reduction -- the reduction of the dynamics onto an invariant torus -- captures the emergence of collective dynamical phenomena, such as synchronization. While a first-order approximation of the dynamics on the torus may be appropriate in

Jiacheng Lin, Jiajun Chen, Kailun Yang, Alina Roitberg

Interactive Image Segmentation (IIS) has emerged as a promising technique for decreasing annotation time. Substantial progress has been made in pre- and post-processing for IIS, but the critical issue of interaction ambiguity, notably hindering segmentation quality, has been under-researched. To address this, we introduce AdaptiveClick -- a click-aware trans

Ge Zhang, Wangzhe Du

In recent years, there is an increasing interests in reconstruction based generative models for image One-Class Novelty Detection, most of which only focus on image-level information. While in this paper, we further exploit the latent space of Variational Auto-encoder (VAE), a typical reconstruction based model, and we innovatively divide it into three regio

K. Deja, V. Martinez-Fernandez, B. Pire, P. Sznajder

Double deeply virtual Compton scattering (DDVCS) is the process where an electron scatters off a nucleon and produces a lepton pair. The main advantage of this process in contrast with deeply virtual and timelike Compton scatterings (DVCS and TCS) is the possibility of directly measuring GPDs for $x\neq\pm\xi$ at leading order in $\alpha_s$ (LO). We present

Jonas Flechsig

The main result of this article is that pure orbifold braid groups fit into an exact sequence $1\rightarrow K\rightarrow\pi_1^{orb}(\Sigma_\Gamma(n-1+L))\xrightarrow{\iota_{\textrm{PZ}_n}}\textrm{PZ}_n(\Sigma_\Gamma(L))\xrightarrow{\pi_{\textrm{PZ}_n}}\textrm{PZ}_{n-1}(\Sigma_\Gamma(L))\rightarrow1.$ In particular, we observe that the kernel $K$ of $\iota_{\

Jonas Flechsig

We define orbifold mapping class groups (with marked points) and study them using their action on certain orbifold analogs of arcs and simple closed curves. Moreover, we establish a Birman exact sequence for suitable subgroups of orbifold mapping class groups. The short exact sequence allows us to deduce finite presentations of these groups. This is the basi

Mustafa Ozger, Istvan Godor, Anders Nordlow, Thomas Heyn

In this paper, we present the vision of our project 6G for Connected Sky (6G-SKY) to integrate terrestrial networks (TNs) and non-terrestrial networks (NTNs) and outline the current research activities in 6G research projects in comparison with our project. From the perspectives of industry and academia, we identify key use case segments connecting both aeri

S. Maharana, S. Kiehlmann, D. Blinov, V. Pelgrims

Next-generation wide-field optical polarimeters like the Wide-Area Linear Optical Polarimeters (WALOPs) have a field of view (FoV) of tens of arcminutes. For efficient and accurate calibration of these instruments, wide-field polarimetric flat sources will be essential. Currently, no established wide-field polarimetric standard or flat sources exist. This pa

Wencong Wu, Shijie Liu, Yi Zhou, Yungang Zhang

In image denoising, deep convolutional neural networks (CNNs) can obtain favorable performance on removing spatially invariant noise. However, many of these networks cannot perform well on removing the real noise (i.e. spatially variant noise) generated during image acquisition or transmission, which severely sets back their application in practical image de

Ze-Xin Yin, Peng-Yi Jiao, Jiaxiong Qiu, Ming-Ming Cheng

Existing Neural Radiance Fields (NeRF) methods suffer from the existence of reflective objects, often resulting in blurry or distorted rendering. Instead of calculating a single radiance field, we propose a multi-space neural radiance field (MS-NeRF) that represents the scene using a group of feature fields in parallel sub-spaces, which leads to a better und

Gen Li, Ganghua Wang, Jie Ding

LASSO regularization is a popular regression tool to enhance the prediction accuracy of statistical models by performing variable selection through the $\ell_1$ penalty, initially formulated for the linear model and its variants. In this paper, the territory of LASSO is extended to two-layer ReLU neural networks, a fashionable and powerful nonlinear regressi

Chenmin Sha, Shidong Zhou

In this paper we study multi-task oriented communication system via studying analog encoding method for multiple estimation tasks. The basic idea is to utilize the correlation among interested information required by different tasks and the feature of broadcast channel. For linear estimation tasks, we provide a low complexity design for multi-user multi-task

Didier Gohourou, Kazuhiro Kuwabara

Vector representations obtained from word embedding are the source of many groundbreaking advances in natural language processing. They yield word representations that are capable of capturing semantics and analogies of words within a text corpus. This study is an investigation in an attempt to elicit a vector representation of relationships between pairs of

W. Yang, Y. Gong, K. M. Menten, J. S. Urquhart

We analyzed the 3-mm wavelength spectral line survey of 408 ATLASGAL clumps observed with the IRAM 30m-telescope, focusing on the class I methanol masers with frequencies near 84, 95 and 104.3 GHz. We detect narrow, maser-like features towards 54, 100 and 4 sources in the maser lines near 84, 95 and 104.3 GHz, respectively. Among them, fifty 84 GHz masers, t

Fridolin Melong

In this paper, we construct the super Virasoro algebra with an arbitrary conformal dimension $\Delta$ from the generalized $\mathcal{R}(p,q)$-deformed quantum algebra and investigate the $\mathcal{R}(p,q)$-deformed super Virasoro algebra with the particular conformal dimension $\Delta=1$. Furthermore, we perform the R(p,q)-conformal Virasoro n-algebra, the $

D. A. D. Chaves, M. I. Valerio-Cuadros, L. Jiang, E. A. Abbey

Ubiquitous in most superconducting materials and a common result of nanofabrication processes, weak-links are known for their limiting effects on the transport of electric currents. Still, they are at the root of key features of superconducting technology. By performing quantitative magneto-optical imaging experiments and thermomagnetic model simulations, we

Marston Conder, Luke Morgan, Primož Potočnik

An LR-structure is a tetravalent vertex-transitive graph together with a special type of a decomposition of its edge-set into cycles. LR-structures were introduced in a paper by P. Poto\v{c}nik and S. Wilson, titled `Linking rings structures and tetravalent semisymmetric graphs', in Ars Math. Contemp. 7 (2014), as a tool to study tetravalent semisymmetric gr

Ons Dabbabi, Mohammad Javad Salariseddigh, Christian Deppe, Holger Boche

Deterministic K-Identification (DKI) for the binary symmetric channel (BSC) is developed. A full characterization of the DKI capacity for such a channel, with and without the Hamming weight constraint, is established. As a key finding, we find that for deterministic encoding the number of identifiable messages $K$ may grow exponentially with the codeword len

Markus J. Buehler

We report a flexible language-model based deep learning strategy, applied here to solve complex forward and inverse problems in protein modeling, based on an attention neural network that integrates transformer and graph convolutional architectures in a causal multi-headed graph mechanism, to realize a generative pretrained model. The model is applied to pre

Debarshi Basu, Jiong Lin, Yizhou Lu, Qiang Wen

In the context of partial entanglement entropy (PEE), we study the entanglement structure of the island phases realized in several 2-dimensional holographic set-ups. The self-encoding property of the island phase changes the way we evaluate the PEE. With the contributions from islands taken into account, we give a generalized prescription to construct PEE an

Mark Edward M. Gonzales, Elyssia Barrie H. Ong, Charibeth K. Cheng, Ethel Chua Joy Ong

Schools are among the primary avenues for public healthcare interventions. With resource limitations posing challenges to the routine conduct of health and wellness checks in Philippine public schools, the deployment of a chatbot-assisted health monitoring system may provide an alternative method. However, deriving insights from raw conversations is not stra

Hossein Rezaei, Elham Abbasi, Nandana Rajatheva, Matti Latva-aho

Over the past decade, polar codes have received significant traction and have been selected as the coding method for the control channel in fifth-generation (5G) wireless communication systems. However, conventional polar codes are reliant solely on binary (2x2) kernels, which restricts their block length to being only powers of 2. In response, multi-kernel

Akshansh Mishra, Vijaykumar S Jatti

In this study, we introduce application of Neurosymbolic Artificial Intelligence (NSAI) for predicting the impact strength of additive manufactured polylactic acid (PLA) components, representing the first-ever use of NSAI in the domain of additive manufacturing. The NSAI model amalgamates the advantages of neural networks and symbolic AI, offering a more rob

T. G. S. Pillai, J. S. Urquhart, S. Leurini, Q. Zhang

The evolutionary sequence for high-mass star formation starts with massive starless clumps that go on to form protostellar, young stellar objects and then compact HII regions. While there are many examples of the three later stages, the very early stages have proved to be elusive. We follow-up a sample of 110 mid-infrared dark clumps selected from the ATLASG

Brahim Dridi, Rached Jaidane, Rima Chetouane

In this article, we study the following non local problem $$g\big(\int_{B}w(x) |\Delta u|^{2}\big)\Delta(w(x)\Delta u) =|u|^{q-2}u +\ f(x,u) \quad\mbox{ in }\quad B, \quad u=\frac{\partial u}{\partial n}=0 \quad\mbox{ on } \quad\partial B,$$ where $B$ is the unit ball in $\mathbb{R}^{4}$ and $ w(x)$ is a singular weight of logarithm type. The non-linearity i

Lintao Ye, Zhi-Wei Liu, Ming Chi, Vijay Gupta

We consider the problem of maximizing a monotone nondecreasing set function under multiple constraints, where the constraints are also characterized by monotone nondecreasing set functions. We propose two greedy algorithms to solve the problem with provable approximation guarantees. The first algorithm exploits the structure of a special class of the general

Zhibao Zheng, Udo Nackenhorst

This paper presents stochastic virtual element methods for propagating uncertainty in linear elastic stochastic problems. We first derive stochastic virtual element equations for 2D and 3D linear elastic problems that may involve uncertainties in material properties, external forces, etc. A stochastic virtual element space that couples the deterministic virt

Santanu Mandal, Ranjit Mehatari, Zoran Stanic

In this paper we consider particular graphs defined by $\overline{\overline{\overline{K_{\alpha_1}}\cup K_{\alpha_2}}\cup\cdots \cup K_{\alpha_k}}$, where $k$ is even, $K_\alpha$ is a complete graph on $\alpha$ vertices, $\cup$ stands for the disjoint union and an overline denotes the complementary graph. These graphs do not contain the $4$-vertex path as an

Gianni Pagnini, Claudio Runfola

It is known that at least ten equivalent definitions of the fractional Laplacian exist in an unbounded domain. Here we derive a further equivalent definition that is based on the Mellin transform and it can be used when the fractional Laplacian is applied to radial functions. The main finding is tested in the case of the space-fractional diffusion equation.

Meng Han, Wei Li, Su-Yan Pei, Ting-Ting Liu

Taking $D_{s0}^{*}(2317)^{+ }$ as a conventional $c\bar s$ meson, we calculate its dominant strong and electromagnetic decays in the framework of the Bethe-Salpeter method. Our results are $\Gamma(D_{s0}^{*+}\to D_s^+\pi^0) = 7.83^{+1.97}_{-1.55}$ keV and $\Gamma(D_{s0}^{*+}\to D_s^{*+}\gamma) = 2.55^{+0.37}_{-0.45}$ keV. The contributions of the different p

Kento Tomita, Koki Ho

Autonomous hazard detection and avoidance is a key technology for future landing missions in unknown surface conditions. Current state-of-the-art stochastic algorithms assume simple Gaussian measurement noise on dense, high-fidelity digital elevation maps, limiting the algorithm's applicability. This paper introduces a new stochastic hazard detection algorit

Allister Loder, Fabienne Cantner, Lennart Adenaw, Markus B. Siewert

In a response to the 2022 cost-of-living crisis in Europe, the German government implemented a three-month fuel excise tax cut and a public transport travel pass for 9 Euro per month valid on all local and regional services. Following this period, a public debate immediately emerged on a successor to the so-called "9-Euro-Ticket", leading to the political de

Ning Ding, Kazuya Takeda, Wenhui Jin, Yingjiu Bei

The application of visual tracking to the performance analysis of sports players in dynamic competitions is vital for effective coaching. In doubles matches, coordinated positioning is crucial for maintaining control of the court and minimizing opponents' scoring opportunities. The analysis of such teamwork plays a vital role in understanding the dynamics of

Dmitry Dolgopyat, Changguang Dong, Adam Kanigowski, Peter Nandori

We consider generalized $(T, T^{-1})$ transformations such that the base map satisfies a multiple mixing local limit theorem and anticoncentration large deviation bounds and in the fiber we have $\mathbb{R}^d$ actions with $d=1$ or $2$ which are exponentially mixing of all orders. If the skewing cocycle has zero drift, we show that the ergodic sums satisfy t

D. V. Zinenko, D. A. Glazov, V. P. Kosheleva, A. V. Volotka

We present the systematic QED treatment of the electron correlation effects on the $g$ factor of lithiumlike ions for the wide range of nuclear charge number $Z= 14$ -- $82$. The one- and two-photon exchange corrections are evaluated rigorously within the QED formalism. The electron-correlation contributions of the third and higher orders are accounted for w

Eilon Bilinsky, Yair Hayut

In this paper we study the spectrum of heights of transitive models of theories extending $V = L[A]$, under various definitions. In particular, we investigate the consistency strength of making those spectra as simple as possible.

G. R. Boroun

We show that the saturation exponent is more effective than the hard pomeron exponent in the nonlinear terms for the GLR-MQ evolution equations. For the gluon distribution the nonlinear terms are found to play an increasingly important role than the singlet distribution. The nonlinear corrections for the singlet and gluon distributions are important in a lim

Hazem Ibrahim, Fengyuan Liu, Rohail Asim, Balaraju Battu

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work -- a possibility that has sparked discussions on the integrity of s

Zhitao Liu, Yi Li, Ning Xie, YouTeng Fan

Virtual reality (VR) produces a highly realistic simulated environment with controllable environment variables. This paper proposes a Dynamic Scene Adjustment (DSA) mechanism based on the user interaction status and performance, which aims to adjust the VR experiment variables to improve the user's game engagement. We combined the DSA mechanism with a musica

Zhanpeng Zeng, Cole Hawkins, Mingyi Hong, Aston Zhang

Transformers are central in modern natural language processing and computer vision applications. Despite recent works devoted to reducing the quadratic cost of such models (as a function of the sequence length), dealing with ultra long sequences (e.g., with more than 16K tokens) remains challenging. Applications such as answering questions based on a book or

Harini Desiraju

This note details the relationship between the isomonodromic tau-function and conformal blocks, on a torus with one simple pole. It is based on the author's talk at ICMP 2021.

Zhitao Liu, Zengyu Liu, Jiwei Wei, Guan Wang

3D cross-modal retrieval is gaining attention in the multimedia community. Central to this topic is learning a joint embedding space to represent data from different modalities, such as images, 3D point clouds, and polygon meshes, to extract modality-invariant and discriminative features. Hence, the performance of cross-modal retrieval methods heavily depend

Bowen Wang

There are confusions about angular momentum propagation in scattering or decay processes involving the transition between particle systems that appear to transform differently under Lorentz transformations. This paper provides an analysis of the transformation properties of the states and interactions for a few typical processes within the standard model of

Charles Courchaine, Ricky J. Sethi

This foundational research provides additional support for using the Fuzzy ARTMAP neural network as a classification algorithm in the TAR domain. While research opportunities exist to improve recall performance and explanation, the robust recall results from this study and the proof-of-concept demonstration of If-Then rules for tf-idf vectorization strongly

Mingrui Ma, Tao Wang, Lei Song, Weijie Wang

The Swin transformer has recently attracted attention in medical image analysis due to its computational efficiency and long-range modeling capability. Owing to these properties, the Swin Transformer is suitable for establishing more distant relationships between corresponding voxels in different positions in complex abdominal image registration tasks. Howev

Guoqiang Wu, Jia-Yong Wu

In this paper, we give various curvature pinching conditions such that shrinkers are compact. On one hand, we prove that shrinkers with positive Ricci curvature are compact when they have bounded curvature and certain curvature pinching conditions. On the other hand, we prove that shrinkers with certain asymptotically nonnegative sectional curvature are comp

Alexey Barsukov, Florent R. Madelaine

Feder and Vardi showed that the class Monotone Monadic SNP without inequality (MMSNP) has a P vs NP-complete dichotomy if and only if such a dichotomy holds for finite-domain Constraint Satisfaction Problems (CSPs). Moreover, they showed that none of the three classes obtained by removing one of the defining properties of MMSNP (monotonicity, monadicity, no

Artem A. Kotov, Dmitry A. Glazov, Aleksei V. Malyshev, Vladimir M. Shabaev

The rigorous two-center approach based on the dual-kinetically balanced finite-basis-set expansion is applied to one-electron, heteronuclear diatomic Bi-Au, U-Pb, and Cf-U quasimolecules. The obtained $1\sigma$ ground-state energies are compared with previous calculations, when possible. Upon analysis of three different placements of the coordinate system's

George Martvel, Nareed Farhat, Ilan Shimshoni, Anna Zamansky

Animal affective computing is a quickly growing field of research, where only recently first efforts to go beyond animal tracking into recognizing their internal states, such as pain and emotions, have emerged. In most mammals, facial expressions are an important channel for communicating information about these states. However, unlike the human domain, ther

Yichuan Lou

A sender seeks to persuade a receiver by presenting evidence obtained through a sequence of private experiments. The sender has complete flexibility in his choice of experiments, contingent on the private experimentation history. The sender can disclose each experiment outcome credibly, but cannot prove whether he has disclosed everything. By requiring `cont

O. Ogulcan Tuncer

We introduce null surfaces (or nullcone fronts) of pseudo-spherical spacelike framed curves in the three-dimensional anti-de Sitter space. These surfaces are formed by the light rays emitted from points on anti-de Sitter spacelike framed curves. We then classify singularities of the nullcone front of a pseudo-spherical spacelike framed curve and show how the

Davide Batic, Marek Nowakowski, Aya Mohammad Abdelhaq

Scalar, vector and tensor conserved quantities are essential tools in solving different problems in physics and complex, nonlinear differential equations in mathematics. In many guises they enter our understanding of nature: charge, lepton, baryon numbers conservation accompanied with constant energy, linear or angular total momenta and the conservation of e

Guang Yang, Tiancheng Jin, Liang Dou

Code classification is a difficult issue in program understanding and automatic coding. Due to the elusive syntax and complicated semantics in programs, most existing studies use techniques based on abstract syntax tree (AST) and graph neural network (GNN) to create code representations for code classification. These techniques utilize the structure and sema

Giovanni Covi, Tuhin Ghosh, Angkana Rüland, Gunther Uhlmann

We relate the (anisotropic) variable coefficient local and nonlocal Calder\'on problems by means of the Caffarelli-Silvestre extension. In particular, we prove that (partial) Dirichlet-to-Neumann data for the fractional Calder\'on problem in three and higher dimensions determine the (full) Dirichlet-to-Neumann data for the local Calder\'on problem. As a cons

Birger Winkel, David Nakath, Felix Woelk, Kevin Köser

In order to advance underwater computer vision and robotics from lab environments and clear water scenarios to the deep dark ocean or murky coastal waters, representative benchmarks and realistic datasets with ground truth information are required. In particular, determining the camera pose is essential for many underwater robotic or photogrammetric applicat

Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang

Heterophily has been considered as an issue that hurts the performance of Graph Neural Networks (GNNs). To address this issue, some existing work uses a graph-level weighted fusion of the information of multi-hop neighbors to include more nodes with homophily. However, the heterophily might differ among nodes, which requires to consider the local topology. M