April 2024 arXiv papers — page 63

Biao-Peng Li, Wen-Qi Ma, Zhi-Fu Gao

The pulsar magnetic inclination angle is a key parameter for pulsar physics. It influences the observable properties of pulsars, such as the pulse beam width, braking index, polarisation, and emission geometry. In this study, we give a brief overview of the current state of knowledge and research on this parameter and its implications for the internal physic

Giulio Malavolta, Tomoyuki Morimae, Michael Walter, Takashi Yamakawa

In classical cryptography, one-way functions are widely considered to be the minimal computational assumption. However, when taking quantum information into account, the situation is more nuanced. There are currently two major candidates for the minimal assumption: the search quantum generalization of one-way functions are one-way state generators (OWSG), wh

Mutahira Khalid, Raihana Rahman, Asim Abbas, Sushama Kumari

Knowledge graphs (KGs) serve as powerful tools for organizing and representing structured knowledge. While their utility is widely recognized, challenges persist in their automation and completeness. Despite efforts in automation and the utilization of expert-created ontologies, gaps in connectivity remain prevalent within KGs. In response to these challenge

Akhilan Boopathy, Aneesh Muppidi, Peggy Yang, Abhiram Iyer

State estimation is crucial for the performance and safety of numerous robotic applications. Among the suite of estimation techniques, particle filters have been identified as a powerful solution due to their non-parametric nature. Yet, in high-dimensional state spaces, these filters face challenges such as 'particle deprivation' which hinders accurate repre

Maria-Magdalena Wolf, Richard Taupitz, Frank Diermeyer

Since Automated Driving Systems are not expected to operate flawlessly, Automated Vehicles will require human assistance in certain situations. For this reason, teleoperation offers the opportunity for a human to be remotely connected to the vehicle and assist it. The Remote Operator can provide extensive support by directly controlling the vehicle, eliminat

Dominic Maggio, Yun Chang, Nathan Hughes, Matthew Trang

Modern tools for class-agnostic image segmentation (e.g., SegmentAnything) and open-set semantic understanding (e.g., CLIP) provide unprecedented opportunities for robot perception and mapping. While traditional closed-set metric-semantic maps were restricted to tens or hundreds of semantic classes, we can now build maps with a plethora of objects and countl

Di Zheng, Muhammad Fayyaz Kashif, Linda Piscopo, Liam Collard

Creating plasmonic nanoparticles on a tapered optical fiber tip enables a remote SERS sensing probe, ideal for challenging sampling scenarios like biological tissue, specific cells, on-site environmental monitoring, and deep brain structures. However, nanoparticle patterns fabricated from current bottom-up methods are mostly random, making geometry control d

Keke Song, Jiahui Liu, Shunda Chen, Zheyong Fan

One of the most effective methods to enhance the strength of aluminum alloys involves modifying grain boundaries (GBs) through solute segregation. However, the fundamental mechanisms of solute segregation and their impacts on material properties remain elusive. In this study, we implemented highly efficient hybrid Monte Carlo and molecular dynamics (MCMD) al

Abhishek Jha, Yogesh Rawat, Shruti Vyas

Photovoltaic (PV) systems allow us to tap into all abundant solar energy, however they require regular maintenance for high efficiency and to prevent degradation. Traditional manual health check, using Electroluminescence (EL) imaging, is expensive and logistically challenging which makes automated defect detection essential. Current automation approaches re

Jie Shao, Wei Yao, Lei Luo, Linzhou Zeng

Greenspaces are tightly linked to human well-being. Yet, rapid urbanization has exacerbated greenspace exposure inequality and declining human life quality. Roof greening has been recognized as an effective strategy to mitigate these negative impacts. Understanding priorities and benefits is crucial to promoting green roofs. Here, using geospatial big data,

Rui Pimentel de Figueiredo, Stefan Nordborg Eriksen, Ignacio Rodriguez, Simon Bøgh

Corrosion, a naturally occurring process leading to the deterioration of metallic materials, demands diligent detection for quality control and the preservation of metal-based objects, especially within industrial contexts. Traditional techniques for corrosion identification, including ultrasonic testing, radio-graphic testing, and magnetic flux leakage, nec

Md Mainuddin, Zhenhai Duan, Yingfei Dong

IoT devices fundamentally lack built-in security mechanisms to protect themselves from security attacks. Existing works on improving IoT security mostly focus on detecting anomalous behaviors of IoT devices. However, these existing anomaly detection schemes may trigger an overwhelmingly large number of false alerts, rendering them unusable in detecting compr

Chenxi Deng, Zhong-Jie Han, Zhaobin Kuang, Qiong Zhang

In this paper, we analyze an abstract thermoelastic system, where the heat conduction follows the Cattaneo law. Zero becomes a spectrum point of the system operator when the coupling and thermal damping parameters of system satisfy specific conditions. We obtain the decay rates of solutions to the system with or without the inertial term. Furthermore, the de

Bruce Lionnel Lietap Ndi, Djagwa Dehainsala, Joseph Dongho

The aim of this work is focused on the investigation of the algebraic complete integrability of the Toda lattice associated with the twisted affine Lie algebra $a_4^{(2)}$. First, we prove that the generic fiber of the momentum map for this system is an affine part of an abelian surface. Second, we show that the flows of integrable vector fields on this surf

Daniel Hausmann

We propose a method for solving parity games with acyclic (DAG) sub-structures by computing nested fixpoints of a DAG attractor function that lives over the non-DAG parts of the game, thereby restricting the domain of the involved fixpoint operators. Intuitively, this corresponds to accelerating fixpoint computation by inlining cycle-free parts during the so

Yuxi Ren, Xin Xia, Yanzuo Lu, Jiacheng Zhang

Recently, a series of diffusion-aware distillation algorithms have emerged to alleviate the computational overhead associated with the multi-step inference process of Diffusion Models (DMs). Current distillation techniques often dichotomize into two distinct aspects: i) ODE Trajectory Preservation; and ii) ODE Trajectory Reformulation. However, these approac

Zhicheng Liu, Yuan Li, Huazi Zhang, Jun Wang

In this paper, we establish the second-order randomized identification capacity (RID capacity) of the Additive White Gaussian Noise Channel (AWGNC). On the one hand, we obtain a refined version of Hayashi's theorem to prove the achievability part. On the other, we investigate the relationship between identification and channel resolvability, then we propose

Tom Banks, Patrick Draper

Near horizons, quantum fields of low spin exhibit densities of states that behave asymptotically like 1+1 dimensional conformal field theories. In effective field theory, imposing some short-distance cutoff, one can compute thermodynamic quantities associated with the horizon, and the leading cutoff sensitivity of the heat capacity is found to equal to the l

Tsuyoshi Ichimura, Kohei Fujita, Muneo Hori, Maddegedara Lalith

Faster explicit elastic wavefield simulations are required for large and complex three-dimensional media using a structured finite element method. Such wavefield simulations are suitable for GPUs, which have exhibited improved computational performance in recent years, and the use of GPUs is expected to speed up such simulations. However, available computati

Vivek Chaudhary

Graph coloring is a problem with varied applications in industry and science such as scheduling, resource allocation, and circuit design. The purpose of this paper is to establish if a new gradient based iterative solver framework known as heat diffusion can solve the graph coloring problem. We propose a solution to the graph coloring problem using the heat

Jacopo Tagliabue, Ciro Greco

As the Lakehouse architecture becomes more widespread, ensuring the reproducibility of data workloads over data lakes emerges as a crucial concern for data engineers. However, achieving reproducibility remains challenging. The size of data pipelines contributes to slow testing and iterations, while the intertwining of business logic and data management compl

Siddhartha Ganguly, Rihan Aaron D'Silva, Debasish Chatterjee

This article introduces a new transcription, change point localization, and mesh refinement scheme for direct optimization-based solutions and for uniform approximation of optimal control trajectories associated with a class of nonlinear constrained optimal control problems (OCPs). The base transcription algorithm for which we establish the refinement algori

Bingwen Zhu, Fanyi Wang, Tianyi Lu, Peng Liu

Image-to-video (I2V) generation aims to create a video sequence from a single image, which requires high temporal coherence and visual fidelity. However, existing approaches suffer from inconsistency of character appearances and poor preservation of fine details. Moreover, they require a large amount of video data for training, which can be computationally d

Yuxin Wang, Qianyi Wu, Guofeng Zhang, Dan Xu

This paper tackles the intricate challenge of object removal to update the radiance field using the 3D Gaussian Splatting. The main challenges of this task lie in the preservation of geometric consistency and the maintenance of texture coherence in the presence of the substantial discrete nature of Gaussian primitives. We introduce a robust framework specifi

Mauro Martini, Noé Pérez-Higueras, Andrea Ostuni, Marcello Chiaberge

Human-aware navigation is a complex task for mobile robots, requiring an autonomous navigation system capable of achieving efficient path planning together with socially compliant behaviors. Social planners usually add costs or constraints to the objective function, leading to intricate tuning processes or tailoring the solution to the specific social scenar

Haoyan Gong, Yuzheng Feng, Zhenrong Zhang, Xianxu Hou

Vehicle license plate recognition is a crucial task in intelligent traffic management systems. However, the challenge of achieving accurate recognition persists due to motion blur from fast-moving vehicles. Despite the widespread use of image synthesis approaches in existing deblurring and recognition algorithms, their effectiveness in real-world scenarios r

Bin Dai, Huilan Zeng, Chensong Zhang, Shuo Zhang

In this paper, we study the numerical method for the bi-Laplace problems with inhomogeneous coefficients; particularly, we propose finite element schemes on rectangular grids respectively for an inhomogeneous fourth-order elliptic singular perturbation problem and for the Helmholtz transmission eigenvalue problem. The new methods use the reduced rectangle Mo

Xiangwei Li, Dongdong Wan, Mengqi Zhang, Huanshu Tan

This study presents analytical and numerical investigations of Marangoni interfacial instability in a two-liquid-layer system with constant solute transfer across the interface. While previous research has established that both diffusivity and viscosity ratios affect hydrodynamic stability via the Marangoni effect, the specific nonlinear dynamics and the rol

Yeow Meng Chee, Tuvi Etzion, Hoang Ta, Van Khu Vu

An $(m,n,R)$-de Bruijn covering array (dBCA) is a doubly periodic $M \times N$ array over an alphabet of size $q$ such that the set of all its $m \times n$ windows form a covering code with radius $R$. An upper bound of the smallest array area of an $(m,n,R)$-dBCA is provided using a probabilistic technique which is similar to the one that was used for an up

Lequn Chen, Guijun Bi, Xiling Yao, Jinlong Su

Laser Additive Manufacturing (LAM) presents unparalleled opportunities for fabricating complex, high-performance structures and components with unique material properties. Despite these advancements, achieving consistent part quality and process repeatability remains challenging. This paper provides a comprehensive review of various state-of-the-art in-situ

Temur Kutsia, Daniel Ventura, David Monniaux, José F. Morales

This volume contains * The post-proceedings of the Eighteenth Logical and Semantic Frameworks with Applications (LSFA 2023). The meeting was held on July 1-2, 2023, organised by the Sapienza Universit\`a di Roma, Italy. LSFA aims to bring researchers and students interested in theoretical and practical aspects of logical and semantic frameworks and their app

Zhaopeng Gu, Bingke Zhu, Guibo Zhu, Yingying Chen

Zero-shot anomaly detection (ZSAD) methods entail detecting anomalies directly without access to any known normal or abnormal samples within the target item categories. Existing approaches typically rely on the robust generalization capabilities of multimodal pretrained models, computing similarities between manually crafted textual features representing "no

Shujing Pan, Bo Yang

We prove a Minkowski type inequality for weakly mean convex and star-shaped hypersurfaces in warped cylinders which are asymptotically flat or hyperbolic. In particular, we show that this sharp inequality holds for outward minimizing hypersurfaces in the Schwarzschild manifold or the hyperbolic space using the weak solution of the inverse mean curvature flow

Yaqun Yang, Jinlong Lei

We consider an $n$ agents distributed optimization problem with imperfect information characterized in a parametric sense, where the unknown parameter can be solved by a distinct distributed parameter learning problem. Though each agent only has access to its local parameter learning and computational problem, they mean to collaboratively minimize the averag

Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann

Printed mathematical expression recognition (MER) models are usually trained and tested using LaTeX-generated mathematical expressions (MEs) as input and the LaTeX source code as ground truth. As the same ME can be generated by various different LaTeX source codes, this leads to unwanted variations in the ground truth data that bias test performance results

Ran Chen, Zeke Lian, Yueheng He, Xiao Ling

In traditional human living environment landscape design, the establishment of three-dimensional models is an essential step for designers to intuitively present the spatial relationships of design elements, as well as a foundation for conducting landscape analysis on the site. Rapidly and effectively generating beautiful and realistic landscape spaces is a

Chenhao Du, Qingfeng Sun

Let $\tau_k(n)$ be the $k$-th divisor function. In this paper, we derive an asymptotic formula for the sum $$ \sum_{1\leq n_1,n_2, \dots, n_{\ell}\leq X^{\frac{1}{r}} \atop 1\leq n_{\ell+1}\le X^{\frac{1}{s}}}\tau_k(n_1^r+n_2^r+\dots +n_{\ell}^r+n_{\ell+1}^s), $$ where $k\geq 4$, $r\geq 2$, $s\geq 2$ and $\ell\geq 2$ are integers. Previously only special cas

Emilien Wansart, Maxime Goffart, Justin Iurman, Benoit Donnet

The last few years in the software engineering field has seen a paradigm shift from monolithic application towards architectures in which the application is split in various smaller entities (i.e., microservices) fueled by the improved availability and ease of use of containers technologies such as Docker and Kubernetes. Those microservices communicate betwe

Zoe Shapcott

This report provides an exploration of different distance measures that can be used with the $K$-means algorithm for cluster analysis. Specifically, we investigate the Mahalanobis distance, and critically assess any benefits it may have over the more traditional measures of the Euclidean, Manhattan and Maximum distances. We perform this by first defining the

Bingqing Liu

Most existing temporal point process models are characterized by conditional intensity function. These models often require numerical approximation methods for likelihood evaluation, which potentially hurts their performance. By directly modelling the integral of the intensity function, i.e., the cumulative hazard function (CHF), the likelihood can be evalua

Rohit Parasnis, Saurabh Amin

We address the challenge of promoting sustainable practices in production forests managed by strategic entities (agents) that harvest agricultural commodities under concession agreements. These entities engage in activities that either follow sustainable production practices or expand into protected forests for agricultural growth, which leads to unsustainab

Christian Choffrut

We show that the equational theory of the structure $\langle \omega^{\omega}: (x,y)\mapsto x+y, x\mapsto \omega x \rangle $ is finitely axiomatizable and give a simple axiom schema when the domain is the set of transfinite ordinals. We give an algorithm that given a pair of terms $(E,F)$ decides in linear time with respect of their common length whether or n

Narek Maloyan, Ekansh Verma, Bulat Nutfullin, Bislan Ashinov

Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, but their vulnerability to trojan or backdoor attacks poses significant security risks. This paper explores the challenges and insights gained from the Trojan Detection Competition 2023 (TDC2023), which focused on identifying and evaluating trojan attacks on LLMs. We i

Tong Wang, Guanzhou Chen, Xiaodong Zhang, Chenxi Liu

Despite the rapid evolution of semantic segmentation for land cover classification in high-resolution remote sensing imagery, integrating multiple data modalities such as Digital Surface Model (DSM), RGB, and Near-infrared (NIR) remains a challenge. Current methods often process only two types of data, missing out on the rich information that additional moda

Pradip Laha, P. A. Ameen Yasir, Peter van Loock

We investigate a generic tripartite quantum system featuring a single qubit interacting concurrently with two quantized harmonic oscillators via nonlinear multiphoton Jaynes-Cummings (MPJC) interactions. Assuming the qubit is initially prepared in a superposition state and the two oscillators are in arbitrary Fock states, we analytically trace the temporal e

Sheng Yan, Mengyuan Liu, Yong Wang, Yang Liu

In this paper, we address the unexplored question of temporal sentence localization in human motions (TSLM), aiming to locate a target moment from a 3D human motion that semantically corresponds to a text query. Considering that 3D human motions are captured using specialized motion capture devices, motions with only a few joints lack complex scene informati

Paul Mercat

We define a morphic subshift as a subshift generated by the image of a substitution subshift by another substitution. In other words, it is the subshift associated with a ultimately periodic directive sequence. We present an efficient algorithm for computing eigenvalues of morphic subshifts using coboundaries. We show that continuous eigenvalues of S-adic su

Patil Pratik Vijaykumar, Prerna Tulsiani, Sunil Mane

Public Cloud Computing has become a fundamental part of modern IT infrastructure as its adoption has transformed the way businesses operate. However, cloud security concerns introduce new risks and challenges related to data protection, sharing, and access control. A synergistic integration of blockchain with the cloud holds immense potential. Blockchain's d

Zehao Dong, Muhan Zhang, Yixin Chen

Graph neural networks (GNNs) have revolutionized the field of machine learning on non-Euclidean data such as graphs and networks. GNNs effectively implement node representation learning through neighborhood aggregation and achieve impressive results in many graph-related tasks. However, most neighborhood aggregation approaches are summation-based, which can

Shengbo Wang, Chuan Lin, Guangjie Han, Shengchao Zhu

In recent years, autonomous underwater vehicle (AUV) swarms are gradually becoming popular and have been widely promoted in ocean exploration or underwater tracking, etc. In this paper, we propose a multi-AUV cooperative underwater multi-target tracking algorithm especially when the real underwater factors are taken into account. We first give normally model

Tamoghna Ray, Manas Kulkarni

We investigate two key aspects of quantum systems by using the Tavis-Cummings dimer system as a platform. The first aspect involves unraveling the relationship between the phenomenon of self-trapping (or lack thereof) and integrability (or quantum chaos). Secondly, we uncover {the possibility of} mixed behavior in this quantum system using diagnostics based

Benjamin Alt, Julia Dvorak, Darko Katic, Rainer Jäkel

Over the past decade, deep learning helped solve manipulation problems across all domains of robotics. At the same time, industrial robots continue to be programmed overwhelmingly using traditional program representations and interfaces. This paper undertakes an analysis of this "AI adoption gap" from an industry practitioner's perspective. In response, we p

J. G. Dai, Yiquan Ji, Masakiyo Miyazawa

We are interested to prove that the stationary distribution of a multiclass queueing network converges to the stationary distribution of a semimartingale reflecting Brownian motion (SRBM) in heavy traffic. A key condition for this convergence is that the sequence of the pre-limit stationary distributions under appropriate scaling is tight. In Braverman et al

Shoichi Fujimori, Yu Kawakami, Masatoshi Kokubu

Surfaces with concentric $K$-contours and parallel $K$-contours in Euclidean $3$-space are defined. Crucial examples are presented and characterization of them are given.

Yang He, Joey Tianyi Zhou

Hierarchical vision transformers (ViTs) have two advantages over conventional ViTs. First, hierarchical ViTs achieve linear computational complexity with respect to image size by local self-attention. Second, hierarchical ViTs create hierarchical feature maps by merging image patches in deeper layers for dense prediction. However, existing pruning methods ig

Jie Peng, Weiyu Li, Stefan Vlaski, Qing Ling

Robustness to malicious attacks is of paramount importance for distributed learning. Existing works usually consider the classical Byzantine attacks model, which assumes that some workers can send arbitrarily malicious messages to the server and disturb the aggregation steps of the distributed learning process. To defend against such worst-case Byzantine att

Weiheng Zhong, Hadi Meidani

Solving parametric Partial Differential Equations (PDEs) for a broad range of parameters is a critical challenge in scientific computing. To this end, neural operators, which \textcolor{black}{predicts the PDE solution with variable PDE parameter inputs}, have been successfully used. However, the training of neural operators typically demands large training

Feiqi Cao, Caren Han, Hyunsuk Chung

In this work, we propose a novel tree-based explanation technique, PEACH (Pretrained-embedding Explanation Across Contextual and Hierarchical Structure), that can explain how text-based documents are classified by using any pretrained contextual embeddings in a tree-based human-interpretable manner. Note that PEACH can adopt any contextual embeddings of the

Jinhuan Wang, Keyu Li, Hui Huang

In this paper, we present an innovative particle system characterized by moderate interactions, designed to accurately approximate kinetic flocking models that incorporate singular interaction forces and local alignment mechanisms. We establish the existence of weak solutions to the corresponding flocking equations and provide an error estimate for the mean-

Pramit Rej, Akashdip Karmakar

The primary objective of this paper is to develop a well-behaved class of Heintzmann IIa [{\em H. Heintzmann, Z. Physik 228, 489-493 (1969)}] solution in the context of $f(R,\, T)$ gravity. In the $f(R, T)$ framework, the gravitational action includes both the Ricci scalar ($R$) and the trace of the energy-momentum tensor ($T$). We chose a particular $f(R,\,

Jiehua Mai, Enhui Shi, Kesong Yan, Fanping Zeng

We show a somewhat surprising result: if $E$ is a disk in the plane $\mathbb R^2$, then there is a homeomorphism $h:\mathbb R^2\rightarrow\mathbb R^2$ such that, for every $x\in\partial E$, the orbit $O(x, h)$ is bounded, but for every $y\in {\rm Int}(E)$, the orbit $O(y, h)$ is doubly divergent. To prove this, we define a class of homeomorphisms on the squa

Felix Otto, Christian Wagner

We consider a drift-diffusion process with a time-independent and divergence-free random drift that is of white-noise character. We are interested in the critical case of two space dimensions, where one has to impose a small-scale cut-off for well-posedness, and is interested in the marginally super-diffusive behavior on large scales. In the presence of an (

Kepeng Xu, Li Xu, Gang He, Wenxin Yu

Multiple complex degradations are coupled in low-quality video faces in the real world. Therefore, blind video face restoration is a highly challenging ill-posed problem, requiring not only hallucinating high-fidelity details but also enhancing temporal coherence across diverse pose variations. Restoring each frame independently in a naive manner inevitably

Md Mehedi Hasan, He Feng

Modern technology necessitates the use of dependable, fast, and inexpensive networks as the backbone for data transmission. Switched Ethernet coupled with the Time Sensitive Networking

Shubham Kishore, Alok C. Gupta, Paul J. Wiita, S. N. Tiwari

The extreme TeV blazar 1ES 0229+200 is a high-frequency-peaked BL Lacertae object. It has not shown intraday variability in extensive optical and X-ray observations. Nor has it shown any significant variability on any measurable timescale in the 1-100 GeV energy range over a 14-year span, but variations in the source flux around its average are present in th

Hiroaki Kusunose, Jun-ichiro Kishine, Hiroshi M. Yamamoto

A clear understanding of chirality in spin-active electronic states is discussed in order to address confusions about chiral effects recently discovered in materials science. Electronic toroidal monopole $G_0$ can serve as a measure of chirality in this categorization, which can be clearly related to the chiral density operator in the Dirac equation. We exte

T. Inakura, N. Hinohara, H. Nakada

We investigate the charge and point-proton radii of the Ca nuclei in detail in the density functional theory framework. As the Fayans energy density functional provides characteristic $N$-dependence, successfully describing the parabolic behavior of the differential charge radii in $20\leq N\leq 28$, we pose our particular focus on its physics origin, by dec

Resmi Ramachandranpillai, Md Fahim Sikder, David Bergström, Fredrik Heintz

Synthetic data generation offers a promising solution to enhance the usefulness of Electronic Healthcare Records (EHR) by generating realistic de-identified data. However, the existing literature primarily focuses on the quality of synthetic health data, neglecting the crucial aspect of fairness in downstream predictions. Consequently, models trained on synt

Samuel Rhys Cox

The ubiquity of smartphones has led to an increase in on demand healthcare being supplied. For example, people can share their illness-related experiences with others similar to themselves, and healthcare experts can offer advice for better treatment and care for remediable, terminal and mental illnesses. As well as this human-to-human communication, there h

B. Miao, E. Rockafellow, J. E. Shrock, S. W. Hancock

Hydrodynamic plasma waveguides initiated by optical field ionization (OFI) have recently become a key component of multi-GeV laser wakefield accelerators. Here, we present the most complete and accurate experimental and simulation-based characterization to date, applicable both to current multi-GeV experiments and future 100 GeV-scale laser plasma accelerato

Mingshan Xie, Yuchen Wang, Haiping Huang

Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples. To design a semantically meaningful representation learning, we discard backpropagation, and instead, propose a local contrastive learning, where the representation for the inputs bearing the same label shrink (akin to boson

Keqin Li, Armando Zhu, Peng Zhao, Jintong Song

This study explores the application of deep learning technologies in software development processes, particularly in automating code reviews, error prediction, and test generation to enhance code quality and development efficiency. Through a series of empirical studies, experimental groups using deep learning tools and control groups using traditional method

Mauro González-Otero, Jordi Cepa, Carmen P. Padilla-Torres, Maritza A. Lara-López

Methods.We applied distinct selection criteria to attain an SFG sample with minimal AGN contamination. Multiple approaches were used to estimate the intrinsic extinction, SFR and gas-phase metallicity for the SFGs. In conjunction with findings in the literature, we examined the correlation between SFRs and stellar masses ($M_*$), as well as the metallicity e

Xun Wu, Shaohan Huang, Furu Wei

LoRA has gained widespread acceptance in the fine-tuning of large pre-trained models to cater to a diverse array of downstream tasks, showcasing notable effectiveness and efficiency, thereby solidifying its position as one of the most prevalent fine-tuning techniques. Due to the modular nature of LoRA's plug-and-play plugins, researchers have delved into the

Kenzo Ishikawa, Yuya Nishio

The overlap integrals of scattering states in potentials of finite widths are expressed with their asymptotic behaviors and those of energies $E_1$ and $E_2$ consist of diagonal terms that are proportional to $\delta(E_1-E_2)$ and nondiagonal terms. Owing to the composition of nondiagonal terms, superpositions of stationary states have time-dependent norms a

Chunkit Chan, Cheng Jiayang, Yauwai Yim, Zheye Deng

Large Language Models (LLMs) have sparked substantial interest and debate concerning their potential emergence of Theory of Mind (ToM) ability. Theory of mind evaluations currently focuses on testing models using machine-generated data or game settings prone to shortcuts and spurious correlations, which lacks evaluation of machine ToM ability in real-world h

Maryam Sharifi, Shahab Heshmati-Alamdari

This paper introduces a safe force/position tracking control strategy designed for Free-Floating Mobile Manipulator Systems (MMSs) engaging in compliant contact with planar surfaces. The strategy uniquely integrates the Control Barrier Function (CBF) to manage operational limitations and safety concerns. It effectively addresses safety-critical aspects in th

Anilatmaja Aryasomayajula, Jürg Kramer, Anna-Maria von Pippich

In this article, we give $L^{\infty}$-norm bounds for the natural invariant norm of cusp forms of real weight $k$ and character $\chi$ for any cofinite Fuchsian subgroup $\Gamma\subset\mathrm{SL}_{2}(\mathbb{R})$. Using the representation of Jacobi cusp forms of integral weight $k$ and index $m$ for the modular group $\Gamma_{0}=\mathrm{SL}_{2}(\mathbb{Z})$

Atsushi Miki, Yusuke Morishita, Toshiyasu Matsushima

Private Information Retrieval (PIR) is a mechanism for efficiently downloading messages while keeping the index secret. Here, PIRs in which servers do not communicate with each other are called standard PIRs, and PIRs in which some servers communicate with each other are called colluding PIRs. The information-theoretic upper bound on efficiency has been give

Jenaro Guisasola, Kristina Zuza, Jaume Ametller, Paulo Sarriugarte

Over the last three decades, various didactic proposals have been published in an attempt to connect theory and research findings with the design of Teaching-Learning Sequences (TLS) in various contexts. Many studies have analysed the process of designing teaching-learning sequences as a research activity. This line of research aims to increase the impact an

Zhongwei Tang, Heming Wang, Bingwei Zhang

We prove some results on the density and multiplicity of positive solutions to the prescribed Webster scalar curvature problem on the $(2n+1)$-dimensional standard unit CR sphere $(\mathbb{S} ^{2n+1},\theta_0)$. Specifically, we construct arbitrarily many multi-bump solutions via the variational gluing method. In particular, we show the Webster scalar curvat

Daniel N Wilke

Multifidelity surrogate modelling combines data of varying accuracy and cost from different sources. It strategically uses low-fidelity models for rapid evaluations, saving computational resources, and high-fidelity models for detailed refinement. It improves decision-making by addressing uncertainties and surpassing the limits of single-fidelity models, whi

Peijun Li, Xiaokai Yuan

Consider the interaction of biharmonic waves with a periodic array of cavities, characterized by the Kirchhoff--Love model. This paper investigates the perfectly matched layer (PML) formulation and its numerical soution to the governing biharmonic wave equation. The study establishes the well-posedness of the associated variational problem employing the Fred

Ben Fei, Yixuan Li, Weidong Yang, Lipeng Ma

State-of-the-art 3D models, which excel in recognition tasks, typically depend on large-scale datasets and well-defined category sets. Recent advances in multi-modal pre-training have demonstrated potential in learning 3D representations by aligning features from 3D shapes with their 2D RGB or depth counterparts. However, these existing frameworks often rely

A. A. Osipov

The bounds on the light quark masses are obtained by fitting the squares of pseudoscalar meson masses $m_\pi^2$ and $m_K^2$ to second order in $1/N_c$ expansion. The result is an algebraic cubic curve whose coefficients are the known Weinberg values for the quark mass ratios $m_u/m_d$ and $m_s/m_d$. Additional restrictions arise when using the ratio $m_s/m_{

Ye Cai, Zonglin Yang, Liwei Ni, Junfeng Liu

Algorithm parallelization to leverage multi-core platforms for improving the efficiency of Electronic Design Automation~(EDA) tools plays a significant role in enhancing the scalability of Integrated Circuit (IC) designs. Logic optimization is a key process in the EDA design flow to reduce the area and depth of the circuit graph by finding logically equivale

Mohammad Ali Ahmadpoor, Abbas Moameni

In this paper, we investigate Monge-Kantorovich problems for which the absolute continuity of marginals is relaxed. For $X,Y\subseteq\mathbb{R}^{n+1}$ let $(X,\mathcal{B}_X,\mu)$ and $(Y,\mathcal{B}_Y,\nu)$ be two Borel probability spaces, $c:X\times Y\to\mathbb{R}$ be a cost function, and consider the problem \begin{align*}\tag{MKP}\label{MKPEQ} \inf\left\{

K. Akiba, M. Alexander, C. Bertella, A. Biolchini

The LHCb detector has undergone a major upgrade for LHC Run 3. This Upgrade I detector facilitates operation at higher luminosity and utilises full-detector information at the LHC collision rate, critically including the use of vertex information. A new vertex locator system, the VELO Upgrade, has been constructed. The core element of the new VELO are the do

Ye Cai, Zonglin Yang, Liwei Ni, Biwei Xie

With the development of large-scale integrated circuits, electronic design automation~(EDA) tools are increasingly emphasizing efficiency, with parallel algorithms becoming a trend. The optimization of delay reduction is a crucial factor for ASIC technology mapping, and supergate technology proves to be an effective method for achieving this in EDA tools flo

Shai Meital, Lior Rokach, Roman Vainshtein, Nir Grinberg

Multi-participant discussions tend to unfold in a tree structure rather than a chain structure. Branching may occur for multiple reasons -- from the asynchronous nature of online platforms to a conscious decision by an interlocutor to disengage with part of the conversation. Predicting branching and understanding the reasons for creating new branches is impo

Mingnan Ding, Jun Wu, Xiangjun Xing

In this work, we study the stochastic thermodynamics of micro-magnetic systems. We first formulate the stochastic dynamics of micro-magnetic systems by incorporating noises into Landau-Lifshitz (LL) equation, which describes the irreversible and deterministic dynamics of magnetic moments. The resulting stochastic Landau-Lifshitz (sLL) equation obeys detailed

Cai Chen, Runzhong Zhang, Jianjun Gao, Kejun Wu

Temporal sentence grounding involves the retrieval of a video moment with a natural language query. Many existing works directly incorporate the given video and temporally localized query for temporal grounding, overlooking the inherent domain gap between different modalities. In this paper, we utilize pseudo-query features containing extensive temporally gl

Majid Seyed-Salehi

The probabilistic cellular automaton (PCA) method is highlighted for its relatively simple numerical algorithm and low computational cost in the simulation of microstructural evolution. In this method, probabilistic state change rules are implemented to compute the evolution of cell states at each time step. The stochastic nature of this simulation method le

Yaser Abdi, Masoud Taleb, Soheil Hajibaba, Mohsen Moayedi

Two-dimensional metals, such as graphene, have undergone extensive exploration, with graphene exhibiting a metallic response limited to the infrared spectral range. Overcoming the challenge of extending the electron mobility in two-dimensional metals to achieve plasmonic behaviors in the visible range necessitates innovative synthesis procedures. In this stu

Heng Zhou, Yongjun Wang, Baoshan Wang, Jian Yan

The classical belief revision framework, as proposed by Alchourron, Gardenfors, and Makinson, involves the revision of a theory based on eight postulates. In this paper, we focus on the exploration of a revision theory grounded in quantum mechanics, referred to as the natural revision theory. There are two reasoning modes in quantum systems: static intuition

Gilberto Bini, Robert Laterveer

Cayley and Oguiso have constructed certain quartic K3 surfaces $S$, with automorphisms $g$ of infinite order. We show that when $g$ is symplectic (resp. anti-symplectic), it acts as the identity (resp. minus the identity) on the degree zero part of the Chow group of zero-cycles of $S$.

Pooja, Sachindra Nath Sarangi, D. Samal, Chanchal Sow

The magnetism in the correlated metal CaRuO$_3$ is enigmatic as it is poised near a triple point among the ferromagnetic, antiferromagnetic, and paramagnetic ground states. Here we report a detailed work on structural, spectroscopic, magnetic, and transport properties in CaRu$_{1-x}$Cr$_x$O$_3$. We find that Cr doping reduces the orthorhombicity in CaRuO$_3$

Ripon Kumar Saha, Dehao Qin, Nianyi Li, Jinwei Ye

Tackling image degradation due to atmospheric turbulence, particularly in dynamic environment, remains a challenge for long-range imaging systems. Existing techniques have been primarily designed for static scenes or scenes with small motion. This paper presents the first segment-then-restore pipeline for restoring the videos of dynamic scenes in turbulent e

Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou

The existing definitions of graph convolution, either from spatial or spectral perspectives, are inflexible and not unified. Defining a general convolution operator in the graph domain is challenging due to the lack of canonical coordinates, the presence of irregular structures, and the properties of graph symmetries. In this work, we propose a novel and gen

Bin Li, Ziping Wei, Shaoshi Yang, Yang Zhang

To glean the benefits offered by massive multi-input multi-output (MIMO) systems, channel state information must be accurately acquired. Despite the high accuracy, the computational complexity of classical linear minimum mean squared error (MMSE) estimator becomes prohibitively high in the context of massive MIMO, while the other low-complexity methods degra