December 2024 arXiv papers — page 15

Yang Cai, Siddharth Mitra, Xiuyuan Wang, Andre Wibisono

We study zero-sum games in the space of probability distributions over the Euclidean space $\mathbb{R}^d$ with entropy regularization, in the setting when the interaction function between the players is smooth and strongly convex-strongly concave. We prove an exponential convergence guarantee for the mean-field min-max Langevin dynamics to compute the equili

Haorui Ji, Rong Wang, Taojun Lin, Hongdong Li

Generative modeling of 3D human bodies have been studied extensively in computer vision. The core is to design a compact latent representation that is both expressive and semantically interpretable, yet existing approaches struggle to achieve both requirements. In this work, we introduce JADE, a generative framework that learns the variations of human shapes

Yong Du

We explore two longitudinal single-spin asymmetries induced from parity violation in neutral-current deep inelastic scattering at the proposed Electron-ion collider in China (EicC): $A_{PV}^{e\,(p)}$ from longitudinally polarized (unpolarized) electrons scattering off unpolarized (longitudinally polarized) protons. We find $A_{PV}^e$, of $\mathcal{O}(10^{-4}

Xiujie Song, Xiaoyi Pang, Haifeng Tang, Mengyue Wu

Quantifying image complexity at the entity level is straightforward, but the assessment of semantic complexity has been largely overlooked. In fact, there are differences in semantic complexity across images. Images with richer semantics can tell vivid and engaging stories and offer a wide range of application scenarios. For example, the Cookie Theft picture

Sidra Nasir, Qamar Abbas, Samita Bai, Rizwan Ahmed Khan

This article discusses the evolving role of artificial intelligence (AI) in the legal profession, focusing on its potential to streamline tasks such as document review, research, and contract drafting. However, challenges persist, particularly the occurrence of "hallucinations" in AI models, where they generate inaccurate or misleading information, undermini

Alexander Blatt, Dietrich Klakow

Operational machine-learning based assistant systems must be robust in a wide range of scenarios. This hold especially true for the air-traffic control (ATC) domain. The robustness of an architecture is particularly evident in edge cases, such as high word error rate (WER) transcripts resulting from noisy ATC recordings or partial transcripts due to clipped

Zhengyang Lu, Weifan Wang, Tianhao Guo, Feng Wang

Reflections often degrade the visual quality of images captured through transparent surfaces, and reflection removal methods suffers from the shortage of paired real-world samples.This paper proposes a hybrid approach that combines cycle-consistency with denoising diffusion probabilistic models (DDPM) to effectively remove reflections from single images with

Yuxin Wang, Yi Zhang, Kun Jiang

Determining the electronic structure of La$_3$Ni$_2$O$_7$ is an essential step towards uncovering their superconducting mechanism. It is widely believed that the bilayer apical oxygens play an important role in the bilayer La$_3$Ni$_2$O$_7$ electronic structure. Applying the hybrid exchange-correlation functionals, we obtain a more accurate electronic struct

Aashna Anil Zade, Kenji Sugisaki, Matthias Werner, Ana Palacios

The quantum-classical hybrid variational quantum eigensolver (VQE) algorithm is arguably the most popular noisy intermediate-scale quantum (NISQ) era approach to quantum chemistry. We consider the underexplored quantum annealing eigensolver (QAE) algorithm as a worthy alternative. We use a combination of numerical calculations for a system where strong corre

Miloš Kurilić, Boriša Kuzeljević

If $\lambda <\kappa$ are infinite cardinals, a linear order $L$ is isomorphic to a maximal chain in $[\kappa ]^{\kappa |\kappa }$ (resp. $[\kappa ]^{\lambda |\kappa }$; $[\kappa ]^{\kappa |\lambda }$) iff $L$ is weakly Boolean, the weight of all initial segments of $L$ is equal to $\kappa$ (resp. $\lambda$, $\lambda ^+$) and the weight of all final segments

Kai Li, Yi Ling, Zhangping Yu

We investigate the generation rate of the quantum entanglement in a system composed of multiple massive particles with large spin, where the mass of a single particle can be split into multiple trajectories by a generalized Stern-Gerlach interferometer. Taking the coherent spin states (CSS) as the initial state and considering the gravitational interaction d

Yi-Xian Chen, Jiunn-Wei Chen

The one loop matching kernels between parton distribution functions (PDFs) for parton $i=u,d,s,g$ and their corresponding quasi-PDFs are computed at one loop in the hybrid-ratio scheme. We found that, in addition to the conservation of the quasi-quark number for each flavor, the second moment $\langle x \rangle_{\tilde{i}}=\langle x \rangle_i$ of quasi-PDF o

Clara K. Geschner, Adam Yanis Chaou, Vatsal Dwivedi, Piet W. Brouwer

A two-dimensional second-order topological insulator exhibits topologically protected zero-energy states at its corners. In the literature, the breathing kagome lattice with nearest-neighbor hopping is often mentioned as an example of a two-dimensional second-order topological insulator. Here we show by explicit construction that the corner states of the bre

Thomas Basile, Shailesh Dhasmana, Evgeny Skvortsov

Conformal higher-spin gravity is the log-divergent part of the effective action of the scalar field coupled to background fields via higher-spin currents, as was defined by Segal and Tseytlin, which can be worked out over the flat space background. We revisit the problem of the scalar field in a higher-spin background and propose a manifestly covariant versi

Zhu-Ding Duan, Jian-Peng Wang, Run-Hui Li, Cai-Dian Lv

The first observation of $CP$ violation in baryon decays was recently reported by the LHCb collaboration in $\Lambda_b^0\to pK^-\pi^+\pi^-$ with $A_{CP} = (2.45 \pm 0.46 \pm 0.10)\%$, which inspires the study on baryon non-leptonic decays. In this work, we perform the first calculation of five exclusive non-leptonic decays, $\Lambda^{0}_{b}\to p\pi^{-}, p K^

Zhongzhinan Dong, Dan Zhang, Guoyang Fu, Jian-Pin Wu

In this paper, we exhaustively investigate the quasinormal modes (QNMs) of a probe scalar field over a d-dimensional regular black hole (BH) characterized by the parameter A. The quasinormal frequencies (QNFs) exhibit different behaviors with respect to the parameter A for d = 4 and d > 4. Firstly, the trends of QNFs with respect to A exhibit completely oppo

Yuhan Liu, Florent Guepin, Igor Shilov, Yves-Alexandre De Montjoye

The widespread collection and sharing of location data, even in aggregated form, raises major privacy concerns. Previous studies used meta-classifier-based membership inference attacks~(MIAs) with multi-layer perceptrons~(MLPs) to estimate privacy risks in location data, including when protected by differential privacy (DP). In this work, however, we show th

Ayush Ghadiya, Purbayan Kar, Vishal Chudasama, Pankaj Wasnik

Recently, weakly supervised video anomaly detection (WS-VAD) has emerged as a contemporary research direction to identify anomaly events like violence and nudity in videos using only video-level labels. However, this task has substantial challenges, including addressing imbalanced modality information and consistently distinguishing between normal and abnorm

Shijia Ge, Weixiang Zhang, Shuzhao Xie, Baixu Yan

Respiratory sound classification plays a pivotal role in diagnosing respiratory diseases. While deep learning models have shown success with various respiratory sound datasets, our experiments indicate that models trained on one dataset often fail to generalize effectively to others, mainly due to data collection and annotation \emph{inconsistencies}. To add

Jianing Li, Weiyao Ke

The transport property of cold and dense nucleon matter is important for nuclear physics but is relatively less studied than that at finite temperatures. In this paper, we present a primary study of bulk and shear viscosities in the limit $T/\mu_B \ll 1$, where $T$ and $\mu_B$ are the temperature and the baryon chemical potential. The analysis is performed f

G. Holgado, J. Maíz Apellániz, J. A. Caballero

MUDEHaR is an on-going multi-epoch photometric survey with two narrow filters in H$\alpha$ and the calcium triplet window that uses the T80Cam wide-field imager at the JAST/T80 telescope at Spanish Javalambre astronomical observatory. It is obtaining 100 epochs/year per field for 20 fields in the Galactic disk, each of 2\,deg$^2$, for a total of 40\,deg$^2$.

Tomoki Nakanishi, Takahiro Nishinaka

We study the compactification of 4D $\mathcal{N}=4$ SYM on $S^1$ from the viewpoint of the superconformal index. In the cases that the gauge group of the 4D SYM is $U(N)$ and $Usp(2N)$, the resulting 3D theory is believed to be the ABJM theory with the Chern-Simons level $k=1$ and $k=2$, respectively. This suggests that the small $S^1$ limit of the superconf

Jinming Li, Yichen Zhu, Zhibin Tang, Junjie Wen

Robot foundation models, particularly Vision-Language-Action (VLA) models, have garnered significant attention for their ability to enhance robot policy learning, greatly improving robot's generalization and robustness. OpenAI's recent model, O1, showcased impressive capabilities in solving complex problems by utilizing extensive reasoning chains. This promp

Dan Zhang, Guoyang Fu, Xi-Jing Wang, Qiyuan Pan

This paper investigates the observational appearances of an inner extremal regular black hole(IERBH) illuminated by various types of accretion models. The study reveals that when the BH is illuminated by specific accretion flows, the effects of quantum gravity become more pronounced,significantly impacting key observational features such as the shadow radius

Tommaso Toso, Paolo Frasca, Alain Y. Kibangou

Traditional non-atomic selfish routing games present some limitations in properly modeling road traffic. This paper introduces a novel type of non-atomic selfish routing game leveraging concepts from Daganzo's cell transmission model (CTM). Each network link is characterized by a supply and demand mechanism that enforces capacity constraints based on current

Nassim Mahammedi

The transition to sustainable energy has accelerated research into perovskite solar cells (PSCs) as promising candidates for next-generation photovoltaics. Despite their remarkable efficiencies, the commercialization of PSCs is hindered by lead toxicity and material instability. In this study, we explore a lead-free Samarium-based double perovskite oxide Sm$

Giulio Caldarelli

The Bitcoin Network is a sophisticated accounting system that allows its underlying cryptocurrency to be trusted even in the absence of a reliable financial authority. Given its undeniable success, the technology, generally referred to as blockchain, has also been proposed as a means to improve legacy accounting systems. Accounting for real-world data, howev

Sariel Ofek, Amit Somech

Explaining the results of clustering pipelines by unraveling the characteristics of each cluster is a challenging task, often addressed manually through visualizations and queries. Existing solutions from the domain of Explainable Artificial Intelligence (XAI) are largely ineffective for cluster explanations, and interpretable-by-design clustering algorithms

Shees Zulfiqar, Ozgur B. Akan

Molecular Communication (MC) utilizes chemical molecules to transmit information, introducing innovative strategies for pharmaceutical interventions and enhanced immune system monitoring. This paper explores Molecular communication based approach to disrupt Quorum Sensing (QS) pathways to bolster immune defenses against antimicrobial-resistant bacteria. Quor

Han-Qing Shi, Hai-Qing Zhang

Renyi entropy with multiple disjoint intervals are computed from the improved swapping operations by two methods: one is from the direct diagonalization of the Hamiltonian and the other one is from the state-of-the-art machine learning method with neural networks. We use the paradigmatic transverse-field Ising model in one-dimension to demonstrate the strate

Lenny Jones

We say that a monic polynomial $f(x)\in {\mathbb Z}[x]$ of degree $N\ge 2$ is monogenic if $f(x)$ is irreducible over ${\mathbb Q}$ and $\{1,\theta,\theta^2,\ldots ,\theta^{N-1}\}$ is a basis for the ring of integers of ${\mathbb Q}(\theta)$, where $f(\theta)=0$. In this article, we investigate the divisibility of the class numbers of quadratic fields ${\mat

Toru Kojo

Recent observations of neutron stars, combined with causality, thermodynamic stability, and nuclear constraints, indicate a rapid stiffening of QCD matter at densities slightly above nuclear saturation density ($n_0 \simeq 0.16\,{\rm fm}^{-3}$). The evolution of the stiffening is faster than expected from purely nucleonic models with many-body repulsion. Tak

Md Habibor Rahman, Mohammed Shafae

The increasing cybersecurity threats to critical manufacturing infrastructure necessitate proactive strategies for vulnerability identification, classification, and assessment. Traditional approaches, which define vulnerabilities as weaknesses in computational logic or information systems, often overlook the physical and cyber-physical dimensions critical to

Chang Liu

This note is intended for expanding the details on the derivation and properties of density functional theory, in hope to make them more systematic, better motivated, and step-by-step for readers new to the domain. The note starts with basic concepts in quantum mechanics, then takes the step towards many-body systems using the tools of second quantization an

Pratik Rakesh Singh, Mohammadi Zaki, Pankaj Wasnik

We address the challenging task of neural machine translation (NMT) in the entertainment domain, where the objective is to automatically translate a given dialogue from a source language content to a target language. This task has various applications, particularly in automatic dubbing, subtitling, and other content localization tasks, enabling source conten

Wangyu Wu, Xianglin Qiu, Siqi Song, Zhenhong Chen

Weakly-supervised semantic segmentation (WSSS) has achieved remarkable progress using only image-level labels. However, most existing WSSS methods focus on designing new network structures and loss functions to generate more accurate dense labels, overlooking the limitations imposed by fixed datasets, which can constrain performance improvements. We argue th

Denisa Millo, Blerina Vika, Nevila Baci

The financial sector, a pivotal force in economic development, increasingly uses the intelligent technologies such as natural language processing to enhance data processing and insight extraction. This research paper through a review process of the time span of 2018-2023 explores the use of text mining as natural language processing techniques in various com

Jiong Li, Daniel Braak, Qing-Hu Chen

The anisotropic two-photon quantum Rabi model is studied using the Bogoliubov operator approach. The doubly degenerate exceptional states are identified through analytical methods. By adjusting the position of the last exceptional point belonging to two adjacent energy levels, we derive a condition for the absence of the discrete spectrum at the critical cou

Shonosuke Harada, Ryosuke Yoneda, Hisashi Kashima

Treatment effect estimation, which helps understand the causality between treatment and outcome variable, is a central task in decision-making across various domains. While most studies focus on treatment effect estimation on individual targets, in specific contexts, there is a necessity to comprehend the treatment effect on a group of targets, especially th

Sebastian Bartling, Kazuhiro Ito

We show that the cohomological Brauer groups of the moduli stacks of stable genus $g$ curves over the integers and an algebraic closure of the rational numbers vanish for any $g\geq 2$. For the $n$ marked version, we show the same vanishing result in the range $(g,n)=(1,n)$ with $1\leq n \leq 6$ and all $(g,n)$ with $g\geq 4.$ We also discuss several finiten

Zixuan Cui, Lei Yang

Raising the order of the multipole expansion is a feasible approach for improving the accuracy of the treecode algorithm. However, a uniform order for the expansion would result in the inefficiency of the implementation, especially when the kernel function is singular. In this paper, a $p$-adaptive treecode algorithm is designed to resolve the efficiency iss

Sania Asif, Zhixiang Wu

Building upon the work of Pavel in [P. Kolesnikov, Journal of Mathematical Physics, 56, 7 (2015)], we first present the cohomology of averaging operators on the Lie conformal algebras and use it to develop the cohomology of averaging Lie conformal algebras. We then introduce the homotopy version of averaging Lie conformal algebras and establish a connection

Desmond Lau

We modify Gurevich's definition of sequential algorithms, so that it becomes amenable to computation with arbitrarily large sets on a sufficiently intuitive level. As a result, two classes of abstract algorithms are obtained, namely generalised sequential algorithms (GSeqAs) and generalised sequential algorithms with parameters (GSeqAPs). We derive from each

Björn Garbrecht, Nils Wagner

Extracting information about a system's metastable ground state energy employing functional methods usually hinges on utilizing the late-time behavior of the Euclidean propagator, practically impeding the possibility of determining decay widths of excited states. We demonstrate that such obstacles can be surmounted by working with bounded time intervals, ada

Jiawen Li, Tian Guan, Qingxin Xia, Yizhi Wang

Foundation models have revolutionized the paradigm of digital pathology, as they leverage general-purpose features to emulate real-world pathological practices, enabling the quantitative analysis of critical histological patterns and the dissection of cancer-specific signals. However, these static general features constrain the flexibility and pathological r

Libo Wang

To improve the cognitive autonomy of humanoid robots, this research proposes a multi-scenario reasoning architecture to solve the technical shortcomings of multi-modal understanding in this field. It draws on simulation based experimental design that adopts multi-modal synthesis (visual, auditory, tactile) and builds a simulator "Maha" to perform the experim

Sania Asif

This paper studies the Nijenhuis operator on Hom-Leibniz conformal algebra, defining their representations and cohomologies. We determine the cohomologies for both Hom-Leibniz conformal algebra and Nijenhuis operators on Hom-Leibniz conformal algebra. Subsequently, establishing the cohomology of Hom-Nijenhuis-Leibniz conformal algebras. As an application to

Mansi, Pranshu Pandya, Mahek Bhavesh Vora, Soumya Bharadwaj

Existing datasets for relation classification and extraction often exhibit limitations such as restricted relation types and domain-specific biases. This work presents a generic framework to generate well-structured sentences from given tuples with the help of Large Language Models (LLMs). This study has focused on the following major questions: (i) how to g

Janani Venkatasubramanian, Johannes Köhler, Mark Cannon, Frank Allgöwer

We propose a novel targeted exploration strategy designed specifically for uncertain linear time-invariant systems with energy-bounded disturbances, i.e., without any assumptions on the distribution of the disturbances. We use classical results characterising the set of non-falsified parameters consistent with energy-bounded disturbances. We derive a semidef

Orlando Luongo, Marco Muccino

Differently from the equivalence time between either matter and radiation or dark energy and matter, the equivalence between dark energy and radiation occurs between two subdominant fluids, since it takes place in the matter dominated epoch. However, dark energy--radiation equivalence may correspond to a \emph{cosmographic bound} since it strongly depends on

Lorenzo Poli, Giacomo Oliveri, Nicola Anselmi, Arianna Benoni

The synthesis of thinned isophoric arrays (TIAs) radiating mask-constrained patterns is addressed. By leveraging on the recently-introduced formulation of the design of antenna arrays in the autocorrelation-domain (AD), the TIA synthesis is recast as the matching of a target autocorrelation function derived from the user-defined guidelines and objectives. By

Xilei Zhu, Huiyu Duan, Liu Yang, Yucheng Zhu

With the rapid development of eXtended Reality (XR), egocentric spatial shooting and display technologies have further enhanced immersion and engagement for users, delivering more captivating and interactive experiences. Assessing the quality of experience (QoE) of egocentric spatial videos is crucial to ensure a high-quality viewing experience. However, the

Ohad Rahamim, Ori Malca, Dvir Samuel, Gal Chechik

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide control over the appearance of generated content, including the ability to animate 3D objects. However, their ability to

Vitaly V. Chaban, Nadezhda Andreeva

Capacitor self-healing is a generalized term to describe physical and chemical processes restoring the functionalities of a dielectric capacitor after an electrical breakdown. The efficacy of self-healing depends on the elemental composition of a metalized-film capacitor. We report atomistic simulations of self-healing from a chemical perspective proving the

Thomas Gaertner, Christoph Lippert, Stefan Konigorski

In response to the growing demand for accurate demand forecasts, this research proposes a generalized automated sales forecasting pipeline tailored for small- to medium-sized enterprises (SMEs). Unlike large corporations with dedicated data scientists for sales forecasting, SMEs often lack such resources. To address this, we developed a comprehensive forecas

David Eppstein, Joel Brewster Lewis, Russ Woodroofe, XOR'easter

Over the past 20 years, Wikipedia has gone from a rather outlandish idea to a major reference work, with more than 60 million articles across all languages, including nearly 7 million in English [Wiki01]. Around 27,000 of these articles concern mathematics [b], and Wikipedia is the first place that many of us go to learn about a new mathematical idea. In thi

Yash Agrawal, Srinidhi Balasubramanian, Rahul Meena, Rohail Alam

This research paper delves into the development of an Optical Character Recognition (OCR) system for the recognition of Ashokan Brahmi characters using Convolutional Neural Networks. It utilizes a comprehensive dataset of character images to train the models, along with data augmentation techniques to optimize the training process. Furthermore, the paper inc

Shiyun Chen, Li Lin, Pujin Cheng, ZhiCheng Jin

Multimodal learning has been demonstrated to enhance performance across various clinical tasks, owing to the diverse perspectives offered by different modalities of data. However, existing multimodal segmentation methods rely on well-registered multimodal data, which is unrealistic for real-world clinical images, particularly for indistinct and diffuse regio

Yida Wang, Guojie Hu, Xiaoling Hu, Xingbo Lu

In this paper, we construct a framework of the movable antenna (MA) aided covert communication shielded by the general noise uncertainty for the first time. According to the analysis performance on the derived closed-form expressions of the sum of the probabilities of the detection errors and the communication outage probability, the perfect covertness and t

Xinyu Jia, Weinan Hou, Costas Papadimitriou

Quantifying uncertainty and updating reliability are essential for ensuring the safety and performance of engineering systems. This study develops a hierarchical Bayesian modeling (HBM) framework to quantify uncertainty and update reliability using data. By leveraging the probabilistic structure of HBM, the approach provides a robust solution for integrating

Jiazheng Dou, Jiakang Han, Wen Zhao, Bin Hu

The ground-based cosmic microwave background (CMB) experiments are susceptible to various instrumental errors, especially for $B$-mode measurements. The difference between the response of two polarized detectors, referred to as the beam mismatch, would induce a $T\rightarrow P$ leakage when the detector pair is differenced to cancel the unpolarized signal. W

Kalin Kopanov

The integration of advanced Natural Language Processing (NLP) methodologies and Large Language Models (LLMs) has significantly enhanced the extraction and analysis of geospatial data from multilingual texts, impacting sectors such as national and international security. This paper presents a comprehensive evaluation of leading NLP models -- SpaCy, XLM-RoBERT

Daiheng Gao, Shilin Lu, Shaw Walters, Wenbo Zhou

Removing unwanted concepts from large-scale text-to-image (T2I) diffusion models while maintaining their overall generative quality remains an open challenge. This difficulty is especially pronounced in emerging paradigms, such as Stable Diffusion (SD) v3 and Flux, which incorporate flow matching and transformer-based architectures. These advancements limit

Zibin Pan, Shuwen Zhang, Yuesheng Zheng, Chi Li

Machine unlearning in the domain of large language models (LLMs) has attracted great attention recently, which aims to effectively eliminate undesirable behaviors from LLMs without full retraining from scratch. In this paper, we explore the Gradient Ascent (GA) approach in LLM unlearning, which is a proactive way to decrease the prediction probability of the

Guangming Che

The financial industry is increasingly seeking robust methods to address the challenges posed by data scarcity and low signal-to-noise ratios, which limit the application of deep learning techniques in stock market analysis. This paper presents two innovative generative model-based approaches to synthesize stock data, specifically tailored for different scen

Yan Peng, Yuebing Zhou, Jiawei Hu, Hongwei Yu

We investigate the transition rates of a centripetally accelerated atom inside a high-quality cavity and show that they can be extensively tuned by adjusting the cavity resonance and the rotation frequency. Crucially, while inertial atoms cannot be excited in vacuum, rotation induces spontaneous excitation via the circular Unruh effect, with the cavity servi

Vincenzo Morinelli

In this paper we give a streamlined overview of some of the recent constructions provided with K.-H. Neeb, G. \'Olafsson and collaborators for a new geometric approach to Algebraic Quantum Field Theory (AQFT). Motivations, fundamental concepts and some of the relevant results about the abstract structure of these models are here presented.

Andreas Mueller

Near kinematic singularities of a serial manipulator, the inverse kinematics (IK) problem becomes ill-conditioned, which poses computational problems for the numerical solution. Computational methods to tackle this issue are based on various forms of a pseudoinverse (PI) solution to the velocity IK problem. The damped least squares (DLS) method provides a ro

Andrey Piatnitski, Vladimir Sloushch, Tatiana Suslina, Elena Zhizhina

The paper deals with homogenization of self-adjoint operators in $L_2(\mathbb R^d)$ of the form $$ ({\mathbb A}_\eps u) (\x) = \int_{\R^d} \mu(\x/\eps, \y/\eps) \frac{\left( u(\x) - u(\y) \right)}{|\x - \y|^{d+\alpha}}\,d\y, $$ where $0< \alpha < 2$, and $\eps>0$ is a small parameter. It is assumed that the function $\mu(\x,\y)$ is $\Z^d$-periodic in each va

Amelia Carolina Sparavigna

Recently, arXiv published a work by G. Magli about the eclipse of 1 April 2471 BC and a supposed influence of it on the end of the fourth Egyptian dynasty and the beginning of the fifth one. In Magli's arXiv/2412.13640 paper, the eclipse is defined as the 'Shepseskaf eclipse'. Magli considers that this eclipse happened during the reign of the 'last ruler of

Velizar Varbanov, Kalin Kopanov, Tatiana Atanasova

This paper presents a multidisciplinary approach to analyzing data from Telegram for early warning information regarding cyber threats. With the proliferation of hacktivist groups utilizing Telegram to disseminate information regarding future cyberattacks or to boast about successful ones, the need for effective data analysis methods is paramount. The primar

Ivan Kurniawan, Keita Ito, Takeshi Seki, Keisuke Masuda

Although the relationship between magnetostriction and magnetic damping is often described phenomenologically, their intrinsic connection remains unclear. In this study, we demonstrate that the magnitude of magnetic damping depends on the sign of magnetostriction in ($\mathrm{Fe_{1-x}Co_{x})_{4}N}$ and $\mathrm{Ni_{1-y}Co_{y}}$ alloys across various composit

Zangwei Zheng, Xiangyu Peng, Tianji Yang, Chenhui Shen

Vision and language are the two foundational senses for humans, and they build up our cognitive ability and intelligence. While significant breakthroughs have been made in AI language ability, artificial visual intelligence, especially the ability to generate and simulate the world we see, is far lagging behind. To facilitate the development and accessibilit

Ahmad Bagheri, Mohammadhossein Aghaazizi, Ali Doustmohammadi

It is well established that resource failure, including robots and machines, in a manufacturing system can result in deadlocks. This issue not only hampers the system's performance but can also inflict significant damage on the manufacturing process. In this paper, we present a new algorithm developed through modeling of a manufacturing system using Petri ne

Yohei Fujishima, Toru Kan

For superlinear heat equations with the Dirichlet boundary condition, the $L^\infty$ estimates of radially symmetric solutions are studied. In particular, the uniform boundedness of global solutions and the non-existence of solutions with type II blow-up are proved. For the space dimension greater than $9$, our results are shown under the condition that an e

Tristan Bice, Maciej Malicki

We construct homeomorphisms of compacta from relations between finite graphs representing their open covers. Applied to the pseudoarc, this yields simple Fra\"iss\'e theoretic proofs of several important results, both old and new. Specifically, we recover Bing's classic results on the uniqueness and homogeneity of the pseudoarc. We also show that the autohom

S. O. Zakariyya, B. O. Sadiq, R. A. Alao, J. A. Adesina

The design of an improved microstrip antenna operating in the 28 GHz frequency spectrum is the main goal of this work. The design used a Roger RT 5880 LZ substrate with a thickness and permittivity of 0.762mm and 1.96, respectively. The antenna was simulated in CST Microwave Studio. As the antenna feed, a quarter-wave transformer was used to provide an imped

Natsumi Ikeno, Wen-Hao Jia, Wei-Hong Liang, Eulogio Oset

We study the $D^0 \to \rho^0 \phi$, $\omega \phi$ decays which proceed in a direct mode via internal emission with equal rates. Yet, the experimental branching ratio for the $\rho^0 \phi$ mode is twice as big as that for the $\omega \phi$ mode. We find a natural explanation based on the extra indirect mechanism where $K^{*+} K^{*-}$ is produced via external

Masazumi Honda, Hiroki Matsui, Kota Numajiri, Kazumasa Okabayashi

We directly evaluate the probability amplitudes in Jackiw-Teitelboim (JT) gravity using the Lorentzian path integral formulation. By imposing boundary conditions on the scale factor and the dilaton field, the Lorentzian path integral uniquely yields the probability amplitude without contradiction. Under Dirichlet boundary conditions, we demonstrate that the

Lucas C. D. Bezerra, Ataíde M. G. dos Santos, Shinkyu Park

We propose a decentralized, learning-based framework for dynamic coalition formation in Multi-Robot Task Allocation (MRTA). Our approach extends MAPPO by integrating spatial action maps, robot motion planning, intention sharing, and task allocation revision to enable effective and adaptive coalition formation. Extensive simulation studies confirm the effecti

Ghader Najarbashi, Hassan Bahmani, Babak Tarighi

We investigate thermal and nonthermal quantum correlations in the one dimensional spin 1 bilinear-biquadratic Heisenberg model. Using tools from quantum information theory such as generalized concurrence, negativity, and various measures of quantum, classical, and total correlations in bipartite states we demonstrate that these measures effectively identify

Yuki Oyama, Takashi Akamatsu

Crowdsourced delivery (CSD) is an emerging business model that leverages the underutilized or excess capacity of individual drivers to fulfill delivery tasks. This paper presents a general formulation of a larege-scale two-sided CSD matching problem, considering demand/supply elasticity, heterogeneous preferences of both shippers and drivers, and task-bundli

Yingzhi Chen, Kunpeng Tang, Wendi Zhang, Huiju Cao

Carbyne, a sp1-hybridized allotrope of carbon, is a linear carbon chain with exceptional theoretically predicted properties that surpass those of sp2-hybridized graphene and carbon nanotubes (CNTs). However, the existence of carbyne has been debated due to its instability caused by Peierls distortion, which limits its practical development. The only successf

Amit Sarkar

A new architecture of CNN hardware accelerator is presented. Convolutional Neural Networks (CNNs) are a subclass of neural networks that have demonstrated outstanding performance in a variety of computer vision applications, including object detection, image classification, and many more.Convolution, a mathematical operation that consists of multiplying, shi

Zhifang Zhang, Shuo He, Haobo Wang, Bingquan Shen

Multimodal contrastive learning models (e.g., CLIP) can learn high-quality representations from large-scale image-text datasets, while they exhibit significant vulnerabilities to backdoor attacks, raising serious safety concerns. In this paper, we reveal that CLIP's vulnerabilities primarily stem from its tendency to encode features beyond in-dataset predict

Francesco Conti, Angelo Garofalo, Davide Rossi, Giuseppe Tagliavini

Since 2013, the PULP (Parallel Ultra-Low Power) Platform project has been one of the most active and successful initiatives in designing research IPs and releasing them as open-source. Its portfolio now ranges from processor cores to network-on-chips, peripherals, SoC templates, and full hardware accelerators. In this article, we focus on the PULP experience

Hyunho Ha, Inseung Hwang, Nestor Monzon, Jaemin Cho

Acquisition and modeling of polarized light reflection and scattering help reveal the shape, structure, and physical characteristics of an object, which is increasingly important in computer graphics. However, current polarimetric acquisition systems are limited to static and opaque objects. Human faces, on the other hand, present a particularly difficult ch

Chunpu Liu, Guanglei Yang, Wangmeng Zuo, Tianyi Zan

Deep metric learning aims to learn features relying on the consistency or divergence of class labels. However, in monocular depth estimation, the absence of a natural definition of class poses challenges in the leveraging of deep metric learning. Addressing this gap, this paper introduces MetricDepth, a novel method that integrates deep metric learning to en

Miles Angelo Sodejana

We provided comments on the article Orbits of particles with magnetic dipole moment around magnetized Schwarzschild black holes: Applications to S2 star orbit by Uktamjon Uktamov, Mohsen Fathi, Javlon Rayimbaev, and Ahmadjon Abdujabbarov from arXiv:2406.03371v2. We derived the Hamilton-Jacobi equation used in the article from the Lagrangian utilized and foun

Jindong Guo, Paul Norbury, Di Yang, Don Zagier

In this paper, we study combinatorial and asymptotic properties of some interesting rational numbers called the Br\'ezin--Gross--Witten (BGW) numbers, which can be represented as the intersection numbers of psi and Theta classes on the moduli space of stable algebraic curves. In particular, we discover and prove the uniform large genus leading asymptotics of

Toshiyuki Kobayashi

This article is a record of the lecture at the centennial conference for Harish-Chandra. The admissibility theorem of Harish-Chandra concerns the restrictions of irreducible representations to maximal compact subgroups. In this article, we begin with a brief explanation of two directions for generalizing his pioneering work to {\it{non-compact}} reductive su

Younghyun Cho, Changhun Lee, Seonggon Kim, Eunhyeok Park

Visual Mamba is an approach that extends the selective space state model, Mamba, to vision tasks. It processes image tokens sequentially in a fixed order, accumulating information to generate outputs. Despite its growing popularity for delivering high-quality outputs at a low computational cost across various tasks, Visual Mamba is highly susceptible to quan

Qiang Du, Kaizheng Wang, Edith Zhang, Chenyang Zhong

Variational inference is a fast and scalable alternative to Markov chain Monte Carlo and has been widely applied to posterior inference tasks in statistics and machine learning. A traditional approach for implementing mean-field variational inference (MFVI) is coordinate ascent variational inference (CAVI), which relies crucially on parametric assumptions on

Vitaly V. Chaban, Nadezhda A. Andreeva

Electrical breakdown in a dielectric capacitor occurs when the electric field strength across the dielectric material exceeds its breakdown strength. A conductive channel through the dielectric emerges, resulting in a sudden surge of current. Self-healing represents a phenomenon of restoration of a capacitor's performance. The efficiency of self-healing depe

Li-Jun Zhao, Si-Yuan Zhang, Zhen-Duo Chen, Xin Luo

Current fine-grained classification research primarily focuses on fine-grained feature learning. However, in real-world scenarios, fine-grained data annotation is challenging, and the features and semantics are highly diverse and frequently changing. These issues create inherent barriers between traditional experimental settings and real-world applications,

Shinyoung Yi, Donggun Kim, Jiwoong Na, Xin Tong

The objective of polarization rendering is to simulate the interaction of light with materials exhibiting polarization-dependent behavior. However, integrating polarization into rendering is challenging and increases computational costs significantly. The primary difficulty lies in efficiently modeling and computing the complex reflection phenomena associate

Jia Liu, Yue Wang, Zhiqi Lin, Min Chen

Large language model fine-tuning techniques typically depend on extensive labeled data, external guidance, and feedback, such as human alignment, scalar rewards, and demonstration. However, in practical application, the scarcity of specific knowledge poses unprecedented challenges to existing fine-tuning techniques. In this paper, focusing on fine-tuning tas

Jia Wei Sii, Chee Seng Chan

Makeup is no longer confined to physical application; people now use mobile apps to digitally apply makeup to their photos, which they then share on social media. However, while this shift has made makeup more accessible, designing diverse makeup styles tailored to individual faces remains a challenge. This challenge currently must still be done manually by

Zihao Wang, Hao Tang

Quantum Error Correction (QEC) is the process of detecting and correcting errors in quantum systems, which are prone to decoherence and quantum noise. QEC is crucial for developing stable and highly accurate quantum computing systems, therefore, several research efforts have been made to develop the best QEC strategy. Recently, Google's breakthrough shows gr

Prachi Sharma

A compact Halbach array magnet is used to measure the momentum of the secondary particles in EMPHATIC (Experiment to Measure the Production of Hadrons At a Test beam In Chicagoland). Hall probe data was taken for the central cylindrical bore of the magnet and a field map was constructed. COMSOL Multiphysics Software is used for modeling the magnet and constr