November 2024 arXiv papers — page 82

Yaser Darwesh, Lit Wei Wern, Mumtaz Begum Mustafa

Many of the existing TTS systems cannot accurately synthesize text containing a variety of numerical formats, resulting in reduced intelligibility of the synthesized speech. This research aims to develop a numerical format classifier that can classify six types of numeric contexts. Experiments were carried out using the proposed context-based feature extract

Heiko Dietrich, Melissa Lee, Anthony Pisani, Tomasz Popiel

Seysen's Python package mmgroup provides functionality for fast computations within the sporadic simple group $\mathbb{M}$, the Monster. The aim of this work is to present an mmgroup database of maximal subgroups of $\mathbb{M}$: for each conjugacy class $C$ of maximal subgroups in $\mathbb{M}$, we construct explicit group elements in mmgroup and prove that

Yutong Gou, Jianyang Gao, Yuexuan Xu, Cheng Long

Approximate nearest neighbor (ANN) search in high-dimensional Euclidean space has a broad range of applications. Among existing ANN algorithms, graph-based methods have shown superior performance in terms of the time-accuracy trade-off. However, they face performance bottlenecks due to the random memory accesses caused by the searching process on the graph i

Biao Dong, Bin Cao, Guan Gui, Qinyu Zhang

This work is concerned with robust distributed multi-view image transmission over a severe fading channel with imperfect channel state information (CSI), wherein the sources are slightly correlated. Since the signals are further distorted at the decoder, traditional distributed deep joint source-channel coding (DJSCC) suffers considerable performance degrada

Nathan A. Giauque, Callum E. Flowerday, Steven R. Goates

Often only small amounts of sample are available for spectroscopic analytical determinations. This work investigates the enhancement of signal in columns packed with silica particles. We propose that silica particles cause the light to scatter through the column, effectively increasing optical path length. Packed columns are shown to be effective with fluore

Paula Pereira, Jácome Cunha, João P. Fernandes

Data collection is pervasively bound to our digital lifestyle. A recent study by the IDC reports that the growth of the data created and replicated in 2020 was even higher than in the previous years due to pandemic-related confinements to an astonishing global amount of 64.2 zettabytes of data. While not all the produced data is meant to be analyzed, there a

Baoming Shi, Apala Majumdar, Lei Zhang

The phenomenological Landau-de Gennes (LdG) model is a powerful continuum theory to describe the macroscopic state of nematic liquid crystals. However, it is invariably less accurate and less physically informed than the molecular-level models due to the lack of physical meaning of the parameters. We propose a neural network-based tensor (NN-Tensor) model fo

Hamoud Alhazmi, Ahmed Imran, Mohammad Abu Alsheikh

Perception of privacy is a contested concept, which is also evolving along with the rapid proliferation and expansion of technological advancements. Information systems (IS) applications incorporate various sensing infrastructures, high-speed networks, and computing components that enable pervasive data collection about people. Any digital privacy breach wit

Mingsen Du, Meng Chen, Yongjian Li, Xiuxin Zhang

Multivariate time series (MTS) data is generated through multiple sensors across various domains such as engineering application, health monitoring, and the internet of things, characterized by its temporal changes and high dimensional characteristics. Over the past few years, many studies have explored the long-range dependencies and similarities in MTS. Ho

Niaz Mahmud Zafri, Ming Zhang

This study investigates the dynamic relationship between the built environment and travel in Austin, Texas, over a 20-year period. Using three waves of household travel surveys from 1997, 2006, and 2017, the research employs a repeated cross-sectional approach to address the limitations of traditional longitudinal and cross-sectional studies. Methodologicall

Cheol-Hwan Park

We develop the theory of the non-adiabatic phonon self-energy arising from coupling to electrons with finite linewidths using the spectral representation of Green's functions. Our formalism naturally includes the contribution from the intra-band electronic transitions (as well as the inter-band ones) at all electron wavevectors to the phonon linewidths, whic

Kichang Lee, Yujin Shin, Jonghyuk Yun, Songkuk Kim

Federated Learning (FL) enables collaborative model training across distributed devices while preserving local data privacy, making it ideal for mobile and embedded systems. However, the decentralized nature of FL also opens vulnerabilities to model poisoning attacks, particularly backdoor attacks, where adversaries implant trigger patterns to manipulate mod

Mengzhu Shi, Kaibao Fan, Houpu Li, Senyang Pan

Properties of layered superconductors can vary drastically when thinned down from bulk to monolayer, owing to the reduced dimensionality and weakened interlayer coupling. In transition metal dichalcogenides (TMDs), the inherent symmetry breaking effect in atomically thin crystals prompts novel states of matter, such as Ising superconductivity with an extraor

Chuan Sun, Si-Bin Lu, Min Jiang, Zhan-Wei Yao

Operating atom-interferometer gyroscopes outside a laboratory environment is challenging primarily owing to the instability of laser systems. To enhance the thermal stability of free-space laser systems, a compact laser system using fiber lasers and all-quartz-jointed optical modules was developed for a dual-atom-interferometer gyroscope. Millimeter-scale op

Jiongjie Wang, Jiang Xiao

We explore a system comprising two oscillators that are coupled to an open channel at distinct locations. The coupling nature can be adjusted to be coherent, dissipative, or a combination of both, controlled by a tunable phase resulting from wave propagation between the oscillators. This setup allows us to observe characteristic energy level behaviors: level

Belle Collaboration, R. Seidl, I. Adachi, H. Aihara

We report measurements of production cross sections for $\rho^+$, $\rho^0$, $\omega$, $K^{*+}$, $K^{*0}$, $\phi$, $\eta$, $K_S^0$, $f_0(980)$, $D^+$, $D^0$, $D_s^+$, $D^{*+}$, $D^{*0}$, and $D^{*+}_s$ in $e^+e^-$ collisions at a center-of-mass energy near 10.58 GeV. The data were recorded by the Belle experiment, consisting of 571 fb$^{-1}$ at 10.58 GeV and

Joseph D. Carpinelli

Students and professionals in astronomy, astrodynamics, astrophysics, and other related fields often download and parse data about objects in our solar system -- ephemeris data -- from two major providers: JPL's publicly-available [Generic SPICE Kernels](https://naif.jpl.nasa.gov/pub/naif/generic_kernels/) and JPL's [Horizons platform](https://ssd.jpl.nasa.g

Shuanping Du, Zhaofang Bai

Complex numbers are widely used in quantum physics and are indispensable components for describing quantum systems and their dynamical behavior. The resource theory of imaginarity has been built recently, enabling a systematic research of complex numbers in quantum information theory. In this work, we develop two theoretical methods for quantifying imaginari

Ghassem Jaberipur, Bardia Nadimi, R. Kazemi, Jeong-A Lee

Modulo-$(2^q + 2^{q-1} \pm 1)$ adders have recently been implemented using the regular parallel prefix (RPP) architecture, matching the speed of the widely used modulo-$(2^q \pm 1)$ RPP adders. Consequently, we introduce a new moduli set $\tau^+ = \{2^{2q+1}, 2^q + 2^{q-1} \pm 1\}$, with over $(2^{q+2}) \times$ dynamic range and adder speeds comparable to th

Wenxiao Xue, Zichen Hua, Yu Rong

Utilizing ALFALFA HI data, we investigate the relationship between specific star formation rate (sSFR) and halo spin across various star-forming galaxies. Our analysis reveals weak yet statistically significant positive correlation between sSFR and halo spin, irrespective of the galactic environment. This trend suggests that galaxies with higher spin paramet

Zichen Hua, Yu Rong, Huijie Hu

Leveraging the semi-analytic method, we compute halo spins for a substantial sample of HI-bearing galaxies observed in the Arecibo Legacy Fast Alfa Survey. Our statistical analysis reveals a correlation between halo spin and environment, although the trend is subtle. On average, galaxies exhibit a decreasing halo spin tendency in denser environments. This ob

Yu Rong, Zichen Hua, Huijie Hu

We estimate halo spins for HI-rich galaxies in the Arecibo Legacy Fast Alfa Survey using a semi-analytic approach, examining the relationship between halo spin and stellar surface density. Our findings reveal an inverse correlation in both low- and high-mass galaxy samples, with stellar surface density decreasing as halo spin increases. This trend highlights

Iroro Orife

In genres like Hip-Hop, RnB, Reggae, Dancehall and just about every Electronic/Dance/Club style, DJ tools are a special set of audio files curated to heighten the DJ's musical performance and creative mixing choices. In this work we demonstrate an approach to discovering DJ tools in personal music collections. Leveraging open-source libraries for speech/musi

Wanchen Zhang, Yu Ning, Fei Shi, Xiande Zhang

A pure multipartite quantum state is called absolutely maximally entangled if all reductions of no more than half of the parties are maximally mixed. However, an $n$-qubit absolutely maximally entangled state only exists when $n$ equals $2$, $3$, $5$, and $6$. A natural question arises when it does not exist: which $n$-qubit pure state has the largest number

Srikrishna S Kashyap

I present CMBAnalysis, a state-of-the-art Python framework designed for high-precision analysis of Cosmic Microwave Background (CMB) radiation data. This comprehensive package implements parallel Markov Chain Monte Carlo (MCMC) techniques for robust cosmological parameter estimation, featuring adaptive integration methods and sophisticated error propagation.

Sriram S. K. S Narayanan, Joseph Moyalan, Umesh Vaidya

This work presents a density-based framework for safe navigation in dynamic environments characterized by time-varying obstacle sets and time-varying target regions. We propose an analytical construction of time-varying density functions that enables the synthesis of a feedback controller defined as the positive gradient of the resulting density field. The p

Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao

Recommender systems often rely on large embedding tables that map users and items to dense vectors of uniform size, leading to substantial memory consumption and inefficiencies. This is particularly problematic in memory-constrained environments like mobile and Web of Things (WoT) applications, where scalability and real-time performance are critical. Variou

Lingxiao Hao, Shenglin Zhu

Aguiar and Mahajan provided several coalgebra axioms and algebra axioms for a family of left-regular bands to construct a commutative diagram of algebras and coalgebras. In this paper, we will add compatibility axioms to make it a diagram of Hopf algebras.

Jose A. Magpantay

In two previous papers, the author raised the possibility of a special relativistic Liouville equation. The conclusion then was yes, such an equation is possible in 8N phase space if a Lorentz-invariant Universal (LiU) time can be defined for all the degrees of freedom. Without this LiU time, the existence of a special relativistic Liouville equation is empt

Hokuto Konno, Jianfeng Lin, Anubhav Mukherjee, Juan Muñoz-Echániz

We prove that the monodromy diffeomorphism of a complex 2-dimensional isolated hypersurface singularity of weighted-homogeneous type has infinite order in the smooth mapping class group of the Milnor fiber, provided the singularity is not a rational double point. This is a consequence of our main result: the boundary Dehn twist diffeomorphism of an indefinit

Tonmoy Hossain, Jing Ma, Jundong Li, Miaomiao Zhang

Geometric shape features have been widely used as strong predictors for image classification. Nevertheless, most existing classifiers such as deep neural networks (DNNs) directly leverage the statistical correlations between these shape features and target variables. However, these correlations can often be spurious and unstable across different environments

Zhirong Xin, Junpeng Cao, Wen-Li Yang, Yupeng Wang

The thermodynamic limits of the XYZ spin chain with periodic or twisted boundary conditions are studied. By using the technique of characterizing the eigenvalue of the transfer matrix by the $T-Q$ relation and by the zeros of the associated polynomial, we obtain the constraints of the Bethe roots and the zeros for the eigenvalues. With the help of structure

Tae-Min Choi, Juyoun Park

Surgical instrument segmentation is an essential component of computer-assisted and robotic surgery systems. Vision-based segmentation models typically produce outputs limited to a predefined set of instrument categories, which restricts their applicability in interactive systems and robotic task automation. Promptable segmentation methods allow selective pr

Yifan Xie, Jingge Wang, Tao Feng, Fei Ma

Colonoscopy is crucial for identifying adenomatous polyps and preventing colorectal cancer. However, developing robust models for polyp detection is challenging by the limited size and accessibility of existing colonoscopy datasets. While previous efforts have attempted to synthesize colonoscopy images, current methods suffer from instability and insufficien

Yu Liu, Ruowei Wang, Jiaqi Li, Zixiang Xu

Reconstructing 3D models from single-view images is a long-standing problem in computer vision. The latest advances for single-image 3D reconstruction extract a textual description from the input image and further utilize it to synthesize 3D models. However, existing methods focus on capturing a single key attribute of the image (e.g., object type, artistic

Zixin Liu, Ji Zhang, Yiran Ding

Group polarization is an important research direction in social media content analysis, attracting many researchers to explore this field. Therefore, how to effectively measure group polarization has become a critical topic. Measuring group polarization on social media presents several challenges that have not yet been addressed by existing solutions. First,

Qi Chen, Ruoshan Zhao, Sinuo Wang, Vu Minh Hieu Phan

Medical vision-and-language models (MVLMs) have attracted substantial interest due to their capability to offer a natural language interface for interpreting complex medical data. Their applications are versatile and have the potential to improve diagnostic accuracy and decision-making for individual patients while also contributing to enhanced public health

Jacob D. Carducci, Jeremy D. Brown

Manipulating an environment remotely with a robotic teleoperator introduces novel electromechanical (EM) dynamics between the user and environment. While considerable effort has focused on minimizing these dynamics, there is limited research into understanding their impact on a user's internal model and resulting motor control strategy. Here we investigate t

Yuhui Guo, Jian Song, Ran Wang, Yimin Xiao

We consider the following stochastic space-time fractional diffusion equation with vanishing initial condition:$$ \partial^{\beta} u(t, x)=- \left(-\Delta\right)^{\alpha / 2} u(t, x)+ I_{0+}^{\gamma}\left[\dot{W}(t, x)\right],\quad t\in[0,T],\: x \in \mathbb{R}^d,$$ where $\alpha>0$, $\beta\in(0,2)$, $\gamma\in[0,1)$, $\left(-\Delta\right)^{\alpha/2}$ is the

Leo Matsuoka, Hiromichi Ohno, Etsuo Segawa

We provide a mathematical framework for identifying the shortest path in a maze using a Grover walk, which becomes non-unitary by introducing absorbing holes. In this study, we define the maze as a network with vertices connected by unweighted edges. Our analysis of the stationary state of the Grover walk on finite graphs, where we strategically place absorb

Sven Bjarke Gudnason, Stefano Bolognesi, Roberto Menta

We propose a generalization of the theory of magnetic Skyrmions in chiral magnets in two dimensions to a higher-dimensional theory with magnetic Skyrmions in three dimensions and an $S^3$ target space, requiring a 4-dimensional magnetization vector. A physical realization of our theory could be made using a synthetic dimension, recently promoted and realized

Zenghu Li, Run Zhang

We give characterizations of the transition semigroup and generator of a continuous-time Derrida--Retaux type process that generalizes the one introduced by Hu, Mallein and Pain (Commun. Math. Phys., 2020). It is shown that the process arises naturally as the scaling limit of the discrete-time max-type recursive models introduced by Hu and Shi (J. Stat. Phys

Shuntaro Okada, Kenji Doi, Ryota Yoshihashi, Hirokatsu Kataoka

We propose a general framework for optimizing noise schedules in diffusion models, applicable to both training and sampling. Our method enforces a constant rate of change in the probability distribution of diffused data throughout the diffusion process, where the rate of change is quantified using a user-defined discrepancy measure. We introduce three such m

Sang-Ho Kim, T. -S. H. Lee, R. B. Wiringa

Motivated by the recent experimental developments, the Pom-CQM model of the $\gamma + N \to J/\psi + N$ reaction of Lee et al. [Eur. Phys. J. A. 58, 252 (2022)] and Sakinah et al. [Phys. Rev. C. 109, 065204 (2024)] has been applied to predict the exclusive $J/\psi$ photo-production on nuclei ($A$). Within the multiple scattering theory, the calculations have

Tian Niu, Zijun Xu, Heng Luo, Ziqing Zhou

The estimation of Remaining Useful Life (RUL) plays a pivotal role in intelligent manufacturing systems and Industry 4.0 technologies. While recent advancements have improved RUL prediction, many models still face interpretability and compelling uncertainty modeling challenges. This paper introduces a modified Gaussian Process Regression (GPR) model for RUL

James H. Zhang, Rohith Mittapally, Guangxin Lv, Gang Chen

To explain reported solar interfacial-evaporation rates from porous materials beyond an apparent 100% efficiency using the thermal evaporation mechanism, many publications hypothesize that intermediate water inside porous materials have a reduced latent heat. Key supporting evidence is that water-only surfaces have lower dark evaporation rates than porous ev

Renxiang Xiao, Wei Liu, Yushuai Chen, Liang Hu

We present LiV-GS, a LiDAR-visual SLAM system in outdoor environments that leverages 3D Gaussian as a differentiable spatial representation. Notably, LiV-GS is the first method that directly aligns discrete and sparse LiDAR data with continuous differentiable Gaussian maps in large-scale outdoor scenes, overcoming the limitation of fixed resolution in tradit

Xichen Guo, Zheng Li, Biwei Huang, Yan Zeng

We address the issue of the testability of instrumental variables derived from observational data. Most existing testable implications are centered on scenarios where the treatment is a discrete variable, e.g., instrumental inequality (Pearl, 1995), or where the effect is assumed to be constant, e.g., instrumental variables condition based on the principle o

Siyu Wang, Shengran Dai, Jianhui Jiang, Shuang Wu

Synchrotron radiation sources play a crucial role in fields such as materials science, biology, and chemistry. The beamline, a key subsystem of the synchrotron, modulates and directs the radiation to the sample for analysis. However, the alignment of beamlines is a complex and time-consuming process, primarily carried out manually by experienced engineers. E

Haiping Ma, Aoqing Xia, Changqian Wang, Hai Wang

Computerized Adaptive Testing (CAT) aims to select the most appropriate questions based on the examinee's ability and is widely used in online education. However, existing CAT systems often lack initial understanding of the examinee's ability, requiring random probing questions. This can lead to poorly matched questions, extending the test duration and negat

Mahmut S. Gokmen, Jie Zhang, Ge Wang, Jin Chen

Diffusion models have significant impact on wide range of generative tasks, especially on image inpainting and restoration. Although the improvements on aiming for decreasing number of function evaluations (NFE), the iterative results are still computationally expensive. Consistency models are as a new family of generative models, enable single-step sampling

Chaolin Tian, Yurui Huang, Ching Jin, Yifang Ma

Science prizes purportedly reward innovation and explorations of new phenomena. Yet, in practice prizes may inadvertently divert resources from similarly impactful but less celebrated scholars. Despite this paradox, knowledge of how prizewinning relates to innovation is nascent even as prizes proliferate widely. Analyzing 2,460 worldwide prizes, we compared

Chuan He, Yongchao Liu, Qiang Li, Weiqiang Wang

Sequential recommendation (SR) aims to predict the next purchasing item according to users' dynamic preference learned from their historical user-item interactions. To improve the performance of recommendation, learning dynamic heterogeneous cross-type behavior dependencies is indispensable for recommender system. However, there still exists some challenges

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The $C\!P$ asymmetry and branching fraction of the CKM-suppressed decay $B^+\!\to J\mskip -3mu/\mskip -2mu\psi\,\pi^+$ are precisely measured relative to the favoured decay $B^+\!\to J\mskip -3mu/\mskip -2mu\psi\,K^+$, using a sample of proton-proton collision data corresponding to an integrated luminosity of $5.4~\mathrm{fb}^{-1}$ recorded at center-of-mass

Zhuangwei Zhuang, Ziyin Wang, Sitao Chen, Lizhao Liu

3D semantic occupancy prediction, which seeks to provide accurate and comprehensive representations of environment scenes, is important to autonomous driving systems. For autonomous cars equipped with multi-camera and LiDAR, it is critical to aggregate multi-sensor information into a unified 3D space for accurate and robust predictions. Recent methods are ma

Tatsuhiro Furuta, Shuya Fan, Tadao Takada, Yohei Kondo

We examine quantitatively the transition process from emitting to not-emitting states of fluorescent molecules with a machine learning technique. In a fluorescently labeled DNA, the fluorescence occurs continuously under irradiation, but it often transfers to the not-emitting state corresponding to a charge-separated state. The trajectory of the fluorescence

Zhixiang Wang, Xudong Li, Yizhai Zhang, Fan Zhang

Event cameras, when combined with inertial sensors, show significant potential for motion estimation in challenging scenarios, such as high-speed maneuvers and low-light environments. There are many methods for producing such estimations, but most boil down to a synchronous discrete-time fusion problem. However, the asynchronous nature of event cameras and t

Rahul Garg, Trilok Padhi, Hemang Jain, Ugur Kursuncu

Toxicity identification in online multimodal environments remains a challenging task due to the complexity of contextual connections across modalities (e.g., textual and visual). In this paper, we propose a novel framework that integrates Knowledge Distillation (KD) from Large Visual Language Models (LVLMs) and knowledge infusion to enhance the performance o

Anastassiya Semenova

We study two-crested traveling Stokes waves on the surface of an ideal fluid with infinite depth. Following Chen and Saffman (1980), we refer to these waves as class $\mathrm{II}$ Stokes waves. The class $\mathrm{II}$ waves are found from bifurcations from the primary branch of Stokes waves away from the flat surface. These waves are strongly nonlinear, and

Daiki Suenaga, Makoto Oka

Masses of the singly heavy baryons (SHBs), composed of a heavy quark and a light diquark, are studied from the viewpoints of heavy-quark spin symmetry (HQSS) and chiral-symmetry restoration at finite temperature. We consider the light diquarks with spin-parity $J^P=0^\pm$ and $1^\pm$. Medium corrections to the SHBs are provided through the diquarks whereas t

Fei He, Jianyu Ou

We prove an upper bound for the dimension of the linear space of holomorphic functions with polynomial growth on gradient K\"ahler Ricci shrinkers with bounded curvature. The upper bound is given as a power function of the growth rate. Similar results hold for holomorphic $(p, 0)-$forms, and holomorphic sections of the pluri-anticanonical line bundle $K_M^{-

Jiaqi Dai, Feng Yang, Cong Wang, Fei Pang

In conventional electrides, excess electrons are localized in crystal voids to serve as anions. Most of these electrides are metallic and the metal cations are primarily from the s-block, d-block, or rare-earth elements. Here, we report a class of p-block metal-based electrides found in bilayer SnO and PbO, which are semiconducting and feature electride stat

Shuhan Zheng, Jiamin Liu, Shiqi Zheng, Jiaxing Zhao

Both hot QCD matter and extremely strong electromagnetic fields are generated in relativistic heavy-ion collisions. We employ the transport model and the equivalent photon approximation (EPA) to study charmonium hadroproduction and photoproduction in nucleus-nucleus collisions, respectively. In photoproduction, quasi-real photons may interact with the whole

Tianhao Xie, Noam Aigerman, Eugene Belilovsky, Tiberiu Popa

3D Gaussian Splatting (GS) is one of the most promising novel 3D representations that has received great interest in computer graphics and computer vision. While various systems have introduced editing capabilities for 3D GS, such as those guided by text prompts, fine-grained control over deformation remains an open challenge. In this work, we present a nove

Alexander Felski, Flore K. Kunst

Nonlinearity and non-Hermiticity, for example due to environmental gain-loss processes, are a common occurrence throughout numerous areas of science and lie at the root of many remarkable phenomena. For the latter, parity-time-reflection ($\mathcal{PT}$) symmetry has played an eminent role in understanding exceptional-point structures and phase transitions i

Parmita Mondal, Kyle A Williams, Parisa Naghdi, Ahmad Rahmatpour

In intracranial aneurysm (IA) treatment, digital subtraction angiography (DSA) monitors device-induced hemodynamic changes. Quantitative angiography (QA) provides more precise assessments but is limited by hand-injection variability. This study evaluates correction methods using in vitro phantoms that mimic diverse aneurysm morphologies and locations, addres

Mahmoud A. Hasabelnaby, Mohanad Obeed, Mohammed Saif, Anas Chaaban

Next-generation mobile networks require evolved radio access network (RAN) architectures to meet the demands of high capacity, massive connectivity, reduced costs, and energy efficiency, and to realize communication with ultra-low latency and ultra-high reliability. {Meeting such} requirements for both mobile users and vertical industries in the next decade

Akshara Viswanathan, Danny Horta, Adrian M. Price-Whelan, Else Starkenburg

Observational studies are identifying stars thought to be remnants from the earliest stages of the hierarchical mass assembly of the Milky Way, referred to as the proto-Galaxy. We use red giant stars with kinematics and [$\alpha$/M] and [M/H] estimates from Gaia DR3 data to investigate the relationship between azimuthal velocity and metallicity, aiming to un

Xin Xia, Yajie Zhang, Xiangxiang Zeng, Xingyi Zhang

Molecular optimization, which aims to discover improved molecules from a vast chemical search space, is a critical step in chemical development. Various artificial intelligence technologies have demonstrated high effectiveness and efficiency on molecular optimization tasks. However, few of these technologies focus on balancing property optimization with cons

Yuan Yuan, Chonghua Han, Jingtao Ding, Guozhen Zhang

The urban environment is characterized by complex spatio-temporal dynamics arising from diverse human activities and interactions. Effectively modeling these dynamics is essential for understanding and optimizing urban systems. In this work, we introduce UrbanDiT, a foundation model for open-world urban spatio-temporal learning that successfully scales up di

Pierre Colmez, Sally Gilles, Wiesława Nizioł

We prove that $p$-adic geometric pro-\'etale cohomology of smooth partially proper rigid analytic varieties over $p$-adic fields seen in the category of Topological Vector Spaces satisfies a Poincar\'e duality as we have conjectured. This duality descends, via fully-faithfulness results of Colmez-Nizio{\l}, from a Poincar\'e duality for solid quasi-coherent

Sunil Arora, John Hastings

This paper presents a multi-cloud networking architecture built on zero trust principles and micro-segmentation to provide secure connectivity with authentication, authorization, and encryption in transit. The proposed design includes the multi-cloud network to support a wide range of applications and workload use cases, compute resources including container

Xiaoye Wang, Xuan Li, Linji Wang, Tingyi Ruan

This paper proposes an intelligent cache management strategy based on CNN-LSTM to improve the performance and cache hit rate of storage systems. Through comparative experiments with traditional algorithms (such as LRU and LFU) and other deep learning models (such as RNN, GRU-RNN and LSTM), the results show that the CNN-LSTM model has significant advantages i

Takuya Mieno, Shunsuke Inenaga

A substring $u$ of a string $T$ is said to be a repeat if $u$ occurs at least twice in $T$. An occurrence $[i..j]$ of a repeat $u$ in $T$ is said to be a net occurrence if each of the substrings $aub = T[i-1..j+1]$, $au = T[i-1..j+1]$, and $ub = T[i..j+1]$ occurs exactly once in $T$. The occurrence $[i-1..j+1]$ of $aub$ is said to be an extended net occurren

Benjamin Peters, Ayush Mohanty, Xiaolei Fang, Stephen K. Robinson

Deep-space habitats (DSHs) are safety-critical systems that must operate autonomously for long periods, often beyond the reach of ground-based maintenance or expert intervention. Monitoring system health and anticipating failures are therefore essential. Prognostics based on remaining useful life (RUL) prediction support this goal by estimating how long a su

Sergiu I. Vacaru

Nonassociative modifications of general relativity, GR, and quantum gravity, QG, models naturally arise as star product and R-flux deformations considered in string/ M-theory. Such nonassociative and noncommutative geometric and quantum information theories were formulated on phase spaces defined as cotangent Lorentz bundles enabled with nonassociative symme

Jiajing Chen, Shuo Wang, Zhen Qi, Zhenhong Zhang

This research introduces a novel text generation model that combines BERT's semantic interpretation strengths with GPT-4's generative capabilities, establishing a high standard in generating coherent, contextually accurate language. Through the combined architecture, the model enhances semantic depth and maintains smooth, human-like text flow, overcoming lim

Wenxiao Liu, Zihong Yang, Chaozhuo Li, Zijin Hong

Unsupervised sentence representation learning remains a critical challenge in modern natural language processing (NLP) research. Recently, contrastive learning techniques have achieved significant success in addressing this issue by effectively capturing textual semantics. Many such approaches prioritize the optimization using negative samples. In fields suc

Younggyo Seo, Pieter Abbeel

Predicting a sequence of actions has been crucial in the success of recent behavior cloning algorithms in robotics. Can similar ideas improve reinforcement learning (RL)? We answer affirmatively by observing that incorporating action sequences when predicting ground-truth return-to-go leads to lower validation loss. Motivated by this, we introduce Coarse-to-

Md Ahsanul Kabir, Kareem Abdelfatah, Shushan He, Mohammed Korayem

As recruitment and talent acquisition have become more and more competitive, recruitment firms have become more sophisticated in using machine learning (ML) methodologies for optimizing their day to day activities. But, most of published ML based methodologies in this area have been limited to the tasks like candidate matching, job to skill matching, job cla

Md. Ahsanul Kabir, Mohammad Al Hasan, Aritra Mandal, Daniel Tunkelang

In e-commerce, ranking the search results based on users' preference is the most important task. Commercial e-commerce platforms, such as, Amazon, Alibaba, eBay, Walmart, etc. perform extensive and relentless research to perfect their search result ranking algorithms because the quality of ranking drives a user's decision to purchase or not to purchase an it

Arda Güçlü, Subhonmesh Bose

We propose and analyze TRAiL (Tangential Randomization in Linear Bandits), a computationally efficient regret-optimal forced exploration algorithm for linear bandits on action sets that are sublevel sets of strongly convex functions. TRAiL estimates the governing parameter of the linear bandit problem through a standard regularized least squares and perturbs

Katy Craig, Haoqing Yu

Motivated by classical harmonic analysis results characterizing H\"older spaces in terms of the decay of their wavelet coefficients, we consider wavelet methods for computing s-Wasserstein type distances. Previous work by Sheory (n\'e Shirdhonkar) and Jacobs showed that, for 0 < s <= 1, the s-Wasserstein distance W_s between certain probability measures on E

Guodong Fan, Boru Zhou, Chengwen Meng, Tengwei Pang

This paper develops a comprehensive physics-based model (PBM) that spans a wide operational range, including varying temperatures, charge/discharge conditions, and real-world field data cycles. The PBM incorporates key factors such as hysteresis effects, concentration-dependent diffusivity, and the Arrhenius law to provide a realistic depiction of battery be

Yuyang Xiao

This study aims to optimize the few-shot image classification task and improve the model's feature extraction and classification performance by combining self-supervised learning with the deep network model ResNet-101. During the training process, we first pre-train the model with self-supervision to enable it to learn common feature expressions on a large a

Shuijing Liu, Haochen Xia, Fatemeh Cheraghi Pouria, Kaiwen Hong

We study the problem of robot navigation in dense and interactive crowds with static constraints such as corridors and furniture. Previous methods fail to consider all types of spatial and temporal interactions among agents and obstacles, leading to unsafe and inefficient robot paths. In this article, we leverage a graph-based representation of crowded and c

David Keating, Jiaming Xu

It is well known that the edge limit of Gaussian/Laguerre Beta-ensembles, as well as a large class of $\beta$-ensembles is given by the $\mathrm{Airy}(\beta)$ point process. We extend this universality result to a general class of additions of Gaussian and Laguerre ensembles, which were identified in \cite{AN} as projection of the ergodic measures of the $\b

T. -W. Lee

Scaling of the mean velocity profiles has been studied by many researchers, since it provides a template of universal dynamical patterns across a range of Reynolds numbers. Various normalization schemes have been shown in the past, some with a good degree of success. An alternative, universal scaling is presented, where an integrated velocity serves as a uni

Zhu Liu, Zhen Hu, Ying Liu

We present the results of our system for the CoMeDi Shared Task, which predicts majority votes (Subtask 1) and annotator disagreements (Subtask 2). Our approach combines model ensemble strategies with MLP-based and threshold-based methods trained on pretrained language models. Treating individual models as virtual annotators, we simulate the annotation proce

Sean Wu, Jun Yu Chen, Vahid Mohammadzadeh, Sajad Besharati

Perimetric measurements provide insight into a patient's peripheral vision and day-to-day functioning and are the main outcome measure for identifying progression of visual damage from glaucoma. However, visual field data can be noisy, exhibiting high variance, especially with increasing damage. In this study, we demonstrate the utility of self-supervised de

Qianying Wu, Shigeki Nakauchi, Mohammad Shehata, Shinsuke Shimojo

Traits are patterns of brain signals and behaviors that are stable over time but differ across individuals, whereas states are phasic patterns that vary over time, are influenced by the environment, yet oscillate around the traits. The quality of a social interaction depends on the traits and states of the interacting agents. However, it remains unclear how

Tobias Ekholm

This is an overview paper that describes Eliashberg's Legendrian surgery approach to wrapped Floer cohomology and use it to derive the basic relations between various holomorphic curve theories with additional algebraic constructions. We also give a brief discussion of further results that use the surgery perspective, e.g., for holomorphic curve invariants o

Lucas C. F. Ferreira, Marcos G. Santana

In this work, we obtain the Helmholtz decomposition for vector fields in Morrey, Zorko, and block spaces over bounded or exterior $C^{1}$ domains. Generally speaking, our proofs rely on a careful interplay of localization, flattening, and duality arguments. To accomplish this, we need to extend some classical tools in analysis and PDE theory to those spaces,

John Chen, Alexandros Lotsos, Sihan Cheng, Caiyi Wang

Qualitative analysis is critical to understanding human datasets in many social science disciplines. A central method in this process is inductive coding, where researchers identify and interpret codes directly from the datasets themselves. Yet, this exploratory approach poses challenges for meeting methodological expectations (such as ``depth'' and ``variat

Hai-Jiang Tian, Hai-Bing Fu, Tao Zhong, Ya-Xiong Wang

In the paper, we conduct a detailed investigation of the rare decay processes of charged meson, specifically $B^+ \to K^+\ell^+\ell^-$ with $\ell=(e,\mu,\tau)$ and $B^+ \to K^+\nu\bar{\nu}$. These processes involve flavor-changing-neutral-current (FCNC) transitions, namely $b\to s\ell^+\ell^-$ and $b\to s\nu\bar{\nu}$. The essential components $B\to K$ scala

Engin Başakoğlu, Nikolay Tzvetkov, Chenmin Sun, Yuzhao Wang

We study the Boltzmann equation with the constant collision kernel in the case of spatially periodic domain $\mathbb{T}^d$, $d\geq 2$. Using the existing techniques from nonlinear dispersive PDEs, we prove the local well-posedness result in $L^{2,r}_vH^s_x$ for $s>\frac{d}{2}-\frac{1}{4}$ and $r>\frac{d}{2}$. To reach the result, the main tool we establish i

Miracle Chibuzor Marcel

An updated analysis of pulsar glitch parameters was conducted using a sample of 215 pulsars, encompassing 677 recorded glitch events, each glitch at least once between 1968 and 2024. The glitch rates were estimated and plotted against various pulsar parameters, including rotational frequency, spin-down rate, and characteristic age. These relationships were a

J. M. Pérez-Martínez, H. Dannerbauer, B. H. C. Emonts, J. R. Allison

We obtain CO(1-0) molecular gas measurements with ATCA on a sample of 43 spectroscopically confirmed H$\alpha$ emitters in the Spiderweb protocluster at $z=2.16$ and investigate the relation between their star formation and cold gas reservoirs as a function of environment. We achieve a CO(1-0) detection rate of $\sim23\pm12\%$ with 10 dual CO(1-0) and H$\alp

Mehil B Shah, Mohammad Masudur Rahman, Foutse Khomh

Deep learning (DL) techniques have achieved significant success in various software engineering tasks (e.g., code completion by Copilot). However, DL systems are prone to bugs from many sources, including training data. Existing literature suggests that bugs in training data are highly prevalent, but little research has focused on understanding their impacts

Caleb Geniesse, Jiaqing Chen, Tiankai Xie, Ge Shi

In machine learning, a loss function measures the difference between model predictions and ground-truth (or target) values. For neural network models, visualizing how this loss changes as model parameters are varied can provide insights into the local structure of the so-called loss landscape (e.g., smoothness) as well as global properties of the underlying