April 2024 arXiv papers — page 108

Richard Csaky, Mats W. J. van Es, Oiwi Parker Jones, Mark Woolrich

Foundation models trained with self-supervised objectives are increasingly applied to brain recordings, but autoregressive generation of realistic multichannel neural time series remains comparatively underexplored, particularly for Magnetoencephalography (MEG). We study (i) modified multichannel WaveNet variants and (ii) a GPT-2-style Transformer, autoregre

Manoel Jarra, Oliver Lorscheid, Eduardo Vital

In this paper, we introduce morphisms for matroids with coefficients (in the sense of Baker and Bowler) and quiver matroids. We investigate their basic properties, such as functoriality, duality, minors and cryptomorphic characterizations in terms of vectors, circuits and bases (a.k.a. Grassmann-Pl\"ucker functions). We generalize quiver matroids to quiver m

Wiktor Mucha, Florin Cuconasu, Naome A. Etori, Valia Kalokyri

The ability to read, understand and find important information from written text is a critical skill in our daily lives for our independence, comfort and safety. However, a significant part of our society is affected by partial vision impairment, which leads to discomfort and dependency in daily activities. To address the limitations of this part of society,

Haya Nachimovsky, Moshe Tennenholtz, Fiana Raiber, Oren Kurland

Previous work on the competitive retrieval setting focused on a single-query setting: document authors manipulate their documents so as to improve their future ranking for a given query. We study a competitive setting where authors opt to improve their document's ranking for multiple queries. We use game theoretic analysis to prove that equilibrium does not

Yohei Kawazura, Shigeo S. Kimura

Accretion disks around compact stars are formed due to turbulence driven by magnetorotational instability. Despite over thirty years of numerous computational studies on magnetorotational turbulence, the properties of fluctuations in the inertial range -- where cross-scale energy transfer dominates over energy injection -- have remained elusive, primarily du

Yu Wang, Rahim Moradi, Liang Li

It is generally recognized that the electromagnetic multipolar emission from magnetars can be used to explain radiation from Soft Gamma Repeaters (SGRs) or Anomalous X-ray Pulsars (AXPs), but they have little impact on the spindown of magnetars. We here present a comprehensive analytical solution for the neutron star multipolar electromagnetic fields and the

Jinchen Liu, Kan He, Xingpeng Zhao

In this note, we study a question introduced by Bourin \cite{2009Matrix} and partially solve the question of Bourin. In fact, for t\in[0,\frac{1}{4}]\cup[\frac{3}{4},1], we show that |||x^{t}y^{1-t}+y^{t}x^{1-t}|||\leq|||x+y|||, where x,y\in\mathbb{M}_{n}(\mathbb{C})^+ and \||\cdot\|| is the unitarily invariant norm. Moreover, we prove that the above inequal

Mohamad Nabeel, Doumitrou Daniil Nimara, Tahar Zanouda

In recent years, the evolution of Telecom towards achieving intelligent, autonomous, and open networks has led to an increasingly complex Telecom Software system, supporting various heterogeneous deployment scenarios, with multi-standard and multi-vendor support. As a result, it becomes a challenge for large-scale Telecom software companies to develop and te

Jing-Cheng Pang, Si-Hang Yang, Kaiyuan Li, Jiaji Zhang

Reinforcement learning (RL) trains agents to accomplish complex tasks through environmental interaction data, but its capacity is also limited by the scope of the available data. To obtain a knowledgeable agent, a promising approach is to leverage the knowledge from large language models (LLMs). Despite previous studies combining LLMs with RL, seamless integ

Yifan Yang, Ali Payani, Parinaz Naghizadeh

Generalization error bounds from learning theory provide statistical guarantees on how well an algorithm will perform on previously unseen data. In this paper, we characterize the impacts of data non-IIDness due to censored feedback (a.k.a. selective labeling bias) on such bounds. Censored feedback is ubiquitous in many real-world online selection and classi

Philipp Straubinger, Lena Bloch, Gordon Fraser

Everyone learns to code nowadays. Writing code, however, does not go without testing, which unfortunately rarely seems to be taught explicitly. Testing is often not deemed important enough or is just not perceived as sufficiently exciting. Testing can be exciting: In this paper, we introduce Code Critters, a serious game designed to teach testing concepts en

Haosong Peng, Wei Feng, Hao Li, Yufeng Zhan

The advent of edge computing has made real-time intelligent video analytics feasible. Previous works, based on traditional model architecture (e.g., CNN, RNN, etc.), employ various strategies to filter out non-region-of-interest content to minimize bandwidth and computation consumption but show inferior performance in adverse environments. Recently, visual f

Amir Weiss, Yuval Kochman, Gregory W. Wornell

Motivated by the proliferation of mobile devices, we consider a basic form of the ubiquitous problem of time-delay estimation (TDE), but with communication constraints between two non co-located sensors. In this setting, when joint processing of the received signals is not possible, a compression technique that is tailored to TDE is desirable. For our basic

Alice P. Curtin, Sloane Sirota, Victoria M. Kaspi, Shriharsh P. Tendulkar

We use the Canadian Hydrogen Intensity Mapping Experiment (CHIME) Fast Radio Burst (FRB) Project to search for FRBs that are temporally and spatially coincident with gamma-ray bursts (GRBs) occurring between 2018 July 7 and 2023 August 3. We do not find any temporal (within 1 week) and spatial (within overlapping 3 sigma localization regions) coincidences be

Philipp Straubinger, Alexander Degenhart, Gordon Fraser

Mutation testing consists of evaluating how effective test suites are at detecting artificially seeded defects in the source code, and guiding the improvement of the test suites. Although mutation testing tools are increasingly adopted in practice, equivalent mutants, i.e., mutants that differ only in syntax but not semantics, hamper this process. While prio

Mohamad Nabeel, Doumitrou Daniil Nimara, Tahar Zanouda

In today's hyper-connected world, ensuring the reliability of telecom networks becomes increasingly crucial. Telecom networks encompass numerous underlying and intertwined software and hardware components, each providing different functionalities. To ensure the stability of telecom networks, telecom software, and hardware vendors developed several methods to

Jun Zhang, Li-Hua Zhang, Bang Liu, Zheng-Yuan Zhang

The identification of tipping points is essential for prediction of collapses or other sudden changes in complex systems. Applications include studies of ecology, thermodynamics, climatology, and epidemiology. However, detecting early signs of proximity to a tipping is made challenging by complexity and non-linearity. Strongly interacting Rydberg atom gases

Vadood Adami, Zahra Ebadi, Morteza Nattagh-Najafi

In this paper we introduce a new type of preferential attachment network, the growth of which is based on the eigenvalue centrality. In this network, the agents attach most probably to the nodes with larger eigenvalue centrality which represents that the agent has stronger connections. A new network is presented, namely a dandelion network, which shares some

Hongjun Guo, Kelei Wang

We construct entire solutions of bistable reaction-diffusion equations by mixing finite planar fronts, which form a finite-dimensional manifold. These entire solutions are generalized traveling fronts, that is, transition fronts. We also show their uniqueness and stability. Furthermore, we prove that transition fronts with level sets having finite facets are

Carlos V. G. C. Lima, Thiago Marcilon, Pedro Paulo de Medeiros

The subject of graph convexity is well explored in the literature, the so-called interval convexities above all. In this work, we explore the cycle convexity, an interval convexity whose interval function is $I(S) = S \cup \{u \mid G[S \cup \{u\}]$ has a cycle containing $u\}$. In this convexity, we prove that determine whether the convexity number of a grap

Asunción Fuente, Evelyne Roueff, Franck Le Petit, Jacques Le Bourlot

One of the main problems in astrochemistry is determining the amount of sulfur in volatiles and refractories in the interstellar medium. The detection of the main sulfur reservoirs (icy H$_2$S and atomic gas) has been challenging, and estimates are based on the reliability of models to account for the abundances of species containing less than 1% of the tota

Wageesh Mishra, Preity Sukla Sahani, Soumyaranjan Khuntia, Dibyendu Chakrabarty

Coronal mass ejections (CMEs) and Stream Interaction Regions (SIRs) are the main drivers of intense geomagnetic storms. We study the distribution of geomagnetic storms associated with different drivers during solar cycles 23 and 24 (1996-2019). Although the annual occurrence rate of geomagnetic storms in both cycles tracks the sunspot cycle, the second peak

Achraf Zinihi, Moulay Rchid Sidi Ammi, Matthias Ehrhardt

This paper deals with a new epidemiological model of SIRS with stochastic perturbations. The primary objective is to establish the existence of a unique non-negative nonlocal solution. Using the basic reproduction number $\mathscr{R}_0$ derived from the associated deterministic model, we demonstrate the existence of a stationary distribution in the stochasti

Xin-Chun Li, Shaoming Song, Yinchuan Li, Bingshuai Li

In some real-world applications, data samples are usually distributed on local devices, where federated learning (FL) techniques are proposed to coordinate decentralized clients without directly sharing users' private data. FL commonly follows the parameter server architecture and contains multiple personalization and aggregation procedures. The natural data

Diandian Guo, Manxi Lin, Jialun Pei, He Tang

A comprehensive understanding of surgical scenes allows for monitoring of the surgical process, reducing the occurrence of accidents and enhancing efficiency for medical professionals. Semantic modeling within operating rooms, as a scene graph generation (SGG) task, is challenging since it involves consecutive recognition of subtle surgical actions over prol

Jasper Zevering, Dorit Borrmann, Anton Bredenbeck, Andreas Nuechter

Lunar caves are promising features for long-term and permanent human presence on the moon. However, given their inaccessibility to imaging from survey satellites, the concrete environment within the underground cavities is not well known. Thus, to further the efforts of human presence on the moon, these caves are to be explored by robotic systems. However, a

Alejandro Adem, José Manuel Gómez, Simon Gritschacher

We prove an analogue of Miller's stable splitting of the unitary group $U(m)$ for spaces of commuting elements in $U(m)$. After inverting $m!$, the space $\text{Hom}(\mathbb{Z}^n,U(m))$ splits stably as a wedge of Thom-like spaces of bundles of commuting varieties over certain partial flag manifolds. Using Steenrod operations we prove that our splitting does

Yeseung Kim, Dohyun Kim, Jieun Choi, Jisang Park

In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of LLMs on robotics, addressing key challenges and opportunities for leveraging these models across various domains. By categ

Yueming Zhao, Xuening Yuan, Hongyu Yang, Di Huang

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present DreamScape, a method for generating 3D scenes from text. Utilizing Gaussian Splatting for 3D representation, DreamScape introduc

Weimin Wang, Yufeng Li, Xu Yan, Mingxuan Xiao

To address the issues of limited samples, time-consuming feature design, and low accuracy in detection and classification of breast cancer pathological images, a breast cancer image classification model algorithm combining deep learning and transfer learning is proposed. This algorithm is based on the DenseNet structure of deep neural networks, and construct

Claudio Corianò, Stefano Lionetti, Matteo Maria Maglio, Riccardo Tommasi

Conformal back-reaction generates cosmological models where the trace anomaly reflects the breaking of Weyl invariance. Analyzing these actions yields a dynamic approach to dark energy through anomaly-induced actions (AIAs), that are variational solutions of the trace anomaly functional constraint. Expanded around Minkowski space, they produce semiclassical

Niklas Ludwig

B. A. Barnes introduced so-called Fredholm elements in a semiprime ring whose definition is inspired by Atkinson's theorem. Here the socle of a semiprime ring generalizes the ideal of finite-rank operators on a Banach space. In this paper, we aim to see that the algebraic concept of the length of a module is strongly related to that of Fredholm elements. Thi

Yukako Iimura, Masanari Kondo, Kazushi Tomoto, Yasutaka Kamei

We have selected six myths about the OSS community and have tested whether they are true or not. The purpose of this report is to identify the lessons that can be learned from the development style of the OSS community and the issues that need to be addressed in order to achieve better Employee Experience (EX) in software development within companies and org

Peiwen Yang, Shuguang Li

Origami designs and structures have been widely used in many fields, such as morphing structures, robotics, and metamaterials. However, the design and fabrication of origami structures rely on human experiences and skills, which are both time and labor-consuming. In this paper, we present a rapid design and fabrication method for string-driven origami struct

Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley

Despite the remarkable strides made by autoregressive language models, their potential is often hampered by the slow inference speeds inherent in sequential token generation. Blockwise parallel decoding (BPD) was proposed by Stern et al. as a method to improve inference speed of language models by simultaneously predicting multiple future tokens, termed bloc

Sophia Maria

Large language models have exhibited significant proficiency in languages endowed with extensive linguistic resources, such as English and Chinese. Nevertheless, their effectiveness notably diminishes when applied to languages characterized by limited linguistic resources, particularly within the Southeast Asian linguistic landscape, such as Indonesian. The

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We report the first amplitude analysis of the decays $D^{0} \to \pi^{+} \pi^{-} \eta$ and $D^{+} \rightarrow \pi^{+}\pi^{0}\eta$ using a data sample taken with the BESIII detector at the center-of-mass energy of 3.773 GeV, corresponding to an integrated luminosity of 7.9 ${\rm fb}^{-1}$. The contribution from the process $D^{0(+)} \to a_{0}(980)^{+} \pi^{-(0

Francesco Binucci, Paolo Banelli, Paolo Di Lorenzo, Sergio Barbarossa

The Information Bottleneck (IB) method is an information theoretical framework to design a parsimonious and tunable feature-extraction mechanism, such that the extracted features are maximally relevant to a specific learning or inference task. Despite its theoretical value, the IB is based on a functional optimization problem that admits a closed form soluti

Shen Wang, Wenchuang Guan, Jipeng Cheng

The CKP tau function has been an important topic in mathematical physics. In this paper, the inverse of vacuum expectation value of exponential of certain bosonic fields, is showed to be the CKP tau function given by Chang and Wu, in the language of CKP Darboux transformation. In fact, computation of the above vacuum expectation value is usually quite diffic

Lewei Yao, Renjie Pi, Jianhua Han, Xiaodan Liang

Existing open-vocabulary object detectors typically require a predefined set of categories from users, significantly confining their application scenarios. In this paper, we introduce DetCLIPv3, a high-performing detector that excels not only at both open-vocabulary object detection, but also generating hierarchical labels for detected objects. DetCLIPv3 is

Sai Sanjay Narayanan, Uday K Khankhoje, Radha Krishna Ganti

Ensuring adequate wireless coverage in upcoming communication technologies such as 6G is expected to be challenging. This is because user demands of higher datarate require an increase in carrier frequencies, which in turn reduce the diffraction effects (and hence coverage) in complex multipath environments. Intelligent reflecting surfaces have been proposed

Nick Early, Jian-Rong Li

Finite dimensional simple modules of quantum affine algebras of type A correspond to semistandard Young tableaux of rectangular shapes. In this paper, we classify all prime modules corresponding to 2-column semistandard Young tableaux, up to a conjectural property. Moreover, we give a conjectural sufficient condition for a module corresponding to a tableau w

Man Zhou, Shuao Su, Qian Wang, Qi Li

Fingerprint authentication has been extensively employed in contemporary identity verification systems owing to its rapidity and cost-effectiveness. Due to its widespread use, fingerprint leakage may cause sensitive information theft, enormous economic and personnel losses, and even a potential compromise of national security. As a fingerprint that can coinc

Gerhard Stenzel, Sebastian Zielinski, Michael Kölle, Philipp Altmann

To address the computational complexity associated with state-vector simulation for quantum circuits, we propose a combination of advanced techniques to accelerate circuit execution. Quantum gate matrix caching reduces the overhead of repeated applications of the Kronecker product when applying a gate matrix to the state vector by storing decomposed partial

Zheng Li, Chengyang Lv, Min Tan

This paper presents a high linearity PAM-4 transmitter (TX) architecture, consisting of a three-segment micro-ring modulator (MRM) and a matched CMOS driver. This architecture can drive a high-linearity 4-level pulse amplitude (PAM-4) modulation signal, thereby extending the tunable operating wavelength range for achieving linear PAM-4 output. We use the thr

Fabrizio Berritta, Jan A. Krzywda, Jacob Benestad, Joost van der Heijden

Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strate

Zhong C. F. Li, Yuxuan Deng, Shuai A. Chen, Dmitri K. Efetov

In this work, we consider superconductor/flat band material/superconductor (S/FB/S) Josephson junctions (JJs) where the flat band material possesses isolated flat bands with exactly zero Fermi velocity. Contrary to conventional S/N/S JJs where the critical Josephson current vanishes when the Fermi velocity goes to zero, we show in this work that the critical

Margherita Fadda

As the African continent continues to urbanise, cities are becoming increasingly central to the transformations of societies and economies. Many studies highlight the limits of urban planning in these cities, emphasising the high share of population living in slums and the low levels of services that reach neighbourhoods. Less attention is given to the urban

Changlin Song, Divya Saxena, Jiannong Cao, Yuqing Zhao

Federated Learning (FL) is a novel approach that allows for collaborative machine learning while preserving data privacy by leveraging models trained on decentralized devices. However, FL faces challenges due to non-uniformly distributed (non-iid) data across clients, which impacts model performance and its generalization capabilities. To tackle the non-iid

Marcus Johan Schytt, John Bagterp Jørgensen

This paper considers the optimal boundary control of chemical systems described by advection-diffusion-reaction (ADR) equations. We use a discontinuous Galerkin finite element method (DG-FEM) for the spatial discretization of the governing partial differential equations, and the optimal control problem is directly discretized using multiple shooting. The tem

Hideo Kojima

Let $S$ be a smooth affine surface of logarithmic Kodaira dimension one and let $(V,D)$ be a pair of a smooth projective surface $V$ and a simple normal crossing divisor $D$ on $V$ such that $V \setminus \operatorname{Supp} D = S$. In this paper, we consider the logarithmic multicanonical system $|m(K_V + D)|$. We prove that, for any $m \geq 8$, $|m(K_V+D)|$

Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua

Graph Neural Networks (GNNs) have achieved notable success in various applications over graph data. However, recent research has revealed that real-world graphs often contain noise, and GNNs are susceptible to noise in the graph. To address this issue, several Graph Structure Learning (GSL) models have been introduced. While GSL models are tailored to enhanc

Yuqi Wang, Zeqiang Wang, Wei Wang, Qi Chen

Safe and reliable natural language inference is critical for extracting insights from clinical trial reports but poses challenges due to biases in large pre-trained language models. This paper presents a novel data augmentation technique to improve model robustness for biomedical natural language inference in clinical trials. By generating synthetic examples

Iwo Bialynicki-Birula, Zofia Bialynicka-Birula

In relativistic theories the principle of microscopic causality states that ``information cannot travel faster than the speed of light'' \cite{kaku}. In the present work we show that the time evolution of relativistic wave functions violates this principle. We consider here the wave functions of massless and massive particles. In the case of massless particl

Ya-Qi Yu, Minghui Liao, Jihao Wu, Yongxin Liao

Multimodal Large Language Models (MLLMs) have shown impressive results on various multimodal tasks. However, most existing MLLMs are not well suited for document-oriented tasks, which require fine-grained image perception and information compression. In this paper, we present TextHawk, a MLLM that is specifically designed for document-oriented tasks, while p

Yuyan Li

This review explores the application of intelligent optimization algorithms to Multi-Objective Optimal Power Flow (MOPF) in enhancing modern power systems. It delves into the challenges posed by the integration of renewables, smart grids, and increasing energy demands, focusing on evolutionary algorithms, swarm intelligence, and deep reinforcement learning.

Ahmed R. Saikia, Narayan Mohanta

We investigate theoretically magnetoentropic signatures of the crystal phase of magnetic skyrmions of various kinds, commonly appearing in two dimensions, \textit{viz.}, N\'eel, Bloch and anti skyrmions. Using Monte Carlo calculations based on spin Hamiltonians, we obtain magnetic entropy change $\Delta S_m$ in the presence of three different types of Dzyalo

Fei Liu, Zhengdao Yuan, Qinghua Guo, Yuanyuan Zhang

This work deals with the problem of uplink communication and localization in an integrated sensing and communication system, where users are in the near field (NF) of antenna aperture due to the use of high carrier frequency and large antenna arrays at base stations. We formulate joint NF signal detection and localization as a problem of recovering signals w

Pengda Mao, Shuli Lv, Quan Quan

Recently, the concept of homotopic trajectory planning has emerged as a novel solution to navigation in large-scale obstacle environments for swarm robotics, offering a wide ranging of applications. However, it lacks an efficient homotopic path planning method in large-scale obstacle environments. This paper introduces Tube RRT*, an innovative homotopic path

Dmitrii V. Semenok, Ivan A. Troyan, Di Zhou, Wuhao Chen

Among known materials, hydride superconductors have the highest critical temperatures and are very promising as a basis for electronic sensors. Superconducting quantum interference devices (SQUID), due to its unique sensitivity to magnetic fields, are the most important applications of superconductors in microelectronics. In this work, we describe a direct c

Junyuan Gao, Yongpeng Wu, Giuseppe Caire, Wei Yang

This paper explores the fundamental limits of unsourced random access (URA) with a random and unknown number ${\rm{K}}_a$ of active users in MIMO quasi-static Rayleigh fading channels. First, we derive an upper bound on the probability of incorrectly estimating the number of active users. We prove that it exponentially decays with the number of receive anten

Priya Goyal, Sunil Malik, Jaswant k. Yadav, T. R. Seshadri

We analyze the volume-limited subsamples extracted from the sixteenth data release of the SDSS-IV eBOSS quasar survey spanning a redshift interval of $0.8 < z < 2.2$, to estimate the scale of transition to homogeneity in the Universe. The multi-fractal analysis used for this purpose considers the scaling behavior of different moments of quasar distribution i

Ziqiang Liu, Tonghua Liu, Xinyi Zhong, Yifei Xu

In this work, we studied four types of cosmological models with different mechanisms driving the accelerated expansion of the universe, include Braneworld models, Chaplygin Gas models, Emergent Dark Energy models, and cosmological torsion models. Considering that the dynamics of these models at low redshifts are very similar and difficult to distinguish, we

Paula Pico, Lyes Kahouadji, Seungwon Shin, Jalel Chergui

We present a numerical study of the main sub-stages preceding aerosol formation via bursting bubbles: capillary wave propagation along the bubble, convergence at the bubble's apex, the ascent of a Worthington jet and its break-up to release liquid drops. We focus on two crucial yet overlooked aspects of the system: the presence of surface-active agents and d

Zdzisław Brzeźniak, Jacek Jendrej, Nimit Rana

This paper aims to establish the local and global well-posedness theory in $L^1$, inspired by the approach of Keel and Tao [Internat. Math. Res. Notices, 1998], for the forced wave map equation in the ``external'' formalism. In this context, the target manifold is treated as a submanifold of a Euclidean space. As a corollary, we reprove Zhou's [Math. Z., 199

Tejasv Bedi, Bencong Zhu, Michael L. Neugent, Kevin C. Lutz

The human body consists of microbiomes associated with the development and prevention of several diseases. These microbial organisms form several complex interactions that are informative to the scientific community for explaining disease progression and prevention. Contrary to the traditional view of the microbiome as a singular, assortative network, we int

Jiawei Chen, Xiao Yang, Yinpeng Dong, Hang Su

Face anti-spoofing (FAS) and adversarial detection (FAD) have been regarded as critical technologies to ensure the safety of face recognition systems. However, due to limited practicality, complex deployment, and the additional computational overhead, it is necessary to implement both detection techniques within a unified framework. This paper aims to achiev

Quanxiu Wang, Hui Huang, Mingjie Wang, Yong Dai

Over the past decade, a series of unflagging efforts have been dedicated to developing highly expressive and controllable text-to-speech (TTS) systems. In general, the holistic TTS comprises two interconnected components: the frontend module and the backend module. The frontend excels in capturing linguistic representations from the raw text input, while the

Ralph Kenna, Bertrand Berche

Scaling, hyperscaling and finite-size scaling were long considered problematic in theories of critical phenomena in high dimensions. The scaling relations themselves form a model-independent structure that any model-specific theory must adhere to, and they are accounted for by the simple principle of homogeneity. Finite-size scaling is similarly founded on t

Ralph Kenna, Bertrand Berche

In the 1960's, four famous scaling relations were developed which relate the six standard critical exponents describing continuous phase transitions in the thermodynamic limit of statistical physics models. They are well understood at a fundamental level through the renormalization group. They have been verified in multitudes of theoretical, computational an

Yidan Wu, Jianan Zhang, Li Jin

Learning-based approaches are increasingly popular for traffic control problems. However, these approaches are applied typically as black boxes with limited theoretical guarantees and interpretability. In this paper, we consider the theory of dynamic routing over parallel servers, a representative traffic control task, using semi-gradient on-policy control a

Ziqin Yang, Yuan He, Tiancai Jiang, Feng Bai

The design, construction, and commissioning of a conduction-cooled Nb3Sn demonstration superconducting radio frequency (SRF) electron accelerator at the Institute of Modern Physics of the Chinese Academy of Sciences (IMP, CAS) will be presented. In the context of engineering application planning for Nb3Sn thin-film SRF cavities within the CiADS project, a 65

Yanlin Zhou, Tong Zhan, Yichao Wu, Bo Song

The Human Genome Project has led to an exponential increase in data related to the sequence, structure, and function of biomolecules. Bioinformatics is an interdisciplinary research field that primarily uses computational methods to analyze large amounts of biological macromolecule data. Its goal is to discover hidden biological patterns and related informat

Siva Satya Sri Ganesh Seeram, Luca Feltrin, Mustafa Ozger, Shuai Zhang

This paper explores the evolution of Radio Access Network (RAN) architectures and their integration into Non-Terrestrial Networks (NTN) to address escalating mobile traffic demands. Focusing on Low Earth Orbit (LEO) satellites as key components of NTN, we examine the feasibility of RAN function splits (FSs) in terms of fronthaul (FH) latency, elevation angle

X. Y. Zhou, S. J. Zhang, D. Wu, H. Wang

Near-infrared (NIR) pump-terahertz (THz) probe spectroscopy is used to investigate the charge and spin exciations in a strongly correlated electron compound Na0.5CoO2. This compound exhibits a coexistence of various charge and spin orders arising from intricate interactions among charge, spin, and orbital degrees of freedom. NIR pulses create significantly d

Alapan Mukhopadhyay, Karen E. Smith

Let $k$ be an arbitrary field. We construct examples of regular local $k$-algebras $R$ (of positive dimension) for which the ring of differential operators $D_k(R)$ is trivial in the sense that it contains {\it no} operators of positive order. The examples are excellent in characteristic zero but not in positive characteristic. These rings can be viewed as b

D. Levin, A. Zuevsky

We consider families of chain-cochain infinite complexes $\mathcal C$ of spaces with elements depending on a number of parameters, and endowed with a converging associative multiple product. The existence of left/right local/non-local square-vanishing ideals is assumed for subspaces of $\mathcal C$-spaces. We show that a set of differential and orthogonality

B. Q. Lv, Alfred Zong, Dong Wu, Zhengwei Nie

Coexisting orders are key features of strongly correlated materials and underlie many intriguing phenomena from unconventional superconductivity to topological orders. Here, we report the coexistence of two interacting charge-density-wave (CDW) orders in EuTe4, a layered crystal that has drawn considerable attention owing to its anomalous thermal hysteresis

Parameswaran Ajith, Pau Amaro Seoane, Manuel Arca Sedda, Riccardo Arcodia

The Lunar Gravitational-wave Antenna (LGWA) is a proposed array of next-generation inertial sensors to monitor the response of the Moon to gravitational waves (GWs). Given the size of the Moon and the expected noise produced by the lunar seismic background, the LGWA would be able to observe GWs from about 1 mHz to 1 Hz. This would make the LGWA the missing l

Rodolfo G. Campos, Iliana Reggio, Jacopo Timini

We describe an algorithm for computing counterfactual trade flows, prices, output, and welfare in a large class of general equilibrium trade models. We introduce a command called ge_gravity2 that allows users to perform these computations in Stata. This command extends the existing ge_gravity command by allowing users to compute the general equilibrium effec

Chengxi Han, Chen Wu, Haonan Guo, Meiqi Hu

The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks. However, there is still a lot of space to study for precise detection, especially the edge integrity and internal holes phenomenon of change features. In order to solve these problems, we design the Change Guiding Ne

Nan Fanghong, Teng Zhang

Byusing equivalence conditions for sectorial matrices obtained by Alakhrass and Sababheh in 2020, we improve a Rotfel'd type inequality for sectorial matrices derived by P. Zhang in 2015 and generalize a result derived by Y. Mao et al. in 2024.

Chengxi Han, Chen Wu, Haonan Guo, Meiqi Hu

Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the change detection (CD) task. However, the performance of existing deep-learning-based CD methods is hindered by the imbalance between changed and unchanged pixels. To tackle this proble

Gabriel Meseguer-Brocal, Dorian Desblancs, Romain Hennequin

Self-supervised learning has emerged as a powerful way to pre-train generalizable machine learning models on large amounts of unlabeled data. It is particularly compelling in the music domain, where obtaining labeled data is time-consuming, error-prone, and ambiguous. During the self-supervised process, models are trained on pretext tasks, with the primary o

Jiaqi Liu, Yuanyuan Zhang

In this paper, we first propose the concepts of BiHom-$\Omega$-associative algebras, BiHom-$\Omega$-dendriform algebras, BiHom-$\Omega$-pre-Lie algebras and BiHom-$\Omega$-Lie algebras. We then obtain a new BiHom-$\Omega$-associative (resp. Lie) algebra by defining a new multiplication on a BiHom-$\Omega$-associative (resp. Lie) algebra with the Rota-Baxter

Chunlin Wang

It is well known that any power series over a finite field represents a rational function if and only if its sequence of coefficients is ultimately periodic. The famous Christol's Theorem states that a power series over a finite field is algebraic if and only if its sequence of coefficients is $p$-automatic. In this paper, we extend these two results to expa

Francesco Vona, Sina Hinzmann, Michael Stern, Tanja Kojić

The collaboration in co-located shared environments has sparked an increased interest in immersive technologies, including Augmented Reality (AR). Since research in this field has primarily focused on individual user experiences in AR, the collaborative aspects within shared AR spaces remain less explored, and fewer studies can provide guidelines for designi

Dongseong Hwang, Weiran Wang, Zhuoyuan Huo, Khe Chai Sim

While Transformers have revolutionized deep learning, their quadratic attention complexity hinders their ability to process infinitely long inputs. We propose Feedback Attention Memory (FAM), a novel Transformer architecture that leverages a feedback loop to enable the network to attend to its own latent representations. This design fosters the emergence of

Fanyi Wang, Peng Liu, Haotian Hu, Dan Meng

Research on diffusion model-based video generation has advanced rapidly. However, limitations in object fidelity and generation length hinder its practical applications. Additionally, specific domains like animated wallpapers require seamless looping, where the first and last frames of the video match seamlessly. To address these challenges, this paper propo

Satyabrat Sahoo

Let $K$ be a totally real number field and $\mathcal{O}_K$ be the ring of integers of $K$. In this article, we study the asymptotic solutions of the generalized Fermat equation $Ax^p+By^p+Cz^p=0$ over $K$ with prime exponent $p$, where $A,B,C \in \mathcal{O}_K \setminus \{0\}$. For certain class of fields $K$, we prove that the equation $Ax^p+By^p+Cz^p=0$ ha

Xiaoshu Chen, Sihang Zhou, Ke Liang, Xinwang Liu

Chain of thought finetuning (cot-finetuning) aims to endow small language models (SLM) with reasoning ability to improve their performance towards specific tasks by allowing them to imitate the reasoning procedure of large language models (LLM) beyond simply predicting the answers. Most existing cot-finetuning methods adopt a pre-thinking mechanism, allowing

Yanhao Zhang, Yujiao Shi, Shan Wang, Ankit Vora

Vision-based localization for autonomous driving has been of great interest among researchers. When a pre-built 3D map is not available, the techniques of visual simultaneous localization and mapping (SLAM) are typically adopted. Due to error accumulation, visual SLAM (vSLAM) usually suffers from long-term drift. This paper proposes a framework to increase t

Jianbo Cui, Derui Sheng

The long-term dynamics of particles involved in an incompressible flow with a small viscosity ($\epsilon>0$) and slow chemical reactions, is depicted by a class of stochastic reaction-diffusion-advection (RDA) equations with a fast advection term of magnitude $1/\epsilon$. It has been shown in [7] the fast advection asymptotics of stochastic RDA equation in

Manita Pote

Knowledge Graph (KG) is a graph based data structure to represent facts of the world where nodes represent real world entities or abstract concept and edges represent relation between the entities. Graph as representation for knowledge has several drawbacks like data sparsity, computational complexity and manual feature engineering. Knowledge Graph embedding

Dacheng Zhou

This paper introduces an innovative framework for understanding the world, termed the "Three Realms and Six Layers Model". Based on the concept of scale, the world is divided into three realms, each encompassing six layers, with a ten-thousand-fold difference in scale between adjacent layers. This unique division reveals the variations in laws at different l

Jinbao Zhu, Lanping Li, Xiaohu Tang, Ping Deng

We consider the problem of private multiple linear computation (PMLC) over a replicated storage system with colluding and unresponsive constraints. In this scenario, the user wishes to privately compute $P$ linear combinations of $M$ files from a set of $N$ replicated servers without revealing any information about the coefficients of these linear combinatio

Qiang Hu, Jin Wen, Maxime Cordy, Yuheng Huang

Large language models (LLMs) have recently achieved significant success across various application domains, garnering substantial attention from different communities. Unfortunately, even for the best LLM, many \textit{faults} still exist that LLM cannot properly predict. Such faults will harm the usability of LLMs in general and could introduce safety issue

Oluwatosin Ogundare, Lewis Njualem

Gender inequality is a significant concern in many cultures, as women face significant barriers to asset acquisition particularly land ownership and control. Land acquisition and land tenure security are complex issues that affect various cultural groups differently, leading to disparities in access and ownership especially when superimposed with other socio

Amani Namboori, Shivam Mangale, Andy Rosenbaum, Saleh Soltan

The emergence of Large Language Models (LLMs) with capabilities like In-Context Learning (ICL) has ushered in new possibilities for data generation across various domains while minimizing the need for extensive data collection and modeling techniques. Researchers have explored ways to use this generated synthetic data to optimize smaller student models for r

Junkang Huang, Tao Zhou

We explore the superconducting pairing mechanisms in the trilayer $\mathrm{La}_4\mathrm{Ni}_3\mathrm{O}_{10}$ material through self-consistent mean-field calculations. Our findings demonstrate that intralayer pairings are substantially weaker compared to interlayer ones. Remarkably, in the state characterized by interlayer pairing, we detect the presence of