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Delayed threshold and spatial diffusion in k-core percolation induced by long-range connectivity

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Communications Physics 2025年第1期8卷 1-10页

作者： Zhang, Xin-Ya Yao, Yi Han, Zhiyu Yan, Gang Center for Interdisciplinary Studies and Department of Physics School of Science Westlake University Hangzhou310030 China National Key Laboratory of Autonomous Intelligent Unmanned Systems MOE Frontiers Science Center for Intelligent Autonomous Systems and Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Physical Science and Engineering Tongji University Shanghai200092 China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China

Most real-world complex networks are spatially embedded, with nodes positioned in physical space. In such systems, distance-based connectivity shapes not only the information transmission efficiency but also the network robustness and vulnerability behavior. Here, we systematically examined how spatial distance influences network robustness using k-core percolation across a pair of models of long-range connectivity. For structural connected components, we found that long-range connectivity can trigger explosive phase transitions, but with a delayed threshold. For spatial neighborhoods, two core phenomena emerge: spatial diffusion and clustering. Both synthetic model networks and the empirical Drosophila neuronal network, that follow geometric scaling laws with small exponents, exhibit gradual spatial spread. In contrast, strong geometric constraints lead to spatial clustering. Despite varying connectivity models, spatial neighborhoods consistently demonstrate self-organized criticality throughout the percolation process. Our findings reveal how geometric constraints influence structural and spatial robustness, which may in turn support functional robustness. © The Author(s) 2025.

关键词： Geometry

Distributed mirror descent algorithm with bregman damping for nonsmooth constrained optimization

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arXiv 2021年

作者： Chen, Guanpu Li, Weijian Xu, Gehui Hong, Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Automation University of Science and Technology of China Anhui Hefei China Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

To solve distributed optimization efficiently with various constraints and nonsmooth functions, we propose a distributed mirror descent algorithm with embedded Bregman damping, as a generalization of conventional distributed projection-based algorithms. In fact, our continuous-time algorithm well inherits good capabilities of mirror descent approaches to rapidly compute explicit solutions to the problems with some specific constraint structures. Moreover, we rigorously prove the convergence of our algorithm, along with the boundedness of the trajectory and the accuracy of the solution. © 2021, CC0.

关键词： Mirrors

How Long Is Enough? Exploring the Optimal Intervals of Long-Range Clinical Note Language Modeling

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arXiv 2022年

作者： Cahyawijaya, Samuel Wilie, Bryan Lovenia, Holy Zhong, MingQian Zhong, Huan Ip, Nancy Y. Fung, Pascale Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong Division of Life Science State Key Laboratory of Molecular Neuroscience Molecular Neuroscience Center The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Hong Kong Hong Kong Center for Neurodegenerative Diseases Hong Kong Science Park Hong Kong Hong Kong

Large pre-trained language models (LMs) have been widely adopted in biomedical and clinical domains, introducing many powerful LMs such as bio-lm and BioELECTRA. However, the applicability of these methods to real clinical use cases is hindered, due to the limitation of pre-trained LMs in processing long textual data with thousands of words, which is a common length for a clinical note. In this work, we explore long-range adaptation from such LMs with Longformer, allowing the LMs to capture longer clinical notes context. We conduct experiments on three n2c2 challenges datasets and a longitudinal clinical dataset from Hong Kong Hospital Authority electronic health record (EHR) system to show the effectiveness and generalizability of this concept, achieving 10% F1-score improvement. Based on our experiments, we conclude that capturing a longer clinical note interval is beneficial to the model performance, but there are different cut-off intervals to achieve the optimal performance for different target variables. © 2022, CC BY-NC-SA.

关键词： Modeling languages

Enhanced Ticket Transparency (eTT) Framework for Single Sign-On Services with Pseudonyms

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Enhanced Ticket Transparency (eTT) Framework for Single Sign...

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Guangqi Liu Jingqiang Lin Dawei Chu Xiaokun Zhang Qiongxiao Wang Cunqing Ma Fengjun Li Dingfeng Ye State Key Laboratory of Information Security Institute of Information Engineering CAS Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Cyber Security University of Science and Technology of China Hefei China Headquarter of Chinese Academy of Sciences Beijing China Beijing Institute University of Science and Technology of China Beijing China Beijing Certificate Authority Co. Ltd. Beijing China Department of Electrical Engineering and Computer Science University of Kansas KS USA

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Recently, a series of vulnerabilities occurred to divulge or forge single sign-on tickets, such as the famous SolarWinds incident Once malicious attackers obtain fraudulent tickets, they can pry into user privacy as well as compromise the system by impersonating the victim user. Inspired by certificate transparency, a ticket transparency (TT) framework for detecting fraudulent tickets is proposed. However, it suffers from inefficiency and potential failure. In this paper, we further propose an enhanced ticket transparency (eTT) scheme, which ensures that all fraudulent tickets can be detected efficiently through a novel dual-backup structure to store ticket entries in the public log. Meanwhile, we design specific calculations for pairwise pseudonymous identifiers (PPIDs), to support fraudulent-detection towards tickets in which user identifiers are pseudonyms. We implemented the prototype system, and the experimental evaluation shows that eTT framework introduces acceptable overheads in the sign-on process.

关键词： Privacy Prototypes Performance analysis Servers Security

A Learning Convolutional Neural Network Approach for Network Robustness Prediction

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arXiv 2022年

作者： Lou, Yang Wu, Ruizi Li, Junli Wang, Lin Li, Xiang Chen, Guanrong The Department of Computing and Decision Sciences Lingnan University Hong Kong The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China The College of Computer Science Sichuan Normal University Chengdu610066 China The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China The Department of Control Science and Engineering Tongji University Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various societal and industrial networks again malicious attacks. In particular, connectivity robustness and controllability robustness reflect how well a networked system can maintain its connectedness and controllability against destructive attacks, which can be quantified by a sequence of values that record the remaining connectivity and controllability of the network after a sequence of node- or edge-removal attacks. Traditionally, robustness is determined by attack simulations, which are computationally very time-consuming or even practically infeasible. In this paper, an improved method for network robustness prediction is developed based on learning feature representation using convolutional neural network (LFR-CNN). In this scheme, higher-dimensional network data are compressed to lower-dimensional representations, and then passed to a CNN to perform robustness prediction. Extensive experimental studies on both synthetic and real-world networks, both directed and undirected, demonstrate that 1) the proposed LFR-CNN performs better than other two state-of-the-art prediction methods, with significantly lower prediction errors;2) LFR-CNN is insensitive to the variation of the network size, which significantly extends its applicability;3) although LFR-CNN needs more time to perform feature learning, it can achieve accurate prediction faster than attack simulations;4) LFR-CNN not only can accurately predict network robustness, but also provides a good indicator for connectivity robustness, better than the classical spectral measures. © 2022, CC BY.

关键词： Complex networks

Revealing vulnerable regions through diverse adversarial examples

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Machine Learning 2025年第7期114卷

作者： Zhao, Yunce Huang, Wei Liu, Wei Yao, Xin Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China School of Computer Science FEIT University of Technology Sydney SydneyNSW2007 Australia Tokyo103-0027 Japan School of Data Science Lingnan University Hong Kong

Current explainable AI approaches to Deep Neural Networks (DNNs) primarily aim to understand network behavior by identifying key input features that influence predictions. However, these methods often fail to identify vulnerable regions in the input that are sensitive to minor perturbations and pose significant security risks. The vulnerability of DNNs is typically studied through adversarial examples, but traditional norm-based algorithms, lacking spatial constraints, distribute perturbations across the entire image, obscuring these critical areas. To overcome this limitation, we propose the Vulnerable Region Discovery Attack (VrdAttack), an efficient method that leverages Differential Evolution to generate diverse one-pixel perturbations, enabling the discovery of vulnerable regions and uncovering pixel-level vulnerabilities in Deep Neural Networks (DNNs). Our extensive experiments on CIFAR-10 and ImageNet demonstrate that our proposed VrdAttack outperforms existing methods in identifying diverse critical weak points in an input, highlighting model-specific vulnerabilities, and revealing the impact of adversarial training on these vulnerable regions. © The Author(s) 2025.

关键词： Deep neural networks

A Pose Estimation Method for Fisheye Cameras Based on the EPnP Algorithm 11th

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A Pose Estimation Method for Fisheye Cameras Based on the...

11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Wang, Chenxiao Wang, Biao Ding, Yulong Xiao, Dunhui Chen, Ben M. Zhang, Keping Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Tongji University Shanghai China Department of Mechanical and Automation Engineering the Chinese University of Hong Kong China State Grid Nanjing Lishui District Power Supply Jiangsu Nanjing China

ISBN: (纸本)9789819647521

Fisheye cameras offer a wider field of view compared to traditional pinhole cameras. This paper presents a pose estimation method for fisheye cameras based on the EPnP algorithm. A unified projection model is used to analyze the imaging process, and it is shown to be applicable to fisheye cameras. A virtual pinhole camera is constructed, where the image captured by the fisheye camera is mapped onto the virtual camera’s image. The resulting virtual 2D reference points are then used as input to the EPnP algorithm for estimating the fisheye camera’s pose. The mapping error from the fisheye image to the virtual camera image is analyzed, revealing that the process does not amplify pixel error when extracting 2D reference points. It is recommended to select points near the image’s central focus as 2D reference points. Experimental results demonstrate that the proposed method is both reliable and efficient. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Pinhole cameras

Single-Photon-Memory Measurement-Device-Independent Quantum Secure Direct Communication - Part I: Its Fundamentals and Evolution

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arXiv 2023年

作者： Li, Xiang-Jie Pan, Dong Long, Gui-Lu Hanzo, Lajos State Key Laboratory of Low-dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Beijing Academy of Quantum Information Sciences Beijing100193 China Frontier Science Center for Quantum Information Beijing100084 China Beijing National Research Center for Information Science and Technology Beijing100084 China School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Quantum secure direct communication (QSDC) has attracted a lot of attention, which exploits deep-rooted quantum physical principles to guarantee unconditional security of communication in the face of eavesdropping. We first briefly review the fundamentals of QSDC, and then present its evolution, including its security proof, its performance improvement techniques, and practical implementation. Finally, we discuss the future directions of QSDC. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum communication

Anisotropic tensile properties and high-cycle fatigue behavior of Ti6Al4V fabricated by single and dual laser-powder bed fusion

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Materials science and Engineering: A 2025年 941卷

作者： Guotai Li Peichen Hu Yuzhan Fan Ming Wu Mingjun Chen Tianyu Yu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China Key Laboratory of Micro-systems and Micro-structures Manufacturing Ministry of Education Harbin Heilongjiang 150001 China Department of Computer Science KU Leuven 3001 Leuven Belgium Department of Mechanical Engineering KU Leuven 3001 Leuven Belgium

The development of multi laser-powder bed fusion (PBF) technology has significantly reduced the production time for large engine components. However, the impact of thermal effects and microstructural characteristics in the laser beam overlap region on the anisotropic mechanical behavior of metallic materials remains unclear. This study investigated the anisotropic tensile properties and high-cycle fatigue behavior of Ti6Al4V produced by both single laser-PBF (SL-PBF) and dual laser-PBF (DL-PBF). As-built DL-PBF samples exhibited high strength (1404 MPa) but low ductility (3.6 %). After heat treatment, the samples achieved a strength-ductility balance, with an ultimate tensile strength of 1089 MPa, and an elongation of 17.1 %. The mechanical properties of Ti6Al4V produced by DL-PBF were influenced by the α lath thickness, dislocation density and texture. The precipitation of small-angle grain boundaries during DL-PBF process was found to contribute to the strong anisotropy. Due to the influence of internal pore forming, the fatigue strength of the DL-PBF samples was lower than that of the SL-PBF samples. Pores in the dual-laser beam overlap region accelerated the fatigue crack propagation, resulting in a venation-like pattern. In contrast, cracks in the SL-PBF samples propagated in a circular pattern around internal pore. A high-speed camera was employed to capture the dual-laser beams dynamics during pore formation. This study provides a comprehensive analysis of the mechanical properties and pore formation mechanisms in the DL-PBF process.

关键词： Anisotropy Dual laser-powder bed fusion High-cycle fatigue Tensile properties Ti6Al4V