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Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis

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Computer Modeling in engineering & Sciences 2023年第12期137卷 2129-2147页

作者： Qiankun Zuo Junhua Hu Yudong Zhang Junren Pan Changhong Jing Xuhang Chen Xiaobo Meng Jin Hong School of Information Engineering Hubei University of EconomicsWuhan430205China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing100038China School of Computing and Mathematic Sciences University of LeicesterLeicesterLE17RHUK Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen518055China Faculty of Science and Technology University of MacaoMacao999078China School of Geophysics Chengdu University of TechnologyChengdu610059China Laboratory of Artificial Intelligence and 3D Technologies for Cardiovascular Diseases Guangdong Provincial Key Laboratory of South China Structural Heart DiseaseGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou519041China Medical Research Institute Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou519041China

The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia *** brain functional network is suitable to bridge the correlation between abnormal connectivities and dementia ***,it is challenging to access considerable amounts of brain functional network data,which hinders the widespread application of data-driven models in dementia *** this study,a novel distribution-regularized adversarial graph auto-Encoder(DAGAE)with transformer is proposed to generate new fake brain functional networks to augment the brain functional network dataset,improving the dementia diagnosis accuracy of data-driven ***,the label distribution is estimated to regularize the latent space learned by the graph encoder,which canmake the learning process stable and the learned representation ***,the transformer generator is devised to map the node representations into node-to-node connections by exploring the long-term dependence of highly-correlated distant brain *** typical topological properties and discriminative features can be preserved ***,the generated brain functional networks improve the prediction performance using different classifiers,which can be applied to analyze other cognitive *** on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset demonstrate that the proposed model can generate good brain functional *** classification results show adding generated data can achieve the best accuracy value of 85.33%,sensitivity value of 84.00%,specificity value of 86.67%.The proposed model also achieves superior performance compared with other related ***,the proposedmodel effectively improves cognitive disease diagnosis by generating diverse brain functional networks.

关键词： Adversarial graph encoder label distribution generative transformer functional brain connectivity graph convolutional network dementia

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Co‑packaged optics(CPO):status,challenges,and solutions

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Frontiers of Optoelectronics 2023年第1期16卷 1-40页

作者： Min Tan Jiang Xu Siyang Liu Junbo Feng Hua Zhang Chaonan Yao Shixi Chen Hangyu Guo Gengshi Han Zhanhao Wen Bao Chen Yu He Xuqiang Zheng Da Ming Yaowen Tu Qiang Fu Nan Qi Dan Li Li Geng Song Wen Fenghe Yang Huimin He Fengman Liu Haiyun Xue Yuhang Wang Ciyuan Qiu Guangcan Mi Yanbo Li Tianhai Chang Mingche Lai Luo Zhang Qinfen Hao Mengyuan Qin School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong KongChina HKUST Fok Ying Tung Research Institute Guangzhou 511462China The Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511462China Chongqing United Micro-Electronics Center(CUMEC) Chongqing 401332China Hisense Broadband Multimedia Technologies Co. Ltd.Qingdao 266000China Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China State Key Laboratory of Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China School of Microelectronics Xi’an Jiaotong UniversityXi’an 710049China Zhangjiang Laboratory Shanghai 201210China The State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Huawei Technologies Co. Ltd.Shenzhen 440307China College of Computer National University of Defense TechnologyChangsha 410073China Institute of Computing Technology Chinese Academy of SciencesBeijing 100086China

Due to the rise of 5G,IoT,AI,and high-performance computing applications,datacenter trafc has grown at a compound annual growth rate of nearly 30%.Furthermore,nearly three-fourths of the datacenter trafc resides within *** conventional pluggable optics increases at a much slower rate than that of datacenter *** gap between application requirements and the capability of conventional pluggable optics keeps increasing,a trend that is *** optics(CPO)is a disruptive approach to increasing the interconnecting bandwidth density and energy efciency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and *** is widely regarded as a promising solution for future datacenter interconnections,and silicon platform is the most promising platform for large-scale *** international companies(e.g.,Intel,Broadcom and IBM)have heavily investigated in CPO technology,an inter-disciplinary research feld that involves photonic devices,integrated circuits design,packaging,photonic device modeling,electronic-photonic co-simulation,applications,and *** review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform,identify the key challenges,and point out the potential solutions,hoping to encourage collaboration between diferent research felds to accelerate the development of CPO technology.

关键词： Co-packaged optics Silicon photonics High-performance computing advanced packaging External laser Optical power delivery Co-simulation Standardization Transmitter Receiver

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LCJ-Seg: Tunnel Lining Construction Joint Segmentation via Global Perception

LCJ-Seg: Tunnel Lining Construction Joint Segmentation via G...

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International Conference on Intelligent Transportation

作者： Lei Tan Xiaohan Zhang Xinrui Zeng Xiaoxi Hu Fei Chen Zongyang Liu Jin Liu Tao Tang State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China Beijing Municipal Engineering Research Institute Beijing China College of Information and Electronic Engineering Zhejiang University Hangzhou China School of Mathematical Sciences Beihang University Beijing China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan China Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan China Institute for Transport Studies University of Leeds Leeds United Kingdom

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

As railway facilities and equipment maintenance becomes a focal point of current railway research, tunnels, as fundamental components of railway infrastructure, rightly garner attention for intelligent railway maintenance. However, detecting tunnel lining joints poses challenges due to their potential confusion with other internal tunnel objects such as pipelines and cables. To address this issue, we propose an effective segmentation method, LCJ-Seg, leveraging Global Perception Module (GPM) and Detail Preservation and Feature Denoising Module (DPFDM). The GPM is incorporated into the backbone for accurately identifying tunnel lining joints, as these joints require global context to properly distinguish them from other internal tunnel objects. The DPFDM preserves fine details and reduces noise of low-level features to enhance feature fusion. It ensures that both high-level and low-level features retain important details crucial for the lining construction joint segmentation task. Comprehensive comparative experiments and ablation studies on a real collected dataset, demonstrating the superiority of our approach over existing segmentation methods.

关键词： Noise reduction Pipelines Noise Rail transportation Maintenance Object recognition Intelligent transportation systems Cables

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Visualizing nonlinear resonance in nanomechanical systems via single-electron tunneling

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Nano Research 2021年第4期14卷 1156-1161页

作者： Xinhe Wang Lin Cong Dong Zhu Zi Yuan Xiaoyang Lin Weisheng Zhao Zaiqiao Bai Wenjie Liang Ximing Sun Guang-Wei Deng Kaili Jiang Fert Beijing Research Institute School of Microelectronics&Beijing Advanced Innovation Centre for Big Data and Brain Computing(BDBC)Beihang UniversityBeijing 100191China State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics and Tsinghua-Foxconn Nanotechnology Research CenterTsinghua UniversityBeijing 100084China Key Laboratory of Quantum Information CASUniversity of Science and Technology of ChinaHefei 230026China Department of Physics Beijing Normal UniversityBeijing 100875China Institute of Physics Chinese Academy of SciencesBeijing 100080China Institute of Nuclear and New Energy Technology Collaborative Innovation Center of Advanced Nuclear Energy TechnologyKey Laboratory of Advanced Reactor EngineeringTsinghua UniversityBeijing 100084China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China

Numerous reports have elucidated the importance of mechanical resonators comprising quantum-dot-embedded carbon nanotubes(CNTs)for studying the effects of single-electron ***,there is a need to investigate the single-electron transport that drives a large amplitude into a nonlinear ***,a CNT hybrid device has been investigated,which comprises a gate-defined quantum dot that is embedded into a mechanical resonator under strong actuation *** Coulomb peak positions synchronously oscillate with the mechanical vibrations,enabling a single-electron Chopper*1 ***,the vibration amplitude of the CNT versus its frequency can be directly visualized via detecting the time-averaged single-electron tunneling *** understand this phenomenon,a general formula is derived for this time-averaged single-electron tunneling current,which agrees well with the experimental *** using this visualization method,a variety of nonlinear motions of a CNT mechanical oscillator have been directly recorded,such as Duffing nonlinearity,parametric resonance,and double-,fractional-,mixed-frequency *** approach opens up burgeoning opportunities for investigating and understanding the nonlinear motion of a nanomechanical system and its interactions with electron transport in quantum regimes.

关键词： carbon nanotube mechanical resonator quantum dot nonlinear coupling

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Photonic axion insulator

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Science (New York, N.Y.) 2025年第6730期387卷 162-166页

作者： Liu, Gui-Geng Mandal, Subhaskar Xi, Xiang Wang, Qiang Devescovi, Chiara Morales-Pérez, Antonio Wang, Ziyao Yang, Linyun Banerjee, Rimi Long, Yang Meng, Yan Zhou, Peiheng Gao, Zhen Chong, Yidong García-Etxarri, Aitzol Vergniory, Maia G. Zhang, Baile Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Research Center for Industries of the Future Department of Electronic and Information Engineering School of Engineering Westlake University Hangzhou China School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan China National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing China Donostia International Physics Center Donostia-San Sebastian Spain Institute for Theoretical Physics ETH Zurich Zurich Switzerland Material and Applied Physics Department University of the Basque Country (UPV/EHU) Donostia-San Sebastián Spain Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China National Engineering Research Center of Electromagnetic Radiation Control Materials Key Laboratory of Multi-spectral Absorbing Materials and Structures of Ministry of Education University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Department of Electronic and Electrical Engineering Guangdong Key Laboratory of Integrated Optoelectronics Intellisense Southern University of Science and Technology Shenzhen China Centre for Disruptive Photonic Technologies Photonics Institute Nanyang Technological University Singapore IKERBASQUE Basque Foundation for Science Bilbao Spain Max Planck Institute for Chemical Physics of Solids Dresden Germany Département de Physique et Institut Quantique Université de Sherbrooke Sherbrooke Canada

Axions, hypothetical elementary particles that remain undetectable in nature, can arise as quasiparticles in three-dimensional crystals known as axion insulators. Previous implementations of axion insulators have largely been limited to two-dimensional systems, leaving their topological properties in three dimensions unexplored in experiment. Here, we realize an axion insulator in a three-dimensional photonic crystal and probe its topological properties. Demonstrated features include half-quantized Chern numbers on each surface that resembles a fractional Chern insulator, unidirectional chiral hinge states forming topological transport in three dimensions, and arithmetic operations between fractional and integer Chern numbers. Our work experimentally establishes the axion insulator as a three-dimensional topological phase of matter and enables chiral states to form complex, unidirectional three-dimensional networks through braiding.

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Traditional Chinese Medicine Constitution and Clinical Data Association with Machine Learning for Prediction of Spontaneous Abortion

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Clinical Complementary Medicine and Pharmacology 2022年第2期2卷 1-9页

作者： Yan Liu Yangyang Geng Liuqing Yang Shate Xiang Qiaotong Wang Lanyawen Hu Ping Ye The Second clinical medical college Zhejiang Chinese Medical UniversityHangzhou 310053ZhejiangChina State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001HenanChina Tongde hospital of Zhejiang province Hangzhou 310012ZhejiangChina Zhejiang Chinese medical university Hangzhou 310053ZhejiangChina

Background:Early prevention of Spontaneous Abortion(SA)is essential for the treatment of recurrent spontaneous ***:In this retrospective study,a variety of machine learning methods were used to develop predictive models and diagnose the potential risk of ***:A total of 663 pregnant women participated in the case-control study,586 of which were SA patients and 77 were normal parturition *** research data included 25 features of Traditional Chinese Medicine(TCM)constitution and clinical data related to *** work utilized 8 machine learning techniques including logistic regression,gradient boosting decision tree,k-nearest neighbor,classification and r-egression tree,multilayer perceptron,support vector machine,random forest and XG-Boost to predict *** performances of the applied models were evaluated by using the method of 10-fold cross-validation and by computing the diagnostic test characteristics,including accuracy,precision,recall,𝐹1 score,and the AUC of ROC ***:The𝐹1 scores of these eight machine learning techniques were all above 97.5%.Among them,gradient boosting decision tree had the best prediction result on *** accuracy,precision,recall,𝐹1 score,and the AUC of ROC curve of gradient boosting decision tree were 97.9%,99%,98.6%,98.8%,and 97.3%,***:The paper has accurately predicted the risk of SA combined with TCM constitution and clinical data.

关键词： Spontaneous abortion Machine learning TCM constitution Clinical data Prediction modeling

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Unpolarized transverse momentum dependent parton distributions of the nucleon from lattice QCD

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Physical Review D 2024年第11期109卷 114513-114513页

作者： Jin-Chen He Min-Huan Chu Jun Hua Xiangdong Ji Andreas Schäfer Yushan Su Wei Wang Yi-Bo Yang Jian-Hui Zhang Qi-An Zhang Yang Yuanqing Scientific Computering Center Tsung-Dao Lee Institute Shanghai Key Laboratory for Particle Physics and Cosmology Key Laboratory for Particle Astrophysics and Cosmology (MOE) School of Physics and Astronomy Department of Physics Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center Institut für Theoretische Physik Southern Center for Nuclear-Science Theory (SCNT) CAS Key Laboratory of Theoretical Physics School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou 310024 China Beijing/Hangzhou China School of Physical Sciences School of Science and Engineering Center of Advanced Quantum Studies Department of Physics School of Physics

We present a first lattice QCD calculation of the unpolarized nucleon’s isovector transverse-momentum-dependent parton distribution functions (TMDPDFs), which are essential to predict observables of multiscale, semi-inclusive processes in the standard model. We use a Nf=2+1+1 MILC ensemble with valence clover fermions on a highly improved staggered quark (HISQ) sea to compute the quark momentum distributions in a large-momentum nucleon on the lattice. The state-of-the-art techniques in renormalization and extrapolation in the correlation distance on the lattice are adopted. The perturbative kernel up to next-to-next-to-leading order is taken into account, and the dependence on the pion mass and the hadron momentum is explored. Our results are qualitatively comparable with phenomenological TMDPDFs, which provide an opportunity to predict high energy scatterings from first principles.

关键词： Lattice QCD Nucleon distribution Parton distribution functions

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A Robust Deep Learning-Based DOA Super-Resolution Estimation Method With Single Snapshot

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IEEE Transactions on Vehicular Technology 2025年

作者： Luo, Tao Chen, Peng Yang, Zihan Zheng, Le Zhang, Yudong Liu, Jun Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China Beijing Institute of Technology School of Information and Electronics Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China University of Leicester School of Computing and Mathematical Sciences LeicesterLE1 7RH United Kingdom Army Engineering University of PLA National Key Laboratory on Electromagnetic Environment Effects and Electro-optical Engineering Nanjing210007 China

At present, deep learning (DL) has attracted widespread attention and has been widely applied in different areas of wireless communication, and signal processing. Due to its excellent feature extraction capability, it has been extensively used in the direction of arrival (DOA) estimation. In this paper, a robust network for super-resolution single-snapshot DOA estimation called DeepDOA is proposed. Different from other network-based DOA algorithms, DeepDOA takes the normalized real and imaginary parts of the received signal as inputs. Meanwhile, the network output is a vector instead of a spatial spectrum, and the corresponding spatial spectrum can be obtained by a simple transformation, which makes the spectrum smoother. Moreover, a sparse constraint is first introduced into the loss function, which improves the accuracy of the algorithm. Numerical simulations are conducted to verify its excellent performance. Finally, a frequency-modulated continuous wave (FMCW) radar location system is built to validate the proposed algorithm. © 1967-2012 IEEE.

关键词： Frequency modulation

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Memory Error Detection Based on Dynamic Binary Translation

Memory Error Detection Based on Dynamic Binary Translation

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International Conference on Communication Technology (ICCT)

作者： Hang Xu Wei Ren Zimian Liu Jiajun Chen Junhu Zhu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

Dynamic memory error detection technology is widely utilized in locating and mitigating memory-corruption vulnerabilities. High false negative in existing technologies impairs the effectiveness of detection, especially when the detector has no source code. We proposed a dynamic memory error detection method based on dynamic binary translation. It realized the detection by combining a call stack tracing method and an IR language level memory error detection method. Experiments show that the detection success rate of this method in the heap and stack memory destruction is more than 80%.

关键词： Software Instruments Memory management Runtime Static analysis Aerospace electronics Security

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UEFI Trusted computing Vulnerability Analysis Based on state Transition Graph

UEFI Trusted Computing Vulnerability Analysis Based on State...

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International Conference on Computer and Communications (ICCC)

作者： Yanyang Gu Ping Zhang Zhifeng Chen Fei Cao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In the face of increasingly serious firmware attacks, it is of great significance to analyze the vulnerability security of UEFI. This paper first introduces the commonly used trusted authentication mechanisms of UEFI. Then, aiming at the loopholes in the process of UEFI trust verification in the startup phase, combined with the state transition diagram, PageRank algorithm and Bayesian network theory, the analysis model of UEFI trust verification startup vulnerability is constructed. And according to the example to verify the analysis. Through the verification and analysis of the data obtained, the vulnerable attack paths and key vulnerable nodes are found. Finally, according to the analysis results, security enhancement measures for UEFI are proposed.

关键词： Analytical models Trusted computing Computational modeling Bayes methods Security Network theory (graphs) Microprogramming

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