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Bioinspired sensing-memory-computing integrated vision systems: biomimetic mechanisms, design principles, and applications

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Science China(Information Sciences) 2024年第5期67卷 5-27页

作者： Yujie HUANG Yinlong TAN Yan KANG Yabo CHEN Yuhua TANG Tian JIANG Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology College of Advanced Interdisciplinary Studies National University of Defense Technology Institute for Quantum Science and technology College of ScienceNational University of Defense Technology

With the explosion of sensory data in the Internet of Things(Io T) era, conventional machine vision systems are becoming increasingly difficult to meet the requirements of high efficiency, low energy consumption, and low latency due to their inherent shortcomings of separate sensing, memory, and computing units. Inspired by the retina and neuromorphic computing, the sensing-memory-computing integrated vision system(SMCVS) that features low power consumption, low latency, and high parallelism has been considered a promising technology to surpass the von Neumann architecture and realize strong artificial intelligence.Meanwhile, novel materials like two-dimensional semiconductors and quantum dots with novel optoelectronic performance provide hardware carriers for implementing integrated sensing-memory-computing architectures,attracting considerable attention. This paper reviews the recent research progress in bioinspired vision systems in terms of biomimetic mechanisms, design principles, computational architectures, and applications.Firstly, the biomimetic mechanisms are illustrated to guide the design of high-performance artificial visual perception systems. Then the research progress of optoelectronic-synapse-based bioinspired vision systems in the device principles and applications including image filtering, color recognition, visual adaptation, and motion detection are summarized. Finally, the challenges and future developing directions of the SMCVS are provided regarding bionic application, architecture design, and device fabrication.

关键词： sensing-memory-computing architecture neuromorphic computing retinomorphic device image recognition visual system

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Hybrid effect on mechanical properties and high-temperature performance of copper matrix composite reinforced with micro-nano dual-scale particles

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Journal of Materials Science & technology 2024年第5期172卷 94-103页

作者： Xingde Zhang Yihui Jiang Fei Cao Tian Yang Fan Gao Shuhua Liang School of Materials Science and Engineering Xi’an University of TechnologyXi’an 710048China Engineering Research Center of Conducting Materials and Composite technology Ministry of EducationXi’an University of TechnologyXi’an 710048China Shaanxi Province Key Laboratory of Electrical Materials and Infiltration technology Xi’an University of TechnologyXi’an 710048China

A dual-scale hybrid HfB_(2)/Cu-Hf composite with HfB_(2) microparticles and Cu_(5) Hf nanoprecipitates was designed and prepared.The contribution of the hybrid effect to the mechanical properties and high-temperature performances was studied from macro and micro perspectives,respectively.The hybrid of dual-scale particles can make the strain distribution of the composite at the early deformation stage more uniform and delay the strain concentration caused by the HfB_(2) particle.The dislocation pinning of HfB_(2) particles and the coherent strengthening of Cu_(5) Hf nanoprecipitates simultaneously play a strengthening role,but the strength of the hybrid composite is not a simple superposition of two strengthening mod-els.In addition,both Cu_(5) Hf nanoprecipitates and HfB_(2) microparticles contribute to the high-temperature performance of the composite,the growth and phase transition of nanoprecipitates at high temperature will reduce their contribution to strength,while the stable HfB_(2) particles can inhibit the coarsening of matrix grains and maintain the high-density geometrically necessary dislocations(GNDs)in the matrix,which ensures more excellent high-temperature resistance of the hybrid composite.As a result,the hy-brid structure can simultaneously possess the advantages of multiple reinforcements and make up for the shortcomings of each other.Finally,a copper matrix composite with high strength,high conductivity,and excellent high-temperature performance is displayed.

关键词： Copper matrix composite HfB 2 particles Hybrid effect High strength and high conductivity High-temperature performance

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Development of lithium-free P2-type high-sodium content cathode materials with enhanced cycle and air stability for sodium-ion batteries

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Rare Metals 2024年第1期43卷 113-123页

作者： Jin-Lv Tian Lin-Rong Wu Hai-Jun Zhao Shou-Dong Xu Liang Chen Ding Zhang Xiao-Chuan Duan College of Chemical Engineering and technology Taiyuan University of TechnologyTaiyuan 030024China College of Chemistry Taiyuan University of TechnologyTaiyuan 030024China School of Chemical Engineering and Pharmacy Wuhan Institute of TechnologyWuhan 430205China

The effect of partial substitution of Mg for Ni on a high-sodium and lithium-free layered P2-type Na_(45/54)Mg_(6)/_(54)Ni_(12/54)Mn_(34/54)O_(2) cathode with high initial Coulombic efficiency and excellent cyclic stability has been investigated in this study.Based on the crystal structural analysis,the Mg doping can retain the P2 structure up to 4.3 V,thus restraining the detrimental phase transformation of P2-02during the Na-ion intercalation/deintercalation process.Therefore,the obtained Mg-doped P2-type cathode exhibits a reversible specific capacity of 109 mAh·g^(-1) at 0.1C between 2.0 and 4.3 V and a retention rate of 81.5% after 200cycles at 1C.In addition,the full cell consisting of Mg-doped P2-type cathode and hard carbon anode shows a capacity retention rate of 85.6% after 100 cycles.This study provides new insight into the development of durable cathode materials for sodium-ion batteries.

关键词： Sodium-ion batteries Cathode material High sodium content Air stability

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A hybrid WUDT-NAFnet for simultaneous source data deblending

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Petroleum Science 2024年第3期21卷 1649-1659页

作者： Chao-Fan Ke Shao-Huan Zu Jun-Xing Cao Xu-Dong Jiang Chao Li Xing-Ye Liu Key Laboratory of Earth Exploration and Information technology of Ministry of Education Chengdu University of Technology State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of Technology College of Geophysics Chengdu University of Technology

Simultaneous source technology, which reduces seismic survey time and improves the quality of seismic data by firing more than one source with a narrow time interval, is compromised by the massive blended interference. Therefore, deblending algorithms have been developed to separate this interference.Recently, deep learning(DL) has been proved its great potential in suppressing the interference. The most popular DL method employs neural network as a filter to attenuate the blended noise in an iterative estimation and subtraction framework(IESF). However, there are still amplitude distortion and blended noise residual problems, especially when dealing with weak signal submerged in strong interference. To address these problems, we propose a hybrid WUDT-NAFnet, which contains two sub-networks. The first network is a wavelet based U-shape deblending transformer network(WUDTnet), incorporated into IESF as a robust regularization term to iteratively separate the blended interference. The second network is a nonlinear activate free network(NAFnet) designed to recover the event amplitude and further suppress the weak noise residual in IESF. With the hybrid network, the blended noise can be separated purposefully and accurately. Examples using synthetic and field seismic data demonstrate that the WUDTNAFnet outperforms traditional curvelet transform(CT) based method and the deblending transformer(DT) model in terms of deblending. Additionally, for field applications, the data augmentation method of bicubic interpolation is applied to mitigate the feature difference between synthetic and field data.Consequently, the trained network exhibits strong signal preservation ability in numerical field example without requiring additional training.

关键词： Simultaneous-source Deblending Deep learning Transformer

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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Journal of Computer Science & technology 2024年第2期39卷 245-266页

作者：廖小飞赵文举金海姚鹏程黄禹王庆刚赵进郑龙张宇邵志远 National Engineering Research Center for Big Data technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graph processing has been widely used in many scenarios,from scientific computing to artificial intelligence.Graph processing exhibits irregular computational parallelism and random memory accesses,unlike traditional workloads.Therefore,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph algorithm.While domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software codesigns.This article presents a graph processing ecosystem from hardware to software.We start by introducing a series of hardware accelerators as the foundation of this ecosystem.Subsequently,the codesigned parallel graph systems and their distributed techniques are presented to support graph applications.Finally,we introduce our efforts on novel graph applications and hardware architectures.Extensive results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

关键词： graph processing hardware accelerator software system high performance ecosystem

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Fixed-time stabilization of output-constrained stochastic high-order nonlinear systems

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Science China(Information Sciences) 2024年第4期67卷 5-20页

作者： Ruiming XIE Shengyuan XU Nanjing university of Science and technology School of Automation

In this study, the fixed-time stabilization problem of stochastic high-order nonlinear systems with output constraint and high-order and low-order nonlinearities is addressed. A new coordinate transformation is employed to directly convert output-constrained stochastic systems into an equivalent unconstrained form.By fully extracting the characteristics of system nonlinearities and using the stochastic fixed-time stability theorem, a new design and analysis method is constructed to guarantee that the trivial solution of the closed-loop system is stochastically fixed-time stable while fulfilling the output constraint.

关键词： stochastic high-order nonlinear system outputconstraint high-order and low-order nonlinearity fixed-timestabilization finite-time stabilization

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Reorganization of 3D genome architecture provides insights into pathogenesis of early fatty liver disease in laying hens

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Journal of Animal Science and Biotechnology 2024年第3期15卷 1086-1100页

作者： Yanli Liu Zhuqing Zheng Chaohui Wang Yumeng Wang Xi Sun Zhouzheng Ren Xin Yang Xiaojun Yang College of Animal Science and technology Northwest A&F UniversityYangling 712100China Institute of Agricultural Biotechnology Jingchu University of TechnologyJingmen 448000China

Background Fatty liver disease causes huge economic losses in the poultry industry due to its high occurrence and lethality rate.Three-dimensional(3D)chromatin architecture takes part in disease processing by regulating tran-scriptional reprogramming.The study is carried out to investigate the alterations of hepatic 3D genome and H3K27ac profiling in early fatty liver(FLS)and reveal their effect on hepatic transcriptional reprogramming in laying hens.Results Results show that FLS model is constructed with obvious phenotypes including hepatic visible lipid deposi-tion as well as higher total triglyceride and cholesterol in serum.A/B compartment switching,topologically associat-ing domain(TAD)and chromatin loop changes are identified by high-throughput/resolution chromosome conforma-tion capture(HiC)technology.Targeted genes of these alternations in hepatic 3D genome organization significantly enrich pathways related to lipid metabolism and hepatic damage.H3K27ac differential peaks and differential expres-sion genes(DEGs)identified through RNA-seq analysis are also enriched in these pathways.Notably,certain DEGs are found to correspond with changes in 3D chromatin structure and H3K27ac binding in their promoters.DNA motif analysis reveals that candidate transcription factors are implicated in regulating transcriptional reprogram-ming.Furthermore,disturbed folate metabolism is observed,as evidenced by lower folate levels and altered enzyme expression.Conclusion Our findings establish a link between transcriptional reprogramming changes and 3D chromatin struc-ture variations during early FLS formation,which provides candidate transcription factors and folate as targets for FLS prevention or treatment.

关键词： 3D chromatin architecture Fatty liver disease Folate H3K27ac profiling Transcription reprogramming

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Quantum key distribution over a mimicked dynamic-scattering channel

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Science China(Information Sciences) 2024年第4期67卷 323-330页

作者： Qi-Hang LU Fang-Xiang WANG Wei CHEN Hai-Yang FU Yin-Jie LU Shuang WANG De-Yong HE Zhen-Qiang YIN Guang-Can GUO Zheng-Fu HAN CAS Key Laboratory of Quantum Information University of Science and Technology of China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei National Laboratory University of Science and Technology of China

Free-space quantum key distribution(QKD) plays an important role in the global quantum network. However, free space channels suffer from the atmospheric turbulence and scattering effects of haze,fog, and dust, which significantly weaken the performance of QKD or even block the secure quantum link.Here, we prove the performance of QKD over a dynamic scattering channel can be enhanced significantly using a fast wavefront shaping technique. The system achieves on average 10-dB enhancement of quantum transmission efficiency and establishes a secure quantum link for QKD. Our work demonstrates the feasibility of QKD through free-space dynamic scattering channels and enhances the deployment capability of complex-channel QKD system.

关键词： quantum key distribution free space channel channel turbulence channel scattering wavefront shaping

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Span-based joint entity and relation extraction augmented with sequence tagging mechanism

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Science China(Information Sciences) 2024年第5期67卷 84-98页

作者： Bin JI Shasha LI Hao XU Jie YU Jun MA Huijun LIU Jing YANG College of Computer National University of Defense Technology

Span-based joint extraction simultaneously conducts named entity recognition(NER) and relation extraction(RE) in a text span form. However, since previous span-based models rely on span-level classifications, they cannot benefit from token-level label information, which has been proven advantageous for the task. In this paper, we propose a sequence tagging augmented span-based network(STSN), a spanbased joint model that can make use of token-level label information. In STSN, we construct a core neural architecture by deep stacking multiple attention layers, each of which consists of three basic attention units.On the one hand, the core architecture enables our model to learn token-level label information via the sequence tagging mechanism and then uses the information in the span-based joint extraction; on the other hand, it establishes a bi-directional information interaction between NER and RE. Experimental results on three benchmark datasets show that STSN consistently outperforms the strongest baselines in terms of F1,creating new state-of-the-art results.

关键词： joint extraction named entity recognition relation extraction span sequence tagging mechanism

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Research progress and prospects on the formation mechanism of macrosegregation and shrinkage porosity in large steel ingots

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Progress in Natural Science:Materials International 2024年第3期34卷 470-481页

作者： Xiang Liu Chaojie Zhang Shaowei Hu Liqiang Zhang Haichuan Wang School of Metallurgical Engineering Anhui University of Technology

Macrosegregation and shrinkage porosity in large steel ingots are key factors restricting the homogenization of large cast and forged parts. Due to the complex mechanisms of their formation, they have always been challenging issues in the research on solidification control of large steel ingots. The purpose of this review is to systematically revisit the research progress on the mechanisms of macrosegregation and shrinkage porosity formation in large steel ingots, focusing on the mechanisms of formation of 'A' type segregation, positive segregation at the top, and negative segregation at the bottom, and their impact on the quality of steel ingots. At the same time, the conditions and influencing factors for the formation of shrinkage porosity are analyzed in detail, and the interaction between macrosegregation and shrinkage porosity during the solidification process of steel ingots is discussed.Based on existing research results and challenges, prospects for future research directions are proposed,emphasizing the development of high-precision numerical simulation techniques and experimental research methods to deeply understand the internal mechanisms of segregation and porosity formation, providing a scientific basis for formulating effective control strategies.

关键词： Large steel ingot Macrosegregation Mathematical model Shrinkage porosity Solidification process

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