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Line-of-shower trigger method to lower energy threshold for GRB detection using LhAASO-WcDA

Radiation Detection Technology and Methods 2021年第4期5卷 531-541页

作者： F.Aharonian Q.An Axikegu L.X.Bai Y.X.Bai Y.W.Bao D.Bastieri X.J.Bi Y.J.Bi h.cai J.T.cai Z.cao Z.cao J.chang J.F.chang X.c.chan B.M.chen J.chen L.chen L.chen L.chen M.J.chen M.L.chen Q.h.chen S.h.chen S.Z.chen T.L.chen X.L.chen Y.chen N.chen Y.D.chen S.W.cui X.h.cui Y.D.cui B.Z.Dai h.L.Dai Z.G.Dai Danzengluobu D.della Volpe B.D’Ettorre Piazzoli X.J.Don J.h.Fan Y.Z.Fan Z.X.Fan J.Fang K.Fan c.F.Feng L.Feng S.h.Fen Y.L.Feng B.Gao c.D.Gao Q.Gao W.Gao M.M.Ge L.S.Gen G.h.Gong Q.B.Gou M.h.Gu J.G.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.han h.h.he h.N.he J.c.he S.L.he X.B.he Y.he M.heller Y.K.hor c.hou X.hou h.B.hu S.hu S.c.hu X.J.hu D.h.huang Q.L.huan W.h.huang X.T.huang Z.c.huang F.Ji X.L.Ji h.Y.Jia K.Jiang Z.J.Jiang c.Jin D.Kuleshov K.Levochkin B.B.Li c.Li c.Li F.Li h.B.Li h.c.Li h.Y.Li J.Li K.Li W.L.Li X.Li X.Li X.R.Li Y.Li Y.Z.Li Z.Li Z.Li E.W.Liang Y.F.Liang S.J.Lin B.Liu c.Liu D.Liu h.Liu h.D.Liu J.Liu J.L.Liu J.S.Liu J.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.N.Liu Z.X.Liu W.J.Long R.Lu h.K.Lv B.Q.Ma L.L.Ma X.h.Ma J.R.Mao A.Masood W.Mitthumsiri T.Montaruli Y.c.Nan B.Y.Pang P.Pattarakijwanich Z.Y.Pei M.Y.Qi D.Ruffolo V.Rulev A.Sáiz L.Shao O.Shchegolev X.D.Shen J.R.Shi h.c.song Yu.V.Stenkin V.Stepanov Q.N.Sun X.N.Sun Z.B.Sun P.h.T.Tam Z.B.Tang W.W.Tian B.D.Wan c.Wang h.Wang h.G.Wang J.c.Wang J.S.Wang L.P.Wang L.Y.Wan R.N.Wang W.Wang W.Wang X.G.Wang X.J.Wan X.Y.Wang Y.D.Wan Y.J.Wan Y.P.Wang Z.Wang Z.Wang Z.h.Wang Z.X.Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen c.Y.Wu h.R.Wu S.Wu W.X.Wu X.F.Wu S.Q.Xi J.Xia J.J.Xia G.M.Xiang G.Xiao h.B.Xiao G.G.Xin Y.L.Xin Y.Xing D.L.Xu R.X.Xu L.Xue D.h.Yan c.W.Yang F.F.Yang J.Y.Yang L.L.Yang M.J.Yan R.Z.Yang S.B.Yang Y.h.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.h.You Z.Y.You Y.h.Yu Q.Yuan h.D.Zeng T.X.Zeng W.Zeng Z.K.Zeng M.Zha X.X.Zhai B.B.Zhang h.M.Zhang h.Y.Zhang J.L.Zhang J.W.Zhang L.Zhang L.Zhang L.X.Zhang P.F.Zhang P.P.Zhang R.Zhang S.R.Zhang S.S.Zhan X.Zhang X.P.Zhan Y.Zhan Y.Zhang Y.F.Zhang Y.L.Zhan B.Zhao J.Zhao L.Zhao L.Z.Zhao S.P.Zhao F.Zheng Y.Zheng B.Zhou h.Zhou J.N.Zhou P.Zhou R.Zhou X.X.Zhou c.G. Key Laboratory of Particle Astrophysics&Experimental Physics Division&computing center Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of chinese Academy of Sciences Beijing 100049China TIANFU cosmic Ray Research center ChengduSichuanChina State Key Laboratory of Particle Detection and Electronics BeijingChina University of Science and Technology of china Hefei 230026AnhuiChina Department of Engineering Physics Tsinghua UniversityBeijing 100084China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China National Space Science center Chinese Academy of SciencesBeijing 100190China School of Physics Peking UniversityBeijing 100871China center for Astrophysics Guangzhou UniversityGuangzhou 510006GuangdongChina School of Physics and Astronomy&School of Physics(Guangzhou) Sun Yat-sen UniversityZhuhai 519000GuangdongChina School of Physical Science and Technology Guangxi UniversityNanning 530004GuangxiChina hebei Normal University Shijiazhuang 050024HebeiChina School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001HenanChina School of Astronomy and Space Science Nanjing UniversityNanjing 210023JiangsuChina Key Laboratory of Dark Matter and Space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023JiangsuChina Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237ShandongChina Key Laboratory for Research in Galaxies and cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031SichuanChina college of Physics Sichuan UniversityChengdu 610065SichuanChina Key Laboratory of cosmic Rays(Tibet University) Ministry of EducationLhasa 850000TibetChina School of Physic

Purpose Observation of high energy and very high emission from Gamma Ray Bursts(GRBs)is crucial to study the gigantic explosion and the underline *** a large field-of-view and almost full duty cycle,the Water cherenkov Detector Array(WcDA),a sub-array of the Large high Altitude Air Shower Observatory(LhAASO),is appropriate to monitor the very high energy emission from unpredictable transients such as *** Nevertheless,the main issue for an extensive air shower array is the high energy threshold which limits the horizon of the *** address this issue a new trigger method is developed in this article to lower the energy threshold of WcDA for GRB *** The proposed method significantly improves the detection efficiency of WcDA for gamma-rays around the GRB direction at 10-300 *** sensitivity of the WcDA for GRB detection with the new trigger method is *** achieved sensitivity of the quarter WcDA array above 10 GeV is comparable with that of *** data analysis process and corresponding fluence upper limit for GRB 190719c is presented as an example.

关键词： LhAASO WcDA GRB

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A dynamic range extension system for LhAASOWcDA-1

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Radiation Detection Technology and Methods 2021年第4期5卷 520-530页

作者： F.Aharonian Q.An Axikegu L.X.Bai Y.X.Bai Y.W.Bao D.Bastieri X.J.Bi Y.J.Bi h.cai J.T.cai Z.cao Z.cao J.chang J.F.chang X.c.chang B.M.chen J.chen L.chen L.chen L.chen M.J.chen M.L.chen Q.h.chen S.h.chen S.Z.chen T.L.chen X.L.chen Y.chen N.cheng Y.D.cheng S.W.cui X.h.cui Y.D.cui B.Z.Dai h.L.Dai Z.G.Dai Danzengluobu D.della Volpe B.D’Ettorre Piazzoli X.J.Dong J.h.Fan Y.Z.Fan Z.X.Fan J.Fang K.Fang c.F.Feng L.Feng S.h.Feng Y.L.Feng B.Gao c.D.Gao Q.Gao W.Gao M.M.Ge L.S.Geng G.h.Gong Q.B.Gou M.h.Gu J.G.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.han h.h.he h.N.he J.c.he S.L.he X.B.he Y.he M.heller Y.K.hor c.hou X.hou h.B.hu S.hu S.c.hu X.J.hu D.h.huang Q.L.huang W.h.huang X.T.huang Y.huang Z.c.huang F.Ji X.L.Ji h.Y.Jia K.Jiang Z.J.Jiang c.Jin D.Kuleshov K.Levochkin B.B.Li c.Li c.Li F.Li h.B.Li h.c.Li h.Y.Li J.Li K.Li W.L.Li X.Li X.Li X.R.Li Y.Li Y.Z.Li Z.Li Z.Li E.W.Liang Y.F.Liang S.J.Lin B.Liu c.Liu D.Liu h.Liu h.D.Liu J.Liu J.L.Liu J.S.Liu J.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.N.Liu Z.X.Liu W.J.Long R.Lu h.K.Lv B.Q.Ma L.L.Ma X.h.Ma J.R.Mao A.Masood W.Mitthumsiri T.Montaruli Y.c.Nan B.Y.Pang P.Pattarakijwanich Z.Y.Pei M.Y.Qi D.Ruffolo V.Rulev A.Sáiz L.Shao O.Shchegolev X.D.Sheng J.R.Shi h.c.song Yu.V.Stenkin V.Stepanov Q.N.Sun X.N.Sun Z.B.Sun P.h.T.Tam Z.B.Tang W.W.Tian B.D.Wang c.Wang h.Wang h.G.Wang J.c.Wang J.S.Wang L.P.Wang L.Y.Wang R.N.Wang W.Wang W.Wang X.G.Wang X.J.Wang X.Y.Wang Y.D.Wang Y.J.Wang Y.P.Wang Z.Wang Z.Wang Z.h.Wang Z.X.Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen c.Y.Wu h.R.Wu S.Wu W.X.Wu X.F.Wu S.Q.Xi J.Xia J.J.Xia G.M.Xiang G.Xiao h.B.Xiao G.G.Xin Y.L.Xin Y.Xing D.L.Xu R.X.Xu L.Xue D.h.Yan c.W.Yang F.F.Yang J.Y.Yang L.L.Yang M.J.Yang R.Z.Yang S.B.Yang Y.h.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.h.You Z.Y.You Y.h.Yu Q.Yuan h.D.Zeng T.X.Zeng W.Zeng Z.K.Zeng M.Zha X.X.Zhai B.B.Zhang h.M.Zhang h.Y.Zhang J.L.Zhang J.W.Zhang L.Zhang L.Zhang L.X.Zhang P.F.Zhang P.P.Zhang R.Zhang S.R.Zhang S.S.Zhang X.Zhang X.P.Zhang Y.Zhang Y.Zhang Y.F.Zhang Y.L.Zhang B.Zhao J.Zhao L.Zhao L.Z.Zhao S.P.Zhao F.Zheng Y.Zheng B.Zhou h.Zhou J.N.Zhou Key Laboratory of Particle Astrophyics&Experimental Physics Division&computing center Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of chinese Academy of Sciences Beijing 100049China TIANFU cosmic Ray Research center ChengduSichuanChina State Key Laboratory of Particle Detection and Electronics BeijingChina University of Science and Technology of china Hefei 230026AnhuiChina Department of Engineering Physics Tsinghua UniversityBeijing 100084China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China National Space Science center Chinese Academy of SciencesBeijing 100190China School of Physics Peking UniversityBeijing 100871China center for Astrophysics Guangzhou UniversityGuangzhou 510006GuangdongChina School of Physics and Astronomy&School of Physics(Guangzhou) Sun Yat-sen UniversityZhuhai 519000GuangdongChina School of Physical Science and Technology Guangxi UniversityNanning 530004GuangxiChina hebei Normal University Shijiazhuang 050024HebeiChina School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001HenanChina School of Astronomy and Space Science Nanjing UniversityNanjing 210023JiangsuChina Key Laboratory of Dark Matter and Space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023JiangsuChina Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237ShandongChina Key Laboratory for Research in Galaxies and cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031SichuanChina college of Physics Sichuan UniversityChengdu 610065SichuanChina Key Laboratory of cosmic Rays(Tibet University) Ministry of EducationLhasa 850000TibetChina School of Physics

Purpose The main scientific goal of LhAASO-WcDA is to survey gamma-ray sources with energy from 100 GeV to 30 *** observe high-energy shower events,especially to measure the energy spectrum of cosmic rays from 100 TeV to 10 PeV,a dynamic range extension system(WcDA++)is designed to use a 1.5-inch PMT with a dynamic range of four orders of magnitude for each cell in *** The dynamic range is extended by using these PMTs to measure the effective charge density in the core region of air shower events,which is an important parameter for identifying the composition of primary *** and conclusion The system has been running for more than one *** this paper,the details of the design and performance of WcDA++are presented.

关键词： LhAASO-WcDA WcDA++ Water cherenkov detector Performance

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Dissecting the cell microenvironment of ovarian endometrioma through single-cell RNA sequencing

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Science china Life Sciences 2025年第1期68卷 116-129页

作者： Jiangpeng Wu Siyu Xia Wenting Ye Yan Sun Jing cai Fubing Yu haiping Wen Xiuwei Yi Taikang Li Mingwei chen Jiayun chen Ge song chuanbin Yang Yali song Jigang Wang Department of Reproductive Medicine Dongguan Maternal and Child Health Care Hospital Department of Urology and Shenzhen Clinical Research Centre for GeriatricsShenzhen People's HospitalSouthern University of Science and Technology State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di herbs Artemisinin Research Centerand Institute of Chinese Materia MedicaChina Academy of Chinese Medical Sciences Reproductive Medicine center Foshan Women and Children Hospital State Key Laboratory of Antiviral Drugs School of PharmacyHenan University

Ovarian endometrioma（OE）, also known as “chocolate cysts,” is a cystic mass that develops in the ovaries due to endometriosis and is a common gynecological condition characterized by the growth of endometrial tissue outside the uterus, leading to symptoms such as dysmenorrhea, pelvic pain, and infertility. however, the precise molecular and cellular mechanisms driving this pathophysiology remain largely unknown, posing challenges for diagnosis and treatment. here, we employed integrated single-cell transcriptomic profiling of over 52,000 individual cells from endometrial tissues of OE patients and healthy donors and identified twelve major cell populations. We identified notable alterations in cell type-specific proportions and molecular signatures associated with OE. Notably, the activation of IGFBP5+macrophages with pro-inflammatory properties, NK cell exhaustion, and aberrant proliferation of IQcG+and KLF2+epithelium are key features and may be the potential mechanisms underlying the pathogenesis of OE. collectively, our data contribute to a better understanding of OE at the single cell level and may pave the way for the development of novel therapeutic strategies.

关键词： ovary high-throughput sequencing transcriptomics gene expression analysis ligand-receptor analysis

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Research progress of catalysts for direct coal liquefaction

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Journal of Energy chemistry 2025年第1期100卷 481-497页

作者： Wei song Penggao Liu Xinyue chen Ting Wang chunrong he Rui hao Kaiyu Liu State Key Laboratory of chemistry and Utilization of carbon Based Energy Resources College of Chemistry Xinjiang University college of chemistry and chemical Engineering Henan Polytechnic University hunan Provincial Key Laboratory of chemical Power Sources College of Chemistry and Chemical Engineering Central South University

coal direct liquefaction technology is a crucial contemporary coal chemical technology for efficient and clean use of coal resources. The development of direct coal liquefaction technology and the promotion of alternative energy sources are important measures to guarantee energy security and economic security. however, several challenges need to be addressed, including low conversion rate, inadequate oil yield, significant coking, demanding reaction conditions, and high energy consumption. Extensive research has been conducted on these issues, but further exploration is required in certain aspects such as pyrolysis of macromolecules during the liquefaction process, hydrogen activation, catalysts' performance and stability, solvent hydrogenation, as well as interactions between free radicals to understand their mechanisms better. This paper presents a comprehensive analysis of the design strategy for efficient catalysts in coal liquefaction, encompassing the mechanism of coal liquefaction, catalyst construction,and enhancement of catalytic conversion efficiency. It serves as a comprehensive guide for further research endeavors. Firstly, it systematically summarizes the conversion mechanism of direct coal liquefaction, provides detailed descriptions of various catalyst design strategies, and especially outlines the catalytic mechanism. Furthermore, it addresses the challenges and prospects associated with constructing efficient catalysts for direct coal liquefaction based on an understanding of their action mechanisms.

关键词： Direct coal liquefaction catalysts Mechanism of action Solvent hydrogenation

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Synergistically S/N self-doped biochar as a green bifunctional cathode catalyst in electrochemical degradation of organic pollutant

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Green Energy & Environment 2025年第1期10卷 214-230页

作者： Xuechun Wang huizhong Wu Jiana Jing Ge song Xuyang Zhang Minghua Zhou Raf Dewil Key Laboratory of Pollution Process and Environmental criteria Ministry of EducationCollege of Environmental Science and EngineeringNankai UniversityTianjin300350China Tianjin Key Laboratory of Environmental Technology for complex Trans-Media Pollution Nankai UniversityTianjin300350China Tianjin Advanced Water Treatment Technology International Joint Research center College of Environmental Science and EngineeringNankai UniversityTianjin300350China Department of chemical Engineering KU LeuvenJ.De Nayerlaan 5Sint-Katelijne-Waver B2860Belgium

Biomass-derived heteroatom self-doped cathode catalysts has attracted considerable interest for electrochemical advanced oxidation processes(EAOPs)due to its high performance and sustainable ***,we illustrated the morphological fates of waste leaf-derived graphitic carbon(WLGc)produced from waste ginkgo leaves via pyrolysis temperature regulation and used as bifunctional cathode catalyst for simultaneous h_(2)O_(2) electrochemical generation and organic pollutant degradation,discovering S/N-self-doping shown to facilitate a synergistic effect on reactive oxygen species(ROS)*** the optimum temperature of 800℃,the WLGc exhibited a h_(2)O_(2) selectivity of 94.2%and tetracycline removal of 99.3%within 60 *** functional theory calculations and in-situ Fourier transformed infrared spectroscopy verified that graphitic N was the critical site for h_(2)O_(2) *** pyridinic N and thiophene S were the main active sites responsible for_Oh generation,N vacancies were the active sites to produce ^(1)O_(2) from *** performance of the novel cathode for tetracycline degradation remains well under a wide ph range(3–11),maintaining excellent stability in 10 *** is also industrially applicable,achieving satisfactory performance treating in real water *** system facilitates both radical and non-radical degradation,offering valuable advances in the preparation of cost-effective and sustainable electrocatalysts and hold strong potentials in metal-free EAOPs for organic pollutant degradation.

关键词： Biochar S and N self-doping h_(2)O_(2)production In-situ FTIR Metal-free electrochemical advanced oxidation processes

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All-optical neuromorphic devices: materials, working mechanism,and applications

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Science china chemistry 2025年

作者： song Wang hao chen hui huang college of Materials Science and Opto-Electronic Technology Center of Materials Science and Optoelectronics Engineering CAS Center for Excellence in Topological Quantum Computation CAS Key Laboratory of Vacuum Physics University of Chinese Academy of Sciences college of chemistry and Molecular Engineering Peking University

Traditional von Neumann computing, with physical separation of memory and processing units, cannot satisfy the development of artificial intelligence and cloud computing. Neuromorphic computing, inspired by the human brain, has drawn much ***-optical neuromorphic (AON) devices employ optical signals as information carriers and leverage the neuromorphic functions to implement fast operation speed, low energy consumption, and high bandwidth of neuromorphic computing. here, we discuss the recent progress in AON devices, including materials, device performance, working mechanisms, and applications. Moreover,the advantages and limitations of AON are presented and discussed. Finally, the perspective of AON devices points out the future research direction of neuromorphic computing.

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Electrochemical conversion of methane to bridge the gap in the artificial carbon cycle

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Journal of Energy chemistry 2025年第1期100卷 286-308页

作者： Yuhao Peng Yuefeng song Ihar Razanau Juanxiu Xiao Wei Xiao Di hu Guoxiong Wang college of chemistry and Molecular Sciences Hubei Key Laboratory of Electrochemical Power Sources Wuhan University State Key Laboratory of catalysis Dalian National Laboratory for Clean Energy iChEM (Collaborative Innovation Center of Chemistry for Energy Materials) Dalian Institute of Chemical Physics Chinese Academy of Sciences Laboratory of Physical-chemical Technologies SSPA Scientific and Practical Materials Research Centre of NAS of Belarus State Key Laboratory of Marine Resources Utilization in South china Sea Collaborative Innovation Center of Marine Science and Technology School of Marine Science and Engineering Hainan University Department of chemical and Environmental Engineering University of Nottingham Ningbo China

Methane, an abundant one-carbon（c1） resource, is extensively used in the industrial production of vital fuels and value-added chemicals. however, current industrial methane conversion technologies are energy-and carbon-intensive, mainly due to the high activation energy required to break the inert c–h bond, low selectivity, and problematic side reactions, including cO2emissions and coke deposition. Electrochemical conversion of methane（EcM） using intermittent renewable energy offers an attractive solution, due to its modular reactor design and operational flexibility across a broad spectrum of temperatures and pressures. This review emphasizes conversion pathways of methane in various reaction systems, highlighting the significance and advantages of EcM in facilitating a sustainable artificial carbon cycle. This work provides a comprehensive overview of conventional methane activation mechanisms and delineates the complete pathways of methane conversion in electrolysis contexts. Based on surface/interface chemistry, this work systematically analyzes proposed reaction pathways and corresponding strategies to enhance EcM efficiency towards various target products, including syngas, hydrocarbons, oxygenates, and advanced carbon materials. The discussion also encompasses opportunities and challenges for the EcM process, including insights into EcM pathways, rational electrocatalyst design, establishment of benchmarking protocols, electrolyte engineering, enhancement of ch4conversion rates, and minimization of cO2emission.

关键词： Activation energy

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clinical observation of white eye distribution in patients with hyperlipidemia: an artificial intelligence digital visual examination technique

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Journal of Traditional chinese Medicine 2025年

作者： song Tianli LI haixia LIU Li'an Department of cardiology， the Guang'anmen hospital， china Academy of chinese Medical Sciences National college， Beijing University of chinese Medicine

Objective: To explore the clinical observation of white eye distribution characteristics of hyperlipidemic patients based on artificial intelligence digital eye diagnosis technology. Methods: One hundred and fifty subjects were examined in the outpatient and inpatient departments of Guang'anmen hospital of the china Academy of Traditional chinese Medicine from 01 February 2022 to 01 February 2023， including 80 cases in the hyperlipidemic patient (hLP) group and 70 cases in the normal lipid level patient (Nc) group. The two groups were collected and extracted by the artificial intelligence visual diagnostic instrument and analyzed by the MyEyeD-10 white eye shadowless imaging health intelligence analysis system. Finally， SPSS 26.0 (Version X; IBM corp.， Armonk， NY， USA) was used for statistical processing. Results: Significant differences were noted in the scores of "spot" and "foggy" features between the two groups. Between groups， the "spot" feature score of the white eye morphology in the hLP group (11.07 ± 3.22) was higher than that in the Nc group (7.50 ± 4.11) (P he "foggy" feature score of the eye morphology in the hLP group (8.37 ± 2.25) was higher than that in the Nc group (P higher than that of the Nc group (5.72 ± 1.21) (P here were significant differences in the "A" (stomach)， "B"， "O" (spleen)， and "M" (liver) eye-contact region scores between the two groups， and the "B"， "O" (spleen) and "M" (liver) eye-contact region scores were significantly different. The scores of the white eye channel region in the hLP group were significantly higher than those in the control group， with the "A"， "B"， and "O" regions (P he scores of "dull red" and "yellow" features were significantly different， and the scores of "dull red" and "yellow" colors of the white eye choroid in the hLP group were significantly higher than those in the hLP g

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Satellite-assisted 6G wide-area edge intelligence:dynamics-aware task offloading and resource allocation for remote IoT services

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Science china(Information Sciences) 2025年

作者： Di ZhAO Rui DING Bin song State Key Laboratory of Integrated Services Networks Xidian University hangzhou Institute of Technology Xidian University china Satellite Network Group co. Ltd.

Future 6G networks will integrate non-terrestrial communication with mobile edge computing to enable wide-area edge intelligence, providing ubiquitous communication and computation services for everyone and everything. In this paper, we introduce the intelligent cloud-edge-device architecture into low Earth orbit (LEO) satellite-supported remote Internet of Things(IoT) networks to facilitate latency-sensitive and compute-intensive IoT applications. however, the dynamic spatio-temporal characteristics inherent in LEO satellite networks, such as the high volatility of task traffic and the high mobility of space nodes, pose severe challenges. For efficient task execution, we investigate the joint optimization of cross-region task offloading and cross-domain resource allocation, and innovatively propose a spatio-temporal attention-based proximal policy optimization(STA-PPO) algorithm. Specifically, the temporal attention-based actor network analyzes the timing dependencies of task arrival and makes time-variant decisions. Simultaneously, the spatial attention-based critic network captures the spatial variations of satellite motion and evaluates the topology-related value. We verify the effectiveness of the cloud-edge-device collaboration through extensive simulations. Numerical results demonstrate that the STA-PPO algorithm outperforms benchmarks, showing the lowest system delay and the highest link throughput.

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Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

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Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua Xu Miao Yu Yuhang song School of health Sciences and Biomedical Engineering Hebei University of TechnologyTianjinChina Department of computer Science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable

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