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Four decades of full-scale nitrous oxide emission inventory in China

National Science Review 2024年第3期11卷 137-149页

作者： Minqi Liang Zheyan Zhou Peiyang Ren Han Xiao Xu-Ri Zhongmin Hu Shilong Piao Hanqin Tian Qing Tong Feng Zhou Jing Wei Wenping Yuan School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University State Key Laboratory of Tibetan Plateau Earth System Resources and Environment Institute of Tibetan Plateau Research Chinese Academy of Sciences Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province Hainan University Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking University Schiller Institute for Integrated Science and Society Department of Earth and Environmental Sciences Boston College Institute of Energy Environment and Economy Tsinghua University Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)

China is among the top nitrous oxide（N2O）-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade（1980–2020） of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4（1774.8–2799.9） Gg N2O yr-1in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry,energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020,respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture,industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3（290.3–344.1） Gg N2O yr-1in 1980 to 376.2（335.5–407.2） Gg N2O yr-1in 2020. Our study produces a Full-scale Annual N2O dataset in China（FAN2020）, providing emergent counting to refine the current national N2O inventories.

关键词： nitrous oxide four decades anthropogenic sources natural sources

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An Entity Relation Extraction Framework Based on Large Language Model and Multi-Tasks Iterative Prompt engineering

An Entity Relation Extraction Framework Based on Large Langu...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Geng, Haibin Shi, Chenglong Jiang, Xuesong Kong, Zan Liu, Song Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781665410205

Document-level entity relation extraction is an important task in the field of natural language processing, which plays an important role in semantic understanding and knowledge graph construction. However, existing deep neural networks and graph neural networks models are limited by their performance and parameters number, which can not capture global semantics and have poor generalization ability. Furthermore, existing methods employing large language model for entity relation extraction do not establish good relationships among multi-tasks of entity relation extraction task, resulting in more information can not be effectively shared and transmitted between tasks. In addition, previous approaches can not effectively eliminate false entities and relationships. To solve these problems, we propose an entity relation extraction framework based on large language model and multi-tasks iterative prompt engineering. In our model, we design an iterative prompt engineering, which can better establish the relationship among multi-tasks, and ensure every task to obtain the optimal results. Moreover, we design semantic merging, group disambiguation and self-verification modules to eliminate the false entity relations and noise nodes. Additionally, we design summary prompts to provide sufficient global semantics for better text segmentation. Finally, we evaluated our model on wikiann, wikineural, ACE2005, CoNLL2003, CoNLL2004, and SciERC datasets and compared it with other baseline models. © 2024 IEEE.

关键词： Graph neural networks

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Nondestructive technique for identifying nuclides using neutron resonance transmission analysis at CSNS Back-n

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Nuclear Science and Techniques 2024年第1期35卷 178-187页

作者： Sheng-Da Tang Yong-Hao Chen Jing-Yu Tang Rui-Rui Fan Qiang Li Gong Li Dong Liu Zheng-Yao Jin Xing-Zhu Cui Tian-Xiang Chen Yi-Wei Yang Rong Liu Han Yi Yang Li Zhen Yang Qi An Hao-Fan Bai Jiang-Bo Bai Jie Bao Ping Cao Qi-Ping Chen Zhen Chen Zeng-Qi Cui An-Chuan Fan Chang-Qing Feng Fan-Zhen Feng Ke-Qing Gao Min-Hao Gu Chang-Cai Han Zi-Jie Han Guo-Zhu He Yong-Cheng He Yang Hong Yi-Wei Hu Han-Xiong Huang Wei-Hua Jia Hao-yu Jiang Wei Jiang Zhi-jie Jiang Ling Kang Bo Li Chao Li Jia-Wen Li Xiao Li Jie Liu Shu-Bin Liu Guang-Yuan Luan Chang-Jun Ning Bin-Bin Qi Jie Ren Zhi-Zhou Ren Xi-Chao Ruan Zhao-Hui Song Kang Sun Zhi-Xin Tan Li-Jiao Wang Peng-Cheng Wang Zhao-Hui Wang Zhong-Wei Wen Xiao-Guang Wu Xuan Wu Li-Kun Xie Yong-Ji Yu Guo-Hui Zhang Lin-Hao Zhang Mo-Han Zhang Qi-Wei Zhang Xian-Peng Zhang Yu-Liang Zhang Yue Zhang Zhi-Yong Zhang Mao-Yuan Zhao Lu-Ping Zhou Zhi-Hao Zhou Ke-Jun Zhu Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen UniversityZhuhai 519082China Institute of High-Energy Physics Chinese Academy of Sciences(CAS)Beijing 100049China Spallation Neutron Source Science Center Dongguan 523803China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Particle Detection and Electronics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China USTC Archaeometry Laboratory University of Science and Technology of ChinaHefei 230026China Institute of Nuclear Physics and Chemistry China Academy of Engineering PhysicsMianyang 621900China Department of Modern Physics University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Nuclear Physics and Technology School of PhysicsPeking UniversityBeijing 100871China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China Northwest Institute of Nuclear Technology Xi’an 710024China University of Chinese Academy of Sciences Beijing 100049China

Nondestructive and noninvasive neutron assays are essential applications of neutron *** resonance transmission analysis(NRTA)is a powerful nondestructive method for investigating the elemental composition of an *** back-streaming neutron line(Back-n)is a newly built time-of-flight facility at the China Spallation Neutron Source(CSNS)that provides neutrons in the eV to 300 MeV range.A feasibility study of the NRTA method for nuclide identification was conducted at the CSNS Back-n via two test *** results demonstrate that it is feasible to identify different elements and isotopes in samples using the NRTA method at *** study reveals its potential future applications.

关键词： CSNS White neutron beam NRTA Nuclide identification Nondestructive method

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Vehicle Identification Model of Expressway Service Area Based on ETC Transaction data 15th

Vehicle Identification Model of Expressway Service Area Base...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： You, Yi Zou, Fumin Cai, Qiqin Guo, Feng Fujian Provincial Key Laboratory of Automotive Electronics and Electric Drive Technology Fuzhou350118 China School of Mechanical Engineering and Automation Huaqiao University Xiamen361021 China College of Computer and Data Science Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789819700677

This paper mainly focuses on vehicle identification model of expressway service area based on ETC transaction data, First Steps, Define the time when the service area entrance RSU identifies the vehicle as the vehicle order entry time;the second step, The identification time of the RSU at the service area is the export time of the vehicle order;the third step, Determine whether the vehicle order exit time minus the vehicle order entry time is greater than or equal to the threshold time T;In Step 4, If order exit time minus order entry time is greater than or equal to threshold time T, The order vehicle is considered as the vehicle entering the service area;If order exit time minus order entry time is less than threshold time T, Think that the order vehicle did not enter the service area, For the arterial road vehicles, Based on the method and system of identifying whether the vehicle enters the service area on the expressway, ETC effectively solves the expressway service area scenario, The difficult problem of the vehicle information collection in the service area being misread by the ETC equipment in the service area. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicles

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Dual-Threshold Personalized Federated Learning Method Based on Blockchain

Dual-Threshold Personalized Federated Learning Method Based ...

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Blockchain Technology and Information Security (ICBCTIS), International Conference on

作者： Wei Liu Ying Wang Wentao Cui Wei She Zhao Tian Henan Key Laboratory of Network Cryptography Technology Zhengzhou Key Laboratory of Blockchain and Data Intelligence School of Cyber Science and Engineering Zhengzhou University Zhengzhou China School of Cyber Science and Engineering Zhengzhou University Zhengzhou China SongShan Laboratory School of Cyber Science and Engineering Zhengzhou University Zhengzhou China Zhengzhou Key Laboratory of Blockchain and Data Intelligence School of Cyber Science and Engineering Zhengzhou University Zhengzhou China

ISBN: (数字)9798331528324

ISBN: (纸本)9798331528331

Federated learning has emerged as the forefront of research in recent years. However, its distributed framework poses a risk of a single point of failure in data research. Moreover, distinguishing malicious clients in the process of realizing personalized federated learning through client similarity is a critical concern. To overcome the aforementioned problems, we recommend a blockchain-based, dual-threshold personalized federated learning approach. Blockchain is used to replace the central server in the traditional federated learning framework. And we design a double-threshold-based malicious client screening algorithm, which achieves final malicious client identification by establishing screening criteria on both the blockchain side and the client side. The experimental findings demonstrate that the suggested technique maintains good accuracy and convergence even in the presence of malicious clients, compared to the FedAvg algorithm.

关键词： Accuracy Federated learning Filtering Information security Benchmark testing Blockchains Servers Convergence

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Design and Implementation of an Automated APK Analysis System for Practical Forensics 13th

Design and Implementation of an Automated APK Analysis Syste...

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13th International Conference on Computer engineering and Networks, CENet 2023

作者： Li, Yicheng Liang, Guangjun Tang, keyan Teng, Yijia Ruan, Haoran Mo, Zixi Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing China

ISBN: (纸本)9789819992386

In order to cope with the widespread emergence of malicious APK in the application market and the increasingly rampant situation of mobile malware, as well as to meet the needs of the actual forensics work, this paper, based on the analysis of Android security mechanisms and their security problems, analyses and summarises the methodological principles, main technologies and functional flaws of existing APK automated analysis tools, and proposes an APK automated analysis system for actual forensics. Compared with traditional systems, the system is easy to operate and has a higher recognition accuracy rate. Besides, it will perform machine learning on the analysis results and calculate the similarity through the model to effectively assist the forensic work and fill the demand for APK analysis in the field of combat. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Malware

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FedDGL: Federated Dynamic Graph Learning for Temporal Evolution and data Heterogeneity 16

FedDGL: Federated Dynamic Graph Learning for Temporal Evolut...

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16th Asian Conference on Machine Learning, ACML 2024

作者： Xie, Zaipeng Li, Likun Chen, Xiangbin Yu, Hao Huang, Qian Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China College of Artificial Intelligence and Automation Hohai University Nanjing China

Federated graph learning enhances federated learning by enabling privacy-preserving collaborative training on distributed graph data. While traditional methods are effective in managing data heterogeneity, they typically assume static graph structures, overlooking the dynamic nature of real-world graphs. Integrating federated graph learning with dynamic graph neural networks addresses this issue but often fails to retain previously acquired knowledge, limiting generalization for both global and personalized models. This paper proposes FedDGL, a novel framework designed to address temporal evolution, and data heterogeneity in federated dynamic graph learning. Unlike conventional approaches, FedDGL captures temporal dynamics through a global knowledge distillation technique and manages client heterogeneity using a global prototype-based regularization method. The framework employs contrastive learning to generate global prototypes, enhancing feature representation while utilizing a prototype similarity-based personalized aggregation strategy for effective adaptation to local and global data distributions. Experiments on multiple benchmark datasets show that FedDGL achieves significant performance improvements over state-of-the-art methods, with up to 9.02% and 8.77% gains in local and global testing, respectively, compared to FedAvg. These results highlight FedDGL’s effectiveness in improving personalized and global model performance in dynamic, heterogeneous federated graph learning scenarios. © 2024 Z. Xie, L. Li, X. Chen, H. Yu & Q. Huang.

关键词： Dynamic Graph Learning Federated Graph Learning knowledge Distillation Personalized Aggregation Prototype Learning Temporal Evolution

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A Police UAV System Based on Target Recognition 13th

A Police UAV System Based on Target Recognition

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13th International Conference on Computer engineering and Networks, CENet 2023

作者： Qiu, Zhenyu Liang, Guangjun Du, Hongtian Yan, Bohan Peng, Jiahao Ju, Zexin Department of Computer Information and Cyber Security Jiangsu Police Institute Nanjing China Engineering Research Center of Electronic Data Forensics Analysis Nanjing China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu Province Nanjing China

ISBN: (纸本)9789819992386

The As a kind of aircraft without carrying operators, unmanned aerial vehicle (UAV) has been rapidly developed in the civil field. It is widely used in police, urban management, agriculture, geology, meteorology, electric power, disaster relief and other industries. However, the current police UAV still has shortcomings in specific target recognition and tracking. Therefore, the police UAV equipped with target recognition technology is designed in this project to enhance its performance. The project also investigates the materials and structure of police UAV, and focuses on target recognition systems which use sensors and algorithms to identify, classify and track targets, providing support for autonomous navigation and surveillance of UAV. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Python

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Measuring drug similarity using drug–drug interactions

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Quantitative Biology 2024年第2期12卷 164-172页

作者： Ji Lv Guixia Liu Yuan Ju Houhou Huang Ying Sun College of Computer Science and Technology Jilin UniversityChangchunChina Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina Sichuan University Library Sichuan UniversityChengduChina College of Chemistry Jilin UniversityChangchunChina Department of Respiratory Medicine The First Hospital of Jilin UniversityChangchunChina

Combination therapy is a promising approach to address the challenge of antimicrobial resistance,and computational models have been proposed for predicting drug–drug *** existing models rely on drug similarity measures based on characteristics such as chemical structure and the mechanism of *** this study,we focus on the network structure itself and propose a drug similarity measure based on drug–drug interaction *** explore the potential applications of this measure by combining it with unsupervised learning and semi-supervised learning *** unsupervised learning,drugs can be grouped based on their interactions,leading to almost monochromatic group–group *** addition,drugs within the same group tend to have similar mechanisms of action(MoA).In semi-supervised learning,the similarity measure can be utilized to construct affinity matrices,enabling the prediction of unknown drug–drug *** method exceeds existing approaches in terms of ***,our experiments demonstrate the effectiveness and practicability of the proposed similarity *** the one hand,when combined with clustering algorithms,it can be used for functional annotation of compounds with unknown *** the other hand,when combined with semi-supervised graph learning,it enables the prediction of unknown drug–drug interactions.

关键词： drug similarity drug–drug interactions drug combinations synergy effect clustering semi-supervised learning

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Spectroscopy and molecule opacity investigation on excited states of SiS

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Chinese Physics B 2024年第5期33卷 381-387页

作者：李瑞吕浩男桑纪群刘晓华梁桂颖吴勇 College of Teacher Education Qiqihar UniversityQiqihar 161006China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Department of Physics College of ScienceQiqihar UniversityQiqihar 161006China School of Data Science and Artificial Intelligence Jilin Engineering Normal UniversityChangchun 130052China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100084China

The SiS molecule,which plays a significant role in space,has attracted a great deal of attention for many *** to complex interactions among its low-lying electronic states,precise information regarding the molecular structure of SiS is *** obtain accurate information about the structure of its excited states,the high-precision multireference configuration interaction(MRCI)method has been *** method is used to calculate the potential energy curves(PECs)of the 18Λ–S states corresponding to the lowest dissociation limit of *** core–valence correlation effect,Davidson’s correction and the scalar relativistic effect are also included to guarantee the precision of the MRCI *** on the calculated PECs,the spectroscopic constants of quasi-bound and bound electronic states are calculated and they are in accordance with previous experimental *** transition dipole moments(TDMs)and dipole moments(DMs)are determined by the MRCI *** addition,the abrupt variations of the DMs for the 1^(5)Σ^(+)and 2^(5)Σ^(+)states at the avoided crossing point are attributed to the variation of the electronic *** opacity of SiS at a pressure of 100 atms is presented across a series of *** increasing temperature,the expanding population of excited states blurs the band boundaries.

关键词： SiS opacity excited state spectroscopic constant configuration interaction

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