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Soil microbial respiration is regulated by stoichiometric imbalances: Evidence from a humidity gradient case

Pedosphere 2023年第6期33卷 905-915页

作者： Jiwei LI Jiangbo XIE Jianzhao WU Yongxing CUI Lingbo DONG Yulin LIU Xuying HAI Yan LI Zhouping SHANGGUAN Kaibo WANG Changhui PENG Lei DENG State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau College of Soil and Water Conservation Science and Engineering(Institute of Soil and Water Conservation)Northwest A&F UniversityYangling 712100China Institute of Soil and Water Conservation Chinese Academy of Sciences and Ministry of Water ResourcesYangling 712100China State Key Laboratory of Subtropical Silviculture Zhejiang A&F UniversityLin'an 311300China Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing 100871China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy of SciencesXi'an 710061China Center of CEF/ESCER Department of Biological ScienceUniversity of Quebec at MontrealMontreal H3C 3P8Canada

Humidity not only affects soil microbial respiration(SMR) directly, but, indirectly by regulating the availability of soil water and nutrients. However,the patterns of direct and indirect effects of humidity on SMR over large precipitation gradients remain unclear, limiting our understanding of the effects of precipitation changes on soil C cycle. Here, we investigated the relationships among humidity, soil nutrients, and SMR by identifying stoichiometric imbalances, microbial elemental homeostasis, and microbial C use efficiency along a precipitation gradient at a continental scale. The relationship between SMR and humidity index(HI) corresponded to a Richard’s curve with an inflection point threshold value of approximately 0.7. Soil microbial respiration increased with increasing humidity in drier areas(HI < 0.7), but tended to balance above this threshold. Increasing humidity exacerbated C:P and N:P imbalances across the selected gradient. Severe N and P limitations in soil microbial communities were observed in drier areas, while soil microbes suffered from aggravated P limitation as the humidity increased in wetter areas(HI > 0.7). Soil microbial communities regulated their enzyme production to maintain a strong stoichiometric homeostasis in drier areas;enzyme production, microbial biomass, and threshold elemental ratios were non-homeostatic under P limitation in wetter areas, which further contributed to the increase in SMR. Our results identified a moisture constraint on SMR in drier areas and highlighted the importance of nutrient(especially for P) limitations induced by humidity in regulating SMR in wetter areas. Understanding the modulation of SMR via soil enzyme activity may improve the prediction of soil C budget under future global climate change.

关键词： carbon use efficiency ecological stoichiometry microorganisms nutrient limitations precipitation soil enzyme activities stoichiometric homeostasis

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Reinforcement-Learning-Enabled Beam Alignment for Water-Air Direct Optical Wireless Communications

Reinforcement-Learning-Enabled Beam Alignment for Water-Air ...

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IEEE International Conference on Communications in China (ICCC)

作者： Jiayue Liu Tianqi Mao Dongxuan He Yang Yang Zhen Gao Dezhi Zheng Jun Zhang State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of Technology Beijing China Yangtze Delta Region Academy Beijing Institute of Technology (Jiaxing) Jiaxing China School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

The escalating interests on underwater exploration/ reconnaissance applications have motivated high-rate data transmission from underwater to airborne relaying platforms, especially under high-sea scenarios. Thanks to its broad bandwidth and superior confidentiality, Optical wireless communication has become one promising candidate for water-air transmission. However, the optical signals inevitably suffer from deviations when crossing the highly-dynamic water-air interfaces in the absence of relaying ships/buoys. To address the issue, this article proposes one novel beam alignment strategy based on deep reinforcement learning (DRL) for water-air direct optical wireless communications. Specifically, the dynamic water-air interface is mathematically modeled using sea-wave spectrum analysis, followed by characterization of the propagation channel with ray-tracing techniques. Then the deep deterministic policy gradient (DDPG) scheme is introduced for DRL-based transceiving beam alignment. A logarithm-exponential (LE) nonlinear reward function with respect to the received signal strength is designed for high-resolution rewarding between different actions. simulation results validate the superiority of the proposed DRL-based beam alignment scheme.

关键词： Wireless communication Integrated optics Water Sea surface Analytical models simulation Ray tracing

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Semantic segmentation of track image based on deep neural network

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The Journal of China Universities of Posts and Telecommunications 2020年第5期27卷 23-33页

作者： Wang Zhaoying Zhou Junhua Liao Zhonghua Zhai Xiang Zhang Lianping School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Kngineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China Alibaba Cloud Computing Beijing 100020China

In this paper,deep learning technology was utilited to solve the railway track recognition in intrusion detection *** railway track recognition can be viewed as semantic segmentation task which extends image processing to pixel level *** encoder-decoder architecture DeepLabv3+model was applied in this work due to its good performance in semantic segmentation *** images of the railway track collected from the video surveillance of the train cab were used as experiment dataset in this work,the following improvements were made to the *** first aspect deals with over-fitting problem due to the limited amount of training *** augmentation and transfer learning are applied consequently to rich the diversity of data and enhance model robustness during the training ***,different gradient descent methods are compared to obtain the optimal optimizer for training model *** third problem relates to data sample imbalance,cross entropy(CE)loss is replaced by focal loss(FL)to address the issue of serious imbalance between positive and negative *** of the improved DeepLabv3+model with above solutions is demonstrated by experiment results with different system parameters.

关键词： railway track recognition convolutional neural networks semantic segmentation DeepLabv3+

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Analysis of land-atmosphere interactions and their influence on the energy and water cycle over the Tibetan Plateau

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地球空间信息科学学报（英文版） 2024年第3期27卷 902-921页

作者： Yaoming Ma Zhongbo Su Lei Zhong Yijian Zeng Xuelong Chen Cunbo Han Binbin Wang Zhipeng Xie Weiyao Ma Longtengfei Ma Qianqian Han Ruodan Zhuang Lijie Zhang Shaoning Lv Lianyu Yu Jan Hofste Hong Zhao Jun Wen Weiqiang Ma Land-Atmosphere Interaction and its Climatic Effects Group State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijingChina College of Atmospheric Science Lanzhou UniversityLanzhouChina National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes DingriChina Kathmandu Center of Research and Education Chinese Academy of SciencesBeijingChina China-Pakistan Joint Research Center on Earth Sciences Chinese Academy of SciencesIslamabadPakistan Faculty of Geo-Information Science and Earth Observation(ITC) University of TwenteEnschedeThe Netherlands Planetary atmospheres and global change School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina Land-Atmosphere Interaction and its Climatic Effects Group State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina Department of European and Mediterranean Cultures:Architecture EnvironmentCultural HeritageUniversity of BasilicataMateraItaly Institute for Bio-and Geosciences:Agrosphere(IBG-3) Research Centre JülichJülichGermany Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences Fudan UniversityShanghaiChina College of Water Resources and Architectural Engineering Northwest Agriculture and Forestry UniversityYanglingChina College of Atmospheric Sciences Plateau Atmosphere and Environment Key Laboratory of Sichuan ProvinceChengdu University of Information TechnologyChina Land-Atmosphere Interaction and its Climatic Effects Group State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina College of Atmospheric Science Lanzhou University

The Tibetan Plateau(TP)has been the focus of numerous studies examining the energy and water cycle variations,but there is still a lack of long-term,quantitative precise assessments of *** research first provided two sets of long-term comprehensive observa-tional datasets,and an advanced monitoring technique to measure soil moisture,which can improve the estimation accuracy of ***,using microwave data,the Surface Energy Balance system model and Machine Learning methods,it calculated a complete set of long-term evapotranspiration *** the same time,based on reasonable assumptions,it also estimated the total evaporation from plateau *** findings con-tribute significantly to the understanding of the relationship between the Asian monsoon,the TP's physical characteristics,and its atmosphere,thereby improving predictions of water resource variability in the *** study's innovative methodologies and synthesis of diverse data sources provide critical information for informed and sustainable water management strategies in the region.

关键词： Tibetan Plateau in-situ observation Evapotranspiration(ET) evaporation remote sensing

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FULLY POLARIZED RADAR TARGET DETECTION AND WAVEFORM OPTIMIZATION UNDER RAINY CONDITION

FULLY POLARIZED RADAR TARGET DETECTION AND WAVEFORM OPTIMIZA...

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IET International Radar Conference 2023, IRC 2023

作者： Li, Xinda Cheng, Xu Ju, Xinjie Wang, Xuesong Li, Jianbing College of Electronic Science and Technology National University of Defense Technology Hunan Changsha410073 China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Hunan Changsha410073 China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Intelligent Robot Wuhan430205 China

ISBN: (纸本)9781839539954

Polarization and waveform optimization can significantly improve the detection ability of fully polarized radar. However, in practical scenarios, atmospheric particles frequently induce depolarization effects on radar waves, thereby influencing precise target detection, a phenomenon predominantly observed with raindrop particles. This paper establishes a target detection model for fully polarized radar in rainy condition. Subsequently, a joint transceiver iterative optimization algorithm is devised, utilizing the maximum output signal-to-interference plus noise ratio (SINR) of the system as the benchmark, and imposing dual constraints of energy and resemblance on the transmitting waveform. Ultimately, the effectiveness of the proposed method under rainy condition is validated through simulation, and recommendations for engineering applications are provided based on the analysis. © The Institution of engineering & Technology 2023.

关键词： Signal to noise ratio

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Tuning 2D magnetism in Fe3+XGeTe2 films by element doping

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National Science Review 2022年第6期9卷 163-170页

作者： Shanshan Liu Zihan Li Ke Yang Enze Zhang Awadhesh Narayan Xiaoqian Zhang Jiayi Zhu Wenqing Liu Zhiming Liao Masaki Kudo Takaaki Toriyama Yunkun Yang Qiang Li Linfeng Ai Ce Huang Jiabao Sun Xiaojiao Guo Wenzhong Bao Qingsong Deng Yanhui Chen Lifeng Yin Jian Shen Xiaodong Han Syo Matsumura Jin Zou Yongbing Xu Xiaodong Xu Hua Wu Faxian Xiu State Key Laboratory of Surface Physics and Department of Physics Fudan University Institute for Nanoelectronic Devices and Quantum Computing Fudan University College of Science University of Shanghai for Science and Technology Laboratory for Computational Physical Sciences(MOE) Fudan University Solid State and Structural Chemistry Unit Indian Institute of Science School of Electronic Science and Engineering Nanjing University Department of Physics University of Washington Department of Electronic Engineering Royal Holloway University of London Materials Engineering The University of Queensland Beijing Key Laboratory of Microstructure and Property of Advanced Materials Institute of Microstructure and Property of Advanced Materials Beijing University of Technology The Ultramicroscopy Research Center Kyushu University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Collaborative Innovation Center of Advanced Microstructures Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Centre for Microscopy and Microanalysis The University of Queensland Shanghai Research Center for Quantum Sciences

Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.

关键词： 2D ferromagnetic material Fe3+XGeTe2 film element doping above room temperature TC tunability

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Organic Memristor Based on High Planar Cyanostilbene/Polymer Composite Films

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Chemical Research in Chinese Universities 2023年第1期39卷 121-126页

作者： ZHAO Jinjin LI Wei WANG Xuechen WEI Xiao ZHU Huiwen QU Wenshan MEN Dandan GAO Zhixiang WEI Bin GAO Hanfei WU Yuchen Department of Physics Shanxi Datong UniversityDatong037009P.R.China Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing100190P.R.China Ji Hua Laboratory Foshan528000P.R.China Shanxi Province Key Laboratory of Microstructure Electromagnetic Functional Materials Institute of Solid State PhysicsShanxi Datong UniversityDatong037009P.R.China School of Chemistry and Chemical Engineering Shanxi Datong UniversityDatong037009P.R.China Key Laboratory of Advanced Display and System Applications Ministry of EducationSchool of Mechatronic Engineering and AutomationShanghai UniversityShanghai200072P.R.China

Organic memristors with low power consumption,fast write/erasure speed,and complementary metal-oxide-semiconductor(CMOS)compatibility have attracted tremendous attention to mimic biological synapses to realize neuromorphic computation in recent *** this paper,organic resistive switching memory(ORSM)based on(Z)-3-(naphthalen-2-yl)-2-(4-nitrophenyl)acrylonitrile(NNA)and polymer poly(N-vinylcarbazole)(PVK)composite film was prepared by spin-coating *** performance based on NNA:PVK composite films with different mass fractions of NNA were systematically *** ORSM based on PVK:40%(mass fraction)NNA composite film exhibited non-volatile and bipolar memory properties with a switching ratio(Ion/Ioff)of 24.1,endurance of 68 times and retention time of 104 s,a“SET”voltage(Vset)of−0.55 V and a“RESET”voltage(Vreset)of 2.35 *** resistive switching was ascribed to the filling and vacant process of the charge traps induced by NNA and the inherent traps in PVK *** holes trapping and de-trapping process occurred when the device was applied with a negative or positive bias,which caused the transforming of the conductive way of charges,that is the resistive behaviors in the *** study provides a promising platform for the fabrication of ORSM with high performance.

关键词： Organic memristor Resistive switching Polymer/molecule composite film

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A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification

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Plant Diseases and Pests 2024年第2期15卷 9-16页

作者： Mengmeng ZHANG Xiujuan WANG Mengzhen KANG Jing HUA Haoyu WANG Feiyue WANG State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning *** demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model ***,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial *** issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data *** address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.

关键词： Rice disease and pest identification Convolutional neural networks Distributed training Federated learning(FL) Open-source data sharing platform

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Economic Dispatch Strategy for Virtual Power Plants Based on Distributed Multi-Agent Algorithms

Economic Dispatch Strategy for Virtual Power Plants Based on...

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Energy engineering and Power systems (EEPS), International Conference on

作者： Dong Jiang Chenxia Wang Yali Xue Department of Energy and Power Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China College of New Energy Harbin Institute of Technology at Weihai Weihai China Department of Energy and Power Engineering State Key Laboratory of Power System Operation and Control Tsinghua Shanxi Clean Energy Research Institute Tsinghua University Beijing China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

This paper proposes an economic dispatch strategy for virtual power plants(VPP) based on distributed multi-agent algorithms to optimize resource allocation and maximize the VPP economy, in response to the volatility and uncertainty associated with a significant amount of renewable energy. An economic dispatch model for VPP is established in which the coefficients of the cost function are time-varying to account for the effect of the renewable energy output variation. Then a distributed multi-agent algorithm based on graph theory and the Lagrange multiplier method is developed to facilitate communication among individual units and minimize the total operational cost of the system. The effectiveness of the proposed algorithm is validated through numerical examples, which demonstrate its capability to optimize resource allocation, achieve economic dispatch for the VPP, and exhibit a rapid rate of convergence.

关键词： Economics Renewable energy sources Uncertainty Virtual power plants Cost function Graph theory Scheduling Power systems Resource management Convergence

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A Real-Time Digital Twin Model Dynamically Modifying Method Based on Consistency Measurement Model 4

A Real-Time Digital Twin Model Dynamically Modifying Method ...

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4th IEEE International Conference on Electronics Technology, ICET 2021

作者： Song, Wei-Ning Li, Tan Zhou, Jun-Hua Xu, Lin East China University of Technology School of Software Nanchang China Beijing Institute of Electronic System Engineering State Key Laboratory of Intelligent Manufacturing System Technology Beijing China

ISBN: (纸本)9781728176734

The dynamically modifying method is proposed to correct digital twin model online in real-time. Firstly, the digital twin model is divided into gradual-changing model and fast-changing model based on data changing ratio. The proximity of the position and the similarity of the shape is introduced to described the consistency of gradual-changing model and Empirical Mode Decomposition is depicted to decompose fast-changing model into trend item and stationary item, so that the consistency between physical entity and digital twin can be measured. Solution of parameters is acquired by searching instead of solving for the purpose of quick adjustment. Furthermore, a searching method combined Latin Hypercube global searching and greedy local searching is studied. The validity of the proposed method is proved by simulation. © 2021 IEEE.

关键词： Shape Digital twin simulation Shape measurement Position measurement Hypercubes Market research

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