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Introduction of Dalbergia odorifera enhances nitrogen absorption on Eucalyptus through stimulating microbially mediated soil nitrogen-cycling

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Forest Ecosystems 2021年第4期8卷 789-800页

作者： Xianyu Yao Qianchun Zhang haiju zhou Zhi Nong Shaoming Ye Qi Deng Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China Center for Plant Ecology Core Botanical GardensChinese Academy of SciencesGuangzhou 510650China State Key Laboratory of Conservation and Utilization of Subtropical Agro-bioresources College of ForestryGuangxi UniversityNanning 530004China Experimental Center of Topical Forestry Chinese Academy of ForestryPingxiang 532600China

Background:There is substantial evidence that Eucalyptus for nitrogen(N)absorption and increasing the growth benefit from the introduction of N-fixing species,but the underlying mechanisms for microbially mediated soil N cycling remains ***:We investigated the changes of soil pH,soil water content(SWC),soil organic carbon(SOC),total N(TN),inorganic N(NH_(4)^(+)-N and NO_(3)^(-)-N),microbial biomass and three N-degrading enzyme activities as well as the biomass and N productivity of Eucalyptus between a pure Eucalyptus urophylla×grandis plantation(PP)and a mixed Dalbergia odorifera and Eucalyptus plantation(MP)in Guangxi Zhuang Autonomous Region,***:Compared with the PP site,soil pH,SWC,SOC and TN in both seasons were significantly higher at the MP site,which in turn enhanced microbial biomass and the activities of soil N-degrading *** stimulated microbial activity at the MP site likely accelerate soil N mineralization,providing more available N(NH_(4)^(+)-N in both seasons and NO_(3)^(-)-N in the wet-hot season)for Eucalyptus ***,the N productivity of Eucalyptus at the MP site was increased by 19.7% and 21.9%,promoting the biomass increases of 15.1% and 19.2% in the drycold season and wet-hot season,***:Our results reveal the importance of microbially mediated soil N cycling in the N absorption on *** of *** enhances Eucalyptus biomass and N productivity,improve soil N availability and increased soil C and N concentration,which hence can be considered to be an effective sustainable management option of Eucalyptus plantations.

关键词： Eucalyptus plantations Soil physical-chemical properties Microbial biomass Soil enzyme activities Nitrogen availability

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基于GIS和空间自相关模型的南宁市林地空间变化研究

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广东农业科学 2022年第1期49卷 51-61页

作者：周海菊胡靓达喻素芳广西大学林学院广西南宁530004

【目的】掌握南宁市林地时空分布的变化规律,为制定科学有效的林地管理措施提供基础数据。【方法】基于2008、2013、2018年3期南宁市森林资源调查数据,应用空间统计技术,结合转移矩阵及空间自相关模型,分析不同时期南宁市林地分布格局,... 详细信息

【目的】掌握南宁市林地时空分布的变化规律,为制定科学有效的林地管理措施提供基础数据。【方法】基于2008、2013、2018年3期南宁市森林资源调查数据,应用空间统计技术,结合转移矩阵及空间自相关模型,分析不同时期南宁市林地分布格局,探究林地时空分布动态变化特征及空间聚集规律。【结果】2008—2018年,南宁市天然林面积减少2.39×10^(4)hm^(2),人工林面积增加2.60×10^(4)hm^(2),其他林地面积减少2.98×10^(4)hm^(2),林地总面积略有减少;林地类型变化繁杂,天然林和其他林地主要转化为人工林,人工林主要转化为非林地,其中2013—2018年林地变化更为剧烈;天然林和人工林的分布均具有显著的空间自相关性,天然林的空间自相关性高于人工林。整个研究期间,天然林和人工林的空间聚集性均呈下降趋势。【结论】2008—2018年南宁市林地发生较大的转移及变化,为有效保护林地、实现森林资源的可持续发展,需进一步加强实施科学有效的林地资源保护政策和措施。

关键词：天然林人工林空间分布转移矩阵空间自相关性

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Parallel Physics-Informed Neural Networks Method with Regularization Strategies for the Forward-Inverse Problems of the Variable Coefficient Modified KdV Equation

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Journal of Systems Science & Complexity 2024年第2期37卷 511-544页

作者： zhou Huijuan School of Science Shanghai Maritime UniversityShanghai 201306China

This paper mainly introduces the parallel physics-informed neural networks(PPINNs)method with regularization strategies to solve the data-driven forward-inverse problems of the variable coefficient modified Korteweg-de Vries(VC-MKdV)*** the forward problem of the VC-MKdV equation,the authors use the traditional PINN method to obtain satisfactory data-driven soliton solutions and provide a detailed analysis of the impact of network width and depth on solving accuracy and ***,the author finds that the traditional PINN method outperforms the one with locally adaptive activation functions in solving the data-driven forward problems of the VC-MKdV *** for the data-driven inverse problem of the VC-MKdV equation,the author introduces a parallel neural networks to separately train the solution function and coefficient function,successfully addressing the function discovery problem of the VC-MKdV *** further enhance the network’s generalization ability and noise robustness,the author incorporates two regularization strategies into the *** amount of numerical experimental data in this paper demonstrates that the PPINNs method can effectively address the function discovery problem of the VC-MKdV equation,and the inclusion of appropriate regularization strategies in the PPINNs can improves its performance.

关键词： Data-driven forward-inverse problems parallel physics-informed neural networks regularization strategies variable coefficient modified KdV equation

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Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei WANG Xiaoping ZHU zhou zhou Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision *** this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better *** training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario *** order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation *** results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

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Oxidation of emerging organic contaminants by in-situ H_(2)O_(2) fenton system

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Green Energy & Environment 2024年第3期9卷 417-434页

作者： Yuqin Ni Chuxiang zhou Mingyang Xing Yi zhou State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes School of Resources&Environmental EngineeringEast China University of Science and TechnologyShanghai200237China Key Laboratory for Advanced Materials and Institute of Fine Chemicals National Engineering Laboratory for Industrial Wastewater TreatmentSchool of Chemistry and Molecular EngineeringEast China University of Science and Technology130 Meilong RoadShanghai200237China Department of Applied Natural Sciences Technische Hochschule LubeckMonkhofer Weg 23923562 LubeckGermany

The existence and risk of emerging organic contaminants(EOCs)have been under consideration and paid much effort to degrade these *** system is one of the most widely used technologies to solve this *** original Fenton system relies on the hydroxyl radicals produced by Fe(Ⅱ)/H_(2)O_(2) to oxidize the organic ***,the application of the Fenton system is limited by its low iron cycling efficiency and the high risks of hydrogen peroxide transportation and *** introduction of external energy(including light and electricity etc.)can effectively promote the Fe(Ⅲ)/Fe(Ⅱ)cycle and the reduction of oxygen to produce hydrogen peroxide in *** review introduces three in-situ Fenton systems,which are electro-Fenton,Photo-Fenton,and chemical *** mechanism,influencing factors,and catalysts of these three in-situ Fenton systems in degrading EOCs are discussed *** review strengthens the understanding of Fenton and in-situ Fenton systems in degradation,offering further insight into the real application of the in-situ Fenton system in the removal of EOCs.

关键词： In-situ H_(2)O_(2)production Fenton Emerging organic contaminants Photocatalysis Electrocatalysis

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SPARSE RECOVERY BASED ON THE GENERALIZED ERROR FUNCTION

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Journal of Computational Mathematics 2024年第3期42卷 679-704页

作者： Zhiyong zhou Department of Statistics and Data Science and Institute of Digital FinanceHangzhou City UniversityHangzhou 310015China

In this paper,we offer a new sparse recovery strategy based on the generalized error *** introduced penalty function involves both the shape and the scale parameters,making it extremely *** both constrained and unconstrained models,the theoretical analysis results in terms of the null space property,the spherical section property and the restricted invertibility factor are *** practical algorithms via both the iteratively reweighted■_(1)and the difference of convex functions algorithms are *** experiments are carried out to demonstrate the benefits of the suggested approach in a variety of *** practical application in magnetic resonance imaging(MRI)reconstruction is also investigated.

关键词： Sparse recovery Generalized error function Nonconvex regularization Itera-tive reweighted Li Difference of convex functions algorithms

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Emergent Geometry of KP Hierarchy

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Acta Mathematica Sinica,English Series 2024年第1期40卷 3-25页

作者： Jian zhou Department of Mathematical Sciences Tsinghua UniversityBeijng 100084P.R.China

We explain how to construct a quantum deformation of a spectral curve associated to a tau-function of the KP *** construction is applied to Witten-Kontsevich tau-function to give a natural explanation of some earlier ... 详细信息

关键词： KP hierarchy tau-functions spectral curves

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The dry-hot feedback between soil moisture and atmosphere and the accelerated global warming

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Science China Earth Sciences 2024年第3期67卷 890-891页

作者： Tianjun zhou State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Greenhouse gas (GHG) emissions have been increasing due to human activities since the Industrial Revolution, resulting in continuous warming of the global climate system and significant drought over a large parts of global land, both have shown a non-linear growth trend in recent decades(Berg et al., 2017;zhou et al., 2019;IPCC, 2021).

关键词： warming moisture drought

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Phase field modeling of ferroelastic variant switching in yttria-stabilized t'zirconia with strain gradient elasticity and interface tension

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Science China(Technological Sciences) 2024年第5期67卷 1443-1457页

作者： zhou QianQian WEI YueGuang zhou YiChun YANG Li College of Engineering BIC-ESATPeking UniversityBeijing100871China School of Advanced Materials and Nanotechnology Xidian UniversityXi’an710126China Frontier Research Center of Thin Films and Coatings for Device Applications Academy of Advanced Interdisciplinary ResearchXidian UniversityXi’an710126China

The 6–8 wt%yttria-stabilized zirconia with a tetragonal structure(t’-YSZ)is extensively employed in thermal barrier *** exceptional fracture toughness of t’-YSZ can be attributed to its distinctive ferroelastic toughening *** and interface tension play a critical role in ferroelastic variant switching at the micro-and *** paper presents an original thermodynamically consistent phase field(PF)theory for analyzing ferroelastic variant switching at the micro-and nano-scale of t’-*** theory incorporates strain gradient elasticity using higher-order elastic energy and interface tension tensor via geometric nonlinearity to represent biaxial tension resulting from interface ***,a mixed-type formulation is employed to implement the higher-order theory through the finite element *** an interface in equilibrium,the effects of strain gradient elasticity result in a more uniform distribution of stresses,whereas the presence of interface tension tensor significantly amplifies the stress magnitude at the *** introduction of an interface tension tensor increases the maximum value of stress at the interface by a factor of 4 to *** nucleation and evolution of variants at a pre-existing crack tip in a mono-phase t’-YSZ have also been *** strain gradient elasticity is capable of capturing the size effect of ferroelastic variant switching associated with microstructures in ***,when the grain size approaches that of the specimen,the critical load required for variant switching at the crack tip increases,resulting in greater dissipation of elastic energy during ferroelastic variant ***,the interface tension accelerates the evolution of *** presented framework exhibits significant potential in modeling ferroelastic variant switching at the micro-and nano-scale.

关键词： thermodynamics strain gradient elasticity interface tension phase field method ferroelastic variant switching

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Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 345-358页

作者： Zan zhou Thomas Man-Hoi Lok Wan-Huan zhou Department of Civil and Environmental Engineering Faculty of Science and TechnologyUniversity of MacaoMacaoChina

Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization ***,an improper selection of the number of layers may lead to an incorrect shear wave velocity *** this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil ***,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer ***,the shear-wave velocity profile is determined by a genetic algorithm with the known layer *** applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

关键词： surface wave inversion analysis shear-wave velocity profile deep neural network genetic algorithm

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