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Spatiotemporal Changes in NDVI and Its Driving Factors in the Kherlen River Basin

Chinese Geographical Science 2023年第2期33卷 377-392页

作者： MUHAMMAD Naveed HE hongshi ZONG shengwei DU Haibo SATTI Zulqarnain TAN Xinyuan QAZI Muhammad Yasir Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains Ministry of EducationSchool of Geographical SciencesNortheast Normal UniversityChangchun 130024China School of Natural Resources University of MissouriColumbia 65211USA Xinjiang Institute of Ecology and Geography Chinese Academy of SciencesUrumqi 830011China

Vegetation is an important factor linking the atmosphere,water,soil,and biological functions,and it plays a specific role in the climate change response and sustainable development of regional ***,little information is available on vegetation vulnerability and its driving ***,studying temporal and spatial change characteristics of vegetation and their corresponding mechanisms is important for assessing ecosystem stability and formulating ecological policies in the Kherlen River *** used Moderate-resolution Imaging Spectroradiometer(MODIS)normalized difference vegetation index(NDVI)remote sensing images from 2000 to 2020 to analyse temporal changes in NDVI with the autoregressive moving average model(ARMA)and the breaks for additive season trend(BFAST)in the basin and to assess natural,anthropogenic and topographic factors with the Geodetector *** results show that:1)the long NDVI time series remained stable in the Kherlen River Basin from 2000 to 2020,with a certain significant mutation period from 2013 to 2017;2)the coefficient of variation(CV)in the analysis of the spatial NDVI was generally constant,mainly at the level of 0.01–0.07,and the spatial NDVI change was minimally impacted by external interference;and 3)temperature and precipitation are the key factors affecting the NDVI in the basin,and changes in local hydrothermal conditions directly affect the local *** results of this study could provide a scientific basis for the effective protection of the ecological environment and will aid in understanding the influence of vegetation change mechanisms and the corresponding factors.

关键词： normalized difference vegetation index(NDVI) spatial stability vegetation ecology Geodetector Kherlen River Basin

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Pyrolysis of vulcanized styrene-butadiene rubber via ReaxFF molecular dynamics simulation

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Chinese Journal of Chemical Engineering 2021年第3期34卷 94-102页

作者： Yinbin Wang Senjun Yao Wei Wang Chenglong Qiu Jing Zhang shengwei Deng hong Dong Chuan Wu Jianguo Wang Institute of Industrial Catalysis State Key Laboratory Breeding Base of Green-Chemical Synthesis TechnologyCollege of Chemical EngineeringZhejiang University of TechnologyHangzhou 310014China College of Computer Science and Technology Zhejiang University of Technology310014China Key Laboratory of Organosilicon Chemistry and Material Technology Ministry of EducationHangzhou Normal University310012China

Styrene-butadiene rubber(SBR)is widely used in tires in the automotive segment and vulcanization using sulfur is a common process to enhance its mechanical ***,the addition of sulfur as the cross-linking agent usually results in impurities in pyrolysis products during rubber recycling,and thus the desulfurization during tire pyrolysis attracts much *** this work,the pyrolysis of vulcanized SBR is studied in detail with the help of Reax FF molecular dynamics simulation.A series of crosslinked SBR models were built with different sulfur contents and *** following Reax FF MD simulations were performed to show products distributions at different pyrolysis *** simulation results show that sulfur products distribution is mainly controlled by sulfur contents and *** reaction mechanism is proposed based on the analysis of sulfur products conversion pathway,where most sulfur atoms are bonded with hydrocarbon radicals and the rest transfer to H_(2)*** sulfur contents tend to the formation of elemental sulfur intermediate,and temperature increase facilitates the release of H_(2)S.

关键词： Pyrolysis ReaxFF Molecular simulation Vulcanized Styrene-butadiene rubber Sulfur products

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A fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of communication link in IoT-enabled building automation systems

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Energy and Built Environment 2024年第3期5卷 446-454页

作者： Wenzhuo Li Rui Tang shengwei Wang Institute for Environmental Design and Engineering The BartlettUniversity College LondonUK Department of Building Environment and Energy Engineering The Hong Kong Polytechnic UniversityKowloonHong Kong Research Institute for Smart Energy The Hong Kong Polytechnic UniversityKowloonHong Kong

Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control ***,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link *** and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms *** study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled *** distributed algorithm is adopted that agents know their out-neighbors *** directly coordinate with the connected neighbors for global *** are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed *** show that different approaches are vulnerable against to uncertainties of communication link to different *** proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high *** also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.

关键词： Multi-agent system Edge computing Air-conditioning system Internet of Things(IoT) Communication link failure

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非线性H_∞控制的粘性解及近似逼近分析

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自动化学报 1998年第4期24卷 447-453页

作者：洪奕光梅生伟秦化淑翁绍鹏中国科学院系统科学研究所清华大学电机系香港大学数学系

讨论非线性（在鞍点条件成立时）Ｈ∞控制的（干扰抑制问题的）粘性解法．此方法基于对策论和Ｈａｍｉｌｔｏｎ－Ｊａｃｏｂｉ－Ｉｓａａｃｓ（ＨＪＩ）不等式．主要结果分三个方面．首先，是将所求的关于ＨＪＩ不等式的解推广到不可微... 详细信息

讨论非线性（在鞍点条件成立时）Ｈ∞控制的（干扰抑制问题的）粘性解法．此方法基于对策论和Ｈａｍｉｌｔｏｎ－Ｊａｃｏｂｉ－Ｉｓａａｃｓ（ＨＪＩ）不等式．主要结果分三个方面．首先，是将所求的关于ＨＪＩ不等式的解推广到不可微的粘性解情形．随后，讨论了此情形下的Ｈ∞状态控制器对被控系统的镇定问题．最后给出了求解该问题的近似逼近的理论依据和算法的初步讨论．

关键词：非线性粘性解近似逼近 H∞控制鲁棒控制

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Generic load regulation strategy for enhancing energy efficiency of chiller plants

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Building Simulation 2024年第8期17卷 1273-1287页

作者： Hang Wan Yuyang Gong shengwei Wang Yongjun Sun Tao Xu Gongsheng Huang Department of Architecture and Civil Engineering City University of Hong KongHong KongChina Department of Building Environment and Energy Engineering Hong Kong Polytechnic UniversityHong KongChina School of Civil Engineering Guangzhou UniversityGuangzhouChina Shenzhen Research Institute of City University of hong Kong ShenzhenChina

In many chiller plants,high coefficient of performance(COP)is only achieved at a few favorable part load ratios(PLRs),while the COP is low at many other non-favorable *** address this issue,this study proposes a generic load regulation strategy that aims to maintain chiller plants operating at high COP,particularly under non-favorable *** is achieved by incorporating thermal energy storage(TES)units and timely optimizing the charging and discharging power of the integrated TES *** optimal charging and discharging power is determined by solving a dynamic optimization problem,taking into account the performance constraints of the TES units and the chiller *** provide an overview of the energy-saving potential of the proposed strategy,a comprehensive analysis was conducted,considering factors such as building load profiles,COP/PLR curves of chillers,and attributes of the TES *** analysis revealed that the proposed load regulation strategy has the potential to achieve energy savings ranging from 5.7%to 10.8%for chiller plants with poor COPs under unfavorable PLRs,particularly in buildings with significant load variations.

关键词： load regulation thermal energy storage chiller plants building energy efficiency

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基于双层规划的非线性鲁棒电力系统稳定器参数整定方法

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电力系统自动化 2014年第14期38卷 42-48页

作者：王宏魏韡潘艳菲张雪敏梅生伟东北电力大学电气工程学院吉林省吉林市132012 清华大学电机工程与应用电子技术系北京市100084 电力系统及发电设备控制和仿真国家重点实验室清华大学北京市100084

使用先进的励磁控制技术是改善电力系统稳定性和动态品质的有效手段。采用反馈线性化和鲁棒控制理论设计的非线性鲁棒电力系统稳定器(NR-PSS)是一种先进的励磁控制装置。在深入研究电力系统稳定器(PSS)参数整定原理和NR-PSS现有参数整... 详细信息

使用先进的励磁控制技术是改善电力系统稳定性和动态品质的有效手段。采用反馈线性化和鲁棒控制理论设计的非线性鲁棒电力系统稳定器(NR-PSS)是一种先进的励磁控制装置。在深入研究电力系统稳定器(PSS)参数整定原理和NR-PSS现有参数整定方法的基础上,提出了一种基于双层规划的NR-PSS线性部分参数整定方法,以满足阻尼频带宽和控制代价低两方面要求。通过等价非线性规划可求出最优参数。仿真结果表明,应用所提出方法设定的参数可以改善NRPSS的控制效果。

关键词：电力系统稳定器参数整定鲁棒控制双层规划非线性控制

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Protective Film for NiSO4.6H2O UV Light Filter Based on Diisocyanate-Bridged Polysilsesquioxane

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材料科学与工程（中英文版） 2011年第1期5卷 1-11页

作者： Weimei Shi hong Tian shengwei Hu Yao Xu Dong WU State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Taiyuan 030001 China Graduate University of the Chinese Academy of Sciences Beijing 100049 China

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基于系统药理学分析透解祛瘟颗粒治疗COVID-19的活性成分

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南方医科大学学报 2020年第8期40卷 1072-1080页

作者：马世堂张雪岑金凤洪阁洪盛威居文政安徽科技学院生命与健康科学学院安徽凤阳233100 中国医学科学院北京协和医学院生物医学工程所天津300192 南京中医药大学江苏南京200019

目的采用系统药理学多维阐释探寻透解祛瘟颗粒(TJQW)治疗新型冠状肺炎(COVID-19)药效物质基础,并筛选活性成分。方法采用数据库搜寻、文献挖掘与类药性指标筛选确定TJQW化合物、疾病阳性药物及作用靶点,基于活性成分-阳性药物-疾病潜在... 详细信息

目的采用系统药理学多维阐释探寻透解祛瘟颗粒(TJQW)治疗新型冠状肺炎(COVID-19)药效物质基础,并筛选活性成分。方法采用数据库搜寻、文献挖掘与类药性指标筛选确定TJQW化合物、疾病阳性药物及作用靶点,基于活性成分-阳性药物-疾病潜在靶点交联互作明确关键节点靶标,并对其进行GO生物过程分析和KEGG通路分析,在此基础上针对核心靶标对TJQW组分进行虚拟筛选,构建成分-靶点-通路网络效应图,最后对活性成分分子结构特征进行阐释。结果从TJQW组方中得到159个化合物,基于活性成分-阳性药物-疾病三者交联得到18个核心节点蛋白,结合新近报道的4个COVID-19相关蛋白共22个靶标构成了COVID-19靶标。虚拟筛选结果显示每个靶标蛋白有14个及以上化合物与其应答,其中与NR1I2蛋白结合效应的分子多达64个,多途径、多成分、多靶点阐释了TJQW抗COVID-19物质基础,共筛选得到与疾病核心靶标结合较好的前30个分子,黄酮类起主导作用。结论从“关键活性药效分子-疾病关键节点靶标-相关生物学通路”角度来揭示TJQW多个成分、多个靶点和多条通路机制治疗COVID-19的作用机制药效物质基础,并筛选出前30个活性先导物,为该组方的临床应用和深入开发提供参考。

关键词：系统药理学透解祛瘟颗粒新型冠状肺炎药效物质基础

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Design and control optimization of energy systems of smart buildings today and in the near future

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Frontiers of Engineering Management 2017年第1期4卷 58-66页

作者： shengwei WANG Wenjie GANG Department of Building Services Engineering The Hong Kong Polytechnic University Department of Building Environment and Energy Engineering Huazhong University of Science and Technology

Buildings contribute to a major part of energy consumption in urban areas, especially in areas like hong Kong which is full of high-rise buildings. Smart buildings with high efficiency can reduce the energy consumption largely and help achieve green cities or smart cities. Design and control optimization of building energy systems therefore plays a significant role to obtain the optimal performance. This paper introduces a general methodology for the design and control optimization of building energy systems in the life cycle. When the design scheme of building energy systems is optimized, primary steps and related issues are introduced. To improve the operation performance, the optimal control strategies that can be used by different systems are presented and key issues are discussed. To demonstrate the effect of the methods, the energy system of a high-rise building is introduced. The design on the chilled water pump system and cooling towers is improved. The control strategies for chillers,pumps and fresh air systems are optimized. The energy saving and cost from the design and control optimization methods are analyzed. The presented methodology will provide users and stakeholders an effective approach to improve the energy efficiency of building energy systems and promote the development of smart buildings and smart cities.

关键词： Design optimization Optimal control Smart building Energy efficiency

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Identification of soybean in Argentina using Sentinel-2 composite images

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International Journal of Agricultural and Biological Engineering 2024年第5期17卷 266-274页

作者： Linsheng Huang Yue Chen Yuhao Pan Zihang Lou Shijun Zheng Xiaoyang Zhang Le Yu shengwei Liu Dailiang Peng National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230601China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China Research Area of Ecology and Biodiversity School of Biological SciencesThe University of Hong KongPokfulamHong KongChina College of Environmental and Resource Sciences Zhejiang UniversityHangzhou 310058China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Geospatial Sciences Center of Excellence Department of Geography&Geospatial SciencesSouth Dakota State UniversityBrookingsSD 57007USA Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing 100084China Tsinghua University(Department of Earth System Science)-Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing 100084China School of Surveying and Land Information Engineering Henan Polytechnic UniversityJiaozuo 454000HenanChina

Soybean is one of the most important oil crops, and Argentina is the third-largest soybean producer in the world, accounting for 17% of the global soybean yield. Timely and accurate information on soybean spatial distribution is critical for ensuring global food security. Sentinel-2 multispectral data and machine learning classification models are used to investigate the potential of soybean identification in the early stage of the growing season in Argentina, with the help of Google Earth Engine (GEE). The earliest time window and optimal feature set for soybean identification are explored. Results are as follows: 1) the random forest (RF) classification model demonstrated the highest level of classification accuracy compared to the backpropagation neural network (BPNN), support vector machine (SVM), and naive Bayes (NB) models;2) Soybean can be accurately identified as early as the end of February (filling stage), which is approximately one month before harvest;3) The optimal feature-subset can reduce the amount of input data by 80% while maintaining high classification accuracy. The overall accuracy (OA) of the RF classification model is 85.87%, and the relative error between the estimated soybean planting area and the agricultural statistics is 3.45%. This study provided a high-precision method for early-season identification of soybeans over large scales. The results can provide a data support for early futures trading and agricultural insurance, as well as a reference for policy-making to ensure global soybean food security.

关键词： soybean machine learning time window feature selection Sentinel-2 Google Earth Engine

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