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Soil and Environmental Health 2024年第1期2卷

作者： Zhu, Zhe Chan, Faith Ka Shun Li, Gang Xu, Mengxia Feng, Meili Zhu, Yong-Guan Key Laboratory of Urban Environment and Health Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 China Department of Chemical and Environmental Engineering University of Nottingham Ningbo China Ningbo 315100 China Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control CAS Haixi Industrial Technology Innovation Center in Beilun Ningbo 315830 China School of Geographical Sciences University of Nottingham Ningbo China Ningbo 315100 China Water@Leeds School of Geography University of Leeds Leeds LS2 9JT United Kingdom Research Base for Shenzhen Municipal Policy & Development Southern University of Science and Technology Shenzhen 518000 China New Materials Institute University of Nottingham Ningbo China Ningbo 315100 China Key Laboratory for Carbonaceous Wastes Processing and Process Intensification of Zhejiang Province University of Nottingham Ningbo China Ningbo 315100 China State Key Lab of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China

Urban agriculture, the cultivation, processing and distribution of plants and animals within urban or suburban boundaries, is becoming an increasingly relevant strategy to enhance food safety for urban residents. With the rapid urbanization in the past decades, three forms of urban agriculture have emerged in China: small-scale, capital-intensive, and tourism-type. Each form presents unique benefits and challenges, and their development has been largely shaped by the local socio-economic context and government policies. The benefits of urban agriculture are numerous including the improvement of community cohesion, promotion of physical health, enhancement of environmental sustainability, and creation of new economic opportunities. However, it also faces many challenges such as land availability, capital shortage, market access, and governmental support. This review summarized the benefits of urban agriculture and its current limitations and challenges, and proposed strategies to overcome these hurdles in China based on successful examples in the Global North. Four specific recommendations were provided to promote urban agriculture in China: integration of urban agriculture into cities, solutions for land and resource use, government support and reactions, as well as planning and regulations. Adoption these recommendations is expected to result in healthier cities and a more robust agricultural system in China. © 2024 The Author(s)

关键词： Environmental health Environmental sustainability Food security Global North Green city One health Urban farming Urban planning

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Breakdown of effective-medium theory by a photonic spin Hall effect

arXiv

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arXiv 2023年

作者： Yuan, Shuaijie Zhou, Xinxing Chen, Yu Zhong, Yuhan Sheng, Lijuan Hu, Hao Chen, Hongsheng Kaminer, Ido Lin, Xiao Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing312000 China Department of Electrical Engineering Technion-Israel Institute of Technology Haifa32000 Israel

Effective-medium theory pertains to the theoretical modelling of homogenization, which aims to replace an inhomogeneous structure of subwavelength-scale constituents with a homogeneous effective medium. The effective-medium theory is fundamental to various realms, including electromagnetics and material science, since it can largely decrease the complexity in the exploration of light-matter interactions by providing simple acceptable approximation. Generally, the effective-medium theory is thought to be applicable to any all-dielectric system with deep-subwavelength constituents, under the condition that the effective medium does not have a critical angle, at which the total internal reflection occurs. Here we reveal a fundamental breakdown of the effective-medium theory that can be applied in very general conditions: showing it for deep-subwavelength all-dielectric multilayers even without critical angle. Our finding relies on an exotic photonic spin Hall effect, which is shown to be ultra-sensitive to the stacking order of deep-subwavelength dielectric layers, since the spin-orbit interaction of light is dependent on slight phase accumulations during the wave propagation. Our results indicate that the photonic spin Hall effect could provide a promising and powerful tool for measuring structural defects for all-dielectric systems even in the extreme nanometer scale. Copyright © 2023, The Authors. All rights reserved.

关键词： Spin Hall effect

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Emission of marine microbes via sea spray aerosol generation: Enrichment, influencing factors and the potential role in marine carbon cycle

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Atmospheric Environment 2025年 359卷

作者： Linyao Wu Ting Liu Yingyi Zhang Yuhan Shen Yinxi Yao Zhaokang Ruan Yee Jun Tham Wei Song Shan Huang Jun Li Senchao Lai The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters Ministry of Education School of Environment and Energy South China University of Technology Guangzhou 510006 China School of Environmental Science and Engineering Hubei Polytechnic University Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation Huangshi 435003 China Now at: Atmospheric Environmental Risk Characterization and Management Lab Sustainable Energy and Environment Thrust Function Hub The Hong Kong University of Science and Technology (Guangzhou) Nansha Guangzhou 511453 China School of Marine Sciences State Key Laboratory of Environmental Adaptability for Industrial Products Sun Yat-sen University Zhuhai 519082 China State Key Laboratory of Advanced Environmental Technology Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou 510640 China College of Environment and Climate Jinan University Guangzhou 511443 China

Marine microorganisms, widely distributed in seawater, can be transferred into the atmosphere through sea spray aerosols (SSA) generated by the bursting of bubbles. Considering the vast oceanic coverage on Earth, this process has significant climatic implications on regional and global scales, particularly under the influence of global warming. Using a self-constructed sea spray aerosol generation tank (SAGT), we simulated SSA production with seawater of varying salinities to investigate the transfer and enrichment of microorganisms in SSA. Our results confirm that microorganisms can be enriched in SSA. The microbial enrichment was size-dependent, with elevated enrichment factors observed in fine particles. Chlorophyll a, a proxy for marine primary production, demonstrated a significant positive correlation with microbial enrichment in submicron SSA, indicating the influence of marine biological activities. Additionally, salinity was found to play a critical role, with high salinity promoting the enrichment of microbes in SSA. Microbial cell growth in seawater should also be considered when assessing marine microbial contributions. We estimated the emission fluxes of microbial carbon via SSA production from low and high salinity seawater, and a global annual emission of marine microbes was estimated in the range of 0.68–2.50 Gg yr −1 . This study underscores the importance of understanding microbial transfer through SSA production and highlights its relevance in the context of global environmental changes driven by warming, emphasizing the intricate connections between marine ecosystems and atmospheric processes.

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An Approach for Peg-in-Hole Assembling Based on Force Feedback control

An Approach for Peg-in-Hole Assembling Based on Force Feedba...

引用

Chinese Automation Congress (CAC)

作者： Peng Zou Qiuguo Zhu Jun Wu Jianxiang Jin State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Zhejiang University Hangzhou P. R. China

In this paper, an intuitive and effective method is proposed for a sensor guided industrial robot to carry out the Peg-in-Hole assembly. This method contains two main steps. The first step is calibrating the wrist force sensor to compensate the load gravity and the bias of sensor so that the external force on the load can be precisely obtained. Secondly an impedance controller is designed to realize the compliant behavior between the manipulator and external environment. Different from the traditional method based on the position control loop, the force control strategy is based on the robot end-effector velocity control loop, which is easier and convenient to implement. Finally, a Peg-in-Hole experiment using an industrial manipulator with wrist sensor and a Peg-in-Hole mould with a tiny clearance was successfully completed. The experimental results verified the effectiveness and practicability of the proposed method.

关键词： Robot sensing systems Service robots Robot kinematics Gravity Task analysis

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Globally optimal consensus maximization for robust visual inertial localization in point and line map

arXiv

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arXiv 2020年

作者： Jiao, Yanmei Wang, Yue Fu, Bo Tan, Qimeng Chen, Lei Wang, Minhang Huang, Shoudong Xiong, Rong State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China Application Lab Huawei Incorporated Company China University of Technology Sydney Australia

Map based visual inertial localization is a crucial step to reduce the drift in state estimation of mobile robots. The underlying problem for localization is to estimate the pose from a set of 3D-2D feature correspondences, of which the main challenge is the presence of outliers, especially in changing environment. In this paper, we propose a robust solution based on efficient global optimization of the consensus maximization problem, which is insensitive to high percentage of outliers. We first introduce translation invariant measurements (TIMs) for both points and lines to decouple the consensus maximization problem into rotation and translation subproblems, allowing for a two-stage solver with reduced search space. Then we show that (i) the rotation can be estimated by minimizing TIMs using only 1-dimensional branch-and-bound (BnB), (ii) the translation can be estimated by running 1-dimensional search for each of the three axes with prioritized progressive voting. Compared with the popular randomized solver, our solver achieves deterministic global convergence without requiring an initial value. Furthermore, ours is exponentially faster compared with existing BnB based methods. Finally, our experiments on both simulation and real-world datasets demonstrate that the proposed method gives accurate pose estimation even in the presence of 90% outliers (only 2 inliers). Copyright © 2020, The Authors. All rights reserved.

关键词： Statistics

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Gauss-Newton unrolled neural networks and data-driven priors for regularized PSSE with robustness

arXiv

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arXiv 2020年

作者： Yang, Qiuling Sadeghi, Alireza Wang, Gang Giannakis, Georgios B. Sun, Jian State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Renewable energy sources, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today’s power systems (PS). In this context, fast and robust state estimation (SE) is timely and of major importance to maintain a comprehensive view of the system in real time. Conventional PSSE solvers typically entail minimizing a nonlinear and nonconvex least-squares cost using e.g., the Gauss-Newton method. Those iterative solvers however, are sensitive to initialization, and may converge to local minima. To overcome these hurdles, the present paper adapts and leverages recent advances on image denoising to introduce a PSSE approach with a regularizer capturing a deep neural network (DNN) prior. For the resultant regularized PSSE objective, a "Gauss-Newton-type" alternating minimization solver is developed first. To accommodate real-time monitoring, a novel end-to-end DNN is constructed subsequently by unrolling the proposed alternating minimization solver. The deep PSSE architecture can further account for the power network topology through a graph neural network (GNN) based prior. To further endow the physics-based DNN with robustness against bad data, an adversarial DNN training method is put forth. Numerical tests using real load data on the IEEE 118-bus benchmark system showcase the improved estimation and robustness performance of the proposed scheme compared with several state-of-the-art alternatives. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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Resonant beam communications with echo interference elimination

arXiv

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arXiv 2021年

作者： Xiong, Mingliang Liu, Qingwen Wang, Gang Giannakis, Georgios B. Zhang, Sihai Zhu, Jinkang Huang, Chuan College of Electronics and Information Engineering Tongji University Shanghai201804 China State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Key Lab of Wireless-Optical Communications University of Science and Technology of China Hefei Anhui230026 China School of Science and Engineering Chinese University of Hong Kong Shenzhen Guangdong518172 Hong Kong

Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier. Besides, the RBCom system possesses the characteristics of mobility, high signal-to-noise ratio (SNR), and multiplexing. Nevertheless, the channel of the RBCom system is distinct from other light communication technologies due to the echo interference issue. In this paper, we reveal the mechanism of the echo interference and propose the method to eliminate the interference. Moreover, we present an exemplary design based on frequency shifting and optical filtering, along with its mathematic model and performance analysis. The numerical evaluation shows that the channel capacity is greater than 15 bit/s/Hz. Copyright © 2021, The Authors. All rights reserved.

关键词： Internet of things

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Efficient two step optimization for large embedded deformation graph based SLAM

arXiv

引用

arXiv 2019年

作者： Song, Jingwei Bai, Fang Zhao, Liang Huang, Shoudong Xiong, Rong Centre for Autonomous Systems University of Technology P.O. Box 123 BroadwayNSW2007 Australia State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University 38 Zheda Road Zhejiang310027

Embedded deformation nodes based formulation has been widely applied in deformable geometry and graphical problems. Though being promising in stereo (or RGBD) sensor based SLAM applications, it remains challenging to keep constant speed in deformation nodes parameter estimation when model grows larger. In practice, the processing time grows rapidly in accordance with the expansion of maps. In this paper, we propose an approach to decouple nodes of deformation graph in large scale dense deformable SLAM and keep the estimation time to be constant. We observe that only partial deformable nodes in the graph are connected to visible points. Based on this fact, sparsity of original Hessian matrix is utilized to split parameter estimation in two independent steps. With this new technique, we achieve faster parameter estimation with amortized computation complexity reduced from O(n2) to closing O(1). As a result, the computation cost barely increases as the map keeps growing. Based on our strategy, computational bottleneck in large scale embedded deformation graph based applications will be greatly mitigated. The effectiveness is validated by experiments, featuring large scale deformation scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Deformation

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PIDNet: An efficient network for dynamic pedestrian intrusion detection

arXiv

引用

arXiv 2020年

作者： Sun, Jingchen Chen, Jiming Chen, Tao Fan, Jiayuan He, Shibo State Key lab. of Industrial Control Technology Zhejiang University Hangzhou China Alibaba-ZJU Joint Research Institute of Frontier Technologies School of Information Science and Technology Fudan University Shanghai China Academy for Engineering and Technology Fudan University Shanghai China

Vision-based dynamic pedestrian intrusion detection (PID), judging whether pedestrians intrude an area-of-interest (AoI) by a moving camera, is an important task in mobile surveillance. The dynamically changing AoIs and a number of pedestrians in video frames increase the difficulty and computational complexity of determining whether pedestrians intrude the AoI, which makes previous algorithms incapable of this task. In this paper, we propose a novel and efficient multi-task deep neural network, PIDNet, to solve this problem. PIDNet is mainly designed by considering two factors: accurately segmenting the dynamically changing AoIs from a video frame captured by the moving camera and quickly detecting pedestrians from the generated AoI-contained areas. Three efficient network designs are proposed and incorporated into PIDNet to reduce the computational complexity: 1) a special PID task backbone for feature sharing, 2) a feature cropping module for feature cropping, and 3) a lighter detection branch network for feature compression. In addition, considering there are no public datasets and benchmarks in this field, we establish a benchmark dataset to evaluate the proposed network and give the corresponding evaluation metrics for the first time. Experimental results show that PIDNet can achieve 67.1% PID accuracy and 9.6 fps inference speed on the proposed dataset, which serves as a good baseline for the future vision-based dynamic PID study. Copyright © 2020, The Authors. All rights reserved.

关键词： Intrusion detection

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An augmented regression model for tensors with missing values

arXiv

引用

arXiv 2020年

作者： Wang, Feng Gahrooei, Mostafa Reisi Zhong, Zhen Tang, Tao Shi, Jianjun State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Department of Industrial and Systems Engineering University of Florida GainesvilleFL32611 United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA30332 United States

Heterogeneous but complementary sources of data provide an unprecedented opportunity for developing accurate statistical models of systems. Although the existing methods have shown promising results, they are mostly applicable to situations where the system output is measured in its complete form. In reality, however, it may not be feasible to obtain the complete output measurement of a system, which results in observations that contain missing values. This paper introduces a general framework that integrates tensor regression with tensor completion and proposes an efficient optimization framework that alternates between two steps for parameter estimation. Through multiple simulations and a case study, we evaluate the performance of the proposed method. The results indicate the superiority of the proposed method in comparison to a benchmark. Copyright © 2020, The Authors. All rights reserved.

关键词： Tensors

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