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Risk assessment of agricultural green water security in Northeast China under climate change

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Science China Earth Sciences 2024年第7期67卷 2178-2194页

作者： Jingxuan SUN Guangxin zhang Yanfeng WU Liwen chen peng QI Boting HU Yijun XU Northeast Institute of Geography and Agroecology.Chinese Academy of Sciences Changchun 130102China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Black Soils Conservation and Utilization Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China School of Renewable Natural Resources Louisiana State University Agricultural Center227 Highland RoadBaton RougeLA 70803USA

Northeast China is an important base for grain production,dominated by rain-fed agriculture that relies on green ***,in the context of global climate change,rising regional temperatures,changing precipitation patterns,and increasing drought frequency pose threats and challenges to agricultural green water *** study provides a detailed assessment of the spatiotemporal characteristics and development trends of green water security risks in the Northeast region under the base period(2001-2020)and the future(2031-2090)climate change scenarios(SSP245 and SSP585)using the green water scarcity(GWS)index based on raster-scale crop spatial distribution data,Delta downscaling bias-corrected ERA5 data,and CMIP6 multimodal *** the base period,the green water risk-free zone for dry crops is mainly distributed in the center and east of the Northeast region(72.4% of the total area),the low-risk zone is primarily located in the center(14.0%),and the medium-risk(8.3%)and high-risk(5.3%)zones are mostly in the *** SSP245 and SSP585 future climate change scenarios,the green water security risk shows an overall expansion from the west to the center and east,with the low-risk zone increasing to 21.6% and 23.8%,the medium-risk zone increasing to 16.0% and 17.9%,and the high-risk zone increasing to 6.9% and 6.8%,*** dry crops with GWS greater than 0.1 as in need of irrigation,the irrigated area increases from 27.6%(base period)to 44.5%(SSP245)and 48.6%(SSP585),with corresponding increases in irrigation water requirement(IWR)of 4.64 and 5.92 billion m~3,respectively,which further exacerbates conflicts between supply and demand of agricultural water *** response to agricultural green water security risks,coping strategies such as evapotranspiration(ET)-based water resource management for dry crops and deficit irrigation are *** results of this study can provide scientific basis and decision support for the development

关键词： Climate change Food security Green water security risk Irrigation water requirement Green water scarcity

FIBTNet:Building Change Detection for Remote Sensing Images Using Feature Interactive Bi-Temporal Network

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Computers, Materials & Continua 2024年第9期80卷 4621-4641页

作者： Jing Wang Tianwen Lin chen zhang Jun peng School of Geographic Information and Tourism Chuzhou UniversityChuzhou239000China Anhui Province Key Laboratory of Physical Geographic Environment Chuzhou UniversityChuzhou239000China

In this paper,a feature interactive bi-temporal change detection network(FIBTNet)is designed to solve the problem of pseudo change in remote sensing image building change *** network improves the accuracy of change detection through bi-temporal feature *** designs a bi-temporal feature exchange architecture(EXA)and a bi-temporal difference extraction architecture(DFA).EXA improves the feature exchange ability of the model encoding process through multiple space,channel or hybrid feature exchange methods,while DFA uses the change residual(CR)module to improve the ability of the model decoding process to extract different features at multiple ***,at the junction of encoder and decoder,channel exchange is combined with the CR module to achieve an adaptive channel exchange,which further improves the decision-making performance of model feature *** results on the LEVIR-CD and S2Looking datasets demonstrate that iCDNet achieves superior F1 scores,Intersection over Union(IoU),and Recall compared to mainstream building change detectionmodels,confirming its effectiveness and superiority in the field of remote sensing image change detection.

关键词： Change detection change residual module feature exchange mechanism feature fusion

Online learning-based model predictive trajectory control forconnected and autonomous vehicles: Modeling and physical tests

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Journal of Intelligent and Connected Vehicles

Journal of Intelligent and Connected Vehicles 2024年第2期7卷 86-96页

作者： Qianwen Li peng zhang Handong Yao Zhiwei chen Xiaopeng Li School of Environmental CivilAgricultural and Mechanical EngineeringUniversity of GeorgiaAthens 30602USA Department of Civil and Environmental Engineering University of Wisconsin–MadisonMadison 53706USA Department of Civil Architecturaland Environmental EngineeringDrexel UniversityPhiladelphia 19104USA

Motivated by the promising benefits of connected and autonomous vehicles (CAVs) in improving fuelefficiency, mitigating congestion, and enhancing safety, numerous theoretical models have been proposed to plan CAVmultiple-step trajectories (time–specific speed/location trajectories) to accomplish various operations. However, limitedefforts have been made to develop proper trajectory control techniques to regulate vehicle movements to follow multiplesteptrajectories and test the performance of theoretical trajectory planning models with field experiments. Without aneffective control method, the benefits of theoretical models for CAV trajectory planning can be difficult to harvest. This studyproposes an online learning-based model predictive vehicle trajectory control structure to follow time–specific speed andlocation profiles. Unlike single-step controllers that are dominantly used in the literature, a multiple-step model predictivecontroller is adopted to control the vehicle’s longitudinal movements for higher accuracy. The model predictive controlleroutput (speed) cannot be interpreted by vehicles. A reinforcement learning agent is used to convert the speed value to thevehicle’s direct control variable (i.e., throttle/brake). The reinforcement learning agent captures real-time changes in theoperating environment. This is valuable in saving parameter calibration resources and improving trajectory control accuracy.A line tracking controller keeps vehicles on track. The proposed control structure is tested using reduced-scale robot *** adaptivity of the proposed control structure is demonstrated by changing the vehicle load. Then, experiments on twofundamental CAV platoon operations (i.e., platooning and split) show the effectiveness of the proposed trajectory controlstructure in regulating robot movements to follow time-specific reference trajectories.

关键词： connected and autonomous vehicles(CAVs) reinforcement learning physical tests time-specific speed and location longitudinal and lateral control

Stabilization and Blow-up in an Infinite Memory Wave Equation with Logarithmic Nonlinearity and Acoustic Boundary Conditions

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Journal of Systems Science & Complexity 2024年第4期37卷 1368-1391页

作者： peng Qingqing zhang Zhifei School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China

In this paper,the authors consider the stabilization and blow up of the wave equation with infinite memory,logarithmic nonlinearity and acoustic boundary *** authors discuss the existence of global solutions for the initial energy less than the depth of the potential well and investigate the energy decay estimates by introducing a Lyapunov ***,the authors establish the finite time blow up results of solutions and give the blow up time with upper bounded initial energy.

关键词： Acoustic boundary condition finite time blow-up general decay infinite memory logarithmic nonlinearity

Brain-inspired chaotic spiking backpropagation

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National Science Review 2024年第6期11卷 169-179页

作者： Zijian Wang peng Tao Luonan chen Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences Key Laboratory of Systems Biology Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Guangdong Institute of Intelligence Science and Technology Pazhou Laboratory(Huangpu)

Spiking neural networks(SNNs) have superior energy efficiency due to their spiking signal transmission,which mimics biological nervous systems, but they are difficult to train effectively. Although surrogate gradient-based methods offer a workable solution, trained SNNs frequently fall into local minima because they are still primarily based on gradient dynamics. Inspired by the chaotic dynamics in animal brain learning, we propose a chaotic spiking backpropagation(CSBP) method that introduces a loss function to generate brain-like chaotic dynamics and further takes advantage of the ergodic and pseudo-random nature to make SNN learning effective and robust. From a computational viewpoint, we found that CSBP significantly outperforms current state-of-the-art methods on both neuromorphic data sets(***-CIFAR10 and DVS-Gesture) and large-scale static data sets(e.g. CIFAR100 and Image Net) in terms of accuracy and robustness. From a theoretical viewpoint, we show that the learning process of CSBP is initially chaotic, then subject to various bifurcations and eventually converges to gradient dynamics,consistently with the observation of animal brain activity. Our work provides a superior core tool for direct SNN training and offers new insights into understanding the learning process of a biological brain.

关键词： spiking neural networks surrogate gradient local minima backpropagation brain-inspired learning chaos

Development of MoS_(2)-stainless steel catalyst by 3D printing for efficient destruction of organics via peroxymonosulfate activation

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Journal of Environmental Sciences 2024年第1期135卷 108-117页

作者： Yufeng Liu Jianhui Xu Xin Fu pengxu Wang Dan Li Yunfei zhang Shenggui chen Chunhui zhang peng Liu School of Environment and Civil Engineering Dongguan University of TechnologyDongguan 523808China School of Art and Design Guangzhou Panyu PolytechnicGuangzhou 511483China Dongguan Institute of Science and Technology Innovation Dongguan University of TechnologyDongguan 523808China School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China

Herein,a novel MoS_(2)-stainless steel composite material was first synthetized via a 3D printing method(3DP MoS_(2)-SS)for peroxymonosulfate(PMS)activation and organics *** with MoS_(2)-SS powder/PMS system(0.37 g/(m^(2)/min)),4.3-fold higher k_(FLO)/S_(BET)value was obtained in 3DP MoS_(2)-SS/PMS system(1.60 g/(m^(2)/min),resulting from the superior utilization of active *** observed that 3DP MoS_(2)-SS significantly outperformed the 3DP SS due to the enhanced electron transfer rate and increased active ***,Mo^(4+)facilitated the Fe^(2+)/Fe^(3+)cycle,resulting in the rapid degradation of florfenicol(FLO).Quenching experiments and electron paramagnetic resonance spectra indicated that·OH,SO_(4)·^(-),O_(2)·^(-)and^(1)O_(2)were involved in the degradation of *** effect of influencing factors on the degradation of FLO were evaluated,and the optimized degradation efficiency of 98.69%was achieved at 1 mM PMS and pH of *** degradation products were detected by UPLC/MS analyses and several possible degradation pathways were proposed to be the cleavage of C-N bonds,dechlorination,hydrolysis,defluorination and *** addition,3DP MoS_(2)-SS/PMS system also demonstrated superior degradation performance for 2-chlorophenol,acetaminophen,ibuprofen and *** study provided deep insights into the MoS_(2)-SS catalyst prepared by 3DP technology for PMS activation and FLO-polluted water treatment.

关键词： 3D printing Stainless steel MoS_(2) Peroxymonosulfate activation Degradation mechanism

Association between heat and upper urinary tract stones morbidity and medical costs: A study in the subtropical humid climate zone

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Advances in Climate Change Research 2024年第4期15卷 717-724页

作者： chen-Lu YANG Jun-Zhe BAO peng BI Ya-Dong zhang Chao-Ming TAN Kai chen College of Public Health Zhengzhou UniversityZhengzhou 450001China School of Public Health The University of AdelaideAdelaide 5000Australia Department of Andrology The First Affliated Hospital of Sun Yat-sen UniversityGuangzhou 510080China Nanjing Social Insurance Management Center Nanjing 210008China Department of Environmental Health Sciences Yale UniversityNew Haven 06520USA Yale Center on Climate Change and Health Yale UniversityNew Haven 06520USA

Urolithiasis is a heat-specific *** heat-related urolithiasis susceptibility subtypes,economic burden,and modifying factors could assist governments in targeting interventions to reduce the heat-related health risks of urolithiasis *** collected data on 23,492 patients with upper urinary tract stones(main subtypes of urolithiasis)from 2013 to 2017 in Nanjing,*** adopted generalized additive quasi-Poisson models to examine the associations between daily mean temperatures and morbidity of upper urinary tract stones,while generalized additive Gaussian models were used to explore the relationships between temperatures and log-transformed medical *** examined the modification effects of disease subtypes(kidney and ureteral calculus),sex,and age through stratified analyses and the modif-cation effects of other meteorological factors by introducing interaction terms in the *** found that short-term summer heat exposure has a statistically significant effect on ureteral calculus morbidity but not on kidney calculus *** ureter calculus,a 1℃ temperature increase was associated with a 4.36%(95%confidence interval[CI]:1.94%,6.83%)increase in daily hospitalization and a 5.44%(95%CI:2.71%,8.25%)increase in daily medical *** attributable fraction associated with heat(greater than the median value of daily mean temperature,26.8℃)was 7.85%(95%empirical confidence interval[eCI]:3.64%,11.44%)for hospitalization and 9.36%(95%eCI:4.91%,13.14%)for medical *** effects of heat on ureter calculus morbidity were significantly higher among the males and those with high sunshine duration than females and those with low sunshine ***-term summer heat exposure was associated with increased morbidity and medical costs of ureteral *** government organizations should take effective intervention measures,including community health education,to reduce the health hazards and economic losses caused by heat.

关键词： Heat Upper urinary tract stones Economic burden Modification effects

Comparison of Adaptive Simulation Observation Experiments of the Heavy Rainfall in South China and Sichuan Basin

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Advances in Atmospheric Sciences 2024年第11期41卷 2173-2191页

作者： Linbin HE Weiyi peng Yu zhang Shiguang MIAO Siqi chen Jiajing LI Duanzhou SHAO Xutao zhang College of Ocean and Meteorology Guangdong Ocean UniversityZhanjiang 524088China Chinese Academy of Meteorology Sciences Beijing 100081China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China School of Marine Sciences Nanjing University of Information Science and TechnologyNanjing 210044China Dalian Marine Center Ministry of Nature Resources of the People's Republic of ChinaDalian 116001China

This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.

关键词： adaptive observation ensemble transform sensitivity data assimilation rainfall

Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 673-689页

作者： Cong Pan Junran peng Zhaoxiang zhang the Center for Research on Intelligent Perception and Computing(CRIPAC) National Laboratory of Pattern Recognition(NLPR)Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 the School of Future Technology University of Chinese Academy of Sciences(UCAS)Beijing 100049China the Huawei Inc. Beijing 100085China IEEE the Institute of Automation Chinese Academy of Sciences(CASIA)Beijing 100190 the University of Chinese Academy of Sciences(UCAS) Beijing 100049 the Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science&Innovation Chinese Academy of Sciences(HKISI CAS)Hong Kong 999077China

Monocular 3D object detection is challenging due to the lack of accurate depth *** methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB ***-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion ***,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with *** from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth *** we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each ***,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input *** method is the first Swin-Transformer-based backbone architecture for monocular 3D object *** experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.

关键词： Monocular 3D object detection normalizing flows Swin Transformer