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Impact of net-zero emissions on atmospheric CO_(2) concentration in China: Ideal simulations based on the GEOS-Chem model

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science China Earth sciences 2025年第3期68卷 867-881页

作者： Jingye TAN Jun WANG Huiqin MAO Hengmao WANG Zhiqiang LIU Meirong WANG Ran YAN Xunmei WANG Fei JIANG Frontiers Science Center for Critical Earth Material Cycling International Institute for Earth System ScienceNanjing UniversityNanjing 210023China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China Satellite Environmental Application Center Ministry of Environmental ProtectionBeijing 100094China CMA Key Open Laboratory of Transforming Climate Resources to Economy Chongqing Institute of Meteorological SciencesChongqing 401147China State Key Laboratory of Climate System Prediction and Risk Management Key Laboratory of Meteorological DisasterMinistry of EducationCollaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Xizang Field Station for Scientific Observation and Research on Atmospheric Water Cycle in Mêdog Xigazêand Mêdog National Climate ObservatoryXizang Meteorological ServiceLhasa 850000China

Elevated atmospheric carbon dioxide(CO_(2)) concentrations have caused global climate change such as global warming and more frequent climate extremes. Countries worldwide have proposed carbon neutrality strategies to curb the rising CO_(2) concentrations. To investigate the impact of China's carbon neutrality goal on atmospheric CO_(2) concentrations, we conducted a series of ideal simulations from 2015 to 2019 using a global 3D chemistry transport model, Goddard Earth Observing system Chemistry(GEOS-Chem). Compared with the column-averaged dry-air mole fraction of atmospheric CO_(2) (XCO_(2) ) from Orbiting Carbon Observatory-2(OCO-2) and surface CO_(2) measurements in Obs Pack, we find that GEOS-Chem effectively reproduces the spatiotemporal variability of CO_(2) . The model exhibits a root mean square error(RMSE) of 1.51 ppm(R^(2)=0.89) for OCO-2 XCO_(2) in China and 2.65 ppm(R^(2)=0.75) for surface CO_(2) concentrations at the WLG station. Further, compared to 2.83 ppm yr^(-1)in the control experiment, we suggest that net-zero CO_(2) emissions in China decelerate the increasing trends of XCO_(2) to 1.81 ppm yr^(-1),making a decrease of approximately 35.89%. Meanwhile, the seasonal cycle amplitude(SCA) of XCO_(2) is moderately reduced from 7.39±0.81 to 6.75±0.70 ppm, representing a relative reduction of 9.91%. Spatially, net-zero CO_(2) emissions induce a more significant decrease in XCO_(2) trends over northern and southern China, while their impact on SCA is more evident in northern and northeastern China. Moreover, ideal experiments demonstrate that zero fossil CO_(2) emissions lead to a greater attenuation of the linear trends of XCO_(2) by 40.81%, while the absence of terrestrial CO_(2) sinks largely diminishes the SCA by 16.61%. Additionally,trends and SCA in surface CO_(2) concentrations exhibit almost identical decreasing responses to net-zero CO_(2) emissions but display greater sensitivities compared to XCO_(2) . Overall, our study underscores the pote

关键词： XCO_(2) GEOS-Chem Carbon neutrality Net-zero emissions Surface CO_(2)concentrations

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Research on Improving Wavelet Thresholding Method for Noise Reduction of Current Ripples in Motors

Research on Improving Wavelet Thresholding Method for Noise ...

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International Conference of Electrical, Electronic and Networked Energy systems, EENES 2024

作者： Qin, Xu Wang, Wei School of Electronic and Information Engineering Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and System Tianjin China Engineering Research Center of Ministry of Education for High Power Semiconductor Lighting Application System Tianjin China

ISBN: (纸本)9789819620456

The vigorous development of new energy vehicles has brought new opportunities and challenges to related industries. In order to gain greater competitive advantages, major automobile manufacturers have begun to focus on using motor current ripple signals directly to achieve various functions in a cheaper and more integrated way. However, the current ripple signal generated when the motor rotates is mixed with a lot of noise. If it is to be put into practical application, it needs to be denoised first, such as the improved wavelet threshold denoising method studied in this paper. First, the denoising principle and the shortcomings of the traditional method are introduced, and the design of the improved method is given on this basis. Subsequently, verification is conducted using simulated signals and actual current ripple signals, with SNR (Signal to Noise Ratio) and RMSE (Root Mean Square Error) used as quantitative evaluation criteria for comparing and analyzing the results. Finally, the experiments have confirmed that the improved threshold method proposed in this paper outperforms traditional methods in noise removal, proving its significance and value for further research. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Noise abatement

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Targeted-tuning competitive acidic CO2RR via metalloid antagonism sites

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Materials Today 2025年 83卷 54-63页

作者： Sheng, Beibei Cao, Dengfeng Qi, Zhenghang Shou, Hongwei Xia, Yujian Su, Xiaozhi Chen, Shuangming Wu, Chuanqiang Liu, Hengjie Chimtali, Peter Joseph Chu, Yongheng Liu, Chongjing Wu, Xiaojun Song, Li National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience Key Laboratory of Precision and Intelligent Chemistry School of Nuclear Science and Technology University of Science and Technology of China Hefei230029 China SINOPEC Shanghai Research Institute of Petrochemical Technology Co. Ltd. Shanghai201208 China Engineering Laboratory of Chemical Resources Utilization in South Xinjiang of Xinjiang Production and Construction Corps College of Chemistry and Chemical Engineering Tarim University Alar843300 China School of Chemistry and Materials Science CAS Center for Excellence in Nanoscience and Synergetic Innovation of Quantum Information & Quantum Technology Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei230026 China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley CA94720 United States Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201204 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

To mitigate the high separation costs associated with conventional neutral/alkaline electrocatalysis for CO2 reduction reactions (CO2RR), acidic CO2RR offers economic advantages and improved efficiency in CO2 utilization. However, it typically involves the cleavage of M−H bonds at a relatively negative potential, leading to the predominant formation of H2 and poor HCOOH selectivity. Herein, we develop a facile solid-phase thermal diffusion approach to controllably synthesize a novel metalloid-metal single atom alloys (m-SAAs) electrocatalyst Te1Bi with unique metalloid antagonistic sites, thus enabling high-efficient acidic CO2-to-HCOOH conversion. Electrochemical test and operando synchrotron radiation multi-techniques (SRMS) characterization reveal that metalloid Te sites bring steric hindrance effect and blocks *H coupling. Furthermore, it actively adsorbs OH− species as a proton source, allowing for effective separation of protons and electrons in space. Thus, leading to enhanced hydrogenation in acidic CO2RR to produce HCOOH. The flow cell test results demonstrate that the carefully designed Te1Bi catalyst exhibits a milder reaction potential, along with higher HCOOH Faraday efficiency (∼94.5 %) and single-pass carbon efficiency (SPCE, ∼40 %) in acidic media. This work significantly expands the family of SAAs and offers a novel perspective to analyze the regulation of competitive reactions through site-specific modifications for industrial acidic CO2RR. © 2024 Elsevier Ltd

关键词： Synchrotron radiation

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Improved ADRC PMSM Control system Based on Compensation Function Observer

Improved ADRC PMSM Control System Based on Compensation Func...

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International Conference of Electrical, Electronic and Networked Energy systems, EENES 2024

作者： Wu, Chuangyi Wang, Wei School of Electronic and Information Engineering Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and System Tianjin China Engineering Research Center of Ministry of Education for High Power Semiconductor Lighting Application System Tianjin China

ISBN: (纸本)9789819620791

The Adaptive Disturbance Rejection Control (ADRC) is widely used in nonlinear systems such as Permanent Magnet Synchronous Motors (PMSM) due to its adaptability, strong robustness, and ease of implementation. However, traditional ADRC performs poorly in high-order nonlinear systems, as its performance mainly depends on the nonlinear function representing the total disturbance. To address this issue, this paper proposes an improved ADRC based on the Compensation Function Observer (CFO). The CFO belongs to the type III system, exhibiting significantly improved signal processing performance compared to the type I Extended State Observer (ESO), and it can attenuate the influence of the nonlinear function in the compensation stage. Additionally, in order to alleviate the difficulty of parameter tuning in ADRC, fuzzy control is introduced in the error feedback loop. The feasibility of the proposed method is verified by establishing a Matlab/Simulink simulation model. The simulation results demonstrate that, compared to traditional ADRC, the new ADRC exhibits better response speed and disturbance rejection for common signals. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： MATLAB

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DD-Net: Dynamic Network Architecture for Optimized Curve Segmentation and Reduce Computational Redundancy 27th

DD-Net: Dynamic Network Architecture for Optimized Curve Seg...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Cao, Yunxiang Chen, Li Wang, Yubo Feng, Zhida Tian, Jing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Institute of Systems Science National University of Singapore Singapore Singapore

ISBN: (纸本)9783031783821

Curvilinear Structure segmentation has numerous applications in various fields, including providing a better understanding of defects such as cracks on roads or walls, thereby assessing the structural safety of buildings. Numerous curve segmentation methods based on Convolutional Neural Networks(CNN) have been developed in recent years. However, preserving feature integrity remains a challenge. To address this issue, this paper introduces a double dynamic network, called DD-Net, which consists of a dynamic structure for training and dynamic masking for inference. Firstly, to enhance the nonlinearity of the model, a paradigm to auto-adjust the CNN structure via a trainable module is formed for better fine-grained feature extraction. This dynamic structure (DS) paradigm enables a trade-off to extract or discard the feature data in the model training. Due to the data heterogeneity between the training and inference data, models may contain some useless nodes that are less effective during inference. The dynamic masking (DM) is proposed to omit the useless nodes based on the score difference between the train and inference feature statistics, thereby reducing redundant computations. To further improve the model’s performance on thin-curve segmentation and to preserve feature integrity, we introduce a non-curve suppression (NCS) module. This module focuses on background information while considering foreground prediction to address noisy conditions. The experimental results show that our DD-Net achieves promising results on three benchmark datasets and outperforms state-of-the-art curve segmentation models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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MM-UKAN++: A Novel Kolmogorov–Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation

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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 2025年第4期72卷 498-514页

作者： Zhang, Boheng Huang, Haorui Shen, Yi Sun, Mingjian Harbin Institute of Technology Department of Control Science and Engineering Heilongjiang Harbin150001 China Pohang University of Science and Technology Department of Convergence IT Engineering Pohang37673 Korea Republic of Harbin Institute of Technology Suzhou Research Institute Jiangsu Suzhou215000 China Harbin Institute of Technology Department of Information Science and Engineering Shandong Weihai264200 China Harbin Institute of Technology Shandong Weihai264200 China Shandong Laboratory of Advanced Biomaterials and Medical Devices Shandong Weihai264209 China

Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (ROIs) in US images is essential for enhancing the efficiency of clinical and robot-assisted diagnosis. However, US images suffer from low contrast, fuzzy boundaries, and significant scale variations in ROIs. Existing convolutional neural network (CNN)-based and transformer-based methods struggle with model efficiency and explainability. To address these challenges, we introduce MM-UKAN++, a novel U-shaped network based on Kolmogorov-Arnold networks (KANs). MM-UKAN++ leverages multilevel KAN layers as the encoder and decoder within the U-network architecture and incorporates an innovative multidimensional attention mechanism to refine skip connections by weighting features from frequency-channel and spatial perspectives. In addition, the network effectively integrates multiscale information, fusing outputs from different scale decoders to generate precise segmentation predictions. MM-UKAN++ achieves higher segmentation accuracy with lower computational cost and outperforms other mainstream methods on several open-source datasets for US image segmentation tasks, including achieving 69.42% IoU, 81.30% Dice, and 3.31 mm HD in the BUSI dataset with 3.17 G floating point of operations (FLOPs) and 9.90 M parameters. The excellent performance on our automatic carotid artery US scanning and diagnostic system further proves the speed and accuracy of MM-UKAN++. Besides, the good performance in other medical image segmentation tasks reveals the promising applications of MM-UKAN++. The code is available on GitHub. © 1986-2012 IEEE.

关键词： Image segmentation

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Multitarget gas alarm system for high-performance and anti-interference chemical warfare agents simulants detection

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science China(Technological sciences) 2025年第3期68卷 349-358页

作者： Yubin YUAN Qiang WU Menglong JIAO Haiyang WU Weihua LIU Xuming WANG Xiangrui BU Gong LI Chuanyu HAN Long HU Xin LI Xiaoli WANG Shool of Microelectronics School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’an710049China The Key Lab of Micro-nano Electronics and System Integration of Xi’an City Xi’an710049China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou310024China School of Automation and Information Engineering Xi’an University of TechnologyXi’an710048China Key Laboratory for Physical Electronics and Devices of the Ministry of Education Xi’an Jiaotong UniversityXi’an710049China School of Science Xi’an Jiaotong UniversityXi’an710049China

Chemical warfare agents(CWAs)can cause significant harm to health and even death in a very short time even when inhaled in small amounts(~100 mg min/m^(3)).Detection equipment based on conventional techniques,including gas chromatography-mass spectrometry,Raman spectroscopy,fluorescence spectroscopy,and ion mobility spectrometry,have the disadvantages of high cost,long detection time,and high power ***,portable,and convenient equipment for target CWAs detection under interference is a *** this study,we propose an alarm system comprising a multitype micro sensor array and a field-programmable gate array-based readout circuit for CWAs simulants *** common volatile organic compound,temperature,and water vapor interference,the proposed multitype sensor-based detection system realizes an alarm function in less than 20 s with thresholds of 1 ppm dimethyl methylphosphonate(DMMP),4.6 ppm 2,2'-dichlorodiethyl ether(DCE),and 20 ppm SO_(2).Furthermore,the proposed detection system was evaluated outside the laboratory and passed the wilderness test,demonstrating its reliability in the *** believe that the proposed alarm system will contribute to the development of intelligent,portable,low-cost,and anti-interference CWAs detection technology.

关键词： alarm system CWAs simulants surface acoustic wave sensor mixed gas anti-interference

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Thermal stress concentration points and stress mutations in nano-multilayer film structures

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Communications in Theoretical Physics 2025年第1期77卷 179-189页

作者： Ying Zheng Zhi You Wang Qianju Song Zao Yi Shubo Cheng Can Ma Chaojun Tang Qingdong Zeng Sohail Ahmad School of Mathematics and Science Joint Laboratory for Extreme Conditions Matter PropertiesThe State Key Laboratory of Environment-friendly Energy MaterialsTianfu Institute of Research and InnovationSouthwest University of Science and TechnologyMianyang 621010China School of Electronic Information and Electric Engineering Changsha UniversityChangsha 410022China School of Physics and Optoelectronic Engineering Yangtze UniversityJingzhouHubei 434023China School of Chemistry and Chemical Engineering Jishou UniversityJishou 416000China Department of Oncology Sichuan Science City HospitalMianyangSichuan Province 621000China College of Science Zhejiang University of TechnologyHangzhou 310023China School of Physics and Electronic-information Engineering Hubei Engineering UniversityXiaogan 432000China Institute of Physics Bahauddin Zakariya UniversityMultan66000Pakistan

In the multilayer film-substrate system,thermal stress concentration and stress mutations cause film buckling,delamination and cracking,leading to device *** this paper,we investigated a multilayer film system composed of a substrate and three film *** thermal stress distribution inside the structure was calculated by the finite element method,revealing significant thermal stress differences between the *** is mainly due to the mismatch of the coefficient of thermal expansion between *** materials respond differently to changes in external temperature,leading to compression between *** are obvious thermal stress concentration points at the corners of the base layer and the transition layer,which is due to the sudden change of the shape at the geometric section of the structure,resulting in a sudden increase in local *** address this issue,we chamfered the substrate and added an intermediate layer between the substrate and the transition layer to assess whether these modifications could reduce or eliminate the thermal stress concentration points and extend the service life of the multilayer *** results indicate that chamfering and adding the intermediate layer effectively reduce stress discontinuities and mitigate thermal stress concentration points,thereby improving interlayer bonding strength.

关键词： multilayer structure thermal stress concentration point stress mutation chamfer intermediate layer

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Annual Optimal Performance Analysis of Micro Heat Pipe PV/T under Different Angles in Northwest China

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Journal of Thermal science 2025年第2期34卷 400-412页

作者： LIU Xiaomin WU Qingbai LI Jinping Vojislav NOVAKOVIC School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou730050China Collaborative Innovation Center for Supporting Technology of Northwest Low-Carbon Towns Lanzhou730050China Gansu Key Laboratory of Complementary Energy System of Biomass and Solar Energy Lanzhou730050China Gansu Natural Energy Research Institute Lanzhou730050China Department of Energy and Process Engineering Norwegian University of Science and TechnologyTrondheimNO-7491Norway

The exploitation of photovoltaic/thermal(PV/T)systems,which facilitate concurrent conversion of solar radiation into electrical and heat energies,presents substantial potential in the solar-abundant northwestern zone of *** investigation endeavors to evaluate the efficacy of a micro heat pipe(M-HP)PV/T system via exhaustive experimental analysis conducted in *** improve the performance of M-HP-PV/T system,a comparison was made between the optimal angles for each day and the entire *** system inside greenhouse exhibited an average photovoltaic conversion efficiency(PCE)and thermal conversion efficiency(TCE)of12.32%and 42.81%.The system of external environment registered average PCE and TCE values of 12.99%and21.08%.To further understand the system's operational results,a mathematical model was constructed through the integration of experimental data,exhibiting good agreement between the simulated outcomes and empirical *** average solar irradiance of daily optimum angle was 728.3 W/m^(2);the annual optimum angle was 29°with an average solar irradiance of 705.6 W/m^(2).The average annual total powers at the optimal angle outside the greenhouse and inside the greenhouse were 448.0 W and 398.7 *** average annual total efficiencies at the optimal angle outside the greenhouse and inside the greenhouse were 40.8%and 56.9%.The total power in the greenhouse was lower by 49.3 W,while total efficiency in the greenhouse was higher by 16.1%.

关键词： solar energy micro heat pipe PV/T system greenhouse optimal angle

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Edge-aware Feature Aggregation Network for Polyp Segmentation

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Machine Intelligence Research 2025年第1期22卷 101-116页

作者： Tao Zhou Yizhe Zhang Geng Chen Yi Zhou Ye Wu Deng-Ping Fan PCA Lab Key Laboratory of Intelligent Perception and Systems for High-dimensional Information of Ministry of EducationSchool of Computer Science and EngineeringNanjing University of Science and TechnologyNanjing210094China School of Computer Science and Engineering Northwestern Polytechnical University(NPU)Xi’an710129China School of Computer Science and Engineering Southeast UniversityNanjing211189China Computer Vision Lab ETH ZürichZürich8092Switzerland

Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfactory segmentation performance with different scales and *** this study,we present a novel edge-aware feature aggregation network(EFA-Net)for polyp segmentation,which can fully make use of cross-level and multi-scale features to enhance the performance of polyp ***,we first present an edge-aware guidance module(EGM)to combine the low-level features with the high-level features to learn an edge-enhanced feature,which is incorporated into each decoder unit using a layer-by-layer ***,a scale-aware convolution module(SCM)is proposed to learn scale-aware features by using dilated convolutions with different ratios,in order to effectively deal with scale ***,a cross-level fusion module(CFM)is proposed to effectively integrate the cross-level features,which can exploit the local and global contextual ***,the outputs of CFMs are adaptively weighted by using the learned edge-aware feature,which are then used to produce multiple side-out segmentation *** results on five widely adopted colonoscopy datasets show that our EFA-Net outperforms state-of-the-art polyp segmentation methods in terms of generalization and *** implementation code and segmentation maps will be publicly at https://***/taozh2017/EFANet.

关键词： Colorectal cancer polyp segmentation edge-aware guidance module scale-aware convolution module cross-level fusion module

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