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Revealing the Role of Defect in 3D Graphene-Based Photocatalytic Composite for Efficient Elimination of Antibiotic and Heavy Metal Combined Pollution

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Energy & Environmental Materials 2024年第3期7卷 164-174页

作者： Xin Wang Jingzhe Zhang Hui Wang Mengjun Liang Qiang Wang Fuming Chen Research Institute of Frontier Science Southwest Jiaotong UniversityChengdu 610031China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials School of Electronics and Information EngineeringSouth China Normal UniversityFoshan 528225China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068China MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an 710049China

Defect engineering can give birth to novel properties for adsorption and photocatalysis in the control of antibiotics and heavy metal combined pollution with photocatalytic ***,the role of defects and the process mechanism are complicated and ***,TiO_(2)/CN/3DC was fabricated and defects were introduced into the tripartite structure with separate O_(2)plasma treatment for the single *** find that defect engineering can improve the photocatalytic activity,attributing to the increase of the contribution from h^(+)and *** contrast to TiO_(2)/CN/3DC with a photocatalytic tetracycline removal rate of 75.2%,the removal rate of TC with D-TiO_(2)/CN/3DC has increased to 88.5%.Moreover,the reactive sites of tetracycline can be increased by adsorbing on the defective *** defect construction on TiO_(2)shows the advantages in tetracycline degradation and Cu^(2+)adsorption,but also suffers significant inhibition for the tetracycline degradation in a tetracycline/Cu^(2+)combined *** contrast,the defect construction on graphene can achieve the cooperative removal of tetracycline and Cu^(2+).These findings can provide new insights into water treatment strategies with defect engineering.

关键词： 3D graphene Cu defect photocatalytic composite tetracycline

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Flow field characteristics,mixing and emissions performance of a lab-scale rich-quench-lean trapped-vortex combustor utilizing a quench orifice plate combined with a bluff-body

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Chinese Journal of Aeronautics 2021年第4期34卷 476-492页

作者： Bo JIANG Gaowei CUI Yi JIN Ziqiang ZHAO Dong LIU Xiaomin HE MIIT Key Laboratory of Thermal Control of Electronic Equipment School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China Advanced Combustion Laboratory School of Energy and Power EngineeringNanjing University of Science and TechnologyNanjing 210094China Jiangsu Province Key Laboratory of Aerospace Power Systems Nanjing 210016China Shanghai Aerospace Control Technology Institute Shanghai 201109China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Beijing Power Machinery Institute Beijing 100074China

In this study,the low emission combustion technology of Rich-Quench-Lean(RQL)has been applied in Trapped-Vortex Combustor(TVC),and the combinative RQL-TVC shows a promising low emissions *** utilizing a quench orifice plate combined with a bluffbody,a lab-scale RQL-TVC was *** flow fields of RQL-TVC were measured by 2-D PIV and predicted by 3-D numerical *** structures,radial profiles of normalized mean axial velocity,turbulence intensity and mixing level of the quench zone were *** reveal that the dual-vortex and the single-vortex flow patterns both exist in cavities and quench zone of RQL-TVC,and the turbulence intensity is strong in the quench zone with some reverse *** spiral vortex was discussed by 3-D streamlines and the detail flow structures of the quench zone were analyzed based on the numerical *** mixing level of the quench zone was determined,and results show that the quench device enhances the mixing level compared with *** efficiency and emissions performance were investigated experimentally,and results demon-strate that RQL-TVC has relatively higher combustion efficiency and lower emission index of CO,UHC and NO_xthan the same size lab-scale TVC in present work.

关键词： RQL TVC Quench orifice plate Flow field Mixing level Emissions performance

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Yolo-S: Texture-Less Object Pose Estimation with Shape Prior

Yolo-S: Texture-Less Object Pose Estimation with Shape Prior

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Data Driven control and Learning Systems (DDCLS)

作者： Danzhu Wang Shan Liu Polytechnic Institute Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper aims to address the challenge of pose estimation for texture-less objects under conditions of stacking, occlusion, and complex backgrounds. The proposed method, called Yolo-S, consists of two parts: a pre-estimation network based on Yolov8 backbone and a key point post-refinement network based on Graph Neural Network. The first part uses off-the-shelf detectors result as inputs (e.g. MaskRCNN) and outputs the pre-estimate keypoints at the pixel coordinates. The second part encodes the roughly estimated keypoints and the priori knowledge of the object's CAD model, uses a graph neural network to intergrate feature and predict the final keypoints. PNP method is used to obtain the object's pose. The main advantage of Yolo-S is that is has a prior knowledge embedded GNN model for estimating the pose of texture-less objects, which greatly improves prediction quality and accuracy and achieves zero-shot sim-to-real model transfer. Experimental results on the LINEMOD dataset demonstrate the effectiveness of the proposed method and its significant competitiveness with other state-of-the-art methods.

关键词： Knowledge engineering Solid modeling Three-dimensional displays Computational modeling Image edge detection Pose estimation Stacking

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Deep Learning of Process Data with Supervised Variational Auto-encoder for Soft Sensor 11

Deep Learning of Process Data with Supervised Variational Au...

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Tang, Xiaochu Yan, Jiawei Song, Zhihuan Zhang, Xinmin School of Automation Shenyang Aerospace University Liaoning Province Shenyang110136 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Nonlinearity and uncertainty are two critical characteristics when process data modeling is applied to soft sensor. In this paper, a supervised variational auto-encoder (SVAE) is developed to capture both nonlinear and untcertain feature for regression modeling. SVAE, as a deep generative model, provides a probabilistic framework, based on which the deep nonlinear feature extraction is carried out and a probabilistic respresentation can be obtained. In this way, the probability distribution mapping between process data and key quality variables is learned so that quality prediction can be well achieved. The feasibility of the proposed method is illustrated by a numerical example and an industrial example, and the effectiveness of the proposed model is verified by comparing with the linear model. © 2022 IEEE.

关键词： Probability distributions

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Global methyl halide emissions from biomass burning during 2003-2021

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Environmental Science and Ecotechnology 2023年第2期14卷 79-86页

作者： Xiaoyi Hu Di Chen Liting Hu Bowei Li Xinhe Li Xuekun Fang College of Environmental&Resource Sciences Zhejiang UniversityHangzhouZhejiang310058PR China State Key Joint Laboratory for Environmental Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking UniversityBeijing100871PR China Center for Global Change Science Massachusetts Institute of TechnologyCambridgeMA02139USA

Methyl halides(CH3Cl,CH3Br,and CH3I)are ozone-depleting *** burning(BB)is an important source of methyl *** temporal variations and global spatial distribution of BB methyl halide emissions are ***,global methyl halide emissions from BB during 2003e2021 were estimated based on satellite data.A significant decreasing trend(p<0.01)in global methyl halide emissions from BB was found between 2003 and 2021,with CH3Cl emissions decreasing from 302 to 220 Gg yr^(-1),CH3Br emissions decreasing from 16.5 to 11.7 Gg yr^(-1),and CH3I emissions decreasing from 8.9 to 6.1 Gg yr^(-1).From a latitudinal perspective,the northern high-latitude region(60e90N)was the only latitude zone with significant increases in BB methyl halide emissions(p<0.01).Based on an analysis of the drivers of BB methyl halide emissions,emissions from cropland,grassland,and shrubland fires were more correlated with the burned area,while BB emissions from forest fires were more correlated with the emissions per unit burned *** non-BB emissions of CH3Cl increased from 4749 Gg yr^(-1)in 2003 to 4882 Gg yr^(-1)in 2020,while those of CH3Br decreased from 136 Gg yr^(-1)in 2003 to 118 Gg yr^(-1)in 2020(global total CH3I emissions are not available).The finding indicates that global CH3Cl and CH3Br emissions from sources besides BB increased and decreased during *** on our findings,not only searching for unknown sources is important,but also re-evaluating known sources is necessary for addressing methyl halide emissions.

关键词： Methyl halides Biomass burning Emission inventory Global budget Ozone depletion

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Oracle Bone Inscriptions Image Recognition and Classification Method Based on Deep Learning 7

Oracle Bone Inscriptions Image Recognition and Classificatio...

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7th IEEE Information technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Zhu, Mingzhi Wu, Di Xu, Binbin Cao, Shunhua Cao, Jie Wang, Kaiwei Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China College of Civil and Transportation Engineering Shenzhen University Shenzhen China College of Economics Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology Guangzhou China China Electronic Product Reliability and Environmental Testing Research Institute GuangZhou China

ISBN: (纸本)9798350370782

Applying advanced image processing and deep learning techniques to the segmentation and recognition of oracle bone inscriptions can help accelerate the research process and improve the efficiency of cultural relic protection and historical and cultural research. Firstly, mathematical morphology methods are used to denoise the original oracle bone rubbings, which can better identify and process interfering elements. Subsequently, by applying one of the most advanced visual algorithm models, YOLOv8, to image recognition and segmentation of raw oracle bone rubbings, the recognition and segmentation tasks can be quickly and accurately completed. Finally, an improved ConvNeXt, which represents the most advanced convolutional neural network, was firstly applied to the classification experiment of oracle bone character images, achieving a validation accuracy of 94.5%. Through the aforementioned steps, a complete and effective method for pre-processing, image recognition, image segmentation, and image classification of oracle bone inscriptions is constructed in this paper. © 2024 IEEE.

关键词： Convolutional neural networks

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3D printed fiber-optic nanomechanical bioprobe

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International Journal of Extreme Manufacturing 2023年第1期5卷 222-234页

作者： Mengqiang Zou Changrui Liao Yanping Chen Lei Xu Shuo Tang Gaixia Xu Ke Ma Jiangtao Zhou Zhihao Cai Bozhe Li Cong Zhao Zhourui Xu Yuanyuan Shen Shen Liu Ying Wang Zongsong Gan Hao Wang Xuming Zhang Sandor Kasas Yiping Wang Guangdong and Hong Kong Joint Research Centre for Optical Fibre Sensors College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China School of Electronic and Communication Engineering Shenzhen PolytechnicShenzhen 518000People’s Republic of China Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical EngineeringHealth Science CenterShenzhen UniversityShenzhen 518055People’s Republic of China Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China Laboratory of Food and Soft Materials Department of Health Sciences and TechnologyETH Zurich8092 ZurichSwitzerland Wuhan National Laboratory for Optoelectronics(WNLO) Huazhong University of Science and Technology(HUST)Wuhan 430074People’s Republic of China Department of Applied Physics The HongKong Polytechnic UniversityHong KongPeople’s Republic of China Laboratory of Biological Electron Microscopy Ecole Polytechnique Fédérale de Lausanne1015 LausanneSwitzerland UnitéFacultaire d’Anatomie et de Morphologie(UFAM) CUMRLUniversity of Lausanne1005 LausanneSwitzerland

Ultrasensitive nanomechanical instruments,*** force microscopy(AFM),can be used to perform delicate biomechanical measurements and reveal the complex mechanical environment of biological ***,these instruments are limited because of their size and complex feedback *** this study,we demonstrate a miniature fiber optical nanomechanical probe(FONP)that can be used to detect the mechanical properties of single cells and in vivo tissue measurements.A FONP that can operate in air and in liquids was developed by programming a microcantilever probe on the end face of a single-mode fiber using femtosecond laser two-photon polymerization *** realize stiffness matching of the FONP and sample,a strategy of customizing the microcantilever’s spring constant according to the sample was proposed based on structure-correlated *** a proof-of concept,three FONPs with spring constants varying from 0.421 N m^(−1)to 52.6 N m^(−1)by more than two orders of magnitude were *** highest microforce sensitivity was 54.5 nmμN^(−1)and the detection limit was 2.1 *** Young’s modulus of heterogeneous soft materials,such as polydimethylsiloxane,muscle tissue of living mice,onion cells,and MCF-7 cells,were successfully measured,which validating the broad applicability of this *** strategy provides a universal protocol for directly programming fiber-optic ***,this method has no special requirements for the size and shape of living biological samples,which is infeasible when using commercial *** has made substantial progress in realizing basic biological discoveries,which may create new biomedical applications that cannot be realized by current AFMs.

关键词： two-photon polymerization nanolithography optical fiber sensor nanomechanical probe stiffness tunable microcantilever biosensor

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The impact of AR-HUD lane enhancement on lateral control performance under fog conditions 8

The impact of AR-HUD lane enhancement on lateral control per...

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8th International Conference on Traffic engineering and transportation System, ICTETS 2024

作者： Zeng, Mengjin Tang, Qiuyang Deng, Pingping Jia, Yuchen Zhang, Yu Chen, Haolin Yu, Duan Zhao, Xiaohua Electronic Communication and Software Evaluation Research Center China Automotive Engineering Research institute Co. Ltd. 9 Jinyu Ave. Yubei District Chongqing401120 China Beijing Key Laboratory of Traffic Engineering College of Metropolitan Transportation Beijing University of Technology 100 Pingleyuan Rd. Chaoyang District Beijing100124 China

ISBN: (数字)9781510686298

ISBN: (纸本)9781510686281

This study investigates the impact of Augmented Reality Head-Up Display (AR-HUD) lane enhancement system on lateral control performance in fog conditions. Using Unity-based simulations, a controlled, immersive driving scenario in fog was created to assess the impact of the AR-HUD system on lateral control performance. Participants drove on a curved road in a foggy environment while their lateral control metrics, specifically steering speed (SS) and standard deviation of lateral position (SDLP), were monitored. The results showed that the AR-HUD system significantly reduced SS and SDLP in all driving segments, demonstrating improved steering accuracy and stability. Notably, the most significant improvements were observed during the initial phase when foggy conditions were encountered, i.e., the Approach Segment, highlighting the utility of the AR-HUD when transitioning to low visibility conditions. © 2024 SPIE.

关键词： Head-up displays

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Experimental Study on the Characterisation Parameters of Shield Tunnel Single-Fluid Inert Synchronized Grouting Slurry 9

Experimental Study on the Characterisation Parameters of Shi...

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9th International Technical Conference on Frontiers of Hydraulic and Civil engineering technology, HCET 2024

作者： Liu, Heng Wei, Binpin Wu, Shuwei Xi, Xiaoguang Cao, Hong Wang, Zhe Zhang, Qiongfang Sheng, Jianchao Tengda Construction Group Co. Ltd. Shanghai200122 China Zhejiang Key Laboratory of Civil Engineering Structures & Disaster Prevention and Mitigation Technology Zhejiang University of Technology Hangzhou Zhejiang310012 China Shaoxing Transportation Construction Co. Ltd Shaoxing312099 China Hangzhou Municipal Facilities Management Center Hangzhou313099 China Huadong Engineering Corporation Limited Hangzhou311100 China

ISBN: (纸本)9781643685595

Shield tunneling technology has been widely applied in subway construction. To effectively control ground deformation, synchronous grouting behind the shield has become a crucial method and key process in shield construction. Appropriate synchronous grouting parameters are essential for guiding both theoretical research and engineering practice in shield tunneling. A series of laboratory tests were conducted to study the characterization parameters of single-fluid inert grout uplift. The relationships between synchronous grouting parameters-such as slump, consistency, buoyancy, flow index, and shear strength-were obtained. The results indicate that the flow index can serve as a characterisation parameter for grout fluidity, and the shear strength of P2.0~P2.5 with greater buoyancy variation can be used as a characterization parameter for grout uplift. In contrast, consistency and slump are not suitable as fluidity characterisation parameters. © 2024 The Authors.

关键词： representation parameters shear strength of slurry Shield tunnel slurry fluidity synchronous grout

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Conjunction Screening Method for Cataloged Space Objects Based on GCN Model

Conjunction Screening Method for Cataloged Space Objects Bas...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Qinghao Chu Zhelong Wang Yu Jiang Pengrong Hou School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Astronautic Dynamics Xi'an Satellite Control Center Xi'an China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

As the space environment becomes increasingly congested, efficiently identifying and mitigating potential on-orbit collisions has become critical for Space Traffic Management (STM). However, the rapid growth in the number of Resident Space Objects (RSOs) presents significant challenges for accurate collision risk assessment. Advanced conjunction screening methods are essential to enhance the efficiency of collision analysis. In this study, we formulate the all-vs-all conjunction screening as a link prediction problem within the framework of Graph Neural Network (GNN). Specifically, we develop a Graph Convolutional Network (GCN) model to capture graph topology features, thereby identifying spatial dependencies between nodes. The exper-imental findings indicate that the proposed GCN model attains an F1-score of 0.8847, successfully forecasting con-junction events involving RSOs and outperforming current approaches.

关键词： Accuracy Network topology Graph convolutional networks Predictive models Rendering (computer graphics) Market research Topology Risk management Splines (mathematics) Forecasting

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