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IEEE International Conference on Parallel and Distributed computing, Applications and Technologies (PDCAT)

作者： Kejian Li Gang Liu Minhua Lu Guangdong Province Key Laboratory of Popular High Performance Computers Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science and Software Engineering Shenzhen University Shenzhen China School of biomedical engineering Shenzhen University Shenzhen China

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

The performances of modern distributed stream processing systems are critically affected by the distribution of the load across workers. Skewed data streams in real world are very common and pose a great challenge to these systems, especially for stateful applications. key splitting, which allows a single key to be routed to multiple workers, is a great idea to achieve good balance of load in the cluster. However, it comes with the cost of increased memory consumption and computation overhead as well as network communication. In this paper, we present a new definition of metric to model the cost of key splitting for intra-operator parallelism in stream processing systems and provide a novel perspective to reduce replication factor while keeping both overall load imbalance and processing latency low. Similar to previous work, our approach treats the head and the tail of the distribution differently in order to reduce memory requirements. For the head, it uses our proposed notion of regional load imbalance to decide dynamically whether to make one more worker responsible for the heavy hitter or not. For the tail, it simply uses hash partitioning to keep the size of the routing table for the head as small as possible. Extensive experimental evaluation demonstrates that our approach provides superior performance compared to the state-of-the-art partitioning algorithms in terms of load imbalance, replication factor and latency over different levels of skewed stream distributions.

关键词： Partitioning algorithms Memory management Measurement Parallel processing Microsoft Windows Load modeling Throughput

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Environmental, health and economic impact assessment of clean heating renovation: Evidence from 88 cities in northern China

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Environmental Impact Assessment Review 2025年 115卷

作者： Jingting Huang Huili Wang Zhaoyin Liu Li Zhang Hanyu Gao Zhe Wang Yixuan Zheng Xiaojun Chen Lin Zhao Shangmin Guo Bofeng Cai Linyan Li Department of Data Science College of Computing City University of Hong Kong Hong Kong SAR China Center for Carbon Neutrality Chinese Academy of Environmental Planning Beijing 100043 China School of the Environment and Safety Engineering Jiangsu University Zhenjiang 212013 China Department of Chemical and Biological Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong Department of Civil and Environmental Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong State Environmental Protection Key Laboratory of Environmental Pollution and Greenhouse Gases Co-control Chinese Academy of Environmental Planning Beijing 100043 China State Grid Liaoning Electric Power Company Limited Economic Research Institute Shenyang 110000 China Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life Sciences City University of Hong Kong Hong Kong SAR China

To address environmental issues related to heating, the Chinese government launched the “Clean Heating Plan in the Northern Region” as a national energy transition strategy, renovating heating systems for over 30 million households in 88 cities. With the completion of five implementation phases by March 2024, this study presents an evaluation framework to comprehensively assess the environmental, health, and economic impacts of the policy. On-site surveys were conducted annually, monitoring the advancements of clean heating renovations in over 100,000 households across these cities. Combined with air pollution metrics, meteorological data, and city statistical records, a Difference-in-Differences (DID) model with continuous treatment was used to evaluate the environmental benefits associated with the incremental adoption of clean heating in each city. Subsequently, a health impact assessment and cost-benefit analysis were conducted to analyze changes in all-cause mortality and their associated economic benefits. Results indicated an average PM 2.5 reduction of 10.31 μg/m 3 (95 % CI: [9.25, 11.37]) per heating season and an annual reduction of 1573 in all-cause mortality (95 % CI: [630, 2518]). The economic benefits of these improvements were estimated at 717.1 billion CNY, contributing to an average benefit-cost ratio of 1.48. The proposed evaluation framework serves as a structured method for evaluating the environmental, health, and economic impacts of the energy policy and provides robust evidence to support implementing similar initiatives.

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Mapping Heavy Metals in Cultivated Soils Based on Land Use Types and Cokriging 5th

Mapping Heavy Metals in Cultivated Soils Based on Land Use T...

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5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Zhao, Jinling Liu, Chuang Song, Qixiang Jiang, Yan Hong, Qi Huang, Linsheng Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University Hefei230601 China Information Engineering Institute Suzhou University Suzhou234000 China

ISBN: (纸本)9789811308925

It is extremely important to explore the heavy metal content and spatial distribution in different cultivated soils. In our study, cokriging (COK) method was used to investigate the relationship between heavy metals and land use types. A total of six heavy metals including Zn, Fe, Cu, Mn, B, S were selected to forecast the heavy metals in cultivated soils. Five types of cultivated land were considered in the study area, including vegetable land, irrigated land, irrigated paddy field, dry land, orchard. Test of normality was firstly carried out to assure that higher prediction accuracy can be obtained, and then correlation analysis and analysis of variance (ANOVA) were performed to find out the most sensitive heavy metals for spatial interpolation. The analysis results showed that Zn, Cu and Fe were the primary heavy metals in soil of the study area. It was obvious that the effect of Mn and Fe were much greater caused by land use types, while they were smaller for B and S. Three errors of mean standard (MS), root mean square error (RMSE), and root mean square standardized error (RMSSE) were derived to assess the prediction accuracy. In comparison with ordinary kriging (OK), the MS of COK approached to 1, the RMSE was much smaller and the RMSSE also approached to 1, which showed that COK can make better predictions than OK. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Heavy metals

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Gut microbiota and diabetes: From correlation to causality and mechanism

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World Journal of Diabetes 2020年第7期11卷 293-308页

作者： Wei-Zheng Li Kyle Stirling Jun-Jie Yang Lei Zhang Microbiome-X Beijing Advanced Innovation Center for Big Data-Based Precision MedicineSchool of Medicine and EngineeringKey Laboratory of Big Data-Based Precision MedicineBeihang UniversityBeijing 100191China School of Biological Science and Medical Engineering Beihang UniversityBeijing 100191China Luddy School of Informatics Computing and EngineeringIndiana UniversityBloomingtonIN 47408United States The Crisis Technologies Innovation Lab Indiana UniversityThe Information Technology Services and the Pervasive Technology InstituteBloomingtonIN 47408United States Shandong Institute of Industrial Technology for Health Sciences and Precision Medicine Jinan 250000Shandong ProvinceChina College of Life Science Qilu Normal UniversityJinan 250000Shandong ProvinceChina Microbiome Research Center Shandong Institutes for Food and Drug ControlJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Qilu Children's Hospital of Shandong UniversityJinan 250000Shandong ProvinceChina Microbiological Laboratory Lin Yi People’s HospitalLinyi 276000Shandong ProvinceChina Qingdao Human Microbiome Center The Affiliated Central Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina Institute for Medical Dataology Cheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Department of Biostatistics School of Public HealthCheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Research Institute of PediatricsQilu Children's HospitalCheeloo College of MedicineShandong Universityand Jinan Children's HospitalJinan 250022Shandong ProvinceChina

In this review,we summarize the recent microbiome studies related to diabetes disease and discuss the key findings that show the early emerging potential causal roles for *** a global scale,diabetes causes a significant negative impact to the health status of human *** review covers type 1 diabetes and type 2 *** examine promising studies which lead to a better understanding of the potential mechanism of microbiota in diabetes *** appears that the human oral and gut microbiota are deeply interdigitated with *** is that *** studies of the human microbiome are capturing the attention of scientists and healthcare practitioners worldwide by focusing on the interplay of gut microbiome and *** studies focus on the role and the potential impact of intestinal microflora in *** paint a clear picture of how strongly microbes are linked and associated,both positively and negatively,with the fundamental and essential parts of diabetes in *** microflora seems to have an endless capacity to impact and transform *** conclude that there is clear and growing evidence of a close relationship between the microbiota and diabetes and this is worthy of future investments and research efforts.

关键词： Diabetes Microbiota Causality Mechanism Type 1 diabetes Type 2 diabetes Insulin resistance Inflammation Metabolites

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Empirical topological investigation of practical supply chains based on complex networks

引用

Chinese Physics B 2017年第11期26卷 144-150页

作者：廖好沈婧吴兴桐陈博奎周明洋 National Engineering Laboratory for Big Data Computing Systems Guangdong Province Key Laboratory of Popular High Performance ComputersCollege of Computer Science and Software Engineering Shenzhen University Department of Computer Science School of Computing National University of Singapore

The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.

关键词： China supply chain networks complex networks data science network science

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Insight-HXMT and GECAM-C observations of the brightest-of-all-time GRB 221009A

arXiv

引用

arXiv 2023年

作者： An, Zheng-Hua Antier, S. Bi, Xing-Zi Bu, Qing-Cui Cai, Ce Cao, Xue-Lei Camisasca, Anna-Elisa Chang, Zhi Chen, Gang Chen, Li Chen, Tian-Xiang Chen, Wen Chen, Yi-Bao Chen, Yong Chen, Yu-Peng Coughlin, Michael W. Cui, Wei-Wei Dai, Zi-Gao Hussenot-Desenonges, T. Du, Yan-Qi Du, Yuan-Yuan Du, Yun-Fei Fan, Cheng-Cheng Frontera, Filippo Gao, He Gao, Min Ge, Ming-Yu Gong, Ke Gu, Yu-Dong Guan, Ju Guo, Dong-Ya Guo, Zhi-Wei Guidorzi, Cristiano Han, Da-Wei He, Jian-Jian He, Jun-Wang Hou, Dong-Jie Huang, Yue Huo, Jia Ji, Zhen Jia, Shu-Mei Jiang, Wei-Chun Kann, David Alexander Klotz, A. Kong, Ling-Da Lan, Lin Li, An Li, Bing Li, Chao-Yang Li, Cheng-Kui Li, Gang Li, Mao-Shun Li, Ti-Pei Li, Wei Li, Xiao-Bo Li, Xin-Qiao Li, Xu-Fang Li, Yan-Guo Li, Zheng-Wei Liang, Jing Liang, Xiao-Hua Liao, Jin-Yuan Lin, Lin Liu, Cong-Zhan Liu, He-Xin Liu, Hong-Wei Liu, Jia-Cong Liu, Xiao-Jing Liu, Ya-Qing Liu, Yu-Rong Lu, Fang-Jun Lu, Hong Lu, Xue-Feng Luo, Qi Luo, Tao Ma, Bin-Yuan Ma, Fu-Li Ma, Rui-Can Ma, Xiang Maccary, Romain Mao, Ji-Rong Meng, Bin Nie, Jian-Yin Orlandini, Mauro Ou, Ge Peng, Jing-Qiang Peng, Wen-Xi Qiao, Rui Qu, Jin-Lu Ren, Xiao-Qin Shi, Jing-Yan Shi, Qi Song, Li-Ming Song, Xin-Ying Su, Ju Sun, Gong-Xing Sun, Liang Sun, Xi-Lei Tan, Wen-Jun Tan, Ying Tao, Lian Tuo, You-Li Turpin, Damien Wang, Jin-Zhou Wang, Chen Wang, Chen-Wei Wang, Hong-Jun Wang, Hui Wang, Jin Wang, Ling-Jun Wang, Peng-Ju Wang, Ping Wang, Wen-Shuai Wang, Xiang-Yu Wang, Xi-Lu Wang, Yu-Sa Wang, Yue Wen, Xiang-Yang Wu, Bo-Bing Wu, Bai-Yang Wu, Hong Xiao, Sheng-Hui Xiao, Shuo Xiao, Yun-Xiang Xie, Sheng-Lun Xiong, Shao-Lin Xiong, Sen-Lin Xu, Dong Xu, He Xu, Yan-Jun Xu, Yan-Bing Xu, Ying-Chen Xu, Yu-Peng Xue, Wang-Chen Yang, Sheng Yang, Yan-Ji Yang, Zi-Xu Ye, Wen-Tao Yi, Qi-Bin Yi, Shu-Xu Yin, Qian-Qing You, Yuan Yu, Yun-Wei Yu, Wei Yu, Wen-Hui Zeng, Ming Zhang, Bing Zhang, Bin-Bin Zhang, Da-Li Zhang, Fan Zhang, Hong-Mei Zhang, Juan Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences 19B Yuquan Road Beijing100049 China Institut für Astronomie und Astrophysik Kepler Center for Astro and Particle Physics Eberhard Karls Universität Sand 1 Tübingen72076 Germany College of Physics Hebei Key Laboratory of Photophysics Research and Application Hebei Normal University Hebei Shijiazhuang050024 China Department of Physics and Earth Science University of Ferrara Via Saragat 1 Ferrara44122 Italy Department of Astronomy Beijing Normal University Beijing100875 China CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Hefei230026 China Department of Astronomy Tsinghua University Beijing100084 China Southwest Jiaotong University Chengdu610092 China INAF Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 101 Bologna40129 Italy University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing100049 China College of physics Sciences Technology Hebei University No. 180 Wusi Dong Road Lian Chi District Hebei Baoding071002 China INFN - Sezione di Ferrara Via Saragat 1 Ferrara44122 Italy Physics and Space Science College China West Normal University China Yunnan Observatories Chinese Academy of Sciences Yunnan Province Kunming650011 China Key Laboratory of Space Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China School of Astronomy and Space Science Nanjing University Nanjing210093 China School of Physics and Optoelectronics Xiangtan University Yuhu District Hunan Xiangtan411105 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang550001 China Institute of Astrophysics Central China Normal University Wuhan430079 China Nevada Center for Astrophysics Department of Physics and Astronomy University of

GRB 221009A is the brightest gamma-ray burst ever detected since the discovery of this kind of energetic explosions. However, an accurate measurement of the prompt emission properties of this burst is very challenging due to its exceptional brightness. With joint observations of Insight-HXMT and GECAM-C, we made an unprecedentedly accurate measurement of the emission during the first ∼1800 s of GRB 221009A, including its precursor, main emission (ME, which dominates the burst in flux), flaring emission and early afterglow, in the hard X-ray to soft gamma-ray band from ∼ 10 keV to ∼ 6 MeV. Based on the GECAM-C unsaturated data of the ME, we measure a record-breaking isotropic equivalent energy (Eiso) of ∼ 1.5 × 1055 erg, which is about eight times the total rest-mass energy of the Sun. The early afterglow data require a significant jet break between 650 s and 1100 s, most likely at ∼ 950 s from the afterglow starting time TAG, which corresponds to a jet opening angle of ∼ 0.7◦ (ηγn)1/8, where n is the ambient medium density in units of cm−3 and ηγ is the ratio between γ-ray energy and afterglow kinetic energy. The beaming-corrected total γ-ray energy Eγ is ∼ 1.15 × 1051 (ηγn)1/4 erg, which is typical for long GRBs. These results suggest that this GRB may have a special central engine, which could launch and collimate a very narrowly beamed jet with an ordinary energy budget, leading to exceptionally luminous gamma-ray radiation per unit solid angle. Alternatively, more GRBs might have such a narrow and bright beam, which are missed by an unfavorable viewing angle or have been detected without distance measurement. Copyright © 2023, The Authors. All rights reserved.

关键词： Gamma rays

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GECAM Localization of High Energy Transients and the Systematic Error

arXiv

引用

arXiv 2022年

作者： Zhao, Yi Xue, Wang-Chen Xiong, Shao-Lin Wang, Yuan-Hao Liu, Jia-Cong Luo, Qi Zhang, Yan-Qiu Sun, Jian-Chao Zhao, Xiao-Yun Cai, Ce Xiao, Shuo Huang, Yue Li, Xiao-Bo Zhang, Zhen Liao, Jin-Yuan Yang, Sheng Qiao, Rui Guo, Dong-Ya Zheng, Chao Yi, Qi-Bin Xie, Sheng-Lun Guo, Zhi-Wei Li, Chao-Yang Wang, Chen-Wei Tan, Wen-Jun Wang, Yue Peng, Wen-Xi Zheng, Shi-Jie He, Jian-Jian Wang, Ping Wang, Jin Ma, Xiang Song, Xin-Ying Zhang, Hong-Mei Li, Bing Zhang, Peng Wu, Hong Du, Yan-Qi Liang, Jing Zhao, Guo-Ying Li, Xin-Qiao Wen, Xiang-Yang An, Zheng-Hua Sun, Xi-Lei Xu, Yan-Bing Zhang, Fan Zhang, Da-Li Gong, Ke Liu, Ya-Qing Liang, Xiao-Hua Liu, Xiao-Jing Gao, Min Wang, Jin-Zhou Song, Li-Ming Chen, Gang Zhang, Ke-Ke Han, Xing-Bo Wu, Hai-Yan Hu, Tai Geng, Hao Lu, Fang-Jun Zhang, Shu Zhang, Shuang-Nan Lu, Gao-Peng Zeng, Ming Yu, Heng Department of Astronomy Beijing Normal University Beijing100875 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China College of Physics Hebei Normal University 20 South Erhuan Road Hebei Shijiazhuang050024 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University GuiZhou Guiyang550001 China School of Physics and Electronic Science Guizhou Normal University GuiZhou Guiyang550001 China School of Physics and Optoelectronics Xiangtan University Hunan Xiangtan411105 China Institute of Astrophysics Central China Normal University Wuhan430079 China College of Physics Sciences Technology Hebei University No. 180 Wusi Dong Road Lian Chi District Hebei Province Baoding City071002 China Physics and Space Science College China West Normal University Nanchong637002 China College of Electronic and information Engineering Tongji University Shanghai201804 China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai201304 China National Space Science Center Chinese Academy of Sciences Beijing100190 China School of Earth and Space Sciences University of Science and Technology of China Hefei230026 China Ministry of Education Beijing100084 China Department of Engineering Physics Tsinghua University Beijing100084 China

Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch in December 2020, GECAM-B has detected hundreds of astronomical and terrestrial events. For these bursts, localization is the key for burst identification and classification as well as follow-up observations in multi-wavelength. Here, we propose a Bayesian localization method with Poisson data with Gaussian background profile likelihood to localize GECAM bursts based on the burst counts distribution in detectors with different orientations. We demonstrate that this method can work well for all kinds of bursts, especially for extremely short ones. In addition, we propose a new method to estimate the systematic error of localization based on a confidence level test, which can overcome some problems of the existing method in literature. We validate this method by Monte Carlo simulations, and then apply it to a burst sample with accurate location and find that the mean value of the systematic error of GECAM-B localization is ∼ 2.5◦. By considering this systematic error, we can obtain a reliable localization probability map for GECAM bursts. Our methods can be applied to other gamma-ray monitors. Copyright © 2022, The Authors. All rights reserved.

关键词： Errors

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Distortion-adaptive salient object detection in 360◦ omnidirectional images

arXiv

引用

arXiv 2019年

作者： Li, Jia Su, Jinming Xia, Changqun Tian, Yonghong State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Adavanced Innovation Center for Big Data and Brain Computing Beihang University China National Engineering Laboratory for Video Technology School of Electronics Engineering and Computer Science Peking University Beijing China Peng Cheng Laboratory Shenzhen518000 China

Image-based salient object detection (SOD) has been extensively explored in the past decades. However, SOD on 360◦ omnidirectional images is less studied owing to the lack of datasets with pixel-level annotations. Toward this end, this paper proposes a 360◦ image-based SOD dataset that contains 500 high-resolution equirectangular images. We collect the representative equirectangular images from five mainstream 360◦ video datasets and manually annotate all objects and regions over these images with precise masks with a free-viewpoint way. To the best of our knowledge, it is the first public available dataset for salient object detection on 360◦ scenes. By observing this dataset, we find that distortion from projection, large-scale complex scene and small salient objects are the most prominent characteristics. Inspired by these foundings, this paper proposes a baseline model for SOD on equirectangular images. In the proposed approach, we construct a distortion-adaptive module to deal with the distortion caused by the equirectangular projection. In addition, a multiscale contextual integration block is introduced to perceive and distinguish the rich scenes and objects in omnidirectional scenes. The whole network is organized in a progressively manner with deep supervision. Experimental results show the proposed baseline approach outperforms the top-performanced state-of-the-art methods on 360◦ SOD dataset. Moreover, benchmarking results of the proposed baseline approach and other methods on 360◦ SOD dataset show the proposed dataset is very challenging, which also validate the usefulness of the proposed dataset and approach to boost the development of SOD on 360◦ omnidirectional scenes. Copyright © 2019, The Authors. All rights reserved.

关键词： Benchmarking

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Surface Modification of (001) Facets Dominated TiO2 with Ozone for Adsorption and Photocatalytic Degradation of Gaseous Toluene

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Chinese Journal of Chemical Physics 2019年第5期32卷 611-619页

作者： Yue Yang Zhi-yu Wang Fan Zhang Yi Fan Jing-jing Dong Song Sun Chen Gao Jun Bao National Synchrotron Radiation Laboratory Collaborative Innovation Center of Chemistry for Energy Materials Key Laboratory of Surface and Interface Chemistry and Energy Catalysis of Anhui Higher Education Institutes University of Science and Technology of China Hefei 230029 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China School of Chemistry and Chemical Engineering Anhui University Hefei 230601 China Beijing Advanced Sciences and Innovation center Chinese Academy of Sciences Beijing 101407 China

This study investigated the positive effect of surface modification with ozone on the photocatalytic performance of anatase TiO2 with dominated（001） facets for toluene *** performance of photocatalyst was tested on a home-made volatile organic compounds degradation system. The ozone modification, toluene adsorption and degradation mechanism were established by a combination of various characterization methods, in situ diffuse reflectance infrared fourier transform spectroscopy, and density functional theory *** surface modification with ozone can significantly enhance the photocatalytic degradation performance for toluene. The abundant unsaturated coordinated 5 c-Ti sites on（001）facets act as the adsorption sites for ozone. The formed Ti–O bonds reacted with H2O to generate a large amount of isolated Ti5 c-OH which act as the adsorption sites for toluene,and thus significantly increase the adsorption capacity for toluene. The outstanding photocatalytic performance of ozone-modified TiO2 is due to its high adsorption ability for toluene and the abundant surface hydroxyl groups, which produce very reactive OH·radicals under irradiation. Furthermore, the O2 generated via ozone dissociation could combine with the photogenerated electrons to form superoxide radicals which are also conductive to the toluene degradation.

关键词： Ozone modification (001) Facets Toluene degradation TiO2 In situ diffuse reflectance infrared fourier transform spectroscopy

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The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023

arXiv

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arXiv 2024年

作者： Lyu, Jun Qin, Chen Wang, Shuo Wang, Fanwen Li, Yan Wang, Zi Guo, Kunyuan Ouyang, Cheng Tänzer, Michael Liu, Meng Sun, Longyu Sun, Mengting Li, Qin Shi, Zhang Hua, Sha Li, Hao Chen, Zhensen Zhang, Zhenlin Xin, Bingyu Metaxas, Dimitris N. Yiasemis, George Teuwen, Jonas Zhang, Liping Chen, Weitian Pang, Yanwei Liu, Xiaohan Razumov, Artem Dylov, Dmitry V. Dou, Quan Yan, Kang Xue, Yuyang Du, Yuning Dietlmeier, Julia Garcia-Cabrera, Carles Hemidi, Ziad Al-Haj Vogt, Nora Xu, Ziqiang Zhang, Yajing Chu, Ying-Hua Chen, Weibo Bai, Wenjia Zhuang, Xiahai Qin, Jing Wu, Lianmin Yang, Guang Qu, Xiaobo Wang, He Wang, Chengyan Psychiatry Neuroimaging Laboratory Brigham and Women’s Hospital Harvard Medical School 399 Revolution Drive BostonMA02215 United States Department of Electrical and Electronic Engineering & I-X Imperial College London United Kingdom Digital Medical Research Center School of Basic Medical Sciences Fudan University Shanghai China Department of Bioengineering & I-X Imperial College London LondonW12 7SL United Kingdom Cardiovascular Magnetic Resonance Unit Royal Brompton Hospital Guy’s and St Thomas’ NHS Foundation Trust LondonSW3 6NP United Kingdom Department of Radiology Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Institute of Artificial Intelligence Xiamen University Xiamen361102 China Department of Computing Department of Brain Sciences Imperial College London LondonSW7 2AZ United Kingdom Human Phenome Institute Fudan University 825 Zhangheng Road Pudong New District Shanghai201203 China Department of Radiology Zhongshan Hospital Fudan University Shanghai China Department of Cardiovascular Medicine Ruijin Hospital Lu Wan Branch Shanghai Jiao Tong University School of Medicine Shanghai China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai200433 China Department of Computer Science Rutgers University PiscatawayNJ08854 United States AI for Oncology Netherlands Cancer Institute Plesmanlaan 121 Amsterdam1066 CX Netherlands Department of Imaging and Interventional Radiology The Chinese University of Hong Kong Hong Kong TJK-BIIT Lab School of Electrical and Information Engineering Tianjin University Tianjin300072 China Skolkovo Institute Of Science And Technology Center for Artificial Intelligence Technology 30/1 Bolshoy blvd. Moscow121205 Russia Department of Biomedical Engineering University of Virginia

Cardiac magnetic resonance imaging (MRI) provides detailed and quantitative evaluation of the heart’s structure, function, and tissue characteristics with high-resolution spatial-temporal imaging. However, its slow imaging speed and motion artifacts are notable limitations. Undersampling reconstruction, especially data-driven algorithms, has emerged as a promising solution to accelerate scans and enhance imaging performance using highly under-sampled data. Nevertheless, the scarcity of publicly available cardiac k-space datasets and evaluation platform hinder the development of data-driven reconstruction algorithms. To address this issue, we organized the Cardiac MRI Reconstruction Challenge (CMRxRecon) in 2023, in collaboration with the 26th International Conference on Medical Image computing and Computer-Assisted Intervention (MICCAI). CMRxRecon presented an extensive k-space dataset comprising cine and mapping raw data, accompanied by detailed annotations of cardiac anatomical structures. With overwhelming participation, the challenge attracted more than 285 teams and over 600 participants. Among them, 22 teams successfully submitted Docker containers for the testing phase, with 7 teams submitted for both cine and mapping tasks. All teams use deep learning based approaches, indicating that deep learning has predominately become a promising solution for the problem. The first-place winner of both tasks utilizes the E2E-VarNet architecture as backbones. In contrast, U-Net is still the most popular backbone for both multi-coil and single-coil reconstructions. This paper provides a comprehensive overview of the challenge design, presents a summary of the submitted results, reviews the employed methods, and offers an in-depth discussion that aims to inspire future advancements in cardiac MRI reconstruction models. The summary emphasizes the effective strategies observed in Cardiac MRI reconstruction, including backbone architecture, loss function, pre-processing techn

关键词： Mapping

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