检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Wang, Yaqi Zhang, Yifan Chen, Xiaodiao Wang, Shuai Qian, Dahong Ye, Fan Xu, Feng Zhang, Hongyuan Zhang, Qianni Wu, Chengyu Li, Yunxiang Cui, Weiwei Luo, Shan Wang, Chengkai Li, Tianhao Liu, Yi Feng, Xiang Zhou, Huiyu Liu, Dongyun Wang, Qixuan Lin, Zhouhao Song, Wei Li, Yuanlin Wang, Bing Wang, Chunshi Chen, Qiupu Li, Mingqian College of Media Engineering Communication University of Zhejiang Hangzhou China State Key Laboratory of Oral Diseases National Clinical Research Center for Oral Diseases West China Hospital of Stomatology Sichuan University Chengdu China Lishui University School of Medicine Hangzhou Geriatric Stomatology Hospital Hangzhou Dental Hospital Group Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China Suzhou Research Institute of Shandong University Suzhou China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Medical School Shenzhen University Shenzhen China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Department of Mechanical Electrical and Information Engineering Shandong University Weihai China School of Management Hangzhou Dianzi University Hangzhou China Department of Stomatology Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu China School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Zeta Technology Co. Ltd. No. 1158 Zhangdong Road Pudong New Area Shanghai China China Academy of Information and Communications Technology Beijing China HangZhou Dianzi University Xiasha Higher Education Zone Hangzhou China Southeast University Sipailou Xuanwu District Nanjing China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Changchun University of Science and Technology Changchun China School of Artificial Intelligence Guilin University of Electronic Technology Guilin China University of Science and Technology of China Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences No. 350 Shushan

Computer-aided design (CAD) tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation. In particular, the 2D panoramic X-ray image efficiently detects invisible caries, impacted teeth and supernumerary teeth in children, while the 3D dental cone beam computed tomography (CBCT) is widely used in orthodontics and endodontics due to its low radiation dose. However, there is no open-access 2D public dataset for children's teeth and no open 3D dental CBCT dataset, which limits the development of automatic algorithms for segmenting teeth and analyzing diseases. The Semi-supervised Teeth Segmentation (STS) Challenge, a pioneering event in tooth segmentation, was held as a part of the MICCAI 2023 ToothFairy Workshop on the Alibaba Tianchi platform. This challenge aims to investigate effective semi-supervised tooth segmentation algorithms to advance the field of dentistry. In this challenge, we provide two modalities including the 2D panoramic X-ray images and the 3D CBCT tooth volumes. In Task 1, the goal was to segment tooth regions in panoramic X-ray images of both adult and pediatric teeth. Task 2 involved segmenting tooth sections using CBCT volumes. Limited labelled images with mostly unlabelled ones were provided in this challenge prompt using semi-supervised algorithms for training. In the preliminary round, the challenge received registration and result submission by 434 teams, with 64 advancing to the final round. This paper summarizes the diverse methods employed by the top-ranking teams in the STS MICCAI 2023 Challenge. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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FAST observations of an extremely active episode of FRB 20201124A: IV. Spin Period Search

arXiv

引用

arXiv 2022年

作者： Niu, Jia-Rui Zhu, Wei-Wei Zhang, Bing Yuan, Mao Zhou, De-Jiang Zhang, Yong-Kun Jiang, Jin-Chen Han, J.L. Li, Di Lee, Ke-Jia Wang, Pei Feng, Yi Li, Dong-Zi Luo, Rui Wang, Fa-Yin Dai, Zi-Gao Miao, Chen-Chen Niu, Chen-Hui Xu, Heng Zhang, Chun-Feng Wang, Wei-Yang Wang, Bo-Jun Xu, Jiang-Wei National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China University of Chinese Academy of Sciences Beijing China Institute for Frontier in Astronomy and Astrophysics Beijing Normal University Beijing102206 China Department of Physics and Astronomy University of Nevada Las VegasNV89154 United States Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China Department of Astronomy Peking University Beijing100871 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China Cahill Center for Astronomy and Astrophysics MC 249-17 California Institute of Technology PasadenaCA91125 United States CSIRO Space and Astronomy PO Box 76 EppingNSW1710 Australia School of Astronomy and Space Science Nanjing University Nanjing210093 China Key Laboratory of Modern Astronomy and Astrophysics Nanjing University Ministry of Education China Department of Astronomy University of Science and Technology of China Hefei230026 China

We report the properties of more than 800 bursts detected from the repeating fast radio burst (FRB) source FRB 20201124A with the Five-hundred-meter Aperture Spherical radio telescope (FAST) during an extremely active episode on UTC September 25th-28th, 2021 in a series of four papers. In this fourth paper of the series, we present a systematic search of the spin period and linear acceleration of the source object from both 996 individual pulse peaks and the dedispersed time series. No credible spin period was found from this data set. We rule out the presence of significant periodicity in the range between 1 ms to 100 s with a pulse duty cycle −2 in each of the four one-hour observing sessions, and up to 0.6 m s−2 in all 4 days. These searches contest theoretical scenarios involving a 1 ms to 100 s isolated magnetar/pulsar with surface magnetic field 15 G and a small duty cycle (such as in a polar-cap emission mode) or a pulsar with a companion star or black hole up to 100 M☉ and Pb > 10 hours. We also perform a periodicity search of the fine structures and identify 53 unrelated millisecond-timescale"periods" in multi-components with the highest significance of 3.9 σ. The"periods" recovered from the fine structures are neither consistent nor harmonically related. Thus they are not likely to come from a spin period. We caution against claiming spin periodicity with significance below ∼ 4 σ with multi-components from one-off FRBs. We discuss the implications of our results and the possible connections between FRB multi-components and pulsar micro-structures. © 2022, CC BY.

关键词： Pulsars

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Accelerated MRI reconstruction with separable and enhanced low-rank Hankel regularization

arXiv

引用

arXiv 2021年

作者： Zhang, Xinlin Lu, Hengfa Guo, Di Lai, Zongying Ye, Huihui Peng, Xi Zhao, Bo Qu, Xiaobo Biomedical Intelligent Cloud R&D Center Department of Electronic Science National Institute for Data Science in Health and Medicine Xiamen University Xiamen361105 China The Department of Biomedical Engineering University of Texas at Austin AustinTX78712 United States The School of Computer and Information Engineering Xiamen University of Technology Xiamen361021 China The School of Information Engineering Jimei University Xiamen361024 China The State of Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Zhejiang University Hangzhou310058 China The Department of Radiology Mayo Clinic RochesterMN55902 United States The Department of Biomedical Engineering Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX78712 United States

The combination of the sparse sampling and the low-rank structured matrix reconstruction has shown promising performance, enabling a significant reduction of the magnetic resonance imaging data acquisition time. However, the low-rank structured approaches demand considerable memory consumption and are time-consuming due to a noticeable number of matrix operations performed on the huge-size block Hankel-like matrix. In this work, we proposed a novel framework to utilize the low-rank property but meanwhile to achieve faster reconstructions and promising results. The framework allows us to enforce the low-rankness of Hankel matrices constructing from 1D vectors instead of 2D matrices from 1D vectors and thus avoid the construction of huge block Hankel matrix for 2D k-space matrices. Moreover, under this framework, we can easily incorporate other information, such as the smooth phase of the image and the low-rankness in the parameter dimension, to further improve the image quality. We built and validated two models for parallel and parameter magnetic resonance imaging experiments, respectively. Our retrospective in-vivo results indicate that the proposed approaches enable faster reconstructions than the state-of-the-art approaches, e.g., about 8× faster than STDLR-SPIRiT, and faithful removal of undersampling artifacts. Copyright © 2021, The Authors. All rights reserved.

关键词： Image reconstruction

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Hi content of selected mid-infrared bright, starburst blue compact dwarf galaxies

arXiv

引用

arXiv 2023年

作者： Chandola, Yogesh Li, Di Tsai, Chao-Wei Li, Guodong Peng, Yingjie Zuo, Pei McIntyre, Travis Ma, Yin-Zhe Stern, Daniel Griffith, Roger Jarrett, Thomas Eisenhardt, Peter Balkowski, Chantal CAS Key Laboratory of FAST National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China 10 Yuan Hua Road Qixia District Nanjing210023 China Post bag 4 Ganeshkhind Pune411007 India Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China University of KwaZulu-Natal Durban4000 South Africa Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University Beijing102206 China University of Chinese Academy of Sciences Beijing100049 China Department of Astronomy School of Physics Peking University 5 Yiheyuan Road Beijing100871 China Kavli Institute for Astronomy and Astrophysics Peking University 5 Yiheyuan Road Beijing100871 China University of Western Australia 35 Stirling Highway CrawleyWA6009 Australia Department of Physics Stellenbosch University Matieland7602 South Africa Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive M/S 169-327 PasadenaCA91109 United States Department of Astronomy University of Cape Town Private Bag X3 Rondebosch7701 South Africa Observatorie de Paris 61 Av. de l’Observatoire Paris75014 France

We report measurements of Hi content in 11 nearby, actively star-forming, blue compact dwarf galaxies (BCDs) from 21 cm observations with the Arecibo telescope. These BCDs, selected by their red (W2[4.6 µm]−W3[12 µm]>3.8 mag) and bright mid-infrared (MIR) emission (W4[22 µm]−7.8 yr−1), similar to high redshift galaxies. Hi emission was detected in six sources. We analyze our new detections in the context of previous Hi observations of 218 dwarf irregulars (dIs) and BCDs in the literature. The MHIM∗ relation resulting from our observations confirms the dominating fraction of Hi gas among baryons in galaxies with lower stellar masses. This Arecibo BCD sample has significantly lower median Hi depletion timescales (τHI ∼ 0.3 Gyr) than other dIs/BCDs (∼ 6.3 Gyr) in the literature. The majority of the sources (10/11) in the Arecibo sample are very red in W1[3.4 µm]−W2[4.6 µm] colour (> 0.8 mag) implying the presence of warm dust. We investigate the relation of τHI with stellar mass (M∗) and sSFR. We find that τHI is significantly anti-correlated with M∗ for higher sSFR (>10−8.5 yr−1) and with sSFR for higher stellar mass (> 107.5 M☉) dwarf galaxies. The high sSFR for the BCDs in the Arecibo observed sample is mainly due to their high atomic gas star formation efficiency (SFE) or low τHI. The low τHI or high SFE in these sources is possibly due to runaway star formation in compact and dense super star clusters. Copyright © 2023, The Authors. All rights reserved.

关键词： Galaxies

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Protonated hydrogen cyanide as a tracer of pristine molecular gas

arXiv

引用

arXiv 2023年

作者： Gong, Y. Du, F.J. Henkel, C. Jacob, A.M. Belloche, A. Wang, J.Z. Menten, K.M. Yang, W. Quan, D.H. Bop, C.T. Ortiz-León, G.N. Tang, X.D. Rugel, M.R. Liu, S. Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Astronomy Department Faculty of Science King Abdulaziz University PO Box 80203 Jeddah21589 Saudi Arabia Xinjiang Astronomical Observatory Chinese Academy of Sciences 150 Science 1-Street Xinjiang Urumqi830011 China Department of Physics & Astronomy Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States Guangxi Key Laboratory for Relativistic Astrophysics Department of Physics Guangxi University Nanning530004 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China UMR 6251 RennesF-35000 France Instituto Nacional de Astrofísica Óptica y Electrónica Apartado Postal 51 y 216 Puebla72000 Mexico Key Laboratory of Radio Astronomy Chinese Academy of Sciences Urumqi830011 China University of Chinese Academy of Sciences Beijing100049 China Center for Astrophysics Harvard & Smithsonian 60 Garden St. CambridgeMA02138 United States National Radio Astronomy Observatory 1003 Lopezville RD SocorroNM87801 United States National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China

Context. Protonated hydrogen cyanide, HCNH+, plays a fundamental role in astrochemistry because it is an intermediary in gas-phase ion-neutral reactions within cold molecular clouds. However, the impact of the environment on the chemistry of HCNH+ remains poorly understood. Aims. We aim to study HCNH+, HCN, and HNC, as well as two other chemically related ions, HCO+ and N2H+, in different star formation regions in order to investigate how the environment influences the chemistry of HCNH+. Methods. With the IRAM-30 m and APEX-12 m telescopes, we carried out HCNH+, H13CN, HN13C, H13CO+, and N2H+ imaging observations toward two dark clouds, the Serpens filament and Serpens South, both of which harbor sites of star formation including protostellar objects as well as regions that are quiescent. Results. We report the first robust distribution of HCNH+ in the Serpens filament and in Serpens South. Our data suggest that HCNH+ is abundant in cold and quiescent regions, but is deficient in active star-forming regions. The observed HCNH+ fractional abundances relative to H2 range from 3.1 × 10−11 in protostellar cores to 5.9 × 10−10 in prestellar cores, and the HCNH+ abundance generally decreases with increasing H2 column density, which suggests that HCNH+ coevolves with cloud cores. Our observations and modeling results suggest that the abundance of HCNH+ in cold molecular clouds is strongly dependent on the H2 number density. The decrease in the abundance of HCNH+ is caused by the fact that its main precursors (e.g., HCN and HNC) undergo freeze-out as the number density of H2 increases. However, current chemical models cannot explain other observed trends, such as the fact that the abundance of HCNH+ shows an anti-correlation with that of HCN and HNC, but a positive correlation with that of N2H+ in the southern part of the Serpens South northern clump. This indicates that additional chemical pathways have to be invoked for the formation of HCNH+ via molecules like N2 in reg

关键词： Cyanides

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Dependence of Chemical Abundance on the Cosmic Ray Ionization Rate in IC 348

arXiv

引用

arXiv 2022年

作者： Luo, Gan Zhang, Zhi-Yu Bisbas, Thomas G. Li, Di Tang, Ningyu Wang, Junzhi Zhou, Ping Zuo, Pei Yue, Nannan Zhou, Jing Lin, Lingrui School of Astronomy and Space Science Nanjing University Nanjing210093 China Ministry of Education Nanjing210093 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China I. Physikalisches Institut Universität zu Köln Zülpicher Straβe 77 KölnD-50923 Germany CAS Key Laboratory of FAST National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China University of Chinese Academy of Sciences Beijing100049 China NAOC-UKZN Computational Astrophysics Centre University of KwaZulu-Natal Durban4000 South Africa Department of Physics Anhui Normal University Anhui Wuhu241002 China School of Physical Science and Technology Guangxi University Nanning530004 China Kavli Institute for Astronomy and Astrophysics Peking University Beijing 5 Yiheyuan Road Haidian District Beijing100871 China University of Western Australia CrawleyWA6009 Australia

Ions (e.g., H+3 , H2O+) have been used extensively to quantify the cosmic-ray ionization rate (CRIR) in diffuse sightlines. However, measurements of CRIR in low-to-intermediate density gas environments are rare, especially when background stars are absent. In this work, we combine molecular line observations of CO, OH, CH, and HCO+ in the star-forming cloud IC 348, and chemical models to constrain the value of CRIR and study the response of the chemical abundances distribution. The cloud boundary is found to have an AV of approximately 4 mag. From the interior to the exterior of the cloud, the observed 13CO line intensities drop by an order of magnitude. The calculated average abundance of 12CO (assuming 12C/13C = 65) is (1.2±0.9) ×10−4, which increases by a factor of 6 from the interior to the outside regions. The average abundance of CH (3.3±0.7 × 10−8) is in good agreement with previous findings in diffuse and translucent clouds (AV V 8 mag) as previously reported in Taurus. By comparing the observed molecular abundances and chemical models, we find a decreasing trend of CRIR as AV increases. The inferred CRIR of ζcr = (4.7±1.5) × 10−16 s−1 at low AV is consistent with H+3 measurements toward two nearby massive stars. © 2022, CC BY.

关键词： Cosmic rays

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Searching for axion dark matter with the MeerKAT radio telescope

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Physical Review D 2022年第8期106卷 083006-083006页

作者： Yun-Fan Zhou Nick Houston Gyula I. G. Józsa Hao Chen Yin-Zhe Ma Qiang Yuan Tao An Yogesh Chandola Ran Ding Fujun Du Shao-Guang Guo Xiaoyuan Huang Mengtian Li Chandreyee Sengupta Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing 210023 China School of Astronomy and Space Science University of Science and Technology of China Hefei Anhui 230026 China Institute of Theoretical Physics Faculty of Science Beijing University of Technology Beijing 100124 China Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 53121 Bonn Germany Department of Physics and Electronics Rhodes University PO Box 94 Makhanda 6140 South Africa South African Radio Astronomy Observatory Black River Park 2 Fir Street Observatory Cape Town 7925 South Africa Department of Astronomy University of Cape Town Private Bag X3 7701 Rondebosch South Africa Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou 311100 China School of Chemistry and Physics University of KwaZulu-Natal Westville Campus Durban 4000 South Africa NAOC-UKZN Computational Astrophysics Centre (NUCAC) University of KwaZulu-Natal Durban 4000 South Africa National Institute for Theoretical and Computational Sciences (NITheCS) Durbun 3630 South Africa Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing 210023 China Shanghai Astronomical Observatory Chinese Academy of Sciences Nandan Road 80 Shanghai 200030 China School of Physics and Optoelectronics Engineering Anhui University Hefei 230601 China

Axions provide a natural and well-motivated dark matter candidate, with the capability to convert directly to photons in the presence of an electromagnetic field. A particularly compelling observational target is the conversion of dark matter axions into photons in the magnetospheres of highly magnetised neutron stars, which is expected to produce a narrow spectral peak centerd at the frequency of the axion mass. We point the MeerKAT radio telescope towards the isolated neutron star J0806.4−4123 for 10-hours of observation and obtain the radio spectra in the frequency range 769–1051 MHz. By modeling the conversion process of infalling axion dark matter (DM), we then compare these spectra to theoretical expectations for a given choice of axion parameters. Whilest finding no signal above 5σ in the data, we provide a unique constraint on the Primakoff coupling of axion DM, gaγγ≲9.3×10−12 GeV−1 at the 95% confidence level, in the mass range 3.18–4.35 μeV. This result serves the strongest constraint in the axion mass range 4.20–4.35 μeV.

关键词： Axions Particle dark matter

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Searching for axion dark matter with the MeerKAT radio telescope

arXiv

引用

arXiv 2022年

作者： Zhou, Yun-Fan Houston, Nick Józsa, Gyula I.G. Chen, Hao Ma, Yin-Zhe Yuan, Qiang An, Tao Chandola, Yogesh Ding, Ran Du, Fujun Guo, Shao-Guang Huang, Xiaoyuan Li, Mengtian Sengupta, Chandreyee Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Institute of Theoretical Physics Faculty of Science Beijing University of Technology Beijing100124 China Max-Planck-Institut für Radioastronomie Radioobservatorium Effelsberg Max-Planck-Straße 28 Bad Münstereifel53902 Germany Department of Physics and Electronics Rhodes University PO Box 94 Makhanda6140 South Africa South African Radio Astronomy Observatory Black River Park 2 Fir Street Observatory Cape Town7925 South Africa Department of Astronomy University of Cape Town Private Bag X3 Rondebosch7701 South Africa Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China School of Chemistry and Physics University of KwaZulu-Natal Westville Campus Durban4000 South Africa University of KwaZulu-Natal Durban4000 South Africa South Africa Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China Shanghai Astronomical Observatory Chinese Academy of Sciences Nandan Road 80 Shanghai200030 China School of Physics and Optoelectronics Engineering Anhui University Hefei230601 China

Axions provide a natural and well-motivated dark matter candidate, with the capability to convert directly to photons in the presence of an electromagnetic field. A particularly compelling observational target is the conversion of dark matter axions into photons in the magnetospheres of highly magnetised neutron stars, which is expected to produce a narrow spectral peak centred at the frequency of the axion mass. We point the MeerKAT radio telescope towards the isolated neutron star J0806.4−4123 for 10-hours of observation and obtain the radio spectra in the frequency range 769-1051 MHz. By modelling the conversion process of infalling axion dark matter (DM), we then compare these spectra to theoretical expectations for a given choice of axion parameters. Whilst finding no signal above 5σ in the data, we provide a unique constraint on the Primakoff coupling of axion DM, gaγγ. 9.3 × 10−12 GeV−1 at the 95% confidence level, in the mass range 3.18-4.35 µeV. This result serves the strongest constraint in the axion mass range 4.20-4.35 µeV. Copyright © 2022, The Authors. All rights reserved.

关键词： Bosons

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Photocatalytic Hydrogen Production on a sp2-Carbon-Linked Covalent Organic Framework

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Angewandte Chemie 2022年第42期134卷

作者： Si Ma Prof. Dr. Tianqi Deng Dr. Ziping Li Zhenwei Zhang Ji Jia Qizhen Li Prof. Dr. Gang Wu Prof. Dr. Hong Xia Prof. Dr. Shuo-Wang Yang Prof. Dr. Xiaoming Liu College of Chemistry Jilin University Changchun 130012 P.R. China Institute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200 P.R. China State Key Laboratory of Silicon Materials & School of Materials Science and Engineering Zhejiang University Hangzhou 310027 P.R. China Department of Biomedical Engineering Southern University of Science and Technology Shenzhen 518055 P.R. China Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Technology Jilin University Changchun 130012 P.R. China

Two-dimensional covalent organic frameworks (2D-COFs) have emerged as attractive platforms for solar-to-chemical energy conversion. In this study, we have implemented a gradient heating strategy to synthesize a sp 2 -carbon-linked triazine-based COF, COF-JLU100, exhibiting high crystallinity, large surface area, good durability and carrier mobility for solar-driven photocatalytic hydrogen evolution. The Pt-doped COF-JLU100 demonstrated a high hydrogen evolution rate of over 100 000 μmol g −1 h −1 for water splitting under visible-light illumination (λ>420 nm). Experimental and theoretical studies corroborate that the cyano-vinylene segments in COF-JLU100 extend the π-delocalization and enable fast charge transfer and separation rates as well as good dispersion in water. Moreover, COF-JLU100 can be prepared by low-cost and easily available monomers and has excellent stability, which is desirable for practical solar-driven hydrogen production.

关键词： Covalent Organic Frameworks Gradient Heating Hydrogen Evolution Photocatalysis sp2 Carbon Linkage

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REFUGE2 CHALLENGE: A TREASURE TROVE FOR MULTI-DIMENSION ANALYSIS AND EVALUATION IN GLAUCOMA SCREENING

arXiv

引用

arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

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