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Knowledge Mapping of Opuntia Milpa Alta Since 1998: A Scientometric Analysis

Phyton-International Journal of Experimental Botany 2021年第5期90卷 1507-1518页

作者： Meixiang Chen Hong Yang Zhengda Song Yonghua Gu Yuhong Zheng Jiangwei Zhu Aiwu Wang Li Fu Institute of Botany Jiangsu Province and Chinese Academy of Sciences(Nanjing Botanical GardenMem.Sun Yat-Sen)Nanjing210014China The Jiangsu Provincial Platform for Conservation and Utilization of Agricultural Germplasm Nanjing210014China Co-Innovation Center for Sustainable Forestry in Southern China Nanjing Forestry UniversityNanjing210037China Center for Advanced Material Diagnostic Technology Shenzhen Technology UniversityShenzhen518118China Key Laboratory of Novel Materials for Sensor of Zhejiang Province College of Materials and Environmental EngineeringHangzhou Dianzi UniversityHangzhou310018China

Opuntia Milpa Alta is a cactus cultivated,domesticated,hybridized and selected from the plant Opuntia ficusindica by Mexican agricultural experts,which can be used as fruit and *** Milpa Alta leaves and fruit are superior to wild varieties and suitable for storage and *** 1998,Opuntia Milpa Alta was introduced to China from Mexico by the Quality Product Development Center of the Ministry of Agriculture of *** to now,the Opuntia Milpa Alta has been cultivated on a certain scale in *** study aims to identify the research progress and development trends of Opuntia Milpa Alta in *** published between 1998 to 2019 from two major Chinese academic databases(CNKI and Wangfang)with a topic search related to Opuntia Milpa Alta were *** research progress and development trends were analyzed based on CiteSpace software of text mining and *** analysis found that Opuntia Milpa Alta has gone through three obvious research phases after being introduced to *** the first phase,the researchers paid attention to its cultivation ***,researchers began to use extraction methods to extract some of its components,such as polysaccharides and ***,these extracted ingredients began to be used in some biomedical research.

关键词： Opuntia Milpa Alta China bibliometric analysis planting technique biomedical uses

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Pattern-Dependent Equalization for PAM-4 IM/DD System with Severe Bandwidth Limitation

Pattern-Dependent Equalization for PAM-4 IM/DD System with S...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Wei Wang Dongdong Zou Weihao Ni Zhaohui Li Fan Li Yi Cai Qi Sui School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Guangzhou China Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network Suzhou Key Laboratory of Advanced Optical Communication Network Technology Soochow University Suzhou China Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Technology Zhuhai China

LUT enabled pattern-dependent equalization combined with MLSE is proposed for bandwidth-limited IM/DD system. The experimental results show that the proposed method can provide significant improvement compared to the ... 详细信息

关键词： Maximum likelihood estimation Sensitivity C-band Asia Bandwidth Receivers Table lookup

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advanced polishing methods for atomic-scale surfaces: A review

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Materials Today Sustainability 2024年 27卷

作者： Luo, Zhun Zhang, Zhenyu Zhao, Feng Fan, Cheng Feng, Junyuan Zhou, Hongxiu Meng, Fanning Zhuang, Xuye Wang, Jianmei State Key Laboratory of High-performance Precision Manufacturing Dalian University of Technology Dalian 116024 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electrical Engineering Soochow University Suzhou 215021 China School of Mechanical Engineering Hangzhou Dianzi University Hangzhou 310018 China School of Energy and Power Engineering Dalian University of Technology Dalian 116024 China School of Mechanical Engineering Shandong University of Technology Zibo 255000 China School of Mechanical Engineering Taiyuan University of Science and Technology Taiyuan 030024 China

With the development of high-performance components in advanced equipment, manufacturing precision and scale are approaching to atomic-scale, especially in the fields of electronic information, integrated circuits, and ultra-precision instruments towards miniaturization and portability. Surface roughness with Ra less than 0.2 nm has attracted considerable attentions for ultraprecision machining, owing to inducing unique properties of components and great potential in a wide range of applications. Great efforts have been devoted to production of atomic surfaces on components through machining their surface layer at the atomic scale. In this review, advanced polishing methods have been addressed, such as chemical mechanical polishing (CMP), elastic emission machining (EEM), ion beam figuring (IBF), magnetorheological finishing (MRF), plasma-assisted polishing (PAP), ultrasonic and photocatalytic polishing, electrochemical polishing, and bubble-assisted polishing. Although present advanced polishing methods and technologies have achieved partially progresses, atomic-scale surface and atomic layer removal are generally a new field of research developed recently. This review focuses on advanced polishing at atomic scale for enhancing the performance of components made of different materials. It covers the application and development of new equipment, novel processes, and innovative abrasive particles, such as CeO₂, etc. Additionally, future trends of research works are also discussed. © 2024 Elsevier Ltd

关键词： advanced polishing Atomic layer removal Atomic surface Atomic-scale Roughness

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Analysis of Tool Wear and Wear Mechanism in Dry Forming Milling for Rail Milling Train

Analysis of Tool Wear and Wear Mechanism in Dry Forming Mill...

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作者： Pan, Chao Gu, Xiaoshan Wang, Mulan Wang, Baosheng China Railway Shanghai Administration Group Nanjing EMU Department Nanjing210012 China Jiangsu Key Laboratory of Advanced Numerical Control Technology NanjingJiangsu211167 China Jiangsu Provincial Engineering Laboratory of Intelligent Manufacturing Equipment Nanjing211167 China

Milling tools of the rail milling train have to face severe weariness due to the uneven surface hardness, inconsistent cutting rate and uncertain status of the rail itself as well as the vibration caused by the suspension system of the rail milling train and its characteristic hunting motion. This study performed a milling tool wearing status analysis and conducted relative research on wearing mechanisms with electron scanning microscope based on the typical milling tools and specific working conditions of rail milling train. Results indicate that the wearing status of rail milling train consists mainly of crater wear, notch wear, cutting edge chipping, surface exfoliation, milling sintering and tool break. The tool wearing conditions of rail milling train, compared with ordinary milling process, are significantly severe, and associated with multiple types of wearing status of which certain relevance exists. The research is of great significance for the improvement of the milling tool, the optimization of the process and the improvement of the mobile milling quality of the rail. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Milling (machining)

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Emerging Internet of Things driven carbon nanotubes-based devices

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Nano Research 2022年第5期15卷 4613-4637页

作者： Shu Zhang Jinbo Pang Yufen Li Feng Yang Thomas Gemming Kai Wang Xiao Wang Songang Peng Xiaoyan Liu Bin Chang Hong Liu Weijia Zhou Gianaurelio Cuniberti Mark HRümmeli Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinan 250022China Department of Chemistry Guangdong Provincial Key Laboratory of CatalysisSouthern University of Science and TechnologyShenzhen 518055China Leibniz Institute for Solid State and Materials Research Dresden P.O.Box 270116Dresden D-01171Germany State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong University27 Shandanan RoadJinan 250100China School of Electrical Engineering Qingdao UniversityQingdao 266071China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences 1068 Xueyuan AvenueShenzhen University TownShenzhen 518055China High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China School of Chemistry and Chemical Engineering University of JinanJinan 250022China College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhou 215006China Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhou 215006China Centre of Polymer and Carbon Materials Polish Academy of SciencesM.Curie Sklodowskiej 34Zabrze 41-819Poland Institute of Environmental Technology(CEET) VSB-Technical University of Ostrava17.Listopadu 15Ostrava 70833Czech Republic Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics D

Carbon nanotubes(CNTs)have attracted great attentions in the field of electronics,sensors,healthcare,and energy *** emerging applications have driven the carbon nanotube research in a rapid ***,the structure control over CNTs has inspired an intensive research vortex due to the high promises in electronic and optical device ***,this in-depth review is anticipated to provide insights into the controllable synthesis and applications of high-quality ***,the general synthesis and post-purification of CNTs are briefly ***,the state-of-the-art electronic device applications are discussed,including field-effect transistors,gas sensors,DNA biosensors,and pressure ***,the optical sensors are delivered based on the *** addition,energy applications of CNTs are discussed such as thermoelectric energy ***,future opportunities are proposed for the Internet of Things(IoT)oriented sensors,data processing,and artificial intelligence.

关键词： carbon nanotubes electronics sensors electronic skins Internet of Things artificial intelligence

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Manipulating charge density wave state in kagome compound RbV3Sb5

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Chinese Physics B 2023年第9期 453-457页

作者：孟雨欣薛成龙窦立国赵伟民汪琪玮徐永杰刘祥麒夏威郭艳峰李绍春 National Laboratory of Solid State Microstructures School of Physics Nanjing University Collaborative Innovation Center of Advanced Microstructures Nanjing University School of Physical Science and Technology Shanghai Tech University Shanghai Tech Laboratory for Topological Physics Jiangsu Provincial Key Laboratory for Nanotechnology Nanjing University Hefei National Laboratory

Owing to the unique electronic structure, kagome materials AV3Sb5（A = K, Rb, Cs） provide a fertile platform of quantum phenomena such as the strongly correlated state and topological Dirac band. It is well known that RbV3Sb5exhibits a 2 × 2 unconventional charge density wave（CDW） state at low temperature, and the mechanism is ***, by using scanning tunneling microscopy/spectroscopy（STM/STS）, we successfully manipulated the CDW state in the Sb plane of RbV3Sb5, and realized a new3（1/2） ×3（1/2） modulation together with the ubiquitous 2 × 2 period in the CDW state of RbV3Sb5. This work provides a new understanding of the collective quantum ground states in the kagome materials.

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UOD: Universal One-shot Detection of Anatomical Landmarks

arXiv

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arXiv 2023年

作者： Zhu, Heqin Quan, Quan Yao, Qingsong Liu, Zaiyi Zhou, S. Kevin School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Anhui Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Jiangsu Suzhou215123 China Institute of Computing Technology CAS Beijing100190 China Department of Radiology Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences Guangzhou China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences Guangzhou China

One-shot medical landmark detection gains much attention and achieves great success for its label-efficient training process. However, existing one-shot learning methods are highly specialized in a single domain and suffer domain preference heavily in the situation of multi-domain unlabeled data. Moreover, one-shot learning is not robust that it faces performance drop when annotating a sub-optimal image. To tackle these issues, we resort to developing a domain-adaptive one-shot landmark detection framework for handling multi-domain medical images, named Universal One-shot Detection (UOD). UOD consists of two stages and two corresponding universal models which are designed as combinations of domain-specific modules and domain-shared modules. In the first stage, a domain-adaptive convolution model is self-supervised learned to generate pseudo landmark labels. In the second stage, we design a domain-adaptive transformer to eliminate domain preference and build the global context for multi-domain data. Even though only one annotated sample from each domain is available for training, the domain-shared modules help UOD aggregate all one-shot samples to detect more robust and accurate landmarks. We investigated both qualitatively and quantitatively the proposed UOD on three widely-used public X-ray datasets in different anatomical domains (i.e., head, hand, chest) and obtained state-of-the-art performances in each domain. The code is at https://***/heqin-zhu/UOD_universal_oneshot_detection. © 2023, CC BY-NC-SA.

关键词： Learning systems

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PR2: A Physics- and Photo-realistic Humanoid Testbed with Pilot Study in Competition

arXiv

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arXiv 2024年

作者： Liu, Hangxin Xie, Qi Zhang, Zeyu Yuan, Tao Leng, Xiaokun Sun, Lining Zhu, Song-Chun Zhang, Jingwen He, Zhicheng Su, Yao Beijing100080 China Institute for Artificial Intelligence School of Artificial Intelligence Peking University Beijing100871 China Department of Automation Tsinghua University Beijing100084 China Department of Computer Science Harbin Institute of Technology Harbin150001 China School of Mechatronics Engineering Harbin Institute of Technology Harbin150080 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric Engineering Soochow University Suzhou215000 China

This paper presents the development of a Physicsrealistic and Photo-realistic humanoid robot testbed, PR2, to facilitate collaborative research between Embodied Artificial Intelligence (Embodied AI) and robotics. PR2 offers high-quality scene rendering and robot dynamic simulation, enabling (i) the creation of diverse scenes using various digital assets, (ii) the integration of advanced perception or foundation models, and (iii) the implementation of planning and control algorithms for dynamic humanoid robot behaviors based on environmental feedback. The beta version of PR2 has been deployed for the simulation track of a nationwide full-size humanoid robot competition for college students, attracting 137 teams and over 400 participants within four months. This competition covered traditional tasks in bipedal walking, as well as novel challenges in loco-manipulation and language-instruction-based object search, marking a first for public college robotics competitions. A retrospective analysis of the competition suggests that future events should emphasize the integration of locomotion with manipulation and perception. By making the PR2 testbed publicly available at https://***/pr2-humanoid/PR2-Platform, we aim to further advance education and training in humanoid robotics. © 2024, CC BY.

关键词： Anthropomorphic robots

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Recognition Method of Turbine Pollutant Adhesion in Tidal Energy Generation Systems Based on Deep Learning

SSRN

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SSRN 2023年

作者： Mo, Caixia Zhu, Wanqiang Lu, Bingquan Zu, Shuai Zhang, Fuli Chen, Jianmei Zhang, Xiao Wu, Baigong Zhang, Xueming School of Physics Northeast Normal University 5268 Renmin Street Jilin Province Changchun China Jilin Provincial Key Laboratory of Advanced Energy Development and Application Innovation 5268 Renmin Street Jilin Province Changchun China College of Mechanical and Electrical Engineering Central South University Changsha China Changchun University of Science and Technology China Jiangsu University of Science and Technology China

In light of the extended exposure of tidal energy generation systems to seawater, which can lead to marine biofouling and subsequent reductions in turbine efficiency, this paper presents a deep learning-based method for the identification of pollutant adhesion. This method aims to rapidly assess the adhesion status of turbines in tidal energy generation systems. A dataset of adhesion images from tidal energy generation system turbines under varying levels of pollution was obtained through underwater experiments with artificial fouling. Three different deep learning algorithms were employed to investigate the enhancement of underwater biofouling image quality. Image segmentation algorithms were used to extract and identify information related to the location and area of biofouling. The results demonstrate that the proposed deep learning-based pollutant adhesion identification method effectively recognizes the adhesion status on turbine blades, improving the accuracy of pollutant identification. This approach provides an efficient and accurate means of pollutant detection and management for the operation and maintenance of tidal energy generation systems, ultimately reducing operational costs. © 2023, The Authors. All rights reserved.

关键词： Image enhancement

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Lancet (London, England) 2025年第10481期405卷 777-779页

作者： Jieyu Qi Lei Xu Fan-Gang Zeng Renjie Chai State Key Laboratory of Digital Medical Engineering Department of Otolaryngology Head and Neck Surgery Zhongda Hospital School of Life Sciences and Technology School of Medicine Advanced Institute for Life and Health Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research Southeast University Nanjing 210096 China Department of Neurology Aerospace Center Hospital School of Life Science Beijing Institute of Technology Beijing China State Key Laboratory of Hearing and Balance Science Beijing Institute of Technology Beijing China School of Medical Engineering Affiliated Zhuhai People's Hospital Beijing Institute of Technology Zhuhai China Advanced Technology Research Institute Beijing Institute of Technology Jinan China. Department of Otolaryngology-Head and Neck Surgery Shandong Provincial ENT Hospital Shandong University Jinan Shandong China. Center for Hearing Research Departments of Anatomy and Neurobiology Biomedical Engineering Cognitive Sciences Otolaryngology-Head and Neck Surgery University of California Irvine Irvine CA USA. Co-Innovation Center of Neuroregeneration Nantong University Nantong China Department of Otolaryngology Head and Neck Surgery Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu China Southeast University Shenzhen Research Institute Shenzhen China. Electronic address: renjiec@***.

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