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26th International Conference on Miniaturized Systems for Chemistry and Life sciences, MicroTAS 2022

作者： Cao, Wenjian Pan, Yating Mu, Ying Zhu, Qiangyuan Research Center for Analytical Instrumentation College of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Research Center for Analytical Instrumentation College of Life Sciences State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781733419048

The unprecedented single-cell resolution provided by single-cell RNA sequencing (scRNA-seq) powered the progress of biomedical research, leading to revolutionary discoveries. However, current high-throughput scRNA-seq methods are limited by sensitivity and can only detect polyadenylated transcripts. Utilizing polymer-tethered degenerate primer and droplet-based microfluidics, we developed a high-throughput scRNA-seq method with high sensitivity and whole transcriptomic detection capability. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life sciences. All rights reserved.

关键词： Microfluidics

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Improved material descriptors for bulk modulus in intermetallic compounds via machine learning

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Rare Metals 2023年第7期42卷 2396-2405页

作者： De-Xin Zhu Kun-Ming Pan Yuan Wu Xiao-Ye Zhou Xiang-Yue Li Yong-Peng Ren Sai-Ru Shi Hua Yu Shi-Zhong Wei Hong-Hui Wu Xu-Sheng Yang National Joint Engineering Research Center for Abrasion Control and Molding of Metal Materials Henan Key Laboratory of High-Temperature Structural and Functional MaterialsHenan University of Science and TechnologyLuoyang471003China Longmen Laboratory Luoyang471003China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing100083China Guangdong Province Key Laboratory of Durability for Marine Civil Engineering School of Civil EngineeringShenzhen UniversityShenzhen518060China Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong999077China

Bulk modulus is an important mechanical property in the optimal design and selection of intermetallic *** this study,bulk modulus datasets of intermetallic compounds were collected,and the features affecting the bulk modulus of intermetallics were screened via feature *** features B_(cal),dB_(avg),and TIE(corresponding to calculated bulk modulus,mean bulk modulus,and third ionization energy,respectively)were found to be the dominant factors influencing bulk modulus and can be extended to other multi-component ***,we predicted the bulk modulus with an accuracy of 95%using surrogate machine learning models with the selected features,and these features were also demonstrated to be effective for high-entropy ***,symbolic regression provided an expression for the relationship between bulk modulus and the screened *** machine learning models provide a new approach for optimizing and predicting the bulk moduli of intermetallic compounds.

关键词： Bulk modulus Intermetallic compounds Machine learning Symbolic regression

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Rydberg-Induced Topological Solitons in Three-Dimensional Rotation Spin–Orbit-Coupled Bose–Einstein Condensates

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Chinese Physics Letters 2024年第9期41卷 9-14页

作者： Yang Wang Jinlong Cui Hongkai Zhang Yuan Zhao Siliu Xu Qin Zhou Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and TechnologyXianning 437100China School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100China School of Biomedical Engineering and Imaging Xianning Medical CollegeHubei University of Science and TechnologyXianning 437100China Research Center of Nonlinear Science School of Mathematics and Physical SciencesWuhan Textile UniversityWuhan 430200China

We present a novel approach for generating stable three-dimensional(3D)spatiotemporal solitons(SSs)within a rotating Bose–Einstein condensate,incorporating spin–orbit coupling(SOC),a weakly anharmonic potential and cold Rydberg *** intricate system facilitates the emergence of quasi-stable 3D SSs with topological charges|m|≤3 in two spinor components,potentially exhibiting diverse spatial *** findings reveal that the Rydberg long-range interaction,spin–orbit coupling,and rotational angular frequency exert significant influence on the domains of existence and stability of these ***,the Rydberg interaction contributes to a reduction in the norm of topological solitons,while the SOC plays a key role in stabilizing the SSs with finite topological *** research of SSs exhibits potential applications in precision measurement,quantum information processing,and other advanced technologies.

关键词： Rydberg topological Einstein

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Erratum to:A nonlinear wake model of a wind turbine considering the yaw wake steering

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Journal of Oceanology and Limnology 2024年第3期42卷 1016-1017页

作者： Yunzhou LI Zhiteng GAO Shoutu LI Suiping QI Xiaoyu TANG College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Multi-function Towing Tank School of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730050China Institute of Oceanographic Instrumentation Qilu University of Technology(Shandong Academy of Sciences)Qingdao 266061China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Laoshan Laboratory Qingdao 266237China

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Efficient Autonomous Exploration of Unknown Environment Using Regions Segmentation and VRP 1

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16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Xue, Chaoyu Zhao, Tianhao Xie, Anhuan Zhu, Qiuguo Wu, Jun Xiong, Rong College of Control Science and Engineering Zhejiang University Hangzhou China Polytechnic Institute Zhejiang University Hangzhou China Zhejiang Lab Hangzhou China State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Autonomous exploration of unknown environments is a critical application scenario in robotics. However, existing studies have strived to generate an efficient tour plan that enables the robots to fully explore the environment. This is due to the greedy strategies and the lack of utilizing the information of the unexplored area. To address the above issues, we propose a new exploration strategy. Our approach involves partitioning the unexplored area into distinct regions and utilizing their estimated workload and spatial structure to construct a region graph. Subsequently, a VRP (Vehicle Routing Problem) planner allocates regions to robots and generates a global tour for each robot in a coordinated manner, which is then refined and provided to the robot’s navigation module. Experimental results demonstrate that that our method outperforms existing approaches in terms of exploration speed, total distance, and overlap ratio. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Robots

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Reproductive Toxicities of Tetradecyltrimethylammonium Chloride and Tetradecyltrimethylammonium Bromide on Caenorhabditis elegans over Four Consecutive Generations

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Chemical Research in Chinese Universities 2024年第6期40卷 1060-1067页

作者： ZHANG Jing DING Ruoqi YU Zhenyang Ecological Technique and Engineering College Shanghai Institute of TechnologyShanghai 201418P.R.China Jiaxing Tongji Institute for Environment Jiaxing 314051P.R.China State Key Laboratory of Pollution Control and Resource Reuse Key Laboratory of Yangtze River Water EnvironmentMinistry of EducationCollege of Environmental Science and EngineeringTongji UniversityShanghai 200092P.R.China

Quaternary ammonium compounds (QACs) become emerging pollutants and their toxicities earn increasing *** far,their reproductive toxicities were poorly investigated,and their effects over generations were even less *** the present study,reproductive toxicities of two QACs,i.e.,tetradecyltrimethylammonium chloride (TTAC);tetradecyltrimethylammonium bromide (TTAB) were studied on Caenorhabditis elegans with a consecutive exposure over four generations (from F1 to F4).The effects of TTAC on total and initial reproduction showed stimulation and inhibition,which oscillated from F1 to *** effects of TTAB on the total reproduction commonly showed stimulation over generations with the greatest stimulation in F2,and it inhibited the initial reproduction but stimulated the reproduction *** exploration demonstrated that TTAC and TTAB significantly disturbed the levels of spermatocyte protein 8 (SPE8);sperm transmembrane protein 9 (SPE9);vitellogenin (Vg);major sperm protein (MSP);ephrin receptor protein tyrosine kinase (VAB-1);the expressions of vab-1,ceh-18,set-2,met-2 and *** disturbances demonstrated that both QACs impacted the reproductive processes via oocyte meiosis,gonadal support and germline ***,the effects of TTAC and TTAB in parents were connected with those in the offspring,which highlighted the roles of reproduction in connecting *** addition,different effects between TTAC and TTAB demonstrated the anionic influences on the QACs’ toxicities.

关键词： Multigenerational effect Oocyte meiosis Gonadal support Germline development Anionic influence

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Root-KGD: A Novel Framework for Root Cause Diagnosis Based on Knowledge Graph and industrial Data

arXiv

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arXiv 2024年

作者： Chen, Jiyu Qian, Jinchuan Zhang, Xinmin Song, Zhihuan State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China

With the development of intelligent manufacturing and the increasing complexity of industrial production, root cause diagnosis has gradually become an important research direction in the field of industrial fault diagnosis. However, existing research methods struggle to effectively combine domain knowledge and industrial data, failing to provide accurate, online, and reliable root cause diagnosis results for industrial processes. To address these issues, a novel fault root cause diagnosis framework based on knowledge graph and industrial data, called Root-KGD, is proposed. Root-KGD uses the knowledge graph to represent domain knowledge and employs data-driven modeling to extract fault features from industrial data. It then combines the knowledge graph and data features to perform knowledge graph reasoning for root cause identification. The performance of the proposed method is validated using two industrial process cases, Tennessee Eastman Process (TEP) and Multiphase Flow Facility (MFF). Compared to existing methods, Root-KGD not only gives more accurate root cause variable diagnosis results but also provides interpretable fault-related information by locating faults to corresponding physical entities in knowledge graph (such as devices and streams). In addition, combined with its lightweight nature, Root-KGD is more effective in online industrial applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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Short‐term and long‐term memory self‐attention network for segmentation of tumours in 3D medical images

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1524-1537页

作者： Mingwei Wen Quan Zhou Bo Tao Pavel Shcherbakov Yang Xu Xuming Zhang Department of Biomedical Engineering College of Life Science and TechnologyHuazhong University of Science and TechnologyWuhanChina State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Institute for Control Science Russian Academy of SciencesMoscowRussia Hubei Medical Devices Quality Supervision and Test Institute WuhanChina

Tumour segmentation in medical images(especially 3D tumour segmentation)is highly challenging due to the possible similarity between tumours and adjacent tissues,occurrence of multiple tumours and variable tumour shapes and *** popular deep learning‐based segmentation algorithms generally rely on the convolutional neural network(CNN)and *** former cannot extract the global image features effectively while the latter lacks the inductive bias and involves the complicated computation for 3D volume *** existing hybrid CNN‐Transformer network can only provide the limited performance improvement or even poorer segmentation performance than the pure *** address these issues,a short‐term and long‐term memory self‐attention network is ***,a distinctive self‐attention block uses the Transformer to explore the correlation among the region features at different levels extracted by the ***,the memory structure filters and combines the above information to exclude the similar regions and detect the multiple ***,the multi‐layer reconstruction blocks will predict the tumour *** results demonstrate that our method outperforms other methods in terms of subjective visual and quantitative *** with the most competitive method,the proposed method provides Dice(82.4%vs.76.6%)and Hausdorff distance 95%(HD95)(10.66 vs.11.54 mm)on the KiTS19 as well as Dice(80.2%vs.78.4%)and HD95(9.632 vs.12.17 mm)on the LiTS.

关键词： 3D medical images convolutional neural network self‐attention network transformer tumor segmentation

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Robust production of N-acetyl-glucosamine in engineered Escherichia coli from glycerol-glucose mixture

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Synthetic and Systems Biotechnology 2025年第3期10卷 1014-1026页

作者： Sun, Wenchao Tang, Yulin Tian, Yahao Liu, Zhengkai Xiong, Wenwen Zhang, Hengshuai Chen, Liang Wu, Heyun Ma, Qian Xie, Xixian Key Laboratory of Industrial Fermentation Microbiology Ministry of Education Tianjin University of Science and Technology Tianjin 300457 China College of Biotechnology Tianjin University of Science and Technology Tianjin 300457 China National and Local United Engineering Lab of Metabolic Control Fermentation Technology Tianjin University of Science and Technology Tianjin 300457 China

Achieving a balanced cell growth and biosynthesis of target products is a pivotal challenge confronted in the realm of green biomanufacturing of chemicals, and it holds the promise of significantly enhancing the titer/yield/productivity of the target products. The co-utilization of carbon sources has emerged as a proven approach for the precise regulation of cell growth and biosynthesis processes, thereby serving as a potent strategy to expedite the production of chemicals. In our previous study, we successfully demonstrated the efficient production of N-acetyl-glucosamine in engineered Escherichia coli by leveraging an appropriate catabolic division of labor, utilizing a mixture of glycerol and glucose as the carbon source. In this study, we further refined the division of labor between these two carbon sources by meticulously regulating the expression of the zwf gene, which encodes glucose-6-phosphate dehydrogenase and is crucial in diverting carbon source to the pentose phosphate pathway (PPP). After comparing three strategies for balancing cell growth and production, the engineered strain NAG-1 with zwf knocked out aided by the optimization of the glycerol-to-glucose ratio and the feeding mode of carbon sources resulted in robust production of N-acetyl-glucosamine. Remarkable production in a 5 L bioreactor was achieved, obtaining 249 g/L of N-acetyl-glucosamine with a yield of 0.684 g/g of total carbon sources (specifically, 0.791 g/g of glucose) and a productivity of 3.46 g/L/h. These results establish NAG-1 as the most efficient microbial cell factory reported thus far for the bioproduction of N-acetyl-glucosamine. The robust production of N-acetyl-glucosamine in E. coli using a mixture of glycerol and glucose suggests the immense potential of mixed carbon sources in the industrial green biomanufacturing of chemicals. © 2025 The Authors

关键词： Escherichia coli Glycerol-glucose mixture N-Acetyl-glucosamine Robust production

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Self-Preloading Flexible Attachment Actuator with Multi-Mechanism Hierarchical Structure

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Journal of Bionic engineering 2024年第4期21卷 1830-1846页

作者： Zhouyi Wang Qingsong Yuan Zhiyuan Weng Junsheng Yao Xuan Wu Lei Li Weipeng Li Yiping Feng Zhendong Dai College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics210016NanjingChina State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and Astronautics210016NanjingChina Robotics Laboratory China Nanhu Academy of Electronics and Information Technology314000JiaxingZhejiangChina

Flexible attachment actuators are popular in a wide range of applications,owing to their flexibility and highly reliable ***,their reversible adhesion performance depends on the actual effective contact area and peel angle during ***,a good actuator must ensure a uniform and reliable pre-pressure load on an adhesive surface,to increase the effective contact area of the attached surface,thereby maximizing *** study was inspired by fusion bionics for designing a hierarchical attachment structure with vacuum-adsorption and dry-adhesion *** designed structure used the normal force under the negative pressure of a suction cup as a stable source of a pre-pressure *** optimizing the rigid and flexible structural layers of the attachment structure,a load was applied uniformly to the adhesion area;thus,reliable attachment was achieved by *** structure achieved detachment by exploiting the large deformation of a pneumatic structure under a positive *** hierarchical attachment structure achieved up to 85%of the optimal performance of the adhesive *** to its self-preloading and reliable attachment characteristics,the designed structure can be used as an attachment unit in various complex scenarios,such as small,lightweight climbing platforms and the transport of objects in long,narrow pipelines.

关键词： Multi-mechanism attachment Self-preloading Hierarchical structure Adhesion Vacuum adsorption

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