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DPA-2:a large atomic model as a multitask learner

npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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Line Spacing Effect on the Giant Magnetoimpedance Behavior of Microribbon Meanders: A Comparison of Theory and Experiment

SSRN

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SSRN 2023年

作者： Yang, Zhen Wang, Zhenbao Liu, Mengyu Meng, Ziqin Sun, Xuecheng Huang, Yong Guo, Yongbin School of Electronic and Information Engineering School of Integrated Circuits Guangxi Normal University Guangxi Guilin541004 China Education Department of Guangxi Zhuang Autonomous Region Guangxi Guilin541004 China Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University Guilin541004 China Microelectronic Research & Development Center School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Xidian-Wuhu Research Institute Anhui Wuhu241000 China Key Laboratory of UWB & THz of Shandong Academy of Sciences Institute of Automation Qilu University of Technology Shandong Academy of Sciences Jinan250014 China

Microribbon meanders based on giant magnetoimpedance (GMI) effect have become a research hot spot due to their higher sensitivity and spatial resolution. However, further optimization of the line spacing is required to improve the performance of meanders for sensor application. The model of GMI effect of microribbon meanders is established. The effect of variable line spacing (Ls) on GMI behavior in meanders are analyzed systematically. Comparison of theory and experiment indicates that the smaller line spacing increases the spatial resolution of the meanders and improves its performance. The line spacing is roughly negatively correlated with GMI ratio. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance. The superior line spacing is found in the identical sensing area. Our findings will contribute to the design of high-performance micropatterned meander GMI sensors and the establishment of ribbon-based magnetic-sensitive biosensing system. © 2023, The Authors. All rights reserved.

关键词： Electric impedance

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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An IoT Edge computing System Architecture and its Application

An IoT Edge Computing System Architecture and its Applicatio...

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2020 IEEE International Conference on Networking, Sensing and Control, ICNSC 2020

作者： Chen, Shichao Li, Qijie Zhang, Hua Zhu, Fenghua Xiong, Gang Tang, Ying Macau University of Science and Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China Beijing University of Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Platform Research and Development Department Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Research Center of Intelligent Systems and Technology Institute of Automation Cloud Computing Center Chinese Academy of Sciences Beijing China Rowan University Department of Electrical and Computer Engineering GlassboroNJ United States Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781728168531

As the number of devices connected to the Internet of things (IoT) surges, the amount of data explodes. Therefore it not only increases the bandwidth load of data transmission but also aggravates the computing and storage load of a cloud platform. At the same time, the traditional computing paradigm centered on cloud computing cannot meet the real-time requirements in many application scenarios. The emergence of edge computing can solve the problems of realtime data processing and network bandwidth occupation in the current IoT scene. In this paper, according to the characteristics of IoT, such as fragmented data, heterogeneous network, and limited energy consumption, the architecture of an IoT edge computing system is constructed to suit better an IoT scene. In addition, the application of edge computing key technologies such as virtualization, edge intelligence, computing offload, collaborative scheduling and micro-services in resource-constrained IoT scenarios is analyzed in detail. Finally, the functions and application of energy consumption monitoring and optimization to a central air-conditioning system are analyzed and summarized, which is a typical application of edge computing in the context of the IoT. © 2020 IEEE.

关键词： Edge computing

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Revealing the Hot Workability and Deformation Mechanism of a Low-Density Fe-Mn-Al-C Duplex Steel

SSRN

引用

SSRN 2022年

作者： Wu, Zhiqiang Liu, Shuai Hasan, Md Nzmul Li, Eric Chi, Yunguang Xiao, Daheng Yu, Qing Zhang, Shunhu Hu, Jun Chen, Lei Lu, Liwei An, Xianghai Engineering Research Center of Mineral Resources Development Technology and Equipment for Deep Sea and Deep Earth Ministry of Education Hunan University of Science and Technology Hunan Xiangtan411201 China School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2006 Australia School of Computing Engineering & Digital Technologies Teesside University Middlesbrough United Kingdom Technical Quality Department Xiangtan Iron & Steel Co. Ltd of Hunan Valin Hunan Xiangtan411101 China Shagang School of Iron and Steel Soochow University Suzhou215021 China The State Key Laboratory of Rolling and Automation Northeastern University Liaoning Shenyang110819 China Xiangtan University China

In this study, we systematically investigated the hot deformation behavior of a low-density dual-phase Fe-Mn-Al-C steel during compression tests at the temperature range of 800-1000 °C and strain rates of 0.01-101s-1. The constitutive relation for the hot deformation of this steel was established to explore its flow behavior quantitatively, while the hot processing map was constructed to optimize the hot working parameters. In addition, the flow behavior, mechanical properties and microstructural evolutions of the steel at different temperatures and a high strain rate 101s-1 that are comparable to that during hot processing (rolling and forging) were mainly focused. The flow stress decreases with increasing the temperatures, while the peak stress appears at a more considerable strain with lowering the deformation temperatures. Moreover, the steel exhibited superior peak strengths at different temperatures compared to other traditional steels. In the unstable zone of the processing map, the ferrite and the austenite exhibit distinct hot deformation behavior, leading to inhomogeneous deformation. With increasing the temperature, the critical zone and the stable zone appear successively. The dynamic recrystallization (DRX) played increasingly crucial roles in the deformation of austenite, while a gradual transition from dynamic recovery to DRX occurred to undertake the deformation of ferrite. © 2022, The Authors. All rights reserved.

关键词： Dynamic recrystallization

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A Conceptual Model of Cyberterrorists’ Rhetorical Structure in Protecting National Critical Infrastructure 1st

A Conceptual Model of Cyberterrorists’ Rhetorical Structure...

引用

1st International Conference on Smart Innovation, Ergonomics and Applied Human Factors, SEAHF 2019

作者： Osman, Khairunnisa Alarood, Ala Jano, Zanariah Ahmad, Rabiah Manaf, Azizah Abdul Mahmoud, Marwan Innovative and Sustainable Technical Education Centre of Technopreneurship Development University Teknikal Malaysia Melaka Melaka Malaysia Department of Computer Science Faculty of Computing and Information Technology University of Jeddah Jeddah Saudi Arabia Information Security and Networking Research Group Center for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Melaka Malaysia King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9783030229634

This study presents a conceptual paper on developing a model of cyberterrorists’ rhetorical structure. The objectives of the study are to identify the type of rhetoric’s in cyber terrorists’ communication, analyze how the cyber terrorists utilize appeal to audience, stylistic devices and argumentation in their communication and to propose a model of cyber terrorists’ rhetorical structure. A rhetorical analysis is conducted by examining recent cyberterrorists sites in popular media. Several categories are utilized;Appeal to the audience;Stylistic devices and Argumentation model. Drawing on a selected theoretical framework a combination of quantitative word-level analysis and qualitative coding will be used to assess the categories which are framed by cyber terrorists. © 2019, Springer Nature Switzerland AG.

关键词： Terrorism

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Intelligent Paving and Rolling Construction Technology of Asphalt Pavement

引用

Journal of Physics: Conference Series 2022年第1期2185卷

作者： Taiping Yuan Zheng Wang Qiaozhang Hong Jing Chen Jiechao Lei Yongjun Meng China Southern Power Grid Energy Development Research Institute College of Civil Engineering and Architecture Guangxi University Nanning People's Republic of China Key Laboratory of Disaster Prevention and Engineering Safety of Ministry of Education Nanning People's Republic of China National High- performance Computing Center Nanning Branch Nanning People's Republic of China

The intelligent construction system of asphalt pavement consists of an intelligent paver, driverless roller, mobile base station, intelligent control program, etc. By installing GPS(BDS)+ GNS satellite receiver, 5G communication chip, microwave communication host, radio signal receiving antenna on the construction equipment and connecting with the processor, switch, program software, and other components set on the equipment, integrate the laser obstacle avoidance radar, infrared temperature detection device, laser ranging sensor and other terminal equipment set on the equipment to realize the intellectualization of equipment use function; By running the intelligent control system, mobile 5G communication base station system and construction area acquisition system, command the linkage operation of multiple intelligent types of equipment to realize the intelligent control of pavement construction and meet the requirements of asphalt pavement design specifications.

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Eye tracking: empirical foundations for a minimal reporting guideline

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Behavior research methods 2023年第1期55卷 364-416页

作者： Kenneth Holmqvist Saga Lee Örbom Ignace T C Hooge Diederick C Niehorster Robert G Alexander Richard Andersson Jeroen S Benjamins Pieter Blignaut Anne-Marie Brouwer Lewis L Chuang Kirsten A Dalrymple Denis Drieghe Matt J Dunn Ulrich Ettinger Susann Fiedler Tom Foulsham Jos N van der Geest Dan Witzner Hansen Samuel B Hutton Enkelejda Kasneci Alan Kingstone Paul C Knox Ellen M Kok Helena Lee Joy Yeonjoo Lee Jukka M Leppänen Stephen Macknik Päivi Majaranta Susana Martinez-Conde Antje Nuthmann Marcus Nyström Jacob L Orquin Jorge Otero-Millan Soon Young Park Stanislav Popelka Frank Proudlock Frank Renkewitz Austin Roorda Michael Schulte-Mecklenbeck Bonita Sharif Frederick Shic Mark Shovman Mervyn G Thomas Ward Venrooij Raimondas Zemblys Roy S Hessels Department of Psychology Nicolaus Copernicus University Torun Poland. kenneth.holmqvist@ur.de. Department of Computer Science and Informatics University of the Free State Bloemfontein South Africa. kenneth.holmqvist@ur.de. Department of Psychology Regensburg University Regensburg Germany. kenneth.holmqvist@ur.de. Department of Psychology Regensburg University Regensburg Germany. Experimental Psychology Helmholtz Institute Utrecht University Utrecht The Netherlands. Lund University Humanities Lab and Department of Psychology Lund University Lund Sweden. Department of Ophthalmology SUNY Downstate Health Sciences University Brooklyn NY USA. Tobii Pro AB Danderyd Sweden. Social Health and Organizational Psychology Utrecht University Utrecht The Netherlands. Department of Computer Science and Informatics University of the Free State Bloemfontein South Africa. TNO Soesterberg The Netherlands. Department of Ergonomics Leibniz Institute for Working Environments and Human Factors Dortmund Germany. Institute of Informatics LMU Munich Munich Germany. Institute of Child Development University of Minnesota Minneapolis USA. School of Psychology University of Southampton Southampton UK. School of Optometry and Vision Sciences Cardiff University Cardiff UK. Department of Psychology University of Bonn Bonn Germany. Vienna University of Economics and Business Vienna Austria. Department of Psychology University of Essex Essex UK. Department of Neuroscience Erasmus MC Rotterdam The Netherlands. Machine Learning Group Department of Computer Science IT University of Copenhagen Copenhagen Denmark. SR Research Ltd Ottawa Canada. Human-Computer Interaction University of Tübingen Tübingen Germany. University of British Columbia Columbia Canada. Department of Eye and Vision Science Institute of Life Course and Medical Sciences University of Liverpool Liverpool UK. Department of Education and Pedagogy Division Education Faculty of Social and Behavioral Sciences Ut

In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").

关键词： Data quality Eye movements Eye tracking Replicability Reporting guidelines Reporting practices Reporting standards Reproducibility

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Optimization of 4D/3D printing via machine learning: A systematic review

Hybrid Advances

引用

Hybrid Advances 2024年 6卷

作者： Alli, Yakubu Adekunle Anuar, Hazleen Manshor, Mohd Romainor Okafor, Christian Emeka Kamarulzaman, Amjad Fakhri Akçakale, Nürettin Mohd Nazeri, Fatin Nurafiqah Bodaghi, Mahdi Suhr, Jonghwan Mohd Nasir, Nur Aimi Department of Manufacturing and Materials Engineering Kulliyyah of Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur 53100 Malaysia CNRS LCC (Laboratoire de Chimie de Coordination) UPR8241 Université de Toulouse UPS INPT Toulouse cedex 4 F-31077 France Department of Chemical Sciences Faculty of Science and Computing Ahman Pategi University Km 3 Patigi-Kpada Road Kwara State Patigi Nigeria Food Sciences & Technology Research Center Malaysian Agricultural Research and Development Institute Persiaran MARDI-UPM Selangor Serdang 43400 Malaysia Department of Mechanical Engineering Nnamdi Azikiwe University Awka Nigeria Textile Clothing Footwear and Leather Department Gerede Vocational School of Higher Education Abant İzzet Baysal University Bolu 14900 Turkey Department of Engineering School of Science and Technology Nottingham Trent University Nottingham NG11 8NS United Kingdom Faculty of Mechanical Engineering College of Engineering Sungkyunkwan University Natural Sciences Campus 2066 Seobu-ro Jangan-gu Gyeonggi-do Suwon 16419 South Korea NanoVerify Sdn Bhd e-8-6 (Suite 5.8) Block E Megan Avenue 1 189 Jalan Tun Razak Kuala Lumpur 54050 Malaysia

This systematic review explores the integration of 4D/3D printing technologies with machine learning, shaping a new era of manufacturing innovation. The analysis covers a wide range of research papers, articles, and patents, presenting a multidimensional perspective on the advancements in additive manufacturing. The review underscores machine learning's pivotal role in optimizing 4D/3D printing, addressing aspects like design customization, material selection, process control, and quality assurance. The examination reveals novel techniques enabling the fabrication of intelligent, self-adaptive structures capable of transformation over time. Additionally, the review investigates the use of predictive algorithms to enhance efficiency, reliability, and sustainability in 4D/3D printing processes. Applications span aerospace, healthcare, architecture, and consumer goods, showcasing the potential to create intricate, personalized, and once-unattainable functional products. The synergy between machine learning and 4D/3D printing is poised to unlock new manufacturing horizons, enabling rapid responses to market demands and sustainability challenges. In summary, this review provides a comprehensive overview of the current state of 4D/3D printing optimization through machine learning, highlighting the transformative potential of this interdisciplinary fusion and offering a roadmap for future research and development. It aims to inspire innovators, researchers, and industries to harness this powerful combination for accelerated evolution in manufacturing processes into the 21st century and beyond. © 2024 The Authors

关键词： 3D printing 4D printing Machine learning Smart materials

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Thalamocortical Connection Topography Mapping in Human by Co-clustering

Thalamocortical Connection Topography Mapping in Human by Co...

引用

2019 3rd International Conference on Machine Vision and Information Technology (CMVIT 2019)

作者： Hewei Cheng Jie Liu Yiying Tao Department of Biomedical Engineering School of Bioinformatics Chongqing University of Posts and Telecommunications Center for Biomedical Image Computing and Analytics Department of Radiology Perelman School of Medicine University of Pennsylvania Research Institute of Education Development Chongqing University of Posts and Telecommunications

Connection topography mapping is crucial for understanding how information is processed in the brain, which is an essential precursor for revealing principles of brain organization. However, existing connectopic mapping methods are dependent on prior knowledge, or not completely driven by data. Accordingly, the constructed connection topographies by these methods are biased towards hypotheses, or deviate from data. For these challenges, we propose a novel co-clustering based method for connection topography mapping in a fully data-driven manner. The proposed method aims to construct the connection topography between two ROIs of a certain neural circuit in consideration by leveraging the power of co-clustering. More precisely, the proposed method parcellates one ROI into subregions and identified their respective connected subregions from the other ROI simultaneously. The effectiveness of our method was validated on the mapping of the human thalamocortical system for 57 subjects based on their resting state f MRI data. The validation experiment results have demonstrated that our method can construct neurobiologically meaningful thalamocortical connection topography. Compared with existing methods, our method yields more meaningful and interpretable connection topography.

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