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Comparison of corrosion resistance of MgAl-LDH and ZnAl-LDH films intercalated with organic anions ASP on AZ31 Mg alloys

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Transactions of Nonferrous Metals Society of China 2020年第9期30卷 2424-2434页

作者： Jia-ling CHEN Liang FANG Fang WU Xian-guang ZENG Jia HU Shu-fang ZHANG Bin JIANG Hai-jun LUO Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials State Key Laboratory of Power Transmission Equipment&System Safety and New TechnologyCollege of PhysicsChongqing UniversityChongqing 400044China Material Corrosion and Protection Key Laboratory of Sichuan Province Institute of Materials Science and EngineeringSichuan University of Science and EngineeringZigong 643000China National Engineering Research Center for Magnesium Alloys College of Materials Science and EngineeringChongqing UniversityChongqing 400044China College of Software Chongqing College of Electronic EngineeringChongqing 401331China Chongqing Key Laboratory on Optoelectronic Functional Materials College of Physics and Electronic EngineeringChongqing Normal UniversityChongqing 401331China

The aspartic acid(ASP),an environment-friendly corrosion inhibitor,was explored to intercalate into the ZnAl-layered double hydroxide(ZnAl-LDH)and MgAl-LDH coatings on AZ31 magnesium alloys by a facile one-step hydrothermal *** morphology,composition,structure and corrosion resistance of the prepared coatings were comparatively *** is found that the uniform and dense layered nanosheet(NS)vertically grows on the substrate,and the MgAl−ASP-LDH films exhibit a three-dimensional(3D)rose-like sheet structure with high ratio of pore *** MgAl−ASP-LDH coating exhibits better corrosion resistance and durability of longtime immersion than ZnAl−ASP-LDH *** corrosion current density of two coatings is two or three orders of magnitude lower than that of bare Mg alloy,indicating that ZnAl/MgAl-LDH films intercalated with organic ASP anions can significantly improve the corrosion resistance of Mg alloy.

关键词： hydrotalcite magnesium alloy aspartic acid corrosion resistance corrosion inhibitor

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Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks

arXiv

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arXiv 2022年

作者： Gong, Jibing Wan, Yao Liu, Ye Li, Xuewen Zhao, Yi Wang, Cheng Lin, Yuting Fang, Xiaohan Feng, Wenzheng Zhang, Jingyi Tang, Jie School of Information Science and Engineering The Key Lab for Computer Virtual Technology and System Integration The Key Laboratory for Software Engineering of Hebei Province Yanshan University No. 438 West Hebei Avenue Hebei Qinhuangdao066004 China School of Computer Science and Technology Huazhong University of Science and Technology Luoyu Road 1037 Hubei Wuhan430074 China Salesforce Research 556 Xixi Road Chicago United States School of Cyber Science and Technology Beihang University 37 Xueyuan Road Beijing100191 China Department of Computer Science Tsinghua University Beijing100084 China

Massive open online courses (MOOCs), which offer open access and widespread interactive participation through the internet, are quickly becoming the preferred method for online and remote learning. Several MOOC platforms offer the service of course recommendation to users, to improve the learning experience of users. Despite the usefulness of this service, we consider that recommending courses to users directly may neglect their varying degrees of expertise. To mitigate this gap, we examine an interesting problem © 2022, CC BY.

关键词： Information services

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Study of the maturity of Logistics Service Providers in the Moroccan Context

Study of the maturity of Logistics Service Providers in the ...

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International Conference on Logistics (LOGISTIQUA)

作者： Khaoula Azzouz Jabir Arif Mohamed Badr Benboubker Research team: System Information and Software Engineering ENSA of Tetouan Abdelmalek Essaadi University Tetouan Morocco Laboratory: Modeling and Optimization of Industrial Systems and Logistics National School of Applied Sciences Tetouan Morocco

ISBN: (数字)9781728198811

ISBN: (纸本)9781728198828

This paper concerns the study of the market of logistics service providers (LSP) in Morocco, in particular, the study of the maturity of their logistics activities, particular attention is paid to the level of diversification of their logistics services offerings. Nowadays the extension in terms of service has become unavoidable for any implementation of a successful outsourcing strategy and to attract and convince clients through efficient and determined services. This work is structured mainly around two parts: the first part presenting the state of the art in the outsourcing of logistics activities in Morocco. The second part concerns an exploratory study grouping together a set of LSP operating in Morocco through several conditions. Those conditions include the most widespread fields, services offered and categorization of the Party Logistics (PL). This study will emphases the maturity of the LSP market in Morocco.

关键词： Economics Technological innovation Supply chain management Sociology Outsourcing Statistics Logistics

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Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

arXiv

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arXiv 2022年

作者： Chen, Huayu He, Huanhuan Zhu, Jing Sun, Shuting Li, Jianxiu Shao, Xuexiao Li, Junxiang Li, Xiaowei Hu, Bin Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China Brain Health Engineering Laboratory School of Medical Technology Beijing Institute of Technology Beijing China School of Information Science and Engineering Inner Mongolia University Inner Mongolia China Shandong Academy of Intelligent Computing Technology Jinan China Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences Lanzhou China Open Source Software and Real-Time System Lanzhou University Ministry of Education Lanzhou China

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results. Facing the situation that lacks EEG information decoding research, we first analyzed the impact of different EEG information(individual, session, emotion and trial) for emotion recognition by sample space visualization, sample aggregation phenomena quantification, and energy pattern analysis on five public datasets. Based on these phenomena and patterns, we provided the processing methods and interpretable work of various EEG differences. Through the analysis of emotional feature distribution patterns, the Individual Emotional Feature Distribution Difference(IEFDD) was found, which was also considered as the main factor of the stability for emotion recognition. After analyzing the limitations of traditional modeling approach suffering from IEFDD, the Weight-based Channel-model Matrix Framework(WCMF) was proposed. To reasonably characterize emotional feature distribution patterns, four weight extraction methods were designed, and the optimal was the correction T-test(CT) weight extraction method. Finally, the performance of WCMF was validated on cross-dataset tasks in two kinds of experiments that simulated different practical scenarios, and the results showed that WCMF had more stable and better emotion recognition ability. Copyright © 2022, The Authors. All rights reserved.

关键词： Emotion Recognition

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A TPAA-SBFE Based Partitioning Algorithm for Structural Viscoelastic Dynamic Analysis With Cyclic Symmetry

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International Journal for Numerical Methods in engineering 2025年第11期126卷

作者： Yang Yu Chongshuai Wang Ean Tat Ooi Sundararajan Natarajan Haitian Yang State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Department of Engineering Mechanics International Research Centre for Computational Mechanics Dalian University of Technology Dalian China College of Civil Engineering Jilin Jianzhu University Changchun China State Key Laboratory of Intelligent Power Distribution Equipment and System School of Electrical Engineering Hebei University of Technology Tianjin China Institute of Innovation Science and Sustainability Federation University Australia Ballarat Australia Integrated Modelling and Simulation Lab Department of Mechanical Engineering Indian Institute of Technology Chennai India

An innovative and efficient reduced order algorithm is proposed for the dynamic analysis of 2-D and 3-D viscoelastic structures featuring cyclic symmetry, which is applicable to complete cyclically symmetric structures with or without common nodes, as well as incomplete cyclically symmetric structures. The proposed algorithm is developed on a recursive platform based on TPAA-SBFEM and inherits all the advantages of TPAA-SBFEM. For complete cyclically symmetric structures with or without common nodes, the global stiffness and mass matrices are proved to be block-circulant and can be generated via a cyclically symmetric part instead of the whole domain. And then a recursive partitioning algorithm is rendered, such that the solution scale and computational cost can be efficiently reduced via solving a series of independent problems with small scales. For incomplete cyclically symmetric structures, the complete cyclic symmetry and Woodbury formula are utilized to reduce computational expense. Four numerical examples are provided to elucidate the effectiveness and efficiency of the proposed approach with satisfactory results.

关键词： cyclically symmetric dynamic analysis partitioning algorithm scaled boundary finite element method (SBFEM) viscoelasticity Woodbury formula

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Design and Application of a Portable Sleep Inertia Detection system Based on EEG Signals

Design and Application of a Portable Sleep Inertia Detection...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yunzhi Cui Fuze Tian Qinglin Zhao Bin Hu Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Chinese Academy of Sciences Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors Ministry of Education Engineering Research Center of Open Source Software and Real-Time System (Lanzhou University) Lanzhou China

ISBN: (纸本)9781665429825

Sleep inertia is a transitional state from sleep to wakefulness, accompanied by groggy feelings and cognitive impairment. Previous research on sleep inertia mainly used expensive and cumbersome equipment, and the analysis of physiological signals relied on computers. This work introduces a sleep inertia detection system that consists of a wearable low-power electroencephalogram (EEG) acquisition module based on STM32WB55 and ADS1299, and a data processing module based on the Xilinx ® Zynq ® -7000 XC7Z020. This work recorded the EEG signals of ten subjects in the alert and sleep inertia states to extract the delta power, alpha power, beta power, EEG vigilance, and sample entropy. A linear support vector machine (SVM) was then used to classify the two states based on all subjects’ EEG signals, with an accuracy of 72.5%, and the average accuracy based on a single participant was 8S.9%. Finally, the feature extraction algorithm and SVM parameters were entered into the Zynq ® system-on-chip (SoC) development board to realize onboard processing of the algorithm. The system is capable of evaluating the severity of human sleep inertia, which has reference significance for the practical application of sleep inertia detection.

关键词： Support vector machines Sleep Conferences Feature extraction Data processing Electroencephalography Physiology

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Logistics Service Providers in Morocco: A Study of the offer's suitability for local demand

Logistics Service Providers in Morocco: A Study of the offer...

引用

International Conference on Logistics and Operations Management (GOL)

作者： Azzouz Khaoula Arif Jabir Benboubker Mohamed Badr Research team: System Information and Software Engineering ENSA of Tetouan Abdelmalek Essaadi University Tetouan Morocco Associate researcher at Laboratory: Modeling and Optimization of Industrial Systems and Logistics National School of Applied Sciences Tetouan Morocco

ISBN: (数字)9781728164250

ISBN: (纸本)9781728164267

The main objective of this paper is to study the adequacy of the offer of the logistic service providers with the needs anticipated by the different national economic sectors. This study will allow us to appreciate the maturity of the LSP operating in Morocco, through the level of diversification of their logistics services offerings and thus the extent of their responsiveness. Nowadays the expansion in terms of service has become crucial for any implementation of a successful outsourcing strategy and to attract and convince contractors through efficient and well adapted services. This paper is structured mainly around three parts: the first part presenting the state of the art in the outsourcing of logistics activities in Morocco. The second part is a presentation of the Moroccan economy through the different national economic sectors. The third part concerns an exploratory study grouping, on the one hand, the various Moroccan sectors and their needs in logistics services, and on the other hand, the offers of a group of LSP operating in Morocco through several services they offer. This study will allow knowing the maturity of the market of the LSP operating in Morocco and its homogeneity with the existing sectors in the country.

关键词： Logistics Outsourcing Companies Economics Business Technological innovation Supply chains

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A NOMA Power Allocation Strategy Based on Genetic Algorithm 8th

A NOMA Power Allocation Strategy Based on Genetic Algorithm

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8th International Conference on Communications, Signal Processing, and systems, CSPS 2019

作者： Yin, Lu Chenggong, Wang Kai, Mao Kuanxin, Bao Haowei, Bian Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003 China Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Nanjing University of Posts and Telecommunications Ministry of Education Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789811394089

The NOMA technology uses the power domain non-orthogonal multiplexing method to enable multiple users to occupy the entire frequency band simultaneously to transmit signals. In order to maximize the total transmission rate of the system, an effective method is to use the genetic algorithm for NOMA power allocation. In this paper, the NOMA downlink system model is constructed, and the objective function and constraints are analyzed. A NOMA power allocation strategy based on genetic algorithm is proposed. The algorithm distributes user power based on the criterion of maximizing total transmission rate, therefore the algorithm has random search capabilities and relatively low search complexity. The simulation results show that when the system transmits power or multiplexed users is fixed the proposed algorithm outperforms the fixed power allocation algorithm in the total transmission rate. The total system transmission rate of the genetic algorithm is similar to the full space search algorithm. As the number of multiplexed users increases, the computational complexity of genetic algorithms is much lower than that of full-space search algorithms. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Computational complexity

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A Model Based Heterogeneous Data Collaboration Method

A Model Based Heterogeneous Data Collaboration Method

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IEEE International Conference on Electronics and Communication engineering (ICECE)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Bowen Wei Hongyan Quan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Simulation Center Science and Technology on Space System Simulation Laboratory Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728192581

ISBN: (纸本)9781728192598

Model based heterogeneous data collaboration is important in the integrated design and manufacturing technology. In this work, we propose a systematic method of collaborative design method for heterogeneous data sources. In our method, we use the Open Model Based engineering Environment (OpenMBEE) to study. In our work, we setup environment and construct the integrated multi-tools achieving consistency design, and then we successfully design and implement a reasonable scheme to parameterize the model in requirement analysis and store the extracted parameters in Model Management system (MMS) for transporting to the visualization tool for further simulation. We integrate the mathematical analysis tools of MATLAB, and successfully design the interface in the tool integration, and realize the model consistency in the problem of integrating multiple tools in the design based on model center. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our provided study can an effective design idea for complex production.

关键词： Analytical models Collaboration Production Tools Data models Mathematical model Matlab

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

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arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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