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One-step pore diffusion mechanism of Li+ in solid electrolyte interphase for fast-charging lithium-ion battery

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Rare Metals 2024年第7期43卷 3438-3440页

作者： shan Wang Shu-Yuan liu Alireza Khataee ke-Zhen Qi College of Pharmacy Dali University Research Laboratory of Advanced Water and Wastewater Treatment Processes Department of Applied ChemistryFaculty of ChemistryUniversity of Tabriz Peoples' Friendship University of Russia (RUDN University)

Li+transport in solid electrolyte interphase is recognized as important factor,which has become a research ***,an one-step pore diffusion mechanism for Li+transport through solid electrolyte interphase was proposed,which was different from previous two-step *** one-step pore diffusion process could effectively eliminate the dynamic limitations of Li+transport in solid electrolyte interphase （SEI） for rapid charging *** work will contribute to the development of rapid charging lithium-ion batteries.

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Evolution and Application of Sealing Ability of Gypsum Caprocks under Temperature-Pressure Coupling:An Example of the ZS5 Well in the Tazhong Area of the Tarim Basin

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Acta Geologica Sinica(English Edition) 2024年第1期98卷 168-184页

作者： liu Hua ZHAO shan YANG Xianzhang ZHU Yongfeng WANG Shen ZHANG ke National key Laboratory of Deep Oil and Gas China University of Petroleum(East China)QingdaoShandong 266580China School of Geosciences China University of Petroleum(East China)QingdaoShandong 266580China Laboratory for Marine Mineral Resources National Laboratory for Marine Science and TechnologyQingdaoShandong 266071China PetroChina Tarim Oil Field Company KorlaXinjiang 841001China

Gypsum caprocks'sealing ability is affected by temperature-pressure *** to the limitations of experimental conditions,there is still a lack of triaxial stress-strain experiments that simultaneously consider changes in temperature and pressure conditions,which limits the accuracy of the comprehensive evaluation of the brittle plastic evolution and sealing ability of gypsum rocks using temperature pressure *** stress-strain tests were utilized to investigate the differences in the evolution of the confinement capacity of gypsum rocks under coupled temperaturepressure action and isothermal-variable pressure action on the basis of sample feasibility *** to research,the gypsum rock's peak and residual strengths decrease under simultaneous increases in temperature and pressure over isothermal pressurization experimental conditions,and it becomes more *** reduces the amount of time it takes for the rock to transition from brittle to *** temperature is taken into account,both the brittle–plastic transformation's depth limit and the lithological transformation of gypsum rocks become shallower,and the evolution of gypsum rocks under variable temperature and pressure conditions is more complicated than that under isothermal *** sealing ability under the temperature-pressure coupling is more in line with the actual geological context when the application results of the Well#ZS5 are *** provides a theoretical basis for precisely determining the process of hydrocarbon accumulation and explains why the early hydrocarbon were not well preserved.

关键词： temperature-pressure coupling gypsum caprocks brittle-plastic evolution sealing capacity Tarim Basin

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An artificial intelligence diabetes management architecture based on 5G

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Digital Communications and Networks 2024年第1期10卷 75-82页

作者： Ruochen Huang Wei Feng shan Lu Tao shan Changwei Zhang Yun liu Department of Geriatrics The First Affiliated Hospital of Nanjing Medical UniversityNanjing210096China Department of Information The First Afliated Hospital of Nanjing Medical UniversityNanjing210096China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing211166China Department of Outpatient The First Affiliated Hospital of Nanjing Medical UniversityNanjing210096China Jiangsu key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing210003China

Along with the development of 5G network and Internet of Things technologies,there has been an explosion in personalized healthcare *** the 5G and Artificial Intelligence(Al)is introduced into diabetes management architecture,it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of *** this article,we propose a 5G-based Artificial Intelligence Diabetes Management architecture(AIDM),which can help physicians and patients to manage both acute complications and chronic *** AIDM contains five layers:the sensing layer,the transmission layer,the storage layer,the computing layer,and the application *** build a test bed for the transmission and application ***,we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission *** application layer,we build a prediction model using a deep forest *** on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

关键词： Diabetes 5G Artificial intelligence Deep forest Smart hospital ward

Proposing a machine learning approach to analyze and predict basic high-temperature properties of iron ore fines and its factors

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Journal of Iron and Steel Research(International) 2024年第5期31卷 1082-1094页

作者： Qing-ke Sun Yao-zu Wang Jian-liang Zhang Zheng-jian liu Le-le Niu Chang-dong shan Yun-fei Ma Institute of Artificial Intelligence University of Science and Technology BeijingBeijing100083China School of Intelligence Science and Technology University of Science and Technology BeijingBeijing100083China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

The basic high-temperature properties of iron ore play a crucial role in optimizing sintering and ore blending,but the testing process for these properties is complex and has significant lag time,which cannot meet the actual needs of ore blending.A prediction model for the basic high-temperature properties of iron ore fines was thus proposed based on a combination of machine learning algorithms and genetic ***,the prediction accuracy of different machine learning models for the basic high-temperature properties of iron ore fines was ***,a random forest model optimized by genetic algorithms was built,further improving the prediction accuracy of the *** test results show that the random forest model optimized by genetic algorithms has the highest prediction accuracy for the lowest assimilation temperature and liquid phase fluidity of iron ore,with a determination coefficient of 0.903 for the lowest assimilation temperature and 0.927 for the liquid phase fluidity after *** trained model meets the fluctuation requirements of on-site testing and has been successfully applied to actual production on site.

关键词： Iron ore Basic high-temperature property Machine learning Random forest Genetic algorithm

Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： ke Li Shunyi Zhao Biao Huang Fei liu key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally *** paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear *** high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense *** that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state ***,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing *** results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： filtering estimation error

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Bi2S3 nanofiber bunch for highly efficient CO2 electroreduction to formate at low overpotential

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Rare Metals 2024年第7期43卷 3391-3399页

作者： Li Wang Wen-ke Gui shan Jiang Liang Wang Jian-Ping Yang State key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua University Centre for Catalysis and Clean Energy Griffith UniversityGold Coast Campus

Electrochemical conversion of CO2into valuable chemicals represents a promising strategy to alleviate the environmental issues caused by excessive CO2levels in the *** this work,Bi2S3with different morphologies have b... 详细信息

关键词： Carbon dioxide

Experimental investigation of engineered geopolymer composite for structural strengthening against blast loads

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Defence Technology（防务技术） 2024年第2期32卷 496-509页

作者： shan liu Chunyuan liu Yifei Hao Yi Zhang Li Chen Zhan Li key Laboratory of Coast Civil Structure Safety of Ministry of Education Tianjin UniversityTianjin 300072China Tianjin key Laboratory of Prefabricated Buildings and Intelligent Construction Hebei University of TechnologyTianjin 300400China Institute of Defense Engineering AMSPLABeijing 100850China Engineering Research Center of Safety and Protection of Explosion&Impact of Ministry of Education Southeast UniversityNanjing 211189JiangsuChina State key Laboratory of Disaster Prevention&Mitigation of Explosion&Impact Army Engineering University of the PLANanjing 210007JiangsuChina

The recent increase in blast/bombing incidents all over the world has pushed the development of effective strengthening approaches to enhance the blast resistance of existing civil *** geopolymer composite(EGC)is a promising material featured by eco-friendly,fast-setting and strain-hardening characteristics for emergent strengthening and ***,the fiber optimization for preparing EGC and its protective effect on structural elements under blast scenarios are *** this study,laboratory tests were firstly conducted to evaluate the effects of fiber types on the properties of EGC in terms of workability,dry shrinkage,and mechanical properties in compression,tension and *** experimental results showed that EGC containing PE fiber exhibited suitable workability,acceptable dry shrinkage and superior mechanical properties compared with other types of *** that,a series of field tests were carried out to evaluate the effectiveness of EGC retrofitting layer on the enhancement of blast performance of typical *** tests include autoclaved aerated concrete(AAC)masonry walls subjected to vented gas explosion,reinforced AAC panels subjected to TNT explosion and plain concrete slabs subjected to contact *** was found that EGC could effectively enhance the blast resistance of structural elements in different *** AAC masonry walls and panels,with the existence of EGC,the integrity of specimens could be maintained,and their deflections and damage were significantly *** plain concrete slabs,the EGC overlay could reduce the diameter and depth of the crater and spallation of specimens.

关键词： Engineered geopolymer composites Fiber optimization Strengthening material Blast resistance Masonry wall Reinforced AAC panel Plain concrete slab

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Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

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Computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang Yuan Xiangwei liu ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral *** present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process ***,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data ***,the first layer BERT network learns the correlations between different category attribute ***,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted ***,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual ***,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

Optimization of Fixture Number in Large Thin-Walled Parts Assembly Based on IPSO

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 213-227页

作者： Changhui liu Jing Wang Ying Zheng ke Jin Jianbo Yu Jianfeng liu School of Mechanical Engineering Tongji UniversityShanghai 201804China shanghai Jiaotong University Shanghai 200240China shanghai Waigaoqiao Shipbuilding Co. Ltd.Shanghai 200137China

There are lots of researches on fixture layout optimization for large thin-walled *** researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of ***,how to determine the number of fixtures is *** most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra ***,this paper constructs an optimization model to minimize the number of *** constraints are set in the optimization model to ensure that the part deformation is within the surface profile *** addition,the assembly gap between two parts is also *** conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia *** the algorithm,particles are encoded according to the fixture *** dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization ***,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality *** research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.

关键词： Assembly quality Large thin-walled parts Fixture layout PSO FEM