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物理学报 2005年第3期54卷 1015-1017页

作者：楼智美绍兴文理学院物理系绍兴312000

把mei对称性方法用于电磁场中带电粒子的运动 ,从二维运动电荷的mei对称性出发 ,运用比较系数法 ,得到与mei对称性相应的生成元的普遍表达式及电磁场所满足的偏微分方程组 .对一特例进行了讨论 .

关键词： mei对称性运动电荷比较系数法偏微分方程组生成元二维电磁场特例带电粒子表达式

天才制造中国家庭如何运用mei教育法则第1版

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有猫的日子就对了! 专访设计师Lonely mei

2001年

作者： mei课题组译编

本书着眼于二十一世纪的社会需要，从把孩子培养成在未来社会具有生存和自我发展能力的人的角度出发，以培养孩子“成才”为己任，参考大量资料文献，总结出非智力因素主要以德、力、变、理等和智力因素的培养内容、途径及方法。

ISBN: (纸本)7800843726

关键词：儿童教育学科:家庭教育家庭教育

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宠物世界（猫迷） 2013年第5期 100-102页

作者： Lonely mei 鱼鱼

Lonely mei每天回家推开门,一眼就可以瞧见在门口的喵星人朋友,打开电脑开始设计工作的时候,它们在腿上陪伴……简单的事物会更容易诠释对设计的表达,下面的采访就让我们先从了解她的喵星人朋友开始吧。

关键词： Lonely mei 动物保护人说会说话对你说回过头我自己给你创作作品水盆

mei symmetry and mei conserved quantity of the Appell equation in a dynamical system of relative motion with non-Chetaev nonholonomic constraints

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Chinese Physics B 2012年第5期21卷 6-10页

作者：王肖肖孙现亭张美玲韩月林贾利群 School of Science Jiangnan University School of Electric and Information Engineering Pingdingshan University

The mei symmetry and the mei conserved quantity of Appell equations in a dynamical system of relative motion with non-Chetaev nonholonomic constraints are *** differential equations of motion of the Appell equation for the system,the definition and the criterion of the mei symmetry,and the expression of the mei conserved quantity deduced directly from the mei symmetry for the system are *** example is given to illustrate the application of the results.

关键词： non-Chetaev nonholonomic constrained system dynamics of relative motion Appell equation mei conserved quantity

Preparation of Low Ratio Magnesium Ccement by Acid Leaching Treatment of Boron Mud

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 120-129页

作者： YANG mei ZHANG Mingzhe CHEN Hao School of Materials Science and Engineering Shenyang Jianzhu UniversityShenyang 110168China School of Physical Science and Technology Shenyang Normal UniversityShenyang 110168China

The effects of liquid-solid ratio and reaction time on the leaching rate of magnesium at room temperature were investigated,as well as the effects of the molar ratio of MgO/MgCl_(2),the amount of water added,and the amount of acid-impregnated slag dosed on the compressive strength and water resistance of *** results showed that the magnesium element in the boron mud could be maximally leached under the conditions of 1:1 concentration of hydrochloric acid at room temperature,liquid-solid ratio of 2.5 mL·g^(-1),and reaction time of 5 h,and the main products were amorphous SiO_(2) as well as a small amount of magnesium olivine which had not been completely *** LR-MOC prepared using the acid-soaked mixture could reach a softening coefficient of 0.85 for 28 d of water immersion when the molar ratio of MgO/MgCl_(2) was 2.2,the amount of water added was 0 g,and the acid-soaked slag dosing was 40 wt%,which also led to an appreciable late-strength,with an increase of 19.4%in compressive strength at 28 d compared to that at 7 *** previous studies,LR-MOC prepared in this way has a final strength phase that is not the more easily hydrolysed 3-phase but the lath-like *** this phenomenon,we analyzed the mechanism and found that,during the acid leaching process,a part of amorphous SiO_(2) dissolved in the acid leaching solution formed a silica sol,in which Mg^(2+)played a bridging role to make the silica sol more *** the addition and hydrolysis of MgO,the silica sol gel coagulation slows down,providing a capping layer to inhibit the hydrolysis of the 5-phase crystals and providing some strength after *** amorphous SiO_(2) in the other part of the acid-impregnated slag generated M-S-H gel with Mg^(2+)and OH-,which synergised with the dense structure composed of interlocking crystals to improve the water resistance of LR-MOC.

关键词： boron mud magnesium chloride-oxygen cement acid immersion water resistance silica sol

相对运动动力学系统Nielsen方程mei对称性导致的一种新型守恒量

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河南师范大学学报（自然科学版） 2012年第3期40卷 48-51页

作者：贾利群解银丽韩月林张美玲王肖肖孙现亭江南大学理学院江苏无锡214122 平顶山学院电气信息工程学院河南平顶山467002

研究相对运动动力学系统Nielsen方程的mei对称性导致的一种新型守恒量.在群的无限小变换下,给出相对运动动力学系统Nielsen方程mei对称性的定义和判据;得到相对运动动力学系统Nielsen方程mei对称性导致的新型结构方程和新型守恒量的表达式.

关键词：相对运动动力学系统 Nielsen方程 mei对称性,新型守恒量

Nielsen系统mei对称性的新型守恒量

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河南教育学院学报（自然科学版） 2011年第3期20卷 19-21页

作者：张美玲王肖肖贾利群田燕宁江南大学理学院江苏无锡214122

研究Nielsen系统mei对称性的新型守恒量.在群的无限小变换下,由Nielsen系统mei对称性的定义和判据,得到Nielsen系统mei对称性的一种新结构方程和一种新型守恒量.

关键词： Nielsen系统 mei对称性结构方程新型守恒量

Microstructural evolution during the progressive transformation-induced plasticity effect in a Fe-0.1C-5Mnmedium manganese steel

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 369-379页

作者： mei Zhang Wenhao Li Yangfei Chen Yang Jiang Xiaofei Guo Han Dong School of Materials Science and Engineering Shanghai UniversityShanghai 200444China State Key Laboratory of Advanced Special Steel Shanghai UniversityShanghai 200444China

The microstructural evolution of a cold-rolled and intercritical annealed medium-Mn steel(Fe-0.10C-5Mn)was investigated during uniaxial tensile ***-situ observations under scanning electron microscopy,transmission electron microscopy,and X-ray diffraction analysis were conducted to characterize the progressive transformation-induced plasticity process and associated fracture initiation *** findings were discussed with the local strain measurements via digital image *** results indicated that Lüders band formation in the steel was limited to 1.5%strain,which was mainly due to the early-stage martensitic phase transformation of a very small amount of the less stable large-sized retained austenite(RA),which led to localized stress concentrations and strain hardening and further retardation of *** small-sized RA exhibited high stability and progressively transformed into martensite and contributed to a stably extended Portevin-Le Chatelier *** volume fraction of RA gradually decreased from 26.8%to 8.2%prior to *** the late deformation stage,fracture initiation primarily occurred at the austenite/martensite and ferrite/martensite interfaces and the ferrite phase.

关键词： medium-Mn steel retained austenite progressive transformation-induced plasticity effect local strain fracture initiation

MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

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Computers, Materials & Continua 2025年第1期82卷 485-498页

作者： Jun Wang Mingjie Wang Zijie Li Ken Chen Jiatian mei Shu Zhang Key Laboratory of Education Informatization for Nationalities Ministry of EducationYunnan Normal UniversityKunming650000China Yunnan Key Laboratory of Smart Education Yunnan Normal UniversityKunming650000China

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant *** tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional *** knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential ***,these models may neglect crucial short-term dynamics and other relevant *** paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)*** proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature *** architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key *** evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge *** results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

关键词： Knowledge tracing multilayer perceptron channel mixer sequence mixer

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Contrastive Learning