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On the interaction phenomena to the nonlinear generalized Hietarinta-type equation

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Journal of Ocean Engineering and Science 2024年第1期9卷 89-97页

作者： Usman Younas T.A.Sulaiman jingli ren A.Yusuf State Key Laboratory of Power Grid Environmental Protection/Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Faculty of Science Federal University DutseJigawaNigeria Department of Computer Engineering Biruni University IstanbulTurkey

In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and various test function *** Hirota method is a widely used and robust mathematical tool for finding soliton solutions of nonlinear partial differential equa-tions(NLPDEs)in a variety of disciplines like mathematical physics,nonlinear dynamics,oceanography,engineering sciences,and others requires bilinearization of nonlinear *** different wave structures in the forms of new breather,lump-periodic,rogue waves,and two-wave solutions are *** addi-tion,the physical behavior of the acquired solutions is illustrated in three-dimensional,two-dimensional,density,and contour profiles by the assistance of suitable *** on the obtained results,we can assert that the employed methodology is straightforward,dynamic,highly efficient,and will serve as a valuable tool for discussing complex issues in a diversity of domains specifically ocean and coastal *** have also made an important first step in understanding the structure and physical be-havior of complex structures with our findings *** believe this research is timely and relevant to a wide range of engineering *** results obtained are useful for comprehending the fundamental scenarios of nonlinear sciences.

关键词： Hirota’s bilinear method Lump-periodic solutions Breather waves Rouge waves Multi-waves

Sparse identification-assisted exploration of the atomic-scale deformation mechanism in multiphase CoCrFeNi high-entropy alloys

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Science China(Technological Sciences) 2024年第4期67卷 1124-1132页

作者： XIAO Lu GUO XiaoXiang SUN YuTong WANG Gang LONG WeiMin LIAW Peter K. ren jingli School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Institute of Materials Shanghai UniversityShanghai 200444China SKL of Advanced Brazing Metals&Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996USA

This study investigated the atomic-scale deformation mechanism of multiphase CoCrFeNi high-entropy alloys(HEAs)at liquid helium,liquid nitrogen,and room temperatures.A million-atom multiphase HEA was prepared using molecular dynamics simulation involving melt and quench *** HEA exhibited high-density dislocations and some twins,consistent with experimental *** analysis revealed an inconsistent evolution of the microstructure under tensile *** particular,the elastic and initial plastic stages exhibited an increase in the disordered structure at the expense of the face-centered cubic and hexagonal close-packed structures,followed by a subsequent transformation involving multiple structural ***,through sparse identification,a model depicting microstructural evolution during tension was extracted for the CoCrFeNi HEA at three typical temperatures and three tensile *** model highlighted the importance of the body-centered cubic structure in the evolutionary process.

关键词： high-entropy alloy data-driven method microstructure evolution multiphase structure molecular dynamics simulation

Design of a prediction system based on the dynamical feed-forward neural network

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Science China(Information Sciences) 2023年第1期66卷 43-59页

作者： Xiaoxiang GUO Weimin HAN jingli ren Henan Academy of Big Data Zhengzhou University Department of Mathematics University of Iowa

Analysis and prediction of time series play a significant role in scientific fields of meteorology,epidemiology, and economy. Efficient and accurate prediction of signals can give an early detection of abnormal variations, provide guidance on preparing a timely response and avoid presumably adverse *** this paper, a prediction system is designed based on the dynamical feed-forward neural network. The trajectory information in the reconstructed phase space, which is topologically equivalent to the dynamical evolution of the system, is applied to establish the prediction model. Moreover, an integer constrained particle swarm optimization algorithm is employed to select the optimal time delay, which is the parameter of our system. Simulation results for applications on the Lorenz system, stock market index, and influenza data indicate that our proposed method can produce efficient and reliable predictions.

关键词： prediction system phase space reconstruction topological equivalence dynamical feed-forward neural network integer constrained particle swarm optimization algorithm

Phase prediction for high-entropy alloys using generative adversarial network and active learning based on small datasets

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Science China(Technological Sciences) 2023年第12期66卷 3615-3627页

作者： CHEN Cun ZHOU HengRu LONG WeiMin WANG Gang ren jingli Henan Academy of Big Data School of Mathematics and StatisticsZhengzhou UniversityZhengzhou 450001China State Key Laboratory of Advanced Brazing Filler Metals and Technology Zhengzhou Research Institute of Mechanical EngineeringZhengzhou 450001China Institute of Materials Shanghai UniversityShanghai 200444China

In this paper,a new machine learning(ML)model combining conditional generative adversarial networks(CGANs)and active learning(AL)is proposed to predict the body-centered cubic(BCC)phase,face-centered cubic(FCC)phase,and BCC+FCC phase of high-entropy alloys(HEAs).Considering the lack of data,CGANs are introduced for data augmentation,and AL can achieve high prediction accuracy under a small sample size owing to its special sample selection ***,we propose an ML framework combining CGAN and AL to predict the phase of *** arithmetic optimization algorithm(AOA)is introduced to improve the artificial neural network(ANN).AOA can overcome the problem of falling into the locally optimal solution for the ANN and reduce the number of training *** AOA-optimized ANN model trained by the AL sample selection strategy achieved high prediction accuracy on the test *** improve the performance and interpretability of the model,domain knowledge is incorporated into the feature ***,considering that the proposed method can alleviate the problem caused by the shortage of experimental data,it can be applied to predictions based on small datasets in other fields.

关键词： high-entropy alloys phase prediction machine learning conditional generative adversarial networks active learning

Extracting governing system for the plastic deformation of metallic glasses using machine learning

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Science China(Physics,Mechanics & Astronomy) 2022年第6期65卷 76-87页

作者： Liping Yu Xiaoxiang Guo Gang Wang Baoan Sun Dongxue Han Cun Chen jingli ren Weihua Wang College of Science Henan University of TechnologyZhengzhou 450001China Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450052China Institute of Materials Shanghai UniversityShanghai 200444China Institute of Physics Chinese Academy of SciencesBeijing 100190China

This paper shows hidden information from the plastic deformation of metallic glasses using machine ***_(62)Nb_(38)(at.%)metallic glass(MG)film and Zr_(64.13)Cu_(15.75)Al_(10)Ni_(10.12)(at.%)BMG,as two model materials,are considered for nano-scratching and compression experiment,*** interconnectedness among variables is probed using correlation *** evolvement mechanism and governing system of plastic deformation are explored by combining dynamical neural networks and sparse *** governing system has the same basis function for different experiments,and the coefficient error is≤0.14%under repeated experiments,revealing the intrinsic quality in metallic ***,the governing system is conducted based on the preceding result to predict the deformation *** shows that the prediction agrees well with the real value for the deformation process.

关键词： metallic glasses sparse identification dynamical neural networks correlation analysis

基于OBE与PBL耦合的混合式实验教学实践

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实验室科学 2024年第1期27卷 107-111,115页

作者：郑彬刘春晓任静丽李建忠黄超赣南师范大学地理与环境工程学院江西赣州341000 赣南师范大学新闻与传播学院江西赣州341000 山东省淄博市张店区铝城第一中学山东淄博255022

面向传统混合式教学存在的“痛点”问题,以“遥感概论”实验课程为例,引入“学生中心、产出导向、持续改进”的高校师范类专业认证理念,耦合项目驱动与产出导向,深度融入课程思政,构建“以学生为中心,以育人成效为导向”的混合式教学模... 详细信息

面向传统混合式教学存在的“痛点”问题,以“遥感概论”实验课程为例,引入“学生中心、产出导向、持续改进”的高校师范类专业认证理念,耦合项目驱动与产出导向,深度融入课程思政,构建“以学生为中心,以育人成效为导向”的混合式教学模式。实践证明,基于OBE与PBL耦合的混合式教学模式能够有效衔接线上与线下学习,激发学生学习自主性与内动力,深化实操能力,加深情感体验。“遥感概论”课程现已建设成为江西省高校线上、线下混合式一流本科课程。

关键词：产出导向项目驱动混合式教学遥感概论课程思政

FURTHER RESULTS ON LIMITATIONS OF SAMPLED-DATA FEEDBACK

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Journal of Systems Science & Complexity 2014年第5期27卷 817-835页

作者： ren jingli CHENG Zhibo GUO Lei School of Mathematics and Statistics Zhengzhou University School of Mathematics and Information Science Henan Polytechnic University Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences

To control continuous-time uncertain dynamical systems with sampled data-feedback is prevalent today,but the sampling rate is usually not allowed to be arbitrarily fast due to various physical and/or computational *** this paper,the authors examine the limitations of sampled-data feedback control for a class of uncertain systems in continuous-time,with sampling rate not necessary fast enough and with the unknown system structure confined to a set of functions with both linear and nonlinear *** limitations of the sampled-data feedback control for the uncertain systems are established quantitatively,which extends the existing related results in the literature.

关键词：采样数据反馈控制不确定系统连续时间动力系统未知系统采样率非线性

Microfluidics-assisted optimization of highly adhesive haemostatic hydrogel coating for arterial puncture

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Bioactive Materials 2022年第6期7卷 133-142页

作者： Xingjie Yin jingli ren Wei Lan Yu Chen Mengping Ouyang Hua Su Lianbin Zhang Jintao Zhu Chun Zhang Department of Nephrology Union HospitalTongji Medical CollegeHuazhong University of Science and Technology Wuhan430022China Key Lab of Material Chemistry for Energy Conversion and Storage of Ministry of Education School of Chemistry and Chemical EngineeringHuazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Coal Combustion and School of Energy and Power Engineering Huazhong University of Science and TechnologyWuhan430074China

Although common in clinical practice,bleeding after tissue puncture may cause serious outcomes,especially in arterial ***,gelatin-tannic acid composite hydrogels with varying compositions are prepared,and their adhesive properties are further optimized in microfluidic channel-based simulated vessels for haemostasis in arterial *** is revealed that the composite hydrogels on the syringe needles used for arterial puncture should possess underwater adhesion higher than 4.9 kPa and mechanical strength higher than 86.0 *** needles coated with the gelatin-tannic acid composite hydrogel completely prevent blood loss after both vein and arterial puncture in different animal *** study holds great significance for the preparation of haemostatic needles for vessel puncture,and gelatin-tannic acid hydrogel coated needles may help to prevent complications associated with arterial puncture.

关键词： Gelatin hydrogel Underwater adhesive Microfluidics Haemostatic coating Vessel puncture

课程思政融入《遥感概论》课程教学的探索与实践

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地理空间信息 2024年第2期22卷 128-132页

作者：郑彬陈淑茵任静丽李建忠刘春晓赣南师范大学地理与环境工程学院江西赣州341000 赣南师范大学新闻与传播学院江西赣州341000

课程思政在遥感概论课程中的教学案例较为少见,且在教学策略、方法与评价、反馈等方面存在一定的不足。针对《遥感概论》教学设计存在的问题,开展了教学改革的探索与实践:(1)结合课程思政理念与课程目标,提出了遥感概论课程思政教学设... 详细信息

课程思政在遥感概论课程中的教学案例较为少见,且在教学策略、方法与评价、反馈等方面存在一定的不足。针对《遥感概论》教学设计存在的问题,开展了教学改革的探索与实践:(1)结合课程思政理念与课程目标,提出了遥感概论课程思政教学设计方案,挖掘了适宜课程思政教学的内容与案例;(2)搭建了线上线下混合式教学平台,并构建了遥感概论课程思政教学评价体系。教学改革实践证明:融入课程思政后的遥感概论课程教学满意度在90%以上,学生通过课程既提高了自主学习能力和专业素养,又获得了极大的学习满足感和获得感;(3)有近95%的学生能够通过课程项目训练,亲身感受到家乡和祖国的变化,深化了学生的家国情怀。

关键词：课程思政遥感概论教学改革家国情怀