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Journal of Wuhan University of Technology(Materials Science) 2020年第1期35卷 87-98页

作者：祁渊龚俊 cao wenhan 王宏刚 Mechanical and Electrical Engineering College Lanzhou University of TechnologyLanzhou 730050China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of SciencesLanzhou 730000China

Nano-ZrO2 and PEEK particles were synergistically filled in unfilled PTFE to improve the wear resistance and maintain a relatively low friction coefficient,and the materials were studied using a reciprocating sliding friction and wear tester.In the friction tests,the evolution of various tribological characteristics in both the contact interfaces and debris was observed,and the wear mechanism of the PTFE composites was investigated.The results showed that the wear rate of the PTFE composites synergistically filled with nano-ZrO2 and PEEK was lower and its friction coefficient was slightly higher than that of the unfilled PTFE;the uniformity and continuity of the transfer film generated by the composite with nano-ZrO2 and PEEK were the best,and the particle size of the debris was minimal in comparison to that in other sample systems.

关键词： PTFE nano-ZrO2 tribology transfer film

多策略改进的NGO算法在大坝参数反演中的应用

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水力发电 2024年第5期50卷 101-109页

作者：曹文翰马琳郝小鸟河海大学水利水电学院江苏南京210024 杨凌职业技术学院陕西咸阳712100 新昌县水利水电局浙江绍兴312500

为解决混凝土坝参数优化反演存在的问题,包括寻优性能不佳、精度不足和效率低下等,提出了一种基于多策略改进北方苍鹰算法(MSNGO)的混凝土坝参数优化反演策略。首先,采取多个策略改进北方苍鹰算法,以提高原始算法的寻优能力。接着,结合... 详细信息

为解决混凝土坝参数优化反演存在的问题,包括寻优性能不佳、精度不足和效率低下等,提出了一种基于多策略改进北方苍鹰算法(MSNGO)的混凝土坝参数优化反演策略。首先,采取多个策略改进北方苍鹰算法,以提高原始算法的寻优能力。接着,结合有限元正分析,构建计算与实测值之间合适的目标函数,利用MSNGO构建智能优化反演模型,并通过并行策略提高反演效率,搜索得到参数反演最优值。通过两个算例对该方法进行验证,并与基准优化算法比较计算结果。结果表明,MSNGO反演策略比其他优化算法收敛速度快、且能跳出局部极值使反演参数结果更为准确,测点计算值与实测值有良好的吻合度,表明该智能优化方法可在混凝土坝参数反演的实际问题中进行应用。

关键词：多策略改进北方苍鹰优化算法位移统计模型参数反演弹性模量混凝土坝

Approximate Optimal Filter Design for Vehicle System through Actor‑Critic Reinforcement Learning

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Automotive Innovation 2022年第4期5卷 415-426页

作者： Yuming Yin Shengbo Eben Li Kaiming Tang wenhan cao Wei Wu Hongbo Li School of Mechanical Engineering Zhejiang University of TechnologyHangzhou 310023China School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Beijing Geekplus Tech.Co. LtdBeijingChina

Precise state and parameter estimations are essential for identification,analysis and control of vehicle engineering problems,especially under significant model and measurement uncertainties.The widely used filtering/estimation algorithms,such as Kalman series like Kalman filter,extended Kalman filter,unscented Kalman filter,and particle filter,generally aim to approach the true state/parameter distribution via iteratively updating the filter gain at each time step.However,the optimal-ity of these filters would be deteriorated by unrealistic initial condition or significant model error.Alternatively,this paper proposes to approximate the optimal filter gain by considering the effect factors within infinite time horizon,on the basis of estimation-control duality.The proposed approximate optimal filter(AOF)problem is designed and subsequently solved by actor-critic reinforcement learning(RL)method.The AOF design transforms the traditional optimal filtering problem with the minimum expected mean square error into an optimal control problem with the minimum accumulated estimation error,in which the estimation error is used as the surrogate system state and the infinite-horizon filter gain is the control input.The estimation-control duality is proved to hold when certain conditions about initial vehicle state distributions and policy structure are maintained.In order to evaluate of the effectiveness of AOF,a vehicle state estimation problem is then demonstrated and compared with the steady-state Kalman filter.The results showed that the obtained filter policy via RL with different discount factors can converge to theoretical optimal gain with an error within 5%,and the average estimation errors of vehicle slip angle and yaw rate are less than 1.5×10–4.

关键词： Vehicle state estimation Kalman filter Estimation-control duality Reinforcement learning

GOPS:A general optimal control problem solver for autonomous driving and industrial control applications

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Communications in Transportation Research 2023年第1期3卷 92-106页

作者： Wenxuan Wang Yuhang Zhang Jiaxin Gao Yuxuan Jiang Yujie Yang Zhilong Zheng Wenjun Zou Jie Li Congsheng Zhang wenhan cao Genjin Xie Jingliang Duan Shengbo Eben Li School of Vehicle and Mobility Tsinghua UniversityBeijing100084China

Solving optimal control problems serves as the basic demand of industrial control tasks.Existing methods like model predictive control often suffer from heavy online computational burdens.Reinforcement learning has shown promise in computer and board games but has yet to be widely adopted in industrial applications due to a lack of accessible,high-accuracy solvers.Current Reinforcement learning(RL)solvers are often developed for academic research and require a significant amount of theoretical knowledge and programming skills.Besides,many of them only support Python-based environments and limit to model-free algorithms.To address this gap,this paper develops General Optimal control Problems Solver(GOPS),an easy-to-use RL solver package that aims to build real-time and high-performance controllers in industrial fields.GOPS is built with a highly modular structure that retains a flexible framework for secondary development.Considering the diversity of industrial control tasks,GOPS also includes a conversion tool that allows for the use of Matlab/Simulink to support environment construction,controller design,and performance validation.To handle large-scale problems,GOPS can automatically create various serial and parallel trainers by flexibly combining embedded buffers and samplers.It offers a variety of common approximate functions for policy and value functions,including polynomial,multilayer perceptron,convolutional neural network,etc.Additionally,constrained and robust algorithms for special industrial control systems with state constraints and model uncertainties are also integrated into GOPS.Several examples,including linear quadratic control,inverted double pendulum,vehicle tracking,humanoid robot,obstacle avoidance,and active suspension control,are tested to verify the performances of GOPS.

关键词： Industrial control Reinforcement learning Approximate dynamic programming Optimal control Neural network Benchmark

宋、金、蒙政局变动下的华北武装团体政治抉择研究:以红袄军杨妙真、李璮集团为例

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中国史研究 2023年第1期 134-151页

作者：曹文瀚四川师范大学历史文化与旅游学院

金朝末年,华北政治秩序瓦解,民众为求自保,组成大大小小的武装团体,他们的政治向背对当时宋、金、蒙三方逐鹿中原的成果有莫大的影响力。红袄军是这些武装团体中最反复无常者,研究他们政治抉择的因素,可以增进我们对当时武装团体政治向... 详细信息

金朝末年,华北政治秩序瓦解,民众为求自保,组成大大小小的武装团体,他们的政治向背对当时宋、金、蒙三方逐鹿中原的成果有莫大的影响力。红袄军是这些武装团体中最反复无常者,研究他们政治抉择的因素,可以增进我们对当时武装团体政治向背的认识。杨妙真和李璮是红袄军第三代及第四代首领,李璮起事对元代以至后世历史皆产生深远的影响。除此之外他们集团内部还有无数的各级领导人,大致上可分成山东和涟海两大集团,后者受限于史料,生平事迹多不得而知;前者则能利用地方志史料,大量恢复他们的生平事迹,由此得知李璮集团的组成结构及其对李璮政治抉择的影响。李璮失败后,元朝将罪责限定在李璮、王文统及涟海集团,以此争取山东集团的认同,进而稳定对山东的统治。

关键词：红袄军杨妙真李璮山东

Dysfunction of synaptic endocytic trafficking in Parkinson's disease

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Neural Regeneration Research 2024年第12期19卷 2649-2660页

作者： Xin Yi Ng Mian cao Programme in Neuroscience and Behavioural Disorders Duke-NUS Medical SchoolSingaporeSingapore Department of Physiology National University of SingaporeSingaporeSingapore

Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive.Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease.Notably,several of these genes are linked to the synaptic vesicle recycling process,particularly the clathrinmediated endocytosis pathway.This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease,followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a"dying back"mechanism.Recently,several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized.These models faithfully recapitulate certain Parkinson's disease-like features at the animal,circuit,and cellular levels,and exhibit defects in synaptic membrane trafficking,further supporting the findings from human genetics and clinical studies.In this review,we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins:auxilin(DNAJC6/PARK19)and synaptojanin 1(SYNJ1/PARK20).The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect.Subsequently,we will delve into the involvement of several clathrin-mediated endocytosis-related proteins(GAK,endophilin A1,SAC2/INPP5 F,synaptotagmin-11),identified as Parkinson's disease risk factors through genome-wide association studies,in Parkinson's disease pathogenesis.We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins(alpha-synuclein(PARK1/4),Parkin(PARK2),and LRRK2(PARK8))in synaptic endocytic trafficking.Additionall

关键词： autophagy auxilin/PARK19 clathrin-mediated endocytosis dopamine neurons neurodegeneration nigrostriatal pathway Parkinson's disease synaptic vesicle recycling synaptojanin1/PARK20

Dynamic Setting Method of Assessment Indicators for Power Curves of Renewable Energy Sources Considering Scarcity of Reserve Resources

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 101-114页

作者： Minghao cao Jilai Yu the Department of Electrical Engineering Harbin Institute of TechnologyHarbinChina

With the increasing proportion of renewable energy sources(RESs)in power grid,the reserve resource(RR)scarcity for correcting power deviation of RESs has become a potential issue.Consequently,the power curve of RES needs to be more rigorously assessed.The RR scarcity varies during different time periods,so the values of assessment indicators should be dynamically adjusted.The assessment indicators in this paper include two aspects,i.e.,deviation exemption ratio and penalty price.Firstly,this paper proposes a method for dynamically calculating the supply capacity and RR cost,primarily taking into account the operating status of thermal units,forecast information of RES,and load curve.Secondly,after clarifying the logical relationship between the degree of RR scarcity and the values of assessment indicators,this paper establishes a mapping function between them.Based on this mapping function,a dynamic setting method for assessment indicators is proposed.In the future,RES will generally be equipped with battery energy storage systems(BESSs).Reasonably utilizing BESSs to reduce the power deviation of RESs can increase the expected income of RESs.Therefore,this paper proposes a power curve optimization strategy for RESs considering self-owned BESSs.The case study demonstrates that the dynamic setting method of assessment indicators can increase the revenue of RESs while ensuring that the penalty fees paid by RESs to the grid are sufficient to cover the RR costs.Additionally,the power curve optimization strategy can help RESs further increase income and fully utilize BESSs to reduce power deviation.

关键词： Renewable energy battery energy storage system(BESS) power curve assessment reserve service parameter setting

Zeros of Complete Symmetric Polynomials over Finite Fields

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Journal of Systems Science & Complexity 2024年第4期37卷 1772-1788页

作者： cao Wei School of Mathematics and Statistics Minnan Normal University

Wan and Zhang(2021) obtained a nontrivial lower bound for the number of zeros of complete symmetric polynomials over finite fields, and proposed a problem whether their bound can be improved. In this paper, the author improves Wan-Zhang's bound from three aspects. The proposed results are based on the estimates related to the number of certain permutations and the value sets of non-permutation polynomials associated to the complete symmetric polynomial. And the author believes that there are still possibilities to improve the bounds and hence Wan-Zhang's bound.

关键词： Complete symmetric polynomial finite field permutation polynomial value set

Bioinspired Closed-loop CPG-based Control of a Robotic Manta for Autonomous Swimming

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Journal of Bionic Engineering 2024年第1期21卷 177-191页

作者： Yiwei Hao Yonghui cao Yingzhuo cao Xiong Mo Qiaogao Huang Lei Gong Guang Pan Yong cao School of Marine Science and Technology Northwestern Polytechnical UniversityXi'an 710072China Unmanned Vehicle Innovation Center Ningbo Institute of NPUNingbo 315103China Key Laboratory of Unmanned Underwater Vehicle Technology of Ministry of Industry and Information Technology Xi'an 710072China

Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish to swim autonomously in a confined area as a real fish.Here,we develop an untethered robotic manta as an experimental platform,which consists of two flexible pectoral fins and a tail fin,with three infrared sensors installed on the front,left,and right sides of the head to sense the surrounding obstacles.To generate multiple swimming modes of the robotic manta and online switching of different modes,we design a closed-loop Central Pattern Generator(CPG)controller based on distance information and use a combination of phase difference and amplitude of the CPG model to achieve stable and rapid adjustment of yaw angle.To verify the autonomous swimming ability of the robotic manta in complex scenes,we design an experimental scenario with a concave obstacle.The experimental results show that the robotic manta can achieve forward swimming,backward swimming,in situ turning within the concave obstacle,and finally exit from the area safely while relying on the perception of external obstacles,which can provide insight into the autonomous exploration of complex scenes by the biomimetic robotic fish.Finally,the swimming ability of the robotic manta is verified by field tests.

关键词： Biomimetic robotic manta Central Pattern Generator Closed-loop control Backward swimming

Impacts of pancreatic exocrine insufficiency on gut microbiota

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2024年第4期25卷 271-279页

作者： Yulin GUO Feng cao Fei LI Department of General Surgery Xuanwu Hospital of Capital Medical UniversityBeijing 100053China Acute Pancreatitis Clinical Center of Capital Medical University Beijing 100053China

Pancreatic exocrine insufficiency(PEI)can be induced by various kinds of diseases,including chronic pancreatitis,acute pancreatitis,and post-pancreatectomy.The main pathogenetic mechanism of PEI involves the decline of trypsin synthesis,disorder of pancreatic fluid flow,and imbalance of secretion feedback.Animal studies have shown that PEI could induce gut bacterial overgrowth and dysbiosis,with the abundance of Lactobacillus and Bifidobacterium increasing the most,which could be partially reversed by pancreatic enzyme replacement therapy.Clinical studies have also confirmed the association between PEI and the dysbiosis of gut microbiota.Pancreatic exocrine secretions and changes in duodenal p H as well as bile salt malabsorption brought about by PEI may affect and shape the abundance and composition of gut microbiota.In turn,the gut microbiota may impact the pancreatic exocrine acinus through potential bidirectional crosstalk.Going forward,more and higher-quality studies are needed that focus on the mechanism underlying the impact of PEI on the gut microbiota.

关键词： Pancreatic exocrine insufficiency Gut microbiota Gut microbiome Pancreatic enzyme replacement therapy