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Journal of Advanced Ceramics 2020年第3期9卷 292-302页

作者： Hongxian WANG peiyao zhao Lingling CHEN Longtu LI Xiaohui WANG State Key Lab of New Ceramic and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

Multilayer ceramic capacitors(MLCCs)for energy storage applications require a large discharge energy density and high discharge/charge efficiency under high electric ***,0.87BaTiO3--0.13Bi(Zn23(Nbog8sTao.1s)u3)O3(BTBZNT)MLCCs with double active dielectric layers were fabricated,and the effects of inner electrode and sintering method on the energy storage properties of BTBZNT MLCCs were *** using the pure Pt as inner electrode instead of Ago.6Pdo4 aloys,an alternating current(AC)breakdown strength(BDS)enhancement from 1047 to 1500 kV/cm was *** investigating the leakage current behavior of BTBZNT MLCCs,the Pt inner electrode and two-step sintering method(TSS)were confirmed to enhance the Schottky barrier and minimize the leakage current *** relatively high permitivity,dielectric sublinearity,and ultra-high BDS,the Pt TSS BTBZNT MLCCs exhibited a surprisingly discharge energy density(Udis)of 14.08 J/***,under an operating electric field of 400 kV/cm,the MLCCs also exhibited thermal stability with Udis variation<±8%over a wide temperature (t) range from-50 to 175℃ and cycling reliability with Uais reduction<0.3%after 3000 charge-discharge *** remarkable performances make Pt TSS BTBZNT MLCCs promising for energy storage applications.

关键词： BaTiO multilayer ceramic capacitor(MLCC) leakage current energy storage

Achieving Safe Deep Reinforcement Learning via Environment Comprehension Mechanism

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Chinese Journal of Electronics 2021年第6期30卷 1049-1058页

作者： PENG Pai ZHU Fei LIU Quan zhao peiyao WU Wen School of Computer Science and Technology Soochow University

Deep reinforcement learning(DRL), which combines deep learning with reinforcement learning, has achieved great success recently. In some cases, however,during the learning process agents may reach states that are worthless and dangerous where the task fails. To address the problem, we propose an algorithm, referred as Environment comprehension mechanism(ECM) for deep reinforcement learning to attain safer decisions. ECM perceives hidden dangerous situations by analyzing object and comprehending the environment, such that the agent bypasses inappropriate actions systematically by setting up constraints dynamically according to states. ECM, which calculates the gradient of the states in Markov tuple, sets up boundary conditions and generates a rule to control the direction of the agent to skip unsafe states. ECM is able to be applied to basic deep reinforcement learning algorithms to guide the selection of actions. The experiment results show that the algorithm promoted safety and stability of the control tasks.

关键词： multi-agent systems deep learning (artificial intelligence) Markov tuple agent direction Markov processes basic deep reinforcement learning algorithms environment comprehension mechanism safety boundary conditions ECM

A stable actor-critic algorithm for solving robotic tasks with multiple constraints

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Frontiers of Computer Science 2023年第4期17卷 233-235页

作者： peiyao zhao Fei ZHU Quan LIU Xinghong LING School of Computer Science and Technology Soochow UniversitySuzhou 215006China

1 *** reinforcement learning has achieved great success especially in game[1]and control ***,for real world environments that involve more than one *** example,an autonomous car should consider constraints such as the driving speed,energy efficiency,comfort and safety of the passengers[2,3].To solve the problems,Constrained Markov Decision Process(CMDP)was proposed to model tasks with constraints[4,5].

关键词： constraints Deep tasks

Expanding the Scope of Multivariate Regression Approaches in Cross-Omics Research

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Engineering 2021年第12期7卷 1725-1731页

作者： Xiaoxi Hu Yue Ma Yakun Xu peiyao zhao Jun Wang CAS Key Laboratory of Pathogenic Microbiology and Immunology Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Bloomberg School of Public Health Johns Hopkins UniversityBaltimoreMD 21205USA University of Chinese Academy of Sciences Beijing 100049China Department of Biostatistics University of MichiganAnn ArborMI 48109-2029USA

Recent technological advancements and developments have led to a dramatic increase in the amount of high-dimensional data and thus have increased the demand for proper and efficient multivariate regression *** traditional multivariate approaches such as principal component analysis have been used broadly in various research areas,including investment analysis,image identification,and population genetic structure ***,these common approaches have the limitations of ignoring the correlations between responses and a low variable selection ***,in this article,we introduce the reduced rank regression method and its extensions,sparse reduced rank regression and subspace assisted regression with row sparsity,which hold potential to meet the above demands and thus improve the interpretability of regression *** conducted a simulation study to evaluate their performance and compared them with several other variable selection *** different application scenarios,we also provide selection suggestions based on predictive ability and variable selection ***,to demonstrate the practical value of these methods in the field of microbiome research,we applied our chosen method to real population-level microbiome data,the results of which validated our *** method extensions provide valuable guidelines for future omics research,especially with respect to multivariate regression,and could pave the way for novel discoveries in microbiome and related research fields.

关键词： Multivariate regression methods Reduced rank regression Sparsity Dimensionality reduction Variable selection

Perspectives and challenges for lead-free energy-storage multilayer ceramic capacitors

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Journal of Advanced Ceramics 2021年第6期10卷 1153-1193页

作者： peiyao zhao Ziming CAI Longwen WU Chaoqiong ZHU Longtu LI Xiaohui WANG State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China School of Material Science and Physics China University of Mining and TechnologyXiizhou 221116China College of Electrical Engineering Sichuan UniversityChengdu 610065China

The growing demand for high-power-density electric and electronic systems has encouraged the development of energy-storage capacitors with attributes such as high energy density,high capacitance density,high voltage and frequency,low weight,high-temperature operability,and environmental *** with their electrolytic and film counterparts,energy-storage multilayer ceramic capacitors(MLCCs)stand out for their extremely low equivalent series resistance and equivalent series inductance,high current handling capability,and high-temperature *** characteristics are important for applications including fast-switching third-generation wide-bandgap semiconductors in electric vehicles,5G base stations,clean energy generation,and smart *** have been numerous reports on state-of-the-art MLCC energy-storage ***,lead-free capacitors generally have a low-energy density,and high-energy density capacitors frequently contain lead,which is a key issue that hinders their broad *** this review,we present perspectives and challenges for lead-free energy-storage ***,the energy-storage mechanism and device characterization are introduced;then,dielectric ceramics for energy-storage applications with aspects of composition and structural optimization are *** on state-of-the-art energy-storage MLCCs is discussed after elaboration of the fabrication process and structural design of the *** applications of energy-storage MLCCs are then discussed in terms of advanced pulsed power sources and high-density power converters from a theoretical and technological point of ***,the challenges and future prospects for industrialization of lab-scale lead-free energy-storage MLCCs are discussed.

关键词： multilayer ceramic capacitors(MLCCs) lead-free dielectric ceramics energy storage high power density

Improving deep reinforcement learning by safety guarding model via hazardous experience planning

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Frontiers of Computer Science 2022年第4期16卷 223-225页

作者： Pai Peng Fei Zhu Xinghong Ling peiyao zhao Quan Liu School of Computer Science and Technology Soochow UniversitySuzhou215006China

1Introduction and main contributions Deep reinforcement learning that considers the advantages of both deep learning and reinforcement learning has achieved success in many fields[1],However,during the learning process,a possibility still exists that the agent fails in the task because of falling into hazardous states due to taking improper actions.

关键词： guard learning has

Optimizing the grain size and grain boundary morphology of (K,Na) NbO_(3)-based ceramics: Paving the way for ultrahigh energy storage capacitors

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Journal of Materiomics 2021年第4期7卷 780-789页

作者： Xiaozhi Wang Yu Huan peiyao zhao Xiaoming Liu Tao Wei Qiwen Zhang Xiaohui Wang School of Material Science and Engineering University of JinanJinan250022China State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing100084China Key Laboratory of Electromagnetic Processing of Materials(Ministry of Education) Northeastern UniversityShenyang110819China The Chinese Ceramic Society Beijing100831China

Relaxor dielectric ceramic capacitors are very attractive for high-power energy ***,the low breakdown strength severely restricts improvements to the energy storage density and practical ***,a strategy of designing small grain sizes and abundant amorphous grain boundaries is proposed to improve the energy storage properties under the guidance of phase field theory.0.925(K_(0.5)Na_(0.5))NbO_(3)-e0.075Bi(Zn_(2/3)(Ta_(0.5)Nb_(0.5))1/3)O_(3)(KNNe-BZTN)relaxor ferroelectric ceramic is taken as an example to verify our *** grain sizes and grain boundaries of the KNNeBZTN ceramics are carefully controlled by the high-energy ball milling method and twoestep sintering *** analysis and diffusion reflectance spectra demonstrate that KNNeBZTN ceramics with a small grain size and abundant amorphous grain boundary exhibit a lower charge carrier concentration and higher band *** a consequence,the breakdown electric field of KNNeBZTN ceramics increases from 222 kV/cm to 317 kV/cm when the grain size is decreased from 410 nm to 200 nm,accompanied by a slightly degraded maximum *** ceramics with an average grain size of~250 nm and abundant amorphous grain boundaries exhibit optimum energy storage properties with a high recoverable energy density of 4.02 J/cm^(3) and a high energy efficiency of 87.4%.This successful local structural design opens up a new paradigm to improve the energy storage performance of other dielectric ceramic capacitors for electrical energy storage.

关键词： Grain size Grain boundary KNN-based dielectric ceramic capacitors Energy storage properties Breakdown strength Two-step sintering strategy

Research Hotspots and Trends Analysis of Real-World Data Based on Social Network Analysis and Knowledge Graph

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Asian Journal of Social Pharmacy 2021年第3期16卷 272-279页

作者： Li Jiahui zhao peiyao Yuan Xiaoliang School of Business Administration Shenyang Pharmaceutical UniversityShenyang 110016China Research Institute of Drug Regulatory Science Shenyang Pharmaceutical UniversityShenyang 110016China

Objective To study the research status,research hotspots and development trends in the field of real-world data(RWD)through social network analysis and knowledge graph *** RWD of the past 10 years were retrieved,and literature metrological analysis was made by using UCINET and CiteSpace from *** and Conclusion The frequency and centrality of related keywords such as real-world study,hospital information system(HIS),drug combination,data mining and TCM are *** clusters labeled as clinical medication and RWD contain more *** recent 4 years,there are more articles involving the keywords of data specification,data authenticity,data security and information *** them,compound Kushen injection,HIS database and RWD are the top three *** is a long-term research hotspot for Chinese and western medicine to use HIS to study clinical medication,clinical characteristics,diseases and ***,the research of RWD database has changed from construction to standardized collection and governance,which can make RWD *** authenticity,data security and information security will become the new hotspots in the research of RWD.

关键词： social network analysis knowledge graph real-world data data specification technical specification

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基于动态优先级的奖励优化模型

郑州大学学报（理学版） 2022年第1期54卷 62-68页

作者：赵沛尧黄蔚苏州大学计算机科学与技术学院江苏苏州215006 苏州大学江苏省计算机信息处理技术重点实验室江苏苏州215006 苏州大学东吴学院江苏苏州215006

传统的约束马尔可夫决策过程(constrained Markov decision process,CMDP)模型用来解决多目标决策的困难,但该模型缺乏通用性并且只适用于离散环境。为了解决这一问题,提出一种基于CMDP的改进算法CRODP,与强化学习(reinforcement learni... 详细信息

传统的约束马尔可夫决策过程(constrained Markov decision process,CMDP)模型用来解决多目标决策的困难,但该模型缺乏通用性并且只适用于离散环境。为了解决这一问题,提出一种基于CMDP的改进算法CRODP,与强化学习(reinforcement learning,RL)算法结合,将带约束问题建模为拉格朗日公式,其中包含着深度强化学习的策略参数。然后进一步推导出模型参数的更新公式,并将其作为深度强化学习神经网络的损失函数。模型在学习过程中动态调整约束与主要目标之间的权重以确保最终策略符合给定的约束。在若干机器人平台上与基准的深度强化学习算法进行比较,显示本算法得出的最优策略能够更好地满足相应约束。

关键词：强化学习深度学习受限马尔可夫模型动态优先级机器人环境

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社会主义文化强国的内涵解构、建成逻辑与实践进路

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东岳论丛 2023年第1期44卷 5-12,191页

作者：洪向华赵培尧科研部北京100091 山东大学马克思主义学院山东济南250013

国家和民族的强盛,必须以文化的繁荣和兴盛为支撑。新时代十年来,在以习近平同志为核心的党中央坚强领导下,我国意识形态领域形势发生了全局性、根本性转变,全党全国各族人民文化自信明显增强、精神面貌更加奋发昂扬,全社会凝聚力和向... 详细信息

国家和民族的强盛,必须以文化的繁荣和兴盛为支撑。新时代十年来,在以习近平同志为核心的党中央坚强领导下,我国意识形态领域形势发生了全局性、根本性转变,全党全国各族人民文化自信明显增强、精神面貌更加奋发昂扬,全社会凝聚力和向心力极大提升。在实现物质文明和精神文明相协调的中国式现代化新征程中,围绕举旗帜、聚民心、育新人、兴文化、展形象建设社会主义文化强国正当其时。未来五年乃至更长时期是统筹高质量发展与文化建设的重要战略机遇期,必须深入理解并扎实推进社会主义文化强国战略,从基础理论出发厘定社会主义文化强国战略的要素内涵,深入分析社会主义文化强国的建成逻辑,明晰社会主义文化强国的建成方向与路径指向,以清晰的理论导向和明确的战略定位确保文化建设新实践的顺利实施,为社会主义现代化建设夯实文化基础。

关键词：社会主义文化强国文化建设文化自信文化软实力