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Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 162-174页

作者： Yu Zeng Yinliang Xu Xinwei shen Hongbin Sun Tsinghua-Berkeley shenzhen Institute.Tsinghua shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high *** this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer *** the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward *** pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed *** numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed ***,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.

关键词： Game theory microgrid multi-agent system renewable energy time-of-use pricing

“Blocking and rebalance” mechanism-guided design strategies of bimetallic doped 2D a-phosphorus carbide as efficient catalysts for N2 electroreduction

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Journal of Energy Chemistry 2024年第10期97卷 68-78页

作者： Cheng He Jianglong Ma shen Xi Wenxue Zhang State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and Engineering Xi'an Jiaotong University School of Materials Science and Engineering Chang'an University

Compared to single atom catalysts（SACs）,the introduction of dual atom catalysts（DACs） has a significantly positive effect on improving the efficiency in the electrocatalytic nitrogen reduction reaction（NRR） which provides an environmental alternative to the Haber-Bosch ***,the research on the mechanism and strategy of designing bimetallic combinations for better performance is still in its early ***,based on "blocking and rebalance" mechanism,45 combinations of bimetallic pair doped α-phosphorus carbide（TMATMB@PC） are investigated as efficient NRR catalysts through density functional theory and machine learning *** a multi-step screening,the combinations of TiV,TiFe,MnMo,and FeW exhibit highly efficient catalytic performance with significantly lower limiting potentials（-0.17,-0.18,-0.14,and-0.30 V,respectively）.Excitingly,the limiting potential for CrMo and CrW combinations is 0 V,which are considered to be extremely suitable for the NRR *** mechanism of "blocking and rebalance" is revealed by the exploration of charge transfer for phosphorus atoms in electron blocking ***,the descriptor φ is proposed with machine learning,which provides design strategies and accurate prediction for finding efficient *** work not only offers promising catalysts TMATMB@PC for NRR process but also provides design strategies by presenting the descriptor φ.

关键词： 2D α-phosphorus carbide DACs Inherent attributes Machine learning Nitrogen reduction reaction

A toroidal SAW gyroscope with focused IDTs for sensitivity enhancement

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Microsystems & Nanoengineering 2024年第2期10卷 47-56页

作者： Lu Tian Haitao Zhao Qiang shen Honglong Chang Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an710072China

A surface acoustic wave(SAW)gyroscope measures the rate of rotational angular velocity by exploiting a phenomenon known as the SAW gyroscope *** a gyroscope is a great candidate for application in harsh environments because of the simplification of the suspension vibration mechanism necessary for traditional microelectromechanical system(MEMS)***,for the first time,we propose a novel toroidal standing-wave-mode SAW gyroscope using focused interdigitated transducers(FIDTs).Unlike traditional SAW gyroscopes that use linear IDTs to generate surface acoustic waves,which cause beam deflection and result in energy dissipation,this study uses FIDTs to concentrate the SAW energy based on structural features,resulting in better focusing performance and increased SAW *** experimental results reveal that the sensitivity of the structure is 1.51µV/(°/s),and the bias instability is 0.77°/s,which are improved by an order of magnitude compared to those of a traditional SAW ***,the FIDT component can enhance the performance of the SAW gyroscope,demonstrating its superiority for angular velocity *** work provides new insights into improving the sensitivity and performance of SAW gyroscopes.

关键词： angular deflection gyroscope

Physical neural networks with self-learning capabilities

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 23-42页

作者： Weichao Yu Hangwen Guo Jiang Xiao Jian shen State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Department of Physics Fudan UniversityShanghai 200433China Shanghai Research Center for Quantum Sciences Shanghai 201315China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China

Physical neural networks are artificial neural networks that mimic synapses and neurons using physical systems or *** networks harness the distinctive characteristics of physical systems to carry out computations effectively,potentially surpassing the constraints of conventional digital neural networks.A recent advancement known as“physical self-learning”aims to achieve learning through intrinsic physical processes rather than relying on external *** article offers a comprehensive review of the progress made in implementing physical self-learning across various physical *** learning strategies that contribute to the realization of physical self-learning are *** challenges in understanding the fundamental mechanism of learning,this work highlights the progress towards constructing intelligent hardware from the ground up,incorporating embedded self-organizing and self-adaptive dynamics in physical systems.

关键词： self-learning physical neural networks neuromorphic computing physical learning

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Recent advances in post-chiroptical manipulation of supramolecular aggregates assembled with molecular modules

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Science China Chemistry 2024年第9期67卷 2842-2863页

作者： Yanling shen Wanhua Wu Zhipeng Yu Cheng Yang Key Laboratory of Green Chemistry&Technology of Ministry of Education College of Chemistry InstitutionSichuan UniversityChengdu 610064China

Recently,various supramolecular assembly systems have been identified where the pre-existing chiral supramolecular structure can be manipulated through environmental adjustments,such as temperature,solvent,and *** changes result in diverse microscopic morphologies during the assembly process and induce chiroptical variations,particularly in circular dichroism(CD)and circularly polarized luminescence(CPL)*** chiroptical properties serve as direct indicators of the chiral supramolecular structure and hold promise for applications in sensing,molecular recognition,asymmetric synthesis,and material *** review focuses on research published in the last five years,highlighting instances where assembled structures aggregated by small organic molecular modules demonstrate in-situ chiroptical changes through external condition *** categorizes and discusses different modes of regulation,aiming to offer insights and guidelines for exploring dynamic changes in assembly processes and designing in-situ adjustable structures of assembly modules.

关键词： supramolecular assemblies post-chiroptical manipulation in-situ structural changes

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Real-time monitoring of oxygenation in deep brain tissue using a wireless photoelectric probe

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Science China Materials 2024年第4期67卷 1361-1362页

作者： Hao Pang Qilin Hua Guozhen shen School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100084China Institute of Flexible Electronics Beijing Institute of TechnologyBeijing 102488China

Oxygen(O2) supply to the brain is of utmost importance for human health, as cerebral hypoxia can result in irreversible brain damage. Neurodegenerative diseases, such as epilepsy, are closely associated with cerebral hypoxia [1,2]. Real-time monitoring of cerebral oxygenation holds significant value in neuroscience research and clinical diagnostics [3–10].

关键词： epilepsy cerebral diseases

Advances in MET tyrosine kinase inhibitors in gastric cancer

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Cancer Biology & Medicine 2024年第6期21卷 484-498页

作者： Yifan Zhang Lin shen Zhi Peng Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education) Department of Gastrointestinal OncologyPeking University Cancer Hospital&InstituteBeijing 100142China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers Beijing Key Laboratory of Carcinogenesis and Translational ResearchDepartment of Gastrointestinal OncologyPeking University Cancer Hospital&InstituteBeijing 100142China

Gastric cancer is among the most frequently occurring cancers and a leading cause of cancer-related deaths *** gastric cancer is highly heterogenous and comprised of different subtypes with distinct molecular and clinical characteristics,the management of gastric cancer calls for better-defined,biomarker-guided,molecular-based treatment *** is a receptor tyrosine kinase mediating important physiologic processes,such as embryogenesis,tissue regeneration,and wound ***,mounting evidence suggests that aberrant MET pathway activation contributes to tumour proliferation and metastasis in multiple cancer types,including gastric cancer,and is associated with poor patient *** such,MET-targeting therapies are being actively developed and promising progress has been demonstrated,especially with MET tyrosine kinase *** review aims to briefly introduce the role of MET alterations in gastric cancer and summarize in detail the current progress of MET tyrosine kinase inhibitors in this disease area with a focus on savolitinib,tepotinib,capmatinib,and *** on current knowledge,this review further discusses existing challenges in MET alterations testing,possible resistance mechanisms to MET inhibitors,and future directions of MET-targeting therapies.

关键词： Gastric cancer MET alterations MET tyrosine kinase inhibitors savolitinib MET testing

Optimization in Machine Learning:a Distribution-Space Approach

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Communications on Applied Mathematics and Computation 2024年第2期6卷 1217-1240页

作者： Yongqiang Cai Qianxiao Li Zuowei shen School of Mathematical Sciences Laboratory of Mathematics and Complex SystemsMOEBeijing Normal UniversityBeijing 100875China Department of Mathematics National University of Singapore21 Lower Kent Ridge RoadSingapore119077Singapore

We present the viewpoint that optimization problems encountered in machine learning can often be interpreted as minimizing a convex functional over a function space,but with a non-convex constraint set introduced by model *** observation allows us to repose such problems via a suitable relaxation as convex optimization problems in the space of distributions over the training *** derive some simple relationships between the distribution-space problem and the original problem,e.g.,a distribution-space solution is at least as good as a solution in the original ***,we develop a numerical algorithm based on mixture distributions to perform approximate optimization directly in the distribution *** of this approximation is established and the numerical efficacy of the proposed algorithm is illustrated in simple *** both theory and practice,this formulation provides an alternative approach to large-scale optimization in machine learning.

关键词： Machine learning Convex relaxation Optimization Distribution space

A Survey on Graph Neural Network Acceleration: A Hardware Perspective

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Chinese Journal of Electronics 2024年第3期33卷 601-622页

作者： Shi CHEN Jingyu LIU Li shen School of Computer National University of Defense Technology Key Laboratory of Advanced Microprocessor Chips and Systems

Graph neural networks(GNNs) have emerged as powerful approaches to learn knowledge about graphs and *** rapid employment of GNNs poses requirements for processing *** to incompatibility of general platforms,dedicated hardware devices and platforms are developed to efficiently accelerate training and inference of *** conduct a survey on hardware acceleration for *** first include and introduce recent advances of the domain,and then provide a methodology of categorization to classify existing works into three ***,we discuss optimization techniques adopted at different *** finally we propose suggestions on future directions to facilitate further works.

关键词： Graph neural networks Deep learning acceleration Domain-specific architecture Hardware accelerator