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Microglia in drug addiction:A perspective from neuroimmunopharmacology

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Zoological Research 2024年第3期45卷 704-706页

作者： Cong Lin Xiaohui WANG Laboratory of Chemical Biology Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin 130022China Beijing National Laboratory for Molecular Sciences Beijing 100190China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefeiAnhui 230026China

Drug addiction refers to a state of dependence that arises from habitual drug intake and can result in specific withdrawal symptoms upon cessation.The most commonly abused substances include psychostimulants,cannabinoids,and opioids.When drugs are consumed,they stimulate the release of dopamine,a neurotransmitter crucial for the pleasure and reward centers of the brain.With repeated drug use,the brain undergoes various changes,leading to tolerance,dependence,and addiction(Lüscher et al.,2020).The mechanisms involved in drug addiction are highly complex and involve diverse cell types within the brain.

关键词： addiction drugs intake

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

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Global Energy Interconnection 2024年第1期7卷 94-105页

作者： Pengtian Guo Kai Xiao Xiaohui WANG Daoxing Li China Electric Power Research Institute Co.Ltd. Beijing 100192P.R.China

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

关键词： Power Internet of Things Object model High concurrency access Zero trust mechanism Multi-source heterogeneous data

Next-generation vaccines for substance use disorders

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Zoological Research 2024年第3期45卷 707-708页

作者： Kaixuan wang Hongshuang wang Xiaohui WANG Laboratory of Chemical Biology Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin 130022China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefeiAnhui 230026China

Substance use disorders(SUDs)impact an estimated 300 million people worldwide,significantly impairing both health and social functioning.These disorders are marked by an inability to regulate substance use,despite the harmful consequences.Addiction affects various neurotransmitter systems,including dopamine,serotonin,γ-aminobutyric acid(GABA),and glutamate,each of which plays a role in the reward,stress,and self-control pathways of the brain(Koob&Volkow,2016).While significant advances have been made in neuroscience,our understanding of how these neurotransmitter systems interact and contribute to addiction is still evolving.This knowledge gap represents a significant challenge in the formulation of effective treatments for SUDs.At present,the US Food and Drug Administration(FDA)has approved pharmacological treatments for alcohol,nicotine,and opioid use disorders(Vasiliu,2022);however,no such treatments have been authorized for SUDs in general,or specifically for stimulant use disorders,such as cocaine and methamphetamine addiction.Notably,the FDA has not approved any new drugs for SUD treatment in the past 40 years.

关键词： disorders treatment consequences

Effects of pellet surface roughness and pre-oxidation temperature on CMAS corrosion behavior of Ti_(2)AlC

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Journal of Advanced Ceramics 2022年第6期11卷 945-960页

作者： Lei GUO Guang LI Jing WU Xiaohui WANG School of Materials Science and Engineering Tianjin UniversityTianjin 300072China Tianjin Key Laboratory of Advanced Joining Technology Key Lab of Advanced Ceramics and Machining Technology of Ministry of EducationTianjin 300072China School of Materials Science and Engineering Shenyang Ligong UniversityShenyang 110159China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China

Calcium–magnesium–alumina–silicate(CMAS)corrosion is a serious threat to thermal barrier coatings(TBCs).Ti_(2)AlC has been proven to be a potential protection layer material for TBCs to resist CMAS corrosion.In this study,the effects of the pellet surface roughness and temperature on the microstructure of the pre-oxidation layer and CMAS corrosion behavior of Ti_(2)AlC were investigated.The results revealed that pre-oxidation produced inner Al_(2)O_(3)layer and outer TiO_(2)clusters on the pellet surfaces.The content of TiO_(2)decreased with decreasing pellet surface roughness and increased along with the pre-oxidation temperature.The thickness of Al_(2)O_(3)layer is also positively related to the pre-oxidation temperature.The Ti_(2)AlC pellets pre-oxidized at 1050℃could effectively resist CMAS corrosion by promoting the crystallization of anorthite(CaAl_(2)Si_(2)O_(8))from the CMAS melt rapidly,and the resistance effectiveness increased with the pellet surface roughness.Additionally,the CMAS layer mainly spalled off at the interface of CaAl_(2)Si_(2)O_(8)/Al_(2)O_(3)layer after thermal cycling tests coupled with CMAS corrosion.The Al_(2)O_(3)layer grown on the rough interface could combine with the pellets tightly during thermal cycling tests,which was attributed to obstruction of the rough interface to crack propagation.

关键词： thermal barrier coatings(TBCs) Ti2AlC surface roughness pre-oxidation temperature calcium-magnesium-alumina-silicate(CMAS)corrosion thermal cycling

Modeling and application of marketing and distribution data based on graph computing

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Global Energy Interconnection 2022年第4期5卷 448-460页

作者： Kai Xiao Daoxing Li Xiaohui WANG Pengtian Guo China Electric Power Research Institute Co.Ltd. Beijing 100192P.R.China

Integrating marketing and distribution businesses is crucial for improving the coordination of equipment and the efficient management of multi-energy systems.New energy sources are continuously being connected to distribution grids;this,however,increases the complexity of the information structure of marketing and distribution businesses.The existing unified data model and the coordinated application of marketing and distribution suffer from various drawbacks.As a solution,this paper presents a data model of"one graph of marketing and distribution"and a framework for graph computing,by analyzing the current trends of business and data in the marketing and distribution fields and using graph data theory.Specifically,this work aims to determine the correlation between distribution transformers and marketing users,which is crucial for elucidating the connection between marketing and distribution.In this manner,a novel identification algorithm is proposed based on the collected data for marketing and distribution.Lastly,a forecasting application is developed based on the proposed algorithm to realize the coordinated prediction and consumption of distributed photovoltaic power generation and distribution loads.Furthermore,an operation and maintenance(O&M)knowledge graph reasoning application is developed to improve the intelligent O&M ability of marketing and distribution equipment.

关键词： Marketing and distribution connection Graph data Graph computing Knowledge graph Data model

Trading platform for cooperation and sharing based on blockchain within multi-agent energy internet

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Global Energy Interconnection 2021年第4期4卷 384-393页

作者： Xiaohui WANG Peng Liu Zhixiang Ji China Electric Power Research Institute Beijing 100192P.R.China

With the release of the electricity sales side,large-scale small-capacity distributed power generation units are connected to the distribution side,forming multi-type market entities such as microgrids,integrated energy systems,and virtual power plants.With the large-scale integration of distributed energy,the energy market under the energy internet is different from a traditional transmission grid.It is currently developing in the direction of diversified entities and commodities,a flat structure,and a flexible and competitive multi-agent market mechanism.In this context,this study analyzes the value of combining blockchain and the electricity market presents the design of a blockchain trading framework for multi-agent cooperation and sharing of the energy internet.The nodes in market transactions are modeled through power system modeling in the physical layer and the transaction consensus strategy in the cyber layer;moreover,the nodes are verified in a modified IEEE 13 testing feeder of a distribution network.A transaction example is demonstrated using the multi-agent cooperation and sharing transaction platform based on the Ethereum private blockchain.

关键词： Energy internet Distributed energy resource Electricity transaction Blockchain Multi-agent cooperation and sharing

Towards sparse matrix operations:graph database approach for power grid computation

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Global Energy Interconnection 2023年第1期6卷 50-63页

作者： Daoxing Li Kai Xiao Xiaohui WANG Pengtian Guo Yong Chen China Electric Power Research Institute Co.Ltd. Beijing 100192P.R.China

The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion ability.Native graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing tasks.However,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power grids.In this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the graph.Based on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,etc.Specifically,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix computation.Based on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph database.It promotes the efficiency of PIoT when handling multi-source heterogeneous data.An comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB baselines.The results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations.

关键词： Graph database Graph description Matrix Parallel computing Power flow

创新对外翻译传播模式,服务对外话语体系建设--王晓辉访谈录

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山东外语教学 2022年第6期43卷 1-6页

作者：王晓辉曾佳宁中国互联网新闻中心北京100089 北京外国语大学高级翻译学院北京100089

中国互联网新闻中心总编辑王晓辉多年从事文学、文化、时政等多个领域的翻译、译评、新闻和传播工作,获全国新闻出版行业领军人才、中宣部文化名家暨“四个一批”人才称号。在本次访谈中,王总编辑重点论述了国际传播战略背景下的对外话... 详细信息

中国互联网新闻中心总编辑王晓辉多年从事文学、文化、时政等多个领域的翻译、译评、新闻和传播工作,获全国新闻出版行业领军人才、中宣部文化名家暨“四个一批”人才称号。在本次访谈中,王总编辑重点论述了国际传播战略背景下的对外话语体系建设及对外翻译传播人才培养等相关话题。

关键词：翻译传播对外话语翻译教育模式创新

Deep reinforcement learning based multi-level dynamic reconfiguration for urban distribution network:a cloud-edge collaboration architecture

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Global Energy Interconnection 2023年第1期6卷 1-14页

作者： Siyuan Jiang Hongjun Gao Xiaohui WANG Junyong Liu Kunyu Zuo College of Electrical Engineering Sichuan UniversityChengdu Sichuan 610065P.R.China China Electric Power Research Institute Haidian DistrictBeijing 100192P.R.China Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ 07030USA

With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.

关键词： Cloud-edge collaboration architecture Multi-agent deep reinforcement learning Multi-level dynamic reconfiguration Offline learning Online learning