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Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang Zeng wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen wei Yufei Mei Yan Zeng Brain Science and Advanced Technology Institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan University of Science and Technology WuhanHubei ProvinceChina School of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

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A generative deep learning framework for airfoil flow field prediction with sparse data

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Chinese Journal of Aeronautics 2022年第1期35卷 470-484页

作者： Haizhou WU Xuejun LIU wei AN hongqiang LYU MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerodynamic Noise Control Mianyang 621000China State Key Laboratory of Aerodynamics Mianyang 621000China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Deep learning has been probed for the airfoil performance prediction in recent *** with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper ***,effective training of the data-driven models in deep learning severely hinges on the data in diversity and *** this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse *** presented approach consists of two modules,pre-training module and fine-tuning *** pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training *** the fine-tuning module,we propose a novel adversarial architecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the *** use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training *** results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.

关键词： CFD Flow field Generative adversarial networks(GANs) Sparse data Supercritical airfoil

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On developing data-driven turbulence model for DG solution of RANS

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Chinese Journal of Aeronautics 2019年第8期32卷 1869-1884页

作者： Liang SUN wei AN Xuejun LIU hongqiang LYU College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210093China

High-order Discontinuous Galerkin(DG) methods have been receiving more and more attentions in the area of Computational Fluid Dynamics(CFD) because of their high-accuracy property. However, it is still a challenge to obtain converged solution rapidly when solving the Reynolds Averaged Navier–Stokes(RANS) equations since the turbulence models significantly increase the nonlinearity of discretization system. The overall goal of this research is to develop an Artificial Neural Networks(ANNs) model with low complexity acting as an algebraic turbulence model to estimate the turbulence eddy viscosity for RANS. The ANN turbulence model is off-line trained using the training data generated by the widely used Spalart–Allmaras(SA) turbulence model before the Optimal Brain Surgeon(OBS) is employed to determine the relevancy of input *** the selected relevant features, a fully connected ANN model is constructed. The performance of the developed ANN model is numerically tested in the framework of DG for RANS, where the‘‘DG+ANN' method provides robust and steady convergence compared to the ‘‘DG+SA' method. The results demonstrate the promising potential to develop a general turbulence model based on artificial intelligence in the future given the training data covering a large rang of flow conditions.

关键词： Artificial neural network Discontinuous Galerkin method Fluid Optimal brain surgeon Spalart–Allmaras turbulence model

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Solar cycles during the seventeenth century revealed by equatorial aurora records

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Earth and Planetary Physics 2025年第1期9卷 182-187页

作者： Yong wei LiMei Yan Key Laboratory of Earth and Planetary Physics Institute of Geology and GeophysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China

Solar cycles are fundamental to astrophysics,space exploration,technological infrastructure,and Earth's climate.A better understanding of these cycles and their history can aid in risk mitigation on Earth,while also deepening our knowledge of stellar physics and solar system *** the solar cycles between 1600 and 1700-especially the post-1645 Maunder Minimum,characterized by significantly reduced solar activity-poses challenges to existing solar activity *** study utilizes a new red equatorial auroral catalog from ancient Korean texts to establish solar cycle patterns from 1623 to ***,a further reevaluation of the solar cycles between 1610 and 1755 identified a total of 13 cycles,diverging from the widely accepted record of 12 cycles during that *** research enhances our understanding of historical solar activity,and underscores the importance of integrating diverse historical sources into modern analyses.

关键词： solar cycle Maunder Minimum solar activity red equatorial aurora West Pacific geomagnetic anomaly

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From text to image:challenges in integrating vision into ChatGPT for medical image interpretation

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Neural Regeneration Research 2025年第2期20卷 487-488页

作者： Shunsuke Koga wei Du Department of Pathology and Laboratory Medicine Hospital of the University of PennsylvaniaPhiladelphiaPAUSA

Large language models(LLMs),such as ChatGPT developed by OpenAI,represent a significant advancement in artificial intelligence(AI),designed to understand,generate,and interpret human language by analyzing extensive text *** potential integration into clinical settings offers a promising avenue that could transform clinical diagnosis and decision-making processes in the future(Thirunavukarasu et al.,2023).This article aims to provide an in-depth analysis of LLMs’current and potential impact on clinical *** ability to generate differential diagnosis lists underscores their potential as invaluable tools in medical practice and education(Hirosawa et al.,2023;Koga et al.,2023).

关键词： image diagnosis text

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Boosting Oxygen Evolution Reaction Performance on NiFe‑Based Catalysts Through d‑Orbital Hybridization

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Nano-Micro Letters 2025年第1期17卷 281-292页

作者： Xing Wang wei Pi Sheng Hu Haifeng Bao Na Yao wei Luo State Key Laboratory of New Textile Materials and Advanced Processing Technology Key Laboratory of New Textile Materials and Applications of Hubei ProvinceSchool of Materials Science and EngineeringWuhan Textile UniversityWuhan 430200People’s Republic of China College of Chemistry and Molecular Sciences Wuhan UniversityWuhan 430072People’s Republic of China

Anion-exchange membrane water electrolyzers(AEMWEs)for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant NiFe-based *** introducing a third metal into NiFe-based catalysts to construct asymmetrical M-NiFe units,the d-orbital and electronic structures can be adjusted,which is an important strategy to achieve sufficient oxygen evolution reaction(OER)performance in ***,the ternary NiFeM(M:La,Mo)catalysts featured with distinct M-NiFe units and varying d-orbitals are reported in this *** and theoretical calculation results reveal that the doping of La leads to optimized hybridization between d orbital in NiFeM and 2p in oxygen,resulting in enhanced adsorption strength of oxygen intermediates,and reduced rate-determining step energy barrier,which is responsible for the enhanced OER *** critically,the obtained NiFeLa catalyst only requires 1.58 V to reach 1 A cm^(−2) in an anion exchange membrane electrolyzer and demonstrates excellent long-term stability of up to 600 h.

关键词： NiFe-based catalysts d-orbital coupling Oxygen evolution reaction Anion exchange membrane electrolyzer

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A mesh optimization method using machine learning technique and variational mesh adaptation

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Chinese Journal of Aeronautics 2022年第3期35卷 27-41页

作者： Tingfan WU Xuejun LIU wei AN Zenghui HUANG hongqiang LYU MIITKey Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical *** light of the introduced large amount of computational costs for many adaptive mesh methods,moving mesh methods keep the number of nodes and topology of a mesh unchanged and do not increase CFD computational *** the state-of-the-art moving mesh method,the variational mesh adaptation approach has been introduced to CFD ***,quickly estimating the flow field on the updated meshes during the iterative algorithm is challenging.A mesh optimization method,which embeds a machine learning regression model into the variational mesh adaptation,is *** regression model captures the mapping between the initial mesh nodes and the flow field,so that the variational method could move mesh nodes iteratively by solving the mesh functional which is built from the estimated flow field on the updated mesh via the regression *** the optimization,the density of the nodes in the high gradient area increases while the density in the low gradient area *** examples are first used to verify the feasibility and effectiveness of the proposed *** then we use the steady subsonic and transonic flows over cylinder and NACA0012 airfoil on unstructured triangular meshes to test our *** show that the proposed method significantly improves the accuracy of the local flow features on the adaptive *** work indicates that the proposed mesh optimization approach is promising for improving the accuracy and efficiency of CFD computation.

关键词： CFD Flow field Machine learning Moving mesh method Regression models Variational mesh adaptation

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飞轮储能技术研究进展

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中国科技纵横 2020年第20期 104-107页

作者：罗桂平卫宏强孟德超宋浩强华驰动能(北京)科技有限公司北京 101111 华驰动能(北京)科技有限公司北京 101111 华驰动能(北京)科技有限公司北京 101111 华驰动能(北京)科技有限公司北京 101111

储能是智能电网、能源互联网的重要组成部分和关键支撑技术.近年来储能产业发展迅猛,各类储能技术也日趋成熟.本文对各种储能技术进行了介绍,着重分析了飞轮储能技术的特性,对其国内外研究现状及进展进行阐述,以期推动飞轮储能技术在电... 详细信息

储能是智能电网、能源互联网的重要组成部分和关键支撑技术.近年来储能产业发展迅猛,各类储能技术也日趋成熟.本文对各种储能技术进行了介绍,着重分析了飞轮储能技术的特性,对其国内外研究现状及进展进行阐述,以期推动飞轮储能技术在电力行业中的大规模应用.

关键词：储能飞轮智能电网新能源

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Multiscale Characteristics and Connection Mechanisms of Attraction Networks:A Trajectory Data Mining Approach Leveraging Geotagged Data

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Chinese Geographical Science 2024年第3期34卷 533-547页

作者： JIANG hongqiang wei Ye MEI Lin WANG Zhaobo School of Resource and Environment Engineering Ludong UniversityYantai 264025China School of Geographical Sciences Northeast Normal UniversityChangchun 130024China Changchun University of Finance and Economics Changchun 130122China Jilin Jizhi City Architectural Design Co. LTDChangchun 130012China

Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination *** paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the *** results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism *** macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high *** mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of *** pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four diff

关键词： attraction network travel mobility polycentric structure network motif connectivity mechanism destination management organization(DMO) destination planning Beijing,China

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Synthesis, characterization and photoactivity of bi-crystalline mesoporous TiO2

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Frontiers of Materials Science 2016年第1期10卷 23-30页

作者： Dongthanh NGUYEN wei WANG Haibo LONG hongqiang RU Key Laboratory for Anisotropy and Texture of Materials of Ministry of Education (ATM) Northeastern University Shenyang 110819 China School of Materials and Metallurgy Northeastern University Shenyang 110819 China

Mesoporous titania （meso-TiO2） has received extensive attention owing to its versatile potential applications. This paper reports a low-temperature templating approach for the fabrication of meso-TiO2 using the peroxo titanic acid （PTA） sol as precursor and Pluronic P123 as nonionic template. The TGA, XRD, N2 sorption, FE-SEM and HRTEM were used to characterize the obtained samples. The results showed that meso-TiO2 with high surface area up to 163 m2.g^-1 and large pore volume of 0.65 cm3.^-1 can be obtained. The mesopore sizes can be varied between 13 and 20 nm via this synthesis approach. The amount of P123 and the calcination conditions were found to have great influence on the mesoporous and crystalline structures of meso-TiO2. The photocatalytic activity testing clearly shows that the high surface area and bi-crystallinity phases of meso-TiO2 play important roles in enhancing photocatalytic properties of meso-TiO2 in photo-decomposing Rhodamine B in water.

关键词： surfactant templating mesopore bi-crystallinity titania

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