The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle...The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle remains a challenging task.To tackle this challenge,the present study proposes a novel approach for identifying the gradient-distributed plastic parameters for the S38C axle by integrating nano-indentation techniques with the machine learning method.Firstly,nano-indentation tests are conducted along the radial direction of the S38C axle to obtain the gradient-distributed load-displacement curves,nano-hardness,and elastic modulus.Subsequently,the dimensionless analysis is performed to obtain the representative stress,strain,and yield stress from load-displacement curves.These parameters are then incorporated into the machine learning method as physical information to identify the gradient-distributed plastic parameters of the S38C axle.The results indicate that the proposed method based on the physics-informed neural network and multi-fidelity neural network successfully identifies the gradient-distributed plastic parameters of the S38C axles and demonstrates superior prediction accuracy and generalization compared with the purely data-driven machine learning method.展开更多
Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders...Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.展开更多
ArcGIS Server可以构建Web应用、Web服务,ArcGIS Server的出现为网络地图服务提供了一个全新的途径。以ArcGIS Server10.0为平台研究网络地图服务系统的设计与实现,基于B/S三层混合模式,采用ArcGIS REST API和ArcGIS API For Flex,将Arc...ArcGIS Server可以构建Web应用、Web服务,ArcGIS Server的出现为网络地图服务提供了一个全新的途径。以ArcGIS Server10.0为平台研究网络地图服务系统的设计与实现,基于B/S三层混合模式,采用ArcGIS REST API和ArcGIS API For Flex,将ArcSDE作为空间数据引擎,SQLServer作为数据库进行空间数据管理,设计和实现一个具有基本地图操作功能、地图定位、查询、空间分析的地图网络发布系统,为地图的网络服务奠定基础。展开更多
为了解决装备全寿命管理工作中数据变更频繁、管理复杂等问题,设计并实现了装备电子档案系统。该系统使用C#语言,以SQL Sever 2008作为底层数据库,采用LINQ to Entities进行数据查询与绑定,并用MS Chart实现数据可视化。实现了对装备从...为了解决装备全寿命管理工作中数据变更频繁、管理复杂等问题,设计并实现了装备电子档案系统。该系统使用C#语言,以SQL Sever 2008作为底层数据库,采用LINQ to Entities进行数据查询与绑定,并用MS Chart实现数据可视化。实现了对装备从生产、列装、使用到退役报废全过程信息的采集、管理与分析,对于掌握部队装备技术状况,开展装备维护和维修管理、辅助决策具有重要的指导作用。展开更多
基金supported by the National Key Research and Development Plan(Grant No.2022YFB3401901)the National Natural Science Foundation of China(Grant Nos.12192210,12192214,12072295,and 12222209)+1 种基金Independent Project of State Key Laboratory of Rail Transit Vehicle System(Grant No.2023TPL-T03)Fundamental Research Funds for the Central Universities(Grant No.2682023CG004).
文摘The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle remains a challenging task.To tackle this challenge,the present study proposes a novel approach for identifying the gradient-distributed plastic parameters for the S38C axle by integrating nano-indentation techniques with the machine learning method.Firstly,nano-indentation tests are conducted along the radial direction of the S38C axle to obtain the gradient-distributed load-displacement curves,nano-hardness,and elastic modulus.Subsequently,the dimensionless analysis is performed to obtain the representative stress,strain,and yield stress from load-displacement curves.These parameters are then incorporated into the machine learning method as physical information to identify the gradient-distributed plastic parameters of the S38C axle.The results indicate that the proposed method based on the physics-informed neural network and multi-fidelity neural network successfully identifies the gradient-distributed plastic parameters of the S38C axles and demonstrates superior prediction accuracy and generalization compared with the purely data-driven machine learning method.
基金supported by the NIA/NIH(1K01AG060040).Studies performed by JN were funded by the NICHD/NIH(5R00HD096117)Microscopy Core Facility supported,in part,with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.
文摘Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.
文摘ArcGIS Server可以构建Web应用、Web服务,ArcGIS Server的出现为网络地图服务提供了一个全新的途径。以ArcGIS Server10.0为平台研究网络地图服务系统的设计与实现,基于B/S三层混合模式,采用ArcGIS REST API和ArcGIS API For Flex,将ArcSDE作为空间数据引擎,SQLServer作为数据库进行空间数据管理,设计和实现一个具有基本地图操作功能、地图定位、查询、空间分析的地图网络发布系统,为地图的网络服务奠定基础。
文摘为了解决装备全寿命管理工作中数据变更频繁、管理复杂等问题,设计并实现了装备电子档案系统。该系统使用C#语言,以SQL Sever 2008作为底层数据库,采用LINQ to Entities进行数据查询与绑定,并用MS Chart实现数据可视化。实现了对装备从生产、列装、使用到退役报废全过程信息的采集、管理与分析,对于掌握部队装备技术状况,开展装备维护和维修管理、辅助决策具有重要的指导作用。
