目的对我国同情心疲乏现有文献进行文献计量学分析,了解同情心疲乏的研究现状、研究热点及发展趋势,为今后研究和发展提供借鉴。方法通过CNKI、万方数据库、中国生物医学文献数据库(CBM)、维普数据库、Web of Science及PubMed数据库检索...目的对我国同情心疲乏现有文献进行文献计量学分析,了解同情心疲乏的研究现状、研究热点及发展趋势,为今后研究和发展提供借鉴。方法通过CNKI、万方数据库、中国生物医学文献数据库(CBM)、维普数据库、Web of Science及PubMed数据库检索2008年1月—2018年7月发表的有关我国同情心疲乏的文献,利用文献计量学方法及社会网络化分析对纳入的文献进行多维度分析。使用SPSS 22.0对数据进行统计学处理。结果最终纳入143篇文献,其中中文文献138篇;文献发文量随年份总体呈上升趋势;期刊论文120篇,其中《中华现代护理杂志》发表文献量最多共9篇,占6.3%;按第一作者所在地区排名,前10位共发表文献96篇,占67.1%,其中湖北省发表文献量最多共16篇,占11.2%;合著率为85.3%,合作度为3,核心作者20人;31篇文献得到科研基金的资助,基金论文比为21.7%,引文数量共2 106篇,篇均引文率为17.6%;研究类型以调查和访谈类为主,共106篇,占74.1%;词频≥14的关键词共有4个:同情心疲乏、护士、共情疲劳、影响因素。结论我国同情心疲乏的研究正处于发展阶段,应拓展研究的广度和深度,加大科研基金的投入,加强机构间的合作,促进专业核心团队的构建,以推动我国同情心疲乏研究的发展。展开更多
随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Ge...随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Gephi做出网络图,将清洁能源企业整合成网络架构体系并进行统计分析,通过研究发现,清洁能源企业具有一定的相关关系,形成一定程度上的聚集,各企业间的联系比较密切。通过网络的方法,进一步理解清洁能源企业之间的联系,以帮助清洁能源企业做出正确的判断与决策,从而做出较为正确的选择并且建立更加完善的网络体系。With the rapid development of China’s economy, there is an increasing emphasis on the expansion of clean energy projects, especially in the Qinghai region. This is not only beneficial for the protection of the ecological environment but also irreplaceable for social development. This paper constructs a clean energy enterprise network, processing the collected data concretely, and using Gephi to create a network diagram. The clean energy enterprises are integrated into a network architecture system for statistical analysis. The study finds that there are certain correlations among clean energy enterprises, forming a degree of aggregation, and the connections between enterprises are relatively close. Through the method of networking, we can further understand the relationships between clean energy enterprises, help them make correct judgments and decisions, thus make more accurate choices, and establish a more comprehensive network system.展开更多
[目的]分析我国循证中医护理发展现状以及存在的不足,为今后发展提供借鉴。[方法]通过检索中国知网数据库、维普数据库、万方数据知识服务平台、中国生物医学文献数据库、Web of Science、Cochrane Library关于循证中医护理的文献,利用...[目的]分析我国循证中医护理发展现状以及存在的不足,为今后发展提供借鉴。[方法]通过检索中国知网数据库、维普数据库、万方数据知识服务平台、中国生物医学文献数据库、Web of Science、Cochrane Library关于循证中医护理的文献,利用文献计量学方法、社会网络化分析、系统评价再评价等方法对纳入的文献进行多维度分析。[结果]共纳入109篇文献,通过分析获知我国循证中医护理研究相对较少,内容较局限,理论性研究多于实践性研究,机构合作欠缺,作者合作少,基金资助少,文献质量不高。[结论]循证中医护理发展仍处于初期发展阶段,应拓展研究的广度和深度,理论与实践共同发展,加强机构间的合作,加大基金投入,提高研究质量,以此推动中医护理的发展。展开更多
In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by p...In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by presenting a simplified bridge model(SBM)optimized for both computational efficiency and precise representation,a seminal contribution to the engineering design landscape.Central to this innovation is a novel model-updating methodology that synergistically melds artificial neural networks with an augmented particle swarm optimization.The neural networks adeptly map update parameters to seismic responses,while enhancements to the particle swarm algorithm’s inertial and learning weights lead to superior SBM parameter updates.Verification via a 4-span high-speed railway bridge revealed that the optimized SBM and TBSM exhibit a highly consistent structural natural period and seismic response,with errors controlled within 7%.Additionally,the computational efficiency improved by over 100%.Leveraging the peak displacement and shear force residuals from the seismic TBSM and SBM as optimization objectives,SBM parameters are adeptly revised.Furthermore,the incorporation of elastoplastic springs at the beam ends of the simplified model effectively captures the additional mass,stiffness,and constraint effects exerted by the track system on the bridge structure.展开更多
The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system f...The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.展开更多
This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model,which is the interconnection of a linear delayed dynamic syste...This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model,which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator,and covers several well-known neural networks,such as Hopfield neural networks,cellular neural networks(CNNs),bidirectional associative memory(BAM)networks,recurrent multilayer perceptrons(RMLPs).By virtue of Lyapunov-Krasovskii stability theory and linear matrix inequality(LMI)technique,some exponential synchronization criteria are derived.Using the drive-response concept,hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria.Finally,detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.展开更多
文摘目的对我国同情心疲乏现有文献进行文献计量学分析,了解同情心疲乏的研究现状、研究热点及发展趋势,为今后研究和发展提供借鉴。方法通过CNKI、万方数据库、中国生物医学文献数据库(CBM)、维普数据库、Web of Science及PubMed数据库检索2008年1月—2018年7月发表的有关我国同情心疲乏的文献,利用文献计量学方法及社会网络化分析对纳入的文献进行多维度分析。使用SPSS 22.0对数据进行统计学处理。结果最终纳入143篇文献,其中中文文献138篇;文献发文量随年份总体呈上升趋势;期刊论文120篇,其中《中华现代护理杂志》发表文献量最多共9篇,占6.3%;按第一作者所在地区排名,前10位共发表文献96篇,占67.1%,其中湖北省发表文献量最多共16篇,占11.2%;合著率为85.3%,合作度为3,核心作者20人;31篇文献得到科研基金的资助,基金论文比为21.7%,引文数量共2 106篇,篇均引文率为17.6%;研究类型以调查和访谈类为主,共106篇,占74.1%;词频≥14的关键词共有4个:同情心疲乏、护士、共情疲劳、影响因素。结论我国同情心疲乏的研究正处于发展阶段,应拓展研究的广度和深度,加大科研基金的投入,加强机构间的合作,促进专业核心团队的构建,以推动我国同情心疲乏研究的发展。
文摘随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Gephi做出网络图,将清洁能源企业整合成网络架构体系并进行统计分析,通过研究发现,清洁能源企业具有一定的相关关系,形成一定程度上的聚集,各企业间的联系比较密切。通过网络的方法,进一步理解清洁能源企业之间的联系,以帮助清洁能源企业做出正确的判断与决策,从而做出较为正确的选择并且建立更加完善的网络体系。With the rapid development of China’s economy, there is an increasing emphasis on the expansion of clean energy projects, especially in the Qinghai region. This is not only beneficial for the protection of the ecological environment but also irreplaceable for social development. This paper constructs a clean energy enterprise network, processing the collected data concretely, and using Gephi to create a network diagram. The clean energy enterprises are integrated into a network architecture system for statistical analysis. The study finds that there are certain correlations among clean energy enterprises, forming a degree of aggregation, and the connections between enterprises are relatively close. Through the method of networking, we can further understand the relationships between clean energy enterprises, help them make correct judgments and decisions, thus make more accurate choices, and establish a more comprehensive network system.
文摘[目的]分析我国循证中医护理发展现状以及存在的不足,为今后发展提供借鉴。[方法]通过检索中国知网数据库、维普数据库、万方数据知识服务平台、中国生物医学文献数据库、Web of Science、Cochrane Library关于循证中医护理的文献,利用文献计量学方法、社会网络化分析、系统评价再评价等方法对纳入的文献进行多维度分析。[结果]共纳入109篇文献,通过分析获知我国循证中医护理研究相对较少,内容较局限,理论性研究多于实践性研究,机构合作欠缺,作者合作少,基金资助少,文献质量不高。[结论]循证中医护理发展仍处于初期发展阶段,应拓展研究的广度和深度,理论与实践共同发展,加强机构间的合作,加大基金投入,提高研究质量,以此推动中医护理的发展。
基金Project(2022YFC3004304)supported by the National Key Research and Development Program of ChinaProjects(52078487,U1934207,52178180)supported by the National Natural Science Foundation of China+2 种基金Project(2022TJ-Y10)supported by the Hunan Province Science and Technology Talent Lifting Project,ChinaProject(2023QYJC006)supported by the Frontier Cross Research Project of Central South University,ChinaProject(SKL-IoTSC(UM)-2024-2026/ORP/GA08/2023)supported by the Science and Technology Development Fund and the State Key Laboratory of Internet of Things for Smart City(University of Macao),China。
文摘In the realm of high-speed railway bridge engineering,managing the intricacies of the track-bridge system model(TBSM)during seismic events remains a formidable challenge.This study pioneers an innovative approach by presenting a simplified bridge model(SBM)optimized for both computational efficiency and precise representation,a seminal contribution to the engineering design landscape.Central to this innovation is a novel model-updating methodology that synergistically melds artificial neural networks with an augmented particle swarm optimization.The neural networks adeptly map update parameters to seismic responses,while enhancements to the particle swarm algorithm’s inertial and learning weights lead to superior SBM parameter updates.Verification via a 4-span high-speed railway bridge revealed that the optimized SBM and TBSM exhibit a highly consistent structural natural period and seismic response,with errors controlled within 7%.Additionally,the computational efficiency improved by over 100%.Leveraging the peak displacement and shear force residuals from the seismic TBSM and SBM as optimization objectives,SBM parameters are adeptly revised.Furthermore,the incorporation of elastoplastic springs at the beam ends of the simplified model effectively captures the additional mass,stiffness,and constraint effects exerted by the track system on the bridge structure.
基金supported by the Natural Science Foundation of Tianjin(No.20JCQNJC00720)the Fundamental Research Fund for the Central Universities(No.3122021052)。
文摘The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.
基金Project supported in part by the National Natural Science Foundationof China (No. 60504024)the Specialized Research Fund for theDoctoral Program of Higher Education,China (No. 20060335022)+1 种基金theNatural Science Foundation of Zhejiang Province (No. Y106010),China the "151 Talent Project" of Zhejiang Province (Nos.05-3-1013 and 06-2-034),China
文摘This paper investigates the exponential synchronization problem of some chaotic delayed neural networks based on the proposed general neural network model,which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator,and covers several well-known neural networks,such as Hopfield neural networks,cellular neural networks(CNNs),bidirectional associative memory(BAM)networks,recurrent multilayer perceptrons(RMLPs).By virtue of Lyapunov-Krasovskii stability theory and linear matrix inequality(LMI)technique,some exponential synchronization criteria are derived.Using the drive-response concept,hybrid feedback controllers are designed to synchronize two identical chaotic neural networks based on those synchronization criteria.Finally,detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.
