目的分析2008—2024年老年性肌少症与线粒体相关性研究的现状、热点及发展趋势,为该领域的后续研究提供参考。方法检索2008年1月1日至2024年12月31日Web of Science核心合集数据库收录的老年性肌少症与线粒体相关性研究的文献,使用R 4....目的分析2008—2024年老年性肌少症与线粒体相关性研究的现状、热点及发展趋势,为该领域的后续研究提供参考。方法检索2008年1月1日至2024年12月31日Web of Science核心合集数据库收录的老年性肌少症与线粒体相关性研究的文献,使用R 4.2.0软件的Bibliometrix包对发文国家、合作网络、作者、机构、期刊、高被引文献、关键词和文献被引频次进行定量和可视化分析,并运用H指数分析作者的学术影响力。结果共纳入1219篇文献,2008—2024年发文量总体呈上升趋势。累计发文量排名前三位的国家分别是美国、中国和意大利;发文量排名前三位的期刊分别为Journal of Cachexia,Sarcopenia and Muscle、International Journal of Molecular Sciences和Experimental Gerontology;H指数排名前六位的作者分别为Marzettie E、Calvani R、Picca A、Van Remmen H、Leeuwenbugh C和Bernabel R;被引频次最高的文献是“Sarcopenia:agingrelated loss of muscle mass and function”;出现频次排名前五的关键词分别为skeletalmuscle、sarcopenia、oxidative stress、exercise和expression。结论老年性肌少症与线粒体相关性研究领域呈现良好的发展态势。未来需加强跨国家、跨机构和跨学科合作,可重点关注线粒体融合蛋白等对线粒体功能的影响,以及饮食和运动对老年性肌少症的干预作用等方面的探索。展开更多
With more and more IoT terminals being deployed in various power grid business scenarios,terminal reliability has become a practical challenge that threatens the current security protection architecture.Most IoT termi...With more and more IoT terminals being deployed in various power grid business scenarios,terminal reliability has become a practical challenge that threatens the current security protection architecture.Most IoT terminals have security risks and vulnerabilities,and limited resources make it impossible to deploy costly security protection methods on the terminal.In order to cope with these problems,this paper proposes a lightweight trust evaluation model TCL,which combines three network models,TCN,CNN,and LSTM,with stronger feature extraction capability and can score the reliability of the device by periodically analyzing the traffic behavior and activity logs generated by the terminal device,and the trust evaluation of the terminal’s continuous behavior can be achieved by combining the scores of different periods.After experiments,it is proved that TCL can effectively use the traffic behaviors and activity logs of terminal devices for trust evaluation and achieves F1-score of 95.763,94.456,99.923,and 99.195 on HDFS,BGL,N-BaIoT,and KDD99 datasets,respectively,and the size of TCL is only 91KB,which can achieve similar or better performance than CNN-LSTM,RobustLog and other methods with less computational resources and storage space.展开更多
文摘目的分析2008—2024年老年性肌少症与线粒体相关性研究的现状、热点及发展趋势,为该领域的后续研究提供参考。方法检索2008年1月1日至2024年12月31日Web of Science核心合集数据库收录的老年性肌少症与线粒体相关性研究的文献,使用R 4.2.0软件的Bibliometrix包对发文国家、合作网络、作者、机构、期刊、高被引文献、关键词和文献被引频次进行定量和可视化分析,并运用H指数分析作者的学术影响力。结果共纳入1219篇文献,2008—2024年发文量总体呈上升趋势。累计发文量排名前三位的国家分别是美国、中国和意大利;发文量排名前三位的期刊分别为Journal of Cachexia,Sarcopenia and Muscle、International Journal of Molecular Sciences和Experimental Gerontology;H指数排名前六位的作者分别为Marzettie E、Calvani R、Picca A、Van Remmen H、Leeuwenbugh C和Bernabel R;被引频次最高的文献是“Sarcopenia:agingrelated loss of muscle mass and function”;出现频次排名前五的关键词分别为skeletalmuscle、sarcopenia、oxidative stress、exercise和expression。结论老年性肌少症与线粒体相关性研究领域呈现良好的发展态势。未来需加强跨国家、跨机构和跨学科合作,可重点关注线粒体融合蛋白等对线粒体功能的影响,以及饮食和运动对老年性肌少症的干预作用等方面的探索。
基金supported by National Key R&D Program of China(No.2022YFB3105101).
文摘With more and more IoT terminals being deployed in various power grid business scenarios,terminal reliability has become a practical challenge that threatens the current security protection architecture.Most IoT terminals have security risks and vulnerabilities,and limited resources make it impossible to deploy costly security protection methods on the terminal.In order to cope with these problems,this paper proposes a lightweight trust evaluation model TCL,which combines three network models,TCN,CNN,and LSTM,with stronger feature extraction capability and can score the reliability of the device by periodically analyzing the traffic behavior and activity logs generated by the terminal device,and the trust evaluation of the terminal’s continuous behavior can be achieved by combining the scores of different periods.After experiments,it is proved that TCL can effectively use the traffic behaviors and activity logs of terminal devices for trust evaluation and achieves F1-score of 95.763,94.456,99.923,and 99.195 on HDFS,BGL,N-BaIoT,and KDD99 datasets,respectively,and the size of TCL is only 91KB,which can achieve similar or better performance than CNN-LSTM,RobustLog and other methods with less computational resources and storage space.
