The Internet of Things(IoT)has characteristics such as node mobility,node heterogeneity,link heterogeneity,and topology heterogeneity.In the face of the IoT characteristics and the explosive growth of IoT nodes,which ...The Internet of Things(IoT)has characteristics such as node mobility,node heterogeneity,link heterogeneity,and topology heterogeneity.In the face of the IoT characteristics and the explosive growth of IoT nodes,which brings about large-scale data processing requirements,edge computing architecture has become an emerging network architecture to support IoT applications due to its ability to provide powerful computing capabilities and good service functions.However,the defense mechanism of Edge Computing-enabled IoT Nodes(ECIoTNs)is still weak due to their limited resources,so that they are susceptible to malicious software spread,which can compromise data confidentiality and network service availability.Facing this situation,we put forward an epidemiology-based susceptible-curb-infectious-removed-dead(SCIRD)model.Then,we analyze the dynamics of ECIoTNs with different infection levels under different initial conditions to obtain the dynamic differential equations.Additionally,we establish the presence of equilibrium states in the SCIRD model.Furthermore,we conduct an analysis of the model’s stability and examine the conditions under which malicious software will either spread or disappear within Edge Computing-enabled IoT(ECIoT)networks.Lastly,we validate the efficacy and superiority of the SCIRD model through MATLAB simulations.These research findings offer a theoretical foundation for suppressing the propagation of malicious software in ECIoT networks.The experimental results indicate that the theoretical SCIRD model has instructive significance,deeply revealing the principles of malicious software propagation in ECIoT networks.This study solves a challenging security problem of ECIoT networks by determining the malicious software propagation threshold,which lays the foundation for buildingmore secure and reliable ECIoT networks.展开更多
目的:检索、评价、整合国内外新生儿压力性损伤预防与管理的最佳证据,为临床规范管理新生儿压力性损伤提供循证依据。方法:系统检索BMJ Best Practice、UpToDate、国际指南协作网(GIN)、苏格兰校际指南网、加拿大安大略注册护士协会、th...目的:检索、评价、整合国内外新生儿压力性损伤预防与管理的最佳证据,为临床规范管理新生儿压力性损伤提供循证依据。方法:系统检索BMJ Best Practice、UpToDate、国际指南协作网(GIN)、苏格兰校际指南网、加拿大安大略注册护士协会、the Cochrane Library、澳大利亚Joanna Briggs Institute(JBI)循证卫生保健中心、PubMed、EMbase、医脉通、CINAHL、中国生物医学文献数据库(CBM)及中国知网等的指南、专家共识、证据总结、系统评价、临床决策、原始研究。检索时限为建库至2023年3月6日。由2名研究者对文献进行质量评价及证据提取。结果:共纳入15篇文献,包括指南6篇,专家共识1篇,系统评价2篇,原始研究5篇,证据总结1篇。汇总了包括评估、体位管理、医疗器械应用、预防、处置、人员管理6个方面,共20条证据。结论:本研究总结的新生儿压力性损伤预防与管理的最佳证据便于临床护理人员对患儿采取更有针对性的措施。展开更多
目的:通过Meta分析研究早产儿低血糖的危险因素。方法:计算机检索中国知网、中国生物医学文献数据库、万方数据库、维普数据库、PubMed、Web of Science、EMbase、the Cochrane Library,检索时限为建库至2023年12月22日,计算合并各危险...目的:通过Meta分析研究早产儿低血糖的危险因素。方法:计算机检索中国知网、中国生物医学文献数据库、万方数据库、维普数据库、PubMed、Web of Science、EMbase、the Cochrane Library,检索时限为建库至2023年12月22日,计算合并各危险因素的比值比(OR)值及其95%置信区间(CI)。结果:共纳入10篇文献,涉及4564例病人,共合并11个变量。Meta分析结果显示,母亲患糖尿病(OR=2.24)、母亲患胰岛素依赖型糖尿病(OR=3.41)、母亲患高血压(OR=1.86)、剖宫产(OR=1.79)、早产儿性别(男)(OR=2.74)、小于胎龄儿(OR=2.16)、早产儿窒息(OR=5.27)为早产儿低血糖的危险因素;产前使用硫酸镁(OR=0.43)、阴道分娩(OR=0.44)为早产儿低血糖的保护因素。结论:现有证据表明,医务人员应对母亲患有糖尿病,尤其是胰岛素依赖型糖尿病、母亲患高血压、选择剖宫产分娩、小于胎龄儿、有窒息等情况的早产儿予以高度重视,并制定个性化预防策略,以减少低血糖的发生。展开更多
Objective:To investigate the causal relationship between blood metabolite levels and the occurrence of prostate cancer by using two-sample Mendelian randomization method.Methods:Pooled data from public databases for g...Objective:To investigate the causal relationship between blood metabolite levels and the occurrence of prostate cancer by using two-sample Mendelian randomization method.Methods:Pooled data from public databases for genome-wide association analyses of blood metabolites and prostate cancer were selected,and inverse variance weighting(IVW)was used as the primary method for estimating the causal effects,while heterogeneity tests,gene multiplicity tests and sensitivity analyses were performed to assess the stability and reliability of the results.Results:A total of six known metabolites were found to potentially increase the risk of prostate cancer development(P<0.05),namely fructose,allantoin,5-hydroxytryptophan,potassium ketoisocaproate,glycyltryptophan,and 1-heptadecanoyl-glycerol-3-phosphorylcholine,with no heterogeneity or genetic pleiotropy found.Conclusion:Six known blood metabolites may be potential risk factors for prostate cancer development in European populations.展开更多
近年来大数据及云计算技术、人工智能技术的发展,使得K-Means聚类算法、DBSCAN聚类算法、BIRCH聚类算法、Cluster数据分布算法不断涌现,但不同算法在面对海量化、多样化网络数据样本时的性能存在差异。基于此,从不同数据文本关联性、数...近年来大数据及云计算技术、人工智能技术的发展,使得K-Means聚类算法、DBSCAN聚类算法、BIRCH聚类算法、Cluster数据分布算法不断涌现,但不同算法在面对海量化、多样化网络数据样本时的性能存在差异。基于此,从不同数据文本关联性、数据集资源的海量性角度出发,利用云计算Spark分布式架构、HDFS(Hadoop Distributed FileSystem)分布式文件系统、Spark SQL数据计算引擎、YARN(Yet Another Resource Negotiator)资源管理器等软件,建构起融合K-Means聚类算法、BIRCH(Balanced Iterative Reducing and Clustering using Hierarchies)聚类算法的数据挖掘模型,根据CF树聚类的判别函数确定被测试数据集的类别,由Spark计算模型将完成聚类的数据集分布式缓存至网络节点内存中,以实现对海量化网络数据的挖掘、聚类及存储操作。展开更多
基金in part by National Undergraduate Innovation and Entrepreneurship Training Program under Grant No.202310347039Zhejiang Provincial Natural Science Foundation of China under Grant No.LZ22F020002Huzhou Science and Technology Planning Foundation under Grant No.2023GZ04.
文摘The Internet of Things(IoT)has characteristics such as node mobility,node heterogeneity,link heterogeneity,and topology heterogeneity.In the face of the IoT characteristics and the explosive growth of IoT nodes,which brings about large-scale data processing requirements,edge computing architecture has become an emerging network architecture to support IoT applications due to its ability to provide powerful computing capabilities and good service functions.However,the defense mechanism of Edge Computing-enabled IoT Nodes(ECIoTNs)is still weak due to their limited resources,so that they are susceptible to malicious software spread,which can compromise data confidentiality and network service availability.Facing this situation,we put forward an epidemiology-based susceptible-curb-infectious-removed-dead(SCIRD)model.Then,we analyze the dynamics of ECIoTNs with different infection levels under different initial conditions to obtain the dynamic differential equations.Additionally,we establish the presence of equilibrium states in the SCIRD model.Furthermore,we conduct an analysis of the model’s stability and examine the conditions under which malicious software will either spread or disappear within Edge Computing-enabled IoT(ECIoT)networks.Lastly,we validate the efficacy and superiority of the SCIRD model through MATLAB simulations.These research findings offer a theoretical foundation for suppressing the propagation of malicious software in ECIoT networks.The experimental results indicate that the theoretical SCIRD model has instructive significance,deeply revealing the principles of malicious software propagation in ECIoT networks.This study solves a challenging security problem of ECIoT networks by determining the malicious software propagation threshold,which lays the foundation for buildingmore secure and reliable ECIoT networks.
文摘目的:通过Meta分析研究早产儿低血糖的危险因素。方法:计算机检索中国知网、中国生物医学文献数据库、万方数据库、维普数据库、PubMed、Web of Science、EMbase、the Cochrane Library,检索时限为建库至2023年12月22日,计算合并各危险因素的比值比(OR)值及其95%置信区间(CI)。结果:共纳入10篇文献,涉及4564例病人,共合并11个变量。Meta分析结果显示,母亲患糖尿病(OR=2.24)、母亲患胰岛素依赖型糖尿病(OR=3.41)、母亲患高血压(OR=1.86)、剖宫产(OR=1.79)、早产儿性别(男)(OR=2.74)、小于胎龄儿(OR=2.16)、早产儿窒息(OR=5.27)为早产儿低血糖的危险因素;产前使用硫酸镁(OR=0.43)、阴道分娩(OR=0.44)为早产儿低血糖的保护因素。结论:现有证据表明,医务人员应对母亲患有糖尿病,尤其是胰岛素依赖型糖尿病、母亲患高血压、选择剖宫产分娩、小于胎龄儿、有窒息等情况的早产儿予以高度重视,并制定个性化预防策略,以减少低血糖的发生。
基金National Natural Science Foundation of China(No.81303095)Tianjin Graduate Student Research and Innovation Project(YJSKC-20231031).
文摘Objective:To investigate the causal relationship between blood metabolite levels and the occurrence of prostate cancer by using two-sample Mendelian randomization method.Methods:Pooled data from public databases for genome-wide association analyses of blood metabolites and prostate cancer were selected,and inverse variance weighting(IVW)was used as the primary method for estimating the causal effects,while heterogeneity tests,gene multiplicity tests and sensitivity analyses were performed to assess the stability and reliability of the results.Results:A total of six known metabolites were found to potentially increase the risk of prostate cancer development(P<0.05),namely fructose,allantoin,5-hydroxytryptophan,potassium ketoisocaproate,glycyltryptophan,and 1-heptadecanoyl-glycerol-3-phosphorylcholine,with no heterogeneity or genetic pleiotropy found.Conclusion:Six known blood metabolites may be potential risk factors for prostate cancer development in European populations.
文摘近年来大数据及云计算技术、人工智能技术的发展,使得K-Means聚类算法、DBSCAN聚类算法、BIRCH聚类算法、Cluster数据分布算法不断涌现,但不同算法在面对海量化、多样化网络数据样本时的性能存在差异。基于此,从不同数据文本关联性、数据集资源的海量性角度出发,利用云计算Spark分布式架构、HDFS(Hadoop Distributed FileSystem)分布式文件系统、Spark SQL数据计算引擎、YARN(Yet Another Resource Negotiator)资源管理器等软件,建构起融合K-Means聚类算法、BIRCH(Balanced Iterative Reducing and Clustering using Hierarchies)聚类算法的数据挖掘模型,根据CF树聚类的判别函数确定被测试数据集的类别,由Spark计算模型将完成聚类的数据集分布式缓存至网络节点内存中,以实现对海量化网络数据的挖掘、聚类及存储操作。
