目的探讨IQSEC1是否通过病毒蛋白PB1调控甲型流感病毒的增殖。方法首先克隆甲型流感病毒[A/Shanghai/02/2013(H7N9)]的8个基因;其次,通过免疫共沉淀检测IQ模体Sec7结构域蛋白1(IQSEC1)与聚合酶PB1(PB1)存在相互作用;此外,通过过表达或...目的探讨IQSEC1是否通过病毒蛋白PB1调控甲型流感病毒的增殖。方法首先克隆甲型流感病毒[A/Shanghai/02/2013(H7N9)]的8个基因;其次,通过免疫共沉淀检测IQ模体Sec7结构域蛋白1(IQSEC1)与聚合酶PB1(PB1)存在相互作用;此外,通过过表达或者敲低IQSEC1的方法检测IQSEC1对PB1核定位的影响;最后,过表达或者敲低IQSEC1后检测Influenza A virus[A/Shanghai/02/2013(H7N9)]。结果病毒感染条件下,外源IQSEC1和PB1存在相互作用。当过表达IQSEC1时,细胞中IQSEC1的表达量上升,相应的PB1在细胞核中的定位减少;当用敲低IQSEC1时,细胞中IQSEC1的表达量下降,相应的PB1在细胞核中的定位上升。过表达IQSEC1后,甲型流感病毒的增殖水平下降(P<0.05)。敲低IQSEC1后,甲型流感病毒的增殖水平上升(P<0.05)。结论IQSEC1通过减少甲型流感病毒蛋白PB1的核定位抑制甲型流感病毒的增殖。展开更多
Structural shape monitoring plays a vital role in the structural health monitoring systems.The inverse finite element method(iFEM)has been demonstrated to be a practical method of deformation reconstruction owing to i...Structural shape monitoring plays a vital role in the structural health monitoring systems.The inverse finite element method(iFEM)has been demonstrated to be a practical method of deformation reconstruction owing to its unique advantages.Current iFEM formulations have been applied to small deformation of structures based on the small-displacement assumption of linear theory.However,this assumption may be inapplicable to some structures with large displacements in practical applications.Therefore,geometric nonlinearity needs to be considered.In this study,to expand the practical utility of iFEM for large displacement monitoring,we propose a nonlinear iFEM algorithm based on a four-node inverse quadrilateral shell element iQS4.Taking the advantage of an iterative iFEM algorithm,a nonlinear response is linearized to compute the geometrically nonlinear deformation reconstruction,like the basic concept of nonlinear FE analysis.Several examples are solved to verify the proposed approach.It is demonstrated that large displacements can be accurately estimated even if the in-situ sensor data includes different levels of randomly generated noise.It is proven that the nonlinear iFEM algorithm provides a more accurate displacement response as compared to the linear iFEM methodology for structures undergoing large displacement.Hence,the proposed approach can be utilized as a viable tool to effectively characterize geometrically nonlinear deformations of structures in real-time applications.展开更多
目前应用于辐射源识别的卷积神经网络对时序同相正交(in-phase and quadrature-phase,IQ)信号的处理有两种方式:一种方式是将其变换为图像,另一种方式是提取IQ时序数据的浅层特征。前一种方式会导致算法计算量大,而后一种方式会导致识...目前应用于辐射源识别的卷积神经网络对时序同相正交(in-phase and quadrature-phase,IQ)信号的处理有两种方式:一种方式是将其变换为图像,另一种方式是提取IQ时序数据的浅层特征。前一种方式会导致算法计算量大,而后一种方式会导致识别准确率低。针对上述问题,提出一种多尺度特征提取与特征选择网络。该网络以IQ信号为输入,经多尺度特征提取网络提取IQ信号的浅层特征和多尺度特征,采用特征选择网络降低多尺度特征的数据维度,通过自适应线性整流单元实现特征增强,使用单个全连接层对辐射源进行分类。在FIT/CorteXlab射频指纹识别数据集上,与ORACLE、CNN-DLRF和IQCNet对比实验表明,所提网络在一定程度上提高了识别准确率,降低了计算量。展开更多
Music education has long been debated for its influence on children’s cognitive development,particularly regarding their thinking methods and adaptability.This article synthesizes research data to examine the cogniti...Music education has long been debated for its influence on children’s cognitive development,particularly regarding their thinking methods and adaptability.This article synthesizes research data to examine the cognitive benefits of music instruction,including increased IQ,language proficiency,memory,and attention.Traditional face-to-face training,while personalized and socially interactive,faces limitations such as budget constraints and accessibility.Modern digital platforms offer individualized learning paths with AI-driven feedback but may lack necessary interpersonal interaction.This paper proposes a hybrid approach to music education,integrating traditional and digital methods to maximize cognitive gains.Further research is recommended to explore the implementation of these integrated learning strategies in varied educational settings.展开更多
文摘目的探讨IQSEC1是否通过病毒蛋白PB1调控甲型流感病毒的增殖。方法首先克隆甲型流感病毒[A/Shanghai/02/2013(H7N9)]的8个基因;其次,通过免疫共沉淀检测IQ模体Sec7结构域蛋白1(IQSEC1)与聚合酶PB1(PB1)存在相互作用;此外,通过过表达或者敲低IQSEC1的方法检测IQSEC1对PB1核定位的影响;最后,过表达或者敲低IQSEC1后检测Influenza A virus[A/Shanghai/02/2013(H7N9)]。结果病毒感染条件下,外源IQSEC1和PB1存在相互作用。当过表达IQSEC1时,细胞中IQSEC1的表达量上升,相应的PB1在细胞核中的定位减少;当用敲低IQSEC1时,细胞中IQSEC1的表达量下降,相应的PB1在细胞核中的定位上升。过表达IQSEC1后,甲型流感病毒的增殖水平下降(P<0.05)。敲低IQSEC1后,甲型流感病毒的增殖水平上升(P<0.05)。结论IQSEC1通过减少甲型流感病毒蛋白PB1的核定位抑制甲型流感病毒的增殖。
基金supported by the NationalNatural Science Foundation of China(Grant No.11902253)the Fundamental Research Funds for the Central Universities of China.The authors are grateful for this support.
文摘Structural shape monitoring plays a vital role in the structural health monitoring systems.The inverse finite element method(iFEM)has been demonstrated to be a practical method of deformation reconstruction owing to its unique advantages.Current iFEM formulations have been applied to small deformation of structures based on the small-displacement assumption of linear theory.However,this assumption may be inapplicable to some structures with large displacements in practical applications.Therefore,geometric nonlinearity needs to be considered.In this study,to expand the practical utility of iFEM for large displacement monitoring,we propose a nonlinear iFEM algorithm based on a four-node inverse quadrilateral shell element iQS4.Taking the advantage of an iterative iFEM algorithm,a nonlinear response is linearized to compute the geometrically nonlinear deformation reconstruction,like the basic concept of nonlinear FE analysis.Several examples are solved to verify the proposed approach.It is demonstrated that large displacements can be accurately estimated even if the in-situ sensor data includes different levels of randomly generated noise.It is proven that the nonlinear iFEM algorithm provides a more accurate displacement response as compared to the linear iFEM methodology for structures undergoing large displacement.Hence,the proposed approach can be utilized as a viable tool to effectively characterize geometrically nonlinear deformations of structures in real-time applications.
文摘目前应用于辐射源识别的卷积神经网络对时序同相正交(in-phase and quadrature-phase,IQ)信号的处理有两种方式:一种方式是将其变换为图像,另一种方式是提取IQ时序数据的浅层特征。前一种方式会导致算法计算量大,而后一种方式会导致识别准确率低。针对上述问题,提出一种多尺度特征提取与特征选择网络。该网络以IQ信号为输入,经多尺度特征提取网络提取IQ信号的浅层特征和多尺度特征,采用特征选择网络降低多尺度特征的数据维度,通过自适应线性整流单元实现特征增强,使用单个全连接层对辐射源进行分类。在FIT/CorteXlab射频指纹识别数据集上,与ORACLE、CNN-DLRF和IQCNet对比实验表明,所提网络在一定程度上提高了识别准确率,降低了计算量。
文摘Music education has long been debated for its influence on children’s cognitive development,particularly regarding their thinking methods and adaptability.This article synthesizes research data to examine the cognitive benefits of music instruction,including increased IQ,language proficiency,memory,and attention.Traditional face-to-face training,while personalized and socially interactive,faces limitations such as budget constraints and accessibility.Modern digital platforms offer individualized learning paths with AI-driven feedback but may lack necessary interpersonal interaction.This paper proposes a hybrid approach to music education,integrating traditional and digital methods to maximize cognitive gains.Further research is recommended to explore the implementation of these integrated learning strategies in varied educational settings.
