The highly conserved human leukocyte antigen-A2(HLA-A2)-restricted epitope NS3-1073 represents a promising candidate for a therapeutic vaccine against hepatitis C virus(HCV).In this study,we engineered a set of fusion...The highly conserved human leukocyte antigen-A2(HLA-A2)-restricted epitope NS3-1073 represents a promising candidate for a therapeutic vaccine against hepatitis C virus(HCV).In this study,we engineered a set of fusion proteins based on the artificial self-assembling peptide(SAP),which were expressed in Escherichia coli and spontaneously self-assembled into nanosized particles displaying HCV epitopes,including NS3-1073.To enhance immunogenicity,we incorporated the T helper epitope PADRE into the construct.Alpha-helical linkers were introduced between SAP and the epitopes to facilitate proper protein folding.Notably,a helical linker with a high supercoiling propensity enabled soluble expression of the fusion protein containing both the NS3-1073 and PADRE epitopes,allowing purification of the in vivo-formed nanoparticles by metal affinity chromatography.Human dendritic cells derived from peripheral blood monocytes showed robust activation in response to the fusion proteins and preferentially stimulated T lymphocytes toward a Th1-biased immune response.In mice,immunization with nanoparticles carrying NS3-1073 induced splenocyte proliferation in response to in vitro stimulation with a mixture of NS3 peptides.These results demonstrate that recombinant nanoparticle-based carriers presenting the NS3-1073 epitope can be produced in bacterial systems and hold strong potential as a foundation for a therapeutic HCV vaccine.展开更多
软件定义自组网(Software Defined Mobile Ad Hoc Network,SD-MANET)融合了软件定义网络(Software Defined Network,SDN)集中控制优势和移动自组网(Mobile Ad Hoc Network,MANET)的动态组网优势,但Mininet等现有仿真平台在动态拓扑与扩...软件定义自组网(Software Defined Mobile Ad Hoc Network,SD-MANET)融合了软件定义网络(Software Defined Network,SDN)集中控制优势和移动自组网(Mobile Ad Hoc Network,MANET)的动态组网优势,但Mininet等现有仿真平台在动态拓扑与扩展性等方面存在显著局限,严重制约了其关键算法的研究。针对这一问题,提出基于网络模拟器-3(Network Simulator-3,NS-3)的仿真平台NS3-SDMANET,具体工作包括:基于NS-3框架实现了SD-MANET网络层关键特性的仿真;基于远程过程调用对平台功能进行封装,并提供可编程接口。战术网的测试案例表明:NS3-SDMANET在SD-MANET网络层关键特性仿真方面表现优异,能够有效支撑SD-MANET网络层算法的高效验证与性能评估,为相关研究提供了高扩展性的基础仿真环境。展开更多
GNSS信号丢失会导致GNSS/I NS组合导航系统定位失准甚至失效,而现有辅助模型仍存在不足。针对这一问题,本文提出了一种基于遗传算法(GA)优化E l man神经网络的车辆辅助组合导航算法。首先,使用小波阈值去噪算法降低惯导系统测量数据的噪...GNSS信号丢失会导致GNSS/I NS组合导航系统定位失准甚至失效,而现有辅助模型仍存在不足。针对这一问题,本文提出了一种基于遗传算法(GA)优化E l man神经网络的车辆辅助组合导航算法。首先,使用小波阈值去噪算法降低惯导系统测量数据的噪声,然后再使用GA优化E l man神经网络的权重和结构参数,以提高模型的预测精度和泛化能力。其次,构建基于GA-E l man神经网络的车辆辅助导航模型。该模型将系统分为两种模式,在GNSS信号正常时进入训练模式进行在线训练;当GNSS信号丢失后系统变为纯惯导模式,此时启用训练好的模型接收惯导系统的数据进行实时解算和预测。最后,跑车实验结果表明,与PSO-BPNN辅助模型和E l man辅助模型相比,本文所提出算法的定位精度得到有效提升。展开更多
Railway safety and efficiency increasingly rely on precise train positioning. The integration of the Global Navigation Satellite System (GNSS) into railway control systems aims to reduce dependence on track-side infra...Railway safety and efficiency increasingly rely on precise train positioning. The integration of the Global Navigation Satellite System (GNSS) into railway control systems aims to reduce dependence on track-side infrastructure. While GNSS has significantly improved train localization, challenges such as the susceptibility to jamming remain. To address this, this paper introduces an Inertial Navigation System (INS)-aided train positioning system based on deep integration, exploring its performance through semi-physical experiments and simulations. Experimental results demonstrate that the proposed solution is able to reduce the positioning error by 63.47%, and the velocity error by 58.47% under jamming conditions. The study highlights the potential of deep integration for improving the resilience of GNSS-based train control systems, especially in the face of Radio Frequency (RF) jamming threats.展开更多
基金supported by the Russian Science Foundation(Grant No.24-25-20087 to V.K.)。
文摘The highly conserved human leukocyte antigen-A2(HLA-A2)-restricted epitope NS3-1073 represents a promising candidate for a therapeutic vaccine against hepatitis C virus(HCV).In this study,we engineered a set of fusion proteins based on the artificial self-assembling peptide(SAP),which were expressed in Escherichia coli and spontaneously self-assembled into nanosized particles displaying HCV epitopes,including NS3-1073.To enhance immunogenicity,we incorporated the T helper epitope PADRE into the construct.Alpha-helical linkers were introduced between SAP and the epitopes to facilitate proper protein folding.Notably,a helical linker with a high supercoiling propensity enabled soluble expression of the fusion protein containing both the NS3-1073 and PADRE epitopes,allowing purification of the in vivo-formed nanoparticles by metal affinity chromatography.Human dendritic cells derived from peripheral blood monocytes showed robust activation in response to the fusion proteins and preferentially stimulated T lymphocytes toward a Th1-biased immune response.In mice,immunization with nanoparticles carrying NS3-1073 induced splenocyte proliferation in response to in vitro stimulation with a mixture of NS3 peptides.These results demonstrate that recombinant nanoparticle-based carriers presenting the NS3-1073 epitope can be produced in bacterial systems and hold strong potential as a foundation for a therapeutic HCV vaccine.
文摘软件定义自组网(Software Defined Mobile Ad Hoc Network,SD-MANET)融合了软件定义网络(Software Defined Network,SDN)集中控制优势和移动自组网(Mobile Ad Hoc Network,MANET)的动态组网优势,但Mininet等现有仿真平台在动态拓扑与扩展性等方面存在显著局限,严重制约了其关键算法的研究。针对这一问题,提出基于网络模拟器-3(Network Simulator-3,NS-3)的仿真平台NS3-SDMANET,具体工作包括:基于NS-3框架实现了SD-MANET网络层关键特性的仿真;基于远程过程调用对平台功能进行封装,并提供可编程接口。战术网的测试案例表明:NS3-SDMANET在SD-MANET网络层关键特性仿真方面表现优异,能够有效支撑SD-MANET网络层算法的高效验证与性能评估,为相关研究提供了高扩展性的基础仿真环境。
文摘GNSS信号丢失会导致GNSS/I NS组合导航系统定位失准甚至失效,而现有辅助模型仍存在不足。针对这一问题,本文提出了一种基于遗传算法(GA)优化E l man神经网络的车辆辅助组合导航算法。首先,使用小波阈值去噪算法降低惯导系统测量数据的噪声,然后再使用GA优化E l man神经网络的权重和结构参数,以提高模型的预测精度和泛化能力。其次,构建基于GA-E l man神经网络的车辆辅助导航模型。该模型将系统分为两种模式,在GNSS信号正常时进入训练模式进行在线训练;当GNSS信号丢失后系统变为纯惯导模式,此时启用训练好的模型接收惯导系统的数据进行实时解算和预测。最后,跑车实验结果表明,与PSO-BPNN辅助模型和E l man辅助模型相比,本文所提出算法的定位精度得到有效提升。
基金supported by the Beijing Natural Science Foundation(4232031)the National Natural Science Foundation of China(T2222015,U2268206).
文摘Railway safety and efficiency increasingly rely on precise train positioning. The integration of the Global Navigation Satellite System (GNSS) into railway control systems aims to reduce dependence on track-side infrastructure. While GNSS has significantly improved train localization, challenges such as the susceptibility to jamming remain. To address this, this paper introduces an Inertial Navigation System (INS)-aided train positioning system based on deep integration, exploring its performance through semi-physical experiments and simulations. Experimental results demonstrate that the proposed solution is able to reduce the positioning error by 63.47%, and the velocity error by 58.47% under jamming conditions. The study highlights the potential of deep integration for improving the resilience of GNSS-based train control systems, especially in the face of Radio Frequency (RF) jamming threats.
