Sanjiao acupuncture and HuangDiSan can promote the proliferation, migration and differentiation of exogenous neural stem cells in senescence-accelerated mouse prone 8 （SAMP8） mice and can improve learning and memory...Sanjiao acupuncture and HuangDiSan can promote the proliferation, migration and differentiation of exogenous neural stem cells in senescence-accelerated mouse prone 8 （SAMP8） mice and can improve learning and memory impairment and behavioral function in dementia-model mice. Thus, we sought to determine whether Sanjiao acupuncture and HuangDiSan can elevate the effect of neural stem cell transplantation in Alzheimer’s disease model mice. Sanjiao acupuncture was used to stimulate Danzhong （CV17）, Zhongwan （CV12）,Qihai （CV6）, bilateral Xuehai （SP10） and bilateral Zusanli （ST36） 15 days before and after implantation of neural stem cells （5 × 10^5） into the hippocampal dentate gyrus of SAMP8 mice. Simultaneously, 0.2 mL HuangDiSan, containing Rehmannia Root and Chinese Angelica,was intragastrically administered. Our results demonstrated that compared with mice undergoing neural stem cell transplantation alone,learning ability was significantly improved and synaptophysin mRNA and protein levels were greatly increased in the hippocampus of mice undergoing both Sanjiao acupuncture and intragastric administration of HuangDiSan. We conclude that the combination of Sanjiao acupuncture and HuangDiSan can effectively improve dementia symptoms in mice, and the mechanism of this action might be related to the regulation of synaptophysin expression.展开更多
Aged populations have remarkable variability in recent memory and cognitive mapping. Although some individuals may have substantial age-related impairments, others perform almost as well as young individuals. This pap...Aged populations have remarkable variability in recent memory and cognitive mapping. Although some individuals may have substantial age-related impairments, others perform almost as well as young individuals. This paper reviews the relevant data on aged rats and indicates two challenges for biomarkers of aging. The first is to provide an appropriate quantitative description of these individual differences. The second is to use them effectively as markers for age-related changes in psychological functions and their neural substrates.展开更多
With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recogn...With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.展开更多
By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in g...By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in generalized sense is obtained. This result reported has an important guide to concrete neural network designs.展开更多
现有5G(5th GenerationMobile Communication Technology)核心网异常检测主要基于信令流量深度解析,但较少利用核心网网络功能交互关系的作用。针对上述问题,提出一种基于交互的5G核心网网络功能异常检测模型。首先,该模型以行为分析为...现有5G(5th GenerationMobile Communication Technology)核心网异常检测主要基于信令流量深度解析,但较少利用核心网网络功能交互关系的作用。针对上述问题,提出一种基于交互的5G核心网网络功能异常检测模型。首先,该模型以行为分析为驱动,基于信令流量和网络功能注册数据提取多维属性,通过行为画像来表征网络功能行为模式,并采用集成学习算法RFECV(Recursive Feature Elimination with Cross-Validation)进行属性特征选择,降低特征维度的同时筛选出与区分网络功能行为模式高度相关的属性特征。然后,模型基于网络功能交互关系对核心网进行图建模,建模后的图数据融合了网络功能属性信息和交互信息。最后,模型通过基于空间域的图卷积网络聚合邻域节点属性信息和结构信息来融合行为模式特征,新生成的节点表示用于分类,从而将核心网网络功能异常检测问题转化为图节点分类问题。通过在free5GC仿真平台上采集数据,并在搭建的异常检测系统中的实验表明,该模型的异常检测性能优于基于属性特征分析的传统机器学习模型、基于结构特征分析的图嵌入模型及部分5G核心网异常检测模型。10%数据集作为训练集时,所提模型的准确率比支持向量机模型提高6.6%,比Struc2vec模型提高13%,比深度神经网络模型提高8%。展开更多
基金supported by the National Natural Science Foundation of China,No.81202740 and 81603686the Natural Science Foundation of Tianjin of China,No.17JCYBJC26200 and 12JCQNJC07400+1 种基金the Public Health Bureau Science and Technology Foundation of Tianjin of China,No.2014KY15the Specialized Research Foundation for the Doctoral Program of Higher Education,No.20121210120002
文摘Sanjiao acupuncture and HuangDiSan can promote the proliferation, migration and differentiation of exogenous neural stem cells in senescence-accelerated mouse prone 8 （SAMP8） mice and can improve learning and memory impairment and behavioral function in dementia-model mice. Thus, we sought to determine whether Sanjiao acupuncture and HuangDiSan can elevate the effect of neural stem cell transplantation in Alzheimer’s disease model mice. Sanjiao acupuncture was used to stimulate Danzhong （CV17）, Zhongwan （CV12）,Qihai （CV6）, bilateral Xuehai （SP10） and bilateral Zusanli （ST36） 15 days before and after implantation of neural stem cells （5 × 10^5） into the hippocampal dentate gyrus of SAMP8 mice. Simultaneously, 0.2 mL HuangDiSan, containing Rehmannia Root and Chinese Angelica,was intragastrically administered. Our results demonstrated that compared with mice undergoing neural stem cell transplantation alone,learning ability was significantly improved and synaptophysin mRNA and protein levels were greatly increased in the hippocampus of mice undergoing both Sanjiao acupuncture and intragastric administration of HuangDiSan. We conclude that the combination of Sanjiao acupuncture and HuangDiSan can effectively improve dementia symptoms in mice, and the mechanism of this action might be related to the regulation of synaptophysin expression.
文摘Aged populations have remarkable variability in recent memory and cognitive mapping. Although some individuals may have substantial age-related impairments, others perform almost as well as young individuals. This paper reviews the relevant data on aged rats and indicates two challenges for biomarkers of aging. The first is to provide an appropriate quantitative description of these individual differences. The second is to use them effectively as markers for age-related changes in psychological functions and their neural substrates.
文摘With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.
文摘By establishing concept an transient solutions of general nonlinear systems converging to its equilibrium set, long-time behavior of solutions for cellular neural network systems is studied. A stability condition in generalized sense is obtained. This result reported has an important guide to concrete neural network designs.
文摘现有5G(5th GenerationMobile Communication Technology)核心网异常检测主要基于信令流量深度解析,但较少利用核心网网络功能交互关系的作用。针对上述问题,提出一种基于交互的5G核心网网络功能异常检测模型。首先,该模型以行为分析为驱动,基于信令流量和网络功能注册数据提取多维属性,通过行为画像来表征网络功能行为模式,并采用集成学习算法RFECV(Recursive Feature Elimination with Cross-Validation)进行属性特征选择,降低特征维度的同时筛选出与区分网络功能行为模式高度相关的属性特征。然后,模型基于网络功能交互关系对核心网进行图建模,建模后的图数据融合了网络功能属性信息和交互信息。最后,模型通过基于空间域的图卷积网络聚合邻域节点属性信息和结构信息来融合行为模式特征,新生成的节点表示用于分类,从而将核心网网络功能异常检测问题转化为图节点分类问题。通过在free5GC仿真平台上采集数据,并在搭建的异常检测系统中的实验表明,该模型的异常检测性能优于基于属性特征分析的传统机器学习模型、基于结构特征分析的图嵌入模型及部分5G核心网异常检测模型。10%数据集作为训练集时,所提模型的准确率比支持向量机模型提高6.6%,比Struc2vec模型提高13%,比深度神经网络模型提高8%。
