As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly ess...As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional(ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated.The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.展开更多
Objective：To investigate the influences of urapidil and nicardipine on rabbit sinus function, atrio-ventricular node function and hemodynamics. Methods：Thirty-two Angora＇ s rabbits were selected and randomly divide...Objective：To investigate the influences of urapidil and nicardipine on rabbit sinus function, atrio-ventricular node function and hemodynamics. Methods：Thirty-two Angora＇ s rabbits were selected and randomly divided into four groups. U1 group：urapidil 0.25 mg/kg; U2 group：urapidil 0.5 mg/kg; N1 group：nicardipine 10 μg/kg; N2 group： nicardipine 20 μg/kg. All these medicine were administrated within 30 seconds. Measurements were taken before and after the administration of urapidil or nicardipine for the following data： mean blood pressure（MAP）, heart rate（HR）, sino-atrial conduction time（SACT）, maximal sinoatrial recovery time（SNRTmax） corrected sinus node recovery time（CSNRT）, index of sinus node recovery time（SNRTI）, Wenckebach A-V conduction frequency （WB）, and P-R interval. Results：Significant MAP and HR changes were identified in all of the four groups before and after administration of both urapidil and nicardipine. No significant changes could be found in the rest of the parameters. Intergroup analysis showed that SACT and CSNRT of N1 and N2 groups were shorter than those of the U2 group（P 〈 0.01）; the MAP decreased（P 〈 0.01） and the HR increased drastically（P〈 0.01）. Conclusions：Neither urapidil（0.25 mg/kg, 0,5 mg/kg） nor nicardipine（10 μg/kg, 20 μg/kg） has any significant influence on rabbit sinus function or rabbit atrio-ventricular node function. Nicardipine could be a better choice than urapidil for parafunctional sinus node patients.展开更多
In this letter, a Function node-based Multiple Pairwise Keys Management (MPKMF) protocol for Wireless Sensor Networks (WSNs) is firstly designed, in which ordinary nodes and cluster head nodes are responsible for data...In this letter, a Function node-based Multiple Pairwise Keys Management (MPKMF) protocol for Wireless Sensor Networks (WSNs) is firstly designed, in which ordinary nodes and cluster head nodes are responsible for data collection and transmission, and function nodes are responsible for key management. There are more than one function nodes in the cluster consulting the key generation and other security decision-making. The function nodes are the second-class security center because of the characteristics of the distributed WSNs. Secondly, It is also described that the formation of function nodes and cluster heads under the control of the former, and five kinds of keys, i.e., individual key, pairwise keys, cluster key, management key, and group key. Finally, performance analysis and experiments show that, the protocol is superior in communication and energy consumption. The delay of establishing the cluster key meets the requirements, and a multiple pairwise key which adopts the coordinated security authentication scheme is provided.展开更多
In this paper we propose a collocation method for solving Lane-Emden type equation which is nonlinear or-dinary differential equation on the semi-infinite domain. This equation is categorized as singular initial value...In this paper we propose a collocation method for solving Lane-Emden type equation which is nonlinear or-dinary differential equation on the semi-infinite domain. This equation is categorized as singular initial value problems. We solve this equation by the generalized Laguerre polynomial collocation method based on Her-mite-Gauss nodes. This method solves the problem on the semi-infinite domain without truncating it to a fi-nite domain and transforming domain of the problem to a finite domain. In addition, this method reduces so-lution of the problem to solution of a system of algebraic equations.展开更多
Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representativ...Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.展开更多
A Coupling Magneto-Electro-Elastic(MEE)Node-based Smoothed Radial Point Interpolation Method(CM-NS-RPIM)was proposed to solve the free vibration and transient responses of Functionally Graded Magneto-Electro-Elastic(F...A Coupling Magneto-Electro-Elastic(MEE)Node-based Smoothed Radial Point Interpolation Method(CM-NS-RPIM)was proposed to solve the free vibration and transient responses of Functionally Graded Magneto-Electro-Elastic(FGMEE)structures.By introducing the modified Newmark method,the displacement,electrical potential and magnetic potential of the structures under transient mechanical loading were obtained.Based on G space theory and the weakened weak(W2)formulation,the equations of the multi-physics coupling problems were derived.Using triangular background elements,the free vibration and transient responses of three numerical examples were studied.Results proved that CM-NS-RPIM performed better than the standard FEM by reducing the overly-stiff of structures.Moreover,CM-NS-RPIM could reduce the number of nodes while guaranteeing the accuracy.Besides,triangular elements could be generated automatically even for complex geometries.Therefore,the effectiveness and validity of CM-NS-RPIM were demonstrated,which were valuable for the design of intelligence devices,such as energy harvesters and sensors.展开更多
In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation ...In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.展开更多
针对无线和电力线通信混合组网的信道竞争接入问题,提出了一种基于深度强化学习的电力线与无线双模通信的MAC接入算法。双模节点根据网络广播信息和信道使用等数据自适应接入双媒质信道。首先建立了基于双模通信网络交互和统计信息的双...针对无线和电力线通信混合组网的信道竞争接入问题,提出了一种基于深度强化学习的电力线与无线双模通信的MAC接入算法。双模节点根据网络广播信息和信道使用等数据自适应接入双媒质信道。首先建立了基于双模通信网络交互和统计信息的双模通信节点数据采集模型;接着定义了基于协作信息的深度强化学习(deep reinforcement learning,DRL)状态空间、动作空间和奖励,设计了联合α-公平效用函数和P坚持接入机制的节点决策流程,实现基于双深度Q网络(double deep Q-network,DDQN)的双模节点自适应接入算法;最后进行算法性能仿真和对比分析。仿真结果表明,提出的接入算法能够在保证双模网络和信道接入公平性的条件下,有效提高双模通信节点的接入性能。展开更多
目的探讨腔镜下不同手术入路甲状腺切除术对cN0期甲状腺乳头状癌(PTC)的手术效果。方法回顾性分析2019年8月—2022年11月于本院就诊并接受腔镜手术治疗的118例cN0期PTC患者的临床资料,根据腔镜下不同手术入路,分为胸乳组与经口组,应用...目的探讨腔镜下不同手术入路甲状腺切除术对cN0期甲状腺乳头状癌(PTC)的手术效果。方法回顾性分析2019年8月—2022年11月于本院就诊并接受腔镜手术治疗的118例cN0期PTC患者的临床资料,根据腔镜下不同手术入路,分为胸乳组与经口组,应用倾向性评分匹配法各纳入59例患者。比较两组围术期相关指标。结果经口组术后引流量、住院时长均少于胸乳组(P<0.05),而手术时间、中央区淋巴结清扫数目多于胸乳组(P<0.05);经口组术后12、24 h VAS评分均低于胸乳组(P<0.05);术后3 d,经口组吞咽功能优于胸乳组(P<0.05);术后3个月,经口组瘢痕评估量表评分低于胸乳组(P<0.05);随访1年,组间术后复发、无进展生存期比较无明显差异(P>0.05)。结论经胸乳入路腔镜术与经口腔前庭腔镜术治疗cN0期PTC整体疗效相当,但经口腔前庭入路腔镜术后恢复更快,更值得应用。展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 71971150)the Project of Research Center for System Sciences and Enterprise Development (Grant No. Xq16B05)the Fundamental Research Funds for the Central Universities of China (Grant No. SXYPY202313)。
文摘As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional(ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated.The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.
文摘Objective：To investigate the influences of urapidil and nicardipine on rabbit sinus function, atrio-ventricular node function and hemodynamics. Methods：Thirty-two Angora＇ s rabbits were selected and randomly divided into four groups. U1 group：urapidil 0.25 mg/kg; U2 group：urapidil 0.5 mg/kg; N1 group：nicardipine 10 μg/kg; N2 group： nicardipine 20 μg/kg. All these medicine were administrated within 30 seconds. Measurements were taken before and after the administration of urapidil or nicardipine for the following data： mean blood pressure（MAP）, heart rate（HR）, sino-atrial conduction time（SACT）, maximal sinoatrial recovery time（SNRTmax） corrected sinus node recovery time（CSNRT）, index of sinus node recovery time（SNRTI）, Wenckebach A-V conduction frequency （WB）, and P-R interval. Results：Significant MAP and HR changes were identified in all of the four groups before and after administration of both urapidil and nicardipine. No significant changes could be found in the rest of the parameters. Intergroup analysis showed that SACT and CSNRT of N1 and N2 groups were shorter than those of the U2 group（P 〈 0.01）; the MAP decreased（P 〈 0.01） and the HR increased drastically（P〈 0.01）. Conclusions：Neither urapidil（0.25 mg/kg, 0,5 mg/kg） nor nicardipine（10 μg/kg, 20 μg/kg） has any significant influence on rabbit sinus function or rabbit atrio-ventricular node function. Nicardipine could be a better choice than urapidil for parafunctional sinus node patients.
基金Supported by the National Natural Science Foundation of China (No. 60475012)
文摘In this letter, a Function node-based Multiple Pairwise Keys Management (MPKMF) protocol for Wireless Sensor Networks (WSNs) is firstly designed, in which ordinary nodes and cluster head nodes are responsible for data collection and transmission, and function nodes are responsible for key management. There are more than one function nodes in the cluster consulting the key generation and other security decision-making. The function nodes are the second-class security center because of the characteristics of the distributed WSNs. Secondly, It is also described that the formation of function nodes and cluster heads under the control of the former, and five kinds of keys, i.e., individual key, pairwise keys, cluster key, management key, and group key. Finally, performance analysis and experiments show that, the protocol is superior in communication and energy consumption. The delay of establishing the cluster key meets the requirements, and a multiple pairwise key which adopts the coordinated security authentication scheme is provided.
文摘In this paper we propose a collocation method for solving Lane-Emden type equation which is nonlinear or-dinary differential equation on the semi-infinite domain. This equation is categorized as singular initial value problems. We solve this equation by the generalized Laguerre polynomial collocation method based on Her-mite-Gauss nodes. This method solves the problem on the semi-infinite domain without truncating it to a fi-nite domain and transforming domain of the problem to a finite domain. In addition, this method reduces so-lution of the problem to solution of a system of algebraic equations.
文摘Purpose: Brain functional networks (BFNs) has become important approach for diagnosis of some neurological or psychological disorders. Before estimating BFN, obtaining blood oxygen level dependent (BOLD) representative signals from brain regions of interest (ROIs) is important. In the past decades, the common method is generally to take a ROI as a node, averaging all the voxel time series inside it to extract a representative signal. However, one node does not represent the entire information of this ROI, and averaging method often leads to signal cancellation and information loss. Inspired by this, we propose a novel model extraction method based on an assumption that a ROI can be represented by multiple nodes. Methods: In this paper, we first extract multiple nodes (the number is user-defined) from the ROI based on two traditional methods, including principal component analysis (PCA), and K-means (Clustering according to the spatial position of voxels). Then, canonical correlation analysis (CCA) was issued to construct BFNs by maximizing the correlation between the representative signals corresponding to the nodes in any two ROIs. Finally, to further verify the effectiveness of the proposed method, the estimated BFNs are applied to identify subjects with autism spectrum disorder (ASD) and mild cognitive impairment (MCI) from health controls (HCs). Results: Experimental results on two benchmark databases demonstrate that the proposed method outperforms the baseline method in the sense of classification performance. Conclusions: We propose a novel method for obtaining nodes of ROId based on the hypothesis that a ROI can be represented by multiple nodes, that is, to extract the node signals of ROIs with K-means or PCA. Then, CCA is used to construct BFNs.
基金co-supported by the National Key R&D Program of China(Nos.2018YFF01012401-05)the National Natural Science Foundation of China(No.51975243)+2 种基金Jilin Provincial Department of Education(No.JJKH20180084KJ),Chinathe Fundamental Research Funds for the Central Universities and Jilin Provincial Department of Science&Technology Fund Project,China(Nos.20170101043JC and 20180520072JH)Graduate Innovation Fund of Jilin University,China(No.101832018C184).
文摘A Coupling Magneto-Electro-Elastic(MEE)Node-based Smoothed Radial Point Interpolation Method(CM-NS-RPIM)was proposed to solve the free vibration and transient responses of Functionally Graded Magneto-Electro-Elastic(FGMEE)structures.By introducing the modified Newmark method,the displacement,electrical potential and magnetic potential of the structures under transient mechanical loading were obtained.Based on G space theory and the weakened weak(W2)formulation,the equations of the multi-physics coupling problems were derived.Using triangular background elements,the free vibration and transient responses of three numerical examples were studied.Results proved that CM-NS-RPIM performed better than the standard FEM by reducing the overly-stiff of structures.Moreover,CM-NS-RPIM could reduce the number of nodes while guaranteeing the accuracy.Besides,triangular elements could be generated automatically even for complex geometries.Therefore,the effectiveness and validity of CM-NS-RPIM were demonstrated,which were valuable for the design of intelligence devices,such as energy harvesters and sensors.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.62373197 and 61873326)。
文摘In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.
文摘针对无线和电力线通信混合组网的信道竞争接入问题,提出了一种基于深度强化学习的电力线与无线双模通信的MAC接入算法。双模节点根据网络广播信息和信道使用等数据自适应接入双媒质信道。首先建立了基于双模通信网络交互和统计信息的双模通信节点数据采集模型;接着定义了基于协作信息的深度强化学习(deep reinforcement learning,DRL)状态空间、动作空间和奖励,设计了联合α-公平效用函数和P坚持接入机制的节点决策流程,实现基于双深度Q网络(double deep Q-network,DDQN)的双模节点自适应接入算法;最后进行算法性能仿真和对比分析。仿真结果表明,提出的接入算法能够在保证双模网络和信道接入公平性的条件下,有效提高双模通信节点的接入性能。
文摘目的探讨腔镜下不同手术入路甲状腺切除术对cN0期甲状腺乳头状癌(PTC)的手术效果。方法回顾性分析2019年8月—2022年11月于本院就诊并接受腔镜手术治疗的118例cN0期PTC患者的临床资料,根据腔镜下不同手术入路,分为胸乳组与经口组,应用倾向性评分匹配法各纳入59例患者。比较两组围术期相关指标。结果经口组术后引流量、住院时长均少于胸乳组(P<0.05),而手术时间、中央区淋巴结清扫数目多于胸乳组(P<0.05);经口组术后12、24 h VAS评分均低于胸乳组(P<0.05);术后3 d,经口组吞咽功能优于胸乳组(P<0.05);术后3个月,经口组瘢痕评估量表评分低于胸乳组(P<0.05);随访1年,组间术后复发、无进展生存期比较无明显差异(P>0.05)。结论经胸乳入路腔镜术与经口腔前庭腔镜术治疗cN0期PTC整体疗效相当,但经口腔前庭入路腔镜术后恢复更快,更值得应用。
