The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles（IOV...The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles（IOV） and community discovery of complex networks. The communities in complex network model of traffic flow reflect the local aggregation of vehicles in the traffic system, and it is used to predict the upcoming congestion. The real-time information of vehicles on the roads is obtained from the IOV, which includes the locations, speeds and orientations of vehicles. Then the vehicles are mapped into nodes of network, the links between nodes are determined by the correlations between vehicles in terms of location and speed. The complex network model of traffic flow is hereby established. The communities in this complex network are discovered by fast Newman（FN） algorithm, and the congestion warnings are generated according to the communities selected by scale and density. This method can detect the tendency of traffic aggregation and provide warnings before congestion occurs. The simulations show that the method proposed in this paper is effective and practicable, and makes it possible to take action before traffic congestion.展开更多
In this paper,cluster synchronization of fractionalorder complex community networks(FOCCNs)in quaternionvalued filed is addressed based on the non-separation approach.To carry out tasks with different requirements,qua...In this paper,cluster synchronization of fractionalorder complex community networks(FOCCNs)in quaternionvalued filed is addressed based on the non-separation approach.To carry out tasks with different requirements,quaternionvalued FOCCNs are divided into several clusters,each of which owns different dynamic behaviors.Considering the interaction of nodes in the cluster and the influence of external driving,a hybrid controller is designed,in which the coupling strength and feedback control gains are simultaneously regulated with the evolution of states.To establish the cluster synchronization criteria for the quaternion-valued FOCCNs,some analytical approaches,such as the mean value theorem and the proof by contradiction are utilized.Furthermore,for the asymptotical synchronization of fractional-order complex networks,the case with identical nodes is also considered as a special case.Finally,two quaternion-valued FOCCNs are divided to synchronize to the desired trajectory,and a numerical simulation shows the validity of the proposed approach.展开更多
The distance dynamics model is excellent tool for uncovering the community structure of a complex network. However, one issue that must be addressed by this model is its very long computation time in large-scale netwo...The distance dynamics model is excellent tool for uncovering the community structure of a complex network. However, one issue that must be addressed by this model is its very long computation time in large-scale networks. To identify the community structure of a large-scale network with high speed and high quality, in this paper, we propose a fast community detection algorithm, the F-Attractor, which is based on the distance dynamics model. The main contributions of the F-Attractor are as follows. First, we propose the use of two prejudgment rules from two different perspectives： node and edge. Based on these two rules, we develop a strategy of internal edge prejudgment for predicting the internal edges of the network. Internal edge prejudgment can reduce the number of edges and their neighbors that participate in the distance dynamics model. Second, we introduce a triangle distance to further enhance the speed of the interaction process in the distance dynamics model. This triangle distance uses two known distances to measure a third distance without any extra computation. We combine the above techniques to improve the distance dynamics model and then describe the community detection process of the F-Attractor. The results of an extensive series of experiments demonstrate that the F-Attractor offers high-speed community detection and high partition quality.展开更多
Background:Irritable bowel syndrome(IBS)is reported associated with the alteration of gut microbial composition termed as dysbiosis.However,the pathogenic mechanism of IBS remains unclear,while the studies of Chinese ...Background:Irritable bowel syndrome(IBS)is reported associated with the alteration of gut microbial composition termed as dysbiosis.However,the pathogenic mechanism of IBS remains unclear,while the studies of Chinese individuals are scarce.This study aimed to understand the concept of dysbiosis among patients with Chinese diarrhea-predominant IBS(IBS-D),as a degree of variance between the gut microbiomes of IBS-D population and that of a healthy population.Methods:The patients with IBS-D were recruited(assessed according to the Rome III criteria,by IBS symptom severity score)from the Outpatient Department of Gastroenterology of Peking University Third Hosp让al,and volunteers as healthy controls(HCs)were enrolled,during 2013.The 16S rRNA sequences were extracted from fecal samples.Ribosomal database project resources,basic local alignment search tool,and SparCC software were used to obtain the phylotype composition of samples and the internal interactions of the microbial community.Herein,the non-parametric test,Wilcoxon rank-sum test was carried out to find the statistical significance between HC and IBS-D groups.All the P values were adjusted to q values to decrease the error rate.Results:The study characterized the gut microbiomes of Chinese patients with IBS-D,and demonstrated that the dysbiosis could be characterized as directed alteration of the microbiome composition leading to greater disparity between relative abundance of two phyla,Bacteroidetes(Z=4.77,q=1.59×10^-5)and Firmicutes(Z=-3.87,q=5.83×10^-4).Moreover,it indicated that the IBS symptom features were associated with the dysbiosis of whole gut microbiome,instead of one or several certain genera even they were dominating.Two genera,Bacteroides and Lachnospiracea incertae sedis,were identified as the core genera,meanwhile,the non-core genera contribute to a larger pan-microbiome of the gut microbiome.Furthermore,the dysbiosis in patients with IBS-D was associated with a reduction of network complexity of the interacted microbial community(HC us.IBS-D:639 vs.154).The disordered metabolic functions of patients with IBS-D were identified as the potential influence of gut microbiome on the host(significant difference with q<0.01 between HC and IBS-D).Conclusions:This study supported the view of the potential influence of gut microbiome on the symptom of Chinese patients with IBS-D,and further characterized dysbiosis in Chinese patients with IBS-D,thus provided more pathological evidences for IBS-D with the further understanding of dysbiosis.展开更多
基金supported by the National Natural Science Foundation of China(61433003,61273150)the Beijing Higher Education Young Elite Teacher Project(YETP1192)
文摘The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles（IOV） and community discovery of complex networks. The communities in complex network model of traffic flow reflect the local aggregation of vehicles in the traffic system, and it is used to predict the upcoming congestion. The real-time information of vehicles on the roads is obtained from the IOV, which includes the locations, speeds and orientations of vehicles. Then the vehicles are mapped into nodes of network, the links between nodes are determined by the correlations between vehicles in terms of location and speed. The complex network model of traffic flow is hereby established. The communities in this complex network are discovered by fast Newman（FN） algorithm, and the congestion warnings are generated according to the communities selected by scale and density. This method can detect the tendency of traffic aggregation and provide warnings before congestion occurs. The simulations show that the method proposed in this paper is effective and practicable, and makes it possible to take action before traffic congestion.
基金supported by the National Natural Science Foundation of China(No.62373089)the Synthetical Automation for Process Industries(SAPI)Fundamental Research Funds(No.2018ZCX22)the Natural Science Foundation of Liaoning Province,China(No.2022JH25/10100008).
文摘In this paper,cluster synchronization of fractionalorder complex community networks(FOCCNs)in quaternionvalued filed is addressed based on the non-separation approach.To carry out tasks with different requirements,quaternionvalued FOCCNs are divided into several clusters,each of which owns different dynamic behaviors.Considering the interaction of nodes in the cluster and the influence of external driving,a hybrid controller is designed,in which the coupling strength and feedback control gains are simultaneously regulated with the evolution of states.To establish the cluster synchronization criteria for the quaternion-valued FOCCNs,some analytical approaches,such as the mean value theorem and the proof by contradiction are utilized.Furthermore,for the asymptotical synchronization of fractional-order complex networks,the case with identical nodes is also considered as a special case.Finally,two quaternion-valued FOCCNs are divided to synchronize to the desired trajectory,and a numerical simulation shows the validity of the proposed approach.
基金supported by the National Natural Science Foundation of China(Nos.61573299,61174140,61472127,and 61272395)the Social Science Foundation of Hunan Province(No.16ZDA07)+2 种基金China Postdoctoral Science Foundation(Nos.2013M540628and 2014T70767)the Natural Science Foundation of Hunan Province(Nos.14JJ3107 and 2017JJ5064)the Excellent Youth Scholars Project of Hunan Province(No.15B087)
文摘The distance dynamics model is excellent tool for uncovering the community structure of a complex network. However, one issue that must be addressed by this model is its very long computation time in large-scale networks. To identify the community structure of a large-scale network with high speed and high quality, in this paper, we propose a fast community detection algorithm, the F-Attractor, which is based on the distance dynamics model. The main contributions of the F-Attractor are as follows. First, we propose the use of two prejudgment rules from two different perspectives： node and edge. Based on these two rules, we develop a strategy of internal edge prejudgment for predicting the internal edges of the network. Internal edge prejudgment can reduce the number of edges and their neighbors that participate in the distance dynamics model. Second, we introduce a triangle distance to further enhance the speed of the interaction process in the distance dynamics model. This triangle distance uses two known distances to measure a third distance without any extra computation. We combine the above techniques to improve the distance dynamics model and then describe the community detection process of the F-Attractor. The results of an extensive series of experiments demonstrate that the F-Attractor offers high-speed community detection and high partition quality.
基金the National Key Research and Development Program of China(No.2017YFC1200205)the National Natural Science Foundation of China(No.31671366 and No.91231119)the Special Research Project of‘Clinical Medicine+X’by Peking University.
文摘Background:Irritable bowel syndrome(IBS)is reported associated with the alteration of gut microbial composition termed as dysbiosis.However,the pathogenic mechanism of IBS remains unclear,while the studies of Chinese individuals are scarce.This study aimed to understand the concept of dysbiosis among patients with Chinese diarrhea-predominant IBS(IBS-D),as a degree of variance between the gut microbiomes of IBS-D population and that of a healthy population.Methods:The patients with IBS-D were recruited(assessed according to the Rome III criteria,by IBS symptom severity score)from the Outpatient Department of Gastroenterology of Peking University Third Hosp让al,and volunteers as healthy controls(HCs)were enrolled,during 2013.The 16S rRNA sequences were extracted from fecal samples.Ribosomal database project resources,basic local alignment search tool,and SparCC software were used to obtain the phylotype composition of samples and the internal interactions of the microbial community.Herein,the non-parametric test,Wilcoxon rank-sum test was carried out to find the statistical significance between HC and IBS-D groups.All the P values were adjusted to q values to decrease the error rate.Results:The study characterized the gut microbiomes of Chinese patients with IBS-D,and demonstrated that the dysbiosis could be characterized as directed alteration of the microbiome composition leading to greater disparity between relative abundance of two phyla,Bacteroidetes(Z=4.77,q=1.59×10^-5)and Firmicutes(Z=-3.87,q=5.83×10^-4).Moreover,it indicated that the IBS symptom features were associated with the dysbiosis of whole gut microbiome,instead of one or several certain genera even they were dominating.Two genera,Bacteroides and Lachnospiracea incertae sedis,were identified as the core genera,meanwhile,the non-core genera contribute to a larger pan-microbiome of the gut microbiome.Furthermore,the dysbiosis in patients with IBS-D was associated with a reduction of network complexity of the interacted microbial community(HC us.IBS-D:639 vs.154).The disordered metabolic functions of patients with IBS-D were identified as the potential influence of gut microbiome on the host(significant difference with q<0.01 between HC and IBS-D).Conclusions:This study supported the view of the potential influence of gut microbiome on the symptom of Chinese patients with IBS-D,and further characterized dysbiosis in Chinese patients with IBS-D,thus provided more pathological evidences for IBS-D with the further understanding of dysbiosis.
