Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on cou...Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on country comparisons or institutional en-vironment.In today’s networked era in which the global economy,trade,personnel,and information are closely connected,studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient.In this study,from the perspective of diverse global contact networks,we constructed economic,cultural,and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018.The results show that during the study period,China’s global influence in the fields of economic ties,cultural exchanges,and political contacts increased significantly,but its influ-ence in the fields of cultural exchanges and political contacts lagged far economic ties.The pattern of China’s economic influence on various economies around the world has shown a transformation from an‘upright pyramid’to an‘inverted pyramid’structure.The proportion of these economies in low-influence zones has decreased from more than 60%in 2005 to less than 20%in 2018.China’s cultural and political influence on various economies around the world has increased significantly;however,for the former,the percentage of high-influence areas is still less than 20%,whereas for the latter the percentage of these economies in medium-and high-influence areas is still less than 50%.Analyses such as a scatter plot matrix show that geographical proximity,economic globalization,close cooperation with developing countries,and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.展开更多
During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to inv...During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.展开更多
Background The interconnectedness of human society in this modern world can transform localised outbreaks into global pandemics,underscoring the pivotal roles of social,mobility and contact networks in shaping infecti...Background The interconnectedness of human society in this modern world can transform localised outbreaks into global pandemics,underscoring the pivotal roles of social,mobility and contact networks in shaping infectious disease dynamics.Although these networks share analogous contagion principles,they are often studied in isolation,hindering the incorporation of behavioural,informational,and epidemiological processes into disease models.This review synthesises current research on the interplay between social,mobility and contact networks in health behaviour contagion and infectious disease transmission.Methods We searched Web of Science and PubMed from January 2000 to June 2025 for research on health behaviour contagion and information dissemination in social networks,pathogen spread through mobility and contact networks,and their joint impacts on epidemic dynamics.This was first done by a preliminary literature screening based on predefined criteria.With potentially relevant publications retained,we performed keyword co-occurrence network analysis to identify the most common themes in studies.The results guide us to narrow down the reviewing scope to the social,mobility and contact network impacts on informational,behavioural,and epidemiological dynamics.We then further identified and reviewed the literature on these multidimensional network influences.Results Our review finds that each network type plays a distinct yet interconnected role in shaping behaviours and disease dynamics.Social networks,comprising both online and offline interpersonal relationships,facilitate the dissemination of health information and influence behavioural responses to public health interventions.Concurrently,mobility and contact networks govern the spatiotemporal pathways of pathogen transmission,as demonstrated in recent pandemics.While traditional population-level models often overlook individual discrepancies and social network effects,significant efforts have been made through developing individual-level simulation-based models that integrate behavioural dynamics.With emerging new data sources and advanced computational techniques,two promising approaches—multiplex network analysis and generative agent-based modelling—offer frameworks for integrating the complex interdependencies among social,mobility and contact networks into epidemic dynamics estimation.Conclusions This review highlights the theoretical and methodological advances in network-based infectious disease modelling and identifies critical knowledge and research gaps.Future research should prioritise integrating multi-source behavioural and spatial data,unifying modelling strategies,and developing scalable approaches for incorporating multilayer network data.The integrated approach will strengthen public health strategies,enabling equitable and effective interventions against emerging infections.展开更多
Traditional compartmental models such as SIR(susceptible,infected,recovered)assume that the epidemic transmits in a homogeneous population,but the real contact patterns in epidemics are heterogeneous.Employing a more ...Traditional compartmental models such as SIR(susceptible,infected,recovered)assume that the epidemic transmits in a homogeneous population,but the real contact patterns in epidemics are heterogeneous.Employing a more realistic model that considers heterogeneous contact is consequently necessary.Here,we use a contact network to reconstruct unprotected,protected contact,and airborne spread to simulate the two-stages outbreak of COVID-19(coronavirus disease 2019)on the‘‘Diamond Princess"cruise ship.We employ Bayesian inference and Metropolis-Hastings sampling to estimate the model parameters and quantify the uncertainties by the ensemble simulation technique.During the early epidemic with intensive social contacts,the results reveal that the average transmissibility t was 0.026 and the basic reproductive number R0 was 6.94,triple that in the WHO report,indicating that all people would be infected in one month.The t and R0 decreased to 0.0007 and 0.2 when quarantine was implemented.The reconstruction suggests that diluting the airborne virus concentration in closed settings is useful in addition to isolation,and high-risk susceptible should follow rigorous prevention measures in case exposed.This study can provide useful implications for control and prevention measures for the other cruise ships and closed settings.展开更多
As the COVID-19 vaccination has been quickly rolling out around the globe,the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators,decision-make...As the COVID-19 vaccination has been quickly rolling out around the globe,the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators,decision-makers,and the general public.Within this context,we develop a contact network agent-based model(CN-ABM)to simulate on-campus disease transmission scenarios.The CN-ABM establishes contact networks for agents based on their daily activity patterns,evaluates the agents’health status change in different activity environments,and then simulates the epidemic curve.By applying the model to a real-world campus environment,we identify how different community risk levels,teaching modalities,and vaccination rates would shape the epidemic curve.The results show that without vaccination,retaining under 50%of on-campus students can largely flatten the curve,and having 25%on-campus students can achieve the best result(peak value<1%).With vaccination,having a maximum of 75%on-campus students and at least a 45%vaccination rate can suppress the curve,and a 65%vaccination rate can achieve the best result.The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools.展开更多
Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduct...Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduction number(R0)have been adapted to account for the structure of social contact networks but still may be unable to capture epidemic potential relative to more recent measures based on spectral graph properties.Here,we explore the ability of R0 and the spectral radius of the social contact network to estimate epidemic susceptibility.To do so,we simulate epidemics on a series of constructed(small world,scale-free,and random networks)and a collection of over 700 empirical biological social contact networks.Further,we explore how other network properties are related to these two epidemic estimators(R0 and spectral radius)and mean infection prevalence in simulated epidemics.Overall,we find that network properties strongly influence epidemic dynamics and the subsequent utility of R0 and spectral radius as indicators of epidemic risk.展开更多
In multi-layer satellite-terrestrial network, Contact Graph Routing(CGR) uses the contact information among satellites to compute routes. However, due to the resource constraints in satellites, it is extravagant to co...In multi-layer satellite-terrestrial network, Contact Graph Routing(CGR) uses the contact information among satellites to compute routes. However, due to the resource constraints in satellites, it is extravagant to configure lots of the potential contacts into contact plans. What's more, a huge contact plan makes the computing more complex, which further increases computing time. As a result, how to design an efficient contact plan becomes crucial for multi-layer satellite network, which usually has a large scaled topology. In this paper, we propose a distributed contact plan design scheme for multi-layer satellite network by dividing a large contact plan into several partial parts. Meanwhile, a duration based inter-layer contact selection algorithm is proposed to handle contacts disruption problem. The performance of the proposed design was evaluated on our Identifier/Locator split based satellite-terrestrial network testbed with 79 simulation nodes. Experiments showed that the proposed design is able to reduce the data delivery delay.展开更多
A new method was described for using a recurrent neural network with bias units to predict contact maps in proteins. The main inputs to the neural network include residues pairwise, residue classification according to...A new method was described for using a recurrent neural network with bias units to predict contact maps in proteins. The main inputs to the neural network include residues pairwise, residue classification according to hydrophobicity, polar, acidic, basic and secondary structure information and residue separation between two residues. In our work, a dataset was used which was composed of 53 globulin proteins of known 3D structure. An average predictive accuracy of 0.29 was obtained. Our results demonstrate the viability of the approach for predicting contact maps.展开更多
Under the background of high-speed rail networking, this paper uses the passenger trains, the type and direction of the railway via Hang Yong and its extension road line, to construct adsorption and dependency index a...Under the background of high-speed rail networking, this paper uses the passenger trains, the type and direction of the railway via Hang Yong and its extension road line, to construct adsorption and dependency index among cities, depict the contact pattern between the Hang Yong dual-core and its hinterland, measure the “net effect” that two center cities (Hangzhou, Ningbo) have on their hinterland, and estimate population agglomeration potential and future possible population flows of Zhejiang Province and the main sample cities. The result shows that, compared with Ningbo, Hangzhou has stronger radiation force to the vast majority of sample cities, and the sample cities affected more by Ningbo mainly concentrates in Ningbo-Taizhou-Wenzhou along;in addition, the sample cities such as Hangzhou, Ningbo and so on show better population agglomeration, then the population “scramble” phenomenon between cities has begun to appear.展开更多
Satellite networks have many inherent advantages over terrestrial networks and have become an important part of the global network infrastructure.Routing aimed at satellite networks has become a hot and challenging re...Satellite networks have many inherent advantages over terrestrial networks and have become an important part of the global network infrastructure.Routing aimed at satellite networks has become a hot and challenging research topic.Satellite networks,which are special kind of Delay Tolerant Networks(DTN),can also adopt the routing solutions of DTN.Among the many routing proposals,Contact Graph Routing(CGR) is an excellent candidate,since it is designed particularly for use in highly deterministic space networks.The applicability of CGR in satellite networks is evaluated by utilizing the space oriented DTN gateway model based on OPNET(Optimized Network Engineering Tool).Link failures are solved with neighbor discovery mechanism and route recomputation.Earth observation scenario is used in the simulations to investigate CGR's performance.The results show that the CGR performances are better in terms of effectively utilizing satellite networks resources to calculate continuous route path and alternative route can be successfully calculated under link failures by utilizing fault tolerance scheme.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42201181,42171181)Fundamental Research Funds for the Central Universities(No.2412022QD002)The Medium and Long-term Major Training Foundation of Philosophy and Social Sciences of Northeast Normal University(No.22FR006)。
文摘Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on country comparisons or institutional en-vironment.In today’s networked era in which the global economy,trade,personnel,and information are closely connected,studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient.In this study,from the perspective of diverse global contact networks,we constructed economic,cultural,and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018.The results show that during the study period,China’s global influence in the fields of economic ties,cultural exchanges,and political contacts increased significantly,but its influ-ence in the fields of cultural exchanges and political contacts lagged far economic ties.The pattern of China’s economic influence on various economies around the world has shown a transformation from an‘upright pyramid’to an‘inverted pyramid’structure.The proportion of these economies in low-influence zones has decreased from more than 60%in 2005 to less than 20%in 2018.China’s cultural and political influence on various economies around the world has increased significantly;however,for the former,the percentage of high-influence areas is still less than 20%,whereas for the latter the percentage of these economies in medium-and high-influence areas is still less than 50%.Analyses such as a scatter plot matrix show that geographical proximity,economic globalization,close cooperation with developing countries,and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.
文摘During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.
基金National Institutes of Health(MIDAS Mobility R01AI160780)U.S.National Science Foundation(DMS-2327797)China Scholarship Council(202204910015)。
文摘Background The interconnectedness of human society in this modern world can transform localised outbreaks into global pandemics,underscoring the pivotal roles of social,mobility and contact networks in shaping infectious disease dynamics.Although these networks share analogous contagion principles,they are often studied in isolation,hindering the incorporation of behavioural,informational,and epidemiological processes into disease models.This review synthesises current research on the interplay between social,mobility and contact networks in health behaviour contagion and infectious disease transmission.Methods We searched Web of Science and PubMed from January 2000 to June 2025 for research on health behaviour contagion and information dissemination in social networks,pathogen spread through mobility and contact networks,and their joint impacts on epidemic dynamics.This was first done by a preliminary literature screening based on predefined criteria.With potentially relevant publications retained,we performed keyword co-occurrence network analysis to identify the most common themes in studies.The results guide us to narrow down the reviewing scope to the social,mobility and contact network impacts on informational,behavioural,and epidemiological dynamics.We then further identified and reviewed the literature on these multidimensional network influences.Results Our review finds that each network type plays a distinct yet interconnected role in shaping behaviours and disease dynamics.Social networks,comprising both online and offline interpersonal relationships,facilitate the dissemination of health information and influence behavioural responses to public health interventions.Concurrently,mobility and contact networks govern the spatiotemporal pathways of pathogen transmission,as demonstrated in recent pandemics.While traditional population-level models often overlook individual discrepancies and social network effects,significant efforts have been made through developing individual-level simulation-based models that integrate behavioural dynamics.With emerging new data sources and advanced computational techniques,two promising approaches—multiplex network analysis and generative agent-based modelling—offer frameworks for integrating the complex interdependencies among social,mobility and contact networks into epidemic dynamics estimation.Conclusions This review highlights the theoretical and methodological advances in network-based infectious disease modelling and identifies critical knowledge and research gaps.Future research should prioritise integrating multi-source behavioural and spatial data,unifying modelling strategies,and developing scalable approaches for incorporating multilayer network data.The integrated approach will strengthen public health strategies,enabling equitable and effective interventions against emerging infections.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA19070104)13th Five-year Informatization Plan of Chinese Academy of Sciences (XXH13505-06)+1 种基金Foundation for Excellent Youth Scholars of Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (Y851D41)National Natural Science Foundation of China (41801270)。
文摘Traditional compartmental models such as SIR(susceptible,infected,recovered)assume that the epidemic transmits in a homogeneous population,but the real contact patterns in epidemics are heterogeneous.Employing a more realistic model that considers heterogeneous contact is consequently necessary.Here,we use a contact network to reconstruct unprotected,protected contact,and airborne spread to simulate the two-stages outbreak of COVID-19(coronavirus disease 2019)on the‘‘Diamond Princess"cruise ship.We employ Bayesian inference and Metropolis-Hastings sampling to estimate the model parameters and quantify the uncertainties by the ensemble simulation technique.During the early epidemic with intensive social contacts,the results reveal that the average transmissibility t was 0.026 and the basic reproductive number R0 was 6.94,triple that in the WHO report,indicating that all people would be infected in one month.The t and R0 decreased to 0.0007 and 0.2 when quarantine was implemented.The reconstruction suggests that diluting the airborne virus concentration in closed settings is useful in addition to isolation,and high-risk susceptible should follow rigorous prevention measures in case exposed.This study can provide useful implications for control and prevention measures for the other cruise ships and closed settings.
基金supported by the National Natural Science Foundation of China(grant number 41971372)in part by the Natural Science Foundation of Guangdong Province(grant number 2020A1515010680).
文摘As the COVID-19 vaccination has been quickly rolling out around the globe,the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators,decision-makers,and the general public.Within this context,we develop a contact network agent-based model(CN-ABM)to simulate on-campus disease transmission scenarios.The CN-ABM establishes contact networks for agents based on their daily activity patterns,evaluates the agents’health status change in different activity environments,and then simulates the epidemic curve.By applying the model to a real-world campus environment,we identify how different community risk levels,teaching modalities,and vaccination rates would shape the epidemic curve.The results show that without vaccination,retaining under 50%of on-campus students can largely flatten the curve,and having 25%on-campus students can achieve the best result(peak value<1%).With vaccination,having a maximum of 75%on-campus students and at least a 45%vaccination rate can suppress the curve,and a 65%vaccination rate can achieve the best result.The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools.
基金supported by the U.S.National Science Foundation RAPID grant(NSF-DEB-2031196).
文摘Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduction number(R0)have been adapted to account for the structure of social contact networks but still may be unable to capture epidemic potential relative to more recent measures based on spectral graph properties.Here,we explore the ability of R0 and the spectral radius of the social contact network to estimate epidemic susceptibility.To do so,we simulate epidemics on a series of constructed(small world,scale-free,and random networks)and a collection of over 700 empirical biological social contact networks.Further,we explore how other network properties are related to these two epidemic estimators(R0 and spectral radius)and mean infection prevalence in simulated epidemics.Overall,we find that network properties strongly influence epidemic dynamics and the subsequent utility of R0 and spectral radius as indicators of epidemic risk.
基金supported by National High Technology of China ("863 program") under Grant No. 2015AA015702NSAF under Grant No. U1530118+1 种基金NSFC under Grant No. 61602030National Basic Research Program of China ("973 program") under Grant No. 2013CB329101
文摘In multi-layer satellite-terrestrial network, Contact Graph Routing(CGR) uses the contact information among satellites to compute routes. However, due to the resource constraints in satellites, it is extravagant to configure lots of the potential contacts into contact plans. What's more, a huge contact plan makes the computing more complex, which further increases computing time. As a result, how to design an efficient contact plan becomes crucial for multi-layer satellite network, which usually has a large scaled topology. In this paper, we propose a distributed contact plan design scheme for multi-layer satellite network by dividing a large contact plan into several partial parts. Meanwhile, a duration based inter-layer contact selection algorithm is proposed to handle contacts disruption problem. The performance of the proposed design was evaluated on our Identifier/Locator split based satellite-terrestrial network testbed with 79 simulation nodes. Experiments showed that the proposed design is able to reduce the data delivery delay.
文摘A new method was described for using a recurrent neural network with bias units to predict contact maps in proteins. The main inputs to the neural network include residues pairwise, residue classification according to hydrophobicity, polar, acidic, basic and secondary structure information and residue separation between two residues. In our work, a dataset was used which was composed of 53 globulin proteins of known 3D structure. An average predictive accuracy of 0.29 was obtained. Our results demonstrate the viability of the approach for predicting contact maps.
文摘Under the background of high-speed rail networking, this paper uses the passenger trains, the type and direction of the railway via Hang Yong and its extension road line, to construct adsorption and dependency index among cities, depict the contact pattern between the Hang Yong dual-core and its hinterland, measure the “net effect” that two center cities (Hangzhou, Ningbo) have on their hinterland, and estimate population agglomeration potential and future possible population flows of Zhejiang Province and the main sample cities. The result shows that, compared with Ningbo, Hangzhou has stronger radiation force to the vast majority of sample cities, and the sample cities affected more by Ningbo mainly concentrates in Ningbo-Taizhou-Wenzhou along;in addition, the sample cities such as Hangzhou, Ningbo and so on show better population agglomeration, then the population “scramble” phenomenon between cities has begun to appear.
基金Supported by the open project of Communication network transmission and distribution technologies Key Laboratory(ITD-12005/K1260011)the National Natural Science Foundation of China(61371126) and the National Natural Science Foundation of China(60903195)
文摘Satellite networks have many inherent advantages over terrestrial networks and have become an important part of the global network infrastructure.Routing aimed at satellite networks has become a hot and challenging research topic.Satellite networks,which are special kind of Delay Tolerant Networks(DTN),can also adopt the routing solutions of DTN.Among the many routing proposals,Contact Graph Routing(CGR) is an excellent candidate,since it is designed particularly for use in highly deterministic space networks.The applicability of CGR in satellite networks is evaluated by utilizing the space oriented DTN gateway model based on OPNET(Optimized Network Engineering Tool).Link failures are solved with neighbor discovery mechanism and route recomputation.Earth observation scenario is used in the simulations to investigate CGR's performance.The results show that the CGR performances are better in terms of effectively utilizing satellite networks resources to calculate continuous route path and alternative route can be successfully calculated under link failures by utilizing fault tolerance scheme.
