The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network.The positive influence maximization(PIM)problem is an extension of the IM problem...The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network.The positive influence maximization(PIM)problem is an extension of the IM problem,which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely spread.To solve the PIM problem,this paper proposes the polar and decay related independent cascade(IC-PD)model to simulate the influence propagation of nodes and the decay of information during the influence propagation in signed social networks.To overcome the low efficiency of the greedy based algorithm,this paper defines the polar reverse reachable(PRR)set and devises a signed reverse influence sampling(SRIS)algorithm.The algorithm utilizes the ICPD model as well as the PRR set to select seeds.There are two phases in SRIS.One is the sampling phase,which utilizes the IC-PD model to generate the PRR set and a binary search algorithm to calculate the number of needed PRR sets.The other is the node selection phase,which uses a greedy coverage algorithm to select optimal seeds.Finally,Experiments on three real-world polar social network datasets demonstrate that SRIS outperforms the baseline algorithms in effectiveness.Especially on the Slashdot dataset,SRIS achieves 24.7% higher performance than the best-performing compared algorithm under the weighted cascade model when the seed set size is 25.展开更多
Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT ...Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT problem,we propose an influence maximization algorithm based on an improved K-shell method,namely improved K-shell in temporal social networks(KT).The algorithm takes into account the global and local structures of temporal social networks.First,to obtain the kernel value Ks of each node,in the global scope,it layers the network according to the temporal characteristic of nodes by improving the K-shell method.Then,in the local scope,the calculation method of comprehensive degree is proposed to weigh the influence of nodes.Finally,the node with the highest comprehensive degree in each core layer is selected as the seed.However,the seed selection strategy of KT can easily lose some influential nodes.Thus,by optimizing the seed selection strategy,this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization(KTIM).According to the hierarchical distribution of cores,the algorithm adds nodes near the central core to the candidate seed set.It then searches for seeds in the candidate seed set according to the comprehensive degree.Experiments showthatKTIMis close to the best performing improved method for influence maximization of temporal graph(IMIT)algorithm in terms of effectiveness,but runs at least an order of magnitude faster than it.Therefore,considering the effectiveness and efficiency simultaneously in temporal social networks,the KTIM algorithm works better than other baseline algorithms.展开更多
Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most exi...Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social networks.To bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation model.Firstly,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes selection.Specifically,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their features.During the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability accordingly.The process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based algorithms.Secondly,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node features.Finally,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model.展开更多
Bogie is a pivotal system and plays a critical part in the safety and reliability management of high-speed rail.However,the available bogie system reliability analysis methods lack the consideration of multi-state cha...Bogie is a pivotal system and plays a critical part in the safety and reliability management of high-speed rail.However,the available bogie system reliability analysis methods lack the consideration of multi-state characteristics,and the common multi-state reliability analysis methods,being an NP-hard problem,lead to low efficiency.In order to overcome these drawbacks,this paper proposes a novel multi-state rail train bogie system reliability analysis approach based on the extended d-MC model.Three different function interactions within the bogie system are considered to build the multi-state bogie system flow network model.Meanwhile,an extended d-MC model is established to remove unnecessary d-MC candidates and duplicates,which greatly enhances the computing efficiency.The bogie system reliability is calculated,and examples are provided.Numerical experiments are carried out for the different operational conditions of the bogie system and are used to test the practicability of the method proposed in this article;it is found that this method outperforms a newly developed method in solving multi-state reliability problems.展开更多
Background:Elimination of hepatitis B virus(HBV)is a striking challenge for countries with high or moderate disease burden.Therefore,using China as a practical case to share experiences for similar countries may accel...Background:Elimination of hepatitis B virus(HBV)is a striking challenge for countries with high or moderate disease burden.Therefore,using China as a practical case to share experiences for similar countries may accelerate the achievement of the WHO 2030 target of 90%reduction in HBV-related incidence.We aim to evaluate the impact of national HBV immunization strategies in China;and the feasibility to achieve WHO 2030 targets under diferent scenarios.Methods:We constructed an expanded Susceptible-Exposed-Infectious-Recovered(SEIR)model and decision treeMarkov model to estimate the epidemic of HBV in China,assess the feasibility of 2030 Elimination Goals through the projections and conduct the economic analysis.Least square method was used to calibrate the expanded SEIR model by yearly data of laboratory-confrmed HBV cases from 1990 to 2018.Two models were separately used to evaluate the impact and cost-efectiveness of HBV vaccine by comparing prevalence of chronic HBV infections,qualityadjusted life-years(QALYs),incremental cost efectiveness ratio and beneft–cost ratio(BCR)under various intervention options,providing a basis for exploring new containment strategies.Results:Between 1990 and 2020,the number of chronic HBV infections decreased by 33.9%.The current status quo would lead to 55.73 million infections(3.95%prevalence)in 2030,compared to 90.63 million(6.42%prevalence)of the“Without the NIP”scenario(NIP:National Immunization Program),114.78 million(8.13%prevalence)without any interventions.The prevention of mother to child transmission(PMTCT)strategy showed a net beneft as 12,283.50 dollars per person,with BCR as 12.66,which is higher than that of universal vaccination at 9.49.Compared with no screening and no vaccination,the PMTCT strategy could save 7726.03 dollars for each QALY increase.Conclusions:Our fndings proved the HBV vaccination has demonstrated a substantial positive impact on controlling the epidemic of HBV in terms of efectiveness and economy after about 30 years of implementation of the national hepatitis B immunization program which also provided containment experience for high or medium burden countries.As for China,the next step should focus on exploring strategies to improve diagnosis and treatment coverage to reduce the burden of HBV-related deaths and ultimately eliminate HBV.展开更多
Background:While a COVID-19 vaccine protects people from serious illness and death,it remains a concern when and how to lift the high-cost and strict non-pharmaceutical interventions(NPIs).This study examined the join...Background:While a COVID-19 vaccine protects people from serious illness and death,it remains a concern when and how to lift the high-cost and strict non-pharmaceutical interventions(NPIs).This study examined the joint efect of vaccine coverage and NPIs on the control of local and sporadic resurgence of COVID-19 cases.Methods:Between July 2021 and January 2022,we collected the large-scale testing information and case number of imported COVID-19 patients from the website of the National Health Commission of China.A compartment model was developed to identify the level of vaccine coverage that would allow safe relaxation of NPIs,and vaccination strategies that can best achieve this level of coverage.We applied Monte Carlo simulation 50000 times to remove random fuctuation efects and obtain ftted/predicted epidemic curve based on various parameters with 95% confdence interval at each time point.Results:We found that a vaccination coverage of 50.4% was needed for the safe relaxation of NPIs,if the vaccine efectiveness was 79.3%.The total number of incidence cases under the key groups frstly strategy was 10^(3) times higher than that of accelerated vaccination strategy.It needed 35 months to fully relax NPIs if the key groups frstly strategy was implemented,and 27 months were needed with the accelerated vaccination strategy.If combined the two strategies,only 8 months are needed to achieve the vaccine coverage threshold for the fully relaxation of NPIs.Sensitivity analyses results shown that the higher the transmission rate of the virus and the lower annual vaccine supply,the more difcult the epidemic could be under control.When the transmission rate increased 25% or the vaccination efectiveness rate decreased 20%,33 months were needed to reduce the number of total incidence cases below 1000.Conclusions:As vaccine coverage improves,the NPIs can be gradually relaxed.Until that threshold is reached,however,strict NPIs are still needed to control the epidemic.The more transmissible SARS-CoV-2 variant led to higher resurgence probability,which indicates the importance of accelerated vaccination and achieving the vaccine coverage earlier.展开更多
Background:The pandemic of coronavirus disease 2019(COVID-19)has changed human behavior in areas such as contact patterns and mask-wearing frequency.Exploring human–human contact patterns and mask-wearing habits in h...Background:The pandemic of coronavirus disease 2019(COVID-19)has changed human behavior in areas such as contact patterns and mask-wearing frequency.Exploring human–human contact patterns and mask-wearing habits in high-risk groups is an essential step in fully understanding the transmission of respiratory infection-based diseases.This study had aims to quantify local human–human(H–H)contacts in high-risk groups in representative provinces of China and to explore the occupation-specific assortativity and heterogeneity of social contacts.Methods:Delivery workers,medical workers,preschoolers,and students from Qinghai,Shanghai,and Zhejiang were recruited to complete an online questionnaire that queried general information,logged contacts,and assessed the willingness to wear a mask in different settings.The“group contact”was defined as contact with a group at least 20 individuals.The numbers of contacts across different characteristics were assessed and age-specific contact matrices were established.A generalized additive mixed model was used to analyze the associations between the number of individual contacts and several characteristics.The factors influencing the frequency of mask wearing were evaluated with a logistic regression model.Results:A total of 611,287 contacts were reported by 15,635 participants.The frequency of daily individual contacts averaged 3.14(95%confidence interval:3.13–3.15)people per day,while that of group contacts was 37.90(95%CI:37.20–38.70).Skin-to-skin contact and long-duration contact were more likely to occur at home or among family members.Contact matrices of students were the most assortative(all contacts q-index=0.899,95%CI:0.894–0.904).Participants with larger household sizes reported having more contacts.Higher household income per capita was significantly associated with a greater number of contacts among preschoolers(P_(50,000–99,999)=0.033)and students(P_(10,000–29,999)=0.017).In each of the public places,the frequency of mask wearing was highest for delivery workers.For preschoolers and students with more contacts,the proportion of those who reported always wearing masks was lower(P<0.05)in schools/workplaces and public transportation than preschoolers and students with fewer contacts.Conclusions:Contact screening efforts should be concentrated in the home,school,and workplace after an outbreak of an epidemic,as more than 75%of all contacts,on average,will be found in such places.Efforts should be made to improve the mask-wearing rate and age-specific health promotion measures aimed at reducing transmission for the younger demographic.Age-stratified and occupation-specific social contact research in high-risk groups could help inform policy-making decisions during the post-relaxation period of the COVID-19 pandemic.展开更多
基金supported by theYouth Science and Technology Innovation Personnel Training Project of Heilongjiang(No.UNPYSCT-2020072)the FundamentalResearch Funds for the Universities of Heilongjiang(Nos.145109217,135509234)+1 种基金the Education Science Fourteenth Five-Year Plan 2021 Project of Heilongjiang(No.GJB1421344)the Innovative Research Projects for Postgraduates of Qiqihar University(No.YJSCX2022048).
文摘The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social network.The positive influence maximization(PIM)problem is an extension of the IM problem,which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely spread.To solve the PIM problem,this paper proposes the polar and decay related independent cascade(IC-PD)model to simulate the influence propagation of nodes and the decay of information during the influence propagation in signed social networks.To overcome the low efficiency of the greedy based algorithm,this paper defines the polar reverse reachable(PRR)set and devises a signed reverse influence sampling(SRIS)algorithm.The algorithm utilizes the ICPD model as well as the PRR set to select seeds.There are two phases in SRIS.One is the sampling phase,which utilizes the IC-PD model to generate the PRR set and a binary search algorithm to calculate the number of needed PRR sets.The other is the node selection phase,which uses a greedy coverage algorithm to select optimal seeds.Finally,Experiments on three real-world polar social network datasets demonstrate that SRIS outperforms the baseline algorithms in effectiveness.Especially on the Slashdot dataset,SRIS achieves 24.7% higher performance than the best-performing compared algorithm under the weighted cascade model when the seed set size is 25.
基金Thiswork is supported by theYouth Science and Technology Innovation Personnel Training Project of Heilongjiang(No.UNPYSCT-2020072)the FundamentalResearch Funds for the Universities of Heilongjiang(Nos.145109217,135509234)+1 种基金the Education Science Fourteenth Five-Year Plan 2021 Project of Heilongjiang(No.GJB1421344)the Innovative Research Projects for Postgraduates of Qiqihar University(No.YJSCX2022048).
文摘Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT problem,we propose an influence maximization algorithm based on an improved K-shell method,namely improved K-shell in temporal social networks(KT).The algorithm takes into account the global and local structures of temporal social networks.First,to obtain the kernel value Ks of each node,in the global scope,it layers the network according to the temporal characteristic of nodes by improving the K-shell method.Then,in the local scope,the calculation method of comprehensive degree is proposed to weigh the influence of nodes.Finally,the node with the highest comprehensive degree in each core layer is selected as the seed.However,the seed selection strategy of KT can easily lose some influential nodes.Thus,by optimizing the seed selection strategy,this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization(KTIM).According to the hierarchical distribution of cores,the algorithm adds nodes near the central core to the candidate seed set.It then searches for seeds in the candidate seed set according to the comprehensive degree.Experiments showthatKTIMis close to the best performing improved method for influence maximization of temporal graph(IMIT)algorithm in terms of effectiveness,but runs at least an order of magnitude faster than it.Therefore,considering the effectiveness and efficiency simultaneously in temporal social networks,the KTIM algorithm works better than other baseline algorithms.
基金supported by the Fundamental Research Funds for the Universities of Heilongjiang(Nos.145109217,135509234)the Youth Science and Technology Innovation Personnel Training Project of Heilongjiang(No.UNPYSCT-2020072)the Innovative Research Projects for Postgraduates of Qiqihar University(No.YJSCX2022048).
文摘Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social networks.To bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation model.Firstly,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes selection.Specifically,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their features.During the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability accordingly.The process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based algorithms.Secondly,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node features.Finally,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model.
基金funded by the Hunan Science and Technology‘Lotus Bud’Talent Support Program(Grant No.2022TJ-XH-009).
文摘Bogie is a pivotal system and plays a critical part in the safety and reliability management of high-speed rail.However,the available bogie system reliability analysis methods lack the consideration of multi-state characteristics,and the common multi-state reliability analysis methods,being an NP-hard problem,lead to low efficiency.In order to overcome these drawbacks,this paper proposes a novel multi-state rail train bogie system reliability analysis approach based on the extended d-MC model.Three different function interactions within the bogie system are considered to build the multi-state bogie system flow network model.Meanwhile,an extended d-MC model is established to remove unnecessary d-MC candidates and duplicates,which greatly enhances the computing efficiency.The bogie system reliability is calculated,and examples are provided.Numerical experiments are carried out for the different operational conditions of the bogie system and are used to test the practicability of the method proposed in this article;it is found that this method outperforms a newly developed method in solving multi-state reliability problems.
文摘Background:Elimination of hepatitis B virus(HBV)is a striking challenge for countries with high or moderate disease burden.Therefore,using China as a practical case to share experiences for similar countries may accelerate the achievement of the WHO 2030 target of 90%reduction in HBV-related incidence.We aim to evaluate the impact of national HBV immunization strategies in China;and the feasibility to achieve WHO 2030 targets under diferent scenarios.Methods:We constructed an expanded Susceptible-Exposed-Infectious-Recovered(SEIR)model and decision treeMarkov model to estimate the epidemic of HBV in China,assess the feasibility of 2030 Elimination Goals through the projections and conduct the economic analysis.Least square method was used to calibrate the expanded SEIR model by yearly data of laboratory-confrmed HBV cases from 1990 to 2018.Two models were separately used to evaluate the impact and cost-efectiveness of HBV vaccine by comparing prevalence of chronic HBV infections,qualityadjusted life-years(QALYs),incremental cost efectiveness ratio and beneft–cost ratio(BCR)under various intervention options,providing a basis for exploring new containment strategies.Results:Between 1990 and 2020,the number of chronic HBV infections decreased by 33.9%.The current status quo would lead to 55.73 million infections(3.95%prevalence)in 2030,compared to 90.63 million(6.42%prevalence)of the“Without the NIP”scenario(NIP:National Immunization Program),114.78 million(8.13%prevalence)without any interventions.The prevention of mother to child transmission(PMTCT)strategy showed a net beneft as 12,283.50 dollars per person,with BCR as 12.66,which is higher than that of universal vaccination at 9.49.Compared with no screening and no vaccination,the PMTCT strategy could save 7726.03 dollars for each QALY increase.Conclusions:Our fndings proved the HBV vaccination has demonstrated a substantial positive impact on controlling the epidemic of HBV in terms of efectiveness and economy after about 30 years of implementation of the national hepatitis B immunization program which also provided containment experience for high or medium burden countries.As for China,the next step should focus on exploring strategies to improve diagnosis and treatment coverage to reduce the burden of HBV-related deaths and ultimately eliminate HBV.
文摘Background:While a COVID-19 vaccine protects people from serious illness and death,it remains a concern when and how to lift the high-cost and strict non-pharmaceutical interventions(NPIs).This study examined the joint efect of vaccine coverage and NPIs on the control of local and sporadic resurgence of COVID-19 cases.Methods:Between July 2021 and January 2022,we collected the large-scale testing information and case number of imported COVID-19 patients from the website of the National Health Commission of China.A compartment model was developed to identify the level of vaccine coverage that would allow safe relaxation of NPIs,and vaccination strategies that can best achieve this level of coverage.We applied Monte Carlo simulation 50000 times to remove random fuctuation efects and obtain ftted/predicted epidemic curve based on various parameters with 95% confdence interval at each time point.Results:We found that a vaccination coverage of 50.4% was needed for the safe relaxation of NPIs,if the vaccine efectiveness was 79.3%.The total number of incidence cases under the key groups frstly strategy was 10^(3) times higher than that of accelerated vaccination strategy.It needed 35 months to fully relax NPIs if the key groups frstly strategy was implemented,and 27 months were needed with the accelerated vaccination strategy.If combined the two strategies,only 8 months are needed to achieve the vaccine coverage threshold for the fully relaxation of NPIs.Sensitivity analyses results shown that the higher the transmission rate of the virus and the lower annual vaccine supply,the more difcult the epidemic could be under control.When the transmission rate increased 25% or the vaccination efectiveness rate decreased 20%,33 months were needed to reduce the number of total incidence cases below 1000.Conclusions:As vaccine coverage improves,the NPIs can be gradually relaxed.Until that threshold is reached,however,strict NPIs are still needed to control the epidemic.The more transmissible SARS-CoV-2 variant led to higher resurgence probability,which indicates the importance of accelerated vaccination and achieving the vaccine coverage earlier.
文摘Background:The pandemic of coronavirus disease 2019(COVID-19)has changed human behavior in areas such as contact patterns and mask-wearing frequency.Exploring human–human contact patterns and mask-wearing habits in high-risk groups is an essential step in fully understanding the transmission of respiratory infection-based diseases.This study had aims to quantify local human–human(H–H)contacts in high-risk groups in representative provinces of China and to explore the occupation-specific assortativity and heterogeneity of social contacts.Methods:Delivery workers,medical workers,preschoolers,and students from Qinghai,Shanghai,and Zhejiang were recruited to complete an online questionnaire that queried general information,logged contacts,and assessed the willingness to wear a mask in different settings.The“group contact”was defined as contact with a group at least 20 individuals.The numbers of contacts across different characteristics were assessed and age-specific contact matrices were established.A generalized additive mixed model was used to analyze the associations between the number of individual contacts and several characteristics.The factors influencing the frequency of mask wearing were evaluated with a logistic regression model.Results:A total of 611,287 contacts were reported by 15,635 participants.The frequency of daily individual contacts averaged 3.14(95%confidence interval:3.13–3.15)people per day,while that of group contacts was 37.90(95%CI:37.20–38.70).Skin-to-skin contact and long-duration contact were more likely to occur at home or among family members.Contact matrices of students were the most assortative(all contacts q-index=0.899,95%CI:0.894–0.904).Participants with larger household sizes reported having more contacts.Higher household income per capita was significantly associated with a greater number of contacts among preschoolers(P_(50,000–99,999)=0.033)and students(P_(10,000–29,999)=0.017).In each of the public places,the frequency of mask wearing was highest for delivery workers.For preschoolers and students with more contacts,the proportion of those who reported always wearing masks was lower(P<0.05)in schools/workplaces and public transportation than preschoolers and students with fewer contacts.Conclusions:Contact screening efforts should be concentrated in the home,school,and workplace after an outbreak of an epidemic,as more than 75%of all contacts,on average,will be found in such places.Efforts should be made to improve the mask-wearing rate and age-specific health promotion measures aimed at reducing transmission for the younger demographic.Age-stratified and occupation-specific social contact research in high-risk groups could help inform policy-making decisions during the post-relaxation period of the COVID-19 pandemic.
