On collaborative content distribution using multi-message gossip

We study epidemic schemes in the context of collaborative data delivery. In this context, multiple chunks of data reside at different nodes, and the challenge is to simultaneously deliver all chunks to all nodes.     

Multi：DTN中一种自适应的消息转发算法

为了充分利用DTN中各节点资源,减少Epidemic Routing、spray and wait中不区分各节点资源不同,提出了一个基于节点密度、节点运动速度、生存期、节点缓存大小诸多因素,来进行消息转发的算法multi。通过仿真实验表明,multi算法较Epidemic Routing、spray and wait算法在消息成功传输率、平均延迟、网络开销、消息在缓存中滞留的时间上都有明显改善。     

Matrix expression and vaccination control for epidemic dynamics over dynamic networks

This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks (SISED-DN) is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.     

Optimizing counter-terror operations: Should one fight fire with “fire” or “water”?

This paper deals dynamically with the question of how recruitment to terror organizations is influenced by counter-terror operations. This is done within an optimal control model, where the key state is the (relative) number of terrorists and the key controls are two types of counter-terror tactics, one (“water”) that does not and one (“fire”) that does provoke recruitment of new terrorists. The model is nonlinear and does not admit analytical solutions, but an efficient numerical implementation of Pontryagin's minimum principle allows for solution with base case parameters and considerable sensitivity analysis. Generally, this model yields two different steady states, one where the terror organization is nearly eradicated and one with a high number of terrorists. Whereas water strategies are used at almost any time, it can be optimal not to use fire strategies if the number of terrorists is below a certain threshold.     

基于状态概率转移的SIRS病毒传播模型及其临界值分析

针对SIRS(Susceptible-Infected-Removed-Susceptible)病毒传播模型,利用状态转移概率的方法,通过计算节点处于各个状态的概率来研究SIRS病毒传播过程。首先建立状态概率方程组,描述各个时刻各个节点处于易感染态、感染态、免疫态的概率,通过稳态分析理论推导网络的病毒传播临界值;然后利用蒙特卡罗方法,对均匀网络和非均匀网络的病毒传播临界值进行分析和仿真。结果表明,相对于传统的平均场方法,基于状态概率方程组模型求得的传播临界值更加接近真实蒙特卡罗值,并且与免疫丧失率无关。     

平疫结合的城市韧性社区建设与规划应对

作为疫情防控的基础单元,城市社区在面对突发公共卫生事件的冲击时,良好的应对能力对减少病毒传播、降低灾害损失至关重要。文章通过解读平疫结合的韧性社区内涵,从物质空间和社会空间层面构建了韧性社区评估框架,结合基层社区在新型冠状病毒肺炎疫情中的表现,剖析社区在疫情防控中存在的问题,并针对不足提出规划应对策略。期望为未来城市社区的韧性提升提供有益参考。     

Transparent three-phase Byzantine fault tolerance for parallel and distributed simulations

A parallel and distributed simulation (federation) is composed of a number of simulation components (federates). Since the federates may be developed by different participants and executed on different platforms, they are subject to Byzantine failures. Moreover, the failure may propagate in the federation, resulting in epidemic effect. In this article, a three-phase (i.e., detection, location, and recovery) Byzantine Fault Tolerance (BFT) mechanism is proposed based on a transparent middleware approach. The replication, checkpointing and message logging techniques are integrated in the mechanism for the purpose of enhancing simulation performance and reducing fault tolerance cost. In addition, mechanisms are provided to remove the epidemic effects of Byzantine failures. Our experiments have verified the correctness of the three-phase BFT mechanism and illustrated its high efficiency and good scalability. For some simulation executions, the BFT mechanism may even achieve performance enhancement and Byzantine fault tolerance simultaneously.     

一类具饱和传染率和两阶段结构的传染病模型

对一类具饱和传染率和阶段结构传染病模型进行了分析,得到了传染病最终消除和成为地方病的阈值,当它小于1时,无病平衡点是全局渐近稳定的,此时疾病消除;当它大于1时,地方病平衡点是局部渐近稳定的,此时传染病成为地方病。     

Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of Brazil for the period January 2001 to December 2008 at the microregion level (typically consisting of one large city and several smaller municipalities). The covariates explored include temperature and precipitation data on a 2.5^°×2.5^° longitude-latitude grid with time lags relevant to dengue transmission, an El Niño Southern Oscillation index and other relevant socio-economic and environmental variables. A negative binomial model formulation is adopted in this model selection to allow for extra-Poisson variation (overdispersion) in the observed dengue counts caused by unknown/unobserved confounding factors and possible correlations in these effects in both time and space. Subsequently, the selected global model is refined in the context of the South East region of Brazil, where dengue predominates, by reverting to a Poisson framework and explicitly modelling the overdispersion through a combination of unstructured and spatio-temporal structured random effects. The resulting spatio-temporal hierarchical model (or GLMM—generalised linear mixed model) is implemented via a Bayesian framework using Markov Chain Monte Carlo (MCMC). Dengue predictions are found to be enhanced both spatially and temporally when using the GLMM and the Bayesian framework allows posterior predictive distributions for dengue cases to be derived, which can be useful for developing a dengue alert system. Using this model, we conclude that seasonal climate forecasts could have potential value in helping to predict dengue incidence months in advance of an epidemic in South East Brazil.     

践行社会责任开展线上公益主题海报设计教育实践——苏州大学师生抗击疫情公益海报创作纪实

从践行社会责任的设计教育工作人才培养目标出发,在疫情期间,组织学生,深入了解社会生活的工艺诉求,通过线上线下的教学模式,指导学生创作抗击疫情公益海报。这种融入网络远程教学与实践教育的活动,不仅提升了学生的社会责任感,激活了假期课堂模式,而且提升了学生设计实践能力,实现了“立德树人”的人才培养目标。