Investigation and control of a Plasmodium falciparum malaria outbreak in Shan Special Region II of Myanmar along the China-Myanmar Border from June to December 2014

Background:From 2007 to 2013,intensive control measures reduced malaria burden by 90%along the China-Myanmar border.However,despite these measures a P.falciparum malaria outbreak was reported in the Shan Special Region II of Myanmar in June of 2014.Methods:Epidemiological,parasitological and entomological investigations were performed.Dihydroartemisinin piperaquine(DAPQ)was immediately administered to treat parasite positive individuals.Long lasting insecticidal nets(LLIN),indoor residual spraying(IRS)with insecticides and behavior change communication(BCC)were also provided for outbreak control.An embedded efficacy study was conducted evaluating DP.Molecular genotyping via polymerase chain reaction(PCR)was performed on the Kelch gene on chromosome 13.Results:All infections were identified as Plasmodium falciparum by RDT and microscopy.Two fatalities resulted from the outbreak.The attack rate was 72.8%(67/92)and the incidence density rate was 14.2 per 100 person-weeks.The positive rate of rapid diagnostic test(RDT)was 72.2%(65/90)and microscopically-determine parasite rate 42.2%(38/90).Adjusted odds ratio(OR)of multivariate logistic regression analysis for aged<15 years,15–45 years,inappropriate treatment from a private healer and lack of bed nets were 13.51(95%confidence interval,2.21–105.89),7.75(1.48–44.97),3.78(1.30–46.18)and 3.21(1.21–15.19)respectively.In the six surrounding communities of the outbreak site,positive RDT rate was 1.2%(4/328)and microscopically-determine parasite rate 0.6%(2/328).Two light traps collected a total of 110 anopheline mosquitoes including local vectors,An.minimus,An.sinensis and An.maculates.After intensive control,the detection of malaria attacks,parasites and antigen were reduced to zero between July 1 and December 1,2014.The cure rate of P.falciparum patients at day 42 was 94.3%(95%CI,80.8–99.3%).The PCR did not detect K13-propeller mutations.Conclusion:Imported P.falciparum caused the outbreak.Age,seeking inappropriate treatment and lack of bed nets were risk factors for infection during the outbreak.P.falciparum was sensitive to treatment with DAPQ.The integrated measures controlled the outbreak and prevented the spread of P.falciparum effectively.The results of this study indicate that malaria control on the China-Myanmar border,especially among special populations,needs further collaboration between China,Myanmar and international societies.

Multi-class classification method for steel surface defects with feature noise

Defect classification is the key task of a steel surface defect detection system.The current defect classification algorithms have not taken the feature noise into consideration.In order to reduce the adverse impact of feature noise,an anti-noise multi-class classification method was proposed for steel surface defects.On the one hand,a novel anti-noise support vector hyper-spheres(ASVHs)classifier was formulated.For N types of defects,the ASVHs classifier built N hyper-spheres.These hyper-spheres were insensitive to feature and label noise.On the other hand,in order to reduce the costs of online time and storage space,the defect samples were pruned by support vector data description with parameter iteration adjustment strategy.In the end,the ASVHs classifier was built with sparse defect samples set and auxiliary information.Experimental results show that the novel multi-class classification method has high efficiency and accuracy for corrupted defect samples in steel surface.

Decentralized runtime enforcement for robotic swarms

Robotic swarms are usually designed in a bottom-up way,which can make robotic swarms vulnerable to environmental impact.It is particularly true for the widely used control mode of robotic swarms,where it is often the case that neither the correctness of the swarming tasks at the macro level nor the safety of the interaction among agents at the micro level can be guaranteed.To ensure that the behaviors are safe at runtime,it is necessary to take into account the property guard approaches for robotic swarms in uncertain environments.Runtime enforcement is an approach which can guarantee the given properties in system execution and has no scalability issue.Although some runtime enforcement methods have been studied and applied in different domains,they cannot effectively solve the problem of property enforcement on robotic swarm tasks at present.In this paper,an enforcement method is proposed on swarms which should satisfy multi-level properties in uncertain environments.We introduce a macromicro property enforcing framework with the notion of agent shields and a discrete-time enforcing mechanism called D-time enforcing.To realize this method,a domain specification language and the corresponding enforcer synthesis algorithms are developed.We then apply the approach to enforce the properties of the simulated robotic swarm in the robotflocksim platform.We evaluate and show the effectiveness of the method with experiments on specific unmanned aerial vehicle swarm tasks.