The research analyzed characters of rice/wheat growth and yield structure in Puyang and explored the effects of droughts and floods on the crops. The re-sults showed that droughts and floods had significant effects on...The research analyzed characters of rice/wheat growth and yield structure in Puyang and explored the effects of droughts and floods on the crops. The re-sults showed that droughts and floods had significant effects on crop growth and yield. In Puyang, the relieving and prevention technology of the disasters is con-cluded. Specifical y, it is recommended to make ful use of agricultural climate re-sources in a rational way and select suitable crop varieties according to climate and disaster characters, fol owed by timely sowing and scientific crop arrangement. What＇s more, ploughing should proceed in deeper soil layers and management measures should be optimized to reduce the effects of disasters on crops. In addi-tion to that, disaster index system should be reinforced in terms of establishment, monitoring, warning and prevention to lay scientific foundations and provide refer-ences for safe crop production and preventing and reducing disasters.展开更多
This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republi...This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republic of Korea,where most fires are caused by human activities.To examine this tradeoff relationship,we develop a hybrid model that combines a robust optimization model with a stochastic simulation model.The robust optimization minimizes the expected number of fires not receiving a pre-defined response,such as the number of firefighting resources that must arrive at the fire within half an hour,subject to budget constraints and uncertainty about the daily number and location of fires.The simulation model produces a set of fire scenarios in which a combination of number,location,ignition time,and intensity of fires occur.Results show that fire ignition prevention is as cost-effective as initial attack firefighting resources given the current budget in the Republic of Korea for reducing the expected number of fires not covered by the predefined response.The mixed policy of fire suppression and fire prevention may produce some gains in efficiency relative to the dominant policy of strong fire suppression strategies.展开更多
Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving th...Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.展开更多
Citrus Huanglongbing(HLB)is an infectious disease transmitted by Asian citrus psyllids(ACP),which leads to serious economic losses in the citrus industry.Therefore,it is crucial to investigate the prevention and contr...Citrus Huanglongbing(HLB)is an infectious disease transmitted by Asian citrus psyllids(ACP),which leads to serious economic losses in the citrus industry.Therefore,it is crucial to investigate the prevention and control strategy of citrus HLB.In this paper,the dynamics of HLB propagation between citrus trees and ACP is considered.By applying reinforcement learning(RL)technique,an event-driven optimal prevention control(EDOPC)strategy is developed to ensure the HLB propagation model state converges to a disease-free equilibrium point.Initially,in order to address the challenge of obtaining precise models in practice,a radial basis function-based event-driven observer is built by adopting system input-output data to obtain the approximate HLB propagation model.Subsequently,an EDOPC strategy is devised,which updates only at triggering times to reduce management costs.Additionally,a single critic network structure is constructed to obtain the solution of the Hamilton-Jacobi-Bellman equation,thereby deriving an approximate EDOPC strategy.To align with real-world scenarios,the weights of the observer and the critic network are updated only at event occurrence times.Moreover,by employing the Lyapunov stability principle,the critic network weight error is proved to be uniformly ultimately bounded under the novel event-driven weight adjusting law.Finally,simulation experiments confirm the efficacy of the present RL-based EDOPC strategy.展开更多
Introduction:Data on inter-regional transmission clusters of Hepatitis C Virus(HCV)helps optimize targeted preventive strategies.This study aims to detect the national and international dimensions of HCV 1b transmissi...Introduction:Data on inter-regional transmission clusters of Hepatitis C Virus(HCV)helps optimize targeted preventive strategies.This study aims to detect the national and international dimensions of HCV 1b transmission clusters.Methods:Available published HCV 1b nonstructural protein 5B sequences sampled between 1989 and 2021 were collected,including 1,750 sequences from China and 482 comparable sequences from other countries.Network-based and tree-based approaches were introduced to detect transmission clusters and infer their relationships.Results:Three distinct transmission cluster patterns were identified across China:a large cluster with nationwide distribution,two medium clusters predominantly in the Central and Eastern China,and 103 small clusters scattered across 19 provincial-level administrative divisions.No genetic linkages were found between Chinese sequences and those from other countries.The medium clusters exhibited a similar expansion risk compared with the large cluster[adjusted odds ratio(aOR)=1.247,95%confidence interval(CI):0.862,1.804,P=0.241],but showed significantly lower inter-provincial transmission(aOR=0.255,95%CI:0.077,0.798,P=0.019).The small clusters demonstrated faster expansion[adjusted hazard ratio(aHR)=1.327,95%CI:1.050,1.676,P=0.018]and markedly reduced inter-provincial transmission(aOR=0.006,95%CI:0.002,0.014,P<0.001)compared to the large cluster.The Northeast China groups showed significantly higher interprovincial transmission risk compared to the Central China groups(aOR=11.461,95%CI:2.262,87.014,P=0.006).Conclusions:This study emphasizes the urgent need to establish a national molecular epidemiological surveillance network for detecting hidden transmission chains and monitoring the emergence of variants.展开更多
Accurate transient stability assessment(TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely...Accurate transient stability assessment(TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely used in TSA nowadays. Data-driven TSA model can be adopted in the stability constraints of preventive control optimization, but existing methods are mostly iteration-based ones, which may result in low efficiency, sometimes even non-convergence. In this paper,an analytical representation method of data-driven transient stability constraint is proposed based on a non-parametric regression model built for TSA. Key feature extraction and dominant sample selection are proposed to reduce the scale of the TSA model, and bi-level linearization is applied to further modify it.Optimal preventive control model is then formulated as a mixed-integer linear program(MILP) problem with the linearized analytical data-driven transient stability constraint, which can be solved without iterations. An overall procedure of datadriven TSA and preventive control is finally developed. Case studies show that the proposed method has high accuracy in TSA and can achieve effective preventive control of power system with high efficiency.展开更多
文摘The research analyzed characters of rice/wheat growth and yield structure in Puyang and explored the effects of droughts and floods on the crops. The re-sults showed that droughts and floods had significant effects on crop growth and yield. In Puyang, the relieving and prevention technology of the disasters is con-cluded. Specifical y, it is recommended to make ful use of agricultural climate re-sources in a rational way and select suitable crop varieties according to climate and disaster characters, fol owed by timely sowing and scientific crop arrangement. What＇s more, ploughing should proceed in deeper soil layers and management measures should be optimized to reduce the effects of disasters on crops. In addi-tion to that, disaster index system should be reinforced in terms of establishment, monitoring, warning and prevention to lay scientific foundations and provide refer-ences for safe crop production and preventing and reducing disasters.
基金supported by 2014 Yeungnam University Research Grant
文摘This study explores the tradeoff relationship between the number of initial attack firefighting resources and the level of fire ignition prevention efforts mitigating the probability of human-made fires in the Republic of Korea,where most fires are caused by human activities.To examine this tradeoff relationship,we develop a hybrid model that combines a robust optimization model with a stochastic simulation model.The robust optimization minimizes the expected number of fires not receiving a pre-defined response,such as the number of firefighting resources that must arrive at the fire within half an hour,subject to budget constraints and uncertainty about the daily number and location of fires.The simulation model produces a set of fire scenarios in which a combination of number,location,ignition time,and intensity of fires occur.Results show that fire ignition prevention is as cost-effective as initial attack firefighting resources given the current budget in the Republic of Korea for reducing the expected number of fires not covered by the predefined response.The mixed policy of fire suppression and fire prevention may produce some gains in efficiency relative to the dominant policy of strong fire suppression strategies.
基金Supported by National Natural Science Foundation of China(Grant Nos.51205347,51322506)Zhejiang Provincial Natural Science Foundation of China(Grant No.LR14E050003)+3 种基金Project of National Science and Technology Plan of China(Grant No.2013IM030500)Fundamental Research Funds for the Central Universities of ChinaInnovation Foundation of the State Key Laboratory of Fluid Power Transmission and Control of ChinaZhejiang University K.P.Chao’s High Technology Development Foundation of China
文摘Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.
文摘Citrus Huanglongbing(HLB)is an infectious disease transmitted by Asian citrus psyllids(ACP),which leads to serious economic losses in the citrus industry.Therefore,it is crucial to investigate the prevention and control strategy of citrus HLB.In this paper,the dynamics of HLB propagation between citrus trees and ACP is considered.By applying reinforcement learning(RL)technique,an event-driven optimal prevention control(EDOPC)strategy is developed to ensure the HLB propagation model state converges to a disease-free equilibrium point.Initially,in order to address the challenge of obtaining precise models in practice,a radial basis function-based event-driven observer is built by adopting system input-output data to obtain the approximate HLB propagation model.Subsequently,an EDOPC strategy is devised,which updates only at triggering times to reduce management costs.Additionally,a single critic network structure is constructed to obtain the solution of the Hamilton-Jacobi-Bellman equation,thereby deriving an approximate EDOPC strategy.To align with real-world scenarios,the weights of the observer and the critic network are updated only at event occurrence times.Moreover,by employing the Lyapunov stability principle,the critic network weight error is proved to be uniformly ultimately bounded under the novel event-driven weight adjusting law.Finally,simulation experiments confirm the efficacy of the present RL-based EDOPC strategy.
基金Supported by the National Natural Science Foundation of China(12071366)the project of the Disease Control and Prevention Administration of Guangxi Zhuang Autonomous Region(GXJKKJ24C002).
文摘Introduction:Data on inter-regional transmission clusters of Hepatitis C Virus(HCV)helps optimize targeted preventive strategies.This study aims to detect the national and international dimensions of HCV 1b transmission clusters.Methods:Available published HCV 1b nonstructural protein 5B sequences sampled between 1989 and 2021 were collected,including 1,750 sequences from China and 482 comparable sequences from other countries.Network-based and tree-based approaches were introduced to detect transmission clusters and infer their relationships.Results:Three distinct transmission cluster patterns were identified across China:a large cluster with nationwide distribution,two medium clusters predominantly in the Central and Eastern China,and 103 small clusters scattered across 19 provincial-level administrative divisions.No genetic linkages were found between Chinese sequences and those from other countries.The medium clusters exhibited a similar expansion risk compared with the large cluster[adjusted odds ratio(aOR)=1.247,95%confidence interval(CI):0.862,1.804,P=0.241],but showed significantly lower inter-provincial transmission(aOR=0.255,95%CI:0.077,0.798,P=0.019).The small clusters demonstrated faster expansion[adjusted hazard ratio(aHR)=1.327,95%CI:1.050,1.676,P=0.018]and markedly reduced inter-provincial transmission(aOR=0.006,95%CI:0.002,0.014,P<0.001)compared to the large cluster.The Northeast China groups showed significantly higher interprovincial transmission risk compared to the Central China groups(aOR=11.461,95%CI:2.262,87.014,P=0.006).Conclusions:This study emphasizes the urgent need to establish a national molecular epidemiological surveillance network for detecting hidden transmission chains and monitoring the emergence of variants.
基金supported by National Key R&D Program of China (No.2018YFB0904500)State Grid Corporation of China (No. SGLNDK00KJJS1800236)。
文摘Accurate transient stability assessment(TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely used in TSA nowadays. Data-driven TSA model can be adopted in the stability constraints of preventive control optimization, but existing methods are mostly iteration-based ones, which may result in low efficiency, sometimes even non-convergence. In this paper,an analytical representation method of data-driven transient stability constraint is proposed based on a non-parametric regression model built for TSA. Key feature extraction and dominant sample selection are proposed to reduce the scale of the TSA model, and bi-level linearization is applied to further modify it.Optimal preventive control model is then formulated as a mixed-integer linear program(MILP) problem with the linearized analytical data-driven transient stability constraint, which can be solved without iterations. An overall procedure of datadriven TSA and preventive control is finally developed. Case studies show that the proposed method has high accuracy in TSA and can achieve effective preventive control of power system with high efficiency.
