Public emergencies are generally sudden with huge real or potential danger to the whole society.The COVID-19 pandemic is a typical public emergency with a long duration involving a wide range of people,and has extreme...Public emergencies are generally sudden with huge real or potential danger to the whole society.The COVID-19 pandemic is a typical public emergency with a long duration involving a wide range of people,and has extremely bad social impact.The pandemic can be classified into four stages:initial stage,outbreak stage,durative stage and post-pandemic stage.The focus of mass media varied according to the characteristics of different stages.Based on different stages,mass media should change their roles timely and always be aware of the mainstream ideological construction in public opinions to firmly control the direction of public opinion by using the theory and method of communication.展开更多
[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infra...[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.展开更多
Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canol...Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canola.Butisanstar(BUT)and clopyralid(CLO)are widely used for broadleaf weed control in these rotations.However,how residual herbicide activity influences cotton growth and development is not well understood.This study evaluated these residual effects by measuring multiple growth parameters in a greenhouse.Cotton was grown for 40 days in soil incubated for 90 days with herbicide treatments arranged in a factorial design(type:BUT,CLO,and their combination;dose:0,1/2,1,2,and 5×recommended field dose[RFD]).Results Herbicide residues reduced cotton growth in a dose-dependent manner,with greater inhibition at higher doses.The combined BUT+CLO treatment produced the strongest negative effects,followed by CLO and then BUT alone.Compared with controls,seedling emergence declined by 12%–83%,root length by 12%–87%,plant height by 10%–84%,and chlorophyll index by 12%–80%across treatments from 1/2×RFD BUT to 5×RFD BUT+CLO.Root and shoot biomass also decreased significantly.Under the 5×RFD combined treatment,shoot N,P,and K concentrations dropped by 48%,78%,and 70%,respectively,relative to the control.Conclusions Even low levels of residual BUT and CLO impair cotton growth.To mitigate these effects,it should avoid planting cotton on recently treated soils,leave sufficient intervals between herbicide application and cotton planting,and apply soil amendments to boost microbial degradation.These measures are essential for sustaining soil health and cotton productivity.展开更多
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat...This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.展开更多
针对目前EPS(Emergency Power Supply,EPS)应急电源切换速度慢的问题,提出了一种快速切换的单相应急电源的数字化解决方案。基于锁相原理,令EPS输出电压和市电电压的大小、频率、相位保持一致,用DSP实现了EPS的快速切换技术,同时提出了...针对目前EPS(Emergency Power Supply,EPS)应急电源切换速度慢的问题,提出了一种快速切换的单相应急电源的数字化解决方案。基于锁相原理,令EPS输出电压和市电电压的大小、频率、相位保持一致,用DSP实现了EPS的快速切换技术,同时提出了一种简单的蓄电池在线监测系统硬件实现方式。并设计了一台50Hz,220V/1.5kVA的EPS应急电源,采用继电器切换,从市电出现异常时刻开始到切换完成时刻止,切换时间小于10ms。展开更多
The earth observation satellites(EOSs)scheduling problem for emergency tasks often presents many challenges.For example,the scheduling calculation should be completed in seconds,the scheduled task rate is supposed to ...The earth observation satellites(EOSs)scheduling problem for emergency tasks often presents many challenges.For example,the scheduling calculation should be completed in seconds,the scheduled task rate is supposed to be as high as possible,the disturbance measure of the scheme should be as low as possible,which may lead to the loss of important observation opportunities and data transmission delays.Existing scheduling algorithms are not designed for these requirements.Consequently,we propose a rolling horizon strategy(RHS)based on event triggering as well as a heuristic algorithm based on direct insertion,shifting,backtracking,deletion,and reinsertion(ISBDR).In the RHS,the driven scheduling mode based on the emergency task arrival and control station time window events are designed to transform the long-term,large-scale problem into a short-term,small-scale problem,which can improve the schedulability of the original scheduling scheme and emergency response sensitivity.In the ISBDR algorithm,the shifting rule with breadth search capability and backtracking rule with depth search capability are established to realize the rapid adjustment of the original plan and improve the overall benefit of the plan and early completion of emergency tasks.Simultaneously,two heuristic factors,namely the emergency task urgency degree and task conflict degree,are constructed to improve the emergency task scheduling guidance and algorithm efficiency.Finally,we conduct extensive experiments by means of simulations to compare the algorithms based on ISBDR and direct insertion,shifting,deletion,and reinsertion(ISDR).The results demonstrate that the proposed algorithm can improve the timeliness of emergency tasks and scheduling performance,and decrease the disturbance measure of the scheme,therefore,it is more suitable for emergency task scheduling.展开更多
It′s very useful tools for an instant analysis of organic pollutants monitoring using the HAPSITE portable GC-MS.It discusses how to use HAPSITE portable GC-MS in emergency monitoring and treatment.
To reduce the longitudinal coupler forces of heavy haul trains and improve the running safety, the velocity method and New-mark method were used for the coupler simulation and numerical integration, and a numerical mo...To reduce the longitudinal coupler forces of heavy haul trains and improve the running safety, the velocity method and New-mark method were used for the coupler simulation and numerical integration, and a numerical model on the longitudinal dynamics of heavy haul trains was established. Validation was performed against the experimental data. Using this model, the emergency braking process for a combined marshalling heavy haul train was investigated to obtain the distributions of the longitudinal compressive forces and strokes of coupler devices. Then, the influences of the initial braking velocity, the synchronization time of master and slave locomotives, the coupler stiffness and the vibrator mass on the longitudinal forces and strokes were analyzed. The results show that it should be avoided that the emergency braking starts at a low initial speed. Keeping synchronism between master locomotive and slave locomotives effectively helps to reduce the longitudinal forces. Reducing the coupler stiffness appropriately and adding rigid arm connections, the longitudinal vibration frequency can be brought down and the longitudinal forces will be decreased, which improves the running safety of heavy haul trains. All of these research results can provide a reference for the operation and development of heavy haul trains.展开更多
Satellite observation scheduling plays a significant role in improving the efficiency of satellite observation systems.Although many scheduling algorithms have been proposed,emergency tasks,characterized as importance...Satellite observation scheduling plays a significant role in improving the efficiency of satellite observation systems.Although many scheduling algorithms have been proposed,emergency tasks,characterized as importance and urgency（e.g.,observation tasks orienting to the earthquake area and military conflict area）,have not been taken into account yet.Therefore,it is crucial to investigate the satellite integrated scheduling methods,which focus on meeting the requirements of emergency tasks while maximizing the profit of common tasks.Firstly,a pretreatment approach is proposed,which eliminates conflicts among emergency tasks and allocates all tasks with a potential time-window to related orbits of satellites.Secondly,a mathematical model and an acyclic directed graph model are constructed.Thirdly,a hybrid ant colony optimization method mixed with iteration local search（ACO-ILS） is established to solve the problem.Moreover,to guarantee all solutions satisfying the emergency task requirement constraints,a constraint repair method is presented.Extensive experimental simulations show that the proposed integrated scheduling method is superior to two-phased scheduling methods,the performance of ACO-ILS is greatly improved in both evolution speed and solution quality by iteration local search,and ACO-ILS outperforms both genetic algorithm and simulated annealing algorithm.展开更多
基金This paper is a milestone of“Research on Effectively Guiding the Mental Health Education of Special College Students In Jilin University”,a scientific research project planned by Jilin Provincial Education Department(Project No.:JJKH20200590SK).
文摘Public emergencies are generally sudden with huge real or potential danger to the whole society.The COVID-19 pandemic is a typical public emergency with a long duration involving a wide range of people,and has extremely bad social impact.The pandemic can be classified into four stages:initial stage,outbreak stage,durative stage and post-pandemic stage.The focus of mass media varied according to the characteristics of different stages.Based on different stages,mass media should change their roles timely and always be aware of the mainstream ideological construction in public opinions to firmly control the direction of public opinion by using the theory and method of communication.
文摘[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
文摘Background The intensive use of herbicides in agriculture raises concerns about their residual impacts on non-target crops such as cotton(Gossypium hirsutum L.),which is often rotated with cereals,sugar beet,and canola.Butisanstar(BUT)and clopyralid(CLO)are widely used for broadleaf weed control in these rotations.However,how residual herbicide activity influences cotton growth and development is not well understood.This study evaluated these residual effects by measuring multiple growth parameters in a greenhouse.Cotton was grown for 40 days in soil incubated for 90 days with herbicide treatments arranged in a factorial design(type:BUT,CLO,and their combination;dose:0,1/2,1,2,and 5×recommended field dose[RFD]).Results Herbicide residues reduced cotton growth in a dose-dependent manner,with greater inhibition at higher doses.The combined BUT+CLO treatment produced the strongest negative effects,followed by CLO and then BUT alone.Compared with controls,seedling emergence declined by 12%–83%,root length by 12%–87%,plant height by 10%–84%,and chlorophyll index by 12%–80%across treatments from 1/2×RFD BUT to 5×RFD BUT+CLO.Root and shoot biomass also decreased significantly.Under the 5×RFD combined treatment,shoot N,P,and K concentrations dropped by 48%,78%,and 70%,respectively,relative to the control.Conclusions Even low levels of residual BUT and CLO impair cotton growth.To mitigate these effects,it should avoid planting cotton on recently treated soils,leave sufficient intervals between herbicide application and cotton planting,and apply soil amendments to boost microbial degradation.These measures are essential for sustaining soil health and cotton productivity.
文摘This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.
文摘针对目前EPS(Emergency Power Supply,EPS)应急电源切换速度慢的问题,提出了一种快速切换的单相应急电源的数字化解决方案。基于锁相原理,令EPS输出电压和市电电压的大小、频率、相位保持一致,用DSP实现了EPS的快速切换技术,同时提出了一种简单的蓄电池在线监测系统硬件实现方式。并设计了一台50Hz,220V/1.5kVA的EPS应急电源,采用继电器切换,从市电出现异常时刻开始到切换完成时刻止,切换时间小于10ms。
基金supported by the National Natural Science Foundation of China(71671059)
文摘The earth observation satellites(EOSs)scheduling problem for emergency tasks often presents many challenges.For example,the scheduling calculation should be completed in seconds,the scheduled task rate is supposed to be as high as possible,the disturbance measure of the scheme should be as low as possible,which may lead to the loss of important observation opportunities and data transmission delays.Existing scheduling algorithms are not designed for these requirements.Consequently,we propose a rolling horizon strategy(RHS)based on event triggering as well as a heuristic algorithm based on direct insertion,shifting,backtracking,deletion,and reinsertion(ISBDR).In the RHS,the driven scheduling mode based on the emergency task arrival and control station time window events are designed to transform the long-term,large-scale problem into a short-term,small-scale problem,which can improve the schedulability of the original scheduling scheme and emergency response sensitivity.In the ISBDR algorithm,the shifting rule with breadth search capability and backtracking rule with depth search capability are established to realize the rapid adjustment of the original plan and improve the overall benefit of the plan and early completion of emergency tasks.Simultaneously,two heuristic factors,namely the emergency task urgency degree and task conflict degree,are constructed to improve the emergency task scheduling guidance and algorithm efficiency.Finally,we conduct extensive experiments by means of simulations to compare the algorithms based on ISBDR and direct insertion,shifting,deletion,and reinsertion(ISDR).The results demonstrate that the proposed algorithm can improve the timeliness of emergency tasks and scheduling performance,and decrease the disturbance measure of the scheme,therefore,it is more suitable for emergency task scheduling.
文摘It′s very useful tools for an instant analysis of organic pollutants monitoring using the HAPSITE portable GC-MS.It discusses how to use HAPSITE portable GC-MS in emergency monitoring and treatment.
基金Project(U1334208)supported by the National Natural Science Foundation of ChinaProject(2016zzts331)supported by the Fundamental Research Funds for the Central Universities,China
文摘To reduce the longitudinal coupler forces of heavy haul trains and improve the running safety, the velocity method and New-mark method were used for the coupler simulation and numerical integration, and a numerical model on the longitudinal dynamics of heavy haul trains was established. Validation was performed against the experimental data. Using this model, the emergency braking process for a combined marshalling heavy haul train was investigated to obtain the distributions of the longitudinal compressive forces and strokes of coupler devices. Then, the influences of the initial braking velocity, the synchronization time of master and slave locomotives, the coupler stiffness and the vibrator mass on the longitudinal forces and strokes were analyzed. The results show that it should be avoided that the emergency braking starts at a low initial speed. Keeping synchronism between master locomotive and slave locomotives effectively helps to reduce the longitudinal forces. Reducing the coupler stiffness appropriately and adding rigid arm connections, the longitudinal vibration frequency can be brought down and the longitudinal forces will be decreased, which improves the running safety of heavy haul trains. All of these research results can provide a reference for the operation and development of heavy haul trains.
基金supported by the National Natural Science Foundation of China (61104180)the National Basic Research Program of China(973 Program) (97361361)
文摘Satellite observation scheduling plays a significant role in improving the efficiency of satellite observation systems.Although many scheduling algorithms have been proposed,emergency tasks,characterized as importance and urgency（e.g.,observation tasks orienting to the earthquake area and military conflict area）,have not been taken into account yet.Therefore,it is crucial to investigate the satellite integrated scheduling methods,which focus on meeting the requirements of emergency tasks while maximizing the profit of common tasks.Firstly,a pretreatment approach is proposed,which eliminates conflicts among emergency tasks and allocates all tasks with a potential time-window to related orbits of satellites.Secondly,a mathematical model and an acyclic directed graph model are constructed.Thirdly,a hybrid ant colony optimization method mixed with iteration local search（ACO-ILS） is established to solve the problem.Moreover,to guarantee all solutions satisfying the emergency task requirement constraints,a constraint repair method is presented.Extensive experimental simulations show that the proposed integrated scheduling method is superior to two-phased scheduling methods,the performance of ACO-ILS is greatly improved in both evolution speed and solution quality by iteration local search,and ACO-ILS outperforms both genetic algorithm and simulated annealing algorithm.
