Spodoptera frugiperda(Lepidoptera:Noctuidae)is an important migratory agricultural pest worldwide,which has invaded many countries in the Old World since 2016 and now poses a serious threat to world food security.The ...Spodoptera frugiperda(Lepidoptera:Noctuidae)is an important migratory agricultural pest worldwide,which has invaded many countries in the Old World since 2016 and now poses a serious threat to world food security.The present monitoring and early warning strategies for the fall army worm(FAW)mainly focus on adult population density,but lack an information technology platform for precisely forecasting the reproductive dynamics of the adults.In this study,to identify the developmental status of the adults,we first utilized female ovarian images to extract and screen five features combined with the support vector machine(SVM)classifier and employed male testes images to obtain the testis circular features.Then,we established models for the relationship between oviposition dynamics and the developmental time of adult reproductive organs using laboratory tests.The results show that the accuracy of female ovary development stage determination reached 91%.The mean standard error(MSE)between the actual and predicted values of the ovarian developmental time was 0.2431,and the mean error rate between the actual and predicted values of the daily oviposition quantity was 12.38%.The error rate for the recognition of testis diameter was 3.25%,and the predicted and actual values of the testis developmental time in males had an MSE of 0.7734.A WeChat applet for identifying the reproductive developmental state and predicting reproduction of S.frugiperda was developed by integrating the above research results,and it is now available for use by anyone involved in plant protection.This study developed an automated method for accurately forecasting the reproductive dynamics of S.frugiperda populations,which can be helpful for the construction of a population monitoring and early warning system for use by both professional experts and local people at the county level.展开更多
This paper aims to improve the pre-hospital first-aid knowledge and pre-hospital first-aid success rate and optimize the pre-hospital emergency system.This paper mainly discusses a comprehensive pre-hospital emergency...This paper aims to improve the pre-hospital first-aid knowledge and pre-hospital first-aid success rate and optimize the pre-hospital emergency system.This paper mainly discusses a comprehensive pre-hospital emergency system,which consists of the hardware part and software part.The hardware is based on the international cardiopulmonary resuscitation guidelines,and a cardiopulmonary resuscitation(CPR)training auxiliary equipment is developed,which can be applied in pre-hospital first aid training to help people perform accurate chest compressions.The software part is based on the WeChat applet platform to set up a pre-hospital first-aid dispatching system that connects callers and CPR rescuers.The software system effectively improves the pre-hospital CPR first-aid system and increases the rescue success rate of cardiac arrest patients.展开更多
基金supported by the National Natural Science Foundation of China(31727901)the National Key R&D Program of China(2021YFD1400702)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences.
文摘Spodoptera frugiperda(Lepidoptera:Noctuidae)is an important migratory agricultural pest worldwide,which has invaded many countries in the Old World since 2016 and now poses a serious threat to world food security.The present monitoring and early warning strategies for the fall army worm(FAW)mainly focus on adult population density,but lack an information technology platform for precisely forecasting the reproductive dynamics of the adults.In this study,to identify the developmental status of the adults,we first utilized female ovarian images to extract and screen five features combined with the support vector machine(SVM)classifier and employed male testes images to obtain the testis circular features.Then,we established models for the relationship between oviposition dynamics and the developmental time of adult reproductive organs using laboratory tests.The results show that the accuracy of female ovary development stage determination reached 91%.The mean standard error(MSE)between the actual and predicted values of the ovarian developmental time was 0.2431,and the mean error rate between the actual and predicted values of the daily oviposition quantity was 12.38%.The error rate for the recognition of testis diameter was 3.25%,and the predicted and actual values of the testis developmental time in males had an MSE of 0.7734.A WeChat applet for identifying the reproductive developmental state and predicting reproduction of S.frugiperda was developed by integrating the above research results,and it is now available for use by anyone involved in plant protection.This study developed an automated method for accurately forecasting the reproductive dynamics of S.frugiperda populations,which can be helpful for the construction of a population monitoring and early warning system for use by both professional experts and local people at the county level.
基金Natural Science Foundation of Guangdong Province,grant number:2016KZDXM013
文摘This paper aims to improve the pre-hospital first-aid knowledge and pre-hospital first-aid success rate and optimize the pre-hospital emergency system.This paper mainly discusses a comprehensive pre-hospital emergency system,which consists of the hardware part and software part.The hardware is based on the international cardiopulmonary resuscitation guidelines,and a cardiopulmonary resuscitation(CPR)training auxiliary equipment is developed,which can be applied in pre-hospital first aid training to help people perform accurate chest compressions.The software part is based on the WeChat applet platform to set up a pre-hospital first-aid dispatching system that connects callers and CPR rescuers.The software system effectively improves the pre-hospital CPR first-aid system and increases the rescue success rate of cardiac arrest patients.
