Asparagus stem blight,also known as“asparagus cancer”,is a serious plant disease with a regional distribution.The widespread occurrence of the disease has had a negative impact on the yield and quality of asparagus ...Asparagus stem blight,also known as“asparagus cancer”,is a serious plant disease with a regional distribution.The widespread occurrence of the disease has had a negative impact on the yield and quality of asparagus and has become one of the main problems threatening asparagus production.To improve the ability to accurately identify and localize phenotypic lesions of stem blight in asparagus and to enhance the accuracy of the test,a YOLOv8-CBAM detection algorithm for asparagus stem blight based on YOLOv8 was proposed.The algorithm aims to achieve rapid detection of phenotypic images of asparagus stem blight and to provide effective assistance in the control of asparagus stem blight.To enhance the model’s capacity to capture subtle lesion features,the Convolutional Block AttentionModule(CBAM)is added after C2f in the head.Simultaneously,the original CIoU loss function in YOLOv8 was replaced with the Focal-EIoU loss function,ensuring that the updated loss function emphasizes higher-quality bounding boxes.The YOLOv8-CBAM algorithm can effectively detect asparagus stem blight phenotypic images with a mean average precision(mAP)of 95.51%,which is 0.22%,14.99%,1.77%,and 5.71%higher than the YOLOv5,YOLOv7,YOLOv8,and Mask R-CNN models,respectively.This greatly enhances the efficiency of asparagus growers in identifying asparagus stem blight,aids in improving the prevention and control of asparagus stem blight,and is crucial for the application of computer vision in agriculture.展开更多
In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the wh...In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.展开更多
Background With the aim of addressing the difficulty in identifying temperatures in virtual chemistry experiments,we propose a temperature-sensing simulation method of virtual chemistry experiments.Methods We construc...Background With the aim of addressing the difficulty in identifying temperatures in virtual chemistry experiments,we propose a temperature-sensing simulation method of virtual chemistry experiments.Methods We construct a virtual chemistry experiment temperature simulation platform,based on which a wearable temperature generation device is developed.The typical middle school virtual experiments of concentrated sulfuric acid dilution and ammonium nitrate dissolution are conducted to verify the actual effect of the device.Results The platform is capable to indicate near real-world experimental situations.The performance of the device not only meets the temperature sensing characteristics of human skin,but also matches the temperature change of virtual chemistry experiments in real-time.Conclusions It is demonstrated that this temperature-sensing simulation method can represent exothermic or endothermic chemistry experiments,which is beneficial for students to gain understanding of the principles of thermal energy transformation in chemical reactions,thus avoiding the danger that may be posed in the course of traditional teaching of chemistry experiments effectively.Although this method does not have a convenient enough operation for users,the immersion of virtual chemical experiments can be enhanced.展开更多
This study investigated a combined low-thermal and CaO_(2)pretreatment to enhance the volatile fatty acid(VFA)production from waste activated sludge(WAS).The fermentative product was added to a sequencing batch reacto...This study investigated a combined low-thermal and CaO_(2)pretreatment to enhance the volatile fatty acid(VFA)production from waste activated sludge(WAS).The fermentative product was added to a sequencing batch reactor(SBR)as an external carbon source to enhance nitrogen removal.The results showed that the combined pretreatment improved WAS solubilization,releasing more biodegradable substrates,such as proteins and polysaccharides,from TB-EPS to LB-EPS and S-EPS.The maximum VFA production of 3529±188 mg COD/L was obtained in the combined pretreatment(0.2 g CaO_(2)/g VS+70℃for 60 min),which was 2.1 and 1.4-fold of that obtained from the sole low-thermal pretreatment and the control test,respectively.Consequently,when the fermentative liquid was added as an external denitrification carbon source,the effluent total nitrogen decreased to Class A of the discharge standard for pollutants in rural wastewater treatment plants in most areas of China.展开更多
基金supported by the Feicheng Artificial Intelligence Robot and Smart Agriculture Service Platform(381387).
文摘Asparagus stem blight,also known as“asparagus cancer”,is a serious plant disease with a regional distribution.The widespread occurrence of the disease has had a negative impact on the yield and quality of asparagus and has become one of the main problems threatening asparagus production.To improve the ability to accurately identify and localize phenotypic lesions of stem blight in asparagus and to enhance the accuracy of the test,a YOLOv8-CBAM detection algorithm for asparagus stem blight based on YOLOv8 was proposed.The algorithm aims to achieve rapid detection of phenotypic images of asparagus stem blight and to provide effective assistance in the control of asparagus stem blight.To enhance the model’s capacity to capture subtle lesion features,the Convolutional Block AttentionModule(CBAM)is added after C2f in the head.Simultaneously,the original CIoU loss function in YOLOv8 was replaced with the Focal-EIoU loss function,ensuring that the updated loss function emphasizes higher-quality bounding boxes.The YOLOv8-CBAM algorithm can effectively detect asparagus stem blight phenotypic images with a mean average precision(mAP)of 95.51%,which is 0.22%,14.99%,1.77%,and 5.71%higher than the YOLOv5,YOLOv7,YOLOv8,and Mask R-CNN models,respectively.This greatly enhances the efficiency of asparagus growers in identifying asparagus stem blight,aids in improving the prevention and control of asparagus stem blight,and is crucial for the application of computer vision in agriculture.
基金The authors acknowledge financial support for this research from the National Key Research and Development Program of China(2017YFB0403300 and 2017YFB043305)the National Natural Science Foundation of China(51425405 and 51874269),the National Science-Technology Support Plan Projects(2015BAB02B05)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2014037).Zhi Sun acknowledges financial support from the National Youth Thousand Talents Program.The authors acknowledge constructive suggestions from Prof.Jianxin Yang.
文摘In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.
基金the National Key Research and Development Program of China(2018YFB1004901)Zhejiang Natural Science Fund Project of China(LY20F020019,LQ19F020012,LQ20F020001)+1 种基金Zhejiang Basic Public Welfare Research Project of China(LGF19E050005)and Major Scientific Research Project of Zhejiang Lab(2019MC0AD01).
文摘Background With the aim of addressing the difficulty in identifying temperatures in virtual chemistry experiments,we propose a temperature-sensing simulation method of virtual chemistry experiments.Methods We construct a virtual chemistry experiment temperature simulation platform,based on which a wearable temperature generation device is developed.The typical middle school virtual experiments of concentrated sulfuric acid dilution and ammonium nitrate dissolution are conducted to verify the actual effect of the device.Results The platform is capable to indicate near real-world experimental situations.The performance of the device not only meets the temperature sensing characteristics of human skin,but also matches the temperature change of virtual chemistry experiments in real-time.Conclusions It is demonstrated that this temperature-sensing simulation method can represent exothermic or endothermic chemistry experiments,which is beneficial for students to gain understanding of the principles of thermal energy transformation in chemical reactions,thus avoiding the danger that may be posed in the course of traditional teaching of chemistry experiments effectively.Although this method does not have a convenient enough operation for users,the immersion of virtual chemical experiments can be enhanced.
基金supported by the Major Science and Technology Program for Water Pollution Control and Treatment(No.2018ZX07110-002)。
文摘This study investigated a combined low-thermal and CaO_(2)pretreatment to enhance the volatile fatty acid(VFA)production from waste activated sludge(WAS).The fermentative product was added to a sequencing batch reactor(SBR)as an external carbon source to enhance nitrogen removal.The results showed that the combined pretreatment improved WAS solubilization,releasing more biodegradable substrates,such as proteins and polysaccharides,from TB-EPS to LB-EPS and S-EPS.The maximum VFA production of 3529±188 mg COD/L was obtained in the combined pretreatment(0.2 g CaO_(2)/g VS+70℃for 60 min),which was 2.1 and 1.4-fold of that obtained from the sole low-thermal pretreatment and the control test,respectively.Consequently,when the fermentative liquid was added as an external denitrification carbon source,the effluent total nitrogen decreased to Class A of the discharge standard for pollutants in rural wastewater treatment plants in most areas of China.
