Rational application of different forms of nitrogen（N） fertilizer for peanut（Arachis hypogaea L.） requires tracking the N supplied sources which are commonly not available in the differences among the three source...Rational application of different forms of nitrogen（N） fertilizer for peanut（Arachis hypogaea L.） requires tracking the N supplied sources which are commonly not available in the differences among the three sources：root nodule,soil and fertilizer.In this study,two kinds of peanut plants（nodulated variety（Huayu 22） and non-nodulated variety（NN-1）） were choosed and four kinds of N fertilizers：urea-N（CONH_2-N）,ammonium-N（NH_4~＋-N）,nitrate-N（NO_3^--N） and NH_4~＋ ＋NO_3^--N labeled by^（15）N isotope were applied in the field barrel experiment in Chengyang Experimental Station,Shandong Province,China,to determine the N supplied sources and N use efficiency over peanut growing stages.The results showed that intensities and amounts of N supply from the three sources were all higher at middle growing stages（pegging phase and podding phase）.The accumulated amounts of N supply from root nodule,soil and fertilizer over the growing stages were 8.3,5.3 and 3.8g m^（-2） in CONH_2-N treatment,which are all significantly higher than in the other three treatments.At seedling phase,soil supplied the most N for peanut growth,then root nodule controlled the N supply at pegging phase and podding phase,but soil mainly provided N again at the last stage（pod filling phase）.For the whole growing stages,root nodule supplied the most N（47.8 and 43.0%） in CONH_2-N and NH_4~＋-N treatments,whereas soil supplied the most N（41.7 and 40.9%） in NH_4~＋ ＋NO_3^--N and NO_3^--N treatments.The N use efficiency was higher at pegging phase and podding phase,while accumulated N use efficiency over the growing stages was higher in CONH_2-N treatment（42.2%） than in other three treatments（30.4%in NH_4~＋-N treatment,29.4%in NO_3^--N treatment,29.4%in NH_4~＋ ＋NO_3^--N treatment）.In peanut growing field,application of CONH_2-N is a better way to increase the supply of N from root nodule and improve the N use efficiency.展开更多
Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for ...Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for high recognition accuracy with datasets with problems such as scenes with blurred pictures,and inconsistent objects.To address this challenge,we proposed an effective,lightweight object detector method called the RFNet model(YOLO-FR).The YOLO-FR is a lightweight and effective model.Specifically,for efficient multi-scale feature extraction,effective feature pyramid shared convolutional(FPSC)was designed to improve the feature extract performance by leveraging convolutional layers with varying dilation rates from the input image in the backbone.Secondly,to address the problem of multi-scale variability in the scene,we design the Rep Ghost fusion Cross Stage Partial and Efficient Layer Aggregation Network(RGCSPELAN)to improve the network performance further and reduce the amount of computation and the number of parameters.In addition,by conducting experimental valuation on the SCB dataset3 and STBD-08 dataset.Experimental results indicate that,compared to the baseline model,the RFNet model has increased mean accuracy precision(mAP@50)from 69.6%to 71.0%on the SCB dataset3 and from 91.8%to 93.1%on the STBD-08 dataset.The RFNet approach has effectiveness precision at 68.6%,surpassing the baseline method(YOLOv11)at 3.3%and archieve the minimal size(4.9 M)on the SCB dataset3.Finally,comparing it with other algorithms,it accurately detects student behavior in complex classroom environments results confirmed that RFNet is well-suited for real-time and efficiently recognizing classroom behaviors.展开更多
This paper presents the experimental results to understand the performance of moderately loaded high speed single stage transonic axial flow compressor subjected to various configurations of axial extensions of bend s...This paper presents the experimental results to understand the performance of moderately loaded high speed single stage transonic axial flow compressor subjected to various configurations of axial extensions of bend skewed casing treatment with moderate porosity.The bend skewed casing treatment of 33%porosity was coupled with rectangular plenum chamber of depth equal to the slots depth.The five axial extensions of 20%,40%,60%,80%and 100%were used for the experimental evaluations of compressor performance.The main objective was to identify the optimum extension of the casing treatment with reference to rotor leading edge which results in maximum stall margin improvements with minimum loss in the stage efficiency.At each axial extension the compressor performance is distinctive.The improvement in the stall margin was very significant at some axial extensions with 4%–5%penalty in the stage efficiency.The compressors stage shows recovery in terms of efficiency at lower axial extensions of 20%and 40%with increase in the peak stage efficiency.Measurements of flow parameters showed the typical behaviors at near stall flow conditions.Hot wire sensor was placed at the rotor upstream in the tip region to capture the oscillations in the inlet axial and tangential velocities at stall conditions.In the absence of casing treatment the compressor exhibit abrupt stall with very high oscillations in the inlet axial and tangential velocity of the flow.The extents of oscillations reduce with bend skewed casing treatment.Few measurements were also performed in the plenum chamber and salient results are presented in this paper.展开更多
基金supported by the Youth Scientific Research Foundation of Shandong Academy of Agricultural Sciences, China(2014QNM27)the Applying Basic Research Project of Qingdao,Shandong Province,China(14-2-4-90-jch)+3 种基金the Modern Agricultural Industry Technology System,China (SDAIT-05-021-04)the National Key Technology R&D Program of China(2014BAD11B04)the Key Innovation of Science and Technology Project of Shandong Academy of Agricultural Sciences,China(2014CXZ06-22014CXZ11-2)
文摘Rational application of different forms of nitrogen（N） fertilizer for peanut（Arachis hypogaea L.） requires tracking the N supplied sources which are commonly not available in the differences among the three sources：root nodule,soil and fertilizer.In this study,two kinds of peanut plants（nodulated variety（Huayu 22） and non-nodulated variety（NN-1）） were choosed and four kinds of N fertilizers：urea-N（CONH_2-N）,ammonium-N（NH_4~＋-N）,nitrate-N（NO_3^--N） and NH_4~＋ ＋NO_3^--N labeled by^（15）N isotope were applied in the field barrel experiment in Chengyang Experimental Station,Shandong Province,China,to determine the N supplied sources and N use efficiency over peanut growing stages.The results showed that intensities and amounts of N supply from the three sources were all higher at middle growing stages（pegging phase and podding phase）.The accumulated amounts of N supply from root nodule,soil and fertilizer over the growing stages were 8.3,5.3 and 3.8g m^（-2） in CONH_2-N treatment,which are all significantly higher than in the other three treatments.At seedling phase,soil supplied the most N for peanut growth,then root nodule controlled the N supply at pegging phase and podding phase,but soil mainly provided N again at the last stage（pod filling phase）.For the whole growing stages,root nodule supplied the most N（47.8 and 43.0%） in CONH_2-N and NH_4~＋-N treatments,whereas soil supplied the most N（41.7 and 40.9%） in NH_4~＋ ＋NO_3^--N and NO_3^--N treatments.The N use efficiency was higher at pegging phase and podding phase,while accumulated N use efficiency over the growing stages was higher in CONH_2-N treatment（42.2%） than in other three treatments（30.4%in NH_4~＋-N treatment,29.4%in NO_3^--N treatment,29.4%in NH_4~＋ ＋NO_3^--N treatment）.In peanut growing field,application of CONH_2-N is a better way to increase the supply of N from root nodule and improve the N use efficiency.
基金suported by the Fundamental Research Grant Scheme(FRGS)of Universiti Sains Malaysia,Research Number:FRGS/1/2024/ICT02/USM/02/1.
文摘Classroom behavior recognition is a hot research topic,which plays a vital role in assessing and improving the quality of classroom teaching.However,existing classroom behavior recognition methods have challenges for high recognition accuracy with datasets with problems such as scenes with blurred pictures,and inconsistent objects.To address this challenge,we proposed an effective,lightweight object detector method called the RFNet model(YOLO-FR).The YOLO-FR is a lightweight and effective model.Specifically,for efficient multi-scale feature extraction,effective feature pyramid shared convolutional(FPSC)was designed to improve the feature extract performance by leveraging convolutional layers with varying dilation rates from the input image in the backbone.Secondly,to address the problem of multi-scale variability in the scene,we design the Rep Ghost fusion Cross Stage Partial and Efficient Layer Aggregation Network(RGCSPELAN)to improve the network performance further and reduce the amount of computation and the number of parameters.In addition,by conducting experimental valuation on the SCB dataset3 and STBD-08 dataset.Experimental results indicate that,compared to the baseline model,the RFNet model has increased mean accuracy precision(mAP@50)from 69.6%to 71.0%on the SCB dataset3 and from 91.8%to 93.1%on the STBD-08 dataset.The RFNet approach has effectiveness precision at 68.6%,surpassing the baseline method(YOLOv11)at 3.3%and archieve the minimal size(4.9 M)on the SCB dataset3.Finally,comparing it with other algorithms,it accurately detects student behavior in complex classroom environments results confirmed that RFNet is well-suited for real-time and efficiently recognizing classroom behaviors.
基金Authors take this opportunity to thank Director,CSIRNAL,for funding the research program through elevenths five year plan and allow publishing the results.
文摘This paper presents the experimental results to understand the performance of moderately loaded high speed single stage transonic axial flow compressor subjected to various configurations of axial extensions of bend skewed casing treatment with moderate porosity.The bend skewed casing treatment of 33%porosity was coupled with rectangular plenum chamber of depth equal to the slots depth.The five axial extensions of 20%,40%,60%,80%and 100%were used for the experimental evaluations of compressor performance.The main objective was to identify the optimum extension of the casing treatment with reference to rotor leading edge which results in maximum stall margin improvements with minimum loss in the stage efficiency.At each axial extension the compressor performance is distinctive.The improvement in the stall margin was very significant at some axial extensions with 4%–5%penalty in the stage efficiency.The compressors stage shows recovery in terms of efficiency at lower axial extensions of 20%and 40%with increase in the peak stage efficiency.Measurements of flow parameters showed the typical behaviors at near stall flow conditions.Hot wire sensor was placed at the rotor upstream in the tip region to capture the oscillations in the inlet axial and tangential velocities at stall conditions.In the absence of casing treatment the compressor exhibit abrupt stall with very high oscillations in the inlet axial and tangential velocity of the flow.The extents of oscillations reduce with bend skewed casing treatment.Few measurements were also performed in the plenum chamber and salient results are presented in this paper.
