Photocatalysis has been predicted as a promising technology for waste water treatment. N-doped zinc oxide has been used as an effective catalyst for carrying out number of chemical reactions, but limited work has been...Photocatalysis has been predicted as a promising technology for waste water treatment. N-doped zinc oxide has been used as an effective catalyst for carrying out number of chemical reactions, but limited work has been reported on use of N-doped ZnO as photocatalyst. In the present work, the photocatalytic degradation of Azure A was carried out in the presence of N-doped zinc oxide and the progress of the reaction was observed spectrophotometrically. The morphologies and structures of the as-synthesized nanomaterials were investigated by using FT-IR and DRS techniques. On the basis of observations, a tentative mechanism has been proposed for the photocatalytic degradation of dye.展开更多
Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phe...Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phenotypes mainly relies on manual measurement which is inefficient,subjective and destroys samples.Therefore,the paper proposes a nondestructive measurement method for the canopy phenotype of the watermelon plug seedlings based on deep learning.The Azure Kinect was used to shoot canopy color images,depth images,and RGB-D images of the watermelon plug seedlings.The Mask-RCNN network was used to classify,segment,and count the canopy leaves of the watermelon plug seedlings.To reduce the error of leaf area measurement caused by mutual occlusion of leaves,the leaves were repaired by CycleGAN,and the depth images were restored by image processing.Then,the Delaunay triangulation was adopted to measure the leaf area in the leaf point cloud.The YOLOX target detection network was used to identify the growing point position of each seedling on the plug tray.Then the depth differences between the growing point and the upper surface of the plug tray were calculated to obtain plant height.The experiment results show that the nondestructive measurement algorithm proposed in this paper achieves good measurement performance for the watermelon plug seedlings from the 1 true-leaf to 3 true-leaf stages.The average relative error of measurement is 2.33%for the number of true leaves,4.59%for the number of cotyledons,8.37%for the leaf area,and 3.27%for the plant height.The experiment results demonstrate that the proposed algorithm in this paper provides an effective solution for the nondestructive measurement of the canopy phenotype of the plug seedlings.展开更多
Windows Azure作为微软公司赢在未来的云计算平台,具有许多新的特性,正逐渐受到业界的青睐,因此在现阶段研究基于该平台来设计和开发大规模Web应用程序十分必要。首先分析Windows Azure云服务中与编程相关的关键组件,如计算服务、存储...Windows Azure作为微软公司赢在未来的云计算平台,具有许多新的特性,正逐渐受到业界的青睐,因此在现阶段研究基于该平台来设计和开发大规模Web应用程序十分必要。首先分析Windows Azure云服务中与编程相关的关键组件,如计算服务、存储服务和数据库服务的特点,特别是它们与本地开发的差异;在此基础上根据平台提出两个设计大规模Web应用程序的要点:计算资源的"无状态"处理和数据库的"横向"扩展,并给出了相应的实例进行说明。展开更多
文摘Photocatalysis has been predicted as a promising technology for waste water treatment. N-doped zinc oxide has been used as an effective catalyst for carrying out number of chemical reactions, but limited work has been reported on use of N-doped ZnO as photocatalyst. In the present work, the photocatalytic degradation of Azure A was carried out in the presence of N-doped zinc oxide and the progress of the reaction was observed spectrophotometrically. The morphologies and structures of the as-synthesized nanomaterials were investigated by using FT-IR and DRS techniques. On the basis of observations, a tentative mechanism has been proposed for the photocatalytic degradation of dye.
基金funded by the National Key Research and Development Program of China(Grant No.2019YFD1001900)the HZAU-AGIS Cooperation Fund(Grant No.SZYJY2022006).
文摘Nondestructive measurement technology of phenotype can provide substantial phenotypic data support for applications such as seedling breeding,management,and quality testing.The current method of measuring seedling phenotypes mainly relies on manual measurement which is inefficient,subjective and destroys samples.Therefore,the paper proposes a nondestructive measurement method for the canopy phenotype of the watermelon plug seedlings based on deep learning.The Azure Kinect was used to shoot canopy color images,depth images,and RGB-D images of the watermelon plug seedlings.The Mask-RCNN network was used to classify,segment,and count the canopy leaves of the watermelon plug seedlings.To reduce the error of leaf area measurement caused by mutual occlusion of leaves,the leaves were repaired by CycleGAN,and the depth images were restored by image processing.Then,the Delaunay triangulation was adopted to measure the leaf area in the leaf point cloud.The YOLOX target detection network was used to identify the growing point position of each seedling on the plug tray.Then the depth differences between the growing point and the upper surface of the plug tray were calculated to obtain plant height.The experiment results show that the nondestructive measurement algorithm proposed in this paper achieves good measurement performance for the watermelon plug seedlings from the 1 true-leaf to 3 true-leaf stages.The average relative error of measurement is 2.33%for the number of true leaves,4.59%for the number of cotyledons,8.37%for the leaf area,and 3.27%for the plant height.The experiment results demonstrate that the proposed algorithm in this paper provides an effective solution for the nondestructive measurement of the canopy phenotype of the plug seedlings.
