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91.
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Yuanyuan Zhang Haiyan Lu Bing Wang Zhuo Zhang Xiaorong Lin Zhongzheng Chen Bin Li 《International Journal of Food Science & Technology》2015,50(6):1397-1404
Removal of imidacloprid and acetamiprid in tea infusions by microfiltration membrane using dead‐end model was investigated in the present study. The results showed that microfiltration significantly promoted the removal of both pesticides (P < 0.05) in tea infusions. Furthermore, the extent of removal was strongly influenced by the pore size of membrane, operational pressure and the concentrations of tea infusions. The initial concentration of imidacloprid and acetamiprid showed no significant effect on their removal rates. The maximum removal rates were 79.7% for imidacloprid and 81.9% acetamiprid. The changes in major chemical components of tea infusions after microfiltration were evaluated. The results indicated that microfiltration caused no considerable changes in total polyphenols and total free amino acids, and small but statistically significant losses (6.3–18.0%) of eight catechins and three methylxanthines when filtration volume reached to 200 mL. The present study validated the application of microfiltration as a potentially feasible and promising method for the removal of imidacloprid and acetamiprid residues from tea infusions. 相似文献
93.
Zhang Keguo Cao Yang An Jianlin Wang Keyi 《Journal of Mechanical Science and Technology》2021,35(12):5405-5413
Journal of Mechanical Science and Technology - The flow stress increases with the increase in strain rate. This phenomenon is the strain rate effect of plastic deformation. Hopkinson experiment... 相似文献
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Huizhu Cai Bingbing Chen Xiao Zhang Yuchen Deng Dequan Xiao Ding Ma Chuan Shi 《Nano Research》2021,14(1):122-130
Over recent years,catalytic materials of Fe-N-C species have been recognized being active for oxygen reduction reaction(ORR).However,the identification of active site remains challenging as it generally involves a pyrolysis process and mixed components being obtained.Herein Fe3C/C and Fe2N/C samples were synthesized by temperature programmed reduction of Fe precursors in 15%CH4/H2and pure NH3,respectively.By acid leaching of Fe2N/C sample,only single sites of FeN4species were presented,providing an ideal model for identification of catalytic functions of the single sites of FeN4in ORR.A correlation was conducted between the concentration of FeⅡN4in low spin state by Mossbauer spectra and the kinetic current density at 0.8 V in alkaline media,and such a structure-performance correlation assures the catalytic roles of low spin FeⅡN4 species as highly active sites for the ORR. 相似文献
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Zhijiang Li Yingping Zheng Liqin Cao Lei Jiao Yanfei Zhong Caiyi Zhang 《Color research and application》2020,45(4):656-670
Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results. 相似文献