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    Analysis of the durability of fly ash concrete with alkaline activator dosage
    LUO Jia-hui, GONG Ai-min, WANG Fu-lai, SHAO Shan-qing, WANG Ran, YONG Kang, JIN Zhuo, HUANG Yi-er
    HUBEI AGRICULTURAL SCIENCES    2024, 63 (12): 178-184.   DOI: 10.14088/j.cnki.issn0439-8114.2024.12.032
    Abstract111)      PDF (6004KB)(5)       Save
    To improve the durability of fly ash concrete, fly ash concrete was used as the object to analyze the effects of different alkaline activator dosages (0%, 5%, 8%, and 10%) on the quality loss rate, relative dynamic elastic modulus, and compressive strength of fly ash concrete. Microscopic analysis of the alkali excitation process in fly ash concrete was conducted using scanning electron microscopy (SEM) and EDS spectroscopic diffraction patterns. The results showed that with the increase of alkaline activator dosage, the compressive strength of alkali activated fly ash concrete at different curing times showed a trend of first increasing and then decreasing. The quality loss rate of fly ash concrete with four different alkaline activator dosages increased with the increase of freeze-thaw cycles, and the quality loss rate of fly ash concrete was the smallest when the alkaline activator dosage was 8%;the relative dynamic elastic modulus of fly ash concrete with four different alkaline activator dosages decreased with the increase of freeze-thaw cycles, and the decrease in relative dynamic elastic modulus of fly ash concrete was the smallest when the alkaline activator dosage was 8%;the compressive strength of fly ash concrete with four different alkaline activator dosages decreased with the increase of freeze-thaw cycles. When the alkaline activator dosage was 8%, the compressive strength of fly ash concrete was the highest and the decrease in compressive strength was the smallest. The main elements of fly ash concrete with two alkaline activators (0%, 8%) were Ca, O, C, Si, and S. When the dosage of the alkaline activator was 8%, it could effectively promote the hydration reaction of fly ash concrete, increase the hydration product content of cementitious materials, and improve the mechanical and durability properties of fly ash concrete.
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    Prediction of severity grading of black measles disease in grapes based on improved BiSeNet
    BAI Chun-hui, CHEN Jian, GAO Lu-tao
    HUBEI AGRICULTURAL SCIENCES    2024, 63 (5): 187-193.   DOI: 10.14088/j.cnki.issn0439-8114.2024.05.033
    Abstract231)      PDF (5730KB)(103)       Save
    In order to accurately grade and predict the degree of black measles disease in grapes(Vitis vinifera L.), a semantic segmentation model was used to separate the leaf and lesion parts. The ratio of lesion area to total leaf area on the same leaf was used as the basis for disease severity grading, and the degree of black measles disease in grapes was predicted. 419 grapes disease images from the PlantVillage public database were accurately annotated and subdivided into three categories: background, leaves, and lesions, and data augmentation techniques were applied to increase sample diversity. Using BiSeNet as the benchmark model and introducing GhostNet as the backbone extraction network for context paths not only maintained a small number of model parameters, but also achieved a significant improvement in accuracy, meeting the needs of disease severity classification prediction. A cumulative atrous spatial pyramid pooling (CASPP) module was proposed to replace the single context embedding module in the BiSeNet model, in order to enhance the multi-scale context information extraction ability of the BiSeNet model and improve the segmentation accuracy of the model. After testing, the average Intersection over to Union of this research model in the test set was 94.11%. When predicting the degree of black measles disease in grapes, the accuracy reached 98.21%, which could accurately predict the degree of black measles disease in grapes.
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