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The proportions of fat and carbohydrate in diet have an important impact on lipid metabolism, glucose metabolism and health. On the premise of consistent dietary available energy (metabolic energy), the effects of different fat and carbohydrates energy supply ratios in diet on fat metabolism and gut microbiota were studied. Sixty-four 9-weeks-old SPF grade male SD rats aged 9 weeks were randomly divided into 4 groups including: HFf group (energy supply ratio of fat to carbohydrate (F/C) 40% : 45%), MFf group (F/C 31% : 54%), LFf group (F/C 21% : 64%) and CON group (control diet). The results showed that there were no significant differences in body weight, blood glucose, blood lipid and liver steatosis among all groups (P > 0.05). The liver triglyceride and abdominal adiponectin of HFf group were significantly higher than those of the other three groups (P < 0.05). Compared to the CON group, the acetyl-CoA carboxylase (ACC) gene expression in the liver of HFf group decreased, while the expressions of lipid synthesis genes, fatty acid transporter (FAT/CD36), sterol regulatory element binding protein (SREBP1), and adipocyte differentiation gene peroxisome proliferator-activated receptor (PPARγ) increased in HFf group (P < 0.05). Compared with CON group, the cholesterol synthesis factor hydroxymethylglutarate monoacyl CoA (HMG-CoA) gene expression in the liver of HFf, MFf and LFf groups were all increased (P < 0.05). In addition, the higher dietary F/C (40% : 45% and 30% : 55%) resulted in impaired gut villi development, which led to decreasing abundance of beneficial bacteria but increasing abundance of potentially pathogenic bacteria. In conclusion, under the same dietary available energy, although the diet of the high-fat group contained a high proportion of fat, it also contained a high content of cellulose, which effectively alleviated the weight gain and blood glucose and lipid abnormalities caused by the high-fat diet. However, there were still symptoms such as increased liver fat and impaired intestinal health, and the F/C in the diet of rats should not exceed 30%. This provides a theoretical reference for the appropriate proportion of macronutrients in the diet.

In order to provide richer interactive response effect,the visualization elements of the Web application is becoming more complex and diverse.The traditional test based on DOM cannot match the new requirement to test Web application.A new generation test based on computer vision provides an efficient way for the complex elements in Web application.This test for the Web based on computer vision mainly depends on template matching technique to recognize the page elements,so that it can ge-nerate visualization test script.However,the subtle changes of the page elements’ appearance can lead to the failure of template matching technique,so that the Web page elements cannot be recognized and the visualization test script cannot be generated.How to improve the accuracy of Web page element recognition based on machine vision and make it still applicable in complex conditions is a challenging task.Object detection based on deep learning is a research hotspot in the field of today’s computer vision and machine learning.It has been shown from the deep data characteristics gained through the large sample learning that it can recognize the target accurately and has stronger generalization ability.Therefore,this paper targets the Web application,starts from the visual characteristics of the page elements,and proposes a Web page elements recognition method based on deep lear-ning.This method uses YOLOv3 algorithmic structure model based on the target testing to automatically localize the position and boundary of an element,recognize the type of Web page elements as well as describe its function.On the base of the Web page elements recognition,it can automatically generate visualization test script for the Web application.To verify the accuracy of the page elements recognition based on computer vision,experiments are set to test between different versions of the same Web application,and between different Web applications to analyze its accuracy.The results show that the average recall rate of machine vision-based Web page element recognition model is 75.6%.It provides foundation for the Web application’s visualization test script.

In order to investigate the energy evolution and failure characteristics of carbonaceous shale containing single fissure under drying−wetting cycles, the intact carbonaceous shale samples and the carbonaceous shale samples with fissure angles of 30°, 45° and 60° were prepared. MTS815 rock mechanics test system was used to conduct triaxial compression tests under different drying−wetting cycles. The influence of drying−wetting cycles on the strength, failure mode and energy evolution of single fissure carbonaceous shale were studied. The results show that the elastic energy and dissipated energy at crack initiation stress, damage stress and peak stress present exponential relationships with drying-wetting cycles. The elastic energy and dissipated energy at crack initiation stress and dissipated energy at damage stress are less sensitive to drying−wetting cycle, while the sensitivities of elastic energy at damage stress, and elastic energy and dissipated energy at peak stress are relatively high. The failure mode of carbonaceous shale is dominated by drying−wetting cycle and fissure angle, in which the drying-wetting cycle is the main controlling factor, and the fissure angle is the secondary controlling factor. It is found that tensile shear failure occurs in dry rock sample with fissure angle of 30°, while the dry rock sample with fissure angle of 45°and 60° are subjected to shear failure. With the increase of the number of drying−wetting cycles, the macroscopic length of the main crack increases, the density of secondary cracks increases, and the failure mode transforms to shear-tension composite failure. With the increase of the number of drying−wetting cycles, the energy storage level at crack initiation stress Kci and the energy storage level at damage stress Kcd increase gradually. The higher the energy storage level at crack initiation and damage stress, the more likely the crack initiation and rock damage occur. Kcd can be used as a warning indicator of rock failure. A larger Kcd indicates that the rock is more vulnerable to failure.