RESUMEN
The southwest region of China has abundant groundwater and high-temperature geothermal energy. Carbonaceous shale, as one of the typical surrounding rocks in this region, often suffers from deterioration effects due to the coupled action of groundwater chemical erosion and high temperature, which affects the long-term stability of tunnel engineering. In order to investigate the deterioration effects of carbonaceous shale under the coupled action of chemical erosion and high temperature, carbonaceous shale from a tunnel of Lixiang Railway in Yunnan Province was taken as the research object. The microstructure and mineral composition of the samples before and after chemical erosion were obtained with a scanning electron microscope-energy dispersive spectrometer and an X-ray diffraction test. Then, triaxial compression tests were conducted on the samples under different time points and different temperature effects of chemical erosion, and the stress-strain curves and the deterioration laws under a single factor were obtained. An improved numerical simulation method based on the parallel bond model was developed, which can account for the coupled effects of chemical erosion and high temperature on the rock. By simulating the triaxial compression test of carbonaceous shale, the deterioration law of carbonaceous shale under the coupled action was discussed. The results show that chemical erosion has a significant deterioration effect on the triaxial compressive strength of carbonaceous shale, and the degree of deterioration is related to the erosion time. In the first 30 days of erosion, the triaxial compressive strength of carbonaceous shale decreased by 11.38%, which was the largest deterioration range. With the increase in erosion time, the deterioration rate gradually decreased; temperature had a significant threshold effect on the strength of carbonaceous shale, and a clear turning point appeared at about 200 °C. By simulating the deterioration effects of carbonaceous shale under the coupled action of chemical erosion and high temperature, it was found that the longer the duration of chemical erosion, the stronger the temperature sensitivity of carbonaceous shale, and the more serious the loss of compressive strength during the heating process. When the temperature was low, the strength of carbonaceous shale changed little, and some samples even showed an increase in strength; when the temperature was high, the strength of carbonaceous shale decreased significantly, showing deterioration characteristics. The numerical simulation method was compared and verified with the indoor test results, and it was found that the numerical calculation had a good agreement with the test results.
RESUMEN
There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors and their host kidneys is a promising tool for quantitatively characterizing these lesions, but its adoption is limited due to the manual effort required to produce high-quality 3D segmentations of these structures. Recently, methods based on deep learning have shown excellent results in automatic 3D segmentation, but they require large datasets for training, and there remains little consensus on which methods perform best. The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address these issues and stimulate progress on this automatic segmentation problem. A training set of 210 cross sectional CT images with kidney tumors was publicly released with corresponding semantic segmentation masks. 106 teams from five continents used this data to develop automated systems to predict the true segmentation masks on a test set of 90 CT images for which the corresponding ground truth segmentations were kept private. These predictions were scored and ranked according to their average Sørensen-Dice coefficient between the kidney and tumor across all 90 cases. The winning team achieved a Dice of 0.974 for kidney and 0.851 for tumor, approaching the inter-annotator performance on kidney (0.983) but falling short on tumor (0.923). This challenge has now entered an "open leaderboard" phase where it serves as a challenging benchmark in 3D semantic segmentation.