scholarly journals 3-D fracture evolution and water migration in fractured coal under variable stresses induced by fluidized mining: In situ triaxial loading and CT imaging analysis

2021 ◽  
Vol 7 ◽  
pp. 3060-3073
Author(s):  
Yang Ju ◽  
Chaodong Xi ◽  
Shaojie Wang ◽  
Lingtao Mao ◽  
Kai Wang ◽  
...  
2020 ◽  
Vol 15 (6) ◽  
pp. 752-758
Author(s):  
Qian Wang ◽  
Wangxi Hai ◽  
Sanyuan Shi ◽  
Jinliang Peng ◽  
Yuhong Xu
Keyword(s):  
Pet Ct ◽  

2020 ◽  
Vol 279 (2) ◽  
pp. 79-84
Author(s):  
J. YAO ◽  
A. OSSANA ◽  
J. CHUN ◽  
X.‐Y. YU

Author(s):  
A. Amyar ◽  
R. Modzelewski ◽  
S. Ruan

ABSTRACTThe fast spreading of the novel coronavirus COVID-19 has aroused worldwide interest and concern, and caused more than one million and a half confirmed cases to date. To combat this spread, medical imaging such as computed tomography (CT) images can be used for diagnostic. An automatic detection tools is necessary for helping screening COVID-19 pneumonia using chest CT imaging. In this work, we propose a multitask deep learning model to jointly identify COVID-19 patient and segment COVID-19 lesion from chest CT images. Our motivation is to leverage useful information contained in multiple related tasks to help improve both segmentation and classification performances. Our architecture is composed by an encoder and two decoders for reconstruction and segmentation, and a multi-layer perceptron for classification. The proposed model is evaluated and compared with other image segmentation and classification techniques using a dataset of 1044 patients including 449 patients with COVID-19, 100 normal ones, 98 with lung cancer and 397 of different kinds of pathology. The obtained results show very encouraging performance of our method with a dice coefficient higher than 0.78 for the segmentation and an area under the ROC curve higher than 93% for the classification.


1997 ◽  
Vol 272 (6) ◽  
pp. C1980-C1987 ◽  
Author(s):  
H. Ohata ◽  
Y. Ujike ◽  
K. Momose

The mechanisms for mobilization of intracellular free Ca2+ have been studied in various types of isolated and cultured cells, but little is known about Ca2+ mobilization in individual cells in situ. We tried to establish imaging analysis of intracellular free Ca2+ concentration ([Ca2+]i) in individual cells loaded with the acetoxymethyl ester of fluo 3 in situ, using laser scanning confocal microscopy. The method permitted us to distinguish signals from endothelial and smooth muscle cells of guinea pig artery. Addition of ATP to the artery caused a transient increase in endothelial [Ca2+]i. It was concluded that the response was induced via P2Y purinoceptors, because adenosine 5'-O-(2-thiodiphosphate), but not UTP, caused a similar response independent of extracellular Ca2+. The percentage of cells that responded to ATP (1-10 microM) and the peak amplitude of the transient increase in [Ca2+]i were dose dependently increased. Using rapid xy-scanning and line-scanning modes, we confirmed that 10 microM ATP induced Ca2+ waves, at a rate of 10-30 microns/s, after a lag time of approximately 3 s. These results show that [Ca2+]i waves within endothelial cells are physiologically induced by ATP via P2Y purinoceptor, but not P2U purinoceptor, in aortic strips in situ. The method should be of use in the study of vascular physiology and pathophysiology.


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