During the processes of methane adsorption and desorption,the internal structure of coal changes,accordingly leading to changes in electrical conductivity.In this paper,using low rank coal seams of the Yan'an Form...During the processes of methane adsorption and desorption,the internal structure of coal changes,accordingly leading to changes in electrical conductivity.In this paper,using low rank coal seams of the Yan'an Formation in the Dafbsi field as the research subject,the relationship between coal resistivity,methane adsorption quantity,and equilibrium pressure is analyzed through proximate analysis,mercury injection tests,low temperature liquid nitrogen adsorption tests,and coal resistivity measurements during methane adsorption and desorption.The results show that during the process of pressure rise and methane adsorption,the conductivity of coal increases,resulting from heat release from methane adsorption,coal matrix swelling and adsorbed water molecules replaced by methane,but the resistivity reduction gradually decreases.The relationship between coal resistivity and methane adsorption quantity and equilibrium pressure can be described by a quadratic function.During the processes of depressurization and desorption,the resistivity of coal rebounds slightly,due to decalescence of methane desorption,coal matrix shrinkage and water-gas displacement,and the relationship coincides with a linear function.Methane adsorption leads to irreversible changes in coal internal structure and enhances the coal conductivity,and resistivity can not be restored to the initial level even after methane desorption.The resistivity and reduction rate of durain are higher than those of vitrain,with relatively greater homogeneous pore throat structure and fewer charged particles in the double electric layer.In addition,moisture can enhance the conductivity of coal and makes it change more complexly during methane adsorption and desorption.展开更多
Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases.However,the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures,such as gastroscopy and b...Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases.However,the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures,such as gastroscopy and bronchoscopy,owing to its severe invasiveness.In comparison,virtual pancreatoscopy(VP)has shown notable advantages.However,because of the low resolution of current computed tomography(CT)technology and the small diameter of the pancreatic duct,VP has limited clinical use.In this study,an optimal path algorithm and super-resolution technique are investigated for the development of an open-source software platform for VP based on 3D Slicer.The proposed segmentation of the pancreatic duct from the abdominal CT images reached an average Dice coefficient of 0.85 with a standard deviation of 0.04.Owing to the excellent segmentation performance,a fly-through visualization of both the inside and outside of the duct was successfully reconstructed,thereby demonstrating the feasibility of VP.In addition,a quantitative analysis of the wall thickness and topology of the duct provides more insight into pancreatic diseases than a fly-through visualization.The entire VP system developed in this study is available at https://github.com/gaoyi/VirtualEndoscopy.git.展开更多
The mortality rate in the intensive care unit(ICU)is a key metric of hospital clinical quality.To enhance hospital performance,many methods have been proposed for the stratification of patients’different risk categor...The mortality rate in the intensive care unit(ICU)is a key metric of hospital clinical quality.To enhance hospital performance,many methods have been proposed for the stratification of patients’different risk categories,such as severity scoring systems and machine learning models.However,these methods make capturing time sequence information difficult,posing challenges to the continuous assessment of a patient’s severity during their hospital stay.Therefore,we built a predictive model that can make predictions throughout the patient’s stay and obtain the patient’s risk of death in real time.Our proposed model performed much better than other machine learning methods,including logistic regression,random forest,and XGBoost,in a full set of performance evaluation processes.Thus,the proposed model can support physicians’decisions by allowing them to pay more attention to high-risk patients and anticipate potential complications to reduce ICU mortality.展开更多
基金financially supported by the Independent Projects of the Key Lab. of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources of China (grants No. KF2019-2, ZKF2018-1, KF2018-4, ZP2018-2)the Major National Science and Technology Special Projects (grant No. 2016ZX05042004)+3 种基金the Projects Funded by China Postdoctoral Science Foundation (grant No. 2019M653873XB)the Natural Science Foundation Research Projects of Shaanxi Province (grant No. 2019JQ-245)the Doctoral Research Starting Foundation of Xi’an University of Science and Technology (grant No. 2016QDJ041)the Research Projects of the Geological Research Institute for Coal Green Mining of Xi’an University of Science and Technology (grant No. MTy2019-04)
文摘During the processes of methane adsorption and desorption,the internal structure of coal changes,accordingly leading to changes in electrical conductivity.In this paper,using low rank coal seams of the Yan'an Formation in the Dafbsi field as the research subject,the relationship between coal resistivity,methane adsorption quantity,and equilibrium pressure is analyzed through proximate analysis,mercury injection tests,low temperature liquid nitrogen adsorption tests,and coal resistivity measurements during methane adsorption and desorption.The results show that during the process of pressure rise and methane adsorption,the conductivity of coal increases,resulting from heat release from methane adsorption,coal matrix swelling and adsorbed water molecules replaced by methane,but the resistivity reduction gradually decreases.The relationship between coal resistivity and methane adsorption quantity and equilibrium pressure can be described by a quadratic function.During the processes of depressurization and desorption,the resistivity of coal rebounds slightly,due to decalescence of methane desorption,coal matrix shrinkage and water-gas displacement,and the relationship coincides with a linear function.Methane adsorption leads to irreversible changes in coal internal structure and enhances the coal conductivity,and resistivity can not be restored to the initial level even after methane desorption.The resistivity and reduction rate of durain are higher than those of vitrain,with relatively greater homogeneous pore throat structure and fewer charged particles in the double electric layer.In addition,moisture can enhance the conductivity of coal and makes it change more complexly during methane adsorption and desorption.
基金This work is partially supported by the Key-Area Research and Development Program of Guangdong Province,No.2021B0101420005the Key Technology Development Program of Shenzhen,No.JSGG20210713091811036+4 种基金the Department of Education of Guangdong Province,No.2017KZDXM072the National Natural Science Foundation of China,No.61601302the Shenzhen Key Laboratory Foundation,No.ZDSYS20200811143757022the Shenzhen Peacock Plan,No.KQTD2016053112051497the SZU Top Ranking Project,No.86000000210.
文摘Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases.However,the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures,such as gastroscopy and bronchoscopy,owing to its severe invasiveness.In comparison,virtual pancreatoscopy(VP)has shown notable advantages.However,because of the low resolution of current computed tomography(CT)technology and the small diameter of the pancreatic duct,VP has limited clinical use.In this study,an optimal path algorithm and super-resolution technique are investigated for the development of an open-source software platform for VP based on 3D Slicer.The proposed segmentation of the pancreatic duct from the abdominal CT images reached an average Dice coefficient of 0.85 with a standard deviation of 0.04.Owing to the excellent segmentation performance,a fly-through visualization of both the inside and outside of the duct was successfully reconstructed,thereby demonstrating the feasibility of VP.In addition,a quantitative analysis of the wall thickness and topology of the duct provides more insight into pancreatic diseases than a fly-through visualization.The entire VP system developed in this study is available at https://github.com/gaoyi/VirtualEndoscopy.git.
基金This research was supported by the Key Discipline Fund of Shenzhen Hospital of Southern Medical University(No.2021-2023ICU)the New-Generation Information Technology by the Scientific Research Platform of Institutions of Higher Education of the Education Department of Guangdong Province(No.2021ZDZX1014)the Shenzhen University(SZU)Top Ranking Project(No.86000000210)。
文摘The mortality rate in the intensive care unit(ICU)is a key metric of hospital clinical quality.To enhance hospital performance,many methods have been proposed for the stratification of patients’different risk categories,such as severity scoring systems and machine learning models.However,these methods make capturing time sequence information difficult,posing challenges to the continuous assessment of a patient’s severity during their hospital stay.Therefore,we built a predictive model that can make predictions throughout the patient’s stay and obtain the patient’s risk of death in real time.Our proposed model performed much better than other machine learning methods,including logistic regression,random forest,and XGBoost,in a full set of performance evaluation processes.Thus,the proposed model can support physicians’decisions by allowing them to pay more attention to high-risk patients and anticipate potential complications to reduce ICU mortality.
