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In order to explore the law of proppant migration and placement under clean fracturing fluid, an Euler multiphase flow model was established through FLUENT numerical simulation software based on computational fluid dynamics(CFD). The model takes into account the rheological properties of fracturing fluid and the friction and collision of proppant particles. The influence of proppant size, density and sand ratio on the shape of the sand dike is studied by using the equilibrium height and equilibrium time as the characterization parameters. The results show that the clean fracturing fluid is easier to carry the proppant to the depth of the fracture than the conventional fracturing fluid, so that the proppant is evenly distributed in the fracture; proppant with large particle size and high density can easily settle in the fracture opening under the carrying of the clean fracturing fluid, while proppant with small particle size and low density can improve the sand carrying capacity of fracturing fluid and transport proppant into deep fracture. Increasing sand ratio in a certain range can improve the height and laying area of the sand dike, but excessive sand ratio has little effect on the shape of the proppant sand dike and is easy to cause sand blockage.

Objective To analyze the expression of KCNJ11 mRNA in gliomas and its prognostic value. Methods The clinical, histopathological and molecular pathological features of 273 patients with gliomas were collected from CGGA. We analyzed the differences of KCNJ11 mRNA expression in different types of gliomas and the survival time of patients with high and low expression of KCNJ11 mRNA in different subtypes of gliomas. Results The expression levels of KCNJ11 mRNA in young glioma and primary glioma patients were higher than those in old glioma and recurrent glioma patients, respectively (P=0.008, 0.001). The expression of KCNJ11 mRNA in oligodendroglioma was the highest, astrocytoma was the second, and glioblastoma was the lowest (P=0.000). The expression of KCNJ11 mRNA in WHOⅡ grade glioma was the highest, WHOⅢ was the second, and WHOⅣ was the lowest (P=0.000). The expression levels of KCNJ11 mRNA in IDH-mutant type glioma patients were higher than those in IDH-wild type glioma patients (P=0.000). The expression of KCNJ11 mRNA in deletion of 1p/19q glioma patients was higher than that in non-deletion of 1p/19q ones (P=0.000). The expression of KCNJ11 mRNA in MGMT methylated glioma patients was higher than that in non-methylated ones (P=0.036). The survival time of patients with high expression of KCNJ11 mRNA (≥2.77) was longer than that with low expression (P=0.000). Multivariate Cox analysis showed that the high expression of KCNJ11 mRNA was an independent factor affecting the good prognosis of patients with glioma. Conclusion The expression of KCNJ11 mRNA is negatively related to the malignant degree of the tumor. The high expression of KCNJ11 mRNA is an independent factor affecting the good prognosis of patients with glioma.

Energy management strategy (EMS), as a core technology in fuel cell vehicles (FCVs), profoundly influences the lifespan of fuel cells and the economy of the vehicle. Aiming at the problem of the EMS of FCVs based on a global optimization algorithm not being applicable in real-time, a rule extraction-based EMS is proposed for fuel cell commercial vehicles. Based on the results of the dynamic programming (DP) algorithm in the CLTC-C cycle, the deep learning approach is employed to extract output power rules for fuel cell, leading to the establishment of a rule library. Using this library, a real-time applicable rule-based EMS is designed. The simulated driving platform is built in a CARLA, SUMO, and MATLAB/Simulink joint simulation environment. Simulation results indicate that the proposed strategy yields savings ranging from 3.64% to 8.96% in total costs when compared to the state machine-based strategy. [ABSTRACT FROM AUTHOR]