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In actual production, the cutting and crushing process is the result of multi action coupling. The bidirectional coupling technology of discrete element method (DEM) and multi bodydynamics (MBD) can achieve information exchange between coal mining equipment and coal wall. It is in line with actual production situations and has significant advantages. In order to improve the working performance of the shearer drum, based on the DEM-MBD bidirectional coupling mechanism, combined with mechanical performance experiments and simulation experiments to obtain actual operating parameters, a bidirectional coupling model of the shearer drum cutting coal wall is established using simulation software EDEM and RecurDyn. The torque and cutting force experienced by the drum during the simulation process are analyzed, and it is proved that the coupling effect and cutting effect are good. Single factor experiments and orthogonal experiments are designed to analyze the influence of drum operating parameters on working performance. SPSS software is used to obtain the degree of influence of drum speed, cutting depth, and traction speed on cutting specific energy consumption, coal loading rate, and load fluctuation coefficient. The feasibility of the model is verified through on-site experiments. A multi-objective optimization model is constructed with drum speed, cutting depth, and traction speed as decision variables, and cutting specific energy consumption, coal loading rate, and load fluctuation coefficient as objectives. The improved multi-objective gray wolf optimization (MOGWO) algorithm and technique for order preference by similarity to ideal solution (TOPSIS) method are used to solve the model. It is found that when the drum speed is 31.12 r/min, the cutting depth is 639.4 mm, and the traction speed is 5.58 m/min, the working performance of the shearer drum is optimal. At this time, the cutting specific energy consumption is 0.467 7 kW·h/m3, the coal loading rate is 43.01%, and the load fluctuation coefficient is 0.327 8.

Based on the National Census data of 2000, 2010, and 2020, with districts and counties as spatial units, the current situation of population aging is described using a time-series comparison method, and its distribution position is identified using a standard deviation ellipse. Moran's I index was used to investigate the spatial correlation and evolution characteristics of population aging, and the Dagum Gini coefficient and decomposition were used to evaluate its regional differences and sources. Then, a spatial econometric regression model was used to test the factors influencing the spatial differentiation of population aging. This study revealed that the population aging of counties in the Chengdu-Chongqing economic circle has been accelerating as a unit from 2000 to 2020. However, different regions before and after 2010 have shown relatively different changes. The center of population aging in the counties gradually shifted to Chengdu over time. Population aging in counties of the Chengdu-Chongqing economic circle mainly shows the spatial distribution characteristics of similar types of agglomeration; counties with significant spatial correlation are mainly characterized by high-high or low-low type clustering, of which the latter has gradually concentrated in Chengdu and Chongqing during the survey period. After 2010, the high-high type clustering areas rapidly concentrated on the two wings of the central axis of Chengdu and Chongqing. The overall difference in population aging of the counties in the Chengdu-Chongqing economic circle accelerated during the investigation period. The increase and decrease in intra-regional differences varied among different periods, with increased inter-regional differences occurring after 2010. Hypervariable density contributed the most to the overall difference in population aging. Compared with 2010, factors such as aging inertia, fertility inertia, population inflow, and education level had a greater impact on the spatial differentiation of population aging in the Chengdu-Chongqing economic circle in 2020, and an increasing number of elderly people have been observed to gather in more densely populated districts and counties since 2010. Overall, this study provides a detailed presentation of the spatial imbalance and dynamic evolution characteristics of population aging at the county level in the Chengdu-Chongqing economic circle over the past two decades and reports that, compared to 2000-2010, the population aging in the counties of the Chengdu-Chongqing economic circle during 2010-2020 underwent rapid deepening with an overall increase in differences and showed new changes in deepening speed, regional relative aging degree, and distribution of similar types of agglomeration counties, that could be considered, there are also certain differences in the causes of population aging in the counties.

Objective To investigate the role of lncRNA PTENP1 in regulating TGF-β-induced epithelial-mesenchymal transition (EMT) in esophageal squamous cell carcinoma (ESCC). Methods Eca109 and TE-1 cells were treated with TGF-β1, and the expression of PTENP1 was detected by qRT-PCR before and after treatment. PTENP1-overexpressing stably transfected cell lines were constructed in Eca109 and TE-1 cells. The effects of overexpression of PTENP1 on TGF-β1-induced migration, proliferation and EMT-related proteins expression in Eca109 and TE-1 cells were detected by Transwell assay, CCK-8 test and Western blot, respectively. Results The expression of PTENP1 was significantly decreased in Eca109 and TE-1 cells treated with TGF-β1 (P < 0.05). Overexpression of PTENP1 significantly prevented cell migration, decreased the cell vitality, upregulated the E-cadherin expression, and downregulated the expression of N-cadherin and vimentin in Eca109 and TE-1 cells (P < 0.05). Furthermore, PTENP1 overexpression attenuated TGF-β-induced migration of Eca109 and TE-1 cells. PTENP1 overexpression partially reversed TGF-β-induced EMT (P < 0.05). Conclusion PTENP1 plays an important role in TGF-β-induced EMT in ESCC cells.