Study on Mudcake disintegration in clayey strata during shield tunneling: Effects of dispersants and bentonite slurry.

While tunnel boring machines (TBMs) tunneling in clayey strata, the adhered excavated soil on the cutterhead and cutting tools tends to form mudcake after compaction and consolidation. Mudcake can obstruct the cutterhead openings and rendering the cutting tools ineffective, leads to a substantial reduction in advance rate. Dispersants are recognized as an effective method for the disintegration of mudcakes. A novel set of equipment, comprising a mudcake compression device and a mudcake disintegration apparatus, is developed for assessing mudcake disintegration properties. The results showed that mudcakes underwent a tripartite disintegration process in water, including an initial stage, a rapid disintegration stage, and a stable stage. In the initial stage, the mudcakes absorbed water before disintegration, resulting in marginal changes in the weight of the disintegrated mudcakes. In the rapid disintegration stage, the weight of the disintegrated mudcakes increased quickly. During the stable stage, the weight of the disintegrated mudcakes remained relatively constant. The submersion of mudcakes in a dispersant solution substantially increased the rate of disintegration. Greater dispersant concentration corresponded to an increase in the disintegration rate. No weight gain was observed in mudcakes during the initial disintegration stage. When mudcakes disintegrated in a bentonite slurry, the weight of the disintegrated mudcakes initially decreased and then stabilized. The weight of the disintegrated mudcakes turned negative, indicating an increase in the weight of mudcakes. This suggested that bentonite significantly hindered mudcake disintegration.

An analytical methodology of rock burst with fully mechanized top-coal caving mining in steeply inclined thick coal seam.

Rock burst disaster is still one of the most serious dynamic disasters in coal mining, seriously restricting the safety of coal mining. The b value is the main parameter for monitoring rock burst, and by analyzing its changing characteristics, it can effectively predict the dangerous period of rock burst. This article proposes a method based on deep learning that can predict rock burst using data generated from microseismic monitoring in underground mining. The method first calculates the b value from microseismic monitoring data and constructs a time series dataset, and uses the dynamic time warping algorithm (DTW) to reconstruct the established b value time series. A bidirectional short-term and short-term memory network (BiLSTM) loaded with differential evolution algorithm and attention mechanism was used for training, and a prediction model for the dangerous period of rock burst based on differential algorithm optimization was constructed. The study used microseismic monitoring data from the B1+2 fully mechanized mining face and B3+6 working face in the southern mining area of Wudong Coal Mine for engineering case analysis. The commonly used residual sum of squares, mean square error, root mean square error, and correlation coefficient R2 for time series prediction were introduced, which have significant advantages compared to basic LSTM algorithms. This verifies that the prediction method proposed in this article has good prediction results and certain feasibility, and can provide technical support for the prediction and prevention of rock burst in steeply inclined thick coal seams in strong earthquake areas.

Plasma n-3 and n-6 fatty acids and inflammatory markers in Chinese vegetarians.

BACKGROUND: Polyunsaturated fatty acid (PUFA) intake favorably affects chronic inflammatory-related diseases such as cardiovascular disease; however, the relationship between the PUFA and inflammatory factors in the healthy vegetarians were not clear. We aimed to investigate the plasma fatty acids status, and its association with plasma inflammatory factors in Chinese vegetarians and omnivores. METHODS: A total of 89 male vegetarians and 106 male omnivores were participated the study. Plasma concentrations of inflammatory factors were detected by ELISA, and as standard methods fatty acids were extracted and determined by chromatography. RESULTS: Compared with omnivores, vegetarians have significant higher interleukin-6 (IL-6), plasma n-6 PUFA, n-6/n-3, and 18:3n-3; while they have significant lower leukotriene B4 (LTB4), cyclo-oxygenase-2 (COX2) and prostaglandin E2 (PGE2), 20:5n-3, 22:5n-3, 22:6n-3, and n-3 PUFA. In vegetarians, plasma 20:4n-6 was significant positively related to TNF-α. LTB4 was significantly positively related to plasma 22:6n-3, and negatively associated with n-6 PUFA. CONCLUSION: Vegetarians have higher plasma n-6 PUFA and IL-6, but lower LTB4, n-3 PUFA, 22:6n-3, COX2 and PGE2 levels. It would seem appropriate for vegetarians to increase their dietary n-3 PUFA, while reduce dietary n-6 PUFA and thus reduce the risk of chronic inflammatory-related diseases.