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Aerodynamic shape optimization based on computational fluid dynamics still has a huge demand for improvement in the optimization effect and efficiency when optimizing the unstable flow of airfoils. This article presents a physics-informed hot-start method combined with modified metric-based proper orthogonal decomposition (MPOD-ML-Phys). The data-based filtering strategy is a core step in the original metric-based proper orthogonal decomposition method (MPOD), but existing filtering strategies generate a significant amount of additional computational consumption. Therefore, this article applies machine learning methods to data-based filtering strategy in MPOD and establishes a modified MPOD method (MPOD-ML). In addition, during the MPOD-ML process, a lot of hidden physical knowledge that is beneficial for optimization will also be generated. This article combines Bayesian optimization to construct an MPOD-ML-Phys method, which fully utilizes the flow physical knowledge in MPOD-ML. The efficiency and effect of MPOD-ML and MPOD-ML-Phys are validated by two typical cases: inverse and direct design for airfoils. The results indicate that both MPOD-ML and MPOD-ML-Phys methods can effectively improve the overall optimization efficiency. However, the intervention of machine learning models has significantly reduced the robustness of the MPOD-ML method, while the embedding of physical knowledge makes MPOD-ML-Phys more robust. Meanwhile, the optimized airfoil obtained by MPOD-ML-Phys has better drag divergence characteristics, a later flow separation point, and better flow stability. [ABSTRACT FROM AUTHOR]

Objective By stimulating intermittent cold exposure to mice for a long term, to investigate the effect of cold exposure on amelioration of glucose homeostasis and prevention of glucose homeostasis disorder induced by high-fat diet (HFD), and analyze the regulative effect of adipose tissue in the process. Methods A total of 24 male C57 BL/6J male mice (8 weeks old) were equally divided into 4 groups, that is, control group (normal diet+room temperature), cold exposure group (normal diet+4 ℃, 2 h/d), HFD group (HFD feeding+room temperature), and HFD and cold exposure group. Intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (IPITT) were carried out in 1, 8, 16 and 22 weeks after intervention. In 22 weeks after intervention, scapular brown adipose tissue (BAT) and inguinal white adipose tissue (WATi) were collected for transcriptome profiling analysis. Results When having no effect on the bodyweight, intermittent cold exposure for 22 weeks significantly reduced the weight of WATi (0.221±0.016 vs 0.338±0.024 g, P < 0.05), but increased the weight of BAT (0.095±0.005 vs 0.079±0.003 g, P < 0.05) when compared with the control group, and elevated glucose tolerance by 25.9% (P < 0.01) and enhanced insulin sensitivity by 50.4% (P < 0.01). The amelioration of glucose homeostasis was positively correlated with the length of cold exposure. However, in the mice with HFD feeding, the cold exposure inhibited the increase of bodyweight (43.3±1.8 vs 32.9±0.7 g, P < 0.01) and WATi (1.186±0.215 vs 0.434±0.059 g, P < 0.05), and improved insufficient glucose tolerance by 25.5% (P < 0.01) and insulin resistance by 33.9% (P < 0.01) when compared to the mice of HFD and cold exposure group. Transcriptome profiling analysis showed that long-term intermittent cold exposure obviously activated the glycolysis in the brown fat and white fat tissues, and the PI3K-Akt and insulin signaling pathways (P < 0.01), but HFD reversed the activation of glycolysis-related pathways in white fat tissues. Conclusion Long-term intermittent cold exposure may promote glucose homeostasis and prevent glucose homeostasis disorder induced by HFD via activating glycolysis, PI3K-Akt and insulin signaling pathways in adipose tissue.

The present study focuses on the synthesis of a manganese dioxide lithium ion sieve and its application for the extraction of lithium from coal fly ash. The preparation and adsorption experiments of the manganese dioxide lithium ion sieve were carried out using the orthogonal method, while the HCl elution experiment was carried out using the single factor method. The results showed that the optimum preparation conditions under which the average lithium adsorption efficiency reached 99.98% were a 10:1 mass ratio of manganese dioxide to lithium hydroxide, calcination at 800 °C for 60 min, 1.5 mol/L HCl, soaking for 24 h and stirring for 18 h. Additionally, the optimum adsorption efficiency was observed with an adsorption time of 30 min, KOH pH of 8 and KOH scrubbing time of 10 min, resulting in 100% lithium adsorption efficiency. The optimum elution conditions for lithium were determined to be an HCl concentration of 0.01 mol/L and an elution time of 40 min, giving 100% lithium elution efficiency. [ABSTRACT FROM AUTHOR]