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To improve the poor toughness of traditional particulate reinforced composites, microstructurally toughened composites with WC/H13 as reinforced region and Inconel625 as toughened region were prepared by laser cladding. The microstructure of composites and impact fracture were analysed by optical microscopy, ultra-depth 3D microscope and scanning electron microscopy. The impact toughness and wear property of composites were investigated by Charpy impact testing machine and friction-abrasion testing machine. The results show that the reinforced region of 20% (volume fraction,the same below)WC/H13 is reinforced by WC particles and M6C carbides while the toughened region of Inconel625 alloy is mainly composed of columnar dendrite crystals and precipitated phases. The average hardness of Inconel625 is 230.5HV, while the hardness of WC/H13 is gradually increased to 402HV from the interface to the center area. The average impact energy of microstructurally toughened composites is 13.8J/cm2, which is 5.5 times of traditional 10% WC/H13. In the condition of dry sliding wear at room temperature, the wear resistance of microstructurally toughened composites is comparable to traditional 10% WC/H13 and 5 times of quenched H13 steel. The average friction coefficient of microstructurally toughened composites is 81% of traditional 10% WC/H13 and 80% of quenched H13 steel, which indicates excellent anti-wear and wear resistant property. By microstructurally toughening, the impact toughness of particulate reinforced composites can be substantially improved with excellent wear resistant property ensured.

In practical problems, in addition to the processing time of the job, the impact of the time required for delivering the service to customers on the cost is also considered, i.e., delivery time, where the job processing time is a simple linear function of its starting time. This paper considers the impact of past-sequence-dependent delivery times (which can be referred to as p s d d t ) on the studied objectives in three types of due windows (common, slack and different due windows). This serves to minimize the weighted sum of earliness, tardiness, starting time and size of due window, where the weights (coefficients) are related to the location. Through the theoretical analysis of the optimal solution, it is found that these three problems can be solved in time O (N log N) , respectively, where N is the number of jobs. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate and compare the performances of the random forest (RF) and support vector regression (SVR) models combined with different feature selection methods, including recursive feature elimination (RFE), simulated annealing feature selection (SAFS), and selection by filtering (SBF) in predicting soil pH in Anhui Province, East China. We also used the ALL original features to build the RF and SVR models as a comparison. A total of 140 samples were selected, following the principles of randomness, uniformity, and representativeness, to consider the combination of landscape elements, such as topography, parent material, and land use. Auxiliary data, including climatic, topographic, and vegetation indexes, were used for predicting soil pH. The results showed that compared with the use the ALL original modeling features (ALL-RF, ALL-SVR), the combination of the three feature selection algorithms with RF and SVR can eliminate some redundant features and effectively improve the prediction accuracy of the soil pH model. For the RF model, the RMSE and the MAE of the calibration of the RFE-RF model were 0.73 and 0.57 and had the highest R2 in four different RF models. The testing set of the RFE-RF model had an R2 of 0.61, which was better than that of the ALL-RF (R2 = 0.45) model and lower than those of the SAFS-RF (R2 = 0.71) and SBF-RF (R2 = 0.69) models. For the SVR model, the RFE-RF model was more robust and had better generalization ability. The accuracy of digital soil mapping can be improved through feature selection. [ABSTRACT FROM AUTHOR]

Objective: To analyze the correlation between serum Nrf2 and GPX4 activity levels with coronary heart disease (CHD) and the severity of coronary artery disease, and to explore the role of ferroptosis mediated by its signaling pathway in the progression of CHD. Methods: A total of 540 patients suspected of CHD were selected for coronary angiography, of which 360 patients were diagnosed with CHD. The activity levels of Nrf2 and GPX4 in the serum of CHD patients were detected by ELISA, and the differences in the activities of Nrf2 and GPX4 in the presence or absence of CHD were statistically analyzed. Western blot detection of Nrf2 protein expression of peripheral blood mononuclear cells (PBMCS) in the control(CON) and CHD groups (90 cases each).The expression and significance of its signaling pathway in CHD patients were analyzed. Results: The activity levels of Nrf2 and GPX4 in the CHD group were lower than those in the CON group (P<0.05), and the expression levels of Nrf2 in PBMCs of the two groups were detected by Western blot. The protein expression level of Nrf2 in the CHD group (0.25±0.05) was down-regulated compared with CON group (0.87±0.16) (P<0.05), indicating that Nrf2 protein expression level was low in CHD patients. Pearson correlation analysis showed that serum Nrf2 and GPX4 levels were negatively correlated with Gensini score (Nrf2: r=-0.347, P<0.001; GPX4: r=-0.423, P=0.001). Nrf2 and GPX4 were negatively correlated with TG (Nrf2: r=-0.284, P<0.001; GPX4: r=-0.275, P=0.001), Nrf2 and GPX4 levels were negatively correlated with LDL (Nrf2: r=-0.418, P<0.001) 0.05; GPX4: r=- 0.426, P<0.05), Nrf2 and GPX4 levels were positively correlated with HDL (Nrf2: r=0.318, P<0.05; GPX4: r=0.428, P<0.05), and Nrf2 was positively correlated with GPX4 ( r=0.456, P<0.01). Conclusion: The ferroptosis pathway mediated by the Nrf2-GPX4 signaling pathway is closely related to the degree of coronary artery disease and the pathogenesis of CHD, and its mechanism may be related to the down-regulation of the Nrf2-GPX4 signaling pathway. [ABSTRACT FROM AUTHOR]