This study focuses on the production of functionally graded composites by utilizing magnesium matrix waste chips and cost-effective eggshell reinforcements through centrifugal casting. The wear behavior of the produced samples was thoroughly examined, considering a range of loads (5 N to 35 N), sliding speeds (0.5 m/s to 3.5 m/s), and sliding distances (500 m to 3500 m). The worn surfaces were carefully analyzed to gain insights into the underlying wear mechanisms. The results indicated successful eggshell particle integration in graded levels within the composite, enhancing hardness and wear resistance. In the outer zone, there was a 25.26% increase in hardness over the inner zone due to the particle gradient, with wear resistance improving by 19.8% compared to the inner zone. To predict the wear behavior, four distinct machine learning algorithms were employed, and their performance was compared using a limited dataset obtained from various test operations. The tree-based machine learning model surpassed the deep neural-based models in predicting the wear rate among the developed models. These models provide a fast and effective way to evaluate functionally graded magnesium composites reinforced with eggshell particles for specific applications, potentially decreasing the need for extensive additional tests. Notably, the LightGBM model exhibited the highest accuracy in predicting the testing set across the three zones. Finally, the study findings highlighted the viability of employing magnesium waste chips and eggshell particles in crafting functionally graded composites. This approach not only minimizes environmental impact through material repurposing but also offers a cost-effective means of utilizing these resources in creating functionally graded composites for automotive components that demand varying hardness and wear resistance properties across their surfaces, from outer to inner regions.

Background:Atrial fibrillation (AF) is a very common clinical arrhythmia, accompanied by the overproliferation of cardiac fibroblasts (CFs). This study aimed to investigate the role of the long non-coding RNA(lncRNA) taurine upregulated gene 1 (TUG1) in the proliferation of CFs and further investigated its underlying mechanism.Methods:One hundred four paroxysmal AF patients and 94 healthy controls were recruited. Human cardiac fibroblasts (HCFs) were applied to establish an AF cell model through treatment with angiotensin II (AngII). qRT-PCR was used for the measurement of gene levels. The cell proliferation was detected by cell counting kit-8 (CCK-8). Luciferase reporter assay was performed for target gene analysis.Results:Elevated levels of TUG1 and low expression of miR-29b-3p were detected in the serum of AF patients compared with the healthy controls. Pearson's correlation analysis exhibited an inverse relationship between TUG1 and miR-29b-3p expression in AF patients (r= −7.106,p< 0.001). Knockdown of TUG1 inhibited AngII-induced CF proliferation. Taurine upregulated gene 1 (TUG1) functions as a competing endogenous RNA (ceRNA) for miR-29b-3p, and downregulation of miR-29b-3p reversed the role of TUG1 in CF proliferation. TGF-β1 is a direct target gene of miR-29b-3p.Conclusions:Long non-coding RNA taurine upregulated gene 1 is a key regulator in the occurrence of AF. Slicing TUG1 inhibits CF proliferation by regulating the miR-29b-3p/TGF-β1 axis.