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Long-term load forecasting (LTLF) is a challenging task because of the complex relationships between load and factors affecting load. However, it is crucial for the economic growth of fast developing countries like China as the growth rate of gross domestic product (GDP) is expected to be 7.5%, according to China’s 11th Five-Year Plan (2006-2010). In this paper, LTLF with an economic factor, GDP, is implemented. A support vector regression (SVR) is applied as the training algorithm to obtain the nonlinear relationship between load and the economic factor GDP to improve the accuracy of forecasting

This study aims to investigate the effects of microRNA (miR)‐16/dedicator of cytokinesis 2 (DOCK2) on myocarditis. The differences in the expression of genes in acute myocarditis were filtered out across Gene Expression Omnibus (GEO) database. Myocarditis cell model was established by lipopolysaccharide (LPS) stimulation in cardiomyocytes. The association between miR‐16 and DOCK2 was predicted by bioinformatics software and confirmed by dual‐luciferase assay. Polymerase chain reaction and western blot analysis were employed to assess the expression levels of miR‐16 and DOCK2 under different conditions. Cells viability, apoptosis, and inflammatory reaction were evaluated by Cell Counting Kit‐8, flow cytometry, and enzyme‐linked immunosorbent assays. miR‐16, as an upstream regulator of DOCK2, exhibited lower expression in LPS‐induced myocarditis model. More importantly, we revealed that a marked augmentation of miR‐16 promoted the growth of LPS‐stimulated cardiomyocytes, and attenuated cell apoptosis and inflammatory response. However, an increasing expression of DOCK2 inhibited the remission of LPS‐induced myocardial injury caused by miR‐16 mimic. Herein, our results highlighted that upregulation of miR‐16 resulted in the protective effects on LPS‐induced myocardial injury by reducing DOCK2 expression, affording a pair of novel target molecules for ameliorating the symptoms of myocarditis.

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