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Brassica rapa has been widely reported as an anti-diabetic plant and is widely used in traditional medicine for the treatment of various disorders. However, the molecular mechanism underlying the plant's anti-diabetic activity has not been elucidated. Therefore, the present study aimed to investigate the possible molecular mechanism of B.rapa for managing diabetes mellitus through network pharmacology and molecular docking studies. The active ingredients and associated target proteins were obtained from a literature review and the Swiss Target Prediction platform and validated using the PubChem database. The disease-associated genes were retrieved from the Genecard database. The B. rapa-DM target network was analyzed using the STRING database, and the results were integrated and visualized using Cytoscape software. The molecular mechanism and therapeutic effect of B.rapa for the treatment of DM were determined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the Enrichr Platform. Fifty-two active ingredients were screened from B. rapa, and 1528 putative target genes were identified from these ingredients. Four hundred and fifty-four overlapping targets matched with DM were considered potential therapeutic targets. First, ten key targets (ALB, AKT1, TNF, GAPDH, MAPK3, EGFR, VEGFA, CTNNB1, CASP3, and STAT3) were found by topological analysis. Then, the results of GO and KEGG suggested that the anti-diabetes effect of B. rapa was strongly associated with the AGE-RAGE signaling pathway in diabetic complications, Neuroactive ligand-receptor interaction, Lipid and atherosclerosis, PI3K-Akt signaling pathway, and Calcium signaling pathway. The AKT1 (Serine/Threonine Protein Kinase) enzyme is targeted by major bioactive constituents of B.rapa. Molecular Docking studies revealed that Liquiritin (docking score -6.1 Kcal/mol) showed the highest binding affinity with AKT1. These results suggest that Brassica rapa may play a role in regulating several pathways that are involved in the development of Diabetes Mellitus. Keywords: Network pharmacology, molecular mechanisms, Brassica rapa, Diabetes Mellitus (DM)

The technique for order of preference by similarity ideal solution (TOPSIS) approach was used for optimizing the process parameters of laser micro-drilling of nickel superalloy C263 with Thermal Barrier Coating (TBC). Plasma spraying was used to deposit the TBC and a pico-second Nd:YAG pulsed laser was used to drill the specimens. Drilling angle, laser scan speed and number of passes were considered as input parameters. Based on the machining conditions, Taguchi L8 orthogonal array was used for conducting the experimental runs. The surface roughness and surface crack density (SCD) were considered as the output measures. The surface roughness was measured using 3D White Light Interferometer (WLI) and the crack density was measured using Scanning Electron Microscope (SEM). The optimized result achieved from this approach suggests reduced surface roughness and surface crack density. The holes drilled at an inclination angle of 45°, laser scan speed of 3 mm/s and 400 number of passes found to be optimum. From the Analysis of variance (ANOVA), inclination angle and number of passes were identified as the major influencing parameter. The optimized parameter combination exhibited a 19% improvement in surface finish and 12% reduction in SCD.