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Over the past decades, facial expression recognition (FER) has become an interesting research area and achieved substantial progress in computer vision. FER is to detect human emotional state related to biometric traits. Developing a machine based human FER system is a quite challenging task. Various FER systems are developed by analysing facial muscle motion and skin deformation based algorithms. In conventional FER system, the developed algorithms work on the constrained database. In the unconstrained environment, the efficacy of existing algorithms is limited due to certain issues during image acquisition. This study presents a detailed study on FER techniques, classifiers and datasets used for analysing the efficacy of the recognition techniques. Moreover, this survey will assist researchers in understanding the strategies and innovative methods that address the issues in a real-time application. Finally, the review presents the challenges encountered by FER system along with the future direction.

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microRNAs (miRNAs) constitute a family of small, non-coding RNA molecules that regulate gene expression and protein expression. microRNAs have influence on a broad range of physiologic and pathologic conditions. They are also considered as promising biomarkers especially when they are secreted extracellularly. In the inflammatory pathways, they dysregulate the molecular processes and contribute to the development of chronic inflammatory diseases including periodontitis. In this review, we provide an overview of miRNA characteristics, biogenesis, mechanisms of action and profiling methods. In addition, the role of miRNAs in the pathobiology of periodontitis, especially those pertaining to the cellular and molecular pathways of inflammation has been considered to enhance our understanding of the pathobiology of periodontitis. www.adum.edu.my