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( Rahman ),( Raja Noor Zaliha Raja Abd ),( Noor Dina Muhd Noor ),( Noor Azlina Ibrahim ),( Abu Bakar Salleh ),( Mahiran Basri ) 한국미생물 · 생명공학회 2012 Journal of microbiology and biotechnology Vol.22 No.1
A thermophilic Bacillus stearothermophilus F1 produces an extremely thermostable serine protease. The F1 protease sequence was used to predict its three-dimensional (3D) structure to provide better insights into the relationship between the protein structure and biological function and to identify opportunities for protein engineering. The final model was evaluated to ensure its accuracy using three independent methods: Procheck, Verify3D, and Errat. The predicted 3D structure of F1 protease was compared with the crystal structure of serine proteases from mesophilic bacteria and archaea, and led to the identification of features that were related to protein stabilization. Higher thermostability correlated with an increased number of residues that were involved in ion pairs or networks of ion pairs. Therefore, the mutants W200R and D58S were designed using site-directed mutagenesis to investigate F1 protease stability. The effects of addition and disruption of ion pair networks on the activity and various stabilities of mutant F1 proteases were compared with those of the wild-type F1 protease.
A systematic review of emotion recognition using cardio-based signals
Sayed Ismail Sharifah Noor Masidayu,Ab. Aziz Nor Azlina,Ibrahim Siti Zainab,Mohamad Mohd Saberi 한국통신학회 2024 ICT Express Vol.10 No.1
There is a growing demand for emotion recognition systems (ERS) to be adopted in everyday life from various fields, particularly automotive, education, and social security. Recently, the use of cardio-based physiological signals, electrocardiogram (ECG), and photoplethysmogram (PPG) in ERS has yielded promising results. Furthermore, the development of wearable devices equipped with cardio-based physiological sensors has significantly aided towards the adoption of ERS in daily life. This paper systematically reviews emotion recognition using cardio-based physiological signals, encompassing emotion models, emotion elicitation methods, and ERS development methods, emphasizing feature extraction, feature selection methods, feature dimension reduction methods, and classifiers. A summary and comparison of recent studies are presented to highlight existing studies’ gaps and suggest future research for better ERS especially using cardio-based signals.