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  1. Ahmed Al-Hussein W, Mat Kiah ML, Lip Yee P, Zaidan BB
    PeerJ Comput Sci, 2021;7:e632.
    PMID: 34541305 DOI: 10.7717/peerj-cs.632
    In the plan and development of Intelligent Transportation Systems (ITS), understanding drivers behaviour is considered highly valuable. Reckless driving, incompetent preventive measures, and the reliance on slow and incompetent assistance systems are attributed to the increasing rates of traffic accidents. This survey aims to review and scrutinize the literature related to sensor-based driver behaviour domain and to answer questions that are not covered so far by existing reviews. It covers the factors that are required in improving the understanding of various appropriate characteristics of this domain and outlines the common incentives, open confrontations, and imminent commendations from former researchers. Systematic scanning of the literature, from January 2014 to December 2020, mainly from four main databases, namely, IEEEXplore, ScienceDirect, Scopus and Web of Science to locate highly credible peer-reviewed articles. Amongst the 5,962 articles found, a total of 83 articles are selected based on the author's predefined inclusion and exclusion criteria. Then, a taxonomy of existing literature is presented to recognize the various aspects of this relevant research area. Common issues, motivations, and recommendations of previous studies are identified and discussed. Moreover, substantial analysis is performed to identify gaps and weaknesses in current literature and guide future researchers into planning their experiments appropriately. Finally, future directions are provided for researchers interested in driver profiling and recognition. This survey is expected to aid in emphasizing existing research prospects and create further research directions in the near future.
  2. Alghamdi A, A Awadh Ali N, Alafnan A, Zainal Abidin SA, Alamri A, Hussein W, et al.
    Food Chem Toxicol, 2024 Nov;193:115028.
    PMID: 39368542 DOI: 10.1016/j.fct.2024.115028
    This study explores the phytochemical composition and biological activities of Verbascum yemenense, a plant known for its medicinal properties. The plant extract revealed a rich presence of bioactive compounds that exhibited significant antioxidant properties against free radicals. The enzyme inhibition potential was particularly notable against cholinesterases (AChE: 2.56 mg GALAE/g; BChE: 1.98 mg GALAE/g), and tyrosinase (87.94 mg KAE/g), α-glucosidase suggesting potential therapeutic applications in neurodegenerative diseases, skin disorders and diabetes. Molecular docking studies and Molecular Dynamics simulations, providing insights into the interaction mechanisms of the identified compounds with the target proteins. Molecular docking studies revealed high binding affinities of the phytoconstituents, with compounds like VY4 and phyllanthusol-A (VY15) showing substantial docking scores against AChE (-9.840 kcal/mol) and BChE (-9.853 kcal/mol), respectively. For instance, the RMSD values during the MD simulations for compound VY17 in the AML complex showed a stable conformation, fluctuating within a range of 0.75 Å to 1.75 Å, indicating a strong and consistent interaction with the enzyme. MESP studies highlighted VY17's distinctive electrostatic features, notably a pronounced electronegative region, which might contribute to its binding efficiency. These findings suggest that V. yemenense is a promising candidate for developing novel therapeutic agents.
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