The railway industry has witnessed increasing adoption of digital technologies, known as Railway 4.0, that is revolutionizing operations, infrastructure, and transportation systems. However, developing countries face challenges in keeping pace with these technological advancements. With limited research on Railway 4.0 adoption in developing countries, this study was motivated to investigate the awareness, readiness, and challenges faced by railway professionals towards implementing Railway 4.0 technologies. The aim was to assess the level of awareness and preparedness and identify the key challenges influencing Railway 4.0 adoption in Nigeria's railway construction industry. A questionnaire survey (was distributed to professionals in the railway construction sector to gather their perspectives on awareness of, preparation for, and challenges associated with the use of Railway 4.0 technologies. The results revealed that awareness of Railway 4.0 technologies was moderate, while readiness was low among the professionals. Using exploratory factor analysis, 10 underlying challenge constructs were identified including lack of technical know-how, resistance to change, infrastructure limitations, and uncertainty about benefits, amongst others. Partial Least Square Structural Equation Modelling (PLS-SEM) confirmed these constructs, with reliability and availability, lack of technical know-how, lack of training and resources, and uncertainties in benefit and gains having significant influence on awareness and readiness. The study concludes that focused efforts in training, infrastructure improvement, supportive policies, and communicating the advantages of Railway 4.0 are critical to drive adoption in Nigeria and other developing economies. The findings provide insights into tailoring Railway 4.0 implementation strategies for developing contexts.
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http://dx.doi.org/10.1016/j.heliyon.2024.e25934 | DOI Listing |
J Drug Target
January 2025
Sunirmal Bhattacharjee, Bharat Pharmaceutical Technology, Amtali, Agartala, Tripura, India.
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.
View Article and Find Full Text PDFUltrasonics
December 2024
School of Mechatronic & Automation Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Silicate Cultural Relics Conservation (Shanghai University), Ministry of Education, China. Electronic address:
Fiber reinforced polymer composites (FRPs) are essential for various industrial fields, but wrinkles inside will greatly reduce their mechanical properties. Full-matrix capture (FMC) is a popular data structure for ultrasonic phased array imaging in composites. However, such structure may lead to data redundancy and noise interference.
View Article and Find Full Text PDFPsychol Res Behav Manag
December 2024
Department of Psychiatry, Sleep Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People's Republic of China.
Purpose: Network analysis is a statistical method that explores the complex interrelationships among variables by representing them as nodes and edges in a network structure. This study aimed to examine the interconnections between family functioning, anxiety, and depression among vocational school students through network analysis approach.
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Sci Rep
December 2024
School of Civil Engineering, Southeast University, Nanjing, 211189, China.
Collapsible loess soils, known for their significant volume reduction upon the wetting, pose critical challenges in the geotechnical engineering. The estimation of the wetting-induced settlement is crucial for the foundation design and the determination of the negative skin friction on the pile. In this paper, a new method is proposed to estimate the wetting induced collapse from the wetting soil-water characteristic curve (SWCC) and the index properties of the loess soils.
View Article and Find Full Text PDFSci Rep
December 2024
School of Civil and Hydraulic Engineering, Chongqing University of Science & Technology, Chongqing, 400074, China.
The CRTS (China Railway Track System) II slab ballastless track is widely utilized in high-speed railway construction owing to its excellent structural integrity. However, its interfacial performance deteriorates under high-temperature conditions, leading to significant damage in structural details. Furthermore, the evolution of its performance under these conditions has not been comprehensively studied.
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