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The purpose of this study is to build a structural relationship model based on total interpretive structural modeling (TISM) and fuzzy input-based cross-impact matrix multiplication applied to classification (MICMAC) for analysis and prioritization of the barriers influencing the implementation of Industry 4.0 technologies. 10 crucial barriers that affect the deployment of Industry 4.0 techniques are identified in the literature. Also, the Fuzzy MICMAC approach is applied to classify the barriers. The importance of TISM over traditional interpretive structural modeling (ISM) is shown in this work. Results proved that the barriers, namely IT infrastructure, lack of cyber physical systems, and improper communication models, are identified as the most dependent barriers, and the barriers of lack of top management commitment and inadequate training are identified as the most driving barriers. This study makes it easier for decision-makers to take the necessary steps to mitigate the barriers. The bottom level of the TISM hierarchy is occupied by barriers that need more attention from top management in order to be effectively monitored and managed. This study explains the steps to execute TISM in detail, making it easy for researchers and practitioners to comprehend its principles.
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http://dx.doi.org/10.1016/j.heliyon.2023.e22506 | DOI Listing |
PLoS One
September 2025
Department of Engineering and School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Citizen science engages volunteers to contribute data to scientific projects, often through visual annotation tasks. Hearing based activities are rare and less well understood. Having high quality annotations of performed music structures is essential for reliable algorithmic analysis of recorded music with applications ranging from music information retrieval to music therapy.
View Article and Find Full Text PDFMol Omics
September 2025
Laboratory of Structural Bioinformatics and Computational Biology, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, 9500, Porto Alegre 91501-970, RS, Brazil.
The integration of multimodal single-cell omics data is a state-of-art strategy for deciphering cellular heterogeneity and gene regulatory mechanisms. Recent advances in single-cell technologies have enabled the comprehensive characterization of cellular states and their interactions. However, integrating these high-dimensional and heterogeneous datasets poses significant computational challenges, including batch effects, sparsity, and modality alignment.
View Article and Find Full Text PDFHealth Expect
October 2025
School of Pharmacy, Newcastle University, Newcastle Upon Tyne, UK.
Introduction: There remains limited research exploring the experiences of informal carers from ethnically minoritised groups, particularly to illustrate perceptions of caring roles and challenges they may face to address unmet needs. While barriers such as language, cultural expectations and discrimination are acknowledged in wider literature, little is known about how these influence caregiving experiences or access to services in practice. This work seeks to better describe the barriers and facilitators impacting carers from ethnically minoritised groups, as well as illustrate possible influences of culture and carer identity affecting this under-researched population.
View Article and Find Full Text PDFDeath Stud
September 2025
Department of Educational Sciences, University of Catania, Catania, Italy.
This study explored the network relationships between defense mechanisms and symptoms of depression, anxiety, and stress in a sample of 327 Italian bereaved adults (M = 46.92, SD = 14.66).
View Article and Find Full Text PDFAnn Acad Med Singap
August 2025
Dementia Research Centre (Singapore), Lee Kong Chian School of Medicine, Nanyang Technology University, Singapore.
Introduction: Interpretation and analysis of magnetic resonance imaging (MRI) scans in clinical settings comprise time-consuming visual ratings and complex neuroimage processing that require trained professionals. To combat these challenges, artificial intelligence (AI) techniques can aid clinicians in interpreting brain MRI for accurate diagnosis of neurodegenerative diseases but they require extensive validation. Thus, the aim of this study was to validate the use of AI-based AQUA (Neurophet Inc.
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