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r, s, t-spherical fuzzy (r, s, t-SPF) sets provide a robust framework for managing uncertainties in decision-making, surpassing other fuzzy sets in their ability to accommodate diverse uncertainties through the incorporation of flexible parameters r, s, and t. Considering these characteristics, this article explores sine trigonometric laws to enhance the applicability and theoretical foundation for r, s, t-SPF setting. Following these laws, several aggregation operators (AOs) are designed for aggregation of the r, s, t-SPF data. Meanwhile, the desired characteristics and relationships of these operators are studied under sine trigonometric functions. Furthermore, we build a group decision-making algorithm for addressing multiple attribute group decision-making (MAGDM) problems using the developed AOs. To exemplify the applicability of the proposed algorithm, we address a practical example regarding laptop selection. Finally, parameter analysis and a comprehensive comparison with existing operators are conducted to uncover the superiority and validity of the presented AOs.
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http://dx.doi.org/10.1038/s41598-024-61382-y | DOI Listing |
Community Health Equity Res Policy
September 2025
College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia.
BackgroundThe nutritional status of Cambodian women and children remain poor despite implementation of dietary intake interventions. Cambodia-specific studies have explored how education influences nutrition and health behavior, but not factors influencing Cambodian women's food decision-making for themselves and their families.ObjectiveTo understand Cambodian women's food decision-making, particularly related to barriers and enablers of healthy eating for themselves and their families.
View Article and Find Full Text PDFArq Bras Cir Dig
September 2025
Universidade de São Paulo, Faculty of Medicine, Department of Gastroenterology, Colonoscopy Division - São Paulo (SP), Brazil.
Background: Artificial intelligence (AI)-assisted colonoscopy has emerged as a tool to enhance adenoma detection rates (ADRs) and improve lesion characterization. However, its performance in real-world settings, especially in developing countries, remains uncertain.
Aims: The aim of this study was to evaluate the impact of AI on ADRs and its concordance with histopathological diagnosis.
PLoS One
September 2025
Department of Community Ecology, Helmholtz Centre for Environmental Research - UFZ, Halle (Saale), Germany.
Pollination is essential for maintaining biodiversity and ensuring food security, and in Europe it is primarily mediated by four insect orders (Coleoptera, Diptera, Hymenoptera, Lepidoptera). However, traditional monitoring methods are costly and time consuming. Although recent automation efforts have focused on butterflies and bees, flies, a diverse and ecologically important group of pollinators, have received comparatively little attention, likely due to the challenges posed by their subtle morphological differences.
View Article and Find Full Text PDFPLoS One
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York, New York, United States of America.
While there has been extensive research on techniques for explainable artificial intelligence (XAI) to enhance AI recommendations, the metacognitive processes in interacting with AI explanations remain underexplored. This study examines how AI explanations impact human decision-making by leveraging cognitive mechanisms that evaluate the accuracy of AI recommendations. We conducted a large-scale experiment (N = 4,302) on Amazon Mechanical Turk (AMT), where participants classified radiology reports as normal or abnormal.
View Article and Find Full Text PDFBrain
September 2025
Sorbonne University, Inserm U1127, CNRS UMR7225, UM75, Paris Brain Institute, Movement Investigation and Therapeutics Team, 75013 Paris, France.
Adolescence is frequently called the second brain maturation period. In Tourette disorder (TD), the clinical trajectory of tics and associated psychiatric co-morbidities vary significantly across individuals during the transition from adolescents to adulthood. In this study, we aimed to identify patterns of resting-state functional connectivity that differentiate adolescents with TD from their neurotypical peers, and to monitor symptom-specific functional changes over time.
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