In their anthology Everything Flows: Towards a Processual Philosophy of Biology, Daniel J. Nicholson and John Dupré argue that modern theories of biology imply that the fundamental structure of reality is processual at its core. In the present work, I first examine the implicit and explicit metaphysical presuppositions the editors make in order to allow for such an inference from scientific theory to ontology. After showing the difficulties of a naïve transfer of theoretical entities to fundamental ontology, I argue that the editors can nevertheless extend their claims beyond the mere articulation of different domain ontologies. This leads to the idea of a scientifically informed induction base for an ontology of processes.
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http://dx.doi.org/10.1007/s40656-024-00618-6 | DOI Listing |
Through progressive policies, Rwanda has made significant strides in promoting girls' education and empowerment. However, female enrollment in Bachelor of Medicine and Bachelor of Surgery (MBBS) programs remains disproportionately low. This cross-sectional study investigates the influence of gender stereotypes and girls' self-perceptions on female engagement in MBBS programs in Rwanda.
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January 2025
School of Allied Health Science and Practice, Engineering Math and Science Building, University of Adelaide, North Terrace, Level 4, Adelaide, South Australia, 5005, Australia.
Background: Training programs grounded in educational theory offer a systematic framework to facilitate learning and outcomes. This scoping review aims to map the educational approaches documented for manual wheelchair training and to record intended learning outcomes and any relationships between learning theories, instructional design and outcomes.
Methods: Eight databases; Cochrane's Library, EMBASE, CINAHL, PubMed, Scopus, EmCare, Medline, ProQuest Nursing and Allied Health Database and grey literature were searched in September 2023, with citation chaining for relevant papers.
Sci Rep
January 2025
School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia.
Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. To address the issue, this study uses optical coherence tomography (OCT) images to develop an explainable artificial intelligence (XAI) tool for diagnosing and staging glaucoma, with a focus on its clinical applicability.
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January 2025
School of Computer Science and Technology, Donghua University, Shanghai, 201620, China.
Extracting high-order abstract patterns from complex high-dimensional data forms the foundation of human cognitive abilities. Abstract visual reasoning involves identifying abstract patterns embedded within composite images, considered a core competency of machine intelligence. Traditional neuro-symbolic methods often infer unknown objects through data fitting, without fully exploring the abstract patterns within composite images and the sequential sensitivity of visual sequences.
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