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http://dx.doi.org/10.1016/j.jdcr.2024.04.046 | DOI Listing |
iScience
October 2024
Department of Mathematics, Faculty of Science, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic.
Machine translation facilitates cross-linguistic communication by converting text between languages. However, producing contextually accurate translations remains a challenge. This review explores the difficulties in achieving such accuracy, particularly in capturing contextual information, disambiguating polysemous words, and handling idiomatic expressions, cultural nuances, and domain-specific terms.
View Article and Find Full Text PDFJAAD Case Rep
July 2024
Department of Dermatology, University of Washington, Seattle, Washington.
Anat Sci Int
September 2024
Division of Clinical Anatomy, Department of Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Anatomy, the study of human structure, is foundational to medicine. Its language has a long history, with contributions from authors hailing from diverse cultures and countries, adhering to various scientific traditions, speaking different languages, and practicing medicine across a wide gamut of specialties. The resultant disparity in terms provides challenges both for students in learning and for interdisciplinary communication.
View Article and Find Full Text PDFMachine translation produces marginal accuracy rates for low-resource languages, but its deep learning model expects to yield improved accuracy with time. This longitudinal study investigates how Google Translate's Urdu-to-English translated output has evolved between 2018 and 2021. Accuracy and acceptability of the translations have been determined by, a) an interlinear gloss that identifies core semantic units and grammatical functions to be translated and, b) a descriptive comparison of the translated text's syntactic and semantic properties with those of the source text.
View Article and Find Full Text PDFJ Morphol
July 2023
Department of Philosophy, University of Alberta, Edmonton, Canada.
The term "homology" is persistently polysemous, defying the expectation that extensive scientific research should yield semantic stability. A common response has been to seek a unification of various prominent definitions. This paper proposes an alternative strategy, based on the insight that scientific concepts function as tools for research: When analyzing various conceptualizations of homology, we should preserve those distinguishing features that support particular research goals.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!