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A multi-feature dataset of coated end milling cutter tool wear whole life cycle.
Sci Data
January 2025
School of Cyber Science and Engineering, Qufu Normal University, Qufu, 273165, China.
Deep learning methods have shown significant potential in tool wear lifecycle analysis. However, there are fewer open source datasets due to the high cost of data collection and equipment time investment. Existing datasets often fail to capture cutting force changes directly.
View Article and Find Full Text PDFMachine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.
Nat Commun
January 2025
NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust & University College London Institute of Ophthalmology, London, UK.
Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset.
View Article and Find Full Text PDFMachine learning-based geospatial applications offer unique opportunities for environmental monitoring due to domains and scales adaptability and computational efficiency. However, the specificity of environmental data introduces biases in straightforward implementations. We identify a streamlined pipeline to enhance model accuracy, addressing issues like imbalanced data, spatial autocorrelation, prediction errors, and the nuances of model generalization and uncertainty estimation.
View Article and Find Full Text PDFFrom bits to bedside: entering the age of digital twins in cardiac electrophysiology.
Europace
December 2024
Gottfried Schatz Research Center, Medical Physics and Biophysics, Medical University of Graz, Graz, Austria.
This State of the Future Review describes and discusses the potential transformative power of digital twins in cardiac electrophysiology. In this 'big picture' approach, we explore the evolution of mechanistic modelling based digital twins, their current and immediate clinical applications, and envision a future where continuous updates, advanced calibration, and seamless data integration redefine clinical practice of cardiac electrophysiology. Our aim is to inspire researchers and clinicians to embrace the extraordinary possibilities that digital twins offer in the pursuit of precision medicine.
View Article and Find Full Text PDFProduction of Novel Energy Gases in Bioprocesses Using Undefined Mixed Cultures.
Adv Biochem Eng Biotechnol
December 2024
Savonia University of Applied Sciences, Kuopio, Finland.
Three phases of matter intermingle in various environments. The phenomena behind these fluctuations provide microbial cultures with beneficial interphase on the borderlines. Correspondingly, a bioreactor broth usually consists of a liquid phase but also contains solid particles, gas bubbles, technical surfaces, and other niches, both on a visible scale and microscopically.
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