A complex of short-basis photogrammetry, methods and software for obtaining and analysis of 3D digital models of relief of dentition and its fragments is presented. This complex is intended for planning and evaluation of tooth preparation and quality of prosthetic treatment. The method was used to assess the correctness of dental shape repair by artificial crowns. The complex can form the base for the CAD/CAM technology.
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Neural Netw
December 2024
Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2BP, UK; Centre for AI-Physics Modelling, Imperial-X, White City Campus, Imperial College London, W12 7SL, UK.
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this development via implementing conventional partial differential equation (PDE) solvers with machine learning packages, most of which rely on structured spatial discretisation and fast convolution algorithms. However, unstructured meshes are favoured in problems with complex geometries.
View Article and Find Full Text PDFCurr Ther Res Clin Exp
December 2024
Department of Infection Management, Nantong Fourth People's Hospital, Nantong, Jiangsu, China.
Background: The escalating threat of multidrug-resistant organisms (MDROs) in intensive care unit (ICU) demands innovative management strategies to curb the rising infection rates and associated clinical challenges.
Objective: To assess the effectiveness of integrating the multidisciplinary team (MDT) approach with the SHEL (Software, Hardware, Environment, Liveware) model in reducing MDRO infections within ICU settings.
Methods: From January 2021 to April 2024, a prospective, randomized controlled study was conducted in the ICU of Nantong Fourth People's Hospital, enrolling 411 patients with MDRO infections.
Philos Trans A Math Phys Eng Sci
January 2025
RPTU Kaiserslautern-Landau, Kaiserslautern, Germany.
The advent of in-memory computing has introduced a new paradigm of computation, which offers significant improvements in terms of latency and power consumption for emerging embedded AI accelerators. Nevertheless, the effect of the hardware variations and non-idealities of the emerging memory technologies may significantly compromise the accuracy of inferred neural networks and result in malfunctions in safety-critical applications. This article addresses the issue from three different perspectives.
View Article and Find Full Text PDFJ Neurol
January 2025
Department of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.
Background: Neurological disorders pose a substantial burden worldwide in healthcare and health research. eHealth has emerged as a promising field given its potential to aid research, with lower resources. With a changing eHealth landscape, identifying available tools is instrumental for informing future research.
View Article and Find Full Text PDFBiofabrication
January 2025
Biomedical Engineering and CÚRAM, SFI Research Centre for Medical Devices, University of Galway, School of Engineering, University Road, Galway, Ireland, Galway, H91 TK33, IRELAND.
Despite significant advances in bioprinting technology, current hardware platforms lack the capability for process monitoring and quality control. This limitation hampers the translation of the technology into industrial GMP-compliant manufacturing settings. As a key step towards a solution, we developed a novel bioprinting platform integrating a high-resolution camera for in-situ monitoring of extrusion outcomes during embedded bioprinting.
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