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Fast surface reconstruction algorithm with adaptive step size.
PLoS One
January 2025
School of Mathematics and Finance, Hunan University of Humanities, Science and Technology, Loudi, China.
In (Dai et al. 2023), the authors proposed a fast algorithm for surface reconstruction that converges rapidly from point cloud data by alternating Anderson extrapolation with implicit progressive iterative approximation (I-PIA). This algorithm employs a fixed step size during iterations to enhance convergence.
View Article and Find Full Text PDFA safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.
PLoS One
January 2025
Institute of Visual Informatics, The National University of Malaysia (UKM), Bangi, Malaysia.
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enable adaptive insulin dosing control, they face numerous challenges, including safety and training efficiency, which have hindered their clinical application. This paper proposes a safe and efficient adaptive insulin delivery controller based on DRL.
View Article and Find Full Text PDFTwo-Dimensional Liquid Chromatography-Isotope Ratio Mass Spectrometry Opens New Possibilities in the Field of Compound-Specific Stable Isotope Analysis.
Anal Chem
January 2025
Instrumental Analytical Chemistry, University of Duisburg-Essen, Universitätsstraße 5, 45141 Essen, Germany.
Compound-specific stable isotope analysis (CSIA) using liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is a powerful tool for determining the isotopic composition of carbon in analytes from complex mixtures. However, LC-IRMS methods are constrained to fully aqueous eluents. Previous efforts to overcome this limitation were unsuccessful, as the use of organic eluents in LC-IRMS was deemed impossible.
View Article and Find Full Text PDFIdentifying gait differences between Alzheimer's disease and dementia with Lewy bodies and their associations with regional amyloid deposition.
Alzheimers Dement
January 2025
Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Introduction: We aimed to compare gait between individuals with Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and cognitively unimpaired (CU) individuals and to evaluate the association between gait and regional amyloid beta (Aβ) burden in AD and DLB.
Methods: We included 420 participants (70 AD, 70 DLB, 280 CU) in the Mayo Clinic Study of Aging (MCSA). Gait was assessed using a pressure-sensor walkway.
An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.
Alzheimers Dement
January 2025
Department of Public Health Sciences, University of California, Davis, Davis, California, USA.
Introduction: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.
Methods: We define a syndrome as a unique biomarker progression pattern and develop a lag measure to cluster pre-dementia individuals, reflecting their pathology's multi-dimensionality. The technique uses the time-ordering of events to group individuals based on their position along the disease process and the relative positions of their markers.
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