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Improving ocean reanalyses of observationally sparse regions with transfer learning.
Sci Rep
January 2025
Institute of Oceanography, Center for Earth System Sustainability, Universität Hamburg, Hamburg, Germany.
Oceanic subsurface observations are sparse and lead to large uncertainties in any model-based estimate. We investigate the applicability of transfer learning based neural networks to reconstruct North Atlantic temperatures in times with sparse observations. Our network is trained on a time period with abundant observations to learn realistic physical behavior.
View Article and Find Full Text PDFStochastic Thermodynamics of a Linear Optical Cavity Driven on Resonance.
ACS Photonics
January 2025
Center for Nanophotonics, AMOLF, Science Park 104, XG Amsterdam 1098, the Netherlands.
We present a complete framework of stochastic thermodynamics for a single-mode linear optical cavity driven on resonance. We first show that the steady-state intracavity field follows the equilibrium Boltzmann distribution. The effective temperature is given by the noise variance, and the equilibration rate is the dissipation rate.
View Article and Find Full Text PDFAutomated Detection of Filamentous Fungal Keratitis on Whole Slide Images of Potassium Hydroxide Smears with Multiple Instance Learning.
Ophthalmol Sci
November 2024
Casey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Purpose: The diagnosis of fungal keratitis using potassium hydroxide (KOH) smears of corneal scrapings enables initiation of the correct antimicrobial therapy at the point-of-care but requires time-consuming manual examination and expertise. This study evaluates the efficacy of a deep learning framework, dual stream multiple instance learning (DSMIL), in automating the analysis of whole slide imaging (WSI) of KOH smears for rapid and accurate detection of fungal infections.
Design: Retrospective observational study.
Author Correction: Future increase in compound soil drought-heat extremes exacerbated by vegetation greening.
Nat Commun
January 2025
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China.
[Management of risks linked to the sterilization of reusable medical devices in dentistry].
Ann Pharm Fr
January 2025
Service de la pharmacie, pharmacologie et pharmacotechnie hospitalière, hôpital militaire principal d'instruction de Tunis, Tunis, Tunisie; Faculté de pharmacie de Monastir, université de Monastir, Monastir, Tunisie.
Objective: The aim of this study was to analyze the risks associated with the sterilization process for reusable medical devices (RMD) in stomatology, by applying the FMECA method, with a view to implementing the necessary corrective and preventive actions necessary to secure this process.
Methods: The study, which was descriptive, took place between June and July 2024 in the medicine and dental surgery department of our hospital and concerned the moist heat sterilization process of RMD. The study began by defining its scope and the formation of the work team, followed by the functional analysis of the process, the identification of the failure modes (FM), the definition of the rating scales, the rating of the FM and finally the calculation of the criticality index and the development of the action plan.
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