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Blending deep-learning and observers for improved state of charge estimation in vanadium flow batteries.
ISA Trans
December 2024
Group of Power Systems, Catalonia Institute for Energy Research (IREC), Jardins de les Dones de Negre, 1, 08930, Sant Adrià del Besòs, Spain. Electronic address:
This paper presents the design and implementation of a deep-learning-based observer for accurately estimating the State of Charge (SoC) of a vanadium flow battery. The novelty of the proposal lies in its direct use of terminal voltage and the application of a machine learning algorithm to model the battery's overpotentials, leading to greater accuracy and reduced complexity compared to classical models. The overpotentials model consists of a neural network trained using data generated by a classical observer that estimates species concentration using a physical electrochemical model and the open-circuit voltage measurement.
View Article and Find Full Text PDFThe transport, distribution, and budget of anthropogenic I in the Bohai and North Yellow Seas, China.
J Hazard Mater
January 2025
State Key Laboratory of Loess and Quaternary Geology, Shaanxi Key Laboratory of Accelerator Mass Spectrometry Technology and Application, Xi'an AMS Center, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China. Electronic address:
The potential release of radionuclides threatens marine ecosystems with the rapid development of coastal nuclear power plants in China. However, transport, dispersion, and final budget of anthropogenic radionuclides remain unclear, especially in the Bohai and North Yellow Seas, which are semi-enclosed marginal seas with poor water exchange. This study analyzed anthropogenic I concentration (a typical product of nuclear power plant operations) in seawater samples from this area.
View Article and Find Full Text PDFAutomated segmentation of deep brain structures from Inversion-Recovery MRI.
Comput Med Imaging Graph
January 2025
Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal, F-63000 Clermont-Ferrand, France; Université Clermont Auvergne, CNRS, CHU Clermont-Ferrand, Clermont Auvergne INP, Institut Pascal, F-63000 Clermont-Ferrand, France.
Methods for the automated segmentation of brain structures are a major subject of medical research. The small structures of the deep brain have received scant attention, notably for lack of manual delineations by medical experts. In this study, we assessed an automated segmentation of a novel clinical dataset containing White Matter Attenuated Inversion-Recovery (WAIR) MRI images and five manually segmented structures (substantia nigra (SN), subthalamic nucleus (STN), red nucleus (RN), mammillary body (MB) and mammillothalamic fascicle (MT-fa)) in 53 patients with severe Parkinson's disease.
View Article and Find Full Text PDFAutomatic medical report generation based on deep learning: A state of the art survey.
Comput Med Imaging Graph
January 2025
College of Medicine and Biological Information Engineering, Northeastern University, 110819, China. Electronic address:
With the increasing popularity of medical imaging and its expanding applications, posing significant challenges for radiologists. Radiologists need to spend substantial time and effort to review images and manually writing reports every day. To address these challenges and speed up the process of patient care, researchers have employed deep learning methods to automatically generate medical reports.
View Article and Find Full Text PDFDeep brain stimulation - A primer for psychiatrists.
Asian J Psychiatr
December 2024
OCD Clinic, Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), India.
Deep Brain Stimulation is a form of neurostimulation where electrical stimulation is delivered via intracranial electrodes over specific subcortical targets. It has been increasingly used as an alternative to ablative procedures for psychiatric disorders refractory to standard treatments. This review describes the common psychiatric indications for DBS, the current evidence base, putative mechanisms, and future directions.
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