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Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework.
Sci Rep
December 2024
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, 03680, Kyiv, Ukraine.
The integration of Electric Vehicles (EVs) into power grids introduces several critical challenges, such as limited scalability, inefficiencies in real-time demand management, and significant data privacy and security vulnerabilities within centralized architectures. Furthermore, the increasing demand for decentralized systems necessitates robust solutions to handle the growing volume of EVs while ensuring grid stability and optimizing energy utilization. To address these challenges, this paper presents the Demand Response and Load Balancing using Artificial intelligence (DR-LB-AI) framework.
View Article and Find Full Text PDFLyophilization of ASFV vaccine candidate ASFV-G-ΔI177L offers long term stability.
Sci Rep
December 2024
Plum Island Animal Disease Center, Agricultural Research Service, USDA, Greenport, NY, 11944, USA.
For over a century African swine fever (ASF) has been causing outbreaks leading to devastating losses for the swine industry. The current pandemic of ASF has shown no signs of stopping and continues to spread causing outbreaks in additional countries. Currently control relies mostly on culling infected farms, and strict biosecurity procedures.
View Article and Find Full Text PDFA lightweight and precision dual track 1D and 2D feature fusion convolutional network for machinery equipment fault diagnosis.
Sci Rep
December 2024
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, 325035, China.
Addressing the issues of a single-feature input channel structure, scarcity of training fault data, and insufficient feature learning capabilities in noisy environments for intelligent diagnostic models of mechanical equipment, we propose a method based on a one-dimensional and two-dimensional dual-channel feature information fusion convolutional neural network (1D_2DIFCNN). By constructing a one-dimensional and two-dimensiona dual-channel feature information fusion convolutional network and introducing a Convolutional Block Attention Mechanism, we utilize Random Overlapping Sampling Technique to process raw vibration signals. The model takes as inputs both one-dimensional data and two-dimensional Continuous Wavelet Transform images.
View Article and Find Full Text PDFIn vivo imaging of glycogen in human muscle.
Nat Commun
December 2024
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
Probing regional glycogen metabolism in humans non-invasively has been challenging due to a lack of sensitive approaches. Here we studied human muscle glycogen dynamics post-exercise with a spatial resolution of millimeters and temporal resolution of minutes, using relayed nuclear Overhauser effect (glycoNOE) MRI. Data at 5T showed a homogeneous distribution of glycogen in resting muscle, with an average concentration of 99 ± 13 mM.
View Article and Find Full Text PDFMortality in Haemophilia Patients in India: A National Cohort Study.
Haemophilia
December 2024
Advanced Center for Oncology, Hematology and Rare Disorders (ACOHRD), K.J. Somaiya Super Speciality Hospital & Research Center, Somaiya Ayurvihar, Sion East, Mumbai, Maharashtra, India.
Introduction: Mortality and morbidity in persons with haemophilia (PWH) have decreased due to improved diagnosis and treatment along with comprehensive population outreach efforts, but the impact is not uniform in different countries.
Aim: The study aims to assess all-cause and intracranial haemorrhage (ICH)-specific mortality of PWH in India.
Methods: This is a retrospective, observational, multi-centric cohort study of 1020 haemophilia patients from three centres in India.
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