Results 61 to 70 of about 16,838,211 (334)

The Intelligent Data Analysis Techniques and its Significant Impact on Managing Renewable Energy Resources

Ibn Al-Haitham Journal for Pure and Applied Sciences
Accelerated technological development has a significant role in highly increasing energy demand, which enhances the interest of companies and governments in adopting renewable energy sources and finding new technologies that enable the effective use of ...
Ghada S. Mohammed, Osama Basil Ghazi , Ahmed Basil Ghazi , Salahuddin I. Abdrabba   +3 more
doaj   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Blockchain-Enabled Privacy-Preserving Federated Learning with Deep Capsule Networks for Energy-Efficient Speed Control in Autonomous Vehicles

Communications
Rough roads negatively affect the ride quality and energy efficiency of autonomous vehicles (AVs) and demand adaptive speed control. To solve this, this research proposes a Deep Capsule Network integrated with Sparse Kernel K-means Clustering (DCapsNet +
N Sanjith, M. Nithya, Sreeju P Sreedharan   +2 more
doaj   +1 more source

Autophagy and mitophagy in pancreatic β‐cell homeostasis and their involvement in diabetes pathophysiology

FEBS Letters, EarlyView.
This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee, Mingming Tong, Anna L. Gloyn   +2 more
wiley   +1 more source

An Accelerated Edge Cloud System for Energy Data Stream Processing Based on Adaptive Incremental Deep Learning Scheme

IEEE Access, 2020
As smart metering technology evolves, power suppliers can make low-cost, low-risk estimation of customer-side power consumption by analyzing energy demand data collected in real-time.
Seong-Hwan Kim, Changha Lee, Chan-Hyun Youn   +2 more
doaj   +1 more source

Performance Analysis of Deep Learning-Based Routing Protocol for an Efficient Data Transmission in 5G WSN Communication

IEEE Access, 2022
For the past few years, huge interest and dramatic development have been shown for the Internet of Things (IoT) based constrained Wireless sensor network (WSN) to achieve efficient resource utilization and better service delivery.
Greeshma Arya, Ashish Bagwari, Durg Singh Chauhan   +2 more
doaj   +1 more source

Emerging experimental and computational methods for studying redox‐regulated structural transitions

FEBS Letters, EarlyView.
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass, Dana Reichmann, Gábor Erdős   +2 more
wiley   +1 more source

Soft motions encoded by the fold and mediated by conserved hinge sites drive V‐ATPase allosteric machinery and autoinhibition

FEBS Letters, EarlyView.
Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana, Xiaowei Bogetti, Stuti Sharma, Ivet Bahar   +3 more
wiley   +1 more source

An Energy-Efficient Cross-Layer Routing Protocol for Cognitive Radio Networks Using Apprenticeship Deep Reinforcement Learning

Energies, 2019
Deep reinforcement learning (DRL) has been successfully used for the joint routing and resource management in large-scale cognitive radio networks. However, it needs lots of interactions with the environment through trial and error, which results in ...
Yihang Du, Ying Xu, Lei Xue, Lijia Wang, Fan Zhang   +4 more
doaj   +1 more source

Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model

, 2022
Optimal utilisation of the sun's freely available energy to generate electricity requires efficient predictive models of global solar radiation (GSR). These are necessary to provide solar energy companies an early and effective market entry to support ...
Sujan Ghimire, Deo, Ravinesh C., Casillas-Perez, David, David Casillas-Pérez, Ghimire, Sujan, Ravinesh C Deo, Thong Nguyen-Huy, Nguyen-Huy, Thong, Salcedo-sanz, Sancho, Sancho Salcedo-Sanz   +9 more
core   +1 more source