Results 111 to 120 of about 1,629,210 (315)

Unlocking the Power of Quercetin‐Encapsulated Mesoporous Bioactive Glass Nanoparticles: A Multifunctional Approach to Bone Regeneration

Advanced Engineering Materials, EarlyView.
Mesoporous bioactive glass nanoparticles (MBGNs) are investigated for bone regeneration given their remarkable structural and functional properties. MBGNs are functionalized with Mn and Cu and incorporated with quercetin, a natural flavonoid exhibiting antioxidant, anti‐inflammatory, and antimicrobial properties.
Giovanni Lo Bello, Qaisar Nawaz, Pier Francesco Ferrari, Laura Pastorino, Roberto Raiteri, Aldo R. Boccaccini   +5 more
wiley   +1 more source

Two-stage data-driven optimal energy management and dynamic real-time operation in networked microgrid based on a deep reinforcement learning approach

International Journal of Electrical Power & Energy Systems
Given the significant challenges posed by the vast and diverse data in energy management, this study introduces a two-stage approach: optimal energy management system (OEMS) and dynamic real-time operation (DRTOP).
Atefeh Hedayatnia, Javid Ghafourian, Reza Sepehrzad, Ahmed Al-Durrad, Amjad Anvari-Moghaddam   +4 more
doaj   +1 more source

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Advanced Functional Materials, EarlyView.
Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai, Md Shakhawath Hossain, Nhat Minh Nguyen, Yongliang Chen, Chaohao Chen, Xiaoxue Xu, Quang Thang Trinh, Toan Dinh, Toan Trong Tran   +8 more
wiley   +1 more source

Efficient Exploration through Bayesian Deep Q-Networks

, 2018
We study reinforcement learning (RL) in high dimensional episodic Markov decision processes (MDP). We consider value-based RL when the optimal Q-value is a linear function of d-dimensional state-action feature representation. For instance, in deep-Q networks (DQN), the Q-value is a linear function of the feature representation layer (output layer).
Azizzadenesheli, Kamyar, Anandkumar, Animashree   +1 more
openaire   +2 more sources

Single Pair of Weyl Points Evolve From Spin Group‐Protected Nodal Line in Half‐Metallic Ferromagnet V3S4

Advanced Functional Materials, EarlyView.
A spin group (SG)‐based mechanism is proposed to realize a single pair of Weyl points. PT‐symmetric nodal lines (NLs) persist under T‐breaking, protected by the combination of SG and P symmetry. When considering spin‐orbit coupling, the SG‐protected NL will split into Weyl points, which will also induce anomalous transport phenomena arising from ...
Shifeng Qian, Yao Zhang, Xiaowei Sheng, Xiuxian Yang, Gang Zhang, Junfeng Gao, Xiaotian Wang   +6 more
wiley   +1 more source

Self-Driving Car using Deep-Q-Networks

International Journal for Research in Applied Science and Engineering Technology, 2021
A autonomous car is also called a self-driving car or a robot car. As for the history of self-driving cars, radio technology was used to control the tests, which began in 1920, and later in 1950, the tracks were finally put in place. The present-day individual is habituated to automation technology and the use of robotics in areas such as agriculture ...
openaire   +1 more source

Synchrotron Radiation for Quantum Technology

Advanced Functional Materials, EarlyView.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader, Sakura Pascarelli, Klaus Attenkofer, Anna A. Makarova, Karsten Holldack, Kai Rossnagel, Kristiaan Temst, George Kourousias, Stefano Carretta, Caterina Biscari, Helmut Dosch   +10 more
wiley   +1 more source

A DEEP REINFORCEMENT LEARNING APPROACH TO JOINT CODEBOOK SELECTION AND UE SCHEDULING FOR NR-U/WIGIG COEXISTENCE IN UNLICENSED MMWAVE BANDS [PDF]

Journal of Mechanics of Continua and Mathematical Sciences
This paper introduces an intelligent method to enhance communication in unlicensed millimetre-wave (mmWave) networks for New Radio Unlicensed (NR-U) and Wireless Gigabit (WiGig) systems.
K N S K Santhosh, Angara Satyam, Kante Satyanarayana, Venkata Raju Athili, Ponugoti Gangadhara Rao, Bhatraju Mahalakshmi Rao   +5 more
doaj   +1 more source

Deep Q-Network for Stochastic Process Environments

, 2023
Reinforcement learning is a powerful approach for training an optimal policy to solve complex problems in a given system. This project aims to demonstrate the application of reinforcement learning in stochastic process environments with missing information, using Flappy Bird and a newly developed stock trading environment as case studies.
openaire   +2 more sources

Copper‐based Materials for Photo and Electrocatalytic Process: Advancing Renewable Energy and Environmental Applications

Advanced Functional Materials, EarlyView.
Cu‐based catalysts as a cornerstone in advancing sustainable energy technologies are fully reviewed in this manuscript, highlighting their potential in photo‐ and electrocatalysis. It includes metallic copper, copper oxides, copper sulfides, copper halide perovskites, copper‐based metal–organic frameworks (MOFs), and covalent organic frameworks (COFs),
Jéssica C. de Almeida, Yanjie Wang, Thais A. Rodrigues, Paulo H. H. Nunes, Vagner R. de Mendonça, Paulo H. E. Falsetti, Leticia V. Savazi, Tao He, Alexandra V. Bardakova, Aida V. Rudakova, Jie Tian, Alexei V. Emeline, Osmando F. Lopes, Antonio Otavio T. Patrocínio, Jia Hong Pan, Caue Ribeiro, Detlef W. Bahnemann   +16 more
wiley   +1 more source