Results 141 to 150 of about 398 (236)

Giant Exfoliation Induced Magnetic Coercivity in Fe3GaTe2

open access: yesAdvanced Electronic Materials, Volume 12, Issue 15, 10 August 2026.
Mechanical exfoliation is shown to transform the van der Waals ferromagnet Fe3GaTe2 from a soft into a hard magnetic system. Reducing thickness drives a crossover to single‐domain behavior, dramatically enhancing in‐plane coercivity to near–permanent‐magnet levels at room temperature.
Lingrui Mei   +8 more
wiley   +1 more source

Brain‐Wide Mapping and Synaptic Localization of C1QL3 Using a Novel Epitope‐Tagged Knock‐In Mouse

open access: yesJournal of Comparative Neurology, Volume 534, Issue 8, August 2026.
C1QL3 is a secreted adhesion molecule that acts as a key regulator of synaptic structure and function. We generated and validated a novel epitope‐tagged knock‐in mouse line (C1ql32HA) in which two hemagglutinin (HA) epitopes were inserted near the N‐terminus of the endogenous C1QL3 protein.
William P. Armstrong IV   +12 more
wiley   +1 more source

Enhancing Agricultural Management With Internet of Things and Deep Learning

open access: yesEngineering Reports, Volume 8, Issue 8, August 2026.
The proposed smart IoT‐based farming framework integrates IoT sensors, machine learning, and intelligent automation for crop recommendation, soil fertility analysis, weed detection, pest detection, and smart irrigation. The system combines real‐time sensor data with AI‐driven decision‐making to improve crop productivity, optimize water and fertilizer ...
Chinmaya Prasad Mohanty   +2 more
wiley   +1 more source

Extension of pole differential current based relaying for bipolar LCC HVDC lines. [PDF]

open access: yesSci Rep
Tiwari RS   +3 more
europepmc   +1 more source

Photovoltaic Power Generation Fault Diagnosis Model Based on Multi‐Source Data Fusion Using Neural Network Algorithms

open access: yesEngineering Reports, Volume 8, Issue 8, August 2026.
This study introduces a multi‐source data fusion framework for PV fault diagnosis that integrates an adaptive CNN with a collaborative data‐feature layer architecture. The model achieves 99.0% accuracy and 98.8% F1‐score, outperforming traditional methods by over 10% and offering a promising solution for reliable PV system monitoring. ABSTRACT Research
Zheng Li   +5 more
wiley   +1 more source

Real‐Time Incremental Learning Artificial Neural Networks Maximum Power Point Tracking With Raspberry Pi‐Based Meteorological Data Acquisition

open access: yesEnergy Science &Engineering, Volume 14, Issue 8, Page 3741-3773, August 2026.
We present a smart solar tracking method using artificial intelligence to improve the efficiency of solar panels. Unlike traditional techniques, our system learns and adapts to changing sunlight conditions, ensuring faster and more reliable power generation for real‐world energy needs.
Rida Amine   +5 more
wiley   +1 more source

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