Results 211 to 220 of about 520,035 (296)

A Comprehensive Review of AI‐Powered Energy Systems

open access: yesEnergy Science &Engineering, EarlyView.
The role of Artificial Intelligence (AI) in developing next‐generation energy systems is getting more day by day. Therefore, incorporating AI enables real‐time decision‐making and advanced grid management, which are essential for optimizing the use of intermittent renewable sources like wind and solar power.
Armin Razmjoo   +5 more
wiley   +1 more source

Genome sequence of <i>Cysteiniphilum</i> sp. GTC20157 isolated from coastal seawater in Osaka, Japan. [PDF]

open access: yesMicrobiol Resour Announc
Hayashi M   +7 more
europepmc   +1 more source

Thermal Analysis of Cells Behavior in Modular Lithium Iron Phosphate Battery System in Urban Electric Bus Fleet

open access: yesEnergy Science &Engineering, EarlyView.
Real‐world analysis of lithium iron phosphate battery systems in electric buses shows minimal short‐term temperature impact on energy but significant long‐term degradation at higher temperatures. Efficient cooling and thermal uniformity are critical to prevent accelerated aging, maintain performance, and ensure safety under dynamic operating conditions.
Wiktoria Kaczmarek   +4 more
wiley   +1 more source

Complete genome sequence of <i>Cellulomonas</i> sp. GTC 20042 isolated from human bile. [PDF]

open access: yesMicrobiol Resour Announc
Yonetamari J   +4 more
europepmc   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

open access: yesEnergy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif   +5 more
wiley   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

open access: yesEnergy Science &Engineering, EarlyView.
A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti   +4 more
wiley   +1 more source

Efficacy of Liposomal Bupivacaine in Third Molar Extraction: A Systematic Review and Meta-Analysis. [PDF]

open access: yesCureus
Aljumaiaan M   +9 more
europepmc   +1 more source

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