Results 251 to 260 of about 14,302 (309)

Exploring Curvature Effects in Direct‐Written 3D Curved Hollow Magnetic Nanoshells

Advanced Functional Materials, EarlyView.
Fabricated by a hybrid FEBID/CVD method, 3D PtC/Co3Fe core–shell heterostructures with engineered curvature and shell thickness exhibit complex reversal modes with axially symmetric N'eel‐type domain walls. XMCD‐PEEM combined with full‐scale micromagnetic simulations reveal how curvature and thickness govern the domain wall energy landscape and shape ...
Oleksii M. Volkov, Fabrizio Porrati, Florian Kronast, Riccardo Hertel, Pavlo Makushko, Olha Bezsmertna, Alexander Kuprava, Mohamad‐Assaad Mawass, Sven Barth, Michael Huth, Denys Makarov   +10 more
wiley   +1 more source

A physics-guided machine learning framework for enhancing dust storm visibility prediction in arid and semi-arid regions. [PDF]

Sci Rep
Xu C, Zhang H, Luo K, Liu J, Shen Y, Qin H, Qu Y, Zhu C, Han Z.   +8 more
europepmc   +1 more source

IN4MER Biomaterial Ink: A Phosphorescent Biosensing Biomaterial Ink for Multiple Analytes (Glucose, Lactate, Oxygen) Measurements and Temperature Sensing Applications

Advanced Functional Materials, EarlyView.
Multianalyte, real‐time monitoring of bioprinted scaffolds remains challenging. Phosphorescence‐lifetime–based, optically responsive microparticles are embedded in diverse printable hydrogels (κ‐carrageenan, GelMA, PEGDA) to form biomaterial inks that report oxygen, glucose, lactate, and temperature.
Waqas Saleem, David Chimene, Berkley P. White, Kaivalya A. Deo, Jeremy L. Thomas, Nithin Chidambara, Cole Mandrona, Kirsten Landsgaard, Brian Ko, Roland Kaunas, Akhilesh K. Gaharwar, Michael J. McShane   +11 more
wiley   +1 more source

SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction. [PDF]

Sci Data
Roy S, Hegde DV, Schmude J, Lal R, Gaur V, Lin A, Mandal K, Singh T, Muñoz-Jaramillo A, Yang K, Pandey C, Hong J, Aydin B, McGranaghan R, Kasapis S, Upendran V, Bahauddin S, da Silva D, Freitag M, Gurung I, Pogorelov N, Watson C, Maskey M, Bernabe-Moreno J, Ramachandran R.   +24 more
europepmc   +1 more source

UniEload: Electrical load dataset for energy forecasting applications at public universities in Bangladesh. [PDF]

Data Brief
Sutradhar U, Biswas P, Hossain S, Islam ATMS, Dev S.   +4 more
europepmc   +1 more source

A multi-component hybrid model for renewable energy integrated grid power load forecasting: DWT, SAE, and FA-LSTM. [PDF]

Sci Rep
Peng S, Zhu J.
europepmc   +1 more source

Predicting Algal Bloom Dynamics in Drinking Water Reservoirs Using High-Frequency In Situ Data and Machine Learning. [PDF]

Toxins (Basel)
Wang J, Jiang M, Wang S, Wang Z, Cui Y, Feng Y, Zhang S, Cai M, Zhong Y.   +8 more
europepmc   +1 more source

Maximum dispatchable capacity evaluation of a VPP with hybrid wind-solar-gas-storage systems. [PDF]

Sci Rep
Zhang C, Li D, Li C.
europepmc   +1 more source

Hydrological dataset on mediterranean catchments of the real collobrier observatory for 1967-2024. [PDF]

Data Brief
Folton N, Arnaud P, Tolsa M.
europepmc   +1 more source

An AI-Based Hybrid Forecasting Model for Wind Speed Forecasting

, 2017
Forecasting of wind speed plays an important role in wind power prediction for management of wind energy. Due to intermittent nature of wind, accurately forecasting of wind speed has been a long standing research challenge. Artificial neural networks (ANNs) is one of promising approaches to predict wind speed.
Haiyan Lu, Jiani Heng, Chen Wang
openaire   +2 more sources