Results 221 to 230 of about 814,546 (308)

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Modification of the existing maximum residue level for dodine in grapes. [PDF]

EFSA J
European Food Safety Authority (EFSA), Bellisai G, Bernasconi G, Carrasco Cabrera L, Castellan I, Del Aguila M, Ferreira L, Greco L, Leuschner R, Mioč A, Nave S, Reich H, Ruocco S, Scarlato AP, Szot M, Theobald A, Tiramani M, Verani A, Zioga E.   +18 more
europepmc   +1 more source

Techno‐Economic and Life Cycle Assessment of a Nanofluid‐Based Concentrated PV/T–TEG Hybrid System With Spectral Filtering

Energy Science &Engineering, EarlyView.
A novel cascade nanofluid‐based PV/T–TEG hybrid system (CS4) achieves 81.1% thermal and 18.75% exergy efficiency while cutting CO₂ emissions by 7.8 tons year⁻¹. The system delivers superior energy performance, economic savings, and environmental benefits, offering a sustainable pathway for next‐generation solar energy applications.
Abdelhak Lekbir, Samir Hassani, Saad Mekhilef, Kok Soon Tey, Abdullahi Mohamed Samatar   +4 more
wiley   +1 more source

Modification of the existing maximum residue levels for tebufenozide in tree nuts. [PDF]

EFSA J
EFSA (European Food Safety Authority), Bellisai G, Bernasconi G, Carrasco Cabrera L, Castellan I, Del Aguila M, Ferreira L, Greco L, Leuschner R, Mioč A, Nave S, Reich H, Ruocco S, Scarlato AP, Szot M, Theobald A, Tiramani M, Verani A, Zioga E.   +18 more
europepmc   +1 more source

Development of the Human–Equine Attachment Scale

Equine Veterinary Journal, EarlyView.
Abstract Background Human–horse relationships encompass diverse roles, from companion to competition partner. The impact of such bonds informs owner decision‐making regarding horse management and veterinary care, yet standardised instruments to measure these unique bonds are limited.
Richard H. Corrigan, Marc Pierard, Emma Davies, David Marlin, Stephanie Evans, Jane M. Williams   +5 more
wiley   +1 more source

Caught in the fire: An accidental ethnography of discomfort in researching sex work

Feminist Anthropology, EarlyView.
Abstract Drawing on fifteen years of engagement with researching Israel's sex industry, this article uses accidental ethnography to propose discomfort‐as‐method for feminist anthropology. I argue that discomfort is not a by‐product of fieldwork but a constitutive condition that disciplines researchers and shapes what can be known.
Yeela Lahav‐Raz
wiley   +1 more source

Understanding Privatisation of Mental Health Services: Insights From Karl Marx's Capital. [PDF]

J Psychiatr Ment Health Nurs
Balfe M.
europepmc   +1 more source

When Are Statistical Forecast Gains Economically Relevant? Evidence From Bitcoin Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study how statistical forecast gains for Bitcoin translate into trading profits. Using real‐time out‐of‐sample forecasts from daily bivariate VARs from October 2021 to February 2024, we show that Bitcoin returns are forecastable and that seven predictive indices yield significant gains in directional accuracy (DA).
Rehan Arain, Stephen Snudden
wiley   +1 more source

Does geopolitical risks drive the extreme spillovers of bulk energy and chemical commodity. [PDF]

PLoS One
Tao Z, Li T, Chen Y, Huang X.
europepmc   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source