Results 161 to 170 of about 7,455 (227)

Inter‐Material Transfer Learning for Accelerated Nanofluid Heat Transfer Prediction: A Machine Learning Approach for Energy Systems

Energy Science &Engineering, EarlyView.
This study presents an inter‐material transfer learning framework for nanofluid heat transfer prediction in energy systems. By leveraging knowledge from Al2O3‐water data, the model accurately predicts hybrid Al2O3‐TiO2 nanofluid performance with only 20 simulations, achieving R2 = 0.985 and reducing computational requirements by 78. ABSTRACT This paper
Soumaya Hadj Salah, Aymen Ochi, Sonia Bezi   +2 more
wiley   +1 more source

Two-Stage Double-Arm Trial Optimal Design of Restricted Mean Survival Time With Sculpted Critical Region. [PDF]

Stat Med
He J, Lin R, Chen Y, Lam KF.
europepmc   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

Energy 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, Jamal Dabbagh, Jhila Nasiri Reveshti, Karim Farajeyan Bonab, Farid Hosseini Mansoub   +4 more
wiley   +1 more source

Kidney Function, Alzheimer Disease Blood Biomarkers, and Dementia Risk in Community-Dwelling Older Adults. [PDF]

Neurology
Gasparini F, Valletta M, Vetrano DL, Beridze G, Rizzuto D, Calderón-Larrañaga A, Fredolini C, Dale M, Winblad B, Fratiglioni L, Grande G.   +10 more
europepmc   +1 more source

Legacy effects of locally extinct flagship species on protected areas

Frontiers in Ecology and the Environment, EarlyView.
Protected areas (PAs) are often established to conserve flagship megafauna so as to mobilize political support and secure sustained conservation investment, with the expectation that flagship‐centered governance will also protect habitat. Despite such efforts, flagship species can experience extirpation, raising a fundamental question: do conservation ...
Rachakonda Sreekar, James EM Watson, Jiajia Liu, Aakash Lamba, Hoong Chen Teo, Jun Ying Lim, Yiwen Zeng   +6 more
wiley   +1 more source

Sector-specific Long-term Associations Between Transportation, Industrial, and Residential Combustion Air Pollutant Mixtures (PM_2.5, SO₂, NO₂, O₃) and Neurological Disease-related Mortality in Canada. [PDF]

Environ Epidemiol
Mitchell K, Hebbern C, Ferro A, Olaniyan T, Christidis T, Cakmak JD, Rouleau M, Anastasopolos AT, Popadic I, Johnson M, Zhao N, Tjepkema M, Cakmak S.   +12 more
europepmc   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

A Revised Bimodal Generalized Extreme Value Distribution: Theory and Climate Data Application. [PDF]

Entropy (Basel)
Otiniano CEG, Lisboa MNS, Ribeiro TKA.
europepmc   +1 more source

Threshold Asymmetric Conditional Autoregressive Range (TACARR) Model

Journal of Forecasting, EarlyView.
ABSTRACT This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed ...
Isuru Ratnayake, V. A. Samaranayake
wiley   +1 more source

Association of prognostic nutritional index with all-cause and CVD mortality in hypertensive individuals. [PDF]

Sci Rep
Liu W, Liu Y, Guo X, Cao C, Weng S, Peng D.   +5 more
europepmc   +1 more source