Results 211 to 220 of about 2,018,706 (306)

Rapid and Intense Declines of Forest Connectivity in the Amazon Arc of Deforestation Over Four Decades. [PDF]

Glob Chang Biol
Favretto MA, Hirota M.
europepmc   +1 more source

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

Seed dispersal and predation of the African walnut tree, Coula edulis Baill. (Coulaceae): contrasting fates in intact and hunted rainforests. [PDF]

BMC Plant Biol
Kamdem NG, Sonké B, Deblauwe V, Forget P-, Droissart V, Hardy OJ.   +5 more
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Seed Coat Impermeability and Physical Dormancy in Amazonian <i>Mimosa</i> L. Species: Anatomical, Ecophysiological, and Germination Insights. [PDF]

Plants (Basel)
Santos MMD, Martins AGDN, Sousa VFG, Costa JVTA, Silva BMDSE.   +4 more
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Mechanisms and scales in modeling forest responses to changing disturbance regimes. [PDF]

New Phytol
Xu X, Scholl C, Ma Y, Gora E, Uriarte M, Anderegg WRL, Liu Y, Han T, Luo Y, Koven CD, Hansen WD, Morton DC.   +11 more
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Frugivore richness poorly predicts seed dispersal effectiveness under climate change. [PDF]

Sci Rep
Rigacci EDB, Silva WR, Boom MP, Kissling WD.   +3 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source