Results 221 to 230 of about 2,433,577 (353)

Declines of ebony and ivory are inextricably linked in an African rainforest. [PDF]

Sci Adv
Deblauwe V, Luskin MS, Assola SD, Hardy OJ, Jansen S, Loubières C, Mempong GG, Ntsihe JM, Oum Ndjock G, Onguene Kwecheu ER, Powell LL, Sonké B, Sonké B, Smith TB.   +13 more
europepmc   +1 more source

Interacting effects of forest fragmentation and howler monkey foraging on germination and disperal of fig seeds

Oryx, 2002
J. C. Serio‐Silva, V. Rico‐Gray
semanticscholar   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Identification and Classification of Snack-Type Watermelon (<i>Citrullus lanatus</i>) Genotypes Using Seed Morphology and Machine Learning Techniques. [PDF]

Foods
Ercan U, Ermiş S, Kabas O, Öktem G, Kabas A, Paraschiv G.   +5 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

Effects of exogenous proline on rice seedling germination and physiological and biochemical characteristics under stress from different Cr(VI) concentrations. [PDF]

Sci Rep
Zhang Q, Tang L, Wang X, Lin Y, Feng Y, Huang J.   +5 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

Potential Sustainability and Stress Resilience of Forest Trees Induced by Nanotechnology Applications. [PDF]

Plant Environ Interact
Siam AMJ, Abu-Zurayk R, Abdelkheir RM, Siam N, Shibli R, Sawwan J.   +5 more
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source