Results 171 to 180 of about 4,786,586 (290)

Biological effects 26 years after simulated deep-sea mining. [PDF]

Sci Rep, 2019
Simon-Lledó E, Bett BJ, Huvenne VAI, Köser K, Schoening T, Greinert J, Jones DOB.   +6 more
europepmc   +1 more source

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Open-Source Marine Biodiversity Data Quality in the Norwegian Sea Spanning 149 Years: Knowledge Gaps in the Deep-Sea Mining Opening Area. [PDF]

Ecol Evol
Paiba-García LC, Johnsen G, Perrin SW, Bakken T.   +3 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Deep-sea mining and its risks for social-ecological systems: Insights from simulation-based analyses. [PDF]

PLoS One
Alam L, Pradhoshini KP, Flint RA, Sumaila UR.   +3 more
europepmc   +1 more source

A strategy for the conservation of biodiversity on mid-ocean ridges from deep-sea mining. [PDF]

Sci Adv, 2018
Dunn DC, Van Dover CL, Etter RJ, Smith CR, Levin LA, Morato T, Colaço A, Dale AC, Gebruk AV, Gjerde KM, Halpin PN, Howell KL, Johnson D, Perez JAA, Ribeiro MC, Stuckas H, Weaver P, SEMPIA Workshop Participants.   +17 more
europepmc   +1 more source

A Computational Approach for Biomimetic Design of Liver‐On‐A‐Chip

Advanced Intelligent Discovery, EarlyView.
A biomimetic liver‐on‐a‐chip with antiparallel perfusion was designed using COMSOL‐guided simulation to replicate hepatic acinus transport. Full‐scale modelling revealed diffusion‐dominated, length‐dependent nutrient gradients and low‐shear conditions.
Zhenxu Yang, Qiankun Yin, Qingxin Liu, Zhejun Xu, Ye Zhang, Christopher Vega‐Sánchez, Xiaochen Liu, Daniele Vigolo, Jiao Jiao Li, Ken‐Tye Yong   +9 more
wiley   +1 more source

Probabilistic ecological risk assessment for deep-sea mining: A Bayesian network for Chatham Rise, Pacific Ocean. [PDF]

Ecol Appl
Kaikkonen L, Clark MR, Leduc D, Nodder SD, Rowden AA, Bowden DA, Beaumont J, Cummings V.   +7 more
europepmc   +1 more source

Geomorphological evidence of large vertebrates interacting with the seafloor at abyssal depths in a region designated for deep-sea mining. [PDF]

R Soc Open Sci, 2018
Marsh L, Huvenne VAI, Jones DOB.
europepmc   +1 more source

Embedded Morgan Fingerprints for More Efficient Molecular Property Predictions With Machine Learning

Advanced Intelligent Discovery, EarlyView.
High dimensionality of Morgan fingerprints causes overfitting and slow training. Embedded Morgan Fingerprint (eMFP) compresses this encoding while keeping key structural information intact. Tested on five regression models across three databases for HOMO–LUMO gap prediction, eMFP outperforms standard fingerprints, training faster on large, high ...
Emilio Nuñez‐Andrade, Isaac Vidal‐Daza, Rafael Gómez‐Bombarelli, James W. Ryan, Francisco J. Martin‐Martinez   +4 more
wiley   +1 more source