V. Tran results 158
· Newest (Page 1/7, per page 25)
Author: V. Tran ×Clear All Filters
Search Results
Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...
Logging intensity alters tree species composition and wood density, but not tree diversity, in lowland forests in VietnamNARA Subscribed
Tropical forests host considerable biodiversity but face degradation from timber extraction (“logging”). We examined how logging intensity affected tree diversity, species composition, community wood density and availability of timber species in a lowland forest in north-central Vietnam. We measured and identified trees in 18 quarter-hectare plots that vary in historical logging intensity. Tree diversity showed no significant...
Global Molecular Taxonomy, Phylogeny and Biogeography of the Clam Genus Corbicula (Bivalvia: Cyrenidae)NARA Subscribed
The Corbicula clams (Bivalvia: Cyrenidae) are an ecologically significant and widespread group of fresh‐ and brackish‐water molluscs, playing a keystone role in aquatic ecosystems. Some species of this genus are subglobal invaders. The taxonomy of Corbicula remains very confusing, which hinders both fundamental and applied research on this genus. A comprehensive revision of the taxonomic structure of this group has been lackin...
A Machine Learning Approach for Improving the Accuracy of Gridded Precipitation With Uncertainty QuantificationNARA Subscribed
The proliferation of gridded precipitation datasets produced through diverse methods has led to user confusion due to discrepancies in values for identical locations and times, underscoring the inherent uncertainty in current precipitation data. However, quantifying this uncertainty remains challenging since most datasets are deterministic and offer no easy mechanism for such quantification. This study proposes a novel machine...