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Everwet tropical forests, defined by the absence of a pronounced dry season, are globally significant carbon sinks, covering roughly 80% of Southeast Asian tropical forests, 30% of the Amazon basin, and 10% of the Congo Basin. Yet the climatic drivers of stem radial growth in these ecosystems remain understudied. The prevailing hypothesis is that growth is primarily light‐limited, as persistent cloud cover constrains photosynt...
Monitoring evapotranspiration to link agricultural water use with crop yield at sub-field scalesNARA Subscribed
Purpose Scientists and producers have pursued precision agriculture to increase yields and limit environmental impacts. Applying precision agriculture concepts has not been straightforward, however, because complex interactions between soil and weather govern crop growth. We hypothesize that evapotranspiration (ET) is a single metric that captures interactions between plant status, soil, topography, and weather and can be used...
Predictive validation of the repeated low-dose reserpine rodent model of parkinsonismNARA Subscribed
L-DOPA (LD) is the gold-standard treatment of motor symptoms in Parkinson’s disease (PD), conventionally used to prove the predictive value of PD animal models. This study aimed to investigate the predictive validity of an adaptation of the conventional reserpine model of PD: the repeated low-dose reserpine administration in rodents, which promotes progressive motor impairment in catalepsy, vacuous chewing behavior tests, and...
A machine learning framework for California vineyard water status monitoring using sUAS Imagery and short-term meteorological dataNARA Subscribed
Efficient irrigation management is essential for sustainable crop production under increasing temperatures and tightening water supplies. In vineyards, water status significantly influences vine growth, yield, and fruit quality, and deficit irrigation is often used to impose controlled stress while avoiding damaging levels of water limitation. This creates a practical need for routine, field-scale monitoring of vine water stat...
Understanding future changes in cumulative water deficit (CWD) is essential for assessing the vulnerability of Amazonian ecosystems to climate change. This study evaluates the performance of CMIP6 models in simulating CWD in the southwestern Amazon from 1985 to 2024 and projects future changes through 2100 under three emission scenarios (SSP1‐2.6, SSP3‐7.0, SSP5‐8.5). CWD was calculated using a fixed evapotranspiration thresho...
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...
Background Despite important advancements in diagnostic modalities, routine use of therapeutic drug monitoring (TDM) and newer antifungal therapies, there is a paucity of contemporary data regarding clinical characteristics and outcomes of invasive aspergillosis (IA) in the United States. Methods Single-center, retrospective cohort study of hospitalized patients between 2015 and 2020, who had active hematological malignancy (H...
Larval Genomics as a Viable, Fisheries‐Independent Tool for Investigating Population Structure in Tropical Pacific TunasNARA Subscribed
Understanding how dispersal, life history, and environmental variability shape genetic connectivity in the open ocean remains a central challenge in evolutionary biology. Highly migratory marine predators like tunas have traditionally been considered genetically homogeneous across ocean basins, yet emerging genomic evidence suggests that cryptic population structure can persist even in species with high gene flow and large eff...