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On‐Farm Demonstration and Economic Evaluation of an IoT Sensing System for Irrigation Management in South CarolinaNARA Subscribed
Irrigation can strongly influence agricultural productivity and sustainability. While sensor‐based irrigation has the potential to improve yield, reduce input costs and enhance resource‐use efficiency, its adoption in commercial agriculture remains limited. This study evaluated and demonstrated the performance of an IoT soil water monitoring system and the effects of sensor‐based irrigation on crop yield and economic returns i...
Marine energies can reduce carbon emissions, diversify energy supply, and improve energy security worldwide. However, no form of energy generation is without a social and environmental impact, and these impacts can lead to tension and conflict between governments, energy providers, and communities. Understanding heterogeneity in public preferences towards marine energy is critical to formulating appropriate policies and target...
Tide gauges have been critical sources for sea level research, enabling the development of tidal theory and an understanding of local variations that occur across the global oceans. Tides play important roles in a variety of oceanographic and geodetic applications, and characterizing their spatial variability is valuable for applications ranging from fishing to flood risk management. This manuscript presents the coastal charac...
The first confirmed observations of wild spawning behaviour in the tropical Gulf Damselfish Pristotis obtusirostris were recorded within the temperate Port Stephens estuary, south‐eastern Australia. In 2025, large aggregations occurred at two sites, with males guarding adhesive eggs within defined nesting areas containing densities of up to 1.1 nests per m 2 and dozens of nests per site. During nesting, males displayed reprodu...
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...