Different technologies have been developed to help parents and caregivers address pediatric vehicular heatstroke (PVH), or scenarios where a child dies from overheating in an unattended motor vehicle. In a new study, researchers identified exemplar PVH scenarios that have occurred during recent years and studied the different technologies designed to prevent them from occurring. The study found that while certain technologies may be effective for different scenarios, no single technology is effective in preventing all the scenarios that lead to pediatric vehicular heatstroke, suggesting a combination of interventions is required to achieve the best prevention strategy.

A research team leverages chlorophyll fluorescence (ChlF) imaging, a cutting-edge technique, to identify reliable pre-symptomatic diagnostic indicators for rice blast and brown spot.

A research team has developed an innovative remote sensing model that significantly improves the accuracy of monitoring nitrogen accumulation in wheat crops.

A research team now proposes a novel Multi-Granularity Alignment (MGA) domain adaptation framework that dramatically improves cross-domain detection accuracy, enabling deep learning models to maintain high performance across datasets collected in different countries and conditions.

A research team pioneers an automated, high-throughput pipeline using open-source tools to quantify over 50 root traits in diverse maize genotypes, enabling researchers to investigate how genetics, hormones, and developmental stages influence root growth.