Perivascular adipose tissue (PVAT), the fat layer surrounding blood vessels, is increasingly recognized as an active regulator of vascular function rather than a passive structural cushion. Yet whether PVAT contains functionally important sympathetic nerves has remained debated, largely because conventional two-dimensional imaging can miss sparse, spatially complex neural structures.

Electric vehicles (EVs) are crucial for sustainable transport, but their environmental benefit depends heavily on when they charge. Charging during periods when the grid relies on fossil fuels can significantly increase their carbon footprint. New research from Multimedia University reveals that "carbon-aware" charging strategies can unlock substantial emission reductions simply by optimizing charging times.

The study, led by Md Sabbir Hossen and Gobbi Ramasamy from Multimedia University, quantifies the real-world carbon emission reduction potential of smart EV charging. Researchers reconstructed hourly residential charging data and combined it with time-varying grid carbon intensity from the Malaysian Peninsula power system. They then evaluated a reinforcement learning-based carbon-aware smart charging strategy, comparing its performance against both uncontrolled charging and an intelligent but carbon-unaware charging approach, all while delivering identical total energy.

The Power of Carbon Awareness

The findings are compelling: while intelligent charging without carbon awareness failed to reduce total carbon emissions, the carbon-aware strategy achieved a statistically significant reduction of approximately 1.62%. This crucial difference comes from proactively shifting charging demand away from periods when grid electricity is most carbon-intensive. Specifically, evening peak hours were found to be approximately 18% more carbon-intensive than off-peak periods, making targeted load shifting highly effective.

Citrus crops are among the world's most familiar fruits, but their genomes have remained difficult to interpret because of ancient hybridization, complex ancestry, and incomplete gene annotation.