A recent study has revealed the intricate dynamics of submesoscale eddies (SEs) in the South China Sea, harnessing cutting-edge satellite technology to uncover their critical role in oceanic processes.

A recent study by Concordia University researchers reveals that social media platforms are highly susceptible to manipulation by relatively simple AI techniques. By employing reinforcement learning and systems theory, the researchers demonstrated how bots can be strategically placed to exploit platform algorithms, intensifying polarization with minimal intervention. The study aims to enhance detection mechanisms and raise awareness among policymakers and tech companies about the vulnerabilities inherent in current social media infrastructures.​

Natasha D. Sheybani, PhD, is exploring the potential of focused ultrasound to improve the effectiveness and precision of immunotherapy for breast cancer.

A new study from Umeå University has revealed that the trees’ circadian clock guides their growth and the timing of seasonal events like the appearance of leaves in spring. The researchers investigated the growth of genetically modified poplars in greenhouse and field conditions, combining statistical learning and plant biology methods. Their findings suggest that adjusting clock-associated genes could help trees better synchronize with changing climates, offering new opportunities for forestry.

First ever supercomputer simulations of Mars with a fully molten core could explain the Red Planet's unusual magnetic field. Billions of years ago, Mars had an active magnetic field. Mysteriously, its imprint is strongest in the southern hemisphere. Research led by the University of Texas Institute for Geophysics found that Mars could have produced a one-sided magnetic field with a fully molten core, rather than the traditional, Earth-like solid inner core setup.

In the U.S., credit card fraud costs $5 billion annually, identity theft adds $16.4 billion, and Medicare fraud drains $60 billion each year. A new machine learning breakthrough generates accurate fraud labels from large, imbalanced datasets without costly, time-consuming labeled data. It outperforms traditional methods by reducing false positives and minimizing cases needing further inspection, crucial for sectors like Medicare and credit card fraud, where fast data processing is vital to preventing losses and improving efficiency.