The gerotor tooth profile is crucial for determining hydraulic system performance in automotive engineering. In a new development, researchers from Pusan National University have leveraged conditional generative adversarial networks for machine learning-driven gerotor profile synthesis and optimization. The novel approach has remarkably produced designs that outperform human efforts and lead to 32% more efficient hydraulic pumps, potentially revolutionizing the automotive industry.

This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine for cancer drug delivery. It demonstrates how ML algorithms—including support vector machines, neural networks, and deep learning models—are revolutionizing nanoparticle design, drug release prediction, and personalized therapy planning. The article outlines the complete ML workflow from data acquisition to model interpretation, compares key algorithms, and presents real-world case studies spanning multidrug carrier optimization and cancer diagnostics. While highlighting substantial preclinical advances, the authors identify critical barriers to clinical translation such as data heterogeneity, model opacity, and regulatory challenges. The review concludes with a forward-looking roadmap emphasizing data standardization, explainable AI, and clinical validation to bridge the gap between computational innovation and patient-ready nanomedicine.

In media coverage, individuals’ membership in minority groups, such as their country of origin, is often explicitly mentioned. In contrast, majority membership is usually not highlighted. Does this reflect prejudice against minorities? A study with over 900 participants suggests that it does not. Instead, a fundamental cognitive principle of differentiation drives this pattern: People tend to notice and communicate rare or striking characteristics more readily than common and redundant ones. Artificial intelligence shows the same tendency and even amplifies it. This is reported by a team from the Social Cognition Lab at Ruhr University Bochum, Germany, led by Dr. Anna Schulte in the journal Social Psychological and Personality Science on December 1, 2025.

A monitoring system devised by the University of Cordoba ascertains the flowering stages of each hive, with high precision, exploiting data on bees' behavior

Huaqiao university and ELSPublishing hosts 2025 IEEE the 6th International Conference on Computer, Big Data and Artificial Intelligence (IEEE ICCBD+AI 2025) in Xiamen.

Chinese researchers have taken a fresh look at one of the biggest challenges in precision manufacturing: understanding and controlling the many different errors that affect the accuracy of machine tools. Their review, published in the International Journal of Extreme Manufacturing, explains why these errors are becoming increasingly complex to manage and how new technologies can help.