Dr. Sahely Bhadra, "Large-Scale Sparse Kernel Canonical Correlation Analysis",

Neha A S, "Security in AI"

Abstract: In the age of fluctuating renewable energy production and consumption using wind, hydroelectric and solar energy, the need for energy storage becomes a very important matter to guarantee energy whenever and wherever needed independent of wind and sunshine conditions. Both chemical and electrical energy storage needs to be further developed to fully exploit the renewables and thus to contain the global warming and CO2 emissions arising out of fossil fuel consumption.

Reinforcement learning (RL) is a sub-area of machine learning to solve control tasks such as self-driving, learning to playing Chess or Go. RL algorithms need to balance exploration (finding new ways) as well as  exploitation (sticking to old ways that have worked).

Based on a detailed study of the bacterial Shiga toxin we discuss the membrane mediated interactions between membrane inclusions. Shiga toxin interacts with its cellular receptor, the glycosphingolipid globotriaosylceramide (Gb3 or CD77), as a first step to entering target cells. This is followed by clustering of the Shiga Toxin-receptor complexes at the membrane and tubular invagination into the cytoplasm of the cell.