A research paper by scientists at the Beijing Institute of Technology proposed a brain–machine hybrid intelligent system for sound target detection (STD), featuring a neuroanatomy-informed EEG decoding network and an adaptive confidence-based fusion strategy to address poor robustness and limited generalization of existing methods under low signal-to-noise ratio (SNR) conditions or with unseen target classes.

Harvard engineers, as part of Project CETI, have built an open-source bio-logger that adheres to sperm whales and records high-fidelity, multi-channel audio plus rich behavioral and environmental data. The data are tailored for machine learning analysis so that researchers can better understand whale communication.

Extracellular vesicles serve as essential mediators of communication between immune cells and tumor cells, and the recent advances in artificial induction strategies offer an adaptable and efficient platform for engineering extracellular vesicles, enabling their application as next-generation strategies in cancer immunotherapy.