Low Power Ternary State Channel Computing-in-Memory Transistor for Federated Learning.

Federated learning is a communication collaborative learning architecture that protects personal privacy. Utilization of the ternary weight changes can efficiently reduce the communication workload and energy consumption of federated learning, which is beyond the realization of most single transistors. Here, we demonstrate a ternary state channel computing-in-memory transistor that can generate three conductivity states at a minimum ternary voltage of 5 mV for low-power computing and can distinguish the direction of weight changes for federated learning.

Biochemical characterization and antifungal activity of a recombinant β-1,3-glucanase FlGluA from Flavobacterium sp. NAU1659.

β-1,3-glucanases can degrade β-1,3-glucoside bonds in β-glucan which is the main cell-wall component of most of fungi, and have the crucial application potential in plant protection and food processing. Herein, a β-1,3-glucanase FlGluA from Flavobacterium sp. NAU1659 composed of 333 amino acids with a predicted molecular mass of 36.