Inferring network structure with unobservable nodes from time series data.

Network structures play important roles in social, technological, and biological systems. However, the observable nodes and connections in real cases are often incomplete or unavailable due to measurement errors, private protection issues, or other problems. Therefore, inferring the complete network structure is useful for understanding human interactions and complex dynamics.

Synthesis of a novel amphoteric copolymer and its application as a dispersant for coal water slurry preparation.

In this work, a novel amphoteric copolymer named Poly(sodium p-styrenesulfonate--acrylic acid--diallyldimethylammonium chloride) (P(SS--AA--DMDAAC)) was synthesized via free radical polymerization. Afterwards, P(SS--AA--DMDAAC) was explored for use as a dispersant in coal water slurry (CWS) preparation. The structure of P(SS--AA--DMDAAC) was verified by Fourier transform infrared spectroscopy and nuclear magnetic resonance.