Learning Politics From Social Media: Interconnection of Social Media Use for Political News and Political Issue and Process Knowledge

Drawing on a national survey of 1,157 South Korean adults, the present study finds that social media use for political news is positively associated with knowledge about political issues, but not with knowledge about political processes. Professional media use for political news is significantly associated with both political issue knowledge and political process knowledge. The impact of social media for news on political issue knowledge increases with the additive role of professional media news use. This study also finds that political talk strengthens the positive association between social media use for news and political issue knowledge.     

Synchronization of discrete-time complex dynamical networks with interval time-varying delays via non-fragile controller with randomly occurring perturbation

This paper addresses synchronization problem for discrete-time complex dynamical networks with interval time-varying delays. In order to achieve the synchronization, a feedback controller subjected to randomly occurring perturbations will be considered. The randomly occurring perturbations are assumed to belong to the Binomial sequence. By constructing a suitable Lyapunov–Krasovskii functional, and utilizing reciprocally convex approach and Finsler?s lemma, the synchronization criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. The networks are represented by the use of Kronecker product technique. The effectiveness of the proposed methods will be verified via numerical examples.     

Programmed sample delivery on a pressurized paper

This paper reports a method to control the fluid flow in paper-based microfluidic devices simply by pressing over the channel surface of paper, thereby decreasing the pore size and permeability of a non-woven polypropylene sheet. As a result, fluid resistance is increased in the pressed region and causes flow rate to decrease. We characterize the decrease of flow rate with respect to different amounts of pressure applied, and up to 740% decrease in flow velocity was achieved. In addition, we demonstrate flow rate control in a Y-shaped merging paper and sequential delivery of multiple color dyes in a three-branched paper. Furthermore, sequential delivery of multiple fluid samples is performed to demonstrate its application in multi-step colorimetric immunoassay, which shows a 4.3-fold signal increase via enhancement step.     

Stabilizability of complex complex-valued memristive neural networks using non-fragile sampled-data control

This paper investigates the stability and stabilizability of complex-valued memristive neural networks (CVMNNs) with random time-varying delays via non-fragile sampled-data control. Taking the influence of gain fluctuations into account, a non-fragile sampled-data controller is designed for CVMNNs. Compared with the existing control schemes, the one here is more applicable and can effectively save the communication resources. The assumption on activation functions of CVMNNs is relaxed by only needing the complex-valued activation functions satisfying the Lipschitz condition. By constructing a suitable Lyapunov–Krasovskii functional (LKF), new stability and stabilizability criteria are derived for CVMNNs. Different from the existing results with the maximum absolute values of memristive connection weights, our ones are based on the average values of the maximum and minimum of the memristive connection weights. Finally, numerical simulations are given to validate the effectiveness of the theoretical results.