An On-Demand TDMA Approach Optimized for Low-Latency IoT Applications.

The never-ending evolution of the Internet of Things ecosystem is reshaping the arena of wireless communications and competing against conventional networking solutions in fields such as battery life, device and deployment cost, coverage, and support for an immense number of devices. Inspired by this phenomenon, this paper presents a novel Medium Access Control protocol utilizing long-range technology, based on a Time Division Multiple Access communication protocol variant, adjusted to make better use of each device's hardware. Focusing on Low Power Wide Area Network applications, this implementation improves data latency and offers amplified performance due to better network awareness and dynamic time slot rescheduling.

Development of a Nanoparticle-based Lateral Flow Strip Biosensor for Visual Detection of Whole Nervous Necrosis Virus Particles.

Effective analysis of pathogens causing human and veterinary diseases demands rapid, specific and sensitive detection methods which can be applied in research laboratory setups and in field for routine diagnosis. Paper lateral flow biosensors (LFBs) have been established as attractive tools for such analytical applications. In the present study a prototype LFB was designed for whole particles (virions) detection of nodavirus or fish nervous necrosis virus.