Uncertainty Quantification in Molecular Signals Using Polynomial Chaos Expansion

@article{Abbaszadeh2018UncertaintyQI,
  title={Uncertainty Quantification in Molecular Signals Using Polynomial Chaos Expansion},
  author={Mahmoud Abbaszadeh and Giannis Moutsinas and Peter J. Thomas and Weisi Guo},
  journal={IEEE Transactions on Molecular, Biological and Multi-Scale Communications},
  year={2018},
  volume={4},
  pages={248-256}
}
Molecular signals are abundant in engineering and biological contexts, and undergo stochastic propagation in fluid dynamic channels. The received signal is sensitive to a variety of input and channel parameter variations. Currently we do not understand how uncertainty or noise in a variety of parameters affect the received signal concentration, and nor do we have an analytical framework to tackle this challenge. In this paper we utilize Polynomial Chaos Expansion (PCE) to show that uncertainty… 

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TURBULENT DIFFUSION

Almost all flows encountered by the engineer in the natural or built environment are turbulent, resulting in rapid mixing of contaminants introduced into them. Despite many years of intensive