Both the methodology and the underlying mathematical framework presented in this paper contribute new capabilities and perspectives at the interface of uncertainty quantification, statistical data analysis, stochastic modeling and associated statistical inverse problems.
The mathematical framework presented here may represent an important tool for the design of future in vitro and in vivo tests, as well as a precedent for future in silico studies on osseointegration and mechanobiology.
The mathematical framework presented in this paper can be an important tool in furthering the understanding of the mechanisms causing compromised healing and can be applied in the design of future fracture healing experiments.
Therefore, it is expected that the mathematical framework presented in this work may form the basis for several future directions of research and not simply be limited to the application of bit-rate transparent detection in optical-network links.
In reality, due to the nature of the problem, the mathematical framework presented here is not meant to be highly precise, but it can be made sufficiently precise with the inclusion of experimental data.
By using the mathematical framework presented in [28], the ETTR can be computed as: text{ETTR} = frac{1}{T}sumlimits_{d(0)=0}^{T-1}minleft{t_{r}:S_{T}(t_{r})=S_{R}(t_{r})right}.
