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Not only those interactions are context-dependent and thus cannot be understood by keeping cells in an inappropriate milieu, like that provided by 2D-cultures, but also they follow nonlinear dynamics which make impractical modeling processes with more than two variables.
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RRs and corresponding 95% confidence intervals (CI) were estimated using Cox proportional hazard models processed with STATA (STATA statistical software, Release 7, STATA Corporation, College Station, TX, USA, 2001), after testing the proportional hazards assumption using scaled Schoenfeld residuals (Schoenfeld, 1982).
This model is suitable for modeling Markov process with imperfect sensing.
The main reason is that the fractional derivative is nonlocal, which provides an excellent instrument to model the processes with fractal geometry, hereditary, and non-Markovian properties.
Hence, modeling the process with linear relations is inadequate.
IBVPs appear in mathematical models of processes with sudden changes in their states.
We've also been analyzing digital transformation and how companies can change their business models and processes with emerging digital technology.
There are others, of course, but these usually come to mind when Chief Information Officers, Chief Technology Officers, Chief Digital Officers, consultants and vendors think about how to disrupt business models and processes with digital technology.
Of course it is preferable to implement an authoring system which assists/guides authors in describing model-making processes with our framework.
The final models for each outcome were selected using a sequential model-building process, with model fitness being based on log-likelihood ratio tests.
Both, the sensory signal and the independent noise signals, are modeled by Gaussian processes with unit variance and zero mean.
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