Intelligent models are claimed for ATFM as presented in (Weigang et al. 2010).
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Identification of their bioactive components and a dose response relationship study in in vivo model is claimed to use these indigenous sources for pharmaceutical preparations.
Noticeably, the models in [6, 8, 9] were claimed to achieve a very high Pearson correlation above 0.95, and the RMSE lower than 0.3 on the 5-point rating scale or 7 on the 0-100 rating scale, even if the video content features were not considered in the models.
On the basis of protein homology models, it is claimed that another active site phenylalanine, F483, may also play an important role in the interaction with the aromatic moiety of CYP2D6 substrates.
Although application of software-based tools for automatic generation of printable models has been claimed with regard to certain conceptual prototype designs of novel 3D-printed splints, the construction methodology employed and modeling mechanism have not yet been proposed [7, 8].
An important modeling deficiency is claimed to be the use of a mean time scale in the EMST mixing model, which limits the possibilities to model high scalar dissipation rate events.
This Marxian model, which was claimed to be particularly valid for capitalist societies, has met with much criticism.
Once societal costs (all costs including both direct and indirect) were included in the model, it was claimed that treatment of RRMS with IFNβ-1a could provide "substantial" cost savings to society, increasing with treatment duration.
To ensure that we accurately measured time spent on benefit, we did not model those who were claiming benefit in the first wave.
