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These models can prove especially useful in fields where concepts are often difficult to spatially comprehend from a two-dimension (2D) image.
The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors.
The proposed models can prove useful for assessing the road safety performance of the examined countries, as well as for obtaining some insight on the current and future trends of less developed countries.
Mathematical models can prove to be useful in testing the impact of varying reaction conditions upon a chemical system, with a significant time and cost saving compared to experimentation.
This is where computational models can prove handy as they have shown to be able to reproduce enough biological complexity to be of use in suggesting new experiments [ 3, 4].
However, it is not only in the area of meat cookery that predictive cooking models can prove useful; the whole area of gels and gelation (under what conditions will the diverse range of food-approved gelling agents actually form gels, what properties will these gels have, and how stable will they remain) is another area that is ripe for development of a detailed set of models.
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Kinetic modeling can prove to be a powerful tool in the analysis of many systems.
The model can prove useful to optimize design factors of an electrolyzer cell for future use in that it provides clear tendencies for electrolyte conductivity from combinations of pressure, current density and electrolyte width among others.
In an existing company, the introduction of a new business model can prove challenging because of a cultural mismatch, the ability of existing businesses to influence budgets, or other reasons that start-ups do not face.
We do not claim, however, that our statistical model can prove or confirm human-to-human transmission, as Uyeki and Bresee state.
The ability to conduct mechanistic studies with the same data generated for the model can prove itself valuable in later stages of development.
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