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In this paper, we construct both first order and uniformly high order accurate conservative Lagrangian schemes which preserve positivity of physically positive variables such as density and internal energy in the simulation of compressible multi-material flows with general equations of state (EOS).
The findings show that each and every year the positive variables – trust and liking – improve.
By means of variable transformation, the GGP problem with non-positive variables can be equivalently solved with another one having positive variables.
However, the use of logarithmic/exponential transformations restricts these methods to handle the problems with strictly positive variables.
Second optimization step was performed using fractional factorial design in order to optimize the amounts of highest positive variables that had significant effect on levansucrase productivity.
Although some exponential-based decomposition methods have been developed for GGP problems, these methods can only handle problems with positive variables.
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NaNO3 concentration was the most significant positive variable while methanol was not a significant variable.
In what follows we give certain generalizations of some notions for a positive valued function of a positive variable.
Because negative values are impossible for such a variable, its distribution is necessarily asymmetric (right panel: example of a strictly positive variable characterized by a large SD).
ϑ and (vartheta_{s}) denote elements in (mathbb {T}) whereas θ and (theta_{s}) represent functions of the real positive variable with values in (mathbb {T}).
Therefore, given a n × p data matrix X and an integer positive variable k, we may define xi,j, 0 ≤ i < n, and 0 ≤ j < p as follow.
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CEO of Professional Science Editing for Scientists @ prosciediting.com