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The programming interfaces between components are well defined and narrow.
Both components are well known since the 1950s and have shown remarkable staying power.
It is shown that the Lorentz-Lorenz model is the most appropriate for the given mixture, suggesting components are well mixed and there are no separated phases.
As the most important cultural practices for cotton production, the single effects of plant density and [nitrogen (N) and potassium (K)] fertilization on yield and yield components are well documented but their combined effects on Bt cotton are poorly understood.
While the first two components are well identified and easy to work out, the implementation of the last ones is problematic as the investor must identify all the relevant state variables and estimate their distribution characteristics.
In many cases the technologies required to manufacture these components are well established, in others there is still ongoing design and R&D work to select and optimise the final design solutions and to consolidate the underlying technologies as, for example, in the areas of heating and current drive, plasma diagnostics, shield blanket and first wall, remote handling, etc.
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Our experimental results also show that bimetallic PtMo/C catalysts are apparently inherently unstable and suffer from the gradual loss of Mo due to its dissolution into the electrolyte, regardless of whether the components are well-mixed or present in the segregated phases.
These components are well-resolved and could be approximated by three Lorentz contours.
The postulate is especially worrying when applied to entangled compound systems whose components are well-separated in space.
Given our economic setup, these two components are well-captured by the following decomposition of per capita income growth12 begin{aligned} (Y/N _{text {gr}}=underbrace{left( frac{alpha }{1-alpha }K/Yright) _{text {gr}}+(L/W)_{text {gr}}}_{textit{Productivity component}}+underbrace{(W)_{text {gr}}- N _{text {gr}}- N _{textTranslation component}}+A_{gr}t {gr}}.
One goal of our study was to evaluate whether simulation results from a spatial stochastic model would differ significantly from a deterministic solution that assume all components are well-mixed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com