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Interactions between these factors and their optimal levels were investigated using a two level factorial design.
Interactions between analytical factors and their optimized levels were investigated using a central composite design.
Interactions between analytical factors and their optimal levels were investigated using two level factorial and Box Behnken designs.
Interactions, between analytical factors and their optimised levels were investigated using full factorial, Plackett Burman and central composite designs.
Protein levels were investigated using immunoblots to quantify levels of proteins and indirect immunohistochemistry to define the distribution of protein.
The trends of rainfall and temperature at station and regional levels were investigated using Mann-Kendall (MK) and Regional Kendall (RK) tests, respectively (Helsel and Frans 2006).
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Moreover, uncertainty propagation at different load levels is investigated using nonlinear incremental dynamic analysis (NIDA).
The impact of mean sea level rise (SLR) on extreme water levels is investigated using a numerical model that covers the entire North Sea, but has its highest spatial resolution in the northern part of the German Bight.
Second, the variation in economic disparity at both the national and regional levels is investigated using three indexes: the weighted coefficient of variation, the Theil index and the Gini index.
The diagnostic value of EA levels was investigated using ROC curve analysis.
The association of circulating blood glucose levels with corresponding lactate levels was investigated using a linear regression model.
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