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Based on graphical examination of the data, a quadratic term for time of day was introduced to model the possible curvilinear association between symptoms and time of day.
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The algorithm is applied on both synthetic and real data, using a quadratic separable kernel TFD.
Then, using the experimental data obtained, a quadratic model was built.
We fit these data by a quadratic line which approximately represents the mean values of log FmsxE/FmsxC.
The paper also introduces a method for characterising the measured aspheric surface by least square fitting the measured data to a quadratic paraboloid function.
The original 22 full factorial design study was further expanded to a central composite design for poloxamer and carbopol, in order to fit the measured data to a quadratic model and to calculate response surfaces.
Regression analysis indicated the good fitness of experimental data to a quadratic polynomial model with the determination coefficient (R2) value of 0.9957 and 0.9929 for As III) and As V).
We thereafter reanalysed our data using a quadratic term for each of the exposure variables to examine potential non-linear associations.
Curve estimation determined that the data fit a quadratic model.
The highest correlation coefficient (R = 0.9906) was obtained by approximating the experimental data with a quadratic equation.
Analysis of the tumour blood flow data using a quadratic polynomial model showed that endostatin-induced changes in tumour blood flow were significantly related to dose at 56 days (Davis et al, submitted).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com