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The reasons invoked were the limited availability of independent data, the need to remove contributions from other sources than the core prior to comparing measured data with candidate models, and the absence of measurements during the time interval of the secular variation candidates.
PLS analysis maximizes the product of variance matrix of measured variables (e.g. lipid profile data) and correlation of measured data with properties of interest (e.g. ob/ob and WT groups).
Results show that the measurements were very repeatable, producing results that compare favorably with measured data with an uncertainty of approximately 10%.
Measured data with their error-bars are supplemented with both the non-Markovian as well as Markovian predictions in the spirit of the insets.
The models demonstrated an excellent fitting to the measured data with coefficient of determination varied between 0.987 and 0.999.
The ANN prediction was in good agreement with the measured data with an absolute average deviation of 6.46%.
The results show that the Paulson Gibbins fits well with measured data with a low RMS error of 0.2 dB.
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Assuming users opt-in and allow first-party pixel usage, advertisers are able to track and measure data with very few limitations.
Measured data obtained with the catheter are in good agreement with the theoretical prediction of the simulation.
However, performing realtime imaging with resource-intensive algorithm on a large amount of measured data confronts with a technical challenge.
Both the numerical analysis and measured data agree with the nodal simulation results.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com