The LPJ-DGVM has been extensively validated using various data from atmospheric measurements, active and passive remote sensing data, and flux measurements.
For the derivation of the pressure drop and heat transfer coefficients various data from experimental measurements were used.
Recently, it has become easier to access climate data from satellites, ground measurements, and models from various data centers.
Biased measurements can affect the quality of care from interventions derived from various data collection methods.
In this paper, we first introduce various measurement data types and describe how they feature within an ideal fab-wide control architecture; subsequently, and from a process control point of view, we derive various run-to-run controllers, carry out stability analyses, and analyze control system performance.
Biobank samples are typically annotated with relevant phenotypic information, such as the type of sample (e.g. blood), the age and disease state of the person the sample was taken from and possibly with various measurement data such as glucose level and blood pressure at the time the sample was taken.
Various statistical tests were selected based on the level of data measurement and data distributions (McDaniel et al. 2014; Hair Jr. et al. 2010).
The extracted data were stored as results files containing raw data and various statistical measurements.
The resulting images were analyzed in GenePix Pro 5.1 (Molecular Devices, CA, USA), and the extracted data were stored as results files containing raw data and various statistical measurements.
The analytical solution was compared with the various field measurements including data sets of the US Army Corps of Engineers.
The antiadalimumab ADAb titres did not correlate with the various disease activity measurements (data not shown).
