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EQ.PET filtering was not applied to CT since the method parameters were already optimised for each reconstruction.
The following method parameters were used: injector, 120 °C; column, 60 °C; detector, 120 °C; and current, 150 mV.
Thus, systematic investigations of crucial method parameters were performed by employing well characterized Au nanoparticles (Au-NPs) as a defined model system.
The method parameters were: I pol) of 50 μA, end point and dynamics at 250 mV, maximum rate of 5 mL/min, drift was used as stop criterion, with a stop drift of 15 μL/min.
These method parameters were used throughout the study.
To our knowledge, this is the first time that all SPME/GC-MS method parameters were optimized.
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In the PSO-NTVENN method, parameters are determined by using a sequential neural network approximation.
As with process parameters, the method parameters are the detailed steps of a method attribute, such as the extraction time for sample preparation.
Automated generation of method parameters is needed in benchmarking scenarios where manual or random generation of parameters are not suitable, do not scale or are too costly.
The data reduction software developed here is designed to be flexible and a discussion of the effects of varying method parameters is provided.
The method parameters are usually chosen so that a Runge-Kutta method has appropriate efficiency, order and stability characteristics.
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