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We illustrated, in a previous work, the feasibility and success of performing model checking and assertions monitors generation of SystemC using a variant of Abstract State Machines (ASM) languages (AsmL).
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The values of agreement between outputs from each monitor generation when assessing mcpm is shown in Table 2.
Alveolar macrophage (AM) function was assessed by monitoring generation of chemiluminescence and production of tumor necrosis factor-alpha and interleukin-1.
Because of the small amounts of substrate obtained from the previous step, mass spectrometry was utilized to monitor generation of the CMP-activated sugar product.
While some studies report no difference between monitor generations [ 14, 19, 21, 23, 25], others urges for caution when comparing data assessed by different monitor generations due to differences in outputs [ 13, 15, 16, 18, 24, 25].
However, perfect agreement is the assumption for researchers using different monitor generations within studies and when comparing results across studies.
The GT1M and the newer monitor generations are initialized and downloaded over a USB interface using the ActiLife software (v. 5.5.5).
With outputs from the GT1M as reference to the other monitor generations, negative relationships were seen for sedentary time, and positive relationships were seen for the higher intensities.
Some authors have suggested applying a correction factor to data obtained by one of the monitor generations to correct for this difference, for mean physical activity (mcpm).
All correlations were highly significant (p < 0.001).Figure 1 illustrates the agreement between the 16 recordings of mean physical activity (mcpm) by the different monitor generations in Bland-Altman plots.
In the SAS method for tyrosine kinases, diverse phenolic fragments are screened using an assay that monitors ADP generation to identify substrates of the kinase.
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