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Wildfire susceptibility can be assessed using various models, which range from conventional regressions to more recently developed machine-learning models.
Model quality can be assessed using various techniques, like geometric or energetic criteria derived from known protein structures.
Website engagement and retention will be assessed using various website statistics, self-reported internet self-efficacy and website usability.
The effects of genotoxic substances on ecosystems should be assessed using various test systems with multiple genetic end points.
Homoeologous gene expression in polyploids can be assessed using various SNP-based assays [ 16], expression and genotyping arrays [ 30, 31] or next-generation sequencing technologies [ 32, 33].
In addition, the effects of gene knockdown can be assessed using various loss-of-function mutants, and researchers recently developed a new method of generating loss-of-function mutations in targeted genes in C. elegans [ 2].
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The limitations of generalized all-purpose commercial software, as well as the subtleties of numerical computer simulation of induction-hardening processes, are assessed using various case studies as examples.
The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000.
Using a recently developed fMRI technique that acquires vascular space occupancy (VASO), arterial spin labeling (ASL) perfusion and blood oxygenation level-dependent (BOLD) signals simultaneously, the additivity property of the three hemodynamic responses in human visual cortex was assessed using various visual stimulus durations.
The hepatoprotective activity was assessed using various biochemical parameters such as liver marker enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP)) and oxidative stress parameters.
Overall model fit was assessed using various global fit indices, where the following indices and fit values were used as criteria to assess acceptable model fit: Chi-square test of overall model fit; root mean square error of approximation (RMSEA) <0.06 (MacCallum et al. 1996); and Tucker Lewis index (TLI) and the comparative fit index (CFI) >0.90 (Hu and Bentler 1999).
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