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On the one hand, use of a theory-based classification method helps us to understand the 'why' of how interventions work by implying a set of causal mechanisms attributable to an intervention effect.
This method helps us to obtain a new composition to extend the use of low-cost materials.
The mapping method helps us make an uniform interface between wrapper and an integrator.
This method helps us learn about animals difficult to study in the wild, like the endangered aye-aye.
The results show that this replenishment method helps us to evaluate the influence of missing data and correct the bias caused by missing data.
This method helps us to identify groups of variables (i.e. heavy metals concentrations or other soil or plant parameters) based on the loadings and groups of samples (soil or vegetable species) based on the scores.
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The data analysis method helped us by correlation matrix tool and multiple regression.
This method helped us to estimate deflection ratio as a mathematical function of the main process planning parameters.
This method helped us to identify13 key hub genes as features associated to stage progression in OSCC.
However, the SDvEP method helped us to find a target marker within the intervals supporting QTLGLSchr8a (Table 5).
This method helped us to find more conserved microsyntenic regions between the ancestral Arabidopsis and Prunus genomes and also to delineate the putative evolutionary steps in the microsyntenic regions.
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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