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to explore and describe how healthcare professionals in the Southern Region of Denmark experienced motivational interviewing as a communication method when working with pregnant women with obesity.
A detailed analysis of the artifacts caused by different types of errors in the analysis and synthesis stages could be useful to improve the performance of the method when working in difficult acoustic environments.
However, for anything more than the most trivial networks, a greater calculation effort is required for this method when working manually.
For statistical analyses bootstrapping (10000 resamplings each, 2-sided t-test, routine "FTBOOT "from the package„ computer intensive statistics") was used as a well proven method when working with a relatively low number of samples and high variances [51].
It is important to test the performance of the method when working with sequences of poorly known taxa since many metagenomes could be enriched in these rare taxa.
It is particularly advantageous to use this method when working in species with poorly characterized genomes, since variation in miR sequences between species has become apparent [ 27, 29, 30].
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Unsupervised methods are very useful to find hidden structures in the unlabeled data and are often used as precursor to supervised methods when working on huge data sets.
Being GIPS-compliant can actually make things easier for firms that are trying to compete in multiple markets, because they have to abide by only one set of standards and they can avoid having to make major changes in their presentation or calculation methods when working in other countries.
In Figure 5 we show the accuracy of the sparse representation and SVM methods when working with DPPS encoding for different IC 50 cutoff values.
Several methods for RNA amplification are available; however, there has been little consideration of the accuracy of these methods when working with very low-input quantities of RNA as is often required with rare clinical samples.
This power-sharing approach is consistent with decolonizing methods when working across cultures and goes some way to addressing the dilemma of a researcher from a different cultural background interpreting existing data on 'behalf' of others.
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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