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The model presented by equation 1 (see Methods) delivers a response surface for the experimental design space, consisting of the predicted values of the response y in each point.
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The combination of qualitative and quantitative research methods within the framework of mixed methods delivered a multilayered comprehensive picture of the subject of analysis.
These methods deliver a relatively cold sample molecules, ∼1 K, albeit with a large velocity in the laboratory frame, 100 400 m/s.
Some of these methods deliver a point estimate of the level of illegal fishing, some deliver statistical estimates with confidence intervals, and some deliver upper and lower bounds.
Hence, the results indicate that the regression methods deliver a lower accuracy and greater bias in predicting breeding values than 'BayesB', and are less responsive to the addition of further marker information.
Compared with the fixed feedback rate scheme, the proposed method delivers a better performance without incurring additional feedback bandwidth.
The empirical result that a matched Q matrix model is the best proxy for describing apprentices' underlying cognitive processes while solving each IP task confirmed the expectation that no source and no method is without limitations and that every different source and method delivers a unique contribution within the process of specifying a sounded Q matrix.
For any chosen rejection value for the test statistic, the method delivers a set of candidate modules.
This heuristic method delivers a good estimate of the segmentation (see Fig. 4 (d)), but can be further enhanced.
In conclusion, the model-based mJSW measurement method delivers a more accurate estimation of the in vivo insert thickness from planar radiographs compared with the conventional measurement.
When applied to species interactions, these methods deliver an unprecedented level of insight into ecological networks, making it possible to simultaneously assess thousands of interactions and providing a powerful tool for conservation biology.
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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