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After the first 2.5 years, we began recording simulated procedures separately.
Avoiding the necessity of performing in vitro and in vivo procedures separately.
Therefore, we applied the similarity reduction procedures separately to the set of binders and non-binders in each dataset.
To reduce the computational cost, most of the existing models addressed the feature selection and parameter optimization procedures separately.
As the aim of the present work is to find if we could obtain a similar rank of genes irrespective of the Petunia line, growth conditions or sample processing, we developed all the data mining procedures separately for each line.
Regression models looking at hospital admissions and surgical procedures separately (figures 1 and 5), illustrate that admissions are increasing at 3.5 times the rate of surgical interventions (β values of 7.63 vs 2.18, respectively).
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We implement this procedure separately for each of the 18 manufacturing industries available in our dataset.
We run the IPWRA procedure separately by country and gender for any outcome we consider.
We initially carried out a paired t-test to study activations in the premonitory phase > baseline, in the nausea group, and then carried out the same procedure separately for the no-nausea group.
To determine the expected return value of this random choice, we implemented the following procedure separately for each of the 33 test years, following Lakonishok et al. (1994): For April of each of the 5 years postportfolio formation, the market value of stocks for which monthly return is available for April of the given year is extracted from CRSP.
One can simply apply the similarity reduction procedure separately to data from each class.
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