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The study used the implementing of a new curriculum as an intervention (quasi-experimental) and therefore we had to accept the low target population and the resulting low number of participants, which was limited by the given number of eligible students.
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We used the implemented L-BFGS algorithm to optimize the Softmax regression objective function [31] for these datasets.
We used the implemented version in the "lmer" function from the "lme4" R-package [ 34].
For the GO analysis, we used the implemented statistical features of Expander 4.0 with an adjusted p-value < 0.05.
Using the implemented models, a numerical study was carried out.
Urine excretion data were modeled using the implemented dynamic voiding bladder module [11] in OLINDA/EXM.
Skull stripping was performed by using the implemented algorithm on MATLAB software.
Using the implemented function, we executed automatic verification test cases after applying CentOS 6 patches for 12 user virtual machines.
The structures were analyzed using the implemented GoldScore fitness function to identify the most accurate simulation.
We batch-processed all 1000 term sets automatically using the implemented system.
Acceptor bleaching was accomplished with a TCS SP5 using the implemented FRET acceptor bleaching wizard.
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