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We found good correlation between methods when comparing fold-change from ESC to NSC (r = 0.730, Pearson).
We will, of course, use patient risk-adjustment methods when comparing your team's performance to other teams' data.
We also demonstrated the importance of rigorous quantitative analysis methods when comparing ChIP-seq results across conditions.
Thus, targeted sequencing offers a savings of ∼80% over traditional Sanger methods when comparing the amount of data.
Moreover, our analysis found no effect from differing study methods when comparing 2 pairs of studies performed in the same populations.
No differences were found between the subset of patients analysed using the different methods when comparing tumour and patient characteristics or survival.
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Numerical results show favorable properties of expK methods when compared to current exponential schemes.
Numerical results show the practicality and advantages of our new methods when compared with typical methods in the literature.
An uncertain LTI power system model is adopted as an illustrated example to demonstrate the efficacy of the proposed methods when compared to other methods from the literature.
Moreover, the suggested methods when compared with other controllers in the literature show great success in overcoming the external disturbance and the change of parameters.
Performance, correctness, code flexibility, and implementation time have been analyzed to gauge the success and applicability of these methods when compared to the traditional multi-CPU approach.
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