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Figure 5 The initialization phase performance comparison (IEEE 802. 11).
In the first phase, performance of the ML-based parameter generation was assessed.
Subsequently, we provide a phase performance evaluation based on VSE, which includes phase identification, two kinds of phase performance indicators and ranking method.
This second phase performance deterioration was accompanied by an increase in generalised astrocyte reactivity.
The magnitude of the refocused component is not significantly compromised in achieving such ideal phase performance.
The requirements imposed on CEC stationary phase performance are significantly more demanding compared with those for HPLC.
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Again, during the test phase, performances of random and control flies were indistinguishable (Figure 4).
The phasing performance was robust to effective population size, pedigree and data structure, and SNP density.
Ignoring pedigree information had a negligible effect on the phasing performance but did increase computation time in the larger datasets.
Given that phasing accuracy is robust to minor changes in CplusT lengths around the optimum, the opportunity exists for using slightly longer CplusT lengths with minimal loss in phasing performance but major advantages in terms of computation time.
Then the samples were detected with reverse phase high performance liquid chromatography (RP-HPLC) analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com