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Three different preprocessing algorithms, namely orthogonal signal correction (OSC), standard normal variate transformation (SNV) and multiplicative scatter correction (MSC), were applied in order to eliminate effects caused by sample preparation and sample inhomogeneities.
Through comparison we unveil that both changes in the band structure resulting from a different sample thickness and the disorder induced by sample preparation and graphene/substrate interface are responsible for the MR behavior in the thickness variation.
This can be justified by sample preparation and electrospinning conditions.
XAS spectral quality mostly reflects the lead concentration in a given sample, but also is affected by sample preparation and presentation, and differences in experimental setup (e.g., detector, beam line, and beam condition).
These noise sources include mechanical noise that caused by the instrument settings, electronic noise from the fluctuation in an electronic signal and travel distance of the signal, chemical noise that is influenced by sample preparation and sample contamination, temperature in the flight tube and software signal read errors.
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Therefore, stable heavy isotope-labeled standards (stds) are commonly spiked into unknown samples to correct the error introduced by sample preparations and MS response fluctuations.
The results from these techniques are limited by sample preparation constraints and a large area (or number) of an intact plant part cannot be studied.
Intra-assay precision was monitored by repeated sample preparation and analysis by the same operator.
The present findings provide fundamental insight into the reliability analysis on the metallic nanowire mesh hindered by difficult sample preparation and experimental measurement, which will be helpful to develop ideal metallic nanowire mesh-based TCE with considerable reliability.
For example, by optimizing sample preparation and measurement conditions, Keshishian et al. [ 13] used MRM and achieved limits of quantification (LO Qs in the low nanogram per milliliter range without the need for antibody-based enrichment.
In order to correct many types of systemic bias created by sample preparation, amplification, sequencing (or hybridization), and alignment, it uses both a ChIP sample and a negative control sample (input DNA or mock-ChIP with IGG) to compute FDR at each specific location.
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by bowel preparation and
by sample storage and
by sample size and
by sample means and
by sample origin and
by slide preparation and
by sample selection and
by cytospin preparation and
by sample molecule and
by sample type and
by sample history and
by seafood preparation and
by sample amount and
by sample handling and
by sample entropy and
by sample basis and
by sample batch and
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