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Recently, although many researchers commit themselves to modeling giant magnetostrictive actuators, there is still lack of simplified model of analyzing nonlinear properties to deal with the problems on active vibration control with giant magnetostrictive actuators.
Many of the current approaches for identifying relevant genes associated with survival phenotypes using microarray data focus on trimming or extending a Cox regression model [ 7], a commonly used model of analyzing survival data in traditional clinical settings.
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This holistic model consists of analyzing one's unique constitution and recommending supportive lifestyle modifications.
The adopted model consists of analyzing separately the behavior and the damage evolutions.
The approach involves two models capable of analyzing geometries that include inelastic materials.
The simplest of such models consists of analyzing two or more genetically distinct tumor clones grown in coculture under different environmental constraints.
However, in a mouse model of sepsis, analyzing spleen NK cells, we recently showed that TGF-β, more than IL-10, was the deactivating cytokine [ 55].
Figure 1 Conceptual model for analyzing the effect of prenatal care on birth weight.
The objective of this paper is to construct a class of models for analyzing data in initiation-promotion (IP) studies.
Recent articles [ 29, 30] on sample size calculations emphasize the superiority of ANCOVA models for analyzing the results of randomized, controlled trials over the repeated-measures ANOVA approach.
In this article, we have demonstrated the utility of PSG RNA-Seq models for analyzing AP of gene transcripts.
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