Due to the features of mixture method and to the proper ratios of four independent variables, the optimal points were in the range of temperature (37 °C), pressure (24.3 25.0 MPa), dynamic time (19 24 min) and modifier volume (100 200 μl).
Khayati et al. [60, 61] proposed an automated method for segmentation of MS lesions in brain MRI images using an adaptive mixture method and a Markov random field model in 3-D MRI images.
We also compare the time consumption of our mixture method and the original parsimony method.
Generally, solubility profile of SESDs of ARTM was agreed with data of XRD, FTIR, DSC, and SEM, which indicated that both procedures such as physical mixture method and freeze-dried method improved the solubility profile of ARTM.
The dissolution profile of SESDs of ARTM agreed with data of XRD, FTIR, DSC, and SEM, which indicated that both procedures such as physical mixture method and freeze-dried method improved the dissolution profile of ARTM.
Si wafers were cleaned prior to spin coating by heating to 80 °C in the hydrogen peroxide ammonium water mixture for 15 min, followed by dilution with Millipore water, 15 min ultrasonication in hydrochloric acid water mixture method, and dilution with Millipore water.
Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIXobs), based on the likelihood of the concentration data (MIXconc), or combined likelihood of observed covariate data and concentration data (MIXjoint).
We applied both the CLR and Dirichlet mixture methods described above to 8 different hierarchical mixing models.
For the mixture methods, no correlation was observed between pmix and θmale.
In the situation of non-random missingness, DROP and EXTRA methods showed less bias than the mixture methods.
