RESUMO
Partial least square (PLS) combining with Raman spectroscopy was applied to develop predictive models for plasma paclitaxel concentration detection. In this experiment, 312 samples were scanned by Raman spectroscopy. High performance liquid chromatography (HPLC) was applied to determine the paclitaxel concentration in 312 rat plasma samples. Monte Carlo partial least square (MCPLS) method was successfully performed to identify the outliers and the numbers of calibration set. Based on the values of degree of approach ( ), moving window partial least square (MWPLS) was used to choose the suitable preprocessing method, optimum wavelength variables and the number of latent variables. The correlation coefficients between reference values and predictive values in both calibration set ( ) and validation set ( ) of optimum PLS model were 0.933 1 and 0.926 4, respectively. Furthermore, an independent verification test was performed on the prediction model. The results showed that the correlation error of the 20 validation samples was 9.36%±2.03%, which confirmed the well predictive ability of established PLS quantitative analysis model.
RESUMO
This paper demonstrates the successful application of a novel approach to the computer aided design (CAD) of removable partial denture (RPD) framework. Firstly, we get the data of the partially edentulous cast, a mandibular Kennedy Class II, through a 3D-optical grating measuring system after corresponding pretreatment. Then, the reverse engineering software and 3D CAD software was used to design basis, big conjunction, clasp, small conjunction of the RPD framework. Finally 3D surface model of the RPD framework was created in preparation for direct manufacture using rapid prototyping (RP) methods and foundry. The result indicated that the RPD framework was fabricated successfully and the resulting frameworks provided a satisfactory fit.
