No abstract

An efficient supercritical fluid extraction (SFE) process with carbon dioxide (SFE-CO(2)) was developed for the extraction of natural vitamin E (V(E)) from wheat germ. Both the pretreatment of extracted wheat germ and extraction conditions were optimized to ensure maximal V(E) yield. The extraction was undertaken at the extracting pressure of 4000-5000 psi, the extracting temperature of 40-45 degrees C, and the carbon dioxide flow rate of 2.0 mL/min for 90 min. An optimized pretreatment of wheat germ was usually necessary with a particle size of 30 mesh and a moisture content of 5.1%. A yield comparison of V(E) and its isomers extracted by supercritical CO(2) with those by conventional solvent extraction suggested that this SFE process was a practical process prospectively superior to conventional solvent extraction to prepare V(E) from wheat germ.

Although intracranial hematoma detection only requires the continuous wave technique of near infrared spectroscopy (NIRS), previous studies have shown that there are still some problems in obtaining very accurate, reliable hematoma detection. Several of the most important limitations of NIR technology for hematoma detection such as the dynamic range of detection, hair absorption, optical contact, layered structure of the head, and depth of detection are reported in this article. A pulsed light source of variable intensity was designed and studied in order to overcome hair absorption and to increase the dynamic range and depth of detection. An adaptive elastic optical probe was made to improve the optical contact and decrease contact noise. A new microcontroller operated portable hematoma detector was developed. Due to the layered structure of the human head, simulation on a layered medium was analyzed experimentally. Model inhomogeneity tests and animal hematoma tests showed the effectiveness of the improved hematoma detector for intracranial hematoma detection.

Natural vitamin E was extracted by supercritical fluid extraction of carbon dioxide (SFE-CO 2 ) from wheat germ. Several SFE-CO 2 parameters, such as extracting pressure, extracting temperature, and flow rate of carbon dioxide were examined as the independent variables of central composite rotate design (CCRD). Through the response surface methodology (RSM), the optimal processing conditions were determined and the quadratic response surfaces were drawn from the mathematical models. The results demonstrated that the extracting pressure, temperature, pressure ϫ ϫ ϫ ϫ ϫ temperature interaction, and flow rate of CO 2 significantly affected the yield of the natural Vitamin E's extraction, while two interactions containing the flow rate of CO 2 had no significant effect on the yield of natural vitamin E. The optimal processing conditions of the extraction of natural vitamin E in wheat germ by SFE-CO 2 were: extracting pressure 5000 PSI, extracting temperature 316 K, and flow rate of carbon dioxide 1.7 ml/min. Optimum value predicted by RSM for the concentration of natural vitamin E was 2307 mg/100g. Close agreement between experimental and predicted values was obtained.

The competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA) method was proposed as a novel variable selection approach to process multivariate calibration. The CARS was first used to select informative variables, and then SPA to refine the variables with minimum redundant information. The proposed method was applied to near-infrared (NIR) reflectance data of nicotine in tobacco lamina and NIR transmission data of active ingredient in pesticide formulation. As a result, fewer but more informative variables were selected by CARS-SPA than by direct CARS. In the system of pesticide formulation, a multiple linear regression (MLR) model using variables selected by CARS-SPA provided a better prediction than the full-range partial least-squares (PLS) model, successive projections algorithm (SPA) model and uninformative variables elimination-successive projections algorithm (UVE-SPA) processed model. The variable subsets selected by CARS-SPA included the spectral ranges with sufficient chemical information, whereas the uninformative variables were hardly selected.