[Using GA-dOSC method to eliminate interference of peel with prediction of apple firmness based on near infrared diffuse reflection spectra].

In the present work, "Fuji" apples from Shandong Yantai were used to take the diffuse reflection spectra by FT-NIR PLS components (i.e., factors) were computed by nonlinear iterative partial least squares (NIPALS) and the number of latent factors (LV) was optimized by a leave-one-out cross-validation procedure on the calibration set. On the basis of partial least square (PLS) regression, the models for apples' firmness before and after peeling were compared. In order to eliminate the effect of apple peel on prediction, spectral pretreatments such as multiplicative scatter correction (MSC), derivative, direct orthogonal signal correction (DOSC) and wavelengths selection based on genetic algorithms (GA) were used. Finally, the results of different spectral treatments were compared. In conclusion, the RSDp of models for apples before and after peeling was 16.71% and 12.36%, respectively, suggesting that the apple peel played a negative role in constructing good predictive models. Moreover, the traditional spectral pretreatments (such as MSC, derivative) can hardly resolve the problem. In this research, GA-DOSC played an important role in reducing the interference of apple peel. It not only reduced the wavelength variables from 1480 to 36, but also reduced the latent variables from 5 to 1. The correlation coefficient (r) was improved from 0.753 to 0.805, and the RMSECV and RMESP were reduced from 1.019 kgf x cm(-2) and 1.197 kgf x cm(-2) to 0.919 kgf x cm(-2) and 0.924 kgf x cm(-2), respectively. Especially, the RSDp was decreased remarkably from 16.71% to 12.89%. The performance of the model after GA-DOSC treatment was similar to the model using spectra of apple flesh (12.36%). It was concluded that the prediction precision based on GA-DOSC satisfied the requirement of NIR non-destruction determination of apples firmness.

Hyperbranched Polymer Functionalized Carbon Dots with Multistimuli-Responsive Property.

The pyrolysis of a hyperbranched polyethylenimine (PEI) and glycerol mixture under microwaves generated the carbon dot (CD) functionalized with PEI (CD-PEI). Isobutyric amide (IBAm) groups were attached to CD-PEI through the amidation reaction of isobutyric anhydride and the PEI moiety, which resulted in the thermoresponsive CD-PEI-IBAm's. CD-PEI-IBAm's were not only thermoresponsive but also responded to other stimuli, including inorganic salt, pH, and loaded organic guests. The cloud point temperature (Tcp) of the aqueous solutions of CD-PEI-IBAm's could be modulated in a broad range through changing the number of IBAm units of CD-PEI-IBAm or varying the type and concentration of the inorganic salts, pH, and loaded organic guests. All the obtained CD-PEI-IBAm's were photoluminescent, which could be influenced a little or negligibly by the added salts, pH, and the organic guests encapsulated.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.