Improvement of NIR prediction ability by dual model optimization in fusion of NSIA and SA methods.

Feature selection and sample partitioning are both important to establish a quantitative analytical model for near-infrared (NIR) spectroscopy. The classical interval partial least squares (iPLS) model for waveband selection can be improved in combination of the simulated annealing (SA) algorithm. The sample set partitioning based on a joint x-y distance (SPXY) method for sample partitioning is based on the distances of both the x- and y- dimensions; it is expected to be optimized using the non-dominant sorting strategies (NS) combined with the immune algorithm (IA). In this study, we investigated the dual model optimization mode for simultaneous selection of feature waveband and sample partitioning, and proposed a novel method defined as SA-iPLS & SPXY-NSIA. The method explores a population evolution process, and takes the candidate individual as the link for the fusion optimization of SA-iPLS and SPXY-NSIA. The method screens feature wavebands and observes a good partition of the modeling samples, to construct a combined optimization strategy for fusion optimization of the target waveband and suitable sets of sample partitioning. The performance of the SA-iPLS & SPXY-NSIA method was tested using a soil sample dataset. To prove model enhancement, the proposed method was compared to the two traditional methods of Kennard-Stone (KS) and SPXY in combination with SA-iPLS. Experimental results show that the fusion model established by SA-iPLS & SPXY-NSIA performed better than the KS-SA-iPLS and SPXY-SA-iPLS models. The best testing results of the fusion model is with RMSET, RPDT and RT observed as 0.0107, 1.7233 and 0.9097, respectively. The proposed method is prospectively able to effectively improve the predictive ability of the NIR analytical model.

A hybrid optimization method for sample partitioning in near-infrared analysis.

The division of calibration and validation is one of the essential procedures that affect the prediction result of the calibration model in quantitative analysis of near-infrared (NIR) spectroscopy. The conventional methods are Kennard-Stone (KS) and sample set partitioning based on joint x-y distances (SPXY). These algorithms use Euclidean distance to cover as many representative samples as possible. This paper proposes an Adaptive Hybrid Cuckoo-Tabu Search (AHCTS) algorithm for partitioning samples based on optimization. The algorithm combines the characteristics of cuckoo search (CS) and tabu search (TS) and fuses with an adaptive function. For comparison, using fishmeal samples as spectral analysis data, KS, SPXY, and AHCTS algorithms were used to divide the modeling samples to establish partial least squares regression (PLSR) models. The experimental results showed that the model established by the proposed algorithm performs better than KS and SPXY. It reveals that the AHCTS method may be an advantageous alternative for quantitative analysis of NIR spectroscopy.

Glycopolymers Made from Polyrotaxanes Terminated with Bile Acids: Preparation, Self-Assembly, and Targeting Delivery.

The use of natural compounds to construct biomaterials, including delivery system, is an attractive strategy. In the present study, through threading functional α-cyclodextrins onto the conjugated macromolecules of poly(ethylene glycol) (PEG) and natural compound bile acid, glycopolymers of polyrotaxanes with the active targeting ability are obtained. These glycopolymers self-assemble into micelles as evidenced by dynamic light scattering and transmission electron microscopy, in which glucosamine, as an example of targeting groups, is introduced. These micelles after loading doxorubicin (DOX) exhibit the selective recognition with cancer cells 4T1. Meanwhile, the maximal half inhibitory concentration is determined to be ≈2.5 mg L-1 for the DOX-loaded micelles, close to the value of free DOX·HCl (1.9 mg L-1 ). The cumulative release of DOX at pH 5.5 is faster than at pH 7.4, which may be used as the controlled release system. This drug delivery system assembled by glycopolymers features high drug loading of DOX, superior biocompatibility. The strategy not only utilizes the micellization induced by bile acids, but also overcomes the major limitation of PEG such as the lack of targeting groups. In particular, this drug delivery platform can extend to grafting the other targeting groups, rendering this system more versatile.