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Polypeptoids represent a significant class of synthetic analogues of natural polypeptides with potential biomimetic applications in materials, catalysis, and pharmaceuticals, but their simple and general synthesis still remains a key challenge. Herein, we demonstrate that Ugi reaction of natural amino acids leads to structurally diverse polypeptoids, including γand δ-, as well as poly(ε-peptoid)s, under mild conditions (open to air, room temperature, and catalyst free). Moreover, this strategy also offers manifold opportunities to introduce functional groups such as fluorescent and clickable alkenes groups into polypeptoids. Such poly(ε-peptoid)s not only exhibit good biocompatibility and antibacterial activity, but perform very effectively as a drugdelivery system. The bacterial inhibition rate of poly(ε-peptoid) was up to 88.8% at concentration of 20 μg mL −1 in comparison to 61.8% of the poly(ε-lysine) control. Overall, this study offers us a general methodology toward facile preparation of polypeptoids for bioapplications.

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An organic dye JY1 bearing a nitro group was designed, synthesized and applied in DSCs. An unusual colour change was observed when the voltage applied to the device was reversed which was accompanied by a five-fold increase in the cell efficiency. We propose that applying a bias enabled the attachment of nitro groups to the TiO(2) surface.

As a source of data continuity between Landsat and SPOT, Sentinel-2 is an Earth observation mission developed by the European Space Agency (ESA), which acquires 13 bands in the visible and near-infrared (VNIR) to shortwave infrared (SWIR) range. In this study, a Sentinel-2A imager was utilized to assess its ability to perform lithological classification in the Shibanjing ophiolite complex in Inner Mongolia, China. Five conventional machine learning methods, including artificial neural network (ANN), k-nearest neighbor (k-NN), maximum likelihood classification (MLC), random forest classifier (RFC), and support vector machine (SVM), were compared in order to find an optimal classifier for lithological mapping. The experiment revealed that the MLC method offered the highest overall accuracy. After that, Sentinel-2A image was compared with common multispectral data ASTER and Landsat-8 OLI (operational land imager) for lithological mapping using the MLC method. The comparison results showed that the Sentinel-2A imagery yielded a classification accuracy of 74.5%, which was 2.5% and 5.08% higher than those of the ASTER and OLI imagery, respectively, indicating that Sentinel-2A imagery is adequate for lithological discrimination, due to its high spectral resolution in the VNIR to SWIR range. Moreover, different data combinations of Sentinel-2A + ASTER + DEM (digital elevation model) and OLI + ASTER + DEM data were tested on lithological mapping using the MLC method. The best mapping result was obtained from Sentinel-2A + ASTER + DEM dataset, demonstrating that OLI can be replaced by Sentinel-2A, which, when combined with ASTER, can achieve sufficient bandpasses for lithological classification.

D-tagatose, a functional sweetener, is commonly transformed from D-galactose by L-arabinose isomerase (L-AI). In this study, a novel type of biocatalyst, L-AI from Lactobacillus fermentum CGMCC2921 displayed on the spore surface of Bacillus subtilis 168, was developed for producing D-tagatose. The anchored L-AI, exhibiting the relatively high bioactivity, suggested that the surface display system using CotX as the anchoring protein was successfully constructed. The stability of the anchored L-AI was significantly improved. Specifically, the consolidation of thermal stability representing 87% of relative activity was retained even at 80 °C for 30 min, which remarkably favored the production of D-tagatose. Under the optimal conditions, the robust spores can convert 75% D-galactose (100 g/L) into D-tagatose after 24 h, and the conversion rate remained at 56% at the third cycle. Therefore, this biocatalysis system, which could express the target enzyme on the food-grade vector, was an alternative method for the value-added production of D-tagatose.