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Aiming at the difficulty of extracting radio fingerprint feature caused by insufficient traditional training method under small labeled sample prerequisite, the deep autoencoders regularized by marginal Fisher analysis algorithm for radio fingerprint extraction is proposed. Based on deep autoencoders, the training procedures was divided into two parts: unsupervised pre-training and supervised finetuning based on marginal Fisher analysis. In the algorithm, firstly the individual information of radio classes in large amounts of unlabeled signal samples was extracted, whose information was then applied on model optimal parameters learning by deep autoencoders. Then the trainable parameters were analyzed by marginal Fisher method with the assistant of labeled samples to improve the discriminant capability of fingerprint feature between radio individuals of the same model. The classification experiment was operated on several communication radio signal dataset. The results proved that the differences of radio individuals of the same model can be represented effectively through the algorithm proposed.

The development of high-performance nickel-zinc (Ni-Zn) alkaline batteries is mainly plagued by short life span and poor rate performance of ZnO anode materials. To improve the cycling stability and rate capability of Ni-Zn batteries, carbon dots (CDs) are employed to construct clustered ZnO-CDs nanocomposites, coating ZnO with protective shells of carbon layers and providing electron paths to enhance conductivity of the nanocomposites. Univalent zinc species are found at the interfaces between CDs derivatives and ZnO, which are embedded in the nanoclusters and protected well by carbon coating. Theoretical calculations show univalent zinc species change the electronic structures of ZnO surface, so as to accelerate the charging process of ZnO anode materials. Such ZnO-CDs derived nanocomposites exhibit excellent rate capability (95.3%, 84.7% and 75.0% of capacity retention rate at 2, 5 and 10 A g−1, respectively) and outstanding cycling stability with 92.0% of capacity retention rate after 5000 cycles, which is far better than ZnO based anodes without the protection of CDs (39.1% retention rate from 1 to 10 A g−1 and 71.6% of capacity retention rate after 500 cycles).

The corrosion behavior of the new Ni–Cr–Fe base superalloy GH984G in a synthetic coal ash and flue gas environments was studied at 700 °C. The results showed that the corrosion rate was slow during the initial corrosion stage, then followed by a stage of faster mass loss. During the corrosion test, the scale trended to spall slightly, resulting in the formation of corrosion pits on the sample surfaces. The main corrosion products were identified as NiFeCrO4 and a small amount of Cr2O3. The scale microstructure involved the presence of three corrosion layers. The outer layer contained Cr, Ni, Fe, O and a small amount of S. Many micro-cracks were detected in the Cr-rich intermediate oxide layer. The inner corrosion layer was thin and rich in S. Internal sulfidation and internal oxidation occurred in the substrate. Because of its relatively high Cr content, the GH984G superalloy exhibited a good corrosion resistance under the test conditions.

The binding mechanism of Hematoxylin-Zn(II) complex with Herring sperm DNA has been investigated using UV–vis and fluorescence spectroscopies and viscosity measurement. With the increase in the concentration of complex, the viscosity of DNA decreased, and the binding mode is more detailed: there is partially intercalate binding. Furthermore, besides the intercalate binding, the existence of groove binding was confirmed through the ionic strength experiment in Scatchard analysis. Thermodynamic studies provided some thermodynamic parameters: ΔrHmΘ = 1.43 × 105 J mol−1, ΔrSmΘ = 576.14 J mol−1, ΔrGmΘ303K = −3.16 × 104 J mol−1, they illustrated that the binding mechanism between HE-Zn(II) complex and hsDNA was driven mainly by entropy.

Correction for ‘Mechanistic study on NO reduction by sludge reburning in a pilot scale cement precalciner with different CO2 concentrations’ by Xiang Xiao et al., RSC Adv., 2019, 9, 22863–22874.