Subdomain Adaptation Capsule Network for Partial Discharge Diagnosis in Gas-Insulated Switchgear.

Deep learning methods, especially convolutional neural networks (CNNs), have achieved good results in the partial discharge (PD) diagnosis of gas-insulated switchgear (GIS) in the laboratory. However, the relationship of features ignored in CNNs and the heavy dependance on the amount of sample data make it difficult for the model developed in the laboratory to achieve high-precision, robust diagnosis of PD in the field. To solve these problems, a subdomain adaptation capsule network (SACN) is adopted for PD diagnosis in GIS. First, the feature information is effectively extracted by using a capsule network, which improves feature representation. Then, subdomain adaptation transfer learning is used to accomplish high diagnosis performance on the field data, which alleviates the confusion of different subdomains and matches the local distribution at the subdomain level. Experimental results demonstrate that the accuracy of the SACN in this study reaches 93.75% on the field data. The SACN has better performance than traditional deep learning methods, indicating that the SACN has potential application value in PD diagnosis of GIS.

A sensitive ratiometric fluorescent chemosensor for visual and wearable mercury (II) recognition in river prawn and water samples.

A novel ratiometric fluorescent probe p-RPT was prepared with triphenylamine and a rhodamine derivative. The probe displays high sensitivity and selectivity for Hg2+, which was applied in real water sample detection and biologic cell imaging. Hydrogel-coated paper sensors were fabricated with p-RPT, which displayed fluorescent colour change upon Hg2+ ion contact with a detection limit of 1.2 × 10-8 M (∼10 ppb). In addition, flexible fluorescent p-RPT gloves were developed for visible and wearable Hg2+ detection and applied to detect mercury (II) in river prawn samples. In summary, the p-RPT probe not only shows great potential in mercury (II) detection for food and water, but also provides a new perspective for wearable sensing apparatus.

Molecular characterization of an alanine-, proline-, glycine-, threonine-, and serine-rich protein of the hard tick Haemaphysalis qinghaiensis and its effect as a vaccine against tick infestation in sheep.

An immunological tick control approach has been proved to be the most promising alternative strategy compared to the current usage of acaricides that suffers from a number of serious limitations. The success of this method is mainly dependent on the identification of tick antigen candidates. Here, the complete sequence of a positive clone Hq15 that we screened from a cDNA library of Haemaphysalis qinghaiensis was cloned by using rapid amplification of cDNA ends. Hq15 contains an open reading frame (ORF) of 1851 bp that codes for 616 amino acid residues with a coding capacity of 61 kDa. The deduced Hq15 amino acid sequence was characterized by a high content of alanine (13.80%), proline (12.82%), glycine (12.18%), threonine (10.71%), and serine (10.06%). Sequence similarity and phylogenetic analyses indicated that Hq15 might encode a novel protein of the tick. Expression analysis by reverse transcription polymerase chain reaction indicated that the gene was expressed in every developmental stage of the tick in its salivary glands, but not in the midgut. The cDNA was expressed as glutathione S-transferase-fused protein in a prokaryotic system. Vaccination of sheep with rHq15 conferred a significant protective immunity in sheep, resulting in a reduction of the amount of eggs laid by each tick compared to the controls. These results show that rHq15 might be one of the candidate vaccine molecules for the control of ticks.