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This paper addresses the issue of the difficulty in obtaining inter-turn fault (ITF) samples in electric motors, specifically in permanent magnet-synchronous motors (PMSMs), where the number of ITF samples in the stator windings is severely lacking compared to healthy samples. To effectively identify these faults, an improved fault diagnosis method based on the combination of a cycle-generative adversarial network (GAN) and a deep autoencoder (DAE) is proposed. In this method, the Cycle GAN is used to expand the collection of fault samples for PMSMs, while the DAE enhances the capability to extract and analyze these fault samples, thus improving the accuracy of fault diagnosis. The experimental results demonstrate that Cycle GAN exhibits an excellent capability to generate ITF fault samples. The proposed method achieves a diagnostic accuracy rate of up to 98.73% for ITF problems.

Pesticide residues in kumquat fruits from China, and the quality and chronic/acute intake risks in Chinese consumers, were assessed using the QuEChERS procedure and UHPLC-MS/MS and GC-MS/MS methods. Our 5-year monitoring and survey showed 90% of the 573 samples of kumquat fruits collected from two main production areas contained one or multiple residual pesticides. Overall, 30 pesticides were detected, including 16 insecticides, 7 fungicides, 5 acaricides, and 2 plant growth modulators, of which 2 pesticides were already banned. Two or more residual pesticides were discovered in 81% of the samples, and pesticide residues in 9.4% of the samples surpassed the MRLs, such as profenofos, bifenthrin, triazophos, avermectin, spirodiclofen, difenoconazole, and methidathion. The major risk factors on the safety of kumquat fruits before 2019 were profenofos, bifenthrin, and triazophos, but their over-standard frequencies significantly declined after 2019, which was credited to the stricter supervision and management policies by local governments. Despite the high detection rates and multi-residue occurrence of pesticides in kumquat fruits, about 81% of the samples were assessed as qualified. Moreover, the accumulative chronic diet risk determined from ADI is very low. To better protect the health of customers, we shall formulate stricter organic phosphorus pesticide control measures and stricter use guidelines, especially for methidathion, triazophos, chlorpyrifos, and profenofos. This study provides potential data for the design of kumquat fruit quality and safety control guidelines and for the reduction in health risks to humans.

MicroRNA160 plays a crucial role in plant development by negatively regulating the auxin response factors (ARFs). In this manuscript, we design an automatic molecule machine (AMM) based on the dual catalytic hairpin assembly (D-CHA) strategy for the signal amplification detection of miRNA160. The detection system contains four hairpin-shaped DNA probes (HP1, HP2, HP3, and HP4). For HP1, the loop is designed to be complementary to miRNA160. A fragment of DNA with the same sequences as miRNA160 is separated into two pieces that are connected at the 3′ end of HP2 and 5′ end of HP3, respectively. In the presence of the target, four HPs are successively dissolved by the first catalytic hairpin assembly (CHA1), forming a four-way DNA junction (F-DJ) that enables the rearrangement of separated DNA fragments at the end of HP2 and HP3 and serving as an integrated target analogue for initiating the second CHA reaction, generating an enhanced fluorescence signal. Assay experiments demonstrate that D-CHA has a better performance compared with traditional CHA, achieving the detection limit as low as 10 pM for miRNA160 as deduced from its corresponding DNA surrogates. Moreover, non-target miRNAs, as well as single-base mutation targets, can be detected. Overall, the D-CHA strategy provides a competitive method for plant miRNAs detection.