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It has been widely accepted that China is one of the biggest natural gas consumers. Related to the imports of LNG, China stands in a very uncomfortable situation. Most domestic gas reservoirs fall within deep water drive gas reservoirs inordinately, which has entered the production depletion stage. Accurate estimation of SEC recoverable reserves of deep water drive gas reservoirs is of great significance for gas consumption planning and peak shaving. The existing calculation methods of recoverable reserves mainly consist of static methods and dynamic methods. In the early stage of exploration and development, the volumetric method has often been utilized to calculate the recoverable reserves. With the continuous development of gas reservoirs, the main methods for evaluation are dynamic methods, including the successive subtraction of production method, water drive curve method, prediction model method, attenuation curve method, improved virtual curve method, and material balance method for deep gas reservoirs.

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.

Dissipation of imidacloprid (IMI) and its metabolites (urea, olefin, 5-hydroxy, guanidine, 6-chloronicotinic acid) in Chinese prickly ash (CPA) was investigated using QuEChERS combined with UPLC-MS/MS. Good linearity (r2 ≥0.9963), accuracy (recoveries of 71.8–104.3%), precision (relative standard deviations of 0.9–9.4%), and sensitivity (limit of quantification ≤0.05 mg kg−1) were obtained. After application of IMI at dosage of 467 mg a.i. L−1 for three times with interval of 7 d, the dissipation dynamics of IMI in CPA followed first-order kinetics, with half-life of 6.48–7.29 d. IMI was the main compound in CPA, followed by urea and guanidine with small amounts of olefin, 5-hydroxy, and 6-chloronicotinic acid. The terminal residues of total IMI and its metabolites at PHI of 14–21 d were 0.16–7.80 mg kg−1 in fresh CPA and 0.41–10.44 mg kg−1 in dried CPA, with the median processing factor of 3.62. Risk assessment showed the acute (RQa) and chronic dietary risk quotients (RQc) of IMI in CPA were 0.020–0.083% and 0.052–0.334%, respectively. Based on the dietary structures of different genders and ages of Chinese people, the whole dietary risk assessment indicated that RQc was less than 100% for the general population except for 2- to 7-year-old children (RQc of 109.9%), implying the long-term risks of IMI were acceptable to common consumers except for children.

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.