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Arc fault in the three-phase load circuit may cause fire, resulting in production interruption and even worse, it will cause casualties. In order to effectively detect the arc fault in the three-phase circuit, series arc fault experiments of three-phase motor load and frequency converter were carried out under different current conditions. Firstly, variational mode decomposition (VMD) was performed for each cycle of A-phase current, and then the VMD energy entropy and sample entropy were calculated. Secondly, the noise-dominated component was removed according to the permutation entropy, then the average value after first-order difference of the half-cycle reconstructed signal was obtained. An arc fault diagnosis model of extreme learning machine (ELM) optimized by sparrow search algorithm (SSA) was established. The feature vectors were divided into training group and test group to train the model and test its fault diagnosis accuracy. Compared with GA-ELM, PSO-ELM, support vector machine (SVM) and SSA-SVM, the experimental results show that the proposed method can identify the series arc fault accurately and more quickly.

Ocean currents make it difficult for unmanned surface vehicles (USVs) to keep a safe distance from obstacles. Effective path planning should adequately consider the effect of ocean currents on USVs. This paper proposes an improved A* algorithm based on an artificial potential field (APF) for USV path planning in a current environment. There are three main improvements to the A* algorithm. Firstly, the proposed algorithm ignores unnecessary perilous nodes to decrease calculation. Secondly, an adaptive guidance angle is developed to guide the search in the most appropriate direction to reduce the computing time. Thirdly, the potential field force function is introduced into the cost function to ensure that the path designed for the USV always maintains a safe distance from obstacles under the influence of ocean currents. Furthermore, the Bezier curve is adapted to smooth the path. The experimental results show that the USV path-planning algorithm proposed in this paper, which synthesizes the APF and A* algorithms, runs 22.5% faster on average than the traditional A* algorithm. Additionally, the path developed by the proposed A* algorithm effectively keeps appropriate and different distances from obstacles by considering different ocean currents.

Background High intensity interval training (HIIT) has been reported to exert better effects on cardiovascular fitness in obesity, but little known about the arterial stiffness (AS) in female university students with normal weight obesity (NWO). Thus, this study aimed to investigate the effects of HIIT on the body composition, heart rate (HR), blood pressure (BP), blood lipids metabolism as well as the novel parameters of propensity for AS (arterial velocity pulse index [AVI], arterial pressure volume index [API]) for female university students with NWO. Methods Forty female university students with NWO were randomly assigned to control group ( n  = 20) and HIIT group (3 bouts of 9‑min intervals at 90% of the maximal heart rate [HR max ], interspersed by 1 min rest, 5 days a week, n  = 20). Tests were performed before and after 4 weeks of training. Repeated measures ANOVA and simple effect test analysis were used to analyze dependent variable changes. Results After 4 weeks HIIT statistically significantly improved the body composition by decreasing the body mass index, body fat percent, total body fat mass (BFM), BFM of left arm, measured circumference of left arm, and obesity degree, and increasing the total body skeletal muscle mass, protein content, total body water, fat free mass, body cell mas, and InBody score. HIIT also statistically significantly decreased the HR and BP. As for the lipid profile, HIIT obviously ameliorated the blood lipids metabolism by decreasing the levels of total cholesterol (TC), triglyceride, low-density lipoprotein, and TC/HDL, and increasing the levels of high-density lipoprotein (HDL). In addition, the AVI and API were markedly decreased via HIIT intervention. Conclusions HIIT produced significant and meaningful benefits for body composition, HR, BP, and blood lipids metabolism, and could decrease AS in female university students with NWO. This suggests that HIIT may effectively reduce the risk of arteriosclerosis and protect the cardiovascular function for female university students with NWO. Trial registration ChiCTR2100050711. Registered 3 September 2021. Retrospectively registered.

Seed size traits, including seed length (SL), seed width (SW), and seed thickness (ST), are crucial appearance parameters that determine soybean seed weight, yield, and ultimate utilization. However, there is still a large gap in the understanding of the genetic mechanism of these traits. Here, 281 soybeans were utilized to analyze the genetic architecture of seed size traits in different years through multiple (single-locus and multi-locus) genome-wide association study (GWAS) models, and candidate genes were predicted by integrating information on gene function and transcriptome sequencing data. As a result, two, seven, and three stable quantitative trait nucleotides (QTNs) controlling SL, SW, and ST were detected in multiple environments using the single-locus GWAS model, and concurrently detected by the results of the multi-locus GWAS models. These stable QTNs are located on 10 linkage disequilibrium blocks, with single genome regions ranging in size from 20 to 440 kb, and can serve as the major loci controlling soybean seed size. Furthermore, by combining gene functional annotation and transcriptome sequencing data of seeds at different developmental stages from two extreme soybean accessions, nine candidate genes, including Glyma.05G038000, Glyma.05G244100, Glyma.05G246900, Glyma.07G070200, Glyma.11G010000, Glyma.11G012400, Glyma.17G165500, Glyma.17G166500, and Glyma.20G012600 within the major loci that may regulate soybean seed size, were mined. Overall, these findings offer valuable insights for molecular improvement breeding as well as gene functional studies to unravel the mechanism of soybean seed size.

With the rapid emergence and distribution of red crown rot (RCR) across countries, durable sources of resistance against Calonectria ilicicola in soybean [Glycine max (L.) Merrill] is required to control the disease. We employed two RIL populations for the experiment. We identified 15 and 14 QTLs associated with RCR resistance in ZM6 and MN populations, respectively, totaling 29 QTLs. Six and eight QTLs had phenotypic variation above 10% in ZM6 and MN populations, respectively. We identified six (6) “QTL hotspots” for resistance to RCR from the ZM6 and MN RIL populations on chromosomes 1, 7, 10, 11, 13, and 18. Gene annotations, gene ontology enhancement, and RNA sequencing assessment detected 23 genes located within six “QTL Hotspots” as potential candidate genes that could govern RCR resistance in soybeans. Our data will generally assist breeders in rapidly and effectively incorporating RCR resistance into high-yielding accession through marker-assisted selection.

Red crown rot (RCR) disease caused by Calonectria ilicicola negatively impacts soybean yield and quality. Unfortunately, the knowledge of the genetic architecture of RCR resistance in soybeans is limited. In this study, 299 diverse soybean accessions were used to explore their genetic diversity and resistance to RCR, and to mine for candidate genes via emergence rate (ER), survival rate (SR), and disease severity (DS) by a multi-locus random-SNP-effect mixed linear model of GWAS. All accessions had brown necrotic lesions on the primary root, with five genotypes identified as resistant. Nine single-nucleotide polymorphism (SNP) markers were detected to underlie RCR response (ER, SR, and DS). Two SNPs colocalized with at least two traits to form a haplotype block which possessed nine genes. Based on their annotation and the qRT-PCR, three genes, namely Glyma.08G074600, Glyma.08G074700, and Glyma.12G043600, are suggested to modulate soybean resistance to RCR. The findings from this study could serve as the foundation for breeding RCR-tolerant soybean varieties, and the candidate genes could be validated to deepen our understanding of soybean response to RCR.

The hundred-seed weight (HSW) is an important yield component and one of the principal breeding traits in soybean. More than 250 quantitative trait loci (QTL) for soybean HSW have been identified. However, most of them have a large genomic region or are environmentally sensitive, which provide limited information for improving the phenotype in marker-assisted selection (MAS) and identifying the candidate genes. Here, we utilized 281 soybean accessions with 58,112 single nucleotide polymorphisms (SNPs) to dissect the genetic basis of HSW in across years in the northern Shaanxi province of China through one single-locus (SL) and three multi-locus (ML) genome-wide association study (GWAS) models. As a result, one hundred and fifty-four SNPs were detected to be significantly associated with HSW in at least one environment via SL-GWAS model, and 27 of these 154 SNPs were detected in all (three) environments and located within 7 linkage disequilibrium (LD) block regions with the distance of each block ranged from 40 to 610 Kb. A total of 15 quantitative trait nucleotides (QTNs) were identified by three ML-GWAS models. Combined with the results of different GWAS models, the 7 LD block regions associated with HSW detected by SL-GWAS model could be verified directly or indirectly by the results of ML-GWAS models. Eleven candidate genes underlying the stable loci that may regulate seed weight in soybean were predicted. The significantly associated SNPs and the stable loci as well as predicted candidate genes may be of great importance for marker-assisted breeding, polymerization breeding, and gene discovery for HSW in soybean.

Controlled-source electromagnetic method (CSEM), as a significant geophysical exploration technique, plays a crucial role in imaging subsurface structures. To enhance the accuracy and efficiency of CSEM simulations, this paper introduces a 3D unstructured vector finite element numerical simulation method based on the third-type boundary condition. Vector finite elements are particularly suitable for handling discontinuities in the electric field normal. They automatically satisfy tangential field continuity and zero-divergence requirements, providing a solid foundation for forward modeling in the CSEM. The adoption of the third-type boundary condition aims to reduce computational scale while ensuring higher simulation accuracy. Using this method, we conducted detailed numerical simulations on various models, including layered models, single-anomaly models, composite-anomaly models, and layered-anomaly models. The experimental results demonstrate that the algorithm accurately reproduces the electromagnetic responses of various geological models. It also exhibits superior computational accuracy under low-frequency conditions, outperforming traditional simulation methods. In summary, the 3D unstructured vector finite element numerical simulation method proposed in this study offers an efficient and reliable solution for CSEM, which is of great significance for advancing CSEM technology, especially in inversion techniques and data interpretation. Future work will focus on further optimizing algorithm performance and exploring its application potential in complex geological environments.

Room-temperature skyrmions in magnetic multilayers are considered to be promising candidates for the next-generation spintronic devices. Several approaches have been developed to control skyrmions, but they either cause significant heat dissipation or require ultrahigh electric fields near the breakdown threshold. Here, we demonstrate electric-field control of skyrmions through strain-mediated magnetoelectric coupling in ferromagnetic/ferroelectric multiferroic heterostructures. We show the process of non-volatile creation of multiple skyrmions, reversible deformation and annihilation of a single skyrmion by performing magnetic force microscopy with in situ electric fields. Strain-induced changes in perpendicular magnetic anisotropy and interfacial Dzyaloshinskii–Moriya interaction strength are characterized experimentally. These experimental results, together with micromagnetic simulations, demonstrate that strain-mediated magnetoelectric coupling (via strain-induced changes in both the perpendicular magnetic anisotropy and interfacial Dzyaloshinskii–Moriya interaction is responsible for the observed electric-field control of skyrmions. Our work provides a platform to investigate electric-field control of skyrmions in multiferroic heterostructures and paves the way towards more energy-efficient skyrmion-based spintronics. The common approaches to control of skymions cause significant heat dissipation or require high electric fields near the breakdown threshold. Here, the authors demonstrate electric-field control of skyrmions through strain-mediated magnetoelectric coupling in multiferroic heterostructures.

Side-chain engineering has been considered as one of the most promising strategies to optimize non-fullerene small-molecule acceptors (NFSMAs). Previous efforts were focused on the optimization of alkyl-chain length, shape, and branching sites. In this work, we propose that asymmetric side-chain engineering can effectively tune the properties of NFSMAs and improve the power conversion efficiency (PCE) for binary non-fullerene polymer solar cells (NFPSCs). Specifically, by introducing asymmetric side chains into the central core, both of the absorption spectra and molecule orientation of NFSMAs are efficiently tuned. When blended with polymer donor PM6, NFPSCs with EH-HD-4F (2-ethylhexyl and 2-hexyldecyl side chains) demonstrate a champion PCE of 18.38% with a short-circuit current density ( J SC ) of 27.48 mA cm − 2 , an open circuit voltage ( V OC ) of 0.84 V, and a fill factor (FF) of 0.79. Further studies manifest that the proper asymmetric side chains in NFSMAs could induce more favorable face-on molecule orientation, enhance carrier mobilities, balance charge transport, and reduce recombination losses.