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The parameter variations of magnetically coupled resonant wireless power transmission (MCR‐WPT) system cause frequency splitting and resonant frequency shift, which lead to the system detuning and reduce the transmission efficiency. To solve the problems, a frequency tracking control method based on the phase difference between the primary‐side voltage and the secondary‐side current (Frequency Tracking Control‐the primary‐side voltage and the secondary‐side current, FTC‐PS) in this paper. According to the characteristics that the phase difference between the voltage of transmitting side and the current of receiving side is not affected by frequency splitting, the phase difference is controlled at 90°, so that the system can achieve the maximum transmission efficiency under the condition of frequency splitting and resonant frequency shift. The experimental results show that the method can make the system always work at the natural resonant frequency when the parameters change, and the transmission efficiency is not affected by the frequency splitting phenomenon. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Antarctic sea ice concentration (SIC) prediction at seasonal scale has been documented, but a gap remains at subseasonal scale (1–8 weeks) due to limited understanding of ice‐related physical mechanisms. To overcome this limitation, we developed a deep learning model named Sea Ice Prediction Network (SIPNet) that can predict SIC without the need to account for complex physical processes. Compared to mainstream dynamical models like European Centre for Medium‐Range Weather Forecasts, National Centers for Environmental Prediction, and Seamless System for Prediction and Earth System Research developed at Geophysical Fluid Dynamics Laboratory, as well as a relatively advanced statistical model like the linear Markov model, SIPNet outperforms them all, effectively filling the gap in subseasonal Antarctic SIC prediction capability. SIPNet results indicate that autumn SIC variability contributes the most to sea ice predictability, whereas spring contributes the least. In addition, the Weddell Sea displays the highest sea ice predictability, while predictability is low in the West Pacific. SIPNet can also capture the signal of ENSO and SAM on sea ice. Plain Language Summary: Antarctic sea ice has changed significantly since 2016, leading to a higher demand for sea ice forecasts. However, forecasting Antarctic sea ice has not received enough attention. Limited observations and lack of understanding of ice‐related physical mechanisms result in significant errors in sea ice predictions in dynamical models, particularly at the subseasonal timescale. We utilized a deep‐learning model to predict Antarctic sea ice at this timescale to fill this gap. Results showed that the deep‐learning model performed skillfully 1–8 weeks in advance, with the Weddell Sea being the best‐predicted region and the West Pacific being the worst. Furthermore, our study found that the model significantly outperformed mainstream dynamic models and a conventional statistical model. These findings build a foundation for developing more advanced prediction models at high resolutions for operational applications. Key Points: A deep‐learning model outperforms dynamic models, filling a subseasonal Antarctic sea ice prediction gap by bypassing physical mechanismsUnlike a Markov model that predicts time series of fixed spatial patterns, our model can extract ice synchronized spatiotemporal evolutionsThe deep‐learning model captures climate signals in sea ice, delivering the best prediction in fall season and the Weddell Sea region [ABSTRACT FROM AUTHOR]

Unsupervised clustering is an essential step in identifying cell types from single‐cell RNA sequencing (scRNA‐seq) data. However, a common issue with unsupervised clustering models is that the optimization direction of the objective function and the final generated clustering labels in the absence of supervised information may be inconsistent or even arbitrary. To address this challenge, a dynamic ensemble pruning framework (DEPF) is proposed to identify and interpret single‐cell molecular heterogeneity. In particular, a silhouette coefficient‐based indicator is developed to determine the optimization direction of the bi‐objective function. In addition, a hierarchical autoencoder is employed to project the high‐dimensional data onto multiple low‐dimensional latent space sets, and then a clustering ensemble is produced in the latent space by the basic clustering algorithm. Following that, a bi‐objective fruit fly optimization algorithm is designed to prune dynamically the low‐quality basic clustering in the ensemble. Multiple experiments are conducted on 28 real scRNA‐seq datasets and one large real scRNA‐seq dataset from diverse platforms and species to validate the effectiveness of the DEPF. In addition, biological interpretability and transcriptional and post‐transcriptional regulatory are conducted to explore biological patterns from the cell types identified, which could provide novel insights into characterizing the mechanisms. [ABSTRACT FROM AUTHOR]

The lepidopteran crop pest Plutella xylostella causes severe constraints on Brassica cultivation. Here, we report a novel role for RPX1 (resistance to P. xylostella) in resistance to this pest in Arabidopsis thaliana. The rpx1‐1 mutant repels P. xylostella larvae, and feeding on the rpx1‐1 mutant severely damages the peritrophic matrix structure in the midgut of the larvae, thereby negatively affecting larval growth and pupation. This resistance results from the accumulation of defence compounds, including the homoterpene (3E)−4,8‐dimethyl‐1,3,7‐nonatriene (DMNT), due to the upregulation of PENTACYCLIC TRITERPENE SYNTHASE 1 (PEN1), which encodes a key DMNT biosynthetic enzyme. P. xylostella infestation and wounding induce RPX1 protein degradation, which may confer a rapid response to insect infestation. RPX1 inactivation and PEN1 overexpression are not associated with negative trade‐offs for plant growth but have much higher seed production than the wild‐type in the presence of P. xylostella infestation. This study offers a new strategy for plant molecular breeding against P. xylostella. Summary statement: Plutella xylostella pests show severely negative influence on plant growth and reproduction, and the identification of resistant genes is essential. This study reveals that inactivation of RPX1 confers significant resistance to the pest by enhancing PEN1 expression and accumulating the homoterpene DMNT in Arabidopsis thaliana. [ABSTRACT FROM AUTHOR]

Background: Intracardiac echocardiography (ICE) technology has been increasingly accepted as an integral part of atrial fibrillation (AF) ablation procedures. It is still unknown whether ICE can routinely replace transesophageal echocardiography (TEE) for routine thrombus screening in non‐selective AF patients. Objective: To assess whether ICE can routinely replace TEE in screening for left atrial (LA)/left atrial appendage (LAA) thrombus in general patients undergoing catheter ablation for AF. Methods: A total of 2003 consecutive patients undergoing AF ablation were included. 1155 patients (ICE group) received intra‐procedural ICE examination for LA/LAA thrombus screening, while 848 patients (TEE group) received pre‐procedure TEE examination. The incidence of thrombus, peri‐procedure complications, and hospital efficiency were assessed. Results: The LA and LAA were adequately visualized in all patients. Five patients in the ICE group and 15 patients in the TEE group were found to have LAA thrombus. The incidence of major periprocedural thrombo‐embolic events was comparable between two groups (0.2% vs. 0.1%, p =.76), none were due to undetected LA/LAA thrombus. Other major periprocedural complications occurred at similar rates in both groups, while post‐procedure fever was less common in the ICE group (12.7% vs. 17.4%, p <.001). Procedure times and hospital length of stay were both shorter in the ICE group (142 min [87–197 min] vs. 150 min [95–205 min], and 3[2–4] day vs. 4[3–5] day, respectively, both p <.001). Conclusions: ICE can replace TEE for atrial thrombus screening in AF patients undergoing ablation without increased complications. An "ICE replacing TEE" workflow can also reduce the incidence of postoperative fever and improve hospital efficiency. [ABSTRACT FROM AUTHOR]

In recent years, hydrophobic deep eutectic solvents as new generation of green solvents have attracted wide attention in liquid microextraction technique. In this article, four hydrophobic deep eutectic solvents composed of trioctylmethylammonium chloride and oleic acid were designed and prepared firstly. Combined with high‐performance liquid chromatography, these deep eutectic solvents were used as an extraction solvent in vortex‐assisted dispersive liquid–liquid microextraction for the selective enrichment and indirect determination of trace nitrite from real water and biological samples. This method is based on the diazotization‐coupling reaction of nitrite with p‐nitroaniline and diphenylamine in acidic water, and then the nitrite is quantified indirectly by measuring the obtained azo compounds. Some factors influencing the extraction efficiency, including the reaction and extraction conditions, were investigated. Under the optimized conditions, the method has a linear range of 1–300 μg/L with a correlation coefficient of 0.9924, limit of detection of 0.2 μg/L, limit of quantitation of 1 μg/L, intraday and interday relative standard deviations of 4.0 and 6.0%. This method was successfully applied in determination of nitrite from three environmental water and two biological samples with the recovery in the range of 90.5–115.2%. In addition, these results were well agreement with those obtained by the conventional Griess method. [ABSTRACT FROM AUTHOR]