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Given the challenges associated with the low accuracy, complexity of the equipment, and poor interference resistance observed in current wireless multipath channel measurements, this study introduces a novel algorithm called KFSC-WRELAX. This algorithm integrates techniques involving pseudorandom noise (PN) sequences, Kalman filtering (KF), sliding correlation, and weighted Fourier transform combined with the RELAXation (WRELAX) algorithm. An m-sequence is employed as the probing sequence for channel detection. The effectiveness of the KFSC-WRELAX algorithm is demonstrated through both simulation experiments and corridor testing, showing that it can accurately determine the delays in various paths with robust performance at a signal-to-noise ratio (SNR) of −5 dB or higher. [ABSTRACT FROM AUTHOR]

SUMMARY: Several dwarf and semi‐dwarf genes have been identified in barley. However, only a limited number have been effectively utilized in breeding programs to cultivate lodging resistant varieties. This is due to the common association of dwarf and semi‐dwarf traits with negative effects on malt quality. In this study, we employed gene editing to generate three new haplotypes of sdw1/denso candidate gene gibberellin (GA) 20‐oxidase2 (GA20ox2). These haplotypes induced a dwarfing phenotype and enhancing yield potential, and promoting seed dormancy, thereby reducing pre‐harvest sprouting. Moreover, β‐amylase activity in the grains of the mutant lines was significantly increased, which is beneficial for malt quality. The haplotype analysis revealed significant genetic divergence of this gene during barley domestication and selection. A novel allele (sdw1.ZU9), containing a 96‐bp fragment in the promoter region of HvGA20ox2, was discovered and primarily observed in East Asian and Russian barley varieties. The 96‐bp fragment was associated with lower gene expression, leading to lower plant height but higher germination rate. In conclusion, HvGA20ox2 can be potentially used to develop semi‐dwarf barley cultivars with high yield and improved malt quality. Significance Statement: Gene editing of HvGA20ox2 led to reduced plant height, improved yield potential, and pre‐harvest sprouting in barley. A novel allele sdw1.ZU9 containing a 96‐bp fragment located in the promoter region of HvGA20ox2 results in suppression of the gene expression, leading to reduced plant height and increased germination rate. [ABSTRACT FROM AUTHOR]

A molecular pump is the core component of vacuum systems in portable mass spectrometers and other analytical instruments. The forms of the existing molecular pumps mainly are the combinations of vertical bleed and compression channel, which have the shortcomings of heavy mass and large volume, which seriously restricts the application and development of portable mass spectrometers. Aiming at the problems of low strength and insufficient pumping performance under the miniaturization constraints (mass of 1.8 kg; exhaust diameter of 25 mm) of molecular pumps, a compound pump consisting of a horizontal bleed channel and multi-stage spiral compression channel is proposed. The pumping principle of the compound molecular pump is analyzed to obtain its preliminary structural size parameters. The test particle Monte Carlo method is presented for establishing an aerodynamic model for a high-speed small compound molecular pump, which can be used to investigate the pumping performance of bleed blades and compression channels in a thin air environment. On the basis of the aerodynamic model, the NNIA multi-objective optimization algorithm is presented to optimize the structural parameters of the compound molecular pump. After structural parameter optimization, the maximum flow rate and compression ratio of the compound molecular pump are increased by 13.6% and 41.6%, respectively. The experimental results of the pumping performance show that the predicted data of the aerodynamic model are in good agreement with the experimental data, with an error of 12–27%. Namely, the established aerodynamic model has high accuracy and the optimized structural parameters of the compound molecular pump can provide basic conditions for the large-scale application and promotion of portable mass spectrometers. [ABSTRACT FROM AUTHOR]

Introduction: Although microRNA (miR)-150-5p participates in the progression of renal fibrosis, its mechanism of action remains elusive. Methods: A mouse model of unilateral ureteral obstruction was used. The in vitro renal fibrosis model was established by stimulating human kidney 2 (HK-2) cells with transforming growth factor beta 1 (TGF-β1). The expression profiles of miR-150-5p, zinc finger E-box binding homeobox 1 (ZEB1), and other fibrosis- and epithelial-mesenchymal transition (EMT)-linked proteins were determined using Western blot and quantitative reverse transcription polymerase chain reaction. The relationship between miR-150-5p and ZEB1 in HK-2 cells was confirmed by a dual-luciferase reporter assay. Results: Both in vivo and in vitro renal fibrosis models revealed reduced miR-150-5p expression and elevated ZEB1 level. A significant decrease in E-cadherin levels, as well as increases in alpha smooth muscle actin (α-SMA) and collagen type I (Col-I) levels, was seen in TGF-β1-treated HK-2 cells. The overexpression of miR-150-5p ameliorated TGF-β1-mediated fibrosis and EMT. Notably, miR-150-5p acts by directly targeting ZEB1. A significant reversal of the inhibitory impact of miR-150-5p on TGF-β1-mediated fibrosis and EMT in HK-2 cells was observed upon ZEB1 overexpression. Conclusion: MiR-150-5p suppresses TGF-β1-induced fibrosis and EMT by targeting ZEB1 in HK-2 cells, providing helpful insights into the therapeutic intervention of renal fibrosis. [ABSTRACT FROM AUTHOR]

Antibiotics are commonly used to prevent and control aquaculture diseases. However, long-term overuse of antibiotics not only leaves residues but also leads to changes in the nitrogen cycle in water, which threatens the survival of aquaculture organisms. The current results showed that sulfamethoxazole had no significant effect on the nitrogen cycle process in the actual aquaculture concentration. The inhibitory effect of 1.05 mg/L norfloxacin on ammonia-oxidizing bacteria was significantly greater than that on ammonia-oxidizing archaea, and the gene abundance of AOB amoA on the 14th day increased by 2.48 times compared with the 7th day. Under the influence of 3.9 mg/L oxytetracycline, the gene abundance of AOB amoA decreased significantly, while the number of AOA amoA genes increased, suggesting that there may be functional redundancy between AOA and AOB. At the genus level in the norfloxacin group, the relative abundance of Sva0485 increased by 14.0% on the 7th day compared with the control group but decreased 12.77% in the addition group. The relative abundance of Firmicutes, another dominant species in the oxytetracycline group, was 25.9%. This study shows that the addition of antibiotics may have a negative effect on the nitrogen-cycling microorganisms in aquaculture water. [ABSTRACT FROM AUTHOR]

Radar emitter signal sorting (RESS) is a crucial process in contemporary electronic battlefield situation awareness. Separating pulses belonging to the same radar emitter from interleaved radar pulse sequences with a lack of prior information, high density, strong overlap, and wide parameter distribution has attracted increasing attention. In order to improve the accuracy of RESS under scenarios with limited labeled samples, this paper proposes an RESS model called TR-RAGCN-AFF-RESS. This model transforms the RESS problem into a pulse-by-pulse classification task. Firstly, a novel weighted adjacency matrix construction method was proposed to characterize the structural relationships between pulse attribute parameters more accurately. Building upon this foundation, two networks were developed: a Transformer(TR)-based interleaved pulse sequence temporal feature extraction network and a residual attention graph convolutional network (RAGCN) for extracting the structural relationship features of attribute parameters. Finally, the attention feature fusion (AFF) algorithm was introduced to fully integrate the temporal features and attribute parameter structure relationship features, enhancing the richness of feature representation for the original pulses and achieving more accurate sorting results. Compared to existing deep learning-based RESS algorithms, this method does not require many labeled samples for training, making it better suited for scenarios with limited labeled sample availability. Experimental results and analysis confirm that even with only 10% of the training samples, this method achieves a sorting accuracy exceeding 93.91%, demonstrating high robustness against measurement errors, lost pulses, and spurious pulses in non-ideal conditions. [ABSTRACT FROM AUTHOR]