Zunyi Normal College

This study designed a geography teaching for the transition from junior high school to senior high school based on regional cognitive literacy, focusing on aspects such as concept construction, regional comparison, and multi-source information integration. Through progressive concept construction, students have significantly improved their understanding of regional element identification and the interrelationships among elements. In the regional comparison exercises, students gradually mastered the unified standards, better analyzed information such as natural conditions and economic structures among different regions, and were able to conduct more logically rigorous, comprehensive comparisons. In the multi-source information integration training, students utilized various types of information such as remote sensing images, topographic maps, and statistical data, enhancing their comprehensive interpretation and analysis capabilities of regional issues. Overall, bridging teaching has effectively enhanced students’ abilities in regional cognition, comparative analysis, and information integration, laying a solid foundation for geography learning in high school.

<italic>γ</italic>-Aminobutyric acid (GABA) is a nonprotein amino acid involved in plant stress responses and metabolic regulation. In this study, we investigated the effects of exogenous GABA on postharvest senescence in baby mustard stored at 20 °C. GABA treatment preserved external quality and delayed the loss of chlorophylls, ascorbic acid, and phenolics. Quasi-targeted metabolomics identified 195 differentially accumulated metabolites (DAMs) in the comparison between untreated and GABA-treated samples, including amino acids (e.g., threonine, phenylalanine), soluble sugars (e.g., trehalose), and phenylpropanoids (e.g., sinapine, astragalin). Transcriptomic profiling of the same comparison revealed 5,912 differentially expressed genes (DEGs). Many of these DEGs were enriched in phenylpropanoid biosynthesis and antioxidant pathways, with GABA upregulating antioxidant enzyme genes and contributing to redox stability. Moreover, GABA treatment suppressed ethylene signaling by downregulating <italic>ETR</italic>, <italic>CTR1</italic>, and 40 out of 42 ethylene-responsive (ERF) transcription factors, thereby repressing ethylene-responsive transcription. These integrated responses delayed oxidative damage and maintained nutritional stability. This study provides the first omics-based evidence of GABA-mediated alleviation of senescence in baby mustard, highlighting its potential as a postharvest preservation strategy for <italic>Brassica</italic> vegetables.

PtFeCoNiMo/C exhibits exceptional alkaline HER performance, attributed to the synergistic effects of multiple elements and the modulation of its electronic structure.

Addressing the critical demand for next-generation lightweight, high-efficiency microwave absorbers, this paper proposes a “micro-meso-macro” multi-scale synergistic regulation strategy. Specifically, core@shell mesoporous carbon hollow nanospheres (HNSs)@carbon bean-shaped nanofibers (BNFs) are designed and fabricated efficiently using SiO2/carbon solid nanospheres as precursor through a continuous electrostatic spinning, heat treatment, carbonization, and hydrofluoric (HF) etching. The acquired results suggest that the regulation of carbonization temperature greatly improves the graphitized degree of mesoporous carbon HNSs@carbon BNFs, which significantly enhances the values of complex permittivity. Furthermore, the introduction of a controllable number of mesoporous carbon HNSs at the mesoscale significantly increases the specific surface area and promotes the interfacial polarization effects. The macroscopic 3-dimensional continuous conductive network constructed via electrospinning further enhances electron transport capability and conductive loss efficiency. Benefiting from the excellent collaborative design between multi-scale structure and composition, the optimized mesoporous carbon HNSs@carbon BNFs display excellent microwave absorption properties with a minimum reflection loss (RLmin) of −61.03 dB at 2.42 mm and an effective absorption bandwidth (EAB) of 6.2 GHz at 2.18 mm. Meanwhile, the acquired mesoporous carbon HNSs@carbon BNFs also present excellent corrosion resistance, hydrophobicity, flexibility, and lightweightness. Generally, the finding proposes a simple route for the production of novel core@shell C@C nanocomposites, which makes the best of multi-scale construction strategy to develop lightweight multifunctional microwave absorbers.

The research on fog image recognition of unmanned aerial vehicles (UAVs) aims to address the issues of poor image quality and low recognition accuracy in foggy weather, which is of great significance for enhancing the perception ability of UAVs in harsh environments and expanding application scenarios. Compared with traditional methods, convolutional neural networks (CNNs) have advantages such as automatic feature extraction and spatial information retention in fog image recognition. Although conventional CNNs have relatively high recognition accuracy, their computational complexity is extremely high, making them difficult to deploy on mobile devices such as UAVs. Therefore, a fog image recognition network called FIRNet is proposed. In this network, neurons in each layer are trimmed to a number suitable for the binary classification task of images, and depth-separable convolution is used to replace conventional convolution. The fog image dataset HazyDet for UAV is used to train FIRNet. The experimental results show that FIRNet achieves the fog image recognition accuracy of 0.9865 with an ultra-low computational complexity of 48.43 MFLOPS.