Journal of Research in Multidisciplinary Methods and Applications

Transcriptomic Analysis of Permafrost Mucormycete Stress on Fennel Thin-Winged Borer

Yulun Chen — 2025-08-15

In this study, a comprehensive transcriptome analysis was performed on Evergestis extimalis Scoli under the stress of Mucor permafrost by transcriptome sequencing technology, aiming to reveal the regulatory mechanism and biological characteristics of gene expression under pathogenic fungal stress. The experiment used high-throughput sequencing technology to annotate Unigenes using multiple databases, and found that Asian corn borer was the species with the most homologous sequences. A total of 357, 444, 198 and 890 differentially expressed genes were detected by differential expression analysis, which were mainly enriched in cell components, molecular functions and biological processes, involving polysaccharide degradation, metabolic processes, and antibacterial humoral reaction regulation. KEGG enrichment analysis revealed multiple pathways related to insect metabolism and signaling, such as "oxidative phosphorylation", "glycolysis/gluconeogenesis" and "MAPK signaling pathway", among which the environmental information processing-signal transduction pathway enriched the most differential genes. In addition, real-time PCR verified that the expression trends of 9 genes with large differences were basically consistent with the transcriptome sequencing results, indicating that the transcriptome data had high accuracy and reliability. The results of this study provide an important theoretical basis for understanding the gene expression regulation mechanism and biological characteristics of F. fennel under permafrost Mucormycete stress.

A Screw Surface Defect Detection Model Based on YOLO11- DySample

Zhenglong Zhu — 2025-08-15

As critical components in fastening systems, screws play an essential role in structural connection and load transmission, where surface quality directly affects product safety and reliability. To achieve efficient and accurate detection of various surface defects on screws, this paper proposes a detection model based on the YOLO11-DySample algorithm. The proposed method adopts YOLO11 as the backbone detection framework and integrates the lightweight and efficient DySample dynamic upsampling module, which enhances feature reconstruction and improves the perception of small defects. Experimental results on a screw defect dataset demonstrate that the proposed model outperforms other benchmark algorithms in several key performance metrics, achieving a mAP50 of 0.991, mAP50-95 of 0.859, precision of 0.996, and recall of 0.994, indicating excellent accuracy and robustness. Further analysis of loss curves and precision-recall curves confirms the model’s convergence and generalization capability. Visual inspection results show that the model can effectively identify typical defects such as scratches and dents, demonstrating strong potential for practical industrial deployment.

Research on Generation Z's Willingness to Work in Rural Homestays

Yuxi Zeng — 2025-08-15

Rural homestays can drive rural economic growth and contribute to rural revitalization. In the digital age, the operation of rural homestays cannot do without digital elements. Generation Z is relatively easy to learn digital knowledge, which in turn improves the operational efficiency of rural homestays. This paper studies the employment intentions of Generation Z in rural homestays and proposes research suggestions based on the relevant current situation. First, increase the number of rural homestay operation projects to diversify income sources; second, rural homestays can provide more job opportunities to attract different types of Generation Z talents; third, improve rural supporting facilities to meet the living needs of Generation Z; fourth, establish township youth associations to gather youth power; fifth, develop detailed promotion plans for Generation Z to attract more Generation Z to work in rural homestays; sixth, improve the employment benefits of Generation Z in rural homestays to retain the talent who build rural homestays; seventh, strengthen communication with family members to gain support for working in rural homestays; and eighth, increase publicity for rural homestay employment to encourage more Generation Z youth to aspire to work in rural homestays.