Lightweight Object Detection Algorithm for UAV Aerial Imagery.

Addressing the challenges of low detection precision and excessive parameter volume presented by the high resolution, significant scale variations, and complex backgrounds in UAV aerial imagery, this paper introduces MFP-YOLO, a lightweight detection algorithm based on YOLOv5s. Initially, a multipath inverse residual module is designed, and an attention mechanism is incorporated to manage the issues associated with significant scale variations and abundant interference from complex backgrounds. Then, parallel deconvolutional spatial pyramid pooling is employed to extract scale-specific information, enhancing multi-scale target detection. Furthermore, the Focal-EIoU loss function is utilized to augment the model's focus on high-quality samples, consequently improving training stability and detection accuracy. Finally, a lightweight decoupled head replaces the original model's detection head, accelerating network convergence speed and enhancing detection precision. Experimental results demonstrate that MFP-YOLO improved the mAP50 on the VisDrone 2019 validation and test sets by 12.9% and 8.0%, respectively, compared to the original YOLOv5s. At the same time, the model's parameter volume and weight size were reduced by 79.2% and 73.7%, respectively, indicating that MFP-YOLO outperforms other mainstream algorithms in UAV aerial imagery detection tasks.

Long non-coding RNA DDX11-AS1 promotes esophageal carcinoma cell proliferation and migration through regulating the miR-514b-3p/RBX1 axis.

Esophageal carcinoma (ESCA) is one of the most aggressive malignancies with extremely high morbidity and mortality. At present, limited advancement in ESCA treatment has achieved. Therefore, it is urgent to explore the pathogenesis and progression mechanism of ESCA to provide the basis for the formulation of novel therapeutic strategies. Previous studies have found that long non-coding RNA (lncRNA) DDX11-AS1 expression enhances the paclitaxel resistance of ESCA cells. However, the mechanisms underlying the drug resistance conferred by lncRNA DDX11-AS1 in ESCA remains to be elucidated. Our research aims to clarify the role and mechanism of lncRNA DDX11-AS1 in regulating the progression of ESCA. We found that the expression of lncRNA DDX11-AS1 in ESCA tissues and cell lines was significantly upregulated. Subsequently, silencing lncRNA DDX11-AS1 significantly inhibited the proliferation, migration and invasion of ESCA cells, and induced the level of cell apoptosis. In terms of mechanism, our data showed that miR-514b-3p/RING box protein 1 (RBX1) axis played a crucial role in the oncogenic function of lncRNA DDX11-AS1. LncRNA DDX11-AS1 expression impaired the inhibitory function of miR-514b-3p on RBX1 through sponging effect. Taken together, our data support the notion that lncRNA DDX11-AS1 promotes the progression of ESCA through miR-514b-3p/RBX1 axis. Our research uncovers the novel regulatory role of lncRNA DDX11-AS1 in ESCA and lays a theoretical basis for developing novel treatment strategy of ESCA.

Correlations among Work Stressors, Work Stress Responses, and Subjective Well-Being of Civil Servants: Empirical Evidence from China.

BACKGROUND: The work stress of civil servants has gradually increased as a result of the modernization of China's national governance system and capacity. However, research on the correlations among work stressors, work stress responses, and subjective well-being (SWB) of civil servants is scarce. METHODS: In accordance with the current research status on work stress and SWB, a survey of 874 civil servants in China was carried out from May to June 2018. The revised stress response questionnaire of civil servants, work stressors questionnaire of civil servants, and a simplified edition of the SWB scale of China's urban residents were used in this study. RESULTS: Superiors impose the major work pressure on civil servants, followed by interpersonal relationship, work particularity, career prospect, work task, perfectionism, and job responsibility. The work stressors of civil servants were significantly related to gender, age, marital status, working years, educational background, and position (P<0.05). The work stressors of civil servants were significantly positively correlated with work stress responses (P<0.05). The work stressors and work stress responses had a significantly negative correlation with SWB. CONCLUSION: SWB can be accurately predicted by work stressors and work stress responses. These findings can provide references and guidance for the society and government sectors to accurately understand and cope with the treatment of civil servants, formulate work stress management countermeasures, and create a high-level working environment for civil servants.