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Problem: China's declining birth rate presents significant challenges to obstetricians, impacting workload, career prospects, and the obstetric service system. Background: The reduction in birth rates alters the landscape for obstetricians, necessitating adaptation to new medical demands and technological environments. Aim: This paper aims to explore the future development and role transformations of Chinese obstetricians amidst declining birth rates. Key questions include: What is the impact of declining birth rates on China's obstetric services?What are the future development directions for obstetricians in this scenario?How will their roles evolve to meet new medical demands and technological environments?What international experiences can be drawn upon, and how applicable are they to China? Methods: A literature review method is employed, analyzing research papers, statistical data, and policy reports from domestic and international sources. Findings: The paper systematically summarizes and evaluates current and future trends in Chinese obstetrics in the context of declining birth rates. Discussion: It discusses practical implications for sustainable development, including optimizing medical resources, leveraging technological innovations, and enhancing talent development. Conclusion: This paper contributes a comprehensive analysis and practical recommendations for navigating the challenges posed by declining birth rates to Chinese obstetricians.

Ship tracking technology is crucial for emergency rescue in the event of a disaster. Quickly identifying the position and status of vessels is vital for rescue teams to be able to deploy efficiently in disaster areas. When responding to emergencies or natural disasters, ship tracking technology plays a critical role in supporting emergency rescue operations and resource allocation, improving the overall resilience of the maritime transportation system. However, the research on multi-object tracking (MOT) algorithms has primarily focused on optical image datasets. In contrast, image data from synthetic aperture radar (SAR) presents unique challenges, such as defocus interference, a high false alarm rate, and a lack of prior samples. To overcome these particular challenges, we propose a robust MOT algorithm developed for SAR images to achieve effective multi-vessel tracking under difficult imaging conditions. In particular, we optimize the YOLOv8 detection network by introducing a diffusion model-based training method for data augmentation. This method improves the robustness of the network to scaling, rotational and translational deformations. Moreover, an enhanced swin transformer is proposed as a feature extraction network, which strengthens the representation capability of the detection network. Furthermore, the state parameters within the KF technique are enhanced by directly capturing the details of the height and width of the tracking rectangle box. This refinement of the ByteTrack algorithm aims to achieve a more precise and accurate fit of the tracking rectangle to the ship, further improving the overall tracking performance. The experimental results from the ship detection and multiple objects tracking datasets show the impressive performance of the proposed model. With a precision of 97.60%, a recall of 96.36%, and an average precision of 96.72%, the model achieves exceptional detection accuracy with an 18% reduction in model parameters. Furthermore, significant improvements can be observed in key tracking metrics such as HOTA, MOTA and IDF1, with improvements of 4.8%, 8.5% and 6.8% respectively compared to the baseline algorithm, alongside a remarkable 37.5% reduction in IDS. It is noteworthy that the tracker works in real time, achieving an average analysis speed of 47 frames per second. The proposed MOT algorithm achieves state-of-art tracking performance on a SAR image dataset with short time sequences. Therefore, the proposed approach is a compelling solution for ship tracking in SAR imagery.

The Xuefeng black bone chicken (XFBC) represents an important poultry genetic resource. However, the darkness in breast muscle is heterogeneous. The molecular genetic mechanisms underlying melanogenesis of breast muscle in XFBC remains unclear. This study used RNA-seq to compare the difference in transcriptome between hyperpigmentation and hypopigmentation of breast muscle. Six cDNA libraries were constructed for hyperpigmentation and hypopigmentation groups in XFBC. We identified 395 differently expressed genes (DEGs) between hyperpigmentation and hypopigmentation group (P < 0.05, |[log.sub.2]FC|[greater than or equal to]1). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated several differentially enriched biological functions and pathways involved in melanogenesis of the breast muscle. Gene set enrichment analysis (GSEA) GO analysis identified two significant gene sets, including the pathways of pigment metabolic process and transmembrane receptor protein tyrosine kinase activity. GSEA-KEGG analysis identified the process of tyrosine metabolism and several genes related with melanogenesis in breast muscle of the XFBC. The protein-protein interaction network was constructed and eight genes were clustered in the module. We identified nine hub genes, including TYR, TYRP1, DCT, GPR143, MLANA, SLC24A5, GPNMB, MLPH, and EDNRB2. Taken together, the DEGs and hub genes identified in the study provide a solid basis for the study of the genetic regulatory mechanisms involved the melanogenesis in the breast muscle of the XFBC. Key words: Xuefeng black bone chicken, breast muscle, RNA-Seq, melanogenesis, 1. Introduction The black bone chicken is one of the most important poultry genetic resources in China (Li et al. 2020). The productions of black bone chicken are very popular [...]