This article explores the possibilities of developing Oman’s tourism sector under China’s Belt and Road Initiative (BRI). Tourism is a cornerstone of Oman’s economy, with the government prioritizing substantial efforts toward its development to foster economic diversification. This paper examines the broader efforts of Oman to strengthen its relations with China, which will indirectly benefit the tourism industry. This article presents a comprehensive analysis of the historical exchanges and future cooperation between China and Oman under BRI, specifically focusing on developing infrastructure and technology in Oman to support the tourism sector. It has been argued that BRI has the potential to significantly contribute to the growth and development of Oman’s tourism sector through increased investment and cooperation with Chinese counterparts.

Medicare, a major healthcare program under the Centers for Medicare & Medicaid Services (CMS) has extended telemedicine services within several states in the US for different specialties for which it reimburses in order to establish a qualitative and accessible healthcare system. In parallel, it has been seen that teleradiology services by American Board Certified radiologists based offshore can significantly supplement healthcare delivery in the US by mitigating the shortage of radiologists and enhance outcomes of patient care especially for after-hours emergency work. Teleradiology can help workflow by improving workload distribution, lowering the cost of reporting, shortening turn-around-time for reports, and improving quality of life for staff. The aim of the article is to provide perspective on Medicare reimbursement of offshore telereporting services. We submit that due to its value proposition and contribution to healthcare, offshore telereporting by American Board Certified Radiologists is worthy of Medicare reimbursement and should be re-evaluated for its credits.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity's greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.

This research introduces a novel framework integrating stochastic finite element analysis (FEA) with advanced circular statistical methods to optimize heat pump efficiency under material uncertainties. The proposed methodologies and optimization focus on balancing the mean efficiency and variability by adjusting the concentration parameter of the Von Mises distribution, which models directional variability in thermal conductivity. The study highlights the superiority of the Von Mises distribution in achieving more consistent and efficient thermal performance compared to the uniform distribution. We also conducted a sensitivity analysis of the parameters for further insights. The results show that optimal tuning of the concentration parameter can significantly reduce efficiency variability while maintaining a mean efficiency above the desired threshold. This demonstrates the importance of considering both stochastic effects and directional consistency in thermal systems, providing robust and reliable design strategies.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.