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.

The article discusses the essence of integrative geography and its importance for the theory and practice of geographical science. Such areas of integrative geography are characterized, the development of which will further increase the importance of applied geographical science. They include teaching about cultural landscape and historical landscape (part of landscape studies), geoecological expertise and environmental impact assessment (part of geographic ecology), geographic archeology and ecological culture (part of historical geography), landscape management and landscape services (part of landscape planning), and tourism—Assessment and planning of recreational resources (part of recreational geography).

Using a Global Trade Analysis Project (GTAP) model, and China as the base for analytical comparison, this paper shows that there are significant economic benefits to China and the participating countries along all six Belt and Road Initiative (BRI) economic corridors. However, to maximize these benefits, the social and environmental risks need to be well managed. The analysis shows a clear sequencing in terms of priority corridors. Two corridors have minimal investments and immediate returns, two corridors have significant investments with huge returns, and two corridors have high investments with lower returns. Overall, the paper demonstrates that to ensure the sustainability of any BRI corridor development, there is a need to consider its costs and benefits from the economic, social and environmental perspectives.