At present, states and entire regions that possess significant reserves of sought-after minerals have great potential to maintain and even improve their socio-economic position in the foreseeable future. Since the beginning of 2000, the increase in mining volumes of minerals has been more than 50%; however, more than half of all extracted raw materials fall to only five leading countries: China, the USA, the Russian Federation, Australia, and India. This article presents the results of the analysis of the global structure of mineral production by type and geographic region. The article provides an in-depth analysis of the world’s leading mining companies, identifying the key players in the industry. A comprehensive overview of each company’s performance, including key financial indicators and production statistics, is presented. The main environmental risks as a result of the continued increase in the global scale of mining have been identified. The prospects for the development of the mining sector are shown. The results of the study can be used by the scientific community as an information source.

The recent crisis-filled period has placed a significant burden on various businesses, including in the tourism sector. As a result, the concept of resilience, the flexible ability to resist, has become more and more tangible. This study aims to update the quantitative organizational resilience assessment scale of Orchiston, Prayag and Brown. The paper analyses a sample of 87 tourism service providers managing attractions, and factor analysis was carried out to identify the factors in order to be able to measure the resilience of tourism service providers. Four factors could be identified: Leadership and Organization, Strategy, Independence, and Internal Identity. These identified factors and the included 14 items mean the key contribution, as a new, updated assessment system.

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.

Low levels of financial literacy cause people to have lower savings rates, higher transaction costs, larger debts and the loans acquisition with higher interest rates, therefore it becomes relevant to analyze the determinants of financial literacy. The aim of this research is to identify whether there is an association between the financial literacy level and sociodemographic characteristics. The Mexican Petroleum Company (Pemex) employees is the population analyzed. Pemex is the state-owned oil and natural gas producer, transporter, refiner and marketer in Mexico. A non-probabilistic convenience sampling was performed and 404 responses were obtained. The analysis of data was carried out with the Bayesian method. The results show that there is an association between Pemex employees’ level of financial literacy and their level of education, income, age and type of retirement saving. No association was found between their level of financial literacy and gender, marital status and whether or not they have children.

This study explores the scale efficiency of four star hotels in a small tourist destination in Croatia. The number of overnight stays and the increase in hotel beds are two indicators of the development of a tourist destination. Among the accommodation facilities, hotels play a significant role in the development of a tourist destination, but they are increasingly facing a labor force crisis. Data envelopment analysis is used to rank hotels by efficiency coefficient. The aim of the paper is to investigate the efficiency of the hotel by taking certain inputs and outputs, which are explained in detail in the paper. The paper uses the CCR (Charnes, Cooper, and Rhodes) and BCC (Banker, Charnes, and Cooper) models to calculate hotel scale efficiency and also presents an overview of previous research around the world.