This scientific study aims to thoroughly assess the current status and evaluate key indicators influencing healthcare and the workforce in selected European Union (EU) member states. Building upon this ambitious research agenda, we focused on a comprehensive descriptive analysis of selected indicators within the healthcare sector, including healthcare financing schemes, overall employment in healthcare and social care, the number of graduates in healthcare (including physicians and general practitioners), as well as migration patterns within the healthcare sector. The data forming the basis of this analysis were systematically gathered from Organization for Economic Co-operation and Development (OECD) and Eurostat databases. Subsequently, we conducted a robust correlation analysis to explore the intricate relationships among these indicators. Our research endeavour aimed to identify and quantify the impact of these indicators on each other, with a focus on their implications for overall healthcare and the workforce in the respective countries. Based on the findings obtained, we derived several significant conclusions and recommendations. For instance, we identified that increasing employment in the healthcare sector may be associated with the overall quality of healthcare provision in a given country. These findings have important implications for policymaking and decision-making at the EU level. Therefore, we recommend that policymakers in these countries consider implementing measures to further develop the healthcare sector while also helping to retain and attract qualified professionals in the healthcare industry. Such recommendations could include improving healthcare infrastructure, incentivizing professional education and further training in the healthcare sector, and implementing policies to support healthcare provision more broadly.

The research aimed to: 1) analyze components and indicators of digital transformation leadership among school administrators, 2) assess their leadership needs, and 3) develop mechanism models to promote this leadership. A mixed-method approach was applied, involving three sample groups: 8 experts, 406 administrators, and 7 experts. Data collection tools included semi-structured interviews, leadership scales, needs assessments, and focus group discussions, with analysis performed through construct validity testing, needs assessment, and content analysis. The findings revealed: 1) The components and indicators of digital transformation leadership showed structural validity, as confirmed by the model's alignment with empirical data (Chi-Square = 82.3, df = 65, p = 0.072, CFI = 0.998, TLI = 0.997, RMR = 0.00965, RMSEA = 0.0256). 2) Among the leadership components, "innovative knowledge" ranked highest in need (PNImodified = 0.075), followed by "ideological influence" (0.066), "consideration of individuality" (0.055), "intellectual stimulation" (0.052), and "inspiration" (0.053). 3) Mechanism models for promoting leadership emphasized enhancing these five components to strengthen administrators' skills in applying technology, managing teaching and development plans, and fostering innovation. Administrators were encouraged to tailor strategies to individual needs, inspire personnel, and create a commitment to organizational change and development. These mechanisms aim to equip administrators to effectively lead transformations, motivate staff, and drive educational institutions to adapt and thrive in evolving environments.

The use of porous media to simplify the thermohydraulic of a nuclear reactor is the topic of recent research. As a case study, the rector of 200 kW installed at Missouri University of Science and Technology is modeled in this paper. To help this objective, a fundamental CFD examination was completed to supplement the neutronics investigation on the present reactor. Characteristics of thermal energy removal from a typical research reactor are modeled by numerical thermal transport in porous media. The neutron flux is modeled by the nodal expansion method. For the thermo-hydraulic part, a three-dimensional governing equation is solved by an iterative method to find the steady-state solution of fluid flow and temperature in loss of coolant condition where the heat produced in the reactor core is removed by free convection. The profiles of heat flux for various power levels are benchmarked. Pressure, temperature, and velocity contours in the power passage were assessed at 300 kW and 500 kW power levels. To reduce the computational cost, a porous media approach for the whole geometry was utilized. The numerical results agree with the experimental results. The developed model can be used for safety and reliability analysis for various loss of coolant accidents.

In order to scientifically evaluate the germplasm resources of Momordica charantia in southern China, the diversity, correlation and cluster analysis were carried out on the main botanical characters of 56 Momordica charantia varieties, such as melon length, melon transverse diameter, single melon weight, internode length, stem diameter, leaf length and leaf width. The results showed that the variation coefficients of 7 agronomic characters of 56 Momordica charantia varieties ranged from 8.81% to 19.44%, the average variation coefficient was 14.21%, the maximum variation coefficient of single melon weight was 19.44%, and the minimum variation coefficient of melon cross diameter was 8.81%. The correlation analysis showed that there were correlations among the agronomic traits. The positive correlation coefficient between leaf length and leaf width was up to 0.978, and the negative correlation coefficient between single melon weight and internode length was up to 0.451. The 56 varieties were divided into 3 groups by cluster analysis, of which 92.86% of the materials were concentrated in the first and second groups, and there were only 4 materials in the third group. The results can provide a reference for the cultivation, utilization and genetic improvement of Momordica charantia resources in southern China.