This study examines the spatial distribution of socioeconomic conditions in Colombia, using Moran's Index as a tool for spatial autocorrelation analysis. Key indicators related to education, health, infrastructure, access to basic services, employment, and housing conditions are addressed, allowing the identification of inequalities and structural barriers. The research reveals patterns of positive autocorrelation in several socioeconomic dimensions, suggesting a concentration of poverty and underdevelopment in certain geographic areas of the country. The results show that municipalities with more unfavorable conditions tend to cluster spatially, particularly in the northern, northwestern, western, eastern, and southern regions of the country, while the central areas exhibit better conditions. Permutation analyses are employed to validate the statistical significance of the findings, and LISA cluster maps highlight the regions with the highest concentration of poverty and social vulnerability. This work contributes to the literature on inequality and regional development in emerging economies, demonstrating that public policies should prioritize intervention in territories that exhibit significant spatial clustering of poverty. The methodology and findings provide a foundation for future studies on spatial correlation and economic planning in both local and international contexts.

This study explores the spatial distribution pattern of educational infrastructure development across districts and cities in North Sumatra, identifying significant disparities between urban and rural areas. The study aims to: (1) determine the distribution of educational development across districts and cities, (2) analyze global spatial autocorrelation, and (3) identify priority locations for educational development policies in North Sumatra Province. The methodology includes quantile analysis, Moran’s Global Index, and Local Indicators of Spatial Autocorrelation (LISA) using GeoDa software to address spatial autocorrelation. The results indicate that there are nine areas with a low School Participation Rate Index (SPRI), eleven areas with a low School Facilities and Infrastructure Index (SFII), and eleven areas with a low Regional Education Index (REI). Spatial autocorrelation analysis reveals that SFII shows positive spatial autocorrelation, while SPRI and REI exhibit negative spatial autocorrelation, indicating a high level of inequality between regions. Labuhan Batu Selatan and Labuhan Batu are identified as priorities for the provincial government in overseeing educational development policies.

This paper examines the impact of the COVID-19 pandemic on financial inclusion in China, a country with a significant agricultural sector and an evolving digital landscape. The pandemic has accelerated the shift towards digital financial services, underscoring disparities in access. This study explores the pre- and post-pandemic scenarios of financial inclusion in China, evaluates the economic and social impacts of the pandemic, and assesses the role of digital transformation in the financial sector. It also investigates the changing roles of commercial banks and microfinance institutions, the integration of technology in finance, and the development of rural-urban economic linkages. The paper aims to propose strategies to enhance financial inclusion, ensuring it reaches the most vulnerable, and concludes with recommendations for creating a more equitable and robust economic system.

Helical deep hole drilling is a process frequently used in industrial applications to produce bores with a large length to diameter ratio. For better cooling and lubrication, the deep drilling oil is fed directly into the bore hole via two internal cooling channels. Due to the inaccessibility of the cutting area, experimental investigations that provide information on the actual machining and cooling behavior are difficult to carry out. In this paper, the distribution of the deep drilling oil is investigated both experimentally and simulatively and the results are evaluated. For the Computational Fluid Dynamics (CFD) simulation, two different turbulence models, i.e. the RANS k-ω-SST and hybrid SAS-SST model, are used and compared. Thereby, the actual used deep drilling oil is modelled instead of using fluid dynamic parameters of water, as is often the case. With the hybrid SAS-SST model, the flow could be analyzed much better than with the RANS k-ω-SST model and thus the processes that take place during helical deep drilling could be  simulated with realistic details. Both the experimental and the simulative results show that the deep drilling oil movement is almost exclusively generated by the tool rotation. At the tool’s cutting edges and in the flute, the flow velocity drops to zero for the most part, so that no efficient cooling and lubrication could take place there. In addition, cavitation bubbles form and implode, concluding in the assumption that the process heat is not adequately dissipated and the removal of chips is adversely affected, which in turn can affect the service life of the tool and the bore quality. The carried out investigations show that the application of CFD simulation is an important research instrument in machining technology and that there is still great potential in the area of tool and process optimization.

The article presents an answer to the current challenge about needs to form methodological approaches to the digital transformation of existing industrial enterprises (EIE). The paper develops a hypothesis that it is advisable to carry out the digital transformation of EIE based on considering it as a complex technical system using model-based system engineering (MBSE). The practical methodology based on MBSE for EIE digital representation creation are presented. It is demonstrated how different system models of EIE is created from a set of entities of the MBSE approach: requirements—unctions—components and corresponding matrices of interconnections. Also the principles and composition of tasks for system architectures creation of EIE digital representation are developed. The practical application of proposed methodology is illustrated by the example of an existing gas distribution station.