Intellectual capital is one of the most crucial determinants of long-term economic development. The countries compete for highly skilled labor and talented youth. State regulatory interventions aim to, on the one hand, facilitate the retention of foreign high-productivity intellectual capital in the host country, transforming ‘educational’ and ‘scientific’ migrants into residents, and on the other hand, prevent the outflow of their own qualified workforce. The paper aims to outline the role of the nation’s higher education system in the influx and outflow of labor resources. A two-stage approach is applied: 1) maximum likelihood—to cluster the EU countries and the potential candidates to become members of EU countries based on the integrated competitiveness of their higher education systems, considering quantitative, qualitative, and internationalization aspects; 2) logit and probit models—to estimate the likelihood of net migration flow surpassing baseline cluster levels and the probability of migration intensity changes for each cluster. Empirical findings allow the identification of four country clusters. Forecasts indicate the highest likelihood of increased net migration flow in the second cluster (66.7%) and a significant likelihood in the third cluster (23.4%). However, the likelihood of such an increase is statistically insignificant for countries in the first and fourth clusters. The conclusions emphasize the need for regulatory interventions that enhance higher education quality, ensure equal access for migrants, foster population literacy, and facilitate lifelong learning. Such measures are imperative to safeguard the nation’s intellectual potential and deter labor emigration.

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required the same memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data is used to verify the performance of the proposed RMA.

Instability is inherent in global capitalism, impacting all countries, particularly those directly reliant on this economic framework. The USA shapes tourism metrics in dependent nations and influences inbound tourism spending. Using logarithmic models and power tests, the study delineated four dynamic fields (Cn) supporting the thesis of the fusion of tourism and temporary residency. This study demonstrates that tourism and migration correlate with political, economic, and social instability, as evidenced by high statistical correlations. Variance increases during instability, leading to more residency petitions per tourist entry. This pattern is repeated during three major crises: the 2008–2009 financial crisis, the 2011–2013 conflicts in the Middle East and Africa, and the 2016–2017 regional political turmoil and Venezuelan migration. Economic classification tests confirm the association between instability, armed conflict, and heightened tourism and residency tendencies. Tourism income rises steadily, and residency averages increase, especially during periods of regional instability. The study highlights the tight link between tourism and migration with political, economic, and social instability. The statistical analysis reveals significant correlations, showing higher residency pressure during unstable periods. The applied tests confirm that countries in turmoil exhibit heightened tourism and migration tendencies.

The Bini people of Edo State, located in the Edo South senatorial district, have been the focus of a study investigating the impact of international migration on Nigerian infrastructure. The study employed a descriptive-qualitative approach, using a survey research methodology and structured questionnaires to gather data from 401 respondents. The study used regression and thematic analysis to examine the collected data, focusing on the connection between migration and the advancement of infrastructure. The findings suggest that low incomes, job insecurity, and the development of domestic infrastructure contribute to the momentum behind international migration movements. The study suggests that remittances from migrants and investments are needed to alleviate the situation, highlighting the need for a more inclusive and sustainable approach to addressing the challenges faced by the Bini people in Edo State.

The aim of this research is to determine the incidence of socioeconomic variables in migration flows from the main countries of origin that form part of the international South-North migration corridor, such as Mexico, China, India, and the Philippines, during the 1990–2022 period. The independent variables considered are GDP per capita, unemployment, poverty, higher education, and public health, while the dependent variable is migration flows. An econometric panel data model is implemented. The tests conducted indicate that all variables have an integration order of I (1) and exhibit long-term equilibrium. The econometric models used, Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS), reveal that unemployment and poverty had the strongest influence on migration flows. In both models, within this international migration corridor, GDP per capita, higher education, and health follow in order of importance.