Soil salinization is a difficult challenge for agricultural productivity and environmental sustainability, particularly in arid and semi-arid coastal regions. This study investigates the spatial variability of soil electrical conductivity (EC) and its relationship with key cations and anions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, CO₃²⁻, HCO₃⁻, SO₄²⁻) along the southeastern coast of the Caspian Sea in Iran. Using a combination of field-based soil sampling, laboratory analyses, and Landsat 8 spectral data, linear Multiple Linear Regression and Partial Least Squares Regression (MLR, PLSR) and nonlinear Artifician Neural Network and Support Vector Machine (ANN, SVM) modeling approaches were employed to estimate and map soil EC. Results identified Na⁺ and Cl⁻ as the primary contributors to salinity (r = 0.78 and r = 0.88, respectively), with NaCl salts dominating the region’s soil salinity dynamics. Secondary contributions from Potassium Chloride KCl and Magnesium Chloride MgCl₂ were also observed. Coastal landforms such as lagoon relicts and coastal plains exhibited the highest salinity levels, attributed to geomorphic processes and anthropogenic activities. Among the predictive models, the SVM algorithm outperformed others, achieving higher R² values and lower RMSE (RMSE_Test = 27.35 and RMSE_Train = 24.62, respectively), underscoring its effectiveness in capturing complex soil-environment interactions. This study highlights the utility of digital soil mapping (DSM) for assessing soil salinity and provides actionable insights for sustainable land management, particularly in mitigating salinity and enhancing agricultural practices in vulnerable coastal systems.

In recent years, enological tourism, also known as wine tourism, has emerged as a globally popular tourism product. The role of wine tourism in Slovakia is similarly significant, given the country’s favourable conditions for the development of wine tourism products. The objective of this study is to analyze the current demand for wine-themed experiences among tourists in the Nitra region. This paper presents a characterization of wine tourism based on an analysis of secondary sources. Following the processing of the initial findings from a demand-oriented questionnaire survey, the authors endeavor to delineate the profile of the wine tourism visitor by examining the demand for wine tourism from the vantage point of domestic consumers. It is the authors’ contention that an understanding of the profile of the wine tourism visitor is beneficial in optimising the provision of wine tourism products and stimulating the development of tourism infrastructure.

This study explores the determinants of control loss in eating behaviors, employing decision tree regression analysis on a sample of 558 participants. Guided by Self-Determination Theory, the findings highlight amotivation (β = 0.48, p < 0.001) and external regulation (β = 0.36, p < 0.01) as primary predictors of control loss, with introjected regulation also playing a significant role (β = 0.24, p < 0.05). Consistent with Self-Determination Theory, the results emphasize the critical role of autonomous motivation and its deficits in shaping self-regulation. Physical characteristics, such as age and weight, exhibited limited predictive power (β = 0.12, p = 0.08). The decision tree model demonstrated reliability in explaining eating behavior patterns, achieving an R² value of 0.39, with a standard deviation of 0.11. These results underline the importance of addressing motivational deficits in designing interventions aimed at improving self-regulation and promoting healthier eating behaviors.

This study delves into the dynamic landscape of pension funds in Colombia, examining both its current research status and practical implications. Understanding the state of pension systems is crucial for individuals' financial security and a country's overall economic stability, especially given factors such as an aging population and evolving socio-economic dynamics. By comprehensively analyzing scholarly publications on Colombian pension funds using the Scopus database, this research sheds light on key trends and contributors shaping policy formulation and financial planning. The analysis covers a period from 1987 to 2023, identifying 71 relevant articles through keyword searches and filters. Various metrics, including publication trends, citations, international collaboration, and authorship dynamics, were quantitatively assessed. The results reveal an annual growth rate of 5.37%, with research articles comprising 81.69%, review articles 7.04%, and other formats like books, book chapters, and conference papers making up 11.27% of the total documents. Notably, countries such as the UK, the USA, Spain, and Colombia emerge as key contributors to the literature. Among authors, Mesa-Lago, L., stands out as a significant figure, with one of the earliest publications on the topic. The findings underscore the growing importance of pension funds in Colombia, particularly in the context of fund performance research amid financial crises. The prevalence of international collaboration suggests a global interest in understanding and contributing to the development of Colombian pension systems. Furthermore, the study identifies research gaps, particularly in areas concerning the socio-economic impact of pension policies, providing a roadmap for future investigations. Policymakers, financial practitioners, and researchers can leverage these insights to inform strategic decision-making and address critical challenges in optimizing pension fund management in Colombia.

New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.