Search Results (1,806)

Recent discussions on the future of European Union governance highlight a growing emphasis on integrated policy frameworks that align agricultural, territorial, and socio-economic development objectives within unified strategic planning systems. One of the proposed innovations for the next EU programming period is the introduction of National and Regional Partnership Plans (NRPPs), which aim to coordinate several EU funding instruments within a single national planning framework. This article explores stakeholder perspectives on the development of integrated policy planning in this context. The analysis is guided by analytical propositions derived from the literature on policy integration and multi-level governance, focusing on how stakeholder interpretations influence strategic priority alignment, perceived policy trade-offs, and governance coordination capacity. The study is based on a qualitative focus group discussion involving policy stakeholders, researchers, and institutional representatives in Lithuania. Using thematic analysis, the study examines how stakeholders interpret integrated planning concepts, identify strategic priorities, and assess governance challenges associated with policy integration. The findings reveal three key issues shaping stakeholder perspectives. First, conceptual ambiguity surrounding strategic priorities such as competitiveness, regional vitality, and sustainability may complicate policy coordination. Second, perceived conflicts between economic competitiveness and environmental sustainability may be less pronounced than often assumed. Third, the implementation of integrated policy frameworks requires stronger governance capacity, including improved cross-ministerial coordination and shared monitoring systems. The article contributes to research on policy integration and multi-level governance by providing empirical evidence on how policy actors interpret integrated strategic planning frameworks and how these interpretations shape perceptions of governance capacity, policy trade-offs, and stakeholder participation in EU funding reforms. Full article

As a member state of the European Union, Bulgaria is committed to decarbonisation and the achievement of sustainable development goals. The country has a well-established energy sector and is a net exporter of electricity produced from diverse sources. Electricity generation relies mainly on two key pillars: lignite-fired Thermal Power Plants (TPPs) and the Nuclear Power Plant (NPP) in Kozloduy. This study examines the status of Bulgarian state-owned energy companies (SOEC) and their capacity to respond to the challenges of a sustainable transition towards low- or zero-emission electricity production. The study contributes to the existing literature by providing insights from a comparative analysis of state-owned thermal and nuclear power generation in Bulgaria, examined through the lens of sustainable development. From a practical standpoint it contributes by outlining possible pathways for the sustainable transformation of carbon-intensive TPPs. The analy-sis is based on key sustainability indicators covering the three pillars of sustainable development—economic, social and environmental performance. It includes not only an assessment of the financial performance of state-owned thermal power plants and the nuclear power plant over the past five years but also selected social and environmental indicators. The findings suggest that nuclear energy production in Bulgaria is largely consistent with the core principles of sustainability, while coal-based thermal power plants face increasing economic pressures and contribute to significant environmental impacts. The results highlight the need to transform the coal-based electricity sector into a more economically viable and socially responsible alternative, such as low-carbon generation technologies including nuclear energy. Full article

The transition to renewable energy is a central objective of the European Union’s energy and climate policies, yet adoption rates differ significantly across Member States. This study analyses the economic, structural, and energy determinants of renewable energy adoption in the EU-27 over the period 2008–2023, using panel data models with country and year fixed effects and clustered standard errors. The results indicate that the relationship between renewable energy and its main determinants is limited and heterogeneous across countries. Most explanatory variables do not exhibit consistent and statistically significant effects across model specifications. In particular, research and development expenditure does not show a robust impact, while GDP per capita is associated with negative coefficients in several specifications, suggesting the presence of structural constraints and path dependency. Energy-related variables also display weak and unstable relationships. The findings suggest that renewable energy adoption is shaped by context-specific and heterogeneous dynamics rather than by uniform drivers. The study contributes by highlighting the limited explanatory power of standard macroeconomic indicators and supports the need for differentiated policy approaches across Member States. Full article

Buildings represent 40% of the European Union’s energy consumption and 36% of its greenhouse gas emissions. Nursing homes are among the buildings that consume the most energy. The objective of this study was to make predictive models of Energy Consumption, Energy Costs, and CO₂ Emissions in nursing homes using different variables. To do this, data from 20 public nursing homes located in Extremadura (Spain) during the 2019–2023 period were analyzed. All the buildings were built or renovated between 1995 and 2009; the useful area and the number of residents were in the range of 1332–10,880 m² and 24–254 residents. A statistical analysis was performed using multivariable linear regression. During the research, equations that allow for the estimation of the annual Energy Consumption, Energy Costs and CO₂ Emissions of nursing homes, according to the useful area and number of residents, were found. The R_adj² was 0.9710, 0.9744 and 0.9742, respectively. The quality of the models obtained was contrasted using the mean absolute error (MAE), the relative error (RE) and the root mean square error (RMSE), together with the assessment of multicollinearity through the Variance Inflation Factor (VIF). The findings of this study may prove beneficial for stakeholders within the elder care sector. Full article

Sustainable development is a core objective of European Union (EU) policy, making energy transition performance a key analytical and policy issue. This article examines the role of energy and the energy sector in Poland’s sustainable development through an indicator-based empirical assessment for 2010–2024 in a comparative EU context. In addition to the national analysis, Poland’s trajectories are positioned against the EU-27 average and selected Central and Eastern European (CEE) economies in order to assess whether the observed changes represent relative progress, convergence, or persistent lagging. The study combines a harmonised indicator framework with formal trend tests, structural-break analysis, a simplified additive LMDI decomposition, and exploratory cross-indicator analysis. The results show strong improvement in macro-level energy efficiency, continued growth in the renewable-energy share, and a reduction in the emissions intensity of energy use, while also revealing an asymmetric transition pattern in which transport remains less stable and energy self-reliance declines. From a comparative perspective, Poland performs relatively strongly in economy-wide, energy-efficiency improvement, but less favourably in renewable-energy deployment than the EU-27 average and the selected CEE comparators. Overall, the findings point to measurable progress in efficiency and decarbonisation alongside persistent tensions between sectoral adjustment, renewable energy expansion, and energy security. Full article

This study investigates the direct impact of financial repression on economic growth in the Central African Economic and Monetary Community (CEMAC) and the West African Economic and Monetary Union (UEMOA) using a lagged composite repression index and panel fixed-effects regressions. Contrary to theoretical expectations, lagged repression exhibits a significantly positive association with GDP growth in the main model, with robustness checks confirming no negative direct effect. The findings suggest that in pegged currency unions, repression may support growth through public channels or forced savings, offsetting private crowding-out, while capital formation remains a key driver. This effect, contrasting with repression’s negative impact on investment, highlights union-specific resilience and calls for calibrated reforms to balance stability with deepening. Full article

In this paper, an intelligent localization framework based on deep learning is proposed to address the limitations of insufficient accuracy and robustness in defect identification and localization during the ultrasonic guided-wave non-destructive testing (NDT) of receiver tubes in tower-type molten salt Concentrated Solar Power (CSP) stations. In the proposed method, a 1D convolutional neural network (1D-CNN) initially processes raw time-series-guided wave signals, achieving coarse identification and preliminary localization of defective segments. Then, Mel spectrograms are employed to exploit multi-dimensional features in the time–frequency domain and transform 1D signals into 2D representations, thereby enriching feature diversity. A regression-based 2D-CNN was designed to predict the start and end points of defect segments, enabling precise interval localization. Furthermore, the Tree Seed Algorithm (TSA) was integrated to jointly optimize key hyperparameters, enhancing training efficiency and prediction accuracy. Experimental validation on a dataset of ultrasonic guided-wave signals from molten salt receiver tubes demonstrates that the TSA-optimized Mel+2D-CNN model achieves superior performance, with a Mean Absolute Error (MAE) of 75.11 sampling points and a Coefficient of Determination (R²) of 0.90. At an Intersection over Union (IoU) threshold of 0.3, the model achieves a hit rate of 89.21%, exhibiting significantly higher localization accuracy and stability compared to the 1D-CNN baseline model. These findings indicate that the proposed method effectively enhances the accuracy and robustness of guided wave-based defect localization in slender structures. While promising, the model’s generalization capability remains dependent on the data distribution and operating conditions; future work will focus on validating its engineering applicability across diverse, multi-scenario industrial environments. Full article

Livestock farming represents a key economic activity in the Tataouine Governorate of southern Tunisia, where cattle and dromedary camels coexist. Varicellovirus bovinealpha1 (BoAHV-1), the etiological agent of infectious bovine rhinotracheitis (IBR), primarily affects cattle, while its circulation in camelids remains poorly understood. Following recent European Union regulations requiring BoAHV-1 surveillance in multiple animal species, this short communication reports serological findings from dairy cattle and dromedary herds in southern Tunisia. In March 2024, serum samples were collected from four non-vaccinated farms, including two intensive Friesian dairy cattle herds and two extensive dromedary herds (50 animals each). Serum samples from all animals were tested for BoAHV-1 antibodies using competitive commercial gB- and gE-based enzyme-linked immunosorbent assays (c-ELISA) and confirmed by virus neutralization test (VNT). Antibodies against BoAHV-1 were detected in cattle from both dairy farms, with low seroprevalence and neutralizing antibody titers, indicating past or ongoing exposure. In contrast, all dromedary samples tested seronegative by both c-ELISA and VNT. These findings confirm BoAHV-1 circulation in cattle in the Tataouine region and its absence in dromedaries at sampling. Further studies involving larger sample sizes and molecular investigations are required to clarify the potential role of camelids in BoAHV-1 epidemiology in southern Tunisia. Full article

This study examines whether fiscal decentralization operates as a strategic macroeconomic risk-management instrument and whether its effectiveness depends on institutional quality. Using a balanced panel of 27 European Union member states over 2008–2023, a composite fiscal decentralization index combining expenditure and revenue autonomy is constructed, and a dynamic specification is estimated using a two-step System-GMM estimator. Output volatility is measured as a five-year rolling standard deviation of real GDP growth. The results indicate that fiscal decentralization exhibits a statistically significant effect on volatility whose direction depends on governance quality. Institutional quality directly reduces volatility, and the interaction between decentralization and institutional quality is negative and highly significant. A critical institutional threshold of 1.865 (WGI estimate scale), above which decentralization reduces output volatility, is identified. These findings indicate that decentralization functions as a conditional risk-management mechanism embedded within institutional capacity. The results provide policy-relevant insights into EU fiscal architecture design in an era of recurrent macroeconomic shocks. Full article

This study examines the association between tourism intensity, the free movement of people, and water quality outcomes across the European Union (EU-27) over the period 2012–2024. By integrating open-access datasets from Eurostat, the European Environment Agency (EEA), and the EXIOBASE input–output framework, the analysis estimates the direct (blue), indirect, and grey components of the tourism-related water footprint and explores their relationship with bathing water quality indicators using panel econometric models. The results indicate that tourism activity increased substantially during the study period, while the share of bathing waters classified as “excellent” also improved. The findings further show that the gray water footprint is strongly associated with variations in water quality, whereas higher wastewater treatment coverage is positively associated with improved environmental outcomes. These results highlight the importance of wastewater management and governance capacity in moderating the relationship between tourism and water quality across diverse European contexts. We find that tourism activity rose by approximately 28% during the study period; yet, through improvements in wastewater treatment infrastructure and governance, the share of bathing waters rated “excellent” also increased. Notably, the grey water footprint emerged as the strongest predictor of water quality deterioration, while wastewater treatment coverage significantly mitigated negative impacts. Comparative case studies of Spain, Greece, Croatia and Romania highlight how institutional and technological capacity are associated with differences in tourism–water relationships across diverse hydro-climatic contexts. Our findings underscore that sustainable tourism in Europe is less a matter of visitor numbers and more a question of effective water management systems. The study supports a policy shift towards integrated water-tourism planning and circular water-use strategies to support more sustainable management of tourism-related environmental pressures. Full article

Security and stability constitute fundamental preconditions for long-term sustainable development. Russia’s aggression against Ukraine and the return of high-intensity interstate warfare to Europe have profoundly transformed the European security environment and challenged long-standing assumptions underpinning European integration and economic development. This article analyses the ongoing transformation of European security with particular attention to industrial resilience, the evolution of the defence technological and industrial base, and the expanding institutional role of the European Union in strengthening strategic autonomy. Using a qualitative analytical approach based on the examination of strategic documents, policy initiatives, and academic literature, the study identifies structural weaknesses in Europe’s defence-industrial system and evaluates recent institutional and financial responses aimed at enhancing resilience and sustainability. The findings demonstrate that security, industrial capacity, and institutional adaptation are increasingly interconnected, and that strengthening resilience and reducing strategic dependencies are essential conditions for Europe’s long-term sustainable development in an unstable geopolitical environment. Full article

Monitoring progress toward Sustainable Development Goal 8 (SDG 8) requires analytical tools that enable flexible and transparent assessment of multiple indicators. However, existing monitoring approaches are usually based on predefined indicator sets and static analytical frameworks, which limit their adaptability. This study develops and demonstrates a computer-assisted system for monitoring SDG 8 achievement. The system integrates automatic data retrieval from Eurostat, flexible selection of indicators, countries, and years, procedures for handling missing data, and alternative options for constructing a synthetic index. The system was tested in an illustrative case study for European Union countries using Eurostat data for 2015–2023. The empirical application initially covered 19 indicators (11 core SDG 8 indicators and 8 supplementary indicators) for 27 EU countries, while the final analytical sample included 24 countries after data-based exclusions. The results showed substantial differences in SDG 8 achievement trajectories across countries: some countries maintained relatively stable high positions over time (e.g., Italy, Estonia, Germany, and Austria), whereas others recorded marked improvement (e.g., Ireland, Denmark, Cyprus, Lithuania, and Latvia). These findings confirm the practical usefulness of the proposed tool for data processing, comparative assessment, and evidence-informed monitoring of SDG 8 progress. Full article

This study aimed to estimate life expectancy at birth and survival patterns within a multigenerational family from Romania (102 individuals), whose members lived across the period 1900–2024. Life expectancy was estimated using abridged synthetic cohort life tables, and the results were interpreted through survival curve analysis. Life expectancy at birth was estimated at approximately 84 years for females and 80 years for males, while the overall life expectancy for the total family population was 81 years, representing a weighted estimate derived from sex-specific life tables, with weights corresponding to the proportion of females and males in the studied population, rather than a simple arithmetic mean, following standard demographic practice. The resulting survival curves exhibited a clear Type I survival pattern, characterized by low mortality at younger ages and an increasing concentration of deaths at older ages. When contextualized using recent Eurostat data, the life expectancy estimated for the analyzed family exceeds current national-level values reported for Romania and is close to the European Union average, particularly for females. These findings indicate a favorable survival profile at the familial level and illustrate the usefulness of life tables for investigating longevity patterns in small populations. Full article

This study investigates the determinants of GDP per capita across 26 European Union member states over the period of 2006–2024, with a particular focus on entrepreneurship, institutional quality, and macroeconomic factors. Given the presence of long-run income differences across EU countries, the analysis explicitly accounts for structural heterogeneity in economic development and institutional capacity. To ensure robust estimation in the presence of cross-sectional dependence and slope heterogeneity, the study employs advanced panel econometric techniques, including tests for cross-sectional dependence, unit roots, and cointegration. Long-run relationships and short-run dynamics are estimated using the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model, complemented by robustness checks based on the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators. In addition, the Method of Moments Quantile Regression (MMQR) is applied to capture heterogeneity across different points of the income distribution, thereby reflecting long-run income disparities among EU member states. The empirical results confirm the existence of a stable long-run equilibrium relationship among the variables. The baseline CS-ARDL estimates indicate that institutional quality, entrepreneurial activity, trade openness, and government expenditure exert positive and statistically significant effects on GDP per capita, while financial development exhibits a negative effect and foreign direct investment remains insignificant. In the short run, entrepreneurship and trade openness contribute positively to GDP per capita, whereas government expenditure and credit expansion generate contractionary effects. The robustness analysis using AMG and CCEMG estimators largely supports these findings, as the direction of the coefficients remains consistent across alternative specifications, although some variation in statistical significance is observed due to differences in the treatment of cross-sectional dependence and unobserved common factors. The MMQR results further reveal substantial heterogeneity across the income distribution, indicating that the effects of key determinants vary depending on countries’ long-run income levels. In particular, trade openness and institutional quality exert stronger positive effects in lower-income quantiles, while the adverse effects of excessive financial development are more pronounced in higher-income quantiles. Overall, the findings underscore the importance of promoting productive entrepreneurship, strengthening institutional frameworks, facilitating trade integration, and ensuring efficient financial intermediation to enhance GDP per capita within the European Union. The results also highlight the need for differentiated policy approaches that explicitly account for long-run income heterogeneity, structural differences, and varying institutional capacities across EU member states. Full article

Mangrove represent vital coastal ecosystems that contribute to shoreline stabilization, ecological balance, and environmental management. Nevertheless, the precise delineation of mangrove regions using remote sensing data is often impeded by spectral similarities with intertidal mudflats and aquatic features, alongside the irregular spatial patterns and intricate margins of mangrove stands. This research utilizes high-resolution Gaofen-6 (GF-6) satellite observations as the foundational data to develop Triplet Axial High-Resolution Network (TAHRNet), a semantic segmentation architecture derived from the High-Resolution Network with Object-Contextual Representations (HRNet-OCR) framework for mangrove identification. The model integrates a Triplet Attention module to facilitate cross-dimensional feature dependencies and an improved Multi-Head Sequential Axial Attention mechanism to capture long-range spatial context while maintaining structural consistency. Based on evaluations using the test dataset, TAHRNet yielded a Mean Intersection over Union (MIoU) of 92.01% and a Overall Accuracy of 96.38%. Relative to U-Net and SegFormer, the proposed approach showed MIoU improvements of 5.25% and 1.88%, with corresponding Accuracy gains of 2.68% and 0.94%. Further application to coastal mapping in Zhanjiang produced results that align with manual visual interpretation. These findings suggest that TAHRNet is a viable tool for mangrove extraction and can provide technical support for coastal monitoring and ecological analysis. Full article