High operating temperatures are a major limitation for photovoltaic (PV) systems, as they reduce electrical efficiency and long-term reliability. Effective thermal regulation is therefore essential to maintain stable performance under strong solar irradiation. In this study, a numerical investigation is conducted to examine the thermal performance of a PV panel integrated with a paraffin-based cooling system positioned beneath the module. To improve the low thermal conductivity of paraffin, ternary nanoparticles together with metal foam are introduced into the phase change material (PCM). This hybrid enhancement significantly improves heat transfer, increases thermal diffusion, and accelerates the melting process. The transient melting behavior is modeled using the Galerkin finite element method, which ensures accurate prediction of temperature variation and phase change dynamics. The liquid fraction (LF) is increased by about 68.93%, indicating faster melting and improved energy absorption. In addition, the temperature distribution inside the PCM is enhanced by approximately 5.71%. Compared with a conventional uncooled PV system, the proposed configuration reduces the PV panel temperature ($T_{\mathrm{PV}}$) by 8.53%, while increasing electrical efficiency by 17.16%. Overall, the study demonstrates that combining ternary nanoparticles with metal foam inside PCM provides a strong synergistic cooling effect. This integrated approach offers a more effective thermal management strategy than traditional single-enhancement methods, leading to improved PV performance, higher efficiency, and better thermal stability under real operating conditions.

Driver drowsiness is one of the major reasons behind road accidents, emphasizing the need for accurate and efficient fatigue detection systems that can help monitor practical in-vehicle environments. While significant progress has been made in visual fatigue detection based on deep learning, many previous studies have been performed using a single dataset for training or controlled environments for testing. In this paper, we examine the reliability of lightweight driver-monitoring architectures for vision-based driver drowsiness detection based on three heterogeneous public datasets, i.e., Yawning Detection Dataset (YawDD), Driver Drowsiness Dataset (DDD), and National Tsing Hua University Drowsy Driving Dataset (NTHU-DDD), which cover different lighting conditions, facial characteristics, and head poses as encountered in driving scenarios. Among the considered architectures, Single Shot Detector (SSD)-MobileNetV2 was the most consistent, yielding an accuracy of 92%, precision of 93%, recall of 92%, and F1-score of 92% while also being computationally lighter than the other considered architectures. Reliability of the proposed architecture was statistically validated using the McNemar Test and 95% Confidence Intervals (CI). Our results show that SSD-MobileNetV2 could be a promising baseline for future lightweight driver-monitoring systems for heterogeneous driving environments.

Despite increasing attention to inclusive education, sustainability transitions under the Industry 5.0 paradigm remain constrained by the limited integration of socio-cultural barriers affecting marginalised groups. This study examines how harmful cultural practices (HCPs) and socio-economic conditions are associated with education access among 467 ethnic minority youth engaged in agri-startups, contributing theoretically by linking social norms and human capital perspectives within sustainability transition frameworks. A mixed-methods approach combining regression analysis and the Analytic Hierarchy Process (AHP) is employed to capture both statistical relationships and priority-setting mechanisms. The regression results indicate that early marriage (-0.171), gender bias (-0.199), and restrictive religious norms (-0.127) are associated with lower education access, while household income shows a significant positive association (0.722); the model is statistically significant with acceptable explanatory power (R² = 0.315; Adjusted R² = 0.280). The AHP results, based on expert evaluation, demonstrate consistent judgments (CR = 8.120%) and identify personal factors (0.341), particularly HCP awareness, as the highest priority, followed by socio-economic conditions (0.310), education and skills (0.212) and cultural–community factors (0.141). These findings suggest that although economic capacity is a dominant enabling factor, individual agency and behavioural change are critical for reducing harmful practices and improving access to education. However, education access reflects both actual and perceived opportunities due to infrastructural constraints in remote areas. Although the study is limited to data from marginalised youth in agri-startups, the findings highlight that education functions as a key enabling condition linking cultural transformation and livelihood improvement, offering policy-relevant insights for designing inclusive, human-centred education systems to support future-oriented Industry 5.0 transitions.

The aim of the submitted scientific article is to identify significant predictors of the sense of safety at the university and to compare their differences between the male and female populations of respondents. The empirical research was conducted in 2024 at Alexander Dubček University of Trenčín, with the participation of 358 respondents. Data were collected through an online questionnaire containing statements rated on a 5-point Likert scale, examining factors associated with informational influences, subjective concerns, and reflection on the Prague incident of December 2023. Descriptive statistics, correlation analysis, and multiple linear regression methods were used for analytical processing at a significance level of α = 0.05. The results showed that among women in this sample, the sense of safety was significantly associated with concerns about potential threats (X3) and the role of the incident at the Faculty of Arts of Charles University in Prague (X5). Among men in this sample, only factor X5 was confirmed as a key determinant, with its association being stronger than in women. Correlation analysis also indicated different patterns of perception—female respondents in this sample showed a higher sensitivity to subjective concerns, whereas male respondents in this sample appeared to respond more strongly to external security events. These findings confirm the importance of gender differences in shaping the sense of safety in the academic environment and highlight the need for targeted communication and security measures on the part of universities.

Renewable Energy Communities (RECs) are increasingly recognized as decentralized energy systems capable of improving renewable energy integration, enhancing local self-consumption, and supporting the transition toward low-carbon energy infrastructures. However, the effective deployment of RECs still faces significant challenges related to the integration of spatial analysis, energy modelling, operational optimization, and socio-economic assessment within a unified framework. This study investigates an integrated multi-objective framework for the design, evaluation, and operational support of RECs through the combination of geospatial analysis, energy performance modelling, and digital decision-support tools developed within the ENEA Smart Energy Communities (SEC) platform. The proposed methodology was developed by integrating spatially explicit territorial datasets, renewable resource assessments, electricity demand profiles, and multidimensional key performance indicators (KPIs) within a coordinated analytical framework. Three complementary tools were implemented and evaluated: the geoCER geoportal for territorial-scale renewable energy planning and REC scenario modelling, the DHOMUS platform for residential load monitoring and self-consumption optimization, and the Local Token Economy (LTE) system for token-based user engagement and energy-aware behavioral incentives. The results showed that the integrated framework effectively supported the assessment of REC configurations under different territorial and operational conditions. In the Anguillara Sabazia case study, the REC configuration increased the Self-Consumption Index (SCI) from 30% to 65% and the Self-Sufficiency Index from 36% to 79%, while reducing the Energy Surplus Index from 70% to 35%. In the Sardinia case study, the scenario-based analysis demonstrated that renewable energy integration and coordinated energy sharing significantly improved territorial self-sufficiency under optimized REC configurations. The geospatial modelling approach also enabled the identification of suitable renewable deployment scenarios while considering environmental and territorial constraints. The results indicate that the integration of energy modelling, digital monitoring systems, and spatially explicit planning tools provides an effective pathway for improving the operational performance, flexibility, and scalability of RECs. The proposed framework offers practical support for decentralized energy planning, distributed renewable energy management, and data-driven decision-making processes in future community-based energy systems.

This study addresses the growing role of Renewable Energy Communities (RECs) in supporting decentralized renewable energy integration and improving local energy self-sufficiency within the European energy transition framework. The work aimed to evaluate the technical and economic feasibility of a municipal REC in Pattada, a small municipality located in Sardinia, Italy, through an energy balance analysis based on distributed photovoltaic generation and shared electricity consumption. A techno-economic assessment framework was developed by combining the estimated electricity production of municipally owned photovoltaic systems with the load profiles of municipal, commercial, and residential users participating in the REC. The photovoltaic energy production was estimated using the Photovoltaic Geographical Information System (PVGIS) simulation platform, while the shared energy within the REC was evaluated by considering the simultaneity between electricity generation and demand under different residential participation scenarios. The results showed that the municipal photovoltaic systems achieved an annual electricity production of approximately 506.41 MWh, while direct physical self-consumption remained limited to 3.10 MWh/year due to the mismatch between municipal demand and photovoltaic generation profiles. The analysis further showed that the REC reached an energy equilibrium condition with the participation of 285 residential users, corresponding to nearly 23% of the households within the municipality, allowing virtually shared energy to reach 425.92 MWh/year. The economic evaluation demonstrated that the municipal administration obtained the highest share of the overall economic return, mainly driven by electricity exported to the grid and incentive revenues associated with shared energy. The results indicate that the integration of municipally owned photovoltaic systems within REC configurations provides an effective approach for improving local energy sharing and enhancing the economic viability of distributed renewable energy systems in small municipalities. The proposed framework offers practical support for local administrations in planning renewable energy investments and optimizing REC configurations under real operating conditions.