Aurel Vlaicu University of Arad

Portable toilets provide essential sanitation for events and sites, benefiting people and the environment by conserving vital natural resources. The study aimed to assess the feasibility and accuracy of a wastewater-based epidemiological (WBE) monitoring tool derived from portable toilets. This study addresses a critical challenge for public health and the environment, the potential presence of SARS-CoV-2 in sanitary wastewater, and evaluates the biological load in sewage from portable toilets, addressing overlooked challenges in sanitation, sustainability, and waste management. Specifically, it investigates the rapid detection of SARS-CoV-2 antigens in wastewater samples collected from the tanks of portable toilets placed in three towns in western Romania. The results provide valuable insights into the potential role of wastewater surveillance in monitoring SARS-CoV-2 at the community level, especially in areas with limited access to traditional testing facilities. These findings emphasize the importance of integrating wastewater analysis into public health monitoring frameworks. However, the study also highlights the need for further research to confirm the presence and viability of SARS-CoV-2 in wastewater from portable toilets, including a detailed analysis of the viral load, its persistence, and the potential risk of fecal-oral transmission. The study also emphasizes the limitations of rapid antigen tests, especially in wastewater applications. It emphasizes validating these methods and developing robust protocols to ensure accurate and reliable detection, which are crucial for both immediate public health interventions and long-term strategies to prevent the spread of infectious diseases.

This study maps European countries' resilience to cognitive warfare by developing a cross-national composite measure. The framework integrates three pillars: information ecology, institutional-digital capacity, and socioeconomic context-drawing on a systemic perspective linking social structures to societal functions. Publicly available secondary indicators are compiled from online sources for EU (European Union) and EEA (European Economics Area) states. The dataset is examined through descriptive analysis, association testing, multivariate modelling, dimensionality reduction to derive a composite resilience score, and unsupervised clustering to produce a country typology. Indicators capture governance effectiveness, e-government maturity, public-sector AI (Artificial Intelligence) readiness, digital connectivity and infrastructure, media freedom and broader media-ecosystem quality, academic freedom, and socioeconomic vulnerabilities such as youth labour market exclusion. Results show that resilience aligns most strongly with institutional capacity and governance performance; a healthy ecology acts as a reinforcing layer. Digital infrastructure appears necessary but insufficient without capable, credible institutions and coherent public policy. Socioeconomic vulnerabilities tend to erode resilience and heighten susceptibility to hostile cognitive influence. The study concludes that policy efforts should prioritise governance integrity and effectiveness, end-to-end digital government, responsible public-sector AI capability, and safeguards for media and academic autonomy, alongside measures that improve youth inclusion.

The rapid expansion of artificial intelligence (AI) in higher education has intensified concerns regarding autonomy, control, and ethical engagement with digital technologies. While prior research has primarily addressed AI adoption through acceptance-and performance-oriented frameworks, less is known about how students' experiences of digital agency shape the psychological mechanisms underlying their intention to use AI. Grounded in digital agency theory and expectancy-value perspectives, the present study examines a moderated mediation model explaining students' intention to use AI in higher education. Using survey data from 673 university students, a conditional process analysis (PROCESS Model 59) was conducted to test whether sense of negative agency (SONA) predicts intention to use AI indirectly through perceived value of AI, and whether this pathway is conditioned by sense of positive agency (SOPA). Performance control was examined as a parallel mediator to assess the role of self-regulated learning mechanisms. Results revealed a significant moderated mediation effect. Specifically, perceived value of AI mediated the relationship between negative agency and intention to use AI only at moderate to high levels of positive agency. When SOPA was low, negative agency was unrelated to perceived value and intention. In contrast, at higher levels of SOPA, negative agency was positively associated with perceived value of AI, which in turn strongly predicted intention to use AI (b = .83, p < .001). Performance control did not emerge as a significant mediator, indicating that AI adoption decisions were not driven by self-regulated performance mechanisms. These findings suggest that students' engagement with AI is guided primarily by value-based cognitive evaluation rather than by performance regulation. Experiences of reduced control do not necessarily inhibit AI adoption; instead, when integrated through positive agency, they may foster reflective meaning-making and intentional AI use. The study highlights the ethical relevance of digital agency in AI adoption and underscores the importance of agency-aware approaches to AI integration in higher education.

The transition to a circular economy is a strategic direction of the European Union, and the agri-food sector is essential in this transformation through resource consumption, climate impact and an economic role in the food chain. This study analyses the relationship between the circularity of the economy and the sustainable performance of agri-food systems in the EU-27, using Eurostat data for the period of 2014-2023. Circularity is operationalised through a composite index built from the circularity of materials and resource productivity, aggregated through principal component analysis and complemented by an alternative measure based on the average of the standardised components. Sustainable performance is assessed through economic indicators (value added and output in agriculture, value added in the food industry), environmental indicators (greenhouse gas emissions from agriculture) and, complementary, energy indicators (energy intensity in the food industry), the latter being analysed separately on the available observations. The results do not indicate clear aggregate differences in sustainable performance associated with circularity measured at the macro level over the analysed period, underlining the importance of connecting circularity objectives with interventions and indications specific to the agri-food chain for monitoring and policy design at the EU level.

This study examines the relationship between early maladaptive schemas and attachment styles in emerging adulthood, within the theoretical frameworks of schema therapy (Young, 1990; Young et al., 2003) and attachment theory (Bowlby, 1969). Using a non-probabilistic sample of 170 participants (equally distributed by gender), Pearson correlation analyses revealed significant associations between schemas and attachment styles. Anxious attachment was positively correlated primarily with vulnerability, dependence, and subjugation, highlighting the role of threat anticipation and increased need for reassurance (Rad et al. (2025). Secure attachment was negatively correlated with strong negative correlations with defectiveness/shame, social isolation, failure, and vulnerability, confirming its protective function. Disorganised attachment was the most sensitive to schema activation, showing positive correlations with a broad spectrum of maladaptive patterns. Avoidant attachment was weakly associated with classical schemas and was modestly associated with unrelenting standards. Gender differences were observed primarily in attachment styles and vulnerability.