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This study explores public perceptions, involvement, and barriers to energy communities in Romania, a country where decentralized renewable energy initiatives are still in their infancy. Data were collected through a nationwide online survey based on a quantitative research design, involving 118 respondents from all four macro-regions in Romania. The survey assessed awareness of the concept of energy communities, perceived benefits, technological and regulatory challenges, and willingness to participate or invest. The results show that the perception of energy communities is generally positive, with solar and environmental benefits being the most important. However, significant barriers remain, particularly in terms of financing, institutional support, and regulatory complexity. Urban, involved, and female respondents consistently rated benefits higher and identified more barriers than rural, non-participants and male respondents. Statistical differences between groups were confirmed using the Mann–Whitney U-test. These results highlight the importance of targeted communication, improved policy frameworks, and educational initiatives to ensure broader public involvement and inclusive development of renewable energy systems in Romania.

This study is the result of the need to research the visualization of brainwaves. The aim is based on the idea of using generative AI art systems as a method. Data visualization is an important part of understanding the evolution of the world around us. It offers the ability to see a representation that goes beyond numbers. Generative AI systems have gained the possibility of helping the process of visualizing data in new ways. This specific process includes real-time-generated artistic renderings of these data. This real-time rendering falls into the field of brainwave visualization, with the help of the EEG (electroencephalogram), which can serve here as input data for Generative AI systems. The brainwave measurement technology as a form of input to real-time generative AI systems represents a novel intersection of neuroscience and art in the field of neurofeedback art. The main question this paper hopes to address is as follows: How can brainwaves be effectively fed into generative AI art systems, and where can the outcome lead, in terms of progress? EEG data were successfully integrated with generative AI to create interactive art. The installation provided an immersive experience by moving the image with the change in the user’s mental focus, demonstrating the impact of EEG-based art.

Background: Peripheral nerve injuries (PNIs) represent a significant clinical problem, and standard approaches to nerve repair have limitations. Recent breakthroughs in 3D printing and stem cell technologies offer a promising solution for nerve regeneration. The main purpose of this study was to examine the biomechanical characteristics in muscle tissue distal to a nerve defect in a murine model of peripheral nerve regeneration from physiological stress to failure. Methods: In this experimental study, we enrolled 18 Wistar rats in which we created a 10 mm sciatic nerve defect. Furthermore, we divided them into three groups as follows: in Group 1, we used 3D nerve guidance conduits (NGCs) and adipose stem cells (ASCs) in seven rats; in Group 2, we used only 3D NGCs for seven rats; and in Group 3, we created only the defect in four rats. We monitored the degree of atrophy at 4, 8, and 12 weeks by measuring the diameter of the tibialis anterior (TA) muscle. At the end of 12 weeks, we took the TA muscle and analyzed it uniaxially at 10% stretch until failure. Results: In the group of animals with 3D NGCs and ASCs, we recorded the lowest degree of atrophy at 4 weeks, 8 weeks, and 12 weeks after nerve reconstruction. At 10% stretch, the control group had the highest Cauchy stress values compared to the 3D NGC group (0.164 MPa vs. 0.141 MPa, p = 0.007) and the 3D NGC + ASC group (0.164 MPa vs. 0.123 MPa, p = 0.007). In addition, we found that the control group (1.763 MPa) had the highest TA muscle stiffness, followed by the 3D NGC group (1.412 MPa), with the best muscle elasticity showing in the group in which we used 3D NGC + ASC (1.147 MPa). At failure, TA muscle samples from the 3D NGC + ASC group demonstrated better compliance and a higher degree of elasticity compared to the other two groups (p = 0.002 and p = 0.008). Conclusions: Our study demonstrates that the combination of 3D NGC and ASC increases the process of nerve regeneration and significantly improves the compliance and mechanical characteristics of muscle tissue distal to the injury site in a PNI murine model.