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  An Environmental Psychology Model of Sustainability in Sport: The Roles of Sustainability Consciousness, Environmental Awareness, and Personal Social Responsibility

  (FRONTIERS MEDIA SA, AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2026) Karaoğlu, Barış; Usuflu, Oğulcan; Genç, Harun; Pepe, Bilgehan; Koçyiğit, Berat; Turan, Mehmet Behzat; Dalbudak, İbrahim; Pepe, Osman

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  Background: Understanding the psychological processes associated with sustainable behavior has become a major focus of environmental psychology. Although sustainability consciousness is generally associated with environmentally responsible behavior, the psychological processes underlying this association in sport remain insufficiently understood, particularly among sport science students. Therefore, the present study examined the serial mediating roles of environmental awareness and personal social responsibility in the association between sustainability consciousness and sustainability in sport. Methods: A cross-sectional correlational design was employed. The study included 521 undergraduate students enrolled in Faculties of Sport Sciences at six universities in Türkiye during the 2025–2026 academic year. Participants completed the sustainability consciousness scale, environmental awareness scale, personal social responsibility scale, and sustainability in sport scale. Serial mediation analysis was performed using Hayes’ PROCESS Macro (Model 6) with 5,000 bootstrap resamples. Prior to hypothesis testing, the assumptions required for regression analyses, including normality, multicollinearity, and the absence of influential cases, were examined and found to be satisfactory. Results: Sustainability consciousness was positively associated with environmental awareness, personal social responsibility, and sustainability in sport. Multiple regression analyses indicated that sustainability consciousness was positively associated with sustainability in sport. The serial mediation analysis further showed that sustainability consciousness was positively associated with environmental awareness and personal social responsibility, environmental awareness was positively associated with personal social responsibility, and both environmental awareness and personal social responsibility were positively associated with sustainability in sport. The direct association between sustainability consciousness and sustainability in sport remained statistically significant after accounting for the proposed mediators, suggesting partial mediation. Bootstrap analyses further indicated statistically significant indirect associations involving environmental awareness, personal social responsibility, and the sequential pathway including both constructs, as none of the 95% bootstrap confidence intervals included zero. These findings support the proposed serial mediation model as a theoretically informed pattern of statistical associations rather than evidence of causal mediation. Conclusion: The findings suggest that sustainability consciousness, environmental awareness, personal social responsibility, and sustainability in sport are statistically associated in a manner consistent with the proposed environmental psychology framework. By examining these constructs within a serial mediation model, the present study contributes to the environmental psychology literature by providing a theoretically grounded perspective on the statistical associations underlying sustainability-related orientations within the sport context. The findings also have practical implications for the development of sustainability education and environmental responsibility initiatives within Faculties of Sport Sciences and provide a foundation for future longitudinal and experimental research examining these associations.

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  Political Efficacy Among Rural Women: a Multidimensional Analysis of Empowerment, Social Capital, and Institutional Engagement

  (FRONTIERS MEDIA SA, AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2026) Kariveliparambil Mohammed Ashraf, Ashifa; Varghese, Neethu; Ranganathan, Maharishi; Babu, Jobi; Saravanan, K.; Philip, Sheena Rajan

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  Introduction: Political efficacy is a key determinant of democratic participation; however, it remains unevenly distributed, particularly among rural women in India. Existing research has largely emphasized sociodemographic predictors, with limited attention to the combined associations of sociocultural, relational, digital, and institutional factors on political efficacy. This study addresses this gap by adopting a multidimensional framework to examine the determinants of political efficacy among rural women in India. Methods: A quantitative cross-sectional design was employed using data from 394 rural women in Kerala. Data were obtained through a structured questionnaire administered online (Google Forms) and in person (face-to-face). Political efficacy, gender norms, household decision-making power, social capital, digital engagement, and institutional exposure were also assessed. The incremental contribution of the predictors was measured using hierarchical multiple regression analysis. Results: Sociodemographic variables were significant in the baseline model but no longer significant in the fully adjusted model. In contrast, gender norms and the power to make household decisions were strong and reliable predictors of political efficacy in this study. Social capital and digital engagement contributed additional explanatory power, whereas institutional exposure had a significant independent effect in the final model. The full model accounted for 42% of the variance in political efficacy. Discussion: The findings indicate that political efficacy is more strongly associated with sociocultural, relational, digital, and institutional factors than with the sociodemographic characteristics included in the analysis. The findings further suggest that gender norms, household agency, social capital, digital engagement, and institutional exposure should be considered together when developing policies and programs to support women’s political efficacy.

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  Techno-Economic Assessment of Large-Scale 700-Bar Type IV Hydrogen Storage Tank Manufacturing: Cost Drivers, Production-Scale Effects, and Industrial Implications

  (PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, 2026) Oktay, Zuhal; Coşkun, Can; İnanır, Fedai; Erdoğan, Muzaffer; Yıldız, Şükrü; Erbayrak, Engin; Oktay, Alperen

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  The commercialization of hydrogen energy systems requires cost-effective and scalable manufacturing of highpressure composite storage tanks. This study develops a bottom-up techno-economic framework for industrialscale 700-bar Type IV hydrogen storage tank manufacturing, integrating manufacturing costs, production capacity, capital investment, operating expenditure, and sensitivity analysis. Six tank configurations with hydrogen storage capacities of 0.9996–6.9203 kg were evaluated. Manufacturing cost per kilogram of stored hydrogen decreased with increasing tank capacity, primarily due to improved material utilization. Carbon fiber composites dominated manufacturing costs, while a ±30% variation in raw material prices caused cost changes of up to ±19.6%. A fixed-configuration analysis using the 103-L tank isolated production-scale from tank-size effects. Increasing production from 25,000 to 100,000 tanks/year reduced unit manufacturing cost by 36.2%, whereas expansion to 113,390 tanks/year provided only an additional 2.2% reduction. These results identify an economic production threshold of 100,000 tanks/year, beyond which further expansion provides limited cost benefits.

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  Toward Evidence-Based Neuroarchitecture: a Systematic Mapping and Framework for Immersive Spatial Cognition

  (FRONTIERS MEDIA SA, AVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2026) Yılmaz, Ezgi; Akkam, Mehmet Sair; Sedes, Fatma

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  Neuroarchitecture has developed rapidly at the intersection of architecture, environmental cognition, neuroscience, and immersive technologies, yet the field remains methodologically heterogeneous and its progression from measurement toward design application is insufficiently structured. This study addresses this gap through a PRISMA 2020-compliant systematic mapping review of neuroarchitecture and closely related architectural and spatial-cognition research published between 2015 and 2025. Expanded searches across Scopus and Web of Science Core Collection identified 510 records. After removal of 206 duplicates, 304 unique records were screened; 125 records entered the final eligibility and data-extraction audit, and four additional boundary or temporal exclusions resulted in a final corpus of 121 studies. The corpus comprised 61 human empirical studies, one non-human empirical study, 58 review or conceptual synthesis records, and one methodological/protocol record. Publication activity increased markedly in the later review period, with 81 studies (66.9%) published between 2023 and 2025. Among the 61 human empirical studies, questionnaire/self-report measures were used in 39 studies (63.9%), behavioral task/performance measures in 32 (52.5%), EEG in 32 (52.5%), eye tracking in 15 (24.6%), EDA/GSR in 14 (23.0%), HRV in six (9.8%), fMRI in three (4.9%), and fNIRS in one (1.6%). To organize this heterogeneous evidence base, the study develops an Immersive Spatial Cognition Framework (ISCF) linking spatial stimuli, environmental exposure, neurophysiological measurement, cognitive–emotional processing, evidence interpretation, design translation, and adaptive design, together with an Evidence-Based Neuroarchitecture Maturity Model (EBN-MM). EBN-MM classification indicated that 30.6% of the corpus remained at Stage I (Conceptual Interpretation), 35.5% reached Stage II (Experimental Validation), 33.1% reached Stage III (Evidence Integration), and only 0.8% reached Stage IV (Adaptive Design Operationalization). These findings indicate that neuroarchitecture is progressing beyond isolated experimental validation toward evidence integration, while translation into adaptive and operational design remains exceptional. The proposed frameworks provide a structured basis for comparing heterogeneous evidence and identifying methodological priorities for future evidence-based neuroarchitecture research.

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  Thermal Enhancement of PCM-Based Latent Heat Storage With Perforated Fin Networks and Coupled Effects of Geometry, Natural Convection, and PCM Melting Using MLP/GA Optimization

  (2026) Al-Mutiry, Motrih; Balla, Hyder H. Abed; Khlifi, Mohamed Arbi; Haji, Banaz Shahab; Althobaiti, Mohammad Abdulhadi O.; Althbiti, Ashrf; Alsairy, Norah; Abu-Zinadah, Hanaa; Nguyen, Duc Chuan; Mahariq, Ibrahim

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  The growing demand for sustainable and efficient energy systems has significantly increased the importance of latent heat storage systems (LHSSs) in renewable energy applications, particularly in solar thermal technologies. Despite the high energy storage density of PCMs, their inherently low thermal conductivity remains a major obstacle that limits charging performance and practical utilization. In the present study, a novel perforated finassisted LHSS is proposed and numerically investigated to enhance the charging performance of PCM-based storage systems. The effects of three key geometrical parameters, including perforation length (L), tube diameter (D), and storage body inclination angle (α), are systematically examined through a full factorial design approach. Furthermore, a multilayer perceptron neural network is established to estimate the system's thermal behavior, while genetic algorithm-based optimization identifies optimal configurations for short- and long-term heat absorption. The optimized short-term energy absorption design (OSTE) absorbs 7763 kJ during the shortterm charging period. In contrast, the optimized long-term energy absorption design (OLTE) absorbs 7343 kJ, indicating that OSTE achieves approximately 5.72% higher short-term energy absorption than OLTE. Compared with the core design without perforated fins, which absorbs only 3077 kJ under the same conditions, the OSTE and OLTE configurations improve short-term energy absorption by approximately 152.3% and 138.6%, respectively. Under long-term operating conditions, OLTE absorbs 10,011 kJ, while OSTE absorbs 9957 kJ, corresponding to only 0.54% higher long-term energy absorption for OLTE. In contrast, the core design absorbs only 5395 kJ under the same conditions, demonstrating that OLTE and OSTE improve long-term energy absorption by approximately 85.6% and 84.6%, respectively. The results reveal that OSTE's superiority during most stages of the charging process is substantially greater than OLTE's slight long-term advantage. The findings demonstrate the strong potential of combining perforated fin networks, machine learning prediction models, and optimization algorithms to develop high-performance LHSSs for renewable energy applications.

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