Search Results (2,437)

The central challenge of the energy transition lies in whether an economy possesses the institutional capacity to systematically regulate its own energy inputs and carbon emissions. Drawing upon social metabolism theory, this study constructs an indicator of carbon–energy metabolic control capacity (CMCC). Building on business ecosystem theory, it conceptualizes the intelligent economic ecosystem (IEE) and incorporates industrial chain intellectual property empowerment (IP) into a causal framework of institutional provision → ecosystem development → enhancement of metabolic control capacity. Using panel data from 30 provincial-level administrative regions in China covering the period 2010–2022, this study employs a spatial Durbin difference-in-differences (SDID) model and a double machine learning (DML) framework for empirical analysis. The results indicate that industrial chain intellectual property empowerment significantly enhances carbon–energy metabolic control capacity and generates positive spatial spillover effects on neighboring regions through the public diffusion of patent information. Furthermore, intelligent economic ecological development serves as a significant partial mediator between intellectual property empowerment and carbon–energy metabolic control capacity, with the indirect effect accounting for more than one-third of the total effect. This mediating mechanism remains robust after replacing machine learning algorithms, altering sample-splitting ratios, controlling for concurrent innovation policies, and excluding the impact of the COVID-19 pandemic. Path-specific mediation analysis further reveals that computing power acquisition and value transformation together with digital substrate robustness constitute the dominant transmission channels, whereas innovation metabolic flux contributes a relatively smaller mediating effect due to the long gestation period required for translating fundamental research into practical applications. Heterogeneity analysis further demonstrates that the transmission mechanism exhibits full mediation in the dimension of metabolic structure, indicating that the contribution of industrial chain intellectual property empowerment to the clean substitution of energy structures depends almost entirely on the mediating role of the intelligent economic ecosystem. These findings provide clear actionable guidelines for three specific policy-making domains to advance low-carbon transitions. First, intellectual property authorities should transition from quantity-driven patent creation to establishing cross-regional patent navigation and industrial chain IP pooling. Second, digital economy and industry regulators need to prioritize computing power value conversion (CCV) over raw infrastructure expansion to mitigate energy rebound effects. Third, energy and environmental agencies ought to integrate real-time algorithmic dispatching with green finance incentives. Ultimately, this study demonstrates that achieving deep low-carbon transformation requires leveraging institutional public goods to catalyze digital ecosystems, which in turn enable precise, dynamic carbon–energy metabolic control. Full article

Dynamic electricity tariffs are increasingly deployed to manage demand-side flexibility in decarbonising power systems, making AI-driven load forecasting a critical enabler of adaptive pricing. However, existing studies largely treat forecasting and tariff design as independent problems, evaluating models on predictive accuracy alone while neglecting the feedback effects through which price signals reshape consumer behaviour and introduce non-stationarity into the very demand distributions forecasts depend upon. This gap leaves practitioners without coherent guidance on how to structure, govern, and adapt forecasting models in price-responsive environments. This paper addresses the gap through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-informed structured review of peer-reviewed studies spanning statistical, machine learning, deep learning, probabilistic, and reinforcement learning forecasting paradigms. Three principal findings emerge. First, dynamic pricing fundamentally invalidates static forecasting assumptions by inducing a distributional shift in demand data, making robustness to behavioural feedback a first-order requirement for deployment. Second, no single forecasting paradigm simultaneously satisfies the requirements of accuracy, interpretability, uncertainty quantification, and regulatory defensibility that dynamic tariff systems impose; layered, role-specific architectures are therefore operationally necessary. Third, explainability and governance constraints are structural requirements for tariff-oriented forecasting, not optional enhancements, because forecast outputs directly influence economically and socially consequential pricing decisions. Building on these findings, the paper proposes a Forecast-Driven Dynamic Tariff Design Framework that separates forecasting intelligence from pricing authority, embeds uncertainty management as a first-class design element, and positions a governance layer as the mandatory interface between predictive outputs and consumer-facing tariff signals. The framework provides a practical and regulatorily defensible foundation for deploying adaptive, resilient, and equitable electricity tariffs in data-intensive power systems. Full article

The development of arid-oasis agriculture and territorial spatial restructuring strongly influence regional eco-environmental quality. Clarifying production–living–ecological space (PLES) transitions and the nonlinear mechanisms driving eco-environmental quality is important for sustainable agricultural land use and ecological governance. Northern Xinjiang combines economic agglomeration with ecological sensitivity, making it a representative region for examining changes in eco-environmental quality and their underlying drivers. Land-use data for 1990, 2000, 2010, and 2020 were analyzed using land-use transition matrices, the eco-environmental quality index (EEQI), spatial autocorrelation, and hotspot analysis to characterize spatiotemporal changes under PLES transitions. XGBoost–SHAP was applied to identify the dominant factors, nonlinear responses, and interactions. The results showed that: (1) ecological space remained dominant from 1990 to 2020, but its share declined from 91.72% to 87.36%. Production and living spaces increased from 7.78% and 0.50% to 11.72% and 0.92%, respectively. Agricultural production space expanded most markedly, and spatial restructuring was most intense during 2000–2010. (2) EEQI decreased from 0.3100 to 0.2922 and showed an overall fluctuating decline. Significant spatial clustering was observed, with Moran’s I values consistently above 0.81 (p < 0.001). High-value areas were mainly distributed in the Ili River Valley and along the northern slope of the Tianshan Mountains, whereas low-value areas were concentrated in the Junggar Basin interior and the arid areas along its eastern margin. (3) During 2000–2020, LAI and NPP in agricultural production space increased by 45.7% and 48.2%, respectively. These increases indicated overall improvements in canopy condition and productivity. After 2010, NPP growth slowed markedly while LAI remained relatively stable, indicating a stage-specific divergence. (4) XGBoost–SHAP showed good robustness and spatial generalizability, with R² values of 0.868–0.918 and RMSE values of 0.059–0.075. NDVI remained the primary driver, while Elev contributed consistently. The dominant interaction shifted from NDVI ∩ PopDen in 1990 and 2000 to NDVI ∩ Elev in 2010 and NDVI ∩ GDP in 2020. This shift indicated fundamental natural constraints and stronger joint effects of population and economic activities during the later stages. These findings provide a scientific basis for optimizing PLES, regulating arid-oasis agriculture, and safeguarding regional ecological security. Full article

The rapid integration of artificial intelligence (AI) into educational settings presents a profound challenge for teacher education. This study examines how pioneering teacher educators in Israeli colleges of education perceive their role in training student teachers for AI-integrated teaching. Using a qualitative, interpretive phenomenological approach, semi-structured interviews were conducted with 13 participants—seven pedagogical advisors and six lecturers—from seven teacher training institutions representing diverse educational streams. Data were analyzed using a hybrid approach combining human thematic analysis and AI-assisted dialogic analysis. Findings revealed that participants perceived themselves as agents of change responsible for modeling critical AI use, while raising epistemic concerns regarding cognitive atrophy and the erosion of expertise. A crisis of trust triggered by students’ uncritical submission of AI-generated outputs prompted a shift toward process-based and in-class assessment. Pre-service teachers used AI for differentiated lesson planning, visual aids, and simulations, with experiences ranging from heightened self-efficacy to frustration. Persistent challenges included rapid technological change, the absence of institutional policy, ethical and privacy concerns, cultural factors, and economic barriers. Drawing on post-digital theory and AI literacy frameworks, this study argues that effective preparation for the AI era requires a fundamental reimagining of teacher education—one that redefines literacy, pedagogy, and human agency. Full article

This paper examines the energy renovation of buildings using building-integrated photovoltaic (BIPV) systems applied to facades and roofs. Although BIPVs are increasingly recognized as a vital component of sustainable retrofit strategies, designers still lack comparative decision-support tools for the simultaneous technical and economic evaluation of roof- and facade-integrated (envelope-integrated) configurations. To address this gap, this study presents a methodology for the energy-efficient retrofit of multi-story student residence halls through a parametric analysis. This comparative approach evaluates energy performance and electricity production while estimating the associated costs of BIPV systems. Building upon prior research, the current analysis utilizes innovative, energy-optimized models to form the basis of computer simulations. The methodology relies on a fundamental assumption involving an arbitrary parameter that defines grid-energy substitution rates by BIPV-generated electricity. Regarding the economic aspects, the results indicate that while certain rooftop installations offer lower costs and shorter payback periods than facade systems, other rooftop configurations exhibit higher costs and extended payback periods. This research provides valuable insights for optimizing civil engineering solutions in photovoltaics, where local electricity production effectively replaces grid-supplied energy. Furthermore, the proposed innovative qualitative and quantitative input/output models can be extended to parameterize other building renovation characteristics within civil engineering methods. Full article

Transportation infrastructure plays a fundamental role in shaping sustainable urban and regional development by improving accessibility, strengthening territorial cohesion, and supporting long-term economic resilience. While previous studies have primarily examined this relationship through macroeconomic indicators and secondary datasets, limited attention has been given to the perceptions of transportation professionals directly involved in infrastructure planning, implementation, and management. Addressing this gap, the present study investigates how transportation professionals in Greece perceive the contribution of transport infrastructure to sustainable regional development within the European policy context. A quantitative, cross-sectional design was employed, administering a structured questionnaire to 384 transportation professionals in October–November 2025. The study examined four interrelated dimensions: socio-economic contribution, environmental sustainability, infrastructure resilience, and long-term development. Multiple regression analysis showed that all four dimensions are significantly and positively associated with perceived regional development, with socio-economic contribution (β* = 0.359) and long-term development (β* = 0.304) showing the largest coefficients (R² = 0.597, p < 0.001). The study contributes practitioner-grounded evidence from the Greek context, with implications for the European Green Deal, TEN-T, and EU Cohesion Policy. Full article

Ensuring long-term agricultural sustainability depends heavily on preserving soil health, a process fundamentally governed by humic substances (HSs) and their vital physicochemical and biological functions. However, because intensive farming rapidly degrades natural HSs reserves, external replenishment has become essential, driving the expansion of the humic preparations market. This article constitutes a comprehensive review of the entire technological chain of humic preparations: from the identification of raw materials, through advanced extraction techniques, up to agrochemical mechanisms in the soil–plant system. Both traditional fossil deposits (leonardite, brown coal, peat) and renewable waste sources fitting into the concept of the circular economy were discussed. Classical alkaline extraction was confronted with green methods such as ultrasound-assisted (UAE), microwave-assisted (MAE) or high voltage electrical discharge (HVED) extraction, which allow for shortening the operation time and reducing the consumption of reagents. Strategies of integrating HSs with mineral fertilizers (coating, liquid formulas, organo-mineral products) and their direct impact on improving nutrient use efficiency (NUE), mitigating plant abiotic stress, agricultural performance, and environmental impact were described in detail. Research perspectives were also presented, including, among others, economic aspects of scaling up humic technologies and an assessment of the development potential of innovative nanofertilizers functionalized with HSs. Full article

Background: Health literacy is widely recognized as a fundamental determinant of chronic disease self-management. Despite the escalating burden of diabetes mellitus in Saudi Arabia, the relationship between health literacy and diabetes self-care management within specific urban–peripheral communities remains inadequately characterized. This study aimed to examine the relationship between health literacy and diabetes self-care management among adults with diabetes residing in southern Riyadh, and to examine associations with key sociodemographic variables, including age, income, gender, and educational attainment. Methods: A non-experimental, cross-sectional, correlational design was employed. A purposive sample of 92 adults with a confirmed diagnosis of diabetes was recruited from primary healthcare centers in southern Riyadh. Data were gathered using the Arabic-validated 12-item European Health Literacy Scale (HLS-Q12) and the 8-item Arabic Summary of Diabetes Self-Care Activities (SDSCA). Descriptive statistics and Spearman rank-order correlations were computed using IBM SPSS Statistics, Version 25. Results: A significant positive correlation was identified between health literacy and diabetes self-care management (rs = 0.64, 95% CI [0.50, 0.75], p < 0.01). Income level demonstrated significant positive associations with both health literacy (rs = 0.41, p < 0.01) and self-care practices (rs = 0.40, p < 0.01). Age exhibited significant negative correlations with health literacy (rs = −0.36, p < 0.01) and self-care management (rs = −0.49, p < 0.01). Educational attainment was significantly associated with both self-care management (rs = 0.29, p < 0.01) and health literacy (rs = 0.26, p < 0.05). Gender was not significantly associated with either outcome. Conclusions: Health literacy was significantly associated with diabetes self-care management in southern Riyadh and may represent a potentially modifiable target for nursing intervention. Findings point to the urgency of designing equity-sensitive, culturally responsive interventions targeting older adults and economically marginalized populations. These preliminary findings may carry implications for nursing practice, diabetes education, and health policy in Saudi Arabia, pending confirmation in larger, prospective samples. Full article

The maritime sector is increasingly focused on green propulsion technologies to address stringent regulations on greenhouse gas emissions and other pollutants. In recent years, research has proposed novel electric and hybrid propulsion architectures and advanced energy management systems. This paper reviews the fundamentals and the most recent developments of hybrid and electric propulsion technologies, evaluating their environmental and economic implications. Particular attention is given to the various onboard energy storage, conversion, and generation technologies, outlining their potential and limitations. Through the analysis of numerous research studies in alternative marine propulsion, the suitability of Li-ion batteries, supercapacitors, flywheels, and different types of fuel cells for maritime transport needs is evaluated, along with the possibilities offered by renewable energy to reduce the environmental impact of marine energy systems. Additionally, it discusses important future directions, research gaps, and emerging paradigms in sustaining maritime eco-systems. Unlike previous reviews that mainly focus on individual technologies, this study provides an integrated analysis connecting propulsion architectures, energy storage systems, fuel cells, alternative fuels, renewable energy integration, and energy management strategies. The review also discusses technology limitations, operational suitability for different vessel categories, and future research challenges toward maritime decarbonization. In presenting these issues, the author’s intention is to promote interdisciplinary cooperation between shipbuilders, policymakers, and researchers for the benefit of more sustainable development of the maritime industry. Full article

Dyes widely used in industrial sectors like pharmaceuticals and textiles cause a severe environmental threat due to the high stability and toxicity of synthetic dyes, which impair water quality and aquatic ecosystems. Normally, there are used traditional treatment methods, such as adsorption, and membrane filtration, but showed limitations including high costs, energy intensity, and low selectivity in complex matrices. Aqueous Two-Phase Systems (ATPSs) are an sustainable, economic, and versatile alternative for the extraction, separation, and purification of dyes. Therefore, this review examines the thermodynamic fundamentals, formation mechanisms, and the integration of innovative components like Ionic Liquids (ILs) and Deep Eutectic Solvents (DESs). Recent research highlights that ATPS can achieve extraction efficiencies exceeding 95% for dyes; however, the optimization of critical parameters such as pH, temperature, polymer molecular weight, and salt concentration is necessary. Furthermore, this review discusses the potential of these systems within circular economy schemes, emphasizing component recyclability and their alignment with green chemistry principles. Ultimately, ATPSs represent a scalable and eco-friendly platform for managing industrial effluents and recovering valuable compounds. Full article

This article looks at how trade, energy transition indicators, and economic prosperity are connected in the ASEAN-7 countries (Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam) from 1995 to 2021. Using dynamic panel data and panel threshold regression analysis, the research shows that trade openness has a significant effect on energy transition and economic prosperity. The key findings include: first, there is a strong conditional relationship between trade openness and energy transition indicators that affect economic prosperity. Second, the study finds different patterns for the indicators: an inverted U-shaped relationship for renewable energy share, peaking at about 34.7% before declining, and a U-shaped relationship for total energy use, which first drops to a low of 50.9 kgoe per capita before rising again. This indicates that economic prosperity first benefits from an increase in renewable capacity but later shifts toward total energy consumption. Third, the research identifies a trade threshold of 5.40, connected to a trade share of GDP of 221.41%, necessary to maximize the benefits of energy transitions in the region. The article highlights the complexity of the relationship between trade dynamics and energy policies. It suggests that well-designed trade strategies can improve the benefits of energy transitions. However, it also points out limitations, such as its focus on ASEAN-7 due to data constraints, possible biases from endogeneity in the model, and the complex effects of CO₂ emissions on economic prosperity. Future research could help policymakers find a balance between economic prosperity and sustainable energy use. Future research should explore more fundamental trade liberalization issues involving the US and other global regions. Including a broader array of topics, especially relevant research on the sustainable development of countries in the Asia-Pacific region, could enhance future studies. Full article

Jacket foundations, with their excellent adaptability and economic efficiency, have been increasingly widely applied in medium-deep water areas. However, the scouring and erosion effects in the marine environment, coupled with complex wind-wave loads, have severely restricted the long-term safe service of jacket foundations. In this study, a structure-pile-soil coupled dynamic response model considering the effects of scour depth and changes in wind and wave directions for the jacket-type offshore wind turbine is developed by integrating the wind and wave load generation capability of OpenFAST and the nonlinear pile-soil interaction analysis function of OpenSees. By quantitatively analyzing key response parameters such as tower top displacement, nacelle acceleration, and internal forces of the foundation tower and pile shaft, this study reveals the significant influence of soil stiffness degradation induced by scour on structural dynamic characteristics, and verifies the effective suppression mechanism of the feathering shutdown strategy on structural responses under extreme loads. The research results indicate that scour has a negligible impact on the fundamental frequency of the jacket-type offshore wind turbine structure, while it significantly reduces the high-order frequencies and leads to a substantial increase in pile shaft internal forces; the effect of wind-wave angle intensifies the spatially coupled vibration response of the structure. The study provides important theoretical and technical support for the anti-scour design, multi-directional load assessment, and formulation of safety control strategies for jacket foundations in complex deep-sea environments. Full article

The study presents methodological approaches to developing regional agri-food strategies integrating economic, social, and environmental indicators, aiming to improve socio-economic and environmental efficiency in the context of food security. To assess regional sustainable development, a hierarchical cluster analysis using Ward’s method was applied to compare Russian regions based on indicators of agricultural specialization, economic efficiency, food security, social conditions, and environmental impact. The analysis identified seven distinct regional clusters with significant socio-economic and environmental differences. A critical finding is that all clusters exhibit persistent problems with waste disposal and neutralization, alongside an acute shortage of investment for technological modernization and additional processing capacity. Key priorities for improving efficiency in achieving food security are identified, and differentiated sustainable development strategies for the selected groups are proposed, including recommendations for adapting governance mechanisms and state support. The need for fundamentally new forms of financing innovative businesses is substantiated. This study provides a differentiated framework for developing regulatory tools for regional agri-food systems based on cluster analysis results. The findings have practical value for planning socio-economic and environmental development programs and for formulating state innovation policy in agricultural support. Full article

The transition from sustainable to regenerative tourism requires a fundamental shift in how destination success is measured and managed. While theoretical frameworks for regenerative tourism have proliferated, empirical assessments of the macro-structural conditions that enable or constrain these transitions remain scarce. This study addresses this gap by developing a multivariate indicator framework to map the structural enabling conditions for regenerative tourism potential across ten diverse coastal tourism countries. Using a hierarchical cluster analysis of seven Tier 1 indicators spanning economic yield, social equity, governance effectiveness, and environmental pressure, we identify three distinct exploratory typologies: (1) High-Capacity Systems with Environmental Tradeoffs, (2) Tourism-Intensive Systems with Transition Potential, and (3) High-Need Systems with Uneven Capacity. The results reveal that while high-capacity systems possess the institutional stability to pilot regenerative innovations, they are often constrained by high per-capita environmental footprints. Conversely, high-need systems demonstrate strong community-centric potential but face significant structural barriers related to governance and climate vulnerability. These findings suggest that a “one-size-fits-all” approach to regenerative tourism is insufficient. Instead, policy interventions must be tailored to the specific structural archetypes of destinations, moving beyond generic sustainability goals toward place-based, redistributive, and restorative stewardship. Full article

Insects are fundamental to ecosystem functioning and human welfare, yet their multifaceted contributions to ecological services, food security, rural livelihoods, and cultural heritage remain insufficiently represented in mainstream scientific research and policy. Despite growing global recognition of insect decline and the potential of entomophagy to address food system challenges, integrated evidence linking global ecological knowledge with community-level indigenous practices is lacking, particularly in sub-Saharan African contexts. A narrative bibliometric review was conducted through systematic searches of Web of Science, Scopus, and PubMed databases, supplemented by FAO, IPBES, and MDPI Insects repositories. Searches were conducted between January 2024 and May 2026 using keyword combinations spanning entomophagy, ecosystem services, insect decline, indigenous knowledge and edible insects in Africa. Four thematic dimensions are synthesised: (1) ecological services, (2) nutritional value and food security, (3) economic contribution and livelihoods, and (4) socio-cultural and ethnomedicinal significance. The Venda region of Limpopo Province emerges as a compelling case study of how insect–human relationships intersect with biodiversity conservation, food security, and rural development. Actions include integrating indigenous knowledge with scientific research, strengthening sustainable community-based insect harvesting practices, and incorporating edible insects into South Africa’s food, nutrition, and biodiversity policies in alignment with global sustainability and biodiversity goals. Full article