Search Results (1,659)

Understanding the complex interplay between environmental factors and fruit quality development requires sophisticated analytical approaches linking cellular architecture to environmental conditions. This study introduces a novel application of dual-resolution X-ray computed tomography (CT) for the non-destructive characterization of apple internal tissue architecture in relation to fruit growth, thereby advancing beyond traditional methods that are primarily focused on postharvest analysis. By extracting detailed three-dimensional structural parameters, we reveal tissue porosity and heterogeneity influenced by crop load, maturity timing and canopy position, offering insights into internal quality attributes. Employing correlation analysis, Principal Component Analysis, Canonical Correlation Analysis, and Structural Equation Modeling, we identify temperature as the primary environmental driver, particularly during early developmental stages (45 Days After Full Bloom, DAFB), and uncover nonlinear, hierarchical effects of preharvest environmental factors such as vapor pressure deficit, relative humidity, and light on quality traits. Machine learning models (Multiple Linear Regression, Random Forest, XGBoost) achieve high predictive accuracy (R² > 0.99 for Multiple Linear Regression), with temperature as the key predictor. These baseline results represent findings from a single growing season and require validation across multiple seasons and cultivars before operational application. Temporal analysis highlights the importance of early-stage environmental conditions. Integrating structural and environmental data through innovative visualization tools, such as anatomy-based radar charts, facilitates comprehensive interpretation of complex interactions. This multidisciplinary framework enhances predictive precision and provides a baseline methodology to support precision orchard management under typical agricultural variability. Full article

Non-digital traditional games such as board and card formats are increasingly recognised as valuable tools for active learning in higher education. These analogue approaches promote engagement, collaboration, and conceptual understanding through embodied and social interaction. This scoping review mapped research on the use of traditional, non-digital games as active learning strategies in tertiary education and examined whether the rise in generative artificial intelligence (GenAI) since 2022 has influenced their pedagogical role. Following the PRISMA-ScR framework, a systematic search of Scopus (October 2025) identified 2480 records; after screening, 26 studies met all inclusion criteria (explicitly using card and/or board games). Whilst this was a scoping, not a systematic review, some bias due to using only one database and evidence could have missed some studies. Results analysed the use and impacts of the games and whether AI was a specific driver in its use. Studies spanned STEM, business, health, and social sciences, with board and card games most frequently employed to support engagement, understanding, and collaboration. Most reported positive learning outcomes. Post-2023 publications suggest renewed interest in analogue pedagogies as authentic, human-centred responses to AI-mediated education. While none directly investigated GenAI, its emergence appears to have acted as an indirect catalyst, highlighting the continuing importance of tactile, cooperative learning experiences. Analogue games therefore remain a resilient, adaptable form of active learning that complements technological innovation and sustains the human dimensions of higher-education practice. Full article

Mammalian placentation represents one of the most striking evolutionary innovations among vertebrates, and accumulating evidence indicates that virus-derived genes—particularly the metavirus-derived PEG10 and PEG11/RTL1—have played indispensable but distinct roles: PEG10 in the emergence of therian viviparity and PEG11/RTL1 in the subsequent differentiation between marsupial and eutherian placental types. Notably, the metavirus-derived SIRH/RTL gene group, which includes PEG10 and PEG11/RTL1, exhibits unique and diverse functions not only in placenta development but also within microglia of the brain. Because microglia originate from yolk sac progenitors, these findings suggest that extraembryonic tissues such as the placenta and yolk sac provided permissive environments that enabled the retention, expression and functional domestication of virus-derived sequences. Once the placenta itself was established through viral gene integration, it may in turn have acted as a powerful driver of eutherian evolution through recurrent acquisition and co-option of additional virus-derived genes—a process we refer to as “placenta-driven evolution.” This perspective offers a unified framework in which viral gene acquisition is viewed as a key driver of genomic innovation, tightly intertwined with the emergence of viviparity, subsequent divergence at the marsupial–eutherian split, and continued diversification of placental structure and function across eutherian lineages. Full article

Green finance is increasingly recognized as an important instrument for improving sustainable development. Existing research has focused on green finance’s impact on corporate environmental performance, failing to account for the complex regional mechanisms that shape its contribution to systemic sustainability. This study fills the gaps by examining the mechanism and spatial heterogeneity of green finance’s influences on regional sustainability measured by environmental performance. Using panel data from 30 Chinese provinces during 2010–2022, it shows that green finance increased from 0.318 to 0.539, while environmental performance improved from 0.441 to 0.656. The empirical evidence demonstrates that green finance has a robust positive effect on environmental performance, acting as an effective tool for environmental governance. This impact is primarily channeled through technological innovation and green consumption, with environmental regulation providing a synergistic moderating role. Furthermore, significant regional heterogeneity in sustainability outcomes is observed, while the effect is strongest in eastern China, unstable or negligible in old industrial bases, and unexpectedly negative in ecologically fragile Northwest China. The disparities are attributed to variations in local economic structure, institutional capacity, and development stage. Corresponding policy recommendations include improving the institutional framework, channeling financial resources to green technology R&D and sustainable consumption incentives, integrating green finance with environmental policies, and implementing region-specific strategies. This study offers practical benchmarks for China and other developing economies to leverage green finance as a driver of sustainable development. Full article

Urban air mobility solutions such as drone taxi services are increasingly viewed as a promising response to congestion, sustainability, and smart-city mobility challenges. However, the large-scale adoption of such services depends on users’ perceptions of service experience, trust, and readiness to engage with emerging technologies. This study investigates the determinants of sustainable adoption of drone taxi services in the United Arab Emirates (UAE) by examining technology readiness and service experience factors, interpreted through conceptual alignment with the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). A structured questionnaire was administered to potential users, capturing perceptions related to optimism, innovation readiness, efficiency, control, privacy, insecurity, discomfort, inefficiency, and perceived operational risk, along with behavioral intention to adopt drone taxi services. Measurement reliability and validity were rigorously assessed using Cronbach’s alpha, composite reliability, average variance extracted (AVE), and the heterotrait–monotrait (HTMT) criterion. The validated latent construct scores were subsequently used to estimate a structural regression model examining the relative influence of each factor on adoption intention. The results indicate that privacy assurance and perceived control exert the strongest influence on behavioral intention, followed by optimism and innovation readiness, while negative readiness factors such as discomfort, insecurity, inefficiency, and perceived chaos demonstrate negligible effects. These findings suggest that in technologically progressive contexts such as the UAE, adoption intentions are primarily shaped by trust-building and empowerment-oriented perceptions rather than deterrence-based concerns. By positioning technology readiness and service experience constructs within established TAM and UTAUT theoretical perspectives, this study contributes a context-sensitive understanding of adoption drivers for emerging urban air mobility services. The findings offer practical insights for policy makers and service providers seeking to design user-centric, trustworthy, and sustainable drone taxi systems. Full article

Diabetic retinopathy (DR) has been classically considered a microvascular disease with all diagnostic and therapeutic resources focusing on its vascular components. However, during the past years, the obtained evidence highlighted the critical pathogenic role of early neuronal impairment redefining DR as a neurovascular complication. Retinal neurodegeneration is triggered by chronic hyperglycemia, which activates harmful biochemical pathways that lead to oxidative stress, metabolic overload, glutamate excitotoxicity, inflammation, and neurotrophic factor deficiency. These drivers of neurodegeneration can precede detectable vascular abnormalities. Simultaneously, endothelial injury, pericyte loss, and breakdown of the blood–retinal barrier compromise neurovascular unit integrity and establish a damaging cyclic loop in which neuronal and vascular dysfunctions reinforce each other. The interindividual variability of these processes highlights the need to properly redefine patient phenotyping by using advanced imaging and functional biomarkers. This would allow early detection of neurodegeneration and patient subtype classification. Nonetheless, translation of therapies based on neuroprotection has been limited by classical focus on vascular impairment. To meet this need, several strategies are emerging, with the most promising being those delivered through innovative ocular routes such as topical formulations, sustained-release implants, or nanocarriers. Future advances will depend on proper guidance of these therapies by integrating personalized medicine with multimodal biomarkers. Full article

Technological innovation plays a vital role in enhancing the economic growth and sustainability of the forestry sector. However, research on the nature, dynamics, and impact of such innovations, particularly within small and medium-sized enterprises (SMEs), remains limited. The forestry sector is often characterised by low levels of technological advancement and a traditionally conservative attitude toward change. Limited expertise, financial constraints, and ownership structures further influence the potential for innovation. This study examines the development of innovation among SMEs in Lithuania’s forestry sector and its contribution to sustainable forest management. Forestry innovations are understood as new processes, products, or services introduced by forest owners and managers to improve management efficiency and sustainability. The study employed the method of a structured questionnaire survey to evaluate technological, organisational, and financial aspects of innovation adoption among small and medium-sized enterprises in the forestry sector. Drawing on comparative survey data from 2005 and 2024, the study analyses the types of innovations implemented by forestry enterprises, the factors driving or hindering their adoption, and the evolving trends in innovation application. The results reveal a significant shift toward digitalisation and technology-based management practices, suggesting that Lithuanian forestry enterprises are gradually transitioning toward a more innovation-driven model. These developments appear to be influenced by the EU Green Deal policy framework, evolving innovation support mechanisms, and broader socio-economic changes. Nonetheless, technological transformation introduces new challenges, including the need for workforce upskilling and enhanced adaptability to rapidly changing market conditions. Full article

Gastronomic tourism has emerged as a significant driver of destination competitiveness, cultural preservation, and sustainable development. This comprehensive review synthesizes the scientific literature published between 2010 and 2025, examining the evolution of gastronomic tourism research, global trends, sustainability dimensions, and emerging challenges. Through systematic analysis of 150 peer-reviewed articles from major academic databases, this paper identifies key themes including cultural heritage preservation, sustainability practices, digital transformation, and educational innovations. The findings reveal a growing recognition of gastronomy as intangible cultural heritage, increased focus on farm-to-fork practices, and the transformative role of social media in destination branding. Despite the rapid growth of gastronomic tourism research, important gaps remain. The literature lacks standardized sustainability indicators, limiting comparability across studies, while cross-cultural comparative research and interdisciplinary integration remain insufficiently developed. Addressing these gaps is essential for advancing theoretical coherence and supporting evidence-based practice in gastronomic tourism. Full article

The mobility of data factors and the adoption of a collaborative innovation framework are key drivers influencing the gaps in total factor productivity (TFP) among enterprises in the digital economy. Using panel data from Chinese A-share listed companies between 2006 and 2022, this study empirically demonstrates how data factor flow reduces TFP gaps. The findings reveal that data factor flow enhances TFP convergence by facilitating knowledge diffusion, improving information transmission, and boosting innovation efficiency. However, the heterogeneity in enterprise RD efforts limits this convergence effect, highlighting the importance of collaborative innovation. The study further shows that the impact of data factor flow is more significant in smaller, privately owned enterprises in the eastern regions and in industries with low to high technology intensity and high market concentration. Key insights include (1) a positive synergy between government data openness policies and enterprise data flow, which reinforces the narrowing of TFP gaps; (2) a nonlinear relationship between data flow and TFP gaps, suggesting an optimal range for its maximum impact. The study concludes that an integrated framework optimizing both data governance and collaborative innovation ecosystems can foster innovation diffusion and support productivity-based competition. These findings provide valuable insights for innovation policy formulation and strategic decision-making in the digital economy. Full article

This study aimed to analyze the impact of the digital economy and artificial intelligence (AI) on GDP growth in 10 developed and developing countries during the period 2010–2024. It was based on the hypothesis that increased digitalization and AI investments promote sustainable economic growth by improving national productivity and efficiency, in accordance with modern technological growth theory, which links digital innovation to economic development. The study used tablet data comprising 150 observations, which were analyzed using fixed- and random-effects models, controlling for traditional variables such as employment, human capital, and investment. The results showed that the Digitalization Indicators (DIGI) had a significant positive impact on growth (fixed: 0.003479, p < 0.01; random: 0.003325, p < 0.01), and that investment in AI also had a significant positive impact (fixed: 0.063695, p < 0.05; random: 0.066548, p < 0.05). In contrast, workforce size had a limited impact, while education and human capital emerged as key drivers of sustainable growth (Constant: 0.003257, p < 0.01; Random: 0.003264, p < 0.01). The inclusion of dummy variables further differentiated between developed and developing countries in the random-effects model, reinforcing the economic interpretation of the findings. The study suggests that integrating digitalization, education, and investment in artificial intelligence is an effective strategy for promoting sustainable economic growth, while emphasizing the importance of workforce skills development to maximize its impact. Full article

Against the backdrop of rapid urbanization, megacities have become crucial drivers of development. As the country with the largest number of megacities (seven in total), China is confronted with significant challenges such as population–resource–environment conflicts, which render high-quality development an imperative pursuit. This study employs a system dynamics approach to assess high-quality development in China’s megacities. It analyzes interactions among economic growth, technological innovation, environmental quality, and livelihood security under policy regulation, clarifying their evolutionary mechanisms and constructing a model to project the high-quality development index (HQDI) and coupling coordination degree (CCD) among subsystems. Findings reveal an upward trend in both HQDI and CCD across the seven megacities, with notable stratification. Beijing, Shanghai, and Shenzhen form the top echelon, leveraging financial and technological resources, driven by science and green development. Guangzhou and Chongqing constitute the second tier, supported by regional integration and industrial clusters, while Chengdu and Tianjin form the third echelon via regional strategic transformations. In coordinated development, Shanghai, Beijing, Shenzhen, and Guangzhou lead with multi-link synergy, whereas Chengdu, Chongqing, and Tianjin advance industry–ecology–livelihood coordination through regional strategies. This study offers insights for overcoming development bottlenecks, optimizing policies, and enhancing urban governance to foster a coordinated, high-quality development pattern. Full article

This paper develops a new conceptual and operational understanding of cultural heritage transformation, interpreting it as a systemic and dynamic process rather than a static state. It explores the realities and opportunities for action when cultural heritage is understood and managed as a complex, adaptive system. The study builds on a critical review of contemporary literature to identify the multi-scalar challenges currently facing urban heritage systems, such as climate change, disaster risks, social fragmentation, and unsustainable urban development. To respond to these challenges, the paper introduces a metamodel for heritage-based urban transformation, designed to apply systems thinking to heritage management that was developed based on cases from the Western European context. This metamodel integrates key variables—actors, resources, tools, and processes—and is used to test the hypothesis that a systems-oriented approach to cultural heritage can enhance the capacity of stakeholders to connect, adapt, use, and safeguard heritage in the face of complex urban transitions. The hypothesis is operationalized through scenario-based applications in the fields of disaster risk management (DRM), circular economy, and broader sustainability transitions, demonstrating how the metamodel supports the design of cross-over resilience strategies. These strategies not only preserve heritage but activate it as a resource for innovation, cohesion, identity, and adaptive reuse. Thus, cultural heritage is reframed as a strategic investment—generating spillover benefits such as improved quality of life, economic opportunities, environmental mitigation, and enhanced social capital. In light of the transition toward a greener and more resilient society, this paper argues for embracing heritage as a driver of transformation—capable of engaging with well-being, behavior change, innovation, and education through cultural crossovers. Heritage is thus positioned not merely as something to be protected, but as a catalyst for systemic change and future-oriented urban regeneration. Full article

In a context of increasing natural hazards due to climate change, forest insurance is a relevant tool to consider. However, the development of forest insurance schemes varies widely across countries, reflecting differences in forest characteristics, institutional frameworks, and public risk management policies. In this article, we investigate the drivers of this heterogeneity by comparing forest insurance schemes in two contrasting national contexts: France and China. While forest insurance coverage remains relatively limited in France, China has implemented large-scale insurance programs. By examining the design, governance, and role of government intervention in both schemes, we identify the key factors that help explain the differences in insurance uptake across countries. Finally, we discuss innovative insurance products and policy mechanisms that could encourage the adoption of forest insurance. Full article

The accounting and analysis of agricultural grey water footprint (AGWF) are crucial for building a low-water-consumption agricultural production model and improving water resource efficiency in Fujian Province. This study innovatively integrated green development indicators into an extended STIRPAT model, quantitatively analyzed the drivers of AGWF from six dimensions (population, economy, technology, dietary structure, meteorology, and green development) based on data from 2009 to 2023. The results indicated that the AGWF in Fujian Province exhibited an overall upward trend, increasing from 114.61 billion m³ to 221.30 billion m³. Population expansion (elasticity: 0.49853) and economic growth (elasticity: 0.46329) were identified as the primary positive drivers, while technological progress exerted a mitigating effect (elasticity: −0.07253). The impacts of dietary structure, precipitation, and green development measures, though statistically significant, were quantitatively limited within the study period (elasticities of 0.0312, 0.0273, and 0.004, respectively). These findings provide quantitative support for formulating targeted policies for agricultural water resource management and non-point source pollution control in regions with similar characteristics. Full article

With the rapid growth of the social economy and the increasing prevalence of e-commerce, urban distribution centers (UDCs) have become vital hubs for the efficient functioning of cities. The decision regarding the location of UDCs not only impacts the operational efficiency of logistics companies but also plays a crucial role in urban sustainable development planning. Traditional location models are limited in addressing these complexities, which is why this paper introduces an innovative multi-objective location decision-making model. This model accounts for both the construction and operational costs of enterprises, and it uniquely incorporates the industrial sustainable development potential (ISDP) as a core objective function. The goal is to balance enterprise costs with the needs of urban development in location decision-making. This research adopts an interdisciplinary approach, initially using ecological theories to quantify ISDP, then employing System Dynamics to simulate the future trajectories of key industry drivers, and finally applying genetic algorithms to find solutions. The results from the numerical example demonstrate that the model and algorithm are both effective and practical. This research presents a novel approach and method for UDC location decision-making based on the long-term sustainable development of cities for logistics enterprises and urban planners. It also contributes to the related research on urban sustainable development and logistics location. Full article