Search Results (1,339)

Hawthorn (Crataegus spp.), a horticultural crop with significant edible, medicinal, and ornamental values, has garnered increasing attention from breeders to markets, leading to continuous emergence of new varieties. Accurate phenotypic characterization and robust Distinctness, Uniformity, and Stability (DUS) testing are fundamental for plant variety protection and breeding innovation. Employing the Chinese DUS Test Guidelines for Hawthorn (LY/T 3208-2020) as an analytical framework, this study systematically evaluated 197 germplasm accessions from the Chinese National Field Genebank. Results demonstrated: (1) Coefficients of Coincidence (COC) for example varieties and test traits ranged between 0.980 and 1.000, fully meeting the testing requirements; (2) the 22 qualitative (QL) and pseudo-qualitative traits (PQ) were categorized into 2–5 classes with Shannon-Wiener indices of 0.032–1.174, indicating high polymorphism; (3) correlation analysis of 11 quantitative traits (QN) revealed coefficients from 0.006 to 0.922, with 23 trait pairs showing statistical significance, while principal component analysis identified fruit and leaf traits as primary drivers of phenotypic variation; (4) grading schemes were established by using Least Significant Difference (LSD) for eight normally or near-normally distributed traits (5–7 classes) and range-based grading approach for three non-normal traits (5 classes). Based on the above results, this study evaluated China’s current DUS testing guidelines for hawthorn. Subsequently, 197 hawthorn accessions were used to evaluate the QL, PQ, and QN traits, based on which corresponding optimization recommendations were proposed. Ultimately, an optimized testing framework for hawthorn DUS testing was established. The resulting analytical insights and phenotypic grading system will enrich the current descriptor framework and provide a foundational dataset for trait-DNA association and marker-assisted breeding. Notably, this optimization strategy serves as a methodological template for updating DUS guidelines in other taxa. Overall, these insights strengthen the protection, development, and breeding of new hawthorn varieties while advancing the standardization of DUS testing. Full article

Ecotourism, as one of the most important forms of sustainable tourism, plays a significant role in the conservation of natural resources, the economic development of local communities, and the achievement of sustainable development goals. However, the sustainable development of this sector requires the accurate identification of suitable areas and the simultaneous assessment of the ecological capacities and limitations arising from anthropogenic activities, an issue that has received less attention at the national scale, particularly in countries with high environmental diversity such as Iran. Therefore, the present study was conducted with the aim of assessing the potential for ecotourism development in Iran based on Geographic Information System (GIS) and Spatial Multi-Criteria Decision Analysis (SMCDA). In line with the scope of the sub-factors evaluated, the assessed construct is referred to throughout this study as Environmental–Anthropogenic Ecotourism Suitability (EAES), reflecting an environmental-quality and anthropogenic-pressure perspective rather than a comprehensive assessment of ecotourism sustainability. The main innovation of this study lies in the simultaneous integration of natural and anthropogenic factors at the national scale and the sensitivity assessment of the results through the design of different development scenarios. In this study, a set of natural sub-factors including protected areas, vegetation cover, slope, precipitation, land use, and natural attraction density, as well as anthropogenic sub-factors including settlements, roads, accommodations, mines, industrial parks, dams, power transmission lines, dust, and the Global Human Modification (GHM) index were used. The weighting of the sub-factors was carried out using the Best–Worst Method (BWM), and spatial suitability maps were subsequently generated through the Weighted Linear Combination (WLC) method in the GIS environment. To evaluate uncertainty and examine the effect of the relative importance of sub-factors, three scenarios including natural factor dominance, anthropogenic factor dominance, and a balanced scenario were designed and analyzed. The results showed that protected areas (0.19), vegetation cover (0.17), and natural attraction density (0.16) were the most important natural sub-factors, while the GHM index (0.16), roads (0.15), and settlements (0.14) were the most important anthropogenic sub-factors affecting ecotourism development. The spatial pattern of the results indicated the concentration of areas with good potential in the Alborz and Zagros mountain ranges, the Hyrcanian forests, and parts of the protected areas of Iran. In the balanced scenario, approximately 24.8% of Iran’s area was classified within the suitable and highly suitable classes, while 46.3% was classified within the moderately suitable class. Furthermore, comparison of the scenarios showed that the use of one-dimensional approaches may lead to unrealistic estimates of ecotourism capacity. Overall, the results of this study indicate that the sustainable development of ecotourism in Iran requires the adoption of an integrated approach in which the conservation of natural assets and the management of anthropogenic interventions are simultaneously considered. The proposed framework can serve as a decision-support tool for spatial planning, investment prioritization, and sustainable ecotourism development policymaking in Iran and other similar regions. Full article

Education for Sustainable Development (ESD) has become a central priority in international education policy, increasing expectations for teacher education systems to prepare future teachers for sustainability challenges. This study examines how sustainability, the Sustainable Development Goals (SDGs), and higher-order cognitive expectations are embedded within teacher education policy frameworks in Hungary, Finland, and Poland. Using qualitative document analysis supported by MAXQDA, national policy documents, teacher education regulations, and programme frameworks were systematically analysed. Sustainable Development Goals were used to examine policy content, while Bloom’s Taxonomy provided a framework for investigating cognitive expectations in teacher education requirements. The findings reveal substantial cross-national differences in how sustainability is conceptualised and operationalised within teacher education. Finland demonstrates the most comprehensive and transversal integration, whereas Hungary primarily adopts a disciplinary approach and Poland places greater emphasis on digitalisation and innovation. In the Hungarian teacher education qualification requirements, lower- and intermediate-level cognitive processes are more frequently represented than higher-order processes, while the Finnish and Polish frameworks also contain explicit expectations related to higher-order thinking. Beyond comparing national frameworks, the study demonstrates how qualitative policy document analysis combined with SDG mapping and Bloom’s Taxonomy reveals pedagogical priorities within teacher education systems. The findings suggest that national policy frameworks may shape how sustainability competences and cognitive expectations are represented within teacher education requirements, offering policy-level implications for sustainability-oriented teacher education. Full article

Urban solid waste governance has become a key component of sustainable urban development. However, integrated analyses that combine thematic evolution and spatial heterogeneity remain scarce. This study applies an LDA-based systems analysis of USWG policies through a life-cycle governance perspective to examine the evolution of solid waste policies using a corpus of 13,161 policy documents from 35 major Chinese cities covering the period 2000–2025. The analysis compares thematic trends across three predefined policy phases grounded in major national policy milestones: Exploration period (2000–2010), Stabilization period (2011–2019), Transformation period (2020–2025). Six governance themes are identified relating to regulatory enforcement, procedural supervision, construction-site management, waste resource utilization, green innovation, and long-term institutional mechanisms. Based on these themes, the study examines changes in relative thematic shares over time and compares city-level theme intensity across urban tiers. The results show a gradual reconfiguration of policy attention, with pollution control and construction-site management remaining important while resource circulation, green innovation, and institutional coordination become more prominent. Spatially, Tier-1 cities exhibit relatively stronger attention to innovation and institutional coordination, Tier-2 cities show a more balanced profile across resource recovery and operational management, and Tier-3 cities display comparatively closer attention to enforcement and pollution control. By synthesizing temporal patterns, thematic structures, and urban-level differentiation, this study provides a systems-oriented account of policy attention in China’s urban solid waste governance. The findings offer a descriptive basis for understanding differentiated governance priorities across cities with different development conditions. Full article

Microalgae facade systems have emerged as an innovative approach in sustainable architecture, offering benefits in energy efficiency, carbon reduction, and biomass production. However, research remains fragmented across biotechnology, environmental engineering, and architectural design, with limited synthesis of its intellectual structure and thematic evolution. This study presents a bibliometric and thematic analysis of microalgae facade research in buildings from 2016 to 2025 using a combined Web of Science and Scopus dataset of 59 publications. The analysis examines publication trends, influential authors, journals, collaboration networks, and key research themes, while science mapping identifies conceptual clusters and their evolution. A sustainability-oriented perspective further links these themes to the environmental, economic, and social dimensions of sustainability and the United Nations Sustainable Development Goals (SDGs). The findings show that research has primarily focused on photobioreactor technologies, energy performance, and biomass production, whereas architectural integration and real-world building applications remain underexplored. Although interdisciplinary collaboration has increased in recent years, the field is still at an early stage of development. This study provides a systematic overview of the current intellectual landscape, identifies research gaps, and offers directions for advancing microalgae facade technologies toward sustainable and net-zero built environments. Full article

Innovation systems are commonly analysed through indicators of investment, performance, technological capacity, and research output, while less attention is paid to the composition of the research workforce. This article asks whether workforce composition can be understood as a structural dimension of national innovation systems and whether it is systematically associated with their capacity configuration. Using comparative 2023 data for 28 European and selected non-European national R&D systems, the study combines correlation analysis, a multidimensional capacity coordinate, and quadrant-based configurational mapping. Innovation-system capacity is operationalised through R&D intensity, innovation performance, and R&D expenditure per researcher. Workforce composition is measured by the share of women among researchers and is treated as a separate aggregate dimension rather than as a comprehensive measure of substantive inclusion. The results indicate a recurrent negative association between innovation-system capacity and the relative representation of women among researchers. Higher-capacity systems are more frequently positioned in configurations characterised by lower female representation, although cases combining high capacity with higher representation demonstrate that the pattern is not universal. The study does not establish causality, temporal development, or a deterministic trade-off. Sectoral, disciplinary, institutional, educational, and cultural factors may contribute to the observed cross-national differences. The article contributes to innovation-systems research by integrating aggregate workforce composition into systems-level analysis and by demonstrating how coordinate-based configurational mapping can reveal relationships that remain obscured in composite rankings. Full article

Scientific problem. Although digital transformation is widely regarded as a system-level enabler of regional innovation, regions with similar digital investment still display markedly different innovation outcomes, and the organizational channels that convert digital conditions into innovation performance remain insufficiently specified. Aim and method. Using panel data for 30 Chinese provinces from 2014 to 2019, this study conceptualizes State Key Laboratories (SKLs) as a specific institutional form of public research platforms (PRPs) and examines whether SKLs transmit the effect of regional digital transformation to regional innovation performance. We construct a Regional Digital Transformation Index using the entropy weight TOPSIS method and estimate its effects using two-way fixed effects models, IV estimation, policy shock DID, mediation analysis, and fsQCA. Results. Regional digital transformation is positively associated with regional innovation performance, and DID estimates based on the National Big Data Comprehensive Pilot Zone policy point in the same direction, with the average policy effect significant at the 5% level under province-clustered inference (p < 0.05). Mediation analysis shows that SKLs transmit part of this effect through both boundary-spanning functions. The external knowledge introduction channel, captured by international collaboration, carries the larger indirect effect (318.966, Sobel z = 2.14, p = 0.032), while the internal network diffusion channel, captured by the network hub function, carries a smaller indirect effect (93.285, Sobel z = 1.89, p = 0.059) whose cluster bootstrap interval excludes zero. H3a (external collaboration) is confirmed by both the Sobel test and the BCa bootstrap interval, while H3b (network hub) is supported by the BCa interval and marginally by the Sobel test. fsQCA further shows that superior innovation performance arises from multiple configurations of digital transformation, SKL boundary-spanning functions, human capital, and industrial base. Conclusion and future research. The findings suggest that digital transformation acts less as a standalone technological input than as a system-level enabling condition whose innovation effects depend on the boundary-spanning functions of public research platforms and their alignment with regional conditions. Future research could use laboratory- and firm-level data and dynamic configurational methods to trace these mechanisms over time. Full article

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia’s emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare. Full article

Infective endocarditis (IE) continues to represent a major challenge for global health systems. In 2019, its annual incidence was estimated at 13.8 cases per 100,000 individuals, contributing to approximately 66,300 deaths worldwide. Due to its high morbidity and mortality rates, enhancing preventive measures has become a priority in both clinical practice and ongoing research efforts. Since the publication of the 2015 ESC Guidelines for the management of IE, several pivotal studies have emerged, prompting a re-evaluation and potential update of the existing recommendations. One growing concern is the increasing antibiotic resistance among oral streptococci, particularly to macrolides such as azithromycin and clarithromycin, which now show higher resistance levels than penicillin. Changes in national antibiotic stewardship programs may have inadvertently contributed to a rise in IE incidence, in part due to altered prophylactic practices. At the same time, advances in diagnostic modalities—including more widespread and targeted use of echocardiography in patients with positive blood cultures for organisms like Enterococcus faecalis, Staphylococcus aureus, and various streptococci—have likely improved detection rates. Additionally, innovations in imaging, particularly computed tomography (CT) and nuclear medicine techniques, have enhanced the diagnosis of IE, especially among patients with prosthetic heart valves or implantable cardiac devices. This has allowed for better characterization of patient populations, aiding in the refinement of diagnostic criteria and therapeutic approaches. Furthermore, updated antibiotic treatment protocols, informed by EUCAST’s antimicrobial susceptibility data, have helped tailor antimicrobial regimens to current resistance trends. The combination of improved diagnostic sensitivity and evolving microbial resistance patterns has also led to an increased number of patients being considered for cardiac surgery as part of their treatment pathway. This review seeks to synthesize the latest findings and guideline revisions, offering an integrated overview of recent progress in the diagnosis, medical treatment, and surgical management of infective endocarditis. It will also explore current therapeutic strategies and operative indications in light of the most recent evidence. Full article

Health systems are fundamental to ensuring the right to health and maintaining the stability of welfare states. In this broad framework, this narrative review takes a look at Italy and China—two countries with very different historical backgrounds and institutional paths—as they deal with challenges like demographic aging, increasing chronic illnesses, and ongoing disparities in access to care. This paper aims to examine the most relevant peer-reviewed studies, as well as current legal and policy documents, in order to outline a comparative overview of the approaches to financing, coverage, and service provision in Italy and China, two very different countries. The Italian National Health Service, financed through general taxation and designed to be universal, aims to ensure equitable access to healthcare while having to contend with significant regional differences and financial difficulties. On the other hand, China, which operates with a mixed model, has rapidly expanded its insurance coverage using a variety of schemes and embracing technological advances, which has enabled large-scale access to healthcare, although considerable differences remain between urban and rural areas and provinces. When compared, each system shows particular strengths: Italy’s local care networks and focus on continuous services offer a model for inclusive welfare, while China’s use of digital tools demonstrates how innovation might help overcome obstacles in settings with limited resources and maintain continuity of care. There is a noticeable overlap in how both countries handle chronic diseases and their shared concern for equity in health policy. Considering these points, mixed approaches that combine universal coverage, financial viability, and flexible use of technology could provide useful ideas for crafting more fair, effective, and resilient health policies in various settings. Rather than proposing direct policy transfer, the comparison identifies context-dependent strategies that may inform future healthcare reforms. Full article

High-risk industries (HRI) face persistent safety challenges due to complex environments and multi-factor risks. Traditional manual monitoring is inefficient and reactive. While computer vision (CV) and deep learning (DL) have enabled automated risk perception, existing research lacks systematic review of the transition toward risk cognition. This systematic review, following PRISMA 2020 guidelines, searched Web of Science, Scopus, and IEEE Xplore for studies published from January 2021 to December 2025. After two-stage screening, 108 eligible studies were included. These studies span construction, mining, oil and gas, petrochemical, rail, energy, and maritime industries, with perception-layer applications predominating while cognition and early warning layer studies remain limited. We propose a “perception–cognition–early warning” framework to map the evolution from data to information, knowledge, and actionable decisions. Our findings reveal that visual perception technologies (e.g., Personal Protective Equipment (PPE) detection, object tracking) have matured, but significant bottlenecks persist in multimodal information fusion, knowledge reasoning, and decision-making. Achieving a true cognitive leap requires multimodal semantic alignment, scene graph construction, and causal inference. The proposed framework enables practitioners to design cognitive safety vision systems with scene understanding and interpretable decision-making capabilities. Key implementation strategies include addressing challenges in few-shot learning, cross-domain generalization, and human–machine collaboration. By integrating AI-driven perception, cognitive reasoning, and proactive intervention, this review supports the United Nations Sustainable Development Goals. Relevant goals include Goal 3 (health and well-being), Goal 8 (decent work), and Goal 9 (industry and innovation). Full article

The logistics industry remains a critical bottleneck for decarbonization due to its extensive physical networks and high-carbon path dependencies. To address the spatial heterogeneity and transition constraints in the logistics industry of China, this study proposes a Performance–Topology–Mechanism (PTM) framework. Analyzing panel data from 30 Chinese provinces, we integrate a Super-SBM model with the Global Malmquist–Luenberger (GML) index, Dagum Gini decomposition, and a panel Tobit model to decode the spatiotemporal dynamics of green innovation performance (GIP) and its underlying spatial lock-in mechanisms. The results reveal a steady but spatially uneven increase in the national GIP (from 0.4526 to 0.5724), characterized by a leading East and a lagging West/Northeast. GML decomposition indicates this growth is predominantly driven by outward shifts in the technological frontier rather than efficiency improvements, highlighting the weak spatial conversion of green technologies into transport optimization. Topological tracing demonstrates that inter-regional disparities have become the dominant source of spatial inequality, with their contribution rising from 60% to 75%. Spatial autocorrelation further exposes a deepening core–periphery polarization and persistent low-performance spatial lock-in. Crucially, the mechanism analysis identifies a pronounced infrastructure-based carbon lock-in. While economic capacity and green patents stimulate GIP, road network density exerts a significant negative effect, reflecting a systemic path dependence on high-carbon road freight. The findings suggest that decarbonizing transport logistics requires shifting from singular technological investments toward multimodal transport restructuring, overcoming physical network dependencies, and promoting the regional diffusion of green innovations. These findings provide an empirical basis for differentiated green-logistics policies, coordinated low-carbon transport infrastructure planning, and cross-regional diffusion of green technologies. Full article

The aorta is a single arterial organ, yet the clinical response to its diseases is fragmented across specialties, institutions, and nations. Acute aortic syndromes remain lethal at every stage of the care continuum: a large share of patients with type A dissection die before reaching any hospital, roughly half die before reaching a specialist centre, a substantial proportion are misdiagnosed at first medical contact, and untreated mortality has historically been estimated at approximately one to two percent per hour. Reported 30-day mortality differs across surgical registry cohorts—for example, 7.6% in the Japan Cardiovascular Surgery Database and 16.9% in the cited GERAADA cohort—but such ecological comparisons are descriptive and cannot identify the contribution of organisational, biological, clinical, or ascertainment differences. This review synthesises registry, population, and health-services data from Europe, Japan, North America, and low- and middle-income settings to characterise where the pathway fails and what each system has already demonstrated. We argue that the next material advance in aortic care will come not from any single innovation in isolation but from the architecture that connects prevention, diagnosis, treatment, and follow-up and that system redesign and technological progress are complementary rather than competing; we propose a five-pillar framework (Prevention, Presentation, Pathway, Person, and Learning) mapped throughout to published exemplars and future research priorities. Full article

This paper presents a resilience-driven probabilistic multiobjective framework for reactive power planning in islanded microgrids under extreme contingencies, explicitly integrating sustainability objectives and alignment with the United Nations Sustainable Development Goals (SDGs). The proposed planning framework simultaneously optimizes technical reliability, economic viability, environmental sustainability, and social resilience using the IEEE 33-bus distribution system as a representative test network. Uncertainties associated with solar irradiance, wind speed, and load demand are modeled using the Two-Point Estimation Method (2PEM), while the Non-dominated Sorting Genetic Algorithm II (NSGA-II) determines Pareto optimal planning solutions for five reactive power support strategies. The results demonstrate that planning solutions optimized for grid-connected operation are not necessarily the most effective under islanded conditions. Within the adopted multi-criteria evaluation framework, the dedicated D-STATCOM strategy achieves the highest overall normalized performance, providing 87.2% load preservation, 93.7% critical-load protection, and an 8.7 h representative survival time, while reducing total load shedding to 12.8% and eliminating high-risk shedding events (>30%). Furthermore, it decreases event-related economic losses by more than 75% and achieves the lowest environmental impact, with a 62.5% reduction in life-cycle CO₂ emission intensity relative to the conventional grid baseline. A normalization sensitivity analysis confirms that the comparative ranking of the investigated strategies remains unchanged under alternative normalization methods, demonstrating the robustness of the proposed evaluation framework. From a sustainability perspective, the proposed framework contributes to SDG 7 (Affordable and Clean Energy) through reliable low-carbon microgrid operation, SDG 9 (Industry, Innovation and Infrastructure) through resilient power system planning, SDG 11 (Sustainable Cities and Communities) by enhancing the continuity of critical urban services, SDG 13 (Climate Action) through reduced life-cycle emissions, and SDG 8 (Decent Work and Economic Growth) by supporting local employment associated with distributed energy deployment. Full article

Entrepreneurial ecosystems are increasingly viewed as drivers of sustainable and inclusive development, yet their true capacity to translate entrepreneurship into inclusive outcomes remains insufficiently understood. This study addresses this gap by linking national-level entrepreneurship indicators to three dimensions of inclusive growth—decent work and economic growth (SDG 8), innovation and infrastructure (SDG 9), and inequality reduction (SDG 10)—using data from the Global Entrepreneurship Monitor’s National Expert Survey (NES) for 37 countries over the period 2020 to 2024. By integrating multistage machine learning techniques with institutional and ecosystem theories, the study captures the nonlinear and interdependent dynamics among entrepreneurial framework conditions. The results reveal that development outcomes depend not on isolated factors but on complementarities among finance, infrastructure, and R&D transfer. Entrepreneurial ecosystems foster innovation and productive employment, yet their inclusiveness hinges on institutional efficiency, governance quality, and redistributive capacity. The findings show that policy intent diverges from policy impact, as governmental support and cultural norms exert adverse effects when institutional coherence and absorptive capacity are weak. The research advances entrepreneurship theory by moving beyond linear, additive models toward a systemic understanding of ecosystem complementarity, and offers policy insights, emphasizing that innovation-led growth must be embedded in institutional coherence and social inclusion to achieve sustainable and equitable development. Full article