Search Results (1,120)

Background/Objectives: Wound infections caused by multidrug-resistant Gram-negative bacteria, such as Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii, pose a major clinical challenge. This study evaluated the interactions between gamma-polyglutamic acid (γ-PGA), cefiderocol, and silver nanoparticles (AgNPs) within multilayer wound dressing configurations. The primary goal was to clarify the dual role of γ-PGA as a healing promoter and a potential protector of bacterial cells against antimicrobial agents. Methods: Multilayer dressing models were assembled in 96-well plates to simulate vertical stratification of antimicrobial layers4. Bacterial viability was assessed through relative OD₆₀₀ measurements following incubation with varying concentrations and spatial arrangements of cefiderocol, AgNPs, and γ-PGA. Data were analyzed using generalized linear modeling (GLM) with a gamma distribution and random forest regression to determine the relative importance of each factor in modulating bacterial survival. Results: γ-PGA concentration emerged as the dominant factor influencing bacterial viability, accounting for nearly 100% of variable importance in random forest analysis. Despite high antimicrobial pressure from cefiderocol and AgNPs, bacterial viability stabilized at approximately 40% in the presence of γ-PGA. The vertical positioning of γ-PGA significantly impacted survival; direct physical contact between the polymer and bacteria, particularly at high concentrations, enhanced bacterial persistence in P. aeruginosa and E. coli. Cefiderocol showed strain-specific potency, while AgNPs provided consistent growth inhibition. Conclusions: γ-PGA plays a paradoxical role in wound care by providing moisture retention while simultaneously acting as a cytoprotective agent that reduces antimicrobial efficacy, likely by facilitating biofilm formation. These findings underscore the necessity of optimizing the spatial layering and concentration of biopolymers in advanced dressings. Strategic design is crucial to balance regenerative benefits with maximal antimicrobial control to improve clinical outcomes in chronic wound management. Full article

Chinese local governments have long financed public services through land-sale revenues. The shift from selling undeveloped land to redeveloping existing urban areas has disrupted this traditional financing model, exposing a critical tension between the pursuit of immediate revenue and the assurance of long-term fiscal health. The continued dependence on land-based finance has led many local governments to overlook long-term public service obligations and the long-term operating deficits associated with intensive urban development. Thus, by examining the relationship between the development rights allocation and the sustainable fiscal capacity of the government, the study evaluates both short-term revenue generation and long-term expenditure commitments in urban redevelopment contexts. However, existing research has yet to provide actionable tools to reconcile this structural mismatch between short-term revenues and long-term liabilities. We employ a comprehensive analytical framework that integrates fiscal impact modeling with the optimization of development rights allocation. Based on this framework, we construct a quantitative, dual-period fiscal balance model using mathematical programming to analyze various combinations of land development rights supply strategies for achieving fiscal equilibrium. Our results identify multiple feasible supply combinations that can maintain fiscal balance while supporting sustainable urban development. The findings demonstrate that strategic development rights allocation functions as an effective tool for balancing short-term revenue needs with long-term obligations in local land finance systems. Our study contributes to establishing a sustainable land finance framework, particularly for jurisdictions lacking comprehensive land value capture mechanisms. The proposed approach offers an alternative to traditional land rights transfer models and provides guidance for avoiding long-term fiscal distress caused by excessive land transfer. The framework supports more sustainable urban redevelopment financing while maintaining fiscal responsibility across temporal horizons. Full article

The sustainability of the beef and dairy industry requires a systems approach that integrates environmental stewardship, social responsibility, and economic viability. Over the past two decades, global genetics consortia have advanced data-driven germplasm programs (breeding and conservation programs focusing on genetic resources) to enhance sustainability across cattle systems. These initiatives employ multi-trait selection indices aligned with consumer demands and supply chain trends, targeting production, longevity, health, and reproduction, with outcomes including greenhouse gas mitigation, improved resource efficiency and operational safety, and optimized animal welfare. This study analyzes strategic initiatives, germplasm portfolios, and data platforms from leading genetics companies in the USA, Europe, and Brazil. US programs combine genomic selection with reproductive technologies such as sexed semen and in vitro fertilization to accelerate genetic progress. European efforts emphasize resource efficiency, welfare, and environmental impacts, while Brazilian strategies focus on adaptability to tropical conditions, heat tolerance, and disease resistance. Furthermore, mathematical models and decision support tools are increasingly used to balance profitability with environmental goals, reducing sustainability trade-offs through data-driven resource allocation. Industry-wide collaboration among stakeholders and regulatory bodies underscores a rapid shift toward sustainability-oriented cattle management strategies, positioning genetics and technology as key drivers of genetically resilient and sustainable breeding systems. Full article

Pre-sowing seed treatment (priming) is a strategic tool for programming future crop yield, aimed at improving early plant development and enhancing stress resilience. This study investigated the effects of priming wheat seeds with 100 µM ibuprofen on early ontogeny under optimal conditions and salt stress (100 mM NaCl). An evaluation of germination energy, growth parameters, phytohormone levels (abscisic acid, indolylacetic acid, and cytokinins) and the status of the antioxidant system in 7-day-old seedlings demonstrated that ibuprofen treatment stimulates wheat growth and tolerance, despite its absence of accumulation in plant tissues. Modulation of hormonal balance plays a key role in these protective effects: under optimal conditions, ibuprofen elevates abscisic acid and indolylacetic acid levels, while under salt stress, it prevents excessive abscisic acid accumulation and mitigates the stress-induced decline in indolylacetic acid and cytokinins. Furthermore, ibuprofen promotes a coordinated increase in glutathione, ascorbate, and H₂O₂ levels, concomitant with the activation of key enzymes (glutathione reductase and ascorbate peroxidase), thereby enhancing the plants’ antioxidant potential. Under saline conditions, ibuprofen pretreatment also reduces stress-induced dysregulation of this system. Therefore, ibuprofen acts as a hormetic preconditioning agent that improves seedling vigor and stress tolerance by fine-tuning hormonal signaling and redox metabolism. Full article

Integrated control systems (Supervisory Control and Data Acquisition–SCADA and Manufacturing Execution Systems—MES) constitute the backbone of Industry 4.0; however, research on their implementation remains scarce. This study analyzes the opportunities and challenges of modernizing these systems within the context of the Brazilian industry. A survey of 101 experts was conducted, with results analyzed via Friedman and Holm–Sidak nonparametric tests to establish a clear hierarchy of factors. Findings reveal that while economic efficiency, productivity gains, and real-time remote access represent the most significant opportunities, they are countered by critical structural challenges: obsolete machinery and inadequate infrastructure. These challenges significantly inflate implementation costs and highlight the reality of technological obsolescence that is typical of emerging economies. By applying the Resource-Based View (RBV), this research frames digital integration as a strategic competitive capability rather than a mere technical upgrade. Practically, the study provides a roadmap for industrial leaders to balance digital agility expectations with pragmatic operational constraints. These insights offer a foundation for successful digital transformation, delivering actionable value for academics, industrial managers, and policymakers. Full article

Despite the growing recognition of Artificial Intelligence (AI)’s potential for global education, the literature lacks strategic analyses on how to maximize personalized learning and ensure equitable access within the vast and diverse Indian educational system. The objective of this study is to analyze this strategic integration of AI into the Indian educational system, focusing on maximizing personalized learning and ensuring equitable access across diverse socioeconomic contexts, while evaluating current initiatives and the relevance of reporting guidelines, such as the use of Self-Sovereign Identity (SSI). The methodology employed bibliographic and documentary research, alongside the analysis of governmental and sectoral policies. The results indicate that the sustainable implementation of AI is critically dependent on the mitigation of algorithmic bias and the rigorous assurance of data privacy. In conclusion, to balance technological innovation with human-centered pedagogical approaches, maintaining the educator’s fundamental role and fostering collaboration among stakeholders for responsible governance are essential. Full article

Teacher education represents a global strategic priority for improving educational systems and fostering inclusive, high-quality processes. Recent studies highlight the need for systematic and replicable education models capable of addressing the challenges of contemporary complexity and bridging the gap between theory and practice. Teaching professionalism is increasingly recognized as a key driver of change, requiring a balance of pedagogical, relational, and technological competences, along with strong reflective capacity. Within this framework, practicum programs play a crucial role for the development of professional identity and authentic teaching skills. Methods: This contribution adopts a theoretical–argumentative approach grounded in a critical analysis of the international scientific literature on teacher education, with specific focus on the role of practicums. The aim is to present the model implemented by Pegaso University in the context of practicum activities within initial teacher education programs to outline an interpretative framework and provide pedagogical reflections in light of the results arising from critical reflection and systematic monitoring (not covered in this specific contribution) of the effectiveness of the model implemented in the first two training cycles (academic years 23–24 and 24–25), with the involvement of 5 regions and a total of 2834 teachers in the first cycle and 10 regions and a total of 5551 teachers in the second cycle. Convenience sampling based on a non-probabilistic method was adopted, using the entire sample of teachers admitted to the training program who met the requirements of Article 7 of the Decree of the President of the Council of Ministers (DPCM). Results: This paper outlines the theoretical and methodological trajectories of the model, offering interpretative frameworks and pedagogical reflections in light of the outcomes achieved during the initial implementation phase. Conclusions: In accordance with recent national and European regulatory frameworks, the Pegaso teaching model is presented as an example of good practice for initial teacher education. It aims to foster a reflective, situated, and responsible teaching professionalism, moving beyond traditional approaches toward a continuous and transformative learning process. Full article

As transparency and sustainability gain strategic importance, the mass balance approach under chain of custody (MB-CoC) has become a central mechanism for assessing product carbon footprints (PCFs) in complex chemical value chains. The MB-CoC enables the attribution of renewable and recycled feedstock characteristics via certified bookkeeping when physical segregation or molecular tracing is infeasible—thus complementing PCF methodologies based on ISO 14067 and the LCA standards ISO 14040/44. However, the methodological integration of the MB-CoC into ISO-conformant PCFs remains insufficiently defined and empirically underexplored. This paper systematically reviews the interaction between the MB-CoC and PCF/LCA frameworks. It (i) synthesizes the allocation rules of ISO 14040/44/67 and the attribution principles of the MB-CoC according to ISO 22095 and key industry initiatives; (ii) analyzes academic publications, guidelines, and corporate applications; and (iii) identifies methodological tensions concerning system boundaries, allocation logic, residual mixes, treatment of biogenic and recycled carbon, and risks of double counting. Our review reveals five recurring insights across the literature: the need for certification and standardization; the importance of primary data and residual mixes; the requirement for ISO conformity; the necessity of transparent reporting of conventional versus alternative inputs; and the lack of independent empirical case studies. Addressing these gaps through harmonized rules, residual mix development, and comparative applications will be essential for establishing the MB-CoC as a robust instrument for circularity, decarbonization, and regulatory compliance, developed by interdisciplinary research and industry approaches. Full article

This paper analyses the role of landscape as a fundamental dimension of post-earthquake recovery in the inland areas of Central Italy, arguing that reconstruction must be understood not only as the repair of damaged buildings but as a broader territorial process affecting identity, spatial organization, and long-term settlement trajectories. In this sense, post-earthquake recovery is also interpreted as a strategic opportunity to reinforce coast–inland relationships, acknowledging the structural interdependence between inland Apennine areas and coastal urban systems. Drawing on insights from applied research conducted in the L’Aquila 2009 crater and on the conceptual framework developed within the PRIN TRIALS project, the paper discusses how seismic events accelerate pre-existing territorial dynamics and produce enduring transformations, particularly in the proximity landscapes surrounding historic centres. Rather than presenting empirical findings, the contribution offers a theoretical and operational framework aimed at integrating landscape considerations into reconstruction processes. It outlines key concepts such as landscape quality, transformative resilience, and permanent temporariness; reviews critical normative aspects linked to emergency procedures; and proposes a set of landscape-oriented guidelines and criteria for the contextual integration of reconstruction projects. These include landscape quality objectives, multiscalar readings of identity values, and operational tools such as visual-impact assessment, Project Reference Context analysis, and principles for managing transformations in peri-urban and historic environments. Overall, the paper argues that adopting a landscape-based perspective can strengthen territorial cohesion, support the sustainable redevelopment of historic centres and their surroundings, and embed post-earthquake reconstruction within broader coast–inland territorial strategies aimed at long-term resilience and balanced regional development in Apennine communities. Full article

In the era of digital transformation, organizations increasingly invest in Artificial Intelligence (AI) to enhance competitiveness, yet persistent evidence shows that AI investment does not automatically translate into superior firm performance. Drawing on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), this study aims to explain this paradox by examining how AI-enabled dynamic capability (AIDC) is converted into performance outcomes through organizational mechanisms. Specifically, the study investigates the mediating roles of organizational data-driven culture (DDC) and organizational learning (OL). Data were collected from 254 senior managers and executives in U.S. firms actively employing AI technologies and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that AIDC exerts a significant direct effect on firm performance as well as indirect effects through both DDC and OL. Serial mediation analysis reveals that AIDC enhances performance by first fostering a data-driven mindset and subsequently institutionalizing learning processes that translate AI-generated insights into actionable organizational routines. Moreover, DDC plays a contingent moderating role in the AIDC–performance relationship, revealing a nonlinear effect whereby excessive reliance on data weakens the marginal performance benefits of AIDC. Taken together, these findings demonstrate the dual role of data-driven culture: while DDC functions as an enabling mediator that facilitates AI value creation, beyond a threshold it constrains dynamic reconfiguration by limiting managerial discretion and strategic flexibility. This insight exposes the “dark side” of data-driven culture and extends the RBV and DCT by introducing a boundary condition to the performance effects of AI-enabled capabilities. From a managerial perspective, the study highlights the importance of balancing analytical discipline with adaptive learning to sustain digital efficiency and strategic agility. Full article

Background: Nutrition during the perinatal period, including pregnancy, childbirth, postpartum, and lactation, is a critical determinant of maternal and neonatal health. While the importance of balanced nutrition is well established, the integration of nutritional counseling into midwifery care remains inconsistent across settings. Evidence suggests that midwives are uniquely positioned to deliver nutrition-related support, yet gaps persist in their formal training and in the availability of structured guidance. These gaps are particularly evident in certain regions, such as Greece, where dedicated national guidelines for perinatal nutrition are lacking. Methods: This systematized narrative review synthesises evidence from studies published between 2010 and 2025, retrieved through PubMed, CINAHL, Scopus, and relevant national guidelines. Although the synthesis draws on diverse study designs to provide contextual depth, randomized controlled trials (RCTs) were prioritized and synthesized separately to evaluate the effectiveness of midwife-led interventions. In total, ten randomized controlled trials were included in the evidence synthesis, alongside additional observational and qualitative studies that informed the narrative analysis. Both international and Greek literature were examined to capture current practices, challenges, and knowledge gaps in the nutritional dimension of midwifery care. Results: Findings indicate that adequate intake of macronutrients and micronutrients, including iron, folic acid, vitamin D, iodine, calcium, and omega-3 fatty acids, is essential for optimal maternal and neonatal outcomes. Despite this, studies consistently report insufficient nutritional knowledge among midwives, limited confidence in providing counseling, and variability in clinical practice. Socio-cultural factors, such as dietary traditions and migration-related challenges, further influence nutritional behaviors and access to guidance. Emerging approaches, including e-health tools, group counseling models, and continuity-of-care frameworks, show promise in enhancing midwives’ capacity to integrate nutrition into perinatal care. Conclusion: Nutrition is a cornerstone of perinatal health, and midwives are strategically placed to address it. However, gaps in training, inconsistent guidelines, and cultural barriers limit the effectiveness of current practices. Strengthening midwifery education in nutrition, developing context-specific tools, and fostering interdisciplinary collaboration are essential steps toward more comprehensive and culturally sensitive perinatal care. Future research should focus on longitudinal and intervention studies that assess the impact of midwife-led nutritional counseling on maternal and neonatal outcomes. Full article

The strategic balance between strength and electrical conductivity in Al-Mg-Si alloys is a critical challenge that must be overcome to enable their widespread adoption as viable alternatives to copper conductors in power transmission systems. To address this, the present study comprehensively investigates model alloys with Mg/Si ratios ranging from 1.0 to 2.0. A multi-faceted experimental approach was employed, combining tailored thermo-mechanical treatments (solution treatment, cold drawing, and isothermal annealing) with comprehensive microstructural characterization techniques, including electron backscatter diffraction (EBSD) and scanning electron microscopy (SEM). The results elucidate a fundamental competitive mechanism governing property optimization: excess Mg atoms concurrently contribute to solid-solution strengthening via the formation of Cottrell atmospheres around dislocations, while simultaneously enhancing electron scattering, which is detrimental to conductivity. A critical synergy was identified at the Mg/Si ratio of 1.75, which promotes the dense precipitation of fine β″ phase while facilitating extensive recovery of high dislocation density. Furthermore, EBSD analysis confirmed the development of a microstructure comprising 74.1% high-angle grain boundaries alongside a low dislocation density (KAM ≤ 2°). This specific microstructural configuration effectively minimizes electron scattering while providing moderate grain boundary strengthening, thereby synergistically achieving an optimal balance between strength and electrical conductivity. Consequently, this work elucidates the key quantitative relationships and competitive mechanisms among composition (Mg/Si ratio), processing parameters, microstructure evolution, and final properties within the studied Al-xMg-0.5Si alloy system. These findings establish a clear design guideline and provide a fundamental understanding for developing high-performance aluminum-based conductor alloys with tailored Mg/Si ratios. Full article

This mixed-methods study investigates the strategic management of digital transformation in Bulgarian schools by analysing principals’ self-reported leadership practices and styles. Using data from a nationally representative sample (N = 349) gathered through the SELFIE tool, complemented by 30 in-depth interviews, the research examines how school leaders understand and enact their roles as digital leaders within a context of fragmented policies and uneven digital capacity. Quantitative results reveal a central paradox: although 89.7% of principals claim to actively support teachers’ digital innovation, only about half report having a formalised digital strategy. This imbalance between strong operational support and weak institutionalisation reflects the dominant approach to school digitalisation in Bulgaria. Qualitative cluster analysis identifies three leadership profiles: (1) a strategic–collaborative profile, characterised by long-term planning, partnerships, and data-driven decisions; (2) a supportive–collaborative profile focused on teacher communities and context-specific professional development but lacking strategic vision; and (3) a balanced–pragmatic profile oriented toward measurable improvements and adaptive responses. Triangulation with national assessment data shows that leadership styles align with institutional contexts: high-performing schools tend to apply strategic–collaborative leadership, while lower-performing schools adopt pragmatic, adaptive approaches. The study argues that digital transformation requires context-sensitive frameworks recognising multiple developmental trajectories, highlighting the need for differentiated policies that support strategic institutionalisation of existing digital innovations while addressing structural inequalities. Full article

The European forest-based sector faces a perfect storm of demographic, geopolitical, climatic, and policy-driven challenges. These multipronged, oftentimes interlinked factors are particularly consequential for export-oriented, forest-rich economies like Sweden. This study provides a qualitative scenario analysis to assess potential futures for the Swedish forest sector towards 2050, focusing on the impacts of key drivers: geopolitical alignment, European Union (EU) policy implementation, economic and demographic trends, technological progress, and climate change. Two critical uncertainties—Europe’s geopolitical positioning and the policy balance between wood use and forest conservation—form the axes for four contrasting scenarios. Results indicate that, across all futures, volume-based manufacturing in Sweden is expected to stagnate or decline due to high costs and weak EU demand, with bulk production shifting to the Global South. Long-term viability hinges on a strategic shift to high-value segments (e.g., specialty packaging solutions, biochemicals, construction components) and the adoption of advanced technologies. Concurrently, the sector must adapt to increased forest disturbances and diversify tree species, despite industry processes being optimized for current conifers. The study concludes that without a decisive transition from commodity production to innovative, value-added strategies, the Swedish forest sector’s competitiveness and resilience are at serious risk. Full article

Metal additive manufacturing (AM) generates complex microstructures through extreme thermal gradients and rapid solidification, critically influencing mechanical performance and industrial qualification. This review synthesizes recent advances in cellular automata (CA) and phase-field (PF) modeling to predict grain-scale microstructure evolution during AM. CA methods provide computational efficiency, enabling large-domain simulations and excelling in texture prediction and multi-layer builds. PF approaches deliver superior thermodynamic fidelity for interface dynamics, solute partitioning, and nonequilibrium rapid solidification through CALPHAD coupling. Hybrid CA–PF frameworks strategically balance efficiency and accuracy by allocating PF to solidification fronts and CA to bulk grain competition. Recent algorithmic innovations—discrete event-inspired CA, GPU acceleration, and machine learning—extend scalability while maintaining predictive capability. Validated applications across Ni-based superalloys, Ti-6Al-4V, tool steels, and Al alloys demonstrate robust process–microstructure–property predictions through EBSD and mechanical testing. Persistent challenges include computational scalability for full-scale components, standardized calibration protocols, limited in situ validation, and incomplete multi-physics coupling. Emerging solutions leverage physics-informed machine learning, digital twin architectures, and open-source platforms to enable predictive microstructure control for first-time-right manufacturing in aerospace, biomedical, and energy applications. Full article