Search Results (1,489)

Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional state (e.g., mastery, confidence, context, and decay). The seamless integration of in-workflow performance data will transform daily work activities into granular and actionable data points through AI-powered dynamic xAPI generation into Learning Record Stores (LRSs). This system enables continuous, authentic performance-based assessment, precise skill gap identification, and highly personalized interventions. The significance of this ecosystem lies in its ability to provide a real-time understanding of everyone’s capabilities, enabling more accurate workforce planning for the future and cultivating a workforce that is continuously learning and adapting. It ultimately helps to transform learning from a disconnected, occasional event into an integrated and responsive part of everyday work. Full article

Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires tailored evaluation tools for policymakers. This study proposes a custom-designed framework to quantify its macroeconomic effects through changes in gross domestic product (GDP) at the city level. Unlike traditional economic models, the proposed approach is specifically adapted to Hyperloop’s multimodality, infrastructure, speed profile, and digital-green footprint. A Poisson pseudo-maximum likelihood (PPML) model is developed and applied at two technology readiness levels (TRL-6 and TRL-9). Case studies of Glasgow, Berlin, and Busan are used to simulate impacts based on geo-spatial features and city-specific trade and accessibility indicators. Results indicate substantial GDP increases driven by factors such as expanded 60 min commute catchment zones, improved trade flows, and connectivity node density. For instance, under TRL-9 conditions, GDP uplift reaches over 260% in certain scenarios. The framework offers a scalable, reproducible tool for policymakers and urban planners to evaluate the economic potential of Hyperloop within the context of sustainable smart city development. Full article

Using waste biomass as a raw material for the combined production of electricity and heat offers corresponding energy, economic, environmental and resource efficiency benefits. The study examines both the performance of a system for combined energy production based on the Organic Rankine Cycle (ORC) utilizing wood biomass and the market interest in its deployment within Bulgaria. Its objective is to propose a technically and economically viable solution for the recovery of waste biomass through the combined production of electricity and heat while simultaneously assessing the readiness of industrial and municipal sectors to adopt such systems. The cogeneration plant incorporates an ORC module enhanced with three additional economizers that capture residual heat from flue gases. Operating on 2 t/h of biomass, the system delivers 1156 kW of electric power and 3660 kW of thermal energy, recovering an additional 2664 kW of heat. The overall energy efficiency reaches 85%, with projected annual revenues exceeding EUR 600,000 and a reduction in carbon dioxide emissions of over 5800 t/yr. These indicators can be achieved through optimal installation and operation. When operating at a reduced load, however, the specific fuel consumption increases and the overall efficiency of the installation decreases. The marketing survey results indicate that 75% of respondents express interest in adopting such technologies, contingent upon the availability of financial incentives. The strongest demand is observed for systems with capacities up to 1000 kW. However, significant barriers remain, including high initial investment costs and uneven access to raw materials. The findings confirm that the developed system offers a technologically robust, environmentally efficient and market-relevant solution, aligned with the goals of energy independence, sustainability and the transition to a low-carbon economy. Full article

This study investigates the relationship between the dynamic capabilities of university administration and students’ awareness of artificial intelligence (AI) tools within a higher education context. Drawing on data from 139 students at the College of Education, Sultan Qaboos University, the research employed two validated instruments, one measuring the dynamic capabilities of university administration and another assessing students’ awareness and perception of AI tool use. Understanding this relationship is critical, as universities increasingly face pressure to guide responsible and effective AI use among students. Findings reveal significant correlations between the university administration’s dynamic capabilities, particularly technological agility, and students’ engagement with AI tools. Notably, technological dynamic capabilities within the administration significantly predicted two specific dimensions of student awareness: effectiveness of using AI tools and perceived faculty members’ efficiency in AI. These results highlight the critical role of institutional leadership in promoting equitable and sustainable integration of AI in education. The study contributes to the broader discourse on AI for sustainable development by illustrating how institutional strategies can enhance innovation, inclusion, and student readiness in support of SDG 4. Full article

Background/Objectives: Military Service Members (SMs) require optimal nutrition to support health, readiness, and job performance. However, they often fall short of meeting nutrition guidelines. This study aimed to determine the impact and feasibility of implementing the U.S. Marine Corps (USMC) “Fueled to Fight^®” (F2F) nutrition program in non-appropriated fund (NAF) food venues. Objectives included evaluating changes in Military Nutrition Environment Assessment Tool (mNEAT) scores, feasibility of implementing and maintaining F2F strategies, and influence on customer purchasing patterns. Methods: Researchers conducted a pre-post interventional study from January to December 2024 at three NAF food venues across two USMC bases. F2F strategies, including identifying items using a stoplight color coding system (Green = healthy, Yellow = less healthy, Red = least healthy), menu revisions, food placement, promotion, and marketing, were implemented. Data included mNEAT assessments, sales reports, and stakeholder focus groups. Generalized Estimating Equations models were used to analyze sales data. Results: mNEAT scores increased across all venues post-intervention. Availability and sales of Green items increased, while sales of Red items decreased in some venues. Profit increased at all three food venues. Focus groups revealed feasibility and provided insights for future interventions. Conclusions: F2F interventions in NAF food venues are feasible and can positively impact the food environment and customer purchasing patterns without negatively affecting profit. This study highlights the importance of integrating nutrition programs into all military food venues, not just government-funded dining facilities, to support the nutritional fitness and readiness of SMs. Full article

Introduction: The increasing cultural diversity of patients poses new challenges for nurses. Cultural competence, especially knowledge of the cultural determinants of health and illness, is an important element of professionalism in nursing care. The aim of this study was to analyse nurses’ self-assessment of cultural knowledge, with a focus on the six dimensions of the Giger and Davidhizar model, prior to formal training in this area. Methods: A triangulation method combining qualitative and quantitative analysis was used. The analysis included 353 statements from 36 master’s student nurses. Data were coded according to six cultural phenomena: biological factors, communication, space, time, social structure, and environmental control. Content analysis, ANOVA, Spearman’s rank correlation, and cluster analysis (k-means) were conducted. Results: The most frequently identified that categories were environmental control (34%), communication (20%), and social structure (16%). Significant knowledge gaps were identified in the areas of non-verbal communication, biological differences, and understanding space in a cultural context. Three cultural knowledge profiles of the female participants were distinguished: pragmatic, socio-reflective, and critical–experiential. Conclusions: The cultural knowledge of the participants was fragmented and simplified. The results indicate the need to personalise cultural learning and to take into account nurses’ level of readiness and experience profile. The study highlights the importance of the systematic development of reflective and contextual cultural knowledge as a foundation for competent care. Full article

The global spread of Mpox virus (MPXV) underscores the urgent need for rapid, field-deployable diagnostic tools, especially in low-resource settings. We evaluated a loop-mediated isothermal amplification (LAMP) assay, termed LAMPOX, developed by Coris BioConcept. The assay was tested in three formats—two liquid versions and a dried, ready-to-use version—targeting only the ORF F3L (Liquid V1) or both the ORF F3L and N4R (Liquid V2 and dried) genomic regions. Analytical sensitivity and specificity were assessed using 60 clinical samples from confirmed MPXV-positive patients. Sensitivity on clinical samples was 81.7% for Liquid V1 and 88.3% for Liquid V2. The dried LAMPOX assay demonstrated a sensitivity of 88.3% and a specificity of 100% in a panel of 112 negative controls, with most positive samples detected in under 7 min. Additionally, a simplified sample lysis protocol was developed to facilitate point-of-care use. While this method showed slightly reduced sensitivity compared to standard DNA extraction, it proved effective for samples with higher viral loads. The dried format offers key advantages, including ambient-temperature stability and minimal equipment needs, making it suitable for point-of-care testing. These findings support LAMPOX as a promising tool for rapid MPXV detection during outbreaks, especially in resource-limited settings where traditional PCR is impractical. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

This study assessed the effectiveness of stress-based cognitive-behavioral training compared to standard training in firefighters, emphasizing their ability to distribute extinguishing water and cool environments evenly during enclosure fires. Experiments took place at the Zbiroh training facility with two firefighter teams (Team A with stress-based training and Team B with standard training) under realistic conditions. Using 58 thermocouples and 4 radiometers, temperature distribution and radiant heat flux were measured to evaluate water distribution efficiency and cooling performance during interventions. Team A consistently achieved temperature reductions of approximately 320 °C in the upper layers and 250–400 °C in the middle layers, maintaining stable conditions, whereas Team B only achieved partial cooling, with upper-layer temperatures remaining at 750–800 °C. Additionally, Team A recorded lower radiant heat flux densities (e.g., 20.74 kW/m² at 0°) compared to Team B (21.81 kW/m²), indicating more effective water application and adaptability. The findings confirm that stress-based training enhances firefighters’ operational readiness and their ability to distribute water effectively during interventions. This skill is essential for safer and effective management of indoor fires under extreme conditions. This study supports the inclusion of stress-based and scenario-based training in firefighter education to enhance safety and operational performance. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

As the global energy transition accelerates, the integration of solar power and artificial intelligence (AI) technologies offers new pathways for sustainable local development. This study examines four Serbian municipalities—Šabac, Sombor, Pirot, and Čačak—to assess how AI-enabled solar power systems can enhance energy resilience, reduce emissions, and support community-level sustainability goals. Using a mixed-method approach combining spatial analysis, predictive modeling, and stakeholder interviews, this research study evaluates the performance and institutional readiness of local governments in terms of implementing intelligent solar infrastructure. Key AI applications included solar potential mapping, demand-side management, and predictive maintenance of photovoltaic (PV) systems. Quantitative results show an improvement >60% in forecasting accuracy, a 64% reduction in system downtime, and a 9.7% increase in energy cost savings. These technical gains were accompanied by positive trends in SDG-aligned indicators, such as improved electricity access and local job creation in the green economy. Despite challenges related to data infrastructure, regulatory gaps, and limited AI literacy, this study finds that institutional coordination and leadership commitment are decisive for successful implementation. The proposed AI–Solar Integration for Local Sustainability (AISILS) framework offers a replicable model for emerging economies. Policy recommendations include investing in foundational digital infrastructure, promoting low-code AI platforms, and aligning AI–solar projects with SDG targets to attract EU and national funding. This study contributes new empirical evidence on the digital–renewable energy nexus in Southeast Europe and underscores the strategic role of AI in accelerating inclusive, data-driven energy transitions at the municipal level. Full article

Background/Objectives: Heart transplantation is a life-saving procedure for patients with end-stage heart failure, yet it involves significant psychological and emotional challenges throughout its various stages. International guidelines recommend a multi-professional approach to the care of these patients and a psycho-social assessment for listing. The recommendations focus on content aspects, but not on the psychometric measure to be administered to patients as part of the assessment. Therefore, the purpose of this study is to provide the preliminary results of administering the protocol used by our center, measuring coping strategies, cognitive functioning, quality of life, and psychological distress in a sample of patients who are candidates for and undergo cardiac transplantation, and to observe any variations after the procedure. Methods: We conducted a comprehensive psychological-clinical assessment involving 40 patients, focusing on psychosocial functioning, cognitive reserves, mental health, and coping strategies. Tools such as the Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT), Beck Depression Inventory-II (BDI-II), Montreal Cognitive Assessment (MoCA), General Anxiety Disorder 7 (GAD-7), and Medical Outcomes Survey Short Form 36 (SF-36) were employed to evaluate readiness for transplantation and post-transplant adaptation. Results: Results showed high levels of clinical anxiety (52.5%) and low perceived physical health (98%) before the transplant, while post-operative evaluations indicated reduced anxiety (13.51%) and depressive symptoms (10.81%), along with improved psychological well-being and reintegration into daily life. Conclusions: These results show improvement in physical and cognitive levels, accompanied by a state of enhanced psychological well-being after transplantation. A longitudinal psychological approach, from pre-transplant screening to post-discharge follow-up, is needed to address distress, improve coping mechanisms, and promote treatment adherence. This integrative strategy is critical to improving the quality of life and long-term outcomes for heart transplant recipients. Full article

Background: The spread of ESBL-producing Enterobacteriaceae (ESBL-PE) strains in food poses a potential risk to human health. The aim of the study was to determine the occurrence of ESBL-PE and to investigate their distribution on foods. Methods: A total of 1000 food samples, including both raw and ready-to-eat products, was analyzed for the presence of ESBL-producing Enterobacteriaceae using chromogenic selective agar. Antibiotic resistance in the isolated strains was assessed using conventional methods, while whole-genome sequencing was employed to predict antimicrobial resistance and virulence genes. Results: The overall occurrence of ESBL-PE strains was 2.8%, with the highest contamination in raw meat samples (10%). A total of 31 multidrug-resistant (MDR) strains was isolated, mainly Escherichia coli, followed by Klebsiella pneumoniae, Salmonella enterica, and Enterobacter hormaechei. All strains exhibited high levels of resistance to at least four different β-lactam antibiotics, as well as to other antimicrobial classes including sulfonamides, tetracyclines, aminoglycosides, and quinolones. Whole-genome sequencing identified 63 antimicrobial resistance genes, with bla_CTX-M being the most prevalent ESBL gene. Twenty-eight (90%) isolates carried Inc plasmids, known vectors of multiple antimicrobial resistance genes, including those associated with ESBLs. Furthermore, several virulence genes were identified. Conclusions: The contamination of food with ESBL-PE represents a potential public health risk, underscoring the importance of the implementation of genomic surveillance to monitor and control the spread of antimicrobial resistance. Full article

Background/Objectives: This scoping review critically evaluated existing literature and summarized the impact of occupational, physiological, and psychological stressors on adrenal and neuroendocrine responses, body composition, and physical performance amongst women in tactical occupations. Methods: Boolean searches identified potentially qualifying reports involving: (1) adult women (≥19 y) currently employed or completing their training for a tactical profession; (2) ≥1 marker of “stress”; and (3) ≥1 adrenal, neuroendocrine, body composition, or fitness/performance outcome. Quantitative data (e.g., sample characteristics, outcomes of interest) were extracted and summarized. The completeness of reporting for each study was documented using existing checklists and quantified as: low (<50%), moderate (50–79%), or high (≥80%). Results: 40 studies (k) of moderate reporting quality (~64%) were included in the final sample (3693 women); 11 studies (28%) focused on women exclusively, and 16 studies identified sex differences in ≥1 outcome. Most studies involved military trainee populations (80%, k = 32). Occupation-related stress tended to negatively impact adrenal, neuroendocrine, body composition, and performance outcomes. Conclusions: This review highlights progress in assessing occupational performance in female tactical personnel exposed to diverse stressors; however, our understanding remains incomplete due to methodological and conceptual limitations in the literature. Holistic research strategies are needed to capture the complexity of performance readiness in women, integrating how stress affects key tactical performance aspects such as muscle physiology, reproductive health, and energy and nutrient balance in realistic operational contexts. Integrating such data is vital for informing policy, improving readiness, and enhancing the health and career longevity of female tactical personnel. Full article

Healthcare Information Systems (HISs) are essential for improving care quality, managing chronic diseases, and supporting clinical decision-making. Despite significant investments, HIS implementations often fail due to the complexity of healthcare environments. Maturity Models (MMs) have emerged as tools to guide organizational improvement by assessing readiness, process efficiency, technology adoption, and interoperability. This study presents a comprehensive literature review identifying 45 Maturity Models used across various healthcare domains, including telemedicine, analytics, business intelligence, and electronic medical records. These models, often based on Capability Maturity Model Integration (CMMI), vary in structure, scope, and maturity stages. The findings demonstrate that structured maturity assessments help healthcare organizations plan, implement, and optimize HIS more effectively, leading to enhanced clinical and operational performance. This review contributes to an understanding of how different MMs can support healthcare digital transformation and provides a resource for selecting appropriate models based on specific organizational goals and technological contexts. Full article