Search Results (2,007)

Welsh onion (Allium fistulosum L.), a globally significant vegetable, flavoring agent, and phytomedicine resource, has remained unavailable with established transient expression platforms for functional genomic investigations. To address this critical methodological limitation, we present systematically optimized protocols for both Agrobacterium-mediated hairy root transformation and protoplast transient expression systems, achieving significant advances in transformation efficiency for this species. Through systematic optimization of key parameters, including Agrobacterium rhizogenes (A. rhizogenes) strain selection (with Ar.Qual demonstrating superior performance), explant type efficacy, bacterial suspension optical density (OD₆₀₀ = 0.3), and acetosyringone induction concentration (100 μM), we established a highly efficient stem disc infection methodology, achieving 88.75% hairy root induction efficiency. Subsequent optimization of protoplast isolation protocols identified the optimal enzymatic digestion conditions: 6-h dark digestion of young leaves using 1.0% (w/v) Cellulase R-10, 0.7% (w/v) Macerozyme R-10, and 0.4 M mannitol, yielding 3.3 × 10⁶ viable protoplasts g⁻¹ FW with 90% viability. System functionality validation through PEG-mediated transient transformation demonstrated successful green fluorescent protein (GFP) reporter gene expression, confirmed by fluorescence microscopy. As the first documented transient expression platforms for Welsh onion, these protocols enable essential molecular investigations, including in planta promoter activity profiling, subcellular protein localization, and CRISPR-based genome-editing validation. This methodological breakthrough overcomes previous technical constraints in Welsh onion molecular biology, providing critical tools for accelerated gene functional characterization in this agriculturally important species. Full article

The research and analyses presented in this paper are an attempt to prove the concept that a flexible and efficient energy transformation requires a gradual digitalization of the energy system, starting from the inside out, i.e., from the low-voltage micro- and nano-grids, which mostly integrate low-power photovoltaic power plants and consumers with similar demand profiles. This approach is supported by the two main advantages of these grids: they are almost similar in structure and they are scalable, the two characteristics indicating a possible successful digitalization. For this to happen, we need to study the problems in these grids and be aware of the technological maturity of the energy facilities. This paper (the first of several to follow) examines the electricity performance problems caused by the stochastic nature of solar generation. A technique for monitoring and predictive load analysis is proposed, as well as technical measures for implementing decentralised control. Full article

Turfgrass systems in European urban green spaces, including sports fields, golf courses, and residential lawns, must balance high performance with compliance with stricter pesticide regulations. This review examines Synergistic Pest Management (SPM), an advanced form of Integrated Pest Management (IPM) that integrates monitoring, biological, cultural, and targeted chemical strategies for sustainable control of major turfgrass pests. Focus is placed on key insect pests such as Tipula spp. larvae and chafer beetle grubs (Scarabaeidae) and fungal pathogens, including Microdochium nivale, Clarireedia spp., Laetisaria fuciformis, Gaeumannomyces graminis var. avenae, and Colletotrichum spp., which cause significant losses in Central Europe and similar regions. Effective combinations include entomopathogenic nematodes with fungi, endophyte-infected cultivars with optimized mowing and irrigation, and low-dose insecticides paired with biological agents. The review considers how soil conditions, environmental timing, and maintenance practices influence success. Practical tools such as decision-support matrices and a seasonal calendar are provided for regional use. SPM can reduce chemical inputs, enhance biodiversity, and improve turf resilience, but adoption is limited by biological sensitivity, product availability, costs, and technical demands. SPM aligns with EU Directive 2009/128 and offers a pathway to sustainable turfgrass pest management. Future efforts should focus on regional validation, practitioner training, and precision technologies. Full article

Background/Objectives: Nipple trauma is a common challenge during the early postpartum period, often undermining maternal confidence and breastfeeding success. Although deep-learning-based image analysis offers the potential for objective and remote assessments, its feasibility in clinical practice has not been well examined. This study aimed to evaluate the feasibility and acceptability of a deep-learning-based nipple trauma assessment system and explore maternal perceptions of the intervention. Methods: A quasi-experimental study was conducted at a maternity hospital in Japan. Participants were assigned to intervention or control groups based on their delivery month. Mothers in the intervention group used a dedicated offline smartphone to photograph their nipples during hospitalization. Images were analyzed using a pretrained deep-learning model, and individualized feedback was delivered via a secure messaging platform. Self-administered questionnaires were collected at three points: late pregnancy, during hospitalization, and one month postpartum. Maternal experiences and satisfaction with breastfeeding were also assessed. Results: A total of 23 participants (intervention = 8 and control = 15) completed the study. The system functioned without technical errors, and no adverse events were reported. Most participants found the AI results useful, with 75% receiving high-confidence outputs (predicted class probability ≥ 60%). Participants expressed interest in real-time feedback and post-discharge use. Breastfeeding self-efficacy scores (BSES-SF) improved more in the intervention group (+9.8) than in the control group (+7.8). Conclusions: This study confirmed the feasibility and acceptability of a deep-learning-based nipple trauma assessment system during postpartum hospitalization. The system operated safely and was well received by participants. Future developments should prioritize real-time, remote functionality to support diverse maternal needs. Full article

Background: Cellulosimicrobium, formerly known as the Oerskovia genus, is a Gram-positive organism known for its characteristic bright yellow colonies. While abundant in nature, it is very rarely linked to pathogenesis in humans. While there is no classical presentation for Cellulosimicrobium-associated infections, cases tend to be foreign body-related or involve immunocompromised patients. Rates of Cellulosimicrobium-associated infections have been hypothesised to rise in the future, due to rising numbers of immunocompromised patients in the community and increasing usage of foreign bodies such as prostheses and long-term catheters. Existing technical difficulties regarding misidentifying cultures as other species (often other coryneforms) may also play a significant role in the low number of documented cases, and this may change in the near future with diagnostic advancements such as whole genomic sequencing. Case Presentation: A 57-year-old immunocompetent Irish male presented with concomitant neck and lung masses. Notably, this was found to be directly following a recent dental procedure. During extensive investigations, Cellulosimicrobium was isolated from biopsied lung tissue using 16S ribosomal ribonucleic acid gene-sequencing analysis. The patient was treated with long-term oral amoxicillin and safely discharged, with both masses showing measurable reductions in size on subsequent imaging. Conclusions: Should Cellulosimicrobium represent the causative pathological organism in this case, then we believe this to represent a potential novel documented presentation of the organism’s pathogenesis in humans. We provide detailed discussion surrounding the successful management of this patient and the evaluation of the evolving differential diagnosis throughout this case. Full article

In the context of the rapid digitalization of higher education, proactive artificial intelligence (AI) agents embedded within multi-agent systems (MAS) offer new opportunities for personalized learning, improved quality of education, and alignment with sustainable development goals. This study aims to analyze how such AI solutions are perceived by students at Narxoz University (Kazakhstan) prior to their practical implementation. The research focuses on four key aspects: the level of student trust in AI agents, perceived educational value, concerns related to privacy and autonomy, and individual readiness to use MAS tools. The article also explores how these solutions align with the Sustainable Development Goals—specifically SDG 4 (“Quality Education”) and SDG 8 (“Decent Work and Economic Growth”)—through the development of digital competencies and more equitable access to education. Methodologically, the study combines a bibliometric literature analysis, a theoretical review of pedagogical and technological MAS concepts, and a quantitative survey (n = 150) of students. The results reveal a high level of student interest in AI agents and a general readiness to use them, although this is tempered by moderate trust and significant ethical concerns. The findings suggest that the successful integration of AI into educational environments requires a strategic approach from university leadership, including change management, trust-building, and staff development. Thus, MAS technologies are viewed not only as technical innovations but also as managerial advancements that contribute to the creation of a sustainable, human-centered digital pedagogy. Full article

Location-based games offer innovative approaches for health promotion among older adults, but their effectiveness depends on understanding complex contextual factors beyond technological design. In our study, we aimed to adapt a location-based game in the form of a smartphone application which originally targeted younger people. We employed ethnographic observations in a field test under real-world conditions for identifying the needs and preferences of older adults in this regard. Field notes of one co-creative workshop were analyzed using thematic analysis. Four key contextual factor categories emerged that significantly influenced user engagement: (1) temporal/spatial factors including weather conditions, topography, and traffic safety that impacted screen visibility and cognitive function; (2) virtual-physical orientation challenges requiring high cognitive load to transfer abstract digital maps to real environments; (3) individual factors such as technical competence, mobility levels, and prior accessibility experiences that shaped usage patterns; and (4) social dynamics that provided motivation and peer support while potentially creating exclusionary practices. Successful digital health innovations for older adults require a socio-technical systems approach that addresses environmental conditions, reduces cognitive transfer demands between virtual and physical navigation, leverages social elements while preventing exclusion, and accounts for heterogeneity among older adults as contextually interactive factors rather than merely individual differences. Full article

Aim: This study extends existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often overlooked group of stakeholders in the adoption of new technologies within the hotel sector. The objective of this research is to investigate the perceptions of hotel employees in Hong Kong regarding the implementation of Metaverse hotels. This study emphasizes their evaluations of the strengths, weaknesses, opportunities, and threats associated with these establishments through a SWOT analysis. Ultimately, the study aims to provide recommendations for addressing technological challenges, supporting employees during the transition, and facilitating adaptation across the industry. Design/Methodology/Approach: A convenience and purposive sampling method is employed to investigate 20 participants, comprising hotel staff from various departments in the Metaverse hotel in Hong Kong. This study adopts a qualitative research design, utilizing semi-structured interviews to gather in-depth insights into the perceptions of the Metaverse hotel among these employees. Purposive sampling ensures that participants have relevant experience and familiarity with VR/AR technologies. Interviews, each lasting 45–60 min, were conducted in person, with informed consent obtained beforehand. Findings: The exploration of hotel employees’ perceptions of Metaverse hotels in Hong Kong underscores the innovative potential of these establishments to enhance operational efficiency and guest engagement, while also offering new training opportunities and streamlining daily tasks. However, employees express concerns about the potential erosion of personal interactions, which are crucial to the hospitality experience, and foresee significant technical and integration challenges. Despite these drawbacks, Metaverse hotels present distinctive opportunities for market differentiation, appealing to tech-savvy guests and generating new revenue streams that contribute to industry growth. Nonetheless, potential threats such as guest skepticism and challenges in industry adaptation highlight the necessity for cautious implementation and robust privacy measures. Balancing these aspects—strengths, weaknesses, opportunities, and threats—will be pivotal for the successful integration of Metaverse technologies into the hotel industry. Theoretical/Practical Implications: Participants recognized that the Metaverse hotel could offer various potential benefits for both employees and businesses, such as enhanced operational efficiencies and new opportunities for guest engagement. Understanding the perceptions of hotel staff towards the Metaverse carries significant real-world implications for shaping policies, practices, and technologies that facilitate its operational success and market acceptance. Leveraging these insights enables the optimization of Metaverse’s advantages while mitigating associated risks and drawbacks. This study advances existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often neglected group of stakeholders in the adoption of new technologies within the hospitality sector. By understanding the perspectives of hotel employees, this research provides valuable insights into the practical challenges and benefits of implementing Metaverse technologies in the hotel industry. Originality/Value: The Metaverse hotel is still relatively new and evolving, making it crucial to conduct research to understand how hotel staff perceive it. However, there is limited research specifically focusing on the perceptions of hotel employees regarding Metaverse hotels. This gap highlights the need for a comprehensive investigation into how employees perceive the strengths, weaknesses, opportunities, and threats of implementing the Metaverse in hotels. Full article

The social integration of artificial intelligence (AI) poses fundamental challenges to value-driven domains such as education, where the adoption of new technologies raises not merely technical but also deeply rooted ethical and identity-related questions. While dominant technology acceptance models (e.g., TAM and UTAUT) primarily focus on cognitive-rational factors (e.g., perceived usefulness), they often overlook the cultural and value-based elements that fundamentally shape adaptation processes. Addressing this research gap, the present study examines how two hitherto under-researched factors—religiosity and teacher’s sense of calling—influence teachers’ attitudes toward AI and, ultimately, its adoption. The research is based on a survey of 680 Catholic secondary school teachers in Hungary. To analyse the data, we employed structural equation modelling (PLS-SEM) to examine the mechanisms of influence among religiosity, sense of calling, and AI attitudes. The results indicate that neither religiosity nor a sense of calling exerts a significant direct effect on AI adoption, and their indirect effects are also marginal. Although statistically significant relationships were found—stronger religiosity reduces a supportive evaluation of AI, while a higher sense of calling increases AI-related concerns—their practical significance is negligible. The study’s main conclusion is that successful AI integration, building on teachers’ pragmatic attitudes, is achieved not by neglecting value-based factors, but by developing critical AI literacy that treats technology as a responsible amplifier of pedagogical work. This finding suggests that value-based extensions of technology acceptance models should be approached with caution, as the role of these factors may be more limited than theoretical considerations imply. Full article

Background and Objectives: Transpyloric (TP) feeding tube placement is a viable nutritional strategy in low birth weight infants (LBWIs) with severe gastroesophageal reflux or feeding intolerance. However, technical challenges are encountered in patients of this age group due to their small body size and the limited availability of appropriately sized equipment. Materials and Methods: We retrospectively reviewed 15 endoscopic TP tube placements performed in 12 LBWIs weighing less than 2.5 kg between May 2017 and March 2025. Emphasis was placed on procedural techniques, equipment selection, and troubleshooting strategies for successful bedside execution. Results: All procedures were performed without the use of additional accessories, by advancing a feeding tube preloaded with a guidewire under direct visualization provided by a 5.5 mm outer diameter endoscope. All procedures were technically successful, including 14 performed at the bedside using a portable endoscope. A 6 or 8 Fr feeding tube loaded with a soft-tipped guidewire was advanced through the pylorus under direct endoscopic visualization. The average body weight at the time of the procedure was 1950 ± 296 g. No complications such as mucosal injury, perforation, or tube dislodgement occurred during the procedure. The average enteral feeding volume increased from 33.4 ± 52.8 cc/kg to 92.0 ± 44.4 cc/kg within 7 days. Full enteral nutrition was achieved in all surviving patients within three weeks. The feeding tube remained in place for a mean duration of 26.1 ± 19.2 days. Conclusions: Endoscopic TP tube placement in LBWIs can be safely and reliably performed at the bedside with appropriate technical modifications. It facilitates earlier advancement to full enteral nutrition and may serve as a viable option for LBWIs unresponsive to standard feeding methods. Full article

Background and Objectives: Deep venous thrombosis (DVT) is associated with pulmonary embolism and long-term complications such as post-thrombotic syndrome (PTS). Anticoagulation prevents thrombus extension but does not actively remove clot. Interventional techniques, including catheter-directed thrombolysis, mechanical and pharmacomechanical thrombectomy, and venous stenting, have been introduced to restore venous patency and reduce complications. This systematic review summarizes current evidence on outcomes, safety, and patient selection for these procedures. Materials and Methods: A systematic search of PubMed, EMBASE, Cochrane Library, and Web of Science was conducted for studies published between January 2000 and February 2024. Eligible studies included randomized controlled trials, systematic reviews, meta-analyses, and observational studies with ≥20 patients. Extracted outcomes were technical success, thrombus clearance, venous patency, PTS, quality of life, and complications. Risk of bias was assessed using the Cochrane Risk of Bias Tool, Newcastle–Ottawa Scale, and AMSTAR-2. Results: Of 456 records screened, 35 studies were included. Randomized trials (CaVenT, ATTRACT, CAVA) showed that catheter-directed and pharmacomechanical approaches improved venous patency and reduced moderate-to-severe PTS in selected patients with iliofemoral DVT, though overall benefit was variable. Mechanical thrombectomy devices (e.g., AngioJet, ClotTriever, FlowTriever) achieved high thrombus clearance and shorter procedural times, with device-specific complication profiles. Observational data demonstrated venous stenting patency rates of 74–89% at 12 months. Study heterogeneity limited direct comparisons. Conclusions: Interventional procedures can reduce PTS and improve outcomes in carefully selected patients, particularly those with acute iliofemoral DVT. Modern mechanical and pharmacomechanical techniques enhance efficiency and safety, while venous stenting addresses underlying obstructions. Further high-quality trials with long-term follow-up are needed to define optimal patient selection and comparative effectiveness. Full article

Artificial intelligence (AI) is playing an increasingly important role in driving sustainable change across coastal and marine environments. Artificial intelligence offers strong support for environmental decision-making by helping to process complex data, anticipate outcomes, and fine-tune day-to-day operations. In busy coastal zones such as the Mediterranean where tourism and boating place significant strain on marine ecosystems, AI can be an effective means for marinas to reduce their ecological impact without sacrificing economic viability. This research examines the contribution of artificial intelligence toward the development of environmental sustainability in marina management. It investigates how AI can potentially reconcile economic imperatives with ecological conservation, especially in high-traffic coastal areas. Through a focus on the impact of social and technological context, this study emphasizes the way in which local conditions constrain the design, deployment, and reach of AI systems. The marinas of Ibiza and Monaco are used as a comparative backdrop to depict these dynamics. In Monaco, efforts like the SEA Index^® and predictive maintenance for superyachts contributed to a 28% drop in CO₂ emissions between 2020 and 2025. In contrast, Ibiza focused on circular economy practices, reaching an 85% landfill diversion rate using solar power, AI-assisted waste systems, and targeted biodiversity conservation initiatives. This research organizes AI tools into three main categories: supervised learning, anomaly detection, and rule-based systems. Their effectiveness is assessed using statistical techniques, including t-test results contextualized with Cohen’s d to convey practical effect sizes. Regression R² values are interpreted in light of real-world policy relevance, such as thresholds for energy audits or emissions certification. In addition to measuring technical outcomes, this study considers the ethical concerns, the role of local communities, and comparisons to global best practices. The findings highlight how artificial intelligence can meaningfully contribute to environmental conservation while also supporting sustainable economic development in maritime contexts. However, the analysis also reveals ongoing difficulties, particularly in areas such as ethical oversight, regulatory coherence, and the practical replication of successful initiatives across diverse regions. In response, this study outlines several practical steps forward: promoting AI-as-a-Service models to lower adoption barriers, piloting regulatory sandboxes within the EU to test innovative solutions safely, improving access to open-source platforms, and working toward common standards for the stewardship of marine environmental data. Full article

Customer segmentation is a foundation of Customer Relationship Management (CRM) and is widely regarded as a key to business development success. As the principles of sustainable development become increasingly central to business strategy, it is necessary that social, environmental, and economic considerations be incorporated into customer segmentation—even in regulated markets such as the postal market. The article develops and applies a three-dimensional (3D) segmentation model of business customers in the Slovak postal market, utilizing cluster analysis within STATISTICA analytical software for operationalization of the segmentation criteria. The 3D model reacts to the three pillars of sustainable development and is verified under real conditions at Slovak Post, plc. By adopting a systems perspective, the research places customer segmentation as an integral component of the entire socio-technical system, emphasizing the interrelatedness of organizational, social, and environmental considerations. The study illustrates how a systems-based approach to segmentation enables postal operators to uncover key customer segments, optimize resource allocation, and support competitiveness and sustainability goals. The practical applicability of the model is illustrated by its potential for application in other regulated service industries, providing a solid framework for sustainable customer management and strategic decision-making in complex environments. The research underscores the critical role of systems thinking in addressing the complex challenges of sustainable development in regulated industries. Full article

To address the critical challenge of ensuring bottom water-inrush stability during the excavation of ultra-deep foundation pits for riverside suspension-bridge anchorages under complex geological conditions involving high-pressure confined groundwater, we investigate the application of D-RJP high-pressure rotary jet grouting pile technology for ground improvement. Its effectiveness is systematically validated through a case study of the South Anchorage Foundation Pit for the North Channel Bridge of the Zhangjinggao Yangtze River Bridge. The D-RJP method led to the successful construction of a composite foundation within the soft soil that satisfies the permeability coefficient, interface friction coefficient, bearing capacity, and shear strength requirements, significantly improving the geotechnical performance of the anchorage foundation. A series of field experiments were conducted to optimize the critical construction parameters, including the lifting speed, water–cement ratio, and stroke spacing. Core sampling and laboratory testing revealed the grout columns to have good structural integrity. The unconfined compressive strength of the high-pressure jet grout columns reached 5.45 MPa in silty clay layers and 8.21 MPa in silty sand layers. The average permeability coefficient ranged from 1.67 × 10⁻⁷ to 2.52 × 10⁻⁷ cm/s. The average density of the columns was 1.66 g/cm³ in the silty clay layer and 2.08 g/cm³ in the silty sand layer. The cement content in the return slurry varied between 18% and 27%, with no significant soil squeezing effect observed. The foundation interface friction coefficient ranged from 0.44 to 0.52. After excavation, the composite foundation formed by D-RJP columns was subjected to static load and direct shear testing. The results showed a characteristic bearing capacity value of 1200 kPa, the internal friction angle exceeded 24.23°, and the cohesion exceeded 180 kPa. This study successfully verifies the feasibility of applying D-RJP technology to construct high-performance artificial composite foundations in complex strata characterized by deep soft soils and high-pressure confined groundwater, providing valuable technical references and practical insights for similar ultra-deep foundation pit projects involving suspension bridge anchorages. Full article

Digital transformation (DT) requires organizations to navigate complex technological and organizational changes, often under conditions of uncertainty. While agile methodologies are widely adopted to address the iterative and cross-functional nature of DT, limited attention has been paid to identifying critical success factors (CSFs) from a socio-technical systems (STS) perspective. This study addresses that gap by integrating and prioritizing CSFs as interdependent elements within a layered socio-technical framework. Drawing on a systematic review of 17 empirical and conceptual studies, we adapt Chow and Cao’s agile success model and validate a set of 14 CSFs across five domains—organizational, people, process, technical, and project—through a Delphi-informed Analytic Hierarchy Process (AHP). The findings reveal that organizational and people-related enablers, particularly management commitment, team capability, and organizational environment, carry the greatest weight in agile-based DT contexts. These results inform a three-layered framework—comprising organizational readiness, agile delivery, and project artefacts—which reflects how social, technical, and procedural factors interact systemically. The study contributes both theoretically, by operationalizing STS theory in the agile DT domain, and practically, by providing a prioritized CSF model to guide strategic planning and resource allocation in transformation initiatives. Full article