Search Results (2,531)

Digital telecommunications have become the backbone of modern healthcare, transforming how patients and professionals interact, share information, and deliver treatment. The integration of telecommunications with medicine, biomedical engineering and health services has enabled rapid growth in telemedicine, remote patient monitoring, wearable biomedical devices, and data-driven clinical decision-making. Emerging technologies such as artificial intelligence, big data analytics, virtual and augmented reality and robotic tele-surgery are further expanding the scope of digital health. This review provides a comprehensive overview of the role of telecommunications in medicine and biomedical engineering. We classify key applications, highlight enabling technologies and critically examine the challenges regarding interoperability, data security, latency, and cost. Finally, we discuss future directions, including 5G/6G networks, edge computing, and privacy-preserving medical AI, emphasizing the need for reliable and equitable access to telecommunications-enabled healthcare worldwide. Full article

Digital Transformation (DT) is a strategic challenge that reshapes the way companies operate. Nevertheless, its adoption in the construction industry remains slow. This paper analyzes the DT process in Brazilian construction companies through two phases. Initially, an exploratory study was conducted with 17 firms using semi-structured interviews with their Technical Directors. Second, three companies were selected for case studies involving 14 in-depth interviews, observation, and document analysis. Data underwent content analysis. In the exploratory phase, DT was found to be mainly pursued to improve construction efficiency. Barriers were strongly associated with individual aspects, especially limited knowledge about technologies and resistance to change, reinforced by difficulties in implementing organizational changes. Most problems that DT seeks to address are concentrated in the technical department and construction site. Companies adopted approaches such as technology investments, open innovation, organizational restructuring, and training, but the success of these strategies depends on top management engagement and employee acceptance. Besides cultural barriers, technological obstacles, system integration and digital delay were identified, along with process difficulties such as the complexity and costs of the DT journey. Indirect sustainability objectives also emerged, indicating that DT is perceived as both technological advancement and a means to transform the sector. Finally, based on the empirical findings, a multi-level framework comprising 12 strategies for DT in the construction industry was proposed. Overall, the empirical field investigated remains in the early stages of DT, with experimentation with technologies and a focus on efficiency, characteristics of digitization, a step prior to total transformation. The study provides a valuable diagnosis of DT to support the digital transition and informs policymakers in designing initiatives that foster DT, contributing to sector sustainability and SDG9. Full article

3D concrete printing (3DCP) is an emerging intelligent construction technology that enables the direct transformation of digital models into physical components, thereby facilitating the precise fabrication of complex geometries. This study investigates the anisotropic mechanical properties and construction applicability of low-carbon 3D printed concrete for reusable formwork systems. Axial compression, flexural, and splitting tensile tests were conducted to examine mechanical anisotropy, and the effects of steel slag and iron tailings replacement levels on mechanical performance were evaluated. Carbon emission analysis was also performed. Using the coefficient-of-variation TOPSIS method, an optimal printable low-carbon mixture was identified, comprising 30% steel slag, 40% iron tailings sand, and 0.3% fibre content, balancing both mechanical performance and environmental benefits. To address the challenges associated with printing large monolithic formwork units, such as excessive weight and demoulding difficulties, three connection strategies for curved wall modular reusable formwork were designed. Finite element analyses were conducted to assess the strength and stiffness of each strategy, and an optimized connection configuration was proposed. The findings demonstrate the feasibility of accurately fabricating complex architectural components using low-carbon 3D printed concrete, providing theoretical and practical support for the industrialized production of large-scale, geometrically complex structures. Full article

Micro and small enterprises (MSEs) in emerging markets often face resource and capability constraints, highlighting the need to leverage digital innovation for improved performance. Although entrepreneurial orientation (EO) is widely recognized as a driver of firm performance (FP), the capability-based mechanisms linking EO to performance through digital innovation remain underexplored. To address this gap, this study develops and empirically validates a Digital Innovation Opportunity Transformation (DIOT) framework, which explains how EO enhances FP through sequential capability mechanisms—digital opportunity recognition and digital opportunity exploitation—and how IT-environmental support (ITES) strengthens these effects. Using survey data from 286 Ethiopian MSEs and structural equation modeling, the findings reveal that EO has a significant positive impact on FP (β = 0.14, p < 0.05) and generates indirect benefits through internal digital innovation capabilities. Additionally, ITES amplifies these indirect pathways, suggesting that supportive digital infrastructures enhance the outcomes of EO-driven innovation efforts. The study advances theoretical understanding by validating the DIOT framework and elucidating the internal mechanisms linking EO to FP. It also offers practical insights for managers, technology providers, and policymakers seeking to promote EO-led digital innovation in resource-constrained emerging economies. Full article

Joining technologies play a decisive role in the sustainability, circularity, and end-of-life performance of metal structures. Despite the increasing emphasis on low-impact manufacturing and Extended Producer Responsibility (EPR), the connection between joining methods and producers’ environmental obligations remains underexplored. This review provides a comprehensive assessment of conventional and emerging techniques, including fusion welding, solid-state welding, mechanical fastening, adhesive bonding, and hybrid and AM-assisted processes, examining how each technology influences material efficiency, durability, repairability, disassembly, and recyclability. Particular attention is devoted to the effects of joint characteristics on life-cycle impacts, waste generation, and the technical and economic feasibility of high-quality material recovery, using recent LCA evidence and industrial case studies from automotive, shipbuilding, aerospace, and consumer products. Building on this analysis, the review proposes qualitative checklists and semi-quantitative scoring schemes to compare joining options under EPR-relevant criteria and to identify best- and worst-case design scenarios. Finally, promising research directions are outlined, including reversible and debond-on-demand solutions, low-energy solid-state routes, joining strategies for multi-material yet recyclable structures, and the integration of digital twins and LCA-informed design tools, offering a roadmap for metal structures that align technical performance with EPR-driven end-of-life management. Full article

Knowledge Management (KM) has evolved over the last five decades as a complex socio-technical system shaped by interactions between organizational processes, technologies and social actors. This study maps the systemic evolution of KM research between 1975 and 2025 by examining its intellectual, conceptual and social subsystems. Using a large-scale bibliometric science-mapping approach that combines performance indicators and network-based techniques, we analyze 33,153 documents indexed in the Web of Science Core Collection. The results reveal a pronounced post-1995 expansion of the field, marked by a consolidated core of specialized journals and influential scholars, alongside an increasingly global research network. The analysis shows that KM research is structured around four interdependent dimensions: organizational processes, strategic orientations, technological infrastructures and socio-cultural factors. More recent developments indicate the emergence of new system trajectories associated with digital transformation, knowledge governance and sustainability. Viewed through a system-level lens, these findings position KM as an evolving research system characterized by adaptive and cross-domain dynamics. Full article

Rapid adoption of digital surveying technologies in construction has highlighted the need for engineering education to equip students with technological competency as well as higher-order problem-solving skills. This experiment explores undergraduate students’ acceptance of emerging surveying technologies and their perceived learning results within a constructivist framework of experiential learning. Thirty-six students in a required construction surveying class interacted with traditional and advanced technologies such as total stations, terrestrial laser scanning, drones, and mobile LiDAR through structured, semi-structured, and unstructured lab activities. Data were gathered based on two post-course surveys: a technology acceptance survey grounded in Unified Theory of Acceptance and Use of Technology (UTAUT) and a self-perceived cognitive learning outcome survey through Bloom’s Taxonomy. Qualitative analysis along with quantitative analysis indicated a gap between technology acceptance and perceived learning gains. Laser scanner had the greatest acceptance scores followed by other advanced tools. Total station (widespread in hands-on lab activities) was perceived to have been most influential in terms of enhancing learning. Lower-order skills were strengthened in structured labs, while higher-order thinking emerged more unevenly in open-ended labs. These findings underscore that the mode of student engagement with technology matters more for learning than the sophistication of the tools themselves. By embedding UTAUT and Bloom’s Taxonomy in an authentic learning environment, this experiment provides engineering educators a mechanism to assess technology-enhanced learning and identifies strategies to facilitate higher-order skills aligned with industry needs. Full article

The rapid development of educational technologies requires a deeper understanding of pre-service teachers’ readiness for artificial Intelligence and the extent to which their professional self-efficacy beliefs influence this process. Although the integration of emerging technologies has gained increasing attention, the relationship between technological competence and professional confidence among pre-service teachers remains underexplored. This study aims to investigate the interplay between pre-service teachers’ readiness for artificial intelligence and their professional self-efficacy. An exploration sequential mixed method design was employed, beginning with a quantitative phase involving 293 pre-service teachers, followed by a qualitative phase to capture deeper insights. Findings revealed that pre-service teachers demonstrated an elevated level of readiness for artificial intelligence and positive self-efficacy beliefs, yet no meaningful relationship emerged between the two variables. The results suggest that professional self-efficacy and technological readiness are influenced by broader contextual and pedagogical factors rather than functioning in a straightforward manner. In the qualitative phase, participants highlighted both opportunities and challenges related to the use of artificial intelligence in primary education. While many emphasized its potential to support personalized learning, reduce workload, and enhance student adaptability, concerns were raised about ethical implications, risks to social-emotional development, cultural values, digital literacy gaps, and infrastructural limitations. The study underscores the necessity for teacher education programs to extend beyond technical training by incorporating pedagogical, ethical, and cultural dimensions to prepare pre-service teachers for meaningful integration of artificial intelligence into educational practice. Full article

The vitality of public space in traditional villages has emerged as a crucial issue central to both rural revitalization and cultural heritage preservation. This study applied a theoretical analysis grounded in Scene Theory to reveal the specific issues and propose spatial strategies. With a mixed-methods approach combining quantitative surveys and field investigations in Shen’ao Village, China, this study developed a spatial perception evaluation index which contains three dimensions of scene value and 15 specific indicators. The evaluation results indicate generally low satisfaction and vitality in public space, primarily due to deficiency in normalization and planning of spatial construction, disconnection between cultural preservation and utilization, inequality of functional supply and spatial distribution, and decoupling of spatial design and users’ emotional resonance. We propose targeted spatial strategies including experience enhancement through digital technology, mixed-use design, and an all-age suitable optimization approach. This study contributes theoretically by adapting Scene Theory to reveal the reasons for vitality decline in rural public spaces, and methodologically by offering a structured evaluation index that quantitatively assesses subjective feelings. This study also offers new perspectives and technical support for the rural public space development policy of village committees and local governments, thereby enhancing rural revitalization efficiency. Full article

In the era of the digital economy, AI technology is regarded as a key driver in promoting the development of new quality productive forces of enterprises. Based on the theories of creative destruction and resource allocation, this study selects Chinese enterprise-level data from 2009 to 2022 as the research sample, constructs enterprise new quality productivity indicators through text analysis and machine learning methods, and explores the impact of artificial intelligence on new quality productivity. The study results show that AI technology significantly improves the new quality productivity of enterprises. Further research found that enterprise director background, digital industry agglomeration and financial agglomeration positively moderated the relationship between AI and new quality productivity. Heterogeneity analysis shows that the enabling effect of AI technology on new quality productivity is more significant in high-tech enterprises, state-owned enterprises and enterprises with strong policy support. Through empirical analysis, this study verifies the facilitating effect of AI technological innovation on enterprises’ new quality productivity, which provides important insights for enterprises in emerging economies to achieve the development of new quality productive forces in digital transformation. Full article

Background/Objectives: Unmet healthcare needs, driven by structural and patient-level barriers, are particularly critical in chronic obstructive pulmonary disease (COPD). However, limited research has examined how academic themes on this topic connect and evolve over time. This study analyzed the structure and temporal shifts in research trends on unmet healthcare needs in COPD to identify key concepts and topics and policy implications. Methods: We systematically searched PubMed, Embase, and CINAHL (12–15 March 2025) to identify English-language abstracts on unmet healthcare needs in COPD. Eligible studies were peer-reviewed articles with an English-language abstract that examined unmet healthcare needs from the patient perspective. In total, 451 abstracts were analyzed using text network analysis and Latent Dirichlet Allocation. Topic distributions before and after the coronavirus disease pandemic were assessed using chi-square tests, and findings were interpreted within Penchansky and Thomas’s 5A healthcare access framework. Results: Six topics emerged: socioeconomic disparities, early diagnosis and symptom management, guideline-based information and technology use, integrated care for advanced COPD, access to pulmonary rehabilitation, and equitable medication availability. These topics mapped onto all five access dimensions, underscoring the multidimensional nature of unmet healthcare needs. Network analysis identified management, diagnosis, symptoms, exacerbation, and other related terms as central hubs in the discourse. Post-pandemic, research shifted toward digital information delivery, technology adoption, and equitable pharmacotherapy. Conclusions: Findings suggest that reducing unmet healthcare needs in COPD requires integrated systems that address both disease complexity and access barriers. Targeted, multidisciplinary, and policy-driven interventions in highly central domains are needed to reduce disparities and improve outcomes. This study also confirmed a post-pandemic shift in research priorities, emphasizing the need for equitable and adaptive healthcare policies. Full article

Cyber–physical systems (CPS) in healthcare represent a deep integration of computational intelligence, physical medical devices, and human-centric data, enabling continuous, adaptive, and personalized care. These systems combine real-time measurements, artificial intelligence (AI)-based analytics, and networked medical devices to monitor, predict, and optimize patient health outcomes. A key development in the field of CPS is the emergence of patient digital twins (DTs), virtual models of individual patients that simulate biological, behavioral, and social parameters. Using AI, DTs analyze complex medical and social data (genetics, lifestyle, environment, etc.) to support precise diagnosis and treatment planning. The implications of the bibliometric findings suggest that the field emerges from the conceptual phase, justifying the article’s emphasis on both the proposed architectures and their clinical validation. However, most research was conducted in computer science, engineering, and mathematics, rather than medicine and healthcare, suggesting an early stage of technological maturity. Leading countries were India, the United States, and China, but these countries did not have a high number of publications, nor did they record leading researchers or affiliations, suggesting significant research fragmentation. The most frequently observed Sustainable Development Goals indicate an industrial context. Reflecting insights from medical and social research, AI-based DT systems provide a holistic view of the patient, taking into account not only physiological states but also psychological and social well-being. These systems promote personalized therapy by dynamically adapting treatment based on real-time feedback from wearable sensors and electronic medical records. More broadly, CPS and DT systems increase healthcare system efficiency by reducing hospitalizations and supporting remote preventive care. Their implementation poses significant ethical and privacy challenges, particularly regarding data ownership, algorithm transparency, and patient autonomy. Full article

In the context of green transition and digital transformation, forestry is becoming a strategic area of application of current modern technologies. The Internet of Things (IoT), artificial intelligence (AI), big data analysis (Big Data) and Digital Twins define the basic infrastructure of smart forestry. By connecting sensors, drones and satellites, IoT allows for continuous monitoring of forest ecosystems, risk anticipation and decision optimization in real-time. The purpose of this study is to perform a comprehensive narrative analysis of the relevant scientific literature from the recent period (2020–2025) regarding the application of IoT in forestry, highlighting the conceptual, technological and institutional developments. Based on a selection of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (29 full-text articles), four major axes are analyzed: (A) forest fire detection and prevention; (B) climate-smart forestry and carbon accounting; (C) forest digitalization through the concepts of Forest 4.0, Forest 5.0 and Digital Twins; (D) sustainability and digital forest policies. The results show that IoT is a catalyst for the sustainable transformation of the forest sector, supporting carbon accounting, climate-risk reduction and data-driven governance. The analysis highlights four major developments: the consolidation of IoT–AI architectures, the integration of IoT and remote sensing, the emergence of Forest 4.0/5.0 and Digital Twins and the growing role of governance and data standards. These findings align with the objectives of the EU Forest Strategy 2030 and the European Green Deal. Full article

Artificial intelligence (AI) is rapidly transforming the landscape of dental implantology by enhancing every stage of treatment, from diagnostics and digital planning to intraoperative navigation, outcome prediction, and long-term follow-up. This narrative review explores the current and emerging applications of AI technologies in implant dentistry, with a focus on machine learning, neural networks, and computer vision. It examines how AI is utilized in digital implant planning, surgical navigation, peri-implant disease monitoring, risk assessment, and the prediction of treatment outcomes such as peri-implantitis and implant failure. These innovations contribute to more efficient workflows, more personalized treatment strategies, and improved cost-effectiveness of care. Finally, future perspectives and educational implications of AI integration in clinical implantology are discussed. Full article

Heavy earth-moving machinery is essential for construction, mining, and infrastructure development, but its traditional hydraulic systems, powered by diesel engines, are major contributors to energy losses and inefficiencies. Hydraulic circuits typically account for significant parasitic losses due to throttling, leakage, and low energy recovery, resulting in high fuel consumption and emissions. Recent innovations are transforming hydraulic technology to improve energy efficiency and sustainability. This review highlights advancements such as electro-hydraulic actuators, independent metering systems, and digital hydraulics, which enable precise flow control and minimize throttling losses. The integration of energy recovery systems, including hydraulic accumulators and hybrid architectures, further enhances efficiency by capturing and reusing energy during braking and lowering operations. Additionally, the adoption of smart sensors, predictive analytics, and advanced control algorithms enables real-time optimization of hydraulic performance, reducing idle losses and improving overall system responsiveness. Emerging trends such as fluid power electrification, compact high-pressure components, and the use of eco-friendly hydraulic fluids are also discussed. By synthesizing current research and industrial practices, this paper provides insights into the challenges, opportunities, and future prospects for achieving substantial energy efficiency gains through next-generation hydraulic technologies in heavy earth-moving equipment. Full article