Search Results (493)

This study presents a next-generation clinical decision-support architecture for Clinical Decision Support Systems (CDSS) focused on emergency triage. By integrating Large Language Models (LLMs), Federated Learning (FL), and low-latency streaming analytics within a modular, privacy-preserving framework, the system addresses key deployment challenges in high-stakes clinical settings. Unlike traditional models, the architecture processes both structured (vitals, labs) and unstructured (clinical notes) data to enable context-aware reasoning with clinically acceptable latency at the point of care. It leverages big data infrastructure for large-scale EHR management and incorporates digital twin concepts for live patient monitoring. Federated training allows institutions to collaboratively improve models without sharing raw data, ensuring compliance with GDPR/HIPAA, and FAIR principles. Privacy is further protected through differential privacy, secure aggregation, and inference isolation. We evaluate the system through two studies: (1) a benchmark of 750+ USMLE-style questions validating the medical reasoning of fine-tuned LLMs; and (2) a real-world case study (n = 132, 75.8% first-pass agreement) using de-identified MIMIC-III data to assess triage accuracy and responsiveness. The system demonstrated clinically acceptable latency and promising alignment with expert judgment on reviewed cases. The infectious disease triage case demonstrates low-latency recognition of sepsis-like presentations in the ED. This work offers a scalable, audit-compliant, and clinician-validated blueprint for CDSS, enabling low-latency triage and extensibility across specialties. Full article

Background/Objectives: Mpox re-emerged in 2022 as a global health concern. Between 2022 and 2025, Portugal experienced three distinct outbreak waves, highlighting the critical role of laboratory surveillance and public health interventions. This study describes the epidemiological trends, diagnostic performance, and key lessons learned to improve outbreak preparedness. Methods: A total of 5610 clinical samples from 2802 suspected cases were analyzed at the National Institute of Health Doutor Ricardo Jorge using real-time PCR methods. Positivity rates and viral loads (Ct values) were assessed across different clinical specimen types, including lesion, anal, oropharyngeal swabs, and urine samples. Results: Mpox was confirmed in 1202 patients. The first outbreak accounted for 79.3% of cases (n = 953), followed by a significant reduction in transmission during subsequent waves. Lesion and rectal swabs provided the highest diagnostic sensitivity (95.1% and 87.9%, respectively). Oropharyngeal swabs contributed to diagnosis in cases without visible lesions, while urine samples showed limited utility. Conclusions: This study underscores the importance of sustained laboratory surveillance and adaptive public health strategies in controlling mpox outbreaks. Optimizing specimen collection enhances diagnostic accuracy, supporting early detection. Continuous monitoring, combined with targeted vaccination and effective risk communication, is essential to prevent resurgence and ensure rapid response in non-endemic regions. Full article

Over a three-year R&D project, the perception of mobile phone use in Spanish secondary schools shifted from initial tolerance to increasingly prohibitive policies. Drawing on the Actor–Network Theory, this study examines how mobile phones—alongside institutional discourses and school and family concerns—acted as dynamic actants, shaping public and political responses. The research adopted a qualitative design combining policy and media document analysis, nine semi-structured interviews with key stakeholders, ten regional case studies, and twelve focus groups. The study concluded with a public multiplier event that engaged the broader educational community. The Madrid region, among the first to adopt a restrictive stance, contributed two school-based case studies and three focus groups with teachers, students, and families. Findings suggest that the turn toward prohibition was motivated less by pedagogical evidence than by cultural anxieties, consistent with what it conceptualizes as a techno-pessimistic shock. This shift mirrors the historical patterns of societal reaction to disruption and technological saturation. Rather than reinforcing binary framings of promotion versus prohibition, such moments invite critical reflection. The study argues for nuanced, evidence-based, and multilevel governance strategies to address the complex role of mobile technologies in education. Full article

A university’s reputation is a key indicator of the quality of its education, the competitiveness of its alumni, its institutional influence in society, and its degree of global recognition, including its ranking and rating among higher education institutions (HEIs) around the world. This not only enhances institutional standing and secures positions in international rankings but also promotes sustainable education practices. In addition, students, their parents, and their partners select universities due to their trust in the reliability of a university’s public reputation and ranking. This study proposes a model to assess a university’s reputation based on specific factors. In this research, the dependent variable is university reputation, the mediating variable is university social responsibility, and the independent variables include the teacher reputation, alumni reputation, research and innovation, and cooperation. A survey of 5902 respondents—including alumni, employers, and parents—offers diverse perspectives on university reputation. Data were analyzed using structural equation modeling tools (Smart PLS 4.1 and SPSS 25.0). The findings confirm that social responsibility has a strong and positive influence on university reputation. Furthermore, faculty and alumni reputation, research and innovation, and external collaboration directly enhance universities’ social responsibility. This suggests that social responsibility serves as a key mediating variable in the relationship between institutional capacity and reputation. This study represents the first empirical assessment of university reputation in Mongolia, addressing a notable gap in the literature. By incorporating context-specific insights and stakeholder perspectives, the research offers both theoretical contributions and practical implications. The results provide a foundation for developing regionally responsive strategies to improve the quality of higher education and advance sustainable development goals. Full article

Background/Objectives: Image-guided adaptive brachytherapy is a standard modality in the treatment of locally advanced cervical cancer. However, the availability of isotope-based brachytherapy is limited in countries with lower resources. The objective of this study is to report the first institutional dosimetric and clinical data on intracavitary electronic brachytherapy. Methods: A total of 25 patients with histologically proven cervical cancer stage IB-IVA were treated with concurrent chemoradiotherapy and electronic brachytherapy. The patients were followed up for a median of 12 months (range 6–24). Toxicity was evaluated by the radiation oncologist and gynecologist on each visit and scored by Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Results: All patients completed the treatment successfully with a median overall treatment time (OTT) of 52 days (range 39–89). The desired target coverage was achieved in all patients, and the dose limits for the organs at risk were achieved in 88% of the patients. No Grade 3 toxicities occurred. A total of 84% of the patients achieved local control in the cervix, and a complete response was noted in 72% of the patients. Conclusions: Electronic brachytherapy provides the option to deliver a high dose of radiation to the uterine cervix without leading to severe toxicity. Further improvements to the treatment protocol could provide better locoregional and systemic control of the disease. Studies with larger cohorts and longer follow-up are necessary. Full article

This study investigates the convergence of blockchain, artificial intelligence (AI), near-field communication (NFC), and mobile technologies in electronic payment (e-payment) systems, proposing an innovative integrative framework to deconstruct the systemic innovations and transformative impacts driven by such technological synergy. Unlike prior research, which often focuses on single-technology adoption, this study uniquely adopts a cross-technology convergence perspective. To our knowledge, this is the first study to empirically map the multi-technology convergence landscape in e-payment using scientometric techniques. By employing bibliometric and thematic network analysis methods, the research maps the intellectual evolution and key research themes of technology convergence in e-payment systems. Findings reveal that while the integration of these technologies holds significant promise, improving transparency, scalability, and responsiveness, it also presents challenges, including interoperability barriers, privacy concerns, and regulatory complexity. Furthermore, this study highlights the potential for convergent technologies to unintentionally deepen the digital divide if not inclusively designed. The novelty of this study is threefold: (1) theoretical contribution—this study expands existing frameworks of technology adoption and digital governance by introducing an integrated perspective on cross-technology adoption and regulatory responsiveness; (2) practical relevance—it offers actionable, stakeholder-specific recommendations for policymakers, financial institutions, developers, and end-users; (3) methodological innovation—it leverages scientometric and topic modeling techniques to capture the macro-level trajectory of technology convergence, complementing traditional qualitative insights. In conclusion, this study advances the theoretical foundations of digital finance and provides forward-looking policy and managerial implications, paving the way for a more secure, inclusive, and innovation-driven digital payment ecosystem. Full article

Ensuring consistent progress toward cities’ net-zero emission goals requires understanding key dimensions of urban climate governance—particularly the motivations driving municipalities toward net zero and the critical barriers and enablers along this pathway. Current knowledge on these critical aspects is fragmented, lacking a holistic framework and empirical prioritization of key factors. We developed an integrated analytical framework and empirically distilled the most salient motivations, barriers, and enablers through a large-scale survey targeting 489 net-zero-committed municipalities—known as “Zero Carbon Cities”—across Japan. With responses from 309 municipalities, we deliver the first systematic mapping of factors perceived as most influential by Japanese local authorities. The results indicate that municipalities are primarily motivated by seizing local economic development opportunities (enhanced local energy conditions, financial gains and savings, and local industry revitalization), future-proofing communities against disasters, and enhancing the local quality of life. Key barriers and enablers were identified across four categories: municipal resources and authority (budgets, dedicated staff, and empowered climate agencies), knowledge and expertise (staff climate competence), institutional coherence (cross-departmental coordination and stakeholder involvement), and political will and leadership (the presence of climate champions and awareness within city halls and among residents). Accordingly, we discuss implications and derive recommendations toward strengthened local action in Japan and beyond. Full article

This concept-centric review identifies and synthesizes emerging drivers of Generative AI (GenAI) adoption in education, addressing a critical gap by offering the first structured integration of empirically supported predictors. Based on 27 peer-reviewed studies featuring validated research models, the review distils 11 predictors into a Three-Tier Framework. Core predictors—Performance Expectancy and Trust—consistently influence adoption across contexts. Moderate predictors—Effort Expectancy, Facilitating Conditions, Social Influence, Perceived Behavioral Control, and Perceived Compatibility—show variable relevance depending on technological and institutional factors. Emerging predictors—Habit, AI Literacy, Anxiety, and Playfulness—capture evolving socio-technical and individual dynamics, reflecting the rapid development of GenAI technologies. While the current literature offers valuable insights, gaps remain in addressing ethical concerns, barriers to adoption, teacher professional development, student engagement, and the influence of cultural and contextual diversity. The findings emphasize the need to iteratively refine the Three-Tier Framework by incorporating these dimensions and adapting to technological advancements. By consolidating empirical evidence and distinguishing between mature and emerging predictors, this review advances theoretical understanding of technology acceptance in education. It provides a structured foundation for guiding future research, informing policy and practice, and supporting responsible, context-sensitive GenAI integration across diverse educational settings. Full article

Motivated to create a children’s VR game for the Netherlands Institute for Sound and Vision (NISV), this research asks how might we design an immersive game for children to meaningfully interact with media and metadata in cultural heritage contexts? First, during a ‘design salon,’ 13 data and heritage experts challenged children’s ability to interact with metadata. In response, we ran workshops with 19 children focused on understanding abstract media and data. We found that while (1) metadata has many challenges, (2) children understand abstract data when it is grounded in concrete experiences, are (3) motivated to interact with archival media through in immersive and collaborative contexts, and (4) are interested in exploring media diversity through categorisation games with high-level narrative goals. These findings inform our game concept and three core insights for designing immersive experiences for cultural heritage: Considering the Contextual Complexity of Data and Audience Needs, Connecting Data Abstractions to Embodied Narratives Through Categorisation Mechanics, and Supporting Abstract Meaning Making Using the Immersive Affordances of VR. Full article

The Belt and Road Initiative (BRI) is the first and currently the most expansive global infrastructure initiative, notably for its scale and emphasis on connectivity. In response, alternative initiatives such as the Partnership for Global Infrastructure and Investment (PGII) and Free and Open Indo-Pacific Strategy (FOIP), including their components the Blue Dot Network (BDN) and Partnership for Quality Infrastructure (PQI), as well as Global Gateway (GG) and the Three Seas Initiative (3SI), have emerged to counterbalance the BRI’s influence and promote more transparent, sustainable, and rules-based infrastructure frameworks. This review investigates how global and regional infrastructure initiatives—namely PGII/BDN, GG, FOIP/PQI, and 3SI—compare with the BRI in terms of development objectives, implementation models, institutional structures, and implications for developing economies. Adopting an inductive approach, this review identifies key themes from the literature to evaluate these initiatives across seven dimensions: (1) infrastructure objectives, (2) the quality and transparency of investments, (3) investment policy orientation, (4) trade policy orientation, (5) inclusivity and regional integration, (6) coordination mechanisms, and (7) environmental sustainability. While PGII/BDN, GG, FOIP/PQI, and 3SI appear well-positioned to address some of BRI’s shortcomings, the evidence does not clearly favour one model over another in terms of achieving welfare-enhancing outcomes and bridging development gaps. Nonetheless, strategic competition and complementarities among the connectivity policies of multiple initiatives can ultimately contribute to more accountable, multidimensionally sustainable, and socially inclusive infrastructure development. We also illustrate how stated preference methods, i.e., willingness to pay (WTP) and willingness to accept (WTA), can be used to quantify the value of soft infrastructure, particularly public preferences for sustainable investment and norm diffusion, which are central to evaluating the social welfare gains from participating in these initiatives. Full article

Background and Objectives: Healthcare payment systems face challenges such as fraud and overbilling, which often require costly and resource-intensive detection tools. In response, the utility of simple statistical tests was explored in this study as a practical alternative for identifying irregularities in dermatology service payments within the Health Insurance Institute of Slovenia (HIIS). Materials and Methods: Ten-year-old anonymized billing data from 30 dermatology providers in Slovenia (with a population of 2 million) were analyzed to evaluate the effectiveness of the proposed methodology while aiming to avoid reputational harm to current providers. The dataset from 2014 included variables such as the “number of services charged”, “total number of points charged” (under Slovenia’s point-based tariff system at the time), “number of points per examination”, “average examination values (EUR)”, “number of first examinations”, and “total number of first/follow-up examinations”. Data credibility was assessed using Benford’s Law (for calculating χ² values and testing null hypothesis rejection at the 95% level), and Grubbs’ test, Hampel’s test, and T-test were used to identify outliers. Results: An analysis using Benford’s Law revealed significant deviations for the “number of services charged” (p < 0.005), “total number of points charged” (p < 0.01), “number of points per examination” (p < 0.0005), and “average examination values (EUR)” (p < 0.005), suggesting anomalies. Conversely, data on the numbers of “first” (p < 0.7) and “total first/follow-up examinations” (p < 0.3) were found to align with Benford’s Law, indicating authenticity. Outlier detection consistently identified two institutions with unusually high values for points per examination and average examination monetary value. Conclusions: Simple statistical tests can effectively identify potential irregularities in healthcare payment data, providing a cost-effective screening method for further investigation. Identifying outlier providers highlights areas needing detailed scrutiny to understand anomaly causes. Full article

Since the launching of ChatGPT (generative) AI has been developed so much and fast that it has entered higher education (HE) and higher education institutions (HEIs). The article is meant to help HE(Is) how to deal with AI strategically and in leadership. It investigates which influences AI and the use of AI tools is having on HE(Is). Therefore 4 research questions are formulated: how does AI and AI tools influence HE(Is) in its mission, organization and context; should AI and its applications then be regarded as an strategic objective or only as a tool to realize the strategy; how is AI and the use of AI tools, as developed and described in an AI strategy, best managed to be adopted and integrated in an effective and responsible way, and finally which influence does AI and its tools have on the leadership and culture? In order to answer those questions, the article describes first our contemporary times, and the leadership needed, then delves into the history of the development of AI and its tools and investigates the current and future attitudes towards, degrees of implementation, and uses of AI and its tools among the internal and external stakeholders of HE(Is). The findings result from a global literature study of international surveys and 2 case studies. The selection is based on topical usefulness, international scope, (statistical) relevance and quality of research in general. In this way the article aims to help to develop an AI strategy and thus can be read as a policy paper underpinned by a meta-analysis. The main results are that, although the use of AI in HEIs is divided, the effective and responsible adoption and integration of AI is a new strategic objective in order to help to realize HE’s three-fold mission in a well-planned and managed way asking for a visionary leadership and a clear policy framework and guidelines, in which the words transparency, responsibility and critical thinking link AI use with an enhancement of unique human competences such as critical thinking. Full article

Amid intensifying climatic threats, university campuses are increasingly vulnerable. Morphological resilience offers a practical pathway to strengthen disaster response in higher-education institutions. However, research on University Campus Morphological Resilience (UCMR) remains underexplored, with gaps in theory, quantitative methodology, and empirical application. The study established a theoretical framework and an assessment system for UCMR, focusing on four core resilience attributes—robustness, redundancy, connectivity, and diversity—in three common disaster scenarios: earthquakes, flooding, and extreme heat. The Weijinlu (WJL) and Beiyangyuan (BYY) campuses of Tianjin University were selected as case studies. We used Unmanned Aerial Vehicle (UAV) photogrammetry to collect morphological data at a high spatial resolution of 0.1 m. UCMR was evaluated for each disaster scenario, followed by a multi-scenario cluster coupling analysis. The results indicate that, first, the WJL Campus exhibited a lower overall UCMR across various disaster scenarios compared to the BYY Campus, particularly during earthquakes and flooding, with less pronounced differences observed under extreme heat. Second, both campuses demonstrate significant spatial heterogeneity in UCMR across three disaster scenarios. Third, the WJL Campus performs better in redundancy and diversity but worse in connectivity, with lower robustness under earthquakes and flooding, and higher robustness under extreme heat. Fourth, UCMR in BYY Campus displayed consistent spatial patterns characterized by high-resilience clusters, while UCMR in WJL Campus presented greater variability across the three disaster scenarios, showcasing complex multi-scenario cluster types and spatial fragmentation. Based on the above findings, we developed tailored UCMR optimization strategies. The study offers a scientific reference for resilience-oriented campus planning and disaster risk management. Full article

In early 2025, the Santorini–Amorgos area (Aegean Volcanic Arc, Greece) experienced a seismic swarm, with dozens of M ≥ 4.0 earthquakes and a maximum magnitude of M = 5.2. Beyond its seismological interest, the sequence was notable for triggering rare increased preparedness actions by Greek Civil Protection operational structures in anticipation of an imminent destructive earthquake. These actions included (i) risk communication, (ii) the reinforcement of operational structures with additional personnel and equipment on the affected islands, (iii) updates to local emergency plans, (iv) the dissemination of self-protection guidance, (v) the activation of emergency alert systems, and (vi) volunteer mobilization, including first aid and mental health first aid courses. Although it was in line with contingency plans, public participation was limited. Volunteers helped bridge this gap, focusing on vulnerable groups. The implemented actions in Greece are also compared with increased preparedness during the 2024–2025 seismic swarms in Ethiopia, as well as preparedness before the highly anticipated major earthquake in Istanbul (Turkey). In Greece and Turkey, legal and technical frameworks enabled swift institutional responses. In contrast, Ethiopia highlighted the risks of limited preparedness and the need to embed disaster risk reduction in national development strategies. All cases affirm that preparedness, through infrastructure, planning, communication, and community engagement, is vital to reducing earthquake impacts. Full article

Background: We reviewed outcomes of short and long-term chemotherapy with or without breaks in pancreatic ductal adenocarcinoma (PDAC) patients. Methods: PDAC patients receiving ≥3 chemotherapy cycles between 2019 and 2024 at three institutions were included. Progression-free survival after first-line chemotherapy (PFS1), overall survival (OS) and best overall response (BOR) to chemotherapy were assessed using the Wilcoxon test, Kaplan–Meier test, and univariate and multivariate Cox regression models. Results: We screened 237 patients, and 135 patients met the study criteria. Among these patients, 25 had resectable disease, and 110 had unresectable/metastatic disease (13% borderline resectable (BRPC), 20% locally advanced (LAPC), 10% localised developing metastases, 57% de novo metastatic). Ten patients (7%) underwent genetic profiling; KRAS aberrations (N = 4), actionable PLAB2/BRCA2/FGFR2 mutations (N = 3), ATM/BRIP1 alteration (N = 1). Two patients were managed with PARP inhibitors after receiving multiple lines of chemotherapy. Median PFS1 and OS were concordant with the published literature, but select patient groups achieved prolonged survival outcomes. Among the 36 BRPC/LAPC patients, we observed >1-year PFS1 in 9 (25%) patients and >2-year OS in 3 (8%) patients. Among the 63 de novo metastatic patients, we observed >1-year PFS1 and >2-year OS in 6 (10%) patients. Among patients with localised disease, smoking history was a poor prognostic factor with respect to OS (p = 0.03). Improved PFS1 and OS was associated with ≥6 cycles of first-line chemotherapy, its duration of ≥3.66 months, and local treatment after first chemotherapy (p < 0.05 for all). Stereotactic body radiotherapy following first-line chemotherapy was delivered in N = 6 (27%) and N = 1 (7%) of patients with LAPC and BRPC, respectively. Chemotherapy interruption duration, but not number, was associated with PFS1 and OS only in the localised cohort (p < 0.05). In patients with de novo metastatic disease, prevalence of type 2 diabetes was adversely associated with OS (p = 0.03). Improved PFS and OS was associated with ≥6 cycles of first-line chemotherapy, its duration of ≥4.37 months, and BOR to it (only in this cohort) (p < 0.05 for all). A favourable OS was associated with >1 line of chemotherapy (p = 0.003). Conclusion: Despite challenges, extended chemotherapy and multiple treatment lines may improve survival, with localised treatments benefiting select patients. Full article