Search Results (230)

Despite serological evidence of tick-borne encephalitis virus (TBEV) circulation in Belgian animals since 2007, confirmed autochthonous human infection was only first documented in 2020. We review the current national epidemiologic situation and investigate a household cluster of confirmed autochthonous cases identified in 2025. A cohabiting couple experienced a near-simultaneous onset of meningoencephalitis and tested positive for TBEV-specific IgM and IgG, with confirmation by PRNT90. One patient reported a recent tick bite, and both patients reported consumption of unpasteurized milk and goat cheese, suggesting possible alimentary transmission. The identification of Case 2, who lacked neurological symptoms at presentation and was only tested due to the index case, illustrates the risk of missed diagnoses and supports the notion that human TBEV infection is likely underdiagnosed in Belgium. These findings underscore the need to increase clinical awareness, strengthen surveillance, and reinforce prevention strategies. TBE should be considered in the differential diagnosis of patients presenting with non-specific fever or neurological syndromes such as meningoencephalitis, particularly during the spring-to-autumn tick activity season. Full article

Background/Objectives: Digital health interventions are increasingly used to support person-centered care (PCC) in chronic disease management, yet it remains unclear which PCC components are most consistently enabled by digital tools and how these relate to outcomes. This study synthesized evidence on digitally supported PCC for adults with chronic conditions, examining how interventions operationalize PCC and which clinical, patient-reported, and implementation outcomes are reported. Methods: A structured literature synthesis was conducted according to PRISMA guidelines across a heterogeneous evidence base, including randomized and pragmatic trials, observational studies, qualitative studies, and systematic reviews. The review protocol was pre-registered in the Open Science Framework (OSF) Registries. Results: Across 16 included studies, digital solutions most consistently supported PCC through enhanced situational awareness via self-monitoring, strengthened partnership through two-way communication and coaching, and reinforced shared documentation through co-created health plans. Benefits were reported most consistently for process and experience outcomes, such as perceived access to support, engagement, and empowerment. Evidence for sustained long-term clinical improvements, such as glycemic control, was mixed and frequently limited by short follow-up periods and variation in intervention integration. Conclusions: Digitalization can strengthen PCC when embedded within relational care models and organizational workflows that translate patient-generated data into meaningful action. Future work should utilize clearer PCC operationalization, longer follow-up, and routine reporting of equity outcomes, alongside targeted training for healthcare professionals delivering PCC in digital encounters. Full article

Accurate forecasting of respiratory virus-associated hospitalization rates per 100,000 population is essential for healthcare capacity planning, yet remains challenging during the COVID-19 era due to abrupt distribution shifts and symptom overlap among influenza-like illnesses caused by multiple pathogens. We propose a two-stage deep learning framework that disentangles stable pre-pandemic seasonal dynamics from COVID-19-induced excess hospitalizations. A lightweight GRU is first trained on pre-pandemic surveillance data to model baseline influenza/RSV-driven seasonality, after which an excess model learns from the residual series and integrates multiple online search trends (flu, COVID-19, and fever) using a standard multi-head self-attention mechanism. While we use COVID-19-era data as a case study, the proposed baseline–excess decomposition is not disease-specific and is intended to generalize to future large-scale respiratory outbreaks or pandemics that induce abrupt regime shifts. Experiments on U.S. weekly respiratory hospitalization rate data curated from CDC surveillance networks (AME) show that the proposed approach achieves strong accuracy on a chronological COVID-era split (2020–2025), reaching $R^2=0.907$ with MAPE = 19.22%. Beyond point forecasts, we further evaluate an expanding-window rolling-origin protocol and report calibrated prediction intervals via split conformal prediction, supporting deployment-oriented uncertainty quantification. By decoupling baseline and excess components and fusing behavioral trend signals in a disciplined manner, this framework improves predictive performance under regime shift while providing interpretable excess estimates for timely situational awareness and healthcare resource planning. Full article

We developed a hardware-in-the-loop simulation of a battery management system (BMS) using controller area network (CAN) as the communication backbone for electric-powered response boats in flood rescue. A LiFePO4 pack and discharge motor/charger were modeled in MATLAB/Simulink/Simscape, while an STM32 Nucleo-F446RE executed CAN messaging. The BMS monitored voltage, current, temperature, and state of charge. Results indicate CAN’s reliability under rescue-like disturbances: priority arbitration delivered over-temperature and over-current warnings ahead of routine telemetry; error detection and retransmission preserved data integrity; and bus-load analysis showed low latency for urgent frames without interrupting state-of-charge reporting, improving situational awareness and reducing operator risk. Full article

This study addressed how business administration training influenced perceptions of sustainable development goals (SDGs) within park management, situating the research at the intersection of sustainability education and applied management practice. A controlled experiment was conducted in Chongqing Central Park, where 100 undergraduate students were randomly assigned to either an integrated business administration training program or a conventional park management program for two months, followed by standardized questionnaire surveys and statistical analyses, including analysis of variance and multivariate linear regression. A pretest verified randomization equivalence. The results demonstrated that participants who received integrated training reported higher perceptions of SDGs related to quality education, climate action, and life on land, alongside improvements in entrepreneurial mindset, social and economic value preferences, multitasking awareness, decision-related attributes, and interest in nature education. Regression analyses revealed that SDG perception was primarily strengthened by social value orientation and entrepreneurial mindset factors, whereas certain employee attributes and elements of nature education satisfaction exerted negative or weaker effects, particularly among trained participants. In contrast, the control group showed limited and mostly insignificant relationships, with SDG perception relying largely on baseline attitudes. Overall, the findings indicate that embedding business administration concepts into park management training enhances multidimensional sustainability awareness and provides evidence that socially oriented entrepreneurship and structured management thinking contribute meaningfully to SDG perception formation without overstating causal claims. Full article

Background: To mitigate the negative impacts of the pandemic, it is essential to understand how the associations between different types of physical activity (PA) and adolescent well-being changed before and after the COVID-19 pandemic (defined here as the period marked by students’ return to stable in-person education). This study aimed to examine gender differences in the associations between school-related PA and subjective well-being before and after the pandemic. Methods: A cross-sectional design was used, including 430 boys and 571 girls from 22 high schools. Participants completed the Youth Activity Profile questionnaire to assess school-related and school-associated PA and the WHO-5 Well-Being Index to evaluate subjective well-being. Differences in participants’ PA across segments of the school day before and after the pandemic were evaluated using the Kruskal–Wallis test, and compliance with PA recommendations was analyzed using cross-tabulation and Pearson’s chi-square tests. Results: After the pandemic, both boys and girls reported significantly lower levels of active transportation to and from school compared with the pre-pandemic period. In addition, well-being levels were significantly lower in both genders after the pandemic. Before the pandemic, boys and girls with higher well-being met the recommendations for PA to school, from school, and outside of school significantly more often than their peers with lower well-being. Higher levels of well-being were observed both before and after the pandemic in boys and girls who participated in organized PA compared with non-participants. Conclusions: This study confirms lower levels of PA and well-being among adolescents after the pandemic. In particular, PA to and from school was at a lower level after the pandemic than before the pandemic. Participation in organized PA was significantly associated with higher well-being in both boys and girls before and after the pandemic. Supporting adolescents’ participation in organized PA should be a priority when addressing the negative consequences of societal crisis situations. Improved knowledge of the associations between PA and well-being may contribute to more effective support for adolescents’ PA and greater awareness of the importance of meeting PA recommendations. Full article

Adolescents increasingly engage with digital technologies, yet understanding patterns of smartphone use and fostering reflective awareness remain challenging. Traditional assessments in clinical or school settings may limit participation and self-reflection. This study evaluated the feasibility and impact of a Computer-Assisted Web Interviewing (CAWI) approach to monitor smartphone use, provide immediate individualized feedback, and support peer-mediated dissemination in a public science engagement context. Across three editions of the European Researchers’ Night in Rome (2023–2025), 807 adolescents aged 10–19 completed the SAS-SV questionnaire via on-site tablets or personal devices using QR codes. Smartphone use was categorized into Low Involvement, At-Risk, or Problematic. Participants were encouraged to share the survey link with peers, enabling snowball-mediated recruitment. Participant acceptance was assessed through the Net Promoter Score (NPS). Snowball participation accounted for the majority of responses, highlighting the effectiveness of peer-mediated diffusion. SAS-SV categorization indicated 46% Low Involvement, 39% At-Risk, and 15% Problematic use, with minimal gender differences. NPS values ranged from +69 to +79, with snowball participants reporting slightly higher satisfaction than on-site attendees. These results underscore high engagement, perceived value, and the role of peer networks in promoting reflective digital behavior. Integrating CAWI assessment, immediate feedback, and peer-mediated diffusion created a socially situated environment supporting self-reflection and voluntary dissemination. Peer networks extended both the temporal and social reach of the initiative beyond the public event, demonstrating a scalable and non-stigmatizing model. CAWI-based monitoring combined with feedback and peer-driven diffusion is feasible and effective for adolescent digital wellbeing interventions. This approach fosters reflective digital citizenship, supports self-awareness, and leverages social networks to enhance the reach and impact of youth-centered health promotion initiatives. Full article

Dynamic positioning (DP) systems are essential to maritime operations, as they ensure precise station keeping. Yet human error remains a major contributor to DP incidents, often interacting with technical failures and environmental conditions. This study proposes an adaptive probabilistic framework to characterise human-error contributions to DP risk and support targeted mitigation. We compare integrated Bayesian network (BN)/fuzzy analytic hierarchy process (AHP) and Bayesian network (BN)/Dempster–Shafer (D-S) theory to model causal relationships, aggregate uncertain expert judgements, and prioritise risk factors. Historical incident narratives, accident reports, and expert elicitation inform the model to analyse failure propagation and quantify factor contributions. In a representative DP case application, insufficient training, operator fatigue, and reduced situational awareness—together with software anomalies and adverse environmental loads—emerge as dominant contributors; BN backward analysis corroborates their diagnostic relevance. The approach yields actionable insights for risk reduction, including tailored training programmes, strengthened safety protocols, and integration of real-time monitoring. It provides an auditable, updateable basis for scenario-based training, software/maintenance assurance, and environment-aware operating envelopes, and is readily extendable as new evidence becomes available. Overall, the framework offers practical value for improving safety, operational continuity, and system resilience in DP operations. Full article

This article explores the incorporation of linguistic landscape (LL) studies into English for General Academic Purposes (EGAP) courses, emphasizing its potential to enhance language learning through real-world engagement. This study highlights the growing interest in LL as a sociolinguistic phenomenon that reflects urban multilingualism and cultural dynamics. The goal of this article is to analyze pedagogical benefits of integrating LL into language education, such as fostering critical thinking, pragmatic competence, intercultural awareness among students, and creating situations in which the target language is used in natural communication. Through a case study conducted at the Guangdong Technion–Israel Institute of Technology, the author presents specific classroom activities and reports on how they can be combined with fieldwork conducted by students. The goal of the tasks was to let students analyze language use in public spaces, classifying the surrounding signs into top-down and bottom-up, and informative and regulatory, and discuss how social prestige of languages is reflected in multilingual signs. In documenting written language in public places, creating their own signs and assessing their peers’ work, students were practicing both receptive and productive skills. Most of the work was done in small groups, which contributed to the students’ ability to collaborate with peers. The findings suggest that LL projects can effectively bridge classroom learning with lived language experiences, although challenges remain in implementation due to time constraints and pedagogical ideologies. Full article

Artificial intelligence (AI) is rapidly transforming language education. However, its pedagogical and sociocultural impacts on Japanese business writing remain underexplored. This study aims to examine how ChatGPT4o-based automated feedback functions within Japanese business writing education for adult learners in online higher education, with particular attention to both its instructional impact and learners’ sociocultural awareness. Situated in a cyber university context where the proportion of adult learners is increasing, the study explores the potential of AI-mediated feedback to address learners’ diverse educational and cultural needs. It employed a mixed-methods design, combining a survey of 27 participants and in-depth interviews with 11 participants. The interviews were transcribed and thematically coded to gain deeper insights into learners’ perceptions. The findings indicate that ChatGPT feedback contributed to learners’ planning of study strategies, the provision of immediate and personalized corrections, the reinforcement of error awareness, and the acquisition of honorific and polite expressions. On the one hand, learners reported that they could quickly understand regional language practices and communication conventions in business contexts, thereby deepening their cultural sensitivity. On the other hand, some learners expressed concern that increased reliance on AI could weaken exploratory and critical learning. These results suggest that ChatGPT can serve not merely as a correction tool but also as an educational resource that simultaneously fosters self-directed learning and sociocultural competence. However, to ensure reliability and cultural appropriateness, hybrid feedback incorporating instructor guidance is necessary. This study has academic significance in demonstrating the potential of extending AI-based feedback to Japanese business communication education, thereby constructing an integrated language and culture learning environment. Full article

Despite sustained efforts to improve construction health and safety (CHS), accident and injury rates remain persistently high, driving increased interest in Artificial Intelligence (AI)-enabled safety solutions. This study presents a thematic systematic literature review of 148 peer-reviewed journal articles published between 2013 and 2025, conducted in accordance with PRISMA guidelines and sourced from Scopus. The synthesis identifies four dominant thematic areas: AI use cases, adoption barriers, realised benefits, and future research directions. Findings indicate a strong concentration of studies on vision-based monitoring, predictive hazard detection, and automated risk assessment, while organisational, ethical, and governance dimensions remain comparatively underexplored. Recurring impediments include data quality limitations, algorithmic opacity, fragmented digital ecosystems, and organisational resistance, highlighting persistent non-technical constraints on implementation. Reported benefits consistently emphasise improved predictive accuracy, real-time situational awareness, and proactive safety intervention, signalling a transition from reactive compliance-based approaches toward anticipatory, data-driven safety management. Based on these patterns, future research should prioritise explainable AI, interoperable data infrastructures, and cross-disciplinary integration to support scalable and trustworthy AI adoption in CHS. Full article

Effective command-and-control (C2) decision-making during emergency response relies on timely access to spatially accurate information. It also requires a clear understanding of evolving incident conditions. Traditional fire-service training methods provide limited opportunities to rehearse complex, high-risk, and large-scale incidents under realistic yet safe conditions. This exploratory pilot study presents the design and experimental evaluation of an integrated training environment that combines geographic information system (GIS) data, unmanned aerial vehicle (UAV) imagery, and immersive virtual reality (VR) simulations to support C2 training for fire-service incident commanders. The system was assessed through scenario-based exercises involving 23 active incident commanders across three representative emergency scenarios: wildland fire, hazardous materials transport accident, and flood response. The training scenarios were based on real geographic areas in central Slovakia, using authentic terrain, land-cover, infrastructure, and hydrological GIS layers to ensure spatial realism of the simulated emergency environments. Pre-training and post-training questionnaires were used to evaluate perceived training realism, preparedness for command tasks, decision-making confidence, and the perceived usefulness of digital spatial information tools. Results indicate a substantial post-training increase in perceived realism and preparedness, with strong positive correlation between these variables (Spearman ρ = 0.71, p < 0.001). Participants reported improved confidence in assessing incident conditions, prioritizing operational tasks, and allocating resources under dynamically evolving scenarios. The study evaluates perceived spatial situational understanding derived from multi-source spatial information integration rather than directly measured situational awareness using standardized psychometric instruments. UAV imagery was found to be particularly valuable for rapid incident size-up, while GIS layers primarily supported spatial planning, hazard delineation, and resource coordination; VR served as a unifying platform for fusing these information sources into a coherent operational picture. Scenario-specific differences in tool usefulness were observed, reflecting the spatial and risk characteristics of each incident type. Overall, the findings indicate that integrated GIS–UAV–VR environments provide a realistic and scalable complement to traditional fire-service command training, enhancing spatially supported decision-making and preparedness for complex emergency response. Given the single-group pretest–posttest design, limited sample size, absence of a control group, and reliance on perceived evaluation measures, the results should be interpreted as indicative rather than as generalizable evidence of training effectiveness. Full article

The safe and efficient integration of small unmanned aircraft systems (sUAS) into the National Airspace System (NAS) requires a systems-based understanding of the interrelations among human, technological, and regulatory components. Existing Federal Aviation Administration (FAA) guidelines restrict most operations to visual line of sight (VLOS), which constrains operational scalability and underscores the need for system-level innovations supporting beyond-visual-line-of-sight (BVLOS) operations. This study adopted a socio-technical systems approach to evaluate how first-person view (FPV) technologies influence operator workload and situational awareness (SA), key human performance elements within the broader sUAS safety system. Participants meeting FAA Part 107 eligibility criteria were assigned to one of three visual configurations: (a) traditional VLOS, (b) FPV using a 21-inch monitor, or (c) FPV with immersive goggles. Workload was measured with the NASA Task Load Index (NASA-TLX), and Level 1 SA was assessed via post-task recall. ANOVA results revealed no statistically significant differences across visual conditions, indicating no evidence that FPV integration either increased cognitive load or impaired perceptual awareness compared to traditional methods. Complementary analysis of NASA’s Aviation Safety Reporting System (ASRS) identified SA as the most recurrent human-factor issue, suggesting system-level implications for human–machine interaction and training design. These findings contribute to the systemic understanding of human factors in UAS operations, supporting FPV’s potential as a viable subsystem for achieving safe and effective BVLOS integration within complex socio-technical aviation systems. Full article

Timely identification of infectious disease threats is essential for public health readiness. Conventional indicator-based surveillance systems, while dependable for tracking established pathogens, frequently lack the agility and sensitivity to detect new infections promptly. Syndromic surveillance, which examines pre-diagnostic and non-specific health indicators from many data sources in near real time, serves as a significant complementary method that improves early warning and situational awareness. This narrative study analysed selected experiences with syndromic surveillance, utilising peer-reviewed literature and institutional records. Four primary data streams were examined: emergency department and hospital records, pharmacy and over the counter (OTC) sales, participative citizen-generated data, and hybrid multi-source systems. Syndromic indicators were reported to identify outbreaks two to fourteen days before standard laboratory reporting across many trials. Data from the emergency department exhibited the highest sensitivity and specificity (47.34% and 91.95%, respectively), whereas pharmacy and participative data offered early indicators at the community level. Integrated systems like ESSENCE (Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA) and SurSaUD^® (Saint-Maurice cedex, Paris, France) attained enhanced accuracy yet necessitated significant data integration and governance capabilities. Syndromic surveillance enhances epidemic preparation by detecting atypical health-seeking behaviours and variations from baseline patterns prior to formal diagnosis. Nonetheless, its efficacy is contingent upon data quality, interoperability, and contextual adaptation. Countries like Bulgaria could improve national early-warning capabilities and overall health security through the gradual adoption of pilot projects and integration with existing surveillance networks. Full article

As part of our technology-enhanced learning (TEL) strategy, we developed a field-based augmented reality (AR) learning system for biodiversity education among senior elementary school students. Using a 2D illustration style to present the appearance of the species and a situational interactive design, the AR app focused on common wild animals in Taiwan. They also gained insight into wild animal species in outdoor settings, gained knowledge about the phenomenon of roadkill and the rescue of wild animals, and promoted their awareness of ecological conservation. Using the design-based research (DBR) method, we integrated user-oriented design processes and iteratively modified the system functions and interface through expert review and field usability testing. During this activity, 26 senior elementary school students were recruited to participate in an interactive AR game designed for a single player. As part of the learning content, students must collect images of species, recognize roadkill, and learn about wildlife rescue. To evaluate the effect of the activity on knowledge learning and the app’s usability, data were collected through pre- and post-test paper tests, questionnaires, and so on. Based on the research results, this system can significantly enhance students’ learning interests and contextual understanding of biodiversity topics as an effective technology-assisted learning tool. Students reported high levels of immersion and learning motivation, and the teachers agreed that it promoted inquiry-based and independent learning. The results of this study contribute to the field of educational and environmental education. Consequently, context-aware AR tools may enhance students’ situational learning experience and environmental literacy. In addition, it provides a practical design reference for future AR educational applications, demonstrating that gamification and outdoor learning can enhance the learning outcomes of traditional science education. Full article