Search Results (697)

This study examines how rising tourism demand reshapes residents’ environmental responsibility behaviors (ERB) in South Korea, and the moderating role of metropolitan status therein. Using a balanced panel of 174 municipalities over 2015–2023, semi-log regression with a quadratic tourism-demand term and Driscoll–Kraay standard errors is applied to address heteroskedasticity, autocorrelation, and cross-sectional dependence. The estimates show that tourism demand displays a positive effect on ERB (a 6.6% increase in recycling volume proxy per million visitors) up to a certain threshold, beyond which the influence reverses—consistent with an inverted U-shaped relationship under overtourism. Turning points are approximately 11.06 million visitors for non-metropolitan municipalities and 6.95 million for metropolitan ones, where saturation occurs earlier. The negative interaction between metropolitan status and the squared tourism-demand term indicates that the erosion is sharper in metropolitan areas. Among controls, inbound visitor share (+2.8%), regional population (+3.6% per ten thousand residents), resident cost-sharing ratio (+0.4%), tourism special zones (≈1.45 times non-designated areas), tourism complexes (+19.2%), and COVID-19 intervention (≈1.30 times pre-pandemic) are significant, while the fiscal self-reliance ratio exhibits a small adverse impact. These findings suggest tourism policy should favor demand-management over growth-oriented strategies, aligned with regional structural differences and community-based environmental governance. Full article

Kauri dieback, caused by Phytophthora agathidicida Weir, Beever, Pennycook & Bellgard, poses a major threat to the ecological and cultural significance of Aotearoa New Zealand’s kauri forests. Visitor behaviour, particularly boot-cleaning and adherence to track-use guidelines, is a key transmission pathway. Using the COM-B framework and audience segmentation, we surveyed 451 visitors to the Waitākere and Hunua Ranges to identify behavioural drivers, barriers, and segment-specific intervention needs. Stepwise regressions accounted for 52% of the variance in self-reported boot-cleaning compliance and 56% in track-use compliance within this sample (adjusted R²). Boot-cleaning compliance was enhanced by habit strength, worry about spreading the pathogen, awareness of correct procedures, and reliance on functional cleaning stations, while inconvenience and chemical aversion reduced compliance. Track-use compliance was lowered by perceived low likelihood of spread, doubts about mitigation effectiveness, time-cost concerns, and strong forest-use identity, whereas protection motivation and habitual rule-following increased compliance. Latent profile analyses produced three segments per behaviour: boot-cleaning—Conflicted, Receptive, Engaged; and track-use—Identity-Driven Forest Users, Uncommitted, Engaged—which differed systematically in knowledge, concern, and compliance. We outline potential intervention implications informed by these findings and prior literature. Full article

A dual-platform mushroom cultivation system integrating artificial intelligence (AI)-assisted environmental monitoring and controlled-environment agriculture (CEA) was developed to support experiential STEM education across K–12 and undergraduate settings. Hands-on instruction with multicellular fungi is often limited by reliance on microbial models and by constraints associated with field-based activities. To address this gap, we implemented an indoor instructional platform that combines a commercial AI-assisted automated cultivation unit with a tent-based chamber for hands-on environmental control. Representative cultivated species included oyster mushrooms (Pleurotus spp.) and lion’s mane (Hericium erinaceus). The AI-assisted system provided sensor/camera-based monitoring, app-based feedback, and software-assisted regulation of humidity, light, and airflow, whereas the tent-based system enabled direct student manipulation of cultivation conditions. Together, the systems allowed students to observe fungal development, manage environmental parameters, and collect quantitative and qualitative data within a single academic term. Post-harvest activities, including mushroom-based food preparation and tasting, further connected fungal biology with food and sustainability. A matched pre- and post-course survey (n = 30) showed increases in students’ self-reported perceived understanding, cultivation confidence, and engagement, with mean scores increasing from approximately 2–4 to 6–8. Because the survey instrument was not formally validated and no control group was included, these results are interpreted as preliminary self-reported perceptions rather than objective evidence of learning gains. The platform provides a practical model for integrating fungal biology, AI-assisted environmental monitoring, and CEA into STEM education. Full article

Wound-rotor synchronous machines (WRSMs) offer a promising, magnet-free alternative for safety-critical transportation sectors like electric vehicles (EVs) and marine propulsion. While multiphase structures enhance fault tolerance in these applications, conventional WRSMs still suffer from reliance on maintenance-prone slip rings and brushes. Brushless multiphase self-excitation presents a compelling solution, but it introduces a critical design challenge: ensuring decoupled control between the torque-producing (αβ) and magnetizing () subspaces to prevent severe performance degradation. To address this cross-coupling issue, this paper proposes a 20-slot/18-pole five-phase architecture. By exploiting distinct spatial harmonics, the stator generates two independently controlled magnetic fields with a dedicated rotor harmonic winding. An integrated diode rectifier then seamlessly converts the induced AC voltages into the required DC field excitation. Extensive finite-element analysis (FEA) using ANSYS Maxwell is conducted to validate the design and rigorously evaluate subspace cross-coupling. Simulation results confirm that the proposed machine meets design specifications, demonstrating stable self-excited operation, acceptable efficiency, and representative fault-tolerant operation under a single open-phase condition, thereby confirming the electromagnetic feasibility of the proposed topology as a promising magnet-free candidate for future alternatives to PMSM-based traction solutions. Full article

Despite the growing attention paid to sustainability education, limited quasi-experimental research has examined how metacognitive guidance can integrate cognitive, affective, and agency-oriented learning in food-related climate education. This classroom-based quasi-experimental study, complemented by student interviews, investigated a six-lesson metacognitive guidance-based unit designed to strengthen ninth-grade students’ sustainable food literacy (SFL), climate-change perceptions and attitudes, and constructive hope. Participants were 59 students from two intact classes in northern Israel; one class received the intervention, and the other received traditional instruction on the same content. Quantitative data were collected through a sustainable food and climate change knowledge test and a climate change literacy questionnaire and were analyzed using mixed-design repeated-measures ANOVA, t-tests, and multiple regression. Qualitative data were obtained from individual semi-structured interviews with students in the experimental group. Results indicated significant intervention-related gains in SFL knowledge, climate-change perceptions, climate-change attitudes, and constructive hope, with moderate-to-large time × group effects across the main outcomes (partial η² = 0.16–0.33). Climate-change perceptions emerged as the strongest post-intervention predictor of constructive hope (β = 0.92, p < 0.001). Interviews illustrated how reflective prompts, self-monitoring, discussion, and learning artifacts supported conceptual understanding, moral responsibility, perceived agency, and self-reported short-term intentions for sustainable food choices. The findings suggest that metacognitive guidance can support integrative, hope-oriented sustainability learning among adolescents. These findings should be interpreted cautiously given the small non-random sample, the use of two intact classes, the short six-lesson intervention, and the reliance on short-term self-reported outcomes. The study’s novelty lies in integrating sustainable food literacy, climate-change perceptions and attitudes, and constructive hope within a metacognitively guided food–climate unit in a culturally underrepresented Druze school context. Full article

Deep learning has achieved remarkable progress in electrocardiogram (ECG) analysis, but its heavy dependence on labeled data greatly increases annotation cost. This work proposes wall-aligned vector embedding (WAVE), a self-supervised learning framework that effectively extracts prior knowledge from unlabeled ECGs to reduce reliance on labels. WAVE fully leverages the diversity, synergy, and lead correlation of multi-lead ECGs by explicitly incorporating the correspondence between ECG leads and cardiac walls. Specifically, a multi-branch network captures lead-wise diversity; wall-wise synergy is modeled by concatenating leads from the same wall and projecting them via shared projection; and a dual alignment task is designed to learn correlations both within and across cardiac walls. Experimental results demonstrate that WAVE consistently surpasses all baselines under various evaluation settings, and maintains strong performance even when only a small fraction of labeled ECGs is available. Furthermore, components such as dual alignment, shared projection, wall-based concatenation, and mean target embedding are empirically verified to significantly enhance pretraining quality. In summary, WAVE learns highly informative ECG representations from unlabeled data, enabling low-cost and label-efficient ECG analysis for real-world cardiovascular diagnostics. Full article

This study investigates the pedagogical landscape of state language instruction in Hungarian-medium schools in Slovakia. Situated within the wider context of European minority language policies, this study explores the institutional ecosystems, didactic approaches and teaching strategies, and the relationship between teacher- and student-centered methodologies in state language instruction. A questionnaire survey based on a self-developed Multi-Level Diagnostic Model was administered to a representative sample of teachers, accounting for 23% of the total Slovak teacher population working in this distinctive sociolinguistic setting (N = 112). Although the results indicate that the educational process is shaped by various factors and there is an endeavor to promote communicative practice, the competence–use gap persists due to the reliance on conventional teacher-centered teaching approaches. This trend is driven by a methodological vacuum, the absence of specialized L2 teaching materials and the lack of modern digital resources; it also suggests that teachers are forced to prioritize instructional security rather than being resistant to innovation. The findings suggest that the current educational system is ready for change, but it requires systemic investment in resources to promote the balanced development of intercultural communicative competence. Addressing the linguistic distance between Hungarian L1 and Slovak L2 through specialized materials may promote a model of additive bilingualism that ensures professional credibility and the protection of minority cultural identity. Full article

Background/Objectives: The rapid expansion of social media platforms has profoundly changed the way adolescents access reproductive health information. While digital environments increase accessibility to contraceptive content, they also facilitate the dissemination of misinformation, potentially influencing both contraceptive literacy and psychological well-being. The present study aimed to evaluate the relationship between sources of contraceptive information, contraceptive misinformation endorsement, contraceptive knowledge, and mental health indicators among Romanian adolescents and young adults. Methods: A cross-sectional observational study was conducted in a cohort of 210 Romanian adolescents and young adults. Participants completed a structured self-administered questionnaire assessing demographic characteristics, contraceptive information sources, digital health behaviors, contraceptive misconceptions, and contraceptive knowledge. Anxiety and depressive symptoms were evaluated using the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) scales. Correlation analyses and multivariable logistic regression models were performed to identify factors associated with poor contraceptive knowledge and moderate-to-severe anxiety. Results: Social media represented the primary source of contraceptive information for 58.1% of participants. Individuals relying predominantly on social media demonstrated significantly lower contraceptive knowledge questionnaire (CKQ) scores compared to those obtaining information from healthcare professionals (5.9 ± 1.8 vs. 8.1 ± 1.7, p < 0.001). Contraceptive misinformation endorsement was inversely correlated with CKQ scores (r = −0.44, p < 0.001) and positively associated with anxiety (r = 0.47, p < 0.001) and depressive symptoms (r = 0.41, p < 0.001). In multivariable analyses, primary reliance on social media (OR 2.21, 95% CI 1.12–4.34, p = 0.022) and low digital health literacy (OR 2.94, 95% CI 1.51–5.71, p = 0.001) were independently associated with poor contraceptive knowledge. Higher misinformation endorsement, infertility-related fears, and high social media exposure were independently associated with moderate-to-severe anxiety. Conclusions: Contraceptive misinformation endorsement was associated with lower contraceptive literacy and poorer psychological outcomes among adolescents and young adults. These findings highlight the growing importance of digital health literacy. However, given the cross-sectional design, the observed relationships should be interpreted as associations rather than causal effects, and longitudinal studies are required to clarify their directionality. Full article

Background/Objectives: Higher education requires students to communicate in complex academic and social contexts, including oral presentations, group work, help-seeking, assessment, and peer interaction. For students with developmental communication disorders, and communication-related developmental profiles, these demands may create hidden participation vulnerabilities that affect mental health, academic engagement, and belonging. This scoping review mapped empirical evidence among tertiary students, focusing on mental health, academic participation, social belonging, institutional support, and contextual influences. Methods: A scoping review was conducted in accordance with PRISMA-ScR guidance. Five databases, PubMed, PsycINFO, CINAHL, Scopus, and Web of Science, were searched for English-language, peer-reviewed empirical studies published from 2000 onwards. Eligible studies involved university, college, or tertiary students with developmental speech, language, fluency, pragmatic communication, or communication-related developmental profiles, who reported at least one mental health, academic, or social participation outcome. Data were charted and synthesised thematically, with methodological quality appraised using CASP-informed criteria. Results: Twenty-one studies were included. Evidence was strongest for stuttering and fluency-related participation, while research on developmental language disorder, speech sound disorder, pragmatic language impairment, cluttering, and mixed communication profiles was limited. Across studies, communication needs intersected with anxiety, depression, stress, self-efficacy, oral assessment, help-seeking, disclosure, stigma, accommodation access, and belonging. Key limitations included reliance on self-report, cross-sectional or retrospective designs, inconsistent diagnostic confirmation, and limited evidence for intervention. Conclusions: The available evidence suggests that developmental communication disorders and communication-related developmental profiles can function as hidden participation vulnerabilities in higher education. These vulnerabilities are shaped by students’ communication profiles and by communication-intensive university environments. Universities may therefore need communication-accessible teaching, flexible assessment, visible support pathways, and coordinated support across disability services, counselling, academic support, and speech–language pathology. Full article

This paper investigates the feasibility of 3D self-localization and tracking using chipless radio frequency identification (RFID) tags operating in the terahertz (THz) frequency band. The primary objective is to achieve sub-millimeter (sub-mm) localization and tracking accuracy while minimizing reliance on external infrastructure. To this end, a hybrid localization framework is proposed that jointly exploits round-trip time-of-flight (RToF) and angle-of-arrival (AoA) measurements to enhance localization performance. Although near-field propagation effects are inherently significant in the considered THz operating regime, a simplified far-field approximation is adopted to facilitate tractable system modeling and analytical development. The proposed framework is further extended to dynamic scenarios through an extended Kalman filter (EKF)-based tracking algorithm, which incorporates temporal state evolution to improve estimation robustness under noisy measurements. Furthermore, the Cramér–Rao lower bound (CRLB) for the hybrid RToF-AoA system is derived to establish the fundamental limits of localization accuracy under varying system configurations and measurement conditions. Simulation results demonstrate that the proposed approach is capable of achieving sub-mm localization and tracking accuracy with a highly constrained anchor infrastructure, including operation with a single anchor in the considered scenario. These findings highlight the potential of THz chipless RFID technology as a promising enabling solution for next-generation high-accuracy localization and tracking applications. Full article

Background/Objectives: Community hospitals can be a valuable and cost-effective resource for elderly people, especially in rural areas. Their aim is to promote self-reliance, prevent unnecessary hospital admissions, and facilitate rapid recovery after acute illness. The widespread adoption of intermediate care facilities helps alleviate hospital overcrowding by preventing clinical deterioration through advanced and continuous nursing care. An intermediate care unit was established in a rural area of central Italy. This study aims to describe the impact of a community hospital on patients’ functional status from admission to discharge, describing a real-life model. Methods: This single-center descriptive study examines trends in the quality of care provided. Data were retrieved from anonymized electronic clinical records. Statistical analyses were performed using descriptive statistics, paired t-tests, and Pearson correlation coefficients. Results: A total of 532 residents (mean age 80.7 ± 13.2 years; 61% female) were admitted to the community hospital between January 2022 and September 2025. The mean length of stay was 15.2 ± 7.6 days, with a mean improvement in Modified Barthel Index score of 5.24 ± 7.95 (p < 0.05). Most patients (81.8%) were discharged home, while 6.0% required hospitalization. No readmissions were recorded in 2025. Clinical risk events occurred only in 1.2% of the total. Nursing specialization increased during the study period, correlating with improved patient outcomes (R = 0.88). Conclusions: This descriptive cross-sectional study in a rural nurse-led intermediate care unit found relatively short lengths of stay, high rates of home discharges and modest, but statistically significant, improvements in functional autonomy. Full article

Prior research suggests that programming is a fundamental competency for all students. Due to its importance, programming education is integrated across many disciplines beyond computer science (e.g., humanities, social sciences, and engineering). Also, many existing courses report increasing enrollment trends. However, these changes have also introduced instructional challenges, particularly in supporting students with diverse backgrounds at scale. In this context, many studies have explored the use of AI code assistants as tools that may support instruction and learning. In these studies, while examining the use of AI code assistants, researchers have reported variation in educational contexts, implementation approaches, and outcomes. With this paper, we argue that synthesized information of such variations could help in understanding the effective use of such tools in programming education. To create a synthesized resource on AI code assistants, in this paper, we present a narrative review that synthesizes existing research. We reviewed 29 peer-reviewed studies identified through searches across three databases. The studies were analyzed to identify reported patterns of use, student and instructor perceptions, limitations in existing research, and suggested directions for future research. Across the reviewed studies, AI code assistants were commonly discussed for tasks such as code generation, debugging support, and real-time feedback, with ChatGPT reported most often (16 mentions), followed by GitHub Copilot (6 mentions). Disciplinary information was available in 24 studies, which helped identify the academic settings where AI code assistants were reported. Students generally describe these tools as useful, while also expressing concerns related to over-reliance and accuracy. Student perceptions were reported in 10 studies, while instructor perceptions were reported in 4 studies. Common reported limitations include small sample sizes, short intervention durations, reliance on self-reported data, and limited examination of long-term learning outcomes. Overall, this review consolidates current evidence on how AI code assistants are used and perceived in programming education and identifies areas where more research is needed. Full article

AI use is associated with both cognitive relief and cognitive offloading, leading to uncertainty in how users make value judgments and decisions. This study focuses on in-class AI use and explores the perceptions of cognitive relief and cognitive offloading among university students, as well as the distinct mediating mechanisms through which these factors shape the attitudes of students. Based on questionnaire data from 287 respondents, structural equation modeling and bootstrap methods were employed to test the research hypotheses. The results show that cognitive relief exerts a complementary mediating effect between AI use and attitudes, whereas cognitive offloading functions as a competitive mediator. The two mechanisms produce opposing effects on students, with cognitive relief demonstrating a stronger overall mediating effect. These findings suggest that educators should guide students toward a more nuanced understanding of AI use to mitigate confusion and its potential negative psychological consequences. Moreover, educators and institutions should leverage AI to provide cognitive relief for higher-order learning activities, thereby enhancing the engagement, motivation, and deeper learning processes of students, while simultaneously implementing reflective and critical thinking practices to guard against the risks of cognitive offloading. This study is limited by its single-institution convenience sample and reliance on self-reported data; future research incorporating qualitative methods such as interviews and classroom observations is encouraged to further validate and extend these findings. Full article

This study examines how the relationship between perceived financial accounting disclosures (FAD) and investor reactions to negative financial news (IRNFN) is conditioned by two individual-level moderators among 310 retail investors holding shares in project-based organisations (PBOs) listed on the Dubai Financial Market and Abu Dhabi Securities Exchange. The two moderators are framing bias susceptibility, a cognitive predisposition to be influenced by presentational form, and AI channel reliance (AICR), the extent to which investors rely on AI-mediated information channels—including algorithmic news aggregators, robo-advisory tools, AI-curated social media feeds, and automated sentiment-scored financial alerts—for receiving and interpreting corporate disclosures. Drawing on Behavioural Finance Theory and the Theory of Planned Behaviour, the study investigates whether the strength of the FAD–IRNFN association depends on these cognitive and informational processing conditions. The measurement model was estimated using confirmatory factor analysis in AMOS 25, and the moderation hypotheses were tested through path analysis with mean-centred composite scores and bias-corrected bootstrap inference, with a latent interaction robustness check reported in parallel. AI channel reliance emerged as a substantial moderator of the FAD–IRNFN relationship, while framing bias provided a smaller, marginally significant moderating effect. The findings are consistent with the theoretical expectation that, in AI-mediated information environments, the perceived quality and presentation of complex disclosures are associated with stronger, rather than weaker, investor reactions to negative news. Because the design is cross-sectional and based on self-reported data, the results are interpreted as associations rather than causal effects, with implications for disclosure regulation, corporate communication, and AI platform design in the UAE and comparable emerging markets. Full article

This study examined Saudi adolescents’ digital use, experiences of cyberbullying, and willingness to seek help when facing online risks. Furthermore, the study examined how perceived online safety, preferred reporting sources, exposure to online safety education, and demographic characteristics are associated with resistance to help-seeking. A cross-sectional online survey was completed by 302 adolescents aged 11–17 years across Saudi Arabia. Descriptive statistics, one-way ANOVAs, and hierarchical multiple regression were used to explore patterns and predictors of resistance to help-seeking. Descriptively, the results showed near-universal smartphone access, high daily screen time, and that a substantial minority had experienced recent cyberbullying, including repeated victimization. Although most participants reported feeling safe online, many expressed uncertainty and endorsed self-reliant or avoidant responses, with over half agreeing they would “just ignore” cyberbullying. Parents were the most frequently identified reporting source, yet around one-fifth of adolescents said that they would not seek help from anyone. Regression analyses indicated that female gender, higher socioeconomic status, feeling less safe online, and receiving online safety education from multiple sources were associated with lower resistance to help-seeking, whereas greater cyberbullying exposure predicted higher resistance. Overall, the results highlight the need for multi-source, culturally grounded online safety education and strengthened reporting pathways across families, schools, and digital platforms to support Saudi adolescents who experience cyberbullying and related online harms. Full article