Search Results (3,492)

The integration of artificial intelligence (AI) in education offers novel opportunities to enhance critical thinking while also posing challenges to independent cognitive development. In particular, Human-Centered Artificial Intelligence (HCAI) in education aims to enhance human experience by providing a supportive and collaborative learning environment. Rather than replacing the educator, HCAI serves as a tool that empowers both students and teachers, fostering critical thinking and autonomy in learning. This study investigates the potential for AI to become a collaborative partner that assists learning and enriches academic engagement. The research was conducted during the 2024–2025 winter semester within the Pedagogical and Teaching Sufficiency Program offered by the Audio and Visual Arts Department, Ionian University, Corfu, Greece. The research employs a hybrid ethnographic methodology that blends digital interactions—where students use AI tools to create artistic representations—with physical classroom engagement. Data was collected through student projects, reflective journals, and questionnaires, revealing that structured dialog with AI not only facilitates deeper critical inquiry and analytical reasoning but also induces a state of flow, characterized by intense focus and heightened creativity. The findings highlight a dialectic between individual agency and collaborative co-agency, demonstrating that while automated AI responses may diminish active cognitive engagement, meaningful interactions can transform AI into an intellectual partner that enriches the learning experience. These insights suggest promising directions for future pedagogical strategies that balance digital innovation with traditional teaching methods, ultimately enhancing the overall quality of education. Furthermore, the study underscores the importance of integrating reflective practices and adaptive frameworks to support evolving student needs, ensuring a sustainable model. Full article

This study explores the migration intentions of university students—representing the potential creative class—in Erzurum, a medium-sized city in eastern Turkey experiencing shrinkage. Within the theoretical framework of shrinking cities, it investigates how economic, social, physical, and personal factors influence students’ post-graduation stay or leave decisions. Survey data from 742 Architecture and Fine Arts students at Atatürk University were analyzed using factor analysis, logistic regression, and correlation to identify key migration drivers. Findings reveal that, in addition to economic concerns such as limited job opportunities and low income, personal development opportunities and social engagement also play a decisive role. In particular, the perception of limited chances for skill enhancement and the belief that Erzurum is not a good place to meet people emerged as the strongest predictors of migration intentions. These results suggest that members of the creative class are influenced not only by economic incentives but also by broader urban experiences related to self-growth and social connectivity. This study highlights spatial inequalities in access to cultural, educational, and social infrastructure, raising important questions about spatial justice in shrinking urban contexts. This paper contributes to the literature on shrinking cities by highlighting creative youth in mid-sized Global South cities. It suggests smart shrinkage strategies focused on creative sector development, improved quality of life, and inclusive planning to retain young talent and support sustainable urban revitalization. Full article

Social anxiety is a prevalent mental health concern among college students, often intensified by academic and interpersonal pressures on campus. This study investigated the relationship between physical activity, loneliness, and social anxiety among college students, aiming to examine the mediating role of loneliness in the process of physical activity affecting social anxiety, as well as the moderating role of gender in this mediating effect. A cross-sectional research design was adopted, and data on physical activity levels, loneliness, and social anxiety were collected through questionnaires completed by 638 students at a university in China. This study conducted a single-factor Harman test, descriptive statistical analysis, reliability analysis, correlation analysis, and independent-samples t-tests, and it modeled the moderated mediation effect. The results showed that physical activity was significantly and negatively correlated with both loneliness and social anxiety. Loneliness played a mediating role in the influence of physical activity on social anxiety, and this mediating effect was moderated by gender, being more pronounced in the female group. This study concluded that physical activity can help alleviate social anxiety, but the mechanism involving the reduction of loneliness is more apparent in women, indicating the need to consider gender differences when developing interventions, as there may be other, more significant reasons for men. Full article

Directed Energy Deposition is an additive manufacturing subgroup that uses a laser beam to melt the wire or powder to create a melt pool. In the current study, a scientometric analysis has been carried out to analyze the contribution of countries, publication type analysis, distribution of publications over the years, keywords analysis, author analysis, cited journal, categories, institutes of publication, and report the practical implications. Firstly, the database was extracted from the Web of Science and then post-processed with CiteSpace 6.2.R4 and VOSviewer 1.6.20 software. Afterward, the associated results had been extracted and reported. It was found that China is the leader according to publication, followed by the USA and Germany, which mostly published their achievements in article and proceeding paper formats, which are increasing annually. According to the keywords, additive manufacturing, Laser Metal Deposition, and fabrication are the most commonly used. Based on the CiteSapce and VOSviewer results, Lin, Xin and Huang, Weidong are the authors with the highest publication rates. In addition, Additive Manufacturing, Materials & Design, and Materials Science and Engineering: A are the most cited journals, and regarding the categories, materials science, multidisciplinary, applied physics, and manufacturing engineering are the most commonly used DED processes. Northwestern Polytechnical University, Fraunhofer Gesellschaft, and the United States Department of Energy (DOE) have performed the most research in the field of DED. Full article

Vortex-induced vibrations (VIVs) pose significant risks to the structural integrity of subsea cables and pipelines under free-span conditions. It is extremely helpful to be able to screen for VIV and understand for a particular cable or pipeline what the minimum free-span threshold lengths are beyond which in-line and/or cross-flow VIV can be excited, causing fatigue problems. To date screening is a more complex and detailed task. This paper introduces a universal dimensionless velocity, V*, and one graph that can be used across all types of VIV free spans to quickly assess minimum free-span threshold lengths. Natural frequencies are not required to be calculated for screening each time, as they are implicit in the curve. The universal criteria are developed via non-dimensional analysis to establish the significant physical mechanisms, after which the relationships are populated, forming a single curve for in-line and for cross-flow VIV with a typical mass ratio and a conservative zero as-laid tension case. Full article

This study examines how Ontario’s Health and Physical Education curriculum addresses the needs of young adults with disabilities. A total of 54 individuals aged 18–35 years old with developmental, learning, or physical disabilities who had completed secondary school in Ontario participated in a cross-sectional mixed-methods survey. Participants were recruited through disability-focused community networks and a university psychology participant pool. They completed the Sex Education subscale of the Sexual Knowledge, Experience, Feelings and Needs Scale, a 35-item sexual knowledge questionnaire, and open-ended questions. Quantitative data were analyzed using descriptive statistics and independent samples t-tests; qualitative responses were examined using thematic analysis. Participants reported limited factual knowledge, minimal classroom representation, and heavy reliance on independent learning. Barriers included inaccessible materials, teacher discomfort, and the absence of disability narratives in sexuality units. Findings point to three priorities: revising curriculum content, expanding educator training, and creating disability-affirming resources. These measures will help ensure comprehensive and rights-based sexuality education that supports the autonomy and well-being of students with disabilities. Full article

The increasing penetration of photovoltaic solar energy has intensified the need for accurate production forecasting to ensure efficient grid operation. This study presents a critical comparison of traditional statistical methods and machine learning approaches for forecasting solar irradiance using the benchmark Folsom PLC dataset. Two primary research questions are addressed: whether machine learning models outperform traditional techniques, and whether time series modelling improves prediction accuracy. The analysis includes an evaluation of a range of models, including statistical regressions (OLS, LASSO, ridge), regression trees, neural networks, LSTM, and random forests, which are applied to physical modelling and time series approaches. The results reveal that although machine learning methods can outperform statistical models, particularly with the inclusion of exogenous weather features, they are not universally superior across all forecasting horizons. Furthermore, pure time series approach models yield lower performance. However, a hybrid approach in which physical models are integrated with machine learning demonstrates significantly improved accuracy. These findings highlight the value of hybrid models for photovoltaic forecasting and suggest strategic directions for operational implementation. Full article

This study proposes a novel metaheuristic algorithm, Cosmic Evolution Optimization (CEO), for numerical optimization and engineering design. Inspired by the cosmic evolution process, CEO simulates physical phenomena including cosmic expansion, universal gravitation, stellar system interactions, and celestial orbital resonance.The algorithm introduces a multi-stellar framework system, which incorporates search agents into distinct subsystems to perform simultaneous exploration or exploitation behaviors, thereby enhancing diversity and parallel exploration capabilities. Specifically, the CEO algorithm was compared against ten state-of-the-art metaheuristic algorithms on 29 typical unconstrained benchmark problems from CEC2017 across different dimensions and 13 constrained real-world optimization problems from CEC2020. Statistical validations through the Friedman test, the Wilcoxon rank-sum test, and other statistical methods have confirmed the competitiveness and effectiveness of the CEO algorithm. Notably, it achieved a comprehensive Friedman rank of 1.28/11, and the winning rate in the Wilcoxon rank-sum tests exceeded 80% in CEC2017. Furthermore, CEO demonstrated outstanding performance in practical engineering applications such as robot path planning and photovoltaic system parameter extraction, further verifying its efficiency and broad application potential in solving real-world engineering challenges. Full article

Objectives: This study investigated levels of work engagement and the occurrence of compassion fatigue among nursing professionals during the COVID-19 pandemic. Methods: A cross-sectional, descriptive, and correlational study was conducted at a Brazilian university hospital between February and April 2022. The Brazilian versions of the Utrecht Work Engagement Scale (UWES-9) and the Professional Quality of Life Scale (ProQOL-BR) were administered. Results: High levels of compassion satisfaction (44.9 points), low levels of burnout (21.0 points), and low levels of secondary traumatic stress (22.8 points) were observed. No professional demonstrated a profile consistent with compassion fatigue. Engagement levels were high for dedication (5.3) and moderate for vigor (4.9), absorption (4.5), and overall engagement (4.9). Burnout showed moderate negative correlations with vigor (r = −0.611, p = 0.005) and dedication (r = −0.599, p = 0.019). Compassion satisfaction showed moderate positive correlations with vigor (r = 0.522, p < 0.001) and dedication (r = 0.572, p < 0.001). The overall engagement score was moderately and positively correlated with compassion satisfaction (r = 0.532, p < 0.001). Conclusions: This study identified high levels of work engagement, especially regarding dedication, and low levels of compassion fatigue among nursing professionals. The data suggest that even amid the emotional and physical demands imposed by the pandemic, participants preserved their emotional well-being and maintained a positive relationship with their work. Full article

Objectives: The aim of this study was to examine the impact of physical activity levels and body mass index (BMI) on the quality of life among university students. Methods: The sample consisted of 495 students (176 males and 319 females). Physical activity was assessed using the International Physical Activity Questionnaire—Short Form (IPAQ-SF), while quality of life was measured using the WHOQOL-BREF questionnaire. Pearson’s correlation coefficient and regression analysis were employed to determine relationships and predictive influence. Data were analyzed using SPSS version 20, with the level of significance set at p < 0.05. Results: The results indicated that male students reported significantly higher levels of moderate and vigorous intensity physical activity compared to female students (p = 0.015 and p = 0.001, respectively), as well as higher scores in the physical health and social relationships domains of quality of life (p = 0.002 and p = 0.001, respectively). Both physical activity and BMI had a statistically significant impact on the physical health (p = 0.040 for males; p = 0.024 for females) and psychological health (p = 0.047 for males; p = 0.000 for females) domains. Specifically, moderate-intensity PA positively influenced physical health (β = 0.21, p = 0.005), while BMI was a predictor of psychological health in males (β = 0.18, p = 0.016). Among females, BMI negatively influenced physical health (β = −0.18, p = 0.002), and both low-intensity PA (β = 0.17, p = 0.002) and BMI (β = −0.21, p = 0.000) significantly affected psychological health. Conclusions: These findings underscore the importance of promoting diverse forms of physical activity and maintaining a healthy BMI in student populations, with consideration for gender-specific approaches to maximize quality of life outcomes. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

Background: Post-traumatic trigeminal neuropathic pain (PTTNP) is a chronic condition often caused by dental procedures such as implant placement or tooth extraction. It involves persistent pain and sensory disturbances, negatively affecting the quality of life of patients. Methods: This retrospective observational study was conducted at Chosun University Dental Hospital and included 120 patients diagnosed with PTTNP involving the orofacial region. Patient data were collected between January 2014 and December 2023. Among them, 79 patients (65.8%) developed PTTNP following dental implant placement, with a total of 121 implants analyzed. The inferior alveolar nerve was most frequently involved. Clinical factors, including the time to treatment, removal of the causative factor, the Sunderland injury grade, and the type of treatment, were evaluated. Pain intensity and sensory changes were assessed using the visual analog scale (VAS). Results: Treatment initiated within the early post-injury period, commonly regarded as within three months, and implant removal tended to improve outcomes. Pharmacological therapy was the most commonly employed modality, particularly gabapentinoids (e.g., gabapentin, pregabalin) and tricyclic antidepressants such as amitriptyline. However, combined therapy, which included pharmacologic, physical, and surgical approaches, was associated with the greatest sensory improvement. Conclusions: Prompt, multidisciplinary intervention may enhance recovery in patients with PTTNP. Implant-related injuries require careful management, and multimodal strategies appear more effective than monotherapies. Full article

Background/Objectives: International students pursuing higher education in the United States face unique challenges that increase their risk of food insecurity, including limited financial resources, employment restrictions, and cultural barriers. While food insecurity among domestic students has been widely studied, limited research focuses on the lived experiences of international graduate students. This study explores the challenges, perceptions, and coping strategies related to food insecurity among international graduate students at a large public university in North Texas. Methods: This qualitative, ethnographic study involved 20 semi-structured interviews with international graduate students who were clients of the university’s food pantry. Participants were recruited using purposive convenience sampling. Interviews focused on students’ experiences with food access, financial constraints, campus resources, and cultural food preferences. Data were analyzed using thematic coding in MAXQDA. Two standardized food insecurity measures—the USDA and FAO scales—were also administered and analyzed using SPSS. Results: Findings revealed that 85% of participants experienced limited access to nutritious and culturally appropriate foods, with 70% reporting hunger due to financial constraints. Themes included lack of cooking skills, limited campus food options, difficulty accessing familiar groceries, and limited job opportunities. Students expressed that food insecurity significantly impacted their physical health, mental well-being, and social lives, though many continued to prioritize academics over personal nourishment. Conclusions: Food insecurity among international graduate students is multifaceted, shaped by financial, cultural, and institutional barriers. Addressing this issue requires culturally sensitive interventions, improved access to diverse food options, tailored student support services, and institutional efforts to better understand and meet the needs of international students. Full article

Background: Overtime adversely affects physical and mental health, contributing to irritability, anxiety, reduced sleep, and even cardiovascular issues, ultimately lowering care quality and increasing turnover intentions. This study aimed to investigate whether prolonged overtime increases the risk of occupational burnout over time among healthcare workers. Methods: We conducted a four-year longitudinal observational study using secondary data from annual surveys (2021–2024) of healthcare workers at a medical university hospital in Taichung, Taiwan. Burnout was assessed using the personal burnout (PB) scale from the Copenhagen Burnout Inventory (CBI), with high PB levels (HPBL) defined as scores in the upper quartile of the 2021 baseline. Survival analysis utilizing the Kaplan–Meier method and Cox regression investigated burnout progression and the effects of overtime. Results: HPBL was defined as PB scores ≥45.83 (upper quartile in 2021). The proportions of HPBL were 30.28% (2021), 33.29% (2022), 36.75% (2023), and 32.51% (2024). Survival analysis confirmed that the risk of burnout increased over time, with the survival time estimated at 2.50 ± 0.03 years and lower survival probabilities observed among participants working overtime (Log-rank test, p < 0.0001). Multivariate logistics revealed overtime work, female gender, being a physician/nurse, and reduced sleep as independent risk factors for HPBL (OR = 3.14 for overtime, p < 0.001). These findings support the hypotheses on burnout progression and the impact of overtime. Conclusions: Overtime significantly heightens the risk of burnout, which worsens over time. Female sex, healthcare roles, obesity, and insufficient sleep are additional risk factors. Limiting overtime and proactive interventions are crucial to preventing burnout in healthcare workers. Full article

This article presents a new method of parametric shaping of buildings with buffer spaces characterized by complex forms and effective thermal operation in the moderate climate of the Central Europe Plane. The parameterization of an elaborated thermal qualitative model of buildings with buffer spaces and its configuration based on computer simulations of thermal operation of many discrete models are the specific features of the method. The model uses various original building shapes and a new parametric artificial neural network (a) to automate the calculations and recording of results and (b) to predict a number of new buildings with buffer spaces characterized by effective thermal operation. The configuration of the parametric quantitative model was carried out based on the simulation results of 343 discrete models defined by means of ten independent variables grouping the properties of the building and buffer space related to their forms, materials and air circulation. The analysis performed for the adopted parameter variability ranges indicates a varied impact of these independent variables on the thermal operation of buildings located in a moderate climate. The infiltration and ventilation and physical properties of the windows and walls are the independent variables that most influence the energy savings utilized by the examined buildings with buffer spaces. The optimal values of these variables allow up to 50–60% of the energy supplied by the HVAC system to be saved. The accuracy and universality of the method will continuously be increased in future research by increasing the types and ranges of independent variables. Full article