Search Results (1,876)

Distance learners in higher education are often assumed to face limited peer interaction, potentially weakening their sense of belonging. This study examines peer relationships and belonging among students in distance and blended university programs, with attention to the role of virtual reality (VR) within digitally mediated learning environments. Immersive VR teaching is included in the curriculum for distance learning students in the studied programs. Using a mixed-methods design, survey data and open-ended responses were collected from 17 students in Information Studies and Information Service Design. An adapted Classroom Community Scale was supplemented with items addressing the perceived contribution of different communication technologies. Contrary to expectations, fully distance learners did not report weaker agreement with statements reflecting belonging than blended students; on several items, they expressed stronger agreement, particularly regarding perceived peer support and learning opportunities. Results indicate that conventional 2D communication tools, particularly chats and video calls, are central to sustaining peer relationships. VR was not perceived as essential but described by some students as an added value supporting shared experience and group cohesion. Overall, belonging emerges as a socio-technical achievement shaped by communication practices rather than physical proximity. Full article

Distance higher education places increased demands on instructors’ emotional and communicative competencies, as teaching and interaction occur in technologically mediated environments. This study examines the role of teachers’ emotional intelligence, empathy, and communication-related competencies in distance higher education, with particular emphasis on emotional management and instructor well-being. A quantitative research design was employed, using self-report instruments administered to higher education instructors engaged in distance teaching. Non-parametric statistical analyses revealed strong internal coherence among emotional intelligence dimensions and a pattern of functional empathy characterized by high perspective taking and low personal distress. Self-perceived communication was found to be consistent across interactional contexts, indicating a stable communicative disposition. Most notably, emotional management emerged as a key factor associated with positive work-related emotions among instructors. The findings highlight emotional management as a critical mechanism supporting both teaching effectiveness and emotional sustainability in online learning environments. The study contributes to the literature by integrating emotional intelligence, empathy, and self-perceived communication within a unified empirical framework and offers practical implications for professional development and institutional support in distance higher education. Full article

As AI-driven educational systems increasingly rely on deep neural networks, their vulnerability to adversarial perturbations raises concerns about assessment integrity, fairness, and reliability. Adversarial example purification is attractive for such deployments because it removes input perturbations without modifying the already deployed models. However, most existing purification methods are inherently goal-free: denoising-based approaches apply blind heuristic operators, while reconstruction-based methods rely on stochastic sampling guided by natural image priors. These methods typically suppress perturbations at the cost of weakening semantic details or inducing structural distortions. To address this limitation, we propose a novel goal-directed purification framework, termed adversarial energy field optimization for adversarial example purification (AEFOP). AEFOP formulates purification as a constrained optimization problem by defining a learnable adversarial energy which quantifies how far an input deviates from the benign region. This allows adversarial examples to be explicitly pushed from high-energy regions toward low-energy benign regions along an interpretable descent trajectory. Specifically, we build an adversarial energy network and optimize the energy field via a two-stage strategy: adversarial energy field shaping, which enforces distance-like energy behavior and correct gradient directions, and task-driven energy field calibration, which unrolls the descent process to calibrate the field with classification-consistency and semantic-preservation objectives. Extensive experiments across multiple attack scenarios demonstrate that AEFOP achieves superior purification accuracy and high visual quality while requiring only a few gradient steps during inference, offering a practical and efficient robustness layer for vision-based AI services in education. Full article

This paper aims to navigate the complexity inherent in the concept of place by defining and highlighting the role of place-informed education across different international contexts: the periphery in Northern Israel, coastal areas of England, and rural Montana in the United States. Using a thematic analytic framework, we conducted a cross-context comparison of three case studies in order to identify each locale’s unique definitions and meanings of place, producing a portrait of the similarities and differences among the three international contexts. Following the ‘Simplicity–Accuracy Paradox’ and recognizing the ‘cost of oversimplification’, we explored complexity as a basis for action, which enables the creation of a process in which the strengths and limitations of the place both have an important role to play in any intervention or action to mitigate and/or enhance the consequences of distance from urban centers. The proposed strategies presented in the paper are based on embracing the complexity of place for place-informed education, and include context-responsive policy design, targeted workforce strategies, international learning exchanges, and policy and classification reform. These processes may serve as a guide for action among educators, policymakers and researchers, supporting a mindset of place-informed education where complexity is embraced and where challenges of place may also offer solutions. Full article

Although Spain has formally aligned with the 2030 Agenda, the implementation of the Sustainable Development Goals (SDGs) remains uneven and fragmented. This study proposes a multi-criteria framework for evaluating national SDG performance between 2015 and 2024. The approach combines trend analysis, statistical coverage, and distance-to-target metrics. The results reveal clear structural asymmetries. Spain has made significant progress in terms of health, education, and access to energy. However, the country continues to underperform in terms of inequality, climate action, biodiversity, and institutional effectiveness. These disparities are exacerbated by data limitations, as several SDGs lack updated, disaggregated information. The findings highlight a systemic disconnect between political commitment and implementation capacity. Key weaknesses include limited policy coherence, poor coordination between government bodies, and inadequate fiscal alignment with sustainability goals. This study contributes to shifting the focus from reporting on indicators to governance for sustainability by integrating quantitative analysis with structural interpretation. The proposed framework is transparent and adaptable, offering relevant insights for countries facing similar challenges in decentralised governance contexts. Full article

Background: In multicultural healthcare systems such as the Italian one, migrant children may experience dental care as particularly stressful because linguistic and cultural barriers can limit communication, emotional expression, and understanding of the clinical setting. Aim: Understanding the emotional experience of migrant children during dental visits is essential for improving clinical management in pediatric dentistry and orthodontics within multicultural contexts. Because linguistic barriers often limit verbal communication, this study aimed to explore children’s mental representations, emotional states, and perceptions of the dental environment through drawing and to evaluate the clinical implications for communication and therapeutic collaboration. Methods: This qualitative study was conducted in Italy between 2016 and 2025 and analyzed 50 drawings produced by 50 foreign-born migrant children aged 6–13 years, recruited through an educational cooperative in Piacenza. Most participants originated from developing countries and had limited proficiency in Italian, frequently showing a marked “experience gap” in drawing ability that interfered with normative developmental stages described by Lowenfeld. The analysis focused on spatial organization, line quality, color use, posture, interpersonal distance, and representation of the clinical environment, integrating graphic competence assessment with emotional interpretation. Results: Younger children commonly depicted rigid lines, essential settings, and oversized dental unit lamps, whereas older children increasingly represented threatening or disproportionate instruments, aggressive dentists, and omission of the patient figure. Around age 10, drawings became more detailed and colorful, although symbols of closure, such as locked doors, persisted. In adolescents, representations polarized between rich, coherent scenes and extremely essential drawings dominated by fear, rigidity, minimal environments, and symbols of constraint. The findings suggest that drawing may represent a valuable non-verbal clinical and communicative resource for exploring migrant children’s emotional experience of dental care and for identifying signs of anxiety and vulnerability that may not emerge through verbal interaction alone. Conclusions: These findings support the value of a culturally sensitive dental approach integrating drawing, visual aids, multilingual educational materials, and play-based strategies to reduce communication barriers and improve cooperation in migrant children receiving pediatric dental and orthodontic care. Full article

Background: Nursing homes are congregate settings for elderly individuals where infectious diseases can easily spread. The elderly are at high risk of contracting and dying from influenza, and the most effective way to prevent this is to receive the influenza vaccine. Methods: This study conducted a cross-sectional survey of elderly people in nursing homes to investigate the occurrence of influenza symptoms during the 2024–2025 flu season, as well as vaccination status and reasons for receiving or not receiving the vaccine. Bivariate logistic regression was used to determine the factors influencing the vaccination rate. Results: Of the 1024 elderly people who participated in the survey, 25.39% reported experiencing flu-related symptoms in the previous flu season. While 16.21% of the elderly expressed willingness to receive vaccination, only 5.57% actually received it. Influenza vaccination was positively correlated with educational attainment (aOR 3.800, 95% CI 1.480–9.758 for middle school; aOR 5.138, 95% CI 1.738–15.191 for high school), monthly household income (aOR 0.216, 95% CI 0.072–0.644 for >8000), ability for self-care (aOR 0.269, 95% CI 0.123–0.591), and the scale of the nursing home (aOR 9.033, 95% CI 1.531–53.305 for 151–299; aOR 2.629, 95% CI 1.359–5.084 for ≥300). Willingness to receive the influenza vaccination was positively correlated with an unhealthy health status (aOR 0.398, 95% CI 0.204–0.779), symptoms of influenza (aOR 2.730, 95% CI 1.861–4.007), nursing home location (aOR 1.537, 95% CI 1.099–2.941 for outer suburbs), and the scale of the nursing home (aOR 1.991, 95% CI 1.154–3.435 for 151–299; aOR 2.158, 95% CI 1.374–3.390 for ≥300). Most elderly people who received the vaccine believed that vaccination could effectively prevent flu and that it could reduce the risk of complications, the rest were not vaccinated due to concerns about adverse reactions, mobility issues, or the distance to vaccination sites. Conclusions: Low awareness of flu vaccines and physical inability to travel to vaccination sites may be potential barriers to receiving the flu vaccine. It is worrying that the influenza vaccination rate is low among the elderly in nursing homes in Shanghai. As a result, it is crucial to prioritize targeted monitoring and intervention strategies for vulnerable populations living in collective institutions. Full article

Massive Open Online Courses (MOOCs) serve as catalysts for sustainable education by democratizing access to lifelong learning. While this potentially positions them as a key driver of the United Nations Sustainable Development Goal 4 (SDG 4), their long-term impact depends heavily on the implementation of inclusive design and ethical governance. This study evaluates the social sustainability of the AKADEMA platform—defined through equity of access, institutional trust, and long-term learner retention—using Badrul Khan’s e-learning framework. Employing a multi-layered mixed-methods design, the study triangulates subjective user perceptions—gathered via quantitative surveys (N = 209; a convenience sample of 6140 contacted users) and qualitative insights (n = 122)—with objective structural evidence from a technical accessibility audit. Although the results indicate high satisfaction with pedagogical quality, the findings reveal specific structural nuances regarding platform inclusivity and user diversity. Specifically, data triangulation highlights a notable ‘privacy awareness gap’—where working professionals demonstrate higher sensitivity regarding data governance than learners—alongside structural barriers hindering ‘Universal Design’ for learners with disabilities. Consequently, to strengthen the sustainability of open education models, future strategies should emphasize digital equity and institutional trust, ensuring that technical environments align with the promise of inclusive quality education. Full article

Flooding is a recurrent climate-related hazard in southern Thailand that frequently disrupts schooling and undermines educational continuity. Despite the critical importance of school-based disaster preparedness, there is limited empirical evidence explaining the drivers of flood preparedness among primary school teachers in climate-vulnerable regions. This study aimed to identify the cognitive, experiential, and topographic factors correlated with flood knowledge, flood risk perception (FRP), and flood preparedness (FP) among primary school teachers in Nakhon Si Thammarat province. A cross-sectional survey was conducted with 745 teachers using a structured questionnaire that covered sociodemographic characteristics, flood experience, training, information sources, and regional topography (elevation, slope, and distance to river). Spearman’s rank correlation and Generalized Linear Models (GLMs) were applied to examine the relationships and predictive factors. The findings revealed that topographic factors, specifically distance to the nearest river, were significantly associated with teachers’ flood knowledge, while school elevation was significantly related to FRP. Community-based information was a strong predictor of flood knowledge. Furthermore, prior flood experience, first-aid training, access to school-based information networks, and FRP were identified as key drivers of FP. Moreover, the negative relationships were found between flood knowledge and FP suggest that preparedness is influenced by complex cognitive and behavioral mechanisms rather than knowledge alone. These findings highlight the importance of integrating topographic risk information, experiential learning, and community-based information networks into school-based disaster preparedness programs rather than relying solely on knowledge. These findings offer practical implications for designing targeted teacher training and school-based disaster risk reduction (DRR) strategies in climate-vulnerable settings. Full article

Early and reliable fault detection in Brushless Direct Current (BLDC) motors is essential for improving system reliability and reducing unplanned industrial downtime. This study presents a controlled experimental investigation of data-driven machine learning approaches for the classification of multiple common BLDC motor faults. Four representative fault-related indicators were obtained under systematically designed operating conditions, and a consistent feature extraction procedure was applied prior to model development. A comparative evaluation was conducted using Multi-Layer Perceptron (MLP), Support Vector Machines (SVM), k-Nearest Neighbour (kNN), and decision tree-based classifiers. All models were trained and tested on the same dataset using an identical validation protocol to ensure methodological fairness and reproducibility. Performance was assessed through standard classification metrics, enabling a transparent comparison of predictive capability and stability. The results show that the MLP model achieved the highest overall classification accuracy (91.6%), closely followed by SVM (91.4%) and kNN (90.2%). Although the performance differences are moderate, the neural network demonstrated more consistent behaviour in scenarios where fault signatures exhibited overlapping characteristics. These findings suggest that non-linear feature interactions play a significant role in BLDC fault discrimination and can be effectively captured by multi-layer architectures. The study provides a reproducible experimental framework and a balanced performance assessment that may support both academic research and the practical development of intelligent condition monitoring systems for BLDC-driven applications. Full article

Background/Objectives: Accurate pedicle screw placement is critical in spine surgery, as malposition can cause neurological, vascular, or visceral injuries and compromise construct stability. The primary objective of this study was to develop and experimentally validate a dual quantitative framework for assessing pedicle screw placement accuracy, combining (1) coaxiality, a standardized geometric metric of trajectory alignment, and (2) pedicle wall distance (dpw), a novel parameter defined as the minimal distance between the screw axis and the pedicle cortex providing surgeons with direct, millimetric, clinically actionable feedback. A secondary objective was to compare these parameters: dpw, coaxiality, entry point errors and orientation angle errors between senior surgeons and residents to evaluate the influence of surgical experience. We hypothesized that this framework would provide reproducible quantitative measurements, demonstrate strong agreement with established CBCT-based grading systems, and allow meaningful subgroup comparisons by experience level. Methods: Eight operators (four senior surgeons, four residents) performed 240 pedicle screw insertions on synthetic polyurethane lumbar spine models using freehand, CBCT-assisted, and navigation-assisted techniques. Predefined 3D trajectories were compared with actual screw positions digitized with sub-millimetric precision. Errors, coaxiality, and dpw were computed, and dpw was validated against CBCT-based Gertzbein and Heary classifications. Agreement and diagnostic performance metrics (Kappa, sensitivity, specificity) were calculated. Results: Of 236 analyzable screws, coaxiality correlated with entry point errors (ρ = 0.41), target point errors (ρ = 0.85), and orientation angle errors (ρ = 0.48), confirming its robustness as an engineering metric. dpw provided immediate, interpretable feedback and demonstrated near-perfect agreement with CBCT grading (Kappa = 0.86; sensitivity = 0.96; specificity = 0.97), detecting breaches missed by qualitative classifications. Subgroup analyses indicated small but significant differences between senior and junior surgeons for target point errors (p = 0.006), orientation angle errors (p = 0.025), and coaxiality (p = 0.023), whereas entry point errors (p = 0.201) and dpw (p = 0.163) did not differ significantly. Conclusions: This dual-metric framework bridges engineering rigor and intraoperative applicability. Coaxiality supports reproducible research assessment, while dpw enables actionable surgical feedback. The framework allows objective comparison across operators of different experience levels. Together, these metrics offer a standardized, clinically relevant, and quantitative method for evaluating pedicle screw placement, with potential to enhance surgical safety, education, and patient outcomes. Full article

Background: Gait re-education is one of the key elements of comprehensive rehabilitation after total hip replacement. Recent technological advancements allow patients to benefit from increasingly sophisticated training solutions based on biofeedback. The aim of this study was to assess the impact of a treadmill training protocol with a digital biofeedback component on the gait parameters of patients after an uncomplicated total hip replacement and on their functional status. Methods: The study included 137 patients after total hip replacement. In the control group, traditional walking training with biofeedback in the form of a mirror was used. In the study group, the Biodex Gait Trainer 3 treadmill was used for this purpose, which also served as a diagnostic tool for both groups. The following parameters were assessed: distance, average walking speed, average step cycle, step length, coefficient of variability and time on each foot. Additionally, the study included the Timed Up & Go (TUG) test and the use of orthopedic supplies. Results were considered statistically significant at p < 0.05. Results: Significant statistical differences were found between the groups in terms of distance, average walking speed, and step length. Additionally, significantly shorter TUG times were observed and a higher rate of discontinuation of orthopedic supplies in the study group. However, the therapy method did not have a significant effect on the average step cycle, coefficient of variability or time on each foot. These parameters showed comparable improvement in both groups. Conclusions: Treadmill training with visual biofeedback has a positive effect on certain gait parameters. The greatest benefits from this type of training can be gained by patients with deficits in stability and mobility in space. Full article

This article explores how young women of colour in Norway navigate everyday racism and how such negotiations are shaped by the tension between speaking out or maintaining social harmony in a society that largely perceives itself as egalitarian and non-racist. The study draws on qualitative interviews with 13 participants from diverse ethnic backgrounds—some were adopted, and others were children of immigrant parents or immigrants themselves. The analysis examines how anti-racism strategies are shaped by drawing on feminist and postcolonial theory, particularly the concept of the feminist killjoy. The notion of Orientalism, and the notion of cultural repertoires. The findings show that participants demonstrated different reactions from silence to confrontation, all demanding emotional labour. Several participants described the burden of having to choose between remaining polite and educating others, while others chose silence as a protective strategy. Rather than viewing resistance as a binary between silence and confrontation, this study demonstrates that everyday anti-racism is a fluid and context-dependent practice. How women performed anti-racism was also closely linked to their social position, social support, cultural norms, and access to political perspectives. The stories show that, over time, some women became more outspoken or secure in their interpretations of racist encounters, especially when gaining distance from constraining environments. Full article

Objective: Population mobility complicates the prevention and control of HIV. To address these challenges, this study explored the molecular epidemiology of HIV among migrant populations in Hangzhou. Methods: People newly diagnosed with HIV/AIDS from 2020 to 2023 were divided into permanent migrant population (PMP), temporary migrant population (TMP), and non-migrant population (NMP). HIV-1 pol gene sequencing was performed to calculate genetic distance. Sample pairs with genetic distances ≤0.005 were used to construct the molecular transmission network. Results: PMP comprised people living with HIV in Hangzhou, characterized by younger age, higher education, and predominantly homosexual transmission. This population forms multiple large molecular clusters together with NMP. TMP accounted for the highest proportion of females and people infected through heterosexual contact, but the education level was the lowest. NMP had the fewest people living with HIV. The main subtypes identified were CRF01_AE, CRF07_BC, CRF08_BC and CRF55_01B. Drug resistance prevalence did not differ significantly among the populations. The molecular transmission network included 833 cases forming 275 clusters, with an overall sample inclusion rate of 23.04%. PMP, TMP and NMP inclusion rates were 27.10%, 19.03% and 21.4%, respectively. All molecular clusters involved migrant populations. Factors associated with inclusion in the network for migrants included current residence, household registration, STD history, sample source, and stage at diagnosis. Conclusions: Migrant populations play a major role in ongoing HIV transmission. Prevention and control measures should be strengthened according to population-specific characteristics. Molecular transmission networks are useful tools for assisting precise control. Full article

Computational simulation is a valuable tool for advancing personalized ergonomics. This study evaluated the ability of musculoskeletal simulation to estimate individual lumbar loading during manual lifting tasks representative of construction activities. Fifty-six Colombian adults were recruited to reflect national anthropometric distributions and grouped by BMI and stature. Participants performed two standardized lifting tasks with a 10 kg load: symmetric lifting from the floor to xiphoid height and lateral lifting from a 0.40 m surface to shoulder height with contralateral transfer. Whole-body kinematics and ground reaction forces were processed in OpenSim software using the validated model to estimate L5–S1 compression and shear forces. Results showed a moderate association between lumbar compression and body weight, while shear forces exhibited low correlations with kinematic variables. Subject-specific scaled models revealed substantial inter-individual differences in lumbar loading related to lifting technique and anthropometric characteristics, highlighting the potential of musculoskeletal simulation for personalized risk assessment in construction. Full article