Search Results (368)

Background: Manual wheelchair propulsion is often associated with pain in the upper extremities. Recording spatio-temporal parameters can optimize movement patterns and prevent injuries. This study compares a marker-based camera system with inertial measurement units to validate their use in wheelchair propulsion on a test stand. Methods: Spatio-temporal parameters of 27 manual wheelchair users propelling at three self-selected speeds (slow, normal, fast) were simultaneously recorded using a marker-based camera system and inertial measurement units, and subsequently compared between both systems. Results: A high correlation was observed among all spatio-temporal parameters (ρ > 0.992). The biases for the start time of hand contact with the pushrim (−0.02 ± 0.02 s), hand release from the pushrim (−0.02 ± 0.01 s), and push length (−0.45 ± 21.45 ms) were slightly overestimated, while recovery length (0.54 ± 21.02 ms), cycle speed (2.37 ± 2.67°/s), and push angle (1.75 ± 4.14°) were slightly underestimated. No bias was found for propulsion frequency. Conclusions: The spatio-temporal parameters recorded using inertial measurement units are suitable for the evaluation of manual wheelchair propulsion and can be used in a clinical context. The low acquisition costs and simple installation process may increase the use of inertial measurement units in the future. Full article

Forest fire detection is an essential application in environmental surveillance since wildfires cause devastating damage to ecosystems, human life, and property every year. The effective and accurate detection of fire is necessary to allow for timely response and efficient management of disasters. Traditional techniques for fire detection often experience false alarms and delayed responses in various environmental situations. Therefore, developing robust, intelligent, and real-time detection systems has emerged as a central challenge in remote sensing and computer vision research communities. Despite recent achievements in deep learning, current forest fire detection models still face issues with generalizability, lightweight deployment, and accuracy trade-offs. In order to overcome these limitations, we introduce a novel technique (FireNet-KD) that makes use of knowledge distillation, a method that maps the learning of hard models (teachers) to a light and efficient model (student). We specifically utilize two opposing teacher networks: a Vision Transformer (ViT), which is popular for its global attention and contextual learning ability, and a Convolutional Neural Network (CNN), which is esteemed for its spatial locality and inductive biases. These teacher models instruct the learning of a Swin Transformer-based student model that provides hierarchical feature extraction and computational efficiency through shifted window self-attention, and is thus particularly well suited for scalable forest fire detection. By combining the strengths of ViT and CNN with distillation into the Swin Transformer, the FireNet-KD model outperforms state-of-the-art methods with significant improvements. Experimental results show that the FireNet-KD model obtains a precision of 95.16%, recall of 99.61%, F1-score of 97.34%, and mAP@50 of 97.31%, outperforming the existing models. These results prove the effectiveness of FireNet-KD in improving both detection accuracy and model efficiency for forest fire detection. Full article

Traditional neuroticism assessments primarily rely on self-report questionnaires, which can be difficult to implement in highly confrontational scenarios and are susceptible to subjective biases. To overcome these limitations, this study develops a machine learning-based approach using behavioral data to predict an opponent’s neuroticism in competitive environments. We analyzed behavioral records from 167 participants on the MiaoSuan Wargame platform. After data cleaning and feature selection, key behavioral features associated with neuroticism were identified, and predictive models were developed. Neuroticism was assessed using the 8-item neuroticism subscale of the Big Five Inventory. Results indicate that this method can effectively infer an individual’s neuroticism level. The best-performing model was LinearSVR, which balances interpretability, robustness to noise, and the ability to capture moderate nonlinear relationships—making it suitable for behavior-based psychological inference tasks. The correlation between predicted scores and self-reported questionnaire scores was 0.606, the R-squared value was 0.354, and the test–retest reliability was 0.516. These behavioral features provide valuable insights into neuroticism prediction and have practical applications in psychological assessment, particularly in competitive environments where conventional methods are impractical. This study demonstrates the feasibility of behavior-based neuroticism assessment and suggests future research directions, including refining feature selection techniques and expanding the application scenarios. Full article

Negative weight-based attitudes are pervasive and difficult to change. One reason may be the moralization of weight: if people use higher weight as a cue for lower self-control, they may infer lower moral character, given the strong link between self-control and morality. Moralized attitudes tend to be resistant to change. Accordingly, we tested whether (1) people perceived others with higher (vs. lower) weight as having lower self-control and, in turn, morality and (2) whether targeting control-related perceptions attenuated the weight → self-control → morality links. To that end, in two preregistered experiments (see OSF), we employed intervention strategies targeting control-related perceptions to increase moral evaluations of higher-weight individuals. Specifically, we provided evidence of a higher-weight person’s (a) weight uncontrollability (Study 1) and (b) high self-control (Study 2). People perceived higher-weight targets as having lower self-control, and this predicted perceptions of lower moral character. However, as with extant weight-based attitude interventions, neither experimental intervention strategy attenuated less positive (i.e., made more positive) moral character perceptions. These findings suggest that it is not enough to intervene on control-related beliefs to reduce the moralization of weight. We suggest intervening on moral perceptions directly and the possibility that moralization of weight may be automatic, requiring interventions targeting automatic attitudes. Full article

The COVID-19 pandemic severely impacted Japan’s inbound tourism, but recent recovery trends highlight the growing importance of Chinese tourists. Understanding their motivations is crucial for revitalizing the industry. Building on our previous framework, this study applies Transformer-based natural language processing (NLP) models and principal component analysis (PCA) to analyze large-scale user-generated content (UGC) and identify key motivational factors influencing Chinese tourists’ visits to Hokkaido. Traditional survey-based approaches to tourism motivation research often suffer from response biases and small sample sizes. In contrast, we leverage a pre-trained Transformer model, RoBERTa, to score motivational factors like self-expansion, excitement, and cultural observation. PCA is subsequently used to extract the most significant factors across different destinations. Findings indicate that Chinese tourists are primarily drawn to Hokkaido’s natural scenery and cultural experiences, and the differences in these factors by season. While the model effectively aligns with manual scoring, it shows limitations in capturing more abstract motivations such as excitement and self-expansion. This research advances tourism analytics by applying AI-driven methodologies, offering practical insights for destination marketing and management. Future work can extend this approach to other regions and cross-cultural contexts, further enhancing AI’s role in understanding evolving traveler preferences. Full article

This study used an equity ethic framework and a STEM identity model to contextualize and understand Latine students’ perceptions of STEM identity development. The purpose of this study was to investigate how Latine undergraduate students who engaged in STEM coursework perceived their learning experiences and stories of resilience through an equity ethic framework. Data were collected through interviews with 19 Latine college students attending a Hispanic-Serving Institution. Findings revealed the following themes related to Latine students’ STEM identity development and lived experiences in STEM coursework: implicit biases, imposter syndrome, self-efficacy, and support system and resources. Findings highlight the need for institutions of higher education to promote Latine students’ self-efficacy to positively influence STEM identity development while addressing systemic issues, such as implicit biases and imposter syndrome to create safe, growth-enhancing educational climates for students with minoritized identities. We provided implications to cultivate Latine students’ STEM identity development through inclusive teaching and learning practices that foster equitable learning environments as well as institutional resources that support students’ mental health and resilience. Implications of this study can be modeled at HSIs to positively influence STEM identity development and increase Latine students’ persistence in STEM fields. Full article

Data bias in geohazard artificial intelligence (AI) systems, particularly class distribution imbalances, critically undermines the reliability of landslide detection models. While active learning (AL) offers promise for mitigating annotation costs and addressing data biases, the interplay between landslide class proportions and AL efficiency remains poorly quantified; additionally, self-optimizing mechanisms to adaptively manage class imbalances are underexplored. This study bridges these gaps by rigorously evaluating how landslide-to-non-landslide ratios (1:1, 1:12, and 1:30) influence the effectiveness of a widely used AL strategy—margin sampling. Leveraging open-source landslide inventories, we benchmark margin sampling against random sampling using the area under the receiver operating characteristic curve (AUROC) and partial AUROC while analyzing spatial detection accuracy through classification maps. The results reveal that margin sampling significantly outperforms random sampling under severe class imbalances (1:30), achieving 12–18% higher AUROC scores and reducing false negatives in critical landslide zones. In balanced scenarios (1:1), both strategies yield comparable numerical metrics; however, margin sampling produces spatially coherent detections with fewer fragmented errors. These findings indicate that regardless of the landslide proportion, AL enhances the generalizability of landslide detection models in terms of predictive accuracy and spatial consistency. This work also provides actionable guidelines for deploying adaptive AI systems in data-scarce, imbalance-prone environments. Full article

This article explores the impact of internalized oppression on young women of colour in Norway, focusing on how it unfolds across individual life trajectories. Drawing on a qualitative methodology, the study is based on narrative in-depth interviews with thirteen participants aged 18 to 35. The findings reveal that internalized oppression, particularly related to physical appearance, emerges early in life and is often reinforced through social interactions such as bullying, exclusion, and racialized commentary. These experiences frequently convey implicit preferences for whiteness, leading to marginalization and insecurity during adolescence. In response, several participants engaged in practices of assimilation, altering their physical appearance in attempts to embody features aligned with dominant white norms. In adulthood, many of these women have developed a critical awareness of internalized oppression and are engaged in processes of decolonizing their self-perceptions through solidarity with other women of colour. Nevertheless, they continue to grapple with lingering internalized biases. This study highlights the need for further research into the life narratives and everyday experiences of racialized individuals to better understand how they navigate, resist, and unlearn internalized oppression—while also considering the gendered dimension of how such oppression works. Full article

Reference-based super-resolution (RefSR) enhances the detail restoration capability of low-resolution images (LR) by utilizing the details and texture information of external reference images (Ref). This study proposes a RefSR method based on hash adaptive matching and progressive multi-scale dynamic aggregation to improve the super-resolution reconstruction capability. Firstly, to address the issue of feature matching, this chapter proposes a hash adaptive matching module. On the basis of similarity calculation between traditional LR images and Ref images, self-similarity information of LR images is added to assist in super-resolution reconstruction. By dividing the feature space into multiple hash buckets through spherical hashing, the matching range is narrowed down from global search to local neighborhoods, enabling efficient matching in more informative regions. This not only retains global modeling capabilities, but also significantly reduces computational costs. In addition, a learnable similarity scoring function has been designed to adaptively optimize the similarity score between LR images and Ref images, improving matching accuracy. Secondly, in the process of feature transfer, this chapter proposes a progressive multi-scale dynamic aggregation module. This module utilizes dynamic decoupling filters to simultaneously perceive texture information in both spatial and channel domains, extracting key information more accurately and effectively suppressing irrelevant texture interference. In addition, this module enhances the robustness of the model to large-scale biases by gradually adjusting features at different scales, ensuring the accuracy of texture transfer. The experimental results show that this method achieves superior super-resolution reconstruction performance on multiple benchmark datasets. Full article

Color blindness can create challenges in recognizing visual cues, potentially affecting players’ performance, emotional involvement, and overall gaming experience. This study examines the impact of color blindness on player engagement and emotional experiences in digital games. The research aims to analyze how color-blind individuals engage with and emotionally respond to games, offering insights into more inclusive and accessible game design. An experiment-based study was conducted using a between-group design with a total of 13 participants, including 5 color-blind and 8 non-color-blind participants (aged 18–30). The sample was carefully selected to ensure participants had similar levels of digital gaming experience and familiarity with digital games, reducing potential biases related to skill or prior exposure. A custom-designed game, “Color Quest,” was developed to assess engagement and emotional responses. Emotional responses were measured through Emotion AI analysis, video recordings, and self-reported feedback forms. Participants were also asked to rate their engagement and emotional experience on a 1 to 5 scale, with additional qualitative feedback collected for deeper insights. The results indicate that color-blind players generally reported lower engagement levels compared to non-color-blind players. Although quantitative data did not reveal a direct correlation between color blindness and visual experience, self-reported feedback suggests that color-related design choices negatively impact emotional involvement and player immersion. Furthermore, in the survey responses from participants, color-blind individuals rated their experiences lower compared to individuals with normal vision. Participants emphasized that certain visual elements created difficulties in gameplay, and alternative sensory cues, such as audio feedback, helped mitigate these challenges. This study presents an experimental evaluation of color blindness in gaming, emphasizing how sensory adaptation strategies can support player engagement and emotional experience. This study contributes to game accessibility research by highlighting the importance of perceptual diversity and inclusive sensory design in enhancing player engagement for color-blind individuals. Full article

Financial literacy plays a crucial role in shaping individual investment decisions by influencing susceptibility to behavioural biases such as heuristics, framing effects, cognitive illusions, and herding mentality. While most existing studies have examined financial literacy as a mediating factor, our study is among the first in the literature to analyse the role of behavioural biases as mediating factors in the relationship between financial literacy and investment decisions. Specifically, we investigate key biases, including overconfidence, herding, disposition effect, self-attribution, anchoring, availability, representativeness, and familiarity. Using purposive sampling, we collected 482 responses through a structured Likert scale questionnaire. The dataset underwent rigorous validation and reliability tests to ensure robustness. We employed Python-based statistical analysis and used Pearson’s correlation and mediation analysis to explore the relationships between financial literacy, behavioural biases, and investment decisions. With the help of these methods, we were able to uncover relationships and causal pathways which further our understanding of the role of behavioural biases in determining the impact of financial literacy on investment behaviour. The findings illustrate a notable positive correlation between investment decisions and financial literacy, implying that people with higher financial literacy levels possess greater and more rational financial decision-making capabilities. Other analyses have revealed that biases have a moderating effect on this relationship, showing another path through which financial literacy impacts behaviour at the level of the investor. By placing behavioural biases as mediating constructs, this research broadens the scope of investor psychology and the body of knowledge in behavioural finance, highlighting the need to change the approach to how financial literacy programs aimed at investors are structured and implemented. Full article

This research aims to study the impact of experiential learning and skill empowerment and community engagement and institutional support systems on student engagement and motivation and sustainable education in Saudi Arabian higher education institutions. The research uses Structural Equation Modeling (SEM) with Partial Least Squares (PLS) as its quantitative methodology to study the relationships between experiential learning, skill empowerment, institutional support systems, and sustainable education. The proposed theoretical model was evaluated through a survey distributed to participants who were conveniently sampled from Saudi Arabian higher education institutions. The research shows that experiential learning together with skill development and community engagement boosts student motivation and supports sustainable education in Saudi Arabia. The study further reveals that institutional support systems have a weak moderating effect because their implementation and perception require improvement to effectively support sustainability. The main limitations are the use of self-reported data which may be influenced by response biases and the focus on higher education only which limits the generalizability of the findings to other educational levels. The research indicates that experiential learning activities including internships, community projects, and skill empowerment programs should be integrated into education to boost student involvement and motivation toward sustainability. The research applies the established theories of Kolb’s Experiential Learning, Human Capital, and Social Learning to Saudi Arabia’s educational context to show how they can be adapted to promote sustainable education through experiential learning, skill development, and community engagement. This study bridges critical research gaps by elucidating the nuanced moderating role of institutional support systems—an underexplored factor—and addressing the methodological limitations associated with a reliance on self-reported data, thereby significantly advancing the understanding of their influence on student engagement and sustainable education within diverse academic and cultural contexts. Full article

Adolescence is a key period for the development and consolidation of habits that favour a healthy and active lifestyle. The promotion of healthy habits in this critical period of development is essential to ensure a better quality of life and the prevention of chronic diseases in the long term. This study aims to analyse how physical activity (PA) and adherence to the Mediterranean diet (MD) influence motivation towards physical education (PE) in adolescents. It also aims to explore gender differences and provide information that will allow the design of educational strategies to promote healthy lifestyle habits in schools. Method: descriptive cross-sectional quantitative study. An ad hoc socio-demographic questionnaire, the Physician-based Assessment and Counselling for Exercise, the KIDMED Mediterranean diet adherence questionnaire and the motivation in Physical Education questionnaire were administered in the school environment under direct supervision of the researchers to minimise biases in self-perception. Results: Students with higher adherence to the Mediterranean diet showed higher intrinsic motivation towards physical education (F = 5.133, p < 0.01), while those with lower adherence showed higher demotivation (F = 5.507, p < 0.01). Conclusions: The findings suggest the need to reinforce physical activity and nutrition education programmes in adolescents, promoting interdisciplinary approaches to increase adherence to healthy lifestyles. Full article

Background/Objectives: Individuals with eating disorders (EDs) experience stronger body illusions than control participants, suggesting that abnormalities in multisensory integration may underlie distorted body perception in these conditions. These illusions can also temporarily reduce body image disturbance. Given the centrality of the face to identity and social functioning—and emerging evidence of face image disturbance in EDs—this study examined, for the first time, whether individuals with EDs exhibit heightened susceptibility to a facial illusion (the enfacement illusion) and whether experiencing this illusion improves face and/or body image. Methods: White Australian female participants (19 with an ED and 24 controls) completed synchronous and asynchronous facial mimicry tasks to induce the enfacement illusion. Susceptibility was assessed via self-report and an objective self-face recognition task, alongside pre- and post-task measures of perceived facial attractiveness, facial adiposity estimation, and head/body dissatisfaction. Results: The illusion was successfully induced across both groups. Contrary to predictions, ED and control participants demonstrated comparable susceptibility, and neither group experienced improvements in face or body image. Notably, participants with EDs experienced increased head dissatisfaction following the illusion. Conclusions: These findings indicate that the multisensory integration processes underlying self-face perception, unlike those underlying body perception, may remain intact in EDs. Participant reflections suggested that the limited therapeutic benefit of the enfacement illusion for EDs may reflect the influence of maladaptive social-evaluative processing biases inadvertently triggered during the illusion. A novel dual-process model is proposed in which distorted self-face perception in EDs may arise from biased social-cognitive processing rather than sensory dysfunction alone. Full article

Background: Life satisfaction serves as a preventive agent against various emotional, cognitive, and behavioral challenges, making it a crucial cognitive indicator of subjective well-being, particularly during adolescence. Accurately assessing life satisfaction is essential for understanding and promoting adolescent mental health, especially in applied settings such as physical education, which plays a key role in fostering psychological well-being and positive youth development. However, additional investigation is needed to confirm the tools used for this purpose. This study aimed to analyze the psychometric properties, metric invariance, and temporal stability of the Satisfaction with Life Scale (SWLS) in adolescents from a region in southeastern Spain. Thus, the present study sought to answer the following research questions: (1) Does the SWLS demonstrate adequate psychometric properties in an adolescent population? (2) Is the SWLS invariant across gender and residential environments? (3) Does the SWLS show adequate stability over time? Methods: A sample of 400 students was assessed using exploratory and confirmatory factor analyses, multigroup comparisons, and test–retest techniques. Results: The results showed significant differences in scale scores in the sex and demographic location variables. Also, a robust unifactorial model with five items demonstrated good performance in terms of goodness of fit and internal consistency. Furthermore, full metric invariance was observed across genders, while configural invariance was supported for residential environment. Concurrent validity analyses revealed significant associations with another unidimensional well-being measure, and temporal stability was confirmed through the intraclass correlation coefficient. Conclusions: The findings support the SWLS as a potentially valid, reliable, and time-effective tool for assessing adolescent life satisfaction. Its strong psychometric properties make it highly suitable for use in mental health research, longitudinal monitoring, and large-scale studies. Moreover, its ease of administration allows its integration into educational, clinical, community-based, and physical education contexts, offering insightful information for the creation of long-lasting mental health regulations and preventive measures meant to improve the well-being of adolescents. Notwithstanding these encouraging results, some restrictions must be noted. The sample was restricted to a single geographic area, and contextual or cultural factors may have an impact on how satisfied people are with their lives. Furthermore, response biases could have been introduced by using self-report measures. Full article