Search Results (3,295)

This study presents the validation of the Player Personality and Dynamics Scale (PPDS), designed to identify player profiles in educational gamification contexts with narrative elements. Through a sample of 635 participants, a questionnaire was developed and applied, covering sociodemographic data, lifestyle habits, gaming practices, and a classification system of 40 items on a six-point Likert scale. The results of the factorial analysis confirm a structure of five factors: Toxic Profile, Joker Profile, Tryhard Profile, Aesthetic Profile, and Coacher Profile, with high fit and reliability indices (RMSEA = 0.06; CFI = 0.95; TLI = 0.91). The resulting classification enables the design of personalized gamified experiences that enhance learning and interaction in the classroom, highlighting the importance of understanding players’ motivations to better adapt educational dynamics. Applying this scale fosters meaningful learning through the creation of narratives tailored to students’ individual preferences. Full article

Background/Objectives: The transformation of nursing and midwifery education through digital technologies has gained momentum worldwide, with algorithm-based video instruction and virtual reality (VR) emerging as promising tools for improving clinical learning. This quasi-experimental study explores the impact of an enhanced flipped classroom model on Bulgarian nursing and midwifery students’ self-perceived competence. Methods: A total of 228 participants were divided into a control group receiving traditional instruction (lectures and simulations with manikins) and an experimental group engaged in a digitally enhanced preparatory phase. The latter included pre-class video algorithms, VR, and clinical problem-solving tasks for learning and improving nursing skills. A 25-item self-report questionnaire was administered before and after the intervention to measure perceived competence in injection techniques, hygiene care, midwifery skills, and digital readiness. Results: Statistical analysis using Welch’s t-test revealed significant improvements in the experimental group in all domains (p < 0.001). Qualitative data from focus group interviews further confirmed increased student engagement, motivation, and receptiveness to digital learning tools. Conclusions: The findings highlight the pedagogical value of integrating structured video learning, VR components, and case-based learning within flipped classrooms. The study advocates for the wider adoption of blended learning models to foster clinical confidence and digital competence in healthcare education. The results of the study may be useful for curriculum developers aiming to improve clinical readiness through technology-enhanced learning. Full article

Gaming has evolved into a cultural phenomenon with a global reach, captivating millions of individuals. Nevertheless, little is known about this population. We aim to physiologically characterise the Portuguese gamers, bearing in mind that phase angle (PhA) is a general indicator of health, to check possible correlations between body composition, strength, and nutrition. A sample of 35 male gamers (individuals who play video games) was evaluated for anthropometry; body composition through DXA for whole-body bone mineral content (BMC), fat-free mass (FFM, kg), fat mass, and visceral adipose tissue, and through BIA (bioelectrical impedance analysis) for total body water (TBW), water pools (extracellular water and intracellular water, ICW), and PhA; strength through maximal isometric handgrip strength using a dynamometer; and nutritional intake using a three-day food record. Results show that participants are within reference metrics for all the analysed variables except regarding protein and carbohydrate intake (all values are above and below the Acceptable Macronutrient Distribution Ranges, respectively). A positive correlation was observed between PhA and TBW, ICW, handgrip strength, BMC and FFM, and a negative correlation with fat mass (absolute, percentage and visceral). In conclusion, PhA correlates with body composition variables, which aligns with previous research as a predictor of health and performance. Full article

Multimodal sentiment analysis (MSA) benefits from integrating diverse modalities (e.g., text, video, and audio). However, challenges remain in effectively aligning non-text features and mitigating redundant information, which may limit potential performance improvements. To address these challenges, we propose a Hierarchical Text-Guided Refinement Network (HTRN), a novel framework that refines and aligns non-text modalities using hierarchical textual representations. We introduce Shuffle-Insert Fusion (SIF) and the Text-Guided Alignment Layer (TAL) to enhance crossmodal interactions and suppress irrelevant signals. In SIF, empty tokens are inserted at fixed intervals in unimodal feature sequences, disrupting local correlations and promoting more generalized representations with improved feature diversity. The TAL guides the refinement of audio and visual representations by leveraging textual semantics and dynamically adjusting their contributions through learnable gating factors, ensuring that non-text modalities remain semantically coherent while retaining essential crossmodal interactions. Experiments demonstrate that the HTRN achieves state-of-the-art performance with accuracies of 86.3% (Acc-2) on CMU-MOSI, 86.7% (Acc-2) on CMU-MOSEI, and 80.3% (Acc-2) on CH-SIMS, outperforming existing methods by 0.8–3.45%. Ablation studies validate the contributions of SIF and the TAL, showing 1.9–2.1% performance gains over baselines. By integrating these components, the HTRN establishes a robust multimodal representation learning framework. Full article

This article reports on a Swedish study investigating how children aged 2–3 years experience mathematical concepts through representations in play-responsive teaching. Drawing on the semiotic–cultural theory of learning, this study examines how representations, such as spoken language, bodily action, and artifacts, are mediated. Video-recorded teaching sessions are analyzed to identify semiotic means of objectification and semiotic nodes at which these representations converge. The analysis distinguishes between children encountering concepts expressed by others and expressing concepts themselves. The results indicate that play-responsive teaching creates varied opportunities for experiencing mathematical concepts, with distinct modes of sensuous cognition linked to whether a concept is encountered or expressed. This study underscores the role of teachers’ choices in shaping these experiences and highlights bodily action as a significant form of representation. These findings aim to inform the use of representations in teaching mathematics to the youngest children in preschool. Full article

Museums serve as essential cultural centers, yet their mostly visual exhibits restrict access for blind and partially sighted (BPS) individuals. While recent technological advances have started to bridge this gap, many accessibility solutions focus mainly on basic inclusion rather than promoting independent exploration. This research addresses this limitation by creating features that enable visitors’ independence through customizable interaction patterns and self-paced exploration. It improved upon existing interactive tangible user interfaces (ITUIs) by enhancing their audio content and adding more flexible user control options. A mixed-methods approach evaluated the ITUI’s usability, ability to be used independently, and user satisfaction. Quantitative data were gathered using ITUI-specific satisfaction, usability, comparison, and general preference scales, while insights were obtained through notes taken during a think-aloud protocol as participants interacted with the ITUIs, direct observation, and analysis of video recordings of the experiment. The results showed a strong preference for a Pushbutton-based ITUI, which scored highest in usability (M = 87.5), perceived independence (72%), and user control (76%). Participants stressed the importance of tactile interaction, clear feedback, and customizable audio features like volume and playback speed. These findings underscore the vital role of user control and precise feedback in designing accessible museum experiences. Full article

The ability to quantify equine kinematics is essential for clinical evaluation, research, and performance feedback. However, current methods are challenging to implement. This study presents a motion capture methodology for horses, where three-dimensional, full-body kinematics are calculated without instrumentation on the animal, offering a more scalable and labor-efficient approach when compared with traditional techniques. Kinematic trajectories are calculated from multi-camera video data. First, a neural network identifies skeletal landmarks (markers) in each camera view and the 3D location of each marker is triangulated. An equine biomechanics model is scaled to match the subject’s shape, using segment lengths defined by markers. Finally, inverse kinematics (IK) produces full kinematic trajectories. We test this methodology on a horse at three gaits. Multiple neural networks (NNs), trained on different equine datasets, were evaluated. All networks predicted over 78% of the markers within 25% of the length of the radius bone on test data. Root-mean-square-error (RMSE) between joint angles predicted via IK using ground truth marker-based motion capture data and network-predicted data was less than 10 degrees for 25 to 32 of 35 degrees of freedom, depending on the gait and data used for network training. NNs trained over a larger variety of data improved joint angle RMSE and curve similarity. Marker prediction error, the average distance between ground truth and predicted marker locations, and IK marker error, the distance between experimental and model markers, were used to assess network, scaling, and registration errors. The results demonstrate the potential of markerless motion capture for full-body equine kinematic analysis. Full article

The accurate perception of visual stimuli in human–machine systems is crucial for improving system safety, usability, and task performance. The widespread adoption of digital technology has significantly increased the importance of visual interfaces and information. Therefore, it is essential to design visual interfaces and information with user characteristics in mind to ensure accurate perception of visual information. This study employed the Cognitive Perceptual Assessment for Driving (CPAD) to evaluate and compare gender differences in the ability to perceive visual signals within complex visual stimuli. The experimental setup included a computer with CPAD installed, along with a touch monitor, mouse, joystick, and keyboard. The participants included 11 male and 20 female students, with an average age of 22 for males and 21 for females. Prior to the experiment, participants were instructed to determine whether a signal stimulus was present: if a square, presented as the signal, was included in the visual stimulus, they moved the joystick to the left; otherwise, they moved it to the right. Each participant performed a total of 40 trials. The entire experiment was recorded on video to measure overall response times. The experiment measured the number of correct detections of signal presence, response times, the number of misses (failing to detect the signal when present), and false alarms (detecting the signal when absent). The analysis of experimental data revealed no significant differences in perceptual ability or response times for visual stimuli between genders. However, males demonstrated slightly superior perceptual ability and marginally shorter response times compared to females. Analyses of sensitivity and response bias, based on signal detection theory, also indicated a slightly higher perceptual ability in males. In conclusion, although these differences were not statistically significant, males demonstrated a slightly better perception ability for visual stimuli. The findings of this study can inform the design of information, user interfaces, and visual displays in human–machine systems, particularly in light of the recent trend of increased female participation in the industrial sector. Future research will focus on diverse types of visual information to further validate these findings. Full article

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

Background/Objectives: Senior nurses in Taiwan shoulder layered responsibilities shaped by professional roles, gendered expectations, and family duty. Although Taiwan faces a persistent shortage of experienced clinical nurses, limited research has explored how long-serving nurses sustain identity and commitment across decades of caregiving. This study examines how senior staff nurses understand their journeys of becoming—and remaining—nurses within a culturally and emotionally complex landscape. Methods: Interviews were conducted between May 2019 and September 2023 in locations chosen by participants, with most sessions face-to-face and others undertaken via video conferencing during COVID-19. This narrative inquiry involved in-depth, multi-session interviews with five female senior staff nurses born in the 1970s to early 1980s. Each participant reflected on her life and career, supported by co-constructed “nursing life lines.” Thematic narrative analysis was conducted using McCormack’s five-lens framework and Riessman’s model, with ethical rigor ensured through reflexive journaling and participant validation. Results: Three overarching themes emerged: (1) inner strength and endurance, highlighting silent resilience and the ethical weight of caregiving; (2) support and responsibility in relationships, revealing the influence of family, faith, and relational duty; and (3) role navigation and professional identity, showing how nurses revisit meaning, self-understanding, and tensions across time. Participants described emotionally powerful moments, identity re-connection, and cultural values that shaped their paths. Conclusions: These narratives offer a relational and culturally embedded understanding of what it means to sustain a career in nursing. Narrative inquiry created space for reflection, meaning-making, and voice in a system where such voices are often unheard. Identity was not static—it was lived, reshaped, and held in story. Full article

Background/Objectives: Sprinting is a fundamental locomotor skill and a key indicator of lower limb strength and anaerobic power in early childhood. The aim of the study was to examine possible differences in the step kinematic parameters and their contribution to sprint speed between children with different patterns of speed development. Methods: 65 prepubescent male and female track athletes (33 males and 32 females; 6.9 ± 0.8 years old) were examined in a maximal 15 m short sprint running test, where photocells measured time for each 5 m segment. At the last 5 m segment, step length, frequency, and velocity were evaluated via a video analysis method. The symmetry angle was calculated for the examined step kinematic parameters. Results: Based on the speed at the final 5 m segment of the test, two groups were identified, the maximum sprint phase (MAX) and the acceleration phase (ACC) group. Speed was significantly (p < 0.05) higher in ACC in the final 5 m segment, while there was a significant (p < 0.05) interrelationship between step length and frequency in ACC but not in MAX. No other differences were observed. Conclusions: The difference observed in the interrelationship between speed and step kinematic parameters between ACC and MAX highlights the importance of identifying the speed development pattern to apply individualized training stimuli for the optimization of training that can lead to better conditioning and wellbeing of children involved in sports with requirements for short-sprint actions. Full article

Background/Objectives: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative factors, but no real-time predictive tool exists. This study aimed to develop an artificial intelligence model based on intraoperative laparoscopic recording of the anastomosis for CAL prediction. Methods: A convolutional neural network (CNN) was trained with annotated frames from colorectal surgery videos across three international high-volume centers (Instituto Português de Oncologia de Lisboa, Hospital das Clínicas de Ribeirão Preto, and Royal Liverpool University Hospital). The dataset included a total of 5356 frames from 26 patients, 2007 with CAL and 3349 showing normal anastomosis. Four CNN architectures (EfficientNetB0, EfficientNetB7, ResNet50, and MobileNetV2) were tested. The models’ performance was evaluated using their sensitivity, specificity, accuracy, and area under the receiver operating characteristic (AUROC) curve. Heatmaps were generated to identify key image regions influencing predictions. Results: The best-performing model achieved an accuracy of 99.6%, AUROC of 99.6%, sensitivity of 99.2%, specificity of 100.0%, PPV of 100.0%, and NPV of 98.9%. The model reliably identified CAL-positive frames and provided visual explanations through heatmaps. Conclusions: To our knowledge, this is the first AI model developed to predict CAL using intraoperative video analysis. Its accuracy suggests the potential to redefine surgical decision-making by providing real-time risk assessment. Further refinement with a larger dataset and diverse surgical techniques could enable intraoperative interventions to prevent CAL before it occurs, marking a paradigm shift in colorectal surgery. Full article

This study investigates the evolving pedagogical strategies and professional identity development of two novice college English teachers in China through a semester-long classroom-based inquiry. Drawing on Norris’s Multimodal (Inter)action Analysis (MIA), it analyzes 270 min of video-recorded lessons across three instructional stages, supported by visual transcripts and pitch-intensity spectrograms. The analysis reveals each teacher’s transformation from textbook-reliant instruction to student-centered pedagogy, facilitated by multimodal strategies such as gaze, vocal pitch, gesture, and head movement. These shifts unfold across the following three evolving identity configurations: compliance, experimentation, and dialogic enactment. Rather than following a linear path, identity development is shown as a negotiated process shaped by institutional demands and classroom interactional realities. By foregrounding the multimodal enactment of self in a non-Western educational context, this study offers insights into how novice EFL teachers navigate tensions between traditional discourse norms and reform-driven pedagogical expectations, contributing to broader understandings of identity formation in global higher education. Full article

This study examines how Environmental, Social, and Governance (ESG) reporting is communicated and perceived on YouTube. A dataset of 553 relevant videos and 5060 user comments was extracted on 2 April 2025 ranging between 2014 and 2025, and sentiment, topic, and stance analyses were applied to both transcripts and comments. The majority of video content strongly endorsed ESG reporting, emphasizing themes such as transparency, regulatory compliance, and financial performance. In contrast, viewer comments revealed diverse stances, including skepticism about methodological inconsistencies, accusations of greenwashing, and concerns over politicization. Notably, statistical analysis showed minimal correlation between video sentiment and audience sentiment, suggesting that user perceptions are shaped by factors beyond the tone of the videos themselves. These findings underscore the need for more rigorous ESG frameworks, enhanced standardization, and proactive stakeholder engagement strategies. The study highlights the value of online platforms for capturing stakeholder feedback in real time, offering practical insights for organizations and policymakers seeking to strengthen ESG disclosure and communication. Full article

This paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and temporal redundancy via multiframe embedding. Watermark bits are embedded selectively in blocks with high perceptual masking using a QIM strategy, and the corresponding DCT coefficients are estimated directly from the spatial domain to reduce complexity. To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. The system outperforms several recent state-of-the-art techniques in both quality and speed, requiring no access to the original video during extraction. These results confirm the method’s viability for practical applications such as copyright protection and secure video streaming. Full article