Search Results (426)

This study examines the factors that motivate viewers to financially support streamers on the Twitch digital platform. It proposes a conceptual framework that combines the uses and gratifications theory (UGT) with Michel Foucault’s concept of the practice of freedom (PF). Using a cross-sectional quantitative survey of 560 Portuguese Twitch users, the model investigates how three core constructs from UGT—entertainment, socialization, and informativeness—affect the intention to donate, with PF acting as a mediating variable. Structural equation modeling confirms that all three UGT-based motivations significantly influence donation intentions, with socialization exhibiting the strongest mediated effect through PF. The findings reveal that Twitch donations go beyond mere instrumental or playful actions; they serve as performative expressions of identity, autonomy, and ethical subjectivity. By framing PF as a link between interpersonal engagement and financial support, this study provides a contribution to media motivation research. The theoretical integration enhances our understanding of pro-social behavior in live streaming environments, challenging simplistic, transactional interpretations of viewer contributions vis-à-vis more political ones and the desire to freely dispose of what is ours to give. Additionally, this study may lay the groundwork for future inquiries into how ethical self-formation is intertwined with monetized online participation, offering useful insights for academics, platform designers, and content creators seeking to promote meaningful digital interactions. Full article

Background: With the ongoing development of game-changing technologies, assessing healthcare provider burden is desirable. This requires developing and evaluating subjective outcome measures, but there is no single scale that measures this burden. We developed a measure of quality of life (QOL) to address this, focusing on medical doctors (MDs). Methods: Based on Japan’s national statistical distribution of MDs in Japan, we qualitatively interviewed twenty MDs to identify factors that influenced their QOL and another eight MDs to verify the appropriateness and interpretability of the questions. Validity and reliability were evaluated and verified in a quantitative survey of 374 MDs to finalize the questionnaire. Results: Based on our initial research and interviews, we derived nine dimensions and developed the work-related QOL questionnaire for MDs (WQMD-9) accordingly. Correlation coefficients between questionnaire items were 0.3–0.7 and Cronbach’s α was 0.897, confirming the validity and reliability of the questionnaire. Conclusions: The WQMD-9 is an original profile-type scale with nine dimensions and five levels. We expect that as new technologies develop, evaluations of the associated medical treatment will involve measuring the QOL of not only patients but also MDs, and the WQMD-9 will facilitate this process. Full article

Robust statistical analysis is essential for advancing evidence-based nutrition research, particularly when investigating the complex relationships between dietary exposure and health outcomes. Multiple regression is a widely used analytical technique in nutrition studies due to its ability to control for confounding variables and assess multiple predictors simultaneously. However, the reliability, validity, and generalizability of findings from regression analyses depend heavily on having an appropriate sample size. Despite its importance, many published nutrition studies do not include formal sample size justifications or power calculations, leading to a high risk of Type II errors and reduced interpretability of results. This methodological review examines three commonly used approaches to sample size determination in multiple regression analysis: the rule of thumb, variance explained (R²) method, and beta weights approach. Using a consistent hypothetical example, rather than empirical data, this paper illustrates how sample size recommendations can differ depending on the selected approach, highlighting the advantages, assumptions, and limitations of each. This review is intended as an educational resource to support methodological planning for applied researchers rather than to provide new empirical findings. The aim is to equip nutrition researchers with practical tools to optimize sample size decisions based on their study design, research objectives, and desired power. The rule of thumb offers a simple and conservative starting point, while the R² method ties sample size to anticipated model performance. The beta weights approach allows for more granular planning based on the smallest effect of interest, offering the highest precision but requiring more detailed assumptions. By encouraging more rigorous and transparent sample size planning, this paper contributes to improving the reproducibility and interpretability of quantitative nutrition research. Full article

This work probes the possibility of controlling the morphology of silver crystals through inoculation of trace-level metallic species, building on an industrial-scale cooling process. The obtained crystals are analyzed via X-ray tomography (XRT), dynamic picture analysis, and scanning electron microscopy (SEM). The results reveal assemblages composed of octahedral crystals and triangular platelets. X-ray tomography yields pore size distributions that correlate with Ag% composition. Out of several trace metals tested, cadmium was found to yield a greater number of octahedral morphologies with pronounced twinning, contributing to a fibrous structure. This behavior is consistent with the energetic preference of cadmium atoms to integrate on Ag (111) planes and the limitation of twinning to the (111) planes in FCC metals. Faceting of the interiors of the triangular facets of octahedral crystals is noted in all SEM images of acid-washed samples. These physical features are interpreted as a product of crystal growth and not selective acid etching. The generation of octahedral silver crystals from a molten melt and the presence of faceting are research firsts, such crystal morphologies being previously generated only from aqueous chemical reduction systems. Adding traces of cadmium to primary lead melts is promising for producing silver nanocrystals with desired morphologies. Full article

The utilization of machine learning (ML) has brought more opportunities for the discovery of high-performance materials with specific properties to replace traditional engineering materials. The glass transition temperature (T_g) is a crucial characteristic of polyimide (PI). But small datasets can only partially reveal structural information and decrease the ability of the models to learn from the observed data. In this investigation, a dataset comprising 1261 PIs was assembled. A quantitative structure–property relationship targeting T_g was constructed using nine regression algorithms, with the Categorical Boosting demonstrating the highest accuracy, achieving a coefficient of determination of 0.895 for the test set. SHapley Additive exPlanations analysis identified the NumRotatableBonds descriptor had a significantly negative impact on T_g. Finally, all-atom molecular dynamics (MD) simulations calculated eight PI structures to verify the accuracy of the prediction model. The ML prediction was consistent with the MD simulation, with the lowest prediction deviation of approximately 6.75%, but the time and resource consumption were tremendously reduced. These findings emphasize the significance of utilizing extensive datasets for model training. This available and interpretable ML framework provides impressive acceleration over the MD simulation and serves as a reference for the structural design of PI with the desired T_g in the future. Full article

Background: Rigorous evaluation of vacuum blood collection tubes is essential to ensure the reliability of laboratory results. Methods: In this study, we compared the serum separator tube V-Tube™ (V-Tube SST), the quick-clotting serum separator tube VQ-Tube™ (VQ-Tube SST), and the K₂EDTA V-Tube™ (V-Tube K₂EDTA) manufactured by AB Medical (Seoul, Republic of Korea), with their respective counterparts from Becton Dickinson (BD, Franklin Lakes, NJ, USA): BD Vacutainer^® SST™ II Advance Tube (BD SST) and BD Vacutainer^® K₂EDTA 5.4 mg Tube (BD K₂EDTA). The evaluation encompassed 61 measurands across the fields of chemistry, immunology, and hematology, and incorporated a stability assessment for the VQ-Tube SST. Results: The V-Tube SST, VQ-Tube SST, and V-Tube K₂EDTA demonstrated comparable analytical performance to the BD tubes for the majority of measurands. However, glucose, lactate dehydrogenase, mean corpuscular volume, and mean corpuscular hemoglobin concentration indicated clinically significant differences according to the desirable biological variation database (Ricos). Conclusions: These findings suggest that, while the V-tube and VQ-tube SST generally serve as alternatives to BD tubes, caution should be taken when interpreting results for specific measurands that demonstrated clinically significant discrepancies. Full article

Bicycle use has been increasing in many countries for active, sustainable transportation and recreation. Bicycling can benefit an individual’s mental and physical health and contribute to a community’s well-being and desirability, and it is more environmentally sustainable than automobiles. Nonprofit organizations lead bicycle advocacy efforts in the USA, both for bicycling as recreation and as part of local transportation systems. Outride is one of the larger advocacy organizations, and it sponsors a unique grant system targeting grassroots bicycling organizations dedicated to increasing bicycling. Using the Bicycle Community Development Framework (BCDF) as a lens, this study aims to evaluate Outride’s efforts through an interpretative phenomenological approach (IPA) using semi-structured interviews to gather data regarding grant recipients’ experiences using Outride funds. Findings suggest fund recipients are increasing bicycling through programs and infrastructure development, but with more intentionality, could better support building bicycle communities. Regarding the BCDF, the recipients strongly promoted education, engineering, and equity & accessibility while fostering a sense of community, belonging, and empowerment in their participants. Full article

Over the last three decades, composite structures have become increasingly more common in everyday life, such as in wind turbines as part of the solution to produce clean energy, and their use in the aerospace industry due to their advantages over conventional materials. Most of these advantages are dependent upon the reliability and quality of the manufacturing process to ensure that there are no defects/faults or imperfections during manufacturing. Thus, it is critical to monitor the enclosed environment of moulds during fabrication in real time. This need has caused many researchers—past and present—to create or apply many sensing technologies to achieve real-time monitoring of the manufacturing processes of composite structures to ensure that the structures can meet their requirements. A consequence of these research activities is the myriad of sensing schemes, (for example, optical, electrical, piezo, and nanomaterial schemes and the use of digital twins) available to consider, and the investigations all of them have both strengths and weaknesses for a given application, with no apparent option having a distinct advantage. This review reveals that the best possible sensing solution depends upon a large set of parameters, the geometry of the composite structure, the required specification, and budget limits, to name a few. Furthermore, challenges remain for researchers trying to find solutions, such as a sensing scheme that can directly detect wrinkles/waviness during the laying-up procedure, real-time detection of the resin flow front throughout the mould, and the monitoring of the resin curing spatially, all at a spatial resolution of ~1 cm with the required sensitivity along with the need to obtain the true interpretation of the real-time data. This review offers signposts through the variety of sensing options, with their advantages and failings, to readers from the composite and sensing community to aid in making an informed decision on the possible sensing approaches to help them meet their composite structure’s desired function and tolerances, and the challenges that remain. Full article

The quality of children’s early childhood education (ECE) experiences significantly impacts their long-term outcomes and wellbeing. While extensive research has explored quality from the perspectives of adult stakeholders, including educators and authorities, there remains a paucity of studies prioritizing the viewpoint of children, the main beneficiaries of ECE. This study sought to address this gap by investigating children’s preschool experiences at an Australian inner-city preschool center. Using child-friendly interview techniques, researchers engaged 32 children aged 3–4 years in discussions about their likes, dislikes, and desired changes in their preschool settings. Open-ended questions such as “What do you love about preschool?” and “What do you think makes a good preschool?” were used to encourage reflection and storytelling. To complement verbal responses, children were invited to illustrate their thoughts through drawings, offering a visual dimension to their perspectives. Deductive thematic analysis identified eight themes within the dimensions of structural and process quality. The findings highlight the unique and insightful ways young children interpret their experiences, shedding light on aspects of preschool life they value most. By amplifying children’s voices, this study highlights the importance of integrating their perspectives into the design and evaluation of ECE environments, promoting practices that better align with their needs and support their wellbeing. Full article

Early modern theologians often cast female curiosity as both a moral flaw and an epistemic transgression. Aware of this suspicion, Teresa of Ávila professed to have renounced such dangerous impulses in her youth. Yet the persistent presence of curiosity in her writings suggests a strategic redeployment—one that fosters attentiveness and subtly renegotiates ecclesiastical authority as she actively advances reform within the Carmelite order. Through life-writing and scriptural exegesis, Teresa cultivates a disciplined appetite for knowledge: an appetite that outwardly conforms to, yet quietly subverts, doctrinal anxieties surrounding women’s intellectual desires. Her use of curiosidad moves fluidly between sacred and secular registers—sometimes connoting superficial fascination, at other times signaling a deeper, interior restlessness. Resisting reductive interpretation, Teresa reveals a sophisticated and self-aware engagement with a disposition both morally ambiguous and intellectually generative. The same culture that once feared her intellect would ultimately aestheticize it. After her death, Teresa’s relics were fragmented and displayed in Philip II’s Wunderkammer, transforming her once-condemned curiosidad into curiositas, an imperial collectible. Reading Teresa alongside her posthumous interpreters—Fray Luis de León and Miguel de Cervantes—this essay explores how her radical epistemological ambition reverberated through Spanish intellectual culture. Spanning this cultural arc—from sin to spectacle, from forbidden desire to sanctified display—Teresa emerges as a masterful theorist and activist reformer of spiritual authority. In these expansive roles, she reveals the immense and often contradictory power that curiosity wielded in the early modern world. Full article

This study presents a systematic method for mix design for optimizing the aggregate proportions in concrete, aiming to minimize paste volume while ensuring adequate workability. Based on a binary paste–aggregate system model, the method refines the calculation of the aggregate packing density by excluding fine particles smaller than 75 μm and incorporating inter-particle interactions across multiple size fractions. A modified approach for calculating the aggregate’s specific surface area is introduced, which accounts for both intra-fraction particle size variation and particle morphology through image-based shape coefficients. Inter-particle spacing is identified as a key control parameter of concrete flowability. Using this criterion, an optimization strategy is developed to determine the ideal aggregate composition that achieves the required spacing with the least amount of paste. Experimental validation confirms that the model reliably predicts paste demand while maintaining desired workability and compressive strength. This physics-based, interpretable approach offers a practical alternative to data-intensive machine learning models and contributes to more sustainable and efficient concrete mix design. Full article

Artificial intelligence has brought tremendous convenience to human life in various aspects. However, during its application, there are still instances where AI fails to comprehend certain problems or cannot achieve flawless execution, necessitating more cautious and thoughtful usage. With the advancements in EEG signal processing technology, its integration with AI has become increasingly close. This idea of interpreting electroencephalogram (EEG) signals illustrates researchers’ desire to explore the deeper relationship between AI and human thought, making human-like thinking a new direction for AI development. Currently, AI faces several core challenges: it struggles to adapt effectively when interacting with an uncertain and unpredictable world. Additionally, the trend of increasing model parameters to enhance accuracy has reached its limits and cannot continue indefinitely. Therefore, this paper proposes revisiting the history of AI development from the perspective of “anthropomorphic computing”, primarily analyzing existing AI technologies that incorporate structures or concepts resembling human brain thinking. Furthermore, regarding the future of AI, we will examine its emerging trends and introduce the concept of “Cyber Brain Intelligence”—a human-like AI system that simulates human thought processes and generates virtual EEG signals. Full article

Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow learning models often fall short in detecting sophisticated fraud patterns. This study addresses the challenge of accurately identifying fraudulent financial activities, especially in highly imbalanced datasets where fraud instances are rare and often masked by legitimate behavior. The existing models also lack interpretability, limiting their utility in regulated financial environments. Experiments were conducted on three benchmark datasets: IEEE-CIS Fraud Detection, European Credit Card Transactions, and PaySim Mobile Money Simulation, each representing diverse transaction behaviors and data distributions. The proposed methodology integrates a transformer-based encoder, multi-teacher knowledge distillation, and a symbolic belief–desire–intention (BDI) reasoning layer to combine deep feature extraction with interpretable decision making. The novelty of this work lies in the incorporation of cognitive symbolic reasoning into a high-performance learning architecture for fraud detection. The performance was assessed using key metrics, including the F1-score, AUC, precision, recall, inference time, and model size. Results show that the proposed transformer–BDI model outperformed traditional and state-of-the-art baselines across all datasets, achieving improved fraud detection accuracy and interpretability while remaining computationally efficient for real-time deployment. Full article

Testing is a part of education around the world; however, there are concerns that consequences of testing is underexplored within current educational scholarship. Moreover, usability studies are rare within education. One aim of the present study was to explore the usability of a mathematics problem-solving test called the Problem Solving Measures–Computer-Adaptive Test (PSM-CAT) designed for grades six to eight students (ages 11–14). The second aim of this mixed-methods research was to unpack consequences of testing validity evidence related to the results and test interpretations, leveraging the voices of participants. A purposeful, representative sample of over 1000 students from rural, suburban, and urban districts across the USA were administered PSM-CAT followed by a survey. Approximately 100 of those students were interviewed following test administration. Findings indicated that (1) participants engaged in the PSM-CAT as desired and found it highly usable (e.g., most respondents were able to use and find the calculator and several students commented that they engaged with the test as desired) and (2) the benefits from testing largely outweighed any negative outcomes (e.g., 92% of students interviewed had positive attitudes towards the testing experiences), which in turn supports consequences from testing validity evidence for PSM-CAT. This study provides an example of a usability study for educational testing and builds upon previous calls for greater consequences of testing research. Full article

This study, employing an interpretative qualitative method, explored the childhood experiences of 34 gifted adults aged 26–50, aiming to understand how these early encounters shaped their lives. Themes emerged from semi-structured interviews, encompassing the gifted adult today, childhood experiences, ‘my second childhood’, and giftedness from a mature perspective. The majority expressed a connection with like-minded individuals and a desire to work with those who stimulate creativity and learning. While pull-out programs enriched knowledge and skills, the label “gifted” often led to social and emotional challenges, particularly in regular school settings. The participants highlighted supportive family environments and unique relationships with parents and grandparents. Many believed their talents, often rooted in genetics or upbringing, extended beyond measurable tests. Notably, respondents expressed a sense of unfulfilled giftedness in adulthood. The findings contribute to understanding giftedness theoretically and provide practical insights for education ministries, educators, and families in designing programs for gifted individuals. Full article