mdpi-ai/citelens huggingface dataset:
Frugal innovation in the business environment: a literature review and future perspectives
Field: AI

Introduction: This research aims to explore the growing field of frugal innovation within the business environment, particularly its intersection with sustainability and artificial intelligence.Methods: Through a comprehensive literature review, the study analyzes key research trends and methodologies from 420 scholarly articles published between 2012 and August 2024. A bibliometric review traces the evolution of frugal innovation, while a content analysis provides insights into its practical applications across various industries, especially in resource-constrained settings.Results: The findings highlight the significant role of frugal innovation in addressing global challenges, such as reducing environmental impact and promoting social inclusion, especially through the adoption of cleaner technologies and socially responsible business practices. The study also emphasizes the transformative potential of AI in enhancing the scalability and efficiency of frugal solutions.Discussion: This research contributes to the ongoing conversation on sustainable development by identifying knowledge gaps and proposing future strategies for leveraging frugal innovation to drive inclusive growth. The implications of this research are valuable for academics, practitioners, and policymakers aiming to foster sustainable innovation in diverse socio-economic contexts.
Research on the driving mechanism of tourists’ ecological protection behavior in intangible cultural heritage sites
Field: PSYCHOLOGY

Despite the increasing focus on intangible cultural heritage tourism, there is a lack of research on the ecological protection behaviors of tourists in these contexts. With UNESCO’s continuous refinement of the World Heritage system, intangible cultural heritage has gradually become a focal point for tourism development and protection. While such tourism can promote the preservation and transmission of heritage, it also introduces ecological environmental issues that need to be addressed. Therefore, exploring the driving mechanisms of tourists’ ecological protection behavior holds significant practical value. Based on the Theory of Planned Behavior (TPB), this study constructs a driving model of tourists’ ecological protection behavior. It examines the influence of behavioral attitude, subjective norms, perceived behavioral control, and personal norms on tourists’ willingness to engage in ecological protection. By distributing questionnaires both offline and online, we analyzed data from 312 valid responses. The results indicate that all four factors have a significant positive impact on tourists’ willingness to engage in ecological protection behavior. Among these factors, personal norms and behavioral attitude have a relatively larger influence. The findings provide valuable references for intangible cultural heritage sites in China and regions with similar cultural and tourism dynamics.
Empowering young athletes: the influence of autonomy-supportive coaching on resilience, optimism, and development
Field: PSYCHOLOGY

Introduction: The present study investigates how autonomy-supportive coaching style influences youth athlete development through psychological resilience and dispositional optimism. Despite growing interest in factors that contribute to athlete development, gaps remain in understanding how coaching approaches interact with psychological traits to foster youth athletes’ growth. This study addresses these gaps by proposing a serial mediation model in which autonomy-supportive coaching indirectly enhances athlete development through resilience and optimism.Methods: Data were collected from 325 youth athletes and their coaches across training facilities and schools in China, and analyzed using structural equation modeling in SmartPLS.Results: Results indicate that autonomy-supportive coaching style significantly increases psychological resilience, which in turn boosts dispositional optimism, positively impacting athlete development. Both resilience and optimism serially mediate the link between coaching style and athlete growth.Discussion: These findings emphasize the importance of autonomy-supportive coaching in creating psychologically supportive environments that foster resilience, optimism, and developmental pathways in youth sports.
A Novel Conflict Deduction Algorithm Based on Contradiction Separation Inference Rule
Field: AI

Automated reasoning, a significant field within artificial intelligence, has attracted increased attention in recent years due to the rising demand for trustworthy AI. Binary resolution, among other inference rules, is crucial in automated reasoning of first-order logic, including the new conflict resolution method. Conflict resolution processes only two clauses in each deduction step and eliminates a complementary pairs of literals from input clauses. This paper proposes a contradiction separation conflict deduction (CSCD) method based on the contradiction separation rule to address these limitations. This novel resolution methodology, together with its automated reasoning theory and method, handles several clauses in each deduction step to seek for conflicts and generates learnt clauses through synergized deduction. Thus, the approach improves deduction by detecting conflicts more effectively, especially with lengthier input clauses. CSCD and conflict resolution are analyzed in detail, then how to create a practical CSCD algorithm and its implementation is summarized. We tested the CSCD algorithm to solve the CASC-26 problems and also applied it to the current leading ATP system (Eprover). Experimental results show that the CSCD deduction approach improves reasoning capability of conflict deduction method. Additionally, the Eprover with the proposed CSCD algorithm improves its performance and has solved various problems with a rating of 1 from the benchmark database TPTP.
The attractiveness of the teaching profession: a integrative literature review
Field: EDUCATION

The widespread shortage of teachers highlights the urgent need to examine the factors influencing the attractiveness of the teaching profession. This issue is driven by high rates of early-career attrition, an ageing workforce, and a decline in candidates entering teacher education programs. Understanding the factors that make the profession appealing—or unappealing—has become essential for ensuring educational quality and equity. An integrative literature review was conducted to identify the key themes related to the attractiveness of the teaching profession, synthesizing evidence from multiple studies and highlighting research gaps. Findings reveal that teaching still attracts candidates driven by intrinsic motivations and social utility. However, external factors such as low salaries, challenging working conditions, and limited career progression remain significant deterrents. The social image of teaching, shaped by media and community perceptions, also influences career choices. The intersection of demographic shifts and educational policy changes highlights the complexity of addressing teacher shortages. Despite increased attention from policymakers, significant gaps remain, particularly in relation to interventions that reduce early-career attrition and support teacher retention. Future research should explore targeted strategies to support early-career teachers and examine the socio-economic factors that influence career decisions. Addressing these issues is critical to developing sustainable policies that enhance the attractiveness of the teaching profession and promote educational equity.
Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm
Field: AI

Background: The Department of Rehabilitation Medicine is key to improving patients’ quality of life. Driven by chronic diseases and an aging population, there is a need to enhance the efficiency and resource allocation of outpatient facilities. This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.Methods: Data were collected from 38 Chinese institutions, including 4,244 patients visiting outpatient rehabilitation clinics. Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. The steps included handling missing values, data normalization, and encoding conversion. The data were divided into 80% training and 20% test sets using the Scikit-learn library to ensure model independence and prevent overfitting. Performance comparisons among XGBoost, random forest, and logistic regression were conducted using metrics, including accuracy and receiver operating characteristic (ROC) curves. The imbalanced learning library’s SMOTE technique was used to address the sample imbalance during model training. The model was optimized using a confusion matrix and feature importance analysis, and partial dependence plots (PDP) were used to analyze the key influencing factors.Results: XGBoost achieved the highest overall accuracy of 80.21% with high precision and recall in Category 1. random forest showed a similar overall accuracy. Logistic Regression had a significantly lower accuracy, indicating difficulties with nonlinear data. The key influencing factors identified include distance to medical institutions, arrival time, length of hospital stay, and specific diseases, such as cardiovascular, pulmonary, oncological, and orthopedic conditions. The tiered diagnosis and treatment tool effectively helped doctors assess patients’ conditions and recommend suitable medical institutions based on rehabilitation grading.Conclusion: This study confirmed that ensemble learning methods, particularly XGBoost, outperform single models in classification tasks involving complex datasets. Addressing class imbalance and enhancing feature engineering can further improve model performance. Understanding patient preferences and the factors influencing medical institution selection can guide healthcare policies to optimize resource allocation, improve service quality, and enhance patient satisfaction. Tiered diagnosis and treatment tools play a crucial role in helping doctors evaluate patient conditions and make informed recommendations for appropriate medical care.
Application value of 18F-FDG PET/CT in soft tissue metastasis of intrahepatic cholangiocarcinoma: a case report and literature review
Field: ONCOLOGY

Intrahepatic cholangiocarcinoma (ICC)originates from the epithelial cells of the intrahepatic bile ducts, with insidious onset and strong invasiveness, and most of the cases are found in the advanced stage, with extremely poor prognosis. In advanced stages, distant metastases to the lungs, bones, and brain are common, but distant soft tissue (subcutaneous and skeletal muscle) and breast metastases are rare, and simultaneous metastases to all three rare sites had not been reported. We report a 69-year-old woman with right upper abdominal pain who underwent a plain and enhanced CT scan of the upper abdomen, which revealed an intrahepatic space-occupying lesion, as well as subcutaneous and peritoneal nodules in the abdomen. To further evaluate the presence of other metastases, an 18F-FDG PET/CT scan was performed, which showed abnormal FDG uptake in the liver, peritoneum, left upper femur, right breast, subcutaneous tissues of the thoracic and abdominal regions, and skeletal muscle, while the corresponding CT densities of part of the skeletal muscle and the left upper femur did not show any significant abnormality. Pathologic confirmation of ICC with multiple metastases was obtained by puncture biopsy of the liver and subcutaneous nodes. This case demonstrates the advantages of 18F-FDG PET/CT in comprehensively evaluating systemic metastasis of ICC and detecting occult metastases, which is of great significance in its clinical diagnosis and staging.
The effects of physical activity on social physique anxiety in college students—the mediating and moderating role of mental toughness and negative physical self
Field: PSYCHOLOGY

To examine the effects of physical activity on college students' social physique anxiety and the mediating and moderating roles of negative physical self and mental toughness in it, and to provide empirical evidence that physical activity improves college students' social physique anxiety. Stratified whole cluster convenience sampling was used to survey 1177 university students, 53.8% male and 46.2% female, with a mean age of (19.12 ± 1.21) years. Mediated and moderated effects were analysed using SPSS 26.0 and AMOS 28.0. (1) Physical activity negatively predicted social physique anxiety (2) Negative physical self and mental toughness (individual power) played a significant partial mediating role between physical activity and social physique anxiety, with mediating effects accounting for 40.09% and 27.11% of the total effect, respectively; (3) The R2 change in the interaction term of physical activity and family support in mental toughness (supporting force) reached a significant level, and family support played a significant negative moderating role between physical activity and social physique anxiety, whereas the interaction term of interpersonal assistance and physical activity was not significant and could not moderate the interrelationship between physical activity and social physique anxiety. Physical activity affects college students' levels of social physique anxiety through negative physical self and mental toughness (individual power); the effect of physical activity on social physique anxiety is negatively moderated by the family support dimension of mental toughness (supporting force).
Supporting a state in developing a working theory of improvement for promoting equity in science education
Field: EDUCATION

Introduction: This study was undertaken to explore the potential of developing a working theory of improvement for creating a more equitable system of science education at the level of a US state. We ask: How can tools from a long-term research-practice partnership support a state team in initiating improvement research toward promoting a more equitable system of science education?Methods: This design study took place in winter 2024 in a single state. External partners supported leaders of a single state in the US Northeast to support a process of articulating aims, specifying primary and secondary drivers, and identifying change strategies to promote a more equitable system of science education in the state, grounded in the vision of A Framework for K-12 Science Education (National Research Council, 2012). In this paper, we rely on descriptive analyses of joint meetings and a focus group with state leaders describe the tools supporting the process of development, the team’s use of the tools to generate an early draft of the Driver Diagram, and issues surfaced while developing it with a team of interest holders in the state.Results: Two meanings of equity emerged as significant within the series of meetings: that of the importance of universal access to professional learning and the importance of students having opportunities to experience culturally relevant instruction. The issues surfaced highlighted the need for infrastructures for professional learning to reach a diverse group of interest holders in science, including teachers, school leaders, and district leaders across the state. They also saw curriculum materials that connect to students’ everyday lives and community priorities as key drivers for equitable change in the system, around which professional learning activities should be organized. The team also surfaced several policy changes needed to implement change strategies, only some of which team members felt they had some authority.Discussion: Where past researchers have observed that equity can disappear as a focus during implementation of reforms, this study found that developing an aim statement and driver diagram helped energize and refocus a team’s implementation efforts geared toward a vision for science teaching and learning that is focused on ensuring all students can engage in meaningful science learning that is culturally and locally relevant to them.
Factors influencing the implementation of a teacher professional development program to improve teaching quality
Field: EDUCATION

In this study, we examined why a Teacher Professional Development (TPD) program, designed to support teachers in using students’ perceptions of teaching quality (SPTQ) data, faced significant implementation challenges in 17 secondary schools in Chile. Despite voluntary participation and initial interest, 15 of the 17 schools dropped out within 2–3 months of starting the program. Through 12 semi-structured interviews with professional learning community coordinators from nine schools, we investigated four key attributes of the TPD program to understand implementation challenges: its added value, compatibility, clarity, and tolerance. While coordinators valued several aspects of the program (including its structured manual, evidence-based teaching strategies, and integration of SPTQ data) significant implementation barriers emerged. Time constraints, lack of technological infrastructure, and insufficient organizational routines made the implementation of the TPD program too burdensome for most schools. We discuss how compatibility between TPD programs and schools’ existing structures and routines acts as a critical bottleneck that can prevent successful implementation, even when participants see value in the program. This study provides important insights into the conditions necessary for successful TPD implementation in a global south country.
A more positive mindset context is associated with better student outcomes in STEM, particularly for traditional-age students
Field: EDUCATION

Students' beliefs about their ability to grow in STEM disciplines have been linked to better course outcomes. However, such mindset beliefs are subject to the environmental cues projected by the instructor in the classroom, which we refer to as the mindset context. Recent meta-analyses indicated heterogeneity in the benefits of student mindset interventions, which the classroom environment may shape. In this work, we use structural equation modeling (SEM) to investigate the mindset context and its impact on students’ affect and performance in STEM courses, particularly for students from marginalized groups who may be disproportionately affected by these factors. We collected student perceptions of their instructors’ universality beliefs about student abilities (all people or only some people can reach excellence in STEM), students’ growth beliefs, sense of belonging (as measured by peer support, faculty support, and classroom comfort) and course grades. The sample was collected from courses in a STEM college within a demographically diverse, moderately selective institution in the Southern United States (N = 625). We found that student perceptions of the mindset context did not directly predict course grades, but ACT scores did (standardized exams used for college entry in the USA). However, SEM analysis revealed that when students perceived instructors to believe only some students can succeed in STEM (endorse more non-universal beliefs), they reported fewer growth beliefs about their abilities in STEM. This led to less classroom comfort in contributing to class discussions, ultimately lowering STEM grades. Multigroup moderation analysis showed no differences in paths based on race, gender, and generational status. However, the mindset context impacted traditional students’ (age of 18–22) growth beliefs to a greater extent than non-traditional students (> 22 years old). Additionally, classroom comfort significantly predicted grades for traditional students but not for non-traditional students. Our finding suggests that when students perceive the mindset context more positively, their outcomes improve, especially for traditional students who may be more sensitive to classroom cues. Thus, mindset interventions for faculty (coupled with student interventions) may also be beneficial to supporting student success. Additionally, we recommend improving student content preparation to enhance foundational knowledge, considering that indicators of prior preparation (ACT scores) play a more direct role in predicting student grades.
Analysis of two pedagogical approaches to foster discipline integrations in an educational data mining class using communities of practice
Field: EDUCATION

This paper describes research into two pedagogical approaches to foster transdisciplinarity in a graduate engineering course that involves education and computer science. Leveraging the Communities of Practice framework, we examine how students majoring in computer science can integrate new knowledge from education and computer science to engage in an educational data mining project. The first course iteration sought to connect students from education and computer science disciplines through a blend of problem-based learning and traditional lectures. The second course iteration involved computer science students only, but included two instructors, one from computer science and the other from education. To evaluate these approaches, we conducted multiple student interviews and classroom observations. We found that pursuing interdisciplinary through student brokers had a localized student impact on discipline integration without creating an entire class transdisciplinary environment, proving particularly effective for students with backgrounds outside of computer science. However, it fell short of achieving an overarching integration of education knowledge across the entire class. In contrast, the co-teaching approach influenced class dynamics significantly as instructors honed their brokerage skills and introduced crucial components to the multidisciplinary toolkit. Students reinterpreted these elements within the context of their projects, leading to a deeper integration of education and computer science disciplines. However, while students did acquire more knowledge from both disciplines, they did not always achieve a comprehensive practical understanding of the class outcomes. Findings suggest that differences in instructional design can significantly impact how interdisciplinary integration forms within a class. Using CoP, we identified various models to foster disciplinary integration. The two pedagogical approaches used—student brokers and co-instructors—achieved some disciplinary integration, highlighting multidisciplinary, interdisciplinary, and transdisciplinary integration. Engaging in projects with multidisciplinary teams allows students to interact one-on-one while working on real projects, enabling them to negotiate their participation with peers and resulting in a deeper integration of the involved disciplines. This paper discusses the merits and the drawbacks of employing both approaches to build an interdisciplinary class.