Class imbalance poses a fundamental challenge in medical image classification, where rare pathologies are severely underrepresented in training datasets. This paper presents ADCL-DHNM (Adaptive Dynamic Contrastive Learning with Dynamic Hard Negative Mining), a novel framework that synergistically combines supervised contrastive learning with an adaptive hard negative mining strategy. Our approach introduces a class-aware contrastive loss with dynamic threshold adaptation based on training progress and class distribution, ensuring proportional representation of minority classes during feature learning. We provide theoretical analysis demonstrating that our adaptive threshold mechanism approximates optimal sampling distributions and that the proposed loss function increases gradient contributions from minority classes. Extensive experiments across four benchmark medical imaging datasets (ISIC 2019, ChestX-ray14, HAM10000, and MIMIC-CXR) demonstrate state-of-the-art performance with AUC improvements of 8.2-9.1% over cross-entropy baselines. Rigorous statistical validation (paired t-tests, effect size analysis, bootstrap confidence intervals) confirms the significance of our results (p < 0.001). Comprehensive stress testing under extreme imbalance (up to 1000:1), label noise (up to 30%), and limited data scenarios validates the robustness of our approach.
Aim: This study aimed to explore the prevalence and determinants of musculoskeletal pain (MSP) among undergraduate medical students and compare the findings across physiotherapy, medicine, and pharmacy faculties. Subject and Methods: A cross-sectional study was conducted from August 2023 to February 2024 among 252 female students at Merit University. A structured questionnaire was used, incorporating the Nordic Musculoskeletal Questionnaire (NMQ) and the Global Physical Activity Questionnaire (GPAQ), to evaluate the presence, location, and severity of MSP. Demographic data, body mass index (BMI), and study habits were also collected. Results: The prevalence of MSP was notably high, particularly in the neck and lower back regions. Female students and physiotherapy students in years beyond the first year reported significantly higher rates of pain. A positive correlation was observed between higher BMI, prolonged poor postures during lectures and study sessions, and increased MSP. However, there was no statistically significant difference in MSP prevalence between physiotherapy and other medical students overall. Conclusion: The high prevalence of musculoskeletal pain among female medical students calls for further ergonomic research and clinical evaluation. Medical schools should address MSP by improving seating arrangements and educating students on lifestyle modifications for MSP prevention.
Sustainable technology development has become a strategic priority for manufacturing firms undergoing digital transformation and facing increasing environmental pressures. Open innovation (OI), particularly inbound knowledge acquisition, plays a crucial role by enabling organizations to integrate diverse technological, scientific, market-based, and digitally mediated knowledge. However, the effectiveness of inbound OI depends on the firm's ability to absorb, analyse, and apply external information, a capability that is increasingly shaped by artificial intelligence (AI). This study investigates how four dimensions of inbound OI (external technology sourcing, university-industry collaboration, customer and market knowledge acquisition, and digital platform engagement) affect sustainable technology development in Saudi Arabian manufacturing firms, and whether AI capability strengthens these effects. Using data collected from 211 IT managers and IT experts and analysed through Smart PLS 4, the results show that all four inbound OI dimensions significantly enhance sustainable technology development. AI capability moderated the relationship between inbound OI and sustainability outcomes. These findings enrich OI theory by introducing a multidimensional conceptualization and highlight AI capability as a strategic enabler of environmental technological progress. The study offers actionable insights for managers and policymakers seeking to accelerate sustainable industrial transformation.
A major challenge in learning biology (marine biodiversity) is how to convey it contextually and relevantly, and how to utilize it effectively for the lives of the people in this region. One solution is the implementation of the integrated learning model of PjBL and Etnobameti, which is the local wisdom of the Maluku community. Based on the results of the implementation of this learning tool by fifth-semester students of the Biology Education study program, FKIP, Patimura University, the results of the syntax mastery assessment were 70.8% with very good and good criteria, only 29.2% with a score of less than or poor. The assessment of students'critical thinking skills was 87.5% with very good and good criteria, only 12.5% with less criteria. The assessment of students' innovative work (products) was 95.8% with very good criteria and only 4.2% with less criteria. The results of the correlation analysis showed a significant relationship between syntax and critical thinking with an R2 value of 0.707, or 70.9% of the syntax of the PjBL and Etnobameti learning integration model correlated with students' critical thinking, and only 29.3% with other factors.The assessment results also show a correlation between syntax and innovative work (products) with correlation values of R2 = 0.438 or 43.8% influenced by syntax while 56.2% is influenced by other factors, especially student knowledge that has been obtained from generations through the Bameti culture which is seen in the form of critical thinking intelligence in recognizing and obtaining various types of marine biota. Based on the results of the analysis, it can be seen that there is an influence of the syntax of the Etnobameti integrated PjBL model on critical thinking intelligence with a df value = 23-22 = 1 with an F value = 53.022 where the significance level is 000, < p 0.05, indicating a significant influence and also a significant influence between the syntax of the PjBL and Etnobameti integration models on = = with an F value = 17,886 with a significance level of 000 < p 0.05, indicating a significant influence between the syntax of the project based learning (PjBL) integration learning model and Etnobameti. The development of students'thinking in understanding the integrated model of project based learning (PjBL) and Etnobameti, as the local wisdom of the Maluku community in the process of learning biology on marine biodiversity material is a form of building intelligent and innovative constructivism of thinking to develop the potential of natural resources for the welfare of society in the future through the biology learning process.
This study explores the socio-cognitive predictors of academic writing proficiency and assesses the impact of a Self-Regulated Strategy Development (SRSD) intervention among multilingual senior high school students in the Philippines. Utilizing a convergent mixed-methods design, the study found that socioeconomic status, language proficiency, parental involvement, and access to academic resources significantly predicted writing outcomes (adjusted R2 = 0.46). Pre-intervention assessments revealed persistent challenges in citation, grammatical accuracy, and academic register. Following a six-week SRSD-based intervention, students demonstrated statistically significant gains across all writing domains (p < .001, d = 1.04). Qualitative data indicated enhanced metacognitive awareness and confidence in managing academic discourse. These findings support the efficacy of structured, strategy-focused instruction in mitigating writing inequities in under-resourced ESL settings and affirm SRSD as a viable pedagogical model for fostering writer agency and academic literacy (Harris, 2022; Zhang & Hyland, 2023).
