Self-Efficacy and Push-Pull Factors in International Student Mobility: A Study of Chinese Students’ Decision to Study in Malaysia by Meng Na, Mazzlida Mat Deli, Ummu Ajirah Abdul Rauf

“…Using a cross-sectional, quantitative design, data were collected from a stratified sample of 377 Chinese students, enabling robust analysis of psychological and contextual factors. …”
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Applying Neutrosophic Natural Language Processing to Analyze Complex Phenomena in Interdisciplinary Contexts by Diego Fernando Coka Flores, Ignacio Fernando Barcos Arias, María Elena Infante Miranda, Omar Mar Cornelio

“…This approach becomes particularly relevant in an increasingly digitalized world, where human-machine interaction requires a deeper understanding of linguistic and contextual nuances. Despite advances in conventional NLP, many existing methodologies lack tools to effectively manage undefined or contradictory elements present in real data. …”
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Hybrid boosted attention-based LightGBM framework for enhanced credit risk assessment in digital finance by Chengwei Ying, Anlu Shi, Xiongyi Li

“…The HBA-LGBM model introduces four key innovations: (1) a multi-stage feature selection mechanism that dynamically filters key borrower attributes; (2) an attention-based feature enhancement layer, which prioritizes critical financial risk factors dynamically based on contextual importance; (3) a hybrid boosting strategy, integrating LightGBM with an adaptive neural network, enabling the model to capture complex borrower behavior and non-linear credit risk patterns; and (4) an advanced imbalanced learning strategy, combining synthetic data augmentation and cost-sensitive learning to mitigate class imbalance and enhance minority class predictions. …”
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A neuro-symbolic AI approach for translating children’s stories from English to Tamil with emotional paraphrasing by P. Matan, P. Velvizhy

“…Our approach uses a neuro-symbolic AI framework, specifically integrating the T5 transformer and few-shot learning, allowing effective model adaptation with minimal data. …”
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Religious and Cultural Moderation in Responding to the Challenges of Globalisation in Local Communities by Baktiar Leu

“…through contemporary arts and culture, and integrating religious moderation values ??into regional development policies. …”
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Artificial intelligence in coronary angiography: benchmarking the diagnostic accuracy of ChatGPT-4o against interventional cardiologists by John Michael Hoppe, Christopher Stremmel, Antonia Kellnar, David Esser, Kathrin Diegruber

“…Future developments should focus on enhancing AI capabilities for analysing complex anatomical structures and integrating dynamic imaging data to augment clinical utility.…”
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Do Responsible Consumption and Production and Climate Policies Influence an Individual’s Environmentally Oriented Consumption and Anti-consumption? by Felipe Roberto da Silva, Felipe Gerhard

“…Conclusion: this research contributes to the literature on sustainability by quantitatively integrating both contextual levels – an approach that is still uncommon – and by demonstrating how individual perceptions and broader political and cultural environments jointly shape sustainable consumer behavior. …”
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Comparative Study of Hybrid Deep Learning Models for Kannada Sign Language Recognition by Gurusiddappa Hugar, Ramesh M. Kagalkar, Abhijit Das

“…The proposed framework demonstrates superior performance with 97.6% training accuracy, 96.75% validation accuracy, and 81% testing accuracy on unseen data—outperforming conventional CNN-LSTM (46%) and HKP-LSTM (71%) baselines. …”
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SLGMA-UNet: Comprehensive Feature Aggregation With Context-Sensitive Attention for Medical Image Segmentation by Xinghuo Ye, Na Wang

“…Existing segmentation methods encounter challenges such as managing size variations, interpreting contextual relationships, and integrating multi-source data. …”
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Designing Psychological Treatments for Scalability: The PREMIUM Approach. by Sukumar Vellakkal, Sukumar Vellakkal, Vikram Patel

“…<h4>Conclusions</h4>Integrating global evidence with local knowledge and practices are complementary and feasible goals to contribute to the development of contextually appropriate and feasible EPT in resource poor country settings. …”
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Exploring social interaction patterns and drivers in VGI communities using a custom geovisual analytics tool by Guiming Zhang, Wei Luo, Mingguang Wu, Liangfei Ye

“…Social interactions among data contributors are essential to the success of many VGI (volunteered geographic information) projects, and the patterns of such interactions are often shaped by geographies in which the contributors are situated. …”
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Joint Entity–Relation Extraction for Knowledge Graph Construction in Marine Ranching Equipment by Du Chen, Zhiwu Gao, Sirui Li, Xuruixue Guo, Yaqi Wu, Haiyu Zhang, Delin Zhang

“…This study proposes the first knowledge graph (KG) framework tailored for marine ranching equipment, integrating hybrid ontology design, joint entity–relation extraction, and graph-based knowledge storage: (1) The limitations in existing KG are obtained through targeted questionnaires for diverse users and employees; (2) A domain ontology was constructed through a combination of the top-down and the bottom-up approach, defining seven key concepts and eight semantic relationships; (3) Semi-structured data from enterprises and standards, combined with unstructured data from the literature were systematically collected, cleaned via Scrapy and regular expression, and standardized into JSON format, forming a domain-specific corpus of 1456 annotated sentences; (4) A novel BERT-BiGRU-CRF model was developed, leveraging contextual embeddings from BERT, parameter-efficient sequence modeling via BiGRU (Bidirectional Gated Recurrent Unit), and label dependency optimization using CRF (Conditional Random Field). …”
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Exploring Oral History Archives Using State-of-the-Art Artificial Intelligence Methods by Martin Bulín, Jan Švec, Pavel Ircing, Adam Frémund, Filip Polák

“…The goal is to improve accessibility while preserving the authenticity and integrity of historical records.Methods: We developed an asking questions framework utilizing a fine-tuned T5 model to generate contextually relevant questions from interview transcripts. …”
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Digital Gamification to Foster Attitudes Toward Science in Early Childhood Teacher Education by Noëlle Fabre-Mitjans, Gregorio Jiménez-Valverde, Gerard Guimerà-Ballesta, Genina Calafell-Subirà

“…Integrating technology-enhanced gamification into teacher education can significantly foster motivation and reshape perceptions toward science learning. …”
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Visualizing climate change: a systematic scoping review of digital climate knowledge centers for Indigenous communities in Canada, the United States, Australia, and New Zealand by Iliana Loupessis, Sonia D. Wesche, Ahmad Teymouri, Liam Peyton, Joseph Wabegijig, Colin Rennie

“…Digital climate knowledge centers, which serve as virtual hubs by providing crucial data and adaptation information, are essential for addressing the specific impacts of climate change on Indigenous communities. …”
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Building Safer Social Spaces: Addressing Body Shaming with LLMs and Explainable AI by Sajedeh Talebi, Neda Abdolvand

“…Limitations include Reddit-specific data and potential misses of implicit shaming. Future research should explore multi-platform datasets and few-shot learning. …”
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Fostering Place Attachment Through Activity: Insights from Qaisaria Buildings in the Kurdistan Region of Iraq –Koya and Kifri as Case Studies by Mohammad Ahmed Shehab, Asst. Prof. Dr. Raz Saeed Faraj

“…These findings emphasize the importance of integrating dynamic activities in heritage preservation policies to strengthen historic marketplaces' social and functional continuity.…”
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Large language models in clinical nutrition: an overview of its applications, capabilities, limitations, and potential future prospects by Jamal Belkhouribchia, Joeri Jan Pen

“…This review provides an overview of their current and potential applications in clinical nutrition, focusing on key technologies including prompt engineering, fine-tuning, retrieval-augmented generation, and multimodal integration. These enhancements increase domain relevance, factual accuracy, and contextual responsiveness, enabling LLMs to deliver more reliable outputs in nutrition-related tasks. …”
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Applying machine learning to decode built environment thresholds for public and active transport distances in the global south by Ali Shkera, Domokos Esztergár-Kiss

“…By integrating advanced ML methods with transportation policy analysis, this research bridges critical methodological and contextual gaps thus offering actionable insights for urban planners in high-density, transit-dependent cities worldwide.…”
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Optimal features assisted multi-attention fusion for robust fire recognition in adverse conditions by Inam Ullah, Nada Alzaben, Yousef Ibrahim Daradkeh, Mi Young Lee

“…Abstract Deep neural networks have significantly enhanced visual data-based fire detection systems. However, high false alarm rates, shallow-layered networks, and poor recognition in challenging environments continue to hinder their practical deployment. …”
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