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To bridge the gap in visualization and interactivity found in traditional chemistry tools, this study developed an AR-powered comic using differentiated instruction to help students navigate the spatial complexities of m...

Abstract Background Blended learning, integrating traditional teaching with digital resources, has shown promise in medical education. The Radiology Assistant platform offers structured, case-based content that may addre...

University physical education (PE) is increasingly expected to foster physical literacy by integrating movement competence with cognitive understanding and intrinsic motivation. However, rigorous evidence regarding the e...

Technology-based learning is increasingly integrated into school environments, yet its role in students' moral and psychosocial development remains underexplored. This study investigates the relationship between technolo...

With the increasing integration of artificial intelligence (AI) across industries, there is a growing need to transform traditional teaching methods into more innovative, technology-driven, and practice-oriented approach...

Adaptive learning systems require effective mechanisms to model students’ evolving learning states and provide personalized learning path recommendations. Traditional rule-based approaches are limited in capturing...

Abstract Background Carotid atherosclerosis is a kind of systemic atherosclerosis in the carotid arteries. It remains one of the leading causes of ischemic stroke. However, the efficiency of treatment is insufficient. Th...

Optimizing modern factories requires dynamic, data-driven decision support aligned with Industry 5.0’s human-centric principles. This research introduces the ‘immersive cognitive factory twin’, a novel framework le...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Abstract Background Accurate and timely estimation of nitrogen nutrition index (NNI) is critical for assessing crop nitrogen (N) status and implementing precision N management. While machine learning (ML) techniques comb...

Cadmium poses severe threats to ecosystems and human health due to its high toxicity and bioaccumulative nature. The global regulatory limits for Cd are often low at 0.1-0.6 mg kg−1, which is 1 to 2 orders of magnitude...

ObjectiveTo develop and internally validate an interpretable, non-invasive machine learning framework to predict detrusor underactivity (DU) in patients with benign prostatic hyperplasia (BPH).MethodsThis retrospective c...

Abstract Background Rapid and accurate pest diagnosis is essential for reducing crop losses and improving agricultural productivity. Most existing methods rely on deep learning-based object detection to classify pests in...

Surabaya City is one of the urban areas in Indonesia with a high incidence of breast cancer. Multiple factors, including genetic predisposition, lifestyle patterns, and environmental exposures, influence this condition. ...

Abstract Alkaline water electrolysis represents a promising pathway for green hydrogen production, yet comprehensive multi-physics simulation remains computationally prohibitive for practical design optimization. This st...

Advances in Artificial Intelligence (AI), particularly through Machine Learning (ML) and Deep Learning (DL), have enabled innovative solutions in industries including automotive, healthcare, and transportation. These tec...

Learning enjoyment among university students has shown signs of decline in recent years, raising growing concerns about student motivation and engagement in higher education. Although previous research has identified sev...

To overcome the limitations of traditional models to simulate discrete environmental variables, this study introduces a novel, integrated simulation framework: the Spatio-Temporal Integrated Geographic Generative Adversa...

Abstract Objective: To estimate the effect of integrating responsive care, early learning and development monitoring into a community-based package of activities on nutrition, sanitation and hygiene, on improvements in ...

This study investigates the impact of Content and Language Integrated Learning (CLIL) on academic vocabulary development and disciplinary understanding among newly recruited teachers at Batna 2 University, Algeria. Condu...

Purpose – This study systematically maps global research trends on entrepreneurial readiness in vocational education from 2020 to 2025 and identifies implications for strengthening the Indonesian vocational education s...

Abstract Roadside areas are major sources of traffic-related air pollutant emissions. This study identified the spatial distribution of roadside pollutants using Unmanned Aerial Vehicle (UAV) measurements and predicted t...

This study integrates geochemical, statistical, and machine learning methods to investigate hydrothermal systems and mineralization processes within southern Georgia's Bektakari–Bnelikhevi ore knot. A total of 212 geoc...

Purpose – this study differs from previous research in that it focuses on developing the DCALL model in writing learning. The main target is students' writing skills in any text, supported by an application integrated ...