Playing with Numbers: The Social and Behavioural Impacts of Using a Card Game to Teach Business Metrics by Ruth Smith, Elaine Conway

“…The theoretical contribution of this paper lies in its explicit application and extension of SLT within the context of business education, illustrating empirically how social interactions facilitated by game-based activities significantly enhance learning outcomes. …”
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A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data by Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He

“…The CNN-GRU model can produce prediction vectors by fusing implicit and explicit information extracted from the original MS data and early warning indicators. …”
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Technical note: Applicability of physics-based and machine-learning-based algorithms of a geostationary satellite in retrieving the diurnal cycle of cloud base height by M. Wang, M. Min, J. Li, H. Lin, Y. Liang, B. Chen, Z. Yao, N. Xu, M. Zhang

“…<p>Two groups of retrieval algorithms, physics based and machine learning (ML) based, each consisting of two independent approaches, have been developed to retrieve cloud base height (CBH) and its diurnal cycle from Himawari-8 geostationary satellite observations. …”
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Characterizing Breast Tumor Heterogeneity Through IVIM-DWI Parameters and Signal Decay Analysis by Si-Wa Chan, Chun-An Lin, Yen-Chieh Ouyang, Guan-Yuan Chen, Chein-I Chang, Chin-Yao Lin, Chih-Chiang Hung, Chih-Yean Lum, Kuo-Chung Wang, Ming-Cheng Liu

“…<b>Background/Objectives:</b> This research presents a novel analytical method for breast tumor characterization and tissue classification by leveraging intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) combined with hyperspectral imaging techniques and deep learning. Traditionally, dynamic contrast-enhanced MRI (DCE-MRI) is employed for breast tumor diagnosis, but it involves gadolinium-based contrast agents, which carry potential health risks. …”
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Culturaliser les difficultés scolaires ? L’exemple des politiques éducatives en Picardie face aux classes populaires blanches by Ismail Ferhat

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應用智慧型家教系統於國小學童閱讀策略 教學之學習歷程研究 A Study on the Learning Process of Applying an Autotutoring System to Teach Reading Strategies to Elementary School Children... by 陳茹玲 Ju-Ling Chen, 曾厚強 Hou-Chiang Tseng, 連啟舜 Chi-Shun Lien, 蔡旻穎 Min-Ying Tsai, 宋曜廷 Yao-Ting Sung

“…High-reading-ability learners showed shorter learning paths and required minimal assistance, while low-reading-ability learners needed more explicit prompts and sometimes overlooked the autotutor’s support role in learning. …”
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CCD-Net: Color-Correction Network Based on Dual-Branch Fusion of Different Color Spaces for Image Dehazing by Dongyu Chen, Haitao Zhao

“…Image dehazing is a crucial task in computer vision, aimed at restoring the clarity of images impacted by atmospheric conditions like fog, haze, or smog, which degrade image quality by reducing contrast, color fidelity, and detail. Recent advancements in deep learning, particularly convolutional neural networks (CNNs), have shown significant improvements by directly learning features from hazy images to produce clear outputs. …”
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Directed Graph Neural Networks for Anomaly Detection of Smart Ponzi Schemes by Xiaofang Jiang, Wei-Tek Tsai

“…The proposed model employs a self-supervised learning paradigm that combines contrastive and generative learning to derive node embeddings without relying on labeled data, making it particularly well-suited for imbalanced datasets. …”
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Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China by Lingzhi Luo, Liang Wang, You Li, Hongying Cao, Yanling Guo, Xiaoyong Liao

“…To address this gap, we introduce a novel framework integrating machine learning and spatially explicit risk models to assess individual- and population-level health risks from soil heavy metals in Baoding City, China. …”
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Application of physics-informed neural networks for two-phase flow model with variable diffusion and experimental validation by Daulet Kalesh, Timur Merembayev, Sagyn Omirbekov, Yerlan Amanbek

“…Recent advancements in deep learning have significantly improved solving complex computational physics problems. …”
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Apple Detection via Near-Field MIMO-SAR Imaging: A Multi-Scale and Context-Aware Approach by Yuanping Shi, Yanheng Ma, Liang Geng

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MT-CMVAD: A Multi-Modal Transformer Framework for Cross-Modal Video Anomaly Detection by Hantao Ding, Shengfeng Lou, Hairong Ye, Yanbing Chen

“…To address the sparse anomaly supervision dilemma, we propose a hybrid learning objective that integrates dual-stream reconstruction loss with prototype-based contrastive discrimination, enabling the joint optimization of pattern restoration and discriminative representation learning. …”
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Student and educator perspectives on clinical reasoning: A qualitative study by Danelle Hess, Jacqueline Hendricks, José Frantz, Michael Rowe

“…This includes developing holistic assessment rubrics that acknowledge both foundational and advanced CR skills and implementing case-based learning approaches. And creating opportunities for educators to make their reasoning processes explicit and visible to students.…”
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Multi-Scale Venation Pattern Analysis for Medicinal Plant Species Recognition by Arnav Sanjay Karnik, Nikhil Nair, Yashas Sagili, P. B. Pb

“…To validate the effectiveness of our approach, we developed and evaluated three distinct model architectures: 1) a modified ResNet-50 model utilizing transfer learning with an adapted input pipeline for venation-aware channels; 2) a custom-built convolutional neural network, VenationNet, explicitly designed for multi-scale venation analysis; and 3) a Dual-Stream CNN architecture that processes leaf texture and venation maps independently before merging via attention-based fusion. …”
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Improving L2 pronunciation inside and outside the classroom by Angélica Carlet, Hanna Kivistö-de Souza

“… Spanish/Catalan learners of English as a Foreign Language (EFL) attended a formal instruction (FI) period combined with explicit pronunciation instruction, which consisted of theoretical and practical approaches to English segmental phonetics as well as a contrastive analysis between the participants’ first languages and the target language, English. …”
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Synthetic Sentiment Cue Enhanced Graph Relation-Attention Network for Aspect-Level Sentiment Analysis by Hongwei Tang, Haining Yan, Ran Song

“…Our method introduces three key innovations: 1) a synthetic data augmentation paradigm leveraging LLMs to generate semantically coherent sentiment cues, thereby enriching aspect-opinion interactions; 2) a hierarchical graph architecture that models syntactic dependency structures and aspect-context relationships through relation-aware attention mechanisms; and 3) a contrastive learning objective that aligns representations from both authentic and synthetic data to enhance model robustness. …”
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Réflexions sur l’appropriation du théâtre historique élisabéthain par la scène britannique contemporaine : usages de Macbeth dans Thirteenth Night de Howard Brenton (1981) et Dunsi... by Line Cottegnies

“…These two plays can help us think in a contrastive way about the question of adaptation. They show a complex rapport with the canonical source. …”
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Improving student understanding of fermionic and bosonic wave function by Christof Keebaugh, Emily Marshman, Chandralekha Singh

“…We discuss how research on student difficulties was used as a guide to develop, validate, and evaluate a Quantum Interactive Learning Tutorial (QuILT) to help students learn how to determine the completely symmetric bosonic or completely antisymmetric fermionic wave function and be able to compare and contrast them from the case when the particles can be treated as distinguishable. …”
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DREAM3: network inference using dynamic context likelihood of relatedness and the inferelator. by Aviv Madar, Alex Greenfield, Eric Vanden-Eijnden, Richard Bonneau

“…In contrast, methods for learning regulatory networks based on explicit dynamical models are more complex and scale less gracefully, but are attractive as they may allow direct prediction of transcriptional dynamics and resolve the directionality of many regulatory interactions.…”
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Enhanced Multimodal Content Moderation of Children’s Videos using Audiovisual Fusion by Syed Hammad Ahmed, Muhammad Junaid Khan, Gita Sukthankar

“…However, recent content moderation approaches rarely employ multimodal architectures that explicitly consider non-speech audio cues. To address this, we present an efficient adaptation of CLIP (Contrastive Language–Image Pre-training) that can leverage contextual audio cues for enhanced content moderation. …”
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