GRAPPA—A hybrid graph neural network for predicting pure component vapor pressures by Marco Hoffmann, Hans Hasse, Fabian Jirasek

“…We found excellent prediction accuracy for unseen components, outperforming state-of-the-art group contribution methods and other machine learning approaches in applicability and accuracy. …”
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Enhanced Non-Destructive Testing of Small Wind Turbine Blades Using Infrared Thermography by Majid Memari, Mohammad Shekaramiz, Mohammad A. S. Masoum, Abdennour C. Seibi

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State-of-the-Art Document Image Binarization Using a Decision Tree Ensemble Trained on Classic Local Binarization Algorithms and Image Statistics by Nicolae Tarbă, Costin-Anton Boiangiu, Mihai-Lucian Voncilă

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SaeGraphDTI: drug–target interaction prediction based on sequence attribute extraction and graph neural network by Qiaosheng Zhang, Zhenyu Sun, Zhaoman Zhong, Huihui Yang, Yalong Wei, Junjie Xu

“…Abstract Background Accurately identifying drug–target interactions (DTI) can greatly shorten the drug development cycle and reduce the cost of drug development. In current deep learning-based DTI prediction models, the extraction of drug and target features is a key step to improve model performance. …”
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A Framework for Domain-Specific Dataset Creation and Adaptation of Large Language Models by George Balaskas, Homer Papadopoulos, Dimitra Pappa, Quentin Loisel, Sebastien Chastin

“…By enabling privacy-preserving, domain-specific adaptation without requiring extensive expertise, this framework represents a significant step forward in the deployment of LLMs for specialised applications. …”
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Ionospheric Time Series Prediction Method Based on Spatio-Temporal Graph Neural Network by Yifei Chen, Yang Liu, Kunlin Yang, Lanhao Li, Chao Xiong, Jinling Wang

“…For the geomagnetic storm event, the proposed STGNN achieves 16.0% higher stability. For the one-week (84 step) prediction test, the STGNN shows a 27.0% lower error compared to the MLPMultivariate model. …”
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Reliable smart models for estimating frictional pressure drop in two-phase condensation through smooth channels of varying sizes by M. A. Moradkhani, S. H. Hosseini, Mengjie Song, A. Abbaszadeh

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Relapse prediction using wearable data through convolutional autoencoders and clustering for patients with psychotic disorders by April Yujie Yan, Traci Jenelle Speed, Casey Overby Taylor

“…It contributes to the first step towards determining relapse-related biomarkers that could improve predictions and enable timely interventions to enhance patients’ quality of life.…”
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Individual Differences in Strategy and the Item-Position Effect in Reasoning Ability Measures by Helene M. von Gugelberg, Stefan J. Troche

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Tomato-Nerf: Advancing Tomato Model Reconstruction With Improved Neural Radiance Fields by Xiajun Zheng, Xinyi AI, Hao Qin, Jiacheng Rong, Zhiqin Zhang, Yan Yang, Ting Yuan, Wei Li

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Simultaneous text and gesture generation for social robots with small language models by Alessio Galatolo, Alessio Galatolo, Katie Winkle

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A Semi-Automatic Framework for Practical Transcription of Foreign Person Names in Lithuanian by Gailius Raškinis, Darius Amilevičius, Danguolė Kalinauskaitė, Artūras Mickus, Daiva Vitkutė-Adžgauskienė, Antanas Čenys, Tomas Krilavičius

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Prediction of Temporal Liking from Temporal Dominance of Sensations by Using Reservoir Computing and Its Sensitivity Analysis by Hiroharu Natsume, Shogo Okamoto

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DeepInterAware: Deep Interaction Interface‐Aware Network for Improving Antigen‐Antibody Interaction Prediction from Sequence Data by Yuhang Xia, Zhiwei Wang, Feng Huang, Zhankun Xiong, Yongkang Wang, Minyao Qiu, Wen Zhang

“…Abstract Identifying interactions between candidate antibodies and target antigens is a key step in developing effective human therapeutics. …”
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A novel system applying artificial intelligence in the identification of air leak sitesCentral MessagePerspective by Yuka Kadomatsu, MD, PhD, Megumi Nakao, PhD, Harushi Ueno, MD, Shota Nakamura, MD, PhD, Toyofumi Fengshi Chen-Yoshikawa, MD, PhD

“…Intraoperative leak site detection is the first step in decreasing the risk of leak-related postoperative complications. …”
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Chinese Paper-Cutting Style Transfer via Vision Transformer by Chao Wu, Yao Ren, Yuying Zhou, Ming Lou, Qing Zhang

“…To further embody the symmetrical structures and hollowed hierarchical patterns intrinsic to Chinese paper-cutting, the multi-level feature contrastive learning module is designed based on a contrastive learning strategy. …”
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An Automated Framework of Superpixels-Saliency Map and Gated Recurrent Unit Deep Convolutional Neural Network for Land Cover and Crops Disease Classification by Irfan Haider, Muhammad Attique Khan, Muhammad Nazir, Saleha Masood, Naoufel Kraiem, Dina Abdulaziz Alhammadi

“…The proposed framework is based on two embedded steps. In the first step, crop leaf disease segmentation was performed using superpixel clustering-based saliency maps and Bayesian optimization. …”
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AHP-Guided Stacked Ensemble Modeling for Student Engagement Level Prediction in Online Education by Jingjing Fu, Linjie Luo, Zhifeng Zhong, Jiaming Qin

“…The proposed method consists of three key steps: first, data preprocessing to prepare and refine a set of indicators related to the level of student engagement in online education environments. …”
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A Semi-Automated, Hybrid GIS-AI Approach to Seabed Boulder Detection Using High Resolution Multibeam Echosounder by Eoin Downing, Luke O’Reilly, Jan Majcher, Evan O’Mahony, Jared Peters

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Detection and Identification of Dental Caries Using Segmentation Techniques by Noor A. Ibraheem

“…We tested both traditional methods—like Quickshift, Simple Linear Iterative Clustering (SLIC) superpixels, and k-means clustering—combined in the Multi-Step Segmentation with K-Means (MSS-KM) approach, as well as a more advanced deep learning method using YOLOv12 for segmentation. …”
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