Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction by Zexi Yang, Qi Yu, Yapeng Zhan, Jiying Liu

“…Indeed, even the periodic patterns of the crystal structures are not seriously considered. …”
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Trajectory Prediction and Intention Recognition Based on CNN-GRU by Jinghao Du, Dongdong Lu, Fei Li, Ke Liu, Xiaolan Qiu

“…Accurate trajectory prediction and intention recognition are essential for effective decision-making, as different intents manifest in distinct trajectory patterns. This study focuses on trajectory prediction and intention recognition for airborne moving targets by proposing an integrated approach that leverages trajectory data for both tasks. …”
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Exploring Conceptualizations of Disability Using Story-Completion Methods by Nicole Giouridis, Toni Louise Williams, Julia McKenna, Jennifer Rose Tomasone

“…Through the process of thematic analysis, three themes were generated as patterns across stories: (1) assumptions about disability present from first glance; (2) uncertainty in navigating negative assumptions of disability; and (3) from discomfort to acceptance of disability through social connection. …”
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A Network Approach for Discovering Spatially Associated Objects by Changfeng Jing, Tao Liang, Yunlong Feng, Jianing Li, Sensen Wu, Jiale Ding, Gaoran Xu, Yang Hu

“…The WSTA can capture both spatial interaction patterns and topological relationships in complex urban environments, thereby improving the accuracy of spatially associated object discovery. …”
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Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorderResearch in context by Stephen Joza, Aline Delva, Christina Tremblay, Andrew Vo, Marie Filiatrault, Max Tweedale, Jean-François Gagnon, Ronald B. Postuma, Alain Dagher, Johannes Klein, Michele Hu, Petr Dusek, Stanislav Marecek, Zsoka Varga, John-Paul Taylor, John T. O'Brien, Michael Firbank, Alan Thomas, Paul C. Donaghy, Stéphane Lehéricy, Marie Vidailhet, Jean-Christophe Corvol, ICEBERG Study Group, Richard Camicioli, Howard Chertkow, Simon Lewis, Elie Matar, Kaylena A. Ehgoetz Martens, Lachlan Churchill, Michael Sommerauer, Sinah Röttgen, Per Borghammer, Karoline Knudsen, Allan K. Hansen, Dario Arnaldi, Beatrice Orso, Pietro Mattioli, Luca Roccatagliata, Oury Monchi, Shady Rahayel, Isabelle Arnulf, Samir Bekadar, Eve Benchetrit, Alexis Brice, Vanessa Brochard, Alizé Chalançon, Benoit Colsch, Florence Cormier-Dequaire, Jean-Christophe Corvol, Virginie Czernecki, Bertrand Degos, Cécile Delorme, Pauline Dodet, Carole Dongmo-Kenfack, Marie-Odile Habert, Farid Ichou, Jonas Ihle, Cécile Galléa, Rahul Gaurav, Marie-Alexandrine Glachant, Manon Gomes, David Grabli, Elodie Hainque, Laetitia Jeancolas, Christelle Laganot, Stéphane Lehéricy, Suzanne Lesage, Smaranda Leu-Semenescu, Richard Levy, Valentine Maheo, Graziella Mangone, Louise Laure Mariani, Aurelie Méneret, Poornima Menon, Fanny Mochel, Vincent Perlbarg, Dijana Petrovska, Fanny Pineau, Nadya Pyatigorskaya, Sophie Rivaud-Pechoux, Emmanuel Roze, Sara Sambin, Julie Socha, Arthur Tenenhaus, Romain Valabregue, Marie Vidailhet, Lydia Yahia-Cherif

“…Interpretation: There are two distinct atrophy progression subtypes in iRBD, with the cortical-first subtype linked to an increased likelihood of developing DLB, while both subtypes were associated with worsening parkinsonian motor features. …”
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Sequence Modeling of Passive Sensing Data for Treatment Response Prediction in Major Depressive Disorder by Bochao Zou, Xiaolong Zhang, Le Xiao, Ran Bai, Xin Li, Hui Liang, Huimin Ma, Gang Wang

“…To overcome that, the proposed approach combined feature extraction and sequence modeling methods to fully utilize the pattern of missing values from longitudinal data. …”
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SHIFA: SBERT-Based Healthcare Information Focused Arabic Question Answering by Rahaf Alruwaithi, Sarah AlHumoud

“…The idea behind this research is to use the SBERT method for entities and context patterns to effectively capture the semantics between QA pairs in two different ways: the feature extractor and the transfer learning model. …”
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Potential of EnMAP Hyperspectral Imagery for Regional-Scale Soil Organic Matter Mapping by Yassine Bouslihim, Abdelkrim Bouasria

“…Partial Least Squares Regression (PLSR) models were developed under different pre-treatment scenarios. …”
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning by Swetha Valavarasu, Yasaswini Sangu, Tanmaya Mahapatra

“…Abstract Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. …”
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lexible sensors for food monitoring. Part II: Applications by D. Luo, M. A. Nikitina, X. Xiao

“…We also highlight the benefits and the technical challenges along with the appropriate solutions provided by the presented flexible sensors, and we also consider the potential strategies that allow overcoming limitations in power consumption, quantitatively assess the trade-offs in maintaining the quality and marketability, to optimize wireless communication and explore new sensing patterns.…”
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Addressing Sensor Data Heterogeneity and Sample Imbalance: A Transformer-Based Approach for Battery Degradation Prediction in Electric Vehicles by Bi Wu, Shi Qiu, Wenhe Liu

“…To tackle data heterogeneity, we developed a multimodal feature fusion strategy that effectively integrates battery sensor data from different sources and formats, including time-series charge-discharge sensor data and spectral impedance sensor measurements. …”
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Dynamics of HLB Transmission: Integrating Saturated Removal and Vector Bias in Spatial/Non-Spatial Models by Yang Liu, Yirong Gao, Fumin Zhang, Shujing Gao

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Altered microbial biogeography in an innate model of colitis by Antonia Boger-May, Theodore Reed, Diana LaTorre, Katelyn Ruley-Haase, Hunter Hoffman, Lauren English, Connor Roncagli, Anne-Marie Overstreet, David Boone

“…RAG1−/−, but not TRAG, mice exhibited a structured pattern of bacterial abundance with decreased Firmicutes and Proteobacteria but increased Bacteroidetes along the proximal to distal axis of the gut. …”
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Hybrid AE and Bi-LSTM-Aided Sparse Multipath Channel Estimation in OFDM Systems by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

“…Traditional channel estimation methods, such as Least-Squares (LS), utilize randomly spaced pilot patterns, which can compromise spectral efficiency. …”
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Atypical cristae in bundle sheath mitochondria in leaves of Atriplex tatarica (Chenopodiaceae s. str. / Amaranthaceae s. l.) by Fediuk O., Bilyavska N., Akimov Yu., Zolotareva O.

“…Electron microscopic analysis of leaf ultrastructure patterns of Atriplex tatarica (Chenopodiaceae s. str. / Amaranthaceae s. l.) revealed a prominent feature in mitochondria in bundle sheath cells (BSCs). …”
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Long non-coding RNA SNHG7 as a key driver of colorectal cancer proliferation and metastasis by inhibiting cuproptosis by Xin Guo, Xinyi He, Weitao Chen, Jianlong Zhou, Zejian Lyu, Zhou Li, Yong Li

“…The prognostic lncRNA signatures were used to construct a prognostic model and validated by Kaplan–Meier and ROC curves. Clinical feature analysis and immune microenvironment assessment of identified lncRNAs were conducted, and in vitro assays were performed to validate their expression pattern and effect in CRC. …”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…All the data sets consisted of a minute trait total derived from a sparkling file. The attack patterns that were not anonymized or were indicative of the vulnerability of cyber-attack were denoted with yellow. …”
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Advancing sedimentation modeling in large reservoir systems: Insights from multi-scale process coupling and machine learning by Yuning Tan, Huaixiang Liu, Yongjun Lu, Zhili Wang, Wenjie Li

“…Random Forest outperformed XGBoost, Support Vector Regression, and Artificial Neural Network, demonstrating the most robust performance and the clearest feature attribution. Our climate scenario simulations revealed uneven sedimentation patterns and projected declining sedimentation rates over the next 30 years. …”
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Optimizing Sensitivity in Machine Learning Models for Pediatric Post-operative Kyphosis Prediction by Raja Ayu Mahessya, Dian Eka Putra, Rostam Ahmad Efendi, Rayendra, Rozi Meri, Riyan Ikhbal Salam, Dedi Mardianto, Ikhsan, Ismael, Arif Rizki Marsa

“…This study demonstrates the capacity of decision tree models to extract clinically meaningful patterns from small, imbalanced surgical datasets that elude conventional statistical approaches.…”
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Predicting female football outcomes by machine learning: behavioural analysis of goals as high stress events by Aratz Olaizola, Ibai Errekagorri, Elsa Fernández, Julen Castellano, John Suckling, Karmele Lopez-de-Ipina

“…We applied a comprehensive approach that integrates spatiotemporal and behavioural data during the transitional period following goals focusing on team dynamics, including chaotic and collective behavioural analysis with entropy and fractality, spatial area, movement trajectories, and locomotor patterns. Several well-established ML models and feature extraction techniques were deployed with overall good performance of greater than 70% accuracy, with some specific methodology combinations have superior performance. …”
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