Identification method for malicious traffic in industrial Internet under new unknown attack scenarios by ZENG Fanyi, MAN Dapeng, XU Chen, HAN Shuai, WANG Huanran, ZHOU Xue, LI Xinchun, YANG Wu

“…Finally, the statistical independence of high-dimensional traffic features was realized by applying graph representation learning and stable learning strategies, combined with adaptive sample weighting and collaborative loss optimization methods. …”
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Structural Fingerprinting of Crystalline Materials from XRD Patterns Using Atomic Cluster Expansion Neural Network and Atomic Cluster Expansion by Xiao Zhang, Xitao Wang, Shunbo Hu

“…This study introduces a novel contrastive learning-based X-ray diffraction (XRD) analysis framework, an SE(3)-equivariant graph neural network (E3NN) based Atomic Cluster Expansion Neural Network (EACNN), which reduces the strong dependency on databases and initial models in traditional methods. …”
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Longitudinal alterations in morphological brain networks and cognitive function in common-type COVID-19: a 3-month follow-up study by Ying Liu, Ying Liu, Bei Peng, Haixia Qin, Kaixuan Zhou, Shihuan Lin, Yinqi Lai, Lingyan Liang, Gaoxiong Duan, Xiaocheng Li, Xiaoyan Zhou, Yichen Wei, Qingping Zhang, Jinli Huang, Yan Zhang, Jiazhu Huang, Ruijing Sun, Sijing Tuo, Yuxin Chen, Demao Deng

“…Individual morphological brain networks were constructed using grey matter volume similarity, and topological properties were analyzed using graph theory. We used an independent sample t-test at baseline and a paired sample t-test to compare the 3-month follow-up with the acute phase, with false discovery rate corrections (p < 0.05).ResultsIn the acute phase, patients exhibited increased subcortical network (SCN) connectivity, and reduced connectivity between the frontoparietal network (FPN) and limbic network (LN), the SCN and dorsal/ventral attention network (DAN/VAN), and the LN and DAN. …”
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Tell me why: A scoping review on the fundamental building blocks of fMRI-based network analysis by Z. van der Pal, L. Douw, A. Genis, D. van den Bergh, M. Marsman, A. Schrantee, T.F. Blanken

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KG2Tables: A Domain-Specific Tabular Data Generator to Evaluate Semantic Table Interpretation Systems (Resource Paper) by Abdelmageed, Nora, Jiménez-Ruiz, Ernesto, Hassanzadeh, Oktie, König-Ries, Birgitta

“…We demonstrate the data quality level using a sample-based approach for the generated benchmarks including, for example, realistic tables assessment. …”
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Design of an Iterative Method for Time Series Forecasting Using Temporal Attention and Hybrid Deep Learning Architectures by Yuvaraja Boddu, A. Manimaran

“…Additionally, by representing the multivariate time series data as a graph in which variables are nodes connected by edges denoting temporal relationships, TGAMTSA leverages Graph Neural Networks (GNNs) to decode complex inter-variable dependencies, resulting in a 20% improvement in prediction accuracy over traditional methods. …”
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From network biology to immunity: potential longitudinal biomarkers for targeting the network topology of the HIV reservoir by Heng-Chang Chen

“…Furthermore, I point out potential longitudinal biomarkers identified using network-based analysis and systematically compare them with other potential biomarkers identified based on experimental research with longitudinal clinical samples.…”
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Generative and Contrastive Self-Supervised Learning for Virulence Factor Identification Based on Protein–Protein Interaction Networks by Yalin Yao, Hao Chen, Jianxin Wang, Yeru Wang

“…Moreover, a severe imbalance exists between virulence and non-virulence proteins, which causes existing models trained on balanced datasets by sampling to fail in incorporating proteins’ inherent distributional characteristics, thus restricting generalization to real-world imbalanced data. …”
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Identification of cropland in Tibetan Plateau based on time series remote sensing features by Xin Du, Qiangzi Li, Longcai Zhao, Yunqi Shen, Sichen Zhang, Yuan Zhang, Hongyan Wang, Jingyuan Xu

“…The cropland identification approach proposed by this study reduced reliance on known samples, improving spatiotemporal generalization capability. …”
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Revisiting the link between COVID-19 incidence and infection fatality rate during the first pandemic wave by Benjamin Glemain, Charles Assaad, Walid Ghosn, Paul Moulaire, Xavier de Lamballerie, Marie Zins, Gianluca Severi, Mathilde Touvier, Jean-François Deleuze, SAPRIS-SERO study group, Nathanaël Lapidus, Fabrice Carrat, Pierre-Yves Ancel, Marie-Aline Charles, Gianluca Severi, Mathilde Touvier, Marie Zins, Sofiane Kab, Adeline Renuy, Stephane Le-Got, Celine Ribet, Mireille Pellicer, Emmanuel Wiernik, Marcel Goldberg, Fanny Artaud, Pascale Gerbouin-Rérolle, Mélody Enguix, Camille Laplanche, Roselyn Gomes-Rima, Lyan Hoang, Emmanuelle Correia, Alpha Amadou Barry, Nadège Senina, Julien Allegre, Fabien Szabo de Edelenyi, Nathalie Druesne-Pecollo, Younes Esseddik, Serge Hercberg, Mélanie Deschasaux, Marie-Aline Charles, Valérie Benhammou, Anass Ritmi, Laetitia Marchand, Cecile Zaros, Elodie Lordmi, Adriana Candea, Sophie de Visme, Thierry Simeon, Xavier Thierry, Bertrand Geay, Marie-Noelle Dufourg, Karen Milcent, Delphine Rahib, Nathalie Lydie, Clovis Lusivika-Nzinga, Gregory Pannetier, Nathanael Lapidus, Isabelle Goderel, Céline Dorival, Jérôme Nicol, Olivier Robineau, Cindy Lai, Liza Belhadji, Hélène Esperou, Sandrine Couffin-Cadiergues, Jean-Marie Gagliolo, Hélène Blanché, Jean-Marc Sébaoun, Jean-Christophe Beaudoin, Laetitia Gressin, Valérie Morel, Ouissam Ouili, Jean-François Deleuze, Laetitia Ninove, Stéphane Priet, Paola Mariela Saba Villarroel, Toscane Fourié, Souand Mohamed Ali, Abdenour Amroun, Morgan Seston, Nazli Ayhan, Boris Pastorino, Xavier de Lamballerie

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Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng, Jiyang Dong

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Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically by Yu Lin, Yan Wang, Juexin Wang, Mauminah Raina, Ricardo Melo Ferreira, Michael T. Eadon, Yanchun Liang, Dong Xu

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Open-World Semi-Supervised Learning for fMRI Analysis to Diagnose Psychiatric Disease by Chang Hu, Yihong Dong, Shoubo Peng, Yuehan Wu

“…Specifically, we employ spectral augmentation self-supervised learning and dynamic concept contrastive learning to achieve open-world graph learning guided by pseudo-labels, and construct hard positive sample pairs to enhance the network’s focus on potential positive pairs. …”
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Isomeric Differentiation of Four Triterpene Acids Using Full Collision Energy Ramp-MS2 Analysis by Li-juan WU, Rui-ru NAN, Qian WANG, Xin CHEN, Wen-jing LIU, Yue-lin SONG

“…FCER-MS2 spectra were configured by assembling sigmoid- and Gaussian-shaped breakdown graphs of those primary MS2 spectral signals after appropriate data normalization. …”
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Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

“…A comprehensive dataset of ignition delays was generated using a random sampling technique across different temperatures and pressures, focusing on hydrocarbon fuels with 1–4 carbon atoms. …”
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Evaluation of the Idle time of Single-Chain and Double-Chain Overhead Power Lines of 6–10 kV by Methods of Queuing Theory by Basmanov V.G., Kholmanskikh V.M.

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Style Transfer and Topological Feature Analysis of Text-Based CAPTCHA via Generative Adversarial Networks by Tao Xue, Zixuan Guo, Zehang Yin, Yu Rong

“…Initially, the recognition success rates of the three methods across four styles were evaluated using Muggle-OCR. Subsequently, the graph diameter was employed to quantify the differences between text-based CAPTCHA images before and after style transfer. …”
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Review and prospect of floating car data research in transportation by Chi Zhang, Yuming Zhou, Min Zhang, Bo Wang, Yuhan Nie

“…A systematic review of key literature was conducted to address research challenges related to floating car sampling proportions and frequencies, and future research challenges and opportunities were proposed. …”
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Research and Construction of Knowledge Map of Golden Pomfret Based on LA-CANER Model by Xiaohong Peng, Hongbin Jiang, Jing Chen, Mingxin Liu, Xiao Chen

“…Furthermore, the knowledge graph can be integrated with large models like GPT-4 and DeepSeek-R1. …”
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Angus: efficient active learning strategies for provenance based intrusion detection by Lin Wu, Yulai Xie, Jin Li, Dan Feng, Jinyuan Liang, Yafeng Wu

“…They either select samples to update the training set according to similarities of provenance graphs or preferentially select samples with low redundancy and large differences from the current training set. …”
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