Dream content discovery from social media using natural language processing by Anubhab Das, Sanja Šćepanović, Luca Maria Aiello, Remington Mallett, Deirdre Barrett, Daniele Quercia

“…To overcome these issues, we conducted data-driven mixed-method analysis identifying topics in free-form dream reports through natural language processing. …”
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Hyperdimensional computing: a framework for stochastic computation and symbolic AI by Mike Heddes, Igor Nunes, Tony Givargis, Alexandru Nicolau, Alex Veidenbaum

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Decision support for the identification of testate amoebae in microscopy images to detect peat presence in horticultural substrates by Serge Zaugg, Camille Vögeli, Lena Märki, Clément Duckert, Edward A.D. Mitchell

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Optimizing group utility in itinerary planning: a strategic and crowd-aware approach by Junhua Liu, Aldy Gunawan, Kristin L. Wood, Kwan Hui Lim

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A dataset of tracked mesoscale precipitation systems in the tropics by James Russell, Manikandan Rajagopal, Peter Veals, Gregor Skok, Edward Zipser, Michell Tinoco‐Morales

“…IMERG is a global gridded precipitation product that incorporates observations from a constellation of satellites with passive microwave sensors and other sources, allowing the TIMPS dataset to have continuous temporal precipitation information for MCSs in a global tropical strip with data every 30 min in time and 0.1° in space. TIMPS are provided in a publicly available data base with a variety of variables including MCS size, motion, and precipitation properties, estimations of MCS life cycle stages, and their proximity to the nearest tropical cyclone. …”
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Identifying key genetic variants in Alzheimer’s disease progression using Graph Convolutional Networks (GCN) and biological impact analysis by Belal A. Hamed, Heba Mamdouh Farghaly, Ahmed Omar, Tarek Abd El-Hafeez

“…We present a novel deep learning framework integrating Single Nucleotide Polymorphism (SNP) data with Graph Convolutional Networks (GCNs) to predict gene-disease relationships in AD. …”
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Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

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A deep operator network for Bayesian parameter identification of self-oscillators by Tobias Sugandi, Bayu Dharmaputra, Nicolas Noiray

“…The proposed method is validated against numerical simulations and experimental data obtained from a linearly unstable turbulent combustor.…”
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Exo-Tox: Identifying Exotoxins from secreted bacterial proteins by Tanja Krueger, Damla A. Durmaz, Luisa F. Jimenez-Soto

“…We provide open access to the model, training data, and usage guidelines via the LMU Munich Open Data repository.…”
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Building a reliable 16S mini-barcode library of wild bees from Occitania, south-west of France by Anaïs Marquisseau, Kamila Canale-Tabet, Emmanuelle Labarthe, Géraldine Pascal, Christophe Klopp, André Pornon, Nathalie Escaravage, Rémi Rudelle, Alain Vignal, Annie Ouin, Mélodie Ollivier, Magalie Pichon

“…This high-quality reference library data are freely available to the scientific community, with the aim of facilitating future large-scale characterisation of wild bee communities in a context of pollinators' decline.…”
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Feature Enhanced Spatial–Temporal Trajectory Similarity Computation by Silin Zhou, Chengrui Huang, Yuntao Wen, Lisi Chen

“…Abstract Trajectory similarity computation is a fundamental function in many applications of urban data analysis, such as trajectory clustering, trajectory compression, and route planning. …”
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Whole-genome sequence of Pseudomonas sp. strain HOU2 isolated from dangshen (Codonopsis javanica) roots by Van Hong Thi Dao, Loan To Nguyen, Khanh Phuong Do, Vinh The Nguyen, Hieu Van Nguyen, Khanh Ngoc Pham, Truong Xuan Nguyen, Son Truong Dinh

“…Further investigation of the whole genome of Pseudomonas sp. strain HOU2 will help identify potential genes or pathways that could be involved in the plant growth-promoting effects on in vitro dangshen plants, providing valuable information for future applications. Data description The genomic DNA of Pseudomonas sp. strain HOU2 was sequenced using Oxford Nanopore’s PromethION sequencer with an R10.4.1 flow cell (Table 1, Data file 1). …”
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Drug repurposing for Alzheimer’s disease using a graph-of-thoughts based large language model to infer drug-disease relationships in a comprehensive knowledge graph by Zhiping Paul Wang, Xi Li, Nicholas Matsumoto, Mythreye Venkatesan, Jui-Hsuan Chang, Jay Moran, Hyunjun Choi, Binglan Li, Yufei Meng, Miguel E. Hernandez, Jason H. Moore

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The inconvenient truth of ground truth errors in automotive datasets and DNN-based detection by Pak Hung Chan, Boda Li, Gabriele Baris, Qasim Sadiq, Valentina Donzella

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The relevance of higher-order ties by Alberto Ceria, Frank W. Takes

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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions by Krishnashree Achuthan, Sasangan Ramanathan, Sethuraman Srinivas, Raghu Raman

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Residual-enhanced graph convolutional networks with hypersphere mapping for anomaly detection in attributed networks by Wasim Khan, Afsaruddin Mohd, Mohammad Suaib, Mohammad Ishrat, Anwar Ahamed Shaikh, Syed Mohd Faisal

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A probabilistic approach for building disease phenotypes across electronic health records by David Vidmar, Jessica De Freitas, Will Thompson, John M. Pfeifer, Brandon K. Fornwalt, Noah Zimmerman, Riccardo Miotto, Ruijun Chen

“…Abstract Background Identifying the set of patients with a particular disease diagnosis across electronic health records (EHRs), referred to as a phenotype, is an important step in clinical research and applications. However, this task is often challenging, where incomplete data can render definitive classifications impossible. …”
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Automated road surface classification in OpenStreetMap using MaskCNN and aerial imagery by R. Parvathi, V. Pattabiraman, Nancy Saxena, Aakarsh Mishra, Utkarsh Mishra, Ansh Pandey

“…The model is robust across varied terrains and visual conditions and shows potential for real-world applications such as OSM data enhancement, infrastructure analysis, and autonomous navigation. …”
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On the effectiveness of neural operators at zero-shot weather downscaling by Saumya Sinha, Brandon Benton, Patrick Emami

“…Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. …”
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