HETEROGENEOUS LITHOSPHERIC STRUCTURE OF THE FENNOSCANDIAN SHIELD: SEISMIC DATA by N. V. Sharov, A. A. Lebedev

“…This provided an opportunity to obtaine quantitative data on the horizontal and vertical heterogeneities of the lithosphere. 3D seismological models were first constructed for the individual parts of the Fennoscandian Shield which show that the crystalline crust structure acquires a block hierarchy pattern, with no persistent seismic boundaries found within the entire shield. …”
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anomaly: Detection of Anomalous Structure in Time Series Data by Alex Fisch, Daniel Grose, Idris A. Eckley, Paul Fearnhead, Lawrence Bardwell

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Structural Stability of Pseudo-Parabolic Equations for Basic Data by Yanping Wang, Yuanfei Li

“…By extending the data at the finite end forward, we can establish the continuous dependence on the perturbation of base data.…”
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Real time structural search of the Protein Data Bank. by Dmytro Guzenko, Stephen K Burley, Jose M Duarte

“…This fact, together with recent growth of oligomeric structures in the Protein Data Bank (PDB), demands more efficient approaches to oligomeric assembly alignment/retrieval. …”
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Data structures for deductive simulation of HDL conditional operators by Євгеній Шовковий, Олена Гриньова, Сергій Удовенко, Лариса Чала

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Deep structure of South Kamchatka according to geophysical data by Yu. F. Moroz, L. I. Gontovaya

“…Comprehensive analysis of the geological and geophysical data shows differences in the structure of the crust and upper mantle in North and South Kamchatka and common features of the deep structures of South Kamchatka and the Kuril Islands. …”
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How to structure data from an IoT monitoring network by Ziwen Yu

“…This publication discusses the typical attributes in IoT monitoring networks and presents a data structure that outlines best practices in organizing data. …”
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A Model-driven Approach to Data Structure Conceptualization by Sonja Ristić, Slavica Kordić, Milan Čeliković, Vladimir Dimitrieski, Ivan Luković

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Model for developing educational games based on data from dictionary structure by Josip Mihaljević, Lana Hudeček

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Beyond contrastive learning: adaptive graph representations with mutual information maximization for blockchain and structured data by Yifeng Zhang, Qianqian Ren, Yourong Chen, Meng Han

“…Abstract Graph representation learning has emerged as a powerful approach for modeling structured data across diverse domains, including social networks, biochemical interactions, and financial transaction systems. …”
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Identifying the diagnostic gap of tardive dyskinesia: an analysis of semi-structured electronic health record data by Kira Griffiths, Yida Won, Zachery Lee, Lu Wang, Christoph U. Correll, Rashmi Patel

“…Results Altogether, 1,301 (4.0%) patients had either description of abnormal movements associated with TD (n=691) or documented TD (n=610) within semi-structured EHR data. Of those patients, only 64 (4.9%) had an ICD-TD diagnosis in structured EHR data. …”
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Federated Learning in Healthcare: A Benchmark Comparison of Engineering and Statistical Approaches for Structured Data Analysis by Siqi Li, Di Miao, Qiming Wu, Chuan Hong, Danny D’Agostino, Xin Li, Yilin Ning, Yuqing Shang, Ziwen Wang, Molei Liu, Huazhu Fu, Marcus Eng Hock Ong, Hamed Haddadi, Nan Liu

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Semi-automatic staging area for high-quality structured data extraction from scientific literature by Luca Foppiano, Tomoya Mato, Kensei Terashima, Pedro Ortiz Suarez, Taku Tou, Chikako Sakai, Wei-Sheng Wang, Toshiyuki Amagasa, Yoshihiko Takano, Masashi Ishii

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A Structured Data Model for Asset Health Index Integration in Digital Twins of Energy Converters by Juan F. Gómez Fernández, Eduardo Candón Fernández, Adolfo Crespo Márquez

“…First, the proposed AHI methodology is introduced, and after a structured data model specifically designed, orientated to a basic and economic cloud implementation architecture. …”
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Redefining comorbidity understanding in rheumatoid arthritis through novel approaches using real-world data by Diego Benavent, Chamaida Plasencia-Rodríguez

“…Meanwhile, natural language processing (NLP) and artificial intelligence (AI) image analysis can bridge the gap between structured and unstructured data, by extracting meaningful information from unstructured fields such as free text or imaging. …”
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SAFlex: A structural alphabet extension to integrate protein structural flexibility and missing data information. by Ikram Allam, Delphine Flatters, Géraldine Caumes, Leslie Regad, Vincent Delos, Gregory Nuel, Anne-Claude Camproux

“…Secondly, our new algorithm deals with the missing data in the protein structure files (concerning more than 75% of the proteins from the Protein Data Bank) in a rigorous probabilistic framework. …”
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Structuring a textile knitting dataset for machine learning and data mining applicationsMendeley Data by Toufique Ahmed, Abu Saleh Muhammad Junayed

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Data of the crystal structure of xylose isomerase from Streptomyces avermitilisProtein Data BankZENODO by Ki Hyun Nam

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Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs by Domenico Paolo, Carlo Greco, Alessio Cortellini, Sara Ramella, Paolo Soda, Alessandro Bria, Rosa Sicilia

“…Specifically, this study addresses Overall Survival (OS) in Non-Small Cell Lung Cancer (NSCLC) using unstructured EHRs data collected from an Italian clinical centre encompassing 838 records from 231 lung cancer patients. …”
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Using large language models to extract plant functional traits from unstructured text by Viktor Domazetoski, Holger Kreft, Helena Bestova, Philipp Wieder, Radoslav Koynov, Alireza Zarei, Patrick Weigelt

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