Tendon Anomaly Identification in Prestressed Concrete Beams Based on an Advanced Monitoring MEMS and Data-Driven Detection of Structural Damage by Giorgio de Alteriis, Giulio Mariniello, Tommaso Pastore, Alessia Teresa Silvestri, Giuseppe Augugliaro, Ida Papallo, Canio Mennuti, Antonio Bilotta, Rosario Schiano Lo Moriello, Domenico Asprone

“…The integration of MEMS sensors into structural health monitoring (SHM) systems offers a promising approach to long-term structural maintenance, especially in large-scale infrastructure. …”
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REGIONAL STRUCTURAL‐TECTONIC ZONING OF THE UPPER CRUST OF TRANSBAIKALIA BASED ON SEISMOGRAVITATIONAL DATA ALONG REFERENCE PROFILE 1‐SB by V. D. Suvorov, E. A. Melnik, E. V. Pavlov, A. S. Salnikov

“…Upper crust features revealed from seismic data agree with known geological structures, this indicating the basic applicability of refraction surveys to tectonically complex areas with 7 to 10 km wide low‐angle dipping fault zones between blocks marked by velocity anomalies to depths of 4–6 km. …”
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Detection of Structural Control on Formation Water Quality, in Hemrin Oilfield, northern Iraq, Using Lineament Analysis and Hydrochemical Data by Faraj Ahmed Al-Sulaiman, Sameer Shaker Abbas Al Fahdawi, Sabbar Abdullah Saleh Al Qaisy

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Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences by Julia Walsh, Jonathan Cave, Frances Griffiths

“…ObjectiveThe study aims to (1) investigate how combining unsupervised natural language processing (NLP) and corpus linguistics can explore patient perspectives from a large unstructured dataset of modafinil experiences, (2) compare findings with Cochrane meta-analyses on modafinil’s effectiveness, and (3) develop a methodology for analyzing such data. …”
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A Novel Skeletonization Algorithm for Topologically Complex Structures: Comparative Analysis and Application to Renal Arterial Trees by Katarzyna Heryan, Stefan-Daniel Caliman

“…These datasets pose challenges due to the complexity of the vascular tree, making it difficult to convert raw <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-CT data into meaningful representations. Without proper reconstruction, skeletonization, and graph representation, raw <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-CT data remains an unstructured point cloud, unsuitable for quantitative analysis. …”
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Linearity of Structure Kernels in Main-sequence and Subgiant Solar-like Oscillators by Lynn Buchele, Earl P. Bellinger, Saskia Hekker, Sarbani Basu

“…With the high-precision frequencies obtained using data from the Kepler mission, it has now become possible to study other solar-like oscillators using structure inversions, including both main-sequence and subgiant stars. …”
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SuperBand: an Electronic-band and Fermi surface structure database of superconductors by Tengdong Zhang, Chenyu Suo, Yanling Wu, Xiaodan Xu, Yong Liu, Dao-Xin Yao, Jun Li

“…Abstract In comparison to simpler data such as chemical formulas and lattice structures, electronic band structure data provide a more fundamental and intuitive insight into superconducting phenomena. …”
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Re-evaluation of the stratigraphy, structural, and depositional environment of Kolmani field, Gongola sub-basin, northeast Nigeria using outcrop data, ditch cutting data, and well log data for enhanced hydrocarbon exploration by Chekwube Nnamdi Didi, Olawale Olakunle Osinowo, Okey Eliseus Akpunonu, Musa Bappah Usman

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Fine-tuning of language models for automated structuring of medical exam reports to improve patient screening and analysis by Luis B. Elvas, Rafaela Santos, João C. Ferreira

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Network controllability mediates the relationship between rigid structure and flexible dynamics by Shi Gu, Panagiotis Fotiadis, Linden Parkes, Cedric H. Xia, Ruben C. Gur, Raquel E. Gur, David R. Roalf, Theodore D. Satterthwaite, Dani S. Bassett

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Research on real-world knowledge mining and knowledge graph completion (II): Methods and pro-gress of information extraction from unstructured electronic medical records by Si-Yu YAN, Xu-Hui LI, Mu-Kun CHEN, Hai-Feng ZHU, Jie-Jun TAN, Kuang GAO, Yong-Bo WANG, Qiao HUANG, Xiang-Ying REN, Ying-Hui JIN, Xing-Huan WANG

Subjects: “…unstructured data…”
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Change probability-aware graph for multimodal change detection by Te Han, Yuqi Tang, Yuzeng Chen, Yuqiang Guo, Bin Zou, Huihui Feng

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Biomedical Scholarly Article Editing and Sharing using Holistic Semantic Uplifting Approach by Asim Abbas, Steve Fonin Mbouadeu, Fazel Keshtkar, Joan DeBello, Syed Ahmad Chan Bukhari

Subjects: “…structured data…”
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Innovation-Based Research Using Structural Flexibility and Acceptance Model (SFAM) by   Solimun, Adji Achmad Rinaldo Fernandes

“…The research objectives are as follows: (1) Develop a solid structural model assuming normality and homoscedasticity. (2) Obtain the property estimator of the flexible and robust SFAM structural model. (3) Obtaining hypothesis testing of each relationship built from the flexible and strong SFAM structural model. …”
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From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision supportResearch in context by Sijm H. Noteboom, Eline Kho, Maria Galanty, Clara I. Sánchez, Frans C.P. ten Bookum, Denise P. Veelo, Alexander P.J. Vlaar, Björn J.P. van der Ster

“…Here, we showcase a successful example of a data pipeline to efficiently move patient data to the cloud environment for structured storage. …”
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Civil structural health monitoring and machine learning: a comprehensive review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…More robust prediction models may be produced by combining test data collected in the laboratory or field with ML. …”
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Civil Structural Health Monitoring and Machine Learning: A Comprehensive Review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…More robust prediction models may be produced by combining test data collected in the laboratory or field with ML. …”
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High earnings through firm influence: the role of hierarchical structures in public procurement by Niclas Frederic Sturm, Cristian Candia, Bruno Damásio, Flávio L. Pinheiro

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A structural biology compatible file format for atomic force microscopy by Yining Jiang, Zhaokun Wang, Simon Scheuring

“…Abstract Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. …”
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Advancing Structural Health Monitoring with Deep Belief Network-Based Classification by Álvaro Presno Vélez, Zulima Fernández Muñiz, Juan Luis Fernández Martínez

“…In recent years, deep learning techniques have emerged as powerful tools for analyzing the complex data generated by SHM systems. This study investigates the use of deep belief networks (DBNs) for classifying structural conditions before and after retrofitting, using both ambient and train-induced acceleration data. …”
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