NEW DATA ON THE GEOLOGICAL STRUCTURE OF THE SYNNYR ULTRA-K INTRUSIVE FORMATION by S. A. Smyslov, A. E. Kayukov, A. O. Bystritsky, A. N. Sokolova, I. A. Sotnikova, A.  Yu. Rytsk

“…An extensive complex of geological and geochemical studies has been carried out, including exploratory drilling, which was carried out on the massif for the first time. The data obtained made it possible to significantly change the idea of the structure of the massif, including a different look at the regularities of the placement of potash-alumina ores, significantly increasing the ore potential and the reliability of its assessment. …”
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Methodologies for the formation of structures of information systems for storing and analyzing patient data by Z. A. Shogenova, D. А. Krymshokalova, F. R. Ketova, F. H. Dzamikhova

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Disassembling-Based Structural Damage Detection Using Static Measurement Data by Eun-Taik Lee, Hee-Chang Eun

“…Damage detection methods can be classified into global and local approaches depending on the division of measurement locations in a structure. The former utilizes measurement data at all degrees of freedom (DOFs) for structural damage detection, while the latter utilizes data of members and substructures at a few DOFs. …”
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Intra-BRICS Trade: A Panel Data Analysis with Structural Breaks by Alper Yılmaz

“…For this purpose, we employed the Westerlund and Edgerton cointegration approach to check for cointegration under structural breaks and the procedure for the asymmetric Granger non-causality test to assess the causal relationship between the custom tariff and export variables of BRICS countries with regard to the panel data methodology for the 2000-2020 period using annual data. …”
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Structuring Multidimensional Data in the Study of the Development of Information Society in Russian Regions by N. M. Gabdullin, I. A. Kirshin

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Incorporating Prior Information in Latent Structures Identification for Panel Data Models by Yi Li, Xingxing Luo, Mengqi Liao

Subjects: “…latent structures…”
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Data-driven contact structures: From homogeneous mixing to multilayer networks. by Alberto Aleta, Guilherme Ferraz de Arruda, Yamir Moreno

“…Nonetheless, current models still lack a faithful representation of all possible heterogeneities and features that can be extracted from data. Here, we bridge a current gap in the mathematical modeling of infectious diseases and develop a framework that allows to account simultaneously for both the connectivity of individuals and the age-structure of the population. …”
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The method to develop classifi ers based on geometrical interpretation of data structure by М. N. Nessonova

“…It is based on metric approach to representations, generated by statistical methods of geometric interpreting of data structure.…”
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Structured Dynamics in the Algorithmic Agent by Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek

“…In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. …”
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A Sociotechnical Framework for Semantic Biomedical Content Authoring and Publishing by Steve Fonin Mbouadeu, Asim Abbas, Fazel Keshtkar, Iram Wajahat, Syed Ahmad Chan Bukhari

Subjects: “…structured data…”
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Social environment and brain structure in adolescent mental health: A cross-sectional structural equation modelling study using IMAGEN data. by Jessica Stepanous, Luke Munford, Pamela Qualter, Tobias Banaschewski, Frauke Nees, Rebecca Elliott, IMAGEN Consortium

“…The current study addressed that gap by applying structural equation modelling to IMAGEN data from adolescents aged 14 years (n = 1950). …”
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SemantiPack: An Efficient Real-World Data Compressor Using Structural and Semantic Metadata by Yoshiteru Nagata, Daiki Kohama, Yoshiki Watanabe, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

“…The exponential growth of Real-World Data (RWD), primarily collected from IoT sensors and spanning domains such as mobility, environment, and energy consumption, presents critical challenges due to its scale, heterogeneity, and structural variability. …”
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Ancestor regression in structural vector autoregressive models by Schultheiss Christoph, Ulmer Markus, Bühlmann Peter

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Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

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Semantic web ontology for structured knowledge representation and clinical decision support in eye diseases by Fatima Anjum, Fahad Maqbool, Muhammad Saad Razzaq, Hafiz Muhammad Faisal Shehzad, Shujaat Ali, Dilawar Shah, Muhammad Tahir, Muhammad Ilyas

“…Ontologies are used as excellent tools for organizing and managing complicated information due to their structured representations of domain knowledge and to make data more findable, accessible, interoperable, and reusable. …”
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Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation Framework by Diya Li, Yue Zhao, Zhifang Wang, Calvin Jung, Zhe Zhang

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Constructing Rasterized Covariates from LiDAR Point Cloud Data via Structured Query Language by Rory Pittman, Baoxin Hu

Subjects: “…structured query language (SQL)…”
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Enhancing structured data generation with GPT-4o evaluating prompt efficiency across prompt styles by Ashraf Elnashar, Jules White, Douglas C. Schmidt

Subjects: “…structured data generation…”
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UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

“…Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have utilized GCNs for data with Euclidean structures. such as image data and language data, and achieved good results, expanding the application scope of GCN. …”
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Advancing plant metabolic research by using large language models to expand databases and extract labeled data by Rachel Knapp, Braidon Johnson, Lucas Busta

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