Seasonal genetic variation and genetic structure of Spodoptera exigua in Liaoning Province, Northeast China: insights from 11 years of microsatellite data by Ming-Li Yu, Xian-Zhi Xiu, Jin-Yang Wang, Xin-Yi Cao, Fa-Liang Qin, Xing-Ya Wang, Li-Hong Zhou

“…To control this pest effectively, it is crucial to investigate its seasonal genetic variation and population genetic structure in northern China. Methods In this study, we used eight nuclear microsatellite loci to investigate the seasonal genetic variation and genetic structure of BAW in Shenyang, Liaoning Province, Northeast China, from 2012–2022, collected from a single location on Welsh onion. …”
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The glucose-lowering therapy structure in special groups of type 2 diabetes mellitus patients based on data from the Moscow region register by Inna V. Misnikova, Yulia A. Kovaleva, Mikhail А. Isakov, Alexander V. Dreval

“…BACKGROUND: Data of real clinical practice in diabetes mellitus (DM) register allow to evaluate features and trends in structure of glucose-lowering therapy (GLT). …”
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Data Assimilation Informed Model Structure Improvement (DAISI) for Robust Prediction Under Climate Change: Application to 201 Catchments in Southeastern Australia by Julien Lerat, Francis Chiew, David Robertson, Vazken Andréassian, Hongxing Zheng

Subjects: “…model structure…”
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A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles by Hua Yi Lin, Meng-Yen Hsieh

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PATIENTS WITH ATRIAL FIBRILLATION IN MULTIDISCIPLINARY HOSPITAL: STRUCTURE OF HOSPITALIZATION, CONCOMITANT CARDIOVASCULAR DISEASES AND DRUG TREATMENT (DATA OF RECVASA AF-TULA REGISTRY) by M. N. Valiakhmetov, T. A. Gomova, M. M. Loukianov, S. Yu. Martsevich, K. N. Nadejkina, M. N. Artemova, D. N. Jilin, E. E. Fedotova, A. V. Zagrebelnyy, E. V. Kudryashov, S. A. Boytsov

“…All patients with a diagnosis of AF in the patient's chart (n=1225) were included into the RECVAZA AF-Tula registry; that is 4.2% of 29018 patients hospitalized to the Tula Regional Clinical Hospital in 2013. The structure of the associated cardiovascular diseases, as well as drug therapy, was evaluated on the basis of data in the medical documentation.Results. …”
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Detachment‐Fault Structure Beneath the TAG Hydrothermal Field, Mid‐Atlantic Ridge, Revealed From Dense Wide‐Angle Seismic Data by Szu‐Ying Lai, G. Bayrakci, B. J. Murton, T. A. Minshull

“…We used dense wide‐angle seismic data to define TAG's detachment structure at a finer scale than has previously been possible. …”
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A comparative study of regression methods to predict forest structure and canopy fuel variables from LiDAR full-waveform data by P. Crespo-Peremarch, L.A. Ruiz, A. Balaguer-Beser

“…Regression methods are widely employed in forestry to predict and map structure and canopy fuel variables. We present a study where several regression models (linear, non-linear, regression trees and ensemble) were assessed. …”
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Structure of snow-­ice dams of the outburst lakes in the Broknes Peninsula (Larsemann Hills, East Antarctica) based on ground­penetrating radar data by S. D. Grigoreva, E. R. Kiniabaeva, M. R. Kuznetsova, S. V. Popov, M. P. Kashkevich

“…During the summer field season of the 65th Russian Antarctic Expedition a research aimed at studying the structure of the snow-­ice dams of the Lakes Progress and Discussion (Larsemann Hills, East Antarctica), which are characterized with annual outburst floods, was carried out. …”
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A nonparametric approach for detecting urban polycentric spatial structure in China using remote sensing nighttime light and point of interest data by Linlin Jiang, Yizhen Wu, Junru Wang, Huiran Han, Kaifang Shi

“…Effectively identifying urban polycentric spatial structure (UPSS) is essential for data-driven evaluation of urban performance, and it serves as a scientific basis for urban spatial planning. …”
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Infrastructure Lifecycle Corrosion Management Using AI Analytics and Digital Twins by Bilal Ayyub, Karl Stambaugh

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Index-Based Neural Network Framework for Truss Structural Analysis via a Mechanics-Informed Augmented Lagrangian Approach by Hyeonju Ha, Sudeok Shon, Seungjae Lee

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A Data-Driven Analysis of Electric Vehicle Adoption Barriers in the Philippines: Combining SEM and ANNs by Charmine Sheena R. Saflor, Klint Allen Mariñas, Ma. Janice Gumasing, Jazmin Tangsoc

“…This study investigates the factors influencing the adoption of electric vehicles in the Philippines, focusing on key barriers through an integrated approach using machine learning and structural equation modeling (SEM). Specifically, artificial neural networks (ANNs) and SEM are employed to analyze data from online surveys and the existing literature, identifying the critical obstacles that impact consumer acceptance. …”
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Limit Theorems for Kernel Regression Estimator for Quasi-Associated Functional Censored Time Series Within Single Index Structure by Said Attaoui, Oum Elkheir Benouda, Salim Bouzebda, Ali Laksaci

“…In this paper, we develop kernel-based estimators for regression functions under a functional single-index model, applied to censored time series data. By capitalizing on the single-index structure, we reduce the dimensionality of the covariate-response relationship, thereby preserving the ability to capture intricate dependencies while maintaining a relatively parsimonious form. …”
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ABOUT DATA MODELING SUBJECT DOMAINS PRACTICE-ORIENTED DIRECTION FOR UNIVERSAL SYSTEM OF STORAGE AND PROCESSING DATA by L. V. Rudikova, E. V. Zhavnerko

Subjects: “…data warehouse…”
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Distributed energy sharing algorithm for Micro Grid energy system based on cloud computing by Wenwei Su, Yan Shi

Subjects: “…Data Structures…”
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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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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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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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