Numerical simulation of snow deposition around structural snow fences by K. Yu. Litvintsev, A. A. Gavrilov, A. A. Dekterev, Yu. N. Zaharinsky, A. A. Minakov, S. A. Filimonov, K. A. Finnikov

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Interpretive structural modeling of the implementation of the comprehensive scientific map of Iran by Bahram Akbari, Abouzar Alidadi Talkhestani, Mohammad Reza Navab Esfahani, Meysam Alipour

“…Purpose: The present study aims to present an "interpretive structural modeling of the implementation of the country's comprehensive scientific map." …”
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Local structural–functional coupling with counterfactual explanations for epilepsy prediction by Jiashuang Huang, Shaolong Wei, Zhen Gao, Shu Jiang, Mingliang Wang, Liang Sun, Weiping Ding, Daoqiang Zhang

“…Specifically, we first construct structural and functional connections using diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) data, subsequently organizing them into a multimodal brain network. …”
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Neuroadaptive changes in brain structural–functional coupling among pilots by Xi Chen, Qingbin Meng, Qingsong Song, Peiran Xu, Shicong Zhang, Donglin Huang, Qi Chu, Jiamin Fan, Cheng Luo, Xiuyi Li

“…However, prior research has predominantly focused on identifying structural and functional differences in the brain, while the relationship between structure and function remains insufficiently elucidated.MethodsThis study collected T1-weighted structural magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), and diffusion tensor imaging (DTI) data from 47 pilots and 38 matched controls. …”
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Structural basis for Retriever-SNX17 assembly and endosomal sorting by Amika Singla, Daniel J. Boesch, Ho Yee Joyce Fung, Chigozie Ngoka, Avery S. Enriquez, Ran Song, Daniel A. Kramer, Yan Han, Esther Banarer, Andrew Lemoff, Puneet Juneja, Daniel D. Billadeau, Xiaochen Bai, Zhe Chen, Emre E. Turer, Ezra Burstein, Baoyu Chen

“…Here, we provide biochemical, structural, cellular, and proteomic analyses of the SNX17-Retriever interaction. …”
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Exploring the predictive value of structural covariance networks for the diagnosis of schizophrenia by Clara S. Vetter, Clara S. Vetter, Clara S. Vetter, Annika Bender, Dominic B. Dwyer, Dominic B. Dwyer, Dominic B. Dwyer, Max Montembeault, Anne Ruef, Katharine Chisholm, Lana Kambeitz-Ilankovic, Linda A. Antonucci, Stephan Ruhrmann, Joseph Kambeitz, Marlene Rosen, Theresa Lichtenstein, Anita Riecher-Rössler, Rachel Upthegrove, Raimo K. R. Salokangas, Jarmo Hietala, Christos Pantelis, Christos Pantelis, Rebekka Lencer, Rebekka Lencer, Eva Meisenzahl, Stephen J. Wood, Stephen J. Wood, Paolo Brambilla, Paolo Brambilla, Stefan Borgwardt, Peter Falkai, Peter Falkai, Alessandro Bertolino, Nikolaos Koutsouleris, Nikolaos Koutsouleris, Nikolaos Koutsouleris, PRONIA Consortium

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Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection by Qifan Yang, Yu-Ang Chen, Yifan Shi

“…Specifically, a multi-view co-association matrix optimization objective function with doubly-stochastic constraints is first designed to capture the cross-view cluster structure. Then, a multi-view cluster structure guided one-class BLS-autoencoder (MOCBLSAEs) is proposed, which learns the discriminative patterns of normal traffic data by preserving the cross-view clustering structure while minimizing the intra-view sample reconstruction errors, thereby enabling the identification of unknown intrusion data. …”
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The 102–103° E geodivider in the modern lithosphere structure of Сentral Asia by Yu. G. Gatinsky, T. V. Prokhorova, D. V. Rundquist

“…According to our investigations, the 102–103° E geodivider is a regional geological-geophysical border that may be compared with the Tornquist Line, and, by its scale, with the Uralian and Appalachian fronts and some others large structures.…”
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Quantum chemical research of the molecular structure of 3,4-dicyanofuroxan by I. N. Kolesnikova, N. V. Lobanov, V. N. Lobanov, I. F. Shishkov

“…The equilibrium molecular structure of 3,4-dicyanofuroxan was refined by means of quantum chemical calculations using the Gaussian09 program. …”
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Learning Gaussian Bayesian Network from Censored Data Subject to Limit of Detection by the Structural EM Algorithm by Ping-Feng Xu, Shanyi Lin, Qian-Zhen Zheng, Man-Lai Tang

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Investigation of the Internal Structure of Hard-to-Reach Objects Using a Hybrid Algorithm on the Example of Walls by Rafał Brociek, Józef Szczotka, Mariusz Pleszczyński, Francesca Nanni, Christian Napoli

“…The article presents research on the application of computed tomography with an incomplete dataset to the problem of examining the internal structure of walls. The case of incomplete information in computed tomography often occurs in various applications, e.g., when examining large objects or when examining hard-to-reach objects. …”
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BACKGROUND OF THE ANATOMY OF PERITONEAL CARCINOMATOSIS. ANALYSIS OF LITERATURE AND SHAREHOLDERS DATA by R. Sh. Ishmuratova, Sh. R. Kzyrgalin, K. Sh. Gantsev, R. S. Minigazimov, S. V. Solomenny, L. V. Khalikova

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Structural Tectonic Scheme Creation Based on Seismic-Gravity Models and Isostasy Usage: Ural Case by Martyshko Petr, Ladovskii Igor, Byzov Denis, Tsidaev Aleksandr

“…They contain solution of non-linear (structural) inverse problem and the solution of the linear three-dimensional inverse problem taking note of the side sources. …”
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A structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model by Xiaoliang Jia, Guoyan Zhang, Zhiqiang Wang, Huacong Li, Jing Hu, Songlin Zhu, Caiwei Liu

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Applying a K-means model to TSD data to find categories for the structural assessment of flexible pavements by Mahdi Rahimi Nahoujy

“…Since 2018, the German Federal Highway Research Institute (BASt) has been using a traffic speed deflectometer (TSD) for measurements on network level to assess the structural condition of asphalt pavements. TSD collects a variety of data, such as deflections, temperature and slope values at each measuring point. …”
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Transfer Learning and Neural Network-Based Approach on Structural MRI Data for Prediction and Classification of Alzheimer’s Disease by Farideh Momeni, Daryoush Shahbazi-Gahrouei, Tahereh Mahmoudi, Alireza Mehdizadeh

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A dynamic early-warning method for bridge structural safety based on data reconstruction and depth prediction by Yanqing Men, Hu Li, Fengzhou Liu, Yongliang Huang, Mingxin Gao, Xiaohui Wang, Hao Xie, Jianxin Cao

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Detection and functional assessment of structural variants using whole-genome re-sequencing data in Nellore cattle by Natalia A. Marín-Garzón, Lucio F. M. Mota, Giovana Vargas, Leonardo M. Arikawa, Larissa F. S. Fonseca, Gerardo A. Fernandes Júnior, Roberto Carvalheiro, Lucia G. Albuquerque

“…Thus, this study aimed to detect structural variants using whole genome re-sequencing (WGS) data and identify positional candidate genes and quantitative trait loci (QTL) overlapping the most frequent SV regions in Nellore cattle. …”
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Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties by Fredi Alegría, Eladio Martínez, Claudia Cortés-García, Quirino Estrada, Andrés Blanco-Ortega, Mario Ponce-Silva

Subjects: “…structural damage…”
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Barriers to the Adoption of Big Data Analytics in Saudi Arabia’s Manufacturing Sector: An Interpretive Structural Modeling Approach by Almuhannad S. Alorfi, Naif Alsaadi

“…However, there exist several barriers that undermine the successful adoption of big data analytics in these industries. This paper presents a structural analysis of the barrier to big data analytics adoption in manufacturing industries. …”
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