THE ADVANTAGES OF THE DISTRIBUTION FUNCTION AS A METHOD OF GRAPHICAL REPRESENTATION OF THE ECONOMIC STRUCTURE OF SOCIETY by V. A. Kapitanov, A. A. Ivanova, A. Yu. Maksimova

“…The presence of features in the economic structure of society must be reflected in the qualitative behavior of the curves. …”
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Detecting Urban Mobility Structure and Learning Functional Distribution with Multi-Scale Features by Jia Li, Chuanwei Lu, Haiyan Liu, Jing Li, Dewei Zhou, Qingyun Liu

“…However, existing methods have limitations in handling complex urban data and capturing global spatial structure features. …”
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Retracted: Internet of Things Health Detection System in Steel Structure Construction Management by Qinglin Liu, Yongjiang Zhu, Xiongzhou Yuan, Jian Zhang, Rui Wu, Qianwen Dou, Song Liu

“…It is concluded that the time series model established in this study can objectively reflect the change trend and law of strain data, has certain prediction accuracy, and has certain value significance for monitoring data analysis and construction management of steel building structures.…”
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An open-source platform for structured annotation and computational workflows in digital pathology research by Luca Lianas, Mauro Del Rio, Luca Pireddu, Oskar Aspegren, Francesca Giunchi, Michelangelo Fiorentino, Simone Leo, Renata Zelic, Per Henrik Vincent, Nicolas Destefanis, Daniela Zugna, Lorenzo Richiardi, Andreas Pettersson, Olof Akre, Francesca Frexia

“…However, currently available open-source annotation tools typically employ single-label approaches that provide a flat representation of whole-slide images (WSI), limiting their ability to capture the complexity of the diagnosis-significant elements in a detailed and structured way. Furthermore, the difficulty of strictly following precise review protocols and lack of provenance tracking during annotation processes can result in high variability and limit reproducibility and reusability of the collected data. …”
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Structural Feedback Analysis Based on Monitoring Data from Units with Different Spiral Case Embedding Methods at Three Gorges Hydropower Station by CHEN Qin, SU Hai-dong, DUAN Guo-xue, CUI Jian-hua, ZHOU Shi-hua

“…As the supporting system of hydroelectric generators, both the steel spiral cases and surrounding reinforced concrete structures have significant differences in construction processes and structural bearing characteristics due to different embedding methods. …”
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A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses. by William T Harvey, Vinny Davies, Rodney S Daniels, Lynne Whittaker, Victoria Gregory, Alan J Hay, Dirk Husmeier, John W McCauley, Richard Reeve

“…We show that incorporating protein structural data into variable selection helps resolve ambiguities arising due to correlated signals, with the proportion of variables representing haemagglutinin positions decisively included, or excluded, increased from 59.8% to 72.4%. …”
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Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning by Alfredo Ordinola, David Abramian, Magnus Herberthson, Anders Eklund, Evren Özarslan

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Investigation into the Mechanism of the Impact of Sunlight Exposure Area of Urban Artificial Structures and Human Activities on Land Surface Temperature Based on Point of Interest Data by Yuchen Wang, Yu Zhang, Nan Ding

Subjects: “…urban artificial structures…”
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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

“…Based on this algorithm, correlation considerations can be performed on the data structure, the measured variables, and the diagnostic parameters. …”
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The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction by Chenyue Zhang, Qinxin Wang, Yiyang Li, Anqi Teng, Gang Hu, Qiqige Wuyun, Wei Zheng

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Calculation of Water Saturation of Dolomite Reservoir Based on Multi-Pore Structure Model by Xinzhong Qi, Xingneng Wu, Yong Ai, Ruokun Huang, Wenxing Duan, Yaqi Liu

“…The total conductivity of the rock is established by the parallel combination of the effective components to establish the porous structure response equation, the equation is fitted by the rock electrical experimental data, and the parameters such as the fracture porosity index (mj) and the interconnected void porosity (ml) are calculated. …”
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From sequence to protein structure and conformational dynamics with artificial intelligence/machine learning by Alexander M. Ille, Emily Anas, Michael B. Mathews, Stephen K. Burley

“…The 2024 Nobel Prize in Chemistry was awarded in part for de novo protein structure prediction using AlphaFold2, an artificial intelligence/machine learning (AI/ML) model trained on vast amounts of sequence and three-dimensional structure data. …”
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Deep nested U-structure network with frequency attention for building semantic segmentation by Khaled Moghalles, Zaid Al-Huda, Dalal AL-Alimi, Yeong Hyeon Gu, Mugahed A. Al-antari

“…We have introduced a novel approach to address these issues: an end-to-end residual U-structure embedded within a U-Net, enhanced by a frequency attention module and a hybrid loss function. …”
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Local Scouring Visualization of Bed Channel Surface in Hydraulic Structure Using Surfer by Tifarah Dayansabila Paramadita, Nadia Azarine, Aburizal Azhar, Didit Puji Riyanto

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Research on Structure and Characteristics of Gear System of Crossflow in Flow Domain of Reactor Core by CHEN Guangliang, ZHANG Hanqi, TAO Wenquan

“…However, in traditional research, the states of flow resistance, thermal resistance, flow mixing and other states are measured by the macroscopic integration of lines, surfaces and volumes, and the fine data of tens of millions or hundreds of millions of computing grids are mostly converted into hundreds or thousands of sets of average data, the physical state is reduced from three-dimensional to two-dimensional or one-dimensional state, and the spatial resolution is reduced from submillimeter to decimeter or lower, and the fine data cannot be effectively and fully utilized. …”

Analysis and selection of the structure of a multiprocessor computing system according to the performance criterion by G. V. Petushkov, A. S. Sigov

“…Analysis of the various architectures of computing systems (CSs) used in recent decades has allowed us to identify the most common structures. One of the key features is the use of mass-produced equipment to create data processing subsystems (for example, multicore processors and high-capacity semiconductor memory), as well as network equipment to build communication subsystems. …”
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Limitations of risk-based artificial intelligence regulation: a structuration theory approach by Lily Ballot Jones, Julia Thornton, Daswin De Silva

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On the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem by Eric Sakk, Ayanna Alexander

“…In this context, neural network mappings are constructed between protein training set sequences and their assigned structure classes in order to analyze the class membership of test data and associated measures of significance. …”
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Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies. by Nicholas Furnham, Ian Sillitoe, Gemma L Holliday, Alison L Cuff, Roman A Laskowski, Christine A Orengo, Janet M Thornton

“…In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. …”
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HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors by Viet-Khoa Tran-Nguyen, Ulrick Fineddie Randriharimanamizara, Olivier Taboureau

“…Multiple structure-based artificial intelligence (AI) binary classifiers for predicting hERG inhibitors were developed, employing, as descriptors, protein–ligand extended connectivity (PLEC) fingerprints fed into random forest, extreme gradient boosting, and deep neural network (DNN) algorithms. …”
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