Does Urban Polycentric Structure Improve Carbon Emission Efficiency? A Spatial Panel Data Analysis of 279 Cities in China from 2012 to 2020 by Shihan Zhang, Yanxin Xue, Shuzhen Jin, Zhenghong Chen, Suiying Cheng, Wei Wang

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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

“…To address the issue of insufficient prediction accuracy in traditional GM(1,1) models caused by significant nonlinear fluctuations in time-series data for ancient building structural health monitoring, this study proposes a wavelet decomposition-based GM(1,1)-BP neural network coupled prediction model. …”
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Exploration of 3D Coal Seam Geological Modeling Visualization and Gas Content Prediction Technology Based on Borehole Data by Xiangfeng Zhao, Tianxuan Hao, Huiyan Feng, Fan Li, Xu Li

“…ABSTRACT The geological structure of coal mines and the precise prediction of coal seam gas content are key factors in creating the transparent working face, and they also represent an important aspect of intelligent coal mining. …”
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Predicting the impact of public events and mobility in Smart Cities by Elena Bellodi, Riccardo Zese, Carlo Petrovich, Angelo Frascella, Francesco Bertasi

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Support of Home-Based Structured Walking Training and Prediction of the 6-Minute Walk Test Distance in Patients With Peripheral Arterial Disease Based on Telehealth Data: Prospective Cohort Study by Fabian Wiesmüller, Andreas Prenner, Andreas Ziegl, Gihan El-Moazen, Robert Modre-Osprian, Martin Baumgartner, Marianne Brodmann, Gerald Seinost, Günther Silbernagel, Günter Schreier, Dieter Hayn

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Physics-Informed Neural Networks for Structural Mechanics and Construction: Modeling the Deflection of a Single-Span Beam Physics-Informed Neural Networks by F. N. Zakharov, Qian Jie, Xu Yi

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A Bibliometric Analysis of International Structural Engineering Standards Using VOS Viewer by Andri Irfan Rifai, Darius Angtony, Ade Jaya Saputra, Joewono Prasetijo

“…The outcome indicates that “standards” and “structure” are still trending topics in global discourse. …”
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Structural and functional insights into the pilotin-secretin complex of the type II secretion system. by Shuang Gu, Saima Rehman, Xiaohui Wang, Vladimir E Shevchik, Richard W Pickersgill

“…Gram-negative bacteria secrete virulence factors and assemble fibre structures on their cell surface using specialized secretion systems. …”
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Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures by Mathilde Papillon, Sophia Sanborn, Johan Mathe, Louisa Cornelis, Abby Bertics, Domas Buracas, Hansen J Lillemark, Christian Shewmake, Fatih Dinc, Xavier Pennec, Nina Miolane

“…The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern machine learning increasingly encounters richly structured data that is inherently non-Euclidean. …”
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Geotectonics and geodynamics of structures of the stretching of continents and oceans, communications with rudo petroleum potential and seismicity by Vladimir Mikhaylovich Harchenko, Galina Valentinovna Kolyadova, Boris Fyodorovich Galaj, Marina Anatolievna Beytuganova

“…To assess the concepts about the structures of the stretching assembled factual material: data structures of stretching of various ranks in the Eastern and Western Ciscaucasia, and the Red Sea. …”
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The political structures and its influences in sport development in the state of Paraná, Brazil: the case of athletics by Lenamar Fiorese Vieira, José Luiz Lopes Vieira

“…Informer's record, semi-structured interview, research diary and documents, were used to collect the data. …”
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Validation of modeling the delamination process of composite panels of load-bearing elements of aircraft structures by I. S. Belousov

“…Both in the manufacture and operation of structural elements made of layered composite materials, interlayer defects may occur upon impact as a result of operation or violation of manufacturing technology, which significantly reduces the strength characteristics of such structures. …”
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Identifying and Forecasting Recurrently Emerging Stock Trend Structures via Rising Visibility Graphs by Zhen Zeng, Yu Chen

“…This approach produces graph representations that capture direction-sensitive market dynamics and facilitate the extraction of meaningful topological features from price data. By applying the WL kernel, RVGWL quantifies structural similarities between graph-transformed time series, enabling the identification of structurally similar preceding patterns and the probabilistic forecasting of their subsequent trajectories based on nine canonical trend templates. …”
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Ensemble refinement of mismodeled cryo-EM RNA structures using all-atom simulations by Elisa Posani, Pavel Janoš, Daniel Haack, Navtej Toor, Massimiliano Bonomi, Alessandra Magistrato, Giovanni Bussi

“…An analysis of all RNA-containing structures deposited in the Protein Data Bank reveals that this issue affects most cryo-EM structures in the 2.5–4 Å range. …”
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Post-Earthquake Fire Resistance in Structures: A Review of Current Research and Future Directions by Shahin Dashti, Barlas Ozden Caglayan, Negar Dashti

“…Key findings of current studies reveal that seismic damage, including spalling, cracking, and loss of fireproofing, substantially reduces the fire resistance of materials like steel and reinforced concrete, exacerbating structural vulnerabilities. Despite advancements, critical gaps persist in experimental data, probabilistic modeling, and comprehensive performance-based design guidelines for PEF scenarios. …”
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Lamb wave ultrasonic testing technology for diagnosis and prediction of hidden cracks in metal structures by Dawen Yao, Peiwen Meng, Shuqi Li, Jinggang Xu

“…Abstract In the field of traditional hidden crack detection in metal structures, detection technologies are often limited by low sensitivity and imprecise data analysis. …”
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Modeling Asymmetric Shift in the Threshold Voltage of MOS Structures under Thermal Field Treatment by O. V. Aleksandrov, N. N. Morozov

“…The conducted comparison of the data calculated by the developed model and the experimental data reported in literature for the time dependencies of the threshold voltage shift of MOS structures with positive and subsequent negative gate bias determined the range of binding energies, the characteristic dispersion energy, the concentrations of impurity ions and traps near the gate and the silicon substrate, and the width of the region of their localization. …”
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Improved machine learning framework for prediction of phases and crystal structures of high entropy alloys by Debsundar Dey, Suchandan Das, Anik Pal, Santanu Dey, Chandan Kumar Raul, Pritam Mandal, Arghya Chatterjee, Soumya Chatterjee, Manojit Ghosh

“…Within the dataset, 705 data were utilized to predict the crystal structures with the help of thermodynamics and electronic configuration as input features. …”
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Protein-ligand binding affinity prediction using multi-instance learning with docking structures by Hyojin Kim, Heesung Shim, Aditya Ranganath, Stewart He, Garrett Stevenson, Jonathan E. Allen

“…Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. …”
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A Case-Study-Based Comparative Analysis of Using Prefabricated Structures in Industrial Buildings by Abdelhadi Salih, Cynthia Changxin Wang, Rui Tian, Mohammad Mojtahedi

“…The prefabrication system has been used for years in industrial construction, resulting in better performance in regard to structure stability, the control of wastage, and the optimisation of construction time and cost. …”
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