Integrated structural analysis for geothermal exploration: A new protocol combining remote sensing and aeromagnetic geophysical data by Jawad Rafiq, Israa S. Abu-Mahfouz, Konstantinos Chavanidis, Pantelis Soupios

“…The approach integrates surface data from remote sensing and data from airborne magnetic geophysical surveys that provide information on the subsurface structures, to analyze structural lineament density analysis, orientation, and high permeable zones, and assess geothermal potential. …”
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Debiasing Structure Function Estimates from Sparse Time Series of the Solar Wind: A Data-driven Approach by Daniel Wrench, Tulasi N. Parashar

“…Structure functions (SFs), which quantify the moments of increments of a stochastic process, are essential complementary statistics to power spectra for analyzing the self-similar behavior of a time series. …”
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Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data by Jing Liu, Xinping Zhang, Kai Huang, Yuqi Wei, Xiao Guan

“…The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. …”
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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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Crashworthiness simulation dataset of re-entrant crash box with combined in-plane and out-of-plane filling structureMendeley Data. by Arif Rochman Fachrudin, Moch. Agus Choiron, Anindito Purnowidodo, Yudy Surya Irawan

“…This article presents a dataset generated from finite element simulations of square aluminum crash box with various re-entrant infill structures. The configurations include in-plane, out-of-plane and combined in-plane and out-of-plane geometries. …”
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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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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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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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A Tertiary lymphoid structures-based pathological score predicts survival and recurrence in colorectal Cancer patients by Marion Le Rochais, Marie Morvan, Servane Bouzeloc, Jean-Baptiste Nousbaum, Matthieu Guillard, Pierre Le Noac'h, Soizic Garaud, Arnaud Uguen

“…The immune response within the tumor microenvironment (TME), especially the presence of tertiary lymphoid structures (TLS), plays a critical role in prognosis. …”
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Innovative device for crack monitoring and deflection analysis in structures: Improved accuracy, safety and efficiency by Alfonso C. Marcos-Romero, Laura Mendoza-Cerezo, Antonio Macías-García, Noelia Rebollo Muñoz, Jesús M. Rodríguez-Rego

“…It is of the utmost importance to ensure the structural integrity of buildings in order to guarantee the safety of their occupants. …”
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Knowledge Transfer between Oscillators and Real Vibrating Structures to Enrich Dynamic Monitoring Datasets by Valeria Cavanni, Rosario Ceravolo, Gaetano Miraglia

“… Transfer learning (TL) techniques can be exploited in engineering structures to overcome the main limit of the data-driven approaches for dynamic monitoring, namely the lack of a labelled dataset for some structural configuration of the monitored systems. …”
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