Urban Viaduct Structural Health Monitoring: A Review of Wireless Sensor Approaches by Tianli Wang, Tong Cui, Xin Qi, Xintao Huan

“…In this paper, we review the full-chain methods of employing wireless sensor technology for urban viaduct structural health monitoring. By proposing a general wireless structural health monitoring approach as a framework, we first review the sensor types and wireless transmission technologies, then the data processing and modal identification methods, and finally the damage detection methods. …”
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Molecular structure data and modelling roadmap for optimized oxidized graphene quantum dot and epoxy interface and mechanical propertiesMendeley Data by Prathamesh Deshpande, Robert Chan-Jobe, Ozgur Keles

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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…ObjectiveStructural parameter identification based on swarm intelligent optimization methods has become one of the popular methods for finite element model modification. …”
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Damage Detection in Beam Structures Based on Frequency-Domain Analysis Methods for Nonlinear Systems by Wenbo Zhang, Xiaoyue Guo, Liangliang Cheng, Bo Zhang

“…To improve the accuracy of the Nonlinear Auto-Regressive with eXogenous inputs (NARX) model and reduce the impact of noise interference, we proposed a Multi-input Multi-output Forward Regression Orthogonal Least Squares (MFROLS) algorithm for processing multi-input multi-output data to identify the NARX model of the same structural system. …”
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DETERMINANTS OF STRUCTURAL DIMENSION OF DAILY BEHAVIOUR IN A TRADITIONAL AFRICAN CITY: A CASE STUDY OF ILORIN, NIGERIA by Moses Olutoyin ADEDOKUN

“…The study also shows clearly that the temporal structure of activity in Ilorin is different from what obtains in Western cities where there is flexibility in the usage of time. …”
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Knowledge and theme discovery across very large biological data sets using distributed queries: a prototype combining unstructured and structured data. by Uma S Mudunuri, Mohamad Khouja, Stephen Repetski, Girish Venkataraman, Anney Che, Brian T Luke, F Pascal Girard, Robert M Stephens

“…As we move towards personalized medicine, the need to combine unstructured data, such as medical literature, with large amounts of highly structured and high-throughput data such as human variation or expression data from very large cohorts, is especially urgent. …”
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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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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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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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Small language models enable rapid and accurate extraction of structured data from unstructured text: An example with plants and their specialized metabolites by Lucas Busta, Alan R. Oyler

“…Small language models (SLMs), however, also have potential in this area as they have smaller compute footprints and allow users to keep data in-house. Here, we quantitatively evaluate the ability of SLMs to: (i) score references according to project-specific relevance and (ii) extract and structuring data from unstructured sources (scientific abstracts). …”
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