Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure by Chunzhong Li, Chenglan Liu, Wenliang Ju, Yuanquan Zhong, Yonghui Li

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Modal Identification and Finite Element Model Updating of Flexible Photovoltaic Support Structures Using Multi-Sensor Data by Mingfeng Huang, Chen Yang, Kang Cai, Xianzhe Li

“…In this study, field modal testing of a flexible PV support structure was conducted, and high-order modal properties were identified from multi-sensor data. …”
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New data on the structure and motion of the ice sheet in the area of a runway of the Novolazarevskaya Reserch Station (East Antarctica) by A. S. Boronina, M. P. Kashkevich, S. V. Popov, E. M. Mikhailov, A. E. Druzhin

“…The central part of the runway appears to be the most complex in structure, demonstrating relatively high deformations in the marginal parts and characterized by large vertical structures in the glacier. …”
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Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education by Ashish Garg, K. Nisumba Soodhani, Ramkumar Rajendran

“…Our research investigates the impact of structured prompt training on students' learning in data analysis and programming. …”
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THE STRUCTURE AND HISTORY OF ABYSSAL HILLS OF THE NORTH-WESTERN PACIFIC PLATE FROM CONTINUOUS SEISMIC PROFILING AND STRATIGRAPHIC DATA by V. L. Lomtev

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Local structure of solid and liquid gold probed by reverse Monte Carlo analysis of X-ray absorption data by Nodoka Hara, Fabio Iesari, Toshihiro Okajima, Andrea Di Cicco

“…The increase in computational capabilities of modern computers has allowed us to develop new accurate methods for EXAFS (extended X-ray absorption fine structure) data-analysis. In particular, the RMC-GNXAS package provides models of the three-dimensional structure applying the reverse Monte Carlo (RMC) method to EXAFS of condensed or molecular systems. …”
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Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification by Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan

“…The primary objective is to determine whether converting structured data into text format improves model accuracy. …”
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Automated Collection Planning for Civilian and Commercial Satellite Imagery, and Definition and Exploitation of the Collection Asset Specification Data Structure by Jeff Secker, Katerina Biron, Dany Dessureault, Pierre Lamontagne, Rodney Rear

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mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. by Hannes Doerfler, Xiaoliang Sun, Lei Wang, Doris Engelmeier, David Lyon, Wolfram Weckwerth

“…Pathways are extracted directly from the data and putative novel structures can be identified. …”
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Data of vegetation structure metrics retrieved from airborne laser scanning surveys for European demonstration sitesZenodo by W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

“…It supports landscape-scale habitat analysis and contributes to the standardization of vegetation metrics from ALS data for site-specific ecological monitoring (e.g., Natura 2000). …”
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Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans. by Mei Zhan, Matthew M Crane, Eugeni V Entchev, Antonio Caballero, Diana Andrea Fernandes de Abreu, QueeLim Ch'ng, Hang Lu

“…Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. …”
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An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures by Xue-Yang Pei, Hai-Bin Huang, Peng Cao

Subjects: “…structural health monitoring…”
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Structuring data analysis projects in the Open Science era with Kerblam! [version 1; peer review: 2 approved] by Federico Alessandro Ruffinatti, Luca Munaron, Luca Visentin

“…Background Structuring data analysis projects, that is, defining the layout of files and folders needed to analyze data using existing tools and novel code, largely follows personal preferences. …”
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Enhancing Standardized and Structured Recording by Elderly Care Physicians for Reusing Electronic Health Record Data: Interview Study by Charlotte A W Albers, Yvonne Wieland-Jorna, Martine C de Bruijne, Martin Smalbrugge, Karlijn J Joling, Marike E de Boer

“…The findings will be used to formulate recommendations aimed at enhancing standardized and structured data recording for the reuse of EHR data. …”
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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

“…However, many real-world data sets, such as those from spacecraft monitoring the solar wind, contain gaps, which inevitably corrupt the statistics. …”
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Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome by Filip Miljković, Jürgen Bajorath

“…Limitations & next steps: PC and PCP data structures capture structure–promiscuity relationships. …”
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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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TRsv: simultaneous detection of tandem repeat variations, structural variations, and short indels using long read sequencing data by Shunichi Kosugi, Chikashi Terao

“…Abstract Tandem repeat copy number variations (TR-CNVs), structural variations (SVs), and short indels have been responsible for many diseases and traits, but no tools exist to distinguish and detect these variants. …”
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Structure and nodal points of Smart City infrastructure by Magdalena Grochulska-Salak, Tomasz Wężyk

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Railway traffic characterisation data based on weigh-in-motion and machine learning: A case study in PortugalZenodo by Idilson A. Nhamage, Cláudio S. Horas, José A. Campos e Matos, João Poças Martins

Subjects: “…Railway traffic data…”
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