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

“…A total of 35 LiDAR metrics were calculated, of which 28 represent vegetation structural attributes. These include vegetation height (seven metrics), vegetation cover (fourteen metrics), and vegetation vertical variability (seven metrics). …”
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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

“…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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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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SV-MeCa: an XGBoost-based meta-caller approach for structural variant calling from short-read data by Rudel Christian Nkouamedjo Fankep, Arda Söylev, Anna-Lena Kobiela, Jochen Blom, Corinna Ernst, Susanne Motameny

“…Abstract Background Calling structural variants (SVs), i.e., genomic alterations of $$\ge $$ 50bp, from whole genome short-read data remains challenging, as existing callers are known to lack accuracy and robustness. …”
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Structural Characteristics of the Turning End of the Kaiping Syncline and Its Influence on Coal Mine Gas by Zhenning Chen, Yanming Zhu, Hanyu Zhang, Jin Li

“…This study, drawing on previous theories, research, and practical coal mine production data, analyzes the structural characteristics of the Kaiping syncline, with particular emphasis on the structural differentiation at its northeastern uplifted end. …”
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State of India's Birds 2023: A framework to leverage semi‐structured citizen science for bird conservation by Ashwin Viswanathan, Karthik Thrikkadeeri, Pradeep Koulgi, Praveen J., Arpit Deomurari, Ashish Jha, Ashwin Warudkar, Kulbhushansingh Suryawanshi, M. D. Madhusudan, Monica Kaushik, Naman Goyal, Rajah Jayapal, Suhel Quader, Sutirtha Dutta, Tarun Menon, Vivek Ramachandran

“…Semi‐structured data are generated and uploaded by birdwatchers to citizen science platforms such as eBird. …”
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A Semi-Supervised Deep Network Embedding Approach Based on the Neighborhood Structure by Wenmao Wu, Zhizhou Yu, Jieyue He

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A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen by Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

“…Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. …”
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Auxo: A Temporal Graph Management System by Wentao Han, Kaiwei Li, Shimin Chen, Wenguang Chen

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STRUCTURAL-COMPOSITIONAL MODEL OF THE NYURBINSKAYA KIMBERLITE PIPE FORMATION (SREDNE-MARKHA AREA OF THE YAKUTIAN DIAMONDIFEROUS PROVINCE) by A. S. Gladkov, D. A. Koshkarev, A. V. Cheremnykh, F. João, M. A. Karpenko, M. V. Marchuk, I. A. Potekhina

“…Analysis of different faults and tectonic fracturing allowed to reconstruct the tectonic stress fields acting at the stage of the kimberlite body formation and to determine their occurrence sequence in time. The data obtained about regularities of the Nyurbinskaya pipe compositional structure and results of geologo-structural studies are combined in a single structural-compositional model of the deposit formation. …”
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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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Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies by Justin C. Quon, MD, Christopher P. Long, MD, William Halfpenny, MBBS, MEng, Amy Chuang, MS, Cindy X. Cai, MD, MS, Sally L. Baxter, MD, MSc, Vamsi Daketi, MS, Amanda Schmitz, BS, Neil Bahroos, MS, Benjamin Y. Xu, MD, PhD, Brian C. Toy, MD

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Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia. by Hastings Shamaoma, Paxie W Chirwa, Jules C Zekeng, Abel Ramoelo, Andrew T Hudak, F Handavu, Stephen Syampungani

“…The estimation of forest structural data in area-based forest inventories relies on the relationship between field-based estimates of forest structural attributes (FSA) and lidar-derived metrics at plot level, which can be modeled using either parametric or non-parametric regression techniques. …”
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Structural Feature-Preserving Point Cloud Denoising Method for Aero-Engine Profile by Jieqiong Yan, Laishui Zhou, Jun Wang, Xiaoping Wang, Xia Liu

“…In order to ensure that noise is removed without blurring or distorting structural features, a structural feature-preserving point cloud denoising method is proposed. …”
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Structural Component Identification and Damage Localization of Civil Infrastructure Using Semantic Segmentation by Piotr Tauzowski, Mariusz Ostrowski, Dominik Bogucki, Piotr Jarosik, Bartłomiej Błachowski

“…The data includes semantic segmentation masks for both categorizing structural elements (slabs, beams, and columns) and assessing structural damage (concrete spalling or exposed rebars). …”
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Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy by Aileen Luo, Tao Zhou, Martin V. Holt, Andrej Singer, Mathew J. Cherukara

“…Abstract Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor—corresponding to dilation and two potential rigid body rotations of the unit cell. …”
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Interpretive Structural Modeling of Factors Affecting Organizational Ambidexterity in the Ministry of Sports and Youth by Ainolah Ahmadnejad Joghie, Mozafar Yektayar, Mozhgan Khodamoradpoor

“…The statistical population of this study consisted of experts who were selected purposefully based on theoretical saturation of 15 of them. Semi-structured interviews were used to collect data in the qualitative study and a questionnaire was used to collect data in the quantitative study. …”
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