Numerical power prediction for waDED produced aluminium ER5183 wall structures on vertical substrate plates by Fabio Haunreiter, Hugo Drexler, Martin Schnall, Alois Birgmann, Johannes Kronsteiner, Thomas Kopf, David Gruber, Pauline Meyer-Heye, Matthias Hartmann

“…Experiments using tungsten inert gas (TIG) welding and aluminium substrate plates are conducted to obtain data required for the calibration of the finite element method (FEM) model. …”
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Extensional forearc structures at the transition from Alaska to Aleutian Subduction Zone: slip partitioning, terranes and large earthquakes by Kahrizi, Amin, Delescluse, Matthias, Chamot-Rooke, Nicolas, Pubellier, Manuel, Bécel, Anne, Shillington, Donna, Nedimović, Mladen, Bulois, Cédric

“…Using legacy seismic profiles and modern multichannel seismic data, we update the structural map of the area, focusing on the intersection between trench-parallel, landward-dipping normal faults rooting in the plate interface and trench-oblique to trench-perpendicular normal faults, all showing signs of recent activity. …”
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Stage-Dependent Microphysical Structures of Meiyu Heavy Rainfall in the Yangtze-Huaihe River Valley Revealed by GPM DPR by Zhongyu Huang, Leilei Kou, Peng Hu, Haiyang Gao, Yanqing Xie, Liguo Zhang

“…We classified the heavy rainfall events into three life stages of developing, mature, and dissipating using ERA5 reanalysis and IMERG precipitation estimates, and examined vertical microphysical structures using Dual-frequency Precipitation Radar (DPR) data from the Global Precipitation Measurement (GPM) satellite during the Meiyu period from 2014 to 2023. …”
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Global Research Trends in Biomimetic Lattice Structures for Energy Absorption and Deformation: A Bibliometric Analysis (2020–2025) by Sunny Narayan, Brahim Menacer, Muhammad Usman Kaisan, Joseph Samuel, Moaz Al-Lehaibi, Faisal O. Mahroogi, Víctor Tuninetti

“…Notably, the integration of artificial intelligence into structural modeling is accelerating a shift toward data-driven design frameworks. …”
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Identifying important and feasible primary care structures and processes in the US healthcare system: a modified Delphi study by Daphna Harel, Bryan J Weiner, Saul B Blecker, Ann M Nguyen, Maggie M Paul, Stephanie L Albert, Lorraine Kwok, Donna R Shelley, Charles M Cleland, Deborah J Cohen, Laura Damschroder, Carolyn A Berry

“…Objective To identify primary care structures and processes that have the highest and lowest impact on chronic disease management and screening and prevention outcomes as well as to assess the feasibility of implementing these structures and processes into practice.Design A two-round Delphi study was conducted to establish consensus on the impact and feasibility of 258 primary care structures and processes.Participants 29 primary care providers, health system leaders and health services researchers in the USA.Outcomes Primary outcomes were (1) consensus on the impact of each structure and process on chronic disease management and screening and prevention outcomes, separately and (2) consensus on feasibility of implementation by primary care practices.Results Consensus on high impact and feasibility of implementation was reached on four items for chronic disease management: ‘Providers use motivational interviewing to help patients set goals’, ‘Practice has designated staff to manage patient panel’, ‘Practice has onsite providers or staff that speak the most dominant, non-English language spoken by patients’ and ‘Practice includes mental health providers and/or behavioural health specialists in care team’ and seven items for screening and prevention: ‘Practice utilizes standing protocols and orders’, ‘Practice generates reports to alert clinicians to missed targets and to identify gaps in care, such as overdue visits, needed vaccinations, screenings or other preventive services’, ‘Practice has designated staff to manage patient panel’, ‘Practice sets performance goals and uses benchmarking to track quality of care’, ‘Practice uses performance feedback to identify practice-specific areas of improvement’, ‘Practice builds quality improvement activities into practice operations’ and ‘Pre-visit planning data are reviewed during daily huddles’. …”
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Associations of ambient air pollution exposure and sleep pattern with brain structures: A prospective study in the UK Biobank by Ting Song, Xiyin Qiu, Jialong Wu, Huan Xu, Juying Zhang, Bing Guo, Xing Zhao

“…Neuroimaging data were processed to obtain measures of global brain volume, GMV, and WMV, as well as white matter hyperintensity volume (WMHV). …”
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A novel approach for snow depth retrieval in forested areas by integrating horizontal and vertical canopy structures information by Shanna Yue, Liyun Dai, Jie Deng, Yanxing Hu, Lin Xiao, Tao Che

“…In this study, a normalized maximum stem volume (NMSV) index was constructed by combining canopy height and tree cover data obtained through remote sensing techniques. …”
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Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records by Daniel C. Thompson, Reza Mofidi

“…Abstract Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing (NLP) offers a promising solution by automating analysis of electronic health records (EHRs). …”
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Interpretable machine learning excavates a low-alloyed magnesium alloy with strength-ductility synergy based on data augmentation and reconstruction by Qinghang Wang, Xu Qin, Shouxin Xia, Li Wang, Weiqi Wang, Weiying Huang, Yan Song, Weineng Tang, Daolun Chen

“…The data augmentation technique expands the original dataset through Gaussian noise. …”
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Acoustic Data on Vowel Nasalization Across Prosodic Conditions in L1 Korean and L2 English by Native Korean Speakers by Jiyoung Jang, Sahyang Kim, Taehong Cho

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Automated Modal Analysis Using Stochastic Subspace Identification and Field Monitoring Data by Shieh-Kung Huang, Zong-Zhi Lai, Hoong-Pin Lee, Yen-Yu Yang

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Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

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Anatomy, histology, and electron microscopy of the cardiac conduction system. Current views and new data: review by L. B. Mitrofanova

“…The review provides a current view of the anatomy, histology, immunohistochemistry, electron microscopy, and electron immunocytochemistry of the cardiac conduction system (CCS) based on literature data and the author's own research over more than 30 years. …”
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Adaptive Scattering Feature Awareness and Fusion for Limited Training Data SAR Target Recognition by Chenxi Zhao, Daochang Wang, Xianghui Zhang, Yuli Sun, Siqian Zhang, Gangyao Kuang

“…Deep learning methods have achieved huge success in synthetic aperture radar (SAR) target recognition, yet insufficient data limits their performances. If the key prior knowledge that describes the target is incorporated into the network, this problem can be effectively mitigated. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

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Remote Inspection of Bridges with the Integration of Scanning Total Station and Unmanned Aerial Vehicle Data by Piotr Olaszek, Edgar Maciejewski, Anna Rakoczy, Rafael Cabral, Ricardo Santos, Diogo Ribeiro

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Research on Reliability Testing Technology of Rail Transit Software by Ying YANG, Zhifei ZHOU, Buqi LIU, Weiqi JIAO

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Redshift Distributions of Fast Radio Bursts Inferred Using Clustering in Dispersion Measure Space by Hui Peng, Yu Yu

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Predicting the Acceptance of Informal Learning Technologies: A Case of the TikTok Application by Ahmed Al-Azawei, Ali Alowayr

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Methodology to identify robots given the type of control designation by S. A. Arkhipenka, L. U. Shilin, A. A. Naurotsky, A. P. Kuznetsov

Subjects: “…data structure…”
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