Effectiveness and patient-reported impact of on-flare retreatment in patients with rheumatoid arthritis: insights from retrospective long-term real-world data by Delphine Bertrand, Elias De Meyst, Michaël Doumen, Diederik De Cock, Johan Joly, Barbara Neerinckx, Sofia Pazmino, Nele Pype, Tom Conings, René Westhovens, Patrick Verschueren

“…Trial registration Not applicable.…”
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Real-world data on clinical outcomes and validation of prognostic models for angioimmunoblastic T-cell lymphoma: a multicentric retrospective study in Southern China by Qiu-Yuan Xiang, Jing-Song Wu, Ling Huang, Zong-Kai Zou, Ting-Bo Liu, Zhi-Gang Peng, Li-E. Lin, Xiao-Lei Wei, Hong-Yu Zhang, Yun Lin, Guo-Wei Li, Yi-Rong Jiang, Hua Wang, Ke-Qian Shi, Rui-Ji Zheng, Zhi-Jun Han, Xiao Qiu, Wen-Yu Li, Ji-Hao Zhou

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Toward an Operational System for Automatically Detecting <i>Xylella fastidiosa</i> in Olive Groves Based on Hyperspectral and Thermal Remote Sensing Data by Annarita D’Addabbo, Raffaella Matarrese, Francesco Lovergine, Alberto Refice, Antonella Belmonte, Fabio Bovenga, Antonia Gallo, Serafina Serena Amoia, Raied Abou Kubaa, Giovanni Mita, Donato Boscia

“…First, we assess whether the size of a data set, composed of a limited number of labelled examples, is sufficient to train accurate classifiers. …”
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A Hybrid Brain Tumor Classification Using FL With FedAvg and FedProx for Privacy and Robustness Across Heterogeneous Data Sources by N. Sivakumar, Ahmad Raza Khan, Syed Umar, R. N. Ravikumar, I. Bremnavas, Munindra Lunagaria, Krunal Vaghela, Ghanshyam G. Tejani, Sunil Kumar Sharma

“…This method is especially suitable for medical applications with strict privacy regulations, as it provides an approach to linking heterogeneous data from multiple healthcare institutions.…”
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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data by Yun Zhang, Ganyao Qin, Shuhu Yang, Yanling Han, Zhonghua Hong

“…The current deep-learning-based SSH inversion techniques primarily relying on single-modal data are unable to fully leverage the rich feature information from global navigation satellite system reflectometry (GNSS-R) remote sensing data, therefore limiting the potential accuracy improvement. …”
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Space-Frequency Fusion Dual-Branch Convolutional Neural Networks for Significant Wave Height Retrieval From GF-3 SAR Data by Xuan Jin, Yawei Zhao, Xin Zhang, Yanlei Du, Jinsong Chong

“…Most retrieval models based on GF-3 data primarily focus on wave mode data, with limited utilization of data from other imaging modes. …”
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Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning by Steve Agius, Vincent Cassar, Caroline Magri, Wasiq Khan, Dhiya Al-Jumeily Obe, Godwin Caruana, Luke Topham

“…In Stage 1, predictions were made at the triage level using basic demographic and presenting symptom data. Stage 2 incorporated critical blood test results (e.g., Haemoglobin, C-Reactive Protein, Troponin T, and White Blood Cell Count) alongside the demographic and symptom data from Stage 1 to refine and enhance predictions. …”
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Interpretable Machine Learning for Multi-Crop Yield Prediction in Semi-Arid Regions: A Hierarchical Approach to Handle Climate Data Sparsity by Rachid Ed-daoudi, M’barek El Haloui

“… This study develops a hierarchical machine learning framework to address the challenges of multi-crop yield prediction in semi-arid regions, focusing on sparse climate data, model interpretability, and heterogeneous climate-crop interactions. …”
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A Novel Approach to Generate Large-Scale InSAR-Derived Velocity Fields: Enhanced Mosaicking of Overlapping InSAR Data by Xupeng Liu, Guangyu Xu, Yaning Yi, Tengxu Zhang, Yuanping Xia

“…For instance, the LiCSAR processing platform provides interferometric images covering approximately 250 km × 250 km, facilitating scientific applications of InSAR data. However, the transition from individual interferograms to large-scale, three-dimensional deformation fields often requires additional processing steps, including ramp correction within the images, mosaicking between adjacent images, and the joint inversion of InSAR observations from different viewing angles. …”
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Multimodal Data-Driven Visual Sensitivity Assessment and Planning Response Strategies for Streetscapes in Historic Districts: A Case Study of Anshandao, Tianjin by Ya-Nan Fang, Aihemaiti Namaiti, Shaoqiang Zhang, Tianjia Feng

“…Subjective weights were obtained via the analytic hierarchy process (AHP), incorporating expert and public judgments, while objective weights were derived through the entropy weight method (EWM) based on data information entropy. The integration of both approaches enhances the methodological rigor and scientific validity of SVS weight determination. …”
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Spatio-Temporal Fusion of Landsat and MODIS Data for Monitoring of High-Intensity Fire Traces in Karst Landscapes: A Case Study in China by Xiaodong Zhang, Jingyi Zhao, Guanzhou Chen, Tong Wang, Qing Wang, Kui Wang, Tingxuan Miao

“…The surface fragmentation of karst landscapes leads to a high degree of coupling between fire scar site boundaries and topographic relief. However, the applicability of spatio-temporal data fusion methods for fire scar extraction in such geomorphological areas remains systematically unevaluated. …”
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Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in Coal Mining Areas and Their Responses to Mining Activities Using Sentinel-2A Data by Pengfei Wang, Shidong Wang, Hebing Zhang, Yiheng Jiao, Menglin Liu

“…Based on the Sentinel-2A remote sensing data during 2016&#x2013;2024, this article assessed the applicability of NDVI-f_PV and DFI-f_NPV in low hilly areas by establishing two sets of quantitative models; innovatively adopted GF-2 imagery and utilized supervised classification to remove pixel noise in Sentinel-2A to quantitatively estimate the photosynthetic and NPV cover in the coal mine area. …”
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Context-Contingent Privacy Concerns and Exploration of the Privacy Paradox in the Age of AI, Augmented Reality, Big Data, and the Internet of Things: Systematic Review by Christian Herriger, Omar Merlo, Andreas B Eisingerich, Annisa Rizkia Arigayota

“… BackgroundDespite extensive research into technology users’ privacy concerns, a critical gap remains in understanding why individuals adopt different standards for data protection across contexts. The rise of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR), and big data has created rapidly evolving and complex privacy landscapes. …”
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Expert identification blitz: A rapid high value approach for assessing and improving iNaturalist identification accuracy and data precision and confidence by Thomas Mesaglio, Kelly A. Shepherd, Juliet A. Wege, Russell L. Barrett, Hervé Sauquet, Will K. Cornwell

“…Societal Impact Statement Citizen science data are increasingly used in research and conservation, so assessing and improving data accuracy is important. …”
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Fine-grained building function recognition with street-view images and GIS map data via geometry-aware semi-supervised learning by Weijia Li, Jinhua Yu, Dairong Chen, Yi Lin, Runmin Dong, Xiang Zhang, Conghui He, Haohuan Fu

“…This study offers a new solution for large-scale and multi-city applications by efficiently utilizing multi-source geoinformation data, enhancing urban information acquisition efficiency, and assisting in rational resource allocation.…”
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Super-Resolution of Landsat-8 Land Surface Temperature Using Kolmogorov–Arnold Networks with PlanetScope Imagery and UAV Thermal Data by Mahdiyeh Fathi, Hossein Arefi, Reza Shah-Hosseini, Armin Moghimi

“…Despite this, the proposed approach is effective in areas with limited UAV data availability.…”
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The Capabilities of Optical and C-Band Radar Satellite Data to Detect and Understand Faba Bean Phenology over a 6-Year Period by Frédéric Baup, Rémy Fieuzal, Clément Battista, Herivanona Ramiakatrarivony, Louis Tournier, Serigne-Fallou Diarra, Serge Riazanoff, Frédéric Frappart

“…This study analyzes the potential of optical and radar satellite data to monitor faba bean (<i>Vicia faba</i> L.) phenology over six years (2016–2021) in southwestern France. …”
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Proof of concept for multirotor systems with vortex-generating modes for regenerative wind energy: a study based on numerical simulations and experimental data by F. Avila Correia Martins, A. van Zuijlen, A. van Zuijlen, C. Simão Ferreira

“…The wind flow is modeled using steady-state Reynolds-averaged Navier–Stokes (RANS) computations, with the multirotor and ABL-control devices represented by three-dimensional actuator surface models based on momentum theory. Force coefficient data for the actuator surface models, as well as validation data for the numerical computations, were obtained from a scaled model at TU Delft's Open Jet Facility. …”
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Prediction of gestational diabetes mellitus using early-pregnancy data: a secondary analysis from a prospective cohort study in Iran by Mohammadamin Parsaei, Mohadese Dashtkoohi, Mohammadamin Noorafrooz, Mohammad Haddadi, Mahdi Sepidarkish, Azar Mardi-Mamaghani, Mahnaz Esmaeili, Mehrnoosh Shafaatdoost, Arshia Shizarpour, Ashraf Moini, Reihaneh Pirjani, Sedigheh Hantoushzadeh

“…Trial registration Not applicable.…”
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A Long‐Term (2012–2024) Data Set of Integrated Land–Atmosphere–Carbon–Hydrology Interactions Observations in Ningxiang, East Monsoon Region by Ruichao Li, Zhenghui Xie, Binghao Jia, Zhipeng Xie, Longhuan Wang, Yuhang Tian, Heng Yan, Yanbin You

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