Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study by Mengdie Liu, Wen Guo, Jin Peng, Jinhui Wu

“…This study aims to utilize machine learning techniques that incorporate sociodemographic factors, health-related metrics, lifestyle variables, and biomarker data to improve risk stratification and management in older adults with SP.MethodsWe analyzed data from the NHANES from 1999–2006 and 2010–2018, including a total of 1,619 older adult patients with SP, with a 10-year follow-up period for this population, during which 541 (33%) patients died and 1,078 (67%) survived. …”
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High-Performance O-Band Angled Multimode Interference Splitter with Buried Silicon Nitride Waveguide for Advanced Data Center Optical Networks by Eduard Ioudashkin, Dror Malka

“…These limitations reduce their effectiveness as photonic data-center applications, where precise waveguide configurations are crucial. …”
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Multivariate Time Series Clustering with State Space Dynamical Modeling and Grassmann Manifold Learning: A Systematic Review on Human Motion Data by Sebin Heo, Andrew Beng Jin Teoh, Sunjin Yu, Beom-Seok Oh

“…These challenges can be addressed in Grassmann manifold learning combined with state-space dynamical modeling, which allows existing clustering techniques to be applicable using similarity measures defined on MTS data. …”
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Spatial Downscaling of Soil Moisture Product to Generate High-Resolution Data: A Multi-Source Approach over Heterogeneous Landscapes in Kenya by Asnake Kassahun Abebe, Xiang Zhou, Tingting Lv, Zui Tao, Abdelrazek Elnashar, Asfaw Kebede, Chunmei Wang, Hongming Zhang

“…The coarse SM datasets exhibited spatiotemporal consistency, with a standard deviation below 0.15 m³/m³, capturing over 95% of the variability in the original data. Validation against in situ SM data at the station confirmed the framework’s reliability, achieving an average UbRMSE of less than 0.04 m³/m³ and a correlation coefficient (r) over 0.52 for each downscaled dataset. …”
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A Pressure-Driven Recovery Factor Equation for Enhanced Oil Recovery Estimation in Depleted Reservoirs: A Practical Data-Driven Approach by Tarek Al Arabi Omar Ganat

“…The novelty of the new <i>DRF</i> equation lies in its capability to correctly estimate <i>RFs</i> using limited available historical data, making it appropriate for early-stage development and data-scarce situations. …”
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Diagnostic accuracy of case-identification algorithms for heart failure in the general population using routinely collected health data: a systematic review by Anita Andreano, Vito Lepore, Pietro Magnoni, Alberto Milanese, Caterina Fanizza, Deborah Testa, Alessandro Musa, Adele Zanfino, Paola Rebora, Lucia Bisceglia, Antonio Giampiero Russo, the PROPHET-I study group

“…Several algorithms based on administrative health data (HAD) have been developed to detect patients with HF in a timely and inexpensive manner, in order to perform real-world studies at the population level. …”
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Prediction of Global, Diffused and Direct Solar Radiation for Oriented and Inclined Surface Based on Meteorological Data for efficient energy use in the south of Tunisia by mahmoud ben amara, Elhem Rdhaounia, moncef balghouthi

“…The determination of solar radiation data at a given geographic location is very important for the development of solar applications and for the evaluation of their performances. …”
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Interval Prediction of Landslide Displacement Using a Pretrained Large Time Series Model Based on Large-scale Cross-domain Data by Xuhuang Du, Cheng Lian, Bo Xu, Zhiyong Qi, Jin Yuan, You Mou, Bing Li

“…These results highlight the potential of large pre-trained models in addressing data scarcity and improving predictive accuracy in geohazard monitoring applications.…”
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Comparison of DJI Zenmuse L1 and RIEGL miniVUX-3UAV Data for DTM Generation in the Forestry Area for Archaeological Purposes by M. Pilarska-Mazurek, W. Ostrowski, W. Ostrowski, P. Zachar, M. Czarnowicz

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A Comparison of the Meta Quest Pro and HTC Vive Focus 3 Eye-Tracking Systems: Analysis of Data Accuracy and Spatial Precision by Erica Rocchi, Anna Ferrarotti, Marco Carli

“…The rise of Virtual Reality has highlighted eye gaze as a key interaction method. Data reliability becomes critical in this context, with gaze accuracy and precision serving as leading indicators of data quality. …”
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Enhancing land feature classification with the BTR Extractor: A novel software package for high-accuracy analysis of aerial laser scan data by Jamshid Talebi, Zahra Azizi

“…Our findings advocate for the use of supervised algorithms in classifying cloud data for enhanced accuracy and efficiency in remote sensing applications.…”
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Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning by A.M. Petrov, A.R. Leonenko, K.N. Danilovskiy, O.V. Nechaev

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A networked station system for high-resolution wind nowcasting in air traffic operations: A data-augmented deep learning approach. by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Diogo Freitas, João Pestana, Dinarte Vieira, Marko Radeta, Fernando Morgado-Dias

“…This study introduces a high-resolution wind nowcasting model designed for aviation applications at Madeira International Airport, a location known for its complex wind patterns. …”
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3D Urban Digital Twinning on the Web with Low-Cost Technology: 3D Geospatial Data and IoT Integration for Wellness Monitoring by Marcello La Guardia

“…Recent advances in computer science and geomatics have enabled the digitalization of complex two-dimensional and three-dimensional spatial environments and the sharing of geospatial data on the web. Simultaneously, the widespread adoption of Internet of Things (IoT) technology has facilitated the rapid deployment of low-cost sensor networks in various scientific applications. …”
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Dynamic Localized SNV, Peak SNV, and Partial Peak SNV: Novel Standardization Methods for Preprocessing of Spectroscopic Data Used in Predictive Modeling by Emily Grisanti, Maria Totska, Stefan Huber, Christina Krick Calderon, Monika Hohmann, Dominic Lingenfelser, Matthias Otto

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Identification of Salt-Stress-Induced Genes from the RNA-Seq Data of Reaumuria trigyna Using Differential-Display Reverse Transcription PCR by Zhen-hua Dang, Qi Qi, Hui-rong Zhang, Hao-yu Li, Shu-Biao Wu, Ying-chun Wang

“…The method presented here successfully identified responsive genes from the massive amount of RNA-seq data. Thus, we suggest that DDRT-PCR could be employed to mine NGS data in a wide range of applications in transcriptomic studies. …”
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Towards Improved Turbomachinery Measurements: A Comprehensive Analysis of Gaussian Process Modeling for a Data-Driven Bayesian Hybrid Measurement Technique by Gonçalo G. Cruz, Xavier Ottavy, Fabrizio Fontaneto

“…This study investigates Gaussian Process (GP) modeling approaches within the framework of a data-driven hybrid measurement technique for turbomachinery applications. …”
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Enhanced Tumor Diagnostics via Cyber-Physical Workflow: Integrating Morphology, Morphometry, and Genomic MultimodalData Analysis and Visualization in Digital Pathology by Marianna Dimitrova Kucarov, Niklolett Szakállas, Béla Molnár, Miklos Kozlovszky

“…Additionally, the intelligent system integrates data from open-access genomic databases for gene-specific molecular pathways and drug targets. …”
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Lessons Learned From European Health Data Projects With Cancer Use Cases: Implementation of Health Standards and Internet of Things Semantic Interoperability by Amelie Gyrard, Somayeh Abedian, Philip Gribbon, George Manias, Rick van Nuland, Kurt Zatloukal, Irina Emilia Nicolae, Gabriel Danciu, Septimiu Nechifor, Luis Marti-Bonmati, Pedro Mallol, Stefano Dalmiani, Serge Autexier, Mario Jendrossek, Ioannis Avramidis, Eva Garcia Alvarez, Petr Holub, Ignacio Blanquer, Anna Boden, Rada Hussein

“… The adoption of the European Health Data Space (EHDS) regulation has made integrating health data critical for both primary and secondary applications. …”
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Universal IoT-Enabled Smart Battery Charging Optimization: Leveraging AI, Automata Theory, and Real-Time Data for Enhanced Lifespan and Efficiency by Arora Divyansh, Goswami Ananya, Ranjan Mritunjay, Sattar Arif Md

“…The system constantly collects and processes data from IoT sensors with real-time charging cycle and battery health feedback. …”
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