Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches by Burcu Ramazanli, Oyku Yagmur, Efe Cesur Sarioglu, Huseyin Enes Salman

“…However, their reliability depends on high-quality training data derived from CFDs and FEA simulations, where BC modeling plays a crucial role. …”
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De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level by Qingyuan Fan, Xuyang Zhao, Junyao Li, Ronghui Liu, Ming Liu, Qishun Feng, Yanping Long, Yang Fu, Jixian Zhai, Qing Pan, Yi Li

“…Abstract Hidden messages in DNA molecules by employing chemical modifications has been suggested for private data storage and transmission at high information density. …”
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A Hybrid Framework for Enhancing Privacy in Blockchain-Based Personal Data Sharing using Off-Chain Storage and Zero-Knowledge Proofs by Godwin Mandinyenya, Vusumuzi Malele

“…The framework also enables GDPR-compliant erasure by removing encrypted off-chain data while preserving on-chain auditability. Despite challenges such as IPFS latency and trusted setup complexities, the solution offers a scalable and privacy-preserving architecture applicable to real-world domains, especially in privacy-critical environments like healthcare and finance by resolving blockchain’s GDPR compliance paradox.…”
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One-dimensional time-frequency dual-channel visual transformer for bearing fault diagnosis under strong noise and limited data conditions by Shaobin Cai, Yuchen Wang, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…Experiments on the CWRU and PU datasets demonstrate that the proposed model achieves 99.42% and 98.14% accuracy, respectively, under noisy and data-scarce conditions. The results confirm superior noise robustness and diagnostic performance over recent state-of-the-art methods, highlighting its practical potential for real-world industrial applications.…”
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Integrating Humidity‐Resistant and Colorimetric COF‐on‐MOF Sensors with Artificial Intelligence Assisted Data Analysis for Visualization of Volatile Organic Compounds Sensing by Qin Ouyang, Yanna Rong, Gaofan Xia, Quansheng Chen, Yujie Ma, Zhonghua Liu

“…This work paves the way for the direct visualization of sensing processes of VOCs via the integration of advanced humidity‐resistant sensing materials and AI‐assisted data analyzing techniques.…”
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A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks by Xiaoying Song, Wei Sun, Qilong Zhang

“…Data gathering is the basis of monitoring applications in an underwater sensor network, and excellent network coverage and data transmission reliability are the guarantees for the quality of monitoring tasks. …”
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A Cloud-Based Framework for Creating Scalable Machine Learning Models Predicting Building Energy Consumption from Digital Twin Data by Elham Mahamedi, Alaeldin Suliman, Martin Wonders

“…Although machine learning (ML) techniques are increasingly used to predict building energy consumption from this DT data, existing approaches often lack scalability in handling data growth (data scalability) and/or adapting to evolving data patterns (model scalability). …”
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Reserve Estimation from Early Time Production Data in Geopressured Gas Reservoir: Gas Production of Cumulative Unit Pressure Drop Method by Hongfeng Wang, Xiaoping Li, Hedong Sun, Guangren Meng, Wen Cao, Songbai Zhu

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The impact of PCR duplication on RNAseq data generated using NovaSeq 6000, NovaSeq X, AVITI, and G4 sequencers by Natalia Zajac, Ioannis S. Vlachos, Sija Sajibu, Lennart Opitz, Shuoshuo Wang, Sridar V. Chittur, Christopher E. Mason, Kevin L. Knudtson, John M. Ashton, Hubert Rehrauer, Catharine Aquino

“…Results For broader applicability, we sequenced the data on four short-read sequencing platforms: Illumina NovaSeq 6000, Illumina NovaSeq X, Element Biosciences AVITI, and Singular Genomics G4. …”
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Integrated process-property modeling of YBa2Cu3O7 superconducting film for data and model driven process design by Tomoya Horide, Shin Okumura, Shunta Ito, Yutaka Yoshida

“…Our integrated process and property modelling strategy enables data/model-driven process design for YBa2Cu3O7 film fabrication for coated conductor applications.…”
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Cross-Attention-Based High Spatial-Temporal Resolution Fusion of Sentinel-2 and Sentinel-3 Data for Ocean Water Quality Assessment by Yanfeng Wen, Peng Chen, Zhenhua Zhang, Yunzhou Li

“…Current marine research that leverages remote sensing data urgently requires gridded data of high spatial and temporal resolution. …”
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Modeling Ocean Wave Conditions at a Shallow Coast Under Scarce Data Availability: A Case Study in the Mekong Delta, Vietnam by Hoang Thai Duong Vu, Moritz Zemann, Roderick van der Linden, Trinh Cong Dan, Peter Oberle, Frank Seidel, Nguyet Minh Nguyen, Le Xuan Tu

“…However, it requires a much broader amount of input parameters and more complex boundary conditions. Then, SwanOne was applicable to calculate nearshore wave characteristics based on the input parameters extracted from the statistical analysis of long-term ERA5 data. …”
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A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…These results demonstrate that the methodology enables interpretable, data-efficient, and uncertainty-aware turbine-level power predictions, suitable for advanced wind farm monitoring and control applications, enabling a more sensitive underperformance detection.…”
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Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data by Jong-Whi Park, Young-Min Ju, Hak-Sung Kim

“…The foundational framework, reward function, and data communication methods, previously optimized for small-scale facilities, were adjusted to suit the requirements of the extended cold storage settings. …”
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Boosting all-optical wavelength conversion efficiency using an AlGaAs-on-insulator Fabry–Perot microresonator without data rate limits by Chaochao Ye, Ping Zhao, Yang Liu, Xinda Lu, Chanju Kim, Kresten Yvind, Peter A. Andrekson, Minhao Pu

“…We also demonstrate a continuously tunable wavelength conversion system, showcasing its potential to support high signal data rates. Our approach provides a promising pathway for on-chip laser-driven nonlinear signal processing, enabling efficient high-speed wavelength conversion and applications where both high CE and data rate are crucial.…”
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Evaluating Population Normalization Methods Using Chemical Data for Wastewater-Based Epidemiology: Insights from a Site-Specific Case Study by Marco Verani, Ileana Federigi, Alessandra Angori, Alessandra Pagani, Francesca Marvulli, Claudia Valentini, Nebiyu Tariku Atomsa, Beatrice Conte, Annalaura Carducci

“…Wastewater-based epidemiology (WBE) has been widely employed to track the spread of human pathogens; however, correlating wastewater data with clinical surveillance remains challenging due to population variability and environmental factors affecting wastewater composition. …”
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eLogUp! A precise, affordable and open-source IoT data logger to scale-up long-term environmental monitoring by Franck Perret, Ilane Cherif, Frédéric Cherqui, Nicolas Walcker, Adrien Barra, Bastien Bourjaillat, Laëtitia Bacot, Oldrich Navratil

“…is a low-cost, modular, and open-source data logger designed to support both research and operational environmental monitoring applications requiring accurate data recording and storage, efficient power management, and reliable data transmission. …”
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End-to-end 3D instance segmentation of synthetic data and embryo microscopy images with a 3D Mask R-CNN by Gabriel David, Emmanuel Faure

“…In recent years, the exploitation of three-dimensional (3D) data in deep learning has gained momentum despite its inherent challenges. …”
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Estimating fine age structure and time trends in human contact patterns from coarse contact data: The Bayesian rate consistency model. by Shozen Dan, Yu Chen, Yining Chen, Melodie Monod, Veronika K Jaeger, Samir Bhatt, André Karch, Oliver Ratmann, Machine Learning & Global Health network

“…The Bayesian rate consistency model provides a model-based, non-parametric, computationally tractable approach for estimating the fine structure and longitudinal trends in social contacts and is applicable to contemporary survey data with coarsely reported age of contacts as long as the exact age of survey participants is reported.…”
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Development of Novel Soil Salinity Spectral Index Using Remotely Sensed Data: A Case Study on Balod District, Chhattisgarh, India by Deshpande Vaibhav Prakashrao, Ahmad Ishtiyaq, Singh Chandan Kumar

“…This study demonstrates a strong correlation between reflectance values and field EC data with an R2 value of 0.83 and a mean relative error of 10 %. …”
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