Secular trends in types of cardiovascular disease in the West of Scotland by Naveed Sattar, Colin Berry, Daniel F Mackay, Christian Delles, Ruth Dundas, Frederick K Ho, Sandosh Padmanabhan, Claudia Geue, Michael Fleming, Denise Brown, Clea du Toit, Jill Pell, Claire E Hastie, Anna Kamdar, Jocelyn M Friday, Tran Q B Tran, Alan Stevenson, Jim D Lewsey

“…Poisson regressions with robust standard errors were used to examine the relative change in event rates over time, overall and by subgroup.Results Overall, the event rate ratios (RRs) for IHD, MI, AF and AAA all fell between 2012 and 2021 after adjustment for age, sex and deprivation. …”
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Brief communication: Improving lake ice modeling in ORCHIDEE-FLake model using MODIS albedo data by Z. Titus, Z. Titus, A. Cuynet, E. Salmon, C. Ottlé

“…The results are in better agreement with the observations for all lake size categories, with the largest and deepest lakes showing more significant error reductions in the duration of the ice cover period up to 18 d. …”
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Distributed Adaptive Coding Optimization for IoT Using Fulcrum Code and Model-Agnostic Meta-Learning (MAML) in Ultra-Low Latency Environments by Yair Rivera Julio, Angel Pinto, Rodrigo Garcia, Jose Aguilar, Nelson A. Perez-Garcia

“…FEC and HARQ further balance error correction and retransmission overhead. Simulations show significant reductions in transmission time and energy consumption, particularly in high-packet-loss scenarios. …”
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Mapping near-real-time soil moisture dynamics over Tasmania with transfer learning by M. T. Widyastuti, J. Padarian, B. Minasny, M. Webb, M. Taufik, D. Kidd

“…Results showed that (1) models calibrated from the Australian dataset performed worse than Tasmanian models regardless of the type of DL approaches; (2) Tasmanian models, calibrated solely using local data, resulted in shortcomings in predicting soil moisture; and (3) transfer learning exhibited remarkable performance improvements (error reductions of up to 45 % and a 50 % increase in correlation) and resolved the drawbacks of the two previous models. …”
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Highlight Removal From Wireless Capsule Endoscopy Images by Shaojie Zhang, Yinghui Wang, Peixuan Liu, Wei Li, Jinlong Yang, Tao Yan, Liangyi Huang, Yukai Wang, Ibragim R. Atadjanov

“…Existing methods fail to satisfactorily address specular highlights in the gastrointestinal tract, often resulting in loss of image details, texture blurring, or texture continuity errors. Therefore, we propose a highlight removal method for capsule endoscopy images. …”
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A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions by Waiard Saikong, Prasophchok Phumma, Suradet Tantrairatn, Chaiyut Sumpavakup

“…Results indicate that the Thevenin model, with selective SOC-dependent parameters, demonstrated superior predictive accuracy, achieving error reductions of up to 4.26 times compared to the fixed resistance model. …”
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Three‒Dimensional Numerical Simulation of the Breaching Process of Landslide Dams with Heterogeneous Structures by HU Xianrui, PENG Ming, FU Xiaoli, YANG Ge, ZHU Yan, SHI Zhenming, ZHANG Gongding

“…The developed 3D VOF-LES-based hydro-sediment coupled model overcomes the limitations of the traditional homogeneous assumption and, for the first time, enables high-resolution simulation of breach morphology evolution under realistic heterogeneous conditions. With prediction errors maintained within 10% under complex experimental conditions, this model provides a robust tool for enhancing risk assessments and emergency planning in regions prone to landslide dam breaches.…”
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Dynamic Tensile Properties of Ultra–High–Performance Concrete Under Impact Splitting Tensile Load Based on Digital Image Correlation Technology by Xudong CHEN, Xuyang WANG, Tao JI, Jixuan LIU, Yingjie NING

“…The experiment utilized a 100 mm large diameter split Hopkinson compression rod as a dynamic loading device, Different strain rates were applied by adjusting the impact air pressure, with three repeated specimens are selected under different air pressures to minimize errors. Based on one-dimensional stress wave theory, the stress, strain, and strain rate of the specimen under dynamic impact splitting tensile load were calculated from the stress wave data collected by strain gauges on the incident and transmission rods. …”
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Advances in the pilot point inverse method: Où En Sommes-Nous maintenant? by White, Jeremy, Lavenue, Marsh

“…., 2000], but with a particular focus on the incredible adoption and advancement of de Marsily’s PPM and related inverse techniques over the last twenty years in the field of predictive groundwater modeling.Much has been written about the vast array of inverse techniques developed by researchers and practitioners since the 1960s. de Marsily’s PPM, like many methods developed in the late 70s and early 80s, structured its approach to parameterization to overcome many of the challenges of applying inverse methods to real world problems, namely, limited head and transmissivity data relative to the number of unknowns to be estimated, measurement errors, inferred covariance structures of the state variables, and limited computational resources. …”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…In particular, LSTM-based controllers achieved reductions in tracking errors of 10%, 74%, 21%, and 37% for DDPG-LSTM, PPO-LSTM, TD3-LSTM, and SAC-LSTM, respectively, compared with their non-recurrent counterparts. …”
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Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements by Jelle Bosmans, Simone Gallas, Victor Smeets, Matteo Kirchner, Luk Geens, Jan Croes, Wim Desmet

“…Experimental validation results show that the virtual torque sensor can detect the load torque with a normalized mean absolute error (NMAE) between 3.41% and 7.47%, depending on the sensor set. …”
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Coordination of preventive, emergency and restorative trading strategies under uncertain sequential extreme weather events by Xuemei Dai, Jing Zhou, Xu Zhang, Kaifeng Zhang, Wei Feng

“…Additionally, the two-layer GNN model achieves a root mean square error of 0.01, demonstrating high accuracy in predicting system outage statuses.…”
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LET-SE2-VINS: A Hybrid Optical Flow Framework for Robust Visual–Inertial SLAM by Wei Zhao, Hongyang Sun, Songsong Ma, Haitao Wang

“…In no-loop scenarios, the method also achieves error reductions of 29.7%, 21.8%, and 24.1% on the MH_04, MH_05, and V2_03 sequences, respectively. …”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. …”
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FlexiNet: An Adaptive Feature Synthesis Network for Real-Time Ego Vehicle Speed Estimation by Abdalrahaman Ibrahim, Kyandoghere Kyamakya, Wolfgang Pointner

“…On the nuImages dataset, our model achieves an RMSE of 1.1358 m/s and an MAE of 0.9599 m/s, while on the KITTI dataset it records an RMSE of 1.9542 m/s and an MAE of 1.0610 m/s&#x2014;reductions in error of up to 27.6% and 75.5% compared to baseline methods. …”
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Investigating the role of micromobility for first- and last-mile connections to public transport by Giulia Oeschger, Brian Caulfield, Páraic Carroll

“…In this study, the combination of micromobility and active modes with public transport was examined through a survey that included a stated preference experiment. Normal error component mixed logit models were estimated to determine how commuters in County Dublin, Ireland, travel on the first- and last-mile of public transport trips. …”
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Toric Intraocular Lenses for the Management of Corneal Astigmatism at the Time of Cataract Surgery by Colm McAlinden, David Janicek

“…Furthermore, the use of an optical biometer that directly measures the posterior corneal curvature and permits automatic toric IOL power determination with modern formulas avoiding the need for manual data entry may reduce the risk of human error and improve visual and refractive outcomes.…”
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Static Calibration of a New Three-Axis Fiber Bragg Grating-Based Optical Accelerometer by Abraham Perez-Alonzo, Luis Alvarez-Icaza, Gabriel E. Sandoval-Romero

“…To improve the accuracy of our sensor, we propose a table with correction terms that can be subtracted from the estimated acceleration. The mean error of each estimated acceleration component of the sensor is zero, with a maximum standard deviation of 0.018 m/s². …”
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AI-powered spatiotemporal imputation and prediction of chlorophyll-a concentration in coastal ecosystems by Fan Zhang, Hiusuet Kung, Fa Zhang, Can Yang, Jianping Gan

“…STIMP reduced the imputation mean absolute error (MAE) by 45.90–81.39% compared with the data interpolating empirical orthogonal function method in geoscience and by 8.92–43.04% against leading AI methods. …”
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Quality optimization of liquid silicon lenses based on sequential approximation optimization and radial basis function networks by Hanjui Chang, Shuzhou Lu, Yue Sun, Yuntao Lan

“…This approach not only reduces trial-and-error costs and material waste but also significantly decreases carbon emissions, showcasing extensive potential for application in various manufacturing processes. …”
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