Environmental monitoring and assessment
Sep 2, 2025
The operation of wastewater treatment plants (WWTPs) is frequently characterized by complexity, largely attributable to the properties of the influent and the nonlinear fluctuations that occur throughout the wastewater treatment process. Accurate mod...
Kinematic calibration is essential for improving the absolute accuracy of parallel robots, but conventional identification methods often struggle with the complex, non-linear coupling of their numerous geometric error parameters. This can lead to con...
Proceedings of the National Academy of Sciences of the United States of America
Aug 29, 2025
Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theo...
The icing failures of wind turbine blades are critical factors that affect both power generation efficiency and safety. To improve the diagnostic accuracy and speed, an improved weighted kernel extreme learning machine (IWKELM) optimized by multi-str...
Humans tackle unknown tasks by integrating information from multiple sensory modalities. Existing robotic frameworks struggle to achieve effective multimodal manipulation, especially when sufficient training data is lacking. This study introduces "Pa...
In vitro gas production (GP) is commonly used to evaluate ruminant feed, yet its accurate interpretation requires robust mathematical modeling. This study systematically explores a wide array of nonlinear models to explain GP dynamics across various ...
The classification of hyperspectral images (HSI) is an important foundation in the field of remote sensing. Mamba architectures based on state space model (SSM) have shown great potential in the field of HSI processing due to their powerful long-rang...
Understanding the impact of hydrological indicators on flow regimes is essential for sustainable water resource management. This study presents a data-driven framework integrating eXtreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations...
Coseismic landslides are among the most perilous geological disasters in hilly places after earthquakes. Precise assessment of coseismic landslide susceptibility is crucial for forecasting the effects of landslides and alleviating subsequent tragedie...
Digital twin (DT) technology is revolutionizing clinical practice by integrating diverse epidemiological data sources to create dynamic, patient-specific simulations. By leveraging data from genomics, proteomics, imaging, sociodemographics, and real-...
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