AIMC Topic: Water

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Experimental characterization and machine learning modeling of leakage-induced soil fluidization in water distribution systems.

PloS one
Leakage in water distribution systems poses a global challenge, not only due to resource loss but also through soil erosion and sinkhole formation, which risk infrastructure collapse. This study investigates the mechanisms of soil fluidization, a pro...

Multi-scale diffusion model for underwater image restoration and enhancement.

PloS one
BACKGROUND: Underwater environments face challenges with image degradation due to light absorption and scattering, resulting in blurring, reduced contrast, and color distortion. This significantly impacts underwater exploration and environmental moni...

Soft buckling achieves consistent large-amplitude deformation for pulse jetting underwater robots.

Bioinspiration & biomimetics
Jellyfish achieve efficient pulse jetting through large-amplitude, low-frequency deformations of a soft bell. This is made possible through large localised deformations at the bell margin. This paper develops a novel soft-robotic underwater pulse jet...

Integrated deep eutectic solvent with amorphous metal-organic framework for highly sensitive electrochemical determination of dicofol in milk and water.

Food chemistry
High-throughput screening of deep eutectic solvents (DESs) was performed using artificial intelligence/quantum mechanical models. Ni-amorphous metal-organic frameworks (aMOFs) was synthesized through amine-DES aqueous solution. The target-specific DE...

Advancing Aqueous Solubility Prediction: A Machine Learning Approach for Organic Compounds Using a Curated Data Set.

Journal of chemical information and modeling
Aqueous solubility is one key property of a chemical compound that determines its possible use in different applications, from drug development to materials sciences. In this work, we present a model for the prediction of aqueous solubility that leve...

Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction.

Scientific reports
Accurate scientific predicting of water requirements for protected agriculture crops is essential for informed irrigation management. The Penman-Monteith model, endorsed by the Food and Agriculture Organization of the United Nations (FAO), is current...

Machine learning analysis of molecular dynamics properties influencing drug solubility.

Scientific reports
Solubility is critical in drug discovery and development, as it significantly influences a medication's bioavailability and therapeutic efficacy. Understanding solubility at the early stages of drug discovery is essential for minimizing resource cons...

Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge.

PloS one
Physics-informed machine learning techniques have emerged to tackle challenges inherent in pure machine learning (ML) approaches. One such technique, the hybrid approach, has been introduced to estimate terrestrial evapotranspiration (ET), a crucial ...

Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning.

Scientific reports
Soil water retention is a critical aspect of water conservation. To quantitatively assess the Soil Water-Holding Capacity (SWHC), this study focused on a typical wild fruit forest in Xinjiang, China. The spectral characteristics of the forest canopy ...

Bionic Pneumatic-Driven Actuator for Underwater Sensing and Motion Control.

ACS applied materials & interfaces
Biological organisms exhibit remarkable capabilities to dynamically adjust their physiological states through autonomous neural perception and adaptive locomotion, offering profound inspiration for the development of intelligent bionic systems. Parti...