AIMC Topic: Water

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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...

MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures.

Nature communications
At sufficiently high resolution, x-ray crystallography and cryogenic electron microscopy are capable of resolving small spherical map features corresponding to either water or ions. Correct classification of these sites provides crucial insight for u...

Hybrid machine learning and physics-based model for estimating lettuce (Lactuca sativa) growth and resource consumption in aeroponic systems.

Scientific reports
As the global population is expected to reach 10.3 billion by the mid-2080s, optimizing agricultural production and resource management is crucial. Climate change and environmental degradation further complicate these challenges, impacting crop produ...

Prediction of thermodynamic properties of aqueous carbohydrates solution using the PHSC and ANN models.

Scientific reports
In this work the Artificial Neural Network (ANN) and the Perturbed Hard Sphere Chain (PHSC) equation of state (EoS) have been utilized to estimate the osmotic coefficient, activity coefficient, and water activity of aqueous sugar solutions containing...

Bio-inspired swarm of underwater robots: a review.

Bioinspiration & biomimetics
With the in-depth integration of research across multiple disciplines, such as biomimetics, robotics, and sensing technology, significant advancements have been made in swarm robotics technology, which has been applied in areas including drone swarms...

Soil moisture mapping in Indian tropical islands with C-band SAR and artificial neural network models.

Environmental monitoring and assessment
This study aims at analyzing the patterns of soil moisture in the South Andaman district using an integrated approach that incorporates Sentinel-1A C-band synthetic aperture radar (SAR) data and other auxiliary data from Sentinel-2A and Landsat 8. A ...