AIMC Topic: Water

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Measuring water holding capacity in pork meat images using deep learning.

Meat science
Water holding capacity (WHC) plays an important role when obtaining a high-quality pork meat. This attribute is usually estimated by pressing the meat and measuring the amount of water expelled by the sample and absorbed by a filter paper. In this wo...

Using Machine Learning To Predict Partition Coefficient (Log ) and Distribution Coefficient (Log ) with Molecular Descriptors and Liquid Chromatography Retention Time.

Journal of chemical information and modeling
During preclinical evaluations of drug candidates, several physicochemical (p-chem) properties are measured and employed as metrics to estimate drug efficacy in vivo. Two such p-chem properties are the octanol-water partition coefficient, Log , and d...

Prediction of Soil Water-Soluble Organic Matter by Continuous Use of Corn Biochar Using Three-Dimensional Fluorescence Spectra and Deep Learning.

Computational intelligence and neuroscience
The purpose is to study the soil's water-soluble organic matter and improve the utilization rate of the soil layer. This exploration is based on the theories of three-dimensional fluorescence spectroscopy, deep learning, and biochar. Chernozem in Har...

Formulation and Characterization of Buccal Films Containing Valsartan with Additional Support from Image Analysis.

AAPS PharmSciTech
The present study was aimed to the development and characterization of valsartan-containing buccal films with an introduction to a novel technique of image analysis. Visual inspection of the film provided a wealth of information that was difficult to...

pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants.

Journal of computer-aided molecular design
Aqueous solubility is the most important physicochemical property for agrochemical and drug candidates and a prerequisite for uptake, distribution, transport, and finally the bioavailability in living species. We here present the first-ever direct ma...

Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data.

Scientific reports
The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structur...

Water-Immiscible Coacervate as a Liquid Magnetic Robot for Intravascular Navigation.

Journal of the American Chemical Society
Developing magnetic ultrasoft robots to navigate through extraordinarily narrow and confined spaces like capillaries in vivo requires synthesizing materials with excessive deformability, responsive actuation, and rapid adaptability, which are difficu...

Deep learning for detecting macroplastic litter in water bodies: A review.

Water research
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate t...

Grass Cutting Robot for Inclined Surfaces in Hilly and Mountainous Areas.

Sensors (Basel, Switzerland)
Grass cutting is necessary to prevent grass from diverting essential nutrients and water from crops. Usually, in hilly and mountainous areas, grass cutting is performed on steep slopes with an inclination angle of up to 60° (inclination gradient of 1...

Mateverse, the Future Materials Science Computation Platform Based on Metaverse.

The journal of physical chemistry letters
Currently, computational materials science involves human-computer interaction through coding in software or neural networks. There is still no direct way for human intelligence endorsement. The digitalization of human intelligence should be the ulti...