AIMC Topic: Water

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Deep-Learning-Guided Electrochemical Impedance Spectroscopy for Calibration-Free Pharmaceutical Moisture Content Monitoring.

ACS sensors
The moisture content of pharmaceutical powders can significantly impact the physical and chemical properties of drug formulations, solubility, flowability, and stability. However, current technologies for measuring moisture content in pharmaceutical ...

Basic research for identification and classification of organophosphorus pesticides in water based on ultraviolet-visible spectroscopy information.

Environmental science and pollution research international
In this study, the goal was to develop a method for detecting and classifying organophosphorus pesticides (OPPs) in bodies of water. Sixty-five samples with different concentrations were prepared for each of the organophosphorus pesticides, namely ch...

ATR-FTIR spectroscopy and machine/deep learning models for detecting adulteration in coconut water with sugars, sugar alcohols, and artificial sweeteners.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Packaged coconut water offers various options, from pure to those with added sugars and other additives. While the purity of coconut water is esteemed for its health benefits, its popularity also exposes it to potential adulteration and misrepresenta...

Clivia biosensor: Soil moisture identification based on electrophysiology signals with deep learning.

Biosensors & bioelectronics
Research has shown that plants have the ability to detect environmental changes and generate electrical signals in response. These electrical signals can regulate the physiological state of plants and produce corresponding feedback. This suggests tha...

Advancing deep learning-based acoustic leak detection methods towards application for water distribution systems from a data-centric perspective.

Water research
Against the backdrop of severe leakage issue in water distribution systems (WDSs), numerous researchers have focused on the development of deep learning-based acoustic leak detection technologies. However, these studies often prioritize model develop...

Towards transferable metamodels for water distribution systems with edge-based graph neural networks.

Water research
Data-driven metamodels reproduce the input-output mapping of physics-based models while significantly reducing simulation times. Such techniques are widely used in the design, control, and optimization of water distribution systems. Recent research h...

Comparison of water and terrestrial jumping in natural and robotic insects.

Annals of the New York Academy of Sciences
Jumping requires high actuation power for achieving high speed in a short time. Especially, organisms and robots at the insect scale jump in order to overcome size limits on the speed of locomotion. As small jumpers suffer from intrinsically small po...

Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models.

Environmental science & technology
Knowing odor sensory attributes of odorants lies at the core of odor tracking when addressing waterborne odor issues. However, experimental determination covering tens of thousands of odorants in authentic water is not pragmatic due to the complexity...

Detection of milk adulteration using coffee ring effect and convolutional neural network.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
A low-cost and effective method is reported to identify water and synthetic milk adulteration of cow's milk using coffee ring patterns. The cow's milk samples were diluted with tap water (TW), distilled water (DW) and mineral water (MW) and drop cast...

The use of image analysis to study the effect of moisture content on the physical properties of grains.

Scientific reports
Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture cont...