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Water

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Count-Based Morgan Fingerprint: A More Efficient and Interpretable Molecular Representation in Developing Machine Learning-Based Predictive Regression Models for Water Contaminants' Activities and Properties.

Environmental science & technology
In this study, we introduce the count-based Morgan fingerprint (C-MF) to represent chemical structures of contaminants and develop machine learning (ML)-based predictive models for their activities and properties. Compared with the binary Morgan fing...

Techno-economic optimization of a new waste-to-energy plant for electricity, cooling, and desalinated water using various biomass for emission reduction.

Chemosphere
A newly developed waste-to-energy system using a biomass combined energy system designed and taken into account for electricity generation, cooling, and freshwater production has been investigated and modeled in this project. The investigated system ...

Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

PloS one
Robust semantic segmentation of tumour micro-environment is one of the major open challenges in machine learning enabled computational pathology. Though deep learning based systems have made significant progress, their task agnostic data driven appro...

Underwater Target Detection Utilizing Polarization Image Fusion Algorithm Based on Unsupervised Learning and Attention Mechanism.

Sensors (Basel, Switzerland)
Since light propagation in water bodies is subject to absorption and scattering effects, underwater images using only conventional intensity cameras will suffer from low brightness, blurred images, and loss of details. In this paper, a deep fusion ne...

Shortwave infrared diffuse optical wearable probe for quantification of water and lipid content in emulsion phantoms using deep learning.

Journal of biomedical optics
SIGNIFICANCE: The shortwave infrared (SWIR, to 2000 nm) holds promise for label-free measurements of water and lipid content in thick tissue, owed to the chromophore-specific absorption features and low scattering in this range. water and lipid est...

Tri-objective optimization of a waste-to-energy plant with super critical carbon dioxide and multi-effect water desalination for building application based on biomass fuels.

Chemosphere
In the present research, an innovative biomass-based energy system for the production of electricity and desalinated water for building application is proposed. The main subsystems of this power plant include gasification cycle, gas turbine (GT), sup...

Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI.

Magnetic resonance in medicine
PURPOSE: Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone...

Optimization of a near-zero-emission energy system for the production of desalinated water and cooling using waste energy of fuel cells.

Chemosphere
In the present study, a biomass-based multi-purpose energy system that can generate power, desalinated water, hydrogen, and ammonia is presented. The gasification cycle, gas turbine, Rankine cycle, PEM electrolyzer, ammonia production cycle using the...

Prediction of microplastic abundance in surface water of the ocean and influencing factors based on ensemble learning.

Environmental pollution (Barking, Essex : 1987)
Microplastics are regarded as emergent contaminants posing a serious threat to the marine ecosystem. It is time-consuming and labor-intensive to determine the number of microplastics in different seas using traditional sampling and detection methods....

Building Machine Learning Small Molecule Melting Points and Solubility Models Using CCDC Melting Points Dataset.

Journal of chemical information and modeling
Predicting solubility of small molecules is a very difficult undertaking due to the lack of reliable and consistent experimental solubility data. It is well known that for a molecule in a crystal lattice to be dissolved, it must, first, dissociate fr...