AIMC Topic: Kinetics

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Machine-learning model selection and parameter estimation from kinetic data of complex first-order reaction systems.

PloS one
Dealing with a system of first-order reactions is a recurrent issue in chemometrics, especially in the analysis of data obtained by spectroscopic methods applied on complex biological systems. We argue that global multiexponential fitting, the still ...

Total-Body PET Kinetic Modeling and Potential Opportunities Using Deep Learning.

PET clinics
The uEXPLORER total-body PET/CT system provides a very high level of detection sensitivity and simultaneous coverage of the entire body for dynamic imaging for quantification of tracer kinetics. This article describes the fundamentals and potential b...

MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

Biomolecules
In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. Howeve...

Energy optimization from a binary mixture of non-edible oilseeds pyrolysis: Kinetic triplets analysis using Thermogravimetric Analyser and prediction modeling by Artificial Neural Network.

Journal of environmental management
Pyrolysis kinetics and thermodynamic parameters of two non-edible seeds, Pongamia pinnata (PP) and Sapindus emarginatus (SE), and their blend in the ratio of 1:1 (PS) were studied using the thermogravimetric analyzer. Kinetic triplets were determined...

Augmenting Adaptive Machine Learning with Kinetic Modeling for Reaction Optimization.

The Journal of organic chemistry
We combine random sampling and active machine learning (ML) to optimize the synthesis of isomacroin, executing only 3% of all possible Friedländer reactions. Employing kinetic modeling, we augment machine intuition by extracting mechanistic knowledge...

Intelligent modeling and experimental study on methylene blue adsorption by sodium alginate-kaolin beads.

International journal of biological macromolecules
As tighter regulations on color in discharges to water bodies are more widely implemented worldwide, the demand for reliable inexpensive technologies for dye removal grows. In this study, the removal of the basic dye, methylene blue, by adsorption on...

A Comparison of Three Neural Network Approaches for Estimating Joint Angles and Moments from Inertial Measurement Units.

Sensors (Basel, Switzerland)
The application of artificial intelligence techniques to wearable sensor data may facilitate accurate analysis outside of controlled laboratory settings-the holy grail for gait clinicians and sports scientists looking to bridge the lab to field divid...

Artificial Intelligence Assisted Ultrasonic Extraction of Total Flavonoids from .

Molecules (Basel, Switzerland)
Flavonoids in were studied. The flavonoids in were extracted by ultrasonic method, and the extraction conditions were modeled and optimized by response the surface methodology and the artificial intelligence method. The results show that the ultras...

Valorization of groundnut shell via pyrolysis: Product distribution, thermodynamic analysis, kinetic estimation, and artificial neural network modeling.

Chemosphere
Pyrolysis of agricultural biomass is a promising technique for producing renewable energy and effectively managing solid waste. In this study, groundnut shell (GNS) was processed at 500 °C in an inert gas atmosphere with a gas flow rate and a heating...

Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning.

Scientific reports
We developed a method to improve protein thermostability, "loop-walking method". Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as ...