AIMC Topic: Kinetics

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Intelligent Diagnostics of Radial Internal Clearance in Ball Bearings with Machine Learning Methods.

Sensors (Basel, Switzerland)
This article classifies the dynamic response of rolling bearings in terms of radial internal clearance values. The value of the radial internal clearance in rolling-element bearings cannot be described in a deterministic manner, which shows the chall...

Control of drug release kinetics from hot-melt extruded drug-loaded polycaprolactone matrices.

Journal of controlled release : official journal of the Controlled Release Society
Sustained local delivery of meloxicam by polymeric structures is desirable for preventing subacute inflammation and biofilm formation following tissue incision or injury. Our previous study demonstrated that meloxicam release from hot-melt extruded (...

Structure-Based Drug Discovery with Deep Learning.

Chembiochem : a European journal of chemical biology
Artificial intelligence (AI) in the form of deep learning has promise for drug discovery and chemical biology, for example, to predict protein structure and molecular bioactivity, plan organic synthesis, and design molecules de novo. While most of th...

Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst Case.

Molecules (Basel, Switzerland)
Ab initio kinetic studies are important to understand and design novel chemical reactions. While the Artificial Force Induced Reaction (AFIR) method provides a convenient and efficient framework for kinetic studies, accurate explorations of reaction ...

Knowledge in Motion: A Comprehensive Review of Evidence-Based Human Kinetics.

International journal of environmental research and public health
This comprehensive review examines critical aspects of evidence-based human kinetics, focusing on bridging the gap between scientific evidence and practical implementation. To bridge this gap, the development of tailored education and training progra...

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.

GigaScience
BACKGROUND: Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed in the texts of several research articles, hindering the possibility of practically integrating it ...

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Journal of applied physiology (Bethesda, Md. : 1985)
Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurately predicted during moderate exercise using easy-to-obtain sensor inputs. However, V̇o prediction a...

Prediction of Kinetic Product Ratios: Investigation of a Dynamically Controlled Case.

The journal of physical chemistry. A
Of the various factors influencing kinetically controlled product ratios, the role of nonstatistical dynamics is arguably the least well understood. In this paper, reactions were chosen in which dynamics played a dominant role in product selection, b...

Machine learning and statistical analysis for biomass torrefaction: A review.

Bioresource technology
Torrefaction is a remarkable technology in biomass-to-energy. However, biomass has several disadvantages, including hydrophilic properties, higher moisture, lower heating value, and heterogeneous properties. Many conventional approaches, such as kine...