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Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug.

Molecules (Basel, Switzerland)
The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents is known as a breakthrough technology towards developing cost-effective therapeutic drugs. Drug solubility is a significant parameter which must be m...

Construction of AI Environmental Music Education Application Model Based on Deep Learning.

Journal of environmental and public health
The art of music, which is a necessary component of daily life and an ideology older than language, reflects the emotions of human reality. Many new elements have been introduced into music as a result of the quick development of technology, graduall...

Adaptive Neural Network Fixed-Time Control Design for Bilateral Teleoperation With Time Delay.

IEEE transactions on cybernetics
In this article, subject to time-varying delay and uncertainties in dynamics, we propose a novel adaptive fixed-time control strategy for a class of nonlinear bilateral teleoperation systems. First, an adaptive control scheme is applied to estimate t...

Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence.

Molecules (Basel, Switzerland)
Nowadays, supercritical CO(SC-CO) is known as a promising alternative for challengeable organic solvents in the pharmaceutical industry. The mathematical prediction and validation of drug solubility through SC-CO system using novel artificial intelli...

An Improved Gray Neural Network Method to Optimize Spatial and Temporal Characteristics Analysis of Land-Use Change.

Computational intelligence and neuroscience
In this article, the principles of the gray model and BP neural network model are analyzed, and the characteristics of land-use change and spatial and temporal distribution are studied in-depth, and at the same time, to explore the influence of land-...

Identification of Cardiac Patients Based on the Medical Conditions Using Machine Learning Models.

Computational intelligence and neuroscience
Chronic diseases are the most severe health concern today, and heart disease is one of them. Coronary artery disease (CAD) affects blood flow to the heart, and it is the most common type of heart disease which causes a heart attack. High blood pressu...

Hardware-in-the-loop implementation of an unknown input observer for synchronous reluctance motor.

ISA transactions
In this paper, we design a proportional integral observe for a nonlinear synchronous reluctance motor described by a Takagi-Sugeno multi-model. In this design, both states and unknown inputs are estimated simultaneously. First, the mathematical nonli...

Prediction of pH Value of Aqueous Acidic and Basic Deep Eutectic Solvent Using COSMO-RS σ Profiles' Molecular Descriptors.

Molecules (Basel, Switzerland)
The aim of this work was to develop a simple and easy-to-apply model to predict the pH values of deep eutectic solvents (DESs) over a wide range of pH values that can be used in daily work. For this purpose, the pH values of 38 different DESs were me...

Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: a mixed methods study.

BMC health services research
BACKGROUND: Technological progress in artificial intelligence has led to the increasing popularity of virtual assistants, i.e., embodied or disembodied conversational agents that allow chatting with a technical system in a natural language. However, ...

Design and Research of an Articulated Tracked Firefighting Robot.

Sensors (Basel, Switzerland)
Aiming to improve the situation where a firefighting robot is affected by conditions of space and complex terrain, a small four-track, four-drive articulated tracked fire-extinguishing robot is designed, which can flexibly perform fire detection and ...