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This study developed a scientific process parameter setup based on nozzle pressure and screw position, with the process parameter search sequence being injection speed, / switchover position, packing pressure, and packing time. Unlike previous studies, this study focuses on the scientific process parameter setup of experiments and simulations, as well as on the implementation of calibration. Experiments and simulations had the same trend of results in the scientific process parameter setup.

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The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems.

Sensors (Basel)

January 2025

Department of Computer-Integrated Technologies of Device Production, Faculty of Instrumentation Engineering, National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Beresteiskyi Ave., 37, 03056 Kyiv, Ukraine.

This study presents a method for aligning the geometric parameters of images in multi-channel imaging systems based on the application of pre-processing methods, machine learning algorithms, and a calibration setup using an array of orderly markers at the nodes of an imaginary grid. According to the proposed method, one channel of the system is used as a reference. The images from the calibration setup in each channel determine the coordinates of the markers, and the displacements of the marker centers in the system's channels relative to the coordinates of the centers in the reference channel are then determined.

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The corrosion of low-alloy steel in ethanolamine solution, simulating steam generator chemistry, is studied by in situ chronopotentiometry and electrochemical impedance spectroscopy combined with ex situ analysis of the obtained oxide films and model calculations. Hydrodynamic calculations of the proposed setup to study flow-assisted corrosion demonstrate that turbulent conditions are achieved. Quantum chemical calculations indicate the adsorption orientation of ethanolamine on the oxide surface.

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A growing need to reduce the environmental impact and cost of manufacturing stainless steels has led to the development of ferritic stainless steel as an alternative to austenitic and duplex steels. The development of new stainless steels involves the optimization of their hot rolling processes, with the aim of minimizing the occurrence of defects and improving productivity. In this context, numerical simulation using the finite element method (FEM) is presented as a key tool to reduce the time and cost associated with traditional trial-and-error optimization methods.

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Oxidative stress caused by reactive oxygen species (ROS) affects the aging process and increases the likelihood of several diseases. A new frontier in its prevention includes bioactive foods and natural extracts that can be introduced by the diet in combination with specific probiotics. Among the natural compounds that we can introduce by the diet, extract is one of the most utilized since it contains a vast number of bioactive molecules such as phenolic acids, flavonoids, and polysaccharides that have been shown to possess antioxidant, anti-ageing, anti-cancer, and immunomodulatory activity.

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