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It was shown that OG is a promising extractor material for the fabrication of ceramic-ceramic, ceramic-metal and ceramic-MWCNT nanocomposites.
Our conclusion is that it is possible to reach a trade-off that makes the implementation of an alarm system for coffee rust disease feasible.
Furthermore, the water-based rust converter formulated with acrylic resin may be sensitive to salt contamination of rust.
This can be interpreted by the difference of the rust reduction behavior owing to the existence of Cr in the rust layer.
2, due to its off-white colour on firing, is suitable for other types of ceramic products except porcelain dinnerware.
Digital image analysis of rust reactions can be a powerful tool to do this.
The authors advocate revision with ceramic-on-ceramic couplings after ceramic liner fracture.

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Machine learning has gained popularity for gait analysis in recent years due to its effectiveness in diagnosing gait-related diseases, especially in the elderly population. Studies have shown that machine learning models, including LSTM recurrent neural networks and various classification algorithms, can achieve high accuracy rates of over 90% in detecting gait abnormalities and differentiating pathological gait from normal gait patterns. The incorporation of machine learning techniques allows for the efficient analysis of a large number of interrelated parameters involved in gait, which can be challenging to process manually. By leveraging machine learning algorithms, researchers have been able to improve the diagnosis, treatment, and rehabilitation of gait-related conditions, making it a promising solution for enhancing clinical gait analysis and patient care.
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