A FRAMEWORK FOR PREDICTING ODOR THRESHOLD VALUES OF PERFUMES BY SCIENTIFIC MACHINE LEARNING AND TRANSFER LEARNING

A framework for predicting odor threshold values of perfumes by scientific machine learning and transfer learning

Knowledge of odor thresholds is very important for the perfume industry.Due to the difficulty associated with measuring odor thresholds, empirical models capable of estimating these values can be an invaluable contribution to the field.This work developed a framework based on scientific machine learning strategies.A transfer learning-based strategy

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AtOMA1 Affects the OXPHOS System and Plant Growth in Contrast to Other Newly Identified ATP-Independent Proteases in Arabidopsis Mitochondria

Compared with yeast, our knowledge on members of the ATP-independent plant mitochondrial proteolytic machinery is rather poor.In the present study, using confocal microscopy and immunoblotting, we proved that homologs of yeast Oma1, Atp23, Imp1, Imp2, and Oct1 proteases are localized in Arabidopsis mitochondria.We characterized these components of

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