Abstract Graph neural networks (GNNs) have emerged as powerful tools to accurately predict materials and molecular properties in computational and automated discovery pipelines.In this article, we exploit the invertible nature of these neural networks to directly generate molecular structures with desired electronic properties.Starting from a Milit

IntroductionFortification of cereal products with natural plant extract is an interesting approach to fulfill the dietary requirement of the people.Materials and methodsPeels of pomegranate (rich source of natural compounds) were cut into small pieces and dried in three different methods such as solar drying (SOD), oven drying (OD), and sun drying

Certain aspects of child sexual abuse are well studied in Russia and elsewhere.These are, in particular, risk factor studies focused on the characteristics of children who have Cartridges been victims of sexual abuse as well as those who have committed sexual abuse against children.Researchers pay insufficient attention to the situational factors u

Community detection is one of the key research directions in complex network studies.We propose a community detection algorithm based on a density peak clustering model and multiple attribute decision-making strategy, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution).First, the two-dimensional dataset, which is transformed