Unlocking the potential of biowaste: Sustainable strategies to produce valuable industrial products.

Global solid waste generation is expected to double by 2050 from the present annual level of 2.01 metric ton. Traditional biowaste treatment methods, such as landfilling and incineration, cannot meet the need to deal with gigantic amounts of waste and reduce environmental harm.

Customer churn prediction using composite deep learning technique.

Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers. When dissatisfied customers find their present company's services inadequate, they frequently migrate to another service provider. Machine learning and deep learning (ML/DL) approaches have already been used to successfully identify customer churn.

; a biotechnological perspective on the coming-of-age prince's pine.

has been studied for almost two centuries now, with the first paper exploring the phytochemistry of the plant published in 1860. Almost all contemporary studies focus on the biotechnological advances of including its utilization as a natural alternative in the cosmetic, food, biofuel, and healthcare industry, with a special focus on its therapeutic uses. This literature review critically investigates the significance and applications of secondary metabolites extracted from the plant and presses on the biotechnological approaches to improve its utilization.