Abstract Effective transfer learning for molecular property prediction has shown considerable strength in addressing insufficient labeled molecules.Many ford tridon existing methods either disregard the quantitative relationship between source and target properties, risking negative transfer, or require intensive training on target tasks.To quantif
A Machine-Learning-Based IoT System for Optimizing Nutrient Supply in Commercial Aquaponic Operations
Nutrient regulation in aquaponic environments has been a topic of activecare spitfire research for many years.Most studies have focused on appropriate control of nutrients in an aquaponic set-up, but very little research has been conducted on commercial-scale applications.In our model, the input data were sourced on a weekly basis from three commer
Uncovering the spectrum of adult zebrafish neural stem cell cycle regulators
Adult neural stem and progenitor cells (aNSPCs) persist lifelong in teleost models in diverse stem cell niches of the brain and spinal cord.Fish maintain developmental stem cell populations throughout life, including both neuro-epithelial cells (NECs) and radial-glial cells (RGCs).Within stem cell domains of the brain, RGCs persist in a cycling or