The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.
Read More...Evaluating the feasibility of SMILES-based autoencoders for drug discovery
The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.
Read More...Examining the Growth of Methanotrophic Bacteria Immersed in Extremely Low-Frequency Electromagnetic Fields
Scientist are investigating the use of methane-consuming bacteria to aid the growing problem of rising greenhouse gas emissions. While previous studies claim that low-frequency electromagnetic fields can accelerate the growth rate of these bacteria, Chu et al. demonstrate that this fundamental ideology is not on the same wavelength with their data.
Read More...Monitoring the formation of polyurethane foams with an infrared camera: Classroom activity
In this study, the authors utilize an infrared camera to visualize and investigate the exothermic reaction of polyurethane foam, which has many everyday uses including automotive seats, bedding, and insulation.
Read More...Detergent pollutants decrease nutrient availability in soil
Household detergents have surfactants that can potentially harm the soil and broader ecosystems. In this study, the authors investigate whether eco-friendly and less-eco-friendly detergents affect soil pH, phosphorus, nitrogen, and potassium levels.
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