The feasibility of generating a lipid-containing algal-bacterial polyculture biomass in municipal primary wastewater and enhancing biomethanation of lipid-extracted algal residues (LEA) through hydrothermal pretreatment and co-digestion with sewage s...
Direct disposal of vinasse, a by-product of molasses fermentation plants, threatens environmental health. This study investigated the usage of vinasse as a nutrient source for the heterotrophic and mixotrophic cultivation of novel Micractinium sp. ME...
Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water...
Most applications of flow cytometry or cell sorting rely on the conjugation of fluorescent dyes to specific biomarkers. However, labeled biomarkers are not always available, they can be costly, and they may disrupt natural cell behavior. Label-free q...
Quantitative structure-activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application...
Climate change and human activities affect the biomass of different algal and the succession of dominant species. In the past, phytoplankton phyla inversion has been focused on oceanic and continental shelf waters, while phytoplankton phyla inversion...
Annals of agricultural and environmental medicine : AAEM
40159751
Using deep learning and neural networks enables us to greatly speed-up quantitative studies and provide a useful tool for analyzing microscopic images. Studies conducted on selected algae and sp. confirm the feasibility of using the deep learning n...