Activatable NIR Fluorescence Probe for Epinephrine Detection and Bioimaging Based on Anionic Heptamethine Cyanine.

Epinephrine (EP) is an essential catecholamine in the human body. Currently, most EP detection methods are not suitable for in vivo detection due to material limitations. An organic small molecule fluorescent probe based on a chemical cascade reaction for the detection of EP was designed.

Using machine learning to understand the implications of meteorological conditions for fish kills.

Fish kills, often caused by low levels of dissolved oxygen (DO), involve with complex interactions and dynamics in the environment. In many places the precise cause of massive fish kills remains uncertain due to a lack of continuous water quality monitoring. In this study, we tested if meteorological conditions could act as a proxy for low levels of DO by relating readily available meteorological data to fish kills of grey mullet (Mugil cephalus) using a machine learning technique, the self-organizing map (SOM).

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

Background And Aims: Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel).

Methods: The model used potential individual kernel growth rates to characterize the individual potential sink demand.