Performance evaluation of non-water absorption coefficient partitioning algorithms in optically complex coastal waters of Kochi and Goa, India

Absorption coefficient partitioning algorithms (APAs) were developed to partition the total absorption coefficient (a(λ)) or total non-water absorption coefficient (anw (λ)) into the absorption subcomponents, i.e., absorption due to phytoplankton aph(λ), colored dissolved organic matter (CDOM) ag(λ) and non-algal particulate matter ad (λ), λ is the wavelength. Absorption coefficients of CDOM and non-algal particulate matter are generally combined due to a similarity in exhibited spectral shape and represented as colored detrital matter (CDM) absorption coefficient, adg(λ). This study focuses on the applicability of five APAs Schofield’s, Lin’s, Zhang’s, Stacked Constraints Model (SCM) and Generalized Stacked Constraints Model (GSCM), in deriving the absorption subcomponents from anw (λ) in optically complex coastal waters of Kochi and Goa, India. The average spectral Mean Absolute Percentage Errors (MAPE) obtained for all models in the retrieval of aph(λ), ad (λ), ag(λ) and adg(λ) lie in the ranges of 26—44%, 37—45%, 34—65% and 42—56%. Slopes of adg(λ), ag(λ) and ad (λ) as indicated by Sdg, Sg and Sd are derivable from GSCM, Schofield and Lin’s models only. GSCM model exhibited good retrieval capability of Sd with MAPE values of 22% and a correlation coefficient of 0.74. In retrieval of Sg parameter, none of the models demonstrated satisfactory performance. Overall, the GSCM and Schofield’s models demonstrated good performance in the retrieval of absorption subcomponents, aph(λ), adg(λ), ad (λ) and Sd. Effect of applying baseline correction to ad (λ) on model performance is studied. Tuning with in situ data can further improve the absorption subcomponent and slope parameter retrieval capability of the models

Fly Cell Atlas: a single-nucleus transcriptomic atlas of the adult fruit fly

For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae, that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution