A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery

This research proposes an ensemble method for synergistically combining multiple empirical algorithms to better estimate chlorophyll-a (Chl-a) concentration. In previous studies, different empirical algorithms have been employed separately and a single algorithm was often identified as the most suitable predictor for Chl-a retrieval. Our ensemble method combines different individual algorithms to form an ensemble predictor that exploits advantages of each individual algorithm to maximize the overall estimation accuracy. We evaluated two ensemble predictors: the optimally weighted ensemble predictor and the spectral space partition guided ensemble predictor. The ensemble method has been successfully applied to a Sentinel-2A multispectral image acquired over Harsha Lake, Ohio in 2016. Based on in situ water reference data and satellite imagery, we constructed two ensemble predictors that consist of three individual empirical algorithms/estimators, including 2BDA (two-band algorithm), 3BDA (three-band algorithm), and NDCI (Normalized Difference Chlorophyll Index). For the optimally weighted ensemble predictor, the weights for individual algorithms are computed by solving an overdetermined linear system with the pseudoinverse technique. For the spectral space partition guided ensemble predictor, the rules for partitioning spectral space into spectral regions were established as a decision-tree using the CART method. The optimal Chl-a estimate for a pixel is obtained by selectively using the empirical algorithm in the ensemble that has the highest expected accuracy in the spectral region where the pixel is located. Our assessments suggest that the spectral space partition guided ensemble method performs significantly better than three individual empirical algorithms and also better than the optimally weighted ensemble method.     

Fibrinogen Replacement Therapy for Traumatic Coagulopathy: Does the Fibrinogen Source Matter?

Fibrinogen is the first coagulation protein to reach critically low levels during traumatic haemorrhage. There have been no differential effects on clinical outcomes between the two main sources of fibrinogen replacement: cryoprecipitate and fibrinogen concentrate (Fg-C). However, the constituents of these sources are very different. The aim of this study was to determine whether these give rise to any differences in clot stability that may occur during trauma haemorrhage. Fibrinogen deficient plasma (FDP) was spiked with fibrinogen from cryoprecipitate or Fg-C. A panel of coagulation factors, rotational thromboelastography (ROTEM), thrombin generation (TG), clot lysis and confocal microscopy were performed to measure clot strength and stability. Increasing concentrations of fibrinogen from Fg-C or cryoprecipitate added to FDP strongly correlated with Clauss fibrinogen, demonstrating good recovery of fibrinogen (r² = 0.99). A marked increase in Factor VIII, XIII and α₂-antiplasmin was observed in cryoprecipitate (p < 0.05). Increasing concentrations of fibrinogen from both sources were strongly correlated with ROTEM parameters (r² = 0.78–0.98). Cryoprecipitate therapy improved TG potential, increased fibrinolytic resistance and formed more homogeneous fibrin clots, compared to Fg-C. In summary, our data indicate that cryoprecipitate may be a superior source of fibrinogen to successfully control bleeding in trauma coagulopathy. However, these different products require evaluation in a clinical setting.