A QSAR model for predicting passive permeability (Papp ) was derived from Papp values measured in the LLC-PK1 cell line. The QSAR method and descriptor set that performed best in terms of cross-validation was random forest with a combination of AP, DP, and MOE_2D descriptors. The QSAR model was used to predict the Caco-2 cell permeability for 313 compounds described in the literature with good success. We find that passive permeability for different cell lines can be predicted with similar molecular properties and descriptors. It is shown that the variation in experimental measurements of Papp is smaller than the error in QSAR predictions indicating that predictions are not quantitatively perfect, although qualitatively useful. We get better predictions if the training set is large and diverse, rather than smaller and more internally consistent. This is because prediction accuracy falls off quickly with decreasing similarity to the training set and it is therefore better to have as large a training set as possible. While single physical parameters are not as good as a full QSAR model in predicting Papp , logD seems the most important parameter. Intermediate values of logD are associated with higher Papp .
Abstract. Remote sensing is a potentially very useful source of information for spatial monitoring of natural or cultivated vegetation. The latest advances, in particular the arrival of new image acquisition programs, are changing the temporal approach to monitoring vegetation. The latest European satellites launched, delivering an image every 5 days for each point on the globe, allow the end of a growing season to be monitored. The main objective of this work is to identify and map the vegetation in the Pays de Brest area by using a multi sensors stacking of Sentinel-1 and Sentinel-2 satellites data via Random Forest, Rotation forests (RoF) and Canonical Correlation Forests (CCFs). RoF and CCF create diverse base learners using data transformation and subset features. Twenty four radar images and optical dataa representing different dates in 2017 were processed in time series stacks. The results of RoF and CCF were compared with the ones of RF.
This paper describes a software tool, the Partial Metrics System, that supports the metricsdriven design of Ada program modules.In particular, it focuses on the stepwise refinement of a pseudocode program as assessed in terms of a set of partial metrics.These metrics are extensions of Halstead's Software Science, McCabe's Cyclomatic Complexity, and others.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.