We report how changing these variables affect the morphology, selectivity, permeance and fouling resistance of membranes, and associate this data with design rules for selecting favorable copolymers.
But how do we associate this information to the data and enable it to be discoverable and accessible in our machine-to-machine systems.
Information describing the chemical composition and three-dimensional (3D) structure of nanomaterials is often represented in an unstructured fashion, with no standardized way to associate this information with the assay data from characterization studies.
Conversely, HER4 positivity was significantly correlated (P = 0.013) with low BLI values, in line with previous data associating this receptor with good prognosis tumours.
Are there any unique identifiers associated with this data that could lead back to an individual, despite any precautions Last.fm might take?
Due to complexities associated with this data processing problem, a novel visual analytics approach was explored in a 3D interactive display to facilitate identification of significant features for use in a classifier algorithm.
The data presented in this paper are solely based on self-report and the limitations associated with this data collection (as discussed above) are acknowledged.
Google searches for the presence of online databases of all collections associated with this data set were performed and specimen specific pages identified.
The Grubbs' test statistic associated with this data point was 3.83 that indicated that the value lay beyond 99% of the range of sample Z, given a normal distribution.
