The phrase "aggregation sampling" is correct and usable in written English.
It can be used in contexts related to statistics, data analysis, or research methodologies where multiple samples are combined for analysis.
Example: "In our study, we employed aggregation sampling to ensure a more comprehensive understanding of the data trends."
Alternatives: "combined sampling" or "collective sampling".
In three of these (Hungary, Italy, and Portugal), the so-called 'centres of aggregation sampling technique' (Baio, Blangiardo, & Blangiardo, 2011) was employed, in France random dialling was employed, and in Belgium random routes including focused enumeration of the nearest neighbour technique was chosen as the sampling strategy.
This showed that larger aggregates were present in the early fibril disaggregation sample compared to late aggregation samples, as was also observed in solution smFRET experiments.
The larger fraction of aggregated species detected in the early fibril disaggregation sample compared to the late aggregation sample is in agreement with solution single-molecule results.
To induce protein aggregation, samples were aged for 15 days at 37 °C.
To determine aggregation, samples were analyzed using analytical size exclusion chromatography (SEC; Tosoh #08541) with a mobile phase of 300 mM NaCl, 25 mM sodium phosphate pH 6.8.
The distribution extended to lower FRET efficiencies for both samples, and this was particularly pronounced for the late aggregation sample, which showed a secondary peak around 0.4-0.5 0.4-0.5eement winh solution single-molecule experiments.
To estimate the average blue monomer brightness, the brightness of blue noncoincident events from a dilute late aggregation sample, where lots of monomers were detected (in contrast to the early disaggregation sample, where the majority of the objects detected were oligomers, in agreement with solution single-molecule experiments) was examined.
Fig. 2 Centres of Aggregation and sampling intensity in Budapest by types of centres Source: Technical reports and information provided by Hungarian research team.
For a simple aggregate query on one table, like SELECT op (expression) FROM table WHERE predicate, it's easy to achieve online aggregation by continuously sampling from the target table.
There are also variations in the statistical models, data aggregation, study periods, sampling protocols, and the coverage of laboratory virus surveillance systems.
The classification of aggregator samples in the aggregation pool proactively prevents duplicate outcomes that increase communication overhead.
