We have identified the influence of fluorescent dye solution concentration and water/dye solution flow rate ratio on obtained product polydispersity, size, zeta potential, and fluorescence.
Complementary to meta-analysis, we identified the individual influence of four factors; study area, surrogate type, test features, and testing method, likely to influence surrogate effectiveness by systematic explorations of their variations within a well-studied system.
Ex post we identified the significant influence of Trust and Perceived Ease of Use on the variable Perceived Usefulness.
Using linear regression and the ENFA method, we identified the factors influencing fire occurrences in the landscape on two time scales.
We identified the areas of influence of the plume of radionuclides from the river, located major areas of SGD and proposed a location for two submarine emissaries.
We identified the factor or influence each participant reported as the strongest (ranked first) and using NVivo, re-examined the entire dataset to unpack influences into aspects (of the participants' nominated influences).
Based of the top 100 ranked genes from each cluster, we identified the genes with most influence on the differences and similarities across the clusters, thus most central for regulation.
Based on the findings, we identified the following variables that significantly influence tax evasion cases: 1. Inspector: Significant differences exist among inspectors.
We identified the nucleotide positions with the strongest influence on BTR in humans by feature selection, that is by successively eliminating those positions that contribute least to the prediction.
Furthermore, we identified the CETP and ITPR2 genes that influenced FCR by affecting egg production.
