The use of data mining to investigate a possible quality problem with ultrasensitive HIV viral load data at a large reference laboratory.
Suppression of HIV viral load to <50 copies/mL, the lower limit of detection for the ultrasensitive assays, has been shown to correlate with favorable clinical outcome. Patients periodically exhibited transient or sustained low-level viremia based on this test. In order to investigate a possible quality concern, we used our corporate data warehouse to examine the patterns in our data over time as well as across geographic regions.
Abstract Wind is one of the fastest-growing renewable sources of electricity. As with most renewables, the economic viability relies on public subsidies. Even among renewables, the economic evaluation of wind projects is particularly challenging due to the unpredictability of the energy source, wind, and the high sensitivity of the project profitability to changes in a number of parameters. This makes the uncertainty analysis an important topic of research in the wind power sector. This study presents a method of combining two uncertainty analysis methods, sensitivity study and the Monte Carlo method, together with a technical and economic model of a wind farm, in an effort to improve the understanding of the practical effects of the uncertainties, and how they affect the financial risks of wind projects.