Here in the Mara we are collecting the samples needed to test these hypotheses.
Dr. Rodchenkov said that each night, a sports ministry official would send him a list of athletes whose samples needed to be swapped.
But every area could be encouraged to provide the basic necessities: to do all the medical tests and take all the samples needed, to provide female doctors and to arrange for an examination place where the forensics would be secure.
The proposed method fixes the number of samples needed to estimate the power spectrum and its corresponding cumulative energy distribution using the Kolmogorov Smirnov test.
The paper highlights the structural difference between online and offline sampling and provides rigorous bounds on the number of samples needed to guarantee chance constraint satisfaction.
However, only three microcolonies were used to estimate short-term calcification rates at each time because data being expressed as µmol CaCO3 cm−2 d−1, samples needed to be dried immediately after to measure their surface area.
The large quantities of calcined, carbonated, recalcined, or sulfated samples needed to pack the chromatographic column are produced in a fluidized-bed reactor and two types of limestones containing more than 95% CaCO3 are employed.
Using differential scanning calorimetry (DSC), we show how emulsions can reduce the number of kinetic samples needed to obtain a statistical analysis of the effectiveness of polyvinylcaprolactam, PVCap, a common kinetic inhibitor.
Since the number of training samples needed to design a classifier grows with the dimension of the features, a way to reduce the dimension of the features without losing any essential information is needed.
Small-scale spatial variability in soil carbon dioxide (CO2) and nitrous oxide (N2O) fluxes poses serious challenges to the experimental design, and number of gas samples needed to provide a reliable estimate of flux usually exceeds analytical capacities.
Experiments show that compared to a random sampling strategy, the proposed supervised sampling method significantly reduces the number of samples needed to achieve the same level of accuracy, even when the training image is not optimally chosen.
