Effect of missing values in estimation of mean of auto-correlated measurement series

Sampling and uncertainty of sampling are important tasks, when industrial processes are monitored. Missing values and unequal sources can cause problems in almost all industrial fields. One major problem is that during weekends samples may not be collected. On the other hand a composite sample may be collected during weekend. These systematically occurring missing values (gaps) will have an effect on the uncertainties of the measurements. Another type of missing values is random missing values. These random gaps are caused, for example, by instrument failures. Pierre Gy's sampling theory includes tools to evaluate all error components that are involved in sampling of heterogeneous materials. Variograms, introduced by Gy's sampling theory, have been developed to estimate the uncertainty of auto-correlated process measurements. Variographic experiments are utilized for estimating the variance for different sample selection strategies. The different sample selection strategies are random sampling, stratified random sampling and systematic sampling. In this paper both systematic and random gaps were estimated by using simulations and real process data. These process data were taken from bark boilers of pulp and paper mills (combustion processes). When systematic gaps were examined a linear interpolation was utilized. Also cases introducing composite sampling were studied. Aims of this paper are: (1) how reliable the variogram is to estimate the process variogram calculated from data with systematic gaps, (2) how the uncertainty of missing gap can be estimated in reporting time-averages of auto-correlated time series measurements. The results show that when systematic gaps were filled by linear interpolation only minor changes in the values of variogram were observed. The differences between the variograms were constantly smallest with composite samples. While estimating the effect of random gaps, the results show that for the non-periodic processes the stratified random sampling strategy gives more reliable results than systematic sampling strategy. Therefore stratified random sampling should be used while estimating the uncertainty of random gaps in reporting time-averages of auto-correlated time series measurements.     

Still Elusive – Pd(II)-Mediated Base Pairing by an Acetophenone Oxime Palladacycle within 15N-Labelled Double-Helical Oligonucleotides

Both α and β anomers of an acetophenone C-nucleoside were synthesized and incorporated in the middle of short oligodeoxynucleotides. The ketone oligonucleotides were converted to ¹⁵N-labelled oxime oligonucleotides by treatment with ¹⁵N-hydroxylamine and, finally, cyclopalladated by treatment with lithium tetrachloropalladate. Comparison of the UV melting profiles of duplexes bearing the β anomer of either the palladacyclic or the metal-free oxime C-nucleoside suggested formation of a stable Pd(II)-mediated base pair, especially with adenine or thymine as the base pairing partner. Melting profiles of the corresponding duplexes bearing the α anomer were much more convoluted, precluding meaningful comparison. ¹⁵N NMR spectra were obtained for the β anomeric oxime oligonucleotide as well as its palladacyclic derivative but the signals unfortunately diminished below detection limit when the latter was hybridized with a complementary strand placing a ¹⁵N3-labelled thymine opposite to the palladacyclic residue.