Quantitative estimation of sampling uncertainties for mycotoxins in cereal shipments

Many countries receive shipments of bulk cereals from primary producers. There is a volume of work that is ongoing that seeks to arrive at appropriate standards for the quality of the shipments and the means to assess the shipments as they are out-loaded. Of concern are mycotoxin and heavy metal levels, pesticide and herbicide residue levels, and contamination by genetically modified organisms (GMOs). As the ability to quantify these contaminants improves through improved analytical techniques, the sampling methodologies applied to the shipments must also keep pace to ensure that the uncertainties attached to the sampling procedures do not overwhelm the analytical uncertainties. There is a need to understand and quantify sampling uncertainties under varying conditions of contamination. The analysis required is statistical and is challenging as the nature of the distribution of contaminants within a shipment is not well understood; very limited data exist. Limited work has been undertaken to quantify the variability of the contaminant concentrations in the flow of grain coming from a ship and the impact that this has on the variance of sampling. Relatively recent work by Paoletti et al. in 2006 [Paoletti C, Heissenberger A, Mazzara M, Larcher S, Grazioli E, Corbisier P, Hess N, Berben G, Lubeck PS, De Loose M, et al. 2006. Kernel lot distribution assessment (KeLDA): a study on the distribution of GMO in large soybean shipments. Eur Food Res Tech. 224:129–139] provides some insight into the variation in GMO concentrations in soybeans on cargo out-turn. Paoletti et al. analysed the data using correlogram analysis with the objective of quantifying the sampling uncertainty (variance) that attaches to the final cargo analysis, but this is only one possible means of quantifying sampling uncertainty. It is possible that in many cases the levels of contamination passing the sampler on out-loading are essentially random, negating the value of variographic quantitation of the sampling variance. GMOs and mycotoxins appear to have a highly heterogeneous distribution in a cargo depending on how the ship was loaded (the grain may have come from more than one terminal and set of storage silos) and mycotoxin growth may have occurred in transit. This paper examines a statistical model based on random contamination that can be used to calculate the sampling uncertainty arising from primary sampling of a cargo; it deals with what is thought to be a worst-case scenario. The determination of the sampling variance is treated both analytically and by Monte Carlo simulation. The latter approach provides the entire sampling distribution and not just the sampling variance. The sampling procedure is based on rules provided by the Canadian Grain Commission (CGC) and the levels of contamination considered are those relating to allowable levels of ochratoxin A (OTA) in wheat. The results of the calculations indicate that at a loading rate of 1000 tonnes h-1, primary sample increment masses of 10.6 kg, a 2000-tonne lot and a primary composite sample mass of 1900 kg, the relative standard deviation (RSD) is about 1.05 (105%) and the distribution of the mycotoxin (MT) level in the primary composite samples is highly skewed. This result applies to a mean MT level of 2 ng g-1. The rate of false-negative results under these conditions is estimated to be 16.2%. The corresponding contamination is based on initial average concentrations of MT of 4000 ng g-1 within average spherical volumes of 0.3m diameter, which are then diluted by a factor of 2 each time they pass through a handling stage; four stages of handling are assumed. The Monte Carlo calculations allow for variation in the initial volume of the MT-bearing grain, the average concentration and the dilution factor. The Monte Carlo studies seek to show the effect of variation in the sampling frequency while maintaining a primary composite sample mass of 1900 kg. The overall results are presented in terms of operational characteristic curves that relate only to the sampling uncertainties in the primary sampling of the grain. It is concluded that cross-stream sampling is intrinsically unsuited to sampling for mycotoxins and that better sampling methods and equipment are needed to control sampling uncertainties. At the same time, it is shown that some combination of crosscutting sampling conditions may, for a given shipment mass and MT content, yield acceptable sampling performance

Proximity effects and characteristic lengths in ferromagnet-superconductor structures

We present an extensive theoretical investigation of the proximity effects that occur in Ferromagnet/Superconductor ($F/S$) systems. We use a numerical method to solve self consistently the Bogoliubov-de Gennes equations in the continuum. We obtain the pair amplitude and the local density of states (DOS), and use these results to extract the relevant lengths characterizing the leakage of superconductivity into the magnet and to study spin splitting into the superconductor. These phenomena are investigated as a function of parameters such as temperature, magnet polarization, interfacial scattering, sample size and Fermi wavevector mismatch, all of which turn out to have important influence on the results. These comprehensive results should help characterize and analyze future data and are shown to be in agreement with existing experiments.Comment: 24 pages, including 26 figure

Amplitude, frequency and drivers of Caspian Sea lake-level variations during the Early Pleistocene and their impact on a protected wave-dominated coastline

The Caspian Sea, the largest isolated lake in the world, witnessed drastic lake-level variations during the Quaternary. This restricted basin appears very sensitive to lake-level variations, due to important variations in regional evaporation, precipitation and runoff. The amplitude, frequency and drivers of these lake-level changes are still poorly documented and understood. Studying geological records of the Caspian Sea might be the key to better comprehend the complexity of these oscillations. The Hajigabul section documents sediment deposited on the northern margin of the Kura Basin, a former embayment of the Caspian Sea. The 2035 m thick, well-exposed section was previously dated by magneto-biostratigraphic techniques and provides an excellent record of Early Pleistocene environmental, lake-level and climate changes. Within this succession, the 1050 m thick Apsheronian regional stage, between ca 2·1 Ma and 0·85 Ma, represents a particular time interval with 20 regressive sequences documented by sedimentary and palaeontological changes. Sequences are regressing from offshore to coastal, lagoonal or terrestrial settings and are bounded by abrupt flooding events. Sediment reveals a low energy, wave-dominated, reflective beach system. Wave baselines delimiting each facies association appear to be located at shallower bathymetries compared to the open ocean. Water depth estimations of the wave baselines allow reconstruction of a lake-level curve, recording oscillations of ca 40 m amplitude. Cyclostratigraphic analyses display lake-level frequency close to 41 kyr, pointing to allogenic forcing, dominated by obliquity cycles and suggesting a direct or indirect link with high-latitude climates and environments. This study provides a detailed lake-level curve for the Early Pleistocene Caspian Sea and constitutes a first step towards a better comprehension of the magnitude, occurrence and forcing mechanisms of Caspian Sea lake-level changes. Facies models developed in this study regarding sedimentary architectures of palaeocoastlines affected by repeated lake-level fluctuations may form good analogues for other (semi-)isolated basins worldwide