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Radionuclide contamination in foods has been a public concern in Japan after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. To estimate time and regional trends of daily intake and annual committed effective dose of strontium-90 (90Sr) after the accident, we analysed Market basket samples using a low background 2π gas-flow counter. Samples were collected from six regions, once a year from 2013 to 2018. There appeared to be little variation in estimated daily intake and annual committed effective dose of 90Sr across the time periods and regions. The estimated maximum annual committed effective dose of 90Sr was 0.00076 mSv/year, a value sufficiently lower than the intervention exemption level, 1 mSv/year, in foods in Japan. There was no noticeable difference between the range of estimated daily intake of 90Sr in this study compared with daily intake measured before the FDNPP accident. These results suggested that no obvious increase in dietary intake of 90Sr was observed after the FDNPP accident, and that the effects on commercial foods from 90Sr due to the FDNPP accident were negligible. [ABSTRACT FROM AUTHOR]

This paper develops a mathematical model for describing the within-plate variation as the RSD (relative standard deviation) of absorbance measurements in a wide concentration range in competitive ELISA and proposes a method for determining the limit of detection (LOD) and range of quantitation (ROQ). The ELISA for 17[alpha]-hydroxyprogesterone is taken as an example. The theoretical RSD description involves analyte concentration as an independent variable and error sources as parameters which concern the pipetting and absorbance measurement. Our model can dispense with repeated experiments of real samples, but the error parameters should be determined experimentally. The theory is in good agreement with the experiments. The most influential error sources at low and high sample concentrations are shown to be the pipetting of a viscous solution of antiserum and the absorbance inherent to the wells of a plate, respectively. The LOD and ROQ are defined as the concentration with 30% RSD and the region with

The relative standard deviation of measurements in atomic absorption spectrometry for cadmium determination is predicted by the signal fluctuation model, which is made up of the white noise and Markov process. The standard deviation (SD), [Mathematical Expression Omitted], of the white noise and SD, [Mathematical Expression Omitted], and autocorrelation parameter, [Rho], of the Markov process are determined from the power spectrum of the actual signal fluctuation in the system and in turn are put to use for the uncertainty prediction of measurements in the time space. The confidence intervals of the conventional calibration and standard addition method are calculated from the predicted SD of measurements.

The aim of this paper is to propose and experimentally prove a probability theory to predict the relative standard deviation of repeated measurements in high-performance liquid chromatography (HPLC). The baseline drift in HPLC, often formulated as 1/f noise, is approximated by a mixed random process comprising white noise and Markov process. The standard deviations (SD), [tilde w], of the white noise and the SD, [tilde m], and retention parameter, [Rho], of the Markov process completely specify the stochastic properties of the respective random processes and are determined from the power spectral density of the baseline by least-squares curve fitting. All the required parameters for the prediction are the noise parameters, [tilde w], [tilde m], and [Rho], working domain of signal processing (here, integration), area of a target peak in the domain, and constant error (mainly originating from sample injection). Every parameter is uniquely determined from experimental data, and no arbitrary constants are involved in the theoretical prediction. The prediction is shown to be excellent for peaks with various areas, heights, and widths over a wide concentration range in the HPLC analysis for some aromatic compounds.