Development of a Pure Certified Reference Material of D-Mannitol
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A new certified reference material (CRM) of D-mannitol (GBW(E) 100681) has been developed in this study. We describe the preparation, structure determination, characterization, homogeneity study, stability study, as well as uncertainty estimation. The main component was 99.91% ± 0.01%. The moisture content of the candidate CRM was 0.036% ± 0.002%, as measured by Karl Fischer titration. The nonvolatile and volatile impurities in the candidate CRM were all much less than 0.01%, which was determined by the ICP-MS and headspace GC-FID methods, respectively. The purity of the D-mannitol CRM was 99.9% ± 1.1% (k = 2), as measured by the two independent approaches involving the mass balance method (MB) and quantitative nuclear magnetic resonance technique (qNMR). The D-mannitol CRM was stable during the monitoring period for each temperature. It is stable for up to 48 months at room temperature and 28 days at 50 °C. The uncertainty was evaluated by combining the contributions from characterization, homogeneity, and stability. The developed D-mannitol CRM would effectively support method validation and proficiency testing, as well as effectively guarantee the accuracy, reliability, and comparability of results.Keywords:
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Repeatability
To evaluate the short- and long-term repeatability (intraobserver variation) of the renal resistive index (RI) in a pig model.Under standardized ambient conditions, short- and long-term repeatabilities were assessed by measuring the RI three consecutive times at 30-minute intervals in 14 pigs and twice 4 weeks apart in 6 pigs, respectively. Repeatability was judged according to predefined criteria, which included calculation of coefficients of variation (CVs) and repeatability coefficients combined with visual assessment and estimation of bias.Short-term repeatability was acceptable, having an average CV of 4.9% +/- 2.9% and of 6.1% +/- 4.7% in two comparisons, findings that were reiterated in the visual assessment. Long-term results were, however, less consistent, having an average CV of 8.1% +/- 6.1% and prominent scatter on the visual assessment graphs.In this study, RI measurements showed an acceptable short-term repeatability, whereas long-term results were less consistent. The components of error contributing to the modest long-term repeatability need to be investigated in studies of larger populations.
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Abstract Objective This study aimed to investigate the inter‐and intraday repeatability of RHI measured by Endo‐ PAT in healthy volunteers. Methods Interday RHI repeatability was tested in two consecutive days in a group of 31 male subjects. Intraday repeatability was investigated at baseline and after 2 and 4 hour in a group of 16 volunteers. Data were evaluated by analysis of variance. Bland‐Altman plot, CV , CR , and ICC were measured. Results While interday RHI repeatability was found to be reliable ( CV : 6.0%; CR : 0.51; ICC : 0.77), multiple evaluations within the same day significantly ( P <.001) affected RHI (repeatability of the measurement ‐ CV : 18.8%; CR : 1.26; ICC : 0.48). In particular, a significant increase in RHI occurred at 4 hour compared to 2 hour (+16.8%; P <.05) and to baseline (+30.1%; P <.05). Conclusions RHI showed good interday but poor intraday repeatability. Multiple evaluations increased RHI especially in subjects with endothelial dysfunction who improved or reversed their impairment. These results show the potential limitations of multiple Endo‐ PAT measurements within the same day and the importance of standardizing the protocols before RHI evaluations.
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Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4 whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 16. Based on detailed statistical analysis, the data has been shown to be statistically significant.
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The aim of this study was to investigate intra- and interspecimen repeatability of an experimental procedure, which determines elastic and viscoelastic properties of knee ligaments. The collateral ligaments from sheep were used and the repeatability was evaluated in terms of the coefficient of variation. The results indicated a good intraspecimen repeatability (the coefficient of variation generally less than 5%), whereas the interspecimen repeatability was lower (coefficient of variation of about 50%). In conclusion, since the intraspecimen coefficient of variation was low the test procedure was assumed to be repeatable.
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Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation (MLI) has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five Glenn Research Center (GRC) provided coupons with 25 layers was shown to be +/- 8.4% whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0%. A second group of 10 coupons has been fabricated by Yetispace and tested by Florida State University, the repeatability between coupons has been shown to be +/- 15-25%. Based on detailed statistical analysis, the data has been shown to be statistically significant.
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Repeatability
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The introduction of the latest (1997) version of ISO 230-2—the ISO Standard for Repeatability and Accuracy of Positioning of Machine Tools—has changed the way we calculate Repeatability. 'Standard Uncertainty' has replaced 'Standard Deviation', and the band width has been reduced This new concept of Repeatability is examined from both a theoretical and a practical standpoint, and evidence is presented of the way results vary and what sorts of distributions of Repeatability occur in practice. The scope of accuracy measurements and the time scale are then expanded, since positioning is not the only factor controlling a machine's overall accuracy: thermal problems, in particular, are discussed Problems of maintaining Repeatability in the longer term are discussed with particular reference to installing the machine in a customer's premises. 1 The New Version of ISO 230-2 The publication in 1997 of the new version of the ISO standard ISO 230-2* for Repeatability and Accuracy has forced us to look again at what we mean by Repeatability. The old standard of 1988 had much in common with most of the other existing standards at that time: BS3800/2 (originally BS4656/16), VDI/DGQ 3441 and the old NMTBA procedure from around 1970. All these embraced the concept of Repeatability being measured as a six standard deviation spread on an assumed Normal distribution curve. Putting it very simply, this meant that we believed that nature had carefully arranged things so that we could, by measuring a few results, compute the overall Repeatability that would be expected (with 99.7% confidence) from a much larger set of data. Transactions on Engineering Sciences vol 23, © 1999 WIT Press, www.witpress.com, ISSN 1743-3533
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The paper deals with the influence of interactions between parts and appraisers on the results of the analysis of repeatability and reproducibility of the measurement system. The appropriate interactions have been created by simulated changes of selected values measured within the framework of real gauge repeatability and reproducibility study and evaluation was performed using average and range method and analysis of variance (ANOVA). Effects of changes type and size on the results of the analysis (%EV – repeatability; %AV – reproducibility; %INT – interaction between operators and parts; %GRR – gauge repeatability and reproducibility; ndc – number of distinct categories) are compared and mechanisms of these effects are analysed.
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Variability introduced into numerical measurements by a measuring instrument is referred to as measurement instrument repeatability. Measurement instrument repeatability estimation methods exist when the measurements are repeatable. However, when measurements are destructive and repeated measurements are not possible, estimating measuring instrument repeatability is difficult since repeatability is confounded with, and usually cannot be separated from item variability. In this paper an estimator for destructive measuring instrument repeatability is obtained from measurements of two different item types, under the assumptions of constant item type measurement coefficient of variation, constant repeatability, and independent and normally distributed measurements. The estimator's variance is also derived, from which a confidence interval for repeatability can be computed. The results add to the body of existing methods that exploit some assumed pattern of item variability, or alternatively make other assumptions needed to estimate measurement instrument repeatability when repeated measurements are unavailable.
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