Pesticides and transformation products footprint in Greek market basket vegetables: Comprehensive screening by HRMS and health risk assessment.

Healthy dietary habits encourage vegetable consumption. Although pesticide use in crops may negatively affect human health through food intake, it can also contaminate aquatic and terrestrial environments. Thus, monitoring pesticides in high-consumption matrices is crucial. This study conducted a complete workflow of analysis, including a step of target analysis of 30 widely used pesticides and a subsequent step of suspect screening. A validated QuEChERS method was employed to analyze 61 samples of fruiting vegetables and cucurbits, packaged leafy greens, and root and tuber vegetables, commercially distributed across Greece. The method proved to be highly efficient for all validation characteristics. After target analysis, the change in the residue levels detected during sample processing was evaluated as a case study using available literature data. A health risk assessment based on diet indicated acute and chronic hazard quotients (aHQ and cHQ) and chronic hazard index (cHI) values below 1. Concerning suspect screening, 53 additional identifications of pesticides and transformation products (TPs) were revealed, totaling 86 detections. Overall, 18 parent pesticide compounds and 5 TPs were identified. Ultimately, this approach is expected to provide added value in pesticide and TPs analysis of food matrices without prior data, minimizing experimental time and costs.

Validation, measurement uncertainty, and determination of polysorbate-labeled foods distributed in Korea.

This study reports the improvement and validation of a colorimetric method to quantify polysorbates (20, 60, 65, and 80) in food by measuring absorbance at 620 nm using ultraviolet-visible spectrophotometry. The method was validated for linearity, limit of detection (LOD), limit of quantitation (LOQ), precision, accuracy, and measurement uncertainty. The coefficient of determination was linear (r 2 ≥ 0.9991) over the measured concentration range of 50-1000 mg/L. The LOD and LOQ were 2.3-4.9 and 7.0-15.0 mg/kg, respectively. Intra-day and inter-day accuracy and precision were 91.9-104.1% and 0.1-1.1% RSD, and 91.6-103.8% and 0.4-5.0% RSD, respectively. The result of inter-laboratory recovery was 90.9-99.8% and the measurement uncertainty was < 16% with the compliance of the CODEX recommendation. Sauce, bread, whipped cream, rice cake, ice cream, and various other polysorbate-labeled food products (n = 229, detection range; N.D.-16,442.3 mg/kg) distributed in Korea were analyzed to confirm the applicability of the analytical method. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-024-01544-w.

Investigations into the Geometric Calibration and Systematic Effects of a Micro-CT System.

Micro-Computed Tomography (µCT) systems are used for examining the internal structures of various objects, such as material samples, manufactured parts, and natural objects. Resolving fine details or performing accurate geometric measurements in the voxel data critically depends on the precise calibration of the µCT systems geometry. This paper presents a calibration method for µCT systems using projections of a calibration phantom, where the coordinates of the phantom are initially unknown. The approach involves detecting and tracking steel ball bearings and adjusting the unknown system geometry parameters using non-linear least squares optimization. Multiple geometric models are tested to verify their suitability for a self-calibration approach. The implementation is tested using a calibration phantom captured at different magnifications. The results demonstrate the system's capability to determine the geometry model parameters with a remaining error on the detector between 0.27 px and 0.18 px. Systematic errors that remain after calibration, as well as changing parameters due to system instabilities, are investigated. The source code of this work is published to enable further research.

Impact of Measurement Uncertainty on Fault Diagnosis Systems: A Case Study on Electrical Faults in Induction Motors.

Classification systems based on machine learning (ML) models, critical in predictive maintenance and fault diagnosis, are subject to an error rate that can pose significant risks, such as unnecessary downtime due to false alarms. Propagating the uncertainty of input data through the model can define confidence bands to determine whether an input is classifiable, preferring to indicate a result of unclassifiability rather than misclassification. This study presents an electrical fault diagnosis system on asynchronous motors using an artificial neural network (ANN) model trained with vibration measurements. It is shown how vibration analysis can be effectively employed to detect and locate motor malfunctions, helping reduce downtime, improve process control and lower maintenance costs. In addition, measurement uncertainty information is introduced to increase the reliability of the diagnosis system, ensuring more accurate and preventive decisions.

Precision and accuracy of four handheld blood lactate analyzers across low to high exercise intensities.

PURPOSE: To evaluate the precision and accuracy in measured blood lactate concentrations among four commonly used handheld lactate analyzers compared to two stationary analyzers. METHODS: Venous blood samples were taken at exercise intensities ranging from low to high. The blood lactate concentration was measured simultaneously with four pairs of handheld lactate analyzers (two new units of each brand: Lactate Plus, Lactate Pro2, Lactate Scout 4, and TaiDoc TD-4289), and compared with two stationary analyzers (Biosen C-Line and YSI Sport 1500). Measurements were repeated for a range of blood lactate concentrations (measured with Biosen) from 0.88 to 4.89 mM with a median difference between measurements of 0.10 mM. RESULTS: The mean relative differences to the Biosen analyzer were - 7% (Plus), 7% (Pro), - 10% (Scout), 42% (Tai), and - 32% (Ysi). The residual standard errors after linear regression against Biosen were 0.18 mM (Plus), 0.20 mM (Pro), 0.22 mM (Scout), 0.15 mM (Tai), and 0.06 mM (Ysi). Accordingly, a blood lactate concentration of 3 mM measured with Biosen yielded 95% prediction intervals that were 0.72 mM (Plus), 0.80 mM (Pro), 0.87 mM (Scout), 0.60 mM (Tai), and 0.23 mM (Ysi) wide. CONCLUSION: Compared to our two stationary analyzers, the precision of the four handheld lactate analyzers evaluated in this study was poor. Among the four, Tai was the most precise; however, this analyzer had low accuracy with a substantial mean difference to the reference analyzer.

Strategy and Metrological Support for Indoor Radon Measurements Using Popular Low-Cost Active Monitors with High and Low Sensitivity.

Traditionally, for indoor radon testing, predominantly passive measurements have been used, typically applying the solid-state alpha track-etch method for long-term and the charcoal method for short-term measurements. However, increasingly, affordable consumer-grade active monitors have become available in the last few years, which can generate a concentration time series of an almost arbitrary duration. Firstly, we argue that consumer-grade monitors can well be used for quality-assured indoor radon assessment and consequent reliable decisions. Secondly, we discuss the requirements of quality assurance, which actually allow for reliable decision-making. In particular, as part of a rational strategy, we discuss how to interpret measurement results from low-cost active monitors with high and low sensitivity with respect to deciding on conformity with reference levels that are the annual average concentration of indoor radon. Rigorous analysis shows that temporal variations in radon are a major component of the uncertainty in decision-making, the reliability of which is practically independent of monitor sensitivity. Manufacturers of low-cost radon monitors already provide sufficient reliability and quality of calibration for their devices, which can be used by both professional inspectors and the general public. Therefore, within the suggested measurement strategy and metrologically assured criteria, we only propose to clarify the set and values of the key metrological characteristics of radon monitors as well as to upgrade user-friendly online tools. By implementing clear metrological requirements as well as the rational measurement strategy for the reliable conformity assessment of a room (building) with radon safety requirements, we anticipate significant reductions in testing costs, increased accessibility, and enhanced quality assurance and control (QA/QC) in indoor radon measurements.

In Situ Pipe Prover Volume Measurement Method.

To improve the accuracy of in situ measurement of the standard volumes of pipe provers and to shorten the traceability chain, a new method of in situ pipe prover volume measurement was developed alongside a supporting measurement device. This method is based on the geometric dimension approach, which measures the inner diameter and length of a pipe prover to calculate its volume. For inner diameter measurement, a three-probe inner-diameter algorithm model was established. This model was calibrated using a standard ring gauge of Φ313 mm, with the parameters calculated through fitting. Another standard ring gauge of Φ320 mm was used to verify the inner diameters determined by the algorithmic model. A laser interferometer was employed for the segmented measurement of the pipe prover length. The comprehensive measurement system was then used for in situ measurement of the standard pipe prover. The newly developed system achieved an expanded uncertainty of 0.012% (k = 2) in volume measurement, with the deviation between the measured and nominal pipe prover volumes being merely 0.007%. These results demonstrate that the proposed in situ measurement method offers ultra-high-precision measurement capabilities.

Calibrations, Validations, and Checks of a Dual 23 nm and 10 nm Diffusion Charger-Based Portable Emissions Measurement System (PEMS).

The upcoming Euro 7 vehicle exhaust emissions regulation includes particle number (PN) limits for all vehicles, not only those with direct fuel injection. It also sets the lower detection particle size of the PN methodology to 10 nm from 23 nm. Recently, a commercial diffusion charger-based PEMS added the possibility of switching the lower size between 23 nm and 10 nm. In this study, we assessed the dual PEMS in the calibration laboratory using diffusion flame soot or spark discharge graphite particles following the regulated procedures. Furthermore, we compared the dual PEMS with a laboratory grade system (LABS) using soot, graphite, and vehicle exhaust particles. To put the results into perspective, we added comparisons (validations) of two additional 23 nm PEMSs with LABSs over a three-year period. The results showed that the differences of the 23 nm PEMSs remained the same (around 35% underestimation) over the years and were similar to the dual PEMS. This difference is still well within the permissible tolerance from the regulation (50%). We argued that the reason is the calibration material used by the manufacturer (spark discharge graphite). We demonstrated that calibrating with combustion soot could reduce the differences. The 10 nm PEMS gave similar results but with much smaller differences, indicating that the calibration material is of less importance for the Euro 7 step. The results showed that the measurement uncertainty has not increased but rather decreased for the specific PEMS switching from 23 nm to 10 nm.

Vision Measurement System for Gender-Based Counting of Acheta domesticus.

The exploitation of insects as protein sources in the food industry has had a strong impact in recent decades for many reasons. The emphasis for this phenomenon has its primary basis on sustainability and also to the nutritional value provided. The gender of the insects, specifically Acheta domesticus, is strictly related to their nutritional value and therefore the availability of an automatic system capable of counting the number of Acheta in an insect farm based on their gender will have a strong impact on the sustainability of the farm itself. This paper presents a non-contact measurement system designed for gender counting and recognition in Acheta domesticus farms. A specific test bench was designed and realized to force the crickets to travel inside a transparent duct, across which they were framed by means of a high-resolution camera able to capture the ovipositor, the distinction element between male and female. All possible sources of uncertainty affecting the identification and counting of individuals were considered, and methods to mitigate their effect were described. The proposed method, which achieves 2.6 percent error in counting and 8.6 percent error in gender estimation, can be of significant impact in the sustainable food industry.

Adventitious Error and Its Implications for Testing Relations Between Variables and for Composite Measurement Outcomes.

Wu and Browne (Psychometrika 80(3):571-600, 2015. https://doi.org/10.1007/s11336-015-9451-3 ; henceforth W &B) introduced the notion of adventitious error to explicitly take into account approximate goodness of fit of covariance structure models (CSMs). Adventitious error supposes that observed covariance matrices are not directly sampled from a theoretical population covariance matrix but from an operational population covariance matrix. This operational matrix is randomly distorted from the theoretical matrix due to differences in study implementations. W &B showed how adventitious error is linked to the root mean square error of approximation (RMSEA) and how the standard errors (SEs) of parameter estimates are augmented. Our contribution is to consider adventitious error as a general phenomenon and to illustrate its consequences. Using simulations, we illustrate that its impact on SEs can be generalized to pairwise relations between variables beyond the CSM context. Using derivations, we conjecture that heterogeneity of effect sizes across studies and overestimation of statistical power can both be interpreted as stemming from adventitious error. We also show that adventitious error, if it occurs, has an impact on the uncertainty of composite measurement outcomes such as factor scores and summed scores. The results of a simulation study show that the impact on measurement uncertainty is rather small although larger for factor scores than for summed scores. Adventitious error is an assumption about the data generating mechanism; the notion offers a statistical framework for understanding a broad range of phenomena, including approximate fit, varying research findings, heterogeneity of effects, and overestimates of power.

Assessing the impact of nodule features and software algorithm on pulmonary nodule measurement uncertainty for nodules sized 20 mm or less.

Background: Measurements are not exact, so that if a measurement is repeated, one would get a different value each time. The spread of these values is the measurement uncertainty. Understanding measurement uncertainty of pulmonary nodules is important for proper interpretation of size and growth measurements. Larger amounts of measurement uncertainty may require longer follow-up intervals to be confident that any observed growth is due to actual growth rather than measurement uncertainty. We examined the influence of nodule features and software algorithm on measurement uncertainty of small, solid pulmonary nodules. Methods: Volumes of 107 nodules were measured on 4-6 repeated computed tomography (CT) scans (Siemens Somatom AS, 100 kVp, 120 mA, 1.0 mm slice thickness reconstruction) prospectively obtained during CT-guided fine needle aspiration biopsy between 2015-2021 at Department of Diagnostic, Molecular, and Interventional Radiology in Icahn School of Medicine at Mount Sinai, using two different automated volumetric algorithms. For each, the coefficient of variation (standard deviation divided by the mean) of nodule volume measurements was determined. The following features were considered: diameter, location, vessel and pleural attachments, nodule surface area, and extent of the nodule in the three acquisition dimensions of the scanner. Results: Median volume of 107 nodules was 515.23 and 535.53 mm3 for algorithm #1 and #2, respectively with excellent agreement (intraclass correlation coefficient =0.98). Median coefficient of variation of nodule volume was low for the two algorithms, but significantly different (4.6% vs. 8.7%, P<0.001). Both algorithms had a trend of decreasing coefficient of variation of nodule volume with increasing nodule diameter, though only significant for algorithm #2. Coefficient of variation of nodule volume was significantly associated with nodule volume (P=0.02), attachment to blood vessels (P=0.02), and nodule surface area (P=0.001) for algorithm #2 using a multiple linear regression model. Correlation between the coefficient of variation (CoV) of nodule volume and the CoV of the x, y, z measurements for algorithm #1 were 0.29 (P=0.0021), 0.25 (P=0.009), and 0.80 (P<0.001) respectively, and for algorithm #2, 0.46 (P<0.001), 0.52 (P<0.001), and 0.58 (P<0.001), respectively. Conclusions: Even in the best-case scenario represented in this study, using the same measurement algorithm, scanner, and scanning protocol, considerable measurement uncertainty exists in nodule volume measurement for nodules sized 20 mm or less. We found that measurement uncertainty was affected by interactions between nodule volume, algorithm, and shape complexity.

Measurement Uncertainty and Risk of False Compliance Assessment Applied to Carbon Isotopic Analyses in Natural Gas Exploratory Evaluation.

The concept of uncertainty in an isotopic analysis is not uniform in the scientific community worldwide and can compromise the risk of false compliance assessment applied to carbon isotopic analyses in natural gas exploratory evaluation. In this work, we demonstrated a way to calculate one of the main sources of this uncertainty, which is underestimated in most studies focusing on gas analysis: the δ13C calculation itself is primarily based on the raw analytical data. The carbon isotopic composition of methane, ethane, propane, and CO2 was measured. After a detailed mathematical treatment, the corresponding expanded uncertainties for each analyte were calculated. Next, for the systematic isotopic characterization of the two gas standards, we calculated the standard uncertainty, intermediary precision, combined standard uncertainty, and finally, the expanded uncertainty for methane, ethane, propane, and CO2. We have found an expanded uncertainty value of 1.8‰ for all compounds, except for propane, where a value of 1.6‰ was obtained. The expanded uncertainty values calculated with the approach shown in this study reveal that the error arising from the application of delta calculation algorithms cannot be neglected, and the obtained values are higher than 0.5‰, usually considered as the accepted uncertainty associated with the GC-IRMS analyses. Finally, based on the use of uncertainty information to evaluate the risk of false compliance, the lower and upper acceptance limits for the carbon isotopic analysis of methane in natural gas are calculated, considering the exploratory limits between -55‰ and -50‰: (i) for the underestimated current uncertainty of 0.5‰, the lower and upper acceptance limits, respectively, are -54.6‰ and -50.4‰; and (ii) for the proposed realistic uncertainty of 1.8‰, the lower and upper acceptance limits would be more restrictive; i.e., -53.5‰ and -51.5‰, respectively.

Assessment of Measurement Uncertainty for S-Parameter Measurement Based on Covariance Matrix.

S-parameters are widely used to detail the scattering parameters of radio frequency (RF) components and microwave circuit modules. The vector network analyzer (VNA) is the most commonly used device for measuring S-parameters. Given the multiple frequency points, complex values, and intricate uncertainty propagation involved, accurately assessing the uncertainty of S-parameter measurements is difficult. In this study, we proposed a new method for assessing S-parameter uncertainty based on the covariance matrices, tracing back to the nominal uncertainty of calibration standards. First, we analyzed the relevant theory of uncertainty assessment using covariance matrices and subsequently deduced the mechanism of Type B uncertainty propagating from calibration standards to error model coefficients and S-parameter measurements to evaluate Type B measurement uncertainty. In this study, a novel measurement system was constructed for measuring grounded coplanar waveguides by using a VNA and calibration standards with 8- and 12-error models. Initially, the model assessed the Type B uncertainty of measuring four S-parameters of a grounded coplanar waveguide. Next, the VNA calibrated with the 12-error model was used to conduct multiple repeated measurements to assess the Type A uncertainty of the grounded coplanar waveguide. Finally, the composite uncertainty was constructed, which demonstrated that the proposed method can be used for assessing the uncertainty of S-parameters.

The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery.

This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters. For this reason, it is important to assess how the NVDI measurement is affected by the camera characteristics, light environmental conditions, as well as atmospheric and seasonal/weather conditions. The proposed study investigates the impact of atmospheric conditions on solar irradiation and vegetation reflection captured by a multispectral UAV camera in the red and near-infrared bands and the variation of the nominal wavelengths of the camera in these bands. Specifically, the study examines the influence of atmospheric conditions in three scenarios: dry-clear, humid-hazy, and a combination of both. Furthermore, this investigation takes into account solar irradiance variability and the signal-to-noise ratio (SNR) of the camera. Through Monte Carlo simulations, a sensitivity analysis is carried out against each of the above-mentioned uncertainty sources and their combination. The obtained results demonstrate that the main contributors to the NVDI uncertainty are the atmospheric conditions, the nominal wavelength tolerance of the camera, and the variability of the NDVI values within the considered leaf conditions (dry and fresh).

Measurement uncertainty in clinical chemistry: ISO 20914 versus nordtest or intermediate precision versus bias.

AIM: Measuring uncertainty (MU) is crucial to ensure the accuracy and precision of laboratory results. This study compares the ISO 20914 and Nordtest guidelines to analyze the MU values for 20 clinical chemistry analytes over six months. METHODS: The researchers calculated MU components, including within-laboratory reproducibility (Rw), laboratory analytical performance bias (u(bias)), and combined standard uncertainty (uc), based on internal quality control and external quality assessment data. The final expanded uncertainty (U) values were determined by multiplying the combined uncertainty with a coverage factor (k = 2 for 95% Confidence Interval), following each guideline's respective procedures. Clinical chemistry analytes were analyzed on Roche Cobas 6000 c501 auto analyzer (Roche Diagnostics, Mannheim, Germany) and manufacturer's kits were used analysis. RESULTS: The results show that 11 out of 20 clinical chemistry analytes met the targeted maximum allowable measurement uncertainty (MAU) values when calculated according to ISO 20914 guideline. Also, 11 out of 20 clinical chemistry analytes' MU values met the MAU values with the Nordtest guideline's recommended calculations. However, some tests met the MAU in the ISO 20914 approach but not in the Nordtest guideline, and vice versa. CONCLUSIONS: The study found that intermediate precision (uRw) in the ISO 20914 approach and performance bias (u(bias)) in the Nordtest approach significantly impacted MU values. The research highlights the importance of standardization in MU calculation approaches across clinical laboratories. These findings have implications for patient care and clinical decision-making, emphasizing the importance of selecting appropriate laboratory guidelines for routine use.

Proficiency testing for event-specific quantification of genetically modified maize MON87427: Performance assessment based on the metrologically traceable reference values as assigned values.

The Asia Pacific Metrology Program and the Accreditation Cooperation joint Proficiency Testing (PT) program for the quantification of genetically modified maize MON87427 was organized by the National Institute of Metrology, China, to enhance the measurement accuracy and metrological traceability in the region. Certified reference materials were employed as test samples; metrologically traceable certified reference values served as PT reference values (PTRVs) for evaluating the participants results. The consensus values obtained from the participants were higher than the assigned values, potentially due to the systematic effects of DNA extraction process. The participants' relatively poor overall performance by the ζ-score compared with z-score demonstrates their need to thoroughly investigate quantification bias to elevate the measurement capability of genetically modified (GM) content and deepen their understanding of uncertainty estimation. This program confirmed the importance of using metrologically traceable reference values instead of consensus values as PTRV for reliable performance assessment.