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Objectives: This study aims to calculate the measurement uncertainty values of prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer, and fibrinogen tests according to ISO/TS 20914 and Nordtest 2017 guidelines and to compare these values with the total allowable error (TEa%) and maximum expanded allowable measurement uncertainty (MAU) values established by international organizations. Methods: Normal and pathological level internal quality control data for PT, APTT, D-dimer, and fibrinogen tests performed on the Sysmex CS2100 device between January and May 2024 were obtained from the Laboratory Information System. External quality control data for October 2023 and September 2024 were sourced from the external quality control system. Measurement uncertainty was calculated following ISO/TS 20914 and Nordtest 2017 guidelines. Results: According to the ISO/TS 20914 guideline, the measurement uncertainty values for PT, APTT, D-dimer, and fibrinogen tests were 10.42%, 3.49%, 4.81%, and 19.10%, respectively. According to the Nordtest guideline, the measurement uncertainty values were 10.44%, 12.64%, 17.94%, and 21.69%, respectively. Conclusion: Based on the ISO/TS 20914 guideline, it was observed that the measurement uncertainty values for all coagulation tests met the TEa% analytical targets. According to the Nordtest guideline, all tests except fibrinogen met these targets. When evaluated against the MAU criterion, it was determined that D-dimer met the targeted quality specification according to both guidelines; however, the measurement uncertainty values for PT, APTT, and fibrinogen exceeded the allowed targets. Standardization of the measurement uncertainty calculation model and the determination of analytical targets based on laboratory priorities can ensure reliable monitoring of analytical performance. [ABSTRACT FROM AUTHOR]

Copyright of Turkiye Klinikleri Journal of Health Sciences / Türkiye Klinikleri Sağlık Bilimleri Dergisi is the property of Turkiye Klinikleri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants. [ABSTRACT FROM AUTHOR]

The dimensional accuracy of a laser scanner has been extensively evaluated using various measurement methods and diverse reference standards. This study specifically focuses on two key considerations. Firstly, it assesses the dimensional accuracy of the laser scanner by employing another laser scanner, a handheld scanner, as the reference measurement method. Secondly, the study involves the use of three spheres fixed on each wall in both coplanar and non-coplanar positions within a laboratory room at SENAI ISI-SIM. The primary objective is to determine the dimensional accuracy between the centers of the coplanar and non-coplanar spheres up to 10 m. The comparison includes measurement uncertainties, as per ISO GUM standards, obtained using the laser scanner in a laboratory setting with controlled temperature and humidity. Analyzing non-coplanar dimensional accuracy enhances our understanding of the metrological performance of the laser scanner, particularly when assessing the dimensions of objects positioned randomly within a scanning scene. [ABSTRACT FROM AUTHOR]

The imperative need to advance the development of more efficient electric motors requires the meticulous measurement of small increments while minimizing the associated uncertainty in dynamometer tests. One of the key variables in such tests is the angular speed, which is typically obtained based on encoder measurements. This paper proposes a systematic measurement uncertainty assessment method based on the Guide to the Expression of Uncertainty for the two most widely used methods for angular speed measurement, namely, the frequency and period methods. In addition, the impact of the angular speed calculation method on the efficiency test uncertainty is assessed using an automatic test rig for electric motors. Our experimental results consider both steady-state and dynamic analyses. The results show that the period measurement method provides measurements with lower uncertainty for the encoders typically used in such test rigs, about 30 times less than the uncertainty determined for the frequency measurement method. Based on these results, the choice of a proper method can drastically decrease the angular speed uncertainty, and consequently the motor efficiency uncertainty, without increasing instrumentation cost. [ABSTRACT FROM AUTHOR]

High-resolution multi-channel digitizers are used extensively for precision low voltage measurements in numerous applications and allow the simultaneous measurement of voltage magnitude ratio and phase difference between two different waveforms in power system applications. Delta–sigma-based analog-to-digital conversion enables the use of sampling frequencies in the range of megahertz, which provides accurate measurement bandwidths for transformed high-frequency, high-voltage signals. With the increased use of power electronic converters contributing to high-frequency harmonic emissions in power systems, there is a growing interest in developing calibration systems to measure voltage ratio and phase difference of distorted fundamental frequency waveforms consisting of superimposed, high-frequency harmonics. However, information regarding the accuracy of the high-resolution digitizers in the measurement of distorted voltage waveforms is limited as characterization is typically performed under sinusoidal voltage waveform conditions. This paper presents the details of the accuracy characterization of a 24-bit resolution digitizer under both sinusoidal and distorted waveform conditions for measuring complex voltage ratio and phase error for frequencies up to 10 kHz. The detailed experimental results and the measurement uncertainty evaluations show that increased voltage ratio and phase difference errors should be allocated when these high-resolution digitizers are used to measure distorted voltage waveforms. The estimated expanded uncertainties of complex voltage ratio measurement and phase error measurement for harmonic frequencies up to 10 kHz are ±260 ppm and ±100 µrad, respectively. [ABSTRACT FROM AUTHOR]

Dimensional measurements are fundamental in microfluidic device manufacturing and performance. The main focus of this study is the measurement of the connection port sizes in microfluidic devices and components and, accordingly, the possible existence of fluid leaks determined using the flow rate error. The sizes associated with three different microfluidic systems were determined using laser interferometry and through an optical measuring instrument, with metrological traceability to national length standards. It was possible to infer the method with the greatest accuracy and lowest measurement uncertainty for characterizing this kind of system. In conclusion, the results of this work directly address the current lack of dimensions measuring methods of microfluidic components by providing a comprehensive comparison of different protocols, ultimately suggesting a preferred option for immediate application within the microfluidic industry. [ABSTRACT FROM AUTHOR]

Objectives: Ensuring the accuracy and consistency of data obtained in the biochemistry laboratory is essential for obtaining reliable and comparable results. This study aims to calculate total analytical error (TAE) and measurement uncertainty (MU) values to assess the analytical performance of the 25-hydroxyvitamin D3 (25-OH vitD3) analyte measured using high-performance liquid chromatography (HPLC) in our laboratory. Methods: In our study, the internal quality control (IQC) results, which were analyzed at two levels daily between 01--01.2022--31.12.2022, and the data of the external quality control (EQC) program, which was performed at two levels per period for four periods per year, were retrospectively examined for the MU and TAE calculations of the 25-OH vitD3 analyte. TAE was calculated by the formula TAE% = Bias% + (1.65xCV%). MU has been calculated adhering to the Nordtest guideline. Results: In our study, while TAE values and U value calculated using EQC data for bias and u(bias) calculation were found to be higher than the analytical performance goals we used in our study, TAE values and U value calculated using IQC data for bias and RMSbias calculation were found to be lower than the analytical performance goals we used in our study. Conclusion: Clinical laboratories should evaluate analytical performance at regular intervals using appropriate methods. In cases where the number of participants using the same method and device in the EQC program is low, we recommend that EQC data not be used in the calculation of the bias component when evaluating analytical performance with TAE or MU. [ABSTRACT FROM AUTHOR]

Do democratic regimes depend on public support to avoid backsliding? Does public support, in turn, respond thermostatically to changes in democracy? Two prominent recent studies (Claassen 2020a; 2020b) reinvigorated the classic hypothesis on the positive relationship between public support for democracy and regime survival—and challenged its reciprocal counterpart—by using a latent variable approach to measure mass democratic support from cross-national survey data. However, both studies used only the point estimates of democratic support. We show that incorporating the concomitant measurement uncertainty into these analyses reveals that there is no support for either study's conclusion. Efforts to minimize the uncertainty by incorporating additional survey data still fail to yield evidence in support of either hypothesis. These results underscore the need for both more nuanced analyses of the relationships between public support and democracy and taking measurement uncertainty into account when working with latent variables. [ABSTRACT FROM AUTHOR]

Optical flats and parallels are precisely polished surfaces, customarily used as reference standards for quality assurance of fabricated components in numerous industries. In-line with the quality control, reliable flatness and parallelism measurements of optical flats and parallels through appropriate measurement methodologies are immensely significant. The present study describes a comparative investigation for flatness measurement of an optical flat with an effective diameter of 150 mm and parallelism measurement of an optical parallel with an effective diameter of 30 mm, through laser interferometry and image processing using MATLAB, followed by measurement uncertainty evaluation for perceptive and subjective confirmation of the measurement process. Outgrowths of both the approaches have been contemplated to be in significant congruence; the flatness value observed using laser interferometry is 120.50±30 nm whereas the flatness value observed using image processing is 118±32 nm. The parallelism values using laser interferometry is 0.44±0.009 arc second and using image processing is 0.36±0.01 arc second. [ABSTRACT FROM AUTHOR]

This Brief Guide reintroduces readers to the main concepts and technical tools used for the evaluation and expression of measurement uncertainty, including both classical and Bayesian statistical methods. The general approach is the same that was adopted by the Guide to the Expression of Uncertainty in Measurement (GUM): quantities whose values are surrounded by uncertainty are modeled as random variables, which enables the application of a wide range of techniques from probability and statistics to the evaluation of measurement uncertainty. All the methods presented are illustrated with examples involving real measurement results from a wide range of fields of chemistry and related sciences, ranging from classical analytical chemistry as practiced at the beginning to the 20th century, to contemporary studies of isotopic compositions of the elements and clinical trials. The supplementary material offers profusely annotated computer codes that allow the readers to reproduce all the calculations underlying the results presented in the examples. [ABSTRACT FROM AUTHOR]

Recent polling failures highlight that election polls are prone to biases that the margin of error customarily reported with polls does not capture. However, such systematic errors are difficult to assess against the background noise of sampling variance. Shirani-Mehr et al. (2018) developed a hierarchical Bayesian model to disentangle random and systematic errors in poll estimates of two-party vote shares at the election level. The method can inform realistic assessments of poll accuracy. We adapt the model to multiparty elections and improve its temporal flexibility. We then estimate bias and variance in 5,240 German national election polls, 1994–2021. Our analysis suggests that the average absolute election-day bias per party was about 1.5 percentage points, ranging from 0.9 for the Greens to 3.2 for the Christian Democrats. The estimated variance is, on average, about twice as large as that implied by usual margins of error. We find little evidence of house or mode effects. Common biases indicate industry effects due to similar methodological problems. The Supplementary Material provides additional results for 1,751 regional election polls. [ABSTRACT FROM AUTHOR]

We present a semi-static replication algorithm for Bermudan swaptions under an affine, multi-factor term structure model. In contrast to dynamic replication, which needs to be continuously updated as the market moves, a semi-static replication needs to be rebalanced on just a finite number of instances. We show that the exotic derivative can be decomposed into a portfolio of vanilla discount bond options, which mirrors its value as the market moves and can be priced in closed form. This paves the way toward the efficient numerical simulation of xVA, market, and credit risk metrics for which forward valuation is the key ingredient. The static portfolio composition is obtained by regressing the target option's value using an interpretable, artificial neural network. Leveraging the universal approximation power of neural networks, we prove that the replication error can be arbitrarily small for a sufficiently large portfolio. A direct, a lower bound, and an upper bound estimator for the Bermudan swaption price are inferred from the replication algorithm. Additionally, closed-form error margins to the price statistics are determined. We practically study the accuracy and convergence of the method through several numerical experiments. The results indicate that the semi-static replication approaches the LSM benchmark with basis point accuracy and provides tight, efficient error bounds. For in-model simulations, the semi-static replication outperforms a traditional dynamic hedge. [ABSTRACT FROM AUTHOR]

The need to control the real-time location of assets is increasingly relevant worldwide. The Ultra-wideband (UWB) technology is an IoT solution for real-time locating systems (RTLS). The location of the asset is obtained by the signal exchange between a wireless tag (asset) and fixed anchors. The tag interacts with the fixed anchors, defining its position through the distances obtained by trilateration. This data is sent to the server through the gateway. It is well-known that this process has several sources of errors. However, the measurement uncertainty assessment of UWB technology is an important topic regarding its scope of use. This paper presents a task-specific measurement uncertainty evaluation for the UWB positioning system, according to the ISO GUM. It aims to propose a method to support decision-making regarding the possible uses of UWB technology. The position provided by the UWB is compared with reference points using Cartesian coordinates that are measured with a total station, providing metrological reliability. Using the information from the estimated uncertainty, one can define the minimum tolerance interval associated with UWB technology for a given use. A case study demonstrates the method. [ABSTRACT FROM AUTHOR]

Copyright of Acibadem Saglik Bilimleri Dergisi is the property of Acibadem University Medical School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We describe a novel approach to quantifying the uncertainty inherent in the chemical kinetic master equation with stochastic coefficients. A stochastic collocation method is coupled to an analytical expansion of the master equation to analyze the effects of both extrinsic and intrinsic noise. The method consists of an analytical moment-closure method resulting in a large set of differential equations with stochastic coefficients that are in turn solved via a Smolyak sparse grid collocation method. We discuss the error of the method relative to the dimension of the model and clarify which methods are most suitable for the problem. We apply the method to two typical problems arising in chemical kinetics with time-independent extrinsic noise. Additionally, we showagreement with classical Monte Carlo simulations and calculate the variance over time as the sum of two expectations. The method presented here has better convergence properties for low to moderate dimensions than standard Monte Carlo methods and is therefore a superior alternative in this regime. [ABSTRACT FROM AUTHOR]

Although the fidelity of computational-fluid-dynamics (CFD) models for the study of flow in plant canopies has significantly increased over the past decades, the inability to exactly measure the canopy structure and its material and physiological properties introduces a degree of uncertainty in model results that is often difficult to quantify. The present work addresses this problem by proposing a Bayesian uncertainty quantification (UQ) framework for evaluating the impact of uncertain canopy geometry on selected microscale flow statistics (the quantities of interest, QoIs, of the problem). The framework links available in-situ measurements of flow statistics to the uncertainty stemming from foliage spatial distribution and orientation, as well as from the aerodynamic plant response. The uncertainty is first characterized via a Markov chain Monte Carlo procedure, and then propagated to the QoIs through the Monte Carlo sampling method, which returns mean profiles and two-standard-deviation-(2SD-)intervals for the QoIs. The UQ framework relies on a one-dimensional CFD solver to simulate the flow over the Duke Forest, located near Durham, North Carolina, USA. Model results are compared against a standard deterministic solution in terms of mean velocity, Reynolds stress and turbulence-kinetic-energy profiles, as well as canopy aerodynamic parameters. For the considered QoIs, it is found that the 2SD-intervals obtained with the UQ procedure cover 80 % of the experimental intervals, whereas the deterministic solution overlaps with only 47 % of them. Overall, this study highlights the potential of UQ to advance CFD capabilities for predicting exchange processes between realistic plant canopies and the surrounding atmosphere. [ABSTRACT FROM AUTHOR]

The article discusses the how education policies that leverage census data misallocate funding because of statistical uncertainty, comparing the impacts of quantified data error and of a possible differentially private mechanism. Topics include the quantified and unquantified errors alike are not acknowledged; differential privacy is the cornerstone of the Census Bureau's updated disclosure avoidance system, and negative impacts of statistical uncertainty on marginalized groups.

The course "Acoustical Measurement Techniques TTT4250," offered by the Acoustics Group at the Department of Electronic Systems, Norwegian University of Science and Technology, is a fourth-year course in the specialization of acoustics in the five-year master program "Electronics Systems Design and Innovation" or MTELSYS, and the two-year international master program "Electronic Systems Design" or MSELSYS. It is one of the four required courses for MTELSYS and one of the two required courses for MSELSYS. It offers a hands-on approach to acoustics. This paper outlines the topics covered in this course and the involvement of several academic staff members, as well as invited industry and research institute guest speakers, as teachers. The assessment of laboratory reports is described, and general lecture topics, including measurement uncertainty and statistics, the introduction of standards, and programming, are also described. All aspects of the course aim to maximize students' experience with a broad range of acoustic measurements and their interest in acoustics. [ABSTRACT FROM AUTHOR]

Distance is measured by the gasoline needed to get from HT ht to HT ht . The HT ht diamond-shaped ball of City1 rotates into the HT ht square of City2. In HT ht , for example, the HT ht ball is polyhedral with 2-dimensional "faces" that are triangles. The HT ht unit ball is a cube with square faces. [Extracted from the article]

Copyright of Erzincan University Journal of Science & Technology is the property of Erzincan Binali Yildirim Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent product components have been designed as a combination of complex forms for advanced functionality. Such high degree-of-freedom forms are shaped by various manufacturing processes. In the industrial supply chain, the deviation of a manufactured form from its designed form must be verified to ensure product quality. Three-dimensional (3D) measuring systems are typically used for verification. To validate the product manufacturing performance accurately, a measurement procedure that can derive the measurands of forms with small measurement uncertainty is necessitated. For simple geometries such as flats, spheres, and cylinders, precise measurement and uncertainty evaluation methods have been established; however, those for complex forms are still being developed. In this study, measurement uncertainty is assessed by measuring a calibrated gauge and comparing the measured with calibrated values. Several gauges configured with basic geometric elements have been proposed as a reference for complex form measurements, and some issues remain. Some of the gauges do not sufficiently simulate the forms of actual product components, whereas other gauges are difficult to calibrate with small uncertainties. Herein, we discuss a possible approach for solving these problems in the metrology of complex forms using 3D measuring systems. First, a new gauge concept is proposed. The gauge is designed by extracting the complex features of the actual product form and segmenting the gauge's form into various circular arc curvatures. The geometric parameters are well calibrated, and the measurable angular range of the curvature is not limited. A representative gauge based on this concept is described. Next, a robust and small-uncertainty calibration method for complex-form objects is described. The area encompassing the target cross-section is measured, and an envelope is generated on the probe tip mechanical surface from the probe tip centers to determine the measured surface. Finally, the calibration and measurement uncertainty evaluation for the geometric parameters of the new gauge are quantitatively presented. It is verified that the proposed calibration procedure is applicable to freeform measurements, and that both simple and complex forms can be measured within a 1.5 μm uncertainty. [ABSTRACT FROM AUTHOR]

The cross-spectrum method consists in measuring a signal ${c}(t)$ simultaneously with two independent instruments. Each of these instruments contributes to the global noise by its intrinsic (white) noise, whereas the signal ${c}(t)$ that we want to characterize could be a (red) noise. We first define the real part of the cross spectrum as a relevant estimator. Then, we characterize the probability density function (pdf) of this estimator knowing the noise level (direct problem) as a Variance-gamma (VG) distribution. Next, we solve the “inverse problem” due to Bayes’ theorem to obtain an upper limit of the noise level knowing the estimate. Checked by massive Monte Carlo simulations, VG proves to be perfectly reliable for any number of degrees of freedom (DOFs). Finally, we compare this method with another method using the Karhunen–Loève transform (KLT). We find an upper limit of the signal level slightly different as the one of VG since KLT better considers the available information. [ABSTRACT FROM AUTHOR]

In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment. [ABSTRACT FROM PUBLISHER]