Reproducibility Error Research Articles

Developing guidelines for a reproducible method for low-frequency impact measurements in buildings

The impact noise performance in buildings is evaluated using the measured radiated sound pressure level when impacted by a standard tapping machine. Recent work has shown that there can be 4 - 5 dB variation in the sound pressure levels at different measurement locations in the room. This can lead to a high reproducibility error for field tests. In this work, the authors have developed a novel reciprocity-based measurement method that shows approximately 1 - 1 .25 dB standard deviation in low-frequencies. Additionally, this method provides output/input ratio-based measurements, which can be useful in design predictions. The method was developed using a simulation model and verified using testing in three structures.

Microsphere lens array embedded microfluidic chip for SERS detection with simultaneous enhancement of sensitivity and stability

Surface enhanced Raman spectroscopy (SERS) utilizes the fingerprint features of molecular vibrations to identify and detect substances. However, in traditional single focus excitation scenarios, its signal collection efficiency of the objective is restricted. Furthermore, the uneven distribution of samples on the SERS substrate would result in poor signal stability, while the excitation power is limited to avoid sample damage. SERS detection system always requires precise adjustment of focal length and spot size, making it difficult for point-of-care testing applications. Here, we proposed a SERS microfluidic chip with barium titanate microspheres array (BTMA) embedded using vacuum self-assembled hot-pressing method for SERS detection with simultaneous enhancement of sensitivity and stability. Due to photonic nano-jets and directional antenna effects, high index microspheres are perfect micro-lens for effective light focusing and signal collecting. The BTMA can not only disperse excitation beam into an array of focal points covering the target uniformly with very low signal fluctuation, but enlarge the power threshold for higher signal intensity. We conducted a proof-of-principle experiment on chip for the detection of bacteria with immuno-magnetic tags and immuno-SERS tags. Together with magnetic and ultrasonic operations, the target bacteria in the flow were evenly congregated on the focal plane of BTMA. It demonstrated a limit of detection of 5 cells/mL, excellent signal reproducibility (error∼4.84%), and excellent position tolerance of 500 μm in X–Y plane (error∼5.375%). It can be seen that BTMA-SERS microfluidic chip can effectively solve the contradiction between sensitivity and stability in SERS detection.

Sequencing accuracy and systematic errors of nanopore direct RNA sequencing

BackgroundDirect RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied.ResultsWe present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits.ConclusionsAs the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.

Reproducibility of Quantitative Double-Echo Steady-State T2 Mapping of Knee Cartilage.

Cartilage T2 can detect joints at risk of developing osteoarthritis. The quantitative double-echo steady state (qDESS) sequence is attractive for knee cartilage T2 mapping because of its acquisition time of under 5 minutes. Understanding the reproducibility errors associated with qDESS T2 is essential to profiling the technical performance of this biomarker. To examine the combined acquisition and segmentation reproducibility of knee cartilage qDESS T2 using two different regional analysis schemes: 1) manual segmentation of subregions loaded during common activities and 2) automatic subregional segmentation. Prospective. 11 uninjured participants (age: 28 ± 3 years; 8 (73%) female). 3-T, qDESS. Test-retest T2 maps were acquired twice on the same day and with a 1-week interval between scans. For each acquisition, average cartilage T2 was calculated in four manually segmented regions encompassing tibiofemoral contact areas during common activities and 12 automatically segmented regions from the deep-learning open-source framework for musculoskeletal MRI analysis (DOSMA) encompassing medial and lateral anterior, central, and posterior tibiofemoral regions. Test-retest T2 values from matching regions were used to evaluate reproducibility. Coefficients of variation (%CV), root-mean-square-average-CV (%RMSA-CV), and intraclass correlation coefficients (ICCs) assessed test-retest T2 reproducibility. The median of test-retest standard deviations was used for T2 precision. Bland-Altman (BA) analyses examined test-retest biases. The smallest detectable difference (SDD) was defined as the BA limit of agreement of largest magnitude. Significance was accepted for P < 0.05. All cartilage regions across both segmentation schemes demonstrated intraday and interday qDESS T2 CVs and RMSA-CVs of ≤5%. T2 ICC values >0.75 were observed in the majority of regions but were more variable in interday tibial comparisons. Test-retest T2 precision was <1.3 msec. The T2 SDD was 3.8 msec. Excellent CV and RMSA-CV reproducibility may suggest that qDESS T2 increases or decreases >5% (3.8 msec) could represent changes to cartilage composition. Stage 2.

Repeatability and reproducibility of physically consistent single sheet testing with H-coil

Measurements of magnetic losses of electric steel are usually performed by International Electrotechnical Commission standardized Epstein testers or Single Sheet Testers (SSTs). According to round robin tests, the corresponding levels of repeatability are of the order of 0.1%, and those of reproducibility are of the order of 1%. However, orders of absolute accuracy are unknown due to the applied “current method.” Here, we report corresponding tests for the so-called “physically consistent SST.” Consistency is achieved by a “giant” tangential field coil on a 50 cm long and 17 cm wide soft magnetic sample, using a thin amorphous yoke for magnetization. Tests were made in two labs with very different working conditions (sea levels of 200 and 1100 m, respectively), with very similarly built-up testers. Measurements were made for peak inductions between 1 and 1.9 T. For two distributed samples, the repeatability errors were lower than 0.3%, and the reproducibility errors were lower than 1%. This indicates that SSTs with an H-coil are not less reliable than current based ones. However, the absolute accuracy can be estimated to be much better, being close to 2%.

Automatic segmentation of skeletal muscles from MR images using modified U-Net and a novel data augmentation approach.

Rapid and accurate muscle segmentation is essential for the diagnosis and monitoring of many musculoskeletal diseases. As gold standard, manual annotation suffers from intensive labor and high inter-operator reproducibility errors. In this study, deep learning (DL) based automatic muscle segmentation from MR scans is investigated for post-menopausal women, who normally experience a decline in muscle volume. The performance of four Deep Learning (DL) models was evaluated: U-Net and UNet++ and two modified U-Net networks, which combined feature fusion and attention mechanisms (Feature-Fusion-UNet, FFU, and Attention-Feature-Fusion-UNet, AFFU). The models were tested for automatic segmentation of 16-lower limb muscles from MRI scans of two cohorts of post-menopausal women (11 subjects in PMW-1, 8 subjects in PMW-2; from two different studies so considered independent datasets) and 10 obese post-menopausal women (PMW-OB). Furthermore, a novel data augmentation approach is proposed to enlarge the training dataset. The results were assessed and compared by using the Dice similarity coefficient (DSC), relative volume error (RVE), and Hausdorff distance (HD). The best performance among all four DL models was achieved by AFFU (PMW-1: DSC 0.828 ± 0.079, 1-RVE 0.859 ± 0.122, HD 29.9mm ± 26.5mm; PMW-2: DSC 0.833 ± 0.065, 1-RVE 0.873 ± 0.105, HD 25.9mm ± 27.9mm; PMW-OB: DSC 0.862 ± 0.048, 1-RVE 0.919 ± 0.076, HD 34.8mm ± 46.8mm). Furthermore, the augmentation of data significantly improved the DSC scores of U-Net and AFFU for all 16 tested muscles (between 0.23% and 2.17% (DSC), 1.6%-1.93% (1-RVE), and 9.6%-19.8% (HD) improvement). These findings highlight the feasibility of utilizing DL models for automatic segmentation of muscles in post-menopausal women and indicate that the proposed augmentation method can enhance the performance of models trained on small datasets.

Reliability and reproducibility of CBCT assessment of mandibular changes before and after treatment for Class III growing patients - an easy and quick way for evaluation.

The objective of this study was to evaluate intraobserver reliability and inter-observer reproducibility of a 3-dimensional (3D) assessment method for mandibular changes of growing patients after orthodontic treatment for Class III malocclusion.Methods Cone-beam computed tomography (CBCT) scans were performed before and after orthodontic treatment for 27 patients. During the scan, the patient was positioned such that his/her mandibular plane was parallel to floor. Three observers independently worked on the DICOM data, reconstructed the pre- and post-treatment 3D models in software, selected the stable anatomical structures (basal bone area from the lingual surface of the symphysis to the distal aspect of the first molars) to guide the automated superimposition process. Then, each observer registered 14 anatomical landmarks on the virtual models, for three times after suitable interval, to generate 3 sets of coordinates; the mean was taken as the coordinates for that particular landmark. The intraobserver reliability and inter-observer reproducibility of the method were analyzed.Results The ICCs was > 0.90 for 25 (92.6%) of the intraobserver assessments. The precision of the measurement method was < 0.3mm in 24 (88.9%) cases. The interobserver reproducibility errors were < 0.3mm in 21 of the 27 cases.Conclusions The intraobserver reliability and inter-observer reproducibility of 3D assessment of mandibular changes using the virtual models were excellent.

Facial asymmetry and midsagittal plane definition in 3D: A bias-free, automated method.

Symmetry is a fundamental biological concept in all living organisms. It is related to a variety of physical and social traits ranging from genetic background integrity and developmental stability to the perception of physical appearance. Within this context, the study of human facial asymmetry carries a unique significance. Here, we validated an efficient method to assess 3D facial surface symmetry by best-fit approximating the original surface to its mirrored one. Following this step, the midsagittal plane of the face was automatically defined at the midpoints of the contralateral corresponding vertices of the superimposed models and colour coded distance maps were constructed. The method was tested by two operators using facial models of different surface size. The results show that the midsagittal plane definition was highly reproducible (maximum error < 0.1 mm or°) and remained robust for different extents of the facial surface model. The symmetry assessments were valid (differences between corresponding bilateral measurement areas < 0.1 mm), highly reproducible (error < 0.01 mm), and were modified by the extent of the initial surface model. The present landmark-free, automated method to assess facial asymmetry and define the midsagittal plane of the face is accurate, objective, easily applicable, comprehensible and cost effective.

Carbon-based light addressable potential sensor based on nitrogen-doped graphene quantum dots for detection of low-density lipoprotein

Cardiovascular diseases have become the number one killer of human health. Early diagnosis and treatment of cardiovascular diseases can effectively improve the treatment effect and reduce the disease death rate. As an important marker of cardiovascular disease, Low-Density Lipoprotein (LDL) can be used for the early detection of cardiovascular disease. In this study, a novel carbon-based Light Addressable Potentiometric Sensor (C-LAPS) for determination LDL has been constructed based on o-phenylenediamine modified nitrogen-doped graphene quantum dots/reduce graphene oxide (OPD@NGQDs/rGO) photosensitive layer. The OPD@NGQDs/rGO photosensitive layer has excellent photoelectric conversion efficiency, large specific surface area and good biocompatibility to enhance the response signal. For the determination LDL by the C-LAPS system, LDL binding to LDL aptamer causes a change in the surface potential of the photosensitive layer, producing a response signal that can be detected by the I-V curve. Under optimal conditions, the C-LAPS had a good linear relationship with LDL concentration in the range of 0.01 μg/mL- 0.15 μg/mL. The sensitivity was 1819 mV/µg·mL−1 and the limit of detection (LOD) was 6.43 ng/mL (S/N = 3). In addition, the C-LAPS showed good specificity, reproducibility, stability and satisfactory relative error for detecting LDL in human serum samples. Therefore, the C-LAPS has good performance and demonstrates potential clinical value.

3D Surface Imaging in Reducing Setup Error for Prone Whole Breast Radiotherapy

For patients undergoing whole breast radiotherapy, treatment in the prone position allows for reduced dose to critical organs such as the heart and lungs. However, this treatment position comes with greater challenges in reproducibility and setup error given the unstable position. Our objective was to investigate the benefit of using 3D surface imaging to reduce daily setup errors for these patients. We performed a retrospective review of consecutive breast patients receiving prone breast radiotherapy at our institution. All patients were positioned initially using setup tattoos and twice a week, the positioning was adjusted using the aid of a motion tracking system. Then, a daily kilovoltage (kV) cone beam computed tomography (CBCT) image was acquired and positioning was adjusted to setup the breast and chest wall. Shifts in each translational direction were recorded and the three-dimensional vector displacement was calculated. For each patient the average displacements on days where a motion tracking system was used were compared to days whereas motion tracking system was not used. Patients were classified into significant benefit (more than 4 mm improvement), small benefit (0-4 mm improvement) or increased error (increased shifts on days a motion tracking system was used). Patient demographics were collected including stage, BMI, weight, heigh, age, ethnicity. Comparisons were made using t-tests. A total of 40 patients with stage T0-2N0 breast cancer were included. The median age was 64 and 60% of patients had left sided breast cancer. A total of 665 daily CBCT scans were analyzed, and the median daily vector displacement was 7.2 mm (1-21 mm). The median displacement on treatments where a motion tracking system was used (41% of treatments) was 6.1 mm versus 8.1 mm when not used (p<.0001). The use of a motion tracking system significantly reduced the occurrence of shifts more than 1 cm (12% vs. 33%, p < .0001) and 5 mm (65% vs. 83% p < .0001). For individual patients, 28% showed a significant improvement, 55% showed small improvement, 17% showed increased error. The median BMI was 27, weight was 71 kg, and neither was associated with an improvement in the use of Align RT (p > .05). However, patients in the small improvement group had a higher BMI than patients in the other two groups 29 vs. 25 (p = .01). A similar association was seen for weight (p < .05). No association was found for the benefit of a motion tracking system for height, age, stage or ethnicity. The use of 3D surface imaging for breast cancer patients receiving prone whole breast radiotherapy on average significantly reduced setup errors. For patients with higher BMI there was a consistent small reduction in setup error when compared to using setup marks alone. For patients with lower BMI, caution should be exercised as there was more variation with some patients demonstrating a large benefit and other patients having an increased setup error with the use of surface imaging. Further research is needed to investigate on the optimal use of this technology.

Sensitive detection of heavy metal stress in aquatic plants by dissolved oxygen-quenched fluorescence/materials movement-induced beam deflection method.

Sensitive detection of heavy metal (HM) stress in aquatic plants by dissolved oxygen (DO)-quenched fluorescence/materials movement-induced beam deflection method is demonstrated. Egeria densa Planchon and Cu2+ were used as a model aquatic plant and HM ion, respectively. Reproducibility and experimental errors of the method were first investigated in a control culture solution only containing 10-6M Ru (II) complex (Tris (2,2'-bipyridyl) ruthenium (II) chloride) without addition of any fertilizer and Cu2+. Changes of DO concentration (∆DO) and deflection (∆DE) during the monitoring periods were used as parameters to quantitatively evaluate the experimental errors and detection limits. Averages or means ([Formula: see text], [Formula: see text]) and standard deviations (σ∆DO, σ∆DE) of ∆DO and ∆DE in seven control experiments with different aquatic plants sheets during both the respiration and photosynthesis processes were obtained. Next, DO and deflection at the middle vicinities of the aquatic plant were monitored during 2h of both respiration and photosynthesis in presence of 10-10 ~ 10-6M Cu2+. Experimental results showed that the aquatic plant began to suffer from the HM stress in some extent in presence of 10-9M Cu2+. When the concentration of Cu2+ was higher than 10-8M, changing trends of both DO and deflection with time were not reversed during the respiration and photosynthesis, implying that the materials movements in the physiological activities had been altered greatly. It is demonstrated that the method could sensitively detect the HM stress in the aquatic plants given by nM HM ions in culture solution without addition of a fertilizer. Furthermore, detection limits of the method were quantitatively discussed by considering [Formula: see text] σ∆DO and [Formula: see text] σ∆DE as the minimum detectable changes of DO and deflection caused by the HM stress, respectively.

A temperature sensor based on Er3+/Yb3+ co-doped tellurite fiber for real-time thermal monitoring of transformers

In this paper, a temperature sensor based on fluorescence intensity ratio (FIR) technique is prepared by the dual curing method. The pumping threshold is only 0.1 mW for the application of real-time thermal monitoring on small transformers. This not only greatly reduces the thermal effects accumulated by laser irradiation but also contributes to the integration and portability of the light source. Based on the FIR, the temperature information could be demodulated through tracking the fluorescence spectral changes. The basic temperature sensing characteristics of this sensor were evaluated, which showed that the maximum stability deviation and reproducibility error were within ±1.1 K and ±0.8 K, respectively. Notably, it has a maximum measurement error of only 0.61 K when applied to the temperature monitoring of transformers. And a fast time response of 2.1 s was exhibited in the cyclic exhalation experiment. This proposed sensor is suitable for mass production due to its resistance to electromagnetic interference, low pumping power, fast time response, excellent stability and reproducibility.

그리퍼 내에서 물체의 위치를 인지하기 위한 그리퍼의 5축 힘/모멘트센서 개발

In this paper, we describe the development of a 5-axis force/moment sensor of an intelligent gripper designed to grasp the weight of an unknown object and the position of the object in the gripper. The 5-axis force/moment sensor consists of an Fx force sensor, Fy force sensor, and Fz force sensor to measure weight, along with an Mx moment sensor and Mz moment sensor to determine the position of an object in the gripper. These sensors are all built within a single body. Each sensor sensing part of the 5-axis force/moment sensor was newly modeled and custom designed using software, and each sensor was manufactured by attaching a strain gauge. The results of the characteristic test of the fabricated 5-axis force/moment sensor showed that the rated output error was within 0.1%, the reproducibility error was within 0.05%, and the nonlinearity error was within 0.04%. Therefore, the 5-axis force/moment sensor developed in this paper can be attached to an intelligent gripper and be used to grasp the weight of an unknown object as well as the position of the object in the gripper.

An in-depth investigation on the behavior of measures to quantify reproducibility

Science is facing a so-called reproducibility crisis, where researchers struggle to repeat experiments and to get the same or comparable results. This represents a fundamental problem in any scientific discipline because reproducibility lies at the very basis of the scientific method. A central methodological question is how to measure reproducibility and interpret different measures. In Information Retrieval (IR), current practices to measure reproducibility rely mainly on comparing averaged scores. If the reproduced score is close enough to the original one, the reproducibility experiment is deemed successful, although the identical scores can still rely on entirely different result lists. Therefore, this paper focuses on measures to quantify reproducibility in IR and their behavior. We present a critical analysis of IR reproducibility measures by synthetically generating runs in a controlled experimental setting, which allows us to control the amount of reproducibility error. These synthetic runs are generated by a deterioration algorithm based on swaps and replacements of documents in ranked lists. We investigate the behavior of different reproducibility measures with these synthetic runs in three different scenarios. Moreover, we propose a normalized version of Root Mean Square Error (RMSE) to quantify reproducibility better. Experimental results show that a single score is not enough to decide whether an experiment is successfully reproduced because such a score depends on the type of effectiveness measure and the performance of the original run. This study highlights how challenging it can be to reproduce experimental results and quantify the amount of reproducibility.

Promising results of an non-invasive measurement of knee implant loosening using a loading device, CT-scans and 3D image analysis

BackgroundAfter total knee arthroplasty up to 13% requires revision surgery to address loosening. No current diagnostic modalities have a sensitivity or specificity higher than 70–80% to detect loosening, leading to 20–30% of patients undergoing unnecessary, risky and expensive revision surgery. A reliable imaging modality is required to diagnose loosening. This study presents a new and non-invasive method and evaluates its reproducibility and reliability in a cadaveric study. MethodsTen cadaveric specimens were implanted with a loosely fitted tibial components and CT scanned under load towards valgus and varus using a loading device. Advanced three-dimensional imaging software was used to quantify displacement. Subsequently, the implants were fixed to the bone and scanned to determine the differences between the fixed and the loose state. Reproducibility errors were quantified using a frozen specimen in which displacement was absent. FindingsReproducibility errors, expressed as mean target registration error, screw-axis rotation and maximum total point motion were 0.073 mm (SD 0.033), 0.129 degrees (SD 0.039) and 0.116 mm (SD 0.031), respectively. In the loose condition, all displacements and rotation changes were larger than the reported reproducibility errors. Comparing the mean target registration error, screw axis rotation and maximum total point motion in the loose condition to the fixed condition resulted in mean differences of 0.463 mm (SD 0.279; p = 0.001), 1.769 degrees (SD 0.868; p < 0.001) and 1.339 mm (SD 0.712; p < 0.001), respectively. InterpretationThe results of this cadaveric study show that this non-invasive method is reproducible and reliable for detection of displacement differences between fixed and loose tibial components.

Correction factor to the formula of sample reduction error

Introduction. Theoretical results have been obtained that allow calculating random sampling errors. One of the main calculation formulas for determining the sampling error is the sample reduction error formula. The sampling errors determined by this formula differ from the errors determined experimentally. The sample reduction error consists of several components, a separate quantitative determination of which is necessary when developing methodological support for testing processes. It is impossible to determine all these components separately from each other experimentally. It is necessary to determine the ratio of the components of the specified formula. Methods of research. The sample reduction error, determined analytically, is the minimum possible reduction error when this operation is ideally performed. To take into account the deviation from the ideal conditions for performing the reduction operation, it is necessary to experimentally estimate the amount of the actual deviation and link it with the theoretical result. As a result, the value of the correction factor can be obtained, which should be entered into the formula for calculating the reduction error. In order to eliminate the need for experimental determination of the error of the method of measuring the mass fraction, experiments to determine the correction factor should be performed on artificial samples with markers. Research procedure. Experiments were performed to reduce samples with markers. 480 reductions of the same sample were performed, which showed the coincidence of the theoretical and experimental distributions of the number of markers in the reduced samples. The correction factor in the experiment with markers of the correct shape was 1.3. The same coefficient in the experiment with markers whose granulometric composition match with that of the sample material was 2.0. The average value of the correction factor in reproducibility conditions was 2.13. Results and analysis. As a result of two experiments on multiple reduction of the sample, it was found that the correction factor under reproducibility conditions should be within 1.3 and 2.0. Similar information about the differences in reproducibility and repeatability errors in international and Russian standards shows that in order to move from a theoretical formula to a real reproducibility error, a correction factor from 2.0 to 3.0 should be introduced. Conclusions. The introduction of correction coefficients into the reduction error formula makes it possible to calculate the real errors of sample reduction, as well as quantify the results of mineral products testing based on the calculation.

Validity and reliability of a portable handheld dynamometer compared to a fixed isokinetic dynamometer to assess forearm torque strength

To evaluate the effect of treatment on forearm rotation, torque muscle strength can be assessed using an isokinetic device (IKD) or a wrist dynamometer (WD). The aims of this study were 1) to determine concurrent validity and intra- and inter-rater reliability using the WD, and to examine correlations between WD and IKD in different positions; and 2) subsequently, to establish the intermethod reproducibility between WD as a handheld (HHD) or fixed device. We conducted a cross-sectional study in which torque strength was measured in healthy participants by two observers using an IKD and a WD. Study endpoints were concurrent validity (Pearson’s r), intra- and inter-rater reliability, intermethod reproducibility (intraclass correlation coefficient: ICC) and measurement error (limits of agreement: LoA). Concurrent validity ranged, in the 2 studies assessing it, from r 0.37 to 0.52 for pronation and from r 0.50 to 0.82 for supination, with wide 95% confidence intervals. ICC for intra-rater reliability for pronation ranged from 0.85 to 0.91 and for supination from 0.91 to 0.95. ICC for inter-rater reliability for pronation ranged from 0.84 to 0.96 and for supination from 0.92 to 0.96. Despite the excellent intra- and inter-rater reliability and intermethod reproducibility for the WD-HHD and fixed WD, validity was low when compared to IKD and wide LoA indicated a high measurement error of approximately 20%. These results suggest that the WD cannot replace the IKD isometric mode for pronation and supination. Level of evidence2.

Extrapolation errors of force transducer curve fitting equations

Calibration laboratories often face the challenge of the impossibility to perform full capacity range calibration of their force transducers, particularly below 10 % of the force transducer’s capacity. Sometimes these laboratories use curve fitting extrapolation to estimate and predict force transducer behavior within uncalibrated capacity ranges. This work deals with the study of extrapolation errors in force transducers to know and estimate prediction accuracies when using extrapolation for force transducer calibration in ranges below 10 % and between 50 % and 100 % of the transducer’s capacity. The results of this study showed that the magnitude of the extrapolation error is very close to the magnitude of the reproducibility error within calibrated capacity ranges in the laboratory.

Interlaboratory Comparison of 226Ra and 228Ra Activity Concentrations in Groundwater and Surface Water

226Ra and 228Ra are typically monitored for groundwater and surface water compliance at legacy U mining and milling sites. Groundwater monitoring results for combined Ra (226Ra + 228Ra) reported by the existing contract laboratory at a former U mine and mill Site (Converse County, WY, USA) have been highly variable and with increasing trends at the Site compliance and background wells since the method was changed in 2005. Sample reanalysis has indicated poor reproducibility and significant analytical error in 228Ra measurements. An interlaboratory comparison was conducted to evaluate the potential causes of the high variability and analytical error. Two different methods were used for 226Ra (M903.0 and M903.1) and 228Ra (M904.0 and Ra-05). 226Ra results were less variable compared to 228Ra, and 228Ra data from the existing laboratory were qualified as estimated with high bias due to detection of 228Ra in the field blank. Compliance with the 226Ra + 228Ra groundwater standard was either met or not met, depending on which laboratory conducted the analyses. Specific laboratory techniques, rather than the analytical method, are contributing to elevated 228Ra values being reported. It was recommended that samples whose 226Ra + 228Ra results exceed the Site standard in the future be reanalyzed by the existing laboratory with a sample split also being sent to an outside laboratory for confirmatory analysis.

Research on Rapid Identification Technology of Sand and Dust Characteristic Monitoring Data Based on Optimized K-Means Clustering

The criteria-based sand and dust weather determination method has the problem ofbeing a cumbersome and time-consuming process when processing a large amount of raw data, and cannot avoid the problems of repeatability and reproducibility. On the basis of statistical analysis of the air automatic monitoring data in the cities affected by sand and dust, this paper proposes a k-means optimization algorithm (MDPD-k-means) based on maximum density and percentage distance, which can quickly filter the characteristic data of sand and dust in a short time, and identify the days affected by sand and dust. This method effectively improves the data processing efficiency, solves the problems of poor reproducibility and large artificial error of traditional methods, and can support the business application of sand and dust data elimination. This paper uses the method to identify the sand and dust data of 10 cities in Shaanxi Province from 2016 to 2022, determines a total of 1107 sand and dust days, and points out that the number of days affected by sand and dust is increasing year by year. After excluding the effect of sand and dust, the urban PM10 concentration decreases by 18.42~1.41% respectively, which provides important data information for accurately evaluating the effectiveness of air pollution prevention and control.