Correction Of Systematic Errors Research Articles

Scaling and merging macromolecular diffuse scattering with mdx2.

Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three-dimensional reciprocal-space map that is further analyzed todetermine correlated motion. To make diffuse scattering techniques more accessible, software for data processing called mdx2 has been created that is both convenient to use and simple to extend and modify. mdx2 is written in Python, and it interfaces with DIALS to implement self-contained data-reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. mdx2 can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, mdx2 version 1.0 is described, a new release incorporating state-of-the-art techniques for data reduction. The implementation of a complete multi-crystal scaling and merging workflow is described, and the methods are tested using a high-redundancy data set from cubic insulin. It is shown that redundancy can be leveraged during scaling to correct systematic errors and obtain accurate and reproducible measurements of weak diffuse signals.

Novel correction procedure for compensating thermal contraction errors in the measurement of the magnetic field of superconducting undulator coils in a liquid helium cryostat.

Superconducting undulators (SCUs) can offer a much higher on-axis undulator field than state-of-the-art cryogenic permanent-magnet undulators with the same period and vacuum gap. The development of shorter-period and high-field SCUs would allow the free-electron laser and synchrotron radiation source community to reduce both the length of undulators and the dimensions of the accelerator. Magnetic measurements are essential for characterizing the magnetic field quality of undulators for operation in a modern light source. Hall probe scanning is so far the most mature technique for local field characterization of undulators. This article focuses on the systematic error caused by thermal contraction that influences Hall probe measurements carried out in a liquid helium cryostat. A novel procedure, based on the redundant measurement of the magnetic field using multiple Hall probes at known relative distance, is introduced for the correction of such systematic error.

Performance of an offline systematic error correction strategy in pediatric patients receiving adjuvant conformal radiotherapy for Wilm's tumor.

Radiotherapy plays a key role as an adjuvant treatment in pediatric Wilm's tumor, improving both survival and quality of life. The success of radiotherapy depends on the precise delivery of radiation dose to the tumor while sparing radiosensitive structures in the vicinity of the tumor. Pediatric patients pose unique challenges in achieving accurate radiotherapy delivery due to their inability to understand instructions and the high radiosensitivity of their tissues. Thus, it is important to determine the optimum geometric verification strategy that will ensure accurate delivery of the prescribed target as specified in the patient's treatment plan. To evaluate the performance of an offline geometric correction strategy in ensuring accuracy and reproducibility during radiotherapy delivery in Wilm's tumor patients. The extended no-action level offline correction strategy was applied in the radiotherapy delivery of 45 Wilm's tumor patients. Gross errors from the first three fractions were used to calculate the mean errors which were then applied as offline correction factors. Mean errors among different groups were compared using a two-way analysis of variance (ANOVA) and Dunnett's pairwise comparisons. All statistical analyses and data visualization were performed using GraphPad Prism version 7 (Insight Partners, GraphPad Holdings, LLC). A total of 45 patients were included in the study. In all three orthogonal directions, the recorded gross errors were significantly lower after the application of the systematic error corrections. Random errors were significantly larger in the longitudinal direction compared to lateral (mean difference = 0.28, p = 0.036) and vertical directions (mean difference = 0.37 cm, p = 0.003). Patients' age was a significant predictor of random errors whereby the magnitude of random error decreased with increasing age. This study shows that the offline correction strategy used is effective in ensuring the accuracy of radiotherapy delivery in pediatric Wilm's tumor patients.

Using XAS to monitor radiation damage in real time and post-analysis, and investigation of systematic errors of fluorescence XAS for Cu-bound amyloid-β.

X-ray absorption spectroscopy (XAS) is a promising technique for determining structural information from sensitive biological samples, but high-accuracy X-ray absorption fine structure (XAFS) requires corrections of systematic errors in experimental data. Low-temperature XAS and room-temperature X-ray absorption spectro-electrochemical (XAS-EC) measurements of N-truncated amyloid-β samples were collected and corrected for systematic effects such as dead time, detector efficiencies, monochromator glitches, self-absorption, radiation damage and noise at higher wavenumber (k). A new protocol was developed using extended X-ray absorption fine structure (EXAFS) data analysis for monitoring radiation damage in real time and post-analysis. The reliability of the structural determinations and consistency were validated using the XAS measurement experimental uncertainty. The correction of detector pixel efficiencies improved the fitting χ2 by 12%. An improvement of about 2.5% of the structural fitting was obtained after dead-time corrections. Normalization allowed the elimination of 90% of the monochromator glitches. The remaining glitches were manually removed. The dispersion of spectra due to self-absorption was corrected. Standard errors of experimental measurements were propagated from pointwise variance of the spectra after systematic corrections. Calculated uncertainties were used in structural refinements for obtaining precise and reliable values of structural parameters including atomic bond lengths and thermal parameters. This has permitted hypothesis testing.

Unbiased centroiding of point targets close to the Cramer Rao limit.

Systematic errors affecting center-of-gravity (CoG) measurements may occur from coarse sampling of the point-spread-function (PSF) or from signal truncation at the boundaries of the region-of-interest (ROI). For small ROI and PSF widths, these effects are shown to become dominant, but this can be mitigated by introducing novel unbiased estimators that are largely free of systematic error and perform particularly well for low photon numbers. Analytical expressions for the estimator variances, comprising contributions from photon shot noise, random pixel noise, and residual systematic error, are derived and verified by Monte Carlo simulations. The accuracy and computational speed of the unbiased estimators are compared to those of other common estimators, including iteratively weighted CoG, thresholded CoG, iterative least squares fitting, and two-dimensional Gaussian regression. Each estimator is optimized with respect to ROI size and PSF radius and its error compared to the theoretical limit defined by the Cramer Rao lower bound (CRLB). The unbiased estimator with full systematic error correction operating on a small ROI [3×3] emerges as one of the most accurate estimators while requiring significantly less computing effort than alternative algorithms.

Erection strategy for main cable based on unstrained length of parallel wire strands

This paper presents a construction scheme aimed at achieving one-time erection of strands through precise control of the unstrained length. The scheme entails correcting system errors through the initial strand erection and reducing the influence of random errors by improving manufacturing conditions and increasing field measurements. The key objective is to control cable erection using cable length. A reliability analysis program was developed to assess the accuracy of the main cable installation. A case study of an actual bridge was conducted to verify the feasibility of the scheme. First, an assessment of the distribution characteristics of the random variables was performed. Subsequently, a comparative analysis was performed to evaluate the reliability of the proposed scheme against conventional erection methods. Finally, the new method was validated by on-site installation of several strands. Results revealed that while the reliability of cable formation shape was comparable between the traditional method and the proposed scheme, the latter exhibited superior uniformity of internal force among cable strands after formation. In addition, the average value of the cable length correction for Nos. 2 to 15 strands closely aligns with that of the reference strand, suggesting that the systematic error correction determined by the reference strand exhibits relatively high accuracy. Furthermore, strands erected with cable length as the control objective effectively maintained sag errors within the range of [− 4 mm, 8 mm], demonstrating a high level of precision.

Improving odometric sensor performance by real-time error processing and variable covariance

This paper presents a new method to increase odometric sensor accuracy by systematic and non-systematic errors processing. Mobile robot localization is improved combining this technique with a filter that fuses the information from several sensors characterized by their covariance. The process focuses on calculating the odometric speed difference with respect to the filter to implement an error type detection module in real time. The correction of systematic errors consists in an online parameter adjustment using the previous information and conditioned by the filter accuracy. This data is also applied to design a variable odometric covariance which describes the sensor reliability and determines the influence of both errors on the robot localization. The method is implemented in a low-cost autonomous wheelchair with a LIDAR, IMU and encoders fused by an UKF algorithm. The experimental results prove that the estimated poses are closer to the real ones than using other well-known previous methods.

Correcting systematic errors in diffraction data with modern scaling algorithms.

X-ray diffraction enables the routine determination of the atomic structure ofmaterials. Key to its success are data-processing algorithms that allow experimenters to determine the electron density of a sample from its diffraction pattern. Scaling, the estimation and correction of systematic errors in diffraction intensities, is an essential step in this process. These errors arise from sample heterogeneity, radiation damage, instrument limitations and other aspects of the experiment. New X-ray sources and sample-delivery methods, along with new experiments focused on changes in structure as a function of perturbations, have led to new demands on scaling algorithms. Classically, scaling algorithms use least-squares optimization to fit a model of common error sources to the observed diffraction intensities to force these intensities onto the same empirical scale. Recently, an alternative approach has been demonstrated which uses a Bayesian optimization method, variational inference, to simultaneously infer merged data along with corrections, or scale factors, for the systematic errors. Owing to its flexibility, this approach proves to be advantageous in certain scenarios. This perspective briefly reviews the history of scaling algorithms and contrasts them with variational inference. Finally, appropriate use cases are identified for the first such algorithm, Careless, guidance is offered on its use and some speculations are made about future variational scaling methods.

Wapiti: A data-driven approach to correct for systematics in RV data

Context. Recent advances in the development of precise radial velocity (RV) instruments in the near-infrared (near-IR) domain, such as SPIRou, have facilitated the study of M-type stars to more effectively characterize planetary systems. However, the near-IR presents unique challenges in exoplanet detection due to various sources of planet-independent signals which can result in systematic errors in the RV data. Aims. In order to address the challenges posed by the detection of exoplanetary systems around M-type stars using near-IR observations, we introduced a new data-driven approach for correcting systematic errors in RV data. The effectiveness of this method is demonstrated through its application to the star GJ 251. Methods. Our proposed method, Weighted principAl comPonent reconsTructIon (referred to as Wapiti), used a dataset of per-line RV time series generated by the line-by-line (LBL) algorithm and employed a weighted Principal Component Analysis (wPCA) to reconstruct the original RV time series. A multistep process was employed to determine the appropriate number of components, with the ultimate goal of subtracting the wPCA reconstruction of the per-line RV time series from the original data in order to correct systematic errors. Results. The application of Wapiti to GJ 251 successfully eliminated spurious signals from the RV time series and enabled the first detection in the near-IR of GJ 251b, a known temperate super-Earth with an orbital period of 14.2 days. This demonstrates that, even when systematics in SPIRou data are unidentified, it is still possible to effectively address them and fully realize the instrument’s capability for exoplanet detection. Additionally, in contrast to the use of optical RVs, this detection did not require us to filter stellar activity, highlighting a key advantage of near-IR RV measurements.

Magnetic Model Calibration and Distortion Compensation for Electromagnetic Tracking in a Clinical Environment

Electromagnetic tracking (EMT) of surgical tools is used for image-guided navigation in minimally invasive interventions. Calibration of the tracker position and orientation is a fundamental task to correct systematic errors. This article explores the effect of metallic distortion on the open hardware Anser EMT system and describes a newly developed approach for volume calibration of the magnetic field model. The technique is also applied to effectively map the field in the presence of magnetic shields that can be used to reduce electromagnetic distortions passively. Unlike calibration techniques commonly found in literature, which aim to correct the tracking position error, our method can reconstruct an analytical magnetic field model starting from a reduced amount of scattered data. This way, a faster convergence of the solver algorithm is obtained, and EMT position and orientation errors are inherently corrected. The new modelling technique was applied to generate a new, undistorted magnetic field model for Anser EMT, to demonstrate the effectiveness of passive shielding, and to compensate for the distortion introduced by a commercial fluoroscopy C-arm. Furthermore, the concept of a real-time distortion compensation technique is expressed based on the modelling method presented in this article. For all the experiments, sub-millimeter errors were obtained after calibration, which may meet the needs of most endoscopic and surgical navigation tasks.

BEYONDPLANCK

We present a Gibbs sampling solution to the mapmaking problem for cosmic microwave background (CMB) measurements that builds on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps: noise filtering and map binning. Considered as two separate steps, both are computationally much cheaper than solving the combined problem. This provides a huge performance benefit as compared to traditional methods and it allows us, for the first time, to bring the destriping baseline length to a single sample. Here, we applied the Gibbs procedure to simulatedPlanck30 GHz data. We find that gaps in the time-ordered data are handled efficiently by filling them in with simulated noise as part of the Gibbs process. The Gibbs procedure yields a chain of map samples, from which we are able to compute the posterior mean as a best-estimate map. The variation in the chain provides information on the correlated residual noise, without the need to construct a full noise covariance matrix. However, if only a single maximum-likelihood frequency map estimate is required, we find that traditional conjugate gradient solvers converge much faster than a Gibbs sampler in terms of the total number of iterations. The conceptual advantages of the Gibbs sampling approach lies in statistically well-defined error propagation and systematic error correction. This methodology thus forms the conceptual basis for the mapmaking algorithm employed in the BEYONDPLANCKframework, which implements the first end-to-end Bayesian analysis pipeline for CMB observations.

Correction of systematic errors in electronic performance and tracking systems

Electronic performance and tracking systems are becoming a standard in many sports to automate data collection and gather more profound insights into performance and game dynamics. In large soccer clubs and federations, the problem is that different electronic performance and tracking systems report different kinematic parameters and performance indicators, which should be the same. Furthermore, a drawback in recent validation studies is the subdivision of speed and acceleration zones in validating the systems, as we show that the kinematic parameters are interdependent. We propose a new method to classify multidimensional validation outputs with a clustering approach. Additionally, we offer a data-driven strategy to reduce errors between distinct systems when data from different electronic performance and tracking systems are compared and show the method’s effectiveness with data collected in a validation study. This error reduction strategy can be applied to correct errors when no validation data is available.

High Resolution Fourier Transform Spectrometer for Ground-Based Verification of Greenhouse Gases Satellites

Satellite remote sensing is currently the best monitoring means to obtain global carbon source and sink data. The United States, Japan, China and other countries are vigorously developing spaceborne detection technology. However, the important factors that restrict the application of greenhouse gas satellite remote sensing technology include the limited accuracy of data products. How to improve the retrieval level of greenhouse gas payloads is a problem that needs to be solved urgently. One effective way to improve data quality is to carry out satellite ground synchronous authenticity verification and system error correction. This paper mainly aims at the shortcomings of the existing TCCON and the portable verification equipment EM27/SUN, and develops a High-Resolution Fourier Transform Spectrometer (HRFTS) based on dynamic collimation technology. Through the gas absorption method and the band scanning method of the hyperspectral monochromatic light source, the instrument’s absorption spectrum measurement capability and the Instrument Line Shape (ILS) are demonstrated. The instrument’s spectral resolution is consistent with the on-orbit greenhouse gas satellite load, reaching 0.26 cm−1. For the interference data obtained by the spectrometer, spectral restoration processing, data quality control and inversion algorithm optimization were carried out to solve the problems of baseline correction, spectral fine registration, and environmental parameter profile reconstruction, and cross comparison experiments with EM27/SUN were carried out simultaneously. Finally, for the gases monitoring instrument (GMI) of the GF5-02 satellite launched on 7 September 2021, the first satellite ground synchronization verification experiment with high space-time matching was carried out. The results showed that the CO2 column concentration deviation of the satellite ground synchronization inversion was about 1.5 ppm, and the CH4 column concentration deviation was about 11.3 ppb, which verified the on-orbit detection accuracy of the GMI, and laid a foundation for the subsequent satellite inversion algorithm optimization and systematic error correction.

Augmented Underwater Acoustic Navigation with Systematic Error Modeling Based on Seafloor Datum Network

Underwater acoustic navigation technology is an important approach to achieving high precision ocean navigation. One of the critical issues of the technology is to correct systematic errors, which are related to time delays and time-varying sound speed errors. In this study, we propose an augmented underwater acoustic navigation with systematic error model based on seafloor datum network. The proposed algorithm first selects data sets of piece-wise systematic error modeling by extracting the main periodic term of systematic errors based on the Fourier transform. Before that, the wavelet transform is used for denoising to better extract the main periodic term. Then the systematic error correction model is constructed by using the polynomial fitting method. After that, an augmented observation equation of underwater acoustic navigation with systematic error correction is constructed. Finally, an adaptive robust Kalman filter is developed for underwater acoustic navigation. The proposed algorithm is verified by an experiment in the South China Sea. The three-dimensional root mean square values of underwater acoustic navigation are 1.010 and 1.502 m in the operating range of 2.7 and 8.7 km. The results demonstrate that the proposed algorithm can efficiently reduce the influence of systematic error, thus improving underwater acoustic navigation accuracy.

BIOLOGICAL AGE OF PHYSIOLOGICAL SYSTEMS OF THE ORGANISM AND PROFILE OF HUMAN AGING

Aim of the study: comprehensive assessment of the rate of aging of the main physiological systems of the body and analysis of the relationships between them. Materials and methods. 188 practically healthy people of various ages (73 men and 115 women) were examined. Methods: anthropometry, echocardiography with Doppler, spirography, ECG with heart rhythm variability analysis, dual X-ray absorptiometry, clinical laboratory biochemical tests. Results. The method of stepwise multiple regression with systematic error correction was used to calculate the formulas of biological age (BA) of the cardiovascular, respiratory, musculoskeletal systems, autonomic regulation, and metabolic age. The obtained formulas make it possible to estimate the rate of aging of the body’s physiological systems with high accuracy (error of 4–5 years). An original method of calculating the integral BA based on the BA of separate body systems is proposed. Conclusion. By calculating the BA of many body systems, it is possible to estimate the rate of aging of these systems and build a human aging profile. This makes it possible to predict the risk of developing one or another age-related pathology and purposefully apply the necessary treatment and preventive measures. A comprehensive assessment of the rate of aging of the body’s physiological systems made it possible to study the heterochrony of aging, the main trajectories of the body’s aging. The connections between the aging of different body systems revealed in our research are important for the development of a strategy for antiaging effects and prevention of age-related pathology. Keywords: biological age, physiological systems, aging profile

A Case Study of Bias Correction and the Dynamical Downscaling of CFSv2 S2S Forecasts Using a WRF Model: Heatwave in 2018 over South Korea

Extreme weather events caused by climate change affect the growth of crops, requiring reliable weather forecasts. In order to provide day-to-season seamless forecasting data for the agricultural sector, improving the forecasting performance of the S2S period is necessary. A number of studies have been conducted to improve prediction performance based on the bias correction of systematic errors in GCM or by producing high-resolution data via dynamic detailing. In this study, a daily simple mean bias correction technique is applied on CFSv2 (∼100 km) data. We then use case studies to evaluate how beneficial the precision of the high-resolution RCM simulation is in improving S2S prediction performance using the bias-corrected lateral boundary. Based on our examination of 45-day sequences of WRF simulations with 27–9–3 km resolution, it can be concluded that a higher resolution is correlated with better prediction in the case of the extreme heatwave in Korea in 2018. However, the effect of bias correction in improving predictive performances is not significant, suggesting that further studies on more cases are necessary to obtain more solid conclusions in the future.

Associations of Biomarker-Calibrated Healthy Eating Index-2010 Scores with Chronic Disease Risk and Their Dependency on Energy Intake and Body Mass Index in Postmenopausal Women

Prior studies examined associations between the Healthy Eating Index (HEI) and chronic disease risk based on self-reported diet without measurement error correction. Our objective was to test associations between biomarker calibration of the food-frequency questionnaire (FFQ)-derived HEI-2010 with incident cardiovascular disease (CVD), cancer, and type 2 diabetes (T2D) among Women's Health Initiative (WHI) participants. Data were derived from WHI postmenopausal women (n = 100,374) aged 50-79 y at enrollment (1993-1998) at 40 US clinical centers, linked to nutritional biomarker substudies and outcomes over subsequent decades of follow-up. Baseline or year 1 FFQ-derived HEI-2010 scores were calibrated with nutritional biomarkers and participant characteristics (e.g., BMI) for systematic measurement error correction. Calibrated data were then used in HR models examining associations with incidence of CVD (total, subtypes, mortality), cancer (total, subtypes, mortality), and T2D in WHI participants with approximately 2 decades of follow-up. Models were multivariable-adjusted with further adjustment for BMI and doubly labeled water (DLW)-calibrated energy. Multivariable-adjusted HRs modeled a 20% increment in HEI-2010 score in relation to outcomes. HRs were modest using uncalibrated HEI-2010 scores (HRs = 0.91-1.09). Using biomarker-calibrated HEI-2010, 20% increments in scores yielded multivariable-adjusted HRs (95% CIs) of 0.75 (0.60, 0.93) for coronary heart disease; 0.75 (0.61, 0.91) for myocardial infarction; 0.96 (0.92, 1.01) for stroke; 0.88 (0.75, 1.02) for CVD mortality; 0.81 (0.70, 0.94) for colorectal cancer; 0.81 (0.74, 0.88) for breast cancer; 0.79 (0.73, 0.87) for cancer mortality; and 0.45 (0.36-0.55) for T2D. Except for cancer mortality and T2D incidence, results became null when adjusted for DLW-calibrated energy intake and BMI. Biomarker calibration of FFQ-derived HEI-2010 was associated with lower CVD and cancer incidence and mortality and lower T2D incidence in postmenopausal women. Attenuation after adjustment with BMI and DLW-calibrated energy suggests that energy intake and/or obesity are strong drivers of diet-related chronic disease risk in postmenopausal women. The Women's Health Initiative is registered at clinicaltrials.gov at NCT00000611.

A Polynomial Transform Method for Hardware Systematic Error Identification and Correction in Semiconductor Multi-Site Testing

A Polynomial Transform Method for Hardware Systematic Error Identification and Correction in Semiconductor Multi-Site Testing

EAKF-Based Parameter Optimization Using a Hybrid Adaptive Method

Abstract To effectively reduce model bias and improve assimilation quality, we adopt a hybrid adaptive approach of ensemble adjustment Kalman filter (EAKF) and multigrid analysis (MGA), called EAKF-MGA, to implement parameter optimization as follows. For each assimilation cycle, observations are used to adjust the prior ensembles of both state variables and parameters using the EAKF without inflation. Then, the MGA is adaptively triggered to extract multiscale information from the observational residual to innovate the ensemble mean of the state once again. Results of biased twin experiments consisting of a barotropic spectral model and idealized observation systems show that the proposed EAKF-MGA is insensitive to state variance inflation and localization during the parameter optimization process, compared with the EAKF with adaptive inflation. We also find that computational efficiency is another important advantage of the EAKF-MGA for both state estimation and parameter estimation since extremely small ensemble size is allowed, while the EAKF with adaptive inflation does not work anymore. In essence, the EAKF-MGA is designed to estimate and correct systematic errors jointly with model’s state variables. Through alleviating biases, including the model bias caused by the biased parameter and the analysis bias resulting from the sampling noise given the limited ensemble size, it can be guaranteed that the analysis in the EAKF-MGA will be proceeded onward with the standard assumption of the unbiased model background field in modern data assimilation theory to be met.

Systematic error compensation for improving accuracy of the electrosurgical unit.

This paper presents an approach to systematic error correction for improving the accuracy of the electrosurgical unit (ESU), through a method that enables safer operation for both surgeons and patients. The equations for systematic errors encountered during the calibration of the eight ESUs were obtained using regression analysis. The ESU calibration was performed using a power analyzer and the reference power value was selected on the ESU panel; the power value indicated by the ESU was noted from the power analyzer and recorded. The fitted regression models were suitable for predicting systematic errors associated with ESU output power values, as a reduction of about 84 % was noted in cutting power (CuP) and about 74 % for coagulation power (CoP). After correction, systematic error values remained below 1.9 W and 0.4 W in cutting and coagulation power, respectively. The maximum error values obtained were less than those specified for the IEC 60601-2-2 standard for all evaluated ESUs.