Instrumental Errors Research Articles

SWOT Data Assimilation with Correlated Error Reduction: Fitting Model and Error Together

Abstract The Surface Water Ocean Topography (SWOT) satellite mission provides high-resolution two-dimensional sea surface height (SSH) data with swath coverage. However, spatially correlated errors affect these SSH measurements, particularly in the cross-track direction. The scales of errors can be similar to the scales of ocean features. Conventionally, instrumental errors and ocean signals have been solved for independently in two stages. Here, we have developed a one-stage procedure that solves for the correlated error at the same time that data are assimilated into a dynamical ocean model. This uses the ocean dynamics to distinguish ocean signals from observation errors. We test its performance relative to the two-stage method using simplified dynamics and a data set consisting of westward propagating Rossby waves, along with correlated instrumental errors of varying magnitudes. In a series of tests, we found that the one-stage approach consistently outperforms the two-stage approach when estimating SSH signal and correlated errors. The one-stage approach can recover over 95% of the SSH signal, while skill for the two-stage approach drops significantly as error increases. Our findings suggest that solving for the correlated errors within the assimilation framework can provide an effective analysis approach, reducing the risks of confounding signal and instrument noise.

Leveraging virtual reality for advanced scrub nurse education: A non-randomized comparative study of training effectiveness

BackgroundProximal femur fractures are common among the elderly, often leading to various complications if the waiting period for surgery is prolonged. Traditional manual-based training for scrub nurses poses challenges in visualizing and understanding surgical procedures. Virtual Reality (VR) offers a potential solution by providing an immersive and interactive learning environment. PurposeThis study aimed to evaluate the effectiveness of VR-based training compared to traditional manual-based training for scrub nurses involved in orthopedic trauma surgeries. MethodsA single-center non-randomized comparative study was conducted with 10 scrub nurses at a tertiary emergency medical facility in eastern Asia. Participants were divided into a manual-based learning group and a VR-based learning group. The effectiveness of each training method was assessed using self-assessment and peer assessment questionnaires, as well as by measuring surgery time, anesthesia time, and the number of instrument errors. FindingsThe VR group reported significantly higher self-assessment scores in terms of realism, understanding of surgical procedures, and instrument preparation (p < .05). Peer assessments indicated no significant differences between the groups in practical performance (p > .05). The Steps for Coding and Theorization (SCAT) analysis revealed that VR enhanced the learning experience by providing a dynamic and immersive environment, although some limitations, such as difficulties in fine hand movements and potential for motion sickness, were noted. ConclusionsVR-based learning offers significant advantages over traditional manual-based learning for scrub nurses by enhancing understanding of surgical procedures and improving instrument preparation. Integrating VR into nursing education can enhance training outcomes, but further research is needed to address its limitations and optimize its use.

An Interpretation Method of Gas–Water Two-Phase Production Profile in High-Temperature and High-Pressure Vertical Wells Based on Drift-Flux Model

With the increasing demand for oil and gas, the depth of some vertical gas wells can reach 6000 m. At this time, the downhole fluid is in a state of high temperature and pressure, and interpretation of the production logging output profile faces the problem of inaccurate production calculations and difficulty judging the water-producing layer. The drift-flux model is usually used to calculate the gas–water two-phase flow. The drift-flux model is widely used to describe the two-phase flow in pipelines and wells because of its accuracy and simplicity. The constitutive correlations used in drift-flux models, which specify the relative motion between phases, have been extensively studied. However, most of the correlations are only extended by laboratory data of small pipe diameters at standard temperature and pressure and do not apply to high-temperature and high-pressure large-diameter gas wells. Therefore, we improved the distribution coefficient and drift velocity of drift-flux correlations in this study for high-temperature and high-pressure gas wells with large pipe diameters. Therefore, this study improved the distribution coefficient and drift velocity of the drift-flux correlations for high-temperature and high-pressure gas wells with large pipe diameters. In practical application, the coincidence rates of gas production and water production calculated by the new drift-flux model were 12.68% and 19.39%, respectively. For high-temperature and high-pressure deep wells, the measurement errors of production logging instruments are significant, and surface laboratory pipelines are challenging to configure and equip with actual high-temperature and high-pressure conditions. Therefore, this study used the method of numerical simulation to study the flow characteristics of the two phases of high-temperature and high-pressure gas and water to provide a basis for identifying the water layer. Combined with the proposed drift-flux correlations and the new method of determining the water-producing layer, a new method of production profile interpretation of high-temperature and high-pressure gas wells is obtained.

Assessment of Non-Linear Modeling of Ladle Furnace Transformer Using Finite Element Analysis

This paper assesses a non-linear model of a three-phase Ladle Furnace Transformer, on slow front transients under no-load conditions. The model is designed to maintain accuracy and reduce complexity in estimating equivalent circuit parameters using three methods: analytical calculations, finite element analysis, and test measurement. The results reveal that analytical and finite element methods show discrepancies lower than 1%. Tests measurement, on the other hand, shows discrepancies higher than 5%, when compared to ones obtained from analytical and finite elements methods. Such discrepancy is particularly high in the estimation of leakage inductances and capacitances, and it is attributed mainly to differences between the transformer design and its actual assembly. Additionally, there are inherent inaccuracies in test procedures and instrumentation errors. The proposed model does not require difficult-to-obtain parameters and incorporates the non-linearity of magnetizing inductance, contributing to more accurate simulations. This simplified model is suitable for analyzing slow front transients and can be integrated into future studies addressing vacuum circuit breaker switching in electric arc furnace power systems, contributing to performance improvements in industrial applications. Additionally, the methodology for parameter determination can be applied to conventional power transformers, highlighting its versatility.

Rainfall From Brazilian Flying Rivers: Evaluating the Effectiveness of Precipitation Gridded Databases

ABSTRACTThe uneven global distribution of rainfall significantly impacts water resources and environmental sustainability, emphasising the need for reliable climate prediction models. Accurate predictions are vital for sectors such as food security, urban planning and disaster management. Data from ground stations, radars and satellites are essential, despite challenges like instrumental errors. Satellites, with their comprehensive sensors, are crucial for atmospheric observations, aiding in the prediction of large‐scale climatic events. Climate models such as CHIRPS, GLDAS, TerraClimate, and PERSIANN use different approaches to analyse precipitation data, which is key to understanding its spatial and temporal variability. This study evaluated (rainfall data) from these four climate models over 20 years (within the Brazilian territory), focusing on the spatiotemporal behaviour of rainfall using statistical metrics such as R2, RMSE, and MAPE. The findings showed that CHIRPS had the best performance (R2 = 0.843; RMSE = 42.83; MAPE = 0.09%), excelling in both overall database and extreme event analyses. TerraClimate, initially the lowest‐performing model (R2 = 0.413; RMSE = 91.56; MAPE = 0.23%), improved significantly when combined with elevation through multiple linear regression (MLR), achieving R2 of 0.718, RMSE of 31.14, and MAPE of 9.56%. This made TerraClimate a viable model for studying the Flying Rivers. The study highlights that model selection should align with the specific characteristics of the area under consideration, with CHIRPS being particularly suitable for the studied region. This research enhances the understanding of the effectiveness of these models in estimating rainfall compared to in situ measurements, which is crucial for various applications. The authors advocate for further studies to advance research on the Flying Rivers, their significance, and the impacts of climate change on them.

MEASUREMENT ERRORS OF THE FLOW OF NATURAL GAS IN UNCERTAINTY CONDITIONS

The relevance of the topic related to improving the processing of fuzzy information in the control and management system of the natural gas transportation process is substantiated. Factors influencing the errors of instruments that provide gas flow measurement in gas transportation process monitoring and control systems, additional errors arising depending on the influence of the environment, gas content, humidity and hydration in the process of gas flow measurement are determined, and ways and methods for their elimination are analyzed. An analysis of current literature sources, which examines the reasons why measuring instruments have errors and uncertainty is provided. The feasibility of increasing the accuracy and reliability of measurements of natural gas consumption is shown by using new tools and methods of modern information technologies, based on fuzzy sets and fuzzy logic, the feasibility of reducing uncertainty and errors associated with fuzziness based on fuzzy decision-making criteria, for which purpose in uncertain information environment, and new information technologies and Softcomputing technologies, which represent a powerful mathematical apparatus to reduce measurement and processing errors; this is especially clear when identifying mathematical models of technological processes, such as natural gas transportation. Keywords: natural gas, gas flow, error, uncertain information, fuzzy set.

Calibration and Validation of NOAA-21 Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper Sensor Data Record Data

The Ozone Mapping and Profiler Suites (OMPS) Nadir Mapper (NM) is a grating spectrometer within the OMPS nadir instruments onboard the SNPP, NOAA-20, and NOAA-21 satellites. It is designed to measure Earth radiance and solar irradiance spectra in wavelengths from 300 nm to 380 nm for operational retrievals of the nadir total column ozone. This study presents calibration and validation analysis results for the NOAA-21 OMPS NM SDR data to meet the JPSS scientific requirements. The NOAA-21 OMPS SDR calibration derives updates of several previous OMPS algorithms, including the dark current correction algorithm, one-time wavelength registration from ground to on-orbit, daily intra-orbit wavelength shift correction, and stray light correction. Additionally, this study derives an empirical scale factor to remove 2.2% of systematic biases in solar flux data, which were caused by pre-launch solar calibration errors of the OMPS nadir instruments. The validation of the NOAA-21 OMPS SDR data is conducted using various methods. For example, the 32-day average method and radiative transfer model are employed to estimate inter-sensor radiometric calibration differences from either the SNPP or NOAA-20 data. The quality of the NOAA-21 OMPS NM SDR data is largely consistent with that of the SNPP and NOAA-20 OMPS data, with differences generally within ±2%. This meets the scientific requirements, except for some deviations mainly in the dichroic range between 300 nm and 303 nm. The deep convective cloud target approach is used to monitor the stability of NOAA-21 OMPS reflectance above 330 nm, showing a variation of 0.5% over the observed period. Data from the NOAA-21 VIIRS M1 band are used to estimate OMPS NM data geolocation errors, revealing that along-track errors can reach up to 3 km, while cross-track errors are generally within ±1 km.

Replicability of paleotemperature records in the northern Okinawa Trough and its implications for paleoceanographic reconstructions

Geochemical proxies are frequently utilized in the reconstruction of past ocean temperatures. Due to resource constraints, these reconstructions typically rely on a single sediment core, raising questions about the local and regional representativeness of paleotemperature records. To address this, we analyzed four sediment cores located within a 10-km radius in the northern Okinawa Trough (OT), which share the same climatic forcing and thus should reflect similar climate variations. We compiled published data and generated new paleotemperature estimates based on three widely used geochemical proxies (foraminiferal Mg/Ca, U37K′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{U}}_{37}^{{{\ ext{K}}^{\\prime}}}$$\\end{document}, TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document}). Analysis of the mean absolute deviations for nearby records based on the same proxy revealed that U37K′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{U}}_{37}^{{{\ ext{K}}^{\\prime}}}$$\\end{document} has the highest reproducibility, followed by Mg/Ca and TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document}. However, inconsistencies in inter-proxy offsets among nearby sites suggest the presence of noise in the proxy records, likely stemming from instrumental errors and sediment heterogeneity. Furthermore, the Mg/Ca and U37K′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{U}}_{37}^{{{\ ext{K}}^{\\prime}}}$$\\end{document} paleotemperature records agree within uncertainty when accounting for inter-site variability and calibration uncertainties, challenging previous interpretations of temperature signals from different seasons. All proxies indicate similar glacial-interglacial trends, albeit with varying magnitudes of temperature change. Both Mg/Ca and U37K′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{U}}_{37}^{{{\ ext{K}}^{\\prime}}}$$\\end{document} records suggest a glacial cooling of ~ 3 °C, whereas TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document} sea surface temperature (SST) data indicate a stronger glacial cooling of approximately ~ 6–8 °C. Modern observations indicate a subsurface TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document} recording depth of 50–100 m, coinciding with the thermocline. However, the TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document} subsurface temperature (subT) record does not resemble the Mg/Ca records of thermocline-dwelling foraminifera species. Instead, there is a better agreement with benthic foraminiferal Mg/Ca records of Uvigerina spp. (~ 700 m) and the intermediate temperature record derived from radiolarian assemblages (~ 500 m), pointing to a TEX86\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{TEX}}_{86}$$\\end{document} recording depth that is deeper than the thermocline. In summary, our findings show that proxy noise can impact inter-proxy comparisons of paleotemperature records, but not the direction of glacial-interglacial shifts. Future research should prioritize constraining the recording depth of paleotemperature proxies and reducing calibration uncertainty for more precise and reliable quantitative paleotemperature reconstruction.

Enhancing calibration accuracy with laser interferometry for high-resolution measuring systems

This paper presents an analysis of the measurement capability of laser interferometry for calibrating high-resolution measuring systems, focusing on potential errors that need to be carefully controlled to ensure adequate metrological traceability. The primary scientific research focus of our National Dimensional Metrology Laboratory is the development of metrological applications for industry, with ongoing improvements in calibration procedures for measuring machines and tools. Through a review of possible error sources, an innovative approach to reducing the most significant factors is proposed. This is specifically applied to the following calibration cases: field calibration of coordinate measuring machines, and laboratory calibration of precision probes and line scales. Instrumental and environmental errors can be effectively mitigated by using periodically calibrated laser interferometers in well-controlled air conditions, ensuring an uncertainty of 0.2 µm/m. Most geometrical errors can be minimized by precise adjustments to the interferometry and positioning systems, achieving an uncertainty of 0.3 µm/m. However, errors caused by temperature differences in the material along the measuring path remain the most influential. These arise due to the high expansion coefficient of the material and some uncertainty in its properties. After several hours of temperature stabilization, using three temperature sensors along the displacement range for software compensation, temperature differences still contribute significantly to measurement uncertainty. For example, the error is 0.5 µm/min in the case of line scale calibration and 1.1 µm/m for coordinate measuring machine calibration.

IMPROVING THE ACCURACY OF INERTIAL DETERMINATION OF HORIZONTAL PROJECTIONS OF LINEAR VELOCITY AND COORDINATES OF A CRUISING MOVING OBJECT

The paper considers the problem of improving the accuracy of determining the horizontal projections of linear velocity and coordinates of a moving cruising object by an autonomous inertial navigation system built on the basis of domestic precision navigation accelerometers. Typically, these errors of such a system grow linearly and quadratically with the time of its autonomous operation. The main reason for this growth is the integration of instrumental additive errors of its horizontal accelerometers. It is proposed to in- tentionally form a harmonic character of the instrumental additive errors of horizontal accelerometers within an autonomous inertial navigation system. This leads to the fact that the errors in determining the horizontal projections of linear velocity do not increase in time during integration, and the errors in determining the coordinates increase only linearly in time during the second integration. This approach helps to improve the accuracy of the system and the possibility of increasing its autono- mous operation time while ensuring the required accuracy. It is proposed to form the harmonic nature of the additive errors of horizontal accelerometers by rotating these accelerometers around the vertical axis of the object. A mathematical model for determining the horizontal projections of the linear velocity and coordinates of a moving object in the case of such a rotation of accelerometers, as well as a mathematical model of the errors of this determination, is obtained. The effectiveness of the proposed method of improving the accuracy of determining the horizontal projections of the linear velocity and coordinates of a moving object, as well as the adequacy of all the mathematical models obtained in this paper, has been confirmed by experimental studies.

Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments

Since dietary intake is challenging to directly measure in large-scale cohort studies, we often rely on self-reported instruments (e.g., food frequency questionnaires, 24-hour recalls, and diet records) developed in nutritional epidemiology. Those self-reported instruments are prone to measurement errors, which can lead to inaccuracies in the calculation of nutrient profiles. Currently, few computational methods exist to address this problem. In the present study, we introduce a deep-learning approach—Microbiome-based nutrient profile corrector (METRIC), which leverages gut microbial compositions to correct random errors in self-reported dietary assessments using 24-hour recalls or diet records. We demonstrate the excellent performance of METRIC in minimizing the simulated random errors, particularly for nutrients metabolized by gut bacteria in both synthetic and three real-world datasets. Additionally, we find that METRIC can still correct the random errors well even without including gut microbial compositions. Further research is warranted to examine the utility of METRIC to correct actual measurement errors in self-reported dietary assessment instruments.

Limb Temperature Observations in the Stratosphere and Mesosphere Derived from the OMPS Sensor

Molecular scattering (Rayleigh scattering) has been extensively used from the ground with lidars and from space to observe the limb, thereby deriving vertical temperature profiles between 30 and 80 km. In this study, we investigate how temperature can be measured using the new Ozone Mapping and Profiler Suite (OMPS) sensor, aboard the Suomi NPP and NOAA-21 satellites. The OMPS consists of three instruments whose main purpose is to study the composition of the stratosphere. One of these, the Limb Profiler (LP), measures the radiance of the limb of the middle atmosphere (stratosphere and mesosphere, 12 to 90 km altitude) at wavelengths from 290 to 1020 nm. This new data set has been used with a New Simplified Radiative Transfer Model (NSRTM) to derive temperature profiles with a vertical resolution of 1 km. To validate the method, the OMPS-derived temperature profiles were compared with data from four ground-based lidars and the ERA5 and MSIS models. The results show that OMPS and the lidars are in agreement within a range of about 5 K from 30 to 80 km. Comparisons with the models also show similar results, except for ERA5 beyond 50 km. We investigated various sources of bias, such as different attenuation sources, which can produce errors of up to 120 K in the UV range, instrumental errors around 0.8 K and noise problems of up to 150 K in the visible range for OMPS. This study also highlighted the interest in developing a new miniaturised instrument that could provide real-time observation of atmospheric vertical temperature profiles using a constellation of CubeSats with our NSRTM.

Reliability Analysis of Steam Turbine Instrumentation Using the Failure Mode and Effect Analysis (FMEA) Method at PT. PLN Nusantara Power UP Tenayan

PT. PLN Nusantara Power Unit Generation Tenayan is a company operating in the Steam Power Plant sector in Pekanbaru, Indonesia. One of the main components of a steam power plant (PLTU) is a steam turbine. A steam turbine is a machine that functions to convert kinetic energy into electrical current. Operational failures are often caused by less than optimal instrumentation in the steam turbine. This research uses the failure mode and effect analysis (FMEA) method with the aim of identifying the type of failure, the cause of the failure, the effect of the failure, and determining the RPN value. The analysis results from this research show that the turbine instrumentation components still meet performance standards because the risk priority number (RPN) value is less than 200. The conclusion from this research is that errors in steam turbine instrumentation are inaccurate sensor readings, switches cannot deactivate the equipment, and readings control room does not match local readings, the instrumentation component with the highest risk priority number (RPN) is the solenoid valve with a value of 140, and the instrumentation component with the lowest risk priority number (RPN) is the pressure indicator with a value of 30. The component given top priority in action The recommendation is for the solenoid valve component, namely to carry out maintenance every 6 months and add an overspeed protection system

A-245 Evaluation of an Automated MALDI-TOF Target and Antimicrobial Susceptibility Suspension Preparation Instrument

Abstract Background Several studies have shown that the implementation of automation in microbiology laboratories may allow for increased volume growth without the need for additional staffing. One of the more recently available pieces of microbiology automation, the COPAN Colibri, automates the manual steps of colony spotting and preparation of targets for use on MALDI-TOF instruments for bacterial identification. This same instrument can also prepare a diluted bacterial inoculum for immediate use on automated susceptibility testing platforms. We wanted to evaluate the performance of both of these functions in real-time with clinical cultures, to determine if implementation would be beneficial over current workflows. Methods The COPAN Colibri was operated following the manufacturer’s recommendations with the exception of the identification of gram-positive organisms. The Colibri is FDA cleared for MALDI-TOF target spotting, however not with the use of formic acid, nor is it FDA cleared for susceptibility suspension preparation. Preliminary data suggested that addition of formic acid was necessary for accurate identification. A subset of cultures were digitally read in real-time as part of clinical workflows, selected for Colibri MALDI-TOF target spotting and Vitek2 suspension preparation using the COPAN WebApp software. Targets were run on the MALDI Bioptyper Sirius (Bruker) and suspensions were run on Vitek2 (BioMerieux) using the pre-dilution mode using GN-99 and GN-801 cards for appropriate organisms. All results were compared to standard manual workflows. Results A total of 145 gram-negative and 60 gram-positive organisms were picked for MALDI-target spotting on Colibri. Compared to standard testing, 144 (99%) gram-negative and 57 (95%) gram-positive Colibri spotted isolates matched expected species-level identifications. 97 Gram negative bacilli were run on Vitek 2 generating 95.52% categorical agreement across all drugs but with 13 major errors (MEs) and 2 very major errors (VMEs), which exceeded the acceptable percentage for certain drugs. The total number of failed runs was 13 (13.34% of total GNB isolates run), and all required complete resetting of MALDI-spotting and suspension preparation. Conclusions The Colibri performed well for MALDI-TOF target spotting with the addition of formic acid for gram-positive organisms. It did not perform within the acceptable range for susceptibility suspension preparation as it exceeded the recommended cutoffs for MEs and VMEs for certain drugs. The proportion of failed runs due to instrument errors may offset any advantages in labor savings due to the need for repeat set up.

The fault in our nature: Error rates in a human observation study on surgical instrument errors in the OR

BackgroundErrors in sterile processing of surgical instruments result in wasted chargeable operating room minutes. Data delineating this problem have been generated primarily through human observation and reporting. Given the inherent error rate in human tasks, we hypothesized that the observed rate of surgical instrument errors per case per day would increase over a six-week longitudinal study as observers became more familiar with their environment and more comfortable identifying errors. MethodsA previously published dataset on surgical instrument errors was analyzed for the average errors per case per day over six weeks. Errors per case per day were compared to the percentage of inpatient cases for each respective date since the error rate in inpatient cases is twice that of outpatient cases. ResultsWhile the average errors per case per day increases from 0.28 to 0.62, indicating a potential increase over time, no statistically significant trend was found (p = 0.157). A positive but modest correlation was observed between inpatient percentage and error rates (Pearson correlation = 0.344), nearing statistical significance (p = 0.068). The inpatient case percentage remained stable over time, with no significant trend detected (p = 0.284). ConclusionsHuman observation is a critical tool for defining waste arising from sterile processing errors. While the gradual increase in errors per case per day increases, the variability cannot be attributed to the initial adaptation the observer's environment. Future studies should assess inter-rated reliability and explore alternative automated observation methods to have a more accurate measurement of the number of errors observed.

Water budgets in an arid and alpine permafrost basin: Observations from the High Mountain Asia

Ground freeze‒thaw processes have significant impacts on infiltration, runoff and evapotranspiration. However, there are still critical knowledge gaps in understanding of hydrological processes in permafrost regions, especially of the interactions among permafrost, ecology, and hydrology. In this study, an alpine permafrost basin on the northeastern Qinghai‒Tibet Plateau was selected to conduct hydrological and meteorological observations. We analyzed the annual variations in runoff, precipitation, evapotranspiration, and changes in water storage, as well as the mechanisms for runoff generation in the basin from May 2014 to December 2015. The annual flow curve in the basin exhibited peaks both in spring and autumn floods. The high ratio of evapotranspiration to annual precipitation (>1.0) in the investigated wetland is mainly due to the considerably underestimated ‘observed’ precipitation caused by the wind-induced instrumental error and the neglect of snow sublimation. The stream flow from early May to late October probably came from the lateral discharge of subsurface flow in alpine wetlands. This study can provide data support and validation for hydrological model simulation and prediction, as well as water resource assessment, in the upper Yellow River Basin, especially for the headwater area. The results also provide case support for permafrost hydrology modeling in ungauged or poorly gauged watersheds in the High Mountain Asia.

Understanding error rejection of differential impedance spectroscopy for the in situ characterization of highly conductive fluids

Abstract Differential impedance spectroscopy (DIS) can offer distinct advantages over conventional impedance spectroscopy (IS), particularly for the in situ characterization of highly conductive, corrosive fluids. To enhance the understanding of DIS and determine the conditions under which this method is preferable over conventional IS with fixed electrode positions, error calculations were performed. Two scenarios were analyzed, one accounting solely for random instrument errors and the other including random errors as well as systematic errors from a serial offset impedance. Our analyses reveal that while permittivity measurements of highly conductive media remain challenging regardless of whether a conventional or differential impedance approach is used, DIS enables highly accurate conductivity measurements across a wide frequency and conductivity range. Studying different cell dimensions with equal cell constants revealed that despite the increased influence of systematic errors at small scales, conductivity can still be accurately measured, underscoring the applicability of DIS for microfluidic applications. Other potential parasitic effects, such as those arising from the electromagnetic skin effect, stray capacitances, electrode size, and temperature gradients, are discussed, providing a comprehensive framework for sample characterization with DIS.

An efficient electrochemical biosensor based on double-conductive hydrogel as antifouling interface for ultrasensitive analysis of biomarkers in complex serum medium

Electrochemical biosensors are suitable for trace detection of biomarkers in serum due to their high sensitivity and fast response time. However, the extensive adsorption of non-specific biomolecules may affect detection results and reduce the operating life of sensors. Herein, an efficient electrochemical biosensor based on double-conductive antifouling hydrogel was developed for ultrasensitive detection of carcinoembryonic antigen (CEA) in serum. Specifically, the antifouling hydrogel was designed with MXene as the conductive framework, and its inherent surface hydrophilicity made it have good antifouling ability. Meanwhile, the introduction of conductive poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) further improved the conductivity and stability and of antifouling hydrogel. Furthermore, the prepared MXene nanosheets exhibited large surface area, which could load a large amount of [Ru(NH3)6]3+ as internal standards. Importantly, the encapsulation of [Ru(NH3)6]3+ in hydrogel can not only eliminate the environmental and instrument errors, but also realize the integration of antifouling and internal standards, thus simplifying the construction process and improving the detection accuracy of the biosensor. Based on this, the proposed signal “on-off” electrochemical antifouling biosensor realized trace detection of CEA in a wide linear range (1 pg/mL ∼ 1 μg/mL), with a detection limit as low as 0.41 pg/mL (3δ/k). This study broadens the application of hydrogels in electrochemical antifouling systems, providing a positive reference for sensitive and accurate determination of biomarkers in serum samples.

A Postlaunch Update on the Effects of Instrumental Measurement Errors on SWOT Estimates of Sea Surface Height, Velocity, and Vorticity

Abstract The Ka-band radar interferometer (KaRIn) on the Surface Water and Ocean Topography (SWOT) satellite that was launched in December 2022 is providing the first two-dimensional altimetric views of sea surface height (SSH). Measurements are made across two parallel swaths of 50-km width separated by a 20-km gap. In the data product that will be used for most oceanographic applications, SSH estimates with a footprint diameter of about 3 km are provided on a 2 km × 2 km grid. Early analyses of in-flight KaRIn data conclude that the instrumental noise for this footprint diameter has a standard deviation less than σ3km = 0.40 cm for conditions of 2-m significant wave height. This is a factor of 2.3 better than the prelaunch expectation based on the science requirement specification. The SSH fields measured by KaRIn allow the first satellite estimates of essentially instantaneous surface current velocity and vorticity computed geostrophically from SSH. The effects of instrumental noise on smoothed estimates of velocity and vorticity based on early postlaunch assessments are quantified here as functions of the half-power filter cutoff wavelength of the smoothing. Signal-to-noise ratios for smoothed estimates of velocity and vorticity are determined from simulated noisy KaRIn data derived from a high-resolution numerical model of the California Current System. The wavelength resolution capabilities for σ3km = 0.40 cm are found to be about 17 and 35 km for velocity and vorticity, respectively, which correspond to feature diameters of about 8.5 and 17.5 km, and are better than the prelaunch expectations by about 45% and 35%.

RETRACTION: Aggregation‐Induced Emission‐Active Donor‐Substituted Aroyl‐S,N‐Ketene Acetals via Nucleophilic Amine Base Attack

AbstractRetraction: L. Biesen, T.J.J. Müller, “Aggregation‐Induced Emission‐Active Donor‐Substituted Aroyl‐S,N‐Ketene Acetals via Nucleophilic Amine Base Attack”, ChemPhotoChem 2023, 7, e202300111, https://doi.org/10.1002/cptc.202300111.The above article, published online on 25 August 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors; the journal Editor‐in‐Chief, Deanne Nolan; Chemistry Europe; and Wiley‐VCH GmbH. The retraction has been agreed at the request of the authors, who informed the editor of significant errors in the structural assignment of compounds 3a, 3c and 3e, in addition to instrumental error affecting solid state and aggregate quantum yield measurements. As a result, the conclusions reported in the article are not considered reliable.